From 6fa4313efd80330b0f92c4860b6cf03e0980330b Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Mon, 3 Apr 2023 23:54:50 -0400 Subject: [PATCH 01/32] Updating documentation (notebooks) (#340) * update notebooks * build * update history from previous release * update history current release --------- Co-authored-by: Miguel Jimenez --- .DS_Store | Bin 8196 -> 8196 bytes HISTORY.rst | 14 + binder/Tutorial.ipynb | 13177 +++++++++++++++++++++++++++++++++++- docs/.DS_Store | Bin 10244 -> 10244 bytes docs/Kogur.ipynb | 790 ++- docs/Particles.ipynb | 1539 ++++- docs/Statistics.ipynb | 543 +- docs/Tutorial.ipynb | 836 ++- docs/_static/Kogur.gif | Bin 187500 -> 187768 bytes docs/_static/tutorial.gif | Bin 162166 -> 217508 bytes 10 files changed, 15994 insertions(+), 905 deletions(-) diff --git a/.DS_Store b/.DS_Store index cbad612a34e4427860d35231ae0b286773ea7d1c..8504c73a344ff3410966c75a532448f2c3f8f6f8 100644 GIT binary patch delta 103 zcmZp1XmOa}&nUhzU^hRb_+}mfeMZLPlWhbWIK`@~4RjQYEzBk#7nEh3KKZGjJmZYb ztU_E&%FGO@40#M?o;mr+NjdpR3=9kcKX+T^N3t$-pnrXjb-yq5q4$( D5zQZU delta 125 zcmZp1XmOa}&nUJrU^hRb*k&F9eMZKUlWhbWJSD2DP0Y-66ikdQYjqT=EsYF7Y_r;0 zP7ZNZLtD>;+{&uzn%cUV3}C>>2%#DHp)`z|wV7Fni)pj5$Q9;^4Jw=2CBCt2Rup~4 IG_gSu0CH{|(f|Me diff --git a/HISTORY.rst b/HISTORY.rst index 31bbd572..e204d067 100644 --- a/HISTORY.rst +++ b/HISTORY.rst @@ -3,6 +3,20 @@ ======= History ======= +v0.3.4 (2022-04-03) +------------------- +Fixed issues 322 (PR 325), 324 (PR 328), 332 (PR 324), and 312 (PR 337). Additional +grid files and removing (for the day) access to velocity LLC4320 data (PR 326) and update +environment (PR 335). All by `Miguel Jimenez Urias`_. Add daily mean ecco dataset to +catalog (PR 333) by `Wenrui Jiang`_. + + +v0.3.3 (2022-02-07) +------------------- +Update binder environment, add llc4320 forcing files to catalog, fixed issue243, replace +deprecated cartopy property on notebook, Rename to Temp and S by, set persist as option via +argument, all by `Miguel Jimenez Urias`_. Fix toml prettifier by `Mattia Almansi`_. + v0.3.2 (2022-12-29) ------------------- diff --git a/binder/Tutorial.ipynb b/binder/Tutorial.ipynb index 3f615279..79ce5249 100644 --- a/binder/Tutorial.ipynb +++ b/binder/Tutorial.ipynb @@ -17,13 +17,22 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:45:00.077459Z", + "iopub.status.busy": "2023-04-04T02:45:00.076889Z", + "iopub.status.idle": "2023-04-04T02:45:19.132313Z", + "shell.execute_reply": "2023-04-04T02:45:19.130076Z", + "shell.execute_reply.started": "2023-04-04T02:45:00.077399Z" + }, + "tags": [] + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.2.0\n" + "0.3.4\n" ] } ], @@ -64,33 +73,322 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:45:19.138143Z", + "iopub.status.busy": "2023-04-04T02:45:19.137037Z", + "iopub.status.idle": "2023-04-04T02:45:23.411269Z", + "shell.execute_reply": "2023-04-04T02:45:23.408707Z", + "shell.execute_reply.started": "2023-04-04T02:45:19.138086Z" + } + }, "outputs": [ { "data": { "text/html": [ - "\n", - "\n", - "\n", - "\n", + "
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.......... .......... .......... .......... .......... 1% 54.2M 15s\n", + " 6150K .......... .......... .......... .......... .......... 1% 64.7M 15s\n", + " 6200K .......... .......... .......... .......... .......... 1% 53.8M 15s\n", + " 6250K .......... .......... .......... .......... .......... 1% 52.5M 15s\n", + " 6300K .......... .......... .......... .......... .......... 1% 51.7M 15s\n", + " 6350K .......... .......... .......... .......... .......... 1% 47.3M 15s\n", + " 6400K .......... .......... .......... .......... .......... 1% 55.1M 15s\n", + " 6450K .......... .......... .......... .......... .......... 1% 60.1M 15s\n", + " 6500K .......... .......... .......... .......... .......... 1% 48.9M 15s\n", + " 6550K .......... .......... .......... .......... .......... 1% 44.3M 15s\n", + " 6600K .......... .......... .......... .......... .......... 1% 44.0M 15s\n", + " 6650K .......... .......... .......... .......... .......... 1% 67.2M 14s\n", + " 6700K .......... .......... .......... .......... .......... 1% 74.0M 14s\n", + " 6750K .......... .......... .......... .......... .......... 1% 53.1M 14s\n", + " 6800K .......... .......... .......... .......... .......... 1% 46.9M 14s\n", + " 6850K .......... .......... .......... .......... .......... 1% 56.3M 14s\n", + " 6900K .......... .......... .......... .......... .......... 1% 64.6M 14s\n", + " 6950K .......... .......... .......... .......... .......... 1% 71.2M 14s\n", + " 7000K .......... .......... .......... .......... .......... 1% 48.4M 14s\n", + " 7050K .......... .......... .......... .......... .......... 1% 55.6M 14s\n", + " 7100K .......... .......... .......... .......... .......... 1% 49.7M 14s\n", + " 7150K .......... .......... .......... .......... .......... 1% 63.4M 14s\n", + " 7200K .......... .......... .......... .......... .......... 1% 57.3M 14s\n", + " 7250K .......... .......... .......... .......... .......... 1% 61.4M 14s\n", + " 7300K .......... .......... .......... .......... .......... 1% 56.9M 14s\n", + " 7350K .......... .......... .......... .......... .......... 1% 47.8M 14s\n", + " 7400K .......... .......... .......... .......... .......... 1% 43.3M 14s\n", + " 7450K .......... .......... .......... .......... .......... 1% 68.2M 14s\n", + " 7500K .......... .......... .......... .......... .......... 1% 61.9M 14s\n", + " 7550K .......... .......... .......... .......... .......... 1% 49.2M 14s\n", + " 7600K .......... .......... .......... .......... .......... 1% 41.5M 14s\n", + " 7650K .......... .......... .......... .......... .......... 1% 55.1M 14s\n", + " 7700K .......... .......... .......... .......... .......... 1% 65.2M 14s\n", + " 7750K .......... .......... .......... .......... .......... 1% 62.6M 14s\n", + " 7800K .......... .......... .......... .......... .......... 1% 42.5M 14s\n", + " 7850K .......... .......... .......... .......... .......... 1% 45.9M 14s\n", + " 7900K .......... .......... .......... .......... .......... 1% 65.7M 14s\n", + " 7950K .......... .......... .......... .......... .......... 1% 79.1M 14s\n", + " 8000K .......... .......... .......... .......... .......... 1% 54.6M 14s\n", + " 8050K .......... .......... .......... .......... .......... 1% 47.1M 14s\n", + " 8100K .......... .......... .......... .......... .......... 1% 49.9M 14s\n", + " 8150K .......... .......... .......... .......... .......... 1% 60.5M 14s\n", + " 8200K .......... .......... .......... .......... .......... 1% 54.4M 14s\n", + " 8250K .......... .......... .......... .......... .......... 1% 61.2M 14s\n", + " 8300K .......... .......... .......... .......... .......... 1% 57.8M 14s\n", + " 8350K .......... .......... .......... .......... .......... 1% 57.3M 14s\n", + " 8400K .......... .......... .......... .......... .......... 1% 53.7M 14s\n", + " 8450K .......... .......... .......... .......... .......... 1% 71.3M 14s\n", + " 8500K .......... .......... .......... .......... .......... 1% 58.1M 14s\n", + " 8550K .......... .......... .......... .......... .......... 1% 58.0M 14s\n", + " 8600K .......... .......... .......... .......... .......... 1% 38.5M 14s\n", + " 8650K .......... .......... .......... .......... .......... 1% 57.0M 13s\n", + " 8700K .......... .......... .......... .......... .......... 1% 64.4M 13s\n", + " 8750K .......... .......... .......... .......... .......... 1% 75.1M 13s\n", + " 8800K .......... .......... .......... .......... .......... 1% 63.8M 13s\n", + " 8850K .......... .......... .......... .......... .......... 1% 68.1M 13s\n", + " 8900K .......... .......... .......... .......... .......... 1% 68.4M 13s\n", + " 8950K .......... .......... .......... .......... .......... 1% 61.1M 13s\n", + " 9000K .......... .......... .......... .......... .......... 1% 58.3M 13s\n", + " 9050K .......... .......... .......... .......... .......... 1% 52.6M 13s\n", + " 9100K .......... .......... .......... .......... .......... 1% 49.8M 13s\n", + " 9150K .......... .......... .......... .......... .......... 1% 48.5M 13s\n", + " 9200K .......... .......... .......... .......... .......... 1% 60.9M 13s\n", + " 9250K .......... .......... .......... .......... .......... 1% 76.1M 13s\n", + " 9300K .......... .......... .......... .......... .......... 1% 58.5M 13s\n", + " 9350K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", + " 9400K .......... .......... .......... .......... .......... 1% 40.9M 13s\n", + " 9450K .......... .......... .......... .......... .......... 1% 44.8M 13s\n", + " 9500K .......... .......... .......... .......... .......... 1% 59.4M 13s\n", + " 9550K .......... .......... .......... .......... .......... 1% 59.0M 13s\n", + " 9600K .......... .......... .......... .......... .......... 1% 40.5M 13s\n", + " 9650K .......... .......... .......... .......... .......... 1% 43.2M 13s\n", + " 9700K .......... .......... .......... .......... .......... 1% 62.3M 13s\n", + " 9750K .......... .......... .......... .......... .......... 1% 59.1M 13s\n", + " 9800K .......... .......... .......... .......... .......... 1% 40.0M 13s\n", + " 9850K .......... .......... .......... .......... .......... 1% 53.0M 13s\n", + " 9900K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", + " 9950K .......... .......... .......... .......... .......... 1% 64.0M 13s\n", + " 10000K .......... .......... .......... .......... .......... 1% 43.6M 13s\n", + " 10050K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", + " 10100K .......... .......... .......... .......... .......... 1% 56.0M 13s\n", + " 10150K .......... .......... .......... .......... .......... 1% 52.7M 13s\n", + " 10200K .......... .......... .......... .......... .......... 1% 54.6M 13s\n", + " 10250K .......... .......... .......... .......... .......... 1% 48.6M 13s\n", + " 10300K .......... .......... .......... .......... .......... 1% 54.7M 13s\n", + " 10350K .......... .......... .......... .......... .......... 1% 51.4M 13s\n", + " 10400K .......... .......... .......... .......... .......... 1% 56.7M 13s\n", + " 10450K .......... .......... .......... .......... .......... 1% 71.4M 13s\n", + " 10500K .......... .......... .......... .......... .......... 1% 52.8M 13s\n", + " 10550K .......... .......... .......... .......... .......... 1% 65.8M 13s\n", + " 10600K .......... .......... .......... .......... .......... 1% 56.4M 13s\n", + " 10650K .......... .......... .......... .......... .......... 1% 61.8M 13s\n", + " 10700K .......... .......... .......... .......... .......... 1% 68.7M 13s\n", + " 10750K .......... .......... .......... .......... .......... 1% 64.6M 13s\n", + " 10800K .......... .......... .......... .......... .......... 1% 46.0M 13s\n", + " 10850K .......... .......... .......... .......... .......... 1% 53.9M 13s\n", + " 10900K .......... .......... .......... .......... .......... 1% 46.8M 13s\n", + " 10950K .......... .......... .......... .......... .......... 1% 74.4M 13s\n", + " 11000K .......... .......... .......... .......... .......... 1% 38.9M 13s\n", + " 11050K .......... .......... .......... .......... .......... 1% 51.6M 13s\n", + " 11100K .......... .......... .......... .......... .......... 1% 45.4M 13s\n", + " 11150K .......... .......... .......... .......... .......... 1% 54.0M 13s\n", + " 11200K .......... .......... .......... .......... .......... 1% 49.8M 13s\n", + " 11250K .......... .......... .......... .......... .......... 1% 55.0M 13s\n", + " 11300K .......... .......... .......... .......... .......... 1% 37.2M 13s\n", + " 11350K .......... .......... .......... .......... .......... 1% 48.7M 13s\n", + " 11400K .......... .......... .......... .......... .......... 1% 46.1M 13s\n", + " 11450K .......... .......... .......... .......... .......... 1% 59.7M 13s\n", + " 11500K .......... .......... .......... .......... .......... 1% 62.2M 13s\n", + " 11550K .......... .......... .......... .......... .......... 1% 57.6M 13s\n", + " 11600K .......... .......... .......... .......... .......... 1% 49.0M 13s\n", + " 11650K .......... .......... .......... .......... .......... 1% 66.8M 13s\n", + " 11700K .......... .......... .......... .......... .......... 1% 55.0M 13s\n", + " 11750K .......... .......... .......... .......... .......... 1% 69.1M 13s\n", + " 11800K .......... .......... .......... .......... .......... 1% 51.1M 13s\n", + " 11850K .......... .......... .......... .......... .......... 2% 55.9M 13s\n", + " 11900K .......... .......... .......... .......... .......... 2% 70.0M 13s\n", + " 11950K .......... .......... .......... .......... .......... 2% 58.4M 13s\n", + " 12000K .......... .......... .......... .......... .......... 2% 52.8M 13s\n", + " 12050K .......... .......... .......... .......... .......... 2% 57.3M 13s\n", + " 12100K .......... .......... .......... .......... .......... 2% 59.0M 13s\n", + " 12150K .......... .......... .......... .......... .......... 2% 57.1M 13s\n", + " 12200K .......... .......... .......... .......... .......... 2% 44.1M 13s\n", + " 12250K .......... .......... .......... .......... .......... 2% 49.0M 13s\n", + " 12300K .......... .......... .......... .......... .......... 2% 54.8M 13s\n", + " 12350K .......... .......... .......... .......... .......... 2% 50.4M 13s\n", + " 12400K .......... .......... .......... .......... .......... 2% 51.8M 13s\n", + " 12450K .......... .......... .......... .......... .......... 2% 59.3M 13s\n", + " 12500K .......... .......... .......... .......... .......... 2% 46.3M 13s\n", + " 12550K .......... .......... .......... .......... .......... 2% 51.7M 13s\n", + " 12600K .......... .......... .......... .......... .......... 2% 47.3M 13s\n", + " 12650K .......... .......... .......... .......... .......... 2% 64.9M 12s\n", + " 12700K .......... .......... .......... .......... .......... 2% 4.02M 13s\n", + " 12750K .......... .......... .......... .......... .......... 2% 68.4M 13s\n", + " 12800K .......... .......... .......... .......... .......... 2% 64.4M 13s\n", + " 12850K .......... .......... .......... .......... .......... 2% 69.3M 13s\n", + " 12900K .......... .......... .......... .......... .......... 2% 66.0M 13s\n", + " 12950K .......... .......... .......... .......... .......... 2% 63.9M 13s\n", + " 13000K .......... .......... .......... .......... .......... 2% 45.8M 13s\n", + " 13050K .......... .......... .......... .......... .......... 2% 61.4M 13s\n", + " 13100K .......... .......... .......... .......... .......... 2% 47.5M 13s\n", + " 13150K .......... .......... .......... .......... .......... 2% 61.5M 13s\n", + " 13200K .......... .......... .......... .......... .......... 2% 56.4M 13s\n", + " 13250K .......... .......... .......... .......... .......... 2% 15.8M 13s\n", + " 13300K .......... .......... .......... .......... .......... 2% 65.2M 13s\n", + " 13350K .......... .......... .......... .......... .......... 2% 66.9M 13s\n", + " 13400K .......... .......... .......... .......... .......... 2% 50.1M 13s\n", + " 13450K .......... .......... .......... .......... .......... 2% 63.0M 13s\n", + " 13500K .......... .......... .......... .......... .......... 2% 61.4M 13s\n", + " 13550K .......... .......... .......... .......... .......... 2% 50.9M 13s\n", + " 13600K .......... .......... .......... .......... .......... 2% 16.2M 13s\n", + " 13650K .......... .......... .......... .......... .......... 2% 46.6M 13s\n", + " 13700K .......... .......... .......... .......... .......... 2% 56.1M 13s\n", + " 13750K .......... .......... .......... .......... .......... 2% 19.5M 13s\n", + " 13800K .......... .......... .......... .......... .......... 2% 41.9M 13s\n", + " 13850K .......... .......... .......... .......... .......... 2% 50.8M 13s\n", + " 13900K .......... .......... .......... .......... .......... 2% 55.4M 13s\n", + " 13950K .......... .......... .......... .......... .......... 2% 77.1M 13s\n", + " 14000K .......... .......... .......... .......... .......... 2% 62.9M 13s\n", + " 14050K .......... .......... .......... .......... .......... 2% 64.2M 13s\n", + " 14100K .......... .......... .......... .......... .......... 2% 58.2M 13s\n", + " 14150K .......... .......... .......... .......... .......... 2% 57.6M 13s\n", + " 14200K .......... .......... .......... .......... .......... 2% 52.6M 13s\n", + " 14250K .......... .......... .......... .......... .......... 2% 67.0M 13s\n", + " 14300K .......... .......... .......... .......... .......... 2% 57.5M 13s\n", + " 14350K .......... .......... .......... .......... .......... 2% 70.8M 13s\n", + " 14400K .......... .......... .......... .......... .......... 2% 54.5M 13s\n", + " 14450K .......... .......... .......... .......... .......... 2% 65.5M 13s\n", + " 14500K .......... .......... .......... .......... .......... 2% 57.7M 13s\n", + " 14550K .......... .......... .......... .......... .......... 2% 51.0M 13s\n", + " 14600K .......... .......... .......... .......... .......... 2% 37.0M 13s\n", + " 14650K .......... .......... .......... .......... .......... 2% 62.1M 13s\n", + " 14700K .......... .......... .......... .......... .......... 2% 63.0M 13s\n", + " 14750K .......... .......... .......... .......... .......... 2% 47.3M 13s\n", + " 14800K .......... .......... .......... .......... .......... 2% 44.0M 13s\n", + " 14850K .......... .......... .......... .......... .......... 2% 49.7M 13s\n", + " 14900K .......... .......... .......... .......... .......... 2% 53.8M 13s\n", + " 14950K .......... .......... .......... .......... .......... 2% 48.6M 13s\n", + " 15000K .......... .......... .......... .......... .......... 2% 35.1M 13s\n", + " 15050K .......... .......... .......... .......... .......... 2% 48.4M 13s\n", + " 15100K .......... .......... .......... .......... .......... 2% 46.5M 13s\n", + " 15150K .......... .......... .......... .......... .......... 2% 50.0M 13s\n", + " 15200K .......... .......... .......... .......... .......... 2% 39.0M 13s\n", + " 15250K .......... .......... .......... .......... .......... 2% 46.6M 13s\n", + " 15300K .......... .......... .......... .......... .......... 2% 45.6M 13s\n", + " 15350K .......... .......... .......... .......... .......... 2% 63.3M 13s\n", + " 15400K .......... .......... .......... .......... .......... 2% 44.3M 13s\n", + " 15450K .......... .......... .......... .......... .......... 2% 53.1M 13s\n", + " 15500K .......... .......... .......... .......... .......... 2% 54.5M 13s\n", + " 15550K .......... .......... .......... .......... .......... 2% 56.0M 13s\n", + " 15600K .......... .......... .......... .......... .......... 2% 46.2M 13s\n", + " 15650K .......... .......... .......... .......... .......... 2% 56.4M 13s\n", + " 15700K .......... .......... .......... .......... .......... 2% 53.3M 13s\n", + " 15750K .......... .......... .......... .......... .......... 2% 51.4M 13s\n", + " 15800K .......... .......... .......... .......... .......... 2% 41.1M 13s\n", + " 15850K .......... .......... .......... .......... .......... 2% 59.9M 13s\n", + " 15900K .......... .......... .......... .......... .......... 2% 51.1M 13s\n", + " 15950K .......... .......... .......... .......... .......... 2% 50.0M 13s\n", + " 16000K .......... .......... .......... .......... .......... 2% 50.2M 13s\n", + " 16050K .......... .......... .......... .......... .......... 2% 52.1M 13s\n", + " 16100K .......... .......... .......... .......... .......... 2% 52.4M 13s\n", + " 16150K .......... .......... .......... .......... .......... 2% 52.2M 13s\n", + " 16200K .......... .......... .......... .......... .......... 2% 48.7M 13s\n", + " 16250K .......... .......... .......... .......... .......... 2% 67.7M 13s\n", + " 16300K .......... .......... .......... .......... .......... 2% 51.4M 13s\n", + " 16350K .......... .......... .......... .......... .......... 2% 56.3M 13s\n", + " 16400K .......... .......... .......... .......... .......... 2% 48.4M 13s\n", + " 16450K .......... .......... .......... .......... .......... 2% 50.6M 13s\n", + " 16500K .......... .......... .......... .......... .......... 2% 53.1M 13s\n", + " 16550K .......... .......... .......... .......... .......... 2% 53.6M 13s\n", + " 16600K .......... .......... .......... .......... .......... 2% 52.8M 13s\n", + " 16650K .......... .......... .......... .......... .......... 2% 52.2M 13s\n", + " 16700K .......... .......... .......... .......... .......... 2% 54.0M 13s\n", + " 16750K .......... .......... .......... .......... .......... 2% 57.4M 13s\n", + " 16800K .......... .......... .......... .......... .......... 2% 61.0M 13s\n", + " 16850K .......... .......... .......... .......... .......... 2% 50.4M 13s\n", + " 16900K .......... .......... .......... .......... .......... 2% 35.1M 13s\n", + " 16950K .......... .......... .......... .......... .......... 2% 32.1M 13s\n", + " 17000K .......... .......... .......... .......... .......... 2% 38.3M 13s\n", + " 17050K .......... .......... .......... .......... .......... 2% 52.0M 13s\n", + " 17100K .......... .......... .......... .......... .......... 2% 54.7M 13s\n", + " 17150K .......... .......... .......... .......... .......... 2% 51.1M 13s\n", + " 17200K .......... .......... .......... .......... .......... 2% 51.7M 13s\n", + " 17250K .......... .......... .......... .......... .......... 2% 57.6M 13s\n", + " 17300K .......... .......... .......... .......... .......... 2% 64.1M 13s\n", + " 17350K .......... .......... .......... .......... .......... 2% 46.2M 13s\n", + " 17400K .......... .......... .......... .......... .......... 2% 38.6M 13s\n", + " 17450K .......... .......... .......... .......... .......... 2% 54.9M 13s\n", + " 17500K .......... .......... .......... .......... .......... 2% 63.8M 12s\n", + " 17550K .......... .......... .......... .......... .......... 2% 51.2M 12s\n", + " 17600K .......... .......... .......... .......... .......... 2% 36.3M 12s\n", + " 17650K .......... .......... .......... .......... .......... 2% 58.5M 12s\n", + " 17700K .......... .......... .......... .......... .......... 2% 53.1M 12s\n", + " 17750K .......... .......... .......... .......... .......... 2% 48.9M 12s\n", + " 17800K .......... .......... .......... .......... .......... 3% 45.4M 12s\n", + " 17850K .......... .......... .......... .......... .......... 3% 54.0M 12s\n", + " 17900K .......... .......... .......... .......... .......... 3% 39.8M 12s\n", + " 17950K .......... .......... .......... .......... .......... 3% 54.8M 12s\n", + " 18000K .......... .......... .......... .......... .......... 3% 49.8M 12s\n", + " 18050K .......... .......... .......... .......... .......... 3% 56.7M 12s\n", + " 18100K .......... .......... .......... .......... .......... 3% 67.3M 12s\n", + " 18150K .......... .......... .......... .......... .......... 3% 63.0M 12s\n", + " 18200K .......... .......... .......... .......... .......... 3% 42.6M 12s\n", + " 18250K .......... .......... .......... .......... .......... 3% 53.2M 12s\n", + " 18300K .......... .......... .......... .......... .......... 3% 51.4M 12s\n", + " 18350K .......... .......... .......... .......... .......... 3% 41.3M 12s\n", + " 18400K .......... .......... .......... .......... .......... 3% 43.6M 12s\n", + " 18450K .......... .......... .......... .......... .......... 3% 64.1M 12s\n", + " 18500K .......... .......... .......... .......... .......... 3% 62.7M 12s\n", + " 18550K .......... .......... .......... .......... .......... 3% 65.5M 12s\n", + " 18600K .......... .......... .......... .......... .......... 3% 55.3M 12s\n", + " 18650K .......... .......... .......... .......... .......... 3% 62.3M 12s\n", + " 18700K .......... .......... .......... .......... .......... 3% 69.3M 12s\n", + " 18750K .......... .......... .......... .......... .......... 3% 66.0M 12s\n", + " 18800K .......... .......... .......... .......... .......... 3% 55.3M 12s\n", + " 18850K .......... .......... .......... .......... .......... 3% 67.7M 12s\n", + " 18900K .......... .......... .......... .......... .......... 3% 62.2M 12s\n", + " 18950K .......... .......... .......... .......... .......... 3% 59.8M 12s\n", + " 19000K .......... .......... .......... .......... .......... 3% 42.6M 12s\n", + " 19050K .......... .......... .......... .......... .......... 3% 50.0M 12s\n", + " 19100K .......... .......... .......... .......... .......... 3% 47.3M 12s\n", + " 19150K .......... .......... .......... .......... .......... 3% 40.2M 12s\n", + " 19200K .......... .......... .......... .......... .......... 3% 44.2M 12s\n", + " 19250K .......... .......... .......... .......... .......... 3% 43.6M 12s\n", + " 19300K .......... .......... .......... .......... .......... 3% 39.9M 12s\n", + " 19350K .......... .......... .......... .......... .......... 3% 54.1M 12s\n", + " 19400K .......... .......... .......... .......... .......... 3% 39.4M 12s\n", + " 19450K .......... .......... .......... .......... .......... 3% 37.6M 12s\n", + " 19500K .......... .......... .......... .......... .......... 3% 57.3M 12s\n", + " 19550K .......... .......... .......... .......... .......... 3% 62.1M 12s\n", + " 19600K .......... .......... .......... .......... .......... 3% 60.1M 12s\n", + " 19650K .......... .......... .......... .......... .......... 3% 47.1M 12s\n", + " 19700K .......... .......... .......... .......... .......... 3% 41.6M 12s\n", + " 19750K .......... .......... .......... .......... .......... 3% 59.5M 12s\n", + " 19800K .......... .......... .......... .......... .......... 3% 46.3M 12s\n", + " 19850K .......... .......... .......... .......... .......... 3% 54.9M 12s\n", + " 19900K .......... .......... .......... .......... .......... 3% 42.9M 12s\n", + " 19950K .......... .......... .......... .......... .......... 3% 48.3M 12s\n", + " 20000K .......... .......... .......... .......... .......... 3% 44.3M 12s\n", + " 20050K .......... .......... .......... .......... .......... 3% 65.9M 12s\n", + " 20100K .......... .......... .......... .......... .......... 3% 49.3M 12s\n", + " 20150K .......... .......... .......... .......... .......... 3% 52.8M 12s\n", + " 20200K .......... .......... .......... .......... .......... 3% 48.6M 12s\n", + " 20250K .......... .......... .......... .......... .......... 3% 63.3M 12s\n", + " 20300K .......... .......... .......... .......... .......... 3% 64.1M 12s\n", + " 20350K .......... .......... .......... .......... .......... 3% 51.0M 12s\n", + " 20400K .......... .......... .......... .......... .......... 3% 43.7M 12s\n", + " 20450K .......... .......... .......... .......... .......... 3% 57.9M 12s\n", + " 20500K .......... .......... .......... .......... .......... 3% 72.4M 12s\n", + " 20550K .......... .......... .......... .......... .......... 3% 70.6M 12s\n", + " 20600K .......... .......... .......... .......... .......... 3% 50.0M 12s\n", + " 20650K .......... .......... .......... .......... .......... 3% 46.0M 12s\n", + " 20700K .......... .......... .......... .......... .......... 3% 59.2M 12s\n", + " 20750K .......... .......... .......... .......... .......... 3% 67.4M 12s\n", + " 20800K .......... .......... .......... .......... .......... 3% 51.3M 12s\n", + " 20850K .......... .......... .......... .......... .......... 3% 51.3M 12s\n", + " 20900K .......... .......... .......... .......... .......... 3% 49.9M 12s\n", + " 20950K .......... .......... .......... .......... .......... 3% 61.7M 12s\n", + " 21000K .......... .......... .......... .......... .......... 3% 56.6M 12s\n", + " 21050K .......... .......... .......... .......... .......... 3% 65.3M 12s\n", + " 21100K .......... .......... .......... .......... .......... 3% 61.0M 12s\n", + " 21150K .......... .......... .......... .......... .......... 3% 52.1M 12s\n", + " 21200K .......... .......... .......... .......... .......... 3% 50.1M 12s\n", + " 21250K .......... .......... .......... .......... .......... 3% 71.7M 12s\n", + " 21300K .......... .......... .......... .......... .......... 3% 69.4M 12s\n", + " 21350K .......... .......... .......... .......... .......... 3% 65.1M 12s\n", + " 21400K .......... .......... .......... .......... .......... 3% 43.7M 12s\n", + " 21450K .......... .......... .......... .......... .......... 3% 54.3M 12s\n", + " 21500K .......... .......... .......... .......... .......... 3% 66.5M 12s\n", + " 21550K .......... .......... .......... .......... .......... 3% 72.8M 12s\n", + " 21600K .......... .......... .......... .......... .......... 3% 63.5M 12s\n", + " 21650K .......... .......... .......... .......... .......... 3% 63.6M 12s\n", + " 21700K .......... .......... .......... .......... .......... 3% 47.1M 12s\n", + " 21750K .......... .......... .......... .......... .......... 3% 50.3M 12s\n", + " 21800K .......... .......... .......... .......... .......... 3% 57.4M 12s\n", + " 21850K .......... .......... .......... .......... .......... 3% 67.7M 12s\n", + " 21900K .......... .......... .......... .......... .......... 3% 60.5M 12s\n", + " 21950K .......... .......... .......... .......... .......... 3% 53.6M 12s\n", + " 22000K .......... .......... .......... .......... .......... 3% 43.9M 12s\n", + " 22050K .......... .......... .......... .......... .......... 3% 68.9M 12s\n", + " 22100K .......... .......... .......... .......... .......... 3% 67.8M 12s\n", + " 22150K .......... .......... .......... .......... .......... 3% 72.2M 12s\n", + " 22200K .......... .......... .......... .......... .......... 3% 44.0M 12s\n", + " 22250K .......... .......... .......... .......... .......... 3% 48.3M 12s\n", + " 22300K .......... .......... .......... .......... .......... 3% 57.6M 12s\n", + " 22350K .......... .......... .......... .......... .......... 3% 68.5M 12s\n", + " 22400K .......... .......... .......... .......... .......... 3% 61.1M 12s\n", + " 22450K .......... .......... .......... .......... .......... 3% 58.1M 12s\n", + " 22500K .......... .......... .......... .......... .......... 3% 49.4M 12s\n", + " 22550K .......... .......... .......... .......... .......... 3% 49.7M 12s\n", + " 22600K .......... .......... .......... .......... .......... 3% 57.4M 12s\n", + " 22650K .......... .......... .......... .......... .......... 3% 65.6M 12s\n", + " 22700K .......... .......... .......... .......... .......... 3% 57.1M 12s\n", + " 22750K .......... .......... .......... .......... .......... 3% 45.9M 12s\n", + " 22800K .......... .......... .......... .......... .......... 3% 49.7M 12s\n", + " 22850K .......... .......... .......... .......... .......... 3% 61.1M 12s\n", + " 22900K .......... .......... .......... .......... .......... 3% 63.6M 12s\n", + " 22950K .......... .......... .......... .......... .......... 3% 62.3M 12s\n", + " 23000K .......... .......... .......... .......... .......... 3% 37.1M 12s\n", + " 23050K .......... .......... .......... .......... .......... 3% 55.9M 12s\n", + " 23100K .......... .......... .......... .......... .......... 3% 70.7M 12s\n", + " 23150K .......... .......... .......... .......... .......... 3% 67.4M 12s\n", + " 23200K .......... .......... .......... .......... .......... 3% 65.0M 12s\n", + " 23250K .......... .......... .......... .......... .......... 3% 53.2M 12s\n", + " 23300K .......... .......... .......... .......... .......... 3% 45.6M 12s\n", + " 23350K .......... .......... .......... .......... .......... 3% 69.3M 12s\n", + " 23400K .......... .......... .......... .......... .......... 3% 55.1M 12s\n", + " 23450K .......... .......... .......... .......... .......... 3% 70.0M 12s\n", + " 23500K .......... .......... .......... .......... .......... 3% 49.9M 12s\n", + " 23550K .......... .......... .......... .......... .......... 3% 47.9M 12s\n", + " 23600K .......... .......... .......... .......... .......... 3% 54.7M 12s\n", + " 23650K .......... .......... .......... .......... .......... 3% 65.7M 12s\n", + " 23700K .......... .......... .......... .......... .......... 3% 70.3M 12s\n", + " 23750K .......... .......... .......... .......... .......... 4% 54.8M 12s\n", + " 23800K .......... .......... .......... .......... .......... 4% 34.8M 12s\n", + " 23850K .......... .......... .......... .......... .......... 4% 68.6M 12s\n", + " 23900K .......... .......... .......... .......... .......... 4% 63.0M 12s\n", + " 23950K .......... .......... .......... .......... .......... 4% 67.3M 12s\n", + " 24000K .......... .......... .......... .......... .......... 4% 45.9M 12s\n", + " 24050K .......... .......... .......... .......... .......... 4% 46.8M 12s\n", + " 24100K .......... .......... .......... .......... .......... 4% 60.2M 12s\n", + " 24150K .......... .......... .......... .......... .......... 4% 3.76M 12s\n", + " 24200K .......... .......... .......... .......... .......... 4% 54.9M 12s\n", + " 24250K .......... .......... .......... .......... .......... 4% 60.6M 12s\n", + " 24300K .......... .......... .......... .......... .......... 4% 63.3M 12s\n", + " 24350K .......... .......... .......... .......... .......... 4% 71.8M 12s\n", + " 24400K .......... .......... .......... .......... .......... 4% 58.2M 12s\n", + " 24450K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", + " 24500K .......... .......... .......... .......... .......... 4% 68.2M 12s\n", + " 24550K .......... .......... .......... .......... .......... 4% 4.06M 12s\n", + " 24600K .......... .......... .......... .......... .......... 4% 47.2M 12s\n", + " 24650K .......... .......... .......... .......... .......... 4% 65.1M 12s\n", + " 24700K .......... .......... .......... .......... .......... 4% 64.6M 12s\n", + " 24750K .......... .......... .......... .......... .......... 4% 60.8M 12s\n", + " 24800K .......... .......... .......... .......... .......... 4% 61.2M 12s\n", + " 24850K .......... .......... .......... .......... .......... 4% 56.6M 12s\n", + " 24900K .......... .......... .......... .......... .......... 4% 49.6M 12s\n", + " 24950K .......... .......... .......... .......... .......... 4% 62.5M 12s\n", + " 25000K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", + " 25050K .......... .......... .......... .......... .......... 4% 65.5M 12s\n", + " 25100K .......... .......... .......... .......... .......... 4% 58.5M 12s\n", + " 25150K .......... .......... .......... .......... .......... 4% 56.3M 12s\n", + " 25200K .......... .......... .......... .......... .......... 4% 49.7M 12s\n", + " 25250K .......... .......... .......... .......... .......... 4% 68.8M 12s\n", + " 25300K .......... .......... .......... .......... .......... 4% 64.9M 12s\n", + " 25350K .......... .......... .......... .......... .......... 4% 66.1M 12s\n", + " 25400K .......... .......... .......... .......... .......... 4% 42.8M 12s\n", + " 25450K .......... .......... .......... .......... .......... 4% 59.3M 12s\n", + " 25500K .......... .......... .......... .......... .......... 4% 53.8M 12s\n", + " 25550K .......... .......... .......... .......... .......... 4% 70.8M 12s\n", + " 25600K .......... .......... .......... .......... .......... 4% 62.0M 12s\n", + " 25650K .......... .......... .......... .......... .......... 4% 64.2M 12s\n", + " 25700K .......... .......... .......... .......... .......... 4% 49.6M 12s\n", + " 25750K .......... .......... .......... .......... .......... 4% 46.0M 12s\n", + " 25800K .......... .......... .......... .......... .......... 4% 53.6M 12s\n", + " 25850K .......... .......... .......... .......... .......... 4% 67.7M 12s\n", + " 25900K .......... .......... .......... .......... .......... 4% 70.1M 12s\n", + " 25950K .......... .......... .......... .......... .......... 4% 48.2M 12s\n", + " 26000K .......... .......... .......... .......... .......... 4% 47.7M 12s\n", + " 26050K .......... .......... .......... .......... .......... 4% 66.2M 12s\n", + " 26100K .......... .......... .......... .......... .......... 4% 60.9M 12s\n", + " 26150K .......... .......... .......... .......... .......... 4% 67.1M 12s\n", + " 26200K .......... .......... .......... .......... .......... 4% 39.4M 12s\n", + " 26250K .......... .......... .......... .......... .......... 4% 48.9M 12s\n", + " 26300K .......... .......... .......... .......... .......... 4% 63.7M 12s\n", + " 26350K .......... .......... .......... .......... .......... 4% 62.8M 12s\n", + " 26400K .......... .......... .......... .......... .......... 4% 50.0M 12s\n", + " 26450K .......... .......... .......... .......... .......... 4% 56.1M 12s\n", + " 26500K .......... .......... .......... .......... .......... 4% 50.8M 12s\n", + " 26550K .......... .......... .......... .......... .......... 4% 62.1M 12s\n", + " 26600K .......... .......... .......... .......... .......... 4% 53.8M 12s\n", + " 26650K .......... .......... .......... .......... .......... 4% 51.5M 12s\n", + " 26700K .......... .......... .......... .......... .......... 4% 53.0M 12s\n", + " 26750K .......... .......... .......... .......... .......... 4% 55.4M 12s\n", + " 26800K .......... .......... .......... .......... .......... 4% 64.1M 12s\n", + " 26850K .......... .......... .......... .......... .......... 4% 64.9M 12s\n", + " 26900K .......... .......... .......... .......... .......... 4% 69.4M 12s\n", + " 26950K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", + " 27000K .......... .......... .......... .......... .......... 4% 43.7M 12s\n", + " 27050K .......... .......... .......... .......... .......... 4% 72.0M 12s\n", + " 27100K .......... .......... .......... .......... .......... 4% 73.1M 12s\n", + " 27150K .......... .......... .......... .......... .......... 4% 60.4M 12s\n", + " 27200K .......... .......... .......... .......... .......... 4% 52.9M 12s\n", + " 27250K .......... .......... .......... .......... .......... 4% 50.2M 12s\n", + " 27300K .......... .......... .......... .......... .......... 4% 56.4M 12s\n", + " 27350K .......... .......... .......... .......... .......... 4% 68.1M 12s\n", + " 27400K .......... .......... .......... .......... .......... 4% 61.1M 12s\n", + " 27450K .......... .......... .......... .......... .......... 4% 59.5M 12s\n", + " 27500K .......... .......... .......... .......... .......... 4% 46.5M 12s\n", + " 27550K .......... .......... .......... .......... .......... 4% 52.2M 12s\n", + " 27600K .......... .......... .......... .......... .......... 4% 59.6M 12s\n", + " 27650K .......... .......... .......... .......... .......... 4% 65.5M 12s\n", + " 27700K .......... .......... .......... .......... .......... 4% 64.8M 12s\n", + " 27750K .......... .......... .......... .......... .......... 4% 46.6M 12s\n", + " 27800K .......... .......... .......... .......... .......... 4% 40.7M 12s\n", + " 27850K .......... .......... .......... .......... .......... 4% 63.9M 12s\n", + " 27900K .......... .......... .......... .......... .......... 4% 73.5M 12s\n", + " 27950K .......... .......... .......... .......... .......... 4% 69.8M 12s\n", + " 28000K .......... .......... .......... .......... .......... 4% 44.9M 12s\n", + " 28050K .......... .......... .......... .......... .......... 4% 50.6M 12s\n", + " 28100K .......... .......... .......... .......... .......... 4% 61.0M 12s\n", + " 28150K .......... .......... .......... .......... .......... 4% 70.0M 12s\n", + " 28200K .......... .......... .......... .......... .......... 4% 58.9M 12s\n", + " 28250K .......... .......... .......... .......... .......... 4% 49.9M 12s\n", + " 28300K .......... .......... .......... .......... .......... 4% 52.4M 12s\n", + " 28350K .......... .......... .......... .......... .......... 4% 52.0M 12s\n", + " 28400K .......... .......... .......... .......... .......... 4% 55.5M 12s\n", + " 28450K .......... .......... .......... .......... .......... 4% 59.4M 12s\n", + " 28500K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", + " 28550K .......... .......... .......... .......... .......... 4% 56.0M 12s\n", + " 28600K .......... .......... .......... .......... .......... 4% 43.3M 12s\n", + " 28650K .......... .......... .......... .......... .......... 4% 64.3M 12s\n", + " 28700K .......... .......... .......... .......... .......... 4% 65.8M 12s\n", + " 28750K .......... .......... .......... .......... .......... 4% 61.0M 12s\n", + " 28800K .......... .......... .......... .......... .......... 4% 48.1M 12s\n", + " 28850K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", + " 28900K .......... .......... .......... .......... .......... 4% 66.8M 12s\n", + " 28950K .......... .......... .......... .......... .......... 4% 74.3M 12s\n", + " 29000K .......... .......... .......... .......... .......... 4% 55.5M 12s\n", + " 29050K .......... .......... .......... .......... .......... 4% 56.1M 12s\n", + " 29100K .......... .......... .......... .......... .......... 4% 49.3M 12s\n", + " 29150K .......... .......... .......... .......... .......... 4% 62.8M 12s\n", + " 29200K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", + " 29250K .......... .......... .......... .......... .......... 4% 71.1M 12s\n", + " 29300K .......... .......... .......... .......... .......... 4% 58.0M 12s\n", + " 29350K .......... .......... .......... .......... .......... 4% 50.5M 12s\n", + " 29400K .......... .......... .......... .......... .......... 4% 41.0M 12s\n", + " 29450K .......... .......... .......... .......... .......... 4% 64.0M 12s\n", + " 29500K .......... .......... .......... .......... .......... 4% 59.2M 12s\n", + " 29550K .......... .......... .......... .......... .......... 4% 56.9M 12s\n", + " 29600K .......... .......... .......... .......... .......... 4% 47.7M 12s\n", + " 29650K .......... .......... .......... .......... .......... 4% 53.1M 12s\n", + " 29700K .......... .......... .......... .......... .......... 5% 65.3M 12s\n", + " 29750K .......... .......... .......... .......... .......... 5% 72.3M 12s\n", + " 29800K .......... .......... .......... .......... .......... 5% 50.6M 12s\n", + " 29850K .......... .......... .......... .......... .......... 5% 48.0M 12s\n", + " 29900K .......... .......... .......... .......... .......... 5% 50.2M 12s\n", + " 29950K .......... .......... .......... .......... .......... 5% 67.2M 12s\n", + " 30000K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", + " 30050K .......... .......... .......... .......... .......... 5% 70.7M 12s\n", + " 30100K .......... .......... .......... .......... .......... 5% 47.6M 12s\n", + " 30150K .......... .......... .......... .......... .......... 5% 49.0M 12s\n", + " 30200K .......... .......... .......... .......... .......... 5% 51.2M 12s\n", + " 30250K .......... .......... .......... .......... .......... 5% 65.0M 12s\n", + " 30300K .......... .......... .......... .......... .......... 5% 48.0M 12s\n", + " 30350K .......... .......... .......... .......... .......... 5% 53.9M 12s\n", + " 30400K .......... .......... .......... .......... .......... 5% 42.2M 12s\n", + " 30450K .......... .......... .......... .......... .......... 5% 63.1M 12s\n", + " 30500K .......... .......... .......... .......... .......... 5% 65.8M 12s\n", + " 30550K .......... .......... .......... .......... .......... 5% 58.3M 12s\n", + " 30600K .......... .......... .......... .......... .......... 5% 41.9M 12s\n", + " 30650K .......... .......... .......... .......... .......... 5% 44.9M 12s\n", + " 30700K .......... .......... .......... .......... .......... 5% 60.2M 12s\n", + " 30750K .......... .......... .......... .......... .......... 5% 69.3M 12s\n", + " 30800K .......... .......... .......... .......... .......... 5% 45.9M 12s\n", + " 30850K .......... .......... .......... .......... .......... 5% 58.1M 12s\n", + " 30900K .......... .......... .......... .......... .......... 5% 54.6M 12s\n", + " 30950K .......... .......... .......... .......... .......... 5% 69.1M 12s\n", + " 31000K .......... .......... .......... .......... .......... 5% 55.6M 12s\n", + " 31050K .......... .......... .......... .......... .......... 5% 59.1M 12s\n", + " 31100K .......... .......... .......... .......... .......... 5% 42.9M 12s\n", + " 31150K .......... .......... .......... .......... .......... 5% 56.7M 12s\n", + " 31200K .......... .......... .......... .......... .......... 5% 58.9M 12s\n", + " 31250K .......... .......... .......... .......... .......... 5% 66.2M 12s\n", + " 31300K .......... .......... .......... .......... .......... 5% 71.0M 12s\n", + " 31350K .......... .......... .......... .......... .......... 5% 56.4M 12s\n", + " 31400K .......... .......... .......... .......... .......... 5% 39.6M 12s\n", + " 31450K .......... .......... .......... .......... .......... 5% 54.4M 12s\n", + " 31500K .......... .......... .......... .......... .......... 5% 68.6M 12s\n", + " 31550K .......... .......... .......... .......... .......... 5% 72.5M 12s\n", + " 31600K .......... .......... .......... .......... .......... 5% 50.4M 12s\n", + " 31650K .......... .......... .......... .......... .......... 5% 49.3M 12s\n", + " 31700K .......... .......... .......... .......... .......... 5% 52.5M 12s\n", + " 31750K .......... .......... .......... .......... .......... 5% 61.8M 12s\n", + " 31800K .......... .......... .......... .......... .......... 5% 54.1M 12s\n", + " 31850K .......... .......... .......... .......... .......... 5% 48.6M 12s\n", + " 31900K .......... .......... .......... .......... .......... 5% 50.8M 12s\n", + " 31950K .......... .......... .......... .......... .......... 5% 59.5M 12s\n", + " 32000K .......... .......... .......... .......... .......... 5% 60.8M 12s\n", + " 32050K .......... .......... .......... .......... .......... 5% 68.4M 12s\n", + " 32100K .......... .......... .......... .......... .......... 5% 61.7M 12s\n", + " 32150K .......... .......... .......... .......... .......... 5% 48.7M 12s\n", + " 32200K .......... .......... .......... .......... .......... 5% 52.0M 12s\n", + " 32250K .......... .......... .......... .......... .......... 5% 69.0M 12s\n", + " 32300K .......... .......... .......... .......... .......... 5% 70.1M 12s\n", + " 32350K .......... .......... .......... .......... .......... 5% 71.0M 12s\n", + " 32400K .......... .......... .......... .......... .......... 5% 50.0M 12s\n", + " 32450K .......... .......... .......... .......... .......... 5% 45.7M 12s\n", + " 32500K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", + " 32550K .......... .......... .......... .......... .......... 5% 72.9M 12s\n", + " 32600K .......... .......... .......... .......... .......... 5% 46.5M 12s\n", + " 32650K .......... .......... .......... .......... .......... 5% 43.0M 12s\n", + " 32700K .......... .......... .......... .......... .......... 5% 53.0M 12s\n", + " 32750K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", + " 32800K .......... .......... .......... .......... .......... 5% 59.0M 12s\n", + " 32850K .......... .......... .......... .......... .......... 5% 59.5M 12s\n", + " 32900K .......... .......... .......... .......... .......... 5% 56.5M 12s\n", + " 32950K .......... .......... .......... .......... .......... 5% 55.9M 12s\n", + " 33000K .......... .......... .......... .......... .......... 5% 49.9M 12s\n", + " 33050K .......... .......... .......... .......... .......... 5% 70.7M 12s\n", + " 33100K .......... .......... .......... .......... .......... 5% 62.5M 11s\n", + " 33150K .......... .......... .......... .......... .......... 5% 51.1M 11s\n", + " 33200K .......... .......... .......... .......... .......... 5% 43.1M 11s\n", + " 33250K .......... .......... .......... .......... .......... 5% 70.9M 11s\n", + " 33300K .......... .......... .......... .......... .......... 5% 69.8M 11s\n", + " 33350K .......... .......... .......... .......... .......... 5% 71.0M 11s\n", + " 33400K .......... .......... .......... .......... .......... 5% 50.6M 11s\n", + " 33450K .......... .......... .......... .......... .......... 5% 52.5M 11s\n", + " 33500K .......... .......... .......... .......... .......... 5% 52.4M 11s\n", + " 33550K .......... .......... .......... .......... .......... 5% 69.0M 11s\n", + " 33600K .......... .......... .......... .......... .......... 5% 60.1M 11s\n", + " 33650K .......... .......... .......... .......... .......... 5% 70.2M 11s\n", + " 33700K .......... .......... .......... .......... .......... 5% 49.1M 11s\n", + " 33750K .......... .......... .......... .......... .......... 5% 52.4M 11s\n", + " 33800K .......... .......... .......... .......... .......... 5% 52.5M 11s\n", + " 33850K .......... .......... .......... .......... .......... 5% 69.1M 11s\n", + " 33900K .......... .......... .......... .......... .......... 5% 67.1M 11s\n", + " 33950K .......... .......... .......... .......... .......... 5% 65.9M 11s\n", + " 34000K .......... .......... .......... .......... .......... 5% 45.8M 11s\n", + " 34050K .......... .......... .......... .......... .......... 5% 49.7M 11s\n", + " 34100K .......... .......... .......... .......... .......... 5% 65.3M 11s\n", + " 34150K .......... .......... .......... .......... .......... 5% 67.7M 11s\n", + " 34200K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", + " 34250K .......... .......... .......... .......... .......... 5% 55.7M 11s\n", + " 34300K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", + " 34350K .......... .......... .......... .......... .......... 5% 75.0M 11s\n", + " 34400K .......... .......... .......... .......... .......... 5% 53.5M 11s\n", + " 34450K .......... .......... .......... .......... .......... 5% 53.2M 11s\n", + " 34500K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", + " 34550K .......... .......... .......... .......... .......... 5% 52.3M 11s\n", + " 34600K .......... .......... .......... .......... .......... 5% 54.5M 11s\n", + " 34650K .......... .......... .......... .......... .......... 5% 64.8M 11s\n", + " 34700K .......... .......... .......... .......... .......... 5% 57.6M 11s\n", + " 34750K .......... .......... .......... .......... .......... 5% 46.2M 11s\n", + " 34800K .......... .......... .......... .......... .......... 5% 44.7M 11s\n", + " 34850K .......... .......... .......... .......... .......... 5% 67.1M 11s\n", + " 34900K .......... .......... .......... .......... .......... 5% 71.5M 11s\n", + " 34950K .......... .......... .......... .......... .......... 5% 67.4M 11s\n", + " 35000K .......... .......... .......... .......... .......... 5% 41.8M 11s\n", + " 35050K .......... .......... .......... .......... .......... 5% 51.9M 11s\n", + " 35100K .......... .......... .......... .......... .......... 5% 70.4M 11s\n", + " 35150K .......... .......... .......... .......... .......... 5% 65.2M 11s\n", + " 35200K .......... .......... .......... .......... .......... 5% 52.7M 11s\n", + " 35250K .......... .......... .......... .......... .......... 5% 48.0M 11s\n", + " 35300K .......... .......... .......... .......... .......... 5% 52.1M 11s\n", + " 35350K .......... .......... .......... .......... .......... 5% 60.6M 11s\n", + " 35400K .......... .......... .......... .......... .......... 5% 55.8M 11s\n", + " 35450K .......... .......... .......... .......... .......... 5% 55.2M 11s\n", + " 35500K .......... .......... .......... .......... .......... 5% 49.6M 11s\n", + " 35550K .......... .......... .......... .......... .......... 5% 47.6M 11s\n", + " 35600K .......... .......... .......... .......... .......... 5% 58.0M 11s\n", + " 35650K .......... .......... .......... .......... .......... 6% 63.4M 11s\n", + " 35700K .......... .......... .......... .......... .......... 6% 63.0M 11s\n", + " 35750K .......... .......... .......... .......... .......... 6% 45.0M 11s\n", + " 35800K .......... .......... .......... .......... .......... 6% 45.7M 11s\n", + " 35850K .......... .......... .......... .......... .......... 6% 71.6M 11s\n", + " 35900K .......... .......... .......... .......... .......... 6% 70.1M 11s\n", + " 35950K .......... .......... .......... .......... .......... 6% 67.5M 11s\n", + " 36000K .......... .......... .......... .......... .......... 6% 49.0M 11s\n", + " 36050K .......... .......... .......... .......... .......... 6% 44.9M 11s\n", + " 36100K .......... .......... .......... .......... .......... 6% 63.3M 11s\n", + " 36150K .......... .......... .......... .......... .......... 6% 71.3M 11s\n", + " 36200K .......... .......... .......... .......... .......... 6% 57.5M 11s\n", + " 36250K .......... .......... .......... .......... .......... 6% 52.4M 11s\n", + " 36300K .......... .......... .......... .......... .......... 6% 38.1M 11s\n", + " 36350K .......... .......... .......... .......... .......... 6% 57.4M 11s\n", + " 36400K .......... .......... .......... .......... .......... 6% 55.1M 11s\n", + " 36450K .......... .......... .......... .......... .......... 6% 64.3M 11s\n", + " 36500K .......... .......... .......... .......... .......... 6% 44.2M 11s\n", + " 36550K .......... .......... .......... .......... .......... 6% 47.9M 11s\n", + " 36600K .......... .......... .......... .......... .......... 6% 45.2M 11s\n", + " 36650K .......... .......... .......... .......... .......... 6% 60.4M 11s\n", + " 36700K .......... .......... .......... .......... .......... 6% 52.1M 11s\n", + " 36750K .......... .......... .......... .......... .......... 6% 45.1M 11s\n", + " 36800K .......... .......... .......... .......... .......... 6% 49.7M 11s\n", + " 36850K .......... .......... .......... .......... .......... 6% 65.5M 11s\n", + " 36900K .......... .......... .......... .......... .......... 6% 62.9M 11s\n", + " 36950K .......... .......... .......... .......... .......... 6% 57.6M 11s\n", + " 37000K .......... .......... .......... .......... .......... 6% 33.7M 11s\n", + " 37050K .......... .......... .......... .......... .......... 6% 57.7M 11s\n", + " 37100K .......... .......... .......... .......... .......... 6% 61.4M 11s\n", + " 37150K .......... .......... .......... .......... .......... 6% 64.7M 11s\n", + " 37200K .......... .......... .......... .......... .......... 6% 46.0M 11s\n", + " 37250K .......... .......... .......... .......... .......... 6% 54.8M 11s\n", + " 37300K .......... .......... .......... .......... .......... 6% 69.1M 11s\n", + " 37350K .......... .......... .......... .......... .......... 6% 63.3M 11s\n", + " 37400K .......... .......... .......... .......... .......... 6% 52.8M 11s\n", + " 37450K .......... .......... .......... .......... .......... 6% 64.6M 11s\n", + " 37500K .......... .......... .......... .......... .......... 6% 63.8M 11s\n", + " 37550K .......... .......... .......... .......... .......... 6% 59.4M 11s\n", + " 37600K .......... .......... .......... .......... .......... 6% 59.4M 11s\n", + " 37650K .......... .......... .......... .......... .......... 6% 65.8M 11s\n", + " 37700K .......... .......... .......... .......... .......... 6% 56.6M 11s\n", + " 37750K .......... .......... .......... .......... .......... 6% 3.75M 11s\n", + " 37800K .......... .......... .......... .......... .......... 6% 32.9M 11s\n", + " 37850K .......... .......... .......... .......... .......... 6% 62.1M 11s\n", + " 37900K .......... .......... .......... .......... .......... 6% 58.9M 11s\n", + " 37950K .......... .......... .......... .......... .......... 6% 54.4M 11s\n", + " 38000K .......... .......... .......... .......... .......... 6% 48.5M 11s\n", + " 38050K .......... .......... .......... .......... .......... 6% 46.1M 11s\n", + " 38100K .......... .......... .......... .......... .......... 6% 53.1M 11s\n", + " 38150K .......... .......... .......... .......... .......... 6% 43.3M 11s\n", + " 38200K .......... .......... .......... .......... .......... 6% 44.3M 11s\n", + " 38250K .......... .......... .......... .......... .......... 6% 59.0M 11s\n", + " 38300K .......... .......... .......... .......... .......... 6% 49.7M 11s\n", + " 38350K .......... .......... .......... .......... .......... 6% 42.6M 11s\n", + " 38400K .......... .......... .......... .......... .......... 6% 48.4M 11s\n", + " 38450K .......... .......... .......... .......... .......... 6% 60.2M 11s\n", + " 38500K .......... .......... .......... .......... .......... 6% 59.0M 11s\n", + " 38550K .......... .......... .......... .......... .......... 6% 55.5M 11s\n", + " 38600K .......... .......... .......... .......... .......... 6% 39.9M 11s\n", + " 38650K .......... .......... .......... .......... .......... 6% 56.1M 11s\n", + " 38700K .......... .......... .......... .......... .......... 6% 56.9M 11s\n", + " 38750K .......... .......... .......... .......... .......... 6% 50.4M 11s\n", + " 38800K .......... .......... .......... .......... .......... 6% 48.9M 11s\n", + " 38850K .......... .......... .......... .......... .......... 6% 2.73M 12s\n", + " 38900K .......... .......... .......... .......... .......... 6% 62.4M 12s\n", + " 38950K .......... .......... .......... .......... .......... 6% 42.6M 12s\n", + " 39000K .......... .......... .......... .......... .......... 6% 41.4M 12s\n", + " 39050K .......... .......... .......... .......... .......... 6% 60.7M 12s\n", + " 39100K .......... .......... .......... .......... .......... 6% 64.6M 12s\n", + " 39150K .......... .......... .......... .......... .......... 6% 46.8M 12s\n", + " 39200K .......... .......... .......... .......... .......... 6% 32.1M 12s\n", + " 39250K .......... .......... .......... .......... .......... 6% 32.6M 12s\n", + " 39300K .......... .......... .......... .......... .......... 6% 40.5M 12s\n", + " 39350K .......... .......... .......... .......... .......... 6% 46.0M 12s\n", + " 39400K .......... .......... .......... .......... .......... 6% 51.6M 12s\n", + " 39450K .......... .......... .......... .......... .......... 6% 45.2M 12s\n", + " 39500K .......... .......... .......... .......... .......... 6% 52.5M 12s\n", + " 39550K .......... .......... .......... .......... .......... 6% 54.5M 12s\n", + " 39600K .......... .......... .......... .......... .......... 6% 56.3M 12s\n", + " 39650K .......... .......... .......... .......... .......... 6% 56.9M 12s\n", + " 39700K .......... .......... .......... .......... .......... 6% 50.5M 12s\n", + " 39750K .......... .......... .......... .......... .......... 6% 56.0M 12s\n", + " 39800K .......... .......... .......... .......... .......... 6% 38.8M 12s\n", + " 39850K .......... .......... .......... .......... .......... 6% 38.2M 12s\n", + " 39900K .......... .......... .......... .......... .......... 6% 3.58M 12s\n", + " 39950K .......... .......... .......... .......... .......... 6% 42.2M 12s\n", + " 40000K .......... .......... .......... .......... .......... 6% 44.5M 12s\n", + " 40050K .......... .......... .......... .......... .......... 6% 47.0M 12s\n", + " 40100K .......... .......... .......... .......... .......... 6% 43.1M 12s\n", + " 40150K .......... .......... .......... .......... .......... 6% 51.1M 12s\n", + " 40200K .......... .......... .......... .......... .......... 6% 41.0M 12s\n", + " 40250K .......... .......... .......... .......... .......... 6% 36.0M 12s\n", + " 40300K .......... .......... .......... .......... .......... 6% 35.9M 12s\n", + " 40350K .......... .......... .......... .......... .......... 6% 36.2M 12s\n", + " 40400K .......... .......... .......... .......... .......... 6% 46.5M 12s\n", + " 40450K .......... .......... .......... .......... .......... 6% 51.6M 12s\n", + " 40500K .......... .......... .......... .......... .......... 6% 39.8M 12s\n", + " 40550K .......... .......... .......... .......... .......... 6% 60.1M 12s\n", + " 40600K .......... .......... .......... .......... .......... 6% 44.5M 12s\n", + " 40650K .......... .......... .......... .......... .......... 6% 51.0M 12s\n", + " 40700K .......... .......... .......... .......... .......... 6% 14.8M 12s\n", + " 40750K .......... .......... .......... .......... .......... 6% 56.0M 12s\n", + " 40800K .......... .......... .......... .......... .......... 6% 48.6M 12s\n", + " 40850K .......... .......... .......... .......... .......... 6% 45.1M 12s\n", + " 40900K .......... .......... .......... .......... .......... 6% 61.5M 12s\n", + " 40950K .......... .......... .......... .......... .......... 6% 43.5M 12s\n", + " 41000K .......... .......... .......... .......... .......... 6% 49.4M 12s\n", + " 41050K .......... .......... .......... .......... .......... 6% 41.9M 12s\n", + " 41100K .......... .......... .......... .......... .......... 6% 46.7M 12s\n", + " 41150K .......... .......... .......... .......... .......... 6% 53.0M 12s\n", + " 41200K .......... .......... .......... .......... .......... 6% 46.4M 12s\n", + " 41250K .......... .......... .......... .......... .......... 6% 47.8M 12s\n", + " 41300K .......... .......... .......... .......... .......... 6% 57.4M 12s\n", + " 41350K .......... .......... .......... .......... .......... 6% 63.5M 12s\n", + " 41400K .......... .......... .......... .......... .......... 6% 39.1M 12s\n", + " 41450K .......... .......... .......... .......... .......... 6% 20.5M 12s\n", + " 41500K .......... .......... .......... .......... .......... 6% 59.5M 12s\n", + " 41550K .......... .......... .......... .......... .......... 6% 31.9M 12s\n", + " 41600K .......... .......... .......... .......... .......... 7% 36.9M 12s\n", + " 41650K .......... .......... .......... .......... .......... 7% 58.4M 12s\n", + " 41700K .......... .......... .......... .......... .......... 7% 64.5M 12s\n", + " 41750K .......... .......... .......... .......... .......... 7% 30.1M 12s\n", + " 41800K .......... .......... .......... .......... .......... 7% 38.7M 12s\n", + " 41850K .......... .......... .......... .......... .......... 7% 57.3M 12s\n", + " 41900K .......... .......... .......... .......... .......... 7% 4.19M 12s\n", + " 41950K .......... .......... .......... .......... .......... 7% 55.8M 12s\n", + " 42000K .......... .......... .......... .......... .......... 7% 51.8M 12s\n", + " 42050K .......... .......... .......... .......... .......... 7% 57.3M 12s\n", + " 42100K .......... .......... .......... .......... .......... 7% 38.6M 12s\n", + " 42150K .......... .......... .......... .......... .......... 7% 60.9M 12s\n", + " 42200K .......... .......... .......... .......... .......... 7% 53.5M 12s\n", + " 42250K .......... .......... .......... .......... .......... 7% 63.4M 12s\n", + " 42300K .......... .......... .......... .......... .......... 7% 45.0M 12s\n", + " 42350K .......... .......... .......... .......... .......... 7% 31.0M 12s\n", + " 42400K .......... .......... .......... .......... .......... 7% 57.7M 12s\n", + " 42450K .......... .......... .......... .......... .......... 7% 67.4M 12s\n", + " 42500K .......... .......... .......... .......... .......... 7% 33.8M 12s\n", + " 42550K .......... .......... .......... .......... .......... 7% 32.5M 12s\n", + " 42600K .......... .......... .......... .......... .......... 7% 38.2M 12s\n", + " 42650K .......... .......... .......... .......... .......... 7% 26.8M 12s\n", + " 42700K .......... .......... .......... .......... .......... 7% 18.5M 12s\n", + " 42750K .......... .......... .......... .......... .......... 7% 23.4M 12s\n", + " 42800K .......... .......... .......... .......... .......... 7% 19.5M 12s\n", + " 42850K .......... .......... .......... .......... .......... 7% 25.4M 12s\n", + " 42900K .......... .......... .......... .......... .......... 7% 28.5M 12s\n", + " 42950K .......... .......... .......... .......... .......... 7% 25.0M 12s\n", + " 43000K .......... .......... .......... .......... .......... 7% 22.0M 12s\n", + " 43050K .......... .......... .......... .......... .......... 7% 4.34M 12s\n", + " 43100K .......... .......... .......... .......... .......... 7% 64.3M 12s\n", + " 43150K .......... .......... .......... .......... .......... 7% 58.2M 12s\n", + " 43200K .......... .......... .......... .......... .......... 7% 60.1M 12s\n", + " 43250K .......... .......... .......... .......... .......... 7% 51.9M 12s\n", + " 43300K .......... .......... .......... .......... .......... 7% 64.0M 12s\n", + " 43350K .......... .......... .......... .......... .......... 7% 67.0M 12s\n", + " 43400K .......... .......... .......... .......... .......... 7% 34.0M 12s\n", + " 43450K .......... .......... .......... .......... .......... 7% 59.3M 12s\n", + " 43500K .......... .......... .......... .......... .......... 7% 58.7M 12s\n", + " 43550K .......... .......... .......... .......... .......... 7% 33.0M 12s\n", + " 43600K .......... .......... .......... .......... .......... 7% 32.7M 12s\n", + " 43650K .......... .......... .......... .......... .......... 7% 62.7M 12s\n", + " 43700K .......... .......... .......... .......... .......... 7% 63.0M 12s\n", + " 43750K .......... .......... .......... .......... .......... 7% 33.2M 12s\n", + " 43800K .......... .......... .......... .......... .......... 7% 32.6M 12s\n", + " 43850K .......... .......... .......... .......... .......... 7% 56.5M 12s\n", + " 43900K .......... .......... .......... .......... .......... 7% 49.1M 12s\n", + " 43950K .......... .......... .......... .......... .......... 7% 20.5M 12s\n", + " 44000K .......... .......... .......... .......... .......... 7% 21.0M 12s\n", + " 44050K .......... .......... .......... .......... .......... 7% 18.0M 12s\n", + " 44100K .......... .......... .......... .......... .......... 7% 25.3M 12s\n", + " 44150K .......... .......... .......... .......... .......... 7% 19.6M 12s\n", + " 44200K .......... .......... .......... .......... .......... 7% 26.3M 12s\n", + " 44250K .......... .......... .......... .......... .......... 7% 28.4M 12s\n", + " 44300K .......... .......... .......... .......... .......... 7% 24.9M 12s\n", + " 44350K .......... .......... .......... .......... .......... 7% 27.3M 12s\n", + " 44400K .......... .......... .......... .......... .......... 7% 25.8M 12s\n", + " 44450K .......... .......... .......... .......... .......... 7% 42.4M 12s\n", + " 44500K .......... .......... .......... .......... .......... 7% 50.4M 12s\n", + " 44550K .......... .......... .......... .......... .......... 7% 65.8M 12s\n", + " 44600K .......... .......... .......... .......... .......... 7% 64.4M 12s\n", + " 44650K .......... .......... .......... .......... .......... 7% 69.7M 12s\n", + " 44700K .......... .......... .......... .......... .......... 7% 75.7M 12s\n", + " 44750K .......... .......... .......... .......... .......... 7% 72.4M 12s\n", + " 44800K .......... .......... .......... .......... .......... 7% 68.3M 12s\n", + " 44850K .......... .......... .......... .......... .......... 7% 63.6M 12s\n", + " 44900K .......... .......... .......... .......... .......... 7% 69.9M 12s\n", + " 44950K .......... .......... .......... .......... .......... 7% 55.4M 12s\n", + " 45000K .......... .......... .......... .......... .......... 7% 55.7M 12s\n", + " 45050K .......... .......... .......... .......... .......... 7% 58.7M 12s\n", + " 45100K .......... .......... .......... .......... .......... 7% 63.3M 12s\n", + " 45150K .......... .......... .......... .......... .......... 7% 55.1M 12s\n", + " 45200K .......... .......... .......... .......... .......... 7% 46.7M 12s\n", + " 45250K .......... .......... .......... .......... .......... 7% 68.4M 12s\n", + " 45300K .......... .......... .......... .......... .......... 7% 55.7M 12s\n", + " 45350K .......... .......... .......... .......... .......... 7% 60.5M 12s\n", + " 45400K .......... .......... .......... .......... .......... 7% 48.7M 12s\n", + " 45450K .......... .......... .......... .......... .......... 7% 66.4M 12s\n", + " 45500K .......... .......... .......... .......... .......... 7% 63.8M 12s\n", + " 45550K .......... .......... .......... .......... .......... 7% 65.9M 12s\n", + " 45600K .......... .......... .......... .......... .......... 7% 55.8M 12s\n", + " 45650K .......... .......... .......... .......... .......... 7% 63.5M 12s\n", + " 45700K .......... .......... .......... .......... .......... 7% 53.2M 12s\n", + " 45750K .......... .......... .......... .......... .......... 7% 51.1M 12s\n", + " 45800K .......... .......... .......... .......... .......... 7% 29.2M 12s\n", + " 45850K .......... .......... .......... .......... .......... 7% 35.6M 12s\n", + " 45900K .......... .......... .......... .......... .......... 7% 16.4M 12s\n", + " 45950K .......... .......... .......... .......... .......... 7% 35.2M 12s\n", + " 46000K .......... .......... .......... .......... .......... 7% 33.1M 12s\n", + " 46050K .......... .......... .......... .......... .......... 7% 18.1M 12s\n", + " 46100K .......... .......... .......... .......... .......... 7% 35.2M 12s\n", + " 46150K .......... .......... .......... .......... .......... 7% 19.5M 12s\n", + " 46200K .......... .......... .......... .......... .......... 7% 25.2M 12s\n", + " 46250K .......... .......... .......... .......... .......... 7% 37.9M 12s\n", + " 46300K .......... .......... .......... .......... .......... 7% 38.3M 12s\n", + " 46350K .......... .......... .......... .......... .......... 7% 39.2M 12s\n", + " 46400K .......... .......... .......... .......... .......... 7% 62.5M 12s\n", + " 46450K .......... .......... .......... .......... .......... 7% 46.2M 12s\n", + " 46500K .......... .......... .......... .......... .......... 7% 36.5M 12s\n", + " 46550K .......... .......... .......... .......... .......... 7% 32.5M 12s\n", + " 46600K .......... .......... .......... .......... .......... 7% 39.4M 12s\n", + " 46650K .......... .......... .......... .......... .......... 7% 47.6M 12s\n", + " 46700K .......... .......... .......... .......... .......... 7% 30.4M 12s\n", + " 46750K .......... .......... .......... .......... .......... 7% 45.9M 12s\n", + " 46800K .......... .......... .......... .......... .......... 7% 42.1M 12s\n", + " 46850K .......... .......... .......... .......... .......... 7% 57.4M 12s\n", + " 46900K .......... .......... .......... .......... .......... 7% 40.8M 12s\n", + " 46950K .......... .......... .......... .......... .......... 7% 39.6M 12s\n", + " 47000K .......... .......... .......... .......... .......... 7% 42.7M 12s\n", + " 47050K .......... .......... .......... .......... .......... 7% 54.6M 12s\n", + " 47100K .......... .......... .......... .......... .......... 7% 18.5M 12s\n", + " 47150K .......... .......... .......... .......... .......... 7% 18.0M 12s\n", + " 47200K .......... .......... .......... .......... .......... 7% 18.6M 12s\n", + " 47250K .......... .......... .......... .......... .......... 7% 17.5M 12s\n", + " 47300K .......... .......... .......... .......... .......... 7% 21.9M 12s\n", + " 47350K .......... .......... .......... .......... .......... 7% 27.6M 12s\n", + " 47400K .......... .......... .......... .......... .......... 7% 16.0M 12s\n", + " 47450K .......... .......... .......... .......... .......... 7% 22.2M 12s\n", + " 47500K .......... .......... .......... .......... .......... 7% 38.5M 12s\n", + " 47550K .......... .......... .......... .......... .......... 8% 43.0M 12s\n", + " 47600K .......... .......... .......... .......... .......... 8% 38.5M 12s\n", + " 47650K .......... .......... .......... .......... .......... 8% 39.4M 12s\n", + " 47700K .......... .......... .......... .......... .......... 8% 47.0M 12s\n", + " 47750K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", + " 47800K .......... .......... .......... .......... .......... 8% 29.7M 12s\n", + " 47850K .......... .......... .......... .......... .......... 8% 36.2M 12s\n", + " 47900K .......... .......... .......... .......... .......... 8% 38.7M 12s\n", + " 47950K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", + " 48000K .......... .......... .......... .......... .......... 8% 27.3M 12s\n", + " 48050K .......... .......... .......... .......... .......... 8% 63.5M 12s\n", + " 48100K .......... .......... .......... .......... .......... 8% 27.5M 12s\n", + " 48150K .......... .......... .......... .......... .......... 8% 30.1M 12s\n", + " 48200K .......... .......... .......... .......... .......... 8% 42.9M 12s\n", + " 48250K .......... .......... .......... .......... .......... 8% 30.4M 12s\n", + " 48300K .......... .......... .......... .......... .......... 8% 22.6M 12s\n", + " 48350K .......... .......... .......... .......... .......... 8% 20.2M 12s\n", + " 48400K .......... .......... .......... .......... .......... 8% 20.4M 12s\n", + " 48450K .......... .......... .......... .......... .......... 8% 22.0M 12s\n", + " 48500K .......... .......... .......... .......... .......... 8% 26.1M 12s\n", + " 48550K .......... .......... .......... .......... .......... 8% 24.4M 12s\n", + " 48600K .......... .......... .......... .......... .......... 8% 20.8M 12s\n", + " 48650K .......... .......... .......... .......... .......... 8% 22.7M 12s\n", + " 48700K .......... .......... .......... .......... .......... 8% 30.8M 12s\n", + " 48750K .......... .......... .......... .......... .......... 8% 3.96M 12s\n", + " 48800K .......... .......... .......... .......... .......... 8% 55.5M 12s\n", + " 48850K .......... .......... .......... .......... .......... 8% 60.3M 12s\n", + " 48900K .......... .......... .......... .......... .......... 8% 62.9M 12s\n", + " 48950K .......... .......... .......... .......... .......... 8% 29.6M 12s\n", + " 49000K .......... .......... .......... .......... .......... 8% 49.5M 12s\n", + " 49050K .......... .......... .......... .......... .......... 8% 64.6M 12s\n", + " 49100K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", + " 49150K .......... .......... .......... .......... .......... 8% 36.7M 12s\n", + " 49200K .......... .......... .......... .......... .......... 8% 33.0M 12s\n", + " 49250K .......... .......... .......... .......... .......... 8% 62.7M 12s\n", + " 49300K .......... .......... .......... .......... .......... 8% 54.9M 12s\n", + " 49350K .......... .......... .......... .......... .......... 8% 16.7M 12s\n", + " 49400K .......... .......... .......... .......... .......... 8% 27.1M 12s\n", + " 49450K .......... .......... .......... .......... .......... 8% 20.0M 12s\n", + " 49500K .......... .......... .......... .......... .......... 8% 61.6M 12s\n", + " 49550K .......... .......... .......... .......... .......... 8% 64.1M 12s\n", + " 49600K .......... .......... .......... .......... .......... 8% 55.4M 12s\n", + " 49650K .......... .......... .......... .......... .......... 8% 32.6M 12s\n", + " 49700K .......... .......... .......... .......... .......... 8% 49.3M 12s\n", + " 49750K .......... .......... .......... .......... .......... 8% 66.1M 12s\n", + " 49800K .......... .......... .......... .......... .......... 8% 54.8M 12s\n", + " 49850K .......... .......... .......... .......... .......... 8% 48.6M 12s\n", + " 49900K .......... .......... .......... .......... .......... 8% 33.3M 12s\n", + " 49950K .......... .......... .......... .......... .......... 8% 61.1M 12s\n", + " 50000K .......... .......... .......... .......... .......... 8% 52.5M 12s\n", + " 50050K .......... .......... .......... .......... .......... 8% 67.7M 12s\n", + " 50100K .......... .......... .......... .......... .......... 8% 32.5M 12s\n", + " 50150K .......... .......... .......... .......... .......... 8% 46.4M 12s\n", + " 50200K .......... .......... .......... .......... .......... 8% 53.5M 12s\n", + " 50250K .......... .......... .......... .......... .......... 8% 64.5M 12s\n", + " 50300K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", + " 50350K .......... .......... .......... .......... .......... 8% 26.6M 12s\n", + " 50400K .......... .......... .......... .......... .......... 8% 60.9M 12s\n", + " 50450K .......... .......... .......... .......... .......... 8% 59.8M 12s\n", + " 50500K .......... .......... .......... .......... .......... 8% 51.0M 12s\n", + " 50550K .......... .......... .......... .......... .......... 8% 38.1M 12s\n", + " 50600K .......... .......... .......... .......... .......... 8% 34.1M 12s\n", + " 50650K .......... .......... .......... .......... .......... 8% 66.4M 12s\n", + " 50700K .......... .......... .......... .......... .......... 8% 61.7M 12s\n", + " 50750K .......... .......... .......... .......... .......... 8% 27.0M 12s\n", + " 50800K .......... .......... .......... .......... .......... 8% 34.8M 12s\n", + " 50850K .......... .......... .......... .......... .......... 8% 60.3M 12s\n", + " 50900K .......... .......... .......... .......... .......... 8% 4.20M 13s\n", + " 50950K .......... .......... .......... .......... .......... 8% 61.7M 13s\n", + " 51000K .......... .......... .......... .......... .......... 8% 44.3M 13s\n", + " 51050K .......... .......... .......... .......... .......... 8% 52.2M 13s\n", + " 51100K .......... .......... .......... .......... .......... 8% 45.5M 13s\n", + " 51150K .......... .......... .......... .......... .......... 8% 38.8M 13s\n", + " 51200K .......... .......... .......... .......... .......... 8% 50.0M 13s\n", + " 51250K .......... .......... .......... .......... .......... 8% 59.0M 13s\n", + " 51300K .......... .......... .......... .......... .......... 8% 55.1M 13s\n", + " 51350K .......... .......... .......... .......... .......... 8% 56.2M 13s\n", + " 51400K .......... .......... .......... .......... .......... 8% 40.2M 13s\n", + " 51450K .......... .......... .......... .......... .......... 8% 57.1M 13s\n", + " 51500K .......... .......... .......... .......... .......... 8% 61.7M 13s\n", + " 51550K .......... .......... .......... .......... .......... 8% 66.3M 13s\n", + " 51600K .......... .......... .......... .......... .......... 8% 55.1M 13s\n", + " 51650K .......... .......... .......... .......... .......... 8% 53.4M 12s\n", + " 51700K .......... .......... .......... .......... .......... 8% 54.0M 12s\n", + " 51750K .......... .......... .......... .......... .......... 8% 47.2M 12s\n", + " 51800K .......... .......... .......... .......... .......... 8% 53.3M 12s\n", + " 51850K .......... .......... .......... .......... .......... 8% 58.2M 12s\n", + " 51900K .......... .......... .......... .......... .......... 8% 46.4M 12s\n", + " 51950K .......... .......... .......... .......... .......... 8% 51.2M 12s\n", + " 52000K .......... .......... .......... .......... .......... 8% 44.9M 12s\n", + " 52050K .......... .......... .......... .......... .......... 8% 64.8M 12s\n", + " 52100K .......... .......... .......... .......... .......... 8% 55.7M 12s\n", + " 52150K .......... .......... .......... .......... .......... 8% 52.8M 12s\n", + " 52200K .......... .......... .......... .......... .......... 8% 35.3M 12s\n", + " 52250K .......... .......... .......... .......... .......... 8% 53.6M 12s\n", + " 52300K .......... .......... .......... .......... .......... 8% 56.0M 12s\n", + " 52350K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", + " 52400K .......... .......... .......... .......... .......... 8% 42.2M 12s\n", + " 52450K .......... .......... .......... .......... .......... 8% 51.7M 12s\n", + " 52500K .......... .......... .......... .......... .......... 8% 66.5M 12s\n", + " 52550K .......... .......... .......... .......... .......... 8% 64.6M 12s\n", + " 52600K .......... .......... .......... .......... .......... 8% 55.4M 12s\n", + " 52650K .......... .......... .......... .......... .......... 8% 54.3M 12s\n", + " 52700K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", + " 52750K .......... .......... .......... .......... .......... 8% 62.0M 12s\n", + " 52800K .......... .......... .......... .......... .......... 8% 51.7M 12s\n", + " 52850K .......... .......... .......... .......... .......... 8% 52.9M 12s\n", + " 52900K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", + " 52950K .......... .......... .......... .......... .......... 8% 48.8M 12s\n", + " 53000K .......... .......... .......... .......... .......... 8% 43.3M 12s\n", + " 53050K .......... .......... .......... .......... .......... 8% 56.1M 12s\n", + " 53100K .......... .......... .......... .......... .......... 8% 49.4M 12s\n", + " 53150K .......... .......... .......... .......... .......... 8% 4.23M 13s\n", + " 53200K .......... .......... .......... .......... .......... 8% 56.6M 13s\n", + " 53250K .......... .......... .......... .......... .......... 8% 63.6M 13s\n", + " 53300K .......... .......... .......... .......... .......... 8% 62.9M 12s\n", + " 53350K .......... .......... .......... .......... .......... 8% 62.7M 12s\n", + " 53400K .......... .......... .......... .......... .......... 8% 52.5M 12s\n", + " 53450K .......... .......... .......... .......... .......... 8% 43.6M 12s\n", + " 53500K .......... .......... .......... .......... .......... 9% 52.4M 12s\n", + " 53550K .......... .......... .......... .......... .......... 9% 63.7M 12s\n", + " 53600K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", + " 53650K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 53700K .......... .......... .......... .......... .......... 9% 53.7M 12s\n", + " 53750K .......... .......... .......... .......... .......... 9% 49.7M 12s\n", + " 53800K .......... .......... .......... .......... .......... 9% 49.1M 12s\n", + " 53850K .......... .......... .......... .......... .......... 9% 55.6M 12s\n", + " 53900K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 53950K .......... .......... .......... .......... .......... 9% 51.9M 12s\n", + " 54000K .......... .......... .......... .......... .......... 9% 39.5M 12s\n", + " 54050K .......... .......... .......... .......... .......... 9% 60.6M 12s\n", + " 54100K .......... .......... .......... .......... .......... 9% 65.0M 12s\n", + " 54150K .......... .......... .......... .......... .......... 9% 66.2M 12s\n", + " 54200K .......... .......... .......... .......... .......... 9% 38.0M 12s\n", + " 54250K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", + " 54300K .......... .......... .......... .......... .......... 9% 58.6M 12s\n", + " 54350K .......... .......... .......... .......... .......... 9% 66.0M 12s\n", + " 54400K .......... .......... .......... .......... .......... 9% 60.8M 12s\n", + " 54450K .......... .......... .......... .......... .......... 9% 52.1M 12s\n", + " 54500K .......... .......... .......... .......... .......... 9% 49.7M 12s\n", + " 54550K .......... .......... .......... .......... .......... 9% 55.0M 12s\n", + " 54600K .......... .......... .......... .......... .......... 9% 55.7M 12s\n", + " 54650K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", + " 54700K .......... .......... .......... .......... .......... 9% 51.1M 12s\n", + " 54750K .......... .......... .......... .......... .......... 9% 57.2M 12s\n", + " 54800K .......... .......... .......... .......... .......... 9% 42.8M 12s\n", + " 54850K .......... .......... .......... .......... .......... 9% 63.9M 12s\n", + " 54900K .......... .......... .......... .......... .......... 9% 58.8M 12s\n", + " 54950K .......... .......... .......... .......... .......... 9% 47.6M 12s\n", + " 55000K .......... .......... .......... .......... .......... 9% 47.1M 12s\n", + " 55050K .......... .......... .......... .......... .......... 9% 59.2M 12s\n", + " 55100K .......... .......... .......... .......... .......... 9% 65.9M 12s\n", + " 55150K .......... .......... .......... .......... .......... 9% 63.5M 12s\n", + " 55200K .......... .......... .......... .......... .......... 9% 46.1M 12s\n", + " 55250K .......... .......... .......... .......... .......... 9% 61.9M 12s\n", + " 55300K .......... .......... .......... .......... .......... 9% 57.1M 12s\n", + " 55350K .......... .......... .......... .......... .......... 9% 61.9M 12s\n", + " 55400K .......... .......... .......... .......... .......... 9% 56.1M 12s\n", + " 55450K .......... .......... .......... .......... .......... 9% 54.2M 12s\n", + " 55500K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", + " 55550K .......... .......... .......... .......... .......... 9% 44.4M 12s\n", + " 55600K .......... .......... .......... .......... .......... 9% 4.92M 12s\n", + " 55650K .......... .......... .......... .......... .......... 9% 63.8M 12s\n", + " 55700K .......... .......... .......... .......... .......... 9% 68.9M 12s\n", + " 55750K .......... .......... .......... .......... .......... 9% 66.5M 12s\n", + " 55800K .......... .......... .......... .......... .......... 9% 59.3M 12s\n", + " 55850K .......... .......... .......... .......... .......... 9% 61.2M 12s\n", + " 55900K .......... .......... .......... .......... .......... 9% 49.9M 12s\n", + " 55950K .......... .......... .......... .......... .......... 9% 49.1M 12s\n", + " 56000K .......... .......... .......... .......... .......... 9% 7.25M 12s\n", + " 56050K .......... .......... .......... .......... .......... 9% 58.1M 12s\n", + " 56100K .......... .......... .......... .......... .......... 9% 20.6M 12s\n", + " 56150K .......... .......... .......... .......... .......... 9% 64.0M 12s\n", + " 56200K .......... .......... .......... .......... .......... 9% 45.1M 12s\n", + " 56250K .......... .......... .......... .......... .......... 9% 43.6M 12s\n", + " 56300K .......... .......... .......... .......... .......... 9% 62.2M 12s\n", + " 56350K .......... .......... .......... .......... .......... 9% 59.6M 12s\n", + " 56400K .......... .......... .......... .......... .......... 9% 53.2M 12s\n", + " 56450K .......... .......... .......... .......... .......... 9% 44.5M 12s\n", + " 56500K .......... .......... .......... .......... .......... 9% 45.7M 12s\n", + " 56550K .......... .......... .......... .......... .......... 9% 60.9M 12s\n", + " 56600K .......... .......... .......... .......... .......... 9% 57.9M 12s\n", + " 56650K .......... .......... .......... .......... .......... 9% 63.3M 12s\n", + " 56700K .......... .......... .......... .......... .......... 9% 46.9M 12s\n", + " 56750K .......... .......... .......... .......... .......... 9% 44.4M 12s\n", + " 56800K .......... .......... .......... .......... .......... 9% 59.9M 12s\n", + " 56850K .......... .......... .......... .......... .......... 9% 65.9M 12s\n", + " 56900K .......... .......... .......... .......... .......... 9% 69.0M 12s\n", + " 56950K .......... .......... .......... .......... .......... 9% 56.8M 12s\n", + " 57000K .......... .......... .......... .......... .......... 9% 42.4M 12s\n", + " 57050K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", + " 57100K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 57150K .......... .......... .......... .......... .......... 9% 69.2M 12s\n", + " 57200K .......... .......... .......... .......... .......... 9% 58.3M 12s\n", + " 57250K .......... .......... .......... .......... .......... 9% 52.8M 12s\n", + " 57300K .......... .......... .......... .......... .......... 9% 47.3M 12s\n", + " 57350K .......... .......... .......... .......... .......... 9% 51.9M 12s\n", + " 57400K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", + " 57450K .......... .......... .......... .......... .......... 9% 66.2M 12s\n", + " 57500K .......... .......... .......... .......... .......... 9% 50.2M 12s\n", + " 57550K .......... .......... .......... .......... .......... 9% 48.2M 12s\n", + " 57600K .......... .......... .......... .......... .......... 9% 46.9M 12s\n", + " 57650K .......... .......... .......... .......... .......... 9% 60.2M 12s\n", + " 57700K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 57750K .......... .......... .......... .......... .......... 9% 52.1M 12s\n", + " 57800K .......... .......... .......... .......... .......... 9% 44.2M 12s\n", + " 57850K .......... .......... .......... .......... .......... 9% 51.3M 12s\n", + " 57900K .......... .......... .......... .......... .......... 9% 62.3M 12s\n", + " 57950K .......... .......... .......... .......... .......... 9% 68.1M 12s\n", + " 58000K .......... .......... .......... .......... .......... 9% 51.8M 12s\n", + " 58050K .......... .......... .......... .......... .......... 9% 52.4M 12s\n", + " 58100K .......... .......... .......... .......... .......... 9% 51.6M 12s\n", + " 58150K .......... .......... .......... .......... .......... 9% 63.4M 12s\n", + " 58200K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", + " 58250K .......... .......... .......... .......... .......... 9% 58.3M 12s\n", + " 58300K .......... .......... .......... .......... .......... 9% 44.8M 12s\n", + " 58350K .......... .......... .......... .......... .......... 9% 44.1M 12s\n", + " 58400K .......... .......... .......... .......... .......... 9% 57.5M 12s\n", + " 58450K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 58500K .......... .......... .......... .......... .......... 9% 53.9M 12s\n", + " 58550K .......... .......... .......... .......... .......... 9% 58.2M 12s\n", + " 58600K .......... .......... .......... .......... .......... 9% 44.0M 12s\n", + " 58650K .......... .......... .......... .......... .......... 9% 62.0M 12s\n", + " 58700K .......... .......... .......... .......... .......... 9% 68.1M 12s\n", + " 58750K .......... .......... .......... .......... .......... 9% 62.1M 12s\n", + " 58800K .......... .......... .......... .......... .......... 9% 55.3M 12s\n", + " 58850K .......... .......... .......... .......... .......... 9% 56.4M 12s\n", + " 58900K .......... .......... .......... .......... .......... 9% 60.0M 12s\n", + " 58950K .......... .......... .......... .......... .......... 9% 5.45M 12s\n", + " 59000K .......... .......... .......... .......... .......... 9% 58.8M 12s\n", + " 59050K .......... .......... .......... .......... .......... 9% 64.3M 12s\n", + " 59100K .......... .......... .......... .......... .......... 9% 66.7M 12s\n", + " 59150K .......... .......... .......... .......... .......... 9% 20.1M 12s\n", + " 59200K .......... .......... .......... .......... .......... 9% 45.3M 12s\n", + " 59250K .......... .......... .......... .......... .......... 9% 49.0M 12s\n", + " 59300K .......... .......... .......... .......... .......... 9% 60.4M 12s\n", + " 59350K .......... .......... .......... .......... .......... 9% 63.6M 12s\n", + " 59400K .......... .......... .......... .......... .......... 9% 41.4M 12s\n", + " 59450K .......... .......... .......... .......... .......... 10% 53.0M 12s\n", + " 59500K .......... .......... .......... .......... .......... 10% 54.8M 12s\n", + " 59550K .......... .......... .......... .......... .......... 10% 70.9M 12s\n", + " 59600K .......... .......... .......... .......... .......... 10% 55.5M 12s\n", + " 59650K .......... .......... .......... .......... .......... 10% 59.8M 12s\n", + " 59700K .......... .......... .......... .......... .......... 10% 50.6M 12s\n", + " 59750K .......... .......... .......... .......... .......... 10% 19.1M 12s\n", + " 59800K .......... .......... .......... .......... .......... 10% 48.5M 12s\n", + " 59850K .......... .......... .......... .......... .......... 10% 50.5M 12s\n", + " 59900K .......... .......... .......... .......... .......... 10% 59.1M 12s\n", + " 59950K .......... .......... .......... .......... .......... 10% 60.9M 12s\n", + " 60000K .......... .......... .......... .......... .......... 10% 46.2M 12s\n", + " 60050K .......... .......... .......... .......... .......... 10% 59.2M 12s\n", + " 60100K .......... .......... .......... .......... .......... 10% 44.4M 12s\n", + " 60150K .......... .......... .......... .......... .......... 10% 57.8M 12s\n", + " 60200K .......... .......... .......... .......... .......... 10% 49.6M 12s\n", + " 60250K .......... .......... .......... .......... .......... 10% 50.3M 12s\n", + " 60300K .......... .......... .......... .......... .......... 10% 53.8M 12s\n", + " 60350K .......... .......... .......... .......... .......... 10% 50.2M 12s\n", + " 60400K .......... .......... .......... .......... .......... 10% 58.0M 12s\n", + " 60450K .......... .......... .......... .......... .......... 10% 60.2M 12s\n", + " 60500K .......... .......... .......... .......... .......... 10% 54.5M 12s\n", + " 60550K .......... .......... .......... .......... .......... 10% 61.9M 12s\n", + " 60600K .......... .......... .......... .......... .......... 10% 45.7M 12s\n", + " 60650K .......... .......... .......... .......... .......... 10% 67.4M 12s\n", + " 60700K .......... .......... .......... .......... .......... 10% 58.3M 12s\n", + " 60750K .......... .......... .......... .......... .......... 10% 45.4M 12s\n", + " 60800K .......... .......... .......... .......... .......... 10% 40.4M 12s\n", + " 60850K .......... .......... .......... .......... .......... 10% 56.8M 12s\n", + " 60900K .......... .......... .......... .......... .......... 10% 67.9M 12s\n", + " 60950K .......... .......... .......... .......... .......... 10% 57.7M 12s\n", + " 61000K .......... .......... .......... .......... .......... 10% 39.6M 12s\n", + " 61050K .......... .......... .......... .......... .......... 10% 60.6M 12s\n", + " 61100K .......... .......... .......... .......... .......... 10% 55.5M 12s\n", + " 61150K .......... .......... .......... .......... .......... 10% 60.7M 12s\n", + " 61200K .......... .......... .......... .......... .......... 10% 50.2M 12s\n", + " 61250K .......... .......... .......... .......... .......... 10% 49.8M 12s\n", + " 61300K .......... .......... .......... .......... .......... 10% 46.4M 12s\n", + " 61350K .......... .......... .......... .......... .......... 10% 63.1M 12s\n", + " 61400K .......... .......... .......... .......... .......... 10% 56.0M 12s\n", + " 61450K .......... .......... .......... .......... .......... 10% 53.6M 12s\n", + " 61500K .......... .......... .......... .......... .......... 10% 49.1M 12s\n", + " 61550K .......... .......... .......... .......... .......... 10% 62.0M 12s\n", + " 61600K .......... .......... .......... .......... .......... 10% 60.1M 12s\n", + " 61650K .......... .......... .......... .......... .......... 10% 65.7M 12s\n", + " 61700K .......... .......... .......... .......... .......... 10% 57.5M 12s\n", + " 61750K .......... .......... .......... .......... .......... 10% 48.8M 12s\n", + " 61800K .......... .......... .......... .......... .......... 10% 44.0M 12s\n", + " 61850K .......... .......... .......... .......... .......... 10% 61.6M 12s\n", + " 61900K .......... .......... .......... .......... .......... 10% 51.6M 12s\n", + " 61950K .......... .......... .......... .......... .......... 10% 52.5M 12s\n", + " 62000K .......... .......... .......... .......... .......... 10% 43.6M 12s\n", + " 62050K .......... .......... .......... .......... .......... 10% 54.7M 12s\n", + " 62100K .......... .......... .......... .......... .......... 10% 66.1M 12s\n", + " 62150K .......... .......... .......... .......... .......... 10% 61.5M 12s\n", + " 62200K .......... .......... .......... .......... .......... 10% 45.4M 12s\n", + " 62250K .......... .......... .......... .......... .......... 10% 48.9M 12s\n", + " 62300K .......... .......... .......... .......... .......... 10% 60.3M 12s\n", + " 62350K .......... .......... .......... .......... .......... 10% 60.3M 12s\n", + " 62400K .......... .......... .......... .......... .......... 10% 58.1M 12s\n", + " 62450K .......... .......... .......... .......... .......... 10% 52.4M 12s\n", + " 62500K .......... .......... .......... .......... .......... 10% 45.3M 12s\n", + " 62550K .......... .......... .......... .......... .......... 10% 58.1M 12s\n", + " 62600K .......... .......... .......... .......... .......... 10% 59.2M 12s\n", + " 62650K .......... .......... .......... .......... .......... 10% 70.4M 12s\n", + " 62700K .......... .......... .......... .......... .......... 10% 4.16M 12s\n", + " 62750K .......... .......... .......... .......... .......... 10% 62.7M 12s\n", + " 62800K .......... .......... .......... .......... .......... 10% 64.8M 12s\n", + " 62850K .......... .......... .......... .......... .......... 10% 62.2M 12s\n", + " 62900K .......... .......... .......... .......... .......... 10% 63.8M 12s\n", + " 62950K .......... .......... .......... .......... .......... 10% 56.5M 12s\n", + " 63000K .......... .......... .......... .......... .......... 10% 35.5M 12s\n", + " 63050K .......... .......... .......... .......... .......... 10% 63.3M 12s\n", + " 63100K .......... .......... .......... .......... .......... 10% 64.4M 12s\n", + " 63150K .......... .......... .......... .......... .......... 10% 66.4M 12s\n", + " 63200K .......... .......... .......... .......... .......... 10% 57.7M 12s\n", + " 63250K .......... .......... .......... .......... .......... 10% 44.6M 12s\n", + " 63300K .......... .......... .......... .......... .......... 10% 38.9M 12s\n", + " 63350K .......... .......... .......... .......... .......... 10% 69.0M 12s\n", + " 63400K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", + " 63450K .......... .......... .......... .......... .......... 10% 55.7M 12s\n", + " 63500K .......... .......... .......... .......... .......... 10% 40.6M 12s\n", + " 63550K .......... .......... .......... .......... .......... 10% 45.6M 12s\n", + " 63600K .......... .......... .......... .......... .......... 10% 56.1M 12s\n", + " 63650K .......... .......... .......... .......... .......... 10% 64.6M 12s\n", + " 63700K .......... .......... .......... .......... .......... 10% 53.0M 12s\n", + " 63750K .......... .......... .......... .......... .......... 10% 50.4M 12s\n", + " 63800K .......... .......... .......... .......... .......... 10% 47.2M 12s\n", + " 63850K .......... .......... .......... .......... .......... 10% 64.5M 12s\n", + " 63900K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", + " 63950K .......... .......... .......... .......... .......... 10% 42.7M 12s\n", + " 64000K .......... .......... .......... .......... .......... 10% 47.7M 12s\n", + " 64050K .......... .......... .......... .......... .......... 10% 64.1M 12s\n", + " 64100K .......... .......... .......... .......... .......... 10% 64.0M 12s\n", + " 64150K .......... .......... .......... .......... .......... 10% 47.2M 12s\n", + " 64200K .......... .......... .......... .......... .......... 10% 35.0M 12s\n", + " 64250K .......... .......... .......... .......... .......... 10% 53.1M 12s\n", + " 64300K .......... .......... .......... .......... .......... 10% 68.3M 12s\n", + " 64350K .......... .......... .......... .......... .......... 10% 47.9M 12s\n", + " 64400K .......... .......... .......... .......... .......... 10% 40.0M 12s\n", + " 64450K .......... .......... .......... .......... .......... 10% 52.3M 12s\n", + " 64500K .......... .......... .......... .......... .......... 10% 65.8M 12s\n", + " 64550K .......... .......... .......... .......... .......... 10% 50.4M 12s\n", + " 64600K .......... .......... .......... .......... .......... 10% 40.8M 12s\n", + " 64650K .......... .......... .......... .......... .......... 10% 47.1M 12s\n", + " 64700K .......... .......... .......... .......... .......... 10% 58.5M 12s\n", + " 64750K .......... .......... .......... .......... .......... 10% 60.9M 12s\n", + " 64800K .......... .......... .......... .......... .......... 10% 43.7M 12s\n", + " 64850K .......... .......... .......... .......... .......... 10% 51.9M 12s\n", + " 64900K .......... .......... .......... .......... .......... 10% 54.0M 12s\n", + " 64950K .......... .......... .......... .......... .......... 10% 55.8M 12s\n", + " 65000K .......... .......... .......... .......... .......... 10% 49.2M 12s\n", + " 65050K .......... .......... .......... .......... .......... 10% 47.9M 12s\n", + " 65100K .......... .......... .......... .......... .......... 10% 49.8M 12s\n", + " 65150K .......... .......... .......... .......... .......... 10% 54.3M 12s\n", + " 65200K .......... .......... .......... .......... .......... 10% 57.3M 12s\n", + " 65250K .......... .......... .......... .......... .......... 10% 57.1M 12s\n", + " 65300K .......... .......... .......... .......... .......... 10% 49.1M 12s\n", + " 65350K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", + " 65400K .......... .......... .......... .......... .......... 11% 44.6M 12s\n", + " 65450K .......... .......... .......... .......... .......... 11% 61.3M 12s\n", + " 65500K .......... .......... .......... .......... .......... 11% 55.9M 12s\n", + " 65550K .......... .......... .......... .......... .......... 11% 52.6M 12s\n", + " 65600K .......... .......... .......... .......... .......... 11% 56.2M 12s\n", + " 65650K .......... .......... .......... .......... .......... 11% 54.4M 12s\n", + " 65700K .......... .......... .......... .......... .......... 11% 69.2M 12s\n", + " 65750K .......... .......... .......... .......... .......... 11% 52.7M 12s\n", + " 65800K .......... .......... .......... .......... .......... 11% 38.5M 12s\n", + " 65850K .......... .......... .......... .......... .......... 11% 57.9M 12s\n", + " 65900K .......... .......... .......... .......... .......... 11% 3.83M 12s\n", + " 65950K .......... .......... .......... .......... .......... 11% 59.8M 12s\n", + " 66000K .......... .......... .......... .......... .......... 11% 57.0M 12s\n", + " 66050K .......... .......... .......... .......... .......... 11% 57.9M 12s\n", + " 66100K .......... .......... .......... .......... .......... 11% 45.3M 12s\n", + " 66150K .......... .......... .......... .......... .......... 11% 54.6M 12s\n", + " 66200K .......... .......... .......... .......... .......... 11% 50.1M 12s\n", + " 66250K .......... .......... .......... .......... .......... 11% 68.7M 12s\n", + " 66300K .......... .......... .......... .......... .......... 11% 62.2M 12s\n", + " 66350K .......... .......... .......... .......... .......... 11% 46.2M 12s\n", + " 66400K .......... .......... .......... .......... .......... 11% 40.2M 12s\n", + " 66450K .......... .......... .......... .......... .......... 11% 66.3M 12s\n", + " 66500K .......... .......... .......... .......... .......... 11% 72.0M 12s\n", + " 66550K .......... .......... .......... .......... .......... 11% 68.4M 12s\n", + " 66600K .......... .......... .......... .......... .......... 11% 38.1M 12s\n", + " 66650K .......... .......... .......... .......... .......... 11% 51.3M 12s\n", + " 66700K .......... .......... .......... .......... .......... 11% 66.1M 12s\n", + " 66750K .......... .......... .......... .......... .......... 11% 66.7M 12s\n", + " 66800K .......... .......... .......... .......... .......... 11% 55.5M 12s\n", + " 66850K .......... .......... .......... .......... .......... 11% 48.3M 12s\n", + " 66900K .......... .......... .......... .......... .......... 11% 51.0M 12s\n", + " 66950K .......... .......... .......... .......... .......... 11% 66.3M 12s\n", + " 67000K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", + " 67050K .......... .......... .......... .......... .......... 11% 61.7M 12s\n", + " 67100K .......... .......... .......... .......... .......... 11% 43.0M 12s\n", + " 67150K .......... .......... .......... .......... .......... 11% 45.7M 12s\n", + " 67200K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", + " 67250K .......... .......... .......... .......... .......... 11% 65.7M 12s\n", + " 67300K .......... .......... .......... .......... .......... 11% 51.0M 12s\n", + " 67350K .......... .......... .......... .......... .......... 11% 39.7M 12s\n", + " 67400K .......... .......... .......... .......... .......... 11% 51.6M 12s\n", + " 67450K .......... .......... .......... .......... .......... 11% 65.1M 12s\n", + " 67500K .......... .......... .......... .......... .......... 11% 59.7M 12s\n", + " 67550K .......... .......... .......... .......... .......... 11% 48.3M 12s\n", + " 67600K .......... .......... .......... .......... .......... 11% 48.8M 12s\n", + " 67650K .......... .......... .......... .......... .......... 11% 4.99M 12s\n", + " 67700K .......... .......... .......... .......... .......... 11% 61.0M 12s\n", + " 67750K .......... .......... .......... .......... .......... 11% 60.1M 12s\n", + " 67800K .......... .......... .......... .......... .......... 11% 56.4M 12s\n", + " 67850K .......... .......... .......... .......... .......... 11% 60.6M 12s\n", + " 67900K .......... .......... .......... .......... .......... 11% 67.1M 12s\n", + " 67950K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", + " 68000K .......... .......... .......... .......... .......... 11% 50.5M 12s\n", + " 68050K .......... .......... .......... .......... .......... 11% 69.1M 12s\n", + " 68100K .......... .......... .......... .......... .......... 11% 67.8M 12s\n", + " 68150K .......... .......... .......... .......... .......... 11% 45.6M 12s\n", + " 68200K .......... .......... .......... .......... .......... 11% 44.9M 12s\n", + " 68250K .......... .......... .......... .......... .......... 11% 57.0M 12s\n", + " 68300K .......... .......... .......... .......... .......... 11% 68.0M 12s\n", + " 68350K .......... .......... .......... .......... .......... 11% 58.9M 12s\n", + " 68400K .......... .......... .......... .......... .......... 11% 42.9M 12s\n", + " 68450K .......... .......... .......... .......... .......... 11% 51.4M 12s\n", + " 68500K .......... .......... .......... .......... .......... 11% 55.5M 12s\n", + " 68550K .......... .......... .......... .......... .......... 11% 60.3M 12s\n", + " 68600K .......... .......... .......... .......... .......... 11% 46.3M 12s\n", + " 68650K .......... .......... .......... .......... .......... 11% 42.0M 12s\n", + " 68700K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", + " 68750K .......... .......... .......... .......... .......... 11% 64.0M 12s\n", + " 68800K .......... .......... .......... .......... .......... 11% 63.1M 12s\n", + " 68850K .......... .......... .......... .......... .......... 11% 46.0M 12s\n", + " 68900K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", + " 68950K .......... .......... .......... .......... .......... 11% 57.7M 12s\n", + " 69000K .......... .......... .......... .......... .......... 11% 54.0M 12s\n", + " 69050K .......... .......... .......... .......... .......... 11% 66.0M 12s\n", + " 69100K .......... .......... .......... .......... .......... 11% 41.5M 12s\n", + " 69150K .......... .......... .......... .......... .......... 11% 54.2M 12s\n", + " 69200K .......... .......... .......... .......... .......... 11% 53.4M 12s\n", + " 69250K .......... .......... .......... .......... .......... 11% 66.9M 12s\n", + " 69300K .......... .......... .......... .......... .......... 11% 71.0M 12s\n", + " 69350K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", + " 69400K .......... .......... .......... .......... .......... 11% 45.3M 12s\n", + " 69450K .......... .......... .......... .......... .......... 11% 60.2M 12s\n", + " 69500K .......... .......... .......... .......... .......... 11% 64.4M 12s\n", + " 69550K .......... .......... .......... .......... .......... 11% 47.7M 12s\n", + " 69600K .......... .......... .......... .......... .......... 11% 31.2M 12s\n", + " 69650K .......... .......... .......... .......... .......... 11% 37.6M 12s\n", + " 69700K .......... .......... .......... .......... .......... 11% 66.6M 12s\n", + " 69750K .......... .......... .......... .......... .......... 11% 60.0M 12s\n", + " 69800K .......... .......... .......... .......... .......... 11% 39.3M 12s\n", + " 69850K .......... .......... .......... .......... .......... 11% 60.0M 12s\n", + " 69900K .......... .......... .......... .......... .......... 11% 64.5M 12s\n", + " 69950K .......... .......... .......... .......... .......... 11% 66.6M 12s\n", + " 70000K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", + " 70050K .......... .......... .......... .......... .......... 11% 48.9M 12s\n", + " 70100K .......... .......... .......... .......... .......... 11% 60.3M 12s\n", + " 70150K .......... .......... .......... .......... .......... 11% 59.3M 12s\n", + " 70200K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", + " 70250K .......... .......... .......... .......... .......... 11% 42.1M 12s\n", + " 70300K .......... .......... .......... .......... .......... 11% 60.6M 12s\n", + " 70350K .......... .......... .......... .......... .......... 11% 47.8M 12s\n", + " 70400K .......... .......... .......... .......... .......... 11% 49.2M 12s\n", + " 70450K .......... .......... .......... .......... .......... 11% 49.9M 12s\n", + " 70500K .......... .......... .......... .......... .......... 11% 44.7M 12s\n", + " 70550K .......... .......... .......... .......... .......... 11% 50.9M 12s\n", + " 70600K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", + " 70650K .......... .......... .......... .......... .......... 11% 63.9M 12s\n", + " 70700K .......... .......... .......... .......... .......... 11% 45.4M 12s\n", + " 70750K .......... .......... .......... .......... .......... 11% 51.5M 12s\n", + " 70800K .......... .......... .......... .......... .......... 11% 48.5M 12s\n", + " 70850K .......... .......... .......... .......... .......... 11% 50.4M 12s\n", + " 70900K .......... .......... .......... .......... .......... 11% 44.1M 12s\n", + " 70950K .......... .......... .......... .......... .......... 11% 40.8M 12s\n", + " 71000K .......... .......... .......... .......... .......... 11% 38.5M 12s\n", + " 71050K .......... .......... .......... .......... .......... 11% 61.3M 12s\n", + " 71100K .......... .......... .......... .......... .......... 11% 45.0M 12s\n", + " 71150K .......... .......... .......... .......... .......... 11% 42.5M 12s\n", + " 71200K .......... .......... .......... .......... .......... 11% 35.8M 12s\n", + " 71250K .......... .......... .......... .......... .......... 11% 47.7M 12s\n", + " 71300K .......... .......... .......... .......... .......... 11% 47.4M 12s\n", + " 71350K .......... .......... .......... .......... .......... 12% 50.3M 12s\n", + " 71400K .......... .......... .......... .......... .......... 12% 45.9M 12s\n", + " 71450K .......... .......... .......... .......... .......... 12% 52.1M 12s\n", + " 71500K .......... .......... .......... .......... .......... 12% 47.2M 12s\n", + " 71550K .......... .......... .......... .......... .......... 12% 53.4M 12s\n", + " 71600K .......... .......... .......... .......... .......... 12% 54.0M 12s\n", + " 71650K .......... .......... .......... .......... .......... 12% 68.1M 12s\n", + " 71700K .......... .......... .......... .......... .......... 12% 67.4M 12s\n", + " 71750K .......... .......... .......... .......... .......... 12% 70.2M 12s\n", + " 71800K .......... .......... .......... .......... .......... 12% 31.1M 12s\n", + " 71850K .......... .......... .......... .......... .......... 12% 42.9M 12s\n", + " 71900K .......... .......... .......... .......... .......... 12% 57.5M 12s\n", + " 71950K .......... .......... .......... .......... .......... 12% 44.2M 12s\n", + " 72000K .......... .......... .......... .......... .......... 12% 40.0M 12s\n", + " 72050K .......... .......... .......... .......... .......... 12% 46.9M 12s\n", + " 72100K .......... .......... .......... .......... .......... 12% 56.8M 12s\n", + " 72150K .......... .......... .......... .......... .......... 12% 56.9M 12s\n", + " 72200K .......... .......... .......... .......... .......... 12% 42.4M 12s\n", + " 72250K .......... .......... .......... .......... .......... 12% 47.9M 12s\n", + " 72300K .......... .......... .......... .......... .......... 12% 57.1M 12s\n", + " 72350K .......... .......... .......... .......... .......... 12% 51.6M 12s\n", + " 72400K .......... .......... .......... .......... .......... 12% 42.0M 12s\n", + " 72450K .......... .......... .......... .......... .......... 12% 37.6M 12s\n", + " 72500K .......... .......... .......... .......... .......... 12% 47.3M 12s\n", + " 72550K .......... .......... .......... .......... .......... 12% 68.6M 12s\n", + " 72600K .......... .......... .......... .......... .......... 12% 47.4M 12s\n", + " 72650K .......... .......... .......... .......... .......... 12% 52.2M 12s\n", + " 72700K .......... .......... .......... .......... .......... 12% 57.4M 12s\n", + " 72750K .......... .......... .......... .......... .......... 12% 62.9M 12s\n", + " 72800K .......... .......... .......... .......... .......... 12% 49.3M 12s\n", + " 72850K .......... .......... .......... .......... .......... 12% 46.9M 12s\n", + " 72900K .......... .......... .......... .......... .......... 12% 42.9M 12s\n", + " 72950K .......... .......... .......... .......... .......... 12% 42.2M 12s\n", + " 73000K .......... .......... .......... .......... .......... 12% 44.2M 12s\n", + " 73050K .......... .......... .......... .......... .......... 12% 57.4M 12s\n", + " 73100K .......... .......... .......... .......... .......... 12% 38.1M 12s\n", + " 73150K .......... .......... .......... .......... .......... 12% 43.6M 12s\n", + " 73200K .......... .......... .......... .......... .......... 12% 50.5M 12s\n", + " 73250K .......... .......... .......... .......... .......... 12% 64.3M 12s\n", + " 73300K .......... .......... .......... .......... .......... 12% 53.9M 12s\n", + " 73350K .......... .......... .......... .......... .......... 12% 53.5M 12s\n", + " 73400K .......... .......... .......... .......... .......... 12% 44.6M 12s\n", + " 73450K .......... .......... .......... .......... .......... 12% 68.1M 12s\n", + " 73500K .......... .......... .......... .......... .......... 12% 64.8M 12s\n", + " 73550K .......... .......... .......... .......... .......... 12% 61.0M 12s\n", + " 73600K .......... .......... .......... .......... .......... 12% 46.3M 12s\n", + " 73650K .......... .......... .......... .......... .......... 12% 58.0M 12s\n", + " 73700K .......... .......... .......... .......... .......... 12% 69.4M 12s\n", + " 73750K .......... .......... .......... .......... .......... 12% 72.2M 12s\n", + " 73800K .......... .......... .......... .......... .......... 12% 38.0M 12s\n", + " 73850K .......... .......... .......... .......... .......... 12% 38.5M 12s\n", + " 73900K .......... .......... .......... .......... .......... 12% 43.2M 12s\n", + " 73950K .......... .......... .......... .......... .......... 12% 42.3M 12s\n", + " 74000K .......... .......... .......... .......... .......... 12% 45.2M 12s\n", + " 74050K .......... .......... .......... .......... .......... 12% 38.3M 12s\n", + " 74100K .......... .......... .......... .......... .......... 12% 58.1M 12s\n", + " 74150K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", + " 74200K .......... .......... .......... .......... .......... 12% 50.9M 12s\n", + " 74250K .......... .......... .......... .......... .......... 12% 35.6M 12s\n", + " 74300K .......... .......... .......... .......... .......... 12% 53.7M 12s\n", + " 74350K .......... .......... .......... .......... .......... 12% 43.4M 12s\n", + " 74400K .......... .......... .......... .......... .......... 12% 62.0M 12s\n", + " 74450K .......... .......... .......... .......... .......... 12% 45.2M 12s\n", + " 74500K .......... .......... .......... .......... .......... 12% 52.2M 12s\n", + " 74550K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", + " 74600K .......... .......... .......... .......... .......... 12% 55.3M 12s\n", + " 74650K .......... .......... .......... .......... .......... 12% 56.9M 12s\n", + " 74700K .......... .......... .......... .......... .......... 12% 35.0M 12s\n", + " 74750K .......... .......... .......... .......... .......... 12% 43.5M 12s\n", + " 74800K .......... .......... .......... .......... .......... 12% 47.8M 12s\n", + " 74850K .......... .......... .......... .......... .......... 12% 55.1M 12s\n", + " 74900K .......... .......... .......... .......... .......... 12% 38.2M 12s\n", + " 74950K .......... .......... .......... .......... .......... 12% 50.7M 12s\n", + " 75000K .......... .......... .......... .......... .......... 12% 37.3M 12s\n", + " 75050K .......... .......... .......... .......... .......... 12% 43.7M 12s\n", + " 75100K .......... .......... .......... .......... .......... 12% 38.3M 12s\n", + " 75150K .......... .......... .......... .......... .......... 12% 49.6M 12s\n", + " 75200K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", + " 75250K .......... .......... .......... .......... .......... 12% 45.7M 12s\n", + " 75300K .......... .......... .......... .......... .......... 12% 37.8M 12s\n", + " 75350K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", + " 75400K .......... .......... .......... .......... .......... 12% 56.0M 12s\n", + " 75450K .......... .......... .......... .......... .......... 12% 66.8M 12s\n", + " 75500K .......... .......... .......... .......... .......... 12% 61.6M 12s\n", + " 75550K .......... .......... .......... .......... .......... 12% 50.6M 12s\n", + " 75600K .......... .......... .......... .......... .......... 12% 53.2M 12s\n", + " 75650K .......... .......... .......... .......... .......... 12% 59.5M 12s\n", + " 75700K .......... .......... .......... .......... .......... 12% 49.6M 12s\n", + " 75750K .......... .......... .......... .......... .......... 12% 43.1M 12s\n", + " 75800K .......... .......... .......... .......... .......... 12% 30.0M 12s\n", + " 75850K .......... .......... .......... .......... .......... 12% 66.8M 12s\n", + " 75900K .......... .......... .......... .......... .......... 12% 54.6M 12s\n", + " 75950K .......... .......... .......... .......... .......... 12% 66.1M 12s\n", + " 76000K .......... .......... .......... .......... .......... 12% 37.7M 12s\n", + " 76050K .......... .......... .......... .......... .......... 12% 38.2M 12s\n", + " 76100K .......... .......... .......... .......... .......... 12% 49.2M 12s\n", + " 76150K .......... .......... .......... .......... .......... 12% 42.8M 12s\n", + " 76200K .......... .......... .......... .......... .......... 12% 32.0M 12s\n", + " 76250K .......... .......... .......... .......... .......... 12% 58.0M 12s\n", + " 76300K .......... .......... .......... .......... .......... 12% 60.1M 12s\n", + " 76350K .......... .......... .......... .......... .......... 12% 53.1M 12s\n", + " 76400K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", + " 76450K .......... .......... .......... .......... .......... 12% 62.3M 12s\n", + " 76500K .......... .......... .......... .......... .......... 12% 64.0M 12s\n", + " 76550K .......... .......... .......... .......... .......... 12% 60.9M 12s\n", + " 76600K .......... .......... .......... .......... .......... 12% 56.8M 12s\n", + " 76650K .......... .......... .......... .......... .......... 12% 50.3M 12s\n", + " 76700K .......... .......... .......... .......... .......... 12% 38.8M 12s\n", + " 76750K .......... .......... .......... .......... .......... 12% 52.9M 12s\n", + " 76800K .......... .......... .......... .......... .......... 12% 42.2M 12s\n", + " 76850K .......... .......... .......... .......... .......... 12% 59.1M 12s\n", + " 76900K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", + " 76950K .......... .......... .......... .......... .......... 12% 41.4M 12s\n", + " 77000K .......... .......... .......... .......... .......... 12% 41.8M 12s\n", + " 77050K .......... .......... .......... .......... .......... 12% 35.4M 12s\n", + " 77100K .......... .......... .......... .......... .......... 12% 39.1M 12s\n", + " 77150K .......... .......... .......... .......... .......... 12% 62.2M 12s\n", + " 77200K .......... .......... .......... .......... .......... 12% 58.2M 12s\n", + " 77250K .......... .......... .......... .......... .......... 12% 48.5M 12s\n", + " 77300K .......... .......... .......... .......... .......... 13% 41.5M 12s\n", + " 77350K .......... .......... .......... .......... .......... 13% 45.9M 12s\n", + " 77400K .......... .......... .......... .......... .......... 13% 46.1M 12s\n", + " 77450K .......... .......... .......... .......... .......... 13% 68.7M 12s\n", + " 77500K .......... .......... .......... .......... .......... 13% 54.3M 12s\n", + " 77550K .......... .......... .......... .......... .......... 13% 50.7M 12s\n", + " 77600K .......... .......... .......... .......... .......... 13% 54.4M 12s\n", + " 77650K .......... .......... .......... .......... .......... 13% 65.2M 12s\n", + " 77700K .......... .......... .......... .......... .......... 13% 53.2M 12s\n", + " 77750K .......... .......... .......... .......... .......... 13% 33.9M 12s\n", + " 77800K .......... .......... .......... .......... .......... 13% 34.1M 12s\n", + " 77850K .......... .......... .......... .......... .......... 13% 67.9M 12s\n", + " 77900K .......... .......... .......... .......... .......... 13% 70.9M 12s\n", + " 77950K .......... .......... .......... .......... .......... 13% 60.0M 12s\n", + " 78000K .......... .......... .......... .......... .......... 13% 41.1M 12s\n", + " 78050K .......... .......... .......... .......... .......... 13% 62.2M 12s\n", + " 78100K .......... .......... .......... .......... .......... 13% 69.1M 12s\n", + " 78150K .......... .......... .......... .......... .......... 13% 68.7M 12s\n", + " 78200K .......... .......... .......... .......... .......... 13% 53.4M 12s\n", + " 78250K .......... .......... .......... .......... .......... 13% 52.9M 12s\n", + " 78300K .......... .......... .......... .......... .......... 13% 58.0M 12s\n", + " 78350K .......... .......... .......... .......... .......... 13% 68.2M 12s\n", + " 78400K .......... .......... .......... .......... .......... 13% 61.4M 12s\n", + " 78450K .......... .......... .......... .......... .......... 13% 67.5M 12s\n", + " 78500K .......... .......... .......... .......... .......... 13% 54.9M 12s\n", + " 78550K .......... .......... .......... .......... .......... 13% 46.5M 12s\n", + " 78600K .......... .......... .......... .......... .......... 13% 49.2M 12s\n", + " 78650K .......... .......... .......... .......... .......... 13% 68.4M 12s\n", + " 78700K .......... .......... .......... .......... .......... 13% 72.7M 12s\n", + " 78750K .......... .......... .......... .......... .......... 13% 59.8M 12s\n", + " 78800K .......... .......... .......... .......... .......... 13% 45.3M 12s\n", + " 78850K .......... .......... .......... .......... .......... 13% 40.0M 12s\n", + " 78900K .......... .......... .......... .......... .......... 13% 66.8M 12s\n", + " 78950K .......... .......... .......... .......... .......... 13% 67.3M 12s\n", + " 79000K .......... .......... .......... .......... .......... 13% 49.3M 12s\n", + " 79050K .......... .......... .......... .......... .......... 13% 53.1M 12s\n", + " 79100K .......... .......... .......... .......... .......... 13% 54.2M 12s\n", + " 79150K .......... .......... .......... .......... .......... 13% 68.6M 12s\n", + " 79200K .......... .......... .......... .......... .......... 13% 60.7M 12s\n", + " 79250K .......... .......... .......... .......... .......... 13% 66.6M 12s\n", + " 79300K .......... .......... .......... .......... .......... 13% 49.4M 12s\n", + " 79350K .......... .......... .......... .......... .......... 13% 46.0M 12s\n", + " 79400K .......... .......... .......... .......... .......... 13% 51.5M 12s\n", + " 79450K .......... .......... .......... .......... .......... 13% 62.7M 12s\n", + " 79500K .......... .......... .......... .......... .......... 13% 65.1M 12s\n", + " 79550K .......... .......... .......... .......... .......... 13% 48.5M 12s\n", + " 79600K .......... .......... .......... .......... .......... 13% 46.3M 12s\n", + " 79650K .......... .......... .......... .......... .......... 13% 65.8M 12s\n", + " 79700K .......... .......... .......... .......... .......... 13% 67.4M 12s\n", + " 79750K .......... .......... .......... .......... .......... 13% 63.8M 12s\n", + " 79800K .......... .......... .......... .......... .......... 13% 40.6M 12s\n", + " 79850K .......... .......... .......... .......... .......... 13% 49.1M 12s\n", + " 79900K .......... .......... .......... .......... .......... 13% 66.5M 12s\n", + " 79950K .......... .......... .......... .......... .......... 13% 75.7M 12s\n", + " 80000K .......... .......... .......... .......... .......... 13% 52.8M 12s\n", + " 80050K .......... .......... .......... .......... .......... 13% 46.8M 11s\n", + " 80100K .......... .......... .......... .......... .......... 13% 47.3M 11s\n", + " 80150K .......... .......... .......... .......... .......... 13% 59.5M 11s\n", + " 80200K .......... .......... .......... .......... .......... 13% 60.7M 11s\n", + " 80250K .......... .......... .......... .......... .......... 13% 70.0M 11s\n", + " 80300K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", + " 80350K .......... .......... .......... .......... .......... 13% 47.2M 11s\n", + " 80400K .......... .......... .......... .......... .......... 13% 61.2M 11s\n", + " 80450K .......... .......... .......... .......... .......... 13% 64.2M 11s\n", + " 80500K .......... .......... .......... .......... .......... 13% 69.5M 11s\n", + " 80550K .......... .......... .......... .......... .......... 13% 54.1M 11s\n", + " 80600K .......... .......... .......... .......... .......... 13% 36.9M 11s\n", + " 80650K .......... .......... .......... .......... .......... 13% 63.3M 11s\n", + " 80700K .......... .......... .......... .......... .......... 13% 65.1M 11s\n", + " 80750K .......... .......... .......... .......... .......... 13% 68.2M 11s\n", + " 80800K .......... .......... .......... .......... .......... 13% 51.1M 11s\n", + " 80850K .......... .......... .......... .......... .......... 13% 45.6M 11s\n", + " 80900K .......... .......... .......... .......... .......... 13% 53.1M 11s\n", + " 80950K .......... .......... .......... .......... .......... 13% 65.5M 11s\n", + " 81000K .......... .......... .......... .......... .......... 13% 56.4M 11s\n", + " 81050K .......... .......... .......... .......... .......... 13% 68.1M 11s\n", + " 81100K .......... .......... .......... .......... .......... 13% 63.7M 11s\n", + " 81150K .......... .......... .......... .......... .......... 13% 51.2M 11s\n", + " 81200K .......... .......... .......... .......... .......... 13% 53.8M 11s\n", + " 81250K .......... .......... .......... .......... .......... 13% 67.5M 11s\n", + " 81300K .......... .......... .......... .......... .......... 13% 65.0M 11s\n", + " 81350K .......... .......... .......... .......... .......... 13% 57.8M 11s\n", + " 81400K .......... .......... .......... .......... .......... 13% 43.9M 11s\n", + " 81450K .......... .......... .......... .......... .......... 13% 54.0M 11s\n", + " 81500K .......... .......... .......... .......... .......... 13% 75.0M 11s\n", + " 81550K .......... .......... .......... .......... .......... 13% 65.8M 11s\n", + " 81600K .......... .......... .......... .......... .......... 13% 53.8M 11s\n", + " 81650K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", + " 81700K .......... .......... .......... .......... .......... 13% 45.7M 11s\n", + " 81750K .......... .......... .......... .......... .......... 13% 64.3M 11s\n", + " 81800K .......... .......... .......... .......... .......... 13% 56.6M 11s\n", + " 81850K .......... .......... .......... .......... .......... 13% 70.9M 11s\n", + " 81900K .......... .......... .......... .......... .......... 13% 47.6M 11s\n", + " 81950K .......... .......... .......... .......... .......... 13% 50.3M 11s\n", + " 82000K .......... .......... .......... .......... .......... 13% 59.3M 11s\n", + " 82050K .......... .......... .......... .......... .......... 13% 65.4M 11s\n", + " 82100K .......... .......... .......... .......... .......... 13% 58.1M 11s\n", + " 82150K .......... .......... .......... .......... .......... 13% 54.5M 11s\n", + " 82200K .......... .......... .......... .......... .......... 13% 39.4M 11s\n", + " 82250K .......... .......... .......... .......... .......... 13% 61.7M 11s\n", + " 82300K .......... .......... .......... .......... .......... 13% 70.5M 11s\n", + " 82350K .......... .......... .......... .......... .......... 13% 62.4M 11s\n", + " 82400K .......... .......... .......... .......... .......... 13% 3.82M 11s\n", + " 82450K .......... .......... .......... .......... .......... 13% 17.9M 11s\n", + " 82500K .......... .......... .......... .......... .......... 13% 68.7M 11s\n", + " 82550K .......... .......... .......... .......... .......... 13% 3.90M 12s\n", + " 82600K .......... .......... .......... .......... .......... 13% 50.7M 12s\n", + " 82650K .......... .......... .......... .......... .......... 13% 65.7M 12s\n", + " 82700K .......... .......... .......... .......... .......... 13% 58.5M 12s\n", + " 82750K .......... .......... .......... .......... .......... 13% 64.8M 12s\n", + " 82800K .......... .......... .......... .......... .......... 13% 56.7M 12s\n", + " 82850K .......... .......... .......... .......... .......... 13% 63.4M 12s\n", + " 82900K .......... .......... .......... .......... .......... 13% 57.3M 12s\n", + " 82950K .......... .......... .......... .......... .......... 13% 66.7M 11s\n", + " 83000K .......... .......... .......... .......... .......... 13% 55.2M 11s\n", + " 83050K .......... .......... .......... .......... .......... 13% 60.5M 11s\n", + " 83100K .......... .......... .......... .......... .......... 13% 60.3M 11s\n", + " 83150K .......... .......... .......... .......... .......... 13% 56.2M 11s\n", + " 83200K .......... .......... .......... .......... .......... 13% 53.2M 11s\n", + " 83250K .......... .......... .......... .......... .......... 14% 67.3M 11s\n", + " 83300K .......... .......... .......... .......... .......... 14% 66.8M 11s\n", + " 83350K .......... .......... .......... .......... .......... 14% 55.7M 11s\n", + " 83400K .......... .......... .......... .......... .......... 14% 50.8M 11s\n", + " 83450K .......... .......... .......... .......... .......... 14% 62.6M 11s\n", + " 83500K .......... .......... .......... .......... .......... 14% 73.1M 11s\n", + " 83550K .......... .......... .......... .......... .......... 14% 55.5M 11s\n", + " 83600K .......... .......... .......... .......... .......... 14% 53.4M 11s\n", + " 83650K .......... .......... .......... .......... .......... 14% 62.0M 11s\n", + " 83700K .......... .......... .......... .......... .......... 14% 51.0M 11s\n", + " 83750K .......... .......... .......... .......... .......... 14% 65.1M 11s\n", + " 83800K .......... .......... .......... .......... .......... 14% 49.2M 11s\n", + " 83850K .......... .......... .......... .......... .......... 14% 22.9M 11s\n", + " 83900K .......... .......... .......... .......... .......... 14% 47.7M 11s\n", + " 83950K .......... .......... .......... .......... .......... 14% 66.8M 11s\n", + " 84000K .......... .......... .......... .......... .......... 14% 32.3M 11s\n", + " 84050K .......... .......... .......... .......... .......... 14% 67.9M 11s\n", + " 84100K .......... .......... .......... .......... .......... 14% 69.1M 11s\n", + " 84150K .......... .......... .......... .......... .......... 14% 51.9M 11s\n", + " 84200K .......... .......... .......... .......... .......... 14% 39.3M 11s\n", + " 84250K .......... .......... .......... .......... .......... 14% 55.2M 11s\n", + " 84300K .......... .......... .......... .......... .......... 14% 58.0M 11s\n", + " 84350K .......... .......... .......... .......... .......... 14% 57.5M 11s\n", + " 84400K .......... .......... .......... .......... .......... 14% 43.6M 11s\n", + " 84450K .......... .......... .......... .......... .......... 14% 51.1M 11s\n", + " 84500K .......... .......... .......... .......... .......... 14% 52.5M 11s\n", + " 84550K .......... .......... .......... .......... .......... 14% 48.0M 11s\n", + " 84600K .......... .......... .......... .......... .......... 14% 40.7M 11s\n", + " 84650K .......... .......... .......... .......... .......... 14% 51.5M 11s\n", + " 84700K .......... .......... .......... .......... .......... 14% 57.8M 11s\n", + " 84750K .......... .......... .......... .......... .......... 14% 53.2M 11s\n", + " 84800K .......... .......... .......... .......... .......... 14% 54.5M 11s\n", + " 84850K .......... .......... .......... .......... .......... 14% 52.8M 11s\n", + " 84900K .......... .......... .......... .......... .......... 14% 5.51M 11s\n", + " 84950K .......... .......... .......... .......... .......... 14% 70.8M 11s\n", + " 85000K .......... .......... .......... .......... .......... 14% 62.1M 11s\n", + " 85050K .......... .......... .......... .......... .......... 14% 58.2M 11s\n", + " 85100K .......... .......... .......... .......... .......... 14% 64.1M 11s\n", + " 85150K .......... .......... .......... .......... .......... 14% 63.4M 11s\n", + " 85200K .......... .......... .......... .......... .......... 14% 35.9M 11s\n", + " 85250K .......... .......... .......... .......... .......... 14% 62.4M 11s\n", + " 85300K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", + " 85350K .......... .......... .......... .......... .......... 14% 52.4M 11s\n", + " 85400K .......... .......... .......... .......... .......... 14% 55.1M 11s\n", + " 85450K .......... .......... .......... .......... .......... 14% 49.9M 11s\n", + " 85500K .......... .......... .......... .......... .......... 14% 62.7M 11s\n", + " 85550K .......... .......... .......... .......... .......... 14% 65.0M 11s\n", + " 85600K .......... .......... .......... .......... .......... 14% 47.2M 11s\n", + " 85650K .......... .......... .......... .......... .......... 14% 66.7M 11s\n", + " 85700K .......... .......... .......... .......... .......... 14% 62.3M 11s\n", + " 85750K .......... .......... .......... .......... .......... 14% 51.7M 11s\n", + " 85800K .......... .......... .......... .......... .......... 14% 42.5M 11s\n", + " 85850K .......... .......... .......... .......... .......... 14% 60.6M 11s\n", + " 85900K .......... .......... .......... .......... .......... 14% 66.7M 11s\n", + " 85950K .......... .......... .......... .......... .......... 14% 48.9M 11s\n", + " 86000K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", + " 86050K .......... .......... .......... .......... .......... 14% 66.6M 11s\n", + " 86100K .......... .......... .......... .......... .......... 14% 51.5M 11s\n", + " 86150K .......... .......... .......... .......... .......... 14% 54.0M 11s\n", + " 86200K .......... .......... .......... .......... .......... 14% 42.2M 11s\n", + " 86250K .......... .......... .......... .......... .......... 14% 66.4M 11s\n", + " 86300K .......... .......... .......... .......... .......... 14% 71.4M 11s\n", + " 86350K .......... .......... .......... .......... .......... 14% 42.1M 11s\n", + " 86400K .......... .......... .......... .......... .......... 14% 47.4M 11s\n", + " 86450K .......... .......... .......... .......... .......... 14% 50.4M 11s\n", + " 86500K .......... .......... .......... .......... .......... 14% 67.8M 11s\n", + " 86550K .......... .......... .......... .......... .......... 14% 61.0M 11s\n", + " 86600K .......... .......... .......... .......... .......... 14% 43.9M 11s\n", + " 86650K .......... .......... .......... .......... .......... 14% 60.0M 11s\n", + " 86700K .......... .......... .......... .......... .......... 14% 53.8M 11s\n", + " 86750K .......... .......... .......... .......... .......... 14% 71.8M 11s\n", + " 86800K .......... .......... .......... .......... .......... 14% 51.4M 11s\n", + " 86850K .......... .......... .......... .......... .......... 14% 38.8M 11s\n", + " 86900K .......... .......... .......... .......... .......... 14% 44.1M 11s\n", + " 86950K .......... .......... .......... .......... .......... 14% 61.4M 11s\n", + " 87000K .......... .......... .......... .......... .......... 14% 56.8M 11s\n", + " 87050K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", + " 87100K .......... .......... .......... .......... .......... 14% 46.3M 11s\n", + " 87150K .......... .......... .......... .......... .......... 14% 51.6M 11s\n", + " 87200K .......... .......... .......... .......... .......... 14% 58.7M 11s\n", + " 87250K .......... .......... .......... .......... .......... 14% 66.3M 11s\n", + " 87300K .......... .......... .......... .......... .......... 14% 52.6M 11s\n", + " 87350K .......... .......... .......... .......... .......... 14% 52.2M 11s\n", + " 87400K .......... .......... .......... .......... .......... 14% 42.9M 11s\n", + " 87450K .......... .......... .......... .......... .......... 14% 68.0M 11s\n", + " 87500K .......... .......... .......... .......... .......... 14% 70.1M 11s\n", + " 87550K .......... .......... .......... .......... .......... 14% 58.4M 11s\n", + " 87600K .......... .......... .......... .......... .......... 14% 45.2M 11s\n", + " 87650K .......... .......... .......... .......... .......... 14% 3.58M 11s\n", + " 87700K .......... .......... .......... .......... .......... 14% 59.9M 11s\n", + " 87750K .......... .......... .......... .......... .......... 14% 59.8M 11s\n", + " 87800K .......... .......... .......... .......... .......... 14% 34.5M 11s\n", + " 87850K .......... .......... .......... .......... .......... 14% 31.7M 11s\n", + " 87900K .......... .......... .......... .......... .......... 14% 39.1M 11s\n", + " 87950K .......... .......... .......... .......... .......... 14% 33.9M 11s\n", + " 88000K .......... .......... .......... .......... .......... 14% 30.6M 11s\n", + " 88050K .......... .......... .......... .......... .......... 14% 46.2M 11s\n", + " 88100K .......... .......... .......... .......... .......... 14% 47.8M 11s\n", + " 88150K .......... .......... .......... .......... .......... 14% 55.5M 11s\n", + " 88200K .......... .......... .......... .......... .......... 14% 36.2M 11s\n", + " 88250K .......... .......... .......... .......... .......... 14% 57.5M 11s\n", + " 88300K .......... .......... .......... .......... .......... 14% 66.4M 11s\n", + " 88350K .......... .......... .......... .......... .......... 14% 60.4M 11s\n", + " 88400K .......... .......... .......... .......... .......... 14% 50.7M 11s\n", + " 88450K .......... .......... .......... .......... .......... 14% 58.2M 11s\n", + " 88500K .......... .......... .......... .......... .......... 14% 56.9M 11s\n", + " 88550K .......... .......... .......... .......... .......... 14% 64.8M 11s\n", + " 88600K .......... .......... .......... .......... .......... 14% 45.9M 11s\n", + " 88650K .......... .......... .......... .......... .......... 14% 48.9M 11s\n", + " 88700K .......... .......... .......... .......... .......... 14% 53.4M 11s\n", + " 88750K .......... .......... .......... .......... .......... 14% 65.4M 11s\n", + " 88800K .......... .......... .......... .......... .......... 14% 44.4M 11s\n", + " 88850K .......... .......... .......... .......... .......... 14% 48.3M 11s\n", + " 88900K .......... .......... .......... .......... .......... 14% 64.4M 11s\n", + " 88950K .......... .......... .......... .......... .......... 14% 48.5M 11s\n", + " 89000K .......... .......... .......... .......... .......... 14% 51.4M 11s\n", + " 89050K .......... .......... .......... .......... .......... 14% 69.0M 11s\n", + " 89100K .......... .......... .......... .......... .......... 14% 48.2M 11s\n", + " 89150K .......... .......... .......... .......... .......... 14% 41.5M 11s\n", + " 89200K .......... .......... .......... .......... .......... 15% 3.49M 11s\n", + " 89250K .......... .......... .......... .......... .......... 15% 58.9M 11s\n", + " 89300K .......... .......... .......... .......... .......... 15% 9.58M 11s\n", + " 89350K .......... .......... .......... .......... .......... 15% 47.1M 11s\n", + " 89400K .......... .......... .......... .......... .......... 15% 35.5M 11s\n", + " 89450K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", + " 89500K .......... .......... .......... .......... .......... 15% 66.0M 11s\n", + " 89550K .......... .......... .......... .......... .......... 15% 47.4M 11s\n", + " 89600K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", + " 89650K .......... .......... .......... .......... .......... 15% 57.9M 11s\n", + " 89700K .......... .......... .......... .......... .......... 15% 69.5M 11s\n", + " 89750K .......... .......... .......... .......... .......... 15% 47.8M 11s\n", + " 89800K .......... .......... .......... .......... .......... 15% 42.9M 11s\n", + " 89850K .......... .......... .......... .......... .......... 15% 41.7M 11s\n", + " 89900K .......... .......... .......... .......... .......... 15% 52.1M 11s\n", + " 89950K .......... .......... .......... .......... .......... 15% 70.6M 11s\n", + " 90000K .......... .......... .......... .......... .......... 15% 56.5M 11s\n", + " 90050K .......... .......... .......... .......... .......... 15% 50.3M 11s\n", + " 90100K .......... .......... .......... .......... .......... 15% 48.4M 11s\n", + " 90150K .......... .......... .......... .......... .......... 15% 54.8M 11s\n", + " 90200K .......... .......... .......... .......... .......... 15% 55.2M 11s\n", + " 90250K .......... .......... .......... .......... .......... 15% 67.4M 11s\n", + " 90300K .......... .......... .......... .......... .......... 15% 62.5M 11s\n", + " 90350K .......... .......... .......... .......... .......... 15% 49.0M 11s\n", + " 90400K .......... .......... .......... .......... .......... 15% 49.1M 11s\n", + " 90450K .......... .......... .......... .......... .......... 15% 72.4M 11s\n", + " 90500K .......... .......... .......... .......... .......... 15% 67.7M 11s\n", + " 90550K .......... .......... .......... .......... .......... 15% 66.7M 11s\n", + " 90600K .......... .......... .......... .......... .......... 15% 34.5M 11s\n", + " 90650K .......... .......... .......... .......... .......... 15% 48.0M 11s\n", + " 90700K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", + " 90750K .......... .......... .......... .......... .......... 15% 54.7M 11s\n", + " 90800K .......... .......... .......... .......... .......... 15% 25.7M 11s\n", + " 90850K .......... .......... .......... .......... .......... 15% 35.2M 11s\n", + " 90900K .......... .......... .......... .......... .......... 15% 44.7M 11s\n", + " 90950K .......... .......... .......... .......... .......... 15% 47.9M 11s\n", + " 91000K .......... .......... .......... .......... .......... 15% 37.3M 11s\n", + " 91050K .......... .......... .......... .......... .......... 15% 43.7M 11s\n", + " 91100K .......... .......... .......... .......... .......... 15% 44.5M 11s\n", + " 91150K .......... .......... .......... .......... .......... 15% 34.1M 11s\n", + " 91200K .......... .......... .......... .......... .......... 15% 30.6M 11s\n", + " 91250K .......... .......... .......... .......... .......... 15% 44.0M 11s\n", + " 91300K .......... .......... .......... .......... .......... 15% 44.0M 11s\n", + " 91350K .......... .......... .......... .......... .......... 15% 53.0M 11s\n", + " 91400K .......... .......... .......... .......... .......... 15% 52.7M 11s\n", + " 91450K .......... .......... .......... .......... .......... 15% 54.7M 11s\n", + " 91500K .......... .......... .......... .......... .......... 15% 39.6M 11s\n", + " 91550K .......... .......... .......... .......... .......... 15% 37.1M 11s\n", + " 91600K .......... .......... .......... .......... .......... 15% 31.7M 11s\n", + " 91650K .......... .......... .......... .......... .......... 15% 47.2M 11s\n", + " 91700K .......... .......... .......... .......... .......... 15% 47.1M 11s\n", + " 91750K .......... .......... .......... .......... .......... 15% 56.7M 11s\n", + " 91800K .......... .......... .......... .......... .......... 15% 46.9M 11s\n", + " 91850K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", + " 91900K .......... .......... .......... .......... .......... 15% 4.61M 11s\n", + " 91950K .......... .......... .......... .......... .......... 15% 46.8M 11s\n", + " 92000K .......... .......... .......... .......... .......... 15% 36.8M 11s\n", + " 92050K .......... .......... .......... .......... .......... 15% 39.1M 11s\n", + " 92100K .......... .......... .......... .......... .......... 15% 33.0M 11s\n", + " 92150K .......... .......... .......... .......... .......... 15% 43.3M 11s\n", + " 92200K .......... .......... .......... .......... .......... 15% 50.0M 11s\n", + " 92250K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", + " 92300K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", + " 92350K .......... .......... .......... .......... .......... 15% 59.5M 11s\n", + " 92400K .......... .......... .......... .......... .......... 15% 52.4M 11s\n", + " 92450K .......... .......... .......... .......... .......... 15% 14.2M 11s\n", + " 92500K .......... .......... .......... .......... .......... 15% 45.9M 11s\n", + " 92550K .......... .......... .......... .......... .......... 15% 52.3M 11s\n", + " 92600K .......... .......... .......... .......... .......... 15% 53.7M 11s\n", + " 92650K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", + " 92700K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", + " 92750K .......... .......... .......... .......... .......... 15% 50.9M 11s\n", + " 92800K .......... .......... .......... .......... .......... 15% 54.5M 11s\n", + " 92850K .......... .......... .......... .......... .......... 15% 64.2M 11s\n", + " 92900K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", + " 92950K .......... .......... .......... .......... .......... 15% 59.5M 11s\n", + " 93000K .......... .......... .......... .......... .......... 15% 42.0M 11s\n", + " 93050K .......... .......... .......... .......... .......... 15% 49.7M 11s\n", + " 93100K .......... .......... .......... .......... .......... 15% 64.4M 11s\n", + " 93150K .......... .......... .......... .......... .......... 15% 55.0M 11s\n", + " 93200K .......... .......... .......... .......... .......... 15% 59.4M 11s\n", + " 93250K .......... .......... .......... .......... .......... 15% 47.4M 11s\n", + " 93300K .......... .......... .......... .......... .......... 15% 47.2M 11s\n", + " 93350K .......... .......... .......... .......... .......... 15% 68.1M 11s\n", + " 93400K .......... .......... .......... .......... .......... 15% 58.6M 11s\n", + " 93450K .......... .......... .......... .......... .......... 15% 69.9M 11s\n", + " 93500K .......... .......... .......... .......... .......... 15% 57.6M 11s\n", + " 93550K .......... .......... .......... .......... .......... 15% 49.4M 11s\n", + " 93600K .......... .......... .......... .......... .......... 15% 52.3M 11s\n", + " 93650K .......... .......... .......... .......... .......... 15% 66.1M 11s\n", + " 93700K .......... .......... .......... .......... .......... 15% 65.3M 11s\n", + " 93750K .......... .......... .......... .......... .......... 15% 55.0M 11s\n", + " 93800K .......... .......... .......... .......... .......... 15% 3.81M 11s\n", + " 93850K .......... .......... .......... .......... .......... 15% 56.7M 11s\n", + " 93900K .......... .......... .......... .......... .......... 15% 67.9M 11s\n", + " 93950K .......... .......... .......... .......... .......... 15% 67.6M 11s\n", + " 94000K .......... .......... .......... .......... .......... 15% 52.6M 11s\n", + " 94050K .......... .......... .......... .......... .......... 15% 64.6M 11s\n", + " 94100K .......... .......... .......... .......... .......... 15% 69.7M 11s\n", + " 94150K .......... .......... .......... .......... .......... 15% 48.8M 11s\n", + " 94200K .......... .......... .......... .......... .......... 15% 53.6M 11s\n", + " 94250K .......... .......... .......... .......... .......... 15% 56.9M 11s\n", + " 94300K .......... .......... .......... .......... .......... 15% 47.5M 11s\n", + " 94350K .......... .......... .......... .......... .......... 15% 44.6M 11s\n", + " 94400K .......... .......... .......... .......... .......... 15% 52.0M 11s\n", + " 94450K .......... .......... .......... .......... .......... 15% 67.2M 11s\n", + " 94500K .......... .......... .......... .......... .......... 15% 68.7M 11s\n", + " 94550K .......... .......... .......... .......... .......... 15% 47.7M 11s\n", + " 94600K .......... .......... .......... .......... .......... 15% 40.5M 11s\n", + " 94650K .......... .......... .......... .......... .......... 15% 68.1M 11s\n", + " 94700K .......... .......... .......... .......... .......... 15% 68.0M 11s\n", + " 94750K .......... .......... .......... .......... .......... 15% 70.5M 11s\n", + " 94800K .......... .......... .......... .......... .......... 15% 9.29M 11s\n", + " 94850K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", + " 94900K .......... .......... .......... .......... .......... 15% 66.6M 11s\n", + " 94950K .......... .......... .......... .......... .......... 15% 63.0M 11s\n", + " 95000K .......... .......... .......... .......... .......... 15% 53.9M 11s\n", + " 95050K .......... .......... .......... .......... .......... 15% 57.9M 11s\n", + " 95100K .......... .......... .......... .......... .......... 15% 48.0M 11s\n", + " 95150K .......... .......... .......... .......... .......... 16% 56.8M 11s\n", + " 95200K .......... .......... .......... .......... .......... 16% 61.1M 11s\n", + " 95250K .......... .......... .......... .......... .......... 16% 66.1M 11s\n", + " 95300K .......... .......... .......... .......... .......... 16% 63.8M 11s\n", + " 95350K .......... .......... .......... .......... .......... 16% 67.3M 11s\n", + " 95400K .......... .......... .......... .......... .......... 16% 35.2M 11s\n", + " 95450K .......... .......... .......... .......... .......... 16% 61.3M 11s\n", + " 95500K .......... .......... .......... .......... .......... 16% 66.1M 11s\n", + " 95550K .......... .......... .......... .......... .......... 16% 70.6M 11s\n", + " 95600K .......... .......... .......... .......... .......... 16% 53.5M 11s\n", + " 95650K .......... .......... .......... .......... .......... 16% 49.6M 11s\n", + " 95700K .......... .......... .......... .......... .......... 16% 49.0M 11s\n", + " 95750K .......... .......... .......... .......... .......... 16% 72.2M 11s\n", + " 95800K .......... .......... .......... .......... .......... 16% 60.5M 11s\n", + " 95850K .......... .......... .......... .......... .......... 16% 71.3M 11s\n", + " 95900K .......... .......... .......... .......... .......... 16% 48.7M 11s\n", + " 95950K .......... .......... .......... .......... .......... 16% 45.9M 11s\n", + " 96000K .......... .......... .......... .......... .......... 16% 57.2M 11s\n", + " 96050K .......... .......... .......... .......... .......... 16% 70.1M 11s\n", + " 96100K .......... .......... .......... .......... .......... 16% 73.7M 11s\n", + " 96150K .......... .......... .......... .......... .......... 16% 72.0M 11s\n", + " 96200K .......... .......... .......... .......... .......... 16% 37.1M 11s\n", + " 96250K .......... .......... .......... .......... .......... 16% 52.4M 11s\n", + " 96300K .......... .......... .......... .......... .......... 16% 61.4M 11s\n", + " 96350K .......... .......... .......... .......... .......... 16% 65.5M 11s\n", + " 96400K .......... .......... .......... .......... .......... 16% 45.2M 11s\n", + " 96450K .......... .......... .......... .......... .......... 16% 44.0M 11s\n", + " 96500K .......... .......... .......... .......... .......... 16% 53.9M 11s\n", + " 96550K .......... .......... .......... .......... .......... 16% 41.9M 11s\n", + " 96600K .......... .......... .......... .......... .......... 16% 10.1M 11s\n", + " 96650K .......... .......... .......... .......... .......... 16% 52.0M 11s\n", + " 96700K .......... .......... .......... .......... .......... 16% 49.1M 11s\n", + " 96750K .......... .......... .......... .......... .......... 16% 68.4M 11s\n", + " 96800K .......... .......... .......... .......... .......... 16% 56.8M 11s\n", + " 96850K .......... .......... .......... .......... .......... 16% 69.5M 11s\n", + " 96900K .......... .......... .......... .......... .......... 16% 50.8M 11s\n", + " 96950K .......... .......... .......... .......... .......... 16% 17.1M 11s\n", + " 97000K .......... .......... .......... .......... .......... 16% 53.9M 11s\n", + " 97050K .......... .......... .......... .......... .......... 16% 44.4M 11s\n", + " 97100K .......... .......... .......... .......... .......... 16% 50.6M 11s\n", + " 97150K .......... .......... .......... .......... .......... 16% 62.9M 11s\n", + " 97200K .......... .......... .......... .......... .......... 16% 60.1M 11s\n", + " 97250K .......... .......... .......... .......... .......... 16% 57.9M 11s\n", + " 97300K .......... .......... .......... .......... .......... 16% 42.2M 11s\n", + " 97350K .......... .......... .......... .......... .......... 16% 19.0M 11s\n", + " 97400K .......... .......... .......... .......... .......... 16% 43.5M 11s\n", + " 97450K .......... .......... .......... .......... .......... 16% 40.5M 11s\n", + " 97500K .......... .......... .......... .......... .......... 16% 57.8M 11s\n", + " 97550K .......... .......... .......... .......... .......... 16% 65.5M 11s\n", + " 97600K .......... .......... .......... .......... .......... 16% 59.8M 11s\n", + " 97650K .......... .......... .......... .......... .......... 16% 68.5M 11s\n", + " 97700K .......... .......... .......... .......... .......... 16% 48.2M 11s\n", + " 97750K .......... .......... .......... .......... .......... 16% 54.2M 11s\n", + " 97800K .......... .......... .......... .......... .......... 16% 59.6M 11s\n", + " 97850K .......... .......... .......... .......... .......... 16% 67.0M 11s\n", + " 97900K .......... .......... .......... .......... .......... 16% 67.4M 11s\n", + " 97950K .......... .......... .......... .......... .......... 16% 48.9M 11s\n", + " 98000K .......... .......... .......... .......... .......... 16% 42.2M 11s\n", + " 98050K .......... .......... .......... .......... .......... 16% 56.2M 11s\n", + " 98100K .......... .......... .......... .......... .......... 16% 69.9M 11s\n", + " 98150K .......... .......... .......... .......... .......... 16% 61.5M 11s\n", + " 98200K .......... .......... .......... .......... .......... 16% 45.2M 11s\n", + " 98250K .......... .......... .......... .......... .......... 16% 45.0M 11s\n", + " 98300K .......... .......... .......... .......... .......... 16% 65.8M 11s\n", + " 98350K .......... .......... .......... .......... .......... 16% 63.9M 11s\n", + " 98400K .......... .......... .......... .......... .......... 16% 60.2M 11s\n", + " 98450K .......... .......... .......... .......... .......... 16% 63.8M 11s\n", + " 98500K .......... .......... .......... .......... .......... 16% 47.8M 11s\n", + " 98550K .......... .......... .......... .......... .......... 16% 57.9M 11s\n", + " 98600K .......... .......... .......... .......... .......... 16% 57.2M 11s\n", + " 98650K .......... .......... .......... .......... .......... 16% 64.7M 11s\n", + " 98700K .......... .......... .......... .......... .......... 16% 66.8M 11s\n", + " 98750K .......... .......... .......... .......... .......... 16% 58.6M 11s\n", + " 98800K .......... .......... .......... .......... .......... 16% 47.0M 11s\n", + " 98850K .......... .......... .......... .......... .......... 16% 37.1M 11s\n", + " 98900K .......... .......... .......... .......... .......... 16% 47.3M 11s\n", + " 98950K .......... .......... .......... .......... .......... 16% 50.7M 11s\n", + " 99000K .......... .......... .......... .......... .......... 16% 50.3M 11s\n", + " 99050K .......... .......... .......... .......... .......... 16% 47.8M 11s\n", + " 99100K .......... .......... .......... .......... .......... 16% 36.0M 11s\n", + " 99150K .......... .......... .......... .......... .......... 16% 10.6M 11s\n", + " 99200K .......... .......... .......... .......... .......... 16% 56.3M 11s\n", + " 99250K .......... .......... .......... .......... .......... 16% 71.4M 11s\n", + " 99300K .......... .......... .......... .......... .......... 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.......... .......... 16% 72.6M 11s\n", + "100550K .......... .......... .......... .......... .......... 16% 71.3M 11s\n", + "100600K .......... .......... .......... .......... .......... 16% 43.0M 11s\n", + "100650K .......... .......... .......... .......... .......... 16% 41.1M 11s\n", + "100700K .......... .......... .......... .......... .......... 16% 59.0M 11s\n", + "100750K .......... .......... .......... .......... .......... 16% 66.2M 11s\n", + "100800K .......... .......... .......... .......... .......... 16% 60.1M 11s\n", + "100850K .......... .......... .......... .......... .......... 16% 46.8M 11s\n", + "100900K .......... .......... .......... .......... .......... 16% 40.9M 11s\n", + "100950K .......... .......... .......... .......... .......... 16% 60.5M 11s\n", + "101000K .......... .......... .......... .......... .......... 16% 60.3M 11s\n", + "101050K .......... .......... .......... .......... .......... 16% 61.0M 11s\n", + "101100K .......... .......... .......... .......... .......... 17% 46.9M 11s\n", + "101150K .......... .......... .......... .......... .......... 17% 42.2M 11s\n", + "101200K .......... .......... .......... .......... .......... 17% 51.9M 11s\n", + "101250K .......... .......... .......... .......... .......... 17% 66.0M 11s\n", + "101300K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", + "101350K .......... .......... .......... .......... .......... 17% 41.0M 11s\n", + "101400K .......... .......... .......... .......... .......... 17% 32.7M 11s\n", + "101450K .......... .......... .......... .......... .......... 17% 68.8M 11s\n", + "101500K .......... .......... .......... .......... .......... 17% 67.3M 11s\n", + "101550K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", + "101600K .......... .......... .......... .......... .......... 17% 38.3M 11s\n", + "101650K .......... .......... .......... .......... .......... 17% 40.8M 11s\n", + "101700K .......... .......... .......... .......... .......... 17% 66.6M 11s\n", + "101750K .......... .......... .......... .......... .......... 17% 68.6M 11s\n", + "101800K .......... .......... .......... .......... .......... 17% 46.8M 11s\n", + "101850K .......... .......... .......... .......... .......... 17% 39.0M 11s\n", + "101900K .......... .......... .......... .......... .......... 17% 56.2M 11s\n", + "101950K .......... .......... .......... .......... .......... 17% 71.9M 11s\n", + "102000K .......... .......... .......... .......... .......... 17% 62.4M 11s\n", + "102050K .......... .......... .......... .......... .......... 17% 4.93M 11s\n", + "102100K .......... .......... .......... .......... .......... 17% 67.4M 11s\n", + "102150K .......... .......... .......... .......... .......... 17% 66.4M 11s\n", + "102200K .......... .......... .......... .......... .......... 17% 56.9M 11s\n", + "102250K .......... .......... .......... .......... .......... 17% 69.4M 11s\n", + "102300K .......... .......... .......... .......... .......... 17% 61.6M 11s\n", + "102350K .......... .......... .......... .......... .......... 17% 38.6M 11s\n", + "102400K .......... .......... .......... .......... .......... 17% 54.9M 11s\n", + "102450K .......... .......... .......... .......... .......... 17% 74.6M 11s\n", + "102500K .......... .......... .......... .......... .......... 17% 82.8M 11s\n", + "102550K .......... .......... .......... .......... .......... 17% 80.3M 11s\n", + "102600K .......... .......... .......... .......... .......... 17% 57.1M 11s\n", + "102650K .......... .......... .......... .......... .......... 17% 50.3M 11s\n", + "102700K .......... .......... .......... .......... .......... 17% 47.4M 11s\n", + "102750K .......... .......... .......... .......... .......... 17% 4.23M 11s\n", + "102800K .......... .......... .......... .......... .......... 17% 59.5M 11s\n", + "102850K .......... .......... .......... .......... .......... 17% 63.6M 11s\n", + "102900K .......... .......... .......... .......... .......... 17% 59.7M 11s\n", + "102950K .......... .......... .......... .......... .......... 17% 63.8M 11s\n", + "103000K .......... .......... .......... .......... .......... 17% 53.2M 11s\n", + "103050K .......... .......... .......... .......... .......... 17% 45.0M 11s\n", + "103100K .......... .......... .......... .......... .......... 17% 63.3M 11s\n", + "103150K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", + "103200K .......... .......... .......... .......... .......... 17% 56.7M 11s\n", + "103250K .......... .......... .......... .......... .......... 17% 61.3M 11s\n", + "103300K .......... .......... .......... .......... .......... 17% 57.2M 11s\n", + "103350K .......... .......... .......... .......... .......... 17% 46.7M 11s\n", + "103400K .......... .......... .......... .......... .......... 17% 53.8M 11s\n", + "103450K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", + "103500K .......... .......... .......... .......... .......... 17% 70.7M 11s\n", + "103550K .......... .......... .......... .......... .......... 17% 4.12M 11s\n", + "103600K .......... .......... .......... .......... .......... 17% 62.3M 11s\n", + "103650K .......... .......... .......... .......... .......... 17% 58.3M 11s\n", + "103700K .......... .......... .......... .......... .......... 17% 66.1M 11s\n", + "103750K .......... .......... .......... .......... .......... 17% 65.4M 11s\n", + "103800K .......... .......... .......... .......... .......... 17% 51.5M 11s\n", + "103850K .......... .......... .......... .......... .......... 17% 57.2M 11s\n", + "103900K .......... .......... .......... .......... .......... 17% 60.9M 11s\n", + "103950K .......... .......... .......... .......... .......... 17% 51.7M 11s\n", + "104000K .......... .......... .......... .......... .......... 17% 52.6M 11s\n", + "104050K .......... .......... .......... .......... .......... 17% 66.1M 11s\n", + "104100K .......... .......... .......... .......... .......... 17% 60.3M 11s\n", + "104150K .......... .......... .......... .......... .......... 17% 4.06M 11s\n", + "104200K .......... .......... .......... .......... .......... 17% 44.1M 11s\n", + "104250K .......... .......... .......... .......... .......... 17% 59.6M 11s\n", + "104300K .......... .......... .......... .......... .......... 17% 63.9M 11s\n", + "104350K .......... .......... .......... .......... .......... 17% 72.1M 11s\n", + "104400K .......... .......... .......... .......... .......... 17% 13.9M 11s\n", + "104450K .......... .......... .......... .......... .......... 17% 61.4M 11s\n", + "104500K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", + "104550K .......... .......... .......... .......... .......... 17% 67.3M 11s\n", + "104600K .......... .......... .......... .......... .......... 17% 40.2M 11s\n", + "104650K .......... .......... .......... .......... 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.......... .......... 17% 64.8M 11s\n", + "105300K .......... .......... .......... .......... .......... 17% 65.3M 11s\n", + "105350K .......... .......... .......... .......... .......... 17% 59.6M 11s\n", + "105400K .......... .......... .......... .......... .......... 17% 36.6M 11s\n", + "105450K .......... .......... .......... .......... .......... 17% 55.8M 11s\n", + "105500K .......... .......... .......... .......... .......... 17% 72.8M 11s\n", + "105550K .......... .......... .......... .......... .......... 17% 64.0M 11s\n", + "105600K .......... .......... .......... .......... .......... 17% 48.1M 11s\n", + "105650K .......... .......... .......... .......... .......... 17% 43.4M 11s\n", + "105700K .......... .......... .......... .......... .......... 17% 54.7M 11s\n", + "105750K .......... .......... .......... .......... .......... 17% 67.5M 11s\n", + "105800K .......... .......... .......... .......... .......... 17% 54.8M 11s\n", + "105850K .......... .......... .......... .......... .......... 17% 65.6M 11s\n", + "105900K .......... .......... .......... .......... .......... 17% 47.7M 11s\n", + "105950K .......... .......... .......... .......... .......... 17% 59.0M 11s\n", + "106000K .......... .......... .......... .......... .......... 17% 59.1M 11s\n", + "106050K .......... .......... .......... .......... .......... 17% 73.5M 11s\n", + "106100K .......... .......... .......... .......... .......... 17% 4.15M 11s\n", + "106150K .......... .......... .......... .......... .......... 17% 66.3M 11s\n", + "106200K .......... .......... .......... .......... .......... 17% 52.9M 11s\n", + "106250K .......... .......... .......... .......... .......... 17% 64.6M 11s\n", + "106300K .......... .......... .......... .......... .......... 17% 68.4M 11s\n", + "106350K .......... .......... .......... .......... .......... 17% 60.3M 11s\n", + "106400K .......... .......... .......... .......... .......... 17% 41.5M 11s\n", + "106450K .......... .......... .......... .......... .......... 17% 57.9M 11s\n", + "106500K .......... .......... .......... .......... .......... 17% 69.8M 11s\n", + "106550K .......... .......... .......... .......... .......... 17% 59.4M 11s\n", + "106600K .......... .......... .......... .......... .......... 17% 54.9M 11s\n", + "106650K .......... .......... .......... .......... .......... 17% 57.1M 11s\n", + "106700K .......... .......... .......... .......... .......... 17% 47.1M 11s\n", + "106750K .......... .......... .......... .......... .......... 17% 60.9M 11s\n", + "106800K .......... .......... .......... .......... .......... 17% 61.6M 11s\n", + "106850K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", + "106900K .......... .......... .......... .......... .......... 17% 49.9M 11s\n", + "106950K .......... .......... .......... .......... .......... 17% 48.3M 11s\n", + "107000K .......... .......... .......... .......... .......... 17% 46.6M 11s\n", + "107050K .......... .......... .......... .......... .......... 18% 72.3M 11s\n", + "107100K .......... .......... .......... .......... .......... 18% 72.1M 11s\n", + "107150K .......... .......... .......... .......... .......... 18% 60.3M 11s\n", + "107200K .......... .......... .......... .......... .......... 18% 47.6M 11s\n", + "107250K .......... .......... .......... .......... .......... 18% 57.4M 11s\n", + "107300K .......... .......... .......... .......... .......... 18% 69.7M 11s\n", + "107350K .......... .......... .......... .......... .......... 18% 71.7M 11s\n", + "107400K .......... .......... .......... .......... .......... 18% 44.7M 11s\n", + "107450K .......... .......... .......... .......... .......... 18% 52.4M 11s\n", + "107500K .......... .......... .......... .......... .......... 18% 50.8M 11s\n", + "107550K .......... .......... .......... .......... .......... 18% 67.7M 11s\n", + "107600K .......... .......... .......... .......... .......... 18% 57.7M 11s\n", + 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11s\n", + "108250K .......... .......... .......... .......... .......... 18% 60.9M 11s\n", + "108300K .......... .......... .......... .......... .......... 18% 62.1M 11s\n", + "108350K .......... .......... .......... .......... .......... 18% 71.0M 11s\n", + "108400K .......... .......... .......... .......... .......... 18% 64.4M 11s\n", + "108450K .......... .......... .......... .......... .......... 18% 58.3M 11s\n", + "108500K .......... .......... .......... .......... .......... 18% 53.3M 11s\n", + "108550K .......... .......... .......... .......... .......... 18% 54.7M 11s\n", + "108600K .......... .......... .......... .......... .......... 18% 48.5M 11s\n", + "108650K .......... .......... .......... .......... .......... 18% 64.3M 11s\n", + "108700K .......... .......... .......... .......... .......... 18% 64.2M 11s\n", + "108750K .......... .......... .......... .......... .......... 18% 47.7M 11s\n", + "108800K .......... .......... .......... .......... .......... 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.......... .......... .......... 18% 38.0M 11s\n", + "110650K .......... .......... .......... .......... .......... 18% 49.8M 11s\n", + "110700K .......... .......... .......... .......... .......... 18% 70.1M 11s\n", + "110750K .......... .......... .......... .......... .......... 18% 68.3M 11s\n", + "110800K .......... .......... .......... .......... .......... 18% 50.8M 11s\n", + "110850K .......... .......... .......... .......... .......... 18% 45.1M 11s\n", + "110900K .......... .......... .......... .......... .......... 18% 49.2M 11s\n", + "110950K .......... .......... .......... .......... .......... 18% 64.8M 11s\n", + "111000K .......... .......... .......... .......... .......... 18% 59.5M 11s\n", + "111050K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", + "111100K .......... .......... .......... .......... .......... 18% 51.2M 11s\n", + "111150K .......... .......... .......... .......... .......... 18% 54.3M 11s\n", + "111200K .......... .......... .......... .......... .......... 18% 51.6M 11s\n", + "111250K .......... .......... .......... .......... .......... 18% 65.7M 11s\n", + "111300K .......... .......... .......... .......... .......... 18% 72.4M 11s\n", + "111350K .......... .......... .......... .......... .......... 18% 56.8M 11s\n", + "111400K .......... .......... .......... .......... .......... 18% 39.3M 11s\n", + "111450K .......... .......... .......... .......... .......... 18% 59.5M 11s\n", + "111500K .......... .......... .......... .......... .......... 18% 68.9M 11s\n", + "111550K .......... .......... .......... .......... .......... 18% 64.9M 11s\n", + "111600K .......... .......... .......... .......... .......... 18% 45.6M 11s\n", + "111650K .......... .......... .......... .......... .......... 18% 55.9M 11s\n", + "111700K .......... .......... .......... .......... .......... 18% 56.8M 11s\n", + "111750K .......... .......... .......... .......... .......... 18% 65.6M 11s\n", + "111800K .......... .......... .......... .......... .......... 18% 59.7M 11s\n", + "111850K .......... .......... .......... .......... .......... 18% 50.3M 11s\n", + "111900K .......... .......... .......... .......... .......... 18% 48.5M 11s\n", + "111950K .......... .......... .......... .......... .......... 18% 70.7M 11s\n", + "112000K .......... .......... .......... .......... .......... 18% 63.1M 11s\n", + "112050K .......... .......... .......... .......... .......... 18% 67.6M 11s\n", + "112100K .......... .......... .......... .......... .......... 18% 3.89M 11s\n", + "112150K .......... .......... .......... .......... .......... 18% 65.7M 11s\n", + "112200K .......... .......... .......... .......... .......... 18% 53.6M 11s\n", + "112250K .......... .......... .......... .......... .......... 18% 67.8M 11s\n", + "112300K .......... .......... .......... .......... .......... 18% 67.6M 11s\n", + "112350K .......... .......... .......... .......... .......... 18% 71.6M 11s\n", + "112400K .......... .......... .......... .......... .......... 18% 58.5M 11s\n", + "112450K .......... .......... .......... .......... .......... 18% 53.6M 11s\n", + "112500K .......... .......... .......... .......... .......... 18% 48.9M 11s\n", + "112550K .......... .......... .......... .......... .......... 18% 64.8M 11s\n", + "112600K .......... .......... .......... .......... .......... 18% 55.2M 11s\n", + "112650K .......... .......... .......... .......... .......... 18% 66.3M 11s\n", + "112700K .......... .......... .......... .......... .......... 18% 49.2M 11s\n", + "112750K .......... .......... .......... .......... .......... 18% 50.2M 11s\n", + "112800K .......... .......... .......... .......... .......... 18% 56.2M 11s\n", + "112850K .......... .......... .......... .......... .......... 18% 68.1M 11s\n", + "112900K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", + "112950K .......... .......... .......... .......... .......... 19% 67.2M 11s\n", + "113000K .......... .......... .......... .......... .......... 19% 39.2M 11s\n", + "113050K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", + "113100K .......... .......... .......... .......... .......... 19% 69.5M 11s\n", + "113150K .......... .......... .......... .......... .......... 19% 63.1M 11s\n", + "113200K .......... .......... .......... .......... .......... 19% 51.8M 11s\n", + "113250K .......... .......... .......... .......... .......... 19% 53.0M 11s\n", + "113300K .......... .......... .......... .......... .......... 19% 45.8M 11s\n", + "113350K .......... .......... .......... .......... .......... 19% 66.8M 11s\n", + "113400K .......... .......... .......... .......... .......... 19% 53.4M 11s\n", + "113450K .......... .......... .......... .......... .......... 19% 60.1M 11s\n", + "113500K .......... .......... .......... .......... .......... 19% 51.7M 11s\n", + "113550K .......... .......... .......... .......... .......... 19% 49.0M 11s\n", + "113600K .......... .......... .......... .......... .......... 19% 57.8M 11s\n", + "113650K .......... .......... .......... .......... .......... 19% 69.4M 11s\n", + "113700K .......... .......... .......... .......... .......... 19% 67.4M 11s\n", + "113750K .......... .......... .......... .......... .......... 19% 71.3M 11s\n", + "113800K .......... .......... .......... .......... .......... 19% 53.3M 11s\n", + "113850K .......... .......... .......... .......... .......... 19% 52.8M 11s\n", + "113900K .......... .......... .......... .......... .......... 19% 71.3M 11s\n", + "113950K .......... .......... .......... .......... .......... 19% 72.4M 11s\n", + "114000K .......... .......... .......... .......... .......... 19% 56.5M 11s\n", + "114050K .......... .......... .......... .......... .......... 19% 65.0M 11s\n", + "114100K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", + "114150K .......... .......... .......... .......... 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.......... .......... .......... .......... .......... 19% 58.5M 11s\n", + "116600K .......... .......... .......... .......... .......... 19% 59.0M 11s\n", + "116650K .......... .......... .......... .......... .......... 19% 64.6M 11s\n", + "116700K .......... .......... .......... .......... .......... 19% 61.1M 11s\n", + "116750K .......... .......... .......... .......... .......... 19% 67.1M 11s\n", + "116800K .......... .......... .......... .......... .......... 19% 54.6M 11s\n", + "116850K .......... .......... .......... .......... .......... 19% 68.0M 11s\n", + "116900K .......... .......... .......... .......... .......... 19% 67.5M 11s\n", + "116950K .......... .......... .......... .......... .......... 19% 60.1M 11s\n", + "117000K .......... .......... .......... .......... .......... 19% 58.7M 11s\n", + "117050K .......... .......... .......... .......... .......... 19% 66.6M 11s\n", + "117100K .......... .......... .......... .......... .......... 19% 68.9M 11s\n", + 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11s\n", + "117750K .......... .......... .......... .......... .......... 19% 67.9M 11s\n", + "117800K .......... .......... .......... .......... .......... 19% 51.6M 11s\n", + "117850K .......... .......... .......... .......... .......... 19% 47.6M 11s\n", + "117900K .......... .......... .......... .......... .......... 19% 64.9M 11s\n", + "117950K .......... .......... .......... .......... .......... 19% 62.9M 11s\n", + "118000K .......... .......... .......... .......... .......... 19% 63.1M 11s\n", + "118050K .......... .......... .......... .......... .......... 19% 65.0M 11s\n", + "118100K .......... .......... .......... .......... .......... 19% 3.81M 11s\n", + "118150K .......... .......... .......... .......... .......... 19% 74.6M 11s\n", + "118200K .......... .......... .......... .......... .......... 19% 54.3M 11s\n", + "118250K .......... .......... .......... .......... .......... 19% 67.2M 11s\n", + "118300K .......... .......... .......... .......... .......... 19% 69.1M 11s\n", + "118350K .......... .......... .......... .......... .......... 19% 70.2M 11s\n", + "118400K .......... .......... .......... .......... .......... 19% 64.6M 11s\n", + "118450K .......... .......... .......... .......... .......... 19% 42.0M 11s\n", + "118500K .......... .......... .......... .......... .......... 19% 46.6M 11s\n", + "118550K .......... .......... .......... .......... .......... 19% 65.5M 11s\n", + "118600K .......... .......... .......... .......... .......... 19% 57.0M 11s\n", + "118650K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", + "118700K .......... .......... .......... .......... .......... 19% 43.8M 11s\n", + "118750K .......... .......... .......... .......... .......... 19% 43.2M 11s\n", + "118800K .......... .......... .......... .......... .......... 19% 60.0M 11s\n", + "118850K .......... .......... .......... .......... .......... 19% 60.6M 11s\n", + "118900K .......... .......... .......... .......... 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.......... .......... .......... .......... 20% 38.2M 11s\n", + "120750K .......... .......... .......... .......... .......... 20% 50.0M 11s\n", + "120800K .......... .......... .......... .......... .......... 20% 7.12M 11s\n", + "120850K .......... .......... .......... .......... .......... 20% 36.8M 11s\n", + "120900K .......... .......... .......... .......... .......... 20% 50.3M 11s\n", + "120950K .......... .......... .......... .......... .......... 20% 50.8M 11s\n", + "121000K .......... .......... .......... .......... .......... 20% 67.0M 11s\n", + "121050K .......... .......... .......... .......... .......... 20% 56.8M 11s\n", + "121100K .......... .......... .......... .......... .......... 20% 67.0M 11s\n", + "121150K .......... .......... .......... .......... .......... 20% 74.3M 11s\n", + "121200K .......... .......... .......... .......... .......... 20% 63.9M 11s\n", + "121250K .......... .......... .......... .......... .......... 20% 57.0M 11s\n", + "121300K .......... .......... .......... .......... .......... 20% 67.5M 11s\n", + "121350K .......... .......... .......... .......... .......... 20% 16.0M 11s\n", + "121400K .......... .......... .......... .......... .......... 20% 51.8M 11s\n", + "121450K .......... .......... .......... .......... .......... 20% 21.5M 11s\n", + "121500K .......... .......... .......... .......... .......... 20% 6.83M 11s\n", + "121550K .......... .......... .......... .......... .......... 20% 64.1M 11s\n", + "121600K .......... .......... .......... .......... .......... 20% 48.0M 11s\n", + "121650K .......... .......... .......... .......... .......... 20% 52.5M 11s\n", + "121700K .......... .......... .......... .......... .......... 20% 41.5M 11s\n", + "121750K .......... .......... .......... .......... .......... 20% 41.6M 11s\n", + "121800K .......... .......... .......... .......... .......... 20% 27.9M 11s\n", + "121850K .......... .......... .......... .......... .......... 20% 43.0M 11s\n", + "121900K .......... .......... .......... .......... .......... 20% 43.6M 11s\n", + "121950K .......... .......... .......... .......... .......... 20% 48.1M 11s\n", + "122000K .......... .......... .......... .......... .......... 20% 46.1M 11s\n", + "122050K .......... .......... .......... .......... .......... 20% 62.7M 11s\n", + "122100K .......... .......... .......... .......... .......... 20% 64.6M 11s\n", + "122150K .......... .......... .......... .......... .......... 20% 69.3M 11s\n", + "122200K .......... .......... .......... .......... .......... 20% 44.7M 11s\n", + "122250K .......... .......... .......... .......... .......... 20% 57.5M 11s\n", + "122300K .......... .......... .......... .......... .......... 20% 58.7M 11s\n", + "122350K .......... .......... .......... .......... .......... 20% 63.5M 11s\n", + "122400K .......... .......... .......... .......... .......... 20% 67.9M 11s\n", + "122450K .......... .......... .......... .......... .......... 20% 69.8M 11s\n", + "122500K .......... .......... .......... .......... .......... 20% 56.9M 11s\n", + "122550K .......... .......... .......... .......... .......... 20% 67.4M 11s\n", + "122600K .......... .......... .......... .......... .......... 20% 49.8M 11s\n", + "122650K .......... .......... .......... .......... .......... 20% 60.7M 11s\n", + "122700K .......... .......... .......... .......... .......... 20% 66.3M 11s\n", + "122750K .......... .......... .......... .......... .......... 20% 67.1M 11s\n", + "122800K .......... .......... .......... .......... .......... 20% 43.8M 11s\n", + "122850K .......... .......... .......... .......... .......... 20% 56.9M 11s\n", + "122900K .......... .......... .......... .......... .......... 20% 63.8M 11s\n", + "122950K .......... .......... .......... .......... .......... 20% 67.7M 11s\n", + "123000K .......... .......... .......... .......... .......... 20% 52.0M 11s\n", + "123050K .......... .......... .......... .......... .......... 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.......... .......... .......... .......... 21% 39.1M 11s\n", + "125500K .......... .......... .......... .......... .......... 21% 51.5M 11s\n", + "125550K .......... .......... .......... .......... .......... 21% 66.6M 11s\n", + "125600K .......... .......... .......... .......... .......... 21% 49.8M 11s\n", + "125650K .......... .......... .......... .......... .......... 21% 70.7M 11s\n", + "125700K .......... .......... .......... .......... .......... 21% 55.6M 11s\n", + "125750K .......... .......... .......... .......... .......... 21% 52.9M 11s\n", + "125800K .......... .......... .......... .......... .......... 21% 53.2M 11s\n", + "125850K .......... .......... .......... .......... .......... 21% 62.1M 11s\n", + "125900K .......... .......... .......... .......... .......... 21% 69.8M 11s\n", + "125950K .......... .......... .......... .......... .......... 21% 4.10M 11s\n", + "126000K .......... .......... .......... .......... .......... 21% 59.0M 11s\n", + "126050K .......... .......... .......... .......... .......... 21% 44.8M 11s\n", + "126100K .......... .......... .......... .......... .......... 21% 60.5M 11s\n", + "126150K .......... .......... .......... .......... .......... 21% 65.9M 11s\n", + "126200K .......... .......... .......... .......... .......... 21% 49.2M 11s\n", + "126250K .......... .......... .......... .......... .......... 21% 61.9M 11s\n", + "126300K .......... .......... .......... .......... .......... 21% 54.8M 11s\n", + "126350K .......... .......... .......... .......... .......... 21% 71.9M 11s\n", + "126400K .......... .......... .......... .......... .......... 21% 63.3M 11s\n", + "126450K .......... .......... .......... .......... .......... 21% 72.9M 11s\n", + "126500K .......... .......... .......... .......... .......... 21% 72.6M 11s\n", + "126550K .......... .......... .......... .......... .......... 21% 64.5M 11s\n", + "126600K .......... .......... .......... .......... .......... 21% 34.6M 11s\n", + 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11s\n", + "127250K .......... .......... .......... .......... .......... 21% 59.1M 11s\n", + "127300K .......... .......... .......... .......... .......... 21% 45.5M 11s\n", + "127350K .......... .......... .......... .......... .......... 21% 52.5M 11s\n", + "127400K .......... .......... .......... .......... .......... 21% 52.2M 11s\n", + "127450K .......... .......... .......... .......... .......... 21% 64.4M 11s\n", + "127500K .......... .......... .......... .......... .......... 21% 5.63M 11s\n", + "127550K .......... .......... .......... .......... .......... 21% 66.2M 11s\n", + "127600K .......... .......... .......... .......... .......... 21% 60.2M 11s\n", + "127650K .......... .......... .......... .......... .......... 21% 65.2M 11s\n", + "127700K .......... .......... .......... .......... .......... 21% 61.6M 11s\n", + "127750K .......... .......... .......... .......... .......... 21% 60.4M 11s\n", + "127800K .......... .......... .......... .......... .......... 21% 36.4M 11s\n", + "127850K .......... .......... .......... .......... .......... 21% 55.4M 11s\n", + "127900K .......... .......... .......... .......... .......... 21% 65.0M 11s\n", + "127950K .......... .......... .......... .......... .......... 21% 66.2M 11s\n", + "128000K .......... .......... .......... .......... .......... 21% 54.8M 11s\n", + "128050K .......... .......... .......... .......... .......... 21% 61.9M 11s\n", + "128100K .......... .......... .......... .......... .......... 21% 50.5M 11s\n", + "128150K .......... .......... .......... .......... .......... 21% 63.6M 11s\n", + "128200K .......... .......... .......... .......... .......... 21% 57.8M 11s\n", + "128250K .......... .......... .......... .......... .......... 21% 14.4M 11s\n", + "128300K .......... .......... .......... .......... .......... 21% 48.3M 11s\n", + "128350K .......... .......... .......... .......... .......... 21% 47.9M 11s\n", + "128400K .......... .......... .......... .......... 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.......... .......... 21% 27.8M 11s\n", + "129050K .......... .......... .......... .......... .......... 21% 65.7M 11s\n", + "129100K .......... .......... .......... .......... .......... 21% 55.8M 11s\n", + "129150K .......... .......... .......... .......... .......... 21% 22.9M 11s\n", + "129200K .......... .......... .......... .......... .......... 21% 4.02M 11s\n", + "129250K .......... .......... .......... .......... .......... 21% 60.9M 11s\n", + "129300K .......... .......... .......... .......... .......... 21% 59.3M 11s\n", + "129350K .......... .......... .......... .......... .......... 21% 54.7M 11s\n", + "129400K .......... .......... .......... .......... .......... 21% 16.3M 11s\n", + "129450K .......... .......... .......... .......... .......... 21% 3.93M 11s\n", + "129500K .......... .......... .......... .......... .......... 21% 53.3M 11s\n", + "129550K .......... .......... .......... .......... .......... 21% 54.5M 11s\n", + "129600K .......... .......... .......... .......... .......... 21% 59.4M 11s\n", + "129650K .......... .......... .......... .......... .......... 21% 28.7M 11s\n", + "129700K .......... .......... .......... .......... .......... 21% 30.4M 11s\n", + "129750K .......... .......... .......... .......... .......... 21% 48.2M 11s\n", + "129800K .......... .......... .......... .......... .......... 21% 38.5M 11s\n", + "129850K .......... .......... .......... .......... .......... 21% 51.6M 11s\n", + "129900K .......... .......... .......... .......... .......... 21% 37.8M 11s\n", + "129950K .......... .......... .......... .......... .......... 21% 64.0M 11s\n", + "130000K .......... .......... .......... .......... .......... 21% 51.7M 11s\n", + "130050K .......... .......... .......... .......... .......... 21% 46.0M 11s\n", + "130100K .......... .......... .......... .......... .......... 21% 42.3M 11s\n", + "130150K .......... .......... .......... .......... .......... 21% 45.0M 11s\n", + "130200K .......... .......... .......... .......... .......... 21% 50.5M 11s\n", + "130250K .......... .......... .......... .......... .......... 21% 56.7M 11s\n", + "130300K .......... .......... .......... .......... .......... 21% 39.8M 11s\n", + "130350K .......... .......... .......... .......... .......... 21% 26.1M 11s\n", + "130400K .......... .......... .......... .......... .......... 21% 37.6M 11s\n", + "130450K .......... .......... .......... .......... .......... 21% 30.1M 11s\n", + "130500K .......... .......... .......... .......... .......... 21% 25.4M 11s\n", + "130550K .......... .......... .......... .......... .......... 21% 43.0M 11s\n", + "130600K .......... .......... .......... .......... .......... 21% 38.8M 11s\n", + "130650K .......... .......... .......... .......... .......... 21% 48.0M 11s\n", + "130700K .......... .......... .......... .......... .......... 21% 36.9M 11s\n", + "130750K .......... .......... .......... .......... .......... 21% 45.7M 11s\n", + "130800K .......... .......... .......... .......... .......... 22% 60.7M 11s\n", + "130850K .......... .......... .......... .......... .......... 22% 45.8M 11s\n", + "130900K .......... .......... .......... .......... .......... 22% 42.9M 11s\n", + "130950K .......... .......... .......... .......... .......... 22% 51.3M 11s\n", + "131000K .......... .......... .......... .......... .......... 22% 27.0M 11s\n", + "131050K .......... .......... .......... .......... .......... 22% 42.0M 11s\n", + "131100K .......... .......... .......... .......... .......... 22% 47.5M 11s\n", + "131150K .......... .......... .......... .......... .......... 22% 65.0M 11s\n", + "131200K .......... .......... .......... .......... .......... 22% 23.4M 11s\n", + "131250K .......... .......... .......... .......... .......... 22% 42.1M 11s\n", + "131300K .......... .......... .......... .......... .......... 22% 59.7M 11s\n", + "131350K .......... .......... .......... .......... .......... 22% 52.6M 11s\n", + 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11s\n", + "132000K .......... .......... .......... .......... .......... 22% 31.8M 11s\n", + "132050K .......... .......... .......... .......... .......... 22% 70.4M 11s\n", + "132100K .......... .......... .......... .......... .......... 22% 23.6M 11s\n", + "132150K .......... .......... .......... .......... .......... 22% 42.2M 11s\n", + "132200K .......... .......... .......... .......... .......... 22% 44.8M 11s\n", + "132250K .......... .......... .......... .......... .......... 22% 38.3M 11s\n", + "132300K .......... .......... .......... .......... .......... 22% 26.9M 11s\n", + "132350K .......... .......... .......... .......... .......... 22% 41.9M 11s\n", + "132400K .......... .......... .......... .......... .......... 22% 62.6M 11s\n", + "132450K .......... .......... .......... .......... .......... 22% 22.6M 11s\n", + "132500K .......... .......... .......... .......... .......... 22% 40.5M 11s\n", + "132550K .......... .......... .......... .......... .......... 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.......... .......... .......... .......... .......... 22% 5.52M 11s\n", + "135600K .......... .......... .......... .......... .......... 22% 61.3M 11s\n", + "135650K .......... .......... .......... .......... .......... 22% 63.9M 11s\n", + "135700K .......... .......... .......... .......... .......... 22% 67.5M 11s\n", + "135750K .......... .......... .......... .......... .......... 22% 68.9M 11s\n", + "135800K .......... .......... .......... .......... .......... 22% 17.0M 11s\n", + "135850K .......... .......... .......... .......... .......... 22% 61.4M 11s\n", + "135900K .......... .......... .......... .......... .......... 22% 65.7M 11s\n", + "135950K .......... .......... .......... .......... .......... 22% 21.2M 11s\n", + "136000K .......... .......... .......... .......... .......... 22% 47.9M 11s\n", + "136050K .......... .......... .......... .......... .......... 22% 58.4M 11s\n", + "136100K .......... .......... .......... .......... .......... 22% 69.7M 11s\n", + 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11s\n", + "136750K .......... .......... .......... .......... .......... 23% 57.7M 11s\n", + "136800K .......... .......... .......... .......... .......... 23% 45.2M 11s\n", + "136850K .......... .......... .......... .......... .......... 23% 64.2M 11s\n", + "136900K .......... .......... .......... .......... .......... 23% 66.2M 11s\n", + "136950K .......... .......... .......... .......... .......... 23% 29.1M 11s\n", + "137000K .......... .......... .......... .......... .......... 23% 40.0M 11s\n", + "137050K .......... .......... .......... .......... .......... 23% 64.0M 11s\n", + "137100K .......... .......... .......... .......... .......... 23% 66.4M 11s\n", + "137150K .......... .......... .......... .......... .......... 23% 30.5M 11s\n", + "137200K .......... .......... .......... .......... .......... 23% 40.3M 11s\n", + "137250K .......... .......... .......... .......... .......... 23% 52.5M 11s\n", + "137300K .......... .......... .......... .......... .......... 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.......... .......... 23% 52.0M 10s\n", + "138550K .......... .......... .......... .......... .......... 23% 71.0M 10s\n", + "138600K .......... .......... .......... .......... .......... 23% 25.0M 10s\n", + "138650K .......... .......... .......... .......... .......... 23% 51.2M 10s\n", + "138700K .......... .......... .......... .......... .......... 23% 53.4M 10s\n", + "138750K .......... .......... .......... .......... .......... 23% 71.5M 10s\n", + "138800K .......... .......... .......... .......... .......... 23% 27.9M 10s\n", + "138850K .......... .......... .......... .......... .......... 23% 38.4M 10s\n", + "138900K .......... .......... .......... .......... .......... 23% 54.3M 10s\n", + "138950K .......... .......... .......... .......... .......... 23% 68.6M 10s\n", + "139000K .......... .......... .......... .......... .......... 23% 32.6M 10s\n", + "139050K .......... .......... .......... .......... .......... 23% 54.1M 10s\n", + "139100K .......... .......... .......... .......... .......... 23% 57.0M 10s\n", + "139150K .......... .......... .......... .......... .......... 23% 65.1M 10s\n", + "139200K .......... .......... .......... .......... .......... 23% 4.65M 10s\n", + "139250K .......... .......... .......... .......... .......... 23% 54.3M 10s\n", + "139300K .......... .......... .......... .......... .......... 23% 67.4M 10s\n", + "139350K .......... .......... .......... .......... .......... 23% 68.5M 10s\n", + "139400K .......... .......... .......... .......... .......... 23% 22.1M 10s\n", + "139450K .......... .......... .......... .......... .......... 23% 49.0M 10s\n", + "139500K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", + "139550K .......... .......... .......... .......... .......... 23% 71.7M 10s\n", + "139600K .......... .......... .......... .......... .......... 23% 32.8M 10s\n", + "139650K .......... .......... .......... .......... .......... 23% 51.9M 10s\n", + "139700K .......... .......... .......... .......... .......... 23% 50.2M 10s\n", + "139750K .......... .......... .......... .......... .......... 23% 66.2M 10s\n", + "139800K .......... .......... .......... .......... .......... 23% 27.2M 10s\n", + "139850K .......... .......... .......... .......... .......... 23% 59.7M 10s\n", + "139900K .......... .......... .......... .......... .......... 23% 53.9M 10s\n", + "139950K .......... .......... .......... .......... .......... 23% 63.2M 10s\n", + "140000K .......... .......... .......... .......... .......... 23% 61.8M 10s\n", + "140050K .......... .......... .......... .......... .......... 23% 23.7M 10s\n", + "140100K .......... .......... .......... .......... .......... 23% 53.4M 10s\n", + "140150K .......... .......... .......... .......... .......... 23% 62.0M 10s\n", + "140200K .......... .......... .......... .......... .......... 23% 57.9M 10s\n", + "140250K .......... .......... .......... .......... .......... 23% 29.7M 10s\n", + "140300K .......... .......... .......... .......... .......... 23% 49.5M 10s\n", + "140350K .......... .......... .......... .......... .......... 23% 49.8M 10s\n", + "140400K .......... .......... .......... .......... .......... 23% 63.5M 10s\n", + "140450K .......... .......... .......... .......... .......... 23% 43.2M 10s\n", + "140500K .......... .......... .......... .......... .......... 23% 35.1M 10s\n", + "140550K .......... .......... .......... .......... .......... 23% 47.2M 10s\n", + "140600K .......... .......... .......... .......... .......... 23% 51.0M 10s\n", + "140650K .......... .......... .......... .......... .......... 23% 61.5M 10s\n", + "140700K .......... .......... .......... .......... .......... 23% 36.2M 10s\n", + "140750K .......... .......... .......... .......... .......... 23% 53.1M 10s\n", + "140800K .......... .......... .......... .......... .......... 23% 47.1M 10s\n", + "140850K .......... .......... .......... .......... .......... 23% 67.1M 10s\n", + "140900K .......... .......... .......... .......... .......... 23% 67.2M 10s\n", + "140950K .......... .......... .......... .......... .......... 23% 30.3M 10s\n", + "141000K .......... .......... .......... .......... .......... 23% 51.0M 10s\n", + "141050K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", + "141100K .......... .......... .......... .......... .......... 23% 42.2M 10s\n", + "141150K .......... .......... .......... .......... .......... 23% 30.6M 10s\n", + "141200K .......... .......... .......... .......... .......... 23% 46.7M 10s\n", + "141250K .......... .......... .......... .......... .......... 23% 59.6M 10s\n", + "141300K .......... .......... .......... .......... .......... 23% 71.0M 10s\n", + "141350K .......... .......... .......... .......... .......... 23% 35.7M 10s\n", + "141400K .......... .......... .......... .......... .......... 23% 46.7M 10s\n", + "141450K .......... .......... .......... .......... .......... 23% 57.0M 10s\n", + "141500K .......... .......... .......... .......... .......... 23% 59.8M 10s\n", + "141550K .......... .......... .......... .......... .......... 23% 61.2M 10s\n", + "141600K .......... .......... .......... .......... .......... 23% 4.27M 10s\n", + "141650K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", + "141700K .......... .......... .......... .......... .......... 23% 65.0M 10s\n", + "141750K .......... .......... .......... .......... .......... 23% 63.7M 10s\n", + "141800K .......... .......... .......... .......... .......... 23% 56.1M 10s\n", + "141850K .......... .......... .......... .......... .......... 23% 20.1M 10s\n", + "141900K .......... .......... .......... .......... .......... 23% 49.8M 10s\n", + "141950K .......... .......... .......... .......... .......... 23% 64.3M 10s\n", + "142000K .......... .......... .......... .......... .......... 23% 64.9M 10s\n", + "142050K .......... .......... .......... .......... .......... 23% 33.3M 10s\n", + "142100K .......... .......... .......... .......... .......... 23% 56.5M 10s\n", + "142150K .......... .......... .......... .......... .......... 23% 54.8M 10s\n", + "142200K .......... .......... .......... .......... .......... 23% 58.0M 10s\n", + "142250K .......... .......... .......... .......... .......... 23% 68.6M 10s\n", + "142300K .......... .......... .......... .......... .......... 23% 30.5M 10s\n", + "142350K .......... .......... .......... .......... .......... 23% 54.4M 10s\n", + "142400K .......... .......... .......... .......... .......... 23% 47.7M 10s\n", + "142450K .......... .......... .......... .......... .......... 23% 67.8M 10s\n", + "142500K .......... .......... .......... .......... .......... 23% 32.3M 10s\n", + "142550K .......... .......... .......... .......... .......... 23% 46.6M 10s\n", + "142600K .......... .......... .......... .......... .......... 23% 43.3M 10s\n", + "142650K .......... .......... .......... .......... .......... 23% 66.8M 10s\n", + "142700K .......... .......... .......... .......... .......... 24% 66.0M 10s\n", + "142750K .......... .......... .......... .......... .......... 24% 34.8M 10s\n", + "142800K .......... .......... .......... .......... .......... 24% 41.3M 10s\n", + "142850K .......... .......... .......... .......... .......... 24% 55.5M 10s\n", + "142900K .......... .......... .......... .......... .......... 24% 68.0M 10s\n", + "142950K .......... .......... .......... .......... .......... 24% 37.0M 10s\n", + "143000K .......... .......... .......... .......... .......... 24% 40.0M 10s\n", + "143050K .......... .......... .......... .......... .......... 24% 47.0M 10s\n", + "143100K .......... .......... .......... .......... .......... 24% 70.7M 10s\n", + "143150K .......... .......... .......... .......... .......... 24% 66.9M 10s\n", + "143200K .......... .......... .......... .......... .......... 24% 32.8M 10s\n", + "143250K .......... .......... .......... .......... .......... 24% 8.78M 10s\n", + "143300K .......... .......... .......... .......... .......... 24% 68.6M 10s\n", + "143350K .......... .......... .......... .......... .......... 24% 69.1M 10s\n", + "143400K .......... .......... .......... .......... .......... 24% 62.0M 10s\n", + "143450K .......... .......... .......... .......... .......... 24% 66.7M 10s\n", + "143500K .......... .......... .......... .......... .......... 24% 67.6M 10s\n", + "143550K .......... .......... .......... .......... .......... 24% 28.0M 10s\n", + "143600K .......... .......... .......... .......... .......... 24% 44.9M 10s\n", + "143650K .......... .......... .......... .......... .......... 24% 70.6M 10s\n", + "143700K .......... .......... .......... .......... .......... 24% 69.9M 10s\n", + "143750K .......... .......... .......... .......... .......... 24% 29.3M 10s\n", + "143800K .......... .......... .......... .......... .......... 24% 45.7M 10s\n", + "143850K .......... .......... .......... .......... .......... 24% 53.6M 10s\n", + "143900K .......... .......... .......... .......... .......... 24% 71.8M 10s\n", + "143950K .......... .......... .......... .......... .......... 24% 63.6M 10s\n", + "144000K .......... .......... .......... .......... .......... 24% 34.6M 10s\n", + "144050K .......... .......... .......... .......... .......... 24% 54.6M 10s\n", + "144100K .......... .......... .......... .......... .......... 24% 51.3M 10s\n", + "144150K .......... .......... .......... .......... .......... 24% 14.4M 10s\n", + "144200K .......... .......... .......... .......... .......... 24% 39.5M 10s\n", + "144250K .......... .......... .......... .......... .......... 24% 67.9M 10s\n", + "144300K .......... .......... .......... .......... .......... 24% 69.2M 10s\n", + "144350K .......... .......... .......... .......... .......... 24% 65.5M 10s\n", + "144400K .......... .......... .......... .......... .......... 24% 63.1M 10s\n", + "144450K .......... .......... .......... .......... .......... 24% 49.5M 10s\n", + "144500K .......... .......... .......... .......... .......... 24% 50.4M 10s\n", + "144550K .......... .......... .......... .......... .......... 24% 58.5M 10s\n", + "144600K .......... .......... .......... .......... .......... 24% 53.4M 10s\n", + "144650K .......... .......... .......... .......... .......... 24% 69.2M 10s\n", + "144700K .......... .......... .......... .......... .......... 24% 56.2M 10s\n", + "144750K .......... .......... .......... .......... .......... 24% 65.7M 10s\n", + "144800K .......... .......... .......... .......... .......... 24% 49.7M 10s\n", + "144850K .......... .......... .......... .......... .......... 24% 66.2M 10s\n", + "144900K .......... .......... .......... .......... .......... 24% 71.1M 10s\n", + "144950K .......... .......... .......... .......... .......... 24% 32.2M 10s\n", + "145000K .......... .......... .......... .......... .......... 24% 53.6M 10s\n", + "145050K .......... .......... .......... .......... .......... 24% 68.1M 10s\n", + "145100K .......... .......... .......... .......... .......... 24% 70.5M 10s\n", + "145150K .......... .......... .......... .......... .......... 24% 31.9M 10s\n", + "145200K .......... .......... .......... .......... .......... 24% 42.7M 10s\n", + "145250K .......... .......... .......... .......... .......... 24% 51.1M 10s\n", + "145300K .......... .......... .......... .......... .......... 24% 55.0M 10s\n", + "145350K .......... .......... .......... .......... .......... 24% 62.1M 10s\n", + "145400K .......... .......... .......... .......... .......... 24% 32.4M 10s\n", + "145450K .......... .......... .......... .......... .......... 24% 56.7M 10s\n", + "145500K .......... .......... .......... .......... .......... 24% 54.6M 10s\n", + "145550K .......... .......... .......... .......... .......... 24% 66.4M 10s\n", + "145600K .......... .......... .......... .......... .......... 24% 3.91M 10s\n", + "145650K .......... .......... .......... .......... .......... 24% 64.4M 10s\n", + "145700K .......... .......... .......... .......... .......... 24% 72.9M 10s\n", + "145750K .......... .......... .......... .......... .......... 24% 62.9M 10s\n", + "145800K .......... .......... .......... .......... .......... 24% 60.5M 10s\n", + "145850K .......... .......... .......... .......... .......... 24% 67.6M 10s\n", + "145900K .......... .......... .......... .......... .......... 24% 6.18M 10s\n", + "145950K .......... .......... .......... .......... .......... 24% 68.8M 10s\n", + "146000K .......... .......... .......... .......... .......... 24% 57.0M 10s\n", + "146050K .......... .......... .......... .......... .......... 24% 61.1M 10s\n", + "146100K .......... .......... .......... .......... .......... 24% 59.5M 10s\n", + "146150K .......... .......... .......... .......... .......... 24% 68.2M 10s\n", + "146200K .......... .......... .......... .......... .......... 24% 43.7M 10s\n", + "146250K .......... .......... .......... .......... .......... 24% 64.2M 10s\n", + "146300K .......... .......... .......... .......... .......... 24% 59.6M 10s\n", + "146350K .......... .......... .......... .......... .......... 24% 60.9M 10s\n", + "146400K .......... .......... .......... .......... .......... 24% 54.5M 10s\n", + "146450K .......... .......... .......... .......... .......... 24% 56.2M 10s\n", + "146500K .......... .......... .......... .......... .......... 24% 51.4M 10s\n", + "146550K .......... .......... .......... .......... .......... 24% 8.49M 10s\n", + "146600K .......... .......... .......... .......... .......... 24% 44.9M 10s\n", + "146650K .......... .......... .......... .......... .......... 24% 62.3M 10s\n", + "146700K .......... .......... .......... .......... .......... 24% 54.0M 10s\n", + "146750K .......... .......... .......... .......... .......... 24% 57.7M 10s\n", + "146800K .......... .......... .......... .......... .......... 24% 55.7M 10s\n", + "146850K .......... .......... .......... .......... .......... 24% 52.3M 10s\n", + "146900K .......... .......... .......... .......... .......... 24% 55.6M 10s\n", + "146950K .......... .......... .......... .......... .......... 24% 54.0M 10s\n", + "147000K .......... .......... .......... .......... .......... 24% 43.1M 10s\n", + "147050K .......... .......... .......... .......... .......... 24% 63.5M 10s\n", + "147100K .......... .......... .......... .......... .......... 24% 58.5M 10s\n", + "147150K .......... .......... .......... .......... .......... 24% 57.4M 10s\n", + "147200K .......... .......... .......... .......... .......... 24% 40.8M 10s\n", + "147250K .......... .......... .......... .......... .......... 24% 54.7M 10s\n", + "147300K .......... .......... .......... .......... .......... 24% 4.90M 10s\n", + "147350K .......... .......... .......... .......... .......... 24% 62.1M 10s\n", + "147400K .......... .......... .......... .......... 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.......... .......... 24% 53.0M 10s\n", + "148050K .......... .......... .......... .......... .......... 24% 61.8M 10s\n", + "148100K .......... .......... .......... .......... .......... 24% 69.1M 10s\n", + "148150K .......... .......... .......... .......... .......... 24% 68.0M 10s\n", + "148200K .......... .......... .......... .......... .......... 24% 57.3M 10s\n", + "148250K .......... .......... .......... .......... .......... 24% 62.2M 10s\n", + "148300K .......... .......... .......... .......... .......... 24% 60.5M 10s\n", + "148350K .......... .......... .......... .......... .......... 24% 60.5M 10s\n", + "148400K .......... .......... .......... .......... .......... 24% 60.7M 10s\n", + "148450K .......... .......... .......... .......... .......... 24% 68.6M 10s\n", + "148500K .......... .......... .......... .......... .......... 24% 69.3M 10s\n", + "148550K .......... .......... .......... .......... .......... 24% 48.9M 10s\n", + "148600K .......... .......... .......... .......... .......... 24% 25.5M 10s\n", + "148650K .......... .......... .......... .......... .......... 25% 35.4M 10s\n", + "148700K .......... .......... .......... .......... .......... 25% 38.4M 10s\n", + "148750K .......... .......... .......... .......... .......... 25% 33.5M 10s\n", + "148800K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", + "148850K .......... .......... .......... .......... .......... 25% 43.1M 10s\n", + "148900K .......... .......... .......... .......... .......... 25% 69.0M 10s\n", + "148950K .......... .......... .......... .......... .......... 25% 50.3M 10s\n", + "149000K .......... .......... .......... .......... .......... 25% 47.9M 10s\n", + "149050K .......... .......... .......... .......... .......... 25% 18.1M 10s\n", + "149100K .......... .......... .......... .......... .......... 25% 32.1M 10s\n", + "149150K .......... .......... .......... .......... .......... 25% 14.9M 10s\n", + "149200K .......... .......... .......... .......... .......... 25% 45.1M 10s\n", + "149250K .......... .......... .......... .......... .......... 25% 53.7M 10s\n", + "149300K .......... .......... .......... .......... .......... 25% 17.2M 10s\n", + "149350K .......... .......... .......... .......... .......... 25% 48.8M 10s\n", + "149400K .......... .......... .......... .......... .......... 25% 14.6M 10s\n", + "149450K .......... .......... .......... .......... .......... 25% 31.5M 10s\n", + "149500K .......... .......... .......... .......... .......... 25% 37.7M 10s\n", + "149550K .......... .......... .......... .......... .......... 25% 21.0M 10s\n", + "149600K .......... .......... .......... .......... .......... 25% 29.0M 10s\n", + "149650K .......... .......... .......... .......... .......... 25% 20.9M 10s\n", + "149700K .......... .......... .......... .......... .......... 25% 37.3M 10s\n", + "149750K .......... .......... .......... .......... .......... 25% 55.9M 10s\n", + "149800K .......... .......... .......... .......... .......... 25% 14.1M 10s\n", + "149850K .......... .......... .......... .......... .......... 25% 46.2M 10s\n", + "149900K .......... .......... .......... .......... .......... 25% 21.8M 10s\n", + "149950K .......... .......... .......... .......... .......... 25% 32.8M 10s\n", + "150000K .......... .......... .......... .......... .......... 25% 29.5M 10s\n", + "150050K .......... .......... .......... .......... .......... 25% 19.9M 10s\n", + "150100K .......... .......... .......... .......... .......... 25% 40.4M 10s\n", + "150150K .......... .......... .......... .......... .......... 25% 23.5M 10s\n", + "150200K .......... .......... .......... .......... .......... 25% 22.2M 10s\n", + "150250K .......... .......... .......... .......... .......... 25% 24.9M 10s\n", + "150300K .......... .......... .......... .......... .......... 25% 29.7M 10s\n", + "150350K .......... .......... .......... .......... .......... 25% 42.5M 10s\n", + "150400K .......... .......... .......... .......... .......... 25% 18.0M 10s\n", + "150450K .......... .......... .......... .......... .......... 25% 42.3M 10s\n", + "150500K .......... .......... .......... .......... .......... 25% 25.5M 10s\n", + "150550K .......... .......... .......... .......... .......... 25% 20.6M 10s\n", + "150600K .......... .......... .......... .......... .......... 25% 37.2M 10s\n", + "150650K .......... .......... .......... .......... .......... 25% 19.0M 10s\n", + "150700K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", + "150750K .......... .......... .......... .......... .......... 25% 31.3M 10s\n", + "150800K .......... .......... .......... .......... .......... 25% 24.5M 10s\n", + "150850K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", + "150900K .......... .......... .......... .......... .......... 25% 3.65M 10s\n", + "150950K .......... .......... .......... .......... .......... 25% 62.9M 10s\n", + "151000K .......... .......... .......... .......... .......... 25% 54.8M 10s\n", + "151050K .......... .......... .......... .......... .......... 25% 56.6M 10s\n", + "151100K .......... .......... .......... .......... .......... 25% 56.8M 10s\n", + "151150K .......... .......... .......... .......... .......... 25% 67.9M 10s\n", + "151200K .......... .......... .......... .......... .......... 25% 62.6M 10s\n", + "151250K .......... .......... .......... .......... .......... 25% 72.6M 10s\n", + "151300K .......... .......... .......... .......... .......... 25% 65.7M 10s\n", + "151350K .......... .......... .......... .......... .......... 25% 68.7M 10s\n", + "151400K .......... .......... .......... .......... .......... 25% 49.8M 10s\n", + "151450K .......... .......... .......... .......... .......... 25% 16.6M 10s\n", + "151500K .......... .......... .......... .......... .......... 25% 58.0M 10s\n", + "151550K .......... .......... .......... .......... .......... 25% 49.8M 10s\n", + "151600K .......... .......... .......... .......... .......... 25% 4.33M 10s\n", + "151650K .......... .......... .......... .......... .......... 25% 53.9M 10s\n", + "151700K .......... .......... .......... .......... .......... 25% 67.4M 10s\n", + "151750K .......... .......... .......... .......... .......... 25% 12.9M 10s\n", + "151800K .......... .......... .......... .......... .......... 25% 55.1M 10s\n", + "151850K .......... .......... .......... .......... .......... 25% 15.0M 10s\n", + "151900K .......... .......... .......... .......... .......... 25% 54.6M 10s\n", + "151950K .......... .......... .......... .......... .......... 25% 18.6M 10s\n", + "152000K .......... .......... .......... .......... .......... 25% 37.7M 10s\n", + "152050K .......... .......... .......... .......... .......... 25% 44.8M 10s\n", + "152100K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", + "152150K .......... .......... .......... .......... .......... 25% 36.6M 10s\n", + "152200K .......... .......... .......... .......... .......... 25% 18.0M 10s\n", + "152250K .......... .......... .......... .......... .......... 25% 39.5M 10s\n", + "152300K .......... .......... .......... .......... .......... 25% 42.0M 10s\n", + "152350K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", + "152400K .......... .......... .......... .......... .......... 25% 29.9M 10s\n", + "152450K .......... .......... .......... .......... .......... 25% 65.0M 10s\n", + "152500K .......... .......... .......... .......... .......... 25% 18.4M 10s\n", + "152550K .......... .......... .......... .......... .......... 25% 35.0M 10s\n", + "152600K .......... .......... .......... .......... .......... 25% 20.3M 10s\n", + "152650K .......... .......... .......... .......... .......... 25% 60.8M 10s\n", + "152700K .......... .......... .......... .......... .......... 25% 32.7M 10s\n", + "152750K .......... .......... .......... .......... .......... 25% 22.6M 10s\n", + "152800K .......... .......... .......... .......... .......... 25% 25.7M 10s\n", + "152850K .......... .......... .......... .......... .......... 25% 58.4M 10s\n", + "152900K .......... .......... .......... .......... .......... 25% 21.0M 10s\n", + "152950K .......... .......... .......... .......... .......... 25% 31.0M 10s\n", + "153000K .......... .......... .......... .......... .......... 25% 7.67M 10s\n", + "153050K .......... .......... .......... .......... .......... 25% 51.8M 10s\n", + "153100K .......... .......... .......... .......... .......... 25% 69.5M 10s\n", + "153150K .......... .......... .......... .......... .......... 25% 59.7M 10s\n", + "153200K .......... .......... .......... .......... .......... 25% 55.8M 10s\n", + "153250K .......... .......... .......... .......... .......... 25% 70.8M 10s\n", + "153300K .......... .......... .......... .......... .......... 25% 35.5M 10s\n", + "153350K .......... .......... .......... .......... .......... 25% 28.8M 10s\n", + "153400K .......... .......... .......... .......... .......... 25% 21.1M 10s\n", + "153450K .......... .......... .......... .......... .......... 25% 68.2M 10s\n", + "153500K .......... .......... .......... .......... .......... 25% 29.8M 10s\n", + "153550K .......... .......... .......... .......... .......... 25% 23.2M 10s\n", + "153600K .......... .......... .......... .......... .......... 25% 29.5M 10s\n", + "153650K .......... .......... .......... .......... .......... 25% 50.7M 10s\n", + "153700K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", + "153750K .......... .......... .......... .......... .......... 25% 38.1M 10s\n", + "153800K .......... .......... .......... .......... .......... 25% 20.2M 10s\n", + "153850K .......... .......... .......... .......... .......... 25% 45.6M 10s\n", + "153900K .......... .......... .......... .......... .......... 25% 43.1M 10s\n", + "153950K .......... .......... .......... .......... .......... 25% 21.5M 10s\n", + "154000K .......... .......... .......... .......... .......... 25% 41.6M 10s\n", + "154050K .......... .......... .......... .......... .......... 25% 42.0M 10s\n", + "154100K .......... .......... .......... .......... .......... 25% 17.6M 10s\n", + "154150K .......... .......... .......... .......... .......... 25% 53.0M 10s\n", + "154200K .......... .......... .......... .......... .......... 25% 42.7M 10s\n", + "154250K .......... .......... .......... .......... .......... 25% 8.29M 10s\n", + "154300K .......... .......... .......... .......... .......... 25% 62.4M 10s\n", + "154350K .......... .......... .......... .......... .......... 25% 65.2M 10s\n", + "154400K .......... .......... .......... .......... .......... 25% 15.1M 10s\n", + "154450K .......... .......... .......... .......... .......... 25% 60.6M 10s\n", + "154500K .......... .......... .......... .......... .......... 25% 65.7M 10s\n", + "154550K .......... .......... .......... .......... .......... 25% 15.7M 10s\n", + "154600K .......... .......... .......... .......... .......... 26% 45.9M 10s\n", + "154650K .......... .......... .......... .......... .......... 26% 68.6M 10s\n", + "154700K .......... .......... .......... .......... .......... 26% 17.8M 10s\n", + "154750K .......... .......... .......... .......... .......... 26% 33.4M 10s\n", + "154800K .......... .......... .......... .......... .......... 26% 37.1M 10s\n", + "154850K .......... .......... .......... .......... .......... 26% 26.8M 10s\n", + "154900K .......... .......... .......... .......... .......... 26% 38.7M 10s\n", + "154950K .......... .......... .......... .......... .......... 26% 59.8M 10s\n", + "155000K .......... .......... .......... .......... .......... 26% 16.8M 10s\n", + "155050K .......... .......... .......... .......... .......... 26% 52.4M 10s\n", + "155100K .......... .......... .......... .......... .......... 26% 20.9M 10s\n", + 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10s\n", + "155750K .......... .......... .......... .......... .......... 26% 41.6M 10s\n", + "155800K .......... .......... .......... .......... .......... 26% 30.4M 10s\n", + "155850K .......... .......... .......... .......... .......... 26% 26.5M 10s\n", + "155900K .......... .......... .......... .......... .......... 26% 24.3M 10s\n", + "155950K .......... .......... .......... .......... .......... 26% 62.5M 10s\n", + "156000K .......... .......... .......... .......... .......... 26% 22.4M 10s\n", + "156050K .......... .......... .......... .......... .......... 26% 50.0M 10s\n", + "156100K .......... .......... .......... .......... .......... 26% 33.4M 10s\n", + "156150K .......... .......... .......... .......... .......... 26% 30.9M 10s\n", + "156200K .......... .......... .......... .......... .......... 26% 22.9M 10s\n", + "156250K .......... .......... .......... .......... .......... 26% 54.5M 10s\n", + "156300K .......... .......... .......... .......... .......... 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.......... .......... .......... .......... 26% 22.4M 10s\n", + "158750K .......... .......... .......... .......... .......... 26% 44.0M 10s\n", + "158800K .......... .......... .......... .......... .......... 26% 50.1M 10s\n", + "158850K .......... .......... .......... .......... .......... 26% 70.8M 10s\n", + "158900K .......... .......... .......... .......... .......... 26% 16.0M 10s\n", + "158950K .......... .......... .......... .......... .......... 26% 52.6M 10s\n", + "159000K .......... .......... .......... .......... .......... 26% 58.2M 10s\n", + "159050K .......... .......... .......... .......... .......... 26% 18.5M 10s\n", + "159100K .......... .......... .......... .......... .......... 26% 43.9M 10s\n", + "159150K .......... .......... .......... .......... .......... 26% 65.9M 10s\n", + "159200K .......... .......... .......... .......... .......... 26% 24.5M 10s\n", + "159250K .......... .......... .......... .......... .......... 26% 39.5M 10s\n", + "159300K .......... .......... .......... .......... .......... 26% 54.7M 10s\n", + "159350K .......... .......... .......... .......... .......... 26% 65.8M 10s\n", + "159400K .......... .......... .......... .......... .......... 26% 16.8M 10s\n", + "159450K .......... .......... .......... .......... .......... 26% 51.5M 10s\n", + "159500K .......... .......... .......... .......... .......... 26% 66.8M 10s\n", + "159550K .......... .......... .......... .......... .......... 26% 25.0M 10s\n", + "159600K .......... .......... .......... .......... .......... 26% 37.0M 10s\n", + "159650K .......... .......... .......... .......... .......... 26% 61.3M 10s\n", + "159700K .......... .......... .......... .......... .......... 26% 23.5M 10s\n", + "159750K .......... .......... .......... .......... .......... 26% 37.8M 10s\n", + "159800K .......... .......... .......... .......... .......... 26% 38.8M 10s\n", + "159850K .......... .......... .......... .......... .......... 26% 67.8M 10s\n", + "159900K .......... .......... .......... .......... .......... 26% 24.8M 10s\n", + "159950K .......... .......... .......... .......... .......... 26% 38.2M 10s\n", + "160000K .......... .......... .......... .......... .......... 26% 52.7M 10s\n", + "160050K .......... .......... .......... .......... .......... 26% 27.1M 10s\n", + "160100K .......... .......... .......... .......... .......... 26% 37.9M 10s\n", + "160150K .......... .......... .......... .......... .......... 26% 50.2M 10s\n", + "160200K .......... .......... .......... .......... .......... 26% 58.2M 10s\n", + "160250K .......... .......... .......... .......... .......... 26% 25.1M 10s\n", + "160300K .......... .......... .......... .......... .......... 26% 32.7M 10s\n", + "160350K .......... .......... .......... .......... .......... 26% 69.7M 10s\n", + "160400K .......... .......... .......... .......... .......... 26% 22.7M 10s\n", + "160450K .......... .......... .......... .......... .......... 26% 43.9M 10s\n", + "160500K .......... .......... .......... .......... .......... 26% 56.6M 10s\n", + "160550K .......... .......... .......... .......... .......... 27% 69.2M 10s\n", + "160600K .......... .......... .......... .......... .......... 27% 20.9M 10s\n", + "160650K .......... .......... .......... .......... .......... 27% 53.7M 10s\n", + "160700K .......... .......... .......... .......... .......... 27% 65.3M 10s\n", + "160750K .......... .......... .......... .......... .......... 27% 21.0M 10s\n", + "160800K .......... .......... .......... .......... .......... 27% 47.1M 10s\n", + "160850K .......... .......... .......... .......... .......... 27% 56.8M 10s\n", + "160900K .......... .......... .......... .......... .......... 27% 73.9M 10s\n", + "160950K .......... .......... .......... .......... .......... 27% 20.6M 10s\n", + "161000K .......... .......... .......... .......... .......... 27% 37.7M 10s\n", + "161050K .......... .......... .......... .......... .......... 27% 69.8M 10s\n", + "161100K .......... .......... .......... .......... .......... 27% 24.0M 10s\n", + "161150K .......... .......... .......... .......... .......... 27% 60.5M 10s\n", + "161200K .......... .......... .......... .......... .......... 27% 50.8M 10s\n", + "161250K .......... .......... .......... .......... .......... 27% 70.8M 10s\n", + "161300K .......... .......... .......... .......... .......... 27% 18.6M 10s\n", + "161350K .......... .......... .......... .......... .......... 27% 40.1M 10s\n", + "161400K .......... .......... .......... .......... .......... 27% 53.8M 10s\n", + "161450K .......... .......... .......... .......... .......... 27% 29.8M 10s\n", + "161500K .......... .......... .......... .......... .......... 27% 55.6M 10s\n", + "161550K .......... .......... .......... .......... .......... 27% 61.9M 10s\n", + "161600K .......... .......... .......... .......... .......... 27% 48.8M 10s\n", + "161650K .......... .......... .......... .......... 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.......... .......... .......... .......... 27% 67.9M 10s\n", + "163500K .......... .......... .......... .......... .......... 27% 22.4M 10s\n", + "163550K .......... .......... .......... .......... .......... 27% 51.3M 10s\n", + "163600K .......... .......... .......... .......... .......... 27% 50.9M 10s\n", + "163650K .......... .......... .......... .......... .......... 27% 69.5M 10s\n", + "163700K .......... .......... .......... .......... .......... 27% 26.8M 10s\n", + "163750K .......... .......... .......... .......... .......... 27% 48.4M 10s\n", + "163800K .......... .......... .......... .......... .......... 27% 36.9M 10s\n", + "163850K .......... .......... .......... .......... .......... 27% 68.9M 10s\n", + "163900K .......... .......... .......... .......... .......... 27% 27.7M 10s\n", + "163950K .......... .......... .......... .......... .......... 27% 61.7M 10s\n", + "164000K .......... .......... .......... .......... .......... 27% 56.8M 10s\n", + "164050K .......... .......... .......... .......... .......... 27% 63.3M 10s\n", + "164100K .......... .......... .......... .......... .......... 27% 21.5M 10s\n", + "164150K .......... .......... .......... .......... .......... 27% 50.1M 10s\n", + "164200K .......... .......... .......... .......... .......... 27% 46.1M 10s\n", + "164250K .......... .......... .......... .......... .......... 27% 63.6M 10s\n", + "164300K .......... .......... .......... .......... .......... 27% 27.3M 10s\n", + "164350K .......... .......... .......... .......... .......... 27% 61.5M 10s\n", + "164400K .......... .......... .......... .......... .......... 27% 53.7M 10s\n", + "164450K .......... .......... .......... .......... .......... 27% 67.6M 10s\n", + "164500K .......... .......... .......... .......... .......... 27% 21.7M 10s\n", + "164550K .......... .......... .......... .......... .......... 27% 52.2M 10s\n", + "164600K .......... .......... .......... .......... .......... 27% 44.9M 10s\n", + 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10s\n", + "165250K .......... .......... .......... .......... .......... 27% 22.7M 10s\n", + "165300K .......... .......... .......... .......... .......... 27% 52.8M 10s\n", + "165350K .......... .......... .......... .......... .......... 27% 64.2M 10s\n", + "165400K .......... .......... .......... .......... .......... 27% 50.2M 10s\n", + "165450K .......... .......... .......... .......... .......... 27% 26.4M 10s\n", + "165500K .......... .......... .......... .......... .......... 27% 50.6M 10s\n", + "165550K .......... .......... .......... .......... .......... 27% 39.4M 10s\n", + "165600K .......... .......... .......... .......... .......... 27% 54.5M 10s\n", + "165650K .......... .......... .......... .......... .......... 27% 40.5M 10s\n", + "165700K .......... .......... .......... .......... .......... 27% 41.1M 10s\n", + "165750K .......... .......... .......... .......... .......... 27% 51.5M 10s\n", + "165800K .......... .......... .......... .......... .......... 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10s\n", + "170000K .......... .......... .......... .......... .......... 28% 54.3M 10s\n", + "170050K .......... .......... .......... .......... .......... 28% 67.0M 10s\n", + "170100K .......... .......... .......... .......... .......... 28% 64.4M 10s\n", + "170150K .......... .......... .......... .......... .......... 28% 70.7M 10s\n", + "170200K .......... .......... .......... .......... .......... 28% 47.4M 10s\n", + "170250K .......... .......... .......... .......... .......... 28% 50.0M 10s\n", + "170300K .......... .......... .......... .......... .......... 28% 57.0M 10s\n", + "170350K .......... .......... .......... .......... .......... 28% 61.1M 10s\n", + "170400K .......... .......... .......... .......... .......... 28% 62.1M 10s\n", + "170450K .......... .......... .......... .......... .......... 28% 56.0M 10s\n", + "170500K .......... .......... .......... .......... .......... 28% 48.3M 10s\n", + "170550K .......... .......... .......... .......... .......... 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.......... .......... .......... .......... .......... 29% 47.6M 10s\n", + "173600K .......... .......... .......... .......... .......... 29% 18.4M 10s\n", + "173650K .......... .......... .......... .......... .......... 29% 66.0M 10s\n", + "173700K .......... .......... .......... .......... .......... 29% 50.2M 10s\n", + "173750K .......... .......... .......... .......... .......... 29% 51.9M 10s\n", + "173800K .......... .......... .......... .......... .......... 29% 55.0M 10s\n", + "173850K .......... .......... .......... .......... .......... 29% 56.3M 10s\n", + "173900K .......... .......... .......... .......... .......... 29% 18.1M 10s\n", + "173950K .......... .......... .......... .......... .......... 29% 68.4M 10s\n", + "174000K .......... .......... .......... .......... .......... 29% 53.7M 10s\n", + "174050K .......... .......... .......... .......... .......... 29% 46.9M 10s\n", + "174100K .......... .......... .......... .......... .......... 29% 15.4M 10s\n", + 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10s\n", + "174750K .......... .......... .......... .......... .......... 29% 52.0M 10s\n", + "174800K .......... .......... .......... .......... .......... 29% 56.9M 10s\n", + "174850K .......... .......... .......... .......... .......... 29% 60.3M 10s\n", + "174900K .......... .......... .......... .......... .......... 29% 68.1M 10s\n", + "174950K .......... .......... .......... .......... .......... 29% 61.0M 10s\n", + "175000K .......... .......... .......... .......... .......... 29% 41.2M 10s\n", + "175050K .......... .......... .......... .......... .......... 29% 67.2M 10s\n", + "175100K .......... .......... .......... .......... .......... 29% 69.6M 10s\n", + "175150K .......... .......... .......... .......... .......... 29% 61.2M 10s\n", + "175200K .......... .......... .......... .......... .......... 29% 54.4M 10s\n", + "175250K .......... .......... .......... .......... .......... 29% 44.1M 10s\n", + "175300K .......... .......... .......... .......... .......... 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.......... .......... 29% 56.2M 10s\n", + "176550K .......... .......... .......... .......... .......... 29% 49.0M 10s\n", + "176600K .......... .......... .......... .......... .......... 29% 45.8M 10s\n", + "176650K .......... .......... .......... .......... .......... 29% 61.2M 10s\n", + "176700K .......... .......... .......... .......... .......... 29% 62.0M 10s\n", + "176750K .......... .......... .......... .......... .......... 29% 48.4M 10s\n", + "176800K .......... .......... .......... .......... .......... 29% 51.8M 10s\n", + "176850K .......... .......... .......... .......... .......... 29% 53.8M 10s\n", + "176900K .......... .......... .......... .......... .......... 29% 67.8M 10s\n", + "176950K .......... .......... .......... .......... .......... 29% 59.3M 10s\n", + "177000K .......... .......... .......... .......... .......... 29% 57.9M 10s\n", + "177050K .......... .......... .......... .......... .......... 29% 67.5M 10s\n", + "177100K .......... .......... .......... .......... .......... 29% 55.8M 10s\n", + "177150K .......... .......... .......... .......... .......... 29% 60.7M 10s\n", + "177200K .......... .......... .......... .......... .......... 29% 58.5M 10s\n", + "177250K .......... .......... .......... .......... .......... 29% 57.3M 10s\n", + "177300K .......... .......... .......... .......... .......... 29% 70.2M 10s\n", + "177350K .......... .......... .......... .......... .......... 29% 69.6M 10s\n", + "177400K .......... .......... .......... .......... .......... 29% 59.4M 10s\n", + "177450K .......... .......... .......... .......... .......... 29% 67.4M 10s\n", + "177500K .......... .......... .......... .......... .......... 29% 70.8M 10s\n", + "177550K .......... .......... .......... .......... .......... 29% 58.4M 10s\n", + "177600K .......... .......... .......... .......... .......... 29% 52.8M 10s\n", + "177650K .......... .......... .......... .......... .......... 29% 65.2M 10s\n", + "177700K .......... .......... .......... .......... .......... 29% 57.0M 10s\n", + "177750K .......... .......... .......... .......... .......... 29% 71.4M 10s\n", + "177800K .......... .......... .......... .......... .......... 29% 59.7M 10s\n", + "177850K .......... .......... .......... .......... .......... 29% 58.4M 10s\n", + "177900K .......... .......... .......... .......... .......... 29% 55.5M 10s\n", + "177950K .......... .......... .......... .......... .......... 29% 38.0M 10s\n", + "178000K .......... .......... .......... .......... .......... 29% 3.85M 10s\n", + "178050K .......... .......... .......... .......... .......... 29% 68.7M 10s\n", + "178100K .......... .......... .......... .......... .......... 29% 65.9M 10s\n", + "178150K .......... .......... .......... .......... .......... 29% 65.4M 10s\n", + "178200K .......... .......... .......... .......... .......... 29% 16.7M 10s\n", + "178250K .......... .......... .......... .......... .......... 29% 55.3M 10s\n", + "178300K .......... .......... .......... .......... .......... 29% 67.6M 10s\n", + "178350K .......... .......... .......... .......... .......... 29% 21.2M 10s\n", + "178400K .......... .......... .......... .......... .......... 30% 42.9M 10s\n", + "178450K .......... .......... .......... .......... .......... 30% 63.2M 10s\n", + "178500K .......... .......... .......... .......... .......... 30% 63.6M 10s\n", + "178550K .......... .......... .......... .......... .......... 30% 21.3M 10s\n", + "178600K .......... .......... .......... .......... .......... 30% 43.8M 10s\n", + "178650K .......... .......... .......... .......... .......... 30% 67.6M 10s\n", + "178700K .......... .......... .......... .......... .......... 30% 23.2M 10s\n", + "178750K .......... .......... .......... .......... .......... 30% 38.3M 10s\n", + "178800K .......... .......... .......... .......... .......... 30% 55.7M 10s\n", + "178850K .......... .......... .......... .......... .......... 30% 60.3M 10s\n", + 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10s\n", + "179500K .......... .......... .......... .......... .......... 30% 56.0M 10s\n", + "179550K .......... .......... .......... .......... .......... 30% 53.8M 10s\n", + "179600K .......... .......... .......... .......... .......... 30% 21.0M 10s\n", + "179650K .......... .......... .......... .......... .......... 30% 54.1M 10s\n", + "179700K .......... .......... .......... .......... .......... 30% 58.3M 10s\n", + "179750K .......... .......... .......... .......... .......... 30% 55.9M 10s\n", + "179800K .......... .......... .......... .......... .......... 30% 20.8M 10s\n", + "179850K .......... .......... .......... .......... .......... 30% 49.6M 10s\n", + "179900K .......... .......... .......... .......... .......... 30% 53.8M 10s\n", + "179950K .......... .......... .......... .......... .......... 30% 4.07M 10s\n", + "180000K .......... .......... .......... .......... .......... 30% 59.3M 10s\n", + "180050K .......... .......... .......... .......... .......... 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.......... .......... .......... 30% 44.9M 10s\n", + "181900K .......... .......... .......... .......... .......... 30% 65.4M 10s\n", + "181950K .......... .......... .......... .......... .......... 30% 30.1M 10s\n", + "182000K .......... .......... .......... .......... .......... 30% 46.7M 10s\n", + "182050K .......... .......... .......... .......... .......... 30% 51.7M 10s\n", + "182100K .......... .......... .......... .......... .......... 30% 61.6M 10s\n", + "182150K .......... .......... .......... .......... .......... 30% 26.7M 10s\n", + "182200K .......... .......... .......... .......... .......... 30% 38.5M 10s\n", + "182250K .......... .......... .......... .......... .......... 30% 8.10M 10s\n", + "182300K .......... .......... .......... .......... .......... 30% 62.2M 10s\n", + "182350K .......... .......... .......... .......... .......... 30% 67.5M 10s\n", + "182400K .......... .......... .......... .......... .......... 30% 60.0M 10s\n", + "182450K .......... .......... .......... .......... .......... 30% 68.3M 10s\n", + "182500K .......... .......... .......... .......... .......... 30% 28.5M 10s\n", + "182550K .......... .......... .......... .......... .......... 30% 49.9M 10s\n", + "182600K .......... .......... .......... .......... .......... 30% 50.4M 10s\n", + "182650K .......... .......... .......... .......... .......... 30% 68.6M 10s\n", + "182700K .......... .......... .......... .......... .......... 30% 27.3M 10s\n", + "182750K .......... .......... .......... .......... .......... 30% 47.1M 10s\n", + "182800K .......... .......... .......... .......... .......... 30% 50.4M 10s\n", + "182850K .......... .......... .......... .......... .......... 30% 68.7M 10s\n", + "182900K .......... .......... .......... .......... .......... 30% 24.6M 10s\n", + "182950K .......... .......... .......... .......... .......... 30% 46.9M 10s\n", + "183000K .......... .......... .......... .......... .......... 30% 49.3M 10s\n", + "183050K .......... .......... .......... .......... .......... 30% 70.9M 10s\n", + "183100K .......... .......... .......... .......... .......... 30% 5.52M 10s\n", + "183150K .......... .......... .......... .......... .......... 30% 55.0M 10s\n", + "183200K .......... .......... .......... .......... .......... 30% 60.4M 10s\n", + "183250K .......... .......... .......... .......... .......... 30% 68.1M 10s\n", + "183300K .......... .......... .......... .......... .......... 30% 23.7M 10s\n", + "183350K .......... .......... .......... .......... .......... 30% 48.2M 10s\n", + "183400K .......... .......... .......... .......... .......... 30% 51.9M 10s\n", + "183450K .......... .......... .......... .......... .......... 30% 65.7M 10s\n", + "183500K .......... .......... .......... .......... .......... 30% 28.2M 10s\n", + "183550K .......... .......... .......... .......... .......... 30% 49.0M 10s\n", + "183600K .......... .......... .......... .......... .......... 30% 47.4M 10s\n", + 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10s\n", + "184250K .......... .......... .......... .......... .......... 30% 59.3M 10s\n", + "184300K .......... .......... .......... .......... .......... 30% 67.7M 10s\n", + "184350K .......... .......... .......... .......... .......... 31% 41.8M 10s\n", + "184400K .......... .......... .......... .......... .......... 31% 56.3M 10s\n", + "184450K .......... .......... .......... .......... .......... 31% 53.1M 10s\n", + "184500K .......... .......... .......... .......... .......... 31% 67.4M 10s\n", + "184550K .......... .......... .......... .......... .......... 31% 25.7M 10s\n", + "184600K .......... .......... .......... .......... .......... 31% 46.5M 10s\n", + "184650K .......... .......... .......... .......... .......... 31% 51.9M 10s\n", + "184700K .......... .......... .......... .......... .......... 31% 59.4M 10s\n", + "184750K .......... .......... .......... .......... .......... 31% 29.8M 10s\n", + "184800K .......... .......... .......... .......... .......... 31% 4.77M 10s\n", + "184850K .......... .......... .......... .......... .......... 31% 67.5M 10s\n", + "184900K .......... .......... .......... .......... .......... 31% 71.9M 10s\n", + "184950K .......... .......... .......... .......... .......... 31% 62.5M 10s\n", + "185000K .......... .......... .......... .......... .......... 31% 58.5M 10s\n", + "185050K .......... .......... .......... .......... .......... 31% 27.5M 10s\n", + "185100K .......... .......... .......... .......... .......... 31% 47.7M 10s\n", + "185150K .......... .......... .......... .......... .......... 31% 58.6M 10s\n", + "185200K .......... .......... .......... .......... .......... 31% 63.4M 10s\n", + "185250K .......... .......... .......... .......... .......... 31% 32.1M 10s\n", + "185300K .......... .......... .......... .......... .......... 31% 49.7M 10s\n", + "185350K .......... .......... .......... .......... .......... 31% 57.6M 10s\n", + "185400K .......... .......... .......... .......... 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.......... .......... 31% 41.1M 10s\n", + "186050K .......... .......... .......... .......... .......... 31% 61.8M 10s\n", + "186100K .......... .......... .......... .......... .......... 31% 70.6M 10s\n", + "186150K .......... .......... .......... .......... .......... 31% 38.2M 10s\n", + "186200K .......... .......... .......... .......... .......... 31% 38.3M 10s\n", + "186250K .......... .......... .......... .......... .......... 31% 57.4M 10s\n", + "186300K .......... .......... .......... .......... .......... 31% 52.0M 10s\n", + "186350K .......... .......... .......... .......... .......... 31% 35.2M 10s\n", + "186400K .......... .......... .......... .......... .......... 31% 38.9M 10s\n", + "186450K .......... .......... .......... .......... .......... 31% 62.7M 10s\n", + "186500K .......... .......... .......... .......... .......... 31% 71.5M 10s\n", + "186550K .......... .......... .......... .......... .......... 31% 39.0M 10s\n", + "186600K .......... .......... .......... .......... .......... 31% 28.4M 10s\n", + "186650K .......... .......... .......... .......... .......... 31% 37.8M 10s\n", + "186700K .......... .......... .......... .......... .......... 31% 70.9M 10s\n", + "186750K .......... .......... .......... .......... .......... 31% 60.1M 10s\n", + "186800K .......... .......... .......... .......... .......... 31% 51.5M 10s\n", + "186850K .......... .......... .......... .......... .......... 31% 57.6M 10s\n", + "186900K .......... .......... .......... .......... .......... 31% 57.9M 10s\n", + "186950K .......... .......... .......... .......... .......... 31% 71.7M 10s\n", + "187000K .......... .......... .......... .......... .......... 31% 31.1M 10s\n", + "187050K .......... .......... .......... .......... .......... 31% 62.4M 10s\n", + "187100K .......... .......... .......... .......... .......... 31% 65.9M 10s\n", + "187150K .......... .......... .......... .......... .......... 31% 60.5M 10s\n", + "187200K .......... .......... .......... .......... .......... 31% 29.2M 10s\n", + "187250K .......... .......... .......... .......... .......... 31% 55.2M 10s\n", + "187300K .......... .......... .......... .......... .......... 31% 45.9M 10s\n", + "187350K .......... .......... .......... .......... .......... 31% 53.2M 10s\n", + "187400K .......... .......... .......... .......... .......... 31% 56.7M 10s\n", + "187450K .......... .......... .......... .......... .......... 31% 37.7M 10s\n", + "187500K .......... .......... .......... .......... .......... 31% 56.6M 10s\n", + "187550K .......... .......... .......... .......... .......... 31% 51.5M 10s\n", + "187600K .......... .......... .......... .......... .......... 31% 58.6M 10s\n", + "187650K .......... .......... .......... .......... .......... 31% 32.8M 10s\n", + "187700K .......... .......... .......... .......... .......... 31% 59.7M 10s\n", + "187750K .......... .......... .......... .......... .......... 31% 47.8M 10s\n", + "187800K .......... .......... .......... .......... .......... 31% 47.1M 10s\n", + "187850K .......... .......... .......... .......... .......... 31% 66.9M 10s\n", + "187900K .......... .......... .......... .......... .......... 31% 27.1M 10s\n", + "187950K .......... .......... .......... .......... .......... 31% 44.9M 10s\n", + "188000K .......... .......... .......... .......... .......... 31% 48.2M 10s\n", + "188050K .......... .......... .......... .......... .......... 31% 72.9M 10s\n", + "188100K .......... .......... .......... .......... .......... 31% 62.6M 10s\n", + "188150K .......... .......... .......... .......... .......... 31% 33.7M 10s\n", + "188200K .......... .......... .......... .......... .......... 31% 40.8M 10s\n", + "188250K .......... .......... .......... .......... .......... 31% 60.7M 10s\n", + "188300K .......... .......... .......... .......... .......... 31% 77.5M 10s\n", + "188350K .......... .......... .......... .......... .......... 31% 39.3M 10s\n", + "188400K .......... .......... .......... .......... .......... 31% 43.9M 10s\n", + "188450K .......... .......... .......... .......... .......... 31% 53.6M 10s\n", + "188500K .......... .......... .......... .......... .......... 31% 65.7M 10s\n", + "188550K .......... .......... .......... .......... .......... 31% 67.8M 10s\n", + "188600K .......... .......... .......... .......... .......... 31% 27.3M 10s\n", + "188650K .......... .......... .......... .......... .......... 31% 43.3M 10s\n", + "188700K .......... .......... .......... .......... .......... 31% 2.66M 10s\n", + "188750K .......... .......... .......... .......... .......... 31% 63.3M 10s\n", + "188800K .......... .......... .......... .......... .......... 31% 57.3M 10s\n", + "188850K .......... .......... .......... .......... .......... 31% 63.9M 10s\n", + "188900K .......... .......... .......... .......... .......... 31% 65.6M 10s\n", + "188950K .......... .......... .......... .......... .......... 31% 60.2M 10s\n", + "189000K .......... .......... .......... .......... .......... 31% 45.7M 10s\n", + "189050K .......... .......... .......... .......... .......... 31% 52.2M 10s\n", + "189100K .......... .......... .......... .......... .......... 31% 65.9M 10s\n", + "189150K .......... .......... .......... .......... .......... 31% 65.7M 10s\n", + "189200K .......... .......... .......... .......... .......... 31% 61.8M 10s\n", + "189250K .......... .......... .......... .......... .......... 31% 56.6M 10s\n", + "189300K .......... .......... .......... .......... .......... 31% 8.68M 10s\n", + "189350K .......... .......... .......... .......... .......... 31% 66.9M 10s\n", + "189400K .......... .......... .......... .......... .......... 31% 62.8M 10s\n", + "189450K .......... .......... .......... .......... .......... 31% 70.4M 10s\n", + "189500K .......... .......... .......... .......... .......... 31% 69.2M 10s\n", + "189550K .......... .......... .......... .......... .......... 31% 24.0M 10s\n", + "189600K .......... .......... .......... .......... .......... 31% 44.4M 10s\n", + "189650K .......... .......... .......... .......... .......... 31% 69.6M 10s\n", + "189700K .......... .......... .......... .......... .......... 31% 65.8M 10s\n", + "189750K .......... .......... .......... .......... .......... 31% 33.4M 10s\n", + "189800K .......... .......... .......... .......... .......... 31% 36.9M 10s\n", + "189850K .......... .......... .......... .......... .......... 31% 61.0M 10s\n", + "189900K .......... .......... .......... .......... .......... 31% 65.2M 10s\n", + "189950K .......... .......... .......... .......... .......... 31% 71.8M 10s\n", + "190000K .......... .......... .......... .......... .......... 31% 29.3M 10s\n", + "190050K .......... .......... .......... .......... .......... 31% 46.8M 10s\n", + "190100K .......... .......... .......... .......... .......... 31% 61.5M 10s\n", + "190150K .......... .......... .......... .......... .......... 31% 65.5M 10s\n", + "190200K .......... .......... .......... .......... .......... 31% 38.3M 10s\n", + "190250K .......... .......... .......... .......... .......... 31% 46.8M 10s\n", + "190300K .......... .......... .......... .......... .......... 32% 53.8M 10s\n", + "190350K .......... .......... .......... .......... .......... 32% 63.8M 10s\n", + "190400K .......... .......... .......... .......... .......... 32% 60.1M 10s\n", + "190450K .......... .......... .......... .......... .......... 32% 53.2M 10s\n", + "190500K .......... .......... .......... .......... .......... 32% 44.0M 10s\n", + "190550K .......... .......... .......... .......... .......... 32% 55.8M 10s\n", + "190600K .......... .......... .......... .......... .......... 32% 51.5M 10s\n", + "190650K .......... .......... .......... .......... .......... 32% 68.1M 10s\n", + "190700K .......... .......... .......... .......... .......... 32% 38.6M 10s\n", + "190750K .......... .......... .......... .......... .......... 32% 46.3M 10s\n", + "190800K .......... .......... .......... .......... .......... 32% 46.0M 10s\n", + "190850K .......... .......... .......... .......... .......... 32% 67.4M 10s\n", + "190900K .......... .......... .......... .......... .......... 32% 76.3M 10s\n", + "190950K .......... .......... .......... .......... .......... 32% 53.7M 10s\n", + "191000K .......... .......... .......... .......... .......... 32% 37.8M 10s\n", + "191050K .......... .......... .......... .......... .......... 32% 58.9M 10s\n", + "191100K .......... .......... .......... .......... .......... 32% 74.0M 10s\n", + "191150K .......... .......... .......... .......... .......... 32% 33.7M 10s\n", + "191200K .......... .......... .......... .......... .......... 32% 10.5M 10s\n", + "191250K .......... .......... .......... .......... .......... 32% 48.3M 10s\n", + "191300K .......... .......... .......... .......... .......... 32% 70.7M 10s\n", + "191350K .......... .......... .......... .......... .......... 32% 76.1M 10s\n", + "191400K .......... .......... .......... .......... .......... 32% 57.2M 10s\n", + "191450K .......... .......... .......... .......... .......... 32% 75.1M 10s\n", + "191500K .......... .......... .......... .......... .......... 32% 37.5M 10s\n", + "191550K .......... .......... .......... .......... .......... 32% 51.1M 10s\n", + "191600K .......... .......... .......... .......... .......... 32% 45.5M 10s\n", + "191650K .......... .......... .......... .......... .......... 32% 69.5M 10s\n", + "191700K .......... .......... .......... .......... .......... 32% 66.9M 10s\n", + "191750K .......... .......... .......... .......... .......... 32% 45.1M 10s\n", + "191800K .......... .......... .......... .......... .......... 32% 42.3M 10s\n", + "191850K .......... .......... .......... .......... .......... 32% 62.8M 10s\n", + "191900K .......... .......... .......... .......... .......... 32% 65.9M 10s\n", + "191950K .......... .......... .......... .......... .......... 32% 65.9M 10s\n", + "192000K .......... .......... .......... .......... .......... 32% 39.3M 10s\n", + "192050K .......... .......... .......... .......... .......... 32% 51.3M 10s\n", + "192100K .......... .......... .......... .......... .......... 32% 57.0M 10s\n", + "192150K .......... .......... .......... .......... .......... 32% 74.0M 10s\n", + "192200K .......... .......... .......... .......... .......... 32% 34.1M 10s\n", + "192250K .......... .......... .......... .......... .......... 32% 51.3M 10s\n", + "192300K .......... .......... .......... .......... .......... 32% 45.4M 10s\n", + "192350K .......... .......... .......... .......... .......... 32% 56.1M 10s\n", + "192400K .......... .......... .......... .......... .......... 32% 63.8M 10s\n", + "192450K .......... .......... .......... .......... .......... 32% 74.8M 10s\n", + "192500K .......... .......... .......... .......... .......... 32% 42.4M 10s\n", + "192550K .......... .......... .......... .......... .......... 32% 47.9M 10s\n", + "192600K .......... .......... .......... .......... .......... 32% 46.0M 10s\n", + "192650K .......... .......... .......... .......... .......... 32% 64.5M 10s\n", + "192700K .......... .......... .......... .......... .......... 32% 53.1M 10s\n", + "192750K .......... .......... .......... .......... .......... 32% 53.6M 10s\n", + "192800K .......... .......... .......... .......... .......... 32% 41.4M 10s\n", + "192850K .......... .......... .......... .......... .......... 32% 58.0M 10s\n", + "192900K .......... .......... .......... .......... .......... 32% 69.2M 10s\n", + "192950K .......... .......... .......... .......... .......... 32% 56.8M 10s\n", + "193000K .......... .......... .......... .......... .......... 32% 51.8M 10s\n", + "193050K .......... .......... .......... .......... .......... 32% 45.3M 10s\n", + "193100K .......... .......... .......... .......... .......... 32% 52.5M 10s\n", + "193150K .......... .......... .......... .......... .......... 32% 64.9M 10s\n", + "193200K .......... .......... .......... .......... .......... 32% 52.9M 10s\n", + "193250K .......... .......... .......... .......... .......... 32% 56.0M 10s\n", + "193300K .......... .......... .......... .......... .......... 32% 56.7M 10s\n", + "193350K .......... .......... .......... .......... .......... 32% 53.3M 10s\n", + "193400K .......... .......... .......... .......... .......... 32% 52.4M 10s\n", + "193450K .......... .......... .......... .......... .......... 32% 71.0M 10s\n", + "193500K .......... .......... .......... .......... .......... 32% 48.6M 10s\n", + "193550K .......... .......... .......... .......... .......... 32% 5.35M 10s\n", + "193600K .......... .......... .......... .......... .......... 32% 37.9M 10s\n", + "193650K .......... .......... .......... .......... .......... 32% 40.8M 10s\n", + "193700K .......... .......... .......... .......... .......... 32% 52.1M 10s\n", + "193750K .......... .......... .......... .......... .......... 32% 60.3M 10s\n", + "193800K .......... .......... .......... .......... .......... 32% 51.2M 10s\n", + "193850K .......... .......... .......... .......... .......... 32% 57.2M 10s\n", + "193900K .......... .......... .......... .......... .......... 32% 15.4M 10s\n", + "193950K .......... .......... .......... .......... .......... 32% 69.5M 10s\n", + "194000K .......... .......... .......... .......... .......... 32% 62.0M 10s\n", + "194050K .......... .......... .......... .......... .......... 32% 71.0M 10s\n", + "194100K .......... .......... .......... .......... .......... 32% 17.3M 10s\n", + "194150K .......... .......... .......... .......... .......... 32% 57.5M 10s\n", + "194200K .......... .......... .......... .......... .......... 32% 61.5M 10s\n", + "194250K .......... .......... .......... .......... .......... 32% 19.9M 10s\n", + "194300K .......... .......... .......... .......... .......... 32% 46.3M 10s\n", + "194350K .......... .......... .......... .......... .......... 32% 69.4M 10s\n", + "194400K .......... .......... .......... .......... .......... 32% 18.3M 10s\n", + "194450K .......... .......... .......... .......... .......... 32% 55.6M 10s\n", + "194500K .......... .......... .......... .......... .......... 32% 60.7M 10s\n", + "194550K .......... .......... .......... .......... .......... 32% 72.4M 10s\n", + "194600K .......... .......... .......... .......... .......... 32% 18.8M 10s\n", + "194650K .......... .......... .......... .......... .......... 32% 55.0M 10s\n", + "194700K .......... .......... .......... .......... .......... 32% 76.2M 10s\n", + "194750K .......... .......... .......... .......... .......... 32% 4.01M 10s\n", + "194800K .......... .......... .......... .......... .......... 32% 57.6M 10s\n", + "194850K .......... .......... .......... .......... .......... 32% 74.7M 10s\n", + "194900K .......... .......... .......... .......... .......... 32% 68.0M 10s\n", + "194950K .......... .......... .......... .......... .......... 32% 16.6M 10s\n", + "195000K .......... .......... .......... .......... .......... 32% 37.5M 10s\n", + "195050K .......... .......... .......... .......... .......... 32% 62.9M 10s\n", + "195100K .......... .......... .......... .......... .......... 32% 69.2M 10s\n", + "195150K .......... .......... .......... .......... .......... 32% 26.7M 10s\n", + "195200K .......... .......... .......... .......... .......... 32% 38.2M 10s\n", + "195250K .......... .......... .......... .......... .......... 32% 70.3M 10s\n", + "195300K .......... .......... .......... .......... .......... 32% 22.8M 10s\n", + "195350K .......... .......... .......... .......... .......... 32% 36.9M 10s\n", + "195400K .......... .......... .......... .......... .......... 32% 53.5M 10s\n", + "195450K .......... .......... .......... .......... .......... 32% 72.9M 10s\n", + "195500K .......... .......... .......... .......... .......... 32% 21.3M 10s\n", + "195550K .......... .......... .......... .......... .......... 32% 39.6M 10s\n", + "195600K .......... .......... .......... .......... .......... 32% 66.5M 10s\n", + "195650K .......... .......... .......... .......... .......... 32% 22.9M 10s\n", + "195700K .......... .......... .......... .......... .......... 32% 33.2M 10s\n", + "195750K .......... .......... .......... .......... .......... 32% 37.9M 10s\n", + "195800K .......... .......... .......... .......... .......... 32% 26.2M 10s\n", + "195850K .......... .......... .......... .......... .......... 32% 20.7M 10s\n", + "195900K .......... .......... .......... .......... .......... 32% 72.2M 10s\n", + "195950K .......... .......... .......... .......... .......... 32% 76.8M 10s\n", + "196000K .......... .......... .......... .......... .......... 32% 41.0M 10s\n", + "196050K .......... .......... .......... .......... .......... 32% 45.4M 10s\n", + "196100K .......... .......... .......... .......... .......... 32% 46.1M 10s\n", + "196150K .......... .......... .......... .......... .......... 32% 62.0M 10s\n", + "196200K .......... .......... .......... .......... .......... 32% 19.8M 10s\n", + "196250K .......... .......... .......... .......... .......... 33% 57.6M 10s\n", + "196300K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", + "196350K .......... .......... .......... .......... .......... 33% 30.0M 10s\n", + "196400K .......... .......... .......... .......... .......... 33% 22.9M 10s\n", + "196450K .......... .......... .......... .......... .......... 33% 45.5M 10s\n", + "196500K .......... .......... .......... .......... .......... 33% 60.7M 10s\n", + "196550K .......... .......... .......... .......... .......... 33% 40.2M 10s\n", + "196600K .......... .......... .......... .......... .......... 33% 20.0M 10s\n", + "196650K .......... .......... .......... .......... .......... 33% 22.0M 10s\n", + "196700K .......... .......... .......... .......... .......... 33% 62.6M 10s\n", + "196750K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", + "196800K .......... .......... .......... .......... .......... 33% 20.9M 10s\n", + "196850K .......... .......... .......... .......... .......... 33% 46.7M 10s\n", + "196900K .......... .......... .......... .......... .......... 33% 48.4M 10s\n", + "196950K .......... .......... .......... .......... .......... 33% 53.4M 10s\n", + "197000K .......... .......... .......... .......... .......... 33% 21.5M 10s\n", + "197050K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", + "197100K .......... .......... .......... .......... .......... 33% 57.7M 10s\n", + "197150K .......... .......... .......... .......... .......... 33% 24.3M 10s\n", + "197200K .......... .......... .......... .......... .......... 33% 37.0M 10s\n", + "197250K .......... .......... .......... .......... .......... 33% 57.3M 10s\n", + "197300K .......... .......... .......... .......... .......... 33% 58.8M 10s\n", + "197350K .......... .......... .......... .......... .......... 33% 24.2M 10s\n", + "197400K .......... .......... .......... .......... .......... 33% 36.9M 10s\n", + "197450K .......... .......... .......... .......... .......... 33% 57.0M 10s\n", + "197500K .......... .......... .......... .......... .......... 33% 22.1M 10s\n", + "197550K .......... .......... .......... .......... .......... 33% 49.4M 10s\n", + "197600K .......... .......... .......... .......... .......... 33% 48.0M 10s\n", + "197650K .......... .......... .......... .......... .......... 33% 60.8M 10s\n", + "197700K .......... .......... .......... .......... .......... 33% 19.3M 10s\n", + "197750K .......... .......... .......... .......... .......... 33% 47.0M 10s\n", + "197800K .......... .......... .......... .......... .......... 33% 49.6M 10s\n", + "197850K .......... .......... .......... .......... .......... 33% 27.9M 10s\n", + "197900K .......... .......... .......... .......... .......... 33% 36.1M 10s\n", + "197950K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", + "198000K .......... .......... .......... .......... .......... 33% 1.41M 10s\n", + "198050K .......... .......... .......... .......... .......... 33% 55.6M 10s\n", + "198100K .......... .......... .......... .......... .......... 33% 67.8M 10s\n", + "198150K .......... .......... .......... .......... .......... 33% 18.4M 10s\n", + "198200K .......... .......... .......... .......... .......... 33% 43.7M 10s\n", + "198250K .......... .......... .......... .......... .......... 33% 59.8M 10s\n", + "198300K .......... .......... .......... .......... .......... 33% 67.1M 10s\n", + "198350K .......... .......... .......... .......... .......... 33% 17.3M 10s\n", + "198400K .......... .......... .......... .......... .......... 33% 30.6M 10s\n", + "198450K .......... .......... .......... .......... .......... 33% 36.2M 10s\n", + "198500K .......... .......... .......... .......... .......... 33% 34.7M 10s\n", + "198550K .......... .......... .......... .......... .......... 33% 31.3M 10s\n", + "198600K .......... .......... .......... .......... .......... 33% 34.0M 10s\n", + "198650K .......... .......... .......... .......... .......... 33% 30.7M 10s\n", + "198700K .......... .......... .......... .......... .......... 33% 33.3M 10s\n", + "198750K .......... .......... .......... .......... .......... 33% 57.2M 10s\n", + "198800K .......... .......... .......... .......... .......... 33% 54.3M 10s\n", + "198850K .......... .......... .......... .......... .......... 33% 47.5M 10s\n", + "198900K .......... .......... .......... .......... .......... 33% 73.2M 10s\n", + "198950K .......... .......... .......... .......... .......... 33% 66.6M 10s\n", + "199000K .......... .......... .......... .......... .......... 33% 57.6M 10s\n", + "199050K .......... .......... .......... .......... .......... 33% 19.5M 10s\n", + "199100K .......... .......... .......... .......... .......... 33% 42.2M 10s\n", + "199150K .......... .......... .......... .......... .......... 33% 51.0M 10s\n", + "199200K .......... .......... .......... .......... .......... 33% 62.5M 10s\n", + "199250K .......... .......... .......... .......... .......... 33% 6.49M 10s\n", + "199300K .......... .......... .......... .......... .......... 33% 56.6M 10s\n", + "199350K .......... .......... .......... .......... .......... 33% 67.2M 10s\n", + "199400K .......... .......... .......... .......... .......... 33% 17.6M 10s\n", + "199450K .......... .......... .......... .......... .......... 33% 43.5M 10s\n", + "199500K .......... .......... .......... .......... .......... 33% 54.9M 10s\n", + "199550K .......... .......... .......... .......... .......... 33% 60.8M 10s\n", + "199600K .......... .......... .......... .......... .......... 33% 28.0M 10s\n", + "199650K .......... .......... .......... .......... .......... 33% 40.8M 10s\n", + "199700K .......... .......... .......... .......... .......... 33% 42.5M 10s\n", + "199750K .......... .......... .......... .......... .......... 33% 51.4M 10s\n", + "199800K .......... .......... .......... .......... .......... 33% 29.8M 10s\n", + "199850K .......... .......... .......... .......... .......... 33% 46.6M 10s\n", + "199900K .......... .......... .......... .......... .......... 33% 45.8M 10s\n", + "199950K .......... .......... .......... .......... .......... 33% 22.5M 10s\n", + "200000K .......... .......... .......... .......... .......... 33% 35.6M 10s\n", + "200050K .......... .......... .......... .......... .......... 33% 54.8M 10s\n", + "200100K .......... .......... .......... .......... .......... 33% 55.9M 10s\n", + "200150K .......... .......... .......... .......... .......... 33% 33.6M 10s\n", + "200200K .......... .......... .......... .......... .......... 33% 36.7M 10s\n", + "200250K .......... .......... .......... .......... .......... 33% 67.3M 10s\n", + "200300K .......... .......... .......... .......... .......... 33% 69.2M 10s\n", + "200350K .......... .......... .......... .......... .......... 33% 19.3M 10s\n", + "200400K .......... .......... .......... .......... .......... 33% 46.0M 10s\n", + "200450K .......... .......... .......... .......... .......... 33% 58.0M 10s\n", + "200500K .......... .......... .......... .......... .......... 33% 65.7M 10s\n", + "200550K .......... .......... .......... .......... .......... 33% 25.3M 10s\n", + "200600K .......... .......... .......... .......... .......... 33% 39.8M 10s\n", + "200650K .......... .......... .......... .......... .......... 33% 66.9M 10s\n", + "200700K .......... .......... .......... .......... .......... 33% 8.67M 10s\n", + "200750K .......... .......... .......... .......... .......... 33% 24.8M 10s\n", + "200800K .......... .......... .......... .......... .......... 33% 49.0M 10s\n", + "200850K .......... .......... .......... .......... .......... 33% 70.5M 10s\n", + "200900K .......... .......... .......... .......... .......... 33% 67.7M 10s\n", + "200950K .......... .......... .......... .......... .......... 33% 40.2M 10s\n", + "201000K .......... .......... .......... .......... .......... 33% 35.4M 10s\n", + "201050K .......... .......... .......... .......... .......... 33% 48.4M 10s\n", + "201100K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", + "201150K .......... .......... .......... .......... .......... 33% 38.8M 10s\n", + "201200K .......... .......... .......... .......... .......... 33% 30.2M 10s\n", + "201250K .......... .......... .......... .......... .......... 33% 45.3M 10s\n", + "201300K .......... .......... .......... .......... .......... 33% 47.5M 10s\n", + "201350K .......... .......... .......... .......... .......... 33% 46.3M 10s\n", + "201400K .......... .......... .......... .......... .......... 33% 36.7M 10s\n", + "201450K .......... .......... .......... .......... .......... 33% 62.8M 10s\n", + "201500K .......... .......... .......... .......... .......... 33% 68.0M 10s\n", + "201550K .......... .......... .......... .......... .......... 33% 61.5M 10s\n", + "201600K .......... .......... .......... .......... .......... 33% 1.34M 10s\n", + "201650K .......... .......... .......... .......... .......... 33% 57.3M 10s\n", + "201700K .......... .......... .......... .......... .......... 33% 67.8M 10s\n", + "201750K .......... .......... .......... .......... .......... 33% 67.2M 10s\n", + "201800K .......... .......... .......... .......... .......... 33% 22.2M 10s\n", + "201850K .......... .......... .......... .......... .......... 33% 35.1M 10s\n", + "201900K .......... .......... .......... .......... .......... 33% 70.9M 10s\n", + "201950K .......... .......... .......... .......... .......... 33% 79.5M 10s\n", + "202000K .......... .......... .......... .......... .......... 33% 25.4M 10s\n", + "202050K .......... .......... .......... .......... .......... 33% 38.6M 10s\n", + "202100K .......... .......... .......... .......... .......... 33% 58.6M 10s\n", + "202150K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", + "202200K .......... .......... .......... .......... .......... 34% 24.1M 10s\n", + "202250K .......... .......... .......... .......... .......... 34% 30.2M 10s\n", + "202300K .......... .......... .......... .......... .......... 34% 76.8M 10s\n", + "202350K .......... .......... .......... .......... .......... 34% 75.1M 10s\n", + "202400K .......... .......... .......... .......... .......... 34% 30.7M 10s\n", + "202450K .......... .......... .......... .......... .......... 34% 27.4M 10s\n", + "202500K .......... .......... .......... .......... .......... 34% 73.7M 10s\n", + "202550K .......... .......... .......... .......... .......... 34% 71.7M 10s\n", + "202600K .......... .......... .......... .......... .......... 34% 37.0M 10s\n", + "202650K .......... .......... .......... .......... .......... 34% 36.5M 10s\n", + "202700K .......... .......... .......... .......... .......... 34% 45.0M 10s\n", + "202750K .......... .......... .......... .......... .......... 34% 67.7M 10s\n", + "202800K .......... .......... .......... .......... .......... 34% 48.6M 10s\n", + "202850K .......... .......... .......... .......... .......... 34% 42.9M 10s\n", + "202900K .......... .......... .......... .......... .......... 34% 47.0M 10s\n", + "202950K .......... .......... .......... .......... .......... 34% 49.1M 10s\n", + "203000K .......... .......... .......... .......... .......... 34% 43.2M 10s\n", + "203050K .......... .......... .......... .......... .......... 34% 42.6M 10s\n", + "203100K .......... .......... .......... .......... .......... 34% 38.3M 10s\n", + "203150K .......... .......... .......... .......... .......... 34% 49.7M 10s\n", + "203200K .......... .......... .......... .......... .......... 34% 48.9M 10s\n", + "203250K .......... .......... .......... .......... .......... 34% 33.5M 10s\n", + "203300K .......... .......... .......... .......... .......... 34% 49.6M 10s\n", + "203350K .......... .......... .......... .......... .......... 34% 43.0M 10s\n", + "203400K .......... .......... .......... .......... .......... 34% 34.7M 10s\n", + "203450K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", + "203500K .......... .......... .......... .......... .......... 34% 51.2M 10s\n", + "203550K .......... .......... .......... .......... .......... 34% 46.1M 10s\n", + "203600K .......... .......... .......... .......... .......... 34% 41.9M 10s\n", + "203650K .......... .......... .......... .......... .......... 34% 43.8M 10s\n", + "203700K .......... .......... .......... .......... .......... 34% 48.5M 10s\n", + "203750K .......... .......... .......... .......... .......... 34% 60.1M 10s\n", + "203800K .......... .......... .......... .......... .......... 34% 35.4M 10s\n", + "203850K .......... .......... .......... .......... .......... 34% 48.3M 10s\n", + "203900K .......... .......... .......... .......... .......... 34% 43.5M 10s\n", + "203950K .......... .......... .......... .......... .......... 34% 65.2M 10s\n", + "204000K .......... .......... .......... .......... .......... 34% 44.4M 10s\n", + "204050K .......... .......... .......... .......... .......... 34% 49.5M 10s\n", + "204100K .......... .......... .......... .......... .......... 34% 48.9M 10s\n", + "204150K .......... .......... .......... .......... .......... 34% 54.7M 10s\n", + "204200K .......... .......... .......... .......... .......... 34% 30.7M 10s\n", + "204250K .......... .......... .......... .......... .......... 34% 44.1M 10s\n", + "204300K .......... .......... .......... .......... .......... 34% 38.9M 10s\n", + "204350K .......... .......... .......... .......... .......... 34% 61.2M 10s\n", + "204400K .......... .......... .......... .......... .......... 34% 51.4M 10s\n", + "204450K .......... .......... .......... .......... .......... 34% 40.0M 10s\n", + "204500K .......... .......... .......... .......... .......... 34% 38.5M 10s\n", + "204550K .......... .......... .......... .......... .......... 34% 64.1M 10s\n", + "204600K .......... .......... .......... .......... .......... 34% 40.9M 10s\n", + "204650K .......... .......... .......... .......... .......... 34% 32.9M 10s\n", + "204700K .......... .......... .......... .......... .......... 34% 46.1M 10s\n", + "204750K .......... .......... .......... .......... .......... 34% 55.6M 10s\n", + "204800K .......... .......... .......... .......... .......... 34% 47.1M 10s\n", + "204850K .......... .......... .......... .......... .......... 34% 39.8M 10s\n", + "204900K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", + "204950K .......... .......... .......... .......... .......... 34% 51.3M 10s\n", + "205000K .......... .......... .......... .......... .......... 34% 38.0M 10s\n", + "205050K .......... .......... .......... .......... .......... 34% 40.0M 10s\n", + "205100K .......... .......... .......... .......... .......... 34% 46.5M 10s\n", + "205150K .......... .......... .......... .......... .......... 34% 43.6M 10s\n", + "205200K .......... .......... .......... .......... .......... 34% 57.3M 10s\n", + "205250K .......... .......... .......... .......... .......... 34% 57.6M 10s\n", + "205300K .......... .......... .......... .......... .......... 34% 33.8M 10s\n", + "205350K .......... .......... .......... .......... .......... 34% 56.2M 10s\n", + "205400K .......... .......... .......... .......... .......... 34% 38.4M 10s\n", + "205450K .......... .......... .......... .......... .......... 34% 60.4M 10s\n", + "205500K .......... .......... .......... .......... .......... 34% 44.2M 10s\n", + "205550K .......... .......... .......... .......... .......... 34% 43.1M 10s\n", + "205600K .......... .......... .......... .......... .......... 34% 47.7M 10s\n", + "205650K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", + "205700K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", + "205750K .......... .......... .......... .......... .......... 34% 36.8M 10s\n", + "205800K .......... .......... .......... .......... .......... 34% 31.9M 10s\n", + "205850K .......... .......... .......... .......... .......... 34% 50.5M 10s\n", + "205900K .......... .......... .......... .......... .......... 34% 43.8M 10s\n", + "205950K .......... .......... .......... .......... .......... 34% 45.5M 10s\n", + "206000K .......... .......... .......... .......... .......... 34% 33.1M 10s\n", + "206050K .......... .......... .......... .......... .......... 34% 48.6M 10s\n", + "206100K .......... .......... .......... .......... .......... 34% 48.4M 10s\n", + "206150K .......... .......... .......... .......... .......... 34% 44.0M 10s\n", + "206200K .......... .......... .......... .......... .......... 34% 26.0M 10s\n", + "206250K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", + "206300K .......... .......... .......... .......... .......... 34% 42.6M 10s\n", + "206350K .......... .......... .......... .......... .......... 34% 31.3M 10s\n", + "206400K .......... .......... .......... .......... .......... 34% 43.0M 10s\n", + "206450K .......... .......... .......... .......... .......... 34% 47.1M 10s\n", + "206500K .......... .......... .......... .......... .......... 34% 56.3M 10s\n", + "206550K .......... .......... .......... .......... .......... 34% 46.6M 10s\n", + "206600K .......... .......... .......... .......... .......... 34% 50.9M 10s\n", + "206650K .......... .......... .......... .......... .......... 34% 60.5M 10s\n", + "206700K .......... .......... .......... .......... .......... 34% 57.2M 10s\n", + "206750K .......... .......... .......... .......... .......... 34% 55.4M 10s\n", + "206800K .......... .......... .......... .......... .......... 34% 41.6M 10s\n", + "206850K .......... .......... .......... .......... .......... 34% 57.3M 10s\n", + "206900K .......... .......... .......... .......... .......... 34% 68.9M 10s\n", + "206950K .......... .......... .......... .......... .......... 34% 53.3M 10s\n", + "207000K .......... .......... .......... .......... .......... 34% 39.8M 10s\n", + "207050K .......... .......... .......... .......... .......... 34% 50.8M 10s\n", + "207100K .......... .......... .......... .......... .......... 34% 62.6M 10s\n", + "207150K .......... .......... .......... .......... .......... 34% 56.9M 10s\n", + "207200K .......... .......... .......... .......... .......... 34% 46.2M 10s\n", + "207250K .......... .......... .......... .......... .......... 34% 50.4M 10s\n", + "207300K .......... .......... .......... .......... .......... 34% 47.3M 10s\n", + "207350K .......... .......... .......... .......... .......... 34% 65.2M 10s\n", + "207400K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", + "207450K .......... .......... .......... .......... .......... 34% 63.0M 10s\n", + "207500K .......... .......... .......... .......... .......... 34% 51.2M 10s\n", + "207550K .......... .......... .......... .......... .......... 34% 53.1M 10s\n", + "207600K .......... .......... .......... .......... .......... 34% 4.60M 10s\n", + "207650K .......... .......... .......... .......... .......... 34% 60.7M 10s\n", + "207700K .......... .......... .......... .......... .......... 34% 66.8M 10s\n", + "207750K .......... .......... .......... .......... .......... 34% 65.8M 10s\n", + "207800K .......... .......... .......... .......... .......... 34% 56.4M 10s\n", + "207850K .......... .......... .......... .......... .......... 34% 27.6M 10s\n", + "207900K .......... .......... .......... .......... .......... 34% 47.8M 10s\n", + "207950K .......... .......... .......... .......... .......... 34% 60.9M 10s\n", + "208000K .......... .......... .......... .......... .......... 34% 55.8M 10s\n", + "208050K .......... .......... .......... .......... .......... 34% 64.6M 10s\n", + "208100K .......... .......... .......... .......... .......... 34% 35.0M 10s\n", + "208150K .......... .......... .......... .......... .......... 35% 50.5M 10s\n", + "208200K .......... .......... .......... .......... .......... 35% 48.8M 10s\n", + "208250K .......... .......... .......... .......... .......... 35% 62.9M 10s\n", + "208300K .......... .......... .......... .......... .......... 35% 33.0M 10s\n", + "208350K .......... .......... .......... .......... .......... 35% 45.5M 10s\n", + "208400K .......... .......... .......... .......... .......... 35% 46.1M 10s\n", + "208450K .......... .......... .......... .......... .......... 35% 61.9M 10s\n", + "208500K .......... .......... .......... .......... .......... 35% 65.3M 10s\n", + "208550K .......... .......... .......... .......... .......... 35% 28.2M 10s\n", + "208600K .......... .......... .......... .......... .......... 35% 45.4M 10s\n", + "208650K .......... .......... .......... .......... .......... 35% 63.8M 10s\n", + "208700K .......... .......... .......... .......... .......... 35% 65.6M 10s\n", + "208750K .......... .......... .......... .......... .......... 35% 40.6M 10s\n", + "208800K .......... .......... .......... .......... .......... 35% 59.6M 10s\n", + "208850K .......... .......... .......... .......... .......... 35% 56.2M 10s\n", + "208900K .......... .......... .......... .......... .......... 35% 58.1M 10s\n", + "208950K .......... .......... .......... .......... .......... 35% 69.5M 10s\n", + "209000K .......... .......... .......... .......... .......... 35% 22.9M 10s\n", + "209050K .......... .......... .......... .......... .......... 35% 51.6M 10s\n", + "209100K .......... .......... .......... .......... .......... 35% 63.3M 10s\n", + "209150K .......... .......... .......... .......... .......... 35% 63.2M 10s\n", + "209200K .......... .......... .......... .......... .......... 35% 27.0M 10s\n", + "209250K .......... .......... .......... .......... .......... 35% 41.3M 10s\n", + "209300K .......... .......... .......... .......... .......... 35% 57.2M 10s\n", + "209350K .......... .......... .......... .......... .......... 35% 62.7M 10s\n", + "209400K .......... .......... .......... .......... .......... 35% 56.2M 10s\n", + "209450K .......... .......... .......... .......... .......... 35% 10.0M 10s\n", + "209500K .......... .......... .......... .......... .......... 35% 61.3M 10s\n", + "209550K .......... .......... .......... .......... .......... 35% 63.2M 10s\n", + "209600K .......... .......... .......... .......... .......... 35% 59.0M 10s\n", + "209650K .......... .......... .......... .......... .......... 35% 65.8M 10s\n", + "209700K .......... .......... .......... .......... .......... 35% 27.3M 10s\n", + "209750K .......... .......... .......... .......... .......... 35% 60.4M 10s\n", + "209800K .......... .......... .......... .......... .......... 35% 8.30M 10s\n", + "209850K .......... .......... .......... .......... .......... 35% 70.1M 10s\n", + "209900K .......... .......... .......... .......... .......... 35% 63.5M 10s\n", + "209950K .......... .......... .......... .......... .......... 35% 61.4M 10s\n", + "210000K .......... .......... .......... .......... .......... 35% 59.9M 10s\n", + "210050K .......... .......... .......... .......... .......... 35% 67.9M 10s\n", + "210100K .......... .......... .......... .......... .......... 35% 60.0M 10s\n", + "210150K .......... .......... .......... .......... .......... 35% 47.3M 10s\n", + "210200K .......... .......... .......... .......... .......... 35% 50.1M 10s\n", + "210250K .......... .......... .......... .......... .......... 35% 56.0M 10s\n", + "210300K .......... .......... .......... .......... .......... 35% 71.1M 10s\n", + "210350K .......... .......... .......... .......... .......... 35% 58.1M 10s\n", + "210400K .......... .......... .......... .......... .......... 35% 53.4M 10s\n", + "210450K .......... .......... .......... .......... .......... 35% 64.7M 10s\n", + "210500K .......... .......... .......... .......... .......... 35% 64.0M 10s\n", + "210550K .......... .......... .......... .......... .......... 35% 30.6M 10s\n", + "210600K .......... .......... .......... .......... .......... 35% 39.0M 10s\n", + "210650K .......... .......... .......... .......... .......... 35% 63.7M 10s\n", + "210700K .......... .......... .......... .......... .......... 35% 65.1M 10s\n", + "210750K .......... .......... .......... .......... .......... 35% 39.8M 10s\n", + "210800K .......... .......... .......... .......... .......... 35% 46.3M 10s\n", + "210850K .......... .......... .......... .......... .......... 35% 49.5M 10s\n", + "210900K .......... .......... .......... .......... .......... 35% 60.1M 10s\n", + "210950K .......... .......... .......... .......... .......... 35% 64.3M 10s\n", + "211000K .......... .......... .......... .......... .......... 35% 37.1M 10s\n", + "211050K .......... .......... .......... .......... .......... 35% 51.2M 10s\n", + "211100K .......... .......... .......... .......... .......... 35% 49.0M 10s\n", + "211150K .......... .......... .......... .......... .......... 35% 66.5M 10s\n", + "211200K .......... .......... .......... .......... .......... 35% 55.4M 10s\n", + "211250K .......... .......... .......... .......... .......... 35% 49.9M 10s\n", + "211300K .......... .......... .......... .......... .......... 35% 47.7M 10s\n", + "211350K .......... .......... .......... .......... .......... 35% 50.9M 10s\n", + "211400K .......... .......... .......... .......... .......... 35% 55.3M 9s\n", + "211450K .......... .......... .......... .......... .......... 35% 48.8M 9s\n", + "211500K .......... .......... .......... .......... .......... 35% 47.4M 9s\n", + "211550K .......... .......... .......... .......... .......... 35% 43.7M 9s\n", + "211600K .......... .......... .......... .......... .......... 35% 51.2M 9s\n", + "211650K .......... .......... .......... .......... .......... 35% 66.6M 9s\n", + "211700K .......... .......... .......... .......... .......... 35% 65.6M 9s\n", + "211750K .......... .......... .......... .......... .......... 35% 33.2M 9s\n", + "211800K .......... .......... .......... .......... .......... 35% 40.5M 9s\n", + "211850K .......... .......... .......... .......... .......... 35% 65.8M 9s\n", + "211900K .......... .......... .......... .......... .......... 35% 69.8M 9s\n", + "211950K .......... .......... .......... .......... .......... 35% 51.3M 9s\n", + "212000K .......... .......... .......... .......... .......... 35% 45.4M 9s\n", + "212050K .......... .......... .......... .......... .......... 35% 53.5M 9s\n", + "212100K .......... .......... .......... .......... .......... 35% 62.8M 9s\n", + "212150K .......... .......... .......... .......... .......... 35% 69.9M 9s\n", + "212200K .......... .......... .......... .......... .......... 35% 31.8M 9s\n", + "212250K .......... .......... .......... .......... .......... 35% 44.0M 9s\n", + "212300K .......... .......... .......... .......... .......... 35% 56.2M 9s\n", + "212350K .......... .......... .......... .......... .......... 35% 68.2M 9s\n", + "212400K .......... .......... .......... .......... .......... 35% 5.17M 9s\n", + "212450K .......... .......... .......... .......... .......... 35% 63.5M 9s\n", + "212500K .......... .......... .......... .......... .......... 35% 66.2M 9s\n", + "212550K .......... .......... .......... .......... .......... 35% 65.8M 9s\n", + "212600K .......... .......... .......... .......... .......... 35% 56.7M 9s\n", + "212650K .......... .......... .......... .......... .......... 35% 67.7M 9s\n", + "212700K .......... .......... .......... .......... .......... 35% 15.6M 9s\n", + "212750K .......... .......... .......... .......... .......... 35% 66.6M 9s\n", + "212800K .......... .......... .......... .......... .......... 35% 58.3M 9s\n", + "212850K .......... .......... .......... .......... .......... 35% 59.2M 9s\n", + "212900K .......... .......... .......... .......... .......... 35% 54.7M 9s\n", + "212950K .......... .......... .......... .......... .......... 35% 64.0M 9s\n", + "213000K .......... .......... .......... .......... .......... 35% 41.4M 9s\n", + "213050K .......... .......... .......... .......... .......... 35% 53.1M 9s\n", + "213100K .......... .......... .......... .......... .......... 35% 20.4M 9s\n", + "213150K .......... .......... .......... .......... .......... 35% 61.1M 9s\n", + "213200K .......... .......... .......... .......... .......... 35% 46.5M 9s\n", + "213250K .......... .......... .......... .......... .......... 35% 52.4M 9s\n", + "213300K .......... .......... .......... .......... .......... 35% 71.8M 9s\n", + "213350K .......... .......... .......... .......... .......... 35% 67.7M 9s\n", + "213400K .......... .......... .......... .......... .......... 35% 44.5M 9s\n", + "213450K .......... .......... .......... .......... .......... 35% 47.8M 9s\n", + "213500K .......... .......... .......... .......... .......... 35% 52.3M 9s\n", + "213550K .......... .......... .......... .......... .......... 35% 64.6M 9s\n", + "213600K .......... .......... .......... .......... .......... 35% 57.6M 9s\n", + "213650K .......... .......... .......... .......... .......... 35% 58.5M 9s\n", + "213700K .......... .......... .......... .......... .......... 35% 52.2M 9s\n", + "213750K .......... .......... .......... .......... .......... 35% 56.1M 9s\n", + "213800K .......... .......... .......... .......... .......... 35% 50.0M 9s\n", + "213850K .......... .......... .......... .......... .......... 35% 64.4M 9s\n", + "213900K .......... .......... .......... .......... .......... 35% 55.4M 9s\n", + "213950K .......... .......... .......... .......... .......... 35% 50.2M 9s\n", + "214000K .......... .......... .......... .......... .......... 35% 53.3M 9s\n", + "214050K .......... .......... .......... .......... .......... 35% 58.6M 9s\n", + "214100K .......... .......... .......... .......... .......... 36% 72.6M 9s\n", + "214150K .......... .......... .......... .......... .......... 36% 58.3M 9s\n", + "214200K .......... .......... .......... .......... .......... 36% 45.8M 9s\n", + "214250K .......... .......... .......... .......... .......... 36% 56.4M 9s\n", + "214300K .......... .......... .......... .......... .......... 36% 47.7M 9s\n", + "214350K .......... .......... .......... .......... .......... 36% 65.9M 9s\n", + "214400K .......... .......... .......... .......... .......... 36% 36.0M 9s\n", + "214450K .......... .......... .......... .......... .......... 36% 53.9M 9s\n", + "214500K .......... .......... .......... .......... .......... 36% 44.9M 9s\n", + "214550K .......... .......... .......... .......... .......... 36% 61.4M 9s\n", + "214600K .......... .......... .......... .......... .......... 36% 55.3M 9s\n", + "214650K .......... .......... .......... .......... .......... 36% 56.4M 9s\n", + "214700K .......... .......... .......... .......... .......... 36% 60.1M 9s\n", + "214750K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", + "214800K .......... .......... .......... .......... .......... 36% 53.3M 9s\n", + "214850K .......... .......... .......... .......... .......... 36% 3.97M 9s\n", + "214900K .......... .......... .......... .......... .......... 36% 59.1M 9s\n", + "214950K .......... .......... .......... .......... .......... 36% 71.1M 9s\n", + "215000K .......... .......... .......... .......... .......... 36% 54.2M 9s\n", + "215050K .......... .......... .......... .......... .......... 36% 68.1M 9s\n", + "215100K .......... .......... .......... .......... .......... 36% 63.9M 9s\n", + "215150K .......... .......... .......... .......... .......... 36% 41.0M 9s\n", + "215200K .......... .......... .......... .......... .......... 36% 43.9M 9s\n", + "215250K .......... .......... .......... .......... .......... 36% 51.5M 9s\n", + "215300K .......... .......... .......... .......... .......... 36% 64.2M 9s\n", + "215350K .......... .......... .......... .......... .......... 36% 56.8M 9s\n", + "215400K .......... .......... .......... .......... .......... 36% 5.47M 9s\n", + "215450K .......... .......... .......... .......... .......... 36% 67.2M 9s\n", + "215500K .......... .......... .......... .......... .......... 36% 47.0M 9s\n", + "215550K .......... .......... .......... .......... .......... 36% 53.1M 9s\n", + "215600K .......... .......... .......... .......... .......... 36% 56.5M 9s\n", + "215650K .......... .......... .......... .......... .......... 36% 62.3M 9s\n", + "215700K .......... .......... .......... .......... .......... 36% 41.4M 9s\n", + "215750K .......... .......... .......... .......... .......... 36% 47.0M 9s\n", + "215800K .......... .......... .......... .......... .......... 36% 52.6M 9s\n", + "215850K .......... .......... .......... .......... .......... 36% 64.9M 9s\n", + "215900K .......... .......... .......... .......... .......... 36% 61.3M 9s\n", + "215950K .......... .......... .......... .......... .......... 36% 48.4M 9s\n", + "216000K .......... .......... .......... .......... .......... 36% 42.0M 9s\n", + "216050K .......... .......... .......... .......... .......... 36% 50.9M 9s\n", + "216100K .......... .......... .......... .......... .......... 36% 50.1M 9s\n", + "216150K .......... .......... .......... .......... .......... 36% 49.6M 9s\n", + "216200K .......... .......... .......... .......... .......... 36% 30.9M 9s\n", + "216250K .......... .......... .......... .......... .......... 36% 54.8M 9s\n", + "216300K .......... .......... .......... .......... .......... 36% 64.8M 9s\n", + "216350K .......... .......... .......... .......... .......... 36% 50.1M 9s\n", + "216400K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", + "216450K .......... .......... .......... .......... .......... 36% 50.4M 9s\n", + "216500K .......... .......... .......... .......... .......... 36% 58.5M 9s\n", + "216550K .......... .......... .......... .......... .......... 36% 65.7M 9s\n", + "216600K .......... .......... .......... .......... .......... 36% 37.1M 9s\n", + "216650K .......... .......... .......... .......... .......... 36% 43.7M 9s\n", + "216700K .......... .......... .......... .......... .......... 36% 38.3M 9s\n", + "216750K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", + "216800K .......... .......... .......... .......... .......... 36% 36.3M 9s\n", + "216850K .......... .......... .......... .......... .......... 36% 38.6M 9s\n", + "216900K .......... .......... .......... .......... .......... 36% 41.3M 9s\n", + "216950K .......... .......... .......... .......... .......... 36% 46.6M 9s\n", + "217000K .......... .......... .......... .......... .......... 36% 33.9M 9s\n", + "217050K .......... .......... .......... .......... .......... 36% 34.9M 9s\n", + "217100K .......... .......... .......... .......... .......... 36% 37.6M 9s\n", + "217150K .......... .......... .......... .......... .......... 36% 39.9M 9s\n", + "217200K .......... .......... .......... .......... .......... 36% 37.0M 9s\n", + "217250K .......... .......... .......... .......... .......... 36% 40.6M 9s\n", + "217300K .......... .......... .......... .......... .......... 36% 62.9M 9s\n", + "217350K .......... .......... .......... .......... .......... 36% 58.7M 9s\n", + "217400K .......... .......... .......... .......... .......... 36% 36.0M 9s\n", + "217450K .......... .......... .......... .......... .......... 36% 38.5M 9s\n", + "217500K .......... .......... .......... .......... .......... 36% 53.5M 9s\n", + "217550K .......... .......... .......... .......... .......... 36% 53.0M 9s\n", + "217600K .......... .......... .......... .......... .......... 36% 42.5M 9s\n", + "217650K .......... .......... .......... .......... .......... 36% 55.6M 9s\n", + "217700K .......... .......... .......... .......... .......... 36% 43.5M 9s\n", + "217750K .......... .......... .......... .......... .......... 36% 44.4M 9s\n", + "217800K .......... .......... .......... .......... .......... 36% 49.4M 9s\n", + "217850K .......... .......... .......... .......... .......... 36% 44.3M 9s\n", + "217900K .......... .......... .......... .......... .......... 36% 50.6M 9s\n", + "217950K .......... .......... .......... .......... .......... 36% 52.6M 9s\n", + "218000K .......... .......... .......... .......... .......... 36% 63.0M 9s\n", + "218050K .......... .......... .......... .......... .......... 36% 56.0M 9s\n", + "218100K .......... .......... .......... .......... .......... 36% 56.9M 9s\n", + "218150K .......... .......... .......... .......... .......... 36% 54.2M 9s\n", + "218200K .......... .......... .......... .......... .......... 36% 43.7M 9s\n", + "218250K .......... .......... .......... .......... .......... 36% 60.3M 9s\n", + "218300K .......... .......... .......... .......... .......... 36% 54.0M 9s\n", + "218350K .......... .......... .......... .......... .......... 36% 55.0M 9s\n", + "218400K .......... .......... .......... .......... .......... 36% 43.5M 9s\n", + "218450K .......... .......... .......... .......... .......... 36% 43.0M 9s\n", + "218500K .......... .......... .......... .......... .......... 36% 58.1M 9s\n", + "218550K .......... .......... .......... .......... .......... 36% 40.2M 9s\n", + "218600K .......... .......... .......... .......... .......... 36% 39.3M 9s\n", + "218650K .......... .......... .......... .......... .......... 36% 45.9M 9s\n", + "218700K .......... .......... .......... .......... .......... 36% 48.0M 9s\n", + "218750K .......... .......... .......... .......... .......... 36% 49.0M 9s\n", + "218800K .......... .......... .......... .......... .......... 36% 27.4M 9s\n", + "218850K .......... .......... .......... .......... .......... 36% 38.9M 9s\n", + "218900K .......... .......... .......... .......... .......... 36% 28.7M 9s\n", + "218950K .......... .......... .......... .......... .......... 36% 32.1M 9s\n", + "219000K .......... .......... .......... .......... .......... 36% 42.2M 9s\n", + "219050K .......... .......... .......... .......... .......... 36% 46.3M 9s\n", + "219100K .......... .......... .......... .......... .......... 36% 47.2M 9s\n", + "219150K .......... .......... .......... .......... .......... 36% 45.2M 9s\n", + "219200K .......... .......... .......... .......... .......... 36% 40.2M 9s\n", + "219250K .......... .......... .......... .......... .......... 36% 45.5M 9s\n", + "219300K .......... .......... .......... .......... .......... 36% 45.7M 9s\n", + "219350K .......... .......... .......... .......... .......... 36% 46.8M 9s\n", + "219400K .......... .......... .......... .......... .......... 36% 50.4M 9s\n", + "219450K .......... .......... .......... .......... .......... 36% 60.9M 9s\n", + "219500K .......... .......... .......... .......... .......... 36% 52.7M 9s\n", + "219550K .......... .......... .......... .......... .......... 36% 46.3M 9s\n", + "219600K .......... .......... .......... .......... .......... 36% 45.4M 9s\n", + "219650K .......... .......... .......... .......... .......... 36% 66.0M 9s\n", + "219700K .......... .......... .......... .......... .......... 36% 41.2M 9s\n", + "219750K .......... .......... .......... .......... .......... 36% 30.0M 9s\n", + "219800K .......... .......... .......... .......... .......... 36% 26.9M 9s\n", + "219850K .......... .......... .......... .......... .......... 36% 64.1M 9s\n", + "219900K .......... .......... .......... .......... .......... 36% 64.4M 9s\n", + "219950K .......... .......... .......... .......... .......... 36% 44.3M 9s\n", + "220000K .......... .......... .......... .......... .......... 36% 41.3M 9s\n", + "220050K .......... .......... .......... .......... .......... 37% 40.1M 9s\n", + "220100K .......... .......... .......... .......... .......... 37% 35.7M 9s\n", + "220150K .......... .......... .......... .......... .......... 37% 36.5M 9s\n", + "220200K .......... .......... .......... .......... .......... 37% 29.8M 9s\n", + "220250K .......... .......... .......... .......... .......... 37% 58.3M 9s\n", + "220300K .......... .......... .......... .......... .......... 37% 56.7M 9s\n", + "220350K .......... .......... .......... .......... .......... 37% 43.1M 9s\n", + "220400K .......... .......... .......... .......... .......... 37% 41.2M 9s\n", + "220450K .......... .......... .......... .......... .......... 37% 52.9M 9s\n", + "220500K .......... .......... .......... .......... .......... 37% 3.99M 9s\n", + "220550K .......... .......... .......... .......... .......... 37% 40.2M 9s\n", + "220600K .......... .......... .......... .......... .......... 37% 29.8M 9s\n", + "220650K .......... .......... .......... .......... .......... 37% 32.5M 9s\n", + "220700K .......... .......... .......... .......... .......... 37% 24.9M 9s\n", + "220750K .......... .......... .......... .......... .......... 37% 51.9M 9s\n", + "220800K .......... .......... .......... .......... .......... 37% 53.4M 9s\n", + "220850K .......... .......... .......... .......... .......... 37% 38.8M 9s\n", + "220900K .......... .......... .......... .......... .......... 37% 31.4M 9s\n", + "220950K .......... .......... .......... .......... .......... 37% 34.4M 9s\n", + "221000K .......... .......... .......... .......... .......... 37% 43.5M 9s\n", + "221050K .......... .......... .......... .......... .......... 37% 60.2M 9s\n", + "221100K .......... .......... .......... .......... .......... 37% 45.6M 9s\n", + "221150K .......... .......... .......... .......... .......... 37% 46.0M 9s\n", + "221200K .......... .......... .......... .......... .......... 37% 49.1M 9s\n", + "221250K .......... .......... .......... .......... .......... 37% 58.4M 9s\n", + "221300K .......... .......... .......... .......... .......... 37% 35.1M 9s\n", + "221350K .......... .......... .......... .......... .......... 37% 41.1M 9s\n", + "221400K .......... .......... .......... .......... .......... 37% 43.7M 9s\n", + "221450K .......... .......... .......... .......... .......... 37% 50.9M 9s\n", + "221500K .......... .......... .......... .......... .......... 37% 53.2M 9s\n", + "221550K .......... .......... .......... .......... .......... 37% 51.5M 9s\n", + "221600K .......... .......... .......... .......... .......... 37% 5.35M 9s\n", + "221650K .......... .......... .......... .......... .......... 37% 42.1M 9s\n", + "221700K .......... .......... .......... .......... .......... 37% 64.2M 9s\n", + "221750K .......... .......... .......... .......... .......... 37% 62.6M 9s\n", + "221800K .......... .......... .......... .......... .......... 37% 49.1M 9s\n", + "221850K .......... .......... .......... .......... .......... 37% 44.2M 9s\n", + "221900K .......... .......... .......... .......... .......... 37% 43.5M 9s\n", + "221950K .......... .......... .......... .......... .......... 37% 66.4M 9s\n", + "222000K .......... .......... .......... .......... .......... 37% 60.0M 9s\n", + "222050K .......... .......... .......... .......... .......... 37% 57.3M 9s\n", + "222100K .......... .......... .......... .......... .......... 37% 61.9M 9s\n", + "222150K .......... .......... .......... .......... .......... 37% 57.6M 9s\n", + "222200K .......... .......... .......... .......... .......... 37% 41.2M 9s\n", + "222250K .......... .......... .......... .......... .......... 37% 61.2M 9s\n", + "222300K .......... .......... .......... .......... .......... 37% 46.6M 9s\n", + "222350K .......... .......... .......... .......... .......... 37% 62.8M 9s\n", + "222400K .......... .......... .......... .......... .......... 37% 5.97M 9s\n", + "222450K .......... .......... .......... .......... .......... 37% 44.3M 9s\n", + "222500K .......... .......... .......... .......... .......... 37% 43.2M 9s\n", + "222550K .......... .......... .......... .......... .......... 37% 37.2M 9s\n", + "222600K .......... .......... .......... .......... .......... 37% 35.1M 9s\n", + "222650K .......... .......... .......... .......... .......... 37% 47.7M 9s\n", + "222700K .......... .......... .......... .......... .......... 37% 64.0M 9s\n", + "222750K .......... .......... .......... .......... .......... 37% 59.8M 9s\n", + "222800K .......... .......... .......... .......... .......... 37% 48.6M 9s\n", + "222850K .......... .......... .......... .......... .......... 37% 43.6M 9s\n", + "222900K .......... .......... .......... .......... .......... 37% 37.2M 9s\n", + "222950K .......... .......... .......... .......... .......... 37% 59.1M 9s\n", + "223000K .......... .......... .......... .......... .......... 37% 50.0M 9s\n", + "223050K .......... .......... .......... .......... .......... 37% 60.6M 9s\n", + "223100K .......... .......... .......... .......... .......... 37% 32.7M 9s\n", + "223150K .......... .......... .......... .......... .......... 37% 49.9M 9s\n", + "223200K .......... .......... .......... .......... .......... 37% 42.2M 9s\n", + "223250K .......... .......... .......... .......... .......... 37% 53.3M 9s\n", + "223300K .......... .......... .......... .......... .......... 37% 41.9M 9s\n", + "223350K .......... .......... .......... .......... .......... 37% 42.4M 9s\n", + "223400K .......... .......... .......... .......... .......... 37% 44.8M 9s\n", + "223450K .......... .......... .......... .......... .......... 37% 48.3M 9s\n", + "223500K .......... .......... .......... .......... .......... 37% 40.2M 9s\n", + "223550K .......... .......... .......... .......... .......... 37% 46.7M 9s\n", + "223600K .......... .......... .......... .......... .......... 37% 51.8M 9s\n", + "223650K .......... .......... .......... .......... .......... 37% 55.0M 9s\n", + "223700K .......... .......... .......... .......... .......... 37% 46.8M 9s\n", + "223750K .......... .......... .......... .......... .......... 37% 47.1M 9s\n", + "223800K .......... .......... .......... .......... .......... 37% 38.8M 9s\n", + "223850K .......... .......... .......... .......... .......... 37% 59.1M 9s\n", + "223900K .......... .......... .......... .......... .......... 37% 58.6M 9s\n", + "223950K .......... .......... .......... .......... .......... 37% 50.7M 9s\n", + "224000K .......... .......... .......... .......... .......... 37% 33.9M 9s\n", + "224050K .......... .......... .......... .......... .......... 37% 54.0M 9s\n", + "224100K .......... .......... .......... .......... .......... 37% 57.9M 9s\n", + "224150K .......... .......... .......... .......... .......... 37% 51.8M 9s\n", + "224200K .......... .......... .......... .......... .......... 37% 38.7M 9s\n", + "224250K .......... .......... .......... .......... .......... 37% 54.8M 9s\n", + "224300K .......... .......... .......... .......... .......... 37% 57.4M 9s\n", + "224350K .......... .......... .......... .......... .......... 37% 58.5M 9s\n", + "224400K .......... .......... .......... .......... .......... 37% 48.6M 9s\n", + "224450K .......... .......... .......... .......... .......... 37% 48.2M 9s\n", + "224500K .......... .......... .......... .......... .......... 37% 48.0M 9s\n", + "224550K .......... .......... .......... .......... .......... 37% 40.0M 9s\n", + "224600K .......... .......... .......... .......... .......... 37% 49.3M 9s\n", + "224650K .......... .......... .......... .......... .......... 37% 53.3M 9s\n", + "224700K .......... .......... .......... .......... .......... 37% 57.7M 9s\n", + "224750K .......... .......... .......... .......... .......... 37% 45.7M 9s\n", + "224800K .......... .......... .......... .......... .......... 37% 54.1M 9s\n", + "224850K .......... .......... .......... .......... .......... 37% 66.2M 9s\n", + "224900K .......... .......... .......... .......... .......... 37% 53.1M 9s\n", + "224950K .......... .......... .......... .......... .......... 37% 51.0M 9s\n", + "225000K .......... .......... .......... .......... .......... 37% 29.7M 9s\n", + "225050K .......... .......... .......... .......... .......... 37% 34.7M 9s\n", + "225100K .......... .......... .......... .......... .......... 37% 32.8M 9s\n", + "225150K .......... .......... .......... .......... .......... 37% 32.8M 9s\n", + "225200K .......... .......... .......... .......... .......... 37% 34.8M 9s\n", + "225250K .......... .......... .......... .......... .......... 37% 54.0M 9s\n", + "225300K .......... .......... .......... .......... .......... 37% 64.5M 9s\n", + "225350K .......... .......... .......... .......... .......... 37% 47.3M 9s\n", + "225400K .......... .......... .......... .......... .......... 37% 32.9M 9s\n", + "225450K .......... .......... .......... .......... .......... 37% 59.7M 9s\n", + "225500K .......... .......... .......... .......... .......... 37% 49.9M 9s\n", + "225550K .......... .......... .......... .......... .......... 37% 41.9M 9s\n", + "225600K .......... .......... .......... .......... .......... 37% 53.6M 9s\n", + "225650K .......... .......... .......... .......... .......... 37% 57.0M 9s\n", + "225700K .......... .......... .......... .......... .......... 37% 63.2M 9s\n", + "225750K .......... .......... .......... .......... .......... 37% 58.3M 9s\n", + "225800K .......... .......... .......... .......... .......... 37% 48.8M 9s\n", + "225850K .......... .......... .......... .......... .......... 37% 68.4M 9s\n", + "225900K .......... .......... .......... .......... .......... 37% 56.0M 9s\n", + "225950K .......... .......... .......... .......... .......... 38% 58.8M 9s\n", + "226000K .......... .......... .......... .......... .......... 38% 50.1M 9s\n", + "226050K .......... .......... .......... .......... .......... 38% 63.3M 9s\n", + "226100K .......... .......... .......... .......... .......... 38% 57.2M 9s\n", + "226150K .......... .......... .......... .......... .......... 38% 58.7M 9s\n", + "226200K .......... .......... .......... .......... .......... 38% 55.0M 9s\n", + "226250K .......... .......... .......... .......... .......... 38% 49.9M 9s\n", + "226300K .......... .......... .......... .......... .......... 38% 64.6M 9s\n", + "226350K .......... .......... .......... .......... .......... 38% 58.0M 9s\n", + "226400K .......... .......... .......... .......... .......... 38% 44.9M 9s\n", + "226450K .......... .......... .......... .......... .......... 38% 55.9M 9s\n", + "226500K .......... .......... .......... .......... .......... 38% 56.7M 9s\n", + "226550K .......... .......... .......... .......... .......... 38% 59.6M 9s\n", + "226600K .......... .......... .......... .......... .......... 38% 56.0M 9s\n", + "226650K .......... .......... .......... .......... .......... 38% 61.2M 9s\n", + "226700K .......... .......... .......... .......... .......... 38% 61.8M 9s\n", + "226750K .......... .......... .......... .......... .......... 38% 66.6M 9s\n", + "226800K .......... .......... .......... .......... .......... 38% 3.80M 9s\n", + "226850K .......... .......... .......... .......... .......... 38% 63.9M 9s\n", + "226900K .......... .......... .......... .......... .......... 38% 62.5M 9s\n", + "226950K .......... .......... .......... .......... .......... 38% 63.4M 9s\n", + "227000K .......... .......... .......... .......... .......... 38% 53.1M 9s\n", + "227050K .......... .......... .......... .......... .......... 38% 60.7M 9s\n", + "227100K .......... .......... .......... .......... .......... 38% 50.3M 9s\n", + "227150K .......... .......... .......... .......... .......... 38% 56.4M 9s\n", + "227200K .......... .......... .......... .......... .......... 38% 58.4M 9s\n", + "227250K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", + "227300K .......... .......... .......... .......... .......... 38% 66.3M 9s\n", + "227350K .......... .......... .......... .......... .......... 38% 48.2M 9s\n", + "227400K .......... .......... .......... .......... .......... 38% 42.5M 9s\n", + "227450K .......... .......... .......... .......... .......... 38% 68.2M 9s\n", + "227500K .......... .......... .......... .......... .......... 38% 64.4M 9s\n", + "227550K .......... .......... .......... .......... .......... 38% 65.7M 9s\n", + "227600K .......... .......... .......... .......... .......... 38% 50.1M 9s\n", + "227650K .......... .......... .......... .......... .......... 38% 68.0M 9s\n", + "227700K .......... .......... .......... .......... .......... 38% 60.5M 9s\n", + "227750K .......... .......... .......... .......... .......... 38% 57.8M 9s\n", + "227800K .......... .......... .......... .......... .......... 38% 54.7M 9s\n", + "227850K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", + "227900K .......... .......... .......... .......... .......... 38% 66.8M 9s\n", + "227950K .......... .......... .......... .......... .......... 38% 62.3M 9s\n", + "228000K .......... .......... .......... .......... .......... 38% 54.6M 9s\n", + "228050K .......... .......... .......... .......... .......... 38% 58.3M 9s\n", + "228100K .......... .......... .......... .......... .......... 38% 62.3M 9s\n", + "228150K .......... .......... .......... .......... .......... 38% 63.5M 9s\n", + "228200K .......... .......... .......... .......... .......... 38% 49.2M 9s\n", + "228250K .......... .......... .......... .......... .......... 38% 63.8M 9s\n", + "228300K .......... .......... .......... .......... .......... 38% 59.5M 9s\n", + "228350K .......... .......... .......... .......... .......... 38% 71.2M 9s\n", + "228400K .......... .......... .......... .......... .......... 38% 57.9M 9s\n", + "228450K .......... .......... .......... .......... .......... 38% 67.8M 9s\n", + "228500K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", + "228550K .......... .......... .......... .......... .......... 38% 54.8M 9s\n", + "228600K .......... .......... .......... .......... .......... 38% 52.0M 9s\n", + "228650K .......... .......... .......... .......... .......... 38% 64.2M 9s\n", + "228700K .......... .......... .......... .......... .......... 38% 65.1M 9s\n", + "228750K .......... .......... .......... .......... .......... 38% 61.7M 9s\n", + "228800K .......... .......... .......... .......... .......... 38% 57.3M 9s\n", + "228850K .......... .......... .......... .......... .......... 38% 62.9M 9s\n", + "228900K .......... .......... .......... .......... .......... 38% 63.0M 9s\n", + "228950K .......... .......... .......... .......... .......... 38% 65.8M 9s\n", + "229000K .......... .......... .......... .......... .......... 38% 53.8M 9s\n", + "229050K .......... .......... .......... .......... .......... 38% 64.8M 9s\n", + "229100K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", + "229150K .......... .......... .......... .......... .......... 38% 64.9M 9s\n", + "229200K .......... .......... .......... .......... .......... 38% 58.1M 9s\n", + "229250K .......... .......... .......... .......... .......... 38% 58.4M 9s\n", + "229300K .......... .......... .......... .......... .......... 38% 65.5M 9s\n", + "229350K .......... .......... .......... .......... .......... 38% 61.3M 9s\n", + "229400K .......... .......... .......... .......... .......... 38% 46.8M 9s\n", + "229450K .......... .......... .......... .......... .......... 38% 68.3M 9s\n", + "229500K .......... .......... .......... .......... .......... 38% 64.2M 9s\n", + "229550K .......... .......... .......... .......... .......... 38% 64.8M 9s\n", + "229600K .......... .......... .......... .......... .......... 38% 61.2M 9s\n", + "229650K .......... .......... .......... .......... .......... 38% 26.1M 9s\n", + "229700K .......... .......... .......... .......... .......... 38% 65.4M 9s\n", + "229750K .......... .......... .......... .......... .......... 38% 13.9M 9s\n", + "229800K .......... .......... .......... .......... .......... 38% 46.7M 9s\n", + "229850K .......... .......... .......... .......... .......... 38% 13.3M 9s\n", + "229900K .......... .......... .......... .......... .......... 38% 57.8M 9s\n", + "229950K .......... .......... .......... .......... .......... 38% 15.1M 9s\n", + "230000K .......... .......... .......... .......... .......... 38% 43.6M 9s\n", + "230050K .......... .......... .......... .......... .......... 38% 3.74M 9s\n", + "230100K .......... .......... .......... .......... .......... 38% 4.14M 9s\n", + "230150K .......... .......... .......... .......... .......... 38% 56.1M 9s\n", + "230200K .......... .......... .......... .......... .......... 38% 53.8M 9s\n", + "230250K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", + "230300K .......... .......... .......... .......... .......... 38% 19.4M 9s\n", + "230350K .......... .......... .......... .......... .......... 38% 54.7M 9s\n", + "230400K .......... .......... .......... .......... .......... 38% 12.7M 9s\n", + "230450K .......... .......... .......... .......... .......... 38% 53.5M 9s\n", + "230500K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", + "230550K .......... .......... .......... .......... .......... 38% 49.6M 9s\n", + "230600K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", + "230650K .......... .......... .......... .......... .......... 38% 39.9M 9s\n", + "230700K .......... .......... .......... .......... .......... 38% 14.3M 9s\n", + "230750K .......... .......... .......... .......... .......... 38% 47.8M 9s\n", + "230800K .......... .......... .......... .......... .......... 38% 55.7M 9s\n", + "230850K .......... .......... .......... .......... .......... 38% 15.3M 9s\n", + "230900K .......... .......... .......... .......... .......... 38% 51.5M 9s\n", + "230950K .......... .......... .......... .......... .......... 38% 13.1M 9s\n", + "231000K .......... .......... .......... .......... .......... 38% 50.7M 9s\n", + "231050K .......... .......... .......... .......... .......... 38% 14.2M 9s\n", + "231100K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", + "231150K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", + "231200K .......... .......... .......... .......... .......... 38% 34.0M 9s\n", + "231250K .......... .......... .......... .......... .......... 38% 17.2M 9s\n", + "231300K .......... .......... .......... .......... .......... 38% 51.1M 9s\n", + "231350K .......... .......... .......... .......... .......... 38% 13.0M 9s\n", + "231400K .......... .......... .......... .......... .......... 38% 46.9M 9s\n", + "231450K .......... .......... .......... .......... .......... 38% 14.6M 9s\n", + "231500K .......... .......... .......... .......... .......... 38% 53.2M 9s\n", + "231550K .......... .......... .......... .......... .......... 38% 43.1M 9s\n", + "231600K .......... .......... .......... .......... .......... 38% 16.0M 9s\n", + "231650K .......... .......... .......... .......... .......... 38% 39.4M 9s\n", + "231700K .......... .......... .......... .......... .......... 38% 15.1M 9s\n", + "231750K .......... .......... .......... .......... .......... 38% 37.9M 9s\n", + "231800K .......... .......... .......... .......... .......... 38% 17.9M 9s\n", + "231850K .......... .......... .......... .......... .......... 38% 38.2M 9s\n", + "231900K .......... .......... .......... .......... .......... 39% 14.9M 9s\n", + "231950K .......... .......... .......... .......... .......... 39% 48.3M 9s\n", + "232000K .......... .......... .......... .......... .......... 39% 13.9M 9s\n", + "232050K .......... .......... .......... .......... .......... 39% 40.5M 9s\n", + "232100K .......... .......... .......... .......... .......... 39% 50.9M 9s\n", + "232150K .......... .......... .......... .......... .......... 39% 14.0M 9s\n", + "232200K .......... .......... .......... .......... .......... 39% 49.1M 9s\n", + "232250K .......... .......... .......... .......... .......... 39% 15.0M 9s\n", + "232300K .......... .......... .......... .......... .......... 39% 43.4M 9s\n", + "232350K .......... .......... .......... .......... .......... 39% 17.2M 9s\n", + "232400K .......... .......... .......... .......... .......... 39% 44.6M 9s\n", + "232450K .......... .......... .......... .......... .......... 39% 36.1M 9s\n", + "232500K .......... .......... .......... .......... .......... 39% 14.8M 9s\n", + "232550K .......... .......... .......... .......... .......... 39% 55.2M 9s\n", + "232600K .......... .......... .......... .......... .......... 39% 11.3M 9s\n", + "232650K .......... .......... .......... .......... .......... 39% 73.0M 9s\n", + "232700K .......... .......... .......... .......... .......... 39% 13.2M 9s\n", + "232750K .......... .......... .......... .......... .......... 39% 59.8M 9s\n", + "232800K .......... .......... .......... .......... .......... 39% 52.9M 9s\n", + "232850K .......... .......... .......... .......... .......... 39% 12.4M 9s\n", + "232900K .......... .......... .......... .......... .......... 39% 68.5M 9s\n", + "232950K .......... .......... .......... .......... .......... 39% 13.0M 9s\n", + "233000K .......... .......... .......... .......... .......... 39% 55.1M 9s\n", + "233050K .......... .......... .......... .......... .......... 39% 12.4M 9s\n", + "233100K .......... .......... .......... .......... .......... 39% 57.2M 9s\n", + "233150K .......... .......... .......... .......... .......... 39% 67.6M 9s\n", + "233200K .......... .......... .......... .......... .......... 39% 12.8M 9s\n", + "233250K .......... .......... .......... .......... .......... 39% 68.0M 9s\n", + "233300K .......... .......... .......... .......... .......... 39% 12.1M 9s\n", + "233350K .......... .......... .......... .......... .......... 39% 59.9M 9s\n", + "233400K .......... .......... .......... .......... .......... 39% 14.7M 9s\n", + "233450K .......... .......... .......... .......... .......... 39% 46.9M 9s\n", + "233500K .......... .......... .......... .......... .......... 39% 70.7M 9s\n", + "233550K .......... .......... .......... .......... .......... 39% 13.2M 9s\n", + "233600K .......... .......... .......... .......... .......... 39% 60.5M 9s\n", + "233650K .......... .......... .......... .......... .......... 39% 13.7M 9s\n", + "233700K .......... .......... .......... .......... .......... 39% 48.8M 9s\n", + "233750K .......... .......... .......... .......... .......... 39% 63.9M 9s\n", + "233800K .......... .......... .......... .......... .......... 39% 12.7M 9s\n", + "233850K .......... .......... .......... .......... .......... 39% 69.0M 9s\n", + "233900K .......... .......... .......... .......... .......... 39% 14.3M 9s\n", + "233950K .......... .......... .......... .......... .......... 39% 52.2M 9s\n", + "234000K .......... .......... .......... .......... .......... 39% 53.3M 9s\n", + "234050K .......... .......... .......... .......... .......... 39% 13.6M 9s\n", + "234100K .......... .......... .......... .......... .......... 39% 65.9M 9s\n", + "234150K .......... .......... .......... .......... .......... 39% 3.97M 9s\n", + "234200K .......... .......... .......... .......... .......... 39% 57.1M 9s\n", + "234250K .......... .......... .......... .......... .......... 39% 69.4M 9s\n", + "234300K .......... .......... .......... .......... .......... 39% 15.3M 9s\n", + "234350K .......... .......... .......... .......... .......... 39% 55.5M 9s\n", + "234400K .......... .......... .......... .......... .......... 39% 64.0M 9s\n", + "234450K .......... .......... .......... .......... .......... 39% 14.2M 9s\n", + "234500K .......... .......... .......... .......... .......... 39% 56.6M 9s\n", + "234550K .......... .......... .......... .......... .......... 39% 66.2M 9s\n", + "234600K .......... .......... .......... .......... .......... 39% 9.30M 9s\n", + "234650K .......... .......... .......... .......... .......... 39% 67.7M 9s\n", + "234700K .......... .......... .......... .......... .......... 39% 31.9M 9s\n", + "234750K .......... .......... .......... .......... .......... 39% 22.2M 9s\n", + "234800K .......... .......... .......... .......... .......... 39% 58.7M 9s\n", + "234850K .......... .......... .......... .......... .......... 39% 24.9M 9s\n", + "234900K .......... .......... .......... .......... .......... 39% 24.9M 9s\n", + "234950K .......... .......... .......... .......... .......... 39% 29.5M 9s\n", + "235000K .......... .......... .......... .......... .......... 39% 51.1M 9s\n", + "235050K .......... .......... .......... .......... .......... 39% 20.1M 9s\n", + "235100K .......... .......... .......... .......... .......... 39% 28.1M 9s\n", + "235150K .......... .......... .......... .......... .......... 39% 22.1M 9s\n", + "235200K .......... .......... .......... .......... .......... 39% 51.9M 9s\n", + "235250K .......... .......... .......... .......... .......... 39% 29.1M 9s\n", + "235300K .......... .......... .......... .......... .......... 39% 20.1M 9s\n", + "235350K .......... .......... .......... .......... .......... 39% 25.7M 9s\n", + "235400K .......... .......... .......... .......... .......... 39% 52.8M 9s\n", + "235450K .......... .......... .......... .......... .......... 39% 26.5M 9s\n", + "235500K .......... .......... .......... .......... .......... 39% 24.2M 9s\n", + "235550K .......... .......... .......... .......... .......... 39% 26.8M 9s\n", + "235600K .......... .......... .......... .......... .......... 39% 51.3M 9s\n", + "235650K .......... .......... .......... .......... .......... 39% 6.09M 9s\n", + "235700K .......... .......... .......... .......... .......... 39% 69.2M 9s\n", + "235750K .......... .......... .......... .......... .......... 39% 70.8M 9s\n", + "235800K .......... .......... .......... .......... .......... 39% 14.3M 9s\n", + "235850K .......... .......... .......... .......... .......... 39% 56.4M 9s\n", + "235900K .......... .......... .......... .......... .......... 39% 71.6M 9s\n", + "235950K .......... .......... .......... .......... .......... 39% 16.2M 9s\n", + "236000K .......... .......... .......... .......... .......... 39% 57.9M 9s\n", + "236050K .......... .......... .......... .......... .......... 39% 60.1M 9s\n", + "236100K .......... .......... .......... .......... .......... 39% 16.9M 9s\n", + "236150K .......... .......... .......... .......... .......... 39% 56.6M 9s\n", + "236200K .......... .......... .......... .......... .......... 39% 16.8M 9s\n", + "236250K .......... .......... .......... .......... .......... 39% 47.1M 9s\n", + "236300K .......... .......... .......... .......... .......... 39% 58.3M 9s\n", + "236350K .......... .......... .......... .......... .......... 39% 20.3M 9s\n", + "236400K .......... .......... .......... .......... .......... 39% 28.6M 9s\n", + "236450K .......... .......... .......... .......... .......... 39% 60.5M 9s\n", + "236500K .......... .......... .......... .......... .......... 39% 24.2M 9s\n", + "236550K .......... .......... .......... .......... .......... 39% 39.6M 9s\n", + "236600K .......... .......... .......... .......... .......... 39% 38.3M 9s\n", + "236650K .......... .......... .......... .......... .......... 39% 20.7M 9s\n", + "236700K .......... .......... .......... .......... .......... 39% 34.3M 9s\n", + "236750K .......... .......... .......... .......... .......... 39% 68.5M 9s\n", + "236800K .......... .......... .......... .......... .......... 39% 20.8M 9s\n", + "236850K .......... .......... .......... .......... .......... 39% 40.0M 9s\n", + "236900K .......... .......... .......... .......... .......... 39% 44.8M 9s\n", + "236950K .......... .......... .......... .......... .......... 39% 22.4M 9s\n", + "237000K .......... .......... .......... .......... .......... 39% 16.2M 9s\n", + "237050K .......... .......... .......... .......... .......... 39% 57.5M 9s\n", + "237100K .......... .......... .......... .......... .......... 39% 44.6M 9s\n", + "237150K .......... .......... .......... .......... .......... 39% 19.1M 9s\n", + "237200K .......... .......... .......... .......... .......... 39% 40.2M 9s\n", + "237250K .......... .......... .......... .......... .......... 39% 61.5M 9s\n", + "237300K .......... .......... .......... .......... .......... 39% 18.4M 9s\n", + "237350K .......... .......... .......... .......... .......... 39% 46.2M 9s\n", + "237400K .......... .......... .......... .......... .......... 39% 19.9M 9s\n", + "237450K .......... .......... .......... .......... .......... 39% 39.5M 9s\n", + "237500K .......... .......... .......... .......... .......... 39% 44.6M 9s\n", + "237550K .......... .......... .......... .......... .......... 39% 69.1M 9s\n", + "237600K .......... .......... .......... .......... .......... 39% 23.2M 9s\n", + "237650K .......... .......... .......... .......... .......... 39% 29.6M 9s\n", + "237700K .......... .......... .......... .......... .......... 39% 66.5M 9s\n", + "237750K .......... .......... .......... .......... .......... 39% 3.11M 9s\n", + "237800K .......... .......... .......... .......... .......... 39% 56.4M 9s\n", + "237850K .......... .......... .......... .......... .......... 40% 68.5M 9s\n", + "237900K .......... .......... .......... .......... .......... 40% 61.8M 9s\n", + "237950K .......... .......... .......... .......... .......... 40% 64.8M 9s\n", + "238000K .......... .......... .......... .......... .......... 40% 44.5M 9s\n", + "238050K .......... .......... .......... .......... .......... 40% 63.8M 9s\n", + "238100K .......... .......... .......... .......... .......... 40% 65.2M 9s\n", + "238150K .......... .......... .......... .......... .......... 40% 66.4M 9s\n", + "238200K .......... .......... .......... .......... .......... 40% 22.1M 9s\n", + "238250K .......... .......... .......... .......... .......... 40% 68.3M 9s\n", + "238300K .......... .......... .......... .......... .......... 40% 65.6M 9s\n", + "238350K .......... .......... .......... .......... .......... 40% 17.8M 9s\n", + "238400K .......... .......... .......... .......... .......... 40% 48.2M 9s\n", + "238450K .......... .......... .......... .......... .......... 40% 64.3M 9s\n", + "238500K .......... .......... .......... .......... .......... 40% 18.1M 9s\n", + "238550K .......... .......... .......... .......... .......... 40% 46.4M 9s\n", + "238600K .......... .......... .......... .......... .......... 40% 49.3M 9s\n", + "238650K .......... .......... .......... .......... .......... 40% 19.6M 9s\n", + "238700K .......... .......... .......... .......... .......... 40% 44.8M 9s\n", + "238750K .......... .......... .......... .......... .......... 40% 62.7M 9s\n", + "238800K .......... .......... .......... .......... .......... 40% 17.1M 9s\n", + "238850K .......... .......... .......... .......... .......... 40% 41.5M 9s\n", + "238900K .......... .......... .......... .......... .......... 40% 60.3M 9s\n", + "238950K .......... .......... .......... .......... .......... 40% 23.2M 9s\n", + "239000K .......... .......... .......... .......... .......... 40% 37.5M 9s\n", + "239050K .......... .......... .......... .......... .......... 40% 54.7M 9s\n", + "239100K .......... .......... .......... .......... .......... 40% 23.5M 9s\n", + "239150K .......... .......... .......... .......... .......... 40% 3.92M 9s\n", + "239200K .......... .......... .......... .......... .......... 40% 56.3M 9s\n", + "239250K .......... .......... .......... .......... .......... 40% 63.7M 9s\n", + "239300K .......... .......... .......... .......... .......... 40% 17.0M 9s\n", + "239350K .......... .......... .......... .......... .......... 40% 48.3M 9s\n", + "239400K .......... .......... .......... .......... .......... 40% 54.1M 9s\n", + "239450K .......... .......... .......... .......... .......... 40% 18.6M 9s\n", + "239500K .......... .......... .......... .......... .......... 40% 40.4M 9s\n", + "239550K .......... .......... .......... .......... .......... 40% 67.3M 9s\n", + "239600K .......... .......... .......... .......... .......... 40% 22.4M 9s\n", + "239650K .......... .......... .......... .......... .......... 40% 42.8M 9s\n", + "239700K .......... .......... .......... .......... .......... 40% 51.6M 9s\n", + "239750K .......... .......... .......... .......... .......... 40% 70.0M 9s\n", + "239800K .......... .......... .......... .......... .......... 40% 17.4M 9s\n", + "239850K .......... .......... .......... .......... .......... 40% 18.1M 9s\n", + "239900K .......... .......... .......... .......... .......... 40% 49.9M 9s\n", + "239950K .......... .......... .......... .......... .......... 40% 41.8M 9s\n", + "240000K .......... .......... .......... .......... .......... 40% 42.0M 9s\n", + "240050K .......... .......... .......... .......... .......... 40% 69.6M 9s\n", + "240100K .......... .......... .......... .......... .......... 40% 38.6M 9s\n", + "240150K .......... .......... .......... .......... .......... 40% 43.0M 9s\n", + "240200K .......... .......... .......... .......... .......... 40% 34.7M 9s\n", + "240250K .......... .......... .......... .......... .......... 40% 25.8M 9s\n", + "240300K .......... .......... .......... .......... .......... 40% 33.2M 9s\n", + "240350K .......... .......... .......... .......... .......... 40% 40.9M 9s\n", + "240400K .......... .......... .......... .......... .......... 40% 36.0M 9s\n", + "240450K .......... .......... .......... .......... .......... 40% 39.5M 9s\n", + "240500K .......... .......... .......... .......... .......... 40% 38.0M 9s\n", + "240550K .......... .......... .......... .......... .......... 40% 6.29M 9s\n", + "240600K .......... .......... .......... .......... .......... 40% 44.7M 9s\n", + "240650K .......... .......... .......... .......... .......... 40% 67.7M 9s\n", + "240700K .......... .......... .......... .......... .......... 40% 36.2M 9s\n", + "240750K .......... .......... .......... .......... .......... 40% 38.9M 9s\n", + "240800K .......... .......... .......... .......... .......... 40% 24.5M 9s\n", + "240850K .......... .......... .......... .......... .......... 40% 35.4M 9s\n", + "240900K .......... .......... .......... .......... .......... 40% 34.7M 9s\n", + "240950K .......... .......... .......... .......... .......... 40% 29.0M 9s\n", + "241000K .......... .......... .......... .......... .......... 40% 42.7M 9s\n", + "241050K .......... .......... .......... .......... .......... 40% 15.3M 9s\n", + "241100K .......... .......... .......... .......... .......... 40% 36.3M 9s\n", + "241150K .......... .......... .......... .......... .......... 40% 51.9M 9s\n", + "241200K .......... .......... .......... .......... .......... 40% 54.5M 9s\n", + "241250K .......... .......... .......... .......... .......... 40% 51.7M 9s\n", + "241300K .......... .......... .......... .......... .......... 40% 42.3M 9s\n", + "241350K .......... .......... .......... .......... .......... 40% 57.1M 9s\n", + "241400K .......... .......... .......... .......... .......... 40% 31.7M 9s\n", + "241450K .......... .......... .......... .......... .......... 40% 41.6M 9s\n", + "241500K .......... .......... .......... .......... .......... 40% 53.2M 9s\n", + "241550K .......... .......... .......... .......... .......... 40% 57.7M 9s\n", + "241600K .......... .......... .......... .......... .......... 40% 61.4M 9s\n", + "241650K .......... .......... .......... .......... .......... 40% 39.0M 9s\n", + "241700K .......... .......... .......... .......... .......... 40% 59.6M 9s\n", + "241750K .......... .......... .......... .......... .......... 40% 44.1M 9s\n", + "241800K .......... .......... .......... .......... .......... 40% 22.5M 9s\n", + "241850K .......... .......... .......... .......... .......... 40% 46.6M 9s\n", + "241900K .......... .......... .......... .......... .......... 40% 47.1M 9s\n", + "241950K .......... .......... .......... .......... .......... 40% 61.7M 9s\n", + "242000K .......... .......... .......... .......... .......... 40% 21.6M 9s\n", + "242050K .......... .......... .......... .......... .......... 40% 55.0M 9s\n", + "242100K .......... .......... .......... .......... .......... 40% 51.2M 9s\n", + "242150K .......... .......... .......... .......... .......... 40% 66.5M 9s\n", + "242200K .......... .......... .......... .......... .......... 40% 18.0M 9s\n", + "242250K .......... .......... .......... .......... .......... 40% 50.9M 9s\n", + "242300K .......... .......... .......... .......... .......... 40% 65.5M 9s\n", + "242350K .......... .......... .......... .......... .......... 40% 29.5M 9s\n", + "242400K .......... .......... .......... .......... .......... 40% 39.3M 9s\n", + "242450K .......... .......... .......... .......... .......... 40% 50.5M 9s\n", + "242500K .......... .......... .......... .......... .......... 40% 61.9M 9s\n", + "242550K .......... .......... .......... .......... .......... 40% 25.5M 9s\n", + "242600K .......... .......... .......... .......... .......... 40% 36.5M 9s\n", + "242650K .......... .......... .......... .......... .......... 40% 61.4M 9s\n", + "242700K .......... .......... .......... .......... .......... 40% 26.6M 9s\n", + "242750K .......... .......... .......... .......... .......... 40% 34.0M 9s\n", + "242800K .......... .......... .......... .......... .......... 40% 48.0M 9s\n", + "242850K .......... .......... .......... .......... .......... 40% 62.7M 9s\n", + "242900K .......... .......... .......... .......... .......... 40% 28.1M 9s\n", + "242950K .......... .......... .......... .......... .......... 40% 31.2M 9s\n", + "243000K .......... .......... .......... .......... .......... 40% 47.3M 9s\n", + "243050K .......... .......... .......... .......... .......... 40% 40.7M 9s\n", + "243100K .......... .......... .......... .......... .......... 40% 27.5M 9s\n", + "243150K .......... .......... .......... .......... .......... 40% 49.0M 9s\n", + "243200K .......... .......... .......... .......... .......... 40% 56.4M 9s\n", + "243250K .......... .......... .......... .......... .......... 40% 40.0M 9s\n", + "243300K .......... .......... .......... .......... .......... 40% 32.2M 9s\n", + "243350K .......... .......... .......... .......... .......... 40% 58.6M 9s\n", + "243400K .......... .......... .......... .......... .......... 40% 24.0M 9s\n", + "243450K .......... .......... .......... .......... .......... 40% 40.0M 9s\n", + "243500K .......... .......... .......... .......... .......... 40% 52.7M 9s\n", + "243550K .......... .......... .......... .......... .......... 40% 57.8M 9s\n", + "243600K .......... .......... .......... .......... .......... 40% 31.4M 9s\n", + "243650K .......... .......... .......... .......... .......... 40% 26.5M 9s\n", + "243700K .......... .......... .......... .......... .......... 40% 55.7M 9s\n", + "243750K .......... .......... .......... .......... .......... 40% 56.4M 9s\n", + "243800K .......... .......... .......... .......... .......... 41% 33.4M 9s\n", + "243850K .......... .......... .......... .......... .......... 41% 34.0M 9s\n", + "243900K .......... .......... .......... .......... .......... 41% 18.0M 9s\n", + "243950K .......... .......... .......... .......... .......... 41% 50.3M 9s\n", + "244000K .......... .......... .......... .......... .......... 41% 47.7M 9s\n", + "244050K .......... .......... .......... .......... .......... 41% 61.5M 9s\n", + "244100K .......... .......... .......... .......... .......... 41% 28.5M 9s\n", + "244150K .......... .......... .......... .......... .......... 41% 42.8M 9s\n", + "244200K .......... .......... .......... .......... .......... 41% 3.87M 9s\n", + "244250K .......... .......... .......... .......... .......... 41% 60.3M 9s\n", + "244300K .......... .......... .......... .......... .......... 41% 63.6M 9s\n", + "244350K .......... .......... .......... .......... .......... 41% 64.0M 9s\n", + "244400K .......... .......... .......... .......... .......... 41% 58.3M 9s\n", + "244450K .......... .......... .......... .......... .......... 41% 5.78M 9s\n", + "244500K .......... .......... .......... .......... .......... 41% 49.1M 9s\n", + "244550K .......... .......... .......... .......... .......... 41% 47.9M 9s\n", + "244600K .......... .......... .......... .......... .......... 41% 40.5M 9s\n", + "244650K .......... .......... .......... .......... .......... 41% 24.6M 9s\n", + "244700K .......... .......... .......... .......... .......... 41% 39.1M 9s\n", + "244750K .......... .......... .......... .......... .......... 41% 44.2M 9s\n", + "244800K .......... .......... .......... .......... .......... 41% 47.0M 9s\n", + "244850K .......... .......... .......... .......... .......... 41% 44.0M 9s\n", + "244900K .......... .......... .......... .......... .......... 41% 42.5M 9s\n", + "244950K .......... .......... .......... .......... .......... 41% 45.0M 9s\n", + "245000K .......... .......... .......... .......... .......... 41% 40.6M 9s\n", + "245050K .......... .......... .......... .......... .......... 41% 33.8M 9s\n", + "245100K .......... .......... .......... .......... .......... 41% 50.4M 9s\n", + "245150K .......... .......... .......... .......... .......... 41% 63.9M 9s\n", + "245200K .......... .......... .......... .......... .......... 41% 21.7M 9s\n", + "245250K .......... .......... .......... .......... .......... 41% 44.5M 9s\n", + "245300K .......... .......... .......... .......... .......... 41% 55.4M 9s\n", + "245350K .......... .......... .......... .......... .......... 41% 65.0M 9s\n", + "245400K .......... .......... .......... .......... .......... 41% 24.2M 9s\n", + "245450K .......... .......... .......... .......... .......... 41% 54.3M 9s\n", + "245500K .......... .......... .......... .......... .......... 41% 66.7M 9s\n", + "245550K .......... .......... .......... .......... .......... 41% 69.7M 9s\n", + "245600K .......... .......... .......... .......... .......... 41% 20.5M 9s\n", + "245650K .......... .......... .......... .......... .......... 41% 51.7M 9s\n", + "245700K .......... .......... .......... .......... .......... 41% 55.3M 9s\n", + "245750K .......... .......... .......... .......... .......... 41% 65.9M 9s\n", + "245800K .......... .......... .......... .......... .......... 41% 4.66M 9s\n", + "245850K .......... .......... .......... .......... .......... 41% 55.4M 9s\n", + "245900K .......... .......... .......... .......... .......... 41% 66.2M 9s\n", + "245950K .......... .......... .......... .......... .......... 41% 68.8M 9s\n", + "246000K .......... .......... .......... .......... .......... 41% 21.7M 9s\n", + "246050K .......... .......... .......... .......... .......... 41% 48.9M 9s\n", + "246100K .......... .......... .......... .......... .......... 41% 4.40M 9s\n", + "246150K .......... .......... .......... .......... .......... 41% 68.7M 9s\n", + "246200K .......... .......... .......... .......... .......... 41% 56.1M 9s\n", + "246250K .......... .......... .......... .......... .......... 41% 72.0M 9s\n", + "246300K .......... .......... .......... .......... .......... 41% 69.1M 9s\n", + "246350K .......... .......... .......... .......... .......... 41% 68.5M 9s\n", + "246400K .......... .......... .......... .......... .......... 41% 33.9M 9s\n", + "246450K .......... .......... .......... .......... .......... 41% 50.2M 9s\n", + "246500K .......... .......... .......... .......... .......... 41% 59.3M 9s\n", + "246550K .......... .......... .......... .......... .......... 41% 70.6M 9s\n", + "246600K .......... .......... .......... .......... .......... 41% 24.0M 9s\n", + "246650K .......... .......... .......... .......... .......... 41% 49.0M 9s\n", + "246700K .......... .......... .......... .......... .......... 41% 57.9M 9s\n", + "246750K .......... .......... .......... .......... .......... 41% 67.5M 9s\n", + "246800K .......... .......... .......... .......... .......... 41% 24.6M 9s\n", + "246850K .......... .......... .......... .......... .......... 41% 51.9M 9s\n", + "246900K .......... .......... .......... .......... .......... 41% 55.1M 9s\n", + "246950K .......... .......... .......... .......... .......... 41% 66.8M 9s\n", + "247000K .......... .......... .......... .......... .......... 41% 21.4M 9s\n", + "247050K .......... .......... .......... .......... .......... 41% 47.7M 9s\n", + "247100K .......... .......... .......... .......... .......... 41% 60.9M 9s\n", + "247150K .......... .......... .......... .......... .......... 41% 70.8M 9s\n", + "247200K .......... .......... .......... .......... .......... 41% 26.6M 9s\n", + "247250K .......... .......... .......... .......... .......... 41% 44.8M 9s\n", + "247300K .......... .......... .......... .......... .......... 41% 55.1M 9s\n", + "247350K .......... .......... .......... .......... .......... 41% 66.6M 9s\n", + "247400K .......... .......... .......... .......... .......... 41% 27.5M 9s\n", + "247450K .......... .......... .......... .......... .......... 41% 41.2M 9s\n", + "247500K .......... .......... .......... .......... .......... 41% 50.4M 9s\n", + "247550K .......... .......... .......... .......... .......... 41% 71.3M 9s\n", + "247600K .......... .......... .......... .......... .......... 41% 30.1M 9s\n", + "247650K .......... .......... .......... .......... .......... 41% 42.8M 9s\n", + "247700K .......... .......... .......... .......... .......... 41% 30.7M 9s\n", + "247750K .......... .......... .......... .......... .......... 41% 51.0M 9s\n", + "247800K .......... .......... .......... .......... .......... 41% 39.5M 9s\n", + "247850K .......... .......... .......... .......... .......... 41% 45.8M 9s\n", + "247900K .......... .......... .......... .......... .......... 41% 45.3M 9s\n", + "247950K .......... .......... .......... .......... .......... 41% 48.3M 9s\n", + "248000K .......... .......... .......... .......... .......... 41% 52.9M 9s\n", + "248050K .......... .......... .......... .......... .......... 41% 56.5M 9s\n", + "248100K .......... .......... .......... .......... .......... 41% 30.4M 9s\n", + "248150K .......... .......... .......... .......... .......... 41% 45.9M 9s\n", + "248200K .......... .......... .......... .......... .......... 41% 44.6M 9s\n", + "248250K .......... .......... .......... .......... .......... 41% 50.3M 9s\n", + "248300K .......... .......... .......... .......... .......... 41% 42.0M 9s\n", + "248350K .......... .......... .......... .......... .......... 41% 36.0M 9s\n", + "248400K .......... .......... .......... .......... .......... 41% 31.5M 9s\n", + "248450K .......... .......... .......... .......... .......... 41% 61.5M 9s\n", + "248500K .......... .......... .......... .......... .......... 41% 55.5M 9s\n", + "248550K .......... .......... .......... .......... .......... 41% 60.7M 9s\n", + "248600K .......... .......... .......... .......... .......... 41% 53.3M 9s\n", + "248650K .......... .......... .......... .......... .......... 41% 37.1M 9s\n", + "248700K .......... .......... .......... .......... .......... 41% 57.3M 9s\n", + "248750K .......... .......... .......... .......... .......... 41% 35.9M 9s\n", + "248800K .......... .......... .......... .......... .......... 41% 52.3M 9s\n", + "248850K .......... .......... .......... .......... .......... 41% 61.5M 9s\n", + "248900K .......... .......... .......... .......... .......... 41% 49.0M 9s\n", + "248950K .......... .......... .......... .......... .......... 41% 49.8M 9s\n", + "249000K .......... .......... .......... .......... .......... 41% 46.2M 9s\n", + "249050K .......... .......... .......... .......... .......... 41% 42.0M 9s\n", + "249100K .......... .......... .......... .......... .......... 41% 46.4M 9s\n", + "249150K .......... .......... .......... .......... .......... 41% 39.4M 9s\n", + "249200K .......... .......... .......... .......... .......... 41% 57.1M 9s\n", + "249250K .......... .......... .......... .......... .......... 41% 54.3M 9s\n", + "249300K .......... .......... .......... .......... .......... 41% 41.9M 9s\n", + "249350K .......... .......... .......... .......... .......... 41% 44.6M 9s\n", + "249400K .......... .......... .......... .......... .......... 41% 33.9M 9s\n", + "249450K .......... .......... .......... .......... .......... 41% 60.1M 9s\n", + "249500K .......... .......... .......... .......... .......... 41% 45.3M 9s\n", + "249550K .......... .......... .......... .......... .......... 41% 51.2M 9s\n", + "249600K .......... .......... .......... .......... .......... 41% 27.7M 9s\n", + "249650K .......... .......... .......... .......... .......... 41% 49.1M 9s\n", + "249700K .......... .......... .......... .......... .......... 41% 55.5M 9s\n", + "249750K .......... .......... .......... .......... .......... 42% 57.1M 9s\n", + "249800K .......... .......... .......... .......... .......... 42% 20.9M 9s\n", + "249850K .......... .......... .......... .......... .......... 42% 52.2M 9s\n", + "249900K .......... .......... .......... .......... .......... 42% 42.6M 9s\n", + "249950K .......... .......... .......... .......... .......... 42% 63.6M 9s\n", + "250000K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", + "250050K .......... .......... .......... .......... .......... 42% 45.0M 9s\n", + "250100K .......... .......... .......... .......... .......... 42% 60.0M 9s\n", + "250150K .......... .......... .......... .......... .......... 42% 55.8M 9s\n", + "250200K .......... .......... .......... .......... .......... 42% 7.38M 9s\n", + "250250K .......... .......... .......... .......... .......... 42% 45.6M 9s\n", + "250300K .......... .......... .......... .......... .......... 42% 53.5M 9s\n", + "250350K .......... .......... .......... .......... .......... 42% 67.2M 9s\n", + "250400K .......... .......... .......... .......... .......... 42% 59.1M 9s\n", + "250450K .......... .......... .......... .......... .......... 42% 25.2M 9s\n", + "250500K .......... .......... .......... .......... .......... 42% 48.1M 9s\n", + "250550K .......... .......... .......... .......... .......... 42% 50.2M 9s\n", + "250600K .......... .......... .......... .......... .......... 42% 57.8M 9s\n", + "250650K .......... .......... .......... .......... .......... 42% 45.4M 9s\n", + "250700K .......... .......... .......... .......... .......... 42% 63.2M 9s\n", + "250750K .......... .......... .......... .......... .......... 42% 48.7M 9s\n", + "250800K .......... .......... .......... .......... .......... 42% 60.3M 9s\n", + "250850K .......... .......... .......... .......... .......... 42% 32.0M 9s\n", + "250900K .......... .......... .......... .......... .......... 42% 56.5M 9s\n", + "250950K .......... .......... .......... .......... .......... 42% 50.6M 9s\n", + "251000K .......... .......... .......... .......... .......... 42% 45.8M 9s\n", + "251050K .......... .......... .......... .......... .......... 42% 69.5M 9s\n", + "251100K .......... .......... .......... .......... .......... 42% 35.4M 9s\n", + "251150K .......... .......... .......... .......... .......... 42% 53.7M 9s\n", + "251200K .......... .......... .......... .......... .......... 42% 46.4M 9s\n", + "251250K .......... .......... .......... .......... .......... 42% 67.3M 9s\n", + "251300K .......... .......... .......... .......... .......... 42% 36.4M 9s\n", + "251350K .......... .......... .......... .......... .......... 42% 38.8M 9s\n", + "251400K .......... .......... .......... .......... .......... 42% 41.6M 9s\n", + "251450K .......... .......... .......... .......... .......... 42% 68.7M 9s\n", + "251500K .......... .......... .......... .......... .......... 42% 34.6M 9s\n", + "251550K .......... .......... .......... .......... .......... 42% 49.9M 9s\n", + "251600K .......... .......... .......... .......... .......... 42% 34.9M 9s\n", + "251650K .......... .......... .......... .......... .......... 42% 70.0M 9s\n", + "251700K .......... .......... .......... .......... .......... 42% 63.7M 9s\n", + "251750K .......... .......... .......... .......... .......... 42% 46.5M 9s\n", + "251800K .......... .......... .......... .......... .......... 42% 39.7M 9s\n", + "251850K .......... .......... .......... .......... .......... 42% 48.9M 9s\n", + "251900K .......... .......... .......... .......... .......... 42% 64.2M 9s\n", + "251950K .......... .......... .......... .......... .......... 42% 43.4M 9s\n", + "252000K .......... .......... .......... .......... .......... 42% 43.8M 9s\n", + "252050K .......... .......... .......... .......... .......... 42% 63.8M 9s\n", + "252100K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", + "252150K .......... .......... .......... .......... .......... 42% 73.6M 9s\n", + "252200K .......... .......... .......... .......... .......... 42% 28.6M 9s\n", + "252250K .......... .......... .......... .......... .......... 42% 57.2M 9s\n", + "252300K .......... .......... .......... .......... .......... 42% 62.0M 9s\n", + "252350K .......... .......... .......... .......... .......... 42% 52.3M 9s\n", + "252400K .......... .......... .......... .......... .......... 42% 39.7M 9s\n", + "252450K .......... .......... .......... .......... .......... 42% 55.2M 9s\n", + "252500K .......... .......... .......... .......... .......... 42% 52.7M 9s\n", + "252550K .......... .......... .......... .......... .......... 42% 50.8M 9s\n", + "252600K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", + "252650K .......... .......... .......... .......... .......... 42% 37.1M 9s\n", + "252700K .......... .......... .......... .......... .......... 42% 51.1M 9s\n", + "252750K .......... .......... .......... .......... .......... 42% 60.5M 9s\n", + "252800K .......... .......... .......... .......... .......... 42% 63.6M 9s\n", + "252850K .......... .......... .......... .......... .......... 42% 35.0M 9s\n", + "252900K .......... .......... .......... .......... .......... 42% 54.8M 9s\n", + "252950K .......... .......... .......... .......... .......... 42% 52.3M 9s\n", + "253000K .......... .......... .......... .......... .......... 42% 56.0M 9s\n", + "253050K .......... .......... .......... .......... .......... 42% 66.1M 9s\n", + "253100K .......... .......... .......... .......... .......... 42% 32.4M 9s\n", + "253150K .......... .......... .......... .......... .......... 42% 46.0M 9s\n", + "253200K .......... .......... .......... .......... .......... 42% 58.7M 9s\n", + "253250K .......... .......... .......... .......... .......... 42% 52.9M 9s\n", + "253300K .......... .......... .......... .......... .......... 42% 34.6M 9s\n", + "253350K .......... .......... .......... .......... .......... 42% 56.9M 9s\n", + "253400K .......... .......... .......... .......... .......... 42% 50.8M 9s\n", + "253450K .......... .......... .......... .......... .......... 42% 3.65M 9s\n", + "253500K .......... .......... .......... .......... .......... 42% 72.8M 9s\n", + "253550K .......... .......... .......... .......... .......... 42% 67.5M 9s\n", + "253600K .......... .......... .......... .......... .......... 42% 58.4M 9s\n", + "253650K .......... .......... .......... .......... .......... 42% 64.4M 9s\n", + "253700K .......... .......... .......... .......... .......... 42% 72.1M 9s\n", + "253750K .......... .......... .......... .......... .......... 42% 32.3M 9s\n", + "253800K .......... .......... .......... .......... .......... 42% 37.9M 9s\n", + "253850K .......... .......... .......... .......... .......... 42% 69.6M 9s\n", + "253900K .......... .......... .......... .......... .......... 42% 38.1M 9s\n", + "253950K .......... .......... .......... .......... .......... 42% 56.0M 9s\n", + "254000K .......... .......... .......... .......... .......... 42% 46.1M 9s\n", + "254050K .......... .......... .......... .......... .......... 42% 51.5M 9s\n", + "254100K .......... .......... .......... .......... .......... 42% 68.0M 9s\n", + "254150K .......... .......... .......... .......... .......... 42% 66.1M 9s\n", + "254200K .......... .......... .......... .......... .......... 42% 31.1M 9s\n", + "254250K .......... .......... .......... .......... .......... 42% 48.5M 9s\n", + "254300K .......... .......... .......... .......... .......... 42% 54.5M 9s\n", + "254350K .......... .......... .......... .......... .......... 42% 62.7M 9s\n", + "254400K .......... .......... .......... .......... .......... 42% 32.0M 9s\n", + "254450K .......... .......... .......... .......... .......... 42% 26.9M 9s\n", + "254500K .......... .......... .......... .......... .......... 42% 39.9M 9s\n", + "254550K .......... .......... .......... .......... .......... 42% 50.2M 9s\n", + "254600K .......... .......... .......... .......... .......... 42% 53.2M 9s\n", + "254650K .......... .......... .......... .......... .......... 42% 47.8M 9s\n", + "254700K .......... .......... .......... .......... .......... 42% 47.7M 9s\n", + "254750K .......... .......... .......... .......... .......... 42% 67.8M 9s\n", + "254800K .......... .......... .......... .......... .......... 42% 54.5M 9s\n", + "254850K .......... .......... .......... .......... .......... 42% 57.5M 9s\n", + "254900K .......... .......... .......... .......... .......... 42% 48.2M 9s\n", + "254950K .......... .......... .......... .......... .......... 42% 65.5M 9s\n", + "255000K .......... .......... .......... .......... .......... 42% 58.9M 9s\n", + "255050K .......... .......... .......... .......... .......... 42% 69.8M 9s\n", + "255100K .......... .......... .......... .......... .......... 42% 64.3M 9s\n", + "255150K .......... .......... .......... .......... .......... 42% 66.3M 9s\n", + "255200K .......... .......... .......... .......... .......... 42% 38.4M 9s\n", + "255250K .......... .......... .......... .......... .......... 42% 54.2M 9s\n", + "255300K .......... .......... .......... .......... .......... 42% 70.5M 9s\n", + "255350K .......... .......... .......... .......... .......... 42% 62.3M 9s\n", + "255400K .......... .......... .......... .......... .......... 42% 31.1M 9s\n", + "255450K .......... .......... .......... .......... .......... 42% 44.4M 9s\n", + "255500K .......... .......... .......... .......... .......... 42% 61.5M 9s\n", + "255550K .......... .......... .......... .......... .......... 42% 69.5M 9s\n", + "255600K .......... .......... .......... .......... .......... 42% 43.7M 9s\n", + "255650K .......... .......... .......... .......... .......... 42% 55.3M 9s\n", + "255700K .......... .......... .......... .......... .......... 43% 48.6M 9s\n", + "255750K .......... .......... .......... .......... .......... 43% 55.8M 9s\n", + "255800K .......... .......... .......... .......... .......... 43% 48.4M 9s\n", + "255850K .......... .......... .......... .......... .......... 43% 61.5M 9s\n", + "255900K .......... .......... .......... .......... .......... 43% 46.8M 9s\n", + "255950K .......... .......... .......... .......... .......... 43% 50.5M 9s\n", + "256000K .......... .......... .......... .......... .......... 43% 52.3M 9s\n", + "256050K .......... .......... .......... .......... .......... 43% 69.7M 9s\n", + "256100K .......... .......... .......... .......... .......... 43% 54.2M 9s\n", + "256150K .......... .......... .......... .......... .......... 43% 46.2M 9s\n", + "256200K .......... .......... .......... .......... .......... 43% 41.6M 9s\n", + "256250K .......... .......... .......... .......... .......... 43% 65.0M 9s\n", + "256300K .......... .......... .......... .......... .......... 43% 63.8M 9s\n", + "256350K .......... .......... .......... .......... .......... 43% 52.5M 9s\n", + "256400K .......... .......... .......... .......... .......... 43% 46.2M 9s\n", + "256450K .......... .......... .......... .......... .......... 43% 49.4M 9s\n", + "256500K .......... .......... .......... .......... .......... 43% 67.0M 9s\n", + "256550K .......... .......... .......... .......... .......... 43% 54.6M 9s\n", + "256600K .......... .......... .......... .......... .......... 43% 43.5M 9s\n", + "256650K .......... .......... .......... .......... .......... 43% 44.4M 9s\n", + "256700K .......... .......... .......... .......... .......... 43% 63.6M 9s\n", + "256750K .......... .......... .......... .......... .......... 43% 56.7M 9s\n", + "256800K .......... .......... .......... .......... .......... 43% 46.4M 9s\n", + "256850K .......... .......... .......... .......... .......... 43% 52.2M 9s\n", + "256900K .......... .......... .......... .......... .......... 43% 45.8M 9s\n", + "256950K .......... .......... .......... .......... .......... 43% 3.83M 9s\n", + "257000K .......... .......... .......... .......... .......... 43% 50.9M 9s\n", + "257050K .......... .......... .......... .......... .......... 43% 70.5M 9s\n", + "257100K .......... .......... .......... .......... .......... 43% 65.5M 9s\n", + "257150K .......... .......... .......... .......... .......... 43% 69.0M 9s\n", + "257200K .......... .......... .......... .......... .......... 43% 64.8M 9s\n", + "257250K .......... .......... .......... .......... .......... 43% 66.1M 9s\n", + "257300K .......... .......... .......... .......... .......... 43% 52.2M 9s\n", + "257350K .......... .......... .......... .......... .......... 43% 52.4M 9s\n", + "257400K .......... .......... .......... .......... .......... 43% 47.3M 9s\n", + "257450K .......... .......... .......... .......... .......... 43% 70.0M 9s\n", + "257500K .......... .......... .......... .......... .......... 43% 70.1M 9s\n", + "257550K .......... .......... .......... .......... .......... 43% 51.1M 9s\n", + "257600K .......... .......... .......... .......... .......... 43% 40.9M 9s\n", + "257650K .......... .......... .......... .......... .......... 43% 51.2M 9s\n", + "257700K .......... .......... .......... .......... .......... 43% 67.6M 9s\n", + "257750K .......... .......... .......... .......... .......... 43% 69.1M 9s\n", + "257800K .......... .......... .......... .......... .......... 43% 38.0M 9s\n", + "257850K .......... .......... .......... .......... .......... 43% 49.3M 9s\n", + "257900K .......... .......... .......... .......... .......... 43% 59.8M 9s\n", + "257950K .......... .......... .......... .......... .......... 43% 67.7M 9s\n", + "258000K .......... .......... .......... .......... .......... 43% 59.6M 9s\n", + "258050K .......... .......... .......... .......... .......... 43% 53.2M 9s\n", + "258100K .......... .......... .......... .......... .......... 43% 54.8M 9s\n", + "258150K .......... .......... .......... .......... .......... 43% 54.7M 9s\n", + "258200K .......... .......... .......... .......... .......... 43% 54.6M 9s\n", + "258250K .......... .......... .......... .......... .......... 43% 59.5M 9s\n", + "258300K .......... .......... .......... .......... .......... 43% 49.5M 9s\n", + "258350K .......... .......... .......... .......... .......... 43% 52.4M 9s\n", + "258400K .......... .......... .......... .......... .......... 43% 3.94M 9s\n", + "258450K .......... .......... .......... .......... .......... 43% 66.0M 9s\n", + "258500K .......... .......... .......... .......... .......... 43% 60.9M 9s\n", + "258550K .......... .......... .......... .......... .......... 43% 63.6M 9s\n", + "258600K .......... .......... .......... .......... .......... 43% 56.6M 9s\n", + "258650K .......... .......... .......... .......... .......... 43% 63.8M 9s\n", + "258700K .......... .......... .......... .......... .......... 43% 54.4M 9s\n", + "258750K .......... .......... .......... .......... .......... 43% 51.6M 9s\n", + "258800K .......... .......... .......... .......... .......... 43% 49.5M 9s\n", + "258850K .......... .......... .......... .......... .......... 43% 67.9M 9s\n", + "258900K .......... .......... .......... .......... .......... 43% 66.4M 9s\n", + "258950K .......... .......... .......... .......... .......... 43% 38.3M 9s\n", + "259000K .......... .......... .......... .......... .......... 43% 40.4M 9s\n", + "259050K .......... .......... .......... .......... .......... 43% 56.4M 9s\n", + "259100K .......... .......... .......... .......... .......... 43% 65.3M 9s\n", + "259150K .......... .......... .......... .......... .......... 43% 70.8M 9s\n", + "259200K .......... .......... .......... .......... .......... 43% 53.7M 9s\n", + "259250K .......... .......... .......... .......... .......... 43% 55.1M 9s\n", + "259300K .......... .......... .......... .......... .......... 43% 46.3M 9s\n", + "259350K .......... .......... .......... .......... .......... 43% 67.0M 9s\n", + "259400K .......... .......... .......... .......... .......... 43% 57.9M 9s\n", + "259450K .......... .......... .......... .......... .......... 43% 49.3M 9s\n", + "259500K .......... .......... .......... .......... .......... 43% 58.7M 9s\n", + "259550K .......... .......... .......... .......... .......... 43% 56.3M 9s\n", + "259600K .......... .......... .......... .......... .......... 43% 46.1M 9s\n", + "259650K .......... .......... .......... .......... .......... 43% 67.0M 9s\n", + "259700K .......... .......... .......... .......... .......... 43% 67.1M 9s\n", + "259750K .......... .......... .......... .......... .......... 43% 50.3M 9s\n", + "259800K .......... .......... .......... .......... .......... 43% 43.8M 9s\n", + "259850K .......... .......... .......... .......... .......... 43% 54.5M 9s\n", + "259900K .......... .......... .......... .......... .......... 43% 64.7M 9s\n", + "259950K .......... .......... .......... .......... .......... 43% 56.9M 8s\n", + "260000K .......... .......... .......... .......... .......... 43% 42.5M 8s\n", + "260050K .......... .......... .......... .......... .......... 43% 46.5M 8s\n", + "260100K .......... .......... .......... .......... .......... 43% 56.5M 8s\n", + "260150K .......... .......... .......... .......... .......... 43% 66.7M 8s\n", + "260200K .......... .......... .......... .......... .......... 43% 52.4M 8s\n", + "260250K .......... .......... .......... .......... .......... 43% 53.8M 8s\n", + "260300K .......... .......... .......... .......... .......... 43% 53.3M 8s\n", + "260350K .......... .......... .......... .......... .......... 43% 53.5M 8s\n", + "260400K .......... .......... .......... .......... .......... 43% 58.8M 8s\n", + "260450K .......... .......... .......... .......... .......... 43% 54.7M 8s\n", + "260500K .......... .......... .......... .......... .......... 43% 57.1M 8s\n", + "260550K .......... .......... .......... .......... .......... 43% 57.6M 8s\n", + "260600K .......... .......... .......... .......... .......... 43% 43.4M 8s\n", + "260650K .......... .......... .......... .......... .......... 43% 67.6M 8s\n", + "260700K .......... .......... .......... .......... .......... 43% 58.9M 8s\n", + "260750K 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.......... .......... .......... .......... .......... 43% 52.5M 8s\n", + "261400K .......... .......... .......... .......... .......... 43% 57.3M 8s\n", + "261450K .......... .......... .......... .......... .......... 43% 55.7M 8s\n", + "261500K .......... .......... .......... .......... .......... 43% 52.0M 8s\n", + "261550K .......... .......... .......... .......... .......... 43% 52.6M 8s\n", + "261600K .......... .......... .......... .......... .......... 43% 47.2M 8s\n", + "261650K .......... .......... .......... .......... .......... 44% 4.17M 8s\n", + "261700K .......... .......... .......... .......... .......... 44% 63.7M 8s\n", + "261750K .......... .......... .......... .......... .......... 44% 65.6M 8s\n", + "261800K .......... .......... .......... .......... .......... 44% 56.8M 8s\n", + "261850K .......... .......... .......... .......... .......... 44% 63.6M 8s\n", + "261900K .......... .......... .......... .......... .......... 44% 69.6M 8s\n", + "261950K .......... .......... .......... .......... .......... 44% 64.1M 8s\n", + "262000K .......... .......... .......... .......... .......... 44% 58.4M 8s\n", + "262050K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", + "262100K .......... .......... .......... .......... .......... 44% 59.8M 8s\n", + "262150K .......... .......... .......... .......... .......... 44% 68.2M 8s\n", + "262200K .......... .......... .......... .......... .......... 44% 56.9M 8s\n", + "262250K .......... .......... .......... .......... .......... 44% 64.2M 8s\n", + "262300K .......... .......... .......... .......... .......... 44% 51.9M 8s\n", + "262350K .......... .......... .......... .......... .......... 44% 58.1M 8s\n", + "262400K .......... .......... .......... .......... .......... 44% 51.6M 8s\n", + "262450K .......... .......... .......... .......... .......... 44% 67.5M 8s\n", + "262500K .......... .......... .......... .......... .......... 44% 65.1M 8s\n", + "262550K .......... .......... .......... .......... .......... 44% 51.0M 8s\n", + "262600K .......... .......... .......... .......... .......... 44% 40.5M 8s\n", + "262650K .......... .......... .......... .......... .......... 44% 57.9M 8s\n", + "262700K .......... .......... .......... .......... .......... 44% 58.4M 8s\n", + "262750K .......... .......... .......... .......... .......... 44% 57.3M 8s\n", + "262800K .......... .......... .......... .......... .......... 44% 45.3M 8s\n", + "262850K .......... .......... .......... .......... .......... 44% 57.6M 8s\n", + "262900K .......... .......... .......... .......... .......... 44% 54.2M 8s\n", + "262950K .......... .......... .......... .......... .......... 44% 59.3M 8s\n", + "263000K .......... .......... .......... .......... .......... 44% 51.3M 8s\n", + "263050K .......... .......... .......... .......... .......... 44% 50.2M 8s\n", + "263100K .......... .......... .......... .......... .......... 44% 54.7M 8s\n", + "263150K 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.......... .......... .......... .......... .......... 44% 57.4M 8s\n", + "263800K .......... .......... .......... .......... .......... 44% 39.3M 8s\n", + "263850K .......... .......... .......... .......... .......... 44% 47.7M 8s\n", + "263900K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", + "263950K .......... .......... .......... .......... .......... 44% 60.6M 8s\n", + "264000K .......... .......... .......... .......... .......... 44% 44.3M 8s\n", + "264050K .......... .......... .......... .......... .......... 44% 54.2M 8s\n", + "264100K .......... .......... .......... .......... .......... 44% 48.5M 8s\n", + "264150K .......... .......... .......... .......... .......... 44% 62.4M 8s\n", + "264200K .......... .......... .......... .......... .......... 44% 46.3M 8s\n", + "264250K .......... .......... .......... .......... .......... 44% 54.3M 8s\n", + "264300K .......... .......... .......... .......... .......... 44% 49.8M 8s\n", + "264350K 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.......... .......... .......... .......... .......... 44% 57.3M 8s\n", + "265000K .......... .......... .......... .......... .......... 44% 44.4M 8s\n", + "265050K .......... .......... .......... .......... .......... 44% 55.6M 8s\n", + "265100K .......... .......... .......... .......... .......... 44% 54.3M 8s\n", + "265150K .......... .......... .......... .......... .......... 44% 64.2M 8s\n", + "265200K .......... .......... .......... .......... .......... 44% 61.5M 8s\n", + "265250K .......... .......... .......... .......... .......... 44% 48.8M 8s\n", + "265300K .......... .......... .......... .......... .......... 44% 46.4M 8s\n", + "265350K .......... .......... .......... .......... .......... 44% 46.4M 8s\n", + "265400K .......... .......... .......... .......... .......... 44% 56.5M 8s\n", + "265450K .......... .......... .......... .......... .......... 44% 50.6M 8s\n", + "265500K .......... .......... .......... .......... .......... 44% 5.21M 8s\n", + "265550K .......... .......... .......... .......... .......... 44% 68.2M 8s\n", + "265600K .......... .......... .......... .......... .......... 44% 65.1M 8s\n", + "265650K .......... .......... .......... .......... .......... 44% 69.3M 8s\n", + "265700K .......... .......... .......... .......... .......... 44% 70.4M 8s\n", + "265750K .......... .......... .......... .......... .......... 44% 69.9M 8s\n", + "265800K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", + "265850K .......... .......... .......... .......... .......... 44% 57.2M 8s\n", + "265900K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", + "265950K .......... .......... .......... .......... .......... 44% 61.9M 8s\n", + "266000K .......... .......... .......... .......... .......... 44% 61.7M 8s\n", + "266050K .......... .......... .......... .......... .......... 44% 64.7M 8s\n", + "266100K .......... .......... .......... .......... .......... 44% 59.1M 8s\n", + "266150K 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.......... .......... .......... .......... .......... 44% 67.1M 8s\n", + "266800K .......... .......... .......... .......... .......... 44% 55.4M 8s\n", + "266850K .......... .......... .......... .......... .......... 44% 69.5M 8s\n", + "266900K .......... .......... .......... .......... .......... 44% 70.4M 8s\n", + "266950K .......... .......... .......... .......... .......... 44% 50.9M 8s\n", + "267000K .......... .......... .......... .......... .......... 44% 39.0M 8s\n", + "267050K .......... .......... .......... .......... .......... 44% 68.5M 8s\n", + "267100K .......... .......... .......... .......... .......... 44% 66.0M 8s\n", + "267150K .......... .......... .......... .......... .......... 44% 70.5M 8s\n", + "267200K .......... .......... .......... .......... .......... 44% 45.0M 8s\n", + "267250K .......... .......... .......... .......... .......... 44% 50.9M 8s\n", + "267300K .......... .......... .......... .......... .......... 44% 61.5M 8s\n", + "267350K .......... .......... .......... .......... .......... 44% 67.1M 8s\n", + "267400K .......... .......... .......... .......... .......... 44% 57.2M 8s\n", + "267450K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", + "267500K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", + "267550K .......... .......... .......... .......... .......... 44% 52.0M 8s\n", + "267600K .......... .......... .......... .......... .......... 45% 58.6M 8s\n", + "267650K .......... .......... .......... .......... .......... 45% 68.6M 8s\n", + "267700K .......... .......... .......... .......... .......... 45% 56.7M 8s\n", + "267750K .......... .......... .......... .......... .......... 45% 49.0M 8s\n", + "267800K .......... .......... .......... .......... .......... 45% 42.8M 8s\n", + "267850K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", + "267900K .......... .......... .......... .......... .......... 45% 65.3M 8s\n", + "267950K .......... .......... .......... .......... .......... 45% 54.9M 8s\n", + "268000K .......... .......... .......... .......... .......... 45% 39.2M 8s\n", + "268050K .......... .......... .......... .......... .......... 45% 46.8M 8s\n", + "268100K .......... .......... .......... .......... .......... 45% 57.4M 8s\n", + "268150K .......... .......... .......... .......... .......... 45% 74.6M 8s\n", + "268200K .......... .......... .......... .......... .......... 45% 45.7M 8s\n", + "268250K .......... .......... .......... .......... .......... 45% 8.16M 8s\n", + "268300K .......... .......... .......... .......... .......... 45% 66.1M 8s\n", + "268350K .......... .......... .......... .......... .......... 45% 46.8M 8s\n", + "268400K .......... .......... .......... .......... .......... 45% 56.1M 8s\n", + "268450K .......... .......... .......... .......... .......... 45% 66.6M 8s\n", + "268500K .......... .......... .......... .......... .......... 45% 61.9M 8s\n", + "268550K .......... .......... .......... .......... .......... 45% 52.0M 8s\n", + "268600K .......... .......... .......... .......... .......... 45% 37.0M 8s\n", + "268650K .......... .......... .......... .......... .......... 45% 64.3M 8s\n", + "268700K .......... .......... .......... .......... .......... 45% 67.7M 8s\n", + "268750K .......... .......... .......... .......... .......... 45% 65.8M 8s\n", + "268800K .......... .......... .......... .......... .......... 45% 43.5M 8s\n", + "268850K .......... .......... .......... .......... .......... 45% 42.6M 8s\n", + "268900K .......... .......... .......... .......... .......... 45% 59.8M 8s\n", + "268950K .......... .......... .......... .......... .......... 45% 64.4M 8s\n", + "269000K .......... .......... .......... .......... .......... 45% 50.6M 8s\n", + "269050K .......... .......... .......... .......... .......... 45% 46.2M 8s\n", + "269100K .......... .......... .......... .......... .......... 45% 47.5M 8s\n", + "269150K .......... .......... .......... .......... .......... 45% 59.2M 8s\n", + "269200K .......... .......... .......... .......... .......... 45% 64.6M 8s\n", + "269250K .......... .......... .......... .......... .......... 45% 73.6M 8s\n", + "269300K .......... .......... .......... .......... .......... 45% 54.0M 8s\n", + "269350K .......... .......... .......... .......... .......... 45% 65.1M 8s\n", + "269400K .......... .......... .......... .......... .......... 45% 46.2M 8s\n", + "269450K .......... .......... .......... .......... .......... 45% 64.5M 8s\n", + "269500K .......... .......... .......... .......... .......... 45% 65.3M 8s\n", + "269550K .......... .......... .......... .......... .......... 45% 68.0M 8s\n", + "269600K .......... .......... .......... .......... .......... 45% 50.8M 8s\n", + "269650K .......... .......... .......... .......... .......... 45% 59.2M 8s\n", + "269700K .......... .......... .......... .......... .......... 45% 65.8M 8s\n", + "269750K .......... .......... .......... .......... .......... 45% 69.3M 8s\n", + "269800K .......... .......... .......... .......... .......... 45% 55.6M 8s\n", + "269850K .......... .......... .......... .......... .......... 45% 58.0M 8s\n", + "269900K .......... .......... .......... .......... .......... 45% 54.5M 8s\n", + "269950K .......... .......... .......... .......... .......... 45% 50.4M 8s\n", + "270000K .......... .......... .......... .......... .......... 45% 55.5M 8s\n", + "270050K .......... .......... .......... .......... .......... 45% 62.7M 8s\n", + "270100K .......... .......... .......... .......... .......... 45% 68.0M 8s\n", + "270150K .......... .......... .......... .......... .......... 45% 59.6M 8s\n", + "270200K .......... .......... .......... .......... .......... 45% 42.6M 8s\n", + "270250K .......... .......... .......... .......... .......... 45% 55.3M 8s\n", + "270300K .......... .......... .......... .......... .......... 45% 69.9M 8s\n", + "270350K .......... .......... .......... .......... .......... 45% 75.2M 8s\n", + "270400K .......... .......... .......... .......... .......... 45% 55.3M 8s\n", + "270450K .......... .......... .......... .......... .......... 45% 53.1M 8s\n", + "270500K .......... .......... .......... .......... .......... 45% 59.1M 8s\n", + "270550K .......... .......... .......... .......... .......... 45% 57.8M 8s\n", + "270600K .......... .......... .......... .......... .......... 45% 7.64M 8s\n", + "270650K .......... .......... .......... .......... .......... 45% 62.9M 8s\n", + "270700K .......... .......... .......... .......... .......... 45% 73.2M 8s\n", + "270750K .......... .......... .......... .......... .......... 45% 66.2M 8s\n", + "270800K .......... .......... .......... .......... .......... 45% 65.0M 8s\n", + "270850K .......... .......... .......... .......... .......... 45% 62.6M 8s\n", + "270900K .......... .......... .......... .......... .......... 45% 57.8M 8s\n", + "270950K .......... .......... .......... .......... .......... 45% 44.7M 8s\n", + "271000K .......... .......... .......... .......... .......... 45% 44.0M 8s\n", + "271050K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", + "271100K .......... .......... .......... .......... .......... 45% 66.6M 8s\n", + "271150K .......... .......... .......... .......... .......... 45% 57.3M 8s\n", + "271200K .......... .......... .......... .......... .......... 45% 44.9M 8s\n", + "271250K .......... .......... .......... .......... .......... 45% 46.3M 8s\n", + "271300K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", + "271350K .......... .......... .......... .......... .......... 45% 68.1M 8s\n", + "271400K .......... .......... .......... .......... .......... 45% 47.0M 8s\n", + "271450K .......... .......... .......... .......... .......... 45% 54.4M 8s\n", + "271500K .......... .......... .......... .......... .......... 45% 54.8M 8s\n", + "271550K 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.......... .......... .......... .......... .......... 45% 11.1M 8s\n", + "272800K .......... .......... .......... .......... .......... 45% 53.2M 8s\n", + "272850K .......... .......... .......... .......... .......... 45% 58.8M 8s\n", + "272900K .......... .......... .......... .......... .......... 45% 67.6M 8s\n", + "272950K .......... .......... .......... .......... .......... 45% 66.4M 8s\n", + "273000K .......... .......... .......... .......... .......... 45% 57.4M 8s\n", + "273050K .......... .......... .......... .......... .......... 45% 51.9M 8s\n", + "273100K .......... .......... .......... .......... .......... 45% 44.8M 8s\n", + "273150K .......... .......... .......... .......... .......... 45% 58.1M 8s\n", + "273200K .......... .......... .......... .......... .......... 45% 59.8M 8s\n", + "273250K .......... .......... .......... .......... .......... 45% 63.6M 8s\n", + "273300K .......... .......... .......... .......... .......... 45% 47.0M 8s\n", + "273350K 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.......... .......... .......... .......... .......... 46% 69.0M 8s\n", + "274000K .......... .......... .......... .......... .......... 46% 51.9M 8s\n", + "274050K .......... .......... .......... .......... .......... 46% 66.3M 8s\n", + "274100K .......... .......... .......... .......... .......... 46% 52.0M 8s\n", + "274150K .......... .......... .......... .......... .......... 46% 50.0M 8s\n", + "274200K .......... .......... .......... .......... .......... 46% 52.9M 8s\n", + "274250K .......... .......... .......... .......... .......... 46% 50.8M 8s\n", + "274300K .......... .......... .......... .......... .......... 46% 52.2M 8s\n", + "274350K .......... .......... .......... .......... .......... 46% 53.1M 8s\n", + "274400K .......... .......... .......... .......... .......... 46% 43.1M 8s\n", + "274450K .......... .......... .......... .......... .......... 46% 60.8M 8s\n", + "274500K .......... .......... .......... .......... .......... 46% 13.0M 8s\n", + "274550K 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.......... .......... .......... .......... .......... 46% 46.9M 8s\n", + "277000K .......... .......... .......... .......... .......... 46% 42.3M 8s\n", + "277050K .......... .......... .......... .......... .......... 46% 64.2M 8s\n", + "277100K .......... .......... .......... .......... .......... 46% 57.9M 8s\n", + "277150K .......... .......... .......... .......... .......... 46% 51.7M 8s\n", + "277200K .......... .......... .......... .......... .......... 46% 50.8M 8s\n", + "277250K .......... .......... .......... .......... .......... 46% 52.7M 8s\n", + "277300K .......... .......... .......... .......... .......... 46% 54.9M 8s\n", + "277350K .......... .......... .......... .......... .......... 46% 52.3M 8s\n", + "277400K .......... .......... .......... .......... .......... 46% 45.2M 8s\n", + "277450K .......... .......... .......... .......... .......... 46% 53.8M 8s\n", + "277500K .......... .......... .......... .......... .......... 46% 50.3M 8s\n", + "277550K .......... .......... .......... .......... .......... 46% 72.3M 8s\n", + "277600K .......... .......... .......... .......... .......... 46% 59.2M 8s\n", + "277650K .......... .......... .......... .......... .......... 46% 57.7M 8s\n", + "277700K .......... .......... .......... .......... .......... 46% 48.3M 8s\n", + "277750K .......... .......... .......... .......... .......... 46% 58.3M 8s\n", + "277800K .......... .......... .......... .......... .......... 46% 45.6M 8s\n", + "277850K .......... .......... .......... .......... .......... 46% 56.9M 8s\n", + "277900K .......... .......... .......... .......... .......... 46% 58.5M 8s\n", + "277950K .......... .......... .......... .......... .......... 46% 55.5M 8s\n", + "278000K .......... .......... .......... .......... .......... 46% 3.21M 8s\n", + "278050K .......... .......... .......... .......... .......... 46% 62.9M 8s\n", + "278100K .......... .......... .......... .......... .......... 46% 65.4M 8s\n", + "278150K .......... .......... .......... .......... .......... 46% 11.2M 8s\n", + "278200K .......... .......... .......... .......... .......... 46% 47.9M 8s\n", + "278250K .......... .......... .......... .......... .......... 46% 66.9M 8s\n", + "278300K .......... .......... .......... .......... .......... 46% 66.7M 8s\n", + "278350K .......... .......... .......... .......... .......... 46% 3.92M 8s\n", + "278400K .......... .......... .......... .......... .......... 46% 55.5M 8s\n", + "278450K .......... .......... .......... .......... .......... 46% 66.6M 8s\n", + "278500K .......... .......... .......... .......... .......... 46% 60.3M 8s\n", + "278550K .......... .......... .......... .......... .......... 46% 64.3M 8s\n", + "278600K .......... .......... .......... .......... .......... 46% 49.7M 8s\n", + "278650K .......... .......... .......... .......... .......... 46% 44.2M 8s\n", + "278700K .......... .......... .......... .......... .......... 46% 52.6M 8s\n", + "278750K .......... .......... .......... .......... .......... 46% 60.3M 8s\n", + "278800K .......... .......... .......... .......... .......... 46% 58.6M 8s\n", + "278850K .......... .......... .......... .......... .......... 46% 64.1M 8s\n", + "278900K .......... .......... .......... .......... .......... 46% 46.5M 8s\n", + "278950K .......... .......... .......... .......... .......... 46% 50.0M 8s\n", + "279000K .......... .......... .......... .......... .......... 46% 54.8M 8s\n", + "279050K .......... .......... .......... .......... .......... 46% 69.0M 8s\n", + "279100K .......... .......... .......... .......... .......... 46% 66.6M 8s\n", + "279150K .......... .......... .......... .......... .......... 46% 47.9M 8s\n", + "279200K .......... .......... .......... .......... .......... 46% 43.8M 8s\n", + "279250K .......... .......... .......... .......... .......... 46% 64.4M 8s\n", + "279300K .......... .......... .......... .......... .......... 46% 65.2M 8s\n", + "279350K .......... .......... .......... .......... .......... 46% 65.3M 8s\n", + "279400K .......... .......... .......... .......... .......... 46% 39.5M 8s\n", + "279450K .......... .......... .......... .......... .......... 46% 48.0M 8s\n", + "279500K .......... .......... .......... .......... .......... 47% 65.0M 8s\n", + "279550K .......... .......... .......... .......... .......... 47% 62.1M 8s\n", + "279600K .......... .......... .......... .......... .......... 47% 58.3M 8s\n", + "279650K .......... .......... .......... .......... .......... 47% 56.5M 8s\n", + "279700K .......... .......... .......... .......... .......... 47% 45.8M 8s\n", + "279750K .......... .......... .......... .......... .......... 47% 60.6M 8s\n", + "279800K .......... .......... .......... .......... .......... 47% 55.6M 8s\n", + "279850K .......... .......... .......... .......... .......... 47% 60.9M 8s\n", + "279900K .......... .......... .......... .......... .......... 47% 59.3M 8s\n", + "279950K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", + "280000K .......... .......... .......... .......... .......... 47% 48.6M 8s\n", + "280050K .......... .......... .......... .......... .......... 47% 64.9M 8s\n", + "280100K .......... .......... .......... .......... .......... 47% 72.0M 8s\n", + "280150K .......... .......... .......... .......... .......... 47% 60.6M 8s\n", + "280200K .......... .......... .......... .......... .......... 47% 38.1M 8s\n", + "280250K .......... .......... .......... .......... .......... 47% 54.5M 8s\n", + "280300K .......... .......... .......... .......... .......... 47% 5.82M 8s\n", + "280350K .......... .......... .......... .......... .......... 47% 71.2M 8s\n", + "280400K .......... .......... .......... .......... .......... 47% 59.3M 8s\n", + "280450K .......... .......... .......... .......... .......... 47% 61.7M 8s\n", + "280500K .......... .......... .......... .......... .......... 47% 65.3M 8s\n", + "280550K .......... .......... .......... .......... .......... 47% 66.4M 8s\n", + "280600K .......... .......... .......... .......... .......... 47% 40.7M 8s\n", + "280650K .......... .......... .......... .......... .......... 47% 48.4M 8s\n", + "280700K .......... .......... .......... .......... .......... 47% 59.2M 8s\n", + "280750K .......... .......... .......... .......... .......... 47% 63.1M 8s\n", + "280800K .......... .......... .......... .......... .......... 47% 60.0M 8s\n", + "280850K .......... .......... .......... .......... .......... 47% 51.3M 8s\n", + "280900K .......... .......... .......... .......... .......... 47% 48.4M 8s\n", + "280950K .......... .......... .......... .......... .......... 47% 58.0M 8s\n", + "281000K .......... .......... .......... .......... .......... 47% 56.7M 8s\n", + "281050K .......... .......... .......... .......... .......... 47% 68.4M 8s\n", + "281100K .......... .......... .......... .......... .......... 47% 55.3M 8s\n", + "281150K .......... .......... .......... .......... .......... 47% 52.6M 8s\n", + "281200K .......... .......... .......... .......... .......... 47% 47.6M 8s\n", + "281250K .......... .......... .......... .......... .......... 47% 68.5M 8s\n", + "281300K .......... .......... .......... .......... .......... 47% 65.8M 8s\n", + "281350K .......... .......... .......... .......... .......... 47% 54.2M 8s\n", + "281400K .......... .......... .......... .......... .......... 47% 39.8M 8s\n", + "281450K .......... .......... .......... .......... .......... 47% 2.98M 8s\n", + "281500K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", + "281550K .......... .......... .......... .......... .......... 47% 63.7M 8s\n", + "281600K .......... .......... .......... .......... .......... 47% 54.7M 8s\n", + "281650K .......... .......... .......... .......... .......... 47% 65.6M 8s\n", + "281700K .......... .......... .......... .......... .......... 47% 70.2M 8s\n", + "281750K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", + "281800K .......... .......... .......... .......... .......... 47% 38.7M 8s\n", + "281850K .......... .......... .......... .......... .......... 47% 61.0M 8s\n", + "281900K .......... .......... .......... .......... .......... 47% 65.7M 8s\n", + "281950K .......... .......... .......... .......... .......... 47% 67.2M 8s\n", + "282000K .......... .......... .......... .......... .......... 47% 53.4M 8s\n", + "282050K .......... .......... .......... .......... .......... 47% 46.4M 8s\n", + "282100K .......... .......... .......... .......... .......... 47% 48.7M 8s\n", + "282150K .......... .......... .......... .......... .......... 47% 17.6M 8s\n", + "282200K .......... .......... .......... .......... .......... 47% 42.1M 8s\n", + "282250K .......... .......... .......... .......... .......... 47% 51.9M 8s\n", + "282300K .......... .......... .......... .......... .......... 47% 65.1M 8s\n", + "282350K .......... .......... .......... .......... .......... 47% 62.6M 8s\n", + "282400K .......... .......... .......... .......... .......... 47% 60.1M 8s\n", + "282450K .......... .......... .......... .......... .......... 47% 49.0M 8s\n", + "282500K .......... .......... .......... .......... .......... 47% 47.7M 8s\n", + "282550K .......... .......... .......... .......... .......... 47% 56.1M 8s\n", + "282600K .......... .......... .......... .......... .......... 47% 52.3M 8s\n", + "282650K .......... .......... .......... .......... .......... 47% 57.2M 8s\n", + "282700K .......... .......... .......... .......... .......... 47% 45.6M 8s\n", + "282750K .......... .......... .......... .......... .......... 47% 19.4M 8s\n", + "282800K .......... .......... .......... .......... .......... 47% 58.0M 8s\n", + "282850K .......... .......... .......... .......... .......... 47% 61.9M 8s\n", + "282900K .......... .......... .......... .......... .......... 47% 50.4M 8s\n", + "282950K .......... .......... .......... .......... .......... 47% 67.1M 8s\n", + "283000K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", + "283050K .......... .......... .......... .......... .......... 47% 59.0M 8s\n", + "283100K .......... .......... .......... .......... .......... 47% 67.6M 8s\n", + "283150K .......... .......... .......... .......... .......... 47% 46.2M 8s\n", + "283200K .......... .......... .......... .......... .......... 47% 54.7M 8s\n", + "283250K .......... .......... .......... .......... .......... 47% 65.8M 8s\n", + "283300K .......... .......... .......... .......... .......... 47% 47.5M 8s\n", + "283350K .......... .......... .......... .......... .......... 47% 60.8M 8s\n", + "283400K .......... .......... .......... .......... .......... 47% 43.0M 8s\n", + "283450K .......... .......... .......... .......... .......... 47% 16.6M 8s\n", + "283500K .......... .......... .......... .......... .......... 47% 53.7M 8s\n", + "283550K .......... .......... .......... .......... .......... 47% 20.0M 8s\n", + "283600K .......... .......... .......... .......... .......... 47% 44.7M 8s\n", + "283650K .......... .......... .......... .......... .......... 47% 48.0M 8s\n", + "283700K .......... .......... .......... .......... .......... 47% 51.5M 8s\n", + "283750K .......... .......... .......... .......... .......... 47% 67.0M 8s\n", + "283800K .......... .......... .......... .......... .......... 47% 56.5M 8s\n", + "283850K .......... .......... .......... .......... .......... 47% 54.3M 8s\n", + "283900K .......... .......... .......... .......... .......... 47% 45.4M 8s\n", + "283950K .......... .......... .......... .......... .......... 47% 52.8M 8s\n", + "284000K .......... .......... .......... .......... .......... 47% 57.6M 8s\n", + "284050K .......... .......... .......... .......... .......... 47% 67.3M 8s\n", + "284100K .......... .......... .......... .......... .......... 47% 58.4M 8s\n", + "284150K .......... .......... .......... .......... .......... 47% 43.3M 8s\n", + "284200K .......... .......... .......... .......... .......... 47% 45.7M 8s\n", + "284250K .......... .......... .......... .......... .......... 47% 51.7M 8s\n", + "284300K .......... .......... .......... .......... .......... 47% 54.3M 8s\n", + "284350K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", + "284400K .......... .......... .......... .......... .......... 47% 40.2M 8s\n", + "284450K .......... .......... .......... .......... .......... 47% 64.6M 8s\n", + "284500K .......... .......... .......... .......... .......... 47% 57.1M 8s\n", + "284550K .......... .......... .......... .......... .......... 47% 54.8M 8s\n", + "284600K .......... .......... .......... .......... .......... 47% 36.7M 8s\n", + "284650K .......... .......... .......... .......... .......... 47% 50.1M 8s\n", + "284700K .......... .......... .......... .......... .......... 47% 65.9M 8s\n", + "284750K .......... .......... .......... .......... .......... 47% 67.5M 8s\n", + "284800K .......... .......... .......... .......... .......... 47% 42.8M 8s\n", + "284850K .......... .......... .......... .......... .......... 47% 37.5M 8s\n", + "284900K .......... .......... .......... .......... .......... 47% 52.0M 8s\n", + "284950K .......... .......... .......... .......... .......... 47% 51.4M 8s\n", + "285000K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", + "285050K .......... .......... .......... .......... .......... 47% 62.7M 8s\n", + "285100K .......... .......... .......... .......... .......... 47% 44.6M 8s\n", + "285150K .......... .......... .......... .......... .......... 47% 64.3M 8s\n", + "285200K .......... .......... .......... .......... .......... 47% 41.7M 8s\n", + "285250K .......... .......... .......... .......... .......... 47% 49.1M 8s\n", + "285300K .......... .......... .......... .......... .......... 47% 36.0M 8s\n", + "285350K .......... .......... .......... .......... .......... 47% 36.3M 8s\n", + "285400K .......... .......... .......... .......... .......... 47% 32.6M 8s\n", + "285450K .......... .......... .......... .......... .......... 48% 33.9M 8s\n", + "285500K .......... .......... .......... .......... .......... 48% 45.2M 8s\n", + "285550K .......... .......... .......... .......... .......... 48% 56.5M 8s\n", + "285600K .......... .......... .......... .......... .......... 48% 49.4M 8s\n", + "285650K .......... .......... .......... .......... .......... 48% 53.4M 8s\n", + "285700K .......... .......... .......... .......... .......... 48% 58.9M 8s\n", + "285750K .......... .......... .......... .......... .......... 48% 57.0M 8s\n", + "285800K .......... .......... .......... .......... .......... 48% 32.3M 8s\n", + "285850K .......... .......... .......... .......... .......... 48% 51.1M 8s\n", + "285900K .......... .......... .......... .......... .......... 48% 47.3M 8s\n", + "285950K 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.......... .......... .......... .......... .......... 48% 61.2M 8s\n", + "288400K .......... .......... .......... .......... .......... 48% 59.5M 8s\n", + "288450K .......... .......... .......... .......... .......... 48% 60.5M 8s\n", + "288500K .......... .......... .......... .......... .......... 48% 58.0M 8s\n", + "288550K .......... .......... .......... .......... .......... 48% 48.7M 8s\n", + "288600K .......... .......... .......... .......... .......... 48% 55.7M 8s\n", + "288650K .......... .......... .......... .......... .......... 48% 57.8M 8s\n", + "288700K .......... .......... .......... .......... .......... 48% 63.3M 8s\n", + "288750K .......... .......... .......... .......... .......... 48% 50.6M 8s\n", + "288800K .......... .......... .......... .......... .......... 48% 59.9M 8s\n", + "288850K .......... .......... .......... .......... .......... 48% 63.9M 8s\n", + "288900K .......... .......... .......... .......... .......... 48% 49.0M 8s\n", + "288950K .......... .......... .......... .......... .......... 48% 61.5M 8s\n", + "289000K .......... .......... .......... .......... .......... 48% 43.4M 8s\n", + "289050K .......... .......... .......... .......... .......... 48% 59.3M 8s\n", + "289100K .......... .......... .......... .......... .......... 48% 64.8M 8s\n", + "289150K .......... .......... .......... .......... .......... 48% 57.4M 8s\n", + "289200K .......... .......... .......... .......... .......... 48% 61.2M 8s\n", + "289250K .......... .......... .......... .......... .......... 48% 50.6M 8s\n", + "289300K .......... .......... .......... .......... .......... 48% 62.9M 8s\n", + "289350K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", + "289400K .......... .......... .......... .......... .......... 48% 48.5M 8s\n", + "289450K .......... .......... .......... .......... .......... 48% 70.9M 8s\n", + "289500K .......... .......... .......... .......... .......... 48% 53.8M 8s\n", + "289550K .......... .......... .......... .......... .......... 48% 56.7M 8s\n", + "289600K .......... .......... .......... .......... .......... 48% 56.3M 8s\n", + "289650K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", + "289700K .......... .......... .......... .......... .......... 48% 57.1M 8s\n", + "289750K .......... .......... .......... .......... .......... 48% 68.0M 8s\n", + "289800K .......... .......... .......... .......... .......... 48% 51.6M 8s\n", + "289850K .......... .......... .......... .......... .......... 48% 58.7M 8s\n", + "289900K .......... .......... .......... .......... .......... 48% 59.1M 8s\n", + "289950K .......... .......... .......... .......... .......... 48% 48.3M 8s\n", + "290000K .......... .......... .......... .......... .......... 48% 60.0M 8s\n", + "290050K .......... .......... .......... .......... .......... 48% 56.5M 8s\n", + "290100K .......... .......... .......... .......... .......... 48% 57.1M 8s\n", + "290150K .......... .......... .......... .......... .......... 48% 52.6M 8s\n", + "290200K .......... .......... .......... .......... .......... 48% 3.37M 8s\n", + "290250K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", + "290300K .......... .......... .......... .......... .......... 48% 63.3M 8s\n", + "290350K .......... .......... .......... .......... .......... 48% 62.6M 8s\n", + "290400K .......... .......... .......... .......... .......... 48% 59.6M 8s\n", + "290450K .......... .......... .......... .......... .......... 48% 63.9M 8s\n", + "290500K .......... .......... .......... .......... .......... 48% 43.6M 8s\n", + "290550K .......... .......... .......... .......... .......... 48% 37.4M 8s\n", + "290600K .......... .......... .......... .......... .......... 48% 33.5M 8s\n", + "290650K .......... .......... .......... .......... .......... 48% 46.3M 8s\n", + "290700K .......... .......... .......... .......... .......... 48% 37.8M 8s\n", + "290750K .......... .......... .......... .......... .......... 48% 3.68M 8s\n", + "290800K .......... .......... .......... .......... .......... 48% 11.9M 8s\n", + "290850K .......... .......... .......... .......... .......... 48% 32.3M 8s\n", + "290900K .......... .......... .......... .......... .......... 48% 34.8M 8s\n", + "290950K .......... .......... .......... .......... .......... 48% 36.0M 8s\n", + "291000K .......... .......... .......... .......... .......... 48% 34.8M 8s\n", + "291050K .......... .......... .......... .......... .......... 48% 59.1M 8s\n", + "291100K .......... .......... .......... .......... .......... 48% 65.2M 8s\n", + "291150K .......... .......... .......... .......... .......... 48% 66.9M 8s\n", + "291200K .......... .......... .......... .......... .......... 48% 60.1M 8s\n", + "291250K .......... .......... .......... .......... .......... 48% 67.3M 8s\n", + "291300K .......... .......... .......... .......... .......... 48% 41.3M 8s\n", + "291350K .......... .......... .......... .......... .......... 48% 55.0M 8s\n", + "291400K .......... .......... .......... .......... .......... 49% 54.0M 8s\n", + "291450K .......... .......... .......... .......... .......... 49% 65.7M 8s\n", + "291500K .......... .......... .......... .......... .......... 49% 58.1M 8s\n", + "291550K .......... .......... .......... .......... .......... 49% 32.2M 8s\n", + "291600K .......... .......... .......... .......... .......... 49% 39.9M 8s\n", + "291650K .......... .......... .......... .......... .......... 49% 66.8M 8s\n", + "291700K .......... .......... .......... .......... .......... 49% 61.3M 8s\n", + "291750K .......... .......... .......... .......... .......... 49% 38.0M 8s\n", + "291800K .......... .......... .......... .......... .......... 49% 36.2M 8s\n", + "291850K .......... .......... .......... .......... .......... 49% 66.1M 8s\n", + "291900K .......... .......... .......... .......... .......... 49% 65.6M 8s\n", + "291950K .......... .......... .......... .......... .......... 49% 54.3M 8s\n", + "292000K .......... .......... .......... .......... .......... 49% 35.4M 8s\n", + "292050K .......... .......... .......... .......... .......... 49% 54.1M 8s\n", + "292100K .......... .......... .......... .......... .......... 49% 62.7M 8s\n", + "292150K .......... .......... .......... .......... .......... 49% 10.8M 8s\n", + "292200K .......... .......... .......... .......... .......... 49% 3.34M 8s\n", + "292250K .......... .......... .......... .......... .......... 49% 66.8M 8s\n", + "292300K .......... .......... .......... .......... .......... 49% 67.2M 8s\n", + "292350K .......... .......... .......... .......... .......... 49% 50.4M 8s\n", + "292400K .......... .......... .......... .......... .......... 49% 53.2M 8s\n", + "292450K .......... .......... .......... .......... .......... 49% 68.2M 8s\n", + "292500K .......... .......... .......... .......... .......... 49% 67.6M 8s\n", + "292550K .......... .......... .......... .......... .......... 49% 65.3M 8s\n", + "292600K .......... .......... .......... .......... .......... 49% 50.0M 8s\n", + "292650K .......... .......... .......... .......... .......... 49% 49.1M 8s\n", + "292700K .......... .......... .......... .......... .......... 49% 66.3M 8s\n", + "292750K .......... .......... .......... .......... .......... 49% 69.3M 8s\n", + "292800K .......... .......... .......... .......... .......... 49% 60.3M 8s\n", + "292850K .......... .......... .......... .......... .......... 49% 67.8M 8s\n", + "292900K .......... .......... .......... .......... .......... 49% 60.0M 8s\n", + "292950K .......... .......... .......... .......... .......... 49% 58.3M 8s\n", + "293000K .......... .......... .......... .......... .......... 49% 47.3M 8s\n", + "293050K .......... .......... .......... .......... .......... 49% 68.6M 8s\n", + "293100K .......... .......... .......... .......... .......... 49% 5.18M 8s\n", + "293150K .......... .......... .......... .......... .......... 49% 67.9M 8s\n", + "293200K .......... .......... .......... .......... .......... 49% 64.7M 8s\n", + "293250K .......... .......... .......... .......... .......... 49% 4.89M 8s\n", + "293300K .......... .......... .......... .......... .......... 49% 65.7M 8s\n", + "293350K .......... .......... .......... .......... .......... 49% 68.8M 8s\n", + "293400K .......... .......... .......... .......... .......... 49% 54.2M 8s\n", + "293450K .......... .......... .......... .......... .......... 49% 67.0M 8s\n", + "293500K .......... .......... .......... .......... .......... 49% 50.5M 8s\n", + "293550K .......... .......... .......... .......... .......... 49% 46.3M 8s\n", + "293600K .......... .......... .......... .......... .......... 49% 61.0M 8s\n", + "293650K .......... .......... .......... .......... .......... 49% 67.2M 8s\n", + "293700K .......... .......... .......... .......... .......... 49% 69.7M 8s\n", + "293750K .......... .......... .......... .......... .......... 49% 62.6M 8s\n", + "293800K .......... .......... .......... .......... .......... 49% 40.7M 8s\n", + "293850K .......... .......... .......... .......... .......... 49% 11.9M 8s\n", + "293900K .......... .......... .......... .......... .......... 49% 48.2M 8s\n", + "293950K .......... .......... .......... .......... .......... 49% 60.9M 8s\n", + "294000K .......... .......... .......... .......... .......... 49% 54.5M 8s\n", + "294050K .......... .......... .......... .......... .......... 49% 66.4M 8s\n", + "294100K .......... .......... .......... .......... .......... 49% 66.1M 8s\n", + "294150K .......... .......... .......... .......... .......... 49% 64.2M 8s\n", + "294200K .......... .......... .......... .......... .......... 49% 49.5M 8s\n", + "294250K .......... .......... .......... .......... .......... 49% 71.1M 8s\n", + "294300K .......... .......... .......... .......... .......... 49% 63.3M 8s\n", + "294350K .......... .......... .......... .......... .......... 49% 76.2M 8s\n", + "294400K .......... .......... .......... .......... .......... 49% 64.4M 8s\n", + "294450K .......... .......... .......... .......... .......... 49% 62.7M 8s\n", + "294500K .......... .......... .......... .......... .......... 49% 52.2M 8s\n", + "294550K .......... .......... .......... .......... .......... 49% 61.3M 8s\n", + "294600K .......... .......... .......... .......... .......... 49% 58.4M 8s\n", + "294650K .......... .......... .......... .......... .......... 49% 69.7M 8s\n", + "294700K .......... .......... .......... .......... .......... 49% 69.1M 8s\n", + "294750K .......... .......... .......... .......... .......... 49% 55.0M 8s\n", + "294800K .......... .......... .......... .......... .......... 49% 45.4M 8s\n", + "294850K .......... .......... .......... .......... .......... 49% 58.6M 8s\n", + "294900K .......... .......... .......... .......... .......... 49% 68.4M 8s\n", + "294950K .......... .......... .......... .......... .......... 49% 60.4M 8s\n", + "295000K .......... .......... .......... .......... .......... 49% 50.2M 8s\n", + "295050K .......... .......... .......... .......... .......... 49% 49.7M 8s\n", + "295100K .......... .......... .......... .......... .......... 49% 48.4M 8s\n", + "295150K .......... .......... .......... .......... .......... 49% 67.3M 8s\n", + "295200K .......... .......... .......... .......... .......... 49% 61.7M 8s\n", + "295250K .......... .......... .......... .......... .......... 49% 54.8M 8s\n", + "295300K .......... .......... .......... .......... .......... 49% 46.0M 8s\n", + "295350K .......... .......... .......... .......... .......... 49% 55.4M 8s\n", + "295400K .......... .......... .......... .......... .......... 49% 56.5M 8s\n", + "295450K .......... .......... .......... .......... .......... 49% 66.9M 8s\n", + "295500K .......... .......... .......... .......... .......... 49% 68.5M 8s\n", + "295550K .......... .......... .......... .......... .......... 49% 65.9M 7s\n", + "295600K .......... .......... .......... .......... .......... 49% 62.8M 7s\n", + "295650K .......... .......... .......... .......... .......... 49% 66.7M 7s\n", + "295700K .......... .......... .......... .......... .......... 49% 67.4M 7s\n", + "295750K .......... .......... .......... .......... .......... 49% 70.2M 7s\n", + "295800K .......... .......... .......... .......... .......... 49% 57.9M 7s\n", + "295850K .......... .......... .......... .......... .......... 49% 62.7M 7s\n", + "295900K .......... .......... .......... .......... .......... 49% 70.7M 7s\n", + "295950K .......... .......... .......... .......... .......... 49% 69.3M 7s\n", + "296000K .......... .......... .......... .......... .......... 49% 51.6M 7s\n", + "296050K .......... .......... .......... .......... .......... 49% 52.8M 7s\n", + "296100K .......... .......... .......... .......... .......... 49% 55.6M 7s\n", + "296150K .......... .......... .......... .......... .......... 49% 69.5M 7s\n", + "296200K .......... .......... .......... .......... .......... 49% 59.4M 7s\n", + "296250K .......... .......... .......... .......... .......... 49% 53.8M 7s\n", + "296300K .......... .......... .......... .......... .......... 49% 57.9M 7s\n", + "296350K .......... .......... .......... .......... .......... 49% 47.7M 7s\n", + "296400K .......... .......... .......... .......... .......... 49% 59.0M 7s\n", + "296450K .......... .......... .......... .......... .......... 49% 64.2M 7s\n", + "296500K .......... .......... .......... .......... .......... 49% 55.8M 7s\n", + "296550K .......... .......... .......... .......... .......... 49% 55.9M 7s\n", + "296600K .......... .......... .......... .......... .......... 49% 42.3M 7s\n", + "296650K .......... .......... .......... .......... .......... 49% 60.1M 7s\n", + "296700K .......... .......... .......... .......... .......... 49% 64.1M 7s\n", + "296750K .......... .......... .......... .......... .......... 49% 58.8M 7s\n", + "296800K .......... .......... .......... .......... .......... 49% 48.9M 7s\n", + "296850K .......... .......... .......... .......... .......... 49% 44.5M 7s\n", + "296900K .......... .......... .......... .......... .......... 49% 62.4M 7s\n", + "296950K .......... .......... .......... .......... .......... 49% 68.5M 7s\n", + "297000K .......... .......... .......... .......... .......... 49% 50.1M 7s\n", + "297050K .......... .......... .......... .......... .......... 49% 60.5M 7s\n", + "297100K .......... .......... .......... .......... .......... 49% 51.9M 7s\n", + "297150K .......... .......... .......... .......... .......... 49% 51.3M 7s\n", + "297200K .......... .......... .......... .......... .......... 49% 60.8M 7s\n", + "297250K .......... .......... .......... .......... .......... 49% 66.7M 7s\n", + "297300K .......... .......... .......... .......... .......... 49% 57.6M 7s\n", + "297350K .......... .......... .......... .......... .......... 50% 58.5M 7s\n", + "297400K .......... .......... .......... .......... .......... 50% 37.5M 7s\n", + "297450K .......... .......... .......... .......... .......... 50% 61.5M 7s\n", + "297500K .......... .......... .......... .......... .......... 50% 65.5M 7s\n", + "297550K .......... .......... .......... .......... .......... 50% 54.5M 7s\n", + "297600K .......... .......... .......... .......... .......... 50% 46.8M 7s\n", + "297650K .......... .......... .......... .......... .......... 50% 52.5M 7s\n", + "297700K .......... .......... .......... .......... .......... 50% 57.8M 7s\n", + "297750K .......... .......... .......... .......... .......... 50% 49.3M 7s\n", + "297800K .......... .......... .......... .......... .......... 50% 39.1M 7s\n", + "297850K .......... .......... .......... .......... .......... 50% 49.8M 7s\n", + "297900K .......... .......... .......... .......... .......... 50% 51.9M 7s\n", + "297950K .......... .......... .......... .......... .......... 50% 55.2M 7s\n", + "298000K .......... .......... .......... .......... .......... 50% 43.7M 7s\n", + "298050K .......... .......... .......... .......... .......... 50% 57.9M 7s\n", + "298100K .......... .......... .......... .......... .......... 50% 52.0M 7s\n", + "298150K .......... .......... .......... .......... .......... 50% 46.2M 7s\n", + "298200K .......... .......... .......... .......... .......... 50% 50.8M 7s\n", + "298250K .......... .......... .......... .......... .......... 50% 59.8M 7s\n", + "298300K .......... .......... .......... .......... .......... 50% 56.6M 7s\n", + "298350K .......... .......... .......... .......... .......... 50% 51.3M 7s\n", + "298400K .......... .......... .......... .......... .......... 50% 48.7M 7s\n", + "298450K .......... .......... .......... .......... .......... 50% 59.3M 7s\n", + "298500K .......... .......... .......... .......... .......... 50% 4.27M 7s\n", + "298550K .......... .......... .......... .......... .......... 50% 61.4M 7s\n", + "298600K .......... .......... .......... .......... .......... 50% 54.8M 7s\n", + "298650K .......... .......... .......... .......... .......... 50% 61.2M 7s\n", + "298700K .......... .......... .......... .......... .......... 50% 60.3M 7s\n", + "298750K .......... .......... .......... .......... .......... 50% 65.4M 7s\n", + "298800K .......... .......... .......... .......... .......... 50% 45.4M 7s\n", + "298850K .......... .......... .......... .......... .......... 50% 62.6M 7s\n", + "298900K .......... .......... .......... .......... .......... 50% 68.5M 7s\n", + "298950K .......... .......... .......... .......... .......... 50% 60.4M 7s\n", + "299000K .......... .......... .......... .......... .......... 50% 50.8M 7s\n", + "299050K .......... .......... .......... .......... .......... 50% 58.2M 7s\n", + "299100K .......... .......... .......... .......... .......... 50% 54.4M 7s\n", + "299150K .......... .......... .......... .......... .......... 50% 76.3M 7s\n", + "299200K .......... .......... .......... .......... .......... 50% 65.8M 7s\n", + "299250K .......... .......... .......... .......... .......... 50% 49.8M 7s\n", + "299300K .......... .......... .......... .......... .......... 50% 57.7M 7s\n", + "299350K .......... .......... .......... .......... .......... 50% 62.5M 7s\n", + "299400K .......... .......... .......... .......... .......... 50% 47.3M 7s\n", + "299450K .......... .......... .......... .......... .......... 50% 70.9M 7s\n", + "299500K .......... .......... .......... .......... .......... 50% 56.7M 7s\n", + "299550K .......... .......... .......... .......... .......... 50% 54.0M 7s\n", + "299600K .......... .......... .......... .......... .......... 50% 50.4M 7s\n", + "299650K .......... .......... .......... .......... .......... 50% 57.6M 7s\n", + "299700K .......... .......... .......... .......... .......... 50% 67.2M 7s\n", + "299750K .......... .......... .......... .......... .......... 50% 59.3M 7s\n", + "299800K .......... .......... .......... .......... .......... 50% 40.8M 7s\n", + "299850K .......... .......... .......... .......... .......... 50% 47.4M 7s\n", + "299900K .......... .......... .......... .......... .......... 50% 11.2M 7s\n", + "299950K .......... .......... .......... .......... .......... 50% 55.7M 7s\n", + "300000K .......... .......... .......... .......... .......... 50% 58.1M 7s\n", + "300050K .......... .......... .......... .......... .......... 50% 67.1M 7s\n", + "300100K .......... .......... .......... .......... .......... 50% 64.4M 7s\n", + "300150K .......... .......... .......... .......... .......... 50% 56.0M 7s\n", + "300200K .......... .......... .......... .......... .......... 50% 46.6M 7s\n", + "300250K .......... .......... .......... .......... .......... 50% 67.7M 7s\n", + "300300K .......... .......... .......... .......... .......... 50% 67.2M 7s\n", + "300350K .......... .......... .......... .......... .......... 50% 69.6M 7s\n", + "300400K .......... .......... .......... .......... .......... 50% 55.3M 7s\n", + "300450K .......... .......... .......... .......... .......... 50% 61.7M 7s\n", + "300500K .......... .......... .......... .......... .......... 50% 51.2M 7s\n", + "300550K .......... .......... .......... .......... .......... 50% 52.4M 7s\n", + "300600K .......... .......... .......... .......... .......... 50% 53.9M 7s\n", + "300650K .......... .......... .......... .......... .......... 50% 66.3M 7s\n", + "300700K .......... .......... .......... .......... .......... 50% 16.5M 7s\n", + "300750K .......... .......... .......... .......... .......... 50% 66.0M 7s\n", + "300800K .......... .......... .......... .......... .......... 50% 58.7M 7s\n", + "300850K .......... .......... .......... .......... .......... 50% 63.7M 7s\n", + "300900K .......... .......... .......... .......... .......... 50% 68.2M 7s\n", + "300950K .......... .......... .......... .......... .......... 50% 65.1M 7s\n", + "301000K .......... .......... .......... .......... .......... 50% 46.7M 7s\n", + "301050K .......... .......... .......... .......... .......... 50% 49.1M 7s\n", + "301100K .......... .......... .......... .......... .......... 50% 12.9M 7s\n", + "301150K .......... .......... .......... .......... .......... 50% 51.6M 7s\n", + "301200K .......... .......... .......... .......... .......... 50% 56.4M 7s\n", + "301250K .......... .......... .......... .......... .......... 50% 51.1M 7s\n", + "301300K .......... .......... .......... .......... .......... 50% 66.6M 7s\n", + "301350K .......... .......... .......... .......... .......... 50% 60.9M 7s\n", + "301400K .......... .......... .......... .......... .......... 50% 40.4M 7s\n", + "301450K .......... .......... .......... .......... .......... 50% 55.8M 7s\n", + "301500K .......... .......... .......... .......... .......... 50% 60.5M 7s\n", + "301550K .......... .......... .......... .......... .......... 50% 59.5M 7s\n", + "301600K .......... .......... .......... .......... .......... 50% 47.3M 7s\n", + "301650K .......... .......... .......... .......... .......... 50% 56.4M 7s\n", + "301700K .......... .......... .......... .......... .......... 50% 49.2M 7s\n", + "301750K .......... .......... .......... .......... .......... 50% 63.4M 7s\n", + "301800K .......... .......... .......... .......... .......... 50% 53.5M 7s\n", + "301850K .......... .......... .......... .......... .......... 50% 64.0M 7s\n", + "301900K .......... .......... .......... .......... .......... 50% 53.8M 7s\n", + "301950K .......... .......... .......... .......... .......... 50% 54.7M 7s\n", + "302000K .......... .......... .......... .......... .......... 50% 55.8M 7s\n", + "302050K .......... .......... .......... .......... .......... 50% 63.6M 7s\n", + "302100K .......... .......... .......... .......... .......... 50% 63.4M 7s\n", + "302150K .......... .......... .......... .......... .......... 50% 57.3M 7s\n", + "302200K .......... .......... .......... .......... .......... 50% 37.8M 7s\n", + "302250K .......... .......... .......... .......... .......... 50% 60.3M 7s\n", + "302300K .......... .......... .......... .......... .......... 50% 70.9M 7s\n", + "302350K .......... .......... .......... .......... .......... 50% 70.9M 7s\n", + "302400K .......... .......... .......... .......... .......... 50% 48.6M 7s\n", + "302450K .......... .......... .......... .......... .......... 50% 55.8M 7s\n", + "302500K .......... .......... .......... .......... .......... 50% 53.6M 7s\n", + "302550K .......... .......... .......... .......... .......... 50% 70.7M 7s\n", + "302600K .......... .......... .......... .......... .......... 50% 50.4M 7s\n", + "302650K .......... .......... .......... .......... .......... 50% 47.9M 7s\n", + "302700K .......... .......... .......... .......... .......... 50% 51.8M 7s\n", + "302750K .......... .......... .......... .......... .......... 50% 53.1M 7s\n", + "302800K .......... .......... .......... .......... .......... 50% 54.5M 7s\n", + "302850K .......... .......... .......... .......... .......... 50% 67.6M 7s\n", + "302900K .......... .......... .......... .......... .......... 50% 54.1M 7s\n", + "302950K .......... .......... .......... .......... .......... 50% 49.0M 7s\n", + "303000K .......... .......... .......... .......... .......... 50% 43.1M 7s\n", + "303050K .......... .......... .......... .......... .......... 50% 59.5M 7s\n", + "303100K .......... .......... .......... .......... .......... 50% 61.4M 7s\n", + "303150K .......... .......... .......... .......... .......... 50% 57.2M 7s\n", + "303200K .......... .......... .......... .......... .......... 50% 44.4M 7s\n", + "303250K .......... .......... .......... .......... .......... 50% 58.3M 7s\n", + "303300K .......... .......... .......... .......... .......... 51% 61.9M 7s\n", + "303350K .......... .......... .......... .......... .......... 51% 59.9M 7s\n", + "303400K .......... .......... .......... .......... .......... 51% 44.9M 7s\n", + "303450K .......... .......... .......... .......... .......... 51% 47.8M 7s\n", + "303500K .......... .......... .......... .......... .......... 51% 58.8M 7s\n", + "303550K .......... .......... .......... .......... .......... 51% 63.9M 7s\n", + "303600K .......... .......... .......... .......... .......... 51% 53.2M 7s\n", + "303650K .......... .......... .......... .......... .......... 51% 56.5M 7s\n", + "303700K .......... .......... .......... .......... .......... 51% 51.7M 7s\n", + "303750K .......... .......... .......... .......... .......... 51% 52.2M 7s\n", + "303800K .......... .......... .......... .......... .......... 51% 55.9M 7s\n", + "303850K .......... .......... .......... .......... .......... 51% 62.7M 7s\n", + "303900K .......... .......... .......... .......... .......... 51% 56.6M 7s\n", + "303950K .......... .......... .......... .......... .......... 51% 52.1M 7s\n", + "304000K .......... .......... .......... .......... .......... 51% 50.0M 7s\n", + "304050K .......... .......... .......... .......... .......... 51% 67.8M 7s\n", + "304100K .......... .......... .......... .......... .......... 51% 60.9M 7s\n", + "304150K .......... .......... .......... .......... .......... 51% 65.8M 7s\n", + "304200K .......... .......... .......... .......... .......... 51% 46.9M 7s\n", + "304250K .......... .......... .......... .......... .......... 51% 56.5M 7s\n", + "304300K .......... .......... .......... .......... .......... 51% 56.5M 7s\n", + "304350K .......... .......... .......... .......... .......... 51% 75.8M 7s\n", + "304400K .......... .......... .......... .......... .......... 51% 55.7M 7s\n", + "304450K .......... .......... .......... .......... .......... 51% 79.4M 7s\n", + "304500K .......... .......... .......... .......... .......... 51% 57.5M 7s\n", + "304550K .......... .......... .......... .......... .......... 51% 53.3M 7s\n", + "304600K .......... .......... .......... .......... .......... 51% 63.2M 7s\n", + "304650K .......... .......... .......... .......... .......... 51% 66.1M 7s\n", + "304700K .......... .......... .......... .......... .......... 51% 61.7M 7s\n", + "304750K .......... .......... .......... .......... .......... 51% 52.1M 7s\n", + "304800K .......... .......... .......... .......... .......... 51% 66.3M 7s\n", + "304850K .......... .......... .......... .......... .......... 51% 71.1M 7s\n", + "304900K .......... .......... .......... .......... .......... 51% 77.6M 7s\n", + "304950K .......... .......... .......... .......... .......... 51% 67.6M 7s\n", + "305000K .......... .......... .......... .......... .......... 51% 64.5M 7s\n", + "305050K .......... .......... .......... .......... .......... 51% 75.0M 7s\n", + "305100K .......... .......... .......... .......... .......... 51% 70.6M 7s\n", + "305150K .......... .......... .......... .......... .......... 51% 77.3M 7s\n", + "305200K .......... .......... .......... .......... .......... 51% 61.6M 7s\n", + "305250K .......... .......... .......... .......... .......... 51% 62.4M 7s\n", + "305300K .......... .......... .......... .......... .......... 51% 51.1M 7s\n", + "305350K .......... .......... .......... .......... .......... 51% 58.5M 7s\n", + "305400K .......... .......... .......... .......... .......... 51% 58.8M 7s\n", + "305450K .......... .......... .......... .......... .......... 51% 74.9M 7s\n", + "305500K .......... .......... .......... .......... .......... 51% 68.3M 7s\n", + "305550K .......... .......... .......... .......... .......... 51% 46.5M 7s\n", + "305600K .......... .......... .......... .......... .......... 51% 47.3M 7s\n", + "305650K .......... .......... .......... .......... .......... 51% 68.2M 7s\n", + "305700K .......... .......... .......... .......... .......... 51% 74.5M 7s\n", + "305750K .......... .......... .......... .......... .......... 51% 75.1M 7s\n", + "305800K .......... .......... .......... .......... .......... 51% 60.7M 7s\n", + "305850K .......... .......... .......... .......... .......... 51% 52.4M 7s\n", + "305900K .......... .......... .......... .......... .......... 51% 62.0M 7s\n", + "305950K .......... .......... .......... .......... .......... 51% 65.5M 7s\n", + "306000K .......... .......... .......... .......... .......... 51% 61.7M 7s\n", + "306050K .......... .......... .......... .......... .......... 51% 74.4M 7s\n", + "306100K .......... .......... .......... .......... .......... 51% 58.6M 7s\n", + "306150K .......... .......... .......... .......... .......... 51% 65.6M 7s\n", + "306200K .......... .......... .......... .......... .......... 51% 50.2M 7s\n", + "306250K .......... .......... .......... .......... .......... 51% 68.4M 7s\n", + "306300K .......... .......... .......... .......... .......... 51% 72.4M 7s\n", + "306350K .......... .......... .......... .......... .......... 51% 70.2M 7s\n", + "306400K .......... .......... .......... .......... .......... 51% 51.9M 7s\n", + "306450K .......... .......... .......... .......... .......... 51% 61.1M 7s\n", + "306500K .......... .......... .......... .......... .......... 51% 55.6M 7s\n", + "306550K .......... .......... .......... .......... .......... 51% 62.3M 7s\n", + "306600K .......... .......... .......... .......... .......... 51% 61.6M 7s\n", + "306650K .......... .......... .......... .......... .......... 51% 62.8M 7s\n", + "306700K .......... .......... .......... .......... .......... 51% 74.2M 7s\n", + "306750K .......... .......... .......... .......... .......... 51% 60.7M 7s\n", + "306800K .......... .......... .......... .......... .......... 51% 53.4M 7s\n", + "306850K .......... .......... .......... .......... .......... 51% 71.1M 7s\n", + "306900K .......... .......... .......... .......... .......... 51% 73.9M 7s\n", + "306950K .......... .......... .......... .......... .......... 51% 75.8M 7s\n", + "307000K .......... .......... .......... .......... .......... 51% 45.5M 7s\n", + "307050K .......... .......... .......... .......... .......... 51% 58.6M 7s\n", + "307100K .......... .......... .......... .......... .......... 51% 53.2M 7s\n", + "307150K .......... .......... .......... .......... .......... 51% 76.8M 7s\n", + "307200K .......... .......... .......... .......... .......... 51% 71.2M 7s\n", + "307250K .......... .......... .......... .......... .......... 51% 60.1M 7s\n", + "307300K .......... .......... .......... .......... .......... 51% 57.1M 7s\n", + "307350K .......... .......... .......... .......... .......... 51% 49.4M 7s\n", + "307400K .......... .......... .......... .......... .......... 51% 57.7M 7s\n", + "307450K .......... .......... .......... .......... .......... 51% 72.8M 7s\n", + "307500K .......... .......... .......... .......... .......... 51% 64.0M 7s\n", + "307550K .......... .......... .......... .......... .......... 51% 62.4M 7s\n", + "307600K .......... .......... .......... .......... .......... 51% 44.8M 7s\n", + "307650K .......... .......... .......... .......... .......... 51% 50.1M 7s\n", + "307700K .......... .......... .......... .......... .......... 51% 82.0M 7s\n", + "307750K .......... .......... .......... .......... .......... 51% 71.8M 7s\n", + "307800K .......... .......... .......... .......... .......... 51% 47.4M 7s\n", + "307850K .......... .......... .......... .......... .......... 51% 63.2M 7s\n", + "307900K .......... .......... .......... .......... .......... 51% 62.6M 7s\n", + "307950K .......... .......... .......... .......... .......... 51% 59.8M 7s\n", + "308000K .......... .......... .......... .......... .......... 51% 59.5M 7s\n", + "308050K .......... .......... .......... .......... .......... 51% 59.5M 7s\n", + "308100K .......... .......... .......... .......... .......... 51% 56.7M 7s\n", + "308150K .......... .......... .......... .......... .......... 51% 50.4M 7s\n", + "308200K .......... .......... .......... .......... .......... 51% 45.6M 7s\n", + "308250K .......... .......... .......... .......... .......... 51% 73.6M 7s\n", + "308300K .......... .......... .......... .......... .......... 51% 63.4M 7s\n", + "308350K .......... .......... .......... .......... .......... 51% 72.5M 7s\n", + "308400K .......... .......... .......... .......... .......... 51% 52.1M 7s\n", + "308450K .......... .......... .......... .......... .......... 51% 64.8M 7s\n", + "308500K .......... .......... .......... .......... .......... 51% 62.3M 7s\n", + "308550K .......... .......... .......... .......... .......... 51% 76.3M 7s\n", + "308600K .......... .......... .......... .......... .......... 51% 55.1M 7s\n", + "308650K .......... .......... .......... .......... .......... 51% 4.09M 7s\n", + "308700K .......... .......... .......... .......... .......... 51% 76.1M 7s\n", + "308750K .......... .......... .......... .......... .......... 51% 69.0M 7s\n", + "308800K .......... .......... .......... .......... .......... 51% 64.7M 7s\n", + "308850K .......... .......... .......... .......... .......... 51% 62.5M 7s\n", + "308900K .......... .......... .......... .......... .......... 51% 79.4M 7s\n", + "308950K .......... .......... .......... .......... .......... 51% 74.2M 7s\n", + "309000K .......... .......... .......... .......... .......... 51% 44.7M 7s\n", + "309050K .......... .......... .......... .......... .......... 51% 48.4M 7s\n", + "309100K .......... .......... .......... .......... .......... 51% 60.4M 7s\n", + "309150K .......... .......... .......... .......... .......... 51% 70.3M 7s\n", + "309200K .......... .......... .......... .......... .......... 51% 72.4M 7s\n", + "309250K .......... .......... .......... .......... .......... 52% 22.2M 7s\n", + "309300K .......... .......... .......... .......... .......... 52% 46.3M 7s\n", + "309350K .......... .......... .......... .......... .......... 52% 80.1M 7s\n", + "309400K .......... .......... .......... .......... .......... 52% 68.4M 7s\n", + "309450K .......... .......... .......... .......... .......... 52% 48.2M 7s\n", + "309500K .......... .......... .......... .......... .......... 52% 32.4M 7s\n", + "309550K .......... .......... .......... .......... .......... 52% 54.9M 7s\n", + "309600K .......... .......... .......... .......... .......... 52% 71.6M 7s\n", + "309650K .......... .......... .......... .......... .......... 52% 58.8M 7s\n", + "309700K .......... .......... .......... .......... .......... 52% 43.0M 7s\n", + "309750K .......... .......... .......... .......... .......... 52% 36.9M 7s\n", + "309800K .......... .......... .......... .......... .......... 52% 53.0M 7s\n", + "309850K .......... .......... .......... .......... .......... 52% 56.2M 7s\n", + "309900K .......... .......... .......... .......... .......... 52% 44.0M 7s\n", + "309950K .......... .......... .......... .......... .......... 52% 32.8M 7s\n", + "310000K .......... .......... .......... .......... .......... 52% 51.1M 7s\n", + "310050K .......... .......... .......... .......... .......... 52% 79.0M 7s\n", + "310100K .......... .......... .......... .......... .......... 52% 37.0M 7s\n", + "310150K .......... .......... .......... .......... .......... 52% 35.3M 7s\n", + "310200K .......... .......... .......... .......... .......... 52% 40.6M 7s\n", + "310250K .......... .......... .......... .......... .......... 52% 53.6M 7s\n", + "310300K .......... .......... .......... .......... .......... 52% 58.3M 7s\n", + "310350K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", + "310400K .......... .......... .......... .......... .......... 52% 37.2M 7s\n", + "310450K .......... .......... .......... .......... .......... 52% 57.4M 7s\n", + "310500K .......... .......... .......... .......... .......... 52% 51.7M 7s\n", + "310550K .......... .......... .......... .......... .......... 52% 42.3M 7s\n", + "310600K .......... .......... .......... .......... .......... 52% 36.3M 7s\n", + "310650K .......... .......... .......... .......... .......... 52% 46.9M 7s\n", + "310700K .......... .......... .......... .......... .......... 52% 44.7M 7s\n", + "310750K .......... .......... .......... .......... .......... 52% 39.2M 7s\n", + "310800K .......... .......... .......... .......... .......... 52% 31.4M 7s\n", + "310850K .......... .......... .......... .......... .......... 52% 29.0M 7s\n", + "310900K .......... .......... .......... .......... .......... 52% 24.6M 7s\n", + "310950K .......... .......... .......... .......... .......... 52% 37.3M 7s\n", + "311000K .......... .......... .......... .......... .......... 52% 45.5M 7s\n", + "311050K .......... .......... .......... .......... .......... 52% 67.0M 7s\n", + "311100K .......... .......... .......... .......... .......... 52% 42.2M 7s\n", + "311150K .......... .......... .......... .......... .......... 52% 48.8M 7s\n", + "311200K .......... .......... .......... .......... .......... 52% 41.8M 7s\n", + "311250K .......... .......... .......... .......... .......... 52% 61.8M 7s\n", + "311300K .......... .......... .......... .......... .......... 52% 61.3M 7s\n", + "311350K .......... .......... .......... .......... .......... 52% 42.6M 7s\n", + "311400K .......... .......... .......... .......... .......... 52% 31.4M 7s\n", + "311450K .......... .......... .......... .......... .......... 52% 67.6M 7s\n", + "311500K .......... .......... .......... .......... .......... 52% 68.8M 7s\n", + "311550K .......... .......... .......... .......... .......... 52% 41.5M 7s\n", + "311600K .......... .......... .......... .......... .......... 52% 32.7M 7s\n", + "311650K .......... .......... .......... .......... .......... 52% 43.6M 7s\n", + "311700K .......... .......... .......... .......... .......... 52% 77.3M 7s\n", + "311750K .......... .......... .......... .......... .......... 52% 39.8M 7s\n", + "311800K .......... .......... .......... .......... .......... 52% 28.9M 7s\n", + "311850K .......... .......... .......... .......... .......... 52% 49.3M 7s\n", + "311900K .......... .......... .......... .......... .......... 52% 62.8M 7s\n", + "311950K .......... .......... .......... .......... .......... 52% 51.1M 7s\n", + "312000K .......... .......... .......... .......... .......... 52% 41.1M 7s\n", + "312050K .......... .......... .......... .......... .......... 52% 36.8M 7s\n", + "312100K .......... .......... .......... .......... .......... 52% 74.5M 7s\n", + "312150K .......... .......... .......... .......... .......... 52% 51.5M 7s\n", + "312200K .......... .......... .......... .......... .......... 52% 40.0M 7s\n", + "312250K .......... .......... .......... .......... .......... 52% 34.1M 7s\n", + "312300K .......... .......... .......... .......... .......... 52% 62.2M 7s\n", + "312350K .......... .......... .......... .......... .......... 52% 55.0M 7s\n", + "312400K .......... .......... .......... .......... .......... 52% 44.7M 7s\n", + "312450K .......... .......... .......... .......... .......... 52% 46.1M 7s\n", + "312500K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", + "312550K .......... .......... .......... .......... .......... 52% 53.5M 7s\n", + "312600K .......... .......... .......... .......... .......... 52% 41.5M 7s\n", + "312650K .......... .......... .......... .......... .......... 52% 47.4M 7s\n", + "312700K .......... .......... .......... .......... .......... 52% 41.7M 7s\n", + "312750K .......... .......... .......... .......... .......... 52% 54.0M 7s\n", + "312800K .......... .......... .......... .......... .......... 52% 42.3M 7s\n", + "312850K .......... .......... .......... .......... .......... 52% 43.4M 7s\n", + "312900K .......... .......... .......... .......... .......... 52% 37.7M 7s\n", + "312950K .......... .......... .......... .......... .......... 52% 42.2M 7s\n", + "313000K .......... .......... .......... .......... .......... 52% 53.1M 7s\n", + "313050K .......... .......... .......... .......... .......... 52% 46.5M 7s\n", + "313100K .......... .......... .......... .......... .......... 52% 52.4M 7s\n", + "313150K .......... .......... .......... .......... .......... 52% 42.4M 7s\n", + "313200K .......... .......... .......... .......... .......... 52% 42.0M 7s\n", + "313250K .......... .......... .......... .......... .......... 52% 48.8M 7s\n", + "313300K .......... .......... .......... .......... .......... 52% 43.3M 7s\n", + "313350K .......... .......... .......... .......... .......... 52% 44.9M 7s\n", + "313400K .......... .......... .......... .......... .......... 52% 36.4M 7s\n", + "313450K .......... .......... .......... .......... .......... 52% 35.6M 7s\n", + "313500K .......... .......... .......... .......... .......... 52% 41.0M 7s\n", + "313550K .......... .......... .......... .......... .......... 52% 2.01M 7s\n", + "313600K .......... .......... .......... .......... .......... 52% 46.8M 7s\n", + "313650K .......... .......... .......... .......... .......... 52% 62.6M 7s\n", + "313700K .......... .......... .......... .......... .......... 52% 61.7M 7s\n", + "313750K .......... .......... .......... .......... .......... 52% 70.3M 7s\n", + "313800K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", + "313850K .......... .......... .......... .......... .......... 52% 38.4M 7s\n", + "313900K .......... .......... .......... .......... .......... 52% 62.6M 7s\n", + "313950K .......... .......... .......... .......... .......... 52% 72.0M 7s\n", + "314000K .......... .......... .......... .......... .......... 52% 66.8M 7s\n", + "314050K .......... .......... .......... .......... .......... 52% 45.1M 7s\n", + "314100K .......... .......... .......... .......... .......... 52% 34.7M 7s\n", + "314150K .......... .......... .......... .......... .......... 52% 63.9M 7s\n", + "314200K .......... .......... .......... .......... .......... 52% 58.2M 7s\n", + "314250K .......... .......... .......... .......... .......... 52% 72.7M 7s\n", + "314300K .......... .......... .......... .......... .......... 52% 45.4M 7s\n", + "314350K .......... .......... .......... .......... .......... 52% 37.3M 7s\n", + "314400K .......... .......... .......... .......... .......... 52% 69.6M 7s\n", + "314450K .......... .......... .......... .......... .......... 52% 68.6M 7s\n", + "314500K .......... .......... .......... .......... .......... 52% 75.3M 7s\n", + "314550K .......... .......... .......... .......... .......... 52% 74.7M 7s\n", + "314600K .......... .......... .......... .......... .......... 52% 28.3M 7s\n", + "314650K .......... .......... .......... .......... .......... 52% 65.0M 7s\n", + "314700K .......... .......... .......... .......... .......... 52% 71.7M 7s\n", + "314750K .......... .......... .......... .......... .......... 52% 64.4M 7s\n", + "314800K .......... .......... .......... .......... .......... 52% 52.2M 7s\n", + "314850K .......... .......... .......... .......... .......... 52% 42.8M 7s\n", + "314900K .......... .......... .......... .......... .......... 52% 41.7M 7s\n", + "314950K .......... .......... .......... .......... .......... 52% 70.4M 7s\n", + "315000K .......... .......... .......... .......... .......... 52% 61.1M 7s\n", + "315050K .......... .......... .......... .......... .......... 52% 10.5M 7s\n", + "315100K .......... .......... .......... .......... .......... 52% 73.1M 7s\n", + "315150K .......... .......... .......... .......... .......... 52% 70.7M 7s\n", + "315200K .......... .......... .......... .......... .......... 53% 65.8M 7s\n", + "315250K .......... .......... .......... .......... .......... 53% 69.6M 7s\n", + "315300K .......... .......... .......... .......... .......... 53% 73.0M 7s\n", + "315350K .......... .......... .......... .......... .......... 53% 75.7M 7s\n", + "315400K .......... .......... .......... .......... .......... 53% 33.5M 7s\n", + "315450K .......... .......... .......... .......... .......... 53% 54.6M 7s\n", + "315500K .......... .......... .......... .......... .......... 53% 79.5M 7s\n", + "315550K .......... .......... .......... .......... .......... 53% 75.2M 7s\n", + "315600K .......... .......... .......... .......... .......... 53% 61.4M 7s\n", + "315650K .......... .......... .......... .......... .......... 53% 29.8M 7s\n", + "315700K .......... .......... .......... .......... .......... 53% 55.4M 7s\n", + "315750K .......... .......... .......... .......... .......... 53% 70.8M 7s\n", + "315800K .......... .......... .......... .......... .......... 53% 60.4M 7s\n", + "315850K .......... .......... .......... .......... .......... 53% 60.4M 7s\n", + "315900K .......... .......... .......... .......... .......... 53% 38.8M 7s\n", + "315950K .......... .......... .......... .......... .......... 53% 43.5M 7s\n", + "316000K .......... .......... .......... .......... .......... 53% 68.5M 7s\n", + "316050K .......... .......... .......... .......... .......... 53% 80.2M 7s\n", + "316100K .......... .......... .......... .......... .......... 53% 62.2M 7s\n", + "316150K .......... .......... .......... .......... .......... 53% 44.4M 7s\n", + "316200K .......... .......... .......... .......... .......... 53% 34.4M 7s\n", + "316250K .......... .......... .......... .......... .......... 53% 79.6M 7s\n", + "316300K .......... .......... .......... .......... .......... 53% 80.2M 7s\n", + "316350K .......... .......... .......... .......... .......... 53% 56.7M 7s\n", + "316400K .......... .......... .......... .......... .......... 53% 37.5M 7s\n", + "316450K .......... .......... .......... .......... .......... 53% 44.3M 7s\n", + "316500K .......... .......... .......... .......... .......... 53% 62.8M 7s\n", + "316550K .......... .......... .......... .......... .......... 53% 65.7M 7s\n", + "316600K .......... .......... .......... .......... .......... 53% 44.4M 7s\n", + "316650K .......... .......... .......... .......... .......... 53% 31.2M 7s\n", + "316700K .......... .......... .......... .......... .......... 53% 62.9M 7s\n", + "316750K .......... .......... .......... .......... .......... 53% 63.1M 7s\n", + "316800K .......... .......... .......... .......... .......... 53% 46.3M 7s\n", + "316850K .......... .......... .......... .......... .......... 53% 36.4M 7s\n", + "316900K .......... .......... .......... .......... .......... 53% 47.6M 7s\n", + "316950K .......... .......... .......... .......... .......... 53% 73.3M 7s\n", + "317000K .......... .......... .......... .......... .......... 53% 46.0M 7s\n", + "317050K .......... .......... .......... .......... .......... 53% 48.5M 7s\n", + "317100K .......... .......... .......... .......... .......... 53% 32.2M 7s\n", + "317150K .......... .......... .......... .......... .......... 53% 65.0M 7s\n", + "317200K .......... .......... .......... .......... .......... 53% 34.9M 7s\n", + "317250K .......... .......... .......... .......... .......... 53% 31.7M 7s\n", + "317300K .......... .......... .......... .......... .......... 53% 45.4M 7s\n", + "317350K .......... .......... .......... .......... .......... 53% 44.9M 7s\n", + "317400K .......... .......... .......... .......... .......... 53% 46.0M 7s\n", + "317450K .......... .......... .......... .......... .......... 53% 44.2M 7s\n", + "317500K .......... .......... .......... .......... .......... 53% 37.4M 7s\n", + "317550K .......... .......... .......... .......... .......... 53% 50.1M 7s\n", + "317600K .......... .......... .......... .......... .......... 53% 59.3M 7s\n", + "317650K .......... .......... .......... .......... .......... 53% 41.5M 7s\n", + "317700K .......... .......... .......... .......... .......... 53% 35.7M 7s\n", + "317750K .......... .......... .......... .......... .......... 53% 49.7M 7s\n", + "317800K .......... .......... .......... .......... .......... 53% 59.3M 7s\n", + "317850K .......... .......... .......... .......... .......... 53% 55.8M 7s\n", + "317900K .......... .......... .......... .......... .......... 53% 46.4M 7s\n", + "317950K .......... .......... .......... .......... .......... 53% 35.5M 7s\n", + "318000K .......... .......... .......... .......... .......... 53% 65.3M 7s\n", + "318050K .......... .......... .......... .......... .......... 53% 52.1M 7s\n", + "318100K .......... .......... .......... .......... .......... 53% 55.1M 7s\n", + "318150K .......... .......... .......... .......... .......... 53% 43.3M 7s\n", + "318200K .......... .......... .......... .......... .......... 53% 37.2M 7s\n", + "318250K .......... .......... .......... .......... .......... 53% 51.7M 7s\n", + "318300K .......... .......... .......... .......... .......... 53% 43.1M 7s\n", + "318350K .......... .......... .......... .......... .......... 53% 42.9M 7s\n", + "318400K .......... .......... .......... .......... .......... 53% 40.6M 7s\n", + "318450K .......... .......... .......... .......... .......... 53% 75.5M 7s\n", + "318500K .......... .......... .......... .......... .......... 53% 42.3M 7s\n", + "318550K .......... .......... .......... .......... .......... 53% 50.1M 7s\n", + "318600K .......... .......... .......... .......... .......... 53% 36.1M 7s\n", + "318650K .......... .......... .......... .......... .......... 53% 61.5M 7s\n", + "318700K .......... .......... .......... .......... .......... 53% 48.4M 7s\n", + "318750K .......... .......... .......... .......... .......... 53% 48.6M 7s\n", + "318800K .......... .......... .......... .......... .......... 53% 42.7M 7s\n", + "318850K .......... .......... .......... .......... .......... 53% 40.8M 7s\n", + "318900K .......... .......... .......... .......... .......... 53% 42.4M 7s\n", + "318950K .......... .......... .......... .......... .......... 53% 55.2M 7s\n", + "319000K .......... .......... .......... .......... .......... 53% 46.1M 7s\n", + "319050K .......... .......... .......... .......... .......... 53% 39.7M 7s\n", + "319100K .......... .......... .......... .......... .......... 53% 65.4M 7s\n", + "319150K .......... .......... .......... .......... .......... 53% 49.0M 7s\n", + "319200K .......... .......... .......... .......... .......... 53% 44.3M 7s\n", + "319250K .......... .......... .......... .......... .......... 53% 37.7M 7s\n", + "319300K .......... .......... .......... .......... .......... 53% 57.1M 7s\n", + "319350K .......... .......... .......... .......... .......... 53% 51.8M 7s\n", + "319400K .......... .......... .......... .......... .......... 53% 41.4M 7s\n", + "319450K .......... .......... .......... .......... .......... 53% 57.3M 7s\n", + "319500K .......... .......... .......... .......... .......... 53% 40.2M 7s\n", + "319550K .......... .......... .......... .......... .......... 53% 65.8M 7s\n", + "319600K .......... .......... .......... .......... .......... 53% 37.3M 7s\n", + "319650K .......... .......... .......... .......... .......... 53% 68.9M 7s\n", + "319700K .......... .......... .......... .......... .......... 53% 35.4M 7s\n", + "319750K .......... .......... .......... .......... .......... 53% 55.4M 7s\n", + "319800K .......... .......... .......... .......... .......... 53% 39.1M 7s\n", + "319850K .......... .......... .......... .......... .......... 53% 55.7M 7s\n", + "319900K .......... .......... .......... .......... .......... 53% 48.9M 7s\n", + "319950K .......... .......... .......... .......... .......... 53% 39.1M 7s\n", + "320000K .......... .......... .......... .......... .......... 53% 41.9M 7s\n", + "320050K .......... .......... .......... .......... .......... 53% 63.1M 7s\n", + "320100K .......... .......... .......... .......... .......... 53% 50.6M 7s\n", + "320150K .......... .......... .......... .......... .......... 53% 37.8M 7s\n", + "320200K .......... .......... .......... .......... .......... 53% 36.4M 7s\n", + "320250K .......... .......... .......... .......... .......... 53% 79.2M 7s\n", + "320300K .......... .......... .......... .......... .......... 53% 48.5M 7s\n", + "320350K .......... .......... .......... .......... .......... 53% 34.7M 7s\n", + "320400K .......... .......... .......... .......... .......... 53% 43.0M 7s\n", + "320450K .......... .......... .......... .......... .......... 53% 45.4M 7s\n", + "320500K .......... .......... .......... .......... .......... 53% 55.5M 7s\n", + "320550K .......... .......... .......... .......... .......... 53% 33.2M 7s\n", + "320600K .......... .......... .......... .......... .......... 53% 33.9M 7s\n", + "320650K .......... .......... .......... .......... .......... 53% 37.3M 7s\n", + "320700K .......... .......... .......... .......... .......... 53% 21.0M 7s\n", + "320750K .......... .......... .......... .......... .......... 53% 5.10M 7s\n", + "320800K .......... .......... .......... .......... .......... 53% 66.0M 7s\n", + "320850K .......... .......... .......... .......... .......... 53% 71.6M 7s\n", + "320900K .......... .......... .......... .......... .......... 53% 71.4M 7s\n", + "320950K .......... .......... .......... .......... .......... 53% 67.7M 7s\n", + "321000K .......... .......... .......... .......... .......... 53% 56.9M 7s\n", + "321050K .......... .......... .......... .......... .......... 53% 14.5M 7s\n", + "321100K .......... .......... .......... .......... .......... 53% 65.0M 7s\n", + "321150K .......... .......... .......... .......... .......... 54% 50.4M 7s\n", + "321200K .......... .......... .......... .......... .......... 54% 63.8M 7s\n", + "321250K .......... .......... .......... .......... .......... 54% 72.9M 7s\n", + "321300K .......... .......... .......... .......... .......... 54% 67.4M 7s\n", + "321350K .......... .......... .......... .......... .......... 54% 23.5M 7s\n", + "321400K .......... .......... .......... .......... .......... 54% 39.2M 7s\n", + "321450K .......... .......... .......... .......... .......... 54% 58.4M 7s\n", + "321500K .......... .......... .......... .......... .......... 54% 59.3M 7s\n", + "321550K .......... .......... .......... .......... .......... 54% 32.3M 7s\n", + "321600K .......... .......... .......... .......... .......... 54% 51.9M 7s\n", + "321650K .......... .......... .......... .......... .......... 54% 71.4M 7s\n", + "321700K .......... .......... .......... .......... .......... 54% 31.7M 7s\n", + "321750K .......... .......... .......... .......... .......... 54% 33.8M 7s\n", + "321800K .......... .......... .......... .......... .......... 54% 34.7M 7s\n", + "321850K .......... .......... .......... .......... .......... 54% 52.4M 7s\n", + "321900K .......... .......... .......... .......... .......... 54% 28.7M 7s\n", + "321950K .......... .......... .......... .......... .......... 54% 38.1M 7s\n", + "322000K .......... .......... .......... .......... .......... 54% 59.5M 7s\n", + "322050K .......... .......... .......... .......... .......... 54% 63.5M 7s\n", + "322100K .......... .......... .......... .......... .......... 54% 31.6M 7s\n", + "322150K .......... .......... .......... .......... .......... 54% 34.7M 7s\n", + "322200K .......... .......... .......... .......... .......... 54% 63.1M 7s\n", + "322250K .......... .......... .......... .......... .......... 54% 36.0M 7s\n", + "322300K .......... .......... .......... .......... .......... 54% 42.3M 7s\n", + "322350K .......... .......... .......... .......... .......... 54% 33.0M 7s\n", + "322400K .......... .......... .......... .......... .......... 54% 63.1M 7s\n", + "322450K .......... .......... .......... .......... .......... 54% 47.5M 7s\n", + "322500K .......... .......... .......... .......... .......... 54% 38.4M 7s\n", + "322550K .......... .......... .......... .......... .......... 54% 33.5M 7s\n", + "322600K .......... .......... .......... .......... .......... 54% 56.4M 7s\n", + "322650K .......... .......... .......... .......... .......... 54% 48.0M 7s\n", + "322700K .......... .......... .......... .......... .......... 54% 43.1M 7s\n", + "322750K .......... .......... .......... .......... .......... 54% 32.8M 7s\n", + "322800K .......... .......... .......... .......... .......... 54% 44.8M 7s\n", + "322850K .......... .......... .......... .......... .......... 54% 33.8M 7s\n", + "322900K .......... .......... .......... .......... .......... 54% 33.4M 7s\n", + "322950K .......... .......... .......... .......... .......... 54% 34.6M 7s\n", + "323000K .......... .......... .......... .......... .......... 54% 3.66M 7s\n", + "323050K .......... .......... .......... .......... .......... 54% 67.2M 7s\n", + "323100K .......... .......... .......... .......... .......... 54% 72.4M 7s\n", + "323150K .......... .......... .......... .......... .......... 54% 70.4M 7s\n", + "323200K .......... .......... .......... .......... .......... 54% 59.2M 7s\n", + "323250K .......... .......... .......... .......... .......... 54% 27.4M 7s\n", + "323300K .......... .......... .......... .......... .......... 54% 49.1M 7s\n", + "323350K .......... .......... .......... .......... .......... 54% 69.5M 7s\n", + "323400K .......... .......... .......... .......... .......... 54% 58.1M 7s\n", + "323450K .......... .......... .......... .......... .......... 54% 20.1M 7s\n", + "323500K .......... .......... .......... .......... .......... 54% 49.6M 7s\n", + "323550K .......... .......... .......... .......... .......... 54% 76.3M 7s\n", + "323600K .......... .......... .......... .......... .......... 54% 70.3M 7s\n", + "323650K .......... .......... .......... .......... .......... 54% 21.9M 7s\n", + "323700K .......... .......... .......... .......... .......... 54% 47.8M 7s\n", + "323750K .......... .......... .......... .......... .......... 54% 73.2M 7s\n", + "323800K .......... .......... .......... .......... .......... 54% 29.9M 7s\n", + "323850K .......... .......... .......... .......... .......... 54% 45.6M 7s\n", + "323900K .......... .......... .......... .......... .......... 54% 56.4M 7s\n", + "323950K .......... .......... .......... .......... .......... 54% 51.7M 7s\n", + "324000K .......... .......... .......... .......... .......... 54% 47.2M 7s\n", + "324050K .......... .......... .......... .......... .......... 54% 27.7M 7s\n", + "324100K .......... .......... .......... .......... .......... 54% 38.6M 7s\n", + "324150K .......... .......... .......... .......... .......... 54% 49.7M 7s\n", + "324200K .......... .......... .......... .......... .......... 54% 44.4M 7s\n", + "324250K .......... .......... .......... .......... .......... 54% 34.9M 7s\n", + "324300K .......... .......... .......... .......... .......... 54% 3.78M 7s\n", + "324350K .......... .......... .......... .......... .......... 54% 52.8M 7s\n", + "324400K .......... .......... .......... .......... .......... 54% 50.6M 7s\n", + "324450K .......... .......... .......... .......... .......... 54% 68.5M 7s\n", + "324500K .......... .......... .......... .......... .......... 54% 71.9M 7s\n", + "324550K .......... .......... .......... .......... .......... 54% 29.8M 7s\n", + "324600K .......... .......... .......... .......... .......... 54% 37.4M 7s\n", + "324650K .......... .......... .......... .......... .......... 54% 57.1M 7s\n", + "324700K .......... .......... .......... .......... .......... 54% 70.0M 7s\n", + "324750K .......... .......... .......... .......... .......... 54% 27.2M 7s\n", + "324800K .......... .......... .......... .......... .......... 54% 43.8M 7s\n", + "324850K .......... .......... .......... .......... .......... 54% 61.5M 7s\n", + "324900K .......... .......... .......... .......... .......... 54% 68.9M 7s\n", + "324950K .......... .......... .......... .......... .......... 54% 70.7M 7s\n", + "325000K .......... .......... .......... .......... .......... 54% 20.9M 7s\n", + "325050K .......... .......... .......... .......... .......... 54% 49.7M 7s\n", + "325100K .......... .......... .......... .......... .......... 54% 45.2M 7s\n", + "325150K .......... .......... .......... .......... .......... 54% 40.9M 7s\n", + "325200K .......... .......... .......... .......... .......... 54% 55.8M 7s\n", + "325250K .......... .......... .......... .......... .......... 54% 39.2M 7s\n", + "325300K .......... .......... .......... .......... .......... 54% 47.0M 7s\n", + "325350K .......... .......... .......... .......... .......... 54% 59.6M 7s\n", + "325400K .......... .......... .......... .......... .......... 54% 21.3M 7s\n", + "325450K .......... .......... .......... .......... .......... 54% 62.0M 7s\n", + "325500K .......... .......... .......... .......... .......... 54% 79.6M 7s\n", + "325550K .......... .......... .......... .......... .......... 54% 68.5M 7s\n", + "325600K .......... .......... .......... .......... .......... 54% 38.7M 7s\n", + "325650K .......... .......... .......... .......... .......... 54% 32.4M 7s\n", + "325700K .......... .......... .......... .......... .......... 54% 69.1M 7s\n", + "325750K .......... .......... .......... .......... .......... 54% 71.8M 7s\n", + "325800K .......... .......... .......... .......... .......... 54% 33.4M 7s\n", + "325850K .......... .......... .......... .......... .......... 54% 25.1M 7s\n", + "325900K .......... .......... .......... .......... .......... 54% 68.3M 7s\n", + "325950K .......... .......... .......... .......... .......... 54% 68.3M 7s\n", + "326000K .......... .......... .......... .......... .......... 54% 41.6M 7s\n", + "326050K .......... .......... .......... .......... .......... 54% 37.1M 7s\n", + "326100K .......... .......... .......... .......... .......... 54% 32.7M 7s\n", + "326150K .......... .......... .......... .......... .......... 54% 23.7M 7s\n", + "326200K .......... .......... .......... .......... .......... 54% 18.5M 7s\n", + "326250K .......... .......... .......... .......... .......... 54% 60.2M 7s\n", + "326300K .......... .......... .......... .......... .......... 54% 49.3M 7s\n", + "326350K .......... .......... .......... .......... .......... 54% 41.2M 7s\n", + "326400K .......... .......... .......... .......... .......... 54% 51.1M 7s\n", + "326450K .......... .......... .......... .......... .......... 54% 38.4M 7s\n", + "326500K .......... .......... .......... .......... .......... 54% 47.6M 7s\n", + "326550K .......... .......... .......... .......... .......... 54% 3.63M 7s\n", + "326600K .......... .......... .......... .......... .......... 54% 55.7M 7s\n", + "326650K .......... .......... .......... .......... .......... 54% 63.5M 7s\n", + "326700K .......... .......... .......... .......... .......... 54% 72.3M 7s\n", + "326750K .......... .......... .......... .......... .......... 54% 69.2M 7s\n", + "326800K .......... .......... .......... .......... .......... 54% 64.3M 7s\n", + "326850K .......... .......... .......... .......... .......... 54% 67.3M 7s\n", + "326900K .......... .......... .......... .......... .......... 54% 69.6M 7s\n", + "326950K .......... .......... .......... .......... .......... 54% 67.0M 7s\n", + "327000K .......... .......... .......... .......... .......... 54% 10.2M 7s\n", + "327050K .......... .......... .......... .......... .......... 54% 61.2M 7s\n", + "327100K .......... .......... .......... .......... .......... 55% 62.7M 7s\n", + "327150K .......... .......... .......... .......... .......... 55% 19.7M 7s\n", + "327200K .......... .......... .......... .......... .......... 55% 43.3M 7s\n", + "327250K .......... .......... .......... .......... .......... 55% 64.0M 7s\n", + "327300K .......... .......... .......... .......... .......... 55% 21.6M 7s\n", + "327350K .......... .......... .......... .......... .......... 55% 37.2M 7s\n", + "327400K .......... .......... .......... .......... .......... 55% 58.5M 7s\n", + "327450K .......... .......... .......... .......... .......... 55% 19.8M 7s\n", + "327500K .......... .......... .......... .......... .......... 55% 39.3M 7s\n", + "327550K .......... .......... .......... .......... .......... 55% 74.3M 7s\n", + "327600K .......... .......... .......... .......... .......... 55% 18.7M 7s\n", + "327650K .......... .......... .......... .......... .......... 55% 30.2M 7s\n", + "327700K .......... .......... .......... .......... .......... 55% 68.4M 7s\n", + "327750K .......... .......... .......... .......... .......... 55% 21.4M 7s\n", + "327800K .......... .......... .......... .......... .......... 55% 31.8M 7s\n", + "327850K .......... .......... .......... .......... .......... 55% 69.1M 7s\n", + "327900K .......... .......... .......... .......... .......... 55% 23.0M 7s\n", + "327950K .......... .......... .......... .......... .......... 55% 27.8M 7s\n", + "328000K .......... .......... .......... .......... .......... 55% 55.8M 7s\n", + "328050K .......... .......... .......... .......... .......... 55% 24.8M 7s\n", + "328100K .......... .......... .......... .......... .......... 55% 35.8M 7s\n", + "328150K .......... .......... .......... .......... .......... 55% 62.7M 7s\n", + "328200K .......... .......... .......... .......... .......... 55% 18.5M 7s\n", + "328250K .......... .......... .......... .......... .......... 55% 43.2M 7s\n", + "328300K .......... .......... .......... .......... .......... 55% 54.4M 7s\n", + "328350K .......... .......... .......... .......... .......... 55% 20.0M 7s\n", + "328400K .......... .......... .......... .......... .......... 55% 38.9M 7s\n", + "328450K .......... .......... .......... .......... .......... 55% 55.6M 7s\n", + "328500K .......... .......... .......... .......... .......... 55% 18.1M 7s\n", + "328550K .......... .......... .......... .......... .......... 55% 50.4M 7s\n", + "328600K .......... .......... .......... .......... .......... 55% 47.0M 7s\n", + "328650K .......... .......... .......... .......... .......... 55% 19.1M 7s\n", + "328700K .......... .......... .......... .......... .......... 55% 54.0M 7s\n", + "328750K .......... .......... .......... .......... .......... 55% 55.9M 7s\n", + "328800K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", + "328850K .......... .......... .......... .......... .......... 55% 40.6M 7s\n", + "328900K .......... .......... .......... .......... .......... 55% 52.9M 7s\n", + "328950K .......... .......... .......... .......... .......... 55% 19.6M 7s\n", + "329000K .......... .......... .......... .......... .......... 55% 42.5M 7s\n", + "329050K .......... .......... .......... .......... .......... 55% 61.3M 7s\n", + "329100K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", + "329150K .......... .......... .......... .......... .......... 55% 53.4M 7s\n", + "329200K .......... .......... .......... .......... .......... 55% 47.0M 7s\n", + "329250K .......... .......... .......... .......... .......... 55% 21.5M 7s\n", + "329300K .......... .......... .......... .......... .......... 55% 40.0M 7s\n", + "329350K .......... .......... .......... .......... .......... 55% 59.9M 7s\n", + "329400K .......... .......... .......... .......... .......... 55% 18.7M 7s\n", + "329450K .......... .......... .......... .......... .......... 55% 47.5M 7s\n", + "329500K .......... .......... .......... .......... .......... 55% 58.8M 7s\n", + "329550K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", + "329600K .......... .......... .......... .......... .......... 55% 56.3M 7s\n", + "329650K .......... .......... .......... .......... .......... 55% 59.6M 7s\n", + "329700K .......... .......... .......... .......... .......... 55% 17.9M 7s\n", + "329750K .......... .......... .......... .......... .......... 55% 41.7M 7s\n", + "329800K .......... .......... .......... .......... .......... 55% 51.6M 7s\n", + "329850K .......... .......... .......... .......... .......... 55% 18.3M 7s\n", + "329900K .......... .......... .......... .......... .......... 55% 52.0M 7s\n", + "329950K .......... .......... .......... .......... .......... 55% 61.4M 7s\n", + "330000K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", + "330050K .......... .......... .......... .......... .......... 55% 58.3M 7s\n", + "330100K .......... .......... .......... .......... .......... 55% 55.3M 7s\n", + "330150K .......... .......... .......... .......... .......... 55% 20.2M 7s\n", + "330200K .......... .......... .......... .......... .......... 55% 35.7M 7s\n", + "330250K .......... .......... .......... .......... .......... 55% 57.8M 7s\n", + "330300K .......... .......... .......... .......... .......... 55% 17.6M 7s\n", + "330350K .......... .......... .......... .......... .......... 55% 54.5M 7s\n", + "330400K .......... .......... .......... .......... .......... 55% 53.9M 7s\n", + "330450K .......... .......... .......... .......... .......... 55% 18.9M 7s\n", + "330500K .......... .......... .......... .......... .......... 55% 49.3M 7s\n", + "330550K .......... .......... .......... .......... .......... 55% 63.6M 7s\n", + "330600K .......... .......... .......... .......... .......... 55% 13.1M 7s\n", + "330650K .......... .......... .......... .......... .......... 55% 60.5M 7s\n", + "330700K .......... .......... .......... .......... .......... 55% 52.4M 7s\n", + "330750K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", + "330800K .......... .......... .......... .......... .......... 55% 51.1M 7s\n", + "330850K .......... .......... .......... .......... .......... 55% 58.0M 7s\n", + "330900K .......... .......... .......... .......... .......... 55% 17.0M 7s\n", + "330950K .......... .......... .......... .......... .......... 55% 59.3M 7s\n", + "331000K .......... .......... .......... .......... .......... 55% 53.2M 7s\n", + "331050K .......... .......... .......... .......... .......... 55% 18.2M 7s\n", + "331100K .......... .......... .......... .......... .......... 55% 58.4M 7s\n", + "331150K .......... .......... .......... .......... .......... 55% 64.8M 7s\n", + "331200K .......... .......... .......... .......... .......... 55% 16.1M 7s\n", + "331250K .......... .......... .......... .......... .......... 55% 56.3M 7s\n", + "331300K .......... .......... .......... .......... .......... 55% 58.3M 7s\n", + "331350K .......... .......... .......... .......... .......... 55% 17.0M 7s\n", + "331400K .......... .......... .......... .......... .......... 55% 51.1M 7s\n", + "331450K .......... .......... .......... .......... .......... 55% 60.1M 7s\n", + "331500K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", + "331550K .......... .......... .......... .......... .......... 55% 47.8M 7s\n", + "331600K .......... .......... .......... .......... .......... 55% 56.1M 7s\n", + "331650K .......... .......... .......... .......... .......... 55% 18.8M 7s\n", + "331700K .......... .......... .......... .......... .......... 55% 52.0M 7s\n", + "331750K .......... .......... .......... .......... .......... 55% 53.1M 7s\n", + "331800K .......... .......... .......... .......... .......... 55% 16.8M 7s\n", + "331850K .......... .......... .......... .......... .......... 55% 49.6M 7s\n", + "331900K .......... .......... .......... .......... .......... 55% 60.3M 7s\n", + "331950K .......... .......... .......... .......... .......... 55% 21.1M 7s\n", + "332000K .......... .......... .......... .......... .......... 55% 41.7M 7s\n", + "332050K .......... .......... .......... .......... .......... 55% 54.9M 7s\n", + "332100K .......... .......... .......... .......... .......... 55% 20.3M 7s\n", + "332150K .......... .......... .......... .......... .......... 55% 39.0M 7s\n", + "332200K .......... .......... .......... .......... .......... 55% 50.0M 7s\n", + "332250K .......... .......... .......... .......... .......... 55% 20.4M 7s\n", + "332300K .......... .......... .......... .......... .......... 55% 41.8M 7s\n", + "332350K .......... .......... .......... .......... .......... 55% 59.8M 7s\n", + "332400K .......... .......... .......... .......... .......... 55% 20.4M 7s\n", + "332450K .......... .......... .......... .......... .......... 55% 45.8M 7s\n", + "332500K .......... .......... .......... .......... .......... 55% 53.3M 7s\n", + "332550K .......... .......... .......... .......... .......... 55% 68.7M 7s\n", + "332600K .......... .......... .......... .......... .......... 55% 16.5M 7s\n", + "332650K .......... .......... .......... .......... .......... 55% 48.2M 7s\n", + "332700K .......... .......... .......... .......... .......... 55% 69.2M 7s\n", + "332750K .......... .......... .......... .......... .......... 55% 17.9M 7s\n", + "332800K .......... .......... .......... .......... .......... 55% 49.7M 7s\n", + "332850K .......... .......... .......... .......... .......... 55% 70.8M 7s\n", + "332900K .......... .......... .......... .......... .......... 55% 21.4M 7s\n", + "332950K .......... .......... .......... .......... .......... 55% 45.2M 7s\n", + "333000K .......... .......... .......... .......... .......... 56% 48.6M 7s\n", + "333050K .......... .......... .......... .......... .......... 56% 22.0M 7s\n", + "333100K .......... .......... .......... .......... .......... 56% 40.6M 7s\n", + "333150K .......... .......... .......... .......... .......... 56% 60.1M 7s\n", + "333200K .......... .......... .......... .......... .......... 56% 19.7M 7s\n", + "333250K .......... .......... .......... .......... .......... 56% 37.4M 7s\n", + "333300K .......... .......... .......... .......... .......... 56% 68.4M 7s\n", + "333350K .......... .......... .......... .......... .......... 56% 21.3M 7s\n", + "333400K .......... .......... .......... .......... .......... 56% 45.2M 7s\n", + "333450K .......... .......... .......... .......... .......... 56% 50.3M 7s\n", + "333500K .......... .......... .......... .......... .......... 56% 20.3M 7s\n", + "333550K .......... .......... .......... .......... .......... 56% 54.0M 7s\n", + "333600K .......... .......... .......... .......... .......... 56% 48.0M 7s\n", + "333650K .......... .......... .......... .......... .......... 56% 65.0M 7s\n", + "333700K .......... .......... .......... .......... .......... 56% 20.3M 7s\n", + "333750K .......... .......... .......... .......... .......... 56% 44.2M 7s\n", + "333800K .......... .......... .......... .......... .......... 56% 45.8M 7s\n", + "333850K .......... .......... .......... .......... .......... 56% 20.8M 7s\n", + "333900K .......... .......... .......... .......... .......... 56% 57.4M 7s\n", + "333950K .......... .......... .......... .......... .......... 56% 66.6M 7s\n", + "334000K .......... .......... .......... .......... .......... 56% 17.3M 7s\n", + "334050K .......... .......... .......... .......... .......... 56% 45.8M 7s\n", + "334100K .......... .......... .......... .......... .......... 56% 66.4M 7s\n", + "334150K .......... .......... .......... .......... .......... 56% 59.7M 7s\n", + "334200K .......... .......... .......... .......... .......... 56% 21.6M 7s\n", + "334250K .......... .......... .......... .......... .......... 56% 34.7M 7s\n", + "334300K .......... .......... .......... .......... .......... 56% 61.9M 6s\n", + "334350K .......... .......... .......... .......... .......... 56% 21.9M 6s\n", + "334400K .......... .......... .......... .......... .......... 56% 43.7M 6s\n", + "334450K .......... .......... .......... .......... .......... 56% 53.5M 6s\n", + "334500K .......... .......... .......... .......... .......... 56% 23.5M 6s\n", + "334550K .......... .......... .......... .......... .......... 56% 44.2M 6s\n", + "334600K .......... .......... .......... .......... .......... 56% 38.6M 6s\n", + "334650K .......... .......... .......... .......... .......... 56% 29.1M 6s\n", + "334700K .......... .......... .......... .......... .......... 56% 40.6M 6s\n", + "334750K .......... .......... .......... .......... .......... 56% 43.9M 6s\n", + "334800K .......... .......... .......... .......... .......... 56% 57.0M 6s\n", + "334850K .......... .......... .......... .......... .......... 56% 25.6M 6s\n", + "334900K .......... .......... .......... .......... .......... 56% 32.6M 6s\n", + "334950K .......... .......... .......... .......... .......... 56% 51.4M 6s\n", + "335000K .......... .......... .......... .......... .......... 56% 24.5M 6s\n", + "335050K .......... .......... .......... .......... .......... 56% 46.6M 6s\n", + "335100K .......... .......... .......... .......... .......... 56% 39.5M 6s\n", + "335150K .......... .......... .......... .......... .......... 56% 27.2M 6s\n", + "335200K .......... .......... .......... .......... .......... 56% 49.5M 6s\n", + "335250K .......... .......... .......... .......... .......... 56% 40.2M 6s\n", + "335300K .......... .......... .......... .......... .......... 56% 52.5M 6s\n", + "335350K .......... .......... .......... .......... .......... 56% 27.4M 6s\n", + "335400K .......... .......... .......... .......... .......... 56% 32.5M 6s\n", + "335450K .......... .......... .......... .......... .......... 56% 48.6M 6s\n", + "335500K .......... .......... .......... .......... .......... 56% 26.0M 6s\n", + "335550K .......... .......... .......... .......... .......... 56% 45.5M 6s\n", + "335600K .......... .......... .......... .......... .......... 56% 44.5M 6s\n", + "335650K .......... .......... .......... .......... .......... 56% 60.7M 6s\n", + "335700K .......... .......... .......... .......... .......... 56% 25.0M 6s\n", + "335750K 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.......... .......... .......... .......... .......... 58% 64.9M 6s\n", + "345400K .......... .......... .......... .......... .......... 58% 16.6M 6s\n", + "345450K .......... .......... .......... .......... .......... 58% 64.6M 6s\n", + "345500K .......... .......... .......... .......... .......... 58% 23.0M 6s\n", + "345550K .......... .......... .......... .......... .......... 58% 38.1M 6s\n", + "345600K .......... .......... .......... .......... .......... 58% 48.6M 6s\n", + "345650K .......... .......... .......... .......... .......... 58% 66.5M 6s\n", + "345700K .......... .......... .......... .......... .......... 58% 21.1M 6s\n", + "345750K .......... .......... .......... .......... .......... 58% 48.3M 6s\n", + "345800K .......... .......... .......... .......... .......... 58% 21.4M 6s\n", + "345850K .......... .......... .......... .......... .......... 58% 37.4M 6s\n", + "345900K .......... .......... .......... .......... .......... 58% 46.9M 6s\n", + "345950K 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.......... .......... .......... .......... .......... 58% 50.5M 6s\n", + "346600K .......... .......... .......... .......... .......... 58% 22.5M 6s\n", + "346650K .......... .......... .......... .......... .......... 58% 53.5M 6s\n", + "346700K .......... .......... .......... .......... .......... 58% 60.5M 6s\n", + "346750K .......... .......... .......... .......... .......... 58% 22.2M 6s\n", + "346800K .......... .......... .......... .......... .......... 58% 40.7M 6s\n", + "346850K .......... .......... .......... .......... .......... 58% 47.2M 6s\n", + "346900K .......... .......... .......... .......... .......... 58% 60.6M 6s\n", + "346950K .......... .......... .......... .......... .......... 58% 25.7M 6s\n", + "347000K .......... .......... .......... .......... .......... 58% 32.1M 6s\n", + "347050K .......... .......... .......... .......... .......... 58% 54.4M 6s\n", + "347100K .......... .......... .......... .......... .......... 58% 26.3M 6s\n", + "347150K 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.......... .......... .......... .......... .......... 59% 28.5M 6s\n", + "356800K .......... .......... .......... .......... .......... 60% 44.5M 6s\n", + "356850K .......... .......... .......... .......... .......... 60% 60.3M 6s\n", + "356900K .......... .......... .......... .......... .......... 60% 73.3M 6s\n", + "356950K .......... .......... .......... .......... .......... 60% 27.6M 6s\n", + "357000K .......... .......... .......... .......... .......... 60% 33.0M 6s\n", + "357050K .......... .......... .......... .......... .......... 60% 60.8M 6s\n", + "357100K .......... .......... .......... .......... .......... 60% 72.4M 6s\n", + "357150K .......... .......... .......... .......... .......... 60% 32.4M 6s\n", + "357200K .......... .......... .......... .......... .......... 60% 53.8M 6s\n", + "357250K .......... .......... .......... .......... .......... 60% 54.5M 6s\n", + "357300K .......... .......... .......... .......... .......... 60% 73.8M 6s\n", + "357350K 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.......... .......... .......... .......... .......... 60% 56.9M 6s\n", + "358000K .......... .......... .......... .......... .......... 60% 65.1M 6s\n", + "358050K .......... .......... .......... .......... .......... 60% 17.1M 6s\n", + "358100K .......... .......... .......... .......... .......... 60% 48.7M 6s\n", + "358150K .......... .......... .......... .......... .......... 60% 64.0M 6s\n", + "358200K .......... .......... .......... .......... .......... 60% 20.6M 6s\n", + "358250K .......... .......... .......... .......... .......... 60% 52.3M 6s\n", + "358300K .......... .......... .......... .......... .......... 60% 65.4M 6s\n", + "358350K .......... .......... .......... .......... .......... 60% 15.0M 6s\n", + "358400K .......... .......... .......... .......... .......... 60% 53.6M 6s\n", + "358450K .......... .......... .......... .......... .......... 60% 67.3M 6s\n", + "358500K .......... .......... .......... .......... .......... 60% 17.2M 6s\n", + "358550K .......... .......... .......... .......... .......... 60% 48.6M 6s\n", + "358600K .......... .......... .......... .......... .......... 60% 55.4M 6s\n", + "358650K .......... .......... .......... .......... .......... 60% 16.0M 6s\n", + "358700K .......... .......... .......... .......... .......... 60% 56.0M 6s\n", + "358750K .......... .......... .......... .......... .......... 60% 65.3M 6s\n", + "358800K .......... .......... .......... .......... .......... 60% 19.2M 6s\n", + "358850K .......... .......... .......... .......... .......... 60% 38.6M 6s\n", + "358900K .......... .......... .......... .......... .......... 60% 64.0M 6s\n", + "358950K .......... .......... .......... .......... .......... 60% 67.6M 6s\n", + "359000K .......... .......... .......... .......... .......... 60% 15.5M 6s\n", + "359050K .......... .......... .......... .......... .......... 60% 63.5M 6s\n", + "359100K .......... .......... .......... .......... .......... 60% 22.4M 6s\n", + "359150K .......... .......... .......... .......... .......... 60% 39.8M 6s\n", + "359200K .......... .......... .......... .......... .......... 60% 44.5M 6s\n", + "359250K .......... .......... .......... .......... .......... 60% 64.7M 6s\n", + "359300K .......... .......... .......... .......... .......... 60% 19.2M 6s\n", + "359350K .......... .......... .......... .......... .......... 60% 48.8M 6s\n", + "359400K .......... .......... .......... .......... .......... 60% 62.1M 6s\n", + "359450K .......... .......... .......... .......... .......... 60% 18.7M 6s\n", + "359500K .......... .......... .......... .......... .......... 60% 49.1M 6s\n", + "359550K .......... .......... .......... .......... .......... 60% 58.6M 6s\n", + "359600K .......... .......... .......... .......... .......... 60% 9.18M 6s\n", + "359650K .......... .......... .......... .......... .......... 60% 4.33M 6s\n", + "359700K .......... .......... .......... .......... .......... 60% 59.8M 6s\n", + "359750K .......... .......... .......... .......... .......... 60% 50.9M 6s\n", + "359800K .......... .......... .......... .......... .......... 60% 44.4M 6s\n", + "359850K .......... .......... .......... .......... .......... 60% 66.4M 6s\n", + "359900K .......... .......... .......... .......... .......... 60% 5.94M 6s\n", + "359950K .......... .......... .......... .......... .......... 60% 63.2M 6s\n", + "360000K .......... .......... .......... .......... .......... 60% 56.7M 6s\n", + "360050K .......... .......... .......... .......... .......... 60% 53.7M 6s\n", + "360100K .......... .......... .......... .......... .......... 60% 68.1M 6s\n", + "360150K .......... .......... .......... .......... .......... 60% 65.2M 6s\n", + "360200K .......... .......... .......... .......... .......... 60% 54.2M 6s\n", + "360250K .......... .......... .......... .......... .......... 60% 54.1M 6s\n", + "360300K .......... .......... .......... .......... .......... 60% 65.1M 6s\n", + "360350K .......... .......... .......... .......... .......... 60% 67.0M 6s\n", + "360400K .......... .......... .......... .......... .......... 60% 60.2M 6s\n", + "360450K .......... .......... .......... .......... .......... 60% 4.27M 6s\n", + "360500K .......... .......... .......... .......... .......... 60% 68.1M 6s\n", + "360550K .......... .......... .......... .......... .......... 60% 63.1M 6s\n", + "360600K .......... .......... .......... .......... .......... 60% 56.3M 6s\n", + "360650K .......... .......... .......... .......... .......... 60% 60.8M 6s\n", + "360700K .......... .......... .......... .......... .......... 60% 63.0M 6s\n", + "360750K .......... .......... .......... .......... .......... 60% 68.9M 6s\n", + "360800K .......... .......... .......... .......... .......... 60% 53.3M 6s\n", + "360850K .......... .......... .......... .......... .......... 60% 10.4M 6s\n", + "360900K .......... .......... .......... .......... .......... 60% 13.7M 6s\n", + "360950K .......... .......... .......... .......... .......... 60% 54.7M 6s\n", + "361000K .......... .......... .......... .......... .......... 60% 9.71M 6s\n", + "361050K .......... .......... .......... .......... .......... 60% 9.99M 6s\n", + "361100K .......... .......... .......... .......... .......... 60% 16.6M 6s\n", + "361150K .......... .......... .......... .......... .......... 60% 21.1M 6s\n", + "361200K .......... .......... .......... .......... .......... 60% 10.9M 6s\n", + "361250K .......... .......... .......... .......... .......... 60% 11.3M 6s\n", + "361300K .......... .......... .......... .......... .......... 60% 11.1M 6s\n", + "361350K .......... .......... .......... .......... .......... 60% 11.3M 6s\n", + "361400K .......... .......... .......... .......... .......... 60% 10.4M 6s\n", + "361450K .......... .......... .......... .......... .......... 60% 11.2M 6s\n", + "361500K .......... .......... .......... .......... .......... 60% 10.7M 6s\n", + "361550K .......... .......... .......... .......... .......... 60% 24.6M 6s\n", + "361600K .......... .......... .......... .......... .......... 60% 10.7M 6s\n", + "361650K .......... .......... .......... .......... .......... 60% 13.9M 6s\n", + "361700K .......... .......... .......... .......... .......... 60% 9.36M 6s\n", + "361750K .......... .......... .......... .......... .......... 60% 10.5M 6s\n", + "361800K .......... .......... .......... .......... .......... 60% 11.0M 6s\n", + "361850K .......... .......... .......... .......... .......... 60% 9.19M 6s\n", + "361900K .......... .......... .......... .......... .......... 60% 13.9M 6s\n", + "361950K .......... .......... .......... .......... .......... 60% 10.6M 6s\n", + "362000K .......... .......... .......... .......... .......... 60% 41.1M 6s\n", + "362050K .......... .......... .......... .......... .......... 60% 11.7M 6s\n", + "362100K .......... .......... .......... .......... .......... 60% 11.6M 6s\n", + "362150K 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.......... .......... .......... .......... .......... 61% 15.8M 6s\n", + "365800K .......... .......... .......... .......... .......... 61% 31.3M 6s\n", + "365850K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", + "365900K .......... .......... .......... .......... .......... 61% 37.6M 6s\n", + "365950K .......... .......... .......... .......... .......... 61% 15.1M 6s\n", + "366000K .......... .......... .......... .......... .......... 61% 38.9M 6s\n", + "366050K .......... .......... .......... .......... .......... 61% 14.6M 6s\n", + "366100K .......... .......... .......... .......... .......... 61% 45.9M 6s\n", + "366150K .......... .......... .......... .......... .......... 61% 18.2M 6s\n", + "366200K .......... .......... .......... .......... .......... 61% 25.4M 6s\n", + "366250K .......... .......... .......... .......... .......... 61% 14.3M 6s\n", + "366300K .......... .......... .......... .......... .......... 61% 48.9M 6s\n", + "366350K 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.......... .......... .......... .......... .......... 61% 16.8M 6s\n", + "368200K .......... .......... .......... .......... .......... 61% 39.0M 6s\n", + "368250K .......... .......... .......... .......... .......... 61% 14.7M 6s\n", + "368300K .......... .......... .......... .......... .......... 61% 61.4M 6s\n", + "368350K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", + "368400K .......... .......... .......... .......... .......... 61% 42.3M 6s\n", + "368450K .......... .......... .......... .......... .......... 61% 47.4M 6s\n", + "368500K .......... .......... .......... .......... .......... 61% 16.4M 6s\n", + "368550K .......... .......... .......... .......... .......... 61% 46.1M 6s\n", + "368600K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", + "368650K .......... .......... .......... .......... .......... 61% 44.4M 6s\n", + "368700K .......... .......... .......... .......... .......... 62% 16.1M 6s\n", + "368750K .......... .......... .......... .......... .......... 62% 57.1M 6s\n", + "368800K .......... .......... .......... .......... .......... 62% 43.8M 6s\n", + "368850K .......... .......... .......... .......... .......... 62% 14.1M 6s\n", + "368900K .......... .......... .......... .......... .......... 62% 34.5M 6s\n", + "368950K .......... .......... .......... .......... .......... 62% 19.0M 6s\n", + "369000K .......... .......... .......... .......... .......... 62% 34.3M 6s\n", + "369050K .......... .......... .......... .......... .......... 62% 67.0M 6s\n", + "369100K .......... .......... .......... .......... .......... 62% 16.6M 6s\n", + "369150K .......... .......... .......... .......... .......... 62% 48.4M 6s\n", + "369200K .......... .......... .......... .......... .......... 62% 14.8M 6s\n", + "369250K .......... .......... .......... .......... .......... 62% 67.6M 6s\n", + "369300K .......... .......... .......... .......... .......... 62% 54.5M 6s\n", + "369350K .......... .......... .......... .......... .......... 62% 13.6M 6s\n", + "369400K .......... .......... .......... .......... .......... 62% 38.3M 6s\n", + "369450K .......... .......... .......... .......... .......... 62% 19.6M 6s\n", + "369500K .......... .......... .......... .......... .......... 62% 63.9M 6s\n", + "369550K .......... .......... .......... .......... .......... 62% 47.6M 6s\n", + "369600K .......... .......... .......... .......... .......... 62% 14.4M 6s\n", + "369650K .......... .......... .......... .......... .......... 62% 52.3M 6s\n", + "369700K .......... .......... .......... .......... .......... 62% 16.6M 6s\n", + "369750K .......... .......... .......... .......... .......... 62% 62.7M 6s\n", + "369800K .......... .......... .......... .......... .......... 62% 13.2M 6s\n", + "369850K .......... .......... .......... .......... .......... 62% 59.5M 6s\n", + "369900K .......... .......... .......... .......... .......... 62% 69.3M 6s\n", + "369950K .......... .......... .......... .......... .......... 62% 14.9M 6s\n", + "370000K .......... .......... .......... .......... .......... 62% 56.5M 6s\n", + "370050K .......... .......... .......... .......... .......... 62% 54.6M 6s\n", + "370100K .......... .......... .......... .......... .......... 62% 15.2M 6s\n", + "370150K .......... .......... .......... .......... .......... 62% 71.8M 6s\n", + "370200K .......... .......... .......... .......... .......... 62% 14.7M 6s\n", + "370250K .......... .......... .......... .......... .......... 62% 62.3M 6s\n", + "370300K .......... .......... .......... .......... .......... 62% 57.0M 6s\n", + "370350K .......... .......... .......... .......... .......... 62% 16.4M 6s\n", + "370400K .......... .......... .......... .......... .......... 62% 63.3M 6s\n", + "370450K .......... .......... .......... .......... .......... 62% 42.8M 6s\n", + "370500K .......... .......... .......... .......... .......... 62% 14.6M 6s\n", + "370550K .......... .......... .......... .......... .......... 62% 63.7M 6s\n", + "370600K .......... .......... .......... .......... .......... 62% 15.6M 6s\n", + "370650K .......... .......... .......... .......... .......... 62% 51.2M 6s\n", + "370700K .......... .......... .......... .......... .......... 62% 54.4M 6s\n", + "370750K .......... .......... .......... .......... .......... 62% 15.8M 6s\n", + "370800K .......... .......... .......... .......... .......... 62% 50.7M 6s\n", + "370850K .......... .......... .......... .......... .......... 62% 74.8M 6s\n", + "370900K .......... .......... .......... .......... .......... 62% 15.5M 6s\n", + "370950K .......... .......... .......... .......... .......... 62% 52.0M 6s\n", + "371000K .......... .......... .......... .......... .......... 62% 15.9M 6s\n", + "371050K .......... .......... .......... .......... .......... 62% 38.1M 6s\n", + "371100K .......... .......... .......... .......... .......... 62% 76.8M 6s\n", + "371150K .......... .......... .......... .......... .......... 62% 18.3M 6s\n", + "371200K .......... .......... .......... .......... .......... 62% 55.1M 6s\n", + "371250K .......... .......... .......... .......... .......... 62% 71.7M 6s\n", + "371300K .......... .......... .......... .......... .......... 62% 15.5M 6s\n", + "371350K .......... .......... .......... .......... .......... 62% 54.8M 6s\n", + "371400K .......... .......... .......... .......... .......... 62% 16.2M 6s\n", + "371450K .......... .......... .......... .......... .......... 62% 50.2M 6s\n", + "371500K .......... .......... .......... .......... .......... 62% 61.7M 6s\n", + "371550K .......... .......... .......... .......... .......... 62% 15.7M 6s\n", + "371600K .......... .......... .......... .......... .......... 62% 50.1M 6s\n", + "371650K .......... .......... .......... .......... .......... 62% 68.5M 6s\n", + "371700K .......... .......... .......... .......... .......... 62% 16.9M 6s\n", + "371750K .......... .......... .......... .......... .......... 62% 66.6M 6s\n", + "371800K .......... .......... .......... .......... .......... 62% 15.1M 6s\n", + "371850K .......... .......... .......... .......... .......... 62% 62.7M 6s\n", + "371900K .......... .......... .......... .......... .......... 62% 69.3M 6s\n", + "371950K .......... .......... .......... .......... .......... 62% 16.5M 6s\n", + "372000K .......... .......... .......... .......... .......... 62% 41.6M 6s\n", + "372050K .......... .......... .......... .......... .......... 62% 71.2M 6s\n", + "372100K .......... .......... .......... .......... .......... 62% 18.2M 6s\n", + "372150K .......... .......... .......... .......... .......... 62% 42.0M 6s\n", + "372200K .......... .......... .......... .......... .......... 62% 52.4M 6s\n", + "372250K .......... .......... .......... .......... .......... 62% 16.8M 6s\n", + "372300K .......... .......... .......... .......... .......... 62% 58.8M 6s\n", + "372350K .......... .......... .......... .......... .......... 62% 59.2M 6s\n", + "372400K .......... .......... .......... .......... .......... 62% 15.9M 6s\n", + "372450K .......... .......... .......... .......... .......... 62% 61.7M 6s\n", + "372500K .......... .......... .......... .......... .......... 62% 64.3M 6s\n", + "372550K .......... .......... .......... .......... .......... 62% 16.7M 6s\n", + "372600K .......... .......... .......... .......... .......... 62% 52.7M 6s\n", + "372650K .......... .......... .......... .......... .......... 62% 16.2M 6s\n", + "372700K .......... .......... .......... .......... .......... 62% 48.3M 6s\n", + "372750K .......... .......... .......... .......... .......... 62% 54.4M 6s\n", + "372800K .......... .......... .......... .......... .......... 62% 18.4M 6s\n", + "372850K .......... .......... .......... .......... .......... 62% 51.1M 6s\n", + "372900K .......... .......... .......... .......... .......... 62% 56.3M 6s\n", + "372950K .......... .......... .......... .......... .......... 62% 18.3M 6s\n", + "373000K .......... .......... .......... .......... .......... 62% 35.7M 6s\n", + "373050K .......... .......... .......... .......... .......... 62% 65.0M 6s\n", + "373100K .......... .......... .......... .......... .......... 62% 19.2M 6s\n", + "373150K .......... .......... .......... .......... .......... 62% 59.0M 6s\n", + "373200K .......... .......... .......... .......... .......... 62% 58.9M 6s\n", + "373250K .......... .......... .......... .......... .......... 62% 17.2M 6s\n", + "373300K .......... .......... .......... .......... .......... 62% 46.7M 6s\n", + "373350K .......... .......... .......... .......... .......... 62% 67.1M 6s\n", + "373400K .......... .......... .......... .......... .......... 62% 18.0M 6s\n", + "373450K .......... .......... .......... .......... .......... 62% 36.6M 6s\n", + "373500K .......... .......... .......... .......... .......... 62% 60.5M 6s\n", + "373550K .......... .......... .......... .......... .......... 62% 18.1M 6s\n", + "373600K .......... .......... .......... .......... .......... 62% 53.6M 6s\n", + "373650K .......... .......... .......... .......... .......... 62% 62.8M 6s\n", + "373700K .......... .......... .......... .......... .......... 62% 18.2M 6s\n", + "373750K .......... .......... .......... .......... .......... 62% 35.8M 6s\n", + "373800K .......... .......... .......... .......... .......... 62% 40.6M 6s\n", + "373850K .......... .......... .......... .......... .......... 62% 26.8M 6s\n", + "373900K .......... .......... .......... .......... .......... 62% 30.4M 6s\n", + "373950K .......... .......... .......... .......... .......... 62% 47.2M 6s\n", + "374000K .......... .......... .......... .......... .......... 62% 24.6M 6s\n", + "374050K .......... .......... .......... .......... .......... 62% 34.7M 6s\n", + "374100K .......... .......... .......... .......... .......... 62% 45.5M 6s\n", + "374150K .......... .......... .......... .......... .......... 62% 22.6M 6s\n", + "374200K .......... .......... .......... .......... .......... 62% 37.3M 6s\n", + "374250K .......... .......... .......... .......... .......... 62% 37.2M 6s\n", + "374300K .......... .......... .......... .......... .......... 62% 24.1M 6s\n", + "374350K .......... .......... .......... .......... .......... 62% 42.5M 6s\n", + "374400K .......... .......... .......... .......... .......... 62% 52.1M 6s\n", + "374450K .......... .......... .......... .......... .......... 62% 18.8M 6s\n", + "374500K .......... .......... .......... .......... .......... 62% 63.6M 6s\n", + "374550K .......... .......... .......... .......... .......... 62% 44.3M 6s\n", + "374600K .......... .......... .......... .......... .......... 62% 18.1M 6s\n", + "374650K .......... .......... .......... .......... .......... 63% 63.6M 6s\n", + "374700K .......... .......... .......... .......... .......... 63% 60.4M 6s\n", + "374750K .......... .......... .......... .......... .......... 63% 15.5M 6s\n", + "374800K .......... .......... .......... .......... .......... 63% 59.4M 6s\n", + "374850K .......... .......... .......... .......... .......... 63% 65.9M 6s\n", + "374900K .......... .......... .......... .......... .......... 63% 15.2M 6s\n", + "374950K .......... .......... .......... .......... .......... 63% 69.2M 6s\n", + "375000K .......... .......... .......... .......... .......... 63% 59.0M 6s\n", + "375050K .......... .......... .......... .......... .......... 63% 17.0M 6s\n", + "375100K .......... .......... .......... .......... .......... 63% 63.7M 6s\n", + "375150K .......... .......... .......... .......... .......... 63% 67.0M 6s\n", + "375200K .......... .......... .......... .......... .......... 63% 68.8M 6s\n", + "375250K .......... .......... .......... .......... .......... 63% 16.5M 6s\n", + "375300K .......... .......... .......... .......... .......... 63% 57.7M 6s\n", + "375350K .......... .......... .......... .......... .......... 63% 74.0M 6s\n", + "375400K .......... .......... .......... .......... .......... 63% 16.4M 6s\n", + "375450K .......... .......... .......... .......... .......... 63% 56.9M 6s\n", + "375500K .......... .......... .......... .......... .......... 63% 69.5M 6s\n", + "375550K .......... .......... .......... .......... .......... 63% 18.3M 6s\n", + "375600K .......... .......... .......... .......... .......... 63% 49.8M 6s\n", + "375650K .......... .......... .......... .......... .......... 63% 68.1M 6s\n", + "375700K .......... .......... .......... .......... .......... 63% 18.6M 6s\n", + "375750K .......... .......... .......... .......... .......... 63% 50.4M 6s\n", + "375800K .......... .......... .......... .......... .......... 63% 47.0M 6s\n", + "375850K .......... .......... .......... .......... .......... 63% 20.1M 6s\n", + "375900K .......... .......... .......... .......... .......... 63% 55.5M 6s\n", + "375950K .......... .......... .......... .......... .......... 63% 54.8M 6s\n", + "376000K .......... .......... .......... .......... .......... 63% 71.5M 6s\n", + "376050K .......... .......... .......... .......... .......... 63% 17.5M 6s\n", + "376100K .......... .......... .......... .......... .......... 63% 63.1M 6s\n", + "376150K .......... .......... .......... .......... .......... 63% 70.5M 6s\n", + "376200K .......... .......... .......... .......... .......... 63% 18.7M 6s\n", + "376250K .......... .......... .......... .......... .......... 63% 44.2M 6s\n", + "376300K .......... .......... .......... .......... .......... 63% 62.7M 6s\n", + "376350K .......... .......... .......... .......... .......... 63% 21.3M 6s\n", + "376400K .......... .......... .......... .......... .......... 63% 42.6M 6s\n", + "376450K .......... .......... .......... .......... .......... 63% 60.8M 6s\n", + "376500K .......... .......... .......... .......... .......... 63% 20.8M 6s\n", + "376550K .......... .......... .......... .......... .......... 63% 48.1M 6s\n", + "376600K .......... .......... .......... .......... .......... 63% 45.3M 6s\n", + "376650K .......... .......... .......... .......... .......... 63% 20.9M 6s\n", + "376700K .......... .......... .......... .......... .......... 63% 47.4M 6s\n", + "376750K .......... .......... .......... .......... .......... 63% 67.0M 6s\n", + "376800K .......... .......... .......... .......... .......... 63% 61.1M 6s\n", + "376850K .......... .......... .......... .......... .......... 63% 19.6M 6s\n", + "376900K .......... .......... .......... .......... .......... 63% 44.0M 6s\n", + "376950K .......... .......... .......... .......... .......... 63% 63.1M 6s\n", + "377000K .......... .......... .......... .......... .......... 63% 21.7M 6s\n", + "377050K .......... .......... .......... .......... .......... 63% 44.1M 6s\n", + "377100K .......... .......... .......... .......... .......... 63% 52.0M 6s\n", + "377150K .......... .......... .......... .......... .......... 63% 23.7M 6s\n", + "377200K .......... .......... .......... .......... .......... 63% 48.3M 6s\n", + "377250K .......... .......... .......... .......... .......... 63% 51.3M 6s\n", + "377300K .......... .......... .......... .......... .......... 63% 50.3M 6s\n", + "377350K .......... .......... .......... .......... .......... 63% 23.5M 6s\n", + "377400K .......... .......... .......... .......... .......... 63% 39.5M 6s\n", + "377450K .......... .......... .......... .......... .......... 63% 52.7M 6s\n", + "377500K .......... .......... .......... .......... .......... 63% 25.3M 6s\n", + "377550K .......... .......... .......... .......... .......... 63% 38.5M 6s\n", + "377600K .......... .......... .......... .......... .......... 63% 39.0M 6s\n", + "377650K .......... .......... .......... .......... .......... 63% 72.7M 6s\n", + "377700K .......... .......... .......... .......... .......... 63% 20.8M 6s\n", + "377750K .......... .......... .......... .......... .......... 63% 55.5M 6s\n", + "377800K .......... .......... .......... .......... .......... 63% 53.6M 6s\n", + "377850K .......... .......... .......... .......... .......... 63% 25.2M 6s\n", + "377900K .......... .......... .......... .......... .......... 63% 37.0M 6s\n", + "377950K .......... .......... .......... .......... .......... 63% 65.0M 6s\n", + "378000K .......... .......... .......... .......... .......... 63% 23.9M 6s\n", + "378050K .......... .......... .......... .......... .......... 63% 36.4M 6s\n", + "378100K .......... .......... .......... .......... .......... 63% 53.2M 6s\n", + "378150K .......... .......... .......... .......... .......... 63% 70.8M 6s\n", + "378200K .......... .......... .......... .......... .......... 63% 16.4M 6s\n", + "378250K .......... .......... .......... .......... .......... 63% 54.1M 6s\n", + "378300K .......... .......... .......... .......... .......... 63% 73.2M 6s\n", + "378350K .......... .......... .......... .......... .......... 63% 29.7M 6s\n", + "378400K .......... .......... .......... .......... .......... 63% 26.9M 6s\n", + "378450K .......... .......... .......... .......... .......... 63% 66.6M 6s\n", + "378500K .......... .......... .......... .......... .......... 63% 79.2M 6s\n", + "378550K .......... .......... .......... .......... .......... 63% 29.2M 6s\n", + "378600K .......... .......... .......... .......... .......... 63% 24.5M 6s\n", + "378650K .......... .......... .......... .......... .......... 63% 76.8M 6s\n", + "378700K .......... .......... .......... .......... .......... 63% 28.3M 6s\n", + "378750K .......... .......... .......... .......... .......... 63% 32.6M 6s\n", + "378800K .......... .......... .......... .......... .......... 63% 54.0M 6s\n", + "378850K .......... .......... .......... .......... .......... 63% 59.4M 6s\n", + "378900K .......... .......... .......... .......... .......... 63% 26.5M 6s\n", + "378950K .......... .......... .......... .......... .......... 63% 31.7M 6s\n", + "379000K .......... .......... .......... .......... .......... 63% 60.1M 6s\n", + "379050K .......... .......... .......... .......... .......... 63% 26.1M 6s\n", + "379100K .......... .......... .......... .......... .......... 63% 34.9M 6s\n", + "379150K .......... .......... .......... .......... .......... 63% 66.8M 6s\n", + "379200K .......... .......... .......... .......... .......... 63% 71.9M 6s\n", + "379250K .......... .......... .......... .......... .......... 63% 23.1M 6s\n", + "379300K .......... .......... .......... .......... .......... 63% 35.2M 6s\n", + "379350K .......... .......... .......... .......... .......... 63% 71.6M 6s\n", + "379400K .......... .......... .......... .......... .......... 63% 22.2M 6s\n", + "379450K .......... .......... .......... .......... .......... 63% 34.0M 6s\n", + "379500K .......... .......... .......... .......... .......... 63% 61.5M 6s\n", + "379550K .......... .......... .......... .......... .......... 63% 78.3M 6s\n", + "379600K .......... .......... .......... .......... .......... 63% 20.9M 6s\n", + "379650K .......... .......... .......... .......... .......... 63% 47.4M 6s\n", + "379700K .......... .......... .......... .......... .......... 63% 69.0M 6s\n", + "379750K .......... .......... .......... .......... .......... 63% 22.0M 6s\n", + "379800K .......... .......... .......... .......... .......... 63% 27.7M 6s\n", + "379850K .......... .......... .......... .......... .......... 63% 42.9M 6s\n", + "379900K .......... .......... .......... .......... .......... 63% 38.6M 6s\n", + "379950K .......... .......... .......... .......... .......... 63% 43.3M 6s\n", + "380000K .......... .......... .......... .......... .......... 63% 33.4M 6s\n", + "380050K .......... .......... .......... .......... .......... 63% 65.9M 6s\n", + "380100K .......... .......... .......... .......... .......... 63% 38.6M 6s\n", + "380150K .......... .......... .......... .......... .......... 63% 29.5M 6s\n", + "380200K .......... .......... .......... .......... .......... 63% 30.5M 6s\n", + "380250K .......... .......... .......... .......... .......... 63% 40.6M 6s\n", + "380300K .......... .......... .......... .......... .......... 63% 45.5M 6s\n", + "380350K .......... .......... .......... .......... .......... 63% 40.3M 6s\n", + "380400K .......... .......... .......... .......... .......... 63% 42.9M 6s\n", + "380450K .......... .......... .......... .......... .......... 63% 77.7M 6s\n", + "380500K .......... .......... .......... .......... .......... 63% 36.7M 6s\n", + "380550K .......... .......... .......... .......... .......... 63% 37.1M 6s\n", + "380600K .......... .......... .......... .......... .......... 64% 49.7M 6s\n", + "380650K .......... .......... .......... .......... .......... 64% 45.3M 6s\n", + "380700K .......... .......... .......... .......... .......... 64% 26.3M 6s\n", + "380750K .......... .......... .......... .......... .......... 64% 62.3M 6s\n", + "380800K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", + "380850K .......... .......... .......... .......... .......... 64% 32.7M 6s\n", + "380900K .......... .......... .......... .......... .......... 64% 38.6M 6s\n", + "380950K .......... .......... .......... .......... .......... 64% 41.1M 6s\n", + "381000K .......... .......... .......... .......... .......... 64% 41.1M 6s\n", + "381050K .......... .......... .......... .......... .......... 64% 33.3M 6s\n", + "381100K .......... .......... .......... .......... .......... 64% 37.2M 6s\n", + "381150K .......... .......... .......... .......... .......... 64% 51.8M 6s\n", + "381200K .......... .......... .......... .......... .......... 64% 47.6M 6s\n", + "381250K .......... .......... .......... .......... .......... 64% 42.1M 6s\n", + "381300K .......... .......... .......... .......... .......... 64% 30.2M 6s\n", + "381350K .......... .......... .......... .......... .......... 64% 39.9M 6s\n", + "381400K .......... .......... .......... .......... .......... 64% 46.7M 6s\n", + "381450K .......... .......... .......... .......... .......... 64% 32.2M 6s\n", + "381500K .......... .......... .......... .......... .......... 64% 50.9M 6s\n", + "381550K .......... .......... .......... .......... .......... 64% 53.2M 6s\n", + "381600K .......... .......... .......... .......... .......... 64% 37.1M 6s\n", + "381650K .......... .......... .......... .......... .......... 64% 40.7M 6s\n", + "381700K .......... .......... .......... .......... .......... 64% 35.4M 6s\n", + "381750K .......... .......... .......... .......... .......... 64% 51.6M 6s\n", + "381800K .......... .......... .......... .......... .......... 64% 45.3M 6s\n", + "381850K .......... .......... .......... .......... .......... 64% 7.14M 6s\n", + "381900K .......... .......... .......... .......... .......... 64% 70.7M 6s\n", + "381950K .......... .......... .......... .......... .......... 64% 85.1M 6s\n", + "382000K .......... .......... .......... .......... .......... 64% 73.2M 6s\n", + "382050K .......... .......... .......... .......... .......... 64% 18.2M 6s\n", + "382100K .......... .......... .......... .......... .......... 64% 50.7M 6s\n", + "382150K .......... .......... .......... .......... .......... 64% 75.5M 6s\n", + "382200K .......... .......... .......... .......... .......... 64% 67.8M 6s\n", + "382250K .......... .......... .......... .......... .......... 64% 20.6M 6s\n", + "382300K .......... .......... .......... .......... .......... 64% 59.2M 6s\n", + "382350K .......... .......... .......... .......... .......... 64% 74.1M 6s\n", + "382400K .......... .......... .......... .......... .......... 64% 65.7M 6s\n", + "382450K .......... .......... .......... .......... .......... 64% 22.2M 6s\n", + "382500K .......... .......... .......... .......... .......... 64% 56.2M 6s\n", + "382550K .......... .......... .......... .......... .......... 64% 81.0M 6s\n", + "382600K .......... .......... .......... .......... .......... 64% 19.7M 6s\n", + "382650K .......... .......... .......... .......... .......... 64% 46.0M 6s\n", + "382700K .......... .......... .......... .......... .......... 64% 55.3M 6s\n", + "382750K .......... .......... .......... .......... .......... 64% 83.4M 6s\n", + "382800K .......... .......... .......... .......... .......... 64% 22.7M 6s\n", + "382850K .......... .......... .......... .......... .......... 64% 57.1M 6s\n", + "382900K .......... .......... .......... .......... .......... 64% 58.0M 6s\n", + "382950K .......... .......... .......... .......... .......... 64% 77.3M 6s\n", + "383000K .......... .......... .......... .......... .......... 64% 20.1M 6s\n", + "383050K .......... .......... .......... .......... .......... 64% 47.0M 6s\n", + "383100K .......... .......... .......... .......... .......... 64% 67.9M 6s\n", + "383150K .......... .......... .......... .......... .......... 64% 74.4M 6s\n", + "383200K .......... .......... .......... .......... .......... 64% 21.2M 6s\n", + "383250K .......... .......... .......... .......... .......... 64% 54.0M 6s\n", + "383300K .......... .......... .......... .......... .......... 64% 66.4M 6s\n", + "383350K .......... .......... .......... .......... .......... 64% 78.2M 6s\n", + "383400K .......... .......... .......... .......... .......... 64% 19.8M 6s\n", + "383450K .......... .......... .......... .......... .......... 64% 60.2M 6s\n", + "383500K .......... .......... .......... .......... .......... 64% 74.0M 6s\n", + "383550K .......... .......... .......... .......... .......... 64% 72.8M 6s\n", + "383600K .......... .......... .......... .......... .......... 64% 21.2M 6s\n", + "383650K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", + "383700K .......... .......... .......... .......... .......... 64% 65.3M 6s\n", + "383750K .......... .......... .......... .......... .......... 64% 78.1M 6s\n", + "383800K .......... .......... .......... .......... .......... 64% 20.5M 6s\n", + "383850K .......... .......... .......... .......... .......... 64% 57.1M 6s\n", + "383900K .......... .......... .......... .......... .......... 64% 70.9M 6s\n", + "383950K .......... .......... .......... .......... .......... 64% 73.5M 6s\n", + "384000K .......... .......... .......... .......... .......... 64% 22.7M 6s\n", + "384050K .......... .......... .......... .......... .......... 64% 55.1M 6s\n", + "384100K .......... .......... .......... .......... .......... 64% 61.1M 6s\n", + "384150K .......... .......... .......... .......... .......... 64% 79.2M 6s\n", + "384200K .......... .......... .......... .......... .......... 64% 20.1M 6s\n", + "384250K .......... .......... .......... .......... .......... 64% 52.9M 6s\n", + "384300K .......... .......... .......... .......... .......... 64% 66.2M 6s\n", + "384350K .......... .......... .......... .......... .......... 64% 26.7M 6s\n", + "384400K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", + "384450K .......... .......... .......... .......... .......... 64% 59.3M 6s\n", + "384500K .......... .......... .......... .......... .......... 64% 62.2M 6s\n", + "384550K .......... .......... .......... .......... .......... 64% 75.8M 6s\n", + "384600K .......... .......... .......... .......... .......... 64% 21.4M 6s\n", + "384650K .......... .......... .......... .......... .......... 64% 42.6M 6s\n", + "384700K .......... .......... .......... .......... .......... 64% 58.2M 6s\n", + "384750K .......... .......... .......... .......... .......... 64% 31.1M 5s\n", + "384800K .......... .......... .......... .......... .......... 64% 46.3M 5s\n", + "384850K .......... .......... .......... .......... .......... 64% 36.0M 5s\n", + "384900K .......... .......... .......... .......... .......... 64% 67.7M 5s\n", + "384950K .......... .......... .......... .......... .......... 64% 65.2M 5s\n", + "385000K .......... .......... .......... .......... .......... 64% 30.1M 5s\n", + "385050K .......... .......... .......... .......... .......... 64% 36.7M 5s\n", + "385100K .......... .......... .......... .......... .......... 64% 57.1M 5s\n", + "385150K .......... .......... .......... .......... .......... 64% 29.7M 5s\n", + "385200K .......... .......... .......... .......... .......... 64% 36.8M 5s\n", + "385250K .......... .......... .......... .......... .......... 64% 49.2M 5s\n", + "385300K .......... .......... .......... .......... .......... 64% 76.8M 5s\n", + "385350K .......... .......... .......... .......... .......... 64% 83.0M 5s\n", + "385400K .......... .......... .......... .......... .......... 64% 21.1M 5s\n", + "385450K .......... .......... .......... .......... .......... 64% 53.8M 5s\n", + "385500K .......... .......... .......... .......... .......... 64% 66.5M 5s\n", + "385550K .......... .......... .......... .......... .......... 64% 4.40M 5s\n", + "385600K .......... .......... .......... .......... .......... 64% 59.8M 5s\n", + "385650K .......... .......... .......... .......... .......... 64% 65.5M 5s\n", + "385700K .......... .......... .......... .......... .......... 64% 62.8M 5s\n", + "385750K .......... .......... .......... .......... .......... 64% 37.6M 5s\n", + "385800K .......... .......... .......... .......... .......... 64% 36.8M 5s\n", + "385850K .......... .......... .......... .......... .......... 64% 76.3M 5s\n", + "385900K .......... .......... .......... .......... .......... 64% 75.5M 5s\n", + "385950K .......... .......... .......... .......... .......... 64% 30.7M 5s\n", + "386000K .......... .......... .......... .......... .......... 64% 49.6M 5s\n", + "386050K .......... .......... .......... .......... .......... 64% 54.6M 5s\n", + "386100K .......... .......... .......... .......... .......... 64% 71.9M 5s\n", + "386150K .......... .......... .......... .......... .......... 64% 23.9M 5s\n", + "386200K .......... .......... .......... .......... .......... 64% 40.6M 5s\n", + "386250K .......... .......... .......... .......... .......... 64% 58.4M 5s\n", + "386300K .......... .......... .......... .......... .......... 64% 69.2M 5s\n", + "386350K .......... .......... .......... .......... .......... 64% 24.7M 5s\n", + "386400K .......... .......... .......... .......... .......... 64% 45.2M 5s\n", + "386450K .......... .......... .......... .......... .......... 64% 63.1M 5s\n", + "386500K .......... .......... .......... .......... .......... 64% 67.9M 5s\n", + "386550K .......... .......... .......... .......... .......... 65% 60.8M 5s\n", + "386600K .......... .......... .......... .......... .......... 65% 28.0M 5s\n", + "386650K .......... .......... .......... .......... .......... 65% 53.3M 5s\n", + "386700K .......... .......... .......... .......... .......... 65% 59.7M 5s\n", + "386750K .......... .......... .......... .......... .......... 65% 63.2M 5s\n", + "386800K .......... .......... .......... .......... .......... 65% 29.7M 5s\n", + "386850K .......... .......... .......... .......... .......... 65% 52.6M 5s\n", + "386900K .......... .......... .......... .......... .......... 65% 54.2M 5s\n", + "386950K .......... .......... .......... .......... .......... 65% 71.7M 5s\n", + "387000K .......... .......... .......... .......... .......... 65% 27.3M 5s\n", + "387050K .......... .......... .......... .......... .......... 65% 64.0M 5s\n", + "387100K .......... .......... .......... .......... .......... 65% 4.27M 5s\n", + "387150K .......... .......... .......... .......... .......... 65% 52.1M 5s\n", + "387200K .......... .......... .......... .......... .......... 65% 55.6M 5s\n", + "387250K .......... .......... .......... .......... .......... 65% 56.9M 5s\n", + "387300K .......... .......... .......... .......... .......... 65% 66.5M 5s\n", + "387350K .......... .......... .......... .......... .......... 65% 29.8M 5s\n", + "387400K .......... .......... .......... .......... .......... 65% 47.5M 5s\n", + "387450K .......... .......... .......... .......... .......... 65% 64.5M 5s\n", + "387500K .......... .......... .......... .......... .......... 65% 80.5M 5s\n", + "387550K .......... .......... .......... .......... .......... 65% 22.2M 5s\n", + "387600K .......... .......... .......... .......... .......... 65% 30.2M 5s\n", + "387650K .......... .......... .......... .......... .......... 65% 12.7M 5s\n", + "387700K .......... .......... .......... .......... .......... 65% 41.1M 5s\n", + "387750K .......... .......... .......... .......... .......... 65% 73.5M 5s\n", + "387800K .......... .......... .......... .......... .......... 65% 58.7M 5s\n", + "387850K .......... .......... .......... .......... .......... 65% 76.3M 5s\n", + "387900K .......... .......... .......... .......... .......... 65% 49.3M 5s\n", + "387950K .......... .......... .......... .......... .......... 65% 33.2M 5s\n", + "388000K .......... .......... .......... .......... .......... 65% 54.8M 5s\n", + "388050K .......... .......... .......... .......... .......... 65% 70.4M 5s\n", + "388100K .......... .......... .......... .......... .......... 65% 49.6M 5s\n", + "388150K .......... .......... .......... .......... .......... 65% 35.3M 5s\n", + "388200K .......... .......... .......... .......... .......... 65% 41.6M 5s\n", + "388250K .......... .......... .......... .......... .......... 65% 64.5M 5s\n", + "388300K .......... .......... .......... .......... .......... 65% 49.2M 5s\n", + "388350K .......... .......... .......... .......... .......... 65% 37.4M 5s\n", + "388400K .......... .......... .......... .......... .......... 65% 32.7M 5s\n", + "388450K .......... .......... .......... .......... .......... 65% 67.0M 5s\n", + "388500K .......... .......... .......... .......... .......... 65% 56.2M 5s\n", + "388550K .......... .......... .......... .......... .......... 65% 33.3M 5s\n", + "388600K .......... .......... .......... .......... .......... 65% 32.4M 5s\n", + "388650K .......... .......... .......... .......... .......... 65% 66.5M 5s\n", + "388700K .......... .......... .......... .......... .......... 65% 47.8M 5s\n", + "388750K .......... .......... .......... .......... .......... 65% 44.4M 5s\n", + "388800K .......... .......... .......... .......... .......... 65% 35.9M 5s\n", + "388850K .......... .......... .......... .......... .......... 65% 57.2M 5s\n", + "388900K .......... .......... .......... .......... .......... 65% 44.4M 5s\n", + "388950K .......... .......... .......... .......... .......... 65% 43.1M 5s\n", + "389000K .......... .......... .......... .......... .......... 65% 32.4M 5s\n", + "389050K .......... .......... .......... .......... .......... 65% 46.7M 5s\n", + "389100K .......... .......... .......... .......... .......... 65% 54.4M 5s\n", + "389150K .......... .......... .......... .......... .......... 65% 37.1M 5s\n", + "389200K .......... .......... .......... .......... .......... 65% 40.4M 5s\n", + "389250K .......... .......... .......... .......... .......... 65% 42.7M 5s\n", + "389300K .......... .......... .......... .......... .......... 65% 50.3M 5s\n", + "389350K .......... .......... .......... .......... .......... 65% 30.9M 5s\n", + "389400K .......... .......... .......... .......... .......... 65% 40.9M 5s\n", + "389450K .......... .......... .......... .......... .......... 65% 40.8M 5s\n", + "389500K .......... .......... .......... .......... .......... 65% 48.3M 5s\n", + "389550K .......... .......... .......... .......... .......... 65% 52.7M 5s\n", + "389600K .......... .......... .......... .......... .......... 65% 41.9M 5s\n", + "389650K .......... .......... .......... .......... .......... 65% 45.0M 5s\n", + "389700K .......... .......... .......... .......... .......... 65% 53.1M 5s\n", + "389750K .......... .......... .......... .......... .......... 65% 42.0M 5s\n", + "389800K .......... .......... .......... .......... .......... 65% 32.6M 5s\n", + "389850K .......... .......... .......... .......... .......... 65% 45.4M 5s\n", + "389900K .......... .......... .......... .......... .......... 65% 51.3M 5s\n", + "389950K .......... .......... .......... .......... .......... 65% 53.6M 5s\n", + "390000K .......... .......... .......... .......... .......... 65% 44.3M 5s\n", + "390050K .......... .......... .......... .......... .......... 65% 39.6M 5s\n", + "390100K .......... .......... .......... .......... .......... 65% 40.7M 5s\n", + "390150K .......... .......... .......... .......... .......... 65% 49.1M 5s\n", + "390200K .......... .......... .......... .......... .......... 65% 37.0M 5s\n", + "390250K .......... .......... .......... .......... .......... 65% 48.7M 5s\n", + "390300K .......... .......... .......... .......... .......... 65% 39.7M 5s\n", + "390350K .......... .......... .......... .......... .......... 65% 63.1M 5s\n", + "390400K .......... .......... .......... .......... .......... 65% 32.9M 5s\n", + "390450K .......... .......... .......... .......... .......... 65% 40.0M 5s\n", + "390500K .......... .......... .......... .......... .......... 65% 53.6M 5s\n", + "390550K .......... .......... .......... .......... .......... 65% 63.1M 5s\n", + "390600K .......... .......... .......... .......... .......... 65% 45.8M 5s\n", + "390650K .......... .......... .......... .......... .......... 65% 56.1M 5s\n", + "390700K .......... .......... .......... .......... .......... 65% 57.1M 5s\n", + "390750K .......... .......... .......... .......... .......... 65% 51.3M 5s\n", + "390800K .......... .......... .......... .......... .......... 65% 52.5M 5s\n", + "390850K .......... .......... .......... .......... .......... 65% 38.8M 5s\n", + "390900K .......... .......... .......... .......... .......... 65% 40.0M 5s\n", + "390950K .......... .......... .......... .......... .......... 65% 49.0M 5s\n", + "391000K .......... .......... .......... .......... .......... 65% 52.4M 5s\n", + "391050K .......... .......... .......... .......... .......... 65% 50.0M 5s\n", + "391100K .......... .......... .......... .......... .......... 65% 48.3M 5s\n", + "391150K .......... .......... .......... .......... .......... 65% 46.9M 5s\n", + "391200K .......... .......... .......... .......... .......... 65% 49.4M 5s\n", + "391250K .......... .......... .......... .......... .......... 65% 56.1M 5s\n", + "391300K .......... .......... .......... .......... .......... 65% 36.8M 5s\n", + "391350K .......... .......... .......... .......... .......... 65% 46.2M 5s\n", + "391400K .......... .......... .......... .......... .......... 65% 41.5M 5s\n", + "391450K .......... .......... .......... .......... .......... 65% 51.9M 5s\n", + "391500K .......... .......... .......... .......... .......... 65% 50.3M 5s\n", + "391550K .......... .......... .......... .......... .......... 65% 41.0M 5s\n", + "391600K .......... .......... .......... .......... .......... 65% 50.0M 5s\n", + "391650K .......... .......... .......... .......... .......... 65% 46.8M 5s\n", + "391700K .......... .......... .......... .......... .......... 65% 58.2M 5s\n", + "391750K .......... .......... .......... .......... .......... 65% 45.5M 5s\n", + "391800K .......... .......... .......... .......... .......... 65% 38.5M 5s\n", + "391850K .......... .......... .......... .......... .......... 65% 59.9M 5s\n", + "391900K .......... .......... .......... .......... .......... 65% 54.0M 5s\n", + "391950K .......... .......... .......... .......... .......... 65% 48.0M 5s\n", + "392000K .......... .......... .......... .......... .......... 65% 43.6M 5s\n", + "392050K .......... .......... .......... .......... .......... 65% 52.7M 5s\n", + "392100K .......... .......... .......... .......... .......... 65% 55.3M 5s\n", + "392150K .......... .......... .......... .......... .......... 65% 49.6M 5s\n", + "392200K .......... .......... .......... .......... .......... 65% 34.8M 5s\n", + "392250K .......... .......... .......... .......... .......... 65% 42.2M 5s\n", + "392300K .......... .......... .......... .......... .......... 65% 48.4M 5s\n", + "392350K .......... .......... .......... .......... .......... 65% 53.8M 5s\n", + "392400K .......... .......... .......... .......... .......... 65% 42.0M 5s\n", + "392450K .......... .......... .......... .......... .......... 65% 43.9M 5s\n", + "392500K .......... .......... .......... .......... .......... 66% 41.5M 5s\n", + "392550K .......... .......... .......... .......... .......... 66% 48.1M 5s\n", + "392600K .......... .......... .......... .......... .......... 66% 37.0M 5s\n", + "392650K .......... .......... .......... .......... .......... 66% 51.3M 5s\n", + "392700K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", + "392750K .......... .......... .......... .......... .......... 66% 55.5M 5s\n", + "392800K .......... .......... .......... .......... .......... 66% 42.2M 5s\n", + "392850K .......... .......... .......... .......... .......... 66% 39.6M 5s\n", + "392900K .......... .......... .......... .......... .......... 66% 51.4M 5s\n", + "392950K .......... .......... .......... .......... .......... 66% 48.6M 5s\n", + "393000K .......... .......... .......... .......... .......... 66% 40.4M 5s\n", + "393050K .......... .......... .......... .......... .......... 66% 44.0M 5s\n", + "393100K .......... .......... .......... .......... .......... 66% 48.8M 5s\n", + "393150K .......... .......... .......... .......... .......... 66% 41.7M 5s\n", + "393200K .......... .......... .......... .......... .......... 66% 41.1M 5s\n", + "393250K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", + "393300K .......... .......... .......... .......... .......... 66% 45.2M 5s\n", + "393350K .......... .......... .......... .......... .......... 66% 51.5M 5s\n", + "393400K .......... .......... .......... .......... .......... 66% 46.2M 5s\n", + "393450K .......... .......... .......... .......... .......... 66% 43.2M 5s\n", + "393500K .......... .......... .......... .......... .......... 66% 54.7M 5s\n", + "393550K .......... .......... .......... .......... .......... 66% 47.7M 5s\n", + "393600K .......... .......... .......... .......... .......... 66% 54.1M 5s\n", + "393650K .......... .......... .......... .......... .......... 66% 50.9M 5s\n", + "393700K .......... .......... .......... .......... .......... 66% 47.1M 5s\n", + "393750K .......... .......... .......... .......... .......... 66% 42.5M 5s\n", + "393800K .......... .......... .......... .......... .......... 66% 40.1M 5s\n", + "393850K .......... .......... .......... .......... .......... 66% 54.2M 5s\n", + "393900K .......... .......... .......... .......... .......... 66% 45.1M 5s\n", + "393950K .......... .......... .......... .......... .......... 66% 47.5M 5s\n", + "394000K .......... .......... .......... .......... .......... 66% 37.7M 5s\n", + "394050K .......... .......... .......... .......... .......... 66% 40.5M 5s\n", + "394100K .......... .......... .......... .......... .......... 66% 33.7M 5s\n", + "394150K .......... .......... .......... .......... .......... 66% 36.1M 5s\n", + "394200K .......... .......... .......... .......... .......... 66% 35.3M 5s\n", + "394250K .......... .......... .......... .......... .......... 66% 41.2M 5s\n", + "394300K .......... .......... .......... .......... .......... 66% 44.6M 5s\n", + "394350K .......... .......... .......... .......... .......... 66% 38.5M 5s\n", + "394400K .......... .......... .......... .......... .......... 66% 29.3M 5s\n", + "394450K .......... .......... .......... .......... .......... 66% 44.1M 5s\n", + "394500K .......... .......... .......... .......... .......... 66% 52.0M 5s\n", + "394550K .......... .......... .......... .......... .......... 66% 40.2M 5s\n", + "394600K .......... .......... .......... .......... .......... 66% 43.9M 5s\n", + "394650K .......... .......... .......... .......... .......... 66% 43.6M 5s\n", + "394700K .......... .......... .......... .......... .......... 66% 59.5M 5s\n", + "394750K .......... .......... .......... .......... .......... 66% 47.2M 5s\n", + "394800K .......... .......... .......... .......... .......... 66% 43.9M 5s\n", + "394850K .......... .......... .......... .......... .......... 66% 42.4M 5s\n", + "394900K .......... .......... .......... .......... .......... 66% 40.7M 5s\n", + "394950K .......... .......... .......... .......... .......... 66% 37.8M 5s\n", + "395000K .......... .......... .......... .......... .......... 66% 42.0M 5s\n", + "395050K .......... .......... .......... .......... .......... 66% 55.5M 5s\n", + "395100K .......... .......... .......... .......... .......... 66% 50.3M 5s\n", + "395150K .......... .......... .......... .......... .......... 66% 38.3M 5s\n", + "395200K .......... .......... .......... .......... .......... 66% 37.9M 5s\n", + "395250K .......... .......... .......... .......... .......... 66% 35.2M 5s\n", + "395300K .......... .......... .......... .......... .......... 66% 52.4M 5s\n", + "395350K .......... .......... .......... .......... .......... 66% 45.6M 5s\n", + "395400K .......... .......... .......... .......... .......... 66% 39.1M 5s\n", + "395450K .......... .......... .......... .......... .......... 66% 56.2M 5s\n", + "395500K .......... .......... .......... .......... .......... 66% 50.4M 5s\n", + "395550K .......... .......... .......... .......... .......... 66% 44.8M 5s\n", + "395600K .......... .......... .......... .......... .......... 66% 51.4M 5s\n", + "395650K .......... .......... .......... .......... .......... 66% 50.7M 5s\n", + "395700K .......... .......... .......... .......... .......... 66% 47.4M 5s\n", + "395750K .......... .......... .......... .......... .......... 66% 42.1M 5s\n", + "395800K .......... .......... .......... .......... .......... 66% 29.4M 5s\n", + "395850K .......... .......... .......... .......... .......... 66% 43.4M 5s\n", + "395900K .......... .......... .......... .......... .......... 66% 41.1M 5s\n", + "395950K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", + "396000K .......... .......... .......... .......... .......... 66% 43.5M 5s\n", + "396050K .......... .......... .......... .......... .......... 66% 33.1M 5s\n", + "396100K .......... .......... .......... .......... .......... 66% 32.8M 5s\n", + "396150K .......... .......... .......... .......... .......... 66% 33.0M 5s\n", + "396200K .......... .......... .......... .......... .......... 66% 30.5M 5s\n", + "396250K .......... .......... .......... .......... .......... 66% 38.0M 5s\n", + "396300K .......... .......... .......... .......... .......... 66% 50.7M 5s\n", + "396350K .......... .......... .......... .......... .......... 66% 45.9M 5s\n", + "396400K .......... .......... .......... .......... .......... 66% 43.8M 5s\n", + "396450K .......... .......... .......... .......... .......... 66% 45.9M 5s\n", + "396500K .......... .......... .......... .......... .......... 66% 49.6M 5s\n", + "396550K .......... .......... .......... .......... .......... 66% 59.4M 5s\n", + "396600K .......... .......... .......... .......... .......... 66% 37.4M 5s\n", + "396650K .......... .......... .......... .......... .......... 66% 50.5M 5s\n", + "396700K .......... .......... .......... .......... .......... 66% 45.0M 5s\n", + "396750K .......... .......... .......... .......... .......... 66% 3.73M 5s\n", + "396800K .......... .......... .......... .......... .......... 66% 44.3M 5s\n", + "396850K .......... .......... .......... .......... .......... 66% 54.8M 5s\n", + "396900K .......... .......... .......... .......... .......... 66% 47.1M 5s\n", + "396950K .......... .......... .......... .......... .......... 66% 38.9M 5s\n", + "397000K .......... .......... .......... .......... .......... 66% 27.3M 5s\n", + "397050K .......... .......... .......... .......... .......... 66% 34.6M 5s\n", + "397100K .......... .......... .......... .......... .......... 66% 47.4M 5s\n", + "397150K .......... .......... .......... .......... .......... 66% 38.5M 5s\n", + "397200K .......... .......... .......... .......... .......... 66% 30.0M 5s\n", + "397250K .......... .......... .......... .......... .......... 66% 39.8M 5s\n", + "397300K .......... .......... .......... .......... .......... 66% 37.4M 5s\n", + "397350K .......... .......... .......... .......... .......... 66% 31.2M 5s\n", + "397400K .......... .......... .......... .......... .......... 66% 33.1M 5s\n", + "397450K .......... .......... .......... .......... .......... 66% 49.4M 5s\n", + "397500K .......... .......... .......... .......... .......... 66% 24.6M 5s\n", + "397550K .......... .......... .......... .......... .......... 66% 48.7M 5s\n", + "397600K .......... .......... .......... .......... .......... 66% 48.7M 5s\n", + "397650K .......... .......... .......... .......... .......... 66% 57.6M 5s\n", + "397700K .......... .......... .......... .......... .......... 66% 55.3M 5s\n", + "397750K .......... .......... .......... .......... .......... 66% 38.7M 5s\n", + "397800K .......... .......... .......... .......... .......... 66% 39.3M 5s\n", + "397850K .......... .......... .......... .......... .......... 66% 54.0M 5s\n", + "397900K .......... .......... .......... .......... .......... 66% 52.2M 5s\n", + "397950K .......... .......... .......... .......... .......... 66% 56.5M 5s\n", + "398000K .......... .......... .......... .......... .......... 66% 37.6M 5s\n", + "398050K .......... .......... .......... .......... .......... 66% 46.6M 5s\n", + "398100K .......... .......... .......... .......... .......... 66% 3.80M 5s\n", + "398150K .......... .......... .......... .......... .......... 66% 57.9M 5s\n", + "398200K .......... .......... .......... .......... .......... 66% 46.4M 5s\n", + "398250K .......... .......... .......... .......... .......... 66% 60.9M 5s\n", + "398300K .......... .......... .......... .......... .......... 66% 60.2M 5s\n", + "398350K .......... .......... .......... .......... .......... 66% 64.4M 5s\n", + "398400K .......... .......... .......... .......... .......... 66% 49.7M 5s\n", + "398450K .......... .......... .......... .......... .......... 67% 51.4M 5s\n", + "398500K .......... .......... .......... .......... .......... 67% 65.5M 5s\n", + "398550K .......... .......... .......... .......... .......... 67% 61.7M 5s\n", + "398600K .......... .......... .......... .......... .......... 67% 54.0M 5s\n", + "398650K .......... .......... .......... .......... .......... 67% 62.3M 5s\n", + "398700K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", + "398750K .......... .......... .......... .......... .......... 67% 56.4M 5s\n", + "398800K .......... .......... .......... .......... .......... 67% 57.9M 5s\n", + "398850K .......... .......... .......... .......... .......... 67% 65.2M 5s\n", + "398900K .......... .......... .......... .......... .......... 67% 63.2M 5s\n", + "398950K .......... .......... .......... .......... .......... 67% 40.3M 5s\n", + "399000K .......... .......... .......... .......... .......... 67% 45.4M 5s\n", + "399050K .......... .......... .......... .......... .......... 67% 61.5M 5s\n", + "399100K .......... .......... .......... .......... .......... 67% 61.1M 5s\n", + "399150K .......... .......... .......... .......... .......... 67% 62.5M 5s\n", + "399200K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", + "399250K .......... .......... .......... .......... .......... 67% 63.9M 5s\n", + "399300K .......... .......... .......... .......... .......... 67% 59.4M 5s\n", + "399350K .......... .......... .......... .......... .......... 67% 64.0M 5s\n", + "399400K .......... .......... .......... .......... .......... 67% 55.4M 5s\n", + "399450K .......... .......... .......... .......... .......... 67% 54.4M 5s\n", + "399500K .......... .......... .......... .......... .......... 67% 51.4M 5s\n", + "399550K .......... .......... .......... .......... .......... 67% 57.5M 5s\n", + "399600K .......... .......... .......... .......... .......... 67% 59.0M 5s\n", + "399650K .......... .......... .......... .......... .......... 67% 59.3M 5s\n", + "399700K .......... .......... .......... .......... .......... 67% 56.4M 5s\n", + "399750K .......... .......... .......... .......... .......... 67% 53.8M 5s\n", + "399800K .......... .......... .......... .......... .......... 67% 56.7M 5s\n", + "399850K .......... .......... .......... .......... .......... 67% 68.7M 5s\n", + "399900K .......... .......... .......... .......... .......... 67% 70.4M 5s\n", + "399950K .......... .......... .......... .......... .......... 67% 69.2M 5s\n", + "400000K .......... .......... .......... .......... .......... 67% 59.4M 5s\n", + "400050K .......... .......... .......... .......... .......... 67% 54.4M 5s\n", + "400100K .......... .......... .......... .......... .......... 67% 69.5M 5s\n", + "400150K .......... .......... .......... .......... .......... 67% 68.8M 5s\n", + "400200K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", + "400250K .......... .......... .......... .......... .......... 67% 57.0M 5s\n", + "400300K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", + "400350K .......... .......... .......... .......... .......... 67% 52.4M 5s\n", + "400400K .......... .......... .......... .......... .......... 67% 57.1M 5s\n", + "400450K .......... .......... .......... .......... .......... 67% 67.2M 5s\n", + "400500K .......... .......... .......... .......... .......... 67% 52.2M 5s\n", + "400550K .......... .......... .......... .......... .......... 67% 48.6M 5s\n", + "400600K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", + "400650K .......... .......... .......... .......... .......... 67% 64.2M 5s\n", + "400700K .......... .......... .......... .......... .......... 67% 62.9M 5s\n", + "400750K .......... .......... .......... .......... .......... 67% 63.3M 5s\n", + "400800K .......... .......... .......... .......... .......... 67% 46.8M 5s\n", + "400850K .......... .......... .......... .......... .......... 67% 51.6M 5s\n", + "400900K .......... .......... .......... .......... .......... 67% 60.8M 5s\n", + "400950K .......... .......... .......... .......... .......... 67% 57.5M 5s\n", + "401000K .......... .......... .......... .......... .......... 67% 48.0M 5s\n", + "401050K .......... .......... .......... .......... .......... 67% 58.2M 5s\n", + "401100K .......... .......... .......... .......... .......... 67% 51.7M 5s\n", + "401150K .......... .......... .......... .......... .......... 67% 57.7M 5s\n", + "401200K .......... .......... .......... .......... .......... 67% 51.8M 5s\n", + "401250K .......... .......... .......... .......... .......... 67% 58.2M 5s\n", + "401300K .......... .......... .......... .......... .......... 67% 56.5M 5s\n", + "401350K .......... .......... .......... .......... .......... 67% 45.3M 5s\n", + "401400K .......... .......... .......... .......... .......... 67% 63.9M 5s\n", + "401450K .......... .......... .......... .......... .......... 67% 72.5M 5s\n", + "401500K .......... .......... .......... .......... .......... 67% 68.6M 5s\n", + "401550K .......... .......... .......... .......... .......... 67% 63.3M 5s\n", + "401600K .......... .......... .......... .......... .......... 67% 62.7M 5s\n", + "401650K .......... .......... .......... .......... .......... 67% 49.4M 5s\n", + "401700K .......... .......... .......... .......... .......... 67% 58.0M 5s\n", + "401750K .......... .......... .......... .......... .......... 67% 68.2M 5s\n", + "401800K .......... .......... .......... .......... .......... 67% 56.5M 5s\n", + "401850K .......... .......... .......... .......... .......... 67% 23.4M 5s\n", + "401900K .......... .......... .......... .......... .......... 67% 40.4M 5s\n", + "401950K .......... .......... .......... .......... .......... 67% 65.1M 5s\n", + "402000K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", + "402050K .......... .......... .......... .......... .......... 67% 32.9M 5s\n", + "402100K .......... .......... .......... .......... .......... 67% 30.6M 5s\n", + "402150K .......... .......... .......... .......... .......... 67% 69.2M 5s\n", + "402200K .......... .......... .......... .......... .......... 67% 49.5M 5s\n", + "402250K .......... .......... .......... .......... .......... 67% 38.2M 5s\n", + "402300K .......... .......... .......... .......... .......... 67% 30.8M 5s\n", + "402350K .......... .......... .......... .......... .......... 67% 63.4M 5s\n", + "402400K .......... .......... .......... .......... .......... 67% 67.4M 5s\n", + "402450K .......... .......... .......... .......... .......... 67% 27.1M 5s\n", + "402500K .......... .......... .......... .......... .......... 67% 35.0M 5s\n", + "402550K .......... .......... .......... .......... .......... 67% 51.8M 5s\n", + "402600K .......... .......... .......... .......... .......... 67% 28.9M 5s\n", + "402650K .......... .......... .......... .......... .......... 67% 39.9M 5s\n", + "402700K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", + "402750K .......... .......... .......... .......... .......... 67% 53.7M 5s\n", + "402800K .......... .......... .......... .......... .......... 67% 61.5M 5s\n", + "402850K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", + "402900K .......... .......... .......... .......... .......... 67% 56.2M 5s\n", + "402950K .......... .......... .......... .......... .......... 67% 46.7M 5s\n", + "403000K .......... .......... .......... .......... .......... 67% 43.4M 5s\n", + "403050K .......... .......... .......... .......... .......... 67% 31.4M 5s\n", + "403100K .......... .......... .......... .......... .......... 67% 35.9M 5s\n", + "403150K .......... .......... .......... .......... .......... 67% 36.3M 5s\n", + "403200K .......... .......... .......... .......... .......... 67% 45.1M 5s\n", + "403250K .......... .......... .......... .......... .......... 67% 31.3M 5s\n", + "403300K .......... .......... .......... .......... .......... 67% 49.4M 5s\n", + "403350K .......... .......... .......... .......... .......... 67% 42.0M 5s\n", + "403400K .......... .......... .......... .......... .......... 67% 44.3M 5s\n", + "403450K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", + "403500K .......... .......... .......... .......... .......... 67% 44.3M 5s\n", + "403550K .......... .......... .......... .......... .......... 67% 56.2M 5s\n", + "403600K .......... .......... .......... .......... .......... 67% 59.0M 5s\n", + "403650K .......... .......... .......... .......... .......... 67% 51.6M 5s\n", + "403700K .......... .......... .......... .......... .......... 67% 47.9M 5s\n", + "403750K .......... .......... .......... .......... .......... 67% 39.6M 5s\n", + "403800K .......... .......... .......... .......... .......... 67% 47.9M 5s\n", + "403850K .......... .......... .......... .......... .......... 67% 36.1M 5s\n", + "403900K .......... .......... .......... .......... .......... 67% 3.68M 5s\n", + "403950K .......... .......... .......... .......... .......... 67% 58.9M 5s\n", + "404000K .......... .......... .......... .......... .......... 67% 68.3M 5s\n", + "404050K .......... .......... .......... .......... .......... 67% 73.6M 5s\n", + "404100K .......... .......... .......... .......... .......... 67% 20.7M 5s\n", + "404150K .......... .......... .......... .......... .......... 67% 27.7M 5s\n", + "404200K .......... .......... .......... .......... .......... 67% 57.1M 5s\n", + "404250K .......... .......... .......... .......... .......... 67% 55.4M 5s\n", + "404300K .......... .......... .......... .......... .......... 67% 62.6M 5s\n", + "404350K .......... .......... .......... .......... .......... 67% 26.6M 5s\n", + "404400K .......... .......... .......... .......... .......... 68% 58.8M 5s\n", + "404450K .......... .......... .......... .......... .......... 68% 78.0M 5s\n", + "404500K .......... .......... .......... .......... .......... 68% 54.6M 5s\n", + "404550K .......... .......... .......... .......... .......... 68% 25.0M 5s\n", + "404600K .......... .......... .......... .......... .......... 68% 36.4M 5s\n", + "404650K .......... .......... .......... .......... .......... 68% 69.2M 5s\n", + "404700K .......... .......... .......... .......... .......... 68% 52.0M 5s\n", + "404750K .......... .......... .......... .......... .......... 68% 28.4M 5s\n", + "404800K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", + "404850K .......... .......... .......... .......... .......... 68% 54.1M 5s\n", + "404900K .......... .......... .......... .......... .......... 68% 74.9M 5s\n", + "404950K .......... .......... .......... .......... .......... 68% 47.9M 5s\n", + "405000K .......... .......... .......... .......... .......... 68% 32.5M 5s\n", + "405050K .......... .......... .......... .......... .......... 68% 40.6M 5s\n", + "405100K .......... .......... .......... .......... .......... 68% 73.5M 5s\n", + "405150K .......... .......... .......... .......... .......... 68% 53.1M 5s\n", + "405200K .......... .......... .......... .......... .......... 68% 32.2M 5s\n", + "405250K .......... .......... .......... .......... .......... 68% 44.5M 5s\n", + "405300K .......... .......... .......... .......... .......... 68% 51.8M 5s\n", + "405350K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", + "405400K .......... .......... .......... .......... .......... 68% 35.9M 5s\n", + "405450K .......... .......... .......... .......... .......... 68% 39.5M 5s\n", + "405500K .......... .......... .......... .......... .......... 68% 64.6M 5s\n", + "405550K .......... .......... .......... .......... .......... 68% 68.8M 5s\n", + "405600K .......... .......... .......... .......... .......... 68% 33.3M 5s\n", + "405650K .......... .......... .......... .......... .......... 68% 39.1M 5s\n", + "405700K .......... .......... .......... .......... .......... 68% 60.3M 5s\n", + "405750K .......... .......... .......... .......... .......... 68% 52.7M 5s\n", + "405800K .......... .......... .......... .......... .......... 68% 31.6M 5s\n", + "405850K .......... .......... .......... .......... .......... 68% 44.5M 5s\n", + "405900K .......... .......... .......... .......... .......... 68% 41.3M 5s\n", + "405950K .......... .......... .......... .......... .......... 68% 68.9M 5s\n", + "406000K .......... .......... .......... .......... .......... 68% 52.9M 5s\n", + "406050K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", + "406100K .......... .......... .......... .......... .......... 68% 59.3M 5s\n", + "406150K .......... .......... .......... .......... .......... 68% 39.3M 5s\n", + "406200K .......... .......... .......... .......... .......... 68% 28.0M 5s\n", + "406250K .......... .......... .......... .......... .......... 68% 35.7M 5s\n", + "406300K .......... .......... .......... .......... .......... 68% 47.1M 5s\n", + "406350K .......... .......... .......... .......... .......... 68% 59.8M 5s\n", + "406400K .......... .......... .......... .......... .......... 68% 54.0M 5s\n", + "406450K .......... .......... .......... .......... .......... 68% 66.7M 5s\n", + "406500K .......... .......... .......... .......... .......... 68% 53.0M 5s\n", + "406550K .......... .......... .......... .......... .......... 68% 27.6M 5s\n", + "406600K .......... .......... .......... .......... .......... 68% 27.2M 5s\n", + "406650K .......... .......... .......... .......... .......... 68% 29.0M 5s\n", + "406700K .......... .......... .......... .......... .......... 68% 28.2M 5s\n", + "406750K .......... .......... .......... .......... .......... 68% 29.5M 5s\n", + "406800K .......... .......... .......... .......... .......... 68% 42.9M 5s\n", + "406850K .......... .......... .......... .......... .......... 68% 64.4M 5s\n", + "406900K .......... .......... .......... .......... .......... 68% 44.4M 5s\n", + "406950K .......... .......... .......... .......... .......... 68% 55.8M 5s\n", + "407000K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", + "407050K .......... .......... .......... .......... .......... 68% 59.4M 5s\n", + "407100K .......... .......... .......... .......... .......... 68% 48.0M 5s\n", + "407150K .......... .......... .......... .......... .......... 68% 43.8M 5s\n", + "407200K .......... .......... .......... .......... .......... 68% 47.6M 5s\n", + "407250K .......... .......... .......... .......... .......... 68% 41.8M 5s\n", + "407300K .......... .......... .......... .......... .......... 68% 35.7M 5s\n", + "407350K .......... .......... .......... .......... .......... 68% 35.3M 5s\n", + "407400K .......... .......... .......... .......... .......... 68% 35.1M 5s\n", + "407450K .......... .......... .......... .......... .......... 68% 35.0M 5s\n", + "407500K .......... .......... .......... .......... .......... 68% 46.7M 5s\n", + "407550K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", + "407600K .......... .......... .......... .......... .......... 68% 43.7M 5s\n", + "407650K .......... .......... .......... .......... .......... 68% 36.9M 5s\n", + "407700K .......... .......... .......... .......... .......... 68% 53.1M 5s\n", + "407750K .......... .......... .......... .......... .......... 68% 44.1M 5s\n", + "407800K .......... .......... .......... .......... .......... 68% 34.3M 5s\n", + "407850K .......... .......... .......... .......... .......... 68% 38.5M 5s\n", + "407900K .......... .......... .......... .......... .......... 68% 53.3M 5s\n", + "407950K .......... .......... .......... .......... .......... 68% 45.7M 5s\n", + "408000K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", + "408050K .......... .......... .......... .......... .......... 68% 45.9M 5s\n", + "408100K .......... .......... .......... .......... .......... 68% 56.9M 5s\n", + "408150K .......... .......... .......... .......... .......... 68% 51.6M 5s\n", + "408200K .......... .......... .......... .......... .......... 68% 25.4M 5s\n", + "408250K .......... .......... .......... .......... .......... 68% 59.1M 5s\n", + "408300K .......... .......... .......... .......... .......... 68% 61.4M 5s\n", + "408350K .......... .......... .......... .......... .......... 68% 54.5M 5s\n", + "408400K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", + "408450K .......... .......... .......... .......... .......... 68% 39.5M 5s\n", + "408500K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", + "408550K .......... .......... .......... .......... .......... 68% 51.3M 5s\n", + "408600K .......... .......... .......... .......... .......... 68% 28.8M 5s\n", + "408650K .......... .......... .......... .......... .......... 68% 35.5M 5s\n", + "408700K .......... .......... .......... .......... .......... 68% 54.5M 5s\n", + "408750K .......... .......... .......... .......... .......... 68% 45.1M 5s\n", + "408800K .......... .......... .......... .......... .......... 68% 22.8M 5s\n", + "408850K .......... .......... .......... .......... .......... 68% 49.8M 5s\n", + "408900K .......... .......... .......... .......... .......... 68% 50.1M 5s\n", + "408950K .......... .......... .......... .......... .......... 68% 46.0M 5s\n", + "409000K .......... .......... .......... .......... .......... 68% 31.2M 5s\n", + "409050K .......... .......... .......... .......... .......... 68% 68.4M 5s\n", + "409100K .......... .......... .......... .......... .......... 68% 52.5M 5s\n", + "409150K .......... .......... .......... .......... .......... 68% 58.4M 5s\n", + "409200K .......... .......... .......... .......... .......... 68% 29.7M 5s\n", + "409250K .......... .......... .......... .......... .......... 68% 50.1M 5s\n", + "409300K .......... .......... .......... .......... .......... 68% 61.3M 5s\n", + "409350K .......... .......... .......... .......... .......... 68% 46.2M 5s\n", + "409400K .......... .......... .......... .......... .......... 68% 30.5M 5s\n", + "409450K .......... .......... .......... .......... .......... 68% 39.6M 5s\n", + "409500K .......... .......... .......... .......... .......... 68% 38.2M 5s\n", + "409550K .......... .......... .......... .......... .......... 68% 48.1M 5s\n", + "409600K .......... .......... .......... .......... .......... 68% 39.7M 5s\n", + "409650K .......... .......... .......... .......... .......... 68% 31.5M 5s\n", + "409700K .......... .......... .......... .......... .......... 68% 45.1M 5s\n", + "409750K .......... .......... .......... .......... .......... 68% 42.9M 5s\n", + "409800K .......... .......... .......... .......... .......... 68% 39.6M 5s\n", + "409850K .......... .......... .......... .......... .......... 68% 36.8M 5s\n", + "409900K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", + "409950K .......... .......... .......... .......... .......... 68% 46.2M 5s\n", + "410000K .......... .......... .......... .......... .......... 68% 41.8M 5s\n", + "410050K .......... .......... .......... .......... .......... 68% 31.3M 5s\n", + "410100K .......... .......... .......... .......... .......... 68% 44.3M 5s\n", + "410150K .......... .......... .......... .......... .......... 68% 55.2M 5s\n", + "410200K .......... .......... .......... .......... .......... 68% 28.5M 5s\n", + "410250K .......... .......... .......... .......... .......... 68% 43.1M 5s\n", + "410300K .......... .......... .......... .......... .......... 68% 51.9M 5s\n", + "410350K .......... .......... .......... .......... .......... 69% 42.7M 5s\n", + "410400K .......... .......... .......... .......... .......... 69% 42.3M 5s\n", + "410450K .......... .......... .......... .......... .......... 69% 46.5M 5s\n", + "410500K .......... .......... .......... .......... .......... 69% 49.5M 5s\n", + "410550K .......... .......... .......... .......... .......... 69% 44.4M 5s\n", + "410600K .......... .......... .......... .......... .......... 69% 38.4M 5s\n", + "410650K .......... .......... .......... .......... .......... 69% 51.5M 5s\n", + "410700K .......... .......... .......... .......... .......... 69% 44.8M 5s\n", + "410750K .......... .......... .......... .......... .......... 69% 44.9M 5s\n", + "410800K .......... .......... .......... .......... .......... 69% 56.7M 5s\n", + "410850K .......... .......... .......... .......... .......... 69% 40.6M 5s\n", + "410900K .......... .......... .......... .......... .......... 69% 31.8M 5s\n", + "410950K .......... .......... .......... .......... .......... 69% 41.0M 5s\n", + "411000K .......... .......... .......... .......... .......... 69% 41.5M 5s\n", + "411050K .......... .......... .......... .......... .......... 69% 35.5M 5s\n", + "411100K .......... .......... .......... .......... .......... 69% 47.6M 5s\n", + "411150K .......... .......... .......... .......... .......... 69% 43.0M 5s\n", + "411200K .......... .......... .......... .......... .......... 69% 45.2M 5s\n", + "411250K .......... .......... .......... .......... .......... 69% 39.8M 5s\n", + "411300K .......... .......... .......... .......... .......... 69% 50.2M 5s\n", + "411350K .......... .......... .......... .......... .......... 69% 61.2M 5s\n", + "411400K .......... .......... .......... .......... .......... 69% 30.8M 5s\n", + "411450K .......... .......... .......... .......... .......... 69% 32.2M 5s\n", + "411500K .......... .......... .......... .......... .......... 69% 51.2M 5s\n", + "411550K .......... .......... .......... .......... .......... 69% 55.0M 5s\n", + "411600K .......... .......... .......... .......... .......... 69% 29.9M 5s\n", + "411650K .......... .......... .......... .......... .......... 69% 40.0M 5s\n", + "411700K .......... .......... .......... .......... .......... 69% 37.8M 5s\n", + "411750K .......... .......... .......... .......... .......... 69% 34.2M 5s\n", + "411800K .......... .......... .......... .......... .......... 69% 28.9M 5s\n", + "411850K .......... .......... .......... .......... .......... 69% 37.8M 5s\n", + "411900K .......... .......... .......... .......... .......... 69% 41.3M 5s\n", + "411950K .......... .......... .......... .......... .......... 69% 45.0M 5s\n", + "412000K .......... .......... .......... .......... .......... 69% 30.2M 5s\n", + "412050K .......... .......... .......... .......... .......... 69% 46.3M 5s\n", + "412100K .......... .......... .......... .......... .......... 69% 61.4M 5s\n", + "412150K .......... .......... .......... .......... .......... 69% 31.6M 5s\n", + "412200K .......... .......... .......... .......... .......... 69% 30.8M 5s\n", + "412250K .......... .......... .......... .......... .......... 69% 57.9M 5s\n", + "412300K .......... .......... .......... .......... .......... 69% 31.6M 5s\n", + "412350K .......... .......... .......... .......... .......... 69% 78.3M 5s\n", + "412400K .......... .......... .......... .......... .......... 69% 30.2M 5s\n", + "412450K .......... .......... .......... .......... .......... 69% 45.9M 5s\n", + "412500K .......... .......... .......... .......... .......... 69% 52.7M 5s\n", + "412550K .......... .......... .......... .......... .......... 69% 72.8M 5s\n", + "412600K .......... .......... .......... .......... .......... 69% 21.3M 5s\n", + "412650K .......... .......... .......... .......... .......... 69% 44.3M 5s\n", + "412700K .......... .......... .......... .......... .......... 69% 65.5M 5s\n", + "412750K .......... .......... .......... .......... .......... 69% 40.2M 5s\n", + "412800K .......... .......... .......... .......... .......... 69% 25.6M 5s\n", + "412850K .......... .......... .......... .......... .......... 69% 44.7M 5s\n", + "412900K .......... .......... .......... .......... .......... 69% 49.2M 5s\n", + "412950K .......... .......... .......... .......... .......... 69% 38.6M 5s\n", + "413000K .......... .......... .......... .......... .......... 69% 24.8M 5s\n", + "413050K .......... .......... .......... .......... .......... 69% 48.0M 5s\n", + "413100K .......... .......... .......... .......... .......... 69% 37.5M 5s\n", + "413150K .......... .......... .......... .......... .......... 69% 31.7M 5s\n", + "413200K .......... .......... .......... .......... .......... 69% 29.3M 5s\n", + "413250K .......... .......... .......... .......... .......... 69% 37.0M 5s\n", + "413300K .......... .......... .......... .......... .......... 69% 35.5M 5s\n", + "413350K .......... .......... .......... .......... .......... 69% 36.1M 5s\n", + "413400K .......... .......... .......... .......... .......... 69% 33.5M 5s\n", + "413450K .......... .......... .......... .......... .......... 69% 31.9M 5s\n", + "413500K .......... .......... .......... .......... .......... 69% 34.1M 5s\n", + "413550K .......... .......... .......... .......... .......... 69% 38.6M 5s\n", + "413600K .......... .......... .......... .......... .......... 69% 61.9M 5s\n", + "413650K .......... .......... .......... .......... .......... 69% 28.8M 5s\n", + "413700K .......... .......... .......... .......... .......... 69% 36.0M 5s\n", + "413750K .......... .......... .......... .......... .......... 69% 52.3M 5s\n", + "413800K .......... .......... .......... .......... .......... 69% 48.0M 5s\n", + "413850K .......... .......... .......... .......... .......... 69% 36.1M 5s\n", + "413900K .......... .......... .......... .......... .......... 69% 59.8M 5s\n", + "413950K .......... .......... .......... .......... .......... 69% 44.9M 5s\n", + "414000K .......... .......... .......... .......... .......... 69% 56.2M 5s\n", + "414050K .......... .......... .......... .......... .......... 69% 73.0M 5s\n", + "414100K .......... .......... .......... .......... .......... 69% 39.7M 5s\n", + "414150K .......... .......... .......... .......... .......... 69% 34.8M 5s\n", + "414200K .......... .......... .......... .......... .......... 69% 47.6M 5s\n", + "414250K .......... .......... .......... .......... .......... 69% 51.9M 5s\n", + "414300K .......... .......... .......... .......... .......... 69% 36.7M 5s\n", + "414350K .......... .......... .......... .......... .......... 69% 52.6M 5s\n", + "414400K .......... .......... .......... .......... .......... 69% 45.7M 5s\n", + "414450K .......... .......... .......... .......... .......... 69% 63.3M 5s\n", + "414500K .......... .......... .......... .......... .......... 69% 48.2M 5s\n", + "414550K .......... .......... .......... .......... .......... 69% 50.8M 5s\n", + "414600K .......... .......... .......... .......... .......... 69% 41.5M 5s\n", + "414650K .......... .......... .......... .......... .......... 69% 38.5M 5s\n", + "414700K .......... .......... .......... .......... .......... 69% 58.6M 5s\n", + "414750K .......... .......... .......... .......... .......... 69% 51.0M 5s\n", + "414800K .......... .......... .......... .......... .......... 69% 41.3M 5s\n", + "414850K .......... .......... .......... .......... .......... 69% 35.2M 5s\n", + "414900K .......... .......... .......... .......... .......... 69% 7.22M 5s\n", + "414950K .......... .......... .......... .......... .......... 69% 61.3M 5s\n", + "415000K .......... .......... .......... .......... .......... 69% 54.3M 5s\n", + "415050K .......... .......... .......... .......... .......... 69% 77.8M 5s\n", + "415100K .......... .......... .......... .......... .......... 69% 65.1M 5s\n", + "415150K .......... .......... .......... .......... .......... 69% 76.6M 5s\n", + "415200K .......... .......... .......... .......... .......... 69% 70.1M 5s\n", + "415250K .......... .......... .......... .......... .......... 69% 36.9M 5s\n", + "415300K .......... .......... .......... .......... .......... 69% 66.6M 5s\n", + "415350K .......... .......... .......... .......... .......... 69% 58.3M 5s\n", + "415400K .......... .......... .......... .......... .......... 69% 36.4M 5s\n", + "415450K .......... .......... .......... .......... .......... 69% 50.3M 5s\n", + "415500K .......... .......... .......... .......... .......... 69% 42.0M 5s\n", + "415550K .......... .......... .......... .......... .......... 69% 43.9M 5s\n", + "415600K .......... .......... .......... .......... .......... 69% 41.1M 5s\n", + "415650K .......... .......... .......... .......... .......... 69% 57.1M 5s\n", + "415700K .......... .......... .......... .......... .......... 69% 41.0M 5s\n", + "415750K .......... .......... .......... .......... .......... 69% 64.1M 5s\n", + "415800K .......... .......... .......... .......... .......... 69% 27.8M 5s\n", + "415850K .......... .......... .......... .......... .......... 69% 38.2M 5s\n", + "415900K .......... .......... .......... .......... .......... 69% 50.9M 5s\n", + "415950K .......... .......... .......... .......... .......... 69% 48.6M 5s\n", + "416000K .......... .......... .......... .......... .......... 69% 36.6M 5s\n", + "416050K .......... .......... .......... .......... .......... 69% 45.8M 5s\n", + "416100K .......... .......... .......... .......... .......... 69% 59.7M 5s\n", + "416150K .......... .......... .......... .......... .......... 69% 56.3M 5s\n", + "416200K .......... .......... .......... .......... .......... 69% 29.3M 5s\n", + "416250K .......... .......... .......... .......... .......... 69% 56.5M 5s\n", + "416300K .......... .......... .......... .......... .......... 70% 49.2M 5s\n", + "416350K .......... .......... .......... .......... .......... 70% 69.4M 5s\n", + "416400K .......... .......... .......... .......... .......... 70% 26.6M 5s\n", + "416450K .......... .......... .......... .......... .......... 70% 40.4M 5s\n", + "416500K .......... .......... .......... .......... .......... 70% 63.9M 5s\n", + "416550K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", + "416600K .......... .......... .......... .......... .......... 70% 36.7M 5s\n", + "416650K .......... .......... .......... .......... .......... 70% 40.6M 5s\n", + "416700K .......... .......... .......... .......... .......... 70% 67.8M 5s\n", + "416750K .......... .......... .......... .......... .......... 70% 49.8M 5s\n", + "416800K .......... .......... .......... .......... .......... 70% 36.6M 5s\n", + "416850K .......... .......... .......... .......... .......... 70% 56.2M 5s\n", + "416900K .......... .......... .......... .......... .......... 70% 47.6M 5s\n", + "416950K .......... .......... .......... .......... .......... 70% 70.6M 5s\n", + "417000K .......... .......... .......... .......... .......... 70% 35.5M 5s\n", + "417050K .......... .......... .......... .......... .......... 70% 49.0M 5s\n", + "417100K .......... .......... .......... .......... .......... 70% 56.0M 5s\n", + "417150K .......... .......... .......... .......... .......... 70% 77.8M 5s\n", + "417200K .......... .......... .......... .......... .......... 70% 3.66M 5s\n", + "417250K .......... .......... .......... .......... .......... 70% 75.8M 5s\n", + "417300K .......... .......... .......... .......... .......... 70% 68.8M 5s\n", + "417350K .......... .......... .......... .......... .......... 70% 59.4M 5s\n", + "417400K .......... .......... .......... .......... .......... 70% 59.5M 5s\n", + "417450K .......... .......... .......... .......... .......... 70% 64.5M 5s\n", + "417500K .......... .......... .......... .......... .......... 70% 33.9M 5s\n", + "417550K .......... .......... .......... .......... .......... 70% 54.4M 5s\n", + "417600K .......... .......... .......... .......... .......... 70% 63.6M 5s\n", + "417650K .......... .......... .......... .......... .......... 70% 70.8M 5s\n", + "417700K .......... .......... .......... .......... .......... 70% 37.8M 5s\n", + "417750K .......... .......... .......... .......... .......... 70% 29.1M 5s\n", + "417800K .......... .......... .......... .......... .......... 70% 47.2M 5s\n", + "417850K .......... .......... .......... .......... .......... 70% 68.3M 5s\n", + "417900K .......... .......... .......... .......... .......... 70% 42.7M 5s\n", + "417950K .......... .......... .......... .......... .......... 70% 32.9M 5s\n", + "418000K .......... .......... .......... .......... .......... 70% 64.3M 5s\n", + "418050K .......... .......... .......... .......... .......... 70% 66.4M 5s\n", + "418100K .......... .......... .......... .......... .......... 70% 69.6M 5s\n", + "418150K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", + "418200K .......... .......... .......... .......... .......... 70% 35.1M 5s\n", + "418250K .......... .......... .......... .......... .......... 70% 68.4M 5s\n", + "418300K .......... .......... .......... .......... .......... 70% 65.4M 5s\n", + "418350K .......... .......... .......... .......... .......... 70% 48.3M 5s\n", + "418400K .......... .......... .......... .......... .......... 70% 36.8M 5s\n", + "418450K .......... .......... .......... .......... .......... 70% 48.2M 5s\n", + "418500K .......... .......... .......... .......... .......... 70% 75.2M 5s\n", + "418550K .......... .......... .......... .......... .......... 70% 75.3M 5s\n", + "418600K .......... .......... .......... .......... .......... 70% 41.0M 5s\n", + "418650K .......... .......... .......... .......... .......... 70% 31.5M 5s\n", + "418700K .......... .......... .......... .......... .......... 70% 66.9M 5s\n", + "418750K .......... .......... .......... .......... .......... 70% 69.2M 5s\n", + "418800K .......... .......... .......... .......... .......... 70% 43.4M 5s\n", + "418850K .......... .......... .......... .......... .......... 70% 38.1M 5s\n", + "418900K .......... .......... .......... .......... .......... 70% 50.0M 5s\n", + "418950K .......... .......... .......... .......... .......... 70% 63.8M 5s\n", + "419000K .......... .......... .......... .......... .......... 70% 55.1M 5s\n", + "419050K .......... .......... .......... .......... .......... 70% 41.8M 5s\n", + "419100K .......... .......... .......... .......... .......... 70% 38.4M 5s\n", + "419150K .......... .......... .......... .......... .......... 70% 59.3M 5s\n", + "419200K .......... .......... .......... .......... .......... 70% 57.5M 5s\n", + "419250K .......... .......... .......... .......... .......... 70% 36.4M 5s\n", + "419300K .......... .......... .......... .......... .......... 70% 35.7M 5s\n", + "419350K .......... .......... .......... .......... .......... 70% 48.2M 5s\n", + "419400K .......... .......... .......... .......... .......... 70% 33.5M 5s\n", + "419450K .......... .......... .......... .......... .......... 70% 36.2M 5s\n", + "419500K .......... .......... .......... .......... .......... 70% 44.4M 5s\n", + "419550K .......... .......... .......... .......... .......... 70% 63.7M 5s\n", + "419600K .......... .......... .......... .......... .......... 70% 42.0M 5s\n", + "419650K .......... .......... .......... .......... .......... 70% 58.4M 5s\n", + "419700K .......... .......... .......... .......... .......... 70% 33.3M 5s\n", + "419750K .......... .......... .......... .......... .......... 70% 55.3M 5s\n", + "419800K .......... .......... .......... .......... .......... 70% 36.3M 5s\n", + "419850K .......... .......... .......... .......... .......... 70% 36.7M 5s\n", + "419900K .......... .......... .......... .......... .......... 70% 42.6M 5s\n", + "419950K .......... .......... .......... .......... .......... 70% 61.3M 5s\n", + "420000K .......... .......... .......... .......... .......... 70% 37.4M 5s\n", + "420050K .......... .......... .......... .......... .......... 70% 48.5M 5s\n", + "420100K .......... .......... .......... .......... .......... 70% 50.6M 5s\n", + "420150K .......... .......... .......... .......... .......... 70% 40.8M 5s\n", + "420200K .......... .......... .......... .......... .......... 70% 60.6M 5s\n", + "420250K .......... .......... .......... .......... .......... 70% 36.4M 5s\n", + "420300K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", + "420350K .......... .......... .......... .......... .......... 70% 64.7M 5s\n", + "420400K .......... .......... .......... .......... .......... 70% 63.1M 5s\n", + "420450K .......... .......... .......... .......... .......... 70% 64.0M 5s\n", + "420500K .......... .......... .......... .......... .......... 70% 60.0M 5s\n", + "420550K .......... .......... .......... .......... .......... 70% 54.3M 5s\n", + "420600K .......... .......... .......... .......... .......... 70% 57.2M 5s\n", + "420650K .......... .......... .......... .......... .......... 70% 69.1M 5s\n", + "420700K .......... .......... .......... .......... .......... 70% 4.00M 5s\n", + "420750K .......... .......... .......... .......... .......... 70% 32.4M 5s\n", + "420800K .......... .......... .......... .......... .......... 70% 33.5M 5s\n", + "420850K .......... .......... .......... .......... .......... 70% 40.9M 5s\n", + "420900K .......... .......... .......... .......... .......... 70% 27.8M 5s\n", + "420950K .......... .......... .......... .......... .......... 70% 29.4M 5s\n", + "421000K .......... .......... .......... .......... .......... 70% 54.7M 5s\n", + "421050K .......... .......... .......... .......... .......... 70% 29.9M 5s\n", + "421100K .......... .......... .......... .......... .......... 70% 47.1M 5s\n", + "421150K .......... .......... .......... .......... .......... 70% 63.6M 5s\n", + "421200K .......... .......... .......... .......... .......... 70% 61.1M 5s\n", + "421250K .......... .......... .......... .......... .......... 70% 66.9M 5s\n", + "421300K .......... .......... .......... .......... .......... 70% 6.56M 5s\n", + "421350K .......... .......... .......... .......... .......... 70% 14.3M 5s\n", + "421400K .......... .......... .......... .......... .......... 70% 31.1M 5s\n", + "421450K .......... .......... .......... .......... .......... 70% 37.5M 5s\n", + "421500K .......... .......... .......... .......... .......... 70% 29.8M 5s\n", + "421550K .......... .......... .......... .......... .......... 70% 28.7M 5s\n", + "421600K .......... .......... .......... .......... .......... 70% 46.3M 5s\n", + "421650K .......... .......... .......... .......... .......... 70% 62.5M 5s\n", + "421700K .......... .......... .......... .......... .......... 70% 47.9M 5s\n", + "421750K .......... .......... .......... .......... .......... 70% 61.0M 5s\n", + "421800K .......... .......... .......... .......... .......... 70% 56.6M 5s\n", + "421850K .......... .......... .......... .......... .......... 70% 72.6M 5s\n", + "421900K .......... .......... .......... .......... .......... 70% 60.1M 5s\n", + "421950K .......... .......... .......... .......... .......... 70% 56.9M 4s\n", + "422000K .......... .......... .......... .......... .......... 70% 50.1M 4s\n", + "422050K .......... .......... .......... .......... .......... 70% 64.6M 4s\n", + "422100K .......... .......... .......... .......... .......... 70% 42.0M 4s\n", + "422150K .......... .......... .......... .......... .......... 70% 58.2M 4s\n", + "422200K .......... .......... .......... .......... .......... 70% 32.4M 4s\n", + "422250K .......... .......... .......... .......... .......... 71% 46.3M 4s\n", + "422300K .......... .......... .......... .......... .......... 71% 60.5M 4s\n", + "422350K .......... .......... .......... .......... .......... 71% 67.0M 4s\n", + "422400K .......... .......... .......... .......... .......... 71% 43.0M 4s\n", + "422450K .......... .......... .......... .......... .......... 71% 46.7M 4s\n", + "422500K .......... .......... .......... .......... .......... 71% 55.4M 4s\n", + "422550K .......... .......... .......... .......... .......... 71% 67.1M 4s\n", + "422600K .......... .......... .......... .......... .......... 71% 40.3M 4s\n", + "422650K .......... .......... .......... .......... .......... 71% 50.5M 4s\n", + "422700K .......... .......... .......... .......... .......... 71% 52.9M 4s\n", + "422750K .......... .......... .......... .......... .......... 71% 64.5M 4s\n", + "422800K .......... .......... .......... .......... .......... 71% 58.3M 4s\n", + "422850K .......... .......... .......... .......... .......... 71% 69.4M 4s\n", + "422900K .......... .......... .......... .......... .......... 71% 68.2M 4s\n", + "422950K .......... .......... .......... .......... .......... 71% 50.0M 4s\n", + "423000K .......... .......... .......... .......... .......... 71% 46.3M 4s\n", + "423050K .......... .......... .......... .......... .......... 71% 66.9M 4s\n", + "423100K .......... .......... .......... .......... .......... 71% 67.9M 4s\n", + "423150K .......... .......... .......... .......... .......... 71% 7.50M 4s\n", + "423200K .......... .......... .......... .......... .......... 71% 70.4M 4s\n", + "423250K .......... .......... .......... .......... .......... 71% 59.9M 4s\n", + "423300K .......... .......... .......... .......... .......... 71% 54.9M 4s\n", + "423350K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", + "423400K .......... .......... .......... .......... .......... 71% 54.1M 4s\n", + "423450K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", + "423500K .......... .......... .......... .......... .......... 71% 59.6M 4s\n", + "423550K .......... .......... .......... .......... .......... 71% 58.8M 4s\n", + "423600K .......... .......... .......... .......... .......... 71% 57.7M 4s\n", + "423650K .......... .......... .......... .......... .......... 71% 63.8M 4s\n", + "423700K .......... .......... .......... .......... .......... 71% 69.5M 4s\n", + "423750K .......... .......... .......... .......... .......... 71% 55.6M 4s\n", + "423800K .......... .......... .......... .......... .......... 71% 36.6M 4s\n", + "423850K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", + "423900K .......... .......... .......... .......... .......... 71% 72.1M 4s\n", + "423950K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", + "424000K .......... .......... .......... .......... .......... 71% 49.0M 4s\n", + "424050K .......... .......... .......... .......... .......... 71% 45.2M 4s\n", + "424100K .......... .......... .......... .......... .......... 71% 45.8M 4s\n", + "424150K .......... .......... .......... .......... .......... 71% 64.9M 4s\n", + "424200K .......... .......... .......... .......... .......... 71% 54.8M 4s\n", + "424250K .......... .......... .......... .......... .......... 71% 39.1M 4s\n", + "424300K .......... .......... .......... .......... .......... 71% 47.1M 4s\n", + "424350K .......... .......... .......... .......... .......... 71% 53.7M 4s\n", + "424400K .......... .......... .......... .......... .......... 71% 60.3M 4s\n", + "424450K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", + "424500K .......... .......... .......... .......... .......... 71% 56.2M 4s\n", + "424550K .......... .......... .......... .......... .......... 71% 43.2M 4s\n", + "424600K .......... .......... .......... .......... .......... 71% 49.3M 4s\n", + "424650K .......... .......... .......... .......... .......... 71% 3.81M 4s\n", + "424700K .......... .......... .......... .......... .......... 71% 47.1M 4s\n", + "424750K .......... .......... .......... .......... .......... 71% 63.5M 4s\n", + "424800K .......... .......... .......... .......... .......... 71% 50.2M 4s\n", + "424850K .......... .......... .......... .......... .......... 71% 66.7M 4s\n", + "424900K .......... .......... .......... .......... .......... 71% 58.0M 4s\n", + "424950K .......... .......... .......... .......... .......... 71% 56.7M 4s\n", + "425000K .......... .......... .......... .......... .......... 71% 58.8M 4s\n", + "425050K .......... .......... .......... .......... .......... 71% 62.1M 4s\n", + "425100K .......... .......... .......... .......... .......... 71% 51.5M 4s\n", + "425150K .......... .......... .......... .......... .......... 71% 71.6M 4s\n", + "425200K .......... .......... .......... .......... .......... 71% 36.0M 4s\n", + "425250K .......... .......... .......... .......... .......... 71% 66.9M 4s\n", + "425300K .......... .......... .......... .......... .......... 71% 53.7M 4s\n", + "425350K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", + "425400K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", + "425450K .......... .......... .......... .......... .......... 71% 46.8M 4s\n", + "425500K .......... .......... .......... .......... .......... 71% 66.8M 4s\n", + "425550K .......... .......... .......... .......... .......... 71% 57.6M 4s\n", + "425600K .......... .......... .......... .......... .......... 71% 45.9M 4s\n", + "425650K .......... .......... .......... .......... .......... 71% 62.6M 4s\n", + "425700K .......... .......... .......... .......... .......... 71% 46.0M 4s\n", + "425750K .......... .......... .......... .......... .......... 71% 47.9M 4s\n", + "425800K .......... .......... .......... .......... .......... 71% 40.2M 4s\n", + "425850K .......... .......... .......... .......... .......... 71% 67.0M 4s\n", + "425900K .......... .......... .......... .......... .......... 71% 50.5M 4s\n", + "425950K .......... .......... .......... .......... .......... 71% 60.1M 4s\n", + "426000K .......... .......... .......... .......... .......... 71% 66.8M 4s\n", + "426050K .......... .......... .......... .......... .......... 71% 60.6M 4s\n", + "426100K .......... .......... .......... .......... .......... 71% 47.4M 4s\n", + "426150K .......... .......... .......... .......... .......... 71% 50.2M 4s\n", + "426200K .......... .......... .......... .......... .......... 71% 49.2M 4s\n", + "426250K .......... .......... .......... .......... .......... 71% 67.7M 4s\n", + "426300K .......... .......... .......... .......... .......... 71% 34.5M 4s\n", + "426350K .......... .......... .......... .......... .......... 71% 43.8M 4s\n", + "426400K .......... .......... .......... .......... .......... 71% 48.2M 4s\n", + "426450K .......... .......... .......... .......... .......... 71% 61.9M 4s\n", + "426500K .......... .......... .......... .......... .......... 71% 48.7M 4s\n", + "426550K .......... .......... .......... .......... .......... 71% 41.3M 4s\n", + "426600K .......... .......... .......... .......... .......... 71% 39.2M 4s\n", + "426650K .......... .......... .......... .......... .......... 71% 64.2M 4s\n", + "426700K .......... .......... .......... .......... .......... 71% 54.8M 4s\n", + "426750K .......... .......... .......... .......... .......... 71% 44.2M 4s\n", + "426800K .......... .......... .......... .......... .......... 71% 48.5M 4s\n", + "426850K .......... .......... .......... .......... .......... 71% 53.8M 4s\n", + "426900K .......... .......... .......... .......... .......... 71% 65.8M 4s\n", + "426950K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", + "427000K .......... .......... .......... .......... .......... 71% 38.1M 4s\n", + "427050K .......... .......... .......... .......... .......... 71% 47.0M 4s\n", + "427100K .......... .......... .......... .......... .......... 71% 52.8M 4s\n", + "427150K .......... .......... .......... .......... .......... 71% 54.1M 4s\n", + "427200K .......... .......... .......... .......... .......... 71% 51.7M 4s\n", + "427250K .......... .......... .......... .......... .......... 71% 43.4M 4s\n", + "427300K .......... .......... .......... .......... .......... 71% 45.4M 4s\n", + "427350K .......... .......... .......... .......... .......... 71% 46.5M 4s\n", + "427400K .......... .......... .......... .......... .......... 71% 47.3M 4s\n", + "427450K .......... .......... .......... .......... .......... 71% 51.7M 4s\n", + "427500K .......... .......... .......... .......... .......... 71% 49.0M 4s\n", + "427550K .......... .......... .......... .......... .......... 71% 62.0M 4s\n", + "427600K .......... .......... .......... .......... .......... 71% 55.4M 4s\n", + "427650K .......... .......... .......... .......... .......... 71% 25.2M 4s\n", + "427700K .......... .......... .......... .......... .......... 71% 3.48M 4s\n", + "427750K .......... .......... .......... .......... .......... 71% 59.6M 4s\n", + "427800K .......... .......... .......... .......... .......... 71% 47.4M 4s\n", + "427850K .......... .......... .......... .......... .......... 71% 60.5M 4s\n", + "427900K .......... .......... .......... .......... .......... 71% 61.7M 4s\n", + "427950K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", + "428000K .......... .......... .......... .......... .......... 71% 53.4M 4s\n", + "428050K .......... .......... .......... .......... .......... 71% 55.1M 4s\n", + "428100K .......... .......... .......... .......... .......... 71% 36.7M 4s\n", + "428150K .......... .......... .......... .......... .......... 71% 39.3M 4s\n", + "428200K .......... .......... .......... .......... .......... 72% 31.6M 4s\n", + "428250K .......... .......... .......... .......... .......... 72% 34.4M 4s\n", + "428300K .......... .......... .......... .......... .......... 72% 44.5M 4s\n", + "428350K .......... .......... .......... .......... .......... 72% 3.29M 4s\n", + "428400K .......... .......... .......... .......... .......... 72% 38.5M 4s\n", + "428450K .......... .......... .......... .......... .......... 72% 42.8M 4s\n", + "428500K .......... .......... .......... .......... .......... 72% 37.7M 4s\n", + "428550K .......... .......... .......... .......... .......... 72% 32.5M 4s\n", + "428600K .......... .......... .......... .......... .......... 72% 34.2M 4s\n", + "428650K .......... .......... .......... .......... .......... 72% 42.3M 4s\n", + "428700K .......... .......... .......... .......... .......... 72% 31.6M 4s\n", + "428750K .......... .......... .......... .......... .......... 72% 37.8M 4s\n", + "428800K .......... .......... .......... .......... .......... 72% 38.6M 4s\n", + "428850K .......... .......... .......... .......... .......... 72% 34.5M 4s\n", + "428900K .......... .......... .......... .......... .......... 72% 39.8M 4s\n", + "428950K .......... .......... .......... .......... .......... 72% 42.5M 4s\n", + "429000K .......... .......... .......... .......... .......... 72% 35.3M 4s\n", + "429050K .......... .......... .......... .......... .......... 72% 36.4M 4s\n", + "429100K .......... .......... .......... .......... .......... 72% 44.8M 4s\n", + "429150K .......... .......... .......... .......... .......... 72% 43.6M 4s\n", + "429200K .......... .......... .......... .......... .......... 72% 32.4M 4s\n", + "429250K .......... .......... .......... .......... .......... 72% 35.1M 4s\n", + "429300K .......... .......... .......... .......... .......... 72% 42.7M 4s\n", + "429350K .......... .......... .......... .......... .......... 72% 43.3M 4s\n", + "429400K .......... .......... .......... .......... .......... 72% 24.1M 4s\n", + "429450K .......... .......... .......... .......... .......... 72% 38.5M 4s\n", + "429500K .......... .......... .......... .......... .......... 72% 46.9M 4s\n", + "429550K .......... .......... .......... .......... .......... 72% 53.9M 4s\n", + "429600K .......... .......... .......... .......... .......... 72% 52.2M 4s\n", + "429650K .......... .......... .......... .......... .......... 72% 52.5M 4s\n", + "429700K .......... .......... .......... .......... .......... 72% 62.8M 4s\n", + "429750K .......... .......... .......... .......... .......... 72% 65.1M 4s\n", + "429800K .......... .......... .......... .......... .......... 72% 42.7M 4s\n", + "429850K .......... .......... .......... .......... .......... 72% 27.4M 4s\n", + "429900K .......... .......... .......... .......... .......... 72% 38.4M 4s\n", + "429950K .......... .......... .......... .......... .......... 72% 34.9M 4s\n", + "430000K .......... .......... .......... .......... .......... 72% 42.2M 4s\n", + "430050K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", + "430100K .......... .......... .......... .......... .......... 72% 56.0M 4s\n", + "430150K .......... .......... .......... .......... .......... 72% 67.9M 4s\n", + "430200K .......... .......... .......... .......... .......... 72% 54.5M 4s\n", + "430250K .......... .......... .......... .......... .......... 72% 3.83M 4s\n", + "430300K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", + "430350K .......... .......... .......... .......... .......... 72% 63.1M 4s\n", + "430400K .......... .......... .......... .......... .......... 72% 51.4M 4s\n", + "430450K .......... .......... .......... .......... .......... 72% 21.0M 4s\n", + "430500K .......... .......... .......... .......... .......... 72% 60.0M 4s\n", + "430550K .......... .......... .......... .......... .......... 72% 56.6M 4s\n", + "430600K .......... .......... .......... .......... .......... 72% 3.98M 4s\n", + "430650K .......... .......... .......... .......... .......... 72% 64.2M 4s\n", + "430700K .......... .......... .......... .......... .......... 72% 63.7M 4s\n", + "430750K .......... .......... .......... .......... .......... 72% 57.8M 4s\n", + "430800K .......... .......... .......... .......... .......... 72% 59.0M 4s\n", + "430850K .......... .......... .......... .......... .......... 72% 57.0M 4s\n", + "430900K .......... .......... .......... .......... .......... 72% 52.3M 4s\n", + "430950K .......... .......... .......... .......... .......... 72% 69.6M 4s\n", + "431000K .......... .......... .......... .......... .......... 72% 51.7M 4s\n", + "431050K .......... .......... .......... .......... .......... 72% 55.2M 4s\n", + "431100K .......... .......... .......... .......... .......... 72% 62.0M 4s\n", + "431150K .......... .......... .......... .......... .......... 72% 42.1M 4s\n", + "431200K .......... .......... .......... .......... .......... 72% 56.5M 4s\n", + "431250K .......... .......... .......... .......... .......... 72% 55.8M 4s\n", + "431300K .......... .......... .......... .......... .......... 72% 51.8M 4s\n", + "431350K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", + "431400K .......... .......... .......... .......... .......... 72% 45.0M 4s\n", + "431450K .......... .......... .......... .......... .......... 72% 59.7M 4s\n", + "431500K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", + "431550K .......... .......... .......... .......... .......... 72% 51.1M 4s\n", + "431600K .......... .......... .......... .......... .......... 72% 60.2M 4s\n", + "431650K .......... .......... .......... .......... .......... 72% 55.7M 4s\n", + "431700K .......... .......... .......... .......... .......... 72% 59.9M 4s\n", + "431750K .......... .......... .......... .......... .......... 72% 65.5M 4s\n", + "431800K .......... .......... .......... .......... .......... 72% 37.0M 4s\n", + "431850K .......... .......... .......... .......... .......... 72% 65.0M 4s\n", + "431900K .......... .......... .......... .......... .......... 72% 56.2M 4s\n", + "431950K .......... .......... .......... .......... .......... 72% 63.6M 4s\n", + "432000K .......... .......... .......... .......... .......... 72% 61.8M 4s\n", + "432050K .......... .......... .......... .......... .......... 72% 47.7M 4s\n", + "432100K .......... .......... .......... .......... .......... 72% 60.9M 4s\n", + "432150K .......... .......... .......... .......... .......... 72% 61.5M 4s\n", + "432200K .......... .......... .......... .......... .......... 72% 47.6M 4s\n", + "432250K .......... .......... .......... .......... .......... 72% 71.5M 4s\n", + "432300K .......... .......... .......... .......... .......... 72% 52.2M 4s\n", + "432350K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", + "432400K .......... .......... .......... .......... .......... 72% 56.5M 4s\n", + "432450K .......... .......... .......... .......... .......... 72% 68.4M 4s\n", + "432500K .......... .......... .......... .......... .......... 72% 54.8M 4s\n", + "432550K .......... .......... .......... .......... .......... 72% 59.5M 4s\n", + "432600K .......... .......... .......... .......... .......... 72% 40.1M 4s\n", + "432650K .......... .......... .......... .......... .......... 72% 65.1M 4s\n", + "432700K .......... .......... .......... .......... .......... 72% 4.24M 4s\n", + "432750K .......... .......... .......... .......... .......... 72% 59.1M 4s\n", + "432800K .......... .......... .......... .......... .......... 72% 36.1M 4s\n", + "432850K .......... .......... .......... .......... .......... 72% 38.0M 4s\n", + "432900K .......... .......... .......... .......... .......... 72% 43.6M 4s\n", + "432950K .......... .......... .......... .......... .......... 72% 44.3M 4s\n", + "433000K .......... .......... .......... .......... .......... 72% 56.4M 4s\n", + "433050K .......... .......... .......... .......... .......... 72% 72.6M 4s\n", + "433100K .......... .......... .......... .......... .......... 72% 61.3M 4s\n", + "433150K .......... .......... .......... .......... .......... 72% 45.1M 4s\n", + "433200K .......... .......... .......... .......... .......... 72% 49.5M 4s\n", + "433250K .......... .......... .......... .......... .......... 72% 68.6M 4s\n", + "433300K .......... .......... .......... .......... .......... 72% 69.8M 4s\n", + "433350K .......... .......... .......... .......... .......... 72% 70.0M 4s\n", + "433400K .......... .......... .......... .......... .......... 72% 47.6M 4s\n", + "433450K .......... .......... .......... .......... .......... 72% 53.7M 4s\n", + "433500K .......... .......... .......... .......... .......... 72% 58.1M 4s\n", + "433550K .......... .......... .......... .......... .......... 72% 73.9M 4s\n", + "433600K .......... .......... .......... .......... .......... 72% 53.5M 4s\n", + "433650K .......... .......... .......... .......... .......... 72% 70.3M 4s\n", + "433700K .......... .......... .......... .......... .......... 72% 35.5M 4s\n", + "433750K .......... .......... .......... .......... .......... 72% 39.0M 4s\n", + "433800K .......... .......... .......... .......... .......... 72% 40.5M 4s\n", + "433850K .......... .......... .......... .......... .......... 72% 63.5M 4s\n", + "433900K .......... .......... .......... .......... .......... 72% 48.1M 4s\n", + "433950K .......... .......... .......... .......... .......... 72% 41.4M 4s\n", + "434000K .......... .......... .......... .......... .......... 72% 60.1M 4s\n", + "434050K .......... .......... .......... .......... .......... 72% 61.0M 4s\n", + "434100K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", + "434150K .......... .......... .......... .......... .......... 73% 5.50M 4s\n", + "434200K .......... .......... .......... .......... .......... 73% 41.2M 4s\n", + "434250K .......... .......... .......... .......... .......... 73% 61.5M 4s\n", + "434300K .......... .......... .......... .......... .......... 73% 62.0M 4s\n", + "434350K .......... .......... .......... .......... .......... 73% 48.4M 4s\n", + "434400K .......... .......... .......... .......... .......... 73% 47.6M 4s\n", + "434450K .......... .......... .......... .......... .......... 73% 74.2M 4s\n", + "434500K .......... .......... .......... .......... .......... 73% 78.1M 4s\n", + "434550K .......... .......... .......... .......... .......... 73% 74.9M 4s\n", + "434600K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", + "434650K .......... .......... .......... .......... .......... 73% 63.4M 4s\n", + "434700K .......... .......... .......... .......... .......... 73% 43.9M 4s\n", + "434750K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", + "434800K .......... .......... .......... .......... .......... 73% 42.3M 4s\n", + "434850K .......... .......... .......... .......... .......... 73% 49.4M 4s\n", + "434900K .......... .......... .......... .......... .......... 73% 41.7M 4s\n", + "434950K .......... .......... .......... .......... .......... 73% 51.3M 4s\n", + "435000K .......... .......... .......... .......... .......... 73% 47.7M 4s\n", + "435050K .......... .......... .......... .......... .......... 73% 65.2M 4s\n", + "435100K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", + "435150K .......... .......... .......... .......... .......... 73% 49.9M 4s\n", + "435200K .......... .......... .......... .......... .......... 73% 56.2M 4s\n", + "435250K .......... .......... .......... .......... .......... 73% 59.2M 4s\n", + "435300K .......... .......... .......... .......... .......... 73% 65.5M 4s\n", + "435350K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", + "435400K .......... .......... .......... .......... .......... 73% 45.5M 4s\n", + "435450K .......... .......... .......... .......... .......... 73% 49.6M 4s\n", + "435500K .......... .......... .......... .......... .......... 73% 28.7M 4s\n", + "435550K .......... .......... .......... .......... .......... 73% 35.0M 4s\n", + "435600K .......... .......... .......... .......... .......... 73% 28.1M 4s\n", + "435650K .......... .......... .......... .......... .......... 73% 3.63M 4s\n", + "435700K .......... .......... .......... .......... .......... 73% 55.3M 4s\n", + "435750K .......... .......... .......... .......... .......... 73% 43.7M 4s\n", + "435800K .......... .......... .......... .......... .......... 73% 27.8M 4s\n", + "435850K .......... .......... .......... .......... .......... 73% 31.7M 4s\n", + "435900K .......... .......... .......... .......... .......... 73% 37.1M 4s\n", + "435950K .......... .......... .......... .......... .......... 73% 40.4M 4s\n", + "436000K .......... .......... .......... .......... .......... 73% 36.5M 4s\n", + "436050K .......... .......... .......... .......... .......... 73% 29.8M 4s\n", + "436100K .......... .......... .......... .......... .......... 73% 53.0M 4s\n", + "436150K .......... .......... .......... .......... .......... 73% 71.6M 4s\n", + "436200K .......... .......... .......... .......... .......... 73% 57.0M 4s\n", + "436250K .......... .......... .......... .......... .......... 73% 49.0M 4s\n", + "436300K .......... .......... .......... .......... .......... 73% 51.9M 4s\n", + "436350K .......... .......... .......... .......... .......... 73% 68.4M 4s\n", + "436400K .......... .......... .......... .......... .......... 73% 57.4M 4s\n", + "436450K .......... .......... .......... .......... .......... 73% 71.0M 4s\n", + "436500K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", + "436550K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", + "436600K .......... .......... .......... .......... .......... 73% 42.4M 4s\n", + "436650K .......... .......... .......... .......... .......... 73% 65.5M 4s\n", + "436700K .......... .......... .......... .......... .......... 73% 44.1M 4s\n", + "436750K .......... .......... .......... .......... .......... 73% 58.7M 4s\n", + "436800K .......... .......... .......... .......... .......... 73% 48.0M 4s\n", + "436850K .......... .......... .......... .......... .......... 73% 41.8M 4s\n", + "436900K .......... .......... .......... .......... .......... 73% 55.2M 4s\n", + "436950K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", + "437000K .......... .......... .......... .......... .......... 73% 47.7M 4s\n", + "437050K .......... .......... .......... .......... .......... 73% 45.3M 4s\n", + "437100K .......... .......... .......... .......... .......... 73% 36.2M 4s\n", + "437150K .......... .......... .......... .......... .......... 73% 36.4M 4s\n", + "437200K .......... .......... .......... .......... .......... 73% 29.6M 4s\n", + "437250K .......... .......... .......... .......... .......... 73% 35.3M 4s\n", + "437300K .......... .......... .......... .......... .......... 73% 62.0M 4s\n", + "437350K .......... .......... .......... .......... .......... 73% 61.8M 4s\n", + "437400K .......... .......... .......... .......... .......... 73% 44.0M 4s\n", + "437450K .......... .......... .......... .......... .......... 73% 4.55M 4s\n", + "437500K .......... .......... .......... .......... .......... 73% 51.0M 4s\n", + "437550K .......... .......... .......... .......... .......... 73% 61.0M 4s\n", + "437600K .......... .......... .......... .......... .......... 73% 53.5M 4s\n", + "437650K .......... .......... .......... .......... .......... 73% 67.6M 4s\n", + "437700K .......... .......... .......... .......... .......... 73% 58.4M 4s\n", + "437750K .......... .......... .......... .......... .......... 73% 6.50M 4s\n", + "437800K .......... .......... .......... .......... .......... 73% 44.8M 4s\n", + "437850K .......... .......... .......... .......... .......... 73% 64.9M 4s\n", + "437900K .......... .......... .......... .......... .......... 73% 61.5M 4s\n", + "437950K .......... .......... .......... .......... .......... 73% 67.4M 4s\n", + "438000K .......... .......... .......... .......... .......... 73% 54.9M 4s\n", + "438050K .......... .......... .......... .......... .......... 73% 48.9M 4s\n", + "438100K .......... .......... .......... .......... .......... 73% 66.1M 4s\n", + "438150K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", + "438200K .......... .......... .......... .......... .......... 73% 40.0M 4s\n", + "438250K .......... .......... .......... .......... .......... 73% 63.8M 4s\n", + "438300K .......... .......... .......... .......... .......... 73% 47.3M 4s\n", + "438350K .......... .......... .......... .......... .......... 73% 62.5M 4s\n", + "438400K .......... .......... .......... .......... .......... 73% 52.4M 4s\n", + "438450K .......... .......... .......... .......... .......... 73% 17.7M 4s\n", + "438500K .......... .......... .......... .......... .......... 73% 52.3M 4s\n", + "438550K .......... .......... .......... .......... .......... 73% 51.2M 4s\n", + "438600K .......... .......... .......... .......... .......... 73% 45.5M 4s\n", + "438650K .......... .......... .......... .......... .......... 73% 63.4M 4s\n", + "438700K .......... .......... .......... .......... .......... 73% 57.9M 4s\n", + "438750K .......... .......... .......... .......... .......... 73% 54.8M 4s\n", + "438800K .......... .......... .......... .......... .......... 73% 53.5M 4s\n", + "438850K .......... .......... .......... .......... .......... 73% 42.9M 4s\n", + "438900K .......... .......... .......... .......... .......... 73% 67.2M 4s\n", + "438950K .......... .......... .......... .......... .......... 73% 59.1M 4s\n", + "439000K .......... .......... .......... .......... .......... 73% 50.5M 4s\n", + "439050K .......... .......... .......... .......... .......... 73% 48.2M 4s\n", + "439100K .......... .......... .......... .......... .......... 73% 51.1M 4s\n", + "439150K .......... .......... .......... .......... .......... 73% 57.7M 4s\n", + "439200K .......... .......... .......... .......... .......... 73% 59.3M 4s\n", + "439250K .......... .......... .......... .......... .......... 73% 52.3M 4s\n", + "439300K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", + "439350K .......... .......... .......... .......... .......... 73% 48.4M 4s\n", + "439400K .......... .......... .......... .......... .......... 73% 50.9M 4s\n", + "439450K .......... .......... .......... .......... .......... 73% 57.7M 4s\n", + "439500K .......... .......... .......... .......... .......... 73% 50.6M 4s\n", + "439550K .......... .......... .......... .......... .......... 73% 47.1M 4s\n", + "439600K .......... .......... .......... .......... .......... 73% 9.77M 4s\n", + "439650K .......... .......... .......... .......... .......... 73% 46.1M 4s\n", + "439700K .......... .......... .......... .......... .......... 73% 67.6M 4s\n", + "439750K .......... .......... .......... .......... .......... 73% 68.7M 4s\n", + "439800K .......... .......... .......... .......... .......... 73% 52.7M 4s\n", + "439850K .......... .......... .......... .......... .......... 73% 60.3M 4s\n", + "439900K .......... .......... .......... .......... .......... 73% 47.6M 4s\n", + "439950K .......... .......... .......... .......... .......... 73% 54.3M 4s\n", + "440000K .......... .......... .......... .......... .......... 73% 66.0M 4s\n", + "440050K .......... .......... .......... .......... .......... 73% 64.0M 4s\n", + "440100K .......... .......... .......... .......... .......... 74% 66.9M 4s\n", + "440150K .......... .......... .......... .......... .......... 74% 65.0M 4s\n", + "440200K .......... .......... .......... .......... .......... 74% 41.6M 4s\n", + "440250K .......... .......... .......... .......... .......... 74% 54.7M 4s\n", + "440300K .......... .......... .......... .......... .......... 74% 77.6M 4s\n", + "440350K .......... .......... .......... .......... .......... 74% 74.4M 4s\n", + "440400K .......... .......... .......... .......... .......... 74% 62.8M 4s\n", + "440450K .......... .......... .......... .......... .......... 74% 74.7M 4s\n", + "440500K .......... .......... .......... .......... .......... 74% 52.6M 4s\n", + "440550K .......... .......... .......... .......... .......... 74% 49.2M 4s\n", + "440600K .......... .......... .......... .......... .......... 74% 51.9M 4s\n", + "440650K .......... .......... .......... .......... .......... 74% 66.3M 4s\n", + "440700K .......... .......... .......... .......... .......... 74% 64.3M 4s\n", + "440750K .......... .......... .......... .......... .......... 74% 64.3M 4s\n", + "440800K .......... .......... .......... .......... .......... 74% 44.3M 4s\n", + "440850K .......... .......... .......... .......... .......... 74% 51.8M 4s\n", + "440900K .......... .......... .......... .......... .......... 74% 55.0M 4s\n", + "440950K .......... .......... .......... .......... .......... 74% 63.4M 4s\n", + "441000K .......... .......... .......... .......... .......... 74% 43.1M 4s\n", + "441050K .......... .......... .......... .......... .......... 74% 34.4M 4s\n", + "441100K .......... .......... .......... .......... .......... 74% 47.8M 4s\n", + "441150K .......... .......... .......... .......... .......... 74% 41.3M 4s\n", + "441200K .......... .......... .......... .......... .......... 74% 45.2M 4s\n", + "441250K .......... .......... .......... .......... .......... 74% 50.2M 4s\n", + "441300K .......... .......... .......... .......... .......... 74% 43.5M 4s\n", + "441350K .......... .......... .......... .......... .......... 74% 37.1M 4s\n", + "441400K .......... .......... .......... .......... .......... 74% 42.3M 4s\n", + "441450K .......... .......... .......... .......... .......... 74% 74.7M 4s\n", + "441500K .......... .......... .......... .......... .......... 74% 60.6M 4s\n", + "441550K .......... .......... .......... .......... .......... 74% 43.1M 4s\n", + "441600K .......... .......... .......... .......... .......... 74% 35.0M 4s\n", + "441650K .......... .......... .......... .......... .......... 74% 54.5M 4s\n", + "441700K .......... .......... .......... .......... .......... 74% 49.8M 4s\n", + "441750K .......... .......... .......... .......... .......... 74% 36.1M 4s\n", + "441800K .......... .......... .......... .......... .......... 74% 33.6M 4s\n", + "441850K .......... .......... .......... .......... .......... 74% 50.1M 4s\n", + "441900K .......... .......... .......... .......... .......... 74% 44.6M 4s\n", + "441950K .......... .......... .......... .......... .......... 74% 55.9M 4s\n", + "442000K .......... .......... .......... .......... .......... 74% 51.5M 4s\n", + "442050K .......... .......... .......... .......... .......... 74% 48.6M 4s\n", + "442100K .......... .......... .......... .......... .......... 74% 64.4M 4s\n", + "442150K .......... .......... .......... .......... .......... 74% 46.2M 4s\n", + "442200K .......... .......... .......... .......... .......... 74% 38.4M 4s\n", + "442250K .......... .......... .......... .......... .......... 74% 38.3M 4s\n", + "442300K .......... .......... .......... .......... .......... 74% 61.8M 4s\n", + "442350K .......... .......... .......... .......... .......... 74% 30.8M 4s\n", + "442400K .......... .......... .......... .......... .......... 74% 37.0M 4s\n", + "442450K .......... .......... .......... .......... .......... 74% 63.0M 4s\n", + "442500K .......... .......... .......... .......... .......... 74% 54.4M 4s\n", + "442550K .......... .......... .......... .......... .......... 74% 50.7M 4s\n", + "442600K .......... .......... .......... .......... .......... 74% 47.8M 4s\n", + "442650K .......... .......... .......... .......... .......... 74% 54.6M 4s\n", + "442700K .......... .......... .......... .......... .......... 74% 54.4M 4s\n", + "442750K .......... .......... .......... .......... .......... 74% 46.5M 4s\n", + "442800K .......... .......... .......... .......... .......... 74% 51.3M 4s\n", + "442850K .......... .......... .......... .......... .......... 74% 70.9M 4s\n", + "442900K .......... .......... .......... .......... .......... 74% 57.7M 4s\n", + "442950K .......... .......... .......... .......... .......... 74% 58.6M 4s\n", + "443000K .......... .......... .......... .......... .......... 74% 40.6M 4s\n", + "443050K .......... .......... .......... .......... .......... 74% 61.1M 4s\n", + "443100K .......... .......... .......... .......... .......... 74% 49.5M 4s\n", + "443150K .......... .......... .......... .......... .......... 74% 4.57M 4s\n", + "443200K .......... .......... .......... .......... .......... 74% 52.7M 4s\n", + "443250K .......... .......... .......... .......... .......... 74% 58.7M 4s\n", + "443300K .......... .......... .......... .......... .......... 74% 60.7M 4s\n", + "443350K .......... .......... .......... .......... .......... 74% 64.1M 4s\n", + "443400K .......... .......... .......... .......... .......... 74% 46.5M 4s\n", + "443450K .......... .......... .......... .......... .......... 74% 54.5M 4s\n", + "443500K .......... .......... .......... .......... .......... 74% 59.0M 4s\n", + "443550K .......... .......... .......... .......... .......... 74% 60.5M 4s\n", + "443600K .......... .......... .......... .......... .......... 74% 47.5M 4s\n", + "443650K .......... .......... .......... .......... .......... 74% 62.2M 4s\n", + "443700K .......... .......... .......... .......... .......... 74% 53.7M 4s\n", + "443750K .......... .......... .......... .......... .......... 74% 57.3M 4s\n", + "443800K .......... .......... .......... .......... .......... 74% 39.1M 4s\n", + "443850K .......... .......... .......... .......... .......... 74% 55.0M 4s\n", + "443900K .......... .......... .......... .......... .......... 74% 45.3M 4s\n", + "443950K .......... .......... .......... .......... .......... 74% 46.9M 4s\n", + "444000K .......... .......... .......... .......... .......... 74% 56.8M 4s\n", + "444050K .......... .......... .......... .......... .......... 74% 46.2M 4s\n", + "444100K .......... .......... .......... .......... .......... 74% 54.7M 4s\n", + "444150K .......... .......... .......... .......... .......... 74% 42.2M 4s\n", + "444200K .......... .......... .......... .......... .......... 74% 40.3M 4s\n", + "444250K .......... .......... .......... .......... .......... 74% 45.1M 4s\n", + "444300K .......... .......... .......... .......... .......... 74% 46.7M 4s\n", + "444350K .......... .......... .......... .......... .......... 74% 46.8M 4s\n", + "444400K .......... .......... .......... .......... .......... 74% 13.0M 4s\n", + "444450K .......... .......... .......... .......... .......... 74% 42.5M 4s\n", + "444500K .......... .......... .......... .......... .......... 74% 48.0M 4s\n", + "444550K .......... .......... .......... .......... .......... 74% 45.5M 4s\n", + "444600K .......... .......... .......... .......... .......... 74% 40.5M 4s\n", + "444650K .......... .......... .......... .......... .......... 74% 45.3M 4s\n", + "444700K .......... .......... .......... .......... .......... 74% 60.8M 4s\n", + "444750K .......... .......... .......... .......... .......... 74% 62.6M 4s\n", + "444800K .......... .......... .......... .......... .......... 74% 52.5M 4s\n", + "444850K .......... .......... .......... .......... .......... 74% 56.0M 4s\n", + "444900K .......... .......... .......... .......... .......... 74% 47.2M 4s\n", + "444950K .......... .......... .......... .......... .......... 74% 61.5M 4s\n", + "445000K .......... .......... .......... .......... .......... 74% 54.8M 4s\n", + "445050K .......... .......... .......... .......... .......... 74% 49.8M 4s\n", + "445100K .......... .......... .......... .......... .......... 74% 46.8M 4s\n", + "445150K .......... .......... .......... .......... .......... 74% 53.8M 4s\n", + "445200K .......... .......... .......... .......... .......... 74% 52.3M 4s\n", + "445250K .......... .......... .......... .......... .......... 74% 56.7M 4s\n", + "445300K .......... .......... .......... .......... .......... 74% 60.0M 4s\n", + "445350K .......... .......... .......... .......... .......... 74% 35.3M 4s\n", + "445400K .......... .......... .......... .......... .......... 74% 35.3M 4s\n", + "445450K .......... .......... .......... .......... .......... 74% 46.7M 4s\n", + "445500K .......... .......... .......... .......... .......... 74% 45.2M 4s\n", + "445550K .......... .......... .......... .......... .......... 74% 38.3M 4s\n", + "445600K .......... .......... .......... .......... .......... 74% 41.7M 4s\n", + "445650K .......... .......... .......... .......... .......... 74% 55.9M 4s\n", + "445700K .......... .......... .......... .......... .......... 74% 63.6M 4s\n", + "445750K .......... .......... .......... .......... .......... 74% 57.7M 4s\n", + "445800K .......... .......... .......... .......... .......... 74% 44.1M 4s\n", + "445850K .......... .......... .......... .......... .......... 74% 53.0M 4s\n", + "445900K .......... .......... .......... .......... .......... 74% 74.0M 4s\n", + "445950K .......... .......... .......... .......... .......... 74% 65.9M 4s\n", + "446000K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", + "446050K .......... .......... .......... .......... .......... 75% 45.9M 4s\n", + "446100K .......... .......... .......... .......... .......... 75% 49.2M 4s\n", + "446150K .......... .......... .......... .......... .......... 75% 56.9M 4s\n", + "446200K .......... .......... .......... .......... .......... 75% 53.8M 4s\n", + "446250K .......... .......... .......... .......... .......... 75% 50.2M 4s\n", + "446300K .......... .......... .......... .......... .......... 75% 50.7M 4s\n", + "446350K .......... .......... .......... .......... .......... 75% 47.5M 4s\n", + "446400K .......... .......... .......... .......... .......... 75% 65.6M 4s\n", + "446450K .......... .......... .......... .......... .......... 75% 69.4M 4s\n", + "446500K .......... .......... .......... .......... .......... 75% 46.7M 4s\n", + "446550K .......... .......... .......... .......... .......... 75% 50.8M 4s\n", + "446600K .......... .......... .......... .......... .......... 75% 51.0M 4s\n", + "446650K .......... .......... .......... .......... .......... 75% 64.7M 4s\n", + "446700K .......... .......... .......... .......... .......... 75% 50.9M 4s\n", + "446750K .......... .......... .......... .......... .......... 75% 42.2M 4s\n", + "446800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", + "446850K .......... .......... .......... .......... .......... 75% 54.2M 4s\n", + "446900K .......... .......... .......... .......... .......... 75% 57.6M 4s\n", + "446950K .......... .......... .......... .......... .......... 75% 52.2M 4s\n", + "447000K .......... .......... .......... .......... .......... 75% 40.1M 4s\n", + "447050K .......... .......... .......... .......... .......... 75% 56.4M 4s\n", + "447100K .......... .......... .......... .......... .......... 75% 59.3M 4s\n", + "447150K .......... .......... .......... .......... .......... 75% 67.7M 4s\n", + "447200K .......... .......... .......... .......... .......... 75% 46.6M 4s\n", + "447250K .......... .......... .......... .......... .......... 75% 50.7M 4s\n", + "447300K .......... .......... .......... .......... .......... 75% 59.7M 4s\n", + "447350K .......... .......... .......... .......... .......... 75% 56.3M 4s\n", + "447400K .......... .......... .......... .......... .......... 75% 40.2M 4s\n", + "447450K .......... .......... .......... .......... .......... 75% 35.4M 4s\n", + "447500K .......... .......... .......... .......... .......... 75% 49.5M 4s\n", + "447550K .......... .......... .......... .......... .......... 75% 65.9M 4s\n", + "447600K .......... .......... .......... .......... .......... 75% 47.8M 4s\n", + "447650K .......... .......... .......... .......... .......... 75% 49.5M 4s\n", + "447700K .......... .......... .......... .......... .......... 75% 42.1M 4s\n", + "447750K .......... .......... .......... .......... .......... 75% 58.7M 4s\n", + "447800K .......... .......... .......... .......... .......... 75% 48.2M 4s\n", + "447850K .......... .......... .......... .......... .......... 75% 56.1M 4s\n", + "447900K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", + "447950K .......... .......... .......... .......... .......... 75% 51.5M 4s\n", + "448000K .......... .......... .......... .......... .......... 75% 44.6M 4s\n", + "448050K .......... .......... .......... .......... .......... 75% 57.1M 4s\n", + "448100K .......... .......... .......... .......... .......... 75% 40.4M 4s\n", + "448150K .......... .......... .......... .......... .......... 75% 42.9M 4s\n", + "448200K .......... .......... .......... .......... .......... 75% 43.2M 4s\n", + "448250K .......... .......... .......... .......... .......... 75% 70.8M 4s\n", + "448300K .......... .......... .......... .......... .......... 75% 51.5M 4s\n", + "448350K .......... .......... .......... .......... .......... 75% 45.1M 4s\n", + "448400K .......... .......... .......... .......... .......... 75% 45.9M 4s\n", + "448450K .......... .......... .......... .......... .......... 75% 3.62M 4s\n", + "448500K .......... .......... .......... .......... .......... 75% 45.0M 4s\n", + "448550K .......... .......... .......... .......... .......... 75% 45.3M 4s\n", + "448600K .......... .......... .......... .......... .......... 75% 36.0M 4s\n", + "448650K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", + "448700K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", + "448750K .......... .......... .......... .......... .......... 75% 64.0M 4s\n", + "448800K .......... .......... .......... .......... .......... 75% 55.9M 4s\n", + "448850K .......... .......... .......... .......... .......... 75% 50.5M 4s\n", + "448900K .......... .......... .......... .......... .......... 75% 59.7M 4s\n", + "448950K .......... .......... .......... .......... .......... 75% 56.2M 4s\n", + "449000K .......... .......... .......... .......... .......... 75% 53.4M 4s\n", + "449050K .......... .......... .......... .......... .......... 75% 68.9M 4s\n", + "449100K .......... .......... .......... .......... .......... 75% 69.2M 4s\n", + "449150K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", + "449200K .......... .......... .......... .......... .......... 75% 42.9M 4s\n", + "449250K .......... .......... .......... .......... .......... 75% 61.4M 4s\n", + "449300K .......... .......... .......... .......... .......... 75% 62.1M 4s\n", + "449350K .......... .......... .......... .......... .......... 75% 68.4M 4s\n", + "449400K .......... .......... .......... .......... .......... 75% 36.8M 4s\n", + "449450K .......... .......... .......... .......... .......... 75% 46.7M 4s\n", + "449500K .......... .......... .......... .......... .......... 75% 56.0M 4s\n", + "449550K .......... .......... .......... .......... .......... 75% 61.4M 4s\n", + "449600K .......... .......... .......... .......... .......... 75% 57.0M 4s\n", + "449650K .......... .......... .......... .......... .......... 75% 50.1M 4s\n", + "449700K .......... .......... .......... .......... .......... 75% 58.0M 4s\n", + "449750K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", + "449800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", + "449850K .......... .......... .......... .......... .......... 75% 53.2M 4s\n", + "449900K .......... .......... .......... .......... .......... 75% 51.8M 4s\n", + "449950K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", + "450000K .......... .......... .......... .......... .......... 75% 50.6M 4s\n", + "450050K .......... .......... .......... .......... .......... 75% 60.9M 4s\n", + "450100K .......... .......... .......... .......... .......... 75% 41.1M 4s\n", + "450150K .......... .......... .......... .......... .......... 75% 47.0M 4s\n", + "450200K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", + "450250K .......... .......... .......... .......... .......... 75% 60.7M 4s\n", + "450300K .......... .......... .......... .......... .......... 75% 42.0M 4s\n", + "450350K .......... .......... .......... .......... .......... 75% 43.2M 4s\n", + "450400K .......... .......... .......... .......... .......... 75% 3.86M 4s\n", + "450450K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", + "450500K .......... .......... .......... .......... .......... 75% 67.1M 4s\n", + "450550K .......... .......... .......... .......... .......... 75% 65.2M 4s\n", + "450600K .......... .......... .......... .......... .......... 75% 52.8M 4s\n", + "450650K .......... .......... .......... .......... .......... 75% 60.1M 4s\n", + "450700K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", + "450750K .......... .......... .......... .......... .......... 75% 59.1M 4s\n", + "450800K .......... .......... .......... .......... .......... 75% 48.0M 4s\n", + "450850K .......... .......... .......... .......... .......... 75% 53.5M 4s\n", + "450900K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", + "450950K .......... .......... .......... .......... .......... 75% 57.5M 4s\n", + "451000K .......... .......... .......... .......... .......... 75% 54.8M 4s\n", + "451050K .......... .......... .......... .......... .......... 75% 59.0M 4s\n", + "451100K .......... .......... .......... .......... .......... 75% 45.8M 4s\n", + "451150K .......... .......... .......... .......... .......... 75% 48.9M 4s\n", + "451200K .......... .......... .......... .......... .......... 75% 50.9M 4s\n", + "451250K .......... .......... .......... .......... .......... 75% 66.9M 4s\n", + "451300K .......... .......... .......... .......... .......... 75% 50.4M 4s\n", + "451350K .......... .......... .......... .......... .......... 75% 55.5M 4s\n", + "451400K .......... .......... .......... .......... .......... 75% 46.1M 4s\n", + "451450K .......... .......... .......... .......... .......... 75% 58.3M 4s\n", + "451500K .......... .......... .......... .......... .......... 75% 67.0M 4s\n", + "451550K .......... .......... .......... .......... .......... 75% 52.5M 4s\n", + "451600K .......... .......... .......... .......... .......... 75% 48.8M 4s\n", + "451650K .......... .......... .......... .......... .......... 75% 49.3M 4s\n", + "451700K .......... .......... .......... .......... .......... 75% 65.0M 4s\n", + "451750K .......... .......... .......... .......... .......... 75% 62.8M 4s\n", + "451800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", + "451850K .......... .......... .......... .......... .......... 75% 57.5M 4s\n", + "451900K .......... .......... .......... .......... .......... 75% 55.3M 4s\n", + "451950K .......... .......... .......... .......... .......... 76% 63.8M 4s\n", + "452000K .......... .......... .......... .......... .......... 76% 54.1M 4s\n", + "452050K .......... .......... .......... .......... .......... 76% 72.0M 4s\n", + "452100K .......... .......... .......... .......... .......... 76% 57.7M 4s\n", + "452150K .......... .......... .......... .......... .......... 76% 47.6M 4s\n", + "452200K .......... .......... .......... .......... .......... 76% 52.0M 4s\n", + "452250K .......... .......... .......... .......... .......... 76% 50.0M 4s\n", + "452300K .......... .......... .......... .......... .......... 76% 62.9M 4s\n", + "452350K .......... .......... .......... .......... .......... 76% 55.3M 4s\n", + "452400K .......... .......... .......... .......... .......... 76% 42.6M 4s\n", + "452450K .......... .......... .......... .......... .......... 76% 62.8M 4s\n", + "452500K .......... .......... .......... .......... .......... 76% 55.1M 4s\n", + "452550K .......... .......... .......... .......... .......... 76% 72.1M 4s\n", + "452600K .......... .......... .......... .......... .......... 76% 43.3M 4s\n", + "452650K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", + "452700K .......... .......... .......... .......... .......... 76% 64.6M 4s\n", + "452750K .......... .......... .......... .......... .......... 76% 51.9M 4s\n", + "452800K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", + "452850K .......... .......... .......... .......... .......... 76% 51.1M 4s\n", + "452900K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", + "452950K .......... .......... .......... .......... .......... 76% 69.3M 4s\n", + "453000K .......... .......... .......... .......... .......... 76% 51.6M 4s\n", + "453050K .......... .......... .......... .......... .......... 76% 64.7M 4s\n", + "453100K .......... .......... .......... .......... .......... 76% 64.6M 4s\n", + "453150K .......... .......... .......... .......... .......... 76% 50.3M 4s\n", + "453200K .......... .......... .......... .......... .......... 76% 50.3M 4s\n", + "453250K .......... .......... .......... .......... .......... 76% 68.4M 4s\n", + "453300K .......... .......... .......... .......... .......... 76% 54.4M 4s\n", + "453350K .......... .......... .......... .......... .......... 76% 64.1M 4s\n", + "453400K .......... .......... .......... .......... .......... 76% 38.5M 4s\n", + "453450K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", + "453500K .......... .......... .......... .......... .......... 76% 51.3M 4s\n", + "453550K .......... .......... .......... .......... .......... 76% 55.6M 4s\n", + "453600K .......... .......... .......... .......... .......... 76% 55.3M 4s\n", + "453650K .......... .......... .......... .......... .......... 76% 52.1M 4s\n", + "453700K .......... .......... .......... .......... .......... 76% 61.9M 4s\n", + "453750K .......... .......... .......... .......... .......... 76% 65.1M 4s\n", + "453800K .......... .......... .......... .......... .......... 76% 39.2M 4s\n", + "453850K .......... .......... .......... .......... .......... 76% 55.6M 4s\n", + "453900K .......... .......... .......... .......... .......... 76% 66.2M 4s\n", + "453950K .......... .......... .......... .......... .......... 76% 65.8M 4s\n", + "454000K .......... .......... .......... .......... .......... 76% 46.7M 4s\n", + "454050K .......... .......... .......... .......... .......... 76% 45.9M 4s\n", + "454100K .......... .......... .......... .......... .......... 76% 47.4M 4s\n", + "454150K .......... .......... .......... .......... .......... 76% 50.2M 4s\n", + "454200K .......... .......... .......... .......... .......... 76% 54.9M 4s\n", + "454250K .......... .......... .......... .......... .......... 76% 66.2M 4s\n", + "454300K .......... .......... .......... .......... .......... 76% 62.4M 4s\n", + "454350K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", + "454400K .......... .......... .......... .......... .......... 76% 46.3M 4s\n", + "454450K .......... .......... .......... .......... .......... 76% 60.5M 4s\n", + "454500K .......... .......... .......... .......... .......... 76% 68.6M 4s\n", + "454550K .......... .......... .......... .......... .......... 76% 63.4M 4s\n", + "454600K .......... .......... .......... .......... .......... 76% 31.1M 4s\n", + "454650K .......... .......... .......... .......... .......... 76% 44.2M 4s\n", + "454700K .......... .......... .......... .......... .......... 76% 56.7M 4s\n", + "454750K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", + "454800K .......... .......... .......... .......... .......... 76% 39.8M 4s\n", + "454850K .......... .......... .......... .......... .......... 76% 45.3M 4s\n", + "454900K .......... .......... .......... .......... .......... 76% 49.6M 4s\n", + "454950K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", + "455000K .......... .......... .......... .......... .......... 76% 44.7M 4s\n", + "455050K .......... .......... .......... .......... .......... 76% 49.9M 4s\n", + "455100K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", + "455150K .......... .......... .......... .......... .......... 76% 62.9M 4s\n", + "455200K .......... .......... .......... .......... .......... 76% 57.5M 4s\n", + "455250K .......... .......... .......... .......... .......... 76% 55.0M 4s\n", + "455300K .......... .......... .......... .......... .......... 76% 58.9M 4s\n", + "455350K .......... .......... .......... .......... .......... 76% 53.8M 4s\n", + "455400K .......... .......... .......... .......... .......... 76% 51.8M 4s\n", + "455450K .......... .......... .......... .......... .......... 76% 75.1M 4s\n", + "455500K .......... .......... .......... .......... .......... 76% 57.0M 4s\n", + "455550K .......... .......... .......... .......... .......... 76% 63.8M 4s\n", + "455600K .......... .......... .......... .......... .......... 76% 38.4M 4s\n", + "455650K .......... .......... .......... .......... .......... 76% 63.4M 4s\n", + "455700K .......... .......... .......... .......... .......... 76% 65.3M 4s\n", + "455750K .......... .......... .......... .......... .......... 76% 64.3M 4s\n", + "455800K .......... .......... .......... .......... .......... 76% 43.4M 4s\n", + "455850K .......... .......... .......... .......... .......... 76% 57.6M 4s\n", + "455900K .......... .......... .......... .......... .......... 76% 61.0M 4s\n", + "455950K .......... .......... .......... .......... .......... 76% 65.1M 4s\n", + "456000K .......... .......... .......... .......... .......... 76% 59.1M 4s\n", + "456050K .......... .......... .......... .......... .......... 76% 53.3M 4s\n", + "456100K .......... .......... .......... .......... .......... 76% 52.6M 4s\n", + "456150K .......... .......... .......... .......... .......... 76% 61.2M 4s\n", + "456200K .......... .......... .......... .......... .......... 76% 58.8M 4s\n", + "456250K .......... .......... .......... .......... .......... 76% 73.0M 4s\n", + "456300K .......... .......... .......... .......... .......... 76% 53.2M 4s\n", + "456350K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", + "456400K .......... .......... .......... .......... .......... 76% 51.0M 4s\n", + "456450K .......... .......... .......... .......... .......... 76% 76.3M 4s\n", + "456500K .......... .......... .......... .......... .......... 76% 71.2M 4s\n", + "456550K .......... .......... .......... .......... .......... 76% 69.0M 4s\n", + "456600K .......... .......... .......... .......... .......... 76% 49.1M 4s\n", + "456650K .......... .......... .......... .......... .......... 76% 47.0M 4s\n", + "456700K .......... .......... .......... .......... .......... 76% 74.2M 4s\n", + "456750K .......... .......... .......... .......... .......... 76% 69.4M 4s\n", + "456800K .......... .......... .......... .......... .......... 76% 57.3M 4s\n", + "456850K .......... .......... .......... .......... .......... 76% 55.9M 4s\n", + "456900K .......... .......... .......... .......... .......... 76% 49.1M 4s\n", + "456950K .......... .......... .......... .......... .......... 76% 50.9M 4s\n", + "457000K .......... .......... .......... .......... .......... 76% 59.5M 4s\n", + "457050K .......... .......... .......... .......... .......... 76% 64.9M 4s\n", + "457100K .......... .......... .......... .......... .......... 76% 61.5M 4s\n", + "457150K .......... .......... .......... .......... .......... 76% 51.8M 4s\n", + "457200K .......... .......... .......... .......... .......... 76% 46.3M 4s\n", + "457250K .......... .......... .......... .......... .......... 76% 57.4M 4s\n", + "457300K .......... .......... .......... .......... .......... 76% 69.9M 4s\n", + "457350K .......... .......... .......... .......... .......... 76% 69.2M 4s\n", + "457400K .......... .......... .......... .......... .......... 76% 40.9M 4s\n", + "457450K .......... .......... .......... .......... .......... 76% 55.5M 4s\n", + "457500K .......... .......... .......... .......... .......... 76% 61.6M 4s\n", + "457550K .......... .......... .......... .......... .......... 76% 67.5M 4s\n", + "457600K .......... .......... .......... .......... .......... 76% 58.7M 4s\n", + "457650K .......... .......... .......... .......... .......... 76% 47.1M 4s\n", + "457700K .......... .......... .......... .......... .......... 76% 48.0M 4s\n", + "457750K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", + "457800K .......... .......... .......... .......... .......... 76% 59.5M 4s\n", + "457850K .......... .......... .......... .......... .......... 76% 67.3M 4s\n", + "457900K .......... .......... .......... .......... .......... 77% 50.2M 4s\n", + "457950K .......... .......... .......... .......... .......... 77% 49.7M 4s\n", + "458000K .......... .......... .......... .......... .......... 77% 58.4M 4s\n", + "458050K .......... .......... .......... .......... .......... 77% 76.5M 4s\n", + "458100K .......... .......... .......... .......... .......... 77% 67.9M 4s\n", + "458150K .......... .......... .......... .......... .......... 77% 65.1M 4s\n", + "458200K .......... .......... .......... .......... .......... 77% 46.9M 4s\n", + "458250K .......... .......... .......... .......... .......... 77% 49.8M 4s\n", + "458300K .......... .......... .......... .......... .......... 77% 76.1M 4s\n", + "458350K .......... .......... .......... .......... .......... 77% 68.8M 4s\n", + "458400K .......... .......... .......... .......... .......... 77% 67.6M 4s\n", + "458450K .......... .......... .......... .......... .......... 77% 46.7M 4s\n", + "458500K .......... .......... .......... .......... .......... 77% 49.4M 4s\n", + "458550K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", + "458600K .......... .......... .......... .......... .......... 77% 58.1M 4s\n", + "458650K .......... .......... .......... .......... .......... 77% 60.2M 4s\n", + "458700K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", + "458750K .......... .......... .......... .......... .......... 77% 51.0M 4s\n", + "458800K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", + "458850K .......... .......... .......... .......... .......... 77% 69.0M 4s\n", + "458900K .......... .......... .......... .......... .......... 77% 65.1M 4s\n", + "458950K .......... .......... .......... .......... .......... 77% 72.6M 4s\n", + "459000K .......... .......... .......... .......... .......... 77% 37.3M 4s\n", + "459050K .......... .......... .......... .......... .......... 77% 49.2M 4s\n", + "459100K .......... .......... .......... .......... .......... 77% 68.8M 4s\n", + "459150K .......... .......... .......... .......... .......... 77% 71.8M 3s\n", + "459200K .......... .......... .......... .......... .......... 77% 62.2M 3s\n", + "459250K .......... .......... .......... .......... .......... 77% 51.2M 3s\n", + "459300K .......... .......... .......... .......... .......... 77% 50.9M 3s\n", + "459350K .......... .......... .......... .......... .......... 77% 54.6M 3s\n", + "459400K .......... .......... .......... .......... .......... 77% 60.7M 3s\n", + "459450K .......... .......... .......... .......... .......... 77% 77.7M 3s\n", + "459500K .......... .......... .......... .......... .......... 77% 47.9M 3s\n", + "459550K .......... .......... .......... .......... .......... 77% 52.8M 3s\n", + "459600K .......... .......... .......... .......... .......... 77% 51.1M 3s\n", + "459650K .......... .......... .......... .......... .......... 77% 75.3M 3s\n", + "459700K .......... .......... .......... .......... .......... 77% 59.4M 3s\n", + "459750K .......... .......... .......... .......... .......... 77% 46.0M 3s\n", + "459800K .......... .......... .......... .......... .......... 77% 43.0M 3s\n", + "459850K .......... .......... .......... .......... .......... 77% 71.8M 3s\n", + "459900K .......... .......... .......... .......... .......... 77% 72.8M 3s\n", + "459950K .......... .......... .......... .......... .......... 77% 63.2M 3s\n", + "460000K .......... .......... .......... .......... .......... 77% 49.4M 3s\n", + "460050K .......... .......... .......... .......... .......... 77% 60.3M 3s\n", + "460100K .......... .......... .......... .......... .......... 77% 62.1M 3s\n", + "460150K .......... .......... .......... .......... .......... 77% 71.4M 3s\n", + "460200K .......... .......... .......... .......... .......... 77% 62.2M 3s\n", + "460250K .......... .......... .......... .......... .......... 77% 54.4M 3s\n", + "460300K .......... .......... .......... .......... .......... 77% 44.3M 3s\n", + "460350K .......... .......... .......... .......... .......... 77% 53.1M 3s\n", + "460400K .......... .......... .......... .......... .......... 77% 63.7M 3s\n", + "460450K .......... .......... .......... .......... .......... 77% 70.8M 3s\n", + "460500K .......... .......... .......... .......... .......... 77% 61.3M 3s\n", + "460550K .......... .......... .......... .......... .......... 77% 51.9M 3s\n", + "460600K .......... .......... .......... .......... .......... 77% 37.5M 3s\n", + "460650K .......... .......... .......... .......... .......... 77% 65.0M 3s\n", + "460700K .......... .......... .......... .......... .......... 77% 67.4M 3s\n", + "460750K .......... .......... .......... .......... .......... 77% 76.8M 3s\n", + "460800K .......... .......... .......... .......... .......... 77% 46.8M 3s\n", + "460850K .......... .......... .......... .......... .......... 77% 49.0M 3s\n", + "460900K .......... .......... .......... .......... .......... 77% 76.7M 3s\n", + "460950K .......... .......... .......... .......... .......... 77% 77.7M 3s\n", + "461000K .......... .......... .......... .......... .......... 77% 3.78M 3s\n", + "461050K .......... .......... .......... .......... .......... 77% 71.5M 3s\n", + "461100K .......... .......... .......... .......... .......... 77% 65.4M 3s\n", + "461150K .......... .......... .......... .......... .......... 77% 68.3M 3s\n", + "461200K .......... .......... .......... .......... .......... 77% 54.1M 3s\n", + "461250K .......... .......... .......... .......... .......... 77% 60.5M 3s\n", + "461300K .......... .......... .......... .......... .......... 77% 69.4M 3s\n", + "461350K .......... .......... .......... .......... .......... 77% 66.5M 3s\n", + "461400K .......... .......... .......... .......... .......... 77% 52.1M 3s\n", + "461450K .......... .......... .......... .......... .......... 77% 55.6M 3s\n", + "461500K .......... .......... .......... .......... .......... 77% 59.7M 3s\n", + "461550K .......... .......... .......... .......... .......... 77% 17.2M 3s\n", + "461600K .......... .......... .......... .......... .......... 77% 52.8M 3s\n", + "461650K .......... .......... .......... .......... .......... 77% 59.8M 3s\n", + "461700K .......... .......... .......... .......... .......... 77% 49.1M 3s\n", + "461750K .......... .......... .......... .......... .......... 77% 48.9M 3s\n", + "461800K .......... .......... .......... .......... .......... 77% 59.2M 3s\n", + "461850K .......... .......... .......... .......... .......... 77% 45.4M 3s\n", + "461900K .......... .......... .......... .......... .......... 77% 53.4M 3s\n", + "461950K .......... .......... .......... .......... .......... 77% 3.99M 3s\n", + "462000K .......... .......... .......... .......... .......... 77% 60.3M 3s\n", + "462050K .......... .......... .......... .......... .......... 77% 62.7M 3s\n", + "462100K .......... .......... .......... .......... .......... 77% 67.7M 3s\n", + "462150K .......... .......... .......... .......... .......... 77% 63.4M 3s\n", + "462200K .......... .......... .......... .......... .......... 77% 52.4M 3s\n", + "462250K .......... .......... .......... .......... .......... 77% 54.9M 3s\n", + "462300K .......... .......... .......... .......... .......... 77% 60.9M 3s\n", + "462350K .......... .......... .......... .......... .......... 77% 66.0M 3s\n", + "462400K .......... .......... .......... .......... .......... 77% 61.1M 3s\n", + "462450K .......... .......... .......... .......... .......... 77% 15.5M 3s\n", + "462500K .......... .......... .......... .......... .......... 77% 71.2M 3s\n", + "462550K .......... .......... .......... .......... .......... 77% 65.7M 3s\n", + "462600K .......... .......... .......... .......... .......... 77% 43.1M 3s\n", + "462650K .......... .......... .......... .......... .......... 77% 60.2M 3s\n", + "462700K .......... .......... .......... .......... .......... 77% 67.2M 3s\n", + "462750K .......... .......... .......... .......... .......... 77% 49.9M 3s\n", + "462800K .......... .......... .......... .......... .......... 77% 53.2M 3s\n", + "462850K .......... .......... .......... .......... .......... 77% 47.0M 3s\n", + "462900K .......... .......... .......... .......... .......... 77% 61.4M 3s\n", + "462950K .......... .......... .......... .......... .......... 77% 69.6M 3s\n", + "463000K .......... .......... .......... .......... .......... 77% 43.2M 3s\n", + "463050K .......... .......... .......... .......... .......... 77% 49.4M 3s\n", + "463100K .......... .......... .......... .......... .......... 77% 4.37M 3s\n", + "463150K .......... .......... .......... .......... .......... 77% 57.1M 3s\n", + "463200K .......... .......... .......... .......... .......... 77% 53.9M 3s\n", + "463250K .......... .......... .......... .......... .......... 77% 71.2M 3s\n", + "463300K .......... .......... .......... .......... .......... 77% 70.2M 3s\n", + "463350K .......... .......... .......... .......... .......... 77% 65.0M 3s\n", + "463400K .......... .......... .......... .......... .......... 77% 47.9M 3s\n", + "463450K .......... .......... .......... .......... .......... 77% 44.8M 3s\n", + "463500K .......... .......... .......... .......... .......... 77% 56.4M 3s\n", + "463550K .......... .......... .......... .......... .......... 77% 59.2M 3s\n", + "463600K .......... .......... .......... .......... .......... 77% 50.5M 3s\n", + "463650K .......... .......... .......... .......... .......... 77% 40.0M 3s\n", + "463700K .......... .......... .......... .......... .......... 77% 42.3M 3s\n", + "463750K .......... .......... .......... .......... .......... 77% 71.4M 3s\n", + "463800K .......... .......... .......... .......... .......... 77% 48.9M 3s\n", + "463850K .......... .......... .......... .......... .......... 78% 54.7M 3s\n", + "463900K .......... .......... .......... .......... .......... 78% 47.0M 3s\n", + "463950K .......... .......... .......... .......... .......... 78% 49.1M 3s\n", + "464000K .......... .......... .......... .......... .......... 78% 57.3M 3s\n", + "464050K .......... .......... .......... .......... .......... 78% 65.3M 3s\n", + "464100K .......... .......... .......... .......... .......... 78% 57.1M 3s\n", + "464150K .......... .......... .......... .......... .......... 78% 50.9M 3s\n", + "464200K .......... .......... .......... .......... .......... 78% 43.3M 3s\n", + "464250K .......... .......... .......... .......... .......... 78% 62.2M 3s\n", + "464300K .......... .......... .......... .......... .......... 78% 68.2M 3s\n", + "464350K .......... .......... .......... .......... .......... 78% 53.5M 3s\n", + "464400K .......... .......... .......... .......... .......... 78% 46.1M 3s\n", + "464450K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", + "464500K .......... .......... .......... .......... .......... 78% 66.4M 3s\n", + "464550K .......... .......... .......... .......... .......... 78% 64.7M 3s\n", + "464600K .......... .......... .......... .......... .......... 78% 48.2M 3s\n", + "464650K .......... .......... .......... .......... .......... 78% 50.0M 3s\n", + "464700K .......... .......... .......... .......... .......... 78% 51.2M 3s\n", + "464750K .......... .......... .......... .......... .......... 78% 69.3M 3s\n", + "464800K .......... .......... .......... .......... .......... 78% 57.2M 3s\n", + "464850K .......... .......... .......... .......... .......... 78% 72.8M 3s\n", + "464900K .......... .......... .......... .......... .......... 78% 56.5M 3s\n", + "464950K .......... .......... .......... .......... .......... 78% 47.8M 3s\n", + "465000K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", + "465050K .......... .......... .......... .......... .......... 78% 66.1M 3s\n", + "465100K .......... .......... .......... .......... .......... 78% 61.9M 3s\n", + "465150K .......... .......... .......... .......... .......... 78% 58.4M 3s\n", + "465200K .......... .......... .......... .......... .......... 78% 47.4M 3s\n", + "465250K .......... .......... .......... .......... .......... 78% 43.4M 3s\n", + "465300K .......... .......... .......... .......... .......... 78% 64.6M 3s\n", + "465350K .......... .......... .......... .......... .......... 78% 66.7M 3s\n", + "465400K .......... .......... .......... .......... .......... 78% 39.1M 3s\n", + "465450K .......... .......... .......... .......... .......... 78% 47.6M 3s\n", + "465500K .......... .......... .......... .......... .......... 78% 59.3M 3s\n", + "465550K .......... .......... .......... .......... .......... 78% 71.1M 3s\n", + "465600K .......... .......... .......... .......... .......... 78% 57.0M 3s\n", + "465650K .......... .......... .......... .......... .......... 78% 57.6M 3s\n", + "465700K .......... .......... .......... .......... .......... 78% 50.2M 3s\n", + "465750K .......... .......... .......... .......... .......... 78% 49.8M 3s\n", + "465800K .......... .......... .......... .......... .......... 78% 60.6M 3s\n", + "465850K .......... .......... .......... .......... .......... 78% 72.0M 3s\n", + "465900K .......... .......... .......... .......... .......... 78% 72.1M 3s\n", + "465950K .......... .......... .......... .......... .......... 78% 53.8M 3s\n", + "466000K .......... .......... .......... .......... .......... 78% 48.6M 3s\n", + "466050K .......... .......... .......... .......... .......... 78% 63.7M 3s\n", + "466100K .......... .......... .......... .......... .......... 78% 68.7M 3s\n", + "466150K .......... .......... .......... .......... .......... 78% 70.8M 3s\n", + "466200K .......... .......... .......... .......... .......... 78% 41.5M 3s\n", + "466250K .......... .......... .......... .......... .......... 78% 43.7M 3s\n", + "466300K .......... .......... .......... .......... .......... 78% 54.0M 3s\n", + "466350K .......... .......... .......... .......... .......... 78% 63.6M 3s\n", + "466400K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", + "466450K .......... .......... .......... .......... .......... 78% 58.6M 3s\n", + "466500K .......... .......... .......... .......... .......... 78% 52.8M 3s\n", + "466550K .......... .......... .......... .......... .......... 78% 52.1M 3s\n", + "466600K .......... .......... .......... .......... .......... 78% 56.0M 3s\n", + "466650K .......... .......... .......... .......... .......... 78% 62.5M 3s\n", + "466700K .......... .......... .......... .......... .......... 78% 55.1M 3s\n", + "466750K .......... .......... .......... .......... .......... 78% 52.3M 3s\n", + "466800K .......... .......... .......... .......... .......... 78% 44.5M 3s\n", + "466850K .......... .......... .......... .......... .......... 78% 73.7M 3s\n", + "466900K .......... .......... .......... .......... .......... 78% 65.8M 3s\n", + "466950K .......... .......... .......... .......... .......... 78% 49.1M 3s\n", + "467000K .......... .......... .......... .......... .......... 78% 39.2M 3s\n", + "467050K .......... .......... .......... .......... .......... 78% 50.1M 3s\n", + "467100K .......... .......... .......... .......... .......... 78% 67.9M 3s\n", + "467150K .......... .......... .......... .......... .......... 78% 65.5M 3s\n", + "467200K .......... .......... .......... .......... .......... 78% 45.4M 3s\n", + "467250K .......... .......... .......... .......... .......... 78% 45.5M 3s\n", + "467300K .......... .......... .......... .......... .......... 78% 60.9M 3s\n", + "467350K .......... .......... .......... .......... .......... 78% 62.8M 3s\n", + "467400K .......... .......... .......... .......... .......... 78% 60.4M 3s\n", + "467450K .......... .......... .......... .......... .......... 78% 56.1M 3s\n", + "467500K .......... .......... .......... .......... .......... 78% 47.3M 3s\n", + "467550K .......... .......... .......... .......... .......... 78% 59.2M 3s\n", + "467600K .......... .......... .......... .......... .......... 78% 60.2M 3s\n", + "467650K .......... .......... .......... .......... .......... 78% 68.3M 3s\n", + "467700K .......... .......... .......... .......... .......... 78% 70.4M 3s\n", + "467750K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", + "467800K .......... .......... .......... .......... .......... 78% 44.2M 3s\n", + "467850K .......... .......... .......... .......... .......... 78% 63.6M 3s\n", + "467900K .......... .......... .......... .......... .......... 78% 66.0M 3s\n", + "467950K .......... .......... .......... .......... .......... 78% 68.9M 3s\n", + "468000K .......... .......... .......... .......... .......... 78% 49.4M 3s\n", + "468050K .......... .......... .......... .......... .......... 78% 52.1M 3s\n", + "468100K .......... .......... .......... .......... .......... 78% 50.3M 3s\n", + "468150K .......... .......... .......... .......... .......... 78% 57.1M 3s\n", + "468200K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", + "468250K .......... .......... .......... .......... .......... 78% 54.0M 3s\n", + "468300K .......... .......... .......... .......... .......... 78% 44.1M 3s\n", + "468350K .......... .......... .......... .......... .......... 78% 61.7M 3s\n", + "468400K .......... .......... .......... .......... .......... 78% 57.7M 3s\n", + "468450K .......... .......... .......... .......... .......... 78% 74.5M 3s\n", + "468500K .......... .......... .......... .......... .......... 78% 56.0M 3s\n", + "468550K .......... .......... .......... .......... .......... 78% 51.5M 3s\n", + "468600K .......... .......... .......... .......... .......... 78% 56.3M 3s\n", + "468650K .......... .......... .......... .......... .......... 78% 78.4M 3s\n", + "468700K .......... .......... .......... .......... .......... 78% 81.2M 3s\n", + "468750K .......... .......... .......... .......... .......... 78% 76.4M 3s\n", + "468800K .......... .......... .......... .......... .......... 78% 51.0M 3s\n", + "468850K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", + "468900K .......... .......... .......... .......... .......... 78% 77.6M 3s\n", + "468950K .......... .......... .......... .......... .......... 78% 80.9M 3s\n", + "469000K .......... .......... .......... .......... .......... 78% 66.6M 3s\n", + "469050K .......... .......... .......... .......... .......... 78% 78.1M 3s\n", + "469100K .......... .......... .......... .......... .......... 78% 53.3M 3s\n", + "469150K .......... .......... .......... .......... .......... 78% 51.0M 3s\n", + "469200K .......... .......... .......... .......... .......... 78% 53.4M 3s\n", + "469250K .......... .......... .......... .......... .......... 78% 70.1M 3s\n", + "469300K .......... .......... .......... .......... .......... 78% 62.3M 3s\n", + "469350K .......... .......... .......... .......... .......... 78% 61.1M 3s\n", + "469400K .......... .......... .......... .......... .......... 78% 39.4M 3s\n", + "469450K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", + "469500K .......... .......... .......... .......... .......... 78% 61.6M 3s\n", + "469550K .......... .......... .......... .......... .......... 78% 64.0M 3s\n", + "469600K .......... .......... .......... .......... .......... 78% 52.2M 3s\n", + "469650K .......... .......... .......... .......... .......... 78% 51.5M 3s\n", + "469700K .......... .......... .......... .......... .......... 78% 51.4M 3s\n", + "469750K .......... .......... .......... .......... .......... 78% 65.3M 3s\n", + "469800K .......... .......... .......... .......... .......... 79% 53.8M 3s\n", + "469850K .......... .......... .......... .......... .......... 79% 56.9M 3s\n", + "469900K .......... .......... .......... .......... .......... 79% 52.2M 3s\n", + "469950K .......... .......... .......... .......... .......... 79% 55.2M 3s\n", + "470000K .......... .......... .......... .......... .......... 79% 62.5M 3s\n", + "470050K .......... .......... .......... .......... .......... 79% 69.2M 3s\n", + "470100K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", + "470150K .......... .......... .......... .......... .......... 79% 56.9M 3s\n", + "470200K .......... .......... .......... .......... .......... 79% 39.5M 3s\n", + "470250K .......... .......... .......... .......... .......... 79% 65.5M 3s\n", + "470300K .......... .......... .......... .......... .......... 79% 63.5M 3s\n", + "470350K .......... .......... .......... .......... .......... 79% 73.1M 3s\n", + "470400K .......... .......... .......... .......... .......... 79% 48.6M 3s\n", + "470450K .......... .......... .......... .......... .......... 79% 51.4M 3s\n", + "470500K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", + "470550K .......... .......... .......... .......... .......... 79% 66.1M 3s\n", + "470600K .......... .......... .......... .......... .......... 79% 57.7M 3s\n", + "470650K .......... .......... .......... .......... .......... 79% 50.1M 3s\n", + "470700K .......... .......... .......... .......... .......... 79% 48.3M 3s\n", + "470750K .......... .......... .......... .......... .......... 79% 56.1M 3s\n", + "470800K .......... .......... .......... .......... .......... 79% 57.8M 3s\n", + "470850K .......... .......... .......... .......... .......... 79% 71.5M 3s\n", + "470900K .......... .......... .......... .......... .......... 79% 60.7M 3s\n", + "470950K .......... .......... .......... .......... .......... 79% 49.3M 3s\n", + "471000K .......... .......... .......... .......... .......... 79% 43.7M 3s\n", + "471050K .......... .......... .......... .......... .......... 79% 64.0M 3s\n", + "471100K .......... .......... .......... .......... .......... 79% 66.8M 3s\n", + "471150K .......... .......... .......... .......... .......... 79% 64.5M 3s\n", + "471200K .......... .......... .......... .......... .......... 79% 61.6M 3s\n", + "471250K .......... .......... .......... .......... .......... 79% 75.5M 3s\n", + "471300K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", + "471350K .......... .......... .......... .......... .......... 79% 68.7M 3s\n", + "471400K .......... .......... .......... .......... .......... 79% 50.1M 3s\n", + "471450K .......... .......... .......... .......... .......... 79% 51.0M 3s\n", + "471500K .......... .......... .......... .......... .......... 79% 53.0M 3s\n", + "471550K .......... .......... .......... .......... .......... 79% 72.7M 3s\n", + "471600K .......... .......... .......... .......... .......... 79% 63.3M 3s\n", + "471650K .......... .......... .......... .......... .......... 79% 67.9M 3s\n", + "471700K .......... .......... .......... .......... .......... 79% 50.0M 3s\n", + "471750K .......... .......... .......... .......... .......... 79% 48.7M 3s\n", + "471800K .......... .......... .......... .......... .......... 79% 38.7M 3s\n", + "471850K .......... .......... .......... .......... .......... 79% 62.3M 3s\n", + "471900K .......... .......... .......... .......... .......... 79% 57.3M 3s\n", + "471950K .......... .......... .......... .......... .......... 79% 63.8M 3s\n", + "472000K .......... .......... .......... .......... .......... 79% 49.1M 3s\n", + "472050K .......... .......... .......... .......... .......... 79% 42.7M 3s\n", + "472100K .......... .......... .......... .......... .......... 79% 67.0M 3s\n", + "472150K .......... .......... .......... .......... .......... 79% 68.1M 3s\n", + "472200K .......... .......... .......... .......... .......... 79% 50.9M 3s\n", + "472250K .......... .......... .......... .......... .......... 79% 53.4M 3s\n", + "472300K .......... .......... .......... .......... .......... 79% 53.2M 3s\n", + "472350K .......... .......... .......... .......... .......... 79% 53.6M 3s\n", + "472400K .......... .......... .......... .......... .......... 79% 60.4M 3s\n", + "472450K .......... .......... .......... .......... .......... 79% 63.0M 3s\n", + "472500K .......... .......... .......... .......... .......... 79% 48.7M 3s\n", + "472550K .......... .......... .......... .......... .......... 79% 3.68M 3s\n", + "472600K .......... .......... .......... .......... .......... 79% 53.7M 3s\n", + "472650K .......... .......... .......... .......... .......... 79% 61.9M 3s\n", + "472700K .......... .......... .......... .......... .......... 79% 66.3M 3s\n", + "472750K .......... .......... .......... .......... .......... 79% 65.4M 3s\n", + "472800K .......... .......... .......... .......... .......... 79% 64.0M 3s\n", + "472850K .......... .......... .......... .......... .......... 79% 76.4M 3s\n", + "472900K .......... .......... .......... .......... .......... 79% 56.7M 3s\n", + "472950K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", + "473000K .......... .......... .......... .......... .......... 79% 55.8M 3s\n", + "473050K .......... .......... .......... .......... .......... 79% 52.8M 3s\n", + "473100K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", + "473150K .......... .......... .......... .......... .......... 79% 50.5M 3s\n", + "473200K .......... .......... .......... .......... .......... 79% 59.2M 3s\n", + "473250K .......... .......... .......... .......... .......... 79% 72.3M 3s\n", + "473300K .......... .......... .......... .......... .......... 79% 61.4M 3s\n", + "473350K .......... .......... .......... .......... .......... 79% 42.1M 3s\n", + "473400K .......... .......... .......... .......... .......... 79% 41.4M 3s\n", + "473450K .......... .......... .......... .......... .......... 79% 58.6M 3s\n", + "473500K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", + "473550K .......... .......... .......... .......... .......... 79% 56.4M 3s\n", + "473600K .......... .......... .......... .......... .......... 79% 41.5M 3s\n", + "473650K .......... .......... .......... .......... .......... 79% 50.4M 3s\n", + "473700K .......... .......... .......... .......... .......... 79% 58.7M 3s\n", + "473750K .......... .......... .......... .......... .......... 79% 5.62M 3s\n", + "473800K .......... .......... .......... .......... .......... 79% 55.6M 3s\n", + "473850K .......... .......... .......... .......... .......... 79% 72.5M 3s\n", + "473900K .......... .......... .......... .......... .......... 79% 67.9M 3s\n", + "473950K .......... .......... .......... .......... .......... 79% 70.3M 3s\n", + "474000K .......... .......... .......... .......... .......... 79% 51.3M 3s\n", + "474050K .......... .......... .......... .......... .......... 79% 65.4M 3s\n", + "474100K .......... .......... .......... .......... .......... 79% 44.3M 3s\n", + "474150K .......... .......... .......... .......... .......... 79% 58.7M 3s\n", + "474200K .......... .......... .......... .......... .......... 79% 56.3M 3s\n", + "474250K .......... .......... .......... .......... .......... 79% 62.3M 3s\n", + "474300K .......... .......... .......... .......... .......... 79% 49.1M 3s\n", + "474350K .......... .......... .......... .......... .......... 79% 54.9M 3s\n", + "474400K .......... .......... .......... .......... .......... 79% 56.2M 3s\n", + "474450K .......... .......... .......... .......... .......... 79% 66.8M 3s\n", + "474500K .......... .......... .......... .......... .......... 79% 71.6M 3s\n", + "474550K .......... .......... .......... .......... .......... 79% 52.3M 3s\n", + "474600K .......... .......... .......... .......... .......... 79% 42.0M 3s\n", + "474650K .......... .......... .......... .......... .......... 79% 56.0M 3s\n", + "474700K .......... .......... .......... .......... .......... 79% 69.6M 3s\n", + "474750K .......... .......... .......... .......... .......... 79% 70.7M 3s\n", + "474800K .......... .......... .......... .......... .......... 79% 55.4M 3s\n", + "474850K .......... .......... .......... .......... .......... 79% 60.7M 3s\n", + "474900K .......... .......... .......... .......... .......... 79% 50.9M 3s\n", + "474950K .......... .......... .......... .......... .......... 79% 57.2M 3s\n", + "475000K .......... .......... .......... .......... .......... 79% 57.5M 3s\n", + "475050K .......... .......... .......... .......... .......... 79% 78.2M 3s\n", + "475100K .......... .......... .......... .......... .......... 79% 60.1M 3s\n", + "475150K .......... .......... .......... .......... .......... 79% 53.1M 3s\n", + "475200K .......... .......... .......... .......... .......... 79% 45.7M 3s\n", + "475250K .......... .......... .......... .......... .......... 79% 62.2M 3s\n", + "475300K .......... .......... .......... .......... .......... 79% 76.7M 3s\n", + "475350K .......... .......... .......... .......... .......... 79% 50.0M 3s\n", + "475400K .......... .......... .......... .......... .......... 79% 47.6M 3s\n", + "475450K .......... .......... .......... .......... .......... 79% 58.6M 3s\n", + "475500K .......... .......... .......... .......... .......... 79% 63.1M 3s\n", + "475550K .......... .......... .......... .......... .......... 79% 67.6M 3s\n", + "475600K .......... .......... .......... .......... .......... 79% 42.2M 3s\n", + "475650K .......... .......... .......... .......... .......... 79% 67.1M 3s\n", + "475700K .......... .......... .......... .......... .......... 79% 55.7M 3s\n", + "475750K .......... .......... .......... .......... .......... 80% 52.7M 3s\n", + "475800K .......... .......... .......... .......... .......... 80% 54.6M 3s\n", + "475850K .......... .......... .......... .......... .......... 80% 62.6M 3s\n", + "475900K .......... .......... .......... .......... .......... 80% 53.7M 3s\n", + "475950K .......... .......... .......... .......... .......... 80% 56.0M 3s\n", + "476000K .......... .......... .......... .......... .......... 80% 50.7M 3s\n", + "476050K .......... .......... .......... .......... .......... 80% 63.5M 3s\n", + "476100K .......... .......... .......... .......... .......... 80% 5.38M 3s\n", + "476150K .......... .......... .......... .......... .......... 80% 4.12M 3s\n", + "476200K .......... .......... .......... .......... .......... 80% 53.6M 3s\n", + "476250K .......... .......... .......... .......... .......... 80% 60.6M 3s\n", + "476300K .......... .......... .......... .......... .......... 80% 70.6M 3s\n", + "476350K .......... .......... .......... .......... .......... 80% 65.1M 3s\n", + "476400K .......... .......... .......... .......... .......... 80% 60.8M 3s\n", + "476450K .......... .......... .......... .......... .......... 80% 56.0M 3s\n", + "476500K .......... .......... .......... .......... .......... 80% 52.9M 3s\n", + "476550K .......... .......... .......... .......... .......... 80% 68.6M 3s\n", + "476600K .......... .......... .......... .......... .......... 80% 55.1M 3s\n", + "476650K .......... .......... .......... .......... .......... 80% 50.8M 3s\n", + "476700K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", + "476750K .......... .......... .......... .......... .......... 80% 49.4M 3s\n", + "476800K .......... .......... .......... .......... .......... 80% 47.3M 3s\n", + "476850K .......... .......... .......... .......... .......... 80% 70.4M 3s\n", + "476900K .......... .......... .......... .......... .......... 80% 48.3M 3s\n", + "476950K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", + "477000K .......... .......... .......... .......... .......... 80% 44.8M 3s\n", + "477050K .......... .......... .......... .......... .......... 80% 69.1M 3s\n", + "477100K .......... .......... .......... .......... .......... 80% 65.9M 3s\n", + "477150K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", + "477200K .......... .......... .......... .......... .......... 80% 38.2M 3s\n", + "477250K .......... .......... .......... .......... .......... 80% 60.4M 3s\n", + "477300K .......... .......... .......... .......... .......... 80% 64.1M 3s\n", + "477350K .......... .......... .......... .......... .......... 80% 66.2M 3s\n", + "477400K .......... .......... .......... .......... .......... 80% 39.6M 3s\n", + "477450K .......... .......... .......... .......... .......... 80% 42.9M 3s\n", + "477500K .......... .......... .......... .......... .......... 80% 51.6M 3s\n", + "477550K .......... .......... .......... .......... .......... 80% 67.0M 3s\n", + "477600K .......... .......... .......... .......... .......... 80% 60.0M 3s\n", + "477650K .......... .......... .......... .......... .......... 80% 53.8M 3s\n", + "477700K .......... .......... .......... .......... .......... 80% 45.7M 3s\n", + "477750K .......... .......... .......... .......... .......... 80% 60.4M 3s\n", + "477800K .......... .......... .......... .......... .......... 80% 52.5M 3s\n", + "477850K .......... .......... .......... .......... .......... 80% 68.8M 3s\n", + "477900K .......... .......... .......... .......... .......... 80% 62.0M 3s\n", + "477950K .......... .......... .......... .......... .......... 80% 47.6M 3s\n", + "478000K .......... .......... .......... .......... .......... 80% 42.4M 3s\n", + "478050K .......... .......... .......... .......... .......... 80% 61.0M 3s\n", + "478100K .......... .......... .......... .......... .......... 80% 62.5M 3s\n", + "478150K .......... .......... .......... .......... .......... 80% 63.9M 3s\n", + "478200K .......... .......... .......... .......... .......... 80% 50.6M 3s\n", + "478250K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", + "478300K .......... .......... .......... .......... .......... 80% 60.9M 3s\n", + "478350K .......... .......... .......... .......... .......... 80% 71.4M 3s\n", + "478400K .......... .......... .......... .......... .......... 80% 58.0M 3s\n", + "478450K .......... .......... .......... .......... .......... 80% 58.7M 3s\n", + "478500K .......... .......... .......... .......... .......... 80% 58.6M 3s\n", + "478550K .......... .......... .......... .......... .......... 80% 53.6M 3s\n", + "478600K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", + "478650K .......... .......... .......... .......... .......... 80% 71.7M 3s\n", + "478700K .......... .......... .......... .......... .......... 80% 45.0M 3s\n", + "478750K .......... .......... .......... .......... .......... 80% 55.4M 3s\n", + "478800K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", + "478850K .......... .......... .......... .......... .......... 80% 68.3M 3s\n", + "478900K .......... .......... .......... .......... .......... 80% 56.2M 3s\n", + "478950K .......... .......... .......... .......... .......... 80% 61.1M 3s\n", + "479000K .......... .......... .......... .......... .......... 80% 36.7M 3s\n", + "479050K .......... .......... .......... .......... .......... 80% 56.9M 3s\n", + "479100K .......... .......... .......... .......... .......... 80% 66.7M 3s\n", + "479150K .......... .......... .......... .......... .......... 80% 51.0M 3s\n", + "479200K .......... .......... .......... .......... .......... 80% 46.8M 3s\n", + "479250K .......... .......... .......... .......... .......... 80% 70.4M 3s\n", + "479300K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", + "479350K .......... .......... .......... .......... .......... 80% 66.9M 3s\n", + "479400K .......... .......... .......... .......... .......... 80% 52.3M 3s\n", + "479450K .......... .......... .......... .......... .......... 80% 41.5M 3s\n", + "479500K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", + "479550K .......... .......... .......... .......... .......... 80% 46.2M 3s\n", + "479600K .......... .......... .......... .......... .......... 80% 52.3M 3s\n", + "479650K .......... .......... .......... .......... .......... 80% 57.9M 3s\n", + "479700K .......... .......... .......... .......... .......... 80% 59.9M 3s\n", + "479750K .......... .......... .......... .......... .......... 80% 59.0M 3s\n", + "479800K .......... .......... .......... .......... .......... 80% 47.0M 3s\n", + "479850K .......... .......... .......... .......... .......... 80% 68.7M 3s\n", + "479900K .......... .......... .......... .......... .......... 80% 54.8M 3s\n", + "479950K .......... .......... .......... .......... .......... 80% 56.5M 3s\n", + "480000K .......... .......... .......... .......... .......... 80% 48.4M 3s\n", + "480050K .......... .......... .......... .......... .......... 80% 46.1M 3s\n", + "480100K .......... .......... .......... .......... .......... 80% 49.0M 3s\n", + "480150K .......... .......... .......... .......... .......... 80% 3.88M 3s\n", + "480200K .......... .......... .......... .......... .......... 80% 55.3M 3s\n", + "480250K .......... .......... .......... .......... .......... 80% 68.8M 3s\n", + "480300K .......... .......... .......... .......... .......... 80% 60.3M 3s\n", + "480350K .......... .......... .......... .......... .......... 80% 64.8M 3s\n", + "480400K .......... .......... .......... .......... .......... 80% 60.6M 3s\n", + "480450K .......... .......... .......... .......... .......... 80% 61.2M 3s\n", + "480500K .......... .......... .......... .......... .......... 80% 46.8M 3s\n", + "480550K .......... .......... .......... .......... .......... 80% 59.1M 3s\n", + "480600K .......... .......... .......... .......... .......... 80% 51.6M 3s\n", + "480650K .......... .......... .......... .......... .......... 80% 64.9M 3s\n", + "480700K .......... .......... .......... .......... .......... 80% 8.64M 3s\n", + "480750K .......... .......... .......... .......... .......... 80% 55.7M 3s\n", + "480800K .......... .......... .......... .......... .......... 80% 53.4M 3s\n", + "480850K .......... .......... .......... .......... .......... 80% 59.5M 3s\n", + "480900K .......... .......... .......... .......... .......... 80% 60.2M 3s\n", + "480950K .......... .......... .......... .......... .......... 80% 55.2M 3s\n", + "481000K .......... .......... .......... .......... .......... 80% 48.4M 3s\n", + "481050K .......... .......... .......... .......... .......... 80% 54.9M 3s\n", + "481100K .......... .......... .......... .......... .......... 80% 51.4M 3s\n", + "481150K .......... .......... .......... .......... .......... 80% 44.9M 3s\n", + "481200K .......... .......... .......... .......... .......... 80% 59.3M 3s\n", + "481250K .......... .......... .......... .......... .......... 80% 63.4M 3s\n", + "481300K .......... .......... .......... .......... .......... 80% 44.7M 3s\n", + "481350K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", + "481400K .......... .......... .......... .......... .......... 80% 45.8M 3s\n", + "481450K .......... .......... .......... .......... .......... 80% 49.8M 3s\n", + "481500K .......... .......... .......... .......... .......... 80% 3.82M 3s\n", + "481550K .......... .......... .......... .......... .......... 80% 5.11M 3s\n", + "481600K .......... .......... .......... .......... .......... 80% 59.7M 3s\n", + "481650K .......... .......... .......... .......... .......... 80% 64.9M 3s\n", + "481700K .......... .......... .......... .......... .......... 81% 66.9M 3s\n", + "481750K .......... .......... .......... .......... .......... 81% 64.3M 3s\n", + "481800K .......... .......... .......... .......... .......... 81% 56.5M 3s\n", + "481850K .......... .......... .......... .......... .......... 81% 44.7M 3s\n", + "481900K .......... .......... .......... .......... .......... 81% 65.6M 3s\n", + "481950K .......... .......... .......... .......... .......... 81% 58.3M 3s\n", + "482000K .......... .......... .......... .......... .......... 81% 56.4M 3s\n", + "482050K .......... .......... .......... .......... .......... 81% 72.9M 3s\n", + "482100K .......... .......... .......... .......... .......... 81% 63.5M 3s\n", + "482150K .......... .......... .......... .......... .......... 81% 46.2M 3s\n", + "482200K .......... .......... .......... .......... .......... 81% 48.6M 3s\n", + "482250K .......... .......... .......... .......... .......... 81% 65.1M 3s\n", + "482300K .......... .......... .......... .......... .......... 81% 58.2M 3s\n", + "482350K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", + "482400K .......... .......... .......... .......... .......... 81% 53.9M 3s\n", + "482450K .......... .......... .......... .......... .......... 81% 49.0M 3s\n", + "482500K .......... .......... .......... .......... .......... 81% 70.1M 3s\n", + "482550K .......... .......... .......... .......... .......... 81% 67.9M 3s\n", + "482600K .......... .......... .......... .......... .......... 81% 49.8M 3s\n", + "482650K .......... .......... .......... .......... .......... 81% 60.6M 3s\n", + "482700K .......... .......... .......... .......... .......... 81% 61.6M 3s\n", + "482750K .......... .......... .......... .......... .......... 81% 57.1M 3s\n", + "482800K .......... .......... .......... .......... .......... 81% 63.3M 3s\n", + "482850K .......... .......... .......... .......... .......... 81% 67.4M 3s\n", + "482900K .......... .......... .......... .......... .......... 81% 69.8M 3s\n", + "482950K .......... .......... .......... .......... .......... 81% 52.2M 3s\n", + "483000K .......... .......... .......... .......... .......... 81% 34.3M 3s\n", + "483050K .......... .......... .......... .......... .......... 81% 62.1M 3s\n", + "483100K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", + "483150K .......... .......... .......... .......... .......... 81% 56.6M 3s\n", + "483200K .......... .......... .......... .......... .......... 81% 49.5M 3s\n", + "483250K .......... .......... .......... .......... .......... 81% 52.5M 3s\n", + "483300K .......... .......... .......... .......... .......... 81% 53.4M 3s\n", + "483350K .......... .......... .......... .......... .......... 81% 65.6M 3s\n", + "483400K .......... .......... .......... .......... .......... 81% 50.4M 3s\n", + "483450K .......... .......... .......... .......... .......... 81% 55.2M 3s\n", + "483500K .......... .......... .......... .......... .......... 81% 57.1M 3s\n", + "483550K .......... .......... .......... .......... .......... 81% 47.5M 3s\n", + "483600K .......... .......... .......... .......... .......... 81% 59.2M 3s\n", + "483650K .......... .......... .......... .......... .......... 81% 60.7M 3s\n", + "483700K .......... .......... .......... .......... .......... 81% 46.2M 3s\n", + "483750K .......... .......... .......... .......... .......... 81% 62.2M 3s\n", + "483800K .......... .......... .......... .......... .......... 81% 39.9M 3s\n", + "483850K .......... .......... .......... .......... .......... 81% 57.9M 3s\n", + "483900K .......... .......... .......... .......... .......... 81% 59.1M 3s\n", + "483950K .......... .......... .......... .......... .......... 81% 47.6M 3s\n", + "484000K .......... .......... .......... .......... .......... 81% 52.7M 3s\n", + "484050K .......... .......... .......... .......... .......... 81% 51.7M 3s\n", + "484100K .......... .......... .......... .......... .......... 81% 52.5M 3s\n", + "484150K .......... .......... .......... .......... .......... 81% 71.8M 3s\n", + "484200K .......... .......... .......... .......... .......... 81% 50.5M 3s\n", + "484250K .......... .......... .......... .......... .......... 81% 59.9M 3s\n", + "484300K .......... .......... .......... .......... .......... 81% 50.8M 3s\n", + "484350K .......... .......... .......... .......... .......... 81% 62.0M 3s\n", + "484400K .......... .......... .......... .......... .......... 81% 56.1M 3s\n", + "484450K .......... .......... .......... .......... .......... 81% 55.4M 3s\n", + "484500K .......... .......... .......... .......... .......... 81% 55.1M 3s\n", + "484550K .......... .......... .......... .......... .......... 81% 52.7M 3s\n", + "484600K .......... .......... .......... .......... .......... 81% 37.6M 3s\n", + "484650K .......... .......... .......... .......... .......... 81% 46.0M 3s\n", + "484700K .......... .......... .......... .......... .......... 81% 3.92M 3s\n", + "484750K .......... .......... .......... .......... .......... 81% 67.8M 3s\n", + "484800K .......... .......... .......... .......... .......... 81% 50.8M 3s\n", + "484850K .......... .......... .......... .......... .......... 81% 62.0M 3s\n", + "484900K .......... .......... .......... .......... .......... 81% 55.6M 3s\n", + "484950K .......... .......... .......... .......... .......... 81% 67.5M 3s\n", + "485000K .......... .......... .......... .......... .......... 81% 36.4M 3s\n", + "485050K .......... .......... .......... .......... .......... 81% 53.6M 3s\n", + "485100K .......... .......... .......... .......... .......... 81% 67.9M 3s\n", + "485150K .......... .......... .......... .......... .......... 81% 67.0M 3s\n", + "485200K .......... .......... .......... .......... .......... 81% 56.6M 3s\n", + "485250K .......... .......... .......... .......... .......... 81% 55.6M 3s\n", + "485300K .......... .......... .......... .......... .......... 81% 35.0M 3s\n", + "485350K .......... .......... .......... .......... .......... 81% 64.1M 3s\n", + "485400K .......... .......... .......... .......... .......... 81% 58.8M 3s\n", + "485450K .......... .......... .......... .......... .......... 81% 66.2M 3s\n", + "485500K .......... .......... .......... .......... .......... 81% 50.2M 3s\n", + "485550K .......... .......... .......... .......... .......... 81% 51.3M 3s\n", + "485600K .......... .......... .......... .......... .......... 81% 51.6M 3s\n", + "485650K .......... .......... .......... .......... .......... 81% 73.0M 3s\n", + "485700K .......... .......... .......... .......... .......... 81% 73.6M 3s\n", + "485750K .......... .......... .......... .......... .......... 81% 74.2M 3s\n", + "485800K .......... .......... .......... .......... .......... 81% 47.0M 3s\n", + "485850K .......... .......... .......... .......... .......... 81% 48.3M 3s\n", + "485900K .......... .......... .......... .......... .......... 81% 70.8M 3s\n", + "485950K .......... .......... .......... .......... .......... 81% 62.9M 3s\n", + "486000K .......... .......... .......... .......... .......... 81% 59.2M 3s\n", + "486050K .......... .......... .......... .......... .......... 81% 58.2M 3s\n", + "486100K .......... .......... .......... .......... .......... 81% 50.2M 3s\n", + "486150K .......... .......... .......... .......... .......... 81% 3.46M 3s\n", + "486200K .......... .......... .......... .......... .......... 81% 58.3M 3s\n", + "486250K .......... .......... .......... .......... .......... 81% 62.3M 3s\n", + "486300K .......... .......... .......... .......... .......... 81% 55.7M 3s\n", + "486350K .......... .......... .......... .......... .......... 81% 67.0M 3s\n", + "486400K .......... .......... .......... .......... .......... 81% 8.46M 3s\n", + "486450K .......... .......... .......... .......... .......... 81% 56.7M 3s\n", + "486500K .......... .......... .......... .......... .......... 81% 69.6M 3s\n", + "486550K .......... .......... .......... .......... .......... 81% 70.0M 3s\n", + "486600K .......... .......... .......... .......... .......... 81% 52.9M 3s\n", + "486650K .......... .......... .......... .......... .......... 81% 71.6M 3s\n", + "486700K .......... .......... .......... .......... .......... 81% 64.1M 3s\n", + "486750K .......... .......... .......... .......... .......... 81% 47.6M 3s\n", + "486800K .......... .......... .......... .......... .......... 81% 62.3M 3s\n", + "486850K .......... .......... .......... .......... .......... 81% 74.1M 3s\n", + "486900K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", + "486950K .......... .......... .......... .......... .......... 81% 67.1M 3s\n", + "487000K .......... .......... .......... .......... .......... 81% 36.3M 3s\n", + "487050K .......... .......... .......... .......... .......... 81% 55.4M 3s\n", + "487100K .......... .......... .......... .......... .......... 81% 69.9M 3s\n", + "487150K .......... .......... .......... .......... .......... 81% 26.9M 3s\n", + "487200K .......... .......... .......... .......... .......... 81% 30.6M 3s\n", + "487250K .......... .......... .......... .......... .......... 81% 58.8M 3s\n", + "487300K .......... .......... .......... .......... .......... 81% 75.8M 3s\n", + "487350K .......... .......... .......... .......... .......... 81% 23.0M 3s\n", + "487400K .......... .......... .......... .......... .......... 81% 44.1M 3s\n", + "487450K .......... .......... .......... .......... .......... 81% 71.6M 3s\n", + "487500K .......... .......... .......... .......... .......... 81% 24.2M 3s\n", + "487550K .......... .......... .......... .......... .......... 81% 33.4M 3s\n", + "487600K .......... .......... .......... .......... .......... 81% 41.7M 3s\n", + "487650K .......... .......... .......... .......... .......... 82% 69.8M 3s\n", + "487700K .......... .......... .......... .......... .......... 82% 22.3M 3s\n", + "487750K .......... .......... .......... .......... .......... 82% 31.0M 3s\n", + "487800K .......... .......... .......... .......... .......... 82% 31.9M 3s\n", + "487850K .......... .......... .......... .......... .......... 82% 53.3M 3s\n", + "487900K .......... .......... .......... .......... .......... 82% 47.0M 3s\n", + "487950K .......... .......... .......... .......... .......... 82% 41.2M 3s\n", + "488000K .......... .......... .......... .......... .......... 82% 66.3M 3s\n", + "488050K .......... .......... .......... .......... .......... 82% 5.08M 3s\n", + "488100K .......... .......... .......... .......... .......... 82% 63.1M 3s\n", + "488150K .......... .......... .......... .......... .......... 82% 50.6M 3s\n", + "488200K .......... .......... .......... .......... .......... 82% 32.5M 3s\n", + "488250K .......... .......... .......... .......... .......... 82% 13.5M 3s\n", + "488300K .......... .......... .......... .......... .......... 82% 49.7M 3s\n", + "488350K .......... .......... .......... .......... .......... 82% 32.7M 3s\n", + "488400K .......... .......... .......... .......... .......... 82% 42.8M 3s\n", + "488450K .......... .......... .......... .......... .......... 82% 52.8M 3s\n", + "488500K .......... .......... .......... .......... .......... 82% 23.5M 3s\n", + "488550K .......... .......... .......... .......... .......... 82% 33.3M 3s\n", + "488600K .......... .......... .......... .......... .......... 82% 24.9M 3s\n", + "488650K .......... .......... .......... .......... .......... 82% 22.4M 3s\n", + "488700K .......... .......... .......... .......... .......... 82% 48.5M 3s\n", + "488750K .......... .......... .......... .......... .......... 82% 17.1M 3s\n", + "488800K .......... .......... .......... .......... .......... 82% 38.3M 3s\n", + "488850K .......... .......... .......... .......... .......... 82% 28.7M 3s\n", + "488900K .......... .......... .......... .......... .......... 82% 23.9M 3s\n", + "488950K .......... .......... .......... .......... .......... 82% 47.2M 3s\n", + "489000K .......... .......... .......... .......... .......... 82% 16.4M 3s\n", + "489050K .......... .......... .......... .......... .......... 82% 34.6M 3s\n", + "489100K .......... .......... .......... .......... .......... 82% 18.4M 3s\n", + "489150K .......... .......... .......... .......... .......... 82% 47.7M 3s\n", + "489200K .......... .......... .......... .......... .......... 82% 31.5M 3s\n", + "489250K .......... .......... .......... .......... .......... 82% 17.9M 3s\n", + "489300K .......... .......... .......... .......... .......... 82% 50.7M 3s\n", + "489350K .......... .......... .......... .......... .......... 82% 15.2M 3s\n", + "489400K .......... .......... .......... .......... .......... 82% 32.3M 3s\n", + "489450K .......... .......... .......... .......... .......... 82% 35.7M 3s\n", + "489500K .......... .......... .......... .......... .......... 82% 19.4M 3s\n", + "489550K .......... .......... .......... .......... .......... 82% 46.4M 3s\n", + "489600K .......... .......... .......... .......... .......... 82% 16.8M 3s\n", + "489650K .......... .......... .......... .......... .......... 82% 47.8M 3s\n", + "489700K .......... .......... .......... .......... .......... 82% 30.8M 3s\n", + "489750K .......... .......... .......... .......... .......... 82% 20.3M 3s\n", + "489800K .......... .......... .......... .......... .......... 82% 41.8M 3s\n", + "489850K .......... .......... .......... .......... .......... 82% 14.7M 3s\n", + "489900K .......... .......... .......... .......... .......... 82% 34.7M 3s\n", + "489950K .......... .......... .......... .......... .......... 82% 38.8M 3s\n", + "490000K .......... .......... .......... .......... .......... 82% 20.7M 3s\n", + "490050K .......... .......... .......... .......... .......... 82% 31.8M 3s\n", + "490100K .......... .......... .......... .......... .......... 82% 20.4M 3s\n", + "490150K .......... .......... .......... .......... .......... 82% 23.4M 3s\n", + "490200K .......... .......... .......... .......... .......... 82% 25.3M 3s\n", + "490250K .......... .......... .......... .......... .......... 82% 34.7M 3s\n", + "490300K .......... .......... .......... .......... .......... 82% 40.5M 3s\n", + "490350K .......... .......... .......... .......... .......... 82% 16.1M 3s\n", + "490400K .......... .......... .......... .......... .......... 82% 30.1M 3s\n", + "490450K .......... .......... .......... .......... .......... 82% 12.2M 3s\n", + "490500K .......... .......... .......... .......... .......... 82% 24.9M 3s\n", + "490550K .......... .......... .......... .......... .......... 82% 59.0M 3s\n", + "490600K .......... .......... .......... .......... .......... 82% 13.7M 3s\n", + "490650K .......... .......... .......... .......... .......... 82% 53.8M 3s\n", + "490700K .......... .......... .......... .......... .......... 82% 27.3M 3s\n", + "490750K .......... .......... .......... .......... .......... 82% 21.6M 3s\n", + "490800K .......... .......... .......... .......... .......... 82% 59.0M 3s\n", + "490850K .......... .......... .......... .......... .......... 82% 16.3M 3s\n", + "490900K .......... .......... .......... .......... .......... 82% 43.1M 3s\n", + "490950K .......... .......... .......... .......... .......... 82% 23.9M 3s\n", + "491000K .......... .......... .......... .......... .......... 82% 24.5M 3s\n", + "491050K .......... .......... .......... .......... .......... 82% 69.0M 3s\n", + "491100K .......... .......... .......... .......... .......... 82% 15.7M 3s\n", + "491150K .......... .......... .......... .......... .......... 82% 55.9M 3s\n", + "491200K .......... .......... .......... .......... .......... 82% 19.5M 3s\n", + "491250K .......... .......... .......... .......... .......... 82% 25.4M 3s\n", + "491300K .......... .......... .......... .......... .......... 82% 66.1M 3s\n", + "491350K .......... .......... .......... .......... .......... 82% 14.8M 3s\n", + "491400K .......... .......... .......... .......... .......... 82% 44.0M 3s\n", + "491450K .......... .......... .......... .......... .......... 82% 5.43M 3s\n", + "491500K .......... .......... .......... .......... .......... 82% 60.2M 3s\n", + "491550K .......... .......... .......... .......... .......... 82% 70.1M 3s\n", + "491600K .......... .......... .......... .......... .......... 82% 13.7M 3s\n", + "491650K .......... .......... .......... .......... .......... 82% 57.9M 3s\n", + "491700K .......... .......... .......... .......... .......... 82% 59.5M 3s\n", + "491750K .......... .......... .......... .......... .......... 82% 16.2M 3s\n", + "491800K .......... .......... .......... .......... .......... 82% 44.2M 3s\n", + "491850K .......... .......... .......... .......... .......... 82% 15.4M 3s\n", + "491900K .......... .......... .......... .......... .......... 82% 51.5M 3s\n", + "491950K .......... .......... .......... .......... .......... 82% 17.0M 3s\n", + "492000K .......... .......... .......... .......... .......... 82% 44.1M 3s\n", + "492050K .......... .......... .......... .......... .......... 82% 62.3M 3s\n", + "492100K .......... .......... .......... .......... .......... 82% 16.3M 3s\n", + "492150K .......... .......... .......... .......... .......... 82% 46.6M 3s\n", + "492200K .......... .......... .......... .......... .......... 82% 16.6M 3s\n", + "492250K .......... .......... .......... .......... .......... 82% 41.2M 3s\n", + "492300K .......... .......... .......... .......... .......... 82% 54.6M 3s\n", + "492350K .......... .......... .......... .......... .......... 82% 20.1M 3s\n", + "492400K .......... .......... .......... .......... .......... 82% 41.7M 3s\n", + "492450K .......... .......... .......... .......... .......... 82% 53.9M 3s\n", + "492500K .......... .......... .......... .......... .......... 82% 17.5M 3s\n", + "492550K .......... .......... .......... .......... .......... 82% 43.6M 3s\n", + "492600K .......... .......... .......... .......... .......... 82% 17.3M 3s\n", + "492650K .......... .......... .......... .......... .......... 82% 39.0M 3s\n", + "492700K .......... .......... .......... .......... .......... 82% 53.8M 3s\n", + "492750K .......... .......... .......... .......... .......... 82% 18.6M 3s\n", + "492800K .......... .......... .......... .......... .......... 82% 53.0M 3s\n", + "492850K .......... .......... .......... .......... .......... 82% 53.4M 3s\n", + "492900K .......... .......... .......... .......... .......... 82% 17.4M 3s\n", + "492950K .......... .......... .......... .......... .......... 82% 56.4M 3s\n", + "493000K .......... .......... .......... .......... .......... 82% 15.3M 3s\n", + "493050K .......... .......... .......... .......... .......... 82% 43.9M 3s\n", + "493100K .......... .......... .......... .......... .......... 82% 52.0M 3s\n", + "493150K .......... .......... .......... .......... .......... 82% 18.2M 3s\n", + "493200K .......... .......... .......... .......... .......... 82% 47.3M 3s\n", + "493250K .......... .......... .......... .......... .......... 82% 58.8M 3s\n", + "493300K .......... .......... .......... .......... .......... 82% 18.1M 3s\n", + "493350K .......... .......... .......... .......... .......... 82% 37.9M 3s\n", + "493400K .......... .......... .......... .......... .......... 82% 3.78M 3s\n", + "493450K .......... .......... .......... .......... .......... 82% 72.5M 3s\n", + "493500K .......... .......... .......... .......... .......... 82% 84.1M 3s\n", + "493550K .......... .......... .......... .......... .......... 82% 13.5M 3s\n", + "493600K .......... .......... .......... .......... .......... 83% 49.2M 3s\n", + "493650K .......... .......... .......... .......... .......... 83% 64.1M 3s\n", + "493700K .......... .......... .......... .......... .......... 83% 18.1M 3s\n", + "493750K .......... .......... .......... .......... .......... 83% 42.2M 3s\n", + "493800K .......... .......... .......... .......... .......... 83% 5.10M 3s\n", + "493850K .......... .......... .......... .......... .......... 83% 52.6M 3s\n", + "493900K .......... .......... .......... .......... .......... 83% 68.6M 3s\n", + "493950K .......... .......... .......... .......... .......... 83% 64.5M 3s\n", + "494000K .......... .......... .......... .......... .......... 83% 18.1M 3s\n", + "494050K .......... .......... .......... .......... .......... 83% 55.7M 3s\n", + "494100K .......... .......... .......... .......... .......... 83% 66.6M 3s\n", + "494150K .......... .......... .......... .......... .......... 83% 17.6M 3s\n", + "494200K .......... .......... .......... .......... .......... 83% 46.5M 3s\n", + "494250K .......... .......... .......... .......... .......... 83% 71.6M 3s\n", + "494300K .......... .......... .......... .......... .......... 83% 16.4M 3s\n", + "494350K .......... .......... .......... .......... .......... 83% 53.0M 3s\n", + "494400K .......... .......... .......... .......... .......... 83% 59.7M 3s\n", + "494450K .......... .......... .......... .......... .......... 83% 16.8M 3s\n", + "494500K .......... .......... .......... .......... .......... 83% 55.2M 3s\n", + "494550K .......... .......... .......... .......... .......... 83% 68.6M 3s\n", + "494600K .......... .......... .......... .......... .......... 83% 15.1M 3s\n", + "494650K .......... .......... .......... .......... .......... 83% 49.6M 3s\n", + "494700K .......... .......... .......... .......... .......... 83% 17.9M 3s\n", + "494750K .......... .......... .......... .......... .......... 83% 58.7M 3s\n", + "494800K .......... .......... .......... .......... .......... 83% 55.5M 3s\n", + "494850K .......... .......... .......... .......... .......... 83% 15.9M 3s\n", + "494900K .......... .......... .......... .......... .......... 83% 47.8M 3s\n", + "494950K .......... .......... .......... .......... .......... 83% 60.4M 3s\n", + "495000K .......... .......... .......... .......... .......... 83% 17.0M 3s\n", + "495050K .......... .......... .......... .......... .......... 83% 43.8M 3s\n", + "495100K .......... .......... .......... .......... .......... 83% 57.4M 3s\n", + "495150K .......... .......... .......... .......... .......... 83% 20.5M 3s\n", + "495200K .......... .......... .......... .......... .......... 83% 38.8M 3s\n", + "495250K .......... .......... .......... .......... .......... 83% 52.0M 3s\n", + "495300K .......... .......... .......... .......... .......... 83% 19.8M 3s\n", + "495350K .......... .......... .......... .......... .......... 83% 51.9M 3s\n", + "495400K .......... .......... .......... .......... .......... 83% 44.3M 3s\n", + "495450K .......... .......... .......... .......... .......... 83% 19.2M 3s\n", + "495500K .......... .......... .......... .......... .......... 83% 39.8M 3s\n", + "495550K .......... .......... .......... .......... .......... 83% 57.0M 3s\n", + "495600K .......... .......... .......... .......... .......... 83% 17.7M 3s\n", + "495650K .......... .......... .......... .......... .......... 83% 45.6M 3s\n", + "495700K .......... .......... .......... .......... .......... 83% 48.0M 3s\n", + "495750K .......... .......... .......... .......... .......... 83% 62.2M 3s\n", + "495800K .......... .......... .......... .......... .......... 83% 17.0M 3s\n", + "495850K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", + "495900K .......... .......... .......... .......... .......... 83% 18.9M 3s\n", + "495950K .......... .......... .......... .......... .......... 83% 38.1M 3s\n", + "496000K .......... .......... .......... .......... .......... 83% 56.4M 3s\n", + "496050K .......... .......... .......... .......... .......... 83% 61.6M 3s\n", + "496100K .......... .......... .......... .......... .......... 83% 17.8M 3s\n", + "496150K .......... .......... .......... .......... .......... 83% 59.8M 3s\n", + "496200K .......... .......... .......... .......... .......... 83% 18.0M 3s\n", + "496250K .......... .......... .......... .......... .......... 83% 45.9M 3s\n", + "496300K .......... .......... .......... .......... .......... 83% 59.8M 3s\n", + "496350K .......... .......... .......... .......... .......... 83% 66.2M 3s\n", + "496400K .......... .......... .......... .......... .......... 83% 18.5M 3s\n", + "496450K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", + "496500K .......... .......... .......... .......... .......... 83% 56.6M 3s\n", + "496550K .......... .......... .......... .......... .......... 83% 18.5M 3s\n", + "496600K .......... .......... .......... .......... .......... 83% 41.6M 3s\n", + "496650K .......... .......... .......... .......... .......... 83% 66.4M 3s\n", + "496700K .......... .......... .......... .......... .......... 83% 17.5M 3s\n", + "496750K .......... .......... .......... .......... .......... 83% 56.6M 3s\n", + "496800K .......... .......... .......... .......... .......... 83% 53.1M 3s\n", + "496850K .......... .......... .......... .......... .......... 83% 15.9M 3s\n", + "496900K .......... .......... .......... .......... .......... 83% 43.6M 3s\n", + "496950K .......... .......... .......... .......... .......... 83% 61.1M 3s\n", + "497000K .......... .......... .......... .......... .......... 83% 17.6M 3s\n", + "497050K .......... .......... .......... .......... .......... 83% 52.1M 3s\n", + "497100K .......... .......... .......... .......... .......... 83% 66.7M 3s\n", + "497150K .......... .......... .......... .......... .......... 83% 19.8M 3s\n", + "497200K .......... .......... .......... .......... .......... 83% 41.9M 3s\n", + "497250K .......... .......... .......... .......... .......... 83% 55.1M 3s\n", + "497300K .......... .......... .......... .......... .......... 83% 61.2M 3s\n", + "497350K .......... .......... .......... .......... .......... 83% 19.4M 3s\n", + "497400K .......... .......... .......... .......... .......... 83% 39.6M 3s\n", + "497450K .......... .......... .......... .......... .......... 83% 63.5M 3s\n", + "497500K .......... .......... .......... .......... .......... 83% 16.8M 3s\n", + "497550K .......... .......... .......... .......... .......... 83% 59.2M 3s\n", + "497600K .......... .......... .......... .......... .......... 83% 60.0M 3s\n", + "497650K .......... .......... .......... .......... .......... 83% 23.7M 3s\n", + "497700K .......... .......... .......... .......... .......... 83% 47.6M 3s\n", + "497750K .......... .......... .......... .......... .......... 83% 57.5M 3s\n", + "497800K .......... .......... .......... .......... .......... 83% 19.9M 3s\n", + "497850K .......... .......... .......... .......... .......... 83% 44.1M 3s\n", + "497900K .......... .......... .......... .......... .......... 83% 56.0M 3s\n", + "497950K .......... .......... .......... .......... .......... 83% 65.9M 2s\n", + "498000K .......... .......... .......... .......... .......... 83% 19.5M 2s\n", + "498050K .......... .......... .......... .......... .......... 83% 45.7M 2s\n", + "498100K .......... .......... .......... .......... .......... 83% 68.0M 2s\n", + "498150K .......... .......... .......... .......... .......... 83% 22.6M 2s\n", + "498200K .......... .......... .......... .......... .......... 83% 37.4M 2s\n", + "498250K .......... .......... .......... .......... .......... 83% 62.0M 2s\n", + "498300K .......... .......... .......... .......... .......... 83% 22.4M 2s\n", + "498350K .......... .......... .......... .......... .......... 83% 40.6M 2s\n", + "498400K .......... .......... .......... .......... .......... 83% 48.0M 2s\n", + "498450K .......... .......... .......... .......... .......... 83% 62.6M 2s\n", + "498500K .......... .......... .......... .......... .......... 83% 21.0M 2s\n", + "498550K .......... .......... .......... .......... .......... 83% 48.9M 2s\n", + "498600K .......... .......... .......... .......... .......... 83% 61.5M 2s\n", + "498650K .......... .......... .......... .......... .......... 83% 22.0M 2s\n", + "498700K .......... .......... .......... .......... .......... 83% 32.8M 2s\n", + "498750K .......... .......... .......... .......... .......... 83% 54.3M 2s\n", + "498800K .......... .......... .......... .......... .......... 83% 24.0M 2s\n", + "498850K .......... .......... .......... .......... .......... 83% 54.4M 2s\n", + "498900K .......... .......... .......... .......... .......... 83% 4.16M 2s\n", + "498950K .......... .......... .......... .......... .......... 83% 71.0M 2s\n", + "499000K .......... .......... .......... .......... .......... 83% 63.2M 2s\n", + "499050K .......... .......... .......... .......... .......... 83% 17.5M 2s\n", + "499100K .......... .......... .......... .......... .......... 83% 42.7M 2s\n", + "499150K .......... .......... .......... .......... .......... 83% 63.1M 2s\n", + "499200K .......... .......... .......... .......... .......... 83% 4.45M 2s\n", + "499250K .......... .......... .......... .......... .......... 83% 58.8M 2s\n", + "499300K .......... .......... .......... .......... .......... 83% 75.5M 2s\n", + "499350K .......... .......... .......... .......... .......... 83% 68.0M 2s\n", + "499400K .......... .......... .......... .......... .......... 83% 64.2M 2s\n", + "499450K .......... .......... .......... .......... .......... 83% 27.4M 2s\n", + "499500K .......... .......... .......... .......... .......... 83% 54.3M 2s\n", + "499550K .......... .......... .......... .......... .......... 84% 73.7M 2s\n", + "499600K .......... .......... .......... .......... .......... 84% 18.2M 2s\n", + "499650K .......... .......... .......... .......... .......... 84% 49.7M 2s\n", + "499700K .......... .......... .......... .......... .......... 84% 64.9M 2s\n", + "499750K .......... .......... .......... .......... .......... 84% 74.6M 2s\n", + "499800K .......... .......... .......... .......... .......... 84% 17.8M 2s\n", + "499850K .......... .......... .......... .......... .......... 84% 52.6M 2s\n", + "499900K .......... .......... .......... .......... .......... 84% 63.8M 2s\n", + "499950K .......... .......... .......... .......... .......... 84% 19.8M 2s\n", + "500000K .......... .......... .......... .......... .......... 84% 47.2M 2s\n", + "500050K .......... .......... .......... .......... .......... 84% 52.3M 2s\n", + "500100K .......... .......... .......... .......... .......... 84% 23.4M 2s\n", + "500150K .......... .......... .......... .......... .......... 84% 30.4M 2s\n", + "500200K .......... .......... .......... .......... .......... 84% 49.5M 2s\n", + "500250K .......... .......... .......... .......... .......... 84% 68.9M 2s\n", + "500300K .......... .......... .......... .......... .......... 84% 17.6M 2s\n", + "500350K .......... .......... .......... .......... .......... 84% 49.9M 2s\n", + "500400K .......... .......... .......... .......... .......... 84% 62.9M 2s\n", + "500450K .......... .......... .......... .......... .......... 84% 26.4M 2s\n", + "500500K .......... .......... .......... .......... .......... 84% 48.0M 2s\n", + "500550K .......... .......... .......... .......... .......... 84% 58.7M 2s\n", + "500600K .......... .......... .......... .......... .......... 84% 56.0M 2s\n", + "500650K .......... .......... .......... .......... .......... 84% 22.8M 2s\n", + "500700K .......... .......... .......... .......... .......... 84% 53.2M 2s\n", + "500750K .......... .......... .......... .......... .......... 84% 60.7M 2s\n", + "500800K .......... .......... .......... .......... .......... 84% 34.7M 2s\n", + "500850K .......... .......... .......... .......... .......... 84% 15.4M 2s\n", + "500900K .......... .......... .......... .......... .......... 84% 4.27M 2s\n", + "500950K .......... .......... .......... .......... .......... 84% 70.7M 2s\n", + "501000K .......... .......... .......... .......... .......... 84% 54.5M 2s\n", + "501050K .......... .......... .......... .......... .......... 84% 62.3M 2s\n", + "501100K .......... .......... .......... .......... .......... 84% 70.4M 2s\n", + "501150K .......... .......... .......... .......... .......... 84% 70.4M 2s\n", + "501200K .......... .......... .......... .......... .......... 84% 35.7M 2s\n", + "501250K .......... .......... .......... .......... .......... 84% 53.9M 2s\n", + "501300K .......... .......... .......... .......... .......... 84% 78.3M 2s\n", + "501350K .......... .......... .......... .......... .......... 84% 22.3M 2s\n", + "501400K .......... .......... .......... .......... .......... 84% 44.6M 2s\n", + "501450K .......... .......... .......... .......... .......... 84% 60.8M 2s\n", + "501500K .......... .......... .......... .......... .......... 84% 78.5M 2s\n", + "501550K .......... .......... .......... .......... .......... 84% 18.0M 2s\n", + "501600K .......... .......... .......... .......... .......... 84% 56.4M 2s\n", + "501650K .......... .......... .......... .......... .......... 84% 78.1M 2s\n", + "501700K .......... .......... .......... .......... .......... 84% 79.8M 2s\n", + "501750K .......... .......... .......... .......... .......... 84% 14.2M 2s\n", + "501800K .......... .......... .......... .......... .......... 84% 61.5M 2s\n", + "501850K .......... .......... .......... .......... .......... 84% 72.0M 2s\n", + "501900K .......... .......... .......... .......... .......... 84% 17.1M 2s\n", + "501950K .......... .......... .......... .......... .......... 84% 64.7M 2s\n", + "502000K .......... .......... .......... .......... .......... 84% 54.9M 2s\n", + "502050K .......... .......... .......... .......... .......... 84% 72.5M 2s\n", + "502100K .......... .......... .......... .......... .......... 84% 19.4M 2s\n", + "502150K .......... .......... .......... .......... .......... 84% 54.3M 2s\n", + "502200K .......... .......... .......... .......... .......... 84% 53.5M 2s\n", + "502250K .......... .......... .......... .......... .......... 84% 62.8M 2s\n", + "502300K .......... .......... .......... .......... .......... 84% 18.0M 2s\n", + "502350K .......... .......... .......... .......... .......... 84% 45.0M 2s\n", + "502400K .......... .......... .......... .......... .......... 84% 55.3M 2s\n", + "502450K .......... .......... .......... .......... .......... 84% 32.0M 2s\n", + "502500K .......... .......... .......... .......... .......... 84% 41.9M 2s\n", + "502550K .......... .......... .......... .......... .......... 84% 48.4M 2s\n", + "502600K .......... .......... .......... .......... .......... 84% 51.6M 2s\n", + "502650K .......... .......... .......... .......... .......... 84% 31.9M 2s\n", + "502700K .......... .......... .......... .......... .......... 84% 45.4M 2s\n", + "502750K .......... .......... .......... .......... .......... 84% 56.5M 2s\n", + "502800K .......... .......... .......... .......... .......... 84% 55.3M 2s\n", + "502850K .......... .......... .......... .......... .......... 84% 28.9M 2s\n", + "502900K .......... .......... .......... .......... .......... 84% 38.7M 2s\n", + "502950K .......... .......... .......... .......... .......... 84% 60.9M 2s\n", + "503000K .......... .......... .......... .......... .......... 84% 49.3M 2s\n", + "503050K .......... .......... .......... .......... .......... 84% 27.4M 2s\n", + "503100K .......... .......... .......... .......... .......... 84% 46.4M 2s\n", + "503150K .......... .......... .......... .......... .......... 84% 63.7M 2s\n", + "503200K .......... .......... .......... .......... .......... 84% 57.0M 2s\n", + "503250K .......... .......... .......... .......... .......... 84% 24.1M 2s\n", + "503300K .......... .......... .......... .......... .......... 84% 45.1M 2s\n", + "503350K .......... .......... .......... .......... .......... 84% 61.5M 2s\n", + "503400K .......... .......... .......... .......... .......... 84% 29.8M 2s\n", + "503450K .......... .......... .......... .......... .......... 84% 40.4M 2s\n", + "503500K .......... .......... .......... .......... .......... 84% 45.5M 2s\n", + "503550K .......... .......... .......... .......... .......... 84% 63.3M 2s\n", + "503600K .......... .......... .......... .......... .......... 84% 33.7M 2s\n", + "503650K .......... .......... .......... .......... .......... 84% 50.4M 2s\n", + "503700K .......... .......... .......... .......... .......... 84% 50.8M 2s\n", + "503750K .......... .......... .......... .......... .......... 84% 53.4M 2s\n", + "503800K .......... .......... .......... .......... .......... 84% 22.3M 2s\n", + "503850K .......... .......... .......... .......... .......... 84% 49.6M 2s\n", + "503900K .......... .......... .......... .......... .......... 84% 55.5M 2s\n", + "503950K .......... .......... .......... .......... .......... 84% 56.8M 2s\n", + "504000K .......... .......... .......... .......... .......... 84% 27.7M 2s\n", + "504050K .......... .......... .......... .......... .......... 84% 38.7M 2s\n", + "504100K .......... .......... .......... .......... .......... 84% 51.3M 2s\n", + "504150K .......... .......... .......... .......... .......... 84% 65.0M 2s\n", + "504200K .......... .......... .......... .......... .......... 84% 27.6M 2s\n", + "504250K .......... .......... .......... .......... .......... 84% 49.2M 2s\n", + "504300K .......... .......... .......... .......... .......... 84% 49.1M 2s\n", + "504350K .......... .......... .......... .......... .......... 84% 60.3M 2s\n", + "504400K .......... .......... .......... .......... .......... 84% 34.4M 2s\n", + "504450K .......... .......... .......... .......... .......... 84% 38.9M 2s\n", + "504500K .......... .......... .......... .......... .......... 84% 54.7M 2s\n", + "504550K .......... .......... .......... .......... .......... 84% 67.8M 2s\n", + "504600K .......... .......... .......... .......... .......... 84% 24.2M 2s\n", + "504650K .......... .......... .......... .......... .......... 84% 48.4M 2s\n", + "504700K .......... .......... .......... .......... .......... 84% 53.4M 2s\n", + "504750K .......... .......... .......... .......... .......... 84% 66.3M 2s\n", + "504800K .......... .......... .......... .......... .......... 84% 37.1M 2s\n", + "504850K .......... .......... .......... .......... .......... 84% 35.0M 2s\n", + "504900K .......... .......... .......... .......... .......... 84% 55.5M 2s\n", + "504950K .......... .......... .......... .......... .......... 84% 72.2M 2s\n", + "505000K .......... .......... .......... .......... .......... 84% 31.1M 2s\n", + "505050K .......... .......... .......... .......... .......... 84% 38.8M 2s\n", + "505100K .......... .......... .......... .......... .......... 84% 49.9M 2s\n", + "505150K .......... .......... .......... .......... .......... 84% 60.1M 2s\n", + "505200K .......... .......... .......... .......... .......... 84% 24.1M 2s\n", + "505250K .......... .......... .......... .......... .......... 84% 35.6M 2s\n", + "505300K .......... .......... .......... .......... .......... 84% 63.7M 2s\n", + "505350K .......... .......... .......... .......... .......... 84% 52.1M 2s\n", + "505400K .......... .......... .......... .......... .......... 84% 36.8M 2s\n", + "505450K .......... .......... .......... .......... .......... 84% 41.0M 2s\n", + "505500K .......... .......... .......... .......... .......... 85% 47.4M 2s\n", + "505550K .......... .......... .......... .......... .......... 85% 59.4M 2s\n", + "505600K .......... .......... .......... .......... .......... 85% 31.6M 2s\n", + "505650K .......... .......... .......... .......... .......... 85% 35.9M 2s\n", + "505700K .......... .......... .......... .......... .......... 85% 46.3M 2s\n", + "505750K .......... .......... .......... .......... .......... 85% 52.0M 2s\n", + "505800K .......... .......... .......... .......... .......... 85% 37.9M 2s\n", + "505850K .......... .......... .......... .......... .......... 85% 39.6M 2s\n", + "505900K .......... .......... .......... .......... .......... 85% 36.8M 2s\n", + "505950K .......... .......... .......... .......... .......... 85% 31.1M 2s\n", + "506000K .......... .......... .......... .......... .......... 85% 28.2M 2s\n", + "506050K .......... .......... .......... .......... .......... 85% 33.3M 2s\n", + "506100K .......... .......... .......... .......... .......... 85% 32.8M 2s\n", + "506150K .......... .......... .......... .......... .......... 85% 35.7M 2s\n", + "506200K .......... .......... .......... .......... .......... 85% 41.6M 2s\n", + "506250K .......... .......... .......... .......... .......... 85% 52.5M 2s\n", + "506300K .......... .......... .......... .......... .......... 85% 38.6M 2s\n", + "506350K .......... .......... .......... .......... .......... 85% 41.3M 2s\n", + "506400K .......... .......... .......... .......... .......... 85% 6.98M 2s\n", + "506450K .......... .......... .......... .......... .......... 85% 69.8M 2s\n", + "506500K .......... .......... .......... .......... .......... 85% 53.2M 2s\n", + "506550K .......... .......... .......... .......... .......... 85% 58.7M 2s\n", + "506600K .......... .......... .......... .......... .......... 85% 58.4M 2s\n", + "506650K .......... .......... .......... .......... .......... 85% 63.9M 2s\n", + "506700K .......... .......... .......... .......... .......... 85% 51.9M 2s\n", + "506750K .......... .......... .......... .......... .......... 85% 36.7M 2s\n", + "506800K .......... .......... .......... .......... .......... 85% 33.2M 2s\n", + "506850K .......... .......... .......... .......... .......... 85% 37.7M 2s\n", + "506900K .......... .......... .......... .......... .......... 85% 36.9M 2s\n", + "506950K .......... .......... .......... .......... .......... 85% 61.3M 2s\n", + "507000K .......... .......... .......... .......... .......... 85% 46.6M 2s\n", + "507050K .......... .......... .......... .......... .......... 85% 58.6M 2s\n", + "507100K .......... .......... .......... .......... .......... 85% 54.2M 2s\n", + "507150K .......... .......... .......... .......... .......... 85% 40.7M 2s\n", + "507200K .......... .......... .......... .......... .......... 85% 52.1M 2s\n", + "507250K .......... .......... .......... .......... .......... 85% 55.3M 2s\n", + "507300K .......... .......... .......... .......... .......... 85% 35.8M 2s\n", + "507350K .......... .......... .......... .......... .......... 85% 45.7M 2s\n", + "507400K .......... .......... .......... .......... .......... 85% 46.2M 2s\n", + "507450K .......... .......... .......... .......... .......... 85% 58.8M 2s\n", + "507500K .......... .......... .......... .......... .......... 85% 68.2M 2s\n", + "507550K .......... .......... .......... .......... .......... 85% 52.9M 2s\n", + "507600K .......... .......... .......... .......... .......... 85% 43.9M 2s\n", + "507650K .......... .......... .......... .......... .......... 85% 49.0M 2s\n", + "507700K .......... .......... .......... .......... .......... 85% 66.1M 2s\n", + "507750K .......... .......... .......... .......... .......... 85% 53.5M 2s\n", + "507800K .......... .......... .......... .......... .......... 85% 32.2M 2s\n", + "507850K .......... .......... .......... .......... .......... 85% 40.0M 2s\n", + "507900K .......... .......... .......... .......... .......... 85% 70.1M 2s\n", + "507950K .......... .......... .......... .......... .......... 85% 63.7M 2s\n", + "508000K .......... .......... .......... .......... .......... 85% 38.0M 2s\n", + "508050K .......... .......... .......... .......... .......... 85% 40.8M 2s\n", + "508100K .......... .......... .......... .......... .......... 85% 46.1M 2s\n", + "508150K .......... .......... .......... .......... .......... 85% 47.2M 2s\n", + "508200K .......... .......... .......... .......... .......... 85% 37.3M 2s\n", + "508250K .......... .......... .......... .......... .......... 85% 40.3M 2s\n", + "508300K .......... .......... .......... .......... .......... 85% 39.8M 2s\n", + "508350K .......... .......... .......... .......... .......... 85% 49.6M 2s\n", + "508400K .......... .......... .......... .......... .......... 85% 39.3M 2s\n", + "508450K .......... .......... .......... .......... .......... 85% 61.5M 2s\n", + "508500K .......... .......... .......... .......... .......... 85% 48.6M 2s\n", + "508550K .......... .......... .......... .......... .......... 85% 43.3M 2s\n", + "508600K .......... .......... .......... .......... .......... 85% 48.0M 2s\n", + "508650K .......... .......... .......... .......... .......... 85% 46.9M 2s\n", + "508700K .......... .......... .......... .......... .......... 85% 29.9M 2s\n", + "508750K .......... .......... .......... .......... .......... 85% 43.1M 2s\n", + "508800K .......... .......... .......... .......... .......... 85% 48.4M 2s\n", + "508850K .......... .......... .......... .......... .......... 85% 61.9M 2s\n", + "508900K .......... .......... .......... .......... .......... 85% 68.7M 2s\n", + "508950K .......... .......... .......... .......... .......... 85% 47.8M 2s\n", + "509000K .......... .......... .......... .......... .......... 85% 38.7M 2s\n", + "509050K .......... .......... .......... .......... .......... 85% 59.8M 2s\n", + "509100K .......... .......... .......... .......... .......... 85% 60.6M 2s\n", + "509150K .......... .......... .......... .......... .......... 85% 62.4M 2s\n", + "509200K .......... .......... .......... .......... .......... 85% 32.6M 2s\n", + "509250K .......... .......... .......... .......... .......... 85% 43.8M 2s\n", + "509300K .......... .......... .......... .......... .......... 85% 27.2M 2s\n", + "509350K .......... .......... .......... .......... .......... 85% 60.0M 2s\n", + "509400K .......... .......... .......... .......... .......... 85% 22.9M 2s\n", + "509450K .......... .......... .......... .......... .......... 85% 42.2M 2s\n", + "509500K .......... .......... .......... .......... .......... 85% 52.9M 2s\n", + "509550K .......... .......... .......... .......... .......... 85% 64.9M 2s\n", + "509600K .......... .......... .......... .......... .......... 85% 16.0M 2s\n", + "509650K .......... .......... .......... .......... .......... 85% 48.6M 2s\n", + "509700K .......... .......... .......... .......... .......... 85% 51.4M 2s\n", + "509750K .......... .......... .......... .......... .......... 85% 65.5M 2s\n", + "509800K .......... .......... .......... .......... .......... 85% 53.3M 2s\n", + "509850K .......... .......... .......... .......... .......... 85% 13.4M 2s\n", + "509900K .......... .......... .......... .......... .......... 85% 41.9M 2s\n", + "509950K .......... .......... .......... .......... .......... 85% 53.7M 2s\n", + "510000K .......... .......... .......... .......... .......... 85% 59.1M 2s\n", + "510050K .......... .......... .......... .......... .......... 85% 38.8M 2s\n", + "510100K .......... .......... .......... .......... .......... 85% 41.1M 2s\n", + "510150K .......... .......... .......... .......... .......... 85% 50.4M 2s\n", + "510200K .......... .......... .......... .......... .......... 85% 54.6M 2s\n", + "510250K .......... .......... .......... .......... .......... 85% 35.8M 2s\n", + "510300K .......... .......... .......... .......... .......... 85% 52.3M 2s\n", + "510350K .......... .......... .......... .......... .......... 85% 46.1M 2s\n", + "510400K .......... .......... .......... .......... .......... 85% 40.5M 2s\n", + "510450K .......... .......... .......... .......... .......... 85% 49.4M 2s\n", + "510500K .......... .......... .......... .......... .......... 85% 3.71M 2s\n", + "510550K .......... .......... .......... .......... .......... 85% 57.9M 2s\n", + "510600K .......... .......... .......... .......... .......... 85% 46.8M 2s\n", + "510650K .......... .......... .......... .......... .......... 85% 66.7M 2s\n", + "510700K .......... .......... .......... .......... .......... 85% 68.3M 2s\n", + "510750K .......... .......... .......... .......... .......... 85% 31.0M 2s\n", + "510800K .......... .......... .......... .......... .......... 85% 41.9M 2s\n", + "510850K .......... .......... .......... .......... .......... 85% 65.0M 2s\n", + "510900K .......... .......... .......... .......... .......... 85% 59.5M 2s\n", + "510950K .......... .......... .......... .......... .......... 85% 57.0M 2s\n", + "511000K .......... .......... .......... .......... .......... 85% 35.9M 2s\n", + "511050K .......... .......... .......... .......... .......... 85% 52.1M 2s\n", + "511100K .......... .......... .......... .......... .......... 85% 66.4M 2s\n", + "511150K .......... .......... .......... .......... .......... 85% 59.9M 2s\n", + "511200K .......... .......... .......... .......... .......... 85% 26.1M 2s\n", + "511250K .......... .......... .......... .......... .......... 85% 62.9M 2s\n", + "511300K .......... .......... .......... .......... .......... 85% 52.5M 2s\n", + "511350K .......... .......... .......... .......... .......... 85% 60.8M 2s\n", + "511400K .......... .......... .......... .......... .......... 85% 28.6M 2s\n", + "511450K .......... .......... .......... .......... .......... 86% 47.2M 2s\n", + "511500K .......... .......... .......... .......... .......... 86% 55.9M 2s\n", + "511550K .......... .......... .......... .......... .......... 86% 56.7M 2s\n", + "511600K .......... .......... .......... .......... .......... 86% 51.8M 2s\n", + "511650K .......... .......... .......... .......... .......... 86% 58.1M 2s\n", + "511700K .......... .......... .......... .......... .......... 86% 49.3M 2s\n", + "511750K .......... .......... .......... .......... .......... 86% 57.5M 2s\n", + "511800K .......... .......... .......... .......... .......... 86% 42.4M 2s\n", + "511850K .......... .......... .......... .......... .......... 86% 47.7M 2s\n", + "511900K .......... .......... .......... .......... .......... 86% 44.3M 2s\n", + "511950K .......... .......... .......... .......... .......... 86% 45.1M 2s\n", + "512000K .......... .......... .......... .......... .......... 86% 60.0M 2s\n", + "512050K .......... .......... .......... .......... .......... 86% 55.6M 2s\n", + "512100K .......... .......... .......... .......... .......... 86% 39.6M 2s\n", + "512150K .......... .......... .......... .......... .......... 86% 45.3M 2s\n", + "512200K .......... .......... .......... .......... .......... 86% 33.9M 2s\n", + "512250K .......... .......... .......... .......... .......... 86% 58.1M 2s\n", + "512300K .......... .......... .......... .......... .......... 86% 65.1M 2s\n", + "512350K .......... .......... .......... .......... .......... 86% 48.7M 2s\n", + "512400K .......... .......... .......... .......... .......... 86% 49.5M 2s\n", + "512450K .......... .......... .......... .......... .......... 86% 61.1M 2s\n", + "512500K .......... .......... .......... .......... .......... 86% 69.7M 2s\n", + "512550K .......... .......... .......... .......... .......... 86% 62.0M 2s\n", + "512600K .......... .......... .......... .......... .......... 86% 25.7M 2s\n", + "512650K .......... .......... .......... .......... .......... 86% 44.2M 2s\n", + "512700K .......... .......... .......... .......... .......... 86% 52.6M 2s\n", + "512750K .......... .......... .......... .......... .......... 86% 40.7M 2s\n", + "512800K .......... .......... .......... .......... .......... 86% 28.3M 2s\n", + "512850K .......... .......... .......... .......... .......... 86% 35.0M 2s\n", + "512900K .......... .......... .......... .......... .......... 86% 45.9M 2s\n", + "512950K .......... .......... .......... .......... .......... 86% 3.86M 2s\n", + "513000K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", + "513050K .......... .......... .......... .......... .......... 86% 45.4M 2s\n", + "513100K .......... .......... .......... .......... .......... 86% 35.9M 2s\n", + "513150K .......... .......... .......... .......... .......... 86% 41.3M 2s\n", + "513200K .......... .......... .......... .......... .......... 86% 36.1M 2s\n", + "513250K .......... .......... .......... .......... .......... 86% 62.1M 2s\n", + "513300K .......... .......... .......... .......... .......... 86% 63.7M 2s\n", + "513350K .......... .......... .......... .......... .......... 86% 67.6M 2s\n", + "513400K .......... .......... .......... .......... .......... 86% 43.1M 2s\n", + "513450K .......... .......... .......... .......... .......... 86% 46.1M 2s\n", + "513500K .......... .......... .......... .......... .......... 86% 47.0M 2s\n", + "513550K .......... .......... .......... .......... .......... 86% 64.8M 2s\n", + "513600K .......... .......... .......... .......... .......... 86% 58.4M 2s\n", + "513650K .......... .......... .......... .......... .......... 86% 35.7M 2s\n", + "513700K .......... .......... .......... .......... .......... 86% 46.2M 2s\n", + "513750K .......... .......... .......... .......... .......... 86% 63.3M 2s\n", + "513800K .......... .......... .......... .......... .......... 86% 52.6M 2s\n", + "513850K .......... .......... .......... .......... .......... 86% 56.3M 2s\n", + "513900K .......... .......... .......... .......... .......... 86% 50.2M 2s\n", + "513950K .......... .......... .......... .......... .......... 86% 55.2M 2s\n", + "514000K .......... .......... .......... .......... .......... 86% 47.8M 2s\n", + "514050K .......... .......... .......... .......... .......... 86% 62.3M 2s\n", + "514100K .......... .......... .......... .......... .......... 86% 41.8M 2s\n", + "514150K .......... .......... .......... .......... .......... 86% 47.8M 2s\n", + "514200K .......... .......... .......... .......... .......... 86% 36.4M 2s\n", + "514250K .......... .......... .......... .......... .......... 86% 59.0M 2s\n", + "514300K .......... .......... .......... .......... .......... 86% 50.6M 2s\n", + "514350K .......... .......... .......... .......... .......... 86% 39.4M 2s\n", + "514400K .......... .......... .......... .......... .......... 86% 38.0M 2s\n", + "514450K .......... .......... .......... .......... .......... 86% 47.2M 2s\n", + "514500K .......... .......... .......... .......... .......... 86% 52.8M 2s\n", + "514550K .......... .......... .......... .......... .......... 86% 36.7M 2s\n", + "514600K .......... .......... .......... .......... .......... 86% 32.3M 2s\n", + "514650K .......... .......... .......... .......... .......... 86% 75.0M 2s\n", + "514700K .......... .......... .......... .......... .......... 86% 56.1M 2s\n", + "514750K .......... .......... .......... .......... .......... 86% 39.5M 2s\n", + "514800K .......... .......... .......... .......... .......... 86% 34.6M 2s\n", + "514850K .......... .......... .......... .......... .......... 86% 46.3M 2s\n", + "514900K .......... .......... .......... .......... .......... 86% 39.9M 2s\n", + "514950K .......... .......... .......... .......... .......... 86% 39.0M 2s\n", + "515000K .......... .......... .......... .......... .......... 86% 40.1M 2s\n", + "515050K .......... .......... .......... .......... .......... 86% 56.3M 2s\n", + "515100K .......... .......... .......... .......... .......... 86% 58.3M 2s\n", + "515150K .......... .......... .......... .......... .......... 86% 69.4M 2s\n", + "515200K .......... .......... .......... .......... .......... 86% 45.2M 2s\n", + "515250K .......... .......... .......... .......... .......... 86% 53.5M 2s\n", + "515300K .......... .......... .......... .......... .......... 86% 50.8M 2s\n", + "515350K .......... .......... .......... .......... .......... 86% 61.0M 2s\n", + "515400K .......... .......... .......... .......... .......... 86% 52.0M 2s\n", + "515450K .......... .......... .......... .......... .......... 86% 44.9M 2s\n", + "515500K .......... .......... .......... .......... .......... 86% 54.2M 2s\n", + "515550K .......... .......... .......... .......... .......... 86% 55.5M 2s\n", + "515600K .......... .......... .......... .......... .......... 86% 52.9M 2s\n", + "515650K .......... .......... .......... .......... .......... 86% 71.7M 2s\n", + "515700K .......... .......... .......... .......... .......... 86% 43.6M 2s\n", + "515750K .......... .......... .......... .......... .......... 86% 45.1M 2s\n", + "515800K .......... .......... .......... .......... .......... 86% 45.6M 2s\n", + "515850K .......... .......... .......... .......... .......... 86% 62.8M 2s\n", + "515900K .......... .......... .......... .......... .......... 86% 61.7M 2s\n", + "515950K .......... .......... .......... .......... .......... 86% 55.4M 2s\n", + "516000K .......... .......... .......... .......... .......... 86% 45.4M 2s\n", + "516050K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", + "516100K .......... .......... .......... .......... .......... 86% 66.5M 2s\n", + "516150K .......... .......... .......... .......... .......... 86% 69.5M 2s\n", + "516200K .......... .......... .......... .......... .......... 86% 52.1M 2s\n", + "516250K .......... .......... .......... .......... .......... 86% 53.9M 2s\n", + "516300K .......... .......... .......... .......... .......... 86% 44.7M 2s\n", + "516350K .......... .......... .......... .......... .......... 86% 44.7M 2s\n", + "516400K .......... .......... .......... .......... .......... 86% 65.6M 2s\n", + "516450K .......... .......... .......... .......... .......... 86% 58.2M 2s\n", + "516500K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", + "516550K .......... .......... .......... .......... .......... 86% 40.5M 2s\n", + "516600K .......... .......... .......... .......... .......... 86% 56.8M 2s\n", + "516650K .......... .......... .......... .......... .......... 86% 58.9M 2s\n", + "516700K .......... .......... .......... .......... .......... 86% 56.9M 2s\n", + "516750K .......... .......... .......... .......... .......... 86% 55.6M 2s\n", + "516800K .......... .......... .......... .......... .......... 86% 37.7M 2s\n", + "516850K .......... .......... .......... .......... .......... 86% 62.5M 2s\n", + "516900K .......... .......... .......... .......... .......... 86% 61.5M 2s\n", + "516950K .......... .......... .......... .......... .......... 86% 54.2M 2s\n", + "517000K .......... .......... .......... .......... .......... 86% 3.87M 2s\n", + "517050K .......... .......... .......... .......... .......... 86% 47.0M 2s\n", + "517100K .......... .......... .......... .......... .......... 86% 65.7M 2s\n", + "517150K .......... .......... .......... .......... .......... 86% 69.5M 2s\n", + "517200K .......... .......... .......... .......... .......... 86% 61.3M 2s\n", + "517250K .......... .......... .......... .......... .......... 86% 51.4M 2s\n", + "517300K .......... .......... .......... .......... .......... 86% 45.6M 2s\n", + "517350K .......... .......... .......... .......... .......... 86% 61.9M 2s\n", + "517400K .......... .......... .......... .......... .......... 87% 53.6M 2s\n", + "517450K .......... .......... .......... .......... .......... 87% 67.7M 2s\n", + "517500K .......... .......... .......... .......... .......... 87% 68.3M 2s\n", + "517550K .......... .......... .......... .......... .......... 87% 54.0M 2s\n", + "517600K .......... .......... .......... .......... .......... 87% 58.0M 2s\n", + "517650K .......... .......... .......... .......... .......... 87% 55.7M 2s\n", + "517700K .......... .......... .......... .......... .......... 87% 61.0M 2s\n", + "517750K .......... .......... .......... .......... .......... 87% 58.2M 2s\n", + "517800K .......... .......... .......... .......... .......... 87% 48.0M 2s\n", + "517850K .......... .......... .......... .......... .......... 87% 62.1M 2s\n", + "517900K .......... .......... .......... .......... .......... 87% 40.1M 2s\n", + "517950K .......... .......... .......... .......... .......... 87% 63.5M 2s\n", + "518000K .......... .......... .......... .......... .......... 87% 50.7M 2s\n", + "518050K .......... .......... .......... .......... .......... 87% 56.6M 2s\n", + "518100K .......... .......... .......... .......... .......... 87% 48.5M 2s\n", + "518150K .......... .......... .......... .......... .......... 87% 42.4M 2s\n", + "518200K .......... .......... .......... .......... .......... 87% 50.7M 2s\n", + "518250K .......... .......... .......... .......... .......... 87% 55.9M 2s\n", + "518300K .......... .......... .......... .......... .......... 87% 53.3M 2s\n", + "518350K .......... .......... .......... .......... .......... 87% 39.2M 2s\n", + "518400K .......... .......... .......... .......... .......... 87% 48.8M 2s\n", + "518450K .......... .......... .......... .......... .......... 87% 57.9M 2s\n", + "518500K .......... .......... .......... .......... .......... 87% 56.8M 2s\n", + "518550K .......... .......... .......... .......... .......... 87% 50.6M 2s\n", + "518600K .......... .......... .......... .......... .......... 87% 32.6M 2s\n", + "518650K .......... .......... .......... .......... .......... 87% 66.5M 2s\n", + "518700K .......... .......... .......... .......... .......... 87% 51.3M 2s\n", + "518750K .......... .......... .......... .......... .......... 87% 26.5M 2s\n", + "518800K .......... .......... .......... .......... .......... 87% 32.0M 2s\n", + "518850K .......... .......... .......... .......... .......... 87% 52.4M 2s\n", + "518900K .......... .......... .......... .......... .......... 87% 68.2M 2s\n", + "518950K .......... .......... .......... .......... .......... 87% 27.8M 2s\n", + "519000K .......... .......... .......... .......... .......... 87% 40.8M 2s\n", + "519050K .......... .......... .......... .......... .......... 87% 55.6M 2s\n", + "519100K .......... .......... .......... .......... .......... 87% 22.1M 2s\n", + "519150K .......... .......... .......... .......... .......... 87% 31.0M 2s\n", + "519200K .......... .......... .......... .......... .......... 87% 49.9M 2s\n", + "519250K .......... .......... .......... .......... .......... 87% 49.2M 2s\n", + "519300K .......... .......... .......... .......... .......... 87% 32.2M 2s\n", + "519350K .......... .......... .......... .......... .......... 87% 30.5M 2s\n", + "519400K .......... .......... .......... .......... .......... 87% 33.5M 2s\n", + "519450K .......... .......... .......... .......... .......... 87% 39.3M 2s\n", + "519500K .......... .......... .......... .......... .......... 87% 28.8M 2s\n", + "519550K .......... .......... .......... .......... .......... 87% 41.4M 2s\n", + "519600K .......... .......... .......... .......... .......... 87% 62.2M 2s\n", + "519650K .......... .......... .......... .......... .......... 87% 38.0M 2s\n", + "519700K .......... .......... .......... .......... .......... 87% 36.9M 2s\n", + "519750K .......... .......... .......... .......... .......... 87% 37.5M 2s\n", + "519800K .......... .......... .......... .......... .......... 87% 24.9M 2s\n", + "519850K .......... .......... .......... .......... .......... 87% 35.6M 2s\n", + "519900K .......... .......... .......... .......... .......... 87% 48.1M 2s\n", + "519950K .......... .......... .......... .......... .......... 87% 48.0M 2s\n", + "520000K .......... .......... .......... .......... .......... 87% 33.6M 2s\n", + "520050K .......... .......... .......... .......... .......... 87% 34.6M 2s\n", + "520100K .......... .......... .......... .......... .......... 87% 62.4M 2s\n", + "520150K .......... .......... .......... .......... .......... 87% 42.9M 2s\n", + "520200K .......... .......... .......... .......... .......... 87% 37.6M 2s\n", + "520250K .......... .......... .......... .......... .......... 87% 35.9M 2s\n", + "520300K .......... .......... .......... .......... .......... 87% 42.8M 2s\n", + "520350K .......... .......... .......... .......... .......... 87% 52.2M 2s\n", + "520400K .......... .......... .......... .......... .......... 87% 40.9M 2s\n", + "520450K .......... .......... .......... .......... .......... 87% 33.3M 2s\n", + "520500K .......... .......... .......... .......... .......... 87% 45.8M 2s\n", + "520550K .......... .......... .......... .......... .......... 87% 56.5M 2s\n", + "520600K .......... .......... .......... .......... .......... 87% 29.7M 2s\n", + "520650K .......... .......... .......... .......... .......... 87% 17.1M 2s\n", + "520700K .......... .......... .......... .......... .......... 87% 24.6M 2s\n", + "520750K .......... .......... .......... .......... .......... 87% 22.9M 2s\n", + "520800K .......... .......... .......... .......... .......... 87% 40.0M 2s\n", + "520850K .......... .......... .......... .......... .......... 87% 45.8M 2s\n", + "520900K .......... .......... .......... .......... .......... 87% 52.3M 2s\n", + "520950K .......... .......... .......... .......... .......... 87% 39.2M 2s\n", + "521000K .......... .......... .......... .......... .......... 87% 37.7M 2s\n", + "521050K .......... .......... .......... .......... .......... 87% 63.1M 2s\n", + "521100K .......... .......... .......... .......... .......... 87% 51.7M 2s\n", + "521150K .......... .......... .......... .......... .......... 87% 34.3M 2s\n", + "521200K .......... .......... .......... .......... .......... 87% 38.6M 2s\n", + "521250K .......... .......... .......... .......... .......... 87% 44.2M 2s\n", + "521300K .......... .......... .......... .......... .......... 87% 23.5M 2s\n", + "521350K .......... .......... .......... .......... .......... 87% 25.8M 2s\n", + "521400K .......... .......... .......... .......... .......... 87% 26.7M 2s\n", + "521450K .......... .......... .......... .......... .......... 87% 31.6M 2s\n", + "521500K .......... .......... .......... .......... .......... 87% 30.7M 2s\n", + "521550K .......... .......... .......... .......... .......... 87% 36.0M 2s\n", + "521600K .......... .......... .......... .......... .......... 87% 24.3M 2s\n", + "521650K .......... .......... .......... .......... .......... 87% 27.8M 2s\n", + "521700K .......... .......... .......... .......... .......... 87% 35.5M 2s\n", + "521750K .......... .......... .......... .......... .......... 87% 25.9M 2s\n", + "521800K .......... .......... .......... .......... .......... 87% 25.8M 2s\n", + "521850K .......... .......... .......... .......... .......... 87% 28.6M 2s\n", + "521900K .......... .......... .......... .......... .......... 87% 57.6M 2s\n", + "521950K .......... .......... .......... .......... .......... 87% 33.6M 2s\n", + "522000K .......... .......... .......... .......... .......... 87% 56.0M 2s\n", + "522050K .......... .......... .......... .......... .......... 87% 42.0M 2s\n", + "522100K .......... .......... .......... .......... .......... 87% 44.3M 2s\n", + "522150K .......... .......... .......... .......... .......... 87% 29.9M 2s\n", + "522200K .......... .......... .......... .......... .......... 87% 29.4M 2s\n", + "522250K .......... .......... .......... .......... .......... 87% 59.7M 2s\n", + "522300K .......... .......... .......... .......... .......... 87% 26.9M 2s\n", + "522350K .......... .......... .......... .......... .......... 87% 46.1M 2s\n", + "522400K .......... .......... .......... .......... .......... 87% 55.6M 2s\n", + "522450K .......... .......... .......... .......... .......... 87% 35.5M 2s\n", + "522500K .......... .......... .......... .......... .......... 87% 42.9M 2s\n", + "522550K .......... .......... .......... .......... .......... 87% 42.0M 2s\n", + "522600K .......... .......... .......... .......... .......... 87% 49.8M 2s\n", + "522650K .......... .......... .......... .......... .......... 87% 28.1M 2s\n", + "522700K .......... .......... .......... .......... .......... 87% 27.1M 2s\n", + "522750K .......... .......... .......... .......... .......... 87% 38.7M 2s\n", + "522800K .......... .......... .......... .......... .......... 87% 36.4M 2s\n", + "522850K .......... .......... .......... .......... .......... 87% 50.5M 2s\n", + "522900K .......... .......... .......... .......... .......... 87% 41.9M 2s\n", + "522950K .......... .......... .......... .......... .......... 87% 39.1M 2s\n", + "523000K .......... .......... .......... .......... .......... 87% 40.2M 2s\n", + "523050K .......... .......... .......... .......... .......... 87% 28.9M 2s\n", + "523100K .......... .......... .......... .......... .......... 87% 19.5M 2s\n", + "523150K .......... .......... .......... .......... .......... 87% 32.8M 2s\n", + "523200K .......... .......... .......... .......... .......... 87% 34.0M 2s\n", + "523250K .......... .......... .......... .......... .......... 87% 49.7M 2s\n", + "523300K .......... .......... .......... .......... .......... 87% 38.5M 2s\n", + "523350K .......... .......... .......... .......... .......... 88% 43.1M 2s\n", + "523400K .......... .......... .......... .......... .......... 88% 27.6M 2s\n", + "523450K .......... .......... .......... .......... .......... 88% 44.0M 2s\n", + "523500K .......... .......... .......... .......... .......... 88% 49.5M 2s\n", + "523550K .......... .......... .......... .......... .......... 88% 49.1M 2s\n", + "523600K .......... .......... .......... .......... .......... 88% 33.4M 2s\n", + "523650K .......... .......... .......... .......... .......... 88% 20.8M 2s\n", + "523700K .......... .......... .......... .......... .......... 88% 19.5M 2s\n", + "523750K .......... .......... .......... .......... .......... 88% 27.6M 2s\n", + "523800K .......... .......... .......... .......... .......... 88% 23.9M 2s\n", + "523850K .......... .......... .......... .......... .......... 88% 24.6M 2s\n", + "523900K .......... .......... .......... .......... .......... 88% 3.11M 2s\n", + "523950K .......... .......... .......... .......... .......... 88% 38.8M 2s\n", + "524000K .......... .......... .......... .......... .......... 88% 38.1M 2s\n", + "524050K .......... .......... .......... .......... .......... 88% 21.9M 2s\n", + "524100K .......... .......... .......... .......... .......... 88% 41.4M 2s\n", + "524150K .......... .......... .......... .......... .......... 88% 39.5M 2s\n", + "524200K .......... .......... .......... .......... .......... 88% 14.7M 2s\n", + "524250K .......... .......... .......... .......... .......... 88% 38.3M 2s\n", + "524300K .......... .......... .......... .......... .......... 88% 16.0M 2s\n", + "524350K .......... .......... .......... .......... .......... 88% 33.1M 2s\n", + "524400K .......... .......... .......... .......... .......... 88% 24.4M 2s\n", + "524450K .......... .......... .......... .......... .......... 88% 21.9M 2s\n", + "524500K .......... .......... .......... .......... .......... 88% 35.0M 2s\n", + "524550K .......... .......... .......... .......... .......... 88% 34.5M 2s\n", + "524600K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", + "524650K .......... .......... .......... .......... .......... 88% 33.8M 2s\n", + "524700K .......... .......... .......... .......... .......... 88% 15.9M 2s\n", + "524750K .......... .......... .......... .......... .......... 88% 30.9M 2s\n", + "524800K .......... .......... .......... .......... .......... 88% 20.2M 2s\n", + "524850K .......... .......... .......... .......... .......... 88% 48.5M 2s\n", + "524900K .......... .......... .......... .......... .......... 88% 56.7M 2s\n", + "524950K .......... .......... .......... .......... .......... 88% 66.6M 2s\n", + "525000K .......... .......... .......... .......... .......... 88% 49.1M 2s\n", + "525050K .......... .......... .......... .......... .......... 88% 40.4M 2s\n", + "525100K .......... .......... .......... .......... .......... 88% 40.8M 2s\n", + "525150K .......... .......... .......... .......... .......... 88% 63.7M 2s\n", + "525200K .......... .......... .......... .......... .......... 88% 10.9M 2s\n", + "525250K .......... .......... .......... .......... .......... 88% 66.0M 2s\n", + "525300K .......... .......... .......... .......... .......... 88% 67.1M 2s\n", + "525350K .......... .......... .......... .......... .......... 88% 69.6M 2s\n", + "525400K .......... .......... .......... .......... .......... 88% 56.3M 2s\n", + "525450K .......... .......... .......... .......... .......... 88% 66.3M 2s\n", + "525500K .......... .......... .......... .......... .......... 88% 32.8M 2s\n", + "525550K .......... .......... .......... .......... .......... 88% 60.1M 2s\n", + "525600K .......... .......... .......... .......... .......... 88% 52.9M 2s\n", + "525650K .......... .......... .......... .......... .......... 88% 63.7M 2s\n", + "525700K .......... .......... .......... .......... .......... 88% 54.6M 2s\n", + "525750K .......... .......... .......... .......... .......... 88% 3.84M 2s\n", + "525800K .......... .......... .......... .......... .......... 88% 55.4M 2s\n", + "525850K .......... .......... .......... .......... .......... 88% 69.5M 2s\n", + "525900K .......... .......... .......... .......... .......... 88% 64.2M 2s\n", + "525950K .......... .......... .......... .......... .......... 88% 67.3M 2s\n", + "526000K .......... .......... .......... .......... .......... 88% 66.6M 2s\n", + "526050K .......... .......... .......... .......... .......... 88% 38.3M 2s\n", + "526100K .......... .......... .......... .......... .......... 88% 48.5M 2s\n", + "526150K .......... .......... .......... .......... .......... 88% 69.3M 2s\n", + "526200K .......... .......... .......... .......... .......... 88% 58.6M 2s\n", + "526250K .......... .......... .......... .......... .......... 88% 66.5M 2s\n", + "526300K .......... .......... .......... .......... .......... 88% 41.2M 2s\n", + "526350K .......... .......... .......... .......... .......... 88% 43.2M 2s\n", + "526400K .......... .......... .......... .......... .......... 88% 57.2M 2s\n", + "526450K .......... .......... .......... .......... .......... 88% 57.4M 2s\n", + "526500K .......... .......... .......... .......... .......... 88% 58.8M 2s\n", + "526550K .......... .......... .......... .......... .......... 88% 33.2M 2s\n", + "526600K .......... .......... .......... .......... .......... 88% 50.5M 2s\n", + "526650K .......... .......... .......... .......... .......... 88% 48.1M 2s\n", + "526700K .......... .......... .......... .......... .......... 88% 55.0M 2s\n", + "526750K .......... .......... .......... .......... .......... 88% 52.4M 2s\n", + "526800K .......... .......... .......... .......... .......... 88% 47.5M 2s\n", + "526850K .......... .......... .......... .......... .......... 88% 65.1M 2s\n", + "526900K .......... .......... .......... .......... .......... 88% 69.2M 2s\n", + "526950K .......... .......... .......... .......... .......... 88% 57.7M 2s\n", + "527000K .......... .......... .......... .......... .......... 88% 53.4M 2s\n", + "527050K .......... .......... .......... .......... .......... 88% 26.0M 2s\n", + "527100K .......... .......... .......... .......... .......... 88% 35.9M 2s\n", + "527150K .......... .......... .......... .......... .......... 88% 70.0M 2s\n", + "527200K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", + "527250K .......... .......... .......... .......... .......... 88% 48.4M 2s\n", + "527300K .......... .......... .......... .......... .......... 88% 54.5M 2s\n", + "527350K .......... .......... .......... .......... .......... 88% 19.2M 2s\n", + "527400K .......... .......... .......... .......... .......... 88% 5.44M 2s\n", + "527450K .......... .......... .......... .......... .......... 88% 69.0M 2s\n", + "527500K .......... .......... .......... .......... .......... 88% 52.0M 2s\n", + "527550K .......... .......... .......... .......... .......... 88% 13.5M 2s\n", + "527600K .......... .......... .......... .......... .......... 88% 53.3M 2s\n", + "527650K .......... .......... .......... .......... .......... 88% 65.5M 2s\n", + "527700K .......... .......... .......... .......... .......... 88% 16.6M 2s\n", + "527750K .......... .......... .......... .......... .......... 88% 64.1M 2s\n", + "527800K .......... .......... .......... .......... .......... 88% 18.1M 2s\n", + "527850K .......... .......... .......... .......... .......... 88% 34.1M 2s\n", + "527900K .......... .......... .......... .......... .......... 88% 65.9M 2s\n", + "527950K .......... .......... .......... .......... .......... 88% 21.2M 2s\n", + "528000K .......... .......... .......... .......... .......... 88% 31.4M 2s\n", + "528050K .......... .......... .......... .......... .......... 88% 56.6M 2s\n", + "528100K .......... .......... .......... .......... .......... 88% 20.1M 2s\n", + "528150K .......... .......... .......... .......... .......... 88% 44.5M 2s\n", + "528200K .......... .......... .......... .......... .......... 88% 42.0M 2s\n", + "528250K .......... .......... .......... .......... .......... 88% 19.2M 2s\n", + "528300K .......... .......... .......... .......... .......... 88% 37.5M 2s\n", + "528350K .......... .......... .......... .......... .......... 88% 65.7M 2s\n", + "528400K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", + "528450K .......... .......... .......... .......... .......... 88% 42.6M 2s\n", + "528500K .......... .......... .......... .......... .......... 88% 43.1M 2s\n", + "528550K .......... .......... .......... .......... .......... 88% 19.7M 2s\n", + "528600K .......... .......... .......... .......... .......... 88% 33.3M 2s\n", + "528650K .......... .......... .......... .......... .......... 88% 64.6M 2s\n", + "528700K .......... .......... .......... .......... .......... 88% 15.8M 2s\n", + "528750K .......... .......... .......... .......... .......... 88% 47.5M 2s\n", + "528800K .......... .......... .......... .......... .......... 88% 64.4M 2s\n", + "528850K .......... .......... .......... .......... .......... 88% 17.6M 2s\n", + "528900K .......... .......... .......... .......... .......... 88% 46.2M 2s\n", + "528950K .......... .......... .......... .......... .......... 88% 69.3M 2s\n", + "529000K .......... .......... .......... .......... .......... 88% 17.8M 2s\n", + "529050K .......... .......... .......... .......... .......... 88% 37.0M 2s\n", + "529100K .......... .......... .......... .......... .......... 88% 21.8M 2s\n", + "529150K .......... .......... .......... .......... .......... 88% 8.25M 2s\n", + "529200K .......... .......... .......... .......... .......... 88% 58.3M 2s\n", + "529250K .......... .......... .......... .......... .......... 88% 69.4M 2s\n", + "529300K .......... .......... .......... .......... .......... 89% 14.6M 2s\n", + "529350K .......... .......... .......... .......... .......... 89% 53.6M 2s\n", + "529400K .......... .......... .......... .......... .......... 89% 58.2M 2s\n", + "529450K .......... .......... .......... .......... .......... 89% 17.9M 2s\n", + "529500K .......... .......... .......... .......... .......... 89% 50.7M 2s\n", + "529550K .......... .......... .......... .......... .......... 89% 68.7M 2s\n", + "529600K .......... .......... .......... .......... .......... 89% 17.9M 2s\n", + "529650K .......... .......... .......... .......... .......... 89% 40.7M 2s\n", + "529700K .......... .......... .......... .......... .......... 89% 68.7M 2s\n", + "529750K .......... .......... .......... .......... .......... 89% 19.4M 2s\n", + "529800K .......... .......... .......... .......... .......... 89% 30.1M 2s\n", + "529850K .......... .......... .......... .......... .......... 89% 71.2M 2s\n", + "529900K .......... .......... .......... .......... .......... 89% 24.2M 2s\n", + "529950K .......... .......... .......... .......... .......... 89% 42.7M 2s\n", + "530000K .......... .......... .......... .......... .......... 89% 49.4M 2s\n", + "530050K .......... .......... .......... .......... .......... 89% 19.8M 2s\n", + "530100K .......... .......... .......... .......... .......... 89% 34.7M 2s\n", + "530150K .......... .......... .......... .......... .......... 89% 63.7M 2s\n", + "530200K .......... .......... .......... .......... .......... 89% 18.6M 2s\n", + "530250K .......... .......... .......... .......... .......... 89% 44.8M 2s\n", + "530300K .......... .......... .......... .......... .......... 89% 56.3M 2s\n", + "530350K .......... .......... .......... .......... .......... 89% 20.8M 2s\n", + "530400K .......... .......... .......... .......... .......... 89% 34.5M 2s\n", + "530450K .......... .......... .......... .......... .......... 89% 54.8M 2s\n", + "530500K .......... .......... .......... .......... .......... 89% 22.9M 2s\n", + "530550K .......... .......... .......... .......... .......... 89% 7.74M 2s\n", + "530600K .......... .......... .......... .......... .......... 89% 53.8M 2s\n", + "530650K .......... .......... .......... .......... .......... 89% 65.3M 2s\n", + "530700K .......... .......... .......... .......... .......... 89% 65.2M 2s\n", + "530750K .......... .......... .......... .......... .......... 89% 14.4M 2s\n", + "530800K .......... .......... .......... .......... .......... 89% 63.2M 2s\n", + "530850K .......... .......... .......... .......... .......... 89% 5.32M 2s\n", + "530900K .......... .......... .......... .......... .......... 89% 59.4M 2s\n", + "530950K .......... .......... .......... .......... .......... 89% 69.2M 2s\n", + "531000K .......... .......... .......... .......... .......... 89% 52.5M 2s\n", + "531050K .......... .......... .......... .......... .......... 89% 15.9M 2s\n", + "531100K .......... .......... .......... .......... .......... 89% 67.3M 2s\n", + "531150K .......... .......... .......... .......... .......... 89% 12.7M 2s\n", + "531200K .......... .......... .......... .......... .......... 89% 52.2M 2s\n", + "531250K .......... .......... .......... .......... .......... 89% 15.3M 2s\n", + "531300K .......... .......... .......... .......... .......... 89% 52.6M 2s\n", + "531350K .......... .......... .......... .......... .......... 89% 43.8M 2s\n", + "531400K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", + "531450K .......... .......... .......... .......... .......... 89% 67.8M 2s\n", + "531500K .......... .......... .......... .......... .......... 89% 13.2M 2s\n", + "531550K .......... .......... .......... .......... .......... 89% 67.0M 2s\n", + "531600K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", + "531650K .......... .......... .......... .......... .......... 89% 13.7M 2s\n", + "531700K .......... .......... .......... .......... .......... 89% 46.8M 2s\n", + "531750K .......... .......... .......... .......... .......... 89% 51.0M 2s\n", + "531800K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", + "531850K .......... .......... .......... .......... .......... 89% 46.3M 2s\n", + "531900K .......... .......... .......... .......... .......... 89% 57.1M 2s\n", + "531950K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", + "532000K .......... .......... .......... .......... .......... 89% 18.5M 2s\n", + "532050K .......... .......... .......... .......... .......... 89% 22.5M 2s\n", + "532100K .......... .......... .......... .......... .......... 89% 61.2M 2s\n", + "532150K .......... .......... .......... .......... .......... 89% 15.2M 2s\n", + "532200K .......... .......... .......... .......... .......... 89% 40.5M 2s\n", + "532250K .......... .......... .......... .......... .......... 89% 15.1M 2s\n", + "532300K .......... .......... .......... .......... .......... 89% 41.9M 2s\n", + "532350K .......... .......... .......... .......... .......... 89% 69.8M 2s\n", + "532400K .......... .......... .......... .......... .......... 89% 12.8M 2s\n", + "532450K .......... .......... .......... .......... .......... 89% 71.5M 2s\n", + "532500K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", + "532550K .......... .......... .......... .......... .......... 89% 30.6M 2s\n", + "532600K .......... .......... .......... .......... .......... 89% 15.8M 2s\n", + "532650K .......... .......... .......... .......... .......... 89% 36.2M 2s\n", + "532700K .......... .......... .......... .......... .......... 89% 16.3M 2s\n", + "532750K .......... .......... .......... .......... .......... 89% 38.5M 2s\n", + "532800K .......... .......... .......... .......... .......... 89% 16.3M 2s\n", + "532850K .......... .......... .......... .......... .......... 89% 48.0M 2s\n", + "532900K .......... .......... .......... .......... .......... 89% 43.2M 2s\n", + "532950K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", + "533000K .......... .......... .......... .......... .......... 89% 36.2M 2s\n", + "533050K .......... .......... .......... .......... .......... 89% 16.2M 2s\n", + "533100K .......... .......... .......... .......... .......... 89% 40.8M 2s\n", + "533150K .......... .......... .......... .......... .......... 89% 3.77M 2s\n", + "533200K .......... .......... .......... .......... .......... 89% 58.6M 2s\n", + "533250K .......... .......... .......... .......... .......... 89% 14.9M 2s\n", + "533300K .......... .......... .......... .......... .......... 89% 9.77M 2s\n", + "533350K .......... .......... .......... .......... .......... 89% 69.5M 2s\n", + "533400K .......... .......... .......... .......... .......... 89% 12.9M 2s\n", + "533450K .......... .......... .......... .......... .......... 89% 11.9M 2s\n", + "533500K .......... .......... .......... .......... .......... 89% 55.1M 2s\n", + "533550K .......... .......... .......... .......... .......... 89% 12.2M 2s\n", + "533600K .......... .......... .......... .......... .......... 89% 10.8M 2s\n", + "533650K .......... .......... .......... .......... .......... 89% 53.1M 2s\n", + "533700K .......... .......... .......... .......... .......... 89% 12.3M 2s\n", + "533750K .......... .......... .......... .......... .......... 89% 4.25M 2s\n", + "533800K .......... .......... .......... .......... .......... 89% 51.3M 2s\n", + "533850K .......... .......... .......... .......... .......... 89% 11.0M 2s\n", + "533900K .......... .......... .......... .......... .......... 89% 13.2M 2s\n", + "533950K .......... .......... .......... .......... .......... 89% 51.0M 2s\n", + "534000K .......... .......... .......... .......... .......... 89% 11.8M 2s\n", + "534050K .......... .......... .......... .......... .......... 89% 11.6M 2s\n", + "534100K .......... .......... .......... .......... .......... 89% 52.2M 2s\n", + "534150K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", + "534200K .......... .......... .......... .......... .......... 89% 11.6M 2s\n", + "534250K .......... .......... .......... .......... .......... 89% 29.3M 2s\n", + "534300K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", + "534350K .......... .......... .......... .......... .......... 89% 70.7M 2s\n", + "534400K .......... .......... .......... .......... .......... 89% 11.8M 2s\n", + "534450K .......... .......... .......... .......... .......... 89% 14.0M 2s\n", + "534500K .......... .......... .......... .......... .......... 89% 10.4M 2s\n", + "534550K .......... .......... .......... .......... .......... 89% 52.9M 2s\n", + "534600K .......... .......... .......... .......... .......... 89% 14.0M 2s\n", + "534650K .......... .......... .......... .......... .......... 89% 36.3M 2s\n", + "534700K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", + "534750K .......... .......... .......... .......... .......... 89% 65.4M 2s\n", + "534800K .......... .......... .......... .......... .......... 89% 11.2M 2s\n", + "534850K .......... .......... .......... .......... .......... 89% 15.7M 2s\n", + "534900K .......... .......... .......... .......... .......... 89% 29.6M 2s\n", + "534950K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", + "535000K .......... .......... .......... .......... .......... 89% 11.2M 2s\n", + "535050K .......... .......... .......... .......... .......... 89% 50.7M 2s\n", + "535100K .......... .......... .......... .......... .......... 89% 12.0M 2s\n", + "535150K .......... .......... .......... .......... .......... 89% 55.5M 2s\n", + "535200K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", + "535250K .......... .......... .......... .......... .......... 90% 51.2M 2s\n", + "535300K .......... .......... .......... .......... .......... 90% 12.9M 2s\n", + "535350K .......... .......... .......... .......... .......... 90% 48.9M 2s\n", + "535400K .......... .......... .......... .......... .......... 90% 12.1M 2s\n", + "535450K .......... .......... .......... .......... .......... 90% 14.0M 2s\n", + "535500K .......... .......... .......... .......... .......... 90% 40.5M 2s\n", + "535550K .......... .......... .......... .......... .......... 90% 12.8M 2s\n", + "535600K .......... .......... .......... .......... .......... 90% 41.6M 2s\n", + "535650K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", + "535700K .......... .......... .......... .......... .......... 90% 45.3M 2s\n", + "535750K .......... .......... .......... .......... .......... 90% 15.1M 2s\n", + "535800K .......... .......... .......... .......... .......... 90% 12.7M 2s\n", + "535850K .......... .......... .......... .......... .......... 90% 31.2M 2s\n", + "535900K .......... .......... .......... .......... .......... 90% 15.5M 2s\n", + "535950K .......... .......... .......... .......... .......... 90% 32.2M 2s\n", + "536000K .......... .......... .......... .......... .......... 90% 15.8M 2s\n", + "536050K .......... .......... .......... .......... .......... 90% 35.9M 2s\n", + "536100K .......... .......... .......... .......... .......... 90% 14.8M 2s\n", + "536150K .......... .......... .......... .......... .......... 90% 42.8M 2s\n", + "536200K .......... .......... .......... .......... .......... 90% 13.9M 2s\n", + "536250K .......... .......... .......... .......... .......... 90% 33.5M 2s\n", + "536300K .......... .......... .......... .......... .......... 90% 15.9M 2s\n", + "536350K .......... .......... .......... .......... .......... 90% 38.3M 2s\n", + "536400K .......... .......... .......... .......... .......... 90% 15.7M 2s\n", + "536450K .......... .......... .......... .......... .......... 90% 32.1M 2s\n", + "536500K .......... .......... .......... .......... .......... 90% 17.0M 2s\n", + "536550K .......... .......... .......... .......... .......... 90% 32.6M 2s\n", + "536600K .......... .......... .......... .......... .......... 90% 14.2M 2s\n", + "536650K .......... .......... .......... .......... .......... 90% 14.5M 2s\n", + "536700K .......... .......... .......... .......... .......... 90% 41.3M 2s\n", + "536750K .......... .......... .......... .......... .......... 90% 14.7M 2s\n", + "536800K .......... .......... .......... .......... .......... 90% 36.4M 2s\n", + "536850K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", + "536900K .......... .......... .......... .......... .......... 90% 47.6M 2s\n", + "536950K .......... .......... .......... .......... .......... 90% 62.2M 2s\n", + "537000K .......... .......... .......... .......... .......... 90% 13.4M 2s\n", + "537050K .......... .......... .......... .......... .......... 90% 13.1M 2s\n", + "537100K .......... .......... .......... .......... .......... 90% 46.2M 2s\n", + "537150K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", + "537200K .......... .......... .......... .......... .......... 90% 49.1M 2s\n", + "537250K .......... .......... .......... .......... .......... 90% 60.6M 2s\n", + "537300K .......... .......... .......... .......... .......... 90% 13.4M 2s\n", + "537350K .......... .......... .......... .......... .......... 90% 61.3M 2s\n", + "537400K .......... .......... .......... .......... .......... 90% 12.7M 2s\n", + "537450K .......... .......... .......... .......... .......... 90% 62.2M 2s\n", + "537500K .......... .......... .......... .......... .......... 90% 13.0M 2s\n", + "537550K .......... .......... .......... .......... .......... 90% 58.8M 2s\n", + "537600K .......... .......... .......... .......... .......... 90% 14.6M 2s\n", + "537650K .......... .......... .......... .......... .......... 90% 49.6M 1s\n", + "537700K .......... .......... .......... .......... .......... 90% 14.5M 1s\n", + "537750K .......... .......... .......... .......... .......... 90% 51.4M 1s\n", + "537800K .......... .......... .......... .......... .......... 90% 13.1M 1s\n", + "537850K .......... .......... .......... .......... .......... 90% 58.0M 1s\n", + "537900K .......... .......... .......... .......... .......... 90% 15.4M 1s\n", + "537950K .......... .......... .......... .......... .......... 90% 48.7M 1s\n", + "538000K .......... .......... .......... .......... .......... 90% 16.7M 1s\n", + "538050K .......... .......... .......... .......... .......... 90% 30.6M 1s\n", + "538100K .......... .......... .......... .......... .......... 90% 4.25M 1s\n", + "538150K .......... .......... .......... .......... .......... 90% 65.2M 1s\n", + "538200K .......... .......... .......... .......... .......... 90% 12.0M 1s\n", + "538250K .......... .......... .......... .......... .......... 90% 56.5M 1s\n", + "538300K .......... .......... .......... .......... .......... 90% 13.9M 1s\n", + "538350K .......... .......... .......... .......... .......... 90% 58.2M 1s\n", + "538400K .......... .......... .......... .......... .......... 90% 58.6M 1s\n", + "538450K .......... .......... .......... .......... .......... 90% 13.1M 1s\n", + "538500K .......... .......... .......... .......... .......... 90% 65.0M 1s\n", + "538550K .......... .......... .......... .......... .......... 90% 13.3M 1s\n", + "538600K .......... .......... .......... .......... .......... 90% 51.6M 1s\n", + "538650K .......... .......... .......... .......... .......... 90% 15.7M 1s\n", + "538700K .......... .......... .......... .......... .......... 90% 61.2M 1s\n", + "538750K .......... .......... .......... .......... .......... 90% 14.3M 1s\n", + "538800K .......... .......... .......... .......... .......... 90% 45.0M 1s\n", + "538850K .......... .......... .......... .......... .......... 90% 55.4M 1s\n", + "538900K .......... .......... .......... .......... .......... 90% 15.0M 1s\n", + "538950K .......... .......... .......... .......... .......... 90% 48.5M 1s\n", + "539000K .......... .......... .......... .......... .......... 90% 15.6M 1s\n", + "539050K .......... .......... .......... .......... .......... 90% 54.4M 1s\n", + "539100K .......... .......... .......... .......... .......... 90% 16.0M 1s\n", + "539150K .......... .......... .......... .......... .......... 90% 37.0M 1s\n", + "539200K .......... .......... .......... .......... .......... 90% 47.8M 1s\n", + "539250K .......... .......... .......... .......... .......... 90% 17.2M 1s\n", + "539300K .......... .......... .......... .......... .......... 90% 33.4M 1s\n", + "539350K .......... .......... .......... .......... .......... 90% 19.5M 1s\n", + "539400K .......... .......... .......... .......... .......... 90% 26.8M 1s\n", + "539450K .......... .......... .......... .......... .......... 90% 18.7M 1s\n", + "539500K .......... .......... .......... .......... .......... 90% 33.9M 1s\n", + "539550K .......... .......... .......... .......... .......... 90% 52.1M 1s\n", + "539600K .......... .......... .......... .......... .......... 90% 19.3M 1s\n", + "539650K .......... .......... .......... .......... .......... 90% 27.9M 1s\n", + "539700K .......... .......... .......... .......... .......... 90% 20.2M 1s\n", + "539750K .......... .......... .......... .......... .......... 90% 43.9M 1s\n", + "539800K .......... .......... .......... .......... .......... 90% 39.6M 1s\n", + "539850K .......... .......... .......... .......... .......... 90% 17.4M 1s\n", + "539900K .......... .......... .......... .......... .......... 90% 37.2M 1s\n", + "539950K .......... .......... .......... .......... .......... 90% 17.8M 1s\n", + "540000K .......... .......... .......... .......... .......... 90% 47.9M 1s\n", + "540050K .......... .......... .......... .......... .......... 90% 43.2M 1s\n", + "540100K .......... .......... .......... .......... .......... 90% 3.31M 1s\n", + "540150K .......... .......... .......... .......... .......... 90% 66.6M 1s\n", + "540200K .......... .......... .......... .......... .......... 90% 12.4M 1s\n", + "540250K .......... .......... .......... .......... .......... 90% 56.2M 1s\n", + "540300K .......... .......... .......... .......... .......... 90% 65.5M 1s\n", + "540350K .......... .......... .......... .......... .......... 90% 12.3M 1s\n", + "540400K .......... .......... .......... .......... .......... 90% 34.6M 1s\n", + "540450K .......... .......... .......... .......... .......... 90% 38.4M 1s\n", + "540500K .......... .......... .......... .......... .......... 90% 22.2M 1s\n", + "540550K .......... .......... .......... .......... .......... 90% 40.7M 1s\n", + "540600K .......... .......... .......... .......... .......... 90% 3.72M 1s\n", + "540650K .......... .......... .......... .......... .......... 90% 55.6M 1s\n", + "540700K .......... .......... .......... .......... .......... 90% 52.4M 1s\n", + "540750K .......... .......... .......... .......... .......... 90% 55.5M 1s\n", + "540800K .......... .......... .......... .......... .......... 90% 27.7M 1s\n", + "540850K .......... .......... .......... .......... .......... 90% 9.24M 1s\n", + "540900K .......... .......... .......... .......... .......... 90% 14.2M 1s\n", + "540950K .......... .......... .......... .......... .......... 90% 41.5M 1s\n", + "541000K .......... .......... .......... .......... .......... 90% 12.5M 1s\n", + "541050K .......... .......... .......... .......... .......... 90% 68.8M 1s\n", + "541100K .......... .......... .......... .......... .......... 90% 13.6M 1s\n", + "541150K .......... .......... .......... .......... .......... 90% 12.8M 1s\n", + "541200K .......... .......... .......... .......... .......... 91% 32.1M 1s\n", + "541250K .......... .......... .......... .......... .......... 91% 68.0M 1s\n", + "541300K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", + "541350K .......... .......... .......... .......... .......... 91% 54.9M 1s\n", + "541400K .......... .......... .......... .......... .......... 91% 11.2M 1s\n", + "541450K .......... .......... .......... .......... .......... 91% 14.9M 1s\n", + "541500K .......... .......... .......... .......... .......... 91% 43.4M 1s\n", + "541550K .......... .......... .......... .......... .......... 91% 14.0M 1s\n", + "541600K .......... .......... .......... .......... .......... 91% 35.4M 1s\n", + "541650K .......... .......... .......... .......... .......... 91% 14.2M 1s\n", + "541700K .......... .......... .......... .......... .......... 91% 43.5M 1s\n", + "541750K .......... .......... .......... .......... .......... 91% 14.4M 1s\n", + "541800K .......... .......... .......... .......... .......... 91% 33.5M 1s\n", + "541850K .......... .......... .......... .......... .......... 91% 16.9M 1s\n", + "541900K .......... .......... .......... .......... .......... 91% 25.3M 1s\n", + "541950K .......... .......... .......... .......... .......... 91% 18.6M 1s\n", + "542000K .......... .......... .......... .......... .......... 91% 28.5M 1s\n", + "542050K .......... .......... .......... .......... .......... 91% 15.2M 1s\n", + "542100K .......... .......... .......... .......... .......... 91% 37.4M 1s\n", + "542150K .......... .......... .......... .......... .......... 91% 49.5M 1s\n", + "542200K .......... .......... .......... .......... .......... 91% 13.2M 1s\n", + "542250K .......... .......... .......... .......... .......... 91% 14.8M 1s\n", + "542300K .......... .......... .......... .......... .......... 91% 60.4M 1s\n", + "542350K .......... .......... .......... .......... .......... 91% 50.2M 1s\n", + "542400K .......... .......... .......... .......... .......... 91% 12.6M 1s\n", + "542450K .......... .......... .......... .......... .......... 91% 53.1M 1s\n", + "542500K .......... .......... .......... .......... .......... 91% 16.8M 1s\n", + "542550K .......... .......... .......... .......... .......... 91% 38.5M 1s\n", + "542600K .......... .......... .......... .......... .......... 91% 13.3M 1s\n", + "542650K .......... .......... .......... .......... .......... 91% 48.5M 1s\n", + "542700K .......... .......... .......... .......... .......... 91% 16.1M 1s\n", + "542750K .......... .......... .......... .......... .......... 91% 42.1M 1s\n", + "542800K .......... .......... .......... .......... .......... 91% 15.3M 1s\n", + "542850K .......... .......... .......... .......... .......... 91% 38.6M 1s\n", + "542900K .......... .......... .......... .......... .......... 91% 16.1M 1s\n", + "542950K .......... .......... .......... .......... .......... 91% 54.0M 1s\n", + "543000K .......... .......... .......... .......... .......... 91% 12.8M 1s\n", + "543050K .......... .......... .......... .......... .......... 91% 41.3M 1s\n", + "543100K .......... .......... .......... .......... .......... 91% 15.6M 1s\n", + "543150K .......... .......... .......... .......... .......... 91% 44.6M 1s\n", + "543200K .......... .......... .......... .......... .......... 91% 47.6M 1s\n", + "543250K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", + "543300K .......... .......... .......... .......... .......... 91% 44.4M 1s\n", + "543350K .......... .......... .......... .......... .......... 91% 14.7M 1s\n", + "543400K .......... .......... .......... .......... .......... 91% 39.2M 1s\n", + "543450K .......... .......... .......... .......... .......... 91% 13.3M 1s\n", + "543500K .......... .......... .......... .......... .......... 91% 44.7M 1s\n", + "543550K .......... .......... .......... .......... .......... 91% 17.6M 1s\n", + "543600K .......... .......... .......... .......... .......... 91% 43.8M 1s\n", + "543650K .......... .......... .......... .......... .......... 91% 53.0M 1s\n", + "543700K .......... .......... .......... .......... .......... 91% 14.7M 1s\n", + "543750K .......... .......... .......... .......... .......... 91% 42.2M 1s\n", + "543800K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", + "543850K .......... .......... .......... .......... .......... 91% 57.9M 1s\n", + "543900K .......... .......... .......... .......... .......... 91% 14.8M 1s\n", + "543950K .......... .......... .......... .......... .......... 91% 45.9M 1s\n", + "544000K .......... .......... .......... .......... .......... 91% 14.5M 1s\n", + "544050K .......... .......... .......... .......... .......... 91% 53.0M 1s\n", + "544100K .......... .......... .......... .......... .......... 91% 45.0M 1s\n", + "544150K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", + "544200K .......... .......... .......... .......... .......... 91% 42.5M 1s\n", + "544250K .......... .......... .......... .......... .......... 91% 17.4M 1s\n", + "544300K .......... .......... .......... .......... .......... 91% 31.8M 1s\n", + "544350K .......... .......... .......... .......... .......... 91% 18.2M 1s\n", + "544400K .......... .......... .......... .......... .......... 91% 38.3M 1s\n", + "544450K .......... .......... .......... .......... .......... 91% 39.9M 1s\n", + "544500K .......... .......... .......... .......... .......... 91% 16.7M 1s\n", + "544550K .......... .......... .......... .......... .......... 91% 29.1M 1s\n", + "544600K .......... .......... .......... .......... .......... 91% 17.9M 1s\n", + "544650K .......... .......... .......... .......... .......... 91% 28.5M 1s\n", + "544700K .......... .......... .......... .......... .......... 91% 37.5M 1s\n", + "544750K .......... .......... .......... .......... .......... 91% 22.3M 1s\n", + "544800K .......... .......... .......... .......... .......... 91% 29.4M 1s\n", + "544850K .......... .......... .......... .......... .......... 91% 21.2M 1s\n", + "544900K .......... .......... .......... .......... .......... 91% 30.3M 1s\n", + "544950K .......... .......... .......... .......... .......... 91% 38.0M 1s\n", + "545000K .......... .......... .......... .......... .......... 91% 20.0M 1s\n", + "545050K .......... .......... .......... .......... .......... 91% 31.7M 1s\n", + "545100K .......... .......... .......... .......... .......... 91% 22.4M 1s\n", + "545150K .......... .......... .......... .......... .......... 91% 32.5M 1s\n", + "545200K .......... .......... .......... .......... .......... 91% 18.8M 1s\n", + "545250K .......... .......... .......... .......... .......... 91% 34.1M 1s\n", + "545300K .......... .......... .......... .......... .......... 91% 39.0M 1s\n", + "545350K .......... .......... .......... .......... .......... 91% 21.4M 1s\n", + "545400K .......... .......... .......... .......... .......... 91% 18.9M 1s\n", + "545450K .......... .......... .......... .......... .......... 91% 35.5M 1s\n", + "545500K .......... .......... .......... .......... .......... 91% 34.3M 1s\n", + "545550K .......... .......... .......... .......... .......... 91% 20.2M 1s\n", + "545600K .......... .......... .......... .......... .......... 91% 32.8M 1s\n", + "545650K .......... .......... .......... .......... .......... 91% 22.4M 1s\n", + "545700K .......... .......... .......... .......... .......... 91% 30.3M 1s\n", + "545750K .......... .......... .......... .......... .......... 91% 29.7M 1s\n", + "545800K .......... .......... .......... .......... .......... 91% 20.4M 1s\n", + "545850K .......... .......... .......... .......... .......... 91% 50.7M 1s\n", + "545900K .......... .......... .......... .......... .......... 91% 19.0M 1s\n", + "545950K .......... .......... .......... .......... .......... 91% 34.8M 1s\n", + "546000K .......... .......... .......... .......... .......... 91% 31.0M 1s\n", + "546050K .......... .......... .......... .......... .......... 91% 26.2M 1s\n", + "546100K .......... .......... .......... .......... .......... 91% 26.9M 1s\n", + "546150K .......... .......... .......... .......... .......... 91% 41.8M 1s\n", + "546200K .......... .......... .......... .......... .......... 91% 21.3M 1s\n", + "546250K .......... .......... .......... .......... .......... 91% 28.3M 1s\n", + "546300K .......... .......... .......... .......... .......... 91% 33.4M 1s\n", + "546350K .......... .......... .......... .......... .......... 91% 22.5M 1s\n", + "546400K .......... .......... .......... .......... .......... 91% 41.3M 1s\n", + "546450K .......... .......... .......... .......... .......... 91% 23.3M 1s\n", + "546500K .......... .......... .......... .......... .......... 91% 28.1M 1s\n", + "546550K .......... .......... .......... .......... .......... 91% 31.2M 1s\n", + "546600K .......... .......... .......... .......... .......... 91% 20.6M 1s\n", + "546650K .......... .......... .......... .......... .......... 91% 29.2M 1s\n", + "546700K .......... .......... .......... .......... .......... 91% 39.2M 1s\n", + "546750K .......... .......... .......... .......... .......... 91% 28.3M 1s\n", + "546800K .......... .......... .......... .......... .......... 91% 18.6M 1s\n", + "546850K .......... .......... .......... .......... .......... 91% 30.9M 1s\n", + "546900K .......... .......... .......... .......... .......... 91% 54.2M 1s\n", + "546950K .......... .......... .......... .......... .......... 91% 25.8M 1s\n", + "547000K .......... .......... .......... .......... .......... 91% 21.9M 1s\n", + "547050K .......... .......... .......... .......... .......... 91% 42.9M 1s\n", + "547100K .......... .......... .......... .......... .......... 91% 24.5M 1s\n", + "547150K .......... .......... .......... .......... .......... 92% 36.2M 1s\n", + "547200K .......... .......... .......... .......... .......... 92% 25.3M 1s\n", + "547250K .......... .......... .......... .......... .......... 92% 31.6M 1s\n", + "547300K .......... .......... .......... .......... .......... 92% 27.6M 1s\n", + "547350K .......... .......... .......... .......... .......... 92% 41.0M 1s\n", + "547400K .......... .......... .......... .......... .......... 92% 3.60M 1s\n", + "547450K .......... .......... .......... .......... .......... 92% 43.4M 1s\n", + "547500K .......... .......... .......... .......... .......... 92% 59.0M 1s\n", + "547550K .......... .......... .......... .......... .......... 92% 15.6M 1s\n", + "547600K .......... .......... .......... .......... .......... 92% 48.0M 1s\n", + "547650K .......... .......... .......... .......... .......... 92% 48.7M 1s\n", + "547700K .......... .......... .......... .......... .......... 92% 18.5M 1s\n", + "547750K .......... .......... .......... .......... .......... 92% 57.2M 1s\n", + "547800K .......... .......... .......... .......... .......... 92% 15.0M 1s\n", + "547850K .......... .......... .......... .......... .......... 92% 32.2M 1s\n", + "547900K .......... .......... .......... .......... .......... 92% 37.7M 1s\n", + "547950K .......... .......... .......... .......... .......... 92% 29.3M 1s\n", + "548000K .......... .......... .......... .......... .......... 92% 37.3M 1s\n", + "548050K .......... .......... .......... .......... .......... 92% 61.4M 1s\n", + "548100K .......... .......... .......... .......... .......... 92% 15.7M 1s\n", + "548150K .......... .......... .......... .......... .......... 92% 35.0M 1s\n", + "548200K .......... .......... .......... .......... .......... 92% 24.6M 1s\n", + "548250K .......... .......... .......... .......... .......... 92% 33.2M 1s\n", + "548300K .......... .......... .......... .......... .......... 92% 23.5M 1s\n", + "548350K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", + "548400K .......... .......... .......... .......... .......... 92% 31.8M 1s\n", + "548450K .......... .......... .......... .......... .......... 92% 22.8M 1s\n", + "548500K .......... .......... .......... .......... .......... 92% 67.1M 1s\n", + "548550K .......... .......... .......... .......... .......... 92% 33.7M 1s\n", + "548600K .......... .......... .......... .......... .......... 92% 20.9M 1s\n", + "548650K .......... .......... .......... .......... .......... 92% 46.7M 1s\n", + "548700K .......... .......... .......... .......... .......... 92% 33.6M 1s\n", + "548750K .......... .......... .......... .......... .......... 92% 26.6M 1s\n", + "548800K .......... .......... .......... .......... .......... 92% 36.1M 1s\n", + "548850K .......... .......... .......... .......... .......... 92% 35.9M 1s\n", + "548900K .......... .......... .......... .......... .......... 92% 26.3M 1s\n", + "548950K .......... .......... .......... .......... .......... 92% 37.2M 1s\n", + "549000K .......... .......... .......... .......... .......... 92% 37.5M 1s\n", + "549050K .......... .......... .......... .......... .......... 92% 22.2M 1s\n", + "549100K .......... .......... .......... .......... .......... 92% 53.2M 1s\n", + "549150K .......... .......... .......... .......... .......... 92% 33.2M 1s\n", + "549200K .......... .......... .......... .......... .......... 92% 21.3M 1s\n", + "549250K .......... .......... .......... .......... .......... 92% 61.4M 1s\n", + "549300K .......... .......... .......... .......... .......... 92% 30.0M 1s\n", + "549350K .......... .......... .......... .......... .......... 92% 25.7M 1s\n", + "549400K .......... .......... .......... .......... .......... 92% 41.5M 1s\n", + "549450K .......... .......... .......... .......... .......... 92% 38.1M 1s\n", + "549500K .......... .......... .......... .......... .......... 92% 23.5M 1s\n", + "549550K .......... .......... .......... .......... .......... 92% 58.4M 1s\n", + "549600K .......... .......... .......... .......... .......... 92% 32.1M 1s\n", + "549650K .......... .......... .......... .......... .......... 92% 21.4M 1s\n", + "549700K .......... .......... .......... .......... .......... 92% 75.1M 1s\n", + "549750K .......... .......... .......... .......... .......... 92% 40.8M 1s\n", + "549800K .......... .......... .......... .......... .......... 92% 15.8M 1s\n", + "549850K .......... .......... .......... .......... .......... 92% 51.7M 1s\n", + "549900K .......... .......... .......... .......... .......... 92% 52.0M 1s\n", + "549950K .......... .......... .......... .......... .......... 92% 20.5M 1s\n", + "550000K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", + "550050K .......... .......... .......... .......... .......... 92% 48.1M 1s\n", + "550100K .......... .......... .......... .......... .......... 92% 19.9M 1s\n", + "550150K .......... .......... .......... .......... .......... 92% 50.2M 1s\n", + "550200K .......... .......... .......... .......... .......... 92% 36.9M 1s\n", + "550250K .......... .......... .......... .......... .......... 92% 19.6M 1s\n", + "550300K .......... .......... .......... .......... .......... 92% 53.2M 1s\n", + "550350K .......... .......... .......... .......... .......... 92% 4.32M 1s\n", + "550400K .......... .......... .......... .......... .......... 92% 50.0M 1s\n", + "550450K .......... .......... .......... .......... .......... 92% 71.1M 1s\n", + "550500K .......... .......... .......... .......... .......... 92% 20.1M 1s\n", + "550550K .......... .......... .......... .......... .......... 92% 44.3M 1s\n", + "550600K .......... .......... .......... .......... .......... 92% 62.4M 1s\n", + "550650K .......... .......... .......... .......... .......... 92% 20.0M 1s\n", + "550700K .......... .......... .......... .......... .......... 92% 41.8M 1s\n", + "550750K .......... .......... .......... .......... .......... 92% 57.7M 1s\n", + "550800K .......... .......... .......... .......... .......... 92% 49.9M 1s\n", + "550850K .......... .......... .......... .......... .......... 92% 18.2M 1s\n", + "550900K .......... .......... .......... .......... .......... 92% 64.2M 1s\n", + "550950K .......... .......... .......... .......... .......... 92% 76.2M 1s\n", + "551000K .......... .......... .......... .......... .......... 92% 17.2M 1s\n", + "551050K .......... .......... .......... .......... .......... 92% 37.2M 1s\n", + "551100K .......... .......... .......... .......... .......... 92% 53.0M 1s\n", + "551150K .......... .......... .......... .......... .......... 92% 26.3M 1s\n", + "551200K .......... .......... .......... .......... .......... 92% 40.6M 1s\n", + "551250K .......... .......... .......... .......... .......... 92% 69.7M 1s\n", + "551300K .......... .......... .......... .......... .......... 92% 22.2M 1s\n", + "551350K .......... .......... .......... .......... .......... 92% 26.0M 1s\n", + "551400K .......... .......... .......... .......... .......... 92% 54.6M 1s\n", + "551450K .......... .......... .......... .......... .......... 92% 29.5M 1s\n", + "551500K .......... .......... .......... .......... .......... 92% 49.5M 1s\n", + "551550K .......... .......... .......... .......... .......... 92% 40.3M 1s\n", + "551600K .......... .......... .......... .......... .......... 92% 67.4M 1s\n", + "551650K .......... .......... .......... .......... .......... 92% 23.0M 1s\n", + "551700K .......... .......... .......... .......... .......... 92% 29.5M 1s\n", + "551750K .......... .......... .......... .......... .......... 92% 66.1M 1s\n", + "551800K .......... .......... .......... .......... .......... 92% 22.9M 1s\n", + "551850K .......... .......... .......... .......... .......... 92% 28.9M 1s\n", + "551900K .......... .......... .......... .......... .......... 92% 59.0M 1s\n", + "551950K .......... .......... .......... .......... .......... 92% 37.1M 1s\n", + "552000K .......... .......... .......... .......... .......... 92% 25.4M 1s\n", + "552050K .......... .......... .......... .......... .......... 92% 43.6M 1s\n", + "552100K .......... .......... .......... .......... .......... 92% 71.9M 1s\n", + "552150K .......... .......... .......... .......... .......... 92% 23.1M 1s\n", + "552200K .......... .......... .......... .......... .......... 92% 34.3M 1s\n", + "552250K .......... .......... .......... .......... .......... 92% 68.9M 1s\n", + "552300K .......... .......... .......... .......... .......... 92% 26.8M 1s\n", + "552350K .......... .......... .......... .......... .......... 92% 28.6M 1s\n", + "552400K .......... .......... .......... .......... .......... 92% 38.7M 1s\n", + "552450K .......... .......... .......... .......... .......... 92% 35.1M 1s\n", + "552500K .......... .......... .......... .......... .......... 92% 34.3M 1s\n", + "552550K .......... .......... .......... .......... .......... 92% 43.3M 1s\n", + "552600K .......... .......... .......... .......... .......... 92% 32.7M 1s\n", + "552650K .......... .......... .......... .......... .......... 92% 28.8M 1s\n", + "552700K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", + "552750K .......... .......... .......... .......... .......... 92% 63.8M 1s\n", + "552800K .......... .......... .......... .......... .......... 92% 27.9M 1s\n", + "552850K .......... .......... .......... .......... .......... 92% 29.8M 1s\n", + "552900K .......... .......... .......... .......... .......... 92% 48.1M 1s\n", + "552950K .......... .......... .......... .......... .......... 92% 32.6M 1s\n", + "553000K .......... .......... .......... .......... .......... 92% 31.8M 1s\n", + "553050K .......... .......... .......... .......... .......... 93% 52.9M 1s\n", + "553100K .......... .......... .......... .......... .......... 93% 56.5M 1s\n", + "553150K .......... .......... .......... .......... .......... 93% 29.6M 1s\n", + "553200K .......... .......... .......... .......... .......... 93% 19.4M 1s\n", + "553250K .......... .......... .......... .......... .......... 93% 70.0M 1s\n", + "553300K .......... .......... .......... .......... .......... 93% 40.5M 1s\n", + "553350K .......... .......... .......... .......... .......... 93% 40.5M 1s\n", + "553400K .......... .......... .......... .......... .......... 93% 22.3M 1s\n", + "553450K .......... .......... .......... .......... .......... 93% 52.8M 1s\n", + "553500K .......... .......... .......... .......... .......... 93% 46.2M 1s\n", + "553550K .......... .......... .......... .......... .......... 93% 26.0M 1s\n", + "553600K .......... .......... .......... .......... .......... 93% 22.7M 1s\n", + "553650K .......... .......... .......... .......... .......... 93% 52.9M 1s\n", + "553700K .......... .......... .......... .......... .......... 93% 51.0M 1s\n", + "553750K .......... .......... .......... .......... .......... 93% 55.0M 1s\n", + "553800K .......... .......... .......... .......... .......... 93% 22.1M 1s\n", + "553850K .......... .......... .......... .......... .......... 93% 37.5M 1s\n", + "553900K .......... .......... .......... .......... .......... 93% 40.2M 1s\n", + "553950K .......... .......... .......... .......... .......... 93% 20.1M 1s\n", + "554000K .......... .......... .......... .......... .......... 93% 25.1M 1s\n", + "554050K .......... .......... .......... .......... .......... 93% 31.5M 1s\n", + "554100K .......... .......... .......... .......... .......... 93% 20.4M 1s\n", + "554150K .......... .......... .......... .......... .......... 93% 31.4M 1s\n", + "554200K .......... .......... .......... .......... .......... 93% 47.0M 1s\n", + "554250K .......... .......... .......... .......... .......... 93% 32.9M 1s\n", + "554300K .......... .......... .......... .......... .......... 93% 42.6M 1s\n", + "554350K .......... .......... .......... .......... .......... 93% 33.3M 1s\n", + "554400K .......... .......... .......... .......... .......... 93% 18.3M 1s\n", + "554450K .......... .......... .......... .......... .......... 93% 43.9M 1s\n", + "554500K .......... .......... .......... .......... .......... 93% 56.0M 1s\n", + "554550K .......... .......... .......... .......... .......... 93% 37.9M 1s\n", + "554600K .......... .......... .......... .......... .......... 93% 31.8M 1s\n", + "554650K .......... .......... .......... .......... .......... 93% 57.0M 1s\n", + "554700K .......... .......... .......... .......... .......... 93% 54.2M 1s\n", + "554750K .......... .......... .......... .......... .......... 93% 53.3M 1s\n", + "554800K .......... .......... .......... .......... .......... 93% 32.9M 1s\n", + "554850K .......... .......... .......... .......... .......... 93% 41.7M 1s\n", + "554900K .......... .......... .......... .......... .......... 93% 54.6M 1s\n", + "554950K .......... .......... .......... .......... .......... 93% 55.5M 1s\n", + "555000K .......... .......... .......... .......... .......... 93% 41.6M 1s\n", + "555050K .......... .......... .......... .......... .......... 93% 33.1M 1s\n", + "555100K .......... .......... .......... .......... .......... 93% 59.9M 1s\n", + "555150K .......... .......... .......... .......... .......... 93% 50.1M 1s\n", + "555200K .......... .......... .......... .......... .......... 93% 44.9M 1s\n", + "555250K .......... .......... .......... .......... .......... 93% 27.1M 1s\n", + "555300K .......... .......... .......... .......... .......... 93% 49.6M 1s\n", + "555350K .......... .......... .......... .......... .......... 93% 40.0M 1s\n", + "555400K .......... .......... .......... .......... .......... 93% 28.6M 1s\n", + "555450K .......... .......... .......... .......... .......... 93% 29.9M 1s\n", + "555500K .......... .......... .......... .......... .......... 93% 50.9M 1s\n", + "555550K .......... .......... .......... .......... .......... 93% 62.2M 1s\n", + "555600K .......... .......... .......... .......... .......... 93% 35.3M 1s\n", + "555650K .......... .......... .......... .......... .......... 93% 30.9M 1s\n", + "555700K .......... .......... .......... .......... .......... 93% 31.4M 1s\n", + "555750K .......... .......... .......... .......... .......... 93% 29.6M 1s\n", + "555800K .......... .......... .......... .......... .......... 93% 17.7M 1s\n", + "555850K .......... .......... .......... .......... .......... 93% 32.0M 1s\n", + "555900K .......... .......... .......... .......... .......... 93% 38.7M 1s\n", + "555950K .......... .......... .......... .......... .......... 93% 40.7M 1s\n", + "556000K .......... .......... .......... .......... .......... 93% 48.4M 1s\n", + "556050K .......... .......... .......... .......... .......... 93% 40.6M 1s\n", + "556100K .......... .......... .......... .......... .......... 93% 56.0M 1s\n", + "556150K .......... .......... .......... .......... .......... 93% 30.3M 1s\n", + "556200K .......... .......... .......... .......... .......... 93% 48.0M 1s\n", + "556250K .......... .......... .......... .......... .......... 93% 59.6M 1s\n", + "556300K .......... .......... .......... .......... .......... 93% 43.1M 1s\n", + "556350K .......... .......... .......... .......... .......... 93% 59.8M 1s\n", + "556400K .......... .......... .......... .......... .......... 93% 37.5M 1s\n", + "556450K .......... .......... .......... .......... .......... 93% 65.7M 1s\n", + "556500K .......... .......... .......... .......... .......... 93% 53.1M 1s\n", + "556550K .......... .......... .......... .......... .......... 93% 57.3M 1s\n", + "556600K .......... .......... .......... .......... .......... 93% 38.2M 1s\n", + "556650K .......... .......... .......... .......... .......... 93% 50.7M 1s\n", + "556700K .......... .......... .......... .......... .......... 93% 49.2M 1s\n", + "556750K .......... .......... .......... .......... .......... 93% 30.1M 1s\n", + "556800K .......... .......... .......... .......... .......... 93% 42.9M 1s\n", + "556850K .......... .......... .......... .......... .......... 93% 61.0M 1s\n", + "556900K .......... .......... .......... .......... .......... 93% 37.8M 1s\n", + "556950K .......... .......... .......... .......... .......... 93% 35.1M 1s\n", + "557000K .......... .......... .......... .......... .......... 93% 38.9M 1s\n", + "557050K .......... .......... .......... .......... .......... 93% 60.4M 1s\n", + "557100K .......... .......... .......... .......... .......... 93% 24.1M 1s\n", + "557150K .......... .......... .......... .......... .......... 93% 51.0M 1s\n", + "557200K .......... .......... .......... .......... .......... 93% 4.57M 1s\n", + "557250K .......... .......... .......... .......... .......... 93% 49.4M 1s\n", + "557300K .......... .......... .......... .......... .......... 93% 64.8M 1s\n", + "557350K .......... .......... .......... .......... .......... 93% 57.4M 1s\n", + "557400K .......... .......... .......... .......... .......... 93% 47.1M 1s\n", + "557450K .......... .......... .......... .......... .......... 93% 55.5M 1s\n", + "557500K .......... .......... .......... .......... .......... 93% 45.0M 1s\n", + "557550K .......... .......... .......... .......... .......... 93% 59.4M 1s\n", + "557600K .......... .......... .......... .......... .......... 93% 59.0M 1s\n", + "557650K .......... .......... .......... .......... .......... 93% 65.9M 1s\n", + "557700K .......... .......... .......... .......... .......... 93% 3.98M 1s\n", + "557750K .......... .......... .......... .......... .......... 93% 69.3M 1s\n", + "557800K .......... .......... .......... .......... .......... 93% 56.6M 1s\n", + "557850K .......... .......... .......... .......... .......... 93% 69.6M 1s\n", + "557900K .......... .......... .......... .......... .......... 93% 68.0M 1s\n", + "557950K .......... .......... .......... .......... .......... 93% 68.4M 1s\n", + "558000K .......... .......... .......... .......... .......... 93% 55.2M 1s\n", + "558050K .......... .......... .......... .......... .......... 93% 52.4M 1s\n", + "558100K .......... .......... .......... .......... .......... 93% 62.4M 1s\n", + "558150K .......... .......... .......... .......... .......... 93% 54.9M 1s\n", + "558200K .......... .......... .......... .......... .......... 93% 51.7M 1s\n", + "558250K .......... .......... .......... .......... .......... 93% 30.1M 1s\n", + "558300K .......... .......... .......... .......... .......... 93% 53.5M 1s\n", + "558350K .......... .......... .......... .......... .......... 93% 53.3M 1s\n", + "558400K .......... .......... .......... .......... .......... 93% 57.8M 1s\n", + "558450K .......... .......... .......... .......... .......... 93% 25.8M 1s\n", + "558500K .......... .......... .......... .......... .......... 93% 44.6M 1s\n", + "558550K .......... .......... .......... .......... .......... 93% 61.2M 1s\n", + "558600K .......... .......... .......... .......... .......... 93% 25.3M 1s\n", + "558650K .......... .......... .......... .......... .......... 93% 49.8M 1s\n", + "558700K .......... .......... .......... .......... .......... 93% 57.9M 1s\n", + "558750K .......... .......... .......... .......... .......... 93% 60.9M 1s\n", + "558800K .......... .......... .......... .......... .......... 93% 27.4M 1s\n", + "558850K .......... .......... .......... .......... .......... 93% 54.1M 1s\n", + "558900K .......... .......... .......... .......... .......... 93% 43.4M 1s\n", + "558950K .......... .......... .......... .......... .......... 93% 60.8M 1s\n", + "559000K .......... .......... .......... .......... .......... 94% 31.0M 1s\n", + "559050K .......... .......... .......... .......... .......... 94% 36.1M 1s\n", + "559100K .......... .......... .......... .......... .......... 94% 51.7M 1s\n", + "559150K .......... .......... .......... .......... .......... 94% 55.4M 1s\n", + "559200K .......... .......... .......... .......... .......... 94% 36.7M 1s\n", + "559250K .......... .......... .......... .......... .......... 94% 50.8M 1s\n", + "559300K .......... .......... .......... .......... .......... 94% 48.4M 1s\n", + "559350K .......... .......... .......... .......... .......... 94% 59.9M 1s\n", + "559400K .......... .......... .......... .......... .......... 94% 22.7M 1s\n", + "559450K .......... .......... .......... .......... .......... 94% 44.6M 1s\n", + "559500K .......... .......... .......... .......... .......... 94% 54.9M 1s\n", + "559550K .......... .......... .......... .......... .......... 94% 74.2M 1s\n", + "559600K .......... .......... .......... .......... .......... 94% 29.7M 1s\n", + "559650K .......... .......... .......... .......... .......... 94% 52.0M 1s\n", + "559700K .......... .......... .......... .......... .......... 94% 50.2M 1s\n", + "559750K .......... .......... .......... .......... .......... 94% 65.5M 1s\n", + "559800K .......... .......... .......... .......... .......... 94% 5.91M 1s\n", + "559850K .......... .......... .......... .......... .......... 94% 67.7M 1s\n", + "559900K .......... .......... .......... .......... .......... 94% 58.9M 1s\n", + "559950K .......... .......... .......... .......... .......... 94% 69.3M 1s\n", + "560000K .......... .......... .......... .......... .......... 94% 22.6M 1s\n", + "560050K .......... .......... .......... .......... .......... 94% 43.7M 1s\n", + "560100K .......... .......... .......... .......... .......... 94% 54.9M 1s\n", + "560150K .......... .......... .......... .......... .......... 94% 61.0M 1s\n", + "560200K .......... .......... .......... .......... .......... 94% 34.9M 1s\n", + "560250K .......... .......... .......... .......... .......... 94% 54.6M 1s\n", + "560300K .......... .......... .......... .......... .......... 94% 53.8M 1s\n", + "560350K .......... .......... .......... .......... .......... 94% 61.9M 1s\n", + "560400K .......... .......... .......... .......... .......... 94% 21.3M 1s\n", + "560450K .......... .......... .......... .......... .......... 94% 47.5M 1s\n", + "560500K .......... .......... .......... .......... .......... 94% 50.6M 1s\n", + "560550K .......... .......... .......... .......... .......... 94% 69.8M 1s\n", + "560600K .......... .......... .......... .......... .......... 94% 34.0M 1s\n", + "560650K .......... .......... .......... .......... .......... 94% 40.5M 1s\n", + "560700K .......... .......... .......... .......... .......... 94% 47.1M 1s\n", + "560750K .......... .......... .......... .......... .......... 94% 69.6M 1s\n", + "560800K .......... .......... .......... .......... .......... 94% 59.9M 1s\n", + "560850K .......... .......... .......... .......... .......... 94% 28.6M 1s\n", + "560900K .......... .......... .......... .......... .......... 94% 47.6M 1s\n", + "560950K .......... .......... .......... .......... .......... 94% 55.7M 1s\n", + "561000K .......... .......... .......... .......... .......... 94% 50.6M 1s\n", + "561050K .......... .......... .......... .......... .......... 94% 30.7M 1s\n", + "561100K .......... .......... .......... .......... .......... 94% 46.2M 1s\n", + "561150K .......... .......... .......... .......... .......... 94% 54.3M 1s\n", + "561200K .......... .......... .......... .......... .......... 94% 59.5M 1s\n", + "561250K .......... .......... .......... .......... .......... 94% 31.1M 1s\n", + "561300K .......... .......... .......... .......... .......... 94% 51.9M 1s\n", + "561350K .......... .......... .......... .......... .......... 94% 51.9M 1s\n", + "561400K .......... .......... .......... .......... .......... 94% 46.7M 1s\n", + "561450K .......... .......... .......... .......... .......... 94% 31.7M 1s\n", + "561500K .......... .......... .......... .......... .......... 94% 53.2M 1s\n", + "561550K .......... .......... .......... .......... .......... 94% 47.3M 1s\n", + "561600K .......... .......... .......... .......... .......... 94% 47.2M 1s\n", + "561650K .......... .......... .......... .......... .......... 94% 36.0M 1s\n", + "561700K .......... .......... .......... .......... .......... 94% 54.7M 1s\n", + "561750K .......... .......... .......... .......... .......... 94% 48.0M 1s\n", + "561800K .......... .......... .......... .......... .......... 94% 46.0M 1s\n", + "561850K .......... .......... .......... .......... .......... 94% 33.7M 1s\n", + "561900K .......... .......... .......... .......... .......... 94% 46.0M 1s\n", + "561950K .......... .......... .......... .......... .......... 94% 46.5M 1s\n", + "562000K .......... .......... .......... .......... .......... 94% 46.7M 1s\n", + "562050K .......... .......... .......... .......... .......... 94% 67.9M 1s\n", + "562100K .......... .......... .......... .......... .......... 94% 38.3M 1s\n", + "562150K .......... .......... .......... .......... .......... 94% 38.9M 1s\n", + "562200K .......... .......... .......... .......... .......... 94% 48.3M 1s\n", + "562250K .......... .......... .......... .......... .......... 94% 64.6M 1s\n", + "562300K .......... .......... .......... .......... .......... 94% 38.3M 1s\n", + "562350K .......... .......... .......... .......... .......... 94% 8.87M 1s\n", + "562400K .......... .......... .......... .......... .......... 94% 57.3M 1s\n", + "562450K .......... .......... .......... .......... .......... 94% 67.0M 1s\n", + "562500K .......... .......... .......... .......... .......... 94% 59.6M 1s\n", + "562550K .......... .......... .......... .......... .......... 94% 38.4M 1s\n", + "562600K .......... .......... .......... .......... .......... 94% 52.8M 1s\n", + "562650K .......... .......... .......... .......... .......... 94% 6.01M 1s\n", + "562700K .......... .......... .......... .......... .......... 94% 37.5M 1s\n", + "562750K .......... .......... .......... .......... .......... 94% 53.5M 1s\n", + "562800K .......... .......... .......... .......... .......... 94% 22.7M 1s\n", + "562850K .......... .......... .......... .......... .......... 94% 49.0M 1s\n", + "562900K .......... .......... .......... .......... .......... 94% 65.0M 1s\n", + "562950K .......... .......... .......... .......... .......... 94% 17.3M 1s\n", + "563000K .......... .......... .......... .......... .......... 94% 41.0M 1s\n", + "563050K .......... .......... .......... .......... .......... 94% 64.2M 1s\n", + "563100K .......... .......... .......... .......... .......... 94% 20.1M 1s\n", + "563150K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", + "563200K .......... .......... .......... .......... .......... 94% 55.8M 1s\n", + "563250K .......... .......... .......... .......... .......... 94% 17.0M 1s\n", + "563300K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", + "563350K .......... .......... .......... .......... .......... 94% 60.3M 1s\n", + "563400K .......... .......... .......... .......... .......... 94% 16.3M 1s\n", + "563450K .......... .......... .......... .......... .......... 94% 49.7M 1s\n", + "563500K .......... .......... .......... .......... .......... 94% 62.0M 1s\n", + "563550K .......... .......... .......... .......... .......... 94% 19.9M 1s\n", + "563600K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", + "563650K .......... .......... .......... .......... .......... 94% 62.5M 1s\n", + "563700K .......... .......... .......... .......... .......... 94% 17.3M 1s\n", + "563750K .......... .......... .......... .......... .......... 94% 54.0M 1s\n", + "563800K .......... .......... .......... .......... .......... 94% 50.7M 1s\n", + "563850K .......... .......... .......... .......... .......... 94% 18.9M 1s\n", + "563900K .......... .......... .......... .......... .......... 94% 55.9M 1s\n", + "563950K .......... .......... .......... .......... .......... 94% 55.5M 1s\n", + "564000K .......... .......... .......... .......... .......... 94% 15.8M 1s\n", + "564050K .......... .......... .......... .......... .......... 94% 46.3M 1s\n", + "564100K .......... .......... .......... .......... .......... 94% 52.9M 1s\n", + "564150K .......... .......... .......... .......... .......... 94% 70.0M 1s\n", + "564200K .......... .......... .......... .......... .......... 94% 19.5M 1s\n", + "564250K .......... .......... .......... .......... .......... 94% 56.2M 1s\n", + "564300K .......... .......... .......... .......... .......... 94% 70.0M 1s\n", + "564350K .......... .......... .......... .......... .......... 94% 17.6M 1s\n", + "564400K .......... .......... .......... .......... .......... 94% 46.8M 1s\n", + "564450K .......... .......... .......... .......... .......... 94% 65.8M 1s\n", + "564500K .......... .......... .......... .......... .......... 94% 19.0M 1s\n", + "564550K .......... .......... .......... .......... .......... 94% 5.59M 1s\n", + "564600K .......... .......... .......... .......... .......... 94% 53.7M 1s\n", + "564650K .......... .......... .......... .......... .......... 94% 65.1M 1s\n", + "564700K .......... .......... .......... .......... .......... 94% 63.0M 1s\n", + "564750K .......... .......... .......... .......... .......... 94% 20.0M 1s\n", + "564800K .......... .......... .......... .......... .......... 94% 53.8M 1s\n", + "564850K .......... .......... .......... .......... .......... 94% 66.0M 1s\n", + "564900K .......... .......... .......... .......... .......... 94% 18.5M 1s\n", + "564950K .......... .......... .......... .......... .......... 95% 48.7M 1s\n", + "565000K .......... .......... .......... .......... .......... 95% 16.4M 1s\n", + "565050K .......... .......... .......... .......... .......... 95% 59.8M 1s\n", + "565100K .......... .......... .......... .......... .......... 95% 49.3M 1s\n", + "565150K .......... .......... .......... .......... .......... 95% 65.3M 1s\n", + "565200K .......... .......... .......... .......... .......... 95% 23.9M 1s\n", + "565250K .......... .......... .......... .......... .......... 95% 60.2M 1s\n", + "565300K .......... .......... .......... .......... .......... 95% 50.1M 1s\n", + "565350K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", + "565400K .......... .......... .......... .......... .......... 95% 17.9M 1s\n", + "565450K .......... .......... .......... .......... .......... 95% 51.7M 1s\n", + "565500K .......... .......... .......... .......... .......... 95% 56.3M 1s\n", + "565550K .......... .......... .......... .......... .......... 95% 3.78M 1s\n", + "565600K .......... .......... .......... .......... .......... 95% 40.2M 1s\n", + "565650K .......... .......... .......... .......... .......... 95% 54.5M 1s\n", + "565700K .......... .......... .......... .......... .......... 95% 65.5M 1s\n", + "565750K .......... .......... .......... .......... .......... 95% 20.0M 1s\n", + "565800K .......... .......... .......... .......... .......... 95% 45.5M 1s\n", + "565850K .......... .......... .......... .......... .......... 95% 69.1M 1s\n", + "565900K .......... .......... .......... .......... .......... 95% 19.1M 1s\n", + "565950K .......... .......... .......... .......... .......... 95% 33.3M 1s\n", + "566000K .......... .......... .......... .......... .......... 95% 41.5M 1s\n", + "566050K .......... .......... .......... .......... .......... 95% 52.1M 1s\n", + "566100K .......... .......... .......... .......... .......... 95% 36.1M 1s\n", + "566150K .......... .......... .......... .......... .......... 95% 39.6M 1s\n", + "566200K .......... .......... .......... .......... .......... 95% 55.6M 1s\n", + "566250K .......... .......... .......... .......... .......... 95% 18.8M 1s\n", + "566300K .......... .......... .......... .......... .......... 95% 33.6M 1s\n", + "566350K .......... .......... .......... .......... .......... 95% 74.4M 1s\n", + "566400K .......... .......... .......... .......... .......... 95% 5.03M 1s\n", + "566450K .......... .......... .......... .......... .......... 95% 64.6M 1s\n", + "566500K .......... .......... .......... .......... .......... 95% 67.5M 1s\n", + "566550K .......... .......... .......... .......... .......... 95% 67.6M 1s\n", + "566600K .......... .......... .......... .......... .......... 95% 7.14M 1s\n", + "566650K .......... .......... .......... .......... .......... 95% 70.1M 1s\n", + "566700K .......... .......... .......... .......... .......... 95% 70.4M 1s\n", + "566750K .......... .......... .......... .......... .......... 95% 14.9M 1s\n", + "566800K .......... .......... .......... .......... .......... 95% 7.50M 1s\n", + "566850K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", + "566900K .......... .......... .......... .......... .......... 95% 59.2M 1s\n", + "566950K .......... .......... .......... .......... .......... 95% 69.6M 1s\n", + "567000K .......... .......... .......... .......... .......... 95% 18.1M 1s\n", + "567050K .......... .......... .......... .......... .......... 95% 4.20M 1s\n", + "567100K .......... .......... .......... .......... .......... 95% 56.4M 1s\n", + "567150K .......... .......... .......... .......... .......... 95% 65.9M 1s\n", + "567200K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", + "567250K .......... .......... .......... .......... .......... 95% 16.6M 1s\n", + "567300K .......... .......... .......... .......... .......... 95% 69.6M 1s\n", + "567350K .......... .......... .......... .......... .......... 95% 14.5M 1s\n", + "567400K .......... .......... .......... .......... .......... 95% 35.1M 1s\n", + "567450K .......... .......... .......... .......... .......... 95% 17.0M 1s\n", + "567500K .......... .......... .......... .......... .......... 95% 52.9M 1s\n", + "567550K .......... .......... .......... .......... .......... 95% 66.8M 1s\n", + "567600K .......... .......... .......... .......... .......... 95% 15.2M 1s\n", + "567650K .......... .......... .......... .......... .......... 95% 51.1M 1s\n", + "567700K .......... .......... .......... .......... .......... 95% 15.3M 1s\n", + "567750K .......... .......... .......... .......... .......... 95% 53.5M 1s\n", + "567800K .......... .......... .......... .......... .......... 95% 14.1M 1s\n", + "567850K .......... .......... .......... .......... .......... 95% 45.0M 1s\n", + "567900K .......... .......... .......... .......... .......... 95% 54.2M 1s\n", + "567950K .......... .......... .......... .......... .......... 95% 17.5M 1s\n", + "568000K .......... .......... .......... .......... .......... 95% 38.7M 1s\n", + "568050K .......... .......... .......... .......... .......... 95% 62.3M 1s\n", + "568100K .......... .......... .......... .......... .......... 95% 14.1M 1s\n", + "568150K .......... .......... .......... .......... .......... 95% 53.0M 1s\n", + "568200K .......... .......... .......... .......... .......... 95% 16.6M 1s\n", + "568250K .......... .......... .......... .......... .......... 95% 32.4M 1s\n", + "568300K .......... .......... .......... .......... .......... 95% 21.0M 1s\n", + "568350K .......... .......... .......... .......... .......... 95% 34.5M 1s\n", + "568400K .......... .......... .......... .......... .......... 95% 5.57M 1s\n", + "568450K .......... .......... .......... .......... .......... 95% 64.3M 1s\n", + "568500K .......... .......... .......... .......... .......... 95% 57.7M 1s\n", + "568550K .......... .......... .......... .......... .......... 95% 15.4M 1s\n", + "568600K .......... .......... .......... .......... .......... 95% 43.9M 1s\n", + "568650K .......... .......... .......... .......... .......... 95% 14.8M 1s\n", + "568700K .......... .......... .......... .......... .......... 95% 44.9M 1s\n", + "568750K .......... .......... .......... .......... .......... 95% 67.5M 1s\n", + "568800K .......... .......... .......... .......... .......... 95% 16.0M 1s\n", + "568850K .......... .......... .......... .......... .......... 95% 51.8M 1s\n", + "568900K .......... .......... .......... .......... .......... 95% 60.4M 1s\n", + "568950K .......... .......... .......... .......... .......... 95% 9.41M 1s\n", + "569000K .......... .......... .......... .......... .......... 95% 56.7M 1s\n", + "569050K .......... .......... .......... .......... .......... 95% 13.2M 1s\n", + "569100K .......... .......... .......... .......... .......... 95% 56.0M 1s\n", + "569150K .......... .......... .......... .......... .......... 95% 67.3M 1s\n", + "569200K .......... .......... .......... .......... .......... 95% 12.4M 1s\n", + "569250K .......... .......... .......... .......... .......... 95% 61.0M 1s\n", + "569300K .......... .......... .......... .......... .......... 95% 16.4M 1s\n", + "569350K .......... .......... .......... .......... .......... 95% 58.7M 1s\n", + "569400K .......... .......... .......... .......... .......... 95% 15.3M 1s\n", + "569450K .......... .......... .......... .......... .......... 95% 41.6M 1s\n", + "569500K .......... .......... .......... .......... .......... 95% 60.9M 1s\n", + "569550K .......... .......... .......... .......... .......... 95% 15.1M 1s\n", + "569600K .......... .......... .......... .......... .......... 95% 44.4M 1s\n", + "569650K .......... .......... .......... .......... .......... 95% 16.9M 1s\n", + "569700K .......... .......... .......... .......... .......... 95% 48.2M 1s\n", + "569750K .......... .......... .......... .......... .......... 95% 46.8M 1s\n", + "569800K .......... .......... .......... .......... .......... 95% 15.2M 1s\n", + "569850K .......... .......... .......... .......... .......... 95% 58.7M 1s\n", + "569900K .......... .......... .......... .......... .......... 95% 18.0M 1s\n", + "569950K .......... .......... .......... .......... .......... 95% 34.3M 1s\n", + "570000K .......... .......... .......... .......... .......... 95% 49.8M 1s\n", + "570050K .......... .......... .......... .......... .......... 95% 19.7M 1s\n", + "570100K .......... .......... .......... .......... .......... 95% 35.4M 1s\n", + "570150K .......... .......... .......... .......... .......... 95% 59.6M 1s\n", + "570200K .......... .......... .......... .......... .......... 95% 15.5M 1s\n", + "570250K .......... .......... .......... .......... .......... 95% 61.8M 1s\n", + "570300K .......... .......... .......... .......... .......... 95% 17.4M 1s\n", + "570350K .......... .......... .......... .......... .......... 95% 35.8M 1s\n", + "570400K .......... .......... .......... .......... .......... 95% 39.2M 1s\n", + "570450K .......... .......... .......... .......... .......... 95% 17.5M 1s\n", + "570500K .......... .......... .......... .......... .......... 95% 38.5M 1s\n", + "570550K .......... .......... .......... .......... .......... 95% 20.9M 1s\n", + "570600K .......... .......... .......... .......... .......... 95% 32.2M 1s\n", + "570650K .......... .......... .......... .......... .......... 95% 44.7M 1s\n", + "570700K .......... .......... .......... .......... .......... 95% 17.2M 1s\n", + "570750K .......... .......... .......... .......... .......... 95% 46.1M 1s\n", + "570800K .......... .......... .......... .......... .......... 95% 51.8M 1s\n", + "570850K .......... .......... .......... .......... .......... 95% 17.2M 1s\n", + "570900K .......... .......... .......... .......... .......... 96% 50.8M 1s\n", + "570950K .......... .......... .......... .......... .......... 96% 20.1M 1s\n", + "571000K .......... .......... .......... .......... .......... 96% 26.1M 1s\n", + "571050K .......... .......... .......... .......... .......... 96% 67.9M 1s\n", + "571100K .......... .......... .......... .......... .......... 96% 19.6M 1s\n", + "571150K .......... .......... .......... .......... .......... 96% 36.6M 1s\n", + "571200K .......... .......... .......... .......... .......... 96% 61.8M 1s\n", + "571250K .......... .......... .......... .......... .......... 96% 18.2M 1s\n", + "571300K .......... .......... .......... .......... .......... 96% 38.0M 1s\n", + "571350K .......... .......... .......... .......... .......... 96% 18.5M 1s\n", + "571400K .......... .......... .......... .......... .......... 96% 5.70M 1s\n", + "571450K .......... .......... .......... .......... .......... 96% 70.3M 1s\n", + "571500K .......... .......... .......... .......... .......... 96% 73.3M 1s\n", + "571550K .......... .......... .......... .......... .......... 96% 12.2M 1s\n", + "571600K .......... .......... .......... .......... .......... 96% 60.8M 1s\n", + "571650K .......... .......... .......... .......... .......... 96% 70.9M 1s\n", + "571700K .......... .......... .......... .......... .......... 96% 15.4M 1s\n", + "571750K .......... .......... .......... .......... .......... 96% 67.0M 1s\n", + "571800K .......... .......... .......... .......... .......... 96% 16.1M 1s\n", + "571850K .......... .......... .......... .......... .......... 96% 45.8M 1s\n", + "571900K .......... .......... .......... .......... .......... 96% 74.3M 1s\n", + "571950K .......... .......... .......... .......... .......... 96% 15.6M 1s\n", + "572000K .......... .......... .......... .......... .......... 96% 42.0M 1s\n", + "572050K .......... .......... .......... .......... .......... 96% 72.8M 1s\n", + "572100K .......... .......... .......... .......... .......... 96% 18.4M 1s\n", + "572150K .......... .......... .......... .......... .......... 96% 45.0M 1s\n", + "572200K .......... .......... .......... .......... .......... 96% 22.5M 1s\n", + "572250K .......... .......... .......... .......... .......... 96% 31.6M 1s\n", + "572300K .......... .......... .......... .......... .......... 96% 53.0M 1s\n", + "572350K .......... .......... .......... .......... .......... 96% 25.0M 1s\n", + "572400K .......... .......... .......... .......... .......... 96% 34.8M 1s\n", + "572450K .......... .......... .......... .......... .......... 96% 38.2M 1s\n", + "572500K .......... .......... .......... .......... .......... 96% 9.73M 1s\n", + "572550K .......... .......... .......... .......... .......... 96% 69.5M 1s\n", + "572600K .......... .......... .......... .......... .......... 96% 60.1M 1s\n", + "572650K .......... .......... .......... .......... .......... 96% 18.0M 1s\n", + "572700K .......... .......... .......... .......... .......... 96% 41.4M 1s\n", + "572750K .......... .......... .......... .......... .......... 96% 64.2M 1s\n", + "572800K .......... .......... .......... .......... .......... 96% 19.0M 1s\n", + "572850K .......... .......... .......... .......... .......... 96% 33.4M 1s\n", + "572900K .......... .......... .......... .......... .......... 96% 71.0M 1s\n", + "572950K .......... .......... .......... .......... .......... 96% 22.3M 1s\n", + "573000K .......... .......... .......... .......... .......... 96% 31.5M 1s\n", + "573050K .......... .......... .......... .......... .......... 96% 55.6M 1s\n", + "573100K .......... .......... .......... .......... .......... 96% 21.5M 1s\n", + "573150K .......... .......... .......... .......... .......... 96% 41.0M 1s\n", + "573200K .......... .......... .......... .......... .......... 96% 48.2M 1s\n", + "573250K .......... .......... .......... .......... .......... 96% 11.6M 1s\n", + "573300K .......... .......... .......... .......... .......... 96% 59.6M 1s\n", + "573350K .......... .......... .......... .......... .......... 96% 65.8M 1s\n", + "573400K .......... .......... .......... .......... .......... 96% 15.5M 1s\n", + "573450K .......... .......... .......... .......... .......... 96% 68.6M 1s\n", + "573500K .......... .......... .......... .......... .......... 96% 63.9M 1s\n", + "573550K .......... .......... .......... .......... .......... 96% 19.7M 1s\n", + "573600K .......... .......... .......... .......... .......... 96% 43.0M 1s\n", + "573650K .......... .......... .......... .......... .......... 96% 58.8M 1s\n", + "573700K .......... .......... .......... .......... .......... 96% 18.0M 1s\n", + "573750K .......... .......... .......... .......... .......... 96% 45.0M 1s\n", + "573800K .......... .......... .......... .......... .......... 96% 58.8M 1s\n", + "573850K .......... .......... .......... .......... .......... 96% 20.6M 1s\n", + "573900K .......... .......... .......... .......... .......... 96% 41.1M 1s\n", + "573950K .......... .......... .......... .......... .......... 96% 66.2M 1s\n", + "574000K .......... .......... .......... .......... .......... 96% 19.6M 1s\n", + "574050K .......... .......... .......... .......... .......... 96% 39.1M 1s\n", + "574100K .......... .......... .......... .......... .......... 96% 64.9M 1s\n", + "574150K .......... .......... .......... .......... .......... 96% 19.5M 1s\n", + "574200K .......... .......... .......... .......... .......... 96% 32.5M 1s\n", + "574250K .......... .......... .......... .......... .......... 96% 68.9M 1s\n", + "574300K .......... .......... .......... .......... .......... 96% 19.3M 1s\n", + "574350K .......... .......... .......... .......... .......... 96% 33.7M 1s\n", + "574400K .......... .......... .......... .......... .......... 96% 51.6M 1s\n", + "574450K .......... .......... .......... .......... .......... 96% 29.6M 1s\n", + "574500K .......... .......... .......... .......... .......... 96% 51.4M 1s\n", + "574550K .......... .......... .......... .......... .......... 96% 27.7M 1s\n", + "574600K .......... .......... .......... .......... .......... 96% 28.6M 1s\n", + "574650K .......... .......... .......... .......... .......... 96% 42.2M 1s\n", + "574700K .......... .......... .......... .......... .......... 96% 31.7M 1s\n", + "574750K .......... .......... .......... .......... .......... 96% 25.3M 1s\n", + "574800K .......... .......... .......... .......... .......... 96% 40.9M 1s\n", + "574850K .......... .......... .......... .......... .......... 96% 27.8M 1s\n", + "574900K .......... .......... .......... .......... .......... 96% 41.6M 1s\n", + "574950K .......... .......... .......... .......... .......... 96% 37.5M 1s\n", + "575000K .......... .......... .......... .......... .......... 96% 25.3M 1s\n", + "575050K .......... .......... .......... .......... .......... 96% 38.9M 1s\n", + "575100K .......... .......... .......... .......... .......... 96% 45.8M 1s\n", + "575150K .......... .......... .......... .......... .......... 96% 23.5M 1s\n", + "575200K .......... .......... .......... .......... .......... 96% 48.2M 1s\n", + "575250K .......... .......... .......... .......... .......... 96% 46.1M 1s\n", + "575300K .......... .......... .......... .......... .......... 96% 24.7M 1s\n", + "575350K .......... .......... .......... .......... .......... 96% 34.7M 1s\n", + "575400K .......... .......... .......... .......... .......... 96% 35.5M 1s\n", + "575450K .......... .......... .......... .......... .......... 96% 29.2M 1s\n", + "575500K .......... .......... .......... .......... .......... 96% 39.8M 1s\n", + "575550K .......... .......... .......... .......... .......... 96% 43.4M 1s\n", + "575600K .......... .......... .......... .......... .......... 96% 46.7M 1s\n", + "575650K .......... .......... .......... .......... .......... 96% 23.5M 1s\n", + "575700K .......... .......... .......... .......... .......... 96% 44.8M 1s\n", + "575750K .......... .......... .......... .......... .......... 96% 40.5M 1s\n", + "575800K .......... .......... .......... .......... .......... 96% 23.4M 1s\n", + "575850K .......... .......... .......... .......... .......... 96% 55.1M 1s\n", + "575900K .......... .......... .......... .......... .......... 96% 36.3M 1s\n", + "575950K .......... .......... .......... .......... .......... 96% 24.9M 1s\n", + "576000K .......... .......... .......... .......... .......... 96% 36.7M 1s\n", + "576050K .......... .......... .......... .......... .......... 96% 43.9M 1s\n", + "576100K .......... .......... .......... .......... .......... 96% 26.0M 0s\n", + "576150K .......... .......... .......... .......... .......... 96% 44.0M 0s\n", + "576200K .......... .......... .......... .......... .......... 96% 40.6M 0s\n", + "576250K .......... .......... .......... .......... .......... 96% 25.6M 0s\n", + "576300K .......... .......... .......... .......... .......... 96% 44.6M 0s\n", + "576350K .......... .......... .......... .......... .......... 96% 37.2M 0s\n", + "576400K .......... .......... .......... .......... .......... 96% 52.3M 0s\n", + "576450K .......... .......... .......... .......... .......... 96% 23.9M 0s\n", + "576500K .......... .......... .......... .......... .......... 96% 56.3M 0s\n", + "576550K .......... .......... .......... .......... .......... 96% 50.3M 0s\n", + "576600K .......... .......... .......... .......... .......... 96% 21.8M 0s\n", + "576650K .......... .......... .......... .......... .......... 96% 30.4M 0s\n", + "576700K .......... .......... .......... .......... .......... 96% 44.7M 0s\n", + "576750K .......... .......... .......... .......... .......... 96% 39.3M 0s\n", + "576800K .......... .......... .......... .......... .......... 96% 29.4M 0s\n", + "576850K .......... .......... .......... .......... .......... 97% 39.3M 0s\n", + "576900K .......... .......... .......... .......... .......... 97% 60.5M 0s\n", + "576950K .......... .......... .......... .......... .......... 97% 31.0M 0s\n", + "577000K .......... .......... .......... .......... .......... 97% 30.2M 0s\n", + "577050K .......... .......... .......... .......... .......... 97% 53.8M 0s\n", + "577100K .......... .......... .......... .......... .......... 97% 4.25M 0s\n", + "577150K .......... .......... .......... .......... .......... 97% 68.1M 0s\n", + "577200K .......... .......... .......... .......... .......... 97% 63.2M 0s\n", + "577250K .......... .......... .......... .......... .......... 97% 16.5M 0s\n", + "577300K .......... .......... .......... .......... .......... 97% 40.7M 0s\n", + "577350K .......... .......... .......... .......... .......... 97% 70.5M 0s\n", + "577400K .......... .......... .......... .......... .......... 97% 56.2M 0s\n", + "577450K .......... .......... .......... .......... .......... 97% 16.9M 0s\n", + "577500K .......... .......... .......... .......... .......... 97% 49.0M 0s\n", + "577550K .......... .......... .......... .......... .......... 97% 72.1M 0s\n", + "577600K .......... .......... .......... .......... .......... 97% 19.4M 0s\n", + "577650K .......... .......... .......... .......... .......... 97% 34.7M 0s\n", + "577700K .......... .......... .......... .......... .......... 97% 71.2M 0s\n", + "577750K .......... .......... .......... .......... .......... 97% 71.7M 0s\n", + "577800K .......... .......... .......... .......... .......... 97% 18.9M 0s\n", + "577850K .......... .......... .......... .......... .......... 97% 45.7M 0s\n", + "577900K .......... .......... .......... .......... .......... 97% 72.2M 0s\n", + "577950K .......... .......... .......... .......... .......... 97% 28.2M 0s\n", + "578000K .......... .......... .......... .......... .......... 97% 42.1M 0s\n", + "578050K .......... .......... .......... .......... .......... 97% 39.7M 0s\n", + "578100K .......... .......... .......... .......... .......... 97% 38.6M 0s\n", + "578150K .......... .......... .......... .......... .......... 97% 31.0M 0s\n", + "578200K .......... .......... .......... .......... .......... 97% 34.3M 0s\n", + "578250K .......... .......... .......... .......... .......... 97% 4.47M 0s\n", + "578300K .......... .......... .......... .......... .......... 97% 67.0M 0s\n", + "578350K .......... .......... .......... .......... .......... 97% 61.8M 0s\n", + "578400K .......... .......... .......... .......... .......... 97% 66.5M 0s\n", + "578450K .......... .......... .......... .......... .......... 97% 18.6M 0s\n", + "578500K .......... .......... .......... .......... .......... 97% 40.0M 0s\n", + "578550K .......... .......... .......... .......... .......... 97% 70.9M 0s\n", + "578600K .......... .......... .......... .......... .......... 97% 58.3M 0s\n", + "578650K .......... .......... .......... .......... .......... 97% 17.8M 0s\n", + "578700K .......... .......... .......... .......... .......... 97% 52.2M 0s\n", + "578750K .......... .......... .......... .......... .......... 97% 71.9M 0s\n", + "578800K .......... .......... .......... .......... .......... 97% 28.1M 0s\n", + "578850K .......... .......... .......... .......... .......... 97% 32.6M 0s\n", + "578900K .......... .......... .......... .......... .......... 97% 55.3M 0s\n", + "578950K .......... .......... .......... .......... .......... 97% 62.4M 0s\n", + "579000K .......... .......... .......... .......... .......... 97% 22.3M 0s\n", + "579050K .......... .......... .......... .......... .......... 97% 35.3M 0s\n", + "579100K .......... .......... .......... .......... .......... 97% 75.9M 0s\n", + "579150K .......... .......... .......... .......... .......... 97% 31.4M 0s\n", + "579200K .......... .......... .......... .......... .......... 97% 34.7M 0s\n", + "579250K .......... .......... .......... .......... .......... 97% 45.6M 0s\n", + "579300K .......... .......... .......... .......... .......... 97% 70.2M 0s\n", + "579350K .......... .......... .......... .......... .......... 97% 19.9M 0s\n", + "579400K .......... .......... .......... .......... .......... 97% 32.9M 0s\n", + "579450K .......... .......... .......... .......... .......... 97% 63.4M 0s\n", + "579500K .......... .......... .......... .......... .......... 97% 29.1M 0s\n", + "579550K .......... .......... .......... .......... .......... 97% 34.0M 0s\n", + "579600K .......... .......... .......... .......... .......... 97% 45.2M 0s\n", + "579650K .......... .......... .......... .......... .......... 97% 70.5M 0s\n", + "579700K .......... .......... .......... .......... .......... 97% 36.3M 0s\n", + "579750K .......... .......... .......... .......... .......... 97% 35.9M 0s\n", + "579800K .......... .......... .......... .......... .......... 97% 39.6M 0s\n", + "579850K .......... .......... .......... .......... .......... 97% 74.8M 0s\n", + "579900K .......... .......... .......... .......... .......... 97% 21.4M 0s\n", + "579950K .......... .......... .......... .......... .......... 97% 35.1M 0s\n", + "580000K .......... .......... .......... .......... .......... 97% 58.8M 0s\n", + "580050K .......... .......... .......... .......... .......... 97% 73.4M 0s\n", + "580100K .......... .......... .......... .......... .......... 97% 27.7M 0s\n", + "580150K .......... .......... .......... .......... .......... 97% 38.8M 0s\n", + "580200K .......... .......... .......... .......... .......... 97% 53.5M 0s\n", + "580250K .......... .......... .......... .......... .......... 97% 30.1M 0s\n", + "580300K .......... .......... .......... .......... .......... 97% 39.5M 0s\n", + "580350K .......... .......... .......... .......... .......... 97% 47.4M 0s\n", + "580400K .......... .......... .......... .......... .......... 97% 53.9M 0s\n", + "580450K .......... .......... .......... .......... .......... 97% 35.8M 0s\n", + "580500K .......... .......... .......... .......... .......... 97% 39.0M 0s\n", + "580550K .......... .......... .......... .......... .......... 97% 45.1M 0s\n", + "580600K .......... .......... .......... .......... .......... 97% 31.9M 0s\n", + "580650K .......... .......... .......... .......... .......... 97% 49.0M 0s\n", + "580700K .......... .......... .......... .......... .......... 97% 27.3M 0s\n", + "580750K .......... .......... .......... .......... .......... 97% 70.2M 0s\n", + "580800K .......... .......... .......... .......... .......... 97% 52.3M 0s\n", + "580850K .......... .......... .......... .......... .......... 97% 48.1M 0s\n", + "580900K .......... .......... .......... .......... .......... 97% 27.2M 0s\n", + "580950K .......... .......... .......... .......... .......... 97% 63.5M 0s\n", + "581000K .......... .......... .......... .......... .......... 97% 43.3M 0s\n", + "581050K .......... .......... .......... .......... .......... 97% 35.1M 0s\n", + "581100K .......... .......... .......... .......... .......... 97% 33.8M 0s\n", + "581150K .......... .......... .......... .......... .......... 97% 70.4M 0s\n", + "581200K .......... .......... .......... .......... .......... 97% 38.7M 0s\n", + "581250K .......... .......... .......... .......... .......... 97% 28.7M 0s\n", + "581300K .......... .......... .......... .......... .......... 97% 41.3M 0s\n", + "581350K .......... .......... .......... .......... .......... 97% 60.3M 0s\n", + "581400K .......... .......... .......... .......... .......... 97% 4.42M 0s\n", + "581450K .......... .......... .......... .......... .......... 97% 61.6M 0s\n", + "581500K .......... .......... .......... .......... .......... 97% 66.8M 0s\n", + "581550K .......... .......... .......... .......... .......... 97% 64.7M 0s\n", + "581600K .......... .......... .......... .......... .......... 97% 25.9M 0s\n", + "581650K .......... .......... .......... .......... .......... 97% 27.1M 0s\n", + "581700K .......... .......... .......... .......... .......... 97% 63.7M 0s\n", + "581750K .......... .......... .......... .......... .......... 97% 23.3M 0s\n", + "581800K .......... .......... .......... .......... .......... 97% 22.0M 0s\n", + "581850K .......... .......... .......... .......... .......... 97% 22.8M 0s\n", + "581900K .......... .......... .......... .......... .......... 97% 26.5M 0s\n", + "581950K .......... .......... .......... .......... .......... 97% 53.7M 0s\n", + "582000K .......... .......... .......... .......... .......... 97% 25.2M 0s\n", + "582050K .......... .......... .......... .......... .......... 97% 24.4M 0s\n", + "582100K .......... .......... .......... .......... .......... 97% 52.2M 0s\n", + "582150K .......... .......... .......... .......... .......... 97% 25.2M 0s\n", + "582200K .......... .......... .......... .......... .......... 97% 27.7M 0s\n", + "582250K .......... .......... .......... .......... .......... 97% 22.6M 0s\n", + "582300K .......... .......... .......... .......... .......... 97% 30.6M 0s\n", + "582350K .......... .......... .......... .......... .......... 97% 43.2M 0s\n", + "582400K .......... .......... .......... .......... .......... 97% 22.0M 0s\n", + "582450K .......... .......... .......... .......... .......... 97% 36.5M 0s\n", + "582500K .......... .......... .......... .......... .......... 97% 29.1M 0s\n", + "582550K .......... .......... .......... .......... .......... 97% 4.42M 0s\n", + "582600K .......... .......... .......... .......... .......... 97% 57.3M 0s\n", + "582650K .......... .......... .......... .......... .......... 97% 65.3M 0s\n", + "582700K .......... .......... .......... .......... .......... 97% 14.6M 0s\n", + "582750K .......... .......... .......... .......... .......... 97% 11.5M 0s\n", + "582800K .......... .......... .......... .......... .......... 98% 51.9M 0s\n", + "582850K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", + "582900K .......... .......... .......... .......... .......... 98% 62.8M 0s\n", + "582950K .......... .......... .......... .......... .......... 98% 12.5M 0s\n", + "583000K .......... .......... .......... .......... .......... 98% 51.9M 0s\n", + "583050K .......... .......... .......... .......... .......... 98% 12.7M 0s\n", + "583100K .......... .......... .......... .......... .......... 98% 62.1M 0s\n", + "583150K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", + "583200K .......... .......... .......... .......... .......... 98% 54.3M 0s\n", + "583250K .......... .......... .......... .......... .......... 98% 12.7M 0s\n", + "583300K .......... .......... .......... .......... .......... 98% 64.0M 0s\n", + "583350K .......... .......... .......... .......... .......... 98% 12.6M 0s\n", + "583400K .......... .......... .......... .......... .......... 98% 11.9M 0s\n", + "583450K .......... .......... .......... .......... .......... 98% 58.5M 0s\n", + "583500K .......... .......... .......... .......... .......... 98% 12.4M 0s\n", + "583550K .......... .......... .......... .......... .......... 98% 61.3M 0s\n", + "583600K .......... .......... .......... .......... .......... 98% 12.6M 0s\n", + "583650K .......... .......... .......... .......... .......... 98% 49.4M 0s\n", + "583700K .......... .......... .......... .......... .......... 98% 13.1M 0s\n", + "583750K .......... .......... .......... .......... .......... 98% 62.7M 0s\n", + "583800K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", + "583850K .......... .......... .......... .......... .......... 98% 55.0M 0s\n", + "583900K .......... .......... .......... .......... .......... 98% 12.2M 0s\n", + "583950K .......... .......... .......... .......... .......... 98% 56.6M 0s\n", + "584000K .......... .......... .......... .......... .......... 98% 12.8M 0s\n", + "584050K .......... .......... .......... .......... .......... 98% 64.1M 0s\n", + "584100K .......... .......... .......... .......... .......... 98% 12.5M 0s\n", + "584150K .......... .......... .......... .......... .......... 98% 62.4M 0s\n", + "584200K .......... .......... .......... .......... .......... 98% 3.96M 0s\n", + "584250K .......... .......... .......... .......... .......... 98% 56.4M 0s\n", + "584300K .......... .......... .......... .......... .......... 98% 13.5M 0s\n", + "584350K .......... .......... .......... .......... .......... 98% 56.3M 0s\n", + "584400K .......... .......... .......... .......... .......... 98% 11.9M 0s\n", + "584450K .......... .......... .......... .......... .......... 98% 65.5M 0s\n", + "584500K .......... .......... .......... .......... .......... 98% 13.4M 0s\n", + "584550K .......... .......... .......... .......... .......... 98% 47.9M 0s\n", + "584600K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", + "584650K .......... .......... .......... .......... .......... 98% 58.1M 0s\n", + "584700K .......... .......... .......... .......... .......... 98% 13.1M 0s\n", + "584750K 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metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", + "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", + "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", + "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", + " ds = _xr.open_zarr(path, **kwargs)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", "\n", "\n", "Main attributes:\n", " .dataset: \n", " .grid: \n", - " .projection: \n", + " .projection: \n", "\n", "More attributes:\n", " .name: get_started\n", @@ -207,7 +12867,15 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:01.824915Z", + "iopub.status.busy": "2023-04-04T02:47:01.824254Z", + "iopub.status.idle": "2023-04-04T02:47:02.215253Z", + "shell.execute_reply": "2023-04-04T02:47:02.212585Z", + "shell.execute_reply.started": "2023-04-04T02:47:01.824813Z" + } + }, "outputs": [ { "name": "stdout", @@ -218,7 +12886,7 @@ "Main attributes:\n", " .dataset: \n", " .grid: \n", - " .projection: \n", + " .projection: \n", "\n", "More attributes:\n", " .name: oceandataset #1\n", @@ -257,7 +12925,15 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:02.219008Z", + "iopub.status.busy": "2023-04-04T02:47:02.218191Z", + "iopub.status.idle": "2023-04-04T02:47:02.627340Z", + "shell.execute_reply": "2023-04-04T02:47:02.624565Z", + "shell.execute_reply.started": "2023-04-04T02:47:02.218953Z" + } + }, "outputs": [ { "name": "stdout", @@ -268,7 +12944,7 @@ "Main attributes:\n", " .dataset: \n", " .grid: \n", - " .projection: \n", + " .projection: \n", "\n", "More attributes:\n", " .name: oceandataset #1\n", @@ -311,13 +12987,21 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:02.630722Z", + "iopub.status.busy": "2023-04-04T02:47:02.630125Z", + "iopub.status.idle": "2023-04-04T02:47:03.073064Z", + "shell.execute_reply": "2023-04-04T02:47:03.064028Z", + "shell.execute_reply.started": "2023-04-04T02:47:02.630666Z" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Global attributes: {} \n", + "Global attributes: {'OceanSpy_description': 'This is my first oceandataset', 'OceanSpy_grid_coords': \"{'Y': {'Y': None, 'Yp1': 0.5}, 'X': {'X': None, 'Xp1': 0.5}, 'Z': {'Z': None, 'Zp1': 0.5, 'Zu': 0.5, 'Zl': -0.5}, 'time': {'time': -0.5, 'time_midp': None}}\", 'OceanSpy_name': 'oceandataset #1', 'OceanSpy_parameters': \"{'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0': 1027, 'g': 9.81, 'eps_nh': 0, 'omega': 7.292123516990375e-05, 'c_p': 3986.0, 'tempFrz0': 0.0901, 'dTempFrz_dS': -0.0575}\", 'OceanSpy_projection': 'Mercator(**{})'} \n", "\n", "\n", "\n", @@ -325,7 +13009,7 @@ "Main attributes:\n", " .dataset: \n", " .grid: \n", - " .projection: \n", + " .projection: \n", "\n", "More attributes:\n", " .name: oceandataset #1\n", @@ -378,28 +13062,24 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:03.086080Z", + "iopub.status.busy": "2023-04-04T02:47:03.085480Z", + "iopub.status.idle": "2023-04-04T02:47:09.344897Z", + "shell.execute_reply": "2023-04-04T02:47:09.341009Z", + "shell.execute_reply.started": "2023-04-04T02:47:03.086024Z" + } + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", 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lHVu8eDHe9KY3YcWKFXjFK14BIE/Dvvfee2PPPffErFmzsGbNmkKd973vffjiF7+IH//4x6WU6COh0Wig0VyPA/Y6F4nIk4hpk/BNRxI6zt+D9kn67DVigvqLTAEAZFOZ/RpaykJ5HeVvhHLVqR5MdgCRKrPfZQuI6xKnnLcnvvbvDyIdVoDyGmiXVcAUE2EZrQGlg/oVZdpBiPbHu0XQX1yLcPLCN+HrF96DdCg1ZTo87xDtxioCi6YUXvkOzpHKRnk7OomgevKvlqpF+b44P6ZiCWWeqbQvP9aclH+WkyXOm7sDLrvvcQxG+blpMzRl8tupREPTt1bmZRQNv6bcVphnyZSRpj0ZZ4jjvFwcFbeRUIhk/j6JMrsvvyTuWvvvAUBpUXqfmYFnZnBpZq4DAOVd00RLnNvcG1ck96MpFKR5BpsqL99o5ts0Ndcv8+6V6ct/fLUu3i/7uepRMW3pzHwnNaDN9RJJ8J1QwpVL6aYE7Wk3JhH2Zz7XhMBF2+2EC55Zjoa0X87SOSELPkfa3m/7W0I/RbEqHbPna3++tH0WInP/ozjvpF7LkMisUD0194/2D/QMom6eCbr/tJ2WbIAU4cXI0ROliFSMNz/1T3jgFd+Fkk37TMWC2lNIzL66aOb1ZLPwOYGyfSgzto26hsH1GT4y9zdoNBqb5J99o9HAyucyPH7fjpgyeWzKh7XrFHZ4w2ObbKwvJ0xoduFGo4Hrr78e5557rs32GmLNmjUQQmCLLbaw+y666CIcdthhGBwcxNFHH4158+YV6uy4444488wz8YlPfAJHHHEEpOz+AYqjOmKRp2O3E5O4y4kJ/YjrLicmIpiYaPqRcD9YSSTR19eHJKoDkSo20O4fNA23amJCP4g62HbSbj7w9se7RdBfEkXunGVkykzwxKSTcwwnJlEEFScAABVXTEwSUz7Jj6mamZjU83sc1XsQBRMT1M22YmICc2kqJyY0IYnon1Jm/yFFNCHxJiZusjK2iYkwAxeK/vmb66AB4X15Yi3R1+xDnNShvImJMhOTyExMdGpOstOJiX2kN6+JSSREfo97eyAnemJiJ6fFiUlUSxHRxITaNveNnoO4RyGJ8sVBODGp1ZotJyb1SCBSMfr6+lDvT6Cke6YS873LJyZ5Pz2mzR5zPnXqQ2SQZnA0MdFq4v599U8W6J88tt871ckihwFggsWvN998M1avXo0FCxZUHh8aGsLHP/5xnHTSSZgyZYrdf9RRR+H555/H008/jZtuuglRFJXqnn/++Vi+fDluuOGGTTV8BoPBYPwdItNqXF6MzjChjMm1116LI488siBsJTSbTZxwwglQSuGaa64pHa/X6yWzkI+tt94aH/7wh/HpT38a73rXu7oeWyI0LWDtCiafmBfZBE2zdVoB1yJkPcH8ruEeQLuAMUyLCFc03nthTCvSmHKQaWvOkWaVLQd6IBsKwjflhOYaf2vNTFnxmFfPjtUuEs2bTI3AxrRYAXTCZHRQJqlHbktmJ3jMSdiGZTm8+yFHsUoRonxudik58vXQCaDNxcxq5jmxph2JZo9py5hwIvNZ9OfbWixgCAbQojBKzOcEzoRDbB6t7unbLIS9BLSVRONLgZoZZ0IsivkcSWHfx+Y5j9o8r+1Aq8OmWfvEwpl46BIKAdTM8UlCIBHCmn7oAmRZfuL01VRCOBbE3iJRMURiUzyTHBVQxEqYbeqxKvZ8g5PMBISxJpbIAZ+VCR9J+/0TgNCom+vQmwnYdaFvNaT3SXiRK55JOo+mdEtMy4KK6s+A/d6rOD82XE+R1as1FNowJi8O1+0+x7Dl9VclA9iiPggAmFrLt8SgNFUMZR5ildWhdGQHQD0mMkNGJjxTLxW52FRJ2jbRY8w61PaWoomNYny0H4zNCxM2MXn88cexdOlS3HjjjaVjzWYTxx9/PJYvX45f/OIXBbakG5x77rm45pprKic2I2HBuXuir69vVP1OJE4969Uv9RAmHCcvfNNLPYQJxSdev+PEdNScmG46wQcab6g+MKFLp4nDhdu/8qUeQnfw50lpcKwJYOPITbzxiXeO44AMNm4EcNL4txtAQUN1MiMfoQ1GZ5iwr/2SJUswffp0vPWtby3sp0nJI488gl/+8pfYcsstR91Hf38/LrjgAixatAhve9vbuqp73RUPIomMIMnqQaKSsYs0IzppzZjIRpmyK2lTvGfUrqraMCZJInDq+1+Nr37hD2j+HTEmJH5tDga/hpszY1KT0En+1com5arVKsaERK8ZMSZTBD7+ph1x6W8fs+JXYkx88atjTEy/ljExN1Q6oaPTmJCuQKFmVsFJkl9TYkUi6cSvsVmV0uduQVoTErESE5KpgDHREh9svh6La/ehIRQywwI0jKZkqGmoIpJ6KI8xIfhak0BboolV0F0yJvGmY0wW7rwTFj7xqL3HlYxJSaTiHSPQeQg9KsaEzlHWU8QtGBOrMfGeg5AxqSdpS8akLnPx6yErj8Zvtv8elEwhgx+eRGZWW0T6k17DmPQZxqRewZjUhALWTwxjoqBKkqLRtMHoDBMyMVFKYcmSJTjllFMQx67LNE3xzne+E7/97W/x3//938iyDCtXrgQATJs2DbVareu+zjjjDFx55ZX41re+hX333bfjetnGFCKmXx7zoxYpaCtQNFsSOFKZTEEPmS8//RNU5R+VaKj4BVKR+6EgQSxtYeh/kbmJRd2YjgbrERpSQCins6HJi53YGK8gkbo+SYxoBbaZLoteaetr8trNH1SLL5rW5X/g3QhVAzSHMzSbQV8V17jw40wTiayLfgt2ti7qyaIwWmfSPS9m2KkiUaeyHg8N01/T/IOgb8YQNIbInGj2KXP9lAY06JjZmh9qOxmRCjJ27wFnytEyg4xJ6Giej4gmNMqaoKjNrOofZCegr4J5mBpGsZsJbY9JoSG18b4RCg2RITPXZMjczOHgx1wLJwkvmGmQP2LktUOCcu3919dNc4y+5qltKP+s4f6BD5VFs27iHp5sxTXyJyQAZKqhIzdnHs6Ahr1/rn0dilhVOBvxx0Pfe68RBOP2zV6lpoyYtBYD0jx95pEQiibZ5von2j4n9JzR9RdCAyJnueu9+eRhi0n5BGVSbRg1HeEQAI9s3AJNmaE/HgYA9EZm0qFTK6SlyU4sjBlX5/8DerQT2JJQtk82MKhC+obxcsCEiF+XLl2KFStW4NRTTy3sf/LJJ/GDH/wATz75JPbaay9ss8029nXnnXeOqq8kSXDxxRdjaGhoPIbOYDAYjL9zZFqPy4vRGSaEMTn88MOhK27KjjvuWLm/Gzz22GOlfSeeeCJOPPHEMbXLYDAYDAbAGpOJxstUWtY9RKqAwJ4ulLBmDfKht3S9cVkWGhBp0RRCFKsWwtGtxhRB+pMob9S0ZShVY66xdTwzhJxkbpXRP6jEs3Vb2pc2ph1ZbMMvY+MeANbeYMtaqtYzyVRZbcipoIUpqLCvm5gnVZPVsH7URgfSTlfim4DCcp2MsaDR0YWtsDfA0wApiudB10Ei7TU6isn5roykTaQjqTkGnix2Np6J8N5HZK6hY8aUF2tnwiGNCVHkkbLvVeC5orWo1jaMAaRRqRvFZFNEnt5EIKOAbEqggQipMcUMN/PnXQemjPyR9HQjAFRGJjRnrimZQDQgG2QitXam/HOViUYHxyoQSl0KphKynJrvUlrLj1PXOtKlPoQGBMVp6eQ2+PV1xb6RqpO2yIsNQ9Y9QbobIW1ZbbRMmsyE5hoLBRiLHIaSXBP0TD1/qKO+FHVIoA9YvnoahoXC1N5cKbtFPWe1azJDTebPRyxba0YST7cC5Kag4aHNSMHNGDfwxITBYDAYjDZQ0NaleSxtMDoDT0wYDAaDwWgDNuVMLHhiYqCFKJsrpHZmGQp0Rq7ANmy9sB46hbZCkNkmcd4xzoWYlPtk7vFce80xkbgyMlXQUljzgDXBOHcF2662zjuysCl4zhgFPMLQ+L7nThi+3j9fonT9rkbyjPPbCa+XlPlxCufvu21XmWnaXP9SKH7fG6qV6aZKEm7NZs4857cFwAbd00nkpSIo3vesJpCZe6nIEzYKttIzE1SFGqd95CYckdnG2SbIC0eQecfzzhGBBwRBjLMZpxX8fDpkykmVxHAmkAWmDGslpND2yjM9kQmHvG2GJSSFja8w5ZTMHOHpav9YG7NeeJ1Ei/dtmhFKlMcxkgcQve/E4tjGrcE3CwLGfCOCY+QubU5ANgHRqPb8EdqZHK03mjGbqWEJJXJTzupnp2BIK6ybnJt5nq3nZphIauuCTGae/iT32CHX9p6oidR0OGiC7q1Ne9AYnpis8OMhXmXxa+eY0JD0DAaDwWAwGO3AjAmDwWAwGG2gMDIJ3EkbjM7AExMfIX8kpaXnCeRtYQISQitZCpBmTQTCvQ+9Y0SmvQiSLcwkvknCeP7IjSmihjIBk6o5XZ/GbZH0M/cYsudZpG1dGddHZVTZoL4fzKocVTb03KmgNWXAiUdkypHWA6XaTFbeZc9hvDJ6+kltwzatuYaC8cVQPfn7Zn/+FUt7TVC1yQJZr2mHorqSScf3vAmo9YJphyKG2oBqFSYZL4gZAJs1uAq+CUduYju4ELqUnRjII7oqJayZRwdb63mTSsCYCdA0ZobM+55kZTNDCa08WNqZbypPpvw5DLhaCLwammXC74jyxqSK51FqK+g/DMxWMuX4n20f3i5qy5hwbPcUVE0J66kTDTnzDgDIISChsFG2fwreFqEuBTALiFdLJEpAbci/AIMm0rbqUXmGZAAb+3PXtN6eoimnFmfoS4pmm8E0QbphGBOBbBzEr2Ot//cENuUwGAwGg8HYbMCMCYPBYDAYbZDp7rJbtGqD0Rl4YlIFP2Eb5aEB5d6gXBzmKWsql3PD5tjxgrHZ4GcVJpDAnFHyIKk4JvzgXa28SshLpqq9qn2tWP523jV+31XjCDh0160LbtXufLUQXjA7d027RrdB07pp0wbdMx4jJuiejgVUQvuM14kJqtbsE0hNQLUS3e7R8KWcKRQ3LNa2nn0Gi7GwrEeOX8Z64khlvXEo+BltfRNLlbllvOC8ghQiL8ib0sJ6eJVSLZFtYVhCDpnvYNOZTIFqS4y/r+RME5pw2plNvH7KJ9S6/1IQNc8TRqYuQJm/LYylwiRVSosj3QcdBSdpvfC8NukrWDPm0bpyJihKBGmD95FXooA2HlOZSf4ujEktWi8RD5KZxxyjfESZu2y1NQLazz1KgSXrElk976cxaHInxT2F84l6UyT1Yl4crQWyjQkmAqwxmViwKYfBYDAYDMZmA2ZMGAwGg8FoAwWBbIxCejVeQvy/A/DEhBBL6NhcDuKRlPPCsSYcIuS0R+dbbxyzi8wuQrQOdCQ8mX4p0BN5rnjFU5fPphD4rNRmR/GXqlGR86bkTdNNOxVjs8dkG48Zkw8I5BHlB1jrZDzd5OWpGttIZW1wvdCEQ5+l80qIaWu6iJ03Tkj9U4A1FbtxWK8cMs9EHt1uTThEu7sHxplp6Fkc+dQkNMY7yJoKTlIKDW1NSRqRueZxnEGqyJ4nBU/Lhk1OqjU5ZR8NOdcXW9YPGGbNHIEtRnuWjMCEY00oVQHOKkw5dG8pwKH/UxB61VgzTZa/j03deFBApcG1bhdMTVeYl+yz4R7dLPy98UxClONG9+eeLtKYRqJY2ZxKUZgvzLtX9F4H93S4EWN4Y+5NI9bSw+3GlpqHb2hLjWGtEW80Xj3GyUZkQDRsrldKnm30vJs+N0QYjmrF864pqMGJEW4oXe1I2G0bjM7AphwGg8FgMBibDZgxYTAYDAajDbJxMOWMtf7fE3hiYqCldLlPiPeWAExuHJszRxRJJqG1swAE3hoASoHVChStVdwXzRO2jlIuNTuZaZopRKOFvptMDO14e3/4rUwY7eTjY833UDW2kdr08/q0y7EzUj/t2h+pjt9vaGqjfER0OWMBZfLhZIZ9zurOpEN5RaxJRxa3hX1EZRMNH2nrfeM8borDl1LbgGpJnNP2kXCmndAbhzBRuXJ8TyFhvgSx1KjXUjSa+cXJzEmSHwZdD5XA2jTstQk9UQDPBOPuFXnBIAheVjDlhF4wvgeMZ1YxJ1Asi9ws4bcZfrbpn4YBmZWHXYI3Hl3+ebFjs55aWfG50wldI0D3mN+yWt6xMNdNRhr1xJh1osBTC2VTYOix1VtrQk8aBAA0tzRmTVMkzSLUzY+OmppCQaHRa8xzlHtHeKZK+g7Ui2OFBqIk3xcnmR1jtnGiAqzxxGQiwRMTBoPBYDDaQGlR0kuNpg1GZ2CNCYPBYDAYjM0GzJgYiJHMBeEx32wScqsV8msbFK0KNlu9Z8KBMelQPSXdsbCtMOeGd07aN0v55+N7l7QwYbQLgJZXbHG8EzNKVYA2/9r617XqGrfrr4P+tRAjn1+LsdnrFQXXtlDPVCPvHBMHKjdFBGMh0470aHdZNFMQJS9iZW0HwgbBMrQ75TURzoOCTDixR9ETFe9oencdxiuwWpjzhlwl/VVjJBUi87kWp5gEhUjmP0kbh3JbhDT0vZqcJ2ZRvtuJNeFUudAE+zIBNWwCglFgs6B6IVeNLtQ2eaMquvHLqrLpJmxbmnstUq9shTdO1W2oDqxmPlNctMCElJlKWV3bHEPKDEKbIIAqVTYXUa2Wm3RqFLeMzH5wOY5Ck18ilb2v9JzRfR8SQKI1kAEiUhBQ0BRgsIfGrxH35P0mxkxDJsi+Wn7fe+ImBup59La+OHfn2bZ3DYbXN/Gn8qUad7ApZ2LBExMGg8FgMNogg0Q2RgNDJ5IiRg425TAYDAaDwdhswIwJIcsgmsGcVmvrIaOtAp+odcPJRpHzpmnXfrsgXuSBQUGZKPcKFEQ4d6xI2lAySXifRehBUpnXpsXIZcWxTswf7QKsedu23kNw1zzPmzNOc2jf86UVN2/GV/VZ+wH1vNTuAGx+nKxXotFv3tfCdj0PE/LKIXONJNOQy4cD34RjjknzPoqLJhzypIgjZSl1a8kj843QJRPOpsyLE5pwMiULAbqkJi8OgSTKIMz5ZsZ0SVsdtzaFOiurcOcki+eUpREyEwhPNSmYl9nS116jOm8NjBNdK68YKqO8etY86z4L5Z40mQGyWSxTuA0Vp+tMfsF+WTZLReacpHFrkk2BdFL+njyeKA+YioQNaKcDExyZVHSkSgHWMuXKNk1gtMyY2tImuaoh98rpA3Rqnjwaq3nu43qKvt7cPEOmm6m9GwEA/cZsM1AbxCt6XgQA7NbzDACgRzaxERmuLl+qcYceB/FrGJiO0Ro8MWEwGAwGow1YYzKxYFMOg8FgMBiMzQbMmBiIoYabz0qPsyUTTkTmFZMzx6alV3ZfMdkFnNcGUA7K5ffdxhRjzR3tYn8FZqa2qChTqkdmC+VFgauCl1NoRMjqPtq261taxjqF7sCEVfJg8sq4YwKaTDkRBbMyz4Yx5aQ90gZYo61N2SI8Sj7YUr8qAmC8UUB5c8z1k4lqa8KhbTszzUSYcELa2jcRkAlAQUCQ144WiKVCZB6mzFxLGmPqeeOQeYdQdR7OKyj/nCQZmnF+oSk+YWpMO/EG09ewKHvq+E23svz5ZcOh+B47yrNkZi7Amu/JE/ZfaMrmUkLh3LT0zExBffuMCUAm1pCUt2PMZog1kJpn12xVM9826Dn07id5gZGHlEplKWgdvOuvRG7KsTAmnMR44tRqKXpMgLctezcAAPriptnmppzJ8RAmR0PlizJByLRE1jLxWadtjNNg/g7AExMGg8FgMNogd3Qe28REtVvkMQpgUw6DwWAwGIzNBsyYGKTLV0AkOd8oyJQTRZDTpubve000IOONo728OmGuG4sqE0c7c0uVt01gAhK6Q5NNqe0u6lDeDb+fsL4Ujq4NTCKiyhTVRb8ltAqw1u46jNSv7xUUBJ/TQlhzng48cLQU0LExP5hj6aT8mUh7yLQDZPS+njedmYBV2jkrFAKq5VuyO2hnwqEgajavibImHDJh+Cac/DQ0Ipuuvjr3yaaGDcJlnhHhjSfycv3UdAQ0kXvkCG1NMElU9JCLjCeJgkCsO7EdlkHXS08y982YxFKR35xYR5CDdAJm+Ch+LqBNMLQqkxC97OfAA6gqwFtVf2QVLVwGz6yTFzKfvXFQm1kt9CoDVM1cG+OxpIeMVxS1F2n7vIqK72kLa7AxeZt735MigirkuqFtWL8/yc02WyT5DemPhq149K9ZPwCgplIMZikmAix+nVjwxITBYDAYjDYYH40Jm3I6BU9MGAwGg8Fog1xjMjbGY6z1/57AExMPOs2V4Db+T39/OTAaSat9T4rQlBPmvvGPtR1Aa+8cmyuHzDtKO++hVhjJfNNqTJ3IxxXKJp+q3DutFhlKuUByVN6npv16I+XkqTrewfWmUWrDTWvPfKOj4j7nMSOc9009P9bsM6aBXmO+6XGmGxWYcLT0A6vR1tDoFIwt1p4Jx5hgrCeOLplwwmBisiKviR9UbZMGVAu8cShXj6SrLTyzktBIjD2iFqUYrghi5c4j/6yV8+pphzCwHABE5MVktpm5x6puPqfO/UuGFgLPY8YPyEbHgKIppmSS0d6L6nR5G2xbYT4efyx0nejnInJladxy2Bwzz6Ea9rzHyExJz6gxKWoB+0wqMjPSsUg7844snriIXBjDJMmgoCBlEPxPakyqmQBrxhunbm5AIpxJb32Wm9Obnj10yPxmM15e4IkJg8FgMBhtoMYhVw575XQOnphUIJo8GQAg+ic5VoLCzqe07DC7211CpTpjSlpo+XzGhcSPUNoxId0IWtuNY7S2z3DcxKD4Tasi41DIIExZlCvCv2sliqvPbsbosTndQMeGJYm8WCVBHBkdCWQJCVsNU9JDjInpPnZMCYKVq468VShtbTwJUydySkVp7nvkCV6JIYmCOCbEisSRKoSgByYmdkm79mmV7ENpYeObNLIYw3DjVl58kxBRwBD5rBDpAML60mOK6LqRCNOGY4810h7DmGzMb5iNMZIKxzhQvxVZ2UpxSALxqX95KkPRtwOJX9swmsTwEZui/S09g4F4VmTuXOi5pc8khlWxY1hs+CJ64zF80oSwt2JtqRGbgfuEEeCe2/76MLY0IegpbglhvVGPN3VkBd3EnADAcHNiGBPWmEws2F2YwWAwGAzGZgNmTBgMBoPBaAMFyQHWJhA8MfEg6zlFKGpGhSilM5dkxOkaqpQc/EWWlwOsaYLEo8U4JMTDthHudRuroxO0E9SOpi9/jC3jtjhhrhWYhoJFn44PxLPQuWCOMjsLpex7W6XT+ChBVmM//ozNXhwHMUsi75g1xVDMB2lFrjaDsDHhUMwSHTvxoN2SCDbWLmaEEV1SBmFKYSCkJxAkE4gdti6IR32QiUN6Zaz4dBObcFohNClJodHIcpvCcBZDGxtXpiS00MhaiF9hzofinQBAIsu2lKYyYefT/ML77WnPrAO4tBLSmNSyprapAJQx08mGF9BEF58JKz4dhbNFpXDV/0qE1k3/9tkvVcW+VvDMSFVPgr3MZNIJ+1cAyOQVFSuJWENSbJIgXYIUzpRTizJoodBrMggP9OQxSqbUhtET5ftSc3HXNPMvVc0MaFCQbRRIzMVTEGh4WYw3JTItSs/maNpgdAY25TAYDAaDwdhswIwJg8FgMBhtkI2DV07GppyOwRMTA9nbA1E3XHzU5gEMY5b45hoD602TqYryFXRei9Do1QM14dKrPHK6jefR6lg7b592303fJJN57+GF+S9kLi41UOzDv3aq6NUhKsLUV5p3qmKr0Gcb86FYpvJYTOHmhYtXYkw4vjdOXtaZbjIy25BHRKyhzT5nwiFzjXNr8r0aAOfBkMRZIfQ8ACRB2PlIqnEz4YxXfZslWEmbHVh7XjlK5wGswv5K5yhU2zGRecea7IzZKFXSeuhQpuLqZ5AGbu6bTU8BCFV8pq2TRoUpJrS2CI2CF1shE7EItj4884uLuzOySaD0MyNQyDQMuM8qcc8udVIVf6elLUhoa8KJjVeO/4wmWgMaSJIUWihMquWBVChmSSOLsL5ZQxXoXtdkZs06sdkqLdFMJ4b0V1pCjdErR7FXTsdgUw6DwWAwGIzNBsyYMBgMBoPRBmzKmVjwxMRAxDFEzfCXEcVxFqUAa9bMYQKtGSK6TcMdeOF066lDdUYTcr5tduPQg8fnnrv4Ulb1QU1VBGErVVeiHJK+qxDznV1PS/cHmYQhXOZgTcHUEhdMrWmy0zb7TDuB500eYK1ownFmOjhKnILmUbfkJRJpa8Kw+7ytzdQbBE+LOjR3tEMn9UbTdruAaVXlQs8jCh7n991uHFUB5ZQx3YgW9YTQJW8sMukIIew+4/gD2cllINOIAKC8oGQerOeX9Eww9Ez44edb/cxUeedYU6Qbs31PZhqzTXuArC9vhDzGwrZF5gU8pHNIqRPhrncQ/C+Rmc0gvWXfRjRFZk04dK/XNeoYSvPBkMcWoR7noen7koatVzMnlyqJZja6TNPdQmHsXjUTM9KXB3hiwmAwGAxGG4xPHBNWTnQKvlIMBoPBYDA2GzBjYiB6ewEKrNbWK8cQcikFU1POFCMqtnSsGx6vU/W2bbscoMx+Dttql5HX9l8xWLsvSLjRCq36CUw6VXWE1rk5R3l1quq1GIOA73FBgcpksYp0Xj1ljx04Ktx6KThTTmpSdfheDUAxI6s14VDmYOkf03ac+WmT2cYMLVKlPDiJ8XbIPW4CT53IHBujJ067elXHOumnyoQzlvTvSjvPHRUETPP7iM21SOFMA9YDqMqeAhTNbGSnITOf1DYAHj1EutLDzhTxMw6b/aruzEBpD5BSBmNvOKEpxzarXFu2Td8bqMILJx+3V1QWj9FYVF0j680b1TVKrmO+iybAnFAuV5D9LlpPHu36s5fNeNPEGWoaQBPojxtoygw1kzm4Yb4wvUnTBlYjUw5lkKZ2eqIUcZBvaWOaIE0nxkAyPrlymAfoFDwxYTAYDAajDRTEmCbU1AajM/AUjsFgMBgMxmYDZkwI9cR54xC0rvB8CT97phyCNO1Ensy+XR6cIBhZsa1RzLJ9M0rYZjszj61P/G8FTdpJzp/Rwhub0LqQFp6C1lkTTTuXCK3zAGyAy29iArQJMxcveEB4XhHUv22KcuQk5LnjdRMV6yk/mFpIpZMHTqSdgxOZcMyxKCavHIUamW5Ck45U3vuscGxTIDTXFLxi2rg/hqtDMrNkXqAzpYV9r7UomyM6RJWnT1X/ZB6wFpCwngbKNhRvGzwvKiYTHJk7PHNLaPbI8meBrEhZj0u/5fcVsv0Fs014mtqVKZmAvGO27cD0mNXoPLz+TD4cyosjjeeNHBaQjaD7hExo7ntJAen8+93KhEEmnVottaa38HnrNZ44UmgMZflAB5v5CQylCdLhiWEh2JQzseCJCYPBYDAYbTA+cUx4YtIpeGJSBT9mCS1r7NaIxLzljiCmxcZBodDNshgTxd9W9RdCeLFK/G3IWoQi2HbC1Hbi15AFUdJT8cnqMlVtj7RvJLQJ+29b81abTrzqnRMxKiSoDdqW3s7MiJ3pFFWUZxEGgMxkmbWry8TVK8WF8GJfkLAQZlWtTchuEWsIyrxqjkUJhdrOq9SiDIpCewfh5pMos0yFqBB9Ap0LVcN6vrC0Xf2QKSnECqlos/AZomVIeu3Fw7D724y/CmF/VfFMQqakrY6bxiPhPV6isLHh6zU8psI8d+Y5lWl+zDImdftTUpmlIuh+XNCS4Yu9TogxCcL160hD2Fj2+UYOme9IUyI1LDExfDUjyM6Uy8q7MUvQVNI+9wQFYdmQIcOGZB7jYssFKQWaKkJWop0YLwfwxITBYDAYjDbwzY5jaYPRGXhiwmAwGAxGG6hxMOVwgLXOwRMTQqaALBdaoZFvdZpaE062fn3LqiLO6Uc5KY9RLuqG908Sz7Gf4lh3MWv2xauhWcM387SrXxqsZ1JqZdZxwQiqY2iHbXVyrBuTjtKtr1PFOZU0gX5fpTgqxqTSBCSZh5r5PtWT3yM1ObGmmKxmKGVj0lGRJ4ANLUh+yPLEmPxIIEnmPam90PNFwV9s9sdxhkwEMUq8cPNkiqAw3gRfFBvLajEhMLaVm4TuKk6Kn1UYMGJIa8pxlH2uMxf2p9tGzSFzlbnY0SjzjQihbcZb279pUxQsFMWYMiTmFBLQQd8Cbuxe1Rxk3rFZpY1l1/SV9mqk9jtt2vPNJ57w234Otbr+Zyt+bX19/ND3AIopEahaYJ6i6y61q0ciWLsdjDwhbF6+ZkLJb2zU7D1+bn0/GkJhQ324UDZT0ppnQoEoCV2F0Pa+ZZkr479nvHzAExMGg8FgMNpAaQk1Rq+asdb/e0JXV2rHHXeEEKL0OuusswAAN954I+bNm4etttoKQggsW7ZsxDavu+66yjaHhoZsmfXr1+OEE07ANttsgxNOOAEbNmywxxYsWAAhBC677LJCuzfffLNzGWUwGAwGY5TIIMbl1Q0uvfRS7LPPPpg8eTKmT5+Of/qnf8LDDz9cKKO1xqJFizBr1iz09vbioIMOwu9///tCmeHhYXzgAx/AVltthUmTJuGYY47Bk08+WSizatUqzJ8/HwMDAxgYGMD8+fOxevXqUV2r8UBXE5N7770XzzzzjH3deuutAIDjjjsOALBhwwbsv//+pUnCSJgyZUqh3WeeeQY9PT32+FVXXYX+/n787Gc/Q19fH6666qpC/Z6eHnzmM5/BqlWruurXh163HmrNWqg1a5HZ1xpk69e3NeMUkGXmpfKXb0bQKn/ZMpnzsKGXX6/qVRiwLr4fqXwVyJzjm3XC/ZEsvqT3Cuv59cO2CFJ0Zs7yvY/8a1SFTs+3qo7W0LGEjiVUPYKqR8h6JJqT8lfaK/JXj8nC2ms8Kuq5p05Wy0N6q7qGivMXEgUkGkg0RKzyV5S/ZKwQ17L8FeevWpKilqSIKXaJ0Hko7zhDIouvVh43UmjEQuUv6V6lY8HxMMw3ifyonn1Bj2jGUVrYCJnUTqokUiXRyOL8lUZ2Xx4bwnnfkDmHPHT8l7+/HWpRhlpUvF7hmP2QJPkODQhjYqODMn+JSENEOjfJmX3avnQeqj5s2MQM0VEe60Mn+fNB7wGzP0Lw0rZNHeUveqZU4r03L02vxHtPbdEYvc8gryEao6jwCNLFl7k0gNDI6vlLJbknmqrlL9+rJ21ESBsRXljbjxfW9mP9xjo2DNYBAOs39mDdhh6sXD0FK1dPwXOrJ+O51ZPx4vo+bGzUsLFRQzON0Eyj3JtHCaRZbuZpNGMMN/JXI43QSCPzOYg9tYlAjMlYX93g9ttvx1lnnYW77roLt956K9I0xeGHH15YmF9++eW44oorcPXVV+Pee+/FzJkzcdhhh2HdunW2zDnnnIObbroJ3/72t3HHHXdg/fr1OProowseTSeddBKWLVuGW265BbfccguWLVuG+fPnj/3CjRJdmXK23nrrwufLLrsMO++8M+bOnQsA9kQee+yxrgYhhMDMmTNbHl+9ejV23XVXzJ49G7vvvjteeOGFwvG3vOUt+POf/4xLL70Ul19+eVd9MxgMBoMxUVi7dm3hc71eR71eL5W75ZZbCp+XLFmC6dOn47777sOBBx4IrTWuuuoqfOpTn8Kxxx4LAPja176GGTNm4Jvf/Cbe9773Yc2aNbj22mvxjW98A295y1sAANdffz223357LF26FPPmzcMf/vAH3HLLLbjrrruw7777AgC+/OUvY7/99sPDDz+M3XbbbVNchrYYtdGr0Wjg+uuvx6mnnjpmk8n69euxww47YLvttsPRRx+N+++/v3D87LPPxpe+9CUkSYIlS5bggx/8YOF4FEW45JJLsHjx4hJFxWAwGAzGWJBhPMw5ObbffntrMhkYGMCll17a0RjWrFkDAJg2bRoAYPny5Vi5ciUOP/xwW6Zer2Pu3Lm48847AQD33Xcfms1mocysWbOwxx572DK//vWvMTAwYCclADBnzhwMDAzYMhONUYtfb775ZqxevRoLFiwY0wB23313XHfddZg9ezbWrl2Lz33uc9h///3xwAMPYJdddgGQa1seeeQRPPfcc5gxY0blROjtb3879tprLyxcuBDXXntt1+MQ6TAiYbwcyNkhSVqWL9SN88soe4yCvMdc1noCRMElpoBlvumh1cROSGv2SEzAr6QmXd1W9box43Rbz8+8HJpW2nkBhZCiXMYPbAcgqZtz7o0qMz535FzSauotJXRsvHCMNw4mmfvYLxH3Go+LSaYTY1mUCSDN4iYyAapsVmETth6JsB4Pwrhh2CwFsYKke2rGFpnzpzVTn3SeRYkNEOdORJq2+6Nm8ZQomBiAMLZ52yBosrxfmv7Ic8nWr7jFVC8CbJZYG4zLNF4z7ilKR4i8fmpa2q302qdHgvonjyMhNCJdDDpHEEKjZhqgc6LfikxF0OZGaTOWGGRGcoEKbYh88pAhN5qCAcjcExorPcue5wyZeLQNgpgfo/uZ1AV0s8Irp8rDpwV8jx0b0C3MQOyDvl7k6USZk4UufZnCdA0CgIjNs9xr2rHPtHAFG8bjyXjTSKnyZykB5GAdEqp0jiJWkL25F4/NFE3nI90zHZt9WWqepUxAD09MduHxFL8+8cQTmDJlit1fxZaE0Frj3HPPxT/8wz9gjz32AACsXLkSADBjxoxC2RkzZuDxxx+3ZWq1GqZOnVoqQ/VXrlyJ6dOnl/qcPn26LTPRGPXE5Nprr8WRRx6JWbNmjWkAc+bMwZw5c+zn/fffH69//euxePFifP7zn7f7pZRtzT0A8JnPfAaHHHIIzjvvvK7Hceq1x6Kvr6/rehONkz+9z0s9hAnHyZ98w0s9hE2LIHjl2cNvBIZfmqG8VDg3ff3EdbYZ+CJePOOVL/UQJhwXD7yq88JV0hHa560XN8qNOGksg3oJMGXKlMLEpBOcffbZePDBB3HHHXeUjoULde3nCmuBsExV+U7a2VQY1Vf08ccfx9KlS3HjjTeO93ggpcQ+++yDRx55pOu6Bx54IObNm4dPfvKTXTM5Xz3tRiSiM4bEh4ikDUkvkjx+iaAZcD3JRaJAZ3E8KoWkxBrEOHnhm/D1C+9BczgbPeMxUn/dlOmmv7CddgJYjzE5+fw34uv/+hs0m0FffqI987aT8Bp2JRhLKJNCQPXn28bk/OvQ6JdoGqYkNXPVlFaJNSDrMas6YkxowVPPZxgizkWuACDNio9Co8exizFiw6WbMr0QOCd9Pa6u/waakpcFS+eqhH2ihSB2JITMSSyV7a9V/XYxUEj0CrhYIU2zrG6ksflcrF/TEuemr8cV8W/R8Jb54drUMihCu5guHSQvpHEMpRGazXwMwylRXGbjxVKx77Mic6Iz6cK0m2PCJJATqfcsGjZL0y+rEbtSXJA6JC6etjMuePEvGCb2lMLAp8Il/6PzpjEKR4KFbIjIBGTTsBkUW4Ta8W4jMXuqXmT6cjpE237sPh+6eJ5+O+hRLgVEcH8R6fycB16FC1b9GcNQJXZGJBmiWj5guv7ZcP7c0PdIeNkx7D1RAtngECYCL2USvw984AP4wQ9+gF/96lfYbrvt7H5aqK9cuRLbbLON3U+WBSrTaDSwatWqAmvy3HPP4c1vfrMt8+yzz5b6ff7550tszERhVBMTEuG89a1vHe/xQGuNZcuWYfbs2aOqf9lll2GvvfbCrrvu2lW9dLBZ/jJ2ABFFNniWyIjG9pJS0Be2E0+UyolJsX5zOPu7mZgQmsMKzWb4a+xPTIhaH3k8NvhaBigTxitr5NuG6aORCjRT07f5gU9N90oBmaJgUsUthQUTUDllDTexEGabQdngaTShoCBikXkAG0JBm/9QpYlJBUffaW6cEGEGXi06mJi0+ZKQRw4ApKa++X+JhrnuTVH949wQKpiYBJ40/sREuGBzIyEz42gIYdsfRrEeBVrThffh1v3TFHZL33evLcqCHWzzjNeu3DAUhsx/WpeDRrj3dN6etcdacMM5ugZojhZuCxMT+wzTc1u8CkHxInS5X2Wzjyuvppvk5Z9cpWEoDMMFCLSxHqEQmXtC15tca6X9TvkWIHdvFEZ+BsYD2nu2x9JGV+W1xgc+8AHcdNNNuO2227DTTjsVju+0006YOXMmbr31Vuy9994Acu3n7bffjs985jMAgDe84Q1IkgS33norjj/+eADAM888g4ceesg6iuy3335Ys2YN7rnnHrzpTW8CANx9991Ys2aNnbxMNLqemCilsGTJEpxyyimI42L1F198EStWrMDTTz8NANbneubMmXZ2d/LJJ2Pbbbe1gp8LL7wQc+bMwS677IK1a9fi85//PJYtW4YvfOELozqh2bNn493vfjcWL148qvoMBoPBYLzUOOuss/DNb34T3//+9zF58mSr9xgYGEBvby+EEDjnnHNwySWXYJdddsEuu+yCSy65BH19fTjppJNs2dNOOw3nnXcettxyS0ybNg0f/vCHMXv2bOul8+pXvxpHHHEETj/9dHzpS18CAJxxxhk4+uijXxKPHGAUE5OlS5dixYoVOPXUU0vHfvCDH+A973mP/XzCCScAABYuXIhFixYBAFasWAEp3app9erVOOOMM7By5UoMDAxg7733xq9+9Ss7cxsNLr74Ynz3u98ddf2xQtNKKE0BO3kLVordhKYH2gtNR2sHDEW07dopZR7WZdFqO/Fr2Fcn4fT9dsPy3uWsZEpatW8ErzqW0DUjojNpfZVRo1J8EiA33eTHYI+5fWaVmRDdrO02NOHQ5zhSNjR6yJjEQgDNPAw9sSouy67ZqrLxPcw2DHTGmLhQ+G7VaRmPdqkIWrRTlehM2dVx8VyB/La26iWkvS3jpAWaZmzuvF258FGgdoabsQ17rrLiGN29AmhdrgSZC4yYU2ZQxPZERVaAziKPKeJMDwBcKgKrjDWfTXwUAC4DdeTFafGepRBhLBelAZWSeSnvOBoSha1ITYZjd6IeyaGhYhKbmkMk3qUYJcK9F3T9+o3pMnKCVk13lMpkApaKpmtiM3+7c9RemoLCuVHI+cwbL5mLtAAmKCT9S2HK+eIXvwgAOOiggwr7lyxZYqUKH/3oRzE4OIj3v//9WLVqFfbdd1/87Gc/w+TJk235K6+8EnEc4/jjj8fg4CAOPfRQXHfddYgi91tyww034F/+5V+s984xxxyDq6++ehRnOT7oemJy+OGHO3oywIIFC0bUdtx2222Fz1deeSWuvPLKbodhcd1115X27bDDDoXIsQwGg8FgjBYvRXbhVv9nfQghsGjRIrvwr0JPTw8WL17c1oowbdo0XH/99V2Nb1OCg/czGAwGg8HYbLAZOM69fKApc21mqPFIl80cY3W/otDssg1/3Qn8cVCMkKpsw6FJRHi0rArOqRuTzlgxkikoRFSk4SEltHmvTPwRm301Es6DIQm2dQ1VM2aWurnfcXksoQknMeHm40iVRa82c7Ch34UKPYhL3i5+vdBsUxWG3cY4Edq2ReaaRtZ5WO9OsxXbeCDBuFMlkSkyS0loc9GbzRhNmblrE5rC2gT2qLJqUnZb6ne4GSNLyZQjC2XJhcU3kUgrWnd3QhkPEUXt0CPdY56DSNnr43uOeCNFQcJJJjSypMbusDN3VJwvxfgQXhnzVtXze5nK4k97NCgQGY8d8vyhrY6Fq09eRPRIkJdRpN1YyExDXjJCOE8bFWw1PPOtqR8sh7US1RmaC58FNJmrUq+P4Qky5UAiG+M6fqz1/57AExMGg8FgMNrgpTDl/D2DJyYMBoPBYLRBHgBgjJFfmTHpGDwxGSN0llkpu/UOsQEDtHsvR/FQtoj50Lp8FzNyIZw5KKznm13aeQ/RsdCkU4VuTVl+nJbRmL+Cc9PkedOXu9RkPbGlvZUJ95/Vjdmh5gJkOZOO45hFweMAAAVTM9soVi6UNplbPM+XMFYImWQS7zTJrOAClOXbTEsbv0OKIt3ve9nIdiaQoLy/khuvVSF5IJApZe3GPKb/0Pq6u26RRgMSGAA2DtWQJU3PYym3M9SCYGpS6FJAOTqPRGboM4Hp+pM8dG5DuZ+4F7M8Wp6MKq4Jcs8fa86puAxUT0bGBlILDW4ulLr1MjHfDa0FhLA+K3nW4uD+FR7zNl5VVV+HkoXUjJW8bWQMaOOVI8w2okey4bzQKLR9GnsmHJifImveIpMtfQ88kxWZmegeF4K85F5HNrYJhcQvjL343aJAdyIVLtw+HYs0JiiMCWOCwRMTBoPBYDDaINMC2Rgn7WOt//cEnpiMB/QYp+0lxsKsq3y2wiYDE2UWo2USwA7jkrRjM9rED+mov/HKtVCRxK+tkJaYEoo5YXz2tWlH1SJkPRS3xKzyjcBVx0BWd+/zetQuyvEUKKmbH8eE2IuIVvzlWCPCE6T67WRaYjgQphLzkIdkL7ZFbEItctFibTwSw1wQk1HFjoSxUnxUMSihoJXErE0VWcaA0DRMz/CgubgbI7fKnVRkHLQWtn6WufghdN7+OfvwWaGGYZhWN/IcAkMm/HympL1OitiM8LwgKttvhTDGiNbCsTGBoFapXCBq9bZRRRzQLvrO2zZbJfKQ+QB007C3xDT4Qlf6mhOJS2JYDUiTm4lSMBDToiZ5/aUtvstaFhIKFrZ+8kNzDbzwKV4ZA+rDbKU9DwHRpPETC6pt3JZNDdaYTCzY6MVgMBgMBmOzATMmDAaDwWC0gdYSaoyRX/UY6/89gScm44F2ItVQ9NpOTFplwrFxQ6TbSj16E0m7/ruNMdIqlogvrPX3+X1U1SVzTRiCPpI2zH9VtmabmC/y+syMeK8nf8StCceEnVd1ibReNOUQo6wlClldi8e0C9Nt4pnIJOfLo8gJNcmEIytCivsJ6QDfFOHMLeGtIDNNJBUS874e5SrGOMiyqyBsjJLQhOOHxS6ZcrQovM/LF8ukmXQmHGM+aAzn11il0glbw5TPtLumIEgkXFOIzLlHkUIKZx5y5qJ8O5y66xnGUhFW/OqF1g/G30wjlznYlAlDu1eGSmn7dRGF/gvjCnThEqSDp+uhK2xJ7b/TvunG30IJJzolgShdCmpSA9KYQsiEEzW9bslkGbvhAS7Eva4pa0JxF7DL3yBtTpvGT+Y5JazphmKUUF8k1JVNYcdvm0sFMDQx5pEMwiYWHEsbjM7AUzgGg8FgMBibDZgxYTAYDAajDfKA22MVv47TYP4OwBOT8YD24pYAntlFtI/FYY8FJhy/bCuTja4w53SbsbgTdBLHJIQQzrwScHLCOmJ431KKZ+BdKyG0Ne3oCND0qNpMwJGrR5431uwiXDiEGnnhyELZLBGFuCX51pgxYi+7MGUQjt1W1ygUvYtbAqCQUbiS3renW/QwCcOuJzJDjbIRm5PyY3XELULRh6HmAWcaIY+bZhaVTRhefTIXkMmHMvKSd02WSaRNE//FeIDoRv5ZDkrIhvOiAOBlqTWdCBcbI6spZEICvUBjQw3NOHWeTfarkZ9rauPCVJnGyh47KjBl5YOgY0XzFKy5ypWx1lmv7VLf1jpZNOl4XQVj9MciXJI2P9RHi3ujjUcLUPaOEZkz5YRxPax3jrffWnfMOaoEaE7J36eTTPwT89zbeCTtvF+0KJnsfBOSBXkm2bLONCSbZpzNYLzafSazjt/tRMUxUeOgMRlr/b8n8JViMBgMBoOx2YAZk3GAznIaQNQofGIbloQgRGumpKq+v29TMyVdCmt1aTyt29Cxdx52VRoIfAEoIaDqJLxLLCmlTRkdCyto1SFzIlFK0GfjMnifKVYJ7bOxS6LiCrOASDumJDHMSSmuSDk6qZ+4rx2bktdXqIussoz/ORS2+tswNolNopfJUrwSYmoUREHkCgCNZv4TkZrEdelQDAzlDIlomNgqJLhMhRUvUsI4WjpTHBgVu/e6GUGaey/XxICUNkEiCYuJNZMUEdZfSonWLIqNp0Isg/IZErMJPud0TmHYBcaEWDMhWzwcbZZ5Sok83ggJnFPhVtD+8MNkeKk3RmIPKDZJKEat6rdm2CkvvgwlpCRkvUDaZ5itMCoukcCtYpjYYbc+bn+6moDQAo5q8soYpk2mwT2iaxoQTnQeuhx8d5NAQVTG+em2DUZn4IkJg8FgMBhtwJFfJxY8MWEwGAwGow1YYzKx4InJeMIFqMi3UVQUwvplhBzZhOOLZynGRyRtgi5CSKOKbuORtIAWotRWoa/we+aNn0wuNrZIOKYIECbBoS1rhK3amHk0CVfrMRTFJfFC8zvTTdFco2OBjEw2iTPvAL741ZWnUPREcauqkPSUxK+uENVI9Fo0txTFr8XT9RP3hfFLrBjW+xzGJiH4obFDL4F2XgN+HJNhY56JTTyUOKqI/xHGQcnoApbFpMKLQUEmHNGCYpfwKG2trWlGZDmNr42wFkOmf2M+UX7sGDLdUDNR+VqVzDbKMyGQMNfG/PDK0nsr2jUNxBoqM+akFv9gtAJKYeXt9ctNOZRhNhezmiJe2HUbByZIWCe88mVlbeVwCseyui6ZcOz18y3GoVi23U+JX6/FmLQABJnrhgUKVje6jf61oMtvnh/pJR6kfVQmagCwJkPGywk8MWEwGAwGow0UxiFXDmtMOgZPTMYTmlbMxBZE1UwJUGRDWrAqWgjLOOjEYw8gcybDuhsWt9oTunXDnlQJ2FqK2nyBa1BGS1lmU4IIuDoS0IhcW1472rj7WnFrLKFRZEx0JEosiGVHIlEQwvr1lBVhCqiY3udbK4ateaI76a3UAcg4s0xJKHotnG4LYasQ2iaTiwK3Xz8ZXSthq49WP5RVLqe2T6HsexsJ1U/sZ54dFUYX9UShViAZkCitNKGF+spjU7QwYki3QrcjIRFtILrUUWSX51YnSi7dNQURF687udZWsREySDgI7bEn1AedY6ItwyaSgLqwXwOn0NRh2xCmX6IwJNA0z48X7TR0k7XMiX9tQ4Fu0I1f3Q80W2qbqvjPang/2jEnFf2HAX8BIDbfvaghEClvTFXPCx0jga/32SYfNCxKNOSSD25q6HEQv1akbWS0ABu9GAwGg8FgbDZgxoTBYDAYjDbwtV1jaYPRGXhisimhPef7qpglrWJ9+EnpKG5H5NWPTIROm7gr4ETJ/KBcW12JWH2EdKtvdglMOYVor62O+e2Ex6hIJ3FgCm3ROeYfNTxTDPXhmXCAXNRqo7sGQleVOLGrbceYL2SsShR2GJfEj6sRCTLbmMitUWb3tYLSjjZuZ8oJUTDJBIOkY5HUSIwpKoxYqiuS+DkrodeeLl7vKhFlGPlT+NaPiiikUCIv00I86oS27p7Yx8NEC9VD0nv2w5vktR3GLyHLVFMgGqYixedGRy56sBXGWlOiFy016KNw3lq434GGhCBTDl0PJbwYJeXzF8F4C+fWymJbELYGbVcVCsoWYo2QeSe8jLLimGfmszr4IRRMOf4zYs8taMea3TLvPZlyhoFsgsSv7JUzseArxWAwGAwGY7MBMybjiXCF77MUVdFZw/JVDEGYT8MXvY6E3Dczr1bVNrnyhgyFL6b12JfS0KxoNxi/11cpZ07VsZApCSAyDRFmwJJwS7bUrGATb3VJ500rXlH8rGLHkNgy3grY5sapU8TR8gUoEzxujH4UWACoxfkyLxLKMStmS+xE0yhz0ywiEsDCZ0Bky+VxGSHTIoRGRAyJF/E1REkY663Wbf6UDkSMlfAFmV4bQrcRW8OVC8Wb9hjgGLLQpVh6H8KvnSkaDQPxxuIY/UWujRpMOZZ6ioJsNHWrodl+rLf7kHCusB47YlmNQPxZCZ+NCssRC+S5bYdj81kJy3h0EEmVrklELr0NF+mXhOTNflPWi5ggTD9WIGt/m7wxmTajZuE0IABIsy8aMtuGhmh0/l0YC9iUM7HgiQmDwWAwGG3AIeknFmzKYTAYDAaDsdmAGZNxgIiDkIrtBK7thJ1kQglNKnACV6E0RNYFfdlq6umNTcelEK7538wzGwWpyrWULsZKaNIJ+/FQoOpHMOG4St452/FIJ+w1Zh5Lf3u0vTPP5Fsbs6TmRXpN3D76bCONJsUAG1oLCBK0moijFEE18uKaJDI4JlzMklDQmplBpmk+kKE0wRDFeAkQSdU2/gkw8srMmpBMOWmuaQZREvIqTxibvwFcjA8SL5uxpRVxL9oNJTRB6PbFCe3MGzoo48fVKDHpgWhXRy6WjbX6eOYWG3mUnjOyt9GzooSrF4o5szxGSWSuWbxBIAtihQgvxks4fl/gWhLBeqbL0BRD5iI6P78/acwv0bB3vvRdMmWUjRGEQkwRv2xVEkIyuyjXtD0/aseOzTPp0ZhCU6xQ7lgyaJ7RhraxYDY12JQzseCJCYPBYDAYbcATk4kFT0wYDAaDwWgDnphMLHhiMp6gkPCZCVnue9AQ7VmV1C5MwqecXJ2ozIKnTOiVE4amLzRWbUqqDBsfml0ilONBEKJyor6RPCqKfY1wPDxPCvdP48m0i78RlRuTxlOHTDelMNyeGaFAlwMu5oR/0NLmwoUbN/eGTDhkrhHCmXASWeTWMyWt902YKE+k+WCHmhGGyUxFXZFXkJIu3H0Lm4aEdmYaa7Zx4xclO4Fpriq0PpmnKHaHZ65w/Lu5/5Fn5gierUIIB/96j2TF6/a3vEV57fcVjt9c5LRXQ9SL9aKhomnCB5kifDNXGMrdN22JzOapRDwIKM+UYbelMXpDDW5PlQko9PRx+7X9fkpjFnWh3TWiwCTixyjJGxLu983c78x4J6U9opAA047X9EEOUrJR9BKyXjYNd270vbXj8LwZaYzSbKOGgm62jwnE+NsET0wYDAaDwWgDZkwmFjwxGQfoNJ/6i8gsoUnVlmVlsWu7h7MiyqoVmtFKIlX5q50/VUFg2kKgKts04ItwQ8am26ispbG1GCeKq2qhKoTD/jiqolV610+HCRE9ER9g4pjQuVnxI7Fa2gkag3gYENqyB8RihDFLIqkQB8E9SOCaKWmZkswwL40sH0hktsPNBEMoJvpLzDdVRpkTqMKJbX0UIsBWJOojhCJY6NZtWcZEuBghwj4Lpp0E9vlumfytHUsiOmBIRjzuxtmqXy2Lgyp8Xaww1LALRnBZiAdCIlhZrOMLT0sxSkzA4MQ8c/Fg/vMQnpMdWZAgsTDeKvFrKzbFi4tCImdiHGISkaa6paBYe8+9zStI/zXMhVOekLyUhC9zyR1lM7+OdC2JMRGZdnFLPCFy/obYEXgCeHeOIwRRHjdojN3dd2Jkui8PsLswg8FgMBiMzQbMmDAYDAaD0QZsyplY8MRkU4DEq0qVhanE30ZRtVi10A5gCcDMxewQShU43lLYd4IfRyUw4VQJRm3MBX9faMKpQlYUSLYrq/2w4EHbHdGyNvEfbGJCatOPWWH7azWUCvrbHpKAjikUfdFcEkUujkhs4piEMUuk1zCZcNr9KJG5JM0kEAFKiVLCL6LGa1Fm2y/FHOnwh69Voj7/WEsI7ZnzTB2qEplEdgBkGoiGK9vyxZVB0XbDaBPIxG/PH1shzUBSFA/LjcaUNiQQb8grJOvyImRu8OOBhN0bLXMh0ZzVFwcpEcjaGzVcSHc79oK5qXw+ttsqCyftC+tR/xqANR2RedczU1LjQeoHqwePhP3NINGrNWVl7al3X/wapUA8TOYZsx3StqO015g5KX6JJ951MWWc6F23EuePM3hiMrFgUw6DwWAwGIzNBsyYjAOs6LUqUR+BViLS+0zlO0nKZxkX5cS1xDREhgWh1YNdorjoqFZYW5FMz+uk3Gc4Nq+eCI+RKFB4/QQsiBVRSuktx0ZgWvwotRVTaREIYlUkrECPVqw2qivtj91K1wpi64Z56M0gTMRXaZiTODERXCOFJDbu4AFTQaJWSNVWKCcs4yEKn3VFGWJDqM9anBWiyI4ntBYlNkWZZ8o+W7p8m+zKWbtnmiLnCq9eZZ+tNOGhCLcgmm5zDsQYBOyIril7T6O4+FDSOcq1MWpr8321NWY1T27CGqWoqDY6qcdSaM91GvCeNymKLssZSlFa/esauutqCeuCbfdRPVQIYgNoKez3zIpXe4g9dZGV6XydaJe+ry6JYci2Rg3tMVNF9rJQrqkRpdqKb5MNhpVsaqgaPTfF8yCmSjadK7H/zEwUCcGMycSCJyYMBoPBYLQBT0wmFmzKYTAYDAaDsdmAGZMxQkSRM+UQF2uDTsjW5gmtAEv9tyqjy+/JvNJJHBGlPPFakBSuwnwkQqGu1hWxVbx6VohaHIvQ2jPrjH2VoGUFRSyEbZvoc6KDs7pAZt6ndRdrAShS7FlP/j7rNRR3nzHRJMqacIj2pwiocaRKlz6zAR4MNa6Fi9Ta7rzsZTYmHe8Y9UcmnJ4457QjqUomnDBWiYIo76tYrdmgxF7PIhDWliGgSYhtBdnUoHACZGuKMO1pVyZozpywLggvWyXcK733y0a6wpRjzAWJQlzPr2Gtlm+bzfx7qofzSsk6IN6Q14+HjGlj2Jlv3DkEZiYy30j3nGUyFHTn31nhiWOtKUi4IvYUAyG39rLhWXOH9MqEkWbt2Ly2SbwamDdF5sTKqhmcdyCYBVwcFJvoL/ZNWM70Q+dGQ4gHNZRnyrFfmx6JZr8RiZM42JiUauuNKXWjs3tlxgSVJaLStLsp4Js5x9IGozPwxITBYDAYjDZQEGMOsDbW+n9P4InJeMCo0og5cWJYbzrfThjbst12Kr8ym2IXXqEIFrD5d7R1CZZOxNZN9EQqG1eIYKtYGBoTMR50TXyhX+i6LPKVt6Y+IglFbVsBoHBMiRHlpX35wWafsC6NlMbeil9pRdvjMSW1omuwjJRlSoQssxPSnm5RvJr5KyLDnrRjTuiHikSzxGlJqVFL8lV9j9nGnm+pFdm2aE+1Wd3pDm3l0nOPzitS28pzTyfKxVveB67Etl96I4Ioo62EjG0Yk1JuIzMOlWhoupdG9BoZxinpSdFTy5fhqaEMmoO56rm+Kr+e9TVAfZ1ZoQ8SY+C51LaCFYj63wk65sYsoEcUqbqTLG797qNAdOu7vofXxnc3VrJYxuazaQrbke8WXRyPdpFaaUyZc9slFscKySP3HFBAZZmZ3DnEppoyjcmyxJTEGw1TOWzup9LIarLQNrsLv3zBGhMGg8FgMBibDZgxGSN0lkHEZplg2QDP0N6O9QjyuVhU5Lop+2hWuPIat+ECc2Lddp1rHpBrLURJEBAwH1WL/dFOZVuspKvK5G6VolCH2BMVExMi7XtapaU9+edmv0BqmBJt3TVRKKsS7Vb8dknnrie5kEZB7hWlPKYm8AAnaC+7L11jXxcSshnEqtSMMKeeNKGNpiSpCNrWihKuyovTLleOIz4M4wOXeZiCx7nCNPYIIiqeuF2VK88dvEI3Q/CHMqIbcCs9ST7wvNuaGU9PBmk0JYnRkxDjQ1odABgezh8KsSbf1l/M99fWKufCStmpPRdZHbKeodYkEm41HzIWXSJkVvJM5WEhU0QIjz2isQRbj5Hy89gAuRtuZHICRUHwM+Fl+7UB2SwDQu7HrnHSHUkv2GLs5adSAJqTihdFC9j+40FV6J+gYmnvBW2z2tjNK52CNSYTC56YMBgMBoPRBmzKmViwKYfBYDAYDMZmA2ZMxhPEjfvi15D+9cu0MuFYjt0zZ8SeS7IQOY0sg3llRURY3YLqFEpBw1PPdYoK05SuMjfJFmX8fVYQG9QvCfgEtLGbZHXjKtgjrCswuQaT+2/a45tsgm3NmbLsAsbQz8iMuE74gl5DTRuTgPZMKnXjdpqFAjwpEQV2MFVhXiGQ2SSWAFIgiRSU2VflttvKPOO324o2brdqE0KTNRDanL+0phknDFZUqEb57M14MgGkZMIy7YT5l0Z61FoMr2jCMefiRXUFABFpSGNmisnN2twjpQWGhvOHoLk2t/PV1pfXZdZMZ8XTbksCTWcrLQ5WKN90En63i+1r6a5NR/AErt6uvGmt3XeIrLBRcQvpjolgK1NnwnGmFHNNM898QyJ76iM21y8SzoXY/AbRd1vVJKRw39NMOpMrIR7U1i04GjQu+9YV2bsPQU6tcQ583BZsyplY8MSEwWAwGIw26NSbbaQ2GJ2BJybjgU5cgUM2pVC/RaA1P4gYHYqjPHhZJqzY1TIlKliCae1cOaW3j5onF+KQealCRZFSVmNvlahbiF2ta7BwwbjsijtYZdJn5WU2tRlOawJpb/4+NUwJuQKrxHsf5MyxK9dI22BQVvxqO4ZdXdKq1uaDEeU8MjbXjXWphc2DE7oU+5CmE7pFESi4WTkPjs+StPqBrBK9dgMJjQxF8SIxJYpy90ht2SMbD80+o7Ls5krjpqL+Bx/tRK7+ceGJMCkfDwXBi5V1D7YpokxDzTRCs2nc+eneUqAx8/wMbinRnFQcvxVN1zoTsoZ5dPwgalo6BkMn3jWxAeq8foOvj5/rpvTdascctMhZVRp3eN+M6FU26QSc+FYneaNpv3G77pOWcaF8Nj7TIcmVODLPTCDClam2bsHE1Fg2hk6jqRE18gppX2TLWEaH8bICT0wYDAaDwWgDz5I1pjYYnWGTi1933HFHCCFKr7POOgsAcOONN2LevHnYaqutIITAsmXLSm08/PDD2H///bHddtvhoosuqmz/rrvuKuw/55xzcNBBB22q02IwGAzG3wko8utYX4zOsMkZk3vvvRdZ5mIIPPTQQzjssMNw3HHHAQA2bNiA/fffH8cddxxOP/30yjbOOusszJ8/H/vssw/OPPNMHHroodh///3t8Z6eHnzsYx/D7bffvmlPphXo/Gz8D0N/+gJXEcwB28U4qchB40d21EJA+GYfp1gsfNZSdjT1FCFFTGhTVwtRMuEU6ovgWKksnAkniPyqRZ4Dg+jgdFIEE3rCmm2yurBRXX0TDn2mY2HuDjLb6FhbUwCVsVFehXtPMTvItCGkLkVzjWTAg7eBFBow9a2ZJ4juKYWmVEM2yms7+/R4uiGKUgjRsABsHiEdmmki7UV4DaqRvSpDW7Qz4QC5GcfmwbEWjfJzR2a2zAiam2lkc/zoIP5JYwqZB4F0OGjHPFM68uJ/+KYXb1slxhSpV0e4PDVpD5CSRt6LKxK27V/PViacQn6c0nUvv7f5bypuNZlipDGbkJgVALQR4Df78y/j0FRnlramTlUcI5mw8jImtw39PBrzT7JRQxi7YNoTmb7Md8OYaqIhZcv4ZrIwNxDj5YFNPjHZeuutC58vu+wy7Lzzzpg7dy4AYP78+QCAxx57rGUbq1evxt57740999wTs2bNwpo1awrH3/e+9+GLX/wifvzjH+Ooo44a3xNgMBgMxt812CtnYjGhGpNGo4Hrr78e5557rhUHdoKLLroIhx12GAYHB3H00Udj3rx5heM77rgjzjzzTHziE5/AEUccAdmJmHMcQa6saJpEDxSB1XcXrjrdFu7CRaaEljW0WtC5aFXpskuuzWrcQV+dolV2YdlGNNvmXH3Ba0nsarMES2Q1AUkiuzqQmpVrs4/KuPw3oYgxq2sX8TUq0hG+4NUyJVF5yRuyGe1OjRgLYlIktOf5bVagXtbeKGiU+oqUa0cFzEUosB0JoT2829tP46XFtRXfKuGEsea6Kbu6V5bJc8Jos22QilS0dPPMI/7SAIqsiGPcdPkmkD5TCecu64le6Zi9p8bNWPUaoaVh19JMQDRp3NQvfe8ERJArxt4bj+WwImv6mpg6MsvHSV+ZrAfISBRKrIrHJoURi6FdW37+G+o/ZEHs+D2haSvGxIf7vaGyhsmYXMPQlvkXzorOjSu1zLRlSohxoXqqVr7fVCbZ6NgQe96U98qEBbAMTlO7sSnPtbk5MZSJ0sJFyh5DG4zOMKETk5tvvhmrV6/GggULuqp31FFH4fnnn8fatWtLDAzh/PPPx5IlS3DDDTdYFobBYDAYjLGiKgPIaNp4ueDcc8/tus7555+PadOmdVR2Qicm1157LY488kjMmjWr67r1er3lpATITUYf/vCH8elPfxrvete7um4/7k2QiKTregAgiCGpGXdEs9IXCYBa4AocBYHS6L1fxl/eZpTrQ7htZpaW1gXZ6BDsarNqkBXsTJU2pNU5VuUFSULdTOv+tJdtNB+jyz1C/We9JsBZrwDqwmUwnhrZVXrs6UlIWkM6AGmORTFKeVzsStYGnBIoRZoiVkNqKwmKiFWhDNLQkOZCx7RKBDEljt2w3VGANnIFhi67Apt6NXMdeoRARCdA5+j5j5YCqwUUgs5T2Y6IcAWntSPILItjGoroHklHa1C2WmVzB3nPA32VAjdtqQGREg0C1E27NSnyK0RMCT0b9Avl5V6xsDmeSBAiENNqmtgr0vMIjcxSG2bblxbOVWUSWbMN25qSkCIQZ/h1iH2joH2UrVcDsiHsV1xOEdV6kiCbtWNFhKWv7M+GaTtqFNmWQnVyyRXu54UkUpTrJtYC5J2b1CNbHgA0feH6Y2ALYpzMc0r1m0Bsct1QdmLKBNzsE4jM97ge5ZcuNqyUjc/WG1n2RffSdys/RoHXEu1CRcYUaC3VSNOX0X/7vyFcddVV2G+//VCr1Toqf8cdd+Dss8/e/CYmjz/+OJYuXYobb7xxk/Vx7rnn4pprrsE111zTdd1Trz0WfX19m2BU44uTL3jjSz2ECcd5B+/4Ug+hPYL/d2PFmRvfND4NjSdksAXcr0d97M1fuONOY2+kHQQ680Hs3bTDICzceceJ6WgzwocOG/97vHHjRvx86bg3WwJrTMq46aabMH369I7KTp48uau2J2xismTJEkyfPh1vfetbN1kf/f39uOCCC7Bo0SK87W1v66ruV0+7cRwYk3z2KBKzrScAzSilXYKbSl0yJjWJky94I75+8W/QHA6WTi8FYxJHUEkQLG6cGJNmr0BWF6jFAh88cif8+y8fw5BZSWYeYxJmDLZeOonT31ivHEdhmP5Rzi5cYEyM/dss3ayXjnCMR7gql16ZyN4ac0yU6xOIuajpCP/f4D74j7570AyWwO3CzZeZj85+ADthTKxXi3EnIS8hAFCGFVCGSVCZF2DNFiqyCnJIlBiTRa/cCQsfW45haI8xMUVKjInXdqBHQawQm6zCcRwwJlrYcwkxEYyJMIxJXQgs2mknXPiXxzCsfKokOBcam8eY2EdiNIxJ6rx/pPE8ojDy8XAeFh4Akg0mm7XxytGG1mj2xxgyjEmWOG0JkNeNgzYpTURzkvseX3nrcjRSjXgIth4ARE1tGRPSr4iQMVnTtLqVrM9kh1YaaXOo+sTHGTwxKWLJkiUYGBjouPyXvvQlzJgxo+PyEzIxUUphyZIlOOWUUxDHxS5ffPFFrFixAk8//TSAPGYJAMycORMzZ87suq8zzjgDV155Jb71rW9h33337bheOtjsiP5uB4pAKWrG1a6pIGg1aYWp9I9RVE8WAGeM9CcD5h9DcyjNJyZCuAkJ/Si1nZCEVLjubmJCLtDkWhxp6Hqxzcpor3QsSAcP6aK5Uqr41PwTa0gBBW3/SQ5DY5CipJL+DS6qq52seO6/5FJq3YOtSzCNyxMPexMSIHeHpUlG5k0o8mFre0wFE5IqgWskOpiYmAtGP1zDUEjD/zRtblE3E5OqCU7RTJS/zczFyehcQddDQJnJSWYupjXp+NFBqU26xvZ+SMiUzGIOw1pjWCooul/GlbdKmEwPkbaPH11bhcw8Ncpcv3qS//eWQufiWMCNP8hxpGMB1Ir3wp80tJzYeO3YrzAFY7aTGQCZsNd1w9QmhmXxHutMuK+pdW/3hKF03YyQmCZ4IhWQw2ayYCYrkkwrZLYBENFExohoY+Oum2VAZr5YTfp5Nr9XNAlp9ttUUog3mN85U18PaeiN+bk0zXe5aVyLG3CT3Uaq0Ug1lJm8kBUmmyRc/hyzscLYtWai+dwGG4XYLu7SFMjIv5sxkTjllFO6Kn/SSSd1VX5C3FeWLl2KFStW4NRTTy0d+8EPfoC9997bMiknnHAC9t57b/zHf/zHqPpKkgQXX3wxhoYmZibNYDAYjJc3lEkFMdbXyx3r16/H2rVrC6/RYEIYk8MPP9zNdgMsWLCgay8dH1XxT0488USceOKJo25ztNBpvhSxwc+yxAVbs4lFaJUUlaeF7WTbvtnHf40DQjNNJ/JxkWUALVZIxWa2xYzG5D5oPhJzorxSZp/Ndpo584xtItA46MjLgxPS/ALFQGpwbIi75s5cEwZTiyLl6PLA3TeOlDUPRKFQsQ3CdvKhVJgnwmMG7aJGUptVGYxLweCEdmaaFmUAICPzjGEXXH6gcGQOQjpWQgTnpg1zpOuwpg+tPQZNFN2FiX2sFoOa+0XuunQ/aplnwimPku5XZJgKesT83EdpVjxvS5xokT8XVahIf0XQiasjhEbNPIBJfwPaRmyjwi4wXDh+rYU9RgJRChinMglFLMqwMZkZBiXeYK5RBsfGePl7gNxcRm740jI8hsUkF/yaMyVFjbyh3heapq8M2rC3ygRfU0n5eY2HctdoK5A1LEmzT7j7TuYmMjOtN7+p6waBwcH8vcecCNUo9bMpwF45rbF8+XKcffbZuO222wqEgNYaQohCgNVOwblyGAwGg8FgjArvfve7AQBf/epXMWPGjK5ilLUCT0zGEYJsn77AlWCny54R2orZApfiQqOivM3Tz45ukP60vdUUvmo/9e9l8xSZWfpYQaR5nGJZ1q1QgDhvkUiMh13BBUGhbFXpHaswPloSwvOOcXb/kJVwn1uFnS+0TduK4GtEgoWakSrYOl75kAWhPhKZIQ1YDJul12dFWrAoVZRxFasSZjyOpCqIWwGnw0gzF6iMVu7hjRICjuEoiWDNNvYC25kw7UCuARLKq6aL98/pf7TNIBwiSTLL/lRlc6ZzoWsYaoMggdgM1Hr5evdNt7jefl/BU2eZI2HKEbmSJCmEzEr1ibEpZYfwyoT3JEulzcarjYiU9DCqRiHey1+cqOmxKdQ21SfdFnmDaljRqgt65z2Lxj24MZm2TlOmItdmJvNsxICXQiJyuhfSltRXG23QoDmgMss+64YLZKknlDEZ2z/clytj8uCDD+K+++7DbrvtNm5tTmyIVAaDwWAw/sZAXjljfXWDX/3qV3jb296GWbNmQQiBm2++uXB8wYIFpeS4c+bMKZQZHh7GBz7wAWy11VaYNGkSjjnmGDz55JOFMqtWrcL8+fMxMDCAgYEBzJ8/H6tXr+54nPvssw+eeOKJrs5tJDBjwmAwGAxGG2iUScDRtNENNmzYgNe97nV4z3veg3e84x2VZY444ggsWbLEfg4Dnp1zzjn44Q9/iG9/+9vYcsstcd555+Hoo4/Gfffdh8gw+yeddBKefPJJ3HLLLQByz9b58+fjhz/8YUfj/MpXvoIzzzwTTz31FPbYYw8kSTHsxp577tnxORN4YjKeEEXhWB5uMdhHKPB6JJANTDoj2eqcv+TIZewYq8xLASinRsHsUyH8I1dgQ7GKpscJh0JYy3G7MZfy0FAXAiYTaeByWijsTDjUjGP/Pb/XwILmhq7tPj/+iG07cBOOwjLeqVQx/Nbt1ooovfpBbBNC7LkWh6YXW9Y3G1gRK4lJnakizK3jxycJTT3UthTajrN8QsE5w4lObRElUXIXtoXtoKFrpt6wbJNNuHhxrfttZiL7AoiNSSeOKDpyZk0hZOagc4uSFHFUvCaEtMINmNqk+ye0doLYcKh0/TxTYHhvhdCII4WalkAK9NSaaND9Jld4CCTmnGykYG+oJFYO5cfDaYyh4fyfQdqIbFsAoOvmPJrCxpShmD7KiNdFhlKEZDKzkrlFaBcniApL41ssJ0VI+4omnGafa0eYNge3EhjOYL/PNg7LMCCNoJa29pwn0z/aKV4yc3NRensg1DCwCi9LHHnkkTjyyCPblqnX6y3DaqxZswbXXnstvvGNb+Atb3kLAOD666/H9ttvj6VLl2LevHn4wx/+gFtuuQV33XWXDa/x5S9/Gfvttx8efvjhjswzzz//PP7yl7/gPe95j90nhBiT+JVNOQwGg8FgtMF4mnJCd9rh4dHHYrntttswffp07Lrrrjj99NPx3HPP2WP33Xcfms0mDj/8cLtv1qxZ2GOPPXDnnXcCAH79619jYGCgEPNrzpw5GBgYsGVGwqmnnoq9994bv/71r/Hoo49i+fLlhe1owIzJOILchIWhskQcO8aE4BSTbp9dhobMCcplyG9NuTZc8DNaEXXBoHjd2vPw+1JBeZ+lCfsJx0jlgErmQocCXptBGUXu1B+Cf6ms2JWug1kRR44NEeHU2+7XhWiuhWMeYxGyKVKW2QzbtA2qVg6iVjxNYjpIRJtva95YO4l5YDMA62IdpYWjj2Tx2WiHqlgLwrteeZ9AiZSm/qGg7dK7eKxQnFy4vd9jYYKLUQZfTUt3L2ieGSQaZhlP+Vh0LTVj1SXykISimZKFIHd5H6LwOdeUFwdsMylrQJnni9p0gZedi3IVUwLkz0QSZajpCEiBybUGmuQ3S30JbaMJp4GbthQaPSZCWi3KCmVeHHKpNDbS+Q7lP+3RIFEgQNZjnttaUfQqm46gsqJXEzyRHod4o7Dvh6fmWxK6ytSVy8xQiF3RHmmcTgJS5bdptkOw3z0S3zb7o0L/QgG6PpUuqjkmkKZDwApseoyjLWf77bcv7F64cCEWLVrUdXNHHnkkjjvuOOywww5Yvnw5LrjgAhxyyCG47777UK/XsXLlStRqNUydOrVQb8aMGVi5ciUAYOXKlZVh5adPn27LjITHH38cP/jBD/CqV72q63NoBZ6YMBgMBoMxQXjiiScwZcoU+7leH12yKT9Z7R577IE3vvGN2GGHHfCjH/0Ixx57bMt6ZGIhVLn3hmXa4ZBDDsEDDzzAExMGg8FgMCYM45Arh+ifKVOmFCYm44VtttkGO+ywAx555BEAeVqXRqOBVatWFViT5557Dm9+85ttmWeffbbU1vPPP99xbpu3ve1t+NCHPoTf/e53mD17dkn8eswxx3R9LjwxGUdoI/Kxj2+76Ky+icTmGA9MOojaC1tDMwuJygxF20kOHACtI7+G7QMFYW+rWCXItGceIUo4MOlAW9NLKUGgzPdZVlw7YSxtpSeiowuuiOKNCx25RuDFLpGwkTxFVa4b2tcmymsofqX8OEmUleJoFJLftcht06SEeSpyeXgqIsa2aseadir6bWda8k1K4aMQ2SR4bqxWZEuFPI1yKcIz1VMVz6Jwde09JvOKiWqqKaFKQiZQbYWaNG4/kkXN5MaJo6LgTgr3TLqIu8bM0iZya8FaadoksXHYXtXXzUUMzlCPUtSMircnaaIum4UyVaJnvx0SR8cm/gmVGcpi+57ud2ZEsNqcnEiFE7jStaSva48zr6le850g05mJJCvWRzamSWOaOV+KBLvRCdnJXGSTZmqXz1Co/BWkCEJWc78PNEZB15is2/UKoTSAtDlW+0pn+FuI/PrXv/4VTzzxBLbZZhsAwBve8AYkSYJbb70Vxx9/PADgmWeewUMPPYTLL78cALDffvthzZo1uOeee/CmN+VZze+++26sWbPGTl5GwplnngkAuOiii0rHOPIrg8FgMBgvE6xfvx5//vOf7efly5dj2bJlmDZtGqZNm4ZFixbhHe94B7bZZhs89thj+OQnP4mtttoKb3/72wEAAwMDOO2003Deeedhyy23xLRp0/DhD38Ys2fPtl46r371q3HEEUfg9NNPx5e+9CUAubvw0Ucf3XHANKXUyIW6BE9MxhEu8quZ9rdbihUyBwdCUVpcZ1l1FFmqH2Yjts8HsQJenW5ciquYEkIHrsxCKeddbJZL5DLoMyciK/ZDYthcu+kYGaE8ESZpOZUn3rMdm2Ox6xcp0Rk0bLo2qsSU+JFAO8mH0+qY0sKyJ7ZtbwVvV7UqVOa6+pY27iCqLGUwzjy1dKg9LrkdB/1RHXIzdfva3Gfqy9thMy/TMRKKWhGpa09HupCRutAVjZ/qG1pEC+FuOD32Rl2ZyqjgOlwYq9AtmY1OIvf6iFC9AvRZMmKaiOWoxylqMkNivhh9UROawp1WgJ4/5YU6lqL4D4CO9UQpYNiM/lquKF5T7wUArJuU6xcG19WBIRLC0u+MY6NkPWea6iYzOrGJFEG2OSWCMu+TnrwsRQBubEyAoepnWTYc06FM6jArSDeMf9abuwxTGcAJ+EngLFQeITb/ALuPmKFNjdEESKtqoxv85je/wcEHH2w/n3vuuQDyzL5f/OIX8bvf/Q5f//rXsXr1amyzzTY4+OCD8Z3vfAeTJ0+2da688krEcYzjjz8eg4ODOPTQQ3HdddfZGCYAcMMNN+Bf/uVfrPfOMcccg6uvvnospzpm8MSEwWAwGIx20OHMeZRtdIGDDjqoZfJbAPjpT386Yhs9PT1YvHgxFi9e3LLMtGnTcP3113c1ts9//vM444wz0NPT01H5//iP/8C73/3uwqSpHXhiMg6QJtqe6M1XKeQuDCkdw1DFQrR66EIGBSDhRHX9cGuP+xqXUI/S4ZekBUPSVr+itWNDKKusWdXa0QjP5h3Yl2WWawushCRzxAHVF4E+wR+iaApIuzgk30TKgKxs2ZJWAk5X0k3mYFu7HdHk9aJauK1qTyeQ0bKSFskVGYBdv0WWI2+7umw7N2QhAKlJE5Rvm13+mPqutwBcNmjrYqtt5mdE2mmQYp1nnLZ5eFDcei66ljWjwHJxfrNTAMOBRoOYk0QoTx418r2tyrXTCn57VI+YEp85qUUZKNlwIjOkYmQK3GdJ/AB8+Zt8058o60pMjBe5HSeGqVufpNiwMWdPsqYJPme+C7Vaiv6enLKoG40O9dGkfDxKohan9j0ADDbz37kNUqMpzW9egwRAHuNH5GWvRqp1ITcPkOuJSnmyzCmmPcXfBiB3byZkjTFOFhijwoc+9CGceOKJHU9MPvrRj+Lwww/niQmDwWAwGOOBvwXx60RCa41DDz0UcdzZFGJwcLCr9nliwmAwGAxGO4xjgLWXAxYuXNhV+X/8x3/EtGnTOi7PE5NxhKDZIwmLfHNJyXQinHmn1VTan6ZXlQmPhVFlfYFsuFW6tTmnjcC1Uxfk8tiobUP1AzaPDrkLS+MaqpSGzIQdhkx1KYCuVIAygTMpr4efXoXcFaXhgElnSunhRaStQLUq101I5RdMMVUVgIKpwIpeg1+jVnV9aC28HDuiUC/xfC3JXNE0qsAxx1nw4HIE5TeumY7chxDa3dNAl+0Kwd2oxP3a67rOXYPNPSV34VJUYv8zmcA2mvwwdYEGmYIm5RtyG66K6jpatGrHjxgcQkEUIutmSqLR5uc3NLnFQpVEv66sRMM8A7QdSuNCO1oLxMZ0Q9t6LbeJ9NWa6EtydXEcmAzrkYtOS5Fm6Rlwwm4FYcSymsSrgr53Gore9ytkWkEY8wvdY6E1dEwmG/O8F3PRARqIjAA66zW7JJCNPpp7V3gpxK+bM7qdmHQLzpXDYDAYDAZjswEzJuMAHQaQ8TMKt3MZpnqduOvSPqWMz50oMyXdQIpKRmQk+MHQWgZYK4zN7CIXS8pwKmXBdRcAoiFv1dTjZs0yBSISpjY991JyQSY2hDKhprCraZsRlVZiPbSUF55o1BTxLiMxHVUiWJvVuMVlV1qgnRNjJyunMCswKlyLVSB67SS/zkgItdJhlmV/bLZOsUpQL2hYeC7Ckbc6TxQQabvSLrkLBwH2/DLSZiCWUOSuTAHagrxEQGfMSZhHx0erwHZaCxesjkS4XmC5VEkk5qFdm9bRFMVAaX67lA+nZhgyKV2ANZ/FAHLGbGOaP/yrBvNkNYMm8y+dR6PpgrBFASuSKYkhU5+O9cbF4G+pkmhkeZvExhCLBgCSArTRE0sCZ/9aJQoCykat0+a7rDPhGDbTZKCdBxSgkvLzXRW3b5PhZWSK2dzBExMGg8FgMNqATTkTC56YjAOIMVEb83SZsscs06OoyJ4UKunqfUA1k6Iyd4yO0+qylVbED4nvhZKnz630IqUQ9SizI3nIeLNStAGbvPOwwdGM7ZkOksZEKasnoCFlPSZ8ts5ZD+txmrrFtfZ0IfQ9t2GsKZiaRiFzKgA0yc5dN3qE2EVti7wVL21J0xGhzBh0mqmXxlm534Ntu1JGVFzx+/Wr3ITHCyFjpCnglpI2tkLph1YL5/7bYkwtf5zJjdgyVEWmhJgym3naFbEaI5UAommC1xmX2GHfa8C4DnfiHRHGOgTapACouA8hK9M0EQZrhhJYN9yDNMguLIS2bEifYSy2rq8DAGyRDCIxD/UApeU1eK4xBevTemEMww2TgTnzwudbeVmxTKMZ22ewt573S1om0pw0VWSZkiFTj9gg7d13Eehg8nhyvu+3RkgnagnLsOi0qD8hBkVoICMtmUf4qJeTqwvDgicmDAaDwWC0A3vlTCh4YsJgMBgMRlsIVLrvdd3Gyw9ZluG6667Dz3/+czz33HOl3Dm/+MUvum6TJybjCTKxpIairdccJxxVOECFNGRGCj/hPqtAWKtUvl+KIAzqCAhcgAs5R2zbFePrRiBrXYJRFMICFWYfZwoi9WnUIJfDPL+GtOYg7VYb3pitVcdeIrNjWJSiS5IIllwVda+EJtUrRYn1XDllICgmc08oHKzCSLbksZheNrWdOnwkbQZda2JRXoTaNmMKLIgjLxZFnhbZil3N1lD7ZJITWUVjNI4INjeSNiaMxmBudkibEZLERIGNi/lgqsSwAkUzTe7CTYLYvEz4LGjPHZggQ/GwsTs2MonM2Ckmmfw2W9SHsE3vGgDA9j0vAgAmyyEAwKxkFbaINpox5W08PJxnkV2f1fHiUO5DO0SiVzqPiqi0zmRpD9iIr0lwTuQiPNRMsGEw/xI1G3Gxvt9hACG0vZalwsZ8IyI4129K55wWRdC5QNaqnXMoUYgIy3hp8MEPfhDXXXcd3vrWt2KPPfaAGIVTRQiemDAYDAaD0Q5symmJb3/72/jud7+Lo446atza5InJOEI1TASgtblgTcYx0JvnEtCVaroim2BZFVqKSuGlafUYCBt5LJiZhlGtKsSv1eNAcRw+kyGDYxWzYcuG2OBtXvsBrSeMGFhDlvxupWFMZKwAJazgNR4CRGLcEY3LoIoFMhOEidII0WI1q/tZSlE4X1qB6yEJbVaHFNzJZqtVwgr7iLUhAiaCl0fELNdIKCo9ViVchXeSrbdTjIZxGatG0LrEel27lVFZGFxasfvR7zqAlsXnzboLZ574MXAxFZnI2TUAetg8Z+YZUQAoxYq9tyTs9foNR1cgBYLAYiUGwjtGbROrImUefM0XWNM9IYHp1vX1eH3/4wCAfXoey/cZt+E+EWFI5++fNirQF9I878jj66dh/TD5xaPQL2WczlIJQS7QgQu8FNqySD1GdEu5d4Yyx46QkNZm9KUgeJH7ry0MC0J5eAD3UxD3pMigXAZqEs96rvAUoE0ZxkSbrUiFFcbajOXjYV3pFDwxaYlarYZXvepV49omE2EMBoPBYDBGhfPOOw+f+9zn2mZC7hbMmGwCKJOwSDYm5ToTeKxCt1P80N033F91zI/fLkfBlPgIg7fZlL+tmRMAjmIIoA2DIiINbVMA00FiTjIAkWMiUo1IFVfQWQLLmGQmwSWxJCrxGRNz3ekzrRaVsKuxjGzddgXuzs2FZjd9KdlSZ1IVjKwbdFKvW7akFLtvjEvMSGqP0CvqMICRF4V+2PoiqpkVe79ote8xJjpwO40HAWFW3+SIax1V/RV/i/uklXBsQhvqJCzjgshpRIYpIDdW5WVVjiOFiDIia2G1IqTj6I0a2K32DADgVYnZJ3LtSFOnaJovymqV71vVzIOpDWWxbcvPUA04jY3eELtoZD3my2me+6QntazNlr25jiUOMh9vjBRiw6qkJmikogBrqYAg1srUi42ep56kqGsJaGBK/yAaQqHRLAZoK7j8mrcZfd/oOdCwjI8rrl34gE0NLToKEzBiGy8THHvssYXPv/jFL/CTn/wEr33ta5EkSeHYjTfe2HX7PDFhMBgMBqMNOLtwEQMDA4XPb3/728e1fZ6YMBgMBoPRDqwxKWDJkiWbtH2emGxCqPUbIInWIhEfcZS+cNXPgwO4qbWfg4fMHjLKzSlV0V5LJh3PJBG662IEEw7VD005fh+jWAJYuaRfNYgWKZSGyLQV0kHpSq/l0F2Y6GTpm5FIMGd0yWTSyno1lGmf8qvIRNmx2aiqiiJnGjGhlwcndK30Ba+hyaWTKK3j6QrcyoSzKTIQkwi268eh0qITPsNmtxcBVJp7Sfc5Mhlmlfdrpmo0JmPiGJbQcdFNVQUmPADOhbxC12vFtva2ByYdqZ3JiYTVFOmYxLCQtnxvkgtNt6jnLsFT4iE0zdO1Tm0snD8ANM0Ffqo5FQAwbE54OIutK/OwMZM0ns/NPbUXTcTZ1dZTGc0pJiru9NzgVZsyhKnGhLNd7yoA7tle3exFiA3GpDM0bFyxG5H9XaHIrz0mc3F/vZFHux0EJtWaSETmmZuc+FWRmY1Er1nwHAi4qMD0BdTi5Roa5G8KhxxyCG688UZsscUWhf1r167FP/3TP3EcEwaDwWAwxh2sMWmJ2267DQ3ySPUwNDSE//mf/xlVmzwx2YQgESwAyOFcqIaaYVCiqBx0rWrJGQZoi2S+4qsSv1axKJbxoJVbBVPTDbpdFtvUvYErs/JcocM8PJmGkMrlu0k1ImJFrPux5/5IiYuNP6iOPGEkdStstXy3Fmiaa0qrPWUUu0I4QV5qVnKW6Yhh3YxrcTHXSfG0J/5HqFK7vEmYktb92V7a5MwpBP3yWQehS7lybIAtX89tLnuywfRhxMrNSc51nDJVk0AaEbz8K+SnS8+mdn1YISsK/ft5gBxDUjwvrYUjOc1BcpuN4tyFXKO8yifx67PDU/Cb6JUAgNX1lQCA3WvPAQCmSY2nzMk82ZwGAHhmMLfzDzYTKyhtbMjL1F4wwdueNsNRQGOyeU/fJcruq4HpPesBANvWVwMA6iaiXX80CQDQK5uYUsuZnbWNXG3+4lD+mzacOsaGcitNMSzQ1J5BJCpnTPqSBhKRYaiZFMqmmbCMiQoCqxFEpMvfZcCxYJsYQnu67DG08XLCgw8+aN//7//+L1auXGk/Z1mGW265Bdtuu+2o2uaJCYPBYDAYjK6w1157QQgBIQQOOeSQ0vHe3l4sXrx4VG3zxGQTg1gTnz0BgGhgAKI/X420DPsuRXlZRkHT/DpBuPlCgLRwWZsGYe/b9e/Dtjly0UqEzAkAYZaXOjP0RuwdU9rWkamClXOYVW8CuLDlZh/pCpTHmCiztUHYSIfSAKJBs0rLjOZAkOZEecySjRSX/1XlsOORIG0KMS/C6k3GmzmRQrds07/97dyCW9WvCs1eBSdN6lxbYoORCVEI8CUsk5erC63Gw7qlB2OPnZYk6ymyKgAgDGtGCXgpK3FWA1TdY0YAFyCM6mqvv5AxyTwqv8XY4GXwJVbGXmsrj5BALdeCDOo8KNqgYRDWNHowmOXvm+ZBpYzCT4kmnmhuCQB4eijXmKxv5uxIoxljcE3OYtSfyPdNeirvLzVE7fAWQNpv3Lt7zZepl7ItC6xu5FqSF9P8N2mb2moAwECU/27Ve5o28/GkOKft+5N8O5TFlvWh544CtMVCITYPZqok0ooQ+VJo58JN7JUKbwBcCHv6bkaiFMBxk4HFryUsX74cWmu88pWvxD333IOtt97aHqvVapg+fTqiKGrTQmvwxITBYDAYjHZgjUkJO+ywAwCUkvaNB3hiwmAwGAwGY9R4+OGHsXjxYvzhD3+AEAK77747zj77bOy+++6jao8nJpsAwqOvRN3ksLCpWM1WKceBtxKv+nlx/Aiw/n4fQbbetjRnpyLWMPJsO4FuN+35u0gxGESVFRm5TWtI854ErzLT1vVaNk0ETePZmPYIF/mVtHRkfqDTyVzGWiprM9Mqac071k2YBpf60WBNHhTrdmqo6RFMKWNFqzw8VQjdlLV2LtC0z7YXKXtOrcSyaSatINjP+9ISFY901ZMnKNs0mXmsIJVumGsvjPRLbsO+PhXBI6WlE8kK+/UsPhRa6pbPskhFWbwYnrfQzkwUk0mCTDqAyiQkmXIGEzSM+LpWy80ekVBYn+a/F2vMw/x4Yyvb/DONLQA4F96hNL8A61b3ouex3ITT/ySZP/M6w1sYN+LpGZItc0GqMrlufBHyRtPWC41+AMDkKC9LIthEZNgyyXOA9Ztj65MeOx4yQSn7vJnvpJb2uyBFni+IRONk/kkzhSgqXkttXYlb/85pIWATam1qsCmnJb73ve/hxBNPxBvf+Ebst99+AIC77roLs2fPxje/+U0cd9xxXbfJExMGg8FgMNqBJyYt8dGPfhSf+MQncNFFFxX2L1y4EB/72Md4YrK5QNSMj6IQNpsuiEUxn0XsXfpWWYKjqDUb0c7Vtx0b0o756LatsEw3IlqvrGVGaJUcwdh0veOKGBNTSQKREaRSfWJQRCaQWmGkWcEFT7rIXKAu0YNCWWTCrq4p10lEeWGURGrEuqlheiJzT0moGEllmR1as2cdsBpjhdMni1IQKxpzlkl7TgTKgZIHSjMsVEAPEEvSaMYlhsYGWvP30ZhsGfNZFIPlWfGryFkTyzjQvTcrf+EHzSMWzLSjgjoF0KPV9HYRY0KrdC8fjz3typV68WPIoGghXBZkIkgtCwcg0XbwKo2sS3pmmJNGFlnmYn2WMyfrVP5wNlWMVUbJuraZ73t2Ve7/W3uijvqLZtgm+7bRx2J4mhlcX4aeen4RlGFo6km+7as1rFh1nWl7VZKLYKfGG/KysokeczOoLLEpEgqrkY/NMieWPVT2n0x/3EBTZqVM20JoNA3zQflzKNePDbim3O9B1/nGGJsUK1euxMknn1za/8///M/47Gc/O6o2Obswg8FgMBjtoMfp9TLEQQcdVBlI7Y477sABBxwwqjaZMdkEKARW68tXEsSiCAqwFsfFLMCAp+doM1+syibViqkQojWb4R/rhvFo1U/VONuUEUpBB664Nny8iCCELoTMl6nHplAbTbPaDla3WkqrTbChzG0wN7j9FGwtc7oVAFAN6bISk9uvGb+U2jIONjtsVnSJq0epl3kXJYxnsLOREPYlhLaPl5VttBmODRs+yjFbHQMRhx7NoLWwGaStq63Vu1ADpiy5f2svQFgoL/DdhnVQRrtVWDQcsmikaXLaDKpH7uaKArUFbRbGKJ2bsGUDqMywhG7CXeyNEbRx281i9xxtMC7Aa4yOZGqcMxhV6Q78+6aCTNvkJqxqhrmIM2zVnwdRm9mXa0Uog3BDxWiYE03NM70+NZoVoydJdIbEMCQ9xic70fnFGo4Sy/BIc1F9rQnpTSQ0JDRqkrIUp+Y8tA2B3wiYE2JgtHYs4EvyD569clrimGOOwcc+9jHcd999mDNnDoBcY/Kf//mfuPDCC/GDH/ygULYT8MSEwWAwGIw24MivrfH+978fAHDNNdfgmmuuqTwG5KbizM//1gY8MWEwGAwGgzEqcByTv0WQOcJGK/REsCVX4CDz8FhNK7q1++NoMgOPagydHNdkkjEPeAZoRNYO4keBteadWDrXX9OMNKadKNZQSdFtMmoYatlQ3ip2rsRh7hAJQBnbgaqTKSMvJOsuPw6ZOZqi7H6byOLKIBT8jQc6iSpbcm32Rcc2O7AToJKZqmmoffpcNf4q0evIA0JrKt7bb00i5hdKmcsu2/wGCt+OH4hnpXLe8yUTEEGVV7XW2jqEQr4ewDHzZGbSEtAxmRAD06MSkAqIyCQ4LKBjSsWbbyKpbHRVut7PNqbY/kiYShFfKUpq2qeteSo8f8oZ1MykNQeRCWdSnKdljlWGnuDkyPxCz8EQEhuNtmkynfcZ9XginKCVTELrm3X7OTH1NmYJmkpacxGNRwqN2CTDsiagyJlOASO+Dp93jYkzj7BXTkcYGhpCT0/PyAVHAItfGQwGg8FgjApZluHiiy/Gtttui/7+fjz66KMAgAsuuADXXnvtqNpkxmSCIIgN8cWvI7nudsM6tDo+2rY7QTdtBCyQFqI8LSbmJNOAUJ7IsFJBCmEz55qmqX6qLXsijfskMSdy2FSPnJupdfH0cqdIEn2SuyeJWWPpreIi0z+tko2AL40hTYAtyqPThBPIlgKbdYFOc+84poTq0RHXZ5jPRynh3DTDrMod9CUCYWv+hu67d4zEptAuu3AwPFvcqlg9eqyDS2DT2ngiWHIP14F4tSRmBUouyVo6QlMXH2UbzE1Fru1QfK1l7rIcmf2UwwcA4iRvoB6n1hWXMJzlP9GpltaVeO2wcSEeiu04QjaH3KM1uUkPRlhn6r0Y9NEbNSHNF4SeCRKdPj08AADYmNZLz8KW9VxMW5epC6hGDIsZ98ZmDTViTJo1NDy/b2JOtC7nnwpd2vOdZuuXrSrHmFD827/9G772ta/h8ssvx+mnn273z549G1deeSVOO+20rttkxoTBYDAYjDYgh7ExvV7qk9hE+PrXv47/+3//L9797ncXkvbtueee+OMf/ziqNpkxmSgQUxIEWmuLqgzAFJK+m8BnrdrclGgVNK4dbIQwlWdztaH1y0WF8uz3th65fWqPBTHMiVk5RkYDoJqeV7ZthxqHF+yNXJbNCjgT1v5N83rnbW0YCClsGO4Izo4OAE3V+r5XMQ+EzpgLMyrvvtOCMnTT9UFj08K9t+vawCXWH58MxtvJY+n3rbVwwbK0MHXN5yzYeuxG6C5cSTx5TAeAgn6EdCcldsbXuATnLbS3L8guTH3IzGNj4OoB+Zi1AGLPfV3EpPtxHZNGo2HcbofM9RrKYgyl+b5G07jkDuVl6+uFzaZsg5DFrl8AkEMSzz1n9CrT8w1lB54UDyMl/YhhAZ/ckDMlxNisHezB+nU54xIl+bgpYNtW/esxvTcPxOaHnwdy3UxkzmE4i9EQ5eB/PsgFn5g7PwibDhjS8P0mBbsLt8RTTz2FV73qVaX9Sik0m82KGiODGRMGg8FgMBijwmtf+9rKAGv/+Z//ib333ntUbTJjwmAwGAxGO7BXTkssXLgQ8+fPx1NPPQWlFG688UY8/PDD+PrXv47//u//HlWbXTEmO+64I4QQpddZZ50FANBaY9GiRZg1axZ6e3tx0EEH4fe//33bNq+77rrKNoeGhmyZ9evX44QTTsA222yDE044ARs2bLDHFixYACEELrvsskK7N998s8n9sZlAGX9Fcn21n1U5miuZa9rBPy5F8eWXiWT1K6zT6asTdFpOodJMA51HfbVi1lZ8rblu1oartHkBMs2jxcqmER028pekVwb7YyOUeWlHvVvmNtL5i4acSmRphCyNoIxoj6JSKiWhlESqJDJ6aWnpaXd58iyrInj5lD7tGw3o8cn1xbrwatd2JHXpGJ2bVqKQr6RwzL5grwGdv1IiF9WmElkqkTYiNAdj80rQHMxNnNlgDL0xBtblL9EUEE0BaV50/0SamydEVrxf+YBQEsfqyL3ssfC+Z+4l0+LL9lFRPnx+tXBlbH3zgkL+a0sWqrqGSBREoiClziMKQ2DNUC/WDPXi6fVT8PT6KVixdgusWLsFnlozgGfXTsazaydj/doerF/bg+SFBMkLCeqrgNq6/BU185c9RzPWaKOEWJtArE3wwov9eOHFfjy6ehoeXT0Nf1m3Ff68Jn/9afXW+NPqrbFy7RSsXDsFT62ciqdWTsXaJ6dAPtUD+VQPmqvraK6uY3AoweBQgjVDvdiYJtiYJhhKc5NTar4HzSyy5qHhNMJwGmNjI8HGRoKhZv7aMFzD+qE61g/VsXGoho1DNTSbEZrNCOlw/tJZxb+q8ZgsdAo9Tq+XId72trfhO9/5Dn784x9DCIFPf/rT+MMf/oAf/vCHOOyww0bVZlcTk3vvvRfPPPOMfd16660AYLMHXn755bjiiitw9dVX495778XMmTNx2GGHYd26dW3bnTJlSqHdZ555puALfdVVV6G/vx8/+9nP0NfXh6uuuqpQv6enB5/5zGewatWqbk6HwWAwGAzGGDFv3jzcfvvtWL9+PTZu3Ig77rgDhx9++Kjb68qUs/XWWxc+X3bZZdh5550xd+5caK1x1VVX4VOf+hSOPfZYAMDXvvY1zJgxA9/85jfxvve9r2W7QgjMnDmz5fHVq1dj1113xezZs7H77rvjhRdeKBx/y1vegj//+c+49NJLcfnll3dzSpscNoswiV2JTYiderltpuDRoJMAbe2OtVOU+WxIOO6QrekUtOr0p8lKuf2ZcvlwjPBUSyfs04F4VWTOXTgKAnVZt+GmgEyKw7DERuwxJ1b0atqWoixwLIlAtRXvhaLVSKqSaNS2Y8pGUll2w3bltdPKzbhKIBveBqm1FSiG9arapTHSdVBK2Nvk8Tt2oykgG7kbG/Eq7ddNCdEwWaCbOTuKAUCujRBl2rniWvFycWuZrsIgzXhkaVfBtddqV8O2fRFtIIS1LsKRaz8cm9GH5s8YqYaDMakEyOquPTVJ2WvbbJLbubvO5K6dNkygu1QCw/l7OZgf630+b6u+Wrts2GH6LTPWaBiwma5NoLbnV+eB2p7vT90Fo/tltvS9E6kTf4rhojC1mUZ4fmN/Xt2Ub2QUoE+ibi7CcDPGMJT7btAzooR7zshdvWlOxGYXhuvfJ5cnyF2YQ9JPLEYtfm00Grj++utx6qmnQgiB5cuXY+XKlYVZUr1ex9y5c3HnnXe2bWv9+vXYYYcdsN122+Hoo4/G/fffXzh+9tln40tf+hKSJMGSJUvwwQ9+sHA8iiJccsklWLx4MZ588snRnhKDwWAwGGWwKaeAqVOnYtq0aR29RoNRi19vvvlmrF69GgsWLAAArFy5EgAwY8aMQrkZM2bg8ccfb9nO7rvvjuuuuw6zZ8/G2rVr8bnPfQ77778/HnjgAeyyyy4Acm3LI488gueeew4zZsyo1I68/e1vx1577YWFCxeOKtpc3JsgEcnIBbuArNchJ5k0n315iGZyG9b1yC6Hnbti6yc3qedzyKQ3aq3hqLguFfGtRsZYffA6YEtG9JyTQGKCo9Vi2GtFgasQiTxIG+BWp5F/LH+bmTJNct81n+NMIHUR8AG4kOUpBJRhgxSlB/ZWlMIwNIm5TrH5xTEx1RBrjR4XISxvx2c8SOsR/FJRIKqajtw5Uf3CNS1ePMtmVFzUqlvp4taJwlZAQxp3VeJFVHAvlRZ2Na0DNiSqZXbFq9LiMZBGYEja4GKyKVA397OvkYdM17J4vSUFJDNfTakdCxCyEjqCYzpCVgQu2BqtxmTVY168bTYDcVpHKYUBuaDbUwTsLyqxeJlJgSBiDZFoGG911IUAjPuvMNdcS22vlzBMQdKg9MZA7cV8X21tvqtmXIRlBDQn5fWSnmL/9rQUoE2AORtQL3PMhc2eHGq+qJ0a7ANOQeLQSMz5C5sVOWTYzAiBGJDNGiSUvWCRff5grzudf0zPC1FAHmPiIwtPdFNhPCYWL6OJiS+n+Otf/4p//dd/xbx587DffvsBAH7961/jpz/9KS644IJRtS+0Ht1/oXnz5qFWq+GHP/whAODOO+/E/vvvj6effhrbbLONLXf66afjiSeewC233NJRu0opvP71r8eBBx6Iz3/+8yOWX7BgAVavXo2bb74Zv/rVr3DIIYfgwQcfxJ/+9Ce8/e1vx0int3btWgwMDOCb3/wm+vr6Ohojg8FgMF56bNy4ESeddBLWrFmDKVOmjFyhS9D/hx0v/jfIMeaAUUNDeOyCT22ysb5UeMc73oGDDz4YZ599dmH/1VdfjaVLl+Lmm2/uus1RMSaPP/44li5dihtvvNHuI43IypUrCxMTYjk6hZQS++yzDx555JGux3XggQdi3rx5+OQnP2mZnE5x3Vk/QjQ8PlkSSVci+/ogJvXmO+uGMTEB1mwCL3TGZsR1iVM+8Xp8/dLfojnCONuxER0xJ6NlTMaDKSFIIKlJnPKx1+Nrn12GBtEaRqujI2H7KzEnsbRalKyWX++0z9jsewyD0iuQmVuTmVujzKo87c29JgBAm2SAtHJGogETYErW8kElJrFfPc63UaRQj/Nj1g5vVoISufcL4BLr0SqzpiP8f4P74Iu999rQ3WGgKaXFiBoT//ZlXSYPJA+KZkqx1M0BurbGwwbwGBPSqETK0+QETInRJciGKGg76kJg4c474aJHHsOQ1iUaQxjmhbRBIjU6Ew+WMZFuvJYx8bZOX1TchroS/3z9Z8RqWILLb/uP3XNCzxIxQPkxjboQuHjWK3HBX/+C4TgrtteUALFJJilfPEQMCpCsN+OmalZIA6h6cSxh8DjteSv5uhcASHs1sl7D4gXh+UmbhVgXvNMAuM9C24SCMiwDoA6JRb27YeHGhzEM5dq28f49Zo0GmdJW2jIlxkED2eAQJgKsMWmNn/70p/jMZz5T2j9v3jx8/OMfH1Wbo5qYLFmyBNOnT8db3/pWu2+nnXbCzJkzceutt9qgKo1GA7fffnvloFtBa41ly5Zh9uzZoxkaLrvsMuy1117Yddddu6qXDqVQQ9nIBTuAsHrXFCKiNs2Wfu+9rlq6w3qg73BzWKE53H6cus0EoZO+Nu3EpMOZiad+ajYUmllxf9uJiXJmHTLlpOafUGomhM0USEm86OU6AYBUAZkmStpMTLT9NQXx3dJsFYr/BWOhIMx/XzLFUAZiCW2jsFIenVAE2xCZm5gQNU4mHbSZmFBkTG9fRiaZDgNik8mr2aK8hrCmLxuJk6J9QpX2eRXzMlq6aKjkQgtgWGkM6/J/H/pHKf0JRjAvL8wrWk1MMvcPPdy2y5XjPyP2cDgxoa2XwZi22po2vGcIwLDW+T/psCGa5NkIqG6MKhh3YWISzHFCM7EW7pyojDVdao3MKLqFN1nIx+2e+5B9Ft6Vp/eyNHtwGIYqnLP/jLj3gXnRv7kVExMVKtE3FTjya0tsueWWuOmmm/CRj3yksP/mm2/GlltuOao2u56YKKWwZMkSnHLKKYhjV10IgXPOOQeXXHIJdtllF+yyyy645JJL0NfXh5NOOsmWO/nkk7Htttvi0ksvBQBceOGFmDNnDnbZZResXbsWn//857Fs2TJ84QtfGNUJzZ49G+9+97uxePHiUdVnMBgMBoPRGS688EKcdtppuO2226zG5K677sItt9yCr3zlK6Nqs+uJydKlS7FixQqceuqppWMf/ehHMTg4iPe///1YtWoV9t13X/zsZz/D5MmTbZkVK1ZAenliVq9ejTPOOAMrV67EwMAA9t57b/zqV7/Cm970plGdEABcfPHF+O53v9tdpXEIxiZrRgBmtCqit8dLjkFqPq8fWsGELm9VvlJeZtOWrEMHPlallSzgra5ouemYiLYMS1De7vY+h/Xpc8fMSQcotam1XZ0II2KVqaGqjZg1agLa0OUq0DwLfxFm26GmdUmoZ7feiigNAkKRSQZSOcaAVscV52Sz/NK2kGPG1A9JCbNfoZyPxB9bq8BtWgvrplo6ZttBaeXqXD1dv9aEQ67BRM0rr36wChUepV9gVcKxCFSXaUO3a+nMLPZeBsSj8MYWZuul9vOCxXH4piRlXYd1cMyYqVxCo3KDmUBkXIGTdSQQdmOjtjIS1tbLQ7QMU8gGRaXeClm1oyFPZOrBXtpIu+dN6OLBQv6b8g3IIIFeQDWjnLmryBKsLTMk7JjyA15DulgmDyA3QSwEi19bYsGCBXj1q1+Nz3/+87jxxhuhtcZrXvMa/L//9/+w7777jqrNricmhx9+eEtBqRACixYtwqJFi1rWv+222wqfr7zySlx55ZXdDsPiuuuuK+3bYYcdCpFjGQwGg8EYLVhj0h777rsvbrjhhnFrj3PlEMbgIiuMoLXAlAC54DXJL7Em5iSqmOGHHm9VbAKxTJHIX+ORVpP6Id1LRZNuBVtxsAXr0YmOpapMgUXxw/IL4a1SvX1hvapuA2GjyLzPwYo7XAFX1Ydyq3y6NsQyEDvhEzBNRYGmaLwSUhaFsW7BT6tOaTUuVeJVakoG17BKR+KTSPlnXTrmn6woiBK8I6QRibQdf2YEsrTaVZl01yajFX9xBZyHdKd9RdZDKNj7HLIh7TIJ26F6BIy9p+Ti60g068JbYhBSE869Cu0eaZ9BCdiUgnTCC0kPAMIIRYUZrNoYlRgAX6hKnrEF92jAhtKncwA8gbA/7uBZIDYm9jRZzvW+WEdBQhvW0frFV4CycdvAdNr7sDHKL0z43ClAqvC86QFo2RXjZQyemDAYDAaD0Q5syplQ8MTEIGc9OvfKsSxJvQ7ZPynfmZi1MrEjSQzdmy/PaFU/IlPgw1u5a2JMOknwNx5sClCZYG+02pCOvIFaQHuMSeGahGOpGlq4z1/B0iIxDE2uPE0ELdF9jwazT0Z5hchsfZdeWoCSB00nXjHK2uklMhTb9GH7adGkX0cG4/cRevdkWkCSe6sOVqyWqNJOpxQEkUMmcpdXAIKYktDjRbvrLVMvU0OzcEtcvVIQQiAkdSyT4DGPImAMtHDvRcg4UF8JrHtsSdui3eBKbAh91I65oIPKuJvrms7ZBKvPEFBDNPC8bNSQiIwFWjaCPry+qH9qGzUAG1vrlYCcZSm4VcNdo6jpzpsCrWl7X9x9pOCGIZsC4aUSCK6RVLmJH9NyNkcEmiLAPSuFtu099Z7DoO0JNY2MgymHJyadY9Qh6RkMBoPBYDDGG8yYMBgMBoPRDmzKmVDwxMRA9PRAmABrsjcP9yj6em2kVhuNSAYkkxCAcRNG3eTBSYwoMIpKYlctfFtEF0+qpU2NKadd3VDx2Apd9G/NJlUcWwcxjroyAVX0EYpei0LZqg6NCE8V3YSt27BnB6nKGmvzoFg3bTJXoOQmXNV1FvibkqhUCu1penVQrzszmQ1C1QHH7JttyGQUujRXuRSH+Xe0Fp5ZpngdtBKesJXsDWTCNO0qL/Jr6swqsmk8aKm7UKzcxkwX5qWh9gBnWtHSM88E5hHffEABb/NsvK6dgqE3EKvbjMHC9UGmmMxEGlaTNGRPanMQQWjIDXlDkYnuWlsjkKwtjptcgnXkRR822nr6Scp6NKRJwmPLhI+Eb7qkMabuXOna+f0B3ncjFTYoLwUipB1aCmddtm0LW59y64hUFDMD25xDzlSryPWczqPChEuNaIhqt+5NAZ6YtMSGDRtw2WWX4ec//zmee+45KFX8h/Doo4923SZPTBgMBoPBaAN2F26N9773vbj99tsxf/58bLPNNpVJdrsFT0wIU/oRbRGEz5UV7IZ1sTX5QmKZMyOAl7bUHBOi7B7ssxSt1IsGQuvWrIZ/88dL7Bqi09UIlatgTtqJXtuyMC3aqQwQR+1FtEoT0HR/KKBdmJFZo+SCSqvEdJLHLgQBs+AHmjIgd2ESjiol0YpG6oTdyGO4jfzlbtWWELol+6K0sK7LVVmJXQTyVspad76VZcNqobt1YaCuvCa2IfRWrhIv01exghWwuWnMOSq/Xqux0Rg8VkUT40I0SepYlFBEalMZTHPiUZ+pyQsJ6GYEbWPdS/tME7skG+V8PsQqKI8N0tY1mJgIb0wkYg2F3VVu1jT+uII1DB7fAtNB1wiidCwMUKelLrhsV44j8u5bKHr1xa+2rnDHKnLzMCYWP/nJT/CjH/0I+++//7i1yeJXBoPBYDAYo8LUqVMxbdq0cW2TGRODbOokCNk6rbWgTG9+dltCuDi27oiVYom8Pa3LgdVcTHGv41CjIvJQ8S1H6rVTRaltKnYlwEjuwaMOSd/m3HwNQSCDsKta7TEnYUA1mxm27o2dtBJVbpvaW+7DBVFLM2m/WNJknIsjSvynWybh6xSdsC42THxFoLQqpiQ81haBtsQ+06lwbsJeQLXiwDQ06SHgaXgi5IHagntCDEAhcFoYGY0+Zm5n6EJcTDMQbCsggjJ+SHjLQgRu5skGgGKQUZoD65K7QUIPSUjjOisHhc0gTEyM3wcxJPaZ9DUmBpaVaQrL6FEyXlnhri09bY9/bn7wNovQTVuUvy9V7sIl/Y5fTwSXnO5RrJ3GhJjJoA8/eF3ht2WiGBPWmLTExRdfjE9/+tP42te+hj4TZHSs4IkJg8FgMBiMUeHf//3f8Ze//AUzZszAjjvuiCQpJh/77W9/23WbPDFhMBgMBqMNWPzaGv/0T/807m3yxMRARxI6DkwvfrTHWpBQxn/IAhrUF2Fa0aV1f6TEIgIgV9ZOMvgGvPWImX9boVNXYqBav9lG6OpjLBmQQzON0NpeKwgTcVfoihw5JCYEpPVbNKY3EhHSZN7Xa5qiRKkna6Qtp2pkEqkaZrW7b9HttsU5BuWK7QIi4H1lBzxwu+iyypqbZMmEU+y72gRULBQoVGlomShlhQ1FlVrA0u9CCc/saUxJXhZtAPa476LqTCpFU4hMvbxDFaYAlx232LZvmrG5ZszWip8jz9xBZg4UIRsujUwpr01DQMVAbH4PoiEBPWRcyMk1PQlMVn7/cUWbvimFzpdcp2O6xnRBABjTkXVXj7xjdJ1Kebtcn4VMyf4FqLIYVz0+kvrSpbJu/K2UzW6f37Ydy0TgZTqxGCsWLlw47m2y+JXBYDAYDMZmA2ZMCK1mw8EKiJYHJVEfAqbEbGmfdXeVkftsWABpFXNmlSPcKt0FmPJEmK28UTdhjpyOjrVDN1Ngrcvu0LRKNRdeS+licYXMiXbOtoICqjWN+NQIL2XqxIAZCSa91SqtYuleipjclWEDS7VTIJPotUroSoxFeMxnMoghac+4BH2aOlXMCfVVlQ3Kz+fTVcw/cvGsCoJmb075mBUkx078qmIg81flbUSNjg2hc6pashe3fnbhVhmM/d+ALGDWcpdWs6tFSi1fmBu2medfslEGID0XX2KDhPBYDBSPoSLXDf0mKd+kH34/PRGrrVeUABR/y4p6ZnetPaZKe+yVRcieFTqgba4gDe+Dlrokdi23oUvHhADERC2tWfzaElmW4corr8R3v/tdrFixAo1Go3D8xRdf7LpNZkwYDAaDwWgD0piM9fVyxIUXXogrrrgCxx9/PNasWYNzzz0Xxx57LKSUWLRo0aja5IkJQYo8WFosoeqRfcHXiQCgkPA6Mi/p7K/WNc5zbSOQmy/VU7HMdS2RhIoFVCygE5m/pDAvaetVLZ0Lx6pe3UJhREZEaF16tYXE6J4yP7icUhBZlr9Slb+amXvRPmVexEYpDZGp/KXMqlXp/JWh9Sqocp9w/o4jrJ6UFkizCGkW5QHNtIA2L//U6Fim8hedbqoEMi2RaYlU5S+q479K/UKMmMVYiNxd2X8J84qkKpQraGjMOSsl7LWgc9JZ/hJpcH007HWXDQHZyMvQe5l62XgFoGNtX/a5MS/SeOjI22deKtFQiakbmSy+UhdX9FXXwowt3pi/oiHXR9ZrXvX85Wsv/LH4LxV7nz03WXt+HutRHIh7qSh/ZbX8peP8pRK3L6vr/NWbvwrnTU3SP0Mlci2P9n6raIx0vaVhr2J3LQvXNNZQtVxvpWrePnol2gRS86575W+g05Pk46B7BVcvqO//ptqfNqlztq6De/y3jF/96ld429vehlmzZkEIgZtvvrlwXGuNRYsWYdasWejt7cVBBx2E3//+94Uyw8PD+MAHPoCtttoKkyZNwjHHHIMnn3yyUGbVqlWYP38+BgYGMDAwgPnz52P16tUdj/OGG27Al7/8ZXz4wx9GHMc48cQT8ZWvfAWf/vSncdddd43q3HliwmAwGAxGO+hxenWBDRs24HWvex2uvvrqyuOXX345rrjiClx99dW49957MXPmTBx22GFYt26dLXPOOefgpptuwre//W3ccccdWL9+PY4++mhkmbNHnnTSSVi2bBluueUW3HLLLVi2bBnmz5/f8ThXrlyJ2bNnAwD6+/uxZs0aAMDRRx+NH/3oR92dtAFrTAxUTUKQVw7ZkpsKoVdMqDYXEJ7NtJ0nA4r1hdOf2FUjaU1Il5I522shiZ0QhZUCBbqyvftByNqFtC+LFMqwNupyOx0FSaNF+FinwB57Ahi7uA1pb47FFPzOuxbKu5bwNCceM+SHzM7Let4Q1DadvvKut300SA/irpENU0/J++LMVBdWC+Li6eXtZd7DFepQKCmgELojDx1CR142HlqGsjfnnDUiqGGjk7Kh1GXhc6F/KmM1O04ToeFrTHTxrLQrD8B6a2jpjokgpUPIUORlilv/GLVNCeyEcsxISU+i3P0OPYYKEfnb3BqZuiwX0TAQkaeS306gtSh4BcW6UN4NqHW/9Pzm8o6iDkT4z7H1mioKcPwQ8SVvHDse7Qaeht8NrzyBDvq/CTro115jM36fGbH1Js4+8lK4Cx955JE48sgjK49prXHVVVfhU5/6FI499lgAwNe+9jXMmDED3/zmN/G+970Pa9aswbXXXotvfOMbeMtb3gIAuP7667H99ttj6dKlmDdvHv7whz/glltuwV133YV9990XAPDlL38Z++23Hx5++GHstttuI45zu+22wzPPPINXvOIVeNWrXoWf/exneP3rX497770X9Xq9u5M2YMaEwWAwGIx2GEfGZO3atYXX8PBw18NZvnw5Vq5cicMPP9zuq9frmDt3Lu68804AwH333Ydms1koM2vWLOyxxx62zK9//WsMDAzYSQkAzJkzBwMDA7bMSHj729+On//85wCAD37wg7jggguwyy674OSTT8app57a9bkBzJgwGAwGgzFh2H777QufFy5c2LVIdOXKlQCAGTNmFPbPmDEDjz/+uC1Tq9UwderUUhmqv3LlSkyfPr3U/vTp022ZkXDZZZfZ9+985zux3Xbb4c4778SrXvUqHHPMMZ2flAeemBioRNo4abJhzAWpchS+b0rxUEUfV2XNDc09WsKKam3OEVvej2JG3C/VkyYLqm9mCvoVRKe24Q5Dl1za16p40GalGacq+Np4cXJhf1UCX2sbES4PR9A/Ufoy1ZBEOxu6vuDGGLg0FlyEiUE3dgitiNI27XmcrQ1sZraR0CMKVLUWlvcNTTpai5GSUo+IMMCaf4nCoHEiCBqnGhGitfnPRjREz5tpN9al3DSFwGogc4kzSdh0O+QCH2Z8Dp+fqkfU22fNcebeSi94Whh0jcwkgvLaeO6+0mbwrahPzxaN3cvLU8oZ47Un0/L+AoRn1qnIR1OCzbuFrtz4wzxAvkXE5ZsypjsyO0beWEITlhatzTWFcyjWR2gmhWd6IiFv5e+H910c43ehY4xCI1LZBoAnnngCU6ZMsbtHa+4AABH+P9K6tK80jKBMVflO2mmFOXPmYM6cOaOqS2BTDoPBYDAYbTCe7sJTpkwpvEYzMZk5cyYAlFiN5557zrIoM2fORKPRwKpVq9qWefbZZ0vtP//88yU2ph2+8Y1vYP/998esWbMsY3PVVVfh+9//fucn5YEnJgYqkVCJgEq8WaJGZ7PyLmbu1mUuEva9igRU5Lkgx/SS7kUuy5HIX75b8GhccqvcijtwM7YuylXowN14VCicqwSkzJkjc73C8xeeT63I6JW7DdN+LWHvm3Ml9leMwQtuv5AwgZ3yZZRWAloJqExCZbJyZaWUgFKiUlzquxK3ArkWd1q+HUJ3YXJXziqoGOvubM5RCOc2mvXlL+dGCne9ghWmSozLa492brPBtbXiT8+l1X4235WCC2zwvFnmgJgP7X/fymOz/yy8+2yfARq/2V8YbzBGe251IJ2kkU7yXHnpPAKdQSVC9lW48RdA7Sj3Kv0DDM8xdHUP/lm20kQIk2ZApN6rGbyGpXtv2tSi+AJg7rsun4eAfSbsd6v0mzoxIte/Fey0006YOXMmbr31Vruv0Wjg9ttvx5vf/GYAwBve8AYkSVIo88wzz+Chhx6yZfbbbz+sWbMG99xzjy1z9913Y82aNbbMSPjiF7+Ic889F0cddRRWr15tPX622GILXHXVVaM6P56YMBgMBoPRDuMofu0U69evx7Jly7Bs2TIAueB12bJlWLFiBYQQOOecc3DJJZfgpptuwkMPPYQFCxagr68PJ510EgBgYGAAp512Gs477zz8/Oc/x/33349//ud/xuzZs62Xzqtf/WocccQROP3003HXXXfhrrvuwumnn46jjz66I48cAFi8eDG+/OUv41Of+hSiyAX8eeMb34jf/e533Z20AWtMDFQsoE18Y2VcS/NFMWkqggqjXbBarYi3z4RJt4t10kEoeMZfU88LqlYaAq1GNgVrMVqMl7uwd/4tkZFdWsNP9ge4sP+aylT8SFSlGSD42gHrjU0MBiUItA1JCCNuqJLttGI7umVBwvKhPqTzMvnNyZS0QdYk2frD8rECJudlrFZl0FzrZh44DYDV71jNRFzxPaq6NiNoK2jFXqjjJ6wLXbmpjE8M0verWdwWyvnaFyB/fgNtiq8tseMgbYQZo+0jDGMvPImHKG6r0ElOxbxguBX2c0fuqqEehD5617bsN13eVQhl72vuiIVqAW0TJLb+wdXeOenGBK2tx1Fj0il+85vf4OCDD7afzz33XADAKaecguuuuw4f/ehHMTg4iPe///1YtWoV9t13X/zsZz/D5MmTbZ0rr7wScRzj+OOPx+DgIA499FBcd911hQnEDTfcgH/5l3+x3jvHHHNMy9gpVVi+fDn23nvv0v56vY4NGzZ0d9IGPDFhMBgMBmMzw0EHHQTdxiFBCIFFixa19ejp6enB4sWLsXjx4pZlpk2bhuuvv37U49xpp52wbNky7LDDDoX9P/nJT/Ca17xmVG3yxMRAKLekUBTgTArnXWAX2vSgiMIGcKt5Cpzmwyb2K9iRqXwwFgpGFXmr8oo2x4RxSPjXzuunxGy0Y05CpqKiTCVT0obhsN5DFBjPJkwrtxN6kAiFQmCt4kBgV472SbDp4931cOHni1ulRWViv0IX2mu7i9veCeOSt6cL5YV7uJEZTyOli2WkjQYG60VGq1tiCUSj6rnv4jmrGr7pixiHeKNAFIR9ULH7HrVkPPy2S14lbivCY97YwiR2NokesUGxS3QnqsahvTZEeawQFf3SIe0xdeHBCsYkfMSs7sQ/5pcJx1s1juCnr3DIXhtiLVu37Sq5GyCCfVU/LaLi3KqC+m0KvBQB1v5W8JGPfARnnXUWhoaGoLXGPffcg29961u49NJL8ZWvfGVUbfLEhMFgMBiMdngJTDl/K3jPe96DNE3x0Y9+FBs3bsRJJ52EbbfdFp/73OdwwgknjKpNnpgwGAwGg8EYNU4//XScfvrpeOGFF6CUqgza1g14YmKQrG0iMYKgdmaTCt1XOaCapW+FJwILTD/C5dhpJdSrHIXnsuhytlRPxbUvkKUynZhw6Hwqyo6YTbhFOXuNOhHmenHlaDxtA7sR2ujgrLu1cBdXeMG3AM+Uk8IG3bIiTjLXeG6M2jOBAIEpJdhHQlGhBGRUvDaqDX09VpALsFLlixMGWisEjwuOVZqJaFdiLtygc5V2AdXIlNb+5KybKQ2TaHsT4IyCuckmSitPCoamNNwvWrvu6JgV5lYco4+e+caKXuPiMXsdlIAIGlBe20IF5qCK35KS6NS7H8IG8mt9Ts5MIwr7R0RowmllfqmqQxmCCwMIxkFjqRK/kiuzV79k9qhISNQyW/MmAJtyWmP58uVI0xS77LILttpqK7v/kUceQZIk2HHHHbtuk92FGQwGg8FoBz1Or5chFixYUJlX5+6778aCBQtG1SYzJgbJ6iHIfopRbVaZSXnepgPmQ3tZgm0ZX/BWJXolhIuaCuGcbdtjWkoZhsPG27kNt2FD3AmMnilphY4Yjy7G021dt5J0LEcYhttnUMjNkzLPFtsMPgciSp0J+5wo0gJ2cAoFoWx4SyuWW1Wuv2FbxJSkJtux1qJUzxfB6uChVFbo6sZmUygEfq5aeM+u1IUiVRDaO82Rfry9rnTIXLRgHgFUu4AH4k9/1W1F0oYxS/ucsNVm4w1cfwsi2qx4/UqCWe+zDsbWTnCasy3EupWvbSumxBe6VopeQwSiYT99gP8egHONlrrEXLTtq42Iti3TE7I4Unf2xRoPsMakJe6//37sv//+pf1z5szB2WefPao2mTFhMBgMBoMxKgghsG7dutL+NWvW2Ciw3YIZEwPxzAuIphuNSS2/LHpSHdqwJnZ1QgwIBUrzGACXgMsrE6wK2np0Bu7DOtMFTUTL8mGRSl+7LpiSQpjv8Z3m++11xZ4Q81FVN5xeV7QrTGA1fwWtwgBZFa6lpRW3t3ISKrim9qOwTENELuiU8K9ihdfuEodMic92yDZLMBsLK2RHgGq9CO0PNCY6XMFqgE5UN/NzEsNmq0Rpxd0tShouq2Mw2zgci/9MlNsp3L+SbqFYz4aPB5DVzX2rmUI15TRdDWJOgmvjaXTcQEwRWd7qoExhaOH5VzAWPisRSDRK5+i7C4fHfDflElMSu8860YVjVg8SaetmTYyRNtvKJy1g1QpjaekvjRIL10EGjXGDQHu5TadtvBxxwAEH4NJLL8W3vvUtG7gtyzJceuml+Id/+IdRtckTEwaDwWAw2oFNOS1x+eWX48ADD8Ruu+2GAw44AADwP//zP1i7di1+8YtfjKpNNuUwGAwGg8EYFV7z/7f37eF2FFW+v6ruvfc5JwlRNJBkgIRBMzxERECQeG/AC0G8wKD3Q/BBYMA7MoCKoM7AiMagBGYU4+DABT4mqDhynQ/lcX0M8N2A8hoek3gFGcgFFPQGcBxeeZ29u2vdP7pW1erq3n32SU5OQqzf9/Xpvburq6u7q/ep+q3fWmvvvfF//s//wQc+8AG88MILePXVV7Fo0SL827/9G97ylrdsUp2RMbEwa9cCIzbHwOumAgAoVTCppeADEaqnWpXj4p0JJ/VlG003FWo1EGqivymFhAutG16yOc+5L5MXKvKumvNtLWyWIHYMuDoDIXOJUg9Eq9KM4OjyIPIvjAIyXw7wfUP1yy8TgN10+0WA1ZqQ9KlLmm/63bYigXKxkyO5SvPNIBFineiVqXkhgqWsbNJgl+pGV/AawWMl+mmTlZFFqal3D2YRKgtVSYvnFETubXokJY9WmRtHHEdGVdtXI/StiFCDa6g15dQhNK2kVIkQ7SyIefX6Grtg+CxEfw9NOBzVFm3j3MIVR/oVphj3OxOYdErQVDTavTfcx+Fz5LjfsPKalLgot4/GuNCJQ3QXbsbs2bNx8cUXT1h9cWASERERERHRhGjKacRLL72Ea6+9Fo899hiUUth7771x2mmnYfr06ZtUXxyYWKh2CxjqAADMlGJNqfYiVyd25QPsWisxO6+pt09nrHX1C/YpEYStOdBRIIKVTAjPYMaTcXi8x7ip26YxH+NhTgZiV5QS+VDK5WWgtYrgL5gtl7bVuF06d09TfUicnXcQxRuzI4kyQAZobYrPNRjvLWZWZlBtvBe7lsWvpe0sAnXiX9s2+eMdslA1RuOSuzBQzzC6Z+TpLA5a5rTKxpdlQXO4j0x/F1a3XfkZu2JWKGApSuW5OpH/hjMfh0H7OE9OSWgbXutYLEfQJWTd/dxsa39/gu5qEvjszyFTwsHzUoJKbebpVjkDtTHKMWvG3gxmVUg2IiUQkWcW5ZoDALaCBjvGq07ZDGy3itLXEB566CEcddRRGB4exjve8Q4QES677DJ8+ctfxm233Ya3v/3t464zDkwiIiIiIiLGwnbMeGwOPvWpT+G4447DNddcgzQthhRZluGjH/0ozjnnHPz0pz8dd51xYGKhpk0DTRkCAFBq3YaVcH+sYUrcdjer4w9VrUjtOQN3RRWKHojG567rZvfSaB64i9op92a7Adcdv4nMySZrTAZwE0ag+6EWa05Q63bpG2X3BTNo0iQYkoAW4K0NGg5DSsS/K2tNWE8SROMfNwyUC6jmAqsN0DaQDKhmN4XB1IyqulA3VdnEIob3WzAofZsp3jdmTuR71I/NqHOXrbyfOZzbq3/u4sR8QBhojQPUwQfm0wFzYlLYgGD2kIQqKQ2U0LFU7hEp7/HPTIPUs/Q7rnTBpeaW9SvsCsydj5kSu121cseUJJxp2taTKEJuBTDMgnAW9pJGKjFQMF6bwr97mqCSvNRux9S5i665HlHHlkbUmPTHQw89VBqUAECapvjsZz+LAw88cJPqjF45EREREREREZuEHXbYAc8880xl+7PPPotp06ZtUp2RMWEMd2A4sBp7WRjyNs6QFeGAXQo+QR+8Ot+hxhuh2E6u0jBc+iaPrAfQhNQyJeG28ehR6iCubZNQN1wO6xtrSD2QFqVYsS7BBCHOAT/jTbq+XrbHuwR1lVOTu6UVNkSR0G3Y89qGtGuuqSlWXr8yRKqiDRnEE4eEmwyZhplq4FVRmtWHXhXBMYoAPcrvF5DYd0f3CkaA762D89bw70pJWwH/vfTaNfSPvloTCKYkKZ+XNAEykaM8by4uToTnLy7MnioBTNuTbaZFoCCJJIH69qly0L8GbU+AugSBFQ+cFglNiV13rI4kze3auOST3KdLLBz3c3ffjS2jXEmdGmgYz0ppr1XxKRSUPFySx30wSTREwz0eVx3bIU488UScfvrp+MpXvoJDDz0USincfffd+MxnPoMPfvCDm1RnHJhEREREREQ0IJpy+uMrX/kKlFJYtGgRsqywfbZaLfzFX/wFLrnkkk2qMw5MIiIiIiIimhAZk75ot9v4+te/jqVLl+LJJ58EEeFNb3oTRkZGNrnOODCxoJEhwAZT47wqgKe0PX0e8r/KC70cx1t3guAwghtCu6yhXMZ4k07FFbmInhXUvQ32+H5t2txgas4PVPWtq5S/yJrljF3nLf/dOFfwsI1+mwkz2SY+0FXVlduL+tiVkvsPe0PmRiFNmp+XgRDG1vya9bu1RnQ8DuLGJqSSmaOPWccYBcOmi/DiWAxLfpMKzCW1Hs6B4FIZYQIx/bWLPteNvQ8sQvWWgeo7lYvnZoOusRhV5dXyFZA8b7AWmufQBdpl+9W+UaEpiVqFC66zwmiAnC3Pi2crcI/Bm4kqpqw662zw+IqAgrZtLu9Q8d20vPhVuSBqbMqxgtfUbJLOVGmC4t/HpPjM4lkZoM2Vse8ui2lrH1mNeSpi62NkZAT77rvvhNQVByYRERERERENiKacycUW98qZO3culFKV5ayzzgJQzBoWL16M2bNnY3h4GIcddhgeffTRUh2PP/445s+fj1122QVLliyprf/+++8vbT/nnHNw2GGHDdxO0xbTZsFKKEPFYl13ecbnOmrN9JX3jbU4F0k+h5hNAmXhmsxY7MLjuxNa9kBj055oH/ZB8X2oW5rqkUuImjr43jpU3FGLIHYlt2KxrbIPxf0iXaQUMDZQHiXK33sFd79kqPDiYFSehWmRm1ma1IoFW0WY7sqlkmUfRDoAFqQao91nXpSiklulZDSsg2VpCcHbpeg10QaJNq5ubRcFVM7naGp2O3WfFdM3oLwIoqVyBZUVC+yijPKCTFVeSmHn7X7TKi8AbGZfqpZ374hdcrGY8gL4fcloseiuXTJRrh8tX9dePn+moHvF4o6312jSYiHRlzhTMaWWbVMEnQNaBF7j+ybbT5oKoa1dCoaOKv2z1EfFb4lrP99/1x4qxLftImOyaRPMkIEZMqCOgWrZJS0WzUtC0AnVk8BGgYxCnmvXP2QfBCxjwgEEE4MkMW5b0FWKc9gPShu7kF+SYtGJgeZ6Juu/PU3QEjEQtvjA5MEHH8SaNWvccvvttwMATjjhBABFZsLLLrsM3/jGN/Dggw9i5syZOPLII/Hqq6+6Os466yycfPLJuPnmm3HrrbfinnvuKZ1jaGgIf/mXf7mlLyUiIiIiIiJiC2OLm3JmzJhR+n7JJZdgjz32wIIFC0BEWLZsGf76r/8a73//+wEA3/zmN7HzzjvjH//xH/Gxj30MQBGHf//998db3/pWzJ49Gy+//HKpzo997GO48sor8aMf/Qjvfe97N6mdlGphz5Uz80EOtmszviGxcgHZguOF7ZiZBNa9qJxKGpja5rAbMjCY/sT7rQ7Q6Ak06vYLyKbRn3FpOL9jTeqG2/Zem5TXZd0DIPQFQk9Qef5GuVkahRXItvj8APb0dq19Waf/qBBghFAHImeG/az9ObuaknIal8Te44zdbZWf/eaBK7HJFYiT/nFI9jxYZ8q7x4aXLbtaeE2SoGE31US4z6ZWqRXqRkI9hUhYF+o4HHuAgiUBhDYFqLrwhusEVW2R0zQN9m5Xirl3u2BaWEOhuwqa32N+DlK/FOpHxLVV3J1lqHuXVqGsdaG0Jsw860oS40LIO5fghoSU7vTCtdzkurxT+cKux5VXtXBu9YFLs9Jw7sX8vhijgHRzYxsMiIlgPCJjMjAmNcBat9vF9ddfj9NOOw1KKTz99NN47rnnsHDhQlem0+lgwYIFuPfee922JUuW4Mgjj8TIyAi01jjqqKNK9c6dOxdnnHEGzj//fBgzSR01IiIiIuIPAoOa58c030cMhEkVv95000146aWXcOqppwIAnnvuOQDAzjvvXCq3884749e//rX7/t73vhe/+93v8Morr1QYGMbnPvc5LF++HN/5zndw8sknj7ttaVuj1bJKcDfr8LN2n/ytWElvmf7hs1V1n5hJVKYO7J3DXjlaOXbEOpOg1fYzk0qwtID5UMaIKZPdxmWkzqNPgLVaDc14GZNBGJtQH5IU2/haW53EB/Ny913oN8I2JQqmVRyrO4ldW4+rlG+kcsG92GPGzd61b3bG3jTuuYvZaeCxwrNUZRS09TzwMbnsTJAUtK08gSmtOxxojbSjClw+RXtSOZMIh+Atex8MKZf0LLfPP+V+LPUrdluWFz8DOk/8hfKamRNxMq5bJr/jtQsQ1vQrLMp3bBs6wTNkYknzdTMTImeudcHcgu6RiL7Mr4J73vbh5B37veVZBc3MRYMHFV+rD00v2Yz694SvcwjKeTX5xH7KMwRct2V8tNArKcHwAACl5K7F34vg90oTyF4nrK5HldiIcvnEsa66XC0ECWT35aRd8j5/Qls3CB1brsMJ/mo8xcK6+d1yv7vwbJMrqxVyXX+fI17bmNSBybXXXoujjz4as2fPLm2vdDiiyrZOp9N3UAIUJqNPf/rT+PznP48TTzxx3G077cy9NsvverJw2pl7be0mTDpO+fR+W7sJWwb8K5yVN5+bjT8b55joZ5oCgOFgvRXwxbm7b72TbwV8YY/t4Hp5MNQerPiFrb3HX/cYWJ+tx4cGr3XTEU05k4pJG5j8+te/xh133IHvf//7btvMmTMBFMzJrFmz3PYXXnihwqIMgnPPPRdXXHEFrrjiinEf+w9XPIZWq/hl3mqMCZMCIo4JMyZtBZz+sT/BP1zxGHpdMw7GJNStvLYYk1M+uz+++ZWfo5ttGmNiOkUXz4dtUrtOUbY7VcGIhH6A1xWYtp+NZvafdd7xuggfytueT6SGBwpbuEt4lrJd3GtNnP5DlZOidaBwbvZ2XJb+K7ohY2LXTYyJDOvNtyTPeVZbw5jYz1nX3qNuUmFKKowJwSU0dNtEn3aMSZCorZ8XTEcpLN59d3zhV09jtBAkFNdpWQgOX++S49XFI6npki6VwKj9LhkTfs72+dUxJrSlGBOt8IU95uKLTz6NUftueMYE/RmTTFU0Ju64Wsak/J00gYbKGhMl4om4mDS28jDWSC1jwn2rp2GygDERsUs60FgydR4u6v0SoyKJXyNjYqr9NdS7ECnk3Y01tUw8Kp6Dm1hHxGCYtIHJ8uXLsdNOO+G//tf/6rbtvvvumDlzJm6//Xbsv//+AAodyl133YVLL7103OeYOnUqLrzwQixevBjHHnvsuI7NegRyKkhBRwcBzkKBZdmFtVpvdWDS8I89yJWjjBe6Kusi3OsRej0CTM2LEghlQeRy+rjT1w1MguP9wKSmzCDXMt4X0N1vcW9F3d0eoddjbt+lUPanqxmY5GzWsD+wLP60/9+QZYLSD5ptyP/TynjdJleGA2O5ta1BuTVBs5mGygMTRYC221LOFRL8px0FoVcbraxclkWw/OPN4kBSPrtwziYkIbodtQORrGuFrkZchxOE2joT1/Ft+/2gJ+zvOvf/pOU/TVu5O0aKVnnzKBFGiVxWXide7ZGru3TAWLDl+P+1zvw21pjzs+3xwLRNwmRYbr/qCZdoLuIE6X67ku8OUBalivu1EYTRIOAZFLmBYGL/3yrROSkw4RjOCNwSN6XPoI0SAmzeG5UGgw7hdsuD5sy9itUbzgNaY/txTsq9A5WBiTh+IxFG4X+3mkw6bGZkl3uTa8+iCyG52ezEXhHbIiZF/GqMwfLly3HKKaeUUiMrpXDOOefg4osvxg9+8AM88sgjOPXUUzEyMoIPfWjTCLo///M/x/Tp0/Hd7353opofEREREfGHDJqgJWIgTApjcscdd+CZZ57BaaedVtn32c9+Fhs2bMCZZ56JF198EQcffDBuu+22TU6X3Gq1cNFFF417YFOXjVQRQK43sRjMzlKYahVhlevCEFW2BDMpPo+twH4XzEfYmS2LMRAtuKnUIc/MjOp/nolwG26qQ7oLKzimpMKOSMjZfiiKo/JzlKHNHTUug3TxjNHO3FXbztzapjKrrjRd+7Dbg7ib65CbR5nCBvzskgOpSXg3Ye2O5W2GaaHEzyyzXjHlzjeyT6w9R66q7rHOXCFMl06Jajfx+RPPmJTcXCFMIwrleyLfgzqX2M2EM3GI+pzpjoO7hWYn+Ov1jIVy18KsThi2vu6fj2SXSJM/hxImQbFNBb83khBw3QTlIiBU3ITdPn4nWkaIXctrLRiT0MzSL/Bf3fexYEwRCDBRNfc7yMKtKLgAGB88kMPlayr16y2JGPl1cjEpA5OFCxf6vBABlFJYvHgxFi9evEl1/+pXv6ps++AHP7jJ6ZYjIiIiIiJKmAjGIw5MBkbMlbOJcDbkkhtftefVB3OGD4teFOp/HhbCShs7oWAAeDrWFCAtVE+WKg+OD79rgAJr30BMzYBsSt+AaGFIe+XpDW+7F+eQif3Cc/RxJ2xkXurElGImH85OwxmoahJMbuK0qU60ysJWpyexayl+5TaZrKAOjA0dDgBKiHUBgDIN1WX/6CBgFrdf9iPWnbAwtadKAc0A/3642IMJoTxT9vWqXFVj1ZUlLmMTUAHhwH3DpP4zi11z601CkjkRYlEAVaGv+KxyVPb113gEzezHGrG4o66bhMyqVEQzm6LFNnhWRiVjhG8P7q8OgpkBXlOFkIUj5WNDhlITeQplE/rVnCsJArpxny4HXCu/Z0liiv4Usd0hDkwiIiIiIiIaEE05k4s4MGH0TWRXrEOtidsvvUNMzfE1LIorH9YVetUY8uyF0J8oIsuAlG391ZOrTdeZ9GuzuEeb4v5Wy3S4ClWpHIUMjixK1Jf1oKTmWOsPyc9T54TcepyYIAy5aYtZ9ZBdjxi7r2ZW3SAhr/M88ERQ/f0jUo3UgPceUr58n/NyF2FdCeVK9NMy60c2QR8gNBZOK1LVmDA7kq5Xpe+Av5fVxkP0ZX/vimR21J8xaWD+KiHaZXlBBvJtcuHmW6Ih8FoZeR7HjmTKs2YBU+LaXKMHcfeBUJMgkNkYoTEKmA95bWEMs1I9we9EBVSvi3PtDVImpDXaDef9VaJqAKQ5yFJCYd1Ke88enRA0CC3rHZQ4VoaqaRn69APAa7ISbXwkvi2NaMqZVExqSPqIiIiIiIiIiCZExiQiIiIiIqIB0ZQzuYgDk/GiIhSFF3MxJSsFYzXmHQCArjGF1NHUYchPEfTMHZ9XDpsUhKaUOtNOo8jUHajq16X9Y7/VdWYmDsxFXetimFiTTtvT5s4z04oh82EgsyYcwxFfuWmZqokGWhblaekWuolwuXECN8ric5/KWUuckLs2DlBFcm2FhSQyBgOFeNW5BYeosWRygK/eDva8XeUDrPWLnEoIApWx6cgKYPsx88KlNnQp5uioSdc301hTnAxwRvbXLh+mUhudSSWHMOEEfdug4godmnCUqf7zKUXHlUHWZJeWbuL8ntt7myflc8p2u7U0nzh7VdnMSEIQ7Uwy7qfMCPOI6MMQruzwfTK8NwTtIhzXJQz32nQqmb6bzqFDE2iN23JuNHIzSaR/NOVMKqIpJyIiIiIiImKbQWRMLEhX89ooQmVb/cH9v6tgp5vV14r4QqFrzbmcSLdmZ78Q8zXnV332bw4GYkdqDyxPs0ip8uxynOdSBkBWl13Gn0PlQtjMs8rUf+eZru6q8r6U3Ocm0WulTYL50ANwunVMSbiP11mlBLxoNOzApAAX9t2yRyKkej/34FIZfk4cIIzFwx3qOyuU9UjRqIsHJhiJ8UIGR3SEBDM3lgUzqciJ02bG0Zbt+Wur5L9hpoxQdRNueowBq0LKsjZ1jIlofCXomqtH+WB1nM9HCmSD34zKq228oNqxuCI0fRjgLIxHCIh+l1T7JvfBWiE2i6xJgaB8mHm71oJV43OYQIxrjPZibz5XrpH3Y/i2AKIpZvIQByYRERERERFNGCtv2KB1RAyEODBh1Ay8G9mSgTtZg3vxIEnwwqlLU/K9uu9BUrHGdk/Gi9PEMrB2xpgisNtYzWkIrFbNWGxnWyLgFrtyhloFrfxnZkeyupDqYRhvnsFKPUhNs/3stM9laeMyD4cwDTQSzzYJNdomeS/HE0qcymstWA0j6QSUmYsK8+J0LGUdSUWvEXZl76Xsj+mjQzFJzT7x+lRYsECrAQWAkwZyoDPhGpx069vWnCbXnjOvIUlrWAm3i1kEZlB62uulggB/ReqIoIIgwBogiMmgrFbktCXVdAf+cxgELRV1Oy1TeB3wv3lpkiOHEe7C/V9w1p/UPuuG+xaxfSAOTCIiIiIiIhoQvXImF3FgwhC28/EwB2N2tjBpnxvtq4r+pFJnXTvGozExNUzJZNOJmyKvtkHkSm2vk/tzcVWeVhcB1vxnACJFPc/EvNZBc0h1MYNmpsQnepMndCe2zXNuWQNeXtgZavY3zAZdSPqKd0T1HHXMiZtF84q9eaTGw3l32O/Cu8UhCOImk/CF7S8FIys1VKzFj38jqdPn9oVh32XZvAP0Xl9cILWsh9Z6GxQs99da8aoRLEMYtK02XH6wz3l6talgOATbFgaGI125peLhUP+keZr8/XJ6qTKbJ8PWu6pt3+BUBoDwlAlOoRS5fpcEN4nIJ5askc24S061Qa6q4ee5jtpLk5qTcSYNnFAIHc9m1RExEOLAJCIiIiIiogGNruzjqCNiMER34YiIiIiIiIhtBpExYZTUdd6k09dUM06TiEJIuxMqfHdgbhlzhN2vDYOMzPuZifqUqc3qy5io4a0010jzDaHa3lL2YVsstYHDtHJZhd06CW0LqFfq2X0ub05LUOF8XB/xa6nuTQAJ01BO5eyqYZliX/3x5Y3BPu3bXbomFEljXY4cG6DL3zcqlQX6MOuheYPPzyLOMIOwqENeal3+m76QZqbg/EYEemMTjgouSY/WC3NdnbY+mQm5DiSvRxwnv9fVXRL+srsy+9/Wma1C0a1CVYCsw+dFlX5ZMuWwB3FSnLguuzCDg5rxK9nLEm+Rq4m5ED5CF0SNizS4xLPbcK3Zh/qbgCYc0ZQzqYgDk4iIiIiIiAZE8evkIg5MJCqDb4VwvN835PSYCH306s4XHkJ+ohoIQUvh3zdF0CqnQgMIYyuMw5ZEXXvCcPVail4DdiT1jIlJy27CpVQC7DrMs2oRYK3qSirv91jtR99nWxA9VmDIs8KaWV/TrNJlF2YXzUoQtZpHyd9zJeiEssBVGdX32qiOFQtPq2q28QeRwZmzEDe6gg66Xewr6SODtcoUkrWJbye82zC3R2fwgdn4eOFK7B5Bv1dBCYbFueuKNhpBu5Cn7OrubW1qAMcMMdUjjnfsHUr7av8b1lQtM/0W38vH5UbBWKYkD/qdIVUVWTf8XIQBBptYDxbjJkTI2IVfXlr8Z79dIg5MIiIiIiIimhADrE0q4sDEgpTyrADPIOXUt07jUOwQlQze8VQuqm4KFBbCYDANCYC6pHrjxnjaNgkvXsiSAPL++TKhu7DXnPiyzJQYEbYcKFyEnbYk0CzIbc5dOA/P4V3B3excsCS6IbAUo1/Y+mJG62eqxUmq5aRepbTdwAU743UpnPkYNvta5sQ1rulAW2RQ74ZBupKok787QoLZL8F4JOuDxgc6FtKeMXGu0yGDIutuuBchc1ILXe4jgCA4WOvDbVOosiBOv0Jlt+AB4Zi7mpD0PjR9tR9JpsR9DwkTx7wYRzoliUFa8/BNqW4+vn+73fkN+idJnWBEU87kInrlRERERERERGwziIxJDRxzQhAh3e0mTicuZ1kT7J9emgHWZdPqh1qb/QDD9H6B5cablK9Ot7KpCL1u+DMzIOJcHDStFGAr9NgRoegBIG8rFzzNBVEbaCZc5zrCO219RiFJ62echvzEt78OhWo/cz1mHKneeUZJmfXyybRLWufS18tThG0bz2Os8xzhrzUh6akm6JcrP4CmxGlVRMI9I1MHACXPl35JAkkew+cN3ns5hSPx7nPdbl9wXpnokBIRCE16q1RlJ9UQ/UIaVPF8UqJ9lT4pnrF7prZNTisCpElxQl5zEDV3a5UP8OZYFeF6Vdnnjuv/y2Uc81FlY0Idi4RM6bCpeUPHjYnQs0TGZGDEgUlEREREREQDoilnchEHJhZSj9GozWAPEPDMQLlZtJ+BDtgDKTiuaUg9VuK+zUG/uog2fUqyCeH9S8eWGBM1lvShAh/Hws7KWuFazGpDVkXsq9Tb9r9Qrkl1DhRBGRmGfqyQ9PL4OtR58QAitDgpGPbqYKZko13nyve3kBWQcqnxaBVqjnf7Aq0EEDJbfk2qhikIy4mZK8f6kOwlQm2H1LawfoRjhHARP/GH7vryEib17eZ6VA1j4ryPQq8cVbznivu08ZGNjGXXkHgWxdVZx2qFj1/81wxj6jj9U678q+yqtO9CTo4paenyheeOCZF9ssyOFA+uzBDyd2NUkexRF59zqQ2TcXtqPH1K9clr4jgqikpsS8T2gzgwiYiIiIiIaEL0yplUxIFJREREREREA6IpZ3IRByYSg4hYA/6eQC7cfCmYErwoc9yoC57Goao5uJpShb9cXRPrApRt6mh9EP+9JmyiSadw+RXqvsRvL7ahFIIeAExL27Wqmm5SXsuTBOcsZc7ldeCaCUC1wgOLlbGmFEWE3B6XpmHgKlNxF3auwY2WvKIBWa4rgdXYhGOs2YZyDYzattg1BxNTObx5oA5uV/m6wxDzde1VxtddyiYsywYizlLId/HjX/kRrzMX6fImk/r6dCB0VVTTlqBrq6wa/K1OZ+zaKES3QHHuUPTqTUskTLZBRTJgGj/bwOzSCGFmCd18ndtxLkzO7h3wN7OXFS9YEtiw6sWnvK9/k1y4e6WQQ1tTjrYx5soHGpmdmE1H7mT+enwZPklNYLcthSh+nVREd+GIiIiIiIiIbQaRMWGQZxrcrFyjP4simJNKmiox03esSeP0on6fIhICxaCMZEsmI532pjIuNQHRKnWG+5Qqhewvnkcwg098QDwfRM3uS5VjSPK2F7sCnjnJO4Dp2POFAdo0VZiCEmNgguOCIHyUK+SWPmN2pGUTyGlNleBpPtCVAXKUXDMzy4bwjDY3Gnmv+OwErtzFWBTYU9DMmLBrMLvrdqtsRCkYWMgI8ixbPqKQ1eBZrgyeJkSnpXNJ5sn40+msYCzGTN4ntvMzdbuSajnHnDTNeMX1uCKuYeJ70Bd8X/RrDsxXagsK4SuMqLemHpDqL/ptvP815cJ6hNiWD9SWzUtS48SmPetv3S/An9xXCjrXR5CtFLlgg3JbWF8l958q9ztjZGJLWa5vMycU0ZQzuYgDk4iIiIiIiCYYKpbNrSNiIMSBCUMkzCvNTng2KTQexYaaOkLjq1Ry19Xtzt3QrtDYJuvcHKakLkHeWOXkOQc1AjYFbatjSlBoRyhJQAkLBuAjPZEvy8yWCwXPrsGpQt4pa0pCjYlJxExXuAkX9aA6veHvRvlgZawjcKIDr3/hhobujHImOohLcLdXNLjXLdZ5NwE22IZzSPlwBipcgl2COusGK11lK5ooErPgull5iDAkPgWfa9A0a2xMytZPe4JAG9SgTXG6F3b3deIU+10WDxM8Cm1MmKBPBu+ruFmLd1SReP01eR0KB2HTBMU6IVePvyC3rfKb4JkW1wVtnaZVXKwkWB2DwcRwYhoZEndchenznSXwznZ1K0XQdmuSGCTKuISBvD3XBJWXLyo8V4YEOacH6EO0Rmw/iAOTiIiIiIiIJkTx66QiDkwslCEoptoCTxi5rZRUK0TADpTs602j+352YVm11Go4DcwmMCfj1YqE05IBEtCN+/yhDoU1JiKBoLvfIlGeY0jCIGpp1SuHZ7dOa9Lxz9AzJSxMELPjpDy7hIEPxe1Cq1s2TcyAOdCVttt4RmpIVWanPHOUE2KX9E87kZHdK47lwFw66K+58BhxTB+31V+Lv6f+e63uIUQfNkUyHn0n4FQ+ruThMkjXkv8gBnhvZHtCTyFVd2v7BUiT+pswF6AIB+8+c1+QCeqElsIkcM+P+5hKCGQ7lbInIcFQynKlfbkCR3szkv6B1364vin2SYIv4VD0QYA1Pl4rKgKlFVtLZYmUsFKU+7vWBm3SgCk+J8q4cPdcRpE/Jwdaa2JDXHaKNAfSPnkGJhgKE6AxmZCW/GEgeuVEREREREREbDOIA5OIiIiIiIgmsLZvc5dxYPHixVBKlZaZM2eKJhEWL16M2bNnY3h4GIcddhgeffTRUh2jo6P4+Mc/jje+8Y2YMmUKjjvuOPzmN7+ZkFuyJRFNORYqJyjFwbDKrpK15dmdskk3miiobBydMaCmSQkXv00dQtYFWxuzHVUT1tYEKeUz/9qgaibVTtBKQRC1vK2cyNWZcAKhIinAtIvPuXUbdiYdKUwMVX0Ebx5h8SlT8s61lrwrJgv9eN3AB5fjyRXlh9qFWpVzmXRbKXqdgr7mPCjGuhITt4e0++zcLdm1Vp4+6LukqtsGQbNAtlqmnD3b7g/NkWE7pCVCZieWZRXq28BVBCYMb67z9TphLB/U8mUr4tdwncALWV2byiYUaT5z2Ym1v0kc/Iz4tyhjUyS5wH6KzS1WKItRDeS2D/C5wt8u7dui2WxjzSCtNPeml+AG+vRf3gTJJh0lHqqzeAWB3sC3xBSJwRNFlTKJImE9t27xVgzL7vJEyj2UzlCh5J461EWuRjEZ2Fruwvvssw/uuOMO9z1JvB/63/zN3+Cyyy7Dddddh3nz5uFLX/oSjjzySDz++OOYNm0aAOCcc87BrbfeihtuuAFveMMbcN555+GYY47Bww8/XKprW0McmEREREREREwSXnnlldL3TqeDTqdTWzZN0xJLwiAiLFu2DH/913+N97///QCAb37zm9h5553xj//4j/jYxz6Gl19+Gddeey2+/e1v44gjjgAAXH/99dh1111xxx134KijjprgK5s4RFNOHSztVhavqvLCm0ksVkBbGl0H5cfdFHaLZRYn+A6gLBQNr6Nf+2uupXaf1sXSdHxTneO6WEF5lkS+CpRouxSiV9IFU0KtIpgauwjnHYW8XQhiTVIwJyYtGAPTgvtOKZC3i4VSAqUEF0RLLgyjiiBVuYLOi8BdKi++q0x59iS4lVoTtCYkdlGKrADQQKNwpaw8TuW3pdog1QatNEcrzTHU6WFoqFhaQxlaQxnSoR7SoR50J4fu5MBQDtMxMB0DSgr2x7Tt0hGf0/ICLTtzsLhnJDbVLOE+F3TNLsrUlK3tC3YRxzGjwZ/5OZTaEMI+R1Jw74nrCzbIHveD3GaVJi3fadvmmj7hQtDr4t6RQqAgDi4pFBe7k8j6i21KF4trT+IvkowNxW4rpIRAqQGlptpvxQ1Vyi4adrHnUX4ZBNqyHrwk2vhFeYFroggtbdDqwzzz8RLGKBij0MsS9LIEmV3yXLtzvH7KhmIZXo/XDa8fqM2bjT79fdwLgF133RXTp093y9KlS/uedvXq1Zg9ezZ23313nHTSSXjqqacAAE8//TSee+45LFy40JXtdDpYsGAB7r33XgDAww8/jF6vVyoze/ZsvOUtb3FltlVExiQiIiIiIqIBLkfZZtYBAM8++yx22GEHt70fW3LwwQfjW9/6FubNm4fnn38eX/rSl3DooYfi0UcfxXPPPQcA2HnnnUvH7Lzzzvj1r38NAHjuuefQbrfx+te/vlKGj99WEQcmjJo+V7hW1mtJvHmVqvbxusqaQrKPB8yO5KJOricMBqe13zfI+QUrU4HdpvokDqytbyz0Y1YsK+QCqKXK26A5/HxLI7fakmyYk/fBfldCL2KPY9u93c5MCQARUpz8mhko1hw4F1NVebxOu8Cuwalxs89KgDXLkDTBCHt63S1Nk7KLJM86E6tr6ekUOetPOImbEwugqvvg62jSiEgf3T6PuSSnCEPTS41JUzfh8vYSdXD/QQHrIOpu0nuV9B1iW3hq7idNgdwaz8NV1/SRUoA1EhXVBW1kvZJzDVZC8GHPwd8VoNLgRvOJJNnlkuBR8N0nyBskJ55LoSAq9+RmWT+iFSGxdTOjUgfWreTWT5vfG+Pchwktq4mZ2i50JTt21qOXdcdu8ESAWb/NrQPADjvsUBqY9MPRRx/tPu+777545zvfiT322APf/OY3ccghhwCACHJXgIgq20IMUmZrI5pyIiIiIiIitnFMmTIF++67L1avXu10JyHz8cILLzgWZebMmeh2u3jxxRf7ltlWEQcmDZCD+4rJXepQNtUlbAA9RiOFOIaug5QCaV0sgoUo6VTEIlmKfnD1aV2Ejk/993HpS5q0LbXnVSCtYNoapq3RG9HI7NIbUeiNKGTDyrElrCXJOzZhX7tY+Dslhc6EUhReONYThxIqvGysbsA10epJ5KyJy9NQDhrKoVvFkqTGaUtC271S9bb10rWKrmSgYKCK5H1GI881sjxBlid9u1uSGqhWsZhhXvJi6RinqSEblp91DC74Ws1S8koJ2QfJwpj690bqSurs7ooAlQFJN1g2Fku6oViSUd8s1+7+so7xQXn9idcfcR8R96NybTUNIFVaVHC9JY2Nq1dVjnPnypRYdBG6PmRRCL6yfpqbUhuLJTcKhoqF+iwA+upQZJ8Oy3C9EqwV4bLa6lESRU5jwgtDa8JQK8NQK8MOrVHs0BrFtHQUU5PJ8sqhCVk2B6Ojo3jssccwa9Ys7L777pg5cyZuv/12t7/b7eKuu+7CoYceCgA44IAD0Gq1SmXWrFmDRx55xJXZVhFNOREREREREU0YZKA3SB3jwKc//Wkce+yx2G233fDCCy/gS1/6El555RWccsopUErhnHPOwcUXX4w3v/nNePOb34yLL74YIyMj+NCHPgQAmD59Ok4//XScd955eMMb3oAdd9wRn/70p7Hvvvs6L51tFXFgYqHqkvgROVt3JTlXEwYZGQ/ILDidRWhLVKo6Ag9D1QONdtGx2JFG6OpnTuWljKnqX0L0YXgAFCxMq1j4u5MYsMZEhI3nCVouYpeUEvKJtdOapOTijhCnqk+9XZ9jhGg7a3PhwAmFBwsAGrLxIIaLWCOtTrHWqmBLAK8HCWeRYyG0ufeycnwHCS938nZ5FxujbbhCW0iBevaaONaJ0KG4xxVIFRyUF3nUkj6COSl9D+rlMq4bmCLBIB+ne3adlY9T2n+uxDEJ6u+Lfrdf1bzn3I1rvd5sEVMuW98OVbphhaeS14gUayGg4aJa/CiZcF+f66i7AHGgu+d8eiVeU7etrEOR0EE9kv1zfdCuc6q7qeWy3SzBaJaWjmNwqPyhTg/TOhuLz0nROUZNim6T5u01jt/85jf44Ac/iH//93/HjBkzcMghh+D+++/HnDlzAACf/exnsWHDBpx55pl48cUXcfDBB+O2225zMUwA4Gtf+xrSNMUHPvABbNiwAf/lv/wXXHfdddt0DBMgDkwiIiIiIiKasQmRW2vrGAduuOGGxv1KKSxevBiLFy/uW2ZoaAiXX345Lr/88nGde2sjDkwiIiIiIiIasLUiv/6hIg5MGEKcRAgoVni61oWR3lwGkYOIAWObPYBm4VR4vPw+CN0rMpjWbu93TFg+MOmUmhhSrsKU40xKHG6+k8K0vSnHpBrE7rfONOPDzru1CDsfmg54n+nYelrkTDcuE6wMDW5NINS2phhbRppJ2tZ0w985/DyLAeVlMm0tHX3D8N/OJVqUZxNOKTR3AHYPN7aMyZUox9dWOcwz7NyonujXbMKyX5U4JnTPdbfNiAMaTDi+AaKcsT/+eXAcQwhvnbnHmnlImltVtXxYR6UZNWXqwt07syC/tqG5yjSbfCvuwu5e2/2pzz7sC3rTZd/fHOXfc5UE2YFl+H9VfiguJLw2SHR5m6tafG8y4YTwmTBUpc+6vm3D6PdM4kyW7lxJ+Z3qpBlS+zmzN7mtJiezcMTkIw5MIiIiIiIimrAVTDl/yBi3u/Bvf/tbfOQjH8Eb3vAGjIyM4G1vexsefvhht//555/HqaeeitmzZ2NkZATvec97sHr16sY6r7vuOoRZFJVS2Lhxoyuzdu1anHTSSZg1axZOOukkrFu3zu079dRToZTCJZdcUqr3pptuGjyQDMF1vpJrV9AhQ3fITcYA7Sq5mcnpNLM3oXvveMPGu7jpmFjHcV1dQtdiUsqFl0eqgVTDtJJiaWvkrWIBANNWyIY0siGN3pRiyTrwIeiHgHwI3v1VuMCyezC7f5oWFWxJiwq34JSAlgFaBiqlIlCVJqikWHTLFEtC0AmhPexDwSeJQZIYtNMc7TR3YecTbaDtEkK6YOakg8WyKrnGaC/FaC9FlmtkufZhyAHHNJhcweQKeU8j72mYTMFkqhDuNnkRJAQk/hqd23PqQ6A7d2n2PmXvVYX+vDb596MStj4oVxuDMAOSXrGorFjcIcKdWeXFort2yfzi3s/wHCErUvP6SbfpyqJ8nbzNpTdIPJtSOQeHq7ch62vdrHsa6GlQjbDZgZ+HeCY+fL3/rFMDnRokrRxJK3fflXje7Mpe57bOaRLqFv65KIWg1wZ17sHllAqSmTHo5Ql6eYLMaGRGl92CbZvSJEea5Gi3MrRbGYbbPecmPJT0MJT00NI5WnpyWBPXrzdziRgM4/p39OKLL2L+/PlotVr48Y9/jF/+8pf46le/ite97nUAACLC8ccfj6eeego333wzVq5ciTlz5uCII44oDSTqsMMOO2DNmjWlZWhoyO1ftmwZpk6dittuuw0jIyNYtmxZ6fihoSFceumllWAyEREREREREa8djMuUc+mll2LXXXfF8uXL3ba5c+e6z6tXr8b999+PRx55BPvssw8A4IorrsBOO+2E7373u/joRz/at26lVG0WRcZLL72EefPmYd9998Wee+6Jf//3fy/tP+KII/B//+//xdKlS/E3f/M347ms4vyGoHKrMeHZjwgNPmE0nNRWBMNCHzZ8fOcK3X6V1JqEdTXVPd4RfT9tSt0+bqO7t1QkB0ShKQGAfNjqKUYSZB0NlVpb9IhyMohsyOop2t4l2GlL2BVYe91JNky2bnvdLgw9+bDfJcN/oRlxNu5W2d23mM0VFxcyIsZ4HYgOdCfSjTKUAvGMkfIUUMBor4Uc5eNKyeO4row1JU7cU4M6aoB3UbmIFn3SBdWqOVSXD5M7GzUlQZNInI81FK119hnYW9sbsfeGNUJJtR73lQAwyyL6gisbvgqhnkOhqi2RdQe6GROkNEBS1YhIhsQFU5PtAryeJ1NQqSwMd1KVAMjLoh7nwp4UrAjg3Wt9+20/0r4hKtCYcCDA0vU2ELqu/4nvJfdgeD1Kosl9JlIg+P6fB0wJ4LUl3J6ODUM/nPaQWnakJaiHUKe1xRBNOZOKcTEmt9xyCw488ECccMIJ2GmnnbD//vvjmmuucftHR4sofJLpSJIE7XYbd999d2Pda9euxZw5c7DLLrvgmGOOwcqVK0v7zz77bFx11VVotVpYvnw5PvnJT5b2J0mCiy++GJdffjl+85vfjOeyIiIiIiIi+oMmaIkYCONiTJ566ilceeWVOPfcc3HBBRfggQcewCc+8Ql0Oh0sWrQIe+65J+bMmYPzzz8fV111FaZMmYLLLrsMzz33HNasWdO33j333BPXXXcd9t13X7zyyiv4+te/jvnz5+PnP/853vzmNwMomJnVq1e7OP912pH3ve99eNvb3oYvfOELuPbaa8d3J3Jy3hlO7G0MwAG9BtGqNBVpOl6VZ4V8TuRilO6k8HYZL7tRN1ofoI5+3kDyfjimaZBr5HWr0JwAQD5kg4cNFd+zIY1sWEFbxqQ7RaNn25G3bdNTVIKn8TrvANlIUZ69cJgpKQWfC5to9+mWcTNP6blQrMkxJRVPhqT/DfWJz+D6SVOgNT5HO2hHlifo9cqCBhUyHwLeK0NSLsG20rTebtLlwkoeQ+Wy7tDx/vDKJiUFC8bn1Vn5XTTMlKXw3l91t6+Okag5n0SJ5eDjQw8cqinPCSLb/Pyp/2+AfZVJvschu0SC4ax453iGxDE3tk/r1LgEjuH5mbmTMQ+5nzvmT1GFeah77SvsWQ0LyOAAgYmo15ByKRaqdXv2BoDTjgy1imBqqTKOVZHH19W1JTCR2YUjxsa4BibGGBx44IG4+OKLAQD7778/Hn30UVx55ZVYtGgRWq0WbrzxRpx++unYcccdkSQJjjjiiFKWxDoccsghLlsiAMyfPx9vf/vbcfnll+Pv/u7v3HatdaO5ByjMTe9+97tx3nnnjefSkLYVWm3mqMU/0S04MKHQzBEeIgYmLftP2rWxYVBRegGkiLfSgIb21tUlD5UDE3azrs1KbNfWbFM3MEmsyJXFrjotBiVte83txOe2NYLSrwxM7K3JtR/bOeuYCv7DKKBCl3NT4S1OfGbP1pMb22iiUplBIF0nwyiZif1P14GGtp9d0ljXDr+Py1NDx6O6/3AOfE+EuUh+rn4FoPwY2ZoHNA8mtCg34C3p2Do6WiFPgLb9RXIWCdsHtH2gJsG4Bib9TDPyeFdGV4+rG5iYYF/ubrFq/g0A0LE3r1gHNrHSyC68garmd4IHu1TpryEMVKl/A0DHXmRCQDLAP3h/fPkccmAS/iy1SKHN7r3BzU2o6gLP7xT3+7YdWbcoQWrts6kU227HkV//kDGugcmsWbOw9957l7bttddeuPHGG933Aw44AKtWrcLLL7+MbreLGTNm4OCDD8aBBx448Hm01jjooIPG9Oapw3/+z/8ZRx11FC644AKceuqpAx936nlvxcjIyLjPN9n4s4/vs7WbMOk498i5W7sJZQTxJyYM9vf5rxPxjOs0G61gvR3g/LfP3dpNmFRcNPOPt3YTfJ/KGktNGM4eHeB/QB6se83F169fj+X49uY0azBEjcmkYlwDk/nz5+Pxxx8vbXviiSdc7H6J6dOnAygEsQ899BAuuuiigc9DRFi1ahX23Xff8TTP4ZJLLsHb3vY2zJs3b+Bjrvvq/0GrZbUxIvAZ52YJZyvNZouGE9WJXxvqYjNJq6Vw2pl74R/+/jH0ugbKmL4mlFrGpO77ZjAmaDqHyBLsRHcsdG0VczsaSpB1rAln2DIm1kyTtxXytkI7UTj3iLn46p2/wkampEVQNZf3hlkU+486HyIvdmX62033asweqlw27WROhOdEeWy+EdlTQ3OPfJyOdnaiQL5VgoZm0SMzJibF+WpfLKVfYBT+fBKZ0RjdWFwo5/NRNeYprpPLCOqoUtbtk/lbHEVlr8mtldumba4dTvCqMpHbhlE/yXfoaIXz3z4XS//1V+jmhHSDrZuTxtrjM/tqmhaqrrlNqDPthK8ET+SFedD1LZlhmp+XE5/aslPsDWmZqpkscPHuKIWLZuyBC194CqMmaIimog7Am5U5Z43Rnprhw1jw2smdKScUsdYF5OP8TW0rLE21qcRoZBFrOcCavQ917FPAmMiMxG3SODd7O77e+ld0lXHvghFB1dw75UynxXq41QUATG9vxLRW0Sm0EL9213WrjdkSIGz+RCSOSwbGuAYmn/rUp3DooYfi4osvxgc+8AE88MADuPrqq3H11Ve7Mv/0T/+EGTNmYLfddsMvfvELfPKTn8Txxx+PhQsXujKLFi3CH/3RH2Hp0qUAgC9+8Ys45JBD8OY3vxmvvPIK/u7v/g6rVq3C3//932/SRe2777748Ic/PK78AFmXvEF+GxyY8A9dr2smbmCyGRqTgQcmfP/YAsXmC62Q2UELJ9/L+bsuFkY3J4zacxjxex9S6szq5kTI+VlS+EMt/tFU7A7FOodxdLVfVwcmqQoHJvzPBBV7eM4RPEXnyFV5W2LPMQrTf2Bi98vj6uh7qpyvatLxCftsPeQ/h/9gS0FD2ZTF/0PF4KUSumWMgQlj1BC6OSG3M+WEo7raZ5yx1kSLKrhuWWd4PlUtUhmY8NpU+xKJwirYRq5PVyk0NyAo3VuAX4RRIoxScLNI/vcrmwmpVCdfmu0jMK7vhH2hzsznPL7sBRmV+4GJK1O0synya/k8BUzQ7+TxXWXQVbl7F3JRj3YDk3K/T6zIqKdzZJqTZPr7lqlJonsiJhXjGpgcdNBB+MEPfoDzzz8fS5Yswe67745ly5bhwx/+sCuzZs0anHvuuXj++ecxa9YsLFq0CBdeeGGpnmeeeQZa+/88L730Ev78z/8czz33HKZPn479998fP/3pT/GOd7xjky/soosuwve+971NPn4sNOoqJhCVwYuC/7GVQjp5jOEfQ0JlKiTb2yAEBQAYf47aAUoTNemmUOUBirEamWw4QTZi3YOHeSZaHJK3FbIhgBNgZsNALwg/Xze7ZREi2QBiRcNteb59Tk9AFUGEdgyIDClftadzFRwmnkWEecNAoQ4uTL1hzYiHcyUOQ9N3E5je2M50fqbcwJRwiYbmugFJyKSUDiz2aREULdT9OM2KDFsftlkXzxoA8sBMJfVE/YSppP0+F9re+H2MkNWRzfG6kzIrUhwYDEhsVmpmOVRqPIsV3n4emEh2TpXfkXID7LnkYMS911y4+mzdaYPw8wAqGa9lCoUQYXbh8D0AqqygLG/EwMwESmQ32LcCVylgddkpEs/mMLhO3b8rbzFE8evkYtwh6Y855hgcc8wxffd/4hOfwCc+8YnGOu68887S96997Wv42te+Nt6mOFx33XWVbXPmzClFjo2IiIiIiNgkFJTV5tcRMRBirhyGRsmEAwRsSB3j0A9N1LKox8/makwhwecSc+JCyQdt4rrZxGFUOdha2I5+11LzAjYyJyFkvcyUDBddLZtig6kNaRcsLXfaEPu9U7AgObv/tlFN2NcSM1ZOsJeWrx+AD0Jl93GSM6XJMUsu1DsTUImpuASPB0QKmZ3dZUGYcaWoUmfV2uYDVjmNinUR5qBqsr1k6p5jnQ0jOFd4adIVOFyzuSb37Im25v3Ejv+TDYIE4OB3dR40/T7D93Oyx9exOY7JD1mJRJxHl8uW8r2ViR6/WZKJPdvfWcJAnpFz/a5d1oMU9Zb7kgviR7xNsCxspmUGhyCsyWU2hHJVYX9qn3rgdis1UqF7+yDBySRTEibvk7oQx5QYrlvU4YKtGWeqATxTqEWndO2tYSozR1X5siEbE7F9IA5MIiIiIiIimhC9ciYVcWDC2EStiCJq1pmEfdEJ9qSoLmBFajtw+RykVO2MCYCf3Ta9CHVs0OZCCF6pzcxIse5Ns4zJMAdRKxLwFZ9tM1gEa8PNM9mQD/nP3gOnSDpXbONZqP+u2KtGMCQA3PZEBEPLbeXs2ZBo43Qj/tL6zxzrwExJyJgkmqAUh7S3beHYDfBeHTybNFazYEKPjPBzubWC6bDPRDIggaC1xIoEmpLwEutCs9ed1k1uk0qR/tdANXWGEPu5BxtJIvU5XuVCixIwLVKOwRoZty6xFPZZ2KB97lSOedOe8XAMp2iQ9jdPp7nrk2QLS+aLAk2PIsGUsKZFuxe9ogGpeJNpKrEV/dAvYFkduyL7P9fcsufjcPNKAam94a0kB6lq0r0s17UB2UrXIbUy9nNL56BJSuIHg3qKarx1RAyEyINFREREREREbDOIjAlDUnXNGawqZZqYiQqbUqc/4QiiIXMyKIIgAgPpQJrcfQcd2Ycu1BzdNUmQB5qS3hTPlACAaamShw3gtSamVYQn55mwSYWzAutIEvJMifMAYds3aqb6wSUa5RgSDn/Ns8s08ancmzQmoecCI8u186IJw84b42eToc2f2QSlyGsLeG3kNL9fm9iVB+J4u8utVQ1T4mfnFe+bIImgSQFldQR8bW4SrOD6jvOOcQyMXWeAFkGz2PNK9wCdo/KcKuyG2FZxNCL0n9U23TZxP5QnIUrXYdpAzqHn+cRd7qCeelGBq5CL46PIsijMgGl34xSHk5e+0Hwq/k2QfZqrDFMiBJ+L7/6zc11nLzBmU8SNYWYkp6q7cAjZt3Mz9o+WRhH63rkUuxg//ljneWPbwS75qTLusx6A+ZloRK+cyUUcmERERERERDQhakwmFXFgwjAAWuV8LhNh6GocJbsJmCpt8LNWMRPyoUP7dnB3rkFfgHG8KJXrUKpyn8hOf81QgmzYxt3olFkgGXskt9oSl5hPJOgzqWBM2gRjNR9Os9A23uOGZ5CJnPryJdrzZ2zz9loT1ngoHdRT4zlThzBmA0dy7WWJiLlAlbKG2ZRgxpvYXCvGaOSsLeGYJXVxSFy3sR9yZleERsQ1VjY8YEVkVNdAYxLO4JVgFVz/FXqSPulcRL3lOCIu71Bm6w0YkornjUh+V6uRUeIzqm2tbZuUW7GOI5AuyNxMDKc/yWroHK5HnINIefFJT3vGj2+CbKNL22X7j1GiD1SZOgoYNhNU7c5fA6nfqIv42g919Xny1vZ/IrctI40M1LcdgGdxWkEck1TnFU1XTsq1d4sjDkwmFVFjEhEREREREbHNIDImERERERERTYiMyaQiDkwsFJFPkMGKPKX6dya5faLC0jtquuackrYeq3+HAdcmAGGANVIKSK1LazsprfOhBPmQTczX8WJXuc6GgNyGH3fBuGTwtDa5XBqmRTBMe7P4tWV88jphgnHfnVWrTE1re3zSyisulT5w1HjujL/NpcRl1vTEbsldGyAt76XO5OPywtgyGTTQAnrdFCaz9zkLTDmJeKZM33MwMA6HXgpxbtfymirmlf7iV2cKcYHKFNhDMwz73hjavl+gM/LbtTDFhKLXOm7XXRoH3ArMRIAw/SmgrzCWi+ReiE2iLxbfSWSxK/c7913DJQtyJiEWtmrug7bPDWUu/1LJDEPlOp1LcU/7Z8EvBpvQcg2vWGfRal6qG/AuxS3ORyNMiU3mlfEgFLaKnI/I8gSZOE0u+mk/05Ez5SjjRK+cR2fSzDhAdBeeZERTTkRERERERMQ2g8iYWJDIiFs7XAtHu6U06jyDGnxIvSWS/40rbPw42ZQwaSF1EpiODaLWsYxJamdJHV1hSrIgmFo+7MWvblbqQsvDpgjgk8MLbHmWJ/6GYkAFcjNNL3C1rIg9R5rkbsaog2RmTYHTJHJTnh0y0qQaoI3PlWlyXSe3wtZut7gByiTA64B8XQtkw7yH4depRSCehfP1dmuYkiaE4lHJmISCUsdoWDFj5lmJkDGpRcCUyFurxPlKolpAuMSWqimxYWHANNJeSO1IjJ4v48SrQWJB5wrdESJtIbwGCsakMkF3yl3x3YapT1rWFTjx/VApQtsWTju5y/Lrgurl2qccCLugJs+QORaLT2xgHFPCGYPtPtEPm7IDM9w7EPw+yMSWIUKXeAki5d6PnlHoKe3aweyKUuQT+3HmbvtOtm1nS3VeybRtSE9aSProLjy5iAOTiIiIiIiIJkSNyaQiDkwkgkBlqHMZbRqgbwJzUosyEVDdp4J9fppTrHOxvZohrv95G2a+ZJPxuVDzw6ljSjjMvNORpEDetgzJsF2P2KZ17HrIz25dOnmpB5DnrrudJIUk5eNUQkh5xsph3wNWJNE+iNrmMiUhY5Ib7UPKG3bf9KyEyTncvO1MPEvuFjdAbVAVrQRDZcLllMG3ISG/Zndl7gt8fiMZD2ZafJFwAur0GyJUezLKx3Mhe7yucanNg+NF2PvwPHKfk0nx+VnzIWKQubL8VSZv5A9e4uGSQiIo79ZK3kNbiPtmSk7f41g75+5r26GN1zClxYVzugOi8mOTLIGTDynjGD5m0zjAmhLn9y7I/gZIV3e5rkPYz2X/1aF+RqCZGelfVr4nBIWQ2EsUOffgdlJ0lDYHPRSJAhmTqi2J2CqIA5OIiIiIiIgmGGnn3Iw6IgZCHJhYFF459rOYQlaCrU2Qx4u0NzaGrQ9BY+wX9Smi5vaOpRLXAHTZ8yabUughshGNvGPDzA97pqRYK/QsQ2KYIeHgaeyB0xbp45Nq20gLpqRFoKSusdYubTUXMkGf05gEoeVZTwKMj9gybtZXZUpCBsWQcjPdzLIgLqS8Ep4264p9yUYbIpyDUnWVSxUfTg5Lv42B/gRCnuDKMSvCHkBdhWSDLd4rH8/JEwHPGITeNDoDUta/WBZEelU51iLQb0gvmyCeoEeoM4EvmwtWo9E7ItjHQftA/pqcfiTwvCkSQ9rymvVOtpFDuUuelzBzEbBwtSyF7CtBwjnnKSaC8BlbGTNtMrGfYwS5v9elRBiAOQmD/9W1yTVf9HEXNK1GqxKGuzfineCQ88Yo5EohYfmLCzFPjtFMw7ULSe/vnbYd3SiavCR+0ZQzqYheORERERERERHbDCJjUgepFQmZEgTfa2OOULVcA0K1dpPHTqM6vO9UtKYdTaP3hL1rUhgbpp+T8bn4JG3lPG/Y44bjkuRtlELPA+K7iAvBCflcaG4x86eWceng0TGexRJgpoT1JFrEZehnYy+H8YYrD/hZX7l89TieFYb7jJgds7bAhHFIFLkQ5onVESQbiu8pp37vKq9HCO5NaXIcRqs33nMGwosGsNoUFMxHmFiPGQSZRC9M/qe7dt0D0vV8fLGzZxPVUQf+fQkeV53zRIUdEWxg6HEjk+qFbI6vQJwn0B3JBH8yMV+xFrqS4MQ8UTe5gu6UGxemNABEP+H7lnCsEq+xcOUcu8Frz9o6rUmQbqBoWsDiUrUvt6zGhb3DdM1vgtSBhOyJ15rYd4OSvkytZBGZKcly/8BzFNfqNCaurba/g/rqV1pCa9KkcdnymADGZMwAVBGMODCJiIiIiIhoQjTlTCriwKQJRD7Gg4syOs5Re1Nn7FNXHSNSy5KEXkCDdHx5zuCaiPUkQ1ZPMpKCmDFhVsQyJr0R5T1sHAti1wkqSfv82s9O3WdOJy9moEroTlRifKwREZ8k9Ljh2aFkS8J07JL5CG30ctYZetpIW3uoMaGgDBkFcjNcVVoBCsoyJXqjnTGylwu/jUZqSfjZCLt+DXsiG6IyBdVj9oW32bVgGZi9cocrUUcY1VVoTfi5s6dWFsSjAVwAVMe0+B1lxsZ1R1Ms2iar5POzd1cutS8hMchr0e/C6yhdp+ublg1oib4W1OnammmXUNExJPYBsAdO6RyVZHiq+N/mCsi+6PtxnhedwJjyQ5ZysTCZn/xY0VSJmCF1rAnD6U74e02ZMI4Io8g9Wd5nmFUEkEMDSc2BAiFjw+3p2dC9qcpdzJIea1ZIu/1bHEbQeZtVR8QgiBqTiIiIiIiIiG0GkTGJiIiIiIhoAhn4kLubUUfEQIgDkzHgQrGHJh2Jfv1tLD4qNL2wSUWYW/oKXQe0V4ZCWiXMP2y6YXON4YBpQ5yMT/uQ8tYl2FHr7aqwVTLModg171C5rKZyKG+gnJRP+IWS8UJBFgXqxDgTTr/Q8sXnvLTNDBC2nUjVuj3aS3N9oWoC8uegULXpKocP1MXmqkAwGYZqBwBigakWZp2wf8lEez3+XKx9oDVUXXlloDFpWgGqIfETiOSK5X06E2LVIDCbg0KlbUU5QtKlyu1qCh3hEuXJ29hH/03amxr9RlVqKwwqgmAfmI5KZpVibc0kLDoWvw2lhJJgU4eqzaXohNJGIbNiaW8KtM86qbkmYS4kaybIsuIFG9VlEWwRULAo3RRIsJ+7cPGZy1SPc2aewKzVyxIfSM6KXyn47VKKnOvwkA2wNpIWNsBha4ss2lx+OFok9tviiBqTSUU05URERERERERsM4iMSRPECNfNXxxzIsr1mbnC1OzbkqhxF64k3xOuhpRaZmTYrtvWFZgDp41oJzqU4eaBssC1MgNPfEC1kCmRCdTYXViF7sLuGjw7krbLIebrZn3lFO/BLeHTl1w7w+P8d54FO9dgDi2faxieqXKzQwZDuis7XbJ097TrgHFidkF3RbcJXFyL++7ZEz5f0TjPAAwSpNK1Q14+MyWhsFRMVt2zZMGlELg6V16v+SxWgrnRPSvQ7AItew9a6wiUkXNBz4P+Vtv+gKmT4l2XmE/cY/7MjE1qA81hvb9vzAJlw+Sul6+VGQp2AXZ90fbfTitDYveF/SfPdRE8VLAHJi+zciDl2H4Xip5D4hs0CO+p5LIswaxiS6RgCPu7UtRXfDqIi64W/Z27xnCruMm50WhTAmyEc+NnhpNZllaSYyQtyvO6HVBtmUkcO9ISLAlNFmMSxa+TijgwiYiIiIiIaEI05Uwq4sBkUNhOJebkxQc5i+GOJ33uXELATTzt5iQElD6GHDTN6kko0TAhQzLM34WOpFV213QzxdXrKwAAJf1JREFUWI1qEjQ7Xco7gGGmhN08XaI+tkULl+BgtqcTA5UQEjtDSdu50zXU3Y3Q1ZEvfVCEAdKMUaWke7wNKAJtNQWaKtooAqS5CriM9mwChz23uh1lA5clo0CLw70HrEregZ+WBvqTgSAnfk2elgFjkghWxCVfDJgyoIZpCaQ2SoS0TzcYtGx/TEeBPCeY1LJBNlgfuyJnU221iXd9DjUypc+B1kXl4rVslduUrrPXuMEHCeR25NaVWBlV0RaFIeVbaY62TUbHaQq6NnMgEUBGl9xq68LOc78pMSV8bWFAOqHNSmy4/Ha7uDlTOsUDa6eZayP3aR8g0F9PHlxTGERQKTRqVLiu1F7/tHbhA9/WOVqmYEyG2xkSlTsWhxP2DaUZprZsey1TwmwKuwgbqCLIG+qDxUVsX4gDk4iIiIiIiCYQJoAxmZCW/EEgDkwYxng9RlOWMGZOrM08TPNeQhNL0qA/CXUhY4LKs3J3vNYVjxvWkZi29h42HFp+iO36zK6I2TEnPhNakZAp4dl93pGJ3XjKXV5T4hkTFXjl6MRAJ+Qn9KrqLVCHOuakXxmg+jsjg0I5TUlTMrXQ84LXWqSvz8uzUxgAWVnckXNIdBtwTeciBLxdc1AzKPE5aI9MlOe8Y9zF2u/ympnFEcnt+gVWkzqYxGo0HHsmzl85LpA9KUNIRlljQkjsQ0g25NDK19mbYteCKQGK9rl+F/x6KSPaEnSCUqA3ZqEC/Y5p++NqpQtBYjyy/SWzDM7aDR0MtYubk7pQ9J6VkCHpS9UKxlAH7KHhhHV5Tf/TnlFkbUvHUm3MlLRKSe5se5v0I4HnkUTIlMh3kkPQr+8WFNeGXsuekQqNCYAdhjagp3LHjgxxRwIwxVJyqW2v17hU32ZOHZGqPHrlbKeIXjkRERERERER2wwiY7K5aPK8qWM8Qh1KA5QcpbtpYnXkzvFIHKvhGI/E6UdMxyffK8p4/QgzJflQcColku7VeOC4tPGcDM3a402HfPkapgTg2V55BsreDjop1Psq2B8iDOnNyGtmgqEnQt0+qilbd5xLKd/nGRaz4+KzmwHb6857EPcwEGLwt0yEqQ9ZnRYqYdZ50ui0E2N45YSxRlw9JBgP9hDiSW2NB4/TegiWwYXA5+R3afk6dAYkXRt/ZmOOxIagT0ZzJFAgXcyuTVKuh++HrNNdYqhrke3ld6Il2hDEUZH3zyWiHOK+bJmPlKBa5ZtqMmYXigYpRa4NnXbZq8RQWZukFFXYEdnPffyc6rWF/S9JDIY71pslKXcOp5+CqnjacN2J9voTZkXqElqGZbjuRBvnacNxU1qsI0kztMkAPWB6axSZzhwrwixJR2eO+XAMiTs9b69S04Z0LaOyRWCkYHBz6ogYBHFgEhERERER0YRoyplUxIFJREREREREE+LAZFIRByYMpbzYVLr49gkbX8JmugQ71GULdu6OQuBqACTKuYmatnVJ5MBbbMppa2Q2G7AXttpqUoWMXSMDV2DnmjoER6lqr1NzZVgYa1i8ycdrgFqB6SZcawNtXRxZuFcRlcJvHo/T9FimGLev4bh+UIoqjanS7Z4258yzbKYyLQWyWWq5vzGjb0QQtdB0IoWeoQmCy7iI/tIlOLAE2uYV24QrLW8PrUvSPMRrFpKqoG7Sop8EmmfdtVT/eoIetQHKMh8YjJJCjM1aTQ5+xt1eCqwd2y/aXVrXXDfpcgA72X73TrSAbKRswoFdq8TT8Cx6ZR92EgH3ujakfGbfSZ3647TMmK3Jp4cQHdGIQH7FufqLZblvpYmpvDPclzPxo8TbWgmnafDHuEBwvA4yaMuy1f+vWpiHivW60eLHYX23hQ5nBTYaPfhAabzOodCzD8G5XrtOjtL9AOrNTBHbF+LAJCIiIiIiogkx8uukIg5MGE1MiISbltqZBFHVrbfJzZf35aKTDsC0kAyUliiYlkY+VDw+FrEyU8LIOton3+t4F2CgmJ1nI7Zu1pVx01w4efggYFy3c7Ek72ZqXYJZ/ApdZUrgvnuBa5LyzCmY7WFsloRI9Q2x3W8b1z1mWRLb6upmYWKfymXSQcWJBvlaE428bQWVWdk9m1mRfAgICKqSa26YWM+1MBDFyubX6myDfSSuIUy+51zBE8HQZDXr4KYwU9Jea2fCa3Mnfs07Grl1Z98wI8W6jmDxnKC6fH5K/TmUTEwIlF33uYxgetwknMvzbFykT+B+y4yfEiyHc6W1DImyzJfuWuarp8BR6/KOfTdHbBK94QwQwlQF4XbsXirAWMbF9JgiEg8peKeYaVSKHNPBMEKYGiIUr8pt7pYGQllZe4/Kwdco80kr84DhSbSva23WRk/lSO1DyewDS5GXPrsbJNqVCrdnDryYQ8HUXN+WAJEBbWZ24M09/g8J0V04IiIiIiIiYptBZEwsSKlyKHlgcCZjPMO7cbgLk9beBXjIulEOp8gTYxkT1o/YWVarPFsxiXAFtkG5pK3euQILbQjvK7YLt1/HhpArS5VtPE0VpJHQlADe5p6kpjKbc/bspptiMUjAtVLdddtqmBLeHrprOlt/jUtqTetcwdReb9sGvkoTgw1UTNHdOdjttM5NO2AnlEEpINpYqG1in1tH2h/AzEUlYBlVQ7orS+8kPeHmzAEIWfdk+4FpK8cmdHdIkFu2aMMMjQ3D5PtekO7AuSTnqARx43bkUn8SuD2rXLBAfP3BfaQWgVhT0g5mt0Z5poT7gmuH8m3jRH+WRcmcK3KOpOWrU4oqfSrrJjBd26hu+eFSIrQlgilhVFhHvieWSZH784ANqYNz4Rfbchd0UJe+c/A4Cc3JA9McKRGQAUNJEZKe2Q8OLZ9RIlz87e9cXr7+jnAz5nD1OakqtbelQLT5ppgofh0YcWASERERERHRBJoAjUkcmAyMODCxoE4CSphOsBu1+BzCBRwbp0LclielfOj4xNps3SxRue1ONzJctK03JUWvbZC3FXpTmCkJjhPMB7Mh7PHhbPbt/uHmWTNCKdx01LWN9REajinxodgFY6KD1PBpWWtRZ/sOwQHWtBbpAhoCnjHG0p9UwN4ZLvy8rqSfr60ndNjia23l7jo7QYhybQhmqNg2yucdLW4uz/Jb6wHDSfw40Jj03ODTc5NC5qTm96+iNakrr4EsSNAXev7I40NWQ2dFIjzAe9X4UPDWM2NYgWxCye5UILefR3cAem1xXse4FGvWL6UbVFUrIvo7e4glG6zGQgRTCz3Lcr63fI0anhnkyq3mA5mq3jvHJvmG8DnC+2WMKj0XIoW8p0uFTKZB9nyq9oGF+g1+/wRzgvBdsOev4c7kvrHek9yoiu6EmZNS8DghhQOAVBuktvyUtItMZy4UfU9QfkkfBlR68CSOxeFtgAmjDUZsF4gDk4iIiIiIiCYYg/oESuNAFL8OjDgwsciHUqiE42f72YOydkXFxuI674Y+MykQimE9ipgiEiVPnoAp4TDylCg/K7U6ko2v1+hmCibxmhIZh0GenzRKifUAoSdJ/Cw0DDfvNQzeS8HZ46VngCofxzdCaULStvbgwPPGhdOWl+9SnJe3ufx/ItS3UtVZ4nhQmhmyHT6MGUGCKanEkVBVysLFOrez+lbuQpIPW22Ji/OgyF8D31ueZVp9hu760O6J0J0AxfN0cg8OpxE8d5XXMCNCzuCuKNBowAi2zGk6WFdhi2hfxnSYWbMz2VHt+mButU2OORGaE5kYkGTsFghNSOBpw+fKc8+YIGBVpOaGz8dlda/K/vA7weHn+TpKhazWQ3UViOP18DsA/i7ayM85uEcynok7Bd/TrHgpKVNQnOBRB+fSAPUs07S+ZbcV+4Y7pvJehVYD+T0keYlUSS8CVJMJNjIqwXsLeEZ0qNUrQtJ3gemtDch05sLIj7rYJcYxPZ4hsfWIylmHkrMOhRRGJ8sFN5pyJhXRKyciIiIiIiJim0FkTCx601KUZPMAkJNjTJgy0DICK1DEMUnqZxOkVUX34aKyptVjfPI9nl372Vg+bD1wRhR6NvV7mGAvjNxqUojEfnbd9rO8UKNAwSwNCSrxSHxcBz/69zoSO8tJc+9BwFqTAaQenjkJvIugoFQ5jbysz3nO1ER8JVT38Q7HlHAEz1qWJPDGMcozstwWnvU7rwV/PM9EZXv5M89K86zsOZWNCJkTayT4lKmf+bN+Q+qG/PXb4+qYkz4TN0VwM/aQHXAROFPADNtnOrVoXGIj+FKukGX2Zqy38TzWFfc4Xec9V7idlPq+CuX7ZlHO3suAlclHDDh7XZhgEIpjiQTXa9fuHQxYGseUKHHfmF1hpkMroGMjprqAP3Y9ZKP6InPvkIs1EnjSMIyIdeOYxhQglJlZlyhSk//sWBF/raG2pAl1upOxNCZKkX+n+H2T+4PrnNIpOucbhtajZRJgHZAqA6WMi9HTsR41sh0+KV851olWBq0gYmyPEmSTZB4hY0CbacqJcUwGRxyYRERERERENCGaciYVcWBi0Z2WCMO63UioRInUWblzFXlJeHZpZ3kJe9VU9VKe1VClvDVAzYxO5PdQIhprnhfeGmGMh1BrQlqwJy53jWhMyJS0yrNTlVA58iW8t430fHFMScvGJ5A6imAiJlkRlxcEzCr4c2VGI0ERx8UY5WZS3tvG1+lncp4l6RejRHremIApQY3+xK/FbJG1HGyH19UfnMyyMaMqLbUtN8p7M3CsBhsdtGvLbHgjQC8Xu1qv2lP0/NoxJqyRGSq3VT7jUCKjjO9TFDJsLc9auP7i1pYlaRGSTlFB2+pomPnRihzb1R22sUpaRcfd0Cs6ZbKxzOgxC5ANE0yLfN+zzA2vkw0i5wvHRIEqfQc80+LKBu9G6bqbvJkC5qPoVGX2TLGOyvZ7k2lXPmThckoARcihgRaQZwmI2VjJ1HEbKtImn1fI9TvRp41lZjWV782gTAo/w37aFCLl+jTHRpF6lJbN28OMyVBadNi2zpFyW1TBOmj7XcpDQq8hYzsJ60oSsd8fryYvyrsR/ww2FXFgMjAmRWPy29/+Fh/5yEfwhje8ASMjI3jb296Ghx9+2O1//vnnceqpp2L27NkYGRnBe97zHqxevbpUx+OPP4758+djl112wZIlS0r75s6dC6UU7r///tL2c845B4cddtgWu66IiIiIiIiIicUWH5i8+OKLmD9/PlqtFn784x/jl7/8Jb761a/ida97HQCAiHD88cfjqaeews0334yVK1dizpw5OOKII7Bu3TpXz1lnnYWTTz4ZN998M2699Vbcc889pfMMDQ3hL//yL7f05URERERE/KGBCCCzmUtkTAbFFjflXHrppdh1112xfPlyt23u3Lnu8+rVq3H//ffjkUcewT777AMAuOKKK7DTTjvhu9/9Lj760Y8CAF566SXsv//+eOtb34rZs2fj5ZdfLp3nYx/7GK688kr86Ec/wnvf+95xt3N0ukKeFuO0xCYeI62grNjVsXgseBQmmrr07wCQt7zArc6k4+jlwO1TUvEumJRw+83zokwodm0MKR+YbYpK+fgqXW/3oFKYXVtbuRf0sZmrxpXXiQlZPDlIwDNbh6qhoaXZpknY6oJBBWYaGTitkqhPClwbfkOcecoFlLOmDBcq3NPdplc2M8l7w2nrud/R1OJ7NtX4sOH22bLbLQC01pVO60wzzotWBCqrJKXLlFPWhuJPapHoAzak+HDZbDPU7qFtk9G17Lqb+Z+RXpBMLh+xgdVmFefo9rRwFyZoa8vJ35CBRKI2Y4OPJWs5RLvof9yXuJ8KU45/zbyAHCjev/D99GH2WcwK0eVr/G4DN++0HQT3UvKEXLevhkjD2Bcx7yYwPX4mHFQNpZQPRdP4nMqfn/c586BGyh3bBSEb3z9BF7I+eE9L71vwnrGwvdPOMNzqlbbt0C5834eSHlJnvtVC3Fof9I2RB+cqvlshrDBXZSXb9JYDGXLPYpPriAOTgbHFGZNbbrkFBx54IE444QTstNNO2H///XHNNde4/aOjtgMPDbltSZKg3W7j7rvvdtuWLFmCI488EiMjI9Ba46ijjiqdZ+7cuTjjjDNw/vnnw5iofo6IiIiIiHgtYoszJk899RSuvPJKnHvuubjgggvwwAMP4BOf+AQ6nQ4WLVqEPffcE3PmzMH555+Pq666ClOmTMFll12G5557DmvWrHH1vPe978Xvfvc7vPLKK5gxY0btuT73uc9h+fLl+M53voOTTz55XO3s7uDdNV0irkwEmLKTIw5xXRv22w7eM1uPnBCEQjtFNQxH4MYIeKaFJ6W9EaBnE7l5NoQFi3x8edZVNDxUtYn2ceKyGldg1w4Oqc6zxVbuPTFrZhKhILWpjDtHIJgt1R+4KJIIg11xYyRVSZBGAStSCA15elg+HkZVRM++kVQVJrp95euQ53XXJoo7QbVzJfVi2B67ANvAenjRut2u7eMWDtGfOr6NTihqBbYqNWI2b6+bhaYt41iAlhV0cvLBHUfWAwCmtUcxlJQTp3WN77Ab86Ixv+m+zp6jVBSqnXtX2oQKgTOA1kgPuXCnpJZ1j+c7Y92PlUE1PD5fhybh5szX79/f8H2pvJMGPgR9ypHZ7L6S+NRvk9CJqbizOxf0vOiTJFyNHYsqXztJ8aD83aV1CJjKIr8cn7e/6DVkKMIQ800wgjFxx9l9ea4xMlK4B88eeQUAMK21EQCQmcT9k+maFJlohxO21vw2lBL18XlcgLXqti0OMkDf/CTjqWN8uOKKK/C3f/u3WLNmDfbZZx8sW7YM/+k//afNa8drAFt8YGKMwYEHHoiLL74YALD//vvj0UcfxZVXXolFixah1WrhxhtvxOmnn44dd9wRSZLgiCOOwNFHH12pq9Pp9B2UAMCMGTPw6U9/Gp///Odx4oknjqudHa2QWGW7ZOrdP0fe1tS37A8Wp9wZeGASZjkVZbmKtm1bR8RFqXjlhJYJ+c7WBRKpbGoYmHBkRs6a67Txfl+5pmDQMUCZIEwD2nZLx2XHkC30x/JnuS+su/578HT9SEg2vIzSj2j5fnH704b7J6vjH2j3z1lcrzePFR/4+aeJ71/8z5e/c5TYRFya7wt15KgbSbktHGmzZddt28na9mQtStAKXCFIDExyW65jr8UEa346QNGXOuKay3fWDsQUe2P5f/ihtSQ028jymt9pqr4vFUuegojIXH62SrSbSyTBczYN/Y77ZKf0jAM7p6xchRvInS80XqQgtO2o2jmKoYrwpyscaNTBuMGALjyKILzoXB8h1z9SO0pOnItg4j7z2h3fMDBhqDEGHmbS4phMvinnf/7P/4lzzjkHV1xxBebPn4+rrroKRx99NH75y19it91226y2bOvY4gOTWbNmYe+99y5t22uvvXDjjTe67wcccABWrVqFl19+Gd1uFzNmzMDBBx+MAw88cNznO/fcc3HFFVfgiiuuGNdx5+8/ByMjI+M+32Tjwr3mbu0mTDrOV/tWf423JwRv4UWve1O1zNb6HeLf0nXBelBMGazY59t71e8Ytusdx3nebRwX7bjHxFYYhOnfImh6B18N1jU44vnxa//Gwvr16/EtfGvC690WcNlll+H00093Ostly5bhn//5n3HllVdi6dKlW7l1WxZbfGAyf/58PP7446VtTzzxBObMmVMpO336dACFIPahhx7CRRddNO7zTZ06FRdeeCEWL16MY489duDjPv/Yv6Gli19BjqiphRhOiyylQJkND6n1kvCtYcDvZmp94pBAeUa3nSr81e67Yemvfo1RsqLWQCDnZsn8VFPhex+2Q9JBDUI5F9GxVc59owD0y+C7qfMKHZhAOtD4dLIXvpI/ho0oR34FiZgkNRRRJUZJTQRXRzGFuW/kJEzSZ0Bxz8P4JS6eC5u7jDN5sRiQ40Sk2rgJcm7b2LVpbpNeC+cPzcPF61ZjA8fjWFfsa79kWZX1vp/07D99GTEVYJOG/WKjlWqOM9HyF8fZbQ2fv51h2pRC89VJCyPKiBUx7tAqXoqRtItWkNGVqXVDGutteuJfv/x6AMD6UbYv2raKwCpaF4zJZ1t74m+yf8NoDVWedW1elC7bSbUI4GJn3qNiBs6PhK0duX/uzsQZvqe2bNJVMBxhdro1fVnTltLClBOaHMV7EEYh5ngmxmjAFH36c9P/GF968Wmf50W00Zlc+T2z69ZQ5p6Ji9/C2l9FSFxOnbEZhPB9qYsJxMhFGRd/JwiOMzLUw85TCxPOrKFiZDKcFv0lMxqJSTH/+ffizp1uQ64yb8pxjCEhtX2KxbFhGVMJOlOgp7q12ycaGY1ukimmVIeNefvKK6+Utnc6HXQ6ndK2breLhx9+GH/1V39V2r5w4ULce++9m9WO1wRoC+OBBx6gNE3py1/+Mq1evZq+853v0MjICF1//fWuzPe+9z1asWIFPfnkk3TTTTfRnDlz6P3vf//A55gzZw597Wtfc9+73S7tscceNDQ0RAsWLGg8duPGjQRr3Y1LXOISl7i8tpaZM2fShg0bxvuvaSBs2LCBZs6cOWFtnTp1amXbF77whcp5f/vb3xIAuueee0rbv/zlL9O8efO2yLVuS9jijMlBBx2EH/zgBzj//POxZMkS7L777li2bBk+/OEPuzJr1qzBueeei+effx6zZs3CokWLcOGFF27yOVutFi666CJ86EMfGrNsp9PBxo0bnXdQRERERMRrB+12u+TVOZEYGhrC008/jW53YpgZInL6J0bIlkiEZeuO3x6hiKJzdURERERExLaCbreLkZER/NM//RPe9773ue2f/OQnsWrVKtx1111bsXVbHpMSkj4iIiIiIiJiMLTbbRxwwAG4/fbbS9tvv/12HHrooVupVZOHmMQvIiIiIiJiG8O5556Lk08+GQceeCDe+c534uqrr8YzzzyDM844Y2s3bYsjDkwiIiIiIiK2MZx44on4/e9/jyVLlmDNmjV4y1vegh/96Ee1Hq3bG6LGJCIiIiIiImKbQdSYRERERERERGwziAOTiIiIiIiIiG0GcWAyCVi6dCkOOuggTJs2DTvttBOOP/74SjTc73//+zjqqKPwxje+EUoprFq1qlLP448/jvnz52OXXXbBkiVL3PaTTjqpklvoxz/+MZRSlXgwF110EWbPnj1h1/bTn/4Uxx57LGbPng2lFG666abS/ueffx6nnnoqZs+ejZGREbznPe/B6tWrG+u87rrroJSqLBs3bnRl1q5di5NOOgmzZs3CSSedhHXriljp/+N//A9MmzYNWZaVyrZarUryq5/97GdQSuGJJ57YzLtQYKx7sXbtWpx99tnYZZddMDw8jL322gtXXnllqcxr8RkDwGOPPYbjjjsO06dPx7Rp03DIIYfgmWee6Vvn9vqMTz311Mo1HXLIIaUyr8VnvHjxYuy5556YMmUKXv/61+OII47Av/zLvzTW+Vp9xhFbH3FgMgm46667cNZZZ+H+++/H7bffjizLsHDhQvcSAsC6deswf/58XHLJJX3rOeuss3DyySfj5ptvxq233op77rkHAHD44Yfj7rvvLr3Ed955J3bddVesWLGiVMedd96Jww8/fMKubd26ddhvv/3wjW98o7KPiHD88cfjqaeews0334yVK1dizpw5OOKII0rXXocddtgBa9asKS0yiNKyZcswdepU3HbbbRgZGcGyZcsAFPdi7dq1eOihh1zZn/3sZ5g5cyYefPBBrF+/3m2/8847MXv2bMybN28z70KBpnsBAJ/61Kfwk5/8BNdffz0ee+wxfOpTn8LHP/5x3Hzzza7Ma+0ZA8CTTz6Jd73rXdhzzz1x55134uc//zkuvPDCMYNebY/PGADe8573lK7pRz/6UWn/a/EZz5s3D9/4xjfwi1/8AnfffTfmzp2LhQsX4ne/+11jva/FZxyxDWArRp39g8ULL7xAAOiuu+6q7Hv66acJAK1cubKy74ADDqD777+fut0uHXfccfTDH/6QiIgef/xxAkD33XefK/uOd7yD/v7v/57a7TatW7eOiIhGR0dpeHiYrrnmmi1yXQDoBz/4gfvO7XrkkUfctizLaMcdd2xsw/Lly2n69OmN5zrvvPPo0ksvJSKiSy+9lD7zmc+4fbNnz6alS5e675/97GfprLPOor333ptuv/12t/3d7343ffjDHx708saF8F4QEe2zzz60ZMmS0ra3v/3t9LnPfc59f609YyKiE088kT7ykY+Mq57t9Rmfcsop9Kd/+qeNx70Wn3GIl19+mQDQHXfc0bfM9vCMI7YOImOyFfDyyy8DAHbccXwpU5csWYIjjzwSIyMj0FrjqKOOAlDMZmbPnu1mVa+++ir+9V//FSeccAL22GMPNyO7//77sWHDhgmdaTWBw/zLGVKSJGi327j77rsbj127di3mzJmDXXbZBccccwxWrlxZ2n/22WfjqquuQqvVwvLly/HJT37S7TvssMNKM8wVK1bgsMMOw4IFC9z2breL++67b9LuBQC8613vwi233ILf/va3ICKsWLECTzzxhHuOwGvvGRtj8MMf/hDz5s3DUUcdhZ122gkHH3xwrbknxPb4jIFiBr/TTjth3rx5+O///b/jhRdeKO1/rT3jEN1uF1dffTWmT5+O/fbbr7Hs9vqMI7YwtvbI6A8Nxhg69thj6V3velft/ibGhKhIOvjCCy9Utn/oQx+ihQsXEhHRD3/4Q9p7772JiOiMM86gCy64gIiIvvjFL9Kuu+46AVdRDwQzrW63S3PmzKETTjiB/uM//oNGR0dp6dKlBMC1tQ733Xcfffvb36ZVq1bRT3/6U/pv/+2/0fDwMD3xxBOlcnme05o1a8gYU9p+9dVX05QpU6jX69Err7xCaZrS888/TzfccAMdeuihRER01113EQB68sknJ+4GCIT3gqiY6S5atIgAUJqm1G636Vvf+lbl2NfSM16zZg0BoJGREbrsssto5cqVtHTpUlJK0Z133tm3nu31Gd9www30v/7X/6Jf/OIXdMstt9B+++1H++yzD23cuLFU7rX0jBm33norTZkyhZRSNHv2bHrggQca69kennHE1kEcmEwyzjzzTJozZw49++yztfvHGpj0wzXXXENTpkyhbrdLn/nMZ+jMM88kIqLvfve77iU+/PDD6ZRTTtmc5jei7gftoYceov32248AUJIkdNRRR9HRRx9NRx999MD15nlO++23H3384x8fqPzq1asJAN17772lH/c1a9ZQq9WitWvX0he/+EXabbfdBm7DeFF3L/72b/+W5s2bR7fccgv9/Oc/p8svv5ymTp1aoqWbsC0+Y86C+sEPfrBU7thjj6WTTjpp4Hq3l2cc4v/9v/9HrVaLbrzxxoHq3BafMWPt2rW0evVquu++++i0006juXPn0vPPPz9wva/FZxyxdRBNOZOIj3/847jllluwYsUK7LLLLhNa9+GHH45169bhwQcfxIoVK7BgwQIAwIIFC/Dggw/iP/7jP7YK5XnAAQdg1apVeOmll7BmzRr85Cc/we9//3vsvvvuA9ehtcZBBx00pjcP401vehN22WUXrFixonQvZs6cid133x333HMPVqxYgXe/+92bdE2bgg0bNuCCCy7AZZddhmOPPRZvfetbcfbZZ+PEE0/EV77ylYHq2Baf8Rvf+EakaYq99967tH2vvfZq9MoJsT084zrMmjULc+bMGfi6tsVnzJgyZQre9KY34ZBDDsG1116LNE1x7bXXDnz89vqMIyYecWAyCSAinH322fj+97+P//2///e4/ikPij322AO77rorbrnlFqxatcq9xLNmzcLcuXPx1a9+FRs3btxqttjp06djxowZWL16NR566CH86Z/+6cDHEhFWrVqFWbNmDXzM4YcfjjvvvBN33nknDjvsMLd9wYIF+Od//mfcf//9k3over0eer0etC6/ckmSwBgzUB3b4jNut9s46KCDKu7vTzzxxLhCZ28Pz7gOv//97/Hss88OfF3b4jPuByJyOrJBy2+PzzhiC2Cr8jV/IPiLv/gLmj59Ot155520Zs0at6xfv96V+f3vf08rV66kH/7whwSAbrjhBlq5ciWtWbNm4PMsWrSIpk2bRnvuuWdp+0c/+lGaNm0a/fEf//GEXRPj1VdfpZUrV9LKlSsJgNMZ/PrXvyYiou9973u0YsUKevLJJ+mmm26iOXPm0Pvf//5SHSeffDL91V/9lfu+ePFi+slPfkJPPvkkrVy5kv7sz/6M0jSlf/mXfxm4Xf/wD/9Aw8PDlKYpPffcc2779ddfT9OmTSMA9Mwzz2zm1Zcx1r1YsGAB7bPPPrRixQp66qmnaPny5TQ0NERXXHHFwOfYFp/x97//fWq1WnT11VfT6tWr6fLLL6ckSehnP/uZq+MP4Rm/+uqrdN5559G9995LTz/9NK1YsYLe+c530h/90R/RK6+8MvA5trVnvHbtWjr//PPpvvvuo1/96lf08MMP0+mnn06dTqfkcbe9POOIrY84MJkEAKhdli9f7sosX768tswXvvCFgc/DdZxxxhml7d/+9rcJAJ1++ukTdEUeK1asqG0328C//vWv0y677EKtVot22203+tznPkejo6OlOhYsWFCymZ9zzjm02267UbvdphkzZtDChQvp3nvvHVe7WKsT/rg/++yzBID22GOPTbreJox1L9asWUOnnnoqzZ49m4aGhuhP/uRP6Ktf/WpF9NeEbfEZExFde+219KY3vYmGhoZov/32o5tuuqlUxx/CM16/fj0tXLiQZsyY4fr7KaecMu5/nNvaM96wYQO9733vo9mzZ1O73aZZs2bRcccdVxG/bi/POGLrIybxi4iIiIiIiNhmEDUmEREREREREdsM4sAkIiIiIiIiYptBHJhEREREREREbDOIA5OIiIiIiIiIbQZxYBIRERERERGxzSAOTCIiIiIiIiK2GcSBSURERERERMQ2gzgwiYiIiIiIiNhmEAcmEREREREREdsM4sAkIiIiIiIiYptBHJhEREREREREbDP4/2jmh4JPzsHsAAAAAElFTkSuQmCC", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -420,7 +13100,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:09.349943Z", + "iopub.status.busy": "2023-04-04T02:47:09.348913Z", + "iopub.status.idle": "2023-04-04T02:47:14.506219Z", + "shell.execute_reply": "2023-04-04T02:47:14.504239Z", + "shell.execute_reply.started": "2023-04-04T02:47:09.349832Z" + } + }, "outputs": [ { "name": "stdout", @@ -429,26 +13117,14 @@ "Cutting out the oceandataset.\n" ] }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", + "image/png": 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -475,7 +13151,15 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:14.511021Z", + "iopub.status.busy": "2023-04-04T02:47:14.510413Z", + "iopub.status.idle": "2023-04-04T02:47:14.538553Z", + "shell.execute_reply": "2023-04-04T02:47:14.536764Z", + "shell.execute_reply.started": "2023-04-04T02:47:14.510965Z" + } + }, "outputs": [ { "name": "stdout", @@ -483,10 +13167,10 @@ "text": [ "\n", "Original: 1.034784936 Gigabytes\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 55, 'Zl': 55, 'Zp1': 56, 'Zu': 55, 'time': 4, 'time_midp': 3}\n", + "{'time_midp': 3, 'Zl': 55, 'Y': 154, 'X': 207, 'Z': 55, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'Zp1': 56, 'Zu': 55}\n", "\n", "Cutout: 18.010824 Megabytes\n", - "{'X': 170, 'Xp1': 171, 'Y': 93, 'Yp1': 94, 'Z': 1, 'Zl': 1, 'Zp1': 2, 'Zu': 1, 'time': 2, 'time_midp': 1}\n" + "{'time_midp': 1, 'Zl': 1, 'Y': 93, 'X': 170, 'Z': 1, 'Xp1': 171, 'Yp1': 94, 'time': 2, 'Zp1': 2, 'Zu': 1}\n" ] } ], @@ -507,7 +13191,15 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:14.541424Z", + "iopub.status.busy": "2023-04-04T02:47:14.540805Z", + "iopub.status.idle": "2023-04-04T02:47:14.678714Z", + "shell.execute_reply": "2023-04-04T02:47:14.676065Z", + "shell.execute_reply.started": "2023-04-04T02:47:14.541371Z" + } + }, "outputs": [ { "name": "stdout", @@ -516,14 +13208,8 @@ "Cutting out the oceandataset.\n", "\n", "Original oceandataset:\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 55, 'Zl': 55, 'Zp1': 56, 'Zu': 55, 'time': 4, 'time_midp': 3}\n", + "{'time_midp': 3, 'Zl': 55, 'Y': 154, 'X': 207, 'Z': 55, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'Zp1': 56, 'Zu': 55}\n", "\n", - "X Axis (not periodic, boundary=None):\n", - " * center X --> outer\n", - " * outer Xp1 --> center\n", - "time Axis (not periodic, boundary=None):\n", - " * center time_midp --> outer\n", - " * outer time --> center\n", "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", " * outer Yp1 --> center\n", @@ -532,16 +13218,22 @@ " * left Zl --> center\n", " * outer Zp1 --> center\n", " * right Zu --> center\n", - "\n", - "New oceandataset:\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 1, 'Zl': 1, 'Zp1': 1, 'Zu': 1, 'time': 4, 'time_midp': 3}\n", - "\n", "X Axis (not periodic, boundary=None):\n", " * center X --> outer\n", " * outer Xp1 --> center\n", + "time Axis (not periodic, boundary=None):\n", + " * center time_midp --> outer\n", + " * outer time --> center\n", + "\n", + "New oceandataset:\n", + "{'time_midp': 3, 'Zl': 1, 'Y': 154, 'X': 207, 'Z': 1, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'Zp1': 1, 'Zu': 1}\n", + "\n", "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", " * outer Yp1 --> center\n", + "X Axis (not periodic, boundary=None):\n", + " * center X --> outer\n", + " * outer Xp1 --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", " * outer time --> center\n" @@ -591,7 +13283,15 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:14.686925Z", + "iopub.status.busy": "2023-04-04T02:47:14.686347Z", + "iopub.status.idle": "2023-04-04T02:47:14.773871Z", + "shell.execute_reply": "2023-04-04T02:47:14.771396Z", + "shell.execute_reply.started": "2023-04-04T02:47:14.686869Z" + } + }, "outputs": [ { "name": "stdout", @@ -599,11 +13299,11 @@ "text": [ "Computing kinetic energy using the following parameters: {'eps_nh': 0}.\n", "\n", - "Dimensions: (X: 207, Y: 154, Z: 1, time: 4)\n", + "Dimensions: (Y: 154, Z: 1, time: 4, X: 207)\n", "Coordinates:\n", - " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", - " * Z (Z) float64 -1.0\n", " * Y (Y) float64 68.99 69.01 69.03 69.04 ... 71.95 71.97 72.0 72.02\n", + " * Z (Z) float64 -1.0\n", + " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", " * X (X) float64 -22.02 -21.98 -21.93 -21.89 ... -13.05 -13.01 -12.96\n", "Data variables:\n", " KE (time, Z, Y, X) float64 dask.array\n", @@ -632,7 +13332,15 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:14.777258Z", + "iopub.status.busy": "2023-04-04T02:47:14.776673Z", + "iopub.status.idle": "2023-04-04T02:47:14.884015Z", + "shell.execute_reply": "2023-04-04T02:47:14.872333Z", + "shell.execute_reply.started": "2023-04-04T02:47:14.777204Z" + } + }, "outputs": [ { "name": "stdout", @@ -640,109 +13348,30 @@ "text": [ "Computing kinetic energy using the following parameters: {'eps_nh': 0}.\n", "\n", - "Dimensions: (X: 207, Xp1: 208, Y: 154, Yp1: 155, Z: 1, Zl: 1, Zp1: 1, Zu: 1, time: 4, time_midp: 3)\n", - "Coordinates:\n", + "Dimensions: (time_midp: 3, Zl: 1, Y: 154, X: 207, Z: 1, Xp1: 208, Yp1: 155,\n", + " time: 4, Zp1: 1, Zu: 1)\n", + "Coordinates: (12/18)\n", " * X (X) float64 -22.02 -21.98 -21.93 -21.89 ... -13.05 -13.01 -12.96\n", - " * Y (Y) float64 68.99 69.01 69.03 69.04 ... 71.95 71.97 72.0 72.02\n", - " * Z (Z) float64 -1.0\n", - " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", " XC (Y, X) float64 dask.array\n", " XG (Yp1, Xp1) float64 dask.array\n", " XU (Y, Xp1) float64 dask.array\n", " XV (Yp1, X) float64 dask.array\n", " * Xp1 (Xp1) float64 -22.04 -22.0 -21.96 ... -13.03 -12.98 -12.94\n", - " YC (Y, X) float64 dask.array\n", - " YG (Yp1, Xp1) float64 dask.array\n", - " YU (Y, Xp1) float64 dask.array\n", - " YV (Yp1, X) float64 dask.array\n", - " * Yp1 (Yp1) float64 68.98 69.0 69.02 69.03 ... 71.96 71.98 72.01 72.03\n", + " ... ...\n", + " * Z (Z) float64 -1.0\n", " * Zl (Zl) float64 0.0\n", " * Zp1 (Zp1) float64 0.0\n", " * Zu (Zu) float64 -2.0\n", + " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", " * time_midp (time_midp) datetime64[ns] 2007-09-01T03:00:00 ... 2007-09-01...\n", - "Data variables:\n", + "Data variables: (12/88)\n", " ADVr_SLT (time_midp, Zl, Y, X) float64 dask.array\n", " ADVr_TH (time_midp, Zl, Y, X) float64 dask.array\n", " ADVx_SLT (time_midp, Z, Y, Xp1) float64 dask.array\n", " ADVx_TH (time_midp, Z, Y, Xp1) float64 dask.array\n", " ADVy_SLT (time_midp, Z, Yp1, X) float64 dask.array\n", " ADVy_TH (time_midp, Z, Yp1, X) float64 dask.array\n", - " DFrI_SLT (time_midp, Zl, Y, X) float64 dask.array\n", - " DFrI_TH (time_midp, Zl, Y, X) float64 dask.array\n", - " Depth (Y, X) float64 dask.array\n", - " EXFaqh (time, Y, X) float64 dask.array\n", - " EXFatemp (time, Y, X) float64 dask.array\n", - " EXFempmr (time, Y, X) float64 dask.array\n", - " EXFevap (time, Y, X) float64 dask.array\n", - " EXFhl (time, Y, X) float64 dask.array\n", - " EXFhs (time, Y, X) float64 dask.array\n", - " EXFlwnet (time, Y, X) float64 dask.array\n", - " EXFpreci (time, Y, X) float64 dask.array\n", - " EXFpress (time, Y, X) float64 dask.array\n", - " EXFqnet (time, Y, X) float64 dask.array\n", - " EXFroff (time, Y, X) float64 dask.array\n", - " EXFroft (time, Y, X) float64 dask.array\n", - " EXFsnow (time, Y, X) float64 dask.array\n", - " EXFswnet (time, Y, X) float64 dask.array\n", - " EXFtaux (time, Y, X) float64 dask.array\n", - " EXFtauy (time, Y, X) float64 dask.array\n", - " EXFuwind (time, Y, X) float64 dask.array\n", - " EXFvwind (time, Y, X) float64 dask.array\n", - " Eta (time, Y, X) float64 dask.array\n", - " HFacC (Z, Y, X) float64 dask.array\n", - " HFacS (Z, Yp1, X) float64 dask.array\n", - " HFacW (Z, Y, Xp1) float64 dask.array\n", - " KPPg_SLT (time_midp, Zl, Y, X) float64 dask.array\n", - " KPPg_TH (time_midp, Zl, Y, X) float64 dask.array\n", - " KPPhbl (time, Y, X) float64 dask.array\n", - " MXLDEPTH (time, Y, X) float64 dask.array\n", - " RHOAnoma (time, Z, Y, X) float64 dask.array\n", - " R_low (Y, X) float64 dask.array\n", - " Ro_surf (Y, X) float64 dask.array\n", - " S (time, Z, Y, X) float64 dask.array\n", - " SFLUX (time_midp, Y, X) float64 dask.array\n", - " SIarea (time, Y, X) float64 dask.array\n", - " SIheff (time, Y, X) float64 dask.array\n", - " SIhsalt (time, Y, X) float64 dask.array\n", - " SIhsnow (time, Y, X) float64 dask.array\n", - " SIuice (time, Y, Xp1) float64 dask.array\n", - " SIvice (time, Yp1, X) float64 dask.array\n", - " SRELAX (time, Y, X) float64 dask.array\n", - " TFLUX (time_midp, Y, X) float64 dask.array\n", - " TRELAX (time, Y, X) float64 dask.array\n", - " Temp (time, Z, Y, X) float64 dask.array\n", - " U (time, Z, Y, Xp1) float64 dask.array\n", - " V (time, Z, Yp1, X) float64 dask.array\n", - " W (time, Zl, Y, X) float64 dask.array\n", - " drC (Zp1) float64 dask.array\n", - " drF (Z) float64 dask.array\n", - " dxC (Y, Xp1) float64 dask.array\n", - " dxF (Y, X) float64 dask.array\n", - " dxG (Yp1, X) float64 dask.array\n", - " dxV (Yp1, Xp1) float64 dask.array\n", - " dyC (Yp1, X) float64 dask.array\n", - " dyF (Y, X) float64 dask.array\n", - " dyG (Y, Xp1) float64 dask.array\n", - " dyU (Yp1, Xp1) float64 dask.array\n", - " fCori (Y, X) float64 dask.array\n", - " fCoriG (Yp1, Xp1) float64 dask.array\n", - " momVort3 (time, Z, Yp1, Xp1) float64 dask.array\n", - " oceFWflx (time, Y, X) float64 dask.array\n", - " oceFreez (time, Y, X) float64 dask.array\n", - " oceQnet (time, Y, X) float64 dask.array\n", - " oceQsw (time, Y, X) float64 dask.array\n", - " oceQsw_AVG (time_midp, Y, X) float64 dask.array\n", - " oceSPDep (time, Y, X) float64 dask.array\n", - " oceSPflx (time, Y, X) float64 dask.array\n", - " oceSPtnd (time_midp, Z, Y, X) float64 dask.array\n", - " oceSflux (time, Y, X) float64 dask.array\n", - " oceTAUX (time, Y, Xp1) float64 dask.array\n", - " oceTAUY (time, Yp1, X) float64 dask.array\n", - " phiHyd (time, Z, Y, X) float64 dask.array\n", - " phiHydLow (time, Y, X) float64 dask.array\n", - " rA (Y, X) float64 dask.array\n", - " rAs (Yp1, X) float64 dask.array\n", - " rAw (Y, Xp1) float64 dask.array\n", + " ... ...\n", " rAz (Yp1, Xp1) float64 dask.array\n", " surForcS (time, Y, X) float64 dask.array\n", " surForcT (time, Y, X) float64 dask.array\n", @@ -775,7 +13404,15 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:14.887700Z", + "iopub.status.busy": "2023-04-04T02:47:14.887094Z", + "iopub.status.idle": "2023-04-04T02:47:30.653132Z", + "shell.execute_reply": "2023-04-04T02:47:30.650607Z", + "shell.execute_reply.started": "2023-04-04T02:47:14.887636Z" + } + }, "outputs": [ { "name": "stdout", @@ -788,16 +13425,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in divide\n", + " return func(*(_execute_task(a, cache) for a in args))\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -806,14 +13441,12 @@ }, { "data": { - "image/png": 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -842,6 +13475,13 @@ "cell_type": "code", "execution_count": 14, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:30.656613Z", + "iopub.status.busy": "2023-04-04T02:47:30.655985Z", + "iopub.status.idle": "2023-04-04T02:47:30.931672Z", + "shell.execute_reply": "2023-04-04T02:47:30.928393Z", + "shell.execute_reply.started": "2023-04-04T02:47:30.656556Z" + }, "scrolled": true }, "outputs": [ @@ -851,9 +13491,9 @@ "text": [ "Computing gradient.\n", "Data variables:\n", - " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", - " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", - " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", + " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", + " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", + " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", " dTemp_dtime (time_midp, Z, Y, X) float64 dask.array\n" ] } @@ -874,7 +13514,15 @@ { "cell_type": "code", "execution_count": 15, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:30.935530Z", + "iopub.status.busy": "2023-04-04T02:47:30.934910Z", + "iopub.status.idle": "2023-04-04T02:47:31.549823Z", + "shell.execute_reply": "2023-04-04T02:47:31.542510Z", + "shell.execute_reply.started": "2023-04-04T02:47:30.935472Z" + } + }, "outputs": [ { "name": "stdout", @@ -904,7 +13552,15 @@ { "cell_type": "code", "execution_count": 16, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:31.558411Z", + "iopub.status.busy": "2023-04-04T02:47:31.557749Z", + "iopub.status.idle": "2023-04-04T02:47:32.998218Z", + "shell.execute_reply": "2023-04-04T02:47:32.994992Z", + "shell.execute_reply.started": "2023-04-04T02:47:31.558340Z" + } + }, "outputs": [ { "name": "stdout", @@ -914,9 +13570,9 @@ "GRADIENT\n", "Computing gradient.\n", "Data variables:\n", - " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", - " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", - " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", + " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", + " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", + " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", " dTemp_dtime (time_midp, Z, Y, X) float64 dask.array\n", "\n", "DIVERGENCE\n", @@ -925,7 +13581,7 @@ "Data variables:\n", " dU_dX (time, Z, Y, X) float64 dask.array\n", " dV_dY (time, Z, Y, X) float64 dask.array\n", - " dW_dZ (time, Z, Y, X) float64 dask.array\n", + " dW_dZ (time, Z, Y, X) float64 dask.array\n", "\n", "CURL\n", "Computing curl.\n", @@ -934,9 +13590,9 @@ "Computing gradient.\n", "Computing gradient.\n", "Data variables:\n", - " dV_dX-dU_dY (time, Z, Yp1, Xp1) float64 dask.array\n", - " dW_dY-dV_dZ (time, Zl, Yp1, X) float64 dask.array\n", - " dU_dZ-dW_dX (time, Zl, Y, Xp1) float64 dask.array\n", + " dV_dX-dU_dY (time, Z, Yp1, Xp1) float64 dask.array\n", + " dW_dY-dV_dZ (time, Zl, Yp1, X) float64 dask.array\n", + " dU_dZ-dW_dX (time, Zl, Y, Xp1) float64 dask.array\n", "\n", "LAPLACIAN\n", "Computing laplacian.\n", @@ -944,9 +13600,9 @@ "Computing divergence.\n", "Computing gradient.\n", "Data variables:\n", - " ddTemp_dX_dX (time, Z, Y, X) float64 dask.array\n", - " ddTemp_dY_dY (time, Z, Y, X) float64 dask.array\n", - " ddTemp_dZ_dZ (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dX_dX (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dY_dY (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dZ_dZ (time, Z, Y, X) float64 dask.array\n", "\n", "WEIGHTED MEAN\n", "Computing weighted_mean.\n", @@ -991,7 +13647,15 @@ { "cell_type": "code", "execution_count": 17, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:33.001801Z", + "iopub.status.busy": "2023-04-04T02:47:33.001153Z", + "iopub.status.idle": "2023-04-04T02:47:36.897015Z", + "shell.execute_reply": "2023-04-04T02:47:36.893999Z", + "shell.execute_reply.started": "2023-04-04T02:47:33.001743Z" + } + }, "outputs": [ { "name": "stdout", @@ -1022,7 +13686,15 @@ { "cell_type": "code", "execution_count": 18, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:36.902615Z", + "iopub.status.busy": "2023-04-04T02:47:36.901534Z", + "iopub.status.idle": "2023-04-04T02:47:39.547764Z", + "shell.execute_reply": "2023-04-04T02:47:39.545694Z", + "shell.execute_reply.started": "2023-04-04T02:47:36.902522Z" + } + }, "outputs": [ { "name": "stdout", @@ -1037,22 +13709,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in divide\n", + " return func(*(_execute_task(a, cache) for a in args))\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1078,7 +13746,15 @@ { "cell_type": "code", "execution_count": 19, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:47:39.550124Z", + "iopub.status.busy": "2023-04-04T02:47:39.549545Z", + "iopub.status.idle": "2023-04-04T02:47:42.313705Z", + "shell.execute_reply": "2023-04-04T02:47:42.311347Z", + "shell.execute_reply.started": "2023-04-04T02:47:39.550068Z" + } + }, "outputs": [ { "name": "stdout", @@ -1093,22 +13769,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/srv/conda/envs/notebook/lib/python3.7/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in divide\n", + " return func(*(_execute_task(a, cache) for a in args))\n" ] }, { "data": { - "image/png": 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\n", 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This is typically much slower for opening a dataset. To silence this warning, consider:\n", + "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", + "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", + "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", + " ds = _xr.open_zarr(path, **kwargs)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", " REFERENCE NAME: DESCRIPTION\n", "\n", @@ -1437,9 +14138,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Oceanography", "language": "python", - "name": "python3" + "name": "oceanography" }, "language_info": { "codemirror_mode": { @@ -1451,7 +14152,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.8" + "version": "3.9.16" } }, "nbformat": 4, diff --git a/docs/.DS_Store b/docs/.DS_Store index 1a77f9711989bdc005590b77c1dc910adc87ac27..3929ff9c1882af30e59702078f1261cad7fb3677 100644 GIT binary patch delta 54 zcmV-60LlM^P=rvhQxE~ilT;9Z2^M>MFf1T5I5v~t5FG)Rll>4M0hqHL5$X=J1t9zc MlavvJvxgOb0s-U_`2YX_ delta 56 zcmV-80LTA?P=rvhQxE~klT;9Z3mAKQG&VLYAT%>Mlid&<0hyEg5FY`Wvl|iW4zmX! O`UI1Z5r(sc6@3C9X%l7u diff --git a/docs/Kogur.ipynb b/docs/Kogur.ipynb index 3557935d..46df8103 100644 --- a/docs/Kogur.ipynb +++ b/docs/Kogur.ipynb @@ -12,7 +12,16 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:04:40.283048Z", + "iopub.status.busy": "2023-04-04T02:04:40.282458Z", + "iopub.status.idle": "2023-04-04T02:05:00.025362Z", + "shell.execute_reply": "2023-04-04T02:05:00.022917Z", + "shell.execute_reply.started": "2023-04-04T02:04:40.282991Z" + }, + "tags": [] + }, "outputs": [], "source": [ "# Import oceanspy\n", @@ -34,33 +43,322 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:05:00.030115Z", + "iopub.status.busy": "2023-04-04T02:05:00.029011Z", + "iopub.status.idle": "2023-04-04T02:05:04.664095Z", + "shell.execute_reply": "2023-04-04T02:05:04.661109Z", + "shell.execute_reply.started": "2023-04-04T02:05:00.030059Z" + } + }, "outputs": [ { "data": { "text/html": [ - "\n", - "\n", - "\n", - "\n", + "
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Workers

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Worker: 0

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\n", + " Comm: tcp://127.0.0.1:43234\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:41307/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:33098\n", + "
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Worker: 1

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\n", + " Comm: tcp://127.0.0.1:39180\n", + " \n", + " Total threads: 1\n", + "
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Worker: 2

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\n", + " Comm: tcp://127.0.0.1:38105\n", + " \n", + " Total threads: 1\n", + "
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Worker: 3

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\n", + " Comm: tcp://127.0.0.1:43071\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:45757/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
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You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.\n", + " warnings.warn(\n" ] }, { @@ -203,7 +527,15 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:06:41.142433Z", + "iopub.status.busy": "2023-04-04T02:06:41.141752Z", + "iopub.status.idle": "2023-04-04T02:06:57.728612Z", + "shell.execute_reply": "2023-04-04T02:06:57.725891Z", + "shell.execute_reply.started": "2023-04-04T02:06:41.142376Z" + } + }, "outputs": [ { "name": "stdout", @@ -244,28 +576,24 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:06:57.731037Z", + "iopub.status.busy": "2023-04-04T02:06:57.730443Z", + "iopub.status.idle": "2023-04-04T02:07:02.430246Z", + "shell.execute_reply": "2023-04-04T02:07:02.427831Z", + "shell.execute_reply.started": "2023-04-04T02:06:57.730982Z" + } + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -288,7 +616,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:02.433645Z", + "iopub.status.busy": "2023-04-04T02:07:02.432993Z", + "iopub.status.idle": "2023-04-04T02:07:04.211310Z", + "shell.execute_reply": "2023-04-04T02:07:04.208550Z", + "shell.execute_reply.started": "2023-04-04T02:07:02.433588Z" + } + }, "outputs": [ { "name": "stdout", @@ -298,28 +634,29 @@ "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", " * outer Yp1 --> center\n", - "time Axis (not periodic, boundary=None):\n", - " * center time_midp --> outer\n", - " * outer time --> center\n", "X Axis (not periodic, boundary=None):\n", " * center X --> outer\n", " * outer Xp1 --> center\n", + "time Axis (not periodic, boundary=None):\n", + " * center time_midp --> outer\n", + " * outer time --> center\n", "Z Axis (not periodic, boundary=None):\n", " * center Z --> left\n", - " * left Zl --> center\n", " * outer Zp1 --> center\n", " * right Zu --> center\n", + " * left Zl --> center\n", "mooring Axis (not periodic, boundary=None):\n", " * center mooring_midp --> outer\n", " * outer mooring --> center\n", "\n", "Coordinates:\n", - " * mooring_midp (mooring_midp) float64 0.5 1.5 2.5 ... 187.5 188.5 189.5\n", " * Z (Z) float64 -1.0 -3.5 -7.0 ... -1.732e+03 -1.746e+03\n", " * Zp1 (Zp1) float64 0.0 -2.0 -5.0 ... -1.739e+03 -1.754e+03\n", " * Zu (Zu) float64 -2.0 -5.0 -9.0 ... -1.739e+03 -1.754e+03\n", " * Zl (Zl) float64 0.0 -2.0 -5.0 ... -1.724e+03 -1.739e+03\n", " YC (mooring, Y, X) float64 ...\n", + " Xind (mooring, Y, X) float64 ...\n", + " Yind (mooring, Y, X) float64 ...\n", " * mooring (mooring) int64 0 1 2 3 4 5 6 ... 185 186 187 188 189 190\n", " * Y (Y) int64 0\n", " * X (X) int64 0\n", @@ -335,20 +672,19 @@ " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-28\n", " * time_midp (time_midp) datetime64[ns] 2007-09-02T12:00:00 ... 200...\n", " mooring_dist (mooring) float64 ...\n", + " * mooring_midp (mooring_midp) float64 0.5 1.5 2.5 ... 187.5 188.5 189.5\n", " mooring_midp_dist (mooring_midp) float64 ...\n", "\n" ] }, { "data": { - "image/png": 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\n", 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -402,7 +738,15 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:04.215854Z", + "iopub.status.busy": "2023-04-04T02:07:04.214162Z", + "iopub.status.idle": "2023-04-04T02:07:06.221354Z", + "shell.execute_reply": "2023-04-04T02:07:06.219016Z", + "shell.execute_reply.started": "2023-04-04T02:07:04.215797Z" + } + }, "outputs": [ { "name": "stdout", @@ -416,14 +760,12 @@ }, { "data": { - "image/png": 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\n", 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -448,7 +790,15 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:06.232432Z", + "iopub.status.busy": "2023-04-04T02:07:06.231800Z", + "iopub.status.idle": "2023-04-04T02:07:14.392459Z", + "shell.execute_reply": "2023-04-04T02:07:14.389747Z", + "shell.execute_reply.started": "2023-04-04T02:07:06.232375Z" + } + }, "outputs": [ { "name": "stdout", @@ -460,14 +810,12 @@ }, { "data": { - "image/png": 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\n", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -491,7 +839,15 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:14.395624Z", + "iopub.status.busy": "2023-04-04T02:07:14.394988Z", + "iopub.status.idle": "2023-04-04T02:07:15.519798Z", + "shell.execute_reply": "2023-04-04T02:07:15.517559Z", + "shell.execute_reply.started": "2023-04-04T02:07:14.395567Z" + } + }, "outputs": [ { "name": "stdout", @@ -502,14 +858,12 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -530,7 +884,15 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:15.522873Z", + "iopub.status.busy": "2023-04-04T02:07:15.522233Z", + "iopub.status.idle": "2023-04-04T02:07:18.364500Z", + "shell.execute_reply": "2023-04-04T02:07:18.361347Z", + "shell.execute_reply.started": "2023-04-04T02:07:15.522818Z" + } + }, "outputs": [ { "name": "stdout", @@ -544,14 +906,12 @@ }, { "data": { - "image/png": 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\n", 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"text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -576,7 +936,15 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:18.369358Z", + "iopub.status.busy": "2023-04-04T02:07:18.368725Z", + "iopub.status.idle": "2023-04-04T02:07:19.838092Z", + "shell.execute_reply": "2023-04-04T02:07:19.835485Z", + "shell.execute_reply.started": "2023-04-04T02:07:18.369264Z" + } + }, "outputs": [ { "name": "stdout", @@ -584,32 +952,41 @@ "text": [ "Computing horizontal volume transport.\n", "\n", - "Dimensions: (Z: 123, mooring: 191, path: 2, time: 10)\n", - "Coordinates:\n", + "Dimensions: (Z: 123, mooring: 191, time: 10, path: 2)\n", + "Coordinates: (12/13)\n", " * Z (Z) float64 -1.0 -3.5 -7.0 ... -1.732e+03 -1.746e+03\n", " * mooring (mooring) int64 0 1 2 3 4 5 6 ... 185 186 187 188 189 190\n", " Y int64 0\n", " YU (mooring) float64 68.68 68.68 68.68 ... 66.52 66.5 66.49\n", " * time (time) datetime64[ns] 2007-09-01 2007-09-04 ... 2007-09-28\n", " mooring_dist (mooring) float64 0.0 1.778 3.556 ... 378.1 380.2 382.3\n", - " * path (path) int64 0 1\n", + " ... ...\n", " X int64 0\n", " XV (mooring) float64 -26.29 -26.24 -26.2 ... -22.99 -22.99\n", " YC (mooring) float64 68.68 68.68 68.68 ... 66.52 66.5 66.49\n", + " Xind (mooring) float64 -26.29 -26.24 -26.2 ... -22.99 -22.99\n", + " Yind (mooring) float64 68.68 68.68 68.68 ... 66.52 66.5 66.49\n", " XC (mooring) float64 -26.29 -26.24 -26.2 ... -22.99 -22.99\n", "Data variables:\n", " transport (time, Z, mooring, path) float64 nan nan ... nan nan\n", " Vtransport (time, Z, mooring, path) float64 nan nan ... nan nan\n", " Utransport (time, Z, mooring, path) float64 nan nan -0.0 ... nan nan\n", - " Y_transport (mooring) float64 68.68 68.68 68.68 ... 66.52 66.5 66.49\n", - " X_transport (mooring) float64 -26.29 -26.24 -26.2 ... -22.99 -22.99\n", + " Y_transport (mooring) float64 ...\n", + " X_transport (mooring) float64 ...\n", " Y_Utransport (mooring, path) float64 68.68 68.68 nan ... 66.5 66.49 66.49\n", " X_Utransport (mooring, path) float64 -26.31 -26.31 nan ... -23.01 -23.01\n", " Y_Vtransport (mooring, path) float64 68.67 68.67 68.69 ... 66.48 66.48\n", " X_Vtransport (mooring, path) float64 -26.29 -26.29 ... -22.99 -22.99\n", " dir_Utransport (mooring, path) float64 nan nan nan nan ... 1.0 1.0 nan nan\n", " dir_Vtransport (mooring, path) float64 nan nan 1.0 1.0 ... nan nan nan nan\n", - "Attributes:\n", + "Attributes: (12/14)\n", + " build_date: ven 24 giu 2016, 09.35.54, EDT\n", + " build_user: malmans2@jhu.edu\n", + " MITgcm_URL: http://mitgcm.org\n", + " build_host: compute0117\n", + " MITgcm_tag_id: 1.2226 2016/01/20\n", + " MITgcm_version: checkpoint65s\n", + " ... ...\n", " OceanSpy_parameters: {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0':...\n", " OceanSpy_name: EGshelfIIseas2km_ASR_full\n", " OceanSpy_description: High-resolution (~2km) numerical simulation cove...\n", @@ -621,7 +998,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -630,14 +1007,12 @@ }, { "data": { - "image/png": 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\n", 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -731,18 +1106,24 @@ { "cell_type": "code", "execution_count": 14, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:19.842530Z", + "iopub.status.busy": "2023-04-04T02:07:19.841403Z", + "iopub.status.idle": "2023-04-04T02:07:20.449260Z", + "shell.execute_reply": "2023-04-04T02:07:20.445609Z", + "shell.execute_reply.started": "2023-04-04T02:07:19.842418Z" + } + }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -769,7 +1150,15 @@ { "cell_type": "code", "execution_count": 15, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:20.455833Z", + "iopub.status.busy": "2023-04-04T02:07:20.454656Z", + "iopub.status.idle": "2023-04-04T02:07:21.574002Z", + "shell.execute_reply": "2023-04-04T02:07:21.571225Z", + "shell.execute_reply.started": "2023-04-04T02:07:20.455747Z" + } + }, "outputs": [ { "name": "stdout", @@ -780,14 +1169,12 @@ }, { "data": { - "image/png": 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\n", 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", "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -825,7 +1212,15 @@ { "cell_type": "code", "execution_count": 16, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:21.577612Z", + "iopub.status.busy": "2023-04-04T02:07:21.576886Z", + "iopub.status.idle": "2023-04-04T02:07:31.741798Z", + "shell.execute_reply": "2023-04-04T02:07:31.738975Z", + "shell.execute_reply.started": "2023-04-04T02:07:21.577556Z" + } + }, "outputs": [ { "name": "stdout", @@ -838,7 +1233,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/oceanspy/subsample.py:1395: UserWarning: \n", + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/oceanspy/subsample.py:1375: UserWarning: \n", "Time resampling drops variables on `time_midp` dimension.\n", "Dropped variables: ['time_midp'].\n", " return cutout(self._od, **kwargs)\n" @@ -849,120 +1244,46 @@ "output_type": "stream", "text": [ "Carrying out survey.\n", - "Create weight file: bilinear_118x76_142x142.nc\n", - "Variables to interpolate: ['XC', 'YC', 'XU', 'YU', 'XV', 'YV', 'XG', 'YG', 'HFacC', 'HFacW', 'HFacS', 'U', 'V', 'Temp', 'S'].\n", + "Variables to interpolate: ['XC', 'YC', 'XU', 'YU', 'XV', 'YV', 'XG', 'YG', 'HFacC', 'HFacW', 'HFacS', 'U', 'V', 'Temp', 'S', 'Xind', 'Yind'].\n", "Interpolating [XC].\n", - "Interpolating [YC].\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Interpolating [YC].\n", "Interpolating [XU].\n", "Interpolating [YU].\n", - "Interpolating [XV].\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Interpolating [XV].\n", "Interpolating [YV].\n", "Interpolating [XG].\n", - "Interpolating [YG].\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Interpolating [YG].\n", "Interpolating [HFacC].\n", "Interpolating [HFacW].\n", - "Interpolating [HFacS].\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Interpolating [HFacS].\n", "Interpolating [U].\n", "Interpolating [V].\n", - "Interpolating [Temp].\n" + "Interpolating [Temp].\n", + "Interpolating [S].\n", + "Interpolating [Xind].\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/xesmf/smm.py:130: UserWarning: Input array is not C_CONTIGUOUS. Will affect performance.\n", + " warnings.warn('Input array is not C_CONTIGUOUS. ' 'Will affect performance.')\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Interpolating [S].\n", - "Remove file bilinear_118x76_142x142.nc\n" + "Interpolating [Yind].\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/xesmf/frontend.py:412: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", - " dr_out = xr.apply_ufunc(\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/xesmf/smm.py:130: UserWarning: Input array is not C_CONTIGUOUS. Will affect performance.\n", + " warnings.warn('Input array is not C_CONTIGUOUS. ' 'Will affect performance.')\n" ] } ], @@ -986,28 +1307,24 @@ { "cell_type": "code", "execution_count": 17, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:31.745555Z", + "iopub.status.busy": "2023-04-04T02:07:31.744914Z", + "iopub.status.idle": "2023-04-04T02:07:39.720791Z", + "shell.execute_reply": "2023-04-04T02:07:39.718043Z", + "shell.execute_reply.started": "2023-04-04T02:07:31.745498Z" + } + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", 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compute them, please open an issue on GitHub:\n", " https://github.com/hainegroup/oceanspy/issues\n", @@ -1068,7 +1393,16 @@ { "cell_type": "code", "execution_count": 19, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:07:39.862216Z", + "iopub.status.busy": "2023-04-04T02:07:39.861640Z", + "iopub.status.idle": "2023-04-04T02:08:39.896175Z", + "shell.execute_reply": "2023-04-04T02:08:39.891385Z", + "shell.execute_reply.started": "2023-04-04T02:07:39.862163Z" + }, + "tags": [] + }, "outputs": [], "source": [ "anim = od_surv.animate.vertical_section(\n", @@ -1114,7 +1448,15 @@ { "cell_type": "code", "execution_count": 20, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:08:39.902558Z", + "iopub.status.busy": "2023-04-04T02:08:39.901789Z", + "iopub.status.idle": "2023-04-04T02:08:40.162413Z", + "shell.execute_reply": "2023-04-04T02:08:40.159631Z", + "shell.execute_reply.started": "2023-04-04T02:08:39.902467Z" + } + }, "outputs": [ { "name": "stdout", @@ -1154,18 +1496,24 @@ { "cell_type": "code", "execution_count": 21, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:08:40.166533Z", + "iopub.status.busy": "2023-04-04T02:08:40.165913Z", + "iopub.status.idle": "2023-04-04T02:08:50.536470Z", + "shell.execute_reply": "2023-04-04T02:08:50.534547Z", + "shell.execute_reply.started": "2023-04-04T02:08:40.166478Z" + } + }, "outputs": [ { "data": { - "image/png": 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\n", 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Worker: 2

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Worker: 3

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"stdout", "output_type": "stream", "text": [ "Opening EGshelfIIseas2km_ASR_full.\n", - "High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), \n", - "and the Iceland and Irminger Seas (IIseas) forced by the Arctic System Reanalysis (ASR). \n", + "High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf),\n", + "and the Iceland and Irminger Seas (IIseas) forced by the Arctic System Reanalysis (ASR).\n", "Citation:\n", " * Almansi et al., 2020 - GRL.\n", "Characteristics:\n", @@ -233,15 +555,954 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:03.191880Z", + "iopub.status.busy": "2023-04-04T02:14:03.191223Z", + "iopub.status.idle": "2023-04-04T02:14:06.364554Z", + "shell.execute_reply": "2023-04-04T02:14:06.361008Z", + "shell.execute_reply.started": "2023-04-04T02:14:03.191823Z" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Downloading [oceanspy_particle_properties.nc].\n", + "Downloading [oceanspy_particle_properties.nc].\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "--2023-04-03 22:14:03-- https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/EWvf_TyoEdpaDKcFacaPLI4B1fLGf9qleW7xbIDlKVPJDw?download=1\n", + "Resolving livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)... 13.107.138.8, 13.107.136.8, 2620:1ec:8fa::8, ...\n", + "Connecting to livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)|13.107.138.8|:443... connected.\n", + "HTTP request sent, awaiting response... 302 Found\n", + "Location: /personal/malmans2_jh_edu/Documents/BoxMigration/oceanspy_particle_properties.nc?ga=1 [following]\n", + "--2023-04-03 22:14:03-- https://livejohnshopkins-my.sharepoint.com/personal/malmans2_jh_edu/Documents/BoxMigration/oceanspy_particle_properties.nc?ga=1\n", + "Reusing existing connection to livejohnshopkins-my.sharepoint.com:443.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 45981653 (44M) [application/x-netcdf]\n", + "Saving to: ‘oceanspy_particle_properties.nc’\n", + "\n", + " 0K .......... .......... .......... .......... .......... 0% 9.77M 4s\n", + " 50K .......... .......... .......... .......... .......... 0% 9.88M 4s\n", + " 100K .......... .......... .......... .......... .......... 0% 64.0M 3s\n", + " 150K .......... .......... .......... .......... .......... 0% 13.0M 3s\n", + " 200K .......... .......... .......... .......... .......... 0% 71.2M 3s\n", + " 250K .......... .......... .......... .......... .......... 0% 13.2M 3s\n", + " 300K .......... .......... .......... .......... .......... 0% 35.3M 3s\n", + " 350K .......... .......... .......... .......... .......... 0% 61.9M 2s\n", + " 400K .......... .......... .......... .......... .......... 1% 64.1M 2s\n", + " 450K .......... .......... .......... .......... 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.......... .......... 17% 50.6M 1s\n", + " 7850K .......... .......... .......... .......... .......... 17% 65.5M 1s\n", + " 7900K .......... .......... .......... .......... .......... 17% 46.8M 1s\n", + " 7950K .......... .......... .......... .......... .......... 17% 48.2M 1s\n", + " 8000K .......... .......... .......... .......... .......... 17% 5.65M 1s\n", + " 8050K .......... .......... .......... .......... .......... 18% 61.6M 1s\n", + " 8100K .......... .......... .......... .......... .......... 18% 65.5M 1s\n", + " 8150K .......... .......... .......... .......... .......... 18% 66.6M 1s\n", + " 8200K .......... .......... .......... .......... .......... 18% 51.2M 1s\n", + " 8250K .......... .......... .......... .......... .......... 18% 70.1M 1s\n", + " 8300K .......... .......... .......... .......... .......... 18% 57.1M 1s\n", + " 8350K .......... .......... .......... .......... .......... 18% 60.2M 1s\n", + " 8400K .......... .......... .......... .......... .......... 18% 60.6M 1s\n", + " 8450K .......... .......... .......... .......... .......... 18% 65.9M 1s\n", + " 8500K .......... .......... .......... .......... .......... 19% 61.1M 1s\n", + " 8550K .......... .......... .......... .......... .......... 19% 59.5M 1s\n", + " 8600K .......... .......... .......... .......... .......... 19% 48.2M 1s\n", + " 8650K .......... .......... .......... .......... .......... 19% 56.9M 1s\n", + " 8700K .......... .......... .......... .......... .......... 19% 65.7M 1s\n", + " 8750K .......... .......... .......... .......... .......... 19% 66.3M 1s\n", + " 8800K .......... .......... .......... .......... .......... 19% 48.5M 1s\n", + " 8850K .......... .......... .......... .......... .......... 19% 70.7M 1s\n", + " 8900K .......... .......... .......... .......... .......... 19% 47.0M 1s\n", + " 8950K .......... .......... .......... .......... .......... 20% 74.4M 1s\n", + " 9000K .......... .......... .......... .......... .......... 20% 62.4M 1s\n", + " 9050K .......... .......... .......... .......... .......... 20% 75.2M 1s\n", + " 9100K .......... .......... .......... .......... .......... 20% 69.9M 1s\n", + " 9150K .......... .......... .......... .......... .......... 20% 66.9M 1s\n", + " 9200K .......... .......... .......... .......... .......... 20% 52.5M 1s\n", + " 9250K .......... .......... .......... .......... .......... 20% 68.7M 1s\n", + " 9300K .......... .......... .......... .......... .......... 20% 65.9M 1s\n", + " 9350K .......... .......... .......... .......... .......... 20% 64.4M 1s\n", + " 9400K .......... .......... .......... .......... .......... 21% 47.6M 1s\n", + " 9450K .......... .......... .......... .......... .......... 21% 52.4M 1s\n", + " 9500K .......... .......... .......... .......... .......... 21% 51.6M 1s\n", + " 9550K .......... .......... .......... .......... .......... 21% 61.0M 1s\n", + " 9600K .......... .......... .......... .......... .......... 21% 63.4M 1s\n", + " 9650K .......... .......... .......... .......... .......... 21% 52.5M 1s\n", + " 9700K .......... .......... .......... .......... .......... 21% 40.0M 1s\n", + " 9750K .......... .......... .......... .......... .......... 21% 50.2M 1s\n", + " 9800K .......... .......... .......... .......... .......... 21% 57.4M 1s\n", + " 9850K .......... .......... .......... .......... .......... 22% 60.6M 1s\n", + " 9900K .......... .......... .......... .......... .......... 22% 44.1M 1s\n", + " 9950K .......... .......... .......... .......... .......... 22% 41.5M 1s\n", + " 10000K .......... .......... .......... .......... .......... 22% 50.4M 1s\n", + " 10050K .......... .......... .......... .......... .......... 22% 67.7M 1s\n", + " 10100K .......... .......... .......... .......... .......... 22% 47.1M 1s\n", + " 10150K .......... .......... .......... .......... .......... 22% 33.8M 1s\n", + " 10200K .......... .......... .......... .......... .......... 22% 41.8M 1s\n", + " 10250K .......... .......... .......... .......... .......... 22% 69.8M 1s\n", + " 10300K .......... .......... .......... .......... .......... 23% 56.7M 1s\n", + " 10350K .......... .......... .......... .......... .......... 23% 39.8M 1s\n", + " 10400K .......... .......... .......... .......... .......... 23% 42.8M 1s\n", + " 10450K .......... .......... .......... .......... .......... 23% 69.6M 1s\n", + " 10500K .......... .......... .......... .......... .......... 23% 62.9M 1s\n", + " 10550K .......... .......... .......... .......... .......... 23% 51.1M 1s\n", + " 10600K .......... .......... .......... .......... .......... 23% 28.6M 1s\n", + " 10650K .......... .......... .......... .......... .......... 23% 61.7M 1s\n", + " 10700K .......... .......... .......... .......... .......... 23% 70.5M 1s\n", + " 10750K .......... .......... .......... .......... .......... 24% 60.3M 1s\n", + " 10800K .......... .......... .......... .......... .......... 24% 42.7M 1s\n", + " 10850K .......... .......... .......... .......... .......... 24% 40.6M 1s\n", + " 10900K .......... .......... .......... .......... .......... 24% 59.7M 1s\n", + " 10950K .......... .......... .......... .......... .......... 24% 64.0M 1s\n", + " 11000K .......... .......... .......... .......... .......... 24% 57.0M 1s\n", + " 11050K .......... .......... .......... .......... .......... 24% 55.8M 1s\n", + " 11100K .......... .......... .......... .......... .......... 24% 46.1M 1s\n", + " 11150K .......... .......... .......... .......... .......... 24% 63.5M 1s\n", + " 11200K .......... .......... .......... .......... .......... 25% 69.2M 1s\n", + " 11250K .......... .......... .......... .......... .......... 25% 72.0M 1s\n", + " 11300K .......... .......... .......... .......... .......... 25% 72.2M 1s\n", + " 11350K .......... .......... .......... .......... .......... 25% 73.1M 1s\n", + " 11400K .......... .......... .......... .......... .......... 25% 46.8M 1s\n", + " 11450K .......... .......... .......... .......... .......... 25% 56.7M 1s\n", + " 11500K .......... .......... .......... .......... .......... 25% 78.7M 1s\n", + " 11550K .......... .......... .......... .......... .......... 25% 77.3M 1s\n", + " 11600K .......... .......... .......... .......... .......... 25% 76.2M 1s\n", + " 11650K .......... .......... .......... .......... .......... 26% 73.7M 1s\n", + " 11700K .......... .......... .......... .......... .......... 26% 56.5M 1s\n", + " 11750K .......... .......... .......... .......... .......... 26% 66.4M 1s\n", + " 11800K .......... .......... .......... .......... .......... 26% 43.9M 1s\n", + " 11850K .......... .......... .......... .......... .......... 26% 73.1M 1s\n", + " 11900K .......... .......... .......... .......... .......... 26% 69.8M 1s\n", + " 11950K .......... .......... .......... .......... .......... 26% 70.1M 1s\n", + " 12000K .......... .......... .......... .......... .......... 26% 68.5M 1s\n", + " 12050K .......... .......... .......... .......... .......... 26% 65.1M 1s\n", + " 12100K .......... .......... .......... .......... .......... 27% 53.0M 1s\n", + " 12150K .......... .......... .......... .......... .......... 27% 48.3M 1s\n", + " 12200K .......... .......... .......... .......... .......... 27% 50.5M 1s\n", + " 12250K .......... .......... .......... .......... .......... 27% 73.8M 1s\n", + " 12300K .......... .......... .......... .......... .......... 27% 79.5M 1s\n", + " 12350K .......... .......... .......... .......... .......... 27% 66.3M 1s\n", + " 12400K .......... .......... .......... .......... .......... 27% 48.5M 1s\n", + " 12450K .......... .......... .......... .......... .......... 27% 49.4M 1s\n", + " 12500K .......... .......... .......... .......... .......... 27% 70.3M 1s\n", + " 12550K .......... .......... .......... .......... .......... 28% 76.6M 1s\n", + " 12600K .......... .......... .......... .......... .......... 28% 60.9M 1s\n", + " 12650K .......... .......... .......... .......... .......... 28% 68.4M 1s\n", + " 12700K .......... .......... .......... .......... .......... 28% 46.8M 1s\n", + " 12750K .......... .......... .......... .......... .......... 28% 49.6M 1s\n", + " 12800K .......... .......... .......... .......... .......... 28% 69.2M 1s\n", + " 12850K .......... .......... .......... .......... .......... 28% 80.2M 1s\n", + " 12900K .......... .......... .......... .......... .......... 28% 75.8M 1s\n", + " 12950K .......... .......... .......... .......... .......... 28% 62.9M 1s\n", + " 13000K .......... .......... .......... .......... .......... 29% 40.3M 1s\n", + " 13050K .......... .......... .......... .......... .......... 29% 46.0M 1s\n", + " 13100K .......... .......... .......... .......... .......... 29% 64.1M 1s\n", + " 13150K .......... .......... .......... .......... .......... 29% 62.7M 1s\n", + " 13200K .......... .......... .......... .......... .......... 29% 56.9M 1s\n", + " 13250K .......... .......... .......... .......... .......... 29% 48.7M 1s\n", + " 13300K .......... .......... .......... .......... .......... 29% 47.6M 1s\n", + " 13350K .......... .......... .......... .......... .......... 29% 54.0M 1s\n", + " 13400K .......... .......... .......... .......... .......... 29% 51.4M 1s\n", + " 13450K .......... .......... .......... .......... .......... 30% 65.2M 1s\n", + " 13500K .......... .......... .......... .......... .......... 30% 52.1M 1s\n", + " 13550K .......... .......... .......... .......... .......... 30% 47.6M 1s\n", + " 13600K .......... .......... .......... .......... .......... 30% 51.0M 1s\n", + " 13650K .......... .......... .......... .......... .......... 30% 68.5M 1s\n", + " 13700K .......... .......... .......... .......... .......... 30% 64.7M 1s\n", + " 13750K .......... .......... .......... .......... .......... 30% 63.1M 1s\n", + " 13800K .......... .......... .......... .......... .......... 30% 44.6M 1s\n", + " 13850K .......... .......... .......... .......... .......... 30% 56.8M 1s\n", + " 13900K .......... .......... .......... .......... .......... 31% 70.3M 1s\n", + " 13950K .......... .......... .......... .......... .......... 31% 53.5M 1s\n", + " 14000K .......... .......... .......... .......... .......... 31% 64.5M 1s\n", + " 14050K .......... .......... .......... .......... .......... 31% 61.4M 1s\n", + " 14100K .......... .......... .......... .......... .......... 31% 54.2M 1s\n", + " 14150K .......... .......... .......... .......... .......... 31% 59.4M 1s\n", + " 14200K .......... .......... .......... .......... .......... 31% 57.7M 1s\n", + " 14250K .......... .......... .......... .......... .......... 31% 63.5M 1s\n", + " 14300K .......... .......... .......... .......... .......... 31% 72.3M 1s\n", + " 14350K .......... .......... .......... .......... .......... 32% 54.2M 1s\n", + " 14400K .......... .......... .......... .......... .......... 32% 46.8M 1s\n", + " 14450K .......... .......... .......... .......... .......... 32% 63.4M 1s\n", + " 14500K .......... .......... .......... .......... .......... 32% 59.4M 1s\n", + " 14550K .......... .......... .......... .......... .......... 32% 74.2M 1s\n", + " 14600K .......... .......... .......... .......... .......... 32% 52.0M 1s\n", + " 14650K .......... .......... .......... .......... .......... 32% 53.5M 1s\n", + " 14700K .......... .......... .......... .......... .......... 32% 62.2M 1s\n", + " 14750K .......... .......... .......... .......... .......... 32% 60.0M 1s\n", + " 14800K .......... .......... .......... .......... .......... 33% 54.0M 1s\n", + " 14850K .......... .......... .......... .......... .......... 33% 73.9M 1s\n", + " 14900K .......... .......... .......... .......... .......... 33% 65.4M 1s\n", + " 14950K .......... .......... .......... .......... .......... 33% 46.2M 1s\n", + " 15000K .......... .......... .......... .......... .......... 33% 48.7M 1s\n", + " 15050K .......... .......... .......... .......... .......... 33% 49.8M 1s\n", + " 15100K .......... .......... .......... .......... .......... 33% 62.4M 1s\n", + " 15150K .......... .......... .......... .......... .......... 33% 67.2M 1s\n", + " 15200K .......... .......... .......... .......... .......... 33% 53.4M 1s\n", + " 15250K .......... .......... .......... .......... .......... 34% 58.7M 1s\n", + " 15300K .......... .......... .......... .......... .......... 34% 69.3M 1s\n", + " 15350K .......... .......... .......... .......... .......... 34% 58.5M 1s\n", + " 15400K .......... .......... .......... .......... .......... 34% 53.0M 1s\n", + " 15450K .......... .......... .......... .......... .......... 34% 61.8M 1s\n", + " 15500K .......... .......... .......... .......... .......... 34% 60.1M 1s\n", + " 15550K .......... .......... .......... .......... .......... 34% 71.1M 1s\n", + " 15600K .......... .......... .......... .......... .......... 34% 53.9M 1s\n", + " 15650K .......... .......... .......... .......... .......... 34% 55.9M 1s\n", + " 15700K .......... .......... .......... .......... .......... 35% 3.84M 1s\n", + " 15750K .......... .......... .......... .......... .......... 35% 74.1M 1s\n", + " 15800K .......... .......... .......... .......... .......... 35% 3.90M 1s\n", + " 15850K .......... .......... .......... .......... .......... 35% 63.9M 1s\n", + " 15900K .......... .......... .......... .......... .......... 35% 61.2M 1s\n", + " 15950K .......... .......... .......... .......... .......... 35% 65.9M 1s\n", + " 16000K .......... .......... .......... .......... .......... 35% 58.2M 1s\n", + " 16050K .......... .......... .......... .......... .......... 35% 53.8M 1s\n", + " 16100K .......... .......... .......... .......... .......... 35% 46.9M 1s\n", + " 16150K .......... .......... .......... .......... .......... 36% 57.9M 1s\n", + " 16200K .......... .......... .......... .......... .......... 36% 37.3M 1s\n", + " 16250K .......... .......... .......... .......... .......... 36% 60.9M 1s\n", + " 16300K .......... .......... .......... .......... .......... 36% 58.7M 1s\n", + " 16350K .......... .......... .......... .......... .......... 36% 41.2M 1s\n", + " 16400K .......... .......... .......... .......... .......... 36% 55.0M 1s\n", + " 16450K .......... .......... .......... .......... .......... 36% 50.8M 1s\n", + " 16500K .......... .......... .......... .......... .......... 36% 67.0M 1s\n", + " 16550K .......... .......... .......... .......... .......... 36% 68.2M 1s\n", + " 16600K .......... .......... .......... .......... .......... 37% 43.9M 1s\n", + " 16650K .......... .......... .......... .......... .......... 37% 35.3M 1s\n", + " 16700K .......... .......... .......... .......... .......... 37% 55.5M 1s\n", + " 16750K .......... .......... .......... .......... .......... 37% 69.9M 1s\n", + " 16800K .......... .......... .......... .......... .......... 37% 48.0M 1s\n", + " 16850K .......... .......... .......... .......... .......... 37% 54.4M 1s\n", + " 16900K .......... .......... .......... .......... .......... 37% 46.1M 1s\n", + " 16950K .......... .......... .......... .......... .......... 37% 52.6M 1s\n", + " 17000K .......... .......... .......... .......... .......... 37% 56.6M 1s\n", + " 17050K .......... .......... .......... .......... .......... 38% 49.7M 1s\n", + " 17100K .......... .......... .......... .......... .......... 38% 53.5M 1s\n", + " 17150K .......... .......... .......... .......... .......... 38% 5.06M 1s\n", + " 17200K .......... .......... .......... .......... .......... 38% 61.1M 1s\n", + " 17250K .......... .......... .......... .......... .......... 38% 65.9M 1s\n", + " 17300K .......... .......... .......... .......... .......... 38% 57.0M 1s\n", + " 17350K .......... .......... .......... .......... .......... 38% 41.8M 1s\n", + " 17400K .......... .......... .......... .......... .......... 38% 48.3M 1s\n", + " 17450K .......... .......... .......... .......... .......... 38% 66.7M 1s\n", + " 17500K .......... .......... .......... .......... .......... 39% 61.2M 1s\n", + " 17550K .......... .......... .......... .......... .......... 39% 70.5M 1s\n", + " 17600K .......... .......... .......... .......... .......... 39% 31.7M 1s\n", + " 17650K .......... .......... .......... .......... .......... 39% 60.6M 1s\n", + " 17700K .......... .......... .......... .......... .......... 39% 71.8M 1s\n", + " 17750K .......... .......... .......... .......... .......... 39% 65.6M 1s\n", + " 17800K .......... .......... .......... .......... .......... 39% 51.9M 1s\n", + " 17850K .......... .......... .......... .......... .......... 39% 39.3M 1s\n", + " 17900K .......... .......... .......... .......... .......... 39% 57.0M 1s\n", + " 17950K .......... .......... .......... .......... .......... 40% 59.7M 1s\n", + " 18000K .......... .......... .......... .......... .......... 40% 57.9M 1s\n", + " 18050K .......... .......... .......... .......... .......... 40% 42.6M 1s\n", + " 18100K .......... .......... .......... .......... .......... 40% 52.5M 1s\n", + " 18150K .......... .......... .......... .......... .......... 40% 56.8M 1s\n", + " 18200K .......... .......... .......... .......... .......... 40% 48.8M 1s\n", + " 18250K .......... .......... .......... .......... .......... 40% 67.5M 1s\n", + " 18300K .......... .......... .......... .......... .......... 40% 70.4M 1s\n", + " 18350K .......... .......... .......... .......... .......... 40% 54.8M 1s\n", + " 18400K .......... .......... .......... .......... .......... 41% 36.8M 1s\n", + " 18450K .......... .......... .......... .......... .......... 41% 51.3M 1s\n", + " 18500K .......... .......... .......... .......... .......... 41% 61.8M 1s\n", + " 18550K .......... .......... .......... .......... .......... 41% 65.1M 1s\n", + " 18600K .......... .......... .......... .......... .......... 41% 48.8M 1s\n", + " 18650K .......... .......... .......... .......... .......... 41% 41.1M 1s\n", + " 18700K .......... .......... .......... .......... .......... 41% 52.9M 1s\n", + " 18750K .......... .......... .......... .......... .......... 41% 64.0M 1s\n", + " 18800K .......... .......... .......... .......... .......... 41% 55.5M 1s\n", + " 18850K .......... .......... .......... .......... .......... 42% 55.4M 1s\n", + " 18900K .......... .......... .......... .......... .......... 42% 62.6M 1s\n", + " 18950K .......... .......... .......... .......... .......... 42% 46.8M 1s\n", + " 19000K .......... .......... .......... .......... .......... 42% 38.0M 1s\n", + " 19050K .......... .......... .......... .......... .......... 42% 56.8M 1s\n", + " 19100K .......... .......... .......... .......... .......... 42% 57.0M 1s\n", + " 19150K .......... .......... .......... .......... .......... 42% 52.4M 1s\n", + " 19200K .......... .......... .......... .......... .......... 42% 34.9M 1s\n", + " 19250K .......... .......... .......... .......... .......... 42% 59.8M 1s\n", + " 19300K .......... .......... .......... .......... .......... 43% 57.5M 1s\n", + " 19350K .......... .......... .......... .......... .......... 43% 50.4M 1s\n", + " 19400K .......... .......... .......... .......... .......... 43% 28.5M 1s\n", + " 19450K .......... .......... .......... .......... .......... 43% 42.5M 1s\n", + " 19500K .......... .......... .......... .......... .......... 43% 58.6M 1s\n", + " 19550K .......... .......... .......... .......... .......... 43% 44.5M 1s\n", + " 19600K .......... .......... .......... .......... .......... 43% 40.7M 1s\n", + " 19650K .......... .......... .......... .......... .......... 43% 58.8M 1s\n", + " 19700K .......... .......... .......... .......... .......... 43% 60.0M 1s\n", + " 19750K .......... .......... .......... .......... .......... 44% 65.5M 1s\n", + " 19800K .......... .......... .......... .......... .......... 44% 50.9M 1s\n", + " 19850K .......... .......... .......... .......... .......... 44% 64.4M 1s\n", + " 19900K .......... .......... .......... .......... .......... 44% 61.2M 1s\n", + " 19950K .......... .......... .......... .......... .......... 44% 43.8M 1s\n", + " 20000K .......... .......... .......... .......... .......... 44% 57.4M 1s\n", + " 20050K .......... .......... .......... .......... .......... 44% 59.0M 1s\n", + " 20100K .......... .......... .......... .......... .......... 44% 38.2M 1s\n", + " 20150K .......... .......... .......... .......... .......... 44% 37.0M 1s\n", + " 20200K .......... .......... .......... .......... .......... 45% 45.8M 1s\n", + " 20250K .......... .......... .......... .......... .......... 45% 73.5M 1s\n", + " 20300K .......... .......... .......... .......... .......... 45% 58.9M 1s\n", + " 20350K .......... .......... .......... .......... .......... 45% 62.1M 1s\n", + " 20400K .......... .......... .......... .......... .......... 45% 54.3M 1s\n", + " 20450K .......... .......... .......... .......... .......... 45% 51.6M 1s\n", + " 20500K .......... .......... .......... .......... .......... 45% 69.9M 1s\n", + " 20550K .......... .......... .......... .......... .......... 45% 66.2M 1s\n", + " 20600K .......... .......... .......... .......... .......... 45% 43.9M 1s\n", + " 20650K .......... .......... .......... .......... .......... 46% 54.7M 1s\n", + " 20700K .......... .......... .......... .......... .......... 46% 46.2M 1s\n", + " 20750K .......... .......... .......... .......... .......... 46% 66.9M 1s\n", + " 20800K .......... .......... .......... .......... .......... 46% 47.8M 1s\n", + " 20850K .......... .......... .......... .......... .......... 46% 61.5M 1s\n", + " 20900K .......... .......... .......... .......... .......... 46% 60.1M 1s\n", + " 20950K .......... .......... .......... .......... .......... 46% 56.0M 1s\n", + " 21000K .......... .......... .......... .......... .......... 46% 45.6M 1s\n", + " 21050K .......... .......... .......... .......... .......... 46% 72.7M 1s\n", + " 21100K .......... .......... .......... .......... .......... 47% 2.44M 1s\n", + " 21150K .......... .......... .......... .......... .......... 47% 52.1M 1s\n", + " 21200K .......... .......... .......... .......... .......... 47% 49.1M 1s\n", + " 21250K .......... .......... .......... .......... .......... 47% 64.7M 1s\n", + " 21300K .......... .......... .......... .......... .......... 47% 64.4M 1s\n", + " 21350K .......... .......... .......... .......... .......... 47% 67.8M 1s\n", + " 21400K .......... .......... .......... .......... .......... 47% 41.6M 1s\n", + " 21450K .......... .......... .......... .......... .......... 47% 52.0M 1s\n", + " 21500K .......... .......... .......... .......... .......... 47% 68.1M 1s\n", + " 21550K .......... .......... .......... .......... .......... 48% 62.9M 1s\n", + " 21600K .......... .......... .......... .......... .......... 48% 49.1M 1s\n", + " 21650K .......... .......... .......... .......... .......... 48% 46.1M 1s\n", + " 21700K .......... .......... .......... .......... .......... 48% 30.1M 1s\n", + " 21750K .......... .......... .......... .......... .......... 48% 70.4M 1s\n", + " 21800K .......... .......... .......... .......... .......... 48% 55.7M 1s\n", + " 21850K .......... .......... .......... .......... .......... 48% 67.5M 1s\n", + " 21900K .......... .......... .......... .......... .......... 48% 57.2M 1s\n", + " 21950K .......... .......... .......... .......... .......... 48% 51.9M 1s\n", + " 22000K .......... .......... .......... .......... .......... 49% 53.5M 1s\n", + " 22050K .......... .......... .......... .......... .......... 49% 73.7M 1s\n", + " 22100K .......... .......... .......... .......... .......... 49% 68.5M 1s\n", + " 22150K .......... .......... .......... .......... .......... 49% 67.0M 1s\n", + " 22200K .......... .......... .......... .......... .......... 49% 50.9M 1s\n", + " 22250K .......... .......... .......... .......... .......... 49% 50.0M 1s\n", + " 22300K .......... .......... .......... .......... .......... 49% 4.03M 1s\n", + " 22350K .......... .......... .......... .......... .......... 49% 12.8M 1s\n", + " 22400K .......... .......... .......... .......... .......... 49% 42.8M 1s\n", + " 22450K .......... .......... .......... .......... .......... 50% 49.7M 1s\n", + " 22500K .......... .......... .......... .......... .......... 50% 54.6M 1s\n", + " 22550K .......... .......... .......... .......... .......... 50% 70.4M 1s\n", + " 22600K .......... .......... .......... .......... .......... 50% 50.6M 1s\n", + " 22650K .......... .......... .......... .......... .......... 50% 66.7M 1s\n", + " 22700K .......... .......... .......... .......... .......... 50% 49.3M 1s\n", + " 22750K .......... .......... .......... .......... .......... 50% 48.5M 1s\n", + " 22800K .......... .......... .......... .......... .......... 50% 57.7M 1s\n", + " 22850K .......... .......... .......... .......... .......... 50% 60.7M 1s\n", + " 22900K .......... .......... .......... .......... .......... 51% 63.6M 1s\n", + " 22950K .......... .......... .......... .......... .......... 51% 43.5M 1s\n", + " 23000K .......... .......... .......... .......... .......... 51% 31.7M 1s\n", + " 23050K .......... .......... .......... .......... .......... 51% 57.1M 1s\n", + " 23100K .......... .......... .......... .......... .......... 51% 45.9M 1s\n", + " 23150K .......... .......... .......... .......... .......... 51% 41.6M 1s\n", + " 23200K .......... .......... .......... .......... .......... 51% 31.3M 1s\n", + " 23250K .......... .......... .......... .......... .......... 51% 46.6M 1s\n", + " 23300K .......... .......... .......... .......... .......... 51% 52.3M 1s\n", + " 23350K .......... .......... .......... .......... .......... 52% 61.5M 1s\n", + " 23400K .......... .......... .......... .......... .......... 52% 47.4M 1s\n", + " 23450K .......... .......... .......... .......... .......... 52% 46.1M 1s\n", + " 23500K .......... .......... .......... .......... .......... 52% 66.5M 1s\n", + " 23550K .......... .......... .......... .......... .......... 52% 67.4M 1s\n", + " 23600K .......... .......... .......... .......... .......... 52% 62.5M 1s\n", + " 23650K .......... .......... .......... .......... .......... 52% 57.9M 1s\n", + " 23700K .......... .......... .......... .......... .......... 52% 62.7M 1s\n", + " 23750K .......... .......... .......... .......... .......... 53% 57.2M 1s\n", + " 23800K .......... .......... .......... .......... .......... 53% 53.4M 1s\n", + " 23850K .......... .......... .......... .......... .......... 53% 68.3M 1s\n", + " 23900K .......... .......... .......... .......... .......... 53% 55.1M 1s\n", + " 23950K .......... .......... .......... .......... .......... 53% 54.1M 1s\n", + " 24000K .......... .......... .......... .......... .......... 53% 58.7M 1s\n", + " 24050K .......... .......... .......... .......... .......... 53% 68.4M 1s\n", + " 24100K .......... .......... .......... .......... .......... 53% 64.2M 0s\n", + " 24150K .......... .......... .......... .......... .......... 53% 62.3M 0s\n", + " 24200K .......... .......... .......... .......... .......... 54% 55.8M 0s\n", + " 24250K .......... .......... .......... .......... .......... 54% 51.7M 0s\n", + " 24300K .......... .......... .......... .......... .......... 54% 52.4M 0s\n", + " 24350K .......... .......... .......... .......... .......... 54% 64.1M 0s\n", + " 24400K .......... .......... .......... .......... .......... 54% 58.2M 0s\n", + " 24450K .......... .......... .......... .......... .......... 54% 52.8M 0s\n", + " 24500K .......... .......... .......... .......... .......... 54% 52.5M 0s\n", + " 24550K .......... .......... .......... .......... .......... 54% 54.1M 0s\n", + " 24600K .......... .......... .......... .......... .......... 54% 46.9M 0s\n", + " 24650K .......... .......... .......... .......... .......... 55% 60.7M 0s\n", + " 24700K .......... .......... .......... .......... .......... 55% 58.2M 0s\n", + " 24750K .......... .......... .......... .......... .......... 55% 57.4M 0s\n", + " 24800K .......... .......... .......... .......... .......... 55% 48.2M 0s\n", + " 24850K .......... .......... .......... .......... .......... 55% 54.7M 0s\n", + " 24900K .......... .......... .......... .......... .......... 55% 69.3M 0s\n", + " 24950K .......... .......... .......... .......... .......... 55% 62.0M 0s\n", + " 25000K .......... .......... .......... .......... .......... 55% 49.7M 0s\n", + " 25050K .......... .......... .......... .......... .......... 55% 51.3M 0s\n", + " 25100K .......... .......... .......... .......... .......... 56% 63.0M 0s\n", + " 25150K .......... .......... .......... .......... .......... 56% 67.8M 0s\n", + " 25200K .......... .......... .......... .......... .......... 56% 58.1M 0s\n", + " 25250K .......... .......... .......... .......... .......... 56% 56.6M 0s\n", + " 25300K .......... .......... .......... .......... .......... 56% 57.7M 0s\n", + " 25350K .......... .......... .......... .......... .......... 56% 58.2M 0s\n", + " 25400K .......... .......... .......... .......... .......... 56% 46.1M 0s\n", + " 25450K .......... .......... .......... .......... .......... 56% 67.9M 0s\n", + " 25500K .......... .......... .......... .......... .......... 56% 60.6M 0s\n", + " 25550K .......... .......... .......... .......... .......... 57% 59.0M 0s\n", + " 25600K .......... .......... .......... .......... .......... 57% 43.5M 0s\n", + " 25650K .......... .......... .......... .......... .......... 57% 53.4M 0s\n", + " 25700K .......... .......... .......... .......... .......... 57% 50.1M 0s\n", + " 25750K .......... .......... .......... .......... .......... 57% 66.3M 0s\n", + " 25800K .......... .......... .......... .......... .......... 57% 47.4M 0s\n", + " 25850K .......... .......... .......... .......... .......... 57% 60.7M 0s\n", + " 25900K .......... .......... .......... .......... .......... 57% 44.9M 0s\n", + " 25950K .......... .......... .......... .......... .......... 57% 57.8M 0s\n", + " 26000K .......... .......... .......... .......... .......... 58% 50.9M 0s\n", + " 26050K .......... .......... .......... .......... .......... 58% 32.9M 0s\n", + " 26100K .......... .......... .......... .......... .......... 58% 4.58M 0s\n", + " 26150K .......... .......... .......... .......... .......... 58% 60.7M 0s\n", + " 26200K .......... .......... .......... .......... .......... 58% 55.3M 0s\n", + " 26250K .......... .......... .......... .......... .......... 58% 66.4M 0s\n", + " 26300K .......... .......... .......... .......... .......... 58% 64.6M 0s\n", + " 26350K .......... .......... .......... .......... .......... 58% 63.9M 0s\n", + " 26400K .......... .......... .......... .......... .......... 58% 62.4M 0s\n", + " 26450K .......... .......... .......... .......... .......... 59% 62.2M 0s\n", + " 26500K .......... .......... .......... .......... .......... 59% 46.8M 0s\n", + " 26550K .......... .......... .......... .......... .......... 59% 60.1M 0s\n", + " 26600K .......... .......... .......... .......... .......... 59% 52.4M 0s\n", + " 26650K .......... .......... .......... .......... .......... 59% 64.4M 0s\n", + " 26700K .......... .......... .......... .......... .......... 59% 59.9M 0s\n", + " 26750K .......... .......... .......... .......... .......... 59% 58.0M 0s\n", + " 26800K .......... .......... .......... .......... .......... 59% 55.4M 0s\n", + " 26850K .......... .......... .......... .......... .......... 59% 61.9M 0s\n", + " 26900K .......... .......... .......... .......... .......... 60% 64.3M 0s\n", + " 26950K .......... .......... .......... .......... .......... 60% 64.5M 0s\n", + " 27000K .......... .......... .......... .......... .......... 60% 52.0M 0s\n", + " 27050K .......... .......... .......... .......... .......... 60% 72.2M 0s\n", + " 27100K .......... .......... .......... .......... .......... 60% 60.5M 0s\n", + " 27150K .......... .......... .......... .......... .......... 60% 63.4M 0s\n", + " 27200K .......... .......... .......... .......... .......... 60% 58.9M 0s\n", + " 27250K .......... .......... .......... .......... .......... 60% 70.7M 0s\n", + " 27300K .......... .......... .......... .......... .......... 60% 3.80M 0s\n", + " 27350K .......... .......... .......... .......... .......... 61% 65.8M 0s\n", + " 27400K .......... .......... .......... .......... .......... 61% 53.4M 0s\n", + " 27450K .......... .......... .......... .......... .......... 61% 62.8M 0s\n", + " 27500K .......... .......... .......... .......... .......... 61% 67.4M 0s\n", + " 27550K .......... .......... .......... .......... .......... 61% 63.8M 0s\n", + " 27600K .......... .......... .......... .......... .......... 61% 8.78M 0s\n", + " 27650K .......... .......... .......... .......... .......... 61% 51.2M 0s\n", + " 27700K .......... .......... .......... .......... .......... 61% 69.2M 0s\n", + " 27750K .......... .......... .......... .......... .......... 61% 64.8M 0s\n", + " 27800K .......... .......... .......... .......... .......... 62% 14.8M 0s\n", + " 27850K .......... .......... .......... .......... .......... 62% 66.1M 0s\n", + " 27900K .......... .......... .......... .......... .......... 62% 64.1M 0s\n", + " 27950K .......... .......... .......... .......... .......... 62% 15.7M 0s\n", + " 28000K .......... .......... .......... .......... .......... 62% 53.4M 0s\n", + " 28050K .......... .......... .......... .......... .......... 62% 65.5M 0s\n", + " 28100K .......... .......... .......... .......... .......... 62% 17.9M 0s\n", + " 28150K .......... .......... .......... .......... .......... 62% 68.0M 0s\n", + " 28200K .......... .......... .......... .......... .......... 62% 56.8M 0s\n", + " 28250K .......... .......... .......... .......... .......... 63% 15.2M 0s\n", + " 28300K .......... .......... .......... .......... .......... 63% 53.4M 0s\n", + " 28350K .......... .......... .......... .......... .......... 63% 66.9M 0s\n", + " 28400K .......... .......... .......... .......... .......... 63% 15.5M 0s\n", + " 28450K .......... .......... .......... .......... .......... 63% 47.1M 0s\n", + " 28500K .......... .......... .......... .......... .......... 63% 64.6M 0s\n", + " 28550K .......... .......... .......... .......... .......... 63% 17.5M 0s\n", + " 28600K .......... .......... .......... .......... .......... 63% 45.6M 0s\n", + " 28650K .......... .......... .......... .......... .......... 63% 68.0M 0s\n", + " 28700K .......... .......... .......... .......... .......... 64% 17.7M 0s\n", + " 28750K .......... .......... .......... .......... .......... 64% 47.4M 0s\n", + " 28800K .......... .......... .......... .......... .......... 64% 51.4M 0s\n", + " 28850K .......... .......... .......... .......... .......... 64% 67.1M 0s\n", + " 28900K .......... .......... .......... .......... .......... 64% 20.3M 0s\n", + " 28950K .......... .......... .......... .......... .......... 64% 47.4M 0s\n", + " 29000K .......... .......... .......... .......... .......... 64% 55.9M 0s\n", + " 29050K .......... .......... .......... .......... .......... 64% 17.5M 0s\n", + " 29100K .......... .......... .......... .......... .......... 64% 53.0M 0s\n", + " 29150K .......... .......... .......... .......... .......... 65% 67.1M 0s\n", + " 29200K .......... .......... .......... .......... .......... 65% 16.4M 0s\n", + " 29250K .......... .......... .......... .......... .......... 65% 51.0M 0s\n", + " 29300K .......... .......... .......... .......... .......... 65% 63.4M 0s\n", + " 29350K .......... .......... .......... .......... .......... 65% 17.8M 0s\n", + " 29400K .......... .......... .......... .......... .......... 65% 47.3M 0s\n", + " 29450K .......... .......... .......... .......... .......... 65% 60.7M 0s\n", + " 29500K .......... .......... .......... .......... .......... 65% 16.0M 0s\n", + " 29550K .......... .......... .......... .......... .......... 65% 55.9M 0s\n", + " 29600K .......... .......... .......... .......... .......... 66% 53.7M 0s\n", + " 29650K .......... .......... .......... .......... .......... 66% 17.4M 0s\n", + " 29700K .......... .......... .......... .......... .......... 66% 48.3M 0s\n", + " 29750K .......... .......... .......... .......... .......... 66% 57.4M 0s\n", + " 29800K .......... .......... .......... .......... .......... 66% 18.2M 0s\n", + " 29850K .......... .......... .......... .......... .......... 66% 44.6M 0s\n", + " 29900K .......... .......... .......... .......... .......... 66% 58.9M 0s\n", + " 29950K .......... .......... .......... .......... .......... 66% 44.8M 0s\n", + " 30000K .......... .......... .......... .......... .......... 66% 21.1M 0s\n", + " 30050K .......... .......... .......... .......... .......... 67% 52.8M 0s\n", + " 30100K .......... .......... .......... .......... .......... 67% 67.9M 0s\n", + " 30150K .......... .......... .......... .......... .......... 67% 15.1M 0s\n", + " 30200K .......... .......... .......... .......... .......... 67% 47.8M 0s\n", + " 30250K .......... .......... .......... .......... .......... 67% 69.0M 0s\n", + " 30300K .......... .......... .......... .......... .......... 67% 16.1M 0s\n", + " 30350K .......... .......... .......... .......... .......... 67% 53.8M 0s\n", + " 30400K .......... .......... .......... .......... .......... 67% 59.5M 0s\n", + " 30450K .......... .......... .......... .......... .......... 67% 17.7M 0s\n", + " 30500K .......... .......... .......... .......... .......... 68% 46.3M 0s\n", + " 30550K .......... .......... .......... .......... .......... 68% 65.0M 0s\n", + " 30600K .......... .......... .......... .......... .......... 68% 15.4M 0s\n", + " 30650K .......... .......... .......... .......... .......... 68% 56.1M 0s\n", + " 30700K .......... .......... .......... .......... .......... 68% 49.7M 0s\n", + " 30750K .......... .......... .......... .......... .......... 68% 21.7M 0s\n", + " 30800K .......... .......... .......... .......... .......... 68% 48.6M 0s\n", + " 30850K .......... .......... .......... .......... .......... 68% 58.1M 0s\n", + " 30900K .......... .......... .......... .......... .......... 68% 17.4M 0s\n", + " 30950K .......... .......... .......... .......... .......... 69% 50.3M 0s\n", + " 31000K .......... .......... .......... .......... .......... 69% 38.2M 0s\n", + " 31050K .......... .......... .......... .......... .......... 69% 25.7M 0s\n", + " 31100K .......... .......... .......... .......... .......... 69% 41.4M 0s\n", + " 31150K .......... .......... .......... .......... .......... 69% 43.1M 0s\n", + " 31200K .......... .......... .......... .......... .......... 69% 53.8M 0s\n", + " 31250K .......... .......... .......... .......... .......... 69% 19.6M 0s\n", + " 31300K .......... .......... .......... .......... .......... 69% 43.1M 0s\n", + " 31350K .......... .......... .......... .......... .......... 69% 54.3M 0s\n", + " 31400K .......... .......... .......... .......... .......... 70% 20.3M 0s\n", + " 31450K .......... .......... .......... .......... .......... 70% 39.1M 0s\n", + " 31500K .......... .......... .......... .......... .......... 70% 58.8M 0s\n", + " 31550K .......... .......... .......... .......... .......... 70% 21.4M 0s\n", + " 31600K .......... .......... .......... .......... .......... 70% 35.1M 0s\n", + " 31650K .......... .......... .......... .......... .......... 70% 53.7M 0s\n", + " 31700K .......... .......... .......... .......... .......... 70% 22.3M 0s\n", + " 31750K .......... .......... .......... .......... .......... 70% 50.0M 0s\n", + " 31800K .......... .......... .......... .......... .......... 70% 36.5M 0s\n", + " 31850K .......... .......... .......... .......... .......... 71% 26.4M 0s\n", + " 31900K .......... .......... .......... .......... .......... 71% 31.6M 0s\n", + " 31950K .......... .......... .......... .......... .......... 71% 36.0M 0s\n", + " 32000K .......... .......... .......... .......... .......... 71% 39.8M 0s\n", + " 32050K .......... .......... .......... .......... .......... 71% 27.4M 0s\n", + " 32100K .......... .......... .......... .......... .......... 71% 55.0M 0s\n", + " 32150K .......... .......... .......... .......... .......... 71% 59.9M 0s\n", + " 32200K .......... .......... .......... .......... .......... 71% 16.7M 0s\n", + " 32250K .......... .......... .......... .......... .......... 71% 45.7M 0s\n", + " 32300K .......... .......... .......... .......... .......... 72% 41.7M 0s\n", + " 32350K .......... .......... .......... .......... .......... 72% 26.9M 0s\n", + " 32400K .......... .......... .......... .......... .......... 72% 53.8M 0s\n", + " 32450K .......... .......... .......... .......... .......... 72% 4.50M 0s\n", + " 32500K .......... .......... .......... .......... .......... 72% 40.2M 0s\n", + " 32550K .......... .......... .......... .......... .......... 72% 55.8M 0s\n", + " 32600K .......... .......... .......... .......... .......... 72% 19.8M 0s\n", + " 32650K .......... .......... .......... .......... .......... 72% 61.0M 0s\n", + " 32700K .......... .......... .......... .......... .......... 72% 56.5M 0s\n", + " 32750K .......... .......... .......... .......... .......... 73% 65.0M 0s\n", + " 32800K .......... .......... .......... .......... .......... 73% 17.5M 0s\n", + " 32850K .......... .......... .......... .......... .......... 73% 63.3M 0s\n", + " 32900K .......... .......... .......... .......... .......... 73% 43.8M 0s\n", + " 32950K .......... .......... .......... .......... .......... 73% 18.1M 0s\n", + " 33000K .......... .......... .......... .......... .......... 73% 43.4M 0s\n", + " 33050K .......... .......... .......... .......... .......... 73% 40.7M 0s\n", + " 33100K .......... .......... .......... .......... .......... 73% 23.8M 0s\n", + " 33150K .......... .......... .......... .......... .......... 73% 52.7M 0s\n", + " 33200K .......... .......... .......... .......... .......... 74% 37.4M 0s\n", + " 33250K .......... .......... .......... .......... .......... 74% 24.5M 0s\n", + " 33300K .......... .......... .......... .......... .......... 74% 39.4M 0s\n", + " 33350K .......... .......... .......... .......... .......... 74% 38.5M 0s\n", + " 33400K .......... .......... .......... .......... .......... 74% 18.5M 0s\n", + " 33450K .......... .......... .......... .......... .......... 74% 50.3M 0s\n", + " 33500K .......... .......... .......... .......... .......... 74% 66.9M 0s\n", + " 33550K .......... .......... .......... .......... .......... 74% 47.5M 0s\n", + " 33600K .......... .......... .......... .......... .......... 74% 29.1M 0s\n", + " 33650K .......... .......... .......... .......... .......... 75% 37.2M 0s\n", + " 33700K .......... .......... .......... .......... .......... 75% 56.9M 0s\n", + " 33750K .......... .......... .......... .......... .......... 75% 23.6M 0s\n", + " 33800K .......... .......... .......... .......... .......... 75% 30.9M 0s\n", + " 33850K .......... .......... .......... .......... .......... 75% 68.8M 0s\n", + " 33900K .......... .......... .......... .......... .......... 75% 22.6M 0s\n", + " 33950K .......... .......... .......... .......... .......... 75% 53.7M 0s\n", + " 34000K .......... .......... .......... .......... .......... 75% 50.3M 0s\n", + " 34050K .......... .......... .......... .......... .......... 75% 47.4M 0s\n", + " 34100K .......... .......... .......... .......... .......... 76% 25.3M 0s\n", + " 34150K .......... .......... .......... .......... .......... 76% 40.6M 0s\n", + " 34200K .......... .......... .......... .......... .......... 76% 44.4M 0s\n", + " 34250K .......... .......... .......... .......... .......... 76% 4.47M 0s\n", + " 34300K .......... .......... .......... .......... .......... 76% 64.1M 0s\n", + " 34350K .......... .......... .......... .......... .......... 76% 66.5M 0s\n", + " 34400K .......... .......... .......... .......... .......... 76% 17.1M 0s\n", + " 34450K .......... .......... .......... .......... .......... 76% 54.3M 0s\n", + " 34500K .......... .......... .......... .......... .......... 76% 62.9M 0s\n", + " 34550K .......... .......... .......... .......... .......... 77% 64.5M 0s\n", + " 34600K .......... .......... .......... .......... .......... 77% 16.4M 0s\n", + " 34650K .......... .......... .......... .......... .......... 77% 52.9M 0s\n", + " 34700K .......... .......... .......... .......... .......... 77% 65.8M 0s\n", + " 34750K .......... .......... .......... .......... .......... 77% 20.6M 0s\n", + " 34800K .......... .......... .......... .......... .......... 77% 45.5M 0s\n", + " 34850K .......... .......... .......... .......... .......... 77% 59.5M 0s\n", + " 34900K .......... .......... .......... .......... .......... 77% 65.4M 0s\n", + " 34950K .......... .......... .......... .......... .......... 77% 19.9M 0s\n", + " 35000K .......... .......... .......... .......... .......... 78% 42.8M 0s\n", + " 35050K .......... .......... .......... .......... .......... 78% 60.7M 0s\n", + " 35100K .......... .......... .......... .......... .......... 78% 19.3M 0s\n", + " 35150K .......... .......... .......... .......... .......... 78% 49.6M 0s\n", + " 35200K .......... .......... .......... .......... .......... 78% 52.8M 0s\n", + " 35250K .......... .......... .......... .......... .......... 78% 22.8M 0s\n", + " 35300K .......... .......... .......... .......... .......... 78% 70.8M 0s\n", + " 35350K .......... .......... .......... .......... .......... 78% 68.0M 0s\n", + " 35400K .......... .......... .......... .......... .......... 78% 55.7M 0s\n", + " 35450K .......... .......... .......... .......... .......... 79% 16.7M 0s\n", + " 35500K .......... .......... .......... .......... .......... 79% 3.84M 0s\n", + " 35550K .......... .......... .......... .......... .......... 79% 68.3M 0s\n", + " 35600K .......... .......... .......... .......... .......... 79% 57.4M 0s\n", + " 35650K .......... .......... .......... .......... .......... 79% 63.8M 0s\n", + " 35700K .......... .......... .......... .......... .......... 79% 64.3M 0s\n", + " 35750K .......... .......... .......... .......... .......... 79% 23.6M 0s\n", + " 35800K .......... .......... .......... .......... .......... 79% 9.25M 0s\n", + " 35850K .......... .......... .......... .......... .......... 79% 13.7M 0s\n", + " 35900K .......... .......... .......... .......... .......... 80% 71.4M 0s\n", + " 35950K .......... .......... .......... .......... .......... 80% 55.6M 0s\n", + " 36000K .......... .......... .......... .......... .......... 80% 59.9M 0s\n", + " 36050K .......... .......... .......... .......... .......... 80% 14.9M 0s\n", + " 36100K .......... .......... .......... .......... .......... 80% 64.2M 0s\n", + " 36150K .......... .......... .......... .......... .......... 80% 14.7M 0s\n", + " 36200K .......... .......... .......... .......... .......... 80% 17.6M 0s\n", + " 36250K .......... .......... .......... .......... .......... 80% 31.7M 0s\n", + " 36300K .......... .......... .......... .......... .......... 80% 35.8M 0s\n", + " 36350K .......... .......... .......... .......... .......... 81% 63.6M 0s\n", + " 36400K .......... .......... .......... .......... .......... 81% 15.5M 0s\n", + " 36450K .......... .......... .......... .......... .......... 81% 53.1M 0s\n", + " 36500K .......... .......... .......... .......... .......... 81% 68.6M 0s\n", + " 36550K .......... .......... .......... .......... .......... 81% 14.9M 0s\n", + " 36600K .......... .......... .......... .......... .......... 81% 35.9M 0s\n", + " 36650K .......... .......... .......... .......... .......... 81% 16.6M 0s\n", + " 36700K .......... .......... .......... .......... .......... 81% 53.5M 0s\n", + " 36750K .......... .......... .......... .......... .......... 81% 15.8M 0s\n", + " 36800K .......... .......... .......... .......... .......... 82% 40.5M 0s\n", + " 36850K .......... .......... .......... .......... .......... 82% 33.2M 0s\n", + " 36900K .......... .......... .......... .......... .......... 82% 19.0M 0s\n", + " 36950K .......... .......... .......... .......... .......... 82% 61.1M 0s\n", + " 37000K .......... .......... .......... .......... .......... 82% 13.9M 0s\n", + " 37050K .......... .......... .......... .......... .......... 82% 43.4M 0s\n", + " 37100K .......... .......... .......... .......... .......... 82% 34.8M 0s\n", + " 37150K .......... .......... .......... .......... .......... 82% 18.2M 0s\n", + " 37200K .......... .......... .......... .......... .......... 82% 5.73M 0s\n", + " 37250K .......... .......... .......... .......... .......... 83% 66.1M 0s\n", + " 37300K .......... .......... .......... .......... .......... 83% 65.9M 0s\n", + " 37350K .......... .......... .......... .......... .......... 83% 14.2M 0s\n", + " 37400K .......... .......... .......... .......... .......... 83% 50.2M 0s\n", + " 37450K .......... .......... .......... .......... .......... 83% 15.7M 0s\n", + " 37500K .......... .......... .......... .......... .......... 83% 36.9M 0s\n", + " 37550K .......... .......... .......... .......... .......... 83% 70.1M 0s\n", + " 37600K .......... .......... .......... .......... .......... 83% 13.0M 0s\n", + " 37650K .......... .......... .......... .......... .......... 83% 61.5M 0s\n", + " 37700K .......... .......... .......... .......... .......... 84% 17.3M 0s\n", + " 37750K .......... .......... .......... .......... .......... 84% 40.8M 0s\n", + " 37800K .......... .......... .......... .......... .......... 84% 38.9M 0s\n", + " 37850K .......... .......... .......... .......... .......... 84% 16.0M 0s\n", + " 37900K .......... .......... .......... .......... .......... 84% 49.1M 0s\n", + " 37950K .......... .......... .......... .......... .......... 84% 17.9M 0s\n", + " 38000K .......... .......... .......... .......... .......... 84% 30.6M 0s\n", + " 38050K .......... .......... .......... .......... .......... 84% 40.9M 0s\n", + " 38100K .......... .......... .......... .......... .......... 84% 18.9M 0s\n", + " 38150K .......... .......... .......... .......... .......... 85% 42.4M 0s\n", + " 38200K .......... .......... .......... .......... .......... 85% 16.2M 0s\n", + " 38250K .......... .......... .......... .......... .......... 85% 42.0M 0s\n", + " 38300K .......... .......... .......... .......... .......... 85% 58.5M 0s\n", + " 38350K .......... .......... .......... .......... .......... 85% 14.4M 0s\n", + " 38400K .......... .......... .......... .......... .......... 85% 46.1M 0s\n", + " 38450K .......... .......... .......... .......... .......... 85% 19.2M 0s\n", + " 38500K .......... .......... .......... .......... .......... 85% 27.7M 0s\n", + " 38550K .......... .......... .......... .......... .......... 85% 68.3M 0s\n", + " 38600K .......... .......... .......... .......... .......... 86% 14.6M 0s\n", + " 38650K .......... .......... .......... .......... .......... 86% 31.2M 0s\n", + " 38700K .......... .......... .......... .......... .......... 86% 22.9M 0s\n", + " 38750K .......... .......... .......... .......... .......... 86% 24.3M 0s\n", + " 38800K .......... .......... .......... .......... .......... 86% 32.5M 0s\n", + " 38850K .......... .......... .......... .......... .......... 86% 20.4M 0s\n", + " 38900K .......... .......... .......... .......... .......... 86% 27.2M 0s\n", + " 38950K .......... .......... .......... .......... .......... 86% 36.9M 0s\n", + " 39000K .......... .......... .......... .......... .......... 86% 16.3M 0s\n", + " 39050K .......... .......... .......... .......... .......... 87% 54.7M 0s\n", + " 39100K .......... .......... .......... .......... .......... 87% 25.5M 0s\n", + " 39150K .......... .......... .......... .......... .......... 87% 28.6M 0s\n", + " 39200K .......... .......... .......... .......... .......... 87% 28.1M 0s\n", + " 39250K .......... .......... .......... .......... .......... 87% 22.3M 0s\n", + " 39300K .......... .......... .......... .......... .......... 87% 34.9M 0s\n", + " 39350K .......... .......... .......... .......... .......... 87% 24.3M 0s\n", + " 39400K .......... .......... .......... .......... .......... 87% 30.1M 0s\n", + " 39450K .......... .......... .......... .......... .......... 87% 28.9M 0s\n", + " 39500K .......... .......... .......... .......... .......... 88% 14.2M 0s\n", + " 39550K .......... .......... .......... .......... .......... 88% 54.5M 0s\n", + " 39600K .......... .......... .......... .......... .......... 88% 35.3M 0s\n", + " 39650K .......... .......... .......... .......... .......... 88% 19.5M 0s\n", + " 39700K .......... .......... .......... .......... .......... 88% 59.2M 0s\n", + " 39750K .......... .......... .......... .......... .......... 88% 27.1M 0s\n", + " 39800K .......... .......... .......... .......... .......... 88% 18.5M 0s\n", + " 39850K .......... .......... .......... .......... .......... 88% 43.5M 0s\n", + " 39900K .......... .......... .......... .......... .......... 88% 17.7M 0s\n", + " 39950K .......... .......... .......... .......... .......... 89% 41.7M 0s\n", + " 40000K .......... .......... .......... .......... .......... 89% 41.1M 0s\n", + " 40050K .......... .......... .......... .......... .......... 89% 20.3M 0s\n", + " 40100K .......... .......... .......... .......... .......... 89% 52.6M 0s\n", + " 40150K .......... .......... .......... .......... .......... 89% 31.6M 0s\n", + " 40200K .......... .......... .......... .......... .......... 89% 15.8M 0s\n", + " 40250K .......... .......... .......... .......... .......... 89% 44.5M 0s\n", + " 40300K .......... .......... .......... .......... .......... 89% 18.7M 0s\n", + " 40350K .......... .......... .......... .......... .......... 89% 39.9M 0s\n", + " 40400K .......... .......... .......... .......... .......... 90% 38.7M 0s\n", + " 40450K .......... .......... .......... .......... .......... 90% 20.0M 0s\n", + " 40500K .......... .......... .......... .......... .......... 90% 44.7M 0s\n", + " 40550K .......... .......... .......... .......... .......... 90% 56.8M 0s\n", + " 40600K .......... .......... .......... .......... .......... 90% 12.4M 0s\n", + " 40650K .......... .......... .......... .......... .......... 90% 55.3M 0s\n", + " 40700K .......... .......... .......... .......... .......... 90% 33.5M 0s\n", + " 40750K .......... .......... .......... .......... .......... 90% 23.3M 0s\n", + " 40800K .......... .......... .......... .......... .......... 90% 40.1M 0s\n", + " 40850K .......... .......... .......... .......... .......... 91% 38.0M 0s\n", + " 40900K .......... .......... .......... .......... .......... 91% 23.4M 0s\n", + " 40950K .......... .......... .......... .......... .......... 91% 40.1M 0s\n", + " 41000K .......... .......... .......... .......... .......... 91% 15.7M 0s\n", + " 41050K .......... .......... .......... .......... .......... 91% 37.7M 0s\n", + " 41100K .......... .......... .......... .......... .......... 91% 50.1M 0s\n", + " 41150K .......... .......... .......... .......... .......... 91% 19.6M 0s\n", + " 41200K .......... .......... .......... .......... .......... 91% 46.8M 0s\n", + " 41250K .......... .......... .......... .......... .......... 91% 59.3M 0s\n", + " 41300K .......... .......... .......... .......... .......... 92% 15.1M 0s\n", + " 41350K .......... .......... .......... .......... .......... 92% 51.8M 0s\n", + " 41400K .......... .......... .......... .......... .......... 92% 42.5M 0s\n", + " 41450K .......... .......... .......... .......... .......... 92% 17.8M 0s\n", + " 41500K .......... .......... .......... .......... .......... 92% 56.5M 0s\n", + " 41550K .......... .......... .......... .......... .......... 92% 40.5M 0s\n", + " 41600K .......... .......... .......... .......... .......... 92% 17.9M 0s\n", + " 41650K .......... .......... .......... .......... .......... 92% 59.2M 0s\n", + " 41700K .......... .......... .......... .......... .......... 92% 13.9M 0s\n", + " 41750K .......... .......... .......... .......... .......... 93% 51.9M 0s\n", + " 41800K .......... .......... .......... .......... .......... 93% 3.70M 0s\n", + " 41850K .......... .......... .......... .......... .......... 93% 64.2M 0s\n", + " 41900K .......... .......... .......... .......... .......... 93% 66.9M 0s\n", + " 41950K .......... .......... .......... .......... .......... 93% 62.6M 0s\n", + " 42000K .......... .......... .......... .......... .......... 93% 15.7M 0s\n", + " 42050K .......... .......... .......... .......... .......... 93% 55.0M 0s\n", + " 42100K .......... .......... .......... .......... .......... 93% 64.1M 0s\n", + " 42150K .......... .......... .......... .......... .......... 93% 17.1M 0s\n", + " 42200K .......... .......... .......... .......... .......... 94% 43.1M 0s\n", + " 42250K .......... .......... .......... .......... .......... 94% 65.8M 0s\n", + " 42300K .......... .......... .......... .......... .......... 94% 15.4M 0s\n", + " 42350K .......... .......... .......... .......... .......... 94% 34.0M 0s\n", + " 42400K .......... .......... .......... .......... .......... 94% 31.7M 0s\n", + " 42450K .......... .......... .......... .......... .......... 94% 31.7M 0s\n", + " 42500K .......... .......... .......... .......... .......... 94% 35.5M 0s\n", + " 42550K .......... .......... .......... .......... .......... 94% 65.8M 0s\n", + " 42600K .......... .......... .......... .......... .......... 94% 18.7M 0s\n", + " 42650K .......... .......... .......... .......... .......... 95% 45.3M 0s\n", + " 42700K .......... .......... .......... .......... .......... 95% 64.2M 0s\n", + " 42750K .......... .......... .......... .......... .......... 95% 18.2M 0s\n", + " 42800K .......... .......... .......... .......... .......... 95% 53.8M 0s\n", + " 42850K .......... .......... .......... .......... .......... 95% 62.4M 0s\n", + " 42900K .......... .......... .......... .......... .......... 95% 14.6M 0s\n", + " 42950K .......... .......... .......... .......... .......... 95% 59.3M 0s\n", + " 43000K .......... .......... .......... .......... .......... 95% 48.1M 0s\n", + " 43050K .......... .......... .......... .......... .......... 95% 17.5M 0s\n", + " 43100K .......... .......... .......... .......... .......... 96% 40.4M 0s\n", + " 43150K .......... .......... .......... .......... .......... 96% 41.0M 0s\n", + " 43200K .......... .......... .......... .......... .......... 96% 22.2M 0s\n", + " 43250K .......... .......... .......... .......... .......... 96% 49.5M 0s\n", + " 43300K .......... .......... .......... .......... .......... 96% 57.3M 0s\n", + " 43350K .......... .......... .......... .......... .......... 96% 18.0M 0s\n", + " 43400K .......... .......... .......... .......... .......... 96% 38.7M 0s\n", + " 43450K .......... .......... .......... .......... .......... 96% 67.2M 0s\n", + " 43500K .......... .......... .......... .......... .......... 96% 19.2M 0s\n", + " 43550K .......... .......... .......... .......... .......... 97% 41.0M 0s\n", + " 43600K .......... .......... .......... .......... .......... 97% 56.1M 0s\n", + " 43650K .......... .......... .......... .......... .......... 97% 17.1M 0s\n", + " 43700K .......... .......... .......... .......... .......... 97% 52.3M 0s\n", + " 43750K .......... .......... .......... .......... .......... 97% 61.2M 0s\n", + " 43800K .......... .......... .......... .......... .......... 97% 19.4M 0s\n", + " 43850K .......... .......... .......... .......... .......... 97% 48.0M 0s\n", + " 43900K .......... .......... .......... .......... .......... 97% 51.8M 0s\n", + " 43950K .......... .......... .......... .......... .......... 97% 18.6M 0s\n", + " 44000K .......... .......... .......... .......... .......... 98% 29.0M 0s\n", + " 44050K .......... .......... .......... .......... .......... 98% 60.0M 0s\n", + " 44100K .......... .......... .......... .......... .......... 98% 66.2M 0s\n", + " 44150K .......... .......... .......... .......... .......... 98% 23.0M 0s\n", + " 44200K .......... .......... .......... .......... .......... 98% 25.2M 0s\n", + " 44250K .......... .......... .......... .......... .......... 98% 67.7M 0s\n", + " 44300K .......... .......... .......... .......... .......... 98% 24.4M 0s\n", + " 44350K .......... .......... .......... .......... .......... 98% 31.0M 0s\n", + " 44400K .......... .......... .......... .......... .......... 98% 57.3M 0s\n", + " 44450K .......... .......... .......... .......... .......... 99% 26.4M 0s\n", + " 44500K .......... .......... .......... .......... .......... 99% 31.0M 0s\n", + " 44550K .......... .......... .......... .......... .......... 99% 57.1M 0s\n", + " 44600K .......... .......... .......... .......... .......... 99% 21.6M 0s\n", + " 44650K .......... .......... .......... .......... .......... 99% 27.4M 0s\n", + " 44700K .......... .......... .......... .......... .......... 99% 54.7M 0s\n", + " 44750K .......... .......... .......... .......... .......... 99% 29.8M 0s\n", + " 44800K .......... .......... .......... .......... .......... 99% 31.8M 0s\n", + " 44850K .......... .......... .......... .......... .......... 99% 54.6M 0s\n", + " 44900K ... 100% 7.37T=1.3s\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Opening dataset from [oceanspy_particle_properties.nc].\n" ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2023-04-03 22:14:05 (34.7 MB/s) - ‘oceanspy_particle_properties.nc’ saved [45981653/45981653]\n", + "\n" + ] } ], "source": [ @@ -331,14 +1592,22 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:06.376442Z", + "iopub.status.busy": "2023-04-04T02:14:06.375793Z", + "iopub.status.idle": "2023-04-04T02:14:06.409345Z", + "shell.execute_reply": "2023-04-04T02:14:06.403005Z", + "shell.execute_reply.started": "2023-04-04T02:14:06.376365Z" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", - "Dimensions: (particle: 3954, time: 121, time_midp: 120)\n", + "Dimensions: (time: 121, particle: 3954, time_midp: 120)\n", "Coordinates:\n", " * particle (particle) int64 0 1 2 3 4 5 6 ... 3948 3949 3950 3951 3952 3953\n", " * time (time) datetime64[ns] 2008-02-29 ... 2008-03-30\n", @@ -383,7 +1652,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:06.413597Z", + "iopub.status.busy": "2023-04-04T02:14:06.412931Z", + "iopub.status.idle": "2023-04-04T02:14:06.828086Z", + "shell.execute_reply": "2023-04-04T02:14:06.825564Z", + "shell.execute_reply.started": "2023-04-04T02:14:06.413541Z" + } + }, "outputs": [ { "name": "stdout", @@ -429,7 +1706,15 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:06.833109Z", + "iopub.status.busy": "2023-04-04T02:14:06.832520Z", + "iopub.status.idle": "2023-04-04T02:14:07.340455Z", + "shell.execute_reply": "2023-04-04T02:14:07.337912Z", + "shell.execute_reply.started": "2023-04-04T02:14:06.833051Z" + } + }, "outputs": [ { "name": "stdout", @@ -437,32 +1722,19 @@ "text": [ "Computing gradient.\n", "\n", - "Dimensions: (particle: 3954, time: 121, time_midp: 120)\n", + "Dimensions: (time: 121, particle: 3954, time_midp: 120)\n", "Coordinates:\n", " * particle (particle) int64 0 1 2 3 4 5 ... 3949 3950 3951 3952 3953\n", - " * time_midp (time_midp) datetime64[ns] 2008-02-29T03:00:00 ... 2008-...\n", " * time (time) datetime64[ns] 2008-02-29 ... 2008-03-30\n", - "Data variables:\n", - " XC (time, particle) float64 ...\n", - " YC (time, particle) float64 ...\n", - " Z (time, particle) float64 ...\n", - " Zl (time, particle) float64 ...\n", - " Zp1 (time, particle) float64 ...\n", - " Zu (time, particle) float64 ...\n", - " XG (time, particle) float64 ...\n", - " YG (time, particle) float64 ...\n", - " Depth (time, particle) float64 ...\n", - " Temp (time, particle) float64 2.098 2.098 1.979 ... 1.123 2.757\n", - " S (time, particle) float64 35.13 35.13 35.11 ... 34.52 34.87\n", - " momVort3 (time, particle) float64 ...\n", - " Sigma0 (time, particle) float64 28.06 28.06 28.06 ... 27.65 27.8\n", - " dXC_dtime (time_midp, particle) float64 -2.036e-06 ... -2.036e-06\n", - " dYC_dtime (time_midp, particle) float64 0.0 0.0 0.0 ... 0.0 8.841e-07\n", - " dZ_dtime (time_midp, particle) float64 -0.0003472 -0.0003472 ... 0.0\n", - " dZl_dtime (time_midp, particle) float64 0.0 0.0 0.0 ... 0.0 0.0006944\n", - " dZp1_dtime (time_midp, particle) float64 0.0 0.0 0.0 ... 0.0 0.0006944\n", - " dZu_dtime (time_midp, particle) float64 0.0 0.0 0.0 ... 0.0 0.0006944\n", - " dXG_dtime (time_midp, particle) float64 -2.036e-06 ... -2.036e-06\n", + " * time_midp (time_midp) datetime64[ns] 2008-02-29T03:00:00 ... 2008-...\n", + "Data variables: (12/26)\n", + " XC (time, particle) float64 -24.62 -24.62 ... -29.45 -31.48\n", + " YC (time, particle) float64 65.49 65.49 65.49 ... 67.82 66.79\n", + " Z (time, particle) float64 -23.5 -23.5 ... -276.5 -351.5\n", + " Zl (time, particle) float64 -27.0 -27.0 ... -269.0 -344.0\n", + " Zp1 (time, particle) float64 -27.0 -27.0 ... -269.0 -344.0\n", + " Zu (time, particle) float64 -27.0 -27.0 ... -269.0 -344.0\n", + " ... ...\n", " dYG_dtime (time_midp, particle) float64 -8.841e-07 0.0 ... 0.0 0.0\n", " dDepth_dtime (time_midp, particle) float64 4.819e-05 ... -0.000665\n", " dTemp_dtime (time_midp, particle) float64 -3.942e-07 ... -1.581e-07\n", @@ -495,7 +1767,15 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:07.344241Z", + "iopub.status.busy": "2023-04-04T02:14:07.343642Z", + "iopub.status.idle": "2023-04-04T02:14:08.249060Z", + "shell.execute_reply": "2023-04-04T02:14:08.246775Z", + "shell.execute_reply.started": "2023-04-04T02:14:07.344184Z" + } + }, "outputs": [], "source": [ "# Overflow mask\n", @@ -530,54 +1810,34 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:08.254042Z", + "iopub.status.busy": "2023-04-04T02:14:08.252878Z", + "iopub.status.idle": "2023-04-04T02:14:34.683376Z", + "shell.execute_reply": "2023-04-04T02:14:34.680449Z", + "shell.execute_reply.started": "2023-04-04T02:14:08.253941Z" + } + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n", - ":13: DeprecationWarning: The background_patch property is deprecated. Use GeoAxes.patch instead.\n", - " ax.background_patch.set_facecolor(land_col)\n" - ] - }, { "data": { - "image/png": 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\n", 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Use GeoAxes.patch instead.\n", - " ax.background_patch.set_facecolor(land_col)\n" - ] - }, { "data": { - "image/png": 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\n", 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"text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -632,7 +1892,15 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:34.686469Z", + "iopub.status.busy": "2023-04-04T02:14:34.685821Z", + "iopub.status.idle": "2023-04-04T02:14:48.111732Z", + "shell.execute_reply": "2023-04-04T02:14:48.096357Z", + "shell.execute_reply.started": "2023-04-04T02:14:34.686409Z" + } + }, "outputs": [ { "name": "stdout", @@ -648,20 +1916,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/oceanspy/plot.py:305: UserWarning: No contour levels were found within the data range.\n", + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/oceanspy/plot.py:306: UserWarning: No contour levels were found within the data range.\n", " CS = ax.contour(s.values, t.values, dens.values, **contour_kwargs)\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -714,7 +1980,15 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:48.115817Z", + "iopub.status.busy": "2023-04-04T02:14:48.115150Z", + "iopub.status.idle": "2023-04-04T02:14:48.137585Z", + "shell.execute_reply": "2023-04-04T02:14:48.134350Z", + "shell.execute_reply.started": "2023-04-04T02:14:48.115760Z" + } + }, "outputs": [], "source": [ "nparts = 5\n", @@ -734,30 +2008,24 @@ { "cell_type": "code", "execution_count": 14, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:48.143180Z", + "iopub.status.busy": "2023-04-04T02:14:48.141626Z", + "iopub.status.idle": "2023-04-04T02:14:52.246919Z", + "shell.execute_reply": "2023-04-04T02:14:52.244502Z", + "shell.execute_reply.started": "2023-04-04T02:14:48.143124Z" + } + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n", - ":12: DeprecationWarning: The background_patch property is deprecated. Use GeoAxes.patch instead.\n", - " ax.background_patch.set_facecolor(land_col)\n" - ] - }, { "data": { - "image/png": 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\n", + "image/png": 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G/4gICAjYpDCYpJjc3Y3uRgPdjQYmdXehwTmmTpiAqRMmYNKkCVjX348Ng4PYMDiIaRMnjEg7NC0qSVPzWRkCqflThkI+OS2jLkmpksilGfUq0dnMM+UjvZ99HIHBNMVgmqKZJCYh3mCWBd3XNqO+RV70Li1Ityf/nbSz4r92oXjuzJJ55dlfVxShO44Rk4R2lMJkZ4FXf4NpioGkiYFmgmaaomkm603Tlym5DlR1zOK315gsWueQxaDQetzr7NJTdHwPLSec83OV0ug40ufT12xibX+/UtVqNokxkiJpJkiaCdJEQGQULG10iDTNKFrS0LVkRuUSqQCPI68dUBg7qf0dyCeLelJcqEhTdxxjhPanz+Cjx/ElQaSfeRRllCxmGSM84iaRoW4fPSbjXMs5mX1UMkSYbPGN7i50TVB/yhih+3vaYrKWM/XH6v/5zt+l/9GyNObHGA6xkiVWCSarY1u0jHGhDVKarO35flp9S/cxDJUrSRLLGKF9kfc9N31bFXND28K5UjSLYqVuFlDEvHnz8MUvfhG/+93v8Lvf/Q5ve9vb8K53vQt//OMfAQBf/vKX8dWvfhVf//rX8dvf/hazZ8/GEUccgbVr15o6zjnnHNxyyy24+eabcc8992DdunU49thjkWY0YgA4+eST8dBDD2HJkiVYsmQJHnroIZx66qmjfr4UwUMSEBAQEBAQEBAQQDCcHpI1a9ZY37u7u9Hd3V0o9853vtP6/vnPfx6LFy/G/fffj1133RVXXHEFPvnJT+L4448HAPzHf/wHZs2ahRtvvBGnn346ent78e1vfxvf+973cPjhhwMArr/+esyfPx933nknFi5ciMcffxxLlizB/fffj/322w8A8M1vfhMHHHAAli1bhp133nlYzrldBIMkICBgVMEZw8RGwygLASrB4sSuLgBKaUgF9SpK18o1a7B8r4uwev16U75n0iRMnTgRPRMnmjqBYvC1lX8io/+Y7yRgnMJdYbeCkrMVb0ppcvdTdCkJTmg6ScYbSYQACGWLBrVr9SogV91yPR96NV+fm49CNFT4+sSFflGb/hQCkgEiy57XIF4RN3+JOR99LvR8GIOQKSJCO4k4h4jzz5LluU2kZFYeE3qcMsqW3uZStFL3ehKvEfWa+MaHOS7Zh4EVgtg1LU8LHjTTJPOKZEkPhVTeEa2kBaWyJcjqtmkzYdMoj0qKZDDRXVs4X9PGilwXlrfC5x0BAJEf2/VKlY1F38TOPS4Ak6DQBJuTsUITJzLGTNkqah7lrfGYI27EiLtiQ9kyiREjuy67bfq87fvQ9Uj62mB+F9Lrhay6d3kUeY9B96tDpyy0xdmFOFEAAKKZWuOEHtMeR6IwDtzrzDMvilWPST4ZYfyDw1Uxax+qb+bPn29t/exnP4uLL764cs80TfGf//mfWL9+PQ444AA8/fTTWLFiBY488khTpru7G4ceeijuvfdenH766Vi6dCmazaZVZu7cudh9991x7733YuHChbjvvvvQ09NjjBEA2H///dHT04N77713zAyStn1mL774It73vvdhyy23xKRJk/CmN70JS5cuNb+vW7cOZ511FubNm4eJEydil112weLFi606li1bhoMOOgjz5s3DJZdcYv22YMECMMZw//33W9vPOeccHHbYYe02NyAgICAgICAgIGDM8Pzzz6O3t9f8XXTRRaVlH3nkEUyZMgXd3d0444wzcMstt2DXXXfFihUrAACzZs2yys+aNcv8tmLFCnR1dWGLLbaoLDNz5szCcWfOnGnKjAXa8pCsWrUKBx10EN761rfijjvuwMyZM/Hkk09aQTDnnnsufvnLX+L666/HggUL8LOf/Qwf/ehHMXfuXLzrXe8CAJx55pk49dRTse++++KMM87A29/+dhx00EGmjgkTJuDjH/847r777uE5y4CAgHGDraZOxWCSoDtWjx/OGOKIY0LmIZmYJGhEkVlRXL66F1tMmlTKSwdQurotpT94GYAJlAbKZW1bxY5499WriKR+KufLSBxInulcFLKhu94Rt/3tQC92ViltlnlGdMB6fj4c4AIAN+2NOIeUEhGpX0gJyQDGItN2N0DfF5wupURCVlylSAG18I+IsUwmWK9oAyB95vvXf66yuFRM2+CRPXaviYSdoyOVrjcrPx8afN6XxYoAQP+gyshuPCZJoqShSYC6FI5niZyfEUFIBZJBFXOi+41H3F5hdz0sUoLH3Ej2AhVeESn1Qq91XB9KY0/MMYqeEsbgeEDMj6YczdweNSIT8+Gu5BdiiHjudYm7Yit4XHtHCsetAZ+Xwo0bMd+zpV8p/GVd8IiDZfdUdfZz7c2qI/KQf6ZdVNfJ4o5BxhjAs/sUDFI4IgPu+VmxPgxsI4ghGU7K1rRp0zBt2rRaZXfeeWc89NBDWL16NX74wx/iAx/4gDUfLhPlqIJbpkyIYbSD+CnaMki+9KUvYf78+bj22mvNtgULFlhl7rvvPnzgAx8w3ozTTjsN3/jGN/C73/3OGCSrV6/GXnvthT333BNz585Fb2+vVcfpp5+OxYsX4/bbb8fRRx/dwWkFBASMV8ycNg0v9/YailZ/swnOuDFQuuJIBUdnkwTOgA0Zfct9WLqGSBHSTMJTnSNB07vgn1S48OWRqEOVcAOe9XF8AdhVxkDZhEd/r1Kccl8wQlYbJVUwtBpoqpT+Rs+DtJXQzwAY46Sq73wvQyHzOvqbTcRCoJHRPRpRlOVVYJAyN0yo4VP2gi0Yex5KjXSuoUvLqtqH7qvbM5imJnAdQC5skFG2RCKy/CFk0u8xtESqftfJEpPBptrPGWe+tplEiKnMAqULhdS/KsJZbRJOHc6YtAKYM2OkENRcGsgOsEgFOxeoU0ZlSxkNmqZFVbYMz0N4JlQsV7bSxog65zxZI+fcJBr0Pg+cm4YVvpdP6l0qG01o6DOk2r0180SSpB5vGadmmg/FeZ7VooF5qW2y0qJzhQPGcuJbF2PVzq6uLrz+9a8HAOyzzz747W9/i6997Wv4+Mc/DkB5OObMmWPKr1y50nhNZs+ejcHBQaxatcrykqxcuRIHHnigKfPyyy8XjvvKK68UvC+jibZM1FtvvRX77LMPTjjhBMycORN77bUXvvnNb1plDj74YNx666148cUXIaXEL3/5S/zpT3/CwoULTZlLLrkERxxxBCZNmgTOufUboIycM844AxdddFHlSkxAQEBAQEBAQEDApgopJQYGBrD99ttj9uzZ+PnPf25+GxwcxN13322Mjb333huNRsMqs3z5cjz66KOmzAEHHIDe3l48+OCDpswDDzyA3t5eU2Ys0JaH5KmnnsLixYtx3nnn4ROf+AQefPBBLFq0CN3d3Xj/+98PALjyyivxkY98BPPmzUMcqxWJb33rWzj44INNPUcffTReeeUVrFmzBltvvbX3WJ/61Kdw7bXX4oYbbmhbiqwpOZpy9AKmkuxYySgec3NC6N+Rx2j2cZqmmDFpEgaz3AsNxgAhYNIWiCwgPAsEl2DQa4d67S5JEiTNJgZaaNlzssLlZg0HqmkTAFmVJgHqdLva1poilGbnmjSb3lVsTfehnoYyqpj2iKRZ+yWzV55dFLxKVl355zIvTdGbo+hONGhY5oUL+2hPCaQEHV06kN+0E8rL4V4jIM9vItIUIk2RZh6SNBMq4IxBZLSnwWYTDadeS1rV8XiVgXrCLMnlkra5ddN+0AIOA4ODaCYJ+kgOnsGBAQz2N7PKhJL5Ffmyu8yEEHQ/ilQqEYEkgcxWupnM8tGQrOe+wHZGaWZMQi1qZx7DzINoxguDWvFW7Dxwnt9HUZm3I8vQzhgzx+ERc1bSc9oVoAOftfRs7rnQ0rK6Di35q/ahngzd3/Y50xwmuo+irN6I1MOyfsgqVO1zvUD0ojMYL5PZByjnRJGfcucTg+SOp4R6r5JUuV5oHdlxKAuVGR5dvo0zQGR1cnJwQaiNRkoZucct9+ZkY4W7FDNYNKuyHCX2Jud5m6syd+ypHU2MhYfkE5/4BN7xjndg/vz5WLt2LW6++WbcddddWLJkCRhjOOecc3DZZZdhxx13xI477ojLLrsMkyZNwsknnwwA6OnpwYc//GGcf/752HLLLTFjxgxccMEF2GOPPYzq1i677IKjjjoKH/nIR/CNb3wDgGIzHXvssWMW0A60aZAIIbDPPvvgsssuAwDstdde+OMf/4jFixdbBsn999+PW2+9Fdtttx1+9atf4aMf/SjmzJljOgNQygBlxggAbL311rjgggvwmc98Bu9973vbOqk700MwKZ3U1j7DgTvFIaN+zM0JoX9HHqPSx7/61cgfY5zi945YR8Dw49Hf/nasm9AWprQqEGV/xlDTGxoj16gK7POG2WNyXAXh/FsFPZkW+deBweFv0ghgRt+6kT0AteOANrgyZKdas0fXfM+/b+BJ3YOOGZTxNFSDpGaQToaXX34Zp556KpYvX46enh7sueeeWLJkCY444ggAwIUXXoi+vj589KMfNYkRf/azn2Hq1KmmjssvvxxxHOPEE080iRGvu+46RETZ7IYbbsCiRYuMGtdxxx2Hr3/960M816GByTZ047bbbjscccQR+Na3vmW2LV68GP/yL/+CF198EX19fejp6cEtt9yCY445xpT5h3/4B7zwwgtYsmRJy2MsWLAA55xzDs455xysW7cOr3/96/HP//zPeOaZZ/DQQw/hrrvuKt13zZo16Onpwcrvn4Fpk4r6ziOFREa4UxyCw/mvELO09Q4BbSH078hjNPu4928+p1acs1Vj/Qjqz3j0qzZsQDPJX1ZmRZV4QyZ2dWFio2HiUMokRWmMhfpMytRkbLsZzGmb1Ta/h8SKIUgS/P7++7HX/vsjiuM8lqQkg7cvoN1F7vlpz0NCUcdD4p4LDe52z12XSkv6xIVLyfWV97XfxBdxjpgp6V+Zpnhs6VLsts8+iOI4HzcevrsbC2La42yiHhJ9vlZsUMW5mX3T1IxtnQBRS1onQqCfeEjSTHJVZdhWtSdNLfubx35IIZAmCZqZzG/aVLK/uZhD7r2yT9DxXnmCsMvGC+cMb95xa/zuiRVGpAHI7it9b3IVRM4Zt4KbXRldHkeIG5moBbe9IroQlYzlEc+lgHV73WB/0848QJ2RjOCcc/BGZAWxm0eKZ4xQlMn8lkJKb/fTbQURhuwaz+hbh9e6J+WuBG8skNXs0u+6XpHJTevjuR5D19vho8prqWRdZ5qkxhOjJ+6uyIAv2F57xPo2bMB5J5+A3t7e2sHeowU9l5w6dQvjtesUUgqsXbtqXJ7neENbHpKDDjoIy5Yts7b96U9/wnbbbQcAaDabaDab+cMpQxRFHcWCTJkyBZ/+9Kdx8cUXF5LFVKHBBBpjMHGNWTomx91cEPp35DEafdzViJEKiSR7TjTiGDHnEFmeka5m05rouUYFkCnncA5JJx9ghUk6ffFyZ2JUlzJAJ6kqoFs6vxcn32UTliiOEcdxIUCaOQZJVFKvO2FyA9qHYpDYdKrSXezg6hLDIxWioFRV1idVRpiePEUl1DxDWePcmJc8isCjyJ7cOnQ9l4Knj0WPQoOMeRSZ7Ouc0L0olcc3npJUIBECzSwqvCkEBoVAmpVtSgkhWU46Yiwzeox4mDFW8+9qMpg0BZKmzlWSU8qyxqt/KoLRfao7jOxbBiHzflP7Mwg9jsEBCUiOfCLH7M6R0EIFWSU8m7jqCTgyo4LDWAwsisw9r85LZvVIaM+Rvtd161nEs4zv2uDJ819werF4a1qOzPY33935jHvDMFawJej9To0QegyQMSsZy/YnfefJDULrs+h2eh+mxpWkdZNjSUD1q7mXAcaLczaHpZbtI0wdUiqWGe0nH41Lgqkx0p7jYEzAGB+yQRJQH20ZJOeeey4OPPBAXHbZZTjxxBPx4IMP4pprrsE111wDQMmaHXroofjYxz6GiRMnYrvttsPdd9+N7373u/jqV7/aUQNPO+00XH755bjpppusJC4BAQEbJ5ThYG+TUqIrU9maNnEiIs7NqnIZJHIlIpUsD2aJXsAvKUtRpjhV11MgnMmd77O7jXoXfGglJUpRxxjpFG6/0D7Rq8WMMeN9cM+HnodRvGKsxCuRHUwIr8eh6rxMjIYQQOZxS7N4CzqN0Mkq6blVJreUumzRADRtlABnznmDWcZOKpRBYmSfpUCSphjUSQ+bSaaO5bSBjBEpBEQqjUdR7aM8JHqFWqSi4BUpM0ZajVXLSKGdqL0VMYdMZP47jSFhzHgguFauInK9+pjKq1KMQymTJZVCQjAJRpTUCgpWZrEi/x41IssDw5221F2VqGybLD5I3IUR4VxjfU5mfxe6nVJWehxMM2rJ/pZ7f5DbFmoESxQWlunxGOcF46h4CrzwnDf1RLmy2XjG8MSQjP/zHC9oy/Tbd999ccstt+Cmm27C7rvvjksvvRRXXHEFTjnlFFPm5ptvxr777otTTjkFu+66K774xS/i85//PM4444yOGthoNHDppZeiv7+/o/0DAgICAgICAgICAsYv2vKQAMCxxx6LY489tvT32bNnW3lK2sUzzzxT2HbSSSfhpJNO6rjOgICA8YOIc0iRWqvoTv5CMMYwZcIEAMD6gQHjWYjJql0qJJrZqrGi9HAYirk04kDmOCJbNXfzctRBG6F2pG6/p6SOwhNAVldJPa28PnXRrsJNoTxjBa+J9bM+T4er7kJImSsFcW6UpEzZNs5X154KgSg7tu+4omTFsuoaC7IaT9JeVMarSimRiNQodKltbhlk8SKZpyP7LETO69cxJUJ7VRIVfyVSu4xVr0lhIr3/VqFI/7HziDDOwWO/d0LnB6G5PnTMQN42aRL/6X1cz4UvuZ7rFdFKWXSM0PiQqBGh0dUgbYSXnlX2XXtf9So5vR9pTEkVTdL0N1fjxmJBOSpW7v4sUl4I4zek94S0br78HkJxjJW1sQDzaGWAkCUJLMmzUwgwYV9XSgNknHljSHx1jVcED8noom2DJCAgIGAo0JKgrmHg0mVc2hJ156ZCmOzguqyiB6nfNX1LAGYWwDK6jesWLtAvasBH16qicxUmjJ4YhjIMlxGS1zd89ZQJA0imqFhWXIZv4uaJmxFSGBpX3Ym0lNJQqXRsgTZuOKGY0bYDuXEinUlmnT7X9C2LAkXiZlQMCvOOC04mrDQJokiF+dNxClJoo4SM9VTUHqt1UTrBltLECADqmuu4DF3emvRnH4xhEDuULS6VURMRg4XZCRoZiSfxgWcxJzQQnjFmBb5HsYoVYSTZIvOOBfockuY7zxSJ9DWzkn5W0Z/0edLJOWMQECbmyEfJbEnjJOdQFZPr2iu+9voolvp6KQqac12dYHVTJwk8S9O0QC9zg+etmL4Wku3jAwxDNyiCQVIXG8OICAgICAgICAgICAjYRBE8JAEBAaMK3+pimQyrLl9G99H7aEqMVmNKhVop5JCQkgTcslxtxnxvY6W5TiB7VaJECen1jgxltbuKUlBU5er4MF5vSNmxI6avg6iUAKaJ2wDlMeGSkVVpUSrF6343HjbYXiktcGDtl3npdFB6atgw1avVFC4lzzd+OWMmcaPVRurZIx4SmVG1BFHMEkIUk9A5517nt7pjjPYnk5quJQ09jUfMcKryIGeb3kW3aW+I8cAgk+A1weY2PUyDrqBrKphJdkileyNC/SLbNe3JXYl3vSNUwU177Kwy8NMvy7wsQJHWVSoeQGhbbnlZQsdjnIFna8mCCEZkhQtfzXXQ3kCPp4MTL5Yea4zBVsyKkHvtJCxxEsWQZNa4dfuI5sBwfxuvCCpbo4tgkAQEBIwqtPyuS5Ww5HVrvKwURSuj+/DcKAFc40OXYZAyn4Co2BWbA18HrSha7m9AcbLqy2dCUWaE+crV2T5UmlYrY6RM8Svi3FDmFI2rWkEsys5bT12E5EjS1MQY1aG4SSmVEUSN1MKE0VbIqtvfOpaJfvflqVGfJVKp4kesGBRCuUmTVMWDJPl3ZaQoZS19DG9gABwDqqL9ZYZWKypPfjLEaGTMsFC0XK9Lw1EGRF7GF6dhxYkwm95jFLF4/j0iUs6qTljUMBOLEuX3tG+MUlqWSzXjYAWlNzqG9f60Pnc7kBvEpj+dgcsJ3VTzVKriSfS/2vgqU6hyn03MYySrfZllbFgxMdn14hG3jAhlGBOqITlfzhlYzCCy2CarDc41Y9m505wy4xdDjyGRboBkQCk2hhEREBAQEBAQEBAQELCJInhIAgICRgz8mKsAOCuvJAs7UJ6VPF+JVJQaK2DUSTCWinIvSb6fWrWVIs3qVcnAKJ2nTHHHR88qo2+5bbTPCWDlC9kt0clq3XAFsXcK02YJRAyWt6NVHgwOII4icl0VF8+3mGytJDMqHKC8JWYVP98hPw5TAe7tUqB83hG6Sq3Pke47mKZIs4SGJoDdM5aqFLIYZ95kfDIt36eVd6TqfIvCD6SviUKWpk3pz7SMhsiuBSPUKlPOBLoruhX9Tf2e08A0hSvPus6UmhWp1+dpdROkqnOyf7f7qTgmy1A6frSnx7pm9rOF8fzmMF4jJ2jfPY6mwrnPqaocJwVKnWffuBGDxw7VTeZ9q6lZhm6mqXSIAKRZfbb3iX6hlL3xjOFQ2doYqGnjBcEgCQgIGFUUDAWX3lCyj+93Gjui40YA9f5XdRZVXjRlSzCRlbPbwj0vfoqyGJEqGV/fBLoVRajTF5lPTapQpkL5pZUcsSlHJkI+9ai8DXZ8gKEvQapJdEVMDWNKXU2aelV5mtzQhTvN0RQu0y+cZ3EBrLx/svHmUvGqklrqY9nnrpIh5oazSoyYJrlBAunI90ppJzXM5FTpJNNL76mgDVpxIc4kv06sCVOq2vl3c0l1IkTbqLDUlCL7OBy8qKgF2PVo+WBqXES2EeOjaHESr0PrLkM9amimqEbGpGusccYsxThfzAkASKMZLdXiiLPQwqgx59Dg8vbYMS7upFmrZOnPrRZbCosuXNG6LBqX3jfSRXhGebXHmIpvsWNFqiia4x3BIBldjH8TNSAgICAgICAgICBgk0XwkAQEBAw7NFXLhXBWjwHl4Kcrz3oFUFZo7etyGmlGAzEr9CRYlRt6l73qF3EOyZhVhoHZq+klx2zlRWgVfF1X8agdDNUzQsu450e/0zrc1U/fyrC7Yh2RFVkhZa7exHJPievVslZzZd4eylxqtbpmUakAMCktda0qelOnYGBoRDEGuaYJZp4XHdSephDCHvv6X7s9/vOooneV0XXclXG3r93yUaySGBpaDudgsVoFj+IIUcTB48jaRwWk599hHVd5xqJsH1XeVsRyKVqAygtitYEpdShD2dL71FiR7mTROh+3KOSf0cfXTywOVcbtW+NBgci8JP57SeVZKY5oxjIviq0AYpdBflOUBVQzZu9ntSNVbRMkvN+9DxG5x1E0Ls45WFfuvpQeWialm413BA/J6CIYJAEBAcMK1xih1Bc9USpyuCvoWmAA7H3Ue1CYybFWZzKvUJnHhrjGiX5Ja7UdSuPSx+HOBLxMJatdtKKmtYOyF53PGKljiNSFzxhzEwAC/vbVOXfafh3XQQ1NmiGd0rdST5t87RFSmvHiixEabtD2U9oPoCbWglF+loRIHQqjhyI4HM31Un8iVqicca6SDOq5aCMCi3KDhKoxuUaIqZcxK2aBsVwy1tCUsuOoeoqqWxaFK8q/R5ZBMvR+UXLQ9FmjYoX0eNKnRp8jVLlLgyZuTUsNRHVE9ZkZjS9GEjra5TXtsGQ7YFGpGPndNY50e1Nn4YfFEaLM4KNUQzpeOKG9ZpUijmObXhaVxF1pg6RhU7vGI4ZD9jfYI/URDJKAgIBKuAaGuO3slmXoi0hn31afMzlUIYxkb5KmSIQwL0YJaV6A+rtbp8+gcVe5qXECwMgA5+/0PMbE8poQI0Ydy39e7aDT/eqsrtUJWpfEA1TruB4jrFX9ZXW78SWuFyWP3ynuy5k02dR1Wb36TPdp1VbbezQ8MwT3mL7A+FS6ZewA76InpDxOpJWBJ6sdiqUwRgTnhYktjdUwBkkcmVgObYyUGSK6jPJomBMxcSb03MoC4s3vWdA6QDwkZGLtu6zuOI48k0vba5sfT1rj1q2cIc1GoTJunV+ZHYOkv1sxGVFmFJN99MBWHib1LKJ5Uso8kNTYoJ4Z93d3PyDP3UQXjdQiTX7eZTF8VDY9ItcEyLzWnGf1ZOVl7s1O4jD9DLARRkRAQEBAQEBAQEAAQaBsjS6CQRIQEFCJgqJMSXwILUtpABJ50kPNnxcy94joz/p7mnHqy5RqNGhyOyFtFoNvRU9RfWz6TxWNC/Bk+Cb1DyeGyxPSClWejOGoW0NTuGyanf96Gs+JrqfiumsPFqPxIFkcillphu0JqurbKgUi13PRajyW1U2RpGmeXRv5yj+lm4kWsVMW3amCcuY7h8J5chSUq1xEEVfxHSz/Lh3JXn8bKUULuefEoV/l24p1uBQtXWdEjl92eQ3FCvm97GtnxOyx4hsTrhdV6ECSDCkEpLS9gG68FFgxxsp3TeixI8dr5V6d3JOh62Pm3tDnzJjf40n7hSZqTIUoPCdi7veYUu+N9lYZj2gUWb/rPmxk9L50o/CQ+LxjndQRUAcbw4gICAgYJ/DRplx6lpR5fgadh0G/pIQQhq6VS2RmdbdDEXJe5Nro8cnOukjJhKOKxgVoo8V+ofiMlE4MlKp96hgfrmFRW663ZGIyWiijTOnJjM+YLPDfs+1pZkBSmkrZqmYnVC1qLCmpYH/8DODp1+w8tNSv73w450hI4K/Oct0KjDNwyUuze7soNarppN+J21BlVIxHFEVkTNoUISllnsmdS0XviuzcJDRfCJDRvujlYHZmdpWVHSZY3g1W19/1ZFujruQvXXDw/OilcbmWDx1vELlR4qtXB8GXxRK5x+IslzimlDQ3t4cb7+K7lcsMHuk8B3Wl1IioC30+kUPRcp8ttF+bG4VBEjCaCCMiICAgICAgICAggCBQtkYXwSAJCAiohHe1EEXZXSD3VOTeD2lWifU+qQlqz7f5VnBNcGSFt8NIvjJ/W63vnv21xC+lcUWcBhfbUqIsq9NdAS2jXrQD1yvSrueibKUeKKqC0WO145nqBGXB7GVlBe1LQssDYAW4A/lKL2esoLLVDsokb027kFP+CvuW9F8dRTWd8ZrWWyrZq1WqJMuCietfNzs4PKdBUa+Ekc/VUrss95hQShXjzBzZBJdn+0SN2NTJiXoWLeNmaNd1MsYQZcpLjTjO6EoV54Si14T+W0/+16Oo5dA2vXWJXBSXMwZwDiYZoaFWX5tWAg8RuS6UWsW4f4zWOVc3OJ6X7Os+NzXK1PVMe5363Mk8HddCyo3CQ6LOYagqWyP7fN2UMP5HREBAwJiAHX2l+rfkd0vK16FoUWPDyjGCYuZgM+khspoq83omgSlZQW1Jo4ra5MuybYFSKHR9QJbxXb9cVXwC/b3MKBkK9HmUSdXWgelXhy/uY/VUGSjDAc1B901uXNWtVqDnwxmMOpuuw6XDdNxmDx3RBWfMGMhCIouHUt/jjBsvyKQLUEavcOrWE0spVZZ2TdVqFT9S2mZNlaygEpr7LHLuO4eiRSqHhL8vcjoWM7LAervODUINHKrg5VPYApSBpOWDoyzjetU1bWWAuNvLFlYUFSrfLjy/W7l3kClfkWtFJX7VwYTX2KBlIs6L8R6ZVJo6d4/SmGfF3pU7dttaoHXBNhbc/vH1l89AjqPI0LMixgvXwwd9v3DGIBqN0nIBmyeCQRIQEBAQEBAQEBBAEChbo4tgkAQEBLQFd+XMVdGiOUR8Qe7uyqFKL5AnJ5QitYLJ1Sp7lpNC2vtpuEo6Vhsdb4GVeE/aVC4dvJx/Z8ZLQn8frpeU7xzo76pM9bHcANkqmlBZcHNF4ueOofPJlMGivOhtzip/FR3KV17XV8dbQr1chTGJ1tdYSonBJMk9JkIgjqJcrYgEtCdaQU4KK8eI8pDkylvGkyhyGlfZ9ay6zj76GVMnZQXUUwqQbkPMI9MGxvPkhyZ1qBDmqsQ8Vr/T3CpCKlUsTTkylC1C4YrssS5lFgxfQZvzbS/LsUFBV/6pN0TVUyxf5XHQ3730JcYsWpQUqe158Xjg6LEYGHQvc3KNaLtcGpv2ftTxTnCnDH0G0edgTn/N93W92pypcRIbjxa9h/N6XE+sVmdz86uMVwSDZHQRDJKAgAAv3AepnSiMUlPsCSL9lxojGpr2kiti2dQRzjjAbdOAZZM7PY/xJfqjkxk/Vcj+V5WTXqMkGoWXiM8YaWWIuJxst5wxTkg8iW9iQOFONty4HLeN3jrKDAciH+peMx234Rq4vpihKiPJp8rVCu6xfRLRdEyUGVYR5+D6OngmWIlIjbIcACSpgExFboAI+/gyt+xJHJMnUaJ091ObfVQoAJYxYiakmfKVmRBnk0tDteri4Jyh0d2lsrNndXVN7M4NkkYM7mQVz6lgeXMpTYtmWTe/Z5PtuGSSWkXLqk39y6hXvuJVVbRM6FmCiHGTPBEAuMnDXuO4jCGOIusYEWfGADHXyDNhLlK6nKo9MsiRW4bZiR0ls2N2OOfoiiNvokkdYeR79uQxMgyxR2I6YPNGMEgCAgICAgICAgICCIKHZHQRDJKAgAAvxG1nW0kQfZQgd2W8TCHIXaF3dfCVy5+smAlkXhIAUAHuNHA0X8X3rwjrIGdfIjJaPk+u6PcGZQUL5+Oi7kunEETs0LTqUlZ8v5lzRjWdpwy+vgHqUbjKaCyAZ4wQT4nbzjqKX676FYBCHpK6qNtPOhkeVeNSYzay2iUoXTHLtzOYpmimCQDlaRHOzSBSFdieNYjsn3tN3PvKt40i94KYDYX+0cpXPMoD0qOY5/kvdP6RWAWtq5VvgUZ3I78nGLNyjFBVLniOZ47LuaHs6DHfFcfozpSX4ihCM02QpLZPoajk5D199VtFQsQ68D1PAJ30UHk89Hddxt03ykaoyDzFbrsZbJqXFhLQqlXaK6LPg/YbYFOl3POm5+7znNWlNepzo5S0iDMrkD1vvt8rTevg2lO1ESQMDAbJ6CIYJAEBAV5UZWR3UTXxL4N5MULTtrLjMi1rmr14M/oWpc1ErJgJ3K3bNV5c0P1NYq8OXh6dvHD0S5nWUWZc1Yll0OUKWaZlTp0AVExMnWvj61sfTc79rR346mM6ZieDG/MDZEpbWRETf8Bs2V9fn9VR0aqiv0Qsk3UltLiIk8SeGa0wzfhTg0liEiLqQwuh6FoisSlb5nyt2BJh9oGURonLKHORtrhtpYaI/s0yFgBFtcqSGAIqAzsYM4pZcSMCj6I8YSKtktBttKyvOU4mEUypYZTCpce6nkxTKlB3przUHccYSDj6MWj1H708ZRNa3yS8XfiokVYMCBiQjVMOf0JPix4nJZBlQKd1UMoVZwyQEgl0gkE9+c//VXE25VRVt+1Vixx0gan0fnDORz8fI8cw8sVyaRSU3zTtLEzUAxwEgyQgICAgICAgICCAgDGOkIdk9BAMkoCAAAO+8CvgFfrwvlWwopu+nNJljsOYFbzMGAPXwZCaGmCUh1i2IJtTtlIhvKvZ7SpM+coMh4u9bKVdKYrlK5xFCkp9z4hbjga5u6u51spsi37SMCvDYJaXYrgTKbqeEjfviG8l3DiAyHm0WnH19WdZH3OnT32/aWocHZNpRtPS56VVtpqZpyRtpkiTXFXLTYyog9ellHngeyqQpsJ4TMwxpTTB7OZ8HIqWTc/K1K7iXO1KK2gBiqLFOTcJDHkUmX0Yy0mNjPNCckNdB2P5sXPPS2SSMAL56rqbVI8zhmaSmHNJhSBlVJ3US1qmsFXnvnHHSqtEhur5ZMM4t5jM6Vu6/mIFAIrjiSqLRZwDUiBBrhRHaVKcc0SsWlWrLN+Ij3apA9LL8gIJKS2XFGfMqGr56LutUNaO8YzhoJZtDNS08YJgkAQEbMbQtCzebAK33w6g+iXjJjmkdJVW+7pwYwGkdPjV9KVrvxu9L0SvseSJcSmcE5ilMiOdF7EPVTQJ70tXn4v+r4JKUazP3xbfJIpSmAAU4klaKW6VwUedamdfiqp6ymhhhYmXlpFGcRyMFB3EpyCXiqJMsZ5UDybKEGmmKdJmFkOSpEgGE+s7jTuhxog0lK3cSDHn6rv2mZIWYFO0AFjGiE4+GHfFYJwhzuI2dALD3LggVCtKXYsigCpkRcz8HjfyKYWJo2hElfEHNMu3kUduDoKBoUu3jXMkaZpLg2cLB74Jedlk2Xd/GSO+0Js5tJFBFw9SIfL4JQmLvpUVLiiz6TiksvYyBiVnBTtehCYfpOpa7jnRc6OJVsuUuGhMjC/erkDX4nbMSN1nfSujKSBAIxgkAQEBAQEBAQEBARSMtVycqlVHQC0EgyQgYDOFL2idrnqVBarTJIdaq74qUV1d5EHuEqkktBmm85bkwcx6Ra9sNZRq6NdB7klp7Rkpp0voGjxUMqZWS12VnKogan28qra4ydZKVZfcXCBtUC7ynB302C13A+D3xpR5TKg3y5ezRLe70/HVCdwcKXR8p2TMA1AJEFOBwYyepYPaB5MESaK26WD0pJkFu5cljpTSOEG8alqMAVKiit5OA9gVhcoOamecKRWtzD0YdzXAeXECZspLwGXrae+IDoRnjKk6AJObRFO0TA4Lh4qUbyPHdNSnNH2tSi3K9ZjosVJ2nwK5h63qfohqjDlzz5N4AdcjQj2X+pjUm8cZA3hOn9J5WTRNSvdblTfWVRbTlDDffZM/b2HtQwpYZannRd/DtA5f/iAKTb8UTj+MZ/i8cJ3UEVAPwSAJCAiwDApKNXApT66MY5kBUhVn4FOj6XSS6TNEVDvtDPK0vRRmyjOEl4Z+UdO4kAIfu2TSROtwMRS5UiueBOW0rXbjSfQ+rWhf3izNJccRKJ9g0cSKuo6yLNntwt2nakzqsSOcoA0a65EIgYGkaZS1UiEwkCQQiYobAYDmYBMioRStYrtoHEmbJ2QZy7Ycb/67mXwLCcEEIqYTIirjgnmsTcayqyCzfnOysJuJaRYkRQ3vOOKFpHrUsKcJ/zQ455jc3Y1JXV0AgHX9/RhM09wwJTEs1FgtNN01rhzDvKy8T67WVduik3E/fTJX7ZMyUzK3JvmwzpvGqcRRhO44tmhS7nOGwjV0Im7H+PgWmtoJ1XblhTlrrdjn3v9aYj3EVASUIRgkAQEBAQEBAQEBAQTBQzK6CAZJQMBmCE3Xclf96Ap02Qq3S0OgnofRpNNUtc2i/5S0SUqpVi0BCB1QD1krF4m1KpytWlIKSYEm4iSOa4XhpjSYY0onL0kHl6uQ68SDduql9fnoXK1UvcqoOb5ynf5u0xKzbZmqlqZoNZMEg0mKARPUniiVrSQ1eUfqHLv2PVTRXkWd4qaIzgWigtvzbZxzQxtrDiZKdStbO8/zh2R/2TI/jxiYpmhxZuUhAc/pWGaVXuedoPk0iBeRegH0uXfFEeIoMn3b1WhYfZQIknWmxAvigt5TVeNT3x9VXsSCZwZZwkTHA0ObSJ8rNNjcem5kdTYidf6MMWu/VjlWDA3Mobu5z2wgp1j5PLq0PqCeqEX+jPE/e801hkQraux4QZD9HV0EgyQgYDOFT6FK0VKK23z7DUfcyFAgpSw1RNxzcPcbCnLOt/ru8t2rjA49ESuT2mwHVTEydII3XDLALqpUjKrKtaqPeSaO5Vx5WZhcDmVVs1I2OqMAGopWmmIwTTHQbAIA+ptNNMn3ZpopaAm7r92meWNE4I+XaAUzuY04eGyrInHOwTlDlClhxY0Ije6uPEu8Pn9zHbgxNhjPJssJwLJkibRORpS5tDESc3sbpWhRlS1rQkzaGzkT5YQx0/cR8ytWVfUJRUTuDxf5mCM0J0orhM7WntdB6VbZUVu2RZ+31S/ZfnEUIXaobWXnU6XW10qFUG8vM5f1ObmULR0/2A7UcTY+6d+A0UMwSAICAgICAgICAgIIAmVrdBEMkoCAzRg6gF2vmHu9DiUeElrG+r0iEL4duHXTego5ITw0s7q5UYSUuea+oSio7xFZxaVQQb72b5Qm4a5atvo+XCgTDBjuvCQ+DMUTUlYPpYwAnedCqdsmiqLCllbSUnShgSRBM02QZB4G7R2xxqYnOF3K1mOT8Zx4JAXAWGQC4+l+zBmfWu2KRwxxI0aUeS7SNFepyvOQNJQnJSsjhX0PGKoW1x6SvG0mH0bmHbGTHjLEPCIr/zZFy1XZKhsHzTQ19bpeJJfKRLeXgTv3ti4vhLDuXea9NqLgJcl/aQ1Ky6LbGGNomOD/yHinuqLIShhJ94l4a1EJDSpuUaWC5bvnyhJPqt9yxUOzj+P1lZlaolchbqPB0A2SjYWeNh4QDJKAgM0INHZEK1Gp7+p34YkHcV8oZRSuuigzcEpVmDy0Az1BqUPRKmu3t22QlfEIehKhBInyF3eVMTIcq2ztoMwood+1zUhlgIeTdteOnHCdeoqGiW1UpcPUdJ/MLwCT8HAwTTGoKVlCoJkkJgv7YJIgESLPyp6mKqkhNeAz2V9LDauEYmMMg4hBemJQrPiDSFGneGaQxI3YMjZ03Swq8uFdVS0rMSLPsrR7qF+qbcoYaRBp2jiKjGytPg1fIkQag1VoExiSNAUjin9l91Er497dxzVkyibe1sKMAIzpwRiEzO8XIwtc0Q7XcNRxZzTWJo64Vv1VfRrb0zPaT2WGedlzsB0JdF+7zXcyuVY2SP48bmX00DZGo/c4DNiIEAySgICAgICAgICAAIJA2RpdBIMkIGAzAT/mKid4XRRW1CSqPRatvCPDQdfy7eNTWvIF4LdamR8uL4CbPwBorYCjf3MVhUYCZcdwA9zVNtXnw9muunXV8ZL46tEekbKV7boB9xRW0kOHytg/2ERfswlBVLWSNEUiVOJDQCk/pUIg1R6Spso/IpJ8G5xx6qMikRNR/wiV68Q3xvPgchWsnlO2bO8IizgYbE+YSJWnhmuFucj2XOgAfMa5qtd4q2CW6HW+Ed3siARim22Zd4RStLSXEaACBcUgfsszU+G1rPreCi3LZ2M0yohaKrFf7hGh944L6smg3gXjSeLcULao4lkURYX+KVM/tJva+pldBr/3yamfJCyt65mkx+clxxmvYOBw5Qrar2PknvObGoJBEhCwGUJz4l0JSHeC5I0RqRE30n5bqg0dBgYphUUn0/SqsjYBrV/GZRPisvqoVKerEjSUidBIq5SVGQhacauTZIl1j9uukdhOPxraDGdIW5Stgk4ISu8HIYQ3XkQbK02dhV1oA0WV1xK/STOBSIRjTGSxGo4R4p6zSoyYn6MvUSIduzyODG0LgJHsdUEleg3t0UheZ2NZT5AjZowRzjl0Fked4R3QGcWVapY+F3NeJMaqeL/YhkiR0uQ3MlqNjU5ijFon+WRWnIibub1swlllYMVRhCgzSqihpmuKYBswdr31294OXMPYdy0tdT7YinE0oW6r4wjPMz8gIBgkAQEBAQEBAQEBARTKSh96HQG1EAySgIDNAJquRYN0fZ6JqpWrUh17L53K3w5KGWtF9zJt9wRLarqWqwjWqs2+1XhbWYxZyRHVdjcI1l7Vdb0jvlXauknF6ngmhrqySFd8S1WehjnIvR3UOa67Ut7uSrGvv6WUSLT3Iwtgb2Z0rGbmLVE0LVUmFSKjbCkPiRACaTNF0lT7aKqVEAIyU7ny0ckKFKzU3u7bx+0D5dlglkJWGXhUXkYHsmdfMq8Lt+ZkPKNlASoQO2K5ypYOZmfM9hBoT4pGaR4S2o5C8Dn5PfPslXkR7P3yMr57hzP32ZK3wZRRG0wdVt9LWRhPxbYrz5N+rkScexMfai+fj9pJvRTtjHdN02xHQKIs/0nVvel7Trv3l0BRVGA8I8SQjC6CQRIQsBkhn3jb3700rFZUmxIDwhsD0gZtp9OJcKnB5DFmNLi7TQjwiHtjL4DsBYXii7ouVUQZM+UT6KHGcXSyH6VtAf4JmXuM0YiDqYI78SubtNMyVfVIKZFKaVG0tGoWoAwUbaxraorK1C5Nsj5Dz9Lf0yKFpcywkCXGQdlnTcmKGnnMCDUm9ETKS4ejE22uEijqz7QOpaaljAsWcSMyFUeRkROOWD6xBuykhwVVLdjf3Zgr9z7yGRt14rSq4E6G3QUHISUiZj/bhLsg4Tm+j/pJz6cRxYijyKIYMrgLGQyixTjQ+7v3Ki3rU9hzDT6fYVYwcN34EfqMrkHRHU46WcDmgWCQBAQEBAQEBAQEBBAED8noIhgkAQGbATQ9y1r5a5OaBbReGRvJVbG6K90uCgHz5BxSmdE+dEAm50iFBOM5FUzIYh0+mon5zRMA6mI0ExJW/a5XULWXpE7bfCv3rY5RVaYVBa1uEsl21Ja0R0UrZA0kCZI0NTlEBpKmFcCeSuUNoZ6YVArru5QSIhV2MHqLcysED+vvnsSI7so3j/IA9DL6lYbOfcI4SZ6ovR/UQxGRAHPOjHoXJ56VmHPEkZo6uEkPI6O6lVO0tCIdpXXR83bVpHSZsnPRx6kjRuH2b5loh/FckLGqf2tw5jw7VWJC24OQnys9xzgL/tceEUqp841rmjzS7Qc/3aywyfLoaM9Np57MgjfYebbVet56vuv/xjuCQTK6CAZJQMAmDJoIsc5LqRMFrVYT6yrKlA/mAe5OwCCtF7WPr9xZ5nhyHGknXKzTZ1QxyDqPFvz2VtStTl/2nYJONkbDYKobC1OUKS5OuChaTSJkRruiMSL6M1XMSkVukEiZ70cVs9x63XbkClnV52jiNvIggvy3iAGpsM5JZU+ncRj2Pr42cc7BM6lZAOAxN2pZur30X845WMTRFUdKRSvri0Ycm4m2NkbcTO2+GBE7eag9eafHtfqF+ctQShEdp75YLs5s2VZ6f7v7ly1sUAUpmdG69LikBhZVzKL0MF9MSWvFsOoFDx8o9RLoLGGoOR8PNZUcyOrDod7jAQFAMEgCAgJQIu87DN6QuhNk3wRcv5CFqsiU0/9yBpQJTdaJb6FxCLp8mq0k0xib4YhvGQnUMUY6mRC4MSWqnnptqPN7VZu8MQ+e/Vt5TVodV0hZyCmSZjEhAIzhQceF3lbWfuVhyHNJtAPZ4mZyM6zrCbCbZd31iuj4Fs45okaUxZqo36MoQhTTTO4APHXqenWcSxxxxHTizfOg9ogxb4wINSC8EsGeCTvd7otpyA2akuvhyW8CqGeG7Y0h48U8C6hnwh8zQseBlvEtO4+y83TLuLla6twPuj1A0ViJePHereO1qxMTpzLNq8+poPEtamd3wWhj9BQwxsHYEPOQDHH/zQnBIAkICAgICAgICAggCJSt0UUw3QICNkO0khT1QcVS5H+t6h9ObwJnuSqN+XO+12m3r23SxInkcshubID1vcT7UtWWOvKkrSBKrpmPF6//ZI0/77l4pI7bhY+qV5Zos6wtVVQQtz+sWA7Pn3veeiVYr5AXqX0yo2r5z48xtaLdiGM04tioVeW/D99ExBr3vj/OC54NN+bEhRACIs3PkTH7ODzm2Sq9vZ9W1oqjKKNvKTlb1zuS05gYGpwj5hFirhS5jKKX9rBk/+o/rfAVcZ14Mbvf6X/0OQAGzrj1V+ca+MadHvvmmZCNFfoXZ1S2rjhCdxwj1u3Ozp3G0lQ9F8o8KLQet5983kH3OPr4qs951j7Vl3HEvXXoutX1s9tP+6pMKc7t7/HkTd6Y8IUvfAH77rsvpk6dipkzZ+Ld7343li1bZpX54Ac/WLjm+++/v1VmYGAAZ599NrbaaitMnjwZxx13HF544QWrzKpVq3Dqqaeip6cHPT09OPXUU7F69eqRPsVSBIMkIGAzQd0JkhtwWMcAsfbv8EWUTyyy7+blaNM2OAOZvKiXbN1M6d4Ay4pJspnMZv/R/Cf5ZNdvyLRCVZ/6DIw651NmtHQCfT00dN+XHbusXa0MkVaoKuMaHQChW5G/VIhCOfcY+rpSw7NqH5Zlqi6bdHZ8HzhUp7IYGSX96w0dMZPoKIoQaVlemcezSHKuUqg/MIYoVpK+UZZ/REn6FttHaVgmaJ1OnLNJcJxNijkxNlwDRB2HGB+ZARLz3LhwJ9q+yb+JZyHbdQ4O9zrWGXt0vPvubd02n/HhtqXsr2zs+IwL3zPO7YOIczSy7O8610kjMx61QcgZt66H2xaaZ8n9rTBWyTPbNUR9lDONdt8pY4WWCwE1/9rB3XffjTPPPBP3338/fv7znyNJEhx55JFYv369Ve6oo47C8uXLzd/tt99u/X7OOefglltuwc0334x77rkH69atw7HHHos0TU2Zk08+GQ899BCWLFmCJUuW4KGHHsKpp57aeYcNEYGyFRAQEBAQEBAQEGCBAWjPoPDXUR9Lliyxvl977bWYOXMmli5dikMOOcRs7+7uxuzZs7119Pb24tvf/ja+973v4fDDDwcAXH/99Zg/fz7uvPNOLFy4EI8//jiWLFmC+++/H/vttx8A4Jvf/CYOOOAALFu2DDvvvHNb7R4OBIMkIGAThrjtbAAAO/rKwm+tFLXaVc+qC1/mYA47CNJdXWOMgQOQMlcV0nQNQAXt0mBn7bXwBbH7vltBrXR71h8u3UtICUZWW73L1PRYNSUuyzwelW12yhbOs8axqyhljEgCA+1JFrdSBauLUmoZuV4mYaGUuYwzrcMZ20lKsqxLaf3rO64btFvutcrLy8wdYbwuJR1HVbbKVsxp2TqrrpxzNCY0AABRxCGEph7ZderM7ZpGpd0C2gMZc7XiLpGLgFnHYa1VtgrnwHIVKuoFrYIO+AbKx7qLMm+Y9b3F/eE+i5QHgVvtoZ+HAtc7Ru81xphRAWRWe+zxEDnUPSH1szPvM85YriDnnL+mw9H2cBQz1Ou6aNstz2jmqXT3EVJultScNWvWWN+7u7vR3d3dcr/e3l4AwIwZM6ztd911F2bOnInp06fj0EMPxec//3nMnDkTALB06VI0m00ceeSRpvzcuXOx++67495778XChQtx3333oaenxxgjALD//vujp6cH9957bzBIAgIChheu7K9+uVUpHbWryjJcMC8uqZRzUvIi1gZL/oKUapJkJnopOMuVgHR594XeegIDS9ITsOkdwvSjAJf5xJRJZqn90Al+HfpblSFSZUi5ZQv11jWERiAnQN1J41BArwvd5jsfM/aFUMZImlr0LD1RA2AytOdjslifT3pa7aP/rVZE8oHuayaFnFmGhLduKQE383fM84zqjRhcG1Ra9jfiJsO7Po5bN0NOB9IGiYoVyYwWQv8B/JnafXlHdL1qn9bTU5cCFGWfBYr0wCrUGYt6nOSywVptKTfU6lJE20GRjlV8Vqh+t1UAteEC2MaE/t1knjeGtI6DUdLNVMpat4M7/Q3GLCO/rJ9TolynaZKR0x5d78YQYzKcKlvz58+3tn/2s5/FxRdfXLmvlBLnnXceDj74YOy+++5m+zve8Q6ccMIJ2G677fD000/j05/+NN72trdh6dKl6O7uxooVK9DV1YUtttjCqm/WrFlYsWIFAGDFihXGgKGYOXOmKTPaCAZJQEBAQEBAQEBAAEEnMSC+OgDg+eefx7Rp08z2Ot6Rs846Cw8//DDuuecea/t73/te83n33XfHPvvsg+222w633XYbjj/++NL6XI+V79x8Xq3RQjBIAgI2UfBjrrJX9lFcaXdXsYXMlS5GcgVL07YAmxYAwKx66u2SlMvblgcUA2qlVpCFrFQIMMlarvyb5GbONtMWshKpvgukQqv75KvoqRCAyUTdGUWrzCvSKqjbV1+dPCxVqFLVasfjVGf1uoquU5UU0S2Tn7vdTv0bpXbpLOtVx1NsK3vlmEI6x3VBV5eLDo0y6hYHj+zx7+7LWEkkO6k3yhIg6vwlLKNVMa5ypQB5xnaR2vQ2fdxGFKG70TBZxqVpj02V1DQtIPeY0OukvudewzyTe1EJS7rPBPc0CSUTyKhEZF/6XPGh1Zil3hHdXhpY7vaRi6rx4v7eCqVJU8EQ6ao9dLiyfTQiBkjifYmjqNAu31h3+456IoX0n5tPRawOPW9TxLRp0yyDpBXOPvts3HrrrfjVr36FefPmVZadM2cOtttuO/z5z38GAMyePRuDg4NYtWqV5SVZuXIlDjzwQFPm5ZdfLtT1yiuvYNasWbXbOZzYHKl8AQGbBWwlKAEh8wRvInOnG/UYJ+uuvW/rv+GGVm4pmxhrmgJVuNGJyajSja8ely5Az1X3RblCU07bSvWfo+rko2X5aHDuZF2W/LkoUwxqNdEqo4r5/lyJZ5/ccytDiRrDvrb6fnfPsezc6fey83WPpce+m3W7MMmSEqkUVt1lSkNS5m2y6C2ZAaCyo1e/Zi1FHm4b2pX7cWb+NPWKtlFKCZkKyFQYPj89ni6jEyiKVIBzhq44zv+iyFLRAgDOi8pPEeOGqmUUmvT5ZzEXuk4tGUzjJHL1PK2a11pqumz1mqpYle1XBs4UHYwTaWPdZiOby4nMMbPb6vZtnTbXXYX39Yc2lqrOF/DHidD2Wwpn5EB1laLofaTrjaPIq+a1MaFKOaudv3YgpcRZZ52FH/3oR/jFL36B7bffvuU+f/3rX/H8889jzpw5AIC9994bjUYDP//5z02Z5cuX49FHHzUGyQEHHIDe3l48+OCDpswDDzyA3t5eU2a0ETwkAQEBAQEBAQEBAQTDSdmqizPPPBM33ngjfvzjH2Pq1KkmnqOnpwcTJ07EunXrcPHFF+Nv//ZvMWfOHDzzzDP4xCc+ga222grvec97TNkPf/jDOP/887HllltixowZuOCCC7DHHnsY1a1ddtkFRx11FD7ykY/gG9/4BgDgtNNOw7HHHjsmAe1AMEgCAjZZ2KvU/uBsn4pUgQJTRi8hdAF3NbkOqFqRFYwLWMGqltKLLiSlyQMBwAS469U9KRXFxFXvclHwVABIhbToWBHPqQpCCAgGQ9tS7RekYTklpcojoc+bbqf/ur9Xtb+wrZDgr/U+deptB7WDzSVIP7ZDZ/FT1XygHix1SIlU+L17ZkyDAU5bzXglx/Ttr4PGEQNcsiz5YD5+IMgkhUtA5PukaVoI+s0dL/oekda9p/9ljBnFLNOn2cXX6kwiFeaeMX1m+kUFv09oNEwdiRDg2Wq3PlOtugVklC0yacvpWMrLoLfp7aofUUCZyhsdL7QMZ7lAh26LUY2qeBa5NNFivcS7as4pPxddxrruhuZFnyPl55o1wPt8oIH07r6UQuaek/FeOW0ro6jVoVsW21YUcdDnQAPjOek3xop0MH38sYpTGO9YvHgxAOCwww6ztl977bX44Ac/iCiK8Mgjj+C73/0uVq9ejTlz5uCtb30rvv/972Pq1Kmm/OWXX444jnHiiSeir68Pb3/723HdddchysQMAOCGG27AokWLjBrXcccdh69//esjf5IlCAZJQMAmCncCaNFKAEsWl/LrKT+9cpKYvQhtvnv7xkkZ79vw1IniFt1Hq2gBgNTucZlz2/X5mG1MmokCPWf6WfPQ9YuXC4FUcMtA0dS3/IXKwbhtaFCSju/l71Og8hkj7UwaqiSbh2pgdIK65+Aanu3CjR1xt7vtqQKd2ClDtGgs0VgnzpiRws2NAoeixQRYahsOxCpQNYl83AoAHMKIGpkYD1OtujPc/uIRQxTnr3SauV1mwWG0bVJKZVB0Ncyxu+LIiZUoqmDpZIaApjfZMrFaKriRtaVsYl0HbllzzjK/n92JsCv4TMeBey4+tSxNI6MGgPscs75nzy9mtaXOWCtuM2OJnLf1mYzP8nqr42hcuLLePkPJNYD1Qg99bvoWIZQomNO/OpZoIzBIxsJD0up5OXHiRPz0pz9tWc+ECRNw1VVX4aqrriotM2PGDFx//fVttW8kEQySgICAgICAgICAAILhlP0NaI1gkAQEbMJwE/pp6MBld1XLpWxVqUUxMJMbxH3kUhpOXQqXS9tyEyXq7QDJSULiiOnqpxSp8ZrQZInFdfTiyjkNehaMWd4QLgREtgquy2mPiklWlilu6eO6no8q70hV/pEyDJWiRT1cQ0ErD49uZyk9p8JT0o6HRwAm54be16Un6m36GunxRNsQgSPN1ttV3guYsrpMYdxF0njkGGcmEaLxKDRUMLfQ9CKhcmkwpvsrW5GNeOkqu+4ei3akPYRa7Up7QvS4zYLeXe8N4wxRQ1E4GnEMBoZmlkeikQW0R5wjjjgE8vPWq/suHUt7R+IosnJjjAb09Ss8bzweEPqZeiqqvCK+/TWo1wxA4TEjIQv94Lsfyj7T49b1OgPlXsFOaZv0fvHBp+YYMepxy9s+XMkkAzYdBIMkIGAThUvXov/mkzN74iiEMFwCl87lgmU8ZzW5K3+RUwpFOyorrdRqaEwJhzQGCJDJADNRSJYokdO2KNWD9otWZAIyyVIhILOXJ1XbYshpborKlbeGSZm3reKch0Klqkr+V1V/3W1DRad1drJfmUocRZp1Tn9zEEA2RjwxINa/2biWkGBMMaysuA0w5HN8Fcckmd0WEIOPcw7EgGzqwAN1DJ8Clp7l8uwD86gfWd95ngiRx5GXiiSlNHK/jDFEETfUqjjKFZEAmNgRzjliHpmxxRgzk0waMwIAjSg2xkhZzIPVN22gE6PZt4+18MFQoERxVt1u/Rttv7tgAubEcviMMtKfvvoLlLwK+lBVX+qFG2qQt1Iw6wQ+Y8RN1LixYSwoW5szgkESELCJgGZlVxNq++Vg83zt7zTgt8yrovaT1sq/nuzrSZkqz4fFY2L2BfPGkbhllIGUtY0p6UmQVbg8nsSe/PnOMSLnSGNvLElglpdX5bKJTFam6kU03IaIakfr+kc6lqRO3EgrT0k7sIzuFmVprgyNMu9ZHqOU/+7r97Js7QAZX4xBH5LJojQvY8x7RV3DxBjbUQTGASmQ16s9JK4HhBotTib2qBGpuogRb+UUyYyTBrczrzc4N1m+acyI2afGhL4OfBNyd5JP48Lce07f264Bovel5bizX7vtq/ImVFRgfaXiHr6FHd/kuOw+a+VpTcnDoo5Hsk4QfNn94fN8+t4t4xEMQ39OBXOkPoLPLCAgICAgICAgICBgzBA8JAEBmzCqZGStlX/iOdH8e5+MJlCM7eCMwUr2zIVN4SI/aRUuuvpXVxHGjTERcBSPIK1s0pwp9RjfNnUerY+pYw8E6Z+cEpR7RASNIXGoZq1W7jU6TTDZKU2LHrOThGVDTYjpo3d0sl9d6Pq7Gg2TGFSI6qtDqTjaS0LvmVZZwXXMhshGgfYdyjiroykJ1c8+pruy7FPVgvNb2lTxHzouxKKXMUUZo9saUUQSHqpYEUrHijNFrTiKcgqiU4eOGQGAmPw2VLiUqDI5W+31EM74KVN4sj0m/jiNdtrWyf6+ujhjEBWeGhpDUuUB8cqJV9wzQ/LWWvcCsvZl7XVjZpx30Ugk1B12MFYYQx3VEVALwSAJCNgEoOlaQM7l9VF49IvJF+Su/6WGiO+lYU2UpB27oY0T/QyOYBsOpo2ec3CNo3ZB85Lo2BFFkSluU+3PtxnDRqIWfYNK+1IaFwAT4M5JHVX9WHo+NWgSdeqsI3873JODToyGTg2NOkilsOVGOQeEMMaqlLbx7b1eKN4POqeJ3lfRprIxk2m48ojn14BlIhA6Jok5xgiHkQB2J+S+mBEapM45N7Qs7tCsVDb3CDzi4HGeQyTmnMjzkjiX7F9K26I5PDSti2c0rzjbpyoYXMPNBVJn0kzz1Vj95eQm8aGKnkXb0QpVMW3u9laxK6q9RcOiEMPkqafde9XNNTVcoG3bKIyLDhBiSEYXgbIVEBAQEBAQEBAQEDBmCB6SgIBNBIUAdelI+BK3epnqVpplZta/VUn/5schQbrZipLJngxFpdJrHxydrfy7KKpswZsoMcpWwlUhbrfbUeai7bOO1UKmVivqaMoWk5qGw833VihbYWwVONsqkL2Od2RTgG/1l9Kx3GvIGYx3pF79ElIW7ym3DJB7GAQEmADSVNr3R6asBQA85uCC51LCAHT2dmtccm4FsPMoUl4P7Zngih4WN+KsjFYE0x2Q/d4Vm30amYIWBaVfNXge5M45B8j56f5sRBHiiGZhr9+nhcDpEllc0wce2pa7vy8Y263Dt73d9rrB8nW8nfT4eht9htFyVSvznUr2DgWdKPO50sP03HkNT9r4wNDzkIR1//pou6defPFFvO9978OWW26JSZMm4U1vehOWLl1qfjdqH87fV77yFVNm2bJlOOiggzBv3jxccsklVv0LFiwAYwz333+/tf2cc87BYYcd1m5zAwI2WfBjrjJ/eqJE6VrGoCDbKaT1e74tl7YVpK7yP1VGQEiBVNh/iqsP8zttk6vyZauAFV92nFW/qBlTMqyaJ06zbqs/GLqMnlRFnBlais5ArQ0Zml+hCjSuhPan9T2bHIusT+h5joaRMBrHca/haIMeNxUCqVR/zczIppOgdukrlK7lnqOul44Ziy7FVH6QXOWq+J7UYxJ6G4fZxjkHjxRFS9G0cmNE18sjnilmZUYIY4jiCFEjRtSI0dXdhbgrRiOO0Z39xVmuHHUPMMRZrEjElEKdPnbEuCU5GwGIo8hIAvPs9ypZ2jrwGRj6P7evfaDXwNzP5LrTa9Mu3Pu7LL7DS62raViUxba4Y7eqDh+lsNU+daHpvGkWfwXAfKfHoc/gMsrZxhJDUjafbfcvoB7aMkhWrVqFgw46CI1GA3fccQcee+wx/Ou//iumT59uyixfvtz6+853vgPGGP72b//WlDnzzDNx6qmn4sc//jF+8pOf4De/+Y11nAkTJuDjH//40M4sICAgICAgICAgIGDcoy3K1pe+9CXMnz8f1157rdm2YMECq8zs2bOt7z/+8Y/x1re+FTvssIPZtnr1auy1117Yc889MXfuXPT29lr7nH766Vi8eDFuv/12HH300e00MSBgswANYs+9GtkqvCyuVrcKGKcr9ozUU7WPRiopJUECkmQ75zpJoF4lEobi5ctkrttQ57ia8qBqtbO7a0qOtVop7VwligKicqgYxSwn4JYze1W2LKGYFfCcJUpMzQkJq//rnN9QV9VG2ksxnnII+FTGpLPdl/+mnXNQOS/yjO56fwYGZMHUEWNWfgdvPaxIK+KcwajSSZWTxFC3sn3AcnqWzrrOODNJDrUXJcooW5xzkxVeoyuOVfZ1Mv4jnqtqNTKviVHMiiKTc4TzPDBfe0f0OXfqGXEpT77r4QZO03u3Tr1DoT2V1Vm3TN0+oTQynYBVb6/rRWhVTr8TfKirGFZINEq+U4Ut7lxX3/4S5VTg8YQQ1D66aMtDcuutt2KfffbBCSecgJkzZ2KvvfbCN7/5zdLyL7/8Mm677TZ8+MMftrZfcsklOOKIIzBp0iRwzrFw4ULr9wULFuCMM87ARRdd1FKWMSBgc4VFx5I5tUq71in9CijGG2gal5vl2j1Ge22xVadoW9zfRclfneNW0rbIC96duFCDQv+uJ5ucwdBX9Pd2kmLR60HPOSXGYl1ak0sRsRR8CI3FPR9fP3QKXxtGkpKlx2+7+wBFfn8q8/4vTJJgX6eUxpqw3Fh2KTSaakXL6vFTOk64h75BKFycc7CI+8uQzxY9izPwmCOKI4vSxaMIje6G+dOGQxxF6G4oY4PSmbrjGBMaDTTi2DJGqLKWNkYixhBlpxRHkSrbgtZYNgbbjTNxJ7VV8VY+Y8RHeSpQ6jqg23ipec42emxOftPPmbLj0HFYp1/c30w9Fc+vVvey7743tGDybE+dWK1WfbcxGCIagbI1umjLQ/LUU09h8eLFOO+88/CJT3wCDz74IBYtWoTu7m68//3vL5T/j//4D0ydOhXHH3+8tf3oo4/GK6+8gjVr1mDrrbf2HutTn/oUrr32Wtxwww049dRT22kmmpKjKaPWBYcJSXasZBSPuTkh9G8RvNm0vBruyntasQ0Aie9QL5M0SdS/aWpeFwKdrSSaFV5AeUgYMwHljDFIlr+4ylAwjDzSlW7MCT1fISUE8pgNZJ8lJERKvhPDzHs+UBNC/coVkGBMqgBf4k2h52zOl55zmvVv1s/DgbI+scqQ/mi7/iEYHmkHC0l6j3aOavaREiJVPimRphCQEFnHKM8YndQKCKHievQ+ykixPYna05J/F5BCQtL8PGQcADqwKmuVEPnvuozMxA/02Mm+61zt6l+PpwAyH1+Q+X6mHlU3aL8zHVCi9kLmNdTbZDZu9Xd9z+g6BZQohXlmZH2VJglSI1tcvI8luS/od1+Zsu+F83dX6z3PjjIPRVXOI188SKu2+o5XVk+ZxLDJneJUnWTPB/2vz3vsMyRcg9z6DXlMW53zKgONHTELLfqeI9ecepkF2Ye2B4DZNyBAoy2DRAiBffbZB5dddhkAYK+99sIf//hHLF682GuQfOc738Epp5yCCRMmFH7r7u4uNUYAYOutt8YFF1yAz3zmM3jve9/bTjNxZ3oIJqWT2tpnOHCnOGTUj7k5IfQvwe23j0i1f3nooRGpN0DhDw8+ONZN2OTx7COPjOrxKM2g4yWTyPkXAKzVbWqoCPUxhcl1gmb27/rqw9ApYKem8aO//W2HewbUxW/vuWesmzDi2LBhw1g3oSUYG7rK1tBVujYftGWQzJkzB7vuuqu1bZdddsEPf/jDQtlf//rXWLZsGb7//e933LjzzjsPV199Na6++uq29js8+hWmRd0dH7ddJDLCneIQHM5/hZgFq3+4sbn3Lzvyy+pfZ8XRJDB0Vnepd8Ss+GYJ3IwHIfMcaB7wwOAgnli6FK9705vAMn54nRU0dzVUfzZJAfX37HeqdGPRjTzUAp/Xoswb4J6vUn5RfUE9JKkUhudPE0C2iufQMsY6k7WbrbrqnJWHJMVjS5dit332QRTHhZXSOijro+GW/h0OSlZSw0NSVaLqFe7z3KVpCpGmeO7RR7HdHnsAjCHNvH86RkJ/T1KBJE3RJCu0LKNkmWMIacYQQGlg+bgxXjlyH6bC9toJISCFMA4SISTSJDWeDJGqMqnx7ojCuamxBjCSsNAob2X3qqZ/8SwpYyOO0d1oYEKjofbJTi6mMQoZ7SqPGVHKcyZRIueWolaaJHj0t7/FXvvvjzirV4/zqszhOm6mnVV9F2XUlzKK1mjCJ2tL26N+a03/lJBIkgQP/Poe7Pc3ByPOroOrgEj7MvfkVfcf9ZBQT3Jle5xy1vUCMJgkGCAeX0MJJO8PV1EQyN9P69aubdmGsQcDWly3enUE1EFbBslBBx2EZcuWWdv+9Kc/YbvttiuU/fa3v429994bb3zjGztu3JQpU/DpT38aF198Md75znfW3q/BBBpjMHGNWTomx91csDn1rw5a972ozQuwxNhgUk2mGHlRCQkwnmdh55yrCVf2Xb9EoihqyyDR5crpEsjkde1MzjbPutZhVAC659j0sz4/kwtEyJy2wlTwsMzoOyzLPl01MXK53CozNgPLXr52mWwfR3ZY0dQygyyOEcWx2V4HVYabhDR9Uha46m6LUG2UDEuMiCMF6kNJYm3veKCTMmqsUFqI3h7FsYq7oJQ6KZFmGdAhlcETVww8mWVUt6lW2b76umbjTX9PpQBnpG8zcQNwDmQ0QUihxqGhTWU0Km0oCEBKYU/As4AmbZAwzsFiJREcd2nDQJXTge9xI0aj0cj3YcrQ6Ioi69p3xTHiLNt7xPKYEfWdoSuOTQxJqo2aRgMNYujo/lXXyX9RfQaJr6zv/tPHcUEXBDSGKj1cpy1VKBtS+r51aV5l5RpxA3Ecm2c7oAVHilTcOsZIBNsgQYsFA6FWuEoXBhIhIJmKW9Ln1cjij0weHiHAiBhCBFixdXrfgACNtnxJ5557Lu6//35cdtll+Mtf/oIbb7wR11xzDc4880yr3Jo1a/Cf//mf+Id/+IchN/C0005DT08PbrrppiHXFRAQEBAQEBAQENAKIah9dNGWh2TffffFLbfcgosuugiXXHIJtt9+e1xxxRU45ZRTrHI333wzpJQ46aSThtzARqOBSy+9FCeffPKQ6woI2FjhruQD7auV0BVJo7BFV80c0JXPoYBK4urMxBFdVfUoRhXbPuRmDAuEBCITkJqt/HXwwmnnJUUlNSWk5SVhYHZSMs81821zsygPFSOZ5Mzn+XH7L44iEx+hPXaU4ui2jzGGCLxAt8nL1Tsf2o4IHCkEOPKgcZdepttl0XCEgEzzFWtN0dKePUPHMrK/mQcu4mDZYNQUwoamX/FIJTvMvnOWJz6knoXIoiOq3zStq0EVtjg3krSu94/+y+EfCz7PgC/YvO59Ucc7orxVsL7XhXKsVu/gq68dVb6qoH/AT8f0UXF1e6va5QqA0H+9x/Z4XuizJklT9SzSnt+s7+OIO21hlvAEZ8ySCx7vGA6DIhgk9dGWQQIAxx57LI499tjKMqeddhpOO+20jhr0zDPPFLaddNJJw2LcBARsLBC3nQ0AYEdfmfOGSyZJvjwMLlzDQ73Y/MemCjCdGiXU2OCMfleTFkrz0p+HanT4+M6t4kN88PHSrQkVpLf97aDVPl6qnu5Lo8hk7+9OwOqg01wHw2HQlFGzhLTHYJUxUsarZ4A1AUtLxoE7sdYULT3pppMnluUc0QZH6plg6TKAipdCRm2RJbJKpk26HVAUQ8ZtOVkaH6KytecGii7TiCJ0ZXTA7jhWcr/Z9wldXeAMaESxnQU8Mzh0e6mMr5K/zrO0M1KO0i3pKdFYKhcuSajVfVkVk0GpXO59RMdVqzg1HyRky3upjjHSrnHl28dnTLvvAred3rw8Ds2rQFWtYYDTeDxDw9I0vihCVxxlEurZcbJ3h3lWZPVEjCHZiIySgNFD2wZJQEBAQEDAxoa+wRSr+1JM6mKY3BWUbwICAqoRPCSji2CQBASMQ9Cgdr0i1u7qt8/lb1bJXHe8WaElbWBF6kKnFC53VZ8GIZfRjFrW6fGIUJT1l0XrgL1y6ztuYaW2xUorDdyvQrt9KaU0XhJfe0wfD5FqV7b/aKgXuY6EVuOCejKohyQlQfVCAj/831fw/d+tNLHlh7+hBx86cGZL2kwVdD8VxpOuisnChIZp7wfPvR8q8N2UKHjlojgytC2AUrjysto7Qj0iExsNQ+HqbjS8iQw5Y5anhapB0XFMKVu6HP3sekl80HtrGhvt+7KxVeY9KHi2UPRatOOxsGh1GTWJ1tfq2dvqWHXuHdcT4t4DPm9JWbvcZyP1iPg87m49bl/ShLsaWm0QUB4SruVtbadfXme20aVUjmcE2d/RRTBIAgLGMXSsR5mCklWuhLLk+53+RsEYsya4vslGO8aDO4lW321DgBomVW1rhSqDqwwuxUR4Jkf05dkOD30koPtTtaVI3SqjmlRNvNuhbbUDN75lpJAKgcFM9hcAmpnylT7X9QMJbnxwpbXPnU/04jdPrsXVJ22PrliNANrWdsZfrrIlrfGkqWdUF9B373DODRWGjrX830zqN7JV3VjEjURvzHmmchThn295Hq+sS3DKW2bhgwfOU7/rrO2WUWEPZp98rTZGWt0DZYn+3HMF8nu/qo/LYkQKdXkoWe0aA8JHn6QLOSUULt/CRNWzsGVMSknb6Gd3carVONXPxJTI77aSCvfRZ90Eh3pcUEU2l5rFoZ5Vun5zzTIqY0CAi2C6BQQEBARsspAS6IqKk8G+psDff/dJ/ObJNRhMBP70ch8eeXEDnvnrgMnyPjLtkVi5TuDJv6Z48jWBZ1YL9CfDc7wPf+9pvLJO5Ya44cGXsfTZNcNSb0DA5ghXLavTv4B6CB6SgIBxiFYrX95Ax2ybpquoAGF/IKOeb9HgUP1vHuALi7rg7lN3Fbmwqi/z4HYg++x4XtqlbNHz9P1u6iVBl3T1TqMqkJaWaRmICr/nZzhBg78Bm2oiyOqt2691rlvdcsOt1uVrh308f3JMrVYFZKu5ZJ+JXRzH77Ulbv7dq95jXH33ywBetrZN7uLYZc5E7D5nAnabOxEzJsc5HSsbPxxFFS03UNjccyQZ5/97dAAPvWTnSZ8YAyfuFmNeD8tpXdmpM84NxQsAOGeIGio4PeJ5oPkPf7+6cG7X3fcSDnjdDHTFsfF0+NStAIC59DPHK2Ll2SFeVOoJ60RYwRzfOl6198GXaLBsX9/9R69TmdqXWdn3ULha1d/qHFyvQaF9kID2iBTGVPWz1xfALmR+R6RtXKBCPxHPVcTzcaDHlkt9A4rep0grt20EE/UQQzK6CAZJQMA4Az/mqoIalssf9nGEzXfy0nLVplomq3Nd7xKlk41OYhXUJDo3SoBiHIdrnJTX5eFJOzKYdSbKhRepZ0JDJ2MuXKWkVm2tizJqHJ3MmP7UZXz8dxTPz2eI+aRxy9oy0mgrg302OdLUKJ1AjuK4PbcoNUh8WD8o8Ltn1+N3z64HAMzpaWC3OROwy+wJ2GlWV07z8vD6dUZ4Se5BKYGBROInj/YXjBEA6EuA7/8xwQff3IWZU/IkiPr8GGOIMsoWj5WiUcxzCd8lj63Dzx8vZr7ubwrEETcKWi6sSXPJ5EtP/r0UJU2TsmiD7cW7UXqWj5al22Adr4TK5f7W6pgaenxTA5vebwV5bVQbT75juIsYPmOeLhgx87n4LnDLa2gD2E2c2MqIaQU9BvV10PEi+hz02KILMUqFzqkHDJKhdDwGbN4IBklAQEBAwCYNxhiu//vX433X/qWj/Zf3NrG8t4k7n1iLmAOvn9mNN8yagO44DzfIJ5M6K3smOSwk+gZS3PfsINYNlE8K+xPgjj818YE3d7fVtnv+sh7//YifmrXjrMlt1RUQEJAjeEhGF8EgCQjYyODqypttxDvgU1apQtlDkzFmZlw+5Zm6XhKXoqAoCVk9UKtqzFkxLAu6pXWWeY1831u1zQe9KqhXZqvUs/IEhkUPED2Wq8xUty2FPtTXliSWdBMnuhSuqvqr6FedeMMAFNoyEuCMISJKNlK5JqwyQkqAAcfuMR3//cjqIR0vEcATKwbwxIqBIdXjw4p1UlG0qAcgyznCY62YFWNSlzJalr3cjx8s7S2tb89tplqr+S7KPCJWGdhc+FYTLE2LrM7jwQp5SSgFjdbla6tPZatO21yU3VPUY0gprD7U6dsy+pbr7dD3iPLKOF5uTyLbsmeiNoqpp7zuGNCecM6QU7SgPSS2N8v1otLr6qNwRVwlI914PCQMQw+1DgZJXQSDJCBgI4QvsZWV/dn5vRV8lCU367JLW6CywO3GkxRlJWXhsV+V0deNGXGpWu6LW+/TjkJNFYZ71Wso14oaJq5R4lK4fHEzLspUt4ZK4Woll1yV+LPseFIqBaFU2tNbq1/IvofsOA0/e7wXg8MURN4pIgYcv0c3JkTA935PDBupDBDa11HEETViKwu7mtQx3PqH3kozz6gheQzpVhNVAJXGTBV0/EBZm/TklW5z40KKE+Xib2UxXlVw1aIAv2HixpaUxc65VDP3tzL4jIsq9Sv3+e7uq79LSBMnoq+vL+atihapM6+XGSC+OlLh6RtyPbUBwpnK6B5HG4NBEjCaCAZJQMA4B2dAWvGicjnCbuZqvU+nK9RVXOrhzFVS5cXx1emeD+0D30vb7adWnpF2tlv11ZjA6YnCUGMzpDNRKstTUpZ3puz47UoBj5R0MIDCWG65Qu+ZyOq2zZ3ehbPfOhuX37m8dpzD7nMnYt4WXfjLyn489epAx0HbGjtuFeGInbowa2qE515z4klYThMxk79ISfpqyd7nXhvEspebkACefHWw8lgsyxWhA5CpQa7HH52M181sXjV+coNDfa+SoQacYPmKuAz/pLp9Y6ksiB3wB5ublX/ym2uwuPt0AnfxJEK+iELL+DzfPo8IbVNVPI7bfmrA0n6hQezuuQopiCcp9zK5i0q672KuJKrHOwJla3QRDJKAgICAgM0Gb5w3Gf9w8Exc8+uVrQsDePSlPjz72gCO22M6/vGQLfGnlQN4fHk/lvc2jfCDgoT1FXohQG3smcix97wGFmzBOzJEk1Ti1kfW4u4/b/D+vuXkGFtN6cKyl/2/BwQEtIdgkIwugkESEDCOoDO0U/hWGN2YkTIMddXatzLoZgbvVH3LrPxJ53sbqKI45GU67wNNI/GtxFatzrqxHJ3AbXfZ8aRzfQSRNnah40ncffxliyvJGnWUusqUjMrgizdxpaar2mytmrfw2B30uqlY05fi5t/9tbJNGmv7BW747Wu4/Y8R9lswCW/deSpmTo2yNjqeyOx7KgWSVFhJ6UQirPYwD4/eeEiy3ClxFOG19QL/8cBqvLCqqNCl8bY3TMdtj7xmbeuOs+zs2vsgc1U297khpQQYq6RNAX7qlO8c9O1cNhZNWSc+wVdvFX2rsm5POdr/hTg1TzlKYQVy+paJdavVEj+ot8N9/vli4qpUtOg+3BlXrsSu2y80pqPME8IZs+rVdEmgnKLnu1frxiIFbH4IBklAwBiDGiEFTrDjri9DHQOg08zZrhSmeVE7+Qc0KIWr7GVEJ0NuAGzVZNNFWSC7j7bm0hnGGu22w5dFvqw+TfFzaTidokwW2GeUqOPXu4ZlVDzKgXf3daktgE33YYxVjnJtlL1j9+lY3ZdgyR97K0rbWLUhxZLH1mLJY2ux7YwGDttxCvbdbiJ41sl0QhuBQ2bzNzNxY6q1Gr7LybnKwi4BrFiT4s8rN+CXf+rDQIu4l8eX92HDoB1L86b502waFjEUgPxeMRCApvaXGdRCSsQVxqp1rPwwpb/TOIV2DI9OJ7RV9FKf7K8u5xomVh0t2uLG6viopb72qN/zzy5ly8267gtQb2XwRRmlL84oVPQ+KttHSlm4x11qcVmb6LmMdwQPyegiGCQBAQEBAZslTtx7Btb2p/jNk+va3ve515r47gOrcOcTa7Fw16mY3MUhoHKOzJwSYcbk9jnyAwnw+xcG8ZdXU/zl1WalTLCLR19ab31/y/bT8fqZU9puQ0BAgEIwSEYXwSAJCBhj6NVTDZeO5a6ila1ItqIm1fGOuCtiVd4KH31L1eGn2ujfSts3DAHeLtygUNqm4V6hs2hFNehawxHU7oMv0F3DBLTSa1izHT5Z4LK+rC3pSTwvLv3EPaeq4/naaiXbBFEpIuMh4hwfOmgm1g0I/OGFzmIvXupNcO19q6xtDMAxe0zB23ae5N1Hn0cqi+Pkv/7Q11E7XLx///mlQciAXyxDAGBZmzLGmLnuPgofZ+WZ3zXKAsZ9npFO1Kro+bSCO7bKxlOZwpaG6/EQUgLEg1nHG1hUynKTIEpL6lfIYtZ1Lc+bS44750e8I7SPGcslljmzE2fW8aoKx+siPOenjzVSYhcBmx6C7lpAwBhDSGH96UmZqwhF3dxVxsVIucKrVGXcTM6c+f+GdvzW9eiX9lApATk9QtMiihm5xwJ122CNFYe2NlSUKSB1+udOat2xPhLgLB+/MWc487BZeP3W5QkJu2OGT75jDo7YZSqmTWj92pQA/vuRdfjNXzaosSMEBKFtKeaUxM+W9bfV7oNfNxlXnDAPC7bsqiz3uq0n4YDXzfCu8Jq+RzHvh44LUFLKHkoXciOkLK7K/XOPq/KNcO8YKBsjPnTybCkrV30c+3zcsq5hQp8/VePY/c39bJ4/2edUCEtNy+QKgd0HjP5H2mzOgVC0Yh6hK47RFUdoRJFRc+NM/THnvyrQXE3cc23t8xofz9NWYIwPy19APQQPSUBAQEDAZo3umOPcw+fg83e8iJdWNwu/DyQSGwYFTnjzFnjPm3rw6Ev9+H8P9eKl3mJZih89tA7dDWC32cVX7dLnm3hhddqybVtNjrDr3AnYb8EU7DxrAoSUOP/wWXj4xX6s6RN4dX2C/3nCjoP5P2+ZG6giAQFDRKBsjS6CQRIQMMaooqio34vKKnQ/l9JVtq3sWFVw6Tw+JSVLNcizilZHcYqz1oGhdvnhWe1vFy5Vo1P4lGaqAmwpyjLZ++CjZPnaP9z0sTJ6jxvA6640t2pD1e91V8lpskiawX5Kd4SPHTEXl97+Il5bX1Szeuj5DXjD7C5wxrDnNhOx+5wJuO/p9bjnL+vx2gZVvrfPoV8C+J8n+rDLrKmIODNB7q+sTfH/HimnZu06pxu7z52AN8zuxqypDTSiyFBquqIIE7o4DttpAuIowr/+/AVr362nNLBwl628/WFdl6wvGlmoSzNVXhzzfBECiGNEGf2Nqu2V3QM+CpSr8ETL6TaVUTvde9x3Tu0m3Kx6dliiHRV0LjfLvItWAhRaec2llGovmvEiZN4qtx1uLhFdh0vRo94RvS1iDHEUIc4SbUaZx8p3DlUUSd+2iDOIjPLHst9T55y47uONwEMSMLoIBklAwBhh8Mivqg8lsQ8adSeKPopOXUlJCnci7L6Uyn4vq9uX7blg2FRkEPdNVDtN8tiqXp+hUIZ2DIOhoIyjX/f4rjFCDYFODZF2uOFu+ywlOd9YrVFv1bENVUSX1e3w7OtmsJ8xOcbHjpiDz932Avqb9jF+++x6bDklwq6zuzF3egOcMxyww2QcsMNk024hJW57ZA2WPKaC5GdNjfDOPSfj8RUJVq5LsXJtglfXCbzU6/eMTJ/IcfK+07H7NnnsScTVhLERx6bNUZbwcOXaBL99xg7IP2GfOehu2K/2atlqLfea9QWJaUvSFDKj+NDYBTfmw6fAVgWfepPfgCqvo66stk9O2lUFtMp7KG5AtVywqse/cED3oYtKqRBWzJQlDy0FIJmhz9G2u+dEv/vic7QxohNrxlGErjgCZ9wqWwX3OeFTAyvbx9TPGETa2iM4vjB0DwlqjtOAYJAEBIw7UFlHwNafB3Kpx6qJm1uH2lZ+zE4euu1MRnzxJ+7Kadn5ULnhdgwRxljB2KvjLbDbXftweb0dvsBGKsjdh6FO+jtBWQ4Fu0x7dVZx9F2PYivo/p87vQv/Z58tcd19r1q/rxsQ+K//XQ0A6JkYYedZ3ZjY4FY+HQkJQU7i5bUpvvWbNbWOf+AOE/GuN07DlO44m0Sq7VEWdMzJ9ziK0J9IXH7nC1YPTu6OcPxecxBHUWkmbhfaUOuKIiQMGCx4YiVEKpGkamKcpCnizDgSKAa2630KxymJu1C/eZtmt38YJnY+6fMyj0ldKfO8fLmRrmVyaZ/q5zj1ICTZ51RISJkao4W2H6i4lqxomGhjRHtEumIVO9Ly2YfWz4Cq3zeNIHeGoRsUwSCpi2CQBAQEBAQEEGy/1YTK33v7Ujz4zPBlRN9vwQSc8OZp9dXJAPz7r17CU6/aQfHvftNsTO4Or/WAgICND+HJFRAwDlBG0aLekTLvQJWq1FCoTa3iRWi5uqiU9yyhJvlW6uqupKtz0J/9krJlbaxCq1iS4cjUXhftxpQAoxdo6Y7rOp6+VpKpdVZYW1FKXO69XiU3VLaWRxg+bLtFAyfvuwV4Rs3SmbIjQrGJOEPE8u/L1zTxm7/Ynpc5Pd34+4O2Vd4REjvgouzaK3oNR1c2K0iFv88TIdBMVcyMloxtJdvrxom08ojUpmNV0C7b8TbSmJUy6lgdyWDXa+zSEIX5V0DIjBKXbRskn5M0BTivpGnZ7bO9T9RTor0j2kNSxztSdj4aPg982f3su18zQeNabRhLhKD20UUwSAICxhg+Y8R9gdnly4PW9T5VUpNDQVUQdp19gHoT51au/aEEtbc7YakzOaIGip7UDJXC5WIo9ImyOI6RfFkWRRhsw5pKmtK2VMUk1aFh6WtBs8bTiavdF7pMqzBlYJvpDfQ3Bf66fvh48NtMj7HorVuZmA8tiRtxjoaeQEaRNaGPOcd/P/yyVc/EBsdVJ+2BGZOVdHHEWMEIAIrB5O6CQxZVoL7z3HCEyPstFQLNjL6l40608eTrxXaNkSqUCTJo+OKlCuU9tC1f23yxJ2VtKgv6dse+hjZGUiEMTUvHlejyrCRQ3W5v8TcrgJ1nlK1MzhcAeA0vnE8MQ0IaI9VdXKiqZ2PGcMj2Btnf+ggGSUBAQEBAQAu8uLqJy941F4kQeGx5P1asSbJJWV5GT8Amd3FsPZWjETHc/Ls16GsWJ2ZbTo7wj38zAxO72puwPPLiOvziiVXWthP2mYNtZ0xs/6QCAgICxgmCQRIQMELgx1wFoLhCrBOO+RSG9GfXa1KWwdr83oKuNRISuWWehqpV99FSpCrLHNwKZYo/Q2m3l7LQgvI13LCVpYoryiPVFp8nL195LnpG3H4vyr4WpYNbwVUWc9uXtym/jyY0/EbCJ378Ei595xwcttNU0kZ71VirVK3pT/D1u1Z5jZHtt2zgfW/pwRaTGxnlKf9Ne0diy0OiqDZPvtKHy+54DgnpmEbE8H/2nYeuOLJW08u8I2UJTo1nKf8hU0JTTr6y/hNSGNeIpm/VVdEaCdAxXeUlAco9H+3QLetK4gIwz/5UCCRpisRS1rI9JFHWDppBXddd8Gw5/Z1TD3PviB5PdQLLfapaNJM8VQQD/HStMi++auvGkTAwULZGF8EgCQgYQbSSq22lqKX3oROzAhffoXe51ICyttRB3ZdXnXpa7V/WPj1JEoCew3rzSAwF7b402i0/nqgLPuOkk/ZV7lMyEaTQ1883UaU5dlqBKhaVN6dkYqqvo1TjSVsGs6Y18IZZE/DEy8VM6p/+yXJc8s7ZmDm1kZ1HbgTrRYaVaxN894HVeHmtTe+av0WMfzxkOqZ0q33jyJ6U6UzavjwRr6xLcPFPnkZf0yZGnfSWeZjdM9GS1/ZReej2sj5yoe87nt1vvnKpkADP2iRg2u2iLKeIL26jLAarlULeaCnVCSnRajrtPtclMXiFo57llmdQ8TnKMM1ih3iERKQYTFIzzoSUllqha/xp+p9SabNpXa3Oj/6r207zpJS1v1X/6+f5SC9ODQeCQTK6CAZJQMAwQntFAL+hQFeRfCu9VcZIdVxJteEzlqj74mmV78Qq6+GBtzsZqeK1t0y21oaHgzMGX9SBW0dZ20dSJrMsIL7Mq9Nuva3aXmaMuJObKqNV3yN0suS7MlWxKVT8QJUFzj18Nk6/4Rlvuz/zkxX4m9dPxhaTImw7owu7zO7G8t4mHnmpH0+/OoBHXxooTMBnTY3w0UO3xLQJsVn11vlE6HnqxHV6oqnzRnzrnuewus9O2Pj2N2yFf3r7DoiYHcTuTqSqgs01yvIK6bgSnbeCKoHpRHcmAJ4LCMEAMgFuda/U9ZwUnmmy6B1olcyvFcqC2u0y2TPaOa7PK5SSnC6uh6Eq/0nEObriGDHJPwOoCVvKpVWv25aIM3Ot9HiiwgNmn5Jj03tPmvbKrM25gWL3SbFeX7LeMDkPqEIwSAICAgICAhx0xxxf/bv5OO+/nvf+/uu/rK9d1/SJHB89dEtM6fZ7D1ph/UCKB57utbbts10PLjt+F0SjxYUKCNjMEDwko4tgkAQEjDBkyaoSXYkqyEQSJSK6ne5bRdXqtI0uhro6P1xueYu2BepFUd91pu3226e8IVXtrNMHrdR/qqRWxwOGwwvTSqq5LjgDUstbYfcjR87F16hSnauC5Zn0eBWnTeD44ru3wRd/ugKr+zpT1+qZyHH2YVthqymKpuWLGYmJ16ErjtEgK+MRZ3jg6dWWDG8jYvjqibtjQjx8r3Cfl8xMyIQwv8ecA1l79ap5rsAlIWSKSAjjSeGcg6PcI1lbzcopp2lEUtIYJOK1cPYfrnutI3qjQ3kqq0crq01oNDChq8vr/aHn6XoiI8as55kvPovKW1fBvSfcWEWXDtyuB3VjSJCo+nuoKlvBIKmLYJAEBAwzytzWPrneujEjtC7fw9/dv5O2uhgvLwwdx0IDbnU8SSfUNHcyRCkovmDOTuofrRwkZRjpYHWNdnOCdEqrc88jIhNiyPauky8uikqa6jZrWsxWU2J8/l1z8djyPlxzz1/RTOsdqxEBh+00BUfuMhWTunIKDcsC1AGgkRkfeQA7R8xV/IienDaiCPc/beccecv2W6BnYlfpsYfjulsGCqFg6TgXDd+zKHGuOZhr7OT3ob6HWfYf3eYij/nJ99XGaYQ8c7xuZ8v4twoJYBdV8Sv6WO0sbLhiCxwA0/EisaL1ubRCZBSshMQ+Fc7JaYO555z4kmL7yOcsaF1vo3QtXbbdRSw7KF9A1pDaDti8EAySgICAgICACjQihjfOm4QvvqcLP/3jWryyLoGQwNOvDmBNf3FiddRuU3HwDpOwxeShv2ITIXH/k6usbYfttOWQ6w0ICKhGoGzZOO+889re51Of+hRmzJhRq2wwSAIChhGud4SqkfjUsXxZ2Mu8I3VUteq0q2qbkBJsGDwjdahaQ3lQc8Ys1S3OJGouXBfqaUX1qOuwr0uDYC1WUocTI+kpqVp9trx5Du2jus722uA7rzIFJF+f55SX6oBcjandMf72zdMBqMXpZirwmyfX43+eWIdVGxIc/PopOOHN00vjOnTiQ03H0tQsXT7mERpxjC6isrWmL8HaAZsuttXUbuu7HsMjNfnh5B6xP8PyflheJpQ/n1qJSFQlA7S2S3Xvm+NJIMlW3qnqWBlc7wj12lBvDQ1Ir4uqsa68vdKimqoA9ExZzZH6pXXSNvsknOk4KHvOVHmGNJ2KqoKZ4w+DWMp48bzXA8v+hlpHfXzhC1/Aj370IzzxxBOYOHEiDjzwQHzpS1/CzjvvbMpIKfG5z30O11xzDVatWoX99tsP//Zv/4bddtvNlBkYGMAFF1yAm266CX19fXj729+Oq6++GvPmzTNlVq1ahUWLFuHWW28FABx33HG46qqrMH36dG/brrjiChxwwAHo6ir3zlLcc889OOuss4JBEhAwVnAnY/odbYwPx8jwGSOtJkdeFaQS5RMf3BdNHVWldlSlOkHVC5zStsrKWu0rqauMu+47VrswbfKcf1l/j5RhMtwT03bHi6aJ+MZ2K8pIFWXOZ9T763Inmh6KDdkuISE9dDIqC+yCMaARcRy201QcttNUCCmtWBDf8bWkb1eUTzwjztCI1Ku4K47AGbcoWzOnNbBgy0l45q8bTH03PfAC3rbz1oW2jtZqrKZs8Yx+Q9uQP9/UtlQIE0eiy5Sh7Ley+0TAvo/pvVtQ6yPb6saqtNNGbzmHciUJPUtKpowpYzzwlosfXsVBYiC6CxDuYgvgPz9X2U5IYRlhLk247PkrKxZbrNwphJ4XYOPuu+/GmWeeiX333RdJkuCTn/wkjjzySDz22GOYPHkyAODLX/4yvvrVr+K6667DTjvthH/5l3/BEUccgWXLlmHqVJUj6ZxzzsFPfvIT3Hzzzdhyyy1x/vnn49hjj8XSpUsRZc+Wk08+GS+88AKWLFkCADjttNNw6qmn4ic/+Ulp+2655RbMnDmz1rnottRFMEgCAgICAgKGiJFSu2KM4f0HzMcl/73MbHvwmdX440trsNvcaSNyzICAgOGlbK1ZY8eBdXd3o7u7u1BeGwca1157LWbOnImlS5fikEMOgZQSV1xxBT75yU/i+OOPBwD8x3/8B2bNmoUbb7wRp59+Onp7e/Htb38b3/ve93D44YcDAK6//nrMnz8fd955JxYuXIjHH38cS5Yswf3334/99tsPAPDNb34TBxxwAJYtW2Z5ZGhbenp6ap/7N77xDcyaNat2+WCQBAQMI6zVWyd7rV5lKvOg6G1ufb7t7rZOXek+rfiyVecqHfl2V/o7SWBGVz9d1S1N3dC0Lc5YQYnJheoz1Q5djz7GUBV5KOWjDrWpqv+q8rGMF0gp8cxTT+G/broJL77wAraZNw9/d9JJ2G6H7QtlXU+Jb/yXiTa4XsZUClJfe2PT5w1p5XkBYFF5GBEw4EzlD6Gr0+79FEccEeOGkqMzsnfFWVA7CWiPiRfl6D1m4eq7nsar6wZNXdfd+zz+7wm7m2N7ExuOgMfETbAnZU7/oclKKYQQ4CUJEyk9q5RixBjEbWcXtkfHXFXwzLHbF6m2HH2ltR/LtqVCFFbnaWC9/5xhvBtVwev0frY8cFKJGRQCzrNM6oDKNyPSxByvCub4ZKzRfymlTlQ8t31t1zlS3GzsdZ7ZVblOTJuzYH1e4k0cT2CcgQ1xoUHvP3/+fGv7Zz/7WVx88cUt9+/t7QUAQ3t6+umnsWLFChx55JGmTHd3Nw499FDce++9OP3007F06VI0m02rzNy5c7H77rvj3nvvxcKFC3Hfffehp6fHGCMAsP/++6Onpwf33nuv1yD5wAc+UP/EoTww7SAYJAEBwwD5jq+pfwlNRRsjKUnYJhyKg0+txGck0H8Lx66galWpcQ0HRoKeVed4ruqWNj4opcul2/h40268gU9OlqJKvpeZtmUTGKdNVdhYDRN9jj+8+WZ88vzzLeWgb119NT7/1X/F8e99L4DWk6w6im96gp9m91CV2k+dsenGkNRSDSNjyJVY5ZyjQfj/iUiRpPnkSxscekxoY0QnsqPGSGRJAXOc/JZtcOUvnjbb7nx8JV5Y1Yd5W0ysPcY6uV9daVlfnBm3pFGLSf/o/jrhI538lxkj5p7yGCO+7fSw8vZFhWUaefsiRJlRku/TYpLtPDdKY3VI/+pnkyTfI8CSSzbJMTX9jdnxa8qYcA9hL2AV1OeyMVgnKaZbr7tw1g58hkjZmIyyZ0S0ERgkw4nnn38e06blHk2fd8SFlBLnnXceDj74YOy+u1p8WLFiBQAUPA+zZs3Cs88+a8p0dXVhiy22KJTR+69YscJLvZo5c6YpUxfr1q2zJK0BWOdaF8EgCQgYJrgeD22MmNVcIWplXm/lDSlbwfe9vDqBlU+C2ZMGitEKzPbBjfNQfG1AT0kof7tqIq9lQ5msfoH7pDTbgY+LXRaQXdaGqvbVOfZwwa3vmaeewifPP7/wQgKAT553PvZ+y1uw3fZFT0kZfAY6nSxRr4hv8sRLJre+c6CB13WFH9yYBbo6naR58LnuDy3lCxRjRuJIGSNdOsjdY4yo4wB/t89cfOue57BhMM3OAbj1Dytw1lt3GLHYkbKx466cc2tCqmIjzDWCtAx/KaU3zsqqP/NyjITpTWk4UsqCweHrS5VfJTOoPNdGLUKUn1PEuYqlyY6jR0k7lCDfs8PdV42nYn1VfU5jfYB63nZXstj9rQxaEl1CIt4IEnoOJ2Vr2rRpbU/SzzrrLDz88MO45557SuvVqGIwlJXxla9TD6A8NWeddRbuuusu9Pf3F/ZP0/bzNgWDJCAgICCgY/zXTTdVqiH914034fxPfmKUW7XpYdqEBo7afSZ+9L/LzbaXVveNYYsCAjZtjKXs79lnn41bb70Vv/rVryxlrNmzZwNQHo45c+aY7StXrjRek9mzZ2NwcBCrVq2yvCQrV67EgQceaMq8/PLLheO+8sorteI+TjnlFADAd77zHcyaNWtYFkWCQbIJgB19JQBgME3R+Om5Y9yazRPUO+Ly3elqrPu73pfW46KUwtVCKtjXxjrwSUlW/T6eoBfdUtk6jqQsOVsdaotN0ZLOCrFajTTXp4Nl3k7pNT7UradTT8rzzzwHUSLpJqXEiy+8UDsBXZl3hN4zblyWCyFlQd2oqs6yelrdL8rbwa3VdiGl8ZLoBIIRI4kPs33o9644NopaXUQC2Iep3e4ru3zC5FMWawel3pEWx8nVlnQ9AEOepbwslmS0IG47G9ExVwHIr5nr9aLQnoNif+afI8Ygne4VsD0xOt7G1EWoWmWgtC1NAXQ9kYwxo+6mPXA+VKla+eJFrBg95Mpg6nxRON86x2SMmYSP2msYYENKibPPPhu33HIL7rrrLmzveJe33357zJ49Gz//+c+x1157AQAGBwdx991340tf+hIAYO+990aj0cDPf/5znHjiiQCA5cuX49FHH8WXv/xlAMABBxyA3t5ePPjgg3jLW94CAHjggQfQ29trjJYqPPzww1i6dKk31qRTBINkE0JXFI2IizugPVBDg8aMuDx1d6KlUcdwcI2RoRohGlUrQuPZEGkHVkZiWT0haAeUTuHWWzbhHQmqTZ06fe2xcrHUHDfJQIpo9TQw+O0uxhi2yVb3yrJwUyPSPX5BCKLGE85ngFC4xo3vN3dfH3VRGRY5HSsVAim5pyPOTMyInjDGkf29UQhgZ21lD2dsZHLMVKFVXJWeuFr5Z6pkdpkdh6PKjyxo7IkbGG/KWEYtwFh1zAOdfOdB/tmihVs2o5RGnLeUvzX3R4nRzxkK/Ufb5N47eny5tMdW1wgo0tWq5L99MSL0/TLa47YTjIWH5Mwzz8SNN96IH//4x5g6daqJ5+jp6cHEiSpe7JxzzsFll12GHXfcETvuuCMuu+wyTJo0yQSR9/T04MMf/jDOP/98bLnllpgxYwYuuOAC7LHHHkZ1a5dddsFRRx2Fj3zkI/jGN74BQMn+HnvssbWMjH333RfPP/98MEgCAgICAsYef/mfV/DmeUfgNtzo/V1KiRPaVFoJCAgIGA8YC4Nk8eLFAIDDDjvM2n7ttdfigx/8IADgwgsvRF9fHz760Y+axIg/+9nPrLwfl19+OeI4xoknnmgSI1533XUmBwkA3HDDDVi0aJFR4zruuOPw9a9/vVY7v/Wtb+GMM87Aiy++iN133x2NRsP6fc8992zrvIFgkGw00CpOGpwx40rWwysRKYITdPTAjr4yXyHyeD3y1V2Y70JKy+XeKlN7HXRCN9HQK2tl4Wfj1StSFqDebt+puopeEndl3BeIbntEyilW9rUd2UztbSVty9BK5a0MA+sSvPC/qzCzZx5OOfR83HD3v6rVXiYNbeeyr34VC3bYofRYPrjHF+T+0KvEnQg20H20wIQrFuGiStQBgJUNPOIc3KG96CSInFJqGDMULe0daUTc1NcJXJGHkbxv3aDYssDmVuPKJxRRpqY1kqDH5ITKRcEZbyn1W0cSV3sN0jTNxBecMi1oVXr8l4lsaLqoW4+Q0rhpIm571ZXMb5n3Jael0uMYWp6nDb52ufW1kmTfnFHn2cYYw8UXX1wpGzxhwgRcddVVuOqqq0rLzJgxA9dff30nzcQrr7yCJ598En//939vtSsEtW+GEJm7lz5MBpMUE8e4XZs6uMM9pvEcOrOtFUMC+3uZMULd8XVebD50qqoFUN366lwAnWIobauqs2oy4M9wb+9PpXoBlcukalLgo1mVbdP5GEZaTKbOdakyQFrlFygzeJ/5zasQifpt/52Pwuvm7oHnJt6HlX99CfPmb4sTTj65Ul3LVZtz7ym9jd4fdQ0alyziixfpxHgFnL5EsS+ppK+WYTWUrMxIiTMDpBHHaEQ5bce80F3lJ/27pz0jZXxoI4c+G0x7yMS0QJEz++p67Im2kBKRJ2ZjLIwRF7oN/Jir8jHUwuDyZYJX20lOFod6qH8TEkZtyorhACtQq5KKCR5dHCmTUzayzal9L+n4kTJKJT1GlXgFc8aJL5ZFG0JlqnbjDYyrv6HWsSniQx/6EPbaay/cdNNNIag9QCHiHH3NJgBgIEmw+sDPoW9Qfe8bHMSGwUHs+8QVY9jCTQPuypnr2aAPWjuGJK/DF8yuJ1tVge4a5oYfwRX20mOOA7QTdO1b+aYSr245d5JJkxq6fd0q9mOkYkOGAmvCUmKAtIpj0r83+1M8/t/LsfyRXuv3N/7Nbjjl3UeY4/ja4E52yiYmVIKU3h9VqJKoLYtDqaq3bMXX5evriaIOcDf5JYzxEZncGzrviJb91TEEZd6XuuhUBMFnSFN4JbDJfr6cHBwAODeTi1QIq9+kVNeU8eyZp+s5+koj9zvWELedbZ75QIvnsef3OnFAUkpr0l64FsYrWAxip59pckVdHfXald2Lbr2t2loH2gMIwLSJvtsYJJKNwBAxYKylRHWtOjZBPPvss7j11lvx+te/ftjq3ERtt4CAgICA4cbq5zfgvsVPFowRAFhw4JZj0KKAgICAgNHG2972NvzhD38Y1jqDh2Qjx2CaopkkAICBZhMDzQSD+nuSoJkm+OWCMwDAZAjmDIhYnk2YrqJolRe9yrfbw18e7VMaV3BXyVzvhhsfYsWQwF6ZpfXo3/Xqr6vM5VWyIRQBd21ruDwmwxHENxLw9aFLmdPbO4FZxUOR192Jl2SoqHs9O22DxTlvgcH+BC8/vhbL/7Aaf316vVcC6fVv3RpTZtqZh12PSO51Ir+XeTVIzMhwUTuqlOnKko1q6BV+m5qC7F8SQ0IytWuqlvaUAJnKFo8sClfZSrt7jVjJam0dz2HZ9XaP57bFtx+lder3iXMwMJl74SLOvW3UcQRRtg+QS9iPB0+JL7akFaz7UZr/eSXIq7xTvgS6dPxqzwpn3JL61YpvrofEfQ9J8kwTMo/5clHmsXfPR88j6Fj3KXIlaWrG2Xh8z7gYi6D2jQXvfOc7ce655+KRRx7BHnvsUQhqP+6449quMxgkGwnYHf9kfZfv+BpSIZQRkhkgg0mCgSTBQJJRuDIDxZWUtA2QjGbg4QkH+GlWQP7CcONDaABuGUdeow6H3ZfLQgCFYEL3hd/qOpYFRQ4HfJP1dibAQwE9Loea9JQFUlYZFVQiE6iXQb0O3Mmc7/eRhI+iBgAbVg1i2S9WYN3KAfCYYesdp2LijAZefnwtVj6xBqLpv27xBI5d3zkXs3dTGYipYehO+rOwCet+oLSRiHMz0XHvHRdlE2VdDz0/l9vv9kUZ3PgIPTkxtBio3w1dJpuQ6QB2aozoMt1xnJ1n9XF93zljWN7bXyhfNWZ8dZUagbJ1Fme93TXKXHoZZ9Kcc5Km4KQ+IwKRlU0BwKF1tTJMxFFXII4iNNPEHJsvOcdbdjhQZZzo53od2eyctsa88Wo+SqOLiDNwloskqOzs+QKj79+qOnWskO+eqhvPyLM5hI8iZso42zaGiXoZnbLdOjZFnHGGWui+5JJLCr+FoPaAgICAgI7w+x88h1XPbzDfVz27oaK0wvRtJ2GP47fBxOmNlmXbxXNPP41b//M/8dLzz2POvHl459/9HbatCJDfHLBq/SDuXvaqtW27GZPGqDUBAQGbM9wEncOBYJBspGB3/BMYgCnZn8aje3wMA82csqVcqbk7l1IPgNxr4lsJDLADCn1udBN8SyhELo3LRVWwo08GWO8zkkGuw3W96eq3r+46x/GtyrmypnXhrgjXC462M7i7CkF1+3Wk1bWGArcf1r06UHvfqItj+4O3xPYHbwVw/3imVETdX0nq0OykRCqFuV8iIcAZw4++/31c+s//rK5dtnL+vWuuwae+8AUc+3d/Zx2namyV0U1cz6Zvf5eelW/PVzx1pnatmBUxRdnyBbV3ERpLVSb2svuDM4Zv/voZ9Cf58yjmDO958zZt19XqHqTNo1nC81V3u4xvFVlrRAEAjyNLRdA8J/UGKSGz95Qk6b8lJNhRV1j15t5niTRJwFn183QkQJW4NMqeCTTpp1bFBGwamy95opAAc94fnHEIJqz3NWMqS7sec5T54B5fo5W3mmVpTqtkmsuexT6vIoWROs7ojeMdgbI1uggGySaGgYy2BZDsrY7EIieUAQaGPR/9v6PezvGM5sLL8y8lnGs3XqTMkPDtUwUTH0KKtTJGyqhHdSbPo/GwbDfeYij0Lj2uqdxmrk7mN1B8vHkqWVpmlJTRnwrnU+L2d4/dLl2r6rh126ax7d4z8OQ9r1SW2WqnKZizZw+23mkKoi41mSjLdE4lSlOnv6naFTUOmkLguaefxqX//M/26lv2+79cdBHetO++mL9gQWU7pXNvuoZP2bhy+58xZuJB1HkIS9FIUWXyeDwaM6J/18aI3qeT+40zhhseeB7fvf95a/sxe87GnJ4J3n2G474uo5RqSVrfsaw+1BNtqRS1DA1SsoLCk5ASIi0+r/RXbQgaqtISm8I8FqCGSR1qk1LV0veNykfUarHEjdXwqWi5SmdeZTTGLMoU7f26SnMtn3MllK1COTB0RdwY6QEbD6688kqcdtppmDDB/9xx8e///u845ZRTrISNVQgGySYGHT+iwcgDjWeTgcZmaLGzo69EItQkqZkKDCZNNFObv64nElFm0PlWR9wXiC/IvR0DRIOuknHYLwxtnGxuKy3DEXdCX+h65a8daG+JG1NShbH2MFYZXGV4w5FzsHZlP1b+aa33993ePQdz3zQdALJ8O/5j+T5bwbQVgeWMMfz3t78NVrH6+uMf/ABnXXhh4TdqgKSZp4UeX0g/xcCdvNFVW9eREbGMr088IJGzOk2DerviPIC9VcxFVbt+8ofl+MIdf7Lbwhn+4WCbwlZ1nY2h3sbwLyTts2yN4sp3eT3M2lkZ9HmSS1EyVmisTcyjcRHoXgb3WaXPOT8fYXkpKHxy1LROPb7UGHeND2QLjFWewuJ9Rt8xrldbt8NnXNI20+NEPBfCoeAsH3M0ueJYPyPrgnEGNkRX91D3H08499xzcdJJJ9U2SC688EIceeSRwSAJCAgICKgHHjHsfdJ2ePLXr6B3eR9efnyN9fv6VwdH9Pjs5ZfR+N71ePm/b6sMul7+wgsmvmT5Cy9gzrx5OO6EE1p6TTZW3LXsFXzq/z1e2P7Jo3fGjrOmePYICAgYNgyH4bQRGF51IaXE29/+dsRxPdOhr6+vrfqDQbKJIRWSxIzEGExTs/IvpASEgIQ0NIPNBakQ+Ypc9pmuqAohkGrebcZb1yugPpSpbrmos7pPaUSaslXmXtdl3P19GAvFtCoVn+FAHYocRdnqfKtj2Hzp8piSkUSZh6gOVatdSCkRNTh2etssCCnxxM+W46lf5wHUq5/v86rGabjewCqviIXeXnR9//uIf/LfYEmCbRpxae8yxrBu3Tr83RFHqHd8RsH73jXX4BOXXYZ3vPvdALLM06SPUimze15YdflWld3YCPq7K+tLtwEoKGpR70hVvRS0TX94vhfn/eDRgjrcore/Difvt21JL/mhx3Cni7WUpjXUCZqKI4igxctTHVPipSxl3oFx7B2h1K3SexYMjPnvHQ3OuDU2fHFObqyI75rQOKesJq/ylX7HCLItK67/V/5ucfbRtNQq74x+rrr3ScDGg89+9rNtlX/Xu96FGTNm1C4fDJJNAA/urPi0yvgAkoyKNKV7Arobsfmu6Fz2A2xzyTMiSZBemsnz0oD0RAogo3Rxplzg0nlg+ibbPolf11hplX3d1ft384yUmY7D4fKuekF2irrtKivnm4DXDUandbixBO2gVQxGp5mxW8F3vLr9ORRjxMUW204GkBska17sQ9pMwWNeSkm0PlPjr78f/JFHwf7392g88QTYwEBWBuAvvQRGVtGO75mO77z2mredQkrcd/fdmSFq47JPfAK7vOlNmAx1fzeddrUSWfAZDVTSV0+2aN6QOIqMKIj+TgPYuSOpTtGK8jSYCHzq/z2GwdRejvjAgdviHw/doWV9PlDDui7ohHcoCx+WgZ9N4OMsKDySEoOZNLCbKyPJntHdx1xlSe+OR9Ds7vqZRSXHObODy6vuV997pOw5yFkxF4z9PrGfjdpgyfUDImXE6/saAIfM4/DIfuQA1niKHNoYLS9A77H8PvLdF+MNIajdRrsGSbsIBklAQEBAgIUttrXlZEUisXb5AHrmTywWfu45sEceAUuo7rwE1qwBf+gP4I8/BpYp/7XCgq4uXDJ/W3zmhefBODfGupQSBxxyCO779a8hffr2jOFnP/4x3rNwYRtnOX7xnd88i6f/aksvv2evubhw4U6b1AQnIGA8wwl/6riOgHoIBskmgMHsBR1lKxApUysdiRBoJgmawpaKBDYtq70KRgFFpBa9ygqCdVZQU6Qq+RTn1kqvb3XKXZVvq22sSGFxV9aAImWrXt3V17fg6RlBmpUPVeOvE9pXWRJKlwrSDv1Jl2+lutUKLj2o7rHrolVf+bwD/rGcb2tMjDBlZjfWrczlgHuf34Ce+RNtz8gDDyD6zGfBnIDxTsgYMo6RHHM0Fv6fk7Dr6lX48Q9+YMWJfOPyyyGl/26QUuK+u+7CexYuxLVf/zreeuyxmLutojW5iSitldrseeijsNIAd0rhNLK+JNGs+s4REwpXI+K1aE7u2Hj2rxtwza+esbbtPncaLn3XrhaFtJPx08pL4q6ktzpOXe+Iz7tBt3UfcxWSNDUekVSIgjpbV8sjjT1c+pbr3WjXe9zq3i5kfy9R9HO9f1SCWE267WeuosoJ67mn9wXUM1BRAG0KmXss63smUqCPX0aHDth8EQySTQCU05yI1Ehu9m7YgO5GbD0UI87xxkf/dczaOhbQKjv591wVC8hkQcmEijOGVKhYE1HzoemjsdSdVLsvg+LLob0cHEOhEo22YQL4FYA6MUqokUmNEZdWR49Rt15dtmpCZ/IKVNRdRgEYyjVrR42slSGiywgpMX3+JMsgWf1cH+YfQMZ3kiD+t6sLxki7kIwhPewwDL7/VMjZswEA86f3WGpaUkpsPXdWaRyQFALPP/ssAOCH11+P711zDc793MU48l3vgpCwJj/UGGlEsdlG7139rNQGi55EaZqWuw2AyQdheP41jVZK/5NS4tLblllULc6AS961q8l3ou+NunKtVj/JIhXHBZ18dmo0+yhaVRC3nQ0OICZ5R+gzORUCfYf/X0y884KO2jPaoPQtH7RBUEZ51KD9SL2F9B2TCoGYx6Z8YTHLqZYa0AAgRQrJWB53pe8BqGzy+rNFdczGEDX2fbRHer9SY0Tevghyw8gKZQwLgotkVBEMkk0AdOWvf7BpbRcyf7BPnTBhs/GM+FD1AvclhnRXuFrV5zMaCjz7moHVXhnJimONRQB7p6gzBmtNriv60jZO6retU9Rd/eQl3hJgdL2WPiOE/ialxPRtJ+KFpavM9t4X+qy4K/z6HrDly2sdT3IO8YY3IH3zXpCzZ+eTHx5B7LwT5Jw55ftKib6kD717vVat2qyvd5pCCoHLP3sxdt9rL2yz7XaF66M8HvZiA5Wn1QZLRFaA3ZgR10DRORh8BqvIPDtlHhN9Pf5r6Yu4/yk7hubUA7bDrnOnWf3hg2vYlJYh34uxLN7dnDLlY5jW2UnMB19yDgBlmDDG7PEGoO9wlTNrUlfXuA50B9T5s6OvbFnOHxeiPHS+YH+6qBHx7D1VIkuu4xGllAXvmpTU2PC3iY5XnwhELgbhH/duexhj4/66UQTZ39FFMEgCAgICAgqYvq0dL9LckKLvtSYmzmgAAKJbfmT9LqdPh5w/L//OI8jttkW615uR7rkHMHly216vVKb41fKf48fP3YTeiauwzYe2wYvfeTHT5mBgsnzyzRjDkltuwYf/6Zy2jjlWePavG/Dln/7Z2jZ7WjcWve11Y9SigICAgNFDMEg2AbhcTEodEUKgK84Z3W9+7Kuj2bQxg3aX+5SWqiYwZn9WdJdXwUqQ2AHtqR3ajWrfyKy6jIUHrZUHw7dK6Ho/dL+3Q21rB66njMo8+yhaUkqz2t4JtaYTVNHcyvrFVYLT2yQkunoa6J4aY2BtHpC++rkNmLDFNIhmE/ETy6y6mh/9R4hDD8nqG9KpQEqJ3716L374zPfwct9LZvsWf7MFJu00CWt/vRY7rZ2FlY89hmWvNP2OEymx8qXlhqJlVnMz6V6aUM6lnESMG9qW/j3izCjwAZmqFqFo8RJevBWHRmiiGgwMiZC46JbH0N+06W+ffecumNxd/pp2lZhSd5x6PLzm/VDiHfFRzVp5RQrtGqIiFl9yDqKjr0SaHVPH+WmPSV+zia6jrjAelfEK0+8eb7rrZaA04rK6XI+5VoPTcLO2AyioWYnbzraOEh19JaRIC+3wUfZ8nhEAlufQe/6kbUMjeI4udHzNUOvYFJGmKa677jr8z//8D1auXFlIPPuLX/yi7TqDQbKR4393Pc88FHo3bIAgrtlUCAwmCRpR91g2ccyhJX/djMC+bNOA/YJo5+HZisLlvmzqTNo6iaXwHXskKV2+GJihoCwGp1ODg8ao1Alib4VO5FN9GC3jr4qeRX+nog8aPfMnYuVjefb2Nc/3YfYbpwFCFDKqyx1fP+S2SimxfMML+OayK/DMuj97y0yZPRVfO/FNeMeTP8VFCcNXXoU/CzZjmD13rjE8dH83eJ5xPXImTDognX5W34vBuNoY4YST7+aAcPMTlY2bb/76GTz6op2M8r37zsOhO2/tLV8lJe7bXkU9LYM76RxtyNsXGXpZdPSVSLP8UBsr1LjIDQptlOj+TUoEG6w6POev6sgN53aNQXn7IrCjrrCMc3f8uEY93abPTZ+La/C2G080nlAW89duHZsi/umf/gnXXXcdjjnmGOy+++7Dcp7BIAkICAgI8KJgkLzQP6LHW77hBXz54U+ht7nK+/tuk3bERcufxhtf+ykA4EN7NfDle0uCY6XEO/72b0eqqcOGh1/oxTd/9ay1bcGWk/CxhTuNUYsCAgICqnHzzTfjBz/4AY4++uhhqzMYJBs5qKt0MFHUiiT7d8qECUjSdKMKeB4uUCqKVtXSgaUmy7fjMXGzz9J6XPhWkXxl2/VudOoRoSgLrh9pL8lQMdIKXz41Lxet+r8d6U6KkaKStXvcMooWYHtGUqHuDzfvSN9rTfSva6LRaP98qvq1L9mAn77wY9zxwo8wKAYKv287+XU4adr++D8PXIE4zRMp7rhlhG8fNwEfvrUfUaZCxTPvx8cuvRTbLlhgPCFUXci3zaJ1OZeYekdipx73vqorXKH75LO3PmHJt8ac4Ut/tzsmdVWLJ3d6v9CVa995djK+R3oVWN6+CPExVyFyPLEbC/2HM2aSIwLKo+eqJzLk73JFxbI9f77r1ohj6xp2OiYizo3ksj4+Rbk6YP47TXoI5N6QsXnyDQ+Ch6QcXV1deP3rh+4Vp2jbIHnxxRfx8Y9/HHfccQf6+vqw00474dvf/jb23ntvU+bxxx/Hxz/+cdx9990QQmC33XbDD37wA2yb6cIvW7YMH/rQh/Dss8/itNNOw2c+8xmz74IFC/Dss8/ivvvuw/7772+2n3POOXjooYdw1113DeF0Nz0o/nH+IBFSYs70HgDAK2vWYkJXF5Es3ZgfDfVhco8gjy1Q2dnV70KIlgpNAq0Ng3b5+nXRSgZ4JDCWD8268TntgjGWZX8mx4K0XuA+42Q0+hvo3Ljp9FgarYyR3ICXmDSzC1EXQzqY/772hX7M2L7RdhvK4qSeXfsULv/j59A7WPSKbNk9E++a/z4cIKdj77vPsowRAEh5F/b74Hn4zkf2wZ0/+QkA4G/f9z4sfM97sP322wOARcMCgEYUGQPEzSlSVJ2iqlvcihmhkzBV1m57FVVLT/ie/msfnnrVToD4j4ftgN2JqpaLqvuhiprltrfwe0nsiK+egkrYKFBx3GNsbG8zmvsj4sroB/JrFXFuYmYoXHUrzoCYR+a3dnIilUHevghs4eWmHfr+L1vE4iSmyrSjA7rYeEcwSMpx/vnn42tf+xq+/vWvD9s5tmWQrFq1CgcddBDe+ta34o477sDMmTPx5JNPYvr06abMk08+iYMPPhgf/vCH8bnPfQ49PT14/PHHMWHCBFPmzDPPxKmnnop9990XZ5xxBt7+9rfjoIMOMr9PmDDBGDQBrZGQzMWcMazpU7SK/mYTk7q78JZlXxurpo0ZBJloab13/TJwX+hlq8iJSM0DV6NKVnMohoi7eu8LSm0n4H20jM+hPIhG63z0NRNSerXxy4wS2k5X8KCsbNU20wZZlGcdbg9TWTJIX+yBm6fFMoY5w9RtJmL10/mkuff5EoOkr9/qy+41z2HmYzegOXFLvLzbByCiYmo7KSX+65nveo2ReZO2x3nbn4VtXvkjXv/Q59BorrN+X9vzOjz6louxvmcHzGMMHzzzTKx76il8eNHZ6O7qthYllERvFvuRGSS+CRU1NtT2rB8IR57GlgwV6wfsrPMTGxz/cPB21rZWMUC+bT6ZY/rvcGJTm4QOJ2jfsKOvtOI7I5V70PLyWDlEnMusjRGeCS4MN7RnQxtFvlFue2lsUYgwDjZ9HH/88db3X/ziF7jjjjuw2267odGw3wk/+pGtwlgHbRkkX/rSlzB//nxce+21ZtuCBQusMp/85Cdx9NFH48tf/rLZtsMOO1hlVq9ejb322gt77rkn5s6di97eXuv3008/HYsXL8btt98+rPy0gICAgID20DN/gmWQrHm+D2jMgOyZBtabB2JHdyxBeuZHAQCTVz6MHX92GqJEeTQmrvoznjr0y/Dhlf4VhW2H85n42IsvYO4fT/DvM/tA/GH/S4F4gvf3jRXUcAoICBhbhDwkNnp6eqzv73nPe4a1/rYMkltvvRULFy7ECSecgLvvvhvbbLMNPvrRj+IjH/kIAEWFue2223DhhRdi4cKF+P3vf4/tt98eF110Ed797nebei655BIcccQR6Ovrw7HHHouFCxdax1mwYAHOOOMMXHTRRTjqqKOGdUVqU4P2AABqJS3mHGv61CRgcnc3Dvzz18eyeWMOTT9JpTSydJLEldhlc3UQ5VEBGLfLUK53u6tU7uq8D3XiHEYCo0FRGsvjAUTZJqM4SKN4Y5erk9Hdldukajl1xsVIxvT4vCNlHhPqHaEeBZrQc9o8e9K/fsUg1i4fQPz2wxGTVbDopz8FTjkZcXeK1995pjFGAGDGMz/Dit3/Hhu23KXYDqe/P7pqNf5x9XOl5/faVm/CH/a/FCLqNqu6zPFcCCEs9auYc3TFWVZ2Ej9CPSJuTIWOG6G/A0UKjTlmzSFdHadRvE5VkuBVMW6uIpKLTWietFFA3r7IJErUHm9NKwVav1u0gps3ZkmaHTtun5GvFqIQm+Nvz6Y/gBgbumzvptRN1BkxEmjLIHnqqaewePFinHfeefjEJz6BBx98EIsWLUJ3dzfe//73Y+XKlVi3bh2++MUv4l/+5V/wpS99CUuWLMHxxx+PX/7ylzj00EMBAEcffTReeeUVrFmzBltv7Zc1/NSnPoVrr70WN9xwA0499dS2TqopOZqyOiBwOJFkx0pG8ZgaIk2xev16AMCU7m4MJglkNvGOGRvVfhgptNO/fOFXkAwOIhGKCpGkAs00RSKEobalIvVOwDRSkIdtyWplGW+3KiDepcZQaOKGzyApk8FtF2nVb5kQgv63Dqom3mWTnTKpZR/cyTS9TkorP6c7uPlmyvqslRRzWZutuBNk159MhhljJvu4+Z6VZ4AxhlNCr5QlE9t2UUXJ8lO0bOhMzlJKJBtSrHp2PVY9uwFrnu9H0i8gUgkW23u9+MBrmPyu48Buu83azpb+L3pmLYdMBtHktiGzw88+ChF3FxowZevJWE2kyXdMosK+GmumvwG/3/8LkLwLTEpIIcCgjAymZVNTAclzidgYio6iZYqZEGCcm/11n3Bm3yMMLL8vSdB7mUFSBs5cWk5OdZEiQXeUd0g3l0iSpEi5Ivvr0r57KJdhtSeM9lhT/7rPA18WeVpHs9m0/tUQm8A7ZrTAs+erphBLSAiR36v6+SCFALKFNBMIL7LnCokZTZi6aoaOyCPITq/Hbeeqdhz+BSSpOoYZp1kROo5lFIH9/ONkS3vHbcqw0Lwx421vext+9KMfWSEbALBmzRq8+93v7igPCZNtzHK6urqwzz774N577zXbFi1ahN/+9re477778NJLL2GbbbbBSSedhBtvvNGUOe644zB58mTcdNNNLY+xYMECnHPOOTjnnHNwySWX4Nprr8WyZctw4YUXtgxqX7NmDXp6enDjjTdi0qRJdU8rICAgICAgICBglLBhwwacfPLJ6O3txbRp5SIOYwE9l/zg6Z9GV9fQaKGDg/247huXjsvzHAo451ixYgVmzpxpbV+5ciW22WabwsJFHbTlIZkzZw523XVXa9suu+yCH/7whwCArbbaCnEce8vcc889bTfuvPPOw9VXX42rr766rf0Oj36FaaOYDDCREe4Uh+Bw/ivErGoduhyvHfRZDDSb6BtUmvo7PPR/a+338C5nY+UaxeOe3TMNT618xfw2q2ca9nvymo7aM55Qp3/5wq8AyFeeNI0tEQKJSNFMhVml1ipbWuXER2vRK0NldMEy1ZwqlAUPF5V98s+uJ2ekkCYJHlu6FLvtsw+iuN5joWx1uBUVpJWXxOfV8K34D4eHBGhPplVfZ3eVnFJkzEq62UeNuT///vd4w957I4qiQh16P6tdUiJtCoABUZxTh6rU3aSU2PDXQbz69Dq89ozydCQDIyOOuu+jX8XEVS/m7Z07F31fuwJcDGDXH/8dGgOra9Vz4jaz8XycB0R+8ZVXsXdjLl6dezBWbf1mrJm+E1KWr77SrOE6GJ1zBiYkXvvLX7Dljjui0WhYq8ZxHCPO9mlEUUsZUw09VmkwMVVFAqoFENw6aXA8ADzyYi/+4bu/N79P6YrwP+f/TaFet6W+EeB6RWgddRxwZVQyXWez2cSdd96JI444ohDAKn76sdYHCDDgC79ixFboM22w2cSv77oLf3PYYUCmdqXhowzq7bEZi5mX5GcXdtw2ecSXTNvo+JEOzZlzhkak3hWdXP81UVHee/xhGDhbw6CCNp7w8MMPm8+PPfYYVqzIYwDTNMWSJUuwzTbbdFR3WwbJQQcdhGXLllnb/vSnP2G77ZQqSFdXF/bdd9/KMu1gypQp+PSnP42LL74Y73znO2vv12ACjQ4Ng6EgZmnHx5UAEimRZDd8q3oe3v0C5c4FsFVmdff2D2AwTbHFlCkAgCiK8dAuZ2PfJ67oqE3jDWX9S2V+RUbDEJnrW09eYkYMEqlykjAyMZZSeh3OZeo0dQ0SX3Z2XmFYuMeJMDoGiZlkxXFHBkmZEeLGawCw+p2iNKaHXNuIlJWQhWtYyDru9lmLPtTtbGVguvKpLpWHZ1m7dV0sG49RFJn+bcXBfvS2F/HMfX9F1+QYb3zPPMx6g391bWBdE68+uQ6vPLkOrz65Dv297srU8L8Q57z0G0xZ8ZS1rf9d74KMIqTRJKzZ9hDMXvaDlvUkAF5mCQYIGeSFHU8Ae90HgMz4UnE/Crrf48yo03EfEeOGyhLFMeJGw8SXNOIYjSgyMSR1pTyllJbSkGQs45RnW7O4lVYUriqDhEcxBtK8QEMwxKSdFNUUyWJZ3zPKfR758k1U1QsAjUajYJDg2CsABMWtuuCNBmJC2wLUu0H3f1ejAR7H5p2lfs9jHF1E1v3AwIcy/7nzArCjr8Sgpd4JK8WAjoHTY1V2cLwG21iyyARQvOlNbzLP0Le97W2F3ydOnIirrrqqo7rbMkjOPfdcHHjggbjssstw4okn4sEHH8Q111yDa67JV+E/9rGP4b3vfS8OOeQQvPWtb8WSJUvwk5/8pOP8Iaeddhouv/xy3HTTTdhvv/06qmNjwECSYDBJTOxDK0jkq8E6NqJ3wwZEUYTJ3co7xFkxAG5TAz9GDXxhJq3CWinX3wGywgRASoZ2lOzdOty4AolisLSGLx6k6jh14wl8Hp120UnsQp19ChMd0jdlUrsUdWV+aaIxbzscj0IrCeE6hkgZXFGEoaysrXt1AM/c91cAwOD6BL+9/hkAwBbb2lTUpD/F2pXDu9LIGwzT5k/AtLkxpqx9AdGTfwb/42Pgq14DAHT3r8Kk/letfdLtF2Dg0EMAKcHSJrZ4/m7r92bXNPzxwC/YXcIYHut7FmtX2FTeSfOOVncQMTDdfCBUljfKPBc0iJ0zEqSbBa/Xkb6tuj+VOAYgsomUNnhA8pzUuX87GRvl3ki/MUSNYaueivFd91lQtZDAj7kqGCVtgDFmXkOcSWs7Zww8ivLnlShO4LVhYO4TAJKR92KH10LevgjRUVfYCTujKDeesgeuvH1RR/VvLAh5SIp4+umnIaXEDjvsgAcffNCKA+/q6sLMmTONgdwu2jJI9t13X9xyyy246KKLcMkll2D77bfHFVdcgVNOOcWUec973oN///d/xxe+8AUsWrQIO++8M374wx/i4IMP7qiBjUYDl156KU4++eSO9g8ICAjY2LDhtUHv9lXPbfBub4VJW3Vh6uwJXmeJnlB298TYInoV0576LeIH/hfsiSeMZ6cKzYMORP8//iPQaABSYtvfX4XuDS9bZf54yL9i9ZZ7FLxK9z3ziFVu3qQFmNHtFzoJCAgIGE0E2d8iNNtJeAzkoaLtTO3HHnssjj322MoyH/rQh/ChD32oowY988wzhW0nnXQSTjrppI7q21gwkCQYSJqIWLXyxMO7XwAAJkZCSonnX1Mrl1tPnYoVq1dbK4F7P375CLZ67KBXgFxqjpCwYkiELF9tp6vrdRIPtlz59Hhc2vGOtFPOl9yxHS/JSK7aDEfmYKA80V+tNpDr6XL87eRjdT0x7Z+T8Kx81kVjwtAUaLqmxNhyh8nYYodJ2GLBJHRNzbjexHto8MKL4L/4H7Bbfgn24oue2vxovulN6D/1fUh32knVLQTmP/JNzHniBqtc71ZvRO9WewLOsfuTPjz02v1W2d179jHtpKBxG1q2F4BJVMhZrj7EmJ11XUv8Djeo5LpqDM+9Y6TNrje103uv4On1eEdcelgd1PG+1N1/LOS8N0aI284GP+YqZLkRFRzHGfXoA4oy6PZvIVEvY+YdCAyNrBlxDkkYG6kQBc92M8vu3vjpuUM4UsDGimXLluGqq67C448/DsYY3vCGN+Css87CG97who7qa9sgCRgZDDabiHnU8sVJJ72GsjWopAQZY2jE8SatL+8aIkBmgGTfdTCe7idqsPiC1ztuR0Ufuw/t4XhJD2VyTjEW7uM6xh7FcGVlr9MWd9JV17Brtx/bHQM920zCtDkTsGZ5f63yURfHjAWTMGOHyZixw2RM3KoLjDEIIZScKFnAAADx6quI7v4V+C9/Cf6nP9VuVzpvHgYPOxTNQw9FMmtWlgNBAFJg3qPXYttHbBENySI89caP5vsLJcebiCa+9ef/i1WDf7XK79azjzKaaMwRMS50bAQVnTDxPGRS7ruGrWSqKYe/k/HKpLTlfWscty4s2WYpvQH1mudfF8ORWyLQs0YG7Q4Z+m6LCFV7KG8eefsi8Hd8zdRP6c+uIZQedTmiJZueURIoW+X4r//6L5x00knYZ599cMABBwAA7r//fuyxxx648cYbccIJ/qS2VQgGyTiB5ka3ytLrKkMtX73a/PbiK3/FtrO29urJbwqgSloaOiiwLKdIHdAkVW797WA8GyLA8I2HMnWwVuWHgpaxH55rV3Y9q67zSBgjFNowZtn5lB2PRwwH/sPr8OvFf8H6V+0Ykd2PIwomTGLyVt2YPm8SwPNg/1TIojEuBHDPPeC33Y74D38Aq+Fyl3GM9A07Y3DPN6K57z5Id9gBMmuy9rZ0r38ZOz/wOWyxcmlh/8f2/SRem7EHkKb5AopI8N2nrsQTax62ym4zcQFmT5yXiU7kEx9GDIyI294PbYywrBzgD9SuI8Bg55qpNl5M/5CkdEXPiCQGst5XlW/V87XitGqcUzt11jVGvF62gBFBneeZW15KaWJRh5ohht3xT6qeY67KYlXt9lBmwqaYjSYYJOW48MILTfgGxWc/+1l8/OMfDwZJQEBAwKaCuDvCLkfNxu+uf9Zs4zHDNntNNzLAtQxWKcF+9ztE37kW7C9/aXlcMWcO0gMPQLLnG5HuvhvS7m6bmkQmJVs99z/Y6bdfQKO5tlDPsjdfgBXbHWXXLQW+/+w1eHj1g9b2SdEUnLTgH7NJTssmBgQEBASMIVasWIH3v//9he3ve9/78JWvfKWjOoNBMk4QR5FZ/QOAp/b5VLbSkeXTSFMkIoVM7bW1Nes2mJXBXbadj77BAUujf1MAX/gV4PbbARAXscmwrFaD9XfFcy1yXdtBOxSjkfCK1IFv5cyHkVydKVMUoopjPrS6Ntob4q4Iul4Sn4ypWwfQ2lPi+60Mw+llYqza68MZwxbbTlZEcC20k0j0vthnqW3ZuVls70j66B/Bv/Nt8D887FZvt2f6dCSHHor0bW9F+v/Ze+8wS47qfPit6r73zuzs7uzO5qRdZZRRTigjrRIyIBBItshgbIMsEz9jCwQ2AoNtAeIHNuEhJ5MRQhGQBCihHJBWm3OcnRzu7a6q74/qqq6qrr5hZnZXGvXLI2Zvd3VVdXV1dZ1z3nPOwQdDANY7ZUbbQVzDnI2/w8KV/4fO7qezdYFg1THvwaYDX5u8j/LazcPr8JstP8DzA/Y1FdqGdxz4IcxrW6wtwOYapvxGAPnMgyRqloKicZkroxladyzvZFMWhxxLtGkp4UKGDs6bN/kyZPb9dq1Cbj8b0bXy3tfJ8p2YjDC/RTShJZoWKt/c5iI1wZUmKOoZv+W9CC+5Se9HZH9SSyIlkzPCWmEhycfZZ5+NP/zhDzjooIOs43/84x9xxhlnjKnOQiB5gSCgBJRQmBx402lSOmrbVIaB0VFwznHAwnkAgBKliGiAk1Z8ft/cxF6CGbtdCSMmR95MJjhWNBJKfJtqX/k97WugrjE3t5T4N0p7Amnb6TFKsvk8XMGhlfvMfJQhv7f1xls5r3NnY5fX7ngdc32bPdPRVNXIhQBJ+tYoRCwXAqX2ANPmtmFge+pL0rd5GDP3m5LNuYJ07rPBQdAbb0R49z35fW5vR3TqqYjOPgvxMccAKlRj4ofFhFp75AYoHN6BRat/gYVrfoHK6G5vnSPtc/HUif+K3jnHQXAGxgV2jm7Dndt+gid6H8iUD0kJb9r/fVjYvr/2Lwko0cE9FJVVbbz9+V+Sf3uSVqpxYZynuUtaSGJqwnedKfj4nn+ewN4Mud8niOSWbdJ3pJWw4vXqUOttOAk3oXsTKidWK6CEWMJ3vWcaM4aJCufAb3kvggulEzvjUukUqHdvkm66Dde0cdUxGXHZZZfhwx/+MB555BGccsopAKQPyY9//GN8/OMfx69+9SurbDMoBJICBQoUeAFjysyyJZDEtQYbGCFAP/0foPff7z3NFi9G9Q1vQHTqKUBbW/26OMOM7Y9iwaqfY/am34OK/DDAWxefh78c+37E5WkgAHpr3bhz6y/w5+57wOFJaIoAf7PsGhw49bD6fShQoECBAi8o/P3fy2AlX/rSl/ClL33Jew6QwiprInw8UAgkLxgc9MgN1u/Vx/+L7ZiKrCNh37DMSTC9rR1AmgBsskI5rCtaCpCG+NUUFWeMmkmCR4kAR2uRoHx9y0Mz9A+ulel2P1qNULUv4PbXDHNaL0lkK/CNg5tUzHyGqrzPSpLX90bttwJTa1nvnpui3jlhg4XI0rRUO5xz8P/7MQKPMMLnzMHolW/E6DnnQKjgGYnzq9VHIdCx+znMXX875m64E5WRnfVuFaPtc7DiiHdj65LzwQFsHlyLe3f+Bk/2PACe4749NezEaxe/DYdMO8a6f9dpXdG19LtqRtWCYUVA9pi+b4/FtOHz9DyzPLpTXl2m9cTsi2lBrGex81G07LbN7toWyWYxXrrWRGrgX2qIGct8r8yf6vkqWpQvOiBzrCOZ92KC1fMhlVZGLliS5DZNCjopIUP2jb+OSYgXRB6SAnsHSgAxo1iYUVsIIRgallrTae1SIKnGccMoXS820EtuQlyTSeIk3YXX9RnxhfbNo/bYC3x24Z/oxbzeZsHMVeEKR+bmGoD2r3ghCiouhUt/VIVdxod6dCt1Ps+fRLVlPkN33GQ//BvTekJgq/OgmdDBvjKtPk/TZwRIqIxPPYXga1+zy3V0YPiNb0D1oosgyiWp6GAqT0+6xrQPbsL8DXdg3oY70DGwoWH73bOOwboDXovtC14BTgI81/sY/rDzVqwZ+kvuNW10Cs6cczFOnX0ByrRinaNECiOuwGGF+SXE2axDXyM8GzMFxjlCJcQZ1+Sh3qc2Lzt6vWNWZEAxtvDCaftGW8aakudP1SoyAl2SMyNX4Lvwc6C3XTshbb9UQC7+AuI4DdefW86gRQmCzHfOjRAJJLl5DIrjRH4lVGZ2mlC3zP3IZKTuFT4kzWF0dBRtjaztTaAQSF6gcC0mCs8c/SEA0gmec46ZndM0NzpmDMc8/V97rY97G8o/hHGehCCUGqJ6oX7rOf8pKOdon0bKXUys0KBjWOkbbVbGUtd4r8/rl4u6Y+j4YJjWgbEqiBrlFLHaFcg8Q1Mocetsut4Jhhn2t/lrMkcsYUQJ53F3N0r//kkrnK8gBL0f/ABqx0hLBIti632h8TDmb7gTi9f9GjN6nm3YlzioYNPiV2Ltslejf/qBiHmEJ3b/EX/adRt2VPOTKoakhFNnnY8zZl+MKeFUfdwWPpD8zfplNPIbMaGu9wkl8nwA4mShc8sGTrvNvGPZtSKdv+Y6pPxigBxflaTv7hi475Hv3t36vGXqKFx8woj6y0UA4BxrbNU8FEm+ChUmtoAf5OIvAABizvQ89vsjJuWNeSDfWTtgi+norn8jrZMLMUFpam1QQu0If5NQGClQH4wx3HDDDfif//kfbN++Hc8//zwOOOAAXHfddVi2bBne/va3t1xnIZAUKFCgwIsdnKP0mc+CdtuJBoevuALRy1+ekWraBzdjyZqfYdG6W1CKBhtW3zf9QGxccgE2LrkIUXkaRuIhPLjz17i/+04Mxn2515VIGcfPPBNnzrkE00szx3RrkxGrV63C97/zHTz13Gr07C5h6lHno9S1qPGFBQoU2HuYAAvJZPVq/+QnP4lvfetb+MxnPoN3vvOd+vhRRx2FG2+8sRBIXgpoL5cBAOUwhBACxy9bhvn3fXQf92rPgF5ykxXRhQsBkfiMMEPj2ChRVzMUITOErE9r5dPy52m3moUV3laZ4j0a00ba2fyQovma+FaON6Md3lM0NyA/hG+9MMCKvuWOgWstaRQauFk0GjcfBahZalemXqQRtZS1MPj+DxA8YicmrB51FHpf+xrwKNIZ1Wdtewj7rf4p5mx/EI3IHEPt87F50XnYsOhc9E9bqo+v6nsSv9jydQzEvbnXdgTTcXLXK3Fi19naIsIEt6hSbvQok67Viq+PukaVIMRD63LmgHCGPdOXJt+DLG2QZM4LZ336/ne+g/dfcw0ECCDkjO1/8KeYddE/ouuUi3LvM9OfBs8vjyI67ihbd3wI9BJJ2VHrsAoHSydpxu49gdLt/5RYltT3LVtGCKHXDvWdUv5yZplGNMKJhrLMKArXZEVB2crHt7/9bXzlK1/Beeedh3e/+936+NFHH43nnntuTHUWAsmLDH0jIwCAWhSBEIKOSqXBFS8c0Etu8h53zb2qnOnEDsjNl9xEpk7secJIM5sHBc3DNULUUoIxazZcfq/6eCgusPnxaJSB3Idmr6m3EOaGJG1Qb167Zs6HRgvwRPi/NOv836hcK6GBfXWPFa3QtjjzzeXk/eAc/PEnUP7Od6zz8YwZ2PHe9yASAlN7V2P+xruweNNd6BjeWret0fIMbFpwFtYvPBe7ZxwmNx1CgMcMMY/w+10/w0M9d+VeP7u8ACd3XYCjp5+CkJaS8ZTn3NtNhY/0mM8R3L5vGTbZR7fKo1e6G3O5rhArFLDZH3Vthm7oozi5ko3TTtqe/Pea1avx/muu8TqEdt/6eZx71ivAOJeULmudyG2mJbi+Br4+N0XfVL4EkD4kSqPCBcCX34iQ0oK+5YFFZb3o85m1xkcxzgRkSIQSVY9v3rca3KBVTHZBpEBjbN68OZODBJDO7lEUjanOQiB5EWHTKdejtlvG/1+zbTuCgGLa7z+8j3tVH6YQkmupSHi1CmZOESYEYmZbSJSDv1lnqxvpVjfEeXxt12ehHnT+AQ/X3I220gh+p+6J/whZWn7PWKcfWJvD7KIZ35tGWnCfMOQ6+puWJrWpbNX6MdEaLVNDrqwbaj7VGzclbA/uqFrHS1Ol/xgXAozFKH/xixm/ke53XIVFW2/Good/ixn9q+v3DwRb5pyIVUsuwdZZJ4AnkXNE4nQLADtGNuLmHd/AzmiLt4792g/FyTNeiQM7jgQhMiqWSgroznd3U2zmD2k09ulYeuo0BBNi1KuEnHrWD9W2OU99zuPutaaVyRVmmeyw7vftz+zEFz9zE/JZ/QS3//yHOHp3G97xiqV43wWHAEj9WVqBu141EkRMtGrtpLddC5L4kKgAIzHnEBf8t66nEFAkzO9VzLllZTeFQepEm3Oh52OOlcy0+I1P9fPSRmEhyccRRxyBP/zhD1i6dKl1/Mc//jGOPfbYMdVZCCQFChQo8AJFNMww2mdrm6bNT62i9L77EWzcaJ2felI7Dt/0rw3rroVTsWbRBVi55FIMdixMT1jaWY4/9/4O93T/Agxxpo5l7Yfh7K6/wvz2ZQAm78d3vPjVE9vx6dtWY+eqtRB1EuHFfTsAAF/743rMmlrBm09bmlu2QIECexaEEpBxmifHe/0LFR/72Mdw9dVXY/PmzeCc42c/+xlWrFiBb3/72/j1r389pjoLgeRFhFIQoJZEl4pjhjAMGlyxb+FaRxqF4jXzKZjXqOtUJuc8M7cPjdp0206vy8b5b9UM7rbHkxCOPq24GS0KTeq0JtIiMlYKVasRoxTGQtuqR6/K8yfx+fm4FpOx0OYaoRn/kEbXA7ASIgIACQgqXSUZ4pdzhD/4gXW+MiPCkmWr6tbdM3UZVix+FdbNPxsxTUI1RnbiKiEEBuIe3LLr29gwuiJTR4AQZ3e9BsdNOwuEUAgmIA1UyTgm4cc5AHOVoiSNMOXStVS75kFFeVR6XpqMjQp1HOZ87G1Lh+1ToiwheZG7TJjvvDeKlmsxoWn0ISLk/GOE4PFNA7K/nXMhrTv++SbPS3zngQ1406n7ecvlodEa1eqcpE1mYlfWjwCSisQFh8k0DCitG0r5pQB6yU06OiSgGAA25VA9Hkpo7roaUKqfCU3YBXmWVtO3qkCBicSrXvUq/OhHP8INN9wAQgg++tGP4rjjjsPNN9+M888/f0x1FgLJiwhhEGBrb6/+TfeQQEIu/kJKxRljOD/TDwQwnDuN5THXic8wazPOEfM0xG8gGjuxN0PP8jmEuv1hXCAwdinmNe6H33SizoN2pk2KcPg3CJQAHreBljDeML7NnDfLtSKUjJVKJa9N2+FGuy7NZCzCjlnvvoLbdv/WEet3x5wyqIgwdf19aPvtD9G7ao11ftZhA17Xp+FyF9bPOxNr5p6F7qkHpnIvYxCeF3HlyOO4fff3URUjmXNzwkW4qOtNmFNeCCRzXs2BVLAWGX+QgMgkhwp5m2NN9YLxPFOXdausytfkChdufS7tSTnQK+EoT4lpJhz0UZnqhc4NCAEVBAQc5xw6G7c9vQNTjzof/Q/+1N8YBKYefYH+9b7zD27pvRqr38B4Azpk6rv1HxEACJPNco2xIiwsYAVj8cHNo+Rb00xhBJC+HPSSm/T8dt+FYtzHB0Ka+5Y2qmOyYvny5Vi+fPmE1VcIJC8ilIMALNGwEEKwYMYMYPfEtkEvuQn9IyMoh3JqlCeoXiWMuImdgKwVwxRi3KSHvqg13khETQoh8nr/Ncr5VcGXGdmtwz6mK06uJ2BcK48BkZ+AjTgfmFY2C83kF1B1+9Cyf02dFdeXO6FZy8W+Qp4/x0SAABY3PE8QUu9L/zbbQjIHz+CwH16JsNqH9b+bBSClb5Wmxpi+JC1fCzuwfvZpWDP3TGyfcSQECSCSpIjWGFvvEsefBm7Bw0O/9fb++I5zcNq0ixHSknw/Ev8u6iRkJclmP0gyq6tjrp+IaRBRgoMZWUjVqjZqBCI3M3jGv8MYYzuQRNIXmtVC5/k3KSdiUzDhSf/qzX81DhcfOR9Pbx7Adx4AZl30j+i+9fOwhSuBWRf9I0ozF6ItpPj31xyOS49ekFtvpp0JiKiVF9mMXPyFMTkxq2tKLV85+UAvuQnVOG7OzzD561rl856lSlxplikEkYmBxwg6pjoKNIdCIClQoECBFxBodQCVbY+isvMpjK48CsBsfW7J0O8Qog/Du0oY3mFH2Jt12CB4WMKWOSdjzdyzsHnWiYgRNC3gjfBB/Kbn29hQez5zbhqdgQs6/xpLKgcXH9gxgBCCDy0/GDOmlPDLrleh55BjUH3mLsxGH045+mW4+i1vxoEHHqjLBzRP7CpQoECBfYOZM2c2reTYvbt1bXkhkLyIUArTx8UZx8uX7gesqXPBGMA4x+Do6Lhzm5haG31MZClcQNZakkYkEplriLAzszez2WpEz8rzSVE+K4DcUDSbdTzPb0VpVJXVhRIBiMYa1rFYSczrG9Vtopk28qIUNWqvWYyHdrWn6FatUrpc/6B6Y6Z/j+zGzMe+gs6nvwfKZGStkdFvW2U6ArnId/9lmn1tR4D1r3kP1s47DcMoI67F0gLHmBxHa04iQ9PaHm3ELX3fwADvyfTzkMqxOGfq69AWTJEWFgA0UAHj/FQR0/qQNzfccSQkaxHkqB9lyrQ26faQ9f2wfEiQWm/SvqixcftE9Pmx+qaa/Xv3WQfg784+MGnnygytzfQFsKg3LbbfzHzLK2dC5+lpvukCHjDOW17PzOhzQPINyrF8FBaRPYUJMJG0+Pbce++9+OxnP4tHHnkEW7duxc9//nO8+tWv1uff8pa34Fvf+pZ1zcknn4wHHnhA/65Wq/jABz6AH/zgBxgZGcF5552HL33pS1i8eLEu09PTg2uuuQa/+tWvAACXXXYZbrrpJsyYMSO3b5/73Of0v7u7u/Hv//7vWL58OU499VQAwP3334/bb78d1113XUv3rFAIJC8ilAKKWdPkRmTrSDdKwcQ9vqeP+iAAINy6FaVg4nxTuCFcuIKEz9Hd9THxXcM4b5gULNsP+7eX0uUIS2aegnSDpD4S2TZcKpl7fxRyg0WMugLi2QR54sy7Gz5f//MoK3n99cWwrwczxK7veDNwAxfUQ6P7deHzLarXzliFvEZoVTgjtUF0PvENzHj866DRkHWuM9yKHVEqfGysHoOFo49gcEubVW7na6/Czv0uwGgUgddiTaUSnFsCSIbuyDmerf4Z9wz9LBNFiyLAmR2vxpFtp1q+H76oMemmW/42qVp6vnAOYfht6D4kfwOShgr25VYw61W+XaoN6nmWGYHPqEP1oZEvmuvLYv672Xlfj0KZ7WOLc2ccTuwZAdGjRCowMZD+HyRX8FVIw/kSLawWNKx9h30R9ndoaAjHHHMM3vrWt+Lyyy/3lrnwwgvxjW98Q/8ul21y/bXXXoubb74ZP/zhDzFr1iy8//3vx6WXXopHHnkEQbKnueqqq7Bp0ybcdtttAIB3vetduPrqq3HzzTfn9u3Nb36z/vfll1+OT3ziE3jPe96jj11zzTX44he/iLvuugv/9E//1NJ9A4VAUqBAgQL7BHS0D9Oe+ylmPPo/CEazlgkAOKDyIHZEh+jfq6NXYF7PkwA26GNs6lQMvPK8ltsf4YP43eBPsKb2VObcFDIdF09/ExaU9m+53gIFChQoMDZcdNFFuOiii+qWqVQqmD9/vvdcX18fvv71r+M73/kOXvnKVwIAvvvd72LJkiW46667sHz5cjz77LO47bbb8MADD+Dkk08GAHz1q1/FqaeeihUrVuDQQw9t2M/bb78d//Ef/5E5vnz5cvx//9//1/B6HwqB5EWEjd27ddJAQggiFqN9guo2Q+vSCeAv00tuchzU5XGTpuVqtE2nd18ZzjlAZBLBPGqFTlRYR/GdR1PiTt/cdmwqSb6lJA9K42pGT/E5LpptmhGp3L6Y/c936DWOGe00ciyvh1aoH3mR1MaLRpQ9nwXNZxGZKEf6RpporWmPRzF13b2YturX6NhwLwj3Z7QVJMTwnCPRuXQu8GB6fCSehu6ds9BlCCQ9F1yAWhgiimPwmMmkiSqZKOOo8VFEqp3kPrdG63H38E8wLAYybS8IlmH5tKsxNeisG0GNEDtGv1mOcQ4k1gzTKqasIAqNrAw6ZK+Z5JBSr7OvHmPYms006SG1yjcKjNEsfNG33L6595SHeu+fepeaXXOateCYmveMFj5JeFhgfKC3XQt6yU36+x17KFxcGFHdEksiv+W9RdjefYiJzEPS399vHa9UKqhUKr5LGuLuu+/G3LlzMWPGDJx11ln45Cc/iblzZcjwRx55BFEU4YIL0oh9CxcuxJFHHon77rsPy5cvx/3334/Ozk4tjADAKaecgs7OTtx3331NCSSzZs3Cz3/+c3zwgx+0jv/iF7/ArFmzxnRfhUDyAsPguZ8BAIzUaog501nKGefoGxnWccxL5RB9wyMYOu3jWHDfx8bc3vqTPorRKEKYLJRhEOCQR28Yc31muF8zzKGmWhmCj4++4/Mn4U7mdpd24hMUXNSjaKm2XKhs2PrePPXmtdcMhBCa45IRKIx6KRENqUe+33nCiPlbRw/yUFLGs0mvR13zoenNU55/Tk79rtA1ETStZvpqPRMWoWPjfQDasewH56NSzXf2EyDoP+hSbDv27zA8dRGqUYzKyi2o7k7pVIO8C13GNT3HHotqHCOKYzDGwaIYA7VePF99DCtGH8UOtjHbUA6OLJ2G09svQYBS7kabEOh5671fGNQwizZozyuSCCcllZcEKUXF9LugxKZmmb8VrYVSCmHkeHB9eMxrxuMw7vp8vNBg+534Bb+WIm8V2dUnDPyW9+pVmF54Y93Q7rSOv0iBvYeJpGwtWbLEOv6xj30M119/fcv1XXTRRXj961+PpUuXYu3atbjuuutw7rnn4pFHHkGlUsG2bdtQLpcxc+ZM67p58+Zh27ZtAIBt27ZpAcbE3LlzdZlG+PjHP463v/3tuPvuu7UPyQMPPIDbbrsNX/va11q+L6AQSF6w4EJqzqux1GzuHhxCNY7RnnAF28tlrNy2DTM6OtAoOKQScmS9HLWYYTSS9cZRBEIIyklOk5BOjP8IT/xBLAEkEUqArMO6eZ2CcIQPAds514emnNxz2nSPhwG1N71oTruptjv1Ys7XQ8b6kfiUmDHqG12nhJF6YSNV3Wb58fTVrNe1NlnP0NMvMy2fL7mXrw2g+cSXvvp8FqeJsN6ousLR3Zj16JcxfdWvIWqjeOyYr4BGw7nXDSw9D9uOfw+qXYcgYjFqMUONMYSdFKYMw6kR3CIMMTB7NlCLUI2reK7/ETw19AA2RauAFnSrbZiCs9oux/6lI/JDyNLsc8n7WKvnToSdA8RnodJW3yBxRydO8kQQbbU1rSVmH2QOB/cYsa5pdWNh8vcpSedsng9VPWuSibEmzWz1HW0myEOx6d03kN9ZZilLzDwkBSYfNm7ciOnTp+vfY7WOvOENb9D/PvLII3HCCSdg6dKluOWWW/Da17429zp3fcr7rja7Tr7lLW/BYYcdhi984Qv42c9+BiEEDj/8cPzpT3+yLC+toBBIChQoUGAiIQQ6V/wU8x78TwTVPgBARNu8RTktYWjp2eg+5u0YmXuM3pw3i9FFi9CPfjy++w94vP9PGOZZClYjLAkOwVmVyzE16Gz52gIFChSYrJhIC8n06dMtgWSisGDBAixduhQrV64EAMyfPx+1Wg09PT2WlWTHjh047bTTdJnt27dn6tq5cyfmzZvXdNsnn3wyvve9743zDlIUAskLCIPnfgZcyA1JLY6xa3AQIzUZ/nO4WgMAzE0m9MyODvSPjODZLVtAjng/AODYZ/6rbv1ccESMI2IxqspCklguVGIzQgii5TeidHvzERLMyCyp5pqD8dQioiwkSkPOuJ/G41J98jAWjXY9io8vQg8lgTdKlvq3LxIQMyJXmb4DZr/dMKVuuyb09lSk9CpfRnilJda/XYpWDr+9mTFuBmY9jPP0uSeUO58Vyo00lAnfalh56mnird8eq0AzfkXjgdm3cu8azP/Dx9Cx9eHc8oJQDC08Bf0HXYL+peeBV6bLJKBxDKbff4ZqHKMWRXW13H+ZPYgvb7gOIjfFZj46MB0vL52Fw4KTQZFaA3PHOhlAEmQtHulcSp4hTAunPMaSPgaE2tfrdxngnsSHZmLD7Bzxv0OudSPwJEF0r2nk29LM++CLhjfeDU2zsC2k/vHZW30pUB/iN9eAXvR5ANy7LhXP6YWBfRFlq1V0d3dj48aNWLBAcmWOP/54lEol3HnnnbjiiisAAFu3bsXTTz+Nz3xGsmVOPfVU9PX14aGHHsJJJ50EAHjwwQfR19enhZZ9gUIgeQFg+LzPyn8IgW190vFpcHQUo1FNbyxnTZuGchCgc8oUAEBIKWZNnYoD583TG65Vx38Ei2Z2WS9AzJjxUaIYro5gJIowMDKiyxBCML1danApIQib4Fj7hRDbid3NNeI6rZvXqn/X23xJ6gaxqF5jedkbOUSbmx0Wx/qYyiTtg948G5v8gNJs6F93g9Bk2E4OaAYOJXIT55r7m62zWbQi7JlBEbjg2vcpZgwsEU7dOl0/AdtvJv0QqM2kK3SNFXlBDVpBxq8irmLW41/B7Me/muuoDgDbTvoAhg54JaL22enciGMICMQsFeRqjKEWRajGMVg1X9h4YlZPbu7yEirYPzgCB9Cj0EXmAc68aEeHJdhb88YQLtx3TckQ5jVq4y2cd0vRtuRBJKFP5W+fUC+Q+owB0qfNfn/suSHpXX4BX5dp8n3wbd591Mc9iXoCTKtO7Y1Q0LVeWNhTCpMCLy4MDg5i1apV+vfatWvx+OOPo6urC11dXbj++utx+eWXY8GCBVi3bh0+8pGPYPbs2XjNa14DAOjs7MTb3/52vP/978esWbPQ1dWFD3zgAzjqqKN01K3DDjsMF154Id75znfif//3fwHIsL+XXnppUw7tewqFQLKPMPLK/8xo7KtxjO4BSblQm/cZiaBQLpUwvS2lfYRBgN7hIYzUqnoh6x4YRGf7FExNyunNobGfGapWMVSt6t+UUrSXSnYUG0Lqss/JxV/I+AmYlg91P5Zm3JPkUGlQffUA+ZsAk2vb7GZyIjah5nV5CdvcvhFCdDn1O2MBaEKoooRoTbIaO6WobiYny1gsSa0knzQtIlEcI+bSKyRmHDFjiDnD6M4I/eurGN1ZA+3tA929G6Q6giAeBeU1yz+IQGAK243OeBNmsC0oixGnRWL8f3oo7GoD3X8B+DEno3bAyYinLaob6KDZ6Eq5nH/OMHXDPZj74H+i0rfWW6T3gIuw5dh/ANbsxo5DXgsaBGBxbPtUCYGIc70Zr8aR9PUailDbzqz6pozs0P9eNy/br4XBATgsOAlLg8NARSBzkfD0noFEcAYAKuToZPw8iLEDtq8FTwQSpFaTjEzEBQSFdY8yVwgBjBw7MlFo0idD4G9kuctYTJCuWa7w6lpHlA+Ha8lw29hX2JtWlQL7BmbELR/47R9EUEyBfY59YSF5+OGHcc455+jf73vf+wDIHCBf/vKX8dRTT+Hb3/42ent7sWDBApxzzjn40Y9+hGnT0nxVN954I8IwxBVXXKETI37zm9/UOUgA4Hvf+x6uueYaHY3rsssuwxe/+MXx3Oq4UQgkBQoUmHAIITDaE6NnzRB6149gYMMo2Ki56asAWCAlilLj+tpHdmJa/3pMH1iHGX2rMW1gQ77O+u7NAB5Gaern0T4HCJfNBw4/HNFxZ2Jkv9MggrE5E5oIRnsw47mfYMazP0J5YLO3TG3qImx9xUcxsPgViaUtP7pWHqobY5hsLMIjdO3+CwCAEWBdEiilhDIOrRyPI0qnYCaZl4b9Fa1TuQoUKFCgAECo/G+8dbSCs88+u65C5vbbb29YR1tbG2666SbcdFN+otOuri5897vfba1zexiFQLKXwC68USscGecYGh3V5yIWg3GB/pERVEpyd0YIQRTHKW1Fa/1SzeDUShtG2yLUVChgSrGhu1v7mUxta0MtjvWmRPltmFJ/QAjKYajrDSnF7qEhVBIaGU1yCVj0BSNSFmBnVDcpG25o34w1xLkmm/cjS0+QmtCxWTeapWoBrWUfd6F9FnIoL63A62ciT6Taff1HWH/r1uuMYx5dwLUi5PlsxIyjOhCje80gutcMoW/9CKIBW7M/Hoy0z8FI+xzsmHcCAGBG7/M49PkfomM465inEA2GiAYBrN0F/P5e0PButM0X4MefjOHlbwI/8BCA0qa04ypi2pSdT2HWsz/E9DW3grKat11BAuw68k3YfuzfQZSmgDGGKHlHq1EMytOQ2NzwsWKcI05+R3GMGmPoXd0PgjQLb9fu5xAyaeF8ZilBe9tcnFQ+DYeWj0MoKvK9ixkEV3lIZBt5YbIpKEAFIIQWYrQ/mZpXHAB16ZVyBqn+U1CZU4catC44fluQVpCUepj0x6pX+pGYtNEwCBAGaWhgn9bSXBv1GmlYfRu9e35/LruOiYSmre0hS0i9SF4FVeuFAbm2TkxkvwIFJgMKgWQvYPDczwC1SAsG1SjGqOGsGrEYMeMYqdWsDy8thWhLBJRyGCKgNBNDv71cBqtK4SYslxFQio27uwEA8ztnoBQEOnSw2Yb60IZBgHKYTgPZhk1lYIofrj9w9gJaj35lJkTkxgZMXwOhaV6qnMlr58bGOQkk3PzA10E9v45mY/ZbHxKLOqI2G2lSQ7v+bD312vFtvoRIPQe405dmuMjUoM24fakXsjeTuJJzbHuqDxvu78HwDv8GfU+gd8YheOiEj2DphjuwdMPtCHjc8BoeUwxvArDpYdBfPgw6tQ3xRZeAXfEGYLo0dxMQwNnMkXgUM9behlnP/hBTdj1Tt43h2Udi8yuux9DMQ+Q8SHIJRYkvUi2OQYSQvjUGpZFxRW2T70d/tR8P7rgTL9tylmVAmrPrCf3vXYcfg9dV3ij7HAEMTL5TBkWLJzQwYTw4QtMNOudcCiWQiQyBhIZFAcUokYftAAiccdCAaqKUSecCAEEFCAeEox1knFt+UY0TI7q/s++Syl/CnffWDB3cDHzKj2YCT5httoqxhADmYux+JIUw8sKDRScs0iC+sGBQpcdVxyTE0NAQPv3pT+O3v/0tduzYYfn+AcCaNWtarrMQSPYQ+s/5tM7pUQ4C9A0Pa87ocK2GWpxuoGqxFFDcGPsdlYplMTEdOLkA2splMCG0QEEIwYbuXSgF8nfP0BDaSiXdrq+NShiiFASpxjTJgmw6ngKJgJHzYpkbVzfZoemPYPqUcMPR2URzcfz9ffDV43e4H1u7jfpESdY6YW4c6m0kTCuRZanJ6Z8vQpY75ua/3evdSF2moEjNZya4Va+OliYEup8fxLp7dmN4Z/OCSNvITszsfR6laAhhG0fYzgBKEIUdYEFqCeCkjAEyDwNkHjjxc7oEDbFu2cXYsfRkHMHuRFdtLfjWfrAt/UAzxpnBUYQ//inCm29G7fVXIHr1q0E6OgDI51Ae2IQ5K36M2St/jjAJ35uH4VmHYedhV2L3gZeCkwA8ETgAIOYMURLVbjSOQBIhRVpEZEcZl0JKtTaCR/p/jwd678D8XQfiKG7QywTH7O4n9c/gZRchYukWRnAzslXyDBkHHMsjRKpcoAG1hZLk/6XlJCkuSOrwYY6/OaE5z/ihCEFAEl8SBZ8V0vfupfPRzoukLCH14ukrv61G73SrvhpjFUTG4hOyp64hF38hFUYT4cQMUOKiEGD2DPgt7wW56POgsINJTJxNucBE4MUQZWtf4R3veAfuueceXH311ViwYMGE3GchkBQoUKBpCCHQs3YY6+7ehYEt1Ybly7V+zOxZgZk9K9DV/yxmz9iGqYtGQZdNw44DTsGWOSdjZ9fREGHF2KBK7fQ0QjCVC7BegWgXR21HjJGNEeJBWxMzTGbhz+Eb0XXMFCw5uwulskBpwwaUn3oI5acfA1atA9sxlN/J0RrK3/kuSr/8FaI3XoH2Y2dh7uqfoHPTH1EvvAOnJfTtvxzdh70Rg7OPgvAbEJsCEzEe7r0bf+q+BUNMRtrbf/fRVpkZvStRjuR99O63FNXp061AAAUKFChQoMDewK233opbbrkFp59++oTVWQgkY8To+TLnByUE1VoNuOsuDJ75CQRhAEooSga9iguB0IhuUAoCKzQqJQQxZwgI1Vz1EqXoqFS0tQOQlhalgVfRaBSlC5C8866OqTqK1lC1iuFaTfOxBYRuo5Qcq5RKKIch4oTjLiNspTxva+tXZ/Pjo2ipe1e/lcYdkBrhPKtGs/H+ff/2HVPWEbMvjagYvjwHri+FGWlLCNHQNJtrHXF2sBmufkI/aTUviGUJ8lBD3DECknwx6p4SOp3S9PdtHMbau3ehb/0o8hDEI5jZu1ILIZ1iE6YtGsXUQ6oYPngZtsx7FR6ffRL6OpamNDcGgNX0ABFCtO8SAJBOgvJMivLBZUxjFfQ/MorBp2qZjf/uZ4bRt3oUC86cjq4jlqC6bBnIZW+QWq7eXkz9wy/R8YebEa0fRDSYXfpIfz/KX/kagmkxppzVDTLVP9+rHQuw69DXY9fBr0bcPkuPpaJFuf4gMWOImLSIVmsRQCliVYYxDMQ9+OGmL2BXtEW3MaU2Hct2H2m1q+hanFCsPOd8sJhb1hD9VxLT034ZPHU5h4TWyXLGtd8HNUiA3PgtiAAR0DQwUMNCp48lZEU9p5TVVVpJ5CH7/c6bzgICxPEEda2ibjhe17+unmbTn7vErs/sZ941bpkXAsznnEcH02Uu/oL12wdlPSksJRMPcus/omRYp/gt70UgAgDn7LtOFbBQWEjyMXPmTHR1dU1onYVA0iKGz/sswiCwNqLmRyCkAcIgsB1HicztoTZ9pSS2fpw4xZoTVnHNK21t6KhU9AdSbW6qkTzfXi6DEoIKIdphtn90FIxzjER2HgSm+5G2UUlCA7eVSro/Zl+EwQ1vFIPfpWl5y2ihIHvOzUfhwjRj1/N5aBausGFuZszzLup+3Alpmdttjmve2FEihcNGjo8C9sbUNyaugGKGZFUCaY0x7Tyg6unfNoqN9/agd/Vwbvsdg5txwLpfY1b306CCozQ1xrwT+tC+kGHFggtx9+LXYKRs5MiJUsoiIcTyayCEgBOeblgpsTaZleNClPYPMHhfFdFO21rCRjk23dGL7meGMP+c6Zgyqyzr7ejAyIVXYdeFV2Hm1gew6J4vYuT+nehf3w4neDBqAyE2/H4Wlp63C6Upaf0980/C1oNfh55FZ4AGiSIg8QVzhfHYomxxRMn9VuMYoBRRHIPHHAPVXvxo5+exO06d8xf3HopXPn81KmyK1a85u56AAMGTl12OnYuXgTNmCR+q7eTx6t+m/4hyPFdjS4gAQBMRJBluUBDi5BASVmDd7Hzk6jklP5WPSR0hGLCTHsr+yMSJSoFTSgRTM0S2S9dSdSgfkiD5PdHBJPY2xtN/hXprYzO+K0p5Qy+5CTSKgN/8Zsx9KZBFIei9sFEIJPn4t3/7N3z0ox/Ft771LUyZMqXxBU2gEEgKFCjgxXB3Devv3Y1dzw7mlmkf3oH91/0a83Y8CgIBEnDMPnwQM142jDWLzsPji6/AYGX2hPct7KLounQKRlfE6P/zKISTi3Bkc4R13+/G7BOnYs6J00BDvaNFz8JT0fPGU3DMnL/FrJVPY+dT0zC4ud26PhqSQsmi5aPoPuISbDv4coxMXyqrmKAkeSNsCD/Z9f+0MEI4wYV/uRhLBy7IlJ3RswJt1V48delrseXIYyak/QIFChQoUGAs+K//+i+sXr0a8+bNw7Jly1Aq2b6ejz76aMt1FgJJiwiDIMk2LH8zztMQupSilDiYu5rAgFLQRGMaBoG2WujzhIJSinIY6DJmxCYuROYaQgiqUYRaEkVrYGQEw7XUwZgmIU11gjCjDaWBbCuVkjL+TZa8T9vCkl+uPgghoOp+PNQIN1t3HhpRtMw688qbjrF5zrWudmSs4Rlb2cBm2lAOqELkOriPpW5Fn1OBBZSVrRZHGO1n2PynXux8ejDXH6Iy2oP91/8G87c9AJpweaYtHsG8Y/uxfr9TceeC16O/bYFsc7SWoeNlNN2Gdh0O5ca1ngAAlSm7ERxM0bmoDcMPRaitt11CBQd2PjiI3hUjmHN2B6YsKuuITHM234vOnY8DM4AlZ/RgZNcgNt8/E9FQuiTWBkp49vljseF1b0F7MAVBYuXI0/rrJIcO1S1mDHEcowxI53ZCMTg6gB/v/CJ2RptRqQmc81QnXtbzFox2HOgZ6904bMX38MwFl2DD0ceCxyy5P27Rsex7N60b6XlCCARLKYs0UOG0KASxaV6a9sWFpG0p66nHwR2AtpKYY6JoW8kP7zumYL6HKngHTaiK6h1yHdpVefOaPK2mLxO79XsMguZYnM9dNIq0Va+NZhLJ1mvXBx+1czz36HOaLywDBV4MIJRoSut46piMePWrXz3hdRYCSZOoXfDfAKA/eqY5XdG3SknIXt8GIQwCHVGHkMDK0qo480IITcmqRjEogY7UFVAKxjk6KmnUHcY5eodSZ93+kRFEjKG9XLb6ESR8bJr4tVTCEsqJQBIxhoCam3NZly9ikylEuNGjfPfNnY0QRRKxBwkVSW1Acnjb+pjnQ+uLnuU7b8KlZWWyPTttyz2vQauqU58PTQlXOTv+ehsAn39OM2XNKGgqqpOak7WaFGpX3rEDu58cQV4+vVJtAMvW34aFW/+oQ+2Wp0WYd1w/ug8/Gj+f/3p0V5aAMQ5UU7NFViBB+vypI4C4fx1hRZ3TlKAAaD89QGkZwcjDMbjjvx71Mmz5RT/a9y+h88Q2lGYEOOiJL1hl2mdHmHtMPzbfZ3Ni2558Gv/253eiY+o8XLX0H7B4ygG6/YyAZ4a0NsJZx4yBRxHKAGqjEWqihp/t+jLCbevx1kc5jt50BFYfdDVGO6Zmxnv2rifxsue+i1Vnno41x54EEcXg3BAUGsx997y7udR+Ho4viuAkoXOZkbvU+yp0bhIF16dEEA7OiM5pIq+z104f9UuV0QngPcKFqbjwvYM+gXFf0yYa0a8a5SVp9R585ZtRqCjfEwXVH1Owpcs/C9zxvoZ1uYKIOQb0kpsKoaTACx4FZSsfH/vYxya8zkIgaQLR8hsRGpPKDM0aEAKinMaTddz3IajFsfERFRip1XS4XpFsZkzrBgBs6enVeUlKQYgwCNA3Mpy0SzF72jQMVke1wDE4OgomuOXoHgbSKgJIoWZqWxsCQlAp2Y++vvUj+RCZx5C9R9fp2+V6qz6oOt2P9EQmCfNZNsx2sjx0Tx1OHgKfUriVxcbdxDbqdz24glheKGQ3L4wKpBAzhhpjiOIY8QjDlod60DYH2P30MATP9iGMh7HfhruwePPdOjEfCTnmHDGIyuEh7l52LTZMfzniKIaoRvkBEAzrh6k5sgUSaMED8FtI3DoIJSBzCNqXU9SeEYieFxnrzsjaCCPrIlQODPH07Nfh5A3phokB+NUBZRx/X7bLlQjYXduBr63+DN6y7EOY37bEOq+eBTN8b4QQECwRBjkHSxQNvYM7sO3Rr+Edf96KwzdQrD7gNVhx2HnZYeIxDlj3K4jO3fjTVX+D/rnzIWLpM8KNdnLHOYHwTQxKMjlHhICeRIIoAURVIrSVJOldRijJCjrpOAQqt5Jj+WoWpmJAWvaA0AyA0EgxQPJ9xCZCedmKr8eeFI6EE0J2LBZdt38+640Qom6o4EbtvxAExAIFCrzwUAgkBQq8RBFXObY82IcdjwxAcI5F52fLUFbFkk13Y7+Nd6IUj+jj0xaPYN5xfdi06CTcs9/bMYysdn9fgJQIKi8nKC0Dqn/mYLvdKAhAdVWMh+m52D5nIY6tfR+zwg24szPGf8yZgX88jOH0Z+1r/vcmhqeWEfzp8AH8MP4s/vrgf8acyoLmO8U5yKZVQNc8nPCf/4HZu6sYaZuFR499G/qnL8sUr1R3o6PyNJ599QmoVdoayRwFChQoUGBPYAIsJJikwjdjDDfeeCP+7//+Dxs2bEDNUajv3r275ToLgaQJmEm2TJ8MQOoKWYPEAyo7sWLBDI1WUSmFmtKhtNeuhaQShhnrwfY+maMgpBS7Bgcxvb0dfaOSo1KNY0xvb9eaWkJk1C9llaiEIaa1VcC40OGEQ0oztCHeTFSnHC2XSxfxWUkAOab1/D58deRRoFzLQz2euu94nu8KcZ57vYXJtLLUo6DlWUncOeXrZx7nW0XYMulZKoGh8jtS52PGwCKOTQ/3YvP9vWCjyVxxVgLCIyza8gcsW38HytGAPl6aIqNnBfu14d6F78az008Dq3EILq0mnNWnkaWWDWNs6lC1fMf1JYaFRPkaKIoQ6QBKZxMEawlqTwvAcXoHBzZufxk24hMAgFrfKF61YwOeO2QrlvVuxtShLegY2oKQVREI4OVrBV6+VmDwt7144JhPIL7kQ4jmL7TGVj8PzlHesRPTn3sOU5//C6au+AsqMcHqT3wcM4aArfNOxvMHvx4sbIcLWu5G98sZdoUvA2ccImK2P4YQhn8IrLFu9D7qMlwABh1LzzdnrihLGSH2/GqmHWWFVNZZ87pGEe0CSjUN1vQfyUNqeUnb2hda+GYtJfXWqrFkbm8VuTRRh1LnrjuuBdxbRxNWYAXXyuKjcKky6nkWNK8CexOOsX7MdUxGfPzjH8fXvvY1vO9978N1112Hf/mXf8G6devwi1/8Ah/96EfHVGchkDSAuOjzCAxeLSHEooLIzWD62/TBMAUDIA2tWkmyp4c0XegppVg4s6zLxJxhYLRqLe6UAFPbpA+JzCci8xj0JH4klTDUwg8AlBOBZmoS4re9VEJbSbahnOcBTcDQ/TbRakhdEy5VgtcRUEy4H2ybpuP4snjqdT/o+c6bSRs5AoBZBoRYYzNRG568tqmzGTChN6jOMzNziSiHdTWfAIBFHJsfk4JINOjPCUwEw4ItD2DZ+lvRVu01T2DGy6roPf0w/K7rNGzsOBwxJ2AjNXDO/dSgvHtu6DNij0XyI1PWpHxJgQQgLj1oCUF5AQFbRcBWA2D+Z1autWFR7RAAh2DFoUmTnGHOriewaMu9mNG7EgTA1FHglQ8OAQ9+DD0vexm2veJM9BxxJEoD/ehc8Tw6Vz6PzpUr0NbTY9XPEt+vZw97M3bOOCbTviAco4sGUJ0llRIiEl4BxBQMWh1z4xeI5S8iIEjqp6PoWakgBLsfJPE7aXb6U/vdVPM08LynlBCEQRr2NzTyOXmqs485dL5W0EjoaUVQaEbRMl7khRhXa4LX766B4sy9Nk9w4gYVNC+3kW/dMsv61s9GfiVjDSpSoECBicf3vvc9fPWrX8Ull1yCj3/847jyyitx4IEH4uijj8YDDzyAa665puU6C4GkAdTH0PwkMiGsxd1R9Gq4DtHKkZwLYVkmuABCzjU3XJWpGAkLVVnl1E5AUI1jRCxGZxIDWgghI32pCFrlMiphaGkbh2s1BIRgJHFipokW0/zou/4graDex7dZQSHPwqG0pZSIjFCSd71INhJjuR+ZyyD5OMO2jLk+NM1w0VU/fP4tLtz+ZpyTnbwXKhmfvFYm3azFMaIkV8XOpwex5b5e1Pr9gojyYj/hkc9gau9m6xSZW8ami8/Gb5e+AhEP5TytCbA4zkR6ElzUjSpCCAHhWWEjz59E/Tb/ArAtLAC4isbEuFWHsqTgQIDuRyBWBxDrKeDxk8kMCQ2wY+5x2DH3OHQMbcWizfdi/vaHEDKZGHLmc89h5nPPYaRC0V7NiQKQYHfX4QCAXbOPBmL7HKvEGF7ag6itpqVLzgxfETOPiGuNaXLzS0Q6htKK1MT962dK4OYlacYKqX1/DEGGC5GuR8gKDmEQWFZdVbf6na4BTvsgmVt6ofgp1LOI+MayWeGnXt6jRsJHq3DnXdqHrGDiBttoRvGkYFpNfONWiCQF9iaKKFv52LZtG4466igAwNSpU9HX1wcAuPTSS3HdddeNqc5CIClQYJJCCIHuZwex+Y+9GO2Jc8vNH3gUi9fchW0X/B3aR3al14cB1l54IdaefCZAKVicJk18MYJUAHI4Aw7g4Gsp0E0hBtCUcDLUsQDPH/IGrD7grzB/+0OYtfsZtI10o310F9qrLh8sRRxUsPLAy7Ftv9OwCNl8LrWuEYws7oegPBvGrUCBAgUK7DsQMgGcrckpkCxevBhbt27Ffvvth4MOOgh33HEHjjvuOPz5z39GxYgG2woKgWQMMGlbPv8LwNbuqCg8puaIGRonFX41Zlzng4gT6lVgRMhyNesRY4mWTFFdKMpBgLayjLJVCkJUwlBH81L5U2JjUxka9at6zQhOppZLXZWXC8DnFzLRUGNPEw4892hZXYgcjWMaWtSfjd4KW6xoDE5OlhZYM8l1trWmFb65OddMPx9lIeGJlaMaxdixoh/r79mNkZ35m+VF5HEsfvo36Ni5WVOKFAYWLcLTr78KAzNngdcYAAbGGHjMdNhZFjO/5tRjhPFGyTJ9RJi9bhPnQ+D6k8jyJu1L5PqlELceCuBAgByUvMcjFBgkwCDB6MAIRvtHMX1kFihSWqO+tbANmxedic2LztTHyrV+tI3sQvtoN9pGu+XfkW4MtAdYfdAVQDDHyHIuwUOO4cW9qE2XgQJEJC1NOnQw49mx1RYLu0/mO6ppN6bZ0DPHlNWFuOZFD3TELcMKJohI3FD8FExirlc5GkKVYd2kKZqWELNMek22DlXeXbPGgzzLhdmmOjZen4/x0D/TNWxsbbvrFyXZb5q7NrrzkuRYoPNotPXGrN6zK/xHChR44eA1r3kNfvvb3+Lkk0/GP/7jP+LKK6/E17/+dWzYsAH/9E//NKY6C4GkCfiEC/u8+ze7qTd/K2HE9BeJGUc1jlBTSc8Uz9r4QGeEGsdHJaBEJ1Ssdy/M0XL7HBFdLjC1L8itvxk60niggwMkVQcNKAsmtSr3HhMamM+p03RqrweTPmFysc3NhvoQ+4WjfIqWu0Fg3BZwGZeCbMwYomGGp3+6BQMbRnP7Oq/yPI7q+RHEw1szIX4FIVh19iux9sxzwAkBq8XSMgK5SWYxS6lELJuYLy+QgZYTaCpoEE6cMrbgYF4ruNpw64rT+qCoYH7aV96mW7cXApgh/wsJQUVQ/Gb4y5i5YyGO2HY6ZozOyxlJiVp5Omrl6ejvPKBuOV1+2giGFvWAUQYRKYqWFEA0bVOIhgECfMfVfQtm3qOAkq3Sd90d6/y6CSHJ+Dd+n33P0j2Xl4jUPK79u3zClLthHuNm3hvqewx1NcohYqJZ4aNVQccnWIwF9QQU969CM/fUiDK7N5z5CxRoFWPxR/PVMRnx6U9/Wv/7da97HRYvXoz77rsPBx10EC677LIx1VkIJE3C5cX6nMCV5kgnoTM29UKkfiepRlttKOVvaSFJqTUBoZYDqOknoIQa05kzpIHNq+ccMecghmOzisDkJrxqJoJKM2j22tyIUaKxjwVtYEblQmiBRfmb1PtoCiG0UALYTp31FpNsAAB7I6DyAlhWpiY+vPl+JUZ/LYGWI4pjDA1W8dyPtmN4e817/ZxwFU6o/ACVZ9agf90U+PwIHv3rt6B7wRKAA4zF4DEDi5M5xxgE49pC4tPi+wQSyxrCnXwjqpwVZow45VLhI61byOuVj49rscvZkTXzcegTPdgVbMGmBSvx1Px7sKj/EByx7RVYtvtIr9WkFQzO3Y3h6UMyEAAzHdQ5BDeE5CRKmolGTuyEpvPcJxS6ZTPnHCFPt9vEO5l5znX9iORf1+rrs7z67oESas0NlackzhHqm33vmsV4An0ArQklgJ2cEGhuDjcjoDSy7o6H+u5aRMx7dp+z+Z1sFIGtQIG9CbnVGK9AMkGdeYHjlFNOwSmnnDKuOpow2BcoUOCFjrjKseInO7zCSFe4Acun/gfO2vIJRLdvSYQRG31L95d/lyzd4319IWNA9OAOfBujSNK9E2Bz5/N44pDfYfDlu1BbOATWEYGHrTl8RO0yLPLojKFm/MkLFChQoECBFzS+853v4PTTT8fChQuxfv16AMDnPvc5/PKXvxxTfYWFpA7ystG6EY5MDY+ZrdnNkm2GZ/Vx71UEGastg5YTc2blLiGEICSBfb2jmYri2Iq+5Itso/JYeMcgh140Vkm2XhjbvN/14NNeUEDn3wDSkKCuNSsP9UJn5l6TPA+zDUV3cC0uLVE8DEucO8+UL9DoSA1P/2gzhrZUrWun0N04bdq3sKD3IWz/Yyd2j07ztrH+jLOw8pwLsB+AuBYjTihaLKFoCe3XIGzKlhCWlt8HGhBt8QDy6VnKJ0SdI8TQsivtu8j6g6Q/haWJcv0sZH9zuwkA6CZbcG/wEwyTAev4HL4YZ8avAwJgZN4AMC95FoyA1oL0v6r6d4igFoBwCkE5hmb1Y2RmH5ahC1EUSwuTkJnOrbEUZohf0bjDeiCS+cUSLTR1T5O6v8eDbN3yL2ccQRJaPGMFcd4r5cdWCkOUkoh/bhkzRLdJe/StmUDrfhlulvOxYCyhgV1KaDN9rhe1qxm0YhnxRfJqNE6+kOXud8mKWmlQiNW67YZ6BprLW1KgwESioGzl48tf/jI++tGP4tprr8UnP/lJsISxMWPGDHzuc5/DX/3VX7VcZyGQeOCGHrT8QRLBwtoc6nN2eZfW5RNAAOn7QYjMGaI+zgICtZhpWg5LhAtVRykMUQpDK6mf+qi6i3kq1AiEVJ53w2i6H7l6m5ixUB/qUbQaIY8i4vt35sOuxr5B2N5W2gb8z9Qtq9qgJvdepH1rJseIassUYJUwEsUxeMzx9P9twcCmrDDyV9OvQ/XpIWxe1eW9h7hcxtN/dTm2H34UeELLiqMYUZT4jHAOHnPL0VpRjdR5dyOtoIQJznNyjjhO1z6aF7Vyitj+J4BL/8p/no0EXi44VoeP4/Hy78CJ7ZE/k83HK6qvAxEUsRmvN7lnFkYQAYB2WGF6BZcCiyACAgw0TsYjYtoHyCeAiJy1wgd978ZcEYCM1uXL5QLj3faMt69uXx3GCbsOKV0kLAABAABJREFUM9+IfnbZttX6wThHQKn+HRj5aSyBw9OXlP6T37+8jft4nMgboVH+jYlGs8JJK8E3Wg3UkQdTMHH7yTj3rnH6m+jU5aXuehSGhZBSYCJRhP3Nx0033YSvfvWrePWrX235k5xwwgn4wAc+MKY6C4GkDkyndFdTbVk/jI0iSDbJoM9Hw43gFBAAQaAXcRlti2lhhyf+IzrKU/IxByG5MfsBGcFL9S9mDAGVH/vQEVpcrb3X8jBOQaTRJqtZLWErmwnlxJvVuLb+1fU5c9Ytr54d0s2TQOrfksfLN9tRFjFm+BQoYWS0FmPlz7ejf73twN5G+rCc/ht23xUjGuzI9osQbDnmWKw64zwMTpsORAxgDECIOIrBtEDiWESS3Bj2xjvr2E4I0ZG2SGKdylhEkN30WhYSCnCezlFKqePorv7adRoVqoHN3r+RaDBGhEfb78SG8l8y5TrZHJwxdDkCEYI7MXnNZJBaMGP2mmCuH+pO4iiWz9QQPvQ1vLl3RY8bVfPbuGUhZ0+9ZJ/NHHfPEQo9pn4B08j54lyfFQCF6r6VZE9dYwoZyt/AvB+rXxPEf/MlA8yU2QOChc8/x22nWYtqq5YTSpq3lhD4LVE+NLIUCWFHmVT9NXPUuFYU3xjkKfgKFCiw57F27Voce+yxmeOVSgVDSbLuVlEIJAUKvAghuMCqX+1A7+oR63iFDGA5Pon+349CsOzr3X3wIXj+4ssw0DVbWkVYTqLESQ4Bjt3BDjzSfhv6gl2Z87PjxThl6FUoo30f9K5AgQIFCuxrFJStfOy///54/PHHsXTpUuv4rbfeisMPP3xMdRYCiQN6yU2W5sVngveF9FX/dildZh2WxSWXCuQvo2gMpsWEcw5hhPkNgwDlUGY6NvtZixOqiUj9WJrVjI4HPuvIWCJ4EY9m1oVbr0kX8F4j3J8NrB3jyBGsLWhCPUfNI9N1uz5JbnhnAaGtJX3bhvH8b7ZnaFolMozl9JMYumcAgtkWMFYqY+XFl2LDsSdKf5qYI45lFC0AEEmGcxYxxAZlS3Cuw89yzmVkLe33kI205YuyZf2lOZpuQ7uu6D/UoBVywr1aep/lxa1fQGCI9qEn2Kb/6w13ICb+HC0HDh2Hw4dPBwVFhCgzf7QFxKGucZb6g+gBUn8UhS2JUia4P+N6o/fD6ktCzUotEXJ4MvQrav47G+JXtdvIiuI+Qzvqmb+sEABRliQio/ul7xKxcy0R6tWsuxYTq98e34+xrDEvBrRCB6tnPcjmcjHbaK4v5nroUn4B24fPvYYLZELPlygBKNUWElkuvzOmFWaybvgK7HsQm9065jomIz74wQ/iH/7hHzA6OgohBB566CH84Ac/wKc+9Sl87WtfG1OdhUBiQAkjec7o+pixAZOUgzQUL3EoXeoa8y83KGAmFC1L1QUgXaAJAaMULNn01BgD4xyhET5YQCSc7LRu6viLBE1K/GPlPdfNp7GHNgp1napJNuSnK6S4lC7z2eQlvmy1H1Ydui0/7c+k5sWM62NRjWHTfb3Y+mBvxmk7JFVcENyA4Xv6wGNbGOlbugx/ed0bMTB9RuIrIhDHkpqlcoyAJyGEI6ad01yKlhRG7I23Dk9rDIw5Rt5p5FC2qsEweju2obdjK3rat2KkNIB9EYkq5CUc3XMeFoweCJ78z/euaKHRGAdTwHD9aYQQ+p4ZY2CeQAD6t0EnU9Bd8HCRbSpTWtgSDHwUqwY0Iass9VDqPIIPnDp1WcMXyK0/DChKSeJWQqQQmuek7rZhwpcfqhF8Dtt7Auaa2GyuEqC5jXardctrVHm/cOJb4wSMsPWeb5cvDH6mjPH9M/ur7tOkEeeNgft9Mc8X/iMFCuw9vPWtb0Ucx/jQhz6E4eFhXHXVVVi0aBE+//nP441vfOOY6iwEEgNKG62iF7nx01UZVQ6or93mRj3c2EG6TsqqHTOKVpwIHOZCzznXbbFkoxi52mkjipb62FgO7Dm87vFqmfIEkXrWpkbaPZ8WfCxw23GzpTeDvMAEjTZB7obBd72bXyZmdjCDmDH0rB7Cxt/2oNaXpVhRGuOC8AbU7u4Gj2xhZOfhR+KZq96EiAvwiCFOrGVKGGGR/K0jaXGmHdwzmv9EGNHzmnOAC8uHxDceAgIDbd3o7tyA0fKgPJg8kuG2Xgy39dUdw72BqbUuvHzH+eiIOhHDsJz4zQnaOiR/+qPm2b8TC0nM9XVJVd7y5jug9+Ii+b/A2LhxYUTVcqKTma17rDzqrxYAdPued44Q2/cnI1zYxVW/zPVT/VVrXECaX4MarQGUEHBH6dDIj2Es68re9DFpRTAB6q+vrdyvmj5c2MKL3ZbVU6udZgKYZITTHB+evPEmhED85ppx2K0LFGiMgrJVH+985zvxzne+E7t27QLnHHPnzh1XfYVAUqDACxi1wRhr79yFnhXD3vNTg504O/gCqvfsBKvZsWm6X3Y4nrnyaoggAHjsvX4iICAw0L4L1dIQhLNRGWzfjZ0z1mO0MpB3+T5FWzwVC4YOwgG9xyEUJWS4fAUKFChQ4KWJgrOVi7Vr1yKOYxx88MGYPXu2Pr5y5UqUSiUsW7as5ToLgQRp+EBlHVE+F1xwbdbP8JRz8kOY1AGlKYqSSFd5VgTVrrKKANBWGmZooyMzwpFxrc/XBJChgRUNAlAm+kRLaWnuke7DxvDyuD4y5r9951Q/8zRpZmbivEhMJvYYFcyxfrXarnt/+rdxnHEOLjjiRGseM4YaY4jiGH2rR7Du1m6warYdihgv7/glXtb/S+x8aApY1RZGeg4+BE9f9SbEIEDMwJmkYimfEWUdYdr6kcwzJ8yvGf1JWUd4YrkbKO3Cjs612NG5DrWyX2B6IaHM2tBZnYvptTnorM3F9NHZqLB27dPBkEYUM5HrQ2LQrPIsHboOId9BzoVsL+e9yAufrPpBCAFVEb8CCs45aGIiIUG+ZaTeXBVcQJCsb0k93y3lP9JMRDw1ppQmPU/6EifWH9W3PIsGF0hDGxvrWysQQug4ab6M8M3kIWn0vjdjhfBZbhpdNxarTDNjlGf98LXPhJy7gPxLc/rEExqnr2+m30hAKYj2HUqsh77kQQmU5d+y+tTvdoECBfYg3vKWt+Btb3sbDj74YOv4gw8+iK997Wu4++67W67zJS2QKEHE3ByY9KpqlCYVdGlPrk+Cgs9xXdFyXO6sSdOJ4hhRIpQAQMRkeFAtoCTHffQjs20luAAyNHA5DEAJ1WXVfbRKB3DRyGE9LxeL7jdsetlEod7Hu14IYuLQqdzABHl1t0L9cq9Xcy1mqRAcMYZqLcLmP/Vi15/9ofMWlJ7FGVP+F9GTvdi2NpvssPeAA/Hk37wFNRDwpN44kgKIclhXwojyIdGOx5wbFC1uUZOUMLK7bTNWLXhoQqlWQVzC9IG56ByYi2mDsxGIUnpS+St4fBDcf6tDyp9CXRfyMtpYR2bTGQmZ20do+lV9aomC+34DsHOKuEhCGPOYgTFDiZAzx1JBwqBZQiQCSvI+gwMB9QtAdemQDTbeFg0src8d42ZgCkygyW+9lvqFg7GgFR8SM7ysiYlIjjhWKmwzc66V61oRfPL8Plylkm+tI863LGZMJq50/EFMxRlJvkPmM1DKH1M4sunHPiGyQIE9iyIPST4ee+wxnH766Znjp5xyCt7znveMqc6XtEACpIslAB0b3XJiT6IbRUZ4VGospmEQWHWZf1000lpxzlFNNpAjtSpixjMfAdMRMKBEZy4G5AeDCZvjHzOCJGFywgkWVmLEvDHJ11XZ5cy/qg/qmM+/Rn9UPJrbvIg9rfbBRJ4Q4osS41q9fALEeOEm2VTCiJpfg/2jWPfr3RjeVMtcWyEDOG3at7B04I/YemcnouFsjpH+/ZbiiavfihoJpJ8ISwWQOJKWEiDNwq78RZSXfF4ULUDm7Fg998/YPOu5Md17ZbQDM3sWgbIQajsRxGVM7Z+NqcMzQZDj/GxZCaD7Zv7W15lafcd5PiZxpn7X2uFGv/L1R10HZ25pGcOpQ1o1JFgikOjrHCEmbUsJH2kGeik0m32hoOAQpkWxiQ21EKlIYr6TuUqKZCzdd9cHqy4O0JAaz0yOi1p72krlzMa0GeQJFHnwbcTH6kMCZNeOVtvek/4tYxVKzPNuX9P1SoIJYW0clD8jIBV36puorfieb1hAbQEjSc9rCSAAIH5zjW6beBIhFiiwJ1H4kOSDEIKBgSwVu6+vT+87WsVLXiApUOCFgoHNo1j1yx2IBrPi4IGV+3BW5/+Cba9i4x+6IHh2kdt1+BF47o1/DRaWgbjxgiAg0BvuwGgwiApvA7Agt2xf2w48M+8ejFT6c8uUa1NAuU0dC3iA6f3zMGv3fugY6gK4X9ibrIt2gQIFChQoMNlwxhln4FOf+hR+8IMfIEiUEIwxfOpTn8IrXvGKMdXZskCyefNmfPjDH8att96KkZERHHLIIfj617+O448/HoDklX3rW9+yrjn55JPxwAMP6N8rVqzA2972Nqxfvx7vete78NGPflSfW7ZsGdavX4/7778fp5xyij5+7bXX4vHHHx8TL82FSdVinGsNjtokKe0boxSEcwiRUmqUWb8cpkOXapSz/iNAaqI2YfJpFVUsZgy1SEb4Ga1F2o8EkBojSoi2XMgNXICAAsSgZJltM8FBnI2raxhR2d4V3Ay59Xw2fJaRemXNurmQ+TiyGdQbaySaoWZ4KWUw+2u2adPKfM8wr91WrDiKoqXaUdG0alGMjff1YNsD/XBNUxQxTpv2LRw95dcY3l7Gpj/MyggjrFLBqsteg80vPx4gRGdbN31GlHWEJRYRFjM82nEHNk2R1o4KKrgQx4JxBjXtOONgIsbaWY9h/aynkjBPNtpGp2LW7v0wa/d+mDIyw3//PKXvZfwvPOOYGVOeHm+WT29bSPxldP8M60YrMK0bLoVLGFYQ2YFk3I1noMqaf62IVNyhSlGAENt6SUhgU8Zo4xvxjYdPc07yjagNKGEOqGk1SbX2YWKpTS2TAkSIzHrkHvOBEgIlgo/Vp8wbbriBNaQZa0melQRoLo/IWChcxPkWjCXDOTfmNTeYBOo3kH77FEXLpAQz57uozlVKIaiRc4YQAn7Le0Ev/kJ2Dibfan7Le4uwvgX2OgoLST4+85nP4Mwzz8Shhx6KM844AwDwhz/8Af39/fjd7343pjpbEkh6enpw+umn45xzzsGtt96KuXPnYvXq1ZgxY4ZV7sILL8Q3vvEN/btcLlvn/+Ef/gFXX301TjzxRLz73e/GeeedZ3HR2tra8OEPfxj33HPPGG6pNahNEpAu3moClQIKIJT5RZJjkUokZ3yIqLOpcDeyofHRledhCUIxY4gT3w8lhKg8I2rRpokE6obQNHm2hBDro6jaMT9AVAjp3C7sclayvgYbv7z7NM+5CSK1c35SztxkuDzhVl/gejQD1Rd53H+NSlhoXZPQHUzBsRHVIg8mjY0LWH5CAzuqWH3LDgxvyybp66DdWD7js1hQXoGBzRVsvi9rGek74EA894YrMTRtBuIoDekbR7EUKJL5qoQR9XtUDGphxKqvtBMdtVkAgP7SLjy74A8YbNudKUd5gKWbXo652w9KEwSC59JjrM06t+lOADTtCGiOc+s6f7vIT8DYnLDbKl1QcMP5n3Orf4QSzY1nsS2QQNeh+qc7mnEcJ8J2audJP0myExd1aJi6L2OYv2P9oBIzfmwCIdLNsat80IIdROZdVPDRtZqlmPpQz7E7LxmqDlHrnFe/6+VRaZW+ZV5r9aGJa1z6lkJD6rAz9upbpb5NMWeghk+j2Y763rjPjBCiqVw0JwHmZN24FXjxohBI8nH44YfjySefxBe/+EU88cQTaG9vx5ve9Ca85z3vQVdX15jqbEkg+Y//+A8sWbLEEjZ8ob0qlQrmz5+fW09vby+OPfZYHH300Vi4cCH6+vqs83/7t3+LL3/5y/jNb36Diy++uJUuNgQ1eKg+DbgwPhBCSMtGOQiszUds5AOpxTEUSSXmHNQTpcfdEKtFPkqsLqNRhOFaDSO1GqqJhSTvA2Zu3gNKkkSIxFtWCAEG+0NJhO0j4wO3xsBfOG/Tn56HlehRa+rMvkmfXCe5WzaKju/j1Wq/fMKIOca++lTUNPdYXp98cPvCk8AF1YEY257sx+b7eiHibNuLyk/igs7/RoX3Y8tDnehbk/UX2X7c8XjuDVeBc+kjovxBGGMQnGOQ9WF18Dj66W4gEBCldGwGaFbIAIAqGUE759g48xmsnvMwBM3O56lDs3DwulPRNjJVR4zK20Aq6Nwbws5bomANp3u9b6wbaMGVkASk3HctADu7T1d4kNU3r2VXwogZncyM1kW4fFd1v83NWo4PCSFJ2SArZGg/Es4hRGMhxKwXgDfDuq98xuLUaMobSgYaUP1eqf6SgABMYKQm/aPay2UQxoBkBSXgCCi1omqpRK71Nvtp884czOmw+e7uCX/TelaTsfiUeNtI6qknQOdZWTJ+iXWu48n3jhkBV8x7cjOum+2Z9YRBgJIWSLJ9pZfcJK0khZ9IgQIvGixcuBA33HDDhNXXkkDyq1/9CsuXL8frX/963HPPPVi0aBH+/u//Hu985zutcnfffTfmzp2LGTNm4KyzzsInP/lJK2HKJz7xCZx//vkYGRnBpZdeiuXLl1vXL1u2DO9+97vxz//8z7jwwgutiB0FCrxYURuOsfXpfmx7ug/9G0a9ZQgYju/4KU6c+iOM7Ayx9oE5iIazr+mulx+L5664UnLwElrhLrEFQ6IPDBzb6To8X3kEjLSef2T7tDVYNe+hbN8EwZJtR2PR1sNAQDF2vXSBAgUKFCjwwsZERAIdb+S+FzJ6e3vx9a9/Hc8++ywIITj88MPxtre9DZ2dnWOqryWBZM2aNfjyl7+M973vffjIRz6Chx56CNdccw0qlQre9KY3AQAuuugivP71r8fSpUuxdu1aXHfddTj33HPxyCOPoFKpAAAuvvhi7Ny5E/39/ZgzZ463rX/913/FN77xDXzve9/D1Vdf3dJNRYIiEoH3HI0ii0bk5g0xteKKPsA517SskMj8GYo7y5BGEYlqNa8GTMHUGMVxjEj5i1SrGKlVUa1FqCVaKJ7QtXS8d84BqgNoIiQEAQgCJPQnAOAMINSiRcnIQ8lvEASEQDCmtYdMCASUgDtWCl7nJTSpFQqu/4WyArl5SHSYSCKtO5xShIp3TKm+bxM6u7jy43E08u7YNuqb++88+HLKKDDYmj7GOQRk2N6IJaF2mbSCDW2rofupIfStGlHBrEA8b14n3YKzOr+MmSPrsfGhuRjY0i5PVOxyu448Cs+++nVgEQMiBs4F7q/djFX8ibQQBUIECOF/D1yUIWmVAYBts55HxWm0fbQTB248CR3DM7SfgiAUCAAhAh1VI6rKOU21pUH5DqjIb/Z8UJBMQTVRXaugtKpQM8+GMjh4rBtAntVL+JUbNM2VIWJbyPJZE4QQYHEajYwGAYKQgidWGVaLIARPOwkg4glVbnAUccwSGlfqvyV9XgzqGiGStkW4ztdQLstQyCosOREEYPY7RikQhgFKSWg9ElLwiEEkvC4SEOnHkUwLSon27VBOIxQAONdRz2QeJqFNTQQCggkQSo33nYIG6ac3DGT/BRfQnm8MEDwd41oUybVL5a0IA8Swc1SQxMqLhKooSBJVLNG2c0J0nijmrhPGs3YtPopq5FpI8vJNjQdunfU2OGOhhNar21x31RnzjtzWhHENFzK6ZJzk0VLjOlqr6e+Ur98BJQhpoK0nhBCUKNHfO/ceU3+XAPj1tbLM8s/KY7d/UNXa6NYnBeJk3xLn7F8mE6Imrbv7EoTW96Vrto7JiIcffhjLly9He3s7TjrpJAgh8N///d/45Cc/iTvuuAPHHXdcy3US0QI3oVwu44QTTsB9992nj11zzTX485//jPvvv997zdatW7F06VL88Ic/xGtf+9qGbSxbtgzXXnstrr32WnziE5/AN77xDaxYsQIf+tCHGjq19/f3o7OzE9///vcxZcqUZm+rQIECBQoUKFCgwF7C8PAwrrrqKvT19WH69On7ujsW1F7yU1/7LtrGuZccHR7GP7/jb16Q9zkenHHGGTjooIPw1a9+FWES5CmOY7zjHe/AmjVrcO+997ZcZ0sWkgULFuDwww+3jh122GH46U9/WveapUuXYuXKlS137n3vex++9KUv4Utf+lJL170yuBfTA1vDS5d/VkcHMTVAVsQQ2E7gpmO2qSGXvhFJPgcuUIsiPPfIIzj0uOMQBIE3O7nrGxFzrrnUg9VRDFVrGK3VrHwnpn9IEATanwUASslvn7ZJRTMJA4qAUB2SjVKKkBCUgsDK3t6sWTLjD2FYHnxjy0VK6nHl3iAZj1IQIAxUhBbZL9cnJooiPPynP+GE00/Xzv2uH0jmr5NTxHcvedYbOS4kcz+xENpaA8jAA+p8FMeIOcdwbw3djw1icGUN3OMbYqKEYSyrPIyDye8RrNiOvo3tyFPI9u9/AJ5/zeWozuyC4DyJmiVHd1XtCdwnbvZeRwTFwtpBqMRTrJwi6zufssqVUcaHZ3wYX9rydXRP2aKPh3EJRz92MQgoaEClf4SRUZkS6SugjsW1GNXhWpr5Xagki7YlI8+yoWDn8lB/s3M913k9x0xOHAuJSLLO6+fMJP2NJiaEIAwRlFJtJY85GIsRRzVtFaKUolxp09eoehWiqAaA4W/+5lx897u/QxQx+Z4GASiVS7DyudD9JkRahAzNflgKQAOKIEydg4NSAJr8DssByuUSaBggrJT0mEi/uOQdCymCMLVAmBZds51yewU0sPPCqLGmlGYd7glBaIyTELJ8UAotaxkAtLVJa1w5DFEphQiSvoWUIggoSkGYrmFJXgu1hgWAlUeJkDQfE4tjPPHQQzj6pBMRhGGaEJba9yHHLrvmqbXQxFgsJPUc5cdqLWnWKb1RriTftS4jIGKpLxoXXOa6ohQsjvHYAw/g2FNOQViS8ytILNzm81L+Rupeg+SYbk9bPQq4iEWAu/iZeCW9FyEZWy6HFwv6g+q+7kJDFE7t+Xj44YctYQQAwjDEhz70IZxwwgljqrMlgeT000/HihUrrGPPP/88li5dmntNd3c3Nm7ciAUL8nMc5GHq1Km47rrrcP311+NVr3pV09eVCEfJeZlpqZTZNKeJENMFmTQpkCgKAbhAoJJCBQGCMNQUqnoCieAMlCUbiyCQGwRKbWddIyQvSWgMmsoQ2Jt3qx0lbARUbloMgSSgNNkIjV8g0YG5knEkxtgSIUAEt8qYCBLKShAECAL1MfMLJOraMAxzBRJXuNBOsHUEEvc5ZTYszv0IbieqpMa1cX+ELQ8MYPfTQ0boXo/zJiIc0PYgDm77AxbET6L7uakYWFMGOEWA7AIdT5mCjRdehC2nn6mj3AiZQgwCQL/Yjd+Ln2Sum8pnYE60Hw4cPA4dvBNRHGEX2YQalb4rVU9bANA9ZYt1bvruhZD7bg6KrMO2nKIp5SmOOeKYWck5gX0gkOQ5NDthcbkTFSgVSFTLBGYuQp7cX2wknaRUgFCmWETWfQNAFDEgCUobRQxRFIMQmrAwk00+F5kNPhW2QAJCQIXsk2wXEJToqFOEUbDEwZ5yNaeTOUrT90H9BySCgzO6PGFnicwZoscEIJpWphoyI6UJ1TghBmdB7dSTNUytacRY0wIKaq5PVP7WAkmicPEJJApBGFoCSVAIJHWvdQUSQXScbbmGww5bH4Sh3oRkBJIg0FS4XIFkkm+0JwIhYZk9zGRDifDGhfY1zDVuPHVMQkyfPh0bNmzAy172Muv4xo0bMW3atDHV2ZJA8k//9E847bTTcMMNN+CKK67AQw89hK985Sv4yle+AgAYHBzE9ddfj8svvxwLFizAunXr8JGPfASzZ8/Ga17zmjF18F3vehduvPFG/OAHP8DJJ588pjoUlDBi5h2xMtE6vhF50ajkgqs+qgLME4NdZXhXv9WHU6EWM73BNNsxo2hRw9ohP8L2hsW9RrWjY8ITqV0MjQ2/+3FQaCmqkBPS1xxH9XFT+TZMfx3bh4MiDADGjXtSO3nd/+y97gm4kblIsrliRhjmKI5RY0xHRmOCS+vYYIxdDw+i56lhiDrfj+nBNhzRfgcOm/JbkCjCxjX7Y+3Ts0GYf1FmbW3Yeu552HLW2YjKbYjjWOe2YImlgzOBHXyz9/oLB9+GuMYR12LUUMV9s36GvsqOlsema/cS/W8ljJgRs3iy0VbDF9WijI+PLG88e2ec1G836hnnqT+VeVzB3cDLv9T5a7wnlGSED6MXug9CpNGrhBDgcTp3ZR6RWGqPdf+UYGKG5iaWhYGxtCznDCTzMQ4tAUu+w35/APN+lGUFkMISL8mwuGoN4JxLf4/A/y5RY80yx5UzkfbRs2b4hEhuRDajATGeo32vtp+ZAKHpGkETPzK9lhrPBQAEMXKTQK4RXAC2exHJhJZtdg1pJpqX+10wh8I85xNM3Pqz0eb8Qojdvj8qVz1hRAsbgljfGJZYCFV/zWhacbJmh9S2FlMjG3slDKUFy3kPfQJfkUekQIHJgze84Q14+9vfjv/8z//EaaedBkII/vjHP+KDH/wgrrzyyjHV2ZJAcuKJJ+LnP/85/vmf/xmf+MQnsP/+++Nzn/sc/vqv/xqAtBA89dRT+Pa3v43e3l4sWLAA55xzDn70ox+NWWIqlUr4t3/7N1x11VVjut5MgpguyvYmuV5SPx/9ShgfBDNHiQnGhV7YWfKBVcmzCSGIWKw3t1EcawfA1DqQaJ+ShV9podwEi9a9JufVB1B+OChCRT/R5vTxaQGVoOGjvimKjipjJscyP35681nHOtNMkkQXeSF8fbAEUYOCBiFztYzWIowkjpjVWD4vdU11KEbPo8Pof2YUIi+QleCY3f00Fm29F127nwUBsBbTks1Ur3fLw8plbDvrbGw591zEHVPBmZBhfBlPHcJ5GlRhFvGH146qTOcj2dm2YUzCyJSRTswcWqB3eyblS4FzYVlNhCN4ulYuIbj124T7jqmNvhQQ/M/UFEQsDThNrYJaOElMHYylwRHU+0AMz0NKQy1MCCFpekp4EUJStjhn1r3UaraUJQRHqdSm+6D6o9chISCEnXuG0jC1rlFo64gpdBFLKZHMhcTcQUNDOFHWmyAANyRAQuQxaoQTVtYq854ZY2kQAS4dydX4EZI4qztCCedc08mEkP8nuKHgSQQONymsuSZwzsEIdPj0gAbOWiO17xmKJoE1Ts3ApKs1C5+SqnEY9ebDC/ustb5zrlCSRxPW16oxNoITMEdxxpPx14oynXeE65C9ANBRLqO9TVKifTlFfH0vhJECL0YUlK18/Od//icIIXjTm96kqeylUgl/93d/h09/+tNjqrPlTO2XXnopLr30Uu+59vZ23H777WPqiMK6desyx6688sqWJS5TEAGSTXOy+KoPoqu1B+BdoE3tUFPUJiTJpIwFnTnt1KII1eQhVuNYRjKB0NY9bd0wTOGZRGIyNpH+rawoSgCR16RCDDWEFfURbfQxBeTH1M3j4QprbhZyLYAoShNnlsWEE0PrrTckdmQRQtJkWmlfSENaApBqICkRVgQx1Td3HFXeFCCNrd8/OoLB0ao+xjgHjzn6H6ti8KlqriBCeYRFm/+AJZt+h7Zqj9OvHK1nqYTtZ56Fza88H1FHh9Q2M6EtEsIcO84THwNgJuYAjsWhnU2T2vJEAFwx0x9wohEOW3M2Ahrq8L48TYWd3AyRG/Q41tpx1zriE0SyZbJCCufMEhwagWphW1kGWEIlMwQStVnnzLhOzS81HykAYVlPhOCWtUYJI2b/3HuSmn55PgzbUS6Huj1KBRiLIAQMQSWlWQLS1yNr/XEEFMOXQ7aTClI6+SIhIJTq42G5hLAcpvlWEuGWxanlSyXfjJN6gyAADVIbF2c8IxwpqOSc6jrzCxOEAcJymHmn9XQydu2+OWT+NiMJuokSXXqsuqbxJj8VHCYiupYJ11rSyBKTWaM874ArlPjGyVu3E4FQKw2SNc5VNIVBgEqppOdDOQz1N0b85hprpKiRWb1AgRc9JkAgmayUrXK5jM9//vP41Kc+hdWrV0MIgYMOOmhcAaVaFkgKFHipQjCB7juHMbrRL4kQHmPh1j9h2frbUan1NVUnD0PsfMUrsGX5hYhmzJCbwpxkYz50863Zfhr5QbZ2rMRguSdTphE6RmairTa15esKFChQoECBAi8NTJkyBUcdddSE1DUpBRIVw9ynZcv4jDiaMC5S87c0XzPbiuAxjbuadU1pgk0N01QxwVGLzXwVDCzREuuIM4l1RGkTlfVDQfKkiaZpyTLSOqKuocSmPZnWkVZ8RphT1PW9UVQs08qgrEvMoHApa5PsC0EEgEdRqjENk7FPHCaVNrgpDbnSfgsngzEIKEk50iZS3xWp6VcUu1oSe79veASjCWWrVosx8Psqok1ZYYEIhvlbH8Cy9behverPgO6CBwF2nnIqtlx4EWpdXbK/jCeUJ8caojTwqfkJPLGebBZrMnUfMnSSnm895W1N9ccE5QGWbT02acp+h6SzefKb80TDbjtxu9e5x1MqlubIWe+HtD4w43xjAY0xpVE2rR80sUiYNEfbryBLQbOFzdSnJO0rTxJRWs/I6qNNq5T3K+d0uVwBISEYC8FYbEXmstrlMp8GpRS0rCw8qr7EmsOItjoASaSuxE/GdAqvTKmgnETdKlXKoGEaPIOzhJLGhcxro8aGEu3fRCmFEL4QDcjV4ltaRcMK4bNe1FMgKv8QM6eFMBymU2tt4/Rj9ShPY6FvjQU+S0k9K0m94+o+6sH1hzSt3eY3EYD2mTNptgGlaC+XMaVcTi1mlEL85hr//RWWkQKTCIQSr79cq3UUaA6TUiBx/RsUUppSDm1G2NfKxH71TeFcCEMQkbGP0o9kWj7mTFPBYsaSBHqpjwkAHV4RSEL2OsKG+eEyhRElqCindfWbOrx6i5LQgkCi7s28f0uwS2huJo1LCSOmY7/JHWeqDscnJgwAaoQ+lpvgVOAjDawHWjAxDwqbpuBzjpZ9Sh3Yq3GM4VpN+o1wgdHf9iPa6mQoFBzztz+EZetuxZTRXdap0VmzsenCCzG0eIm14yJE7s9GZ88Cr0gfAyRCh7xfOBGm0nFQfgFxxMCiGHHEEAURUErLhbyMZSNHIuYMggvMHV6KjdP/UnfMTByz6kIEw+0IRAgupICk6Fg8EUBY4gylHLVJQECF4URtCE/p5kk9Z7WRd4NJ2Bt8+e98fxMXhHDYxajun6KEKT+T1K9F9Se9yhQ80r4JXYc6lvYRyBOY9DrCYnBuC9nyPQ8tYUkIDs5sgUkm5iLqgLU+EWYLH4QSTacK2hKn4ykVTJk2BeX2JPFlQEECagVI4MPcGRcBanyI5fMkIIbs5HsmbqANRelSJeNIClhqvrr87HTNtgVyRoCQpD44jAOgqbMNEcKKeNcIEy18uDTYZlAvElezMO/DXIt97Zi/XeWcWpcjxizKlimMlO94H4gIAJwDfvsHrSACBQpMVhQ+JHsXk1IgAbJOfuZCbTqky7KwyxrXqA1AJmKIUZYbCzx4mqHcrI9xoZ3YY851BlzVjgqtqAUQYgsbqU9EyidX1g8zvCKlNBu60tKo2X02z/ngE+yU9cfNQ2J+zJQwYmrbzHbd+k2kH3gBEQQgIo2LTzyhjn0wLSbZeu0yDOkzAqSFpJY4sPNahNKd6zDanUabAoAgHsHLn/x/6Oxfax0fnTkTG89fjh0nngzuBBHIaEoMJ3VzPCxrARep47jKBB4zMCZ9N2pk1KpyZjxf+wNwxtE1tBgHd5+ElbMeajhmgMzIrvyZlCVGR4iKOeIo1pp0xpixuU7hhux1N/TmfQJIfDKE8/7xzPtYD+47KiNEyYhNqQ+GcmI3fUrsTb6sy247XyHhF5hSSwbT7agxjOMIcczAmMpoX9F1cB5bzvUk8f8w5485n4KQIgwDPa+UEBAEASpTZL1KGFFWFHW93s6LbJ6OPEHB/C2EjD7m83Nxx6EeZF1KiSDXBwpba0+NjPD16iHGvzPnJmBTkCdwtCKI+GApSxraeZxrzXnbQBhR5bkzt7PzN/UV6ahUUA4nf9bwAgUK7HtMWoGkQIHxQnCB8LcbsMsVRlgVxzz5JUsYGVy4CNtOORXbTzkVIkxUwC1aoVoFB8Pakp3gsI13ZMrNHGk9B1CBAgUKFCjwUkZhIdm7mJQCiZvoSR5rTtPqavBzJ2ROXVrrhKzmyWzDPaesHTRHSwnAskqYkWXqWQyEsCPSmH1UfQFc1ntji0g2r4jQkcwAaOuISX/zRa4xKQOEEFDOUUto/GGQaDeTOiLGIBKNsWaxNJnUsRHcZyIgMPxohOGdi6xylNVw9JNfQke4E1tOPR09BxyE3gMORDR1qroQRFm+ktCoWnvM7X76fGS09llHPJL/dsPpCi6wPvwLhmm/VeeiwUPBYqYtJDumrMNTC3/X8P4JN8PAqrCfSZQvRdGKGThLEwJyxjNWH5fipKwf5nkXWU2tJ/pdg3fX72vEAASWFVD+l6Xrce63dpjUsbz+ZK2M3IlLkFK2UotrEg2LpVYUeb1tFaKU6kzxYZI1PrWQBCBB1oISlkPtM1JuLyMIaGqFo0kfWBraNc8KbFo9ZJnkOKDDDStrGSEADQN7/GKABqmlRCV1NUOcE0L0+y3pjMlcMKilnHNwZc1MQqhzFYLY8j/KnyNmv9T9cCDjR8K1Jdq+3rWiu2NUr616cEMC+9bIVpI1utEQs+fTvDC+vFwBpTrEb0elkuaDuejzEFEE3HZb3fspUGAygZDxB8kq5JHmMUkFEm7lwzDhLtIup9b86wMl0snb66tgtOFzoE6dy23hw6UQ+WDFkTfuw8dB1h8sIfuntpomfcq9R1cAMetqlFPETZKo6rOuMepR4yHHkutB5EQ6uiuXiBiQPiZJHbU41knaXMHNHIc82kOeM6cQwnL+DygBiQiGn6nBdOWlrIajn/oywhkR7vu7j0GA6E2aMMLEKsFDCAHCSbogkWxm8QwHXCSO4yr0tLFhTGlcsq0t4Srr/maMzkPn0DxwxsFihp1T1uOphb9LMy/Xwez+/YAuOUh6fFQiRMMfhDNDWBJygjHu+Pw4YXJdupa692ZoOPbfeveRl5+HGWNsU3/8tKTGzvl5VDJb8BFaKBFC6BDB6pmHYSUZp9RxnNLQEgJoIOeLTnQaUoSlUGd3JwFFEASZcLlhKURYLhnH1P+ldDr1DDljKa3NGEK/EGnMXWrP23SOpHVwyhGIQOcm0eKas0aY9ad+Zsk11FZ0qOu0coXI3y6pKC95oHtvjXYLjTb4TVHJWhRKMnXkhQqv07S7xqlj7prMjPedEJm8t5wEFVFZ181rCxQoUGBPYVIKJIwL7+ZTa5/VxyxHY+/7TRzhQX9kPBt7N2s5ID84gaEhtBIcGjx3t22lCVTRURo5QQoh9EdWJEmwzFxrzfhwjMU/xK0ru4nIftSYSDZoRjQyAFDp4gL1zFQ+FyEAxpLoYUkUIceSpH4HzkD5hCb33tU1AaEY2RADhkWDcIajnv5fTKtuxCN//UFwQazIUiJnd+AmsoPxfJS22oQSRrQWU1lHjEhWynJRQ9W6dt7gARBMOp3vbN/gFUY6h+ahHLdjZ+c6fWzG4HwcuPVEYFkqdMh2ZN4V7mjTrf46mmmp0WbGGHOrjGtBseuBUyYriGStEciUkb9NR3qF1Bqhyrht+/rj/50vHKm2lSWGUmpkapfCmkrYqMqojWtYUhGzCIIwzPjnAFIQUfUGIdUb/tQXBNZ17jyVz1hZvaQFzLR26bVORdlSCROVgEUTgZlKJ3l5EbXmLSFECqtxKhDKd8G+F2asfUIAIMJaH90oUeqcT0jKOnArpU3+oplXppEia0+j0Vqf5x9il3F9o7JWbFNgIkRGaSzpKI2FarfASxyFiWSvYlIKJAUKjBf9K0es37N2P4NZPc/h6Te9FdWZM4G4sdVhb0NZhrqnbMbTC38HQe0+zu89GIdsPgUEBGuiDmyc/Qw6h+biyPXngpJiKShQoECBAgUUrCiH46ijQHOYlEMVG+ELTYtF+ptDZRU3yyikZZE5ZloMzDYAGbUrT5Nm1kUTDT4lJKPhN9vjVnv5dbv+JjKXSlIP7Ht370OXMf6nc4ZwmZtDjScT3LKOqDIsydcSca7/Y0mf1X+qnPs8FIeZCRUa2ag3OaaikTHdF4E4iZkfc5nPRfVTRS+LGUfMeKZ98z/zuatoZQQEIgYG1toCyZydj6H3xCOw87AjwWNJiVL+HSm1iUsKjPpPZ1k37zehXAkZpYjH3I6ypfw2knpVFm3GmNRkJ9rs5MFl0N22GU8uvBOc2unb5/cehEO3ngYKGYXtgO3H4+DNp+CIdeeB8jCdW0IY92LcF+cQLA13q6weygLCOdPZ1ZUVQGU0V9QkzmV2c/kf08fSOc+S/1Iripvh3Xw/Gv+n+mbcg/PbpcS5x9z7SP+r37a6Tv7HIUSczGF5/6pMHNeS/6LMe6ktE7pOaf1ikfyPEIKgFKKto03/V6qUIFztvjlPWXJ9nMyrmGm6lQJ1MrBn7k+NkXGdyoESBBRBQJM65MdcWnFkBEBX7W+uT/K9zE5q61nBXMeFtYbnwV3fffflRp5yz5v1uP/52mqUHyTbR/s/3zH3vG8tN/uRmZP622db+gOa/EfsiHnWNxG2xbtAgQJ7Bvfeey9e9apXYeHChSCE4Be/+IV1XgiB66+/HgsXLkR7ezvOPvtsPPPMM1aZarWK9773vZg9ezY6Ojpw2WWXYdOmTVaZnp4eXH311ejs7ERnZyeuvvpq9Pb27uG7q49JqRZVjnvC4KnrBdqhI5nI2/T46rf8MczySGkG6lom0s192hd/qEyzDWK0PxbH7YzDpO+j7FAi1MZA952nSQ/ND7VbR57A5IYXVmDGfSlqgCAEQEr3oUJY9IyYMxAuf7v+OGp3rvxJVLua+uFsOnxQ/ehfMwJh0bVizN79JO77u+ss52drrli0mOQ6KulZOqgAIXgmvh8P1W5HG+nABe1/jdl0EYggEHHSt0Qg0Y7lLHUsZ7FNXXJD/u6ashErux7KCCPz+g7EoVtPSywo6kETLNh9SGYMuPEchbEBBqRAKIUhc8NmJ/10BQk3iWDeBsoN82snI/S/i828E0IYyf5I6vPTCvLmS97xZsopoU35lgRBCMunhFNwxhEYjuJxFIPFDKUkhK8K5RsmTu+V9jRPDg3N/CYpRYsbQqUCIYlAYfg61bsPwaWPjBKw1TmpSUzeZZ6+j2reEuNdBFL6VWz4IIVBAErShH9cSMf1NAywAKGpDwnnHEEgx2giiRHmd6MR3DIm1SnPV2q8gTh8Aoh73izjC6Si+mGGjQ+csOpCfqjsay74DHDn+5vuK73kprrn1Xpuz8mENlgkWiywD7EvomwNDQ3hmGOOwVvf+lZcfvnlmfOf+cxn8N///d/45je/iUMOOQT//u//jvPPPx8rVqzAtGnTAADXXnstbr75Zvzwhz/ErFmz8P73vx+XXnopHnnkEQQJJfOqq67Cpk2bcFsSqOJd73oXrr76atx8883jut/xYJIKJFxzk/VHNEcQcfOFuL4PqoyCqWmS50xuvxSClAVBfWhrsdTau07zZj98vhBmWQp4+eRuP62c1HkbC0+8ejfDOnfGrdnNVyb/izPWJtx8MLK/NE16xpOPlbEZoYKDCJL64wiRGTcOQA0VFzzN6tykhm/3imHr98yeFQg7OOJSWScFVDsxzuy5YQ8GkTlmkk1xFSO4v/YbcDBEoobfDH8LV7Z/ACEppZYCkWZhV3VyjxZ7CL3oC3dax3ZN2Zi5l3n9B+DwbWcAORuj9DklXWaOz4hhxVDCSHqNx+FeuAKILbDYFhFnHjoZ3O2/eX0357j9Wzhzo1mBptm5Xq+8tfZ4/E2kMBIZfi4kU84UDIF0/iqfER4zxLUY1ZEaAGD6rOkoVcpJ+6qOJG9NIhSwmKUP2+irFWyhCYqCEgB8m0gAIEE2vwsNqAyaQIx10PAhCYzjalTUhtgSTo05aK7X/nmT7VszyPO189VZr26f4DCRvhm5wUiaEKgywUAIsaI3pm3Yii3GeUsbh7z3yeqb+s45QT7IxV/QfbOuLQSVAnsB+0Igueiii3DRRRd5zwkh8LnPfQ7/8i//gte+9rUAgG9961uYN28evv/97+Nv//Zv0dfXh69//ev4zne+g1e+8pUAgO9+97tYsmQJ7rrrLixfvhzPPvssbrvtNjzwwAM4+eSTAQBf/epXceqpp2LFihU49NBDx3HHY8ekpGwVKDBWsBpH3xpbIJm78zEMzRt/Lo8+sQscqTZ4BAN4NGockteHTeHzDcvMHdgfh209E6R4zQsUKFCgQIF9hv7+fuu/arXa+CIHa9euxbZt23DBBRfoY5VKBWeddRbuu+8+AMAjjzyCKIqsMgsXLsSRRx6py9x///3o7OzUwggAnHLKKejs7NRl9gUmqYVEas6pYRUB/FojH23LtKS4pm6ThwvYkYeEEGCQGiTlxwAAEYutqFSAbdZX/5ZWEv89aW0cslq5RrQupUGU8ayy1hGTzqSsIyaVy9UOcqc9IojOIWC1a9QrtZrm/STWDUGssZBjlGygqbSGmPlTGBcIqJ3LwNSEM6ePOteBMzY+JTATHN2rB8Fjo5+CYXb3k9hy6EmWdpnF/ohTvlwOyooSoAQXj8f34Gh6BkqQmm2RWIW0hYRxnandfA6bgvoCyfzBA3HEjrO1wcC1hKg2NLVGGaVkB5K+CBndS4c0Tn0zVB2uFUAdM60dWbpVduxc2NfYbSqYVgjf3CckL8O3rYXdE/DNBXlc0dkCBEEJyvJDaZBE3VIRqYz3K8diIZJ3U1HqqiM1lCplGc1KheVVlpFITuo4Ykko4XQdEbIiTalSqGdBIp4x9M19QqQPidln/Q4leYXCwA7aKywrnLB+S8t3oCPzyciBduhfs7zZZ9dORQmx2oFz/7468sbDvP9maF55dTVHQ/R/x+rN53rn0nDn+YoL+R1I6oIAv/Bz+lpy6z/6602sG81EdtTtOL9di4k+ntDACktJgT2JibSQLFliJ1j+2Mc+huuvv76lurZt2wYAmDdvnnV83rx5WL9+vS5TLpcxc+bMTBl1/bZt2zB37txM/XPnztVl9gUmpUACkfhBZEI51jfDc+fj57tWCSzWNepjKTi4INq5uhYnmwDGLb8MANbHL900y5CzQP6Hycy/QSm1cm6oj64mgTh1uP4i6prMh7eOn01enwSEHG9rnAxBx61HJPdC0rYsmgYAxoGAIt3AcA4kAoumpBg5V4BUYDP9UpSfiuX4D+IVSvo32n4ZM3pXohwNYXDOPElfYsZGyTd2QljOvmbY3+mY5Rk94Le1H+F8+tfeOpQwYgq+Q7wX3eEWb11EUBzWdxqW9B0hE9cZFhnzwad0oISOpTZTLM07Yjuwq3vmmffGHgOXwuWOk5/mRWkAShMqkg4bLPRvt995/7YFdduXJrthnijLkU8Yyt/Mp/dGdB8yH76ERiUdxZMwrImzOJxNWilJglgbrSGOYunYzlKKVlyLESXZRjnnMjdOEl7YpHZpwZ/b89but91Xl0Zq0bYUFcwdC2MecnAguT+fkoUnSghCk7abFRLqhHRXa0SGSMez1Lq0yzalyNum0xc3x5A6Vs/npFUhuZXy5rou25Vj4fq8WP12FD7yeDq+QgiQRDjJwKRnNusQ7xTTIevdb1nSJ3rJTYVQUmCPYSIFko0bN2L69On6eKVSybuk6ToV8hRg9crkBVMa7/2OB5NTIEmQF1nF/d3I2dk8JzwbLqWtZ1yAI4kAlQglACz/ESDVzAU03YzIKCc0108kzVAs6wlzJhMAKzM7R3bieu+rzoe+kTYvd5M4xqgspt8MFwTKS5xxDmJYRgB5r/ZLZret/E1cQU0YY2MJJqNDVl86hqS2YGD2HHAmdD4JQFoQ0GDOyM1d8pwpwevxPvwY/22V24yVqMU1BImOV2ZlT8ZCCSOJMFQlI7hl+le87bXFU3Hc7uWYGc0Hp9zayJt9UjCtLjyVQK05wets0vQ9ZpzWs07salaawojrM9K4Hd/7rPJe2A7TCu4mt57A4pbPQ1aQkcJFHsxxNO9fNmVeZ+asSQTpgOpoW2E5RBAEui6V46PUJgWSypQKlLWDaYEkTv2eZAeyTsqUyl6YaxRN16KxaPOVMEKIT9BQ9yiPuQlXKQnA9fubBiNRZWLGQBM/Gt+84AJWosRs4C61vmSvc5Oqun1nRls+i0I9nyV1LOMPIVr3K2nW2b7Ru6UUWwAyuZuU8KS+V9baoZRIRK61lmLMM67NQNWl20dqwfL5CppCiW6rEE4KvEAxffp0SyAZC+bPnw9AWjgWLEhp5Dt27NBWk/nz56NWq6Gnp8eykuzYsQOnnXaaLrN9+/ZM/Tt37sxYX/YmCnJ5gQIGKgObMscEIRiaNWdC6m/HVCzByzLHV+HRhtd2B1tw19Rve8/NGV2KM3a+ATOj+ePuY4ECBQoUKPBSh1asjOe/CbQ47L///pg/fz7uvPNOfaxWq+Gee+7Rwsbxxx+PUqlkldm6dSuefvppXebUU09FX18fHnroIV3mwQcfRF9fny6zLzCpLSQufNaArI9I9jqfNsqKW29kGmeQGrw4yXWh2zC0SEr7mXJ3ZYbcgFJr8ro0L7ctQggEsftM4bdcuGPQ6P7qlVdhOU1aRaNIXGYoz1YgNb7JvyEkLY4Ji7rmas4IIYb1w+inKgNbk8mFijBDUR7YBMB2YK9Nnw5eKoFVI02FSedSts8mDUYIAWq1DJyE5dhIn7OueYjehgOjl4MIqrNpq3Y4Z3g+fBhPVu7NZF4HgM7qPBy7bbnUnoN7F0Cp4bR/2/1PfwvDWmLfVzZsbn4mdvNd84X9te+jWUuMeyz9t9/aYfZX+ZS0atrO1smdYxT1rCSuNcimP6X1+tqSGmzbb0xZPGQ+EaYpXW1T2pIwwekz5ExYIalduhdg+Juk8cudPibWSGWdpDSllBndHittII22J33GGOc6G72yYOv8JJSDgurfhEqrSkhTe4cQft9BE4QQK+eJijhl0lopydK8TKg12KVcjWV+uRb0ehhLKGKftVrRtfRaiiy1tXFfbMuGpsM1Mf6+utJ2PZYXY9xMy41ZZ0HhKjCRIB7G6VjqaAWDg4NYtWqV/r127Vo8/vjj6Orqwn777Ydrr70WN9xwAw4++GAcfPDBuOGGGzBlyhRcddVVAIDOzk68/e1vx/vf/37MmjULXV1d+MAHPoCjjjpKR9067LDDcOGFF+Kd73wn/vd//xeADPt76aWX7rMIW8AkFUhoknTQFTYama/r8Y5dJ2+X4wzID3YsRJKsj9mLpcHVlRQtijAxlYdBkMSAtzfJJpizYSOa3kERUPuMuQE3T41FIMgDJcSiL+jWjbcvANXUC3kuW487Lj6YtCIZMlTosVJO8fpDhazA0SzaRnagNLI7234QgFCa5AhRGz0OQonlL6LvSW/wkrmj+pI8w3ZM9domV4rHcBA7NimaUG5YhIfabsXG8nPZCxKctOVS8JhriYsGcuMdR8xwjvf7vNSFQRvS90yod/OfChx+Z3/7d9Y3xalNl1Pndb3m++zSOzwbGHUf8jfT70we3D4RZ266GyDVz1Qokb1pdpzrUcxSwTadc5IGmAgGgRJQEl+1WmwlUwTkPGIxzwh8WmAhpsBs98tdOzP+IXVoo0C6OdVjygVIYFyToz0011SVc8QUoKy5k1BomTE3fPPcfW55z8d8ne0Ncs7zFPl+Dm67ee3XE07qwfdtqxewxQffczTnvs93xkeRM65uqv1GgpsbatjXt1brLFDgxYCHH34Y55xzjv79vve9DwDw5je/Gd/85jfxoQ99CCMjI/j7v/979PT04OSTT8Ydd9yhc5AAwI033ogwDHHFFVdgZGQE5513Hr75zW9q5RUAfO9738M111yjo3Fddtll+OIXv7iX7tKPSSmQ+JBnGTCtDj5hoxEP14oAI5zM4IYmNRUg5OIeUopymCQ2C6h2Zk8/ACKz6TeFEnvhNRxjYcfwF56Pb3M8+fwPkLtJU07toNTjmJ6fd8LXputgmYeUwyy1oXmO/D7Npg+UANPX3QW/qzgQVSPEtdjeBDDh3VgI5nywWXYMjuXn4rGyHfL34fLtaBvtwML4QCn8gOOBtluwuZwfUWvJ4OGgJAQDQ1SL5L1QChbF0iFeCSR6g2cIS0IYx7N1u5a8eshaQNQYuBYl36bRtn5krSxpokjTl8BqXx1H9nmYe8lUVG8OQmR9RvwWSPPddAfTdgK3/cTyhLLUwqZOccYAI40IDSg45zoPSVgelU7rxvOKazGiaqR/08BW+Unrja0sIITo+ad+W8IITa8VQjuCQBjCq6qDBKSuoKDKmv2x/jpBRrhI/enU7/Rcum77BCizbncNc+tyYfpMuPA5XNdDI+Go1fet7vkm/Ph0WYLcXFZugJKWFBvjgGt5ceGzLBURuApMGPaBieTss8+u+34RQnD99dfXjdDV1taGm266CTfdlJ+UtKurC9/97ndb6tueRuFDUqAAAAiOGc//Yq81t5j7zaL3VX6BLcFqcHA81P6busJImbXjkL6T9lQXCxQoUKBAgZcsTKXceP4r0BxeMhaSZiEMTVAmVC+ymikVA18eS7WAvtCOqc8IlZQtFT2HBoY2V14Xc+adyKrdmGVpMwGlYHC0Yh5B2839kTkPoikKPNHu+iwBZpQZIrKaPi5ELg2tkQbAhFtS8b3TvtZ/6U1LTh46n/0J2rqfBXCWrwKwmFmhd7WW3LBAkIBalCIVXcuiyyRWiTZ0oCtcgN3hVqspTjj+2P4zoD23qxqH95yBMm8HgqQ/UlGuw7+60bok/SrVDLvZ39N+p3S4LJ3DZ12waRpyjLJRpdT16TE7ypbOCM+dbOJKS+XUY16buQdCtHVDvQ+UyOcjrDJCddytwPjhkh99bWWtJaalJDe8r5NXyFxfOOcgjIDTdMzNOVhpl1G1qsMywRaPOSpTKjoMMCDpXKbVREZ9M8aNy/XCdr5MsrDbrk9p1C0OCMItOxOlFL7XizOh51wjBIR65pseIrte9R6a86sJC+xYkdJg/eHCzfpti062T/XoT2ou1bNQ5x1v1nJh9j9bB9dWr4CmPldWf9CYVuajT7VqSfKNtW3R8lkVC9pWgQIvVhQCiQElSPjoID5qgHmdeX2az0SeV+ujmQAxMHKImM7siuIkKV72Zto0m9OkPZPSoIUV7v8gmvlOXFO4DqMr7OOBKuuhQim2BiFpCE7fmJr1umPlUgp8yRvVV4kmCd18fifmOFFK9YfM55+S+VCO9mL2QzIUb1V0OHfAAQG0T21HbbSW0k/U/Sk/EQGImKt9s2xHOzLb46HGYGH14IxA0izmDR2AeYP7a1qN2QhNNpeMCStELITQzsIK6fjlh3i1qVV+3w9XQGjEH4cxb+UmO0vLakS3y6MAme0Tkm5QBCF+HxPfPDR/ktSR3Uy26G5AsxtS5QQeWufkpinfD0P1iTMu6XeJ8oFSCh6nIW9lXhKKOMkxIoTQdCpVrTs8SmmSEYCY0HQrKQEIPVKCAySon4TSfwtCC4aAvf4omDRNQgjCIGh5U6kpWk67eZv6dK1oPiRtPZhrUDMCwXjzkPjK5AkjbjhelXsEQCaIiuugrp329fX1+9Con3lEyXqKIvV8fDKtOx/HEj65QIF6mAgLRyEgN49JK5CohdRdBE3rxVh5sGYdbqZ2IBE4CAVDKlyEQaAtIso64saxb7U/bnQrM56/Ou86/irrjErMSIntCFwvW289NNR2JX0xEy76LEn2JjfdVAJSg0oTLapr9TA3BeZHN6+v5iIx589fQDDaCyGALbXDrbIyD4lAbbQm+2z4XMhoWMn9mb4yhr+Gu0kx/UkWjRyC59ofQExruX31IeRlHLbrNF2XSHxFdDtmpm5j0825AI8iawzUJpQmmRviiOl6OWNWNneVsNBnNbTfAU90OE8md8aSjTTnGV8BaxHXQqBnw+WxLJj35/YTxBE2knp9mmrzurQd5cCenfPmBsnbdh1kzht18CTbuqACQSlEWJLPKiyHCEthOqeEkLlyYmZldxc8XQeC0FYeWPfJ03GW8yIt06qQYJZXl/lCYDbU/juKGCIEBLGfs4DQm2f3nhpBDZPPR8QUVnx1qvU0716adU73baRbFWy8wgixLeFKaDHzX9WDgIB22hdmvq00H5SCTxDIe9bu8bykk7KvjcclTyFQRNwqMF4Q41s6njoKNIfCh6TASxqVXX/BjGd/CADoYwswzLus8zN6V+6xtttEB07svxhUBI0LG1jafyQqfMoe6lWBAgUKFChQoMDexaS1kLjIM6e7dKxG0Jo5HZkrq+VX7YUJlYkQFeZX/i6FIQJCvZoqs/5mtKqcc6gYOi4FIaWHGJrKRJNIDA2k6YNBSGOfDLOf9eDel0krMClbvj4rcMkxkfeXRChy+2f+W1lHfFStjCZOCMz747+BJNr7LbUjrP6Xq32YMrIDo5WZiKqRpMwoa1TMrUzn3v47bj6CicSykh6bw5fgxJ5L8OeZvwb35BiZPbIEu9o36t8BL2G/3qOktUNZMhLriIruxTnXYYkJ17w6IPEVAKTWnUVpB3kk5yaLGHjSQWUtUTk0OOfaqqHGNkvR4ra1xhgX3Tceg7FYU7Qkb92OUuVauJqJFmS2I31VAEoD41ziC0Ky15gWHEKIDtVMQBJKl3nPjaJ0+d5r16dGcfXVcTNssJzrYSkACLEoWQAcH5H0GQqRrgm0nq5J2KM5FkqBSZHS9TTQBCrLkV56kjDe6p2KObPKAtIi4uabyEOaRqU5axQTPm29v6xCQEku5akVqHqDZE2pR+NK+5ZvHQBghb12rSOaeuVSb8f47F1rpi/aVZ7FM88a6aMXm9EUgdTy3Syts7CSFBgPCsrW3sVLRiAZCxQdwHfcoh65/HNim/IDSlEKApSSML8lShEGgSUEqA16mkwxu/D7wIWQ4UCNvpn/Nl+GgFKdo4IYGy7F3VZ98e0rxrJBdPnL6r5U33yJH02aGRdyQ0KMjzf1CHFmf01hpBGmP/8LTNn+mP69uXakdX5G30oQAKxUQltHBSzmegM4OjiCOPI4uTuCQeb5GUKKOjdzdCGOZRfi0dm3ZRIfmsIIAMwfOAC0FoI5uUCE4S/CGQeE9FNQ9B5KKeI41okdCSGIeA1xIpQI7e/CURuNkv4z6y9jsbMZp/q8RaExNvhZJPQyzrXgY9KgVN9kySwlxRZcsn4NYfKOMcZ0v2wqR+qgrq53c6coSpkct6ApXxYbHMqvylfWpK2lzu5uskUilQUB1Rt9FjEdrhmQz1xQYbwTSRuc63DhLo1JzhEKLaf5qDZOIkbfPeSNiX/jmbTN7JDErt8cJQEY5xmfCiu0etJ/kogfckNvt5fd3EMnSrX7VR/1aHzqt18ob75ON7+UqrcZuleeMJKHRj4uktKYraMRXS9PODH9En3icdbnKp8qqY853516921St4AiDHCB1lEIJHsXk14gcZ2160Ftkrmx6XEz9vpyk6h/Ki5wQAmESJ03AyIFkJKRCNHndGkKN+6G3c32bloOdB3uYp18XwJzs5fwntUmPkiEI51oENkXMG+D7+Mw5718WnOn7o8AAQ3AjKzkXNhJ0AgkX5zoqC9p1mq3XrevjRYBOrQDc+//tP7NRIgN0XFWmRm9Mltq90GHIKrFEFxg2sypsnzMUDPyO+j5YPQ/T6DkcersrqwcXfEiHBO/Ek/Mv8ubjV1hTv+yVNDRvh3C8vVIN732tYQQQPuMcBBKofIkKT+dWnUUUZRq5MOwZNxD9hn7EyFmj5kRtDiLLauIacUAkAls4BNwcjnzNPWRMLOj2+XsOnwa39Siw6RQIpyLYT9z8xzRfk6+bVgqkPg2775NrxI4wlIIGlKrr5zzVCAxomBBC/VcRrnS56RVQg8nybbrOp7nIfPcjdwl7j3I/ilLZ1K541OiMrRzAQTW2EAnWNVRtQwLtQrw4fqVmUuFVZ9jSW4F5vroE0QaWTH0sRyFDkHr/jrqOu9xZz0MDCuv22eaWCTMCIbmtWbfcxVSxmFzJvgsQD5BRL93sL87vuel+qn7IrI+o4WTe4ECLx5MSoGk2WR4Ctam37F+mGbjete67QfGxzYMAoSGdp/mOI67WlplMQBgfYBNNBXqMdnvUZFqhpWQomgHeTSEvA2+MCwXvv7nQe+Dkg+v3B8rTal9z2rzQQxzfSMLiNf51NmoQAgs+NO/Iaz26TJrRk/CKJtmXdfV8xxqbW149rhTMdQ7JK0KiRBSG5WO6MoaYm5qM3+5e1zWz+LUsgAOdPUvxtHiPDy54LdeoSSMK5jePzfZzNtJD4UpvDKRsc5Iy00aBlhvgJPwNSbFx7RG1Gqj0JtbJ+meEDzj6O7/K2wrixZskvno0DBcumK+YJEV6PWYGPfgusqZ1g/3nl2tt9GY9VMYCgGlKFD1SWphgAw3TLYOZaUhxFwTspHqlBN4WA71OXPtYIxpWqg5Bu7zICTIJL7UMpSQoz5m6pGa2yTZDfo234GjuKjjVC0EAJJVUphCpE8RYlqKY85RFgJcpIKJu4HOi7BVbw3zWY59Fg5fXU1TDpuwdCi489Rdt12llzpWMm6Ecf/19cCFPXZWGGGDSlXvfXXpWXkCed79qX5k2naG2Xz7C/pWgVZRWEj2Lgqn9gIvOUxfcxumr7vLOvYkrrR+z+hdiSkjO/HcK85FbcrecyCfM7QUS3uO8p6bPbBffd+AAgUKFChQoMDEQDJnx/Vfi/rxlzQmpYUESHnDPo2X0pQz55zLVx4LpPWBWH4koaZFqVC7sqxpieH6P3lMUsdMClfWGqIoXXl0NNf5OyD+8KqB0VdtMbE0a9m6uTDi03s0lrJMdnwt60bCN1bXBFTWqywv+t70eZprXTJRj3JW7luH+ff9u3W+OzgE2/oWW8cWbvkTBhYuwsrDjgFqsUyMyBhqozIJHYvl2LModfLWWmfNJcjSptR9mf92fy/qPhzrup7IXLdw16HgyopkOtQr60BirWGMaT8S0yKikjsC0rJjUUOMYU19EgJEURVxrHxKJD0oDEtJO3FiiWGee+K6jPlbObI34qSbtC8fNcZ3jf2XA/rdURYWYlkleJJ81AzZrP25kmNhWMrkLlHvh6J2EhAQw7JIaQCfT4yvv2bCRJeKJbgAgtQPKFOGcTBCQBLLAKFE+4iZbZvWEZcuJhN62jQheb2ptRYAqLSCqHo4sRIsutY/VZ/ZH229SeYpCR3LJeSaERCSsZIKnfRI/lGafQKOMLEcCWNdNy0Xos5cc5GnkXfDz6q+NvpWNGsZaRV6zPIosh7riOmQrxCa4aHrhNWuB9dSoerK+B3mWExMypg1v5HN0VJomwsUmLyYtAKJD42c+sxyCj7Tfh5liJJ0YxLQlBZFk9wftsk6y2EXyFJOTAjjQyuEABPc8sHI9l1RodJNII1ltC/uXKOc2tVHK0NzMiB9ZYw+kpTzr2gSQtiOjNzzMdECivFhIhD6t4rAFasPFk0jk+XFrs8DIQSlvnVY+uu3IBztsc49MuOfgc3p7zAawpxdj+Gxd/xtyr0XknevKSJcRqlSTu4Wl79Bn6zNe0KjUpdwIRDGZe91U4ZngINripYCdyhhaTuG7wbzROIy/U7C9LnVEwAYYzpRnxDM2szLY4pOllC0EmEGxgaKiPobFjObu328lc2db7Oo6GOqKzZvHcgGIuCcJYG5zI2RszlyaI3Ek3E8FVAofFG40rrNTb+8B6oCTmjn9jjtiHGNSCKvmZtRSqm1ac3eM9G0LZM+CJrSsQBIJ3j1ziW5TCDSLazgAqCpMMsZl+Nm+ol4nqfrBK2FD2IrJZSSwvy3O2YqoEHobnSdMW6UPd2E13/Cub4epXc8KQjcPpnj1GiNISQbZcv8q2DOYx/Nyiznfq/M+nx5XBpFwsrWITICiFpd3MhduQEXDKHK8rdE8uYVDu4FWgEl43uJVR0FmsJLSiDJg8lD9oESGSJS/lvGdzEXeK1kphRBQO0EhLpMVhhR7TLOk/8czR5SDbeKwJVG4Up/uxpe10FVW2biGAElqMbUsNYQS/unnd7rWCJMC0Z6T8nmSWlRCQEX6QcucLVfHgFFlTGzxUvHdlkupBSESo1r0OCD7KLUtx5Lf/0WlIZ3WMd79luOdY/ZviMLtj2I3lNOwtaZc0EMx3VteUCinTYsDnnCbrNaff2cczjpXX1L7AR4xi5IbVz1PNbWEWE7ujtJPOV1ytk8bSsN7Sty+uNaP2zrCOextqoAkEKIq+ms47iuLBRZAcsODewTxN3wuuY8TvuaWkyM2j3HAMbyn6F2FA5CAFSPFaV2pnDTKmNeK4+nviPmHNJKCpEKn4QmwTDUuxt43lMhhRKVAJEEpKFVUXCRsXa4PkUsZhAqIEIYSEf5pD0A4IyBiPQaFbLYWo8I0YKLvEhYVhem1gTOU8UD7EAXWV+Q7OY862uQFWAy1ib4hRL9TjXYVOfBF1pY9rvuZV7UC9iRZxVOFUuNBYNGdeZd637bmrGWtFpvHnzt5ZeVSjJCSCGYFGgKhQ/J3kVBSC8w6SGFkTejNLTdOj486wj8cejdiCI7ytO8nkew+XWX780uNgQRxaJWoECBAgUKFJiceElZSPIsIdzQDLrRQ1xNLqDM4fLfAaUpNYtImpaPouX2w7QEAFkqAE+0yIq6QBMalepLxKR23oycpOrRzTphNWNCUIsZAhKjauQakDQupn8HxliZpv9mQiebEZPc+P8mciVhQixKhhACXFMKEm0YqR/5zESpbwP2+/VbvMLI76b8Fzb8ecQ63tm3Gr1/dQ6Gwgqiao+O3ONqq13qgGslMJHRQBqd5x7rxlDFppQBAImoTmTos0pY1hCPn4lLOTNqBgArApymUDj+Hj4rkCxjWlo4WBxlI2kRRX3jkkJkUUCyFC37/kwrjfAcA9IZ5VrvzPC7HKZviryvxhPJtRK5WjNp8bE1uoSkUbfs8iQ5l/XVkjQ3+TuqRkCiJWaaskUlLSpw3h4r3LMMq1vXR8e0Uqg+wZ7TbkQ1wAjXa5RVfksAEIRIE0qWaZrINDCsyVYdsOaBbINKC7TuS30rRD0/jmask25dedStVuiCvrLNaklNS4JLS61nCXL7bVpG3HrdcvXGT51X/zP7lYdWrBZmO/XrzH82ProYAB11y7bgpFaSAgUaobCQ7F1MWoFkLHHmM0IBCBQzwd14WhlxjfwiYRAk2cSz/cnjwvs2s8rMrYQdDntB1tm5nXrlByTps5D/p7ZTEeQH3vfxcrm7oeHkrihqPoqWO34uTAf+Zl9My/cE9gdZjTsljR9wqW8DFt/8JpSGtlnHR2cfjntmfB7r/zhgXyA45nSsw+aXn4PhASmoRFVJX9JZzfU9OGFmmbBPq1KmsOg8f5P7r8dSCGyc/1TmXjp6uxDVJA2KUGIlyANSwcasj3NuUGqy4WBtpPQiN1kfpaH+zXnNI5SkTu1uMkUgSf6nJ2UijDhCjN03H03M7W8qcPiuEYIjCELYzuUyG3oqaAkAMvM60f5edvhdn8CpPlI6zC+RVEJTqJNtm5a3rAhOaZDQvdIxjGMZThoxIHgFYblk+ZUFNMg+O5Ny6b5iwnFidzZ/qWChxgNA4POBcahscfYZCSG0A34YhtJ/hJrUNc/HPSd+bDoXCEDq0Wn33MfeRwlsVA7IhrR10Uzi2cx5R9jNq78Z/7Vm/C+MgxAQCZ3YXv9V+746WxFKTH9F19elleeb16b7LpuJGotQwAXqoRBI9i4mrUACNKfVMgWFZqA3I8bCafpj+Caf6zOS93FVkbZk37ObCz93GECDj5kJIYCYsXThj+wNF+McpTC0BBLffY2Vd5znXJkHU5ul+qF8EICcjyiAUv9GLL75zV5h5JGXfQlrfuJYIQTHgVt/hW1/exEG+4YxOjSK6nBV5x2Jo1j2w930x+mm2qc5N/+a1yUn9Hl1iHOGnpmGh70ahyjIWEC8AkhSr7KGZHwSciV1W6CQIJaG2vTPSP/aH3tKAyt6HWMMhHAIjx9D1l9CbXKFFSRA9isv4V7avhwD24pUb5qZdapIXLIuqvtCSGApHSy/EKISFpaTZ58EhkiEEf8cZ0lbga5HXkPBWGQlkKSU2vMF9lyilFo+IoSQjL+Oe40WTFSUKmoqGpLrGAcJbRqjW5+aS8paE6hkr4EpANofdGUdsdeO1AfPvzGFPiavte9J+aJxIUDq5ATxoZWNQnPfkhyri6dNK0hCE1a6ZqwIWT8S43rDj8PdoOvrHTaAnCLyWZv+iyaU5SKvTl/7Pn8X97va7D02gnvfvnejEEoKFHhhoPAhKTDpUOrfiMW/ehNKg1ut46OzD8fK0/8HT//MdmyH4Dh01Q/Rd/mJ4JW2vdjTLAThoHxS6wkKFChQoECBFzxoIiSP978CzWFS7nxsLY+HDmXQolzNl20OR+bfTCRmaq3Ng/ZxULzwZk3Vbtu+MI9uJCJNWaIyqo+gqX3Ek9w7125uWkRixlFFpI/HnCGkKgww1RQ0V6tn/vaZ2PMiv7jIo4cojZZpjVJRzlzqXHIBpj3/C8z50w0Iav1WnaOzD8fakz+LJ/7fM4jD+da5g1f9FLWzlmHn1JlA3xBGB0dQHakirsVWNnTGmNYIK+uI6fvh5oBQ15kWEdMaos6r+uQ/KBavOxrrD3rEqieoVmyNvlEvZ0xTstKhcHKVZGC3yy0/BGUJ4RYdizEGzmMdhYtzps+7tBxFZ1J0LGb44vi0lHbeEKGvVf1ILR72/CJOCnJ1bUq9SulYPlqX2yfZpGklkrQulXvFzBtiwu2H9FdJKVwKcRwhjmNQGlrPJgiDZDxrul1CaCbamO9d0e+eh2olOEBoVgfvWkqscKnKv0w7IEgrjJ6i2lLHNR00CAIZAS+JBCcCGb6XGPW4vitCqChoRB3Q1o5ArwHpaSCNLqj7b671RgTCej4HexLCsHJr3zugblTARnQt1woBNGcpcNlw7iwwvycAdJh10/rko3n6KGruWLufHRW90df/Ziwj7jVFJNUCewME46dcFVO1eUxKgcSHRnQpQC6ajXwTXF+KgFBwIjcwKmR1IzqRr04ibJN1rOk3af9NkzklBDQILF8O4em7tWHxvFiSH2w4sMYxGKdggaxL5VNx6Uiu4OE6UQLICCzCU4c5nm4d3DHxayqHsDnxABAMbce8ez6Kjg13Z+5xdNZhWL/wWqz61F3om3umdW7OzsfQtjTCM0cdi+HeIVl+aBRRIoyYYX5V7g4A4LHMx8HjdKNthoPWfbM+6EhD98KmDJn3M2vrUnARY9OBT0FQjo7eWZjSN1NvBN1cNZwJq6+KSmXToLLUHXOzoTbwUuhIcogkiQ85VwIIT0L9prQin8Cj6gKAMJTllECirkt6lLlW9Y0QYt2ne8+aukfsuZPdtNljYMJ03E6fEbOeIeep8J/2jSYBJ9JrpeCjxjAG58QYh1T44FykOWCEK2ykSSeDIEQQhok/Sjqe5pxRx30fTOu5cAJChWrEOxbmXACHTccK1fuflpd+TOl8juMYNEyFFpbQQgXhmsJHCAGcR8GRPgMKCg6eCD9CdUULIYBUkJiKJLWBNjfsMecoId+XY6wbjGaCevjK1xVGGj27HCghup4vh1VPTh+YEJafnxtGvl77JrRgaijkLD9LY+1vxj8k7xnlfV9y+2k446s8K+a4AUV+kgIFXih4yQgkCsKwOrj+I3Kz23qdeuFN/keTBS9dMO0PRRrzJ4XJo1W/Td6u0rypvoeB/PibTO+8iDOqTjPpYR7PXH3sU+GHghNufVSVhUjXkWwICCFgOd9AmmjfzI+UqiNjGdKO67YzvCorjA8KIQRTV92COfd8LGMVAYDh6S/Dxp3nYOv//RIbjniHda5tZBemHzqAv5z8Wgz1DaM6PAoAqFUjnfRQbbgYk5tvM7GgkJ2T/UjGwdYoJvdjCAqu7wec5yWSOTlr8/6YtmseotIoKv3TE58Qox5joF1riGnZcP0/8qDkBc6ZlZld+jWkyR/NZIh5Gyd3k23muZHjCABZzWtqSZCChAktuJrXOMoBcyyVksDeSBMgcWLP9tPeyNmbJ/dc3jXp3DAFbSGEdl6nVPl8qGdkOKyHgRYCKDUzyqdCsdmuoH5rk/c3V+U44Giq3XkJIey1idrRsSCkj5J5jzxmYBGz/X6ozLCojUckWb2MsRUsFXw451ooMftHCQGts0lnnCPi3PqY+TbMzWjhmxE68qzqXuG8QZuuFRiA5YNl9stMDpgK5CRz3u1XIyhndff7kSfQmXPFO/8IyQgLjRRa5n2ZyLOEqO+YW5fb70bf84JOU6AeJoJyVcyx5jFpBRLTdO77bSLV0NlCgiu8qGPmNUA64WSSQarrsvqDdPOqEgaG5sdbLcqBP8oP49xKECZPZu/FpXnJYraFQTmqm+fS66Eji5n9EIblx+eo6R7L9MuJjiU/akQLJqoe+8OctUhpShAAEo9i1h8/iel/+WGmPSGA7ewV6P75INZO5VjvCCOExygdMYh1h52Cod4hjAyOoDoi6TKxYR1RmdhVeOXczQiQJB5EhoZlbuDNMM16I5jjaB4OtyEQlbSspo/BstYYd52UTS0ZeUKD++FXVcVxBMakQKIsJK5FxCfkNKs8VhYG04lc1eXeTupYbmyGzAbN9xvc3qBxtWGxnaxNawuEfFPMOWZq52URKWg0p7VW/aXWeMjnkGj4gxDyFadJX5TgVM4IMQrKCsfUOmPQBt2/Sgts98sQsAQBdYQSd63hTABEWNQtwYV+T9MxsYVJxhgCliZtBJK5nwy3dr43BBQQogUtGtCMUEIpTSy4SR2CWu0q5QlhzJknrSfjawa+eZA3N9R6627mXWuFsq6a1/jgWkMyaHHjoxRyZtj7et9JH1whwvfv8WzI3JC+9Z6p+R03DrZs2SpQQIGQll8rbx0FmsOkFUgKTG6Uetdi7u3XoNL9XObccG02Nq14GYZW7cYzh70VfTMOypRpPxoYXrpwb3S1QIECBQoUKFCgQB1MSoGEW9rJfO1IM1pPVZ9Pc6ngcmMzZmd51OAUIyM2a42iaicJo6moU4oGlqehN/vmaoRc87hphsxSxey6UqtOat1oVvNoas9STrhpWVJUkXTcmNHfPGfHqStvxqzf/ytoNGQd5zHB5i0vx+BDu9A9vQ1/OeGfEZWmZq4PlwEji2IM9wwDgLSODEsndgBgMYPgHFEt0vlHsr4GjhM5595cH5YFRAgrX4iiWdV7prrNhCYDpNYR0x/F9ntI6zXD4PrqTq9XljnTaV35ObTIKbcsF8J7jwBxXgGq23X76tO6iqQdpVt230+iQwfLutU5afWJkzLUspKoMrZFLueGSdahPg8+C19qyUkogYkVRFslCAFJkiASM5AC4zpBoRACPGagZoheNd+SrrnWN7nOSBsEAE2bdC2RYSlEWJafB5H4T5l9S5cHw2qCND8JDXgmFHZKH1OdsQPNCi5AgoSKlDJGM2Nprm+McwRU+hvFOdQp3/vUqh9J3reinvbdds6357Tp19BsfWYZ6qnXbK/+9dDXWj6IdawjbrlmkJfQ0YXvO6GQUtIc/5EWrC91KV1GH4DCl6SADUXDH28dBZrDpBRIGsH8RpsLLXcWXIH0dx63FrA3TnoTTWw/BwBWBnIXQghwKpMrKlBKEagNS7LJ5E7f3MluR+VS/TP6iqyDoY8m0MwH2/wo5H1QMh9icxw9NC7519j4kNS5GdEoZv7hU5j29A/sNhjQs74T21fOx24xA1sOuRQ75h7n6bBAeCRQnT2Ekd3DqA5XAQDV0RpYxBBHyYaYJz4ZLKVFKSqP5Q/CDfpV4qxsCSSJj4jehyV+JzaFS1jO1YTILZq713WzrEsn+9h4FmnujHS8DY6/J9u4CZ74GCialuwfhxQc1JzMOrHr3x4hRNXhCmlGL3RfCBG6D4JzCHAd+YuSIBEA8udkdsMnqUJyw63uUQqaJLvLNd55WC+M7D+B4bab4cNn+9V8Mi31zOK4hjAsW8kVVT9Mp3bzXpOu2/ONKtpVGh3OvCUmBEQgoLzPaJisWUb+EB7zRPBRSVlh1xXIMSWUahqhgsrKzjlHXIsRBFQLTL4xEQJWBvi0onRuBJTa0aCEAFP0OEEQMy5vJ1k3YsbAuIC+JZEj5Dt9cgVH95genxY35NnrDcWPjlqSnnf9Q/L6Vr9tf7tmXW4ULReNlBh5IJ75n+c/4rbVCnwCTzP1KOUekPW9cQUToBBOXsoofEj2LiatQOIKF+rfbhhdVyvkLmguvT/jPEiIFUXG3JwH7kJXZ2IyzlEyeN3aqV1t+pNIP777yoNPE+haHVIhKvnd5Gaq/obMXy4PLk/Y/EgzkW7g5/7ib9Cx68n0Ogb0rZ2CzasWY9O0U7HlkNMx0j7H30gbR+3QIVSnMYz2jqI2WkNUTXxGIum8rqNYMRUFKb1cOB9v0yICGFYJw1FdbRZNIcaXPV07yEOGf5XOvvb4ufNYtal+EyPmc97mpR7/vZ7AYO2WfDDeKzlG3KrP1/e8fviOMRFnhQDIDTvRoXU9dYKDM1jPjAaB9VuVs+o13tVmN0rKN8bsu38DrsYj2fjQNJliWApBwzSssAojbgrFsg5ZlxIafM8u1SwrB3vdATuyVeLP5lpSOGNgiYBOKJE+UnreSmsJhTnnpCWFJH0sORnmzTExLSXSP0U7maTjpvoTOAJAIrynWcON4AVQ80UkyV/l5y0gybuXXOHbgLrYE4KIWbeKSZEqdczFpn7fVF9cxVLgeQnc75el1MpRtPmUDhkFhtq4O5aKwFDK5TEGmg3JbAsxDYs3XZ8w2jeTEct2DItfsZEsUGCvYtIKJAUmDzpW3wpgDsq7nwcgrQW9a6Zg1fqjsG7OBdh59NEQNH8q0wUC/LAaRI3llilQoECBAgUKFFBwFWFjraNAc5icAolH01PPCuIed60oJnyhFS36U5JE0AUX9c3Uqg5lJWHErptyDk5SxrUbsjjvfvJM5248d9P87bOiuIkRZR31X7RWaWCupQTxCOb+8ZOY8vzNwDFfAQBEQxSb75+J5ysXYOURV9StD4GAOCjCyOxh1PpTi0h1RFK0VG4MZR2xQvwyblGptL+H1vqmVhH5W3gjcXGD9iU41xGy1DV6bAy/gEbUEaVhTy0lPkGrfmQoec5I7MhT7bt9XZrHI7USGf1PrCMuRSsvNHBKK8taKo2btmg22pJp5W3hVohZfdwT682ktqlkhend8cxvgtTqkNJnbK2yPJZpqiHSa6Vvjhnq2Pd+cM5Bku6LQCYSFKb1gHNQFdI3SIw7SOcTDRI/GeuRGmPPk3lJHQsbJ4gSnyoaUARBag8hhICCQhCi6Vacc0Q1hlIlKVW2aWdm3daclvF41c1CEAJBUr8yPY/Ue+ho5IVIwxYztTYm4dIV3ZUGNuVrvEkTx0plUte6VssMnayFCGF5vhQ+y4g8nu8z0mi98FppAYQ0De1tWkfqjc9YnkGjMcnrv+87pKlZxI7C5fPPoZfcVNC2XqIoBJK9i8kpkNSB6z/STFl3oXPpSoqapZJC+RZOX8JF5UOhTMjm1igABTHyDPBk4dQJ2owwwibskL/JR6KOIOEzqzdKImaauwHpd5pnnq9Xjw9qb1LZ8RTm//4jqPSsRETbAACD2yrY+ccZWDfnXKw8+PW5dYgpDLU5I4hnVxGxGuKeGHEUawd1xljiuG5sMnmaTZzHqdO4MDbWLOaZTXJK/5EO66ajOaD8RpTjst+JXV0PSIqNb9xMmo9KNGgmLDTLpv3jmc1T2rbKoC7rUHkyzHbcsMGZZH6GMGIKKbaglhVA7H7Aul7fNyjgoaGl7bh1cFAaZGkrBq0LSGhazcxFi9Yi82lMLCgIoZrmFZaUA3k6D0QoZJhbRecTAELjWaoNvLNOCZFuaGlAc/LdpJt3+Q97PE2/FeVwr48E1BAS0zI8ZqiNSr+soBRI+qEA1Drk5mfR89VwctfUx8B4toSDJw4hYRAkGcWTOpJNtdxIJtUl8zL1E7BDmasyssnmNwtm5nXdN4/yIJOpXWT9FLI0Jj0EsoxHKHHX6GbWVFcpZ64/XlpzXrJSS6BL/bACQpMw8tTqV6O+NTvuzVC1mhVElFBBL7nJHkuzTIM9QYECBfYcJqVAYi68Fl/Ws9haGiMn54gPPp8LpZ8mqOOD4WqsYHxAkQo05seCCAH9xacURNjc12b57Xn3odBYQPHXYWrJ3O1aK1oBy1rDauh6+IvoevzrIIkjhdqrbv5TF7bMPQ0rD3qdpxaOaHYN1ZlDqLWNSgf1ISCOYkvAUP02LSJ6E62ysidlVT4S8359G5DkZFqPcY2KOqTqFTxHINEbbe5YAtKs5eam3MySnuaysDc97l/5n5nk0Od3krWIWJG6nM2LK/ikjv22IOLTrpr3nieo1YNrGZLvuz0WRFDt1+DCepYqEhe4bTVJHOPd8TTbkP+226gnmJsbNl+SRv3bGRPOOQgnEFT1xZ6TQsg5HRCaSaKo/zovs9ocu+PPOUcA2xldnSYizTZvVKSjgQHSB4UGFEIQQAnphNSX65SsSEgqoCtLmLEuMi70qksTq7Fc31PBh3GBIBFoBaXS3131fxway2YtCo3QqpUl3/fPf73btzwH9kbCiBvdCpCJFMNkrMMgSBRx9jyrp8RrBRmruXVubJYufst7Lad112JiHi/w0kbh1L53MSkFkgIvTlR2/QXzf/shVHpW6WPREMXGh2cBxwKbF56BVUtfk7mOLRnF6NwhIBRgtRgoXEUKFChQoECBAuNAQdnau5iUAkkrXFjA1gw1k8PEpGW5PiTNUJYUpUK1SxOtoNm2yhqvKSicQ5DUFyWTtb0OfGZon7bNvD99zsobsuderHBgMxbf/FYE1T59jEUE638/G8OsAwCw+sBXA7F9XW2/IQx39SMekSfiKJYRguLU2qGtElqLL7RPiCoDLsCUhSShaplaYE3HSOollCSafdkPZXWRf5P+M6YjEin46EmmtcN3Xh03rQ0ZywU8WlHLusOsa9wyqQ+J4fOirB9mPTkhfbP9t/tq30vWKtCqttlnrZIZ6tNs6QBAqYB2j1DzV1tEFf3RyOYOqrO+ywMcQtBM/9z3Xl1t/87CvE5R7wCAxkxH1QIk5cl9L9Mw0ilNUPqNuFYw6IhTwumPG03LZ7EQXEbiUnl5glKgj6mLiENBpaGkaKkQv9I3RUCQ1qIVyWnu0vnSvCScpHmZACRZ3AlMwisTHDFj2q8hFAJckAxtqx7qUXcazdV6+TfyqGK+NbeeFdsXUcvtW72cImbZvO+fVS9ShoHZfkDHtmFrZN3w+To2i7z+mFYRE753m9/y3kaxBQsUKDDBmJQCCaDoGzYdK8/RTyHPZwSo7yNhhj40F9m8D4KuwxR+FIVLU7IIiBA6MWKgw3smG8gmw/MKkU3O5d6HSUEDGgshEy3xcwF0PfJlSxgBgO1PdKKXL8LTx7wdMz3X1RYPYnBGH6LhCCxWSQ259A9JJQX9J5+iJTTdBUAijGSdOM3NnKaUaIf1NKRvJtmd8hVyJqBvQ2+2l4Ua92xo3ey1rnN5VsgxaWA+AUIJI9ygk/naMulffmGDZ67JlrE0AZ5791xrljNoF8ndJfeIdNPtUJxUEAoAmtYlhAARFAKpsOcXRgwhxvAFaQyqO+QKn4QQHfZX+5QY804KwdmxysxTIaDnihAAERlhzOoPhRU+GEiECWrPCT2PhUjzliT1lsohglJojKcpICVrJ6SwbgZwMEHMPpL0nTGd3NX9uqFruRD67WCMgwVc5ifB/9/evwdadlT1wuivquZce3d3Ok3enSYPorwfKvIGPyA8koAQOHoVEQMqR0FAPhHlHDgiOeCNqB8kHDzi4RwF9XBA7wVBLiASJQHCy4SEQIAQSHgkJOmQ9HPvvdaas6ruH1WjalTNmmut3d3pDrvnL2x6rTXnrNesWbPGGL8xBlBJHx6ZhRM/UIf05HvBz6Pk28HX0NJ62ieMlAKo8H/zz/Panr8TqQ+EvkApxuczolDLSoiQL2sR5/u7Q0NMVMNDUc6AAX2YRYtcTxkDFsOGFEj4Cyv/vXQsOICKrtACdP0puJ+IFGIhhlBpUifbtPCujFYTg6iJsl44USHve9cnppQk0cx5YfQJI4tk2S0dO5CHr977fWy7/h+T3+5cuS++se9huP4Rz4NdGuE47E+Or566F5MT9qOdtN5JPQoBfLNKt5pHu3LCSJag0NjEgT1H7hgcNltMMCHrSM4PT5znrQmO5En5iT9HuvHvROHpFWC6vh99L9xYRhQ+eBvps/H+KkmfO3XrTpb1PhSFqM5Gr/8+lPxk6HPf3EstRfyp83kv2AMQol5R5CpLPhaFyGjhGZGZX4jt/Buvc+flyQ6Jxx4TIxaEjwydYz5Du9Es0aYvp/exZIJGTISYBUnoawPrh5AysfBwXn7Sd0QLomtbT9StopDlS8jmoLHWSZ6+udpal7/In6ONQTVzEPoxa/xLlowcfUIFIUSnYus0bYK6SqNuPet53vqEkVmKuNLv+X3u27DNexeU8n/wOgVjDUhRFgAXwXqEDrKODBgAuCXjYOWJQR5ZHBtSICk5ss9yVOcgQYCuB+YvrLOsJ7PrYtYU+mD58VSgUFIGiwmJJbMWdYouE8ZgxmK+CDWr1xS+TqElgbU4+bMXBQd2AFjTx+Cy7z0ftz3op33b2EtUWozP2IvVzXuBxgsgLEEhCSOWvWQpgha3iHAnd9h042Rt15rR3/x+bbVL+pZaHIzRCW2KNOt8w6t1G65xL/9U+06CRrrhK1Ct+EauuFnmwgfX2ofBQ26JcX/RMR5w2d15ksGEApVp3ns3t+gKImWBhMp2EabA21roZyb2F9GhUzLLCX1PBRESQHy2cylDgkMARUGQvlZVDWtFOJ/+tdagbdqQ6Vx4KkxulbMiCsFW5kKx25jzcMgUtYv3VcguFczABOGCNpyxLWXrD5VF7U376zeU2iRZ4EkoCW0TIhGAJGVlpwHzY2CJIuYXNVr3WmNQAW4uMBoXp1taeGWO7M8Yf6Ao0aryZ65E5c2VQFzBVXqfrFdLOyuBbp9VpNdilaEvtP3B4GBDMXPkSoM+R3uOQKMchJEBA44YNqRAMuBHB8fe8CFs/e4nw3drgX/+wWtw23EP65681aK97woaMwbWDmMjBwwYMGDAgAFHFYT/72DLGLAYNqRAEjS5PQkO6XOJuhV8OYCirY20WX2Upr4Qgvk5OaLel3ck5i8JoYGJVuH7qGZolSiMcDR7d61FfZqueTzlRXxLZlMZgGr/7Tjliv938vtVP/wP+EFdEEYA2IevYbp/jHbauLC+cE7mlFcEAHMsZ1QF7y+SO633abH7Q/Nm3wtWlHkaue48NOCO5M6CkoYK5kn5Sv+Sv0iY10UNfX5NN1yvO26ixajg1pleo6PfDLNwWcT6hU1pObPmROkZzT9nFyRtFJzixO7BrLns5kcLKavkt7y9MtOuc9qVlF0H9JyWR4fqegTAnc8Tb5LFyniLRtu0ncSPuaXGD0F6b4PPRXnMhHBJDWXFtPeZxURKCSEBqVRyTpjv0s19qWJixNgHDyMAGIAncgzdobpdBwKLTsZ5GKwqxpfBrJfcEtloDWMtRkqFmeBCAxtoX7ALXTt/DSvRfBfRrs+it9K86F1nC5sVbi1ZL/rCEoewvwXrSN/7MLFrsbYoKRfaZC3KMDgQlN7B89bbAQPWiyHs7+HFxhRImH9FHjVrXuKjeQttid+7KPpM8IZtgJIkTUCgcOX0LYrCtQi4U7szjXcFsXlYLy1rFkXBNwYnf+oPoab7wk+3r56Ff2+enwyC1BPU918FUGEymWIynoZM64CPZNXqICxQ9KyEvqRTihYJI4u8q2wkWIfy+L+zIARFUouUrU753qek7G9Qpgz5nnbOIyoY3+imdfHz83HycyTLu9LtU7w5UqrQ3r5NAW3M6bpFBZO8rXmbnLN9Sn1LOOb8+nBOeUy01pFmVhCqOYXL9amBlCpGyAp0rahW4EKlUgpVVQMAqmoEF/EsPcdaAyFk3JDb0j2HS0DH54qxQOJ87vqe34++8SZhpPO8KhWEgnz+OYd3Vp//TRudXCN9NK7QJ+9AH/vs22XZM6ZkMi4h0zzLS6JEWk6IqGUjZas1GpVR4bhWKjrco5SYcPHNbL6O5wJEIrT2vCtyWlEIjEI+RAcojHTWBD5XCj4j+TlJeVkfYz/751OuAOj7bRHw6ygfSoj0xfx3cpoVRdNajzASlIj+2oG6NWDA4ce60w/fcsst+JVf+RWccMIJ2Lx5M37qp34KV111VfHcl7zkJRBC4JJLLkl+v/766/GEJzwBp512Gt74xjcmx+5zn/tACIHPf/7zye+/8zu/gyc/+ckLt9PYrgYISBdX/gKhPyVl8seP9QkjeZSt/Jr8hd8N+SiK1ybfIcKLgLeVX1v6K7VfCRlMkbOyuPehr1/8WCyvbIVZ3nktjvne5eH71GzCR3f9FxhZJ+cdd69vY+VUN02naxNM16Zopy2aaYNm2qCdtmgbHb+3LTQlQ/R/FH7XGjNTGHGO7WXHbWCBF9y6X7oxwZxJeO/xz21edec3Y5wgQ39t2yT+Kfl94JYR2qLHzOuZcJMFTOjOZcoy7usQAgISAhJSKEiRWgxIWKK/WeMb/9K2hT+6hz1BOW32ny84aNW7Qpn706aFNi2MaZNzS5Ym6g/dG7oHxtCfdi3xx5WqUNebALgNtlTSX9Ogbd1fmA/aJ+VstEvM2abWL5q7ZBmJiSgXE5SldPWD7psXtvK5EsJlF6yFUskw1fl9gY3tD/NZx3vGQ3DHceRz37pnVmeJMrN7YW0+VzIh2CdGbLVGq92z0hbmHWV4z60KffMTiMIDX1/550pJ1EqhVgojpVziwOydItl7hr+HZt2/WSF86S8fk+Q3H2VSZ+Pvxsr9lcaCUEmJKgh0s9e5wSoxYKOgby+33r8Bi2FdAsmuXbvwhCc8AXVd42Mf+xi+9rWv4S1veQvuda97dc794Ac/iC984QvYsWNH59jLX/5yXHDBBfjQhz6ED3/4w7jiiiuS48vLy/hP/+k/ra8nA36ksPXbHw2frQX++fbfxao6ITnn5NUvY++T7ne4mzZgwIABAwYMOMoxCCSHF+uibP3Jn/wJTj/9dLzrXe8Kv93nPvfpnHfLLbfgFa94BT7+8Y/jZ3/2ZzvHd+/ejYc//OH4iZ/4CezYsQN79uxJjr/kJS/BO97xDnz0ox/FM5/5zPU0EQCgrdP+UtIswjztf279yC0r+bmhvkI5wOywhn1mfH6toz04EH0r0K1EmkgxL6dUbxrwtB+8bX2f+/oQ651RgTU45tsf920FPnvnC/B98cjklK37v4fxz56O8eoE07UJsHkTpuMpmkmDZtIEnxGttePNZzSESO3xn611UYiAxL+E9yOnTdF1QMxVsgi69KVZ9KQ8nGymHUZX40hWhhiON7VwSKkY7aVMF1tUo162EhTIglFlniYWLJTnY7uyS3OKR5eOVkKSC4Qi4y2QziwvTwjBLEvS+U6w8TEAhE/IF8L12khFEoLNRd+KNJKa8L4jgNHaJe7MfEwczU6CIpi5MRaoR3WvRtr6ML/UnSTcb/bcBiqQkh2fETqHzwlKAAoAwngrioxlO58SA6PpNwVkVKiEquV+cWNpy/2hciVkzOEjBFQVfUhCZDw/fEJ1QyiT1YgiEmprvHWAcjqVHVXXq9kn60aliGYli+F6S9eFzzalPIZ28HGkvs9oXx/9itO08meerCI5fSxP3ii9Ncf2RFvjbeORxvrepaVxmNWv2K74XsnHKGmLp1vJn337utfsgao1YMCRw7oEkn/6p3/Cueeei1/4hV/A5Zdfjnvf+9542cteht/4jd8I5xhjcMEFF+D3f//38ZCHPKRYzhvf+EY8/elPx9raGp71rGfh3HPPTY7f5z73wUtf+lK89rWvxXnnnddx7pwHbQymbQtto4N6JVVxAcsz4HY28IXNS1+W85ymsogQ0ndcoutbwn1KXNttRzCZxdeVrpK5fjSd6xbsxyKhIAUElm//MuqV22At8Lm9L8A17f8rOadqVnDsA3bh1k0nY7JnBZPVCXDCJjRjJ4w00yZsmDi9hL7ze8bpWTwxYv4SDtey60zLQof6UMH8XneoMr3jOmtzntYbKTh92drpHM02wGk/8mzsdE0JPFxtt119GdWpHeU8J+uhEKX1pQIhOyF+pvFfcAonfiXo57hzp3WpFBNoDYxp43MoJayVMNZAZOMc74+GlCpslHlfJpMxmsbRtYSQwSnczSeTCFmOGlWiRKZ1Bj8nupVeUKH28ja4dUkm1wOAkAi5V4JArmO5xphEkBDCCShhXrWejsayuQMxpwngBBFhDKj6Yjhh464hIYbmuPIJI/N5LCGhodEKAYg4BEDcjLfaoGlb1CEgiCr6kcxDvvbTb9WMcMIl4Rdga6pfjztKhzkCeb7+0DXJs9qz7pBgVnJ0z5NGOoqvmCmQ9L1PcoXPPKw39K+xs4O6mI/8dlEoEaLrdzKQzAaUMDi1H16sSyC58cYb8Y53vAO/+7u/i9e97nX44he/iFe+8pVYWlrCC1/4QgDOilJVFV75ylf2lvPMZz4Td9xxB/bu3YuTTjqpeM4f/MEf4F3vehfe85734IILLlhPM6GbBpOmgdY6JvuSGku180+gBZk0StyXxLINe6Jxys4hCCFYlvBuwrs+9C3SnU1xtlkrvaj4YjrL0b13wzfrGri+dzSuhXPnJYikEo756vswFcv44uov4drmfIgqbcup+krc+ej/C83uFZjG+YgA7r4a3frNqH/ZWesFLdbeZAPqjllrIRRt2C1rTewTDYk1XvsmAXKUNcK6hNfhfJ9QL1zjNkQuwpHXnENASQXaQxljoXXc/Gpt/KYUiLk9lLcQ0OaQ+hEFAa2NDz7UFSZc2/iG02upaTNR2NwDwMhnBq9qhdrQRloWrDUaxtDmHIkTPMHYGCksFza48Ncv3Km0nWnnyr/HBsaPpURqhQ2l9En9CErVwQmdfD2Uct/rejlco1SV9on6rBSqaoTRaAkAMBpthqKcHsJACIOqUlCqCmUopfz9dOdVVQVZq85zV9Uqyf0hhEBV+Whf3vrh2ubPgUg2nMJaZyFggpCk7yQotHR/adPs/qgpLjmsV0BQ86wBDMK8df5u0l0aJ7HPHUPnpEkpwxw3rM3aZ2G3ro+qkrDGQBsvaCkJoQWgNaAUFJwVyhpD1aBtW0wRN6/Sr+Hr2SaQMKKRChUC6CgG5pVD19J3vs7HcUDvd/4MdYT5bGudJz1stY7vv742+n+VlBBKwQrhIhnqaAnM31/Bst9X5oznlh+ZFzyFH5ZCwkgJY8vrIADIpkm+m4//vv/Uf82RROv70s7o00ZBY9ftwnzYcSgoVwNla3GsSyAxxuCRj3wkLrroIgDAwx/+cFx33XV4xzvegRe+8IW46qqr8La3vQ1f+tKX5t6EpaWlXmEEAE466ST83u/9Hv7wD/8Qz3ve89bTTHzjS1/C5s2b13XNocB1V1552Ov8UcT1W38e+KmfBwDcO8vADgAWP43jxys4fhnA8mbgJHcvH/PQex/OZh6VeNWrXnSkm7Ch8Wu/dt6RbsKPAKLw7aQcBIoWFtD5VDt3QiMqSCYAVgDsOrSNPGrxuU996kg3IcPZ/Yc++tHshxnn3oNwqXnikW7C3Y5VvQrgL490Mwbcg7AugeTUU0/Fgx/84OS3Bz3oQXj/+98PAPj0pz+NnTt34owzzgjHtdZ49atfjUsuuQTf+c531tW43/3d38Vf/MVf4C/+4i/Wdd0Df/qnMdqyJdHk1FJiqa5TbnHggEetlZKyGAYxN2Pz77ptcd2VV+Khj3oUVLXYkPbRm/pCMubtScM5Lg4DdLTeiyDXFPTpNubpAu710f+ML379p3Fz85PpAWtwv5v+Ebte+GTs2rwVALCyZxUru/djujrGIx+4HVd86bsYjxunfc8oWlFTiN48IobyEmiTaNIhsjwL/thkHLVrpjXQbZuUm2agBosgxHJ6INJMXCShGAnLaRxdHgxO93Fd4u2nKFVpueHorHvZoznNUdcVXvWqF+Etb/lrTKfTcGlKH/ORebz/g+nRDFvkIW0L94LlgQn+CzPaKriKnn6bxVFfwMJCc1qpaIkQcD4kZLmI57p77SwZlbuWz3YhkvZX1QibNm0BACwtbYFSEi960dPx7nd/HE3TBpoYt5DUo6XQDlWpkAeE+qYqCVUpqCpqTwWc1QQABFlKZMwzQpnPQ/8kWUSiT0mIskVGNG19+4j35foX2hauQbRwiDRalyvXmVC4FUSIeB9dxK+MTkeRnMga4+uiZy2PCKYqp8UXUkBJga17dmP1+OOxvLSEkbeIV1Jiua4x8mvz5tHIWaAwf73i7eZRtQCgUhKVmr/e5++REvWLUKJvzfLHWtQyQp8popa7pmvR4CtaJSUqpbA8GqFWEm3b4guf/gwe98Qnosrec4tGZ+w9lrej59xoVfVzXylm9fjRR2sVLjVPxNPkp1CJxS1vP4rYqyZHuglzMVhIDi/WJZA84QlPwPXXX5/89s1vfhNnnnkmAOCCCy7A0572tOT4ueeeiwsuuAC/9mu/tu7GHXPMMXj961+PCy+8EM9+9rMXvq4ejZzwUVVRIPFx6Fu2iQr8bZZ0UEkZKQbocs5LTotxE1HNFEhyIaToWFlIXEXtcL8V6GQLbjoBZ6jm5fLrSyg5yS7Sj/waAFi77J/xsWuei1VzfHqiNXjQN96D/c94MO5cPgare1YBAKv7VrF/7yrasdsgTyYtmqaFaXVwUHeXp32ZJ3AF3n3O22ZCjjUWk7W4YLpQplGY6Ped4A7ZRA0jYcMkggUJItwXI/cfoXwVff4aPR2MH1EuN++D1m7ejscTjMfjpP4wBsGZ3sR66B4ndZrOvOV1hhwc+THmgJ9SumQQSOYt7qG+BQQSR9VSjjoH2qArCG1Ajuru+ZaBwgWUBTHuD0G+IZHBOUXlfSCm0wZN0/rAAxra+2koZWGtQj1y9ZiphrXOd4WohhaVo9Aw/yknSKQ0IGsByx3+BaNfAWi1hQwJjtzzIwTC7jQ8QyHnA5DKgzYI9wSlJFDLsBKY1jghQclQrpB+paC5YQy0SdcJ8jEJtCQfGlv4Z1NKR/MiIce0gHJiZCjDWIsWgCJBzlOttO9PYy1GUrrcJT2gNS2hZ3mFFYW/VRnVj8ZuFjo+JBm4QMLX/M5zBAvbk6sG6CqMuCKOz4WSL1bwu1QVlqoKo7pGxZIhVlWVCCTr5cjPc/RP29KvhAi+LRtw414JjXoD9oujFotmUjty6EtbsN4yBiyGdQkkr3rVq/D4xz8eF110EX7xF38RX/ziF/HOd74T73znOwEAJ5xwAk44IQ3dWtc1tm/fjgc84AEH1MDf/M3fxMUXX4z3vve9eMxjHrPQNZUU2OSj0/AXgLEuNj29aLV/yVWzXkyFF4jTcPnP7E29nsnLN/HpIpu+WONnsupELjD1KS8z4YwXhAUVady+7P4X22ytVv/LgsNoi5s+cRO+9bl7o/OqtAYP+sbfQd5vCTed9QCs3rEHK3tWAABr+9awum81cL/baQPTajTTttdJGwCsNh1XCcEchKWUSTZrZ/2IHGmeuyQKEzoIBgDju1OdPQIeF1BoMx/9RdIs7XROnkG95KSedrggHCG31nQFhMTiFoQxnVyTt7/jM7KgkFSsl8+XHgHPtw5CqLnCiCuSnoGetjEtPD8/tZzEueJ8LMi/Ix5Lo2hJL4SQFaXGaLQplOGc3OtQnrPKVKjrpVCu8UkFc226tTZsGq2xMK2G9JYQo43LaeIFFN0aSCUgRnVwSDfCQEoZAjoIWX5mO4oXn62dxibXFOaR6qTPps7Pcbl/bLDgWJOtTcyPhbdHWIHgHmWM8/fgDvVWQJJvFwChnW+BDY7wFk3bBoFDGemjLvrjxvhkit3XHxdE8qSHlZIhkhb1eRH0+VvQsaJyKfuN8ogQ5ild8kAdIVdJpvAqgYIeVD6PyuHQ8OZzh1CK3gX4cYP3L7rbWzdgwIDDgXUJJI961KPwj//4j3jta1+LN77xjTjrrLNwySWX4AUveMHd1T7UdY03velN+OVf/uWFr5lqlxirkmXTeLSIwP8bNV65w/Z6IlLxRIPrI1ItjmDxqaqOCR7wC/sciwU/x8JHIqPNU9bsPgHLOWyn2bfz7PPaGIz3T3HtP9yMXd9dQy6MjCa78ZCvvxvV5jV86ZxXYHXPKsYrYzQTR5Wi0J8c1lroVidWkRw86hbgaSpMmU/0Grq1lJiNNnEhkaJNBZBFLBS5ENB1POXChg6Ru+I5TjAKG156Act0s9onhORt6KNOdS0xMYpR3mdudbAZyYOeFv573uc80zptPpJNE6M8CQgYlC1Ci1pI3IYl/Fg8N2SPRxQmqF0xs7wMViwAUKqCy6g+DefI4EjuhI6lpc1hg05lkuBB/XfWkRZN46xwVVUXrUlCRHpVvoEnGhMPIGCthFQxGpxpDVDFzbMUMakhXZtvrF2dfSOcjnFOmyvdM62jZj4ValyfQihf1ifrAydAWmZjdIIQWQcAZ/GlVUIo/1xplxDVeqOWy9xuIP04tVqjNRq1rRLFEllA3DgVLOFIhRQ+DvSdP8t0bJYFgQse+W9Ujs7GtXRNjhBomcpgFMkZS2ewOtBnrnzrQ96WeRaTPuEjH7e8jlK51lqoIbv6gLsJfE93MGUMWAzrEkgA4FnPehae9axnLXz+ev1GSuc///nPx/Of//x1lTPgyGOyv8WV7/4uVu6Ydo4df+d1ePA3/haq0vjib7wKpq4LJQwYMGDAgAEDBhx+DGF/Dy/WLZD8qEBJ5/BG4Nq7oH2xdG50mOxQF7A+KwkhyX1wENaSXo6wAAyzUoRzxfw8I1yLl4cFPRi+o7E2jHm7v8GV7/5ORxgRVuPHbvwnnPH9f4WAxddf9Ju4q94E7FvFZHWC6doU7dSHUdapv4bRBm2joVudaFVzbVquqRXWOazndBWyohhjAk2L6iHrSJ8juRtD/r1Li4oWhmjp6VpMUmqVMQZGtx3aXSm8Lj+nzxLR78thQt1Ur/s3C9nLNbOFoJ70W9f6Eq1AyfECXStQkxh9ShrACmp7v4N8fu9Lc6Hk55JdlPqrJBYSkVg4nIVEQOu4thCli9o2maz6kL50ThXGIVjjbANro+O4C1HO/dti/hCiWlsjAVW6l5x65+iHnbnurQcuNHDX/JGsCUKAT3ch3UzrrJ9IrQNWx6wjyX0w8R/+sxAWsGm9Rjvfk0AFsxJSIfqmUC4gX6aGcX5xQkBTqGytYYzCxId8bXxwE74x2LzkElVyilbNgxsULAPzrHNlf7v0t771PKdqWWuhs3VkVmjgkkWh80z2vIdkck/ie5N8KteLRfKJ9FlJ+HFqz3rKHTBgwI8u7vmBoA8AIyVRqwqVUtFR3XNOSwt5jHySfifknN8+9EVkmGey45tHw/5mQbNIUiTFUz+pz/R7/jerrYuA+kN0MaIDWOvoX5N9DT7zzm9h/x1pFI2l8S789NUX48zvXwoBi9vPOQff2X4m1vatYm3fKprJFM3UZWHXrQ4UKtqMa63RTlu0TQvdaOjGZ71u2xAn39GdjMtD4P+MccJG27Txb9q4sqZt4jNCfiPk2+F8KEzwE+B/UqqE4uM2dbnjuO60jZzjSYhw9B36a8MY95mLLf3H6D/k6+G+U9st+zPJH2A7xwEkY0cbeAtTFEZc/9JyeP9CH6ksa2PbjUnamZcJEfvvqImta1dB0EqVDRJJBnf+PNOfh5QSsuibIpLrlKpQVSNU1cg7o7t2KFX7nCUjUJZ1azXadorpdA3T6QTT6QRtOw3UrCjglJdea2wQlFXlqWS+3bmQEfrg/yhaGPmaGE55NBYwju7YTtv4fPSsM5yyZQ1c5C368wK8tdHBPCp5/H3uzD/XL3rGXJAIC+39vdwfXZtf5/zQjC6UG8pgQrCPEhbWCO8zEtZWYzDxkc7CPc4oey7Xipj5HJaQr7VUXq4k4et8vv6T8EC/5Wts3z3joLLCteQLN4OSK4VErZSjbfk5SuNwd2CRvvSd4/rnPpuP/PZA1xpwt8Cx2cXB/a2zzgsvvLBTxvbt28Nxay0uvPBC7NixA5s2bcKTn/xkXHfddUkZk8kEv/3bv40TTzwRW7Zswfnnn4+bb7754AfkbsaGtJDIsDm0CYe2LxRi/F4QJjINV+LMnp0zC7OmZaK5Cgrkrmatj/vLz+GO7n3tSnxkWJ2dtsxpd6n8fXeN8fm/vhErd6aWkeW1H+Lh17wNmyZ3AQD2nHUWvvCQR2PfbXdBN1F7jHyzaWxoH21gOWjzMVtTXrZchKNsE8TPc+UUHKDZdXkSQtqUJ23MrARx809Rq5i/RJ8GtWANyfuQHk8tJuUx4P4sMXFin/CxSF2dMQxCTSZ0gDlr5wIJ0nGi45plTBdCIonMAPgEnl3/BrpHJGTGZ1lF36kQgQjgT4jblElmyWihdYvRaBlV5bTsdb0MY1o0DY0bzQMnXLYtgkWFW1ysjSGUAbIKsGdXCAiFYGnJs66XIjxR/8jRHX5jSUOsJw0US7gopISV6UaXQgX3wfl+lJ9/EqZc0tD0rneeU7L8IF4jpVuFgz+XsbCKRVzz2d4pXLAVLsKW1QZGsrVSR98Y4dfExltASXnj1lRmvmERFg0EWETiYGGZ5fsgRGqdXk8krRCKPhNOQn9s2TqQ+/DkdazHOq+k9KGMo4WE17MeBRZv7zzLRskaMqtcwCe3tDZfAgYMOKQ4GMUtL2O9eMhDHoJLL700fFeM7fOnf/qneOtb34p3v/vduP/9748/+qM/wtOf/nRcf/312LrVpUz4nd/5HXz4wx/G+973Ppxwwgl49atfjWc961m46qqrkrLuadiQAgktpKQN4+DasNysXRJY6JrErD1HGOH0h/UivJyzDYEU0pOr/AusUDzVmzuXl84L5SKNRR+c3dfRfmMNWgOs7prg6r/9Hsa70+xlm9buwMOvuQTLk90AgNsf8hP44pPOw55dK2imTbJ51W1X6AgRfUh7zO6rozgZtsFKLVwJpSRoUMuaYa29Mz1ZKYScuZjkVCK3WdXgI8qzONOGk8pPhIJs454HR0iFgLLgk59DVpC+47wMskIZmzqTl4SwfDOVR+LKhSqLVGAJ9wRllATDbvsLoXcFfy5lcEBXIZ+HBNBiNNoUzidrR0rZUjFilqwgVcUENx0sY5RDpKoqaC3Yfe3OLz4f+frAx7BpJhiNln09Bmj9My35uSIsVAZu3hN90RoLVSsX1YqNRU7hstoGCldpnGdtusM5XoCyrC2Um4QVNLecBMYJINziIiVSeqYk65Kn2fp8K1qbRDlgtIFRfpPfaGgW8r1WCmtNAyEERn5uLI/qZCF04WR5w11/ZrU/F7icsqf0/EZhI4+emDqfL2YJCfXxZ7PwdC0SVYuc+93vB2cdySNk5d9zzFt3OLQfa2HFPTTnehfimf8t/S7EYNkZUERVVYlVhGCtxSWXXIL/8l/+C37u534OAPA3f/M3OOWUU/B//s//wUte8hLs2bMHf/VXf4W/+7u/C2k4/vf//t84/fTTcemll+Lcc889rH1ZDzYkZWvA4cfOr+/Fv//ljV1hZPV2/PTVF2N5shu6rvH1838OX3neC9AuLR2hlg4YMGDAgAEDBswGWUYP5o+E67179yZ/k0l/YsgbbrgBO3bswFlnnYVf+qVfwo033ggAuOmmm3DbbbfhnHPOCecuLS3hSU96Ej772c8CAK666io0TZOcs2PHDjz0oQ8N59xTsSEtJKT5zbmzgdLkz8utA4T1mti49jNog9DV+PRp12ZpoWRH40blxXNm1ZNbS3LtlEFXKjWZpq+kQQ385sbgGx+9Bbdcva/T9s0rt+HhX34blqZ7sXLyKfjSc34Bty9vBe7YjbV9Y0zHE1gby3e88hh+l+oILfH31RrmhM1D5AIQxoduVilFhocCjv4WXQsH4CwkTgPelde5RptTrbRuQ6JDrv1OExqm342OwltuCclpS3kbctpZem73eIlSxa0ZxqZO1wSeGTtQSUqhkGe0e5alo4QydW7+M5nSjvzzziwDxhjvD8IjurXBUd3Vo6CUQuVD+BLliYftlVJ6v5FY9mi0hJhfxlnJRCF2brx37lxqSx5euBK1m7uMN0R5R2Iyu3RMdKudhWQU+9eSrwRZ3IyFYQnJrHGO6NwqYa0FTPr8d+6hEZmfiYU2OmSRF+7CuVaSfJ0hHxhEBmHSS+uDHYQ54tsvIcN1rv02saw0bbSMN1pjdTKBMQbHLDuLlGgEapbsz/WZ5ZYR/dSjhKbV08++nCJhHQ0WyvlWkZJze24RmRXaN7RV0L/RIkJ+lxwHS1lx7UnHYhGn9xxCiCTEPXBgEYykDxMMrC9UcG7hsB995bquzRkZQgjIZ/63dZUz4PDiUFK2Tj/99OT3N7zhDbjwwgs75z/mMY/B3/7t3+L+978/br/9dvzRH/0RHv/4x+O6667DbbfdBgA45ZRTkmtOOeUUfPe73wUA3HbbbRiNRjjuuOM659D191RsSIFk33iMetMm7zeSbs555BBrLRQyCtMh4qRKzwFPwEzXB0Lp4sJUJUQw9xt0X+r0OUfpZVASYkzPpoFj/w/HuPY9N2L/ru6xLSs/wE99+e1Ymu7FrY98NL785HOxb63B2t41AEAzbWDIyZVoQ97Blb5TNC3KKGGMc2qNSQtJECBH7dj/unYWGCkVy3UQaTdaxwSAcaxSLrMxOtswGUYVS7OWWxv9QXiZqYBSjtiVY5Z/SOk3Loi4tplOGQSeZZ1nVDeG8e9nJGJMs8qbArWs31F6UeTzMQoZsyl07hzaEBOVp036JoRA00xDPRRZj3KISClRqTrm/mD+J3Q8OrY3Sd3UTidcxHwusmdRcdQvGT4DQFU7vxRVySBU8/IDbQs+xwgAWTGqkg8IwXOWWCaME+Up3kP/fwYxI7xNn4O8f8k5vB4+18MUj1vljnyiuvczEUoA7xcEiIJyINZjyPnHjYHJkkEKAdMaTCVRMRH+rRvylxBAC1gVvxtrEUQ7KV00r1IbmFBgc78mL3z00RDpXZAnRqR25+e6fxkltEfy6KPdcfox0bPIZ0RmFNVD5cxO75x5QskiuVX4WMuCwD8L9hlvSxRPAIDzLp6bt4vGW+T072e8zbVLCNiPvhLmvEtiXTllzuhOPda6SGq8HNE0wMc+tq5+DfjRwPe//30ce+yx4ftSD0vkGc94Rvj8sIc9DI973OPw4z/+4/ibv/kbPPaxjwXQ5886X8g/FMqFuxMbUiBZmUywNJkkGxtjLZSUWK7rdfHUeFjI9aLPykDCytwFeE6dFLI32e8IEbRjHUfv0ibPt2OWRSSHtRY3X70L1///boHW3dE8+fYr8cBvvhfjU4/Dl57wXPzwPj+OyeoY45UJmonbDGof2YpnVSc+P0UHMj4qEAkkumVhf73DcEzkx/sGtG3jx6DtCASLgnxKqB4+NvHfNOt61zIRBR1+XQ7extzKUtogcgtPLgTECF4lQYYFECj2JxVok5d3Vh4XRvjYHuyily+czm+jCpv2EjqbCm7VoY2EXw9o7kihgCBg6NB2i/7sz1JWANIx07rtjDUXeHOfEbKyJOuT0YmlpmRZAJwlgkjztFG3lHhQuYhc7bSFqstjJfwGn2C0gRKyU1/eH7IyUhuCAEKLjfTWF5qTSqYO7nRd8AEBrE/ayC3MND5hM6id/UOp2I6kXRIQUjqlgzHBQsLbFi17rm3TVockhyuMNrE8GsV7KiUqNoTKWlhKnNszOVx13eefK6DyzXnxGS34jcXymVIBXb+MXBk1S8Ahf8qQ0T5EZyz3j3CoQu+u10dGs3khIEIWeX3exQAA9c+vQnPuxUn7E3mN+eekY9HTjk770u+SsS/MuRd3zs/H0a0r/RZDbaOlzD79TyCXlgYfkyOMQ2khOfbYYxOBZFFs2bIFD3vYw3DDDTfguc99LgBnBTn11FPDOTt37gxWk+3bt2M6nWLXrl2JlWTnzp14/OMffxA9ufsx+JAMWBfaicZXPnALvvahWzvCiNRTPPAb/xsP2ff3+PqvvgCfffFv44f3+fEj1NIBAwYMGDBgwIADgxSH5u9gMJlM8PWvfx2nnnoqzjrrLGzfvh2f+MQnwvHpdIrLL788CBuPeMQjUNd1cs6tt96Kr371q/d4gWRDWkhWp1MsT6cYZYmugtZ4QYmXW0dm+WLoGdquWb/PMlnPo1XxNubm4d4HgFlPkvOz79yvRN92G+yXvww0DfaujPCVb52A1UnX1Lhl/y14+M3/E3c+8QH4xEP+EJOVMSa79ockh824wXQ8QetD/DrriHX/mnT8KGRp27p8I1UVKXak4Q5JDE1XOy0EghaclxuPC3BmekkDEqlg6bVkYeCabf59lnWJ6FBdzWdKOeP1UrQs9zmnjxV8OagN1lGyBLu7xupEu1pCJz/GAlpMAQGskz4xs7zsdjhrQhqKdm44U+vPYM87abtiRLaYUyZe5u5RqMuHASZKF1kKXN6PKlzTtVjlEdAWs86F+9hjGfM/xHN8Pg/AUcOkcnQsCqUdaDoqnZ+cAmU9bcswS0tf9MA4JoDV0R9F2HR90m20OOU8Jz4HbcMjnDFrSrZuE6QUHfoWUbzoNhptAMksdlo43xZaZ6SzWrQsAt7KZOIsfZ4yV9E9ZbQ5WpMpwmEfNZZbQ3ILCVG4cqpjDr5Oh3Uxs2ryNgRLSVJGui5QniqqmyjMlYxhfvPIWqV5YKxFldWbtzW/dr3WkPC+ZuNTyRj9jp65po2hwPG0/wfQutPmkkXnYGmlQH+kS4KxZStJcv6s8NrWQv7s2wcryVGG3/u938Ozn/1snHHGGdi5cyf+6I/+CHv37sWLXvQiCCHwO7/zO7joootwv/vdD/e73/1w0UUXYfPmzfjlX/5lAMC2bdvw4he/GK9+9atxwgkn4Pjjj8fv/d7v4WEPe1iIunVPxYYUSNamU4ybKYRYwqbabSQqJZOQhgeDWSZr7fMA5MkUF1kAZ5UbQjH670SzmlVuabEjH1na2/YJKNpamOu/ifaVvw27NsbN934yvvXjz4WVdef8HT/4DB606/34wvN/FTfLk4Fd+zFZnaCZNGgb7yjeusSENvh+UII0nex5hYihcl3iwgYCo9g2yh/AKFvrhduk8e8Ap1oYo9E0k4RrT9f1Uati+7vUN9qMJvQnOqcnR0ruoO7KpfZRJnm2Qck3BpkwMi+3CKGU64V1jjrWPdQjLBwKHroQ8wN7FukQhXvjNmTeUVlVPh+ITupINkLGJNnRqQxOAXLXpONWVTW7JgovpfbQORROmB8vUfZCqF2flb2qXdmyUp22xTWCwhin85ieNQnJHMnT+vqSVzp6pa9HpcJeCZy6FSDT+pTLTlusy30GoA1MOEdCCPIhmbEut2yjakzIScLB6VtLVZ3OYxEj5tA6PW9Nt56CUxI65jmhz6J9lc7LBRM6llA5rYVk59J483wti2I9AkZfufw4+Ufmih16piulsFRVQfmnKbGq7xOh9E5czxtiXtCCedfmQlVgNPYMbd9aSXOHHN9DeYNwclixnqSos8pYD26++WY8//nPxw9/+EOcdNJJeOxjH4vPf/7zOPPMMwEAr3nNa7C2toaXvexl2LVrFx7zmMfgX/7lX0IOEgC4+OKLUVUVfvEXfxFra2t46lOfine/+9336BwkwAYVSKZti9ZvfGt/A0Y+gkqeBf1Q8GHzTQTP0AscnDYmL5sQBBMgUFv7cpgUyw1aMptYTujlp42B/vu/h12b4GsP+lXcfsqjOmWodg0PvP7/4CT1Dfzz81+JXVOJ6dp+AM5pvZ220CSQeAGEa4DJqT33X0heVEpFR/I2ZsiO10yzDTwfnSgM9AkW/LcIEiC4g3q3HGpj/j09h2t3lT8Wy6K2R2HIIM+xkUdrcnVKUBLAYPXjL0M/Bjarq8sxL/uSsMqwXtxdmZ2B9AVubRrJqk/7GIR5qVxmdrYB49GzknrYHHQWEQpmEM/JBcy4sauStilVo643hXKLlk4hvFDiy+BO2tmm3zbp85ILwTxDu/DWjlKWdwCw2qC1FtLIINiQj0qwQmrj/UZ8P6vCmOl4Xd6vcF6vnMssWIXABapSiU8MT2JaAgUR6IwLCWlawAgD3dHgV1glHzdjsVRVMFW8XgqnpddsbpTALRqLRL/qEzRK0bT6MEtYoba6MKTxnUfWER5l6+5CzjDILTdVtlEi6xUFoKmVgrEmRiOboYjqG6s+R3+OWUELZsEJH/3Rw0rWkk49JcHV2iQq6GAxObyg0L0HW8Z68L73vW/mcSEELrzwwmKELsLy8jLe/va34+1vf3vvOfdEbEiBpNUak7aBnMiQ+EoIEYSTPpC5Otn4z5lMJWGkD7M0LX1ZeEsb3uQ6xEX0QJIa5o7xrXFUhva6LwCXXorvn/aUojBy7N7v4GHf+l/Y89B740MP/22srWlM1tYCRattHN2KLCTWOOd1rt211tNE8pcCneMjcAkrWRkWyDSXXWEj3dDHjT+dVw6lm3/Oo02VhJGuo3lqRXHUL4q2NHvzy0rutM+f2fN76cw5ggbSiFmh5sKcOxT0hnmYS8Gi8zqCIXemL9PG+IaX/xstbVEwIWfz9L6mEbPi9WnUNKWW/b8xYhcA1PUSlpaWQ90kfAACMcpWmSZFUeUAQPhoYYqiaok0YpZuusEMlBBQtQrheKWSUCoKPsY46qQV3TnJg0u4a+MYFYX6Nn0uhcxmbKaoAQCrGWVLCojWCTxcIOzMUXYPyptMuLC/LLyxEmnULaEBLaJzuZIStm1YJCunlFkiK2RdQzQCqBGiO/WRFIPDOnN6jm1bTLA40EiM/Hqg/70CuEhi+f04UGVCZy5kFsuO5YYdd4KRTMtRKlGgtBTGP6sn79+sMVvPsXW9Q/0cFWw+SfYb4WCEEiBSqQehZMBGxYYUSAYcHKwxGP3X/4Jdm0/BjT92fuf4j935z7jfpn/Fv/36r2Pv5lNgVsbAtD9U7IABAwYMGDBgwI8S5tFQFy1jwGLYsAJJqw3G0yn2M+qDraNjaoCUUDOsHAcymUpUrZLGK9WGZBGrFqxXCFF0Sp+HvC0Uz77RGur/++cY32HxtYe/CCbxGTE457i34Lb7n4j3yJej2W+A/buDJaSZNJHm0ZqQRwRAoGYFbY+ngQQrCW+LL4Oc3oWnaxhrCnSNnILUR02KlpM+bvN6tWS5ljjWFR33efJDnWnMUvrRPI1cHgo40xb2UDZK7QO8ZnwB/5tOuw6hteTArSIofkcpGaGIVgghuv4Jjo6V+27MctC3AES4B1RG6g/S/+w63xLXptyHhNOq6N4Z3U2mxiln+fNTL9cuSSE5lUuBeqkOZSsloeq47AvnVOItNL5uQ5a++F2q2L6+OcUhhAhtj+PRfe6cociPgXHO6dJ0w5AHGpYP8TtrjK21EDZ9Xoy2jp4Kt/YIIYBWJ/SzVlsA8XkVjN7EaU61d8Tre3p4nhBOhU3al/Uvnr++56tDOZpzPYU7BpylJ0+CWCp/HtVpkXckP58obyznZ8yplY2XTvy0ylajvM/zrCazKNt54sUSSuVzK8mhwCz6FllJAAyWkrsZg0ByeLEhBZJKKVTKLbZTv7ldmUzQGo1Kxky0IQsvveDnJEjiKC3IQkQHwfyc5NrCYtN2MtAiRD+Zh3zz3SdQ5bxkgjYx4sxk750Yve+DuPGs52LfsWcm523ediPef+pzsX+qoBPhQ7O8IoySVXiZ0OaJNk2c2211mi+AhBjap7nv/Un/eD2lzWrpvNI49aFcZ6RnUdsD1atHSJi3qafEelR+3tY8sldeHiU87Aokqb9Ocg1zkF9UCJklUPQ9S4sIIbMEkFkbYLch6P4ens8CyYYiePHzk/bP2fjSv7Ooblo3GI/d56WlTZDS5SjRLCJQ/gyb1nToSkYbqErF5yqjeVF0LGtNoGhVVZVSnBRRteLzEOlbXmCw8fmjNvFnV6quE3TfvZp3z4QVkFWXlsrbJ3Rsm0u1kgk0VKfhcx1xd0uO/EQFtS5xpLUi0kMrmdDmKukEMtqgamsgjcG0bVFRlC9bppQR+oSR/Lf1+Irk562HBiyEi6rF33tOATe/rj7q8Kz7G551ixBdjLedAqu4BMZOUKLxbv2zsZ5IlKVz+voTzp1xjLDohvJQKDOTthQCdXChBBjoWwM2FjakQCJlN6KWtdZbAXRY9JSUsEox7dfiERVy35H8N4718FE58ggis+oooXQuLfoUZUYbg9ZojKcN5HQfTnz7r+Lf73U+vndGGh5OLzX41vESmFi008YJE5mvR163kBLSL/miVrAWMDJ1GE9C3Gabb9JC06ZB68aFAtYt007nGdMt0sDFAJBZZ3pC9ZbuaT9SK0XcfLGNVKZ9LM2DUjhYHjY2bzOvC2Hc+h33O07r8zSAMwSmRS0a6z3XVZsKr+kx27lXJdBm3H2WRZ8FyrQ+C93NF9/487JiOVU1AkXqyjepWuug4TdGF313qFweHStvj1CuXAqLrSrAMiWItRbt1IVBHS356IKjKinDauMCTJg452UlvUWjPDdKPjj5uOaRuBKBYt7mlX7zgoiZmrSuWkB5IYCErtLz6Sw4XlsNJP5q3fFsOw70ou4qb6Km3qKS1ievi8IRbbY5Zgki8Zz5Qsi898a8jXfuZE3jpkT5fXUwwShmRdbjCf8ABL9OHmGQ/EPIeuJv5Uxrf96/WYJvfs6BCAulsSz9PgtJgLkFmlCMHog0zPMglNx9OBJO7UczNqRAwu9/Vyhhx/0iSQ512lgIaSOF4CDMdbM0RyWUFifShrjjqQa1+ELu0dbl2jhtbRBIGq0xbqaY7LsTD/rEy/Dpm5/eEUYsLHafcgeaxkWgaadtsnkJfWWrrRA+JwKnoXjqBwBILaGlDtSSgDZ/kRtYGzdctKGjCEdu41PS/OdhT1NBJL0/dG0ymj33PlpE8k0YRVZSKrWS8TZZa5MXcd4WEkZKOUZyiwgP5VsS5DobonyjzyljC4QmpfbNw2zKUxfzKFn5+PBjJBRw6hOAoJDgwoTwwojMHWjn9iejfYHmFXwbqpnrhKvHndy2LVqfO8FZwmZvRnm5Va2g2yj8C+2yrhs2D6SSqEZVcHzPaVbaWyF5FnUhnGBDdZWEIiW7lC1uDc7Xnr51KA/5CwDGW1UF1SsR8pBIKZ1gP0MYimUjtN/yTVyLhA7nrpWBwsXbG8bJGlTWQvtCZcGh2jkp2+R7CSVryLy5N+84Fyxin9J+8IiSyp9P2diBAvVoHTkyeL2d5zZz5qcQvRRJq1LKWUASp3cTBD1fcNKfvudrvflNyFJDWdYXSQWQW4ho/pUsUOvBIk7u1GZqa94eUloOFK67BwNl6/BiyNQ+AABw1hfejM9e9TR89+Q8cY7F9Kz9aJenR6RdAwYMGDBgwIABAzY2NqaFhNMqAhU81bgAMXQ+aSDIbBx5xDJoQdbjbEga3QPhBvM+zNPClPo0i9ftNGapZr9pW8hbv4qvfeIk3Hivp2YdMRiftQ976l1Y27+GZtIA8HSrTB2Ydy/XLFhrO0nQpEx9bvJ2U9jOXFOudQutqS3tTGtUn/8P11qXcnFYa1FVo/zK5FxjdKI5N6brw1CoPLHYEN0s9xmZlfTQndW1jqRWFtt7ra+l9/fU2b7re9PtUu6ky30jyjqPeeWWLD599ZfaQHD0TZ53hCfQm/9M5lQtmtc5JYnTt2bRy/hzYa2BlFXneH5tsOiYLg1ICBHusRCO2iSE6Pi+JNf1PLt9Fg4pZXD+BhCywIuljLLVKXeOlr9AUxNCACb6lYyWa6hK9eZRoXoEYo4Yo03iXGJgoJg1iu6fbWyH0hbLdO8DxaxpZC0h+lGl1NyEhqENC1pG+pCv+5TrquI+i4h0Mm1MkjSHLCN5IsRZGnpOF5pn8eeZ57llBIiUuchEMNDWBgvPVJcojN36Z7WTtyOhCBbodI55QHQrC/IFAvrpXZI9t6X3Mp1/d1lJgNRSksxlawefkrsJg4Xk8GJDCiSbl0YYVRW0MZgSJaiK5mWaIKUIIynFhzIAdxM78e85j7VvIxI+FzmhJjm2iDAyj+5BbQ0bJP/C4oJS0zTY/GdvwfXHvyaty2pU9/oObh8prO1fw2RtEjYitPmYtUmgB3kmjUMITy3xeRt8joSWRxGaWCiVbgallDCGciLYHk5+t870nIJ/RWfTkG7ME4f1DLmPR/ovOfIb7yfDhRoujMTNd07PyiEgE6EkqWeOMOKuF/1CyQxhoXfDldF8oqC5SMy3vP6yM/QiNBbujB6iZ4U2KXAfENfWng0PE6i4szOVydvn5mQVsuCW14ASxTL6s+S+EWENYolDe595Ws8qBaFk8d6TsBCOUf8Sn5iuwztdQ88+tUlIgbZpuwJUMj+KzUzbxJ3SrQ1jTU75pUSJaRme4mWJpEVUOla5AYywwZ/NoLs+GWMgrYwUJ/iNsx8LKUTYzOb3IATdKAh2s9Zpfg5XfNE7ivsopN97qEbW+7W4s5J6K+WSD8r10ikzuhD1j8/JIm2LKVWMFz6orKkPZgLVzcvUEQxzulJhzUqFQhvoWHSsJBjG1UkEoYTqD+/dAk0LmO0TMI9iVsK8bO6zQHNl8Cm5e+ASiR58GQMWw4YUSCohUSvVkW5Tx2d0Pgc/jcCBdeEjc8FFsgWAzqOyFtWAdRe1Mq93PQtbySLCtUTapBs922psfsOrccP48dBqiRVkUC9dh9vOOB7NXpfs0LQmSXJIvO/QTs9FF2wx77yoipvMrBMiZpUWym1MyCG4qmq0LflY0L1MNVsl/nscm1TAyC0iuWBgTLzvWreJQ7hUFbivR3wxm06f8vlW1qDH32ZlIe5Dp1wb3rD8pAVKWsy5PH4vWy6MiffsYDErqhohv9/B1wBcmEgjauXnlspz16RhgZ1AHDXNVVVDKRX62rZNMchDqV85yKeKB22Apnqdr0oe5Sr8K0XHPyYIIkFb7TcubBiEKvedb9YpO3wYA0hY0dVAx77Z7vMflC3xHBh0wh3zW0SW1PLz7Df8fhittKGOUntCcDIYCAr3ywNztCYKZV7pxBMltlp3wtCqOUoZQhA4su90XphvrG9UthSyVyHG30P5eCsuSHtfKiXzshb3Y1gkUIUJyw67Z521IUbSonaWyuHt6qs7FzgAIHs1dd7PQogk+3kQSsI5ZXZCeB7o2jmCyYFYSxZBbhHidQ0+JQN+lLEhBRIpJUZVhSrbpOl8A2Dmh02ct6jkG8H8RdZXLocQqYPielHSANHvmrWPNH7GGkzWxqjedCEm196GWx7z0qS8enQbvnfmVmDcuIzrWruQvhQCM4T4NdSBsBkKdABygOWa2UKbk7brlPbhKCgqvpiVglI1jDFQitMBDErZ2bNR6myeU4Gka5XQLIcIWTcizUSn2mAU6DZUPsr1lDbZdDyUxcpJIARm7g+yuWtJK947L2cLIrH9ZaGu2w8aQz1zw9937SxhZyaYJUN6Z2ilaJnLNvDZpjB8ZhnU87Zba7xQbIN1Q6naR9nifeJrTb9WmuaYlMrRXbyA2zSTtB++7lw4EpJZo6wLpS2VRJyCNnmuYsSpmG08F+bzvCr5fZfewb04f9nznm+QY1jiMJiAsLEtKm6gE/pXaS6zz/EatgHON5OJNSZauGL29lQZoIWAkpGaZ6SEMSYRSuoqfX1KgUAFik3Poryxc11LunMx17Ln76FFbBz0LqL3ivL5tkrP3XojP+X1lMqUonufpiyACR8Xemfm5eQbdCm6v5WUcKU2lv4FXAQwJSWjcMVrZj3BiVXiIN7d3bam/849n4VWJgxhgQ8dBBaPvDqrjAGLYUMKJANmw06nkG98I/C5L+K79/0FGMV9JQx2P3AEjCdHrH0DBgwYMGDAgAFHFAsopRcpY8Bi2JACSfA1QNRTlrR5wvNaW9KSoUWlFCifgPaaQoOuD0kf7YuOl3AoNCm5Fj63jiTt8g7SZBqfao3p/v3AH/4Bqqu/gu+fdjZu2fEzSfnNyROsaeczAgDT8RTttIVu2pD/QGsN03LtuHVZloWBZvSR3Mk1+S20n1M4kGgtQ/mZRptbYog+Mw8ly0T81yQ0p6B18laRpBziNNv0O6ztaLVKFhGnhSWaFyVAzPOozOkLTCdnRG6tkDLlkC/CZS/V32fFyY/1abCd4383bO6BIK+Da1kdxUIl34muFZ14ZbC6ESgfTrxOJi+hUrvpmrp2grxSjkpF9zXStcqJGLkDfJceFcM9U9AEpXxOkbrylhmyQiJkLgeA1vt5VKMq5PsBUj8UGjfJVOGmNb20LUKfJjyxohib3fuUPmmNhVBpvhMhReLbIVm+EX5OjnzudeYft5yQxSH4CwEwFpaH7NVu3aGQ3UYYtFo4ZxK4sL9GSpdTI9wrk8wlwDtJB81/9PfoG7fiO+EgNkHk1E5Wh0j7inStWWXn1pJF/BusjXQu6i9fN6Ugv78seEGhnD44i8TscxcJHJD7kCw6zpwml1uw+iwlB0LbSuuEL3f+ubnDO1+BBivJgB8VbEiBhCB6KCr5CyIsZMh8LJjZuY83mi9+8+haJSy6cOUUk9ZHJ0k2BexFQD4jRDGY7t2L+jWvwP7va3z5p1+NvceelbZDWKwctxuT1QmmazHniMuozjbwOk00yPsQhItcGBEIWdwBx2Xvo3zM3ji7zTtRXVyyxIZtko3fRIrONd3NtuFfsuhSFhDdl08ssUtfouv6hNVIQ6IXJ0XZ0lEgMcY5q1sePaeb2DFP9nYgwsc8zKKU8bq6fhml/Cg0PiSI9c/5XJDjdfB7xulMUioIKQM9i0cS4lQt7tNCEdry5yrdMBUoLqb1QkKs21qLtm1YGXFp5eOlVOX9TxS05r4mtjOuUjq/lM3Hbg6/8bw94XkskM8DZc47EFc1a49JKU3W2uCn4upxkam4AqDz7PicQsHfCwIGJjzjfc8AtSeMU+YsbbQB6pSWxulWfb4knflkU1WC8zWhtdzApWw1sf3CJ2UkHxs4AYSaboxxUQpN9F/TxqBSMukD/0wyXsmXpEPvZO0sCSmLvlNymhc5sVcqDc6wCPi0Mjb93pezhNaeppBks0SVjOXPDgZD1MJ569o8RWE+T4jaxp3cVWGI5r333bXd8/uUNuvBeih1RCsOzz8pIJ7536IANQgnC2NIjHh4sWEFElq8wsIgBIwPm0nKt0opVFJ1rB8cxmvbwjky1ZgmAgzTlOQL7LzFSGcbZiVlJ5oXWToIIcRitgiTANJqjUZrrDUN6ju/C/W61+Nb6gn4/iPPhpXdW79y7G7sXd3bSXrYTlsXAcs7ghpjYJom0XiFvvvxUZVKFn960VPZWjMfDBpLn7QtZHHXLgEiRdla2b8X4/E4GXOlakhZgXxItL+GOwVTJKs+4YLaIJIdjNuwhsR7PVFe+pMt0vjlL+bM58hoGK1DxKxwDOnGk1tWSAPc93K2hT5yCxDvR8naMc9KMst64MAFlK7wyoUTXk6sL/WjSeukOaidf5G3HtD5PFSzZZt9Dm7JyAUQ/jLn/SefjrZt3HrArBwuylvcwJPFhCfvjM9FBWMFqqqCnVho7crNw1eTMFLVddhIy0o6/xDmDyKlZBGpnAJGqq4AkVhEkG4OY53+N5UKjCWrLCkfyJLR5yuWjyMvL9zfoMVwgpKLrMWuMwbBVIF0vlkvJEROv3RO7tJmKon0OmOcUBKOyzimrg7lFB9sg08+eLQOt0qiMiq8T/osIbMyeeffuYP3vM13/q4qWY2oPIGD31hxJIKXlCHpIY2PFCIktywJIqX1piR0hfHoEUYWEdRyy0liQaByeduYr+B6kLzvsnd3fvxA0Wc1mdVeay1aa4JwKp/53xaubxBiBhxObFiBZICH1lj+8F/jO5drfO+M12X+IhErx+7G3uPvBNri4QEDBgwYMGDAgKMGffTC9ZYxYDFsWIFEChf+j2tQpAAgBFSgf6RafSlkoqFKkjL1mNi1MWi8xmzcNDDCJYBqmcUjjyLitGaR70tm41brhAuqrU00IdrEMJOtdlpBHoaSNFPT/fuhvvZ1TD95BW699V74wYlPgD2xHH7V1BPcddIPsVatANpZMJpJA+1D/FIyRE6lMq2jLVBuAmsjr92q2KcOXUl3fSVyrZHRMZSuS4DYgjTuCbWpoPVy/5rEmhByhyTWgS64BYVH1wpWCeGoYKllrOsfkiP6iaBzXkhgiH7/luQ8+m0BrWCnLcHy0m8Zcf0tUdvSa0pJAPu+O+vHvOSKJhmnrnWkqzUWQiY+IwBQV0vBrwMQmE7HWVuyfA6M4sXvEbduEJVnOl1zLTWG0b5YaF4glFVVoyThpzHTmG9ESEjpQttKJSFaEcolSwsAjEbLqEcjT9NqQ985VY/6IisKP1yFsQu0Ih91i/y/XDS8GDqYWy0o+aHKQuIKFz4quQdCOksG/y23rPb5nPS+oIVrV1VXgUpltIYWArKiuVegj1Ef+HcjAMksBoXqrLWJVdQaHnVLJKGOKyWd9t9oTMnvqHGlLvs5VxXCEy9qlViv9aLPOhJyosBFbqT3WSm0bgmLWPW5lVhJmUQbo6SHs+os+XpQ0l5uiT7Q6ER5ufMsTbxNBxPtktdNFrs+qtehtJQsMk7c8mtQWLcLb8XECuatKkebxWSgbB1ebEiBZKSUD92Zxn+viV/ONiT0kgfcOwwmHm/9y18KYOI3BdoYjJsGq1PnY7E2nWDNR6T61s7bHY9dpFxda9OQw7QW5CF6uXlfiNQ5UBub0Lo2j0Yw1mI03gW5+w7UN9yE6hvfRvOdPdjV3Bs7T/wprG55FnBy3ygZTLav4a7NO9G2TeCmBwf2LBwmD/PbTBvoJnLB+SZWeAdzDUYv8v9yrrtUMjqvdxIQkjChAaTCBS+T+sHvYb6hz4WR5AZQCTbNbVKiornPupvnoUewilXxutKNvUsw2eVak7DTqWeBF2upf67msiDC7yF9z5M/5puUXFgyxsKYKMQpVSdCBBdg0rrL+VZyv5RcCHR1VKjqaO2TUkIq1cn/4ahP3PlcBqG+qpxAonWLyWQt1FHLpdBmYwzadhrKq+sljEbLUKpiCo1uziOiDub9MTTP2kzILyTclEo4BYqKlKxcMDUo06WCQFQhyeVDm34CJTh1Pivu97ZpoZRKhJZcKCHQM2xm+JXNgjUWwmdlj6HDBSRLmpfQ1Iju14kJi6g0MgZWCAiWo0goNj489wmbW7lApSoFqZkCCALa2A51lhRcalSHzxyzxiD3KTlQ5M+lFKnwt0j585QLUcEW1xOaM5PGKa7awtpJ6MvXRcKIu6VRsOpLXMzbsh6fzdzxG3BTWmXv6lKyxGJ5RQVU2r6SXwk/fndoz/M8JTlt0H70lTDnXTw3hHJKm9RJMk7ySTlaBJMBhwcbUiCR0ls6WKZ1sI1KdPzrd7AD3ELlhAkES0SjW4ybKdamTgjZP55gdbwGBWDv6hrg6yaBAoB3gO6PAjJrQU02/dptSu+1/yaccMOlOPHLV2HXLSfiNvMg3Lbtfti97Tw0O7bOHBthNOzmH+L2k8fQdQvdOKsD9+0wxgYBxXirhmlNTNrGHDt5O/NNgmt72uegYdHxeLrpL/lhlMaNbeptKrQkOUms7Tigx0N8E95vGeCfte5uHPvQp5kL/ZmRALFT96LCCC8jE/RK5fZZmGa3i5dloXWbCHFS8met68AeP0dH9ZJwUnL8pY29cw7XHcGF+9kopWCtSfyA2nYayl2qN0PKKrGIAU7AIN8UY5xvB5WxtLQZo9ESAJlYQVJhpE0c1ut6FIQK3bogEa01/lnjiTUllKdUjpaWgwUiEQzYRq+ZtqiqKpkb5FeSb0RNeDZtUibgN/cqzm1SQKgqxCLqzBtaLyhZamkcys9c17eOngOpKow2jVAvjxKfF5FtTItO/MaGOBDWupkfBUYJoxGieVkhICEhVOrozttGY2h83doYKCnRah0EWiEEWqODskoIAVGL1Moe3jXMCpxpzkv+XrOUG4tswAVEyD2S1Dv3ysVA7zbyrWlnrGUEvtZwy4WFDWwB7svFv3fqLwg8JUHH2hisJFoVUuvLIoLzouhT3syzmBxUnXMSVoqP/d/JGfJn346mbYtjxdueegIKABYyvM+9oMMsJxtROBkoW4cXG1IgqZQKLwVLmkcZN0b0rlO9TrkOfANAWrHxtMHKZII9q06jumd1FdPVCY4DsH/PitPMCXjHzHTR45rNcn3xM2kcdWOAncDo5hXgLgEx1djZbsJt5tloq+dB/9imhcZEmAbHTq/Dt+89wupm5ehWjavUWp4h2iaa++QlwjOVszCOANf2dje4QGp1cNersIGcl5l81suZhJGo4ddJFC6ebK6vDBJGyptiTkuZJUAQlSZva7rpTzb8zvwEAQkIk5yTtHGdGsC8XUlZ7HMqkPSFHS5vKgmOZpQJ2EazDWV/CNzZiQ9Nck0nYaQ1MFpDyPjC1zpasJaXt0Drxj27LPoVdzBvmykgGt9eikZUd+abECIIKO4FpZLwve5zXEpJiInf43xsmimaxgVdcAEbYtJGpVSw+qg6Wl14e1Slun5eTHDTjUZr246Den66CZ8jZUzwx0QJJsS49SE8Yz74hMw9a2VuUZxPl3HriDunljKE3eUO7zzsrxCimBlQiLjFpM1fR1tNrwIVhaoQZcsKZ92tYhnWpFRKY6132qbR84IIbc6l7AgjqkD5mCWM5H3i7V8EfCN/KKkixvefwPvJN7elNueKOKJ18bHlSkIqp9SHkjJvpiWGAr+welw4ZvoRgEgtJnn2dlh0Qv8vAluag+x4qbz0XZE/tyXl6WJhgQGE7O1FC5WPIsfbZkUUrmP7qTInnEQhTybCCbAxaF0Ch8B6eWiaclRgQwokRwrtdwBzl/8iLAQtaAqQJwPy1NQMSrAaMLdZjG74ITbfcTvUdAJrgVZuwl2j+8HIEcbw9BQJoOyXXsSy2Y1jlm7A9Sdvxc31MW5TcQi0MgMGDBgwYMCAAQMGHApsSIGkVgpV7rQJG6QBztvNeapce0DaEu64vtY02Ls2xu59+wEAq/vWMF0Z47gR0H5VwLY98vC3gdHSPhw/uh71eD+c5lxhnzkN+/RpMGKEKU7GfnUysJjRoxebcQc2Ld+EOzZpfGN0DETtaFx6beKdxk1CN+F9zjWyRMVKtOsmo/sw60hKner6QnCNUdcfY3FLSU4xIppW7hxcytnBr88/z64/t5akVqO+cvLQwFmhHQFRCBl9Mg6xdSTXwM0b85l1ZveUf47lktWoNE6WnRO/u+Mx9GsaspnNmY4xKlKrhBAYjTahaabFvgNA4+lbHUdk5vNC1pU0r0lXa8Yd5JsGEKJlFKgmMEcpUEMpzK9SVfJcAkhC+OZ1j5adZqKdemugp1pqrQNFTFnAShsTDnrLbel5CIY7RbTKaN3kiVCldA7wQogQ2AJIb0ffs5DTWKSUWNq0BACol2oI5S3LefvIT6aPniLjbDLauM9sKPl6E+hbUoa8KcJbYsgHzkqbaM6tNtDSQAoRrOWGjRkHaZpHlfIvEbmwdj2fo7EeO5eqlVjSZJp3JLHKrhNENaI+jHhiUZ88trQ28/YaHzIZQLCO8IAsEn5uMiqYKrAM8nbl63hOBTO2u9aTlcTVYztUttyvhNcX2rvO+wmUKVwHWhYvs5SnhMZRSRmeixCu2ltDcutfMucQ9z5UjxQpTU5bPucMAo2L2rYB/EykWNwCNauMAYthQwokSkpUmSOtLtCC5jpcWovGCyPkxL5ndRV7VlexsncVtjXA9fshfnAMcPZkbrumk624bfLI7oGDnbB2P1aWx1itV7Cq9mIsNCDcZkW2FvBOuVrrzgsqp+6EIv1XY5zvCM/2HIQNw8tIHcMpF0iSOwNxs0f8/zRrtQyO7OvqPhciCxQiXv+s37oJ/kp1lQWQWbSwpB7+uSCMdMDnaM+5+SZtHk0rfp4nTM0eszwyVbFt1vpu5m3k3+O9o7KI0ucgYS1lfGeb8sJ3Qts2UMp2NgEl4anrDxXnMSXa5JQsazW0BkSg2UnU9VJwxEbTPyZtO0bTtGjbxidU9D4KWqOulzobGNooA+hkLLeNp2h54VVVzrE/jfBloET0d6lGVZIk0dEzvdKB6G9Ix4WEEU4DGy2PXFQqlqhxUWpDcg9YZKrRphGquoKUsc/UtrTjqQIFcDQyE+ardf9jbMHOZlBbJ5TwtiA+j7S+BaFMSsAnojVB2DPd54spKaytsVRXQSghLLoBzalOs67LN7dOgCifdyBULv7sGGvRUiTEgj8PndPZ8Ibn3AknSZvpPi649ucBYdYDTqVyZbnNNIAgBDmFB2tTVsWiapySI3sOXhb1a2FH/ew5IApXeC4++krXjp99O6Y+8EDwrWF1mVwxZXPSbLfPXEDhgQASWhqcYEJt/FETTgTS5K0HWsaAxbAhBZJKiphYkD1R+UPetzDnHNRJ4/xGAGDfeIzVvavY/L3rob96MvbrkyAqC2C+QHLAsAb32v0tnPTDL2O5+SHuOvEkfOe40/HD407EWjVGK2NYUGstuMrEvQu9ZrB1lgJVq1S40Da8l7V2Akhwam9NsKrwTOv5hpIsETxCVsk/JHV+dqFe+6MwWb8hVMnvKITJzRG51BJClB3l1/8ic1YRfv2sTX34zrWTBQHDgm+A+31eOu2Z8/KeJYTN9t9Y37iU66b73PVhoON94y9lhdFomYV/1uwYhehWQXBx9eTCnXO2T6N9pW2he9i2U5bxXQJTQCdRw5xA5L95CyOCMEH+VNOJCzM8na4lwr+UUSBw0bc02nbqwwNXvg7lLCfeQZonGOVO7brRwZHctM4xPmxKtAA9SqGfBhAjiaqOIX2FiKGC7TRuFOM1zkGcnnfyzaGwwG5DbxJBwRgbnMY76FERUkStUEarYaSE9Ikl3Um+P9ERoHMPCdGiZjFLy0MbUmttYpvLHeM1E7ZatFBWAcpiSk74UsKyNyht9GiTTlERR3UMuZ4nvO3dpM5Zm3LFUh6ty/nUlK3CQU5bUDBRUmKkFKS/vjUmWBD62lna8NK45P4o9JuwlvkozEe+hne0/AXrCJAKpyZYZGLbXDsQorSVpm+uOOhD356j1BYgXXlLY7vIPVP//Kq0DeddgmnTzLxXrr74XQiXirQvhDO38ADemuJlOAk+5pkC6Blvi8f27gXwzrn9GXD0YEMKJEA0MYbFREqIBTagPCJTqw0mraNo3bXfUbT27tmPY2/5Eux1W3GHPqm3nFNu/3csTfbACmDXcQ/E/mNOm1OxEzruNfkO2mOWoIUEYLHc3oFjJt/GLrEJX7nf/XDL8feHlRJt20KIfcmCZrWBtUg2t4JbNrRJousAcbMR9iLaCSD8ZVzVFdqmhaFNmX+jcauEE0Za8OzUs5zV6WXiNneuXNKK59YOY0TnunRD3Y0WRSDNXv7yyoWJ9Jp+B+z8+tzSlJ3U13n3D4vsk9C68nHLNtt9gshsIWOelWI+eoW//KVqU+fz9ZRFMEajaabJb8l9ESKhOAnnYukc1QFU9SgVVgp1uuhg2t9H4X/T3XP55iqJ1ke/SbRtpIY1zQQ8wAEJ1ADQtm2ggfH2O+EkKgq01i7sLxBoUdFqECPikSbfFVgeS9dGf06rIep5lmEAPGeQsTAwSX4SKV0IXM3C/prM+TxsjtlQCoGww5NSQtUV6LYKbxkRUiQheHMhZCFwy1KBnuYaLRByldAm1K81QgNWxChcVhi0jaPZEh3OIFJ5qdzORnU6hbYGSz53zaiqXKhaf84iG8xFHN8J88II59aBeVBS+Nw5kXamTWpZ6qsnavtNIhx01srC8zkrC32OzrnrUKjkgonw75LOnMnKzKN0hd/njEvHcbznWsvKTa05ZQGn/ngqhFi/8XcRtuaPB78/RGHTiMIYUfMI2ljULHgQD11CekvX7nQdBSuzY5W5B6JEbz2QMgYshg0rkNxdOHX3l3HWdf+KS9vXdI4tTXZj855bcdrNl+HEu64Lv1sAd57wUPxg++MwWT4+2TgsNbtx0spXsH3Tddh95vH49IlPxT65LWg/jT4JwIN9xBeEXCADBgwYMGDAgAED7h4MiREPLzakQJKGPiStqglakH4zeaq9WfNUrd0rK9i7bwUnff9ayH+/E/86fXXCCFga7wJQ4zFffBPUJKNuCQt7wgj7TrW469Q7cMcpI0yXlkP7gK0AHg9rH+eEkEYDaIKlgjuW8rZZbQGVmZ9NSjOw4RrfFFHmvpbGg3jmVK+yCoZrA42zTMRzTGIViZrkWVYSmfbJplmmY9uofRqA6VzDfVVoXOkKYUmznpbJ6VfddvW1uevEvrBVhB2zLI8HjV1u4SFtVMJrn6HpWtQ5fZ4VBb5Wf/ZCZZbr6VqqZh3jv2ndQOsmfKeEhjzUrgtIUUW/DTi6IY2t02yllq48K7sxTg8oWCJT59sUtWLW001MoOk4awqfb5Q8kayDUqqEHta2LShE7HS6hum0wWi0KdOcZY7BxvEf2qYNz6KqlLMWZBbK3LcEQOLEHsqDWwVtZWFaZunJLAnRChnLt8ZiuuasT/VS7XODZFbDxLu2PMeUUjE8rxSoRhW2HLsFAFDVKtDC+q2AxZ99gfEcaw1AdJFCVvpQnr+N7jcDoxnlyfLnXUJIQDdt6GeFChosQaxSqSO3tbB17eeQ+00bg6W6Cj6OfeFk898W9f1YRBvLqVulMnkZUrhQxjws7DxLayn/R2ox6Xv/2nVlSl/U4ls672C11qX5yRMuLoLcSlZ8n2D2WtoH8bH/GwCgz7sY2qQUuXk0QWttoGoRGt1iZTLBvnHc32wejXD8Fv/sKoVaKUiR+fWhO8fIGb7H/WjAUYwNKZAAkbJlw8PuzIezeKfWWky1Dlln3QM4xp7d+3DMNV/F9759f2g8pENPPvN7/4wVPBv//vDH4gcnb4eulyCVe4GN1Wa0PlN0qHfaFhcVrXVwEjXeoTLG/ncZsXnbq6qiTrjrWw2jdSKAJAKLd+Q01qbJxiRbPEIeAH+s7Tr9lrKik1CQLnaznaadU3DcuHHevTtOn6OQ42gqfAPf9VOxbkfSqS8eT4URmhNxIQ0t6JwXx0B3XyBzXkYWqbDGaV+hnHXQD0o0svz7LJrVrO+HGuX7H/18Sn5B6VyQCS9eqQqCRbYi4S4v39oYXYmEFDpNSgmt6V6SwOFoU1UVef8pRdDAWsrBQwK5TubP8vIWVNUITeNe3m07AZlF63oEawWqqoaUVWg/+drE7O4yUJVIySCEE7pyP6x0PqVjR8JGuMYKt6muYg4VOp9TtChrergfEomywZrUfyVHKXkhAFgZk9IZbRLBjSJsWWsjPa3HIlzeuHGhF6D7Y1u/rtC7ADE7fb554uWb1iRvSGFFEvVMaw1pZaB9kdeRbZtOWZqEYJpX/h8p5FyHdx65iP+Wv8fmOb2X/BdKdVXBT8slfmy98Npm9LS8fPqdCyLhN14/o6z1YT2O/wldNMs7Mk9I6QR56am2FMmqUyZbqxdxZA4KuB4hpE9wSt9Vbh40514MAFiqKoybJtzDpucZ5QKizfZFnLq1RsF81laxZ3UNU+/j1hoDJQXu3L/P11tjy9ISRlWFTSOiJ9ZYqqpA60r6Ym0x0NA9DQNl6/BiQwokFFbQsEmv/YaFHA0BhMgflOhq2rYYcwf2lVWs7lvDtquvxQ+/9xOwokvSPmbfTbjswWfgUQCuPe0BMMYnCSKtqwEw9S8ovjAUJnpuEaFwm/Sdh99d2rzEfCOoeIuWheF0nO88GpYXzDTLEM0iGoUNQea34ZxYkf4W/B5MJ4wp32Dya7pIhRByFObX2OQFY4LVJv42e0PfDT3snJTDPAj9QDje4b+y+otIXorzfWfcZyaMLKBZm52YsSyM9DnILxJR7GAwS1PYmfcmnQNxk5wmmXNzNWr++WbWBUdI+2RMCyHY3M6yP5PFpW2bRDhyiQ1jIkRugWtboK5lIhRTWGkenKHPkqZUBaUApWpUVY08lDQNm9YN2kZBiFhPO1VJ2SSMkMAilYQ1BqqqkvHnY1vVChDcNyI6eCdO6q1OkgRy0DrDhYWSFjff9EklISsZfDCWtywHvxTACTHWB6Dga5b7N60/aU/oSzzuTsksULFx7hpZ7lsoU0aByLB+0CXaGBgpkz74eGfuM/kjwUIb5a9JQ6zWXqmUOw3n6GvnPOd3fg/ySFzW2o6VRAokyfCmbVwn27ZNyuT1h3HLrCKuz6aTDLLUW36O9qHpJbsmqcd2Q9WSMNInLOV1UDmJYFoQJHLZOoYMTn/j3xfx2yCLSslHpM8alaP++KswPeet4bxx07jEkwuEo+fgY0mfV6dT7B+7QB27VlaxfzwO0dWsdc/BeBqTzgohsHk0Cv3ZsrSEYzdtwrZNm8L3SqnOXL4nYxBIDi82pEDSeCtHa0x4KVB22FZHjbq2JjiuA8DqZIqV1TFW960CACY/3IUzPnUtbq7OBrINnNRTnPDDK3HVDovV0WYAQDt11gkjNISSifaxqL3MtZgFi0jQSmoT/EjouJXChbtMHG1Feg2rV0rpX7T85RCv499LIIdfo43bMPlx07pJhASOWUIJLcbp5ok7RNPmgqJscWGEl9O/URcg6o7pnJ8LNbFeou3kwlHBib0jAHXbkveZ17+IMDLPElKqLxdGSMjq0wweSpTucX48FUBU0lZHeao6NLxEQAFFrWqTc/KIbRwibLTgr3XRroxpUddL/phB23IhzgkklbdyulDCMhF+Yr4Hbo1oOpZEAKjrTQBaR13KXnZ5vhXdakglA1WybVLNe+ufh/js+lDfSkbKVkZXCnXRmsGOL212Y6AqhfHKODvfhvwk1it3yIqbDCqdjy6Ut4BQxK9qVKFeqjHaNPLtLy8+s6YoF6KCYOLpbnyup3Q4N2aO1RWFSulpWbyP4T5r45zcs/VUwlnMXBkWaHWwlNDm11gLy6KfWf8eAoCl2mmRl30kLpVle5+FWcJIrsUvCiZUjv9X+Twgi2ygShYR93usrySkhnqzTXhHUIAbozxnWGmj3k/vK0fzmmV9obmipGTO1+V1Mo8INouCxMui7xa2Q/MqCXuxDNE5b+1p/w+Q5dkqtnXGu5n6R0JMawxWJhPsH4+DcnZtOsW4aTCd+LxMlURdVZgavwdoWshKJfd918oKNo1GOGbZUdRPPOaY8H2pqhKL24ABwAYVSA4axuC0S/8Nu3eehZu3PbVzePttn8dxOz+Jjz3yiVgdLRe1PQMGDBgwYMCAAQN+NDE4tR9ebEiBZNq2kE2DqdZBCm90i1YbTNs2aAsarR1Ny/MkJytjrN61D2d8+Av47uanwGwbdco+7eZPYnnXZ/DBn3wSJqICmhYVWThaDW1cVmRpASuIrC4AkzqXh9+RaavJ+dRbR7hPCadsTSdNJ4SvECL5jbR8XItINLKg+QttSPuZaG10zhd3XPfWJ1xMrSOp9r9rIcm1/eggt0yQMtf50KS+KjklqRSecVGza7etOZ0s49n2aCj7rA691qKMW5ues5jpPdey5X4Ni7bx7gLX0PZZCvk95Y7mJeuihXE5O1gZuc+Ju9YkvymlMJ1SfpMGRmuf0ySe7/w6yNrh/EvIH8RpzVWwmLhrIv2RyuC+HqX74Mqxgb7k2hOpYc7SY701sk3K4UkbrbXBDwWA0/pb21kbaB1pvIUiH1shBOqRK0dWCmqqkjwk/B7oRnt6qe48AsHiyr5Eyo+G0CahbC1tXkp8VYLVtECXTL5nlK6kcnYcQMw8n6iwHYWLLDzkG0IUWamE93VIrc/Spv4PQqo0RLFztgHg3kNGKVSznluka+RS3aVw9T2r+UYnpf643Bp9uUgAdBLfWc/DCQyCHo5/sg6CaFnd+5VYMzLKFm+LLFhttAFa24Y2KCnTMLOFd0selOZA4fxPu793LBYLlBXGIFvriKjQ53eyqJWD2lCygHGUymvZfW50i4nPb7R3bQ37J2OMpw3WvFV23DRo2jayL6b+2ob2JwZoNZbqKlLgJw0mTRP9UFZXsXk0wrbNm7Ft0ybs37ev06Z7HA4BZWsm7WRAgg0pkIybKcy0wqRtQ3bStabBtG3dS6KlDYnBdG2K6dg9MM2uPTjli7vx/a1PL5Z7752X4ivH7sF3z3yq9zA1nsrg6SONdv4rxsBWjCvp98x9JuySudVacmr3m7SMftVOW+c4L5BEGnI88khDyJFvatA6KgtvmmXCkwnhhtmLLEt66NrUjX7l/u2nG/W/OKLTrqsvbvSM0c5fJXdk73E+D9Gq1imQ0Dj1cbeRvWRhbcgrMq/cHDltrURBWKTcvjGPv83Pr3Ko0ekbp3owAYRv2qNwkArSnN7gzk/r4UIMfES0jvOvMZhOnXAxna4BcIkYaRyUqpKM6W1rnV8Y811x1DCJEiWL10ORwtz5sV1OYGzTPCpCBuoj4Kho0+kYUirm+C4yilrMYA846mdYN9gmWbcsSaN1zzbPhC6kwGh5hHpp5OvW3uGfCfs2zcpOCpLQlnL2uJSao10uk3o5DRjAnfTz+9U3viXMUgQk65u1gA9YQa0Lggmj9RljONPTjWGlQgJIylNCiidtLYwwLoEiACiLlvrI13WlgpM7+ZbQcW0MlkcjjDDfr4SjV/Eww9HaWovWmhCJMi8jj7TEr+Po5LCYISiVysgjkwHOX4UUhoATWjaNRtjs56hAV2jNcSCJBaWna/Hyc+pXeIcuMC/DOuLXovAcCsGSMs6+lqOj2MjPyd6/ySEmPI6baRBAxj5p4jgIH1OsTqZYm07j/dDaJWWdRtqotRbal6FbA1VJrK5OYp+bFsootFN3zqoQWFsehcilKz6324ABhA0pkKxOp5hAYK1pwkM2GU/RTBu00zb6QrQG0/EE07UpRs0YJ3+lwZ14QKe85eYumPYz+Mfjt0FVpzj1DYPx7w1jDYy2ACTQ6pLZIf3Otbtsg+BO9YIN+24K3ykkKOA3BYZtNlobNhxJexnntNeSkddr4wakbRs0zTS5hsroWCx6NhflzUPqNE4OyXzjSsIIf1nQGMb2ppG3un4qzik5d+RnjaQTs2tY3w7I4hKd8kM9hQ3YgZU7e5zJOftwoLSpLCEVLkTv/QjHcmuVMBCgaFHKbybzua7D8+7CCbcwJibvzB3oXeSrOggBSlUugzpLmEjWQT4vqZ3u3zr5rlQdfFuqagRrZUj6SJnapZJQuu7M07peQu2j1gglMFmdwNppKMtlmY+hkGUlO5sWa2zIzO7GsnsvmkkTnLONdpbZcH8KDub0myj4o6WVR6Gkqits2roJm7duDt/TU20Q9sLYHgDNPAocEaqumCLKsnN8P5AJyRoAS05Jc1K3AMiJXZPAm67j8R76CHCK31MvCPgxaaXxoYDjGEshoLLN6yJ9zhVb3Mch18YDUZAQMv1dM815x9IBb9Vhm1tro/+BsRbwSRT72l1aqyibO2nXJ22DSRMtJFIINGzdX65H3Xm+znV0Fni0rqLfyjqFZmMtwIQ1A4RkkzxbfHivsTGeZznpa38OsmKtTCbYs7qKu1ZW/O8Go0qF/rZaO/9bExN/kqKjmVIUQNcm8ikxrYG1FYAYFrhtdLCgAG6t0K1Gu0lj3DRYXV1dqC9HElL0C4zrKWPAYtiQAsm+tTFsqzEZTzH1cbMna1MnjLStFxqcJrAZN1C7xjjpFoFd7Y+lBVmDE8efw7+pNaypYwGf54Pi8hNIkUWOnv5XCJEvWmnx4bgQyPeKpNVLQ23aqAHRthtfH1FD6s4xgBCJAy7XRoZ/5yxy3Q2J8RGMAvfMl61nLtrpb92IVVxbCgBS2kBdiWPSL4gAlH17thO4u0aCU8O4NlhIF2kJBixstO/bOjbasc0znNh7tZDzqVrdl+KBCxxpWYu99Eiwc5/T+zD7upRG13VEF0zAiPdUqa6GkM9j2txTO6x1FoemGfvfXFtJGNC6hRA1hBBQqvZtSfN3VNUIAiIEcLDWYjJxAnkVIiRVHWFJSgmlYr4hKk+pyltcnOUjhtl2oYCjcCNR1yOMlutguTDaQCqJWjjn83pUox7VYe4G642SSW6RahTrUZWCVKqjpNCtThzZk3WEFBL+1nLqKFkQihYSD6q7XqoxWhqhXqrD71z44GPXFzZ4FhLrG/ud1sWOgAVObbOOVpuv2RRtkGd0z7LIC3YPpZWg2FAh+pmNIYEBQAsLlWW1BwtYoHwEuTDXWZb0Psy1QiDSkMJG2+cWoRCxtZI+IphNjudrrrGxEBJaSHCwsLDaOitDRzDOFHmkSTcG4+kUk7ZF4y2ALj6ADt8rGa1KhKWqPmRCCY0Np1Ql82lGuYs62gtkdD9rE9qcgWBCEHeAP3BBiwcZIGvT6nSKPWurGPt1cHUyxaiqsFSl66ex0QJibXxeAaCdurWVrB+E6aQJ5xhjoJs2PB/WWKjK5TNTdYXxaho4454IAdGxLB5IGQMWw4YUSBaFWFHY/J1jUO9dwu7sWNXsx46b34d/OPXHAKsGGuCAAQMGDBgwYMCAAXcDNqRAsmdtDWrcYLI2QeNNitO1KdqmDfzqau8Im288DqKQCWk03YsHfe0deO+DfhqUsCzA2sSfAkCIVU+aQ9IuztPeRO43/y1Uk2giyTpCRehWo1bSJ0NMtdSBkmYspMoynxcpXDZwQ1VOo2B94pYKIRQiwTr6j3QpWf1a/I7mzehEi0YJ6JSifrUgR94wdp7ryx1/c62r0zrzdqRUsNxqETWBMdcChZnlYX1L0fRL1pG+ekqYxYvusz4tQh84lHSGRcAtJiWrBvl8uO9lrjzdU2N0kkCwVI8QMklmqLW3hjIfC3oOKBgDAEihfJLCaG1s22m4T0LKLlXMWjTNGJSrRC3XIdEhAJ9fRPhnhNqYWoHIQhL8vbIEmVWloKoK9dIIlXc2n65NoZSClVGDzTO509yvRlViOarqKviwyEolFtPQJ8Q1wPOK2Lz15xUcyRNLiSzTwQiqUqhGVQz7W6BsWWvRTJtoncnndsdaG4/31W20QTNOue9di57PzM6c3BPqoBFJSODYXgHb0vqLDj3LUbwQTCSNNhBKwqpyeGrl/SYEozyNqmpu8sTSc5YfJytJXN+cZYOcmxuWAwtAYvUwNvqUcItIq3ViVfG1Jf4nPqZL0hbNQvKH4DJNE/JcAEhyoGjl36tM43/MMpLEewezxpEfjfLvDm4Z0sbAWBP6mI81z23GxwyI2nEhBEZVlVjGJO09eu4n1XOwGc1pvIl+NZ5OMW118CGZ+LGn0NOjQkherbWjfqoY4trqNloBvU+daU0IBCGkQNu4QBaAe3bbaQuzXEO1Jvju3pOxaECceWUMWAwbUiAZ71uFQOX8Q/yLiOha1ljUe5ex+eayMLI0vgs/ee2f418f9FBMtxwD5YUY2PTlzBH33s7PwiBN0jaPZiQYBzlZ1jsbzbQs05qwOQknZBQszRxRpYxUjigEOMdNS+0V2tESssRKPJIW5WHgdLJu5vJ0M943FumGPT1fGAsBA92KcDxPYsjbVwIJUulxk1DBQplZZvmk7aLgsC7SOvv6Fq7reWEuKoT01UN1HRoc3NuvM7cLQjkXRvhvaX9aFnGqChQWvtHOBUI+Blr7CFyWj5MOm3YAUEqhHi15H4+4qeFRnipVOUGDxhwW0+nEC0veN6KqMRptCrQvpZyQQ/W2bdMRAqi9MYeF81NJBCwviJBSZW2/c8KnjbxTPLCNn5RY3rKM0aZR2ICrSkKyABtuHONUpOfa0VB9u1i+I/e930cpud9eKPFnhOPU93qpxtLmpaD0KDqw+0AeszaXueKjNMfyq1PBJSakC74wyv/mzzHadLLVKykTQc3QeTS2yuUl0axOKZ0vIAUeUZWClGmWat5VJQUa7Sha04w+yCNMAf2CCfWxdEzbdCx4GUTRMuw5yqlLgE/4SBtwv/YuksgvT1JM+b+mrYuGOWFRnIQQyRgJIaClQONpR2OBsLknqhHP+7IeKCmSAALG+nxlloQuF52TC2SJwisbA+ojz6NSKYlaRVrUqKpgLKDYM5Ar0qguXg+PSMbRR+mjtrXG5WajtlGSaCBS19vKBxCoWL4noltNnfDBFQK6aUMiZimlz5kU35P1qHLjMiUBxd/HxlEyeRLneyqGsL+HFxtTIFmdAqZBM2nQTClxj7MkLO3djK23ndjh9dXTfTj95n/DvX/wKfzLTzwO3z3ldIimjY6KzCrSt+i6va+FNYBBf7KiXsGk8GI1BesL4F5+xpiOUJXPfb5AoELgN+fK/fAi0CLdgBTalm+0yYmcNv+lc8hawPvmNgTRUTEKG7FOIWR4MXAflbRcXrbTWpbAHe7z7OB5hKz8pdMnVJZf/JnPyAyUI2qVo6P1lpElejwwHNi13I8k/b18D6QsZ+pNtdbGb+aiwzqVqchPxO+q4zGZbOiB6Cifb0ZJkJHKhfvl7VGqghASo9Fy+O7+fKZtrdE0U6fx9OdU1cg7wqtwjZRVsMRImVpvCO6Z8QqTtukIVM3ErWHTieNaN80Ey8tbIMnfpaphdRXC2lJfrbeMAs7iyftHjvzh2fUbbwAhcSTImVmXBe7Sb2Gc6RKylggRNjgqc7iPz25sy6wNNYAQJjd/NrsCbdcKUvJzCtYz758TngNrAcio7RUCRqeR3aB12GSF/igZbGEm9JFt8KSA0CKudcpp46lc0Wa+JR5LdZw/uWACuE1Pab0qJdcLwRaEcBYOf85U6957TNYUIIaLBaJ1gNcX1vOsqGCh9MLH3rW1WEZP+GDe7laLILzF+qIMXPWsLSUkvmdsDSDLTaN1EJjIuZ4EkqZtE8UG9YkjF0iEEBgphTEJJEpheVRDipgIc1SpMGitLgTFgReCZzyHVFd4X3nrVat1aL8UQMUsdFZbGK2D4oOHDCd/L/KbbSnqmZTQbBy11piuuUAfMjAaoi8J1ePK8r/r7ntjwNGNDSmQTFcnMNpZRUggscZg056t2HbnSR1h5OTbr8SDrn8PKjHBpY95Km46/j6QAIyIzrfk3Bw0pT2bVWvhSETMW63XQTMTCpIyedZhpMJJcg0P6yhF8iIGMkHCO20Ki+hEL9MFrPVmXBPM99F0zLW3AKfURGEk3fSb7mY5GzdHVUk38OkGwsCYuLDloVbdtf3O7rEtXWGGQ0AGi0fp3uboe3HnQhh6rgcWF0ZKda5f+DgYYWU2UmuHKR7L507efm41sX6DFiNfsQAEtJlSKpnrXBPvvpc3J/x3EmaMMUFgIOFiNFoK57t/6XlwQTJGo01BIKnrEaqqYu3lVC0qg21arYVS0kfv8mEzveN+jPol0Ewd3ZIEm7ZtnPCvSSnR6R50q12Gd6JoZRYR6m8YDynYZpx+kwB7Xkqb/TieKTUvXMOoKiHXSiYQhOh9mj//yan+9/idFDE5aM7wi5I5VrDGcMS2s7XT2mSdpOiEyZrK9o1RfPHfLaKwp+maNqG+SAugArRf45Qw0Ea6TfsMpYfM2tG3SeWWC+Xph9qUFRglBQpRl7QxMVqdtbA8+lImhOTrbHB894M5aRxFaOI3t3S8r59ADJtLEMJbLpoGY//MbBqllo7y85+OqaLyieZsDWufVxZoZ82hCGDUXm650v7dJEJ7NVYnUyZsVGikROX7vFRVaIzBiOVWabQMsRMarWEKCsqgdGBj2xodBDknYEUKmmX3hlCrCpUPYAB45/PWBMomnwK0f6pHNaQSYR5b/1Byy+tkbeKiBfqw10LqZF3WWsO0TvAhC8s9HQNl6/BiQwokJWzecyzudefJnd9PvfUKPPD692J52xR7HnUyvrXtfsCkKZQwYMCAAQMGDBgw4GjAIJAcXmxIgaRpGkAL58TeGhyz517YtuvEznmn3XwZHnrHe3Hy/7UHx+yY4F3qmRBTNgF7JiPRIghGpxp+kKt17vyeaf9SGli3juRfk/txRE1F4Dnr7rHSA8U1jtbYrqXGO58BXoupU81ZHt7XX9WxQiQ+IcyEzPvVvaZAOzD5+HKakgl18WtmjSVvD0fwSRBlDWzXetH1E0rGZt1WjG6bZ58zLzTw3WcV6UPJQd3Nv/mLMvft4PQrSYnKrA05REjzRhYG932UzA9KNBi0opCJxo5rS8nasbS02bchpVg1nu88nY5hrcVotBSytVOekfw542NRdCRnWuGqqpPcPuSjYowOYYoDvSjw7FXC9waYhWQUHd2NcRYZ36quhaOgKS+9Q0tWyJKli3+WSsaQw95SEtZOiTRwR8E6EuuOn5OklCVriU59YITs9jG3mJA/Ca1PlLk9EAC9xXumBdoCYNQeK70lJFnTXBLaUHcFCA20wnPxhYDQGkoKSEZxUlJCtlGjXElZTJzILSLkjE5QoZ8xZ4hM2t9NABgsJNYG3xitdQyH7uvgc4NbVegcog0BLhHfntVVmJb7iADIfHastcFKQLS2mCOlawmRUmKpihTFfHRK73JKZEzlNrrFeOqsN9xCQpYIwPm8AECtyBIaf+N+LDyPR6M1KikD9U57n5NWqXDNUlWF+bY2nWKp01oEHx+6r9OmgbYm1G+MQV1VIZQzgYdhNsZACQmVWKAFNFmAWu1zoAHKB6Cw2mBp8xJGy6NwjbU2Cfsbgut4q6BpDWQlkzXKtC65ohAi8W8dMADYoAKJbjVgJEyrccyue2Hbnq4wcsb3/gUP3fv/wRlPvRNqZDHGEm6Q94eQqSMd/7cETjMw2gZOdlkQSF+8nXKMLZzLXjBMgNHeB8It2pHnLCTjgmdIKBU2/Ji2w1CGeP/Sak0QhDgdy1ExaNPTJHQq95vpJDDMN9A5xWlWe3m56b+2IyAVBQ+RvexKFdLY9NC3uL+Ea3fcNM+igy2C9Till8bynoZeH4AeagYH+YnQfJLC5c5w2c/TaGocLq+Ij5PfNt4vg9G6KueDwvOeUHSu0WgTAGA0Wk7usxNMLMZjl0TMCSQGQmwK1zhhpJt3Acnc9xtdKRPfGO7vVNejIHy03sGXU55cDhODtok5UWrmkM/HmAvzbvMQjwshAjUTtPHLsrDrtl9RwOvhZfJ7IqVANapxzHHHYNMxbpxUrRJqmDVuM2gYPZUf981L7qF73gsBJgBGb+0qXTp5UvgJrC/p8yxA91AA0ek/o8kGSkob77HrsF/fVBx/I10m91i1SjKn0Wa+1QYCcZPbcYytKljYNGkeaxclLCQBQ3kBRoiuU3RJCKHPXJgwRNkyJjg7Gxud4cM11tGzeL4TSnQIuKhOutFMsPZ90AhBWoKc7F9U2lpMrE18H6athkAc/7WpTxjqz6l8/pbcb4n6QP82WgdhyTl/t5i0bfiNIpFR3g5tnCBHOVLoNzfOpPwQ/j7GMrSUcaxHXpnBFC+t1kGIWptOYTMaKrW/1TomfG4bGIvg7O8GZhrGgNpTqxiNjOZA3N+4yygxqhAC7bRByxLCAs4frV7yyoVaQTUKygsbFDxItzqU1wKQprsu6tYAmKKZ3POjbA1O7YcXG1IgaRsNYS223HUctu05oXP8rJs+jB1rl+HMJ90J6TPk7hbHw8oKQjTJHp2yn3OQtQKgF2TUPBhjnON4WSYI11A5/LfOi99GDnP+Ii69ZIUQEEZA1VGQ6ry4g6YvXYySOrMNDSVlzF/a/F9uIQjlMJ+SUv9Km4qulrn0MHcd6nn7C4X2ajXTUrtllKxLoe25YJNrm8OOqEfggkBJNFpUwJh93qEXUorzqXDOLJAloStERmGDJ0QEnPXACb9tuIYSFXIhM7GG0MbSmBAyVUBmlgyBpdEyNm3eyvxBln3bPMdcOed08uPQugkhe7lm1gkwsVxrs3nJxid9bqj/qcWEylWqCn1WqsamzVuiQGKckoKS+ZH1J1WSmM6mBoiOq6Z1PinViAlpNg0uMQu8L84i4r9LiXqpDpG1gLjhIZAwQprSkh8HKWpsLtz1rKHx3zi2QqTnhXWTPb8dy0fw+Qmld2183qpi8hdEgI+6ZW3YaKtKQbc62fwJEX0fwoaWtUUbg8YYgG06jbVByODnc/+QkvCfr7+6cI+5gzlZOshHAnDCgeC+jWxd58JIDOvbYtrqYC2YTqaJwBuHs2C9o5G0ElZk0cngBAPJkkq6rPduW7Ncj1BlCRo1nJ8IWRQa3aLVLASxd2p3UbasP0cnzxQFAihF0tQm1uUSA8YNva3j2jNtW38PRbBUaGMgfP/2T8ZorO2ENTbWYmUyCQJJa5xQ1ppUgSb8XFFSuKSSJibjrKRywmywmFhorcNz6PYWMggmADDJ5lJVK9SjOirx/LtvsjYJSUArIIkCKlUMoa5b4wWTezYGytbhxYYUSEyrUU9G2Lb7+A5T5L7fej8q803c/4m3QFbxYfmBureffAgaq1nZh8MCrOMLyWqv8QMgrOho+8K1hVj6uQUk17gbY7xJlBaAQjZjX51mofg4g8aGl185Bv4sdELyCoEkeowQblNG7UZXsOH9KSF/+OkFVXqpkgbbGJNoO4XfkPVR7ajc+f3tviyBNKu40RrGxszawqIj/NhEVTt/g7cea9E9F/OEEunpVrTxLWu8o9O5Rts2fsMdfyMhxJXRwBoTrINSutC7U9PNB8TLX1regtFoU6BfEX2raSahnqaZYnV1HwBAty2WtmxGVY2CkFKyZFA/XZmyIxTQXI/PeYvcShY2OV4wU6qGqlXcwEuRPN+JoBNoUbbjLM+fMwpawcfOZBTNHKXxdGE/RRLelv4kW0/JKuL65zc/MyzRTptbnh9xnPIP3eO86BDqN6Nyla6O9YruGX6dCes2CcGk1dca1rpxsWG8DaqqCiGdVa1QKYWKaG1srnAhzBgD8osXtEFmipnSGmmsxYhpyhvmuO3+LecI4VYELmAkoX2zc8Ixb1Fxlgc3b6etzzMyds/UhPJPhPLYu5Yp4BL4XC6U58W1U0IgFdJapRJq1VJVuTwuHtoYjJsmZC1vvbDF37f0G7eiWNg4fsYAxgaKEw1irouyNobdL1kZtTGJUKnYmrg6nWKqDSZ1He6htRaNcVntyRpEtLvEgsjqqZSClqmwZFQaIMblD9HRqd13i5zdCZO1SRCkw7zz87Ya1TDahfKNzvEuM7vI3n8USONH53024HBhQwokALD9llGMjOVx/2++D428Be3P3Aub5ST8biDw6fpJHUvIgAEDBgwYMGDAgKMPLmLZwZcxYDFsSIFk+9fugt30gOS3M773LxiPbsenH3senifenyi7rlMPw055aghluB6k9AHjYtUbE3IDAGXtVaIxsY6aVaIzRedNZxUgCpRSda/ml1NFJGLOASEAKHQc2RONfqZB5drWWE6aGNHRYBSE0JE+kjIvkutLY0K/LWK96NC6ZFcDPY8aNguW5R7gyfcsupQg8vR0GcFV0gey1IT6c0oX+mlbJfByZ41lzn8/OPCyF9ea89C33PeIHyO0rQnJD933tmNlssagXloO98MEahI9Jy5jNI2vc4SXwVrhG5NYz6qqRl2PknOsdf4isS0N9uzZiZWV3QCAul7C0tJmLC9vCdd0rX/dseBWEyltyOoen1Vy2mdJ6YwJOU9c+QZr+1eCw335GYr94OhaNyPlqWSNJaoUgOATl5+XWIUqCSFl0KCOlkcYLY+YM72zXFvbzT/A2yZF9zkuUVlNJ2AIc0C37olK51B3nEq012AdaHW6pkigZPlLx9Vn1s76J4SCFZHuJKVMznHrTKT/1Yr7mCDkAIn9YXQnRf+4NZBTuFrmn6CNBWRM9BfKZu002Vgb6yhd9BvP4M7Hmof95dYRokVN2xaTpokWBX//+DwSAoAQRZoj4B2tlYXyHaY8XxaWhey13h/E+5Aol++EQvsqKdEaHRIx0jXUJz4G5HTOx5+sF6bNtPuaUQszixX3k7HWBvaC1QZT73/E/T2sNqgArE2mkEqjNSYkyAQA7cMS81wwk7YNDvbh/tCaAQugCk71gPPtaHQsw3rrDllGtHY529ppy54HAyF08Pswpkr2AIBLqDjaNIrhoRs3T0MwCxv3FoeCCnU4IBCfzYMpY8Bi2JACyT59XyxPV8L3ulnBXvttXPmoJwGmxXHNd7GXba6+r47FxK66WNxNg8ZHjmgmDdrGZSglx0vTOvOmNnFxMkZgdXUVk+ka2tYELjdFl8gnZKAz6ZSyRZ85YgQvtyDSAjAapeZPwHPIFducCwHdpBumqlYwqkKrKTmcoxRwCodpTYgR3jati1ZmdEiKZEwLY9rwnQQl9xdN6Gm/TOIgR+0tfe84wWk3vnnehjheMUIIr7v0uYQoGNI/BgIUp70spIas7kSjgESrp1CokW+mk8/s5e2uE34+zKe0xXK6cftLlAB+zrxyjTFYXV3t+uRAZGX00WIsOx+hP1KqNCqSdXk1+AaHcoqQX4gTYqL/UV2PHBVEawgR55NzSKeNvULbThFymRhAw81JvqE3RgeBSKkKWuvkOldWGwSGfft24a67bgv0rE2btgZHd6VG/ooWxjRh05s70xtjoBT8HNbuORA+Ipafxy7HSNN5RqqqhhBReHFRjfxz2AIWzEm+UjDQUDYKBsYKiEaGjXcQtNjzXdUK06kO90y3BlqblNpUgJQC1m8QhRpBWgPh1zxZAVAW2rYYrxFtBQlVwz0O6XwiAYbqJMoIV964scgFFAMp3DoxHq85GlC+4SkJcPwz72fYNPGfxEwaL53DqxM+g3WgzEGgWq5hPdVI29YJEv665brGqKoghQh5OwREQu2plIuQJLlAKNw55D8xqmpM2yYIBdbacL025bWSBAtj4+/cb5HWiH179wZqHl1DTt3kazJlUaqm2mCyMk6EvVzwyOm5XYqjS2Qa8rdICQjnaE1Ow8rfL3rfKr/ZJ8qgtfFdaFiftI1R2UhnxGlPLdGbNLuGBYGgtpcivoVzMl8WqWSYTyEburVAq3HM6ipWdu2CrCrUUiaUM2pvGG+b+s7lkdeUEKj8OIRnCwKTpsHe/asAgJV9K2inGs2Y/ORcvpDWJ5MOZVUKU09lrSoV6J6AUyTQvkZr73eyNnHzriZlDFNyWovJeK13vAYcnRB2AxH5JpMJlpeXj3QzBgwYMGDAgAEDBszA9u3bcdNNN93j9m179+7Ftm3bcNeuXTj22GMPuqzjjzsOe/bsOeiyNjo2lIVkaWkJ4/EYk8lk/skDBgwYMGDAgAEDjghGo9E9ThjhGML+Hl5sKIEEcELJ0lIppdCAAQMGDBgwYMCAAQPuadhwAsmAAQMGDBgwYMCAAQeDffv2HbTz/b59+w5RazY+BoFkwIABAwYMGDBgwAA4Ktn27dtx+umnH5Lytm/fjtFoNP/Eoxwbyql9wIABAwYMGDBgwICDwXg8xtQnoDxY3NN9Ze4pGASSAQMGDBgwYMCAAQMGHDHI+acMGDBgwIABAwYMGDBgwN2DQSAZMGDAgAEDBgwYMGDAEcNRLZC84x3vwE/8xE/g2GOPxbHHHovHPe5x+NjHPhaO33777fjVX/1V7NixA5s3b8Z5552HG264ISnj+uuvxxOe8AScdtppeOMb3xh+/6Vf+iU84xnPSM792Mc+BiEEXv/61ye/v+lNb8KOHTvuhh4eecwbYwD4+te/jvPPPx/btm3D1q1b8djHPhbf+973wvFhjGdj3hhfeOGFeOADH4gtW7bguOOOw9Oe9jR84QtfSMoYxrgf88bXWosLL7wQO3bswKZNm/DkJz8Z1113XVLGML6z8cd//Md41KMeha1bt+Lkk0/Gc5/7XFx//fXJOSJkT0///uzP/iycM4xzGYuML8dLXvISCCFwySWXJL8P49uPRcb4Ax/4AM4991yceOKJEELgmmuu6ZQzjPGAoxVHtUBy2mmn4c1vfjOuvPJKXHnllXjKU56C5zznObjuuutgrcVzn/tc3HjjjfjQhz6Eq6++GmeeeSae9rSnYWVlJZTx8pe/HBdccAE+9KEP4cMf/jCuuOIKAMDZZ5+Nz3zmM2jbNpx72WWX4fTTT8cnP/nJpB2XXXYZzj777MPT6cOMWWMMAN/+9rfxMz/zM3jgAx+Iyy67DF/+8pfx+te/PnEAG8Z4NuaN8f3vf3/8+Z//Ob7yla/gM5/5DO5zn/vgnHPOwR133BHKGMa4H/PG90//9E/x1re+FX/+53+Of//3f8f27dvx9Kc/PQn3OIzvbFx++eV4+ctfjs9//vP4xCc+gbZtcc455yRr7a233pr8/fVf/zWEEPj5n//5cM4wzmUsMr6ED37wg/jCF75Q3NAO49uPRcZ4ZWUFT3jCE/DmN7+5t5xhjAcctbADEhx33HH2f/2v/2Wvv/56C8B+9atfDcfatrXHH3+8/Z//83+G3x7xiEfYz3/+83Y6ndrzzz/ffuQjH7HW2nD95z73uXDuox/9aPvf//t/t6PRyK6srFhrrZ1MJnbTpk1JmRsdNMbWWvu85z3P/sqv/MrM84cxXj/4GOfYs2ePBWAvvfTS8NswxusDja8xxm7fvt2++c1vDsfG47Hdtm2b/cu//Mvw2zC+68POnTstAHv55Zf3nvOc5zzHPuUpT0l+G8Z5MfSN780332zvfe97269+9av2zDPPtBdffHFyfBjfxTFrDt90000WgL366qs7x4YxHnC0YhBIPNq2te9973vtaDSy1113nb322mstAPutb30rOW/79u32RS96Ufj+kY98xG7dutVWVWWf+9zn2rZtw7EdO3bYiy66yFpr7d69e21VVXbnzp32QQ96kP2Xf/kXa621l19+ebGejYh8jLXW9phjjrFvfOMb7TnnnGNPOukk++hHP9r+4z/+Y3LdMMaLIx/jHJPJxP7Zn/2Z3bZtm73jjjvC78MYL4Z8fL/97W9bAPZLX/pSct75559vX/jCF4bvw/iuDzfccIMFYL/yla8Uj9922222qir7nve8J/l9GOfFUBpfrbU9++yz7SWXXGKttUWBZBjfxTFrDs8SSIYxHnC04qgXSK699lq7ZcsWq5Sy27ZtC9qI6XRqzzzzTPsLv/AL9q677rKTycT+8R//sQVgzznnnKSM8Xhsd+7c2Sn7l3/5l8O5H/nIR+yDH/xga621L33pS+3rXvc6a621//W//ld7+umn351dPOLoG+Nbb73VArCbN2+2b33rW+3VV19t//iP/9gKIexll12WlDGM8Wz0jTHhwx/+sN2yZYsVQtgdO3bYL37xi50yhjHuR9/4XnHFFRaAveWWW5Lzf+M3fmNYJw4Qxhj77Gc/2/7Mz/xM7zl/8id/Yo877ji7trbWOTaM82z0je9FF11kn/70p1tjjLW2LJBYO4zvIpg3h2cJJNYOYzzg6MRR7UMCAA94wANwzTXX4POf/zx+67d+Cy960Yvwta99DXVd4/3vfz+++c1v4vjjj8fmzZtx2WWX4RnPeAaUUkkZS0tLOOmkkzpln3322bjiiivQNA0uu+wyPPnJTwYAPOlJT8Jll10GwHE9n/KUp9zd3Tyi6BtjYwwA4DnPeQ5e9apX4ad+6qfwn//zf8aznvUs/OVf/mVSxjDGs9E3xoSzzz4b11xzDT772c/ivPPOwy/+4i9i586dSRnDGPdj3vgKIZLzrbWd34bxXQyveMUrcO211+K9731v7zl//dd/jRe84AXFZGPDOM9GaXyvuuoqvO1tb8O73/3uzrzNMYzvfCwyh2dhGOMBRyWOtER0T8NTn/pU+5u/+ZvJb7t37w7aikc/+tH2ZS972UJlfetb37IA7BVXXGEf+chH2r//+7+31lr7gx/8wNZ1be+88067vLxs3/3udx/aTtzDQWM8mUxsVVX2TW96U3L8Na95jX384x+/UFnDGJdRmscc973vfYPpfx6GMe6CxndRytYsDOMb8YpXvMKedtpp9sYbb+w951Of+pQFYK+55pp1lT2Mc//4XnzxxVYIYZVS4Q+AlVLaM888c6Gyh/F1WGQOz7OQ9GEY4wEbGUe9hSSHtRaTyST5bdu2bTjppJNwww034Morr8RznvOchcr68R//cZx++un4p3/6J1xzzTV40pOeBAA49dRTcZ/73AdvectbMB6Pj7poGDTGo9EIj3rUozqhEb/5zW/izDPPXKisYYzLKM3j9RznGMa4Cxq/s846C9u3b8cnPvGJcGw6neLyyy/H4x//+IXKGsbXjecrXvEKfOADH8C//du/4ayzzuo996/+6q/wiEc8Aj/5kz+5rjqO5nGeN74XXHABrr32WlxzzTXhb8eOHfj93/99fPzjH1+ojqN5fIH1zeEDxdE+xgM2OI6cLHTk8drXvtZ+6lOfsjfddJO99tpr7ete9zorpQzOYf/wD/9gP/nJT9pvf/vb9oMf/KA988wz7c/93M+tq44XvvCFduvWrfaBD3xg8vt//I//0W7dutX+2I/92CHrzz0R88b4Ax/4gK3r2r7zne+0N9xwg337299ulVL205/+9MJ1DGPcP8b79++3r33ta+3nPvc5+53vfMdeddVV9sUvfrFdWlpKIsjNw9E8xvPm8Jvf/Ga7bds2+4EPfMB+5Stfsc9//vPtqaeeavfu3btwHUfz+Fpr7W/91m/Zbdu22csuu8zeeuut4W91dTU5b8+ePXbz5s32He94xwHVc7SO86Ljy9HnQzILR+v4WrvYGN9555326quvth/5yEcsAPu+973PXn311fbWW29duJ6jeYwHbGwc1QLJr//6r9szzzzTjkYje9JJJ9mnPvWpYZNhrbVve9vb7GmnnWbrurZnnHGG/YM/+AM7mUzWVce73vUuC8C+9KUvTX7/u7/7OwvAvvjFLz4kfbmnYt4YW2vtX/3VX9n73ve+dnl52f7kT/6k/eAHP7iuOoYx7h/jtbU1+x/+w3+wO3bssKPRyJ566qn2/PPPLzq1z8LRPMbz5rAxxr7hDW+w27dvt0tLS/aJT3xib3SoPhzN42uttQCKf+9617uS8/7H//gfdtOmTXb37t0HVM/ROs6Lji/HgQgkR+v4WrvYGNP45H9veMMbFq7naB7jARsbwlpr704LzIABAwYMGDBgwIABAwb0YfAhGTBgwIABAwYMGDBgwBHDIJAMGDBgwIABAwYMGDDgiGEQSAYMGDBgwIABAwYMGHDEMAgkAwYMGDBgwIABAwYMOGIYBJIBAwYMGDBgwIABAwYcMQwCyYABAwYMGDBgwIABA44YBoFkwIABAwYMGDBgwIABRwyDQDJgwIABAwYMGDBgwIAjhkEgGTBgwIABAwYMGDBgwBHDIJAMGDBgwIABAwYMGDDgiGEQSAYMGDBgwIABAwYMGHDE8P8H8oG1NVdp11cAAAAASUVORK5CYII=", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -804,18 +2072,24 @@ { "cell_type": "code", "execution_count": 15, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:14:52.250617Z", + "iopub.status.busy": "2023-04-04T02:14:52.249990Z", + "iopub.status.idle": "2023-04-04T02:14:54.323710Z", + "shell.execute_reply": "2023-04-04T02:14:54.321686Z", + "shell.execute_reply.started": "2023-04-04T02:14:52.250560Z" + } + }, "outputs": [ { "data": { - "image/png": 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\n", 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", 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a102e758

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\n", + " Dashboard: http://127.0.0.1:8787/status\n", + " \n", + " Workers: 4\n", + "
\n", + " Total threads: 4\n", + " \n", + " Total memory: 100.00 GiB\n", + "
Status: runningUsing processes: True
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Scheduler Info

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Scheduler

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Scheduler-9e161f63-f1eb-4af6-a3b9-d250897338ba

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\n", + " Comm: tcp://127.0.0.1:41736\n", + " \n", + " Workers: 4\n", + "
\n", + " Dashboard: http://127.0.0.1:8787/status\n", + " \n", + " Total threads: 4\n", + "
\n", + " Started: Just now\n", + " \n", + " Total memory: 100.00 GiB\n", + "
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Workers

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Worker: 0

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\n", + " Comm: tcp://127.0.0.1:34950\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:38916/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:39103\n", + "
\n", + " Local directory: /tmp/dask-worker-space/worker-ey9iznna\n", + "
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Worker: 1

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\n", + " Comm: tcp://127.0.0.1:35828\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:39334/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:44181\n", + "
\n", + " Local directory: /tmp/dask-worker-space/worker-4okhcz51\n", + "
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Worker: 2

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\n", + " Comm: tcp://127.0.0.1:42612\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:36310/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:38074\n", + "
\n", + " Local directory: /tmp/dask-worker-space/worker-7b0a_wqe\n", + "
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Worker: 3

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\n", + " Comm: tcp://127.0.0.1:36670\n", + " \n", + " Total threads: 1\n", + "
\n", + " Dashboard: http://127.0.0.1:46541/status\n", + " \n", + " Memory: 25.00 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:46093\n", + "
\n", + " Local directory: /tmp/dask-worker-space/worker-neq_7v61\n", + "
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\n", + "image/png": 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", "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -199,7 +511,15 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:17:41.242719Z", + "iopub.status.busy": "2023-04-04T02:17:41.242020Z", + "iopub.status.idle": "2023-04-04T02:17:41.259645Z", + "shell.execute_reply": "2023-04-04T02:17:41.256620Z", + "shell.execute_reply.started": "2023-04-04T02:17:41.242658Z" + } + }, "outputs": [], "source": [ "# Function for binning a single snapshot in time\n", @@ -232,7 +552,15 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:17:41.263569Z", + "iopub.status.busy": "2023-04-04T02:17:41.262955Z", + "iopub.status.idle": "2023-04-04T02:17:41.274564Z", + "shell.execute_reply": "2023-04-04T02:17:41.272400Z", + "shell.execute_reply.started": "2023-04-04T02:17:41.263514Z" + } + }, "outputs": [], "source": [ "# Parallel switch\n", @@ -250,7 +578,15 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:17:41.283551Z", + "iopub.status.busy": "2023-04-04T02:17:41.282932Z", + "iopub.status.idle": "2023-04-04T02:18:52.707215Z", + "shell.execute_reply": "2023-04-04T02:18:52.704748Z", + "shell.execute_reply.started": "2023-04-04T02:17:41.283498Z" + } + }, "outputs": [ { "name": "stdout", @@ -259,7 +595,7 @@ "Raw statistics (not volume-weighted):\n", " Variable: mean std mode 1 50 99 percentiles\n", "potential_temperature : 0.8009 1.366 0.1019 -1.421 0.4803 5.716 degC\n", - "salinity : 34.44 0.9865 34.9 30.68 34.89 34.93 psu\n", + "salinity : 34.44 0.9865 34.9 30.68 34.89 34.93 g kg-1\n", "potential density anomaly: 27.59 0.7954 28.01 24.55 27.97 28.05 kg/m^3\n" ] } @@ -358,7 +694,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:18:52.710771Z", + "iopub.status.busy": "2023-04-04T02:18:52.710138Z", + "iopub.status.idle": "2023-04-04T02:18:53.132061Z", + "shell.execute_reply": "2023-04-04T02:18:53.129145Z", + "shell.execute_reply.started": "2023-04-04T02:18:52.710714Z" + } + }, "outputs": [ { "name": "stdout", @@ -368,11 +712,11 @@ "\n", "Variables added:\n", " Temp: potential_temperature [degC]\n", - " S: salinity [psu]\n", + " S: salinity [g kg-1]\n", " Sigma0: potential density anomaly [kg/m^3]\n", " w_mean_Temp: potential_temperature [degC]\n", " weight_Temp: Weights for average [s*m^2*m]\n", - " w_mean_S: salinity [psu]\n", + " w_mean_S: salinity [g kg-1]\n", " weight_S: Weights for average [s*m^2*m]\n", " w_mean_Sigma0: potential density anomaly [kg/m^3]\n", " weight_Sigma0: Weights for average [s*m^2*m]\n" @@ -407,7 +751,15 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:18:53.136598Z", + "iopub.status.busy": "2023-04-04T02:18:53.135986Z", + "iopub.status.idle": "2023-04-04T02:19:02.884848Z", + "shell.execute_reply": "2023-04-04T02:19:02.882373Z", + "shell.execute_reply.started": "2023-04-04T02:18:53.136542Z" + } + }, "outputs": [ { "name": "stdout", @@ -419,14 +771,12 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -452,18 +802,24 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:19:02.888570Z", + "iopub.status.busy": "2023-04-04T02:19:02.887882Z", + "iopub.status.idle": "2023-04-04T02:19:18.652068Z", + "shell.execute_reply": "2023-04-04T02:19:18.637760Z", + "shell.execute_reply.started": "2023-04-04T02:19:02.888512Z" + } + }, "outputs": [ { "data": { - "image/png": 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lzZo1PZ6jK4lEgkOHDnHo0CHeeOONbvvtdjuBQKCTKEzVqN1zzz0sWbJkxDNiCsVYZigzYQ8Cvwce6mX/AeBcKWWrEGIJWqq+Wy3F8fDG9rrBPJ2iDxaUOfn9mgocFgPpFiNT8+xsq/ay/kAz/nCUmxZPYdnCMiXEFOMKKWVMCPE/wCtonbvul1JuH+j5Fi1axIoVK7jnnnsIhUIkEgl0Oh0Wi4UVK1a0Cx6r1UpZWRllZWU9nmfZsmU88cQTvWbUcnJyMJvNVFX1bePj9/t73RcIBPjc5z7HDTfcwOzZs5kzZw5TpkzBYOj5YyU1pblnzx7Ky8tHxZSmQjHSDJkIk1K+JYQo62P/ex0erkNL4w8q4chgn1HRG9G4ZH6pkzU7mzh1ghGDTke2zUgwEiEaS+D2Ke8wxfhESvki8OJgnW/lypUsWbLkuGqwjpZRW7VqFYsWLSIUCnHw4EH279/Pvn37Ov3cv39/r4sEUlRVVXHnnXe2PzaZTMyYMYM5c+Ywe/bs9tv999/faUpz06ZNakpToWD01ITdCLzU286OK4tKS0v7fVJVDTY8GCHpki/YW++hsrWNS+fCazvqqPbG0QGv7GzkswsnqHoxhaIfLFq0iEWLFg24iLi/GTWLxcL06dOZPn16t3NIKfn0pz/NqlWr+rVYALR6s82bN7N5c9+VJWpKU6HQGPGiKSHEeWgi7Pu9jZFS/kVKuUBKuSAnJ6ff5z6lUDWTHg5KsnS8vKOBen+EH18+m/llWaw/2Io/GKHIoWfJ7Dx+c/VJSoApFMPIypUrWb16NUuXLmX+/PksXbqU1atX9zvzJITg1ltvxWrtecWzxWLhhz/8IStWrOCSSy6hqKjomGMMBAJ86Utf4sEHH2THjh399j9TKMYLI5oJE0LMBf4GLJFSNg/2+XPSrcDRi1MVx0ex00G1L4zTYuCRDw5hAA40+DCaBKdMyOGWJdOUAFMoRoBURu14ju8ro9ZV0LW2trJ9+3a2bdvG1q1b2bZtG++++y7xeO/egRUVFe2+Zenp6SxYsICFCxe234qKihDiiBPIaLTLUCgGyoiJMCFEKfA08CUp5Z6huMb22kHXdYoeeOuAm7x0A+/ta2ZrzZFJ4NOLMzhzqisphhUKxVjkWGrUMjMzOeusszjrrLPatx1tkUBHfD4fa9asYc2aNe3bCgoK2gXZzp07eeqppwiFQsouQzEuGEqLikeBxYBLCFEF3I5WPoSU8k/Aj4Fs4A/JbzkxKeWCwYxhVkE2VV4lxIaDZl+M88rtxOJxdtYHmFVg45efm0tOulWtiFQoxjjHU6PW1yIBs9nMddddR21tLR988AH19fXdxtTW1vLss8/y7LPPdtunassUY52hXB257Cj7vwJ8ZaiuD7CtRgmw4SIGPLmhlljycYtP+4erBJhCcWLT3ylNKSVVVVV8+OGH7bf169f3aZORIhAIsGzZMn784x+zePFiysrKOk1hKhSjldGyOnJIuPKkUu57+/BIh3HCYNWD2SwIBCVGg4lwTBXZKhSKzlOae/fuZerUqd2mNIUQlJSUUFJSwlVXXQVo7Zl27drFhx9+yC233NJnm6aDBw9yww03ANoq+sWLF7ffehJlyrdMMRoY1yKsJRAd6RBOKAqyLRxsCKHXQSASYc2ueuWUr1AogIEtEtDr9cyaNYtZs2bx6quv9ru27PDhwzz00EM89JDmFd5VlD344IPKt0wxKhhxi4qh5M3dtSMdwgnFnoYQESCYgKYAPPNxFd6gcsxVKBTHz/Lly7FYLD3us1gsfP3rX+eSSy4hLS2t2/6UKLvhhhuYNGkSd911F4FAoN3/rGNt2bp164b0eSgUHRnXImzZaRNHOoQTDhNgFlDiNOK0mkc6HIVCMU5I1ZbZbDZ0Ou2jS6fTYbPZuOWWW7jvvvt46aWXaG1tZd26dfz85z/nkksuwW7vbo/Tm/lsMBjkt7/97ZA+D4WiI+N6OnJijmOkQzjhiABIyEgz4UozYzaoqUiFQjE49Mcuw2g0ctppp3Haaafx/e9/n1gsxsaNG1m7di1r167llVde6XVKU0rJk08+yWc+8xkuvfRSlixZMiATWoWiv4xrEfaDx/punaEYOurdbUgE3lAEp8000uEoFIpxwrHaZRgMhnafsVtuuYVrrrmGJ554otdsWCKR4JlnnuGZZ54BYO7cuVx66aVceumlnH766d0alCvzWMXxMK6nI1USZuRYdtpE/u+ak5VTvkKhGFV8+9vf7rUVU0+2Flu2bOHnP/8555xzDi6Xi6VLl/Lggw9SV1fH7bffzgUXXMDjjz/Onj17eOKJJ7jgggu4/fbbh/ppKMYJ41qEhXrvlKEYInKtOrKMcPGcQqbkqulghUIxuuirtuxHP/oRO3fu5De/+Q2f+MQnMBqNnY71eDz8+9//5vrrr6egoEAV+CuOm3E9HRkc6QBOQFzpRqpaw1Q2B5iUk05VaxsOixGH1YQ3GMEbipJjt6gpSoVCMWIczbds+vTp3Hzzzfj9flavXs1LL73Eiy++SGVlZafz9DalGQqFuPfee9W0pOKo9CrChBDf6cfxbVLKPw9iPIOKGQiPdBAnGDsatFf8zue286nDrTy/uYbiLBuLJmby4UE3e+o9nDbRxc+umqeEmEKhGDH641tmt9u54ooruOKKK5BSsn37dl588UVeeukl1q5d2+txiUSC119/nZdffpnzzz8fk0n9r1P0TF/Tkd8D7EB6H7fvDnWAx0NR1riebR2VpFT9edNz8IZimE16QpEoL22tJx5L0BxI8OauBqrd3fvIKRQKxWhFCMHs2bO55ZZbWLNmDVdddVWfrZGamppYsmQJeXl5fPnLX+a5554jFAoNY8SKsUBf05EPSynv7OtgIUR3V7xRRLHTwf4W90iHcUKR6h05f0IWTqsJkx48wTgVDR6EkBSk6yjKtOOyKw8xhUIxdlmxYgUvvfRSj43JO+J2u9vd++12O5dddhlXXXUVS5YswWazAaqF0olMryJMSnnL0Q7uz5iRJBBRbYtGirtf2I43kCABTHHZ2NWk/aMqyTBx8ewCHFaVnlcoFGOXvhqTX3PNNWRmZvLkk09y6NCh9mP8fj+PPvoojz76KDabjSVLliCl5OWXX1YtlE5QjlqYL4TIAK4FyjqOl1J+a8iiGiS+fsF0bnhow0iHcUISCifIc+hJJBLsagrgMMDJZdl8/9LpTMpJV/0kFQrFmOdo5rG/+tWv2LhxI08++SRPPvkkFRUV7ccGAgGeeuqpbufsuMJyyZIlKiM2zunP6sgXgXXAVuDonVNHEaUu20iHcMLij4PfG2//BcvNtPCjy2cq2wqFQjGu6Ms8VgjB/PnzmT9/Pj/96U/ZunUrTz75JE899RQ7duzo87zBYJD/+7//47HHHhvC6BUjTX8q1y1Syu9IKR+QUv4jdRvyyAYBs0EV5o8kZ0xwUpihZby+fcE0JcAUCsUJixCCuXPncuedd7J9+3Z27NhBYWFhr+OllDz11FN897vfZfNm1f1lvNIflfKwEOKrQogCIURW6jbkkQ0Cw+HWnlobY+zwON0IDiPMKbShT+4zAbbkDFxphpHSzPElEJ1dno4O+LjKw2G35pj7bkUjoahyz1UoFAqAGTNmcM4557QbxvZELBbjN7/5DSeddBJz587lV7/6FTU1NcMYpWKo6Y8SiAC/At4HNiRv64cyqNFOx0XJNjSRlVoCIIHMNDPeKNS1BLAaIc+pBwFGAXYDHHZHqW8dUzO7R8WRbmBWnhmbHqw6sBsh067jrIkZALQEYoSVCFMoFIp2li9fjsVi6dfYrVu3csstt1BSUsJFF13Eww8/jN/vH+IIFUNNf0TYd4ApUsoyKeXE5G3SUAc2mpFoQsymgzY0ATYhU49RB3qgzq0ZljaGYGFZFt5AHJ0AoxH8MZjqMrebyKYZe7zEmKPSE2N3fZhYHKbkp4GEUDTBxkNu8m16qlvbCMeUCFMoFIoUfbVQ+uEPf8hLL73E5z//+U69LhOJBK+99hrXXnst+fn5XHvttbz++uvE43HWrVvHsmXLuOmmm1i2bJlqnTQG6E9h/nZgTDpregKRITu3BAIdklmHWo8IjI5S4/39LQTjYAGakn2U9jYd8fEfTy4aKY+wrTVtnTZEAnHqAm28u7eRT88vHZHYFAqFYjRytBZKl1xyCT6fj6eeeoqHH36YNWvWtLdLamtr4+GHH+bhhx/GbrcTCoWIx+NIKamoqFBWF2OA/oiwOLBJCLGGDl2AxoJFxUi2xTECOh3Ek4oszQSxCGSlQUPbkXEdNZiezgKuJ5w68CTFn46xsVw1Jc5+u3oPCyZmDUutnkKhUIwVjtZCKT09neuuu47rrruOyspK/vnPf/LQQw+xc+fO9jFdpyaV1cXYoD/Tkf8B7gbe40hN2Jgw31p05wtDev6OL17K9cpp0e6nmSGc0DJmk7LMRCUUOA00dhBgM/IsXDI9G6tOK9xPCTCbHpbNL+h2vWybYHZJBkUZ2pVNXd698pzR6ULvMkOWRfDTK+cqAaZQKBTHQUlJCbfeeivbt29n/fr1LF++vM/elIFAgNtvv30YI1QcC31mwoQQc6WU/xBCzJFSbh2uoAYLV7qZusDgtPA2cCSjAzA1x4rDpGdDtfbtwyrAkW5kWl46a/e2cMH0PF7cXE8QmF7g5LCpjWhcIjucZWd9CE8wzqkTMnjvgLt9eyAOj26oBTRxlmUFXwxaApJ3D7kxArlpetJtBgRg0uuJxhM0+UdXX7KyTBPeUJRzphdw7ekTOKl0TCyqVSgUilFPRw+yt956i48//rjXsa+++iqnnnpqe61YWtqo7jh4QnG0TNgNQoipwI3DEcxgs61+cAQYdBZgAHsbg7jDYbKtAh3gl9DgjbKpsoUp2WZe2FKPPfl7/sr2Bqqa2wDJZbNzOKUknexkxqzGG+WtA+5u508RAeqCEIpqWTXQpjCjsThVzWECwTCeYIRGT4iW4KA93UHBH4pCTLJoYiYmg46KBi+VLX521Lj5cH8TO2rceAKR9luDN4gnECEUjXeys0jV9g1ljZ9CoVCMVaZNm9an1QXA+vXr+epXv0phYSHf+MY32LJlyzBFp+iLXjNhQojb0UTaOuCfQogfH62h92hjUpaO/S1DVzW1r6lzVX0MaA1Ba0gTf4nk1KMrXUejL4G7MUhFY/CodV890fWY1qS+rPGnrjz6aApqsvGWp7djFZBuM2A2Clp8UcJxsBhh0aRsirLSiEtJdUuQCS4bc4szsBoNnDc9l3A0zt/fOcDnFhTx7/XV3HjWxBGt9VMoFIrRxvLly1m1alWPzcT1ej06nY5oVPu88nq9/OEPf+APf/gDixYt4qabbmLp0qXtzcQVw0uv0llKuRJ4HXgceH2sCTCA6XkjO/0VQVO59b5EewF9SkyZRM/HjFeEgByHGZmQTMpL5zMn56MHdtT6+PTJRXzvoun84rNzufkT07h0TiHnTc/FYtTjtJm48ayJlGTZlQBTKBSKHujL6uK2226jtraWX//615SXl3c6bt26dVx//fUUFRWxfPny9lZKKauL+fPnK6uLIeZo05GnSSm/Dpw6HMEMNpfOKxrpELrlqExAng0isqfR45dvfmIyXz69jGhcYtIJchxWYgkoz0vHbjHgtJnIdVhx2kxYjPpODb5TwksJMIVCoeiZlStXsnr1apYuXUp5eTlLly5l9erVrFy5kuzsbL7zne+wa9cu1qxZw9VXX43ReMSk0u1287vf/Y5Zs2ZRWlrKueeey+OPP87GjRt54oknuOCCC1Rx/xDRZ2G+lPK25M8fDU84g8vZ5bkjHUI3IkD9mHRdOz7+8uY+QlGwmnXYLUYONLXRFoedtc3c/fwu7rxyplo5qVAoFMdBX83EQSvmX7x4MYsXL6ahoYEHH3yQP//5z+zfv799TGVlZadjlNXF0NJrJkwI4RBC/EwI8bAQYlmXfX8Y+tCOn5F2aD/BZhz7pDUMwQR4gwnW7Wtm9Y4GAOr9kGM38vFhj+otqVAoFMNEbm4ut9xyC3v37uXVV1/lqquuQojeP7WCwSD33nvvMEZ4YtDXdOQDaDriKWCZEOIpIUTKiGpMSOFch5VyV3/8aI8fu+GI6HImZ80k2gpIM1pTb5vQmnrb9Ud8xU40oRYDwlK7ASwocTC3JAMhUL0lFQqFYpjR6XRceOGFPPnkk8yePbvXcVJKnnvuOZ544glisdG5GGws0pcImyylvFVK+R8p5eXARuANIUR2f04shLhfCNEghNjWy34hhPidEKJCCLFFCHHKAOI/Kl8+c+pQnBbQ6rtSs+qxBOSkCcyAJ3Kk8D4OWM3gsBpw2vW0hRIkdFCcacSAJtRMOihy6BgnbST7xNDl/plTsnBYTZw2MYv1h1pVNkyhUChGiFmzZvVpddHW1sbVV1/N5MmTueeee3C73cMX3DilLxFmFkK075dS3g38BXgL6I8QexC4pI/9S4CpydvXgD/245zHzObDrYN6vjQjFKVreawImmdXlkVHeUEaibgkTDLzZdEc7jMtgql5Thw2I82+OAdaQtjMAr0OTAbINmsirNGbII7WY9KsgxwrZJihwN6fpgZjg5l5FrJs2vPJsQpuOqeUG86eykWz8sl1WDlziqtTQb5CoVAoho/ly5djsViOOu7w4cN873vfo6SkhG9961vs27dvGKIbn/T1Cf8ccH7HDVLKfwDfRdMffSKlfAto6WPIFcBDUmMdkCGE6N6r5zg5fUrOoJ6vLQrVviPZGhPQEkqwpbqNpqRhfVG2gZYgxMOSQEiyqdJDs1fzBzMBkYjkUHOUYAw8YTDowWmFDIsghNbuqCkI7jBYLeNHhO1rCNGQ7Hoejkk+eVJJ+2pIQAkwhUKhGEH6srr4zne+w49+9CNcLlf7eL/fz//7f/+PqVOncuWVV/Lmm2+2NxdX9I++fMJukVK+3sP2l6WUgzHHVwR0XIZRldzWDSHE14QQ64UQ6xsbG4/pIj/499B2W0qp0Y7TbE1ebb7cHQe9XnuRBZBm0DJnbRFtmtKu02qkghHwRcAXkmSYtUyaDkjTQVXT+Jl7D3f42/RHIRIbC+3HFQqF4sSho9XF/Pnz260ufv3rX3PnnXdy+PBh/vrXvzJz5sz2Y6SUPPvssyxevJj58+fzyCOP8Pbbb7Ns2bL2VknKa6xnjlq1LoRIl1L6huDaPdWk9yihpZR/QZsKZcGCBccks/MzBQdbh16Zd7yCt4ORfiCu1Y01BcBqoN201aqDUPJBWNLu4uru0GmpLblfx5HjxgN6tDf/uY8rafFHyLKb2FPnxajXcebUHBxWbWWDyowpFArF8JOyuugJq9XKV77yFW688UZee+01fvvb3/Lyyy+37//444/50pe+BGiWGFJKKioqWLVqFStWrGDlypXD8hzGCkdr4F0E/As4dwiuXQWUdHhcDNQM9kWGQ4BZBCRk99ZC2VYd7qAmn+KAP6a94EahCatol/FWtMxa1/Mk0OrQUtOgGQLcUqsba+zQLzLfBnVjwIMs9fz+/n4Vf3+/CsERETu3MI0vLNKc8RdPy1VCTKFQKEYhQgguuugiLrroInbs2MG9997LQw89RCgUah+TmppUXmO901fvyFnAY8BXh+jaq4D/EUI8BpwGeKSUtUN0rUHDQGcXfCOaAEszQySsFdYbjeCLwtyiDLbXthJLgAFJNAG+MBRlG9nfFMUKZDl0tPgTxBMQE3DZ7Fxe3tpACMg2gdRBNA6Nvnj7tYMCTitOZ3aJk9d21JOQCSIxiV6vw26M0RaFLDM0D17/8kHDALjSwG4z88lZ+cwrdalMmEKhUIxhZs6cyZ///Gfuvvtuzj//fLZu7bkMKBAI8JOf/ITnn39+mCMcvfSVCVsDXJEsmj9mhBCPAosBlxCiCridpKODlPJPwIvApUAFEACuH8h1+uIzv1sz2KfsJMBE8pYAvEnBM7fEyYFmD8EorKnQ1iXkWWFKXga7Gr3kGhPUeaLY9BCJQygK0YR23lInvLqzgTQrJIIQkmDTG5iSk8aHlR4Azipzcsgd4EBrGzsa/PiShVZZNmhOrrDMsEBzCDIM4B5lJWUxtOc8Mc3GF86YTK7DCsBJpSPb51OhUCgUx4fL5erUDqknXnjhBa6++mr+93//l3nz5g1TZKOXvpbefQRcNdATSymXSSkLpJRGKWWxlPLvUso/JQUYyVWR35BSTpZSzpFSrh/otXpjYk76YJ+yE6lSLj1w5uQsMszwYaWHxgDYDNp2iw50esGhVj/RSIIaP+gkZKQbuHJ+ISuvmMOUPK17vTsA0RgEwtq0ZHGGmfOm5XDtmWXMyjOhB9Yd9BAORWnwJ1hQmqlNbwIOq5GLZ+XyiWk5lOc4yLKBwaitxhweu9r+YQK+t2QGN19UftSxCoVCoRhblJeX9+k1BvDEE09w0kkncdlll53wBft9fT5fDvxRCPFLKeUtwxXQYBKMDK3xZ6ZZ4A5r3mBv7dOyXhkmMBoEeRlWdtYECCegNSBJJGLkZhhxJCShRAKk4PlNNeyo9tLs1gq5AhHIsusodFrZVN3G7sYwuxtr+ffGWm21JOAFWpNT7u/sbWnPzB1sjnKwuWFIn+9gEAFue3YnADZgUp6ZHLst2cTbSHaakbIcB55gBJfdQq0nwIyCDBp9IWwmA9F4ApvJgMmgw24x4A/FyLKbMBl0FGemAdo0picQwdzF+iIUjROOxlUjcIVCoRgili9fzqpVqwgEuhco63Q6Eokjy8yef/55nn/+ec4//3xuu+02zjvvvD5bJ41HehVhUso48DUhxI+HMZ5B5Q9fPo0zfvICNf6hOX9ruHvRvycCMiJp7PALmFoFKUSMSq92TGG6JBCHnXX+9kL1GNDkTxAJt3U6ZyrjllqiGu3yc6wSALbVh6F+YMVrRrTXIN0IzjQzN549kXyHjfkTMnjw3YNMybVjMxtYPE1r5P7a9jp21nq56dzJSogpFArFEJDyGrvnnnsIhUIkEgl0Oh0Wi4UVK1Zw+eWX87Of/Yynn366vXD/jTfe4I033mDRokXcdtttfPKTnzxhxNhRZ6qklHcORyBDxd9uOJNLf/fusF2vr7WYlR1Warb6tfs9rYR0d1BXVh1EEtq4E8UCz4pWa6czwpQcGzaTmal5Nt7d38wXT5tAaZb9qJmwm86d3C0TduGsfM4pz1ECTKFQKIaQlStXsmTJEu699142btzIKaecwvLly9tXRT755JPs2LGDn//85/zrX/8iHtc+CdetW8dll13GvHnz+N///V+uuuoqPvroI+6991727NlDeXl5p/OMB/pVLiSEyESzk2gfL6XcOFRBDSaThrgurDcsQKjLthwLNIa0Zt/+Hgrme/IDC44ng7B+0u66EYVNNQEEAbZUtxKMQjCa4IypOUddOdmT0LIY9WrFpUKhUAwDKa+xtWvXsnjx4m77Z86cyUMPPcQdd9zBL3/5Sx544AEiEc3+fPPmzVx99dVkZWXh9/uJRqNIKdm0adO48xs7ak8cIcRdwBbgd8Cvk7d7hjiuQWOkPnRTAqxj60djMhZ/THPD16NlfeDIKsujMX6aGPUfA5Dl0HNqaQb5Dgvv7W1k0+EWQtG4avitUCgUY5hJkybxpz/9if3793PzzTdjs9na97W0tBCJRHr0GxsvBf39+UxfCkyWUi6WUp6XvJ1/1KNGEf/5+ukjct3cNDCZBDlWKHbqCEbjZNt05FhBpwODThMXJRkG5pc4sADODrnJbBu4zNr9LANkGrU6KNtoWu44DESBw81xPjzs5uZ/b+WGhzZwzR/f54F39rN2d0OfQiy1T4k1hUKhGL0UFRXxm9/8hkOHDvHDH/6wT6uLUCjEvffeO4zRDR39+TjfBmQAo3/p3SjBrodgHDxBiCQkFh20RROEY5BuSuCLgNEAk1wmAlFBNB5nV40Xk0nrKykAmwlKM9L4uEYr0g8kYGZhOttrfNj0EIppPSaDfUYytrlybh5Om5F4IsGiSTlUtrRR7Q6ypcrDeeUurppf3G7sCuAJRHDaTISicSxGPaFonDW7GjhjcjbrD7Vy5hSXmo5UKBSKUYzL5eKuu+7iueeeY/PmzT2OSSQSfPDBB8TjcfT6sf0/vT+ZsJ8BHwshXhFCrErdhjqwwcRkGJpJPAGk6Y/cByjNMGAwaBmrbJsOCVjNkO80kW0TWExGDAYwCNjZECEYieILxkAHGTZju+WERS8ISYkl+TiUgAMNPjIsEBdawX4QmFVgY5LLTFoHOW1h7JKSVLlWHSajnqsXTuBbn5iO1WzkUycVMackk2kFTi6eW8TWai/eYIR3K5po8Ab5+zsHaPAGebeiqT3zJQSYjXolwBQKhWIMMWPGjD79xg4cOMC8efM6rbIci/RHnfwD+AXwc47UhP16KIMabGYWZgzJeSUQjh+5bwD84RjesFYTFoklSDOAPwg1LREaApK2UBSrTjuuJMNIQibwRcEfhbrkskgJmA3gD0Qxm7U3KV1AawR8IYhEoDDbhtMI+xsDRGMSh0WTgRahXXusLu6NACVOA3arniZfmDuf3c4LW2tIN+v5+LCHaDxBdXOQf314mAnZVrZWe1kwIROH1cSNZ00k12FlTpGjvQg/1X9SCTCFQqEYOyxfvhyLpe+Uwvbt27nqqqs49dRTefnll8ekGOuPCGuSUv5OSrlGSvlm6jbkkQ0ir2wd9L7g7XRtY9QSPFJgH4zBtFyb1pRbaqIrEIO2GNgt0OiN4gkcKd6PcCQTVOOT+AJRwlGtgF/oNbNWm0VHWwLC0SgGPaSZdKRbDFjNBgxorY5gbNtZVHpi7G+J8saeZjYecvPP9w6x/PGNbK9qZnahk0l5aUSiCdbtb2bBhEzMRj3vVjQB0OAN8si6w3gC2iobJb4UCoVi7JHyG7PZbO0ZMZ1Oh9Vq5ZxzzsFut7eP3bBhA0uWLOGcc87hzTfHlDzplwjbIIT4mRDidCHEKanbkEc2iFw8p3BYrhNFE0wpzCbYWBNAJPc1u6MYdNrUYiIOMgGZaXraOiyLjHDkTXFHtbGZNvDGoA1oDmiDa9xRmkNgMQjcgRAHmqOMsjaRg0IEONAcxOuP8s8PKvnRf7YxI9+ONxjlkfcPsLvOy3t7Gylwmnl5Wy0f7G/h8pMKlBeYQqFQjHFWrlzJ6tWrWbp0KfPnz2fp0qW88cYbvPnmmxw4cIAVK1Z0ypa98847LF68mIsuuogPP/xwBCPvP/0pzD85+bOjO5oExtQKyeGi4xq8loCWHXMYNcPVaPIG0JI0iTcbtYbbZj3UJY3y9XS2q4ihnUdyJMOVEnsNvjgGoW3v6jNmAdLN0DgwQ/pRQxwIxSEeh201Pn68aifx5AvxlQc+wBuFCVlmSjLTuGBmLk9v8HLTuRYlxBQKhWKMk/Ib64rL5eJXv/oVN998M3fffTd//etfiUa1kp7XXnuN1157jcsvv5y77rqLuXPnsm7dul7NY0eS/jjmnzccgQwlH+5vGrJzO43giYLLCk1BcAgoyrWysz6IwwzesLZ/XqGdWo8fgZ5oPI4vDFEJbl8coQN3GHKtArPZQFs4Skty2aMBTcwBFDv0BGOS5kACh00QikrCMW3lJBwRYGYBYQk2qw6dSJBhAPcYTpNlmrXXapLLzjfOm0pmmuaQv6fOyyllWRxuCjA1347ZoMdhNan+kAqFQnGCUFhYyH333cf3vvc97rzzTv7xj3+096dctWoVzz33HDNnzmTfvn2Ew2GklFRUVIwa09c+pyOFEH9M/rxveMIZGpb+5YMhO7c3CudNziSe0Erh/RJ84RjnTMrEbtRhQFspWe9twxOCxrY46HR87axS8tL0RONa7VhIgjck8QQ0AWZCE2BmAzgMkGmBWDzRPh0ZTUhCUXDZBEbAlSzML8kwkpOux2kEu1lPfQAcab37rYwF2sJQkmXjh5+aRUm2jYWTXEx02Vm6sIwpuQ7On5lPSZadXIcVi1GvBJhCoVCcYJSVlXH//fezY8cOrr766vbtUkq2b99OKBQalaavvYowIUQp8E7SjuK95OMxR4N3aJy0rEC2RZsGXLOvlUhUYgSm5ZqIxxO8v7+VOn8Cix7SzIJoHE4ry2J+STqhcIJHPjiMLxQn22lkaq7mm2+3QEirJ8dp0aYh22JaPdj0XAfutiPl9v4QTMm14ItBQaaBtojkvCmZhCNRqrxxPFHwtGmp2Qbf2G31nVrlebghwE+e38ZVv3+X3768jW/9ayOvbK2hosE7ovEpxgdCiM8JIbYLIRJCiAVd9v1ACFEhhNgthLi4w/b5QoityX2/EydKx2GFYhQzbdo0HnvsMTZv3szll1/e59jRYPra13TkeUApMAf4EK0M6aHhCGowMRv0nF/u4o09gzclKYAwEOzQHFKvh9MmZPDRYTcyDlYjRGLaNFqaXmI2m3DajOyu9yKkZspq1UOm1USdN4RDB06bGYddEo0mCEYlVuLE0ITeR4e9xIA0oV0rHIM6b4hYBAoL7DS73VR5gjQEjsTkifbep3KsINGK8yMJ2JI0rr137SEA3qxoxq6H5RdNZXKOg/wMS3tD7ym5jnavMLVCUtEPtgGfAf7ccaMQYiZwDTALKAReF0KUSynjwB+BrwHrgBeBS4CXhjNohULRM3PnzuXZZ59l+vTp7N69u8cxiUSCPXv2DHNknelVhEkp/yGE+BtwGvATKeVPhi+swcNpM7HikmnsqfdQ5RmcjFCqQN5ugAk5Vg42BonF4b0Dbs3t3ggZaSbsZj2zC528XdFIizfCc1vrybeBFJCbLjDoDWSlWah2BwgkYF+zVkGfYQSTAdLsgnBQEhfaY70E9AKHxciBlghpgMthYF+9G4MRmn2aKswya5YYNiNEEjr8sfHbBdwfh7tf2ttt+6UzXLT4IzjTTEzJsRFLSM6els/OWjcuu4VoPIHNZMATjOC0mlg4KZsad5CqlgBnl+cSjsUxG/SdHPgV4xcp5U6AHpJZVwCPSSnDwAEhRAWwUAhxEHBIKd9PHvcQcCVKhCkUo4qTTz6ZvXv3tteJdWXPnj0888wzXHnllT39/Q85oi9zMyFEoZSyRghRIKWsHca4emXBggVy/fr1x3zcGzvquOGhDUMQ0chgQssQdcRAZ98yPWDTg0+1TTwqU1wmqloihBJwzuQsDAYdZS4b/3XuFLZWe5Xj/ggjhNggpVxw9JHHfZ21wAop5frk498D66SUjyQf/x1NaB0Efi6l/ERy+9nA96WUn+rlvF9Dy5qRl5c3/7HHHutXPH6/v5Mf0kgzmuIZTbHA6IpHxXKEHTt28J3vfIdwuG+bgLlz5/Jf//VfzJgxY9BjOO+883r9/9Xn6sikAFsOPJCsd/gbmmXFrVLKVwc90iHk/Jn5w35NC5p7/bHQk7jqidSYlHUFdBZgk3PMNLrDeMduOdiQIIAFxXaq3GGKnCbMej05TgtL5hYRjWvflLpmws60mpQAGwcIIV4HevpHcJuU8tneDuthm+xje49IKf8C/AW0L5KLFy/uO9gka9eupb9jh4PRFM9oigVGVzwqliMsXryY+vp67rnnHkKhEIlEAp1Oh16vR6fTtYuzLVu28PWvf51ly5bx05/+lLKysmGJrz9mrTdIKb3ARUAOcD1aC6MxQygap8Eb5ImvnTa81x3AMRGSGSwBBWlHtufZIdOkrbRM12tvnAkwCbDotBWUHRV1kztMWAmwbkjgoyo/tf4o66vbePewl/9sbeCmf37Mz17awfRCB06biVyHtX2VpRJg4wMp5SeklLN7uPUmwACqgJIOj4uBmuT24h62KxSKUUZH09fy8nKWLl3KW2+9RXV1Nd/+9rcxGo84CDz66KNMnz6d73//+3g8niGPrT8iLPWN71LgASnlZnr+FjgqCUXjvLClhm/9ayNf/vsH3H/tfL58WtFIh9Ur2WbNvDUBpNss5GgLJ2n2a70jy/PTSLPoSaAJNqMAnYBpeWkYBBSl67RsWkJbPNCRdMCmA/uYefeGnnwbnFKUzv3XzucfNy5iSq5jpENSjC5WAdcIIcxCiInAVODDZHmGTwixKDlLcC3Ql5hTKBQjyKJFi3j00Uf585//zKOPPsqiRYvIzs7mt7/9LTt27OCqq65qHxsOh/nlL3/JlClT+P3vf99uAjsU9Ldt0atoIuwVIUQ6nY3ZRzUWo55Pzi3kd58/hfu+MJ8H3z3IPz6oHumwupGRtLYyGwXNIc03rLI5hF5vQAB2E9iNcLCpjeY2rcjLqgOdHjLTjHhicdKtOrzBBHG0tkj2LpPNRkvStX8sN5Y8RhwG7XXKtQtuPL2YLy8qIdMC03PSuP/a+dz/lTO5/uzJnDE1h+LMNELROJ5ApH1lZVdC0Xj7vt7GKMYeQohPCyGqgNOBF4QQrwBIKbcDTwA7gJeBbyRXRgL8N1qJRgWwD1WUr1CMSaZMmcKTTz7J22+/zcKFC9u3NzU18c1vfpPZs2fz7LPPIqVk3bp1LFu2jPnz57Ns2bLj9hnrT9uiG4GTgP1SyoAQIhttSnLMYDHqafTFmV+WNSLF+XqOtDNyGsFqEtS1SQrTodYHaTpItxlxR6L4Q7K9ziuYAEMoRpYZPGGtyN5k0jJfaQlwx7Xekq50PXvqO09+xoF4DKblWNjdqO1rGcj86Bij2CFo9UmECT5RnkuTP0azP8Q3LpjKvNIMat0htla5KcpMI8tu4lBzkHPKcwhH47y/v5kmX4jtNV5OLcvi0rmFWIz69tWRoWictbsbkBLOmJzN+kOtqmB/nCClfAZ4ppd9dwN397B9PTB7iENTKBTDxFlnncW6det4/PHHufXWWzl0SLND2rNnD1deeSUTJkygvr6+3Xl/06ZNx+2835dZaz6AlDIhpdwopXQnHzdLKbd0HDPaqWzx861HN7FuXxPO/uT+BhkB7c75oRg0tklOKkwjFBVkmSEhtIbcoHmLdUxUmYw6DAa91j9SaK2RfFEIJFWdBHJ7cMRP10OWTce+xhDZlm67xy1VXkmbBH8Y/rO1gXcOtLCzMcBtT2/m2r+t4/tPbWZfvY9Nh1v47r8/Zv2BBsKxOKt31jOrMJ1d9T42VbUSiGrLHBq8Qd6taGoXYqdPyuaMydlawb4SYAqFQjGuEEJwzTXXsGvXLn75y1/idDrb9x06dGjQnff7kiQv9uP4/owZcRwWE8UZFm77z1ZOmZg57NdPrVrUofV0NAJVLW20hCTNYYjFj2TKuiargpEEOl2CHKuOcOJI6nJKnhkApwk2VPoAbUozJym4/HEIRBPEgOYTIAPWGwIwo4nVaCzO5Jx0rpxfQjQaockT4uF1Vfzu9V28tK2WcCzB5xeWct0ZE7loZj7haJxH1h1mQra1PRP21p5G3t/frLzDFAqFYhxjsVj43ve+R0VFBd/85jf79BA7Huf9vkTYPCGEt4+bD8gb0FWHGafNxPILy8mwGlmzr3VEYohxpFA+BDR1EEa9WVKY0DJegZBEZxCEE9p5zEBT0gZfJsCQ1AKeCCRnHrXpTLU6Eon2unsj0OqPsbO6hZ01XuoCYLfoKcww8fbeJgqdJn72wk5+/uIupuWl88H+FryhCJefVMCqTbV4Atq7ZDToOH1SthJgCoVCcQLgcrn43e9+x8yZM3sdk0gk2Lu3u2l4f+jLMX9cfcqYDTr+9bXTWfHoRt464B7pcLphAgqyDOiFgf3J1FVKnDkdeswGA6GQ1hNSr4dAsjifGASBDDO4kyov16KJMadJ60VpMkIg2j//sfFMWwLafHG8YQ8WAdXeOKkc5H82VuOJwPRcK09urCIel6zaVMOSufl8cVFpu13F4mm5SoApFArFCcacOXPYuXNnj877Op2O8vLyAZ13BCqkhp/KFj/ffXwL4VicGYXpIxaHDlhUkk629cjLbtdpAkwvwGm1cOH0nG7H1bbE2VsfxhMFhxEWTcxkcmEaBqANTUmbjQJbMlvaGtKsKHwRCACBGBj1yb6TaDcrkHkCaok0AelmI3d+ehYz8u0IIMui44ypeVx3egkLJ7u46ZxJ3LpkBnd/ZjaXzikk12FtP14JMIVCoTjxWL58ORZLzwXWFouFb33rWwM6b39WR455SrLs/Prquby1u4E/v1s5rNc2odVv7WsIE5awvtKHK92AkQR5Dh0IHbEY1LXF2Ffnp6LejwUwG7UCfJMOZhU6aPAHsZkM1LQEeaNCm1I9Z1ImrcEIDf4Q4UgckxkCIYgC6SZBLCRxmiDdpqfBEychoTzHxs7GAEEgeII4LBTYQacTFDjSmFeSweziTGwmA7ddOoMad4DCDBvuQKTdKb+j6FIoFAqFYtGiRaxYsYK77rqrvTBfp9NhsVhYsWIFixYtGtB5TwgRBpoQm5o3/BXqEWBHfRgjYBZaY22HTU95noNELMHmGjeudBO0QVtcm1bMzbCxpynA7Dwzdf4Y/kgMfyhKjTuK3QiTs82km/U0tEVx2UwcbmrDHwVHB5HeGpKYBdgsekJRyLKBuw32NQWG/TUYaWr9AJJqr5+Pq/zEqQKOtHyyA37g4uk5lLksTC/IwGYykGY20OgLYTMZKMm2EYkl8IdiTHDZyEm30ugLkpOusmQKhUJxIrBy5UoefvhhDhw4AMDFF1/Mj3/84wELMOinCBNCnAVMlVI+IITIAexSygP9OO4S4F60GbC/SSl/3mW/E3gEKE3Gco+U8oFjfA79ZuEkF4/ccCp3rNpERdPwVq1HgSwDONPNNHnCBMOSQCROukVHsmUhOVYd+U4Lh1s0obStPkymBRo8AQwGwfySdFoDEQwmPfW+ECaDjr0+P/4oTMoxU9kSRg+km2hXGHokdW0JTWzowD9mbHaHho7Jv5QViD/585Vdjcl73bOlZqGNj0iY7LLx2fmFvLqjkatOKcJpM2HQ6ThvuqoXUygUivGMzWZrv//LX/6S2bOPzyrwqCJMCHE7sACYBjyA5rDwCHDmUY7TA/cBF6L1WftICLFKSrmjw7BvADuklJclxd1uIcQ/pZRDVkN+VnkuT319MXc/v40nNtYO1WV6pCUKLUmhZDPHCIQS2DNMVLZEMAAJmWBrXYD8dB0WY4JACMKRpMt9WNLW5qVzHkuTFDogHJPMLXRS5Q0SCkbQ6wUtAYk7ckR1hU5AAdbfhui9YUOrq0vTw7yJLmbm2/BH4syfkM0kVzpGvY7ZxU4cVhNVrW04LJpnW+qx2aAjHEuQY9fSlGajXgk1hUKhGKMEAkc+hW+55ZZhyYR9GjgZ2AggpaxJti46GguBCinlfgAhxGPAFWjtP1JIID3Ze80OtHDEVmvQaPAGcVhN7R9+TpuJ0ye7hl2EpYgDVR5NEcUTMSx6yLbrkUJCKIGMJagPamP1aD2iMkwQk2gpNSBDByX5aXgCYQLhOI2tEQLhCK0BrcVROCSxGSHdDDXJVE+GCZqSisRlhqauzSXHIcer5lN/bi0xWLO3iTXJVcgdW19NydZzxUmlPPjeIWxmQYbVzMmlmby2vQGDQRCPJzh9Si5pFj2nTsjmwln5SogpFArFGOP222/n4MGD7Y9feeUV3nzzzeNyzO+PCItIKaUQQgIIIdL6ee4iOs/rVAGndRnze7QGuTVo/aWvllJ2y9cIIb4GfA2gtLS0n5fXaPAGuWPVdj4xM49L5xS2f/h9en4p0XiCW57efkznG2zq3QmiQMAT11Y5QrsAM6G1KHJYoDHY2UnfnQB3TVt7XRNAMKkYPBEtXRlNQLSDpE0JMJvuxBBgw0VFc5xfr9Zm55uDUOkOsKM2gB6wGMFhM2A16cg065lRmK4EmEKhUIwx1q1bxz333NNelA+dHfOXLFkyoIxYfywqnhBC/BnIEEJ8FXgd+Gs/juvJXrZr6+iLgU1AIVp/yt8LIRzdDpLyL1LKBVLKBTk53S0c+iLXYeWOy2d1EmApli4sY/OPL+SmM0uYmz8yvX06VqZ1NHQFLYsTktAQ7P7Cpehte+q8socBgRNwWnK4iaO9f94oVHliPPJBFX9Ye5AfPrWNyhb/0Q5XKBQKxSji3nvvJRgM9rhvqBzzAZBS3gM8CTyFVhf2Yynl/+vHuauAkg6Pi9EyXh25HnhaalQAB4Dp/Qn8WMh1WHvNPjhtJn5w2Vzu/MzJParGsU7XhJfLNh6f5djAqIcch5mPD3sIRU8QfxCFQqEYB+zZs6dTFqwjQ+KY3xEp5WvAa8d47o+AqUKIiUA1cA3w+S5jDgMXAG8LIfLQRN7+Y7zOcfPK1hoefmd/r1mlsYhND6UuC7vqO9tyBMISqw5IaE77isFDABdNd3HZSUXsrXMzNT8Do15HNJ7AqNdRkm2jKMOmivMVCoVijFFeXs6mTZuG3zFfCOHroW9kpRDiGSHEpN6Ok1LGgP8BXgF2Ak9IKbcLIf5LCPFfyWF3AWcIIbYCq4HvSymbBvRMjkJvU0DPb6ripn9+zDuHPENx2UEltTA2w9xlu0GrH7MlP9ftRijMNFHn1gRYxyK+QFxz51clYYPDhEwD5011cemsPC6d5cJpNzOvNIO5E3JYOCmbjYfdLJyUjcGgZ1JOOk6bSQkwhUKhGGMMlWN+f2rCfgN8D63QvhhYgVYT9hhwf18HSilflFKWSyknSynvTm77k5TyT8n7NVLKi6SUc6SUs6WUjwzoWRyFVNuirkIsFI3z0cEh0XyDitMIuWkGEjqw6yGe0IRWenJmMRbT6o8CyRkufxQONkVwh7U2R10zXv64tuJScfwcao2xZm8TlS0+Zhc5Wbevib+9tQ+zXtDkD+OPRDEb9Jw5xdV+TGoqMhSNq2lJhUKhGAOkHPM1MwcNnU6HzWY7Lsf8/oiwS6SUf5ZS+qSUXinlX4BLpZSPA5kDuuowk2pbVJJl77TdYtTzjfOnUZoxMnH1l2gcmttihBKagPJFNaHlS86fpmwYdGgZMTji8+GNdhZc2SOz/mDcs7U2wC9e3cfh1jD/WFfFjQ98xH8/soH9DW00+kOEo3HerWjCE4iwZldD+89Xt9cpIaZQKBRjgJUrV1JWVtb++OKLL2b16tUDtqeA/omwhBBiqRBCl7wt7bBvzJRRdRVgoWicigYvNz6wjsPukYmpvwQSnZ3eeyPB0X2xxJh5x8YWdqOWpTQBEzKNuNIFmVYjeQ4Lf3t7P89tqWZOkbbwVwjNtPWMydmYDP35E1QoFArFaKCrY/7xGLVC/wrzv4DWeugPaKJrHfBFIYQVreZrzBGKxnlhSw2rd9Zz16fn8a3HP+Rw89jPRjiNYNJDY7IW30z32q+O/mBWHQS7zEu6LOALqZqxY8Uf1b7RJIDa1igRIJbwc+7UbN7f38q+Oj+tvhBF2XZOLdMSyGajnim5/bXdUygUCsV446giLOl4f1kvu98Z3HCGB4tRzyfnFnL2VBcOq4lbLpzN/zy2eaTD6hcGNBd9kx6KXRZa22LEojHiaAq5MQQF6Tq8gQROmw5fOIEvmR67dKaLjYfd1PljmHsQYABNw9/jfMySYdKMcQFMQusrmZ0mSDcbaYvE0Ol0IPQ0h0L4AwkeWx/ktEkutld7mFXkJBCJ8dSGaq45tYQrTi5WBfsKhUIxyhn2tkVCCAtwIzALaK8oklLeMOCrjhCeQARz8oNO+8Az8de1e/j16mF3xegXZsBmBoMBGtu0qa4MK4Si4I/BvoYQUsKkHCvN3iCeZPqq1qepq5gv0Smjtf5AE9HkdKRewqx8K63BIDVdFoamMjqKI1iALIeecDDORXML2FzVytlTcrAYddR6wkzMSaPJF2ZagROn1USe08JHB5qYV5LFeTNyicQSNHhDBCIxZhdnEIklKMywUuiwMr8siy2VrWTZTZgNOpr9EU4qzRrpp6xQKBSKDoxU26KHgV1o7vZ3ok1P7hzQ1UYQTyDCn9/cx+RcO2lmA4un5WIx6vnq4nJOnpDNV+7/iNGQBDKgTRNaTNAWgdYwOJJTXQ4TtAQ1Pyo9MK3ATkW9n2As2q0NkQ7IdQoqPUeKwFqCWm2ZQwfeBGyv69kpTAmw7oSAGq82Zf3oBq3n6I76yh5GVmEACjMMHHbH0ANFmTokgspW7Xg7kNBDcbaR2tYoJ5dm8da+FhwG7X31xuDWJVMpcNqYXujAYTFS4w5SmGHFbNC+RCivMYVCoRg+hqptUX9E2BQp5eeEEFdIKf8hhPgXmvfXmMIbinDTuZO7ZMK0n2eV57L8osn84tV9IxkioK1q9CW0uizQBFdcwNXzC9hY6eWqqVm8u7+JbbVBDjX7MRsgEtWWzM7Ks1DVEsKTXBFZ6ZE4BQSk1si7NaxNWUZVcf6QEgd8oRjTc23saghwuLWzrPUnB+1p0JpLvbWvBdDEV4q7X9Lcl102HSVZdvY2+JhV6GRqXjpmg455JZlcpBqBKxQKxbDQn7ZFQyXCUm0I3UKI2UAdUHbMVxpBUj5hv756LiU2e7f9oWicafkZwx9YPyiwQygGj22oJdem5+/vVrYvaS3PSScmoSUQJssqqGoJIfRgTWi2FjEglQhr6ZApC0ptem00ZP7GCllGuPTkQoJRyVlTXLxd0Uw0Fqc008zexiCXzyvkL2/uw5VuQid0+EMxJubaOXdqNrGEpCQ7jff3teK06qhpjTA5L43iTAuTcxxE4wn21LmZVZRFrSeAy27BqNcRiMRUJkyhUChGASPZtugvQohM4IfAKrTZlB8N6GojRG8+YaAJsHcrmsi2m3o4cuSp6eQvGyeG5pxvNUEwLsmwmMhzWHHaDLy4tZZYSLJgYiYl2VZy7Ub+9OYhpuen0eSPUO3T9LTLKjh9Sg7PbW0YgWc0+hGATYDJCOEoSKHV4b2xo4aZBVk8+v4B9jdob8zqCGQ5YMuhRloDsEWbqUQPrDvk7vUa7xxo6WHrAQBcJs2A12aDhRNzKcqwcPrUPPbU+QDIz9BKMx0WIw6rcuBXKBSKoWao2hb1KcKEEDrAK6VsBd4Cem1TNNoxG/SEovFuH1gWo57yvDRq3aM/L1SfXJQRAIiAp1YTAhlmSLcZiUYkEthyuJV1B1r51Nx8EFDvC/HJOQX84/0qYoA7KHmvorHHa2QaQerAfRSPisnZBhqbY3gBpwCdCYLhsZdd62kRggTapFaT174BCPihZm938RTwdj/v8RieNCWv6/bDf5JC+b63D3caYwEy0+FLp0/hotkF5NgtKjumUCgUQ8Ty5ctZtWpVp9WRKYasbZGUMsEY9QLrSIM3yB2rdvDilppu7uQN3iA/e3EXB5rbWFCc3r49Ywx9lrnDmjdVGM2s1ZucinxjZx3hBNT54/w9KcAgOU0Z7Dmt2ho9ugADOJAUYKBNebaOQQEGY3cRQgio9cEvX63gyt++zVcf+IDbnt7MpsMtNHhVa3aFQqEYTIaqbVF/piNfE0KsAB4H2lIbpZQ9zaeMSnIdVu64fGaPUzfavlk4rCYa3G2sr9KmfNxxzRLiaA70o4VYD9u80R429jH+WBir4mU84pfwYaWXDyu9vLi5llMnZXPP0nnkOqwjHZpCoVCMG1auXMnDDz/MgQNa6cjFF1889D5hQMoP7BsdtknG2NRkXx9IqX3+0BFporyyFKMZHZCbBhfPLiISS3DyhCwCkRgLJ7lw2c1KgCkUCsUQ0LVt0ezZs4/rfP1xzJ94XFcYRXgCWl7LaTN12+60mSh1HSncNwoIn6BWDikBauTI0ljFyJNmhCWzC9he4+Pykwq4an6JElsKhUIxjAy2Y/5RuwcLIWxCiB8KIf6SfDxVCPGpAV9xhNhR4+YPayq4b83edjEGmgD7zWu7O22D8S/A7Maet8/Ks7ZnAJUAG11My7FjMQq+ds5EJrns7YtNKhq8eAIRGrxBQtE4nkCkvfaxaw2kQqFQKAZGT475F1xwAbfffvuAz9mf6cgHgA3AGcnHVcC/gecHfNVhprLFz/ef2sIvrppLUYatUybMG4qwpcqDNxTh5Anjt1VMvhUCYc0pHyAS7bnmrbJeK+rONkDz8RaOKQaVjTV+Ntb4eeTDGgAunZXLyRMyeOj9QyycmI03GOXc8hwqW4PMKnRybnkO6w+1cuYUl1o1qVAoFMfBSDrmT5ZSXi2EWAYgpQyKjssDxhDpFkO3qciSLDu/W3YSJVl2rv/reyMU2dDTtUNRbwsOUiselQAbnaTrAD0UZVq57syJFGRY2N8U4MazJrb7hoWj8Xa7CiXAFAqF4vgZKsf8o05HAhEhhJWkW5IQYjLQDxOD0UNJlp0/fOGUHs1aU/sBirJUfU1/MKJl0XqZ0VQMIb4E+KIgZZzfvLKbl7bWUugwsW5fM+FYnEZfkEZ/iEaf9s/CG4y0W1akfnacolTTlQqFQnF0RtIx/w7gZaBECPFP4EzgugFdbZSzq8Yz0iEMGgNd3ZmTpsNq1HHYHcMC6PUQjGuCK6W8BWPHumO0YwYcVoEvLIkljliHpOsBAcFYdzsRE7C7MYLNECEcT9DgDWEx63hxSy2N/jCBSJQMm5m7Pz2H379RgRBw84Xl/HHtfm65pJw99W2cOcUFwLsVTSpbplAoFEdhRBzzAaSUrwohNgCL0D5/l0spmwZ0tRGiU+/IXrJhAJNy01lf3dbr/tGKDc1F3wLkZBpBSpq8MYI9qLCO4sxA5w/4AhtESHDYrY2IAfoEpOnBnga1Xk2MOSzQNBadWUchYcAXknz6lAIqGto4pdTJ5DwHRr2WpHZaTeyuc2s+dp4AFpMBq8lANJ7AZbcQiMQw6nWUueyYDDre3l3HxBwHe+vcvLa1mvmlDgx6HbtrvcwvdfB+RROHGn3sqW2lJMuOUa/jzV315DktZNtNmA16teJSoVAoujBUjvlHFWFCiFXAo8AqKeXYUyj03TuyI3vqxmYmLPUrEQK83ii+LjNMFh3Y9OCPgt2sNfPuKsBSGBHYkAST+2MSiIMvWSwWRQmwwSYk4dENWtPJjyq9CNo7JZFpgWhUy0Z2fFvNQntvUtvy0yAU0kyGB4IBmOCyUpqVxi8+O1cJMYVCoehAyjH/rrvuap+W1Ol0WCyWIXfM/zVwNfBzIcSHaM75z0spx9RH8dEEGMC80iw21VYPQzRDh9SDUUI4cSTrlWGBuoA29eULa9t7EmC1AQCJSQcZRghFoKfuRul60OvArTwsBgUBFDsNIHRUuiPtAsxlE0QTAn88QZoRglHIsQl0OgPheAJvMI4rTU9bW5z6tiPCrb/YBAQkfPeCiZw9LV9lwhQKhaIPRsQxX0r5JvCmEEIPnA98FbgfcAz4qqOUeGJsmoOlxFaxU4fQG3F7w4QToE9ur0umysKAywpCgstpoc4TorUHKW0CirNtbK0JYNZpgq4jvjjH16H6BMYALJqUyZdOL8Oo15GfYcEfilHmSgPgYFMb/lAMk0HHBJeNcCzBvno/k/PstPgjFGRYAAjHEvhDMbLtJnyhGP7kLYXJoMNuMRCJdZ+TjsQSmAw6suwmWvwRFk5yDctzVygUirHOsDvmAyRXR16GlhE7BfjHcV11BGnwBnvsIQmQZuq5OFnPEc0xGvtJpj5m3b4Ec4ot3HhGGW/uauCUCRm8XdHC+kMe9KTEmqAlJGkMhcgyg8sMTcmKeyuQZoVZxdkcbPGRYQa7xYDRIDjQHKUgDYqy0rHo9biDQUx6Pf5IlLrWKIVZRg43RlkwMYOWQJDd9WEtC2cCgx6MRj1SF2fhhHzqWwNUetuodcdZWOrkQLOH5jat3mxMzncnKXFCkSOdoiwb1uTvkl4nOKk0i2g8QWGGjSy7qZtXXUd6ykJNyU1+38kdgqCH4pwKhUIxThlsx/z+1IQ9DpyGtkLyPmCtlHLMtVWsbPFjNui5Y9UOPjEjl0vnFnYTYmdPy+fP71a2PzYCVgNEE2DUQTjW3ZvDAOTZBbGEpDEwsv0m/Ql4/7CH9w9rtW1rKlrb9yXQ6og8QcnMPAsV9SGcaUaaPEfmFIOALgjeYJTSzHQaDG1UN4WIxDUhOq/URWWrn7gU5DjSaQtFOX1qNq40Iwa9gTp3G55glEBM8un52Rxu8FHqSmNzrYd8uwVXmgl/OMq+Jj9XnlzEG7sa+LjKg0howna0idueMAGZdshx2LDq9cQSCeo8YRr9MRZOLKC6NcC6g02cUpxFrTfEhCwbH+5vwhOIYjLoKMqwEEtIDjYF0OsEep1muZfKTtktBvbV+2gJBrGbTGTaLEzKTSM/w4o/GKHWE6amJYg7FKLBE6bhOIoC8m1QmGHDpNczvywTu9WI1WRg4SQXde4QWXYTdosBs0GnpikVCsUJT0+O+W+++SYrVqxg5cqVAzpnfx3zPy+lHLMTUB1XR95x+cxeM2FzijMoy9ZzsFl7qlG0lYGxGD2uNASttqraPzamMVOtmHbUa5/cB1q6F3W1AR9XaVX4XW0uXt6ZWhQbat//YaUHux4i8c4ian2lJgTXVfoA2E1nk7uOYncsEQHq/dDiD3Rr6/TUptr2+9WeRgDWJ5//wAgCQdbsaz3qyIFQF4C65Le6dR3iNLCbGNqXkGy7AYfNSHFmGj+/ShXsKxSKE5MRc8yXUr4shJgthJiJ5oKQ2v7QMV9thOjv6kiAdJOFjpNiwTDk2HXU+Mdc8u+4OdozTu33j1l5PnDG65qEMyZkcvb0bCa50slzWlQmTKFQKBg6x/z+TEfeDiwGZgIvAkuAd4AxI8J6IhSN4w1GOn2whGNxWgKd53fCcEIKMMWJyXuHWtld3UqRy8LckiycFgMWk548p40yl51ILMFZ5aqQTKFQnFiMpGP+Z4F5wMdSyuuFEHnA3wZ0tRGiq1lrKBrnxS01vL6zgTsun9kuxHIdVq47YxJ3vzSwF1OhGA80x6C5LsSWuppO20Xy9tANpyohplAoTihGzDEfCEopE0KImBDCATQAkwZ0tRGi63Skxajn0rmFnDXV1W2KxWW39HQKRRdcNvAEtFWjqV/JUwpt7KwL9Fo/pxg7FNgFDquFkqw0ZhWkUZRlV5kwhUJxwjJijvnAeiFEBvBXYAPgBz7sz8mFEJcA96ItrvublPLnPYxZDPwfWh1wk5Ty3P6c+1hJZcC8wQgOq6nbVGSKokxbD0crulLosNAUCLVbXNiAiTnp7Krp/guqGFtMy7fw26XzKcqwEY7Fe13IolAoFCcKQ+WYrzvaACnl16WUbinln4ALgS9LKa8/2nFJc9f70GrIZgLLksX9HcdkAH8ALpdSzgI+d+xPoX+EonFe3FrDj/6zjUc/PMQdq3bQ4O25yE5xdLbUabVzKY+xAPDU5nqUBBv7VNaFuP2ZrRxo8nPv6r28sKWGUPQEXH2hUCgUHVi5ciVlZWXtjy+++GJWr149YHsK6KdZawop5cFjGL4QqJBS7gcQQjwGXAHs6DDm88DTUsrDyfM3HEs8x4LFqOfSOYWcNUVzBz+7h6lIoN25XNF/Uma2FrRVg3G0FklxNAsPM4A4YpGhGDnMdPe660oArYfltx/fgJQCg077e9lVG2R6gVNlxRQKxQnLYDvmHzUTdhwUAR3NoKqS2zpSDmQKIdYKITYIIa7t6URCiK8JIdYLIdY3NjYOOCCLUY/ZoOdvb+/n3x9V4Ql0twf9+NDQeDKNN1xpgrJMM3lpOm5dMpUr5+YRAjKs8IlpOSSAi2bl4jBpH/rZ6SMc8DgmJYnsHbSRWfOAxaoDRwdzfrtNM5xN0fEfgDH502mELDME2iLUtIZ56P1KvvvoRq79+wc8/P5+lRVTKBQnLF0d89etW3dc5xtKESZ62NY1F2IA5gOfBC4GfiSE6LbEQEr5FynlAinlgpycnOMKKhyL85WzJ/HF00t73F/rObEn1NINMNllwIDmqO40gt0AM/OOLFjQAwadVpBvter47at7sVtNFDv0BKOwo7oZox7e2dtAOKL9ktV4R+gJnQCkJFFHv7aEBLsJEglw2fUItPctGICyHAuFyU5IHf8gU95nnii0hKEhBFGp1ftdf/ZkHrrxNL50+iSVCVMoFCckPTnmX3DBBdx+++0DPmefIkwIoRNCbBvguauAkg6Pi4GaHsa8LKVsk1I2AW+h2WEMCQ3eIHes2s6rO+p48N2D3Ldmb7dsWKv/OPrAjAN8MdjXFCMG1AfAFwV/7IjLvh7QC2j1SeKxBG2BBBaTYPX2aqq8cQIxqPcnCMTBG9GyYGqx5PATBYLJ139/SxyJJtYCwJ7GULso7s8McRtww0MbiMQSSoApFIoTkqM55g80I9ZnTVjSmmKzEKI0Vbd1DHwETBVCTASqgWvQasA68izweyGEAW2W5DTgt8d4nX7jsJr4zkXlmA06LpqZD9CtkbI7GBuqy48qBFpz7dY+GjZKjnxI29A+wOOAToIzTU+u00pxpoVoLM6ehgA5iQieQBwdR7IziqEn1yZoC0sunF3AGZOzKM93cKDRT503xDt7G9lV72VxeR7nTcvFE4ywv9GHQSdoDcbwB6LsafZzxZwCDHodoUiMN3drpZl7a4O0AYV2+L/Pn8bCSa6RfaIKhUIxQoyYYz5QAGwXQnxIh34+UsrL+zpIShkTQvwP8ApaAuV+KeV2IcR/Jff/SUq5UwjxMrAFLWHyNynlQDNvfRKKxnn0w4McbApQ0xri3OkunBYT55TnYDbq27/hnzEll398UH3M5zfSvZVNSriMRiZlWfB0yfpZ0LpClmaaQAgmZtmwGA18uK+RcFKsXTwtm0yHhYtm5NPgD7OgLJMtVR5mtbRR4w1z4fQ8DrUGqGr2kWE18sq2GuwmMzurvBTlmLAYDNS4A4TD4I73nIlxCHCkg9ur+aE4BHglTMnWU90cZ7StaXUK8EnISwNvG6TbBJGwJBgHlxNqPP0XpalFDn1da2phGhaDgVnFDi6YVUhBhgVfKMaknPT23+OTSrMIReN8/rQyGv0hijPT2vd1renqatdy8yXH8OQVCoXiBGAkHfMHvPZSSvkiWqujjtv+1OXxr4BfDfQa/aXRF+T5zbXcdeVs0i0GNh32EIkneHNPIyaDjsXTcrEY9UzOs2NAW9WXIuUUngDS9WAz6wnG4pgFNIa1uilHmgmDTkcgFMUfiuNyGJlbksWkbAsv72qgyRfB2xYfNT0H97WEyOjy7ofQCrpDkThnT3URicMrW+s7NebeUd/KtZOn8PKOOuYWO9lb38bcYiebKt3MKnAwvyyLqfl2zIYCtlZ7WTKvGIfFyCvb6zDpdThtJkqzrGw83MrrOxq4fF4h0wvScdnNmA16Vm3WBLDJoGP+hEweePcg+ekmDjQH2F3rw2Dwo49p70eaCSJRCI7wqkuPhIlZZqblpfPBwSbqApKyLBMtLREmuTKZX2bBbjXwrfOnsmZ3A1urPJiNOuYVZ3LRrPwhm+KzJL9cdM32dr2exah6QioUCkVfjJhjvpTyzWSrolOTmz4cSiuJoaIky87/XXNSu2t+TnrnD57UB1NxZhrXLCzikQ+PZMM6Tsv54qCLxfFGIMMME7L0HGqJow9FiCcgGodspxG7xciWqlae3xrhlOJ0EmmScCjOaFpYFulBvIQlZKebeG1HA+fPyCUO2PRwUpGDxmCQfY1RkJIP9rcwNTeNgkIza3Y10BaKEYjEWLW5mjW7Grh4dj7T8tL5+Yu7OG1iJgaDjqrWIKeUGLntmW1cflIBn5iRS4bVyG9e20Oew8KUnDRe215Ptt2EJxijxR+i1Rfig4ompC5BdXOYcEITYHHA08dU6nBzoCXMgZYj5g8HW7Tgan1tVHlC5DusNPnDbK/xoNcJli3UFoY0+oL4QjGKMmzsrvMyLd/B23saKM6yUdUSIMNmojw/HbNBE1OeQKQ9c5u6v/5AM3OKMwAwG/U0+rRcYTiWwB+KYbcYiMQSbKtyU+ays6PGzYYDLQQjcWYVpXPezEKy7SZy0q00+oKUZNlp8AZp8of51Qs7KHXZsJv0zCjKpLLFj9VkwGYyUN3ip8EXIRJLcN6MfM4uz+2UVVYoFIrxwog55gshlqJlqtaiff79PyHE96SUTw7oiiNAZYufkix7uwCD7tmAjttvWjyF9w80sq+x86d8QRrUt0GGzUg0HiUYBndYU1UtHWb2Aq1RUpOTAthY5UOHlknrmmUbSQK9CMIWT5C5BU721HmZU2BlU22Q9w4fWd74xzf2kmU38N6eZn73yh6icS0rtaPWxkklmbT4Qry2tZY3djZQ1dRGnaeNSCzOScWZ/PylWsz6OLFYnBe2VLG52s/8knQS8TjethC7altJsxgodth48O0K4nGIC/CGINsKDcH+FZOPFvY0aL9DvrYgX/rru2TazLhsJr74p8PUB45kWLMM0BKDHAs09rA2ZE6+BVealWpfGzp0TMq2s6WmlXgsTm0bpOsAqZ3Pewwv0Ot7W7h37SGg5yl1APalbFt6Lwt9anM9ABk6KM218JkFE1g4ycXMwoz+B6NQKBSjlKFyzO/PdORtwKmp7JcQIgd4HRgTIqxr826gfUVk12maFCVZdm44YzK3Pbuz0/amgPaBecjd/0nF1OdhSu+MFgHWF/VBqD/k6XV/SxhawjEqmpvbt4Ui0FwXYGdd6luCv9txexrr2u93bJK+rtLX+fyhGJXu7p4WDaOtGOwYSMXeHAxT0XwkY5b6/WhJ/mL0JMAAttaF0CaMNXY1dB7oG4QlqIMxVe5OgLsuxJbndwO7mZlr4rxp+Xzy5JJONWsKhUIx1li5ciUPP/wwBw4cADTH/B//+McDFmDQPxGm6zL92MzQ+osNKl2bd3sCEe5bsxeB4OvnTelViH3h9ElsPtzKEx8fEQ7RsZSCUShGATsaIuxoOMx9b2tZtP98/XROKs0a4agUCoViYIyEY/7LQohXhBDXCSGuA16gS7H9aKfjNKTTZuIb503tU4CluGBmQft9Yx/jFApF/7jyD++zo8Y90mF0QwjxKyHELiHEFiHEM8m+tql9PxBCVAghdgshLu6wfb4QYmty3++EED0ZVCsUinHEsDnmCyHMAFLK7wF/BuaiGan+RUr5/eO66gjjtJlw2kyEovE+m3gfbjkypTZaVjUqFGOZIie47OaRDqMnXgNmSynnAnuAHwAIIWaieRzOAi4B/iCESM2p/hH4GjA1eVPmHgrFOGYoHPP7mo58HzhFCPGwlPJLwNMDvsooo8EbxGzQs3pnPa/vbOCOy2f22Mx76allPPTeASo9MfRoilWJscHDZgCz1OrlvKNo1aji+LACeRkmPjknn1AsgS8U42Cjn7On5XD1aRN7/FsbaaSUr3Z4uA74bPL+FcBjUsowcEAIUQEsFEIcBBxSyvcBhBAPAVcCLw1b0AqFYtg4mmP+kiVLBt2s1SSE+DJwhhDiM113SinHpChLtS76xMw8LpiRx1lTXb1+KJiNesqy7VR63MQ50ihZMTgEYhCk82pHiw5Cqs/RmCM3TU9Jlh2nxcCWmlaqPRFe393E3647tVM5wBjhBuDx5P0iNFGWoiq5LZq833V7jwghvoaWNSMvL4+1a9f2KxC/39/vscPBaIpnNMUCoyseFUvvDDSeu+66q1fH/GAwyG233caPfvSjYz5vXyLsv4AvABnAZV32ScZoZizXYeWOy2fhsJo6OYh3dQ1PUZydBvvdAIwiW6oxgQltNWhPmsoCoIPsdB0NnkR7hlEJsKGjNzf+fDsYDQbCkRjNgf67+583JZMbz5kCwASXDbNBj9mgp9EfosUfoSDDMqoEmBDidSC/h123SSmfTY65De3X9p+pw3oYL/vY3iNSyr8AfwFYsGCBXLx4cb9iXrt2Lf0dOxyMpnhGUywwuuJRsfTOQOP57ne/26tjvpQSj8czoPP2KsKklO8A7wgh1ksp/37MZx7FhGPxTgLsxa01vL6jnjsun9VJiIWjcWrcY9gXYYAYADNgt0FjoLuIOqXQxq7aAGGpLVjIcegJxuMYBUQTOtJsevTSQFm2lYpGP0YDTHCmsaveS0mGnenFDnZUean1+inLdmA2hKh3BzHqwaKHuhPvJR8WehNXdX44FvOUhcV2zpuZx/VnT+3RcsJpM0HugEIcUqSUn+hrfzLz/yngAnnkv20VUNJhWDFQk9xe3MN2hUIxDhlJx/xxJcBSvmE/vWo2DouRXIeVS+cUctaU7tOS4VicRl8vxk3jmFjyJiJgFJqLfke21ARwWECXAKdV4AvFObs8nw/2N1GYYdFyBFLS6AvjDUbxhST7GiNMyDCyo85DWyxOIhFHCAMf7m9Fkqy1U3Vho5rfXzOPs8tzj7qqeCwihLgE+D5wrpSyoyX2KuBfQojfAIVoBfgfSinjQgifEGIR8AFwLfD/hjtuhUIxPAyVY/6Y8fsaLEqy7Pz0qtlsqfRwx6odNHiDWIz6HqcizQZ9j6r3RMEf6y7ADIBegDukGbTWeSQJCev2NxGMxHBaDNS52/CF4niCUcIRSRxt+vGQO0o4CjXuNqrdISZm2ynOMqnFDmOEaDwxLgVYkt8D6cBrQohNQog/AUgptwNPADuAl4FvSClTXxf+G/gbUAHsQxXlKxTjlpRjfkcnGp1Oh81mG3LH/DFPqm1R6ueUXAfFmWl9FuWDNq1yw1mTueXp7YMSRxrQdpQxxU6o6t2sftjRATMLbLgDAao8kGnTU5JlY05JBjurvUzNS2N/Y5AvLCrl9V0NmAw6Ejod1542gdW7Gtjf4Mek0xFHImWC5mCUc6dk0+iPYDUb8YSiWESE0CAY4eaYtYbqI4nDAN5+zuyVZuho9iRoGyIT4BInTMvNYlZROvsbA8wsctDkCzOtwInLbmHz4Sam5mcQiMTYXu0mGIkTjMSZW5pBgVMzJKxs8fPwe/v43pI5fHp+6dAEOgqQUk7pY9/dwN09bF8PHJ9To0KhGDOMiGO+EOJMYJOUsk0I8UXgFOBeKeWhAV91GElNP664uJx7XtnDiovLWTjJhcWox2I8+lL5pQvLsJkMBCIxfvLs9n5bKVjQptimuAzsaYqRaQGLyYA5GqMlWfOUawNfQFshWJZlpt4dbhdgi0ocVHkD+IIxPBFwGMGoA4tJRyCaYFquk2pPgErP0OWR0s2woNTFjWdP5ObHN2IkzplTc7juzIkUZlj53eq9TM5NI5oQrD/UyoIJmVw0Kx9vKMoTH1Xy+dNK2VbtwajXMafYyeMfVeI062iLSU4py+LsqTk89P5BvnfxNN7eU080nqA0O42KBj/xeILKljBnTs3k4ff3YTabuHx2AW/vbSHLbuaTcwt4aUsN7kCU8nw7eU4bWypbeXdPMxE5Mu2hCtLgV1drfe5TTbMPNvnxBLUlHfNKsrBbDFQ2a+nsRZNdmI16wtE4jf4QxZlphKNxdtd5qW4NEIjE2FblptEbxhuMsLfWTzwOudl6sqxWTp+SzXkzCznQ6GfBxCzCsQRTch2EovF+tQc6f2ZPNerd+e/zpw/wFVEoFIrxxWA75vcnE/ZHYJ4QYh5wC/B34CHg3OO68jDRsW3RtaeHuOeVPfz66mNbtXV2eS6/eW03VqsRr79/okeiZZGqPTGyzWA06GjyxXDZ9eRY4gg9tAbAaoRQFDKsBg61aGkcAeyo9eJMNxKJQZFdEIpDNCaJBBL44rDusIe0IfbnvmJeETEp+PhQU3vd1rOb66hsCfL9JdM5uTQTAcyfkEmLP4TNZMBs0OOwQCSW4MkNVUzOTcNmMlCUYWNKrp2DTW1cNb+YJzdU4rAYOak4k/L8dA62tLGt2sv+5iA3LZ7CRwda+foFmXx0oJXrz57GB/tbuOyUUj67sIwH3j1AUaaNsBQsmVfIrEInP31hO/tr/ARGsLVUbRt88f6PKM0wsmhySqzaOKUsq11ghWNxJuWkA9DoC2KO6XFYTZgNuuQXAz0LJ7mO6bpd2wCp/owKhUIxNuiPCItJKaUQ4gq0DNjfk6uIxgypqciH3j/Mios7r2Bo8AbJdVh7zR6EonHMRj1fOXsinz65iG8++j6VrUe/psEA4ZgmsAwWiEUTxCVawXqy1n9OnhmT0cyGKi97atrINIMnnDQvjYG3NUqOReANS4yy+zTXUE1jpTjUHKLWG+CxxiDTc4z4A3FcDgPIBD99cRf3LJ2Lw2JkT52Pf314mE/NLWD1znpsZgNLTy3h72/v52BTgJkFBryhCGlmA8WZVtItBkDgDUUxGnS8uqOO7dVeorE4FoOOZn+EXXVepheks+FwK3OKnHztnEn864NDXD6viEAkwb2r9xKOxPlgXxMvbqljc7UfifYL3fFlOqXIzqllmdz/biWZNmjoXlM56Bx2Rzm8oYb/bKghArhsOm48axIHmoM0t4VZNDFLW5W7rZ40k555xQ4+POTmritmc1JpFp5AZDzXXikUCsWYpWvbouFo4O0TQvwA+CJwTrJlx5hrpZjKiAF89/Et/PrqufhCMX7/RgXfuaiczZUePjm3sJMQ8wQivLStFqNex/YaDwVOC+dPL6XRE2BTVRM13t6v1xaDsgwjB91RhARvUlxZzQJrGwQlbK8PU5AexaKDQAKIQY4N6pLvcbHDADpIhGOERqB63ayTxOLaVNquRi2AaCTGhiofs/KtPPr+ATZXeql0Bzh9Ujb+YJhQJMZEl52n1h/iw4PNfPO8qdR7g6x8djtOm4GNla1sPNRKNJbg9me2suy0CWyv8dLqDxGOSeYUObhz1TZmFKTz+9d3c6AlQDQS5fVtNdT5Iqw/0ExBugWzXlATCrGv0cOsgkzMaJk6vYCYhDShidQ6n58H3/UTZXgEWEdSvnJNgQQ7av1sq3FTlmXj0XUHaQ1GsJv17KyLs+mwB6cV/uefG7hgeg7vVDSTYzMSSySYV5rJtAIns4szMBl0tPgjZNlN+EMx/KEYWXYTu2u92EwGmvwhWvwh9jW0UZRhwaAXZNot1LYG2Fnjwx+OsKMmQJgjhlZ24NTJmZxR7uLUiVoGzmTQkW4x8Lc3K3huQzUtMc0FP7Vqdk6+hTp3iPI8JxsPeUi9rA7gS2eXYtALLp5bzMzCjGF7rRUKhWKo6alt0ZtvvsmKFStYuXLlgM4pejMfax8gRD7weeAjKeXbQohSYLGU8qEBXfE4WbBggVy/fv2Aju1YoG826Pnfp7cyrzidXKeNN3Y2cNeVs9sL9T2BCE9trOStPU3ccsk0Nh5u5dVt9dx66XQm5aTjDUb4cH8z339sc4/F9mlC+8DqurpQ0Z0MI7jVEslxhwXIzxQUpqfz+TMmkuuwUOZKG1DbIiHEBinlAiHE7/ox3Cul/OExX2SYOJb/YePF6HIoGE2xwOiKR8XSOwONZ926dVxwwQU9WlTYbDZWr17da0Ys9f+rp339yYTd3LFht5TysBBiVj/jHjWkCvRT9WGeQIT8DAutwRhXL8zlvGm57dOS4Wic57ZU89aeRiIRyc5aH4smZbN6ZwO7an1Mykkn12FlXmkGWVlG2lq6KwidAfRKWPQLJcDGJyHgYKvkYKuX9w5vbt++9OR8Pn/6xG61bP3kCuDHRxlzKzBqRZhCoRh73Hvvvb22LQqFQtx7772D3jsyxYVoJoYdWdLDtlFNxwJ90OwnvnX+VEDzA3PaTISicdbsaiAYiXG4OcAPPzUTh8XY3uLoF1fN7dTuyGExcfrEXOLRamp8R65lAAJR5T2qUPTEEx/X8eTHdTz99dMHIsR+K6X8R18DhBCZA49OoVAourNnz55e2xYlEgn27t07oPP2KsKEEP8NfB2YJITY0mFXOvDegK42wnRcERmKxtlwyE0wEqOiwc9N507GaTNx3nSt38oFM/LahVlKdDX5tdWL4agebyhCSZadFRdPwx+MULOjsf3ccbSiOSXCFIru2IAHv3bagDJhUsr/G4wxCoVCcSyMRNuif6E5QP8MLb2fwielbBnQ1UYRFqO+XXA1+oI4baZOq9IsRj2haJx3K5o4c4qL/Y0+rvv7B0zJc1CUaaWiwc/vlp1ESZadzy4o5cUOIizdBNE4ZOjBYTPS2hYlFEU5wytOeBYW23noprOO20ZDCPFL4CdoNnsvA/OAb0spHzn+KBUKhaIzQ9W2qK8G3h7AAyxLrojMS463CyHsUsrDA7riKKLRF8RhMfHv9dV8bkER/15fzY1nTewkxM6cohm7zizM4MEbT8NlN2M2HMmEAcwvy2JmrokdDdp6OG8Ecq2QabdS1RokI82AgxjVo8gJf7RgM4BBB76I9ssl6dloVUf3RuKK0YcZSDUt0ANzix1cs7CUK04uHmz/souklLcIIT6N1kz7c8AaQIkwhUIx6KTaFt11113t05I6nQ6LxTK0bYuEEP8D3AHUc+RzUAJzB3TFUULHQv2U8OoowFJ0/ODouuTeE4hgNur51weH2gVYisYgxGJBAjFo84yEf/vopyTDSKU7it0IdgOYLYK2kCQWA6cePB3mczPM0DJMLYn0qKnk/uA067jlkmlMzXNgMujwh2KU56ezp04rkDQZdJS50jrVUQ4iKZucS4FHpZQtHXu6KRQKxWAzIm2LgG8D06SUzQO+yighZVEB3Qv1gW4CzBOIdNseisbxBiP84qVdmAw6bl0yg5LM7kvuJdDDoslxgwnNByv1syO5FmgJaRmtPJuesmwbvqgkLuM0+cIEgwkMeqhzR0nXg04IIjFJm1+2f7J6uqig4RJgoARYX6QBUwusnDbJxRfPnNRj54mBWFAMgFVCiF1o05FfF0LkoC3IVCgUiiFjsNsW6foxphJtWnJMk8p8Vbb427f11brIE4jwhzUV3Ldmb7sYC0XjrN3dwFMbKnljZx3rDzdT7Q6wpdpLUXp/Xsqxgx7I6uWzNC8N8jPNZJpBr4d0s+CUIq0VT4YJ8rLSsRih0K4jISAQlzT5gwQjcVx2M4Zkk2u9AEeaAaQkKLU06wj331b0wdKT89n+80/yn+Xn84PL5h5T66/BRAihA54DTgcWSCmjQADNvkKhUCiGjK6O+evWrTuu8/W1OvI7ybv7gbVCiBfo8BkppfzNcV15mOkp89UXTpuJr583pf0+aFOTp0/KxhOIMLPQyfcumc7Mwgx213r5i2/oK5ayrdAcHPr6KGcy8Tc1x4FEx4eH3Rg5srCgvg2umZ5FWzjO9jov0/OdzClKRyI5Y7ILSNDsD3LZ3CKa2qLodIKSDCvNbTFiiQRFWRKjJ8RlJ5fiC8U41NxGa1sEm1FHc1uQGl8Cux6MemjtmmY7RuYVWKnzhWnwJ5BAlgnCCXBaoME/Mo2+R4ISJ+Sk2SjNtuMJRMnPsABQ5w6h1wncgTC5DiubKpswGQXNrRKDHlqTacGlJ+fzy6vnj+AzOIKUMiGE+LWU8vQO29qgR99khUKhGBSGwjG/r+nI9OTPw8mbKXkbsxzLN/dUvVdXnDYTV5xczHnTj5i7njk1hz9/4WSa/CECkRilWXbueHYbZ0zOYs2uepx2K6UZFvY1edHrDTS0hOnZ8q1n0nQwtSCNqsY2Mk1QlGVhT12o2zQg9Dw9eKx4kif44LCX9ORvSBQtOzajII1ttW2YDTq+cUE5vlCMdIuB9/Y1c9HsAg63BtELwZdOLyMrzcIVxU5MBh1bqjwUZ1h5/KPD1Hh0nFeey/SiLKbkpmEy6Khzh3h2cw11HjMLJ5uZlpfGp+YV8be391PnDvHRvkZaenhigiMteEATqEVOqPRAfroBh9mEOxTHZY0QS0AsBm1xaPN3P9dwcFpJOrsbfPjCkGWGz58+gfNmFhKJJbBbDERiCVr8EewWAx/sayDPaaPeE6DJH8ETiPL2rgaa+znNnWOGeaVZ/PRzJw3XFOFw8qoQ4irgaXm0th8KhUJxnKxbt4577rmnk1dYIpEgEAhwzz33sGTJksE1a5VSDkzWjTFSDvlmo769eLiyxc+D7x5kZqGTNLOBxdNyOxUWW4x6LEZNgL24pYbXdzZwx+Uz2z/oKlv8uJwWvn3xdL598XTMBj1mg5639zTw1PrDHDrGAqe2BGyqPvIlv7Wu99KX4xVgXfF1SBXFgWZ/iBwT/OODavY1BJiQa2dGfjrba7xIIBpPMNll48JZBTzw7kFe2lZHcZaVyTlpbDzUik6no9Bppdob5aI5Vn7z2h4cFiNN/jCJhOSaU0t4ckMV71SEKclM4/ktNZw9NZfrz5nCuv3N5KSbqXWHKMi0sqPGy5QcO4I4LcE4U3NsvLy1jnBMADHqfDHqfCM7kz67IA27ycj8UgcXzilif1Mb7kCEC2fmkZNu5d2KJqYXOHssXF84yTUCEY8ZvoNWohYXQgRJ6nEppWNkw1IoFOOREXPMF0I8R+dkA2g1YuuBP0spx0wxbMfCfNAE2Gvb69ha7WZOcQYXzswnHI3z4LsHaYvEWDgxk5x0a68ruyxGPWdNdTG3xNkp01CSZecPXzil07U+3N/E8sc2D6jou+tqvZG0a6j1xXGawa6D+ROcNARiBKMxTEYdLquB9ypa2F3nw2oyMKMgnSm5acTiR6KdV+ykttXP4xtrmJ5v58wp2VQ0+Dl1gpNYHF7cVs9Xzp7E71fv5dEPK5manc7nF5by7w1VCASXzyvinld3sSgzi9qWIELG2dsUwG7SU9kcBCSJWOdX2QBcNMPF27ub0Onh1InZbDrUTNMgF6Bl6OELZ5QyISedDw60cPWppZS50gDaVwhOL3ACR1bdpixQFMeGlDL96KMUCoVicBgqx/z+VJPvB/zAX5M3L5pdRXnyca8IIS4RQuwWQlQIIW7tY9ypQoi4EOKz/Q/92OipMB/gpFInXzp9AqdNzMJi1GM26smwGhEIPjrYyv5GHw3eIA3eIJ5AhAavpoRD0TiVLX7+9GYF//6oCk8g0u3cHR+XudKYlDuwKaGuwm0kBFhqWnJmroloGPwJeHd/C8FInGp3iE+fVER9W5SL5uTz40/NxJVuwRfU5s3eqWhmZ62PyblpnDIhk5jU88lZeeQ5rHxiRh4z8h28vaeZTVVevnbORLLsJswmPadNzODWT83gQHMb1S0BMtKM1HiDTHalkZFmoiDTgsVs5OypLhIJyY46H7FYopO4KrDD3OJ0TCY95YXpfHZhKWdOy+GsGQVMzRncKTp3HO57+zC3PL2dT84pJMuuzd6bDXq8wQieQIRGXxCLUU9li799wYcnEGm/KfqH0PiiEOJHycclQoiFIx2XQqEYn5SXl6PT9SyZhsoxP8XJUspzOjx+TgjxlpTyHCHE9t4OShq83ofWe7IK+EgIsUpKuaOHcb8AXjn28I+NjoX5qanEF7fWkec0k2bS843zptLoD/HUx9XMn5BJRa2be17eRb7DhM1swpVmJBiT/PBTM/joYCvbqt1MyrFz0cx8qt0BfvD0Vn69dB4ANz++iYRM8INLZnJWuVY/dv91C1n5zFZe3zv2Gg74Yppi7+iHZpCS1kCUIoeJrdUeDjS1kWXR8+LWAAsmZPLE+io+N7+I2fkOqj0htlZ5qGoJct60XG59egsuuxlPKMLJJZn88c29XDIzn201Hl7f0cDsgjTW7Wulyh2iwGEmGk/Q4A3T6A6wu9FPaXYah5sDSAGtbWFicZDxaLe6sTKXk2hMcqg5SEJK3t7byJQcO4lEgmbPsVTmHRs3PLQBgAK7gekFTiJS4kozs7fBx9fPnczv11Qwq9CBK81AVWsYi9lAusXAFxdNoDgzDYtRT4M3OB5ruQaLP6B9HzkfuAvti+J9wKkjGZRCoRifDLtjfgdyhBClKYd8IUQpkCpW6eur+0KgQkq5P3ncY2hLyHd0GfdN4CmG8J9nR2PWlM9XrsPKpXMLOWtq57qbKbkO/vblBQCsXLWDWCKOQW/QBEMwyn8vnozZoMcTjDLJZceo13GwqY1Vm2uwGXSs2dVAvtPKjz45kxe2VPPDZ7fxkytmU56fjtmgJ8thJU0HocTY86PqmIETwLpKH+DjzT1N7dvfrdAE5sPvH2Zitp6/r6loLyQ3AU4zfFBRR5U7/P/Zu+/4ts9q8eOfI8uybMszdvaebZo2bZPuTSltgdICpexZ4MIFbrhQ1oXbNLc/1uXCZVxWKRRaZhmFULroSmeaJmmavaeTON5DtmVZ0vn98XwVK473ku2c9+ull6TvPFIS5/gZ5+G+5/ZS1QpnT86hoq6Ne184RCgDmuOwrQzCLbC7opY2hEiLEgxCeWM9dY3Kb1/aR0MESrKhrgWys6CuQ/fiGROz2bC/nsL8DNriCRIJZVxeFo9uqRy27/5oOMbRXdVkAjmZEG6D237/KhFg+7ETJ/ONy4K/risjMyPBuNxMDta2cfbkfM6ZUUhhKItYPEEsnqA4FORgVZimaJxoLEE0luBgdZgpRbkcqG6kvC5Cc8StRJCbC6rQGIbGTiOE2cU+miMJikMBAhkZ7DraQqYPmhOd/wPvOBmio0m5MK0oxHmzinnDOdMoCWUNRTJ5gaqeKyKvAKhqrYiM6olDxpiRK20V84HPAs+JyB7cz99ZuOKIucCvujlvCq7GWFIZcEHqASIyBXgz7rfZLpMwEfko8FGA6dOn9yLkEyXLU5TmZfPQpiM8vvUYd7zpDO8/hgBPba84YSHvqUW5NLRE+fYti2mItJHl99EacynI/S+X0RhpY/ORet60eDIv7K7ku4fqWTqjmMsXlPDS3houmTeOF/ZUsWp7BfMn5PONR7ZTnBPgpnOncNu1C/jAJTOJxhL8+x9eoSYcQRAaW7XLxCDIyKtC2dN0tDiwu/rETxQFKluh8pjLliq8pGn9kfbfLJIlEY55m5qa2+/W0gK1Ld6dvcTumNeY1drJ+K4t5W5nS0N7HDUt6alE1gbUezF39edc3QrJVLey2R38wsEGXjjY0Kt7pH6PeJeq6yrzSrG3xt2zPLU7tJs+757+7I82wdGmMGvKwvzwWbe6WWkWnDtzHEtnF1MSCvLmJX3/d9xBm9eKrgBesVZb2coYM2TSUjFfVR8SkXnAabgkbHvKYPzvdnNqZ2uIdPz5/V3gC6oa727JEVW9C7gLYOnSpf2ajj6tOMShmjDnzSzivJlFx38zD2ZmsGRGIQBXnz6BrMwMfrfmAKv3VHPnTYuYWpTL3zaU8cimcr5581l8+LJZAFSFWwn4ffzupQM0RaIE/D7eumQ6b13ixgDtKG9gw8E6Pn/9AvKCfrL8GccHZyfv/Yd/uZiGSBvldRE+/suX6arU2EhLwIzpq8pWeHRHNY/ucAtvbD9Sx5duGNDKZ98HHgDGi8hXgZuB/xxwoMYY043BrpjfXbHW16jqkyLylg67ZosIqvqXHq5dBkxLeT8VONLhmKXA770ErAR4vYjEVPWvvYq+D9bsreKrD22jMDuTG8+ZcnzWY31zlJ8/uw9FuemcKZSEsli9p5oLZxeTnx2grNZ1GYlAayzOy/traY7GOFIb4Y2LJ5EbzOQrbziDJTOLKcgJnDDj8pbzpjK7NK/T2W+RNtceUhoKUl4XYWJJNlrdQni09VEa0w8/ff4Qly2YyKXzx/frfFX9jYisA67G/cJ3k6puG8wYjTGmo44V84eyJewK4Enghk72KdBTEvYyME9EZgGHgXcA7zrhIqqzkq9F5JfAg0ORgB2qCfPVh7bxudctYGJhkNJQkGBmBpG2+PHK+Ifrmrnjb1v59tvP4itvPJ38YIC9lY3c8betfO2ti7hqwXiy/BmsP1hLIEN41wVuAHVqKYrkeLNrzpjI5fNLT6g9lpRMvv607iBPbqugMCfA+oO1XL1gHOe8Zhz/+edXqR3Da04a884lk3jD4qn9TsAAROQ+VX0vsL2TbcYYM+iGtWK+qi73nj/YnwurakxEPomb9ZgB/EJVt4jIx7z9P+nPdfsjy59BXpafZ3dV0BJTFk7K5/pFk3hky1FuPHsqBTkBCnIC3HbtfErzsvnbhjJUYfvRBv7jDacxd3w+kbY4ZbVN5GRmcMt509h6pJFtRxu5fF4p4MoMPLH92PHxZvnZAVrb4uytbGR2aR5ltU2UhoKsPVDLuNxMDlW38JrTx/O6hRPZWd7I1x7axj+3VSIZtK8P1EGG94hhg1/M6DA5L4MrTpvEF68//fjyX4PkjNQ33viwkbGukjFmzBn2ivlJIjIB+BowWVWvF5GFwEWq+vOezlXVh4CHOmzrNPlS1Q/0KuJ+yM8OsGRaPve8eIBL55ayvi3O+FAW9798iMJgJufMKGJzWT3ffWInn756Pk9uq2TpzAJ2V4R55VAtAb+PdQdqeXJ7Be+9YAbRWILqpggFwQCPbzvGhLwsdlY0cuHscZw11RXj/NuGMn7y9DYaW328/dwpPLj5GG84o5Sls0r5ygOb+Mw1C5g3McSRuhbOnFrIoin5rNpRQU03A8DijL4ZlWbsmpzn59PXLKAgO0BRboCA30c0lqC2KUpbPEFbPMHSWcXkBwODloCJyJeA/wCyRaSB9rGnUbxxo8YYM9jSVjEf+CVwD/Bl7/1O4A9Aj0nYyKLce+uF1ISj/M8/d7DtaAPvWDqVz//pVWaUZHOwpoW8oI+fPbeX/3zjQgJ+HzuPhfnjywe5f00Zk/IyaYwm+OKfXyVDIDsrg++8/VzueX4fT2wrR+MwdZwrRorAy3vK2Vcd59wpQd5w9hT2Vjfz+7VlPPDqUSKtbXzz0e0E/RnsqWjg8rklPLWzijMnhWhoDtMyRpq58jKg0bLGMWVaAVwxfzIXzinl/Nnjhr2Omap+Hfi6iHxdVb80rDc3xpyyhqpifm+SsBJVvd/7DTTZzThq/muNtMX54v3r+eumCsKtcTYdaeKOG85gUmGQacUh5k3IZ8vRBv65uZz3XzyTH63aA8Bf1h8mPyuDHeXNLJ1RyKtHG7hp8WSaWuNcMLuYJ7cfI+D38dqFE7nm9An88Ok9rHiTu+7dz+7jnJkTaI4eIZQd5E/rDvHZaxfw+5ey+c3qA0wqCvKFa0/jkS3l1DZHeOlADefPKmLV7tpOp5SORD4g2wf5uRk0tsQJx1xXaUnIRzjiskgVKPRDSysEAtAcheJcIRpT/D6oHrpaqV3KERCfW8Tb9N74XD8PLrt8JBWP/bKIvAeYpap3isg0YJKqrkl3YMaYsWf+/Pls2LCBROLkVpKhrpjfJCLjaK/HcyFu7chRIZiZwTduOZc543fwqWsWnrR+5PmzSzhrWhFvOHMS4/OzWTgln2nFIaYU5pCVmcFVp03kzKmFHK5rZnZpHpWNLZTmZfOei2Ywd3z+8dmPi6cXHr/uZ65ZAEDrte45y5/hxpxddzpvXDyZcaEA04pDLJlZTEMkSmMkxuzSPFZtP8a0cTk8v6uCrz68i2kFMKu4kEhbjBuXTOOPa/aTUOVgRYT8fFc3KyMD/H6YXpjf63pSqaYXwpvPnsH4ghzmTcgnGkvwj1fLOGdGMefOLKYmHOX5neVUN7lSGs2tMT593ekE/D4Cfh95QT+tsQTldRFCQT/jQgEaI+2rfie7qAJ+HzXhKJMKg7TGEmT5fVSHo9SEo0wsDBLw+whHYkRjCV49VEMsnuBgdTMv76+gvDpOuJPYJ+a4z16cE6QqHCEjA6rqoQUIAa89czxnTC1genGIvZUNLJlZcnwpoZpwlIqGCFXhCNOLQzRHYzRHY6zdV82fXinvdsxdJjBjXAaLJo8jGktQVhtm3oQCVu89Rm6WnwNVMRTIFlcoNRiECq+budAHWVmuvllpFrz+7Ck8/OphgkFoa3P1zs6dVUyGT9hRUcPEUIhwNMqxulYq+1nibHaxj/ysLHIyMzl9Sj6hrAxmluaz4WANVyyYSFs8QX1LlPkT89lZ3sDkwhxCQfej4Vh9hMwMH4umFoykBAxcdXyrmG+MGRbprJj/WWAlMEdEngdKcTV5Ro1gZgafumYhwAkJWOr+YGb2CfuTY1iSM7iS75P7547PP35ux+t2Nf4lmJnB2dOLTzgu9dhrz5wMwMLJhXzkipOz6ndfNLv7DzpITpi1Nt4lqj1Jfh/d6jAZblpx54f15n59N7nbWJJuOX8m//32Ibh9N1a8+ezhvaGns4KpqX8/RzirmG+MGTbDXjFfRD4NPA+8gitXsQA3CHaHqloRhRHiUE2YA1XNHKgO8/jmchZOziMYyODVg/VUhVuobm6hrc3VOWtscq1EcdwffA5QWAi1de1L2kwOwQcvm8dHrph/fLHy/Gz3f1urV14jWQ+tocVVWM/yu4XPUyVng6ZuT55fGY4wtSj3+PbKxhZ3DX8GrbE4rbH48ddJ+cHA8e0NkSitsQSloSCV4Qg14SjhSIx1+yo5fUoROQE/oaB7hCMxQkH/8Za6/VVhJhfm8I1/bGSzV7m/NAsireDPgEtPK6U4FKCyoZXiUICacJSt5dXEE0peVoCZ4/Ipzc/i8a2Hyc3yM7e0kOJQgMvmT6AtnqA5GuPZHRXUN7fxxnOmMLkwh2gswfSSHMKRGLNKQlSGI5SGgu6766SMiekVq5hvjBlWw10xfyrwPVyl/I3AC7ik7Agw+lagHoMe3FDGNx/dzqHa9n6qp/bU9urcGNAANNSduP1IGL768C6e2nKMqEJ2ViavOa0UBPZUNuET+Mhls3lk81Ge311Da2uMaSW5XDB7HPUtUQqzAxyubeKP6w+zeEoh58woJDfgJxpPsKsiTG24lVcO1vH286YSCmaSmeHj1y8doDDopzQvm4qGCPWRGLmBDOpbo8TjLvOfV5pLuC1BSSiLLYfrCEdizCzOZUdFA7WR1P97Dx5/FfTW6PTR/f/Ox7v54vD3LZXdHBlla0X7Opk0xthZ5d7/+uWOdYjhmX3tX25xtlv66tI5JWyvCHP+rGLyg5mcPb2IaxZOtESs7zqrmP+V9IZkjBnrhq1ivqreBuA18S8FLgY+BPxMROpUdeGA7mwG5LmdFXzq96/ix41RGuymyeT4sotmFrH5cD0Hq5uZPi6XSGuUv64/xGNbKzl/ZgGbj4Q5WNnEdWdM5OfP7eWyOUXsqmrh8rnjeGlfLeX1ESYWZJHpz2BSXoBd4SgleZms2llFQ3Mbn712AfmZLknbeLiWkpwAk/MD1EdiTC/MZndlE1WNrdSHWygMZZGT6SMzU2gNt7H6YN1JcU8O+TgSdilXMjcb7uaRKfkQi0FBKMj0ojzmlAa58dzpRGMJawkbJFYx3xiTDsNZMT8pG8gHCrzHEWBTv+9oBizSFucfG8tQBj/56ujF/bVclTmOg7VNzJ0Q4snt1ZQ3Rlk8rYDt5c3kZPo53NDE/WsPEY5EeWJnFRfOGseeY2GCgQxiiQSbDtfhEx8bgOnFOeQHs6kIt1Lb3MpPV+1GxEduIMChmibySkLsq2kiHk/g9+Vw7rRCHtp4jJYEVFe3UtHQStDvI+DrPN665gST86GiwbWAleb78ft9HKiJdn7CEIjH4Os3L2FiYfD4xIUsv4/SvGwaWqLHF4gHl4Qlu3aTEzhMrx0DnsX9HMsWkXNVdX2aYzLGjFHDWjFfRO7CVaVuBF7CdUd+R1V7199lhkwwM4Mvvn4RW4808OqRpiG/X21TC7FYgm1H6jlrciF1kTgPbzxCSW4WPn8GZ08p4JVDDeRm+WmNJnhiSzmleUHqW6JMLshmXE4W2QE/h2qb2FRWS14wkxnjcphSlMOxxgj52X4qwy3E4wkq6lsI+JSmmBLwwbO7KsnPEcKtyoS8DKob4+QHhcONncdaFPJTFY4xdVyAWFucacUhNh2qoygILRHXKjbU6Vh5M3zo3nUAzB0XJI4Qi8d4yznTeKWsntkluWw70oD4hCXT8mhoTbDjSCNnTi/khsWTmVUSoiAnQH2zi9QSs5OJyJ3AB4A9eOPCvOfXpCsmY8zYlY6K+dOBLGAXbu3HMqCuz3cwQ6I1Fqey4eSpskNhwxF3n+rDJxaKqPaqB28rP7mAxNGw23aw7uSUp7qllf0p49gO17e359VE2j9TWV3dCedFvMqvh7upAHu4wZXH2F/t7luWHPSWprpgu6vbl0D43lN7AXhmV/Xxbav3tf9O8+qhen7x/AE6KwdY6IPiQh+BjAya29qYmp9PVXMzOZmZVDe3oOrKgbS0JmhqcuP9BDq91nDJAsaFYGZxPufNLuKS+RMpDgV6N5O2Z7cAc1R1+Jo4jTGnrGGvmK+q14mI4FrDLsaVqlgkIjXAi8m1Jc3wi7TF+Y8/vcqRcDr/izWDrbsyYHUJqKtJkBzhdrAuWRMulnLUiaPf0v23oxU30eNIuIEXDjbwvacPADB3XAafvmYRbzx76kAuvxkoBCoGHKgxxvQgLRXz1d1xs4jU4Qq01gNvBM4HLAlLk9a2OPWRWM8HGjMC7a6O88nfvwowkETs68ArIrKZlPxVVd804ACNMaaDYa+YLyL/hmsBuwQ3/vt54EXgF9jA/LQqyAlw9wfO5zuPbuVXLx1OdzjG9MlZE4N89MoFA20J+xXwTdzPIqsPZowZUumomD8T+BPw76p6tF9XN0OioqGFXz27mz9YAmZGgWmFwmsWTObiueOPrwoxCKpU9fuDdTFjjOnOsFfMV9XP9C9UM5QqGlp4989eYFdlpOeDjRki+cCbzpvMkpnjKMgOEAr6j6//CVDZGKEtnuCiuSXkBwNDMcNznYh8HbekWmp3pJWoMMYMieGumG9GoPzsAG85dyrffHR3ukMxp6BbL5rKf964ON1hAJzjPaf+9LMSFcaYITVsFfPNyBTMzOCDl87lmjMm8cDLB7j72YPdzqrrLR8wvUjw+3yU18V5/VkTmVWaSyQaY9WuSqYV5RJPwJlT8/Fn+Hhs01FK87PJzspgakEWAFuOhAlkZnCguplx2X4aIq0cqW1h7vh8XjnUQGEOxOPQGoWGRPvsvf6WUsjDFbELAVmZkJEB+TlZ4IsTjcWoC8PEQj8TQrlMKsrmSF2EinAzxdlBFkzKIxTI4PHtR6ltamNifpBILMbOqrE34aHYDyWFfhKqLJo8jvrmNkrzs6gJR2lujZGT5ae8oYlZJfms2VuJCNQ3u3VGk0ZQ8gWAql6V7hiMMWagLAkbhYKZGcwdn8/n3nAmn3vDmVQ0tNAai7OrPMzR+mY2l9Wx42g9C6cUAhBPKAsm5ZMT8HO4JkxRKMjVCycyrThERUPL8QW6k8vnHKoJM604dPx+H7o8enwh7uQxt5w386RtEW+B7ta2+PHup0hbnGBmBhUNLYzPzz7huIaWKPnZAYKZGdQ3R2mNxdlZ3kg0lqDeqyhfFY6QE/Bzzoxi8oJ+bwHvtuO1pioaWo5Xmo+0xWltix9fCij5OZIxdBbfp163kIaW6PHYALYeqaMmHCUU9HOsPsLBmjCxeIJxoSAF2QEWTsk/vqB4avyV4QjhSIxwJEbA7yMaSxAK+imraWbx9EKmFYeOF2Bdt7+G6SU5ZPl9J2wvyAkc/0z7qsKMCwXIDwZoiESpDkfZcLCG3ccayfL7CGW5733dvjouWVDCFadNZHZpHuAWUJ9alDvmlkQSkTeq6oMDPcYYY/ojHcsWmREumUCkJk59PTdVx+t0Np6ns23BDklZ6uvU+7Qf174teb3O4uku5o7XTb138nN0jKtjfKlxACycXNhjDB0V5HQ97uns6cUnHAfwmoUTTzo/KfmZOp43rfjEbd0ZpIKoI9G3ROQwrgG1K18DLAkzxgyqYV22yBhjRqBjwHd6OKZ/VRONMaYL6Vi2yBhjRhRVvTLdMRhjTj3DvmyRGR0ibXEqG1sozcvmx09s4/ldVUwqzGH9wcouF7lOVZQBtSnrKk4vhH+/5kyWzio+Pu4pVWssTmleNpWNLeQHXRdaZThCaSh4wjENkTbyg5nkZweOH9sQiZLlz6A1FifL77oEk++B4+c0RNqYWpRLa1v8hHFRSTvKG5hZkkuWP4PDdc08v6uCjQfraInGKcjJZGZJDpFonCWzSgkF/URjCQJ+HwG/j32VYTIzfHzz4Vc5VO+ulw0EBOrVff62NsgNZjAxFCIcjXK4poWGVghlQl5ICAUC7D/WSmYGFOQLk/PyOH1KPnXNbUzMz2J3RRPxhHLVwgmUhIK0xROcNjmfaCxBSSiLhkjb8e8rq0MXqjHGmJEnLcsWmZErOQj9768e5v61h8jz+3j+gJdVHG7q9XVqOyxsfbAO/v2PbkGE8dkwsSiPgE+IA62xBG2JBBfNKmLtwXrmlORQVR/hcGMrc8blUpyXRTgSozoc4VBtMzPGhThnWj5PbK9izvg8dlc2UhTMpLYlRm5AyPD5mTEuhyO1LYCyr7KeKcUhKsJtvO3cSaw/UM8rh2opzA1w1pQisgM+jlQ3sfZQA7NLcyjK8rP6UEPHj9Tu2YO9+g5agBZt//wANMXZXV1/wnGtbVBdqxwvSxWH2lplf61bG7Gjx3fVHH9dHBRUhNnjcqlsbuOCWcXkBzM5e3oR1yycaImYMcaMYMO+bJEZmZ7cWs7zu46xZl81B8tbEJ9b3HkoVLRARUsjpdlCQ4sSBUIZ8Ne6FopCftbsjXCsKcb50/JZva+GUCaEo1CYAw0tUFYTZuexBuojSlM0Rms0hiSgOtzCwVZAIBxtpb4pxtTCLOpaILuplbZYjAdfLedgTYTzZxby/P46wi3HCPqhvMmNyN5RcfLSESPJ1Hw4a0oJ4ajymtNLmF4cIhT0Ewq6f3IBvw+A0lCQVi+hhs4nPJgTiYgPuFBVX0h3LMaYU0M6li0yI8wD6w4eb6U6bhhWzatsaW+CbYtDJK401rQdr+21xmuNaonDuADUhF1bUbwxTgwICTQ1tdEWh92RFoICcWB8ECrqIkSi0NQawwccrGtjWgHsq3ErAmwuqwOgrpXjDVD9qSk23MoaoKyhitwMiLbF2Vu9m/kT8mlsjTMux8+h2mZiCWVKQQ7VTa0E/UJ2ViazS1whwMqGVpoiMc6Yms8Fc8YzsTDIlMIcDtc1H+/SzPL7aIzEqAlHaWqNsXBKPlsPN7C3soG6JldiY1ZpPm3xBFXhCE9tOUZZQwOqUF7vFoSdlAtXnjaJc2YUc9HcElpjCbK8BPFoXYTbH1jPwco2gn4IBqG5Gc6ZVURLNMas8SEO17TwzL46soFZ4wPccPY06pqivOeS2f2ardsbqpoQkW8DFw3JDYwxpoNhX7bIjCwVDS18sWMClgbJxZK6SoSqo+2vky8bFZd1Ja/hnVyeMsaxNaVG6qGUXsD6UV47tSkOq70+zoq9tSft31dzYqndF/bVnfD+uQP1/PT5Q0MVHkeb4HfrjvK7dd0vD9scA8Lu9VN73OdYfah90GELsLUiytbH9gCcFHNy3F1RoXDR7IlcMm/8QBfwfkxE3gr8RbsaqGGMMYPIli06hX3y3jWDUhnfmHRIjrurr1X2pyR9A0jEPgPkAnERacFbeEFVx2yBNGNM+g32skW+gQZkhsf9n7yCqfbfixkj3rp4woBawlQ1T1V9qpqpqvnee/sXYowZUh0r5q9evXpA17MkbBRYs7eKBzeU8f5L5jEus/tS4caMZHPHZXDHGxfw7XcuHdB1xHmPiPyn936aiJw/KEEaY0wnOquYf/XVV7N8+fJ+X9O6I0e4NXuruOWul9IdhjEnCALvvmgqi6YWUZoXpKk1RlFugIqGyPH1PpujMS6dP578YGavlqPqox/hpqW8BrgTN2Lth8B5g30jY4wZlRXzReQ64HtABnC3qn6jw/53A1/w3oaBj6vqq0MZ02hT2xTt+SDTZz6GZWLpiBPA/aOPc3yyKYU+iCbcd9LCCXMojrtwWh4//eCFI6mExgWqeq6IvAKgqrUiMmKCM8aMLaOuYr6IZOB+M70GKANeFpGVqro15bB9wBXeD9DrgbuAC4YqptHo2jMn89N3Q26Wn/ue38vW8mpmFRdSHAqw+Ug1sUSC8bm51EUi7KzqeSqhH5haJFx92hRmj8+jIDtAWzxBaV6QysYIU4pyCPh91IRdiYPapiiZGT6KQwGO1Ucoyg2wv8pVnc/M8NEcjZET8DO1OIeacJSA30c0lqA56mKZPT7EjqMN7C6vx58hzCzN58mt5YSCfnICrkDpgkkFHKtvZmpxiHue3cXGcjcH0wcUZIDfD0V5fibmhTh9ch6XLZjIprIalswsIRpLUNccpdBLDkJBPzvLG5hc6AZPJuNJ1uUqDgXYfqSBxdMLaY0leGlPFQXZAXaV1xEM+NlxtJH9VW7W386jLSckKxm4xO2cyTkU5waZWBhk7oQ8WqIxYvEET207RkKV6uYWMnxCc4tSnJdJQ0sbR8KuHMTrFk0hHInx3M5jnD+7lPkTQ5wxpfh4/bBQ0M/eijDN0RgbD9WSG8jA7xM2lTVQ1dTM1oq+JeWlWXDtWZP5wGVzhqpFKl3avJ8xCiAipZyaebUxZhiMxor55wO7VXUvgIj8HrgROJ6EdSi2uBoY0Jz1seraMycDcOn88WmOxDl/dkmfjl84ufCE929eMr3LY7vbl6q77+Ls6cXdnjt3fH4nrwf+V+9T1ywc8DWg/fu65fyZg3K9Mer7wAPAeBH5KnAz8J/pDckYM1YNVcX8oRyYPwVILRZU5m3ryq3Aw53tEJGPishaEVlbWVk5iCEaY0YjVf0N8Hng68BR4CZVvT+9URljxqply5YRDAY73TeQivlDmYR1Nomv07Y8EbkKl4R9obP9qnqXqi5V1aWlpaWDGKIxZjQSkftUdbuq/lBV/09Vt4nIfQO43p0islFENojIYyIyOWXfl0Rkt4jsEJFrU7YvEZFN3r7vi4hNXDZmjEpWzE/9Z+7z+cjJyRlQxfyhTMLKgGkp76cCRzoeJCJnAXcDN6pq9RDGY4wZO85IfeOND1sygOt9S1XPUtWzgQeB273rLgTe4d3vOuBH3r0Afgx8FJjnPa4bwP2NMSPcihUrmDlz5vH31157LU888QQrVqzo9zWHMgl7GZgnIrO8WUvvAFamHiAi04G/AO9V1Z1DGIsxZgzwWqUagbNEpEFEGr33FcDf+ntdVW1IeZtLe6v9jcDvVbVVVfcBu4HzRWQSkK+qL3rLJt0L3NTf+xtjRoeOFfMHsmQRDOHAfFWNicgngUdxE8t+oapbRORj3v6f4H7bHIf77RIgpqoDq+JojBmzVPXrwNdF5Ouq+qXBvLY3wP99QD1wlbd5Cm7SUFJybGub97rj9q6u/VFcqxkTJkzg6aef7lVM4XC418cOh5EUz0iKBUZWPBZL1wYaT3V1e4fdrbfeyvvf/34WLuz/pKwhrROmqg8BD3XY9pOU1x8GPjyUMYx1kTZX1am1Lc5vV+/l1y/uIR6H8uYeTuzGtQvGcdG8EhZOLiQaS3Dm1EL2VYUZFwrQGkuQH8wkPzvA2n3VzCjJ4WhdhEmFQbL8rpdmf1UTAb+PcaEAWf4MjtS1EPD7CPh9ZPl9VHvlL5LCkdjxawNEYwlKQlk0RNo4WNXMvIkhAPKDAfZVhakJR5lekkN+MJOfPrWTspoWdlXWMntcIRk+oTQ/i/rmNsbnZ7FoahFr9lZxzoxi9hxzjR21zW08/Eo5jXStQKBBu16ovKNbL5pKXXMbLdH48ZIY8ybksni6m0k6vSTnhONLQ0FaY3HyswMEMzM6u6Tphqp+SUSmADNI+Tmmqs90dY6IPA5M7GTXl1X1b6r6ZeDLIvIl4JPAcroe29rrMa9eXHfhSvCwdOlSvfLKK7s69ARPP/00vT12OIykeEZSLDCy4rFYujaQeJYvX86xY8eOv1+7di2bN2/mtttu63eXpFXMH6EibXGCmRlE2uJUNrZQmpdNa1ucfVVhNhys4cktx9h8qA5NwLjiTHZXtQ3avR/dUc2jO9qz/YUTsthb1UpBUEiInwn5mUzJz+af26sZFxRqI8r4vAwKc7KIaoz9Xi2ryUVZZIhypC6KJiAUhJxAJpXhNoI+yAz4aI0miAHFORm0ROMkFBQfpXmZVDW2UtcKxUEfoRw/UwtCvLSvhjiQK5BQV1w0aW9NTSefxjVWJBeM7q363mZfnp+/WHbyxm1VwAEAirMFER+ZksDvD3Dm1EKa2+K8afFk3nDWZEvE+khEvoEb4rCV9vqyCnSZhKnqa3t5+d8C/8AlYV2NbS3jxLomnY55NcaMDaOyYr7pn0hbnOd3V7F0RhGPbD7Kb146yA2LJ3HfC3s5WHdyslU7iAlYZ7Yec+VKI00KtFEZbmPzEdfUVhlxfyGPNMY50nhi89vB2tYT3tdEoCbiYm1NALH2eiuHG1LrtCeob21NOS9BTSTKwZQkq6mPSVK61bQoECcA+Gjl4fpjCLB2ZxVffWAjU0uCVDRECASgps4tHwGQBYwLwexxBUTjcaLxOJFYjMJgkOa2NhKqRGLtRXqbInEamlw2khOAaNQVu63ppo7vpFwob4IQdNs62BeZwLRiH0tnjGfexDzOm1XSY/22PnozsEBVW3s8shdEZJ6qJqstvgnY7r1eCfxWRL4DTMYNwF+jqnFvPNqFwEu4bswfDEYsxpiRZ9RVzDf9F8zM4JK5JQQzM7jqtPFsPFzHE5vLO03AzOiSWu9egSagKQY13ioBdOhGbgWOhOFIuL7DlXr+u9CcvFkPCykcbXLPg5WAgYtub02CvTXlQDnQXk36hjNK+fjV808q4ttHe3G53qAkYcA3RGQBrur+ASA5dnWLiNyPa3GLAZ9Q1eRvDB8Hfglk42ocdlrn0Bgz+o3GivlmAJLdU62xOB+7Yg5f/qMtqWnGhr9vqeTBLZX8498uGUgi1gxsEJEnSEnEVLVfFRNV9a3d7Psq8NVOtq8FFvXnfsaY0WWoKuZbEjaC/WzVTn63poxj1S00pTsYYwbJILWEraRDyRtjjBkqy5YtY+XKlTQ3nzzrbSAV8y0JG6EeWHeQrz7cv+ZNY4ZaELj1sumUFmQzd3w+Ta0x2uIJDtWECbe0UVrgFgq/dP54SkNBCrwF1geLqv5KRLKB6aq6Y1AvbowxHSQr5t95553HuyV9Ph/BYHBAFfMtCRuhkgtZF2QH+OWze9hfW8fBuqG/bxCYWCScP3MC4UiM8vpmFk4p5HBNC9NLcjhY1cyU4mwKgn4mF+fyzPYKCnIyCfh9RGMJwpEYB2sa2XWslVZgXCZMKApQXhPtdHB4EDfXv/Phjp3LwfVFTS+EY3Xu/OwM8PkgEIDkqhJzSwspbwyTUGVmcQEZPiHDJ7RE48wen8uBqmaisQTRmBviU9PSQlVdrNtB7H2ViRv7NYiX7LMAUBh038/UolyCfj8+n5BIKHWRCAlV/D4fzW1t1NTHqYu57zR1qsT/vu1Mls4qZlpxKE2f4kQicgPwP7iPN0tEzgb+S1XflNbAjDFj1ooVK7jvvvvYt28f4Crm33777QMq2GpJ2AiWTMRes7Cz0kYjw7svmp3uEMyp6Q7gfOBpAFXdICKz0hmQMWbs61gxf9GigQ0LHcpli4wxZqjEVLXjlNFRVrjEGDPapI4J+/znP8/q1au7ObpnloQZY0ajzSLyLiBDROaJyA+AF9IdlDFm7Fq+fDn79+8//v7RRx/l6quvZvny5f2+piVhxpjR6FPAGbjyFL/Frff46XQGZIwZu3qqmN/fFjFLwowxo46qNqvql1X1PO/xFVWNpDsuY8zY1JuK+f1hSZgxZtQRkX+KSGHK+yIReTSNIRljxrChqphvSZgxZjQqUdW65BtVrQXGpy8cY8xYNn/+fHy+zlOmgVTMtyTMGDMaJURkevKNiMzAZkcaY4bIsmXLCAaDne4bSMV8S8KMMaPRl4HnROQ+EbkPeAb4UppjMsaMUcmK+ZKsBo5rAcvJyTm1KuavW7euSkQOpDuOIVQCVKU7iCE01j8fjP3PmI7PNyP1jao+IiLnAhfiCvz/u6qO5e/cGJNmVjEfUNXSdMcwlERkraouTXccQ2Wsfz4Y+59xpHw+L+l6MN1xGGNOHVYx3xhjjDEmDaxivjHGGGPMMLOK+aeGu9IdwBAb658Pxv5nTNvnE5Hi7h7pissYM7YNVcX8UTcmbKxT1TH9H/hY/3ww9j9jmj/fOlwpCulknwKzhzccY8ypoDcV8/szQN+SMGPMqKGqs9IdgzHm1DNUFfMtCTPGjBpeWYouqer64YrFGHPqmD9/Phs2bCCRSJy0byAV8y0JGyFE5Drge0AGcLeqfiPNIQ0qEZkG3AtMBBLAXaravxVPRzARyQDWAodV9Y3pjmcweWs13g0swnX9fUhVXxzmML7dzT4FXjNcgRhjTh3Lli1j5cqVJ8yOTBpIxXxLwkYA7z/uHwLXAGXAyyKyUlW3pjeyQRUDPquq60UkD1gnIv8cY58RYBmwDchPdyBD4HvAI6p6s4gEgJyeThhsqnrVcN/TGGOSFfPvvPPO492SPp+PYDA4oIr5NjtyZDgf2K2qe1U1CvweuDHNMQ0qVT2a7CpS1UZcojIlvVENLhGZCrwB11o0pohIPnA58HMAVY2mLqCdhnhyROQrInKX936eiIyplkdjzMiyYsUKZs6cefz9tddeyxNPPMGKFSv6fU1LwkaGKcChlPdljLEEJZWIzATOAV5KcyiD7bvA53HdrWPNbKASuEdEXhGRu0UkN43x3ANEgYu992XA/0tfOMaYU0HHivkDWbIILAkbKbqabj/miEgI+DPwaVVtSHc8g8VrhalQ1XXpjmWI+IFzgR+r6jlAE/DFNMYzR1X/G2gDUNUWOv93ZIwxI5YlYSNDGTAt5f1U4EiaYhkyIpKJS8B+o6p/SXc8g+wS4E0ish/XnfwaEfl1ekMaVGVAmaomWy//hEvK0iUqItl4v6yIyBygNY3xGGNOAbZs0dj0MjBPRGZ5A57fAaxMc0yDSkQEN55om6p+J93xDDZV/ZKqTlXVmbg/vydV9T1pDmvQqGo5cEhEFnibrgbSOaliOfAIME1EfgM8gesKNsaYIWHLFo1RqhoDPgk8ihuwfr+qbklvVIPuEuC9uBaiDd7j9ekOyvTJp4DfiMhG4Gzga+kKRFX/CbwF+ADwO2Cpqj6drniMMWObLVs0xqnqQ8BD6Y5jqKjqc5wiY3a8ZODpNIcx6FR1A7A03XEAiMibca2N//DeF4rITar61/RGZowZi4Zq2SJrCTPGjEbLVbU++cYrl9H/PgFjjOnGUC1bZEmYMWY06uxnl7XsG2OGxPz58/H5Ok+ZBrJskSVhxpjRaK2IfEdE5ojIbBH5X2CslgcxxqTZsmXLCAaDne4byLJFloQZY0ajT+GKtf4BuB9oAT6R1oiMMWNWctkiN9Hf8fl85OTkDGjZImu+N8aMOqqa7mKxxphTzIoVK7jvvvvYt28f4JYtuv322wdUNd+SMGOMMcaYXui4bNGiRYsGdD3rjhylROTTIpLT85Fdnn+liFyc8v5jIvK+Hs65Q0Ru62b/B0Rkcn9jGi4dP/sgX3umiLSIyIYu9nf7Hfbi+vNF5CER2S0i20TkfhGZICKXichWEdnc7+CNMcZ0yyrmm6RPA/1OwoAraV/8GFX9iareO8CYPgCMiCRMRLpr5b2SlM/ey+tl9OHwPap6dl+u38sYgsA/cOs3zlXV04EfA6Wq+iww5ovfisg3vee3pTsWY8ypxSrmj1Fe68l2EfmViGwUkT8lW7lE5GoReUVENonIL0QkS0T+DZfsPCUiT3nHvU5EXhSR9SLyR2+hbERkv4is8LZvEpHTRGQm8DHg373K9ZelttCIyEdE5GUReVVE/tybFjcRuRlXyPM33jWzRWSJiKwSkXUi8qiITPKOfVpE/ldEnvFac84Tkb+IyC4R+X+9+E66u+7XRGQVsExEbhCRl7zv73Gvxaizz/5LL/7kZwl7z1eKyFMi8ltgk4hkiMi3vO9mo4j8Sy//fL8sIjtE5HFgQcr2OSLyiPc5nhWR01K2r/bu81/JeIB3AS+q6t+T11DVp1T1VGr9er24NUi/lO5AjDGnjqGqmG9J2MixALhLVc8CGoB/9Vo+fgm8XVXPxI3h+7iqfh+3wPdVqnqViJQAXwFeq6rnAmuBz6Rcu8rb/mPgNlXdD/wE+F9VPdtrRUn1F1U9T1UX45ZRurWn4FX1T9593+21AsWAHwA3q+oS4BfAV1NOiarq5V4cf8PNbFsEfEBExnXznWT2cN1CVb1CVb8NPAdcqKrn4BbV/nwvPntH5wNfVtWF3vdQr6rnAecBHxGRWd2dLCJLcGtJnoNbZue8lN13AZ/yPsdtwI+87d8DvufdJ3Uh90VYGYZHgCrgLBFpEJHG1Od0B2eMGZt6UzG/P2xg/shxSFWf917/Gvg34J/APlXd6W3/FS5Z+W6Hcy8EFgLPi5s+GwBeTNn/F+95HS4R6Mkir0WqEAjh1rTsqwW4pOGfXkwZwNGU/ckFyjcBW1T1KICI7AWmAXV0/p080sN1/5DyeirwB6+lLADs68fnWKOqyfNeh/vPP9lqVgDM6+G6lwEPqGqz9/lWes8hXJfoH6V9ynOW93wRcJP3+rfA//Qj7jFJVT8HfE5E/qaqN6Y7HmPMqWGoKuZbEjZydPzTVXq/1qIA/1TVd3axv9V7jtO7P/NfAjep6qsi8gHcGKq+ElxydVEPMSVSXiffJ2Ps6jvp7rpNKa9/AHxHVVeKyJXAHV2cE8NrFRaXEQW6uJ7gWq76mpR29i/XB9T1cezYFuCKPt57TFLVG0VkAu0tiy+pamU6YzLGjF3z589nw4YNJBKJk/ZZxfyxYbqIJBOLd+K60rYDM0Vkrrf9vcAq73UjkOe9Xg1ckjxORHJEpKe/Eannd5QHHPW6/t7dh8+Qes0dQGnyM4lIpoic0YdrQeffSV+uWwAc9l6/v4s4AfYDS7zXNwKZXVzvUeDj3veSnKmY28NneAZ4szdGLg+4AUBVG4B94g0wF2exd85q4K3e63ekXOu3wMUi8obkBhG5TkTO7CGGMcf73tYAbwNuAdakjuszxpjBZBXzx75twPtFZCNQjJsBFwE+iOuy2oRrJfqJd/xdwMMi8pTXAvAB4Hfe+auB03q4399xycEGEbmsw77/BF7CdYdu78Nn+CXwE3HlGTKAm4FvisirwAb6OCORzr+TaB+uewfuu3sWN44oqeNn/xlwhYisAS7gxNavVHcDW4H14kpB/JQeWhZVdT2ui3QD8GcgdQzau4Fbvc+xBZcAgpv5+hkvnklAvXetFuCNwKfETWLYivtzr+guhjHqK8B5qvp+VX0fbuzef6Y5JmPMGDVUFfNRVXuk+QHMBDanO46R9Bit38lgxI0rPSLe63cAfxvL31k/v6NNHd77Om4bqY8lS5Zobz311FO9PnY4jKR4RlIsqiMrHoulawONZ9asWYobYqLXX3+9vvjiiz2eA6zVLn4e2JgwYwZXHCgQkQ3a/1phS4D/88an1QEf6ukEr0XvR5zY4jeWPSIijwK/896/HXgojfEYY04Bg10x35KwEUBd2YSB/UkOIxH5IXBJh83fU9V7Buseo+07SVLVQ7jZnQO5xrPA4h4PPPmcU2ZsmKp+TkTeAlyKmzBxl6o+kOawjDFjXMeK+bZ2pBl2qvqJdMdgjKr+hfbyK8YYM6Q6q5i/atUqbrvtNlasWNGva9rAfGOMMcaYbljFfGOMMcaYNBiqivmWhBljRiWv9tqCno80xpiBGaqK+ZaEGWNGHRG5AVd77RHv/dnJJaGMMWawzZ8/H5+v85TJKuYbY041d+AKtNYBqOoGXJ00Y4wZdFYxP4WI/EJEKryq5T0de7mIrBeRWOqyJt5vzi+KyBYR2Sgibx/aqI0xgyimqvXpDsIYc2oYqor5ozIJwy2Pc10vjz2IW9rltx22NwPvU9UzvGt9V0QKByk+Y8zQ2iwi7wIyRGSeiPwAeCHdQRljxq4VK1Ywc+bM4++vvfZannjiiX6Xp4BRmoSp6jNATeo2EZkjIo+IyDoReVZETvOO3a+qG3HrLqZeY6eq7vJeH8Gtv1c6PJ/AGDNAnwLOAFpxv2DVA8vSGpExZszrWDF/IIVaYZQmYV24C/iUqi4BbsMt4dIrInI+EAD2DFFsxpjB9QZV/bKqnuc9vgK8Kd1BGWPGto4V8/tbHyxpTCRhIhICLgb+KCIbgJ8Ck3p57iTgPuCDqpro6XhjzIjwpV5uM8aYQdFZxfyrr76a5cuX9/uaY2XZIh9Q19cFk0UkH/gH8BVVHVg6a4wZciJyPfB6YIqIfD9lVz4QS09UxpixrqeK+ddff32/uibHREuYqjYA+0TkbQDidLsAsogEgAeAe1X1j8MQpjFm4I4Aa4EIsC7lsRK4No1xGWPGMKuYn0JEfge8CCwQkTIRuRV4N3CriLwKbAFu9I49T0TKgLcBPxWRLd5lbgEuBz4gIhu8x9nD/VmMMb2nqq+q6q+Auar6q5THX1S1dqDXF5HbRERFpCRl25dEZLeI7BCRa1O2LxGRTd6+70vq3HVjzJgyVBXzR2V3pKq+s4tdJ5WtUNWXgamdbP818OtBDs0YMzxmisjXgYXA8QqKqjq7vxcUkWnANbiyNsltC4F34GZiTgYeF5H5qhoHfgx8FFgNPIT7+fNwf+9vjBm55s+fz4YNG0gkTh46bhXzjTGnmntwSVAMuAq4FzfBZiD+F/g8kPrr7o3A71W1VVX3AbuB870JPfmq+qK6X4/vBW4a4P2NMSPUUFXMH3UtYSUlJZpaLM0YM/atW7euSlVT6/hlq+oTIiKqegC4Q0SeBfo1TUlE3gQcVtVXO/QqTsG1dCWVedvavNcdt3d1/Y/iWs2YMGECTz/9dK/iCofDvT52OIykeEZSLDCy4rFYujaQeG6++Wbuu+++492SIkIgEODmm28mEon067qjLgmbOXMma9euTXcYxphhJCIHOmyKiIgP2CUinwQOA+N7uMbjwMROdn0Z+A/gdZ2d1sk27WZ7p1T1LlwtQ5YuXapXXnlld6Ee9/TTT9PbY4fDSIpnJMUCIysei6VrA4nnyiuv5Nlnn2Xfvn0AXHfdddx+++0DKtg66pIwY4wBPg3kAP8G3Am8Bnh/dyeo6ms72y4iZwKzgGQr2FRgvVfEuQyYlnL4VNwMzTJOHGua3G6MGcM6VsxftGjRgK5nSZgxZtTxJtwAhIEPDvBam0hpRROR/cBSVa0SkZXAb0XkO7iB+fOANaoaF5FGEbkQeAl4H/CDgcRhjDn12MB8Y8yoIyLzReRnIvKYiDyZfAz2fVR1C3A/sBV4BPiENzMS4OPA3bjB+nuwmZHGjHmDvWyRtYQZY0ajPwI/AX4GxHs4tk9UdWaH918FvtrJcWuBgfVFGGNGjc6WLVq1ahW33XYbK1as6Nc1rSXMGDMaxVT1x6q6RlXXJR/pDsoYMzb1tGxRf1vELAkzxoxGfxeRfxWRSSJSnHykOyhjzNg0VMsWWXekMWY0Ss6E/FzKNgX6XTHfGGO6YssWGWOMR1VnpTsGY8ypY6iWLbIkzJjh1lgOsVao2AHxKORNhOd/BNsfBpqBYjj3LbD+F0ACyIOiKRCLQGMZbqWeXJhwuttWvRnIgMwSUIVQIdTtBPKBFiAHxA9a7e4fmAjRciDb298bASDqYqMVaDpx97SroK0JNAEtNRCLQnMdroJEJ+6o7+V9TyQir1HVJ0XkLZ3tV9W/9OvCxhjTjWXLlrFy5coTZkcmnVLLFhkzqjWWw58/Ake3QWtlFwfVwPq7U0+C2u0djmmCY6krR8Sh7Zh7WVfhbWvwnutPrOUeLfde9DYBA5eAebF15tBTfbgWcEdBfxOxK4AngRs62aeAJWHGmEF34YUXctttt3HnnXce75b0+XwEg0Fuu+22flfNtyTMmOEWCXeTgJnuqOpy73lABVqNMaavVqxYwX333Xd82aJrr73Wli0yZlTJmwhXfQl+dwvdLDVouiAin+luv6p+Z7hiMcacegZ72SIrUWHMcMufBGSkO4rRKs97LMVVrJ/iPT4GLExjXMaYU8BgV8y3JMyY4XZsK25wvekrVV2hqiuAEuBcVf2sqn4WWMKJC2obY8yg6qxi/tVXX83y5cv7fU1LwowZbqEJ6Y5gLJhO+2wBvNcz0xOKMWass4r5xowVlTvTHcFYcB+wRkTuEJHlwEvAr9IckzFmjLKK+caMBVsfhH/eme4oRjUREeBe4GHgMm/zB1X1lfRFZYwZy6xivjGj3aG1cP/7sfFgA6OqKiJ/VdUlwPp0x2OMGfuGqmK+dUcaM1ymLYVrv57uKMaK1SJyXrqDMMacGpYtW0YwGOx030Aq5lsSZsxwaYvA6h+nO4qx4ipcIrZHRDaKyCYR2ZjuoIwxY1OyYr4bDeH4fD5ycnKsYr4xo8LfPwv1e9MdxVhxfboDMMacWoaiYr61hBkzXKYuTXcEY4aqHgAKcWtI3gAUetuMMWbIdKyYP5AEDCwJM2b4ZGSmO4IxQ0SWAb8BxnuPX4vIp9IblTFmrLOK+caMVsWz0x3BWHIrcIGq3q6qtwMXAh9Jc0zGmDFsVFXMF5FfiEiFiGzuYv+7vQG1G0XkBRFZPFSxGDMizLoY5t6Q7ijGCgHiKe/j3jZjjBl0o7Fi/i+B67rZvw+4QlXPAu4E7hrCWIxJv9oDUDIn3VGMFfcAL3kV81cAq4GfpzkmY8wYNeoq5qvqMyIys5v9L6S8XY0tvmvGstoDcO9bobZ/VZXNiVT1OyLyNHCpt8kq5htjhsxQVcwfKWPCbsUtQdIpEfmoiKwVkbWVlZXDGJYxg8SfBWK9ZYMsDiiQ8B7GGDMk5s+fj8/Xeco0qivmi8hVuCTsC10do6p3qepSVV1aWlo6fMEZM1iChXDGm9MdxZiRMjuyBJsdaYwZYmOyYr6InAXcDdyoqtXpjMWYIZUZBH9Oz8eZ3krOjlxusyONMUNtqCrmpy0JE5HpwF+A96rqznTFYcywmXJ2uiMYS2x2pDFmWK1YsYKZM2cef3/ttdfyxBNPsGLFin5fc8gG5ovI74ArgRIRKQOWA5kAqvoT4HZgHPAjL7OMqaqVFDdj1+6n0h3BWJKcHfmA9/4mbHakMWaIdayYv2jRogFdbyhnR76zh/0fBj48VPc3ZsRJxNIdwZjRYXakYLMjjTHDoGPFfFs70pjRoPYArPt1uqMYM0TkQmCXqn5fVb8H7BaRC9IdlzFm7BpVFfONMSn2PgvxunRHMZb8GAinvG/ythljzKAbjRXzjTFJ2YXpjmCsEU35aaiqCYZweIUx5tQ2VBXzLQkzZqg1lsNjt6c7irFmr4j8m4hkeo9lwN50B2WMGZvGesV8Y8auQ2uhbk+6oxhrPgZcDBwGyoALgI+mNSJjzJg1ZivmGzPmTToTyEt3FGOKqlao6jtUdbyqTlDVd6lqRbrjMsaMTWOyYr4xp4SiGbDojemOwhhjTD+NuYr5xpxSbv5JuiMwxhgzAENRMd+SMGOGy1nvSXcExhhjBqBjxfyBFGoFm9JtzPBY9V3YaMVaB0pEPtPdflX9znDFYow59Qx2xfwuk7Cefth5mlT1p/2+uzGnghfvgqf6X1HZnMBmOBhj0qKzivmrVq3itttu63eXZHctYZ/DVaCWbo75GGBJmDHdmXlRuiMYM1S1/4MvjDGmn3qqmH/99df3q0WsuyTsPlX9r+5OFpHcPt/RmFNNrDXdEYw5IhIEbgXOAI7PG1fVD6UtKGPMmNWbivn9ScK6HJivqp/v6eTeHGPMKa9kLkw6J91RjDX3AROBa4FVwFSgMa0RGWPGrKGqmN/jwHwRKQTeB8xMPV5V+1eZzJhTUdWBdEcw1sxV1beJyI2q+isR+S3waLqDMsaMTfPnz2fDhg0kEomT9g11xfyHcAnYJmBdysMY0xuxCMTb0h3FWJP8QutEZBFQgPs5ZYwxg26oKub3pkRFUFV7M1PSGNOZnY9DwnrKTnDDDwd6hbtEpAj4CrASCAG2SroxZkgkK+bfeeedx7slfT4fwWBwyCvm3yciHxGRSSJSnHz0627GnIrqj6Y7gpGnePaATlfVu1W1VlWfUdXZ3hqStiyBMWbIpKtifhT4FvAi7V2Ra/t9R2NONeHydEcw8hROGdDpIvI1b7xq8n2RiPy/gYZljDHdGeyK+b1Jwj6DGwQ7U1VneY+B/RprzKmicidsvj/dUYxF16tqXfKNqtYCr09fOMYY03e9ScK2AM09HmWMOdnBNRBtSHcUI89Prh3oFTJEJCv5RkSygaxujjfGmAHruGzR6tWrB3S93iRhcWCDiPxURL6ffAzorsacKqafT/eLTpyiAgPOl34NPCEit4rIh4B/Ar8acFzGGNOFzpYtuvrqq1m+vP/L0vVmduRfvYcxpq9K58PUy6DsmXRHMrJ8aOWATlfV/xaRTcDVuCz3TlW1OmHGmCGRjmWLEJGzvEKIZ6rqpr6HbYxh9uWWhHUUmjDgS6jqw8DDAw/GGGO6N+zLFnk+JCLzcGu0GWP645xb0h3ByPPsD/p1mog85z03ikhDyqNRRGzwnTFmSAzVskVdJmEistzbvxrwiYgVQjSmP7Y8mO4IRp5+Jqaqeqn3nKeq+SmPPFXNH9QYjTHGM3/+fHy+zlOmIVm2SFVXAI8DfwAeV9X/6tcdjDmV3X0DPP4f6Y5i5PnDhwd0uojc15ttxhgzGIZq2aKeuiMvUNV/Bc7r19WNOZXdfYONBetK+ZqBXuGM1Dci4geWDPSixhjTmeSyRSLts919Ph85OTlDt2yRqn7Ze/7Pfl3dmFPZadelO4KR69pv9es0EfmSiDQCZ6WOBwOOAX8bzBCNMSbVsC5bJCL5IvJ1EblPRN7ZYd+P+n1HY04Vl34Cqx/ahYmL+nWaqn4dKADu7TAebJyqfmlQYzTGmA6Gc9mie3D1d/4MvFNE/pxSoXpgdzXmVCGhdEcwMs26uN+nqmoCWDx4wYCI3CEih0Vkg/d4fcq+L4nIbhHZISLXpmxfIiKbvH3fl9R+CmPMmDScFfPnqOoXVfWvqvomYD3wpIiM682FReQXIlIhIpu72C/eD67dIrJRRM7tR/zGjGxz+p9sjFkZeVB7YKBXWS0igz1W9X9V9Wzv8RCAiCwE3oEbg3Yd8CMRyfCO/zHwUWCe97D+Z2PGsKGomN9dEpYlIsf3q+pXgbuAZ4DeJGK/pPsfStfT/sPro7gfaMaMLcUz0h3ByBNvhLrDA73KVbhEbI/3S9wmEdk4CNF1dCPwe1VtVdV9wG7gfBGZBOSr6ovqigfdC9w0BPc3xowAPVXM72+LWHcV8/8OvAZXpgIAr3r+MaDHSouq+oyIzOzmkBtx4zoU98O0UEQmqerR3oVuzCiw77l0RzAy1ewdUJck7pe4wfZJEXkfsBb4rKrWAlNwtRKTyrxtbd7rjts7JSIfxf2yyYQJE3j66ad7FVA4HO71scNhJMUzkmKBkRWPxdK1/sZz5513dlkxv6WlhS9/+cv853/2fQ5jl0mYqn6+i+2P4FqvBmoKcCjlffKH2ElJWOoPsOnTpw/CrY0ZJud9AB76dLqjGHmizT0f0w1VPSAilwLzVPUeESkFuh2AJyKPAxM72fVlXEv8nYB6z98GPkTnq69rN9u7ivcuXE8CS5cu1SuvvLK7UI97+umn6e2xw2EkxTOSYoGRFY/F0rX+xvPZz362y4r5qkp9fX2/rttTnTBEJK/PV+2dXv8QU9W7VHWpqi4tLS0donCMGQIP35nuCEamR/s/hgKOr+jxBSA5IzIT+HV356jqa1V1USePv6nqMVWNe4P+fwac751WBkxLucxU4Ii3fWon240xY9CwV8wHEJEpwFCtudLVDzdjxoa2CGh1uqMYmV77lYFe4c3Am4AmAFU9AvT7F0ZvjFfqtZMTilYC7xCRLBGZhesFWOMNm2gUkQu9WZHvw+qUGTNmDXvFfBE5A3gE99vmUFgJvM+bJXkhUG/jwcyYEj6W7ghGrsiA19qOeuNJFUBEcgd4vf9OGdx/FfDvAKq6Bbgf2Ir7efgJVY1753wcuBs3WH8P8PAAYzDGjFBDVTG/u4H5TwE3qmq/hvyLyO+AK4ESESkDluO6DFDVnwAPAa/H/QBrBj7Yn/sYM2KFJqQ7gpFr5kUDvcL9IvJToFBEPoIbv/Wz/l5MVd/bzb6vAl/tZPtaoH9VZ40xo86KFSu477772LdvH+Aq5t9+++0DKtjaXRL2MvBW4MX+XFhV39nDfgU+0Z9rGzMqZAZh/LlQsT7dkYw842YN6HRV/R8RuQZoABYAt6vqPwcjNGOM6UrHivmLFg3s97DuxoS9CcgXkf8e0B2MOZXVDrge1tj04l0DOl1E/h3YpqqfU9XbLAEzxgyHYauY780U+igQHtAdjDmVzRpwt9vYtG3A833ygUdF5FkR+YSIWN+vMWZIDXfFfABU9b/6fXVjTkXrfg13TIA7CmDnX9MdzcjUuH9Ap6vqClU9AzekYTKwyqsDZowxg26oKub3mIQBiEiRiJwlIucmH/26mzFj3bpfw98/AUTSHcnI9v5Bm0hYAZQD1cD4wbqoMcak+t73vtdlxfxIJML3vve9fl23u4H5AIjIncAHcFOwkymg4pY0MsaksmWKeqewyxV+ekVEPg68HSgF/gR8RFW3DkJkxhhzkp07d3ZZMT+RSLBr165+XbfHJAy4BZijqtF+3cGYU4k/K90RjA7P/wje+M2BXGEG8GlV3TA4ARljTNfmz5/Phg0bSCQSJ+0bsor5ns1AYb+ubsyp5qb+NUmfciL1AzpdVb9oCZgxZrgMe8X8FF8HXhGRR0VkZfLRr7sZcyp46z3pjmDkm2LDSo0xo0c6KuYn/Qr4JrAJOLkdzhhzotNeD4WzoW5vuiMZuZpsTU1jzOgy3BXzk6pU9fv9voMxp5otf7MErCdzrkh3BMYY02fDWTE/aZ2IfF1ELrISFcb0YOuD8NePpjuKke/5H6U7AmOM6bNhq5if4hzgQuBrwLe9x/8M6K7GjFUL3wi3/CbdUYx8570v3REYY0yfDEXF/B67I1X1qn5f3ZhTUXZxuiMY+Sp3wYLXpTsKY4zplZ4q5l9//fX9GhvWbUuYiPzYe/5hn69szKnqxZ+mO4KRb8o56Y7AGGN6bagq5neZhInIdOA5rxzFC957Y0xPakbCoPzUf9oZaYuiSxMXpjsCY4zptaGqmN9dS9hVwGzgTGAWcGW/7mDMqWbqSJi3klpNJp62KLr0q7elOwJjjOm1+fPn4/N1njINScV8Vf0VbmmQC4Dpqnpvv+5gzKlm8dvTHcHIV74m3REYY0yvpati/u2qWgH0f+i/Maea8s3pjmDku/SL6Y7AGGN6bagq5nebhKnqERFZBjSJ83MRWS8iNq3JmM60RaCpKt1RjHzRcLojMMaYPlmxYgUzZ848/v7aa6/liSeeYMWKFf2+Zm8q5n9IVb8nItcCpcAHgXuAx/p9V2PGml+8FQ4+nu4oRg+rmG+MGYXSUTE/2fb2euAeVX01ZZsxxhKwvguE0h2BMcb0WToq5q8TkcdwSdijIpKHLeRtTDtLwPrGVwCFU9IdhTHG9MlQVMzvTRJ2K/BF4DxVbQYCuC5JYwzAa7+W7ghGl0Q9lK1LdxTGGNNrPVXM72+LWHfFWicCqGpCVderap33vlpVN6YeY8wpq6UOGo6kO4pRJh/OfEu6gzDGmF4b9or5wEO9OL83xxgzNrXUwT03wJr/S3cko0wDvHhXuoMwxpheS0fF/MUi0tDNoxGY0K+7GjMWxCJQsSPdUYxOpf2rLm2MMemQjor5Gaqa380jT1VtdK05tU08Pd0RjE4tNemOwBhjei1dFfONMV3xB6FkPvjy0h1JL/SmJOAw2mFlBo0xo0daKuYbY7rhD8Ksy2Bm//7xDa9YugM40QJbdMMYM7oMRcV8S8KM6a/MIMy+Ao5sSncko0/lnnRHYIwxfdaxYn5/W8CSepWEicilIvJB73WpiMzq5XnXicgOEdktIiet2CsiBSLydxF5VUS2JO9hzKjQFoF1v4FIeboj6UJGugPo2jP/L90RGGNM2vWYhInIcuALwJe8TZnAr3txXgbwQ+B6YCHwThFZ2OGwTwBbVXUxcCXwbREJ9Dp6Y9IpMwhF09MdRTfi6Q6ga1mT0h2BMcb0WTqWLXoz8CagCUBVjwC9GYl8PrBbVfeqahT4PXBjh2MUyBM30i0E1DDiBq8Y04WWOtj893RHMTq90VYZMMaMLulatiiqrkKZAohIbi+vPQU4lPK+zNuW6v+A04EjwCZgmaqetC6liHxURNaKyNrKyspe3t6YIdQWgee+D/seSXcko9Mxq69mjBk9hn3ZohT3i8hPgUIR+QjwOPCzXpwnnWzrWG72WmADMBk4G/g/Eck/6STVu1R1qaouLS0t7cWtjRkGkbp0RzB6zbki3REYY0yvpWPZIgBU9X+APwF/BhYAt6vqD3px7TJgWsr7qbgWr1QfBP6izm5gH3BabwI3Jq0idVC+Od1RjF723RljRpGhWraoVxUcVfWfwD/7eO2XgXneTMrDwDuAd3U45iBwNfCsiEzAJXl7+3gfY4ZHWwTqDkKkAf70Eai3v6r9NnFRuiMwxphemz9/Phs2bCCROGnE1NAsW5QkIo2drBt5SEQeEJHZXZ2nqjHgk8CjwDbgflXdIiIfE5GPeYfdCVwsIpuAJ4AvqGpVvz6JMUOpLQKv/AZ+9Wb4+dUjLAEbwaUojDFmDBiqZYt60xL2HVw34m9x47zeAUwEdgC/wJWW6JSqPgQ81GHbT1JeHwGsdLYZ2RrL4dBaqDsC4YZ0R9OJEVyKoivhkVpbzRhjTpZctujOO+883i3p8/kIBoNDvmzRdar6U1VtVNUGVb0LeL2q/gEo6tddjRkN2iIu+frD++H+d8ML/wOMxCRsFJq6JN0RGGNMnwzFskW9aQlLiMgtuMH5ADen7Ot8lJoxo1VbBKp2ueSrfBNs+wfkT013VGNP2ToompHuKIwxpk86Llu0aNHAxrf2piXs3cB7gQrgmPf6PSKSjRvzZczY0BaBtb+Ee14PD30a1v8cWsrh2Np0Rzb2hCamOwJjjOmzYa+Y71W8v0FVS1S11Hu9W1VbVPW5Ad3dmJEkMwhLPwDvfQDOeg+UWLWUIWMlKowxo8xQVMzvsTtSRILArcAZwPGpAar6oX7f1ZiRKjMI05a6EgqROqgrgwMvQagEjmyEaBgOroaa7emOdHSLNvd8jDHGjBA9Vcy//vrr+zU4vzfdkffhZkNeC6zCFV1t7POdjBlNMoOQN9ElZIvfCi31sPVPsOGXIzQBC9DLsn8jw1P9/83RGGOG21BVzO/NT+25qvo2EblRVX8lIr/F1f4yZmyq3OmeIw3QXAN//ZQbGzaiRdMdQN+11EF2YbqjMMaYHqWzYn6b91wnIouAcmBmv+5mzEh3dBP84V0QbXVJgramO6IBCAHhdAfRuX95zhIwY8yokbaK+cBdIlIEfAVYCWwFvtmvuxkzkrVFoHYfLP0XOPs9EMgdmvuEvCVVsycB2ZA9GXwFkFEIhXPc9rzpUHw6+Ith3CLInQLBiTD9tRAsgQmLoXgBZE+EgulQOBsmLoWieeArhikXQ/44oACKTgN/AUgRFC8EfJDf5WIXw2P/i+m9vzHG9EFaKuaLiA9oUNVa4BkgzT+5jRmgtogb75XUUgf+YPu2SYshuwTW3wutnff/D1j4kHfvo95zyn3q6k4+vrqm/fVBr1s0krK61/HTU5ZSOvxC++va+vbXNbXuuSHNyy7Z2pHGmFEkLRXzVTWB1QIzY0VbBPY+7Z7BJWDPfx+2/8O93vIA/Pljbn3ITb+jvSfe1mYcdFv+lu4IjDGmT4aiYn5vuiP/KSK3icg0ESlOPvp9R2PSJTMIs69sb/XKLoRL/g1Oe4NrDZuyBDQOeEkacfDlQEYurtE4h1E1A3EkO+PGdEdgjDF91rFifn9bwJJ6k4R9CPgErjtynfewEuJmdMrs0KefHBy+6zGo3A6L3+nt8LlHohXiTbhFspuB2HBFOnaFpsOsi9MdhTHG9Fk6KubP6uRhY8PM2JEZhHmvg2nnQ8Um8I+D3MlAApd8xWmvUyxpC3PMCB+ETX9JdxTGGNMnQ1Exv8ckTERyROQrInKX936eiLyx33c0ZiRoqXNjwxrLofYAHFgNr/4ZciZB0SRvbcPUrsfk6Hdbs35Q1B9NdwTGGNNrPVXM72+LWG8GuNyD64JM9h+UAX8EHuzXHY0Zao3lboyXP+iWHkq+jkWg7hBEGmHbX90syD1PQcMh9zDD5wz7Pc4YM3r0pmJ+f8aH9SYJm6OqbxeRdwKoaouIWJ+MSa/KnRDzCqnGWqF6D2QXQbgCXvgBFM2GYAEc3QD50yBvPNSXw4FnQQJQMt2dF49CQ0VaP8opKVwJRTPSHYUxxvRKOivmR0UkG68fRkTmAKO5jLgZjVLre1XuhF+/FZobQBSijbjxWymqU9Z3rN524j5VqNwPoUKIRoBWyCyEtjbc+K8IxhhjTNJQVczvTRJ2B/AIME1EfgNcAnygX3czpj+S9b2S5SVK58M7fuu2xZK1vHzwyi8gM9e1boWmQfVOiEWhtRGXaBVAWx0QBX+OawmLhiF3qitN0VaXns93Knrq2/C+36U7CmOM6ZVly5axcuXKE2ZHJg1ZxXwAVX1MRNYBF+Kmhi1T1aoeTjNm8HSs7wUw6UwomXfiMQtfD8F89z7W6hbgrj0AgVD7otzVe9z7WARyS+Gpb0BT2bB9FOPZ+1C6IziJiHwKV5w6BvxDVT/vbf8ScCuumfTfVPVRb/sS4JdANvAQ7mejzdwwZgwaqor5PSZhIrIS+B2wUlWb+nUXYwaqY32vjtvaIlCz1yVrsQi8+ENoKIedj0DhLKh4ddhCNb10RwHcUd/zccNARK4CbgTOUtVWERnvbV8IvAM4A5gMPC4i81U1DvwY+CiwGpeEXQc8nI74jTFDb8WKFdx3333s27cPcBXzb7/99gEVbO1Nd+S3gbcD3xCRNcAfgAdV1QbOmJEj2VoWi7gCrBd9wg3+LpwFZ9wADUfh0DrY9gC0tXiD8e2vcFp9dke6I0j1ceAbqtoKoKrJ2Ro3Ar/3tu8Tkd3A+SKyH8hX1RcBRORe4CYsCTNmTOtYMX/RooGtg9ub7shVwCoRyQBeA3wE+AWQP6A7G9NfLXUu2QoWQviY63ZMzpDc8yTMvAyOrIejGyHeBofXQaINjm2BRByi9d6YsOEKOA9odC99xZCogbzp0HjQbSucA3Vel6gvAL4MN4MzKwDhasjJh7YEBLOgqdp1w2oCKndAzjgITYCKbW48nAhEa4AMmHCWax1sqwd8MO40aKpxJTp8CokABPwQTcPoglt+A3kTh/++XZsPXCYiX8Vl57ep6svAFFxLV1KZt63Ne91xe6dE5KO4VjMmTJjA008/3augwuFwr48dDiMpnpEUC4yseCyWrg00nurq6uOvb731Vt7//vezcOHCfl+vVwvhebMjb8C1iJ0L/KrfdzRmIFrqYNV/u4RrxqXw6m9c6YlomOMLbm/6fc/XiXVe78XJpr0460D4IDAeouUQmgJtcfBnQEueG1054Vyo2+9imX01HF0PLdUQGAfFM6B8E5TMgjPfDs9+C2ICC2+CxqNwZB0UToMp58G+p10dtHPeDevugYwQLH4HbP4jJBIw+/VuDFbDYZfckYCED6iD6AA/YvZkaDkCmeOhrbelPrLcmL5hJiKPA51lfl/G/Swswo19PQ+4X0Rm0/kSCdrN9k6p6l3AXQBLly7VK6+8slcxP/300/T22OEwkuIZSbHAyIrHYunaQOJZvnw5x44dO/5+7dq1bN68mdtuu63fi3j3ZkzYH4ALcDMkfwg8raonz9E0ZigkS1Mkn5OLbu98DOa/DgI50FLvkrPd/4RJi2H/s9AahYwMaOlQmT2zwLUM+fMgFgb84MuGRK1LlMJVkFMErQGIh3Fjsfsr4RIwgPBh95ws7tLQCA1eS1h8HOx9xB1fNA/qj8GRl4AsaKqFp74ORFyr19Z/QCICU8+Hsueg7iAEikGCsOZn7gaB8fDKb0CjQEb7IPi2IRh/1XLEu3ZdH05qhY0PwBWfHvx4uqGqr+1qn4h8HPiLN7B+jYgkgBJcC9e0lEOnAke87VM72W6MGYN6qph//fXX92tsWG8W8L4HV7D1Y6r6pCVgZtgkS1O01LnnNm8MV7DQJWPJ1p9z3+X+JmvcVcRf/G6YdBpk50OgCPKnc3ztx3FzwZ8PPnHdd8E8GD8DplzgCr1mZELzEYjXM7AErA9i1Ryvc1a7CxIN3o5WL4n0PnfDAW9f1CVg7mSIVnitUF6GF60AbfHiH2hTV2/18T7F04cmjP77K264BSIyHwgAVcBK4B0ikiUis4B5wBpVPQo0isiFXvHq9wF/S0vkxpgh15uK+f3RmzFhj4jIIm+WUDBl+739uqMxvZVamiK1REVmEGZdDgdXw/QL4dU/wtp7oGQ+lM6GJe+Gkjnw938Hf65bBzI0GSo2u6684umQmQ8VW2HeNXDweWiLAm1uDJkZeqERNR4M3DjXX4jIZlxG+X6vVWyLiNwPbMWNIvyENzMS3GD+X+L6rx/GBuUbM2alrWK+iCwHrgQW4qZhXw88B1gSZoZeauKVKrvQJWYAF3wEJp4JE05zA/QPvAAb/gAZAWitgmixK9g64wrY8ygkouCrgtxiKFsD9UcgOA7IAU4uxGfGPlWNAu/pYt9Xga92sn0tMLCpUcaYUWGoKub3pjvyZuBqoFxVPwgsBrL6dTdjBtvep90i3QdfcAlY2VpYcD289Sfwwb/DJf/uZgnmlEDtDpdsXfUVV6i1bi/U7gbaIFLjlkAiN72f55QQhMIuJxIaY8yIs2zZMoLBTupVMrCK+b1Jwlq8cWAxEckHKoDZ/bqbMYMpM+i6I/MmwnkfgrKX4cgGV74C3OzBua+FaIsrzaBA0Ux4/n9d6YfABKDQu1jQG0dl3ZFDLwKrvpPuIIwxpteSFfPdEFDH5/ORk5MztBXzgbUiUgj8DFgHhIE1vbm4iFwHfA/IAO5W1W90csyVwHeBTKBKVa/ozbXNKJY64xHc68by9rpfAMECN1A+mO+KrgbzwZ/lXodKXW2wYD68+ieYcaHbNvNSyAjC5r/Bzocg4YfyV6C1nvaiYLu7CCo5GH64BrKf4ha/Pd0RGGNMn6SlYr6q/qv38ici8giuSvTGns7zirv+ELgGN537ZRFZqapbU44pBH4EXKeqB5NLhZgxqrEcjm2HnQ/DhDNdIdHmKphxCbzwPcibCRUb3aLcxTOgfDvkFrrq9tlFUDARqvdC0RRoroWiWa4KfmYWBHIhb7JLuopmQGsrNB9jGCuyGmOMGeOGvWJ+KlXd34fDzwd2q+peABH5PW4JkK0px7wLV5vnoHf93lZ7NCNdsrUL2ivc//HDbkZjxy6/V7zavxVb2rcd9uprNXi1rVpaINPvrluxF/yZcOhl8AUhkQlNR9wDoHYv+AtwDbCWhI1Iv3or3HG05+OMMWYM682YsP6aAhxKed/Zsh7zgSIReVpE1onI+zq7kIh8VETWisjaysrKIQrX9FmyO7Glzr1OPlrqYNdjruWrpQ6e/Y7rPrz+63DLL2HGayFQCqe91btQBuRPg6I5EJrqKrxLDhCEnEkw3aux2VCOq4XVCrEoSIarmxXvZNmdWD3tlVHNyGOzUI0xo09zc/vPrs9//vOsXr26m6N71qeWsD7qzbIefmAJbvZlNvCiiKxW1Z0nnNRhyY8hiNX0VbKQ6uSz4aW73HqGGZnt+6PNsPqnsPQDEKmHh77kUv6sAtflOH4+bF+JGwrogwYvXw+Oh72PetvjrgXt4PMg2ZBdAM3VuJa0CGSUQizmzpcAaGNKgMnfL1KnE2diA+9HkDsK4I4hqOJvjDFDYPny5ezfv//4+0cffZRVq1YN3bJFIuIDNqpqfzo9u1ruo+MxVaraBDSJyDO4Ehg7MSNbagHVS/7NVa/vKBZx22ddBped57aVvQznfRjqD8CcK10St+Uv0FQP42a5pYSmnA8bfgttTW5NyMx8OLYemjtUK46ltIpqx1avDrVcfEG3ZFHrMcxI0dnvacYYM/IM1bJF3SZhqpoQkVdFZHpy3FYfvAzM85b6OAy8AzcGLNXfgP8TET9umZALgP/t431MuiTHfGUXdr//tDe2vw5N8GZGntt+zPTz28/Z/bg7fvZlsHcVJNpcmYm9z8KmP0PBFNj5CGTmQCIG0y6EbX+GjFyIJyCnEJqPgoRcYubLgkTYrbfYGsH9lfdzfCmgYZcLNLW/zShp707NLIK2RtzCFGHcmLY4rlUvEzdz0w+oWytSW3H/bJpcN264DDKLver/yYS1s6WXMrrYPszuqEt3BMYY0yu9WbZo0JMwzyTc0h1rSPnfQ1Xf1N1JqhoTkU8Cj+J+6v9CVbeIyMe8/T9R1W3ejMuNuKaLu1V1c58/hRkZ2iLtNbr8wfaWsFjEFVQFNzYsNN51USZV74MpZ7t1H2deCgdWQ8FkmHyOKz2x8zEonuu6PKeeC7njoW6/K2nRUgPZE6GlCohBs1diQsPuORFICdAPxTOhKQyt5YP/+f3jIMMHPp/rmm2LQqjEzdo8tMZtz/dmeI5fCNEGiDZB7hmQXey+qyOvuEQyWOi+z9YGyCl2i5TH29xM0Kx80AQ0VUDBdGg4AuPmu+94ytkQrQd8cHSz6/4NZMH4RS6GrBw325TOf5j0KG8mNO7vYmcACAE1PV/n2m/17/7GGJMGaVu2COhfRyegqg/hljpK3faTDu+/BdhP5NEsOftx819dN2MiDlmF0FQOhbOgagdU7Ya2FmiqhinnQtVW13IVbYVIBcy4Cio3QslCOPicK0mRmQ3nvA+2/AmqDgItkLcCDr0EVTtd/a+MEGiM9lmQKS08GSVuIe7CWS6JCU2AeAQkBpkl0NbJgP6BKJ7qSm5kZrmkqHKbS7SC8+Gst8Crf3ClNGZdBjW7oP4oTDgDpl8A2x90C4rPvNSNfdv9BKjCwjfCsW1QvgHGL4a518AL34ZJS+DcW13h2QmnQyDoWsfamqC5BlqbXLFa1BWordnhWhUbjjKgWmjJBOz133UJ8j8+1z4rlSjtCVgI15pnjDGj31AtW9SbOmGrRGQC4A3qYY2VkjDHJWc/NlVDxTZ4/X/D7idhzV0umfC9BG2tUF+GGxSf4araN9d4FeozgEyYcg6ExrlZj0s/6OqAKTDtfDi22Y3pikdg92PuuqHxLtnLLYGmWsgcD1l5EGkCn0AsDtk5MO+tUHsIqre51qdIIzQdhbrDg/cdFJ3mhjdV74Ezb4aaPW4sm8ZhzmtdwtXaAIWToWAa+DIgIwdKFsCkZAtVseuWDVe4maVzX+c+3+5VEG+B+TdBMBs23w+Fs+G0G2Dt3a6o7fRLYc9j4Iu77ld/NrSGobEGpi2Fmu1QVwHBXIhlgvoZ8OzErQ/DFZ+GKz4Pr/wWavZBa+rM5R4SsKbqgd3fGGOG0bJly1i5cuUJsyOTBrJsUW8W8L4F11L1NO6/mh+IyOdU9U/9uqMZW7IL4aJ/hf3PwaXLoHA6NB6BW+516wNGGuC574P4IFgE5RtdF5ymjFk6653wwnfgrLfD3udg5hUuUWk4BI/+B8RbAXHJR+1uaK5wCUogG1pqIVQMdV7NqVAJ1JW5gq/RBgjkwYEX3YD/WBzCyW7IQayMX7u9/fWGX564b8MvOWFWZs0e8OW70hoAVSm971WbUs77PSeU2Kgv44RWvqeWt79e/d3214eeOfH++x5pfx0ZxLIQ+x91j+P6uObmko7DQ40xZuRKLlt05513Hu+W9Pl8BIPBIV+26MvAecnWLxEpBR4HLAkzTt7EEwffz7rcFWUNneu6AOddDRf+C6y/z7VgtVSB+OGMN7ukqWo3ZJfCvNcBCuMWuGSldL677vM/gMlnQvlWKF0Ik86CslegZqdbiDvDD9OnuDFRIjDtAohUQ+UeeOF/2uMM93VuyWDpUBYjmYB1q+NszxEwkL5bTT0fkqpih1vZwBhjRomhWLaoN8VafR26H6t7eZ45lSQTMHCtY8nyFQCBHCic6p7nXOEGj197JzSWwb5VbjzU5CXw4g+hcIbbnhlw46qqdrjB7JU7YfK5bp8C9XvdfYpnu0H+dQcgHnMFYltrYfwZ7n5mZIraeDFjzOjTcdmigSRg0LuWsEdE5FHgd977t9NhsL0xJ0kmYJlB1zKWXQhXfqF9tmR2oUvMoH3GZPlW2PGgS6BmXQZPfwuqtrtEa9YVUDAJznkHxFphyx/Bl+m6Qtfc7caSRWrh4k/Ao19249NCpdAcwBblHmmCMHVJuoMwxpg+61gxf8hawkQkC0BVPwf8FDgLV0j1LlX9Qr/vaMam5BJGyefU7fuecc/JemLZhe79/udgz1NQud0lZjv+DsVz3P5YK9TshqnnQ+1+16pVssCdf+B5VydMfK7lKzMTxs2FmZe7GYfid3XC6vZjCdhIFIHtj/Z8mDHGjCCdVcy/+uqrWb58edcn9aC7lrAXgXNF5D5VfS/wl37fxYw+qQtwJ183lrv6VUnJbeBm+JWe5hKqSYvdWLAqr25KSx3UHXQtXnufcWO9AiHX8lU8EzKCsHml66IKhCA0CfY8DbOvcuUoZlzirve7d7vxX/4s1z1ZMAX++gkITXT1whRX7sIYY4wZROmomB8QkfcDF4vIWzruVFVLyka7ljrXPRg+5pKcWMQNki+cCtv+4ZKpWNTV/orHYf29LtHKyHSlEVqboOxFCBS4Aqr134VAEbRUQMlpsOXvbmxXbglEW6AtDG2pg9IFSs909cHAzRpcfy+Q7ZKtounQcAyOvgov3YMrq5CJK2sRg/qDrh5ZzX7vejZUcdSI2xqexpjRIx0V8z8GvBsoBG7osE+xlrHRJbVlq6XODWZ/+W7IGQ+b/wQLb3KtWDsegglnQvVuaK73qrx7FeoBDr/Uu/sd8xKrthao86rjl5zpquLHWoA2tyh31Q4gy71PNOAW4xZ33/ojrihKWxRohdyp0OTVG5Nc10U5bg4cWee2IeArgpwQhA8N/DsbMh0XEg/gis12LAKYhetO7axKs3SxfZR4/D/g0k+kOwpjjOmVYa+Yr6rPAc+JyFpV/Xm/rm5GhpY6VzJiupelP/Jl8PndTMRoI2Rkwf4X3aD3uiNw6EVXHJUIBCdBXcclfjJwCcDJlYORQq+CfcfZbyGoL4dgCML1QAAKJ7oWMl+Ga/lqqoNE1C2101rvxnb5c6DIq/0VzPcqIfhAm11L3JE62hMahUQthGsH4UsbKiFOLpQapfMK861Atve6BZeUJUtXpP4wEFwrYDzlvdJ1cjdCfG0B/MeOdEdhjDE9GqqK+T3231gCNsq1RVwCNvls91x3CA4861qg9jwB638D9Ydh72Pwt09Daw0gUDLHnd981HVZjl+M+08d8OXg6nkt9G7ic61UZHlFWFuBTPDne/sFiIJPYeJib1sr1O6FphpX3b3hmLuOP+juGW+CWD20HIX6Y24Qfm0yGUzQnoSMtm6tMJ0nRV2VbGihfZ3HjrXDkpQT64glv5toF/caIaJDsH6nMcYMgWXLlhEMBjvdN6QV880olxlsr9mVfH73n1yrUqwVdj3ulgba/ABkhdz4reRA92PbAHVL6QRy3PllL8HUC9pnMobLYcJiV7X+wAtuvFhmrhuI7w9CrAEyCtwajsThwHNujcOsXLc/HoOcIres0JRzoP6QWy+xcg+UPQcEICsL1AelsyE0BSq2uONHjQxOLraaTXty5aPzZKmr8ho5nNya1rGLcxS4o77nY4wxZgRIZ8V8M9ql1uwCNzsx6Zx3u+0l8048vi0CZ9zk3se8shP+oKtKHyyEC251g/PrDnkLReOSNX+We9SVuTpdZetcTajqfVAw2SV+0H5cpMEdd2Rj+9qJofHumH3Puarq/qz2c0IT4MBq+PVbSH8VeYHcKa48RkuVa22s3g/1+90SS6Xz3HJD8Tg0VUCsCWoPuxmh+VPh6HqX+M65GsrWAD63GPfhdTDhbAgfhtZGt8j34XVu0e7qHW4WafY48Oe6wrRtrW4yRc1OOOdDsPrHEGuGnGL3Z5YZcknvgbX0ubL9ULn0i+mOwBhj+iQtFfNF5BIRyfVev0dEviMitt7IWJGaoCUf0J54xSLuP/LkLMq8ie451uoG9wfz3XMs4l77s9y+oNcVOXWJS5xmXOiSv2C+S9qSx1btcNduqWlPwHY/7pK7uHedYL7bXvayK3tRsweySobhy8mGSRdAaDKEpsHEpXD5l2H6VZBTAud+CKZf4BKcWMQllH4fFJ/mEq6avTD+dFflf8Z5oAnAB4GgGxtXMA0mngVtTW4Was4EKN/iWhyrtkKw2K0aUHsIsovdbND86TBunlsXM1TsJjGMX+AK1YYmQ0slZGTABf/q/hxC46G1zi1cXjJtiL4nH5z7Ybj8KzD/jbDoFsgsPPGQ3Cmc8ONmwoIhisUYY4ZOOirm/xhYLCKLgc8DPwfuBa4Y0J3N8Gmpay+QGqlrb42KtXqtVofdGo71R2DcLNdqtc4rR1Gz063XmIjB1gfg8s/Bqm+4mZNZOa5qvSYguwh8WW74V7jcJRb+bJfUnXGzawUrmA6PL3cJTKzZtQZlZrkirOvugxd+AKfdCDW74NnvuDIX63/txoNNPAMaK+D5/3MtZq1Vw/HFwdGU2aDxVtj4WzepITMExzZB4zG33Z/lZpdOWQp7noR4FM55Jxx8AZoqYf/zkJUPcgQaKlzy1HDIfXehya7FK3wQJBOOvArN1e66WYXuzywjG5qq3eLovgy3PW8i7HjE1Var3gulp7tuZQQ2/95Nujiw1iV9TdVu4fQB8SYGBMfDFZ+DJ7/m7hWPwfq73SHFc2D+Dbgu2BSTzoXyVyCWgMgRCA/Hn58xxgyuwa6Y35skLKaqKiI3At9T1Z979cPMaNBSBy/+yHU77n4cNvwBGo+6xKY57EpBtNbg/ipEwD8OEmFItML2EGgb5KxySUZTNTy+wiVasTYoKIK8SdBU7rofJ58Dkxa5bsSMLFcmomAa7Hsa8ie7wfeL3wVPfRUKpkJwHGT4XIKiMdcidvD59gTOH4CZl0FDGbx8D0y/GBa83rUsFc6A+krQxmH8LivAPxVKTnfdhgdegOY6N6bu3HfBSz+BnY9A8Vw4510QroTagy7RuvQzEMiFZ74F5Ttgxvkw51p3TqLVzVydej6s+m/XwjV1qUusWuvceY1HILvEvfdlQvSoa4HMzHElP0rnQcN+973HIpBIuPptiTpI+LwJEwMdpO8l72/4pusSbquFQKEbL5gz0bVQ1uyF1d91x/lyIeElfmXrXPKVVL1ngLEYY8zw6qxi/qpVq7jttttYsWJFv67ZmySsUUS+BLwHuFxEMnCjgE26pdb+6kp2oUvA9q6Cgy/D0W1ePa6OA7lj3lM1EABfMSRqwJ/nEqaC6W58VsNR12qz/3nImwzZBa7ifSLh/hMO5EJOKVTvhLzZrpstkO/OP7IejqyFs97uantFaqB0LrQ0uFabcfPhzJtdkhaPuvpglVtdF93pb4CKra4VKqvIDfyf8zrYMxzLmPogZ5Ibu1ZTBkc2QHOVq61WsRsObYDmCiieB03HIHcCPPlfrjsxGIKSC+HZ/3EteeMXQeksaIvDiz9wf37jz3RrXe5/1n2PGTluRmj1bldLLbsJWqohrhDMc38GGVnw6v2AwJFtQBNkT4SWvZ3EP8jjwCr3QCDPvc6bCtWbIb/UTepoCrffL5EyqSA1AcMHl/zr4MZkjDFDKB0V85PeDrwLuFVVy0VkOvCtPt/JDK62COx6DOa97uRELJmcJddxPPACHNsM53/YdesFi7xZihnw6p9ccuEPuEfVNpc0TTnLtb401UHeFDcGKTMEuYVQNMtVsR+/EPK9gfL+bCic5dZxzAy4bqlYE5z1DpdUSYYboN7a4hIznx/O+zA8/TWXrMy8EvY/A9sfhHnXQ/iIa21DQONujNjkpW52ZtV+IO6WNhoWCWg+7B7g8tXmI3BkTfshxyrh2Kvude1+9xypcc81u9uPK3vOPVdudc/xJtj25xNvV7W5/bU2QrPX2hetcQ9wSepxXgtVyzCVfHjm/7W/rvZirdjUyYFdzdZMuC7vIhtaaowZHdJRMT/p31MX7FbVgyJyRp/vZIZGrENrWGph1mR9MHDLxGz5s+sqq9wK085zXX0ad8nR1CWuVQsf1ByA7Svh9BtdLa8ZF7kxYGUvwcXLXFJRON21zsy5Erb81a3jOHWJu5cCOx+D3HGuxWvyUphyrptBqPH28UCVO10XW04JJCIw71o4/LJr6Zl2Aex61LWMFc6C8ldh/R84sZ5WxzINZtSo3Alzr0x3FMYY0ytDVTG/N4vtXdPJtuv7dTczeDKDMOtyl2glW7yShVmnX+i6Iadf6LrOFlwPr10OV3wBznwrTDzTjSuq3A6XfQbyJ8Kim2DOVa5L8cyb3OD3YB7klsLc10LBJJcs7XjQjf0qneu63Tb+HlAIZLtr1h6AmZe468263LV2FUyAOVe40gzNNW581BlvdjP5Xns75BZAyXy3ruTca1y5hYxMmHmFa7Xb9xSUveLqhBWflqYv3AyqiYvSHYExxvTa/Pnz8fk6T5kGUjG/y5YwEfk48K/AbBHZmLIrD3ihX3czgyu7sL0Aa7ILMvk+uT+ZkKWOH1twPex7xiVJ/iBc/ll3DLjxY0Uz4JJlsO5XcOHHXD2wOVcB4lrajrziZlI2HHELd5/+RnfNYAFsXQkb74ezboHafW5A/8TFrhTFhLNct+KWB+DiT0BGwCVc6nMzIX2ZrpzFwZdg28+8CQMpXVqRY8PytY48nRV7Hc1soXVjzOiybNkyVq5cecLsyKShqpj/W+Bh4OtAamXFRlWt6dfdTO8lW7dSE6yO+5N1vZJdkLOvbO+eTJaj2P+8a5na9g+Y99r28hR5k11CdGiNm90XrnD7XvghLH4HTDnbtVZV74PN97vyB7OvhNU/gTPfBq/7Lzi01g20r9oLsZWuha1gOhzbAi/+0I1XW/XfULLQVcMPTXYlHfavcrM06w+6tSPLN7lZhdlFULnbxZ9IAAnIGu+6N6MVbpC6RgCFYAlETpUyB2MpAYMRvZSSMcZ0Ytgr5qtqPVAPvNObETnBOz4kIiFVPdivO5qeJQfdg0uQjmxwCVBSLHJi0rX7cZh6nku6XroLlrzfFTY98IK71t5Vrp7U6h9BY41LcOKtrjxFIoZrmVA34y5eD5vuh+JZEG7wBoInXLmB7Q/D4Q3w6h+geJorR5BZ5EoVHF9EGlzSkAEbHwC8ZBJx1/BluDUhj2x2+zbfD7mTIbcYWryFt0PjoKkWYuIW9o7UAX7IGQdNZS4ZSyZg2eNd6YgRx8/xGafmZM//CGZdnO4ojDGm14aiYn6PA/NF5JPAHcAx2n+FVeCsft/VdC8z6FqRksnWdO8PeNdjruBmRibMvNTt3/RnNztx77OuOzArDzb+GVrqoe4olG+EcJk7v7lDd17HBol4MmGKnzijDyDRCIeeb39f4+XgbS20l7sIgPhBw0AW5Je4Gl95U6GxHPx+UO+vnGSABoCYS8xqyiHmJWGN1a7URWuDSxYTzeAvdAkYuMH9ABTAxHNh3+OMvIRnIPH4cUltsitWaF+Ue4zY/fd0R2CMMX3WsWL+okUDG9/am9mRnwYWqGr1gO5k+ibZ/Zhs7Qofc61iOx+DaLMrLRFtgD1PucHw/ixXgV2yQQcwa7BwrkvgWutwSUCGqxWWleuWFipZ4GpalZ4GNfvBn+GqvEeqXUvVhPmuW3Hr36ClCUi4tQ4zguDL9so2CKhXS6r4NDf4v/FZIODKW7TVumr8tEGr99cu3gq+kCskm5nrWuCaj8G+R4AgIy8JG4iOn6WrBGyUt7bdUWCLeBtjRpXBrpjfmxGyh3DdkmY4tUVg79OuK+6pr8H9H3SlII5tdl2NL/0YXrjLLYnT3AgNB4HclARMXELmC+EGdmdwvEsQP0gebhkaOP7XIHuie5mR4RIpsgCF7Dwomg55412SlJMHlRsh3uxmSGZkuIr4iVZXP6zhGBCDtnpY+FZXFiMjA4LZ7joIBIrceK9Ykyv86c91i1knW8raWmHSeVAwCzJLXBelxl3sbbVunUaAjHzIKXCxD9t69Bkd7uVzn+n4vt4aaLyjOAEDkHHpjsAYY3qts4r5V199NcuXL+/3NbubHfkZ7+Ve4GkR+QfHq0KCqn6n33c1PUud6XjVf7glakIT2hfWTg6kD+a7hKThqFvI+cBqVxNs/Gmudcyf1Z6wxKJujchwlXuOtbrz8ie5JYnGzfKOS1lbMrk9uTB38nrJWl8ls93yPMk4Yq1QMtctXQQw61Ko2g17n3PdqLtXQWgqFEyE/CmuaOuEBTBhIUw6w7XyVe+D8fPd8RkBN1i/YJJroYu3uWr5wUKoO+DuMf0CdyzA4Vdg+yNuSSbqOnypA5hlePYHYNGbXX2riYtc61407NZtTAqEXBHV8LH27zi7yLt1wGsRDLgWxKnnunIdLbWu6zXa5D7fxEVu7c1os1t8u6XWTXyYc4VricwIwOFX3eeduNDtb6l3SwdFm93Eh0TMJe/VB9zYu3hN/z/3UFreWXV/Y4wZedJRMd9bl4SD3iPgPcxwSS01kSwhkbot1aQz3XNvqpCXptQzSZ7XF3kT26/RFnETBwqnuVYwcInEtKXw0BegZh+s+4Ur+prqUE836cM4qM2/62XgvUhEiuZDIAtmXw0Hn4PTb3KJz7GNsPUvUH/YrW/ZXO+OW3orvHy3W0Pz3PfCpt/D7qdgxiVQHnete80NMOM8OLYVCme6Vsw3/i+svRvIgAv+BTbc5WaVLnm/S8Lqj8K0i2DPP115j7ZGl7TV7HWzStva4OqvwDPfdKsalM5358Xa2qvqDwlvEe8u9yVgwRthx19xLYTJ7zwfaGg/9NIvdjzZGGNGrGGvmK+q/VuN0pxaUlvs5r2ufXveRHj9N12L1Zwr4bH/coP963vb+pGmgein3+Di3PckzL0ejm6E+kNuksDCm9xC1Rt/B4ve5lqcnv46FM106zw+fqdLvkITXQmQbQ+0V/5va3CTE+a9zk2g2PI3iMVcIvfUV2HWla6l7NAa15ro88Oex13r4mVfgA33ufvFWyFngiuc+9JPIDPLfcexVlCFzGyQYq/G2lCIdrPPS852/AP355ea9DaceOicKwY3LGOMGUJpq5gvIn8XkZUdHveJyDIR6WH16DEqWcOrs/cd9/V0TE/Ht9R1vr3jc+pxbZETHy11J94n+T55TmO5eyTfp1679kD7+8by9msm97fUuS7S5LaYV16j9oBLDsC1kr3udleSIDCh88/bZ6EO77M6PapfcgqhYLZrzTu2GVDXulOzF/yZrkBtwyHY+wTMugrOfb83Ji7mZpiGy0FjcMUXXevX4lugtQmKZsO2B91C31nZbqJFzV6XtFXshIxsmHax62Kceh6IuJa0mh1uMsLMy6G5zk3I8AfcGLnTb3YlOmp2u2vGIt6kiqHS8XvvTHeJmmfdvQOOxBhjhsuwV8xPsRcoBZJ9Pm/HlauYD/wMeG9XJ4rIdcD3cINx7lbVb3Rx3HnAauDtqvqnXkefDskB88nWn8byE+t4pe7reM70C12F+i0PeBXocedOv9D95+kPurFfwYL22l/PfAdmXAxl62H2ZVC1CyJhN1tx4iKo3OHWdtz6N9cdBrDvWTdmKO6VOKjYAuPPcEsWgRvoP2GRu/eFH4O/f8b9hz/+NLj4k65bcdblrvzF+nth0c2w4Fp4bLmLJVTing+8CEfWu2uWLIBEm+sOywjAy790nzFU6lp3NObWqJy4EA4ORuX7cIf3XXWR9dHOh2HmxXB0Pawqc+O1VN0Yq4PPu6We2prdckoZQTjwLOx5DDJzXDHa2v1QOAM2/BbGzXZj6BRornatg4dedH8fSt8OjYehuRbiW6Gh0i2uXjTdjSer2OEmXQgw8RzY9DeXAMaiMPEsl+Q21bqu3mSLU0OlK+dxkkzcP/XOm9L7prGL7V53Y+4kaCqnx5bMQlu82xgzeqSjYn7SOap6ecr7v4vIM6p6uYhs6eokr8DrD3FrT5YBL4vISlXd2slx3wQe7Xv4aZDa/dZSBy//As770IklJTpWt88Mti+oPf50t7RP2Ro3kPu8D8OOh93Mx5wSqNwGZ94Cxza51pENf4BXfumus/YnnQQUcIPWx50GK//NtaIkYjBhMTRXQFaRKx9RsdMlZXNfA3VlrlXl8Fo3kL12n+s+y5vsZl6CSwYTbW4poT1PuMr2/mzYt8pNECjf6GY9lixwSxgdWQ+H10NrIyx8EzSWucr4l3wGDr4Aca8e2Pj5cPCpQfwDGeQlfZpqYM+TcPb7YP0v3aSE+kOw6xG48FOw9mduRuj2B933k10IZ9ziui/rDrilnBS4/POw/xm3GsDh37rPnT8N9j8HkSZXWmTqOaAJNzs0hPvunv66S6Dr9rixZBp3qw+0heHQK4C6e5MBwWKIHMU1aCe6SMDAlRpp62JfX2XhZmUKFE2FYKmbaJCIu1v4MuD8T8Ca/zv5VBkHyUo3yQkmxhgzCgx7xfwUpSIyPVkhX0SmAyXevu76Hc4HdqvqXu+83wM3Als7HPcp4M/AeX0JPK1SB8df9K8nDpLvmIAlpa7zeMP/ulYvcM8LvPXQ51zVPsNw/a8gsBu0p9aLqBvE3dLgutGChW78UkaGK/NQvRYmne3GG2170LWsTFkK6+5x9372f9yg8uJZULcXznyLu+zLd7tZj9Fmt5j3jpWQVehmatYfcC1pVTug9qCLdcmH4E0fhDV3w9FNrhVv0dtg21/d+KbxC932eCu89mvwxDdBB6PyySDP+mspdw1GL3wXfAHX0iUhmHaeaxWsO+xmHZbMhsZa16r1zNeALJAsCOVB41F46v9BtB78JUALVLzqHuQBUajY6B4Ala2c1LKXugrA8YH2qSUpYl4CBsO7DFArrp5bAcR9cPTlE3c3lnWegEF7AgbeKgjGGDN6pKViPvBZ4DkR2YP7L3wW8K8ikgv8qpvzpnDiHLgy4ILUA0RkCvBm4DV0k4SJyEeBjwJMnz69FyEPo46zFLuTXNMxWNjelbn7cVf9Ptk9ue9ZrxUqBi1VbmHrSKPrFqvZ075MT0bIVafPL4KFN7tB2tlFUDTLla+44F/gpZ+6loncYrj4U/DMt7wE6VxY8HoomAZP3AFzXuMq7e99EnY9DtkFroVu7yoonA3N5a7eV/0+OLLOJSeb/wJLP+BiL9/iZu+VzHULc6+7B864GXY86MZCXbrMdctVbHHlKuKt8O57Yf8LsOHXED48+H8uAxVLSYo0fHLrXdU293y8F7TFJcyNde5t1EswYx3Xt+ysO69j1+pIF4W2Svfor4aRuNSUMcZ0b9gr5qvqQyIyDzgNl4RtV9VkX8J3uzlVOtnWcaDId4EvqGpcpLPDj8dwF3AXwNKlS0f2+i2dLbadum/XY66W1MxL4bnvuVavQ2tcd1281c3Gyx4HC98Ch15ys+saDgECuSUw+yrY9U/XZVUw2XVdvvgjyCuB+de7el21e91zawPMfg201kLhFNcVWbvXdTHG22Dno26sWGsd5E1wg8szMl3rV7DAje1q9sb3nPUW12264Xcw4Uy49N/c2LFJiyF/Aiz5gPuMa++BtibXApY/zSVdL//SDTBvaYJju+DwJlfHyx9orzdmTi1V29MdgTHG9NlgV8zvrljra1T1SRF5S4dds0UEVf1LD9cuA6alvJ8KHOlwzFLg914CVgK8XkRiqvrXXkU/EqQmXakD8DtrIcsMugHv+55xydfUJS4ZAzdGCOCCj7nB7ADzr4FXfwtXfsG937vKXbvpKJzxNtj4BzcTr2QWTD0fiqYBAnM/7Ap9zrnKJW4lC1wLV+MRGLcAZl/hFvcWhekXwbyr3fWrtsPkc+DV30HkClhwnSsiCi4pO+MmaG2GlkrXstVS58aQ5U1yA9ZjrVC5yw1AL5oNi25y494e+vTJ34WtHXhqa7BCrcaY0aWzivmrVq3itttuY8WK/lX16q4l7ArgSeCGTvYp0FMS9jIwT0RmAYeBdwDvOuEiqrOSr0Xkl8CDIzoB69jK1XGmZOoA/K4SsexCV5rgxR+6Lr9kGYcz3uwqwR98CWZfDqt/AtX73Uyz6n2uKxJg/7Nuhty+59xA8HPfCwXTYc1P3ay+Y5tcMVAyobkKTn8jPPe/cGy7azXb95wr+jn/dVC+zSV2bU2uy/PoNtBfu5l3j69wrWg7Hnfjy2r2umNaG2DKebD2Xlcba9413szMD8Cr/+MmBrTWu+NqD7rB+fhdPMTpVfkCcwrITXcAxhjTa8NeMV9Vl3vPH+xPwKoaE5FP4mY9ZgC/UNUtIvIxb39nU/1Gro4JF5w4UzIpu7A9EetspiS4AfHxmEuAIvUuESue4wbJNx51rUnxVje77sr/gEc/D3GF6edBawvUl8GhtZBTBI9+xXUnjlsA//wPV0ldFWq9wnFb/9x+36e89a12/h2e/6FbDBtg+1/bjzn0bPvrLSnnptr2QPvr5LmHOwzQPvZqh5NG+TqHZpA1pTsAY4zptWGvmJ8kIhOAr8H/b++8w+Mqr/z/OeqS1S1Zstx7LxhjTDc1QLzAjxRIDxuSkITESRY2S7Ihzm6ym7ZsvOmEBAIkEFqAEBMbE9Pde++yLMnqdSyN6vv749zruRrNyJJtaUb2+3meee69723n3pHuPXPe834PBcaYm0RkOnCJMeZ3p9rXGLMcWB7UFtL5MsZ8ulcWR4pQDpfbHox3JGQo4pJg/l2w80XY8oRKU3S2QdJQjTGu+w3EJGru2I7noL4CYmIgfRxs+YPmUw0bD7PugLW/UhmDuGRIGg4x9Ro9yxivdR/bw4xA7DxVMng8p5Q1kCwwtYHllDxocjXAQpUda2se+gAANTBJREFUilXF+aYoTMS3DDw/mAb/tifSVlgsFssp6S/F/N6MjnwMeBT4lmsL8GfglE7YOUc4p6ov27b5Vefp2DqoPqx6XnUHYfiFsG85dBp1qjoagU4o3xzY963vBeaPb9KPS+3BUEb0bGNMkspONNcBHt2m1JHqwBGvyfNtTSozIQLxqWpjrGh7u0enS2Ihzdk3YwTUHoK4TM09w6hTmZwCTTHqZHYaPW9MSg8aV5HmLOuQWQL4g1NELRaLJTqZPHkyW7dupbOzuyRQfyvm5xhjnhGRB+BkN6N9K50u8UkwdTFMvE4FK9tb4M0fqchn5midtsVp8ebEJGjvhOmLNecrcxQ0lqvzkpACsXEw4XrV96opgY4TMOlGrd03dIIKrFbuglELVWD1+A4YPlOV9vevhHmfVPX7t/9HRzE2OZIYYy/XUZpDJ0FKuraVbtZcsdl3qFBrxR5IG6FK+FUHVcU/LVvtGn8NHH0XJr1PR0VufgKGToTcKXBktXax7l+pzmb6KI0Mlm1XYdOGKqJDsiFOSwg1lUHGGGhthIK5jhPa5tjsSN51tKr8RkKqKsFnjlRB3IZj+n0mZ6ujO2KBlhxqqlTpkOoDKqbb2anObnKa/j0010N6PiC63HpCR7s21WgXtK8G2lpxpPjP4BpdBzMGsqdAzQBHpZaeDZ04i8Vi6X8iqZh/QkSG4vQtichCwD49zwQ3id/lfd8PKIj7G/STMzGwPjkTpt2kL363vBHofFp+17qNyZkw706nqLNfc85S8wLr45xzT7wmMHDgph8GHMKkjO7niU+CMQsDxx85r7sdXpIzYdzlgePnTAycd/QCbZ94ja7zHqPdr9deU6gOzabH1fb86SqbMekaKN6k6xJSISlNazOm5qmcRuU+dQKTs+DYJo3epeaoU5M7UZX9MwqgdAccfkuPmz1eddXW/hrtfu2AlJHwtU2B+5eUofPuIAoX73X763XEaFxS4P6515OUrtPM0YF2UDHc1FxdF5eoH/dvIHVYYLv2Fl3ntvvrA23VR6C5Bt5apoMhTKfa2dkO1TshqQCu+Vetg+k9R3uL2uVztL5yJmlJrLhEXbf82+psmk4oXQu5syExXW1aeDe89AAUTFPHvbNdnekh2XqsvcG5hJmoY+3kBX7qVa0jarFYLIOESCrm/wvwMjBBRN5F60h+8LTOZgmNdxRlWn7obcK1Q9eBAt5t45PCq/l728PJaQQve8/jXR8uL66n+eBzem3PdcK6oV7UWUE1B4fPCsx7t59yQ/d9XaYvBh7o2nZjiOHFwfcv1HqXnq7HO/XuE7wuuD0Yt917Lvd+uJUO+or3XN57+ZkXe95v7h09rPz96dlisVgsUcyAKuaLyFeBd4EtqFzFFDTbep8x5mwVorNEI25kzVX4d+eb69QB8LYBLM3RItM5EzQqNeV9ql8Wm6D7DJuq1QFAnQZ/o3a/NZZpV97IC7WrNHcylO2EmiLY9ZJGqmZ/SLs0W3zgK9du1sYyjewc26hdfalOFa2ynRrRaTgOW57WyM7l92oUDeDw2zB8Nqz+MSG7PD//jnb5ulGt9pauUUQ3GhafpOfOn9m13Y2cZY3Re+RzBim4kTTQ7fx1gYhZ1QGNhnmjj270smyndm26EUpfhScilqtdnnGJGg08uFqLfne06jlGzddo4Yg52rb+cUjN1m7Q7U+G/t6zpsKIC5zqBvuh9D0Y+z4omKV2XfSJnn8MWCwWyznOQCrmjwSWoUr524H3UKesFKjpYT/LYMZV9YeAsCyotplbrPzYem2bdAN8fyTQBmXr9QOw9qc9nCAW7dn2JjcmowUbk+gyQKBis+MwhBipmZQDfkdtPyFL62SaEPlRL36u63K3rjIPv7kcptwGNQcgLgU6mlWHLSZeJUea69XBTM6CV74Gcz6mdlXuh7FX6UCE49vg+u9p1+iWxzXfK2+mOqWdnTD2MhW4TR8Oqfmw5UntEs0YpfljKVlQX6T1PXc8q05l6wlIGwOV2yE+BU7UQkY+VB3W7sJQ2msl74S/znDU7tWPl8IV+gHY+Rzc9ZJ1xCwWi+UsERNuhTHmPmPMpUA+8E3U8fpnYKeIBBfhHry0+c98G+96d765LvRy8NRd3+bvvi0EIkjuusayQFvw8ZvrdNmdgibTe7d393G3d9fVHtXl+CR1uMZdqe25U3U+KVOdLtDl4XN02w8/FvKWhKeD7gWnXe2VcPc5hMaY64ABtNaGdsBOh/wZKvfhr4GENE2CP/wWFL6rgxqOroW3fgK5M7W4d8F8zTU7uFI13PwN8OoDULIRMsep/lt7q+ZXNRTDnpf1PlceUGd26mIdoFBTCL5SjbAlZMKxtTBsDgwp0EjW8c3Q0qoyJRkjwFcNxs+pxW9jz/yeJOTBpfdZB8xisZz3BJctWrt27Rkdrzc5YclAOpDhfEqBHWd01mghlABrcFebtxQRdM3Hqdyvyc2F70LOZO3K2vG8RjX2vQKX3Av7VuiowP1/h+RcjSxNuEZf5hd8WF/goy/WF7CvCkbOh71/g4Wf1xf6qv+Ay7+qCdDDpsEr/6JirNcv1XMf3wZpBfpyb/druaDGUh2NmD0R/v6Ali76p4cC3WKHVkPxekCg+ihc9mVYtRRGXgAXf0HrP2aN0RGL5btg9kegpVE1zTLHwtSb4eg7cPEXVVC2v4lJgc4BEvcs3Q5tPk2Az56gNTBNuyb8xyRplCo+GehUSY7Nj+v6jjbIGglH3oD0MdBUr5Gx2FgdzTr+Sq2IMOJyvfcdbSoPUrlHuydjElUnLqFVy1Kl5KvsSGcBJKRDqx86GnQkbEM1mB7GxsRng2mFxAxoa4bWMwxcz/yn0AMTLBaL5TxiQMsWicjDwAygEViHdkc+ZIxXnXOQEyzA6u2Km3RD11JEB1dB2S64fIk6YpX74U93au3FjlZ1Yqbf7tRdbASJg8pDTtedQaM5jtBbyXs6PbpKpzHJMPF6OLoOMofBlFtgz99UFgJRCYt5n1QnKmsUNPtgxbchLlZ1xo78FC7/uirpV+2HabfA/uWw4wV1DofP1lqRpZu1ayt/NnR0ag3J6kOw5yWNeKWPhiNvaw5SxW6QeMicoA7D0bUwdLKO0hy5QNvW/ExzwUZfBUVv9sMX5Ai+DpQDBnD4PRg2Vrs7tz2lDm5cPKSPhUOroGSnSknkTNDcs9R87Qqt2wuJQ2HiDeoQd7Tp38llX4V1v4TDqyE2UZ3x1OFa2aCxBIYMU+eucp/mxtUVq8NT42hodbRCczMnFebrw8h3DBkFJ47pfJvjdLWfJamPzY/odMcL8NEnnBw2JzcNdN7NWXNHXW54HIq3Qn0h1Hs07KwshcViGYQMeNkiYDSQCBxAaz8WA3V9PkO0EzzKz+1yc5PS450E6rGXw8iLHHkAv76Apt2mcg2V+zUpurYQssdqJOTYGtW9IpZAd1sYOpth/8v6Mr7kP1XItWqvRqJi4yF1FLx0L9z6c7jqG6qxdcLpjit6F9JGwZv/raWLGsuh9qdw9b/DjmdU4ys5A/JnqdOw52XImqh1Hw++rk7k3I/B0TVw6HUYOl7V/Kv2qwP3+vcgYQiMuhA2PAbzPw2r/wvGXQWjL9PIzJTrNfrmlko6a4RWJ+5XOqrheDXgCOE2Oo5NrafgdPMJOOZ04zZ5unqPrOh6rOYKWPXN7udo9nSlNlUE5ovfC7FtLx0p1wHrT5pL4XfXntkxlmZEpSMmIn9GBx+BamrUGWPmOuseAD6D9qV/xRizwmm/EBWzTkYrgywx4SS1LRbLoGbAyxYZY24UEUGjYZeiUhUzRaQGWOPWlhz0eItye+eb69RJGXsZ7H8NSrdot1PROh11VnUIOjtgfacmVlcegPYmFfM8+q6O/hs+S0f9DclXMVNjwIiKsDbWQ/IQuOBjGrUafYkKgo5ZCMVrtRD2iPmw4G6NLBSth/d+pppibmRq4jUw7VYYNh1WPgiJQyD/Oihao9GKK76uXUh1RfD2Q6qrdfNPdF1yhiabD58N2/4EHR2QPgKGzdBrdbtfR1yoml9J6RrdK9utOVMtjTrSzt+ovtLkG6AoE6qLoLW8+322WFyW5sPSslNvN4AYY05qbojI/+BoITpl2u5En4MFwCoRmWyM6QB+BXwOWIs6YTcCrw6w6RaLZQCISNki51fdThGpQx9K9cBiYAEw+J0wb04YdJ0/+DqUbNLuu+NbVZ1+8i0qBZAzVbtgxi2CvOlQXwJ7/gpX3ge7XlAHpbFMnaXUXB0d11Cqw/9Th+vIttTh2j1YV6jbXHKPOkVxiXDtd6DumDpDFbu1GyguUaNPWx5Xp2vK+9SRyhyreWHxybDgczqabtr7ta2jVaN37yyDg6/B3E/p8fYVwoTroOaQXmtnu+6XlAEFF8DfvwnbnlHF9+YGzXkbe5lKJhx5C2Jj4Mi7ek/am6F4o0bEkvKhtQJI4NQJ45bzlihzwLw4Pzw/DDhqwtwKPG2MaQGOiMhBYIGIFALpxpg1zn6PA7dhnTCL5Zykv8oWSTjPTkS+gkbALkP1Ad4F1jjTHcaY7pYMAPPnzzcbN248ewcMFwlr8we0nQ6u0u5IN6qUlB7Yf8PvNZoF6igVvqM5V/tWQvlOTZSPjVPnqblek/Yv/hxseAQ6WrTrMi4OFn4RNj2qUaWFn9f5rAma0L3tTzDjgzpibssTGiG76n4o2QLvLtN6jVkjtfswf7Y6kyk5moAfk6Bdl/4adZiyp8DQsVC6AZLytO3EcXXAMscG8sHyZqmu1uRF0N6h0bnUPI3+najWaXMF3eoqxqRBZ+PZ+34s5yZ97JIUkU3GmPn9ZI33PFeiua/zneWfA2uNMU86y79DHa1C4AfGmOuc9iuAbxhjFoc57ufQqBl5eXkXPv30072yx+fzkZqaekbXdDaJJnuiyRaILnusLeE5XXt2797N17/+dVpaWrqtS0xM5KGHHmL69Okh97366qvDPr96ioSNBZ4DvmaMOd5niwcL4ZTfvarwU53nqjtKsmhtIKHf1c1qPaGimQvuVh2o2sMq1hmXCEPyVKYgYzRUbIW/3svJfKfK3UCsjpg7UQl0aoSsoRSM47wlZEBtsXZtNpWCr07rNZZt1+0rd+vxYtOgo4keC07XH4EjYdaVrAvM1+7X6c5nAm2+kh5upEOIXwkWSzcikBsmIqtQyZ1gvmWMecmZ/wjwlHe3ENubHtpDYox5GHgY9IfkokWLemMyb7zxBr3ddiCIJnuiyRaILnusLeE5XXsWLVpEeXl52LJFX/ziF0/Lnp5ywr5+Wkc8F3GdMdfx8o6oTMvXZP52v5NEnxco0O2vV42pkg26fY3r/Tij/k7SASc8eVS1ntFkdc4INE/+Nm01UOaVHUjW/KyOsxmBChJOPUmc6me1NnJSvyshU3Pd2mohMQ1aBnA0o2XwMsCOmBu1CoeIxAG3Axd6mouBUZ7lkahMT7EzH9xusVjOUQa0bJElBME1Gr3t8UnqfHm3Sc7UsjvT/wkO/gOev1vXpRVAY3HQwWPpMYLlJSXPGVXnOnJ+1T9NyYcOozlbTbUgMRATA/GJ2h1JKsQZSHe6LhtLtUSQdOhyw3EtAt1pICERYpNAOmH8tbDrL3q81ByYdJM6ls01UH9cyw2NvgR2PAezPqQiptWF0FLdt/sbbcRnQZvjUA4dB9X7nBXnSs6baGHuym2ROf3nT0PVv3+5DthrjPH+c74M/ElEHkIT8ycB640xHSLSKCILUQmfTwI/G3CLLRbLgDKQZYssfSVUIWvXQZt1u2pKNddoXb+qw1rKJjVfE+gzCmDb81qnr7lOk/ozRkCrDzJHa6J/cnZg/7piracYmxA4V+aIwLy/QbtCQae+Sh0A4Oo4eWsdtreoOKkrveGSlB6on7jgM4FcuNQ8FRiFwHGTMmHex9VW/xd0v6NrYf8qtfVEBdSX6/WlDtN6ku1+FaGNS9L9E9P0uusKNecsKQNi4qCpWrtzW5tVfDQ2ARKSHRtTdaCCv0EV6VNy9L6VbFbB1PRh0FSnzuPxnXo/E9OhdDcMSdN7U19CNxmRz7yu1+Vv0GvJmagjQ5trVMj2RLXWtAT9Hlxane8kNkGlSzIcxXtflQ6kcOtYZoyAQ2+q9Edrk0ZRm+vVzuZ6aCjT+9PZDgWztZZjXBLkTlDHt6EU1v/cY3A6FMzUckgxsZCSraN4M0dC9jgYMlSrIrSe0LzEjlZty5mk0drYBI3Upubq39kr90P1zh7/3APlptz5RHqlYnPlv8O0G7sWDI8O7qRrVyTGmF0i8gywGw39fskZGQnwBQISFa9ik/ItlnOeYMV8GwkbTIy7NDAfqvzLdQ/0/lh9LR+TNaZ7mxut681xg1+Y8fndt8+d3HVd1hiYewfnDN7vrzdMXNTz+ik3nLYpANz8/b5tH87pOWnHokDbl989HYsGNcaYT4dp/z7Q7WYbYzYCZ/Yz2GKxDBr6QzE/bO1Ii8VisVgsFsupFfNPt4akdcIsFovFYrFYeqA3ivmng+2OtCjewuVevTR3XXC+m9vWWAav/Sdc/a+aP+Xmh7V7dNaSMjWHzO26bCzT/KZ2v07jnGO3+7X+YFyi5mH5GzQXK85zbncfX7nmpgVrvDWW6fn2Lof8mZqj5ivvWufw4BvOuhFQfQQK18A7P4Al2wPdtu79cAmV7weavxeXFPq+BW8T7jiuzcHrao927UZu83e9j811Ok3ODBzDX6c5eEnp+olL0ry/d3+p3ZEZI7UCRLtf88OOrgFfI+RNgHkf1fyx2ATIGQ9P3QXXf1vz1OpLYcTc7t3XFovFch4QEcV8y3mCt3D5uCtVFX+SJ1/JW0nAdYIOrNRRnn++C3xFsP1JkERNRB+1UBX/Wxuho10rBtTsh4u/oEnoO54BEwut9ZpAnjcDTIfWzCw/DJ2taMJ3PBRcCKPna8kniYO6o+qEHFoFUxbD5PdpkvmB17QE04bf6qjOorfV3tw5OjK0sQLoLrLXhWWzNSE/LhGq9mm1ADEQnwJjnHyw1Dyd1hXpdPMTWi907BVQuVfvSf7MwH06ulZrcqYOgyE5ehx3wERavlZD2PGsVl+YeaszcCJD79/zn4UP/DYwoGLHC3DoH7DoAXUgX/uulsOKSdAC4Z0CODIlMgQyh+tI2KObAu3hKKuG5eu7t//hJv0eaIOpt8Gty6wjZrFYzjv6SzHfOmFegmtHui+bcO2hcNc3lnVPcvfu693OGwVxlfqTM7tHPtzojK9cIyTBURjQ+ea6rlEotw30uO56bxRq3JUahQJ1atr9sO9VrR05fhFUHdAySpV74OJ7NDKy9Wl1wFxMC9Qd0Y+Xql06ffFzoe9Z4Ruh22mD0rX6CcWan+qnJ/oqv7Di39XRm/MRrVDQ0QEpQ/Vamyq13FN8Kmx9Qh2cvGmw+xXYs1ydpUP/gFl3gr9K7/2mJ+CCT6izljMNNj0OplMdyum3wspvqtO660U4+p7e35xpOhK0aj8s/zegU0eNVh7U+qVPfUy/x/rD4a/DnFC9Oa/m3GnT5hzzLBzKYrFYBiFLlizh5Zdf7jI60iUpKYmvfOUrp3Vc64S5DtaxjVB9AJKH6jD/nS9o+SBfpUaCssbp0P0dT8P021WeoKlGt3UpXKP7jbpYa0hOu0Vf0gkp+hI9vBou+KR29bz5Q9Xb2vI4jLwYLv6sRleK1qrDs+Bu2PWyRocWflG7hI68rcfZ9id4/0Ow+yWtXTnhatj5om6TORZ2/FklDWLiYOr7YdK18O5PVfZh1p2w/c96rqFj9dwYlT3Y8xLM/KBKKVQdhB3Pw9pfw9Xfgr//KwybqVGava9CxR5IGAKjr4KiNyPxzfUP7Seg2afyEg0lKo1Rvgdm3abO68bfQeb4QBHz7c/A7A9DWwvsfE6jcXtf1r8rVyoiayw0lAMxKrHR1qQRwuYqyJujshZ1xdr92FyvchapuerkFW/Sc3V2QkddwM7WmpDmd6UP2nM9EZ8HWSNg8Q9tFMxisZyXLFy4kPvuuy+sYv7pylScv05Yc51Gfg7+A5ob4b2faQ6N7xgkD4eZt8DKpdrN5a/SfWKHQIcfNv8RfbkZIBYkAUwbJxXkS9botIuOk8Pu5fpCP7gK9q7UYtu7X4T8WbD6+yrzkDcLtvwZ9v9NyyS9eI92YcUmwsQb9AV+fBskZ+lLe9eLsP43MPNDsOZXMOX9kN4Iw2ZoEXLQKErjcShar85k9njImQIj5qlzd/RtLQJesQvi4mH/SrjkXtj2NNQfg/x5ULFTHbGyHXrMmFhoqQUy0Nru5wBl23VadQDqStAoUBJs+QMwBDBQ6WxDPBAHmx5D/x5E63nSBvHZWtkAYMX9Oq2uc/ZLAZqgyo92uwaFmFp8XYVu20Ing56as+CAAbSVQ0U5/M8UmOcIDrf7NdLXcFwdz+QM1To7vkN/nBx4U/cL5iPPnrk0h8VisUQAq5h/tmiug398H468qbk/Lj7HkWg+rrlFuH2/cVqIu7aILi+2mHTobABzipdkXKpGEHKnqYNz5E2YcRuUbIWOZnWaag/BlfergKu/XqMp2RPUhvf9F9QXQ+5UbZ/7ET3WigdUnPT6pfoen3gNpOWpGGfxBsidotGZ+Xfpvqv/S6N0yZnq9G17Wru8hl8AIy/RQuONx2DGhyAuQaNd9cXqGE5fDOXbNXerrRkKLoAJi8DfqI7Lqp9AR+WZfzfRQs1ez4KbpB9cjqmNk111gH4JznJbT5GqpqDpIGLzI93b9j7f+/2f+pB1xCwWy6DFKuafDZIz4dJ71Qk6iafrJmMcJKdBQw2kZUHGBCjdAAVzNVE7JVfznobN0KLce16AGR+GGkcFPykDyrZBTLwea+QcrSVZuQeGz9FIR2KqOlmx8ep0bXxMzz37w7p//kwYOlnLTG56XLu1KndrwnbaSNj3Vy0nNOk6dSRjE2DLExCTDGt+BtNuh32vaFL5ez8HRHO9itZqXtGWJ8FXDROv1oja2l9B8jBVon/2nyE+AXJmwPG9ULZfIx8xneqEnajTIuN7XtayPg010DHISxRZBo6n74Hv9JDPZrFYLFGKVcw/W2SNgU88C+sf01yq0QugplDX1R+D8p0wbZRGg46tBWI14pM3HfKmQI2TJH1ktXYP7npGo0wJqdq911YHOdOhswl2PgtlezSxvaUFYmMh1sAFH9d8rrr34MYfwqE31GlKztbE7AOvadmZzNHqqCXnQvYk7WLMGq+5Xwf+rl2EVQd0VGDjMR1JuH851Faiztd7el1xQyEtE1r80NQM1Oq17V2FJn/v6nqP6o92Xe4Eap1Rdq01XRPwk4dr1+hgjO5YBhZjHXaLxTL46A/F/PPXCQONiF311cCyW3bHHaHoaln5KlQi4J3/0266pkqVKsgcpY5SQrrWN0xIV92ltjo9Tu1RqNqt8/WeUYSdaK+Vd3TfukdU0gHhpJRCQjaU7AFTCyQBsVoou+gf2n3Y1KyFwCuDnCcAX/cm2quhNugF2FAUYsOecPKZgmk+3sfjWM5rlmbA0nMkj9BisZzznEox/6abbjqtiNj57YSFwy267c67I8IW/ziwjZuYPO0WHclWV6Kj3S6+W5Pf962ApnIo2wvtvXjZtIaIDnQZAefkJRWt0mnxGgI5a33F6XpNyHQKSrd61iU5y86xU/KhyQexnZpXVrZV90seqknZxnXIBM2JSoaYGOgMzp+yWIKwjpjFYhkk9EYxP+qcMBG5EViGvvUfMcb8IGj9x4BvOIs+4AvGmD4KOw0goYbnj5qv06wxAbkLN5G93a8RtO1/UZX25modlej3Qc5YXV9XBm0+1QJrrgeJheyR0NkOw6YH5C3c0WcJqXq+lGwdhdbRqvlgCanajTp0gspPdLTBiAtU7gC0y9XfoJILSWmaUJ85Qu2rLw0cJ6MgsF1HKwwd11W9vmSrbpOUrvIdfqd7sqNV89xcIVJ/I6z8ro6W65LQHo+OIk3Ta2sth4Q8aPUDLRpdNJ06SCJvEsSlQGuDtjVVQeY4vY+pwx0x2FZISNOu08zx4CvVCGZjuco6pGTofW6sQcOPvRxpeNvDer9jE7R72Fem97K5Xu1OzdFcuppCzd8r26ntJVv0vsfGQ/FmtSUmTqf50+DgamiqhWHT9Dx1hXqv4xLUqS/eDAWzoeoIJKXCyAtVh6yjFRIzoXofNDWBqSG0cFeCc50xhB8dmQ2j58HYhSqPEROnn852SExT6Y33ltF10EE/YB0wi8UySBh0ivkiEgv8ArgeKAY2iMjLxpjdns2OAFcZY2pF5CbgYeDi/rKp3/GWnfE6bFd9tWu3Z3/jOoYQ6GLtid5s4zJxUWA+WIw2mM+v6P1xBzvjHEX9Cz8eaJt7R/ftpi/u+7Ev/9Lp2XQm3PDtgT+nxWKxRCn9pZjfnwW8FwAHjTGHjTGtwNPArd4NjDHvGWNqncW1wMh+tMdisVgsFoulzyxZsoSkpNA1hM9EMb8/nbARwDHPcrHTFo7PAK+GWiEinxORjSKysbLyHNKislgsFovFEvW4ivkpKSnExKjrFBMTQ0pKStQq5kuItpAdqiJyNeqEXR5qvTHmYbSrkvnz59sKdhaLxWKxWAaU7373u9x0000sW7aMAwcOMGnSJJYsWRK1OmHFwCjP8kigNHgjEZkNPALcZIwVELJYLBaLxRKdLFy48IycrmD6sztyAzBJRMaJSAJwJ/CydwMRGQ28AHzCGLO/H22xWCwWi8ViiSr6LRJmjGkXkXuBFahExe+NMbtE5B5n/a+BB4GhwC9FBKDdGDM/3DEt/Uibo0MWn6S1NeM8Wmmu9IZ3G7etsQx+dS3c/gtdN2Soylf4G1TaIjVXZSvaW1Tg1l+n61KHaRWA9hbdPikTfOWqt9bqU+mHjAIYPkvLOPnrux6nrkiPEefY6Hdsdo955F099/BZAVvqilRyYuuzMP1mKN0OB1ZBQ7XWvVyyPSA10u5cq3t87zV775d77rT8rvfJ3a65LrBdqHvaXKc2p+Z1X3dsY9eRrs11WrZq+CxdbizTa8udrFIg7S3aVnMUciepjElqrm6z7hE9f0IqvPdbQFQWo73Cub48uPgu/f5Sc1R24xdXwNUPQMZwlTyZfN2pR8RaLBaLpdf0q06YMWY5sDyo7dee+buBu/vThpB4X5LuMnRtC24PfsEGv2hdSQp3PviF3dM+wTa5TlCwTcHOkBev8+RtO9V9cJ2Ng6u0/NKYS7SOZf4MmLpYHYzSrVo389AbqoU1fI4WCM8cC7+7GWiBJ70DX5NRjal2iM+ClDRobISxF8GxbSCt+qJvqNBalElZqo11YDnd0gZjMiBnlGp0xcZDjEDGeCjbAhljVEers02Loqfkanko/N2PE8z+F7u3LZut+mANJQH9roK5WgN0+Bwo3qTny5kIax+G9OFQewyOb4brvgN7X4VRC1S0N3Oslpxa/k1IToXmBhh3perEJaZCxW4YvRBWfEerFky9FcZdrg6or0y1yf5yD9z4AyiYAyeqtb5nyUa48huqg7b7edWZS8yEllAVC+IgMQNawvTyt3vm28rhnR9032b1dwLzObPgU89ZR8xisVjOEueXYn7lflWzb/NBzlRH6DMVCt/RaEz+bN2uuUZfglv/BLlTIHucli5CoHwXjL0UyvdC1mh1St76CYy4CPJmaGQlcxTExmmB7uQMOFEBBRdC0ToYf4VGJzY+BvM/rdGd8r3gOw5jLtVoxqbHdN/WZpjzQRVFzRwF+17VbQ6/qXZ2tqmvkZCiDsnev6rAa0cbJKdr0XC3/FLdMT1XUrq+RBvLYPuzKvCaM1ULkx/fpo7OzNt1u7KdsOt5mPNR2PM3LRQ+7TZ4Z5nWzax9ipMllrrgEURtq4V6R4Xk8MpAe01tYP6EDw54B9J66KyHiiBRT7cEVOV2/bg0hDlGX3jxixA/ROt1+o7DsU3Q4de/lZZmdQILLoaiNyBvDlQf0L+hv92vVQxikiB3ujpWoy9XxzJ3JpTvgGMb1MGKS9boXlq+OnCJOepgvfUjoA3SRmn9z7Zm+OuXtCh7p3tPk2HF/V1tbgknQNse3gE7HQpmdnXyLRaLxXJGnPtOmBs1qjoAj38QmsucFW6ZHZcEupbvCSIuI1B+aNNvu68PVb/xJALxqfpSfScVpt0EQyfD69/Tbrfj27SLaeNjqv6engdH18Lh1VC0FkrWwfzP6vz+1+BElTpl9SXqtKUP18jUmMvgRKUWEB93BWx+Avat1G6pI2+pg5U3A27+Ibz9EBS+CwXz1MQh+Y6zNwZWfAvaWqCxBIYMU0X95hpIL4C3fqxO3swPQOUBrWFZvKYXX8RgoR3a6qFyhy42V3XfpNARoT2+XqetteBzHMBOP5Rv1vl9L+rUXfYVO6doBF9jYLmlouvxG4OcyU6vk9VLxf/+YPtT+jkj4mFpiHtqsVgs5yH9mZgfedr8cGAl7P0b1B6Bj/4RRl/nrAzururBASNW82FkiKctHnXk3CkQnw3DF8DUD0DGOP1M+X8apRq7CGbcrqVr4hLU8Tq2FkZepOVvZt2hUZIrvg6XLYEZt6pTteBu3XfUAi0QXr5DHbX5d8HlX1WHIS0fMkbBnDuh5iC01GnUbM9ftVvNXwspWU7ErAB2vASVeyF7MlQf0WvY9RLkTId9r0HFPnXw0kdrBG3/Ki0BNGw2ZI2D2kJ49RtQvFP3zz49pWDL+UgbLM2KtBEWi8USFZzbkbD4JJh0Q9flT/wR9i6H1HyNBpXv1pwkEagqhNRMzd/pqIeChVC6EWLTNRcnNi6QRzP8Aqg8DNIJbU6h7bYaaK2DklLNz0rM1P19ddC0DtoqgFQ45kaOMjSBvNkHr/+ndlFt+zNs/QvQCHTC8e3aLXngNZAYaDmhhbMPrNLcpKpjUP4oEAsvftmpFdmEfrWOsQ1FgXuw9Uj3+1TplOus2Nq13eeJyBS9o58utOi9OhldtFh6Q6ct3m2xWCyc604YdE9Oj0+CWbfr/Mh5mjOVnKlOk68iMLKvZAt0tEBMjOZxNVXBpBth69NwfIt2B/qroLYESEQT0Tuh2qO00e4LzLc5ha7xtFEPlVudbQFfA2x9rKu99Ye7X9PJLtadXdt9jZ6FdiyWqMY6YhaL5Tzn3HfCeiLeIxmQnBkYrZiWr8P+2/ww+QaVT3CdtdELVFLAlU3wVQakExrLdN99r0FMHGz/E9SFcKJchs6ExHTw10BTLXQCySmQOkLzwuqLYfqtULzeSbbP0umw6bDlMRh/Lex/FTInQH2hnjsuHWJioblaI2ZDhkLVEU0GHzMPTAxkDneczkrdZ+ylkDEC1jwCCz4JO/4CI+ZB2VYdcFB7SBPFTTsMm6Xbtvpg+wuQkul0r+6Cghkw9Ra1e/OTUDKYc8USYcK1+ncQEweHVkP9UU28l079/rMm6uhR06kDNjJHQXUh5E2DhqPQ1goSD3TofsYPrR1g6tB/vRh67gYfAOLzID0Xqg+jEdQBxDpgFovlPOf8dsJORXwSxOcH5qGrs5acqbpSwbjaThd9Qh2d0m2aj5WQqs5L/kx12ly9J69URLs/oDnlnrftM93tuvQeR6frft0+WNsrmGD5CvdcXpmM8Vc6XbjXBSQvXLkN77ldJl4TOKY7CtNdP/uDOrqyqUave81vYNxlKk3RXK+jTlt9mtyfP0P3afUFdL38jbptUjrUFTtaYul6P13tq5MaYxlw5B39LuIS9ViZo6F4M+SM1/1Tc3XfFp+ep74Usseqbb4y+PuDcKIeaIDxN8P/+191vk/KjNwf0CJzr9V7P33lAR20pEydQtftvc67S12JjrysL1YpiqoDMPVmnabm6rG8x3epOgCv/BuUvAOkwgd+pvt5bYSuchKNZYG22qNqi1daxVfhjAothxXfhc4Olemo2KnH7myHulKVEzn0BkxYBEUbITUbciZDtnPPN/4W6AicN3cuVB4CGuHz7wT+7i0Wi+U8xzph/Ulavn5O9dKJD+E8eZdDOVZum/uS9TpToQi1Ptw5vQ5nuPMHHzPUsbxCo+MuDX2MKTeEbvfidSTc+WCtqumLu+/nntPdNpTD7OJ2UYfD65CHwj32Sac9xLZe5z14Pxf3byX4bybUdp/9Wwg7e7DRe8+Cj+f9cZE1Bu78ffjjAFz3QOj2uXfA4h/2vK/FYrFYgHN9dKTFYrFYLBZLlGKdMIvFYrFYLJYIYJ0wi8VisVgslghgnTCLxWKxWCyWCGCdMIvFYrFYLJYIYJ0wi8VisVgslghgnTCLxWKxWCyWCGCdMIvFYrFYLJYIIMaYSNvQJ0SkEjjqLOYAVRE0pz+w1zR4OBevK1qvaYwxJjfSRpwNgp5hpyLavo9osieabIHossfaEp5I2BP2+TXonDAvIrLRGDP/1FsOHuw1DR7Oxes6F69pMBNt30c02RNNtkB02WNtCU+02WO7Iy0Wi8VisVgigHXCLBaLxWKxWCLAYHfCHo60Af2AvabBw7l4XefiNQ1mou37iCZ7oskWiC57rC3hiSp7BnVOmMVisVgsFstgZbBHwiwWi8VisVgGJdYJs1gsFovFYokAg8IJE5FRIrJaRPaIyC4RWeJZ92UR2ee0/yiSdvaFcNckInNFZK2IbBWRjSKyINK29gURSRKR9SKyzbmu7zrt2SLymogccKZZkba1t/RwTT8Wkb0isl1E/iIimRE2tU+Euy7P+vtExIhITqRsPF/p6ZkXQZtiRWSLiLwSBbZkishzzv/fHhG5JIK2fM35jnaKyFMikjTA5/+9iFSIyE5PW0Set2FsidhzMpQ9nnVR8XwbFE4Y0A78izFmGrAQ+JKITBeRq4FbgdnGmBnATyJpZB8JeU3Aj4DvGmPmAg86y4OJFuAaY8wcYC5wo4gsBP4NeN0YMwl43VkeLIS7pteAmcaY2cB+4IHImXhahLsuRGQUcD1QFDnzzmvCPR8iyRJgT4RtcFkG/N0YMxWYQ4TsEpERwFeA+caYmUAscOcAm/EYcGNQW6Set6FsieRzMpQ9UfV8GxROmDHmuDFmszPfiP7DjQC+APzAGNPirKuInJV9o4drMkC6s1kGUBoZC08Po/icxXjnY1Bn+Q9O+x+A2wbeutMj3DUZY1YaY9qd9rXAyIgYeJr08F0B/C/wr55lywDSw/MhIojISOD9wCORssFjSzpwJfA7AGNMqzGmLoImxQHJIhIHpDDAz2xjzFtATVBzRJ63oWyJ5HMyzL2BKHq+DQonzIuIjAUuANYBk4ErRGSdiLwpIhdF1LjTJOiavgr8WESOoZG9wRZdcbsttgIVwGvGmHVAnjHmOOgLBhgWQRP7TJhr8vLPwKsDbtgZEuq6ROQWoMQYsy2y1lmg2/MhUvwUfWl1RtAGl/FAJfCo0z36iIgMiYQhxpgS9DldBBwH6o0xKyNhSxDR+ryN+HMy2p5vg8oJE5FU4Hngq8aYBvQXSBYarr8feEZEJIIm9pkQ1/QF4GvGmFHA13B+7Q0mjDEdTnfqSGCBiMyMsElnTE/XJCLfQruP/hgh806bENc1G/gW2hVuiTAhng+RsGExUGGM2RSJ84cgDpgH/MoYcwFwggilNzi5VrcC44ACYIiIfDwStkQ70fCcFJEUouz5NmicMBGJRx9GfzTGvOA0FwMvON0q69FfaYMmiTjMNX0KcOefBQZVYr4Xp4vgDbRPvlxEhgM400HTdewl6JoQkU8Bi4GPmUEsuue5LveFsk1EClHnbLOI5EfMuPOUMM+HSHAZcIvz9/A0cI2IPBlBe4qBYk80+jnUKYsE1wFHjDGVxpg29Nl9aYRs8RJVz9soek5OIMqeb4PCCXOiW78D9hhjHvKsehG4xtlmMpBAdFVrD0sP11QKXOXMXwMcGGjbzgQRyXVHv4hIMvqQ2gu8jDqYONOXImLgaRDumkTkRuAbwC3GmKYImnhahLmuLcaYYcaYscaYsegLb54xpixylp5/9PB8GHCMMQ8YY0Y6fw93Av8wxkQs2uP8LR4TkSlO07XA7giZUwQsFJEU5zu7lugYvBA1z9toek4aY3ZE2/MtLlIn7iOXAZ8Adjj5KwDfBH4P/N4ZftoKfGoQRSPCXdNngWVOkqcf+FxkzDtthgN/EJFY1Ml/xhjzioisQbuLP4M+uD4USSP7SLhrOggkAq85veBrjTH3RNDOvhLyuiJsk0UJ+XwwxiyPnElRxZeBP4pIAnAYuCsSRjg5lM8Bm9Guti0McFkcEXkKWATkiEgx8B3gB0TgeRvGlgeI0HMylD3GmKhK8bFliywWi8VisVgiwKDojrRYLBaLxWI517BOmMVisVgsFksEsE6YxWKxWCwWSwSwTpjFYrFYLBZLBLBOmMVisVgsFksEsE6Ypd8QkcdE5IPO/COnKkAsIveIyCed+U+LSEEfz1coIjtEZP7pWx3yuKtFxHe2j2uxWCyW8xvrhFkGBGPM3caYHgUVjTG/NsY87ix+Gi0D0leuNsZsPI39wmKMuRo4q8e0WCzRifMD8OfO/FIRue8sHvu9s3CMPv/YFJEJIrJVRHxnen7L2cU6YZZeIyJDRORvIrJNRHaKyB1O+4MissFpezhU/U4RecN9aDhRpe87x1krInlO+1IRuc+Jns1HxRi3isj7ReQvnmNdLyKnLOPiPKx+KCLrnc9Ep/1Djq3bROQtp+3kg9dZfkVEFp3J/bJYLBYvxpizVdKoTz82jTGHnBqxlijDOmGWvnAjUGqMmWOMmQn83Wn/uTHmIqctGa0R1hNDUNXkOcBbaJWAkxhjnkMjTx9zHhzLgWkikutschfwaC9tbjDGLAB+DvzUaXsQeJ9z/lt6eRyLxTJIEZFPish254fXE05brog87/yA3CAil/XheFs9n2YRuSpo/Qznh99W57yTnHafM/0Pz/4lIvKo0/5xz36/capZnMqWQhH5LxFZIyIbRWSeiKwQkUMiMpgqeJyXWCfM0hd2ANc50aUrjDH1TvvVIrJORHag9S5nnOI4rYBbHmcTMLanjZ1SVE8AHxetdXgJ8GovbX7KM73EmX8XeExEPguc8iFnsVgGLyIyA/gWcI3zw2uJs2oZ8L/GmIuADwCP9PaYxpi5zg/Eb6M/GIO7Ge8BljnbzEdrFHr3f9BZdxVQDfxcRKYBdwCXOes6gI/10qRjxphLgLeBx4APAguB/+jtNVkiw2CpHWmJAowx+0XkQuBm4L9FZCXwI+CXwHxjzDERWQokneJQbZ4anx307u/wUeCvaD3NZ40x7b01O3jeGHOPiFwMvB/YKiJz0bpv3h8lp7oGi8UyOLgGeM4YUwVgjKlx2q8DpnuyJ9JFJK23B3WiWz9Gnbu2oNVrgG+JyEjgBWPMgRD7C/BH1BHcJCL3AhcCGxybkoGKXprzsjPdAaQaYxqBRhHxi0imMaaut9dlGVhsJMzSa5zRik3GmCeBnwDzCDgrVSKSiv4COxs0AicfiMaYUqAU+Hf0l15vucMzXQOapGqMWWeMeRCoAkYBhcBcEYkRkVHAgjO9AIvFEhUIXX+MucQAl7hRLWPMCMd5OfUBRYYAzwCfdZ5NXTDG/AlNdWgGVojINSEOsxQoNsa4qRUC/MFjzxRjzNLe2AO0ONNOz7y7bIMtUYz9cix9YRbwYxHpBNqALxhj6kTkt+gvsEJgw1k612PAr0WkGX1QNqO/GnNPNcoyiEQRWYc+cD/itP3Y+RUrwOvANqf9CHodO4HNZ34JFoslCngd+IuI/K8xplpEsp1o2ErgXjSahYjMNcZs7eUxHwUeNca8HWqliIwHDhtj/s+Znw38w7N+MXA9sCjIzpccOytEJBtIM8Yc7cvFWgYXEugVsliiG2f04hZjzO/CrC9Eu0WrQi2f4bnfAO472/IXFoul/xGRTwH3o+kPW4wxnxaRHOAXwDQ0IPGWk6rwafS5ca+TXuEzxvzEc6wx6A+27Z5T3O19NojIA8DH0R+rZcBHjTE1IuIzxqSKyGpgHFDn7PKyMeZB0RHnD6A/GtuALxlj1gZdSyFhnnNe28Ns6zPGpJ7ufbScfawTZhkUiMgm4ARwvTGmJcw2G4AE4DPGmI1nywlzHpgTgH8yxmw71fYWi8XSX5zJc806YdGHdcIsFovFYhkkBP/Y7OU+E4Dn0e7NCf1pn6VvWCfMYrFYLBaLJQLY0ZEWi8VisVgsEcA6YRaLxWKxWCwRwDphFovFYrFYLBHAOmEWi8VisVgsEeD/A/phQf++Y0cjAAAAAElFTkSuQmCC\n", + "image/png": 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -504,7 +860,16 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:19:18.655981Z", + "iopub.status.busy": "2023-04-04T02:19:18.655397Z", + "iopub.status.idle": "2023-04-04T02:28:58.849918Z", + "shell.execute_reply": "2023-04-04T02:28:58.834236Z", + "shell.execute_reply.started": "2023-04-04T02:19:18.655924Z" + }, + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -512,21 +877,19 @@ "text": [ "Raw statistics (not volume-weighted):\n", " Variable: mean std mode 1 50 99 percentiles\n", - "potential_temperature : 0.5422 1.032 0.1019 -1.435 0.3659 4.811 degC\n", - "salinity : 34.6 0.7318 34.9 31.5 34.89 34.92 psu\n", - "potential density anomaly: 27.75 0.5853 28.01 25.24 27.98 28.05 kg/m^3\n" + "potential_temperature : 0.5422 1.033 0.1019 -1.435 0.3659 4.811 degC\n", + "salinity : 34.6 0.7318 34.9 31.5 34.89 34.92 g kg-1\n", + "potential density anomaly: 27.75 0.5858 28.01 25.24 27.98 28.05 kg/m^3\n" ] }, { "data": { - "image/png": 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W6PDhwxoaGtIxxxzj8U9SfKsOZ97eEJHe/eu4Pv/WzB9sAKgV8bitwfFIMjEXcVbXjU6qfyTiGB8ZmVQ/CTvUOGInAEAt29m4zuspoIYQNwEAaoXty1zwE59YXuaZlBZJvir0qU99Su95z3u0adMmNTU16aabbpIkffKTn9Tb3/52nX766XrFK16ho48+WpJ04okn6l//9V/1mte8RvF4XMFgUF/72tdqMuDKVMk35bQ/21oyaOtwG9V8AKrLZDSuA8MT2j84rhcGJ3RgKPH3weEJR3XdkWTFXbxCE3aGIbU3BrWkqU6Lm+u0uKlOS5qDam8MqrUhqOb6gFrq/WquDyQfB7T5817PGrWA2AkAUMuOBBd5PQXUEOImAECtsDNUp0tSfPKoMs+ktEjyVZiOjg49/vjj0+Mbb7wx43M//vGP0167dOlS/eIXv5ge/8d//Mf040suuUSXXHJJCWZcOfwxW8sHsj/vs6XzHrX1/XNJ8gGoDJFYXAeGJvSCK3n3wuC49ie37z48oqGf3en1VDNqbwxqSXOdFjXNJO6WJJN3i5uCjvGS5jq1Nwblz3IXFTBXxE4AgIVuwlc/+06AZo+b7rvvPrW2thI3AQBqQrYkX2yittaOJcmHmrFkKLH+Xi7nPRrX988xEuUkAFAiqcm7/UMzFXj7U5J4B4YmdGhk0uupTmttCDgSctkSd0uaE9sWNQYV8GcOlgAAAFA+E746r6cAAABQcbK36yTJB1Skhkj6tnd/2K9vfiWmumhivGJAWv+C9NzK8s4NQG0YnYxq/+CEDgxP6EAyeZdoozmRSOYlt3mdvGutD2hRc0qSbro9ZtAxnkrmLW6qU5CEHQAAQFWikg8AACBdpko+25bikyT5gIpUl5LkO+fpndq1VBprMPTwsYY2Pz1T4rf5qbieW+kv+PhXdXyuGNMEUGFicVuHRyYTSbuh8eTfiSTegeEJHUgm9fYPjmtkMubJHA1DWtpcr6Pa6rWitV5HtTVoRVuDlrfWJxN2iQq7JU11WtRUp7oACTsAAIBa9uF1n9O/fjumcyb36SdLJTV6PSMAAABvua/fTyX5znl658y2aJsUbyjrvEqt7Ek+K2ReIOnLkvySbjDDVrfreSP5/EWSRiVdZoath5LPfUvS6yTtN8PWyRmO/VFJX5C03AxbB0v6g6DiTFXrSVL72KT2SJICuu94Z5Lv7KdsffcVhR9/e+PO2XcCUFHGIzHtHRjX3v4x7RkY176Bqb/HHS0zY/FZev2WSMbkXWu9VrQ1TD9+9omH9PpXb6E1JgAAAKY9W79D8YGY2iWN+2vrQhUAAMBcuK/fT7XrbB+b6bhVa606pTIn+ayQ6Zf0NUmvlrRL0v1WyLzdDFtPpux2oaQNyT9nS7ou+bck3Sjpq5K+neHY65LH3VGq+aOy1UWcF+kngokP8UPHGYr6pEA8sX3tIWl5v60Di1iXD6hmE9GY9g2Ma0//uPYNjmlP/7j2DoxNb9s7MKYjoxn6+JbBVPIukbjLnLw7qq1BS1tmb5N55M8+EnwAAABwMFK+/g4HKeMDAABwy9SuMz6x3IOZlFa5K/k2S9puhq1nJckKmbdKulhSapLvYknfNsOWLekPVshcZIXMVWbY2muGrbuskNmR5dj/IenvJf24dNNHJUut5Hts7XIdbpKkIxppNLR9lRTaPfP8yiOFJ/mu3vsOSdK1q26Z/2QB5DQZjeuFwfFEFd5AIoE3VYU3lcg7OFz+de+CfkPLW+q1vK1By1vqtaKt3vH3UckkXj7JOwAAAGCurtz/DtWfauv+gz/XSJBKPgAAgGzX7x9bm0jsbdx1QJpcUvZ5lVq5k3xrJKXWTO7STJVern3WSNqb7aBWyHyDpN1m2HrECplZT24YxuWSLpekQCCg3t5ex/Pt7e0aGhqa9YcoplgsVvZzFmK5Pz2z/erzXq2en/eorq6uoGP957//p/7mI3+T8bkvdH9Bzc3NuvKqKx3bR3wj2tqyNevcUp9bEXhK0i8kSTuXtkmStrZcKklatOwX0u6npvd968QWndtyUkHzv7B/oyQpsqG9oNdNyfZzeMH93lUL92fWC8PDwxUxj2o09d7F4rb6J2wdHk/9E3eMBydslbOBZlNAWlRvqD3lz6J6X/JvQ+11iW3NQckwDEmR5J/hxAHGEn+OHJCOFHlu/JsDqt8ZZ5yhe++9t+DY6bOf/az+8R//MeNzn/rUp9TS0qKPfvSjxZgiAKDKvGboZVKH9KwekG1wcxlqC7ETAGAuLuw/V9JMks+IJ1r7TeUKNu46ICPa5M3kSqjcSb5MpVPu67j57DPNCplNkq6R9JrZTm7b9jZJ2ySpubnZ3rJli/NYlqXW1tbp8ZbvbtGh8UOzHTZvSxuWqveSXse2oaEhxzkrRUdHh/r6+rTjoLP76e4du7Vk5RIN+AekWGHH/M9//0+986/fmfG5EXtEtm3rQOyAY/tQfEjXDV+X8TVbW7Y6njtvOC532m7q+bc3xfSmlO2P7f+tbhu+q6D5v0FfdxwzX1fqyjm9rpTc7121eOzNj3k9BfX29sr9uwMzYnFb+4eSFXjJlplT1XjhHWMasaM6MDShci2B5/cZOqq1XivbG7RqUaNWtzdoZXvi76PaE20zl7XUqyHoL8+E5oB/c6gm5YidKtVU7OTW19enNWvWFHyRSsp9oQoAAEma8BX+/xdUDmKnvrTtxE4AgGKZSvKlsknyzdsuSetSxmsl7ZnDPqleJGm9pKkqvrWSHrJC5mYzbO2bz2SLGWjlc7y+vj5dcMEFOvfcc/WHP/xBp5xyit7znvfok5/8pPbv36+bb75Zmzdv1sjIiK666io99thjikaj+tSnPqWLL75YfX19+qu/+iuNjIxIkr761a/qpS99qXp7e/WpT31Ky5Yt0+OPP64zzjhD3/nOd5LVKIX53a9/p3NfeW7OfQ7sO6CPvv+jGh4aViwW0yf+7RO665d3aWJ8Qm/e8mYdFzpOn7/+8/rGv39DP/neT7RyzUotXrpYJ55yYsHzSVWXY+mtg22GUnPFywbndSpgQYrHbR0cnki0zOyfSd5NjfcNjOuFoQnFcmbwJoo2H8OQVrTWa1V7o1YvatDKtsTfq9obtbK9QasXJVpqsp4dUD7ETunuvPNOXXDBBTn32bt3ry655BINDg4qGo3quuuuU09Pj8bGxnTqqafqpJNO0s0336zPfOYz+va3v61169Zp+fLlOuOMMwqeDwCgtkz66r2eAuah0mKnbdu26bzzziN2AgDUBCPDNUo71uzBTEqr3Em++yVtsELmekm7JV0q6R2ufW6X9KHken1nSxoww1bWVp1m2HpM0oqpsRUy+ySdaYatg0Wee1ls375dt912m7Zt26azzjpLt9xyi+6++27dfvvt+uxnP6sf/ehH+sxnPqNXvvKV+ta3vqX+/n5t3rxZr3rVq7RixQr98pe/VENDg5555hm9/e1v1wMPPCBJ+tOf/qQnnnhCq1ev1jnnnKN77rlH556bO1mXyT2/uUd//y9/n3Ofnh/06KXnvVQf+MgHFIvFND42rjNecoZu+a9b9P3e70uSnnjkCf3sRz/Tbb+5TbFYTG995VvnneSrj2Z/7mCbc0ySD0g3OhnVnv4x7e4f1+4jY9rTn/izK/n3voFxRctVgidpeWu9VrU3JP8kE3nJKrxVixq1orWede8AVHzs9LOf/Uz/8R//kXOfW265Ra997Wt1zTXXKBaLaXR0VC972cv01a9+VQ8//LAk6cEHH9Stt96qP/3pT4pGozr99NO5UAUAoJIPBcsVO33pS1/SeeedR+wEAKgJRixDJV+cSr55McNW1AqZH5L0c0l+Sd8yw9YTVsi8Ivn89ZLukHSRpO2SRiW9Z+r1Vsj8X0lbJC2zQuYuSZ80w9Z/lfNnKLX169dr48bE2m8nnXSSzj//fBmGoY0bN063MfjFL36h22+/XV/84hclSePj49qxY4dWr16tD33oQ3r44Yfl9/v19NNPTx938+bNWrt2rSTp1FNPVV9fX1qw9ZnPfEa33XabJGnPnj069dRTNR4d12mbT9PH/+3jikxG9MKeF7SuY51yOfnUk/WJv/6EotGozr/wfIU2htL2eejeh3T+ReersalRknTeBefN4d1yylnJ1+68e2zZYDlX+wK8Z9u2Dg5PancyYbf7yNjM4+TfR0ZzfIiKbGlznVYlq+5Sk3hT46PaGlQXIIEHYHaVEDvF4/Hp2EmSzjnnHH3ta1/T5OSkdu3apWOPPTbnz3DWWWfpve99ryKRiN74xjdOHyfV7373O73pTW9SU1PiC8kb3vCGgt8rAEDtIcmHQuWKnXbsSCzZUs7rThKxEwCgNDK164yR5Js/M2zdoUQiL3Xb9SmPbUkfzPLat+dx/I55TtFT9fUzrTZ8Pt/02OfzKRpNlKrZtq3vf//7OuGEExyv/dSnPqWjjjpKjzzyiOLxuBoaGjIe1+/3Tx8r1TXXXKNrrrlGUqI3+sMPP6wnDj4x/fyDf3hQp519miTpVz2/0nVfSKzp9un//LROPvXk6f3OfOmZuuknN+muX96lj33wY7rsg5fp4ksuTv9hC+/akFNdNHvizl3Jt3RQMmxb9hxaRwCVamA0op1HRrXz8Kh2HB5NPh7TziOj2nVkTJPR9P+xlcLipmBKxd1M4u6F557SRVterKPaGip6DTwA1aUSYqehoSFt3Lhx+s7xKb/73e+mL2798Ic/1Kc//WlJ0g033KAzzzxzer+Xv/zluuuuu9TT06O/+qu/0t/93d/pXe96V9r55tLyCgBQ22jXiUJVQuwkzVx3SkXsBAAoJneSL2b4FLdJ8qECvPa1r9VXvvIVfeUrX5FhGPrTn/6k0047TQMDA1q7dq18Pp9uuukmxWKxop737t/crZed/zJJ0qs6X6VXdb4q4357du7RilUr9Ja/eovGRsZkPWrp4ksuVjAYVCQSUTAY1BkvOUPXXH2N3nf1+xSLxdT781699d1vndf86lLix7bRCR1qnRmP1RsaqZeak8uB1cWktlFpoIAWvM807JjX/ID5Go/EtCslcbfzcOLxVEJvaDxHz9oiaWsIaPWiRNIutXXm6vYGrUxW5DXWZU7g9Q5u1zFLa6/vNYDK51Xs9LOf/UwXXnihJOlNb3qT3vSmN2Xc7/nnn9eaNWv0/ve/XyMjI3rooYf0rne9yxE7vfzlL9dll12mrq4uRaNR/eQnP9EHPvCBos4XAFA9ngvu0NEHbBkxul+g+IidAADVyH393rATRUFto4mkwFCw0fkC32hZ5lVqJPmq0Cc+8Qn9zd/8jTZt2iTbttXR0aGf/vSnuvLKK/XmN79Zt912m8477zw1Nxf3Yvr999yvD/3Dh/La77+/9t8KBAJqam7SZ7/2WUnSW971Fv3FK/5CJ246UZ+//vO64OIL9Jbz3qJV61bp9BefPu/5pSb5zn1ml7Zd4JM084XnYJvUfGBmn2UDhSX5rl7fPe85ArnE4rb2Doy5knij2nlkTDsPj2r/0ERJzx/wGVrZ3qDVixq1dlGjVif/rFncqDXJirzmev63AVQ6K2ReIOnLSrRGv8EMWxn/B2aFzLMk/UHSJWbY+v/KOMWy8yp26u3t1T//8z/ntd8XvvAFBYNBtbS06Nvf/rYk6fLLL9emTZt0+umn6+abb9Yll1yiU089Vcccc4xe9rKXFXWuAIDqcs1Rn9M3botp5fGvlFZ5PRvUGmInAEA1cl+/N+KJJN+5z+ySJO1oWeF83k+Sr+YtbViqQ+OHinq8XDo6OvT4449Pj2+88caMzzU2Nuob3/hG2us3bNigRx99dHr8uc99TpK0ZcsWbdmyZXr7V7/61VnnOrWGzZR9e/Zp8ZLFamhsyPyCFBdferEuvjS9PedH/ukj+sg/fWR6/IGPfEAf+Ejx7qKqdy0nNuH6132wzdAxB2Zaei4btPXn1bRuQPnYtq0joxHtmGqneXh0ujJvx+FR7ekfUzReuvUiWxsCWrOoUWsyJPBWL2rUitYG+X18JoBqZoVMv6SvSXq1pF2S7rdC5u1m2Hoyw36fV2Kd5KIhdpqxa9cuLVu2TI2NjZlfkOLd73633v3ud6dt//znP6/Pf/7z0+PUFlcAgIXNl/zaMOK+Ix1VpdJip/vuu08SsRMAoDa423UO1jlbdRqBkXJOp2RI8uXQe0mv11OoGCtXr9T1371+9h09VOfqVDgZdI7d6/ItGyztfLBwTURjev7QqJ49MKw/HxjRswdG9OzBYT17YEQDY5HZDzBH9QGf1i5u1LolTVq3uElHL2nSuiWNWru4SeuWNKm9MTj7QQBUu82Stpth61lJskLmrZIulvSka7+rJH1f0lnFPDmx04y1a9fqzjvv9HoaAIAaZSSTfMMk+aoasdMMYicAQLG5k3xDdc4KdCr5gAoTTMmd3HHKi2Q+K90Xen5628F2Q5Kzkq8Qd1pflyRdaF45r3miNti2rQPDE/rz/pkE3rMHhvXswRHtPDyqUhTk+QxpVXuj1i5uTCbwEkm8qYTespZ6+ajEAxa6NZJ2pox3STo7dQcrZK6R9CZJr1SRk3wAAKA8/mfPddIbpe3DD3k9FQAAgIrgvn5vxBJJvjtOeZEkyd9Pkg+oaO5KPjcq+TAXE9GYnjs4kkjmHRjW758Y1388freePTCioYlZ/tHNwdLmOq1d0qR1GSryVrU3qi7gm/0gABayTJl+920H/ynpH8ywFbNCZu6DGcblki6XpEAgoN7eXsfz7e3tGhoamutca0YsFquY92F8fDztv5PXhoeHK25OlYT3J7dafH+2tmwt2rGW+5cX9Xi1Zr7vTzW8t5O+Oq+nAAAAUJEMVxXGYNDVrpMkX22ybVuGQSVMJbBtW3badcns6qK59z3Y5vzvunSgdGufofpEY3E9f3hUT+8b0lMvDOmZF4b11AtDeu7giGJpZXkDcz5PfcCnjqXN02003RV5zfX8WgYwL7skrUsZr5W0x7XPmZJuTSb4lkm6yAqZUTNs/ch9MNu2t0naJknNzc126lorkmRZllpaWhZ87DQ0NKTW1lavpyHbttXQ0KDTTjvN66k49Pb2yv1vBzN4f3KrxffnqpuuKtqxtrZs1XXD1xXteLVmru/PlUrc/V3J7+0blLhTfcJX7/FMUCiuO1UO2+a6EADUsrQ1+erdlXysyVdzGhoadOjQIS1dupSAy2O2bWtyaFI7x3bOvnNS/SxLnVHJBynxb2vf4Lie2D2YTOYN6akXhvXn/cOajMVnP0CeVrc36NjlLTp2ebOOXdY8/Xh1eyMtNQGU0v2SNlghc72k3ZIulfSO1B3MsLV+6rEVMm+U9NNMCb58EDtVDtu2dejQITU0NHg9FQBAGU1QyVdViJ0qB7ETANS+tCRfHZV8NW/t2rXatWuXDhw4ULZzjo+PV3RAsW94nyfntWVr59hOfXPHN/N+zWztOo+0SnFD8iVv1Fo0KgUjtiJBAutadmRkUo/uHtCjO/v1yK5+PbJrQAeGJopy7KY6fzKJl0zmLW9JJvSa1VTHr1cA5WeGragVMj8k6eeS/JK+ZYatJ6yQeUXy+euLeT4vYqdKVCnxXENDg9auXev1NAAAZTRJJV/erJB5gaQvKxEj3WCGrW7X8yFJ/y3pdEnXmGHri67n/ZIekLTbDFuvm8scKj12qpSYplyInQCgtrnbdQ7VsSZfzQsGg1q/fv3sOxZRb29vxbVUSvW2m97m9RTyNluSL+4zdLjVWcG3dEjat6S080L5jEdienz3gB7emUjmPbKzXzsOz/+X9er2Bh13VKuOXdasWP8eXfDS0/Si5S06qq2euy8BVBwzbN0h6Q7XtozJPTNsXTafc3kRO1WiSo/nAAC1i0q+/CQTdF+T9Gol2pvfb4XM282w9WTKboclXS3pjVkO89eSLEltWZ6fVaXHTsQ0AIBaYtjOSr4BknxAZaubpV2nlGjZmZrkWzZoa98SkjTVav/QuB56/ogefP6IHnj+iB7fPaBIbO499Ze11OuElS3asKJVJ6xs1fFHtWrDUS1qawhO79Pbe0DnHLesGNMHAAAAgDmbkK2Yb+ayjqGYh7OpeJslbTfD1rOSZIXMWyVdLGk6yWeGrf2S9lshs9P9YitkrpXUKekzkj5SlhkDAIB5Sa/kc7frZE0+oKKkVvKdvHO/vvVqX9o+B9sMSTMf7kLW5bt25c3zmB2K4flDI/rdMwf1YDKxN9cqvfqATyetbpO5qk0nrGzVhhWtOv6oFi1todUNAAAAgMr3P80361V/CEobL5je5teYhzOqeGsk7UwZ75J0dgGv/09Jfy+ptYhzAgAAReS+fm/EEpV8J+/cL0n69moq+YDKZduqT0nyHX14SNZ6vyRnld5BV1ONZQP5n+LOxffMfX6Ys9jYGkUGNyk2bOoVX+gt+PV+n6Hjj2rVKWvbtWntIp2yrl3HH9WqoD89CQwAAAAA1eDuhrt15gtLnEk+Y9zDGVW8TC188moDY4XM10nab4atB62QuSXnSQzjckmXS1IgEFBvb2+B0/TW8PBw1c25mvD+lg7vbWmV+/3d2rK1bOeqBMv9y6vqZ67oubYk/tqqTZIkv/0tSYlcQVxGWiXfFe1/qat1b1mnWAok+VATgq71+Cb9kp1hrbT0Sr65t3ZEadmxRo2/0KnowJkFvW7NokadccxinbJukU5Z266TVrersc5folkCAAAAQPkZtjQSaHBsI8mX0y5J61LGayXtyfO150h6gxUyL5LUIKnNCpnfMcPWX7p3tG17m6RtktTc3Gxv2bJlXpMut97eXlXbnKsJ72/p8N6WVrnf36tuuqps56oEW1u26rrh67yexqyu1JWSVBVznXJubCb9NRJsUNxIKfrwTWjbaPX8LLmQ5ENNqHMl+Z5f1qrjd/j19NHDju2HXJV8Swto13nhkXMkUdFXDvFIu0aff7/sSO617wI+QyetadeZxyzWGccs1ulHL9bK9oacrwEAAACAavey8XM1vnapY1uAdp253C9pgxUy10vaLelSSe/I54Vm2PqYpI9JUrKS76OZEnwAAMBb7uv3RjzRrnPHklbtb1js2LdW1uOTSPKhRriTfM+sXKGXPq60JF9/s7O6r20s/0q+q/e9UxJJvlKzY40a3fG+jAm+gM/Q5vVLdM5xy3RmslqvIUiVHgAAAICF5Z2j79RvjotIKYm9gKjky8YMW1ErZH5I0s8l+SV9ywxbT1gh84rk89dbIXOlpAcktUmKWyHzbySdaIatAm4PBgAAXnFfv59K8j2+boX21R/l2LdW1uOTSPKhRtRF8ttv0Nl2V22181muCbZtaGz3pbInlzu2++peUN3yX+uP779RbQ1Bj2YHAAAAAJVj2LWkXMCgki8XM2zdIekO17brUx7vU6KNZ65j9ErqLcH0AABAkU0l+SRpzFfvfI4kH1BZ6qOz7yNlSfLZtpRh/T6U3+ShVyg2coJjW6D1MTWsuVWGESPBBwAAAABJaUk+KvkAAACmGfGZWGnc3+h8robadfpm3wWofPlW8k3UGRpPyRMFY1LjRGnmhMJERzs0eeA1jm2+xj41rE4k+AAAAAAAM0jyAQAAZGHbMuyUJF8NV/KR5ENNqIvmv7YeLTsrTzzarPHdb1fqryTDP6zGNbfI8JHgAwAAAAC39CQf7ToBAAAkyedKF4z7GxxjknxAhanLs12nJA06K3NJ8nnMtg2N77lEdrTdsb1h9ffkC7K+OQAAAABkMuwaU8kHAACQ4I87x2M+d5KPdp1ARSkoydfsXH+vfTT/KkAU3+TB8xUbOd6xrW7pbxVoedqjGQEAAABA5XNX8gVtKvkAAAAkyedK8tVyJV/A6wkAxVDvWpOvNfKsvnKxP+O+c23XeaF55Rxmhlyiw8dr8uArHdv8jc+pbvkvPZoRAAAAAFS+v226QsM7rpCWHTu9jUo+AACwkKVev0+t5LvokT/r/86xpeaZbbWU5KOSDzXBXck3Gcy+L2vyVYZ4ZJHG9lwi5zp8Q2pYc4sMI579hQAAAACwwBmSRoLOtSiCrMkHAAAgKb1d53CdM24y/LUTN5HkQ02oc1XyTeaoUR1ool2n1+x4UGM7/0qKpdw+obga1vyvfMEhz+YFAAAAANXAsKXxQJ1jW8Ce9Gg2AAAAlcXdrnPCX+faoXbiJpJ8qAnuSr54bI1ed/fKjPvOtZLv2ue6dO1zXXOYHVLZtqHxPW9TfGKNY3vd8p8r0PysR7MCAAAAgOrx1+MfU7xxsWObTzGPZgMAAOC91Ov3qZV8d29Yq8F615p8NZTkY00+1IS6qLMaz7DrtWww877uJF9rnkm+DeNHz2FmcJs8eL6iQxsd2wItT6hu6f95NCMAAAAAqC5r7WMU9w1Jmvku7LPpUgMAABau1Ov3qUm+waZ6TfqclXyG4WoNWMWo5ENNcLfrzGWQdp2eiQxu1OTBVzm2+er3qmHNd2UYWV4EAAAAAEjjXsncl7YFAABgYfK5LvlHfK56txqq5CPJh5rgbteZy1zbdWJ+YmNrNL7nrY5thn9YjetuqqnyaAAAAAAoB3dKz7BJ8gEAAEjONfniMhQ3/ErdIqOAhEKFI8mHmjDvJB9tTUoqHmnV2K53SXZqWXRUDWv/R75gv1fTAgAAAICqFZPze6xPfK8FAACQnO06o4azis8wIjXVVY4kH2pCIe06J+oMjQdnxsGY1DhR/DkhwY4HNLbrr2RH2x3bG1b9SIGm5z2aFQAAAABUt7R2nVTyAQAASHIm+dytOn2qnfX4JJJ8qBGFVPJJtOwsF9uWxve+WfGURU8lKbjkdwouesCjWQEAAABA9UtP8lHJBwAAIDnbdbor+fyqraWjArPvAlS+elfy/WD7oA61Za+5HWyUVgzMjNtHpReW5D7HnYvunscMF6bJg69WdPA0xzZ/81OqX3GHRzMCAAAAgOr3gH6nqL1RMmbu3aaSDwAALGSp1+9TK/mWDjrb+JHkAypQXdR5x+Kzaw/pyWOyF6oONhtSynoFbaO2pNyNeK9ddct8prjgTPafqcmD5zu2+er2q3HNLTIM7jAFAAAAgLn6qXGz4vHPOb7GkuQDAAALWer1e3/K5eejD4449vPTrhOoPO52nZOB3Ak72nWWVnR4gyb2vsmxzfAPq3HdTTL8LIAIAAAAAPMVN5zfew1xMyUAAIDkbNc54Q86ngvYtVXJR5IPNcGd5KufrNPSgbqs+7uTfO15JPmOG1un48bWzWF2C0tsfJXGdv+lJP/MRiOixrXflq/ukGfzAgAAAIBasdo+WrbhvKTjp5IPAAAsYKnX733xmZufDjU5kwEBm0o+oOLUuT6XZ1mr9fp7VmXdf6DJecdjol1nbl/p+5i+0vexOc1voYhH2jW28zIpXp+6VQ2rb5W/aYdX0wIAAACAmvJeOb+bGnZ8lgUoAAAAalvq9fvUNfkeW+vME1DJB1QgdyXfbGjXWXx2rF5jO98jO9ru2F5/VI+CbU94NCsAAAAAqD3umj2/HZePbp0AAACSnEm+qBFwPFcXJ8kHVJx5J/lGMu+H/Ni2T2O736H4xErH9uDiu1W35B6PZgUAAAAAtcmd5PPZtliSDwAAICH15qeIK8kXjNOuE6g47nadsxl0t+sc49vQfEy80KnYyAmObYHWx1V/VI9HMwIAAACA2pWe5KOSDwAAYIqjks8XdDxXR5IPqCyGbasuVthraNdZPJOHX6zIkXMc23wNO9Ww+rsyDL5lAgAAAECxub8C++y4+PoFAACQkJrkc1fy1ccnyjyb0iLJh6oXdLXqnAxk3i+VO8nXPiLJ5htRoaIjL9LEC693bDMC/Wpc+20Zvtq6IwIAAAAAKkXc1ZvTZ9sysuwLAACw0PhyrckXq63r1iT5UPXqXZ/JiTySfBN1hsZTqnQDcamxthL4JRePNmt89yWS/DMbjQk1rrtJvuCQZ/MCAAAAgFqXqV0nlXwAAAAJjko+n6uSLzZZ5tmUVh7pEKCy1bkr+YLST87ZO+vrBpukhoGZcduoNNaQff+rOj43xxnWHts2NL7nrbJjbSlb42pcc6v8DbO/9wAAAACAufvu5LVS3Xunx36SfAAAYIFLvX6fmuRbOjghpVzGbiDJB1SWOlcl32RAOtQ++wd1sFFakZLkax+VXliSff/tjTvnOMPaEznyEsVGQo5tdUt7FWi1vJkQAAAAACwgB+LOmyt9tk2SDwAALGip1+99KXFRPLUTnaSGKO06gYqSVsmXZ+p6qMm5YkHrGN+I8hGfXKqJ/Rc4tvkan1fd8l95NCMAAAAAWFhsw3k5x2fHWZMPAAAgKXVNvvFAveM5knxAhcmU5HvJY0v0ksdylOVJGm50jlvGcp/n6r3v0NV73zGHGdaOqTadsutmNvrG1bj6VhmGe1UIAAAAAEApnON/o2NMJR8AAFjoUq/fp7brPNzU5NivKVJb7TpJ8qHq1UWc32QmgoZO2NmqE3a25nzdkCvJ1zpLku/C/nN1Yf+5c5lizYgcPkexsQ7Htoajbpev7og3EwIAAACABWhD4EzHmEo+AACw0KVev09N8g3XNTj2ayTJB1SWObfrbKRdZyHik0s1ceC1jm3+FkuB9oc8mhEAAAAALEzuPio+O04lHwAAQFJqu86IL+h4rjFKkg+oKO4kXySYeT+3Qtt1LmS2LY3vu1iyU95c35gaVv5ABreLAgAAAEBZuZN8fpJ8AAAA01Ir+aKGsyqoaZIkH1BR6lzrZOZfyeccz9aucyGLDm1SbOR4x7aGo34iX3DIoxkBAAAAwMIVc42p5AMAAJiRK8nXQrtOoLLMvV2nc0wlX2Z2rF4T+17n2OZv2k6bTgAAAADwSHq7TpskHwAAQJIvPhMYRXzuSr6Ie/eqRpIPVa/e9ZmcyLNdp3tNvjbW5Mto4sCrZcfaZjYYUTWs/BFtOgEAAADAIxnbdXoyEwAAgMrjT7nUn1bJV2PtOvOseQIqV6ZKvsHGiVlfV2gl3zMNOwqcWfWLTyxT5MhLHNvqlv6ffPUHPZoRAAAAAOBgbK/kn7kZk0o+AACw0KVev/cl74iKGj7FDX/K9pgaIzHVUmqsdn4SLFh1Uec3mcmAoZ+eu2/W1w1nWpPPtpWtRO3q9d1znWLVGt9/kaSZX4JG8LDqlv7WuwkBAAAAAPTb0f+RWj84PWZNPgAAsNClXr+fWpNvwl/n2Kc+FkkrGqp2tOtE1Uur5MuzXedEUJqcyV8pGEtv/bmQRUdepNjwiY5t9SvulOGrsd+CAAAAAFB1nJdzEkk+snwAAADSTCXfeMCZ5GuITZLkAypNnSsxN5lvfaphZK7mg2xbmnjhIsc2X2OfAq2PeTQjAAAAAMAMV5JPNmvyAQAAJM1U8jkrgupjk9PP1QqSfKh69a7M+0RQuuyOY3TZHcfM+lr3uny5knx3Wl/XndbX5zDD6hMbNhWfWOPY1nBUT7ZOpgAAAACAMrqw9cOOMe06AQDAQpd6/d6fjIvc7TobohH5bCWqXGoEST5UvTlX8kkaanRmrVrGaufDPVe2LU0cPN+xLdD6qPyNOz2aEQAAAAAgVcw19tnxxAUrAAAAzLTrTFuTb1KSaurmqALSIcVhhcwLJH1Zkl/SDWbY6nY9bySfv0jSqKTLzLD1UPK5b0l6naT9Ztg6OeU1X5D0ekmTkv4s6T1m2Oov/U+DShBwfbuJFPCvmnad6WLDJyg+vtaxrW7ZbzyaDQAAAADALS7nlSl/Dd2NDgAAMF/+6SSfs11nQyxRMeSz02+aqlZlreSzQqZf0tckXSjpRElvt0Lmia7dLpS0IfnncknXpTx3o6QLMhz6l5JONsPWJklPS/pYcWeOSuZO8kUL+FddSLvOhcC2pYlDr3RsC7Q+Ln/DPo9mBAAAAABwcy8lQyUfAADAjOk1+QKZK/l8NbQuX7nbdW6WtN0MW8+aYWtS0q2SLnbtc7Gkb5thyzbD1h8kLbJC5ipJMsPWXZIOuw9qhq1fmGFramW2P0ha694HtSstyefP/7XuSr6WBZ7ki40do/iYcy3DumW/9mg2AAAAAIBM3Hee++24RJIPAABAUvZ2nQ3RZJKvhuKmcif51khKXdhrV3Jbofvk8l5Jd85pdqhKwZjzExkJGFn2TOdek691ga/JN3noFY6xvzksf8Nej2YDAAAAAMiESj4AAIDspuKiCVe7zvqpdp01VMlX7jX5MmVf3GFoPvtkZIXMayRFJd2c8eSGcbkSLUAVCATU29ubz2FLanh4uCLmkc3Wlq1eTyGr5f7l2tqyVWt0m6SZdpJvaHmTXtCfJM0+/5WLLUm/mh6fHjlejS2vyfmaub4nlfReTr13qQ6NBfRfw858+lvXLtLRFTTvSvisVPpntpLx3s0N7xsAAADc0pN8duarKQAAAAvQdLtOf5Z2nTV0c1S5k3y7JK1LGa+VtGcO+6SxQua7Jb1O0vlm2Mr4n8i27W2StklSc3OzvWXLlrwnXiq9vb2qhHlkc9VNV3k9hay2tmzVdcPXqTsSVXvK9u9N/FDBk1slSU8PX5f5xUlnGHGZKeO9Q0/ruuE/Z9y3b+U5kqQ7h+8paJ5X6kpJ0nWzzKWcpt67VOP7LlZq0ayvYad+anxNxnCZJ5fDY29+zOspVPxntpLx3s0N7xsAAADcnhq9W2o6Y3rss+Nlb9UEAABQSa5dOVP7NZXkG3etyddAkm/e7pe0wQqZ6yXtlnSppHe49rld0oeskHmrpLMlDZhhK2e/QCtkXiDpHyS9wgxbo8WfNipZIOocR/3Sc6vyy0wV0q7zzsWFJfeqiR33KzK4ybGtbuldMrgTFAAAAAAqzr7Jp9OSfAAAAAtZ6vV733QlX+236yzrjV5m2IpK+pCkn0uyJH3PDFtPWCHzCitkXpHc7Q5Jz0raLumbUrIMSpIVMv9X0r2STrBC5i4rZP6/5FNfldQq6ZdWyHzYCpnXl+cnQiUIuFYcj/rzf+1Qo3PcMjb/+VSj6HBIijVPjw3/iAKtT3o4IwAAAABANrbrco7PtmvqjnQAAID5yNquM0ol37yZYesOJRJ5qduuT3lsS/pglte+Pcv244o5R1SXgCvrHvVLx+9okSQ9fXTuir5hV5KvNUeS78IjyXadNVjRFx043TEOtD0iw4hl2RsAAAAA4KXldSc4xj47zpJ8AABgQUu9fj9VqTfuz9Kus4Yq+cqe5AOKLVMl30sfXyopjyRfQ2LB8ql7IJsnJF/cVtyX/vXo6n3vlFR7Sb54tEnRYecXxGD7Qx7NBgAAAAAwm2OaXixpfHrst+MstwAAABa01Ov3/niiVG8ikKVdZw1V8rEuM6peMMOafPmyfYZGG5zbFlrLzujgKUrN9/vq9svXsMu7CQEAAAAAcnL3XfHZtowaulgFAAAwH1nbddZgJR9JPlQ9d7vOSAFJPkkaLKBlZy2KDJ7iGAfaH+IOUAAAAACoYO7rUrTrBAAAmDFVqTfhp5IPqHiZ2nUWwr0u30Kq5ItHWxQfO9qxLdj+sDeTAQAAAADkJS7nlSmfHaeSDwAAIMmXrZIvmqzkq6G4iSQfqpttK+hK8sUKTPINNTrvd2wdq6FP+CyiQ6ZSfw34GnbJF+z3bD4AAAAAgNnRrhMAACC7qXadk76AY3tdPLH2F+06gQrhd30Yoz7JLrDXpLuSbyG164wOneQYB1qf9GgmAAAAAIB8ua9L+ankAwAAmDazJl/tt+sMzL4LULnm26pTkoYWaJLPjtUpNnqcY1ug5QmPZgMAc9fR1XOBpC9L8ku6oa+7s9v1fLuk70g6WonY54t93Z3/XfaJAgAAFEnGNfnyvFi1UGMnK2Q6fm4zbHW7ng9J+m9Jp0u6xgxbX0xuXyfp25JWKvHWbzPD1pfLOXcAAFCYqUq9iN+ZAgvOoZKv0mMnKvlQ1bIl+W686HndeNHzeR0j33adF5pX6kLzyoLnWKmiIydI9swvOSN4UL76FzycEQAUrqOrxy/pa5IulHSipLd3dPWc6Nrtg5Ke7OvuPEXSFklf6ujqqRMAAECVevzIjx1jnx1XPj1tFmrsZIXMtJ/bCpnun/uwpKslfdG1PSrpb82wZUp6saQPZngtAADwWOr1e3/yEv98K/mqIXYiyYeq5l6Pby6VfO52nS0LpJIvOuT8XRRofVIFdjoFgEqwWdL2vu7OZ/u6Oycl3SrpYtc+tqTWjq4eQ1KLEhdwouWdJgAAQPHYtvNyTgFr8i3U2GmzpO1m2HrWDFsZf24zbO03w9b9kiKu7XvNsPVQ8vGQJEvSmvJMGwAAzMVUu86Ie02+qSRf/pV8FR87keRDVXNX8kVo15mXWFyKDocc2wKttOoEUJXWSNqZMt6l9IsuX5VkStoj6TFJf93X3VlDSywDAICFxr0WfQFr8i3U2Cmfn3tWVsjskHSapPuKMy0AAFAKvixr8tXFC16Tr+JjJ9bkQ1XL1q7zdXevlCT99Nx9sx7DneRrydKu89rnuiRJV6/vzvh8Ndk51CDFZ35wwz8sf+MOD2cEAFkFDMN4IGW8zbbtbSnjTDXI7l/kr5X0sKRXSnqRpF92dPX8rq+7c7CoMwUAACiTda3n6t6UccqafMROmeXzc+dkhcwWSd+X9Ddm2Mr4XhiGcbmkyyUpEAiot7e3wGl6a3h4uOrmXE14f0uH97a0yv3+bm3ZWrZzVYLl/uVV9TNX8lxf/sRxkqS7TtquFvsGSWOa9LmSfMlKvr9ouFj9LWv0QX2w6mMnknyoatnadS4brM/7GMNpa/Jl3m/D+NGFTK2iPdPf5BgHWiwZ+a7SDgDlFbVt+8wcz++StC5lvFaJO6dSvUdSd193py1pe0dXz3OSQpL+WNSZAgAAlEkw0C5pcnrss+2pK1DETpnl83NnZYXMoBIJvpvNsPWDbPslLwpuk6Tm5mZ7y5Ytc5qsV3p7e1Vtc64mvL+lw3tbWuV+f6+66aqynasSbG3ZquuGr/N6GrO6Uom17ip5rm8Y/bqkxBzPjEXll6GofyYFZthxBeOJhMLtIz/SE8M+qQZiJ5J8qGrZKvkKsdDaddq2oWeOOH9oWnUCqGL3S9rQ0dWzXtJuSZdKeodrnx2Szpf0u46unqMknSDp2bLOEgAAoIjc/Z98+bfrXKix0/2SNlghM9fPnZEVMg1J/yXJMsPWv5duigAAoFj8thRxt+qMRafL8gpo11nxsRNr8qGqlWJNvpYxSXbtVrXFx9doOJKS3zcm5G/e7t2EAGAe+ro7o5I+JOnnkixJ3+vr7nyio6vnio6uniuSu/2LpJd2dPU8JunXkv6hr7vzoDczBgAAmL+0JJ/sjL2k3BZq7GSGrbSf2wxbT1gh8worZF4hSVbIXGmFzF2SPiLp41bI3GWFzDZJ50j6K0mvtELmw8k/F3n0owAAgDz44tKkz1njFoxHHc/noxpiJyr5UNWKUckXCRqaCEj1yc94IC41Tkpj+Xf8rCrRoRMd40DL0zJ80Sx7A0Dl6+vuvEPSHa5t16c83iPpNeWeFwAAQKm4vgoXUsm3YGMnM2yl/dxm2Lo+5fE+JVpwud2tzOvxAACACuWPSxNBZyVffXI9PqmgSr6Kj52o5ENVC8Scn8aof25xd8ZqvhoVHTrJMaZVJwAAAABUl5ic34V9drygi1UAAAC1zB+XIn53Jd/cknyVjiQfqloxKvkkaXiBrMsXn1im+ORRKVtiCrQ85dl8AAAAAACFc3eY8tu2VEMXqwAAAObKsG35bGnC767kK7xdZzWgXSeqWrYk31Prhgo6zlCjodRvRK1jttzdOO5cdPccZlhZosPOVp3+5mdl+Gs0owkAAAAANWpoYp9Uv3R6TCUfAABY6Kau308l8CZ9ziRf3RzbdVY6knyoasEsSb57Nx4u6DjuSr5M7TqvXXVLQcesRBF3q84WWnUCAAAAQLU5PPpnR5LPb9fQ7egAAABzMHX9PpjM5U36cyT5aih0ol0nqlpaJd8c/0W71+SrxXad8Uir4mPrHNsCrZZHswEAAAAAzJnh/PJLJR8AAECCf7qSz1njVleja/JRyYeq5k7yRZL/opcO1EmSDrVP5nWc9CRf+qf8uGSCbHvjzsImWSGiw6ZS8/q+hp3yBQe8mxAAAAAAYE78/hbH2GfHWZMPAAAsaFPX7/cYOyRlquRjTT6g4qS160zmsF5/zypJ0o0XPZ/XcYZda/Jlatf5lb6PSZIuNK8seJ6VIOpu1dn6pEczAQAAAADMx6LWkyWlXKiybRkk+QAAwAI2df3+bcdslSRNuJJ89TW6Jh/tOlHV0tp1+ud2nMEab9cZjzYpNnKcY1ughSQfAAAAAFQj983nPjsuw5OZAAAAVJapKr2I31njFozP3CDlr6FKPpJ8qGppSb451qYOu5J8mSr5qll06GRJMxnQpQ2T8tW/4N2EAAAAAABzlp7ko5IPAABAmkngTfio5AMqXlqSb47/oocanfc8ZlqTr5pFB09xjM2lozK4zRMAAAAAqlKmSr5aulgFAAAwV/6slXwpST4q+YDKEIg5v8VE/XPLXA3VcLvOeKRVsdH1jm2hJSMezQYAAAAAMF+u+13lt2voShUAAMA8TCXwWJMPqALFWpOvltt1Roc2KfWj7mvYpSUN0ewvAAAAAABUtJicV6Z8tl1TF6sAAADmyp+MiSZd7TrrYjPXxKnkAyqEO8kXmWOSb7RBiqcUATZNSv5YbXxDigw4W3UG2x7xaCYAAAAAgGLI1K5TtfEVFgAAYF6m2nVO+t1Jvtqs5AvMvgtQuYJZKvl+cs7ego5jG4aGG6S2lAq+1jGpv2VmfFXH5+Y4S+/EJ5coPn60Y1ug7VFJJ3szIQAAAADAvA2O9EnN66bHiTX5auhqFQAAQIGmrt/7BhPjtCRfnCQfUHGytes81D5Z8LGGGnMn+bY37pzDDL0VGdzkGPsbn5MvOODRbAAAAAAAxRCNO7/zkuADAAAL3dT1+/X9ifGkz5n+ol0nUIGKtSaflEjypar2dflsW4oOnObYFqBVJwAAAABUvbgMx9hvx2vqjnQAAIC5mmrXOeGq5KunXSdQeQKujPvUmnwveWyJJOnejYfzPtZwo6HURQxax2wp5YvT1XvfIUm6dtUtc5prucXH1yo+eVTKlpgCbY95Nh8AAAAAQHHUNRzlGLMmHwAAWOimrt//3L5ZkhTxO9NfwTiVfEDFCUad46lKvhN2tuqEna0FHctdydfqquS7sP9cXdh/boEz9E6k/0zH2N/ylHyBEY9mAwAAAAAoFl/Q+X3XRyUfAABY4Kau308l8CZ8uSr5aidwIsmHquYvYrvO4Rpq12nHA4oMnuLYFlz0gEezAQAAAAAUk/vmc59ty6ida1UAAABz5o8ngqKIq11nsEbbdZLkQ1Vzt+uc35p8zjUNEu06q1N06CQpPpO1NPzDCrSEPZwRAAAAAKBY3Ek+v+1epQ8AAGBhmlmTz9musz6ekuSjXSdQGYJRZyIu6p/715rZ2nVWk8iAs1VnoP1PMowa+s0FAAAAAAtYeiVfnEo+AAAAzSTwJl3tOuuo5AMqT4B2nWnikXbFRl7k2BZsp1UnAAAAANQK11fhRLtOT2YCAABQWaYq+Sb97iRfdPoxlXxAhShuu07nuFrbdUb6z1DqR9vXsFP+hhe8mxAAAAAAoKio5AMAAMhsqkrPneRztOusobgpMPsuQOVyV/JFkkm+g20TBR/LvSafu5LvmYYdBR+z3GzbUGTgDMe24CKq+AAAAACglkTjEck3c5erz44rXkMXqwAAAAo1df3eP54YT/qc6a9gjVbykeRDVQtGneOpSr6fnruv4GO523W61+S7en13wccst9joetmRpTMbjIiCbY96NyEAqHIdXT0BSXXu7X3dnaMeTAcAAECSNDE5IDUsmR77bLsiKvmInQAAgFemrt+f80RiPOGu5KvANfmKETuR5ENVK2W7zpYxSbYtGdWzsoG7ii/Q+oQMf5UuLggAHuno6mmT9FlJfyFphZRxiZt5/B8HAABgfuKu8MSvuKIeXawidgIAAJVkak2+iN9VyVch7TqLHTuR5ENVc7frnE+SLxowNFYnNU4mxn5bapqQRhvmfsxysmP1ig5udGwLttOqEwDm4BuSXifpBklPSpr0djoAAABOtuFzjH22O+1XVsROAACgYvjjUkyGoqntOu24gvGZZILH7TqLGjsVnOSzQmbG8kEzbNF6AWWXluRLfs+57I5jJEk3XvR8QccbapxJ8kmJlp1TSb47ra9Lki40r5zTXEstMrhJsmc+mkagX/7mP3s4IwCoWq+V9OG+7s4bvJoA8RYAAMjFV79I0swt6P543Mt2nWWJnYiPAABALlPX778Yv0IRV6vOgB1z3BDlcbvOosZOeSX5rJBJ6wVUJPeafJF51qYON0orBmbGLWPSC4vnd8xycbfqDC56UEYlLMoAANVnRNKucp+UeAsAAOTLffO5x2vylSx2Ij4CAACF8selCVerzoDtrBbyuJKvqLFTvikRWi+g8th20ZN8Qw2GUu+GbBu1lfk7RGWJTyxTfKzDsS3Y/qA3kwGA6vclSVd2dPX8oq+7s5xhH/EWAADIS0zOjJ7P9rSSr5SxE/ERAAAoiD8uTboq+fy2M5HgcSVfUWOnfFMir5X0YTNseda2CnAzYnGlrkIQM6S4b34JucOtzvHygcz7VZrIwJmOsb/pWfnqDns0GwCoemsknSLpqY6unt9K6nc9b/d1d/5DCc5LvAUAAPKSVsknT9fkK2XsRHwEAAAK4rOlSV96u073Ph4qauyUb5LPk7ZVQC6+mPODOd8qPkk60O6s5FsxUPntLm3bp0j/6Y5twUX3ezQbAKgJb1Hi2llA0qszPG9LKkWSj3gLAADkpcLadZYydiI+AgAABfFlqOQLuCv5vG3XWdTYKd+0yJckXWmFzF+YYcvbHx9I8kWdSb7JIiT59i9yjlf0z/+YpRYbPl52rG1mg29cgdbHvZsQAFS5vu7O9R6dmngLAADkJeYa+2zvKvlKHDsRHwEAgIL449Kkz5ks8FdQJV+xY6d80yLT5YNWyMxYPmiGrVLc0Q5k5U7yRYuw1Pb+Rc6vRdVQyedu1Rlse0SGL+LRbAAA80C8BQAA8pJeyefpmnylRHwEAAAK4o9LE5VdyVdU+Sb5vGpbBWTlizo/mKmVfL8/+dCcjrm/3Tle3j/z+NqVN8/pmKUUjzYrOmQ6tgUXPeDRbACgdnR09Rwr6e8knStpiaTDkn4n6Yt93Z3Plui0xFsAACAvcduWjJmbVP227ekd6SWMnYiPAABAXqau37ccsBXxO1NfkeCYY+zxmnxFjZ3ySvKZYcurtlVAVkaOSr6njx6e0zGPtEoRvxRMHrp1XGqcsDVWb+jOxffMdaolEx04TdLMD+6re0G+hp3eTQgAakBHV88Zkn4raVzSTyW9IOkoSW+W9M6Orp7z+ro7Hyr2eYsVb1kh8wJJX1bifxA3mGGr2/X8xZL+RYkLZlFJf2OGrbuLcW4AAFB6ti3FDWcXGp8dT11evqxKGTtxPQoAAORr6vr9pXZ6JV8sMO4Ye1nJV+zYqQirmAHeKMWafLZh6ECbtPrIzLYV/dLzR83/2MVm21Kk/yzHtuCiB2R4tRADANSOL0r6k6QL+7o7R6c2dnT1NEm6I/n8Kz2aW05WyPRL+poSd7rvknS/FTJvN8PWkym7/VrS7WbYsq2QuUnS9ySFyj9bAAAwNz7HyEiux+fhHelVGzsBAIDak1iTz5nkMwzn8lYeV/IVNXbKOy1ihcys5YNm2CpV2yogq1xr8h2/o0XS3Cr69i8ytPrIzKd8xYCt548ydOGRcySpYir64uNrFZ9MzT7GFGj/k2fzAYAaslnS21IDLUnq6+4c7ejq+aKk75bqxEWItzZL2j61rxUyb5V0saTpJJ8ZtlL/59gsz+77BwAAc2I77+w0bM//V17S2InrUQAAIB9T1+998bs06arka4y4uyCUbVqZFDV2yivJZ4XMnOWDVsg8zwxbRW9bBeSSvibfzAf1pY8vlTS3JN8B17p8K/oTf1+9752SKifJF+k/0zEOtITlC8ytTSkAwGFM0tIszy1RIh4quiLFW2skpfZt3iXp7AznepOkz0laIalz/rMHAADl46rkS96v4+HFqpLFTlyPAgAA+Zq6fv/dDEm+RSPOVJgv7mmWr6ixU76VfNPlg2bYms4uWiGT1gvwjLuSL1Kk5rP7FxlKLWpYNuD5XZFp7HhQkcFTHduCix7wZjIAUHt6JHV3dPU829fdOb1WXUdXz7lKJMZ+UqLzFiPeytS0Oe1/ZGbY+qGkH1oh8+VKrM/3qowHM4zLJV0uSYFAQL29vbP/FAvQ8PAw700OvD+58f7kVovvz9aWrUU71nL/8qIer9bM9/2p1Pd2ImboyyljX/J/9U1q9GZCpY2duB4FAAAK4o9L4z5nsiBgOwuGPK7kK2rslG9aZLOkt6UGVJJkhq1RK2SWtG0VkE2udp3z0d/sHLePZt7PS9HBjVK8YXps+Ifkb3nKwxkBQE35iKQfS/q/jq6eA0rcMb4i+ef3kv62ROctRry1S9K6lPFaSXuy7WyGrbuskPkiK2QuM8PWQffztm1vk7RNkpqbm+0tW7bkMYWFp7e3V7w32fH+5Mb7k1stvj9X3XRV0Y61tWWrrhu+rmjHqzVzfX+u1JWSVLHvrR1rkPSp6bGhuCRpPD7mzYRKGztxPQoAABTEZ0sTrko+v+3MJfji5ZxRmqLGTvkm+TxpWwXk4k7yTRapkm/AleRrq8AkX2TA1aqz/SEZhre/mQCgVvR1dx6SdG5HV88Fks6StErSXkn39XV3/qKEpy5GvHW/pA1WyFwvabekSyW9I3UHK2QeJ+nPZtiyrZB5uqQ6SYfmPGsAAFBetqtdp8dr8pU4duJ6FAAAKIgvLkX8lVvJV+zYKd+0SI+kbitkPmuGrenyQStklrptFZCVL1aaSr7BJmens7bRymrXGZ9YptjosY5tdYvu92g2AFC7+ro7fybpZ2U85bzjLTNsRa2Q+SFJP5fkl/QtM2w9YYXMK5LPX6/EGjbvskJmRIkLZ5eYYauy/mcHAACysl3duStgTT5JJYuduB4FAAAK4o9LEz5nJV/AXclXAVdBihU75Zvkmy4ftEJmOdtWAVn5Is7se9Eq+Zqc40qr5HNX8fkbn5OvPq3DGgCgAB1dPU193Z2jU49n239q3yIrSrxlhq07lFijJnXb9SmPPy/p80WaMwAAKDdXJZ8vWclnlPFiVRljJ65HAQCAgvjjUiStXaerkq/MTfFKGTvllRYxw9YhSedaITOtfNAMW6VsWwVkVbpKPue4bVSSx+1Ppti2T5H+MxzbglTxAUAxDHV09bykr7vzj5KGJc32i79I/9eZQbwFAADy467ki2fYWnJliZ2IjwAAQKF8cWmiztWuM+55JV/JYqeCap/MsDXv8sFkYPZlJSZ5gxm2ul3PG8nnL5I0KukyM2w9lHzuW5JeJ2m/GbZOTnnNEiUWW+6Q1KfEosxH5jNPVL5ca/LdeNHzcz5uJGhorE5qnEyMA3GpeVy60LxyzscsluhwSHasdWaDb1yBtse8mxAA1I73SvpzymPP7u4oRrwFAABqmbOSr2kyIqm8lXwqc+xEfAQAAGYzdf3+I5Y06WrXaR27V7pnZlzuSj6VMHbKmuSzQmaTGbZGpx7PdqCpfXOxQqZf0tckvVrSLkn3WyHzdjNsPZmy24WSNiT/nC3puuTfknSjpK9K+rbr0F2Sfm2GrW4rZHYlx/8w23xQ3dxJvkiR2nVKiWq+qSSflKjmG2ks3vHnKtJ/lmMcbHtYhi/i0WwAoHb0dXfelPL4xnKdtxTxFgAAqHEV0K6zlLET8REAAJgPf1yadLXrlOFtu85Sxk6+HM8NWSFzc/LxsKShWf7kY7Ok7WbYetYMW5OSbpV0sWufiyV92wxbthm2/iBpkRUyV0mSGbbuknQ4w3EvljT1Jt0k6Y15zgdVzBd1fjAj/uI1J6nEdfnikTbFhk9wbAsuesCj2QBA7ero6nm2o6vnlCzPndzR1fNsEU9XingLAADUNOd3X5+dbNfpUR+CEsROxEcAAGDOfJmSfK5CGQ/adU4rduyUq/apFOWDayTtTBnv0kyVXq591ijRcz2bo8ywtVeSzLC11wqZKzLtZBjG5ZIul6RAIKDe3t6CJl8Kw8PDFTGPbLa2bPV6Clk1xx50jM9qfolWtpwuSRr/5d2SpIZXnzunYy9p/YkSnV8T3hZ/rU58/rWSpLtO2j6nY873vbx3T5t+l5KXX944qcuWvV7GHHKby/3LK/q/bTaV8Fmp9M9sJeO9mxveN090SKrP8lyTpLVFPFfFtAkFAADVwXZV8k0EE+Myr8mXqkPFjZ2IjwAAQMGufa5LkrQv/hlN+pypr5Ofa3OMvUzyqcixU9Yknxm2bkp5fGMhB80hU8zpfjvz2WdObNveJmmbJDU3N9tbtmwpxmHnpbe3V5Uwj2yuuukqr6eQ1b9HTMf4/6L36ufD90mSLjtyjCTpuuHr5nTsK+pjemXK+N7DP9NLG944p2NeqSvnNRdJsm1DI/v/1rFtsO1nun7k93M63taWrfOaj1cee7P36w9W+me2kvHezQ3vW3l0dPW0SVqUsmllR1fP0a7dGiRdKml3sc5bongLAADUMleSz05eRSlnJV8pYyfiIwAAMBcbxhOhyH5bmnBV8rWPudqdl7ldZyljp7xWMbNC5rOS3mSGrUcyPHeypNvNsHVsHofaJWldynitpD1z2MftBStkrkpW8a2StD+PuaDKlXpNvlRto0p8xDwSG10vO7JsZoMRUbD9T95NCABqz4clfVKJG4tsST/Msp8h6W+zPDcvRYy3AABATXNdpFL51+RTmWIn4iMAAFAoX1yK+J3JgoDtzCV4UMlXstgp37RIh4pTPni/pA1WyFyvRDbyUknvcO1zu6QPWSHzViVaeQ5MteLM4XZJ75bUnfz7x3nOB1UsLcnnL96xB5oNpRaQto/Y0pLiHb9Qkf6zHONA6xMy/GMezQYAatItkh5QIpi6XdJHJT3l2mdS0lN93Z07SjSHDpWvTSgAAKhWrotShjdr8pUrduoQ8REAACiAP25rwues5PPbUce43JV8KmHslDXJZ4XMtPJBK2TOq3zQDFtRK2R+SNLPJfklfcsMW09YIfOK5PPXS7pD0kWStksalfSelDn9r6QtkpZZIXOXpE+aYeu/lEjufc8Kmf9P0g5Jb81nPqhuvqjzg1nUSr5G57httHjHLpQda1R06GTHtuCi+z2aDQDUpr7uzmckPSNJHV0950l6sK+7c7jU5y1FvAUAAGqbEfe+kq+UsRPxEQAAmA9/XIq42nUG3Em+MlfylTJ2ypUWKUn5oBm27lAikZe67fqUx7akD2Z57duzbD8k6fx854DaUNJ2nc3OsZdJvsjAKZI980vJCB6Sv+lZ7yYEALUvIOktkm50P9HR1XOZpOf7ujt/W6Rzed4mFAAAVBtnks+w7Qxby6rYsRPxEQAAmDNfPH1NvkDc83adqYoaO+VKi+RdPmiGrVK1rQKyKmW7zsEmwzFeNOLNp962pUj/Zse24KIHZZS5DwsALDCfUfaLScskfUDSS4p0LuItAABQEMN2fl813P07y6/YsRPxEQAAmLNAXJr0udfk87xdZ6qixk5Zk3xm2JouH7RC5nmSHjTDVsnbVgH58sXclXwzX3SeWjc0r2MfbHOOV/RLd7b/TjKMjPuXSnx8jeITq1O3KNj+QFnnAAAL0EmSrsny3J8kfaJYJyLeAgAAhTJsZ81eQyTi0UymFTV2Ij4CAABzceeiuyVJHTFp0lXJ17e6X3p4ZuxxJV9RY6d8uzlMlQ+msULmZcmgCygrX8S1Jl9KJd+9Gw/r3o2H53zsoUZpJGVp7/qo9D+tt+jaVbfM+ZhzEek/0zH2Nz8tX3CwrHMAgAUoKmlJlueWlvC8xFsAAGBWRtx582nrxKRHM5lWytiJ+AgAAOTl2lXJ6/dxn2K+1LZ/cf3RPODY1+NKvqLGTvkm+T4j6agszy2T9NlCTwzMV3olXxEPbhjat9i5aeWRIh4/D3Y8qMjgaY5twUX3l3cSALAw3S3p7zq6eupSNybHfyvpdyU6L/EWAACYnauSz2d7e5VKpY2dihYfWSHzAitkPmWFzO1WyOzK8HzICpn3WiFzwgqZHy3ktQAAoHLYrgaWhhGV7Vrqy+NKvqLGTvmmRcrWtgrIV9qafCn/mpcOJD4fh9rnfkfjvsWGXrRv5tN+Sv86RZYb2t64c87HLER06GQp3jA9NvxDCrSGy3JuAFjgrlEi4Nre0dXzXUl7Ja2S9DZJ7ZL+X4nOS7wFAABm5W7XGS/vqhKZlDJ2Kkp8ZIVMv6SvSXq1pF2S7rdC5u1m2HoyZbfDkq6W9MY5vBYAAHjsuLF1kqS4vd+x3aeIFg3WSRqb2ebtPVJFjZ3yreTzqm0VkFVaki8lG//6e1bp9fesmtfxX3BV8r07+I/6St/H5nXMQkT6z3KMA+0PyTBiWfYGABRLX3fno5LOknSPpL+S9Pnk33dL2tzX3fl4iU5NvAUAAGZnO7N6A031WXYsjxLHTsWKjzZL2m6GrWfNsDUp6VZJF6fuYIat/WbYul+Se5HDWV8LAAC895W+j+krfR9TzHDWtjVEbL3+3tWObT5Jsr0p5yt27JRvJd/dkv7OCpk/TgY0kiQrZJa6bRWQlZGjkq8Y9i02JHnzQY9PLFNs9FjHtuCiBzyZCwAsRH3dnU9JenuZT0u8BQAAZudu1ynP23WWMnYqVny0RlJqW55dks4uw2sBAECZxRV0jAN2NLHdcLbp9LJlZzFjp3zTItPlg1bILGfbKiArXzTqGEf8WXaco0SSzxuRgTMdY39jn/z1B7LsDQCoEcRbAABgVu52nYZHd6GXSbHio0xf8PN94/J+rWEYl0u6XJICgYB6e3vzPEVlGB4erro5VxPe39LhvS2tcr+/W1u2lu1clWC5f3lV/czVMVdnl4OAnSwW8vmk2MzNUVc0fUBX6upyTqwk8krymWHrUStkniXpU0qUDS6VdEjSryV92gxbT5dshkAW7nadk0Wv5Cvu8fJl2z5F+k93bAsuut+byQDAAtXR1fMWSX8haa2kBvfzfd2dm4t9TuItAACQj7Qkn0cdaFKVKnYqYny0S9K6lPFaSXuK/VrbtrdJ2iZJzc3N9pYtW/I8RWXo7e1Vtc25mvD+lg7vbWmV+/296qarynauSrC1ZauuG77O62nM6kpdKUkVPdc36OuSpEnDWQ3kT1byRY246lK23zD0jXJNLU0xY6e80yJm2PKibRWQmW3L70ryRYuc5OtvlsaDUoO7G3+JRYdDsmNtMxt84wq0PVreSQDAAtbR1fMpSf8k6RFJT0qazPmCIiLeAgAAs3KtyefzOMlX6tipSPHR/ZI2WCFzvaTdki6V9I4yvBYAAJRZ1Odq1xlP5BHirtp8n0cdz4sdOxU5LQKUh9/1AYz6JNsocntNw9DBNmntoeIedjaRfmerzmDbIzJ8Zc40AsDC9v8kdfd1d/6j1xMBAABwM+Ru1+n5mnwVHzuZYStqhcwPSfq5JL+kb5lh6wkrZF6RfP56K2SulPSApDZJcStk/o2kE82wNZjptZ78IAAAYFaTPmfaa3pNPmcI5eWafEWNnfJO8lkhM2f5oBm2it62CsimzrkcnyIlSlcfbjW09lD5Pu3xSKtiwyc4ttGqEwDKrlWJFlBlR7wFAABmVWGVfCpx7FSs+MgMW3dIusO17fqUx/uS58jrtQAAoDJN+J2VfH67sir5VOTYKa/UiBUyPyWP2lYBmQScnToVcbbZ1U/O2VuU8xxpmXk88tt/1Q/O8WXfuQgiA6crcWNggq9+n3wNu0p6TgBAmlslXaAyJ/qItwAAQF5ca/IdNTDs0USmlSx2Ij4CAAD5uqrjc2oal871tTu2v7B0WD/ZsFfnulby9bCSr6ixU771T/9PUrcZtiq29QIWltkq+Q61FyfuP9w68zg+sEOTgz5JpUn02bYUGXC16lx0v4rdhRQAMKtfS/p8R1fPMkm/lNTv3qGvu7MUd3ITbwEAgFkZriRffTSaZc+yKWXsRHwEAADysr1xpxZHbU34T3dsn6yf0KH2yUpq11nU2CnfJJ9nbauATALuJJ8/837zdbjFkFJanywZLt0nPza2Xvbk8pQtUQXa/lSy8wEAsvpu8u8OSe/O8Lyt1LLr4iHeAgAAs3O16/R7vyZfKWMn4iMAAJA3f1yKuNp1GkZyTb7KaddZ1Ngp3ySfJ22rgGzqXO06J13/kl/y2BJJ0r0bD8/rPEdSKvnqT/1Lnd1maJv+d17HzCbS76ziC7Q+KV9gtCTnAgDktN6j8xJvAQCAWbkr+Y401Xs0k2mljJ2IjwAAQF6u3vsONU7Y6vPvcGxffdivEw4uUcy337Hdw0q+osZO+Sb5fi3p81bIzFo+mFyEGCiLoKuSL+r6l3zCzkR2br5JvkQlX0Jdx8u1WpJKkOSzY/WKDm50bAsuur/o5wEAzK6vu/N5j05NvAUAAGbnquQbbQhm2bE8Shw7ER8BAIC8XNh/riRpm++7ju3LB3064Uir4u4kn0eVfMWOnfJN8nnVtgrIqD7iHE/k+y+5QKmVfKUUGTxFsuumx0agX/7m7eU5OQDAoaOr58TZ9unr7nyyBKcm3gIAAHlwVvIZHrfrLHHsRHwEAAAKMulq1+m3E20B09p1elTJV+zYKd/UiFdtq4CM6qLOT+BE0Miy5/z0N0txOb9C+WO2Yv7ins/dqjO46EEZhnf1wgCwwD2u1AVZMyvFxSTiLQAAMDtXu07frGFLyZUydiI+AgAABXEn+QLxLGvyeRdCFTV2yivJZ4Ytr9pWARnVuSr5IiWq5Iv5DQ00S4tHZrYtHpYOthfxHONHKT5+tGNbsP2B4p0AAFCo8zJsWyLpNck/f12KkxJvAQCAvLiSfIb3Sb6SxU7ERwAAoFDj7iSfnUzyOUMoz9p1qsixU16pEStkzlo+aIatUrStAjJKa9dZwiUIjrQ6k3xLhoqb5IsMOKv4/E3PyFd3pHgnAAAUpK+78/+yPPXDjq6ef5X0Nkk/LfZ5ibcAAEA+DDlvQzdsb5N8pYydiI8AAEChJvx1jnHQrqxKvmLHTvnWP3nVtgrIqC7qHE+WqJJPkg63GDo25Z//0iFbUnHaddq2X9GB0xzbgouo4gOACvZbST8o0bGJtwAAwKzsyqvky2W+sRPxEQAAKMhYoN4xDsYTFUMVVMmXS8GxU76pEU/aVgHZzFbJd7BtomjnOpCs2ov1J7qErCzihz86ZMqOtcxs8I0p0PpE8U4AACi2Tkn9JTo28RYAAJiVIecVqsbJSY9mkpf5xk7ERwAAIC/PNOxQ07itcVcl32jjqA4GJhR/wbm/h2vy5VJw7JTvmnxZywetkFmytlVANrNV8v303H1FO9fupYYkW6O9n5EkrT65OFV8khTpP8sxDrb/SYYvmmVvAEA5dHT1fC/D5jpJIUkbJP1jKc5LvAUAAPJiO7+Tdhwa8GgiyfOXMHYiPgIAAPm6en23Nj8V13hgq2P7HzfuU6Bpn16y3bm/V5V8xY6ditHksJRtq4CM6iLONPtkCdfk27PUOV5zqDgp/nikXbGRDY5ttOoEgIqwQultocYl/U7SR/q6O+8o/5SItwAAQJKrXafP9rzXlFexE/ERAABwCMTS23UaviztOr2r5Ctq7FSMJF8p21YBGaVX8hWvus4tUck3Y/VhSbYtGfM7Z2TgDCmlzYqvfrf8DXvmdUwAwNx0dPW8XNJDfd2dw33dnVu8nk8GxFsAACDBVcnns8t/hapCYifiIwAA4OCPKa1dp+FLLO0Vd13OL2eSr5SxU15JPitketK2CshmtjX5LrvjGEnSjRc9P+9zHWmRxuqkFRdtS2z40eVaNCL1t+R+XS62bSjSf4ZjW3DR/fOYJQBgnn4r6SWS/tjR1fOspDf1dXc+Us4JEG8BAIB82K41+Z5etVh6puzTKEvsRHwEAADydaf1dSkgvT6wy7H9bb9doZZYi+K+Pzu2++JlvVGqZLFTvpV8OcsHzbDlRdsqLGCzrclXVIahPUsSH4Ipaw7Z6m+ZeyVfbPRY2ZGUPqBGRMH2sl5LBgA4DUlanHzcocTFo3Ij3gIAALMyXO06DQ8q+VS+2In4CAAAFMRdyVcXT7brNAylhhVlbtdZstgpa2rECpkvl/SQGbaGzbC1pVgnBIphtkq+YtuzxNCpKePVh6Qnjpn78SL9ZzrGgdYnZPjH5n5AAMB8/V7SDR1dPfclx5/r6Oo5nGVfu6+785JinJR4CwAAFMqWq11nWg6sLEoWOxEfAQCAubJlazzgzJ8F7ETFkLtdp7+8yxqXLHby5Xjut5JOlCQrZD5rhcxT8j0oUGplreSTtMe1Lt+aQ3P/EmXHGhUdOtmxjVadAOC590r6kaR2JW7rWixpeZY/KzIfYk6ItwAAQEHSKvlU3itUSaWMnYiPAADAnExIso2ZWMlvR6ZviIq7smG+8oZQJYudcqVGKqFtFZBRnauSb7LElXy7lsnRIGT9vrkn+SIDp0j2zISN4CH5m56dx+wAAPPV1925T9JVktTR1ROXtLWvu/OPZTg18RYAACiIu5LPi3adJY6diI8AAMCcjLk6HATtienH7kq+crbrLGXslCvJ93tJN1ghc7p80AqZWcsHzbBVlLZVQD7qos5P4ERw7uvj5WP7KkPaMzM+dl9iYc64r/DzRgacrTqD7Q/KMDxprwIAyKCvuzNXp4NiI94CAACFsf2OoUftOqeVIHYiPgIAAHPiXhArYE9OP06r5PMohCp27JQryfdeSddICmmmfNCfY3+gbOrL3K7zUJscSb76qLT2oLSjwKYjsfFVio+vTdkSV3DRg8WYIgCgOhFvAQCAAnlfyVdixEcAAGBO3JV8jiSfu5LPk47nxZc1NWKGrenyQStkxiVtNcNWOdpWAbNyt+uccLXr/P3Jh4p7QsNQePd31LF/5pfEcXts7VhRWCVfpP8sx9jf/Ix8wYGiTBEAUH2ItwAAQKFsOW/+Xnu4tr5TEh8BAIC5uHblzTrqmUVS68umt/k1OZ0r6HTV2nhVyVdsedU/mWGrnG2rgFnVzVLJ9/TRw0U/5+8a79aa52fS+8fttfWbU/N/vR0PKDLgfEFw0QPFmRwAoOoRbwEAgHwYtvNm0xXDIx7NpPSIjwAAQL7uXHyPXjl+rCvJNzGdK7jwIef+tVLJR7CEqlTvquSbDGber5j+vMo5Pm5PYan+6LApxZumx4Z/RIGWJ4sxNQAAAADAAuGu5PPVXrtOAACAOYnZdY6xXznaddZICFXilcyA0pitku/4HS2SilvRt775ZQoeE1fk+d9JklYfkoy4LduXX8vOyMDpjnGg7WEZvljR5gcAC1VHV88Fkr6sxFotN/R1d3Zn2GeLpP+UFJR0sK+78xXlnCMAAEDRuCr5DjfXF/RyYicAAFCLLjxyjhoaVzu2+Y3J6VxB3OdscZ5vJV+lx04k+VB9bDu9ks/1L/mljy+VVNwk3wcOv1M6TdNJvrqYtGJAemHx7K89MDSh2PDxjm3B9gez7A0AyFdHV49f0tckvVrSLkn3d3T13N7X3flkyj6LJH1d0gV93Z07Orp6VuRx3NWSXidpraQG19N2X3fnPxTpRwAAACiQs5Jv95LWvF9J7AQAAGrV1fveqR+1Tkoan97mMyancwVxw5Xky6OSrxpiJ5J8qDr+uPMDGPVJMX9+1XTFtuagrRcWz37uHz+8W4lEf4Kvfp98DXtKODMAWDA2S9re1935rCR1dPXcKuliSan9kN8h6Qd93Z07JKmvu3N/rgN2dPW8SdL/KvGLe7+U0tshwZbEhSoAAOAJ21XJZ6igXlPETgAAoGaNu+Iiw0hp1+lavC7Pdp0VHzuR5EPV8WI9vmzWHJIe2jD7ft9/aLdjHGx/UIY3eUkAqDVrJO1MGe+SdLZrn+MlBTu6enoltUr6cl9357dzHPOzkn4h6bK+7s7DRZwrAABAETivUBWY5CN2AgAANWvMNfYZE9OP09bky69dZ8XHTnkn+ayQmbN80Axb3JWFsphtPb5yWnNo9i9TT+4ZlLV3MGVLXIG2h0s2JwCoMQHDMB5IGW+zbXtbyjjTLRPuX84BSWdIOl9So6R7O7p6/tDX3fl0lnOuk3SVFxepiLcAAMBsbHeSz3Zcoaq52In4CAAA5GvMHdb4Uir53Em+xK5VHzvllR6xQiatF1Ax3JV8E55W8s2e5PvBQ7scY3/zM/IFh0o1JQCoNVHbts/M8fwuJYKjKWslufsh71Ji0eMRSSMdXT13STpFUrZg6/eSTpD0q7lNeW6ItwAAQH6c15p8zutMNRU7ER8BAIBCuJN8vlztOhP3SVV97JRvDdR0+aAZtmi9AE9VViWfJNtWtt6btu3Tjx52fuaD7Q+VYWYAsGDcL2lDR1fPekm7JV2qRC/0VD+W9NWOrp6ApDol2ir8R45jfkTSzR1dPcOSfimp371DX3fn6PynnoZ4CwAAzM52V/IV1K6z2mIn4iMAAJA3d7tO+XK068wvhKr42Mk3+y6SEpnKawmoUAnq3JV8ZU7yjadUDraMS0sHs+8bG96gg8Mzv0jkG1eg9YnSTQ4AFpi+7s6opA9J+rkkS9L3+ro7n+jo6rmio6vniuQ+lqSfSXpU0h8l3dDX3fl4jsM+KmmjpP9Wou/6UIY/pUC8BQAAZpXWrrOANfmqMHYiPgIAAHkbd8dF/plkQlolXx4hVDXETvmmRzxpWwVkklbJl6Fd540XPV/0815oXilJ+tc/SsenFOedY9m6/cWZK/kiA6c7xsG2R2X4ohn39cLLHovrggfj2rnc0P+80qeRxsw/BwBUsr7uzjsk3eHadr1r/AVJX8jzkO9Ven/1ciDeAgAAs3In+V6yfVeWPTOrstiJ+AgAAOTlQvNKrbn3MmlRaGajMTmdK3jnb5z7++LKS6XHTvkm+T4i6WYrZGYtHzTDVinaVgFp6iPOf/+TgfImpn5v+nT8npnfAK94LK7bzzbSWnbasTpFh090bAtUUKvONQdtbb0jrkBc2rDX1pGWuL77Cr/X0wIAz/V1d97o0amJtwAAQB5ca/LZeV6hKpESx07ERwAAIG8RX51jbPtzrMnnxe3dKn7slG+S79Hk3/+t7BlGsgMoi3pXu85MlXyldPdJhv7yt1Ig+T1q3UFp/T7puVXO/aLDJ0r2zOSM4BH5G/vKN9FZXHpXfPpnkKTO+2199xXezQcAKk1HV89qSS+RtETSYUn39nV3uhdXLibiLQAAMCt3JZ/f4yTflBLFTsRHAAAgb5O+esfYDuRYk8/jEKpYsVO+ST6v2lYBadztOjOtyfe6u1dKkn567r6inffa57okSVev79bDxxo6c/vMR+LEnbaeW+X8LREZONUxDrY94i7289QZzzg/0g2RLDsCwALT0dXjl/QVSe+X86JRrKOrZ5ukq/q6O0sRChJvAQCA2dk+RzHfY2uXyzyyw7PplDh2Ij4CAAB5ufa5Ln28qdWxzfZNTucK4sZux3M+25sQo9ixU15JPjNs3VjIJIFSqsujkm/ZYH36xnnaMH709GNrnTPJt+qw8xeCHW1SbGSDY1ug7ZGiz2muGg/1O6r4ptl2WttRAFiAPq3EBaV/lPRdSS9IOkrSJZL+WdIhSf9U7JMSbwEAgHzYrnadow353r9dMiWLnYiPAABAvjaMH61x35BS7w+KBya1bLBFkjTUZjie87CSr6ixU0GRoBUy08oHzbBVyrZVQBp3Jd+kB99n9i5xjlcecY4jQycrNQl/3IoW7avfW/qJ5WlpuC/j9tYxaaipvHMBgAr0Lkkf7+vu/GLKth2SvtDR1WNLulolSPJNId4CAAC5Odt1Gt4XupU8diI+AgAA+RhzxUXxQMqafO52nd6FUEWNnfJKj1ghM2v5oBUyt0m6ygxbldEEHjXP3VZyosxr8knS3iXO3wjuSr7o4KmO8RtOWa1v7ir1rPLXvP9wxu1LhkjyAYCkFZpZ/8Xt0eTzRUe8BQAA8uGu5POq1VSKksVOxEcAACBftmyNu7bF/SlJPud9Ul4m+YoaO/lm30WSs3ywQ1Jj8u9/TG7/VCEnBeajPuL89I3Xlb+95P5FUuq3iKWDUjA5r3ikTbHRDsf+bzhlddnmlo+6oZGM25cMef7lEAAqwdOSLs3y3KWSnirReYm3AADArOy0Sj7Pc1yljJ2IjwAAQF4m5bxmH4xFFEtZsyqtks+7EKqosVO+jQ7fJenjZthKKx+0QmbJ21YBqRomneNxDyr5IgFDB9ulFQOJsU/Syn5p53IpOniKUvPnm9a2q2NZc/knmUPd0GjG7UuGyjwRAKhM/yrp1o6unqMl/X9K9EZfIemtks5T9kBsvoi3AADArNKSfN5X8pUydiI+AgAAeXG36myITSqa0geggir5iho75VvJ50nbKiCTtCRfnTfz2LfYmfpfmWzZGRk8xbG90qr4JKlumEo+AMimr7vze5IukNQs6cuSvi/pWklNki7o6+68rUSnJt4CAAB5cLXr9HhNvhLHTsRHAAAgL2OucWN0UrGUDFilVPIVO3bKt5JvqnzwFxmeK2XbKiCNe02+TEm+p9YVvyTtzkV3O8Z7l0ib+mbGq45I8cmlio+vTdkrrtdXWJLPsG3VDbt/5SUsGS7zZACgQvV1d/5C0i86unp8kpZJOtjX3Vnq8I94CwAAzMpdybf6yKBHM5lRwtiJ+AgAAOTlFy0PSsMnTI/ro5Ma883kCtomnPt7WMlX1Ngp3yTfv0q61QqZ5W5bBaTJp13nvRsPF/281666xTHeu9iQUu6YXHXYTqvi8zc9p6PaGoo+l/loHZV88cy/L2jXCQBOyQBrf5lOR7wFAABm5U7ynbj3oEczSVeC2In4CAAA5OXWxb90JPkaYxPqN4zpXMGrH3Lu72WSb0oxYqe8knxm2PqeFTL7lVjw+MuSgpIikh6UdIEZtn45n0kAhWiYdH76vGrXuXeJc7zmoK3o4EbHtkDbI2WcUX4W56jWo10ngIWqo6vn3yRd29fduSv5OBe7r7vzH4o9B+ItAACQD3eSz+fBmnzlip2IjwAAQL58UWeioCHmbAnoZbvOUsZO+VbyyQxbv5D0CytkTpcPmmHLo66lWMjS23UaafssHUh8oA+1T6Y9N1fHja2TJG1v3ClJ2rnceV7/6DLFJ1albIkr0PpE0c5fLIuGs38BpJIPwAL2Vkk3S9ol6W1SzsVtbElFT/JJxFsAAGB2tmtNvuH6gJaOl30aZYudiI8AAEA+Vo2v0UDKuD6eSCRM5QriPmfAVOZKvpLFTnkn+aYkA6lyta0C0qS168xQyff6exLJthsver5o5/1K38ckSReaV0qSDrZJY3VSY3I+Dy3b5Njf3/SsfIGRop2/WBbnmFLzuCTbloz0xCkA1LK+7s71KY87PJyKJOItAACQnbuS74FjV+mYPxV/yYpcvIidiI8AAEAubzvyFv2zxqbHDfHEhfupXMFza59z7F/OSr5Sxk5Zk3xWyPw3SdeaYWtX8nEuthm28sosWiHzAiVaLPgl3WCGrW7X80by+YskjUq6zAxbD+V6rRUyT5V0vaQGSVFJV5ph64/5zAfVJ581+crCMLRrqbRhb2J49xpnki/Q9pgHk5pdrnadPknBqBTx6j0FgArQ0dXzLkk9fd2dhzI8t0TS6/q6O79djHOVKt4CAAC1y13J55O3RW3Fjp2IjwAAwFyMu4rj6uNRxzitXadHK1cVO3bKVclX9PJBK2T6JX1N0quTx73fCpm3m2HryZTdLpS0IfnnbEnXSTp7ltf+m6RPm2HrTitkXpQcb5ltPqhO6e06vZmHJO1abmjDXlt7m5Zo+6K1Kc9UZqtOKXe7Tkmqj5DkA7Dg/bekl0hKC7YkrU8+X5QknyqkTSgAAKgmzko+w4M1+VyKHTsRHwEAgIKNpSX5nNVCcWcIVdZKPpeixk5Zk3xm2Fqf8rgj//nltFnSdjNsPStJVsi8VdLFklKTfBdL+rYZtmxJf7BC5iIrZK6S1JHjtbaktuTr2yXtKdJ8UWlsO62Sb8LDhNSO5YYkW3evdrfq7JMvkKNkzkO5KvkkqT4qVebMAaBscvUsXippsFgnKlG8BQAAapi7XaeRMwdWFkWNnYiPAADAXIy5xvV2zDFOS/J5F0IVNXbKa00+K2S+S1KPGbbSMotWyFwi6XVm2Mons7hG0s6U8S4lqvVm22fNLK/9G0k/t0LmF5W4pe2lecwFVSgYdX74Jv1SzO/d+nG7liX+TmvV2VqZrTr9MVtHH8j926sukvNpAKhJHV09Fytx89CUT3R09Rxw7dYg6WWS7i/FHIoYbwEAgBqW1q7TLv9t6OWKnYiPAABAvtyVfA1x54VuL9t1ljJ2yivJp+KVD2bKxrjfymz75HrtVkkfNsPW962Q+TZJ/yXpVWknN4zLJV0uSYFAQL29vXlMubSGh4crYh7ZbG3Z6vUUHIIjY5JumNlQ36CtLe9P229Md0gqzfxTj1l/zLBeaPyRnl58tGOf9648Q611p2Z9nVc6fn2fVh92Llc52dSgutHx6fFfBt+q4Zbl5Z5aXirhs1Lpn9lKxns3N7xvZbNC0saU8YskrXTtMynpF5L+tURzKGebUAAAUKUqpJKvXLET8REAAMiLO8lXJ9eafN626yxZ7JRvkq9Y5YO7JK1LGa9VemvNbPvU5XjtuyX9dfLxbXJkgWbYtr1N0jZJam5utrds2ZLntEunt7dXlTCPbK666Sqvp+CwvN/WuSnj/uC4rhu+Lm2/y3SMJGV8bq7eoK+nH9Nn6w3rz3Hs1+J/Tt+Z/EbiIynpSl1Z9LnMhT9m64Z7nCXK94YMLRka1wmjM9tuH7hNT7V5Vx2Zy2Nv9r5CstI/s5WM925ueN/Ko6+785uSvilJHV09v5V0ZV93p1XmaZStTSgAAKhOti3ZhvdJvjLGTsRHAAAgL+Oucb07yedhJV8pY6esST4rZKaVD1ohc77lg/dL2mCFzPWSdku6VNI7XPvcLulDyTX3zpY0YIatvclzZ3vtHkmvkNQr6ZWSnslzPqgy7vX4xrOsx/eTc/YW/dxXdXwufaNhqHfdKY5N5uBjChf97PO3ZEhqnpgZj9ZJN7zWp7/+cVypBbX1kWyFswCwMPR1d55XrnOVKN4CAAA1y/ldzbDjOvfpnVn2LY9ix07ERwAAYC4e8VlS/Ljpcb2dSPJN5QqOdkUTRvk7nksqfuyUq5Kv6OWDZtiKWiHzQ5J+Lskv6Vtm2HrCCplXJJ+/XtIdki6StF3SqKT35Hpt8tDvl/RlK2QGlEjYXp7PfFB90pJ8dZn3O9Q+mfmJedjemP7FKR5p1+7GYxzbXvPsowqfWfTTz1uz61aGA+3SUJOhCVeitN55gwMALDgdXT3/Nts+fd2df1+k01VCm1AAAFA1nFV8PttW+1jxv/8WogSxE/ERAAAo2Iircq9Oia52U7mCta7m336PknzFjp2yJvnMsDVdPmiFzN9KutIMW/MuHzTD1h1ScsG0mW3Xpzy2JX0w39cmt98t6Yz5zg2VryHirKEdr/O24iw6dLJjHDrcp7P7+hWM+BUJVlY1XMu4870bbkz8Pen6LVDnXI8UABait2bYtlhSm6QBSUckFSXJV6p4CwAA1Cjb+T3TZ3t0dcqpqLET8REAAJiLuO2sCKqkdp0uRY2d8lqTzwxbZWtbBeTiruRzV6FNecljSyRJ9248XLRzX7030R322lW3TG+LDp3k2OfcPY8pGJNO3GnrkWMrK8nnruQbaUjML62SjyQfgAWur7tzfabtHV09Zyuxtu8VpTgv8RYAAJiV7XNv0GNrl2vjLnc3y/IpZexEfAQAAPLVZq90LNYbTFbyTeUKBtsOOvb32d5k+YodO+WV5LNC5qzlg2bYKlbbKiCrfNt1nrCzVVJxk3wX9p8raSbJZ0ebFBt1tup86Z7HJEmn/tnWI8cW7dRF0TLmHA83JP4myQcA+enr7ryvo6vnC5K+qhJ0ECDeAgAAs3Ml+Qxp59I2T5N82RQjdipmfGSFzAskfVmJJWBuMMNWt+t5I/n8RUosH3OZGbYeSj73YUnvU2JB+8ckvccMW65baQEAgJcMtUia6XJQn1x0bypXcN/Jzn6dvopoiDBjrrFTXkk+lbFtFZBLgysBlS3JVw7RkROU+G6Q0DGwV6tGE0nF0/5s66ZXezSxLFrSKvkSf0+S5AOAQhySdEKJjk28BQAAcrPT1+SrcPONnYoSH1kh0y/pa5JeLWmXpPutkHm7GbaeTNntQkkbkn/OlnSdpLOtkLlG0tWSTjTD1pgVMr8n6VJJN871hwIAAMU3JmdcVGc4s3hx171SHrbrzKXg2Cnfdp0ZywetkFnStlWAW1olX5Z2neUQHTId480vPDH9ePUR6ajDtl5YUjktO9PX5EvMbTxoSCm/AOsjlfnbDQDKpaOrpynD5jpJpqR/lvREhufnjXgLAADMxpbzO6Yh729BL2XsVMT4aLOk7WbYejb5+lslXSwpNcl3saRvm2HLlvQHK2QuskLmquRzAUmNVsiMSGqStKfgHwYAAJTUeFqSL+YYp63J51EYVezYyd3MvSBm2LpP0lT5IFByDZPOD6pXlXx23J+s5Juxwn7SMT5ze2Uly9xr8g1nqeSrc65HCgAL0bCkIdefQ5LukbRS0pXlnAzxFgAAmFaZlXxlj53mEB+tkbQzZbwruW3WfcywtVvSFyXtkLRX0oAZtn4xl3kDAIDSsG3JtVqVgr5ZknzehVFFjZ3ybdeZSynbVgEO6e06vamUi42+SIrXT4+NwKAOrN4tWTP7vOzxuHo2zyuPXlRZ1+Rz/RagXScA6L2S3KHeuBIXev7Y193pxW9K4i0AACBVYCWfvIudComPMl08cM854z5WyFysRJXfekn9km6zQuZfmmHrO2knMYzLJV0uSYFAQL29vXlOrzIMDw9X3ZyrCe9v6fDella539+tLVvLdq5KsNy/vKp+5kqd60TM0JdTxg3RCbUEmrW1ZavGdIck6S+a3yLpu9P7rDCWlXeSM4oaO+WV5LNCpidtqwC3SmnXGR060TEOtDype1dK7/rNzB0Ax74grTtQEXdVSkqv5Jtak2+CNfkAwKGvu/NGL85LvAUAAGbnvJHUSLs+VH6ljJ2KGB/tkrQuZbxW6S03s+3zKknPmWHrQHJOP5D0UklpST7btrcp0UZUzc3N9pYtW/KcXmXo7e1Vtc25mvD+lg7vbWmV+/296qarynauSrC1ZauuG77O62nM6spkcVmlzjUeWSSpa3rcMjmmUd+Erhu+TpfpGEnS98b/P52V8prD0YNlneOUYsdO+VbyDSs9sygl7nLaLemNxZoQkEtaki9Lu86DbRNFP/czDTskJUp/o8PO9fgCrZaOtBh67BhDp/TNfFRe/nhF3FUpKfuafO52nST5ACCho6vnBElnSVqlRGumB/q6O8MlPCXxFgAAyM3VrtMfj6tttPjff+eiRLFTseKj+yVtsELm+uTrLpX0Dtc+t0v6UHK9vrOVaMu51wqZOyS9OJlwHJN0vqQHCv1BAABA6dgx531BLZFRxf2JuGkqVxB3Nd3zsF2npOLFTvkm+XKWD5phi7QAyiK9XWfm/X567r6in/vq9d2SpPjYGtnR9pknjAn5m/4sSbrrZGeS76Tnvb+rckq2Sj53NWQdn2YAC1xHV0+bpG9KerMSt8sPS2qRFO/o6vmBpPf1dXcOluDUxFsAAGAWzo6STZMRnfvMLo/mklDi2Kko8ZEZtqJWyPyQpJ9L8kv6lhm2nrBC5hXJ56+XdIekiyRtlzQq6T3J5+6zQub/J+khSVFJf1KyWg8AAFQGO9boGLdExmQH/ZJmcgVrXIV7Po/qc4odO+WV5DPD1o2FTxUovmZXNdpoliRfKaW36nxGhi8qSXpsvfML19EHyjatWbW4knxTa/KlVfJFKycxCQAe+bqk10h6l6Qf9HV3jnd09TQoEXx9Nfn8Xxb7pMRbAABgNrarks9nV0T3mJLFTsWMj8ywdYeUXJRnZtv1KY9tSR/M8tpPSvpkseYCAACKy53ka42MKV7vjJvirtV3PazkK2rslG8lnyTJCplp5YNm2Cpl2yrAoX3EOR5szrQudmlFh9PX45vS3yz1N0mLRhPjumg5Z5adL26rKaWDi21Io1Nr8gWc7yHtOgFAF0v6cF935y1TG/q6O8cl3dzR1dMk6d9LeXLiLQAAkJ3z+5vProibNEseOxEfAQCAXNIq+SbHZAf8jm0V1K6zqLFTXkk+K2RmLR9MLjj8PjNslaJtFeDQNuocD2ZaglvSZXckFtO88aLni3buO62va4/iepuGU7bGFWhJ+V5hGOo7ytCpz1XEF61p7lad0YZ62UZMkjTBmnwA4DasxMWjTPZIGsny3LwQbwEAgFm5KvlGGwK645QX6aJH/uzRhCSVMHYiPgIAAHmJu9t1zqzJN5Ur6Hlpn2Mfr9p1qsixk2/2XSQ5ywebzLDVJqlJ0rslvTr5PFBS/pit1pRklW1IQ43Z9y+Fe+TMgPmb+mQEnJnH51eUc0b5aRlzjqON9dOP09p1kuQDgK9J+mhHV4/j/zLJu6k+qtLFPcRbAAAgN1eSz6iMSr5Sxk7ERwAAYFYZ1+Tzudp1Vk4lX1Fjp3zbdV4s6cNm2JouHzTD1rikm62QWfK2VYCUnqiKNDYo7itvP8y75TxfaqvOKX1HGUpfF9xb7kq+SGODEuuIS+OuJF8dST4AC1BHV8+/uTZtkLSzo6vnl5L2S1qhxIWkMUkPlGgaxFsAAGAWriSfR989yxg7ER8BAIBZZWrXGffXObalrclXxkq+UsZO+Sb5PGlbBaRqd7XqjDQ3Shoq2/lHZesRxRzbAq1W2n6JJF9laRl3fvHLWclXIesIAkCZvdU1jiT/vDhl29T/dN4s6e9KMAfiLQAAMAvDNfKsz1S5YifiIwAAMCs7Q7tOO+Dc5nElX8lip3yTfF+T9FErZP7GDFvT9VTJu6ZK2bYKmNY26vzUTbY0qZxJvgcUddTxGXUH5Ks7lLbf3iXScIPU4qqe88dsxfzeJADbXV97EpV8CZOu3wL1EUm2LRmVl6wEgFLp6+5c7/UcRLwFAABmYbvadfo8atdZxtiJ+AgAAMwqr3adHlbylTJ2yprks0JmxvJBK2SWs20VMC0tUdVc3gX5/uBu1dn8VMb94j5Dt53r03t+5fwtsbHP1sMv8iZxtvKI84vf+OK26ccxv6GoTwokp+uzpWBMiuR7CwAAYM6ItwAAQGEqo11nKREfAQCAQrmTfK2TY4r5Z0ny1UgYlesyfiW0rQKmtbnadU6WMcln2xmSfC2Zk3ySdOeZhl72hHRcSlORVYelh19Uqhnmtvqwczy6dJFjPBGUAhMz47oIST4AC0tHV89Fku7u6+4cTD7Oqa+7844inZp4CwAA5M92Xp3y2d606yxx7ER8BAAACpJeyTeqfr/fsc3Ldp2ljJ2yXsY3w1YltK0Cprnbdeaq5Pv9yeltNOcjPnGU9qfeIWlMyt/0XPYXGIbuO8Gn4/bOfOFaddi7WwPclXxjyxY5xhNBqTklyVcfkUbKWygJAF77qRIXjv6YfJyLLck/yz55Id4CAACFcV6dahmf0Mk793sxkZLFTsRHAACgYGlr8o3pcLKSbypX4GW7TpUwdqJWB1WjvYBKvqePHi7quaPDIcfY3/xnGb5olr0T9i12jlceKeqU8mfbWuWu5MuQ5EtVHyntlACgAq2XtDflMQAAQOVxVfI1RSI6+nD51qpPQewEAAAqgm1LdqzBsa1lckx2Msk3lSsIui7nl7ldZ8lip1xr8l0k6W4zbA0mH+dkhq1ita0CMnK364y0NJXt3LGRExzjQEt41tfsXeL88rXqiDeVfIuHpYaUpN1ofbIKMmWNQ3eSry53/hIAak5fd+fzktTR1VMv6S8l/bSvu/ORUp+XeAsAABTGWcnnt735nlnK2In4CAAAFCRer9TCt4bohIJ2THF3u04PK/lKGTvlquTzpG0VkE3biPPLS65KvuN3tEgqTkWfHatXbPQYx7ZA89Ozvs5dybd8QPLHbMX8RuYXlIi7gnDvYkmGcw6Trt8EDVTyAVig+ro7Jzq6eq6RdHeZTkm8BQAA8mc7k3wTAZ92LGn1qpqvVLET8REAAMib7W7VOTmW2J6s5JvKFTyzzhkv+T24V6oUsVOuJB+tF1BR3O06c63J99LHl0oqTpIvOrJBqd8ZfHUvyFc3e+/NyaChQ60zY58tHdUv7Vk67ykVZLVrLcB9i9OTjKP1hpSy5mDzmC2pvMlIAKgg90k6Q9L/leFcxFsAACBvtut72nBDUI+vW+FZki+p2LET8REAAMibHXOvx5dIJExV8hUzV1AkRY2dsib5zLD1vCRZIXO6fNAMWyVvWwVk427XOdnSKJWhpDY27GzV6W95Ku/XprXsPGxrz9IyV/K5knx7lkjLXPsMufKlrWOlnRMAVLi/l3RLR1fPpKQ7JL2g1DshJPV1d45memGhiLcAAEBBXJV8hrxp1+lS1NiJ+AgAABQiPcnnrORLFTO8qeBzKWrslP5Tuphha0LSNZIWFTRNoIiCEVvNEzPjmCFFGxqyv6BIbFuKjhzv2BYoJMnnatm55lAxZlWYtQedY3fiUZKGXUm+lvESTggAKt99kl4k6VpJz0galDTk+lNUxFsAACA/PtfI+6tUKlHsRHwEAADy4U7yteZI8sVnzYiVRVFjp1ztOt0nLVfbKiDNohHnuL9Fkq/0FXHxyRWyo+3T40ZJ/qa+vF+/a5lzjuc+EdftZxtpa+KV0rqDzi99O5cb2ujaZ6jR2a6zZawivigCgFfeK3lyxYx4CwAA5GY7v0sadhna28yulLET8REAAMgp25p8U+06U8UrY4WqosZO+Sb5/l7SLVbIzFo+aIatorStAjJZ7GqXe6S5POeNjWxwjE9VQI8bsbxf/8fjnb81OvZLJ+yWnlpblOnNqnHC1oqBmXHMkHZnWBPQXclHu04AC1lfd+eNHp2aeAsAAMyi8tp1ljh2Ij4CAAC5ZVmTz86U5KuASr5ix075/khlb1sFpFo87Pzi0t9SnpR7dNiZ5DtL6b8YcjnUnj7PV/2pfHdarj3gHO9dIkUD6XNiTT4AmNHR1fNsR1fPKVmeO7mjq+fZEp2aeAsAAORkx4OOccCOejSTGSWOnYiPAABATnasyTGeWpMvnqldZwVU8hU7dsq3ks+rtlWAJGmRu5KvJf9/vHNlx/2KjR7r2HamAvrveR73pB3l+ygdnaFVZyZpa/KR5AOwsHVIqs/yXJOkUtVjE28BAP5/9u47PrKzvPv/50xT76vd1VZtszW219jGvYBNaGuZmFBCDSUhfrCDSYEkmyeF5EkIIuT5JUDA4PAQU0xophhkx5iy2Ma9rOuM7S3aqt3Vqtep5/fHjKQ5Z2akkXSOZiR936+XX9Z95pRbsyvtNec613WLzCwZsAz9yeIn+XA3dlJ8JCIiIjOyr8k32a7T9HrA1pSvFJJ8OBw7FZQnCYZDt83lpCJOaxi1V/LBqhn2v+3aQwu+ZmJ8M5jTH6AM3yA3bd/NQn8PrBqCulGTwSr3f6NsOmV93w7nSfKl1uSbVqM1+URkhWnd3VkL1GdsWtu6u3OTbbdy4J3AMTfmoHhLREREZmOa1iRf24kerg3tX/R5LFbspPhIREREZpO1Jl+6XWfS64WENVdQrHadbsZOBSX5Qm3BA8DvBMOhp3O8dg5wZzAc2pp9pIgzstbkqzZmTPI5ITG63TL2Vu3DcCgvt7Xb5Knt7if5Np62jo80597P3q5TlXwisgL9KfAJUk+Km8AP8+xnAB9zYwKKt0RERGRWtnadZYlokSayOLGT4iMRERGZTVYlX7pdp+kpqXadrsVOhXY8bKU4batEAGiwddnvr3b/mvFR63p8vqqXHTv31hPw1PbZ9yuIaZIv+7ixx9auc1WB7TonHJmZiMhS8i3gcVLB1J3Ax4EXbftEgRe7OtoPuzSHVhyIt0JtwTcCnwW8wFeC4VCH7fX3AH+ZHo4AN+a6cSYiIiKlx7S16ywvXpJvsWKnVnQ/SkRERGZgT/LVZLbrtClWJR8uxk55k3yhtmBW+WCoLbiobatEJtXb23XO0uryugfWAvDTK0/M63pmvJLkxHrLto7eXdT1vZGPbunIc1Thtp5YeDvMuhGTj/8gwfpe+MnFHn54hfU3VO2oSd3Y9DjqgxMNuc81HoC4B3zJ1Lg8Bv64ScxXGk2KRUTc1tXR/jLwMkDr7s5rgCe6OtpHZj5q4ZyOt0JtQS/wBeB1wFHgsVBb8M5gOPRCxm4HgVcHw6H+UFtwF3ArcMn8vwsRERFZNLYk35GmKh7wbODKl48u6jTcjJ10P0pERETmIruSb4y4h6nCmMxcQbEq+dyMnWaq5Ct62yqRSdntOmfef9VQvgf9ChMf2wZMJ808Zd1cGDlzQefMtK174Um+9/0iyZnpjzPvui/J01sNDrRM/5baZKviO7oKTE+e32KGwUg51GckBavHob9mwdMUEVmKQkAzqSo3Wnd3GsAfAmcBv+jqaP+Jg9dyOt66GNgXDIcOAITagt8GrgemknzBcOjBjP0fRk/Ai4iILBmmaW3XmfDBUOXCPv86wOnYSfejREREpHBZa/KNE/dOjzNzBUWs5MvkaOw0U5Kv4PLBYDjkVtsqEbwJa0VaEhiscveaidFt1jlUvQwLTPJFvRBIpL5uHIHmAZOe+vk9OuCPmVz1gjWJ95qnkxxomf7ttbHHeky+Vp2TRiqsSb4aJflEZOW6DdgHfDQ9/gfgf6e3faR1d+eHujrab3PoWk7HW+uBIxnjo8xcpfcHwN35XjQM4wbgBgCfz8eePXsKmMLKMzIyovdmBnp/Zqb3Z2bL8f25sfpGx87V7G129HzLzULfn1J8b3/gaWZfxthnxoo2lwy34WzspPtRIiIiUhDTBDNRbtlWHR0nkucZqCKuyZfpNhyMnfIm+YLh0FT5YKgteA3wRDAccr1tlYhd3ah1PFQJCa+7P42JMeu63b6qfdC3sHPuWwdnZdx2PfuwyQsmjJfBcOXcvp9zu7IrAXd2mZb1+eyVfIebZ77GsG1dvppxk9RnKhGRFecCUi0sad3d6QFuBP53V0f7v7Tu7vwH4E9IBWQL5kK8lesXd87y8fT1/gC4Mt/JTNO8lfR7UVVVZV599dULmNrytWfPHvTe5Kf3Z2Z6f2a2HN+fm792s2PnurH6Rm4ZucWx8y03831/buImgJJ8b8eifwBMrx/vN+PFm8w0R2Mn3Y8SERGRgiXLgOnClwrAbyYYzVOxVyJJPkdjp5kq+TJZygdDbUFL+WAwHHKybZWIhb1V58AsrToXKhmvJhldnbElgbfi0ILP+/xmg7OOTN9nvakztQBexAf//mYPT+wovFb4opey79e29MP6Xji2KjXemJXkm/mcIxUGmfeBq8cLno6IyHJTB/Smv34l0Ajcnh7/EvfaQjkRbx0FNmaMNwDHsy7UFjwX+AqwKxgO9dpfFxERkdJkmtY1+XzJkkjyuRk76X6UiIiI5GXaWnXWpJ99Tnhz7V0y7TodjZ0K/ZZuI9UTfdI/AF8E3gj8MNQW/MBcLioyF/aKtJ66xa3i85Qfw/BGFnze5zflnndZHN5xX7LwE5kmF+zLvabfZPLPME02nra+dmSWSr4RWyWfknwisoIdJXXjCKAdCHd1tKdXQaUOmHDpurex8HjrMWBHqC24JdQWDADvJNXmakqoLbgJ+AHwe8Fw6CUH5i0iIiKLJWlN8vlLo12nm7HTbeh+lIiIiORhJnIn+eL5knylUcnnaOxUaJLvAlIZREJtwanywWA41AZ8klT5oIgrtnVbE1oH1rqc5Bu1t+o84Mh5X15vEM/zE9d6CqrGcyfu7KomrGvnZbropVSycMNpqIhObx8tg75Z1tfLbtdZ0HRERJajrwL/0rq783vAX5BuoZB2Kaknyt2w4HgrGA7FgY8A96Tn+d1gOPR8qC344VBb8MPp3f4OaAK+GGoL7g21BR93/DsRERERV5hJv2VcIpV8bsZOuh8lIiIieeVN8uW5D58ojUo+R2OnQtt1FqttlUiOJN/sx7y4cXje17NX8nkrU0m+u+sfmPc5AWI+g/AGg3MO507mbT9u8vS2/AnM8/YnaR6EY035r7GjGxqGTS4LWSsDX15nTK3Vl89YmbVdZ3mssKSjiMhy09XR/qnW3Z3HgIuAm0kFX5MaSbW5dIMj8VYwHLoLuMu27UsZX38I+NBCJysiIiJFYKvk29zXT12suMvVuRw76X6UiIiI5GUmqizjqtFU2JDZrjMzV1AKlXxOx06FJvkmywfvJ10+GAyHFqNtlaxwvrjJ5lPWbftbZv9JfGhn37yul3s9vi4APtfyrXmdM9M9r8yf5DvjmMnT23Ift+uxJB/8eWEtPf/xGwnKo9ZtD541+3sWs/028JfEA6EiIsXR1dH+deDrObZ/OMfuTlG8JSIiIjOyr8l33tFuqmPFDxFcjJ0UH4mIiEheZrzaMq47lSqCi2Uk+TJzBSWyJp+jsVOhSb6vAv8Sagu+llRQ9VcZr7nZtkpWuM2nwJeR2+qphaEq99Lt9ladqfX4onn2nrtH2jz87XsNNvWYVEbgPXumv7m3/8Zk37okT223/qapnDALTvABrB60juMeeGzH7O9Z1NanOKAkn4isIK27Oyu7OtrHJr+ebf/JfR2meEtERETyMk3A1q6zLF6cNfkWMXZSfCQiIiJ52ZN89ZFU1V7En2vv4lXyuRk7FZS3DIZDnyJVNngi/f/PZbzsZtsqWeG2nrC16iygig+gaTBA02Bg9h1t7K06M9fj2z6+ke3jG+d8TrsXNxrce4GHR8/I/l7+6ntJvvupOP/+pTjbj6W+9zc+MXPbzPvONpgpBbh3q8Foxdwr+XyJWQ8REVlOhlt3d16c/noEGJ7lP8cp3hIREZEZmV5g+ulMbzLBWLmXwYq5f/Z1wKLEToqPREREZCZmosYybjRS2b2If/p+eGauoIiVfK7FToVW8hEMh3KWDwbDITfbVskKt+G0Lcm3prAk35t+0wLAbdcemtP1stfj2z/19ee7Ug8M7greNKdz5tPdCEMVUDue/dq6fvjonQk+9iEvux6fuYrvmS0Gx5oMfvf+JF5bPjBpwI8uK+w3V0yVfCKysv0+sD/j66IsTKp4S0RERPKyteqs8Hj5zRmpB1GvfXp/riPctGixk+IjERERySdpq+RrOfNaCHUSzajky8wVJA2DIt3ycS12ypvkC7UFK4Ph0Njk17OdaHJfESetHrCOTzS6d61krCZ7Pb7KuSUJ58QwuPtCD++4P3cSb+0A3P6vs5fT9dQZ3LfT4JfnpRJ9r3sq9fthPACff5OHlzYUlhjVmnwispJ1dbR/LePr2xbruoq3REREpFCmvVUnReo3hbuxk+IjERERKZS9XWdDOj6K5Ml8FauSz83YaaZKvuFQW/CyYDj0KKnywdkyi95ZXheZs9WD1r92J+tdXI9vbItl7Kk4iuFxbj2+XO64wiC8wcNr95pcEZpf8v50ber/g1UG//lGLz8732TrCZMnthtzWr9QST4RkaJQvCUiIiKFSdoq+YqY5HOZ4iMREREpiBm3tutsSq9QF/XnDhCKtSafm2ZK8pVE2ypZwUwzq5LvVJ17l0uMt1rGvsqD7l1skmHwfKvB863w3682+Z2HkvzW04X/qCUN6LP+HuPQGoNDBbY1zRS1J/m0Jp+IrCCtuzsPModYp6ujfevsexVE8ZaIiIgUxLS16ywv0jzA9dhJ8ZGIiIjMyjTBTGRX8iVIVfLlagdQrCSfm7FT3iRfMBz6WsbXtxV6QhGn1I1CWUY12VgZjFS4d73EWKtl7K3ocu9iOZxqMPjytV48yQTXPFvYz3tfNSS8zvxmitvO44/rc5SIrCh3YA223kkqHrwXOAWsBl4HjALfduqiirdERESkUPZ2neXFreRzLXZSfCQiIiIFSZaDOR0flQOVGAyTquTLleQzi9SuExdjp5kq+USKas2AdXyyHjDc+RBjJgIkI2st21xdj28Gt+7ycKrezLtWX6ZT9c5dN6uST+06RWQF6epo//jk1627O/83qafH27s62kcztlcDPwWGFn+GIiIisuIlS6eST7GTiIiIFJt9Pb7GjAegIv7ceYRiVfK5GTvlTfKF2oJzKh8MhkNOta0SAWD1gPWv36k6F9fjG98ETKfxPYGTGN5x164341y8BndcaXDHlR5e92SS1+5NcrTJ4KGgwV/cYU38/fIVzj16YF+TL6B2nSKycv0RcENmoAXQ1dE+0rq781+B/wT+yYkLKd4SERGRQpmluyafo7GT4iMREREpRDJhXceqMeP+fsRv3zt9TPEq+TI5GjvNVMlXlLZVIpPslXxzqVr7yRXdc7qWfT2+XFV8N7d+ak7ndMK9F3i494Lp3zyffhtcsN9kwg+P7/AQ2ujctWK2lUh9quQTkZWrDliT57W1QHWe1+ZD8ZaIiIgUxrTerfKefJ4rXjpSpMlYOB07KT4SERGRWdkr+Wp7XmL0uU7A2rUuM1dQrEo+G0djp5nW5JsqHwy1BafKB4Ph0GjGdrVeENesHrRV8tUX/hPYWxed07USY5stY29FdpJvX0XxPzw9scPDEzvcObcq+UREptwJfKZ1d+cQ8JOujvZI6+7OMuC3gU8DP3HqQoq3REREpFD2Sr7y8X7qxuf22dcljsZOio9ERESkEGbcWslXP3KS5OBhwFrJl5krKJEkn6OxU6HFiX8EfCYzoAIIhkMjwL+mXxdx1Lpea5LvZL071zFNT7pd5zRvZZc7Fyth9iSf1uQTkRXsRuA+4LvAWOvuzgFgDPgOcH/6dTco3hIREZH8bEm+skRJJPjA3dhJ8ZGIiIjkZK/ka4iMTH1d4u06HY2dZmrXmWkx21aJUDlhsv24dduR5sLT7Jc92wjAQzv7Zt03ObEWzLKpseEdwfD3Zu330e53A/C5lm8VPI+lJGpr16kkn4isVF0d7YPA77Tu7jwLuIhUrHMCeKyro/0FFy+teEtERETyMk1rkq+q6Uye3dAMwM6jPcWYEuB67KT4SERERHKyV/Ktag5SVr6ayN5vWtp1ZuYKEiWQ5HM6dio0yXcn8JlQW3AI+EkwHIqE2oKutK0SATj3oIk3o5Dv8CrorS08yXfmkdQPeCFJvuz1+Lowclxq18CVwPJN8mW161SST0RWuHRg5WZSz07xloiIiOSXtD6SXlW/iSNNtUBxk3yTXIqdFB+JiIhITsmE9Vmf1U1nEGjyE9n7TUslX2auoBSSfJOcip0KTfLdCNxGqnzQDLUFh4EawCAVcLnVtkpWqPP3W1t17t3mXrPcQtbjWwnitko+XxIM08TMlfEUERE3KN4SERGRvOxr8lUAZu5dlxPFRyIiIpKTvV1nI9P3sSP+3Pe07ffAl4OCknzBcGgQ+J1QWzCrfDAYDi3mE+6yEpgm5x2wflR5aquLSb5xW5JvBa7HB4BhEPVCIDG9yReHWJ7+xSIi4izFWyIiIjIj+5p8GEwUaSqLRfGRiIiI5GNv19nIdJleNE/mK15ClXxOKbSSD4B0AKUgSlzVNAwNGUtqT/ghvNGdJF8yVoMZr5/eYMTxlB3Pu/9yF/NZk3wBJflERBad4i0RERHJxTStH84qVkCSb5LiIxEREclkmmDa2nU2ZFTyRfPc004sw0q+ZZi3lKVuQ4+1iu9wMyS8LiX5JjZYxp6y4xieRJ69lz/7unz+lftWiIiIiIiIlBZbJV95kaYhIiIiUnTJCjCnb2aXxSNUWtp15j6slNbkc8qcKvlEFsOm09bxkWY3W3VutIy9FUddu9ZSELM9yeCPF2ceIiKlonV3pwG0AKe6Otr1W1FERESKxkxa71aVU3rrpyt2EhERkcWQtK3HVx8ZBl/z1DiyRNp1OhE7LXqSL9QWfCPwWcALfCUYDnXYXjfSr18LjAEfCIZDT852bKgteDPwESAOdAbDob9YhG9HXGCv5Duyau4fXE7XRgraL2Gr5PNWHMm778vlh+c8j6VGlXwiIimtuzuvBT4BnEcq7rgYeLJ1d+etwH1dHe3fLOL0REREZAUyTWslX2D4BLVjhX32dZtiJxEREVlMpi3J1zgxTCJ2aGqc2a4zM1eQ6hhozT8Ug5Ox06LmLUNtQS/wBWAXcBbwrvTiyZl2ATvS/90A3DLbsaG24DXA9cC5wXDobOBf3f9uxC0bT9uSfM15dpzBT688wU+vPDHjPqaZo5KvPH+S76NbOvjolo68ry8H9gVJVcknIitR6+7O9wF3AmFSsUhmvPQy8AfFmJeIiIiscLZ2nTz+Fa58+ShXvlzcjjSKnURERGSxmYkay7ghMsLYnk8ytueTxD3W5b8ycwXxEliTz+nYqaAkX6gteF2oLehEQvBiYF8wHDoQDIeiwLdJJecyXQ98PRgOmcFw6GGgPtQWbJnl2BuBjmA4FAEIhkOnHJirFIFhmmxYpHadZqwp1bt3kmccI9DryrWWCnu7zoCSfCKyMv018Jmujvb3A/Ynp54n9bCR4xyMt0RERGQZsrfrLItHizSTLK7FToqPREREJBd7JV/DxPDU19E86/FByazJ52jsVGi7zh8Dp0Jtwa8DtwXDodBcLpJhPZBZKnUUuKSAfdbPcuwZwFWhtuAngQng48Fw6DH7xQ3DuIFUZhSfz8eePXvm+W04Z2RkpCTmkc+N1Tcu6vXK+wYpj319ahyrKONda/4QjOxEX7O3eUHze763is6M8eZqeEfNh+d9vtks9ns5k3zvXXPZHcDxqfHbAtczUL1+EWc2s1L4WSn1n9lSpvdufvS+FcVm4N48r00AtS5d16l4S0RERJYjWyVfeaJkknxuxk6Kj0RERCRLVpIvMp3ky7ceH5TMmnyOxk6FJvm2AR8E3gd8PNQWfBT4KvCdYDg0NIfr5SrJsjdAzbfPTMf6gAbgUuAi4LuhtuDWYDhkObdpmrcCtwJUVVWZV199deEzd8mePXsohXnkc/PXbl7U6+16OsllGeN9TRFuGf1Szn1vrL6RW0ZuyfnaB+7aDMBt1x7K+TrARP+bgFVT427/w9wyck/e/e8OfTE1x+BNeffJ5SZS++ebazHke+/+mgT1GeO7hn/E0yOl8ZsP4Nm3PlvsKZT8z2wp03s3P3rfiuIIcD7wyxyvXQjsc+m6TsVbIiIisgzZ1+Rb9cbPcNfBfwHg2qf3F2NKk9yMnRQfiYiISBYzbm3XWR8ZoebNtwJwYs8NltcycwWJEmjXicOxU0F374PhUFcwHPpEMBzaArwufZF/A7pDbcFvpNfEK8RRIHMRtA1klg3NvM9Mxx4FfpBu8fkokCQzeyNLgj9ucv3DScu2Fza506oTIDGxwTL2VORfj2+liGlNPhERgP8HfKJ1d+d7gcm+zkbr7s7fAv4C+E83LupgvCUiIiLLjGkCtnadFbl3LQbXYifFRyIiIpJLMm4tdmuITD/7swTadToaOxVayTclGA79EvhlqC24jtS6eO8B3h1qCx4GPgd8PhgO5UsNPAbsCLUFtwDHgHcC77btcyfwkVBb8Nuk2nEOBsOh7lBbsGeGY38EvAbYE2oLngEEANvKblLqLn/BpHFkehzxwf9c6M5PnWl6SU6ss2zzlivJpySfiAgAnyb1YNHXgER624OAF/hyV0f759yewALjLREREVluTC+pUCTFC/hyNjwqikWJnRQfiYiIyCQzVm8Zrx4bmPo6OlO7ztKo5HM0dppzki/UFnw1qVYJbwViwBdIJdneAPwDqXaZ9sQdAMFwKB5qC34EuCc94a8Gw6HnQ23BD6df/xJwF3AtqaezxtLXynts+tRfBb4aags+B0SB99tbdUrp23Hc+kf28/MMBqvc+dCSnFgL5nRK3/AN4vEPz3DEyhCz/ZLzJ3LvJyKynHV1tJvAH7Xu7vw3Ug8RrQL6gF92dbS/tBhzWEi8JSIiIsuQrVVnCVXxLVrstND4KNQWfCPwWVL3lL4SDIc6bK8b6devJXU/6gPBcOjJ9Gv1wFeAc0gtHfP7wXDoIae+NxERESmcaUIy1mDZtmasb+rryAyVfKWwJp/TsVNBSb5QW3Az8P70f63AHuAGUi0yI+ndfhFqCz4EfHOmcwXDobtIJfIyt30p42sT+KNCj01vjwLvLeR7kdJVN2Ydv7R+8Vp1etWqE1Aln4gsTa27Oy03bLo62jvy7HcR8DDwjq6O9u/PcL7Kro72sa6O9n24t/5eFifjLREREVleTFurzvIFVPEtpdjJqfgo1Bb0kkoKvo7Uki+PhdqCdwbDoRcydtsF7Ej/dwlwS/r/kHq//icYDr0t1BYMAJWOfIMiIiIyZ2aiyvIAlJcJqmPjU+OIL3+cNJ81+Uo9diq0ku8AqfXvbiNVQXcwz37PA48udFKyMtWMWSv5hlwMmRPjGy1jj1p1AtmlzAEl+USkxLXu7sy6YdO6u/POro72F3Ls92lSHQFmc7p1d+dPSLWBuquroz0y2wEOUbwlIiIiuSWtlXzzTfItwdjJqfjoYmBfMBw6AJBeIuZ6IPP7vh74evrh84dDbcH6UFuwBRgFXgV8AKYeNI/O9xsSERGRhTFtVXwV9FsiIyfX5FsKsVOhSb43kXpiKTnTTsFw6CVAix7LvNTaKvmGKt2r5EtmVfIdde1aS0lWJZ/adYpI6bsY2NfV0X4AoHV3Z64bNgA3A3eQauM0m78A3g58Hxhp3d15J6nA656ujnY3H39QvCUiIiI5maY9yTdvSy12cio+Wg9kPt17lOkqvZn2WQ/EgR7gv0JtwVcATwB/HAyHRgv6DkRERMRR9ladlcl+y9jhdp0lHzsVmuR7GxACsp6YSrdO+EQwHPr9uV5cJFN2km/+53rwnN68r5lJP8nIass2b/nsSb7Prb19/hNaIrLW5FMln4gUn88wjMczxreapnlrxnjWGzatuzvXA79Dqs/5rMFWV0f7fwD/0bq7cx3wu+n/7gQGW3d3/hD4dldH+73z+WZmoXhLREREcrK36ywb6WHi5R9yzvAp+67LLXZyKj7K9RSxWeA+PuAC4OZgOPRIqC34WWA38LdZFzGMG0i1E8Xn87Fnz54CplY6RkZGltyclxK9v+7Re+uuxX5/b6y+cdGuVQqavc1L6nsuhbk+MlzLrzPGZxqp1YonnvoGANtXn82N1ddMvbfxVx4G4Mbqa2moPkJqSd8pSz52KjTJ937gS+QIqkgtCvh+QDedZN6MpEn1uHXbyAJWEn9p00je15KRtcB0yt7wn8bwzl4Re3fDb+Y/oSUi5jPI/JzjT9g/84iILLq4aZoXzvB6ITds/h34y66O9kTr7s6CL9zV0X48fey/t+7u3EQq6PpTUnFPoTHUXCjeEhERkdxs7ToDY73EDt3Ppuw9l1vs5FR8dBTIXLdjA6k2oIXsYwJHg+HQI+nt3yeV5MuSvil4K0BVVZV59dVXFzC10rFnzx6W2pyXEr2/7tF7667Ffn9v/trNi3atUnBj9Y3cMnJLsacxq5u4CaAk5jox+tvA5VPj4cjzAMQO3Q/AU6sNvj4Snn5v16R3HIG2qMl51tMt+dip0OJE651/q3NItS0QmbeacetfxpFySHjdadeZmFhnGXvL7XH9ypXVrlOVfCJS+gq5YXMh8O3W3Z1dpJ4G/2Lr7s43F3qB1t2d24HfA94HtADHFjDfmSjeEhERkZxM+5p8iXkvCbfUYien4qPHgB2htuCWUFswALyT1BPzme4E3hdqCxqhtuClwGAwHOoOhkMngCOhtuCZ6f1+i+wWXSIiIrJI7O0662KFt+uc65p8LIHYKW82MNQW/GPgj9NDE/hRqC1oL3cqJ5UHvW0uFxWxc7JVJ8AZh6uB3BV9yYn1lrGnwCTfrv4rgOVd0Re1tesMKMknIqXvMWBH6+7OLaSCoHcC787coaujfcvk1627O28DftrV0f6jmU7auruzldQTVO8AzgNOknpq+8aujnbH/iFQvCUiIiIFMa13qyrK6vBvvor9w3sB2NQ3XOiZSj52ciM+CoZD8VBb8CPAPYAX+GowHHo+1Bb8cPr1LwF3AdcC+4Ax4IMZp7gZuD2dIDxge01EREQWkWlL8jVG+wDwb74KgKjfGnpk5grmsSZfycdOM5X8vUBqoUAD+DPgV0C3bZ8oEAa+O5eLitjVjlkfzFtoku/y55qA3Em++VbyffTEe4DlneSzV/L5EsWZh4hIobo62uOtuzstN2y6Otqfb93d+eH061+a6zlbd3c+QuoprD7gB8DHgT1dHe1u9DBWvCUiIiKzslfyVTVupbzxbJ47mPo8W2iSb4nETq7ER8Fw6C5SibzMbV/K+NoE/ijPsXtJfY8iIiJSRKaZXcnXGElV8pWf/3sARIat9+8zcwUJW5HLbJZC7JQ3yRcMh+4F7gUItQWHga8EwyG32lPJCpddyedOq07T9KTX5JtWaCXfShBTJZ+ILEFdHe1ZN2zyBVldHe0fKOCUIeATwL1dHe2uPu6geEtEREQKYm/XmXN5mMKUeuyk+EhERETySlRCsmx6bESpi45adok6266z5GOnghbvC4ZD/7DQC4nMxOl2nfkkI6vBnP5rb/iG8Piyq/1WKq3JJyJScEDmOMVbIiIiko9p2pN8pcPN2EnxkYiIiGSyV/F5/P2Ux6z7RGbIesXnWMnnBqdjp5nW5Psu8FfBcGh/+uuZmMFw6B1OTkxWlkVL8tladXrKVMWXSUk+EVmpWnd3Xgs80NXRPpT+ekbpp7gWTPGWiIiIFCRpfSR9IZV8TnAzdlJ8JCIiIvkkY/WWseHvJ2BL8s1UyTePNfkc4WbsNFMlXzMw+XasJrXYsYgr7GvyDVe484FlvuvxrRRRe5JPa/KJyMrxU+BS4NH01zMxSfVhd4LiLREREZmVfU2+iiLNI4ObsZPiIxEREcnJzFHJV2av5JupXWfxKvlci51mWpPvmoyvry70hCLzUTtuHbvXrtNWyackn0XUZ02ubuoxKYuaRALFfUpURGQRbAG6M75eFIq3REREpCAOrsnnENdiJ8VHIiIiko+9XacR6CcQtz4PFPHnj5PmsyafQ1yLnQpak0/EbYvRrtM0DVXyzeLw6lQ1XyDdprN+FK571OSOK4v+AVJExFVdHe2HMoYm0N3V0R6z79e6u9MHrLNvFxEREXGTaZZWu07FTiIiIlIM2ZV8A1mVfPZudZmK1a7TzdhppjX5bprLiYLh0Bfnsr9IprpRa7Z9qHJhH1huu/ZQ1jYz1gDJjOXJPeMY/r6Cz7lrbj8SS9J4mcFdFxq8+eHpP49djyf5wRUGpqFEn4isGAeBy0i1ULB7RXq7Iw0eFG+JiIhIQWyVfOYjX2S4+3lmXdBlcTgaOyk+EhERkXzslXyZ7TqHf3QDAJEPWcOOzFxBEdt1ZnI0dpqpku8/5jApE1BQJfNimCZrBqzbTtc6f53sKr5ulLfK9sPLPOx6PEFZupqvdhyqxmHEpRaqIiIlaKZ/HcqBiIPXUrwlIiIiszKTtkq+eLRIM8nJ6dhJ8ZGIiIjklNWu098/1ZVu0kxr8sVLI8nnaOw005p8xetOKitK4zCWH8SRchh2YRXx5IR9Pb5jzl9kGRgvN+ivhrUD09tqlOQTkWWudXfnucB5GZuubd3d2WbbrRz4XeAlp66reEtEREQKYSbLLOOyRFZ3p0XlZuyk+EhERERyMRPl1k59RgzDO0LA3q5zhiRfskhFP27GTlqTT4qupc/aqrO7ARZaYnfdA2sB+OmVJ6a2LXQ9vs8d3A3AR7d0LGhuS8FIBTAwPa4Zn14VVERkmfod4BPpr03g7/LsdxD4X4syIxEREZE0M25td9Ny3u9RmUzys2NfA+DKl48u9pQUO4mIiMiiSkYbLWOPvx/DYKojXeXVfw1AxGe9f2/JFRgGcQ/4ku7P18a12GmmNfnOAvYHw6FI+usZBcOhF+ZyYZFJLbZl8bobF55OXzVUlrUtq5KvbG5Jvh0TmxY0p6VkuMIg9bsmpWbcZOYqYhGRJe+fgX8l9ctuCHgN8Jhtn2iuRZEXQvGWiIiIzMY0vVlJvrW1G/BiMNSf/dl3kbgWOyk+EhERkVySkbWWsRHoBdOcWpPPW78ZyK7ks+cK4t6iJPlci51mquR7DriU1CJ/z5F5x99qMhtQGt1MZcnJquRzIMlnl4zVYCYyPhQZMTxlPY5fZ7mwt0utHi/OPEREFks6iJoMpBazRZTiLREREZmRGasjMzxpHB+krMKFheznwOXYSfGRiIiIZEnYknzesm58CfDYIoWkZ+b8QqIIjcHdjJ1mSvJdA7yQ8bWIK1r6rePuxtz7LUQyYq/iO4FhLH66fqmwJ/lqleQTkRWodXfnBuAMUj3RLbo62u9y6DKKt0RERGRGyVi9Zbx6vB8qNhZnMjNwMHZSfCQiIiJZ7JV8nrITU1V8c1GMJF8uTsVOeZN8wXDo17m+FnHaYlTyJSZaLOO5rse30ozY2nVWj+d7cFJEZPlp3d1ZA3wXeH160+Q/TJm/DB15YlzxloiIiMzGjDVYxqvH+sGFh2Pny+nYSfGRiIiI5JKV5Cs/QSA69/PEi9wDwOnYaaZKviyhtuCZwEVAC9ANPB4Mh8JzOYdIJk/SZPWAdVt3Q85dFyQZsSb5PEryzWio0jquUSWfiKwsnwI2AVcBD5BaHLkfeC+pnunvcvPiirdEREQkU1Yl39hAUeYxA9djJ8VHIiIiK1syXmldo9iI4wmcpmx07ucqdpIPh2OngpJ8obZgLfCfwFtJ9QsdAaqBZKgt+APgQ8FwaGguFxbxxU3OP2BaFrnsr4KJMhfW5JvILuWV/EZs7TqV5BORFeZa4G+AR9Lj410d7Y8B97Xu7vy/wJ8Dv+v0RRVviYiISC5JWyXfmvH+PHsWjWuxk+IjERERgRxVfIFTGEZyqbbrdDR2KvTb+SKp0sH3AZXBcKgWqATeD7wu/bpIwZoHTP6//0zw53dY18ULb3QmwffixmFe3DgMgJn0kYw2W173ziPJd3f9A9xd/4Aj8yt19jX5asbUrlNEVpQ1wJGujvYEMIq1IdZdTLdTcJriLREREcmSq11ntOs+ol33sWZgiI29Rc9xuRk7KT4SERGRnK06AQIZSb5o1330nLov69jMXAGURJLP0dip0Had1wN/GgyHvjW5IRgOTQC3h9qClcD/N5eLiux6PMnagezte7c6k+R7aGff1NfJyGoy89mGvw/DG5nzOT/X8q3Zd1omhiusfw7VquQTkZXlCLAq/fXLwHXAPenxJcCES9dVvCUiIiJZstt19hPZ+00AtlVC/VgRJmXlZuyk+EhERESyknyTRTxl8enilMjeb7Jvs4F9ObvMXAGURLtOR2OnQpN8I6R6nudynFS2UaRgZx/OXRn29BYXWnXa1uPzluX7qyyTsir5lOQTkZXlXuC1wA+BfwO+1rq785VABHgV8H9duq7iLREREbEwTQMzVmfZtjqjXWey+E+ig7uxk+IjERERIZFnOS57u85IARmvePHjJ0djp0K/nS8AHw+1BS23/tNPTX0ctUeQOVqTYwmBw6ugr9aZJF/TYICmwQAACVuSb7KUd662j29k+/jGBc9tKciZ5DPVslNEVoy/BD4B0NXR/g1Sa8AcJLUI8keA3S5dV/GWiIiIWJjxGjKfz/YYo1TGI3jqNuGp28RwWYDBikDxJpjiZuyk+EhERGSFM02DZGSNZdtkki+zXaenbhNl1Zuyjs/MFQAkil/J52jslDevGWoL/ott0w7gSKgteC9wClhNqv/5OPD4XC4qK1tZ1KQymr39kTbnqvje9JtUYu+2aw+RzMryz6+S7/NdfwXAruBNC5vcEhDzG0R8UBZPjX1JqIjCeFlx5yUishi6OtrHgLGM8Q9JPV3lOMVbIiIiMpOkbT0+n3cAgKpr/gaA5w9+GoBrn96/qPPK5HTspPhIREREMpmxBjAzbkx7RzF8qTWJA/HpzVXX/A2XAWC9f5+ZK4Dir8nndOw0U/Hi223jWPq/SzO2Ta5W+Fbgz+c7CVlZ1uao4tuz0+DHlzr/02Waudp1zq+Sb6UZroSyjPXbq8eV5BMRcYHiLREREcnLtK3H5/fm+EC9/Cg+EhERkSmJCfv9/ZMY6Xohe7vOQsS9BrB8utblTfIFw6EtizkRWTnW9Vl/gJ7cavDF69ypkTXjNZiJqukNRhQj0OvKtZab4QpYlZHkqxmHnvqiTUdExFWtuzt7mEOE19XRvtqJ6yreEhERkZnYK/n86Uq+YnMzdlJ8JCIiIpmSkdzr8cF0J7q5KEYln5uxUwHLEIo4a22fddzd6N617FV8nrITGMbyydK7abjC+kRDzZgJONdSVUSkxHyB5fQYl4iIiCwLWZV8npKp5FPsJCIiIosiMb7RMs5cjiswj0q+IrXrdC12KjjJF2oLGsAVwBlAuf31YDikxY6lIPZKvhON7iWOErYsv7dcrToLNVRpHdePFmceIiKLoauj/e+LPQdQvCUiIiJWWZV8JZLkW8zYSfGRiIjIymWaHhLj1iJ/b+Whqa/LYnPPm8XdaSo4Izdjp4KSfKG24BrgF8BZpLKNk1mZzHdQQZUUZG2/9QfvuJuVfBPZlXxSmP5q61hJPhERdyneEhERETt7JV+gRJJ8i0XxkYiIyMqWnFgHybKpseEdwRM4NTWez5p8Rarkc02hlXz/FxgENgJHgEuAk8B7gfcB7a7MTpalFlu7zhMN7lXyZffr7c6zp9gNVFvbdTaMqBOLiKwMrbs7H2OWFgpdHe0Xu3BpxVsiIiIyxTSzK/kCnoHiTGYGLsdOio9ERERWsMTYVsvYW3kAIyOdUBGd+zmLUcmXyenYqdAk36uBPwYmMyRGMBw6DPxzqC3oIfXU1BsKvaisXJUTJrXj0+OYF07XOn+dn1zRjWl6SXZb16dcSLvOm1s/tdBpLSkDVdZxw0hx5iEiUgTPkx1sNQKXAeOkniZ3g+ItERERmWImqsAMTG8wIngZA2D0V/8EwLaqEzQMF2N2Fm7GToqPREREVrD4aHaSL1NFZPrr0V/9E9+8JrtM7ydXWAt/SqCSz9HYqdAkXz3QEwyHkqG24BCQmTl5EPjLuVxUVq41ts4iJ+vB9DhfyddbFyUx0QJMp+UN3wCGdzz/QbPYV3HEgZktHVntOlXJJyIrRFdH+wdybW/d3VkN3Ekq9nFDPYq3REREJC0ZsT606gn0T33CTQ4eBqCsDGonFnliNi7HTvUoPhIREVmRUuvxtVq2eatsSb6MSr7k4GEOlHkAaxavt85a7pcociWf07FToTnLg8Dk4mbPA+/JeO1NQF/WESI52NfjO1m/iK06y9Wqcy76q61/NlqTT0RWuq6O9hFSLaP+2qVLKN4SERGRKcnIOsvYU9aNkePZy6R7H6sXxKHYSfGRiIjICpVaj698amxfjw+gMmINjsbKZg+M4sWv5MtpvrFToZV8ncDrge8C/wT8ONQWPArEgE3oySkp0FpbJd+Jhtz7LdRlzzbyomcLhzJ+YL1l82/VCfDR7ncD8LmWby3oPEuF2nWKiORUD7j0r5fiLREREZmW6k4zzVt+HCOW+rrsvPcCcGz0Hvor4PxDPYs9vULVs7DYSfGRiIjICjXbenxgbddZdt57eVvUoIP/tuxz2bONADy0M/VsULHX5JtFPXOMnQpK8gXDob/K+PruUFvwCuB3gHLg3mA4dPdcLiorl72S70SDO48cnnmkhvCatVA5vc1TtrBKvl0DVwIrJ8k3Wg5RLwQSqXF5DMojJhMFPA0hIrKUte7uvDbH5gAQBP4U+JUb11W8JSIiIpmSE7ZKvvLjGOluU4HWVwEwePAhBiuLm+RzM3ZSfCQiIrJyzbYeH0BlRpIv0PoqXj1BVpLvzCM1wHSSr9hr8jkdOxVayWcRDIceAx6bz7Gysq0ZsCf53LvW6UCTZewpX1gl34pjGAxUw+rB6U0NI9BdVrwpiYgskp+SWgDZ/lRDDPgx8JHFmITiLRERkZXLNL3Za/LladdZAhYtdlJ8JCIisjKYSW/2enyVB7P2q4hmbZpVsZN8OBw7zSnJF2oLvh64mFQ/9G7gkWA4dO9cziErW3a7TneqwsY8FYz5MvpNGjE8gdOuXGs5G6iyJvnqR6G7Kf/+IiLLxJYc2yaAU10d7a7fWlO8JSIiIqkE3/QtG8M3gMc3hqc0k3yux06Kj0RERFaWxOgO23p8w3jKrOvxeZIm5bG5nzvuNUjl2IrG0dipoCRfqC24DvghcBFwKv3fauD/hNqCjwO/EwyHjs314rKylEVNGjPWdUsYcLrOnWudDjRaxp6ykxhG0p2LLWMD1dZfePUjuR4wEBFZXro62g8V47qKt0RERGRSdqvO9PITJZjkczN2UnwkIiKyMsWGzrWMfTXPY9haGmSuxzcXxa7kczp2KrSS71ZST0tdGQyHHpzcmO6F/t/Al4HrnJyYLD9rBqzjnjpIeN1JGPXaW3WWqVXnfPRXWccNI7n3ExFZjlp3d54JrCe15otFV0f7XS5cUvGWiIiIAJCYaLGMveXHASh+d6n8XIqdFB+JiIisMGbSR3zkLMs2X+0zWfvNp1UnQNw7v+Oc5lTsVGiS7zXA72cGVADBcOg3obbgbuA/C72grFxr++3r8blXEWZfj8+rJN+82Cv5GkZK8LFRERGHte7u3EnqplGQ3OXLJuBGSKh4S0RERABIRmyVfGWpJF8prsnncuyk+EhERGSFiY+ekdWqM+d6fEu0ks/p2KnQJN9JYDzPa+OAFjuTWWWvx+fetU5W2Np1TrY2WYCXyw8v+BxLTY+tnWpLf+79RESWma+SWuz4OmAfMM9nw+ZM8ZaIiIhgmrkq+VKfaSeTfImBVJenQDyCP7Go08vFzdhJ8ZGIiMgKE7e36qx9NqtVJ0ClLeIYHT3E8absnNnpWms2sAQq+RyNnQpN8v0zqX7nTwTDoaOTG0NtwQ3AJ4BPLmQSsjIsViWfaXro9zda1ipwol3nR7d0LPgcS80x2y/F9adL8LFRERHnBYG3dnW037PI11W8JSIiIpixRkhWTG/wTGD4U09cGmbqM9nYnlRY0LIp+4HaInAzdlJ8JCIisoKYSR/x4aBlW65WnQAVEeu96if3/TP/fGF2Bu+nV1pzA8Wu5MPh2Clvki/UFvyubVMTsD/UFnyS6YWOL0h//VpSfdJF8rJ/8DjpUiVfMroKzOm/2oZvCI9v1J2LLXPHrV1PWTMA3oTp2lqKIiIl4lFg02JcSPGWiIiI2CXGrWGIt/zY1NPr9ofYTcPALH4PT0djJ8VHIiIiK1d8+Bwwy6bGhm8Ib8WhnPtW2tp1jpfl3C1LCST5HI2dZqrka7aNX07/B1ALTACTPdFXOTUhWb7WLFIlX9LW1sRTtvBWnSvVeJlBXzU0jqTGvmQqWXtMP/EisrzdAPx36+7OMeBXwIB9h66O9jGHrqV4S0RERCyyknwV00tHeOxJPixNbIrF6dhJ8ZGIiMgKFeu/1DL21T6Ts1UnZK/JN1Zgkq8E2nU6GjvlTfIFw6Fr5jM7kVz8cZOmoelxEjhV7861kpG1lrETrToB7g59EYBdwZscOd9ScXSVQePI9C/Sdb0mx1apkk9ElrXTQBfw9Rn2cSQkVLwlIiIidjMl+SbVvDlVvHbk4Kc5Ug/XPr1/MaaWj6Oxk+IjERGRlSkxsZbEeKtlm7/+kbz729fke/OWL/PmUPb9+w/ctRmA265NVQSWQJLP0dip0DX5LEJtQX8wHIrN51hZmVYPQGYVbG8txHzuJIryLVAu83O8Ec7tmh6v74XHijYbEZFF8U3gMuBfcWAB5PlSvCUiIrLymEl/dneaGSr5SsSixU6Kj0RERJYvexWft3I/3rKevPvb1+QrVAm063Q0dio4yRdqC14O/C1wJVAZaguOAfcD/xgMhx5ayCRk+Vu7SK06AZIRtet0Uqpqb/rPb31vaX6qFBFx0DXAH3Z1tH9rsS+seEtERGRlS0xsIPPBbcN/2rLGfPGX38vJ1dhJ8ZGIiMjyl4xXExt8pWWbv2Hmf+bt7ToLVQJJPkdjp4K+nVBb8HXAHmAD8BngpvT/NwB7Qm3B1zoxGVm+Npy2jk80uHMdM1GBGa/L2BLHU3Y67/4yu2NN1vGG06X5qVJExEFdgFNr7hVM8ZaIiIgkxmZu1VmiSb4uXIqdFB+JiIisDNHeV4HpnxobvkF8NS/MeIy9XWehSqBdZxcOxk6FVvJ9ErgTeHswHMoMKf9PqC14B/DPwM+dmpQsP1tOWj+JHF7tVqtO+3p8PRhGwpVrrRRHmq1/Vht7wJswSXi1Lp+ILFt/DvxD6+7OvV0d7V2LeF3FWyIiIitccpb1+Eo0yedm7KT4SEREZJlLxquyWnUGmvZgGMkZj1vClXyOxk6FJvl2An9rC6gm3Qr8aKETkeVta7f1r86Bte4kiNSq03mDVQZ91dA4khoHEql1+Q6vLu68RERc9A/AJuCl1t2dXcCAfYeujvaLXbiu4i0REZEVzDQhYU/yVdqSfIs5ocK5GTspPhIREVnmYn1XghmYGhu+Ifz1j8163LyTfMUvXnE0dio0yTcAbMvz2vZckxCZVDlhsnZgepw04JBLCaJkxFrJ5y0/4c6FVpiDaw0a901/ptp6wnStGlNEpAQ8l/5vsQ2geEtERGTFMmNNmIma6Q1GFE+Z9TOtpzQr+dyMnQZQfCQiIrJsmfFKov2XW7YFmn6N4YnPemxlZH6BUbz4lXyOxk6FJvm+B3wq1BYcAr4fDIcmQm3BcuBtpFonfM2pCcnyY2/VeXQVRP2L1a7TuUq+z6293bFzLTUH1sAr902Pt5ww2XNu8eYjIuKmro72Dxbp0oq3REREVrD46FbL2FtxKKtN1WS7zomnvgFAdWUPtaPFzfy5HDspPhIREVnGon1XQLJsamx4h/HXP1rQsRW2Nfm+Xn07A9XZ+z14Tq9lXOw1+ZyOnQpN8v0l0EQqePpaqC04Aky+Xf+dfl0kp622Yjq3WnWappFVyWd/6nEh7m74jWPnWmoOtBjA9AfHLSdK8/FREZElTvGWiIjICpYYsyX5qg5k7TOZ5Isduh+AsjMNGseX9eczxUciIiLLlJmoINp/hWVboOk+DE+soOMrbe06f1b3AL212bmHlzaNWMYlsCafowpK8gXDoXHgPaG24D8CFwEtQDfwWDAcCrs4P1kGFms9PjPWaO3d6x3F8A27cq2V5uAa659Z6ykwkiamRy07RWT5ad3d+d3Z9unqaP9dp6+reEtERGTlMs0cSb7K/Em+SUkj9V8xuRk7KT4SERFZvqJ9l0OyfGpseEfwNzxS8PH2Sr6xQO797Iqd5HM6dpo1yZdugzAIvCMYDv0IUBAlc2Jv13nQpSSfvVVntdnj6Krku9JPFazEir6+GhishLqx1Lg8BhtPw2GX1lYUESmy5hzbGoEzgV7gRacvqHhLRERkZTNjTZjxuukNRhRvxdGs/SaTfP7NVwEQ8TxNf4VJK0V9wNWV2EnxkYiIyPJlJsqI9l1p2eZvvB/DE81zhJWRNLOSfFePXQnj2ffvzzicagIwWdFX7HadOBw7zZrkS/c7PwXMvtJhAUJtwTcCnwW8wFeC4VCH7XUj/fq1wBjwgWA49GSBx34c+AzQHAyHTjsxX1mYiojJur7pcdKALpcSQ8lIi2W8tX+I7Oce5++jJ94DrMwkH4bBvnUGr9w3nbDdcczk8GpV8onI8tPV0X5Nru2tuzs3Aj8E/s3pazodb4mIiMjSkrUeX+UhDCORtd/kJ7Dy838PgLGDxxmrh/MPFS/J51bspPhIRERk+Yr2XwbJiukN3lECDQ8VfHy5LcE3HoCPnsx9//7y55qA0knyOR07FVqY+GXgo6G2oH8uJ7cLtQW9wBeAXcBZwLtCbcGzbLvtAnak/7sBuKWQY0NtwY3A64DDC5mjOKv1pHV8rAkiAXcSQ/b1+FZFe/PsKfPx0nrrn9sZx5b1ug8iIlm6OtqPAJ8C/sWlSzgSb4mIiMjSU0irTshu11nKHIqdFB+JiIgsM2YiQLTvKsu2QONvMLyFVfEBVNpbdZYVfv1it+vMZ76xU0Fr8gH1wDlAV6gt+AvgJJAZWprBcKiQxY4vBvYFw6EDAKG24LeB64EXMva5Hvh6MBwygYdDbcH6UFuwBWid5dh/A/4C+HGB35Msgq0nbK0617hX+WVv19mkJJ+jXlpnHSvJJyIrVALY4NK563Em3hIREZElpND1+AA8S+9j2EJjp3oUH4mIiCwr0YFLIVE1vcEzTmCO3fMqItbxeIHr8UHpJvnS5hw7FZrkeysw+bZdleN1EygkqFoPHMkYHwUuKWCf9TMdG2oL/jZwLBgOPR1qCxYwDVks9iTfAZfW4zOTAczYqqmxYSZpjPW7cq2Vat86g6Qx/aFyfR9UjZuMVqhlp4gsL627O+1dBgACQBD4R+Axly7tVLwlIiIiS0ih6/FBaVbyuRw7KT4SERFZRsykn1jvqyzbUlV8kTxH5GZP8s2lkq/Y7Tqdjp0KSvIFw6EtcznpDHJlA+whar59cm4PtQUrgb8GXj/rxQ3jBlItQPH5fOzZs2e2Q1w3MjJSEvPI58bqGxd0/AWnvglMJ9vO3fpmNlevX+CsUpq9zVPzOz4S4JsZr9XFhvCb8QXPP5f5ntONucxX5ns3F6Nr/puaE9PLXf5J37X0ndnq4MxmVgo/K6X+M1vK9N7Nj963oniO7PgEUrHIY8CH3Liog/GWiIiILCGFrscHpZnkw8XYSfGRiIjI8hLrvwQzUT29wTNBoHFuVXwAlRFr6DE+hyXCSqCSz9HYacYkX6gtWAFcS6pVZjfwi2A4dHKmY2ZxFNiYMd4AHC9wn0Ce7duALcBkFd8G4MlQW/DiYDh0IvPEpmneCtwKUFVVZV599dUL+FacsWfPHkphHvnc/LWb531szZjJNT3TH0ySwL/X/JiJEWcqv26svpFbRm4BINp/MfCWqddWxVKtOidfd8Jv88V5nfMmbnJ8LguV+d7NxR+uTfC6jJ+q8MFO7li/eL8Vn33rs4t2rXxK/We2lOm9mx+9b0WRawHkCeBoV0f7Macv5kK8JSIiIktIoa06IffTzyXA8djJjfgo1BZ8I/BZwAt8JRgOddheN9KvXwuMAR8IhkNPZrzuBR4n1UnquoXMRUREZCUykz6iva+2bAs0PIjhHZ/zuexr8o3PZU2+Ilfy4XDslDfJF2oLbgV+TiqgmjQUagv+bjAc+tlcL5T2GLAj1BbcAhwD3gm827bPncBH0mvuXQIMBsOh7lBbsCfXscFw6Hlgdca8u4ALg+HQaaSogkesyeiutTBR5s5HkuSEdcE4rcfnjgMtBuyd/nO1t2MVEVkOujraf71Y13Ip3hIREZElYi7r8UFpVvI5HTu5ER+lE3RfAF5H6uHyx0JtwTuD4dALGbvtAnak/7sEuAXrEjN/DISA2vnMQUREZKWL9V+GmaiZ3mBE8Dc+MK9zZa3JN4ckn2kYJAzwFimucjp2mqmS719IFV9dBTxBqlrui8CX01/PWTAciofagh8B7iH15NRXg+HQ86G24IfTr38JuIvUU1P7SD059cGZjp3PPGRxnH3I+lPy/Cb3njlMTFhbgD6z83leqDnk6DV2BW9y9HxL0X7bmopK8onIctG6u7OJVLX/rV0d7ffk2ecNpNp+39jV0X7KoUs7Hm+JiIjI0mFGVxW8Hh9Mr5E+/KMbACh7hcG63sX/XOZy7ORGfHQxsC8YDh0ASD9Yfj2QmeS7Hvh6MBwygYdDbcH6UFuwJf3g+QagHfgk8GfznIOIiMiKlYxXEjn9Gsu2QONDeHxj8zpfha2SbyyQ//79bddm5wkSXvDG53XpeXEzdpopyXcZ8LFgODTZEDUUagv+r/T/W4LhUHehF8kUDIfuIpXIy9z2pYyvTeCPCj02xz6t85mXOO+sw9YPGi+4lOQzTQ/JyFrLNk+F493UBDjSDDEv+NNdWJuGoW7EZLC6RJvGiIgU7k+ArcBMT4f/DPgU8DHgLx26rivxloiIiCwNseGzLeOZ1uMD8NluRsU9YBbn49if4F7s5EZ8tB44kjE+irVKL98+60m1C/134C+AGkRERGTOoqd/C5IV0xs84/gb75v3+bLW5JtDJR+kYqjAvK8+L3+CS7HTTEm+FsDeI2I/qRbwa0kFOSI5VY+ZbO6ZHieB8AaXWnVG1oDpnxobvkE8vhFXrrXSJbwGh1bD9oyf/q0nTJ7ariSfiCx5vwv8f10d7Xkfhe/qaDdbd3d+GfhTnEvyKd4SERFZweLDOy1jX/XMDYv8tvxf3Fe0JJ+bsZMb8VGud8k+95z7hNqC1wGnguHQE6G24NUzXsQwbiD1BD4+n489e/bMY6rFMzIysuTmvJTo/XWP3lt3Lfb7e2P1jYt2rVLQ7G1eUt/zfOZ6aszP1/pbLNtevW6CS+rfP+95bDfvB/ZOjc+rvZym6gss+8z03vq9/0lqGbxF41rsNFOSD7IDHpGCbDlp/atzeDWMVrjzycPeqtNTfozrHkhV9v30yhOOXedzB3cD8NEtHbPsubwdWGuwvXv6z3dbNzy1vYgTEhFxxmas7ZryCWFdH8YJirdERERWoGS0keTEhswt+Gqfm/GYySRf5dV/DYA58DWO18DZ5G/x6RK3Yyen46OjwMaM8QbgeIH7vA347VBb8FqgHKgNtQW/GQyH3mu/iGmat5JqxUVVVZV59dVXO/YNLIY9e/aw1Oa8lOj9dY/eW3ct9vt789duXrRrlYIbq2/klpFbij2NWd1EqhXmXOdqmgZjXTdiZjxLY/h7eaLq33hyZP79Mv/XSMLyj/YveIjrn70GmL5/P/ne5soVnO+JUz/vq8+La7HTbEm+e0JtwVzv9C/s24Ph0Oq5XFiWtw2nreOuNe49Wpgctyb5vOXHWDU0x/rcAuyY2OT4OZei/S0GPDX9eeuC/Um+f5WniDMSEXHEOFBbwH7V6X2dpHhLRERkBYoNWav4vJVds3al8cVTn8W89ZsB8PSXEZvtzo473I6dnI6PHgN2hNqCW4BjwDuBd9v2uRP4SHq9vkuAwXRr0L9K/0e6ku/juRJ8IiIiki3WfwlJ2331sjWdGJ6FLYhXGbGOxwL579/nyhXEvQu6/Hy4FjvNFAr+w1xOJJJpw2nrQ3dHVrmX5LNX8nnLtR6fm/Zutf5Zbu+G5gGTnnq17BSRJe1J4LeBzln2uz69r1MUb4mIiKxQWa06a56d9Rh7u84icjN2cjw+CoZD8VBb8CPAPYAX+GowHHo+1Bb8cPr1LwF3AdcC+4Ax4INOz0NERGQlScZqifS80bLNV/Mc/ppCCtpmVmFL8o2XAdHCj48vfs2Ka7FT3iRfMBzSTSeZN3uS7+gqd65jmh6SEWs/X0/5MaDRnQsK/TUG4Q3QltEN5tIXTX5yiZJ8IrKkfQH4buvuzge7Otq/lmuH1t2d7yN1s+cdTl1U8ZaIiMjKlIw2ZLfqrJm5VSeUVJLPtdjJrfgoGA7dRSqRl7ntSxlfm8AfzXKOPcAeF6YnIiKyrJgmRE7+NiTLpzd6Jihbc6cj56+MWPMP42XGnJJ8icVP8rkWOxWnqYMsb6bJRlu7zqMuVfIlI2vA9E+NDd8QHv8wSvK566E2D21Hk1PjS8JJfnKJWnaKyNLV1dH+g9bdnZ8F/qt1d+dHgP8BDpNaD2YT8AbgQuDfujraf1i8mYqIiMhyYK/i81YcSn+WnZlvYZ2tHKPYSURERGYSHzqf+PA5lm1lzffg8Q85cv4KW0JvLDC34xOL3K7TzdhJd+XFcXVjUD0xPZ7ww+k6d66VGLf22fWUL/pi4yvSw23WpO3WE9NrQ4iILFVdHe0fI9UWYQj4OPBl4Fbgz4Fh4PqujvaPF2+GIiIishyYpkFs4JWWbb7a2Vt1QklV8il2EhERkZyS0SYmTrzZss1Tfhh/w8OOXSNnu845KEK7TtdiJ1XyiePsrTqPNYFpuFPJZ0/yeSsOu3IdseqvMThdC6vSD174krCxBw62zHyciEip6+po/wnwk9bdnT6gKb25t6ujvUSemxcREZGlLj4SJBldk7ElUdB6fFBaST5Q7CQiIiJWZjLA+NHfg2RG1s2IUb7u+xiGc0UilbZKvvG5VvIVqfzNjdhJST5x3IYe69itVp2QP8n34sbZ25zM1d31Dzh+zqXswFqDVUPTv5i3njA52LKwP2t/zMSbhIkyre8nIsWVDq5OFnseIiIisryYJkRPX23Z5qt9pqBWnQD+9O2faNd9AAzUDNHS5+QM50exk4iIiJgmTBx/O8nIWsv2sjU/xVt2yrHrGEmTSlsl31hZ/vv3uXIF8UVu12nnZOykJJ84rvWUNSPvVpJvLObBjDZnbEngrTgCwEM7nf+U87mWbzl+zqXswFqDi1+yJvl+sYDzvWJ/kj++M0l5FP77ao/W+BMRERERkWUnMbaV5IT1YdVA056Cj5+s5Ivs/SYAR9/q4YwTWjpBREREii/ae3XWusO+2r346x9x9Dq5Enymx8h7/z5XriDhNUgth7f06S66OK71pPWH4+CaPDsu0PFRa6NdT3k3hifmzsUkywHrAxlsXeAHy/f9Mkn1RKr157t/laR+ZHn8khUREREREZkU7b3aMvZWh/CWF/4Qt8/WyCnmBVONUERERKTI4sNBoj2vt2zzlB2nvOUOnF7Jq3rCOh4pn/s5irEmn1tUySeO8iZMNtnadXatcecTx7Fha5Ivcz2+psFUE97eOltz3gXYPr4RgH3pasGV7sBa65/rpp7Un3/qKYi5qR4z2Xh6euw14ZUvm/zifH1aFRGZq1Bb8I3AZwEv8JVgONRhe70N+C/gAuCvg+HQvy7+LEVERFae+Mh2EqNnWLbNpYoPwJ9IPQzpqUtVA/pjp4h5TCAyw1EiIiIi7kmMb2D82LvIrCkzvKNUbPiGK0U5VbYk32g6yZfv/n2uXEGx1uRzwzL6VqQUrO+1LgTeVw1DVe4kao4MW1P03opDU1+/6TctvOk3LY5e7/Ndf8Xnu/7K0XMuZUNVBr0102N/Atb2z+9cuaoAzzugSj4RkbkKtQW9wBeAXcBZwLtCbcGzbLv1AR8FlNwTERFZJKbpIXLyTZZt3oqD+CoP5TkiN1/683bVNX9D1TV/wzkH1jNQvsGpaYqIiIjMSTLaxPiRD4AZyNiaoHz9t/AE5nmzeBZVE9b7xqPlqfxDvvv3uXIFiSKvyeckJfnEUfZWnW5V8ZnJAN2jAcs2b+UBV64l+Z2qs44b5tlic9uJ7G3ndpn44kr0iYjM0cXAvmA4dCAYDkWBbwPXZ+4QDIdOBcOhxwD1uBYREVkksf7LSEata1mUremc83kyH6oVERERKaZkvIqxwx/ETFRbtpetvRNf1X7Xrmtv1zk6j3adquQTyWPLIq3HlxjbjMl0AtETOIXHP+zOxSSv/hprErdhnn8EW7uzk3kVUWg7qiSfiMgcrQcy+1IcTW8TERGRIknG6ojY1qjx1T2Ot+LonM/lj8++j4iIiIjbzHgl40c+iBlbZdkeaPolgYZHXL12pT3JV5Z7v5nEl1Eln9bkE0dtPmUdu1XJFx/dbhmriq84+q0PadA4Mr/zbMuR5AM48yg81zq/c4qIrFC5/uGd9xMThmHcANwA4PP52LNnz3xPtayNjIzovZmB3p+Z6f2Z2XJ8f26svtGxczV7mx0933Kz0PfHiffWNOGOl5s5kJy++xTwJvnQljVU++d+/ibza8DQguclIiIiMl/JeDXjhz9EMrLWst1X9wSB5p+5fn0nKvniy6j8TUk+cdTGHut9xMPN7iT57IuVe10s/5X8+qsNMu8d18+jXWf9iMmqPBWA24+rkk9EZI6OAhszxhuA4/M9mWmatwK3AlRVVZlXX331gia3XO3Zswe9N/np/ZmZ3p+ZLcf35+av3ezYuW6svpFbRm5x7HzLzXzfn5u4CcCR9zY2+AomBt9l2WY0/5hvRB6ByNzP94ponIoFz0pERERkfpKxOsYOfwgz2mzZ7q16mfKWH2C4kw6wsK/JN1I+94supzX5lOQTx9SMmdSNTY+jXjjR4Px1krFakpHMhTKT+Kr2OX8hmZUTlXznHsyfyNvebaYefV2Mfx1ERJaHx4AdobbgFuAY8E7g3cWdkoiIyMqUjNUxceLNlm3eioP46x+d9zl9WpNPREREiuRQ7yhjhz6MGbPe9PdW7qNiwzcwjMUJVKq0Jp+FknziGHsV37FVYHqcT87Yq/g8FUcwvOOOX0dm12dL8jXMo5LvvAP5j6kbg+ZB6Kmf82lFRFakYDgUD7UFPwLcA3iBrwbDoedDbcEPp1//UqgtuBZ4HKgFkqG24J8AZwXDIfX+EhERcYhpGkwc/11IZtTdGTHKWn6AYcy/Y4lfST4REREpgpdPDvOerzySneCrDlGx/nYMz+ItHKx2nVZK8oljNp62jo+ucmk9vhFrks9X9VLWPj+5otvx697c+inHz7nUDVRb/4zr51jJZyTNrEq+uAd8yenxjuMmPfWq5BMRKVQwHLoLuMu27UsZX58g1cZTREREXBLtfTWJsW2WbWWr/wdvWc+CzutP3z8b/dU/AXDXO3t46wPJGY4QERERWZjE+EZ+98sP0T8Ws2z31TxD+frvLFoF3yR7Jd9IOsmX7/59rlxBXO06RbJtsFXyHXEhyWcmvcRtlXy+6hez9uutizp+7X0VRxw/51Jnr+RrHGFO7TW3dUNtRhHmSDn86lyDNz06/Xdp+3GTB89yYLIiIiIiIiKLID58JtGe11u2eStfxt/w4ILOa5jm1AORycHDAJxq8OIxlOQTERERd8RHzmT86HsYM20JvronKW/5PkYR4pBK25p8Y+k1+fLdv8+VK1hOa/Ito6JEKbaNp21JvuY8Oy5AYnQ7JKfrbw3vMJ7yY85fSAoyXgYT/ulxIJ79JMVMXv+U9R+BZ1sNutZYE4TzWedPRERERESkGBKRZsaPvwvL7RbvKOXrvregNp2QvR5fzAsYBqYan4iIiIgLYgMXMH7kfWAGLNv99Q9T3vK9oiT4ILtd54jW5BNZOMM02WTrOuJGJV98+BzL2FfzfM4PSpc92wjAQzv7HLv2R7vfDcDnWr7l2DmXPMOgvxpa+qc31Y/CaEX+QyY1D5hc9Zz1z+7BoEHU9lupIuLAPEVERERERFyWjNUyfuQDlgdTIUHF+m/h8S986VtfxlI3Zee9F68HLnv2Z0QME1hYG1ARERGRSaaZaj0e7dmV9Vqg6RcEmu8ttJGbK+xFJpNr8uW7f58rVxD3GMDCHsAqFcsoXynFdMZRawZ9LAA99c5ewzQ9xEesfRt9Nc/l3PfMIzWceaTG0evvGriSXQNXOnrO5aDf3rJzOP8vx/P3JfmD/0lw8YtJ3vJgEm/Grsca4dEzDCYC1n8hKiLL45etiIiIiIgsX8l4NWOH/xAz1mTZXrbmLnxV+x25hj+jki/Q+ioqN72KM4/UkDBqHTm/iIiIiJn0MdH99qwEn2HA/7n+bMpWFzfBZ5gmVbaikMkkX77797lyBcupXacq+cQRl4WtpblPbTMwHf5pT4y1Yiaqpsbl3gTeqgOOXkPmrr/a+tTD2n54dkv2fpe/kORPfpz6e/KGp7ITdz+6zIPpMRgrs75W4fzyiiIiIiIiIo5JxisZP/whzKh1zQpf3eP4G37j2HX88dn3EREREZmvZKyO8aPvJTmx0fqCEecL776Ya3e28JmXijO3SeUR8GTcPp7wQ8I79zzEcmrXuYy+FSkWwzS5NGxNzDwUdL9V5/b68aL1/ZVpxxut49c8nUzVdGdoGDb50D35/6yONcIDZ6f+zoxbWzwrySciIiIiIiUrGath/PANJCNrLdt9Nc9R3vIDR5909ydm30dERERkPuJjmxk7+JHsBJ9ngoqNX+XanS3FmZiNE+vxAcSXUSWfknyyYJe/YNI4Mj2e8MNTW51N8pmmh/jQuZZtOxrGHL2GzM9953jITN9tOwFnHLPu895fJrN+AWe67bWeqScuxsusr1VqTT4RERERESlByVgdY4f+V1aCz1sdonz9fzv+UKqSfCIiIuI004Ro36WMH7oBM2FtaekJnKKq9T/wlVA3Pfu94rH5JvmWUWZsGX0rUgyVEybv/4X1g8tjOwxifodbdY6ciZnIWPzNM86WunFHryHzc7LR4Knt1j/v33p6+u/Elm6Tq17Iv67eb4IGT2+b/lWUVckXIasyUEREREREpJiS0SbGuj6MGVtl2e6tepmK9bdjGM5n5Hxq1ykiIiIOSsarGT/6fiIn3wxYS9u81SEqW7+Ap+x0UeaWT/WE9T7xfCv5tCafSNobnjCpH50ex7zw/Sudzx3HBs+3jP21T+PzlEaJsMD/XGDwyn3Tv2BfccAE02TX4yYf/Hn+p1d/8QqDr7zB+vcl7jOIeiGQ/kzsNSEQh6jflamLiIiIiIjMSXxsM+NH3wcZa8ZD6mZYxfrbMTzuZONUySciIiJOiQ2fRaT7LdbCmrTAql8QWPVzDKP0Ci+qbN3iRsvnV2y0nNbkU5JP5s80efWz1gTOjy416G5yuFVnopz4SNCyzVf3FJA/yXe61vkejy+XH3b8nMvF85sNJvxQHkuNG0fgtXtzJ/j+4zoPMR+crjF4eUPuvysTAQhkFGpWRJTkExERERGR4osNns9E91vBtN5O8dU8Q/n677hSwTfJn5i+0ZYYOMR4IPXZd9WQa5cUERGRZcZMBIicfBOxwYuyX/REKG/5Lv7a5xd/YgXKTvJNf53v/n2uXMFyatepJJ/M2/bjsK5/ehz3wF0XuVDFN7QTzOkMj+HvxVtxaMZjfnrlCcfn8dEtHY6fc7mI+wxe2GhwwYHpD503/E92gi+8Hu47x2C21efHyqA2M8kXhUHHZisiy03r7s43Ap8l1VviK10d7R22198D/GV6OALc2NXR/vTizlJERESWMjPpS90QG7gk6zVf3eOUt9zh+tPume06x/Z8kr1bDH76Ti8f/NncEouKnURERFamxNgmxo+/AzPWlPWat6KL8nXfxRPoK8LMClc9Q5Iv3/37XLmCubTrLPXYaRnlK2WxXWOr4ntiu8FohbNVfADxwQssY3/dU7PliKQIntky8x/KYzsMPvM276wJPoDxMuu4wvnCTBFZJlp3d3qBLwC7gLOAd7Xu7jzLtttB4NVdHe3nAv8I3Lq4sxQREZGlLBltZKzrppwJvsCqn1He8v1FaWdlb9cZT9+cSs7h87FiJxERkZXHND1ETr2OsUMfzpHgSxBo/h8qNn+55BN8AFVZa/LNL1FQaCXfUoidVMkn89I0aHL1M9YfqPt2Op95S0YbSIxvsWzz1z3l+HVk4WZK8j2xLZ3gK9B4wDqujJqAMrsiktPFwL6ujvYDAK27O78NXA+8MLlDV0f7gxn7PwxsWNQZioiIyJIVGzqbie63Q7Lc+oIRo7zlDvx1exdtLvYkXyx9R8ec20clxU4iIiIrSDKyivHj7yA5sTHrNU/gFOXrvoO34lgRZjY/VePW8VhZ7v1mM4dKvpKPnZTkk3l522+Slg8Yp2vhyW3OJ2Fitio+T8UhPIHeWY/7wF2bAbjt2pnbes7F3aEvArAreJNj51xOjq6Cw6tg02nr9iTw31fPrWh4vMwAppPIquQTWdF8hmE8njG+1TTNzCei1gNHMsZHgezH7Kf9AXC3g/MTERGRZSgaTzJx8jpifVdmvWb4T1Ox4Xa85d2LOid/RrvOmjffyuuB/rs+nd6yf/IlxU4iIiICTK4l/DtgBrJe8zc8SNnquzE8sSLMbP6qbPeJRzKew8p3/z5XriCjkm/Jx05K8smcnXnE5JqnrVV837vSQ8LrbJLPNA1iA9YFQP11Tzp6DXGQYXD7NR7+6nvWNq6/Odvg8Oq5/d0Ys/27oySfyIoWN03zwhlez/ULJme/rNbdndeQCray79aJiIiIpO07NczHv/dMzgSfr+aZ1Pp73sX/kGKv5MtDsZOIiMgKZ5oG0Z7XEe19TdZrhneI8nXfx1f9UhFmtnBVM6zJNxcZuYwlHzspySdz4oub3NiZsCzmeLwBfu1Cq87EyBmY8frpDUYUf+1ex68jznlqm8HeLQbnHUz9not64btXzX3pzwn7mnxRJ2YnIsvUUSCz58QG4Lh9p9bdnecCXwF2dXW0z14SLiIiIiuOaXqI9r6Kaz/7ANFE0vZqnLI1d+FveLBoa8T74rPvUwDFTiIiIstYMlbLxPF3khjbmvWar+Y5ytb+AI9vrAgzc4Z9Tb7RivkFZonCb1mXfOykJJ/MyUUvmazrt277zzd6SHpcaNVpW9TcV/tMUZ6WlDkwDD57vYcP3pukcRh+fKnByYa5/93IquRTkk9E8nsM2NG6u3MLcAx4J/DuzB1ad3duAn4A/F5XR/vSfFRNREREXJWYWMfE8beSjKwntejANMPXT8WGb+GtOJL74EVSYCXfbBQ7iYiILFPxkTOYOP67mIlq6wtGjPK1P8JX90TRHlZySrWtkm9knpV8+9bBO/7SC78/664lHzspySdzcvFL1kz5L881eL517pVas0nGaomPtFm2BRoecfw64rzRCoP/+O3CVy7Nxb4mX2UkZwW0iAhdHe3x1t2dHwHuAbzAV7s62p9v3d354fTrXwL+DmgCvti6uxMg3tXRPlMrBhEREVkhzEQZkdOvSbfmzP4c46t+PtWeswSeeHciyafYSUREZPkxTQ/RntcT7b066zXDO0z5htvxVXYt+rzc4FS7TtMwcjfitFkKsZOSfFIwX9zkgv3WZMuvXuF8gg8gNnAhZDQF9ZR14ykv7lOTsnjGtSafiMxBV0f7XcBdtm1fyvj6Q8CHFnteIiIiUrpME+JD5xE5dS1mvDbr9caqAGN1t6U6ypTIE+++uDMPPyp2EhERWT6SsTrGj72L5Hhr1mveypcpX/8dPL6RxZ+YG0wzO8lXlntXJ5V67KQknxSkatzkE99KWNomDlTBS+ucv5ZpGsQGLrJs89c/WjIfrMR9Y1qTT0REREREXJKYaCFy4rdJjG/J+fpvv2Idn3jTWVx9x58t8sxm5lC7ThEREVkm4sNBxo+/HZKVtleSBJrvJdC0B8NYPh3SymLgy+iqHvVCzK+kgZJ8MquaMZO/+1aCzT3W7Y/vMDBdWIsvMXoGZrxheoMRxV/31JzO8eA5zq9t+bm1tzt+Tslt3Jbkq1Qln4iIiIiILFAyVkP09OuyOsdMMnwDlK/9MZ9713cXf3IFyEzyTTz1DR4KGjx4Ti/ndC2fm3ciIiIyO9P0Ejm1K91u3MrwDVK+/tv4Kg8WYWbumq1VZ777927kCkqJknwyo7KoyV9/OzvBB3DfOe606oz2X2oZ+2qfwfBO5Nk7t5c2OV+CfHfDbxw/p+Rmb9dZrko+ERERERGZJzNRRrT3VUT7rgIzkL2DESfQ+GsCq/ZgeGKLP8EC+ePTX8cO3c/TZ3p4aZOHTb3J/AeJiIjIspKMNqbac05szHrNWxWmfN338PhGizAz982W5Mt3/96NXEEpUZJP8jJNkz/+cZKtJ63bByvh26/yEN7ofBVfMtpEYuRMy7ZA/aOOX0dK23jA+nerIqInU0VEREREZG4SSYj2XUr09GsxE9U59/FWhyhf81M8gdJ/wtverjPmtf5fRERElrfY0DlMdL8NkrbsFgnKVt+Dv/H+ZdWe067aluQbsb8NK5SSfJLX6P33c+E+6y+FZ1oNPvNWD5GAO71uo/2Xkdk2xVN+FE/F4Tmf54zDqQ9wTmbpd/VfAaiibzFktetUJZ+IiIiIiBTINCE+fDZfPbCOSGRzzn2MQA/lq+/CVxNa5NnNny+jks+/+SrO9hkcPfwMFeMmMFi0eYmIiIi7zKSPyKl2Yv2XZb1m+PqpWP/feCvnfg99qamasOYqRsutOYp89+/dyBWUEiX5JK/hn//CMj68ClcTfGYykF4bYVqg4UGMeVzu8ueaAGd/cD964j2AknyLYcyW5KvQmnwiIiIiIlKA+NhmIqeuJTm+mVyLPhjeYQLNP8df/xiGsbTaXGZW8pWf/3tcCww/9+n0FiX5RERElqNkZBXjx95NMrIu6zVf9fOUr/s+hne8CDNbfDW2b9PerjPf/Xs3cgWlREk+yck0TUbuu8+y7VtXu5fgA4gNXGApNTa8w/hqn3btelK6In7ruCyeez8RERERERGARKSZ6KldxEfOyr2DESXQdB+BxvswvEuzVYi9XaeIiIgsb7HBVzBx4i2QtFVEEKdszV3451kgs1TV23J0/bm7sa84SvJJTpGXXyZ+4sT02AfPtrr3G8M0IdZ/uWWbv+FRDI8+xaxE9iRfIFaceYiIiIiISGkzk16ivdcQPX01uW9xJPHXP0Zg1c/x+IcXeXbO8unhRxERkRXBTASYOHk98cFXZr1m+HupWP8tvBXHijCz4qoftbbrHKheQRnOGSjJJzmN2qr4nt9sEPO790OTGN1OMro6cwv++oddu56UtoQHEgZ407+3fUnwJpbvorEiIiIiIjI3pmkQHzqXSM8bMGONOffZXj/G8cYv4S07tcizc4dfn4lERESWvcT4RsaPvQMztirrNV/NM5S33IHhXZlrG9WPWscDVcWZR6lRkk9yGrnvfsv4qW3uZsWj6UUxJ/lqn13yT1nKAhgGET9UZnTRKVM1n4iIiIjIijeZ3Iuefg3J6Jqc+3gqDlG2+i7esvpabhlZHgk+AJ8a3YiIiCxbpmkQ7b2aaM9rAa/1RSNG2Zqf4K9/dEW157SrH7FV8inJByjJJzkkRkYYe/JJy7antrpYxTfRQmIkaNkWaHjQtevJ0qAkn4iIiIiITDJND/HB84j0XoMZbc65j+Edpmztnfhqnl2WN8ACatcpIiKyLCVjdUwceyeJ8S1Zr3kCJylf/2285d1FmFlpabCtyad2nSlK8kmW0QcfhPj0p4djjXCqwb0fmOjp11jGnvLDeCoOu3Y9WRq0Lp+IiIiIiJhJP7GBi4n2XokZb8izVwJ/w8OUNf8cwzu+qPNbTKrkExERWX5CvZWMdv0JJCuyXvM3PETZ6k4Mj570AbXrzEdJPskyer+1VedeF1t1JibWEB/eadlWtuoXC37q8rZrDy3sBDnsCt7k+Dklv6gtyVemf8tERERERFaMZLySWP/lRPsvg0S+OzgJfHV7KVv1SzyB3kWdXzH4M5J8wz+6gZv/l5eTQYO6UZNrny7evERERGTuzESAiZPX85PB7A4FhneE8pbv46sJF2FmpaksalKeUQQS88JouXWffPfv3cgVlBIl+cTCNM2s9fiedDHJF+29xjL2lB/FW/2ia9eTpWPCnuSL5t5PRERERESWj0RkNbH+S4kNXAhmIN9e+OueJLBqz4pI7k3y2x58jKfv6ES92fuKiIhI6UqMb2D82DsxY6uyXvNWvUj5uu/h8Y3kOHLlqre36qyCZdmffR6U5BOLyEsvET95cmo84YfQRnd+WBKRZuJD51q2BVb9Uj+bAkDUbwDTi6mWxc38O4uIiIiIyJJlJn3Eh88h1n9JzrVophgx/PWPE2i8D0+gf/EmWCLs7Tqj6Ts6cd3ZERERWRJM00O099VEe14L2J7SMeKUrb4bf8ODGIbug9o12Fp19lcXZx6lSKGgWIzcd59l/Nxmg7jPnaxb9PQ1gGdq7Ck7jq/6BUfOfd0DawH46ZUnHDkfwOcO7gbgo1s6HDun5Bex/XYq05p8IiIiIiLLSiKymtjAxcQGLoBkZf4dPeMEGh7C3/gbPL7R/Pstc5ntOiuv/ms+1W3wP923pbccLcaUREREpECJ8Y1MdL+FZKQl6zVP4CTl67+Nt7y7CDNbGupHrInPwarsnEW++/du5ApKycpN8pnKhucy+mtrku8pl1p1JqNNxIfOs2xzsopv1VCZMyfKsGNik+PnlPyy1uRTkk9EREREZMkruGoPMHyDBBrvx1//KIZX/fsz23V66zezLTr92TfqhUAiz4EiIiJSNMl4NdGe1xIbuJjMgpdJ568e5uWGz2N44tkHy5R623NeAzkq+fLdv3cjV1BKVmySz4wpY2AXO3mSsb17Ldv2bnUnyRexV/EFTuKred6Va8nSlLUmn35kRURERESWrNRaexcTG5ylag/wVh7AX/8ovtpnMQxlrgAM08SXzP96zKckn4iISClJxquI9l5NrP+SnOsMG94Rylvu4HUtV7NvRAm+2dSPWou2BqqKNJEStHKTfAlFv3an/uUzEJ/+hRLYvo2e+kOOXycZbSA+eL5lW2DVL9RrWCzslXwBJflERERERJaUVNXeTmL9F89atYd3FH/dk/jrH8Vb1rM4E1xC7Ovx2cV8QGRRpiIiIiIzSMYrifW9imjf5TmTewC+uicpW92ZbkN+9aLOb6lqGLGO+6vdKU5ailZskg8gMTyMt6am2NMoCeN79zLU2WnZ1vje34PIPzl+rejp15C5sKgncApf7bOOX0eWtoi9kk8PtIiIiIiILAlzr9p7BF/N82pTNQP/LG9NdEXf3RERESk+M15JtO+qdHIvd3tIw3+a8pYf4avat8izW/rqbEk+VfJNW9Fh4EsXXcym//oqVZddVuypFF3fN75pGZedFaT+7W+Dbzqb5EtEmokNvtKyLbUWn6r4xCoryRfV3xERERERkVJlJiqIDe0kPngBifHWGfc1vKP46p4kUP8InrLTizPBJc4/WyWfd+bXRURExB1mooJo75VE+6+AZHnOfQzfIIGmPfjrH9NDTfOU3a5TlXyTFj3JF2oLvhH4LKlSrq8Ew6EO2+tG+vVrgTHgA8Fw6MmZjg21BT8DvAmIAvuBDwbDoYFC5nPszz7G9l/9Ek957h/AlSDe28vQz35m2bb6zz6G4XX+U0K05/VY1+I7ha/2GcevI0tfxG8A07+8VcknIiIiIlJazKSX+OiZxAcvID7SBubMtxi8lftTa+2pam/OfLO8XbEV/Qi3iIjI4jMT5UT7riTad2X+5J53iMCqX+Ovf0SxzwLVj1rH/dXFmUcpWtQwMNQW9AJfAF4HHAUeC7UF7wyGQy9k7LYL2JH+7xLgFuCSWY69F/irYDgUD7UFPw38FfCXhcwp0d/P8M9/Qd117c58k0vQwA9+ALHpBc8CmzdTdbnz1Y2J8Q3Eh3datgWa78EwZlg9fJ5e3Djs+Dnvrn/A8XNKfhHbb6cyrcknIiIiIlJ0pgmJ8c3EB88nNnTurO04U1V7TxCof1RVewtgr+QbPH4fD57lmfrsu13LGIqIiCwKM1FGtO8Kon1XQbIi5z6Gd5hA06/xNzyC4dFNzYUykmZWkm8wR7vOfPfv3cgVlJLFftbrYmBfMBw6ABBqC34buB7ITPJdD3w9GA6ZwMOhtmB9qC3YArTmOzYYDmWWoT0MvG0ukxr8wR0rOsk39FPrWnz173wnhseTZ+/5MU2InLS+x57yI/hqnnf0OpMe2tnn+Dk/1/Itx88p+UVt7ToD+vdQRERERKRoktEmYoMXEBs8DzPWNOv+01V7z2F4Zuk1KbOyJ/mOHfgmn/stH7Skxq9Xg5xZzbezVKgtuBH4OrAWSAK3BsOhzy7q5EVEpOhSyb3Jyr18yb2RdHLvYSX3HFQ7Dp6Mbp0j5RD3ZbfrzHf/3o1cQSlZ7CTfeuBIxvgoqWq92fZZX+CxAL8PfCfXxQ3DuAG4AaDcmP5LMPLQw9z3gx+QbGws6Jtw0sjICHv27Fn0607ynjzJqhdfnBqbHg/PrWrCTM/pxuobHblOqLeSn4w3W7a9fXOAzTXzP3+zt9mx+S2GUprrUnjvVte8BNwzNT7b3FbUn5VJxf6ZXcr03s2P3jcREREplmS8ivjQucQGzyc5sWnW/Q3/afx1T+GvewpPYHnfTFls9nad9jX4Yl7rcgditZDOUkAc+Fg64VcDPBFqC95rO1ZERJapQpJ7eEcJNN5HoPEhDE90cSe4AtSPWMcDOar4VrLFTvLlWg3RHoXm22fWY0Ntwb8mFXzdnuvipmneCtwKUOH1Th1rmCZn9/fT9Ja35J+5S/bs2cPVV1+96NeddPrLt5LZ1aPq4os5601vmhrf/LWbF3wNM+ln9PDHLNu8VWHu8twGI7mPKcSN1Tdyy8gtOV9rGgwA0Fvn3C/V7eMbAdhXcWSWPa1u4iaAvHMthpneu1LxykSSszPGR8b3894i/qxMKvbP7FKm925+9L6JiIjIYjKTPuIjQWKDF5AYOYNU0VN+hncUX+0z+OuexFN+BCPXJ3dZMHslX6BmE9vHvfRHTwIQ840XYVZLyrw7SwXDoW6gGyAYDg2H2oIhUg+iK8knIrKMJSOriA5cQmzgwvzJPc8Ygab7CDQ8iOFVcs8t9SPWFFJ/de6AM9/9ezdyBaVksZN8R4GNGeMNwPEC9wnMdGyoLfh+4Drgt9IB2YwMr/WDylDnXTT9wR/M/h0sM8P33GMZ177h9Y5fI9p7NWa8PmNLnPI1P3X8Opne9JtUz5Lbrj3k2Dk/3/VXAOwK3uTYOSW/iK1dZ5nWphURERERcYVpGiTGtqTW2RveCcnymQ8wYviqQ/jrnsJb/RKGoXacbvMnrLc5guf8DZ/vgu8c/DQAUd+BIsxqSVlIZ6nuyQ2htmArcD7wiCuzFBGRojJND/HhILGBS0mM7si/o2eMQNP96eReZPEmuELZ1+PLV8mX7/69G7mCUrLYSb7HgB2htuAW4BjwTuDdtn3uBD6SfqrqEmAwGA51h9qCPfmOTfdV/0vg1cFwaKyQiRg+HxhGarE4YOKFF4geOkRg8+YFf5NLRezkKSZeyHjwzDCoee1rHb1GItJMtPfVlm3+xt9owXWZVcTWV7ksqtYzIiIiIiJOSkRWpxJ7g+fbHszMzVt5AF/tU/hrn8XwTrg/QZnin+Whx9hi391ZehbSWQqAUFuwGrgD+JNgODSU8yIZy8T4fL4l13ZfSwW4S++ve/Teumux39/FXmLINOHUuJ8XTlfxQl8VEzP8o1ruTXDR2iEuWDNMmbcNaFvw9ZfCskqZijHXTbHHgYemxpsbXsGN1Vfl3X9yjpPv7Th3WbZn+iP+yNnJFsGihoHBcCgeagt+hNRCW17gq8Fw6PlQW/DD6de/BNxFapHjfaQWOv7gTMemT/0fQBlwb6gtCPBwMBz68IyTMQwqL7qIsUcfndo0dM/PWHXDHzr17Za80d/8xjIuP3cnvubmPHvPnWkaRLrfAub0XzPDO0zZql86dg1ZviIB61iVfCIiIiIiC2OakIysIT58DvHhnSQja2c9xhM4ia/uKfx1e/H4B9yfpORkb9dpZ1+jT7IspLMUobagn1SC7/ZgOPSDfBfJXCamqqrKXGpt97VUgLv0/rpH7627Fvv9dWL5qEIkY7XEBs8nPnT+rDGR4R3F3/gAvoYH2euNsNfBLtlLYVklKO6SVO/vS7AtY/zrwDP8ZOS5rP1+my8C03OcfG8/wGbL9uVm0Z/1CoZDd0E6dTq97UsZX5uQO32a69j09u3zmUvNG99gSfKNP/EEsHKSfCP332cZV1+ZP/s9H7GBi0mMb7FsK1vzU5UwS0Eitt9OgVhx5iEiIiIispSZJiQn1hEfPofY8E7M6OwPdhreYXx1T+OvfRJP+XGts1cCfKrkW6iFdJYygP8HhILh0P+3mJMWERFnJaMNxIfPJjZ8Dsnx1ln391QcItDwML6aZzE8qkAolgZ7u87q4syjVK3oMLDylRdaxuPPPINpmhgr4BOMGY8z+uBDlm3VV13p2PmTsVoip3ZZtnmrQ/hqn3bsGrK8Re1r8inJJyIiIiJSENM0SE5sIDZ0DvHhczBjTbMfZETx1TyfWmevah+GkXR/olKwWSv5VvTdndktpLMUcAXwe8Czobbg3vS2/51+EF1EREpcMrKK2HAqJkpObJj9AE8Ef+1e/A0P4y3vnn1/cV3jkLXDdr41+VaqFR0Glm3fhqeykuRYahm/RH8/4eBZtHzyn6h/61uLPDt3Tbz4IsnBwamxt66O8p07HTm3acLEid+xLtbumaB87Y/0BKgUbEJJPhERERGRgpmmQWK8lfjQOcSHzy5ojT1I4K06gL/2KXw1z2F4o25PU+ZptiRfVO06ZzXfzlLBcOgBcq/XJyIiJSjVnnxtuj35OQW1J0/FRC/jr3sKX80LGB7diCwl6/qs4xMN+mc504pO8hleL+U7dzL2yCOW7d1/87eUtbVRcfbZRZqZ+6IHDlrGFRdcgOF15lNBbOASEiNBy7ay5v/B4x/Mc4RItlyVfCul0lZEREREpBBJE+Kj26cTe4maAo6K463aj6/2WXzVL+Dxjbk+T1m42dt1GoA5804iIiLLVKo9+YZUe/KhczBjqwo6zlN+JJXYq30Gj2/E5VnKfFSNm9RmrIEY9cLp2uLNpxSt6CQfQMW552Yl+TBNTv7jP7H5W7djeDzFmZjLoocOWcaB1lZHzpuIrCZy8jrLNm9FF/6GR/Ic4Y6fXOF8KfXNrZ9y/JySX8JrEPeAL90lyGsCsRgEROQsdQAAbixJREFUAkWdl4iIiIhIMZlJL4mxVGLvC6MbGI9/aPaDjBi+qpfTib0QhnfC/YmKo+yVfP9z6pN0Xuyhf91JAC59sQiTEhERKaJUTLSN+PBZxEeCmPG6Ao5K4q04hK/2OXw1z6koZQloyariA9OTuwgk3/17N3IFpURJvlecm3P7+N69jD36GFWXXrLIM1oc0a4uy9iJJJ+Z9DFx7F1gZpRgeSKUr/suhrG4TxT21jnfZmZfxRHHzykzi/rBF5keJ8fH8SrJJyIiIiIrTDJeSWKkjfhIkPjoGZAsA2DGRlJGFF91OHUTqyqsVpxLnD3Jd8o8zL4KL1SkxtEVf3dHRERWAjNRQXzkzFRib/TMqZhoZgm8lQdSMVH1C3j8w67PU5zT0mfNK3Q35u/ylu/+vRu5glKy4sPAile+EqOyEnMsu0XJ+N69yzfJZ6/k27x5weeMnLyOZKTFsq187Y/wBPryHCEyswk/VGYm+SYm8NYV8lSOiIiIiMjSZZqQjK5OJfaGgyTGNwMFdJnxTOCrDuGreQ5f9UtaT2YZ8cetN7jittU2Yiv+7o6IiCxXyWgT8ZE24sNnkRhrBQpZciqOt2of/trn8Ko9+ZK2LivJV6SJlLAVHwb6GhpY98l/oufz/0H0wAHLaxMvhos0K3eZppmjXefCknzR/ouJDVxq2earfQp/3VMLOu98XfZs6qf9oZ3OJRg/2v1uAD7X8i3Hzikzsz+NmsyRjBcRERERWQ7MRAXx0e0kRs4gProDM15f2IGeMXw1L+CveQ5v1csYnsTsx8iSY6/ku6zmvbR0Gzx2+n8AiHlPF2FWIiIizjOTARKj24iPnkF85AzMWFNhBxpRfNUvpR92CmF4I7MfIyWvpd86nqmSL9/9ezdyBaVkxSf5AGp37aJ21y7GnnyKQ+9+99T2SHh5NrVP9PeTHBqaGhsVFfhWr573+eKjW4mcuN6yzfD3Ur72R/M+50KdeSS14LyTP7i7Bq4ElORbTBO2zpzm+HjuHUVERERElhgz6SUxsZHE6HbiI2eQnNhAQdV6gOEbwlcd4s2rW7nb81kMI+nuZKXofHHrOFh2FcEBGDryGwCe36Ykn4iILE2maRLqHua+l3v49Ys9jBz4OwpNWxjeIXw1IXzVL+Ct2o/hic9+kCwp9nadx2dI8uW7f+9GrqCUKMmXoeyMMyzj6KFDJMfH8VRUFGlG7oh22ar4Nm3C8BT2YdIuGW1g4th7sJRJGxEqNnxTT0vIgtmTfKrkExEREZGlaiKWYO+RASI9v0VibCuJ8U3W9cxn4Sk7nm7FGcJTfgzDMNlSfSPGiBJ8K4G9ks9O7TpFRGQp6RmO8MC+Hu5/6TT3vXya0yOZ95Fn/kfNU3YCX/UL+GpemIqJZJkyTVpseTm168ymMDCDt7oK/6ZNxA4fTm1IJons20fFzp3FnZjDol1dlnGgtXVe5zET5YwffT9mosqyvXzdd/GWd89zdiLTJvwGMP0PdXJ0tHiTERERERGZg4lYgicP9fPwwT4ePtDL3iMDRONJ4HWFncCI4q08iK86nErs+QfcnK6UOCX5RERkKRuPJnjiUD/3pxN7L3QPzX7QJCOeiomqXkwl9gLLsxpLsjWMQHnGEtOjZTBUWbz5lCqFgTblZ54xneQDJsLhZZfkix09YhkHNm2a8znMpI/xo+8jGVlrPdeqn+GvfX5B8xOZpEo+EREREVkqxqJxnjjUzyMH+njkYCqpF0vM7clyT1k33qqX8FW/jLeiSy2nZIq9Xadd1Ju/dZWIiMhiiyWSPH1kgAf39/Kbfad56vAA0UTh3QeMQA++qpfwVb+Et/IAhic2+0Gy7KyztersbgQMxTx2SvLZlJ3ZxvC9P58ajz32GA1vf3sRZ+S82HFrlZ1/w4Y5HW+aBhPHf5fE2FbLdl/N0wRW/XLB8xOZNK4kn4iIiIiUqNFInMcP9fPwgV4eOdDLM0cHiSfnltQzfAN4Kw/gq9qHt+plPP5hl2YrS91slXxx3d0REZEiSiZNXuge4sH9p3lwfy+PHuxjLDrLP14Zqst8XLatiVftWEXHc+9XtZ4A5GjVqQRfLgoDbSpe8QrLeOiuu1n9x3+Mf/36gs9hmiYTTz9NrKcH/9oWys85G6OEMsyxbluSb11LwceaJkROthMfPtey3VtxkPJ131MiXRyVVcmndp0iIiIiUiTDEzEe7+rn4YO9PHKgj2ePDZKYY1JvfX0FJ80H8FUeSD2V7u/XZygpyGxJvqju7oiIyCIyTZP9PaM8lE7qPXSgl4GxwqvtDAN2rq/jVTuauWrHKi7Y3IDf6wHgX15Sgk9SWmyVfMeV5MtJYaBN1eWXEdi8meihQ6kN8Tinb/1PWv7h7ws6PjE0RPdf/w3D9947ta3ywgvZ9NX/hxEIzHDk4slK8rUUnuSL9V1FrP9KyzZP4CQVG79eUq1kTtdGZt9pjl4uPzz7TuIotesUERERkWIZHI/xeFdqPb1HDvbx3LFB5pjTY1NjJZdsaeTSrU1csrWRDQ2V7PzaH7szYVnW7O06jxqHGC8zpj77xrxFmJSIiKwoxwbGeXBfKqn34P7TnBya2/3XDQ0VXLFtFZdvb+KqHc00VpXGvXIpXet6rePuxpn3z3f/3o1cQSlRks/G8HppuuEP6f7rv5naNvDd71J3XTuVF10047FmIsHhD/4+E89b16Qbe/xxBn78Yxre/nbifX1Eu7qo2LkTw+935XuYcY7JJHFbks+3trAkX3TgQiKn2i3bDN8gFZu+iuEdd2yOTvjplSccP+dHt3Q4fk6Z2UTAAKbvpCRHleQTEREREeeZpsnhvjH2Hhlg75EBHj3YxwvdQ5hzTOq1NlVyyZYmLt3WyCVbmlhXX+HOhGXF8dvWd/y3ik/xwmYPbEmNG9TpVUREHDY4HuPBfaf5znMRPvHYrzjUO7f7cquqy7h8WxNXbG/i8m2r2NhY6dJMZbmyV/LN1q4z3/17N3IFpURJvhzq3vQmTt/yJWJHj6Y2mCbHPvZxNn31/1G2fXve48affiYrwTep/5u3U94W5PCHPkRycJDA9m1sueMON6Y/o0RvL2ZsunTaU1uLt7pq1uNig+cT6X6LdaNngoqN/4XHP+j0NEUAmLDlwdWuU0REREQWKpk0OdQ3xgvHh3ihe5Dnjg3x9NGBObWYmrS1uSqV1NuaSuqtrSt3YcYi4LdV8sW81ptcatcpIiILlUyaPHtskF+/1MN9L/Xw1JGBjNbks3dwqy33cenWpnRibxXbV1eX1BJWsrR4EyZrBqzbuhuKMpWSpzAwByMQoOWf/onDH/jA1Lb4qVMcet/72Xrnj/GtWpXzuPG9e/OeM/Lii3S9/e1T4+i+/Qzfcw/U1jo17YLMp1VnbGgnE8ffDnimNxpxKjZ8A2/58s6CS3GNl1nHatcpIiIiInMxEUvw0snhdEJviBeODxHqHmI0OssCZ3lsX1093X5zSyOra5XUk8VhX5MvbrubE9PdHRERmaNk0uTlUyM82tXHowf7eODlHvrn8NBTud/DRa2NXLF9FZdva+LsdXV4PUrqiTM29YA3o5CvrxomyvT3KxeFgXlUXXoJjR/4AH233Ta1LdHXR9/Xv8HqP/vTnMfMlOTLuf+zz8EVly9glnMXOz63JF9s+Cwmjr0TS4KPBBXrb8dXtd/5CTrkA3dtBuC2aw85ds67Q18EYFfwJsfOKTNTJZ+IiIiIFKpvNDpVnTeZ1NvfM5rxBPrcnbGmOp3Qa+LiLY0015TNfpCIC+pHrOMv9t8C/fCdg58G4Gtv7Fr8SYmIyJISiSd47tggjx7s5/GuPh4/1M/geOFJPb/X4PyNDVyWrtR7xcY6ynxaFFbcsbPLGsPvWzd7gi/f/Xs3cgWlREm+Gaz+848T7+1l6Cc/mdo2cMcdNH/kj4gdP87Yk09RefFF+Neto//2bzH8s59Zjl9180c4/fn/yHv+yEsvLX6Sz17Jty5/ku9X4VNMHH03kPnLOkn5+v/GVxNyZ4IiGSZs6++qkk9EREREkkmTI/2pdpvPZ1TonRiaWNB5qwJezt1Qzys21nPexjouam2kqVpJPSm+ygmT+oyPQnFP9j6mx8i5XUREVq7hiRhPHOrn8a5+Hu3q4+kjA0TiyTmdY8fqarZWTPCu15zPxVsaqQwonSCL49yD1iTfM62q4stHP5UzMLxeWv7+E4z86lckR1KPzSV6ezn2sY8xcv8DmBMT4PdDLPuJB6OsjMb3v5/eL9+KGY3mPH8kHGbOK7kvUKz7uGXsy1PJd/ez3Xz0209h/SuSpHzdd/HXPufeBEUyjAesv7yV5BMRERFZOZJJk56xJL968RT7T42wv2eEl0+OED4xzEhk9nVhZlJX4eesllrOWldLsKWWV2yoY2tztVpMSUlq6bOOTzRAriVptC6fiMjKdmpogse6+nmsq4/HuvoIdQ8x14YGteU+rtrRzKvOWMVVO5pZV1/Bnj17uPrM1e5MWiQHf8yk7YgtybdFcXo+CgFn4amqou766+m//fapbcP3/nx6hxwJPoDys8/GW11N5YWvZPTBh3LukxgcxDMw4OR0ZxXPWpNvXdY+33/iKH/x/aez/hEob/kB/rq9Ls5OxCqrkk/tOkVERESWnUg8wcHTo+w/Ncq+UyPs6xlh/6kRDpweYSKWhPseW9D5NzZWpBJ6LXWctS6V2FtXV45h6EaBLA3req0fzo83GQRz7Kd1+UREVg7TNDl4ejSd0Esl9g71zv3h+NpyHxe1NnJhayMXb2nkFRvq8HlVGi7F1XbUJJCxHnFPbeohJ8lNIWABGt7zHvq/8x2IF/60aOUF5wNQdfnleZN8AI3/8hmO3X8/jR/8IBU7dy54rrOJnThpGfvXrrGMv/rAQf7PT1/IOq5s7Q/x1z/u6txE7NSuU0RERGT5GByPse/UyFRV3mRC70jf2JyfMs/F7zU4Y03NVIXeWS21tLXUUlfhn/1gkRK2rs/6A9LdmHs/JflERJavaDzJc8cHeaKrn8cP9fHEoX5Oj+TuHjeTlrpyLmpt5KItjVzU2sAZq2vwqJOBlBj7enzPthqgB/TyUghYgLKtW2j5+0/Q/Td/W9D+nro6Gt//fgCqrrwS/vX/5t3X29/P0F13M3L/A2y7qxNfc7Mjc84n3tNjGfvWpJJ8sUSSv7/zeW5/5LDtiCTlLd/HX/+kq/MSyUVJPhEREZGlxTRNugcnppN4Uwm9UU6PRBy7Tm25L53Iq+PsdHXetuZqAj49eS7Lzzpbu87jjblvckW9izAZERFZFANjUZ48nFpP7/FD/fNaTw9Sa+pNJvQuam1kQ0OlC7MVcda5XWrVORdK8hWo/m1vwygr5+SnP03i9GmMQIC6t76F5NAwQ52dAKy66SYqL76Yip3n4KmqAqDszDOped3rGL73XgDKd+5k4tlns86fHB6m53Ofo+Uf/9G178FMJomfPm3Z5mtupn80yo23P8HDB6yfHPxeA+/a2/HXPu/anERmMmF76FrtOkVERERKQyyR5FDvaDqJNzqVzNt/aoTRaGL2ExSoyg/BdQ1sa65m++rp/zY0VKjdpqwYLX3Z7ToZzt5PlXwiIktPImlypG+M8IlhXjwxzEsnhwmdGOJAz9zvgfk8Bjs31KUq9VobeeXmBhqrArMfKFJCasZMWk9Ytz23WXH/TBQCzkHdm66j7k3XYUaj4PFg+FJv3+qPfwwMA//atVnHGIbB+n//N8YefwLfqia8dXXse/0bMHNUJA187/sYgTKafv+D+Nevd3z+if5+S8tRT20tob4IN37zSQ73WedTFfDyxfe+ko889JeOz2MxPHhOr+Pn/Nza22ffSRwV8UMSmHwe24xEMOPxqZ89EREREXHX8ESMAxlJvMkWm4d7x4g70WMzbX19BdtWV7O9uZptq6vYnk7qPfPYg1xzzeWOXUdkqTFMk5asSj74XFXq8+n+qunPvkryiYiULtM06RmJ8GI6mffiiWFePJlK6k3E5l6hB6n7txdsbkivqdfA+RsbqAiorFuWtnO6TDJ7c3SthqGqwpJ8+e7fu5ErKCUKAefBCFifgPC3tMy8v9dL1SUXT41bv/3fDHz720T2H2DskUcs+/bffjv93/0ua//ub2l4+9udmzQQP3Vq6msTuLPtNfznFx4kmrD+Q7KhoYKvvP9C2tbWQv7lBEvaS5tGHD/n3Q2/cfycMgvDYCIAlRktxpNjY3hra4s3JxEREZFlxjRNeoYj7EtX4mVW550YmnDsOn6vwZZVVZaqvG3N1WxtrqIykPujqar1ZKVrHIKy6Wd1GSmH4Qq4uzL9+bRh+rWY7uuKiJSEkUh8KpH30slhwieGePHEMP1jsQWdd21tOa9sbeDCzQ1cuLmRYEsNPq9alcvycs0zOdbjK1C++/du5ApKiZJ8RVB+xhms/bu/A+DBL3yRhi98AZIZibZYjBOf+Hv869ZRfcUVjl13cj2+41VN3LLzzTy+Ngi2BN/FWxq55T0X0FRd5th1RRZCST4RERERZ8QTSY70j1ur8tJfD0/EZz9BgWrKfKmqvHQSL/X/KjY1VupGlMgcrbO36mwE8iS/Yz4lxUVEFlM0nuTA6RFLdV74xDDHBsYXfG7DgLa1tamEXmsDr9zcwPp6tSuX5W1Dj8l5B62xz4NBfX6YjZJ8RRY9+yw2fukWuv/+74kf755+IZnkyB98iLq3vZXK888n3tdH7PBh6t/6VirOO2/O1xmNxPlpuJefXPw+Hll7FnFP9h/9uy/ZxN+/6exlsVj9GYerAWez9Lv6UwlXVfQtrglb6/Bkjla3IiIiIpIyWZV34PQoB9P/HegZpat3lMO9Y1ldPBZibW25pbXmZEKvuaZMN6BEHLLO1l3qeFPqZ2vy8+n+4aeB1GdftesUEXHH8ESM/T2jqY4Hk50PHGxf3lDp58y1NbStreWMNTWcuTb1X3WZfrHLyrLrcetnlfB62L+u8M8V+e7fu5ErKCX6TVECql/1KrZ1dtL7X//F6c993vLa4PfvYPD7d0yP7/wJW77/Pcp27Jj1vCOROL8IneSuZ7vZ82IPkXgA1p2btV9NmY9/fstO3vSKdQv/ZkrE5c81Ac7+4H70xHsAJfkWW1aSb3TuCw+LiIiILDeD4zG6JpN4Uwm9EQ72jDIaTTh2Ha/HYHNT5XSLzeZqtqUr82rK/Y5dR0Rys1fydTembnRNfj79zsGjQOqzb1R3eERE5s00TU4NRywdDyb/f3Io4sg1yv2eVBIvI5F35toamqv1gJSsPEbSpHoChitTf/erx0xe/Zw17rnrorkVI+W7f+9GrqCUKAQsEZ6KCppvugnD66Pn3/4t735mJMKJf/g/bPrG13P+8p9M7HU+082vX+ohEp/5Sd0LNzfwb+84j42NlQv+HkTcMJ6V5FMln4iIiKwMkXiCw71j7O/JSOKlE3qnR6Kzn2AOKgNeS2vNyTXzNjVWLYtOHyJLVUufdXy8Mf++WpNPRGR2yaTJsYFxXj41zL5TI7x8MlWVt+/kCMMRZ9qXewzYsqrKUpnXtraGjY2VeD1K5oms6TP5xLcSrBqGfS3ww8s9XBo2CWT8CJ6uhUfP1M9LIZTkKzFNN/whEy+8wPA99+TdZ+zxxxn6aSd1b7oOSJWM/yJ0is5nU4m96CyJPYC1o6f541eu4p3vv0xPikhJm/AbwPRTHGrXKSIiIstJ0jQ52j821VZzujJvhGP94zjQAcpiVXVguiovo8Xm2tpyPLrpJFJystbka8r/c6p2nSIi02KJJId6x9g3mczLWIt4IuZc+/KWuvJURV5Gdd625mrK/XryQiSfD96bZNVw6uvt3fDnd2T/TN79Sg9JfT4piELAEmMYBuv++ZOcqK5i6Cc/xYzmfkK368v/j5ert/DTx7p4sC9JlNmfrl0bG+bKrse58tgznDFwhNb35a4GFCklatcpIiIiS51pmvSPxTh4emQ6kTf1/zFi9/zK0etVBbxsba5my6oqy3+tq6qoq1CLTZGlwh8zWTU4PU4CJ+rz7692nSKyEk3EEhweSvDjvcfYn5HM6+odJZZw5mkpn619+eT/t6p9ucictfSaXHBg5p/NsQD88hXKWxRKIWAJ8lRVse6Tn2TdJz+JaZpMvPAC0f37eflv/oGH17Rx/7pX8MTqM4nf0zV5RN5ztcRHeMP6Mq5/wyup+qP3k+junnrNt3q1u9+IiAOU5BMREZGlYjyamGqnefD0yNRaeQd6Rhkcjzl6Lb/XYFNjJVubq9mamcxrrtK6LiLLxIbT1k/7p+sg5lcln4isTCOReLq95vBUe819PSMc7hvDNIEH9y74GlUBL9ssaxBPti+vVPtyEYfsenzmStq+avjyLg+jFfo8UyiFgCXONOHJsjV8byzKXbs+QdSYvdR77ehprjr2DFcde5rtg8cwAL4MCdt+vuZmN6Ys4qgh23KRsaNHijMRERERESCRNDnWP87+npGptpoHT49ysGeU44MTjl9vfX2FpRpva3MVW1dVs66+HJ9XN5tElrPXP2W9CXZk1cw3u7Qmn4gsB/2j0alqvMl18/adGqHbwTirvtLPjtWT7ctr2L66mh2rq2mpK9eDUiIuqpwwufrZ7Cq+pAH91XDnJR5+fp4x40NNkk1JvhJ1pG+M7z9xlO8/cZRjA+OpjTMk+FpGTnPV8ae56tgzbJtM7M3A19KCp7Jylr1Eiu9ws3VNvonwi8WbjIiIiKwYE7EEXb2jUzeWJv87eHqUSAFrYM9FQ6U/ncRLtX2aaq/ZVEVFQHftRVaixiGTV9tugt1/zsyf9KM+3RATkaXBNE1ODUemKvNezoi1ekdzL100H6trytixJlWZt31NDdubq9mxppqmqoCSeSJFcM0zJuUZDU76quGPbvLiTabbjuvncl6U5CshE7EEdz/XzfceP8qD+3tn3X/dSA9XnXyeq069wNaTB2ZN7GVqeOc75z/RJeC2aw85fs5dwZscP6fM7tBq69/s0YceIt7Xh6+xsUgzEhERkeVkcDzGvlMj7O8ZYf/kDaaeEY70jZF0ZhkXAMp8nqlKvMmE3pZVVXS/uJfrXn+NcxcSkWXhukeT+DKeJzhRDw+3TX82mvp8GpzeR+06RaTUmKZJ9+AEL54YnqrKm0zoDU/EHbvOqgqDnZtWpSvyalItN1dXay1ikRKy7bjJ7zxofVjyZxd4SHgNEg4915jv/r0buYJSohCwBBwbGOcbDx3i248dZmBs5rU61tdX8NvBJl7d/zI7PD7q3vS/8dbWsv8NbyR29GjW/t76ehIDA5Ztnro6Gt7zbie/BRHXHG+CqBcCk/1mEwlevvwKWv75n6l/y+8UdW4iIiKyNJimycmhyFQyb19GMq9nOOLYdTwGbGiozGirmU7mNVfRUluOx5P9WN6eg3paVUSsasZMXrvX+pTBjy/1kMzxOySTknwiUkzDEzFePDFM+MRw+v9DvHhimCGHknlej8HmpsqpNps70m02tzZX8eiDD3D11Rc7ch0Rcd75+5L86Y+Sliq+qBfuPV+fhZygELBITNPkkYN9fP6pCZ6655czPiVc5vOw65y1vP3CjVy2tSl9c+AVln3WdXyKox+5meTYGJUXX0zNb72Gyosuomz7diIHDtD1zneRHBoCoPmPP4q3utrF707EOUmPwdFm2HrCuv3kpz5F3XXtGIFAcSYmIiIiJSeZNDnSP8ZLJ1NruOw/Ncq+nhEOnBphOOLc0+KNVQG2pdfGm6zM29pcxcbGSsp8aq8pIvMXiJn/f3t3HiZnVef9//2tvffuJJ09JJCEJJogOyiKEZBVcRvcFR2XEdTRZ8aFGZ8ZnfE3M7iMzuigPi7gMiruCiKICgFFQXZZkkASErJ09u703rWd3x/nru7q6qpeq/fP67ruq6ru9fSpu6tOne9ZuPqW7IChrO7aMHQlWFI1PCIyAVKZLM8c7giCea1safKBvd7phsYoFglxwryqfoG81QuqWTG3ilhE8xGLTDcr9zk+/JP+IxQA3HS20VapIF85qAg4wZxz/G7zQa7btI2Hn20ZdN+Tl9VzxelLefnzFlObGLx7eeXpp7P6nj/gkklCFRX9tsVPOIETbr6ZY7/4BfETjqfmggvG+mdMeS/7w0IAfvnC/UPsOXxfeOYaAP72+GvLdk4Znl3zjRP294+EZ9va6Lj3XqrPPXeSUiUiIiKTxTnH3pYunj7QzlMH2th6oI2nD/jeeV2pzNAnGKYl9RWsml/NykbfYjy3zKlSIyMRKb+qLsdHf5xhbcEgPbecGSJdMN9e7vfp7Xu/Cfjfvmm1MRCRMsqNhLBlf2te77w2th9sJ5kZ+/zElbFwb9mqN5g3v5plcyoJD9FzWUSmB3OOd/w6MyDA97PnGz98UfmD9qXq78cjVjCVKMg3QTJZx68ea+K6O7exZX9byf3qKqJccdpSXnfGMlYvqBnRNSwcxgoCfDnRBfOZ9+53jeh809m81njZz7m6+7iyn1OGZ+d8AwZ2dz1w7aeoPOOMAYFtERERmTmOdiTZ3NTK5qZWnjrQxlNBMK+9TD3zomFjxdyq3kqmXEDvhMYqKmP6uSQiE8Oc48M/GRjg2zcHbi8ylFXu9+lDeb991ZNPREaroyfN1gNtbGkKeucFAb1jXYNPKzQcVbEwJy6sYc2CXK88/1hqKHMRmTle8qhjVUFc7RsXhvj1aePTK7dU/f14xAqmEhUBx1k6k+WnD+/ly5u288zhjpL7rV1Yw5UvWMErT15CRUzN70TyPb6ieKEvuWMH2y+5lOXf+TaxZcsmOFUiIiJSTulMlp1HOniyqa03qLe5qZUDreWZM686HmFlYxUrcz3ygmDesjmVRMMa+klEJtdJzzies7v/ul2N8O+vC9MTG14leEpVCSIyBF/e6uydL29LMHfe7qNjH2ozZHBCYzVrFtawdkENaxfVsnZhDUvqKxTME5mFqrocb9zUvwvfn9bauAX4ZjMF+caJc45bH9/PZ3+9lR2DBPee1xjmmleewdknzMFMX3gixexuNG64IMS7nlhAuqmp37b0/v08e+XbWPL5z1HxPD9XpUulINL38ab/LRERkanlWFeKLb2BvDY2BxVNPemxD/3UUBll9YIaTlyQC+T51uILauMqE4jIlHXJ/f1HLnlqsQ/wdSaG/7mVUg2PiASccxxq6+kdZjNX1nr6YDvJMpS35tfEfTBvYQ1rF9ayZqEvbyWiam0gMtuFso4XPe644g9ZavPaD/RE4NvnKcA3HlQEHAf3bDvMp27bwl/2HCu63Qwu3bCIqzeu5NBTD/P8lXMnOIUi08+tZ4T49P/cwYFPfZqjN9zQb1tq3z52vu71WDQKZrhkEksksHAY5xwVGzYQX7mS2IoV1L78ZUQaGibprxAREZldslnHgY4stz7WxOam1t5eentbxt5avCYR4cQFNcFS3ft8XnVMwTwRmVYWHXGcuqN/kO9bF4wswAeQjOizT2Q26kymeepAO1v3+8ZTW/f7+YqPdiTHfO6KqB9qc93CGtYEy9qFtZqfWESKWrPHz8G34uDAbT9/fogjdSqrjAcF+cro4Web+c/bn+IP2w4X3R4JGa88ZQlXbVzJysZqADY9NZEpFJn+Gj/4AUI11Rz+whcHbHOpvrHiXXd37yx+nffdR+d99wFw8HOfo+bClzLnLW+lYsP6iUiyiIjIrNDRk2bL/v5DbW7d30ZHMgM8NOrzxsIhVi+oZl0w5NPqBX5OF/XME5GZ4uIH+/eqeXoRPL1k5J9v6sknMrNlso5dRzp658vLzZ337NFOnBv6+MGEDFbMrWLtohrWLPA989YtqmFZQ6WG2hSRIcVSjrf/Jsv5jxb/MNo5H246W58l40VFwDFyzvGn7Ue4btM27tl2pOg+IYPXnr6M9523iqUNlROcQpGZJRSP03j11cz9679mz9XvpeOPfxzR8a67m9abbqb1l7cw5+1vo/HqqwlVVY1TakVERGaeXAXTUwfa2Lq/nS37fUBvVxkqmOZVx1m3qIbnLKplXbCc0FilOfNEZMaq6HZsfKz/h+etp4/uM09BPpGZIZt17G3pYtvBdp4+2MbTB9rZsr+Npw+20Z0a+1Cb86pjvUNsrllYw7qFtaxeoKE2RWR0KrsdH/1RhnV7Bm5Lh+B3Jxs3nhsipREHxo2KgKOUzTp+u/kAX9q0nUd2t5Tc75L1C/n7C9ewan71xCVO2LqsreznvLX+D2U/p4xeKJFg2de+SvumTTTf+AM6/vAHemsWzRiyljGb5eg3rqf5u9+jYsMGEhs2EKquIrFuHdXnnouFVbgVEZHZzTnH/tZutuxv46lg2KenDviKprHOnRcOGasaq1m3qKY3mLduUS2NNfEypV5EZHo4/1FHRd6Ies1V8Kd1Q1eC5X6f5v/2TeonjMi0kspk2XWkk20H29l2sC0I6rWz/VB7WYJ5iWiIE4MRENYGIyKsWVjDvGqVt0RkbMIZR307rGpyvOaebNHhOe9+rnHji0McnsAhOkvV349HrGAqUZBvhNKZLL/8SxNf2rSNpw60l9zvBSvn8tGL1/K8ZfUTlzjp9acNR8t+zi8s+l7ZzyljY+EwNeefT83555M6eJD0/v1Ely0jXF9P5uhRXDpDen8TnQ88SGrvHtru3ES6qanfOVx3N53330/n/ff3roufeCK1l1xMuGEO8dWriCxYgEWjRBobJ/pPFBERGXcdPWl2Henk2aMd7DzSya4jHTx9oJ2tB9po606P+fxVUThp2dwgkOeDeqsXVBOPqDZaRGa3eNJx+b39K/JvPzVEJjx0ZVjv79NFfevUk09k6klnsjQd6+bZo51s2p3ivtu2sPNwB9sOtrPzSAepzBiHQcC3c14+p7J3vrxcMG/53CrCGmpTZNYLZR3OwI1hqoOGtr7Pqu98Jk18kJ+Je+fAVy8Js/m4if/8KVV/Px6xgqlERcBhSqaz/PjBPXzlru08e7Sz5H4vWDmX975kFeesmjeBqROR6Pz5ROfP730dmTvXr18wn4rnPQ+ABR/7GO133cX+f/0k6f37S56r56mnOPTUwAkzLR5n7pw57P7BDwlVV5PctYvUrl24bJaKDRuoe9WriC5ZDJkMkYULSe1rItPcjEv24LJZ4qtWk1i7Bovoo1dERCZWS2eyN4C360hnsPig3uH2nrJcwwyOn1vFusW1wXCbPqC35aF7eclLzi7LNUREZpILH3bU51UvdEfh9lNHXyHWqc45IhOuO5Wh6Vg3TS1d7G3poulYN/uC588e7WRvcxfpbH4gb/uYrjenKtYbxFsbBPVWL6imMqZ6BhEZ6IWPZ3nznVmqu+G7G0PcesbwhwSfd8xx5lbHWVuzrNkDvM+vHyzAt2UpXHtFmM6EGhhMJH0DDKEnneFHD+zhy5u2s7elq+R+F6xbwNUvWcmpxzVMYOqklLnHYgAcqUsOsefwrepaBsC2it1lO6dMLAuHqTnvPCrPPIsjX/8azd+/keyxY8M+3vX0EGlqor2gNyBAxx//OKz5AUOVlVSccTpz3vxmqs45BwuV/nJ1zmFjaGUjIiKzg3OOIx1J9rV0sa+lm6ZjXf75sW52H/UBvWNdqbJec25VjDULazhxgV/WLfKVTcUqmLbqu0xEZIBivfhuPd1oqxzeZ2bu92lz8gDgf/t2x/V5K1JOmazjYFt3QRkreH2si6aWbo50lK/eKV9dRZTV86tZFSy5+fMaq+OqJxCZYUKpNPXtjpYqfMvJUZjb6sgaNNf448MZx1vuyHLpA32NDN7+2yxNc+CRlcXrIi3rOGE/nLTTccbWLKtK948o6sFVxudfGSIZnbzPqFL19+MRK5hKFOQrIZN1/PCB3Xzxd0+z71h30X1CBi9/3mKu2riStQtrJziFMpiX3+PHLPnmpbvKds4v7vwHAC5Zd3XZzimTI1xdxfwPfpDG97+f1N69dD74ED3bnqb78SfovO++cb12trOTjrvupuOuuwnPmUPV2WdRccqpWDSC6+khuuw4kju20/Ljn5Dcu5dI4zxw4FIpYsuXU3n66YTr60kfOIBVJAhVVBJKxImvWYtFo4TraoktW4bF/JeXS6fpuOcest09VL/ohYQqK8f17xst5xw9Tz9N2+2/IdPcTGzFCmouurBf70wRkdnGOUdbT5qDrT0cbOvmUFtP7/ODwfOmYz6YlxzjHHmlVMXCnLjQz+WyJng8UXO5iIiM2cUPOuryevF1xeDmM4ffuj73+/QHz3wKKO9vX5GZzDlHRzLD4bYejnT0cKgtyeH2Ho60B48duTJWN/tbu8lkxz6c5mDm18RZNb86L6BXw6r51cyrjimYJzKDWdZx6nbHi55wnPX0V3lxOsOuRrh7fYjHVhiHa2FeK2zY6Vhx0FHbAbVd/vMoFYaOhLFtMRyuNTb+Jcu6Pf68uxrh2UZjw87+owXkXP3LLB96p9FaZURTjqVHYM0ex4adjuc866ga5iAvWfMjCOyZC08vMf6ywnj0BBt1kLJcStXfj0esYCpRkK+I3z99iH+7ZTNb9hefkDEaNv7qtKX8zbkrWTGvaoJTJyLlYuEwseOOI3bccb3rknv20v6735LctYv00Wa6/vIoZB3Zzk6yra1lvX7m6FFaf3Urrb+6teQ+6X19vQa7Dh+m68EHhzyvRaPE167F4jGST28jk9dbMdw4j8icuYRrawlVVeGyGUhniB63jIr167FEBZF5c3GZDKlnn8Vls8SOW07lqacQqur/eecyGVL79hGqribSMLxezC6dJn34MKHqanqeeprm//1fuh59lPTBg7hU/14mBz//eea+/e3UveLyfu9RTjaZhFRqQLoyx47R9pvfQChM/ITjSZx00qA9JqcSl81COt0bpBWRmSmbdRztTPYL2PkAXhC8a+sL6nWnxid4ly8SMpY2VHDc3CpWzK3kuDmVHD+vijULa1hSX6EKJhGRMjtza5bX3d3/8/1Xpxvtw+zFJyL9ZbOOlq4Uh9t7ONzWw+GOZG8Q73AQxMtfNxHlq3zzqmMsm1NJPNXGmeuOZ+mcSlY2+qBeXUV0QtMiIpNv3jHHB36RYc3e3JoMAMsPwVvuHO7nk+OUHf4x3/JDsPxQ6cYJ9Z3w6eszZEIwtxVGU1v2N+8L01zNpAf0pI+CfHn2NHfyz794gju2HCy6PRYJ8YYzlvGejStZVFcxwakTkYkQW7qEOVdeWXRburmZB770ZRbv3Em4tpaaC86n4uSTSTU10XrLr+jZsZ1sZyculSK1ew+RefOIr1qJxRNku7roevhhMkfHf6JXl0rR/dhjRbdlDh0mc+jwwA1/hBZ+MOh5LRolsmgR8VWryHZ00LNliw8gmlFxyilEFy8mPKeBSEMDqYMHyXZ0EF2wgMozzwIcdV/+Clv/7u9xnaXnNe33d3R2cvi66zh83XVUnXMO8TVryHZ0kGlupuuxx0gHw6YmnvMcai6+GLIZuh79C+133tnvPJHFi6i96GJiK1YQX7WSilNPHXOFdbarC4vFsHB48L8hmyV96BDZ9nYsHie6YAEWHfgjrv3uuzl83ZfoeuwxyGapOO005v+fDxJftWpM6RSR8ZfOZGlLOnYcaqe5M8WxriQtnSn/vDNJS5d/3tLp1x9q6+Fwe0/B3CzjLx4JsXxuJcvnVrF8TiXL5/nHFXOrWFyfIBKeHo0hRESmM3OOFz3uuOqWLOG8r4HOGPxyBL34RGaibNbRkUzT2p2mtSvll+40x3qfp2jtSgeP/nVLZ4ojHUmOdiTHvcddKSGDBbUJFtUlWFxf4Ze6BIvqKzhujm88VRX31a+bNm1i48Y1k5JOEZkCnOPsLY533+bnyJso3VFI5LWrn9M+vOOywFNL4b41If58onFHsD43JKhMHQry4bvq//CB3Xzyl5tp7xk4c2QsEuKNZx7He168koV1iUlIoYhMBZGGBrrPeQHHfewf+62PLlpE5amnDnm8c47uxx/n6A030H7X3WQ7OsYrqePCpVKknn2W1LPPFmxwdD30EF0PPVT0uCNf+zoACQrbFw1fxz330HHPPUW3dT/5JN1PPlny2PS+Jo7ecEPv69jxxxOuqyPV1ERk3jwS69eTWP9cKtavJ75qVb8gnEulaL39do794hek9uzFpdO47m7SBw9ilZVUv/CFRJcswWXSxFevJrFmDd1PbqZ76xbS+5rouP/+/kHNaJSKk06i5iUbCc+ZS6b5KC0/+xnJbf0nX+968EF2vfktADTWVLN9XiPRRYuILltG8tldZI42E19zIjUbN1L1whcSrp2YIaO7t2yh+cYbST27G6usILbsOFxPN+G5c6k89VQqTjppQM9Kkekik3W0dqWCoFySY50pWrqSNHf4dcc6kz5Y19UXsGvpTNLaHZQd77hrUtNfHY+wuN5XLi2qq2BJfV9F04q5VcyviRMK6ceYiMhkqOhxXPCI46UPZVnY0n9bFvjaxSE6KvQZLdNbbhjMfgG53uep3uDdscKAXfC8rTvFJMXpBjWnKsaiukRv+WpRQSBvQU1cjaVEZhPnqO2ExmOQSDm6YkZXDLrifuhtgFgaYin/GA8e6zodL78vy9o945e0rEEovxFRHP601rjxxSH+/icZ1u4tfWxOawU8sdx4bIXxwGqjpVrlk+lg1gf5DrR2c81P/sKdWw8V3f7qU5bwoYvWsLhePfdEZGzMjIoNG1jyuc/h0mm6H3+cjnvvo/OhB3GpFBaOkD50iFBNNRXPex4NV1wBZlgkQurgQdpu+zXJ3buJzG8kunARLtmDS6VI7t5Dcvt2LB4nffAg6YPFeyNPdaGqKhLr1hFdupS2O+4o+/CoOclnnul9nj5wgO4nniDXidFiMSKNjYRqawlXV5PcvZv0/uIzDbvOTtpuv31kF0+l6HrwwWENu5oTamsn2dbeL90APVu30nrTzVgiQf0VV1B97ouILVtGdMmSor0FxyJz7BhHvvY1jnzzW5Ae2BimlxmRhQuJLV1K4qQNzHnjG4kuWVLWtIgUygStvtu703T0pGnrKf68PXjdEazLPW/LtRDvTuGmYMVSPBJifm2c+TUJ5tfEaayJM7/Gv26sjfe2Gq9NaKgnEZGppqrLcekDWS55wBVtsZ8FvnxZiHueqwCBTI6edIaOngwdPWk6kmm2NWcIPXWIzmSa9rz1HT3p3v06kxnag3JUR9Kva+1O0dadnrTedCMVi4RorI4zrzrG3H6P/vm86nhvYK8iNvjoLSIyCzjH6r1w4cNZznjaUTnMeeuG46GVBue/mi/Hf84Ln3RseMYx/5hjXiskI7B5mfH4cuNgPbRWGtkQRNOw6Khj3W7HnDbYNxd+c0qIY5Vwyg4fhHy2EZ48zsiEfZDui5eH+afvZwY0NtpfD7sbjS3LjMeWG7sWgNMwnNPOrA7y3fZ4Ex/9yWMc60oN2Hb68gb+6WXP4XnL6ic+YSIy41kkQsXJJ1Nx8snD2j+6ZAmVp5wyrH1T+/aR2rsXF9RWx1etIlxTQ6qpCYtESB8+TKalhY4/3UvPju2Eq6qwaBSXSuFSaTLNzT5YM38+Fo3S+fBDpHY9O8RVh88qKiCTIVRbS2LNGupf/zqqX/CCfj3AMi0ttN52Gy0//NGgvfSGvFYigese/hgILpkktXcv7B1G86YpwnV30/yd79D8ne/4FZEI0YULCdfXY9EoiXVriS5eTKiqitgJK6k4aQMunabjnj/ikj0knvtcwrW1uKwDHKHKSsI1NaSbm2m99Vbaf3cHHX/+M6QGflcOTIwj3dREuqmJzvvv5+j1NxBZsACcI7ZiBVVnn0XlWWdTsWF92QORMr045+hKZWjv9sG39iDw1vu82LrgeX7wrj2oaJqOahKR3mDd/No4jdXxfsG8+bVxGmsS1CYimhNPRGQ6cY6Gdrj4wSwXPeioTBbfLWPwpZeF+P16BfhkeHrLT3kBt/ygW7HAXGdPpre81F5k/1SmSFDuvj9P/B9XBjWJCI3VceYGQbrcY37gLhfQq46rfCUixVnWMbfNB9EWHYXV+xxr9zgWtJT3OukQfPclIW45w7iqZjHH2o1bzjRuOXN4xz+11LjrpIHrf7+++GfboXrjQ+8Ms+yQ7/HXmYCWKuiJ6bNwJpi1Qb5svJb3/O/AoeUqomH+8dK1vOms5RrSSESmpejixUQXLx6wPnbccb3bAarPPXfY58x2dfm5/p54gkxLC1ZRQWzZMmLLl5Pau5eeZ54hc7SZzNEjpJubCVdXE25ooOOee+h65FEsHqd16VLW/u3fUnHKyUP+oArX19Pw+tdT/7rX0fXII/Rs3UrmWCuh6irCtbVElywhsX496X37aPvdHT4wFwljZqSPHKX6xS+m9mWXke3ooO3239D1yCMkd+6k84EHIDuxk6yHamuJzJ1Lpr2t+HyIgdiqlSz+j2vp+MPvOfq/3/XB1tGkNZ0mtWcPqT1+DIiuhx8e8SnC8+b5+RaHE9gbjHO9PSHTBw7Qed99wBcIVVZSfcH5VJ15JhZPEKqppvK00wjX1IztejKhnHO09/hecC2dqd6hLo8FS0tn7nmy4HWKjp70lByOabQqIzCvtpL6yij1lTHqK6IDnjdUxqitiNJY7XvjqVW4iMj0F8o6Vu3zFYBLDzuWHHEsOQw1g7QxS4X90Fk3nxVi1wLVOcwmueEsc3PM9XscMPecH8IyN9pAW7cP3E3FUQfKqTIWpjYRpbYiQl1FNHgepTYRCR79tr71UeZWx5hTFSMRVdlKZDYKZR2V3VCRhFDWD1dpgLnguev/vKrb936r74DqbkdVN1R3QVU3NLT7YF50nNuRPrjS+N7GELvnT2w5IBk1tg+sLpQZYBYH+aoHrDt9eQOfveJ5rJin+YSmu5vPaSr7Od+/4j/Kfk6R6SJUUQEVFVQ9//kDtsWWLye2fHnR4xpe//re55s2baLy1OH1RswxMypPOaVkL8bYihXMfcdflzw+XF1N/atfRf2rXwVA+uhRerZsIdPWTnThAjLHjtH1+ON0P/4E3Y8/XnSoU0skqHvlK6i7/HLCdXVkOzqILV9Oz44d9Dz9NJnmFrIdHXQ98gip/fsJVVdRfc45xFasIH7iGhLrn9sb1Ezu2Uv7Hb+jZ/sOsh0dhCoSpI82E1+1innvfhehqioqNqxn3lVXAdCzYwcP3nILzzvjTNIH9pPp6PA9L+Nxuh57jGM//okPxpVZ5nDpYGSksZGGN72RyMKFpPbtw6JRks/spOuhh0ju2sVwah6ynZ203nQzrTfdnHfiCLElSwjV1GDRKBaJYPF4Of4cKZNM5Rxeed09/YJ502VIpuGqSUR6A3J1FT5I11AZpb4iSl3ueWWUuorc8xi1iQh/+P3dbNy4cbKTLyIiZVbV5VvxL2p2VHdBJOuHyGpo88Nord3jqBrmkF3tCfjV6SF+fZrRVjn2Sr3c79PmxQfGfC4ZH5nKuVz+P3/IC95Nn+EsR6siGi4IwvUF5+oqBgbo8l/XJCJENbedyIRy2Szpgwfp2b6d5PYd/nHHDlwySfS444itWE64rp7Es7to7eoiVFlJqLqa6MKFRBYswCIRP4pUKoVLp3HJJJn2drJtbWRa28i2tfY9trX3vnY93X40IYNwdQ3h+joijY1EFi0iXFPLaU9nqeqGBS2OBc0+IFfT5UgkfS80Z5BIQWU3JXvMj6fuKBys99/tiRRU9PilMgkOP8xmT9Q/JnsfjUO1cMfJIbYuVSOf8VKq/n48YgVTyawN8uWLho0PXbiGd77oBMLqvTcjHKkr/yf8tordZT+niEysyJw5RF7wgn7r8ns0ZlpayBw71lv4dNksFevXE66rG3CuwYKPpcSWLmHOW9867P3jJ5xAcsMGqs4+a8C22osvZu4730nz975H95ObyRxrIblr16C9Bcciuvw46l/9Gua85c2EKiuL7pPt6SG1dy+df76f5h/+gJ7NW4YV9AMgnfZBQpmyXCTBI7tbJjsZRVXFwlQnIlTFI9TEI1QnIlTH+7/u9zzmH2viUariYeoqfMVTRBVLIiLTTqLHB+JO2ulYv9MRTzmeWmrctyZEfGE7i1ocsTTB4oil/PNE0rf6r0hCIul8BV3wmiv9uW/4r7E35W+tgJvPCnH7qUZXvHz1Db2/TyvKdkopMxeJ85c95W+QV06RkFEV9+WmyliYTE8nixobfFkpHqEyHqYq7stO/jHcb/+qoLxVm4hQk4gSi6gsNdGynZ2k9h8g296GS6UgmyVcX0947lzCdXVYeGAPx2xnJ9meHt+wMmhgSTisIUzLxGWzZDu7CFUkiub/ULJdXfTs2EFq717S+w+QOrC/9zHb1k62q4tsVyeus4tsd7efcqOuzjfONoNImEh9A+E5c7BYzI8Q5LK4rMOlU77e48hR0keP+hGEMsW/67oefbT3eR2w99vf6b+DGYRCJY8fi4+W/Yxjlw7BwyuN35xiPHq84RRDmJJK1d+PR6xgKpn1Qb4FtXG+9KbTOG15w2QnRUREJlm4vp5wff1kJ2PYIg0NNL73vf3WZdrbSR88SLatjfThw3Q98ggulSZ95IjvbbjbF3jCc+cSqqoi29HhDwwZhpE+erS3kB5bvpy6V72KmgtfSuz444f80ReKx4mfcALxE06g4fWvI9vZSfrwYVxPD52PPELnvffRce+9ZI4cKX9myLQTj4SoyQvGVccj1CT6nlcnIlTH+gJ21fHiz6tiEQ2xLiIyApZ1JFIQS/nW5/EUhDO+VXy/Bf+YDT5is9Y3BFZuOKxQFiIZP6xVJOODaZFM37bcEFkGpMN+qMqQ873hohkfbIsGSyztiGZyz/v2qeyGmm4/FFfhsFvxFEV70q3d67j8vgxwAy8YuHnc9URg9zy457khfnuyab4bKZtENBQE2PoH3ari4b5AXInAXLH9YuFQvzL+pk2b2Ljx7En8C6cH55z/zRQKYaEQLpPxvZhSKR9oyz1Pp4P1vodT9KmnaDcj29XdF6jp6iLb2UW2u6vveUEQp9/rYCoNi0YhHMZ1dpZOaChEuKHBT4sQDkM2S/rwYbJtbcX3z42okrcQzQUCowPWu1QK193jg0i5/YJ9SafJ9vTg0mlC8TiWSBBKJPxjRQWhykosHifb1Um2vYNsRwfZ9nb/2NFBtrMTImFC0RgWK7VECQXPaw4e4sC992GxGC6dJtvWRraj3TfgbfdLpr0dl071pTMaxaKx/q8jkYLtfiEShnQmeK9T/nnu/c2kIeWfpw8fJrVnDy7pAwpWWUm4qopQdbUfqca5YFoO53uyZbPgHM5lIetwyaQfYWgEY/Nm29oGvKfD7GQ+Nrn/gxmotQL2N8D+BmPvPGPrEti22EhG9X0uU9OEB/k2r113MfDfQBj4+rotm68t2G7B9kuBTuBt67ZsfmiwYzevXTcH+AGwAtgJvHbdls3NQ6Xl7BPm8MU3nEpjjYYDm2me/9gcAP604WjZzvm3TW8E4AuLvle2c4qIlFu4uppwdd+Q1DXnn99vu/+xFCEUixU9PtvZSfrgQUJ1dUQaxtYAJlRZ2TsXZHz1ahquuAKXydB+112033032Y5OXDpFz5atJJ95ZkzXkj5jKWuNVCIaor7CD21ZV+l7w9UHveLqg9d1uaEvg/V1FVGqNRzTlJWrtHKZTO+jS6chm8WlM5BJ99vWq7eC0HofcpWG4YMHfU/d3D65x1zlRfDogkoOMhn/PJuFUMhXDOWG73VBhQguOJX5SqtQyLeU7n0MM2i7hFzL41Co7xxF0tSbtlyFTDYbVMhkwMxfKxzGQiGIRKZdC3hXrAJptOuGedyANUMdl0yS7e72eZ9Mku1J4pI9uGTSV6RCcE8ZFjL/PLdgffeiGTjney8ElYfZjg6yySShRAWhSt/63aXTuJ5kUMnoKwSzHR24nmTvXLmhqkpC1TW+dXz++TFfEdveRrazq+Tf+I4tmd4gWCgL4WDJrRv43PnH3P6O3tdz+A7PyaT79g2OzckNaeXMB83iKYjNzPq4SdNaAY+tMLYvMvbOhT3zjMN14Mb58yD3+/T+w7cB5f3tO1ONR33USCXCUBsNURM1amNGbSxMbTxMTcSoixk1YaiNGrWJMPVzamlobKC+ppLaqjiVVQmikcmfd84554NYuUBWJtP3OZj7fnWuN5gx4DuUvNfBNovFCFVVEYrH+86b/5hM4dJ9AbRsTw8u933Q0+O/G3q685734JI9ZLv9dtfTQzbZA1nnA02VFf6zvyKBVfjnFgn3fjfkPvv7B5/ayeStG01wYw5QrjGiXM8wwjjZLJkjR4bfyDIIUk7HQWUrgaN33TXZyRjAdXaS7uyEQ4cmOykzVhboTEBXDDKh/mWfwueYH2qzudo4WgPtFUZ7AjqCpbXCOFgPHRXTq0wvfUrV349HrGAqmdAg3+a168LAdcBLgT3A/ZvXrrtp3ZbNT+btdgmwOljOAr4MnDXEsdcAv1u3ZfO1m9euuyZ4PWjP3lBPO//7jrM0LNMMtWZ3DVDef9xLWl4IKMgnItNbqaE287fHVqwYt+tbOEzNeedRc955/dZn2tpINTX5H+GpFC6ZItvVCQX7FbPimlv6VbrsvPayawu2D6iw2XntZaMKak11YylrDXXuUOtB/l98CzXZJLXhLLUhiEUMC4UhHcLaDNoNLBRU8uADH+QqfPxjxoxjNvh+fRVFffvkR2z6BVIKKlF7A0WOvgomF1QiDXtdsD7XyrbIOt/i1q+rfnYXB/50b96+9LbK7V2XdX3XyV+XC2hlMr4FbyaLy2b8tlzLXvKOz2/564rv47IZ37o4m/WVcJmMb2GcyfrAXLp/oK53XZCOcpsHbC/7Wacos+LBvkGCXfOzWTaHQiX3G20wbSQtwKeyBcDWyU5EmV1U1rO1MPg3u4xFMhy05J9jHKnxvRHTYWit9K/3Nxi7Fox/QK+Y3O/T1t33ACP77Tsby07jWB9VkjU38bm7vkBNqouqYIllR/492x4sgP+OyS3RaNBgxY/I0Rtgs6AslWvMEjwSCspt+evCIcxCvrFLOs2c5mZ2fO7z/Xql9euhlnsUkRkjVFtLbMUK4itXEl95ArETVhKqSJDcuZPknj1kOztpeuYZ5tfWke3qItPSQqqpiczhvKlC8j6XQjXVhGtqCdfUEKqpIVxbQ6imtt+jxRNYOIRLZ8i0tZJpaSF94CCpffvIdnVyT/NDdMXgcC0caPDfua2VRmfc/zQMZ32wrjPuFw2dKTml6u/HGiuY6mWnie7Jdyawbd2WzTsANq9ddyPwCiC/YPQK4Nvrtmx2wL2b166r37x23SJ8L71Sx74C2Bgc/y1gE0MG+VoV4BMREZkiwjU1fhiZEVpxzS0DKl1WXHPLTTuvvWzMQa1patRlrXVbNg8+E3VXG8f94Ou9LzuCRaAKmJntAWXEnPMVoCM4xGDGDnUkMhFSYThSA7sbjUdO8BWAZz7lOHGvo5oqmsMdJKOQjOQWIxmFnih0xqArDl0xozvmKwq7Y5D7tnvLh8IzruJwFpedxqs+qiRLdrKu+dny/hW5HnTlPWuvKBM0zJ+UTyRCdP58P/9aNAr4uebTR4+SPVZiTsholHBlZd5woqne3upSHhaP+yE7R9PoyozosmXEViwnumgx0YULiCxYSHThAsINDYQqKrCKSkKVFX7I044OMi0tvddzySSZ5mbSR44Go08EAf9wCEJhwnV1RObOITzHL6VG+al6/vN7n2/dtIlTN27st92lUr5xwTjM5/jyb20o6/lExmI6lJ0mOsi3hP490/cw8I8tts+SIY5dkKuYWrdlc9PmtevmlzPRIiIiMmWdCWzbee1lOwBWXHNLyQqbndde5oB7V1xzS/2Ka25ZtPPaywYPak1PYylrzcT8EBGRIrqDIFdP1D9Ph4NO0wVz3kH/efByw11l84bDys21l4pY7/Pc9tw+AJGsHzI0G/I95FIRvySDx1TY+p5H+vbpjkFbhQ/eZUL++Fw60mForxjYk+6e5/rHq6r/mi+3f3nU+TTTAnyB2Vp2Gq/6KJmtQqG+wJhZX+/K/Hndens3RbBojNZkkoaFC4M56Sr8UKEVlUHQJtH7vHdbMJx0flAnlEj0zjvnUilCVVXBqBgDuWSSdHML2bbW3mBTeM4cwg0NA45x2awfor3fXIJ9PTl7A8y9PTvTvtdWIu7nBkylcamkH041mcQiUUIVCb+tpwfX3d07v6Dr7vZTNyR7/N9ZVUWoqopwdXXv81BlJS6TDYbnTvrHvCXb0+OHcQ1eP/XkE6xavtwHuiIR34usqppQdZV/Xl3t58WLRvultbfHatElv0drCgv795JwOG+OwrDvxRZsC1XXEFu2lHBdHS6b9XMsdvg5AV1PT29vW8z8exCMXtI75HgoRKSxkVAiMfxbMRYb81Qbo5ELKovMAlO+7DTRQb5iJeTCJg2l9hnOsYNf3OzdwLsBIpEImzZtGsnh46K9vX1KpKOUq6qvmuwklNQYbiyZvi5+BYxP+kd7zqmUl4Pl3VQ2Ff5Xpvr/7FSmvBsd5RsRM3sg7/VXnXNfzXutoFZ/YylrDTxZXtkpMc3mGpPRc3nz3Lm84bxcMMRXv/XBPGfBkX0Pea2WXTab17o3mEvP5Sr+C+bpC86ZO79lM5BMYel0337592LekKWWm8evd6jU0ixvrqDcsQOG2yscFjaXtrw05F/TZlAL+GEPPTic/YrtM4LjnHO994+LRnARX4HqolFc3lyKRsHwu/mv6Xt08bhfEgm/RCNYMon19ADm7/VwpHd7NpHAVST8dUP+fg9192BdXUEPTIc5eq/nYjGyFQlcLO737/uDep/t72jChUK4kAWP+c99ZZ8LGS4cwlmxffqeN0TmcsS19L4m95jLlyA/zEE2EiYTjZCNRob3HpRZhv49hAyIBct4Gevvnun0mymX1vfyXpWdipuQ+qj8slM8FKJn7VosnYJMtv+coWbg/DDZlnV5333BcOXpFKH2DkId7VjaD6s9lb5nXDA8tQvKCxR+Bhf+rSHD5YZhh36BDmdgqTTW3e2/78Nhf95I2Jc9ctcJh3ERP++uC74HCL4XXDSKi0Uh9zwaCbYHryN+HWb+Mz+39PQ9J5PBJeK4ePC5H0+QTcRxiQr/OvedECxEgirVbN57O4T29naa8+ZPH1J3l1/Kae/e8p2rC2gtsS2Vgq7O/utCIaiq8svcuQOP6enxy9FhjJERi/mFKgDaq6voKpW37e1+Ga7gfmP4cTbIpP3S3Q2Hxzj/3vapN9D9RNdLTKfv33KYbvW00yGtuTTm8nawWMFMKDtNdJBvD7As7/VSYN8w94kNcuyB3DBTwVAKB4tdPHhzvgpQVVXlNhZ0M54MmzZtYiqko5T3f+v9k52Ekq6qvqpkq8y3sRxgTK02C13Ol0Z1zqu5uuxpGavB8m4qe+w1j012Eqb8/+xUprwbHeUbaefc6YNsL2tQawYYS1lrgPyyU2U87hb83/+LRcLBfG7B3HG5x1Jz22X7Ktz9fHnF9qP/HHb589fl9ulLVN7zAQnunfvPBwUsrxKJ0uuKzP9nxdblzx2YN5/g9u07WLlqVfE5BvPX5a6fWxcO+5a7wdA5hMyvy58rB+ubp7DwdV4ae1v/WnCOcDh4DFoYh0K+tXG/bWG/LhQKWiCHx2W4ndnyOeZyQcPcPIuDBQ1zq4C77r6bF5977qD7Dedcw11X7vd3vM3E+2dDGYeg8uX6gjnD8z8bg4+d3vXJYJklRvu7Zyr+hiuU+32ak5dWlZ2KG6/6qH4K651O/vnPxpbq/ufu600V9LDqnZs368tMuQYsveWwTKZ3m8tk+q/LZvy+ueehMA899hdOP+usvl5o0agvI0SjWDTme6TlygwyYjPxO22qUN6Or4nO36lcHz0epks97XQqH+XSmMvbIWIF077sNNFBvvuB1ZvXrjse2Au8HnhjwT43Ae8Lxjg/CzgWBO8ODXLsTcCVwLXB4y/G/S8RERGRqaCsQa0ZYNRlraFObJEIc978pnKnd0Z4bNMm5qpSYdazXA/IcLjoL7ySIhGsxFwoIiLjYLaWncarPmrCmJkfCjIahYqKcblGuvUYibVrx+XcIiIi09SULztNaJBv3ZbN6c1r170P+DUQBq5ft2XzE5vXrntPsP0rwK+AS4FtQCfw9sGODU59LfDDzWvXvQN4FrhiAv8smYIO15Z/quinE2WeMFtERMrhfmD1imtuGbLCJhg3/Szg2DSfU6aksZS1REREZPrI/T4dxW/fWVl2Gsf6KBEREZkiStXfjzFWMOXLThPdk491Wzb/CoJBUPvWfSXvuQPeO9xjg/VHgPPLm1KZzn75wv1lP+ffHn9t2c8pIiJjs/Pay9IrrrmlX6XLzmsve2LFNbe8J9g+64JaYylriYiIyPTQ+/v0+JEdN5vLTuNRHyUiIiJTR6n6+7HECqZD2WnCg3wiIiIi5bTz2ssGVLoEhazccwW1RERERAIqO4mIiIgM31QvO4Um68IiIiIiIiIiIiIiIiIiMjrqyScz0tt+tRyAb166q2znvHXzlwC4ZN3VZTuniIiIiIiIyEjlfp/+4JlPAeX97SsiIiIyHZWqvx+PWMFUop58IiIiIiIiIiIiIiIiItOMgnwiIiIiIiIiIiIiIiIi04yCfCIiIiIiIiIiIiIiIiLTjIJ8IiIiIiIiIiIiIiIiItOMgnwiIiIiIiIiIiIiIiIi04yCfCIiIiIiIiIiIiIiIiLTTGSyEyAyHv64/kjZz/mFhd8t+zlFRERERERERir3+3R7Vfl/+4qIiIhMR6Xq78cjVjCVKMgnM9JTx7WX/Zy3NtxT9nOKiIiIiIiIjFTv79OGyU2HiIiIyFRRqv5+PGIFU4mG6xQRERERERERERERERGZZtSTT2akE5+tBsobpb+k+RxAPfpERERERERkcuV+n25vexSY+S3URURERIZSqv5+PGIFU4mCfDIjveDxuUB5/3H/dv+bAAX5REREREREZHLlfp/+4Jk9wMyttBIREREZrlL19+MRK5hKNFyniIiIiIiIiIiIiIiIyDSjIJ+IiIiIiIiIiIiIiIjINKMgn4iIiIiIiIiIiIiIiMg0oyCfiIiIiIiIiIiIiIiIyDSjIJ+IiIiIiIiIiIiIiIjINKMgn4iIiIiIiIiIiIiIiMg0Y865yU7DpDCzLNA12ekAIkB6shMxTSnvRk95N3rKu9FT3o3ObM+3CuecGiVNAVOo7DQVzfb/06Eofwan/Bmc8mdwyp/Bzcb8UdlpipimZafZ+D8zkZS/40d5O76Uv+NL+Tt+hpO3077sNGuDfFOFmT3gnDt9stMxHSnvRk95N3rKu9FT3o2O8k1k6tP/6eCUP4NT/gxO+TM45c/glD8iI6P/mfGl/B0/ytvxpfwdX8rf8TNb8nZaRyhFREREREREREREREREZiMF+URERERERERERERERESmGQX5Jt9XJzsB05jybvSUd6OnvBs95d3oKN9Epj79nw5O+TM45c/glD+DU/4MTvkjMjL6nxlfyt/xo7wdX8rf8aX8HT+zIm81J5+IiIiIiIiIiIiIiIjINKOefCIiIiIiIiIiIiIiIiLTjIJ8U4CZXWFmT5hZ1sxOn+z0TAdmdrGZbTWzbWZ2zWSnZ7ows+vN7KCZPT7ZaZlOzGyZmd1pZpuD/9UPTHaapgszS5jZn83s0SDv/mWy0zTdmFnYzB42s19OdlpEZptSn2Fm9hkz22JmfzGzn5lZfYnjZ3R5pQz5s9PMHjOzR8zsgQlN/AQYJH8+GeTNI2Z2u5ktLnH8bL1/hps/s/L+ydv+ITNzZjavxPGz8v7J2z5U/szo+0ekUKnftGb2CTPbG/wvPGJml5Y4Xv8zJQxWX2Bm7w8+i58ws0+XOH5Gf16PVRnyV/fuIAb5bPhB3ufCTjN7pMTxun9LKEPe6t4dxCD5e7KZ3ZvLNzM7s8TxM+re1XCdU4CZrQOywP8DPuSc0z/uIMwsDDwFvBTYA9wPvME59+SkJmwaMLNzgXbg28659ZOdnunCzBYBi5xzD5lZDfAg8Erdc0MzMwOqnHPtZhYF/gB8wDl37yQnbdows78DTgdqnXMvm+z0iMwmpT7DgFrgDudc2sw+BeCc+2jBsTO+vDKW/AmO3wmc7pw7PIHJnjCD5M+TzrnWYJ+/BZ7jnHtPwbGz+f4ZMn+CbTuZhfePc+5eM1sGfB1YC5xWmAez+f4ZTv4Ex+9kBt8/IoVK/aYFXgu0O+c+O8TxO9H/TFGD5O0C4GPAZc65HjOb75w7WHDsjP+8Hqux5G9w/E5075Y0nPouM/tP4Jhz7l8LjtX9O4ix5G2wbSe6d0sa5LPhv4DPO+duNd9w5SPOuY0Fx864e1c9+aYA59xm59zWyU7HNHImsM05t8M5lwRuBF4xyWmaFpxzdwNHJzsd041zrsk591DwvA3YDCyZ3FRND85rD15Gg0WtS4bJzJYCl+ErqkRkgpX6DHPO3e6cSwfr7wWWFjl8xpdXxpg/M94g+dOat1sVxb8XZ/P9M5z8mfGGKEN9HvgIpfNm1t4/weuh8kdk1tFv2vEzSN5eBVzrnOsJtg0IQDELPq/Haoz5K0MY6rMhaFTzWuD7RQ7X/TuIMeatDGGQ/HX4RqcAdcC+IofPuHtXQT6ZjpYAu/Ne70GFU5kgZrYCOAW4b5KTMm2YH27yEeAg8BvnnPJu+P4LX0mVneR0iMxaw/gM+2vg1iKHzoryyhjyB/wPsNvN7EEze/c4JnPSlMofM/s3M9sNvAn45yKHzur7Zxj5A7P0/jGzy4G9zrlHBzl01t4/w8wfmAX3j0gpRX7Tvs/8MMnXm1lDicP0PzMMBXl7IvAiM7vPzO4yszOKHDIrPq/LZRT5C7p3h61EfdeLgAPOuaeLHKL7d5hGkbege3fYCvL3g8Bngt8SnwX+ocghM+7eVZBvgpjZb83s8SLLtI4STxIrsk6tNGXcmVk18BPggwWtzGUQzrmMc+5kfE+OM81MQ8UOg5m9DDjonHtwstMiMpsN9hlmZh8D0sB3ixw6K8orY8gfgHOcc6cClwDvNT+s+IxSKn+ccx9zzi3D5837ihw6q++fYeQPzM775yT80GSlAp85s/X+GW7+wCy4f0SKKfKb9svASuBkoAn4zxKH6n9mCEXyNgI0AGcDHwZ+GPTc6XdYkVPNuM/rchhl/oLu3WEZpL7rDZTuaab7dxhGmbege3dYiuTvVcD/CX5L/B/gG8UOK7JuWt+7CvJNEOfcBc659UWWX0x22qahPcCyvNdLKd71VqRsgrk+fgJ81zn308lOz3TknGsBNgEXT25Kpo1zgMuDcdhvBM4zs/+d3CSJzF6Fn2FmdiXwMuBNzhWd5HpWlVdGkT845/YFjweBn+GHTZmRBvkO/B7wmiKHzOr7J0+p/Jmt988rgOOBR4PywVLgITNbWHDIbL1/hps/s+r+Eckp9pvWOXcgCJhnga9R4n9B/zODK1FfsAf4aTC88J/xo7PMKzh0Vn1ej9YY8lf37jCUqu8yswjwauAHJQ7V/TuEMeSt7t1hKJG/VwK55z+ieL7NuHtXQT6Zju4HVpvZ8WYWA14P3DTJaZIZLGgN9g1gs3Puc5OdnunEzBrNrD54XgFcAGyZ1ERNE865f3DOLXXOrcB/zt3hnHvzJCdLZFYp9RlmZhcDHwUud851ljh8xpdXxpI/ZlZlfoJ0zKwKuBB4fEISPkEGyZ/VebtdTvHvxdl8/wyZP7P4/nnYOTffObciKB/sAU51zu0vOHy23j/Dyp/ZcP+IFCr1m9bMFuXt9iqK/C/of2Zwg9QX/Bw4L9jnRCAGHC44fMZ/Xo/VWPJX9+7QhqjvugDY4pzbU+Jw3b+DGEve6t4d2iD5uw94cfD8PKDYcKgz7t6NTHYCBMzsVcAXgUbgFjN7xDl30SQna8pyzqXN7H3Ar4EwcL1z7olJTta0YGbfBzYC88xsD/Bx51yxbsvS3znAW4DHzM/7AfCPzrlfTV6Spo1FwLfMLIxvWPJD59wvJzlNIiLDVfQzzMy2AXHgN8GoQPc6595jZouBrzvnLp0l5ZVR5w+wAPhZsD0CfM85d9uk/BXjp1T+/MTM1uBbnO8C3gOg+2f4+cMsvn9K7az7Z/j5w+y4f0QKFf1NC7zBzE7GD1O2E/gb0P/MCJXK2+uB683scSAJXOmcc7Pw83qsRp2/6N4djsHqu15PwXCSun9HZNR5i+7d4Sj12fAu4L/N95bsBt4NM//etRKj54iIiIiIiIiIiIiIiIjIFKXhOkVERERERERERERERESmGQX5RERERERERERERERERKYZBflEREREREREREREREREphkF+URERERERERERERERESmGQX5RERERERERERERERERKYZBflExpGZvdvMXjmO54+Z2SfM7OSC9SvMzJnZy0Z4vm+a2QMj2P8jZrZxJNeYScb7/R2J4L1zwfJfQ+y7Pthv4zimZ4GZ/ZeZbTezHjNrNrNbzeyivH0+kZfmH49XWkRERKay4PvwcN7rjcF34/oRnudtwXHVwev5wblXlCmdm/K+tz9YjnOOIg355Z3PTkYaREREhmum1wnlHTfudQyDXLtfualUnohXWO4cw3mKlguD9WWr3wnqlrJmtq5c5wzO+04z+yczqy2xPWZmPzSzHWbWZWaHgjqt0wr2U72WTAkK8omMr3cDrxzH88eAjwMnF6xvAp4P/GEcrw3wEWDjOF9jKhvv93ektuDf989PZiLMbA3wMHAZ8FngQuCtwE7gJjN7XrDr1/HpfXgSkikiIjJVPYT/ftw+wuNuCY7rDF7Px5cTV5QtZXBncI0by3jOkfhkcP39k3R9ERGRkZjpdUJTQWG5qVSeSPlNRLnwUmCnc25zuU5oZn8HfA34R+CnZhYtslsYcMB/4Ou23gVUAneY2Ql5+6leS6aEyGQnQETKzznXA9w72emYjsyswjnXNUnXTjjnusdwig7n3FR4378LHAVe4JxrzVt/s5l9GWgBcM7tAfaYWevAU4iIiMxOwXfniL/PnXOHgEPlT1E/RyezrOGc2w5sN7OeyUqDiIjIVDeb6oRGW26SspiIcuFl+IZsZWFmVwCfAT4KbAJ+DVxvZm91zrncfkG94OsKjv0tcAQfuP9csJ/qtWRKUE8+kQK54QnM7JVmtsXMus3sD2b2nIL9Ks3sC2a2P9jnfjO7MG/7JuA04Mq8rttvy9v+TjN7IhjKcJeZfaREOl5qZn8xs44gHc/N260teLwh7xorig3NYGZvDY4/GgydeKeZnT6GfNoJzAU+nnftjcG2kJldY2bbgr/vKTO7suD4TWb2YzN7u5k9Y2btZvYdM4ub2Zlm9udg3SYzOy7vuNzf9sZg/zYzO2hmHy+SxvVmdkuwT5uZ/cjMFuZtzw3rcJGZ3WRm7cD/BNv+PnhPj5nZATO72cxW5aefEu9v8Px9BWkpHIorN6TWmcHf2AV8eDjpHikzu9rMdgf30M3AoiL7DOc9MzP7ZJDfrWZ2vZm9PnffBfucG+TLPxQE+ABwzv3FOffsaP8WERGRqcTMnmtmtwXlqw4z22xm783bfpmZ/Sbvu/NeyysvljjngOE6g9cfMLN/Nz9c0EEzu87M4nn79A7XGXwvPxZsujOvrBIxs30lyk13mdlPR5EHuTLdu81sp/khjW4xsyUF+/1DUM7oDspWt+XKN1Yw1GjeMTtNw3KKiMgEMtUJDSePylXHkCtDvDHYr9X8kIhLC/YbrAxRWG4qlSf3m9kNRdL5LTN7aJC/da2Z3Rj8vZ3Be/ZBMwvl7ZNLw0bz9Tft5od5vLrI+V5rZo8FebLbzP7NzCJ523NlolOD/Ok0s0eC11VmdoP5eqodZvaGgnOPqNxp41AuLHKeOjO7x8weNbPGYF1DkKcdwfU/amafNV/PmH9sFHgpQZBvLHkTHP8i4NvAR51zn3bO/Rm4AB9I/Pdh/DkdQDe+t6jIlKIgn0hxy/GtMj4JvBGoA35tZom8fb4GvB34N+BVwG7gFjN7YbD9avzwib/Cd91+Pn1fTB8Gvgz8HHhZ8PyTVhAYAo7DtzD5N+AN+GGXfmhmFmw/L3j8//Ku0VTib1qB/zK7Ivib9gB3W/9u5iPxKuAY8I28a+cKRl8E/i/wVfyX5c/wLWMKx4M/G7gSeD9+6M/XBsd+Dfhv4M3ACcF5Cn0GPxzVXwX7f9z6V6qtAu4BEsBbgLcBz8X3JrOCc30DeBS4PHgOsBQf8HsFvlt+GLjHzOqC7SXf3xH6PvBL/BAEvxxhuodkZq8Arguu8Wp8hd/1RXYdznv2QfxwBl/B53sX8OmC87wYyAC/HWlaRUREpqGb8N97b8aXI74I1ORtPx64Gf+d/hrgj8CtZnbOKK7198Di4FqfAf4G+ECJfZuANwXP30tQVnHOpYFvAW/LL1cE5cEXAQMqv4bp+fjy3N8B7wBOwpdzc+d/K74M8TngIuAqYBtQNcrriYiIjCfVCZVQ5joGgLOA9+HLOe8GTiWvDmgUZYhSefJ14ArLa1AUPH8Ng5d/lgBb8e/npfj3/V/wPcEKfQ1ft/QqfC+x68zszLzrXQj8AF939gp8Hn2IoLF5gW/h64teAxjwY3x91T58fcx9wLcLAqIjKneOY7kwd545+LqhGPCSYNQJgG/ig3cfwL/nF1LQay7wIvwohJsK1o84b8xsLf7/7R+dc70NyJxzDwLnA+8qEZS1IBi6EF//lQmuLTK1OOe0aNGSt+C/bBx+qMHcuuVAGnhP8HodkAWuzNsnBDwO/Dpv3QPANwvOXwu0Ax8vWP+v+PlFwnnpSAOr8/Z5ZZC2tcHr6uD12wrOtSJY/7ISf2MI/0W5Bfjngr/9gRHk1WHgEwXrVhXmTbD+28D9ea834YdtrMtb98Mg3efmrbs6WFdZ8LfdXnD+rwF7gVDw+jv4glgsb5/V+C/ky4LXG4NzfX6IvzMMVOBbhL11sPc3WO+A9xWs+wRwOO/124L9PlCw35DpHuS+HfDeAX8Gbi2SVw7YONz3LMiDJuC6gn1+FZxrRfD6K0DTCP/nNgE/HskxWrRo0aJFy2QvwLzgO3DDMPfPlb9+DVyft76wjJArn6zPW+eAuwvO93Pg3rzXubJFdfB6ff73fd5+q4P1L8lblyuHRgZJf9Hv62B9Cliet+6c4BoXB6//B/jJIOful/a89TuBzxbZv+h6LVq0aNGiZawLqhMatE6IMtUxBK834RuPN+St+2Bwrorg9VBliI3klZsGyZNafE+st+et+2ugB5g7zHvDgnz7R2BHkTT8a966KH4Y9Wvz1t0L3Flwzo/g63uWBq/fFpwr/966NFiXX36sw5e/rhriPR6q3Dke5cIfA434gOc9QG3e9lz59Iq8dRX4+sWdBef6T+CmvNdlyZuRLMA1wfkdcBA4eyT5oUXLRC3qySdS3EHn3B9zL5xzu4AHgVwLnDPwX+4/ytsnG7x+IYN7Pr7F0Y+C1iCRoGv+HcACfA+ynJ3OuafzXj8ZPPYbumA4zGydmf3MzA7gCxApYA1w4kjPNYTz8YW5nxX8fb8DTjazcN6+DzjnjuW93gYk6T859LbgcXHBdX5W8PqnwT65vLkg2Cebl4Zn8JVChUNSDOiBZ2ZnB8McHMEXrDvxhcVy51fhtUeS7kEFeX0K8IuCTYVDLgznPVsGLMT3WMhX+Bp84UdERGSmO4pvtf8VM3udmc0v3MHMlpofBmovvjyRwrdWHk154vaC108yijJhULa8G19RQtBy+63Ad5xv0T0aDwXl5dw17sFXhOTKzo8Al5rZv5gfqjxc5BwiIiJTheqEip+jnHUMOfc755rzXuf+xtyw349QhjKE89OJ/Jig/BN4Gz6IdKTUcWaWCK69DR8QTOF7Vh5vecNsBnrLas65FPA0wXsVpPtU8u6ZwA/wAbnnF6z/Xd7zXL3YHXnnP4YPIvYOjz6acuc4lQsXAHfh56+70PWfyiVXr3VzXhq6KD4aVKn5+EacN2PwTfz/++X4z4BfWsHQvSJTgYJ8IsUdLLEuN874IqDdOddZsM8BoNLy5kcpYl7w+AT+Cze33BmsX5a3b0vBscngMcEImFkNvrCxDD+M0ovwX1KPjvRcwzAP3+vrGP3/vm/iWxHlj9XeUnBsEmgLCsf56yiSzsL3KPc6d/55+OETUgXLCfTPY/DvWy/zcwDeji+0/w2+NfoZwTXKnV8HCl6PJN1DacTneam8yr/mUO9Zbk7AQwXHFr7eCzQWDGMiIiIy4wTllQvxLZ2vB/ab2e/N7BTwc9HgG8O8APhn4CX48sStjK480VLwOjnK84Af0uivgjLiefgeCjeM8lwwdNn5enyr99fih1A6YH6eXwX7RERkKlKdUHHlrGPIaSk4tvBvLGcZ4hvAi8xspZmtxOdDsaFG830KP6TmV/G9xs7ADwWan8acloLX+WW1efjefYV1QLnXcwY5V7LIun7nH2O5s9zlwufge7t+xznXUbBtIb7er7tgfb+6peD9WYMfPapQS97zIfNmLJxz+51zDzjnbgZejg9cXjPW84qUW2GLAxHxBrTEDtY9ETxvAqrNrLKgULcA6HTO9Qxy7qPB48sY+OUOfqjGcns+vvXQS51zW3Ir8+aXK6ej+BZD5+BbbhUqVlgejcL3KPc6N/78UXyPuK8XOfZwwevCnmcXA5XAK3IFkqCFVmGhq5QeBk7EW+rYwmuPJN1DOYR/L0rlVf41h3rPct8XjQXbCl9vwg/tcD6jm6NQRERk2gjKVa8xsyi+ouhT+Pl4luKHqjoFuMQ5d1vuGDOrmJTE9vcj4Av4eXleAtznnHty8EMGVars3AS9AdHPA583s2X4+QL/Dd846CtArqKnsPzUMIY0iYiIjJbqhIorZx3DsAyjDDFszrm7zexp4Ep8o+59DBwpodAVwBedc5/OrTCzy0Zy3cBhfKCzMK8WBI9HGZuxlDvLXS68E3gY+KqZHQ4CZDn7gRozSxQE+grrli4D/uKc2z2GdJSVcy5tZo/hG+GLTCkK8okUN9/MXpAbniHo2XUqfS1Z7scHZ/4KP6Z4rkv7X9F/qMliLUf+BHQBi51zYw2CDLcVV+5LvbegaWYvwI/T/uAYr1947TvwLbbqnHO/GcO5h/Iq/OTUOa/GF7T3BK9/hx/r+0Hn3EiHj6zAF0TzhyZ4LQM/M0u1DNqDb7UE9LaoOq/IfsWMJd39OOcyZvYIfkLn/MLvqwt2HfI9M7Pd+MLYK/BjuudcXnDN35vZg8C/m9ndzrm2gvNsAFqmUkFNRERkrIIhme4ws88B3wPqKV7+Wo6v8PrLBCSrZDnROddlZt8H3gusxbfqH4tTzew459yzAGZ2Dr4S689Frr0buNbM3o5v6Q195bd1+LlbMLOz8PPniIiITDTVCRVRzjqG0ShRhig0VJ5cD1wdPP+2cy4zxGUr6J9vYeD1w0txnyDvHsQH0vLrsl6Lr3/600jPWSSdMIpy5ziUC3HO/VvQM/BHZnapcy43nOYDwePlwA+DdFYALwXy649KDdU5aYIRq04lKKuKTCUK8okUdxj4jpn9E77w9a/4lkbfBHDObQ6+AP/HzGrxY0C/C/9leFXeebYAF5nZRfgu3c84546Y2SeA/w6+cO/GD517In6i21cNN5HOuaSZPQO81swex7eCLvblfS9+Yuevmdmn8S24PoFv+TQWW4DLzOy24PxbnXNbzewrwI3BtR7AF66eC5zonHvnGK+Z81wz+3/AT4BzgXcAH8gb6vMT+IqlW8zsevx7ugRfcPimc27TIOfOFUhvMLNvBGn/EAO7/xd9f/E98d5rZg8DO4B3MvxKqrGku5h/B35qZl8O0vVifE/FXsN5z4IC6WeAz5jZIXyh5nJgQ3Ca/NZ5b8K33HrAzD6PH1O/FrgI/39yFn4OIxERkWnLzE4CPoufS2UHvtfZR4FHnXNHzawDH7z6z6BMWQP8C2Mvfw3Xs/hy7JVmdgxIOeceyNv+DeA9wT43jvFaB/FzlHwCX4b4FH6evtsAgjLbUXyZ9Bi+lfhqfH6BL/vsBb4Q5NUc4CNA/hwuIiIiE0V1QqWVpY5huBcbRhmin1J54pzLBf++hR9uM0Lwfg7hN/j6nW1BOt4LDDYc62A+DvzazG7Al702AJ8Evuac2zPokUPbwtjKneUsFwLgnLsmCPT9wsxe6py71zn3uJndDHw52LYfH1TsJKhXMrMq/H31r+VIx2iY2RuAS4Db8D0+F+GDw4uAz01WukRK0Zx8IsXtAj6ML/TciK9guKigK/m78IWDf8JPOrwceJlzLr/V1v8HbMa3TrkfP34zQTf/d+O/MH4BfB8fGPn9KNL6HvzY3r8NrrG4cAfn3AF8a6GFwfU+GBy3rXDfEfow0IFvXXM/cFqw/r34gspb8eNnfxPfCufuMV4v30fwgaOf4OfN+yTwP7mNzrmngLPxBYWv4sch/xd8q6ZB/27n3GPA2/HBqF8Cb8Tn37GCXYu+v8F1fhRs/yZ+ouihxnkfc7pLnO9nwPuDtP0cP3zDO4rsOpz37PP4Av3V+HxvCF5DXiWcc24rvnXTbfj36TfAd/A/Wt7onHt0pH+HiIjIFLQfP8zWx/Df11/ClwsuBwiG6no1fmSAH+O/Z/8DuGsiEheUW9+FL5/dhS+r5G9/AF/x81PnXGEZZ6T+hP/7/wtfSfQ48MqC7efie0D8Cj8iw7uccz8P0pIM1mXxefX3+ErS5jGmS0REZDRUJ1RCmesYhmPQMkQJJfPEObcfP7ffPUHdxVDej39frsPX6zyOL8+NmHPudnwvwNOBm/Hvw38C7xvN+QrOPaZyZ5nLhfneh68/utXMnhesexv+vfkCPk/vwtcf5eqVLsDXNd5bxnSM1FZgLj6g92t8Xu4DTnfOPTyJ6RIpysY4GpzIjGNm3wTWO+dOn+y0yEBmtgJ4Bni5c+6Xk5ycKSN33+IDhNm8Ho3jfd2v48f1Xz6KY0P4xia/Aw455/6q3OkTERGR4szsOfi5hS5wzv1uGPtvwvdCeB2QyQ0rHqw/PBHf43llh23Aj51zHxrva4qIyOyiOqGZzczm4INZ73POfWOy0zNVlKtcOMprR/DB0/ucc1ea2VeBKufcm0Z7zomiei2ZKtSTT0Rk5jgNP5HzuAwdYGbrzeyTZnaJmV1kZv+F7/H4xVGe8p/x6T23XGkUERGRwZnZ3GAeni/iK1TuGOKQfK/Gf3d/YDzSNgzXB9cfceMiERERmb3MrCaY7/d/8HO/fX+SkzQlTEa50MyuMLMPmNl5ZvZKfO/S1fjekjjn3j0dAnwB1WvJlKA5+USkqGAyYSux2Q1jcmKZWJ+gb7jSA+N0jQ7ghfjhFqrwQ5h8FD+8xGh8FT8cKvix7UVERGT8vRwfLNsCvGUELa//Bj+/C/j5/ibDJ+gr7+yfpDSIiIjI9HMacCe+HuOtzrnOSU7PVDEZ5cIOfIPxVUAYeAw/WtefR3ieqUD1WjIlaLhOESnKzHZSupX0LufciolLjYiIiIiIiIiIiIiI5FNPPhE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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -677,7 +1040,15 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:28:58.854790Z", + "iopub.status.busy": "2023-04-04T02:28:58.854066Z", + "iopub.status.idle": "2023-04-04T02:28:58.879524Z", + "shell.execute_reply": "2023-04-04T02:28:58.877071Z", + "shell.execute_reply.started": "2023-04-04T02:28:58.854721Z" + } + }, "outputs": [], "source": [ "from xhistogram.xarray import histogram" @@ -693,12 +1064,28 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:28:58.883731Z", + "iopub.status.busy": "2023-04-04T02:28:58.883000Z", + "iopub.status.idle": "2023-04-04T02:29:01.706661Z", + "shell.execute_reply": "2023-04-04T02:29:01.700908Z", + "shell.execute_reply.started": "2023-04-04T02:28:58.883676Z" + } + }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: divide by zero encountered in log10\n", + " return func(*(_execute_task(a, cache) for a in args))\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -707,14 +1094,12 @@ }, { "data": { - "image/png": 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -741,7 +1126,15 @@ { "cell_type": "code", "execution_count": 14, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:29:01.709538Z", + "iopub.status.busy": "2023-04-04T02:29:01.708897Z", + "iopub.status.idle": "2023-04-04T02:29:05.896634Z", + "shell.execute_reply": "2023-04-04T02:29:05.894054Z", + "shell.execute_reply.started": "2023-04-04T02:29:01.709481Z" + } + }, "outputs": [ { "name": "stdout", @@ -750,10 +1143,18 @@ "Computing weighted_mean.\n" ] }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: divide by zero encountered in log10\n", + " return func(*(_execute_task(a, cache) for a in args))\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 14, @@ -762,14 +1163,12 @@ }, { "data": { - 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\n", 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Worker: 2

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Worker: 3

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Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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lpF7Ivf3INRY6gHn6UbBpbYiGOiEYBRCcJhCfwtpwL0rJz62kbpU0rs3YWSBLQXNwStqAVYeAnATCUAh45oBH+3oBBk2gbva/vPTPTJJspxb09Dbg16x9Lgas5QZFZ/xsGEA2Tu76GHPEaK5NIJ/Yjf49D93LZojEoMSYue/wOlf7DauYOIgDI8qN1PPIeHBT1/mJWvFgL6tdDoDd29729qSYIpU3v4x2OQC2fL4hoJ1Pw3ImbNzbiTbN15KWJFKn+Ba8guoeFc9wVOI4WmbBjWk6VjyTJhfc9gce6HIPMYR51oG/ryUUvcw6aINgYe5OaWi+wIvvsl7UewjNuiJWZLDqyAeR4WrHeBjY3COkQ7yQoInXuNel4ucYLXPAdmWebaEHWivea9g6p95t4kn3YNkCqHm0hXLISdAxwCbAIITkA83Mp+YzT/asgOD0f8ZoLPYlufyfe7Mq0z60FB7U72SzbRlGp2QBjdk85FGIx+bNhmPoj30sQcirSLhP6N8TuXF8D/kgI13m+tUVhwfmwa66xFFv1MCNsb+ZS31LbE8R7G1ve9vbbTBF2OjlrRe6PABbeNNkARwlmAc1ZOdD3Yst+a+58SzzxLfW3VXvEyujLZZltt4sGLUrzbMNTk0HaDYvwZhFWlJJxTprBrYrmLVrXfEUrRjRzlLTNHre65EwHjTeV/HKovOvAXJnuZ4lFTc0nqyUvFeZp2jB6ZSr88x43MzgP14rg6U+5yQQjgMySPU8YfovjYdZc1xpPM7m/Mrz1hGb8mNt+3gii2XTMYoHa9dN7HrBxLWL5Q/rOk8ltT4L0CRoCqR7QTaBeC3Q3RDiMVagkexYq/cK+ZqQ14G0VjY3IpvuAI1KPBzp11birXfYm1Qs8HtZ7VIArHZd/TJLdnDFc2M9Am9TP0W8WqmaeOSm/P7TAmwVZEh13XO/vjplLOwEumWGgOp8Cl+W7yoSqOPeYdvW9+XaFXANaAw2De2E3Bk1oF0DVhFDEa/u0qAQDSAkWPYA4GCqW4cUOD8HtliZagZRVJQYlL5LsKGCUTqJyHt74rEhogatQaRK0fjHWcC1TO0py1pKIAiStX5VCgUQhglkJUNs8mdrYEsbwC7XSKHIJKCgnaJXE2E9EjvLtigFF+LnKDLl855sOk6ur5BHPKjnN7Xj5yirhwVJGNiP0Yo+oqKPRU7iysawuvN1Vfsg1972tre93QZTz/a4rHY5ALbkiAZgkz3f1YNdpbqq8QhrDuvME3HPM6VTZbGtB7vUMKizo9ZrbJ2Ii1RqXbSMdpsq1jbbll/b5uBGzHvrxKq2VpDW5sXm6F5s0STAn0fL1dToFVzlkgcLbvWdqWXFMNEDNsTHl6ZVKIcuZPsfE0kCo48n94DYeOqUXADXkwijWLVVE5yq03ppHv7dqJRCsvXD4K99u1MFUo33KjOPGCTZNdVeyVcyskpVbWzdj8To9AmT118olMPVgF65wfDs6BXXEdFMftbASez8GDarYG37RiH2ma5PZ5Yj3y7Lew/2aW7tdLwAXclXbafaTaRe8uKL6KAqSWvhwgSYeYr6Qy1YsPJRmbjNs6btS1pgaUs6YEkRbFtveQiRUzxuu08NwW5GM4rEo9V9AS3fV2wi4g5i2qvxh1KKC/LEvbosYeFdW2rgIvxryRLISKUKClDHQTnsBq4frwh9Jt8zkMs8PDoCthqBScgngThO0oM1A8Dp5Br5bzhbyRPAFu6zPArgLosIZvyrABmib59USJtADhHtA3nM5CSsViOrHgiZiM5KifuQySp0MaMqHAvIABIzeu8IonQHI32f6LvE0WrgoBt4xvqYo27D/YfvPfda30qzINflgJltdnnPfG9729ttt32Q6xJYncK7B1o8Oe0jxGjLT220CAQFj05HQQiT12rfoLm4Nv46s927hFoxda5y1nkesGAqYedZLWJq3LJ2TCXA5bmVuQ+kw8DmaiCV3hJSgirFa/V9BqB4r0GriHQMuQprF3GW1nu92cyB4r2amtbkxQrKYT9MSlvdfPZRymaj5+GmMZJiJA+umOXeqOQmcMViek/zvj9qeax7sPV02hzoUkLs16l4zDFBGCGvhCQBkpKjV565t953yXJhPciVXCFscEHxcbAPIK897zco3Xrk6HDD0Wqwaq5uwzNWN3jfg3fz4oO3cVBd7TtnaZ8Hu7e97W1vt972lVyXwOTa8UzCT2KwVK1gbouWchqYe5aNJ7IU45aSs9MuO8cblYYH1oUc7Fb9AZiEYnYFz5bPt9kWL7pyxGU8rjegUUgr08odD6xFTO4tjU2FSYPAJQpVsLYwnZr32m/zXufe6uPxXovHWry7lI2PLdzkOo6kPhBEGZ1/Tdl1fpv2M6rQ94mhi2wyjDHSPRYIJw0fW4bWOvs6eZ8webOFuy1pW0uJQ43u8XtKVa0EU3svbCyHK/dq13AMjGMgD4FNX2Q2QUImp0AeQw3O1XY4K1unPxhZrUYO+pFnHz7GUTdw1G24pzvmnnh8U9f7VlreZxE8vS29+a1IEIiR8Kz74PAAXA+WAowXifC32QM5O2DqdmCF0xqvxYpyVqtwpRMFUPa3Myg2+74289jzcmELzRDa51OBRV6Z7ut4JTIeePbAgWm/Jhd4AQtuGch6RKizfMsiqh3iHFxnhQU3WRY7Dd1C8rVYIUxAXU6zj3bXihLICJ3ujpgHUfSKMHaZUXo6jYQbdjnVL2u1ReCq0ALSLG/BdlmOGxTqUBxo8ZzY/hqkVbn+XnAwCHocLF82atXWrbts7rnmJCjxYKTvR2LI9f2r/THP7G9wNZ6QEN6VrrLK855yt9sU9h7s3va2t73dDlOkVttdRrsUAKvjgALx6tUpeJXU8j1bOcEtwar5jhae7q51t3mu7TrLDm+Zyattg1kzOcGMBNOfneQXYTYfXQbmtpyDBW+C6+FKrdYimMbtuPaS2EMhHZjnWuUJa4DLg1wr1ziMisRM6Cbd11IiG5o0o8cd3CoBLckEBIRZma1NBmyd4tFqlqoX216esk2M1lkhxUBeZ9JoU/VQHLyq78oUyGzyZevjnLRSMRduXkbrwUKNEK9DOMEEdE6sW4TWyjmrICMquTMKoeQZ456rRDvfvk817/jKasNRN7AOI723iLmWDp4UoLOf2t6DfdpbvOce5OoVn46rtXUJoMtLkPN2cG3VraD8qv29HYCx3M9ZRQUNaFbaL8t0AxAxkG2j/gVAdo33jO+1lcLOVcRSL6S1MB4I46GBae7xfmb+6LygwEWgy5w4RNMhLeBa6IAisF1B9nEUFrTbhCZRvvTpUubasMVio4MQUIYcySp1PDFa8r0mQTtlPAiE67EKXktyNqXhy7eJZrdUwekLDWFxQ7XyW6MNtKRllxzbZNdcEugwlSgHrCtQoWNC58UJDrSqdtO5uj7h2YfXOeqs8uFaWjNoJIpyLd1ZLVgz2Rca7G1ve9vb7TBl78E+7S2sD5DVyroAZIWULLiVgrkKwfNaUyPCkvV025VdwaRttos+2BWImgXZ7NgCk5camv05FSC+asnt3WolhzZOubTaycx7temq0QKbq4F0iDU17NyLLfqvnVbVJ3qbniJYxVbIHm+bxEpicE8xWEfUx+O9tlbzaEXZpMhJ6mp2wSxjIGT6mBBR+qZ1ymObdc3JVPdkS1PGNCj0mbwWi+yXKH3w6f2uy7tQ0IIa+J9nI7TP2+11RvJYTm2aeiZKBpJUYR3plNAnF4bJlRJZdYnn3/Mo965OrIOBBt47HLIKiRtiGrC95CfFm9wHuZ7mJgdriEslap0/8Ol/ys3yRXpTKX0ttgTgs/jPmWxh83z53SsAmuy/eHqZzvhEPc3PNqWzM7BtON0qKB4cWNvXnfOuh1R6oAhrp5VO9MBKa6fTWkYaJ1qg75JpD5Qy1psA1/PWKeA61tbdUlOvptNVO/aWY/YxQYqM2eiEMYXFdcVEz4OYKlh2Trxk8RVKACZ1thY4Fx+R061bb36tIllJf8v91Oes5b1nKCxK7DKdX2cR62a86keOuoFNilwbVvU4QdT7dCW6kO54ypQil1pw+/LeWva2t73ddlNg0O5Cj/NMRN5HRP4vEfkVEXm9iHy5L3+WiLxaRH7d/9/XbPM1IvIbIvJrIvIpzfLfKyK/6O99u8iuKeATs8vhwa56K4n1vM9KAYxFqXIRCt6mShXmXuGZNMFZnmzxXjUzS27ctX3JMFiuUgJgW46x1WsqXmyccl8RrDyzt2aGwxVhOJo8V6MGtBYVuJKNCah4DqY4LSDBvNjS1FBughrY9v6ubZaBrHZ5KySzTch72WpGFu8VuoQw6QLnOLEzs+N1mCqXvy7qYkXcpYjCzPOqy8GYMglc+Ut7GA8gHRkNU9avzRQDMFq+tJRAYsz0IRHHzHOOHgPg0c2a47FnkyxjYN2NHPWWVbBCGPOd9qluaUvuEXiFqr5WRO4Bfl5EXg18AfBTqvqNIvLVwFcDf1FEPgT4HOAlwAuBfykiv0tVE/C3gC8B/i3w48CnAj9xqwZa7FIALKvVFoogw5iNEmiqvCqY7kq/2QasQQw4W6WrpXrX8tj1f9y+z6W84UIEXFQNZNtN26oxCn/r6V1KPc+JMrAVVSw9aDyYT1VNfhBPdmeSI2QCVdBaudV3qXYs6GN6XOA6yxhYvNeC63lcYskWaP93khnxDggq5BZsys0jGP9t4uH2Gcy6AIh9bAHIa8e8YLRKe02BU9VelTMo+ymSj2JAntdKOsyW/qaCbMR6ciXsO9D5GP2rEURZdYmQlKvec+uwN/51kyIp27kfxJHOefHrd7gnl3LrKrlU9W3A2/z5oyLyK8D9wGcCD/hq3w88CPxFX/6PVPUE+G0R+Q3gY0TkDcC9qvpvAETk7wN/hD3A7m1ve7vb7CY82OeIyGua19+lqt+1bUUReX/gI4F/BzzfwRdVfZuIPM9Xux/zUIu92ZcN/ny5/Jbb5QDYrtR4Nrmr1fXL0/Q/RPN0lzJKpTBhUj/efazWiy3bLr1YCZMXuy1b4TzzfZZSXfNwTwfVRMw91ZwRQtP5tXhOE22Q+/Lcp60e2JqS4tX7RFET3GNnKlmrmKpIdAlutdH7i9pyWt+W1RaPtahp5RrgOv/aLb3eXJSpYNpeYXI9m4e3ZBHPXS1asFVbwK9XWk/XChqvtQxPbVn1cMvrGkh02gGnBZIQRiGcSBXz1l6tVVz20tqFstgqmBZB18wcDruBIMpx6rgx9BzfaQ9W5WY82IdU9aPOW0lErgL/O/AVqvrIGfTptjf0jOW33C4HwMIErin5I6PJQEBihFVv3KKGia9dgizYsm2FBYUm2JaGNZM99H0mDGh3pYItn287n7Kaqu2Pwr36e8GB2NcPAAIpBsT5xbwKpLXpDlQ5wp7KReaIVRB1GelKxZYSXR1fxPpidQVYYyKgs8qq6dQbwNQJ7LatU8C1TO9n2yCzLILpkojda86gJVoedhKQWa6kU+aAV44RvPOFYm25YfqpykQRNLu4kM1uaJ1vlKTmaWlUxPuIheNAGgJjiMSYWcXkNwrh+tgTOiUjHKeO46E3QW+nQUrWxJDvbDWXBblu3TFFpMfA9R+q6o/64reLyAvce30B8A5f/mbgfZrNXwS81Ze/aMvyW27n3lpE5MUi8rrm8YiIfIWIfJZH8rKI7LzriMgbPFr3utb9F5EXisi/EpF/4nckROTrROR64+IjItee6EnubW97e7LMquwu8jh3T+aq/j3gV1T1W5u3fgz4fH/++cA/aZZ/joisReR3AB8E/KzTCY+KyMf6Pj+v2eaW2rkerKr+GvARACISgbcArwKOgJcCf+cCx/kEVX1osezlwMuADwD+FPC3fflDwCswkvrW2GaAzYCOI6REujbHbOl6wpUjZL2CvvcIQtw+dd/Wz2rp0e4QzJ4VHywzCHZE/Xd6sS21sAhuQZNF0LS1kQGCKjJk8kEk39OTo6k5pbVUSqBErXME+ox2XlQQPFvAE9y7aJPuKOa5lqwBVeF47CtV0IW81XvdZW0WwGx5kwNrHuz0XvFeo5gXF8+Y8YmPPeWAIvbR2F6MvQli/32pINV7tYEoqaEDNCjpQGeebS2pLYua4Fbr3tZAV1EmK9sEO4/gk6qw8ceN6FSBsOpGrm9WpCy8/do9PLrakHJgTBNg3Rh6RNSuWbrwVP2WmQW5blkWwe8H/hvgF0Xkdb7sa4FvBH5YRL4Y+I/AZwGo6utF5IeBX8YyEL7MMwgAvhT4PuAQC27d8gAX3DxF8EnAb6rqG8uCJ5A+Fqna8DNO5HuALxCRb1LVdz/enbeW3/sIuhnQ8Qw1d6cNKNM0zXXaPYHhgi+dfplz8NxmS042bgHQloZo/+/iaHeJyuz6TLyAQrtAXkfSQWC4EhgPLYMgrZ0LXLu4SF8qtrwNd1RrnBenggJGi2T3YWqol3za30mmC7lGsMu0P4tN7cdm+tptSbEq75VOBmMObFLHZowVQES0/ohNtsFpAuTUPL0PqU6ZofnSiQOriqXERdunjKWIQY0XLR+hZ1S0O6otzMvXYHntm+yCuoJQv/26fM93h6jxu2pyhuW44yby0CNXyVnIMfDoYwdcu75GQqP/EHLVzx2T8danCivugN2qSi5V/Rm286dg2LRtm1cCr9yy/DXAh96SgZ1hN3vmnwP80E1uo8C/EJGfF5EvaZZ/B+b9/rfADzTLr2Eg++U3eZy97W1vTzErlVwXeTwd7cIerIisgM8AvuYmj/H7VfWtzqu+WkR+VVV/2r3gj9uxzbcDrxORbzlrx5vNhgcffPDcAfzx//njz17BdN6mHNjqbW5bd/7ivucf8tKX/e5zx9BGk3fvb/H+Bb5z9z3vkJf++XIj3rLBcpGfY45SAyymSTB5YSXTYBI7KJdkKiwoZaLP0QM+7/h3e27s6ZM46xTOuxTz9cyb3FZ6+Rw94As3L5lSTGsyQDMOH3/2qHZ2nQHbaBHsKsGtMs3X085nu+B53YqvvP/+sz+uOhTZcuI6Ld7yfSgfQ81SkMZNDvA8WfPy8IHN7tSc6bT4KpdCCrjQ7+ZW2b7p4cXs04DXqurbb+YAqvpW//8OEXkV8DHAT5+zzcMi8oPAnztrvdVqxQMPPHDuGF75id+58z2J0R6rFbJew9pFYbZNy+svd3r/pV/xEfzot/+HMvDdg9jFsRY7j1pYjsfpgZe+/Hfzo9/xS3W9Xa1rVAS6QF73pKs9m3s7NvdEq966AuMRDPeq0QNrhYOEdK7x6tVZbf17DNaK+4uHl/CDR79Qp/+FJjirYMCGb+PtXNZwF0fb0gNDjmzGjmFRjfSnh5fw3f0v1zEU3deihdBayoHjsWMzdJyMHSg+jfb/yabRmgKaBEmCnARknKL62pngTfloXnHP+/EtD/9HGG19cLbAAbE2UkwmJBM2JuiCerXcWqeW6OUG19yQy7HzOsOhNZYk25ilU15x5f34lkffCCpIn4irhKqQTiKhyzUrUPNEEbzhpZ9z6jO5HabKqc/rMtnNAOzncpP0gIhcAYJXXVwB/iDw9Rfc/FuBn7vJMe5tb3t7CpnNOPYAe6aJyBHwycCfbZb9UeBvAM8F/k8ReZ2qfoqIvBD4blX9dOD5wKs8ENYBP6iq//wix1TVh9zj/cqbOaEnYqoZGUfoOio9fVaAKXjY96zA0rTzKZugWNl3W2a7zECoYts7AlpaxuKb7FLt6qKJbK8iuQvWlnvlQa2Vl8euXHug96BWoy0QPHiy7LMlo9bMgYyQPc+ydC+w09yeEVCCX/mcGvk2D7Ycu5x+WzJbA18oSYUhBx/HdLmSBk6GzoI+7m2GoBOFIILmgIZElgCxBLqCC42bRyixic2Kwjob1aJSsy2mj6mMH/JoHnE8FuKxWAeFEiwVJXeewRA8L1YssCVJ4Gqy4yoowfJlU5nhAGKfmzYZFjkFC9Yqllv7JHCdt1CL4K6zCwGsql4Hnr1Y9iosXWu57luBT/fnvwV8+EUHo6pft3j9VcBXXXT7J2KaM5KyFxtcEDRbALsIPRDDBJpl2yKDeB7Inme7uiqU40bjmUvVVuFei9arAWy2qW8TIS/g2rf0QDP9bq9QqSwC6/IKk8Rg+3zKCNiegL6LUlDfv6VqTVoCqjCmQCw3gwXJWS7fuh9J2QA2jYGcgn00IVUQDEF9/g65y+QxGC4dZCuyEG2m2uUzBOky0tkia0TYHL8Iy/gmeR0Zg/30Vu+V2slAOwPa3Kvl2ESdGksmgexUj4qBZdNdliJrkRcpZU7s6ihGNdzhLIKS4XFZbT/93tve9nYbbU8RXGrTlECCt9HOPo/LFujaZrskBmG3x7vMTihea2utItdsgGd40i6YvdOKelYXyEcr0kFHXsdZeWztWtBrrYHHg1uxy04T5NoLqwSkWr0B9d5YJT81SmYdJxogLL1K2V4Cu8uyejVQDjxy/YDja2sbZ1TiekTXwpgiIolVaQ8uc4qiD4nnHV5j4wX/705HhNhmO7hqVsvgRCXEBKtJVyFnoxBy8hxctVJkCRMVscy/3ZbqbI0MvWPCaPrlbIyykSyMywaHwaNmybxUsgfUCl2SnVposxWSBe1kdB2FJOYR32Hb9+S67Kb5/HXOS/o/S0Ogrbgq75Up/RJoL6pF0FqRYtyig2CtYSIaA3llxQVpJaTewLW0htHIxNMhEwfrVU9l+m27ber5gZPUuTxecPA1AF4VXQKEcdGUsEz52x/fUlegRPyzT2uHMXJyo4fr0abEV1IdQ85CSsadtuBql9ieP7w55HjsSDkQQybn0Myk5/qws8sYCucrBsrBbsqoWCpYuXeeIUBgjQ09O2EIlp3g3Khkq9IShXBiGR25E/IV33ZsETrMGi/WO0IWL4zx16PAKISSCTEYcM8KJO6AWRbBvm335balVxp2BLjKem2wquTQ7rKz2sq01nKorcD3krMFV/yalmkfZ2latUosKXrQGbj2gbwOjGsD2JJTWdKJSjCFVbaeT66O1cVcW3BPQ2s90knRauXlsn1MrKLzmB7AKuBaAlEVYJv/qak6KqWdx4+tzFtVmfJFVxnpMnFlrbeBKv6SsnAy2phDc0PoQ+ZRP8YwRkvJYgpAnZV/rEXkugCogKqSl/flLZ54BdbCmeZJlQuBMBi4xsE391Y9oiAnwc615Vp3mKj5CZINWM1rFWSEMAjBixhnYH0H7LK3jNkD7N72trfbanuK4LKbOvdaCgyW6VQiU3HBKRnDZj83o+u6XHehcaANTyupOVAozQpLZFrQVUfuTZymVGUVfjatAnll2QOpl8q9ppVlEKSSmlWS5517bVu/LIsG2uWCsupGOtcfKOIuwExvIOVARhhSnGm4lqaFSU2kZBgjKQXGIZKHgLy3J2xsmmupS5gHGZW0yqR1RO8Rxk30jykzenrZdDltvNk96fK55ezet06R96p3K80+ZPJiyydhz92z1ollas9NPS2qeI1SZAibwgPffZWJHO6F8YpOnPjJshPH5MlXcRindsQHFwZBBnFNWveYx2nzO2n7LIK9oSlZW+8leMJpcF3SAWX1mwHXHdxqVcAK83W0K8dmNobs48199FbcwTrExiYNqxfj8/x/WkPu7b9GprbTWKpRLDmwzqW2vGvcArgilpK1FMtuaYHCtRalp+LRFH620AKboWMcA+NxB8cR2QQDi1GIG7vYGi0opxF0iHAjwpGQH+1hlSEGbyNeBjgBZS6Alx0IdfpPqVV1LlXEbjrSVoI1H33OpeJL0BXksfDgDqLjNK23/lzlOM0+Vko6EKviAuvoe6RTIEohbJnSb+tSK4NU9JSNiXWjTLq2haq9s3rbdsx9FsHe9ra3vd16U7UA52W1PcAWK4GlGBdUwYIaaNOtisVQvYptOgBn2cxrLeMQQUOoTffsGCA52/IuTBRCsK4ElR4I5qlqZ5RAW1SQeotOp1JY0GYR9GpBoy651F2hAsrwtBYKtM9hqsgCzlRIKkGuk6Gjiy53WJYXjzeFaR6rVO9Vmg40Aef1vJJNMoTHIhwHcudSiyuv2RdQP071Wj1TgiRTYKhkUJQKqk7JKSMNOGimZgrkMUxNJxV0DFOam6dESfO+fbaLD19guKehIUpcM8nUcmaxPtMQ6jaSIZyIXws/R7FkhzAaPRCSLYsb7rjtKYK9gSoi3i5mG7g66FbgKyAoYlH8orWazwbabdO7OvUvmQAhTIDrdIBGQYl1XXWOVXFqYEELWHqWLwti7WE6r9xyYM0ramsYHFwlLFKcZnTAVMHVVmhtA9TyvOUkiyB3bHRKwabbZcpdVaOimjbrqUg9DmA4/+kUhgKjEKsoS6QIp+RePfNAraKpAcLQimRn4zc12A0nd4L0hZydeNcK0HniWeU4WNTeeU9yM/Zmim6DdTD1m0Od2leVrCbTYEd2Q6Fiy4t4IrObEGrXSMr/bGAbj7mjtudg9zY39V/DrqBWU3JaAkkaAlJydoLWksYCsqe8VKiBjhm4tsGt9nWzXgHWnTmyQaruc2lsqA6uWoJa7rXm3oBkpqgPlWct3KWB4tSKe267PdYKoFUOUGw/XapBowK0Jdg1pU3JlEJmhzHQqEEdX82jPRVc3EuV0c5fBBgEPW4uvvOsZd0SGIon9llpNI7XZgZamz7mXut2NYBUtvcy1AJmdRxLD3YBmHX9uoI/S9O6kpvhhuZ1mDzYCpzlmHn6H7ztdxghnnDHbQ+we9vb3vZ2G2yfB7s3s1ZyCU6lTZ1ax/m6rWYk4ZwOqB5vmdbmyYuloQVaqqD1ZsvrhfcqgBQ1LRUYFe0LH+fRdmGKvpcIvHtlNT3LeVSpQ2iyB4KlYkWZqIGSgqUKg4u2tNkBS8vNNDiKop5BUM+/UAZlRp5k7u0td9l4alMF2mTt1LucVxFOMVpVZpxmPIHuuu2r0K65F/JaSAeKBoFBZ2lOUtKjKgc6CbecKupaerM68aLTvqhtwZemAWLyooSNfZbDVfss6/k2pyzJixf83MNgXm7c3FyM4FbYPg/2kpt0nruypARO5bzqxPnl3EwDt3xpWzqgTPe7GsmyvMSSx+q87ox7LdvRAPVWakBNBUws8CVZ7QfuIGJASpPzao/6vPTeclCNMdPFVFO0+uCvHVzbiqwhRbIK14dVHU3haDuZpAhPXRopDf2UxFQllZ0yKNJ9GkzOr3KRp099BpJL2wZyhbtsqYdyA0prey1+zJCwrgCDWK+2bKAsSs0zlQRkId6YXrfVcTNg1TmAhpGaKhc2Pn0Xu2FKhhwthWviUbUBaKvOyn5ekgxEy/HCZrrBlv33N5RwhwFWlTOlKJ/utgfYYqqWD1tANOs8il+yBJJyqs172WYpM+j/Z8DZBrKKxQZkdwq7bB8zOAAlz92M04phVHLHFEQpEe/mx48WhMECNpHarUAEupiqqEvyrgIl4r9xgD0ZLck/hgyuR1DGW3JdDVTteNIg3Cyg5voHmounbtda6w1j8i5rov3yklzAWarnX7hYEcZDRdb2fjyeSkvtOlKBXxovs/Cnkifvl2bfrcfablduGmUfIakHoJQ4aB1j4dBRu9mktTB63mz2ctowToAaBs8SUPvs7XrZBYmDEgYlbi6gu3GLbU8R7G1ve9vbbbA9B7s3dByQGK1td0oNV7r4Ylg/6Fq6Wr3NVvVjm+e6rP7SxjveVj22tDqdLd6vv6wpRvP5c+XjilxhnLwea2zofGRUm/p6vqi4ClbtudVM9YtcYHKx602KjF72erzpTeSlgxBTLU21odm4SkVXsUIToMzWlaDuvSkiYpF7XeSFbvFeT/2Gz/JufXsNhWeertusZxbmPdfIfTO1l5Famio65ZcqQOA0V6vTuuVYxpOaZ9ndUMKoM1pDixcv9tkhUrtP1DQszzYIA3THNsMqwjGmkKaeR6zVA7/TpnuA3RvgerB5mu6nZHmxszYsUH7pEgwkJelMO2AqSmBK6Wq2tx+mngbW5K1GFsu1BGR8m9OZUuLcolperEw/5Nl3u/mBgwe6urY01tSzCu9a8lyThq0pWGMK9uNP3qolmaJWGwjbZm1aVnk9P59y43H+uNda+jlf77zXiw1CAR4P7nnaVbgeicdC95jQP+oKV+N8FzlO6U6iDnh+TMl4iheUIFrpWKuLcan4OALWgcBbxmjpgqBUlTSBms+c1q4dm+Y0fRljPIHVtUw8tv2Mh4EUCyWhzivPKaQ7ZXdjkEtEnnWB1bKqPnzWCnuABfNet3VtLa1cgsxBtph7BaSMRK/sCWqgKlI93jlgVlTxgxd+1F+n6UdYRUGCelEDW4B5asU87cfachePNa2mDIIcPbi1VvJhQnoT1+76RN+Z91lbv4R86sdh3ulcO7UEqfouseq25crutjYPti02qKcY7PrnTrfW8/slmPhUFp5qY9ZvzIsOehO1ASt0CI90rB6B1XvNAzRvTyt3WkDTtB78urdeatsiuwFZKdu1Q1zc5HIHHAQT2HYPVDKQ1UVgpAJj3LiHH5vjq3nC/WMZGZTsQj44R2s3DK10+500C2fcfQALvNUfZw0+Au971k72ALu3ve3tNtrUp+0us19R1Y88awUR+ffn7eTSA6zEaB6sCEYihrmHqBYZn3UlOM9y9uldPLXNlKXgC8Lkyc70DBK7MwoaUxquVVyLYFVkCYVxbbxdTdU6gHSo5KPJe53kCW2fSQVcwDqG095oqbiqTqZXZx10Yy2jbVW0WlHtdh/FO245W78Y1urEhba1UOLBOcptBKfoac+18SiJ7r325r1265HVamQYOvQk0D8K3WPQHSvxRGu1VPnsNNhMIa8gBUuHKzRG1RtoJiWiuHaBe6gubt6W0FaNCJ9l2HReyIOPIVG/i2Hw1K2ueNFaK7lQ43BVIB8EhquBHC0PdnUt0133LJCDQOrvvDd5l3Kwv+9WrHPpARYACRPQ7upmUNfdArQOmgITTQAmzpJBcB5228w5A10DrC0Y41PBQg/46zKOyvn1LlMYTIdgPAoMRw6y66k1dwXXlffailPfrek0bPqfyo/C26vMh2xeifrlWHUjB/1IF6d0rrLeMri1BNpiwXNwUSFrdk7beckCZBROU09xzDX1CubAKkDwMtejROwS/cHIwWpgTJHhRs/6PYH1e2H9aKa7YdP0UxPDrDXlqWI66qW6C6vvm0WnGAoH3nK1aU3lzMNgaF343/KhhMFp6aTzTsDRrktJ19IobO6ZwLW7ngknGclqusBR7jgHa5Ty3QewqlpVG0TkPuB9aPBSVV/brrPLLj3AakpWaFA8121R/aWC1gxkdcoiiKEBWcyTHSyXU6obNgfRUxGLpTXg0i7TAjyYqHZaB9d9hfFAGK4KY1HKCqXAwDMGotabQM5ilVVSwG8aUqm2EpWpB5f/WGpjQVXW3UjfBMWKZ9qC6xJoDT+nQoOirIWAakRc7EXFOejGY4YtXOI2cAUD15XCQWJ1tCHGTN/ZjeDkpEPe27F+N6weycZhjjqJ5SxmLRqN2z4PLyanWie+VZgq8bz4o1TU1XzY0SL+8USJG0VqLqvtJyQToLGKMTGtCDFe2opHQlXM6m7kWrWVu2BVab3Nau6oLb7ud5uJyF8BvgD4TaZPU4FPvMj2lx5g97a3vd1euxuzCBr7bOB3qurjEnq8ZeyziLxYRF7XPB4Rka8Qkc8SkdeLSBaRj1ps880i8hoR+Xh//f4ioiLysmad7xCRL7hV4zzjBOZasO2ytnQ2Bnt0zfJCK6RsGQWLW7bkbBkHo/9vZ9yNZ6yeO6shoJ1LELbvu1elQdyrBgTSOpAOhOGKsLkazHs9cFpgbV1KxyNrt6KCSfWlQE6BPAbSGMnersVOw5oHJg3V+1gqZnXuCRbvs+VQSxZCqfgqDQnLe/PLPnVOKI0KQ8zmZa/ypPZV+MZdv9Xmvcl7naQKiUrXJQ7XAyEoJ5ue4ZE13bVG7zUIaR0YDwObewIn9wonzxBOnhE4eUahXazdzvRZnDEmpwSqR1tKXdWzOdyDLfysqV2peZ/HiXiSiMeJ7rGR/rHRPFo1Pra7nuhuZKvYEhvTeGApfKtrmf5aIh57DvPaZk+FV95WVny7TJEmf/rsx1PUfgl45uPd+JZ5sKr6a8BHAIhIBN4CvAo4Al4K/J12fRH5YH/6ccD3Af+3v34H8OUi8nce713jpm0b31rAta4zyRfWYFQB2c6LFApVUMVgqPOjKpY9O+70dKewC1RpREvfOl1Oq9EDWocTsObe/y+KC2qBAdQfuzpHWFKlioygxXFk1o/Khq1+esZAtrqwLce6C1Tnl8BoghDUOrUWoI2ZrFi7nDrllkl+oJl6T9ewWSY+te4U6SyYJ2JjGcbIMETjQ6Nx0zeeHRiu+PXwYNY2If5Wp3UGrqG5nv7Rqaf31c9yCWxNKl7dfznXUQlDyck2nn28GhmOAvFEvQxaHDwNrE3zVQknmbjJZNe+sBLZxHgU67I7aXczRQB8A/DvReSXgCr2qKqfcZGNbxdF8EnAb6rqG8sCOR0Rj0xaSO2b7wT+X+Dzgb97m8Y3t5QcFPPksW5r0Q2zSP9cLSvYPmI4LdriNttmB7guhV2qpmsB1zgBcMnLPHnGFNBqwdX6bk16r0WpX2MpaDB+U6KBWglmxdCExBsLouBi2UsvqPVS4eYCG602QTn30NlxiDpL1pcssE1tagu4aqcOdg70WUjuqas3UcwrZXOvNYIcXWwl9wa8k7Yr1Rut12Ljx5EpWNWuX8bcgmtND67nwlQh1lyCMCphk0zEB9AuMlztOL7PbvhWWSb1+LZMiCdKf12RrIwH1qdNkhKP8yyn907bXZpFUOz7gW8CfpHtYeoz7XYB7OcAP3TWCqr6ehE5An4G+AuLt78R+AkR+Z7bNL697W1vd8BmIup3pz2kqt/+eDe+5QArIivgM4CvOW9dVX3ZjuW/LSI/C/zJs7bfbDY8+OCD547ps7/5085eoZa2uuc6i9y3z/11493d97xDXvplL9mx7rZj7Tj+1nXkVKnlxDPasZ71zBVf9PEvmrwZKVNX81Bn21eeUmf7El8mOE+Y58u2DRHsx/McPeTzjj/szGngltn8bHl5R3XyzAlAL+hBWVnqRstqqOevVnzV/fdP+1xeL78WQezcNIAeCKyBZ8h0ORrmZEZDIPOTWIzhuQc9X/LR989Tx5r1ytDn+5wuQvWMsxIySNKqHaDR+quV2QqqUz6tH+vZ96z403/gfkLSSScjTCXThfvVhgq7yO/mVtndmKbV2M+LyDcAP8acInjtRTa+HR7spwGvVdW3P8H9/DXgR4Cf3rXCarXigQceOHdHr/zE7zzzfYkRWa3ssV7BauXBrEIXtAAsxrc6orz05R/Gj/6NX5waH27Rcy3bL7nT2lKmj+S+KCfPt60lkaWpoQjpMDAcBdJa+MJPfBF/8xffUjnD3Jd+W57m1PCupf+WdParFpcHLLmwMWS6kAkh18BTdI2CIPOW3eVH89/c+DD+4dEvzJZt42GXNr3PrHX3MMYpjzYJ40k3gVIW2ATCcUCattRfdf/9fOt/erNrK+iUP4vzoVGhyxxc2RBCroGXYoo1W0zDgtcZw4SQm+Cfh1pTwkEIG2sp/hXvdz9//c1vsW1KTrHYNN6KBUBG5s0b1Z53J6YjEDZKd2K5q/1jiXCS0D44NWAFAiFZQUF3bAIxaSUMVwNf+Akv4u/9P2/m4N2ZOCjj2nKhJcPq0cTq4QFJynilM7AF/tWr/8TWz+V22K3iYH1G+4eAd6jqh/qyrwP+DEYtAnytqv64v/c1wBdjpNLLVfUnffnvxeI+h8CPA1+uunOUH+n/P7Y9JZ7ENK3P5Rx64CKmqr8qIr+MXdCffcKjOutYKcEwUrIEqjbBLCnUf2jblLNK4GkXuO48sNpjFKQEsooXvE0MBgdRD2rlbuIAa5XR2iPnnXOusXCuznW6dytBCbWCa4rit51kz71ui7B+bZAoanm/nAbYAqzBn2/LhxVRcnYBcc8BVRUDr17JoxLSPC82d4qujE+euZLq4/HHqrd83ZSF7MpgANpZBVwV/AZSakD4wNYTwYr7UiCVSrMuM/5nG9S7MEjAqgvAus1u7IYwjkI4MRHxsPHY6jGUvllFY2A8DHAUSb3lM6eV1Aqz7tgyCHIU9DC4yla5BsJwJTAe2Heov67EG5nu4RugSngsImNbxXD7TbHrfIvs+4DvAP7+Yvn/qqr/S7tARD4EoypfArwQ+Jci8rtUNQF/C/gS4N9iAPupwE9sHb/qJzyRAd9SgHVO9ZOBP9ss+6PA3wCeC/yfIvI6Vf2UC+7ylcC/v5Vj3GU6DqaOlXpX1VLsxhfnIFuseracDaKN1fStZRpXSjb56IK15K7Q4VO+KGj2pdECTCG5bB3UxHUro9SJCvDAloRyo5i8VoleOSVUz7R0Mtg69sZ7DV6mlCpYule7ANsCprkpuY2eoZAWZbhpDOTSujtPTWeKALf4MVUyugaGKYWs0ALS5ab02M9XBQmZuEq1iSO4qHhI9EzZE2MKDuwG6DE2N9OFyLpqrtkWEpTV1Q1WcyL1OOr71UMr/c0pkDcBOQmEk0m9S0pzjA6GIyGMRlONB5Z+JclEXg4fGsyzjYF8tSOXstesdMdYqt6RfSetw4HSXRuQR2/AjRv2/YuLE7kDdquSCFT1p0Xk/S+4+mcC/0hVT4DfFpHfAD5GRN4A3Kuq/wZARP4+8EdYAKyI/CFV/WdnHeAi69xSgFXV68CzF8tehaVrXWT7NwAf2rz+BW5hru7e9ra3O2w3F+R6joi8pnn9Xar6XRfY7s+LyOcBrwFeoarvAe7HPNRib/Zlgz9fLl/aN4vIWzg7qvLXgDsHsHezSYzzooIiYq3ZHNnSxhvmvOx5ts1rbaUKkz2XNJqoDJ15sc04JNmnnDsm6bzm0HO5QiyZJGMlu7Uo/nRaVt0GZrmvdao/Ow0x9UXRuUgLU3qXtKWxTblssdarLXm1MeTKh6YsJuKdzfPDKQSCTm5QZko1c8+vHsGUT5z+UGI35XP1fapaCeVYqlKLGwjQkRmbc211BmoTSLuSlgPc8NIHnfWYGVNomCOdnVcaA7kL6NrSxfIq0l23c4/D1HrchHqM8kFNSNuoIL+mKyuE2NwzlUynFYyHUnUI+uvK+uGRcGOAnCBndDNYbOFO28Vd2IdU9aPOX21mfwv4K36UvwJ8C/BFbAdGPWP50t4OfOs5x/718wa3B9hiJXsgyFxRS5tfdg7bv6Db+NKF3utStNvq1Od8ruaMDP4rK1RBw8e2avg0Pzhb6PEYCs4IJUl9yhbwaLpzrYUeKNVUdZgteKvnuBbFKw94AbXbQQHO0JQJ5Ryr1msFb+YBsCLMrS2ga3PpQkZzmHtBAohXZ520dxb82OIcKcQOui7VqrPjTW+iMv1IF7Xuc2y41i4a4ItqpSrKDajclErAr/DFMsC6G8kIfZccfG1/SaVSKCdjx/FJz7iJFthbZ4arweidE5vWt00qS8PDtAY0EIaOcCUyHhm4Dke+XgfXnytV+DtspuaG6Z4VcK+nWQscHnCn7XamabXBdBH5u0we5ZsxgZZiL8L0Xd/sz5fLl/t94FaMbw+wbhIE6Xuk66bS1yK2Df6rz3PXsd3eu8yeUis61Q3BwTU1VV8i1kKmvC4PkRlAtuIjsxYqjddqbaS1tqgu9RLVe12Aa2iCW13Mp9prL73Zwp9mFXr3CHel4dTSWhUI269dW34rPsZQPG4gk9GiWN3icKfICSZpCMggqMbq3ZKVTe5NAGU1Vg/UyoBDBclyA7B7qwNoUK87sWCYxT7z5O0CXcj03hAyjpmr6xPjsUNmdC45iHIQR1YxMebAu4+PALiehXTcEW9E0oEJZJeusKKufra2IonuunmpJ/fB5p5gqlkC6WhS4iLAeBXiDfN2rXxaGK5Gz2YAXd/HtkyW222K8dK3y0TkBar6Nn/5R7HSVrC0qh8UkW/FglwfBPysqiYReVREPhb4d8DnYTGi22J7gHXTlAzHllN/T2uZdTVYfknrOu6F7PgSbw1yudfcUgKlQ6xpnDrIYhU6NbUrTPsrLabx0s0sgna2je/UwRVidKnCxnMtaVl1aGLBqN77a0EjQdhkBwwpVjm6sAWMg2gtuiqg1loB6nI5Ysg1MV29LDYEqBk0WmiPcu2owCujKUzpqOCqYRrsGKXeetWPdVwi6sE6PRX3qffImEga6rrtx7rqRtYOnkGUe1cnp1rlBFE6yXQhkVU4Tt2k07CJphecxVrXqJXsaqfkw2zZECcBuRbJK9g8y6iieN1mMunAuxsrFUTBwLnkEotaqlZehzveyaBanVI9cRORHwIewLjaNwP/E/CAiHyEH+kNeIDdC5l+GPhlYAS+zDMIAL6UKU3rJ9iRQXArbA+we9vb3m6r3ao8WFX93C2L/94Z678Sy0RaLn8NTTD9dtoeYN0syBVOp7HUXlk+ZS+NEAuNoM163hBR2mDYtn3l5hu31JqFKtRNEiRSvVhJxXsV76/k0+NsdG5tiOcpPySBUSA61xom77UqVzXeKzB7nlUqTRAaMe258pEHthbeaZRM8gSQwnZUnrbZfyk0WOrF+mkYuxDU+NssVRsWsEDX2ES5FEvu3zDlJSvkEBhD5HA9+Mcy90i3BfXqeTTCB21g7kq/YRVS9WAP4pRfGkIme+QxuGuZNdg6K7i6OuG960MevbLmxjuPXBjIPO+wHlmvEjFm002415TO+oORnIXN9R6Op+sfNoGqnxAgHRoPa3oKQlq5F+uCP0+GFsEty9N6kkxE/gvg/ZkLbi9zcbfaHmCBsFohh4dI30+qWS0Itrfgwp22VELLmwK1x0n5Zm1T62qA9RSloEVV3xS4hGnaV/6HBOptnsVrJGp5phgnGaLRBZZfa2pSZeoNp8F1MYT5cAsn2nCX6gA5arCbS5PX2gaz5ozLAkTFCg1UlGEXv12KH4KDrKgpgpXusDbAiad13lQyqAa0i4zAyaqj7xK95BnnujzWNivrSpn2S2YVE6swImgF0ml9e91JrlkKV/vMQbRgWOFw3z5E0hAJXWa1Grl6cMK6HwmiDMmq2lbdSMqBG0PPY0EZQm+VZanc2JTxyLNNkkxZJmri6yXLJAxbT+022+kb591kIvIPgN8JvI5JZkg5Xeyw1fYA6yZd555pdWvKOwa2LX/aBqHaZW0H2jaVqw2WlX3vAtdibe+u4O1oEERdqi5bNRNqLUZChjx6KpfzqBohaCAHyF2w4gIPcNXzbooH2kKBAkChcJXMCwlaS151lRH6YN/BwbMILmqlbfgwzrcTsbYs0lDgNWOgV1Syn6uVsNZAYsE7FfR6JK+F4dDa2uwC123WrjcrFXave8yWEbDJ00+pauZKnoAf82I3ObLJkePR+Niuy3RdZr0aOFoNHPUbOr9Rrd0rHl2prGjlSsxoDyqBHIyLTVcT4YZlP5h2gfVis2tgZbrpkK0SjLfd7m4P9qOADzmjlPZM2wMsFuACpvSsJU1Q5Axh8mxzCd0zgesu20IDFKtBqxasC5pkEJIFQkKo0/x47KLbB4Yz3Q0qoBY9AhkBNQlDgpAPLJpfc11rXG5K0ZLmPmKnKMsCpq2gWVKwaKiDNjvgPCvOftv88BRdULxYkSn4F7On1VEDRZJlLsunEBA0B/K9UrMgYHe+71I8vKxbMyhE2aTI6IG7rMIjm3Vd1zxbqxzrJFegHHLk+tjznhtH3Bi66uWXPOKUA8djTwyZw24giDLmwCZ1HI9dFUQPnZJxUXKnZ2RltJImvxlFZ7U8uyQ/Cc0OgdOBybvPfgn4z4C3nbfiNtsD7N72trfbbHcfwIrIP8V873uAX3Z1v6eM4PZdZZoS+fp1wsF6CmAtPcryvIhl5KLOoacpgC0KXC0VsPRaRS39qjZLLIUFOaMEowhyhtF2lw5i5V5t+mfTfqv2oSpNldzKQQJ5Hcmd6RAWPYDSVjt6VdKuPNUqJrKcujev2/xY4KZbgBRPWj3RX9X37x7a8ljNxbSLEIwXkQxhkClPWKak/TRETjr/yndpa3S71expvdf23EwspvXWA9eHFSLKOo4cdQPPXT/KM/sb9JJ4RncdgHds7uXaaJ7uyaYnpYAEra83Q4eIcrge6EOiC5nB6YTjTW+6BsVjdephqlVxyqSIq5e0tei5td2TFODyod2F9r+cv8r5tgfYYikZeK5XThO0LQdKJkHGIkdpel1sGwXQgmv91Z4zjswcZCvweg5sVuImW6vuhiYGvLUzgMJJW3oJsjH1Jc0KkZqPGZzaiDumy6eGd860//EENKb04lItZd0MTBWynBy17mJuHt3LYvTAKJaw710CbNA2Zc4psLnRMw6Rvk/0nUXrZzwrBqZ2/KnIoJxbOf84C+jBKo48c33MCw7fy/scvJt7wjEv7N/DM+N1kgZ+7eQFXEtr3n18yPHQGfbPAoaACOt+pPd9jzlwPPQ8dmPNsOmmG0JzEUrRiA0qIxFqwcvoVXDJaY+AZSzcabsLAVZV/28AEfkmVf2L7Xsi8k1MLa7OtD3AuuXNBh55lNB1cHiwAEVxJaLgSlvMvdY2LWsR4FqCqzTZBrIosa0tZQrIujSihGCerJOkYWM9pnC+UYNJ1aUVtbGhyRYasOBerR4HNOTa5yp7zX8QIQF9yAwaCFgwJzZlsdvSqHZeyx3rXSRMYKWz5XJK9awLINUI3rb9h+L5M7VvcT5SksBJQFd2eQcm5as2dgYTHpTAUgVBH18ICt3E4SpW2fXc9TV+z9U38tEHb+C5MXEkkWNNvDV1PDTewxuvPYtrJ2vANRiwxpPSlOD2XeKgGziII8fJQDUlK0wgifdTcz2Jzr8fAt2BzazUPWvtIY/B5BJHQUextL87ja/K1pnRXWSfDPzFxbJP27Jsq+0BtrF84wZhcwXWKwO7XdzRUvu1LIMpP3apEbsA17b6awmywKzvlGar7NEQ8YJ+wsalFEuEuLcqnnRgwFoeGtUizkEtWDYGUlQPhDhFIUoserH1dJRdKUvtOqeu4TngepEWzjGoTRbEMhuWRymZBb5nX2jAq8EAuQCsepSuuwHp0PIhKmi1QTXPsT2129K7zDMXYpfJaqW0XczucQtjDhzGDS9evY0P7AOHcsigIwOZh/Mh7xmOOE6dd+q12cPmRo8+2sNBgqj0ByNdyDz78HrVebgeM12XGGMkj9G1g0Ek0/WJdT8SNfOMgxs8dmNNbqreUoCEecdSK+buvDt5qwoN7qSJyJcCfw74ABH5D81b92A9Ay9ke4Dd2972dnvt7swi+EGshPYbgK9ulj+qqu++6E72ALuwfO0xQt/bVDM1EoVZbcpeU7oWLV6g8WKn4FVJUZl5r2zZ5ozbvLRve3BDstbKrrqec7ASXZsArJLLK5vSoZKjkoMS+qnuP+eAuMdU+L9la5iWfyx2Ucqg9V5vNjf27BVo5vPl2lMDO2Fj1yGeWKArDGKFByehdnvIcaro0qzzfUoJIrkXW7zjkOsvZxWskuuZ62Pu7Y4ZiDyar9eZy6DKW4b7OMkdJ6kjZeFk6Ni885DVuyP9IzDcGzl53sjq3mPuO7zOiw7fQx8yDw+H9VQf61JV4jJvGw5WA1fXG+Jx5spqw42T3tLRUiCNwToslOsUjHt/MqbrF0w5fkqZqr4XeC/wuSLye4A/gH0z/l9gD7CP1/KNGwCEkyNY9ZZVUAJerdhLDYLJlHXQZhJk58pagN5mZ82f2sKF7NxsyTxIXvqqSv+YkbbiU+M8eE6sl0cWxSVRYYjB9FZJXgOhpuSvwkE3surGxRAe/w9yLiR2s+DaXG44lUlQp/YFEX2qjjJVLo3QP6ZoFIYrEI+Np8Y5WY0K3sNLXShnEpARSrNEqR+/2P1VAiLjLDg25sDbT+7lNfEDeHj9n/jg1Tt4VlDekla8eXgWb7vxDG4MlimweWzF6qHIlbfCcMVvioNN4Z93cI371w+zDgNX4xUOw8C9q2Me2Rzw7uMjTkYD6RiUe9fH3Hdwg25jpbvvCUeMpXOCB7gAb6PzJFGhnuRxt5qI/CXgs4Ef9UXfKyL/WFX/6kW23wPsFss3blSgjc94BnL1ytw7Lb848RSmJh2rpm0VdBjztO02bYJzswqmYJqkhKYInb/2bqHhJNODN9mz3lLZATZHD3xF8+jijUBOShYlh+w3gABMUoVRck3hatWhLmJzUe1yivPtlyLc26x410sTLzIogaGSiqVRq5oYUHVS08GUetBdNy+2ygEGLHBEEzsrAOv9ttp91k69UUlNlkkKwlsefQbv3RxwI/UMGukl8RYZeNPwbN56fB/XhhWboePGew9Yv2nFlbfAeAQ3XqCkwwyHCVXh4c0h7x6v8ILVwzwj3mB9MLCOI1e6DVf7DcepMzlEhIM40klGMYAvlWZJtLbaqScf/Wa/lNO87fZkIfstsz8JfKSqHgOIyDcCrwX2AHuzJl7BJeu1d47NRguUaH8B0fJ/QQlUcM0L1NxFDczqPzkNwFuWS0rzwJhCHLK3bA6EITAeWg16EQBRdYfM82JzD4xe3ZQUcWGWkzFa5kB0Ob8t4HgR2wbKhWIwndVJL5WYXaZwWn9MgTGFmqs7nfx0OeosvmgEhOKJSgXKEvArDQWLGI6JWluwCNf7KxkI9VDjJHA+pTU4KHdKjibCkmIgHwZunPREyVwb17x3POSNm+cA8LbNM3l4OOR47Hn04UMO3rDi6putvPnkmUJ4n+vkTazncX3seWhzlXviMesw0Evi2f2jXI3HXOsPeHg45EbqvVIumA6EX8suZsaUiQ6immVeRVWyVO603cUeLCaBeIC1pwRr9v6bF914D7B729vebq89WQUOt8ZOgNeLyKuxW8UnAz8jIt8OoKovP2vjPcA2JisrMpAQakWXlMqf4qW2fbuK7VLegtNe6q71yrJtHkazXJJ7ah6wEEBGmx5HsnGzKSBJrH2zWntv29ZoAjnAk2UtIT1nq+4aU2RMiRgCvSRiyN5+O9T6/WlI53tChR4oSftjitaLyr2qrkuIy2QVqmBMgc3QzaqmYJq5i+Dta8pBvH13Cf6N1AILXFUqN4Ir6KQqpRGbMpfglTKPeLcZYFigsOgc5BCshbh75SkHNsm0Bq6lNY/mA4bc8Z7xiEeGA97+nntYvWnN+t2mC3B8H5w8Cw7XA3k1su5HjlYbDuLIo8MB7+mvcF/3GOswcCAjB3FkHQYCmYc5Mi9WlKCZIJmr/YZr/YCIMkQTzUnZg13Zuekno2S18Nl3r72KedPWB29m4z3ANlYDXEdHyGqFrHpoW8hs41BLYmX7Xltw0L7eBaDtdu2+m2W1bJZsmQFSppXW6QBABkUcIDQE042NzBLureuCEJKSN8HyZEXJYkCbNDAmo0rWcfQy0XZYj+/HUrYTL/Ms1HVrpRHh7svjN5JGEKayMeJRcj/PXDIqGtEXUWoJbQDiSbn5eMuWkaqdWpSo2pJboxa8zcxJQAcMnK9YXu2YIo8NK947HHJfdzDLxCjnmj1XeTyCvFKec/Ua/9nRo3SS2eSOTY6MGrg2rrgaj+k10YeBAxnodeQkGoCH3FWaAKzUeBWtNU4fMhsH2Rupn6iWJ2mqfjdmERRT1e8XkUPgfVX11252+z3AbjP1wFLRJaicazgbIOE0uJb93awtj9Okc0m2TrfqhQYyZu9E6xk5gxI7JffG9cWNSdflzkCiRK0DkNWk/FQTfZ9IWUy7wHm9Ij94M5Vc20+nVIY1QOueaM7CkKNVljXH2Zmm1cRuWtOoaGeyjWExLRUFknm4wan1WW1+noAgBOB4ykZQB20NmBRgtAKIkI3LLR5aDKaclVV4++ZeAB4dDrg2rJBgmq3xRGpkPR5LbStzpTuhy4kDLa15gukQYEGzIUSOwoZerP3MJkeuDWs2OZI0cH3sq7xkF22dHK1SbUyhjvFJAdm7GGBF5A9jugQr4Hd4e5qv34u9PEETCZam1XXzaf42gN0GhhcJXp21j2Lb9AwaQe5qqkit2lFkVMKghF5ML/bEPbuAl5L6FDxbGaV6GtSYvBtszGzGztpfS2Zw4cJlV4Klbcs4KJVi5mirn5ZNr7M3IUyeKnbq9BsdgJo6hU13pbiWvlvLBNAmu2O+L3U2QLJRJere6ayBpGORBrufaollJs/IyFggLXvA0D3drk+su7F2NjhJHaMD3yMnBwzHnX0tGvFrHeDRkwPe7dscxoEQbNZwI/W89eQZXB8nGcRnr6+xDqMFt3LkOHVcH1YkFR4bVoxeJVbWnzUbzNztU/Uny74O+BicGlDV14nI77joxudKHonIi0Xkdc3jERH5ChF5loi8WkR+3f/ft2P7N4jIL/q2r2mWv1BE/pWI/BMRuerLvk5ErovI85r1rl30ZPa2t7099axISJz3eIra6EUHrV14tOd6sM47fASAiETgLRjp+9XAT6nqN4rIV/vrXQIIn6CqDy2WvRx4GfABwJ8C/rYvfwh4xRn7ujNWigzC4h50EW/0Zr3Xbbarr1fZf841hxOY6u69KEGSuqeqhAFiJ+TBvDK8G2mp8FEXbjaPJzjDoeQwyRkGUYaFBOFyCr+rHQxY7KjlTu0UTdildp9tHNKS07ktRlh7crlXW8NgyR/KTPClDrN4kL6syD0WxcNyaXFHWZWaB1vb9PikoX/MHMKhA2TqdGAdCzqO1brIHo+dBe2OI+trQnfdjqWdje8d77gXngdX+w1XuhNGjQwp8ubHnsFJ6njkxgHXHj0g9pmD9cBzrl7jeYeP1RxlU/US85hTk5urwWUfpWo3PCmaAMvA4d1nvyQifxKIIvJBGG7964tufLMUwScBv6mqbxSRz8Ra6AJ8P+ZC3wwoRlyXivlk7nuAL3CZsAuXpN1yy9kjJedIEpZFbcVWW9W1K4ugHmfLe9t6eMGksgVGCZQgG80yb3EjWQijEgYhesFBWE+nJCU+J7hCE6QxQp8QL58ds+ueNrha1KXKcztF3cnP1lThArTIbP0YlNKNowRiigSfBWe05s1WBbBkZaCag6lEdQKPdlULNm4MPGfgWgDUby5FzrB2P3CgNWUyp9F9uQYqdVDXz0Bv7bOtmM942fceH3Jts2aTIsMYGVPgxrU1/UM96/dAf92UzsboN4BHeh7qrqIKzzw8ZEixAuv1R9fooz3dtcDwzIQ+A97bHXK133i7msCQIlnhxDselECh+g1zPIloA7x7Dvam7WXA/4Cla/0Q8JPAX7noxjcLsJ/jBwF4vqq+DUBV39ZO6xemwL8Q+1X+HVX9Ll/+HcA/wOp9/2Sz/jUMZL8c63t+x01K5kAQ6Fxz4KyWMK1taw+zLfugXb/d/1meK8xBNhsCSNYavJoAxDjY6IGfMBr4hN6HEICueGqCNt7ZFIAygG01UFuALcM01Ssqx7fUMWhPJ+jU+2vJ5xbgzVlqK6usVnufUyAnS5zXISCbYIG6JMgVCJtGpjC5FsPCcxWdOFXFgl0zL9cfEqagVtln6vBOvba/dOSSkFcSAgxDrNVnKQXGTbRy1ZNIuBE4fCesH7ay3TIRkAzdtUAaDnjnwyveeXW0G3YS03B1fVtK1oIKwxh55/WrpCxsUrSbTw4cbzqGoSN7U0jNgTQEGINzzfKkTcOfwtP/c01Vr2MA+z88nu0vDLAisgI+A/iamzzG71fVtzoAv1pEflVVf1pV3wh83I5tvh14nYh8y1k73mw2PPjgg+cO4LO/+dMuPlppsgeKJ9oEZ5Z23/MOeenLf/e2He3c5vHZdu/5vucc8Fmf/4GzZcoU5CldaAkWnKkdR4ODrE/TC10gYtmSkhUZGs3THTG+Z+dDPu/4w2brbLP5W2WKPzn4ZWzTin7dRU36sdAayBTxd6/2+auer3rh/X4gmU35Z4dsvNmyzrYffwlylW0KMLeBMw1ar+PzwoqX8UFG05RjrQR6kF4IhyDPsAPX84TmMyrPdR6HWn6Fogc3b8zfeh5r/py+2Dz54qkD9OwMbF3kd3PL7C4E2KZlzFa7HVkEnwa8VlXf7q/fLiIvcO/1BcA7dgzkrf7/HSLyKiwi99NnHUhVHxaRH8T0GHfaarXigQceOHfgr/zE7zx3HQDpesKVI+TKEXj7GHUPVhbood5t4KVf9hJ+9DtfP1s+2+dFiwzqBqd/EDvLGwP8sS99CT/yvb9u6UIl20BAu4BGIa0j41FgPAwMh8JYPK8VjIc2xdVeyZ3ClURYJfq1Jb53MbPuRvOccqhtXWLI1Yv9b258OP/g8Bcq39d6pSUJH4wT3KVpMIzGO9Z80yxVDUqCi10nMYHT40DYhOqpShK+/P3v56+/6S12+UbLmpBxUhRTv5lUbzUVj94eyyyC8dCu0QTqvg/XN8i9aRnkTtF15r+77334lmtvtFbagxBOAt0NQUboH51KdVHIZb+FpmkaVY5HpksgpTCgU+icIwekM7SXoIQ4fYe+cvUBfOvJb08FBdkQWwdBiujLgip5wx//E7u+gbfe7kKAZWoZ81Ks6eEP+OvPxcpnL2Q3A7Cfy0QPAPwY8PnAN/r/f7LcQESuAEFVH/XnfxD4+gse71uBn7vJMe5tb3t7CtlTPENgpzUtY/6KqrYz7X8qImc6iK1dCLxE5Airwf2zzeJvBH5YRL4Y+I/AZ/m6LwS+W1U/HXg+8Corh6QDflBV//lFjqmqD7nH+5UXPJcnZGG1Qo6OkMMD413bQFVgEs1o4wXFU5DT79V12ql96WpwTjls2wyx/L+oSEdd1xVeJCthtKllHEBPTAQGmvideusZ9360qagqkWkLdmX/wYjrzWh9L+WpnLad+relstsKCApn2V5TbTyuOpYUYGPtTygeZ+sRZ5kqtabTmlVv1ZJXD2RJBk3NtSgBrboD6hS+eMG5M89SXVym9j8HSEK8EegfleoZa4AUzSOun1E2r1YytTik5CbH41Br9zOgRa9WtMpV2vVsrmEPeYg1q0QzVVltRovk5vWdtLs7i+C5IvIBqvpbAJ4D+9yLbnwhgHWi99mLZe/CsgqW674V+HR//lvAh190MKr6dYvXXwV81UW3f7wmMU7gul5D3xk10Eq7xbJys8yj3ednE/t2sWEHMnP6YFvbmHbzZlkF2xaQ2+ft5oVrTM3z3PCMzTqogWtKgZQFx+FaZQWBEJJLGVJ7MxZwLQBqPRp1psQ1Fbjp4nTnHW1VIUQlhEQaowVqnCIIg4FGASNJE2iWQFWJ8rdeU+U4HUDL4dKqYigyQhwW1232AUz7mThrPw+B0Cfy9VgLOMq0v1aAxYmaqPRF4XfVqIquVIYJVcs3E9DRqILWNFrJsZYbzWPRxpSteMTGoFup+zttd6MH29hXAg+KyG/56/cHvuSiG1/q6bfEiKzXhKtXoO/Nc+079HBVOdZip7zUjJWswhx0bzLZ8DzPdCuHO1thGtMEvIv3y39/VC4yG2eJ1/irKCFmYsyVT41SsgROj7O26F6U0apKdVranNdlulfZNpRUrTI+z9u0ftMCg2UMVK5UG7ByMC3PpwDYBKRFfLzcZAofWrIFxFOutG1t3XivNTfXjwPCeJCNG00CWUjXe+ImEI+tSmwWEBPIvVqx5XWZ3Y9bfjgOzvOubFlpP140JdpAmPjYQgauUuUVZXBwjdgNPU7XtSmEu7N2FwOsqv5zz3/9YF/0q6p6ctHtLwXASoyEw0Pk6NAyBHKeC7isVrDu0T6icfJcdZKyP73TMHld84PJ9vW3LJuVv8JWWbezAlztMbeCq2ptLRPGVgiGKdgzWPmsipzSD1W14JQdYkr8r90EbrL0sg1+FeqhpQ3a9jStR23eqjQ0gHuvjScYBiZPfXGD0WjeahgMIMv5V+BxMBqjtZcJg01YEtSZiwTzzEuZ7fhMJRyM5BNrRNm/J7J6r9A/YscoQbLcAQdeF3KghM4FZnQan2TbJp5448r15PnKKKbLG6Ho3UrxVEepHrmMLlgzmAecxdLzZjOscuO6k3aXcrCtOaD+wuPZ9lIA7N72trcn0e5ygH0idikANr7/+9qT0HikIhCDpzNFu8uHYJ5g4V5rt74FP3pRzdezbBtv62Wcs2M1dsrj3WEaxaeVJlk4dVyYptQaYbziHqUHbooTnFKwyqQ8H9A2dSvlbE92WeVVBF5aUZJT7WHUxqCNlzcdrN35NIkovPKMEmm9J/dUc3mv3adMXq0O7hW7R1mDWxHGZ9n0PYxAFnSIyBhsd0msyaKnf0mahGB0dA/TvWft3BtuOOQaQCuzi8I+NRyz0nZZKGPT2Xrm+arTImpVelKum9SqvTtpsmVmdlnsUgBsuu/q7LW1XbE8UWDCkADa9FqypHWdAlyqXsljgLoMNtV1nqhUITvAdZctjln1X3H+LxqP56dUf8x57cdIMvGFXt+fs03jO0zRqouZgHKWklY9/mKdFmRrJ9td4DqdsNEDoxj/6sEtvzhoJ/PK4TCBVylpnWkbpIaLbXnW5b2yDQSW3FnnrPvHYFQLXsXHAnrsR3+mEE+mbYo0ZC4UAU5NDIJ2ytjwqyXohU5BMWDikmX6zGbFCA2vWv9Hu1EiWF5zmK9zLp+/t60mIvcD70eDl6p6oVStSwGw2hfPFfvCrTycX75v/qUunl+p3pKUzdXIOv9yzqL/5xx8l3fbgPq53Os2r7XpyUV2EKsZBOr9p4xr1mQ/3go22byz/r3BkuZX2lRqTfzqxI8uxtaWwDbbhAVabWt2mPPpgoOtWgY11D+lG1UvU7CqpjwFf3JPraya+ErzLOOJ86IN4JToPy2IjrZe7iYwJk8fcdhYMF8j1liy8ThLr7MC7tlLa2sWQQHHAERInYnxcGycqjQCPBVkpblxlIyA9t7dXrKmKs+OsSA/l1Vid9LuYlwXkW8C/gTwyzgtj53RHmC3mpYvsMymLnVaHayNiqiiIRqwei6p6QXkpiXJ4ptzUQ8h73i+zXZRAm0bmZzRYFPVCrLqJa+jIkMmdK4LmyAhFQjCYN6tlNzOxY8wuP5AHe6iUsuGqFtA2Ja3IFtVs5rX+QyVJwkNKJRpbrmviOeyOmCmFbXiqY7BQSfVjai0weTVNd4ukPxGVINMzYBrPq0HumScaIDsqdMSp9eEBiAjNf+4fubu8eoyL7n1Wv1GoX7TqCe/vGYO3pafy/xzlOlzfbzibo/b7v4g1x8BXnwzmQOtXT6A3dve9nZn7e4G2N/CVB32ALvLSl2+pfNMuatVP5XJo6nblMIATFs14w0AByC7X1a3lbnjd6Y84fzl1lzbYucFtEql15gnjzYESltvzUZzSA6errXwfGbPT3tFlk4VEUk2FNGmOqvswvp4oRAX0YxtubMiOmUNiXqzxTDRBGqShDhFYWpSTJ7jMHnfRV7QONnJS6teryfia6/mxCVOVRVJhu66e8EH7pEWr6vOdny/s9S4068RT3lre4N5sEl797CVKWc1t8Ivaq3Ui9dauNVuogfKfxnL+KbPzPJ9/RqExbWolMjpGcodsVsEsCLyPcAfAt6hqh/qy54F/G9YAcAbgM9W1ff4e18DfDE2tX+5qv6kL/+9wPcBh8CPA1+uuvNHex0TnvopGpA9r5tssYvUIN31livA6gxQ7cvnvOspicEytRPyKqC9R+Sdt2urp069PkuuMFCv+pngCufTB3W9jAxpeiQ7T9FJdFtGrVPQmjuZylTUfvhFLIRGkjClUEtZC2AWkC05slPBQdgKqnYJdv/KZlkGWUibyPhYhz7W1cooMD615rLGIrxSyGOoRQTRBGxa3rJOs5nAuSw3emGiBfxktzQ8ZPb5ldzVtjquTM+zC8NoX/JR9dR0WeuU385toiv8Ohdw9ge9oqtspbotdVKsUANlewdbCX5gvxndyTm7wFTUcs7jAvZ9wKculhXh/w8CfspfIyIfgsmrvsS3+ZveMADgb2HVWB/kj+U+W/sxTP/1XwM/3zwuZJfCgwUIm+yeHk6WNV9CcN5LmqooHHyB4An4DrjgHteC7Cogeypa20b5F6B6SmegDXrdzO2vBXjvakADGBaxVoInpLeR6Or1KCZinUtC+8S1WlXX6Yqumsnm3GxbxbXLJu62DN09cfda8yYSH+mIx0LutUb+a+1+duBZFGlUjxa2euoyimkApOL5Oo/bT2Baovp1nVi8Q3/49SpAfyptLEz7XtbrigcklzbToi0gK0JCpwquEigr4gV1QyaJRP8MwcBboi6+Q0+CB3sL8VxVf1pE3n+x+DOBB/z59zMJ/38m8I+cO/1tEfkN4GNE5A3Avar6bwBE5O9jPOtP7Djm9z+RMV8KgM3e+K8Nksxsx5fOflj2Zo5WUaPF/RsbqLHeKLs9zhb4FlkFpzzXx5MzWPJ3mx+TqE3nJSkSDJnKD7+CFUwAC9ZOBq0C11FSfS9nIcgEuttSq1qQPctjrWWyCyTOJTVLLLOhqm4z/c89NfAzC3wFX8WBqE6h23zS6uFO+yyebLku+DWp+28CVPYwuiFsTlMqbQ7u7PIUAKUBm4aGmIFQs09Jljtb952xarZyM2mPV8DVjy2ze/+uL/4dsosD7HPavn3AdzUC/btsl/D//cC/bdZ7sy8b/Ply+VbzMtlvAD4EOCjLVfUDzhkXcEkAVvtATs796Y7p1TaLDUfmeZeSxKfQ0niBhSo4A2Qfj7WJnmfYKZBO6jxcNM5zVDTp/Mebl/tw/FfrbmAJ+QEJaUYpL4sGdo5pAbLblbRMhSuGTAhNp4Quwz2ZrII80hE2UstCZ9Pj2XSbmddY8mfBtmkFYNrihKIJW5cXcG083Oq9dmrpT4NUrdmW61xejm2ZZ3XcfgPYeh9qb3oOqi2iVo0F52uBU98TzSDMv+i1BPlO28WP+ZCqftQtOuq2L+euO81ZI/xerLPK/wp8AvCFO/ax1S4FB7u3ve3tybNC+573eJz2dhf8ZyH8/2bgfZr1XgS81Ze/aMvyXXaoqj8FiKq+0RX/PvGig7scAJuVHKdglk3N5h6diuW/Fm9QgzSerr/X2X88V/bCtq28dmFSglK6KGpYesR5y7Id75X9WKnnNN5ZcCE122TvHNBGp7VporfDY911au229djScK4e+Ek5MCbriBBiJsRcAzNbg0JnWRbCRugeE1aPwupR6B8V4rFMOa2Vdy68JlPlFNM6JbBlATV1HdjmvcB8NrTwYltVr5YOWFIC9b0d+1n6V8WTp6nWqsGtyuPaZ1kejF4VVwo37qTpBR+Pz34ME/yHufD/jwGfIyJr13D9IOBnnU54VEQ+Vkyo+vPY0iygsWMRCcCvi8ifF5E/CuzqP3jKLgVF0F8bTwFiy2FV/lKYeiaVjAGnAnZO5Xz7ZUaAwG5glfKrhl3lixUcRbYD6ln0wXK6WLIkhFnpp4wgvasyRaM/1EGvgqI/z2pN+EqrkrYdzEUsZXFtA+r2dqLMjjfjdhsqwIJbcgpkZ+Ckdk7xWKq6Fnh1lnL62652rbRrXjMBa63GKiCWhdIkPDeBsVnKVjktP6fSkLI95jLFan5CNNTTlvdK4GrJd5TJb9lve3PSaVB6p10qPU1HPV4TkR/CAlrPEZE3Y1P3rcL/qvp6EflhrAJrBL5Mtcir86VMaVo/wY4Al9tXAEdYu+6/gtEEn3/G+jO7FAAbTkYQIffTt6ukXBXPFVpeS+YeRPktFBCOYuWzrUZs2WDJw24rlW06FZxnN9PNYKupzjz2EqWu3VcHS1OydctB7bkm8/qzni5as13Px7XsENuulxsvtQ2UVe1XtUBa6WCgJRfW7w20VV312jRjXnqf4uBYtAn8/dmP3bcvoNP2xjLedvJ6q6dbynab/Nj2mO2+i5arZG0xbu5pbvPeqvess/9EnQJ87flv+xotAbx67Y/fVXzcdosOqaqfu+OtU8L/vv4rgVduWf4a4EMveMyfAxARVdUvvOBQq10KiiC+9wbh+gYZlZr36tP8Cq6BWiZbp4GnPAjxYEb51bfLF8t8+SmzJNKbEt44RRtseb/alPs0vZ+mHNjc5nu2gRRwUJjTAzkX8AsLUe35GAq4lnbfgelRlvkhatqX+jGKBzvpwAJ4e+4sk4d4xn2m4rn4+XlwqgBZG9iqNxj3QFWozQzTWk2b4SCTD7KliS28U5i83EIT1BzZxgMt4Ji7xXt1J7C8QWiznZY82pU1V9Q+wyojq4zELdoCpYXNcrrV3KC2fU1vt91mDva2moj8PhH5ZeBX/PWHi8jfvOj2lwJguXYdcjYFpi6QV5HcB+NlHVA1GMdavZ9tHFjreZ5CGP/vdIO2oHuLvtE3q4ZUjp/7MM/PbECnyuMpVjWVJtHtbalW23jYGPQUsM7TcqV2nS2vl9xsLpxh8WJHQTZb6JFmSHUqvVwluIqVFC+y8TgbcD3VWsazByxftfEABSteaOX/YLqmTN+ZGbh2XmTQrFc96fbSlun9AlxL11rWCVknwkFCeh9064kWAI06daEt65RChRZ87zSa6QUfT03768CnAO8CUNVfAD7uohtfCopgb3vb25NkT23wvJCp6ptk7iSlXesu7XIA7MGafGVdNQksWwC/8xdPc1pdll5Su6wEvZpA1Wx58TLbiqylBbZ/RLs6zja2jZPdytE2njRQA111CtqUfKon9IuClrxLvyBhR+O8GOyXIzrXINjZ4UZ057eyaNBONIF4Qn3J+GjGNyumaK9BWYgn3ZucYIBJH9crwrR4rq03Ke7ZjlIVsdpjFCrAtGlt2zZfttAR8xNjKnQoAbGGG21pDcTpm27yXukzdIp0mdBnF0E3Tz9rMJqgHMrXk6AmiFBKiDNI+yW+0/QAPGWn/xe0N4nIfwGoiKywYNevXHTjSwGweuUA7WIF0jm4QskeqAGhhZXptCCgeTtFAPNgVysEc97Ufqk1ewbInhnw2sK/4tSH9tauuxSizSLvDiw2jZ6mkMsgVlbvD4V4f65pR7uGlTHh7jGFiXOdnVAJblEDW6Va6fS5T8+XAZ5ZZRNMoNU1n5+ePv/6eSeQUK6F70DUxpLs4EIpTJBa51+umQat/PU0NqtK01ACjYv3/TD1ptcVDQUMXHtF+kTorRElAlGUpNGkHJ3fRhxco+kOSExUXrtqBD95dpcD7H8LfBtW7fVm4F8AX3bRjS8FwOZVZxqvWe2OXgA1uY5pMG90ViFUnxvg1Uj8mQc6vWirUPd5aSsX8GRPsefb2PStni1Vab86NgniBrTHUqHq5lZuW8C0lMEWsZcuTiey7EBe1bYaz3RbeW31XvMCCMS5yCDzRoaOe+FEKr86c8syC+EU51qZe7+wAFq/DlLS1YJaSa3zuKWCr2Q2mOg2k6BMwACvuX5TEHELsEJzc/dz7dU9V4V1JnSJ0GVrYy463aBEvaw5WwaGYOt12Tv0enCyBPGebIB7so//BExVHwL+68e7/S0LconIi0Xkdc3jERH5ChF5loi8WkR+3f/f12zzzSLyGhH5eH/9/iKiIvKyZp3vEJEveCJj0y54JF2rSpJk77iasZSrVj0JpmmprwtTfKAGr3Z1ObgVVrzki+w3wCRVGKhZDWBqYFFIvf23wJ5vV4DC6+xbMRM7eaMINFvUf6kdUHayUwDGl2dPx2qzCYrlLORUwNdAQYs36gG45lA1XWqbAlNJsK8tvFsA9a4OW8Vgyuk2+53lSXveac0K6JW8NjB0pcYtGSdU121W2DFNEKabiHuu2TMGWGUkGmDGLp/ZpkeCC6tHJTpFUFqvn7q/SvO4k6YXfDwFTUS+X0Se2by+z2UTL2S3DGBV9ddU9SNU9SOA34vpKL6K3XJipc/4xzF3ud8BfLnzHXvb297uZtPppnI3pmkBH6aqD5cXrjX7kRfd+HalaX0S8Juq+kZMNuz7ffn3Y9JgYBOwpham2jsxIP78WzqikmKVG53UxbR/5wevVG938moW5bILNauttmyGuKtD7TK1q1lPdtEM7rW2HK0GqVq4JZDTpgy1VTa5Tk8bz0dd/BpqsUCZ6p/yRN2TrV4rEyUQQ64Ug8C0bcNLFuUr9VJOGQXGMsdm8l79det1L+mdtpCi9XTjCbXz62y2wmL/ikkbDlK/naX/Vk35EjXpQ6cfJq1drSlTp66zf5daaiCvTDksH2R0nZE+W1DLqYH2h6FZrNtumq6tOEURY547qAISzKMVly4sJchyp4sN7mIPFgiLWfezuAlq9XZxsJ8D/JA/3yon5qVsR8DPAH9hsf03Aj9xM674mWa/6un50hSvpdyxuTdBtOaHBnKSsglbL3fVlsmeelO3AuOFreVmCy2wZR+n2nsHIXdSedd2qtokDNgNpKxQD2mcXxAlhOyH0wX+S10OEzWQvCorBCWqMianCoDkQJ2TmAZtUydfauZpQbCMsWBz1FMFE+UcauBOp5tJ6aMVxnKNqDebuebARAlss7rYOy1UNiXJNKZyYy5jKQBSihJcBcvydXUKaMXsQKhzdTHfvFS45RQmt2Rxfeo4RQlOaUhwsJXphnkn7S5v2/0twL8WkR/x15/FluqwXXbLAdan9p8BfM1566rqy3Ys/20R+VngT561/Waz4cEHHzx3TJ/9eR9YioOage5aW07zae27RSRGQVDue9aaz/r8D5yvpPXP9juz7nrjJswR7r7nHvDHv/jFzfLmMCVVK0yBmZKqtaw4QubtoEtKT2k1UndbbjA+/OfoAX9m/BB2/eK1AE0ZTzFvJV6DVK0X0wDXtK8d10vg+f2Kr7r/fr8J7pAArGNvhtpeg+acl5vPxzKdW9np81crvuL9Xli3retvq+1dLKpgLpPnWfa7vPeqYBKaLXkm8HxZ8/LwgTvW33Id4EK/m1tlT+Hp/7mmqn/fNWo/0Re9VFV/+aLb3w4P9tOA16rq2/3120XkBe69tnJi59lfA36EM9rjrlYrHnjggXN39Ff/8isbYBH/QcksT3QOTP7k1DdWCUktYOaPz/5TH8A//v7fqO+Xdi2kZkrfUgGlVDYvIzQLSmCXFRrAPdg/9qUfwo98z683Y/f9RCGtI3kdGY8iw5EwHoi1m/ZS0lIeOh5Z/X1eeZrQKtecypIiVIIpIWS6aNHqIMqfGT+E7+5fX49fWncnnfpsjcl0X4NPTU82HeMmetWWeWPFg2X0/Ff3YMPo3qFgClKOYG1GwFfdfz9//Q1vNQ91wLRad9zYoq+D2vR8PILhqk3TS08r7dTyXUv0P1H7mRXvP5e+W0H5yve5n2/9T2+pU4J4LFMZbhGO6e3alnHYZwl6dTRaoEzlRWvu8bKbb05CGqKpY/lNR6LyiqPfwbeNv2kUQHO6ZZucQr1Rls/g1x/YVdZ/i+2pPf2/qJWm9+rPL2y3g4P9XCZ6AHbLiZ1pqvqrmBLOH7pVA6ucq3thRROg9UpnpHyewLFwsNIKV+/W6Tt7IMurflGaYIfWQeFetaEPit7CbDz+FSnT15LzaS2oZWqaV3YftOZfnjqFdvrapGCVXl0pC8MYGcZoAJtC1SAYh0g67sgnEY4DOvgFKcCKAZd2WjMeatpVW/JbxtV8budZSVGbOhRA265ckskdiqc5hY1xsWEsYM8kbSjaqLDpXAC7pQeaa28ziSlzgJK7Ggz8Qnm+JetiW5pbOf926i9O58TgKV7RBhw9uyDGOzxn1ws+noImIl8O/EPgOZhM4Q+0WU7n2S31YJ1T/WTgzzaLt8qJXdBeCfz7WzfCve1tb3fSCvNyF9sXA/8/VX0MQES+Cfg3wN+4yMa3FGBV9Trw7MWyd7FDTmzL9m+gkRFzYYXbJkgjqpOwSRNZbWO3NfrefEmsBbbO77rLANayVLbkzfp/DaGO4fTAtnsqs+BVzTRYNE4M8+01yHz72XGapx6EKV1IS+R5PqyzfynVi1VhM3TmtXqPLQlKHqMFtZIgnfUK0zEgmwAlcEMTFFEhnMgUmMomndgKrnhvm3k/LWGb012vT1G3SmvvKNt4sRrUgmxNiWtV3oJT1Hqb2QBMbcZp1m+870Ib4AGoUzmuPvYQpmwOVbXy12hpLFmxkubm2CV4aJ6reb6lHbp91XSakdxhkzMCyHeBCfPC9rbs5Vy7FJVcM+k+BW0yw0rdjbZTrEUaSwFcoxUa2qCAY9L5bWCbBuwOK6B3VjntDDyb89GFcPcsRat0Z1AFCTabTUqKMk2TVw4yB5CO8gQwy4qnJsglwmLaumW8Op/Ols4Fo/OHdq3t5qZN1oBRF1LHEUbobtg+cvtNbSmBUn7aAuzi5lYCW1VzwUG4tNVGvMwVpkKU0avB2lSvPO0v98xiWLXdth9ndsxKZUilqOqpZJl938r0fl4lJ0hB6C6hXioL1EaVISqrfpxleLTXBIzWieFJogfuXvte4N+JyKv89R8B/t5FN74cALvNqjeJeQB58opasDX5uoZXA6acxgncLq6vs2M4W4B2p4jLLE/29DrtvkIC3WRCDMhqOt+8gnQI4wHktWcQ1N/exAle5F5duslOrWCmwGGIWjnCIkWI53KWXNNZC5Pp3kfuleGqtxmP5vGVdWoAqv1M6jVixjfLaMGttKap+4d06ByvysStlhlN8VzLMZbyhsLUrgUovcpNR0BJcVq3Nk0sQKpiKX+uXaHqYC7ZQVBrELFc3zIuJRC7PK+mlgLM821K3nGrLZHybZsQ7rS7mSJQ1W8VkQeBP4B92l+oqhemLS8FwLZiQlvjBDr/X71akYUntBCD2ZJlMPvv+5DFsrPHeg6i+S9rmeu63E4yMJZ5qY21zQ0trVDEAznaQepPe691fzLpESytBdfyeraWNB6tinVl3YQamW+pgbpMLOiW13OPr6zTljaf9wOuubAJdGWea1pb5oAo1n3WQbvoHtSy2bRl/zoB9TL1T4sQdrkJZGovr1q0os3Xodx0PGujXGdtbjRBzEMt13hkPkPAX+empU8QJbs3nHOYBM7TnQfYu9yDRVVfC7z28Wx7KQC22Clw3Ql6C/rgAkB6aplnKJw6xuPRLFj+JlSRnNHlGwv+tVIJLiqeu0ldSkZLMpDRwHb0tCMTEvHk9OKR0u5STx2ilStsE4WqQEmZEZwiLpfnZY/SEjsjM68VcK934bE277f8a7tOjs160txY3LtEgEEJo5iyVjavtw63HbKPcddkuwhz6xBsBlEKC9ocXedg2xtE8V4LeKZSgebA25V+aI2gTMHhLqYZrQCmI3GqRc6F2cNbZ3ezB/tE7VIB7N72trcnwfYA+zS3M4JOW++uOk3zkKmTaHlvtt/FdsDce30iKltnzeZqkG2+/6p5G0v1lkyFEa6zGgYIhRfsGpUpDxoty2Xnh50Ca7ustJWpXlaRI/SFxXNTmbzVokUwKyIQnXVuBWbUQGtb6Z9mqEVsGzF6YLgvoX0mXI+1qKF8F0oedL0m0njG/jqtdMp5dTqh0ABazqfxRoHaFwvXfpWG4y46A2Ce5xTPVLIKseFRVRtJSf/fxVxnHO0xC1VwZnni7TTd+VW6FHY5ABYqyM4A9axGgqXUs/11q27/srT7Oe/9RknlVHeCi9JjTbrX7HUB1y54GarMRWlabPTTsqR7nQI20oiBnPObLK27S9WWDWXaaAYu6q9LaagfL4fCqaqPswGdJojjkgjGcaYmLau9tKfvN9P2XqCQPVimRdRGTVu2pR1q94LFfUbLNfE0q3b/dYUsJtjdXmtpH01BgpRBNwAr0MVxlqYFeE8zGMbo8dUmsNBc7yUXnht+vDaVvIPWnOKltMsBsDI9KeGX6q3svLsWYow50LSVYG3KzTnlrdO2zQ8inoNgZ9kStEvZr0ht4Kgu8qKFm1U7n1Iq24qcTK5Xewxm515StIJ7VcWyitO/5YfcAEB7yoq3vRaLupeofTtBWABXy38qgKeYVUWsdqzbnvvr6pGK8bjxWjQnczOv0qr1+w7op4JYpZLMwbSOrRn3LCtCmBS2/OYiFWBP38iK8lj0m1zKpmJWhHNyOxtobkD1VBeeahXaGZlEaO60PemK30+eXQqA1eg/5jrfK1/sdg65g0LwqHIFqdZ2gPOFur9u298Z4zjL2pbhU8vxiSKooiripaKrtlxU50Cm3t3VvV/BprVBiqLW6fG1mQVSUGnGqkyltFpyTIsaldMSs/PZ5h3WNxua4NSF2L6sUgpNQCteD9M2Dr6SnLJI05DKjWjn+Mqy2Ny4PafX6AA/SX8uQbfOVEqaVStMPrtuBVybKJ54XqugNcBV6RndxmAJSwmMO2F7D/YSmEb/0TvXpi49WFKVLr6jMwB05lFtWUeW4L7FWm/3PGuEXWrua5rq9ytl4BkEaSVT/f0W4LBtJl4xZyF20w89F9px4dXa/2kamrfkWlor7oCMYSakUo61rJabNiwH8n9NFsHWFjCLbat+gMC4mj5vafKWayeH5vtRG0IuviM1j9aphur4y7SPljdu1bqk0Av1Gk+ftWajW7poRQZRrElkAVoRRZwnqa+Zf42yp2qVz6F4vfX6LDJA7ojtom0uiV0agN3b3vb25Ng+yHUJ7JTXKcbHCtJ0BN1xq9VSSjmb9978IG5mm/PKbRstgp2HE6wPV18e1ACOhkWPKkA7z2KdeajmKZXsgW1ZBKe6G5Q8zmQHy0lgDMhx8ICWTJ5iceZ2FTi0hR5pyiOtXnodfDMsmV7LOPGvtVTWPdhWfFvUVcX8eLmzY0jpNlvGES0wZ7m0TnNQuFsPiWaMn1143yU9oQQRNYlx0gKKkJNN9XsvZ00qTWmyB7AaLxaxNt6ESdy89VwrpVAuUQ7okzBf3wPs0922fcCOJBVkva/9ti4Fp6yROqyvy26X2q9n7eO8+do5IFsbGy6yB3IfGlCduhnYyv6v5gFROUJp9EpzCogqSZSuy5XvKxzsMtBlp2Tar9kj4nkMVjl0EpCTYDKAiVpWOp2nH1QmsCvjKGA1S8+acca+C51vV8HNNWRyN6WE1fLXAsJiQFwCZy3DITrn4WsH2HJTLuaBLLLMAnPL82z5VZK1K5du+mCGMdbCjfn0/vRXQbOQvKov51BTumpbHz+Bqasvp/ju227K43NGniZ2KQC2pkOdUriyP7Ww073CKprdWqs70IJr2fbx3KXP++LNNAeYg3IV3baHRpkeAbQzYK28aydWHrpmpmFawKpqEQS/MGrpUEkjISh9n2e17iJquZlpAtZhjKQcSEMkj94KZhDCifOuo5iX2ID8VG7qM4lyuiU2VFKyCigyYUTlUlvAZNoezEsH6g20inEv1m251Nl1rdeXSTg7Ur3wGs8rbmzrtS7OpXLN7Y0h2x2ldJDNKgw5nipJDqINZTvnVdvn7XqFc81ZPJWOJ8X2Qa6nu7WBmYCXLOr8R1ZchDb9Shb7YNoHiQkgzwPXbYGtdttd+a/L7Zr/2gU0xub8XHTb814NUMXLY/1/FR1hahjYZNfrGEyiUIpbZzsvgZMWXFsr8oTDpiNtItyIVfwmOCUQxkVPrDJj8FnvDITq+csEhs3y7cUh8+ftOjP6oXitrc5AbliFksZWbjyhuWZtYLAES4t0YvFqx+Dr6HTsso2fjwhIVHKfyDladotAiNtbdM9FdLSoHs484hgzfUikoIgXLEzaBZGULjZpui22B9int9XOBLWaSE9X/hQPdSHxNu2E2ReliriwxTNubZeXWiUIL0hJtNuVR/nhNgUFlXPtJorAPC/zXlUKuCq1CZ+DhIzmlWkQA1pX2w9xyn0tABDqxWgaIrYI2fv19u6upVfWlEbGdPzq1bU3oGbavwDMFozbbID5NWO6SW7ZtlAO0g7b+VWNTF5sySbw6L8GTI9WBRWdWsdE089VMkIwvdbQLM843xrIjuiqfp3LR4p1hy2SgurXO/tJxJBrNkd73SVb/mwMiqjzt67D25oIxO4Jyr7dpBUG6rLa5QDYMSMik1xcWc7pBocaBRl3gSLO2GLAeNZ39awy2ZvQi72I5VUgd8GKCvqGGvBATXYPTGXSgC2tUgrQliIAGQU698bK1DVkQjjtXVVQkMzBaqSLmU3fMawT6aRDR3MBdbQfe+6ZT6FhN19ZbBewLmiDdp/T9LuhIE7dIP1j8Ol/9WgB+oUHW7lXzFMtqCHUG6R4vqt0oJJrCx7pTVic0bhoklVi1Rurt3SJXaLvkoGmDzTLHGTFTz4yVzCTbHRNoW3Ml4ikFBhTqLmz64MNVw82Z1zs22Cqd7vg9hOySwGwe9vb3p5Eu7z4eokA1lOtlhVZU+S5IaguEL1fzmhnNMFZxQTtFP+8LIOz3mv0B2pgq5+417TyFK3SPbbDNF9XWHfW4tWVIWbxAJAtKK2hRbzcsni0aF3enlInuVYjxZg5EbUOqEHJGSQHtM1kmKjfxbnJnI/d5rVuow2a/bZtXkQhtSldTutKmLIFVGz9Sj9nu1azMtgi1NKkOcy87/rcSmErzYK3JdLSVHIp9+jSkE0V1zZb8t8B2087q2gzO7I3nSwCMl2XuO/KDa6uTrbu/3baniK4JFbAdaaTMRNwWXCddfGOb8gkeWTrlABaCKcjCg3oagPkp9p3X0TToNlPyXXVPpB6YTwM1or7cMp7tdYoE7iWKqRKD5SeU6UKyIMwwdOzapCL3ZVA7bC7mMi9ELvMEDpSslzYWr3VgOPsdJWmnNlPs5nunweupdS1tsx20DvFt0vzWurmVSu37jJwikIqYyo4O0smKc9D4V2l5sOK6xZIV1Dcx6iCaptKJaey2IBTN7dCERSAbVvBZKxzQc7iPdGUvktcXZ3wrPX10zu/nabAniK4HCbZ+bbGa7Uf4xkeZ1m+zHVdvs+0n1YboK5SDrlYXpofFg9Yct4Osq13vdhHXgXGw0BaC8OhVAnCojegrj9Q5Akr99r5cVLTLjsqepCIfSJ2udbHl0Mv81/9HlV/1KU9d7HYZXKfyYeeblV43i1gW/bXAhhMPOsMXBfAGzcOsIOBrIr1Gss7QPL09Z1Sumatwct42gILlSm5b8YpTzcGwM7T17eLoZSMj9NpgBaYiipburo33z2Z86/ttTYQhug3xXpjDMpBP3Jvf8I93Z33YG8lRSAibwAexSIgo6p+lIg8C/jfgPcH3gB8tqq+x9f/GqwzbAJerqo/eetGc75dVCDv7rYWUEuO6zYQm6Vp7VgH3HMsv77mjRLZ3yYG0m6ztDD91xDKvHxOJ7SCLiVNqzd5u0oROCjV4JaDq8ZCEVjwSnt70Nm0V7K3Z1ll8pVEPBrpD0a6Lln6T5e2/qCLFXAdxlinpSXhPXtTP1llWGU4yOjaQLdmMhQQrA8H9MY7XHqwULxuajFAGDwNrMkMmDcdXDxak+la1fxcpu2Kluy0H/ExNN+D6pYzBbFKvuxW830UT7vB3SVVsKQESn+tTcN/qAqbMXI8dPVzijFzsB64Z33MQRw4yR0n+c76VSUb5LzHTdgnqOpHqOpH+euvBn5KVT8I+Cl/jYh8CPA5wEuATwX+pogsawBvq10IYEXkmSLyIyLyqyLyKyLy+0Tkw0Xk34jIL4rIPxWRe3ds+wZf53Ui8ppm+QtF5F+JyD8Rkau+7OtE5LqIPK9Z79oTPcllzuvWRnm7bId3u9OLrelXWx6wHYDbcTjIavA81wXAagjQBfK6I68MPSy/teFbHSTKF1cj5LVaknyn5kmVqPcqofcO8KwN8oyB9b0n9OuxVm0F5wxVheSP+f3HgHQYo1VxeYlmTqXgIEzeX/Bj94qu/FHHMoFsm8o1q7haAqM2n2XbO6vZtuTflpLZ6fNqdtMeu1Hcqs/bY7Xfoxass4OiNOdzyhW1G4rEXPONyzalUi7OZgwT773kW6F8BpP49pAiQ461sWGIxoevu5EuZMZd9ci32STrhR5PwD4T+H5//v1Y59ey/B+p6omq/jbwG8DHPJED3axd9Ip/G/DPVfWDgQ8HfgX4buCrVfV3A68C/sIZ2y/vOAAvB17m+/lTzfKHgFdccFx729vensq2nDWc9YDniMhrmseX7NjjvxCRn2/ef76qvg3A/xcH7X7gTc22b/Zld8zOnSu4Z/pxwBcAqOoG2IjIi4Gf9tVeDfwk8Jdu4tgR893ayRfA9wBfICLfpKrvvon97TZ1wZIyBxO5mPcKuz1XL5nF9ysXKZO5SFEBzG57GsLk4QYgBHIfyatA6q1qaLgSvFOqkA7mU920tuBWLrRAVOizd4+1YIx4iWrsEzHkqi26jGrXZnzNx6UKJ0Nn+ZZFgFohDWFq0720qFNaqgKjt+XJNcTl7mEJEG33XtvncWDeckacNtDpWuSeiYaAuRcb5tsWp7tsO6eCOJVTzRCm/NhiRfvVy2HFixVq8LBtEdNmAyz4CxELYhX+uwi51OwN7P2TsZtV3UkweudwNXBvf8JBHGrrmTtldkkufMyHFk7YNvv9qvpWn+W+WkR+9ZzDL+2OXoCLeLAfALwT+F4R+fci8t0icgX4JeAzfJ3PAt5nx/bb7jgA3wH8HeC/BX6gWX4NA9kvv/hpnG0T71pGpJzHs9qGznnWoMduAJ3zsu0vd3GccktZ2nJZrSgTiDKB67ojXekYjyLD1YgGGA+E8cjAte1WkDsYD5XxarbpeKdTaSdTlVa3SnSrkXU/suqtXYkNXeqPG4x/Tdl+3GMKHG86ow6aZPayXS6AO11MphWY+IvgvHDDwZYE/7LuKXD13bVcaf+YsnpMK1eaF8BY0q/qUOrn1hx3y/pGsUz0Ssm+mAEy2M1hLMjs17dc6xJUjNkKN2K26rg4b9W9DCi28cxWHSs3VM2MwmnAtejKrrvEYTfQhUQvmYCeAvDbbvmCjwuYqr7V/78Dmzl/DPB2EXkBgP9/h6/+Zua49CLgrU/oXG7SRM+5u4jIRwH/Frtz/DsR+TbgEeAfAt8OPBv4MSxC9+wt27+wveMAL1PVn16u5+t+HQaw3w28Dvgw4K2qenXb+h/2YR+m3/7t337uSf76r7zND3DWie5ecJq6m8D6vmevec+7msjs7HKecW238YHK9nEUAPCyXA1SS02ffc+Kd14fJuyaAYZu9b4MtcqPd0q9uqgg8+TEC89jzTs4qcCgmELUsnXJ6UshzQ1v+i/t+nqBmYbC8w573vXIhhLU0iBbP+tlatZyOLN1Zu/pXH2sHTPw/G7F28dNcdem9ZyjLjcUKe8v9mFAqvXz2DG09pTrUkF5jh7ykNw4FYAsaVxRlCjzSrz3O3r/LSc6t0/4hE/4+Qt4lGfavfe+SD/6o77sQuv+q//ra888njt2QVUf9eevBr4e+CTgXar6jSLy1cCzVPW/F5GXAD+IgfALsQDYB6nqHasXvkg48c3Am1X13/nrH8G4178E/EEAEfldwH+1beP2jiMi5Y6zFWCbbR4WkR8E/txZ661WKx544IFzT+AbXvE/VXdA4+QWnIrqL7/JjQfbIk/rEX/25/1OfuTv/X9TR4GlVOEOQZjZtGm5bjvWQgkcRMaDSPJ0rLSyx5/+A/fzt/7DW+YpWT2kQyUdZs+epypn1R95VLr1WHUGQsh0Tg8sAyuTx+QUgeuNjinwZbyY7+TX6tRzTIGT436GE6rWhoY8eXiqVBnCmrJVZQkFMoRB6B6bBGK2gRvAl33I/XzX695KPMY9+lbMplm/9VSb/Zj6GFO2RSl/zVZerR3kK8myIBTLdU5SbwKveNb78C3vepNRAiu75iJqamKlNU6fiWtLfVs2iOxiYtUl+pBqJkHbSHKZf1zS4kpngz8zfAjfs3p9zSgIDqgxKIf9hmeuj7m3PyY0d6vv/egv4I7YttnH47fnA68y0Rs64AdV9Z+LyM8BPywiXwz8R2xGjaq+XkR+GPhlYAS+7E6Caxnkmaaq/0lE3iQiL1bVX8PuFr8sIs9z0AzA/wj87eW2W+44fxC741zEvhX4uYuM8fHaqa6uFzRrITL9cqsUIkxKXQ3fC5ziX+t6dcHiW+jiNBrF81wj41FkPLSUrLQSxgOcg50DRC7R+QKuQtNoD8CnpzLPqSyg2cVMYtGufDY0qZFqsFPMJZNgE8lDmDrTUoCknT77dovd27S88WxFCaN1aW250Fk0373+8RBSI01YH8IkMgOzVjNV2avsqnj9JXPAZwC5V+Otu2wdbcsQdTp+k+gMXjhQbxrVky1eJzV7IASli8mbHTbXQqbWMMXaHORCFdBkEfQhuTCMfSZdTHQNvRNu/qt+C+zWaRGo6m9hQfbl8ndhuLRtm1cCr7wlA3gcdlHwehnwD0VkBfwW8IXA54lI8f1/FPheMEoA+G5V/XR23HEuckBVfcg93q+86MnstOIRtgUB24C19XSa9exHufAuW8Hl4uG21VztMXZUddXg2LbxAkQhH3aMVzrSQWA8EFIP6cC1XQvXumJqYBiV3OkE+FGRTi01KOgUeBKXx/PUoG2mKowOujasqdtpO+zsvGxJywJO868LJ32OakyPWuZq2rHxhgFk7hdFA0sGIoD2c9CuuavCJI9YNGTLGBbUQBgE2dh7eWXca/FK65RfcHEXpil/UPduQVxFprQX17BgaRxYg1dYtVVaLNaz/9ONMDrw5qy0rEUMmZQDwS9waVIJBq6jWrB0mxzibbe94PbZpqqvA5bcyLf5Y7nuW4FP9+db7zhnHOfrFq+/Cviqi26/t73t7SlmflO7rHapSmW32VaaoPVkq06sC8Wc5XEC824Hi/cvcicv4i2rjnTQMdzTMR6697p2WqArqVc2xuK91iyBXqsOaY1Ue9I5WK+s6DKE85Ss0x7O6JJ3gCfBWwFCVKcWElb37noDO4NZubQsAVSmzIAqOzj125qVxBYHN1hmgO9xThFs+xHrtO6yyW0pSmi1CkSxYoSxpRGEvPaS2OwdGjI13Ypg1xcxCqF47Vr0B5yakD6bZGFDxxTeO25Bn9z4u61nWz1SoA+5ar6KQB9T/bwygosizjzZIEof7igFabb3YJ/mto0SaJYtAXGiEnyBA20F2V3H2Aau5b32/7Y7eg2oWQVXcmpguGLgaiLaDq7eejuvfIbt1VnGuzK1Xmkj2uBtuE35PjQBrZYiqP2ioLaBmRSavF5+qfykRicYwCyiShmbLm8FV6ngWt5DXHQle3Dt0K5X0ZCQbCAYBj90qVhL5bOjzOKnCq32syzXo33dgHStfFtBWjkKb8KUy+qkrkYD2pLLKl12DsOvR+3NpZVSaCu0ykdeyoxjyBMoorMgV7HaTHJLW/SAerVdqOsGlE5yfYQny5W8vPh6SQA2hFkg6jw7BZJaQFd3K+iX7Xbdrbcsr8cp/HAAjZ4xcBgZ11KFnnNn4iVp5Zyrl8UiSlobT6jRgLXI5CEOfKMFSyR6rqUD8BJcbZhe6upyd6WLQV0+RvICYFMK5GGpqiJTU78sC6+zeLUTuC6VtkogK8fm3tgAYQ1QleCVNyacZQoUL3jmKcMpcJVpX+XzLe11wD3asUHtUO657v4eMQW1wN6XSaYQpptWVcxSp22ba1Y8zbQIbrWfzfTcwDmoCWwvy2BjyPQe5OpCmu37TtspxbhLZJcDYHOGUte/LXJ/0UyCi9yJtykl7dqdB7lUxPQFVpG8iqSDSDqwdKzS9mU8gHQ4V8nKK0/QX2WvznJvqQRe/AdsnQmU2Kc6NS0J6lvH1Wy3ipYYvxkiaei8YyyVbtAo5CGgowNstHPXQaYW3eXanQJKWfzHg1ymTTvTFyiXdxGkKk0Pi4KWBZyac/FtgoNyafGyDJJJstlBUSLTEigs11L8dcgGxCtPZ/NsDAlN5oDYTUyHUBXEqN5uBgIiya9xppdJg+BU/vAOK2la5b40plgLDVpw7sLkvUbROw+w5eZ2Se1yAOzSe21LT2E7hVDeuok0rp1ZATsAt4CrrqNVaK2j9dJaT+A6ridwTTW/U817rdVEWtPOi7ckeKVWsJLJEEs6kPdx2sK3wpTjCtRqIDD+dQwWuU5DYLPpjZe8Iuh7VzVir72iXUZOwryt9ex6OHA2XGUF3eQNEkeqaHa1PAfdWcaAe7BSKotlOk6pDMu9UQsqzPtuCdavzCvDcql6K8MvJa+e5xr7ROzzdCMLSr8ea6vyyZO1g2vGieBMJiCSyRKssovTNzoRajbA8nPa1iodhCFPmR4B4127kFmFkS6kmqec77Dgi6A3Uyr7tLPLAbBFN6CdDi+/ZxfREljabEYs1D5drRe7/HI1gFGDWYcGriaWbVxrWgnjoTAeuZ6A0wOUPM3lUGvxvL0nUen6hAStOZb2f3swCyZwnQoKwiTc7N5ZTsE8sdJj6tBSm+plGB3llEnUW5tuCbmAp6cwlek809RfRogn7lW2U/Xk7zfT/MKbSvLLniF0Ex1KcebL62wffVH5q/22pIzXr3HhtT1ASMBuVJ0Su+QyjAZognmw0QOARYdBfB/iXm0p9FhqPLQShPV18/meBtX58nbGEUXpY2IVR1ZODRRwfTLogdmAL6FdDoDd29729uTZHmCf5pZB3F2qwa4LcqVlerOVKtjGBsiikqsZw8yccx2v9IxHgbQO1ualg9wJw5FNW0s6Vl5NhQT1WM0UtwwodLmmZIknsxdaAHY76UVIpIiGVHGRLIybWIsTdAzwWCQe21xc7qN6ona9mmsTKiXpXRMgboR4w7MAZDq/trNrGKE7Nk92PJyfZ80SWGQCVF1YgRSm9WYmdh3Nu6YK4kxpbkDwQo2DZOWt0SiW4nnWK52DEb9+jNpSWyxAWAstBMTLYyu/uvBi23bodg6TR5uylEbg9bNrW8K05curmP3z9rLnUDIIjLQOBPKdLjTYc7CXxArotboCNxH02ga02/NddfGa00AexYDVK7TSynNc15aWlLy9y6wzQbdQwwqgvedW9vYNDl2m61NVZdomNWiXQWe5lmWKmXKozwvgTryiRcx1FOIQiDdcR0C9BUxTlmvnDmTjU3FeVUapHGrJNQ3OnZY0rrAx8O2ug2RluOqfWZGGbKidGT/b8K0l1aqAdhlPBV2nUUo6lpUWU3cgCXISwtp2WjIv6nVUowvazIEKwNnkB5OKBbfKd8azGsr177tU+W2YpvttziqiZI2zr1T9fPJUYafiN0TPf20phd5pgm2dKO6U7bMILot5fb/V5J/xhdtVKMAWUC3r7/KIWy0CsY4E+SAy3tMboB4EhiMrfU09VVOgpGdNDQr9/0qhpFo5qMVVqiAQm/xWmHImC8AWT6r80Nv0oeIRqb/W7CItJbEUQYZAOBbiCVMqVLL3pvzbiRKWUZBBrGfWOAFe6X9V1ytdYN2LTWvjqMt6IRv42osJpEtGQUiWQpdWVk48E3pRPD+YWZqdXWMvh4VZgYOMYdJUUCF204ZFxlFLgM4thkxKrslar3Fzkti/OqvYMgWy/NW50xdn3i1VIyJn38MintCWyA450kkia2DQcMeDXPWuckntcgEsBpBaQLZY+23e9v1b5KteJCo6U9dyYNU+kNemijUcGSVgqliTt1pjVUUVa+3g2kSyax188Xq8oqi0HClZAjZkU2jKWyL6xWstwFoB1oGhTkGbggKawFUJINUE/eB5u8HFpUvK1UDt+FrTtWQKMJm3y5SJEM35y73RBSrMcl8Rmn0qZK3vLWfApRChdeCKepZ/UFN6WKngUoGsFSRVrYlgKCpb9SDTTlOy6ziOwW9Kirj+AVBvVJqVcYycBPNiVzGdCjgu1baW8dcoCg74wxhn61qgK3MQR466DYdx4/u3k7vjxQbKHmAvjZXUF3CQ9eXlfxH+fbw3+YYiqClYpYCgi6TDSFoZ3zocNdVZrTh0AZjVBK41HatrRJzthIwtiHOtz9IDq5RRAhUcyhSzrJezUwPOtdr0d1LfL6lIdRuZvOwwUKf1Zdx2LtZEscoPbuWqG9Ar60w4UMVZwoapE7BMQB0GJW7sf9l/8us5O05sjiUN7dI5FXEDuG7jtHbnWj1zTVJLjUNU1v1IjJmchc3QGQZ7CfAw2IE0463b1dKzZjOliWoA/IaYZ+DYep/bpvVV9AU47AdSDsiNSQimj4mjbuCoG1j5XWfMkeD5tk+KXV6G4JIBbLHSQoYGgVwJ6yIge64XW1yOKOQ+oDFYi5f11F47uTJWyWet6ULRpsd5rWjPrMW2lAaBGKjWxnmtM65T2+fdRWVTtVZNv2plAsspILW1DBlUgx0rKHllNIFk6B+bgCutsen4zioG6pR92/LoNEBaUW84FXylTN8tCNbdyDNaQQ9NC3a86qA8Uj1lYB5IwwBVFLrHTLUrHVqAMfVeFp0nzdWifLWKieT8p+bgt7gpqCWBCVyh/pdC4fSZ1WrkynrDqjMANO7bOW8/XuHDy01yeQPtYuKe1QmrkIgnytFq4LDfcNCNXO03rMJo7bvVtAmyxjvfycBtnwe7t73tbW+3y/YA+/Q2UUVZeFSqNZF9ZkvP9aKUQSP20vKtaeXea8kUOBBLwzq0/WanAGaaA+tSEqsWnY+TOlbxhIL3dTolXMLci22XlWHCFCDR3KQVlUi4e03irbtrz60MeN+ptFK66Bzwxh5pDYj9r7ynT88FagCpXFdtAk/FE9VoXGscqHq39b0SEMtKPFHiRpEhm4PdmfD4ULzXNOdaZ0LbJVjWUau68mo6VjWZOhOMI1y7seZgNdDFPCvIAOrUv1AxGVMYszft/W6VrI12P7LqRvqQSBoYl3SAc7/FivdauNkxBa5vDrgx9C7yAs84uMFzDh4D4Erc0IXkNMP0TchITdm6Y6YK6fJyBJcCYM+0JYAuhbGXUnc7BF00BAPMTsh9JK2DlbyuPLe1N3BN3oWg/KBrqWY35brmtfOALbgGmyeX+vfgbUlmDF8TrW6rdpb17W2mQPu+iHOv7XrqoBGVNJTxlkiVHS6eTMCZ+8UUfAsHW4JW0GQDFIWshpstU/y4sX3mztYPI8RNJh4nZMh+U3NhmGTjAQdoH2NNzQoTNVACZYV/tXJkJa+z8d2eXZBHQbUzgFNYr8ZKrYjzF23DwtxKMzbXNcbM4Xpg5dKClarx6xyD1pzYNo2uFdwpgcy+S/Qhs+pGYso8c3XMlbhhHUaCZANWAciW6lX3daezCNh7sE93U5EJSLflut6Ml+rrtzqy///2zjVGkuuq479zq6p7ZtiHs7ZjJY5RTBRCoiAMRCFxJOKABOEhHglGPARBkQBBsthRgmShOMAHHiI8ZAICEuL4SwQSCQjEywqCtYVNHLzICX7EEBFLXpJgEJbs9c5Od9U9fDjn3qru6ZlddrvXOzP3L7W6q6v61r23uk6dex7/YzbWypw7tZd48QoEKXGgHRC1aGU3c6bcqxJLluaKsDrgdBUPdg+NEa9kTXPXrs4Kz/z93P4ZDMzRdqDd/FXdEapIbASdGjNZUGaIU5LzC+gJWJLG6q9h4UBNIVbJxioDgewhWaK9MwpX5sNEac4oYSsiraJVQIOl4tab0Gm/EshhWd7H1AcNJqSH54gNtBsmXBlHJJHZxGCsYM51O2kD7agi1P1Dbng9YtxeUVeCpdcOw+dUhRZbGTRVNxNW18WQa6D1x6fWQo5Rfm5rxJlJQ0SYuCOrQ5jG2mzGYokQiVIxsuCaXwoUAXtAMBOOZR6EGcLtRawbnf855gSwuhNLxZIGYmPCFaD1rCwjbDFB1G6QYzO7kWtKtbj33UOxao/J9PhMcQ1WXGOt6j5aYKBD2rbfjLqD5qpzx6YvdeDO1ziowuUectxUUNWRUAW6UURbM3OoL7GnXvPX6BMHWusw5nQgSG1u3Yzg50phVrE2ngCVpKn2nQ8TZXRaaU53VJNINw5sHauJtbB1RPrSOc6KNWTbmikZMyCNUbGVg0VsKNr4vHuntfPY34k450JFN66RK7eg6vpEOhfgsQ3EaUXij6Xqyc6T8wpMK03l0MPgugVROnrtNv3tpupJIG2fbQdQBVCE09MRV44rajpatXfcOVY7yXaF0l1qIatYyNsBxcEQsD1L3DbsyhO7wESQTAFaC1rb527dNNbY2J83VngFgl6biimJIKVn1kBjal7SWO1zbwMlaa51zBUIrFuyPQt0F412N+GalrOJhX+2YZMadR0ZNS11FdnUkf2mlVweOza9QJSBbXW+pUUdSmaSdp3e46/9Ml7PDIhfPPwrjoRuXDM5UnH2mD3Eto712ilzdl1R6Ny8IM7SFVrvR0rqaBQdR2SUMiFSTS0h8dZKh8X1ToT2qFA1Nu/pIdFOKuKkMoJucFLuXrjCkNjFtNUglvW1sOS2f+6iEGPYRsYTQrSaXp2yVrUElFYrNw9VWXMdDxi1Lj3hi5JDKQ4gDoSA1abqBex8UsFuGV2DxAJbikJsKjMD1F7apRLOXlGZkPFA+6RBRU8WMHZ8slOrZ2oCHUUXCpp5RZPWKEG3CddzYbgE3ZFfVN1O6CVQUjhS2gfWj9BYmemxO3ZCVOLalC2FuBWyJlifcftnb0HpnYdDYSrM2mPV5qT1kKzkyMp5DcE0/2rTlv/mnApM123eJ4dgetiO69Z6x1ZslHqzT8tN10Q6c55J15tnumrgAGvcptEGaPsSNib4raFMd+gPpEQXmFKKtQ256kH+MWS+VxtBL2TTsj19nr9eQ16IGEO2/WILKOpg1+VQs8XUn2rDzK8w4IINxEtfWVYpTq6CgoKClaHYYJcDEbkC+EPg1diz6+3AGeD3gUPAE8APq+ozfvz7gTcB71bVe0TkpcDngZ9R1Q/4Mb8DPKiqd11ov7q1OmuqEhVp4+xyeKhsKBDMUQX09tlgGmq7UblGZHytsaJnwfIihElj6sbkrKfYaF4Om9lAbXmabK3ZmOcB6aMu21wThyvgxB39Z9HtxC6LMNRQu+SEcdNAdsikEidi5oq66RiPWtYb85pr6kviQPDogeqs2wI9GiLQL/lnqhIMrRDJThtNozeHlGdUBbdHjxXpzATQrYlpsW4qyKaIxBXb0tfTGiuds3eRwrVCH40Qpr22bFy7zv9qFxwmAZkIOnJHI5rbRQWtbWXRTy50W7WV5mnFTD2VRQ7oVJicaZCgrI97Pt4hXXCf69IzmfWZd3Mq5+DaVyGy1kypOuVos8lmNzKNFXXNVXOdr06FjmphdtjKUQTs0nAH8Leq+n0iMgI2gE8A73EB+nbgZ4HbReSr/DffCNwF3OPbTwG3iMgfqOqEJaA97IwhnSLRDG+Ww+7RANXAGRSkz6l3U0BCrI07QCtPyxwlodsL1WRzJdlanalJBRfSmklbUoRAumvMJGAe5yFR9jyG7Ei5lsEgAmCm/hMLhGsns4LVJZ95ygWpyPGxQK5ems4TgtK1bmP2kLMw9edT3ds+46jv08yKeXC/mV20F2Y5ZG09IoemECx3nzMV3XOB+jlnuxrZuVLYWLfuwnhswrLbiCAhh34NnWuZByGl9tZ2XnUnmNYRgsC4QxAjRliLRNpMwF035jiKOeVakRoUe3hL5o3w8yW76YJsqllTwXZbbAqXy1Podt0vG0+4cu0M1ZalwcbQ5nYsHCvSap8mGyQy3Rb4vWpoEbDLgIgcwYTljwG4cJyIyCuAe/2wTwB3A7djyZKJm374r/pv4D7gbcCHltG36XrIN3byHIfWhZpJIGNuqmSG4s4EZh9qlcuOeG2n6LbDrqEXqE1/88ZGe1tkEq5eXjs5UxLt3XzdrO1aq6e20ofutDHkmes1IlkoWJPNNbpwZbDPXkIKiB8S4bRdYEvqrF3F6BUNNjom0cY8OQrNsyZkk3Y4473HlGMgk7b0mr09hGLjc9NEpFGqcctoZI61qMJkvWbSjNicNlRn+wdZqkvWbURj7mqFajM5mSyeVKteuqcHIZCdjnkewIRipf2cKMioo2o6YhuQStFO6Noq/5l0ZAPc5iiUPjEkXYMYrFBh4nidRwg6o92qWlpuSqcNHgNbVZG1esoodIhrrAm9kDWHV0US7ov5DVYKBQpd4VLwFZhw/IiIfA1wErgFeBj4LuDPgZuB6wBU9RER2QD+EdNqh/hV4G9E5M5ldGzzqkA1UVtadp67rzIT7J6WkV0j2eECA49/INPgpdjK5C3v1vvP5uDS7M3WJKwEDwOKHsDud6JgNZ48vjUMlvuZ1WqHm2Lo0FokVFOUwJCEJIdlKSYUhtqkkINXUzG/LgbidDYms6o7ujqgh03rnByxB069ae00z5kQ7eg5BXIIVGte+aQ59kI10qybUF0bWTB+U3VM2jrXm+o2AtMXKRMvJqiVWlmWWuFQS5wGqtMVTCRrqkOS8m4kOckhcz8E3FbglySpsv7HkMoysNI1TA8idW4G7QLUAltV5mmwEjSKVOJCNi3/A7WabWQnXoBULmZIgJ6uaRWim2ymVCFyZLTFWmXeusQ5MESKGEhRBUmwX3IUDXZpbX0dcFxVHxCRO4DbMDvsb4vI+4C/APKyX1WPL2pIVT8vIp8CfmgZHdt6AbmYniRmfQ9ez+esoPVUT+g1m6EXekjinL8Lbm8MmgsSZq0ox1N6u+M4axLw+Na68XjKOUKPoVBL3+HHDUtZZ8Gq6Xf+PvR0u73VDKUuWKPMUvlVQ2m7PSIhn1KMbCYSICjTYy1xLcDTgfp0/1DS4HZLF7Bxo0PqmAWVtoI0kXrU0TQdo6bl2MYZDo+2WKssMHYSK852NacmV+TrJaPOY0vTg0Cpxy3aBFognKlmIxLUuGq7dVuppGiDJAzBH6htMBrA4HPsS/zs/a/SagOrpBslk2rPrgRifg91nxyiaoJTpNdeh6aBRQ/SoaCNmIlnY2PCizee4XBzljZWKMJWrE1bHfxfhmFZZoN9HoQrWqIIloRTwClVfcC3Pwbcpqq3A98CICJfCXzHebb3y97GvTsdMJlMOHHixDkb+umvvna2cuncA1WHNrqd4EpfYqZPDqlrRg23Xv/irPyw6H2RtiJzgnLB/l2/8yZfyJjj4eWDUwzsyb0snxvEgm7lOXDh77ZNV7L9fSDsK7vpr5Ex73nBdXBUkKul53R1p1GeszTWHIPlvLOBXEa8EiWcjVRbms+lGMPUFjVxQ7ZPpcA1jLl19DLbHgl6lMFTA7O1586kZbzOzqcnBqSih2nMMyfM5ktBm769a8KId191Xf+/SPPmJXvUzymi0LLwmi/kcU99Df3+oMrouY5ms6MSE/gb7WHe8NSb+tPTc29omqQ5nM99sxQoaImDvXio6pdE5EkReYWqPg58M/CoiLxQVZ8SkQC8F4soOJ/2PisijwLfCXxq0TGj0YibbrrpnG2d+4gLx4kTJ7j5PPpQzr9/+3DixAm+/3k+/1tveuvzdv5z4gBnci2b+eE48FER+QxwA6aF/qCI/BvwWeALwEf+H+39EvCSJfexoKDgUiIRJJ3rtQ+x1DAtVX0IeM3c13f463x+/wQWQ5u2P83yHwIFBQWXCqoliqCgoKBgZdin2un5oAjYgoKCFULR7hKTfF9GKAK2oKBgdVAOtJOrCNiCgoLV4gCHaRUHUkFBwcqggEY9r9f5QETeLCKPi8jnROS21fb+4lEEbEFBwepgbO7n9zoHRKQCfhf4NuBVWAjoq1Y8gotCMREUFBSsFEt0cr0W+Jyq/geAiPwx8N3Ao8s6wbKxpwXsyZMnT8puFQkKCgouBv9zsQ08y9N3/51+7KrzPHxNRB4cbH9QVT842L4WeHKwfQr4hovt4yqxpwWsqs4nNRQUFFxGUNU3L7G5RdrUZR2iUGywBQUFewWncLpTx0uw9PvLFkXAFhQU7BX8M/ByEbneK6b8AEaBetliT5sICgoKDg5UtRWRd2JVUSrgTlV95Hnu1q4QPcB5wgUFBQWrRDEROETkOhH5BxF5TEQeEZFb/PubfTuKyGvmfvN+EXlQRN7o238mIt8z2P+4iLx3sP1xEXnLJRrSBUFE7hSRp0Tk4cF3N4jIJ0XkIR/vawf79tUc7DD+XxCR//TxPyQi3z7Yt6/GX7BcFAHbo8XKh78SeB3wDg9ifhh4C3OVFeaq4r7DP98P3Oj7rwROA68f/Oz1fszljLuAec/vrwG/qKo3AO/z7f06B3exffwAv6WqN/jrr2Hfjr9giSgC1qGqX1TVf/HPzwKPAdeq6mNeoWEei6ri3offXP7+l8DVYrge2FTVL61yHBcLVb0X+N/5r4Ej/vkoved2383BDuPfCftu/AXLRXFyLYCIvBT4WuCBnY7ZoSruSeDV7uG8EbgHq7b7Sm/vvhV2e5W4FbhbRH4deyjfCAduDt4pIj8KPIitdJ4+YOMvuAAUDXYOInII+Dhwq6o+s9uxqnpcVb9eVf/et7eAR7Dquq/DBPQ/YTfajezdpeFPAe9S1euAdwEfTjsOyBz8HvAyrAzSF4HfSDsOyPgLLhBFwA4gIg0mXD+qqn96gc3cj9nkDqvq08An6W+uvaq9vA1I8/EnWE74bthXc6Cq/6WqnVp51A9xwMZfcOEoAtYhRmrwYeAxVf3Ni2jqPuAngU/79mcwTebLMc1mL+ILwBv98zcB/36O4/fVHIjIiwab34s5PnfDvhp/wYWj2GB7vAH4EeBfReQh/+7ngDHwAeBq4K9E5CFV/dZd2rkfs7n9CuTg6KeAJ3UPFIgXkT/CKp1fJSKngJ8Hfhy4Q0Rq4CzwE+doZs/OwQ7jv0lEbsCcWU9gwnM37NnxFywXJdGgoKCgYEUoJoKCgoKCFaEI2IKCgoIVoQjYgoKCghWhCNiCgoKCFaEI2IKCgoIVoQjYgoKCghWhCNiCgoKCFeH/AI+pUzc8zD0QAAAAAElFTkSuQmCC\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -424,7 +750,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:33.541570Z", + "iopub.status.busy": "2023-04-04T02:10:33.540947Z", + "iopub.status.idle": "2023-04-04T02:10:35.867232Z", + "shell.execute_reply": "2023-04-04T02:10:35.865351Z", + "shell.execute_reply.started": "2023-04-04T02:10:33.541513Z" + } + }, "outputs": [ { "name": "stdout", @@ -433,26 +767,14 @@ "Cutting out the oceandataset.\n" ] }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", + "image/png": 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", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -479,7 +801,15 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:35.869605Z", + "iopub.status.busy": "2023-04-04T02:10:35.868982Z", + "iopub.status.idle": "2023-04-04T02:10:35.897843Z", + "shell.execute_reply": "2023-04-04T02:10:35.895543Z", + "shell.execute_reply.started": "2023-04-04T02:10:35.869547Z" + } + }, "outputs": [ { "name": "stdout", @@ -487,10 +817,10 @@ "text": [ "\n", "Original: 1.034784936 Gigabytes\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 55, 'Zl': 55, 'Zp1': 56, 'Zu': 55, 'time': 4, 'time_midp': 3}\n", + "{'Z': 55, 'Zp1': 56, 'Zu': 55, 'Zl': 55, 'X': 207, 'Y': 154, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'time_midp': 3}\n", "\n", "Cutout: 18.010824 Megabytes\n", - "{'X': 170, 'Xp1': 171, 'Y': 93, 'Yp1': 94, 'Z': 1, 'Zl': 1, 'Zp1': 2, 'Zu': 1, 'time': 2, 'time_midp': 1}\n" + "{'Z': 1, 'Zp1': 2, 'Zu': 1, 'Zl': 1, 'X': 170, 'Y': 93, 'Xp1': 171, 'Yp1': 94, 'time': 2, 'time_midp': 1}\n" ] } ], @@ -511,7 +841,15 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:35.901070Z", + "iopub.status.busy": "2023-04-04T02:10:35.900508Z", + "iopub.status.idle": "2023-04-04T02:10:36.059151Z", + "shell.execute_reply": "2023-04-04T02:10:36.055762Z", + "shell.execute_reply.started": "2023-04-04T02:10:35.901016Z" + } + }, "outputs": [ { "name": "stdout", @@ -520,35 +858,35 @@ "Cutting out the oceandataset.\n", "\n", "Original oceandataset:\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 55, 'Zl': 55, 'Zp1': 56, 'Zu': 55, 'time': 4, 'time_midp': 3}\n", + "{'Z': 55, 'Zp1': 56, 'Zu': 55, 'Zl': 55, 'X': 207, 'Y': 154, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'time_midp': 3}\n", "\n", - "Y Axis (not periodic, boundary=None):\n", - " * center Y --> outer\n", - " * outer Yp1 --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", " * outer time --> center\n", + "X Axis (not periodic, boundary=None):\n", + " * center X --> outer\n", + " * outer Xp1 --> center\n", + "Y Axis (not periodic, boundary=None):\n", + " * center Y --> outer\n", + " * outer Yp1 --> center\n", "Z Axis (not periodic, boundary=None):\n", " * center Z --> left\n", - " * left Zl --> center\n", " * outer Zp1 --> center\n", " * right Zu --> center\n", - "X Axis (not periodic, boundary=None):\n", - " * center X --> outer\n", - " * outer Xp1 --> center\n", + " * left Zl --> center\n", "\n", "New oceandataset:\n", - "{'X': 207, 'Xp1': 208, 'Y': 154, 'Yp1': 155, 'Z': 1, 'Zl': 1, 'Zp1': 1, 'Zu': 1, 'time': 4, 'time_midp': 3}\n", + "{'Z': 1, 'Zp1': 1, 'Zu': 1, 'Zl': 1, 'X': 207, 'Y': 154, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'time_midp': 3}\n", "\n", + "X Axis (not periodic, boundary=None):\n", + " * center X --> outer\n", + " * outer Xp1 --> center\n", "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", " * outer Yp1 --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", - " * outer time --> center\n", - "X Axis (not periodic, boundary=None):\n", - " * center X --> outer\n", - " * outer Xp1 --> center\n" + " * outer time --> center\n" ] } ], @@ -595,7 +933,15 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:36.063452Z", + "iopub.status.busy": "2023-04-04T02:10:36.062682Z", + "iopub.status.idle": "2023-04-04T02:10:36.164611Z", + "shell.execute_reply": "2023-04-04T02:10:36.160865Z", + "shell.execute_reply.started": "2023-04-04T02:10:36.063359Z" + } + }, "outputs": [ { "name": "stdout", @@ -603,15 +949,22 @@ "text": [ "Computing kinetic energy using the following parameters: {'eps_nh': 0}.\n", "\n", - "Dimensions: (X: 207, Y: 154, Z: 1, time: 4)\n", + "Dimensions: (Z: 1, Y: 154, time: 4, X: 207)\n", "Coordinates:\n", - " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", " * Z (Z) float64 -1.0\n", " * Y (Y) float64 68.99 69.01 69.03 69.04 ... 71.95 71.97 72.0 72.02\n", + " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", " * X (X) float64 -22.02 -21.98 -21.93 -21.89 ... -13.05 -13.01 -12.96\n", "Data variables:\n", " KE (time, Z, Y, X) float64 dask.array\n", - "Attributes:\n", + "Attributes: (12/14)\n", + " build_date: ven 24 giu 2016, 09.35.54, EDT\n", + " build_user: malmans2@jhu.edu\n", + " MITgcm_URL: http://mitgcm.org\n", + " build_host: compute0117\n", + " MITgcm_tag_id: 1.2226 2016/01/20\n", + " MITgcm_version: checkpoint65s\n", + " ... ...\n", " OceanSpy_parameters: {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0':...\n", " OceanSpy_name: oceandataset #1\n", " OceanSpy_description: This is my first oceandataset\n", @@ -636,7 +989,15 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:36.167232Z", + "iopub.status.busy": "2023-04-04T02:10:36.166678Z", + "iopub.status.idle": "2023-04-04T02:10:36.280893Z", + "shell.execute_reply": "2023-04-04T02:10:36.272626Z", + "shell.execute_reply.started": "2023-04-04T02:10:36.167175Z" + } + }, "outputs": [ { "name": "stdout", @@ -644,116 +1005,44 @@ "text": [ "Computing kinetic energy using the following parameters: {'eps_nh': 0}.\n", "\n", - "Dimensions: (X: 207, Xp1: 208, Y: 154, Yp1: 155, Z: 1, Zl: 1, Zp1: 1, Zu: 1, time: 4, time_midp: 3)\n", - "Coordinates:\n", - " * X (X) float64 -22.02 -21.98 -21.93 -21.89 ... -13.05 -13.01 -12.96\n", - " * Y (Y) float64 68.99 69.01 69.03 69.04 ... 71.95 71.97 72.0 72.02\n", + "Dimensions: (Z: 1, Zp1: 1, Zu: 1, Zl: 1, X: 207, Y: 154, Xp1: 208,\n", + " Yp1: 155, time: 4, time_midp: 3)\n", + "Coordinates: (12/18)\n", " * Z (Z) float64 -1.0\n", - " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", - " * time_midp (time_midp) datetime64[ns] 2007-09-01T03:00:00 ... 2007-09-01...\n", - " * Zl (Zl) float64 0.0\n", " * Zp1 (Zp1) float64 0.0\n", " * Zu (Zu) float64 -2.0\n", - " XC (Y, X) float64 dask.array\n", - " YC (Y, X) float64 dask.array\n", - " * Xp1 (Xp1) float64 -22.04 -22.0 -21.96 ... -13.03 -12.98 -12.94\n", - " XU (Y, Xp1) float64 dask.array\n", - " YU (Y, Xp1) float64 dask.array\n", - " * Yp1 (Yp1) float64 68.98 69.0 69.02 69.03 ... 71.96 71.98 72.01 72.03\n", + " * Zl (Zl) float64 0.0\n", + " * X (X) float64 -22.02 -21.98 -21.93 -21.89 ... -13.05 -13.01 -12.96\n", + " * Y (Y) float64 68.99 69.01 69.03 69.04 ... 71.95 71.97 72.0 72.02\n", + " ... ...\n", " XV (Yp1, X) float64 dask.array\n", " YV (Yp1, X) float64 dask.array\n", " XG (Yp1, Xp1) float64 dask.array\n", " YG (Yp1, Xp1) float64 dask.array\n", - "Data variables:\n", + " * time (time) datetime64[ns] 2007-09-01 ... 2007-09-01T18:00:00\n", + " * time_midp (time_midp) datetime64[ns] 2007-09-01T03:00:00 ... 2007-09-01...\n", + "Data variables: (12/88)\n", " drC (Zp1) float64 dask.array\n", " drF (Z) float64 dask.array\n", " dxC (Y, Xp1) float64 dask.array\n", " dyC (Yp1, X) float64 dask.array\n", " dxF (Y, X) float64 dask.array\n", " dyF (Y, X) float64 dask.array\n", - " dxG (Yp1, X) float64 dask.array\n", - " dyG (Y, Xp1) float64 dask.array\n", - " dxV (Yp1, Xp1) float64 dask.array\n", - " dyU (Yp1, Xp1) float64 dask.array\n", - " rA (Y, X) float64 dask.array\n", - " rAw (Y, Xp1) float64 dask.array\n", - " rAs (Yp1, X) float64 dask.array\n", - " rAz (Yp1, Xp1) float64 dask.array\n", - " fCori (Y, X) float64 dask.array\n", - " fCoriG (Yp1, Xp1) float64 dask.array\n", - " R_low (Y, X) float64 dask.array\n", - " Ro_surf (Y, X) float64 dask.array\n", - " Depth (Y, X) float64 dask.array\n", - " HFacC (Z, Y, X) float64 dask.array\n", - " HFacW (Z, Y, Xp1) float64 dask.array\n", - " HFacS (Z, Yp1, X) float64 dask.array\n", - " EXFhs (time, Y, X) float64 dask.array\n", - " EXFhl (time, Y, X) float64 dask.array\n", - " EXFlwnet (time, Y, X) float64 dask.array\n", - " EXFswnet (time, Y, X) float64 dask.array\n", - " EXFqnet (time, Y, X) float64 dask.array\n", - " EXFtaux (time, Y, X) float64 dask.array\n", - " EXFtauy (time, Y, X) float64 dask.array\n", - " EXFuwind (time, Y, X) float64 dask.array\n", - " EXFvwind (time, Y, X) float64 dask.array\n", - " EXFatemp (time, Y, X) float64 dask.array\n", - " EXFaqh (time, Y, X) float64 dask.array\n", - " EXFevap (time, Y, X) float64 dask.array\n", - " EXFpreci (time, Y, X) float64 dask.array\n", - " EXFsnow (time, Y, X) float64 dask.array\n", - " EXFempmr (time, Y, X) float64 dask.array\n", - " EXFpress (time, Y, X) float64 dask.array\n", - " EXFroff (time, Y, X) float64 dask.array\n", - " EXFroft (time, Y, X) float64 dask.array\n", - " KPPhbl (time, Y, X) float64 dask.array\n", - " MXLDEPTH (time, Y, X) float64 dask.array\n", - " TRELAX (time, Y, X) float64 dask.array\n", - " SRELAX (time, Y, X) float64 dask.array\n", - " RHOAnoma (time, Z, Y, X) float64 dask.array\n", - " SIarea (time, Y, X) float64 dask.array\n", - " SIheff (time, Y, X) float64 dask.array\n", - " SIhsnow (time, Y, X) float64 dask.array\n", - " SIhsalt (time, Y, X) float64 dask.array\n", - " SIuice (time, Y, Xp1) float64 dask.array\n", - " SIvice (time, Yp1, X) float64 dask.array\n", - " momVort3 (time, Z, Yp1, Xp1) float64 dask.array\n", - " oceTAUX (time, Y, Xp1) float64 dask.array\n", - " oceTAUY (time, Yp1, X) float64 dask.array\n", - " oceFWflx (time, Y, X) float64 dask.array\n", - " oceSflux (time, Y, X) float64 dask.array\n", - " oceQnet (time, Y, X) float64 dask.array\n", - " oceQsw (time, Y, X) float64 dask.array\n", - " oceFreez (time, Y, X) float64 dask.array\n", - " oceSPflx (time, Y, X) float64 dask.array\n", - " oceSPDep (time, Y, X) float64 dask.array\n", - " phiHyd (time, Z, Y, X) float64 dask.array\n", - " phiHydLow (time, Y, X) float64 dask.array\n", - " U (time, Z, Y, Xp1) float64 dask.array\n", - " V (time, Z, Yp1, X) float64 dask.array\n", - " Temp (time, Z, Y, X) float64 dask.array\n", - " S (time, Z, Y, X) float64 dask.array\n", - " Eta (time, Y, X) float64 dask.array\n", - " W (time, Zl, Y, X) float64 dask.array\n", - " surForcT (time, Y, X) float64 dask.array\n", - " surForcS (time, Y, X) float64 dask.array\n", - " ADVr_SLT (time_midp, Zl, Y, X) float64 dask.array\n", - " ADVr_TH (time_midp, Zl, Y, X) float64 dask.array\n", - " ADVx_SLT (time_midp, Z, Y, Xp1) float64 dask.array\n", - " ADVx_TH (time_midp, Z, Y, Xp1) float64 dask.array\n", - " ADVy_SLT (time_midp, Z, Yp1, X) float64 dask.array\n", - " ADVy_TH (time_midp, Z, Yp1, X) float64 dask.array\n", - " DFrI_SLT (time_midp, Zl, Y, X) float64 dask.array\n", - " DFrI_TH (time_midp, Zl, Y, X) float64 dask.array\n", - " SFLUX (time_midp, Y, X) float64 dask.array\n", - " TFLUX (time_midp, Y, X) float64 dask.array\n", - " KPPg_SLT (time_midp, Zl, Y, X) float64 dask.array\n", + " ... ...\n", " KPPg_TH (time_midp, Zl, Y, X) float64 dask.array\n", " oceQsw_AVG (time_midp, Y, X) float64 dask.array\n", " oceSPtnd (time_midp, Z, Y, X) float64 dask.array\n", " meanTemp (Z, Y, X) float64 dask.array\n", " meanS (Z, Y, X) float64 dask.array\n", " KE (time, Z, Y, X) float64 dask.array\n", - "Attributes:\n", + "Attributes: (12/14)\n", + " build_date: ven 24 giu 2016, 09.35.54, EDT\n", + " build_user: malmans2@jhu.edu\n", + " MITgcm_URL: http://mitgcm.org\n", + " build_host: compute0117\n", + " MITgcm_tag_id: 1.2226 2016/01/20\n", + " MITgcm_version: checkpoint65s\n", + " ... ...\n", " OceanSpy_parameters: {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0':...\n", " OceanSpy_name: oceandataset #1\n", " OceanSpy_description: This is my first oceandataset\n", @@ -779,7 +1068,15 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:36.283790Z", + "iopub.status.busy": "2023-04-04T02:10:36.283155Z", + "iopub.status.idle": "2023-04-04T02:10:51.998142Z", + "shell.execute_reply": "2023-04-04T02:10:51.994833Z", + "shell.execute_reply.started": "2023-04-04T02:10:36.283734Z" + } + }, "outputs": [ { "name": "stdout", @@ -792,16 +1089,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in divide\n", + " return func(*(_execute_task(a, cache) for a in args))\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -810,14 +1105,12 @@ }, { "data": { - "image/png": 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -846,6 +1139,13 @@ "cell_type": "code", "execution_count": 14, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:52.000671Z", + "iopub.status.busy": "2023-04-04T02:10:52.000061Z", + "iopub.status.idle": "2023-04-04T02:10:52.281555Z", + "shell.execute_reply": "2023-04-04T02:10:52.278815Z", + "shell.execute_reply.started": "2023-04-04T02:10:52.000613Z" + }, "scrolled": true }, "outputs": [ @@ -855,9 +1155,9 @@ "text": [ "Computing gradient.\n", "Data variables:\n", - " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", - " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", - " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", + " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", + " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", + " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", " dTemp_dtime (time_midp, Z, Y, X) float64 dask.array\n" ] } @@ -878,7 +1178,15 @@ { "cell_type": "code", "execution_count": 15, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:52.284034Z", + "iopub.status.busy": "2023-04-04T02:10:52.283464Z", + "iopub.status.idle": "2023-04-04T02:10:52.941886Z", + "shell.execute_reply": "2023-04-04T02:10:52.938714Z", + "shell.execute_reply.started": "2023-04-04T02:10:52.283975Z" + } + }, "outputs": [ { "name": "stdout", @@ -908,7 +1216,15 @@ { "cell_type": "code", "execution_count": 16, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:52.949766Z", + "iopub.status.busy": "2023-04-04T02:10:52.948606Z", + "iopub.status.idle": "2023-04-04T02:10:54.404864Z", + "shell.execute_reply": "2023-04-04T02:10:54.399507Z", + "shell.execute_reply.started": "2023-04-04T02:10:52.949707Z" + } + }, "outputs": [ { "name": "stdout", @@ -918,9 +1234,9 @@ "GRADIENT\n", "Computing gradient.\n", "Data variables:\n", - " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", - " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", - " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", + " dTemp_dY (time, Z, Yp1, X) float64 dask.array\n", + " dTemp_dX (time, Z, Y, Xp1) float64 dask.array\n", + " dTemp_dZ (time, Zl, Y, X) float64 dask.array\n", " dTemp_dtime (time_midp, Z, Y, X) float64 dask.array\n", "\n", "DIVERGENCE\n", @@ -929,7 +1245,7 @@ "Data variables:\n", " dU_dX (time, Z, Y, X) float64 dask.array\n", " dV_dY (time, Z, Y, X) float64 dask.array\n", - " dW_dZ (time, Z, Y, X) float64 dask.array\n", + " dW_dZ (time, Z, Y, X) float64 dask.array\n", "\n", "CURL\n", "Computing curl.\n", @@ -938,9 +1254,9 @@ "Computing gradient.\n", "Computing gradient.\n", "Data variables:\n", - " dV_dX-dU_dY (time, Z, Yp1, Xp1) float64 dask.array\n", - " dW_dY-dV_dZ (time, Zl, Yp1, X) float64 dask.array\n", - " dU_dZ-dW_dX (time, Zl, Y, Xp1) float64 dask.array\n", + " dV_dX-dU_dY (time, Z, Yp1, Xp1) float64 dask.array\n", + " dW_dY-dV_dZ (time, Zl, Yp1, X) float64 dask.array\n", + " dU_dZ-dW_dX (time, Zl, Y, Xp1) float64 dask.array\n", "\n", "LAPLACIAN\n", "Computing laplacian.\n", @@ -948,9 +1264,9 @@ "Computing divergence.\n", "Computing gradient.\n", "Data variables:\n", - " ddTemp_dX_dX (time, Z, Y, X) float64 dask.array\n", - " ddTemp_dY_dY (time, Z, Y, X) float64 dask.array\n", - " ddTemp_dZ_dZ (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dX_dX (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dY_dY (time, Z, Y, X) float64 dask.array\n", + " ddTemp_dZ_dZ (time, Z, Y, X) float64 dask.array\n", "\n", "WEIGHTED MEAN\n", "Computing weighted_mean.\n", @@ -995,7 +1311,15 @@ { "cell_type": "code", "execution_count": 17, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:10:54.408769Z", + "iopub.status.busy": "2023-04-04T02:10:54.408114Z", + "iopub.status.idle": "2023-04-04T02:11:00.276116Z", + "shell.execute_reply": "2023-04-04T02:11:00.271834Z", + "shell.execute_reply.started": "2023-04-04T02:10:54.408710Z" + } + }, "outputs": [ { "name": "stdout", @@ -1003,7 +1327,7 @@ "text": [ "Computing weighted_mean.\n", "w_mean_Temp = 0.5421960292553055 degC\n", - "w_mean_S = 34.600691099468904 psu\n" + "w_mean_S = 34.600691099468904 g kg-1\n" ] } ], @@ -1026,7 +1350,15 @@ { "cell_type": "code", "execution_count": 18, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:11:00.279892Z", + "iopub.status.busy": "2023-04-04T02:11:00.279244Z", + "iopub.status.idle": "2023-04-04T02:11:02.745800Z", + "shell.execute_reply": "2023-04-04T02:11:02.743230Z", + "shell.execute_reply.started": "2023-04-04T02:11:00.279835Z" + } + }, "outputs": [ { "name": "stdout", @@ -1041,22 +1373,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:307: UserWarning: The .xlabels_top attribute is deprecated. Please use .top_labels to toggle visibility instead.\n", - " warnings.warn('The .xlabels_top attribute is deprecated. Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" + "/home/idies/mambaforge/envs/Oceanography/lib/python3.9/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in divide\n", + " return func(*(_execute_task(a, cache) for a in args))\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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", 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Please '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:343: UserWarning: The .ylabels_right attribute is deprecated. Please use .right_labels to toggle visibility instead.\n", - " warnings.warn('The .ylabels_right attribute is deprecated. Please '\n" - ] - }, { "data": { - "image/png": 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\n", 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"/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:741: UserWarning: The labels of this gridliner do not belong to the gridliner axes\n", - " warnings.warn('The labels of this gridliner do not belong to '\n", - "/home/idies/miniconda3/envs/Oceanography/lib/python3.8/site-packages/cartopy/mpl/gridliner.py:741: UserWarning: The labels of this gridliner do not belong to the gridliner axes\n", - " warnings.warn('The labels of this gridliner do not belong to '\n" - ] } ], "source": [ @@ -1250,7 +1570,15 @@ { "cell_type": "code", "execution_count": 21, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:11:17.762062Z", + "iopub.status.busy": "2023-04-04T02:11:17.761413Z", + "iopub.status.idle": "2023-04-04T02:11:17.783055Z", + "shell.execute_reply": "2023-04-04T02:11:17.779737Z", + "shell.execute_reply.started": "2023-04-04T02:11:17.761979Z" + } + }, "outputs": [ { "name": "stdout", @@ -1288,7 +1616,16 @@ { "cell_type": "code", "execution_count": 22, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-04T02:11:17.798048Z", + "iopub.status.busy": "2023-04-04T02:11:17.797473Z", + "iopub.status.idle": "2023-04-04T02:11:20.341580Z", + "shell.execute_reply": "2023-04-04T02:11:20.337939Z", + "shell.execute_reply.started": "2023-04-04T02:11:17.797994Z" + }, + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -1443,6 +1780,13 @@ "for name, desc in sorted(table.items()):\n", " print(\"{:>15}: {}\".format(name, desc))" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -1461,7 +1805,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.9.16" } }, "nbformat": 4, diff --git a/docs/_static/Kogur.gif b/docs/_static/Kogur.gif index b7473d391a8c8eb1a3a71aadd7d93c73195232be..e4bc2fbdf68e7fb89b4d9d5c422f0c7a13e2b09e 100644 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zp6k2)$vUMsTt>wDbK>XqoX_Ps_y6XwFZh*BBO)A=ThS!{hUK7 z=mgDdqi0FJ{z*N^l=~>a;@J<&dz*T)$syN&eCarudhcX}L`wD6(UQ+%>C}+3k5bMZ zNtU|&{phaCLKRjpa_jz{i-*MlYZg03oRhroc2`z%uKsr(U1ME0G1=>_e%;SA`w&gUWGpp#;6OIoqUWw+8l6TAN1-IrED zJb6-I@yX${Pfz@Nl74npaA;s^toaB-3wkG6C#TMYI4jAlG( wI8R1Dbcz?RGFqspavC#kKmdrppfDr=0(4)2_JKeK%mh7|AXcK0hC~oIRF3v From e7791141fe3dcc2f8b3c90c8977f71fbc26fe5b1 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Tue, 11 Apr 2023 08:19:22 -0400 Subject: [PATCH 02/32] masking and dataset list (#343) * compute masks * update dataset list, showing ECCO * add datasets * move order of datasets * . * restore all * restore all * compute when first masking * remove ECCO * include ECCO on dataset list * first perssit then compute * improved description of ECCO and daily ECCO --------- Co-authored-by: Miguel Jimenez --- docs/conf.py | 2 +- docs/datasets.rst | 360 +++++++++++++++++++++++++ oceanspy/subsample.py | 12 +- sciserver_catalogs/catalog_xarray.yaml | 10 +- 4 files changed, 372 insertions(+), 12 deletions(-) create mode 100644 docs/datasets.rst diff --git a/docs/conf.py b/docs/conf.py index 45727bd4..fba74658 100755 --- a/docs/conf.py +++ b/docs/conf.py @@ -238,7 +238,7 @@ SCISERVER_DATASETS = yaml.safe_load(f)["datasets"]["sciserver"] for name in SCISERVER_DATASETS: - if name in ["Arctic_Control", "LLC4320", "ECCO", "HYCOM"]: + if name in ["Arctic_Control", "LLC4320", "HYCOM"]: continue # Section diff --git a/docs/datasets.rst b/docs/datasets.rst new file mode 100644 index 00000000..ef1a3b72 --- /dev/null +++ b/docs/datasets.rst @@ -0,0 +1,360 @@ +.. _datasets: + +======== +Datasets +======== + +List of datasets available on SciServer. + +.. _get_started: + +----------- +get_started +----------- + +Small cutout from EGshelfIIseas2km_ASR_crop_. +Citation: + +* Almansi et al., 2020 - GRL. + +See also: + +* EGshelfIIseas2km_ASR_full_: Full domain without variables to close budgets. +* EGshelfIIseas2km_ASR_crop_: Cropped domain with variables to close budgets. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('get_started') + +.. _IGPwinter: + +--------- +IGPwinter +--------- + +High-resolution numerical simulation carried out in parallel to the observational +component of the Iceland Greenland Seas Project (IGP). +Citation: + +* Renfrew et al., 2019 - BAMS. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('IGPwinter') + +.. _EGshelfIIseas2km_ASR_full: + +------------------------- +EGshelfIIseas2km_ASR_full +------------------------- + +High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), +and the Iceland and Irminger Seas (IIseas) forced by the Arctic System Reanalysis (ASR). +Citation: + +* Almansi et al., 2020 - GRL. + +Characteristics: + +* full: Full domain without variables to close budgets. + +See also: + +* EGshelfIIseas2km_ASR_crop_: Cropped domain with variables to close budgets. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfIIseas2km_ASR_full') + +.. _EGshelfIIseas2km_ASR_crop: + +------------------------- +EGshelfIIseas2km_ASR_crop +------------------------- + +High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), +and the Iceland and Irminger Seas (IIseas) forced by the Arctic System Reanalysis (ASR). +Citation: + +* Almansi et al., 2020 - GRL. + +Characteristics: + +* crop: Cropped domain with variables to close budgets. + +See also: + +* EGshelfIIseas2km_ASR_full_: Full domain without variables to close budgets. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfIIseas2km_ASR_crop') + +.. _EGshelfIIseas2km_ERAI_6H: + +------------------------ +EGshelfIIseas2km_ERAI_6H +------------------------ + +High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), +and the Iceland and Irminger Seas (IIseas) forced by ERA-Interim. +Citation: + +* `Almansi et al., 2017 - JPO.`_ + +Characteristics: + +* 6H: 6-hour resolution without sea ice and external forcing variables. + +See also: + +* EGshelfIIseas2km_ERAI_1D_: 1-day resolution with sea ice and external forcing variables. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfIIseas2km_ERAI_6H') + +.. _EGshelfIIseas2km_ERAI_1D: + +------------------------ +EGshelfIIseas2km_ERAI_1D +------------------------ + +High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), +and the Iceland and Irminger Seas (IIseas) forced by ERA-Interim. +Citation: + +* `Almansi et al., 2017 - JPO.`_ + +Characteristics: + +* 1D: 1-day resolution with sea ice and external forcing variables. + +See also: + +* EGshelfIIseas2km_ERAI_6H_: 6-hour resolution without sea ice and external forcing variables. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfIIseas2km_ERAI_1D') + +.. _EGshelfSJsec500m_3H_hydro: + +------------------------- +EGshelfSJsec500m_3H_hydro +------------------------- + +Very high-resolution (500m) numerical simulation covering the east Greenland shelf (EGshelf) +and the Spill Jet section (SJsec). Hydrostatic solutions. + +Citation: + +* `Magaldi and Haine, 2015 - DSR.`_ + +Characteristics: + +* 3H: 3-hour resolution without external forcing variables. +* hydro: Hydrostatic solutions. + +See also: + +* EGshelfSJsec500m_6H_hydro_: 6-hour resolution with external forcing variables. Hydrostatic. +* EGshelfSJsec500m_6H_NONhydro_: 6-hour resolution with external forcing variables. Non-Hydrostatic. +* EGshelfSJsec500m_3H_NONhydro_: 3-hour resolution without external forcing variables. Non-Hydrostatic. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfSJsec500m_3H_hydro') + +.. _EGshelfSJsec500m_6H_hydro: + +------------------------- +EGshelfSJsec500m_6H_hydro +------------------------- + +Very high-resolution (500m) numerical simulation covering the east Greenland shelf (EGshelf) +and the Spill Jet section (SJsec). Hydrostatic solutions. + +Citation: + +* `Magaldi and Haine, 2015 - DSR.`_ + +Characteristics: + +* 6H: 6-hour resolution with external forcing variables. +* hydro: Hydrostatic solutions. + +See also: + +* EGshelfSJsec500m_3H_hydro_: 3-hour resolution without external forcing variables. Hydrostatic. +* EGshelfSJsec500m_6H_NONhydro_: 6-hour resolution with external forcing variables. Non-Hydrostatic. +* EGshelfSJsec500m_3H_NONhydro_: 3-hour resolution without external forcing variables. Non-Hydrostatic. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfSJsec500m_6H_hydro') + +.. _EGshelfSJsec500m_3H_NONhydro: + +---------------------------- +EGshelfSJsec500m_3H_NONhydro +---------------------------- + +Very high-resolution (500m) numerical simulation covering the east Greenland shelf (EGshelf) +and the Spill Jet section (SJsec). Non-Hydrostatic solutions. + +Citation: + +* `Magaldi and Haine, 2015 - DSR.`_ + +Characteristics: + +* 3H: 3-hour resolution without external forcing variables. +* NONhydro: Non-Hydrostatic solutions. + +See also: + +* EGshelfSJsec500m_6H_NONhydro_: 6-hour resolution with external forcing variables. Non-Hydrostatic. +* EGshelfSJsec500m_6H_hydro_: 6-hour resolution with external forcing variables. Hydrostatic. +* EGshelfSJsec500m_3H_hydro_: 3-hour resolution without external forcing variables. Hydrostatic. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfSJsec500m_3H_NONhydro') + +.. _EGshelfSJsec500m_6H_NONhydro: + +---------------------------- +EGshelfSJsec500m_6H_NONhydro +---------------------------- + +Very high-resolution (500m) numerical simulation covering the east Greenland shelf (EGshelf) +and the Spill Jet section (SJsec). Non-Hydrostatic solutions. + +Citation: + +* `Magaldi and Haine, 2015 - DSR.`_ + +Characteristics: + +* 6H: 6-hour resolution with external forcing variables. +* NONhydro: NONHydrostatic solutions. + +See also: + +* EGshelfSJsec500m_3H_NONhydro_: 3-hour resolution without external forcing variables. Non-Hydrostatic. +* EGshelfSJsec500m_6H_hydro_: 6-hour resolution with external forcing variables. Hydrostatic. +* EGshelfSJsec500m_3H_hydro_: 3-hour resolution without external forcing variables. Hydrostatic. + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('EGshelfSJsec500m_6H_NONhydro') + +.. _KangerFjord: + +----------- +KangerFjord +----------- + +A realistic numerical model constructed to simulate the oceanic conditions +and circulation in a large southeast Greenland fjord (Kangerdlugssuaq) and +the adjacent shelf sea region during winter 2007–2008. + +Citation: + +* `Fraser et al., 2018 - JGR.`_ + + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('KangerFjord') + +.. _ECCO: + +---- +ECCO +---- + +ECCO_ v4r4 3D dataset, ocean simulations on LLC90 grid + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('ECCO') + +.. _daily_ecco: + +---------- +daily_ecco +---------- + +ECCO_ v4r4 3D dataset, ocean simulations on LLC90 grid + +Run the following code to open the dataset: + +.. code-block:: ipython + :class: no-execute + + import oceanspy as ospy + od = ospy.open_oceandataset.from_catalog('daily_ecco') + +.. _`Almansi et al., 2017 - JPO.`: https://journals.ametsoc.org/doi/full/10.1175/JPO-D-17-0129.1 +.. _`Magaldi and Haine, 2015 - DSR.`: https://www.sciencedirect.com/science/article/pii/S0967063714001915 +.. _`Fraser et al., 2018 - JGR.`: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018JC014435 diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index 6118727b..7bd48003 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -246,7 +246,7 @@ def cutout( # Find time indexes maskT = maskT.assign_coords(time=_np.arange(len(maskT["time"]))) - dmaskT = maskT.where(maskT, drop=True) + dmaskT = maskT.where(maskT.compute(), drop=True) dtime = dmaskT["time"].values iT = [min(dtime), max(dtime)] maskT["time"] = ds["time"] @@ -298,7 +298,7 @@ def cutout( # Find vertical indexes maskV = maskV.assign_coords(Zp1=_np.arange(len(maskV["Zp1"]))) - dmaskV = maskV.where(maskV, drop=True) + dmaskV = maskV.where(maskV.compute(), drop=True) dZp1 = dmaskV["Zp1"].values iZ = [_np.min(dZp1), _np.max(dZp1)] maskV["Zp1"] = ds["Zp1"] @@ -529,13 +529,13 @@ def cutout( for var in ds.data_vars: if set(["X", "Y"]).issubset(ds[var].dims): - ds[var] = ds[var].where(maskC, drop=True) + ds[var] = ds[var].where(maskC.compute(), drop=True) elif set(["Xp1", "Yp1"]).issubset(ds[var].dims): - ds[var] = ds[var].where(maskG, drop=True) + ds[var] = ds[var].where(maskG.compute(), drop=True) elif set(["Xp1", "Y"]).issubset(ds[var].dims): - ds[var] = ds[var].where(maskU, drop=True) + ds[var] = ds[var].where(maskU.compute(), drop=True) elif set(["X", "Yp1"]).issubset(ds[var].dims): - ds[var] = ds[var].where(maskV, drop=True) + ds[var] = ds[var].where(maskV.compute(), drop=True) # --------------------------- # TIME RESAMPLING diff --git a/sciserver_catalogs/catalog_xarray.yaml b/sciserver_catalogs/catalog_xarray.yaml index a6928886..6b209880 100644 --- a/sciserver_catalogs/catalog_xarray.yaml +++ b/sciserver_catalogs/catalog_xarray.yaml @@ -865,7 +865,7 @@ sources: tempFrz0: 9.01e-02 dTempFrz_dS: -5.75e-02 name: ECCO_v4r4 - description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid + description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid (monthly mean output) citation: projection: original_output: monthly mean @@ -904,10 +904,10 @@ sources: tempFrz0: 9.01e-02 dTempFrz_dS: -5.75e-02 name: ECCO_v4r4 - description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid + description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid (daily output) citation: projection: - original_output: monthly mean + original_output: daily output # ECCOv4r4 data daily daily_ecco_snap: @@ -922,10 +922,10 @@ sources: parallel: true metadata: name: ECCO_v4r4 - description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid + description: ECCO v4r4 3D dataset, ocean simulations on LLC90 grid (daily mean) citation: projection: - original_output: daily snapshot + original_output: daily mean # ECCOv4r4 data daily daily_ecco_mean: From 2f26afaa6421908fda3e532e65162dcebea53b1b Mon Sep 17 00:00:00 2001 From: Thomas Haine Date: Tue, 11 Apr 2023 12:53:09 -0400 Subject: [PATCH 03/32] Update Live_Demo.ipynb Downloads the OSM2020_EGshelfIIseas2km_ERAI_1D test dataset if necessary. --- binder/Live_Demo.ipynb | 19500 ++++++++++++++++++++++++++++++++++++++- 1 file changed, 19462 insertions(+), 38 deletions(-) diff --git a/binder/Live_Demo.ipynb b/binder/Live_Demo.ipynb index add1c7b2..edfaabdd 100644 --- a/binder/Live_Demo.ipynb +++ b/binder/Live_Demo.ipynb @@ -108,8 +108,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:48:38.436009Z", + "iopub.status.busy": "2023-04-11T16:48:38.435330Z", + "iopub.status.idle": "2023-04-11T16:48:57.336749Z", + "shell.execute_reply": "2023-04-11T16:48:57.334214Z", + "shell.execute_reply.started": "2023-04-11T16:48:38.435944Z" + }, "slideshow": { "slide_type": "-" } @@ -125,11 +132,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:48:57.342882Z", + "iopub.status.busy": "2023-04-11T16:48:57.341519Z", + "iopub.status.idle": "2023-04-11T16:48:57.356685Z", + "shell.execute_reply": "2023-04-11T16:48:57.354441Z", + "shell.execute_reply.started": "2023-04-11T16:48:57.342824Z" + }, "slideshow": { "slide_type": "fragment" - } + }, + "tags": [] }, "outputs": [], "source": [ @@ -138,6 +153,7 @@ "import cartopy.crs as ccrs\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", + "from pathlib import Path\n", "\n", "# Import additional packages and change some defaults\n", "import xarray as xr\n", @@ -163,17 +179,369 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:48:57.359430Z", + "iopub.status.busy": "2023-04-11T16:48:57.358820Z", + "iopub.status.idle": "2023-04-11T16:49:47.330962Z", + "shell.execute_reply": "2023-04-11T16:49:47.328208Z", + "shell.execute_reply.started": "2023-04-11T16:48:57.359341Z" + }, "slideshow": { "slide_type": "-" - } + }, + "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The folder OSM2020_EGshelfIIseas2km_ERAI_1D does not exist...downloading...\n", + "--2023-04-11 12:48:57-- https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/ETTi4yKjbvxOvraRKaydA3kBy_sOKNmkqGFP61CfsgW_bQ?download=1\n", + "Resolving livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)... 13.107.138.8, 13.107.136.8, 2620:1ec:8fa::8, ...\n", + "Connecting to 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"OSM2020_EGshelfIIseas2km_ERAI_1D/Eta/12.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/.zarray\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/.zattrs\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/0.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/4.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/8.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/12.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/2.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/3.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/6.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/14.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/1.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/5.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/10.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/13.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/9.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/7.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/W/11.0.0.0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/time_midp/\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/time_midp/.zarray\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/time_midp/.zattrs\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/time_midp/0\n", + "OSM2020_EGshelfIIseas2km_ERAI_1D/.zmetadata\n", + "Opening dataset from [OSM2020_EGshelfIIseas2km_ERAI_1D].\n" + ] + } + ], "source": [ "# Import OceanDataset\n", - "od = ospy.open_oceandataset.from_zarr(\"OSM2020_EGshelfIIseas2km_ERAI_1D\")\n", "\n", + "# Download the data if you don't already have it. E.g., you're running the notebook in a non-binder environment.\n", + "path_to_file = 'OSM2020_EGshelfIIseas2km_ERAI_1D'\n", + "path = Path(path_to_file)\n", + "if not(path.is_dir()):\n", + " print(f'The folder {path_to_file} does not exist...downloading...')\n", + " # myurl=\"https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/ETTi4yKjbvxOvraRKaydA3kBy_sOKNmkqGFP61CfsgW_bQ?\"\n", + " !wget -v -O tmp.tar.gz -L https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/ETTi4yKjbvxOvraRKaydA3kBy_sOKNmkqGFP61CfsgW_bQ?download=1\n", + " !tar xvzf tmp.tar.gz \n", + " !rm -f tmp.tar.gz \n", + "else:\n", + " print(f'The folder {path_to_file} exists...reading...')\n", + "\n", + "# Then read the data\n", + "od = ospy.open_oceandataset.from_zarr(path_to_file) " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:47.335663Z", + "iopub.status.busy": "2023-04-11T16:49:47.335032Z", + "iopub.status.idle": "2023-04-11T16:49:47.708799Z", + "shell.execute_reply": "2023-04-11T16:49:47.706546Z", + "shell.execute_reply.started": "2023-04-11T16:49:47.335593Z" + }, + "slideshow": { + "slide_type": "-" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "\n", + "\n", + "Main attributes:\n", + " .dataset: \n", + " .grid: \n", + " .projection: \n", + "\n", + "More attributes:\n", + " .name: EGshelfIIseas2km_ERAI_1D\n", + " .description: High-resolution (~2km) numerical simulation covering the east Greenland shelf (EGshelf), \n", + "and the Iceland and Irminger Seas (IIseas) forced by ERA-Interim. \n", + " .parameters: \n", + " .grid_coords: " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ "# Show OceanDataset\n", "od" ] @@ -191,14 +559,2969 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:47.711627Z", + "iopub.status.busy": "2023-04-11T16:49:47.711048Z", + "iopub.status.idle": "2023-04-11T16:49:48.042059Z", + "shell.execute_reply": "2023-04-11T16:49:48.039835Z", + "shell.execute_reply.started": "2023-04-11T16:49:47.711574Z" + }, "scrolled": true, "slideshow": { "slide_type": "-" - } + }, + "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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    <xarray.Dataset>\n",
+       "Dimensions:    (Y: 162, X: 143, time: 15, Z: 123, Yp1: 163, Xp1: 144, Zl: 123,\n",
+       "                Zp1: 124, Zu: 123, time_midp: 14)\n",
+       "Coordinates: (12/18)\n",
+       "  * X          (X) float64 -27.74 -27.7 -27.65 -27.61 ... -21.58 -21.54 -21.49\n",
+       "    XC         (Y, X) float64 dask.array<chunksize=(162, 143), meta=np.ndarray>\n",
+       "    XG         (Yp1, Xp1) float64 dask.array<chunksize=(163, 144), meta=np.ndarray>\n",
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+       "  * Xp1        (Xp1) float64 -27.76 -27.72 -27.67 ... -21.56 -21.52 -21.47\n",
+       "    ...         ...\n",
+       "  * Z          (Z) float64 -1.0 -3.5 -7.0 ... -1.716e+03 -1.732e+03 -1.746e+03\n",
+       "  * Zl         (Zl) float64 0.0 -2.0 -5.0 ... -1.709e+03 -1.724e+03 -1.739e+03\n",
+       "  * Zp1        (Zp1) float64 0.0 -2.0 -5.0 ... -1.724e+03 -1.739e+03 -1.754e+03\n",
+       "  * Zu         (Zu) float64 -2.0 -5.0 -9.0 ... -1.724e+03 -1.739e+03 -1.754e+03\n",
+       "  * time       (time) datetime64[ns] 2007-09-01 2007-09-03 ... 2007-09-29\n",
+       "  * time_midp  (time_midp) datetime64[ns] 2007-09-02 2007-09-04 ... 2007-09-28\n",
+       "Data variables: (12/26)\n",
+       "    Depth      (Y, X) float64 dask.array<chunksize=(162, 143), meta=np.ndarray>\n",
+       "    Eta        (time, Y, X) float64 dask.array<chunksize=(1, 162, 143), meta=np.ndarray>\n",
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+       "    HFacS      (Z, Yp1, X) float64 dask.array<chunksize=(123, 163, 143), meta=np.ndarray>\n",
+       "    HFacW      (Z, Y, Xp1) float64 dask.array<chunksize=(123, 162, 144), meta=np.ndarray>\n",
+       "    S          (time, Z, Y, X) float64 dask.array<chunksize=(1, 123, 162, 143), meta=np.ndarray>\n",
+       "    ...         ...\n",
+       "    fCori      (Y, X) float64 dask.array<chunksize=(162, 143), meta=np.ndarray>\n",
+       "    fCoriG     (Yp1, Xp1) float64 dask.array<chunksize=(163, 144), meta=np.ndarray>\n",
+       "    rA         (Y, X) float64 dask.array<chunksize=(162, 143), meta=np.ndarray>\n",
+       "    rAs        (Yp1, X) float64 dask.array<chunksize=(163, 143), meta=np.ndarray>\n",
+       "    rAw        (Y, Xp1) float64 dask.array<chunksize=(162, 144), meta=np.ndarray>\n",
+       "    rAz        (Yp1, Xp1) float64 dask.array<chunksize=(163, 144), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    OceanSpy_description:    High-resolution (~2km) numerical simulation cove...\n",
+       "    OceanSpy_grid_coords:    {'Y': {'Y': None, 'Yp1': 0.5}, 'X': {'X': None, ...\n",
+       "    OceanSpy_grid_periodic:  []\n",
+       "    OceanSpy_name:           EGshelfIIseas2km_ERAI_1D\n",
+       "    OceanSpy_parameters:     {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0':...\n",
+       "    OceanSpy_projection:     Mercator(**{})
    " + ], + "text/plain": [ + "\n", + "Dimensions: (Y: 162, X: 143, time: 15, Z: 123, Yp1: 163, Xp1: 144, Zl: 123,\n", + " Zp1: 124, Zu: 123, time_midp: 14)\n", + "Coordinates: (12/18)\n", + " * X (X) float64 -27.74 -27.7 -27.65 -27.61 ... -21.58 -21.54 -21.49\n", + " XC (Y, X) float64 dask.array\n", + " XG (Yp1, Xp1) float64 dask.array\n", + " XU (Y, Xp1) float64 dask.array\n", + " XV (Yp1, X) float64 dask.array\n", + " * Xp1 (Xp1) float64 -27.76 -27.72 -27.67 ... -21.56 -21.52 -21.47\n", + " ... ...\n", + " * Z (Z) float64 -1.0 -3.5 -7.0 ... -1.716e+03 -1.732e+03 -1.746e+03\n", + " * Zl (Zl) float64 0.0 -2.0 -5.0 ... -1.709e+03 -1.724e+03 -1.739e+03\n", + " * Zp1 (Zp1) float64 0.0 -2.0 -5.0 ... -1.724e+03 -1.739e+03 -1.754e+03\n", + " * Zu (Zu) float64 -2.0 -5.0 -9.0 ... -1.724e+03 -1.739e+03 -1.754e+03\n", + " * time (time) datetime64[ns] 2007-09-01 2007-09-03 ... 2007-09-29\n", + " * time_midp (time_midp) datetime64[ns] 2007-09-02 2007-09-04 ... 2007-09-28\n", + "Data variables: (12/26)\n", + " Depth (Y, X) float64 dask.array\n", + " Eta (time, Y, X) float64 dask.array\n", + " HFacC (Z, Y, X) float64 dask.array\n", + " HFacS (Z, Yp1, X) float64 dask.array\n", + " HFacW (Z, Y, Xp1) float64 dask.array\n", + " S (time, Z, Y, X) float64 dask.array\n", + " ... ...\n", + " fCori (Y, X) float64 dask.array\n", + " fCoriG (Yp1, Xp1) float64 dask.array\n", + " rA (Y, X) float64 dask.array\n", + " rAs (Yp1, X) float64 dask.array\n", + " rAw (Y, Xp1) float64 dask.array\n", + " rAz (Yp1, Xp1) float64 dask.array\n", + "Attributes:\n", + " OceanSpy_description: High-resolution (~2km) numerical simulation cove...\n", + " OceanSpy_grid_coords: {'Y': {'Y': None, 'Yp1': 0.5}, 'X': {'X': None, ...\n", + " OceanSpy_grid_periodic: []\n", + " OceanSpy_name: EGshelfIIseas2km_ERAI_1D\n", + " OceanSpy_parameters: {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho0':...\n", + " OceanSpy_projection: Mercator(**{})" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# List variables and metadata.\n", "# Exit presentation mode (Alt+r) for better display.\n", @@ -218,13 +3541,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:48.044682Z", + "iopub.status.busy": "2023-04-11T16:49:48.044104Z", + "iopub.status.idle": "2023-04-11T16:49:49.623049Z", + "shell.execute_reply": "2023-04-11T16:49:49.620211Z", + "shell.execute_reply.started": "2023-04-11T16:49:48.044627Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Note: Automatically projected using od.projection\n", "fig = plt.figure(figsize=mapsize)\n", @@ -276,13 +3617,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:49.636557Z", + "iopub.status.busy": "2023-04-11T16:49:49.635568Z", + "iopub.status.idle": "2023-04-11T16:49:53.628922Z", + "shell.execute_reply": "2023-04-11T16:49:53.626634Z", + "shell.execute_reply.started": "2023-04-11T16:49:49.636466Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cutting out the oceandataset.\n", + "Extracting mooring array.\n" + ] + } + ], "source": [ "# Kögur coordinates\n", "lats_Kogur = [68.68, 67.52, 66.49]\n", @@ -305,13 +3662,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:53.632113Z", + "iopub.status.busy": "2023-04-11T16:49:53.631493Z", + "iopub.status.idle": "2023-04-11T16:49:54.477271Z", + "shell.execute_reply": "2023-04-11T16:49:54.474743Z", + "shell.execute_reply.started": "2023-04-11T16:49:53.632056Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Show the array on top of bathymetry\n", "fig = plt.figure(figsize=mapsize)\n", @@ -333,13 +3708,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:54.480480Z", + "iopub.status.busy": "2023-04-11T16:49:54.479826Z", + "iopub.status.idle": "2023-04-11T16:49:57.036978Z", + "shell.execute_reply": "2023-04-11T16:49:57.034535Z", + "shell.execute_reply.started": "2023-04-11T16:49:54.480419Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing weighted_mean.\n", + "Computing weighted_mean.\n", + "Isopycnals: Computing potential density anomaly using the following parameters: {'eq_state': 'jmd95'}.\n" + ] + }, + { + "data": { + "image/png": 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vv/8WFZIp6pbl3bt3omeRS5culXhdhJ49e8YSEhKKfe7p6VmiAsiQkBC2fft2lZqfC9df0bGirop4zjKmnftgbGysqDm5omuhsIm2h4dHqddHlpSUFFHB9Pr160t8rRLev4T31iFDhiid99mzZzy+T58+rE2bNlQASSqMci/RS0lJYdu2bVN4I6MCSNUdOXKE7d+/n2VlZZV3VkpF+OChzo96oll5eXnM0dGR74tVq1bJjf3iiy94XOfOnRWme/nyZdHD0fv372XG7d+/n8dZWloqrKmXnp7OLC0tefzff/+t2krKkZiYKCrQW7t2banSK0r4b+gPP/ygMHbJkiU8tnHjxjJjNm3axGOqVKmitDDn/PnzPN7e3l7ug6y6ynqflVUBpDwlLYBUR1JSkqi20MGDBzWSbkU7ZxkrqFksrP24Z88ehfHjxo3jsYr6T+zevTuP+/zzzxWmuXv3bh5bqVIlhbWWS0pYw2vMmDEsOjpaVKClam3togWQb968YXp6egwAa9u2rdL527dvzwAwPT099vbt2/90AaS6Bg0axNetZ8+ecuO0cU7FxMSICumuXLmiMK/CP4WnTZum2goqIOyjr2/fvqVOT0jT17UnT56Ijus7d+4oTDM5OZmZmZnxeE0V/qjj8ePHojzLq4k5ZMgQHtO7d2+l6Qprqg0cOFDDuRYraQGkuoTH4tSpUzWSZkU8ZxnTzn1wxYoVPK5OnToKa6G+efNGtA1u375dqvWRRVhz1cXFhTHGRP3mq1NbW3j/OnnyJP8jw9jYWOkfyf/73//4vIcOHaICSFKhlMso2IX9iAwbNgz29vYYM2YMXrx4IYoJCQmROeqsvNHzio62qMqotcLRqQrnf/bsGWbMmAE3NzeYm5vD1NQULVu2xC+//CJztMwbN25g+PDhqFu3LkxMTGBraws/Pz8cOXJE7e1y/vx5TJw4EQ0aNEClSpVgaGgIR0dH+Pn5Yf369cjMzFSaxu3btzFo0CA4ODhg4sSJuHr1qtr5KC/C0YmFI9N5e3sr3N/C+QpHBktKSsLatWvRsWNHODk5QU9PDxKJBElJScWWGxcXh2XLlsHT0xMODg4wNDSEra0tmjVrhlmzZuHx48dK8y4cSbRGjRr88+DgYPj7+6NWrVowMjKCtbU1unTpgmPHjhVLQyqV4tChQ+jWrRsfUa5q1aoYNmwYHjx4oPJ21CRdXV20adOGT8sb1ZQxhqNHj/Lp0aNHK0y3Xbt2cHV1BVCw3rK2BwAcPnyYvx88eDBMTEzkpmliYoJBgwbx6UOHDinMgzJ//PEH73tFX18f/v7+pUpP6MWLF6LjatSoUQrjhd/fv38fL1++LBZz7do1/r5Tp04wMDBQmKanpydMTU0BFIzqeeXKFRVyrlx57rOKytLSEg0aNODTmhhduCKes0DBs0Phdd7c3Bz9+/dXGC9c7zNnziA9Pb1YTFpamqhvKmXbasCAATA3NwcAJCQkiPpk1YS0tDTRaNfDhw+Hvb09OnfuzD+T1T+kKqpUqYKuXbsCAEJDQ2VeawpFRETw60a3bt1K3e9kIeH99M2bN/zzmjVrqj168rVr1zBlyhQ0aNAA1tbW/L7atWtXrF+/Xub+Livt2rXj7xWd09o4p44ePcpH4a5Tpw7atm2rMK/CY16Yn5Io2kffyJEjS5WekDaua8J7q4ODA5o2baowTQsLC9G+PXjwoCpZ16j69euL+miUd3wJ161bt25K0+3evTt/f+LECZV+l3zsVD0P1VHRzllAe/dBYd4Kf8/JU716dVF/ktp4ZhTeOwv7fR8+fLjM79VV2M9sZmYm/vrrL7lxjDHs3r0bAGBjY4PPPvusxMsk5GNUpgWQjx8/xuzZs1G9enV06dIFe/bsQUZGRllmQaEdO3agSZMmWLNmDcLDw5GWloaMjAzcunULX375Jbp3784LJKRSKcaPH482bdpg9+7dePbsGTIzMxEfH48zZ86gT58+mDFjhkrLfffuHby9veHr64vffvsNjx8/RmJiInJychAdHY0zZ85g6tSpqF27Ni5duqRSmomJifjtt9/Qtm1b1KlTB0uWLBE9yFdkV65cQePGjTF9+nRcunQJUVFRcju43rZtG2rXro05c+bwTo5zcnIQHx+Pu3fvYuXKlWjcuDFmzJihVifZUqkUU6dORadOnfDHH38gIiIC2dnZSEpKwtmzZ9GrVy/MmzePx79//x7t27dHv379cOrUKbx9+xbZ2dmIjIzEnj170KJFCxw4cKDU26YkhA8D8rbB8+fPRR02e3l5KU1XGBMUFCQzRtihv6bSVJWw4/Du3btr7Mc1IM5bnTp1lA5+4eTkxH8kASg20AEAUQfyzs7OSvOgq6sLJycnPi18sCyN8txnFZkq56E6KuI5W3T5Hh4eMDQ0VBjfunVr/uMwKytL5p92oaGh/N5vamqqdMAQQ0NDuLu782lNH9cHDhzgBWfVq1eHp6cnAPGPpD179pT4OBEOxqFogJnAwEA+MJQqAxOVpfT0dAwZMgQeHh7YsGEDHj9+jKSkJH5fPX36NKZOnQpXV1ecPHmyXPKo6jmtjXNK3TS9vb35+7dv3xarNKAO4Q/4ypUriwq1Sksb1zXhvbV69eoq5UN4D9bUvVVdqhxf6j43CGPS09Nx/fr1UuTw46DpeytQ8c5ZQDv3waysLFEheHk/M0ZERIh+ZxcWQAYEBPCBnIoO5KmOgIAAPviMonvrxYsXeWH4kCFDoK+vX6LlEfKx0vqwwnFxcdi3bx8CAwNx8+bNYt+bmZmhX79+aN++vehzJycnPprehg0b+OfyRtizsLAoVT5PnDiBKVOmgDGG+vXro2XLltDX10dYWBivfXbu3DlMnToVv//+OyZOnIgtW7ZAR0cH7u7uqFevHrKzsxEcHMxHBluzZg1atmyJgIAAucsNDw+Hj48PoqOjARTcCJs2bYoGDRrAxMQEkZGRuHjxIlJTUxEVFYXOnTvj5MmTohuLUM+ePfHgwQMcP36c3yieP3+OefPmYf78+ejYsSNGjhwp+meqNEJCQkR5iYiIENUAVIdwdOJDhw7x7dinTx9RQQkgf3+/ePEC06dPR3JysswRCoVWrlyJWbNm8WlDQ0N4enqievXqSExMRHBwMBISEiCVSrFmzRq8efMGBw8eVPjvXKG5c+di/fr10NHRgYeHB+rWrYusrCwEBwfzfb1kyRLUr18fffr0QefOnXH//n2YmJjA09MTVatWxYcPH3Du3DmkpaUhNzcXw4YNQ7NmzeDi4qL6RtUAYe3LatWqyYwJDw/n7+3t7eHg4KA03ebNm8ucv1BycjLfVkXjVUkzMjISKSkpJbo2PH/+XFQQoayGorqE66vKehXGFY6eKmt7FRYEAFDpGC2qpA9UQuW5zyqy7Oxsvu8B+echUFCDo2bNmnw6ODhY5kP9p3bOLly4EIsWLQJQ8CNYXk0Vdc8tPT09NGrUiP+QDg8Ph6+vr9w0GzVqBD095Y9OzZs3x9mzZ4vNrwnCApyAgAB+vvft2xfm5uZITU1FTEwMTp8+XaLCnV69esHKygpJSUnYvXs3Fi5cKPOasmvXLgAFo7D27NlTY6PUW1hY8Ge9wMBApKamAigo5JT13FL0+SAjIwOdOnUS1bJzdHREhw4dYGZmhhcvXuDy5cuQSqWIjo5Gr169sG/fPgwYMEAj+VeVKvdWbZ1T6p4nDg4OsLOz4wVW4eHhqF27ttL5isrPz+c1ewBg6NChGv1xrY3r2sdwb1VXVFQUEhIS+LSie0ahkq6bKoVGHzNVzsNCNWrU4JU5FixYgIULFxaL+dTOWVV/x2njPvj06VNeq1MikaBZs2YqpSkrT5og/FPNw8ODb6+qVavC29ub/5mwc+dOrFixQu30C1sqnDp1CpcuXcLr169lbmvhPf5j+3OPEI3QRrvu7Oxs9vfff7PevXuLOngvfOnq6rKuXbuy3bt3qzT6qnBeVakyj7BvBgMDA2ZhYcGOHDlSLG7t2rU8Tk9Pj61cuZIBYI0aNSrWt0tWVpZoZL2aNWvK7c8iPT2d1a9fn8f6+vqyp0+fFotLTk5mEydO5HEODg4sKSlJ4fonJCSwTZs2sfbt2zOJRFJsH5iYmLCAgAB2+vTpUvX9FhwcrPE+nxhTrw/IwhH0CvcPADZ58uRiA1bk5OTwdQ0NDRX1l9W1a1cWHR0tis/Kyio26pq8PhCF/Wjp6+sziUTCGjRowB4+fCiKy8zMFI1Q6OrqyqZMmcKAglGmi47UGhUVJep7ZNSoUapsPo25cuWKaP3DwsJkxi1fvpzHtGnTRqW0hZ1Zm5iYFPv++vXromUrGyWUsYJzSjjPjRs3VMpLUd999x1Pw8bGhuXk5JQoHXm6devG0//2229Vmkd4LHbv3r3Y98I+4VTp4DovL0/U8XeDBg3UXo+iymOf/Rf6gNyzZw9fhkQiYbGxsXJji/bpJy9Pn9o5Kxxd1tnZWW56wnvqxo0bVVovYcf+X3zxRbHvJ02axL8fPHiwSmkKB9lwc3NTaR5VvH79WnRPL/oMMmrUKLXyWvR4KRxAZfz48fyzixcvFpvv0qVL/PsJEyYwxgrub5p+HihJH5DC/aWrq8tWr15d7Dnn2bNnrEWLFjzOwsKCvXr1qtT5VVVaWppoQI+ffvpJZpy2ziljY2P+/cmTJ1XKs3C05BUrVqg0T1Fnz54V5U3Tfbhp47om7BPOwcFBpTT9/PxE66nJQXZUIRyUytLSUm7/e8KBUlQZdKpwpPfC1+TJkzWdda4s+oB8+/at6LfAX3/9pTBeeD2Sl6dP7ZxV9XecNu6Df/75J//ezs5OpTQfPXokyq+8/qhLwsXFhae7YcMG0Xc7duzg3zk6Oqo0yFHRPiAZY2zv3r38s++//77YPBkZGczCwoIBYPXq1eOfUx+QpCLRaBPsGzduYPLkyXBwcEC/fv1w5MgRUb+JzZs3x88//4zIyEicPHkSAQEBCvvFKEu5ubk4fPgwevXqVey7adOmwc/PDwCQl5eHr7/+Gvb29jh//jzc3NxEsYaGhvjtt99gY2MDoOCfJOG/8EKrVq3i/9507doVJ0+eRJ06dYrFWVhYYOPGjfxfkOjoaGzatEnh+lhbW2PChAm4dOkSXr58ie+//16UdkZGBvbs2QM/Pz9Ur14d3377rUp9HX7s8vLyMG7cOKxfv57Xpiykr6/Pq9DPnj2bN7Vwd3fHkSNHYG9vL4o3NDTEihUrMG3aNP7ZokWLeG0MeXJzc1G5cmUEBQWJ+m0DACMjI/z+++/8+Hj+/DnWr1+Pzp07Y9++ffzzQg4ODti8eTOfPnDgAPLy8lTZFKWWn58v6kagTZs2aNmypczY+Ph4/t7Ozk6l9IXbOyMjg9fYlZWmhYUFjI2NlaZpYmIiqiEjrAGgKsYYr9kDaL6GBlD67SVrvYT7JigoCDk5OQrTu3Dhgqj/s5Jsq6LKa59VZBkZGZgzZw6fHjhwIKpUqVLqdCvSOSsvD5o6t7SRZknt2rWL19Bo3rx5sWcQYTPsI0eOyOz3WBXCfvlkNRUTfqbJPvxK6+XLl/jtt9/49M8//4wZM2bwe38hV1dXnD17ltc+SUlJweLFi8ssnwsWLEBiYiKAgpZA8mq5aOOcyszMFPXdV5bHtLBmT6NGjVSq8aQObVzXhPfW6Oho3L17V2F6KSkpxfpULsv7WlRUFJYvX86nJ0yYILe2mnDdVOmK4MSJE6LpT/1+LexeqXr16ujZs2ep06xo52yhj/HeKi/dkrh8+TLv81hfXx+DBw8Wfd+/f39eZhEVFYVz586VaDl9+vThtVuFvzUKHTp0CCkpKQCo9iOpuEpdAPnu3TssXboU9erVQ5s2bfDrr7+KLgbVq1fHnDlz8PjxY9y6dQvTp09X+SJTlvr06SO3WTOAYheiuXPnyu0TzszMTNRhbFhYWLGY3NxcrF+/HgCgo6ODTZs2Ka3OvnTpUt5EYs+ePQpjhWrWrIl58+bh6dOnvEN2W1tb/n1kZCRWrFiBBg0aoGXLlli3bh3i4uJUTv9jYmRkpLRafHh4uKg59oYNGxQO2PHjjz/y7ZWSkoK9e/cqzcd3330nt5Cg6PEBFDQHL/oDqZCHhwfvdygtLQ1PnjxRunxNWLx4MS8819HRwcqVK+XGpqWl8feqPGzJihOmUdI0i8YWTVMVISEhePv2LZ/WdPNroPTbS9Z6ffbZZ/wYev/+PdasWSM3LalUiv/973+iz5QVrKuivPZZRTZ58mR+PBobG+OHH37QSLoV6ZwtbR6ULV8baZaUsOBPWNhYyNvbmzcjzMrKwv79+0u0nLZt2/LmZ3/99ReysrL4d1lZWbwDfVdXV3h4eJRoGdqwefNm3qSvcePGmDJlitxYa2trUUHN3r17kZycrPU8nj9/XnR9njNnjtznBW2cU0Wny+qYTktLEw0a8THeW4umARQUlAq7tfjuu+8UprdkyZJiaWji/qoKqVSKkSNH8gKMKlWqYPbs2XLjhZUujh07pnDgysjISP67pVBZrZc27Ny5UzRA0NKlS5X2GayKinTOysvDx3JvlZduSQj/HOnevXuxCiFmZmbo27evzHh1GBsbY+DAgQCKd/cE/N89XkdHh/dBSUhFU6ICyPT0dAQGBsLX1xc1atTA3Llz8fTpU/69paUlxo4di+DgYLx+/Ro//vgj6tevr7FMa4OykTIbNmwomu7Xr5/K8REREcW+v3nzJt6/fw+goIBJlc6fHR0dUa9ePQDAw4cPS1SzoU2bNli3bh2ioqJw9OhRDBw4EEZGRvz7W7duYdq0aXB0dESfPn3w999/K6xJ5eXlBcYYf5W0/0dN6dKli2jkP1mEHTk3adJEaV8qpqamohGQZQ0AUpQ6x5OrqysaN26scrys40nTjh07xvtbA4BZs2YV66dVSPjjVNnoy4WKPugVHU2xJGkWTbckIzQKHyoaNmyoch+N6ijt9pK1Xi4uLqLjdO7cufj555+Ldar+4cMHDBgwoNhDjyZGsyyvfVZRrV+/Hjt27ODTq1evVtrvWo0aNUTXZHn9c31q5+zChQv5OikaqVQb55Y20iyJ0NBQ3heorq6u6HwvJJFIRP1Ol2bEzsICzuTkZBw5coR/LqxZKasQtDwJByUYPXq00n7t+vbti0qVKgEo6GtVUQGMJrx58wZDhgzh1+W2bdvi22+/lRuvjXNKmKY66Zb2mBYOnqSnp6ewf/SS0sZ1TSKRYO7cuXz6xIkTGDlyZLFn8JycHCxatAg//fRTsWWU1X3t22+/FdXM2rFjh8Jn4oCAAF64mp+fj169euHMmTPF4h48eABfX19ea7fQp3q/vnnzJiZOnMinBw8ejKFDhyqd7/Xr1/w+JKv/R+DTO2dV/R33Md5b5aWrrqKjUssr+BPe7w4fPswL+tUlb6C36Ohofv56eXmp1HcrIZ+iEg1C89NPP4kKJ4CC6spdu3bFsGHD0KtXL1Gh1qegaFPZooQ3cEtLy2KdniuKl3WBEj7kxsXFKfyXXqjwgYcxhsjISFhZWak0X1H6+vro2bMnevbsieTkZBw4cAC7du3CxYsXwRhDbm4ujhw5giNHjmD79u1a+adaG1q0aKE05s6dO/x9u3btVEq3Xbt2WLduHQDg9u3bCmPVPT6KNqFTFl/SG56qwsLC4O/vz5v5+fj4KG2aJjzflTX9LVS0mVPRfzVLkmbRdNX59xko+HNF+I+4tpoWlnZ7yVuv9evX4/r163jx4gWkUilmzpyJVatWoX379rC0tMS7d+9w4cIFZGRkACgYtOrYsWMAoJFBqcpjn1VUx44dw/Tp0/n0iBEjRD+YSquinLNFGRkZ8eNbU+eWts5XdQkLEzt37iy3Ncnw4cOxbNkyAP9XaOnq6qr28oYPH84LfgMDA3lLkMIfTBKJ5KMqgGSMiZrHqnJ/19fXR+vWrXHq1CkABff3rl27aiV/CQkJ6NatG29h4uTkhD/++IOPiiqLNs6pos/nZXVMC49fPz8/rbSG0sZ1DQDGjRuHM2fO8EKKwMBAHDp0CF5eXnBwcOADHRYO+CG8twKaub8qs3HjRqxatYpPz5s3D926dVM4j76+Pvbv348OHTogKysLcXFx8PPzQ6NGjdC8eXPo6ekhPDwc165dQ35+PoyNjdG2bVs+GEdZrJemRUREoGfPnrzwq1GjRqJuG0qrIp2z8vLwsdxb5aWrrsOHD/Pa71ZWVnKb4vv6+sLBwQHR0dHIzMzE/v37MW7cOLWX16FDB9SsWRMRERH4888/sXbtWhgYGGD37t38zylqfk0qMo2Mgm1lZYX169djyJAhCh+kPmaWlpYKvxc2j1YWWzRe2A9mocIRnoGCUcCENUhVVfSfyJIqrLEaEBCADRs2YO7cuWrdND8m8prFC3348IG/V6XmKQDRP4LKmqere3xo4njSlMePH6Nbt268lkKrVq1w+PBhpX0gCvvbVPXfyKJxRfvsLEmaRWOLpqnM33//zZtz6OrqqtT84cSJE8X6RSrqyy+/FBUAlHZ7yVsvKysrXLlyBUOGDOE1dSMjI/Hnn3+K4vT19XnXAoU/kmT9maHsjxFXV1d8+eWXMvNVVvusIrpw4QIGDx7MH0R79OiBrVu3anQZFeWcLcrMzIwXQGrq3NLW+aqOos2pFRX8ubm5oUWLFrh16xaAgsKSkvRvWLNmTbRv3x6XLl3CmTNneOFKYQ2pDh06lHurB6Hk5GTR/VEb9/eSSktLQ7du3Xi/3zY2Njhz5ozSGi7aOKeKTpfFMf3mzRtcuHCBT6vyp/bz58+xdu1ahTHdu3cXjfSujetaoT179sDe3h7r168HYwypqamiQsZC/v7+mD9/vui7ovfXtWvX8trM8hRt7qzIH3/8IbpfT5o0Cd9//71K87Zs2RIXL17EwIED+QjPDx48EI0ODRQ05969e7eoC6iSVoIoL9HR0ejcuTNiYmIAALVq1cLp06dVeg5XVUU5Z4vSxn1Qm+erOoR/jgwcOFBuU3xdXV0MHTqUF/Tv3LmzRAWQEokEw4YNw+LFi5GYmIhjx46hf//+vE9IU1NTpS3pCPmUlagA0tbWFhKJhNeQSkpKwrBhw/D1119jyJAhGDZsmEo10T4myprplDRWHk30M6SJwUjy8/Nx4cIF7N69GwcPHiyWLz09Pd486VOgyj9hwv5CTE1NVUpXGKeszxt1jw9NHE+aEBERgc6dO/NOod3c3HDy5EmVbu7CvlIKf6QqU/gACBR0wF30hi9MMyUlBVlZWUprVmdkZIj2j7rHbtEaGkU7u5blxo0b2LBhg8KYAQMGiAogS7u9FK1XlSpVEBQUhNOnT2Pv3r0IDQ1FTEwMpFIpqlWrhi5dumDSpElwc3MTNSGqWrVqsbSUrZenp6eoALI89llFc/PmTfTs2ZM/ZHt5eeGvv/5S2kewuirKOVuUjY0N795EU+eWNs9XVQmbPZuZmaFPnz4K44cPH84LIHft2oXvv/++RPeakSNH4tKlS8jLy+P9Hxc+e3xMg88AxfsC08b9vSSysrLQq1cv3qeyubk5Tp48qVLrB22cU8bGxjA2NubXmLI4poWDJ1lbW6s02EdkZKTSe5Ctra2oAFIb17VC+vr6+OWXXzBx4kT8/vvvCAkJwZs3b5CRkQF7e3u4u7tj7Nix6NKlC0JCQvh8enp6xWp7Hjp0SFQgK4uqBZDHjx/HiBEjeN+n/v7+ahVeAgV/Nj979gy7du3CkSNHcPv2bcTFxcHY2Bi1atVCv379MGHCBNja2or6IZb13PCxio+PR+fOnflAIw4ODjh37hwcHBw0upyKcs4WpY37YGnTlJeuOooOKKOs4sHw4cN5AWThwDUuLi5qL3fEiBH8j8HAwEDUqlWLF/r369eP/ownFVqJftFMmTIFPXr0wK5du7Br1y7+L15MTAzWrFmDNWvWoF69ehg2bBgCAgI+qn/IPxbCB97p06fj559/LtPlP3z4kP+T+e+//xb7vmnTphgxYgQCAgI0MuLqx0R4UReOAqyIMO5TbHKiTGRkJHx8fHjNXBcXF5w9e7ZYJ8zy1K1bl78v/AddGeFAL4V9m8pLszDdop8pSlNWGoq8e/dO1L+nNn9c161bl484qantVZSfnx/8/PwUxggHyGrVqpVK+VCkrPdZRfPgwQP4+fnxHyKtW7fG0aNHtdKlSUU4Z2WpW7cur2WmjfXS1vmqjPDPkbS0NJUL14CCPIeEhCgcaE+egQMHYurUqcjMzERgYCAvRDI2NsaAAQPUTk+biv5gS09PV2k7afP+npubi/79+/N7i7GxMY4dO6by9VZb51TdunV5c/WyOKaF/ZwNGTJEI4N9yFIW56qbm5vCQd4A8b21UaNGWuuWKigoCAMGDOA1f3v16oXAwEC5gxoqYmBggLFjx2Ls2LFyY/Lz80XdEGniuaEspKSkoGvXrnj06BGAgoKvs2fPigYX0pSKcs7KWn4hbdxb379/r1JhrTDNSpUqqdTyTRFhs2eg4I91dQQGBhbrlk4VtWvXRtu2bREaGoqTJ0+K7j3U/JpUdCUeBbtGjRqYN28enj17htDQUEyYMEHUT92TJ0/wv//9D7Vq1UKHDh3w22+/aazJcEUg/DdUWTMMTYmKisLKlSvRtGlTNGrUCMuXLxcVPjo4OOCrr77C/fv3cefOHcyYMaPCFT4C4mbaRW/68ghvtsIRxCuC9+/fw8fHhw9uU7VqVZw7dw6Ojo4qpyEcZComJqbYP5SyCB9iZQ1SZWlpKfpnWth3pyppOjk5wcLCQuk8hXbt2sVrEFhZWaF3794qzSccHEPeq+hAIML1VWW9AOXbS13Z2dkIDQ3l023bti0Wo2y9hLU8gLLfZxXJ06dP0blzZyQkJAAo+NFa9KFUkyrCOSuLuudWXl4eHj58KHN+WZ89ePBApdYHmjxfY2JiZA4MoQ5hAZA6LCws+LXw7t27uHfvHgCgT58+H925amlpKeoupLzv71KpFEOHDuVddOjr6+PAgQNq/cDV1jml7nkSHR0tqqGkzjEtHDwJUH3066KDY8h6FR0IRBvXtZIQ/pkp694aEhKidN2UuXLlCnr16sX7MvTx8cH+/fs1Xlte6ObNm/wPMh0dHbi7u2ttWZqSnp6O7t274+bNmwAKrmmnT59W2vd/SVWEc1YWbdwH69atywvLi/bhW9I01VXSe2MhYe1udRUWNObm5vKuDZycnNCpU6dS5YmQj12JCyCFPDw8sGnTJkRHR+Ovv/5Cjx49+A2QMYbLly9j4sSJsLe3R58+fXDgwIFincj+17Rp04a/v3Dhgta2R2pqKnbs2AFfX19Uq1YNs2bN4j8ggIJ/44cMGYITJ07g3bt3WLlyJRo1aqSVvHwsmjVrxt8LC2AUuXLlCn+vjVGRy0t8fDx8fX15H6RVqlTBuXPn1K617OrqKmqKU7RgShZh8yN5N1thjR1NpSlPYd8rgHZraADi9Xr69Cmio6MVxkdFRYl+wJWkJlNRx44d4006ra2t0aNHj1KnCZTtPqsoIiIi4Ovry38s1KlTB2fPntVqc/SKcM4qW/7Vq1eV9mccFhbGa8AZGRnBw8OjWEzbtm359SA9PZ3/kJUnOzsb165d49OlXa89e/bwGhpmZmZo06aNSq+GDRvyNIQjEKtLVm2MsqqhoW73OE2bNuXTqtzf8/LyeNNoQHP39/z8fIwaNQoHDhwAUNB32N69e0XNhVWljXNK3TSFMdWqVUPt2rWVzlNI+AO/Xr16aN26tcrzqktb1zV1FP3DQBsDNd28eRPdu3fn53Tbtm1x5MgRrT63AOJ92aVLl4++kkJh9weFz/AmJiY4ceKE1rsJ+9TPWVm0cR80MjISFWKX9fl669YtXisWKGh1our9tbDgNCIiApcuXSrR8gcPHlzsnB02bFiJajAT8klhWvL+/Xu2Zs0a1rx5cwag2MvS0pKNHTuWBQcHs/z8fIVpGRkZ8flycnJUWr5wWfI4OzvzmIiICIXpRURE8FhnZ2ely9++fTuPHzlyZLHvs7KymJWVFY9Zt26d0jRVlZuby44dO8YGDx7MjI2Ni217iUTCOnTowLZs2cKSk5M1tlxN8vT05PkNDg5WGDty5Egeu337dqVph4eHi7bH3bt3FcZnZGSwKlWq8PjffvutWIymj4+i1F1HVSQnJ7OWLVvydK2trdm9e/dKnN4XX3zB0/Lz81MYGxoaymN1dHTY+/fvZcbt37+fx1lZWbGMjAy5aWZkZIjOqYMHD6qc92vXromOiatXr6o8b0m5ubnx5S1dulRh7I8//shjGzVqVOpl5+bmsgYNGvA0p0+fXuo0C5XVPiskvI5r6txQh/C4UXatkuXff/9lNWvWFF0/3r59q/mMyvApn7Py5OTkMEtLS57mvn37FMaPHz+ex/bs2VNuXPfu3XnchAkTFKa5d+9e0XU1Nze3ROtSqFGjRjy9GTNmqDxfRkYGs7Cw4PMGBgYWixHeuwCwzMzMYjF5eXnM3t6exzg4OLC8vLxicZmZmaK0lD1XqaJevXo8vWfPnimN//bbb3l88+bNlT5fHjx4kMcbGRmxpKSkUueZMfFxJZFI2M6dO0ucljbOqZiYGKajo6PyPa9Lly48durUqSrnveizrrJ7nSZo47qmDuG+b9q0aanTK+r+/fusUqVKouNcU8etIq9evRL9Hjt8+LBWlyf8HbBgwQK158/JyRFdtw0NDdnZs2c1n1EZPuVzVhFt3AdXrFjB4+rWraswzXfv3jFdXV0ef+vWrRKvC2OMTZ06lafVrFkzteb19fXl844ZM0ZmjPD59OTJkzJjBgwYILpvPnr0SGZcmzZtyvVZlxBN0loBpNDDhw/ZrFmzmKOjo+gkK3xVq1aNXbx4Ue78Tk5Oaj/QCtOXpzwLIBljbOHChTzG3Nyc3b9/X2m6hWJiYmR+vn//fmZraytzO9euXZstWrRIIz8KtE2bBZCMMdaxY0c+T4cOHRQWbH/11Vc81sLCgqWmphaL+dQKINPT01n79u1Fx9/169dLleb9+/dFD0dnzpyRGSeVSkXLHjJkiNw0s7KyWNWqVXnsd999Jzd2zpw5on2QnZ2tct4nTZqk8gOQpqxfv54v08bGRu45HR0dLfqxsWnTplIvW/jQVaVKFRYfH1/qNAuV1T4r9CkXQMbGxrK6devy+R0dHdmLFy+0k1EZPuVzVpGvv/6ap+vq6ir3x9+DBw+YgYEBjz116pTcNP/55x8eZ2BgwB4+fCgzLj09ndWuXZvHzp49u1Trcvv2bdExdvPmTbXmHzVqFJ/Xx8en2PeqFEAyxtjz589ZWFgYCwsLY8+fP5cZo40CyHbt2ql1fr148UJ0TCu6XiYlJTEXFxceO3r06FLnlzHGZsyYIdoOv/76a6nS09Y5Jfzh26FDB7mFtadPn+Zxurq6cn8gy/Lnn3/yeXV0dNi///6r8rwlpY3rmqr279/Ply2RSBT+timJp0+fMjs7O55nNzc39uHDB40uQ5a0tDTm7u7Ol+vr66v1ZZamADIvL090fOvp6bEjR45oJ6MyfMrnrCLauA/GxsYyU1NTHrt582a5sf7+/jzOw8OjVOuSk5Mj+r28cuVKtebfsWOH6DdUenp6sRhVCiBjYmL4vfX27dtyl0cFkKQiKZMCyEJSqZSdPn2aDR06lJmYmIge0BSdTF27duVxy5cvV2lZwrTlKe8CyNTUVFEtJAsLC/b777/LvfnExcWxzZs3s+bNm7OvvvpKZsyCBQtE625lZcXGjx/PLl++rDTPJREcHKzxHxyMab8AMjQ0VPQvWs+ePVlsbKwoJjs7m82dO1e0fqtWrZKZ3qdUAJmVlcU6d+7M0zM2NmYXLlwoVZqFhg8fztO1sbEptu/S0tLYsGHDRA8w8n7MFtq6davoQeqXX34RPXRJpVK2Zs0a0Q8OdWqbZGdniwr4fvzxR7XWuaRycnJEP36bNWvG3rx5I4p5/fo1a9q0KY+pU6eOwtpU9+7dYzNmzJD7sPn27VvRA6xEImF///23RteLMe3vM6FPtQAyMTGRNWnShM9ra2urkR8JRQuUlOXpUzlnhfc2ZdfYuLg4UY2SLl26sLi4OFHM3bt3WY0aNXiMt7e3wjQZY6xDhw48vkaNGsX+NIyLixNdWytVqsQSExOVpqvIl19+KTr/1XX27FlRAVDR2rWqFkCqQhsFkBMnTuTpTZo0SaV5hH8o6enpsfXr1zOpVCqKefHiBWvdurXo+evVq1elzu/8+fNF22DFihWlTpMx7ZxT4eHhTF9fn8ePGDGCpaWliWKCgoJE90d1C2mFNaa6dOmi1ryloY3r2rBhw1hwcHCxY4mxguf5+fPni7anJlsWMMbYmzdvWLVq1Xj6tWvXZlFRUaVOd9euXWzVqlVy/wS9evWq6DnE2tpaI+eKMiUtgMzPzxf98aKjo6O0JryqhM8byvL0qZyz6v6O08Z9cN68eaLfJH/++afo++zsbFHtdgAsJCREYZrKHDp0SHSMqPvnSEpKiqiV4e7du4vFqFIAqSoqgCQVifZ6KpZBR0cHXbp0QZcuXZCamooDBw5g586duHjxosL5+vfvj1OnTgEAZs+ejVOnTqFBgwaifhO+++470SA4nwIzMzMcPXoUvr6+iIiIQEpKCsaPH49Zs2bBw8MDTk5OkEgkSEhIQHh4OJ4+fcoHyVDUB5yenh78/PwwYsQI9O7dW+t9wnyKPDw8sGzZMsyaNQtAQX941atXh7e3N6pVq4bExESEhIQgLi6Oz9O3b1/MmDGjvLKsMfPmzcPZs2f5dP369bF//37s379f6byurq748ssv5X6/fv163L59G48ePUJ8fDy8vb3h7u4ONzc3JCcnIygoSDQY1e+//660X5oxY8YgJCQEu3btglQqxbRp0/DLL7/A3d0djDFcvXoVr1694vGjR49Wq3+yY8eO8YE/dHR0tNJfkyz6+vo4ePAg2rdvj7S0NNy5cwe1a9eGj48Pqlatinfv3iEoKIiPbmlubo6DBw8q7GA+IyMDP//8M37++WfUqFEDTZs2RZUqVZCeno4XL17gxo0bvLNsiUSCLVu2oG/fvhpfN23ss5s3b2LcuHHFPi8cuR0A5s+fX2x00pYtW2LLli2lWyEAR48exfz58xXGjBs3rthIvL169cL3339fLHb8+PGi/ngbNmyIX3/9VaW8uLu7Y9iwYSrFKvMpnrPK2NjY4I8//kCPHj2Ql5eHM2fOwNnZGb6+vrC1tcWLFy9w8eJFfi44OTlh9+7dStPdu3cvWrdujejoaLx+/RpNmzaFp6cnatWqhQ8fPuDcuXPIyMgAUHAf3r9/P6ysrEq8Hnl5edi7dy+fDggIUDuNTp06wdHREVFRUcjPz8euXbswd+7cEueprPXv3x+bNm0CAGzcuBG3b99G8+bNYWJiwmMmTZoEFxcXPr1y5UrcvHkTYWFhyMvLw5QpU7Bs2TK0b98eZmZmePnyJS5evMj71dTT08PWrVtLPSLuiRMnROe6nZ0d3rx5gylTpqg0//r16+V+p41zql69eti4cSO/rgYGBuKff/5Bp06dYG5ujkePHon6x2zcuDHWrl2r0roAQGxsrKgvxJEjR6o8b2lp47r2119/Yffu3bCxsUHLli3h5OQExhjevXuHy5cv88FggILtv2rVKo2u04ABA/Du3Ts+Xb9+ffzwww8qzdu9e3e5/Y/++++/mDNnDmbNmoWGDRvCzc0NlpaWSEhIwN27d0X9T1tbW+PcuXMaHT06KipKZt5evHjB32/atAmHDx8Wfe/o6MgHeBLauHEjduzYwaddXFxw+fJlXL58WWlebGxsSjSisSyf4jmrCm3cB+fNm4crV64gKCgImZmZGDx4MJYsWYLmzZsjKysLFy9eFPWVvmjRIrVHqy5q586d/L2npyecnJzUmt/c3Bw9e/bkv5127txZons0If9J5Vf2+X9ev36tsNlZbm4u8/b2Fv3zUfRV9B8b4XfylHcNyELx8fFs4MCBTCKRKFzHwpeVlRXbsWOHzLQePHhQrCafNn2qNSALbdmyRdRHlqyXrq4u+/LLL2X2eVXoU6oBKUxL3Zenp6fS9CMjI1mnTp0UpmNmZsa2bdumcp6zs7PZlClTFJ4jEomETZs2TeV+Ygv17NmTp9G5c2e15tWE0NBQUR+Asl61atVSqV/Kq1evqrQfa9eurfW+kDS9z4peazR5zKpCeM6q85J3fguvcZpKkzH1a0Ay9mmcs+rUgCx09OhRVrlyZYXr1axZM/bkyROV1ys8PFxUG0jWq3Llyuyff/5ROU15jhw5IkpXWQ0teWbOnMnTKFqL8mOvAckYE9VUk/WSdYynpqayQYMGKT2XHBwc2IkTJzSSz5JeIwpfymjrPrh582ZRE0hZLx8fH7Vr261atYrPb2FhobAfPG3Q9HXN0NBQ6T60sLBgv/zyi8xakqUl/M2i7ktRbb2lS5eqlIavr2+Jr0GKFL0GqfqSdx8o2hJME2kWUqcGJGOfxjlbkt9x2rgPJiUlKb1m6+vrsx9++EHlNOWJi4sT1STdsmVLidI5evQoT0NHR4e9e/dO9D3VgCREtjKtASmPs7Ozwu/19PRw+vRpbNu2DQcPHsSDBw+QkJCgdHTLT0WlSpWwf/9+PHz4EPv27UNISAgiIiIQHx8PHR0dWFlZoXbt2mjevDl8fX3RuXNnGBkZyUxLOOolUW7s2LHo3bs3Nm/ejJMnT+LZs2dISEiAubk5qlWrBl9fX4wZMwZubm7lndVPhqOjI86dO4dDhw5hz549uH37NqKjo2FmZobq1aujZ8+eGDt2LKpXr65ymgYGBli3bh2GDx+Obdu2ISQkBJGRkQAKai95eXlh7NixaNWqlVp5/fDhA06ePMmny7KGRiEPDw/cv38fgYGB2L9/P549e4b4+HjY2NigTp06GDRoEEaMGFGsZp0szZs3x8mTJ3H+/HmEhoYiMjIS79+/h56eHhwcHNCkSRP0798fffr00XrNaG3tM6J5n9I5q46ePXvi0aNH2L59Ow4dOoRXr14hKSkJdnZ2aNCgAfz9/eHv7w99fX2V06xXrx6uX7+OP/74A/v27cOjR48QGxsLKysr1KpVC3379sWYMWNga2tb6vwLa2i0bt26xKOYBgQEYPXq1QCAZ8+e4dq1a6KRRz92gYGB+Oyzz7Bnzx7cvXsXcXFxotpmspiZmeHPP//E9OnTsWvXLoSEhCAqKgqZmZmwtbVFw4YN0aNHD4wZMwampqZltCalo61zaty4cejSpQu2bt2KY8eO4e3bt0hLS4ODgwOaN2+OYcOGoU+fPmqNSA6Ij99BgwbB2NhYrflLS9PXtYsXL+LcuXP8Gf39+/fIycmBnZ0dXF1d0bt3bwwePBiVK1fW8ppp1vjx4+Hs7IygoCDcunULMTExiI+Ph7m5ORwdHdG+fXsMHDhQYcsrItunds6qShv3QUtLS/z555/4/PPPsXPnTly9ehXR0dHQ19dHtWrV4Ofnh7Fjx6J+/fqlzv/evXt56yJDQ0P079+/ROl07doVNjY2iI+PR35+Pnbv3o3Zs2eXOn+EVHQSxv5/GyRCCCGEEEIIIYQQQgjRMJ3yzgAhhBBCCCGEEEIIIaTiogJIQgghhBBCCCGEEEKI1lABJCGEEEIIIYQQQgghRGuoAJIQQgghhBBCCCGEEKI1VABJCCGEEEIIIYQQQgjRGiqAJIQQQgghhBBCCCGEaA0VQBJCCCGEEEIIIYQQQrSGCiAJIYQQQgghhBBCCCFaQwWQhBBCCCGEEEIIIYQQraECSEIIIYQQQgghhBBCiNZQASQhhBBCCCGEEEIIIURrqACSEEII0SAvLy9IJBJIJBKEhISUd3Y+egcOHECvXr3g5OQEQ0NDvu28vLzKO2uEEEIIIYQQDaECSEIIIYSUixEjRmDgwIE4duwYoqKikJOTU95ZqpDevn2LhQsXokWLFqhcuTKMjY3h4uKCAQMG4NChQ2CMlXcWPwrJyckICgrCihUrMHDgQNSoUYMXiEskEuzYsaPEaf/zzz8YMWIEateuDXNzc5iZmcHV1RVDhw7FP//8U6I0GWM4dOgQBgwYABcXFxgbG6Ny5cpo2bIlFi1ahLdv35Y4v4QQQgghmqZX3hkghBBCyH/Pvn37sGvXLj7dunVruLm5wdTUFADg6upaXlmrULZt24Zp06YhPT1d9PmrV6/w6tUrHDx4EL6+vti1axfs7e01sswdO3Zg9OjRAICRI0eWquCurPj7++PPP//UeGHs27dvMXjwYFy7dq3Ydy9evMCLFy+wb98+dO7cGTt27ICjo6NK6UZFRWH48OEICgoSfZ6VlYW4uDjcunULK1euxLp16zBq1ChNrAohhBBCSKlQASQhhBBCytzOnTv5+0WLFmH+/PnlmJuKadu2bRg7diyftra2RqdOnWBhYYGHDx8iLCwMAHDu3Dn4+fnhypUrMDMzK6/slqvo6GiNFz6+efMGbdq0QWxsLP+sYcOGaN68OfT09BAeHo7r168jPz8fZ8+ehY+PD0JDQ2Ftba0w3ZSUFPj5+eHhw4f8s9atW6NBgwa8FmdSUhLS0tIwevRo6OjoYMSIERpdN0IIIYQQdVEBJCGEEKJB1O+jam7fvs3fCwvJiGY8ffoUEydO5NMBAQH47bffeA1TADh//jwGDhyIxMRE3L9/H9OmTcO2bdvKI7sfBR0dHdSrVw+tW7dGq1at0KpVK/Tv3x/v3r1TOy3GGAYOHMgLH21tbbFnzx506dJFFPfgwQMMHDgQT58+xZMnTzBmzBgcOnRIYdpTpkzhhY+VKlXCgQMH4O3tzb9PS0vDhAkTsHfvXgDA559/jrZt26J27dpqrwchhBBCiKZQH5CEEEIIKXOJiYn8vYODQznmpGKaN28ecnNzAQDt2rVDYGCgqPARAHx8fHghFQAEBgbi8ePHZZrPj8Wvv/6K5ORkPHr0CNu3b8cXX3yBVq1aQUenZI/Khw8f5jVMdXR0cPTo0WKFjwDQqFEjnDt3jtd6PHz4MC5fviw33YcPH2LPnj18eu/evaLCRwAwMzPDrl270LZtWwBATk4O1TAmhBBCSLmjAkhCCCGElLm8vDz+vqSFPES22NhYHDx4kE+vWLFC7jbu2rUrfH19AQBSqRS//fZbmeTxY+Pm5qbR5uf79+/n73v27AkPDw+5sVWrVsWUKVP49C+//CI3duPGjcjPzwcAdO7cGX5+fjLjdHR0sGLFClF+Pnz4oHL+CSGEEEI0jZ74CSHkP0g4smuhW7du4fPPP0edOnVgamoKCwsLdOjQAYGBgTL7Rjt//jz69+8PFxcXGBkZwd7eHn379sWlS5fUyktcXByWLVsGT09PODg4wNDQELa2tmjWrBlmzZpVohpZp0+fxpgxY1CnTh1YWFjA2NgYzs7O6Nu3L7Zv385rhikyatSoYqPfJiUlYe3atejYsSOcnJygp6cHiUSCpKQkPp+XlxefT15zbFlpp6en49dff0X79u1hZ2cHQ0NDVKtWDf7+/rhy5Ypa6//w4UNMmjQJrq6uMDExga2tLVq2bImlS5ciLi4OQMFAIYV5KKtBKoSjCgsJj0eJRIIaNWrIne/169cAgJcvX+K7775Ds2bNULlyZejo6KBp06Yyl/vo0SPMmjULzZo1g62tLQwNDeHo6AgvLy8sX74c8fHxSvMua3tJpVIEBgaic+fOcHJygoGBARwdHREQEIAHDx4USyM1NRXr1q1D27ZtYWdnB2NjY9SpUwdfffUV3y+acPToUV5IVadOHV4TTp7CAWOAghp4JVV4XAvT27lzZ7H9K5FI4OXlJTedtLQ0/PLLL/Dz80PVqlVhZGQEa2trNGzYEFOmTMH169dLnMeyIhx0plu3bkrju3fvzt+fOHECmZmZxWIYYzh69CifFm5nWdq1a8cHc5JKpTh27JjSfBBCCCGEaA0jhBDynwOAvxhj7IcffmC6urqiz4WvESNGsPz8fMYYY2lpaaxnz55yYyUSCVu9erVK+di6dSuztLSUmxYApqury6ZPn87y8vKUphcbG8t8fHwUpgeAubq6srCwMIVpjRw5ksdv376dXb58mVWrVk1meomJiXw+T09P/nlwcLBKaT9+/JjVr19fYZ7nz5+v0jZdvnw509fXl5uOg4MDu3LlCtu+fTv/bOTIkSqlXVrOzs5K9w0A5uzsLHe+iIgI9ttvvzEjI6Ni8zVp0kQ0X25uLps6darCYxsAs7KyYjt27FCY96LbKzY2lnXs2FFumgYGBuzEiRN8/qtXrzJHR0e58fb29uzJkyca2c7+/v483fHjxyuNj4qKEuXl+fPnJVqu8LhW9vL09JSZxrFjx5i9vb3S+YcOHcrS09NLlE91CI+97du3qzyfsbExn+/kyZNK44vuA1nXjqdPn4pioqKilKb7+eef8/iAgACV808IIYQQomk0CA0hhPzHbdy4Ed999x0AoEWLFmjUqBEYY7h06RJevXoFoKBvuLp162L27Nno378/Tp8+DQMDA7Rv3x61atVCSkoKzp8/j/j4eDDGMHPmTLRq1Qrt27eXu9yVK1di1qxZfNrQ0BCenp6oXr06EhMTERwcjISEBEilUqxZswZv3rzBwYMHi9WeKxQbG4t27drh5cuX/DMXFxe0adMGhoaGePz4Ma859fz5c3h7e+PUqVNo166d0m304sULTJ8+HcnJyTA3N0fHjh3h6OiIxMREXLx4UflGViAqKgq+vr6IioqClZUVOnToAHt7e8TFxSEoKAjJyckAgO+//x5ubm4YPHiw3LRWr16Nb7/9lk8bGRnB29sbVatWRVxcHIKDgxEdHY0ePXpg+vTpKuVv4cKFWLRoEQDA2dmZ10AsiZEjR/Lahhs2bOCfT548WRRnY2MjN42//voL33zzDQDAyckJbdu2haWlJaKiopCQkMDj8vPz0b9/f1GNsUqVKsHLywuVKlXCu3fvEBwcjJycHCQlJWHUqFFITExUabvk5eWhX79+uHLlCkxMTODl5QUnJye8f/8e586dQ3p6OnJyctCvXz88fPgQOTk56NKlC1JTU2FnZ4cOHTrA2toaL1++REhICPLz8xETE4O+ffvi3r170NfXV2l7yhMeHs7fN2/eXGm8g4MD7Ozs+IAp4eHhJRqwxNfXF2ZmZnjy5AnOnz8PAKhXrx58fHyKxRbWzBP6888/ERAQAKlUCgDQ1dVF+/btUbt2baSlpeHSpUuIiooCUND3YUREBIKCgmBkZKR2XsuSvGuWIo8ePSpWS1S4X+3t7VXqO1W4/4XzE0IIIYSUufIuASWEEFL2UKSmlpOTE7ty5YooJi8vj3399deiWmILFy5kAJiXlxd78+aNKD4pKYl5e3vzeC8vL7nLDw0NFdVK69q1K4uOjhbFZGVlsVmzZonyumrVKrlpduvWjceZmJiwPXv2FIsJCwtjtWrV4nHVqlUT1V4UEtbm0tPTYwDY5MmTWWpqqiguJyeHSaVSPq1uDUhDQ0MGgH3zzTfFanTFx8ezTp068dhatWrxmqhFPXz4kBkYGPDYzz77jL1//14Uk56eziZOnChaLpTUgFywYIHcmomlIdyvyghroenp6TEDAwP2+++/F9sWWVlZ/P3y5ctFy/jmm29E3zPGWHR0NOvSpYso7WvXrsnMg7AGZOF27t+/P4uLixPFRUZGsgYNGvDYESNGsBYtWjCJRMJ++OEHlpOTI4q/cuUKMzc35/HKamKqQt3ad4wx1qpVKz7PihUrSrX8ktSuffHiBTMzM+PztWzZkj179kwUI5VK2apVq5iOjg6Pmzp1aqnyqkxJa0AKa0tv2rRJafzVq1dFx+vkyZOLxQiP6TZt2qiUj+PHj4uui4QQQggh5YUKIAkh5D9I+EPX2NiYPX78WGacVCot1jS4QYMGLDMzU2b827dveWGdRCKR20RQ2HTV3d2dZWdny83rtGnTeKyFhQVLSUkpFhMUFCTK45EjR+SmFxERIWr2vWjRIplxRZuTjhs3Tm6aQuoWQAJgc+bMkZteTEwMMzU15bHyCsgGDBggKrxRtE0HDhwoWv6nVAAJgO3evVthfHJysqgwa+bMmXJjs7KyRIVv3t7eMuOEhWoAWKdOnUQFz0JFC5MAsMWLF8vNw48//igqjC+NjIwM0XJv376t0nzCbhVmz55dqjyUpAByxIgRooJ2eX8MMMbY6tWreayOjg579epVqfKrSEkLIPv27cvn6927t9L4efPmifabv79/sZhvvvmGf9+rVy+V8nHr1i1RukUL4QkhhBBCygoNQkMIIf9xEydORP369WV+p6Ojg4EDB4o+W7p0qdwmj9WqVeMDXjDGcOvWrWIx4eHhombLGzZsgIGBgdz8/fjjj7C1tQUApKSkYO/evcVihCP39uzZE7169ZKbXo0aNTB37lw+vWnTJpmD7AgZGRmJRpTVpMqVK2P+/Plyv7ezs8Nnn33Gp8PCworFJCQk4MiRI3x6xYoVCrfpqlWrPtmRp1u3bo2AgACFMXv37kVaWhqAgu23ZMkSubGGhoZYv349nw4ODsbTp0+V5mP16tVyt6G7uzucnZ35tL29vahpfFFDhgzh72XtX3UUrnchY2NjleYTxhVNQ9uSkpLw559/8umffvoJVlZWcuO//PJLNGjQAEBBU/vff/9d21lUm/AadOzYMVy9elVubGRkpOgYBAoGLCpKuF9Ksl+LpkEIIYQQUpY+zV8fhBBCNKZ///4Kv2/YsCF/b2xsrHREV2F8REREse+Dg4P5+yZNmijto87U1BT+/v4y55f12ZgxYxSmBxSMHltYeBQdHa20wKlLly6wtrZWmm5J9OzZU2kfds2aNePvZfXBGBoaykf2dnBwUDjCMFBQUNyxY0eV8rdw4UKwghYTper/UVOEhXXyBAUFieKVFda0bt0ajRo14tOyjjGh2rVro0mTJgpjCgvIgIJ9rKhfx5o1a8LU1BQAEB8fL7PwSVVZWVmiaUUF0UKGhob8vawRmLUpNDQU2dnZAAr6/1T0BwJQ8MeI8DxXtr/KQ0BAAGrWrAmgoJC0V69eOHPmTLG4Bw8ewNfXF4mJiaLPZe0D4b4tyX6Vly4hhBBCSFmgAkhCCPmPExaUyCIseKtTpw709BSPXyaMT0lJKfb9nTt3+HtVBoApGnf79m3Rd5GRkXj//j2fLqyBqUjlypVRp04duWkW1aJFC5XyWRLCgi95hIOyFA5KI3T37l3+vlWrVioNetGqVSvVMviRUWVfaPoYK0rZOQOIzwM3Nzel8cIaf7LOG1UVLczOyclRab7CAkBA9dp1miLcX23atFF6jQHE++vOnTtKazGXNX19fezfv5/vj7i4OPj5+aFx48YYNWoUxo0bh3bt2qFp06Z48uQJjI2NRYP1mJubF0tTuG9Lsl+Bst+3hBBCCCGFqACSEEL+4ywtLRV+LywMUBZbNL6wVp7Qhw8f+HthM1VFatSowd/HxcXJTc/Y2BhVqlQpdZpFVa5cWaU0S0KVbSqsPSdrmwrzX7VqVZWW6+TkpFLcx0aVfaHpY6wodc8DTZw3qjIzMxNNq1rjTRhXNA1tK+3+ysnJKVWtUW1p2bIlLl68KFqnBw8eYOfOndi6dStCQ0ORn5+PKlWq4MiRI6JzV1YTdOF+Kcl+LZoGIYQQQkhZogJIQgj5j1OltlxJYuUR9kFW2OxUGWFc0YKGkqSnLM2itFlrSNPb1MTERKV51NlWHxNV9oWmj7Gi1N1nmtjHqjI2NhZto9jYWJXmi4mJ4e8rVaqk8XwpUtr9BSjfZ+WlVatWePbsGbZs2YKePXvCyckJhoaGsLKyQvPmzbFkyRI8evQInTt3FnVxIOuPBGFN6JLsVxMTk2JNsgkhhBBCyoryNi6EEEKIBglr4KSnp6s0jzCuaNPEkqSnLM1PjbAwJiMjQ6V51NlWnxozMzPeVF0Tx9inpm7durxZ/ps3b1Sa5+3bt/x9vXr1tJEtuUp7TQA+7n1mYGCAsWPHYuzYsXJj8vPzRU3/ZXWRULduXf7+U9ivhBBCCCFCVAOSEEJImRI2oRX+OFZE+GO7cERsWellZmYqbT6rSpqfGmH+//33X5XmiYyM1FZ2yp2mj7FPjXBUe2H/ivJER0eLatQJ5y8Lpd1fBgYGH3UBpCpu3rzJa3Hq6OjA3d29WIxwv8TExIhqN8ojLNQs6/1KCCGEECJEBZCEEELKlHBE59DQUJXmuXLlCn9fdNRsJycnUb+PqqQZHx8vGvla2UjcH7umTZvy9zdv3lRpQI6wsDAt5qh8afoY+9R4e3vz9yEhIUrjhTHVqlVD7dq1S7V8dZucC/fXjRs3IJVKlc4j3F/NmjUr02bu2hAYGMjfd+nSRWZftq6urqKm2ars2wsXLvD3nTp1Kl0mCSGEEEJKgQogCSGElCnhj+A7d+7g3r17CuMzMzPxxx9/yJy/kLDAZceOHUrzsHPnTuTn5wMAHB0dRU0bP0Vt27blA9VERUUpLZh49+4dLl26VAY5Kx/CY+SPP/5AVlaWwvjbt2/j/v37fFp4PH2KevXqBR2dgke8p0+f4tq1awrjhedMnz59Sr184WjNqgyo07ZtW9434YcPH3D8+HGF8Ywx7Ny5k09/6gVrERER2Lp1K5+eOHGizDiJRIJevXrxaWXXuqtXr+LZs2cACmpV9uzZs/SZJYQQQggpISqAJIQQUqbq1auHjh078umpU6cqLKSYN28e3r9/DwCwsLDA0KFDi8VMmDCBvz906BBOnTolN713795hyZIlonk/9dpTNjY2ooKJb775Bjk5OXLjv/76a5VqmX2qhg4dypvkRkdHY9GiRXJjc3JyMHXqVD7t7e39yRdI29nZoV+/fnz6m2++kVsr9syZMzhz5gwAQFdXV27hlzqEg6Wo0tTfysoKgwcP5tOzZs1SOKjMhg0b+B8XOjo6+Pzzz0uR2/KVnp6OoUOH8kJyX19f9O7dW278xIkTeeHy6dOncfbsWZlx+fn5+Oabb/j0oEGDVBpBnhBCCCFEW6gAkhBCSJlbtmwZdHV1AQCXLl1C//79eSFjoZycHHz33XdYtWoV/2zBggWiASsKeXt7o1u3bnx64MCB+Ouvv4rF3blzBz4+PkhMTARQ0Nx02rRpGlmn8rZgwQJeC/LmzZvo168fPnz4IIrJyMjApEmTsH//fpVHw124cCEkEgkkEglq1Kih6WxrhYWFBf73v//x6WXLlmHevHnFCmVjY2PRt29f3kxbT08PS5cuLdO8asvixYv58XDp0iWMGjWq2MAtwcHB8Pf359MjRoyAm5tbqZfdqFEj/v769esq9esoPLefPXsGPz8/vHr1ShSTn5+PdevWYfr06fyzyZMno2bNmqXOszbs3r0bq1evljti9bVr19C+fXteQ9Xa2hq///67wjQbNWqEgIAAPu3v71+sxnN6ejpGjhyJy5cvAyjoI3Px4sWlWBNCCCGEkNKjUbAJIYSUOQ8PDyxbtgyzZs0CABw7dgzVq1eHt7c3qlWrhsTERISEhIgGlOnbty9mzJghN83t27ejXbt2ePnyJdLS0jBo0CC4urqiTZs2MDAwQHh4OK5du8ZrgpmammLfvn2wsrLS6rqWlUaNGuGHH37gtZ6OHz8OZ2dneHt7w8nJCfHx8QgKCkJSUhKsrKwwY8YMLFiwAAB4jaqK5Ouvv8bly5dx7NgxAMCSJUuwceNGeHt7w9raGu/evUNwcDCys7P5PD/99BPatGlTXlnWqHr16mHjxo0YN24cgII+Bv/55x906tQJ5ubmePToEW7cuMHjGzdujLVr12pk2XZ2dmjXrh2uXLmCrKwsNGnSBF27doWDgwM/1lxcXDBp0iQ+T61atbBlyxYEBARAKpXi6tWrqFu3Ljp06AAXFxekp6fj0qVLokGW3N3dsWLFCo3k+ebNm3xbCUVFRfH38+fPx5o1a0Tft2zZElu2bJGZ5r///os5c+Zg1qxZaNiwIdzc3GBpaYmEhATcvXsXz58/57HW1tY4d+6cSoWp69evx+3bt/Ho0SPEx8fD29sb7u7ucHNzQ3JyMoKCgvifLADw+++/l7pfT0IIIYSQ0qICSEIIIeXi66+/hrW1NWbOnImUlBRkZ2fLbDqtq6uLKVOmYNWqVQqbStvZ2eHKlSsYOnQogoKCAADPnz8X/cgvVLt2bezduxetWrXS3Ap9BGbNmoW8vDzMnz8feXl5yMzMxIkTJ0QxDg4OOHDgAB49esQ/+9RHEJZFR0cHf//9N2bMmIGNGzdCKpUiPj4eBw4cKBZraWmJNWvWYNSoUWWfUS0aO3YsGGOYPn060tPTkZCQIHP9fXx8sGvXLo0eB7/88gu8vb2RkpKCpKQkUT+uAODp6SkqgASAwYMHw9TUFOPGjUNsbCzy8vIQHByM4ODgYun7+/tjy5Ytov4mSyMtLU1pf7Tv3r3Du3fvRJ+p8gdGfn4+7t+/L+pnVMjX1xcbN25UuZDQwsICZ86cwfDhw/m17tq1a8X6+jQzM8Mvv/yCkSNHqpQuIYQQQog2UQEkIYSQcjN27Fj07t0bmzdvxsmTJ/Hs2TMkJCTA3Nwc1apVg6+vL8aMGaNys1A7OzucP38ep0+fxh9//IHLly8jJiYGubm5qFKlCpo1a4Y+ffpg2LBhvHlqRTNnzhz06NED69evx7lz5xAVFQUTExPUqFED/fv3x/jx42FraysahKai1AItSk9PD+vWrcPEiROxbds2nD9/Hu/evUNqaioqVaqEOnXqoHv37vj8889F/RZWJOPGjUOXLl2wdetWHDt2DG/fvkVaWhocHBzQvHlzDBs2DH369NF4P6jNmzfH/fv3sW7dOgQFBeHVq1dIS0tT2vdojx498OLFC2zbtg3//PMPHj16hLi4OBgbG8PR0RHe3t4YMWLEJ1FTdfz48XB2dkZQUBBu3bqFmJgYxMfHw9zcHI6Ojmjfvj0GDhxYokGPHB0dce7cORw6dAh79uzB7du3ER0dDTMzM1SvXh09e/bE2LFjUb16dS2sGSGEEEKI+iRMXq/khBBCCKmwAgICsHfvXgDAvn37MGTIkHLOESGEEEIIIaSiogJIQggh5D8mPT0dVatWRVJSEgDgxYsXcHFxKd9MEUIIIYQQQiqsitfrPCGEEEIU+t///scLH1u1akWFj4QQQgghhBCtogJIQgghpII4cOAAZs2ahRcvXsj8Pi4uDl988YVoJN/CkcgJIYQQQgghRFuoCTYhhBBSQezYsQOjR48GANSpUweNGjWCjY0NsrOzERERgevXryM7O5vHBwQEYPfu3eWVXUIIIYQQQsh/BI2CTQghhFRAz549w7Nnz2R+p6uri8mTJ2P16tVlnCtCCCGEEELIfxHVgCSEEEIqiJycHJw9exanTp3C7du3ERsbi7i4OGRkZMDa2ho1atSAl5cXxowZg7p165Z3dgkhhBBCCCH/EVQASQghhBBCCCGEEEII0RoahIYQQgghhBBCCCGEEKI1VABJCCGEEEIIIYQQQgjRGiqAJIQQQgghhBBCCCGEaA0VQBJCCCGEEEIIIYQQQrSGCiAJIaQCCgsLw6hRo+Dq6gpTU1NIJBL+IoQQQgghhBBCyhIVQBJCSBGvX78WFdiV9lXWfv/9d7i7u2Pnzp148eIFMjIyyjwP5P/k5OQgLCwMGzduxJgxY9CoUSPo6enx42PUqFEqp1XaY3PhwoUlWofbt2+L8iyRSBASEqJ2OtnZ2Thw4AD8/f1Rv359WFpawtTUFC4uLvD09MTcuXNx9uxZ5OTklCifRdWoUUOt7aOnp6eR5f6XxMXF4dSpU1i8eDF69eoFR0fHUh8nJREWFoYvvvgCbm5usLS0hIWFBdzc3PDFF18gLCysTPJACCGEEELkoydtQgipQN6+fYspU6YgPz8fAFCrVi20adMGlSpVKuec/TetX78eX331lcYK1ErL3t5e7Xny8vIwbtw4SKXSUi07ODgYEydOxLNnz4p99+rVK7x69QoXL17E0qVLERYWhpYtW5ZqeeVt4cKFWLRoEQBgwYIFJS78/Zi1bdsWV69eLdc85OTkYNasWVi3bh0YY6LvwsPDER4ejk2bNmHatGn46aefoK+vX045/fh5eXnhwoULAArOVy8vr/LNECGEEEIqFCqAJISQIiwsLDB58uQSzfvu3TscPXqUTzds2FBT2VLJ3r17kZubCwDo0qULjh8/TrW6ylFcXJxGCx/VPTavXr2K27dvAwAMDAwwcOBAtZe5cuVK3LlzR+35hAIDAzF69GheMK6rq4s2bdqgZs2aMDU1RXx8PB48eCCzcFJTRowYAXNzc4Uxurq6Wlt+RRQVFVXeWcDnn3+OwMBAPu3i4gJ3d3cwxnD16lVERESAMYa1a9ciNTUVW7duLcfcEkIIIYT8d9GvUkIIKaJSpUpYv3692vPl5OSgffv2fNrc3BwHDhzQZNaUKixsAgoKXKjw8eNQrVo1tGrVir82bdpUomND3WOzVatW/H2PHj1gY2Oj1vKeP3/Oa/ENHToUe/fuVWt+ADhy5Iio8HHy5MlYuHAhbG1ti8W+fPkSBw8e1EqN3UWLFqFGjRoaT/e/Tl9fHw0bNhQd302bNi2TZW/bto0XPuro6GDVqlWYNm0adHQKehjKz8/H2rVr8fXXXyM/Px/btm2Dp6cnRowYUSb5I4QQQggh/4d+mRJCiIbMmDFD1NfYli1bULdu3TLNQ2JiIn/v4OBQpssmxY0ePRqTJk2CnZ2d6PNdu3ZpfdmPHz/GzZs3+fTIkSPVmp8xhvHjxyMrKwvW1tb4+eef1S6ATEhIwIQJE3jh4/r16xXW4HRxccE333yj1jJI+Tl69Cjq1KkDIyOjMl92dna2qFn7N998g+nTp4tidHR0MGPGDMTGxmL58uUAgPnz52PIkCEwMDAow9wSQgghhBAahIYQQjRg3759+PXXX/n01KlTMWjQoDLPR2HzawC8FhApP87OzsUKH8vKzp07+fvKlSuje/fuas2/efNmPoDIihUrUKVKFbXzsHjxYsTGxgIA+vbtW+KuDcjHqXHjxuVS+AgUFH6+e/cOAGBpaYl58+bJjZ0/fz4sLS0BAG/evMHx48fLJI+EEEIIIeT/0K9TQggppfDwcIwfP55Pu7u7Y9WqVWW2/FGjRvERZwsHEAAAb2/vYqP8vn79WuZ8O3bsAAAkJSVh7dq16NixI5ycnPjIx0lJScWWGxcXh2XLlsHT0xMODg4wNDSEra0tmjVrhlmzZuHx48dK8y4c1VnYPDY4OBj+/v6oVasWjIyMYG1tjS5duuDYsWPF0pBKpTh06BC6desGZ2dnGBkZoWrVqhg2bBgePHig8nasSPLz87Fnzx4+HRAQoFZz/KioKF4TsUOHDhg7dqzaecjKyhIVgs6fP1/tND5FXl5ekEgkvOk6UND8W9ao24pGQNfE+VWRHT58mL8fPHgwTExM5MaamJiI/hA6dOhQqZdfuJ+FI31HRkZi3rx5aNKkCaytrWFkZISGDRvi+++/R3p6erE0wsPDMWnSJDRo0ABmZmawtrZGx44dsWPHjmID6igTFhaGGTNmoGnTpqhcuTIMDAxgb28PT09PLF++XFQ7vihV7x/Ce4Us6enp2LhxI3r27AlnZ2eYmJjA3Nwcrq6uGDNmDIKCgpSux44dO4qdH1KpFH/88Qd69+6NWrVqwdjYGBKJRHQMAAV/wO3evRv9+vVDrVq1YGZmBkNDQzg6OqJx48b47LPPsGrVKjx8+FBpPgghhBCiBYwQQkiJpaWlMTc3NwaAAWA2Njbs7du3ZZqHkSNH8uUre0VERMicb/v27ezy5cusWrVqMudLTEwULXPr1q3M0tJS4bJ0dXXZ9OnTWV5enty8R0RE8HhnZ2eWl5fHpkyZojDd//3vf3z+2NhY5u7uLjdWX1+f/fXXX5re5KUm3PYjR47UePqnT58WbYc7d+6oNX+fPn0YAGZgYMAeP37MPxemGRwcrDCNv/76i8e6ubmVYC1Kz9nZWeaxr02enp4qn4/y9r2mzq/yos5xUlIODg58GXv37lUav2fPHh7v5ORU6uUL93NwcDA7ceIEs7a2lru/mjRpwhISEvj8CxcuZDo6OnLj+/fvr9K+TUhIYP3791d6rFlZWcm9Fqp6vBbeK2TZv38/s7e3Vzp/jx49WFJSktz12b59u+j8iIyMZB06dJCZ1qFDh/h8T58+ZfXr11d5PZ4/f6502xJCCCFEs6gPSEIIKYXx48fzmkg6OjrYs2cPqlWrpnS+kJAQeHt78+mIiIgSD5Dh6+sLMzMzAAU1ewpHpu3Tpw+cnJxEsRYWFjLTePHiBaZPn47k5GSYm5ujY8eOcHR0RGJiIi5evCiKXblyJWbNmsWnDQ0N4enpierVqyMxMRHBwcFISEiAVCrFmjVr8ObNGxw8eBASiUTpusydOxfr16+Hjo4OPDw8ULduXWRlZSE4OBjR0dEAgCVLlqB+/fro06cPOnfujPv378PExASenp6oWrUqPnz4gHPnziEtLQ25ubkYNmwYmjVrBhcXF9U36idOWPOwcePGag0KcuDAAV6z6Ntvv0X9+vVLlIcrV67w9x06dAAAvHr1Chs3bsTx48fx9u1b6OrqwsHBAR07dsTIkSPRrl27Ei1LFbdu3cLhw4cRFRUFiUQCGxsbNGrUCO3atZN7XpRE37590bBhQ9y4cYP3CduqVSu0bt26WKy7u3uxz7R5flUUycnJ/HoAAM2bN1c6jzAmMjISKSkpGtvvd+7cwdy5c5GVlYUaNWrAw8MDJiYmePToEa5duwYAuHfvHgYPHowzZ87ghx9+4P1XNm/eHI0aNYJEIsHly5fx4sULAMDBgwexbNkyfPfdd3KXGxMTg06dOiE8PJx/Vr9+fTRt2hTm5uZ4//49Ll++jLi4OCQlJWHQoEHYtWsXAgICROkUdo2g7P5RmH5RP//8M7766itea9Pc3BweHh6oVq0apFIpHj9+jLCwMDDG8M8//8DT0xOhoaEKa60CBf189urVC7du3YKenh7atm2L2rVrIysrSzTgWmpqKnx9fXmTfB0dHTRr1gz169eHmZkZMjIyEBkZiXv37iEuLk7hMgkhhBCiReVdAkoIIZ+qDRs2iGpUzJ8/X+V5g4ODRfNqqnZW0Vo5ighr4enp6TEAbPLkySw1NVUUl5OTw6RSKWOMsdDQUKarq8vn69q1K4uOjhbFZ2VlsVmzZonWb9WqVTLzIKwBqa+vzyQSCWvQoAF7+PChKC4zM5P5+/vzWFdXV15TctCgQSwuLk4UHxUVxRo0aMDjR40apcrmKzParAGZnJzMjI2NefqrV69Wed7ExERei8nV1ZVlZmaKvhfuU2XHV7t27XjsL7/8wjZv3izKl6zXkCFDWEZGRklWWyZhDUh5LyMjIzZhwoRix3FpLViwgC9jwYIFKs2j6fOrvKhznJTE9evXRctQ5ZhJT08XzXPjxo1S5UF4rTUwMGAGBgZs8+bNLD8/XxR38OBBfn0tPB91dHRYtWrV2JUrV0SxUqlUtG/NzMxYWlqazOVLpVLm7e3NY5s3b87CwsKKxWVmZrKFCxcyiUTCADBTU1P26tUrpeuk6n47d+4cr8mpr6/PlixZIjPPd+7cEbUWmDRpksz0hDUgC7ebp6enzHtkVlYWY4yxn3/+mc/j5ubGnjx5IjPt/Px8duPGDTZp0qQyb6lACCGEEMaoAJIQQkogLCyMGRoa8h89vr6+vJBOFR9bASQANm7cOKXpd+zYkce7u7uz7OxsubHTpk3jsRYWFiwlJaVYjLAAEgCrUqUKi42NlZleamoqs7GxEcV37txZ7nYPDQ0V/ZDPzc1Vun5lRZsFkFu2bBH9gJe3PWUZM2YMn/f8+fPFvlenYKl69eo8tl+/fqKCZh8fHzZu3Dg2cOBAVqVKFVG6HTt21Ni+UqUAsvBlZ2fHLl++rJHlMlayAkhNn1/lRdsFkCdOnBCtu6rMzc35fKdOnSpVHoo2td+xY4fc2AkTJohiTUxM5BaSSaVSUVPiP/74Q2ZcYGAgj2natGmxP46Kmj9/Po+fOHGi0nVSZb9JpVLm6urK59m9e7fC+OjoaH6+6+vrs3fv3hWLERZAAmCNGjVSWsAsbIJ+9uxZpfkmhBBCSPmgQWgIIURNiYmJGDhwILKzswEATk5O2Lt37yc96rSRkRFWrFihMCY8PFzUHHvDhg0wMDCQG//jjz/C1tYWAJCSkoK9e/cqzcd3330nd7RlMzMzfPbZZ6LPVq5cKXe7e3h4oHr16gCAtLQ0PHnyROnyK4LAwED+vlu3biqPXh0UFIRt27YBAEaMGIFOnTqVKh/CgYv+/vtvAAVNkZ8+fYpz585h8+bN2L9/P969e4c5c+bw2IsXL2LJkiWlWnYhfX199O7dG1u3bsX9+/eRkpKC3NxcvH//HidPnsSQIUN40+XY2Fj06NEDT58+1ciy1VUW51dFkZaWxt8bGxurPJ8wVphGaTVr1gwjR46U+/3gwYNF0xMnTkTdunVlxuro6GDgwIF8urAZf1GrV6/m79etW8e74ZBnzpw5sLKyAgDs27cP+fn5CuNVcezYMTx//hwA4OPjU6xpd1H29vaYMWMGgIIBY/bv3690GcuXL1e6j1NSUvj7ypUrK02TEEIIIeXj0/21TAgh5YAxhuHDh/PRpPX19bF//361f/R4eXmBFdRCB2OsxP0/akqXLl1gbW2tMCY4OJi/b9KkidJ+10xNTeHv7y9zfnn69++v8PuGDRvy966urmjcuLHK8REREUqX/6mLiIjApUuX+LSiQhGhzMxMPpK7jY2NRkZxLzrqr5OTE06fPo2aNWuKPjcwMMCPP/6ISZMm8c9+/vlnUaFCSV2/fh2HDx/GmDFj0KhRI5ibm0NPTw+VK1dG165dsW/fPhw/fhxGRkYACgpNv/jii1IvtyTK4vyqKLKysvh7RYW0RRkaGvL3mZmZGsuPOtctdeNlXbeio6Nx9+5dAAXnVfv27ZXm0cjICB4eHgAK+tDUxEjQJ06c4O+HDBmi0jzCPzYuX76sMNba2hp+fn5K0yz8owkAfv31V5XyQQghhJCyR4PQEEKIGpYuXYrjx4/z6eXLl6Nt27blmCPNaNGihdKYO3fu8PeqDhbSrl07rFu3DgBEgwbIYmlpKXPQAyFhIambm5vS5QvjNVGg9bELDAzkA0FUqlQJPXv2VGm++fPn4+XLlwAKapUW1qwrDSMjI1Eh5Ny5cxUWci9evBjbtm1DdnY2UlJScOLECZULNeSpVKmS0phu3bph/fr1GDduHICCmqA3b95Ey5YtS7VsdWn7/KpICguMASAnJ0fl+QprrQPq1ZxUpkGDBgq/L3rcK7t2KbtuXb16lb9njGHKlCmqZJOf4wDw7t07pX/gKCPMx/Hjx3mhqCLJycmiPCjStGlTlVoWDB48GFu3bgUA/P777wgLC8PIkSPh5+eHevXqKZ2fEEIIIWWDCiAJIURFwcHBmD9/Pp/u378/b072qVOlBueHDx/4e2dnZ5XSFdbsVDb6qKWlpdL09PT+77albnxubq7SeHlOnDghqu0jy5dffglXV9cSL0MTdu3axd/7+/urVDvs1q1b+PnnnwEA3t7eGDVqlEbyYmZmJiqA7Nu3r8J4GxsbdOzYEWfPngUAhIaGlroAUlWjR4/G4sWL8ebNGwDAyZMny7wAUtvnlyILFixAfHy83O9tbGywaNGiEqevacLmxurUZBTGKmuyrA5l1yLhdUjdeFnXrcKRqgvfb9iwQZVsiiQmJqo9j6J8HD58WON5ULVlQefOnTFjxgx+Hbtz5w4v0Le1tUW7du3g5eWF/v37o1q1amrnkxBCCCGaQQWQhBCigujoaPj7+0MqlQIoaP5b2F9eRaBKbSBhn2mmpqYqpSuMS01NVRhb2BefqtSNL40bN24o/ZE/YMCAci2AvHz5sqiGk6rNr8eNGwepVApDQ0Ns2rRJY/mxsbFBbGwsAMDKygoODg5K53Fzc+MFkJGRkRrLizI6Ojrw9vbGjh07ABT0x1jWtH1+KbJz505e+CqLs7PzR1UAaWNjw9+npKQgKytLVCtSloyMDNE2UqV2rKrK+tolrEVYUnl5eaVOo7T5UJYHdWqprl69Gt7e3li2bBlCQ0P553FxcThy5AiOHDmCmTNnom/fvli9erXKhfyEEEII0RwqgCSEECXy8vIwZMgQXphibGyMAwcOwMLCopxzVraENYaK9u8njzDO3Nxc43ki/2fnzp38vZubG1q1aqXSfIXNJg0NDTFixAiVl/fFF1/wc6B58+bF+l6rV68eHj9+DED12mbCuNIUqJWEsIBUUW1AbaHzS3VFB3B58+aN3EFdCr19+1ZhGp8SYcFznz59cOjQoXLLR2Eh5N27d9GkSZNyyUehnj17omfPnoiMjERISAguXbqES5cu8esQYwx///03Lly4gNDQUNSpU6dc80sIIYT811ABJCGEKDF37txio9OWtu+sT5GwOVzRH/PyCGtVaaJfwfKycOFCLFy4sLyzIVdWVhb++usvPq1q7UehlJQUXL9+XeV4YS1BWbXPGjZsyEe/VrUwURinShN7TRIW5qlaA1GTyvP8KhxU61NhaWkJBwcHREdHAyhocqusQFHYR6aTk9Mn/QeSnZ0df184CnV55aOwAPL58+flXgBZyMnJCQEBAXxU7n///Rc7duzAsmXLkJ6ejvj4eMycORP//PNPOeeUEEII+W+hUbAJIUSBI0eOYOXKlXx67NixGD16dDnmqPw0a9aMvxc2cVPkypUr/L2yUX1JyR0+fJgXBOjo6GDYsGHlnCPAx8eHv09OThb1FydPYU0lAGXeV5twEBhVmosro24zWzq/1OPt7c3fh4SEKI2/cOECfy8ciflT5O7uzt8/evQI//77r0bSVfeYbdOmDX9/+vRpjeRBG6pWrYr//e9/2Lx5M//szJkzokGJCCGEEKJ9VABJCCFyvHr1CqNGjeKjCjdt2hTr168v51yVH+GP9jt37uDevXsK4zMzM/HHH3/InJ9olrD5defOneHo6KjyvIwxlV9CwcHB/HNZBUDt27dHlSpV+LSyZqLx8fG4dOkSn/b09FR5HUrr6dOnokI/TSxbWCtUlQGQ6PxST58+ffj7P//8U+FgNJmZmdi/f7/MeT9FNWvWRP369fn0mjVrNJKuusdsjx49+Pu9e/fi/fv3GsmHtgjzm5ubi4SEhHLMDSGEEPLfQwWQhBAiQ1ZWFgYMGICkpCQABU3+Dhw4oHSgg4qsXr166NixI5+eOnWqwh+p8+bN4z9ILSwsMHToUK3n8b8oOjqaD9wCQGOjWJeWjo4OpkyZwqeXLl2qcNTbefPm8RpJ9vb28PPzK9XyhYO6KJKVlYXRo0fzAaYqVaqEbt26lWrZgHigFFUG1KHzSz29evVC1apVAQBJSUn44Ycf5MYuXryYX8udnZ1FBVGfqm+//Za/X7t2Lc6dO6fyvDExMTI/V/eY7d+/P2rXrg2gYJCfYcOGqVRwCRScn6r2daqMqiPAC7s20NHR0ehARIQQQghRjgogCSFEhqlTp4qaZG7fvh0uLi4aSz8kJAQSiYS/PpU+2JYtWwZdXV0AwKVLl9C/f/9itV5ycnLw3XffYdWqVfyzBQsWqDwQCVHP7t27eeGZpaXlR1W7a+bMmXBycgJQUKDh5+eHiIgIUUzh8bJx40b+2YIFC+QW9i9cuJCfNzVq1JC7bHd3d8ycOVN0Hhd17do1tG3bFlevXhWlr4kBXRo1asTfnz59WqURg+n8KihAL9y/Xl5ecuMMDQ1FI3MvW7YM69atE9XUzc/Px9q1a7F8+XL+2ffffw8DAwOt5L0sDRs2jNd6zcvLw2effYbly5fLLdRLS0vDvn370KlTJ0ydOlVmjPCYPXDgQLFaz0Xp6upi48aN/Jg9e/YsOnbsiLCwMLnz3L9/H3PmzEH16tWLXQtKysPDA/7+/jhx4gRycnJkxoSHh4sG2fLx8YGhoaFGlk8IIYQQ1dAgNIQQUsTBgwexZcsWPm1vb4/z58/j/PnzJUpv+PDhor6yPmUeHh5YtmwZZs2aBQA4duwYqlevDm9vb1SrVg2JiYkICQkR1Ujp27cvZsyYUV5ZLndNmzYt9pmwJs7Ro0dlxhSOTq1MYGAgfz9o0KCPqpauqakpDh8+DC8vL6SnpyMsLAx169aFp6cnatasieTkZFy4cIGPMA8AAQEBmDhxYqmXnZaWhp9//hk///wzqlSpgiZNmsDBwQHGxsZISkrC7du3iw3gMW7cOLmFM+pq1aoVqlevjrdv3yImJgb16tVDly5dYGtry/vaa9WqFQYPHszn+dTOr6NHj2L+/PkKY8aNG1escLRXr174/vvvS738MWPGICQkBLt27YJUKsW0adPwyy+/wN3dHYwxXL16Fa9eveLxo0ePVmuk94+Zrq4u9u/fj86dO+POnTvIycnB7Nmz8f3338Pd3R3Vq1eHgYEBEhMT8ezZMzx+/JjXTuzfv7/MNPv164c5c+aAMYbjx4+jcePGaNu2rahAfsiQIWjZsiWf9vX1xcaNGzFp0iRIpVJcu3YNrVu3hqurK5o1awZra2tkZmYiJiYGd+/e1Uoz7dzcXPzxxx/4448/YGxsjMaNG6NWrVqwsLBAYmIiXr58iVu3bvF4Y2NjUd/OhBBCCCkbVABJCCFFPHjwQDQdExODDRs2lDi9li1bVpgCSAD4+uuvYW1tjZkzZyIlJQXZ2dk4depUsThdXV1MmTIFq1atUntwg4pEWV9+iYmJCpsmK3L79m08fPiQT38sza+FWrZsibNnz2L48OF4+fIlcnNzZTYX1dPTw1dffYUff/xR43l4//69qJl6URYWFvjxxx8xefJkjS1TR0cHGzduRL9+/ZCdnY2YmBhRYTFQMFq5sAAS+LTOr4SEBKXH98uXL4t9JqvAvaS2bNkCS0tLbNiwAYwxvHjxAi9evBDFSCQSTJ06tcIVOtnY2ODKlSuYOXMmtmzZgry8PGRkZCAoKEjuPMbGxmjRooXM71xdXfHdd99hyZIlAICHDx+Kri9Awej2wgJIAPj8889Ru3ZtTJgwgRfqP3/+XOEI3Q0aNNBYE2hhAWlmZiauX7+O69evy4ytWbMmdu/ejcaNG2tk2YQQQghRHRVAEkIIUdvYsWPRu3dvbN68GSdPnsSzZ8+QkJAAc3NzVKtWDb6+vhgzZgzc3NzKO6sVmnDwmdq1a6Nt27blmBv5PDw8cP/+fezduxf79+9HeHg43r9/D1NTUzg7O8PHxwfjx49HnTp1NLbMS5cuITQ0FKGhobh9+zZiY2MRHx+PlJQUmJqaonLlymjevDl8fHwwdOhQrTRh7t69O27duoX169fj8uXLePPmDdLS0pQ2baXzS3UGBgZYt24dhg8fjm3btiEkJIT3X+jk5AQvLy+MHTsWrVq1KuecaoexsTE2btyIb7/9Frt370ZQUBCePXuG+Ph45Ofnw9LSErVq1UKTJk3g4+ODrl27wsLCQm56ixcvRrt27bBt2zbcvHkTsbGxyMjIUJoPb29vPHnyBIcOHcLx48dx7do1xMTEICUlBSYmJrCzs0O9evXQtm1bdOvWTaOF0Hfv3sW1a9cQHByMGzdu4OnTp4iKikJGRgZMTExgb2+Ppk2bolevXhg0aBA1vSaEEELKiYQpewomhBBCCCGEEEIIIYSQEqJBaAghhBBCCCGEEEIIIVpDBZCEEEIIIYQQQgghhBCtoQJIQgghhBBCCCGEEEKI1lABJCGEEEIIIYQQQgghRGuoAJIQQgghhBBCCCGEEKI1VABJCCGEEEIIIYQQQgjRGiqAJIQQQgghhBBCCCGEaA0VQBJCCCGEEEIIIYQQQrSGCiAJIYQQQgghhBBCCCFaQwWQhBBCCCGEEEIIIYQQraECSEIIIYQQQgghhBBCiNZQASQhhBBCCCGEEEIIIURrqACSkE+El5cXJBIJJBIJQkJCyjs7n5wdO3bw7Tdq1CiZMSEhITzGy8urTPP3MUhISMD333+PNm3awNraGrq6unx77Nixo7yzRwghhBCicao8IxJCCCk9vfLOACGEkPL3+vVrdOzYEe/evSvvrFR458+fx86dO3Ht2jVERkbC0NAQVatWhZ+fH8aOHYt69eppbdmMMRw+fBh79uzBnTt3EBUVBTMzMzg7O6Nnz54YPXo0qlevrrXlfwpSU1Nx69Yt3Lx5E2FhYXj16hU+fPiAuLg45OXlwcrKCvXq1UOHDh0wYsQIuLq6qpV+bGwsdu7ciXPnzuHhw4dITEwEYwzW1tZwc3ODl5cXRo4cqdJ+yM/Px9WrV3Hu3Dlcv34djx8/xocPH5CXl8fT8/b2xtixY+Ho6FjSTSJXTk4OLl68iPPnz+PmzZt48uQJ4uLiAAA2NjZo1KgRfH19MXr0aFSqVEmttKVSKf78808cOnQIYWFheP/+PfT19eHo6Ij27dtj2LBh8PT0VDvP165dw65du3D16lW8fv0aqampMDY2hp2dHZo1a4Y+ffqgf//+MDQ0VDnNV69e4ffff0dQUBAiIiKQkpKCypUrw8XFBf369cPw4cPVWv+4uDh+/IWFheHmzZuIjo7m3wcHB2vsTzKpVAp3d3fcvHmTfzZy5MgS/el0+/Zt7N+/H+fOnUNkZCQSEhJgY2MDe3t7NG3aFN7e3ujcuTPs7e1lzp+VlYU7d+7wdX727Bk+fPiADx8+IDs7G5aWlqhduzY8PDwwbNgwNGvWTO08hoeHY9u2bTh9+jT+/fdfZGdnw8nJCR4eHhgxYgR8fHyUprFw4UIsWrRI7WUXioiIQI0aNRTGXLx4Ebt378alS5cQHR2N7OxsODg4oHHjxhg8eDAGDhwIPb2S/Yx79+4d9u/fj2PHjiEiIgKxsbEwMzODvb096tSpAy8vL3Tu3Bn169dXmI62j9P8/HycOnUKBw8exPXr1xEdHY2MjAzY2dnB0dER7u7u8Pb2RqdOnWBqalri5RBCCClDjBDySfD09GQAGAAWHBxc3tn55Gzfvp1vv5EjR8qMCQ4O5jGenp5azc/IkSP5srZv367VZamiS5cuPD/GxsasZ8+ebOLEiWzy5Mls8uTJ7Nq1a+WdxU9ecnIyGzx4MN/Osl76+vrsxx9/1MryIyMjWadOnRQu38zMTOPHo7OzM08/IiJCo2lrw+TJkxVuI+FLR0eHffHFFywzM1OltDds2MBMTU2VpmtgYMC+//57hWmtWrWK2dvbq5RPfX19tnDhQpaXl6eJTcQYY2zWrFnMyspKpeWbmpqyjRs3qpz2vXv3WN26dZWmO3ToUJaUlKRSmgkJCaxfv34q5dfFxYVduXJFaZpSqZTNmTOH6enpKUzPzs6OHTt2TKV8enh4KM2fJp8BVq5cWSx9efdIeWJjY1lAQIBK23by5Mly0/npp59UPvcAsEGDBrH4+HiV8/nDDz8wfX19hWn6+/uzlJQUheksWLBArXwWPbeTk5Plpp2QkMB69OihNJ0WLVqw8PBwldedMcays7PZ4sWLmZGRkdL0GzRooDAtbR+nd+7cYa1atVJpm/71118lXk4hVZ4RCSGElB7VgCSEkP+4mJgYnDlzBgBgaGiIe/fuqV2riyiWm5uLfv364fz58/yzhg0bokWLFsjMzMTFixcRExOD3NxczJ07F7m5uZg/f77Glp+SkgI/Pz88fPiQf9a6dWs0aNAAycnJCAoKQlJSEtLS0jB69Gjo6OhgxIgRGlv+p6pSpUqoX78+nJ2dYW5ujpycHERERODatWvIyspCfn4+fv31Vzx9+hSnTp1SWCPpp59+wjfffMOndXV10bp1a9SsWRNAQS26sLAwSKVS5OTkYP78+UhOTsbKlStlpnfmzBnExMTwaUNDQ7Rq1QrOzs4wMTHB69evcfnyZWRmZiI3NxcLFy7Es2fPsGvXLujolL4HnqNHjyIpKYlPm5mZoXXr1nBycoKBgQGeP3+Oq1evIjc3F+np6Zg0aRLevHmDpUuXKkz31q1b8PT0RHp6OgBAIpGgZcuWaNiwIfLz83H//n3cuXMHALB37178+++/OHPmjMIai5mZmejcuTNu3brFP6tcuTKaNWuGqlWr4sOHD3j06BFevXoFAHj58iU6d+6MoKAgtGnTRm66w4YNw759+/i0jY0NOnbsCFtbW8TGxuLChQtITk5GbGws+vTpg8OHD6NHjx4K1z8qKkrh95oUERFR6uvM27dv4eXlhYiICP5ZzZo10bx5c9jY2CAzMxPPnz/H3bt3kZWVpXK65ubmqF+/PmrWrAlLS0vk5eXh33//xdWrV5GamgoA2L9/P548eYJLly7BwsJCYXrz58/H4sWL+XRhTVojIyPcunULjx49AgDs27cP8fHxOH78uNzzuXXr1pg8ebLK67J9+3ZkZGQAAHr27Ck3r0lJSWjbti2ePHnCP6tVqxY8PDxgbGyMly9f4vLly8jNzcWtW7fg5eWFa9euKa1NCQDZ2dno168fTpw4wT+ztrZG27ZtYW9vj/z8fLx79w63b99GQkKC0vS0eZyePXsWvXr14seLRCJBs2bNUKdOHVhYWCApKQnh4eF4+PAhGGNaywchhBAtKO8SUEIIKQsf27/bH1MNyOPHj/O8+Pr6lmteKqp58+bxbWxkZMT27dsn+j47O5vNmjVLVKsjJCREY8sfPnw4T7dSpUosKChI9H1qaiobOnSoqJbO8+fPNbLsT60G5NatW9maNWtYeHg4y8/PlxmTlJTEpk6dKtpfK1eulJvm8+fPmYGBAY/18fFhT58+LRb3+PFj1rFjRx4nkUjYzZs3Zabp5+fHJBIJ6969O/v7779l1sL88OED8/f3F+Xz119/VXFLKFa3bl2mp6fHBg8ezM6cOcNyc3OLxbx584b5+PiIln/ixAm5aWZkZLBq1arx2Jo1a7KwsLBicRcuXBDV/pw+fbrCvC5atIjH6ujosCVLlrCMjAxRTH5+Ptu3bx+ztLTksY0bN5ab5rp160TrNWvWrGJppqamsvHjx/MYU1NTFhkZqTCvzs7OTF9fnzVr1oyNHz+ebd68md29e1djNcuEfH19GQBmbW3NunXrpvY9MikpidWqVYvP17x5c7k1R1NTU9kff/xR7NondPjwYbZ06VJ2584dubV1MzIy2JIlS5iOjg5f7pQpUxTm89y5c6Lt980337Ds7GxRzN69e0U1AxctWqRk7VXz8OFD0bKPHj0qN7Z///48ztjYmO3atatYTEREBGvbtq1om8u7TslL287Oju3atUvmNs7Ly2Pnz59nK1asUJieto7TGzduiPbDoEGD2OvXr2XGRkZGsnXr1rEbN26ovZyiPrZnREIIqaioAJIQ8p/wsT1cfkwFkLt37+Z5GT58eLnmpSKKjY0VNbvdtGmT3FhhE20PDw+NLP/BgweiH+unTp2SGSeVSkU/bP39/TWy/E+tAFIdI0aM4Ovm6uoqN27hwoU8ztHRkaWnp8uNTU1NZQ4ODjx+5syZMuNWrlzJ7t69qzSP+fn5rHfv3qLlq1JgocyCBQvYixcvlMZlZWWJmlK6u7vLjV29ejWPMzMzU5j+nTt3eHNaAwMD9vLlS7mxNWrUULmw8sCBA6JClPv37xeLyczMZHZ2djxm0qRJCtMcOHAgjx03bpzC2Hv37sksTNZ0AeS2bdt4eps3bxbdk1S9R44bN47P07FjR4XHtabNnz+fL9vc3FxhNwitW7fmsUOGDJEbt3HjRlGaHz58KHU+hX8sValSRWZBPWOM3b59W7SP//zzT7lppqSkiAp+d+/erTAPwnu8vb29Rv5c0sZxmp2dzRo0aMDn/+qrr0qdT1V9bM+IhBBSUdEo2IQQ8h+Xm5vL32uiaSYR27lzJ29OWqdOHYwfP15u7IoVK/g+uHr1Km9qWhobN25Efn4+AKBz587w8/OTGaejo4MVK1bw6f379+PDhw+lXn5FNm7cOP7++fPnSEtLkxl37949/r53794wMTGRm6aZmRl69erFp589eyYz7quvvkKTJk2U5lEikYiaPUdFRWnkuFq4cCFcXFyUxhkaGooG7Lh+/Tri4+Nlxu7fv5+/Hzt2rML0mzZtiiFDhgAoGAxn06ZNMuNSUlLw+vVrPu3v768wv3369BHtH1nb/8KFC4iNjQUA6OvrY+HChQrTFG7/nTt3ipquF9W4cWMYGRkpTK+0YmNj8dVXXwEA2rdvj7Fjx6qdxt27d7FlyxYABc2l9+zZo/C41jThuZeamooXL17IjAsLC8ONGzcAFHR7ILzGFTVhwgTe/Uhqaip27dpVqjxKpVLs2bOHTwcEBMht1i089ps0aYJBgwbJTdfc3Bzfffcdn167dq3c2JycHL6vAeC3335D7dq1Vcq/Ito4Tjdu3Mibwrds2RLLly/XaPqEEELKH/3SJBolkUj4q9CtW7fw+eefo06dOjA1NYWFhQU6dOiAwMBAmX23nD9/Hv3794eLiwuMjIxgb2+Pvn374tKlS2rlJS4uDsuWLYOnpyccHBxgaGgIW1tbNGvWDLNmzcLjx4/VXr/Tp09jzJgxvB8aY2NjODs7o2/fvti+fbuoIEeeUaNG8W1UOMpkUlIS1q5di44dO8LJyQl6enqQSCSiHyleXl58vpCQEJXTTk9Px6+//or27dvDzs4OhoaGqFatGvz9/XHlyhW11v/hw4eYNGkSXF1dYWJiAltbW7Rs2RJLly7lI5/u2LGD52HUqFFqpV9S4eHhmDJlisJ8qSIkJITnXdnIjU+ePME333wDd3d32NrawsDAgI/Q6e7uji+++AKHDx9GSkqKaL4aNWpAIpFg586d/LPRo0eLzp3Cl7IftaUhXNfRo0fzz3fu3KkwH/K20YkTJ+Dv7w9XV1eYmZlBIpFgzZo1xZbLGMNff/0Ff39/uLi4wMzMDGZmZnBxccHQoUNx4MABlfp0knU+REZGYt68eWjSpAmsra1hZGSEhg0b4vvvv+cFgELh4eGYNGkSGjRoADMzM1hbW6Njx47YsWOHRvuVOnz4MH9feI7KU716ddEorIcOHSrVshljOHr0KJ8W7mtZ2rVrx3+AS6VSHDt2rETLff36Nd8/b9684Z/XrFlT5rEu75oGFIxaPGXKFDRo0IDv16pVq6Jr165Yv369zH1bVqpUqSKaLuybrihhwaSVlZXSdK2trfn7wsLj0qhfv74oTWGBXFlo164df88YEx0ThaRSKcLCwvh0t27dlKbbvXt3/v7gwYMyY4oWCivb/rq6uqI++mRt/2vXrvH3LVq0KHYcFOXi4oK6desCKPjDp6TnlaZMnToViYmJMDAwwG+//abwmiSPsMB3zJgxqFq1qiazqJSq557w+uvj44Nq1arJTbPoc0tpr79nz54V9ZU4cuRIubHCY0rdYz8sLAxv376VGff333/zwvImTZqI/tz42AiPqe+++w66urrlmBv5Xr9+DVdXV37/atu2LRITE0XfF34n7J8zODgY/v7+qFWrFoyMjGBtbY0uXbrIvB5IpVIcOnQI3bp1g7OzM7/vDRs2DA8ePCiL1SSEEO0oz+qXpOKBoOkFYwUjDurq6oo+F75GjBjBm4KlpaWxnj17yo2VSCRs9erVKuVj69aton6cZL10dXXZ9OnTVRoVNDY2tlg/VrJerq6uMvurEira9Pby5cuiPq+Er8TERD6fKqNgF0378ePHrH79+grzPH/+fJW26fLlyxWOHung4MCuXLlS5s1Y1q5dK+pbTVa+Ll++rNFRsBcsWKB01NPCV0BAgGheYXNUZa8FCxZobkMpWFd18lF0GyUlJbG+ffvKnO/nn38WLfPZs2esWbNmSpfXokULpU07i54PJ06cYNbW1nLTbNKkCUtISODzL1y4UNQsueirf//+GhkxODMzU7Sc0NBQpfP88MMPPL5du3alWv7Tp09F6xUVFaV0ns8//1zu8auqiIgIlY8vede0tLQ0paOGF57jivoV1KZDhw7xfJiYmMhtXjl27Fge16tXL6XpCkfBnTNnjkbyWqlSJZ7m/v37NZKmqlJSUkT7TFafbbGxsaIYVUb4DQ0NFc0jq4l/Tk6OqE+5v//+W2GasbGxonNWVl+dkyZN4t8PHjxYaT4ZY6xLly6lujcqO19UdfjwYZ7O//73P/65Ok2w8/LymIWFhcL9qW137twRbRN5fWsKR2v+8ccflaZ75coVHq+rq8uysrJKnEdh/6tNmjRRGCt8VlN1xHhDQ0M+j7yuXD777DMeo6xfR00o6XEaFhbG57OwsJB7LdUWVZ9d79+/zxwdHXls165di3U9ILz/OTs7s7y8PDZlyhSF9zHhuRgbG8vc3d3lxurr62tk5G9CCCkPNAo20ZqNGzfyJiItWrRAo0aNwBjDpUuX+EiTgYGBqFu3LmbPno3+/fvj9OnTMDAwQPv27VGrVi2kpKTg/PnziI+PB2MMM2fORKtWrdC+fXu5y125ciVmzZrFpw0NDeHp6Ynq1asjMTERwcHBSEhIgFQqxZo1a/DmzRscPHhQbg2A2NhYtGvXDi9fvuSfubi4oE2bNjA0NMTjx49x/fp1AAVN8Ly9vXHq1ClRjQ95Xrx4genTpyM5ORnm5ubo2LEjHB0dkZiYiIsXLyrfyApERUXB19cXUVFRsLKyQocOHWBvb4+4uDgEBQUhOTkZAPD999/Dzc0NgwcPlpvW6tWr8e233/JpIyMjeHt7o2rVqoiLi0NwcDCio6PRo0cPTJ8+vVT5VseGDRvw5Zdf8mlDQ0Oerw8fPiAoKEjj+VqzZo2oOaGtrS3c3d3h4OAAiUSChIQEPHnyBOHh4ZBKpcXmHzlyJOLj43H+/Hk+0qWPjw/q1atXLLZ169bFPqtRowavPbRgwYIS15J0cnLio3g+efKEj85cr149UQ08efkAAMYYhg0bhn/++QcSiQStWrVC/fr1wRjDw4cPRedUeHg4PD09RU16GzVqhKZNm0IikeDOnTv8X/1bt26hXbt2uHjxIurUqaN0Xe7cuYO5c+ciKysLNWrUgIeHB0xMTPDo0SNeq+TevXsYPHgwzpw5gx9++IFvt+bNm6NRo0aQSCS4fPkyb8Z38OBBLFu2TNTMrSSePn3Ka1AVjuSpTPPmzfn78PDwUi1fOL+9vT0cHBzKZPkWFhb8+AoMDOS1k0aMGAFzc/Ni8U5OTqLpjIwMdOrUiTedBApGre3QoQPMzMzw4sULXL58GVKpFNHR0ejVqxf27duHAQMGlCi/JZGSkoIFCxbw6V69esltXtmrVy9s3boVAHD8+HFcuXJF7j0iODiYj1RraGhYouaxRUVFRYlGtlVUC0wbitbYkbV8VqTWcUlq5T169KjYiMD6+vro1q0br822ePFi+Pn5yW0uPHv2bH7O+vj4yLwGCfNa0nyWh5SUFH5eurq6lvj69vDhQ16739TUFM2aNUN2djZ27NiBvXv3Ijw8HCkpKbC1tUXTpk3Ru3dvjBw5EgYGBhpZj5ycHNEzibu7OxwdHWXGCq9hwmubPMIYqVSKZ8+eoVGjRmrnMSUlpVjtd0VKckwJ55F3TF29epW/79ChA4CCa9DWrVtx8+ZNxMbGwsrKCrVr10bXrl0xceJEVK5cWaXla5KwRY6Hhwf09PQQExOD3377DYcOHUJERASkUins7OzQrl07DBkyRFQLtKzy2KNHD946yd/fHzt37oS+vr7C+ebOnYv169dDR0cHHh4eqFu3LrKysvizMwAsWbIE9evXR58+fdC5c2fcv38fJiYm8PT05M+0586dQ1paGnJzczFs2DA0a9ZMpW4wCCHko1J+ZZ+kIoLgHzoDAwPm5ORUbETEvLw89vXXX/M4Kysr3kG/l5cXe/PmjSg+KSmJeXt783gvLy+5yw8NDRXVuOzatSuLjo4WxWRlZRUbbXbVqlVy0xSODGliYsL27NlTLCYsLEzUIXi1atVEtReFhLUMCmvRTZ48maWmporicnJymFQq5dPq1oAs/Gf8m2++KfbvbHx8POvUqROPrVWrltxBCR4+fCiqYfjZZ5+x9+/fi2LS09PZxIkTRctFCWt5qOrJkyeiZfn6+hbb1ykpKXz0X+E6lLQGZG5uLrOxseExS5cuZTk5OTLTio+PZ9u2bWPLly+X+X1JB6ER1qDUVA1JdWqtCrdR4fHbqFEjmQM1FNYcyc7OZk2aNOHzVa5cmZ0+fbpY/OnTp5mtrS2Pa968udztKzwfDAwMmIGBAdu8eXOx4/jgwYOi2qqrV69mOjo6rFq1asWuTVKpVHRtMDMzY2lpaQq3hzJ//vknT8/Ozk6leR49eiS6PhU939SxfPlynk6bNm1Umkc4KrqJiUmJl12oJIPQCGuY6erqstWrV4uuh4wV1Kht0aKFqNbMq1evSp1fRbKystjz58/Zpk2bRNf8KlWqyB2plbGCgWA6d+7M442MjNjMmTPZrVu3WGJiIktMTGS3bt1i06ZN49c1AwMDmfebkhDWqrW0tCzz2kXCWrUNGjSQGZObm6vSYElC+/btE50rP/30k8y48PBwZmZmxuNcXFzYjh072PPnz1lmZiZ7+/Yt++eff1j79u15TP369dnbt29lpicc1V7RoDpCdevW5fOYmpqqNI+QcD1LWgNywoQJPI1z586JvlOnBuTmzZtF1+knT56whg0bKqzhVbNmTXbr1q0S5ZuxgvvI69ev2a5du1jTpk1F12l5LU9KUquWMcYqV67M5ylpbWHhNtLT02OxsbEK4zt06MDjZ8+erTT96Oho0bp99tlnxWKeP38uiomMjJTbYqHwZW5uzgIDA0u0zoyV/DgNCAjg882cOZMdPXpUVGtb1svHx4fFxcWVOK9Cyp6D/vnnH2ZsbMxjpkyZIve5WVgDUl9fn0kkEtagQQP28OFDUVxmZqaolqyrqyuvKTlo0KBi6xYVFSUapGfUqFEaWXdCCClLVABJNEr4YGBsbMweP34sM04qlRZrGtygQQO5oxi+ffuWFyJIJBK5zQg7duwo+lGQnZ0tN6/Tpk0T/XBNSUn5f+zdd3xUdfY//te9UzKTmfQCCYTQE0IgjdAsCIhdVwWx94q6a/l+xPKzrLquq7vqruvaFbEB1rWvDRtVQiqEACGB9F4nmXrv+/fHMJeZZNpNGyY5z31kTWbec++ZcDNz59zzfp9+YzZv3uwS42effeZxe5WVlS7Tvh999FG345xP8gHfHTEd5CYgAe9T9xoaGlw68+7YscPtuFWrVklj5s2b5/V36tzp058PMYPhfNI2Z84c1tvb63acIAjsrLPO8isuXwnIkpIS6f7BTo0dDQlIwN5R01enUOduqyqViuXl5Xkc+/vvv7skDNevX+92nPPfAwD21ltvedym84duwJ5UKysrczu272vTxo0bvT43X1588UVpW3PnzvXrMa2trS7xeorVH2vXrpW248/UX8YY2717t8v+BzMFkTH5Ccjy8nKXRNTzzz/vcWxbW5tLh+Nrr712ULH2VV1d7fUDMACWm5vb78KZO0aj0a8p5TzPs1NPPZVt3759SJ5DbW2ty3TZtWvXDsl2/VVYWOhyYfDFF1/0ONZ5iYY77rjD57YdF5j8ec8rLCz0uNyJ81dkZCS77bbbWGdnp8dtffbZZy6vab6SS+Xl5f324+291B3nxw4kAfnLL78wjuMYYF/+pi85CUjnDtTz5s1jkyZNkn5OTU1lV155JbvmmmtYdna2S9w6nY7l5+f7HbO3JXwAe8KmqKjI4+NLS0tdxjsvw+HNnDlzpMe8/PLLfsfrzDmZfe655/ocf9ddd0njfU3XZsy+1JDzc1u0aFG/Mc7nsFqt1uWCenx8PLvooovYDTfcwJYtW9ZviZ1XXnllIE97wMep8/n7ueeeK1005nmenXDCCey6665jl112mcux5jje3J2/y+XtPGj9+vUu5yV//vOfvW6r7xIk8fHxHl8juru7XS5sA2ArVqzod8HNwXnZCb1eP+IXkwghZLAoAUmGlPMb6F133eV1rPMJLAD2+eefex3vfHLyxRdf9Lu/74mmryvtBoPBpdrK3Umm84dFf04gnauNEhIS3F4ddT7J12g0fp8Qy01AxsXFeUzoOqxevVoa/+9//7vf/a2trS4npZs3b/a6vaqqKpfEwXAlINva2lyqH31Vyhw8eFD64OUtLl8JSOe1oc4///xBPYfRkoD0lkxwWLBggTT+j3/8o8/xztVvnqqLnP8esrKyvG6v74WEu+++2+t459em//f//p/PeL15+umnpW35W4HY29vrEq+3hK0vt956q7Qdf9eq6/taOtgKE7kJyHvvvVcaP3fuXI9VJg7OVaYhISGso6NjUPE685aA1Gg0fq9L7Gzbtm0uFcF9v9LS0tirr74qO0Hljs1mY6eeeqrLB2F/33OGgsFgcKmMS0tL81jVzJh9fV3nD9fe1oItKCjot/7v7bff7jUeo9HI/v3vf7tcfOv7dfHFF/tcq7Wzs5OFhYVJj1mzZo3X8X0vzg3k72qgiR3G7M975syZDACLiYlxe9FITgLS+QKu40ur1bJNmzb1G7t582aXc60ZM2Z4PQaceUpA8jzP7r33Xp/Jl99//93lcb7OiRzmz58vPeYf//iHX49xdujQIZdzjo8//tjnY/q+t7r7XTp0dXW5VGADYOnp6f3GffLJJ25/f/fff3+/15dDhw6xefPmubyW+lsx6mygx+ncuXP7xTlt2jRWWFjoMk4QBPavf/1ryM81PZ0HPfPMM9K/Jc/z7D//+Y/PbfVNQP7rX//yOv6qq65yGe8tqc4Yc0nClpSU+PX8CCHkeEFdsMmwWblypdf709PTpe+1Wq3Prn/O4ysrK/vd/9NPP0nfZ2Rk+FzrR6fT4dJLL3X7eHe3XXfddV63B9g7zPK8/c+qvr4e+/fv9zr+tNNOc+lMOpTOPfdcaDQar2Oc16Nz1xV127ZtUmfvhIQEn52hk5KScPLJJ8uOVa5t27bBbDYDAMaNG4cVK1Z4HT99+nQsXrx40PudNGmS9P3mzZsHvT7fQBw+fBjMfvFoWLtk+4PjOK9rhwL2DrR5eXnSz/78Hd1www3S97t27fLZ5VjOa43c8e5ea+QwmUzS9/6ufxYSEuLys9FoDNr9D8TmzZul7x0d4r254IILEB0dDQAwm80ua54Nll6vx2233SZ9XXXVVTjppJOg0WhgMplw9913Iysry6V7syeMMbz00ktYtWoVioqKpDVrr7/+elxzzTVYvHgxFAoFSktLcdNNNyEzMxMHDhwYVPz33nsvfvjhB+nnt956a9jec/pijOHaa6/Fnj17ANiPv/fff9/reml//OMfERERAcD+2nHaaadh9+7d/cb9+uuvOOuss2CxWFxu93asNjc3Y82aNbj77rvR09OD8ePHY+XKlbjppptw8cUXS2tHbtq0CYsXL8bNN9/sdh1fwL7G6Z/+9Cfp55deegn33nuvy9+b4znccsst+PDDD/ttYyT/rh577DHpWPrHP/6B2NjYQW3P3Wvy+vXrsXr16n63L126FJ9//rl0bnTw4EG89957fu3H+W/vmmuuwfLlyxEWFgZRFPHUU08hNTUV//vf/zw+vu+/x0BeAwfy7/T2229L6zNGR0fjnHPO8fmYU045xWVd2GuvvRbvv/9+v3FHjhzBGWecIa2l7i1Od/9Ot956K/7617/2+11MnToV3333nbSWptlsxt/+9jefcQ+VvrHq9Xp89913yMjIcLmd53n86U9/wpNPPind9u6777qs0z5U7r//fvy///f/wBiDSqXCe++9h1tvvVX2duScc8yYMQNz5871e/xgz1EIIWSkUQKSDJvZs2d7vd/5Q9DMmTM9Lt7vbrxj8XNnBQUF0vf+NIDpOy4/P9/lvtraWjQ1NUk/+5PAiouLc1mwvu82+8rJyfErzoHwZ9H0mJgY6XtHUxpnhYWF0ve5ubl+LYyem5vrX4CD0DcuxwcbbxYuXDjo/U6cOFE6Drq6ujBv3jzcdNNN+Oabb6QmG2PJ5MmTpcSPJ0VFRdKHeL1e7/PEGgAyMzOh0+kA2JsAFBUVeR0v57UGANLS0vwe7+61Rg7niwB9kyWeOJLrDlqtNmj3LxdjzOXv25/XcpVK5dIoydfrrhyRkZF44YUXpK/169fj119/RW1tLdauXQuO41BYWIiTTjoJ33//vcftiKKIyy+/HLfeeivq6uqwcuVKHD58GJs3b8brr7+OdevWYevWrdi/f7/0nPft24fly5ejtbV1QLG/9NJLeOaZZ6SfH3roIZ8X+obSfffd55J4e+mll/olE/qKiYnB22+/Lb2mV1RUIDc3FwsWLMD111+Pa6+9FtnZ2ViyZAnq6+sRFxfn8trursERYE96ZWVl4a233gLP83jppZdQU1ODjz76CK+88go2btyIiooKbNq0SUqAvvrqq/jjH//oMdaHH37Y5bzg6aefxsSJE7Fy5UrcfPPNOP/885GUlIRXXnkFgP2ioDNPsQ61oqIi/P3vfwdgT3L5aobij74XN3Nzc3HRRRd5HL9o0SJceOGF0s8bN270az//+te/pL+9devW4YcffkB9fT2eeuophISE4NChQzj77LOxfv16v+IcyGug3Nc/xhjeeecd6edLL73U78Tnu+++KyWHe3t7cfnll2P69Om48sorcdNNN2H58uWYMWMGtm3bBp7nXZqwuDue+j5/jUaDxx9/3OP+o6Ki8MADD0g/f/zxx7DZbH7FPlh9Y12zZg2mTp3qcfzdd98tNVUTBMFtkn+gBEHADTfcICVgdTodvvzyS1xyySWytxUREdGvyVpfzuccvs5P+o4f7DkKIYSMNEpAkmHjOIn3xDnh6Gts3/GOqjxnzt11k5OT/QnRpVtmS0uLx+1ptVrEx8cPept9DWenQX9+p86VKO5+p87xT5w40a/9+jrRGgrO/zbOVYneDFXX1zfffFM66e3t7cVrr72Gs846C1FRUcjKysIdd9yB//3vfyN20h5I/hy/zv9WSUlJfiWLeZ53+ffy9Xck57VG7nh3fxdy6PV66Xt/K2n6jnPeRrDtX67Ozk6X3/lQvJYPh+joaDz11FNSgs9sNuPyyy/3+GHw6aefxoYNGwAAp556Kj744AOMHz++37hp06bh22+/xaxZswAANTU1eOihh2THt3HjRtx+++3Sz2vWrMFjjz0mezsD9fTTT+Ppp5+Wfv7b3/7mV/UzYO8Y/uWXX0qJGMYYfv/9d7z55pt46623pIuN06ZNw//+9z+XarXIyMh+27PZbLjwwgtRW1sLwJ5YvOWWW6BQKFzGcRyH1atX45NPPpFue+mll1w6sTtTq9X49ttvXar+Wltb8cknn+DVV1/FZ599ho6ODnAch7vuugt33nmnNI7neYSHh/v1+xgMQRBw/fXXw2azISQkBC+//PKQbLfva8IFF1zg8zHOY7Zt2zbgfet0Oqxdu1b6exJFEbfccku/ikB3cQ7kNVDu69+WLVtcYpGT8J08eTK2b9/ukqg/dOgQ3n33Xbz22mvYvHkzrFYr9Ho93n77bZcLvu6O/b6xn3zyyT4vGjr/OxkMBhQXF/sd/2DIPaaUSqVLZelgjqm+Nm7ciDfeeAOA/Xzhxx9/xGmnnTagbcn9fDMUn4cIIeR4RglIMmz8qZYbyFhPDAaD9L2jesoX53F9K9gGsj1f2+xrOCuLhvp3Ghoa6tdj5PyuBiqQcaWkpKCoqAh33XWXy4m8IAgoLCzE888/jzPPPBPJycl47bXXhmSfxyt/jt+R+DuSe6wPxd+Gv5yrjBsbG/16TENDg8vPvj4wDuf+Q0ND+03JHk7OxwswNK/lw+mOO+7AjBkzANiT7W+//Xa/MSaTCU899ZT08+OPP+41Ea/T6fDggw9KP7/zzjuyLmh89dVXuOqqqyCKIgB7BdYLL7zg9+MH65VXXsG9994r/Xzfffe5/OyPM888E5WVlXjuueewYsUKJCQkQK1WIyYmBosWLcJzzz2HoqIiZGdnuywf4u5C2ccffyxNA09NTcVVV13ldd/Lli1zWdZj3bp1Hsfq9Xps2rQJ27dvx80334xZs2YhPDwcISEhmDp1Kq655hps374dzz77LKqqqqTHJSYmjsjr0AsvvCBNYb///vuRkpIyJNt1fl0B/Kvach7T3d096L/TCy64AMuXLwdg/xt78cUXfcY5kNdAua+/ztWYaWlpmDdvnqzHT58+Hfn5+di0aRMuuugiJCcnQ6vVIiwsDOnp6bjvvvuwd+9eXH755T6P/YH8OyUmJrokwRyJ++E22GNqKON0vjhvMBhw5MiRAW/reD4/IYSQQPA+55WQIOJ89dTXmnHuxvWdvjKQ7fnaZrBx/lDf29vr12Pk/K4GyvnfJhBxxcXF4dlnn8VTTz2FnTt34tdff8WWLVuwdetWqQKqrq4ON910E0pKSvD8888P2b6DzVj/O3L+wN/U1ASTyeRzbVbnREV0dPSgKqWd9+/vhyjn/aempg543wPRtwqmp6fHryRkoI4XnuexfPlyHDx4EACwdetWl8pDANi5cyc6OjoA2BO6ztPFPVm2bJn0vcFgwP79+30uNQDY189ctWqVVBVz3nnnuUxpHm7vvvuuyxppa9ascVmrTQ69Xo8777zTpXKwr+bmZpfj2t0SIM5rBPpax9hh2bJl0pR65zVsPVm4cKHPZT6c1wkdiaVKANelaT777DN88803Hsc6r6H31VdfuTyfTz/9VKr8B/q/LvhTJdh3THd396D/VlesWIEff/wRgP1vr6/4+HhERkZKf39Hjhzx+ZpmMplcKvflvAYajUaXqcBXX3213491xvM8Vq9e7XZNTWe+jqmB/Ds5xjmW5RmpCzqpqan4+uuvXWLwxXnMUMZ50UUXITQ0FC+//DIEQcDll18OAD7/PQghhPhGCUgyajh/SHf+AO2N8weXvouyO2/PaDSipaXFr4XbvW0z2DjHX1NT49djRuJq+UD+raurq4c8DpVKhRNPPBEnnngiAPtUmM2bN+PJJ5/EL7/8AgD497//jSuvvHLEPnAeb5z/raqrq8EY83mFXxRFl3+vYP47SklJAc/zEEVRWt/QV6LCeQ1Dx1TcgXJ+fENDAxoaGtxO/R2u/csVEREBlUolJdCqqqr8Wv4ikK+7zutxuVuv0fk1MSoqyq9kYN9qIHdr9Pa1detWnHfeeVLjjeXLl+ODDz7wub7yUPn4449xzTXXSJWXV155Jf7zn/8M6z6dG8WFh4e7TdI6//77/l498bU+8kA4xzoUTdHkck5G+tLS0uKylEHfdWH7NvbyJ/nTd4w/U0198fW3B9hfwxyNqQoKCnD66ad73abz659CoXBZ19uXTz/9VLoIqVAocMUVV/j9WLnq6+tRVlYm/ezumAoLC8OkSZOk8yR/k3TO44bi38kf7o4pd9PK+45xGMo4OY6TKmpffvll2Gw2XH755eA4zutap4QQQnyjKdhk1HDu6OzvWjDOV8z7ds2eMGGCywdff7bZ2trq0vnaVyfu411mZqb0fV5entTV0Rt/usEOlnNcu3btkj7werNjx45hjMhOpVLh9NNPx3fffefSBOiLL77oN3asTLPJyMiQ1lozGAwoKSnx+ZiioiKpok2hUPhsXHE802g0LgnHn3/+2edjHMlrwLUSbiBmzJjhMjVvpPcPyF+Ow/nv25/XXZvN5rJO30i/7tbX10vfu5uu6bxUQXt7u1+vo32TKb4+iOfl5eGss86S/m4WL16Mzz77bMSmz3/11Ve49NJLpYZTF154IdatWzfsr3POU94vu+yyfus6Aq6//7a2Nr+26/z79/W790deXh727dsHwP6adumllw56m4E0ZcoUlwYhpaWlPh/jPCY6OnpIlkXx9bcH2LtwO8h9/Vu8eLGsvyHn43HFihVSR+nh8N5770nnPqmpqR6nejumqQP+/TvV1ta6rGU7VOtn+9L3vUbuMTXUcTqSkDfffDMA+/vMZZddho8++mhI90MIIWMNJSDJqOF88lJQUOCzc67RaHTpxOjug7bzietbb73lM4b169dLJ4SJiYlDtt5SoCxevFhaC6eurs7nyXt1dTV+++23EYnL0VWysbHRa/dZACgvLx/SBcp9UavVLmuIuVt3ynka7mheRFyv17t8MPLn78h5zbX58+ePyLqiw+n888+Xvvf1/GtqaqQphX0fOxAcx+G8887ze//bt2/HgQMHANinAfbt3DsQco9159fi9evX+0zYff7551LCSKPRYNGiRQOMVD6LxYLvvvtO+tldxahzo6ze3l7s3LnT53Y3b94sfa9Sqbw22yopKcHpp58uJQ2ys7Px9ddfj9jfTd9p32eeeSY2bNjgNhk4lLZv3+4yZdORKOjL+XfnXIXojfPvf/r06QOM8BjnNT3PPffcEWnWBtj/3hljfn05Txe++uqrXe5zbvLk4Nwk5NNPP/UZi/OYk08+eXBP7KivvvpK+t5Ttbbza+gPP/zgczaH8xqOcl5/6+rq8MMPP0g/D3T6tT86OzulzuYAcMstt3gc69x9/Ndff/WZhHf+d4qOju5XmThckpOTkZOT4zYOd2w2G7788kvp5yVLlgx5TBzH4aWXXnJJQl566aWUhCSEkEGgBCQZNVJTU11Oav/4xz96/bD70EMPoampCYB96tZll13Wb4zzB5pPP/3UZS2pvqqrq/GXv/zF5bHBXuUWExPjkrxYu3YtLBaLx/H/93//J1XADKeoqCiXk+p77rnHY3dLxhjuuOMOv6qOfGlvb/er2hJwnRrubg0/5yl+I7XIe6A4/x395z//8dpVs6CgwKVTq7cPVsHi6quvlpJB+/fvx+uvv+5x7Nq1a6W/oUWLFg1JNd8tt9wiTfv99ttvPSbsRVHE2rVrpZ9Xr149qPUnHeQe6zfeeKMUb35+Pl599VWPYzs7O11ivvTSSwc1Fa+zs1PWa9hDDz2Euro66Wfn1yWHrKwsl9/Bww8/7PV1pKenx+W95IQTTvC4HtqBAwewYsUKKamQlpaGb7/9dsSmTW7bts1l2veSJUvw8ccfSxeIhktjYyOuuuoq6XX9+uuvd6mcdXbqqadK35eVleGdd97xuu3Nmze7/I34mrLryzPPPINvv/0WgL0a07k7eDBbs2aNdIEyLy/PZe3DvrZv3+6SUHLXGbqnp0c6jvzx0ksvucy4WLlypdtxubm50hIogiDgvvvu87jNV199VZrFEhYW5rNhkbN3331Xeu2IiIgY9MUjTwRBwDXXXCOdv6alpWHNmjUex59xxhnSNHKz2YyHHnrI49j29naXNVuvuuqqEVs/FrA39XJ4+eWXUVlZ6XHss88+KzUL0mg0uPjii4clJkcS8qabbgJwLAn58ccfD8v+CCFk1GOEDCEA0pcvP/30kzR2yZIlPsc/8sgj0vhHHnnE7Zht27YxhUIhjTv33HNZY2Ojyxiz2cweeOABl1ifeeYZj/s988wzpXF6vZ598MEH/cbk5+ezGTNmSOOSkpJYe3u72+1dffXV0rh169b5fN4OS5YskR73008/Dcm2161bJ42/+uqr3Y4pLi5mKpVKGnf22WezpqYmlzE9PT3slltuYQBYSEiIz20OhdLSUpd9rVixgtXX17uM6erqYldeeSUDwNRqtc+4fB2T69atY1OnTmVPP/00q6iocLsNo9HInnvuOcZxnLStrVu39hu3ceNG6f6MjAxmNpv9et7Jyck+/w7k8uc4cJD7d8uY/W8uIyNDetz48ePZ5s2b+4374YcfWHx8vDQuOzubWSwWt9v05+/B2XC+NvnjoYcekrap1WrZpk2bXO43m83s3nvvdYnz559/9rpNOceC4+8AAIuJien3OzMYDOyKK66QxqjVanbw4MGBPNV+HK8NANiaNWv8esyaNWukxyiVSvbCCy8wQRBcxpSXl7P58+dL48LDwz3+Xfrr008/ZSkpKezFF1/s9zrn7NChQy6/LwDsiiuu8Dj+sccecxm7cuVK1tDQ0G/cwYMH2QknnOAy9uuvv3a7zSNHjrCkpCRp3PTp01ldXZ38J92H83ttcnKyx3H5+fksIiJCGrtgwQLW3d096P0/99xz7NVXX3X7HiqKIvv666/ZlClTpP1OnjzZ4/stY4xZrVaWkpIijddoNOyll15iNput37Y3bdrk8pySkpKYyWRyu93m5mZ2/fXXs99//93t/S0tLezWW291+bf85z//6ffvoS/n7fjzmieX8/mDv+/dd9xxh/SY0NBQt+dHmzdvZrGxsdK4hQsXMlEU+40rKChgEyZMYE8//TSrqqryuM/6+np25513urzHnnTSSV7j/OGHH1x+f/fdd1+/95aNGzcyrVYrjXn00Uf9+h04zJ49W3rsTTfdJOuxDt9++y175JFHWGVlpdv7S0tL2dKlS6X9hISEsB07dvjc7qeffury/B944IF+5xwVFRUsNzdXGhMVFcVqa2tlP4fBHKeCILDs7GyX17TCwkKXMaIosn//+98u5/r33nuv7Dj78nUeJIoiu+mmm1zelz766CO326qsrPTrNdTfffc10M8RhBByPKAmNGRUWbRoEf72t7/hnnvuAWBfe2/SpElYunQpkpKS0N7ejp9//tllcfULLrgAd911l8dtrlu3DieccAIOHToEg8GA1atXY8aMGViwYAHUajX27duHHTt2SJUYOp0OGzZsGJJ1o44Hc+bMwRNPPCFVGX311VdITk7G0qVLMWHCBLS2tmLz5s3o6OhAZGQk7rrrLjzyyCMAMKxXzmfNmoWnn35aumL+/fffY/LkyVi2bBkmTpyI5uZmbN68GV1dXYiMjMQdd9yBRx99dND7raiowNq1a7F27VpMmjQJc+fORXx8PBhjaGhowI4dO9De3i6Nv/zyy90uDn/mmWciNDQUvb29KCoqwqxZs3DKKacgMjJSqpw97bTTcNpppw065kBTq9XYsGEDlixZgubmZjQ0NGDZsmXIyMiQqpYKCwtdlk2Ij4/Hhg0bpAqbYPfQQw9h69at2Lx5M4xGIy6++GL85S9/QXZ2NkwmE3799VeX9cweffTRIZ1S9sILLyA/Px979+5Fa2srli5dioULFyItLQ2dnZ3YvHmzy3H76quvDsnUU8BemeSoan3ppZeQn5+P7OxshIaGSmPWrFmDadOmST//4x//QF5eHnbt2gWbzYbbb78df/vb33DiiSdCr9fj0KFD+PXXX6WKI6VSiTfeeANTpkwZdLz79+/Hrbfeittvvx3Tp09HWloaoqOjoVKp0N7ejr1792Lv3r0ujznhhBOkpgXu3HPPPfjuu++wZcsWAPaGLV9++SVOOOEETJkyBaIoYv/+/di5c6dLBeatt96KM8880+02V61a5dKsadasWXjiiSf8eo5nnXUWzjrrLL/GenL66ae7NGiZNm2a1+oyZ1deeSUWLFjg9r6ysjK88soruO2225CRkYGUlBTodDq0tLTg999/d5lCm5ycjJ9++snr+61SqcT69euxbNky9Pb2wmQyYc2aNXjsscewePFixMbGorOzEzt27MDhw4elx4WEhOC9997zuAagzWbDG2+8gTfeeAMJCQnIycnB+PHjYbFYcPjwYWzbtg02m00a/8gjj7hUeHny+eef4+GHH/Y65oYbbuhXFXveeefhscce87n9ofTUU08hPz8fv/32G3p7e7F69WrMmjULubm5UCgUKC4uxu7du6XxCQkJ+OCDDzzODqmtrZXeXydPnoz09HTExsYiJCQEXV1dKCsrQ3FxscvfSEpKCjZt2uQ1zuXLl+PBBx+UKov/9re/4e2338bJJ5+MkJAQ7N69G3v27JHGr1ixAg888IDfv4fdu3e7vCYMdPp1W1sbHn30UTz66KNITU3FnDlzEB0djc7OTpSWlrrMHggJCcF///tfj39Hzs4//3zcc8890rTtv/71r3jjjTewZMkSREREoLKyEr/88os0a0ilUuG9997zuoblcBynPM/jo48+wqJFi9DY2Ijy8nJkZ2dj8eLFSElJgclkwpYtW1yajp1yyikuFePDheM4vPzyy2CM4bXXXoPNZsMll1yCTZs2ua18J4QQ4kGAE6BklMEwVhn5UwHp8Prrr7Pw8HCXePp+KRQKdscdd/SrgnCnoaGBLVu2zOv2cPRqradqCIdgq4B0+Otf/8qUSqXH556QkMC2bt3KXn31Vem2P/3pT34/v4F65plnXKob+36NGzeO/fbbb349V1/H5IcffuhSdeHti+d5duutt3qs4GOMsVdffZXxPO9xG+6O82CsgHTYv38/y8rK8vm7y87OZuXl5V63FWwVkIwx1tHRwVavXu31uatUKvbEE0/4tT25x0Jtba3P1zG9Xs/efPPNQT7T/vpWC/b9cvdv2N3d7fP35Xjt8VQlKNfXX3/t19+340utVrP777+f9fb2+tx2Z2cnu+qqq/zarkqlYo899li/qk9nzv/+cr+8HS/+VkAOdN+A9/enm2++2a9tXHzxxf2q3r3ZuXMnmzlzpl/bnjJlCtuyZYvX7dXX1/u1rfHjx7MNGzb4Hafz67Gcr8HOOBhIBSRj9te1Sy+91Gd8CxYs8FrZuGfPHq/vh32/eJ5nN954I2tra/MrTlEU2eOPP+4yo8Pd1yWXXMI6Ozv9fv6MMfbHP/5RevyMGTNkPdbZhg0b/HruOTk5LC8vT9a2RVFkTzzxhNfzJQAsMTHR7QyFvobzON23bx/Lycnxua1rrrmGGY1GWb8Hf56PtxhFUWQ33nijNFalUrFPPvnEZQxVQBJCiGdUAUlGpeuvvx5/+MMf8Nprr+Gbb77BgQMH0NbWhrCwMCQlJeHUU0/Fddddh7S0NL+2N27cOPz444/49ttvsXHjRmzZsgUNDQ2wWq2Ij49HVlYWzj//fFxxxRWjpmKrr/vvvx/nnHMOXnjhBfzwww+oq6tDaGgoJk+ejJUrV+Kmm25CbGysSxOakagCvfvuu3HGGWfghRdewHfffYfa2lqEhoYiOTkZF1xwAW6++WbEx8ejvLx80PtatWoV6uvr8d1332Hr1q0oKipCRUUFOjo6ANjXfZo5cyZOPPFEXHXVVT6PrxtvvBHp6el4+eWXsWPHDtTW1qK3t3dI1qs8Hs2cORN5eXn46KOP8PHHH+P333+X1rGKj4/HggULsGrVKqxcuTLo1091JyIiAps2bcKNN96I9evXY/v27aivr4dKpUJSUhJOP/10XH/99R6bKQxWYmIifvjhB3z66ad47733kJ+fj/r6euj1ekyaNAnnnnsurr/+eq8NTwbq7bffxtlnn4333nsPhYWFaGlp8bnem16vx6ZNm3DnnXfinXfewc8//4y6ujoYjUbExsYiPT0d55xzDq677roha7hy5plnorq6Gt999x127NiBkpISVFZWoqOjA4IgICwsDPHx8cjIyMCSJUtw8cUXu6zv6E14eDjWr1+PtWvXYv369di6dSvKy8vR0dEBnucRFRWFtLQ0nHLKKbjuuuuGtYPu8ezhhx/GggUL8OOPP6K4uBiNjY1ob29HVFQUJkyYgOXLl+Piiy/22PXXk/nz52Pv3r34/PPP8d///hd5eXmoq6uDwWCATqfDuHHjkJOTg/POOw+rVq3y+V4eHx+Pn376CZs3b8avv/6KqqoqNDU1gTGG8ePHIy0tDRdccAFWrVqF8PDwwfxKjmsRERF4//33ccstt+Dtt9/Gli1bUFtbC0EQMG7cOCxcuBCrV6/G+eef7/V1ffbs2WhoaMD333+Pbdu2obi4GBUVFWhtbYXVakVYWBhiYmIwZ84cnHDCCbj00ktlNfPhOA4PPvggVq5ciddffx3fffcdqqurYbVakZCQgEWLFuHqq692WTPUH1arFRs2bJB+HkzzmXPOOQeffvopfvzxR+zcuRP19fVobm6GVqtFQkIC5s+fj1WrVuHMM8+U3eSJ4zg88MADuOiii7Bu3Tp88803qK6uRnd3t/R7dbwHOHeOD4TU1FTs2LEDH374ITZu3Iji4mI0NDRArVZjwoQJWLp0Ka677jqXpjUjheM4vPLKKwCA1157DVarFRdffDE2bdrk0piJEEKIexwbrZ90CSEBcfnll+P9998HAGzYsAGXXHJJgCMihBBCCCGEEEJIIFECkhAyZHp6ejBx4kSpIrC8vNxlXTdCCCGEEEIIIYSMPcPXIYIQMuY8+OCDUvIxNzeXko+EEEIIIYQQQgihBCQhxLePPvoI99xzj8d1FFtaWnDrrbfin//8p3SboxM5IYQQQgghhBBCxjaagk0I8emtt97CtddeC8DeSGTOnDmIiYmB2WxGZWUldu7cCbPZLI2//PLL8e677wYqXEIIIYQQQgghhBxHqAs2IUSWAwcO4MCBA27vUygUuO222/Dss8/2u+/dd9/Fjh07BrXvGTNm4I477hjUNgghhBBCCCGEEDKyqAKSEOKTxWLB999/j//973/Iz89HY2MjWlpa0Nvbi6ioKEyePBmnnHIKrrvuOqSkpLjdxjXXXIP169cPKo4lS5bg559/HtQ2CCGEEEIIIYQQMrKoAnKUEEURdXV1CAsLA8dxgQ6HjEInnXQSTjrpJJ/jurq63N5utVoHHYMgCB63TwghhBBCCBlZjDF0d3cjMTERPD+6W0yYTCZYLJaA7FutVkOj0QRk34QMFaqAHCVqamqQlJQU6DAIIYQQQgghhIwx1dXVmDhxYqDDGDYmkwlTkvVoaBICsv/x48ejsrKSkpAkqFEF5CgRFhYGwP7CHx4eHuBogpvFYsELL7wAs9mMiy66CNOnTw90SCSI/PTTT9ixYwcmTZqEyy+/PNDhkCDS1taGV155BQBwww03IC4uLsARkWDBGMM777yD2tpaLF68GEuWLAl0SCSIbNmyBb/99hvGjRuHa6+9lmbSEL9VVlZi48aNUCqVuPXWW6HT6QId0qhm7XwRxt4XIMJePyRI3wECYxA9PI6DBvHj88Dz6mGJq6urC0lJSdLn0dHKYrGgoUnAkd2TER42spWeXd0iknMOw2KxUAKSBDVKQI4SjpPF8PBwSkAO0u+//w6O4zBhwgRkZWXRiTjxm8ViQVlZGTQaDZYuXUp/i0SWLVu2QKPRYPr06Zg2bVqgwyFBpKqqCq2trdDpdFi6dCn0en2gQyJBwmq1Yu/evdBoNFi+fDkiIiICHRIJIsXFxdBoNMjNzUVCQkKgwxn1rFBDreAhHE07iuAggIExBhu8fV6xgOdeRHj4w8Ma31j5zKQP46APG9nnKnr99yUkeIzuRRoIkYkxhp07dwIA5s+fP2beSMnQKCoqgslkQlRUFGbOnBnocEgQMRqNKCwsBAAsWrQosMGQoLNt2zYAwNy5cyn5SGQpLCxEb28vIiMjMXv27ECHQ4JIXV0dKioqwHEcFi9eHOhwxgReuxI8eCkVxR398lT56Mxo/GL4AiOEED9RApIQJ+Xl5Whra0NISAgyMzMDHQ4JIowx7NixAwCwYMGCUb8INxlaeXl5sFqtGDduHKZMmRLocEgQaWlpwf79+wGAkgBEFlEUsX37dgD2Cx/0vkXk2Lp1KwBgzpw5iIyMDGwwY4RClQwlQqWfOXDg4V8CUhCahy0uQgjxF03BJsSJo/oxKysLavXwrJNCRqeDBw9KyeusrKxAh0OCiCAI+P333wHYkwBUeU3kcCSQUlJSEBsbG+BoSDApLS1Fe3s7QkND6X2LyNLa2orS0lIAwAknnBDgaMYWjo8HJxrAcKyPLAfAV1dZjtMOa1xjicBECCPcxldg/qSZCTn+0aVOQo5qbm7GoUOHwHEc5s+fH+hwSJBxVD9mZ2dT8prIsmfPHhgMBuj1eqSnpwc6HBJEDAYDioqKANDUfSIPY0yaup+bmwuVShXgiEgwcVQ/zpw5E/Hx8QGOZuwQRRE28XCfWzm/VgfUas8bhogIIUQeqoAk5ChHBVJKSgqioqICHA0JJo2NjaisrKTkNZHNeer+/PnzoVAoAhwRCSa7du2CIAiYMGECJk2aFOhwSBA5fPgw6uvroVQq6X2LyNLd3Y3i4mIAVP040oSez1wqHwFABPNrGrZCOXXY4hprRDCn/uMjt09CRgOqgCQE9gYQjiqSBQsWBDgaEmwcCaRZs2bROkhElsOHD6OhoQEqlQrz5s0LdDgkiFitVuzatQuAfe1HmrpP5HBUP2ZlZSE0NNTHaEKO2bFjBwRBwKRJk+jCxwgTDPf2S0T5m5bq7XkDjKbxEkICjCogCQFQUFAgNYBITk4OdDgkiPT09KCkpAQAsHDhwgBHQ4KNI3mdmZkJrZbWZyL+KywshNFoRGRkJFJTUwMdDgkijY2NKC8vB8dxNHWfyGIymZCXlweAqh9HEmNmWAyfwMZMYIBUBen4r39NaGpgteRDHUIXOwdLhOjX73yo90nIaEAJSDLmiaIoTb+eP38+VZEQWfLy8iAIAhITEzFx4sRAh0OCSEtLCw4cOACAKq+JPKIoSslr6l5M5HJUP6alpdGSM0SWXbt2wWKxIC4uDjNmzAh0OKOeKDTD2r4GNkseBKcEVN+qR3+rIAWhachiI4SQgaAEJBnz9u/fj87OTmi1WsyZMyfQ4ZAgYrPZpEqAhQsXUvKayOJIIKWkpCAmJibA0ZBgsn//frS1tUGj0SAzMzPQ4ZAg0tnZiT179gCwT90nxF82mw07d+4EYK9+pHOe4WXpfBq2nhch9Jl07fyTKFVC+on+zQghAUYJSDLmOaofs7OzqQskkWXv3r0wGAwICwtDWlpaoMMhQaS3t1dad5am7hO5tm/fDgCYN28e1Gp1gKMhwWTHjh0QRRGTJ09GYmJioMMhQaSoqAg9PT0IDw9Henp6oMMZtayGN2DtegICBJeGM/3XfmQQAQjM/+YkCn7aUIU5pgmMyfq9D9U+CRkNKAFJxrTGxkYcPnwYHMchNzc30OGQIMIYkyoBcnNzqXsxkSUvLw82mw0JCQm07iyRpaamBtXV1VAoFNS9mMhiMpmQn58PgKofiTyiKEpT9xctWkTnPMNAsDXA0nwqGDPA1me9P3fJRxvsSTBZKwNy5sEHSgghg0AJSDKmOaofZ82ahYiIiABHQ4JJdXU16uvroVQqkZOTE+hwSBARBEHqXkxT94lcjurHOXPmICwsLMDRkGCSl5cHi8WC+Ph4TJ8+PdDhkCBSVlYmLfuQnZ0d6HBGFcYYzG03gll+hMhECH2SjZ6Sj0xu8hEAYBlUrMROBOv37zIS+yRkNKAEJBmzjEYjiouLAYCqSIhsjurHOXPmIDQ0NMDRkGCyZ88eGAwG6PV6zJ49O9DhkCDS3t6Offv2AaCp+0QeQRCk961FixbRhQ/iN8YYtm7dCsA+44OWfRg6jAkwNy4DY1UA0C/5yNwknRxjbLL3poBCMVl+kIQQMoSobSIZs/Lz82Gz2TBu3DhMmjQp0OGQINLR0SElAah7MZGDMSY1n5k/fz5NYyOy7Ny5E4wxTJ06FePGjQt0OCSIlJSUSGsWU8M9IseRI0dQV1cHpVJJ5zxDiIndsDWdJiUfRda/ntFdzRuD/VxCHg4a7blQKKjhHSEksKgCkoxJoihK3Yvnz59PlQBEll27doExhilTplASgMhy5MgRNDQ00NR9IpvJZEJBQQEAewUbIf5ijEnr9y1YsIAufBBZHNWPmZmZ0Ol0AY5mdGCiAULraohipXSbP1Ns3VVE+oPn4xER8fCAHkv6E8H6VauOxD4JGQ2oApKMSQcOHEBHRwe0Wi1VAhBZLBaLtIg/VQIQuRxTIDMyMmjqPpFl9+7dsFgsiIuLw7Rp1MmU+O/QoUNobm6GWq2mCx9ElsbGRpSXl4PjOLrwMUQYYxANz4HZDrgkFIczvRQaehkUivHDuAdCCPEPJSDJmORoPpOdnQ2VShXgaEgwKS4uhslkQlRUFGbMmBHocEgQaW9vR1lZGQBKXhN5BEGQ3rdo/T4il6P6MTs7GxqNJsDRkGDiaHqVlpaG6OjoAEcT3BhjEHvehdi4EGLPWxCcatrkTqmW+x7Q27sRzM0UbzIwjiY0I/1FyGhAU7DJmNPc3IzKykpwHId58+YFOhwSRBhjUhJg/vz54Hm6hkP856h+nD59OuLi4gIcDQkm+/btQ1dXF3Q6HVXtE1kaGhqkcx5qXETk6OzsRElJCQBg8eLFAY4m+LHO/wNMX8Bd72p/k0scODhqJY9955so1kMU22kNSEJIwFECkow5jgRSSkoKIiMjAxsMCSqVlZVobm6GSqVCZmZmoMMhQcRsNkvr91H1I5GDMSZVIeXm5kKppFM34j/HsTN79mxEREQEOBoSTHbu3AlRFDF58mQkJiYGOpygJpp+BUxfQDyafGR9VnOUU92mBAcbGBRw3wmbMXuKU3C6TQGgx/AWwsJvB8eFyH8CxIXAGATZjYAGv09CRgMq3yFjitlsRnFxMQD7BzlC5HBUsGVmZtI0NiJLQUEBLBYLYmNjaf0+Ikt1dbXUgZaq9okcnZ2d2LNnDwBqXETkMZlM2L17NwCqfhwKrPtZKfno4GsStaeGMxw4KGCfht33chRjDFa4Jh9x9Oe27n+gqfkPEMVe/wMnhJAhRglIMqYUFhZKSYApU6YEOhwSRNra2nDgwAEA9unXhPhLFEUpeb1w4UJav4/I4qhgmzt3LnWgJbJQBRsZqLy8PFgsFsTHx2P69OmBDieoMcvvYMIel9u4PulH3mc60hUPHkpw4Dl7MtLBXUWkM5OlCN3d/5C1L0IIGUqUgCRjBmMMu3btAmBPIFESgMjhmLo/ffp0xMbGBjgaEkwOHDiAjo4OaLVazJ07N9DhkCDS1tYmNS6i9fuIHGazGfn5+QCo+pHIY7PZpItm1PRqcETTTxDarnZ7n3MSUm4C0vF4xdEkpBL2zzm+JukyAAbDejBmlL0/cowYoC9CRgNKQJIxo6KiAq2trVCr1ZQEILJYLBYUFhYCoOpHIp/jg1x2djZUKlWAoyHBhBoXkYHKz8+H2WxGbGwsZsyYEehwSBApKSmBwWBAWFgYNb0aIGb+DWLzmRA7bgRg7Xc/x3HgnVKQHGdPJsrlWDuS4/rWVHp5DOuFzXZY9r4IIWQo0ErmZMxwVD9mZmYiJIQWYCb+KyoqgtlsRnR0NE1FIrI0NDTg8OHD4DiOktdEFpPJJF34oOpHIgct+0AGyrnp1YIFC6BQKHw8gjhjtnKw7n8C5u88ruHowHEcFIwHAyBChILjwTEGERwYHwsOHDjlZNgs293vCwwilHBMvOY4DvC7UQmlAAZDAIMgo3HQUO2TkNGAXn3ImNDR0SGt30fNZ4gcjDFp+jVN3SdyOZIAaWlpCA8PD3A0JJjk5+dLa7BNnTo10OGQIFJaWorOzk6EhobSjA8iS3l5OZqbm6FWq5GTkxPocIIGY1awjgcB86eyHueoXOQdKznykVBEvQZOnSWNsRi/hrHzfjCxzemRaig1F8Jmel+6xd9UsQAlTOY8KJVTwHGUCiCEjCx61SFjQl5eHhhjmDp1Kq3fR2SprKxES0sL1Go1MjMzAx0OCSI9PT0oKSkBYK8kIcRfoihKFz4WLFhAFz6I35wr2HJzc2nZByLLtm3bAAA5OTnQaDQBjiZ4sK4n+iUfOXA+qyBdxmuvBB/+//VLCqq1Z0GlWQGb+WeIQi04LhIqzakw9r4HmDjAaRq2kjGfjWgAAa0dd6PX9DXiY94Ex9FrBCFk5FACkox6NptNWoidqh+JXI4KtoyMDJq6T2TJy8uDIAhITEzExIkTAx0OCSL79u2jCjYyINXV1airq4NCoaBzHiJLXV0dDh8+DJ7n6aKZDExsB4zvu73P3yQkH/5X8KGrPd7PcSqoNCv63BYC9Nm2muMgMuajYYn9MUbTj+jqfgUR4bf7jI+4Epj9a6T3SchoQAlIMurt2bMHRqMRERERmDlzZqDDIUGkvb1dmrpP6/cROQRBQF5eHgCqYCPy7dixAwAwb948KJV0qkb856h+zMjIgE6nC3A0JJg4qh/T09MRERER4GiCB+vdOPAHqzKhiHgKnHJa/+0yBsGyCzbLboDjoFSfAKX6WFMgdchSAMcqIAF7FaQGgMAYLOibnuy3B3QZXkd42BpwHK31SQgZGXRWS0Y9R/OZnJwc8Dw1fif+cxw706ZNo6n7RJbS0lIYDAbo9XrMnj070OGQIFJTU4OamhqqYCOytbW1oaysDAA1LiLydHR0oLS0FACwaNGiAEcTZKyFHu9y9KbuVwXJRYMPvx+89gK3jxNslehpuwmirQz21R3trWoUqlzool8CrxgHhTIZas3ZsJi+BpxqHjmOg5LjIIiiz+nYgtgIQWyCUpHg61l6JIre6y1HIxHwUWU6PPskZDSgBCQZ1Wpra6WpSNnZ2YEOhwQRq9WKgoICAFT9SORzTN2fN28edRElsjiOnfT0dOj1+gBHQ4KJo3J2xowZiIuLC3A0JJjs2LFDWit9/PjxgQ4nuHDeX6e5o/87loRUgYv9EbwizO14UWiDoWWlU9MZQbpPsObD0HoJwuK+BsdpER75LDrbOmC1bIE9USkC4MGYDYzTAMzkO/xBpgO++uor1NfXD2obhJCxgxKQZFRzTIGcPXs2TUUispSUlMBkMiEyMhLTp08PdDgkiNTU1KC2thYKhYK6iBJZurq6pCokWoONyGE0GlFYWAiAqh+JPEajUVornaofB0B9EmD6wucwR79rLvI/4BRhEKx7Ye3dBFFoAMfHQKW9EAr1PFh63wUTW+G+5k2AaCuHxfg5QkIvBsfrEBGzEVbLNpiN/4UotkOhmAhOkQRLx4M+Y1IpU8DzA5/hYzAYUFRUhJ6engFvIxiJ4CBgZJfWEUd4f4QMF0pAklGrt7cXe/bsAUDNZ4g8jDGpA21ubi5N3SeyOI4dqmAjcu3atQuiKCI5ORkJCQOfEkfGnt27d8NqtWLcuHGYMmVKoMMhQcRx7MTHx2PatP5rERLvOO2ZYN2PAsxbEo4DQs4EQldDYALMrddCMP+IY1WLClh734MyZAVstoPwPuGWg7X3U4SEXmz/ieOgUEyCVncNeMVE8HwE2ttuP5rw9L4KZHjY7YNao3rnzp0QBAETJkwY8DYIIWMLJSDJqFVQUACbzYaEhAR6YySyVFVVobGxEUqlEllZWYEOhwSR7u5u7N27FwBN3SfyWK1W7N69GwBVsBF5BEGQLnwsXLiQml4RvzkfO4sWLaJjZwA4LgSI/CdY+y2wJw6dk34coEgGol6DtftZiG1XQWBWiNIYx/Rq+2qNNvOPEH1+PGcQj07PNpu+R0/X3yHY9h69T4kQ7Xmw2SrBcYCKAVYPW+EB6DysQekPi8Xi0myPEEL8QQlIMioxxqQPcvPmzaMTKiKLo/nM3LlzodVqAxwNCSZ5eXkQRRFJSUlITEwMdDgkiBQXF8NoNCIqKgozZ84MdDgkiJSWlqK7uxs6nQ7p6emBDocEkT179qC7uxt6vZ6OnUHgQpYAMZvADC8D5s0ARICLBEIvBbSXwNJ2BZhwBIzZnJKP7ogAzLCnBz1VQSqgUE6BqfdDdHfceXSsgw1m42ewHt0Fx3FQMebSNIU7+gieU4HnB75GdX5+PkwmE6KjozFjxowBbycYicz+NdL7JGQ0oAQkGZXKy8vR3t4OjUaDOXPmBDocEkS6u7uxb98+ADR1n8hjs9mkCx9U/UjkYIxJzWfmz59Pyz4QvzHGsH37dgD29yylkk7tiX+cj5358+fTsTNInGouuKgXwZjF3vyF0wNiKyyda8GESrjphe1+OwCY1ynYAlTa89HZcfvRn/uOFeBchclxHBSwT/YGAJExCABszIqq2lkICVmIcP2N0GoW+/U8AXvna0fTq0WLFtF7FiHEb/RqQUYlx5SAzMxMqFSqAEdDgsnu3bshiiImTZpEnSCJLKWlpejp6UFYWBhmzZoV6HBIEKmoqEBzczPUajUyMzMDHQ4JIlVVVaivr4dSqaSLZkSWyspKNDY2QqVSYd68eYEOZ9TgODXAhUEwPA9L02KI5p/hay3GvnjFVLj/mM5BpTkPgtgKMLPnGDzcLjAGm1M0IuuA0fQ9GltWoqPr337HV1pais7OToSGhiIjI8Pvx40WwtEmNCP9RchoQAlIMup0dHTgwIEDAEAnVEQWQRCkCjb6IEfkcqyjNW/ePCgUA5/WRMYeR/VjRkYGNBpNgKMhwcRRhTR37lyEhoYGOBoSTBzVj5mZmbTczBATel6HYHgex9Z4tPMnhcSBQ2jkPxCiuwHgjv1Nc1wkNGF3IzTqXxCEI/A2kdHdB3x2tPLRTbQAgI6uv8Jk3ukzPsYYtm3bBsBeOUuFHoQQOajWnow6jgTS1KlTERMTE+BoSDDZt28fDAYD9Ho9VbARWWpqalBbWwuFQoGcnJxAh0OCSGtrKw4ePAiAFvIn8rS3t6OsrAwANS4i8jQ3N6O8vBwAHTtDjTETBMMLbu/jOA4cc18PycDAwAFQwNC6GpxiHEJ0N0EZsggcFwaFaqa94Q0AnguHt07ZHBxTuY+tJek++eiMR1f3G9CEeH8fOnz4MFVdE0IGjCogyahis9mQn58PgKofiXyO5jM5OTlUwUZkcVQ/pqenQ6fTBTgaEkwc1Y8zZsygi2ZEFsexM23aNMTFxQU4GhJMHNWPqampiI6ODnA0o4to3g6w7n63M8YgMvdTsZm0PiSDvSO2DUyohdnwPIwd94NXJErJRwAI0Z4DbylFjlMgRJUDjeZsOOoufU8CF9Fr+g6MeU9VOqofs7KyxmzVNU3BJmTgKAE5wiwWC9544w2cccYZSEhIQEhICPR6PVJSUnDddddJU2nIwOzbtw+9vb0ICwtDSkpKoMMhQaShoQFVVVXgeZ4q2IgsBoMBe/fuBUDNZ4g8JpMJRUVFAKgKichjNptRUFAAgI4dIo/BYEBxcTEAewMRMsT6JB852JOPNogQPPTAtlcqukswiRCFIzB2PuRyq0I5BSHaizw8xl77GBp2K2y2g5C3/qQZ3T3very3qakJ5eXl4DiOXncIIQNCU7BHUHV1Nc4++2yUlJS43G6xWHDgwAEcOHAA69atw1133YVnnnkGHEdXOuRyNJ/JycmhjmxEFkf1Y2pqKsLCwgIcDQkmjsZFEydORGJiYqDDIUGksLAQFosFcXFxmDJlSqDDIUEkPz9fOnamTZsW6HBIEMnLy4MgCJgwYQKSkpICHc6owyn7vJYzwOZxujQHxsUDrMHLFgVYTV9BFJrAK+LttwgN0OquBmNmWExfwJ505AHYwHE6hEU+g57eT48mIB178i8V2WV4DeH6q93eR5WzdiLjILKR/Zw+0vsjZLhQAnKE2Gw2l+Tj3LlzcffddyMlJQXd3d3YsmULnnnmGfT09OC5555DQkIC7rnnngBHHVyamppQVVUFjuOQnZ0d6HBIEDGZTNLfJlWwETkEQZAufNCxQ+QQRVGauj9//ny66Ej8RscOGSir1SpdcF24cCEdO0OMMStE62GICAXQAwAQvazVCDAfyUcHEYJ1LwShBj1dT8Jq2Xb0dg4q9SIoVXPAcVoolFMRoj0LotgOU9vNcE45KuBt1chjbLZDEMVe8Lzr9Oru7m6pcnbx4sV+bIkQQvqjBOQI+eyzz6QEx6JFi/Dbb7+5rDG3YsUKnHfeeVi0aBGsViuefPJJ3HXXXVAq6Z/IX44kAFWwEbkKCwthtVoRFxeHSZMmBTocEkTKyspgMBig0+mQlpYW6HBIECkvL0d7ezs0Gg3mzp0b6HBIENm/fz86Ojqg1WqRkZER6HBIECkpKUFvby8iIiLoPWuIMbEL5rYrwazFcF7lTPBZd+hfbaLNVg5D1xNwTSMyWC07YbUWIir2UyhV6QAAi2Vzv23aG+Awv6ogOa7/58/ff/8doigiKSkJEydO9GMro1cg1mSkNSDJaEFzVEfI1q1bpe/vv/9+tw0ucnJycM455wBw7WxIfLNYLNI6WrR+H5GDMSYlr3Nzc6kagMjiqEKixkVELkcDkezsbKjV6gBHQ4KJ49jJycmBSqUKcDQkWDDGpLXm58+fT0sVDTFLx/+BWfce/cmfWkMH3ylBhlD09rwOe+OZvk1iBICZ0N3xgNNt7s9lff+LK6AJOREc5/qeZLFYpHNlqn4khAwGldeNEIvFIn0/depUj+Oc1/Exm83DGtNoUlJSAovFgujoaK+/X0L6qqysRGtrK9RqNVUhEVmcGxfNmzcv0OGQINLc3IyKigpwHIfc3NxAh0OCSH19PY4cOQKe5+nYIbIcOnQIzc3NUKvVtFTRADGxHcz4MUTzTgAMvHo+uNBVYKIBovkHuEsm+qpv5KAE+BgwsRnuE5cclJrTYTJ97GUrImzW3bBZD0KpmgG1Ohf2SdeuyUq+3y19CYgIu7XfrQUFBTCZTIiOjsbMmTO9boEQQryhS18jxPnFuqKiwuO4Q4cOAbCXyc+YMWPY4xoNnCvYcnJyqIKNyOJYCykjIwMhISEBjoYEE0f146xZs2jZByKLo4ItJSUFkZGRgQ2GBBXHsZOWlobw8PAAR0OCiaP6MSsrCxqNJsDRBB/RvB1C8xKI3U8Blp8Ay88QDX+H0HQyhN634SnNyPucOitAG/FnKNWOrtIKl/+qtOdDGeLfxQZBqLQ/UhEHrXYl+n7U5zgOrjXTjtgUADhERz4BrWapywhRFKVjZ+HChVQ5C0AAH5AvQkYDOpJHyKWXXiqdKD711FMQhP7XnwoKCvDVV18BAC655BI6sfRTbW0tGhoaoFAokJmZGehwSBDp7OzE/v37AYAqSYgsRqORGheRATGZTNJC/nTsEDkMBgP27NkDAFiwYEGAoyHBpKmpCYcOHQLHcXTsDAAT6iC23wAwI1wTjQyAGaznHY+P5cB5SUHaqxtVmrOgi9kAXfS7UGn/AKX6JKhDL4I+9r8IjfwXeD7Krzg57thnx4jIJ6BSO5al4qX/chyHUFUWoiOfhFZzGjQhSxCuvxkTxm9FuP66ftssKyuT1pylz1mEkMGiKdgjJC4uDm+99RYuv/xybN26Fbm5ubjzzjsxc+ZMGAwGbN26Fc888wwsFgsyMzPx7LPPBjrkoLF7924AwOzZsxEaGupjNCHH5OfngzGGyZMnIy4uLtDhkCBSUFAAm82GcePGISkpKdDhkCBSUFAAq9WK+Ph4TJ48OdDhkCCSl5cHQRAwceLEMd8EgsjjqGBLTU1FVJR/ySxyjNj7PgAr3Fc5MnBe1nzkOA4KxkMEB5HTAKzn6B3hUOuuRUjYn8Bx9gShSrMEKs2SfttQhywFOO3RBKiH/fBxUKmPLQfD8zrExGyA0fgVTMZPIQh1UCgSEBp6CTTas8BxKoTrr/H53Ldv3w4AmDdvHq05exRjHEQ2sjPu2Ajvj5DhQgnIEXTBBRcgLy8Pzz77LN58801cffXVLvePGzcOjz76KG666SbodDqv2zKbzS5rRHZ1dQ1LzMc7o9EoVQPQGmxEDkEQkJ+fD4COHSIPNS4iAyWKorTsw/z58+nYIX6z2WzS6w5VsBE5enp6pKrrhQsX+hhN3GHmH+GtsQzHMXBMAwYr3K2yyHFKqLXnQxXxF4jW/QA48KqZ4Dj/psJzvA6h+j+ht/spj2N0YWul7tUWcx66Df+G2WRfl5LnE6DTXwe9/nqXfTImwmj6Dl2Gt2G1HQDPR0CvvQB63WVQKKJRXV2NmpoaKBQKqtgnhAwJmoI9gqxWK95//3188cUXYKz/FbTGxkZs2LABP//8s89tPfnkk4iIiJC+xmoFTnFxMWw2G+Lj46kagMhSVlYGg8EAvV6P1NTUQIdDgkh5eTna29uh0WgwZ86cQIdDgojzsUNNr4gce/fuRU9PD8LCwjBr1qxAh0OCiKNyNjExccx+Xhg0Zm8myhhz+xkOABSKGEAxHq4frzkAHDjlLKjCHwbHaaBQZ0Chnut38tEhVP9HhOrvhGO9RnsdEQdADV34I9DqLgMAGI1foKXlfJhNm+Go2BTFenR3PYnWlsvAmOnoc7GhuW0Nmlqvhcn8KwShFlZrKdq7nkRt4ymwWsulytk5c+ZAr9fLipcQQtyhBOQI6enpwamnnoonnngCra2tWLt2Lfbt2wez2YzOzk589913OPHEE7Fr1y6ce+65+Ne//uV1e/fffz86Ozulr+rq6hF6JscPaj5DBsNx7GRnZ0OhUPgYTcgxjgq2zMxMqNXqAEdDgomjgUhWVhZNZSN+Y4xJx05ubi69ZxG/OVfOLly4cEyfKzNmAjN+CWZ4Faz3QzCxo/8YoRai6WuIpm/BxNajjxPBuGgITIQIBhEMAhP7JCIV4NXzoYn9Csqwe8AppgBcBDhlKlThjyEk9kNw/ODW9uc4DrrwexAzLh/68McQqr8N+ognETO+AKH6mwAAotiB9rY7YE889q3EFGGx/A6D4RUAQFf3y+g1fnH0PsFlnCi2obzyFuzbtw8AVc72JYALyBchowFNwR4hjzzyCH799VcAwBtvvOEy/VqtVmPFihVYunQpTjvtNPz000+4++67sXTpUo8VEiEhIWO+Y29VVRVaWlqgUqmokoTI0tzcjMOHD4PjOOTk5Ph+ACFHtbW14eDBgwCocRGRp6WlBRUVFQDo2CHyVFdXo76+Hkqlkt6ziCx79+6FwWBAWFgY0tLSAh1OwDDjf8G6HgOYAfYKQgHo+jOgvwXQ3Q6IbRC6HgDMx6oGASWguRAiM4NZd/fbpggGjgE8xwEQwIdeAY6PgEp/C1T6W4btufCKWGjdNIsBgN7ejwCY4akjNyCix7AOOt0adBle8zJOQElxBBhjmDZtGsaNGzf4wAkhBFQBOSIYY1i3bh0AYObMmf3WfnRQKpV4/PHHAdjXiXI8hrjnaD6Tnp4OjUbeNAYytjmqAVJSUqjbPJHFcexMnz4d0dHRAY6GBJPff/8dgP11h5pAEDkc1Y9z5syhZnvEb4wxaQrt/Pnzx2zlLDN9C9a59mjyEThW7WcFM/wbzPAchLZLAPPPcE3I2cCMH4CZPvW8bdinZPP6u8Cps4fnCchgs5bC18d7UWyC1bYXgtjkcYzFrMbBA/bliRYtWjSUIY4KAuMD8kXIaEAVkCOgsbERbW1tAOzTrrxxvrJdVlY2rHEFs97eXpSWlgKgBiJEHovFgqKiIgB07BB5rFYrCgoKAFAFG5HHbDZLrzu0kD+Ro7OzU5oGSc1niBxVVVVoaGgY05WzjDGw7n94H9PzCuwNZvpXA4peGs9IQpaD1982sACHGqcB/Jqq630W3YEDs2CzqhETw2Hq1KlDEhohhABUATkilMpjeV6bzeZ1rNVqdfs44qqwsBCCICAhIQGJiYmBDocEkT179sBsNiMqKopOqogse/bsgclkQmRkJKZPnx7ocEgQKSoqgsViQWxsLKZMmRLocEgQycvLA2MMkydPpmmQRBZH9WNGRga0Wm2AowkQ2z5AOOJ1CIMAz1ORfWNi+4AfO9Q0mtMAePusqYBafQLUqhQoePevJ6LIY9/edADA7LkNaGq/Gx2GdRDErqEPOEiJ4CCCH+EvWgOSjA6UgBwB0dHR0jTP7du3e01C/vLLL9L39CHFPcYY8vPzAWDMXtElA0eNi8hAMMak5jM5OTngeXr7JP5hjEnTr3Nzc+l1h/jNarVKy81Q5SyRo729XZpJNaYrZ8XOYd4Bd7Tq8PgQEnIylKrZsK9z6Y6IsLA/guMUCA+7Ce6qJQ9XTkFvTxg0ml4kTPoGXb0fo7njQVTWZ8Fg/G44wyeEjAH0CWoE8DyPs88+GwBQV1eHJ554wu249vZ23HvvvdLP55xzzojEF2yOHDmC1tZWqNVqpKenBzocEkTq6upQX18PhULhczkEQpw5HzvZ2YFf54kEj8rKSuk9KyMjI9DhkCCyZ88eGI1GREREICUlJdDhkCDiuOgxbdo0xMXFBTiaAFJMGNTD/blcpNCsGNQ+hhLH8YiJeQ9KpeP1Qgn7x30egBKRkf9AiOZkAEC4/mbotOcfHWdPWIoM2LvH/j41I20vFEoz7BWVDIyZUN96A8yWPSP2fAghow/N8R0hDz/8MD777DP09vbiz3/+M3bv3o2rr74aU6dOhclkwo4dO/DPf/4TVVVVAIDly5fjtNNOC3DUxyfn5jNjvRM4kcdRwZaWlkYL+RNZHMfO7Nmz6dghsjgSAZmZmfSeRfzGGJOaz+Tm5lLVNfGb2WyWZgotXLgwwNEEFqecBAYVAKvnMeDAPEzBPnYfh/7TtBUAHwlee4FfsQi2Clh6PwITm8DxcVCHroJCOc2vx8qhUMQjLv5bmM0/w2T8HxgzQqlKQWjoJVAojiWjOU6B2Oj/QGdaie6et2G1HkB9QwTaWuLBK2yYkVraZ8sMAEN798sYH/PCkMcdTARwEEZ4SvRI74+Q4UIJyBGSmpqKzz77DJdeeilaWlrwxRdf4IsvvnA7dtmyZfjwww9HOMLg0NPTIy3GTg1EiBwmkwl79tiv2tKxQ+To7e2Vjh1qPkPk6OjowP79+wHQsUPkOXLkCBobG6FUKqnqmshSWFgorTk7bdrQJ7iCjmISIBzyMoADoIa90k9wvYdTgFfOgGg7DDDT0bGcfRwfC1X0W+D4MK+7Z0yEsfMRWHrfgvPUaLPhBahDr4I24jFw3NB2KOc4BTSa5dBolvsYxyFUuxyhWvu4H3+4DwAwZdpBaLQmN48QYDB+PaSxEkLGFkpAjqBTTz0VZWVleOONN/DNN99g79696OjogFKpxPjx45Gbm4vLLrsM5513Hq0R5UFRUREEQUBiYiISEhICHQ4JIkVFRbDZbIiPj0dSUlKgwyFBxNH0avz48ZgwYXDTucjY4qicnTp1KmJjYwMcDQkmjsrZuXPnjt0GIkQ2URSlytn58+fT5wkAXOilYN1PwLmCkYGBO1pRxgHg9HdBtO4EzD87jVOC05wPRcQjALNCMH4CZikAOCV49UngtWeC43xXtZsN/zqafAT6JjgtvW+D4yOhDb9nkM9y8Nrb23Gk0r6eZUp6icdxDGYwxsb0sSUwHgIb2ap0gQ28URIhxxNKQI6wmJgYrF27FmvXrg10KEHHufkMVQMQORhj0tR9aj5D5GCMSY2LqIEIkcNqtaKgoAAANRAh8nR2dkoNROjYIXIcPHgQ7e3t0Gg0tOasg/ZCoPctMKEOzKlDtD0JyQP8JPChl0HJ3wBmqwazFgOcApwqF5wixj6Y00KpuwbQXSNr10zshcnwstcx5p7XoNGvAcfrZT6xwWOMwWjajO6edfjtF4CxGRg/oRqRUZ46e3NQK2fQuRAhZMBoQRkSNKj5DBmoqqoqNDc3Q6VSYe7cuYEOhwSRQ4cOob29HSEhIfS6Q2TZu3ev1EBkxowZgQ6HBJG8vDwwxjB58mSMGzcu0OGQIOKonM3OzoZarQ5wNMcHjtcD+nvB+lQfAgCDCMaHA5z9IzGnTAKvPRu85oxjyUc3GGMQbYchWEvBxG6P42yWbQDr9R4gM8Jm3urfkxlCjDG0dtyPptYr0Nm1FQf2JwMAUr1UPwJAhP66kQiPEDJKUQUkCRqO6kdqPkPkcm5cpNFoAhwNCSaO6seMjAz6MEdkcUy/njdvHjUQIX6z2WzS+Q5VPxI5mpqaUFFRAY7jaM1ZJ4xZIHY9BPeNZADY9kA0vABF2P/5tT2r8XOYu5+DaHOsK6mGSnsBQsLvA98nacmY0c8Y/Rs3lHp6P4ShZz0AoPzADFitakREtGPChCowtw1POIRqliJCd+nIBnocEsFBHOGmMCO9P0KGC50Rk6DQ29uL0lJ7N7acnJwAR0OCifOxQ81niBydnZ04cOAAAGogQuSpra1FXV0dFAoFsrKyAh0OCSJ79uxBb28vIiIikJKSEuhwSBBxrP2YmpqKyMjIwAZzHGGm7wHWBkD0MEIE630fjFl8bstseBPG9tsh2iqcbrXAavwIPS1/gCi6Tl1WKGf6FaNCdexvnTEGm7UMFvMW2GzemucMTmf3KwB4iCKHfaVzAACz0ouh5AAFGDinZK1SMQGxEQ8hMWYdOE41bDERQkY/qoAkQcHRfGb8+PFITEwMdDgkiDgaiCQkJNCxQ2TZvXu3NA2SGogQORzVj+np6dDpdAGOhgQLxpiURKLKWSKH0WhEcXExAGDBggUBjub4wmx7YP/Ia/MyqAsQ6gDlZI9DRKEJ5q7HHQ/oc68AJtTC0v1vaCIelm5VqFKgUOVAsBaibwOaoyOgUM2BQjULAGAx/QJD12MQbGXSCKUqE/qIR6FSD91FdJEZYbXZL85XV02GoTscISEmTJt+EIC9QomHAqHa8xAT9SR4LpzWfXQigocwwnVcorvqXUKCEJ3ZkOMeNZ8hA9W3+Qwh/hIEQXrdocpZIkdvby/27NkDgCpniTw1NTVoaGiAUqmk8x0iS35+Pmw2G8aPH49JkyYFOpwhwxgDE2rBbIf9qlB0TwW3U6/74rwvs2Lt/djHdgRYejeAMavLraGR/wDH6QEo+oxXgON0CI18BgBgNn2PzrYrINj2u4yyWYvR0bIKVvMu38/Bb8eSifv22tdGn5laCqXSNUnLcSoo+AhKPhJChgwlIMlxr7q6Gi0tLdRAhMh2+PBhtLW1Qa1WY86cOYEOhwSRsrIy9PT0QK/XIzU1NdDhkCBSUFAAQRCQmJiICRMmBDocEkQcDUTS09MRGhoa4GhIsBBFUaq6nj9//qhJFjHjZ2AtZ4I1LwVrOQ2saRHE7r/LXi+RDzkF7qsPHThAMQ3gE7xuRxQOw+dHZ9YDJna43KRQTYc+7muotBcBcCQ5VVBpV0Ef9zUUqplgTICh4z7YE5x9k5wiAAHdnfeDsaGpguM5DdSqLLS2xKGxIREcJyBl1t4+owRoQ0449tSYBVZbFWxC05DEQAgZm2gKNjnuOaqQZs+eTc1niCyO6sc5c+ZQAxEii6P5TFZWFhSKvlULhLgniqJ07FDlLJGju7tbWq+Yms8QOfbv34/Ozk5otVqkp6cHOpwhwQz/ATP8C86VemDdQM/rYJZdQPTbALOA9b4NsXcTIDYBXAS40JXgQ68Fp4g/9jhVFqDKBKwlcJ+IZOD1t/hM3HJcOHxXUnLguP7LbiiUk6CL+jtY5BNgYjc4PgycU8Wl1bwVotjgZbsiBNs+CLZSKFWzfcTgn4iwW7H5h/cBAJOnVkCn63GOGDwfhdDQ8yCKPWjreg6dPe9CZF0AgBDVHESH3wm99swhiSXYCIyHwEa2jksYouQzIYFGFZDkuGYymbB3r/2KHE1HInL09PRg3759ACgRQORpaWnB4cOHwXEcTd0nspSXl6OjowMajWbUJALIyNi9ezdEUURSUhISErxXYhHizLFuaE5ODlSq4G8QwmwVR5OPQP+EHwOshRC7/wOh9UKIhucBsR6AALA2sJ43IbSeC2Y7LD2C4zgoIl8GlDOO3qJw+S+v/xN47QU+41Jpz4X3SkoFlCHLwfGeq5c5Tg1eEeOSfAQAQajxuX/7uFq/xvmDiaegssLe/GbWbOfqRx48F4Zxse8DTERN80q0G16Wko8AYLbuRX3r9egwvDFk8RBCxgZKQJLjWklJCWw2G+Li4jBx4sRAh0OCSGFhIURRxIQJEzB+/PhAh0OCiKOCbcaMGYiIiAhwNCSYOKZBZmVljYpEABkZgiBIFfu0biiRo6GhAUeOHAHHcaPm2GG9H6L/eol9x7wCCNXo39laAMQOCB13udzKKWKhiPkv+MiXwGnOBtRLwYVeDUXst+D1f/IrLoV6LpQhp8L9x2ceAIeQsDv82la/R/PRfo6LGtD23dm1axdEEZgwIQqTk0+GSpkKtSoLUREPYML4LQhRz0G74RWYrXvQ//ds/7m54xHYhPohiylYiOAD8nU8qaqqwksvvYSLL74YKSkp0Ol00Gg0mDhxIv7whz9gw4YNsNm8NH7qY+/evbjlllswffp0aLVaxMXF4eSTT8Yrr7wiazsbN27E6aefjoSEBGg0GkyePBlXXnklduzYMZCnSYYBTcEmx62+zWdGy5o2ZPhR4yIyUFarFUVFRQCocpbI09bWhvLycgB07BB59u3bB4PBAL1ej7S0tECHQ4KIY93QtLQ0hIeHBziaISIchrdKQ+Z2nUSXDQC2EjDrHnCqY5XoHKcEp1kBaFa4bo/ZIJp+gM34CZjYBE6RCKV2NfiQk8FxrkkfbdQLMHbcDZvpazh6RQM2cFwEtFHPQ6HOkPlk7dSaJeC4MDDW7XEMzydCqRqaWRk2m0266LFo0XLERfdPwjLG0GlYj/7JR1edPRuhwvVDEhcJDg8//DD+8pe/uF2TtLa2FrW1tfj888/x7LPP4uOPP/bZGOuNN97AbbfdBrPZLN1mMpnw22+/4bfffsNbb72FL7/8EjExMR63YTKZcNFFF+HLL790uf3IkSM4cuQI3n//ffz5z3/GQw89JPPZkqF2fKXSCXFSX1+PhoYGKBQKaj5DZHFuPkPTIIkce/fuhclkQmRkJKZPnx7ocEgQcXyYmzZtGqKj/atmIQQ4VjmbnZ1Na84Sv/X29qKkpATAKFs3lNPBZe3HAWLWPb7HiAaYWy+FpWMNRPOPYNYiiKbvYGm/Fpb2G8CY2WU8x4ciNPpl6OJ/RkjYvVDrb4M26j/Qj98FpWbJgGPlOC104fd6HaOLeLBfQnSg9uzZg56eHoSHh3tstMeYEYLou+GM1Vo+JDEFE4FxAfk6XtTV1YExBp1OhyuuuALr1q3Dli1bkJeXh3feeUeqxs7Ly8Opp54Kg8HgcVvffvstbrrpJpjNZowbNw7PP/88du7ciW+++QYXXnghAGDHjh248MILIYqek+HXX3+9lHxcunQp/vvf/+L333/HG2+8gWnTpkEURTz88MN4/fXXh/A3QQaCKiDJcaugoAAAMGvWLOoGSWRxJALmzp1LzWeILI7p1zk5OVR1Tfxms9mk96zRMg2SjIyGhgZUVVWB53mqnCWy5Ofnw2azISEhAUlJSYEOZ8hwmjPATJ8PwZZ8L4Nh6XwAzJp/9CdHcsNefSmaf4G16ymoIx7u9ziFcioUYWs8blcUO2E1fglRqAeviIVKcw54RayHsQZYTF9DELqg1v4BFtN3ADPCXickguMioI/4MzTaP/h8Pv5gjEnrhubm5nq86GFfp1IB52pUxo716WZHIwRHDULHmpiYGDz11FNYs2YNwsLCXO7LycnBpZdeissuuwwffPABDh48iOeee85t5aHNZsPtt98OURQRHh6OrVu3Ytq0adL9Z5xxBm677Ta8+OKL+PXXX/Huu+/iqquu6redX375Be+/b2+odO655+LTTz+Vjuvc3Fycd955yMnJQVVVFdauXYtVq1YhMjJyCH8jRA6qgCTHJavVKl3VzcrKCnA0JJg4N5+h6ddEjoaGBtTW1oLneWRmZgY6HBJE9u7dC6PRiIiICMyYMcP3Awg5ylH9mJqa2u+DHCGeiKIoXTCbP3/+6LpgFnIKwEUOciM8uJATvI5gQj1E05fwPMVYhND7PpjY5eF+98yGN9DVkA1j5/0wG/4DY+fD6GqcB2PX3/tNWTX2vIXWxkx0d9wFo+FZWIyfA0xAiOYP0IU/jPCoVxAzPh+a0NWyYvCmqqoKDQ0NUCqVXhvtcZwSOs3pcKzHyRhgAyCAgwh7AlKAiPbez2Aw/jZk8ZHj31NPPYW1a9d6fM9SKBR48cUXpSKQjz76yO24Tz/9VFq65v7773dJPjr8/e9/R1RUlPS9O08//bTLfvsm1WNjY/HUU08BANrb2/HGG9Q8KZAoAUmOS6WlpTCbzYiMjMSUKVMCHQ4JIkVFRRBFEYmJidRJlMji+DA3a9Ys6PX6AEdDgonj2MnOzgbP06kV8Y/JZJIutlLlLJFj//796OzsRGho6KhbaobjlEDEXzzfDw7eP8Ly4DTnglN4b0AomLfD+1qSAGCGaCnwMcZpdM9GGLv+DMBydNs2OFJ1ZsPzMBv+LY019W6CofP/O1rtCKexFphNnwFgCNGeA47TSI9hzIze3k/Q3nYH2ttug8HwOkSxw+/4gGNd0+fOnQutVut1bHT4nwBwYIyDaxsQTvpizIzaVs/VoKORAD4gX8EkJiZGWkLt0KFDbsf897//lb6/5ppr3I4JDQ3F6tX2BPyePXtw8OBBl/sNBgN+/PFHAMCKFSs8Nq298MILpXVyP/nkE7+fBxl6wXUkkzHD0UAkKytrdF3VJcOKMSZNv6bqRyKHxWKREgHeKgII6auhoQE1NTXgeZ5ed4gshYWFsFqtiI+PR3JycqDDIUHE0XwmOzsbSuXoW1GLC1kBKOfA00dVDgDUJx79SeH6X/VC8OGP+7EX781VjvGvAy9jNpi63VdoOZgML4CJPWDMBkPXk17H9nY/AyYlJwGr9QAaGxaho/12GI2fwGj8DF2dj6CxIQcm049+xdjR0YGysjIAwIIFC3yO16jnIjHmraPTrB1Jx74YmN+/SzKWOJrKeLow+9tv9srZlJQUjB/v+YLBkiXH1lfdsmWLy32///67tB/ncX2p1WosXLhQeozVavXjGZDhQAlIctxpbW1FVVUVOI6jaZBEliNHjlDzGTIgJSUlsFgsiI6OxuTJkwMdDgkijim0VDlL5GCMScdObm4uXWwlfmtqasLhw4fBcdyoXTeU4zhw0a8BSse5nPLoFwdADT7iGSii1kER/SE47SpAfRI4zXngo96CIuotcLzvteN5tT9LPPHgVXP8ilmw7Abz1bSFGWE1/wSrZReY2Ox9KDPAYvoVgH2dyNaW1RClxwjA0YnQjJnQ1nodrNYynzHu2rULjDFMmTIF8fHxvp8UAJ12GbQhS+G9MZDnruWjkcj4gHwFk6amJmlJLHeNjgwGA2pqajze78z5fsc23f3s73ZsNlu/SkoyckbfJTMS9BzVj9OnT5dKpQnxh+PYSU9PR0gILYpN/OeonKXmM0QOmkJLBqqiogJtbW0ICQmRpqkR4g9H9WNqaioiIiICHM3w4fhoIOZDwLITzPwDwIzglDMB7R/A8ZH2QeosKPxKJPbHK6eBVy+CaPkd7hNoCvCaM8Ep4iGK7RCtB8FxIeBVs+3TxPtgzL+1IpnYjWNVmz7Gsg4AgNH4CUSPyU0GQITB8Dqiov7hcVsWi0U6T/an+tGZKE0pJ8Q/f//732Gz2auHHVOondXU1EhronqaNu3g3GSrurra5T7nn+VuJy0tzet4MjwoAUmOK4IgoKioCABNoSXyGI1GlJaWAqAptESeuro61NfXQ6FQUNU1kaW4uBhWqxVxcXGYNGlSoMMhQcRR/ZiRkSEt1E+ILyaTCcXFxQDszWdGO47jgJCF4EIWDsv21ZHPwtS6ChDqcWxKtv0iJKecBmXYXehtvxM24+dwTMXm+Fio9bdBrbvO5YIlr5js1z55ZTI43r8CC15hf18xGb89GpenJKAAk/FrwEsCsri4GCaTCVFRUbKbpWlUqegx/QLPlY504XakdHW5JrpDQkKOu6KLnTt34p///CcAe1Lw1ltv7Temu7tb+t7X7BGdTid9bzAYhmU7ZOQEVy0vGfUOHjyInp4e6HQ66iRKZCkqKoIgCBg/fjw1nyGyOBqIpKWlITTU97QtQgD7FFrHsUOVs0SOjo4OHDhwAABVzhJ5aN3QocUpxkMT+xWUYf8HTjEZ4PTglNOgCn8Q6qh16G29FjbjZ3BeB5KJLTB3PQpz1xMu21KoZkChyobnj9c8eEUSlOqFUChnQ6FM8zlWpV4Axsyw2Q7CdwWixeM9jDGpcnb+/Pmym6VF6S6D/2tmjn6BbEKTlJSEiIgI6evJJ72vJTrSGhsbsWrVKthsNnAch/Xr17s9tzaZTNL3vi7COSdYjUajy31DtR0ycigBSY4rBQX2TnMZGRlQKPybnkAIY0w6dqhxEZHDbDZjz549AKhylshTXV2N5uZmqFQqZGRkBDocEkR2794trcMWGxsb6HBIkKB1Q70TLQWwtt8Fc9MSWJqWw9b1VzBblc/HcXwEVPo10MT/BO34EmjivodSdx0sve+DCUfgqerP0vMqBKvrOnLayL8CnAb9p1jzABTQRv4DHMeD4ziERT4F+2TEvh/HeQAcwiL/DsCG1pYrIAg1Pp4FD6XK83TSyspK6f1qIDM91KopGBf5kFN8zjiEak6SvU0yMNXV1ejs7JS+7r//fo9jHUnAwX699dZbfsXW3d2Ns88+W1rb8a9//SuWLVvmdqxGc6y7u8XiOXkOHGtmA6Bf5/ah2g4ZOZSAJMeV008/HSeeeCKysga2ngsZm2pra9HU1ASlUklraRFZSkpKYLVaERsbS1NoiSyO6sf09HSXE2BCvLHZbNIFM6p+JHKUl5ePqXVDGWNgzL+qO5vhJVhbV0I0fQkI1WBCJYSedbA0nwbR/OuA9m/tfQ/eq/4UsPZucrlFqZqNsNjPoAw5Bc7TkhXqBdDHfgRVyGLpNpU6G5Gx/4VKvbDPNrIREfMh1CEnobfnPVgs2/yIVoROd63Hex3Vj5mZmQN+v4oJuxlJsW9Cq848FqsiAfERDyIp5sUBbTNYiQAExo3ol+NIDA8Pd/k6XqZfm0wm/OEPf5DWVL/77rtx3333eRwfFhYmfe9rOnRPT4/0fd9p1kO1HTJyaA1IclyJjo7G8uXLAx0GCTKON7vZs2dTIoD4jTEmHTvZ2dlUTUL81tPTI605O1q79/pfzwABAABJREFU0JLhsW/fPvT09CAsLAwpKSmBDocEEUf1Y2Zm5qheN5RZ8iH0vA6YfwJgA5QzwIdeBU57ETiu/+wo0fwbhO6/H/3JuVrR3ina2nYz1PG/gVP4X23MmAVMbPUxSoQoVPe7VaFKhT7mLYhCM0SxCTwfDV7hfmkglToDkbEfQrDVQhTrwfPxUCiPXQzt6XnLr3i12lXQav/g9r729nbs378fwODXDQ3Tno4w7ekQxG4wZgWgRLfpZ7R1fDyo7ZLhoVQq+3WNHghfS1vZbDasXr0aP/30EwDghhtuwDPPPOP1Mc4NYxwVk544N5pxbiTjbjvezsm8bYeMHEpAEkKCmtlsxt69ewGAKmeJLHV1dWhoaIBCoaAptESWwsJCCIKAxMREJCYmBjocEkQcSaScnBzZ67CRsautrQ0HD9qn+47mylnR+AXEzv8He/Xg0WSi7SDErgfBmbeAj/xXvySkredN2Kc8u5sqzQBYIRg/gFLfvxGGZyr7VGpm8jJGAY6P8ngvr4gDr4jza28K5QQoMKHf7TZbBXyt/ahUpiIy6p/gOPevJ47qx2nTpg3Zkg88p0dT93/Q2PUvMGaCoXtsrQ8pgoc4whNJB7q/1NTUIY7ElSiKuPLKK/HFF18AAC6++GK88sorPh+n1+uRlJSE6upqlJWVeR3rfP+sWbNc7nPuZO3vdpRKJaZPn+4zRjI86MyHEBLU9uzZA6vVipiYGJpCS2RxVD9S8xkih3PlLK0bSuRobGxEdXU1eJ5HdnZ2oMMhQcSRuJ4+fTpiYmICHM3wYEILxM61ODrB1fke+/+bvwUzftj/cebf4bk7MwCIEM07ZMXCcRxU2gvRfy1HZzaotBfI2q5cHOdrVg8PpWqGx+SjxWJBYWEhgKHpmi6KPWgzvI39dQvR0PkUmNcELRkLbr75ZmzcuBEAcM455+Cdd97x++LaiSeeCADYv38/GhoaPI775ZdfpO9POOEEl/tyc3OlinDncX1ZLBbs2LGj32PIyKMEJCEkqDnW0qIptEQOaj5DBqqiogLt7e0ICQlBenp6oMMhQcSRREpNTXVZt4oQb6xWq5REGs3Vj8z4AbwnEgHR3ZRkv0795J8fhuhvOdpQxt3HZR6KkJOgUA8+qeeNRnsevCdBRWi157i9x2qrxq68dTCZTIiK0mPGjBl+7ZMxASZLAXpNW2ATjiWFrLY6HGpYgfq2+2EWamU8CzJa3X333Xj99dcBAMuXL8dHH30ElUrl9+PPP/986XtPjW56e3vxwQcfALAXDMycOdPl/rCwMGn5th9++MHjdO5PPvkEXV1dAIALLhjeCwfEO0pAkmHDmPcpA4QMVmNjI2pra8HzPE2hJbJQ5SwZKEf149y5c+kKOvGb2WxGSUkJAFo3lMhTUlICk8mEyMjIUT1tkFlL4X26MQOEcjBmc7mVUy+E9yQdBz7E3uhFtJbA2vUULJ0PwdbzJpjY7vFRvHIydDEfgFM41oqzd6cGOCg1ZyM06rVhv/Ct198C952yAUABpXI6NJozXG4VxA40tVyHmvoFyNtlX6t42szv0NhyMWxCo8d9McbQYXgblfXzUN10NmpbVqOyPgd1LdfAYq1GdetNsAo1XtvyjBUC4wPydTz585//jOeeew4AsHjxYnz22WeyG+JccMEFmDZtGgDgySefxKFDh/qNueeee9De3i59787//d//AbCvRXnbbbdBEFwvZLS0tODee+8FAERGRuKGG26QFScZWrQGJBlyjDFwHEfVaGTYOaofU1JSoNPpAhwNCSbUfIYMRHd3t7SGEFXOEjmKi4thsVgQGxuLyZMnBzocEiQYY1Ll7Lx580b3uqGcGvYEn7ckpAJ9k3FK3XWwmn/ytFEAIeBDzoG57VqI5p/h+PgrQIC1629QRTwKZeil7vemngN9/K8QLNsgWEvBcSFQhiwFrxyZBhYq1QzExL6LttYbwVgHjn10t0GpTEVM7NvguGMVZ4xZ0Nh8CSzWPWioT0BHRzSUSitmzCiDySygoekCJI77DjzfvwNwW/c/0db19z63MvSYfkSv+XdYxM7hepokyPz73//Go48+CgCYMGECnn76aVRWVnp9TEpKSr/qSJVKheeffx7nnnsuurq6cMIJJ+DBBx/E/Pnz0d7ejtdeew0ff2xvcHTiiSfiyiuvdLvtZcuW4ZJLLsHGjRvx+eefY8WKFbjzzjuRmJiIkpISPPHEE6iqqgIA/O1vf0NUlOe1W8nwowQkGXJlZWUICQlBfHw8dDodfbgnw8Jms6G4uBgANZ8h8tTX16O+vh4KhQKZmZmBDocEkYKCAjDGkJSUhHHjxgU6HBIkGGPIy8sDYE8i0XkR8VdNTQ0aGhqgVCpH/bkOF7IUzPS5lxEKIGRJv/UO+ZAToAi7H0L3k3BtRqMAoIQq+lVYux+HaP716O3OFZRWWDsfAMfHQaE51X1cHAdlyAlQhpzg9v7hFhJyAsYn5MNo/BJWSyHAqaDRnAq1enG/15Ie4xewWIsAAGWl9iVCpk4/AHWIBQBgEw7D0LMB4WE3ujzOaqtDW5enrsUCbGIXHMlhevUCRHAQR/g3MdL788aRFASA2tpaaS1HbyorK91efDvrrLPw8ssv4/bbb0djYyP++Mc/9hszf/58fPrpp1AoPFc6v/nmm+jq6sLXX3+Nn376SerI7cDzPB566CHcfPPNPmMlw4sSkGRImUwmfPDBB4iKikJycjKSkpIwfvx4REVFQavVuox1VEoSMhBlZWUwGo0IDw+XyvcJ8Yej+nHWrFnUfIb4TRRF5OfnA6DqRyJPdXU1mpqaoFKpaLkQIouj+jE9Pf24fL9i1gNgPW8B5h8AWAFlGjjdlUDI6eA4DoxZwIwfQex9D7BVAlwoOO054EOvAaec7LItTnMa0D0BEBvgfi1IEQrdjW5uB5T6G8GrF0DofQfMshvgVOBDlkOhuxxM7IZo/t7Ls+BhNTzvMQF5POA4DUJDVwGhq7yOM/R8AICHwRCK6qrJAIDUtD0uY7rdJCC7ez+GdyIc62ja61Pp8xsZOjfeeCMWLVqE559/Hj/++CPq6uqg0+kwa9YsXH755bjhhhugVHpPW2m1Wnz11Vd4//338dZbb6GoqAgdHR0YN24cTjrpJNx+++1YtGjRCD0j4g0lIMmQKiqyX3Vrb29He3s7iouLkZCQgKSkJEycOBHjxo1DeHg41Gq1S/LRYDCgsbEROp0OsbGxPl9kCHFMv87MzBzdU5LIkLJYLNI6bNSFlshx6NAhdHZ2QqPRIC0tLdDhkCDiqH5MT0+HRuOrqy0hdj09PSgtta/hdzw2n2GmzWAdt8OekjqaMLTuBuvYBWgvAgt7CGLHjYBlO6Sp1cwC1rsBQu/HUESvB6c+9j7McSFQRK+H0HYVINbBPtWawbHuIh/xJDi1598Dr54LXt13CjFg630erpWRfYlg1hIwoQGcYrz8X8RxRBCaAIjYvy8NjPEYn1CDqCjndS4ZBLG53+OsQjXsv2/3Kzw6PrEx5qjEY6Ak5Nj1888/D/k209PT8eqrrw56O5dddhkuu+yyIYiIDBfK8pAh5Vj/ISQkBBqNBp2dnaitrUVtbS00Gg0SExMxadIkTJgwAbGxsQgLC4NCoUBtbS0++ugjAMCtt95KazMQrzo6OlBRUQEANIWWyLJ3715YLBZERUXROmxEFkflbEZGhqwuj2Rsc04iUfMZIkdBQQEEQcCECROQmJgY6HBcMLENrOMO2JN6zms2Hk1gGT8EE9sAy07HI5zGCADMEDrWQBH3GwDenrgUu8ApkqGI+x7M9D8w808AM4NTpYHTrganGOCyF6wX/iTLGOsJ+pSaUjkRJlMFDu6fBQCY1af6EeCgVEzo9zgFHwPva2/asaPJ4LEuEE1hjrcmNIQMFCUgyZBhjGHOnDnYv38/BEFAdnY21Go1Dh06hLq6OvT29qKiogIVFRUIDw/HxIkTkZycjOjoaBw+fBg2mw16vV5KPtIUbeKJo/pxypQplKwmsjiOHWo+Q+To6urCgQMHAND0ayJPYWEhBEFAYmLicZdEIscvURSlytnjsfoRxk8BWOApacXAwMw/wlNFHSACYivErsfAzD8AYsuxu5TpUET8Bbz2D0MSKqecDtd1H93RgFME/9+nXncpSkqqYDZrodN1Y+KkI31GMITpruj3uLDQC9De/S+322QMEI7VQIISkISQwaAEJBkyHMdh9uzZ6O7uxrfffouioiKsXr0ac+fORVVVFWpqalBdXY26ujp0dXWhtLQUpaWliIqKgtVqBQCkpqYCsJ940bRa4o4oiigsLARAzWeIPE1NTaiurgbHcbQOG5HF0Xxm0qRJiIuLC3Q4JEgwxqTKWap+JHIcPHgQnZ2d0Gq1mD17dqDD6YdZivwY5Sn56MCDGTf2v9lWCqH1EihiPgSnmtV/q9YSCIZ1EC1bATDw6oVQ6K4Fr3Z/TqjQng1r15+PVkK6S5gqoAhdBY7TurkvuGhDTsP+ffZmOymzSsHzzs9XAbVqNnQ6d+tIMoSoMmG2FsH5d8QYYKOEYz8CeAgY4QrIEd4fIcOFjmQypBhjyMzMREZGBtra2vDLL7+A53mkpqbixBNPxFlnnYVzzjkHOTk5UgfR9vZ2GAwGAPZufz/++CP27duH1tZWWCyWQD4dchyqqKhAV1cXNBoNZs3qf2JKiCeO6seUlBSEhYUFOBoSLKj5DBmoiooKtLe3IyQk5LhMIpHjl6P6MSsr6/hcF53z3I3Wf16qI2GF0N1/PUehdxOsLedDNH0BiM2A2ALR9A2srSsh9Kx3HyqnhTryWdgr9/rGrQCnSIIq7O5BPI/jR11dA1qatVAoGGaklDvdo4QudCXGx30Inju2Dq1NaEJN80WoalwKs7UQrglart+/0LE2NL6naxNCiDvH4TsaCWYcx0Gj0eDkk09GVVUV9u3bh4SEBJx00knQaDTQaDQYN24cpk2bhs7OTlRWVqKgoABtbW0AgIaGBjQ0NECr1SIxMRETJkzAySefDIViKE50yGjgqH6cM2fO8XlSTo5LNptNapJFzWeIHOXl5dJFD2o+Q+RwJJEyMjKgVqsDHA0JFm1tbSgvtyePjtfKWU59Ipjpq2HcgwBYfgMTmsAp4gEAonU/bJ0PwKXpjWMsAFvXo+BUWeDVc/ttTaE5DeqYjbB1/xui5bejT0IHReglUOlvB8dHDuNzGV4iM6Kn93P0Gr/Gr79FAYhC2uypmDF1FyyWfDAmIkSdAYUi1vVxYi9qmi+E1dZ3mjYAcOC5KHCKSFhslcdu5QAFY0enZI/d6dgi4yCykX3uI70/QoYLVUCSIccYQ3R0NFatWoXQ0FBs3rxZqjxy0Ov1mDBhApKTk6Wp1qmpqUhJSYFWq4XRaMShQ4dw6NAhSj4SSW9vL8rKygBQEonIU1ZWBqPRiPDwcEybNi3Q4ZAg4qh+zMjIoIsexG9dXV3Yv38/gOM3iUSOT47E9fTp04/fda61ZwHw3NGdO/o/z/xJpjBAbJJ+EnrfgfePrgoIPW97vledi5CYt6EZVwxN/A5oxuVDHf5gUCcfrbYjqG04Ga3td6Kt/TccKg8HAEya/A8YDO9Aq1mKUO3yfslHAOjq/QhWWwXcdwdnEFk7RNHQ7x6eAxRUAUkIGSBKQJIhx3EcRFFEYmIili5dCoVCgZ9//hmHDh0CYJ/OBgCCIKCpqQktLfaFp88++2ycccYZOOecc3DCCScgOjoaCxYsCNjzIMefkpISCIKA8ePHY/z48YEOhwQRx0WQzMxMWl+W+I2az5CBonVDyUBYrVZppsdx2XzmKI7TAqGXuL2POf3v2GQ7RzHB0fdfLgZ+JSH5mGPbteyE+2SZgwDRutPL/Ud3zYeBU4wDxwV3VTJjAhpbLoMg1AMADu5PhSgqEBvXiNi4ZrR3PYEe49ceH9/d+yF8/RswZkH/aev2JKQSDAoAOlUapsa7WcuTEELcoEv5ZFg4PuBnZ2ejqqoKJSUl2LZtG+Lj46W113p6enDkiL3sPzU1FXq9HgAQGRmJqVOnIj09XVonkhAA1HyGDEh7ezsqKioA0LFD5CksLKQkEpHNed1Qqn4kcpSWlsJoNCIiIgLTp08PdDhecbqbwHrfgSMpeCzp6MwGKOeAU04FE5sATg9ecxagzoXYfAo8d6fmAdU8cIoEp9v8mRE1di4wGk0/wGazn9uIIocDZfYlQlJn7Tk6gkdn1wvQac9y+3ib0ALvazkyKDglBNY/6cuY45EiInTnQc3mDPRpBCUxAE1oxDF0bJPRjY5kMqx4nse5556LadOmoaKiAt988410X2trK6qqqgAcm04rCPY3OY1Gg/Hjx4PjaL0LYldfX4+GhgYoFArMmTO2TnTI4DgS11OnTkVkZGRAYyHBgzEmJZFoyQcix8GDB9HV1QWtVkvN0ogsjunXOTk5x1W1PhO7wczbwMxbwcQuAACniAUXdt/REZyb5ONRtlIwy29QRDwNZdRL4LXngleMB6+/zcPeeAA8FGH3uN4asgTek5CKo2PGBqPpJzhqiWqqktHTE4YQjRGTp1QcHSHCYi1wO40aAFTKSfCeCuARopyBKN3VR3+2fyYTj3bGdnSCruv4Gw7Unz4UT4kQMgaMugrIX3/9dUT2c/LJJ4/IfoKdKIpQqVRYunQpOjo6sG/fPvz0009YsGABamtr0dnZCY1GgxkzZgAArfdIPHJMoU1NTYVWqw1wNCRYiKIoHTtU/UjkOHTokPQeRc1niBy7d+8GYF/ygdYNJf6qr69HTU0NeJ4/bi56MGYC63oaMH4AwHL0VjWY9kJwYfeB010N8DEQu58BxGoPWxEAsRNiz6tQhD8i3crpbgePEIg9LwCs99hwxQTw4U+CU7u+ZytCL4fQ8xbsXbLdJzsVoVcN8JkGH+ZUPVq2Lx0AMGPmPiiUQp9xVrePj9BdDqP5Ny97EBEZdgX02vOhUc9Ga/dLMFkrXSr/GANEcOi11Q38iQQhkfEQ2QhXQI7w/ggZLqPurOiUU04Z9qo5juNgs3maMkCcOa7eTpgwAQsXLsRXX32F3bt3Q6/Xo67O/mblqGYTRfG4utpLjh82mw0lJSUA7B/oCPHXoUOH0N3dDa1Wi9TU1ECHQ4KIo/px7ty5UKlUAY6GBIuOjg4cPHgQAK0bSuRxVD+mpaVBp9MFOBqAMRtY+42AZRfsST8HC2DcCGb8BCz0CnsSUnMG0PsmPK/RKID1fgQW9iA4zl5swHEcOP1N4EKvALNsAcQucMpJgCrX7Wc5TjkJyqj/wNZ+29H9OGJSAOCgjPwneNXxPW19KIWoMmHAe+jsiER93URwnIiU1FKXMQrFRPBcpNvH67VnQRtyEozmrXD99wUAHlr1Qui154DjOETpL0d46EqU1uYAzF4BKzAOVvAAOAhe1+YkhJBjRl0C0oEx6s51vJk3bx56enrw888/4+uvv5Y+0Dmqkmi6NfGkrKwMJpMJ4eHhmDp1aqDDIUHEUf04d+5cqkQifjMYDFIH4+OlEokEB0fiesqUKYiJifExmhA7k8kkXWg9btYNNX0LWLw1dbEAvevAjB8Aqix4X08QAIz2SkcuzOVWjg8FpznNr5AUmlPBx2+G0PM+RMtWAAy8ehEUoZeDUyb5tY3RQhd6Ado6H8P+fbMBABOTjkAf5jzdmkO4/gaPn684TonE2PVo7XwSnT3vgjHj0ds1iNBdjpiIB8Bxxy6+GUy/QOyXfDy2L0II8ceo/TT25ptvYsqUKUO6zcrKSlx33XVDus2xgjEGjuOQm5uL1tZWHDhwAGazGWFhYUhIsC8wTQlI4oljDb+MjAyqkiV+6+npoSQSGZCioiKIoogJEyZQMzTiN0EQpIseVP1I5CguLobVakVcXBwmTZoU6HAAwJ5YBI/+1XEuowDWC2bZBd9JqBCACx10XJxiApTh9wC4x+fY0YzndYgMewXlB38AAKTM2uu4B4CIUM3pCNdf730bnAZxkY8iJvwemKz2BHiIKh0KPgwiM8NiqwHPhUKpiIZVaJIeZ5OSj2Pzs5sADsIIP/eR3h8hw2XUJiDnz58/5Gs2xcbGDun2xhJHcjE0NBRLlixBfHw8KioqpMXZafo18aSrqwuHDh0CQNOviTzOSaT4+PhAh0OCBDWfIQN14MABGAwGhIaG0pIPxG+MMWn69bx5846fC/JCLbwnHx1EcDB6bkIDAFCA014oTb8mQ6P8YDisVjUiIkRMnNgNIAQq1UyE6a+DPvQiv3/fPK9HaMgiAIAgtKOh/WG092wAO7o2Z6h6IbSakwDYm9AwSoYRQgZo1CYgyfErJiYGJ554ItLT06HX6wFQ9SPxrKioCAAwadIkREdHBzgaEiwYY1LlLCWuiRxHjhxBW1sb1Go10tPTAx0OCSKOxHVmZiY11SN+q66uRnNzM1QqFebOnRvocI7hYwGhGr6nVgMcVGCKSYBwyM14BcDpwOtuHo4oxyzGGHbt2gUAWLDgDCRPfHTQ27QJbTjcdB4stio4r+fZa/kdPead4DkdROeGQWMUNaEhZOBGXQLykUfs3dWGo9olPj5e2j4ZOMd07MjISOk2SkASdyiJRAaqtrYWzc3NUCqVlEQisjiSSOnp6VCr1QGOhgSTZcuWISIigqZfE1mio6OxZMkSCIIAjUYT6HAknPYCMGu+/+PVJwHcErDed3CsYzYA5WwoIp8Gp5w49EGOYTU1NWhsbIRSqRyyc+SWruf6JR/tRHvTIFio9pEQMiijNgE5HOLi4igBOQQo2Uj8VV1djba2NqhUKsyePTvQ4ZAg4kgizZ49+7j6QEeOb0ajEaWl9i6iNP2ayJWQkIBzzjkn0GGQIKPX63HKKacEOoz+tOcBvesBWwV8T8W2gdecCC5kCZj+NjDLVoCZwClTwalmjUS0Y46j+jE9PR1arXbQ2xOZCe09G+G5kzkDDyti9ZegwfAZBFgxdteAHPk1GanPOBktqJaXEHLcclQ/zp49myqRiN8sFgv27rUvxp6VlRXgaEgwKS4uhiAIGDduHBITEwMdDiGEBAzHacFFvwuoT/QxUgEopgBq+xqBHB8OXnMmeO0FlHwcJj09PdLFstzc3CHZpk1olNZ89EwJJa/HrPGfgkMIxmoCkhAycJSAJCNOFO1XUTs7O9HQ0ADGfK8tQ8Yeq9UqJZEyMjICHA0JJqWlpbBYLIiKijpuuomS4x9jTOpgnJWVRdX6hJAxj+OjwUe/DsR8A6gXH73Vsb7p0ddIPh5c1GvgOPpYOVIKCgogCAISExOH7GIZz+n8GCWC53XQhaRjdsKnCAuZNyT7JoSMHaNuCraD2WzG/v37AQARERFITk72+7FHjhxBZ2cnAGDWrFlQqVTDEuNY99VXX+HgwYOYOXMmpk2bhjlz5gzJFAIyOuzbt09KIsn5+yXEUTlLSSQiR319PRobG6FQKI6vRhAkYBxrVhMy1vGqaUD0W2CWIrDeDYBtP8DrwWnOBjTnguP9SV6RoSCKInbv3g3A3jV9qCgVsdCq58FoyYfnKfcCwrVnAQB06jSkjf8AJuthNLeVAThzyGI53lETGkIGbtQeyY8//jiysrKQm5uL6upqWY+trq5Gbm4usrKy8NRTTw1ThKPDQKoXeZ6HKIrSv8uBAwfwzTffoKWlZajDI0HM0f167ty59AGQ+K21tRVHjhwBx3FUOUtkcawbmpaWRhfDCABas5oMzGie2cOpM8BH/g187Kfgo98BF3oJJR9H2KFDh9DR0QGNRjPkTfbiwu+C567nPPSaU6FR29dkF5kZ3aY8mIV6hKpThzQOQsjoNSoTkJ2dnXjuuecAAPfffz9OPNHX2iWuTjzxRDzwwANgjOHpp5+GwWAYjjBHhYGenPf29mLmzJmYOHEi1Go1IiMjkZSUNMTRkWB29tln4+STT6bu10SWsLAw/OEPf8DixYsRHh4e6HBIEJkzZw7S09Op+QxBZ2cndu3ahT179kjLxhDiiyPxSIlrMpwczWcyMzOHfJaeXnsKEqP/BY7TwD7FXgXHlHu9ZhkmxrwIxkTUdv4H+TULUNp4EcoaL0NR7bIhjeN4JzA+IF+EjAajcgr2pk2bYDQaERsbi3vuuWdA27jnnnvw4osvoqWlBZs2bcL1118/xFEGL8YY2traUFlZCbVajbCwMISFhSEqKgoKhQKiKILnvb9I6vV6XHDBBejp6UFZWRlCQkJGKHoSLKKjo7F06dJAh0GCjFqtpqQ1GZDk5GRa7oEAsH/A37VrFxhjiImJQUJCgtfxlHgigL0yTRRFjB8/Hnq93uVcmKbzk6HQ0dGBgwcPAhja6dfOInUrEaZdgc7eT2GxHgLP6xCuPRsatb3asqL1ATQbNvR5FPVoJoT4Z1QmIL///ntwHIcLLrgAOt3ApgWEhoZi5cqVePnll/Hdd99RAvKo7u5u/PbbbygoKIDNZgNg/8A/ceJEpKenIysry2fyEbCvX8JxHHQ6HXJycoY7bEIIIYQQn44cOYJdu3aB4zgsWrTIa/LRYrFAoVBAoVBIt1EycuzatGkTQkJCMHXqVCQnJyMxMRFRUVHQaDR0PJAh4Vj7cerUqYiJiRm2/Sj4cETrr+53e495j5vkIyGE+G9UJiAdXSxPPfXUQW1n2bJlePnll6V1oca6uro6/PbbbygrK5NuCwkJgdlsRkVFBSoqKrB//36ce+65PhO/jiQlnagTQggh5Hixe/duWCwWZGRkSNPxnWd2WK1WVFdXIz8/H4wxdHV1ITIyErNmzcK0adNoRscYVVpaCpvNBpvNhpKSEuzduxeJiYlITk5GUlIS4uPjER4e7pKsBuxJbIPBALVaDZ1OR+fDxCNBEKTPuP4Ub1htdejqeRc9pl8AiNCGLESE/mqolZMHHENzzwewT8m2VzyKDGDgILCxddwycBAxss+ZjfD+CBkuozIB2dzcDACYOHHioLYzYcIEAEBTU9OgYxoNtm7divLycgBAdnY24uPjoVQq0dHRgQMHDqClpQWHDh1CXl4elixZ4tdUbICSj4QQQggJPKPRiJKSEgD2NUHDwsJc7m9sbMSWLVuwZ88e6TaO41BTU4M9e/ZIszpyc3Oh1+tp2u0YUlFRAcA+K0ij0aCrqws1NTWoqamBXq/HxIkTkZycjAkTJiAmJgahoaEA7J8xvvnmGwiCgJUrVyIuLi6QT4Mcx8rKytDT0wO9Xo+UlBSvY3uMm1Hfeh0YbHB0tDZb96DD8DrGRf8L4aEXDigGs7UWgACRAVYowI62k7DSFGxCiJ9GZQLSbDYDsJ8EDIbj8RaLZdAxBbuqqiqUlpYiNDQUS5YscWnsYzQaERcXh++//x4GgwHbt2/HpEmTMGXKFI8n347kJJ2Yjz30gYwMhHO1NFVOE1/odYYMhOMia1JSEhISEqRjyHEx9auvvkJdXR0AICIiAiqVCkajEUqlEkajET09Pfj111/R1NSEM888kxphjSGpqakoLCyEzWZDRkYGQkNDcfDgQdTW1sJgMKCsrAxlZWUYN24cJk2ahOTkZMTGxqKmpkY6piIjIwHQ6xdxLy8vD4C9CKRvJa0zq632aPLRCteO1vYkYWPbHQhRpiJEnebXfs3WCtjEVqgUiVAqoiEyBSxjvBovEE1hqAkNGS1GZQIyNjYW9fX1aGxsHNR2HJWPw7nGRrBwTENPS0uTFj0WBAEKhQJarRZz585FREQENmzYALPZjO+++w433nijxwrIsrIytLS0YPbs2fT7HQOcT6adT6rpJJv4y3Gc9D1mKBlJ3OE4Dr29vQgNDYXJZIJKpYJCoaDXHOJVW1sbAHsiqO9xUlBQgOrqauh0OsyePRtZWVkYP348uru7UVNTg8rKShw8eBAdHR0oKyuDQqHAeeedN+iL4SQ4TJ8+HWeddRa++OILFBcXY/Xq1Zg9ezaOHDmCqqoqHDlyBE1NTWhsbERjYyNKSkowbtw4GI1GAMCsWbOkjsae3u/I2NXS0oLDhw+D4zhpaQhPOnveAYMA1+Sjqw7DmxgX/Q+v2+k2/oq6jr/CZN0r3aZWzoZN+omOTUKIfKMyAZmUlIT6+nps3boVZ5111oC3s3XrVml7Y5kgCFLHtZkzZ0Kj0QCAdPWNMQbGGJKTk7FgwQJs2bIFzc3NKC4udtuNtqenB5s3b0ZrayuSk5MpATkGCIKAlpYWtLa2wmazYeLEiYiJiaETa+KVIAg4fPgw6uvr0dzcjIiICIiiiNDQUCQlJSEpKYkS2qSfuro67Nu3D2VlZbBarUhOTsaUKVMwe/Zs6QM+Ie5EREQAAFpbW6HVagHYX1dEUZTWXlu8eDEWLFgAhUIBURQRFhaGWbNmYdasWaipqcHmzZtRWVmJAwcOoLa21utsEDJ6MMaQnp6OmpoaFBQUYOvWrTjvvPMwe/ZsTJkyBW1tbaitrcWRI0dQXV2Nnp4eHDlyRHq8zWZDaWkpoqKiEB0djZCQEDpmiMRR/Thz5kzpdcqTXtPP8N6VWkCP+Sev2+js/R6HW25A3ySmyVIGESqM9eSjyDiII7zu5Ujvj5DhMioTkMuWLcPOnTuxYcMG/PnPfx7QBw6r1Yr3338fHMdh6dKlwxBl8KitrYXFYkFUVFS/9ZAA+5Vax0lSVlYWysrK0NTUhKKiIqSnp0OhULicRNXV1aG1tRUKhQLJyckj9jxIYJSWlqKgoADl5eVQq9XgeR48zyM5ORnz5s3DlClTAFAFG3FVXV2NH374AVVVVeB5HqJoX8PI0XHWarUiPDwcKSkpyMzMdJkuScauI0eO4Msvv0RLS4t0W3FxMYqLi7F3716cffbZ0jRHQvpSKu2nxY7GIKGhoeB5Hl1dXaiurgbP88jJyZGqaXmed6nCnjhxIlasWIGNGzeiq6sLhYWFmDJlCr02jQEcx0GtVuOkk07C4cOHUVpaigkTJmDx4sXQ6XTQ6XRITEzEzJkz0dLSgoqKCpSWlqK7uxsAcPDgQVRWViIxMRGTJ09GQkICZsyY4XWqLRkbrFYrioqKAECaheYN82c9RiZ6vovZUNN2L+zJxz5VlJwAMKrqJoQM3KhcTGDlypUA7B9EHn/88QFt44knnsDhw4ddtjdWdXV1SdPXfJ1ER0ZGYv78+QCAw4cPo6KiwmXNNlEUpS7a7qojyejBGENpaSm++OILlJeXg+P+f/bOO7qO6tzbz8yp6r3bsiRblns3tjAYbHozJRC4JAQIJSFAclNIQvIlIeWGVHKTG0ggoQRSCMUQqk23jXuTrGLLalbv/fQy8/0hz1iyVY5sFUtnP2tpSWdm7z3vSFtTfvstEh6PB5fLhcPhoLS0lC1btlBXV9dvjggEBQUFvPPOO1RXV2M2mzEYDCQnJxMTE4Pf79fz8nZ1dbFnzx6eeuop/vrXv3LgwAE9nE0QfDQ3N/P+++/T2tqK0WgkLCyMzMxMvahDWVkZBw8e1K81qqricrmor6+no6NjIk0XnCVkZGQQFhZGa2srhw4d0tPIaCl9MjMzsVgsKIrSL62I9rOiKKSkpOgLa36/H6/XOwFnIpgoYmJiuOGGG7Barbz//vt6USPoXUCLjY1l9uzZzJ07Vy9Eo93ffD4f1dXVbN26le3btwvxUQBAUVERLpeL6OhoZs6cOWz7UEsuvZWqB8NAiGX1oHt7XFvxKS0MFMJ9PDnAsDYIBALBYExJD8hly5axYcMG3njjDf7nf/4Hs9nM97///YBWoFVV5dFHH+UnP/kJkiRx1VVXsXz58nGw+uzFZDLhcrmQZTkgz5H58+dTUFBAVVUVH3/8MdnZ2frvvru7Ww/nXrp06ViaLZhgtL+/y+UiMjKSjIwMsrOzqa2t1Vf9q6ur+fe//83tt99OfHz8sGOKMLapj6IobNu2jZaWFuLi4li7di3Tp0/H5/MRGhqK0+mkrKyMyspKWlpacDgceL1e6urqaGtro7y8vJ9nrSB4OHDgAHV1dcTExLBq1SrOOeccurq6aG9v58CBAxQVFbF//37WrFmDw+Fg+/btlJeXI8syHo+HlJQUFi9eTHZ2NiaTSVxvgpDw8HBWrFjBli1beP/994HeZ8rY2FgMBgM2mw2bzTZohWvNWzshIQFJkrDb7RNxGoIJRFEU0tLSOP/88/nggw/YunUrcXFxpKam6gUYFUWhs7NTzzW/YcMGPB4PlZWV1NTUUFFREZDQJAgO9u/fD8Dy5csDuidFhX2BTtszQ7TwEx3+xUH3enzV9EqNAwiQEphUP14MBHMYth8Z/zj7cY338QSCsWJKCpAAf/zjH9m7dy8NDQ386Ec/YuPGjXz1q1/lqquu0r0h+tLS0sLbb7/N//3f/5GXlwdAUlISjz/++Dhbfvbh8Xh0jxGfz4fZbB70BqiqKlarlSVLllBTU0NjYyMFBQUsWrQI6BWlenp6iI6OJi0tbdzOQTD+7N+/n9bWVqZNm8b69et1QWjBggVccsklfPzxx+zduxebzcaHH37Iddddh8ViGXJMIQZMfY4ePUpLSwvx8fFcffXVp6RpCAsLIz4+ntWrV9PW1sbRo0cpKSmhqqoKl8tFcXExra2trF27lvnz5wsRKUjom6NvzZo1LFq0CEmSiI6O1u83nZ2d+Hw+Dh48SEFBAXV1df3GsNlsNDU16fNHzJvgZNmyZboQtG/fPiRJYtGiRcyaNYuSkhKam5sJDw8fcn44nU5UVSUyMlLkHQ0yNK/Zc845h8rKSsrKyti5cyfXXnutHuJvt9uprKxEVVVmzZpFSkoKACkpKXR2dtLQ0MDcuXMn7BwEZw+NjY3U1tYiy3LAkWNm0yySYh6jqePr9AY7aiHZBsBPfNSPCLGsHLS/QY5mKC9Hq+TDqxqOjz14KLdAIBAMxJQVIKdNm8Zbb73FVVddRWNjI/n5+dx1110ApKamkpSURFhYGHa7naamJurr6/W+qqqSlJTEm2++GfQFaABmzJjBxRdfTG1tLW1tbYSFhQ3aVnsgz8nJYc+ePTQ0NHDw4EFycnIwGAwi/DpIcLlcFBYWAnDBBRfoIlLfPH7nnHMOra2tlJSUUFZWRllZGfPnz9c9BPrS3t7Ozp07mTt3LllZWeN7MoJxpbi4GOitCDpt2jSgv+erVvRKlmXi4uLIzc0lNzeXiooKdu3aRWlpKc3Nzbz99ttYrVbhRRIkHD16FI/HQ1JSEjNnztRFH23xzGKxkJqayv79+/n444/xer2kpKQwc+ZMXQzo7Oykq6uLjz/+GEmSOP/88yfylAQTRGRkJGvWrOH111+no6OD9957j507d+rhsps2beLSSy8lIyNDF5QA/d7V3NysP+vMmzdvQs5BMLGoqorRaOTaa6/lX//6F4WFhYSEhOiFMVtbW/UCNFpOP0VRMJvNJCYmkpiYOGG2CyYeVVVwubfg8RSxc1dvWpk5c+YQHh4e8BiRYZ/FbJpLp+3p40VpFEIsuUSH30WI5Zyh+4ZchCRZUVXXgPsNkkqMIRavlILNWxywTVMJUYRGIDh9pqwACb0hvvn5+dx777288cYb+otIfX19P8ER6Jd/bsOGDTz55JMkJSWNq71nK5GRkeTm5mKz2QYsQjMQISEhrF69mtdee42qqiqqq6uJjo6mrKwMgMWLF4+lyYIJpqSkBID09HTS0tJ0QbGvsBgZGclll11GXV0dNpuNffv2MWvWrAG9ICsrK9m3bx/FxcU89NBD43MSgnHH6/XS3d0N9F5DtPxXfT2N+uZb6ytGZmVlkZmZyd69e/n000/p6enhjTfe4O677w74uiWYvFRUVAC9HkRWq1Xf3jc3X2xsLIqi4PV6yc3NZd26dfocU1WVvLw8PvroI2w2G0VFRSxfvpyQkBDhCRmEzJ49m7vvvpsPP/yQiooKenp6sNvtyLJMS0sLH374IYsWLWL69OlERkYSGRmJLMtUVVWxdetW2traSEhIICcnZ6JPRTABSJKEoiiEh4ezdu1a3njjDfLz85k+fTqzZ8+murqazs5OQkJC9Dly8sKrYPKjqj683kJU1Y3JmI1siB22j9tzkJa2L+Hz1+D1Wjhc/DnAzMzZn6AoVyLLgzuBnIzVvJDk2P8dsd0GOYKkyK/S2PWrQdukx/w/osOuocddjMNbhsOqAteN+FgCgSD4mNICJEBCQgKvvfYaxcXFPPvss2zZsoX8/Px+ScFNJhOLFy/mggsu4I477mD+/PkTaPHZiSzLREZGjqjP3Llz2bdvHzU1NezcuZOMjAx8Ph/Tpk0TVUinONXV1UCvt3FfD5G+qKpKTEwMl156KRs3buTYsWMUFhaeknPV5/PpeUPPPffcsTVcMGGoqorBYCA6Opqqqio9PHaoEOqTxUhJknRvko8++oju7m6KiopYvXrwZOuCyY/f79cXEZubm3UBsm91Yp/PpxcSmT9/PuvXr+9XXV2WZZYuXUpTUxN79uyhqamJ9vZ23QtXEFyoqkpsbCxr164lKiqK4uJiurq69P2NjY00NjaSlJREfHy8nie7sbGRnp4eYmNjxf0qyNEExZycHJYsWcKOHTvYvn07ZrNZd4LQooEGivwQTF5UVcVu/yu2nj+iKC3HtxoJCbmWyKhHMBjiBuzn9ZbT2HKj7nlYWZ6F12smMrKTmNjXaW5rISn+3+OyKJYY+QCg0NT1B1Q8aOHbshROWsyPiQ67BoAIyzwiLPPoVrrH3CaBQDA1mPICpMa8efP49a9/rX/u6emhp6eHiIgI4R0TAKeTR81kMrFy5Upqa2uprKyksbEREOHXUx2Px4PX60WSJAwGw6BVHLXK1zk5OaSnp1NdXc3BgweZM2dOvzB/rbAI9OaPFExNNDExJCQEgIaGBqqrq0lPTw+4P/S+9J1zzjmUlJRQUVGhJ/kXuSCnJppwrV0zenp6qK+vJyUlpd/fu76+XvfAX7FiBbIs696z2jiSJLFs2TL27NmDxWKhq6tLCJBBijZ3kpKSuPTSS1m0aBEFBQUcPXqU7u5uVFXF6/XS1NSkC9tav5CQEC699FKR/kGgc8kll2Cz2Th06BD/+c9/dCcIbcFV3JumFt3dP8Fue/KkrT6cztfxeA6QkPg2shx9Sr+unsdRVTdaXsWjJb15QLPnHEaSFFzubbg9u7Back/LLlVVsbu30WH7Bx5fBQY5hujQzxAZugFZDunXVpIkkqK+RlzE7XQ5NuFX2jEZUokKuQxJstLjLsDta8RkiCPSsuS07JnMKMgo41wUZryPJxCMFUEjQJ6MEB4D5+T8axD4w9KsWbNITk6msbERl6t3RU+ISFMbWZZ1cdHn8+kv+gPNGUmSMJvNLF26lLq6Ourr6ykuLmblypW6R0BlZaXuORsVFTUBZyQYT5YvX87evXtpb2/nzTff5NJLLyU7OxsY2fUnPT2dyspKuru7cbvdwxY4EkxOtLkQExODLMv09PSwefNm1q5dS3x8PFarlaamJjZv3qynEUlNTe3Xt+/PqqoSFxdHR0dHv9QsguBEu3clJyeTnJzMunXrqKiooKqqCrvdjtvtprGxEaPRSGJiIvHx8SxdupTo6GgxfwTACe/G3NxcmpqaaG5uRlVVkpOTiYuLE4tjUwyvt3QA8VHDj99fjc32FJGR3+63R1VV7I6NaAVj2lrjaWtNRJb9zMouOd7KiM3x2mkJkKrqp679a3Q7XkPzZgQZh3s7rT2PMyPxZUyGU1OPGeVo4sJv0T93OHdS2v5jnN4KfZvFkEqi8asjtkkgEAQnQStACoambziIJEnYbLZ+OdkCJSQkhOXLl/PWW28BDJrjTzB1MBqNeqha31xsQ7FkyRK9aNGBAwdYtGgRFosFt9ut55MUnrPBQXx8PJdddhkffPABra2tbNq0iZaWFpYvX97v2jGUGKkoii6CG41Gcc0JAhYuXMi+ffuora2lurqaV199ldTUVLq6umhvbyciIkL3lLTZbIOmAfH7/XR1deH3+4X3o+CUfLNGo5HZs2cze/Zs3G43iqIQEhKCzWbrVyBCiEoCDe1ZOjk5mUsuuYQjR45QVlampwYRc2Vq4XD8ixMC30D4cdhfOFWAxI2KW/+seT/OyKjAatWKwSgoSudp2dXa80e6Ha/rNmjjAXh8x6ht/RKZSa8P0PMEHc6dHGq6k5MrZLv99RzpDK787H5Vwj/ORWHG+3gCwVghBEjBgMiyTFNTE/v27aO1tRWz2Ywsy3oC7fj4+IAfmpYsWYLP56OgoIBVq1aNg/WCiURRFGbNmoWiKHR0dAyb20ibRxdccAEvvvgijY2N7Nu3jzVr1tDc3MyxY8cARG7WIGLBggW0trbqnpDvv/8+O3fuZOHChcydO5fp06f3u/Zoc0j73tHRoYfbzp49e6JOQzBOaKHU1113HR999BGVlZU4nU49dYMkSVx88cXs3LmTpqYm2traiI6Oxu/36x7b0Cs+Hjt2DK/XK3IVC/oxUL7Zvgsb4eHh/Z6JhKAkGIiZM2eSlpbGokWL9AUOkftxauH31aIJe4OhKG2oqhtJOnENkbAgy3EoShtej4mK8t7Ij9lzDvfpKWE0zhixTarqob3nL5wsHPaxGqdnL05PASHmhYOMoVLW/tPjYwjvboFAcPoEjQCZlZU14j6SJGG1WomKiiI7O5vVq1dz8803Exs7fBWzyYzf7+fQoUO8//77OJ1Ofbssy1RXV1NVVcWFF15ISkpKQOMZDAaWLVvG7NmziYmJGSuzBWcJsixz3nnnsWLFCtrb24cMwYYT1SJzcnKYNWsWZWVlHDp0iIULF+ri48yZMwP2phRMfkJCQrjiiitISUlh//79NDY2YrPZ2Lt3L0VFRcTHx5ORkUF2djbJyclIkoTH48FsNtPQ0MDWrVupqakhJCSEefPmTfTpCMYYTXyOi4vjoosuoqKigvb2drq6uoiIiGDBggVMmzaNqqoq6uvrKSgoYObMmf0qYEuSREVFBYcOHQJg6dKlE3lKgrOYoe5lAsFwWK1Wpk+fPtFmCMYIWY6h1wPSN2gbSbIC5pO2SUSEfYGunj9QWTELn9dMZFQnScn1fVr5iQi9hZHi8h7Fr3QM08qA3fXpoAKkzXMYh7dsxMeeqiiqhDLOHonjfTzBmbN169YxGXft2rVjMu54ETQCpCZkaGgvLAMx0L7du3fz97//nW9+85v84Ac/4OGHHx4rUyecffv2sWPHDpxOJwaDgcTERHw+Hy0tLTgcDo4ePUpzczPXXnstGRkZAY1pMpmE+BgkaP87Vqt1wFxrA6F5ACxdupTq6mqam5s5cOCA7sUmxIDgQhOEFi1aRGxsLAcPHqSoqAiv10t3dzc2m41jx47x0UcfERkZSXp6uu5x63K56OjoIDIykhUrVgjhOkjQrjGxsbHExsbqgnRftOtRfn4+DQ0NLF++XE8LcuTIEbZt20ZXVxdxcXEiV7FAIBgTRMj15ENV7Lhd76EobRgMaZit6/t5L/YlJPQ6HI4XhhjNQEjIjQPOgciIL2F3/oejJb0Lp7NziunbLCriAUym0yluNVg4eGDtXN5KWu1vnMZxBYLg5sILLxz1670kSfh8gy9wTAaCRoC8/fbbATh06BAHDx7UvSWWLFlCQkICAC0tLeTl5dHW1oYkSSxZsoQFCxbQ3d1NYWEh5eXluFwu/t//+380NDTwhz/8YSJPaUyw2Wzs2LEDm81GQkICGzZsIDIyksjISJqamti5cyfFxcV0dnaya9cu0tLSMJlMw47r9/tHnD9SMDk5kwvtnDlz2LdvH5WVlezatQu3240sy8yZM2cULRSc7fStaJ2enk56ejrr168nPz+f/Px8Wltb9f3a9bkvFouFCy+8UITtByHay73ZbD6lgNrChQupqKiguLiY1tZWPv74YzZt2kRoaCg+nw+32018fDznnnvuKeKlQCAQjAZCfJw8qKqK0/4k9p7fgOoEZEBBkqIJj/oZ1tDrT+ljNq/GYlmL2/0pp4ZiG5CkEMIj7hvweAY5Csn/NG2t/0aW/czMPnp8ezJRkV8lIuyO0zoPi3E2shSGotqHaOUnxLKy3xaPr5Hytofodn163PsuaGQDgWDUEAXpTiVoriTPPvsszz//PP/617/Iysrid7/7HVddddUpuVcUReGtt97i61//OkVFRdx///188YtfBGDv3r3ce++95Ofn8/jjj3PrrbfqSaSnCocOHaK7u5sZM2ZwySWXkJaWBvT+8yQlJbFu3TrsdjtlZWWUlJRw8OBBzjnnnEHHs9vthIWFCfFRMCxaHrdVq1ZRU1ODx+MBekVJMX+CF62gTEREBOeddx7nnXcezc3NlJSU0NjYiKIouN1u2tvbSUtLIyYmhuXLlwuP6yBloMrW2s9Go5HVq1djt9uprKzE5XIhSRJ2e+9LWUhICOvWrSMnJ2fc7RZMLjRxu7W1ldjYWJHHTxAQWk7s7u5uQkNDMRqD5jVsUuK0P4W9+6d9tvQKiqraSU/nA0iSBUvIlf36SJJETOwzdHZ+A5fzTW0roGAwTCcm9s8YjZmDHvPgwd7Inzlz55I5/VUkyYLJNAdJOv3nYFkOISb8Ntp6nmLg/JQGLMZsQs0n3ud8/k6KGm/E4288fgYqEmpvBkhVQgUU+ubiPm3zJiWqKqOo43vdV8f5eIIz5+OPP55oE85KgubOd/DgQe655x6Sk5PZtWsX8fHxA7aTZZkNGzaQm5vL8uXLue+++1i0aBErVqxg5cqVfPDBByxatIjGxkaeeuqpKSdA5uXlAb0VRbVwtb5eJFFRUVx//fW8+OKL1NTUsHXrVnJycoiKijplLJ/Px1tvvcWxY8e49dZbRc4bwZBoqQ9ycnKYPXs2xcXFgKh+HexoL/ZaFVpZlklMTCQxMRHo9dq2Wq0YDAZ8Pl9AHtmC4CUtLY0vfOEL1NbWUlRURGtrK5GRkYSFhbF8+fIB72WCqceZhMFqfbu6unj88ceZPn06CxcuJDs7WxQuEgyJdj/761//itVqZcWKFcyaNWvK55afjKiKA3vPb4doIWHr/hlm6xWnXEtkOZTY2D/j830Pt+sjVNWNyTwfs3nNkNcdj8dDQUEBACuWr8ZiGVyoHCkJkd/C6TmEw70DzZPzuLUY5FimxT/Vz7bGnufx+Bv0dpIERtWPRzXgQ0JFpm8xGi/CUUAgOJkLLrhgok04KwkaAfKxxx7D5/Px8MMPDyo+9iUhIYGHH36Y+++/n8cee4x//vOfAMTFxXHffffxwx/+kE8//XSszR5XWltbaW1tJSQkhNTU1AGrOSqKQmhoKKtXr6apqQm73c7Bgwe58MILT3mgb21tpaysDJ/PR2Rk5Lifj2Dyoc2fc889F7/fT3NzM9nZ2RNsleBs4OQqtJoY2bf6rBAfBcOheSBNmzZNr0KrbQORny1YGI2/sZb6oaamhpqaGqZPn65HzAimHqqq4vP5MBgMp+Xxql1b6urq6Onpoaenh3fffRej0ch3vvMd4Q15luFxfwhDhiyrKP4qfN5DmMyLB2xhNKZjDL8j4GMWFRXh8XiIjY0NOMd+oMhyCDMS/kmXfSMd9hfw+KowyFFEhd5ITPhtGA1x/dq32F7iZG9Jg6SiqL2+kL0E773Sj4R/nM9/vI8nEIwVQXO306oQrVixIuA+K1f25sI4WWg877zzAGhsbBwl684OGhsbMRgMxMTEDPogpD10zZkzhwMHDlBeXk5RURGLFy8mJiam38tbeXk5Pp+P9PR04VUiGBFpaWnccsstehi2QNCXvmKk9lkgCISBPGr7igliLk1t/H4/TU1NxMbGnnaBqr5zJCkpCZfLRVdXF4sWLRotMwVnIeXl5ZSWlhIXF8fChQsJCQkZUX9t3nR3dxMfH4/P56Ozs5OZM2cK8fEsRFHa6BXYho4t7m03Ohw4cADoLbw4FvciSTIRHX4z0eE3D9vWq7Sesk1RwY9MMAuPAoHgzAmaO15zczMAbrc74D5a25aWln7btdxik70C0cloXiAOhwOLZeDqbhqyLLNu3TrKy8tpbW2lsLCQ888/X79hulwujhw5AogKxoKRo+X9E4UgBALBWHCyiC0IDg4ePMhHH33EunXrWL58eUCebIN5xa5Zs4bly5dTVlZGWVmZSBcyhWlvb2fLli3U1taSnJysOygEglaAQJtDc+fOJSsri8rKSvLz81mzZs2Y2CwYGFVVUPy1gB/ZMA1JGjhyQjZMYzjxEcBgmDYqdjU1NVFbW4ssy2fFtcQsJ+D21/bb5hNh1gKBYBQIGgEyLi6OhoYGNm/eHPDNftOmTQCnhGx3dXUNuH2yoj1cy7KMx+MhLCxs2JBpVVVJS0tj4cKFFBQUcODAAebPn6/nsWlsbKS2tvfGJSrRCkaKSOgvEAgEgtFm3759OJ1OfD5fwPcZTTg6OVQfwGq1smDBAhYsWDA2BgvOCg4ePEhtbS0zZszgggsuQJKkfvNBo6enB5PJhNfrRVVVIiMj+4nX2ryxWCzMmTOHOXPmjOt5BDOqquJx/B237U8o/hoAJCkGS/idWMLvR5L6L3ibLRciyfGoShsDC5EyRtMijKbZo2Lf/v37AcjJySE8PHxUxjwTEiJuprbzdwxctEagqByvDD6+xxRMLn7yk5+Mybg//OEPx2Tc8SJoBMh169bxj3/8g8cee4yrrrqKVatWDdl+165dPPbYY0iSxLp16/rtO3ToEAApKSljZu94cvLKviRJtLS0kJCQMGyflStXUlZWRmdnJ/n5+axbtw5FUSgtLQV6xUeRl00wFNpD/JEjR4iPj58ywr5gbNHmTWNjo16YRiAYDm3BzeVy0dnZSVJSkvCEDBJaWlpoamoiJCRkyNzCbrebrq4ufD4fPT09JCYmEhMTM2Ce0L6h/IKpid/vZ9++fUBvgUatoGLf60ZNTQ2HDh2ivr6epqYmkpKSiIyMJCYmhszMTNLT0/XIooEEbcHY4+x6BI/jGehXubkDV8/v8Hn2Exb7bD9vSEkyEhH1KN0d93JqKLYMGAmPGh1xwev16sVnli1bNipjnilJEV+gxfYybl8d4AdARkGEXwsEgfPII4+MyTOmECAnCd/+9rd56aWXcDqdXHjhhTzwwAN84QtfYMGCBf0eJAsKCnj++ed5/PHHcbvdmM1mvv3tb/cb67XXXkOSpClX2WjBggXMnj2biooK/UFpuIT806dPJz09nZKSEoqKili6dCkmk0mEXwsCRpZlXC4X//73v5FlmezsbLKzs1m6dKl4OBcMinZd+ve//01nZyc5OTlkZWWxZMkSEbovGBTtnvbJJ5+we/duZs2aRXZ2NvPnzycsLGyizROMIZqH0ezZs/VUOn1RFIWioiIOHjzIsWPHMJlMWK1WJEkiOTmZRYsWMXv2bIxGoz6PRCj/1Ofw4cO4XC5SU1P1vz+cuAcdPHiQjz/+mJ6eHr1PfX099fX1mM1mKisrycnJYfXq1f3yjornm/HD5zl4XHyEU70ZVXzuLXicG7GE9s+NaAm5kkjpb9i7f4rfV6pvN5qWEh71CCbz6IiF2hyLiopi5syZg7bzeMvodvwbr68WgxxDROgNWM3Lx+QaZJQjmZf8CpVt36XT+TGgYkBFRkU5qQJ2MKKoMoo6vv/D4308weigeb4LThA0AuTChQt56qmnuOuuu3C73Tz22GM89thjWCwWPWy4vb1dz/uorWj/5S9/6RdaU15eTkVFBenp6VxzzTUTci5jidls7hcSEshNbdWqVRw9epS2tjby8/OZMWMG7e3thISEDHkjFUwtTvYKCWTuaO2OHj0K9M63kpISampqWL58+ZjaK5hYzrTasCRJdHV10dnZCUBJSQklJSXMnz9fCJBTmDP1GtL6al76Wv6+0NBQEUY7xcnPzwd6i+gZDL25zLT5ZLfb2bVrl150UEtJoxVC6+7upq6ujpqaGtavXy8iO4KI8vJyADIyMvTCM9r969ixY7zzzjv4fD6sVivx8fHExcWhKArHjh2jp6eHxsZGPS3RNddcI4oyTgBu+z8AA5on36lIeOzPnyJAAlisF2G2rMfvO4yitCEbUjEaR/fdZrjiM6qq0tb1Mzpsf6L3PFRApsv+HKHWS0iJ+zOyNLKiSIFgNiSQk/g0bl8tdncBSAYkKZqDTV9BUV2o/X6fIj+kQHAyiiJSGAxE0AiQALfffjszZ87kgQce0MOoXS4X9fX1p7RdtGgRjz/++Cn5ImfOnEllZeW42DsZUBSFzMxMcnJyOHLkCAUFBZSVlQGIipBBQF8RSZIkPB4PZrM5YGFJaxcZGcmCBQvo6Oigrq6Oc889d8xsFpwd9A1DO10vIp/Px4IFC+js7KS+vp4ZM2YIL7YpjiYgag91pyNGulwuZsyYQUhICO3t7fh8PubOnTuqdgrOLkpKSnC5XCQkJDBt2omiEdr8+fTTT/Xnwvj4eBITE5k+fTrNzc1UVFTQ1dWFzWZj9+7duN1uLr/8crHQEQRoxSa1e5QmXEuShKqq7Ny5E5/PR3Z2NsuXLycnJ0fP/+jxeCgtLeXAgQPU1dVRXl7O/v37Wb9+/USe0qRHVf0o3gJU1YZsyEQ2pg3bR/GVMrj4CKDi91UMuleSJIymeSM3NgBUVSUzM5Pu7u5Bo8Y6bX85Lj7CifPovQc6XB/S3PEdkmP/MCb2AViM07AYp+FTbKAqrEz5N+Udv6PVuRUVL0Y5gvTIa4DJHRYqEAjGh6ASIAHOO+888vLy2L17Nx9++CGFhYV0dHQAvdWt58+fz0UXXcTq1asn2NLJgSYanHvuuVRWVtLW1qY/0J8NVdwEY4uWL3THjh2oqorBYCA+Pp6ZM2eSmJgYsJdbRkYGGRkZdHd3U1ZWJsSAKc4nn3zC7NmzSU1N7ZdXrW9Y42D0nVNxcXF85jOfwWazceTIEZEHcorz8ccfEx8fz9y5c/UwSAhMxO5bidZqtbJhwwYcDgclJSV4vV5dWBBMTbTw6zlz5ugFHjTvx+bmZvbv34+iKGRlZXHNNdcQHR2t91UUhUOHDvHpp5/S1tbGoUOHmDNnDrNnj07xCcHZiaqqGI1GTCYTqqricrmQJAmfz4fRaKSlpUWP3rj44ov1+4/mHWs2m1myZAlxcXFs2rSJhoYGdu3axaJFi0Su69PE43gJd/dvUZWG41skDJbzCYn6GbIxY9B+khzBqXkcT2ojTUzhFy2l19q1awfxfvTS0fN/Q4yg0ON4lbjI72Iypo6Jjc32t6np+is97iIUJBSMqHpxGpk46/mkmm8jmATI3t/DOBehEfk3BVOEoBMgNVatWjVsIRrB8GirwNOnT2fmzJkUFxejKArx8fEkJydPtHmCMcTv97Nnzx4++eQTPUwNICwsjLq6Oi6//PJ+lfxODtGGU5OxR0ZGnjUJuAVjQ1lZGVu2bGHHjh0kJSUxd+5c5s2bR3R0dECFHfo+oGvzJjw8nBUrVozbOQjGH5vNxtatWwGIjo4mOzubBQsWkJ6e3m+eDCZGDlSJNjQ0VOQpDgLsdrsect93cUubB/v27cPr9TJ79mzWrVtHdHS0vk+7Di1ZsgSTycTGjRvx+/0UFxeTlZXVTwgXTC20a4YWdt3S0oLL5dLzOFZVVQG9OUUTExMHTA8hSRLp6elcffXVvPTSS3R1dVFRURH0AqTiK0fx7AUkZPOqIcVDDbftL7i7f3rSVhW/ezu2lg2EJ7yFbEwfsK8p5Bp87i1DjG7AHHJdgNaPDYMtoLk9BfiVtmH7O1wfEhV+22ibRWXH76nuehyQ8SMdz//YN6xUodmxmYa2g6N+bIFAMDURT06CM0a7aebm5lJRUYHL5RK5tIKAPXv2sH37djweD2FhYURERNDc3IzdbqeoqAiv18tnP/tZ3bPI5/PR2tpKYmJiP2+jvkLTmeYFFJz9HDzY+5Cqqiq1tbXU1taydetW0tPTmTdvHjk5OYSEhJwiTjc0NFBWVkZSUhLZ2dlIktRv3kBgOWsFk5O8vDyg17uos7OTvXv3sn//fl3Enj9/PrGxsf1CtGVZprOzk5KSEkJDQ5k3bx4Gg2HQhRDB1ESrYBwSEkJxcTGyLJOQkIDBYEBVVYqKigBYvHgxSUlJwIk50XduzJ8/n8rKSvbv3095ebnwmg0SFixYwM6dO6murmbHjh16CLUWPZWSkjJoX+2ZJjExkbCwMLq6unC5XONi99mI6m/B0/kNFM+n/bbLlvWYo3+NJMcO2E/xt+PufnSQUf2g9uDq+S2hMb8fsIU5ZAPunj+i+Gs4NRTbAFIolvA7R3Yy44SiBjJfJBTVPerH7nEXHBcfQVUVlEHyPKr4cfpOTWc2lfGrEn51fJ8dxvt4gvGhrKyM559/np07d9LY2IjT6WTTpk3MmjVLb1NYWEh1dTVhYWFToghyUAuQdXV1NDY24nA4WLFihb7KKTg9pk2bxre//W3q6uqIi4ubaHMEY0hbWxs7duzA4XCQkpLClVdeSUxMDHa7nS1btnD06FG9MFFMTAzbt2+ntLSU1tZWFEUhOzubZcuWMWvWLN2LVlQTnfr4/X7dE8lgMGA0GnG5XLjdbkpLSyktLSU8PJyZM2cyf/58srKy9Jf8Y8eO8dFHHxEdHX1K6KOYN1OfvoWqQkNDcTgcKIpCQ0MDDQ0NbN++nenTpzN//nzmzJmjeyk1NjayZcsWnE4naWlpetE5bSzB1Ke1tRUAp9PJp59+yqeffkpWVhZLly7FbDbj8XiIj49n+vTpg84JTdDWqmdHRUXR1dXVL1RbMPVQFIWEhASWLl3Knj17yMvLIyIigpUrV5KTk8POnTupqakBBs5H23chLTExkfr6eux2+7iew9mCqthxt92M6q8+ZZ/i3oK77XNY4l9Hkiyn7Pc6X2PoHI5+fM43UaN+djzcuj+SFEJ4/L+xtX0RxVfEiddfH5KcSFjs08iGsQlfPlPMpmyGLqADoGAZgxyV9T0vImFAxY9fD2Ef7L4pim0IBCNBURS+853v8L//+78oitJvUbxvZCFATU0NV199NUajkcrKStLShs99ezYTdAJkT08Pv/nNb3jmmWf6FZ8pKChg3rwTF+8XX3yRjRs3EhUVxV/+8peJMPWs48iRI4SEhJCenj7oQ7okSf0SvAumJvn5+dhsNjIzM1m/fj3Tpk3D7/cTFhbGihUrOHr0KLIs09rayttvv01NTY2eI9Lv93P48GEOHz7MggULuOKKKwgNDZ3oUxKMMdrf/4orruDdd9/FbDazevVqXC5Xv1y8NpuN/Px88vPziY2NJScnh+nTp+sveVlZWUCvR21fbzbB1ObKK6/k5ZdfprOzk9zcXCIjIzl48CANDQ34/X7cbrde0frDDz9k1qxZZGdnU1tbi9PpJD4+ntjYWPx+P7Isi3kTJKiqynnnncfs2bOprq6murpaLyxTUVGBxWLB5/ORmpo6ZGVrTVyyWq0YjUa8Xq+YQ0GA9ndftmwZpaWldHR08M4771BbW0t6ejqhoaE0NDRQWlpKdnb2oOlDfD4fzc3NAKSnDxwmPNlQVQXF/SF+xz9RfeVIUiRyyHUYQm9Ckk+t9O13vozqP8bAeRj9qL4j+J1vYgy98dRj+evpfWX1DmGRD0VpxTCAAAkgG1KJSHgXv2cXXvc2wI/BtBST9WIkaWxeh0cjqsdoSCA85EpszncYWIQ0YDKmE2LJPaPjDESna9dJla4FGooqo6gjL4J3pscUTB2+9KUv8cwzz6CqKmlpaeTm5vLKK68M2PaKK64gKyuLyspKXnnlFb72ta+Ns7WjS1AJkGVlZVxxxRVUVFToKjMM7AWRm5vLbbfdhqIo3H777Zx33nnjaepZh6qqbNq0ia6uLj772c+KIiFBjlYtdP78+Xr4kfbAreX/rKurY/PmzTgcDubPn09qaiodHR20t7fT0NCgF4CIjo7moosumrBzEYwP2nV23rx5VFdXk5eXR1NTE9deey1r166ltLSUw4cPU1FRoXuItLe3s3PnTnbv3q33z8jIANBzr4kw2qmPqqokJyezcuVKNm/eTGlpKTfeeCPLli2jtraWoqIijh49Snt7O9ArYufl5ZGfn6/Pk+zsbADdo1bMm+BAkiSSkpJISkoiKyuLtrY26uvrqa6upra2lp6eHqD3/jWUAAm9c8btduPz+QgNDSUq6lSRRTA1SUpK4pZbbuGdd96hqqqKoqIiuru7kWUZm83Gjh07iI6OJiEhoV+KB0mS8Hq9lJSUUF9fj9lsJicnZ4LPZmgCuTaqqg9f51dRXJvQvPNUwN9zGL/9acxx/0I6Ka+jzzHwi/UJJPzOVwYUICU5hqE9AHv7S3L00C0kCaMlF+MYiHUafUXH0Ur3kRD9U1yePHz+evr/HgxIkpXk2D+N+r2spusZXL6aUR1TIBD08sknn/D0008jSRLf+973+PGPf4zBYBjQk17jpptu4pe//CUff/yxECAnC263m6uuuory8nLCwsK4//77Wbt2LVdfffWA7WfMmMG6dev48MMPeeONN4JegKyrq6Orqwuz2dwvJ4Eg+Kivr6erq4vIyEgyMzP1F3otlNpiseB2u1FVFZPJxM0339xvzvT09HD48GG2bNmCw+HgwIEDnHPOOUREDLxqLZhaWCwWLr/8cpqamjh06BAhISFcfvnlzJ07l7lz5+rCdHFxMTU1Nbjdbr2wCMBbb71FXl4e8+bNY86cOYSFhU3wGQnGGu1vv3r1apqamsjLy+PNN9/k5ptvZtq0aUybNo1LLrmE0tJSioqKdBFbVVV8Ph+SJLF3717q6+v1okfiehN8hIWFERYWRlpaGjk5ObS0tFBbW6t77Gs5IQctBnHcyxZ6q2kLggdVVUlMTOTCCy/kk08+oaqqimPHjgG916djx47xxBNPsHjxYhYvXkxmZiZutxuXy0V+fj579+4FYPny5Wdl4SJV9aM6X0VxPA++EsAIlnUYwu5GMp9aGNBvexLFtVn71HckUFrxdtyLKX5z/+JfSitDVaEGFdXfMuAeU8gG3D2/HqKvAYPlPGQ5Zog244PP56O9vZ2Ojg69SGffgoyng9GQSHriO3TY/kyX7e8oahcSZiJCP0NMxP2YTVmjZH0vTm8NFR2/7LdNQgUGF0ekQfJDCgSCU/nzn/8M9Eb3/OxnPwuozznnnAOg562ezJx9d8Ex4s9//jOlpaWEhYWxbds2lixZMmyfK664gg8++ICdO3eOvYFnOYWFhQDk5OQM6yUgmNpUVFQAkJqaisVyIleP9uLW3d1NS0sLRqORdevW6SGzWg6tiIgIzjnnHFRV5f3338fhcHD48GF9m/BImtpoIvX111/Pyy+/zO7duwkNDWXt2rXAicrES5cupauri927d3PgwAHc7t4E6x6PRw+f3Lx5M0uXLuWKK66YyFMSjAPateHKK6/E6XRSUlLC22+/zXXXXYcsy8iyTE5ODjk5ObhcLg4cOMCuXbt0Dzefz0dVVRVVVVVs2bKFGTNmcNNNNw252iyYmhgMBmJiYoiJiWHGjBnMmTMHs9k8ZB9VVamqqqKyshJJkli4cOE4WSs4G+jrgX/HHXdQWFhIXl4eVVVV+Hw+vZ2WPiQkJISkpCTq6+vx+/34/X4WLFjAypUrJ+oUBkVV/SidX0d1vwN6nj8vuD/E7/4AOeo3yCEb+rT34nc8y+Bioh/VV4bq2YXUx9NQMqShKs1D9DMgGQbOayYb0zGF3obX8cIA/WVAxhrxrQDOdmzJz8/n0KFDVFRUYLVakSQJk8nErFmzWLFiBSkpKQNWSw8EgyGO+KjvExf5PVTViSRZkaSxuX812l6h9/faKy6rKviRGTwHpIQsDX0NnWooSCjjXBRGGTT/pmCysXPnTiRJ4q677gq4j5birrGxcazMGjeC5sl748aNSJLE1772tYDER4BFixYB6EUTghVFUXS1XVS3FnR1dQEQFxfX76VNCzEpKSkBenP1zZw5U3/Q6luxWFVVzjnnnFNWhYX4OPXRPGUTEhI499xzMZlM7N27V583fr8fRelNZh4VFcWsWbP0ubVkyRLi4+P1gkVer1cUDwsStHljMpk499xziY6O5vDhw+zatUufM1oSb6vVSnZ2tr5AMm/ePFJSUvRrkNPpxOfzCfExiNGuKRaLhdTUVOLj44FT70HataipqYkDBw4Avdchkbc4ONHmw7x587jqqqvYsGEDK1asICEhoV87p9PJsWPH8Hg8yLLM4sWL9WJ9Zxuq89Xj4iP0F/f8gILS9e1+nomqrwqU9mFGNaB4dvfbYgy9haE9IP3H2wyMNerHmMLuATQniONhznIyoXF/x2BePIxNY4ff7ycvL4+33nqLiooKJEnC5XLhdDrp7u6msLCQLVu20NHRgSzL/dKAjRRJkpDl0FETH3tc+yhteZADtas4WJtLZdv36HHn0beojE8XviRUFXyqjEc14FEN+NTe81mY+Nio2COY/Lz77rv6c7okSTzyyCMB9SsqKuLLX/4ys2bNIiQkhISEBNauXcuTTz7Zb6FnOF588UUuu+wyUlJSsFqtZGRkcNttt7Fr167TPKPRR8sJnJmZGXAfzXve6x0qF+7kIGg8IIuLiwG49NJLA+6jVXLu7OwcC5MmDdXV1dhsNqxWKzNnzpxocwQTiMvl0m8CBoOhnzes9jKv5YfMycnRK9H2RXvBczgcREREYLPZsNlsY2264CxCmwNLliyhubmZnTt38vHHH5OUlER0dLT+kudwOCgtLcXj8ZCcnMy1116LoihUVFRQVFTE4cOHA15QEkx+tHmTnp7O2rVreeONN/j0009JS0tjxowZeqi+1+ulrKyM1tZWjEYjN910EwCVlZUUFRWRl5fH8uXLJ/JUBBPISDztZVnG7/ezbds2KioqiIqKYunSpWNsoWCiGWiO9N2mVUSPjo5m1qxZOBwOuru7qaqqorm5WV/8iIuLIysri8TERIxG41kZ5aE4/sYJz8cBW6A6X0IKv/+MjmMI2YDP8SKqN49TKybLyObVyNbB39EkyUBI1P/DEv4VfO4PQbEhG2disJw3Zp6AgXL06FG2bNmCz+cjJiaG9PR0ZsyYQVVVFcXFxXg8HkpKSujs7OS22247a1LH1Hf9mZrOX9K3ynaz7SU8KvRKBCqqCioSHPf485wUaq0g4UOm2bFlfI2fYFSkcfdIVCeBB6Tdbue+++4bcb+nn36a+++/X492gt53zm3btrFt2zaee+453nrrLV2bGQiXy8VNN93EW2+91W+7Fv3yz3/+k0ceeYQf/OAHI7ZvtAkJCcHj8eBwOALuU11dDXBWLmSNlKARILUwrJEkDXe5XABBH3KseT/OmTNHz/cnCE6MRiORkZFYrVb9Atj3gVoTikJCQoZd1fH7/VgsFvx+v/AmCUK0eXPxxRfjdDrJy8tj48aN3Hrrrbpw3d3drd9wNY90SZKYNWsWs2bN4sorrwz663OwsnTpUux2Ox9++CEbN27ktttu073Y7Ha7Pm/mz58P9M63zMxMMjMzufTSS4cNuRVMDRRFwe/3Y7PZkCSJ6OjoEQlAfr+foqIifRF7xYoVTJ8+fazMFUwgfZ9lVFXFbrfjdDrx+/0kJSUNOG8kSSIkJISQkBDi4uL05x6v1zvgvelMxEfV34zieA7V+SooXSAnI4feghT6OaRBKj8PO6aqHM/5OGQrVO+JnGOScQbIscN4QfqRzav6bZEkC5bY5/F2/wy/81VOVLS2YAi9GVPkwwFVo5YNsZhDbxq23Xiye/duOjs7yczM5JJLLtGLMy5dupSLL76Y999/n6KiIpqbm9m1axfr1q0LyAN/NAVrRXFic+9AURxYTLPwKt3HxUfon8fTjwEJpZ9I3Ov5eEJ8PNkmlWPdr42KnYLJzQ9+8AOqqqpITEzUvfyGY/Pmzdx7770oikJSUhLf//73WbVqFe3t7fzlL39h48aN7Nq1ixtuuIGPP/540P+du+66Sxcf161bx9e+9jVSU1MpKCjg5z//OeXl5fzwhz8kJSWFu+++e9TO+XTIzMwkLy+PgwcPkpsbWFEs7dzmzZs3lqaNC0EjQMbFxdHY2EhTU1PAfQoKCoDe6nfBiqIo+oO39iInCF6MRiO5ubmkpqYO+BJmNpu5/vrrcbvdw77gezwe/f9Rq2wsCB60kFpZlsnNzaWxsZGamho++eQT1q9fj8FgoLGxkYaGBuCEAAknwuCE+BicaC9lS5Ysoba2lpKSEj788EOuuOIKIiMjaW5upqamt3rnsmXL9D5a2JvZbD4rPZEEo0t5eTkFBQVUVlYSGhqKyWQiLi6OuXPnkpWVFbBHWkZGBtdffz0ej4fZs2ePk/WC8UabB4cPH6a4uJiysjKsVitWq5WoqCjmzJnDnDlzsFqtg3pIavc0k8k0qtcY1VeJv/0WUDrQvQeVWhTbY+B8HUPcv45Xih4pEr2vgkOFN0rQJ7+fJJkwhN2Jv+cxBvaaNCAZs5DMq08dSQ7DHP0oauR3ULyHAAnZtBhJjjwN288OmpubqaqqIiQkhPXr15OcnAyceE4JDw8nNzeX5uZmGhsbOXjwoJ4WZKA50tPTQ0tLC1lZWaMyf1RVobn7jzR3P4Gi2vXtfmLo6/nYFxkVCRVVz/sIPj1r28A5INVTvFoFwcaBAwf4wx/+gMVi4Wc/+xn33nvvsH18Ph8PPPAAiqIQGRnJ9u3b+0VbXn755dx///088cQTbN26lb///e984QtfOGWcLVu28M9//hOAa665htdee013mlq5ciUbNmxg+fLlVFdX8+1vf5sbb7yR6Ojo0Tnx0+DSSy/l4MGDPPXUU3z5y18edkFi//79vPDCC0iSxOWXXz5OVo4dQZMASQvT+/DDDwPu88wzzyBJEqtWrRq+8RTl2LFjOByOgDzaBMGB1WolJydH91rsV+Xw+AO4xWIZ9sGppqYGm81GTEyM/sAmCC60OaJVFzUYDOzevZujR4+iqirV1dW651pYWJj+sK4VHREEJ9q8CQ8PZ926dURGRnLkyBHy8/NRVZX6+nrsdjtRUVGkp6cD6HNGmzdCfJy6eL1e8vPzefHFF8nPz6e7u1tf4CgqKuLjjz/WF1aHmwcGg4HIyEgWLlzIihUriIycvEKJYGg8Hg95eXm8+uqrFBYW4nK56OzspLGxkbKyMrZt26bnAR3MG7LvfWnUxEdVxd/5NVA6OTV0WQF/JUr3T09rbEmSwHIBDFnBWEGyXNhviyHsS8hW7SW4r1ecBHI8ppgnhzx/SY7GYFmLwXL+pBYf4USRzpkzZ/bzlO17v0lOTubyyy9HlmXsdjv79u0DBp4jhYWFvPDCCzzzzDOjYl9D5//Q2PXrfuIjgFftZiDxsdcuMOPDKFmRpN6/rKL9fQfl9PNaTkYUVZqQr7MVv9/PPffcg9/v53vf+x7Z2dkB9XvttdcoKysD4OGHHx4w1duvf/1rPeru17/+9YDj/OpXvwJ679lPPPHEKRGb8fHx/PKXvR6/HR0dPP3004Gd2BjxwAMPEBISQkFBAffcc8+QeR1fffVVLr/8cjweD5GRkQEJu2c7QfMGd8MNN6CqKk8++SRVVVXDtv/xj3/M7t29CZRvvvnmsTbvrEW7sc6dO1eEXwuAE8n7B0JLODwcnZ2demi/yKclgN6coRs29FbafO2119i2bZseRtvXi00g0FBVlaSkJK6//npMJhMfffQR7733HhUVFQAsXtxblEDzRBEEBwcPHtTzsYWFhZGens7ChQuxWq14vV4aGxt57bXXRpSQXgjWU59Dhw6xZcsW/H4/UVFRZGVlsXr1auLj4/H7/bS3t/P+++/z/vvvBzymqvpRXR+gdNyH0nodSseXUF2bUdXACyrgKwBfMYOJReBHdb2NqrQFPmYfDGH3cqqwqe8FOQXJekW/rZJkxBj9fxhjnkKynAeG6UjGeRgiHsacsBnJmHFatkxG6uvrAUhJSRn0PUlVVWbMmMHq1b1eoYWFhfrzTV88Hg/l5eVA73vXmeLx1dDS85fT6itJEGWexeLkf5AcdgVDi4+CYOd3v/sdBw4cYPbs2XznO98JuN/rr7+u/3zHHXcM2CY0NJTPfvazQO//zsnFgW02m+5gdskll+jVok/mhhtu0BcRN27cGLCNY0FaWhp/+MMfUFWV5557jqysLL7yla/o+59++mnuu+8+srOz+exnP0tbWxuSJPHUU0+NKJ3g2UrQhGDfcccdPPbYYxw5coQLLriAxx9/nCuvvFLfL0kSiqKwfft2fvWrX/HOO+8gSZLuthuM+P1+jhw5Aojq14ITjMaLWEFBAceOHSMsLIyFCxeOglWCyY6qqsydO5eqqioOHjxIXl4e3d3dyLKsP4gLr0dBX7Qw/vT0dNasWcOnn37KoUOH9JVkTYAU4lHw4PP52LVrFx0dHaSlpXHttdcSFRWF2WxGURT27t3Ljh076Onp4cCBA8yaNUvPHToUiqKI688URlVVdu3aRWdnJxkZGVx55ZXEx8cjSRKXXXYZxcXFfPLJJ7S2tlJYWEhOTo7uXT34mE78bfch+3agh7r6jqC6PwbjMtSIbyPJZjBkIcmD58FWj4cqD1dBWvUeQbKsGfG5S+blyFG/Qun67vFjKPT6pyggJ2CIfR5JspzaT5IxWC/GYL14xMecKnR3d6MoCgaDAaPROOg1om/hvcLCQrq7u8nLyyM9Pb3ftaW5uVkXIEejwF6H/VV6/5b9xWuf7kmnMriwKBMdspZo60rCzQuosm1DxT1IWxjai3bqoagyijq+94TxPl6gHDt2jB/96EcAPPHEE3oRrkDYtm0b0OuEMFQ03AUXXMCTTz4JwKefftrPw3LPnj168ZoLLrhg0DHMZjOrV6/mvffeY8+ePYPm6h0v7rrrLiRJ4qtf/Sp1dXU8+eQJz/H//d//BU44XlgsFv785z/rRRUnO2fnTB4DDAYDb7zxBgkJCVRXV7Nhw4Z+oTTXXHMNUVFRXHjhhbzzzjuoqkpKSgovv/zyqNvS2trKr371K9asWUNycjIWi4XU1FRWrVrFQw89xM6dO0f9mKdDZWUlTqeTsLAwZsyYMdHmCM4S+nqh9c2rFiiFhYV8+umnGAwGFi9ePKE5OATjx3DzRpIkTCYTF1xwASkpKXR3dwMnvK+FF1twEsi80fKIZmVl4XA48Hq9pKSkEBsbK3I9BhmFhYV0dHSQnJzMVVddRUJCgp7zU5Zlli5dysKFC1FVlZaWFnbs2DHkeFoxQiE+Tm0OHz5MW1sbCQkJXHbZZSQkJOgLHND7crx8+XJkWaa7u5vt27fj9w/mkQhutxu1++fIPs3LVmt7/D7mOwAdt6C23YDavBql+39QlcGqoZoIJLxVkk7/RVoOuR5Dwlbk8AeRLBcjWS9Hjvo1hoQPkYwi/dJgmEwmvF4vfr9fFzKGeiZOSEhg1qxZQG/l7Pr6emRZ1vscPXoUgOzsbEJCQs7YPq+/mZMFRr8q4Ru0mAz6dgkTieG3AFBv24QypPgIg3voCqY69913Hw6Hg8997nNcdNFFAfez2WzU1tYCvYVuh6Lv/sOHD/fb1/dzoOP4fL5TPCkngi9+8YscOXKEb3zjG8ycOVN/ztW+0tLSuO+++zh8+DC33377RJs7agSNByT05ufIy8vjnnvu4e2338Zu782HoaqqHrKlcemll/Lss8/qlcxGi5dffpn77ruPtrb+oRINDQ00NDSwZ88eSktL+7kkTxRaiOzcuXPFw3eQ0/clXpIkPB4PZrN5xC/2bW1t5Ofn4/F4mDdvnh5aK5ia9F3ZlyQJh8NBaGjooPNGVVUiIyO58847KSwsZMeOHaPiBSCYXJw8b3p6erBarYOuVKuqitls5r/+6784cuQIn376qe79KATI4CI/Px/oLZqneVP0nQNms5mLL74Ym81Gfn4+Bw8eZOnSpQMWVVNVla1bt7J//36uvfbaKVF5UjAw2ryZN29ev8KT2rwxGAysWrWKrq4udu7cydGjRykvLx+0KNGe3VvYtk3l8jUZLJlTMWCbE7jA8QKqNx9iXzjF21CynMewHpBSOJgWDb4/ACRDElL4g2c0RrBhNBrp6OgAGLbwosb5559PUVERdrudvXv3cu211yJJEna7XY86W758+ejYZ0ik77xRVa2YzFCejyBhYnbik5iNvf8LdbZ3GW4OGqXBvXinIhORk/FszAH5z3/+k02bNhEdHc1vf/vbEfWtra3VxffBwqY1+t6jtSKDA30e6Thnw3192rRp/OY3v+E3v/kN3d3dNDc34/f7iYuLCyhCYzISVAIk9CYCfvPNNykqKuI///kP+/bt6/eHXrp0Kddeey0rVqwY9WM///zz3HnnnSiKQmJiIvfddx/nnXcesbGxNDY2Ul5ezptvvnlWVHbtG34tql8LJEmiq6uLvXv3Yrfb9UIzGRkZZGZmDloV8mTCw8O57LLLmD9/PtOnTycuLm6czkAwEciyTGtrK3v37qWzs1MPU0pPTyc7O5uoqKhTxG1VVTEajSxZsqSf+CgWQYIHWZapr69n//79NDU1YbVakWWZtLQ05syZQ1JS0oDzRpIkvVJt37EEwYH24G40GklNTe03PzQ0cTs3N5fq6mo6OjrYvXs3aWlpp8yVnp4ejhw5gsfjGVFImWByYbfbaWpqQpblfvOmL9q8WbVqFZWVlTQ2NrJ7924yMzNPeWZ3OBwcLj6E12fEYAjUc18Bbz44Xoawz/fbIxnSkCxXoLo3MXCuRgkp9E4kyRrgsQSjhd/vZ9myZVRUVNDS0gIMnfJDURSio6NZunQpu3bt4ujRo9TW1jJt2jRqa2tpaWnBYrGQk5MzKvbFhN1AU9dj+mcVUAPI5Zge8zDRISdCWb1KN8N64UrBFYI9kWgRQhoWi2VC7lHt7e18/etfB+DRRx/tt3gTCD09PfrP4eHhQ7YNCwvTf7bZbGMyztlAZGRkUBS7CzoBUmP+/PnjKqwdPnyYe++9F0VROP/883nzzTcHTCL64IMP4vF4xs2uwaioqMDlchEeHj5snhvB1Gf//v1s27aNrq4ufZvZbObo0aPMmjWLCy+8sN9FfTC0m2RcXJzwSpriKIpCXl4eH330ke5tDr2eJJWVlRw7dox169adIkJr80JRlICLGgmmDj6fj4KCAt577z09/BV650VtbS3V1dVceOGFp3isiXkjaGlpQZZlIiIiBl3I1UTGpKQk5syZw86dO6moqKC2tvaUfGyaQBkRETFgZU7B1EBL7h8WFobROPBrkTYnoqKiWLBggV5V/dixY2RnZ/ebN7W1tTQ02TEZfSyYdWxEtqjOF5FOEiAB5Kif4+9oBe8e9HySx79L1muRwx8Y0XEEo4PVamX9+vWsWrVKz0E31GK8NkeWLVtGcXGxngsyLS1NDyMdzbzoFmM68RF30drz117bAiokc2q163BzFt2eEtRBw6xlwkzpwO4zMVcQICc///zoRz/ikUceGXc7vvWtb9Hc3MyqVatOqzJz32e84TyI+wqsTqdzTMYRjB/CNWCcePDBB3G73cTHx7Nx48YhKxgF6sY/lojwa4HG3r17+eijj3TxMS4uDqPRiMfjobOzk3379rFx40Y9DCUQhDgw9dm7dy+ffPIJdrsdSZJISkoiKioKv9+PzWajqKiIl19+Wa8geTKyLIt5EoTs37+fLVu24HK5MJlMpKamkpaWhqqqOJ1OKioqeOmll/RcWScj5k3wIkkSfr+fnp4eQkN7wwGHyseWm5uL2WzG6XTqIbja847P59MFAZEGYmojyzIej4eenh59IXWoebN8+XLCw8Pxer0cOnRIzy8KvQsg2rxZPLuSkV2KVPDXDrhHksMxxP4dOeZpJOtVYD4XKeQGDLEvIUf9Gkl4n00IWp62sLAwYmNjgcCebxMSEvRFjZKSEsrKyvTiM6Odmig1+gckRX0TWQpFCiCXKKhYTf0dT2ZE3jiE+AigkB5x/RnZOdlQkCbkC3pDh7u6uvSvhx9+eFA7fT6fvih7Jl/PPfdcv3E/+eQTnn32WQwGA3/+859PSyuwWk94bQ/nfKUJ/MAp+VFHa5zxpKenh5/85Cf85Cc/obGxcdj2DQ0NevupIJwGrQfkeHLkyBG9PPwDDzxw1sfzi/BrgUZbWxuffvopTqeT2NhYLr74YhISEggPD6e0tJQ9e/ZQW1tLZWUl+/fv5+KLLw4oFFtUFJ3adHV1sWPHDux2O/Hx8Vx11VVERUURHR1NdXU1u3btorS0lKamJnbv3s21114b0HwQ82Zq43A49ArFiYmJXHvttURERBAREUFHRwc7duygoKAAm83Gnj17mDFjRkBhR2LeBA9Op5Pw8HBdSBoq32xERASrV69m69atFBUVsXTpUj1/VFtbmy5yL126dHyMF0wIiqLo+Yk14XqoeWO1Wjn33HN57733OHLkCMeOHSMzs7dQS0dHByUlJQAsXZzICW/FAJEiBt8lyUiWC8AyeJVXwfhyJotdK1eu5MiRI9hsNt566y1sNhtxcXGjXntAkmSSo/6bhIh7sbk+5VjHL3D5qhgsnN8kxxNlPb/f1ljLUmZEfJaqnpcG7JMQkktq6GWjardgcCY6TNftdvOlL30JgK9+9aunvUgXEXHiejdcOHTfSKqTw6xHa5zx5PXXX+eRRx4hOzubH/7wh8O2T05O5h//+AdlZWXMmTOHz372s+Ng5dgx5QTI6urqMRn3TMKQ+1bS7ls+vaOjg9bWVmJjY8+qXHjl5eW43W4Rfi0gPz+f7u5usrKyuOCCC/rNh4ULFxIbG8t//vMfWlpa2L59O5mZmUOGqvX09BARESHEgCnOoUOH6O7uJiMjg4suuqhfUugZM2YQHh6Ow+GgurqaQ4cOkZWVpRcNGQi73U5YWJiYN1OcgoICuru7mT59OpdddhmpqalA70t/TEwMF1xwAQ6Hg+LiYsrLy9m7dy/nnXfeoONpooKYN8FBVFQUqampdHd3U19fT1ZW1qBttbyhS5cuJT8/n66uLg4ePKhfq8rKyvD5fEyfPp2YmJjxOgXBBBAXF8eSJUsoLy+nrq5uyCqq2rxZvHgx+/fvp62tjYMHD5KRkYEkSZSXl+N0OklKSiJl1ldR20vAV36893DeZzKEXDtq5yU4e1EUhZSUFObNm8f+/ft1UWQsva0NcihRoZcyyziN4sYbUVQP/cXx3vtkZtwvkKT+8oAkSSyM/x7h5kzKO5/D5W8CwCRHkRl5C9kx92LrmfxeWSNhshShMRqNp1SNPh36CuMbN27k6NGjGI1G5s2bx4svvnhK++LiYv3nwsJCvc2qVav0BZu+7wZaNezB6Fto5uQQ9JPHGaqOx1DjjCcbN25EkqSAhURJkrjlllv46U9/yssvvywEyLMNbVKPJpIk4fP5Trv/rl27gN6H47lz5/KPf/yDX/3qVxw6dEhvk5mZye233843v/nNCVXk4cRFY+7cuSKULcjRwtKWLFmiX6j7ejimpaVx3XXX8eqrr9Le3s5HH33E9OnTB0wj4HQ6+fe//01XVxd33HHHWSW6C0YXbd4sWrSItLQ0oP+8iYuL4/rrr+ell16ioaGBLVu2MGvWrAHziHo8Hl577TXq6+u57bbbRt07QHD2kJeXB/QubvQVH7V5Ex4ezoYNG3A6nVRWVrJ9+3bmz58/oEDk9/t59913KS0t5ZZbbiEjI2O8TkMwQcTFxXHPPffQ09ODwdAbkjqUR74kSURHR5Odnc3+/fs5evQojY2NxMbG6mloRqsareDsJSwsjGuvvRav14ui9HqFDTdvQkNDmTNnDjt27KCsrIy6ujqSk5P7zRtJjoHYl8H5KqrzJfA1Ai7Ay6lipAGkCKTQ28bsPAXjg6K6sDtex2b/N36lCaMhjfCwWwkLuRpJ6s1Nq82tFStWcPToUb2Ixnikewgzz2N+8qtUdzxKl2tbn+0LmB79HaJCzh2wnyTJZEV9jszIW7D7alFVhTDTNGRJy7cbXALkZGKoRZXTQQtj9vl83HPPPcO2f/XVV3n11VcBePbZZ3WtJjw8nOnTp1NTU6NHXg5G3/1z587tt69vJetAxzEajcyaNWtY28cKzY5zzx34/20gcnNzgf7i7mRlyrkFaPk4RvvrTNAmSkZGBg8++CCf//zn+4mPAJWVlTzyyCPk5uYOmhNtPPD7/Xr4iAi/Dm7q6+vp7u4mMjJyyIqiqampLFmyBFmWaWho0Of7yf83DQ0N1NXVYbfbhUfJFKa5uZm2tjbCwsKGnDfR0dGsXLkSo9FIR0eHLlqePG9aWlp0r5KhcucKJjft7e20tLRgtVqHnDcWi4XVq1djtVpxuVzs378fOHXetLe3U1paitvt7heeI5j6REREDBtK25cVK1ZgMpmw2Wzk5+fT3NxMQ0MDsiyzYMGCsTZXcJZgMpn0lA6BzJulS5ditVpxOp3k5eXR3NysR2EtWrSodxw5DCnsC8jxbyEn70NK3AqmVcdHkOkN0QYM6Uix/0AyjKyKrODswq900NB8NW0dX8ft2YPPV4nLvYPW9q/Q2HIjiuIATsyvhISEXrFakvTokPEg1DyXOUnPsyRtB/OSN7I49RMWpPxnUPGxL5JkINw0gwhzZh/xUSA4PbQolpKSkiFzIW7ZskX/ec2aNf32rVy5Und86dvuZDwej+4U1rfPRKB5fI7EqSI5ORmAurq6MbFpPJlyHpDPPvvskPufeOIJ9u7di8lk4tJLL+Wcc84hKSkJVVVpbm5m7969vPfee3i9XlauXMl99913xja1t7cDvWp3fn4+0dHR/OIXv+CGG24gMjKSgoICfvjDH/Luu+9SWFjITTfdxLZt24YMG3O73f0SqXZ3d5+xndC/+vVEuiYLJp6GhgYA4uPjh60MuXLlSg4dOkRrayt5eXnk5OQQEhKiexGoqkppaSnQ690kQiKnLo2NjciyTGxs7LCVaBcuXEheXh7V1dUUFBSwYMECIiMj+3mflJWVATBr1ixdVBBMPRobGzEYDERHRw97vcnOziYzM5PDhw9TXFzMkiVLiI+P7zdvKioqcLvdpKamCm9rwaCoqkpSUhLz5s0jLy+Pw4cP64vACxcu1D0pBYK+qKpKXFwc8+fPZ9++fRw9epSWlhagd/F+sNy0khyLFPc8qvcweLaD6gPTEjCvEhFHU4C29m/g9WoeWEq/727PPto7f0h87G/09gaDgQsuuIBzzjmn3zvdeGExpmAxDi+AqKpKh7uA6p538CgdhBhTyIi4lgjz6EcdThYmSwj2WHDHHXdwxx13DNnmk08+Yd26dcDQVbqvu+46/vWvfwHw3HPP8d3vfveUNg6Hg5de6s0/Om/ePGbPnt1vf0REBBdddBHvvvsuH3zwAbW1tf3CsjU2btyo6yXXXz+xRZO051mHwxFwH63tmUTlni1MOQHy9ttvH3Tf3Xffzb59+7j00kt5+umn9dDAk6mrq+Oee+5h8+bNLFy4kL/85S9nZJOW28PtdmMwGHj33XdZvXq1vn/FihW89dZbXH311bz77rvs2LGDjRs3cuONNw465qOPPsqPf/zjM7JrIPqGXwuRKLjx+XwYjUbcbvegQpKG1Wpl/fr1vPTSS1RVVXHkyJF+ifvtdrue0F9UFJ3a+P1+DAYDTqdz2NVFo9HIunXr+Nvf/kZjYyPFxcX9ro1Op/NEQn9RCGJKo4mHdru9X0XDgZAkiQsuuIDDhw/T0dFBQUEB69at01/g3W63Ht4i5o1gKLQ5c+6553L06FG6urr0JPajXY1WMHXQ5k1ubi6HDx+mp6dHfzkMJGxfMs0F09xh2wkmD15fDQ7XZgbP9algc7xETNT3MBh6K2ZrnvshISETWpF3KPyKiz1N36XBsQUJAyoqEhKlnX9jVtTnWBj3TSGeC06b66+/npkzZ1JeXs6jjz7KTTfddEotgYceeoiOjg7954H41re+xbvvvovP5+P+++9n48aN/RYQW1tb+c53vgNAdHQ0d9999xidUWCkpKRQWlrKvn37Ag7D3rdvH3DCE3IyEzQK0yuvvMIzzzzDihUrePvttwcVH6E3r92bb77J8uXLeeaZZ3TV/XTp+zJ100039XvB1pBlmV//+tf6Z201YDAefvhhurq69K++SVVPl77Vr/vmUxAEJ7Is4/P58Pl8w3qeqarKnDlz9KT/e/fuxW636w8ltbW1tLe3ExISMiZ5WgUTj/YgLcsyXq8XGL7CnKqqZGRk6Plc9u3bR1dXlz5v6uvraWhowGAwjHoOG8HZgTZvJEnSF+mGq+6oea1p4mJeXh6tra36/ubmZo4dOwb0erEJBEOhKAoJCQm6V4Xf7yc6OloU4RMMiaIoxMbGkpOTA/TOm6ioKPGME6S43TsZvtCQF7fnoP5JkqSzXrw72PooDY7eXJEqfkA5/h3Kuv5BadcLE2jdxKF5QI7311TDZDLxhz/8AVmW6e7uZs2aNfzxj39kz549bN68mRtvvJEnnngC6A3Xvu22gfPkrl+/nltuuQWAN954g0suuYQ33niDffv28eyzz7J69Wo9RcYvfvGLCU8Fdv7556OqKk888YT+zjQUXq+XJ554AkmShiy+OFkIGgHyySefRJIkvvGNbwQUUmMwGPjmN7+Jqqo89dRTZ3TsvvmnrrjiikHbzZ8/XxdG9+7dO+SYFouFyMjIfl9nSmVlJS6Xi7CwMPHgLdBX87XcWEOhPURpubQaGhooLCwEeh/KNe9HIQZMXbSHaO1GKkmSvmI5XJ+VK1disVhoa2vT8+MqiqKH7S9YsEB4ZE9RtDlgNBr10OumpqaA+qxcuZLQ0FC6u7v1AjaKoujXm5ycnEFDIQUCDe3asnr1an3RRNyrBMPRd95oz+Bi3kxtzrQmAPTeoxobG0dlrLHG6WumuuctToSTn8rRjmdR1OEFFIFgMK688kr+/Oc/YzabaWpq4sEHH2TVqlVcfvnlevGac845h9dee21IDeeZZ57hyiuvBODjjz/m2muvZeXKlXzxi1+kvLwcWZb50Y9+xJe+9KVxOa+huPPOOwEoLS3l1ltvHTIU2+Fw8F//9V/6s63WdzIz5UKwB0N7qT05b8BQaG0LCgrO6NjTp0/XE6sOlJPg5LZ1dXU0Nzef0TFPBxF+LejL2rVrmTNnDvn5+fj9/oD6zJ49m+TkZGpqasjPz2fhwoV4PB5dSFq8ePFYmiw4C1ixYgVz586lpKQk4OtIRkYG06ZNo7y8nIKCAhYvXowkSXr4tQjbn/rMnj2b7373u1RXV+vV0IeqRAu9ISwZGRkUFxdTXFzMsmXLsFqtuie/CKEVjISkpCS+8Y1v0NTUJApeCQImISGB//7v/6a5uXlUnAEEZy9D3Y8slnOG7KsoErJsoKjQyKZNTzJz5kxmz57N3Llzz9pCaY2OTxlKfATwKJ10uIswkTU+Rp0lBHMOyLHgnnvuITc3lz/84Q98+OGH1NfXExYWxty5c/nc5z7H3XffPWh+cI2QkBDefvtt/vnPf/Lcc8+Rn59PZ2cnSUlJnH/++TzwwAN6JemJ5txzz+WWW27hxRdfZOPGjezevZt77rmHtWvXkpKSgiRJ1NfXs3XrVv76179SW1uLJEnceOONXHDBBRNt/hkTNAJkT08PwIiEPa2t1vd0mT9/vu7ROJyQo+0f7p9stBHh14KTkSSJpKQkLr300oD7GAwGcnNzqampoaGhgUOHDhEXF4fNZiM6OprU1NQxtFhwthAWFjYi8UeSJFavXk15eTktLS0cOnSI1NRUOjs7CQ8PJyMjY+yMFZw1GAyGfuGLgYSmrVq1iiNHjuiV1LOysmhtbcVqtY5owVEwtdmxYwc2m43ly5cPWZRIkqQpkV9JMDp89NFHdHV1kZubO+S80J6XBFOXbdu2MXfuXOLj4wfcbzJmEGK9CKfrE+DUdz1JkgkL/QxHjvSGgZaXl1NeXo7b7eb8888/LZtUVcXh2Ueb7UU8vmMY5Thiwq4nMuQSJOnM3yMV1Q1IDBda7lfciHrYgr5ceOGFI/byXbBgwRlHnQLceuut3HrrrWc8zljzzDPP0NraygcffEBdXd2ghXq03+Mll1zC3/72t3G0cOwIGje3GTNmAPD8888H3Edre6bhyGvXrtV/Li8vH7JtRUUFwJA5KseCqqoqnE4noaGh+u9KIBgpiqIwd+5cXUQ4ePAgW7ZsAWDRokUTaZrgLEZRFGbNmkV2djYA+fn5fPzxx4CYN4LBURSF9PR0PQdbYWEhH374ISBCIQUnUFWV3bt3s3PnzmHD+wUCDUVROHDgAIcOHdIrpwqCk8rKSj766CPefPNNamtrB20XH/O/mIyaJ6C2gNb7qm0xLyIq/BESEhJITU3VPf1P916lqn5q2r5OWdMNdNhfxe7eQ5fzPY613ktp03X4lM7TGrcvUeYchs9rKRNpnjlMG4FAcDJWq5XNmzfzu9/9jtTUVFRVHfBr+vTp/OEPf2DTpk3DFmmcLASNB+S1117Lr371K1588UUWL17Mt7/97SHb/+Y3v+Ff//oXkiSdcan2DRs2YDKZ8Hq9bNy4kS9/+csDttuyZQttbW0Ap70adrpo4ddz5swR4deC00bzWFqzZg21tbU0Nzfr80kISYLB6DtvqquraW1t1eeNCNsXDEbfeVNZWUl7eztdXV2AqH4tOEFVVRXd3d1YLBbhFSsImPLycux2O6GhoadUZRUEFwcOHACgurqa//znP6xbt05/X+qbKsRgiCclcRM2x8vY7C/iV5oxGtIID/sc4aHXIUkWrrzyShwOB6WlpXR0dBAdHX1aNjV3/5EOx6vHP/n7fXd6Cqlu/W+yEp87/ZMG4qxLCTdlYPNWM1AotoSBlLB1WI3xeAgukV4FFMY3JPrszxoqGCmSJPG1r32Nr371q+Tl5XHw4EG9qGJ8fDzLli3T01JNJYJGgPzud7/L888/T1NTEw8//DD/+te/uP3221m5ciWJiYlIkkRTUxN79+7lhRde0BPaJycn62XbT5e4uDjuvvtu/vSnP/H+++/z4osv6pWaNHp6evjv//5v/fN4JkhVFEWEXwtGBUmS9MrGGRkZlJaWoigKiYmJQ4a9CYIbbd6kp6eTmZnJkSNH9Mq0iYmJE22e4CxFmzdpaWnMnDmToqIi/H4/cXFxpKSkTLR5grMELQf4vHnzxj29jWDykp+fD/SGBQZSvFIwNfH5fLqThsFgoLW1lffeew+v1zugMCDLoUSG305k+O2njKWFUoaGhga0uOpXbNicH+BXOjAZpxFuXYckGVFUNy09fxmqJz2uD3F7K7CYTj83oyRJnJP0KFvr7savuvTq1wASMiHGRBbHD+3QIxAIhkeSJJYuXRo0i+dB8yQWHR3NBx98wGWXXUZdXR2HDh3im9/85qDtVVVl2rRpbNq06bRXp/ry4x//mLfffpvq6mpuu+02tm/fzg033EBkZCQFBQX88pe/1EXA++67j5UrV57xMQOluroau92O1WoVudYEZ4wkSRgMBtasWcOxY8fwer0sWLBgos0SnOVoD/HnnnsuFRUVeDwe5s+fP8FWCc52tHmTm5tLeXk5LpdLXG8EOn3FA+GFLwgUl8ulF0ETXvjBTXFxMYqiEB8fT3JyMoWFhXR1dfHWW2/R3NxMbm4u4eHhKIoybASZdr/SQisHa6+qKm09j9PS/TtU1YWWh9EgJ5AS8wsMhiT8Stcwlkt0u7aQcAYCJEC0ZQ7rp/+Lox3PUW17G0V1Y5IjyIz8DNnRX8BiiDmj8ScrogiNQHD6BI0ACb2r30VFRfz4xz/mueeeo6OjY8B2MTEx3Hnnnfzwhz8ctYp2CQkJbNq0iQ0bNlBWVsYf//hH/vjHP57S7otf/CK///3vR+WYgdI3/Fqs8gpGixkzZvDd736Xurq6QZN2CwQnM336dL7zne9QX18v5o0gYNLS0vj2t79NQ0MDMTHB+UIkOJXS0lLcbjeRkZEiv7UgYA4fPozP5yM+Pl54Uwc5Wvj1smXLWLVqFcnJyezevZuenh727duHLMusW7duROmrJEkaMqSytef/aOn6ZZ8tvZ6TfqWV2ra7SYj6USBHAdV3yla3r5EG28vYPIeRMRMXup6YkLU02t6krucV3P4WLIYE0iJuJDXiBoxyGOGm6SxL/AFLE76PX3VjkKxTLiRUIBCMH0ElQAJERkby29/+lkcffZT9+/dTUFBAR0cHqqoSGxvLwoULWb58OWazedSPPXfuXPLy8vjTn/7EK6+8QmlpKTabjcTERNasWcOXvvQl1q1bN+rHHQpVVXXPy7lz547rsQWTm8bGRpKSkoZ8CJFlmenTp4+jVYKznWPHjpGSkoLFYhm0jSzLTJs2bRytEpztHDlyhJSUFKKiogZtI0kSqamp42iV4GynoKAA6A2jFS/MgkDRwvYXLVok5k0Q09XVRVVVFQaDgYyMDGRZZtWqVciyzEcffYTH4+HTTz+lvr6e9evXk5aWhqIowwqMQ+FXumjt+t9B9qqARJf9n0iYUfEMMZJCqKV/OGdjz6uUtP0/tAyGINNsfwcfZlQ9x6OK299JR9svKWr/A1GWRaSEXcK0iKsxyeEYpZDTOi+BQCDQCDoBUsNsNpObm0tubu64HjcsLIxvfetbfOtb3xrX4w5GbW0tPT09mM1msrLOzE1fEDx0dXXx5JNPEhkZyf333z8mgr1g6uFyufj73/+OJEk8+OCDo+ZhLpjaeDweXn31VXw+H1/5yldISEiYaJMEkwCXy8XRo0cBURVdEDhdXV0cO3YMEPMm2NHygM6aNUu/7xiNRnJzc0lNTeXDDz+krq6OY8eOsW3bNi677LIz9sDvcWxCxT1ECxW39yhW0zKc3nwGLk1iwGrKJtS8XN/S6dpDSdv3Tmqv4EPul9vRp8r4jlfuRnXT5tpLm2sfRzv+RG7KX4i0iEJeIEKwBYIzQZQ7DnIOHz4MQE5OjkjOLggYbd5ER0cL8VEQMEeOHMHv9xMTEyPER0HAlJSU4PP5iI2NFWH5goApLi7G7/eTkJBAUlLSRJsjmCRoXrMzZswYlRzwgsmLVpB0zpw5+juSVkhmxowZnH/++cTFxaEoCiUlJfz1r38lPz8fn8/Xr+1I8CntwODpsBQVfEg4vXkMJj4a5ChmxP+pnxdmTddfOPm1X1X7j+BXJXwY6M052VfsUvEoXexq/BI+xTnSUxIIBIJ+CMUpiFFVVReSRPi1YCRoeUNF1XTBSCgqKgIQxWUEI6KwsBAQYbSCkaEJSQsXLhTzRhAQqqr2C78WBC+1tbV0dHQQERHRr0Bn32tJdnY2aWlpfPjhhxQVFeF0Otm5cycmk4l58+ad1nXHZEyFPh6JfVFU8DP4mJJkJSHibuIj7sBkOLHooqp+2p3bQA+zPr69t5f+2Y+MFuY9wNFx+9uot28mPeK6wE5mCiM8IAWC02fKeUBu3bqVrVu34nSO/gqNw+HQx58KNDY20tnZidFoZNasWRNtjmCS0NPTQ01NDSCEa0HgOJ1OKioqACFACgLH6XRSVlYGIKpbCwKmu7tbhNEKRkxjYyMtLS0YDAaxwBrkHDx4EOiNEBss97CqqoSGhnLuuecya9YsVFWlqamJl19+mU2bNmG32/V2gRJhvRRZihhwn1/3TBxYiFJVN7Hht/QTH4HjIdbKgH1O9AXl+Niq2it2eVUZryrjU2UUVUJVZVoc2wM+F4FAIBiIKecBeeGFFyLLMocOHRr1h4fKykp9fM29fjKjeT9mZ2djMpkm2BrBZEGbN9OnTxdhtIKAOXLkCIqikJSUJMJoBQFz+PBhfd6I3I+CQNG8rdPT00UYrSBgNO/HnJwcrFbrBFsjmCgURdGrX8+ZM2dQT0Zte1xcHDfeeCPp6ens3LmTzs5OCgsLMZvNXHDBBRgMg4dUn4wsh5Ac8zPq279Gr9DYK172apiDe8D1ekfKlDTdSah5AbFhVxMTsh5JMiJLZkKMmTh9x+gbdN07Wn+PR1XlRA7I461UVPzISKj4lKHyUwYPwgNSIDh9ppwHJJxezo2zafzxQqt+PWfOnAm2RDCZ0MKvhfejYCRogoDwKhGMBBG2Lzgd+la/FggCQVEUPd2DCL8Obtrb2zGbzcTFxZGcnDxse0Xp9S5ctGgRK1aswGg0Yrfb2bZtG//4xz9obGwc0fGjw25kWtyTmAzTh22rquBVZTwY8SPh9FXS5niH0pYvUdhwHV5/OwDTIm8/pa8k9cqLoOo/nwjx7utpeUKqdPo7R3QuAkEwc8MNN/CZz3yG2traiTblrGJKCpCAyPczDK2trbS0tCDLMrNni4pmgsCw2WxUVVUBQkgSBI7D4RDh14IRY7PZqKysBISQJAictrY2GhoakCRJ3KcEAVNZWYnNZiMkJESkJQoyVFVFUeyoam/6rvj4eL71rW9x2223ERYWNmx/We59nbZaraxZs4bPf/7zpKenA1BTU8Mnn3xCU1PTiGyKDL2aWSk7yEx6l/SEf5KZ9A4Sp0ar+ZGO527svxXA4T1CactXAEiJuJm40IuP7z/xjmxE1j/JKqjIDO5pKdHpPoLH3zOicxEIgpXXX3+d119/ne7u7n7bZVnGaDTqTj3BxpQLwdYQLytDo4XRZmVliTATQcBoXrNpaWmD5sQRCE7myJEjqKpKcnIycXFxE22OYJJQXFyMqqqkpaURExMz0eYIJgma9+PMmTMDEg8EAjgxb+bPnz+ikFnB5EVVFRyOf2K3/QWfrxQAk2k54RFfISTkihE/52oRcunp6axdu5b333+fpqYmSkpKqKmp4a677iI2Njbg8SRJIsR8whs3OnQDHY7X0QRGVR2ucIyfHvdu7O5CwiwLmJ/wBxpsL1PX/QIObxkSRuLD1jMt8k5c/laOtP8Zl6dySJsUvHS4C0kKzQ34PKYiqiqhjnNI9HgfTzB6DBQ9O1Uiak+HKSlABvMfNFBE+LXgdBDh14LTQYRfC04HEX4tGCmqquphtKL4jCBQvF6vvjAv5k1woKoqnR3/jdP5Cn3FO6/3IB3td+GL/A4REV8b0Zh9o+9mzpxJSkoK77//Pnl5eSiKMiLxcSCSo79Dj2sbPqUN8GvB08P0MtDp/JgwywIkyUBqxC2kRtyCqiqApNscBTj9dtpafhKAJeI9WyAIhIiICGw2G01NTeJZtg9TToD80Y9+NNEmnPV0dXVRX18P9CbaFggCweFw6FVFhZAkCBS73a6H0YqbryBQurq6qK6uBsS8EQROQ0MDbW1tGI1G8XwjCJiSkhI8Hg/R0dFMnz583j3B5Mfleue4+Aj9BbXefI493b/Ear0Yk+n07j+KohAaGsqFF16I0+kclWJYZmMK2clv0dD5czodbwHDF0SVkFDwnLpdOjULW5x16bDjyZiIsYh7soJ0vGr4+B5TMLmYM2cO+/bt4/e//z3nnHMO4eHh/fYHa8pAIUAGIZr3Y3p6+in/CALBYPQNoxXhkIJA6TtvznT1XxA89K1iHBkZOcHWCCYLmvdjTk4OFotlgq0RTBa06tcLFy4M2hfCYMNuexYwoIUzn4oBu/0FoqN/oUfWjWRuaHkho6KiuPnmm/H7BzvOyDAbU5gR/39MU36Gy1tJcdOtKMdzVw6Eio9wc2BFlSLMGSRYV9Pk3IufXsFLQsWAgoyKLMmkR1yN2SBSMAkEgXDrrbeyd+9e3nrrLWJjY0lKSsJkOpHL9dJLL+33ORAkSaK8vHy0TR1XppwAKRgeEX4tOB208CQRfi0YCVrYvvCaFYwEbd4I70dBoKiqqgvXIg+4IFAcDof+MifCr4MHr7eQk8VHVe2tDN2rN/ppby/BYnESEhJy2sdRVRVJkjAaR/eV2yBHEWZZQmL4rTT2PIvmudkfGZMhkeiQdQGNqag+kKPwYEDLK6miomBAQiHJPIdF8d8axbMQCKY2Dz74INu3b+eVV17B5/NRV1en71NVtd/nQJkKi2RCgAwyHA6HXsVYCEmCQHG5XHoVYyEkCQLF4XCI8GvBiOno6KCurk5UMRaMiOrqarq7u7FYLKKKsSBgioqKUBSF5ORkEhISJtocwTghSVZUtfukbdDUlETJ0RxaWhIJsVqwhrxKcnIyc+bMIS0tDUmSdFExsOOMrVgwLfrr9Lj3Y/fkH9+ihZMbkCULsxOeQJICe90vaP8rNfZPjn+S+n1XMWAxZWKUQ0fJ8smNokoo41wUZryPJzhzZFnmpZdeYufOnXzwwQfU1dXhdrv529/+hiRJbNiwYVTSM0w2hAAZZJSUlOjhkME44QWnR0lJCYqikJCQQHx8/ESbI5gkiPBrwemgebFlZGSINCGCgNGqGM+dO3fUvY0EUxdt3gjvx+AiJORq7Pa/oXlB+nwGKipmsmPnGrxeLSRSAsqpq6ujtraWtWvXkpWVdVZ5IBnkMOYl/Ysm299p6vk7bl8tBimUuLBrSYm8C6spI6BxfIqTks4XGbzAjEqV7X2W+h4g1Jg4WuYLBEFBbm4uubknKsf/7W9/A+B//ud/gnKhXTyhBRki/FpwOojwa8HpIMKvBaeDqH4tGCl+v1+/3ojwa0GgdHZ2UlNTA4h5E2yEhd+F3f4PegU3hSNH5lJQuBCv14TJ5CUmpofQ0CUcO1aDy+WiqqqKl19+mauvvvqsuzfJspWUyLtJibz7tMdodRXhGyKXZC8KjY49ZEVefdrHmSqoqoQ6zh6J4308gWCsEAJkEOHxePQ8N0KAFARK33kjBEhBoDgcDhG2LxgxbW1tNDY2IkmSuN4IAqayshKn00lYWBiZmZkTbY5gkqB5P2ZmZopiV0GG0ZhJXPwLtLfdhcvlpqBwEXZ7GHFxbay7sIC0ab8nOnoxNpuNnTt3cvDgQZxOJ3v27CEjI4OwsLBhj6Eoil6M5mzGp9jp8VQG1FZRvWNsjUAw9VGUgXK2Bg9CgAwiysrK8Pv9xMTEkJgo3OcFgVFWVobP5yMmJoakpKSJNkcwSdDSPSQlJREXFzfR5ggmCZoXW1ZWFqGhIteUIDC06tdz586dFC/8grMDbd4I78fgxGI5j6TkA+zc+Rw2WwvJyX4uuSSXzMzfIklmVFUlPDycNWvWYLfbyc/Pp7q6mj179rBu3eCFXRwOB6GhoWf9tcjj7+JI+x+osb2Bx+8BLJzI/TgwsVaxoAwiB6RAcCYIATKIKCkpAXq9H8+m/CWCs5u+4ddi3ggCRYRfC04HEX4tGCk+n09PLyPy+AkCpampiebmZgwGg7hPBTGyHEZxsRmQWLLkajIzzzml0ExoaCjXXHMNDoeD0tJSduzYwYIFCwYsWqQoCu+//z7FxcV89rOfZebMmSO2SVUV/EoHkmTCII+NZ65X6WF7/e3YvVX4VAVVkpFU9XgGyFOf9SUMxFhyiLXkjIk9AkGw4vf7ef311/nggw8oLCykvb0dgNjYWBYsWMDFF1/Mddddh8FgmGBLRw8hQAYJfr+fo0ePAiL8WhA4Pp9PnzciHFIQKKJquuB0aG1tpampCVmWxX1KEDBlZWW43W4iIyOZPn36RJsjmCRo4dfZ2dlYrdYJtmZ8URUHijcf8CEb5yEZRhaloCpOvK438HsKkCQTRss6DJbzkKSz2+NvIDo6OmhpacFisZCamqqLjn0X3BVFwWAwkJubS319PXa7nb1793LllVeeUhG7o6ODo0eP4vF4AgrT7ouqemnpeZrWnmfw+hsACDEvJjHyfqJDrxiFsz1+PqqHso6nsXuPoagKCjJ+VUZFRlVV/Miox2vRGCQFWQKTHM6apJ+Mmg0CgQA2bdrEvffeS11dnb5NPf7PJ0kSO3bs4KmnnmLatGk89dRTXHbZZRNl6qgiBMggoaqqCpfLRWhoKNOmTZtocwSThMrKSjweDxEREaSlpU20OYJJgqiaLjgd+oZfh4SETLA1gsmCFkY7f/584aUvCAhVVfV5E0xes6rqxdfzO3yO50AvOGJAtl6DOeoRJDlq2DF87m042r8Mag/aa6TH/jSycQ6hcX9DNqSMmf1jgeYFGxkZiclkGrCNFkqdmZnJzJkzOXToECUlJSxfvpykpKR+ImRlZSUOh4PExESSk5MDtkNVfVS23EWP6xP6VqJ2egqoar0XT/T3SIy877TPE6DF8QnHOp+mw7UPN0ZAQkFCVcGLAZ8q4VP7SwN+1YCsKqRY5xNhFgs8GqIIjeBMeeGFF7jzzjtRVVUXHTMyMkhOTkZVVZqamqiqqkJVVWpqarjqqqv429/+xuc+97mAjzEeXpOSJOHz+UbURwiQQYIWnpSTk3PW5yQRnD1o4dcibF8wErR5I7wfBSNBhF8LRorH49G99EUeP0Gg1NTU0NXVhdlsJjs7e6LNGRdUVcXT+TUU1yb6ClzgR3G9idt3GEvcq0jy4F57fm8JjrY7Aa0QyYmXTsVXiqP1vwhLfA9JMo/FKYwJ2su/zWYLyBP2/PPPp6CggO7ubgoKCkhKStJDth3OCoqK9wOwdOnSEdnRbv/3KeJjL73FKho6f05UyGVYTFnDnk+Xaw/1Pf/E5jmMQQ4lIfRyvKqfis4/Ato74Ilnev9xD8iTxccTFkhUOfbg8fdgNkSM6LwEAsGpVFVVce+996IoCmFhYTz88MPcfffdp9ToaGlp4a9//SuPPvooNpuNe+65h/PPP5/09PSAjqMJm2cbQoAMAlRV7Zf/USAIBEVR9Hkjwq8FgeJ2uykrKwOEACkInNbWVpqbm5FlmZwckWNKEBhHjx7F6/USExNDSsrk8rwSTBxa+PXcuXMH9XqbaiienSiudwfZ60f1HcXveBFj+F2DjuG2PQX4OVUk6x1D8Vfgc23CFLJhFCweW/p6LbrdbqKiooathK6qKvHx8axYsYK9e/eSn5/PokWLsIZtob3n9zTU2zhWeR0AaTPeQ1EWIcuBFVNr7fnbMC0MtNn+QWrMD4a0r7z9f6jreR4JAyp+AHrcR/DqgqNWfVdFEyEVVcKnyv229UdCAZqdhUwLzw3ofKY66gQUoREekFOH3//+97jdbsLDw9m6dStLliwZsF1CQgIPP/wwV155Jeeffz52u53f//73/Pa3vw34WJIk8eUvf3nUCxA3Nzfzpz/96bT6BqUA2d3dzSuvvMLOnTtpbGzE4XDwzDPPMGPGDL1NfX09nZ2dWK1WsrKGXm0622lsbKS7uxuTyURmZuZEmyOYJFRXV+NwOAgJCen3vyEQDMXRo0fx+/3ExcUNmKBdIBgIzftx5syZIvxaEDAi/FowUhRF0dM9BJPXrM/xEmCA46LUwG3+OaQA6XO9PWR/kPE6J4cAqV0vrFYrVqsVVVVpaGgYMt2Q1mfFihUUFxdjs9nYueevzFvyR1RVor52OQCp06px+d+jtmUX0xJeCUiEdHvLGFjY1fDj8pYMOUaT7TXqep4H0MXH3p7auFp+S5BVFQXNH1JCZbjoOJVmV4EQIAWCUeC9995DkiQeeuihQcXHvixevJhvfetbPPLII2zevHlEAiTA/fffP+pOIUVFRUKADJTHH3+c73//+/T09AAnVsDsdnu/dlu2bOFzn/scVquV2tpaYmNjJ8LcUUELv545c2bQrPQKzhwtjFaE7QtGgqiaLjgdRNV0wUhxuVy6t3UwCUmCM6OiogKHw0FoaOikdzAYCaq/lqHFQxVVaRhmEPcwR1FQVfuge1VVwefZjuItAzkEk+ViZMPE5onOyMjgoYceorGxUfeAPLmwzMkkJiaSlZVFQUEBpSVtTMuMwmJ1UVPZ6+QxM+cIoOD2HqLL/hwxEV8Z1g5JsqKq3iFayMjS4EKmqqrUdD9Nr8jYX8hUkTjZs9GIHw9GJElF1r0ih7SQXgFbIBCcKdXV1QBcfPHFAfe55JJLeOSRR/S+k5mgUhUeeeQRvvrVr9Ld3Y3ZbGb58uWDtr355ptJSUnB7Xbz6quvjqOVo48WRivC2gSBIsL2BaeD1+vVBQERti8IFBF+LTgdSkpK8Pv9xMfHj3pokWDqonnNzps3b1Itrqr+NhT3VhT3p6jK4CLfYEhyPMO+9klDO1vIxiwGDtHVMGAwzh5wj8+9l57m87C33Yqz+0c4Ox+iu2kljs4fDiO89Ufxt+Lo+SNd7ffS3fEALsfrqMMKo0MjyzKpqamEh4cDBLR4es4552AwgN0WQWXpbLo6YujqjMFo8jI945hmLZ223tBqRXHSafs3jR2P0Nz5C5zug/3Giwq9iqEFPoWoISph+5UeHN5SBvei7L9dlsB8XJA2S74h+p0g2pIxbJtgQQVUdZy/JvqkBaOG39/7vzeSIjFaW0UJZMGgl7Vr17J27VrCwgbP7Xu6hIWF6eOPlMlz5z1DDh48yE9/+lMAPv/5z9PY2MiePXsGbS/LMjfddBOqqvL++++Pl5mjTmdnJ01NTUiSxOzZAz8UCAQn09DQQFdXFyaTKag8BARnRllZGV6vl6ioKJGPTRAwWvi1qH4tGAl9ixYJb2tBIPh8Pj0qaLJUv1aVLrwd38DTvBpv+x1427+Ap/kcfN2/QFU9AY9jDL0BhvR0kzGG3jTkGOawO4Y5ioIp7NZTtvq9xdja/gvFX3d8iyal+PA4nsPR+fAw4/bicv6HtqYV2Ht+icf1Lm7nG/R03k970/n4fBUBjTEaqKrKtGnTyMiyAVBVMZO8vasAyJhZ2q+tz19Dt+N9jtYvob7jG7TbnqW1509UNl/NseYb8fs7AEiMvAcJAwO/mhswG2cQFXrl4DYNIU/Jg+yTJRULPkJkhQjDUGHiEhY5ihnhIxcaBALBqWipHnbs2BFwH61tampqwH0++eQTPv744zFJpZaRkaGPP1KCRoD8v//7P1RVJTc3l+eff56oqKhh++Tm9ua50JJVT0Y0L7b09HRCQwNLhCwQaA/os2bNEmH7goAR4deC00GEXwtGitPppLy8HBBV0wWBU1paitvtJjIykunTp0+0OcOiKg68bbeguN6kX/i06sRv/wvejq8GXOVUtqxHMi1jYC87A8gJGEM/P+QYptBbMFjO49TXx97PlojvYjCemmve2fMYvRWzBxJAVbzOf+P3lQ95bK/nAD0dD9BbgVs5/tX7O1GURrpab0ZVXUOOMdosWe7HbHZj64mkvbU35/XM2Uf6tVExU9t2F4oemu5Dqx7ucO+huvUOVFXFappNZsKzfcKsjWiZ0izGTGYmvoiq+mnq+QdFDTeQV7eOI0130O7YjKr6McqRhJgG9lA9IUCeOlckScIgGVif+ivCjSlIJ/1tJWQkZC5I+QEGSbwPaChIE/IlmBqsW7cOVVX5xS9+QX19/bDta2tr+cUvfoEkSaxfv34cLBxbgkaA3LJlC5Ik8cADDwTcJyMjA4C6urqhG57FiPBrwemgCZAi/FoQKD6fj6NHjwJCSBIETt/wa3G9EQTKkSNHUBSFxMREUexKEDBa+PWCBQsmxSKZ3/kiqu8oA+duVFHd76F6tgc0liQZscQ+h2y9jJNFKsm0CEvcy0iGuGHGMBEa+yyWiG8hySf+72TTfEJi/owl4r5TrVRs+FzvD3IOGgY8jteHPLbD9udT7D6BH0Wpx+18e8gxRgtJklBVlYz0K0iZXgOAoshERHURl9Dap6UBSdbSQwxcOdzp2YfD3evZFBGylnlp+5kW+2tiw28mLvzzZCY8T07Kh4CJwoarONb+/7B58nD7jtHl+pTSli9ztOUeVLxMj/zigMeRJDCBLi6e8LSUMEhWliQ9TlzIUq5Jf4q50TdglKxaT9LCVnPV9CeYFrb6jH9vAoGglwcffBBZlmlpaWHVqlW8/PLLelh2X/x+Py+99BK5ubn6s/JItKyzlaApQtPQ0JtYeSRCnMViAcDtPrPcIhOF0+nk2LFjgBAgBYHT1tZGS0sLsiyLsH1BwFRWVuJ2uwkPD2fatGkTbY5gkqB5zYrwa8FI6Bt+LRAEgtvt1hfJJkvRIsXx4jAtDPgdLyFbzgtoPEmOwBLzOIqvFsWzHVQ/snkJsinwRUNJMmOJeABz+H2oSitIZmQ5ZtD2qtrN0KHfABKq0j7EGCqeYUVMGY/rfayhnxnmWKODJEmEWdezaMmfaKxz4XZZmZHV14tTBtWI19/A0OdvpNv5NmHWNQAY5FDiwm8hjlv6tSptfQCXr+b4J01k7P19dDo/obbzf5ke/RA97kIabC/Sv+K5jFEOY2nSX3D46mlzbkdV/URZF5MSvgGTHAFAiDGG1Yn/zcqE+3H7uzDJoZgCqOAdjKiqhKqO7yLGeB9PMHYsWLCAn/70p3z/+9+nvr6eW265hejoaJYuXUpSUhKSJNHY2MjBgwfp7OzUPd1/+tOfjuv9y+1209nZSUJCwqjmTA4aAdJsNuN2u/F6A090rImW0dHRY2TV2FJWVoaqqiQkJEzqKt6C8UXzfszIyMBqtQ7TWiDoRROS5syZMyk8SwRnByL8WjBSHA4HFRW9+d6EACkIlJKSEnw+H3FxcSQnJ0+0OQGh+hsYuvSE/3h165EhG6chG28+bbsAJMmAZEgavp0cA5iBofJVKsiG4RYuh3t/U1AZX4cRSTKweO5fiE+4h4aGMsIj7PT6GnoxyDEkxfyBqtahw9pBRVFsQ7awe4qxufcNOUZTz/OkRT1IdtyPiQ+7hPruf2DzHMEgh5AQdiUp4TdjMSYSxTJSwq8ecBSP347D14LFEEmocWKrkwsEU52HH36YqKgovv3tb+NwOOjo6Dgln6ImPIaGhvLrX/+a++471cv8dLDZbGzduhXoLVSjFeDSaG1t5Utf+hJvvfUWPp+P8PBw7rnnHn7+859jNpvP+PhBI0BOmzaNw4cPU1RUxDnnnBNQn/feew/ozYM3GdFWeoUXm2AkiOrXgpGiKIo+b4SQJAiU9vZ2GhsbkSRJeOkLAubIkSOoqkpycjJxcUOHjAoEGpOyaJEcC/6hKl7LIJ/dKQgkKQRTyA14nS8zuAejhDn0hiHGkDAY5+D3lTC4N6GM0TS6hYWcTifNzc2kp6cPOmcMhjjSkzaSGJOH3fkBKh4spoWEh1wGmDDIcfiVtiGOomI2Df2e2e3aRW/I9OCelIpqx+E9QoRlKbEh5xMbcv6w56dh8zbyaeMvqXHs663uDITK0ZyX/E0yIy4MeByBQDAyvvKVr/DZz36WZ599lg8++IDCwkLa23u9wWNjY1mwYAEXX3wxd955J/Hxo7co8Oqrr3LnnXeSnp6uL+hqKIrCFVdcwYEDB3QBtKenh9/97ndUV1fz0ksvnfHxgyYH5Pr161FVlWeffTag9hUVFTz99NNIksQll1wyxtaNPn6/n9LS3kps4sVOECg2m42amt4QDzFvBIFSXV2Nw+EgJCRkTCqtCaYmmvdjZmamKJImCBhNSBKLHYJAcTqdlJWVAZMn/BrAEHIjQ7+qKRiGEO7OFkIiv44kRzNwARywRnwTeRhvypCwuxg6lFnCGvpfp2vigBQVFfHcc8/xr3/9a9i2VvMS4qK+RXzU94gIvQZJMiNJEjHhtzP031AiOmw4b9TACg0F3u4Eld2b+XfFjVQ59qMgoyIDMg6li/fqf8gHdY+MeMxgQFGlCfkSTD3i4+N56KGH2Lx5M3V1dTidTpxOJ3V1dWzevJmHHnpoVMVHgM2bNwPwmc985pTQ6n//+9/s378fgGXLlvH1r3+dZcuWoaoqr776Kps2bTrj4weNAPnAAw9gNBrZvn07jzzyyJBt9+3bx6WXXorNZsNisfClL31pfIwcRaqqqnC73YSFheml3gWC4dC82FJTU4mMjJxgawSTBS38OicnZ1RzhAimNn2rpgsEgWC326msrARE+LUgcA4fPjwpixYZwj4PciIDC3cykmkpsuWi8TZrxMiGVMLj38BouZC+hWQkOZGQqEexhA9fVMEa+lnM1quO9+8rxBgAiYjoX2MwpIyq3QUFBcCJoqSnQ5jlfEyGVAarHJ4c/RNMw4ivEZaVDJdHU5ZCCTWNLHKp1raVjxp+jG9AOaD3d1xu+5ijXZtHNK5AIDi7KSwsRJIkcnNzT9n3wgsvALB8+XJ27drFb3/7W3bu3KlHED///PNnfPygeVOcPXs2P/jBD1BVlZ/+9KesWrWKX/3qV/r+TZs28ctf/pKLLrqIVatWUVlZiSRJ/OIXvyAlZXRvaOOBJiRlZ2cLQUAQMCL8WjBSVFXV84YKIUkQKJ2dndTX1yNJkrjeCAJGC79OSUkRua2DENXfimr7I0rrVSgt61E67kN1f6qHiQ3GZC1aJMkxmONfRjItPXkPsvUyTLHPIUmTI5uWwZhOeNxzRCbtJizuX4THv0Fk0h4sYZ8PKCRekgxExvyJ8KhfYDBma6NitqwjKu4VrKFnltPyZLq6uqiurgZOz2vW5SmkvPFSqlqux+uv5WQB0WpawLS4p4mNuGPYscItiwgzL2EwD1KQSYr4HIYRFIyp6HqFLQ0P4T9eDXvgCuO927Y3/z7gcYMFVZ2YL4FgNGhpaQE4JWrN6/WyZcsWJEniK1/5CkZj7/3FZDLx5S9/GVVV2b179xkff3LctUaJH/zgB3i9Xn7+85+zd+9e9u3bp9/0HnroIb2dqqpIksQPf/hDvvrVr06UuaeNqqp6/kcRRisIFI/Ho+eBEPNGECj19fV0d3djNpvJysqaaHMEkwQt/Do9Pf2U5NcCwWCI8OvgRfUWobbfDqoNXczxN6C6P4SQWyHyRwMKWX29Zscj/Fr1FqB6dgMqkmkFmJacUc5JyZCGOf4lFO8RVG8eYEA2n4tknJzRTbIhBfk0PRUlyUBI2OcJCfs8quoDZCRpbJwsCgsLgd4X9JFGBLm9pRxrvgFFdQ24PybsdlJifz6iMbMTHqe48WY8/jpOhFr35oWMtJ7LtOhvBjzW0Y6/kd/2e1TMx0OuVQYWIHvxKHbc/h4shogR2SwQCM5OtDyTJpOp3/Z9+/bhdDqRJIkrrrii3z6tpkhjY+MZHz+oBEiAn/zkJ2zYsIFf/OIXbNq0CYfD0W+/2Wzmoosu4vvf/z7nnnvuBFl5ZrS0tNDZ2YnBYBCCgCBgysrK8Pv9xMbGTqoQJcHEooXRzpo1S18pEwiGQ5s3QkgSBIrdbufYsWPA5PNkE5wZqupB7binv/gI6EVNnP8E0zwI/ewpfYuLi1FVldTU1DH1mlX9jfg7HwTvQU4EmClgnI8h+nEk43BVnodGNs2BEYbYTmXG2vNTEyBPR7Ru7vrNcfFx4KI7HfbniY+8H9MIRGSLMZWFqW/TYnuFVttGfEo7FuMMEiP+i7jQKwP+fbQ58yhs/18UDJz4XxpeIPerQ1UxFwgEk4mQkBB6enpobm7ut33Lli0AzJw5k6SkpFP6jBZB+ba4YsUKXnnlFXw+H8XFxTQ3N+P3+4mLi2P+/Pmj+gueCLQw2qysrFEplS4IDrR5k5OTM3kqRAomHBG2Lxgp3d3d1NbWAmLeCAKnb/h1TEzMRJsjGE9cm0FpHaKBhGp/BkJuOuX5ZTzCr1XFjr/9VvDXHd/SRyT1HcHf/l8Y4t9GkkVu7clAa2srjY2NyLI84kUyv2Kjx/kug1f8BpDocmwkPvLBEY1tlCNJifwiKZFfHFE/DVX1s7PxG8ctUPvIjkN7QAJYDVGndcypiqpKqONcFGa8jyeYusycOZO8/8/eecfHUV1/+7kz29S7ZMmWKzbd9A7GmDgEQnXo3UAICQ4tQMKPmPqGngahBEJoBhOaMcGEbhtTDHYI1TQXFVuS1evWmbnvH6tdr6xdaVbVsu6Tz4bdmXvPPSvP7s5855TPPmPZsmX8+Mc/jm5ftGgRQggOP/zwbnMiaduFhYX9Xn/UCJAXXBD+sj766KM55ZRTAHA4HEyfPn043RoUIt2vI6GyCkVvWJaluqYrkqa+vp76+np0XVffNwrbRGqGjhs3TjW7UtgmkravomZHHzK4ivAli5FoBJjrQbaC2CKUtLW1UV5eDgyyAOl/GcyKBHtNsGqQvucRaRcOmg+KgSPSfGbKlCmkptqvqwhgWk30LD4C6BhmbS9jBp4a7wcErSYANMLlxnRMzIS1JcMUp+yBNkJqjSoUit6ZPXs2//vf/3jggQc47LDDOOyww3jsscdYtWoVQgiOO+64bnO++OILINyotr+Mmm+TJ554AoDTThvYIsXbGh0dHVRWVgLhBjQKhR0qKirw+XykpKRQWlo63O4oRgiRNNpJkybhdruH2RvFSEF1v1Yki9frjdbxUwLkaKRvkT8R0XrcuHFkZQ1eBJfle5mwj4m6REgs3yI0JUBu80gp+5V+rWs5hJvF9CRCmjh66Xw9kHSEKlnfsoCy1pej2zQhEdLCI0J0SJ34UZASgYOjxiZXr3I0oCIgFSOZyy+/nIceeoi2tjaOPfbYLvt23nnnuALkkiVLEnbOTpZRI0AWFBRQV1fXLZ99e2PdunUAjBkzZlBPthTbF5GIpGnTpqmu6QrbRI4blUarsEtHR0c0IkkJkAq7fPPNN0gpGTNmjOp+PQoRrv2QvoU9jQB9MoiuEdWx6dfSbECG/gcIhGtPhJY3cA5aTSQWHyNjmgduPcWgUVNTQ2NjIw6Ho08ZQbqWTmbKT2n1LaEnETIrdU4/vOyZlsCX1LQvIWS1IHFQ0f46UhqY0iK247ULg6DmINUK4JOuLknZAKl6PnMmPIxbV43iFIrtieLiYv79739z+umnU11dHd0+efJkXnjhhW6lTNatW8eKFSuAcPRkfxk1AuQuu+zC8uXLKS8vZ8899xxudwaNiACp0iEVdpFSdqn/qFDYobW1laqqKkAdNwr7qDp+ir4QiZpVzWdGKZ4fQ1sBWI3EF3UkuGd1uWhqaWmJZgTtNO4lzLrFMXMdCM8JaJnzEdoAiCv6BDArE/gGoIXHKLZ5IunX06ZN63NmR0HWb2j3v4slfWx9TEgJmaknUNf2OJIgqa7pZKUegyY8/XUd0/LzZd1V1HmXItCREvxRUVF09szeEmQgBLikgUMTODExLA1TapSkz+CA/N+Q6d6+g3YUitHMYYcdxoYNG/jggw+oqamhuLiYQw89NG5D0erqaubPnw8Qtz5ksowaAfLss89m2bJlPPHEE5xwwgnD7c6gsX79ejRNUwKkwjaxXdOnTJky3O4oRgiR6MfS0lLS09XdcYU9VNSsIlm8Xi/r168HVPr1aEUIF+Q8gmw4C+iIP8j7T6T7EIT7YGBL+nVpcTvpjlfoKgQZSP8iTHMdeu4zYfv9QEs9HSu4vIcRFlrq6f1aQzH4SCmjUbN9Sb+O4HbuwMTCRVQ1Xo0/9Hl0uyAN9CwavYvZcgluoDfdyMT8h0n32EttlNKk0beCtuBXaDjJTZ1Bumtn1tTPp84bPg4lJiaC2Et9IUBI2RmrK6LbdCQ6Ji7dZIesc5ief1Wf3/towZICMcQp0ZZKwVYMMC6XiyOOOKLXcYceeiiHHnrogK07anIt586dy5FHHsnixYu5+eabkbKXVIkRSjAYJC0tbUAKhCpGB6pruqIvqO7XimTx+/1KSFIkzXfffYeUkqKiIpV+PZpx7Ax6EYnrQVrI1vnR8/to06LJXxM/MtGC0GdI/3/67ZpwHwnuHyXwTQPXYQjP0f1eRzG4VFZW0traisvl6ncdfY9rFyaPeY3JRW8xNu9BxuX9E6GPJWTWdY4wiDRVMq1W1teegz/0Q6922wJf8vHGI/mq9mIqmu9nQ/Of+W/VCXxadTo1Ha8S24HdilOXVI/t0I7sfITlgB2zL2T3vCv7+pYVCkU/kFLS0NBAZWUlptlbI6v+MXnyZCZPnszf/va3QV0nEaMmAnLFihVcffXV1NXVccstt/Dss89y2mmnMX36dHJyctD1njuAzZgxY4g87T9Tp07tlruvUCRCpV8rksXn81FWVgYoAVJhnx9++AHLssjPzyc/P3+43VGMECLp10q0HuUYX4c7XSdEhtOgQ6tp9k5l48aNgGSnyRt7mKNheZ9DS+lfZpQQGnr2fVjt9yO9T4Bs69yRjkg9Ey39coTqIrzNE4l+3HnnneOmIfYFj2sXPK5daPYuIWCsTTDKQmJQ1/owpXl3J7TlC1Xwec25mNIHhKMcIzQHPu82XsbUe4wgBDikhSQiUAomZs5hh6yzyHBNTO7NjWKkDD+Gek3F9oVpmjz55JPRDtTBYBAhBF988UWXc55XX32V9957j6ysLK6//vp+r7tx40ZM0xy2soSj5tdw5syZXUS577//nltvvdXWXCEEhmEMlmsDjkq/Vtilvb2dTZs2Aeq4UdgnIiQVFBSoiCSFbVT3a0Wy+P3+aG1rJUCOcsyehMSu49asCQEwoaSZ9FRvD4MtsKr67xsghBM94wpk+i/B+B6Q4JiKECkDYl8xuFiW1aVp0UDT4l1Cz92xTZq9/+5RgNzY+him9EOXKMYIXRvMkGAUdKZiAxoSl5bDnvn/pwJXFIohpra2lhNPPJGPP/6418zcSZMmcfzxxyOE4Kc//Wm/hcMxY8awadMmUlKG5/dp1KRgQzi0ta+PkYKu60yePHm43VCMEL7//nsASkpKyMjIGGZvFCMFlX6tSJZQKMTateHoDyVAKuzy3XffRW92qKjZUY7Itj0uGsk21UfilG3C+7TC/nrW1aJwI5y7I5zTlfg4gigvL6ejo4OUlJRBuY4yrQ566ooNdDatSUxtx78T2hBIYo/18KVr76Kix1GkxMc+EI6AFEP8GO53rRgoLMvi+OOPZ+XKlQghOPXUU3tMh95111056KBwjdhFixb1e/0DDjgA2BL1PdSMmgjIpUuXDrcLQ8L48eP73LVNMfqICJAq/VphF8Mw+OGHcJ0iJUAq7LJu3TpCoRBZWVmMGTNmuN1RjBBU+rUiimtf0PLBqk88RmTS5N2Vqqr3EEKw866HgflOD0YlWsopA+6qYuTx1VdfAeEbZL2V5eoLHucOtPmXk1iEFLgdEwHwBn/AG/waIZxkeg7GqecAYFgJGjARkRq7ipB2SHWongEKxVDz5JNP8sknn+B0OnnllVc46qijAJg3b17COccddxwfffQR77//fr/X/+Uvf8mLL77In//8Z8444wycTme/bSbDqBEgB6Jl+EhAdTFW2CUUCkVT21T6tcIuGzZsIBQKkZGRQXFx8XC7oxghxHa/VtEWCjsEAgEVNauIIoQD0n+DbL0u8Zj0K/jms/ANsgkTJpCRfzJmw0Iw1tJd+NHBMQ2RctzgOa0YEZimGb3Z0Z/u1z2Rl34WdW0P9zgmM/UE1tScSltgVXSbwEFB+plMyL0ej2MsfqMi7lwhQJeis/M1CCG7dbyOM4t8z/5Uef9HU6Acp+ZhfPpBePSs5N+gQqGwzcKFCxFC8Itf/CIqPvbGXnvtBWzJQusPs2bN4rrrruP222/n2GOP5R//+AelpaX9tmuXUSNAjhaUAKmwy4YNGzAMg8zMTIqKiobbHcUIISIk7bjjjkpIUtjCNM3oCZMSkhR2+eGHHzBNk9zcXAoLBzZNVjEyEak/AwLItjtB+thSU8+DyLgSkXY2a9Y8AoSjZoXwoOcuwGy5DgLvsKUjsAD3kehZtyOEyhoa7axfvx6fz0daWhoTJkwYlDXczsmMybqGmpa7CVdAi63QqJHi2ovqtoUYVlOXeRKD2vanCJmbKck4g/VNd7F1Z2spwUTEWAzvd2ARSnipr2HKND5qXExb6KGYrQ52zZnDgQW/QFONkxISSYse6jUV2wefffYZAMcff7ztOZHzoIaGhn6vf8stt+B2u5k+fTpvvfUWkydP5pBDDrHdnPmGG27o1/rqm2U7QzWEUNglIghMmzZNCUkKW0gpVdq+ImnKy8vx+/2kpqYO6R1WxcgmtmmR+o1SRBCpZ4LnRAi8DeZm0PPBPRuhpdPc3ExVVVU4/brzZofQcnDkPIQ0NiJD/w1vc+2L0McO47tQbEtE6qDtsssuaJq99giG2Uhzx0JavIuxrDbczmnkpJ9LumdWwu+roqzLcDkmUNv6N/yh8M1cXcslP/08AlYHTYGviJ+iLWnyvUFRxrlkuHajLfg1sQKmhejsaB0eG0EXEilNDHQEekzXbA1TplBnpiDl5i4rWRh82fQ8IcvL4WOusfW3UCgUydHc3AyQ1M3VUCjcXM3ud1RP3HTTTdHvKSEEpmmyYsUKVqxYYWu+EiAVCkXSSCmjdfyUkKSwy6ZNm2hvb8flcjFx4sThdkcxQoiNmh2IEyfF9k8oFIr+Rqn6j4qtEVoqpHSPHFmzZg0QTr9OT0/vOscxDuEYNyT+KbZNpAzi9f0Hf2AlIPC4D8Ll/FH0N8pu9+tA6AfKak/GtBqJCIEhcxPt/rfJSj2Zktw/I0T837qctBPITj0ew6pFyhBOvQghnPy3ci96blKj0+h9leljnqCs6a9Utz+HJX2d0Y86W0dFRnAIC10K8tKOojX4PZpwU5w2ix/af8Dy/jfBPMm3La+yZ+4ZZLnUZyYekkR/8cFdU7F9kJOTQ11dXVLRjJHAoYKCggHxYesmy0PZdHnUCJCzZs3q81whBO+801MRa4ViZFFdXU1bWxtOp1MJSQrbRH78pk6disMxan4+FP1AStml/qNCYYe1a9dGmxapWrMKu0QESCVaK7YmEPyK2vqzMa3NRC5/2zoeY1PlngQCB5KRkcH48eN7tSOlSUXduZhWE13TqMPiYYv3BTyu3cjL+HlCG0IInPqW0kdSWhhWcy8rm3hD5VQ0P4jf3ER+yizS3XuiiTTWNMzvcaYQJsWph7JP0d0AdITqWFp7cs9z0Pih9S32zZ/bi18KhSJZdtllF5YvX87777/PEUccYWvOM888gxCCffbZp9/rW5bV+6BBZNRcQS5btgwhRI/q7tYh85GxKvVHsb0RSaOdMmWKEpIUtokIkCpqVmGXqqoq2tracLlcTJ48ebjdUYwQVPq1Ilmam5vZtGkToGrNKrpimnVsrjsFS7Z1bjGi+9atywdg550n2fquafe/S8iM3wgmQkPbw+SmX5gwCnJrhNBwaLkYVmPCMYbUqfevAv+nhMVOnVrvEly6vZqVlgxEn3/a8M/efULgM5tt2VYoFMlx/PHHs2zZMh544AEuvfTSXkvoPfbYY7zxxhsIITjppJOGyMvBY9QoDzNmzOj1h6Wjo4MffviBlpYWhBBMmzZN3XlXbJdEBEjV/Vphl8bGRurq6tA0jalTpw63O4oRQiT6cYcddlA3OxS2ME0z+hulhCSFXSKidbz0a8Xopq3jKSzZSteIRTAMncqKcNTjxEkbbNnyBj4mfPlsJBxjmFUYZjVOh/06owXpp1Hd+jDx0rBNKTCIiJlml/8GjI227Ge4w9+lm32f8kPLks6tia+LLSwyHKpBZSJUExpFf/jFL37BPffcQ3V1NbNnz+bJJ5+MWwKisrKSu+66iwcffBAhBFOnTuXMM88cBo8HllFzNbBs2TJb46SULFmyhMsvv5zGxkb+8Y9/cOihhw6ucwrFENLW1kZ1dTWAEpIUtolEP06YMAGPxzPM3ihGCir9WpEsGzZsIBAIkJ6erpoWKWyj0q8Viejw/putxUeATRtLMUIu0tLayMh+D7hqyH2LUJx5IQ0diwiadcSKkFKCQeKOtEKYCKkh0Yn3HkEnwzWVTNdubOxYwfKq34LQEFJ01hRMJGpJpmb9uM/vRzG6CIVCPP300zz//PN8+eWXbN68mYyMDIqLiznggAM46qijOOWUU3q08fXXX3Pffffx9ttvs2nTJtLT09l5550566yzuPDCC23fxH722Wd57LHH+OKLL2hqamLMmDEcdthhXHrppRx44IED8Xb7TUpKCosWLWLWrFl89tlnTJ8+vUt22SWXXEJdXV30ZqyUkoyMDF544YXtopb6yH8HA4wQgmOPPZb3338fXdc56aSToikdCsX2QKSw/9ixY1WUgMI2KmpWkSz19fXU19erqFlFUkQi2XbaaSeVfq2wRWtrKxs3hiPBVNSsYmuk7Ii7vWzDFAAmTFoH0mvLVqr7AHqKfgRw6CU49OQy6Jx6HruMeZEsz8FdtgvhRvYQqQjgROAQKbCVUCnQcWhp7FZwF6YM8NHmm4iIlHq0pUn80mQlKXuQ5shP6j2MKuQwPbZBvvjiC/bee2/mzp3La6+9RmVlJcFgkIaGBr766iseffRRfv7zxDVRAR599FH22Wcf/v73v7Nu3Tr8fj/19fWsWLGCSy65hMMOO6zXhi1+v5/jjjuOM844gzfffJOamhoCgQDl5eUsWLCAQw45hFtvvXUg33q/2G+//fjwww/ZbbfdutRLB/jggw/47rvvkFIipWTnnXfmgw8+YLfddhtwP5YuXcq5557L1KlTycjIwOFwRG/oRVixYgUPPPAACxYsGJA1R00EZLIUFxdz1VVX8dvf/pa77rqLv/71r8PtkkIxIEQESCUIKOzi8/koLy8HVP1HhX0iUbOTJk1SUbMKW1iWFT0JV0KSwi4R0bq0tJSMjIxh9kaxreF07oJhVhEbWWgYDjZWTARg4uQyXM69bNlK98zCqY8nZG4iUdfqvIyLbdd/hHBjG2/wGyzpY0r+nzGtdrzBNQjhwqEX8Wn1nB7nCyEYm348aClsansew2pDEymUpJ/AxKyLSHGOZX3rEkJWe3g8EgQ4pIWJhkSyJRJSoiE5sOBXtv1XjF6++OILjjjiCBobG3G5XMydO5ejjz6acePG0dzcTHl5Oe+88w4rVqxIaOONN97g4osvxrIsioqKuP766znggANobGzkkUce4aWXXmLlypXMmTOHpUuXJowAvPDCC3n11VcBOOKII7j88sspKSnhyy+/5LbbbmPdunXccMMNFBcXc9FFFw3K3yNZdt99dz7//HOWLFnC4sWLWb16NbW1tZimSV5eHnvttRfHH388P/vZzwY88tHr9XLeeefx0ksvAT33PtF1nXnz5iGE4IADDui3hqAEyB6IpF4vWbJECZCK7QLDMFi3bh2gItkU9vnhhx+QUlJYWEhOTs5wu6MYIUSEJCVaK+xSWVmJ1+vF4/EwYYK95goKRUSAVOnXinhkpp+Hz/9Gl22bKksxDCdp6W3k59eQkX6+LVtC6IwveJKy2pMxrUa2pD3rgElW6snkpl9oy5aUkrr2hWxquY+gWRO1k5t6NBNy5uNyFGLJILpIx5Ttie1gkJ2yL4VpxzA152osGUAT7qiQELLaqWh/A9AQwsKBSUg6EAIcWEi5JbhOQ6MkbR8KUlTZlB4ZhhqQbGM1IP1+P6eccgqNjY0UFxfz5ptvxo3Qu+CCCwgGg3FtGIbBvHnzsCyLzMxMPvjgA6ZMmRLd/5Of/IRLL72UBx54gPfee48FCxZw7rnndrOzfPlynnnmGQCOO+44Fi1ahK6HI4L3228/jj/+ePbZZx8qKiq49tprOfnkk8nOzh6Av8LA8NOf/pSf/vSnQ7rmaaedxmuvvYaUkv33358ZM2Zwzz33xB178MEHs/vuu/PVV1/x4osv8rvf/a5fa6sU7B5wuVxAuIunQrE9UFZWRigUIiMjgzFjxgy3O4oRgkq/ViRLW1tbNCVSCZAKu0SEpB133DF68aBQ9ER7e3s0Ql9FzSri4XHPJD317M5XYREnkn49cdI6MtLPw+M+zLY9t3MqU8YspTDrOtzOXXHq40n3HEFp/pOU5P7FdvTjppb72NB4fYz4CGDS6P0PX9ecRMisRxMuSjLOIPElu4ZTyyE/9UfhdycEuuaJio/rWp7jtbIfUev9gEjEpi4kDmESyesVQqIJiSYg3zONI4pvsf23UIxe7rnnnuj1wTPPPNNjenBEU9maRYsWsXbtWgCuu+66LuJjhLvvvjsa/HD33XfHtXPXXXcB4Ui9Bx54oNv5Q35+PnfeeScATU1NPProoz29te2eRYsWsWRJuBnVww8/zMqVK6N/w0TMmTMHKSXLly/v9/pKgOyB999/H4DU1NRh9kShGBhi069VbS2FHUzTjJ4cKCFJYZfISenYsWPJzMwcZm8UI4HYGkiqaZHCLhHReuzYsWRlZQ2zN4ptESEEeTl3kZd9Fw7HpHD6dWU4wnqP6ceSl3170ufEDj2X/MxfMWXMm0wt+YjxBU+QkXKkbTsBYxObWv6SYK9J0NxMVcuDAEzIvpQM1+5s3TBGoKMJJ7sU/g1NdBd4ytv+zef1t2PKAFqXNGtwCAu3MHAIi3ALG0mus5jjxj+CW1e/2YqeMU2Thx56CICZM2cyc+bMPtl5+eWXo8/PP//8uGNSU1M59dRTAfjqq6+i17IR2tvbeeeddwCYPXs248aNi2tnzpw50fPRSNrxcDFp0iSmTJkSvb6yQ0VFBZMnT44r0ibLE088AcDZZ59tOx19n332Abb85vYHJUAm4KOPPuKWW25BCMH+++8/3O4oFP1GSqnqPyqSpry8nEAgQFpaGmPHjh1udxQjhEj9RyVaK+xSU1NDS0sLTqdzQE6wFaODyMWQin5U9IQQgoz0cxhb9D7+9hcwDCfZ2dnsMOWCYbkhX9f+Aok7UAOY1Lb/CykNdC2VPcY8xeSca3E7wudhmvBQmHYiexcvItuzX7fZUpqsabg/+loTEg2L2E4mQoSFSJdm4tRM9i2Yp4ITbCLl8Dy2FT788MNok97Y7tZer5e1a9dSXV2NZcXryt6VSG3IHXfcscfMvMMPPzz6PBIgFuGTTz4hEAh0G7c1Lpcr2gX7k08+IRQK9erfYFFeXk5ZWVnC1PR4hEIhysrKKCsr6/f6q1atQgjBaaedZntOcXG4sVZdXV2/1x81NSBvuaX3cHLLsmhqamL16tV8/PHHWJaFEIIrr7xyCDxUKAaXhoYGmpqa0HWdyZMnD7c7ihFCREhSUbMKuwSDQdavXw8oAVJhn4iQtMMOO+B0OofZG8VIwOv1Ri/GlACpsIMQgm+/rQTCNUOFEEhpYVoN4YhCLaff5zqWDNLi/Q/t/hVITFJde5OTdhK6lh4dEzA20rMACZbswLDacOo56JqH0qwLKc26ECmtXtO8mwJf4zM3d9nmxCCIo7Or9paqjwKNfQuuZlx6YvFGoYhl5cqV0ecHHXQQn3zyCfPnz+ftt9+OCo+5ubmcdNJJzJ8/P25N5/b29mipnt6yHmL3bx2BF/vajp0333wTwzD44YcfRm3d4EhH8b4EltgRlntj1AiQN910U1I/KFJKHA4Hd911F7Nnzx5EzxSKoSGSEjlx4sSEtTgUiliklKr+oyJp1q5di2ma5OTkUFBQMNzuKEYIKv1akSzfffcdUkrGjBlDbm7ucLujGAGEQqHoec3OO0+jqe0Bmtr+gWmF6zC6nLuQmzGPjNQT+2TfH/qe9bVnEzKrCV9mS5o6XqC6+TYmFjxChifc4NSh2SkXoKNr3cuA2akxGTRb48wDlzQISgetloeAdCER5LhK8VsuTGmgi1EjDfQLOQxNaIa86U0PrFmzJvp85cqVXHbZZRiG0WVMY2Mjjz76KC+++CKLFy9mxowZXfZv3Lgx2nk5Udp0hNLS0ujzysrKLvtiXydrZyQJkC0tLcDAlAbMyMigsbGR1tbu3xOJiDSxzcvL6/f6oyoFW0rZ4wPC/yDTp0/nsssu47PPPuOKK64YXqcVigEikn69ww47DLMnipFCXV0dzc3N6LquUiIVtolNv1ZRswo7NDQ0UFdXh6ZpqkSIwjYq/VqRLGvXriUUCpGdnQXuG6hv+UNUfAQIhr6lpvFXNLT+MWnbptXGus2nEzJrO7cYRBq/WLKDDbXnEwiFswPy006M7ouPTm7qMWjCnbQfAOnO0rjbA9JJrZmJv1N8BGgKbuTdzX/h3xvnY8rhS0tV2KO1tbXLI5J+PJQ0NjZGn1955ZWYpsm1117LunXrCAQCrF27lquvvhohBM3NzcyZMyeash2hra0t+jw9PZ2eSEtLiz5vb+/aEX6g7GzrLFiwACBuNGmyRM6zPvnkE9tzXnzxRQD22GOPfq8/am5zDES4qEIxUvH7/VRUVAAqkk1hn0iUwKRJk1TUrMIWlmVFb3aoSDaFXSLRjxMnTiQlJWWYvVHYRUoDQl+B9IFjCkIvHLK1/X5/NCJDCZAKu0Qit6bsoOELvBVnRPh6sbH1j6SnHIPbaf/Yaup4EcOqJ7bO4hYkEoO6tscYl3srae7dyEk5iibfW9E1t6AhhIOxWZfaXntr0l0TyPPsSaP/C2SnfUtCvRkRaGJvDob9Le9Yzf8aX2TfvNP7vK5i8ImN4gO48cYbuemmm4bUh46OjujzQCDA3XffzdVXXx3dNmXKFO6++25yc3P5v//7PxoaGrj99tv529/+Fh3j9/ujz3u7xnC7twjxPp+vy76BsjOYzJo1K+72uXPndhFF4xEIBFi/fj21tbUIIfjxj3/cb3+OOeYYVq5cyQMPPMCll16Kx+Ppcfzrr7/Oiy++iBCCY489tt/rjxoBUqEYzaxfvx7LssjLy1NpSgrbqPRrRbJUVFTg8/lISUnpdpKsUCRCpV+PLKSU4H0K2fEgWA2dWzWkexYi8waEnriZwEDx/fffY1kW+fn5qtSDwhax6dfFpe8RTgRMFKCi09L+FIU5t9m23+J9vZcRJi3eJYzLvRWAHQr+yoaG/6O+Y1Hnfg0wcelj2CH/r6S6+ldDeY/837F801wsGURi4rXcnVGPiTITJJ81LWKf3FNtpXmPaqQIP4Z6TcKpw5FuztBVVNsawzAGpKbyY4891qVLdaxgNW7cuIT9Mq655hruu+8+qqurefbZZ7nvvvuimTGxNnprxhIb5bn1TcqBsjOYLFu2rLPe7JabE1JKVq1alZSdyZMnc9111/Xbn3nz5vGnP/2JsrIy5syZw1NPPRU3tdrv93P//fczf/58LMuiuLiYuXPn9nt9JUAqFKMA1f1akSxerzdaHFoJkAq7RNKvp02bhqapCxhF77S1tdkuRK/YNpDtf4aOh7baakFgKbLhC8hbhNAHVxSMiNYq+lFhl3Xr1hEMBsnKyiIz938kFh8BTAKhb5Oyb0kf8aMfY8dsidbShJsp+X9kXPZvaPa9g2X5SHHtSJbnsKQFwKDZysb2xTT4/gtArmcfSjNOYObYJ/m68V5qvO/js3oXojqMBrxmC2mOnKTWVwwdmZmZXQTI4SAjIyP6fPbs2ei6Hnecw+Fg1qxZPP300zQ0NLBhw4ZoI9RYG72lQ8dGXG6dZj1QdgaTGTNmdClJtHz5coQQ7LPPPj1GQAoh8Hg8FBcXc/DBB3P66af3GjFph+zsbBYsWMAJJ5zAG2+8wfjx47t0EL/11ltpbm7mgw8+oKOjAyklTqeTp59+utdoSTuMGgFS0zQ0TeOLL76wXXB03bp1TJ06FU3TuhVWVShGClJK1q5dCygBUmGftWvXIqWkqKiIrCw7xdIVox0pZZf6jwqFHSLHzNixY7tcSCi2TaRRCR1/T7DXBKsB2fEwIvP6QfMhFApFb6wqAVJhl0j69c4774ympWBZPaVgamhachf6Ka7d8AY/J3FtR40UV/drULejhKKMc5JaK5Z63yo+qfk1ptzyfmq8S/mu6X72H3MvBxffS0eohifWnU1vAimgGtHYQMrwY6jXTBaHw9Gta3RfKC4u7vI6NsMlmcYvtbW1UQEydl7kJmQiYhvNbJ1ds7Wdfffdt092BpNly5Z1eR25Qf/4448PWyOcY445htdee41zzjmH2tpaXn/99ahI+txzzwFEIzbz8/NZuHAhM2fOHJC1R9U3jOzjN0Vf5ykU2wI1NTW0t7fjdDoZP378cLujGCGoqFlFstTX19PU1KSaFimSIiJAqujHkYH0vUQkVTQ+JvieR2b8FjFIQsbatWsxDIOsrCzGjBn8dG/FyMcwjOh3zS677II75ThaOhaQ+Di2yEhJrtZZXvrZNLQ/2cMIi/yM85Oy2Rs+o4aPay7FkkG2FhdN6ePjmnkcUbqYjR2rgBDQUxSkxK2l4tHVjaDticH4bd11112jz02zp2ZKXfc7HFt+E9LT0yktLaWysjIa0Z6I2P1b33SKFfDs2nE4HMPalPXcc89FCEFOzvBGGs+ePZv169fz2GOPsXjxYlavXk1zczMQ7ra91157cfzxx3PJJZcM6A3iUSVAJktEeFRdPBUjmYiQNHny5C5f/ApFIkzTjEbNqvRrhV0iF3eqaZHCLpHi6qAEyBGDWdX7GOkF2QZicC6uYtOvB+McXUoLGfwQ0/8fsNoRjknoqacg9LH9s2s1Y/oWY5mVCJGFnnIsmmPSAHmt6In169cTDAbJyMhg3LhxhIyf0+r9V+e13tap2DoOvYS0lGNp979HIPQtmkglPeVHOBPUNw2ZdbQHPiLNfSAdgZV0rS8pAElO6hyyUo4Z0PdV1vqvTvExXjq5RMog5a3P8V3bZ2hIBLJTpoz3uRHkuUoG1L/tFomdYNKBX3MbYcaMGdHnkWZgiYjdP3Zs1+/QQw89lIULF/Ldd99RU1OT8IbS8uXLo88POeSQLvv2228/XC4XwWCQ5cuX87vf/S6ujWAwyMqVK7vMGS4ef/zxYVt7a1JTU7n00ku59NJw0yvDMDBNs8faov1FFWjqgYaGcGHtgci1VyiGC5V+rUiWyspK/H4/qamp3U4WFIpEqKZFimT54Ycfog3S8vPzh9sdhR00O6KiA8TgnDubphm92TEY6dfSaibUcAqhxnOxvM9h+Zdgtv+NYO0MjPZ/9Nmu0fEU/s37E2q9GbPjCYz2vxKom0Ww+Rqk7LlxgqL/xKZfCyFwOSczNv8ZNBGppecgEpfjdEwiL2s+62uOpKLuDDY330p10+/4oWo/qhqvxpJbGllIKaluvos1m/ajqulmOgL/7dyzRRB0O6YwLvcOSvP+PCDNXUzLj2mFfajpWEZPtSwtaVHW+hpNgXVoQuIiFCM9ypj/ShyY7Jr90377p9j+mTRpEnvttRcAb7zxBl6vN+64trY23nor3G1+ypQp3VK5TzzxxOjzRKKc1+uNpgTvsssu3c4xMzIyOPLIIwF4++23E6Zzv/TSS7S2tgJw0kkn9fDuRjcOh2NQxUcYhQKk3TulHR0d3HfffQAqlUwxYvH5fNEv4uEMNVeMLCJCUqQGrkLRGx0dHdHaOqr+o8IuKv165CFSjidx2iqADp6fIsTgRJds2LCBQCBAWlpar7XH+kKo6VfI0Bedr0zC4o4FSMy22zB9S5K2afheJdR6A+EUWAkYRP6Gpu9FQi03D4TrigTEitax6Zop7gOZVPJfinL+SlbaWWSnn0dJ3gKKch9iU8PlhMxNnSPD//5g0dzxL6oarojaqG29j9rW+9hyrIS6rF2SczM7lSwlL/2sfomPUkqq2hbx0cbjebd8L94t35OPq04lZDX3MAcC0kmT0YzEREciBLgI4cRAQ6JhoWPhIoRb05ma+aM++6gYXUQiDZubm/nNb34Td8yVV15JW1sbAJdcckm3/SeddFJUZ7n99tvjRlNec801NDU1RZ/H4+qrrwbC0XuXXnppt7Tw+vp6fvvb3wLhBiwXXXRRr+9vqDFNk/r6eiorK6moqOjx0V9mzZrFkUceSXl5ue05VVVV0Xn9ZbvNx4wUON2aH//4x722ow8EAtTW1mJZFkIIjjvuuMFwUaEYdNatW4eUkoKCAtVIRGEbVf9RkSyRY2bMmDHD3p1RMTIwTTN63CjReuQgnLsg3UdD4A3iR145EOm/GLT1Iw0VdtxxxwG/QWYFv0AGV/YwQmC234fmOcZ2QIOUEqPtj0TScOOMwPQ9i8yYh9CL4+zvybaFGXgfI/A2UobQnbviTDkRoQ1dd9eRwIYNG/D7/aSlpXVrPKGJFDLTTiEz7ZToto31v0QSIv7xbdHqewV/8Nc4HRPY3Pq3HteubbmP/PRz+1UPVUrJNw03s6ntX8SmTrcGviYkBaAT79gy0Al1XurrWJhCQ5ed/+0UHmPZL+98nFpqn/0cTUgpkHJoS7QN9Xq9ceqpp/LEE0/w2muv8dBDD1FZWcnFF19MaWkpFRUVPPTQQ7z++usA7LXXXsybN6+bDafTyb333stxxx1Ha2srhxxyCL///e/Zf//9aWpq4pFHHuHFF18Ewuna55wTv1nTrFmzOP3003n22Wd55ZVXmD17NldccQUlJSV8+eWX/OEPf4gKd3fcccew116MUF9fz3333cfLL7/MmjVrsKzE0cwRhBD9bo68bNkyhBBduoL3hs/ni87rL9utAFlWVtZtm5SSTZs2dR/cAwceeCDXXnvtAHmlUAwtkfRrFf2osEtTUxP19fUIIVT0t8I2Kv1akSxlZWWDGsmmGDxE9t3IxjoIrY6zNwSh78Ex8OcdlmUNavq1FXiHsJiTKMJTIo3vwaoG3V6tPGmsRZplvY3C9L+JI+08+76aNXgbzsUyviVyORfCwN/6B1Jy7sfpmWXb1raGlAZ+/1sE/GFh1emaTmrqyWhadp/sRUTrnXbaqVfR2pJ+Wn1L6DnK10GLdxFu155I2VMnbTCsejoCq0j3HJSk11uo9y3vFB+hq9Bo4UAQTJDQGJSOzvECh7AwLC1mdkREkAgE2Y4x7JZzap99VIxO/vWvf/Gzn/2MN998kyVLlrBkSfcI8f32249XXnkFj8cT18YxxxzDQw89xLx589i8eTO//vWvu43Zf//9WbRoEbquJ/Tln//8J62trbz22mssXbqUpUuXdtmvaRrz58/nF78YvBtkyfDhhx8yZ84c6urqRl3D4+1WgDzvvK4/4k888QRCCI4//niys7MTzhNC4PF4KC4u5uCDD2bWrFmqCY1iRCKlVPUfFUkTiUgaP358wpMFhSIWwzCiaTMqkk1hl4iQNG3aNHWeNdIw1kLovwl2WsiW34BzF4Rj4oAuu3HjRjo6OnC73UyaNAjNW2SA+M05thomAzZGRQa32xikIaX9SBQpQ3gbzsAyyjq3xETDSC++xovQCv6N7tw13vRtGsOooKH+DExzA+HLVInP9yKtLbeRk3s/KSlHJ2XPsqwuTYt6H99Bz+JjGNNqwrTabPlgd1xr4AuqWp+mNfApQjjITTmCkowzqGx9BoGOjOOXJiQOaWGgIdCQkahGqWHFCJORr1irW7SkCEuUWipW516FTUaXZhSX9PR03njjDZ599lmeeOIJPvvsMxoaGsjOzmbPPffkjDPO4Nxzz+1ROAT4+c9/zkEHHcS9997LO++8Q1VVFWlpaey8886cddZZXHTRRb02Uk1JSWHJkiU888wzPP7443z++ec0NzdTVFTEYYcdxrx58zjooL7fCBhIGhoaOOGEE2hoaCA9PZ2LLrqI7OxsbrrpJoQQ/OMf/6CpqYnVq1ezePFi/H4/hxxyCBdeeOGw+RyJlhyIa8PtVoB87LHHurx+4oknAPjDH/7Qpf6HQrG9UlNTQ0dHB06nk/Hjxw+3O4oRgkq/ViRLWVkZwWCQ9PT0bgXGFYp4SClV/ccRjOxYQLiMfGKhRnqfQWT+34CuGxGSpk2b1usFbV8Qzp3oIubFHZSOsBn9CCD08XTtiBwPE02PXzoqHob/LSwjUefZcEORQNvfSc2917bNbQEpAzTUn4oZrb0Y+28RoKnxYvSCJbhc023brKiowOv14vF4mDhxYq/jdS0TIVKRMn5TjU5PcepjcdsU2N3O3sXyypZHWd90Zxeh0RsqY1Prk5giNa74GMEhTFL1EpyO8TT6PwUgx7MXbb6vomNCloYRvezvLp83Bjewpvll9sg93dZ7UihiOf300zn99P4dO7vtthsPP/xwv30588wzOfPMM/ttZzD529/+RkNDA263m48++ohdd92Vr7/+mptuugmAuXPnRsfW1NRw5plnsnz5cg466CDuvPPOYfH5P//5D8CAZKxstwLk1tx4440AFBYWDrMnCsXQEBGSJk+ePCgn6ortj2AwyIYNGwAlQCrsE5t+rSLZFHaoqamhtbUVp9M5OJFsisEl+CE9io8Y4H8VU3gQegnC81OEltGvJaWUUQFysERrzXM0iJtBthI/vElHTz0dIex3CBV6HprnKCz/m8T/mwnQctE89gv7G/436DlV3MTwv4aUfx1R38k+3xJMM1GDhfC/R3v7Q+TmPmDbZqT79U477YQlq2hsfphW70tYVjtOx3iy0s4jK/0sNJECgBBOstNOo6n9SRL/fS2y007FoZfgckwgaFQSX2DWSHXticfZ8/lUk28l65vu7HyXsWuaSCwMGxGUKY5c9i/5B03+NVS0vYrfrCdFz8VnNiGl7JKOHR/J10qAVCiGhP/85z8IIbjgggvYddeeI9XHjBnDkiVL2GOPPbjnnns46qijmDUruRIbF1xwQdztv//973vMDIZwb5R169axatUqhBAcfvjhSa0dj1EnQCoUowVV/1GRLBs2bMA0TbKysigoKBhudxQjACmlqv+oSJqIkDRlypReGwMqtkXi5x7Kzv8BYNVCx8NhQaX1VrTM69FS+x6VsrnmK5qamtB1fdDOa4Rw48y5l1DjRYQFpVgxSEM4dkRPvyxpu87M6wkEV4PV2M0mCFxZ9yCE/c9BODqvtzThID0LTtsefv8b9BwtauL3vW7bXqxoPWUHDxWbj8SSPiJ/u5CxnvqWG2nzvcy4/OfQOhuwFGReRpvvPxhmHfH+zgWZV+F0jAWgNPce1tee2XnUx/qtowk343Jv69XPTa2Pk1hQlp2J1RqJc34FBak/YvXmG6ho/3dnFKWFKTXC7WcEEkFvx0J7aHOvvirCqCY0iv4QuUb/0Y+2dJ2PvVlkmmaX4KGUlBSuvPJKLr30Uh566KGkBcjHH3+8280oKSWLFy+2NT9SozI3N5frrrsuqbXjMWoESIViNOHz+di4cSOgBEiFfWLTr0dS1IRi+KitraWlpQWHw8HkyfZTCBWjm4horWqGDh3SagSzGkQWwtHPFCrXweB/ma0FE9lNIImk0AawWm8AkY6WcnxSS8ngfzHb7uSbT0PAnkwaW47WfhEy43cI58CXVNLch+HMX4TZ/iCW/3XABC0fPfUc9LQLEFpa8jb1sXjyFxNq+xOmbzEQCm93HYQj40p01z7J2XNMA94msQgp0PSJCDGwXcIHG2n56TlVHSCAlNLWOcqmTZtoa2vD5XLhybqhi/jYuWLYYvAzGlrvpiA7HKzi0AuZVPhvappvpM33etQnh1ZEftbl5KSdG7WQ7jmQHYpepLr5LtoD73duFWSmHMGYrN+S4uo9WrfZ/zE9Ccp6tDqjoPvfR8OpZdBqNFLR/mrnu4rYsgC9U3wMv1cpRfRTKthSGxLAkURkr0Kh6Dutra0ATJgwIbottrZiW1tbt8jEfffdF4CPP/446fXGjx/f5TuzvLwcIQTFxcU93gTeujfKL3/5S0pK7JcgScSoFiDLysqor6/H5/P12n1oxowZQ+SVQtF/NmzYgJSS/Pz8XkOrFQpQTYsUfSMiJE2aNElFsils0dLSQk1NDUII9V0zBEijHNl2FwTeISJeSMfuiIyrEO5D+mRTpJ2D9L/UdR0bHRms9j8hPMfaFsaswIdYTRcAFt+X/QSAHSdVQHADZsMp6HnPIpy7J+1/b2jOXdBy7kNKk3AkoaffN+WEXowr+25k5k1Iqw6hZSK03D7ZcqWeTrD9bz2PSTs/4T4pQ4BAiG3rMtDp2oVA4F16ElYdDvulPiLdrydPyURS2cNIi5aOBeRlXhONgnQ6SijNfwTDrCUQWocmUvC4dkeI7iWNUt17MaVoISGzFsNswKkX4tDzbPkIvX92hIBs5460GxsxrDZEZ6sYiYlLz2V6wV94r/pSto6QNGOjJqXEwIHRGXUbWdkhrXCMpJBMSN82GnSMCCRD34RGNb3ZbkhPT6elpQXD2FLnNjd3y+9BWVkZe+65Z5c5fr8fCN/4T5aysrIurzUt/Bv85ptvDktvlG3rl2cI+O6777jtttt45ZVXoupzbwghuhwgCsW2TkRImjJlyjB7ohgp1NfX09LSgq7rqiabwjaRqFmVfq2wS6T5TGlpKWlpyUeTKewjjTJkwymdnZhjIqeMr5FNF0D2vQjPUUnbFc5dIPP/IVt/T2/NaLpgbgRjDTh36913aWG1XgeYtLSlUFOfhxAWUyds7HwvIcyW+TjyX07af7uExaaUgbWppfUpijIWzVGKO/NGAq030T1lWUN3HYwz7awuc6SUhHwv4W9/BMv4GgDddQCe9Etwen7EtkBq6lm0t93X45i09Pi1zLZGShkVICdObiN8yZv4Wk7KDkJGGW5X14txh16IQ7fXP8CpF+K0OTaWbM8BNPreI/HnSKMwbTZ7Z55HdfurNAc+RaCR4zmAorSfUOtbiSkD3WZF0q6laRHA05nGHSveCgw0LAROabJv/kVJ+65QKJJnhx124L///S8VFRXsv//+AGRnZzNmzBg2b97M0qVLuwmQH374IcCAnDfNmDEDIcSwnYONrNj8fvLyyy+z9957s2DBAlpaWpBS2n4oFCMFKSXr1oW7I6r0a4VdIkKSimRT2MXr9UZLPahINoVdVM3QoUO23dEpPm4tbHRGQrb8HimDfbItUk9B5L0CKSeDPh5Ejj2fbDTUAJDBT8DcBEi+Ly8FYFxRHWkpEaHFAuMrZOj7Png/8nGnX0BK7qPozr2i24RWiDvjalLzHkMIV3S7lBJfy//hbb4Cy/gmut0MrqajcS7+NvtNXQYTh2McWVl/6HwVG2kYFtLcnh+RmnqGLVu1tbU0NTXhcDiYMDEFO+FjydThtEvIrKehYwkNHf/GH4ofhTku83x6TKcXToozTkHXUhmXeSq7FdzBrgW3UZJxArrmxkzwGRaEr2F9uGNSuLuPstBIdYwhyzW2D+9wtCKG6aHYHjjggAMAWLVqVZftP/nJT5BSctddd0XPlQA++eQT7rrrLoQQ7Lfffv1ef9myZSxdurRLCvhQMmoEyMrKSs4++2x8Ph8lJSX85S9/ibZ6F0Lwzjvv8MILL/C73/0umtt+6KGH8vbbb/Puu+8Op+sKRVLU1dXR2toaPukapi8WxcgjIkAq0Vphl7Vr1yKlpKioiKysrOF2RzECCAQCbNiwAVD1HwcTabVhtd0PPaazSpAtyOarkWbfmk8I545oWbeiFbyNyLrT3hzHeHvGY7ohf78hLEDuOKm7gCMTdk3e/nF6ZpNWsIiMMV+RXvQp6UWf4M6Y161LtxF4i6B3Qeer2GjJ8LHhb7sdM7RmaJzuhbT088jNewaX68DoNl0vJTPrZnJzH7WdNh6JfpwyZQrZmUfQW5SuQy/B6Ri4rCHT8rK+/lo+3Xgga+vnsbb+Mj6vOpzvai8gZNZ1GZuTchCTc64FiKZXh9ERONm14H5cen7CtbJc3W/mmFLDQsdEJ0SkA3YiJG1GUxLvTqFQ9IejjjoKKSUvvdS1lMlVV12Fw+GgtraW3Xbbjf32249dd92VQw45hKam8Gf08ssvHw6XB5RRk4J977334vV6ycjI4OOPP6akpISvv/46uv+II44AYM6cOcyfP58LL7yQf/3rXzz66KM8/fTTw+W2QpE0kfTrCRMmqEg2hS0CgQAVFeGLOBXJprCLimRTJMu6deuwLIu8vDzy8xNfUCv6jgz+F9l0MUh7kYYE3kDWLYOchxDug/u8rnAfBloBWPXEFzt0cB2E0G1GWWnhmxo+v4vy6iIApk3oLkAKLbOPHm8/CC2zx9ioQMfjJO6yDKAT6HiK1OzbB9y3vuDxzMTjmYmUAaQ0ECI16RqcEQFy5513xuOaTorrIHzBT0j0N8jJmDdgTXukNPmu9kLaAp/QVfCVNPve4+uaU9mt+BUcWkZ0T2nWRWR59qeqdQEtgU8R6OSlzqIk40xSnKVd7PuNehr8q5GY5Link+GaQIpjDD6jpnN9CKEDslOI7C16TmCqAoMKxZBx1FFHce6552KaJhs2bIiWvtptt9148MEH+eUvf4lhGPz3v//tMu+mm27iJz/5yYD6snTpUh577DE++ugjampq8Pl8fPHFF11qQ65YsYIvv/ySzMxMzj777H6vOWoEyLfffhshBL/61a967d6TkpLCggUL+P7773n22WeZM2cOP/vZz4bIU4Wif0TSr1X9R4Vd1q9fj2VZ5ObmdimCrFAkwjRN1bRIkTSR+o9KtB4cpFmLbLoQpD+ZWUAA2XQJFLyD0Av6tLYQDrSsO7Cafk73br06iFT0zPn27bkOA5HK2ooipNQoyG0iJ6u96yCtAJx798nf0YQZ/IqeIwBNzNAXQ+WObYRwd4vmtENjYyO1tbUIIaLfNWPyHqaq/nQCoa/ZIsaG/5udfjFZaecNmN/NvndpC6xMsNckYJRT17aQ4qyLu+zJdE8ns+CuhHYNy8uX9bexqf1VZMznqyDlUAyzI/o6ttajpDMVG0gsQkpcnc13FDZRTWgU/cDpdPL444/H3XfhhRdy6KGH8vjjj/P1119jGAZTp07lnHPOiXbCHgi8Xi/nnXdeNAozUnIw3s0eXdeZN28eQggOOOCAfp/3j5oU7Ej3n4MP3nJ3N/YPvHWTGU3TuOyyy5BS8s9//nNIfFQo+ksoFKK8vBxQqbQK+0SEJHXMKOxSWVlJIBAgNTWVsWNV3ShF71iWFS31oNKvBwnfc53io9Xr0K5IIBie3w809+HouU+Dc5/YreD+EXreIkQSKa5CS0VL/zXfl4Wjv6ZN2Nh9vfTfbHOdnLdJYupBJh7jsW1OSknQv5SWxgtp3Hw4TXXH4+t4DMtq733yEBBtPjNxIikp4SZCDj2P0sL/UJz3KOkpx5DiPoystLMpLXyDguyb+t3lPJa69hfoWsNyayS17f9KyqaUJp/UzGPjVuIjQL3vI0IxEc8y5v8F4Oyh+U6EHTNnJeWPQqEYPHbccUduv/12XnnlFV577TX++te/Dqj4CHDaaafx0ksvIaVkv/324+qrr0449uCDD2b33XcH4MUXX+z32qNGgOzoCN8ZKi3dEsaemrrlbk9LS0u3ObvuuisAn3/++SB7p1AMDOXl5ZimSWZmpkpvU9hCSqki2RRJE1szVNNGzamEoh9s3LgRn8+Hx+Ppci6mGDik/22SFx8jWMjAin77IFz74chbiF7wPnreq+iFH+PIuR/hmJi0LdN1Pus2hmtZT5u4kS2JWx60jBvQUk/ut7+jAWfK0fQsiAmcNruhS2nS1vRrWhrPJuh/C9NcixH6lPaW+TTVHYlpxG+0MpR8++23QDj9OhYhHKSnHE1x3t8ZV/AvCnNux+PafcDXD5o19FZzcus6kL1R411Og3818T7fEpNE4XEaFi5hxsRDdp/tEG4OKrgwKX9GPXKYHgrFALBo0SKWLFkCwMMPP8zKlSu5667E0dcQLlMopWT58uX9Xn/U3DbMysqisbERv39LWkpeXl70+bp167q8BmhtbQWgvr5+aJxUKPpJbPr1QN7NVWy/qKZFir4QESCVaK2wSyT9eurUqUq0HjRC/Zzfs2iSDEIfA/qYftkoKysjFIKMjHTGTrkcIRtAG4PwHIWIqZ+n6Bl32gUEOxYSVjC2FrB0hMjAlXqKLVu+9ocI+F/ufBU5XsLKiGVW09J4ATkFbw7bOWhbWxsbN4ajZYcr0tqlj6GDr+np8+TUC3u0ETSbaAusASHIck+nsm0xAq1b9COEaz7GomNhxAjOQkAqQXzS2VkPMjJBIJDslX00Hl19nhSK0cITTzwBwNlnn81FF11ka84++4QzGyIR5v1h1AiQO+64Ix999BHr16/nwAPDndUyMjKYMGECFRUVvPnmm+y///5d5rz99tsAZGdnD7W7CkWfUPUfFckSEZImTpyomhYpbNHc3ExdXR1CCPVdo7CNalo0MEirHXwvIf2vgtUOjimI1NPBdTA4poOxnr4JiTq49u992BASiWTbcced0NN+OszejFx0xyTS8h6jo/EikD6INiUxEVoOaXkL0LScXu1IaeDteJjEoVgmprGGUPBjXO4DE4wZXCI3OsaOHUtm5vA0KCpIP4Um35s9jBAUZpwWd0/IauO7htuoaX8V2Zk6rQk3JtkJxUejh4RGqzP2UROSVIKYaJgIkAJdWOhYVHtXAr+2/f4UCsXA0tbWxoYNG2hra8M0e//9njFjRr/WW7VqFUIITjst/vdQPIqLi4Fw4Ep/GTUC5EEHHcRHH33EypUrOfPMM6Pbjz32WO6//37uvvtuDj74YGbNCtfAeOGFF/jLX/6CEIJDDjlkuNxWKGzT0tISFQUmT5483O4oRgiq/qMiWSJCUmlpabS+lkLRE42NjdTX16Npmvqu6QfSKEc2ng1WbWQLmBuQgTfAczKkngH+vtZnssC97Yh8Usrod42qGdp/nO7DyCpaRdD7IkZoNaDjcB+KK+U4hLD3PW4aG5BWb1lhDkLBD4dNgIyI1jvttNOwrA+QnXIEmZ5DaPV/RLyIU49jPAXpp3ebZ1p+/lt9Pm3Bb7vMs2SAkGwgXhOZeM1lYpvQRMRmKcNipAQ0JEJItM41glYbiiSRYRF3yNdUbFc88sgjPPDAA3zxhf0mYEKIbr1LkqWhoQGgTzXcLauvZV62MGpyYI455hiklLz00ktdlOVrrrmG1NRU2tvbmT17NgUFBWRmZnLaaafh8/nQNI1rrrlmGD1XKOyxfv16AEpKSpQooLBFIBCgoqICUAKkwj6qZqgiWSJC0vjx4/F47De7UGxBSgvZ9Auw6ulaEKzznNb/AiL0P0j7TR9XENByFdJq7b+zA0BVVRXt7e24XC4mTpw43O5sFwgtE3f6XNJy7ict517cqafaFh/D2CxCt3VO8BDh9/vZsGED0LsAGTKqaelYRHPHCwRC6wfUDyF0phU8QkH6qYgusT6C7JRZ7DLmeRxxSghUtb9MW3AN8eo86gmimrumVIeJfSWQWFJioHWO7RQkARMdE41Mp6rJq1AMJaZpcuKJJ3LJJZfwxRdfIKVM6tFfMjLC3z+RcoN2iGRZbl2ysC+MmgjImTNncuONN2IYBps2bWL8+PFA+GT4+eef56yzzqK5uTmqCAO43W4efPDBaMq2QrEto9KvFclSVlaGZVnk5OQMyA+KYvsnFApFL/BUKq3CLpFSD+qY6QfBj8DsWSiRHf+ErNuhoy8LWGCWIzseRmQk7oY5VERSaXfYYQccjlFzubJNozsmIkQ2Ujb3MMrA6R6eVP4ffvgBy7LIz89P2IjRtNqpbvotrd5XiBX60tyHMzbvLzh6qc1oF11LYXLe7ZRmX0NbYDVSGqS798DtSBxxtKnteYgjKEJn1CIWMioi9sSW+RoWJpEu6LHztrSlSXMmHwU12pFy6HX2YdL1FYPAQw89xCuvvAJAUVERc+fOZZ999iE3N3dIamRPnTqVjz/+mE8++YTDDjvM1pxI9+s99tij3+uPml90IQQ33nhj3H1HH300a9eu5fnnn+frr7/GMAymTp3Kqaee2qfQVIViqJFSRiMglQCpsItKv1YkS1lZGYZhkJmZSUFBwXC7oxgBBAIBysrKACVA9gcZXEn4tL2H1CurGjoeJ9zxuC91IE3wPotMvxIheuqaPPhEBEiVfr3tIISLlPQL8bb9ifjRkDq6YxJO16FD7Rqw5ZhJFP0opUFF3dn4gp+ydZRhR+B9NtSexOSi19EHsMGRU88lN/XHtsb6jWoSRZkKAS5pEkLrkmIdT6400Tq3ipiox0QINnk/R0oLIUZNYqRCMaw8+eSTAOyyyy6sWLGCnJzea/AOJMcccwwrV67kgQce4NJLL+01M+X111/nxRdfRAjBscce2+/1R40A2Ru5ubn84he/GG43FIo+UV1djc/nw+12K9FcYQspZVSAVKK1wi6RSLYddthh2LqcKkYW69atw7Is8vLyVKR1v7BZd8mspF/drGVr+CGG9oIolqamJmpraxFCqFIP2xip6b/GCH5BMPAW4UpekeNSQ2i5ZOb+c8B+GyyrHa/vNQyzBl0vJC3lGDQtfmMZwzCiv0+JBMg23+v4gqsSrGYSMsppbn+avMxLBsL9uPiNaja3v0zAqMKp51KYdhxprvBNYJeeS8hqijtPyrCw2LW+I519sbv+vWXMGAsNKSUWGkZnHCWEO2U7sBAC2o0afGYzqY7cgX/D2yuxVTCGck3FdsE333yDEIL58+cPufgIMG/ePP70pz9RVlbGnDlzeOqpp+Ken/n9fu6//37mz5+PZVkUFxczd+7cfq8/agTICy64AAhHO55yyinD7I1CMbBE0q8nTpyIrg9v1IJiZNDY2EhzczOapjFp0qThdkcxAogVrZUooLBLRBRQx0z/EM59kTzS8yAtH/SCzlTtvl6tCkiqLuDAE1szVNW03rYQwklm7qME/EvwdzyFaaxHaJl4UubgST0LTR8YEau1/Z80tdyKlH4iEb0NTb8jJ+u3ZKZf0k3k3LBhA8FgkIyMDEpKSuLabO54nq6i6dZImjqeHRQBUkpJWfO9VLQ8AAhEZ5RiRcuDFKXNYVr+rZRkzOGHxnuI99k10DDpfn4voiGQ4YjH7utCCB0LvcuYcDdsDZc00YTs9EehUAwlwxXhn52dzYIFCzjhhBN44403GD9+PIcffnh0/6233kpzczMffPABHR0dSClxOp08/fTTA1LHe9QIkE888QRAUu3GFYqRgkq/ViRLREiaMGECLperl9EKRbhrXlNTE5qmMXny5OF2RzECiO1krNKv+4l7BuhjwawhfoSjQKSeB1p+Z7p2X9DBfQRCDG+jIJV+vW0jhI4n5Xg8KccPiv22jmdobL4+ZkvkeA/Q1HILQrjITL+wy5xI9+sdd9wxYQRm0FhPb5HEhlnXR697pqrtKSpa7u98JZExfmzuWIRDS2dCzuVsbF2I36hGxnzGI9GPiQhHQW69Pyw2bomahO41ICVBdIqcxXj0rH68O4VCkQxTp07ls88+o7Gxcdh8OOaYY3jttdc455xzqK2t5fXXX49+dz733HMA0YY3+fn5LFy4kJkzZw7I2qPmdkekVlVRUdEwe6JQDCzBYDDayViJAgq7qKZFimSJiNYTJ05UorXCFps2bcLr9eJ2u6PN/xT2kaHvkL5Xkf53QfoR2X8HkUHX0/fO5+7ZkHYhpPwU9EkQJ1qqZ8K14kT64KWf2sHv91NeXg4oAXI0ImWIppbbexzT3HI3lvTHzJG91n9sbHu8U4DsCYHTMSYpf+1gyRDlzQ/2MEJS1fYMyBD7Fi8g27NPl709iY8Q6Wm99WuBlBCQzh5nAhSkTFclVZJFiuF5KLYLTj/9dKSUvPrqq8Pqx+zZs1m/fj333XcfP/rRj8jKyop22k5JSeGQQw7hzjvvZN26dRx55JEDtu6oESB32WUXgOhJjUKxvVBeXo5lWWRnZ5Obq+q3KHrHMIxoUwglQCrsopoWKZIlkn49ZcoUVR4kCWToB6z6k5ENxyFbrkI2X4KsOxjpfx3yliDSfw36ZNAKwbk/Ivve8EM4EMKDyH0SnNM7rfV2qt+ZDCUyEDkPIqLzhoe1a9dGOxmrc5rRhz/wMZZV3+MYS7bg96+Ivt64cSMdHR243U6y85fT2HY/7b63kDLcsMkf/Iaa5t/bWj8n7ay+O5+AtsDnhKyGHsdIDBp8y/E4iti3+AkOGvtvJmaFexP0Vv11Sz/rMBpW2KLsXjOyO1qc6EmFQjGYXHbZZUyfPp0HH3yQFStW9D5hEElNTeXSSy/lzTffpLGxkWAwiM/no729nRUrVnDNNdeQkTFwjblgFKVgn3322SxbtownnniCE044YbjdUSgGjEj69eTJk9UdTIUtKioqCIVCpKenq6hwhS1CoVBUtFYCpMIuqv6jPaT0gf9tMKuQSOh4GKRvq0E+6PgbWC2IrPmI9EsT2hN6ESLvX8jQFxD4ECm9YDVB8BOwGkAfA66ZIJyAAdLCMr6Epl8CElz7oaVdgOaeOYjvOj4qZX90Y1nNNsdtadby7bdrABgz9hsa2+4nLLqb6FoRY3Lvp8X7SnRbYgRux45kp52evM8yRMisRRMenHr3Rg7m1p/lRHasLePSXTuQn3oo65v/3qtAKAQIKaMNZhxYhKSOIXu/6aN1/k+RHEKGH0O9pmL7wO128+abbzJnzhxmz57NZZddxplnnslOO+00IDUW+4PD4cDhGFyJcNQIkHPnzmXhwoUsXryYm2++mRtuuGGbEWuuvfZa7r777ujrpUuXDliOvWL7J1aAVCjsEJt+va18Dyq2bTZs2IBpmmRlZZGfnz/c7ihGAG1tbVRXVwNKtO4J6X0R2fb/QHYQabbRI76nkGnnhUVE43uQJjimILT0bkOFczo4p/cY/2S1P4jV8ceuawc/xgp+COlXoKXP69sb6wOWZUVFayVAjk4cDnulGhyOCdHna755H3AwdnwZ4UjA8HFsWnVsqj8DtHH09rkSuJhY+AKalopptdDY/jzN3lexZAce587kpZ9Numf/LnNMq4NNLfdT2/40ptUKQJprT8ZmzSMndUu6YqpzCpGaiz2R6ur6Pfld/e0Y0VIKPZ+raTFVI4UA09IRQqJJq7NLdvz5Fibj0vbq0bZCoRhYYjNCpJT88Y9/5I9//KOtuUIIDMMYLNeGhFEjQK5YsYKrr76auro6brnlFp599llOO+00pk+fTk5OTq+pQTNmzBgUvz7//HP+/Oc/D4ptxfZPe3s7tbW1AKqTscI2qv6jIlli06+VaK2wQ0RIKikpIT29uzimAOlbgmy9LmZLL+IjABqy5fdgfAuyuXObB5l6MiL9Nwgtzf76wc+x2iMXPbFrh59b7X9BuA5GuPa2bbM/VFZW4vf7SUlJobS0dEjWVGxbuJy743TsTMj4jvjJxxoOfTxuV1gMrK7+mOYmB5pmUlJaudVYCxCYvaQ/Azj0AnQ9B39oLes2n4ph1RMRDP2hH2j2LqIg4+cUZ89HCIFpdbCm5nS8oTVd/OwIfsH3dRcxMfcPFGWcCYDHUUKO51Ca/B/S02e8uvV53PoYUpzjWd/8EG2hNVg46E18BNAEmDIicArMTtHRJQz8MlHNZkmaI58dMg7t1b5CoRg4pJQ9vt7eGTUC5MyZM7tcNH3//ffceuuttuYOltJsWRY///nPMQyDwsLCqJCkUNglEv1YXFxMamrqMHujGAm0t7ezefNmQEXNKuyj6j8qkkWlX/eMlBay/Z6+zITQ1l2u/eB9Bhn6EnIXIITbliXL+xQ9R13qWN4n0YdIgIw0Epk6dSqaptJCRyNCCPJy7qSm7mTAoKsIqQEaeTn3RK/pvlzzFgCFY6pwuYJxLJog2zrnJqqmqJOeMhspDdbXnoNhNdI1WjH8+ahrewSPcydy00+luvUf3cTHMOHXZY03kJM6G5ceboI6Ne9G/ld9KiGrhUSftzrvqzT432Va3h2sa/prAl8To2Nhdmk+JXFg4cIgiINIZ+zIexPAieNuRxc9NapRxEXSW0Dr4Kyp2C648cYbh9sFAL755hsefvhhVqxYwfr162lra8Oyeq46OxC62KgRIGHbU5fvvfdeVq1axU477cRJJ53E7bf33PVNodgalX6tSJZI9GNxcTFpafYjZRSjl4aGBpqamtA0TUVaK2xhmmb090ml0ibA+ArMTX2YmOhc1oLQF+B9HtLO3jJaWsjAMizfv8CsAC0PzXMSIuVYZOh/9Bx1aSJDn/XBx76h6j8qADzu/SgufJnG5lsIBLeI7W7X3uRk/R6P+4Dotg3rgoDOuAmJm4xqSCROJEG6f37CkYK56efT6nubkLmxB88Eta0Pkp36Mza3PUXP7WEk9e0vUJL1SwBSnD2frBIAAQAASURBVOPZu2QR5c0PUNP+XBw/QGJiWl6+a7gZgY7ERISrwmI3CtKSFrKzqqNFOB3biYEp6RQnw9acmLiFQa57Qk8mFQrFILAtCJB33HEHN9xwA6ZpDrlGNmoEyKVLlw63C12orKxk/vz5ADz44IMsW7ZseB1SjDiklEqAVCRNRIBUx4zCLpHox/Hjx+N224usUoxuKioqCAaDpKWlUVxcPNzubJtYLYNiVvoWIjoFSCmDmM3zIPAuWyIdf8AKroS22zub0PTG0ERHNTY20tDQgKZpqjyIArdrL4oLF2EYlRjmZnS9EOdW9SE7OjqoqQ5H/IXrP8ZH01Iozn2EjQ0XI2WALcKhhkBnXP7fcTt3oL7tScKXxomieyQBYy0hcyNGr2ndAl9obZctHkcxJRmnUdP+rx7mmQTM+q4NZWxcrktJp1zZOU8IglIQsjT80c9wRMSUhNDRpKQlWEGOW91YTBopwo+hXlOhGACef/55/u///g8ATdM47LDD2GOPPcjOzh6S7INRI0Aefvjhw+1CF371q1/R3t7Oeeedx8yZM5UAqUiahoYG2tra0HVd1UpS2CJWtFaptAq7RERrdcwo7BKbfq1qhiZAHzcIRiXERHBZ7X+FQOQG/FaRjrLZRkqfjvDMHkD/EhOJfpwwYcKwdwFVbDs4HKU4HPHPcSPfMzl59aSldySwoJOZehoZKbOYWryS5o6FtPtXAJJU94HkpJ+FUx8DgOwxojEG4aTnlG4AgSa6l0bybiVK9oaGRMPEikYvdv8+tSSY0U7W4f1O4cdnpsQRH7c8D+Dk47qH+ck4lYGnUIwm/vrXcImHsWPH8tprr7H77rsP6fqjRoDclnjuued49dVXyc3N7dL9WqFIhoiQNH78eJxOVb9F0TubN2+mo6MDp9PJuHGDcfGr2N4wDIMNGzYASoBU2CciDKhjJjHCMQnp3AtCn9OzkBGZkApaEZjlPY8XmQBI6UN6F9D3wmECcKClnNnH+cmhaoYqkmVLzdCIQLl1p2kdXSsgN/MKABx6PvmZvyY/89dx7aW596Wh/YkeVhS49HG49GKyU2bR7FtK4hIGBrlpx3TbGjKbu22zJFid0YsiWlwwLBIKAU5pYSEx0GLeXXi/jCM+QiRysrcO2pL1HasTvVlFT6gakIoRzBdffIEQgltvvXXIxUdQAuSQ09zczOWXXw7AnXfeSUFBwTB7pBipREQBVZNNYZdIJNvEiRNxONTXv6J3ysvLMQyDjIwMCgsLh9sdxQigqamJ+vp6hBAqlbYXROaNyIbTgSDdm20AGb9HaNlh8dF1IASWIVuu6MGiBiknhZ+GvgGZKCosoUdsET88aDkPIRzxb1ZJaSGDK8FYA7gQ7pmIrVJk7RIIBCgrKwNU/UeFPQzDiJ7T7Dn9HNIyJ9DQ+icMM9IJWyc95acUZN+IQ7f325WVegyOpls606vjifyS/MyfI4RgbNavaPa9S3fRs3Nt13Qy3Qd2s9AS2CL4SQkGAokWtSE7a1LGIgToSHRMTAmhmLIIMjq2+xyjS0OaeAhC0mbUp0KhSJonn3wy+vzcc8+Nu70vxNrqC5HApT333LNfdvrKqLwCbW1t5YUXXuCjjz6ipqYGr9fLP//5TyZM2FKIt6qqiubmZjwez4DWSrv22mupqanh4IMP5sILL+yznUAgQCAQiL5ubW0dCPcUIwTLsqICpKrlp7CLqhmqSJZI/ccpU6aoVFqFLWJrhqpU2p4Rzl0g71lk2x0Q02wDxy6QdgnC/B7Z9jBY9aDlhcVFfSqY6+keeaWDyESkRhrQ9EFYcB0OCDT3AYiUnyG0nLjDZOgrzObLwk1tIuJJ260I90/Qsu5AaMk1OFu3bh2WZZGXl0deXl7yfitGHRs2bCAUCpGRkcGYMWMQ4jQyUk8hGPoGS3pxOibj0JM7ljThYlLBP1lXewaW9LHlMxaun5qdOof89PMASHfvxdSCB1lXfxWW7EB0XlJLDDLcezO14O/dfjNNy0+D953oayOmZqOdJjMAugCzM2KSaIOarlhSxIiPvdlVv+sKxWBx/vnnI4RACNFFNIxs7wtb2+oL06ZN45NPPqGhobdatoPDqBMg77//fq6//nra2tqAcE00IQQdHV3vEi9fvpyzzjoLj8fDxo0byc3N7ffa77//Pv/4xz9wOBw89NBD/bqYu/3227n55pv77ZNiZFJdXU0gEMDj8agC/wpbhEIhysvDXSJVVJLCLqr+oyJZVPp1cgjnLojcJ5FmFZg1oOWCSEE2nhHeFhESrc3Q8TBoBeDcC0KriUZKYoE+CZFzHyIS7eXYEXADgW5rJkLL/D2aY2KPY6RRhtl4Jkj/lrUj+wJvYDa3ouc8ntQ5rkq/ViRLJP16xx13jB5rQmi4Xbv2y26qe092LH6XhvYnafa+gmV58Th3Ij/jXDJTjkKILQ0aclN/TNa4j2no+Dfe0HdowkNO6o9Jd+0Z9/g3rTZkp6hpyfjRjnZwEiIz5TDqfavY+kaDKTVC6EhJZwft+HUjw0hStYyk11egUrAVtknUYXqoO0/Hct555/Hxxx/z8ssvc+SRRw75+qNKgLzpppu49dZbkVLidrvZfffdWb06fu2L0047jauvvpqamhpefPFFfv7zn/dr7WAwyMUXX4yUkiuvvLLf+fbXXXcdV111VfR1a2urakQyiohEsk2cOHFIulUpRj4VFRWYpklGRgb5+fnD7Y5iBNDS0kJdXR1CCBU1q7BFbM1QJSYlh9BLQC8BwGq8GMxqukcxWuFoSH0SIu9VCH4AmODcA5z7dhE9hJaBSD0V6X06jp0EPoiUXsdYHY9Al07CW/kX/ABCn4DrAFtrSimjAqRKvx7dmGYDXv9bSKsdp3MHPO7DEKJ7GrGUMtq0aDCOGZejmOLs31Kc/dtex+paGoUZp9uy69CzELiQBDs/PX2NgILx6cewZ8FtrG15iu+bw+mcUhKt+2hIvTO1u0dLFHrUDWmFYrCInA/Z3T5UXHjhhSxcuJCHH36YH//4xxx33HFDuv6oESD/97//ceuttwJw9tlnc99995GVlZVQvNE0jVNOOYV7772Xt956q98C5G233cY333zD+PHjufHGG/tlC8DtduN2u/ttRzEyUfUfFckSEa1VKq3CLpHox7Fjx5KS0rswoVCUlZWpmqF9REoLrGqkWQPB5SQOdzEhtBKEA5E2t0ebWsa1mKFvOqMle0HLB63nfzMpJdK3mMSNNwB0LN+/0W0KkFVVVXR0dOB2uxk/fksNSWlWYXqfxQr+D4QD3T0TLeUkhJZpy65i5CClQWPzrbR1/BMwiHSY1vUS8nPuJcVzSJfx1dXVtLW14XQ6R9R5sCZc5KbOoMH7Nlav4mDPpLmm4HHks2vuFdR6V9ES/B4j+p0hCFiOmPTuxNR4vyRk+XBq6jc+KVQEpMIGseX97GwfKpxOJ4sXL+a8887jpJNO4vTTT+fUU09l2rRppKam9jo/9re6L4waAfK+++5DSsnBBx9su/DnQQcdxL333suXX37Zr7W//fZbbr/99qgfaWnJ1cZRKGIxDIPKynCR7ZF04qUYXlT9R0WyqGNGkSyR+o877LCDutFhEylN8D6J7HgMrBr7E0NfgaPnz6YQKei5T2J5FyPbbgBCicemX23j3ywE+HsZY4HV1MuYLUQi2aZMmYKuh6O3TN/LGM3XEL7itgCBEXgP2v6CM/cJNNd02/YV2z4Nzf9He0dsx/ZwfKBp1rC5/gyKC1/B7dozOj72mBlpDfWK00+lwft2PyxopDunkunaDQjXgzu4+F7er/4lDYEtUVWmTYHTJMgm76dMTD+k98EKhWK7ITs7m8suu4yVK1eycOFCFi5caGueEALDMPq19sj61u4Hy5cvRwjBvHnzbM+ZOHEiAJs2berX2n/+858JBoNMnjwZr9fLs88+223MV199FX3+7rvvUlMTPgk97rjjlGCp6EJlZSWGYZCenq5SaRW26OjoiH6nKNFaYQfLslT9R0XSxAqQit6RUiJbfgv+V5KfLJydNkJI34tY3qfA2AAiBeE5Bi1tLsIxGSFc6GmnID2HYzbMiStyirRL0VNP7n1J4QrXqLQaexilgW6/JNDW9R+t4BcYzVfTNcW7U5iSbYQaz8NVuFxFQm4nhIzyrcTHWMLic3PrPRTlL4huHcz064HEF6rAZ1Ti1LJId+0CCAJmDSBiWsjYv1Ej0NGEm10Lbutys8DjyOfIcc+yvPo3VHlXAhItiXA5w/LZHqtQKLYPrrjiCu677z5g6OtRjhoBsrq6GggXK7ZLJMU5ttt0X4jMX79+PWeccUav4yOp4hBOtVUCpCKW2O7XKsJEYYfIMVNUVER6evowe6MYCVRVVeH3+3G73YwdO3a43VGMAJqammhoaEDTNBU1a5fAsr6JjzjAdQBSBjGbfgHB9zu3S5BBpO85TN9L6Ln/RHSmQgu9EL1gKdL/FtK/GGm1IZw7o6WeiXDYrwMnUs5EdjxA4rqSJpoNMROgra0ten4eEa3Njn+SWJSxQLZi+l7CkXa+bZ8V2y4d3pcJp1wnSus38fnfxbSa0LUcWltbo8fMtlpntj34LT/U30JrcEvpA7c+jnTXjjT4wl2ww+84uXP4TPfu7Jx3Exnu7teyQujsmH06Vd6PAPBoIfyWM7I3gcWwUJnjmpiUHwpAivBjqNdUKAaABQsWcO+99wKQmZnJSSedxPTp08nOzh6S3hKjRoB0uVwEAgFCocTpJ1sT+YHLzs4eJK8UiuSJiEmRCF2FojcikWxKFFDYJfaYUY2uFHaIRD+Wlpbi8XiG2ZuRgfQuBHR6rqm4NRqknIzQcrHaH+gUH7eOXjABidl0KXrhBwgRvqEuhBORcgykHNNnn7W0CzD9S8CsiOu3SL0I4bAXARs5ZkpKSqI3x6zAu3HtxmL5l4ESILcLLKuBngVIAIllNaNrOdHox3Hjxm2TN1Q7gt/zadXJSIJdtgfMjQR8G6OvNWSnAGk3ClLQEviMNQ3z2XvMozjjdK8ek7I/Oa4daQ6uRcfERYggroQWHVgUenYkz6Mi1hWKwWDWrFkDblMIwTvvvNMvG5HIx5122omlS5dSVFQ0EK7ZZtQIkOPGjeObb77h66+/Zv/997c158033wT6n0r0+OOP8/jjj/c45qabbuLmm28GYOnSpcycObNfayq2TwKBQLQkgBKTFHaQUnaJmlUo7BARIKdMUR0yFfaIiEnqmEkC8wfsi4+dQqXrMETm9UhpYnmfJHFnAgtkM9L/H0TKiQPhLQBCy0TP+xdW6+1I/78JNw0BtAK0tEsQqefatrV1+nWY3v4ekp5qWSpGFro+jt7/zZ3oWgGQ6JgZHpp9y6lp/SdtgU8AQabnQFqCm7qJj/EQAhzSwojWauxNiAx/zlsDX7Ombj57FP0F0wqgCSdCaJ02NWaW/Jl3Nv2a2kA5LmEiZYgQjk7bMvpfB5IU3cPM4t/1+f2PZoQMP4Z6TcXIYtmyZQghekxx3jqbMTLW7va+8O233yKE4Kabbhpy8RFGkQA5a9Ys1qxZw2OPPcbcuT13DYRwuvSjjz6KEILZs2cPgYcKRe+Ul5cjpSQnJ4esrKzhdkcxAmhsbKSlpQVN0/rdtUwxOggEAmzcGI7UUGKSwg6GYURvdGwLwsCIQXSPYuo+Jgucu4BWiEiZA64Dwxc0Zg1Y9b1MdiBDX8AACpAAQstFz74baV0PxnoQLnDshBD2LytM04ze6Ig9ZoRzD2RwFYlFKQ3NuWffnVdsU6SnzqGp5VYSp/TrpKWcgKalEwqFos3Rkimp1V8Ms4XN7U9T1/4chtmAy1GMSy+hxb+c2AjmJu97BBDYreuoCXBKCwv7TWOktKjqeIvN5UcQMBsQOChOO5Idsi8gy70zKY48Up2TEYGNICw8wsRpmYTQkZ21JzUk0zJns0/++WS5xvXlT6JQKGwwY8aMHgXDqqqq6E0VIQQTJ06kqKgIKSW1tbWUlZUhpUQIwbRp0yguLh4Qv5zOcHmG4aqjO2oEyHnz5vHQQw/xwQcfcNNNN3HTTTclHLt69WpOP/102tvb8Xg8/OIXvxg6RxWKHigrKwNUIxGFfSIn66WlpbhciVNxFIoIGzZsQEpJXl6eKkGisEVlZSWhUIj09PRhuZs+UhGenyLbvyex+CIQ6b9ApF0U3SKlH8v3DtJYa3OVwTvVF1o2uPbu09zKykqCwSCpqamUlJREt+tp52EEV/a0KnrqmX1aUzHwGEY5llWPro1BdyRfL1jX88nJ+j+aWm6JtxdNyyQ76xog/NtkGAaZmZkUFhb203N7BIwq1tScQtCsIfI59YXW4gv90Dlii1AelhKT+7wJEZYwdSwcIofxOVfxbcNNccdKCcFOIdEwG8LbMKjueJuq9reZlH0eFjpl7cuJjYzWNdAxiQ3Cmpo5S4mPCsUgs2zZsoT7Xn/9dc4880wyMzO5/vrrmTt3brfmsvX19Tz22GPcdttt1NbW8pe//IWf/OQn/fZrp5124qOPPoo2KB1qRk1hp2nTpjF//nyklNx6660ccMAB3HXXXdH9r7/+OnfeeSdHHnkkBxxwABs2bEAIwR133DFgarNC0V9U/UdFsqj0a0WyqJqhimSJTb8ezc3RZOhrpG8R0v8G0mrrfULqKaBlE5YgtkYHLQ9StjR0sbwvYNYeiNVyObLjfhseGQj34Ta9H1piU2ljjxnN/WO01PMir2Jm6IDAkXUnog9Cl2JgCQQ+oq72WGo3H0R93XFs3rwf9fWnEgp+mbStrIxfkpfzJ3Q99npLkOI+nOLCJTgd4eyN2O7XQ/U9s67+KoLmZuJ2Zd+K/mXI6hSlH4fHkVhYNdCQcSIsTWkRQvJ98xN805i4LIMQ4YcmNJqDZf3ydtQjh+mh2C74/vvvOeWUU5BS8sEHH3DNNdd0Ex8B8vPzueaaa/jggw+QUnLqqadGvwf7w9y5c5FSsnDhwn7b6gujJgISYP78+YRCIW677TZWrVrF6tWroz9g11xzTXRcJNT1hhtu4LLLLhsudxWKLvh8vuidChUBqbCDZVlKgFQkTSRqVqVfK+wSESD7WzN7pCJD3yJbfgfGmpitbmTa+Yj0KxAinsAYTmUmdwGy6WIwN7LltNwAfSwi5+/hKEPA8v0bqzW2XluiqMkIOjimIFwH9e1NDTIRAXLrY0YIgSPzBizXAZjeJ5DBz0A40Nwz0dMuRHPtOfTOKrrg9y+jseEctlZEgoEPqas7gfyCl3G5pidlMyPtDNJTTyUY+hLLasPpmIwjRmiWUkaPmYFIGwyZ9bR4XyVk1uHUx5CddhyOzs9aBG/we9oCH9u2qfVDIRI4KMk4B11PQ6AjtypBIGUkTbur+GhFt4fX3rpwgZQgEdHqj4Jw8UKHltJnXxUKRf/44x//SEdHB3/4wx/Yddddex2/yy67cO2113L99ddzzz338PDDD/dr/QsvvJDFixezYMEC9ttvP+bNm9cve8kyqgRIgFtuuYXjjz+eO+64g9dffx2v19tlv8vl4sgjj+T666/n4IMPHjK/eksLVygi6df5+fnbZOc/xbZHTU0Nfr8ft9vdJcVNoUhEU1MTjY2NaJqmIq0VtmhtbaW2thYYnTc6pFGObDwTpHerPQHoeBhptSCy4qWXhhGOHSD/LQi8hwytCm9z7Q+uGdHmElJaWG13JbTRFQ2wQB+HnvOPqA3b7ye4CrPjUQisAExw7oGWdh7CffSARZ01NzdTV1eHECLujQ4hBHrKT9BT+p9qphhYpDRpbr6asAC+teBmAUFamn9HQeFrSdsWQsedQGDevHkzra2tOJ3Oft2El1JS03IPta33E/ZfBwyqmm6iOPu3FGReHB3bHvhfUrY1AVvynJP7rEgClDX/mZ0L/khR2tHUdPyHWDlRxrEpu4iPIio2RkZbUuvstL1lGwg0KSlNHbprXIVC0ZW33noLIURSXbKPOOIIAN5+++1+r//ee+9x2WWXUVdXx+WXX84zzzzD6aefzrRp00hNTe11/owZM/q1/qgTIAH23XdfXnjhBQzDYM2aNdTW1mKaJnl5eey6666kpKi7Qoptj4gAqUQBhV0ikWwTJkxA00ZNxQ1FP4ikX48bNw632z3M3ihGApFjpqSkxNaJ6/aGbL8fpI/4EYkSfM+GIyEdicVZIXTwHIHwhC8wZOg7ZODdcHq2cy8IfQ5Wde/OOHYEfTya5ycIz08QIrnPsOV9Fqt1PmERs1P8CP0Pq/m/iJRz0TLnD4gIGYlkGzdunDrnHmEEAx9gmVU9jLAIhT4jFPoep3PgGhxE0g4nTZqEw9H3y9fa1r9R23pvzJbw51YSpKr5VjQtjbz0swASRi73hAuTYNySCr1T5/0PGa3T2SlvPu2htbQHvyUiHoqEgmbX7UIIHJgELWeXyMjYcRaCD+vu5cdj/9AnPxUKRf+orrbxe74Vkd/egajbOHPmzC6/5R9//DEff2wv2lsIgWEY/Vp/VAqQERwOB9OnJ5cioFAMF6oBjSJZVPq1IlkiorU6ZhR2iQiQozH9Wsog+F8lccdmAB3pW4zIuLJ3e8HPMVtvAOPrLRu1QoTnp7b80VLPQUs93dbYbmsbZZ3io6Tr++kUaHxPIt0HIzw/6pP9WCIp+6pj+sjDMCtsjTON8gEVIGNrhvYV0+pgc+t9PY6pab6H3LTTEMKBSx+T9BqakDhluOt0slGQINnY+jjjMs9n/+JnqGpfTGXr0/iMjQjhwLBMTIyY0fFthPtyR6Ie4/uwoX0FVR2fUpLWtyZSox0BiCGuyTh6qytvf2RnZ1NbW8vy5cs54IADbM2JNLTJysoaEB+kHL6ioqNagFQoRgodHR3RFLcJEyYMszeKkYBhGFRUhC8UlGitsENszVBV/1FhB8uyogLkqDxmrDagt0gAAVZdr6Zk6CvMxjOB0FZr1CK9j9nzR+97V1vLu5AukY/djWN5n0DrpwBpGEb0e2Y4RWtp1mIG3gHpQzh2QHMdmnS6+mhE0+xd/Gpb1VPsK1JKmppXsnHjRgAmTc7os602/3Kk9PU4xrDq6QisIt1zEI3e1+mavmwPXUiENDDQsHAR+UwJnEiMHu0FzRqCZi0uvYiAuZmO0LrOPX40BGbMpXtYkNoiMgoBurQI4qB3uUrwYe2fOHnSgqTem0Kh6D+HHnooL774InfccQcnnnhir3Vtv//+e+68806EEBx66KH9Xn/p0qX9ttEfRq0AuXnzZpYtW8ZXX31FY2MjALm5uey2227MnDmToqKiYfZQodhCeXk5AIWFhaSlpQ2zN4qRwMaNGzEMg7S0NAoKCobbHcUIoLq6WtUMVSRF7DEzblzfxa8Ri5YBuIBgD4MkaL2fU5qttxMWHxM1l4nUcou3X4BW1K+GMzL0OT1HcpoQ+qLP9iNUVFQQCoVIT09nzJjkI8z6i5RBQi23YPoWEv5bdtbM1Epw5fwF3bXfkPs0knC7ZyFEKrJbzdMtaFoxTlf/I+uCoR+obvwl330TAmaRnVtPo3cWIXkihTl3o2nJlXwwrVab48Id7Jt9S+lr62FNgAtBSeaFZKbMAgS1HUuobnumU4TsCcHGtoVsaH6oy1ZdSExpYnU2oxEiHIUnY0RIByaBmMt7KcMp17ClCU0k87I5WI4lDTQxauUAhWJYuOqqq1i0aBEtLS0ceOCB3HDDDZx77rnk5uZ2GdfU1MSTTz7JrbfeSnNzM7qu85vf/Kbf6x9++OH9ttEfRt03TmVlJVdffTUvv/xywvx1Xdc56aSTuPvuuxk/fvwQe6hQdEfVf1QkSyTCZNKkSQPWOECxfRNJv540aZKqGaqwRSSVdvLkyaPymBHChfQcD/5FJBbvLETKST3akWYVhHqrvxRpmBG2GeMFINAyb+1TzbotZlw2Bjn7br+T2I7pw/HbFGz+HZb/ZbYIS51/S6uGYMPZuPMXoTl3GXK/RgqalkZ6xhW0td6WcExm1nX9OxaBkFFFZd2JWFYrVZUzARhbWgFI2nyLMax6xuY/m9Qx5HZMtDfOGR63dSfqvqBpKWR5wmKsYTVT1fZkD6MFHkcpDi2X9VuJj1F7dP3061gYMY1owlGQZrRBjbFV52xBOEVcExKQVHs/ZmzaIf17k6MRKcKPoV5TsV1w0EEHceedd3LNNdfQ0tLCb37zG66++momTZpEYWEhQgg2b97Mhg0bkFJG06XvvPNODjzwwGH2vv+MqrPFFStWsPvuu/PCCy8QCoWi/6BbPwzD4IUXXmD69Om8//77w+22QqEESEXSxAqQCoUdVP1HRbKM6vTrTkT6r0BkQKLGE6nnIRy93Mw27RSV1xEpp4Wb0sTi2Bkt53G0zgY2ySKlhRVYAbKj9/XdR/ZpjVhiBcihxgr9gOVfRPyoNgswCbXdG2efIpb09EvJyLiWcPSvIBLPIkQqWdl3kpp6cr/XaG5/GMtqxbIsqjaWAlBSGqk/aeELrMAXeB9vYDWbGq5kfc1PKa89g6b2Z7Gs+GnWae4DcDkmkPjyVyPVtTeeztqVGe79SPi5toVJlmeLuJebMgOPY0IPNiWlWRfRHvqWoJmobEPXYzesv3bdpguJicCIU4dSAkF0LBkWIze0vZPE+1EoFAPFb37zG55//nnGjBmDlDJa0mblypV89NFHrFu3DsuykFJSXFzMCy+8wFVXXTXcbg8IoyYCctOmTRx33HG0tobD748++mguuOAC9t9//2i69ebNm1m1ahX//Oc/ee2112htbeW4447j66+/VuloimGjo6ODurrwiYiq/6iwQzAYZNOmTYASkxT2CIVCVFZWAuqYUdjD7/dH67KNagHSMQ7ynkW2/B5Cq2P2pCHSL4a0X/RuRMuzsZKJcO6GnnUz0qgAqwa0PISj7397abVgNl0Eof/1MjIsYmhp5/d5LYCWlhbq6uoQQgzL94zpXwydLToSjMAKvIW0OhCaKneTCCEEGZlXkJZ+Pj7fEiyrAV0vxuM5Bm2A/m6tHf8CTOprxxAKunG7feQV1Eb3S6lR3fR7AsZatvybanQE3qO+9a9MLHwBp2NsN79Lc+9mfe1ZnZJd11hCIVyMy90S2Tkm43wava/28R3opLl2J821R8z6OrsXPcznNefECIwSgY7EpCTjLIrTT6PZvzq+SUCPk8C9pelMp0UZER/jEa5pGULHhcH3rW9QlLInU7OO78ubHL1I+pqd3781FdsVP/vZzzj++ON5+eWXefvtt/nyyy9pampCSklubi677747P/rRjzjxxBNxOvufgbCtMGoEyDvuuIPW1lZ0Xeexxx7j7LPP7jamtLSU0tJS5syZwzPPPMO5555La2srd9xxB/feq+6IKoaHSPRjUVERqanJ1btRjE4qKiqwLIvs7Gyys7OH2x3FCKC8vBzTNMnKyupWg0ahiEdZWRlSSvLy8tT3jD4JkXIC0qoGc1PntkLQ8rHTu1Q4JoBzDwh9SeIakC6E56jO8eOB/pcIMpt/DaHPbYzU0bL/jHDu3K/1ItGP48aNIyUlpV+2+oK0mun938MC2QYoAbI3NC2btLSzBtyulBJLhgNGqirDx/mYcRvRtC0KjIWFYaztfGVGtwKEzE1U1J/P5KI3u6Vop3sOYkrRi9Q030l74IPOrYIMzxEUZ/+WFNdO0bEZnn0ozf4tlc130j35uWc8jvFMK3io2/qpzknsN/Y/bG5fRG3HaxhWG2nOHSnJPAOPPo6KlofwBjeQqPlNpNGMGSMwii5qmCAoe7u8F0gEIanjxOL9zfcwJeOnaFr/0uYVCkXyOJ1OTjnlFE455ZQBt33LLbcA8Ktf/Yr8/PwBtV1XV8eDDz4IwA033JDU3FEjQL722msIIfj5z38eV3zcmjPPPJP333+fhx56iCVLligBUjFsRBrQqOhHhV1U+rUiWWLrP6qaoQo7RNKvR3vErJQS2XoD+P5FF3HLLEO2Xg+hNZB5Q6+fKz3jt5iN55BIeNDSL0NomQPnd+grCH5oa6zIvBnNc3S/1xzO9GsAoY+ldxHJDVrOULijiEFKiS/wIR3+17GkH01kYMlWqjaGBcix0fTrro1V4mMSCK3BG1hJmqd7Y6Y0915MKXqWkLkZw2zAoRfi1LtfnAeMjbQHPqNr86feu2Knu/Zi56Jn0DRP3P0OLYOxmecyNvNc2gJrqGp7hm9qryBo1XXa1xBYyGjjqa3mYyGhSzMah4zUggTTZq1AiQhHTkqLb1teZJecU23NUygU/UPTNDRN47bbbuPaa68dtHVuuukmhBCcfPLJAy5A1tbWRu0rATIBVVVVAEmpy6eccgoPPfRQdK5CMRyo+o+KZIkIkOqYUdglcsyMdjFJYR9V/7GT4Pud4iN0FSY6n/ueBs9scB/coxnh2h8t5x9YLb8Ha1PMjjS09F8jUi8cULdlYCk9pyNH0MJjU0/r13qmaUZvdAyXAOlImYPRdk8PI3T01J8hhHvIfFKAYdZRVX8ugdDnbLk0NfB2pNHcmAdIisdWJmnVQUfgPVLce9Pc8TIN7QsJmdU49SJy008jJ3UOTr0Ipx6/Q33A2MRX1SdiWM3E/Vz3QEfwK4RInC7Z6H2Pja2P0eRfSffPnwRMHEAoKnZ2FRSFABcWhpSdoqMWFSEtwCEsW+m6BhpIEMJidf0jjEs7hEzX2N4nKlQKtqJfuFwuQqEQhx122HC7MiyMGgEyJyeHzZs3k5WVZXtOZGxOjroTqhgeVP1HRbL4fD6qq6sBFQGpsIfX66WmJtwEQx0zCjs0NjbS1NSEpmmj/kaH9D5Nz0KejvQ+g+hFgATQ3IchCpYigx+DWQFaNsI9AyEGPl1ZyiB20sPBAquh3+tt3LiRYDBIamoKY8bYqXk58Ai9CEfGVQlESB20XJzpvx5yv0YzUlpU1Z9NILSmc8uWCodVleHmM/mFm3F7AjGz7EX4mZaXtZvn4At+QbT2oVmNt/F/1Lc9zpTC53Do8a/xNjb/qVN8TL4TtiSEJQPoonvZpPLmByhr/gu9pXQLAU5pYSI6R8WJhBQSS8rOeMjODthAhuajyeq9hICFRhANKU2E5eP1jZczZ+LTODQlwCsUg0lJSQnl5eXo+tCUPVi1ahX19fUDajMSuNAXRo0Aue+++7JkyRK+/PJL9t57b1tzvvzyy+hchWI4iKRfFxYWqvqPCltEjpm8vDwyMjKG2RvFSCByElFYWEh6evowe6MYCUQi2UpLS3G7R9fFqpTBsDiIA/TxEPqOnkUKE4zvbNsXQkO4DwK6p44OJMK5c5x2FvHQEXppv9aSVjPff/0UABNLvia0eTc0z0/Q03+F1s+6ksniTL8UoeWGu11bke7jAs09C2fWjQh9zJD6M9rxBt4jEPoy7r5I+nXJuC3p15rIJCvjIhran8C0GnuwbOANrsEX/LrztezyX3/oByobr2FSwT+6zTStdho6XqEv4iOAQ8tFi3PToMX/aaf4CHbqSQoBDsIio9GZbh2LJcGK02xGF5IszUtLryLkloY0mrRoC9VQ1r6MHTKP6tW30Y6Q4cdQr6nYPpgxYwZPPfUUn376Kfvvv/+gr3fBBRcM+hrJoA23A0PFZZddhpSSu+66C6/X2+t4r9fLnXfeiRCCX/9a3Q1VDA+q/qMiWVT9R0WyRMQklX6tsMtorP8opR+r7W5k7YHI+mOQ9T9G1s0Cgr1PjhMJNVxIGUJKC+H+EYhceo8mMxEpfS+OL61GgvVzWLc+nM0xedwmwMTyv06o/iSswMo+2+4rjtQz8BS+jztvMa7chXgKP8Kd+zCartJPE2FZHXR0PEVDw1wa6s+itfUuTGNT7xN7od33H+LFw5imRk1V+N+jpLSSkrwFjCtYxKSSz8jPuprc9LkkvozV0bUi2gOr6KnjeavvTYLGxm57gmatTXE+HhqFGWfGrfla1fY0ImF36h4sCtDi5N+aaMTLyzXRSBX+uPu6E/bTQEci+KHltaT9UygUyfHrX/8aXde55557aG1tHdS1pJSD9ugroyYC8kc/+hE33ngjN998MzNnzuThhx9mzz33jDv2888/5+KLL+a7777jxhtvZPbs2UPrrELRiRIgFcmiaoYqkkWJ1opksCwresyMhvqPMvQlsuMx8L8OW4sSVqRGeE+NKTTEADRw6Q9ShpDehVjeJ8EsA3RwH4GW/musttuAUIKZAuE+GuE6sM9rG6130dFWx+aGXAAmjYv8zUxAEmq+DFfhBz3WzBsMhNARrulDuuZIJRRaQ0P96VhWPZFjPRBYTnvbfWTn/InU1H4I1NJLvM9O3eYxGCEXnhQvOXn1pLgPQNO2RPTlZ87DG/yUDv9SuqYz62gijdyMX1LVfEtvq9MRWIXLMa7LVodmv1xXV3Q8jokUZ/487t7WwP+QfYyq1JDdYiZlnJsHUoa3W0LHbqo6hEXLoNRoDpb3yb9Rh6oBqegH++yzD/fddx/z5s3j8MMP5/777+fgg3sv05IsS5cuHXCbA8GoESBvueUWhBDsu+++rF69mn322Yfdd9+d/fbbj8LCQoQQbN68mVWrVnVLvY60MI9Hsl1/FAq7+Hw+Nm/eDCgBUmGPjo4OamtrASVAKuzR3NwcreWnvmcUdqiqqiIQCODxeCguLh5udwYV6X0O2Tqfrl1w444kfk03HUQGpA5fd1kpQ5hNl0DwvZitJgSWYgXeRaRfE+6IHXiNLle4Ig2Ren64AU4vHbwTrm21YvleZsOmsMBTlNdAWqo/ZoQFVj1WYCm658d9WkMxuFiWt1N8bOrcEjlGwsd6c9MVOPRJuNx9K1flckwjnrJS3Zl+XTyuEodehNgqilgIF+PzH6fF+xKN7U8QDK1H09LJSj2J3PTz8Qa/6pM/AE49j0z3wbQGVtLT596pFRCywpG9AicF6SdTmv1bHAm61Qv6LrKHP4GyyysRp0GN2SkQx4uY7Nm6JIQDb6ip19EKhaJ/RFKid9xxRz7//HMOO+wwSktLmT59Ojk5OT3WhhRC8Oijj9pa5/DDDx8QfweaUSNARtqEQ/gfTkrJl19+GRUbY5FSIoRg9erVrF69uke7SoBUDBYVFeGaN/n5+aoum8IWkYjZgoIC0tJ6L0CuUEQi2caOHTvqavkp+kYk/XrSpElo2vZbyUeGfugUH+2EumiAC/AT28UXLQ+R8whCyx1ET3tGep/uFB+3fg/hSCzZ/if0wg9A/AVp1YGxHiEc4NwNITz9W9usAIJsqCwBYFJpVZxRDmToO1AC5DaJz7eoM/IxERrt7X8nt48CZGba6TS03tVte6QBTcm4jWSnXxBXBBfCQXbaqWSndRf4U4WL3ru8C9LcB8TdMy77StZsPp340c0Cp1ZIyNoc3SIJ4Qutx5J+IH4EZV7qLDa2Pt6LTwk87exybcSknetYmDEp3ZHoRwh3wnYRIogDe5GQkVTsvt1sUCgU9nn88ce76VIVFRVUVlb2OC+iUdkVILdVtt8zxzhsnbPeUz77YOe+KxS9EUmlHT9+/PA6ohgxqPRrRbJEBEh1zCjsEjlmtvf6j9K7APunyVZYsMv6E6ScAimnIrL+gihYihjiJiuxSCmxvE/0MspA+l5CCIGmF6K5D0S49u23+AiASEFK2LCpU4AcF0+AtGAg1lIMCn7/u/QsYJn4/e/02b4mUshIPbnzVXidjvZ0WppzEcJi4sRcsjMuStquU88nJ/UkEvuuk5VyNC5HSdy9GZ592bHwERzRmweRlGYNXWREIx9jaQusZs3m0zCt9rg2SzLORBN2BcHuaAIcCBxaRvS1FhOhaUa/r8L2s/RIzwP716sGggb/2j75N6qQw/TYBnnzzTc544wzmDx5MqmpqXg8HkpLSznxxBN57rnnbOslX3/9NZdccgk77LADKSkpFBQUMGPGDP7+979jGPZrsj777LMcddRRFBcX4/F4mDhxIueccw4rVw59veFEjB8/vstjwoQJTJgwodv2eOO2B11g1ERAWlbv3cYUim2JSASkEgYUdlECpCIZpJSjRkxSDAzBYDB6h357OGakDIJRjrRawWpECAdSywTvs+BfnIQlDbRsRMqxiJRjB83f5AmA2XNEBQhkaM2grC70yWxu2gWvLwWnI8S4oto4oyw0z5GDsv5QIqWfkO81DN8SpGxHc0zDlXYGunOX4Xatf8ggvSsfiWqI9kxz++PUt9yKlD5ioxWrNoajH4vGOJhcujBuR+neCJn1GFYDiXxPce7EuLw7e7SRnXIEe437iGbfu/hD69G1dEzLT2XzbQlmmASMCuran2dM5tw4a5aya+GDfF37KywZSOhbT+gCxmacSn7qbAJmHU49l41tr7Oh9flu1jyaQZ5so9FKj1svMh4CWFn3ID8t/WPSvilGF8FgkHPOOYfnnnuu276NGzeyceNGFi9ezIMPPsjLL79MVlbi2qqPPvool156KYFAILrN7/ezYsUKVqxYweOPP86rr75KXl5eQht+v59TTjmFV199tcv28vJyysvLeeaZZ7jpppuYP39+H97twBK5XhutjBoBUqEYSQQCAaqrqwFV/1Fhj46ODurqwnfklQCpsEN9fT3t7e04HA7GjRvX+wTFqKesrAzLssjOziY3d/jSivuLlEFk+4PgfQrklg6UWy7gk41QshCeYwbIu4EkErXVk9AhQLgGZXUhBBW1xwE1jC+pQde3DgbQ0Dw/RnOMbDHbMqvpqD8daW4gUgvUDH5CyPsErvRf4864us91NAcCKf1YZi1CpKLp+UnNdbr2IBBYSuJaiBpOZ/LNfFo7nqOu+f9itmxJS67uTL/eeafD+yQ+mlY76zafTMAoSzjGF1pDZf1V5GacSbr7YHQtfqd6TTjJTT0q+npNzan09pmqa38xrgAJkJtyKAeOW0ZN+0vUdrxGe5K1KiUm+alHkOXZI7otx7M3Kc5JfNHQNZVdSnBoFnminWYzBSN62Z/oWJRoWGz0rqY9VEu6szAp30YTQoYfQ73mtsQVV1wRFR8LCwu59tpr2XvvvXE6nXz55ZfceeedlJeXs2zZMs4880yWLFkS184bb7zBxRdfjGVZFBUVcf3113PAAQfQ2NjII488wksvvcTKlSuZM2cOS5cuTVj65cILL4yKj0cccQSXX345JSUlfPnll9x2222sW7eOG264geLiYi66KPmoasXAoQRIhWIbpLKyEikl2dnZZGbGL2atUMQSuZtWWFhIamr8E2mFIpZI9OP48eNxONTpgKJ31q9fD4zs6EcpDWTTpQnqIkZHJWdUZCHds7eJ6mlSGsjAUmTwY0CCYycwviOxgGQi3LMGzZ8NlWEBafK4KsLinOh8GAjXITiy7h60tYcCKSXehrmd9S5hy985LKgF2+9Dc0zCFU0zHjosqxlv25/weZ8F2QGAw7kPaRlX4vIcYctGWtpZtLf9tadVSEuPfzEfMiowjDI0LROXczpChIUDKU3qW+JHEZqmRk31WACmTOnbjbHG9oUEjPX0/DmWtPrfotX/FiDITPkxRVlXkOrarUfbITNxVGXEbqjHmpng1HMpzbqI0qyLqG57gR8abkTaiCIV6KS7diXTvXe3fW49u9s2C4GFjhCgCdnpduJvKYEkopN3GPVKgFQkpLa2lr///e8A5OTk8N///rfLjexDDz2Us846iz322IOysjJee+01Pv30U/beu+uxaxgG8+bNw7IsMjMz+eCDD5gyZUp0/09+8hMuvfRSHnjgAd577z0WLFjAueee282f5cuX88wzzwBw3HHHsWjRomgjl/3224/jjz+effbZh4qKCq699lpOPvlksrOzB/rPorDJqKoBqVCMFCLNRFT0o8IukWNGRT8q7KLqPyqSZaSk7EurBcv/LlbbA1jN87FarkO2P4Q0a8H/HwguZ0ALaskWRODNgbPXVzeMtZj1R2I1/xLpXRBuQGN8Q2LxUQd94qAJkMFgMFpOZtoe96CnX4aWcgJ66tk4817Emfs4QhvZDdPM4EdYxhoSNxYRBNsfGPK68ZbVTHP9Cfg6Ho+KjwBG6H+0NJ6D39s9bTIeul5Mds5fCV8yxnZmDV9CpqSeQUrKiV3mBEPfUV37MzbVHMDm+tOorj2ajTUH0O5dBIA/uBrTipeOD/W1RRghFx6Pl8ycb2y+2640dDyb5AxJq+8t1tacQLv/ox5Huh2l9Hz5rOF22BdOizNOpij9BOxEXac6p7Bb4YNxo2kLUvZH0LVzbrhhTfi4M2TirroRJAKr8zBNiSNoKhQRVq5cGS1vN3fu3LhZNJmZmVx55ZXR1x9++GG3MYsWLWLt2nDN0euuu66L+Bjh7v/P3lnHyVHef/z9zKzvnlsuQggaAsXdKRAIxYsUijtFfxRtC6VCKU6hhSDBPSFQCNrQ4AQpQYKHCMkl57Z7qzPz/P7Y27273OrdniR53ryO3M088p3d2dmZz/OVm26irKws+Xsqbrwx7v2r6zp33XVXvyrSlZWV3HBDPOVCW1vbqC3iYhgGTU1NNDU15ZX3ck1jnXZ56OzsxO/3Y5rZq5GtDQk/FWsOiRt2dd4pciXhAalEa0UuWJaVPGcmTZo0ssYo1ggCgQCNjXHRYLSeM9LqQLZfllJglACB20AfTyJMtnBoyK4HEe5D4nklY18gZRhh2xih1xRwnr5IYykyPAdptYFWjux6qFdIee+Hl0TIaEK40AAT9PHo5Q/Hq14PAcuWLcM0TUpKSqio2gwh1vB8iCkwIm8Sf5xK97AosYxFSKsBoY8ZNruC/jswjSX0F0bj572//QocrqloWmnWsTyeI7HZJhHwTycSmYuUBnb7z/D5zsDlPqyPIBaNfc+qxoO78zr2YJoraG79DdLyZ/xMrOrO/zhm/Aos2Z7LofbDMBvIf4HBQmKwrOVCpoydjxCpBbtq37F0hN/KOE6177i8Zg7GfiSbvZpwse3Y59CEPeV+l62C9YoOZpn/RcDqroid8DhOVMfOLnJGsVFlH0exI3VxHkU3UsR/hnvOUUI0Gk3+nmlBsreg2Du/Y4Lnn38++fspp5yScgyPx8MxxxzDPffcw8KFC/nhhx/YeOONk/sDgQBvvBEvhLX//vunTSl05JFHUlxcTGdnJ7Nnz+a3v/1tWruHk2+++Ya77rqLuXPn8sMPPyQXq4QQbLzxxuy///6cc845TJmy9nx/rnMC5Ouvv87dd9/NO++8Q1tbW059hBBrtQqtGF0YhkFdXR2gxCRFbvTO/6jOGUUuNDQ0EA6HcTgcjB2rHjQU2Ul4P44ZM2ZUpnmQVgDZfBhYqSotJ1vlUJRlIFhI40vMwHRk1/2QFE40cO6LXnxtQYVIKQ2szj8iQ0/Tk+fRJHNIuYZw7ARaKeBEuPZFOPdDpBE0CsGPP/4IxB9CRzIH4pAiszsxxNsN33OElFHCwcdJ75UJECMSnI3bd1pOYzoc21BecU/Wdm0d13WLj6nnbu34I9WVz6btnyhAM3b8cuz6wO5nbHoNptXJQERIw6zHH36LYndqr+Ayz1RKXHvQEX6P/osYGi7bJEzLT1vwP5S490LLIb+qLjxkyyupC19a8THBVpVXEDIaaQh+QJS+bXMrQhO3oSXaSMjswK2nLxqiWLfZZJNNkr8nUrOkIvEdsHqfBO+88w4Am266KWPGpF+g2WuvvZIh3++++24fAfKjjz5Kipt77bVX2jEcDgc777wzr7/+Oh999BGxWAy7fei+/3Lhqquu4uabb8ayrH5e8lJKvvvuO77//nvuvvtuLrvsMv72t3QFsNYs1qkQ7HPOOYdp06bxwgsv0NraipQy5x+FYrioq6vDNE28Xu8aneRfMXwkwq+rqqrwetfscDbF8JAQkyZOnJg2obdC0ZvRnv9RBh/NIj4O8fxIZODmXuIjgAWR/2K2HIU0Wwo2l+W/HhlKhNCaxL3vst2rWkizEb30TvTSm9Fc04ZUfISecyZVWN3agu7YivTej3GEVjGs3o+W1YKUgSytdAxjUUHnNc1mQuH/kEn4lDKMYXyH074lqz+GBrs8tLdWApLxEyzczl0HZEeFNz8PxL7ohGPfp90rhM4m1fcxpugUNOHqtceGQCds/Miytj/zfdNZLFixM81d/846Y6X3ADJ/fnWqvdOyjmPT3OxW+y+2rLwyhcdjrs+yAguDb9pHPqXEqEaO0M8oYcstt2SXXXYB4KGHHmLlyv7fvX6/n9tvvx2Ip/qZOnVqn/2BQIAVK1YAMHny5Izz9d7/zTd9UzP0/jvXcQzD4IcffsjYdqi54IILuPHGGzFNEyklm222GaeccgpXXnklV1xxBaeccgpTpkxBSolpmtxwww1cdNFFI2pzoVhnPCDvuece7r33XgCKioo44ogj2GqrrSgtLVUPX4pRRSL8euLEiWuvx4CioKj8j4p8UeHXinyQUo5aAVJKC6LvQOCukbMho3eRCVYjVtd96MVXDn4uswUZfIwBPY32ygU41HR2dtLU1IQQYq2+zthcByK0ingYfMqwfg2H95QhC3NPhRC5eChLhOYr6LyGuYrs56UNw1hBddnfWdF4JJIoidetvi4eOlle2cx6Y69LFq3Jl3Lfr2gJPE4kZQh6Nqyslbc14WRi+dWML/0/uqILaQu+Qb3//l5H3p130Wrjx+aLEdio8P4i7Xg13kNY1v4vomZzCns1NGFnXHH/whupEEIQtvwIdGT3WFbytOydhiEzq8Jf59ROse7ywAMPcOCBB7Js2TK23XbbZBVsm83GwoULufHGG1myZAkVFRU8/vjjOJ3OPv1XrFiRdPJKFzadYMKECcnfly/vG8XQ++98xxmpsOb33nuPf/3rXwghmDJlCvfeey+77pp6weWDDz7gnHPO4csvv+Sf//wnxx57bNq2ufLII48Acc/TnXbaaVBjDYR1RoBMiI+bbbYZ//3vf6mpGbqcPArFYFD5HxX5oooWKfLBsiwlWivyorW1lc7OTnRdH1XfTdJciWw9A8zCenLlbQcmmfNKmsjQ08iiywcsqiTnirxB/qIKgA62/iFwQ0Ui9G7s2LG43ZkFnTUZIRy4y+8j2PJrkFF63pv4+aA7d8PhO3dYbdK0EuyO3YhF55P+XDFxutKLYgNB13KJ2jHR9XJcjq0ZX/08zR1/IRR5D+gJv950k53wuvZCSkko+gmh6AIENryuPXHaN8rBDh8b1cxieesVdIZeJz+xPl4ROxd0zYfPuQ3fN52Tsd2Slt/RFf0Gm+aj3HMALntfQV7XvGw15lG+bDidsLEc0f14LjGwaT42r74btz33+ztLGvQWGmPJNA25OzVoZC9asy4jZPxnuOeE+OJOb5xOZz9xbziYPHkyn3zyCXfddRc33XRTv5yKdrud3/72t1x44YUp7xv8fn/yd58v82JI7+iuQKCvd3ehxhlOEuHkkyZN4r333qOkJH26g1122YW3336b7bbbjiVLljB9+vRBC5CnnHIKQgiefPJJJUAOJd9++y1CCK699lolPipGLZZlJVdyRtNDnmL0EgqFaGhoAJQAqciNlStXEo1GcblcGXPuKBQJEiH748ePH/GcSQmkjCJbTwKzbgStiItMwrYJMls4q/SDDIEYZJoMGWRgRXRMNM+vBzd3FqTVjjQbEFr5qPWYHQpsju3xVb1GpOsBjNC/kVYQzbYBDu/J2D1H5xzqblntGOF5SNmFbtsI3bHTgCNhPEUX09FyDKlzC+rYHbtjd2w1oLHTYbONw+nYnkj0U9Kfnxoe9yEAuBxbMr5qJjGjjlisnqb6/wARJm+6F5HYIla0nEMk9g0kqzlLvK59GF9+J7peltkWvYJJVfcTNepY3HgSESN9WHVv28q8R+Gw1eZ8zO3BdzCtjoxtTNnJqs5/AYLl7TdQ7jmEDStuRNN6Qrg99vXZcdxrtATn0RZ+DylNip1bU+U9CF3LT8CvcE1BdqcFiBejyf8cmuDdNu8+iuGhtxcfwB//+EeuvfbaEbHl5Zdf5umnn04p5sViMWbNmkVtbS2XXHJJv2tZOBxO/u5wZM6V2ltgDYX6Frgq1DjDyTvvvIMQgiuvvDKj+JigpKSEK664grPPPjuZN3MwlJSU0NnZ2SeX5nCyzsQeJxTxkXqhFYpcaGxsJBKJ4HA4lFCuyImEx2xlZWXWlT+FAnrCr9dff32V5kGREwkBclSF0oZfBfMnBuYNOBgEiHLQ1wfXYYjymeDYmey31E7IEtqZE7YNyE98jH/GhesIhDN1YY3BYhmLibb+hmjD9sSapxFp2InFP34GrBsCJIBmWx93yZ8pGvM5xWN/wFf9Gg7v8TmJj1IaBDv+Smf9tgTbLyTUcRWBlqPxN+6FEf10QPY4nLtSXHY3JPMU2qHbq83u3JPi8uwFZQZCWcnvyORtV1x0Lja9us82u20cba1jCIUiOJ1OasbYWdp4JJFkLkaLhIjaFX6bZU3HI3Ms6uOwjaOm5Pyc2pZ6fsH48tyLPHSEP2BJaz5pFeLH0Bp8iUUtl/TbK4SNSu/+bFxxLZtU/oUxRb/MW3wEGOvZFY9ejUBL5oLUck4iKNHQ2bR4n7znVQwPy5cvp6OjI/lz1VVXpW1rGAZCiEH/PPTQQ/3GvvTSSzn55JP5+uuvOfzww3nvvfcIBAKEQiE+/fRTTj31VJYtW8all17Ksccei2X1/d5yuXoE+N5VtVPRu4L26h71hRpnOKmvrwdgm222ybnPttvGFwUSTieDIXEvl2tB5kKzzgiQm222GQCrVq0aYUsUivQkxKQJEyao3KSKnEiIScpjVpEriXNGecwqckFKmRQgR5OYJMP/YURuY0vuQquZj1b1OlrpDQjHVmiuw8hciERHuA8bdPg1gHDsBtoY0h+7AHo9WOlj0YquQSu5YUgWHKzYImLNRyAj/yEhjDa2lhEM2bDbYoyr/qngc65thDquJtp1LxDrs90ylxFoPhYz9k3qjllwug+houYzfCU34vaejMd3PqVVr1Fa8RiaVlQAy/vjcu5CdeUj6FpCZEyccw5Kii6mrDi1WLJoUdyDeNKkSXQEH8a02km9uGASjn2BP5R7kRSfax+0DJ7HulbGRjVzmFh5F5rILZTVH/6E7xpOwrAGUlzKoi34CsHodwPomx1N2Nij9gZ04UJ0Xyccom9YdiYmerfDPgDhc51iBIvQFBcX9/kZifDrOXPmcMsttwDxcN7nnnuOXXfdFa/Xi8vlYptttuGBBx7g6quvBmDmzJncfffdfcYoKuq5BmULh+7q6slfvLqzRaHGGU4Somlve7KROLZCvN9HHHEEUkpefPHFQY81ENaZEOyzzjqLt99+myeffJJp07JXElMoRgKV/1GRL4lzRuXyU+SCaZrJc2ZUebMpRi319fWEQiEcDgdjx44daXN6kF3kH4ZcADrOw4r+GlF8VU9hEfuW4JwKkbkpbNJBuNG8ZxdkeiF0tJKbsdpOJS4o9BZpdBAlaOUzEZoHkKBVFkT4TCDNBszgk1iR9wCJNBv6vRdLV8TPk/VqG7D8VyLd7yCEyimXCtNYQjT4WJq9FhAj5L8NX/m9Axpf03y4vUMber86HtfPcdd+Qij8Foa5FE0U43bvj66Vpu2TyBm64YYb0h68icyezTodwdkUew7KyZ7GztuxZDD9aKIUj2PLnMYCCMeWsLjlimSY88DQaQnOwePYdBBjpKfCNYWD1nucb9ueYmH7c9iw0DCxsuZ2FFQ4R89Ck2Jw2Gy2flWjB0Jtbd+0BDNmzEj+/te//jVtv9/97nfcdtttBAIB7r//fs4777zkvt4FYxLVsNPRu9DM6iHoq4+z/fbbD2ic4WTSpEl8/vnnvPDCC+y555459UmIhYVYCL7ooot44IEHuPvuuznkkEP4+c+HJjoiHeuMAHn88cfz3HPP8fjjj7Pjjjty/vm5ueMrFMOFlFIJkIq8iEQiSa9u5c2myIWVK1cSi8Vwu91UV1dn76BY50l4P06cOBFdH0Uikm0TiH7A8IdgWxB6FGl8Bd6zwbkHQtjQS2/D6vwTMjQr3iaRe09fH730NoStcNdozbkzomImpv8fEH0zPg92hOsQtKKLEfrQCMVW+C1ibecQ99RLL/4urYs/rK4/fiVY9cjoewhnbg9Z6xqx0PPEQ6PTF4sxwq8hrUDBq1YPJULY8Lj3zaltOBxOChAbbbQRqwLtWXqYGGZ6z8NIbDGtXbMwzCZ0rZxmf+aq8VFzCV2R+fhcu2ScNRj9jqWtV+OPfJzFvuwINEzLn73hIPDZx7J99SWUubbgrfo/45Ixgsnw+PTekBsW7T6kdq0VjEARmrxqKfVi8uTJhbUDkqJmTU0N48aNS9vO5XKx+eab8+GHH/Ltt9/22efz+ZgwYQLLly/vt291eu9PRLUm6F3JOtdxbDYbG22UvaDVUHHQQQfx2Wef8c9//pNp06ax776Zr5VvvPEGd955J0IIDjoot4WXTBQXF/Of//yHo446igMOOIBTTz2V448/ni233JKysrIhT8+0zgiQAI8//jiXXnopF198MU899RTHHHMMm2yyCR6PJ2vfXNVphWKgtLe34/f70TQt48VcoUiwfPlypJSUlpZSXFw80uYo1gBU/kdFvozK/I+A8ByDDD4wcgbEPkW2nw1aJZTcgHDugV7yN6TvYmTkLSCCsG0G9m2H5LMm7FtgK78PaXWC1QFaRbfX49Agzbpu8TFKpidhw9BYviqew3r9casAgTSWghIgU2KZLcTD6TMJ6RbS6lijBMh8WLJkCVJKKioqKC0tpTk0jqjxI+nPMx1HCkFfSpO6tmtoCTwCycrPFtk9pXW6Ip9mFCBDsR/5uv4oTFmYwhUSA1eeixIho55VXW9gWH489gnUevZF71XIJh0bFk8lZLbxUeNdOKRJFDvx17b/dWmceytqXEPjlalYe7DZ4hKSYWT3Ao7FYn369Gb33XfnySef5LvvvqO+vj5tYcS33nor+ftuu+3WZ98OO+yAw+EgGo3y1ltvceWVqfOyRqNR5s+f36fPSHHxxRfzz3/+E7/fz7Rp0zjzzDM57bTT2GabbZIp2CzLYsGCBcyYMYP7778fwzAoKSnh4osvHvT8vReTpZTMmDGjj1drJoQQOb3vmVinBEi73c5WW21FeXk5H3zwAR988EFO/QrxQisU2Uh4P9bW1o6aKqOK0c2yZcsAFX6tyB11zijywTTN5Dkz6gRI2wbguwwZuGlA/WW3uJH4VySKteSQJ032FkasJmg7E8ofRzi2Q+jVCM/RA7JpIAitGLShX4Ayu54k7vmY2Q1nRUM1hmnD5wlSWdYe3ygKL5xJqxMz9BxW9GNAoDl2RncftsaJdJo+luxevHaEVj4c5owIvcOvAcp8J9HQ/scMPUxKfcf121rfcUu3+Bhvkzsya4qA5W03douPhfG4Ftio9B6RU1tLxljYfCPL/DOJ17TWkRh8KXxsVXUtY31Ts46xRdmxbFi0Pz90vMzn7XNojTXT81mOX/PGun/GweOvVYuTiqxMmjSJr776ipaWFr755pt+XokJWltbWbhwYbLP6hx++OE8+eSTADz00EMpxcNgMMgzzzwDxL0dN9lkkz77i4qK2HfffXnllVeYO3cuK1as6BOWnWD27Nl0dnYC8RyII0llZSXPPPMMhx56KNFolOnTpzN9+nQcDgfl5eUIIWhpaUkW1ZFS4nA4mDlzJhUVFYOeX0qZ8e+hZp0RIA3D4LjjjmP27NnA8L/QCkU2EnkpVPi1IldUyL4iH3rnf1Qh+4pc6B2yX1NTM9Lm9Md7BgRuJp/YtNWFx3TbRfd/q7dZvV98u4HovA69cnY+1q9RWJF55JJzc1l3+PXEcauI6xgONFduobi5YkbmE207A2SQhHhihucQ89+Eo/wBdMe2BZ1vKHF4jiDsvyFDCx27+3DEWlwUZPHixUAvAdJ7PB1dMwnHviaV4FfiOQqPY8c+20wrQJP/vgFaYFHkSu+hGzPbaAulyu86cNYvvxabXppT24XNf2eZfxYkr1FxpxhDdvG/xsuwaT6qPbtmHcdtK2fLihPYsuIEAkYLn7XOoiNWj9dWySZFe1PrnqLEx1zJtah4oeccJRxyyCHMmTMHiHvzvfjii/08Ci3L4qKLLkqKaAcffHC/cY444gg23HBDfvzxR66//nqOPvro5HUgwWWXXZas1nzZZZeltOfSSy/llVdewTAMzjvvPGbPnt3Hy6+5uZkrrrgCgNLSUs4444wBHnnhmDp1KvPnz+ess87ik08+Afqm1urNDjvswL333stWW21VkLn/+MdMCzxDzzojQE6fPp1nn30WiHt+nHzyyWy55ZaUlpaqasOKUUHvCtgKRTYMw6Curg5QYpIiN1atWqXyPyryIhF+PVpD9oUQSOzEw4JzI5WAmKldQoRMJz4m2xtfYBk/odnWngUhKUNYkQ9BBpE5hp4m8z92h1/r3tMRWknBbLKMFURbT6UnFLzXeyL9RFtPxlX1X4ReVbA5hxJNr8VVdDFh/60p9uoIUYSr6P+G3a7horW1lba2NjRNS97LaJqbidUzaWy/jvauZ5BE4ttFCRVFZ1FZfEG/61Eg/C5ShgdggY7XuRNux5S0LWJmE4USH932TRlf+n+Uew7oty9qtlEfeImwsRK7XsYY7zSk0PuIj32Jh1F/1/bPnATI3vhsFexeXZjCWIp1j1NOOYXbbruNb7/9ltdff53tt9+eCy64gK222gpd1/n666+5++67k9GmNTU1XHLJJf3Gsdvt3HHHHRxyyCF0dnay22678Yc//IEdd9yRtrY27rvvvqR+s/vuu3PiiSemtOfnP/85v/rVr3jqqad44YUX2H///bn44osZO3YsX375Jdddd13yOfvvf/87ZWVlQ/TK5MfWW2/NRx99xMcff8zcuXNZuHAhra2tAJSXl7PFFluw3377scMOOxR0XiVADhP3338/ADvvvDNvvPEGbvfau5KoWPMIhUI0NTUBSoBU5EZdXR2maeLz+UbNF6lidKPyPyryJXHOjLbw6z7o48BcklNTK08RQSL7CJBZ2wcfhOKRvbEvBFJamF13YwbuARnIuV844qC+OR4eNnFsA7r3NPSi/g+dg8EMPkr6IjgWyCBG8EnsRRcWdN6hxOm7GKGVEfbfjrR6iqvYHLvgLr0O3bbm3hdaVpCo8SMCHYd9Y4Tom2IoEX49YcI4grGZrGqfjWG14rRtQKnvBKpKriJqfA/ouBybowln6nlyzs2oET934v+67BuzfuVdGXvY9cHeY2mUuPZifOmFeB1bpfz+XdbxMD+03ozE7A6xtljUdhtex7YkC1r1Qsr4FgtoCn/NW3WnMbHoEMb7DsS2FnvLjhrWcQ9Ih8PBq6++ymGHHcbnn3/Ol19+yVlnnZWy7aRJk5g9ezaVlZUp9x900EFMnz6d888/n4aGBi644IJ+bXbccUeee+65jIXwHnjgATo7O3n55ZeZN28e8+bN67Nf0zSuvvpqzj579AnvO+ywQ8FFxtHMOiNALlq0CCEEV111lRIfFaOORPW/8vJyfL41K3+RYmRI5GWbOHGiEpMUOdH7nFEosmEYRjI1yGjNGSrNupzFx4GSj2gpw/PWCgHS9P8ds+v+vPstbz0RKQ0qym1UbvA6Qk9dUGBQtoVfI1vBFjP8+holQAohcHpPweH5NWb0U6QMotk2QC9g5fThxpIhWjpupKPrMaTsAkDXKin1nUVZ0W8QIh59lgi/Lq3+L6va5pEQ26LGYvzh1yhyH8z4in8hROZHVpd9k4z7ExS79sWwWrBp5ZR6D6fEMw1NZC5GYderKHbtRmf4AwbmCWnREX6bcNMiNq99HrveN5/nSv/zfN/69+TfiRBrgPbIZ8QL6vQgJZgIJBoJL8iW8Ge0hBfwXdsD7DHuPjy2wn/2FIreTJw4kY8//pinnnqKWbNm8emnn9LU1ISUkvLycrbccksOP/xwTjrpJLxeb8axzjzzTHbZZRfuuOMO3njjDVauXInX62WzzTbj17/+NWeccUbKIja9cbvdvPTSSzzxxBM89NBDfP7557S3t1NTU8Mee+zB+eefzy67ZK50rxge1hkB0uv1EgqFlHeZYlSicvkp8kWdM4p8UPkfFfmyYsUKDMPA5/Ol9VwYcUIv5tw019DrQWGtRMoIIo2X1pqANJZjdmWrhtnbI0sHTPSiq1j26VjgEzbYcJshER8BpMwl3H4gobgjjxB2bM6dRtqMQSNllLqmXxOOfkRvwc60mmnpvJ6o8SM1ZbcipUymeais/TrRO9EaAH/oJZo7J1NVkjkM3e3YHLdjS0LRr0gtUOt4HNswqfqBAR3ThNJL+br+6G7r+ouQNUWnUOrei+8aT00zgknEXMnKzruZWPb75FYpLRa1/SPtvAKL+OetZ6HZSoqP9NoetyxorOKDVRfz8/FPqsXpIUTI+M9wzznasNvtnHjiiWlDo/Nhiy224N577x30OMcffzzHH3/8oMcZbqSULF68uE8I9qRJk4YlVeDixYv54IMPqK+vJxgMcu655w7pfd86k/wwkbQz4QGiUIwmEh6QSiBX5IJlWapokSIv6uvriUajuFyu0VlMRDHqGO35HwGk2Zxbuyz5GwuHhdV53TDMM3SYoefI6fFAlIIoRTj3w17+JDbfmclzZihD9jX7z1jdI6wvOsJWmET9ioHRGZxJODqf1N6CEn/waULR+dTV1RGJRHA4w5SVN6YZTdIauD8n4XlC+S1owkP/80NH13xMqLgpvwPphc+5NZNrHsWhj+2zXQgn40ouZGLZ1QQin5P5s2PS5H8aKXsE0s7o10TM+rQ99BSh11aKkOzkfkw6ot/RHP5f2jEjZoDvO+fxVfsrrAp9rQqzKhQjyGuvvcYhhxxCcXExm2yyCTvvvDM777wzm2yyCSUlJRx66KG8/vrrQzL3ggUL2Guvvdh444056aSTuPzyy7n22mtpbOx7Pf7Xv/5FdXU1G2+8MbFYbNDzrjMC5DnnnIOUkhkzsq3qKhTDi2maSoBU5EVDQwPRaBSn06mKiShyQoXsK/Kld87QUYuefYV++MTH7vlCT2IZPw7bfIVGWg1AtmuExFH1Ks4xn+IovxvNuROdnZ20tLQghBjSc8bmPZnMIdgmdu8JQza/IjsdgUfI/Iip0xl4PJn/sbp2JUJL/xk1rXbCse+zzut2TGaTMS9T5v0lgniuSYGDMu/RbFzzErpWRMxsGLDgVuzama3HvcXk6sdZv/w6Nqz8B9uO/4jxpf+HEBoRYznZPjum9GNa/l7H1pWxvRBgT16/RK9/088j0GkMfdhvuyVN3mu8n/sWHc0rK69jbv0tPLPsQh5bcgYN4eyvr0KhKBzRaJTjjjuOgw46iJdffpmuri6klH1+urq6eOmll5g2bRrHH398sqJ4IXjppZfYddddeffdd/vMmYqTTz6ZUCjE4sWLk9XPB8M6I0AeeeSRnHPOOcyZM4dLL70U08x086JQDB8NDQ0YhoHL5Rq9YW6KUUVCTJowYcKwuOYr1nwS54zymFXkQiwWSy6MjeoCNK7DMu7uER+HU3SXWM3TMDuuQcpI6haWH6vrfoymqRgNW2M07YcVuAdpdQ6jnakRWiXZqx3YQCvusyXh/VhbWzukudZ1567YvIliB72//+Jebzbf/6E5thmy+UcrltWOYfyIZbWPtCnEjKVkzpVoEjUWJ/M/1oxbmcOoueVedNrXZ72KW9hiwjdMGbeAzccvxOPYnMWNx/F13fZ8Xbc9367cjWb/Q0iZfz5HITRK3LtSU3Q8ld5DsXV/DqSUWFYoBzt1NM2T/MtjX49s1yddmEwuPYdiR255LkGkPLY3G/7JJ61PYcq+Hkxt0eU8u+wSWiMqSlChGC6OP/54nnnmGaSU6LrOtGnTuPbaa5k+fTp333031157LQcddBA2mw0pJU8//TQnnFCYxbX6+nqOO+44IpEIU6ZM4ZVXXsHv96dt7/P5OPzwwwF45ZVXBj3/OpMD8pFHHmHnnXdmwYIF3HbbbcyaNYsjjzySTTbZBI/Hk7X/SSedNAxWKtZFEqG0EyZMUJ5JipxQ4deKfLAsKylAjmpvNsWoYfny5ViWRVFREWVlg60AO3Rotlos+3YQSx9uGGe4QwwtZOhJTKsRvfTuPt/t0mzBbD2uu3hOt11mACtwC4SeQi9/GqGPnGe77j4CM3BnphZoroMRwtVn63CEXyewFV2JZt+KWNf9yNhnAGj27bD5zkB37T/k848mjNi3dHXeSDTyHxLVnR3O/fEWX4HNvumI2KRpJVhm+odZ0DCNiuQiR83YnzKPJ3w4bRvnZ4NwIjQHy1svpa3rGXqLfFFzBXVtVxOMLmRC+U2Dvvc2rSA/NJ1DR/idLC11yj0H9Sl647LVUuHenZbQ+6T27NVw6lVsVHY2G5f/Bn90CW/WnUTMSl+dXmJQ4eqbhqAtuoIv21PnzJVYGDLKh82PMm3cH7Icg0KhGCwvvfQSs2fPRgjBPvvswwMPPJA2P/tPP/3Eaaedxn//+1+effZZXn75ZQ466KBBzX/bbbcRCASYOHEi77zzDqWlpVn77L333jz++OP873/Z7reys84IkKecckqfL5jly5fzj3+kT/rbGyGEEiAVQ0ZCTBo/fvwIW6JYE5BSqgI0irxobGyM59lyOBgzRlXGVGQnEX49adKk0b8wVnoXNB8Asr3frh7vx5HIcSYhMhcZ/R/CuX1yq9n5BzCXpbDJAnMlZscV2MofHFZLeyNs66N5TsQKPppirw7ChV50fp+tvYuJDIcAKYRAdx+E7j4omU9PiEx5IddOYtEvaG85EmSUHs87i2hkLtHmtymtmI3dseWw21XsOYpW/52kD5W3aG/+OVL+RFlZEb4iM8MnVKPMdzKalr9XrT/8Zrf4CH0/b/Hf27qeptRzMMXuvfMeuzeLW66gI/xellYaAhvjSn7Tb8/kit/z0cpjMawAss9rpiHQ2Lzq+uT5XeSYxEYlJ/BN2z30PiYpQSKw0LFpHkwZD7nWuvt93PxYRuskFj/432E/K4xdc2VsqyD+0g/314pK1bnW8NBDDwHxGiWvvvoqdrs9bdv11luPV155hZ122onPP/+cBx98cNAC5GuvvYYQgt/+9rc5iY8Am24aX9BK3B8OhnUqdm/1uPp8fhSKoaK3B6RCkY22tjYCgQC6rjNu3LiRNkexBtA7/FqF7CtyYY3I/9iNppchKl8B50H0ua3VKhD2nRne8Ov+WIGewhfSXAmRuaQXZkyIvoM0hj8UUkoTKcNIKbEVX4PuOx/oK0QI22TsFc+g2Tbos721tZXOzk50XR/2hTEh9HVSfJRS4m//LcgI/c8nE2QEf/ulI2EaJb5T0LQSUhcL0nHYNmFVXTzlUMWYBUhSpyoA8Dp3o6rktwOyoyXwaBobemxpCTwyoLEThGPLaQ2+RLbQa5tWxWY1j+JxTO63z2OfyE5jZ1HjPQiR9A0SVLh2YYexj1Ph3qVP+03LTqMmuU1DSohiI4odA42IFePt+st4cdmRtIa/oz74BT90ziWbgiUxiZjpPSsVCkVhmD9/flIAzCQ+JrDb7Vx66aVIKZk/f/6g508sGO6444459ykqKgIgEBj8NWKd8YBMvNAKxWiis7OTzs5OhBBKTFLkRML7sba2FpttnbmEKwaByv+oyIdoNEpdXR2wZgiQAEKvQJTdjrRawfgRabUgI28hQ8+Ta+64ISMWrzIrhEDGviQXNxYZ+xxhSx2OVQiktJDR95HGUqTVjhX7AhmZB5ig1aB7T0T3nYvuPQsr+h5YIYR9IzT7FinHS9xjjx8/PqeHKcXgMWILMY2vM7SwMI2viEW/xO742bDZBWDTq5lQ9RwrW04jZvxIXASUgIXLsR21FfcyZ8lMAKpql5LpM1pTei2acA7IjnD0O7IVLIq3GTjtof/m1G7T6nvwOdNXZ3fbx/Oz6hvZzLqGiNmEXSvFoadOf6EJO7vU/oPlgVf4sf1pGiI/rObfaSIldMaaeOGnM4hKiL8HmYV6Tdhw6UU5HY9CoRg4TU1NAEyZMiXnPpMnxxcvmpubBz1/opJ1Pt/X7e3tAHi93kHPv848vaaLq1coRpKE92NNTQ0OhyNLa4UCFX6tyAspZZ8K2ApFNhL5H4uLi3MOzRktCK0cyTKs9suAKJnFh+EiBLIVRAW5Bx4NnUefFfmAWPtlYKUp/GE1YPpvxQrPxV7xOLrrgKxjDmf4tSKOaS7OuZ2d4RUgARz2jZlY8zahyPuEo58AOh7XnrgcW9LZ2UlzczNCWFTXrsgwik5H8DlcjqsGZIOmebNeAjTNN6CxE0ii5JLmQa5W+CUdNs2HLQebNGFjYtEhxCyL+qa/rTYXxKSOhRZfbEBHR2JkHFEwuWhfbNrAxN51DSHjP8M9p2LtwOv10t7eTktLS859WltbAXKqXZKNMWPGsGzZMpYsWcI22+RWtO2DDz4ACpMyTsViKRQjSCIBt8r/qMgVVYBGkQ8tLS0Eg0FsNhtjx44daXMUawC9CxaN+vyPqyGlgdl+PpAqLHUkib+OwrEDkM3jQEc4dhoSK6zoAmKtJ4NVn60lMvYFZuCurGNKKfvkDFUMD0Lk5oUixOAEtsEghMDj2o3y4osoLz4fV3c+ykT167KKZhzOaMYxDLNhwPOXeg4l86Ou1t1m4HjsU8jmZS2w4bJvOKh50rEs8Dqrp5mwEFjJ4xaAQAjQ09op0YXOTpUnDomNCoWiL4l8ik8//XTOfZ566qk+fQfDbrvtBsBzzz2XU/tgMMj06dMRQrDnnnsOen4lQCoUI4jK/6jIh2AwmHS9V+eMIhcSYtK4ceNUyL4iJ9ak/I+rIyNvgtXAiIdd90bfEEQ8lFJopQj30aS//dYQrsMQeuWQmGL4byH+2uTy+liYXY9n9dxqbGwkGAxit9tVKplhxOHcLau4KEQRDueuKffFol/S2XEd7W2X4ff/C9NsHAozU5LwmK0Zm00IB5teM+B5KnzHo2ulpMtFqWulVPiOG/D4AMWuXXDa1iP9Z1qn3HMw9jTh1IMlavlZ3fvSlNpq2+K/27CwYfZrrwFblx5MsUMVqcsLOcw/irWGQw89FCklDz74YLIgTSYeeughHnzwQYQQHH744YOe/+STT0ZKyZNPPsnrr7+esW0gEOCYY45JRuCdfvrpg55/nRQgFy1axDXXXMP+++/Pz372MzbaaCMWLVrUp83ChQt5+eWXeeutt0bISsXajmEYrFq1ClAekIrcSAjWFRUVBXHBV6z9qJB9RT7EYrFk/sc1MmTf+Jr8swsN7a2w5j2jjyepVvw7cCREIb3vv44d0IqvHRI7pNmEjL5PXuKsbAcrc76phJi03nrroevrXjGYkUIINx7fRRnbeIouQoi+1aOlDNHachpNTQcQCNxDMPg0/s7raajfjkDg3qE0uXt+mfSA3GDDjcicbsCk1HvUgOey6eVsWP00dj0hrNlIXB/s+hg2rH4am14+4PEBhNDYqPJONOGi/7FoOG0TmFj+h0HNkYkS+yTEavNa3V6PcftA61awhACbsHBiYO/+cRDDKSy2Lj9myGxUKBR9ueCCC6itrUVKyemnn84vfvELnn32WVasWEEsFiMWi7FixQqeffZZDjroIE4//XSklIwdO5bzzz9/0PPvt99+HH744ViWxaGHHspll13GRx99lNzf2trKhx9+yF/+8hc23XRTXnnlFYQQnHTSSTmHbGdinXKHsCyLK664gttvvx3LspLVrYUQRKN9QwCWL1/OwQcfjM1mY8mSJWpVV1FwVq1ahWVZeDweysqGZmVUsXahwq8V+aLyPyryoXf+xzXze8lO/q4iQ+EtqQEWwnMywt1XQBHChV72ADL6DjI4E2mtAm0MmvtIhHPvIavoLK3WgXXMUgBkbQy/llJixb7AjH0FwoHNuReaXjXSZvXD7TsXKQMEA/8kft7rxFMPCDy+C3B7z+nXp63tt4TDCY+XvlkBOzuuRdMq8XiOHDKbm5ubCQQC2Gw2pmxyDj81z8GSflKlTCj1noDTvvGg5nM7JrPZ2HfpDP2HQORDAHzOnSl274cQhXkM9jm35Ge1c1jZcS/NweeQMoJNK6fadxy1xWdi00sKMk8qNio5gqWBVzO20ZDdoqSkJxy75zq5Y+WZ+OzVQ2bjWslIeCUqL8i1Bq/Xy5w5c9hvv/1oa2vj1Vdf5dVX03+OpZSUlZUxZ86cgjmgPPbYYxx88MG8+eab3Hrrrdx6663JxdK99tqrz9wA++67L9OnTy/I3OuUAHn22WfzwAMPIKVk3Lhx7LLLLsyaNStl22nTprHBBhuwZMkSZs2axUUXZV5lVCjyJZH/ccKECWtcni3FyKBC9hX50NHRQUdHB0IIdc4ocqK3YL1Gfi/Zt2XEcz9q4xH2rdC8x6fN5SiEhnDuBc69Uu4fCoReTUIYzQ0NYd8CoaX3ELMsa40O2U+FGfueUNtFWMZXvbbq2D3H4ir5E2KAFZmHAiEE3uLLcXlPJhJ6DstsRNNrcLmPQNP7C0qGsZRw6PlMI+L334rbfcSQff4T3o/rrbceHtckJtU8z8rWSwhFP+1jh8u+OWXekwoypxA2SjzTKPFMK8h4qXDZJ7FB5fVMkn9DEkXgGJZraJVrKzYqPpJFnbOT23QsTDR6e0HapIWJ6Naw4tuL7WPZruJkNik5cMjtVCgUfdlmm2348ssvueiii3j++ecxzdT3Lrquc8QRR3DbbbcV1CHO4/Ewd+5cbrvtNm699dZkVObqlJeXc+mll3L55ZejaYWJGFlnBMg333yTGTNmIITgd7/7HX/605/QdT3jC3n00Udzww03MG/ePCVAKgqOKkCjyAfTNJOhkcoDUpELifDr2tpaHA7HCFujWBNYkz1mpdWO1fm7kTVC3whbVWZvpJFCaGUI5/7IyFxyE2ktdN95GVvU19cTiURwOp3U1tYWxM6RxDJW0NX8S5CB1faYxIJPIa0W3GX3jjpxXtdr8Pj6ezuuTjj0GplFaIlpLMYwFmEfpOdhOhIh+xtssAEATvvGlHiO6BYgE156knDsG5Y0TmNcxZ2UeA4bEluGAiEEgrhIbVkRArFvAfDaN0bXCp86RwjBDlWXU+LYgG/aHyVoNGATFqbUV2sHNiRIgU13c8C4W6h2TRl157JCsS4xduxYZs6cSX19PfPmzWPhwoXJatfl5eVsscUW7L333kP2/appGr/97W+56KKL+Oijj/jkk09obGzENE0qKirYZptt2H333XE6C7vwts4IkAmX0YMOOoi//vWvOfXZcccdAfjqq6+ytFQo8kcJkIp8WLVqFaZp4na7KS8fXM4ixbpBQoBU3o+KXDAMI/m9tCZ6s1ld94C5YgQtcKGVPzKC82fHVnwpseb3QIZILUL25I6zFV+N7to/43gJ78eJEycWzDNCSot4mOjwCyORwPRu8THVa2NhhF/DjC3A5th2uE0rCFIGycULVspQn78Ns4FI9FMEAqdje/QBFknq7TGbCNkPRv5HffvViZl7tY6/B3Ut5+GwbYTbsfmA5hwJLBljWfu/qOt8BLNbzNaEm7FFv2JS6SVoWmEf5oUQbFp6NJuU/JKAsRIpLYJGG2+s/B0RqyOZI1Ji4rGVM3X8LZQ7h6Yq97qCkPGf4Z5TsXYyZswYjjtucAWxBoPNZmPXXXdl111TFy0r+HzDMsso4IMPPkAIkVflnoQwVF+fvUqbQpEPnZ2ddHZ2IoRg7NixI22OYg2gd/i1WrFW5EJCgFwTvdkUw09dXR2maeL1eteoRQ4po8jgbGTXDEau+rWOVjVvVOYJ7I1m2xB7xSyMzj8iox/27BClCNvGCL0GYdsI3XM0Qs/ucVGo8GspLczQsxhdDyKNbwEdzbk3Nt9Z6I4dBjV27jZIYqFZZPYO1YkFZ6+xAqTNvimr533sjx2bLR5lYVrttLRdRTD0Ij2viw2f52jKS/+KlqdH38qVK4lEIrhcLsaMiReGafU/QE/uylRIfmr6FRvVvo+uFeU130ggpcXXTRfTEpxLb0HVkiFWdD5MIPoNP6uZgSbsBZ9bCI0ie/zZtdixHsduMJsl/v/SEPoCBIz1bM9E357oQzC3QqFYc3j77bcB2GGHHXC73VlaxwmHw8lCNXvuueeg5l9nBMjGxkYgvyTZNlv85YnFYkNik2LdJeFlUlNTo0IjFTmh8j8q8iEUCiW/99Q5o8iF3mLSmrLIIa0gsvUUpLGAkczQL3xXjXrxMYFm3wRHxZNIYynSWAZaEcK+Vd7FbyzLSobs5ypASimR5jKQIYQ+AaH5kNIi2n4JVvjf9ITgGliReUQjb2AvuRGbZ+CVkHMnCjKYpY2FzFIVfDTjcu2PplVgWW2kFut13O7D0bRSLBmivukoYrFv6SsOGgSCTxMzFjOmahZSRjCtDnS9DE1kfpBNhF+vv/76SY/ZYOR9sqUEMK1WmjpuZkzZn3I+1lRIadAefJFm/6NEjcXoWgll3iOo8J2ITa8Y1NgJWkNv0RL8T5q9Fu3h+TR2zWGM74iCzJcJm+Zk45JpbFwydLkv11lUERrFIEk4CdTU1GQNcQ6Hw8l7+kKk4dp7773RNI0vvviCKVOm5NSnrq4u2c8wsi1kZWadESDdbjfRaJRgMNvNRQ+JE2PNrASpGM0kBEhVXV2RC1JKJUAq8iJxvlRUVODz+UbYGsWaQEJMWpNyzEr/DWB8NqI2CPdJaO5DsGJfg4witFLQJwxZNetCIWzrI2zrD7j/qlWriEajfbzZMmGEXsTw/wNp/ti9xYnuPgLNPqVbfIRUIbixjivRnLui6UMdLeIAUQKyI0MbbUB2WFY70a4niYZmIq1WNH0CDu+vcbiPGNaiNkLYKS37J60tJxEXe3sLfzq6Ppbikj8AEOh6hlgsXQoqi3D0Q1Y0Hk449jlgInDg8xxJRfEl2G2pUwslBMi+ziC5LXa0dT1JdcmVaFpu3jr9LJYRljadjj/8FokwdMNqob7jNpr9D7NhzUxc9o0GNHZvVvmfJrNHp8Yq/9PDIkAqFIrRybvvvsuee+5JUVERS5cuzSpAhkIhtthiC4LBIO+//34yTeBgSFS3Hq5+vSlMwpY1gMSX3YIFC3LuM2fOHICclWGFIlcSxURU/kdFLnR0dBAIBNA0TYXsK3JC5X9U5INpmsmFsTUlZF9aAQg9A4DIUcQoDAK0SQjnwYiS6UjzR8ymnbBaDsVqPQqzeT+Mhh0xOq7Fii2Oe/1ZbUirM263jGBFP8aKvI8011xvut75H7N5zBpdDxBrvxBpLu61NYIZmkms869kFqEkZvDpwZqbFSEEDu9xQCbh2MTuOSavcS1jBf7GAwj7/45l/IC0WjBjXxBqv4xA87FIK3fHiELgcu1FZdULOF370VMl2YvXewqVVS+jd3vyBrqeIN37YgEGgnBsAQmhTRLFH5zJT40HEDWW9OtjGEbye2nSpEkYZiMdwX+ja7k5eUjZRcysy+tYe9PQ8Q/84bd7HUHP0RhWG0ubzijIg3XI+InMHp1WdxuFQrGu8vTT8e+0ww8/PCdHt7KyMn75y19iWRZPPfXUUJuXEsuKXzd1ffCLq+uMB+TUqVNZsGAB9957L+ecc07WZNn/+9//ePTRRxFCcOCBBw6TlYp1AdM0WblyJaAESEVuJLzZamtrsdtV7h5FdhIPemuSN5ti5Fi1ahWxWAy32011dfVIm5MTMvYFvR/0BQKZNkYte+GN3LAhSv6JZp+MNOuw2k4BetL0SCmxkEAbBB/BDD5C/Fa7O1xJq44XOUmG+mporoOxFV+NyDMEVMoQMvopUsbQ7JMRenYvxEKSa/5HaTYS6/xb4q/V9ppkr8htYcUW5m/gAHB4zyYWfAFpNZDKLrvnBHT75LzG7Gr7Tfd4fUUvADO2gFDn3/CU5lYcs1A4HFtRUfEglhVEygCaVooQfdMBmeYqUsV8Snokx/6YWFYnjW1XMr6qr2i8fPlyTNPE5/MSEX/l+5XPkVs19h6yhXinw5IRWvwPp7E5bnfE+JFA5D2KXLsPaI4Edq2MnlQC6dqUDmoOxcijitAoBkOiNsn++2cu9NabqVOn8vDDD/Puu+8OoWXpSXznl5SUDHqsdUaAPP/887njjjv48ssvOfPMM5k+fXraB/lnn32Wc845h2g0SklJCWedddYwW6tYm2lsbMQwDJxOJxUVhck5o1i7SQiQSrBW5IJhGMlFDiVAKnKhd/j1mpL/MZ+K18I5Ne6BGPuQfEWPOBrYNgerGdlxTvcIfUXNHvFxdXrlSrIaV9tnYYVfIBr9CEfVqwitOKslUpqYgTsxux7ortgMIBDOqdhL/owYhlyUlmUlFzmyCZBGaBaDS14mQAxPrmxNr8Bb9Tzh9t9jRHoVERFFOH1n4/Cdn9d4RvRLzFimyCuLaPAp3MVXIEagwEq8iEzqQjK6XoNpNbP6exf/K9M1wiQUeYeY8RN2W8/3TyL8urp2BZ2h2eS3ICBw2jbFNsAw/EhsCabszNJKpyvyyaAFyBrfYXREPs7QQjDGd+Sg5lAoFGs2iee6TTfdNOc+G20UTxGRiKLMh8T39eqsWrUqa5qmSCTCjz/+yNVXX40Qgs033zzv+VdnnREgx40bxx133MGZZ57JQw89xOuvv84hhxyS3D9jxgyCwSBz585l8eJ4yIwQgnvvvbcgSq9CkSBx4Rg3btya86CnGFESoZFKgFTkwqpVqzBNE4/Hs0ZVM1aMHKPdY1ZKCdH3kaHnwGoArQZsPZ5osvu/lLiORC+9EWl1YLadBrHPc59Y1KBXzsQM3A2hJ+krvOQiPuaIVY/RcS32sluzNjU6fo/VHXreg0RG5hJt+QpH5b8ROYa1DpTe+R9ramoytpXGMgbngSrRnfsOsG/+aPoYPBUzsMyVmLHvEMKJ7tgWIVx5j2VGPyGbNxxEMGNfY3PuNFCTC45pdeB27Us0RQ5Imfx/5vvXaGxRHwEy4T1TXvMF+Z8LksqSCwd8zyxEbhnHCpHKodp7CMs7ZqQJxdZx6lWM8R096HkUI4wqQqMYBB0d8VzD+YQzJ9q2tLTkPV+qIsxSSqZOnZr3WCeddFLefVZnnREgAU4//XSEEFx44YXU1dVxzz33JL/Mbr/9dqAnsabT6WT69OkcfbT6klAUlt4CpEKRjVgsRkNDA6Dy+Slyo7eYpBY5FNmQUibPmdGY/1HKKLLtfIi+udqeFwBBXPrL8GTWXfREaCXo5TMxG3cE2Z7b5HotmPXd4iOkewIclPiYGCP8b6S8ASHSp9mwYl+mEB8TmGCuxOx6EFvRJYO2JxP55H8cnGefDloluvvgQYwxMDR97OAL3+R8/R0dKfljxhLaOq4nGHqZdJ7Cotf/M6Fp3uTvkUgkee9bXVuft101JVdT4jks734JnLYNsGmVGBkrmJv4XLsNeI4EuuZmqzGP8nXTxXRGPqHnvbXwOSazedWd2HXl2KJQrMtUVlayatUqFi9ezLbbbptTn8WL4zmUB1IcOV1+23zy3rpcLi688EJOO+20vOdfnXVKgAQ47bTTmDp1KrfffjsvvPACixYt6rN/3LhxHHrooVx22WVZw0oUioGgvNkU+bBy5Uosy6KoqEh5YytyQlVMV+RDY2Mj4XAYu91ObW3tSJvTD9nx1xTiY/e+bOIjQOxzzI5rEc4dEc79EJ4TkF13kd0LSyD0aqzgE6Srajtoz8e+o2GF30B3p887bgZnpbUljoUZfHLYBMhU98mJgjtCq0JoHnTXwRhdMzKMpiNsU5DGt8SPK+FdZ4FWibP8sQF5H44GbI5dyeq2JLzo9i2GxZ5MxGKLWNV4MJYMkDlNgSCbV6euVeBy9DxU//TTT1iWha8ojLcoU5Xx/nNVFJ1LRfE5efSJI6UkaizBkhEc+jjKvEfS5L837Txu+xZ4HNvlPU8qnLZqtql9gkDka9rC8wFJiWt7ihxbDmhR0LBCNIf+hykjlDg2wucYfQtF6xzKA1IxCLbeemtWrVrF008/zVFHHZVTn0TxmS22yP/74sEHH+zz96mnnooQgr/85S8ZHaKEELhcLmpra9lmm22yhmvnyjonQEJc+Ln55pu5+eab6ezspLGxEdM0qaiooLKycqTNU6zFhMNhmpvjK7DKA1KRC0pMUuSDlDJ5zozWcFrF6CKR/3HChAlZC/QNN9Jqg/DgKyDL0BPI0GMgShFF18RDuK1V2XohnHtiBZ8knSBTOPGxe0bjx8wNzPq0tiSxWpDSyjnsNF9653/s7TFrRj/B8N+GFX2/e4sD3X04Nt/FaM69sSJv01/0jYtZjtLrENoYjNAzWNEvEMKB5twH3f0LhHAOyXEMB7p9E2yOPTCi75P6fRM4vacgtIEVVykkLe2/zyA+CqAYm2MLQtH5ZBPvy4su6uPJm8j/OHa8QWYBfXU0yotOz7FtHCklbV3P0NB5J1FjWa698Dp3LHjEgM85BZ9zSk5tI2YLP3U+R1MoLlhWuLZjQtHhLPX/mx/aH8WUoWTbStcObFd9DV67cmRQKNZEDjvsMF5++WVmz57NzJkzs0bcPvPMM8yePRshBIcffnje85188sl9/j711FOBeBXuKVNyu0YVknVSgOxNcXExxcXZk34rFIUgURiitLQUr9ebpbVC0eMxqwRrRS60trYSDAax2Wyj0ptNMfoY6fyP0liEDD4NxmLQfAjXNHDuixB2ZPgtert9yGQGunyFv27BRHYgOy9DK7kDq+tuMNJVV9biYqXrEAjPIZXHVz6hSzmjpS4I0rO/nKwCjigaMvERoL6+nmg0itPpTOZ/NMP/Jdp25moto5ihZzEjb+Isf4IYN2FFXiMekqoBBohSHGW3o9l/BoDdd96Q2T1SeMruJNByLJbxHT25MOPvoc25H64h9lbNhZixnHDk7QwtJAYdxKIfkN4NK37OlRddRImvr2iY8JjdYINtgCdysCj+easu+R32PKu7N3T+g4aOW/LqA9ASeIwxpf+Hrg1/pElTcD4fN1yIKaMkrlUt4f/xTdt9KaXelvCnvFl3Mj8f/yRuW/Ww2qpQKAbPKaecwvXXX8/SpUs5/vjjmT9/PhdffHE/Z5Ply5dz2223ceeddyKEYMKECZxxxhmDnn/evHlA6tyQw8E6I0CedtppCCH461//mvNDWVNTE1dccQVCCGbMyBQ+olDkhsr/qMgHKWVSgFQekIpcSIhJY8eOzSu5tWLdZLjzP0qzHhl8CqIfgLRA2CD2P3qEGYEMvwK2TaDsQTB70uRkLDSTuwWAhdX1L4RzT6RwQyxRKMQimdtOlKCXP4jQvGiug7Ci8/uOUtDQ6x50Z+aE8Lr7CKxQJo9QHd2TWzjXQOmd/1HTNKSMEm2/lNQxiSZYLcQC/8BZPh3L+BEz/B+QIYRtY3TXVMQwVbgeKTS9gqKqOcRCc4gGn8WymtFsE3F6jsPm3GdIxeJcMYwlGffH39lMYdcCh21TxlY+it3WN29mOBymvj6e93HyxtNoj7xIV+RdMnlR2vWJVJX8H6Xe/M7lSGwpDR3ZCzmlQhKhM/QGZd7hrVAdMur5qOECLBmlz2KLtLBI/R0uMYmaHXzf/iBbVV4xTJYqeiNk/Ge451SsHdjtdmbPns2ee+5JIBDg9ttv5/bbb2e99dajtrYWIQQrV65M3p9JKfH5fDz33HM4nYOPCthrr70GPcZgWGcEyIceegghBL/97W9zFiA7OzuT/ZQAqSgECQ9IJUAqcqGjo4Ouri40TVPebIqcUCH7inxob2/H7/ejadqQfy/J8BvI9guJe++tLj4k/u5+wjIWIdvPBddR3VsLIT4mLQHja6TxHUnPRuEFfRJopWjOfRDuI5LFU4TrMAhMB6sBKY0hER4BhGNXhC3zeyAcOyCc+yAjb9H/NdRBFKN7B+8dkYlEyH5CsLbCc0G2ZehhYoVfRlp/QrNtiObbcEjtG40I4cLhOQpHnuKwlBax6PuYxlKEVozD+XM0rTA5uAyzHsvqwKaPRdMyR4LFz7RMla8lUeN7dL28355ly5YhpaS8vJySkjKKrAeob/8T7V1PAbEUYzmoKr6EUu8v8zoegNaup4gvZuQa4t0bgWl1DqDf4FjWOQtLxlhd3LWSgm//11xKMJB80z6b+tD3VLq2YOOSIylWuSEVijWGrbfemvnz53PCCSfw2WefAfHrZW/RMcF2223Ho48+yuTJk0fC1IKzzgiQCsVoQHlAKvIh4f1YW1uLzaYu14rsKAFSkQ+9PWbt9vTVlweLNH5Ctl8AGDn2sCD2BXjzLz6RO71EChkCcwV6+f0IraJPK6F50csfx2g9CcvMNadcvghspbdlbyUE9rJ/YXT8ESv0LL1FSGHbDFvZ7Qh96BarUnnMWsaPxB8nMr23JtJYjnDkX71zXSUaeRt/+2VY5oqejcKNx3c+Ht9FA85XGAq/TXvnjUSi/+veYsfjOhRdq8G0GlL2iT8GZ5vPxLICaHrfgkGrFyzSNDdjy/9ONLaEYPR9+gvpUVa2XYTNVoXPtWfOxwVxD8jsxaXSIXHYhl/Aawimyo2a3tfUkoJo8vFd0hJZSGvkG77reJodqi5jPd9UTBnFpZeiCRUFMWSoIjSKAjBlyhQ+/fRTXn/9dV566SUWLFiQrBVRWVnJtttuyyGHHMK+++47ZDZ8/vnnvPPOOyxevBi/349pZl7AKYRjnnqizUA4HAYoiKurQtHZ2Ynf70cIwZgx+eW0UaybJMQkJVgrciEUCiVvXMaPV8npFdlJiElDLVjL4GMMSBiIfACOvZDReTl28ADB/OfBjOeHDD6N8P2m315hm4DU1wNzOQMXONKjeU5G06tyaiuEC3vpDcii32JF3gWiCPvmyTyKQ0lDQwPhcBiHw5H0yheaj5w8zjSV9zpXYtGP6Wg5kX7nmgwR9N8EMoa3+LK8x+0KzqGp9Sz6iokxguHnESJT/tHsYqcQ7pT5ExMCZO9cY6HoFwSj72acr7nj9rwFSF0rJp5fM9eFjp75bFoVRXnOVwikTG1rqoB3KeklPva8JxITUwrebbgF2RBfyHBqJZS5JtMVayVi+Sm2j2Wz0kPYsGgfNKEe/xWK0cTUqVOZOjVzCpZC891333Haaacxf/787I27kVIqAXKoee+99wCSSbYVisGQ8H6srq7G4Vi7cx4pCkPinFFikiIXEoJ1RUWFKnKlyIlhy/+YsgJyDhgLEWV3Q9O+IP05dIjmP0cSCyv0AloKAVKadcjouwyJC4q+IbbiK/PuJvRqdM/w5qtLVTFdc02Fzr9k6CUQ+oYIfYNhsHDtoKvzeuKfl9SfmWDgn7i9p6HpFSn3p8KSIZrbLiFdrk4p/QhRipQB4gKeHTCxckp+oFHs+VWfytcQXxRL5H9MeEAC+IMvk7mYkkUw+iGG2YotRVh3Okq9h9La9WTO7eMIQGNCxc2IEfAYLHdtQyC2BLnaa6EhseibH9RM/t1XEDakhiF1Eu+rlBAw/QS6PsaSAhON1lgbS4MLKbbP4JBxf6fCtf4QHZFCoRjt1NXVseeee9Lc3JwM9fb5fJSVlSW/24eStVaA/POf/5xy+1133UV1deaKYZFIhB9//JEXXngBIQS77bbbUJioWMdIiEljx47N0lKhAMMwWLVqFaAESEVuJARIdb4ociEYDCY9ZgfrASllFCLzwPgRhAec+yFsvc5DGcl9rN5yh2WgaeUI71nIQC6VbRPeRL3zp+UhGspA6s3GsvzGyQPde+YaU4ilt2AtrVbM4HNY5mKEbWOk8X2aXhJ70f8NOGR4XcM0VxKLfpitFZHwi7i9p+Q8bjD4EjKLiC9lOwC6VovbPQ27bTydodcxo5+QyctVCC/lxRf2254QrCsrK/H5enJXWjJILl6V8Xa5C5A+5254HDsQjH6a0d7euO1bMrbs9/hcu+Q8TyFZv+RYlvln9dsuBAhpdRf/ib9WqwuS0J0PUvYVJo3udqbUiCUL2cTH6Yg18fjSM5k29mo2Lh5+j8+1BhWCrViDue6662hqakIIwRlnnMGll17KJptsMmzzr7UC5LXXXtvvZkdKyd13353zGFJKXC4Xl12Wf5iDQrE6CTFJhdMqcqG+vh7LsvB4PJSWlo60OYo1AFUxXZEPCcG6srISjydT+GVmZOQdZPul3YVIbIAF/uuRrsMQJX9BCCdoNWDVZR4n4b3TR4BchBV8CuE+Fhm4g9RFK1KPBhqIYugWVeJkEiQ1sKUpkNJdkKbwuNDd04Zo7MJimQGWLf0OgNriWwg3fEn8tezxvIqj0RMGa8defA26+6DhNneNxbJac2ilY5nNeY0bMxaTPVdnHNNqJBb7kvKSv9DY8TeyiXluxw7Y9P7RYr0rpvfGYd8w65hCeLHlmJagp49gg+oHWdZ8Pv7wm8TPxXSe13bWq7iNMu9hec1RaIodm7BFxVUsbPkbAj3pCSnQ0TEpcW5DW+RrrDTXPnM1UdKS8d6WZDXxkeTvEsmrK6+j0rUBZQ61YKlQrGu8+uqrCCE46aSTuPfee4d9/rVWgIS+1YMSYmTvbelwuVzU1tay6667cumll7LVVlsNmY2KdQMpZbICtvKAVORCQkwaN26c8hxRZMWyLBWyr8iLQuR/lNHPkG1n0yMm9BI3wv9GWmFE+R3g2A6MT9OPk67KtezC6vwDwvMDWsnfsDouJ/4wnUs4twU40CtfB9mFNFZgdVyQsb3mOT7lHmHbHLRxWUXUfLEVX5Wstj2asWKLWLX4TLqCe6PrJjUVX9LzHvQWtDTQJ6K7fo6mT0B3H45IkRdQkR5dqyG7566Jpud3LxmvdJ1rGgSTSPRjotEFWewAEPFFhhQkPCB7h18DlHiOoKH9z0gZTjOmTpn3OLQ042ZC10rYoPpRQtFv6QzNxZJhYsZKuiKfYlgNaMJHqedwqopPwmEb+sU6KS3qu15meedjBKI/oAknNd4DWK/kJLz2eF7MSSW/oti5CYvbH6U59CEgKXdvxwbFJ1Dl2Zmo6acpNJ+l/rks63qL3u+JJVdztuk+d8yU4mPvdpIv2l5gr5r+KScU2REy/jPccyoUhSChSZx00kkjMv9aK0BaVt8vWU3TEEKwcOFCpkyZMkJWKdZVWltbCYfD2Gy2rCkAFApQFdMV+dHY2EgsFsPpdFJVlZ/XiGLdJOEBud566w14DBn4J+lj0SREX8UKv41w7YcM3pd+nCwihww+jFb+DFrZI1hdd0H0gxwtDCJs3bkHbVsgIr9Ehp9N0U4gnAcgnPunHEUIDVvRJRgdv81x3iyIUmzFV6N7jijMeEOIlBEirSexfGUxAGOrm7Dp6YQsC8wl2NxHotlH7l7bNH4kFnwWaTYg9Crs7iPR7cMXXjYYNL0Ku3NvYpG3Se8l6MTpPjivcb3uX9DWkTo9VWp0QpG5uBzbEY7+j0zipdu5Q79t6fI/QrxYzNiyW6hrPZ/+Cwo6Dtskqkr+Lw9bU9jkmIzbMbnfdiktTKu9X77KoUBKky8aL6Ux+CoJb0xTBqnzz2RlYDbb1NxDuXtnACpc21IxZtuU4zj0Isb59qfctS3Lu97DwiBbbfJ4uHb6xWuJxbKuTwZ8bAqFYs2lrKyMxsbGEYuwG/osk6OE9dZbj/XWW08V/1CMCImVhjFjxqDrw5/kWrHmobzZFPnQu2L6cCSQVqzZGIaR/F4aqAApLT9E3yFrrrWOi5D6hmDbhNVvOyUSKyevLB0r+BSacxds5Y+iV38OrkOATN+nfUOqhRBoJdejFf0etDG9mlWh+S5FK70dIdJ/dnTPEei+TB6UuSBAq8RePX+NEB8BzPCrYK1ixar4wsb4MQ1ZeuiY4deH3rAUSGkRar+arsZ9iAbuJhaaTTRwD11N+xFquwIpc8sLONL4iv8Awkm6xzRf8e+7PRpzx2abgM9zLLnkXowjkDJKqe8s0ouPAiFcFHuO6bcnXf7HBCXew1mv6kk8jh2T2zThpdx3GpNq/o2uleZoZ25YMkpj5118vXInvqrbioUrpvBD/WF0BP9T0Hl6s9z/VLf4CL1fQ4mJJWN81nABphXMeTy3rYLdxlyHQEN0X/s0YdH7PdW6c9/m4iwnB1IYTKFQrPFsv/32AHz/fbrczUPLOvOUsnTpUpYsWcJGG21UkPFWrlzJaaedxumnn16Q8RRrN6oAjSIfurq6aGtrA5QHpCI3VP5HRT6sXLkS0zTxer2UlZUNbBDpJ6es+LILEX4eUXp7PCdjL9Ewl/q6ccw+RU6E5kX3nEJm8dNC8/y6zxYhNDTvqehVb6FX/he98g30qnfQfGcjRPagIGH/WY72puwNwo297D40Lb4YLo06rMj7WLGFSDk6xQAr8jags3xVXLSdUFufpYcGsmvI7UpFNPAPYsGHu/8ye/1ALPQUEf9NI2JXvtjskymrfA6bfZs+2zWthqLSW3H7ThvQuBVlN+BNIRamxsDh+Bk+90GU+s7u3tZb8NcBG7UV96OnqFSdLv9jb3yuPVi/5lk2GfslG9d+xCbjvmRM2bUFFx+ljLGk6VRWtf8dw+w5f4PRz1jafBpNnTMKOl98TslPHQ+TXvCVmDLAqsCcvMad4NuLaRMeZYOiX+DUy3BqHuyaG9H9SB/P2CPRsMh0fRboTPBsndfcil7IEfpRKArAhRdeiJRyRPI/wlocgj3UtLW18dBDDyGEYMaMwn9xKdYuEgVolACpyIWEZ1JFRQUul2uErVGsCSQESOUxq8iFhMfshAkT8soxK2NfQvQTQCDtWwMuIF0et179wi+geU+CyheQXQ9CaDZSduRhsQCtCBlbiBV8AhlbCMIN9h0g9nHq9o49Ea5DU48mdLDl7/kphDvvPsm+roOwF12KsE3EjH6J0X4JmD/2NNCqsBX/Ht2d2uYRQ5p0Bjx0BnwIYVFb3ZSlQwxhG/5wZ2kFiQTuydSCaGAGTt95a0TeTZt9C8qqXsCILcI0l6KJEmyObePn7gARwkFV+e2UFl9Mc+slRKLzSa1qaGhaKV73NIQQVJZcg8e1Fx2BBwlHFyCEA597GiXeU3HYN0g5V7r8jymPNYWAWUhaAo8TCL9D/2ONi/4r2/9EsWd/nAO4JqTDsPyEjOUZ2wh0OiJfMJ5cReE4pc4N2anm9+zU/XfIaOX1ustoiXyHQMcOWFhEM/gZSSy2LBvZAjwKhWJk2H///bn88su58cYbOffcc7njjjuw24c+LUUCJUAqFEOMZVlKgFTkhQq/VuRDV1cXra3xyqnKY1aRC70FyFyQ5kpk24VgfEE8eKbbHUOrAiu7AInlB0DoYxDFV0HxVZj+G6FrBllDuOMWIIQHs+Vw4p5Xvfu4QSsBq9uzSatA85yE8J6Vk1djPgjH9iBKIF/x1LY59pIbEJoHM/IeRutJ9BNDrCaM9ouRph+b79cpRxoJNMdWrKj/EoCaylacjkxVlAUID3qe+QkLgRGdDzJbOGsEI/IedveBw2JTIbDZN8JmL0z0VgK7bX1qKh+jofloIv0KzcQ9G6sr7ksWlxFC4HXtjde1d07jh8PhZP7HTB6Qw0Wz/6EsLTRaA09QW3plwebMTSgWBblGuW3lHLre/dSHFvBT4F1MGaXEMZHlwW/4zv/2ajPqSCz2HXMJlc5Jg557XUUVoVGsyTzyyCNMmTKFXXfdlXvvvZcXX3yRo446ismTJ+PxeLL2H2zxGiVAKhRDTHNzM7FYDIfDQUVFxUibo1gDUCH7inxInC+VlZW43QP30FKsG0gp8ypAIy0/suV4sBK5/3qFClst2ft3e+EYzQeDDCJsmyM8x4PZRm756HSgGBl5o/vv1QXLKMgYWuXceF40vXZAD/VSSmTsU8zQC2C1IfSxaJ6j0frkkXSi+36D6b8+n5HBWEi0cUd032WYgZvJFEtn+v+E7jl01Hjp6e5fsqI+/tqPq8mU/1EHJI7SWwflKTpgZKiw7dYQpLSIxRZgWe3o+nrY7Rvn1E/TPNRUzcIfeBh/4AEMczlCuPG4D6Ok6Bwc9k0HbNNPP/0EQHl5OUVFI3seSymJGIvJVlU8HC1sLjSb5qXY+TM6I1+RLoemxKDSvVtB5hNCUOvZllpPTyGbzctgm9B3fN72PD8FFyCA9TzbsVX54VS7cjtPFArF2scpp5zSJ/pl1apV3HnnnTn1FUIoAVKhGO0kvB/HjBmjikMosiKlVBWwFXmhwq8V+dDa2kowGETXdcaM6SnGIqWEyH+Qwccg9jUIB7imgvCCtYrUD/CZ8xZKJBIDzB4BQJp1yMgrYN8ma38AtAk93o0pMUG2QGwBwj2wwi5Shom1XdAtcurdtgrMrnvRvWegF12VvFnXvWeA1YbZdQ89qdQToqiI57lM5SEpg5j+P+VgjYEZegmb91cDOpZCI7Ri6hq3AoJMqE0Xfi3QnLtj852P7th+OM1LotlyE8y0QQhrqyNlDDP6CVL60fRJ6DmKf4UiGJxNZ+ffsMyVyW12+zaUlF6Pw7Fl1v6acFNSdA4lRecgpZWxCFM+JMKv03k/WlYXHcHnCEU/BXR8rj0pch84JJWphRAI4UTKTJ7aGpoWF81Nq4vmrtk0BWZjWC04betR7fsV5Z4D817YWL/kDL5ovCjNXh23rZZKzz55jZkvNe5Nmeq+YkjnWCcZiZyMygNSUUCkHLkTSgmQCsUQk8jnp7zZFLnQ1tZGKBRC13VqampG2hzFGoASIBX50Ltius0Wvw2UUiI7/wChmcRFNSv+sBN8mtxCpPV4n15PSLL7v8RfPXSPF1tAZg9IAc6fAx6ILM06v4y8DwMUII2OPyAj8/ral/ir637QqrH5zgBAGguRVhNotXFvOr0azbEjuvcUhD6eaOOug35QlMZ3gxuggIRCIZqa46HN603cCUQ7EEHYNkP3nIDu2BWheRFa/0rHQ42UYZBhEMXo9o3QHTtiRv9H6nNWR7Nvjm6fUpC5I12PEfbfgrSae2awb4en9Hp0+2YFmSMTXV1P0NF+ab/tsdjnNDcdTlXVv7E7ci+aVCjxETILkF3h91jefDqW9BO/bgjau57Aro9jvarHcQ6BiFvinkZ78AXSX8ssStwHEjUa+abhV4SNJcSvTZKIUUdn+D2KXbuzafX9aN1h6blQ453KRmUXs6jt9u7QZzM5rlOvZJsx96IVOE2EQqEYPSS8wQtNLtErmViyZEmBLBkY6qqnUAwxSoBU5EPC+7GmpiYpDigU6bAsS+UMVeRF4oZ4/Pjx8crL1ipk6JVu8RH6eiXmIj52t7NvDeZPYMXzkSJ83ZWy0yFAq4BeAk4PejyXo+//sFpyKcoi87B1tZ7mKqzQc2QMi+6aju49GbProe7wa9HT3ujEMhajOfcAc2VOYelZ0YoHP0aBSAjWFRUVlI07H/j7yBoEGNFPiPj/iRmZB0iEVo7dcyKu4j8RbDkeKTvpez7oILy4S28tyPzhwHTCndf1227GFuBvPoKiyhfQ7UNXiMeygnR2/DHdXiBKR8efqayamabN0BGJRJL3vasXoInEFvNT00lIot1bet6jmFnPssZj2LD2HfQCi9nVxefQEZyDTFkZWsdpm0iJ50C+aTiRsJEQDBLt4tfDzvD7LG+7kYnlV+c196TSs6ny7MMK/zP4I9+iax6qPftR6zsYXcuea02hUKy5TJpU+DyrQggMI1Mu5uyMdG5e9XSrUAwhlmUlE3HX1taOsDWKNYHEjbsKv1bkQlNTE9FoFLvdTlVV1UiboxjlyOj/WL7sE0BnfPG9yMarQHYWZvDYt1D1NkK2AAIZuBfCzwPpbpQlWM0I3++RwXvBSoT3auDcF734D8jY1+QUpo2FcGw3ILOtyFtkdVm0WjE6b8UKJqosr+7RaWK0nYde/IcB2bA6unvow6+l2YwRmtVdUdyO5vw5uusAhHD0aZcQrHMtWDTUxEKvEGo7l94isLRaiQbuxIi8gadyJtGuB4kFZwERwIHdfQTOovPRbIN/6LKsNsKdN6bbCzJMyH8jvvL7Bz1XOsLhV5GyK0MLi2j0PQxjBTbb8C5MrVixAiklJSUllJSU9NnXGngASYzUn2kTw2qio2sW5UWnFNQmt2MK61fNYFnzuViyi57HXwOXfUMmVT1KKPYj/siHGUaxaAw8yfjS/8tbIPU5NmFyRWGuDYpRggrBVuTASIY5j2aUAKlQDCFNTU0YhqEK0ChyRgmQinzonS9U5ZhVpENKifT/nXDbYzS3HgPA+OpvQUYKOEsYYf2EsHfnnhOQyxOT5jkavCeC8TXSCiJsGyD06rjdsW9ynNuJcB02IKvjr0Evj8Y0WMH7sgxkxsW8QSLs26PZhnbB0gjNIdZ+CXFxWAACM/Q8MX0czvJH0Ww9XhsJD8iR9pgAkFaAUPvFxN+r1UUsCyv2NbHQs7hLr8dV8mekDCCEr6C5BWOhf5NeVAcwMcL/wbLa0LSygs3bZwazjv7V4PtjmatgmAXIRPj16t6PAJ3Bl8hmc2folYILkADF7n2YMu4T2rueJxj9EiEcFLt/TpFrL4TQaPXPJdt1wJIhuqJfU+zaseD2KRSKtY8HH3xwpE0YlSgBUqEYQhIFaGpra/tUm1IoUmFZVvKcUSH7ilxI5H9UgrUiI6HZEHyQFQ1xYaus2I/XXUjxMUHPbaVw7IQMzcrQVoBtk57cgfYt+2WEFI6tu8fMHG6kldyQVw5CaXViBp/GCj6DNOvJzbUkmyemhRVbjNA3QJpL0owpQKsBqwNIUY1ZXx9b+aM52DJwrOhnxNovoseFp5edZj2RlhNwVf8XIZwYhpFc5BgNHpCx0L+zVLG2iHY9jrPoUoSwI0ThBUDLrCd+TsYy2iHNRhgiAVLTKsgk5Fkynm2wofVsBA7crn0o8p2KYwjDwhMkPGZT5SiTWSuQS6QMDoFVcXTNR0XRCaR0B1CeSoo8EGTOYDxUcyrWLE4++eSRNiErixYt4pFHHuGDDz6gvr6eUCjEq6++ykYbbZRss3DhQn766Se8Xi977bXXoOdUAqRCMYT0FiAVimw0NTURi8VwOBxUVlaOtDmKNQCV/1GRDmk2QmgmMvweGHHPvBUN8evK+Jp01YwHgVYBtp4CEsJ1EHReD7Kd1OKdRPOe3n+rjCIjb4K5CrRycP0Cwi+mGUOAYzc098E5mynNRqItx4C5nNyERx2EG2Qga0shBLbivxBrPbnb3t42a4DAXnojwrYhRtfDWMFZIIOg16B7z0T3HIsQes7HMhBiXfcRf5RNHQaLtRIz9DI2zxGsXLkS0zTxer2Ul5cPqV25YBrfkVWQlp1IqxmhD819l8gi/vVtNzS43QfR0f47SOZS7MHsFh8BTDN+D+rvehR/16NUlf8Lryezp7CUkkhsIZbVjt22HvY8wtYNw0guiqXymHXaNyMU/YT0Yr6Oy755zvMVkmLXTmS7HmjCjddRmCJG6Qga9SztfJ5AbAm68DDOuy81nl0LWiRIoVAoLMviiiuu4Pbbb8eyrGS4uBCCaLTvd8vy5cs5+OCDsdlsLFmyZNBOD+pqplAMIUqAVORD74JFymNWkY1IJEJjYyOgPCAVfZGRd5FN+yIDd4LxCRAGoK4xnid0fE2qwi9ZEMXEwz5Xmyvxn74hsuueZNi0EE708vtBeOl7uxkfQ7hPRLj6Vq22QnMwG3fFav8Nlv+vWB3/B+HX4hWnodc43f/aNkMv/UdehxFrvxTMOnIWH/XaeEGdHNCcu6A5d8Fe8RjCvkWffcK+OfbyR9GcuyP0WuzFV+Ic8wnO2q9xVs/D5j1+yMVHACs8l8wCmoYVeQPoCb+eMGHCqPhOEsKVY8Mc2w0AhztbUSQdm3MPNH3oFhE1rZSi4kv6bbd6iY99iecpbWo9j5iRvvqpP/gSy+p3Y3njAdQ1H8vS+l1Y0fhLItGvc7Krrq4uo2BdXnQqmT2JTcp8J+U0V6HxOCZT5NyJVNe4OBrVvuMKXiCnN4van+DVZb/gu7b7WBGYy0/+F3m//gLmrTiBiNk6ZPMqFIp1j7PPPptbb70V0zQZO3YsRx11VNq206ZNY4MNNsA0TWbNyhTZkhtKgFQohojeBWhUOK0iFxLebOp8UeRCQrAuLi6mqKhohK1RjBakuQrZdi5x76ieh33LEr08IAcgQMpOsCVCOOO3jxLRI0DGPsEK3InZcghG66lIqxNh3xK98jU03/mgbwz6eHDui1b2CFrxNX1ELSv8OlbHxd0ek/HR44TBqovneLTvBPpEsG+HVnIjesVMhNa30EUmLGMJMvouOVXMFiXo3jNxVD7fndcy2y2zQPfEi8dojh1xVD6PvWou9vLHsVf9B0flv9GcO+ds61AQ93DIFDoMYCG7c4NmCqcdCWyuA8gcjq+h27cbstyLAJpeg9N3btr5QcNVdPmQzZ/A57uAouLfIURPJeVc6sD7A4+k3N7Z9Qz1rWcSM5f12R6KfsTypkOJ5JCPNZH/ceLEiSkF62L3wRR7EosOvffHP1tVxZfhGmIPw0xsVPkPnLYJ9A2wjdtW7NyZCWVD976u7JrHFy03AVZ3tW6LhJzcHvmeN+vOZkHzv/i0+R8s9b+GKft7vyqGETlCPwpFAXjzzTeZMWMGAL/73e9YunQpzzzzTMY+Rx99NFJK5s2bN+j5VQi2QjFEtLS0EIvFsNvtqgCNIid6e0AqFNlQ4deKVMjgk8RFpr5PK01tJURjduy2GNXl7QMYWUD504joPGToRaRZhzS+oadwQy9hKPo+ZtvZ6OVPIPRqhO9CNN+F6W2WEsv/915jpWgT+Q961XyE5km5PxdkdEFO7fTSf6K7piVFFJv3BGKR1zP38f22X9ivZtsAbBsMzNjVkDIG6IMKxRRCIGybIo3vSP80q6HZpyCl7OMBORrQ7duiO3bCjH5CarnNwlF0wZDb4Sq6HCFchAN39clJqekT8JTegs2x9ZDbIISgqOh8vN5TiYTfwJLttLT/HSnbMvQyCUfe7bfVsoI0tieqNK9+XphIGaGp/c+Mr3oyo03ZBGshNMaV34HHuSOt/vuIGosBcDm2orLoNxR7Dso4/lDjsNXws9o5NHfNpikwi5jZgtO2HjVFx1PuORAhhu6x+dvW+4mLnX09RKWEKIJw9Cdao48BGhIDZ1MJe9TeQLV7myGzSaFQDD1SSj777DM+//xzmpubCYVCWatnX3PNNYOac/r06QAcdNBB/PWvf82pz447xotvffXVV4OaG5QAOWC8Xi977rnnqAhJUYxOVAEaRT4YhkFDQwOgwmkVuaEqpitSEnmTVGGOdY3xhbBx1S1oWr6uFBrYtkDTXOCahnBNw2y7CIxvU84FJsQ+RkY/ROTi9WcsBPOnzG1kEBmZh3D/Ik/be5GjeCeEq8/3tnDshuY5GSv4cMr2mvtYbEW/GbhdaZAyhhl8DKPrYaS5DNDRnPti952D5hiY8GDznkys46oMLQQ2z69oaWkhFAphs9lGTRoZIQSe8vsItpyGGfuE+GNMwjVIw1VyHXbXz4fBDg1X0cU4vWcQi7yJtALotvXRHTsNyf2eabYQDr2AaTWha9W43Yei6fEQZ03z4vYcSjA0F0t25WJ9vy2B8KvIjDlOTUKRt4gZK7HbUi+QWpaVU8V0ITTKfSdR5j0RSwYQ6GiDWFQoNLrmpaboRGqKThzSebpiy/FHf0TXXHht69OeIsw9Lj7akN3vmeyVVzZi+flv3YVsV3UlHlsVFa5Ncem5e4MrBoeQ8Z/hnlOxdvHwww/zpz/9Kek9niuDFSA/+OADhBCcfnr/PNzpSDg7JKI7B4MSIAfI+uuvz5tvvjnSZihGMQkBcsyYMSNsiWJNoLGxEcuycLvdlJSom0hFdlQFbEUCGfsS2fUIROeD1ZKyzYqGeP7HcXmGX0skYCI8PdUcpTSQkVfJHPRpQ4ZfhhwESGnlkt9MQEbvrmxzdGCGXsyhpQPNsV3fmYXAVnwNpj4Js2sGWHGhRdg2R/edgebKlhcwP6zYN8QCM7DCL9A3ZNrEirxBJDIXR+kd6AMQY3X30ZiRt7HCr3ZvSTzV6oCFveRvCL2W5cvj3qLjxo1D14c+N2WuCK0UT+WzmNEPMcIvI60gmn0j7O6jhjTvYmpbfDjyKYAkLUzjO6QMouuTkiJi+vaSgP8f+P23Efcwjhfg6ej4I0XFl+LznY8QgraO6+jw/zMHC3Rczj37bTWMOuLvf+YgbsNML0A2NDQQjUZxOp1UV1dntUQIgS7WzNQhMbMd0wrg0KvQNGdefbtiy/m86U+0hD9KbtOFN2VbC4FMkfpBSjAkmFi803A9ABo2Niyeyk5VF+LQhy5PpUKhKAy///3v+fvf/57V2xHi18tc2uVKIn/8pEmTcu5js8Vlw1gsWxqXHMYa9AgKhSIliRWC0eI5oBjdqAI0inzo7OzE7/cjhFDXmHUcGXwK2flH4uF76QWEukT+x+rcBMhEbsfk3123Ax0I9/EgIxnnimPlVDkaQOi5pJ2QoA1MbJcyTKzleKTxfZaWGprn2H55JaXVgdHxJ6zwi/QctxPNuSOa68CCXrON0Bxi7ReRPulXfP5o+wWI4KPY3Iejuw9DCHdO4wuh4yi9EzP4NEbXg0hzEaChOffA5j0bvVswToTTjsYUD0IIbM6dsQ1hTk3LasOMfglCx2bfCjHI4iPh4DN0+W/FMpd3b9Fxug7GW3INmlZKMDiTYNdjGMYKNL0cj+cYkCZ+/429Rokl//V3Xo8QbjR9Uo7iYzyvYVGKIi+6Vk7m4jC926Um4cEzYcIENG3kSwyEY4to9j9EZyhedMnj3IFK3yn4XDsOeMz28Mcsa7+T9vB8ADThYozvSCaWXogji5gMEDRW8W7dCcSszj7bDauL+PW773XERCN+DejZLiXEpI7VJ08lmNLg+45X+dH/Dh5bDR5bOZN8e1PtnoJbL8VnH15xfq1nJHIyKg/ItYYPP/yQ66+/HiEE+++/PzfddBOWZbHtttsihMAwDNra2vjkk0+4++67+fe//83uu+/OzJkzqampGfT8brebaDRKMBjMuU/inqCsbPA5ltc6AXKDDQqTa6c3Qgh+/PHHgo+rWHuRUqoK2Iq8UPkfFfmQOF+qq6txOBwjbI1ipJCxr7vFx7iXYjrCETvN7XFRLbsHpOguLrNasQ/zJ6zOaxHR/yGKbwatHDJ6Lop4wZgcELaNwfYzML4itRAiQCtHOPfIabzVsULPdeerzGKHYzdsxX3Dk6UM9RIve7/GEcyuh7GMpdjL7htUbsaknWYdsfb/IxcxCCQy+iGx6IcYgbtwlD+BZstNLBRCx+Y9Hpv3+LS5JRMe1qOlAM1wIS0/wY5riYWeo0fwc+H0noir+AqEyM/jDSAYuJuuztXzbJlEwnOIRuZjaZUYxkISOVBNow1/59+zjuvvvLW7QFI270UB6FRVTMdu6/9++tzTaGy/ivQFfgRO+xY47OmfsUZTwaKO4Cssbf4Nva+LHcGX6Qi+yJiSy6kpyT9PaHPXf/iqqW8/S4ZZ6X+altBbbFs7C4eeOd/7D233EbM6Wb1WuRCgSdn9qe8tQgpWFyUtBNZqXpFSxsVKicCwughHltAY+Ykfuz5P9q9xbcrOlSezvm/gAqxCoSgMd999NxBPV/HSSy9hs9n65FYUQlBeXs7UqVOZOnUqd999N+eddx4HHnggH3744aDv+ydNmsRnn33GggUL2GWXXXLqM2fOHACmTBl8obC1ToBcunRpwcdU3kiKfGlrayMSiaDrOpWVatVRkZ2EYK0ESEUuqIrpCgDZFS9KkM0bsa4x/j1UVuzH646kHqvb00amFTPj7hcy/CLCuS/CfTyy6y7Si2UWmufoHI4ijl58DWbrr4mLIL3HjN+DacV/GnARCCMXDzHbptjLH0CIvuHGVvAZpPEtqd1PLGRkHlbkbXTX3gOyrTdm1xPkJj72RZoribadibPy5bzvWYWw99sWDAZpbo4L1UPhAWnGvsOIvAtIdMd26PatR8W9tpQhAi2/wox9Rd/PQJhI1wxMYzHe8gfyEptNs4GuzuvT7SVmNSCthoQFva3Jwd52otGPyfb517VqxlQ/h92WOtwuZtaRKjdkD4KKkt9lsEOOGgEyZqxiWfN5xF+T3q9h/DWq77gRj3Mbily75zymaYX5tvlKUru9mUSNepa03cqmldelHcOSMVYEXugnPibQkN0LPz2I5Hy9PR37e0VavfpJKYh0P95L2bO9PvQ9/17xOw6ovYrJJftmPWaFQjF0vP/++wghuPDCC5OhzZk499xz+e9//8vs2bO56667uPjiiwc1/9SpU1mwYAH33nsv55xzTlav9f/97388+uijCCE48MADBzU3rIUC5Mknn5y9kUIxxCTCr2tqakZV7iTF6MQwjGQ+DiUoKXIhIUCq/I/rOLGPyB4KDSsS4dcpvB/7hlrnEuOlYQUfRS+7HzPyHzB+oL9gKNF8l+UYWt3dy7ENevkTmP6/Quyznh36BmhFV6K59sl5rN5YsYVgrco+v4z2Ex8BzOBTWXrqmMFnCiNARj5kIAIkmEjjW6zofHRnbt4MmUh4P1ZWVuLxFK5AiGW2EGo7HzP6HiS9uCw0+xZ4yu5Gs01EWp3EQrMxo5+DsGNz7o3NtX9KobTQRIMzMWNfpLMeI/IGRuTNvArdRIKzSFvZXcqcPnGZyS7c2mwbpBUfpbSobzmLTNcRt2N3vK690u5vbW2lq6sLXddH/DupJfBEt8iX7pXVaeqckZcA2Rx8FVP60+6XmDQE/s2G5VdhSxOqH7M6sWQ07RhCgE0KipybETRaCJuN2ABztfc3flR9Q7J7h2PH0Lu3af3CtIWU/GfVLWzg2wWHPnoK/6yxqJBoxQBJOJ1svvnmyW29RcBYLIbd3vc778QTT+TZZ5/l6aefHrQAef7553PHHXfw5ZdfcuaZZzJ9+vR+8yV49tlnOeecc4hGo5SUlHDWWWcNam5YCwXIBx98cKRNUChUARpFXtTX12NZFl6vl6KiNTMpu2L4kFKqCtiKbnLzGkt4QI5bLf/j6nkec8MC43uEVoRe/hRW4DZkaCbIUHy3vgGa7zw0d/6FWYRja2wVs5DGYqS5CqGVg23yoLzjzK7Hcmuop86rJM1VZH7SNMFakbdd8bEbMUL/BqsRy2xFGgsGNE7SkvBbBREgE9WMC+n9KGWYYMuvsIxF3Vt6hFYr9g1dzUfhLLmacPtlIMMkBMpY8CmEPgFvxeNotvULZk8qIl1PkBDQU6MTCT6ZlwBpmj8RP5b+wnIh9AuXY2dCkTdJLyAKPO790vYPRd4jZmauwBqOzse0OtBXy42aIOH9OHbs2Jy8eYaSQGQ+mUV8k67I/LzGDMYWI7D1T0vRC0mUiLEKm2PjlPttWlHWMYSAGs/ObFZ+IaYVQRN2FrY9wJet95E4L+P/7/GA7C1IJsTIRDj26t8PEohIg8/bX2SHimNzPHqFQlFoEoVcehfs8vl6Fi+ampr6OaRMmDABgEWLFjFYxo0bxx133MGZZ57JQw89xOuvv84hhxyS3D9jxgyCwSBz585l8eLFSCkRQnDvvfcWpFDqWidAKhSjgYQHpBIgFbnQO1/oaAhDU4xuWlpaiEQi2Gw2qqqqRtocxQggrTYIzsqpyIuUsLIxnpts9fyPAxZAuvPgCa0IvfgaZNFlYNYBTtDHp72OSRkDqxmEC6GlT2QubBsgbIXJ6S17e1NmQPcck9oWrQJpdqbcF0cDLb/PoZQSI3ALRuBuyMv7NMu4ZmHylSc8IBMPPIUgFpqDZXyXZq+JtBoJt11IT5hrj6AmzZV0Nf8KX82bCOEqmE2rI806sonNlrE8w/7+CK10MCZlRNc3xWHfilDkjTQtNITw4POkF5vCsS/IlkNSEiUaW4TbuV3K/aMl/DpOLuHx+d1n6cKT00KNrqWuZh0fw8FY34GsDLySNgxbYjLed3D3WPFr7M/Kz8BnH8/XrQ/REVuCLiwsmfrxXZIIu073GsSP+5uON5UAOUiEjP8M95yKtYOqqipWrlxJZ2fPvUUiatKyLL755pt+AmTiWdHvT++NnQ+nn356Mgy8rq6Oe+65J3nvdvvttwMkK287nU6mT5/O0UfnnlYnEyNfpkyhWAtRFbAV+ZDwZlPniyIXEufLmDFjVIqHdRAZ+xrZNBUZuBmslqztWzuLCEWc6LpJTXl7fAwkFhYDE710hGtany1CuBG2jRC2CSnFR2l1YfpvxmzcCbNpD8zGHTBajsaKvDmA+fNE5JKs3YHmOijlnngey0y3yxa6+5d5mWR03YMR+Bck34PCPFlasYF5YvYZw7KSKR4GKkBKaWJE/4cRfhvLiItT8aIumV5HCWnPSRNprSQWenFA9uSKyFJEBDQ0PT+x2eU+jHTFXQaz3CilJGq10hG4Ne1IQnipqXwCPcNxCRzkcv6JDJ+jhMfsaBAg46HVmc4znSJXfsWsKr1TyZzqQsPnmILLljnlxCalZ6ELZxr7BBN8R1Dk6L/wMqnoQA5a70kOX/9FDp34DBXOTRHdY6zuB2ll9OCN0xxZhinTe2IqFIqhJRF6/e233ya3ORyO5Pann366X5/HH38cKGyqrtNOO41vv/2WSy65hA033DCeFqTXz7hx4zj33HP55ptvCprmUAmQw8Snn37K3/72N6ZNm8aECRNwOp34fD422WQTTjnlFN55552RNlFRIAKBAIFA3Cult2u1QpEOJVgr8kEVoFl3kTKCbDsdpJ9cRau67vyPtZWt6LrVXehgoBUUNcCG5sn9RlRaQczWXyO77gXZy5Mw9jlW2xlYWXMsDg7NuT/Zbnc1zzFpBRbdcxzoY4l7ifXbi7BvjebaP2d7pAx1i49DgKwf9BANDQ3EYjFcLteAiuhFu54k0LAzweYjCLaeQKBxd7qaj+sOZR9IfssEAiP0+iD6Z8fhPoZsYrPDc1ReY9rsU3C4Dk45rhA6Ghr5SpFSSgwEZnIBov+1wOM+gvG1H+Jy7pBxLK/r52R7X3StGqd9s5T7urq6aGmJ21FIj9mBUu77VfdnOd1ralJVfEZeY3rsG1DpOZD054bFxNLslbV9jvXZdexDFK1WTVzDzgbFJ7Jl1dVp+woh8NiqKXGsx4Hjb2eCd7fu7fECNiDJNYDGwiRqBnNrrFAoCs4ee+yBlJJ58+b12X7ssccipeSBBx7gmmuu4auvvuLjjz/m/PPP58knn0QIwbRp09KMOjDGjx/PzTffzPfff097ezvff/8933zzDY2NjSxfvpx//etfrL/++gWdc50OwV66dCnNzc2EQqGki2k69txzzwHPs9dee/H222/32x6NRvnhhx/44YcfePjhhznxxBO5//77B11aXTGyJMSkyspK9V4qsqIK0CjyReV/XIcJv5yT12Nv6hLh19XN3RkfLfITghICiQnCi1Z6NyKPXHwyeD8YX6eYM/631flHhHM/hJ6/2JULuudXmF33dueoTHXcTmze09P2F1oJjoqnibVfgox+2HsPmmsqtpLr8yqQYkXezyl0fkDIAFKaKYvp5ErCm23cuHF5pwSJBO4h0tm/ErAZnU/8HMoc6psZiWRoRROH99dEgo92i6Wr26mj2adgc+5PLPoJ0gqi2zZEt/Vchy2rk1jkXaQMY7Nvhq1btCsu+wf+djeR0KzulvHK9ZpWSXHpbQS6HiYSfo1cXx+J1v05TtdWIxb7Bk2UZj9m+4Y47JsTjX2Vtk1Z0W/SVqBPnC9VVVW43e6s8w01dr2KSVUPsKTpNKSM0vOZ1wGLcWV/wZtFlE3F5Mob+LbZojn4OgKdeI1qE4GdjSv+SKUnt8rSJc7J7DX+WdojX+KP/oiuuahy74ZDL87ZFqdexH7jrqczWkd9aAExK8w3Ha/QElnUfWZk/tzqwq6K0AyWwjmu5zenYq3g8MMP5+qrr2bOnDl0dnZSXBz//F900UXcd999LF26lOuuu47rruv7fVpWVsZVV101ZHYVFxcnbRlK1jkB8rvvvuNvf/sbL7zwQp+4+0wIITCMgbuq9/ZWOfroo9ljjz1Yb731ME2TDz74gFtuuYW6ujoeffRRDMPgiSeeGPBcipFHFaBR5ENDQwOWZeHxeIbloq9Ys7EsK7nIoQTIdQspDWRwNpmLZPQnUYBmbHVLntWu4wjXgSA8CPvWCNehCC33B1cpLazg42QWPCUyNAvhOyfncfNB6FXYyx8m1npat+do750u7GXTEbaJWcaoxVHxJFbsB2TsU0BHc+yCsOX/GZSyK+8+uWPEi/fYBl48ZqD5Hy2zlUjnDWn2mqQrxJI7OrptyiD6Z0fTSiiqfJautgswox/12iPQHfugu3aitXFXpNWU3G537oWv+M+EQ08RCswAIsleNvu2FJXehs2+EcVlt2MWXUY0/BpSBtHtm+Bw/hwhbDicexKJvEWw63EMcxkCO7EMuUvj6RMyvZ4WMeNbLKsFPYuwH4rMzyg+CuGl2HtS2v2J/I+jwfsxQZFrDybXvk1r4HE6Q28gMfA6d6DCdxJux+QBjalrbjav/ieB6Hc0db2CaQVw2ydS7T0Uux4vytAeXsBPHY/QGv4ACZS5dmBi8UmUufsKnkIIylxbUubaclDHWewYR7Ejfg2aXHIoP/j/w+etz7I8XJe2j0BjSvG+6GkEZYUiVwKBAJ9++ikfffQRH330ER9//DFLly4FYOLEicnfc+Wrr77izjvvZO7cudTV1eHz+dhss8349a9/zemnn55zgaunnnqKBx98kC+++IK2tjbGjBnDHnvswXnnncfOO++c0xgtLS3ccccdPP/88yxduhQpJZMmTeLwww/nwgsvpKIiW7qOzGy++ebMmzcPwzD6aEwej4d58+Zxwgkn8N577/Xps8UWW/Doo48WtDjcSLFOXX2ef/55fv3rXxMOh7N6PBaSyZMn87e//Y1f/vKX/fJ17bzzzpx44onstttufP/99zz55JOce+657LFHfvlJFKOHhoYGIJ5MVqHIhipAo8iHxsZGDMPA6XRSXl4+0uYohglpLEO2nQZmfgUwDEOjoaUU6F8BOzsawnUQeuntefbrhezKwWNTII3CFE9Jh+bYFkf1O1ih57CiH4CUCMf26J6j8ioSotk3BnvqKrc5j2GbNKj+2RiM9yMMvAJ2LPQ8mb33EmJZfgJ67/4O768H0C8/NH0sRZXPYsa+wYj+D9CxOXchHHqers6/rNZaEou8Q1vTfkCM1Y/LiH1Oe/NhlFW9hm4bj24bh9t3Wr85hdBwufbB5donPqqUtLdfQijYPw8YaOh6FZbZTDZBN1PF5QQtnXeQ6T2Rsotg+BWKPEek3J84X0aTAAngsNUypvRSxpReWtBxfY5N8Tk27bd9eecTfNvyFwR6sshMU3AeTcG5bFx+OeuXnFpQO1ZH1xxMLvkFk0t+weurbueL9lf6tRFoODQ3O1UeN6S2rAuoIjRwyCGH8OabbxZkrBkzZnDeeecRifQs4ITDYd555x3eeecdHnroIebMmZNR+AuHwxx99NHMmTOnz/Zly5axbNkynnjiCa699lquvjp9qgOAjz/+mMMOOyz5fJbgiy++4IsvvuD+++/n3//+N9tvv/0AjrSHvfbaK+X2iRMn8s477/Ddd9/x1VdfYRgGG2+8Mdtss82g5uuN3+/ntttuA+Css87K6jS1atUq7rvvPgAuu+yyQXu7rzM5IJcvX84JJ5xAKBRi7Nix3H777dx7771AfCXqjTfeYNasWVx55ZXJMMjdd9+duXPn8t///ndQc8+ZM4djjjkmbbGAyspKbrnlluTfs2bNStlOsWagKmAr8qG3AKlQZCMRfj127FglWK8jSCuIbD0RzJV5921oKcOydDyuMKVFIfJZdxaug9BK0nm0rWaj2YgV+QAZ/QzZu7hBxlxsyUaQh1dlrliRD4m2nkOkfjsiDdtjdFyDsG+Fvexu7OXTsfnOGNIKxekQti1ADFV+aBdoA7/3CAQCtLe3A/l7WEtzJbmcX3bPSSDy8faPnz/O4mvQ8gj9Hyy6fTOc3hNweo8D4SLovzVNSxOIkrZ4jvQTDPwzr7mFEJSW3kJx8R/QtMpe2714fWdTXHw56QrbJO3XxqBrmc+zSPQHQpE309ieHImucOoq24ZhJO9hRkMBmkhsKW1dz9MenEPMzHfBZeD4I9/ybctfAVarcB3//YfWG+mIfJGyr5QWjcH5fNl8K58338Ry/yuYMgqAYYVoCH5CffAjwmZ7zvbsN+YCdqw4FttqeW2rXRtx3Pq3UepQzyeKwdPbmausrIz9998fn8+X9zivvfYaZ511FpFIhJqaGu644w4+/PBDXnnlFY488kgA5s+fz5FHHollpV90Of3005Pi4z777MPzzz/PRx99xIwZM9hwww2xLItrrrmG+++/P+0YdXV1HHLIIaxatQqbzcbll1/O22+/zdtvv83ll1+OzWZj5cqVHHzwwckI16Fi00035cgjj+SYY44pqPgIcae8a6+9lscffzwnvWLMmDE8/vjj/OlPf+LFFwdfDG6d8YC84447CAaDFBUV8eGHHzJ27Fi++qon5GCffeKrjkceeSRXX301p59+Ok8//TQzZsxIVh0aSvbee+/k7z/+OLSeAIqhIxqNJpNxKwFSkQtKsFbkg6qYvg4SngPWwIqLJMOvxwhw7Q+xD8FqI73gIMC2BXrpLQhb/2qsqyPNVZidf4HIXJLeWFoVmvc3CM8JCOEE594QeZv03nEGwnlgfgeWBSNwN6b/JpI59SRY4TlY4RewlVyP7jmmoPPlijSbiXZcBrJxiGYII2NfIhwDC+1MhF9XVVXhcrny6iu0crLnLxQ4iy/BVfJ7ol1PEun8Y/Zx9fVwlfwJu+vnedmTCiO2kEjgYczY5wjhxO6aisNzPFqW6teR4LMMPAGbSTg4E1/JdXl5pwqh4Sv6DV7fmRjGIpAGNvtGCOHGkmHaOv6KZbWT2gtSUFx0BkKk9zORMsrKllw84WR3LsX+rFy5EtM08Xq9lJWV5XJYQ0LMqGd566X4w2/12qpT5j2K8WV/QdOGNjflcv+TCLTVxMceBDo/dTzOz6r7fi6DsVW8X38hndFFybySP/IE9qYSil3bsTI4P+nFKtBZv+gAtqu8BIdelNEeTejsWX0aO1Ucy09dnxGTESqdE6l2bViQ41WgckACxx9/PGeddRY77rgjG220EQDrr79+shBrLhiGwfnnn49lWRQXF/Pee++x4YY95+mBBx7Ieeedx1133cXbb7/NY489xkkn9U8J8dZbbyVT2B1yyCE899xzScevHXbYgUMPPZTtttuOn376icsvv5yjjjqK0tLSfuP8/ve/T0YyPvHEExx99NHJfXvssQfbb789xxxzDA0NDVx99dU88MADOR/raGL27NkIITjmmNzuhYQQ/OpXv+Ivf/kLM2fOzLlfOtYZD8i5c+cihOA3v/lN1kIPbrebxx57jG222YannnqKZ599dsjti0Z7vtw1bZ15W9Y6EsVEvF7vgFaBFOsWpmkmv+iUoKTIhYS3iSpYtG4gzWZk14MD7p8UICu/RUZeB6udzE8xEr3kzzmKj82YLUdB5A36iCBWE5b/T1iBfwCge8/tnjOVJ6QO9q0RjtzyMuWCFf24W3wE+nkjSYyOq7CGOOQ7FdLqItLyK6zIO0M4i4YZfnXAvRMC5EByTNndh5LNk0537oWmlSGECz1HkdRZdH7e4qO0ApjGMqTVk+s97L+LQNM0YqGZWMY3mLHPCPtvprNxD4zogozjmWYdA31kklJiyRDtbRfR2nI6bW2XEfDPIByei2Vlf1AXwo7dvhl2x88QIi6kacJFdcWDcYG/T3X2uI1u134U+87KOG4g9ApGjl7VTvvPUm7vHX6dziNfyijtXU+zpOEQvqvbikWr9qK585+YZltOc2fDtDpY1PBL/OF3V99DW9fM7mI0Ay18lBtt4U/Sio8Q94psD3/S1zorwlsrT6cz+mOyjcTAkuC3gtQF3+0TQi8xWeJ/hbl15xAzuzCsSNZ0Yk7dy8bFuzGl5OdKfFQUnLPOOovjjz8+KT4OhOeee45FixYBcNVVV/URHxPcdNNNyQWOm266qd9+gBtvvBEAXde56667+kWdVlZWcsMN8YiOtrY2ZsyY0W+MhoYGHnvsMQAOOOCAPuJjgqOPPpoDDjgAgEceeST5DJcvpmkmPSs7Ojqytm9vb0+2LwTffvstALvuumvOfXbZZRcAvv7660HPv84oXYlEqL1f6N5flqsXmdE0jQsvvDBZCn2oeeutnlW7yZMHliBZMfIobzZFPjQ3N2OaJk6nc0S9BxRrBoZhJK8xSoBcu5FSYvlvRzbtAebAxDKJZGVTPE/o2Oom4gJcuvCl+P2Q8JyOSCM2rI7VdTdYzaTzepNd/0IaKxCObdFK/wki4YVkIyma2LdGL7uvoOkEzK6H6SvKrI6G1TX0kS2rY4ZmIs3FDLwKdC5YWFZuBRZTMRgBUrONx+45Jd1eQMNV9NvkFt2+FULLlshfx+bMXXw0jcV0tZ5HR/0W+Bt3p6P+ZwRazyQSeJiw//pEq149LJBddLWchLTSFwfStHIG4n4kZVxCMoFQ6HnC4VcIBR+ns/NqWltOor5+Kzo7/tY3bUGOuJw7MrZmHkW+U9G0KoTw4LBvRWXZP6iueCBrZfau8Dwyf04SaBR7U3tKZsv/aFkhljUex8rWSwhFP8O0mokai2jsuIEfG/YnauSX0zYVzf5HiZorSP25sghE3l3NM7LwaDm8jqt7v37dejchYxWrn1exbk/IVBiWpD68hEd/PIBHFu3Lo4um8nHTXcSsoa0Or1AMFc8//3zy91NOOSVlG4/Hk/S4W7hwIT/88EOf/YFAgDfeiKeJ2H///dN+fx155JHJYp+zZ8/ut/+FF17ANOPXkVNPTZ+zNWGnaZq88MILadtlYu7cuey999788pf/z955x0lSlH/4qeqevLN5L5IRyYgoKFFF4IcgGSQLCooICAYUIyoqKGBCMaBEBTyiZBAJEiRnyTlc2hwmd9f7+6NnZmd2J+7O7h3cPHyO3e2urqru6e6p+tYb9sPv91ct7/f72W+//fjEJz7BnXfeOaU2C8l919dj/JLTNhrher7KCJCxmDewKPySDIfHYw6VUp833nhjAJ588skZ7ZsxhjPOOCP/93TNWpusOJoJaJrUQ2HG9GY8vybVWL58OcYYQqFQSdeRRiBmABn7M6Z3X0zvpzCD30CqWAc1mQFif4TYuUxZrNLziGfWY2DYG2wv6KmSCMZaE936M3T0lIrFRBzEeRmTeR5JXFGlfxpJeoN8HdwFq+d+dOtPUOGDUZHPY3Uuwuq8HKUbu/hi0g9X6ZeLKcpwPPOIpHFKJhRpPKpqzM3SGGPyIR6mmlAk2PYD/C1fBnLiV1bYtuYT7vo7lv8D4/1UNoGWr1SoTeELH4y2empq2828wGjv7mSSNzL++Ruc5L9IjHyf8lMeg8gQ6cQ1ZesOhPdhKs9i8RElxH9JMDb2e4YGv1Z33QA+e0262k9jjQVPsebCV1gw9yZaIp9B1ZThuLbzmdtxNnaJTNoiUlWAXD58OvH8s1Z4/gbHXc6bvZ/FmERN/SjHQOxyKifjsRgYu2JabVSjO7wDFafUYhHxb8Rz/b/mmb5f8OrwZbw0fPGkYkZAytSTNhoHm0Jx0pEETw5cysUv78VFL+/JJS/vx3+Wns1oZknJOpo0jlwSmtn+917jnns8j4D111+/ovFOYcKWe+8ttnZ+6KGH8slryiV2AU/Ey2XBfuihh8hkMiX7Uq2eSn2plUWLFgGeRWUtCV3C4TAHHnggIsI//jH9sUTO2zYer33xIld2otHeVFhlYkC2tbUxMDBAMpnMbyvMpPTKK69Myqw0MuKtIvf1zWwg41/96lc89JD3Bb3PPvvUlFUplUoVZYrK9bXJiqVpAdmkHgoFyCZNqlEY/3EmBGvJPIv0Hw6Mjm90X0FS1yHhz6Ki320K5bOAmBgS++PUK9ALoetaljz2aQA6WkcIBUvFcLMguDdW9CTQlRdBRFwk9ldM/Pys1WNtiDu+Uq50Cyp8UM3HTp0a1tZrEmimj5t+DGfs95jUncxWAC9lTW0BdPny5WQyGQKBAN3dkwWnmtpWFsHWUwi0fIlM8g6QMbS9NpZ/25LxCH2RIzGmj/TY7/A+t9w96GAH9yDY9sOa244PfQskwWRhLfd3peuvcVL3EYgcVnKvba9LIHQIqcRlVeoZR0RqLUkicSWR9FH4CwTamSbo+wCjTLYCKsS2VqM1MtkNEWBgYIB4PI5lWSWtaFwzxmDs75QXB13Szou88M4mdESPYE7ryVOK1ei4vVVKuGTcmRXkVosezBvDlyAlMqGLQBrF27E78nEeHXEp9Z4yZd5drlGYElaWjigEBZLCcb13/LND1/H00A0sCH+Y7uB6rBfdgXmhpmddk5WPsbGxvCVeNe/Pwv3PPfdc0b7Cv2up57bbbsNxHF566SU22mijSfW0tbVVnJfNnz+f1tZWRkZGJvWlVh599FGUUuy4Y+0W/p/4xCc499xz85rRdJg/fz4vvfQSjzzySM1u2I884oWRaMScdZWxgFx//fUBePXVV/PbotEoa665JgC33XbbpGNuv/12gBmzNAHP9fqUUzyLgzlz5vCHP/yhpuNOP/102tra8v+mulrdpHGISD4GZNMCskkt5ATrZvzHJrUwkxnTRVLIwJEUiY+FxC9G4pc2vN0mJUjfmxVS6kPwBA8jQ5jej7G411tUXTCnnPWjQik/yqosaIsIZvhbmLFf1CU+ek3MfmgJHdyRai7YOlDeuqFRuIlbSPcfgEndzWxmD1BW55SOy00EFy5cmL8fRFzEjNYdQ0/pdvzhffFHPosd2L5sMhSlFMHWk2mZcy+B6FfwhfbF33I0kZ5bCXf+DqWqu6YBuJkXcTOPMnX39uoZJaLtpxOMHM24dWdlKtnkTcYmPksWsjmikQNQKkilLPWd0RPK7stZPy5YsADbnizopzLPI5KctH0iQpKB0fN4o/cgTA3lJ2Jb1TLKW/ismQ1ZEvItZPO556CVj8KptYgmjZ23aszFeRQU9bwTnBLTdbfIWtL7DDOiSWHjoHkz/jiPDSziH28cz1VvfIOUWz7EQJMpICvo33uIt99+Ox/HtFrYj0KdI/fuKfV3I+qpJQRJrp6JddRK7vt27bXXrvmYtdZaC2iMC/T222+PiHDuuedOsgQtRSaT4dxzz0UpxXbbbTft9lcZATIXOPOBBx4o2v7pT38aEeHMM8/kjjvuyG+/8sor+fWvf41Sim233XZG+vS///2PffbZB8dxCAQCLFq0qGbh6tvf/jbDw8P5f1N9AJo0jqGhIdLpNJZlTdl6oMmqg4g0LWab1MV0E9CI8zKSvBlJ3YVIAuOOYsZ+hxn+OTJ6HshQ5QpGfzmldpvUiSkjAldA8v8ZkFFgjCW93vfQ/LLu1y7Kfn/5Ok0MyTyDxP+BJK+tu0/gokN7TuG46WGFP0vFLN/4sMK1ZP+dOmJGSQ9/LduPmU2AUYzGCuw0pSNzk5qFCxdi3GUkh3/I6NJNGF26MaNLNiAx9C2M80YjO5tH26sTiH6VUMdZBFu/g+XbsGJ513kTJ/UQrvNa9u/pJxWy/JW9j5Syibb9kK65jxFt/xWR6Hdo3DTKxbhTy3Q/VSzdxtyOX5GLzzmO93tLaG9aI4eWPT43gS5vAFHPtTEk0o8yNHZ5Hcd4dLUcXKUtl86W0lacjaQ7vAPbrvYv1mk/lvbAh2gLbEHE/8G6xEZVJlmXTNgmkrOWHC+fEY1bIEga8bZlRPNa/Cn+/tpxmBlOxtNkdhgZGSn6V+gR+W5idHR8rFMtcWskEsn/PjHLdqPrqSWJbK6eejJ+F5JzZ66WSKqQXNlGeL3mYly+9NJLHHLIIRVdsePxOAcffDAvvvhi0bHTYZURIHfbbTdEhKuvvjofYBTg5JNPJhwOMzY2xs4770xPTw+tra0ceOCBJBIJtNacfPLJDe/Pa6+9xi677MLg4CCWZXHZZZdVjDcwkUAgQGtra9G/JiuWnJjU09PTzGTepCqDg4NNwbpJzTiOM+WM6eK8gun7DNK3GzJ0IjL4RWTZB6D3QzD2W0j8FeK/LT6mxH8wislO+JvMIPaadR9Sytlz8fKsBWRPKatFBfhRob0n12XGcEd+hLv8I7j9e2NGv1d3f0CjAp9C+TaqXrTBaN/62O2/xrOCnJgh2I+v888oa2YXfdzEdSBJZtdkRWGFDkZVtQgrTU5QWjA/SKx3N9Kxi0ByVlMpMvFFjPXuhpt5oUH9rR8n/QSjvfsyunxbxvr3Y3T5Doz07tYAYTSAP7x/TSW11Ukw/BnC0ePwBz9FOWvb+mJxWugpus5PBRGXvuEzWDZwIsXJqRR+ez3mdpzDvM7flbVcherWQkHfhmgVratfg2MX1VUeoKvlMPz2mpT+HDTR4MeIBmfe4hkgaM9h3Y7j2XLB31i/6/sMpJ8uWU6VeS/oukzdFDnxUYS8+CiiyIjCnXA9BjJL+N2L+xPLDNR4Nk1WVlZfffUiL8jTTz+9+kErIYVh8aolYgkEAvnfE4liD5FG11NLUphcPRPrqJWeHi+2cS4bdS3kyk4MGTgVttlmGw466KC8NrbBBhtw2mmncffdd/Piiy/y0ksvcffdd3Paaaex4YYbcs0116CUYv/9969LryrHKhMD8uMf/zinnnoqjuPwzjvvsMYaawCwxhprcMUVV3DooYcyNDREf/+4pUAgEOAPf/hDPmBpo1i8eDE77bQTixcvRinF+eefzz777NPQNprMPjlxoGnN1qQWcoL13LlzsaxaMlE2WZXJJaAJBoN1hQUR5y2kb3+gNvernJBVLnqZyrwEdu0uI03qR+wt8CbTtVmrlPqsRmIhxuJhlDLM7R6csNcCBN1+JkoXCwQiCdyBQ8F5vub2x9F4QoZGhQ5At/6gzuMbhxX6NNq3OW7879mEMxod2A4rPHWBrh6M8zzedZ5+sPbJ5CyqFLnPElys0H742qZ2zZPJZD7eeVf0T4gZoGQsRYmTGDyRSM/Nsx4P1kk/xljfAUy8pibzP5KZ/4GKFAim9RFoORGt2+s+rqX1VAbTD5W4XtqTh1QrIsNUd8h2CIdn3kovR+/QDxiOXchkoUuRcd8k4N+koviYTCbzIYfKWUBqHaIz+jn6Rs4p0U4phPQUhGRLt/K+uVfx9sC3GEncnm9L4aMzchALOn9Q8VxmileHL6bceWsEU/QceygFPnHITJieK6TICnJirU6BGOmiYIJrdo60ifO317/CMev9re7zaTKBFeESnW3vrbfeKjI8KhTVJuI4Dj5fbWEjKnHBBReUzVI9VYLBYP73dLpUnOpxCq08JyZtaWQ98Xi8ah2F9dSSQKYUW265JW+99RYXX3wxhx1WOvbwRC688EKUUmyxxRZTanMi559/Pn19fdx+++288847/PCHPyxZLmd5ufPOO3PRRfUvEpVilREglVKceuqpJfd96lOf4uWXX+aKK67gf//7H47jsN566/GZz3yGhQsXNrQffX197LzzzvlYlOeccw6f/exnG9pGkxVDToCcM2fmJzdN3v00E9A0qYdC9+t6Jv4y+htqFR+hvPCY26fM8prralIfYkYgfinE/0bt4p+VFV6GKZwNLVnuWVX3dAzh9xUKNgr822O1fAlVwuVU4n8H51nqnlnp+ejI0aCCqMDHp5wIpZEoezXs1m/NaBsigkk/iDgveLESzTIwgxjnVWq/hgr0Gmj/xpjkTVXK2tiRI9GhPTGp/yLu2yjdgRXaE22vO+XzyLlfd7RHCei7KvTdxTjPYjJPFWW0ng3iw9/FEx8ninmGcTF2ali+9wEgJkEm8xhIBtu3EbqKWG3ZC+nouYnYyJmkEtcAXiwtn39rItFvICj6+g8ESZfodw5FMLgbPt8Hp9z/ekg7rzMcu6DMXoNImoGRs5nf9eeydeTul/b29oruij2tXyOVeYnRxM019U3r+iwmc/isHtbuOZ+08zbx9FMoLCKBrbCt2Y9Bm2Np7K6y+5QCLaZE0hmNQujyb0jSDBNzvO99n4J0wSOZtXss+M376WXRrjw+GHV6eSv2JKtHZvf5bdI43iuej9Ho+PNezZU5Fhsfx0585zSynng8XpNbda6eWty1S7H//vtz9dVX8+9//5uzzz6br3/96xXLn3322dxxxx0opTjggMYsVgWDQW699VZ++9vfctZZZ5WNLbn66qtz8sknc9xxxzVs4XGVESCr0dnZyTHHHDOjbQwPD/N///d/PPvsswCcccYZHHfccTPaZpPZIydANhPQNKmFpsVsk3qYSgIakTSkbhj/O+9KPY7K/pfbXw2TvAldJlNsk6ljnKUwcACY5dQl/lkLIbAjxM8v2pxLQDO/IAGNbv8rKvBRlCpvLWHil9bXvlczOnwwOnJEnce9uzHpp0gPnYi4r5fYm7MGrQUB8waYhYxbN5bDxY5+G6U0lm/TOntcntzEY/78QJX2s73IPDerAqSbeQ6TeaZCCQEZwRfal0zi2uy2nAVq9fPR9rrERn5BIvYXJG9FaREIfpqWtp+gKyT2sawFtHb8Cmn7Ca5ZhlZtaGvcRW5Oz22Mjv2RRPxKYKJljY9w5HDa2n4waxalo/FrqGxh7TKWuBljYmgdKVmievxHD6V8rNb1Z8aSd9E7fBbJzJMVSlu0Rfar2v9K+O3V8NvVE0g0GhFhJP00KaeXgN1Dq39TDKUTO3ju0qpEXEcFuo20xBhIv0ROXLQIs07bHrw59gBjzmLAEzAn39Y5K8nq99GTgzc2BchposT7N9tt1ott21PO1FzITCQ/LAzfkHunlKMw18XE987Eej784fLxfKvVs2zZsqp9KaxnqkmADzzwQH7+85/z5JNP8s1vfpP777+fk046iY9+9KN5i1XHcfjvf//Lr371K/75z3+ilGKTTTap2WKyFpRSnHjiiXzlK1/hiSee4PHHH897Q3R3d7PFFlvwgQ98oOHfT00BcpaIx+PsvvvuPPbYYwB897vf5VvfmtmV+SazRzqdZnDQc3NrCpBNaqGZgKZJPUwpA7YZISeClBIfK20vS+YhxF22Uli4vVeQ1H9h8BigvgywEv4yYt6eJD4CLM1lwM4loFEtqMBWZcVHkTRIAtx6sytaoNtR4QPrPO7djXFeITVwcDbOY8kSddfpCV/VBMjaBIZ6ySegWVCbxZiXPXn2MM6bNZWz/VsTav026cS1GHcJWvd4vzsvU1pws7B8HyE+9tusBWPhtXdJJW/AyTxDe88NaF3Z4kjpCLZeZ3KffO+jo+Ms2tvPBFwc5xUymWdQyk8gsB1az66Vnuv2Uv0ecnHNYFUBspZssUppoqEdaQluz6vLPkUq8yKTPwsLrSJ0tRxVtb6Vjd743bzQ/zMSBfdoyF6TsD2fscwbTHyex8XHApdqgTQWYsbwHK7d/Pa4pHl26GomfmY2Kh+MwEZIl3k3FOa4yGkIjlTPetvkvcMGG2ywortQkpaWFlZffXXeeuutqrEQC/dvuGFxkrKNNtqoZLlK9di2zfve975J9Tz66KMMDw+zdOnSsvOzJUuW5BPBTOxLrSiluOaaa9h2221ZsmQJ1157Lddeey0+n4/Ozk6UUvT39+czVIsICxYsyAuRjUYpxQc/+EE++MHZscRvZsqYBdLpNPvssw/33XcfACeeeCI/+clPVnCvmjSSXCyclpaWogxbTZqUIhaL5bOtNV32m1TDdd2pJaDJTpjrFhmrYZpB7BuFpB5EBj9HPeKjIIiKIqlbIPnPyfsFluQsIHv6AYUKH4ZSk2MVSeY53METcJdtirv8Q9Tm+q3Ir19ba2B1XobS0w+KXi8iBjdxHem+/Ukt3ZjU0i3IDH8Xk3l5xtvODJ/mCbZTEBrLoe1NqtRnof1bN3zyISJ5AXK1NT4CVROH2FiBHRrah2qoGkU6pdvR1jyCLV8i3PYjgtHjiXT83gtTMMlF20Lpdnwth5FKXE1p4dfFdV8jGas/7lUm/QyDA19l6ZIPsHTJJgwOHE06/TA+3/qEw/sRCu0x6+IjgG3Np/p968PSpa0+RaQuATKHUj7W7LmccD70g0XuPeKzFrDWnCvw2Y0NezVdMu4Q8cxrOG7prLO98Tt5YtmxReIjQDzzJmOZ15h4T0neRXqC9SMKQTNJlBSroAbJb3dEF0VC1UoAgyr4XF2jSBmLtPiy/2wc0YjAauHNar4GTcogK+jfe4ztttsOgBdeeCFvmFGKu+++O//7tttuW7Rvyy23zCeOKSw3kXQ6zQMPPDDpmIl9qVZPpb7Uw1prrcXjjz/OXnvtBXjv1nQ6zdKlS1myZAnpdDoff3HfffflscceY6211ppyeysT7zkLyDffHP8SyCWambh9KhTWVS8HH3wwt912GwA77rgjRx11FM88U96VxO/38/73v3/K7TWZfXICZFNMalILOTGps7OzYvDoJk3Aix3sui6BQICOjtonrEr5EcLUEwOyhlpBN99zjUBEkNGfUM+sIi8myzC4wyXLDI+2kEgFsLRLT+cQBHZBt5w4qZxJPYAZ/Dye6Fh7whkV3B2stVH+D6P828x6MhLwxEdn6GuY5HWMuzsnMPFFmPiV+DrPQ8+QSJYe/R0mXX5yMjUC2NETcJM3ZeN5lhKIXOzIFxrcrhceKBaLobVmwYI1cRNfIjV6ZpnSCl/4sIouyTOB5f8QSs9DTPkJKqoFX4lsx5ZvfaI9N5Ec/T2ZxNVAClQIf+gzBKPHERs9m8ouyYZE/BLC0RNq7m88fiVDgyfhCUpevcnkbSSTNxNt/TbROupqNNHwfvSP/LxCCYtoeG+0Dpfc29/fTzKZxLbtuj1+bKubteZeTSL9NLHkXYg4hPybEwl+bFYSxaScJSQyL6JVgJbAB9FlLMLH0s/z+uCv6U/cifd+1nSHd2Kt9pOI+D2rqbQ7zFPLv04pkTFdJh6pKWN56mWwLk5IMy5KFtftlLAdEgELQSsfrgiO0biTpvgKVzQGzWYdu5bsR5Mms83ee+/NZZddBnhJVk455ZRJZeLxOIsWLQI8K8WJGkk0GuWTn/wkN998M7fffjtvv/12ycWRq6++Om+5WCr575577smxxx6LMYYLLriAAw8s7dlx4YUXAqC1Zs8996z9ZEswZ84crrnmGl544QVuuummki7Qu+++O+utt9602lnZeM8JkGuv7WXnVErhOM6k7VNhYl31cvXVV+d/v+OOO9hss8orT2uuuSavv/76lNtrMvs0E9A0qYem+3WTeihMWFRN7BFxIHE1ErsE3BfJSVYNw9oYZc2+tdt7DZEMEv8bOC/UfkyNn2Uu/uOcrkH8nb9DBXeedN+IZDDDJ1E6qUc5LLA3QredjVJTT/jRCEz88qz4CMX9dwFDZvDL+Of8d1KW7+niJu/GHTu7oXUC2JGj0NZcAl0Xkeo/DGSUcWHDE8fs6LexSghs0yVn/Th37lxs28ZqOQ7j9pKJX0ix1aCLHdyTYNv3Gta2iOBmHsfN/A+lgtiBj6OtnknllLIItX6b+NBkIT1HMPr1kla+AJa9JpGOXyDtP8MYT+DVugWlQrjO21QT4I27rOZzcpzXGBr8KpOfK6+N0ZHT8fu3JBD4aM11NhKfvYDO6FcYGP11ib0WWrXQ1fq1ssfnYp8tWLAAy5raeyDk35SQv3ExTKuRdpby2sD3GUr8m9xzZelWFrR+ifmtxxSJnyOpJ3ly6WEYKYwfauiL/5vBxL1sPv8yQvbaPLT4QIwkJrVlSsR3zJHLzz0Rt8S2UlmyxwXMbNzmrCDp5kVJBzEat2xCJoUATw3+mw93fbpMmSZNZo999tmHddddl1deeYXTTz+dAw44gHXXLU6odvLJJ+fDnJ188skl6/nGN77BzTffjOM4HHfccVx99dVF76e+vr586Lv29naOPvroSXXMmzePQw89lEsuuYRbb72VK6+8kv3337+ozBVXXMGtt94KwOGHH96wedz666/P+uuv35C63g285wRIkdKD83LbmzRpBDkLyGb8xya10ExY1KQeqsV/FDOAjJ3nZVBm8oSooVhdmLFzEEmg7PVQwV3LTvqblEbcXs/t2nmxvuOs9cB9mWqCYaH7tfJvVlK0ltSdYPpqaNXCmwQb8G+N1f7rFS4+ArixCygfL1FAEpjENViRzza0XSf2F+pLMFMLIeyoJ/ho36YE59yFE78CN/kvIIn2bY4dPhTtm5k4Xvn4jws991elNKH2H+OPfJZM4grEXYrSXfjC+2L5NmlYu27mOWKDJ2CKRHgLf/hgQm0/nBSv1B/eF5EkiZEfg8QYt1oMEGz9BoFI5fiBxgwSH/0dyfjfERkFNP7gLqBsKltAeq7dtRKLXVylhEVs7C8rTIAE6Gw9Ga3bGRj9NcYM5beH/Fsxp+Pn+Ow1yx5br/t1KvMSQ7ErcNxl2NYc2iL7E/TN3kQ74/bxv6X7knaLE3y5ZoS3hn5B2lnOWl2nAt5c8YW+b2MkQykB2ZUkL/b9gJ6WfUg4b5RszylhzZijlDDpTU8nu2W7MnmbmVDOZbLY6OAr2a9C7u+7silAThMlgpplbWG226vGyy+/zL333lu0LZdBemxsLG8pmGPXXXedJNj5fD5++9vfssceezAyMsK2227L9773PbbaaisGBwc577zzuOqqqwDPRfrwww8v2Zcdd9yRgw46iMsvv5zrrruOnXfemZNOOokFCxbw9NNP89Of/jTvDXvGGWeU9Sb66U9/yi233EJvby8HH3wwjzzyCJ/+tPes3HDDDZx9trcA2dPT0wynNw3ecwLkBRdcUNf22aApfr63EZGmoNSkLpoWkE0g+92Qvh9JXAnuYtA9qNDeEPhEkchTSoAUSUHyNiT9BCQWAanZ6XT6bkz6XjxLCgdGfoRuOwsd3Gl22n+XIyLI4LHgvFLfcUjWorU6OQFyXvco6A4k8yIm9hckdauXNMVeF2WthjcErOzdoUIHoayFqMDHULMoGlRCJIG41a6fxmSeLGsHNFVM+kEaKz5qdGCHoudd6Q58LV/E1/LFBrZTnokCpIjBTd+Hk7oXxGAHP4Ud3AmlGjdlcJ03GO3bDyQ+cQ/p+KWIGSDS+adJxwUih+AP7UMmeQvGXYq2uvEFd61q6WrcAQb79sS4bzIuNBrSyX/l2y2PRTB8UI1nBunUg1Xqc0mnH6hYh0iaWOJGxmL/wHWXYlsLaIkcQji0a0M+B6UUHdEv0t5yJInUQxiJ4bfXw++bnERnIvl4oVUESBGXJYPfYyh2MeMLGdA/ei7t4UOY33nGrCxmLBn5c1Z8LP2ZLBu7kLmthxLyvY/R1JPEK8aQNYyknmQ0Uz4UQK2ZqCuVH48VWbxtYozIie7YRiaLlKUYdfoQMbPi9t7kvcu9997L5z73uZL7+vv7J+278847S857dtttN/74xz9y/PHHs2zZMk44YXKIiq222oprrrmmotX1+eefz8jICDfddBN33nknd955Z9F+rTXf//73OeaYY8rWsfrqq3P99dez9957s3TpUn7+85/z858Xh6yYN28e1157bV0xcJsU854TII844oi6tjdpMl1isRiJRAKlFN3d3Su6O01WchzHycf3aArW7w7EfQeJXwqJW7OukRZgQLdD8FMQ3AtltYJqr3lAL5JGhk6E1L8Zt75RSOo2oAUJ7YGKfBasdfILHLmBmyT/hQyfku1LlXZmJGp5wUROYpihL6M6L0f5t5iBtt5jZB4F56m6DqkniZAILO3z4vMtWH0LJP0gZvAYPNEs+7k5LyE1Wl/qyGdR9rrVC84qtU6aZ0LcqOd5sgAflRMMGezIihufGmPyCxwLFy7EOG8SH/gcxnmJ/BQh9ieUnk+48y9YDXKbTY2dmxUfS4lChkzyJpz0k9j+D0zaq3QIf3hy/K5KjI38bIL4mMN773rnapgsLlso3UG4inXlxGOmU8aYUZb2HkQ68xg5a9uM8zKJ1J0E/B9lbvffy8ZnrBel/ISD21UvmCWVSuU9fqpNvntHzs6KjzDxug/FL0VIsbDrt3X1t15EhOWj/5jUfjEWvWNXsEbHt4k7r1Wpz3OXNmWsx80EkbB4X+3CZCkRUfL/z7pfTyhjhAJX7HER02TdrhWgczWr+kTSJiVYEUlh3sP2TF/4whfYeuut+e1vf8u///1vFi9eTCQSYcMNN+TQQw/l6KOPxrYry1ahUIgbb7yRSy+9lAsvvJAnn3ySoaEh5s6dy/bbb8/xxx/P1ltvXbUvH/nIR3j66af5zW9+w7XXXpsPi7f22muz1157cdJJJ9HVVVsoopUxN8nKwHtOgGzSZLYpTCji81V3fWiyatPX14cxhmAwSGtr64ruznsKEQdSdyGJ60AGwFodFdoffFuglMI4yyB1CyRvAedZwAb/xyCwLcr0AQr8W4HvA3m3VUk/hAwcDaSZNDl1ByD2e4j93hsX6i4IHwqRo1EqWLmvo2dD6o5cRbmt2Z9jkLgcSVzOQOabpNNpbNumu7vb68/QCZP7MrH+Rsd+rNASaNyx32N3/nUW2nt3I6m7qebuOemYOj7HwZEoqbQfy3KZs/rnMEN741k5FtZRS30KrDXAqm4RNdsoFUD5PoxkHqP8c+DOSBIa7f8wJv1QhXZzBLBC+2C3HIMzdj5u4pIy9W2DFag+IZopent7yWQy+P1+OjuCxPr3RNycdde4dayYZcT6D6Zlzu1oa3qW+yIu6fjVVH4GbNKJa0oKkPVizCipxFUV2hPAwfZthZN5mMLnw/ZtSmvH79BW7fG9A8GPkck8Tvl7xCIQ+ETZ4/sGv0k682Su99mfXt9T6YcYGPoB3Z1n1dyfRrJ48WJEhNbWVqLR8lanxsToH/1zxbqG41fRHj6ISGibRndzvB+SxJXSGazHEVLOYgBsFalcH2AqLICUShAD48JlKdfsUtsnvqFlgrg4sczE/ePWkeN1C4KLhULotueukORhTd5bHHnkkRx55JENq2+TTTbhz3+u/N6ohUMOOYRDDjlkWnV0d3dz2mmncdppp02rnpUxN8nKwCojQF58sbcKt/fee9c86R8bG8snkPnsZxsbR6jJe4dmBuwm9ZBzv547tzkAbCRiRpHBoyDzBOMCz6NI4irwb49IEjIPTz4wdQOkbiiwJjBgbwId54BqQwa/REnxsRSmHxn7HaTuhc4Ly4qQYsay8RorCUGegLj4zUuBHejpHIPkIkz82qw9Q4VuNNRFtBZcSP8HMWMo3TLLbb/LkAz1Zr2uh6W9nhX+3LnzsNwHMTLVDOiCbjl+pXhHiThevEoVzMfis1qOwRkslxHaAj0HHdyl4X2xI0dVcZ8NEJhzJ0p7CaNEUrip2ygXN9Kk78dN3Y0VaHxymVpYvNgTXhYsWICb+ifivlOmpAEZIx27iGDrt6bXqCSpbBXqtSc1xSitjmf5mK5SysYf2I7Wzt+RSd2LSBrbtzm+KVh8RiKHMTZ6LuW/N4SWltIWlY6zmHjiujLHARjG4ovoaPs21gpIBlar+3UsdT9SIkHLRJYO/YB1Q7c3pG+l0CqAUgEvZElZFL5sVveO0LZoFSqZXKaUCFiI5/5cRoDMtjP5GJWN4Vi8b2LJUscXjgMK92sM6aLp/YTENUC7v+k62qTJbNDMTVKaVUaAPPLII1FK8eEPf5iNNtqopmOWLVvGkUceida6KUA2KUtTgGxSD814oSBmBEwv6A6U7mxMncPfhMzT2b/c4p/pe2qpgbww5DyH9B8G4cOyyQ7qGSgYyDyOjF2AhPZAUneA+xZKR1HB3VD2+yDzOJViNhZaLy7LutPO63oLM3JFtoRClQxwP1tWj6XwEn9AU4CshPJtgtQhENfzearwMSyNbwA8xvz5ayCZB6glzqOHzfgzIOiWb6BD9bm5NhoxcdzYH3FjfwMZAkD5PojVchxW8JNI9Du4oz+jMIQBCOgufF0Xo5S/YX0xmf9hnJdRKowVORY39geKLVktwMbf+Re0NR6r1U3cCKZSBmWNM/bnFSZA5gSlBQsWkEn8lfKJfQAMmcQ/py9AqhCoaJUQEgptLZheO4XtVcWgVAjLWogVPnBazVnWPLq6LqS//0iKRUjP7bq949dlhc1kTda1GVLpRwiH/m9a/ZwKuQQ0uXih5Sgl4JUi5TxHxl2Gz5qZ8ZBSmp7IviwfW0R5C1iX7oj3rrN0hDXavsTrQ7+aVKqciJgjU0JIHG+htDBZyWKyXCKb3P5MQVxNSrhel++r4tX4UyTdOEGrMa78qyJKvH+z3WaTdxcrY26SlYFVRoCcDqu6St2kMk0Bskk9rMoCpDhvIKO/gtSt5CYDQhBIg2r14imqqBcX0QyCtRAVPhBCe4PzAhK7BDKPAbaXqCV8CMpeHXHeyMZSbBQumMWQvL4g7tJkyouABmJne/+yJQUFY79FBXZDhfaouSdL+7xMfXO7+4vaKNX+ihMfAdXixcRsUhEJ7Dwj9er2P6CDO7N0qeftsWDBAhCHWix3dcdF2azYIyh7DVRoX1SjxJ8pIpIgM3AoknmawnOQzJM4g0dD62nYLUejAx/HxC/FZJ4FFcQK/R86uCdKV3alrBWTeZb00MmI8+z4RhXCCh2AmBgm8wRK+bCCu2CFD0fbqxcfn76Hyi73BpP+LyLuCskuXmgBKTJC1cUWMzbtNpXSBMIHkYqdTyVRyB/6zLTbArCstbGsdXDd16gkrvpDjbOYDQR3YO68+4nH/k4yeRfg4g98hEjks9h2Jde72hYn6lnEaBQiUrMFZNC3Yc31Ok7vjAmQAPNbv0R/7AbckjFHNR2hnYkUuPp3hXZkIHE3I6nH8L5lLQSTjZ5YGiMgFcXE0tmvTd5NehxHNE6RuDgZBz1BZCzI7l2izom44vBO4kXWbdm8YrkmTZpMj2ZuktI0BcgK5PzrqwU9bbLqIiL09vYCTQGySXUKM6avahmwxXkV6T+gROKBrCueDEHisuKDnEFk5GkYO9cTBAsn8vE3kPgl0HEuuG9R2XKnzr5mrcA80aH6RE/lXZvKWSCOW1dK6hYEB13GJXNiHcv6cxaQgzX0eQUS3AelmjFwq6Gc5+v8pApCA5SlFR3cGRHJJxSZG70aSV5d5TgNvs3QgW0hsG1dvZpp3LHzJ4mPHt7fzsgP0cGd0b73odt+MCN9MM4rpPoPgInum5LATVyBHTmKQOfvK1ciLtXfS4L3Xmu8ACmSJJO4CTf9KCgLO7AdduCTKGXhOE7++2jhwoVoeT8m8xzlRUGNtt/XkH4FWo4lnbgeMb0l2/OHP4fla0xbSinC0a8zOnRcmRIaf/D/sBt0bjksax7R1q8Tbf16zccE/B+m+neZRWAFJPwaHh5mbGwMrTXz58+vWDbgWw+ftQYZt3qihYz7NiE2aVQ3JxH0rcFG8xbxct+JJDKFybcselo+w1qdp6KUwjVJnu/7Fn3xm1FY5MYbgqErtBPLEw+ClBbgPSGxtMWiKRP70SnxvIt4AqTHePlx52kQUZNExsL9tSaXEZl9Efs9RTMJTZMmU6aprFXghRdeALzkIk2alGJoaIhMJoNlWc37pElVYrEY8XgcpRQ9PT0rujuzioz8uIT4WPUo74dZnP278FgXMMjgcRA5tuCI4hFaoThY+FPV5MZcebQ30RKxNhHQQOo2xP8JVPpeKl2PsXiQWCKEUoY5ncUCpCAl+7+iUNaqdT9PBRGDxC6s6xjl3x5J/6dCCQsV3gcRw8DyW0kmk1japTu8iOriuUFHjqmrP7OBiODGL6Fy/8UTAVvKiUrTJzP666z4WPoZdWLnY4WPRNvlrcG07wO4yRsqtKJQ9vsb6i4uYnDTD5FJ3EIm/jcK4x9mYhd6Ga27L2PpUj/GGMLhMG1tbbjpQ3ESV1eo2eCPNCYckbZ6iPZcR3zoOzipf5N3cFVtBFqOJdBybOUK6iQY3htjlhEb+SnjYpACHHyBj9PaPrPZmGvFZ69BKPhJEsk7KX3fWYRDn8aeQYvBcuSsH+fOnVtTwsXu1q+zZPDEquXSzkvArtPtXkXC/g3YdP4tjKWfIJ5+Dq0CtIV2wF/wvfVC33foi98CgBRde0Nv/LZsrMbGMB5PcrL1Yzk0ks9oPTlD9nicx2oxonPMD65bc3+bNGnSWFb13CTvWQHyP/8pPWB/+OGH6eurHNg6lUrxyiuvcNZZZ6GUYvPNN5+BHjZ5L5Bzv+7u7kbr8gOHJk1g1c2YLs5bkL5/enWUEBY9N7QUpP49YcJQ/rjC7TkRb7pCXv3Whxp8G4N5B5yXy5bKxX/sbBvF56tHuJ19JHUHtHx5RXdjpUREkNGfQfxyKsX+nHQcAr7NwXnOS8Iy6T6zQIVQocNxh45n8SvPAx9jTtcgllVJvMsmK4h+Cx2cGZfwaSEJMMurF8u8NHNdMDFM8mYqL5go3MS16OjxZUtY4f3JjJ6F97mXto62I6UTkkyFTPJ2kkPfQ/KLNiVaNEuILf8kr798IBBiwYL5KKWwA1viCx9JJn4hk63wFHZgJ+w6wkdUQ1vzaem6AOMuwc08j1JBLP8WKBVoWBuFhFuOIRDai2R8EcZ9A6WiBEJ7Yfs2XymSLeXo7vgVS3v3IeO8kt2SE0wFn28DujrOWCH9ygmQ1eI/5gj5a3HDVlAhsUsjUUoRDXyQaOCDk/YtG7uB3njphYLxjNIV6q4Qr7FkndmjJlIqiY0pEitlksDoiiqwwARbGxxjqHZdFydfZj3fh2ruc5NimjEgm0yHVT03yXtWgPz4xz8+aUAhInz+85+vuQ4RQSnFMcesfBYCTVYOcu7Xq5o1W5OpscrGf6zBDasc5dyai6wUnSenVX+hADk7rsye+7XqXASJRUjsgpKJKpYNZOM/dg1M2qdUO8jIDPezDtzJfVyVEbcXEtd64nvqXyD91Q/KHVt4z8dKWWZlQxFY87Daz8Ukr4HUv1ja68Uxm9dd7bOwsbpvRtlr1dynWUX5KZc1ehwNDYrzWAqRIapba2ukilCqdBv+jt+THjyGcVdr71gwWKH9sEL7Tbe7AKQTt5Ac/GKNpV2WLHkLeD/dbXdh3F3Q1hyCbT/C8q1HauyPiPtW9hx68Ec+h7/lmIbHqTRmiEzyLsT0oa0FWLIZzJAA6Tpvk4z/A9d9E63bCYT2xufffEbamg6W1c38ObcwFv8Ho7FLcd3l2NZ8WiKH0BI+AK1XTOKQegXIgG89tGrHZBNIlUaIBLebfuemwWDifp7vK+8m79YgLOq8MGhNis+Zs1wspFSNRlSBJaPH5MzbKvv/bKAYUQV1ez+tfPuVRFHFg/03sF60KUA2afJu472Qm+Q9K0BC6Q+ong9ttdVW4zvf+Q577713A3vV5L1EM/7jzCBuH7ivgwqDvQFKza51qZgBiP8DSVzvZeq010WFD4bAztPqS7WERSICmYeR+CJwXvWSegT+D/wfQOl20HNXKkuNmlFTEwpmK6vzdN2Z6z/eQdnroHQLRD6PinwecV5GYheikv8CGUNIsSyfgKbQ/VqDbkd13wGxP0L8MsazyTYuDmbdmDcxQyej2n7aUHfSdyMS+wsyelbuL+r5TKrf8wr0fHTrj1CB7TGpO5DYHwBhaS5jelUBMgPWGjX3aaYRyWCSt2OSNyMyirbXQfk/gqQforwI6GAFZ85tU6l2KiePATCoGlxhreCOBLpvwIldgJu8FUij7I2wI0dgBXef8jvdOEtIjf0KJ3E3IoPk4+nWyLLebgDmdL1IvP8IIj03opTGHzkcX/hQxF0CuChrAUo1drogIqTGziE5+hsggyfIuqDChFq/TyByWEPbio/9ivjoLxm3ClMkYn/BH9iF1s5zUTVlyp55HOcdUpmnUNhEwvvR2lK70cRMYozJJyyqVYBUyk9X9Av0jpxF6XegRcj/AUIFCWBmm7H08zy17GjKvaO9RDGVMkp7KAUR3UnSZHAlUeSRoZQiYs0l5iyn8DtaYShMJOO5XxeLhhPFxVxbtrhksEsmxlEqv8RZocfC4sQrFfY3adJkZeO9lJvk3X8GZbjzzjvzv4sIO+64I0op/vrXv7L22uUz0CmlCAaDzJ8/n9VXX71suSZNYFxQalpANgZxlyIjP/UshnKruHo+Evkiyr854vYDaZSKgP9DMyJ0iPMyMnAYmKHxPqR7kfT94N8FCWwNsT+DWertU+0QPhTV8oWqk5hKFpAiBhn+HiSvpGjim77X2w9gr48E9wD3Hc9iTnehQnuD78NlJ7EiJmuB6IK1Wln3NnGXehZb7hLQnajQHih7nYrnUzO+TUHPLWnlV4nZS6zix5sEw1REPGWtAb6tvEzcMlT9eBVFTRBPlP0+VNtPoO0niDi4QyewrN+7n+bm4z9aoAJY7X/yxMvoN5CWE8F9C4XGpJ9ERmpPeNBwkv9ERKM6fr7i+rCCMfErYfQXUzq2NsFdwLyN0iEkeT0y7H3eIrC0rwuoQYDUnbO+qFMOcXvJDByOOC+Smza7qVxs1NzkfLLrufJthPLPXOIcpSPo4O6Y5I2UFyEFK7RPTfVp3/r4288Apu8+K+KQGPouzsSkXXWQydgMDLUDMLd7OcaJ46buxQ7uAHiZqpVdm9A0FVJjfyQ5embBluw1ljiJ4W+jVBh/eN+GtJWM/4346NnF7WRJp25ndOibtHac05C2porr9tE3+A0SydsYv9/9RCOH09n+/RlzS6+V5cuX4zgOgUCA7u7umo/rbj2eVOYFRhLXMT6uybqT26uzWtefZ6jH1XHcMR5ffBDglC1TzlV6Moq12g5jbmR3Xh3+G2+PXY9jYoTs+azVegBzw5/g5eFLWRy7k6Tbi1LgE0V6kthY3FY58dNSgoiLW2Ia71lS5npfvu92gxcVVjmaSWiazDLvpdwk79m3z8c+9rGS27faaquafe2bNKmEMSYfT3RVtIAUcb3Ye4mrwF3iWeeF94XATlPKhivucqR/fzD9FLnemSUw+qOi710BUG0Q+SIS/D9U5ilQFvi2RFm1D44nn5NBBr8EZri4D3kh8jbvX9FBgxD7HRK/BNFdnnBpzUeFPwOhfVAq6NVgzLjFbFcaE18EKJR/S88VMn5+VnyEshNe5wUYe4HCSbkkrgBsxL8NKvI5VDabrYggicsxsT96giV4wlf4EHTLCeP9codg9GdI8lqvP1iAQWK/R1QnWD3g2wwVPgTl27joWpG+B0k/4bnl+bf14tXJCIiDSNpLtmKGUPbqXqKY0R+Wv/YrbGRlQ+QLqOAuAKj4IiRxGbUny9HozktR1jxM4hrM8MnVy7edkb/+pVDKxkR+xcCwJ+TN7Y4DEbDXRoX2B3vtgrI+sNfxrGfdf1LadTUMxGs8n2mSugaT2AkdmnpsQTExSN0BZgCseRD4RH6xwTvPN0AyYK9e8TrONiZxE4x8b8rH1/4MWLiJayFxXX7LaCxMPBksmbCoGI0KHTTlPjYSESEzeAySj3WXu29zz57gLQ6kGR+uOijfpvg6zptxEdUXPZFU6g4vJmWJ94Ed+SLaWjCjfShFYuibOIkrqxeswPL+LkQ0kXCMlkgc0GSS/8oLkDOJmDjJsV9XLJMYOQNfaK9pu3yLuMRHf1OhhCGVuAY3egrWDAqulTBmhCXL98Rx36RYYUgzGrsAx32TOV0XTvt+N5IglfYyy/t9G2LptpqPzblfL1iwoC6LXaVsFnadS3vyQAZjfyOdeRXL6qQtvC9t4X3QesVYnooITy07ClPle3GiS3Q5AtYcVoseSNJdzmrRT7NB53HYOoJrkjze+zOe7D+Hwu/liL06H55zGsuTz/B4/zmlE+KV+TrIWWVKfhyo89szYiHorIu2ym8XFIZcxE3BUpoN27au6dyaNGkyfZq5SYp5zwqQE3nttdeA2l0HmjSpxtDQEI7jYNs27e3tK7o7s4pxl8HA4Z6bdH4Q9CKSvhvsjZDw51A6Cv4tvZ81IGPnZsXHGoUfGUbGzoSxMwuG7BYS3AvV+gNUlThJYvqRxPWIuxilO1DBPcB9ZerxCmUY3GHvd2cQGTkV4oug82KUjjIwMIDruvh8hqizL6YwfJ//Y5B+ZlJw8fJuvRNHpk5WDPwPEjkOHT0RM3oGEv8rRSvgMorEzsNNP4Zu/z0y9susgOkW1OyOJ2aRAXAGwHnZK9fyDVTLF5HMC8jQl8F9C7CzwslvgRBCvEBIUXgxkRxQYZRqQ8nwhDOZHTfr8jgo3wYon7cwpSOfw01cgXeNq2URBhU5BmXN844N7QPucszY2Yx/RgXnZm+OCmyDOC/hjr2C8m2B8n+opGDf29uPCERCaVrCQ9muPoOMPoM7+iMIfBqr7fso7a2ESvwCJFbOimd2xEeD8e6c4ROQwP35vtWKiED8QmT0lxQna2lBWk9FkUbG/gjmrez2EBI+CNXyFZSOeMc7T3vhC1QY/Nt4lqKzgCRvheGTpn58Xc+AQOZ5Cq9Rzv26p2MY2y5331qg56EjR061mw1FMo8hmScqlFCgF2C1HI04L6BUAB3cCeXbclZCUWh7HQJdV5AePgXJFMSZVVHslmOxI1+a8T5MxM08P23xEcbdr+d25yY+BpN5Ztr11kImdSdIFeHHLMHNPI7t//C02nKc5zBmSdVy6dS/CNlHTqutqTIydhGO+walv28MieS/SKbuJTRFcVjEYWDklwyN/QUjYwAo/ETDB9DTfiq6hndkvfEfC1FK0RL6OC2hj9d97EzRG7uR0fTjVcvVklFaBHoie3H32/uTcD3PGK0CrBbZg1FnKcsTDzLxs41l3uE/S45jTvhjzA1uQcqMQmaAhDtCbsxQyoXaCKSxyY27dUHESU98zCYYy7ZoBDJiTxBSBR+KLTt2q3puTcrTTELTpB6auUmKWWUEyDXXXHNFd6HJe4ycNduqlgFb4pfByI8YH1DlvhGzfzvPwsjJ2a0BJHwoKvr1ilaRImlIXE3tVmflcCF5rRc8v/PistYTJvYXzOhZ2T5bXryesbNB91A4UMwJgPXHB8xeE+d5ZOQ0VPsvWLbUE016OgaYNHdO/4dKEkRt7eeSVvweo3uy4mPB9jwGMg9jBvYFdzGlJj25noy3630uMnYWoufC6E8gO5Epdl9KTDgLGd8vcYR4tlaVb2fFio8KdAcq8MnxLfaa6I6/Yoa+lD1Hi5JipIqiW76MCh9dtFm3HIMK7YkkrkKcNxEVRvm2RJwnIX4J4jyRLyv5ek5ChT9bNDhZutgTA+Z0lVoZFUhdj9v/NFbX1aACmLHfT+dCNAzJJdoY+TmqvTZXbDEDkLgGiV8P7rMlSowVvFMKSUD8AiR1L9J2Goz8AJwXC/YHkMgXUC3Hz4i1nLhLkfjlkLwN3NemXs+UngONd296z1dOgJxb1v1aQeDjWK0/rlsYni4iKUzietz4IsQsQek5WOEDMM4beMPQci6QAuZ1rODHUNYhs9jjcbRvA4Ld12Iyz2Ocl1Eqgg5svcIsbzPxqxpSz7K+rADZM/5+cTNPIGa05kXDqSJmqKHlKmISNRTSiNQXP7ORjMX+RuXFLoux2D+mJECKCEsHjmMscQOFYwEhzUj8clKZp1ltzjXoKuFj6o3/2GhEBNcMgVJYqm3aCxDvjF5cUzmtPNFHyibF0tj2Al4evqBoq5EUb4xeU/LNJgIZFMZkeGPs33j2iRaOGHLT8lKxJyUvPuZQKAVKDK7obB+zexRghLSUGncrMgKPD93LzvMOrOk6NGnSZPo0c5OMs8oIkE2aNJpCAXJF4CUseQRJXANuL1g9qNA++XiA3v5Hsy7S74DuRoX2Av/2U56MS+Imz7KvZlKeQOAuhfZflY9T6LyOZMWrqYt+OTyBjdSdENxp8t74IszoGcXl87/2FverYMA+tf64kLwBMaewbPE9APSUdI8sEwB9khBYC5bndl0tlqH7dh11jtcto2d71p4lrk11EWU8NtF0kr7UR+46TLweFqDQbWdPEsd14KOonvuQ5HVI+jFQlhdvzlobzJugIij/R8vG5VLWfFTL8fm/3dGfey72pZBRzOhpKDOEFT0xv3np2/cCdkH8xxK4b2Jif0H5P5L9TFYOBEGSN6DkjKJn3oszeh1ielG6B0J7QvoRZPibVIrDVRX3JRg4lMkLGCkvPIIZRbV9N/tOfMqz3NVR8G9dcxxZkSQkbkIyj+AJ1z0Qu8BrowZL2bL1Tkl8FC8mrvN0fsuy/mwCmokZ01U7OvpNVGA71ApwFxYzSmbgiKylozeJF3cxzvDjoDpqrCRTvcwMo30boH0brOhuIKayq1atLM/GC53TXZid3SWTuAF/5OCGtFEObdeWAEk3IFGSZa9L9WRCLra9/rTbmipulUzq4OLkwqjUSSJ1L2OJ68vWm8o8zUjsH7S3HFm2jnQ6nY93vmDB7L5DRAwDY5fSO3oeKedVAIK+9emJfomOyH5TFiLH0s/VXHad9i/y5sgiHDNKUXIZLLSKEnNKx7Y2eafn4j46WJi8WJgbEblYyvvpiJUNhVOMW5BAqRALISOF4xyPjNgly+e4c/nVbN29Ky127a74TZo0mRrN3CTFrHICpOM43Hjjjdxzzz28+uqrjI6O4rqVra6UUvz73/+epR42ebeQEyBXRAIakTQy9HVI3cr44NpCEldCYCek7SwY+T4kry/en7wB/B+B9j+idH2ZiUUEGfvVVHoLqZsgcwT4Pzhpr4ldjBk9nfGBWPHPvDtwXWgkcRVqggAp4mJGf13vCUwTBzLPsHzZy0AXczqG6q6hvizLrhc3c5qWhaXaFBxEFpcsr7JRh6rVmiuda2Nm0Nk2XMCHF0NuQlt6rmfB6N+uZA1KR7zM5+Hxybi4/aAMqFa82HQgZhhMn2dJWcKyTNxlSOyvk7ZPKhf7vedObM1FRFi2fBDoYU5XpXh+BolfhrI3rlCm8KS6QRojYFQnhWQeR/m3wBgHhr8GqVvyewUFY2dVOL5eKnyPJy7C+D8Eo78BU5j5M4zY63qxJpUFgR29WKf2WoikIHU/yBAiCe9YGYT8xHC61tpTR7d8AxX4GG78wvy2pfmM6QUCpF6I1f1PlG6f3Q4W4Az/EMk8lf1rgtV8TQmbWmEFCKcrK0L98ZUnki5KQFP4PrAxbun3eyOx/dug9AKk7PeUxvJtiuV7/7Tb0lYngeAepJLXU/qZ1Wg9H1+gdNz42UDrbtyKC4IWVjbMR70Mxy6lmgA7PHZJRQFy6dKliAjRaJTW1tYp9WMqiAhvDXyTwdg/KBTRkpkXeWvgqyQzz7Kg4wcVj3fMEFr5sCa4mSt8FIf5KM28yP6s0/FVFkQP4vXhv7J49GpcSWCpMAui+5E2LvHRq4uEyXz7ZeI6uvnxyWRsZbDQdIe35PXYw0X73DLHKOVZaroFj5JrwC0hYhb3z/D00P1s3f2piuWalKGZhKZJHZTKTSIiq2xuklVKgLz33ns5/PDDefPN8RhvlUxfc1ZksxFrqMm7jxUqQI6eCalcMhS3+GfqDhg4DJxnSu9PP4QMHILY64HyowI7QuDjqGoZ8ZyXvOQPUyIrCE4QIE3iOszojysembMQqk+INJCNxVNUV/pxkGrWBqX7AFO3yhR3Kb393sSxp3NoSnXU3NYMjYoqWWqteFfqHD5U609RMoC4A0j8EqCMC55ZjBn5Hoye6SXuUZ2ggqB8KN+GqMBO44lPnDdwR8/wslznRBRrbc+Cy3moA+ZmAAEAAElEQVQiu02Bf3us6NdQvk3yzUjyRmr9PCRxLarlGERSLB/wrBIqC5B4opi9Wk316/ZfYwY/jyfIzgy571RBkIHjcMMHo+IXo2R4wnfp9AXyiVR8PodPLNFm3IsZmf/zIiR+MRI6AJI3gYyWqGjqwuPEPtcm2heg56Cj30KH9vIS9dgbgvM88aSPkTFvgj23a5Dc5Fa3nb5CxUdx+zDJ6yhvIZo79/LujVb4sJqtVKeLSAqTeRrEQfs2WKHXrhzaXmvadfT2dwGKSDhGJFz4fnSgimjRCJSyCLf/nNjAkUwOb2EBPkJtP21Yey1tp5LJPJoVVwufX6+t1s7f1+wVIpIikbiOeOwfuO5SLGs+4cjBhEJ7TCn5HkA0cjBDI2dT/jlxaYl8Zkp1Z5w3qPzOEpwq3hCFCWhmk9Hkv7PiIxS/u73fe0fPozW0Ky3BrYqOM5Jh6cj5LBu9kHR2HBjxf5CFbcfSEfaSo7X4N2Y49WDF9qP+zXl/t3cfBu35bND1Pdbv/A5GkmgVRCnNw0u/ipT53AoTweT7ViarNYyLk0YEkQxBq52kO5TfJ2WOFSmOVWlE4VD9flZoRp2hquWaNGnSeF577TWUUqtsbpJVRoB8/vnn2XXXXUkkEogIfr+f9dZbj87OzlUqfl+T2hARSP8XSd0JkkT5NoDgXvmEBibzKn29XmDzLt/PkLFtIHTAtDIw19w3MwLxyyg/gTcF4mPJGsB5zsuojMIkrgA9DyJHoez1Uf6t8rETvYyzr4IkkOxAqO7+5mLCpR/FpO5C+bdDKRsRwVTJhDm5nlpFQAus+ZO2mnhtcX8ai59U7H4GhtuBqQmQ9VlAahptndVYgVGBvYkXK7ThuMjoT9E99yDDp1BWfCxEhpHkTQUbsmHddSe67TcoawFu/35ZMapgouG+BhTG/RNI34vb/wBW58WobPIEMf3U9pmorEUQDA8nSKX9aO3S3T5S5bgAyt4IfB+EzJOUE3Kw1kH5P4JuOxMzfGKJMtPDiJl0h4gsg9iv838rUVjouhb1JlpEV6NcOIDaWsyK94l/VC1ZD+Wen7qfKWsDdGgvTOouzNCJIDEAlmfdr9tbRwkGMqDC6NafoQPbTLvv08FknqC2d5EXDmG8bDYMh+9DWNHjyx3UMEQcnLHf4cTOLxCdbazQPvhav4fSs2f1VQ2rxsWGSpSK/5jDTDUJW534gh+npesyEiOn42Yez2+3/R8l2PpdbP+mDWtLW3Po6L6R+NjvSMYvRWQMsAkE9yAcPQHbV5v7tTHD9PcdSCbzFDnR3HVfJ52+j1jsQrq6Lq0poctEoi2fYzR2Ka67lMnPiyYY2JZQ4ON11wtgWz2kMuUE/mwLunIohBUV/7Fv9CIqW29a9I9dUiRAGsnw4vIvMpy8m8Ixciz9JC/2fpE1Or6Lba1eVXy0VJTN5p4/6btKKY2lxhMc+qxWFLqkBaQ3kqhtfumIwpFx8X9J4nEcEXIZrksJl7k4kYXJajwRU2UFSUHE2+9KLmt2Lgu2AWVo9c1uPOD3Gs2kME2myjrrrINSip/97Gd885vfXNHdmXVWGQHyZz/7GfF4HMuy+NGPfsRXvvIVWlpmJzvmqoQ4b3nubNbcfGbY/D4xkHnMs0zTXV6G5BJWdyIOoCuuSIuYGUkqACBuLzL4RXD+Rz4gdMKFkV9A+5lghhh8+wwyzl5o7dIZfggZexDGfotEjka1HFcUoF5EQOKggmWTotRF+iEaY8FkxifGZgmM/sQbrum56NbvgyQxY+cUWD36GF+DrT6dnzTpdl9CBo8G3YNuOwOl59Wdcbp2Ic5FhfYvPtaMZi3YpkjrmeC8AfF6kn1oJHQAfW/eCvwf4WCSlnD9we69eEC1CotTj0dX3OZMWH5b4N8B3f5LZOgUVPq2BltOGpBhTOJqJHXr1OsAMEOYwaPA9+GsKFHrtXdwh7+F1X07SimUtaDk5GQygtJeXLZcvK3u9hEsq9LnqVHBPVFKYbX+FHfgMyAJSln5WO2/8CZTwU9B8lYvLEIDKCU8lkMQHFx8NQ496hW+q1nplrunZzIeqWnQ8whA5j+4scuQ0R9R+Bnn3a+7Br0s1103oa2VQTSr7bpa0a8j7huYxPUgCZS1BjpyOFb44LJxVhuFiJAeOhmT/CfFi3oObuJqTOYZAl1XonS4XBWziuXfjsqJe6qzvDcb/7Grf9I+J3kDImc2ZqxSBTuwNdGe63CdNxDTj7bmoWfI3V5bXbS0nUqk9XuIjKJUuG7L2qHBk8lk/pf9yxT9zKQfY3jo+3R01h+mxtIdzO+5jr7Bk0im7incQyS8P13tP5vyeDca3pdY8l8VSmhaI5UTkawoC8hE+jmqxe5MpIsXMnvHrpgkPnp4n9MbAz/D1Z4FcLlFfIXNB+dfhm1VnyMujHyKt0avKV2PAi3FI7KcMFj4bnRF4YhdtD0nXeZKO/lkeNn9QoGVo5eMxsYllU06o5RCGSEjGjPhWC87tkVAKTZr27bqOTZp0qTx+Hw+MpkM22+//YruygphlREg77jjDpRSnHjiiXznO99Z0d15VyKZFyF1N5AB38bg327cUi79kOcWnHlyvLx/W1T0FJRvfSR1NzLyo+LEF7oHoqegQnt44mTiaiR+YTaLqUL826AiR3vukYCYMS+LbPwyMEsxhLwkAqE9UcFPTmuiIpJLJOBHBo/y3I2B4kF+Ehk6ARD6hryBWFfbKFrnBjEuxP6ExBdB51/BWt2L/Ra/PBvryocEP4WKHAP22kjqbk/cU62o4E55dy8Rz52zvJVQYwLyl52sm2WYoZzVSWEfMuScSrw9lSeXZYUD04cZ/AKq5bt19zlX73jbpQaR2otzOSGmk2Qeo1rMn4khGQo/A6W70a17Y0K7wOhZ3r0uDui5QBrMO4y7EmZX7f1bo1pOoHfwPqB260cRoVDWUfbGWP6PoIKfgPQDEP87yETLOG+QqSJfQGJ/qKmdyhR+vo2wqrRARbBav4vSUVTn73HTr8LQoZOS/0wPjaTvZ/r99cREMvfXf5z7hpcIyb8VKrg7jPyE6s+toIJ7ArBsmRfUfk53pYUGBSqAbvmi95fv/Vhd12BGf42kbs72X0NgR6yWk1BZKx+lNFb7r3DHNoTY2XWe24QzrUN8nHicrjKhngm3/nrqm64oOVNhCWTsTCYGn8onoOkeALMUMo+AtWPD264X7fsA1ROAKKzg7ih7ITTQ7bZWTOYRTPLaMntdxHkeN34ZdstRs9mtkoikEPctrMBOuKlbKesFoVpLfD+Ms7w/awHZXSIerCQ9y1o1ewK2Za8JrDkrbSlloVR73ce5zjskK4bTMCQSV9HqfhdrCp4wtr2AeT2LyGReJpV+ApRNKLAtljW9ED8toU8R8G1GKvM/Jj+HFpbupj3y2bLHJxIJBge9MCCzLUBqHaq6nmpNWBhYNnpRxfIGjWMqJ2wTHJTyIeLSl/gPS8ZuIO32E7JXY2F0P9oCm+fHht2hregMfJDB1JMlXLE1PuVj9dYDeWP0OjJmBK1AixRZLTqSkxonWluCJS5GYGLsV7doDJy9FnlzvJyISVZ8LC6XGzdnjDUj31GrDCLev9lus8l7ggULFvDGG29gWTO/2LcyssoIkH193kBrn332WcE9efchZhgZ+hqk76EouYNeAB2/BTOIDB4z+cD0A0j/Z5DoN2H0NCYN3EwvMvx1z+IxfT8k/8n4l6R4x6fvg+gPILQnpv9gz4ou/yUfg/TtSPp2GGlBR45BRY6pa6XYJG/FxM6DzBPeBr0QZTx3k8nxuXLCm6Zv0Bucd3eUGMjIENL/WbA6s4Jrrr8ZSN6ISd6EqBBe1tqsYDVig39rcBeD+wrg84SDyBdQ/s2L668h4US17M21T44nOVVm/195el65bm+gJfELami/BOEvo3zrIb6NYfTMrFVjrj0bQvuiWr872YJDyos5EwW/gh1oFEpZSOZhCG6HstdGWr4CeKKPUiFE0pC8zcs4bnrBWg0VOgACHwcUfYPeJKK7hgQ0RiZ/NuL8D8d9GV9wJ3T0qxD9Ksbtg/giTPJmREbAWgOr5ViU/6OQvM67l6YyuPR9FBX5Cip9OyRvA9JgreZZL9dIoZCbF3EDO2JFv4UqiGFm+ddBuv+FGTkNSf6TaWVCLqJRX+jTyG7svOaFM9Dt6OjJmNGfVSitUKFDULY3Cc9ZQM5bfV8IBCB1A5M+S70Aq+MclD2ePU/Za2N1/AYxP/Es0XVHSfdRpSzs6LE4BCFWu+gjkoswOr1BsIvJ15XvExSJkrM5MarUVrn351TqagglhKVl/TkLyAFAeda/wRUvQCqrGx3aG5O4htLPkoUKfNITH1cQbnwR1URSJ/73FSpAijikx35PauwvjGe7r/ANnHXNL0XGsRgYysaX7Z5sAQk+UPUlqKuEiOCk7yMTvxpj+tHWAvzhA7EnjmtWclLph6j+feqQTj9CKLTrlNvx+d6Hz/e+KR8/EaX8LOy5jKUDXyGe/DeFY+yAb2Pmd/0Jy+oqe/ySJV5YkI6ODkKhUMP6VQvt4U+zfOQPlH82FW3h3Yu2JDKvUO5z8tyTa3s/x9Iv80zvdxlOPU5unD7EIyweu4r5LfuwcfdpWTFbs9X83/HYsm+zPPEf8EaMCC4B3cNq0b1ZGr8P1ySxVYTu0BasEd2bR/p+Q8JZnl3EmzxnycV8dBl3nZ64r9I7QATSE6wqi1EIhocG7uYTcz5d0zVp0qRJ49hhhx245JJLeOyxx9hqq62qH/AeY5URIHt6eli8ePGsf4G+2xExyOAXIJML1F8wiTBLkYEjgAATLTI8XCAJo2eU2Z9l9McFA+bCMt6gQ0ZPQ1IPIu6L5euQMczY2Sj3Hay2n9R0bmbsHMzYb6Dwy9+8k2+h/ETS0JcdwJeKz+YJpKPgjicwyImZkrOCyothuevpZAXeHBlI3Y6b+he6/dfo4G7jddlrIP5tPUu4CQOzUsJiYQKXeuOplUdna3Xzf9cn1hgwlQOflyaIjp6IUtobUnWci7iLIReTyf/hkpmIAZRvY0pZTJYVH/M9FbQoEAdn9Gzc2MXk44SpCFb4UKzoV1GhT6NCpQdyvcMbAIaeUoL1hL6U/mwMSIrM4FH459zniUoy7LnLOc975+6+jRm4DxXYCavlW8jwiSXPt9K5a/822B2/Q+l2jA7gmmHEeREv43MrSkaoFL6v1LVUAkrPxddR2ipT6Ras9p8j5pu4A0dlQx+U67PK9iVD+fvNoAPbYpznwH29fGdnGjXuvqUjnwfVghk9Ey+TciE+VORz6Jav57fkLCDnzlsLu+NXiDkVSd2PZJ4G3Y7ybYTyb1t2sUXpKOho1S7a0c/hpG4C5/GqZas9J/UysS4BELPSJH0rfA5XZisRx9H0Z7+PvAQ0gjizE8dvIuIuw6T+Czgo3wfQvvWwW08l47yKZMYn8rn3krLfj6/9jBXS13yfnTeplqRDZiEzdNnWRUgMfhUneR3F78VK92T58+nr70REEw7FiYTjk/ZbgR0a5n4tJk5s8Gic1D2Mi7wW6fjf8IU+Q7j9F7Pi6t0Yag80US/GxHFNH1q3Ys1A4iNLd7Cw+xLSmZeJp+4FcQgGPkywBhF4RblfA3S3fJa+0QsxEmfy972FpdvozLqPixgWVxQrPZdlU+Pi5Bsjf2M49VT2L6/tXCiVJWPXELZXY52OLwOey/YarXvTHtiEpLuckDWH1sD6vDpyLc8P/YXce89ImmXx+1kaf5CO0EdJOKU9P3LJaPL2jAqUmLzomDOFmHiMQaExGLx4klVFSoTXYy/WdD2aNGnSWE444QQuvfRSzjrrLA455BBaW1eGsDmzxyojQG633XYsWrSIZ555hi222GJFd+fdQ/qecevASRi8eGPlV9u9wVhlt1dPfKwklCgkfUuF/QVVJS5HwgcVZaEtWS7zTFZ8hHqtnAQpaQFZSdyb2gTWBRRm6BuoOVujCgKFq7bTkf4DwSxjfHA0m1mKHVT3HSgcUG3gPIsMHpvts1u+H6Us42rGQoX2nSS6KGsB1BA3SlkLIPCJbBiB8UFqLVfFkEGl/4tkniw+QmK4sb9gMs/h6/xr2UzivQMRYJSeznJucd79X1ngMSBx3MTVWMHdyPQdWGANM34PS+pOXNOH1f5nZPRn2WQpOcJAPC90TmzNpP9Levkn0cEdMYmrGJ80ev0TQIueIEJm95URqLx2DGJiKF3eskbpLnTkaMzwSRWuAajgrllryVJoUC2o4B5oPQ8zdHTFumrDwru+9Tw/AVRgh+KehT+DCu2HpJ9AnMdBUihrDVRgB5Ruy5dzHIf+fs8yae7cuQAo3Y4K7Qah3Wg0VteluMs2p9R7uiijdcNbnown9k/l3TBzrMziI0DvYDvGaEKBFNFIVlAyJVxrZxAxMZzh70/KeK38H8HXfha+rsswiZtwE/9A3MUoPRcrvD86tNeMx3isitUNmSpu4rOQDdvNvISbfgAQLP9WWL4NvO3p+3DKvu/qJ+d+Pae7v+RiUrB1aqFRShEfPgUndV/2L7foZyaxiJS9GsHoVxvW3kzi929JtQU9sPD7P1RznY7zDoMjZxGLX0UuxE0o8Ana204mMAMWon7f+/DXaV2Zs4BcEQKkz57PunMu5dXez+GafsanrA621cM6PRdjWx0kM2/wwvIvknTKi2lGFG5N4qPCby1gMPlQxVJvjFzEmm1H8frIIl4Y/D2ujIv5QWseXc62LI3njArG34muuKTRLIk/UFBbsZWiKSEy2hgy2fN3J1hMGoGM2BTen66UtprMDcG1Ei9G5QzF0l8VUDL7SWiaSW/eO3zoQx/inHPO4fjjj+djH/sYv//979lmmxWbOHA2WWUEyK997WtcddVV/OY3v+GQQw7BtleZU58WkriByu5JjQqwX8mlza24vxgLk7gSq4oAaWJ/p3psqjL9EcpaQDZ+siqAgySuQkXGxRRlzYPua5DYxZBYhJi+7ODCFMcOxLO+LDWhnxRnMOtsWNvkX6OsOePJdqztoftGJP53SN2OMsOIFIizpcSpvHtz6b4Vu2daKB1GR75QQ9/KY7X+xEvU4S6mULitjg+pIMRL+h5M8mas0B6T9qZSKYaHPYvJOfO3BG4if9/pHlRwLyTxDy9JTg1I6gFcd3lWfCx1/7rZvrpY3beB8zTiLkNZcxFrAyR2Dib2V0RKJcMRkKGs+EhB/blrpDHYaMmMf272pojbi5F3ynfa9OIMfxtlrwsI2r8lyr/N5AyTwf+D2GZZK8jJ8aqwFqKip4I1B4mdR/EzrEEFsTrOQ+kIKvhxpOWbyNgvyverKhoV3B1JXk/1yWfBeUS+4FkhTtyuLFTgQxAoP0nt7e1FRAiFQlNKlCbighkEFUSVycgqIkj6XpzY5Yj7lpdd2fHEdaVUw60d66Gcw1jt1P45vTsp/t4qdL/OP07uwKz1RsQlM/gFJP0QE8cDkn6EdN8B+HtuxArvjRXee9b6VSt2aC/SyUoJmTR2eP8K+6eHcXtJDJ6Im76XQvdYy/8RQh3nkI5dxlTHKqVY3lc+AY0vfBhWg9x/jbuETOJaKj2LybHzCLR8CaVWfs8k216dQHAXUsnbKf1ZWIRCe2FZc2qqz3HeYvGyXTAyzPg1EhKpO0ks/w9zuy8jFNyuQb2fOtOxgHTcAUSS2Nacsouz1QgHPshGCx9kOH4TsZQnCrYEtqEtvCtK+RiM38aLvV+m2vPh5FO6VPt2EdqD2zM2diWV7l3HjPBs/5m8Prpo0r6Es4zXR6+Z1JYIeRExhxfn0WRFRZW3ZJx4rKUEI25Rpux8nWIX1KewxIBSqOw42ojGTBAkXdEoMazXUnmu1KRJk5nh85//PADrr78+Tz75JNtvvz2rr746m222GR0dHRVjQyql+Otf/zpbXZ0RVhkVbsstt+SXv/wlJ554Ivvuuy/nn38+3d31B4pe5ZARGjXwnR1cxKnu2islBY7aiCeDJFOe23lXVoCcqYQDOSTz7KRtSneioidB9CTc5H2YwcMn9SAXr63Qqqic9VtuW65sqXKe47PlJc0pyPQNoOw1Ua3fAb6DmFHc5VsDyYpiRimLp1LlBQft2xYmZFavF2XNweq6FolfjIn/o8BSqJqQ7p13+XtG48YvKylA5uLPtrS00DLvVMR8D5zXQAXB3gClbKTli5jYFZixn9d0Hm7iqgp9AU+IvxYruBP4NkP5xs9CWr6Gk7wNnJcpPcCuYoVJGt32U5S1Fsqah7LXxhm70AulUBbBJHOLGeDioqx1sTv/hLbXyZdSyofVeRFm+DtI6pZsQqYs/g9gt/8OZbVC9FsY/8eQ+N8Q5xkggAruig4fhLLmj1+Fli9igrtjRs6E9F3AWIU+TkSDvR669cdI4JOYke9lXe9zGWgLg8CP3xsq/Hl0NkboVMgnoJkzpy5LQDFxnLE/YGIXA1kx21odO/qNovtSJE26/3OQ+W/R8d6VDqMkvkLlO5myBKnx3PPrzzL/rkKvBuaN/J+5BDRzugpc+3V92X2ng0ndjaQfKLPXBbMcN3YJdnTqz8RMogM7onwfRDJPUXLRQ7djh4+YkbbFJIj3H4hxclbq40+em36YseWfxHvfNG4MlhcgJ8R/tEP7E2yr9A6vj0zqbqouBMgoTvoJfIGtp9WWiCGdupNk7O+47qto3UkgtC/B0L4NzV7e0X42fX374zjPM77Q4bnX+nwb09ZeKc5vMcv7j8XIUIk93qJz38DxrDb/0RXqoh6LxRgZ8ca48+fPr1J6nNHEbfSO/IZk+gkALN1OR8sRdEdP8BLL1IlWAToi+9ARKY7hH0+/zIu9X6Im76gq7sgeig26zyLlTgyTUqI+gTfLZL8evy8m96FUvEeLnACZ++6bLFy66AK37IkJbIq35X6zENJiYaS0laOgeC32Kts0p8JTQ5j9tc738trqKsaFF16YH+Pn5txvvvkmb731VsXjRKQpQL6b+PGPvYHVRz7yEW644QbWXHNNdt55ZzbYYAPC4eoDlB/84Acz3cWVE2sNpr/6Xs2F0Y83oW+ENaVVNgZgEdNYce/Pul+3R8fw2bMhzipQlSeUkrq5imw0LvRV+840SH7ltNQ+MPgix1busY6iW7+DO/z9qpZUuZzRUMZSMlcudTPOcCu+Ogb5pfvWjmr5Sl4kMn0HZDNkV4o7CJWfAYM4b5Tc09vrxfnp6enJtt8F/uKg70p3YkWPwU3fhaQfptKzoPxbZt3IK+EipowVlIwUZHmfCjbivI4VPnh8k3mbcWGucr/y3XBfJ9N/MP6eW4rDC+goVsc5uPGrcEfPyoYZANKPkBk8Hit6IpJ53kvwZK+Hjn6tSMSciLYXojt/7bVpYpjUf7ws1Vie6JC6jUI3c68TIVToAHTLV1G6BRXaHRX8JJL8F7hvgop61prKRhI3IGYpSnehgp/2rJOnQS4BTc79uhbExEj3HwjOhIUK9y2coRMxyX/h6/gtAM7QNyeJj+PEkZo+x5WBQktHhffMVMs0vrIRAhL1HWKK4xEuz1lAducmzRoVmL0ENF6CmcpeEm580UohQIoIJv0gJhuP0gpsh/ZtTKDzQtJD38Ck/kWhFaKy18ff8TvUNDMRlyOduAbjvFxmryEfa7hBuK6mb9C7X+Z0jbvp+yMnEmz7ernDpobU+CxWSA5X0+HiMDL4ZdLJG8ndhy6KTPpB4mN/oL37SiyrdvGsEtrqpLvnBhKJq4jHLsN1l2FZCwhHDiYc3nfSomw5MpnXSWcerVjGNctIJO8kHNqpEV2fEosXe++arq4uAoHaQiUMjF7A0qHvUSjAuWaIvpFziCXvYc2eRVMSIUvxUo3io0f1ha2gtSZzW/ZgKPl41XoNPkyd3zemTPs568dyuGic7Ci5sJRnLamL/nazIqcnaqqs5WO5c1c82P8f9lhwIK2+thL7mzRpMlOsscYaK1W4odlmlREgf/jDHxYpzYlEguuvv57rr7++puNXVQFShQ5A4hdVKKG97M3p+8oXCX8e4jmlvsSXesuXYex3lF5OskBFQWp1KXNRoT2rltLBXTAVRafy5Nyvu9rrnDhOGRcV+ETlEqlyFijjCEDZJCcTy1ZKKmM8t002rViHDh+CyTwH8b9XbU3Es36rPKATTOIfmMjRiPsmYvpR1jy0/6NlrQREMrjJm3HjlyPu26C7sUP7Y4X3ybt9WeH9cIYrTQYErDngvkOp+yVvsSUJ0oPHo6z5WKH90b71gXFBKSdAVsKKHIWTfrDMXgUqhBXeHzf+9yoJViyUtXr585k2EwWq2iZexbhg+nDj/8Bu+VLxnsTNOMPfnHSEZB7FGTiccatDwR37DTq0L3bbz1BVhHqlI1ihT+X/Ns5rSPhAlIqAvQmS+g9u4irEeQGVuh8hgBU+FGWvhlJBVGgPxAzgJv6FjP4WJIHyrY8O7p3/vKdL7n6ZM6c2Vz4AN/bnyeJjASZ5A07so+jg7phkte+8FSs+1jQcC+yGbvsppB/GjP0JnNzz+26w1legO1GtZyEj3wCTpL5ncvwdKTLugj2nMydAGiTzP8TEG2r9VQ5xl1P1updbDJlFjPMK6cFjEeclcu8OZ/QMtG8r/B2/I9D5Z4zzOiZ1L+CgfR9A+TafkQmCMYOkx/5EeuxPDa+7Ev2DHRhjEfCnaI2OW4Pbocrji6lg3KU1lNJYvg2n1U587LcFLvTFIUOM+xYjA1+ko6e2cX4taB0mEjmcSOTwKdcxGrukpnKZzIuwEgiQtbpfZ5wlLB3KzZUmjh8NifQTDIz9he7WE6bdt0TmFZLOKzWXt5WfjJgS/cqhmdPixVhuC2xOi299YpmXkZLvNosW/wYMpV8quV8pyAdbrPKNZoQSsSnHjxXJuY9P3i8ThMvCjNm2MsTFX7V9QXhm+DG26W78O6BJkyblef3111d0F1Yoq4wACRQlwCj1d5PJKN/7kcjREPtLib0W2OtB2zkQPx9ifySX5RAcz4oo+h1U+EDE/2Fk9MdZESeL7kZFT0GF9kTs9ZGhk4A04y4ILugudOeFuENfz06wK31mGrKx5aqeV2h/GPtjGRfzQleIyYOV/qFsApoFu6LadkZifwXn+aptTo1s3LvAJ8uWEDETEo2UKYdkozxWo1pGa40bOx+rloQYuoNaLON09BTPgjBxacVygpDq+zRFVkN6Lv62H2MFdykuKwnSA5/DpB8kf07u22Qyj+PEzifQdTnK6kYFdkb0rxGzHPLDN7LXykJZa6LDh+CO/rRkf3JDQWQYN3kzoHBif8EKH46v9Yd5F+ycAClmFDfxT4zzLBDECu6cFVEVVnAnpOUE3LFzKLYqsgAbX8efUboNK3wI7ujplH8eXKzwZ7JtXYWTuBbMEMpeGyt0MKLXRJk3KxxfCQflK07kpYM74cbOnUJdgkn8EwoESJEMzsj38/snlh//OX5PmcQ1OATxtf+kplZN+hGckZ9mkwpl0Quy1mXedRfAdV7BjV2Ar+NPqMB2uKNn4cb+QtE7Iwnu6M9R/u2xo1/3FjYkg/ZtjPJvjScY+WoWMgoFSJE0JnkrJv0QnkXWpt49i43yb4rSnYi4uGOVFok83LFfZuOMrtzfezW9o2QYzChm5AdgahE6Krc4a9dEhVGhz6BbvoKkH0bM5Dh89TAyFiGV9qO1KUqIhvM/zMj3sdrPnmaHq6OsBUi1JC5W7da8M4G4faT6DwQzlN0y3leTeZTUwKEEuq9H22uh7bVmtC/GXU6sb2/EXcJsC+bL8+76xQlotL15Q9tJxf5Oauy3VUpZ+IKfQtcYM7EUIikSY3+h0vegk3mMTPpJfP4PTLmdRuPUmKV+RSfAyiWgqdX9eih2eZUShoGxC+mKHj9tYT+WfqaO0hbzIvuwJH4rjhlj8vhWY6kQC6IHAZ6RymZzfsnDSw4jY4YnlFe0+NZlQetnGOwrH7LAs0CcEK8x//8C0VCKY1N6Ga8l76rtTvg+VAq0CAadHa16xxopdjOv5/KmzHs8bMkMoYz3b7bbbNLkvcAqI0Aa03xqp4pqORmshcjYnwome0EI74tq+YaX6CD6FSRyOCRv9awdrPkQ2CWf9VYFPwGBj0HmUXCXgu4E/0fygalV8JMw5z+QuDobi8mHCmwPwV1RKoDV/ivc/lzW39KfpQrsim47fVKW5JJldRtW5yW4g58D08u4E7ALKoKOnoIZ+TGeeFDcXn/WArKnZwEq9CFUaG+M24/0foypxx9rIx+3LR8/xgVrAVbHRVUCeOcGHY0arFarxyCZJ/NxKCqiItTiWq+DuyESx60gQI6LfRMsT81y0oNfwt9xHlZwXKjNjJyOST+c73OuFvDcf9NDX8Nu+SLpwS9nXd1UQQnvN+3fGl/72aDCuPGLswJ6uQzaxefpxi9BWXPp7fWEsp6eHtzkraSHvgqSJB8PMX4ByrcpgY6/oqwe7OhX0YFtcWOXYDJPoAiggzthhQ9D2asBYIUPwSSuzlrzTJ7E6tB+oOeS7PtUNuFO9gq6b2NSd6HsjRBjJok94/H3cpGGJn6+GnQnOrhz0Vbl+wDKt2XWlb2+SbWY4kROJnX3FCymBJO4HImegKoidpjUg2QGDmfSfZl3bS3svwsYMoNfQof2xSQuK9+D9D1k+u8hdx+5BfHBvBiVn8aKHIL2bVr2eU4kEoyOeu+B7o4B0ssPALOc8TAWhc+HjQ7tjdVyHFAuu3rh+Q0gFawkVxbG3ykVFkLS92GGv5Z9d0+xnehp4DyHVFn0qI3COFxu8XZrLXT777xsz9a8fNZnzw14euSsH7vbh7GtwmslSPJ6xP1m1edhuljh/TEVszRrrPBBM9qHajjxv3mJmUreTy7ivISbuBE7vO+M9yU5fGoDxMdqi4Sl6c3Gf+wpiv/oQ+vGZcIVSZAYqb4QpK3VCbWdNq22nMyLRcnuSmORSd23UgmQVo1hOsKhXaoXmkHqzYCdqiG0i+MuRSTZgMRDtd+zlm5hYftx9EQP5ellR5MxfRSO+W3dxqZz/0zAHv9cIv512HL+Zbw5cgnLY7eQMaME7Xms1nogq0UPBDT/6z+rKPt1Ue+UJmjNI+YsRWEhuJgSWbgnJpyRvJCYY3I8SFNivD/RvdvJu15Xdz2fF1xYcX+TJk2aNJpVRoBsMnWUUhA+FEIHgfMqkAZrzUkZVpXugAoTDaU8C8Wy+3UHRI4qHanEXger+wZM7AIkcSXIEKh2lG8zCGyLDvxfXpyp+bx8G2D13IUkb0bS/wUxKP8WqOCeXhZd38a4w98Dp2ClVXczMLIWkClKYqStLi8xxuiPSrVU8LtM2C6o0KHo1h+CWYYkFnnx7VQAFdgJFdy5ulupUij/ltVjB9ac2KEWIbO2wZ8V3BV3tFJiFY2yN0LZC8GMUM5asrLjuDfAyoyc5iUUUAoxI7jxRZS/Hi4mfQ/pgQcK2itOtyN6Lr7O8/KCgb/rcjKDx2dFNp3tUeVrFR/8K0NDewHQ1bbEEzvzx42fp2SeJTVwJIHu61FKo/1bof1bla1X6TC+rstxRn6WjcGWdctUbViRo9CRL5Hu38cT+4v66E16xXkObW8EznN4ocqdIuG1mJzlrAUqiK/jvEn3pFIKX+cfyQwchWSeyK7ee/FC82VK3n8Wyl67uDX3baY2wRZM8l9YkcPKlxDBGf5utu5a6xcgjUlUs+4oLJ8j10YKSV6Fk7wKVAgd+gzatwmQRlkLUf5tUcrKWz+2tUXRY0eC5NwkS4kVDiZxtRfmoEaUNW8lt38spMrnk3lkGnVbSPo+SN0yxeML70/b+86IHI0krkYSV3kLZXouOnwwKnw4SkcRMUj6v5jEPz235Uy5UAu1s3wgF8+vVNIErz0V2nva7VRC+bfxrMhTt1MqhIqy1sQKHzKjfaiGm7iaqlb9iX/OuABp3OU4yZur9KUaQQKtX8NkXieTWEQ9IROW90/MgK2xg7tPoy+TySRvL3hvlSfc/hu0Nd3sF7W+zVYuA4RwaBdGS3oVjaNVN37ferPUo8kUJqCZN682wVSrCNW/u62qY9qqfUs9zRsDtSVM8lnz2GDOxQTsBQTsBXx09bvojd3CUNILW9QW+DA9kd2w9HgYmaHk47w69Af6E/cCgqXCrN56IGu3H4vfGo9XvXHXyTzVV2rMr0E0EXttbNWGI3FsHWFZ6tVJJSdKiROTzKiyQqNCY8iNxQutHx3ROGJha8Fxc7WWGn8JGpu1wu8rsa8+nnnmGV544YVp1/OuopmEpkmDEREGBgaIx+MsWLCgYibsdztNAbJJzShlwQocEClrLlbrKdB6Sm3Wd7XUqQLeBK3EJE35NsHuvhbJvIC4b6J0K476AIPDnqDW1VWcSERHDgcVxIydXZBdGbDXR0d/AJlHMPGLx/fZ66Mjx6JD2QmANQ81xey5VuToCrEDNeBD4XhipUiZuDbZsipC5eD3FiqwdU3XX9lrooN7Y5LXUXpQarCiJ3pldWs2Rt0N1G8dIoj7BpJ5CuX/ACbzNJCq4TiH0t/oBswS3MRN2GEv86Ky5uHvvhKTeRqTehCTeQq3Sjy9gUFvcBiJRPCZC7KDx3JWOM9iUv/BCn68hn5718vXfgbS+m3EeQHwoXwboVQAN/1oNjt0OQTjvoOv/Vzc2F+RzKOUj28Z8JLkhPbAinwWZZVeLVe6A1/XlZjEtaRHfsrEuK2SHyIX3jcuVvjQSfVMbcKokTLWCPk+ZJ5E3MmTgOo0cNQnCUz8ouIz1HOw237C8uVZ6+quZPYZrHYdDDj/Az2vBldkH1boEEyskssiTNW6qhHUvkgyXQQyT1J/grXctSmwbtUd6PB+KN/7wed9P+VbEUHSD2Ay/0MSV4D7yhTaLE/OAnJuSQESkJmP56mUwtdxDu7ombixvzH+3tXo4C7YbaehdHTG+1EJMdWs5AxSc5zpqWOcl5jes6WxfJsSaPkS6djlZCpYZI8fssBb3BSX3gHPBbunqx9PkNAEol+cRn8mY9xl1OKRIVR+V9eC7VsPpVqQioKni8//kWm31UjSmeohe7o6Tp+FnpQnF/+xu7u75gQ0raHdGIpVsii3iIZ2nVZm75SzhOeWHYorsaplg/Z6bLbg1qKxqlZ+5rbsydyW0rHie+N38eSy4wvcpcGVOG+NXEpv/C62WnA5fst7jtZs3Q9LBXlu4NckXS9ZnhfPPEKGOMuT48nevIhfk4VXVSAilkIViIfj1o8FbtaTQouNZ8bWCLZyccSitAipMLic9+ovOX6976Br8B4rx/PPP8+jj1ZOrNSkSZPJuK7LxRdfzAUXXMDDDz9MOp1GKcVTTz3FRhttlC93ww038J///Ie2tja++93vrsAeN4amANnkXclsZo5SvvVR2QQTA8u8QUYgECASiUwqq8MHoEL7IOlHQIa9RCD2hl5/A1uhIsdkXSr9XiKCBp2HFfwk0vI13LFfUjzB1Z7VWudFXqyuxLXgvI2bvj+bCbhwomCBCmF3/Bln8Fi8+JilxTI78oWa+2a3n44zJFk3PcvrEw4QwG47rcht2m79Bun0vdlYXYWT9NpczCXvkllPZsRyaNzkLXkBMr/VtynatylO/NKqAmT/oCcodXd3YVJ/oPLk08ZN3lKzAJlD6TbwbYGTuhMTuxilW8F5i6pChwyj7TVwrR7I6AplM/i7r64tu7OMkB49MxsqocRuxoVIAZS1DujOogUFHfgkXlKbesMZuCh73crdc9+us85CZjBWoOnFGTyGZUs88aq77Q1qFyo0MPldNKlUaH+0b010aH9M4oqy5ayWE1HWPJyRn2RF0JzoFgTfppB5mJm6FrP4VgeJU78QWBjKIXv+pg934Ajwb+tlbFct6OBuYL8fM/Ld7Hu2kMbF/Vve3w4UJqApRvk2a1hbOUot/inlx279LlbLV5D0YwgO2rfJjLt/14qy10Ay/6P8PWuhrLXL7Gsk07P8AoO/5QgAfKFPkRz+Hl7c7FJoLN/mhDp+R7z/MPoH+shk/FiWQ2f7CKggoY7fYfk2mWafxhERMsm7qOXdoPXUYz/mUCpEMHIEibFy360Wlv1+bP+Hp91Wo0gk72JwuHJSy/bW7xEJf3qWelSaeuM/AkSCHyPo25Rk5lkmv+c84ay79bhp9WvZ6CVZt+fK34+twe1Yf875dY2xXZPimd5vIflFpnEEl6SzmJcHfs1GPePWl6tFd2dhy64Mpp4i7Q7xyvAVLEv8l4mUj1JaLPrVsKyf/82LLFbsYeWJjwXhhPIiZfmaXxp7jhdGn2HD1ql/X7zzzjvVCzVp0qSI5cuXs/fee/Pggw9WzUuy9tprs+eee6KUYvfdd2fzzTefnU7OEKukAHnnnXdywQUX8N///pelS5eSSCQmKc333HMPTz/9NK2trRx2WHmXviarFv39nutSd3d32YGNUjYq8NEy+ywvPuYMYEePRwe2x41dgmSeABVAB3fBCh+MygZ6Vy3HogFLHEziGtz43xDnVVARrNCeWOEjUPZCVOeFZAY+mxUgCgRKDHbrD9CBbWvul1IBfB2/wjgnYBI3g4xmLSM/PckyRlkL8XddizP6M0zyVnKDTKXnI/kYfRXayopk2rcZ3mSv3OSsFkxWpCiNtqtn7+wfagegu7uTmqzZpP4YopnkHSSHvoGYPsbFIo3O/lV4n4pI1jE6+5mOXYAkbkGpyl98TuJafBMyVZcsF780K7BXPlevNY24b5AeOAjl24xAx59R1lyUbsGKnoA7emZhip8JyYEmokB3owMfq9iu0u1Vz6HMkcyY+AjkznD5sueBVro7h+o41gCj6MiXMeUSAVlrYreeDIDddhoZiSPJGycV05EvYLV4CQJ0aA9M8t+IuwSlu9HBnUBFMIl/4sbOQ5yc63eU8fi1U0ejZnFhyQU9B9xqlnG1kA2nkP4Puc/R5N3DGxdbbyKZjMXgiPf+LOmCbW/uWWU2AJN5GTd2nmedLgmwVscKH44VOQylxl0XlY6igpWfwRWBHT6UzPC3K5RwscMHz3g/LP8HUKoDkTIWq0VMfOco7OCn8i7TSrcRiH6VVMkQJ57YE2j9Ntpejcicf/PqkkXAi/R0K8IdP8QX2tdbrGogTvoB3PTdVUoptG9jrAbdm5Ho13EyT5FJ3UOx9bZG627aOv8yqwvW1Rge/QPVFgctq6vsvtliKgKkUpo1ev7OW31Hkkg/hjfFVEAGrcIs7Po9oWnG4uyPXUe1RZywbyM2mHNx3Z/78vi/cCbEpC5EcFkS+yfv7/oWth5f9FPKojP4QTLuKPcv/frk4wTSJabbklcIJ7eUrblASpxczsHKb9cIBoXJhr8RUWTEytdTSYDUaB4ZuH/KAmQ8HmdoaGhKx76bUeL9m+02m7w3MMaw55578tBDD6G15oADDmCHHXbg+OOPL1l+4403Zuutt+aBBx7gmmuuaQqQ7ybi8ThHHHEEV199NUBebS71JWVZFscf703EPvKRj7DeeivO9bjJykNOgJzofr2yoP0fQNcwwFPKxgofgBU+oEw9m+Gfcydu/CpM8nYghfZtjg4fgp6iG76210FHq69+K3shvo7fI26/Z7Gmo6BXI9W7dYXkJAplrYuyN/b+0q1Y4c/gxi+lnGUEBPAS2lSwislavpZs0bc5yt6gbCIYsOgf8a5Vd/fcmtxklV1fLB4n9SCJgc8zfg4m/zO3hm9nA5+LCM6Ea5FJXAEYtCissu43lhezrgbc+FXUbrk3Xk4y/yPVfyiBnhtRKoAOH4Obuh9J3ztepuhYLy6lJ1B65+eLfrtKsiZQ/o94CbDqSnKTjX+JRW1u/VNDROjt9yykenrmULurrkLpbnyt38AN7IA78uOsOCigIujw4dgtX8qLDUr58Xecg8kcj0lch5gBlLUQK7xPkXu9UkGs0OT4cFZ4b6zw3oiJg1Kke3cDd3oCpGImrNptvLtmsiWOCu6LstfBjJ1F44RlmfATpuVuq9cAHQYn566Zs2zxzqd3qA0RTTiYJBKauHDhx+r4zdTbLsCkHiIzcASe1Xr2Wrpv4Y6ejknehK/zbygdbkhbjULcPpzEFdkkZBrt/wjKt4W3MFfiM9HBvdH+0ouGjcLNPEcmfpXnieCUEyA1VnBvfMHtSI/9IeuyDUovwN9yFP7I54vcV/0tXwYVIDX6y6K4i8pajVD7z7EDnuuxUha9/XOAF1mwcEv8kT1m5BzTsUuo5b0Vaq1sAVgPSgVo6/wbqcR1JOKXYJzXUbqdYGh/gpFD0LqjeiWzhIghmbqXavFIk8m7iUZWbOKmqQiQALbVxVpzriORfpjRxK0YSRH0bURbeG90A94TpkqYFY+pLWbF0i+jsJEKcVWNpEk679DinyygvzKyiFLfJya/HFzMROtHr+z4UmtpsouyooqS1UjRNlW2HhEv83Zhdm1LGQbTUw9BkbtXOjpWnmetSZOVnYsvvpiHHnoIn8/Hddddx//93/8BlBUgAfbYYw/++9//cu+995Yt825hlRIgDzzwQG666SZEhK222ooddtiBs846q2TZbbbZhk033ZRnnnmGq666ilNOOaVkuSarFiu7ANlIlO7AbjkaWo5eMe1bXagCSwBf6w/JDJWKkekNuHxtpxYNOn2t30EyL2IyDzFuGZFN/GOtiRU+EGf0jAo9qGwVo5TC3/5rUv2fAYlRPOmyQM9hYHg+MERPTw925Aic0V9QXvBQ2OHPVOjPZFIjOeuX0nV6g1Jv30Tx0cNk/y8oEXT2+hkRTN5O0sVN3YdOP4rt/1DJdozzNun4ZWSc1/GG1cr7r+ZJgIu4r+Amb8UO7Ykb/ysmXfoL1nPhtgsS53jXPT38VXTianxtp6LLuGIr5cOOnoxT0Rqq0IrGCxlgd5wLZnk2gc3MEEsESaaCKAVzF+4Po5MtFMthZe8bK7AVVs8NiKQ9a1rV4iX/KoH2rY/2nTzl/uZFJ7eGDNxVyN2ntd8vGnzboXzvR+J/YTyjqQIcVGBXVPSrmJEfQrrQHS6EihyBbjnJs+6OnZe18m6cW3Sj0NHj0aF9EXcZkrgGcd8B3Y4O7oFJXk/v87cBnvt18WWz0Z0Xl43VWg8iaTJDx+EluZr4/hAk8xTu2DnYrd+adluNwk3ekU32leuzwqTuAELo4KcwqTvHLdtVB3bLUdiRL82YlZyIQ2LoWziJKxjPZp8PQpEt5YXAsAOfINRxBkoF8YX2Q0w/4KJ0T8nnWClFoOVo/JHDcJJ3IzKEttbE8m81qfyybPiYWhOKTAXXeY6qz5JqxxfYuqHtKmUTDO9LsMFJhEQkm2Xbh9bVw1zUUCO1LEpUEsBmg3g8zvCwZx0+lftFKUU4sBXhQPlEelMl5FuP0dQjlL+OFqECcdBIhoH4ncQzr2LpMF3hnQnapUVVS4ez7teVsVTpe2Es82bJ7e6k5z27XSZbJhYmk4HcyG485qMXwz33bI/HhpQJgqNXd3HNIop0kVWkt90VzSuxNxnJjNDqq98qOud+Xa9Y/a5HZFIMzllps8l7gssuuwylFMccc0xefKzGBz/4QYD3RMKnVUaAvOaaa7jxxhtRSvHnP/+Zo4/2RJVyAiTAvvvuy9NPP83dd9/dFCCbANDX5yWQKcyA3WR2sEN7oLC8BCcF7tjKWhtf2w+xAtsVlVcqhL/rb7jJm3DjlyPuW6C7sUMHYIX2AeXHpB/ApO6iWMDzBCg7+q2yQla+pG99At034sT+hBu/EkiCasUOH4QKfp6BgT8BZAXIz+Emb0cyj1M8ePba87X9OO8qXwvGXYJbQybg3HS3Gi4GjYUr49Jjvg7nReJ9+xJs+xn+SHHSmHTs7ySHv0uhdZabjZFni65LVHITN2AFd8EZO6diScGHZ5FV7KZo0veT6tuHQPe1aHud4mPMACbzPFhrYUW/58VLlTh5ix0Vwgofirh9mMzDgI0V3BEdPgydy9StWnBGfgFmYryjANO1juzLZjTu6Ijij+yA4x6OiV9S5SgLZa2BDu1XtFUpP0wz02jNKGmIEaFB0Nl6lFJgrQvua0yeaHrJM6zoCSj/B5HwQZjEleAuBt2JDu2Nysa1052XIM5riPM8EED5t0Lplmw1HVidf8Md/Hw2bEDjksNMHe9doIL7oIJ7A3hhCSaEP9D21+gdNUCcOV1D4zvsjbHaTkf5NqIRmOS/wPRXKoEbvxQrehJK1ZaoYiYxzqukB79EcXKx3M8kJnUnge6bvRjDykLZ6007I281UqO/wElcmf1r4v0laPt9WP6t8YX3wfJ9KP++VEqhaswS7QmWlScwS5d61vczKUCqMsJMITqbwGNlRiRDbOx8xmJ/wbjeu97n35Joy/EEQztPuV6lLPy+TUln/kd5AU0IlFnomy1y90pnZyfBYLBK6dlDRAj51mc09VCFUi5zW7wxykDiXp7vPZmM6UdhIRheHvgp81r2Y72uH6InPPtzwjvx8uCvKtStaPGth1ZhXh++grQZJGwvYF7kkyTdPt4Z/VfpfpdwgTZFomHu/CZ/lZoJZXJ+H+Xrl2yp4tiQMNElm6Lfk26Ky968mGPWLW99VY6pWss2abIq88QTTwCw556lE2KVYs4cb46YM4Z6N7PKCJAXXXQRAIcddlhefKzGhz7kDQKee+65KiWbrAqIyCplAbkyYoV2IxjcFZN5FNw+lDUf5ftAhXicPuzQXtihvUru93f8CSd2Pk7swrx7tPJtgi9yLFZo15r6pO3V8LedhrT+GE+ECqCUore3FxHB7/cTjUY9a5Wuv+GM/RknfnF+Yq99H8JuOQ6rzthpYmqJI2aj/VtjnGerCAkepcTH7B4AksPfwfJvhZV1w3dS95GsYE3oYMqKkCKCW9Sai+28ipu8l8pZ2MFznYfJw3UXJE5m5OcEOj3xV8ww6eEfYZLXQ86yRLVghQ9H2+uB6UdZPejAzqgqVi5WaA908NOI8yzi9gIuyloA1nqY+IW4sT/VdJ1L0TvoCZBz5ixEKYXd+kOMbyPcsb8g7islj1H+bfC1n1W13zOK8jXMizl/N+g1saI/QiUXIcnryYmO4IBqR7efhfJ7K8HKXgsr+o3y3bPXRuUE5Eld3wCr5y4keRuSfsD7TNN344kDhQLBTMcAzbpX2xuiI0eignuWtVwFT5xaPjgXeI25q++NbjvcO88GCY85JPM03jCxgkWWjCLu4rLXeDZxYhcxnqV8Il6MXTfxT3zRE2alP2JGSI9dUKY/2V657xBp/c6MPsOxWIzRUe+dmpvAzAS+0KdxM09R/nw1vuDMuH83ChGHgYGjSCX/TeF5ZNKPMjBwBK1tP6ZlGl4hrS1foG+wlCcHeDH/ArREDpxy/Y0gJyjNpFhdLyLC6wOnsnys8qLc3OiRRIMfYiT5BM8s+yKSHbtIgfi/dOwqjKTZsKfYACXiX4c54V1YHr+dUgKxiIDu4bY3P07hvaF7/fjs1XBLLEKWEhXBc4OeVBaYZCWZjemYt3bMefEohRKD5MXG3LZCgVJlE9XosoLneNuGxwYfYSg9SLu/PlfqnAXkynS/zAbNGJBNpkMubmo938mZTAYArWcuvvhsscoIkA8//DBKKQ48sPYv9txqTm9vb5WSTVYF4vE4yaQXa6uzc+VfxX+vopTG8m/ZoLp8+FqO8bJ6mwFQ/ikH5vdEtnFrgUJr2XGrliC+6FewW44DMwgqMCkRT83t6XkUuwuXwsUO7YGbWRMTv5yKQgKUER8L0aTjlxBq87JApsb+SDXLMcnGayxqR0zWSrIYx3kRiZ2HqssddyIuJnU7YgaAAKn+AxHn5eI+yhhu7E9IcA/87b+uqy2lFMq3MfiKt+uWo7EiR3jWdpIGfLiJ6zzh0/Qy7n5Z6hpr+rICZE9PT74dK3wgOvQZclnFxR1BMg8CgvJ/eJKV5wpBz82eXwNx38Qd/Cy+zovQLSchqds8a1VrXVRw54ZarSnlR4U+DSEv66xknsYd/TmkHxgv5Pswyn4/kvh7w9r10F5Cl85FReEmaiHvUrtwB3RoQYP7lUUFqEV4VdPO7lw/IuLFPVT+vPWlm7ydylasBjd1+6wJkE7qfqpaRksCJ/1ffMGdZqwfuXulo6ODQGDmLFX94QNJjf0puzg28XOwUKqFQKRxSR1FMmTSjyESw7bXxbLXnHad8fg/JomPHt737MjwqQSDO2Hba02p/kh4f5KpBxmL/53i704v3EdP13lYDYhbmUw/RTL9BEpZhAMfw2evVvOxK6NF23Dyrqri44LW41mt/WsAvD7025LZrD2E5bHrWLPtWML+Yi+XTXpO5+neDL3xO1HZJC+Ci8Ii4N+QvuRk60tX0qQyb5Tsk5uP3TuxB5O3TbR2HHetLnTJHv9bY3CxUAi5GJMTRcx8UpqCeJMiuSW2YstJS4Q3Y2/UJUCOjY3lFzdWNQGySZPp0NHRQW9vb13WjDnX69w84d3MKiNA5j7ghQvrj4tkzDQCyTd5z5C7h9ra2vD5fFVKN3k3oZSGGt3daqWSu76XDX167WmrEzu4C07yX5SfdAfwhXYHHDJVxEeluxDjAkMVSrm4WfcnERc3lcv8Wx4DaBVF+7fApO7OWj6WP8ZN/xcrG0NyKniZvl1So39E3LeQzAuU1hcFk7wOkzkU7dsCk74vm/G5Ex34WFmXUpEMSKJkfEWlfCjfpvm/tX8zaPseJv0kJnkDYkZAEpj0o2CWjB9nb8TA2JbA4KSBhVIKVLv3u24H3xpTuCozhw5sjXGeaXCt3vQoM3AY2BtghfbDCh9ZtDggksKkHwdJonzvR1uNEeGUb1Pszr8h7mJwe8Hq8axcAePbFBM7B9ycC/40LCP1PHT4IFT4s3UvesRiMeJxL47hTA5EdeATuBXDISiUtQ406NrXgkgaJ3aBZ+2YfYa0f1vsllzcx2oVpGe2g0VtTUwONM1yU2Q23K8BtO6gpesfjA0c4SWQy08xHJTuItJ5IdqaO+12RIRk/CJio79CTF9+u8+/HS3tp2NPY2EmNnZ+lRKaeOzvtLZNLR6wUoqujjMJhT7ByOj5pDNPo5SfcOhTtLYcjb9C4rtaSDuvs7T/WFKZJymMNdoS2p25Hb9E50JQVCB3v8ymAOm4gwzGriLpvIxWIdrDuxH2fzi/OLh05GIqL3ZqMm4vSiky7jCDyfuo/G62WB67kbX8xdaolg6z+dxzGUk9y7LYzThmlLBvLdoCH+KexYeWrKlcKyK5TNWTKS82ZvfnM2ePx3l0CsRCEZWNLVmcKXv8E5eiuJBGxttxs5JlKWvLe/vvZ7OOzcuc0WQWL/bCIXV3d+P3z/5CVJMm71Y22mgj7r77bu69914+8YlP1HTMpZdeilIq76H7bmaVESCj0SgDAwOMjNQeMP+VVzy3t6a7bROAgQEvS1zzfmhSC7MRLzTQeopnZTMpCY5HsO1UlI7iC+1NcuQnnnBWxgLPHzmCdOwyxAxVbjSfadotU1dRYbR/G4JdFwCa9MCRZFL3VzlGY/CjcSlt3Vle9DFZt27Ac4fODbMFLEq5gls4o7/COK8UW/GpVnzRb2FHDhmvO/MSmbFzMckb8FyBvVifXobpyhYDE7PTixgk81Q+A7Wy309v3y+AmXWRnAns8MGkY+fNUO0CznO4oz/BHfsdVsefMJlncBNXgfMi44KTQgd2xN92GspqzKTZc60vFtZ0eH9UaF+vbYkj1mrIyI+R1C0UWyNrIAS+TSDz8Ph23Y2OfBkVPnxaSU9yFm2dnZ0zuximu0EvyAp9pS2JrJYvz1gCl0mtSZr0wOcx6fuL+mPSD5AeuB9lb5S1fC4nUljoWYyvp30b1lbO3mBG+5G7X+bOnb74Vw3L9/7/Z++84ySpqjb83AqdJ89sJCxJJIOSFCQHBQRUchIUBEEUQQmfEhQRBFFBQEElKCxZgmSRJCgIiOQcdlk2TJ7pXOHe74/q7ume6TSzE3Z36uE37EzVrXtvdVdXdb11znlpnPFP7Mzfcax/AwojsDVmaM9xi1xOJX5DKj6yfrtt/Zv+ri/T0vEgujG2BzWO8w7Vr2sutv1WlfW1EUIQDe9NNLz3cvUzHMftYlHnfrgy72g8VAc1kX4Ax+1ktY47S5zUh2NZVuFh+2RFtPUm7mBR7xkobPKGYt3xPxINbstaHX9EiBCJ7AvUim5OWq8A4Mo4tb6bCASOHKi4vjG4IY3BoZIWLy47vc69GaKcyAdgyVITGalKHbGHxMdcPwqcokhKpcBSOkppSJmreCsEWdck7Wg4CjLSJCN1JAZSajjo2K6Go3QUGrYrcJXu2SJJgYYkZtr8y32BvWZ/xLzovLr2MR8tO2fO5D2EWmFQTGxllkpj+qwS7LvvvjzxxBNcddVVnHTSSTUzK6+77joefvhhhBB85StfmaRZThwrfxJ5nay3nlez7D//qVa8uJQ777wTgM0226xGS5/pQP5LmZ9+7VMPkyFA6sbaRDvuQQ9uR/EXXaGvSbjlioJhjNBihFsuxzvlD7/5EOjmZwnETsAI7VJmfTEaRnAXbysRQDPWpdwX7GKM0E4IEUKIAIHW60CvlSYnUVh4z8eGX6J0vNznMvWTisTH3JKS39yyYqaLtJ6Foigab4NB7MEf4SRv9FpZ/yXbvW9pHUk1iJP8A5nO7cn2fgs7cXVO/KiNEBpaYHPP5MZcn0QiQSaT8aJjVrIHHMKYhxar5io+dlTRf1L1YfcehBv/KTivUxrtppDZx8h07Y90hhsEjS9CaAjz04jAZ9D0GWjNl6M1Xw7mViBaQV8dET0BveNhjLab0DueRmv5C3rr7d7v0aOWW7Dr7OwEJk6sVkrhDF6C3bVjBfHRO0fosVPQI5P3RdhJ/nmE+OjhPQxRNV2YXYxI+SimiUA310c3P0Plc6qOHtgG3Vx3QucxmQIkgBAGgfCXiDT9lEjT+QTCXx438dF1l5KK/6rSWpSKk4xfuhwjVLv+AWgILbIc/U8c/YlrcXPO6SORZKz/kMw8VrWPfPRjQ0MD0ejE1xaOp5/i495Tc9d8hXd99a6xyezzvLfsKF7+ZBdclajZlya8Ejim3lazLIRCEjJWr3ueyQop1sU91l7iiYtymJg4lKbtLbMKx2DO0RqBqwSDVoDObIhPMg0szTaxzGpkkdXEUquVRZkmlmaj9LoN9DmNpGQUS4axZIi0G8ByA9jKxHF1LNfAUQZSadiugSMNMm6Q7kwD7/TP5OB/XsPfPq5tcAhDEZArUrq+j8/KwPHHH8+cOXPo7Oxk99135/XXXy/b7uOPP+bkk0/muOOOQwjBeuutx2GHHVa27crEtBEg99prL5RSXHXVVYU6ftV46KGHuPPOOxFCsM8++0zCDH1WdPwISJ96UUpNmmO6bqxDtO1GYjP+RaTtNqIdDxKb8RRmuNRZzQztQbT9bozQl8jfZAl9LsHG/yPSfhNChAhEj861LieQCBABAkVRgYHoN6rMTAAmZvjAoSUiiGauX6H/ktkSbL8DLbBdSX9acHuC7XehR44Z0Ud5gXEIRa5uXMW1I7HjFyNlEqvvZMCinIstKoXM/h0nfjGZZZ/DTT9QdR7Dke5Sliz0TNJamhTC/TdKrVxlP8yG49Abz2OoDpUq49VZPxKFzPVQf5CBAtVJtmt70su2I9N9IFb/mbjZZ6u878uPEBpaaC+MtpswZv4Ho+Nx9IZTEboXPST0GWjBzyECWyDE+CSdTLQA6Sb/hJv8HZVefWFujNnxD4yGSmYaE4ObuqHsfIoRgW1yvxULSd7vZuPZdUcljhehlktBNDBS2NIRWjPh5ksmdHzXdQt1zFeFGm3JwQuoVfc4m74HJVOj7jud/hveeb4aklCouuP4VDGYvJXqr41OPHVn1T4mu/7j0oHfUOn7gFIuA9bLWO7SOnrSaInsAYCuhZkZ249qYrJAY2asfvdZs0KZjCEBscy6MvvlqNI5OcO29VKlPTFSSujNhFiUbWGp1cyAGyUtI7gEsKRGyjWwlYmtNCxp4mLiSA2FjiU1JDqWK1DoOMozcnPRcZXXvyM1pNSQyvvXyf1YruCcV+5iuwfPJW5V/xxN5wjIvAnNZP/4rBqEw2HuuusuIpEI//vf/9h0003ZcMOhqOsTTjiBDTbYgHnz5nHVVVchpSQWi3HHHXesEiY0K/8e1Ml3vvMdmpub+eijj/jqV79asehnJpPh0ksv5atf/SpSSmbNmsUxxxwzybP1WRHxHbB96iWRSGBZFkKISYuY1Yy5GMFt0c2NKkZY6YHNiLReRcPs92mY/S4NM/9NMHY8Ihc5oJvrE265gpHRhxqIEJHWa9H0oZtYM3IoRmivoTZDIwGCcMvlaHrp/hvBHalVm8kI7ohmbkKw7c+EZvyHYPv9hGY8R7D1ejRzQ8zGszCiJ5CvIqKUqEukkiiUUkjl/VtTmFJx3MTvQS6m+o0dufU2Vv/JyFwqWDXc7HNkuvYh2/k5OhffD0Bb80Ks3qPIdn8J6S4emoZyULIXKeO42WdxM0+WrC9pp+qogzcB6JEjEdGTkIQKspVER4r2XEVHVfJTLFCWRDqOR46RXIyyX8BN34bVeyhW79fHJEisqIynAKmUws38A6vn62SXbUl26Xa4ZdJbS7ax30Rok3sdVCqbqytYHU2bQaDlD2iBbYAAEEQL7kCg9SaMqg9MJgbdWIdYx4OYkcNBhL2FIoIZPZJoxwNoYzQzqZfu7m6klASDQZqamka9vVIudubvJPu+R6LnGNIDP8W135uAmdYzF5tsXQ94bKSsv7C/17dicODCmu00bTXC45w6PV5I2VejhYvrVjcMG2u9UFcOYtkf4tYq4VKE4/aRsopKVAxDFhyea117NXQtRkdsyGR0XvN3CeitlMv4AFi79UxMvb7vZq6yiJrlMzeGajmOrOnoDKtyJmWp8Uux2JjHVhpxO8ASq4HFVhODRAENRwpc5QmEWalhKR2JhisFltQLbYr/9frVkDnB0XaHxrNd71+FwJECmRM8HVfDlRqu1Ik7ku0e/jkfJ8t/luLxOPF4HCHEKvFww8dnstlqq63417/+xcYbb4xSirfeGirv8cwzz/D2228X7lU22GADnnnmGTbeeOMpnPH4MW1qQDY3N3PjjTey33778fDDD7PGGmuw4447Ftaff/759Pf388wzz5BMJlFKYZomN910E6FQqErPPtMBpVQhAtJPwfapRT76saWlBV2vldI1+XjmKeVNVszw3uiBLbCS83Gt5/DSrr+AGTkEbZhxjhA64ZYrsNM7YyWvQ9pvgQhgBPcgGDsOPbBpmf73Jxu/JFdrstyNhSQQO25oDL0DoQ83ZtExG0/HiB2Hm/k7yu3EiV9cc79lGYFLVwJNVH4WJ513qOX0PYTnRmkn/0AwUNm8w808gtV3AnkhtqevGYC25n6vF+d9rJ7DCLTehJP8I27qViA9rBeBFtwZs+l8lP0aduIPKDuXNqWtjh7aBSP6LTRj+SITlNuFk5qPk74T3B4QOkKfhRE+GD1yAEJrQilFtvcYlPXksK0dUF2UdwFluaIk65w9ANJ6BmvgLIItl03weBOPUmrcBEilFM7A2cj0fEprWNbCQmafQg9PZnZI/qFItTkKECH00G7oE+gqPVo0Yy7h5p8Ravqp5+YuIiMMrCaK4vTr0aT+25l/kEn8PncN8GwtQOFkdbLJPxCMfY9Qw2mTVv8TwMo+DtRj2KN5hl2jwLFfx3U/qtkuGju6okHZVGPos7Gr7oOOK3tY3H0MmtZEQ2R/IsEdSo7F0QqQWfs9OgcuIZ5+EO8aKYiFdmNG0+mEAhuOaC9Vlu74dfQn78Vxq5csces0ojO0Zj494wZMfagWc9CYyWdm38n7vRfSlXqY/HkjZKzBWs3fY0asvnOX5Q7y7yXHMWi9WXa9HCYgQq5GY5GBTJ7iOo6Qj5z0PltZR9DpNuJgko9+zBvYWA7YufOfLDKfsaQi/7DXkZAXHfNzsnKCo7fnntgoC5dcT7yUMhcN6Q4tG5qj9+8XH72MZ/f6PxrM0nvhfPRj3oCmnuxCHx+fUjbZZBNefvll7r//fu655x5eeOEFOjs7cV2XtrY2tthiC/bdd1++9rWvrRKRj3mmjQAJXhr2Aw88wJFHHklnZycPPfRQ4cvTbbfdBgyl6LW3t3PzzTez0047TdV0fVYg4vE4tm0jhKC5uXmqp+OzgjNZ6dcThabPIdT4g7raCqETiBxEIHJQfe21KJG2m0j1HI4qRGzkv0grQk0XYQS3qdJDcV8tGJGDUMqBxJU5M57R4aJwlVsSk+fFDWhoCDTRQv3CjNejzPy94lqlslj9P6Q4CrS7vxmAtpb+oVm5C8h27wMqTnnxUyGzT5Lt2hNUgpKbHfkxbuoG3NQNaMEvYjachpt5ADfzCJBFMzdDDx/iibsihKjgTCut/5HtOQIoel0VKCeOHf8ZdvJ3BFtvRtovlREfS+c6tUhk5m9I93Q0fW5hqVIKZC8gQWubNFFoeejv78e2bXRdX+6HYTL915z4CKM7xhnTZ215EEJHC+6MzD5B5YcBLnpo90mc1egQQgNR24V4PBlL/cf04EVkE1cOW5r/DHuvfTZxGZqxOsHIwUwW5aK+y2GYn0HTGkbXt6rHoFIbtzIKE0FT7Ai6By6g8vnWxXLew8o9VIunbiMU2Io57X9B1xpL0vXrScHOWG/xUed+SJVm6DOpSGQeI5n9J2t23E4k+JlC+3jmGT7sPBpVl4icJy9+V2bTOf/A1JuHtlCSnvTjLInfRsZZSENgU5pD29Ae2YOG4MZlRfPB7Ot0p/+JUg6NwY1pD38BIXRe6f4JcevtUczXExaHp197UYZD1xeVi36UErrcGFkZwM0JjrYER+YjHCmIknZRxKQnOBoo5YmKSmm4SitEZMqcIJkfp/Av+T48JODkoiHdXOSklF5WyRCKHR+8mP/ue07JPk12uv4Kh1L5N3Jyx/RZJdl7773Ze+8VM7p+Ilhxr6QTxO67784HH3zAddddV1Ca+/v7AYhEIgWl+YQTTqChYXRfYHxWXfLRjytqRJvPikVegPTT9cujmxsRm/FP7PRd2JlHQVnogc0IRA5HG4N7qRAGgchBWMk/U1+k4hDlUn7zpjUu4GQfQ1duSSKY9zVdVIn+sVFKlV3vZh6CYTe7vX1eamRb8zBXTjVALUdWCsX5y7eT2YfJZh/J/+Vt5bzvOUnn98fYADN2Mnr4S0NDqzTZ3m8AVVKXZR/Z3qNZOaq5KNz0fWix4700/PQduIlrUO773mptLnrsG+iRowousUo5KHcRMvsYyvYiYLTA59DCe09ZFFReIGhvb1/ua5Gb/NOYtxXGp5Zr7FooGUfa/wMl0cyNEHo7RuzbuSg4LxqvFB1hrI2WM8ny8RitAGlnHi8jPpZDkI1fQSB80KRFQQqtpXYjIDyGVHtdr+e6IzFqmqhNHU3RoxhM3o7lvEfl62D+Kuatz1j/ZWnvd5jb/me6urpwXbfudP0lfWcMEx/zuCilWNz7fdaZ9QRCCNLWm3zQeRijedDhxTtXO7YEIWOtEvFRKovXO0+mN/04Q5kLgrj1P7rTf2fzWTcSKMrksNxeXu48hf7M84COQKBwCOqzWL/tPJYkH6XStbWcFuSlXntRiXkcKQrRjIV5IkjYOnFiXnp17hqacQRuTnB0JDlRckh8VMozpJHkajcqgVQCRw05aytF7u+h6EcvLXvk65cnH/noukPjqKJ2KUdx6Wt/57SNhx7wTHsB0sfHZ8xMOwESPKHxpJNO4qSTTgLAcZzCRdfHpxx++rXPaPDrhdZGaA0EokcRiB41Lv0FYt/BTj+Ekp3UK0LWkwKs5BIc8nEHOedKPOFSVxraiJtvgTDWr3hTrpz38S69ntNnOhMklfFqw7UOFyDHJXKwnJFI6d/KeQur/0RMeXahTp6bvg9UrZpiMlcfc2UQIMFJXIMR/TrO4C+QqRtKV8pPcAd/hrJeRm+6AJm8BjdxPRAvaqQh03fC4AUYzb9AC25fqJ86WeTTrzs6Omq0rI5SWZTzVu2GI9AQxjoIc/PlGr8SSmWx45fgJm8EsrmlOlroywSafoLZfBl2/2l4Luj5lEYHYaxDsPWGgng8VSiVwU7fh5N+EKXiaOanCUQOQzc/PSXzGa0AmU3+ifpKTiik+xHSXYA+wXUs8wSDuxMX0arRt0KbTXCYAVs9GMZqBIM7kM0+Q/l9F2haG8HQiitwa1qM1Wb8la6+c4in7yF/jSkv2OdxSWUexbLfZelS73WdNWtWTVE5a79L2qrmlCyxnPdIWy8QCW7Fxz1nMtooax2Fi4HKudyXY1ZjaY3+j/ouozf9RO6voahMgIy9gDe7vs9ms/7izVA5/HfpsSSsdwrt86Nk3U5e7jyl4rjeHo58jfKCX55ygqTtwBLZRD6lOl8rMu1oyNzvWem9AiBw8tGSSuRMbLyoR6k0r4xGkfg4tLeeEKkQXg25ovRvp+TwFoUf1xUopZUIj4X9UnD12//m+xvuWkgDne4C5FSYwvgmNKsOV155JQcffPBKmym3vKwcdw0TjGEYvvjoU5W8oOQLkD71kD9epuuFZSrQ9A6iHXdjhHan5NImmituM5rvcuVqFrrIMkY2CqPgJl4GEaX4Rqyn34s0aYwlCJhOhY0mGm8f7MELUDnHUZmr/1kbg/ERSicB1YvVc+RI8XGoATJzL3b3friJKygVH6Hwvqk+nL5vYS3dAnvgbJRbWqRfZp/F7juJbOeOWF1fxIn/GuUuG5ddyEdALr8BzVii1nQQIYzmX05I1JtSEqvvRNzkdQyJj+CVNfgb2Z5D0IO7EJr5HGbDj9DD+6NHDiLQci3B9gcKzuNThXQWkejcjUz/qTjZR3GtZ7GTfyHZtQeZwV9N+nySySSJhBchXe/x4lgvMaooclXLNXr8EFqEaEP10iANTReM+dhsbDofISKMNC7xxJvm5ksRwhxT35OFrrUwq+23rDX7Jea238KM5kupfX7WSGb+Mar6j5bzQV3zsewPsJ0lpO3/1tW+mObIXqzbfjneuar4PfHe35bwHsyIHVpY6so0i+PzqRixiEt/5jkSuZTqrtRjxK03cwLncCSyiqGbUpUEyNJrpq2GxEfHFSyzIiyRnjmOKwVZ6aVRpx2REx8FWentr1ICRw3Vbsw7aKuc+AjgDhMfgZzpzFBBGalKa08qvIjH4qjIoRRtL+VdugLpUvTjpYv/34v3AN65ZXDQy+TwDWh8fEbPySefzJw5c9h7772ZP38+qdSqY5RYD9NGgNxll13YddddWbBgQd3bLF68uLCdz/Smr8+LBPIFSJ9a2LZdKOvgR0BOLpo+m0jrNcRmPkek7RYi7XcT7ajHNXXsOLi4SmIrF1u5ONoaYIw038mjh75IsQDZnTegKdR/nFqc1G2530YhKor6UiNXBKRdLWoHQID7AfXtfxaZugWr5ysot9uLRhm8CLv3MGTmEXA/Rjnv4CauwOrcCXvgbNzkDSj3kzHPf6wRkNJ+DTd1K27qbpTbjRAB0EeTRq2jhb6E2XY3mrnJqMaue47ZJ5HZxygfKeWinLdw07chtGaM2DcJNP+SQNMF6KGdV4DIR0mq9+tF721pzUQr8Rvs1N2TOqf8sdLS0kIgEKhrm9G9jgLHfmkMMxs74ehxRBvPAREpzAFAiBYaWq4iGN5z1H1K2U8qeSvZzGM0NJ5JMLgzxYKNaW5OW/uthMIrbn3R4Rh6G5HQDgTLGMGMRKCUVYiWrUdQ0kS0rnloWhQ791BrdOiEAp+mNfolNpp1F62RvXJlLzTC5vqs1Xoh63VcWXK8Jqw3cWvWphX0Z54DYEnibxVbeZGLlRmqpVgq4rlFQqlUniDpSEG3HWaZ20iWEHnTl6QMYimDlGsgCZCvCZkXH92CC7jAVfl+88vy8xhpgjMaHFfgypxDt/JSr2VxGrYs/bnjw9eAoejHtra26RvAo6box2eVwXEcHnroIY488khmzpzJEUccwYMPPojrjq6U1MrItEnBfuIJrw5JMll/4fR0Ol3Yzmd640dA+tRLXqwOBoNEo/V9SfcZXzR9JlqRsYpuboVrv8iojTZqkDeukcX9ugtIdO9OMHYSoYYzRlw/NGNNtND+yMw9gKKnUv1HESuq7zhZCFQuskULbI2b/msd2zjokUNwk1dN7NTGEYUqpNOXWzs6XHCX4CR+jRb4HG7ymqHlJX1mkambvKiZwZ+ihQ/AaPrpiFqSSrngfgII0OeU3GBLKQv1ZeuJaJP2e8jMA7jp23N95tHRwgejRY9GDv5fzX6MluvRglshRLhm2+XBE7+rp/86qVuqRxhPEW72aaTzbpUWGtnEVRjh/SbtO2VeUBpNtKwR3BU7fRf1RUEq0v0/IDN4GZHm8zCCu0/4vgkhiMSOJxw5gmz2UZTbg6bPJRDa2RPVR4FSknj8UhLxKxhK6ZcIrYWm5ksxzQ3RtFYMY7WJ2JVJwTTWBgJAtUhVl4C5MUuXPg/Ul64fCW6NrjXjyv6KbYQIEw3thCOru11XmlNz5MsAxIKbsl7H5QAVayt71HPu9qIDlVL0pZ+r2EoicmnLZdYpCjUbi3GGLXOUju1CvwxjK7MgTmYdjUxOcCx2r1YKbDQv8nGYsFksNNbyIRnmyY0mwC27jRj2AypXC1JJGC6wohRKSf6x6G0CS7yHG9M1/drHZ3l57rnnmD9/PrfeeitLly4lmUxy8803c/PNN9Pe3s7BBx/MYYcdxrbbbjvVU50Qpk0EpI/PWFFK+RGQPnVTXP/Rf3ixYhBsPJ0RX6bHgfL3AXmX2CuxUjeWtve+1RNovggt5Lnd9Q7kBch+r5E2C7P5MszGs+qYwcj0q+VDgOa59OrhfXPp69VNANDaMBu+ixH97hjGm5rIiXwNz3pqgNaHi0z9FTdxNbW/VnlhDDJ9J07/6UNLlYuT+ANW53ZYXTthde2I1bk9TuKPniiJ54DtOA6GYdDc3Fx5BLcLq/tA7O49cBO/GSY+5uabno8cPLvGXDWE+Vn00A4TLj4CKPkJ1YUvhXKXTPg8xoKTfYLqz/Ql0nkLNSYxZmyMxQE7GPsmoxXhlfyYZO83SQ+cV6YkxcQgtCih8H6EY98gGN5z1OIjQDz+SxLxX+OJj5B/QKVkPwP9pyFl70otPgKkMk/VSBvXMfTVsDObk8lk0DStruhqIQK0N55atU17w4noWoygsQYhs3JWQDlaIl8lZK5TZtzK16NoYH20mjV5JU3BLenNPIujhpfYGMITE8sY1BXEx9J5yGHRj66EhBugV8ZwMAvbuFIUxEfvozIkPnq1HDXcQt/FYwz9XvwSiDJhcVquUKAo+jffTgNMfWgbWUZoVDlRdGQaNiilcdpz94wqXd/Hx2ckW221Fb/+9a9ZtGgRjzzyCF//+tdpaGhAKUVXVxdXXnkl2223Heussw7nnnsub701lprdKy6+AFmFfLRkKDS5ReZ9ViwSiQS2bSOEqHrT5+MDvgHNiogR3IZw67UILV+T07v0ieVIAqhHvMokrsR1PiE9cB79SzZiYMmaDCzdnEz8MsymnxJs/zu9A577asfsLxHseIzQjH9hhPdFDx+KEfs+1YRTYayD2XzZOKZAO+ihvby+RZhg67VAJeFJgIgSbPkjQgQxG79PoO1eRGAbL3pTRBGBbTBbb0UL7sTwmykt8HkCM17AaPg/0IbXSp0c4X58pZIsynmd+qNsJTLzN6T9jpe63X8abvxCkJ1FTZbhxi/E6f8hSqlCSm17e3vBCGBEr04XVtcuKPvFOuZQI8pNm43Z8ts692f5EdoMan0tFdqK+hCw3vqtlevKjTf11AtVMomVvods4lqs9IPoxnpEWi7Hi0Qd3S2ClboWO/PQcsx48nDdHhLxSm7f3pkhPvjzyZvQBBBP3cPS3uNQFdOSNYQIMbvtD3R2esdKe3s7hlHfdbE19g06Gn/A0LFikBfUWhuOp73xFDL2uyzo/i4Z+/W6590Y/hKrtV1cd/s8hhZjduxgKh23Ap2G4GY0BDdiWfLBiu2gcmpzuchHoMjl2hMTB9wwgzKCxMDN13GUioQcup90lSi0t5WGRBsR7Qh5wXFINCz2p9bLuJIIAYbmXYf03PXI0NzcupwQKfKP4cB1c6Y2kkLkYz4Nu5CKrTzxUUnBQMae9gY0MGRCM9k/PqsWmqax2267cd1117Fs2TJuu+029ttvP0zTRCnFhx9+yM9+9jM22mgjttxyS37zm98UPn8rM9MmBXssPPjggwCsttrK/QTUZ/nIRz82NTWh61NbZ8pnxccXIFdMzNDOGDOfw8k+gXQ+QmiNGKHdsVN/JT14Hvn0u0oUu2DXi3I/Id61R8611bsBULKHbOJK7PTdBJvuYGDQG3PWGt9CM4ZS9oUQmA3fRY98DTd1J8pdBCKA0GYgtHaEuT6a+RmEEOihPXBSt+MkrgH5CcUF6IW5Jcp+BU8gqSY46QhzM7TA5wpLtMAWhGY8hp2c76Xx5qO3tGaM8Ncwokcg9KEbED2wCXrbLSN6NoJbI90kyn4RhUQLbI2meTXc9NhxGNFjUM47oByUCCHTf8XNPgVI0FZHWY+O6nUfDSPTsfPn+MmowaMjM/chzM2QmXsrtFHIzN04AybLFnnRqR3tDQBI+21k6lak8z5CawJjS2Tqd1VdgutHgPHpSTV2McJfwcr+o+qc9MhBkzaf0aCZmwPXV23jfXaXz728XooF63IRkEopssk/kYlfAipFIf1YNBFuOp/GGc+QTd2EY72Aaz1LfXK9Tjb5JwLhL43nrkwImcyD1KryZ9uv4TgfYBhrT9a0xo2s9TrL+qob9miikdVm3EfQXJtly54CRhfRJoSgo+n7tMQOZyB1F7azBEPvoCmyP6Yxl1T2f7zXeRBKWdR7Pm2LHcNqrT+tew7DWavlNBLWmwxk/8PQNd07vwf0mWzYcRkAjoxT7Zgu5xvuiYP5taXLZVEkY8rRGZARyAmKMpdWHZeBwrZSkjOZ0UrMbCrNSBeyYDgjBAiVs4sRwnMLL2zo9aUJhaFJHCnQlUQKgam5uNJzuTZ1F8ctFlMF5ARR6eaER7e4z1zqOgKzKCvMj4D08Rk/gsEgBxxwAAcccAD9/f3ccccdzJ8/n6eeegopJf/973956aWXOP3007GsyTOAmwhWWQHyG9/4RtnlP/7xj2tGsWWzWd5//32ef/55hBDsuOOOEzBDn5WF3l7vpttPv/aph/zx4guQKx5CGJih3UqWBWPfxAh+nmzyz9iZx1Cyk5IbUxFDqMSoxccCKsFIYVMi3cUsXng+MItwOEwkEimzMWj6XLSG6unNQoQwo0diRo9EuZ1I63kUCi3wGTR9DtL5GDf1F9zMwygZBxXP7WPewdpFC2xFoOV3I1LchD6TQOP3ofH7Y9v/wn5EQd+hwvwNhDlklqCbZ2JyZuFvJ3UP9sAPmYjoMUXx7WQYo+l8nIEzK29QFg1hbuz1Z79G/VGQAiX7kambqFX7UKZvp2vZDsBatIZvxeq+Kxfl6G3n3X/eN8p5V0OB9RjSWYhmrDGO/VZGC+2BMLfICebDXwsd9FkYkcMmZS6jxQzvRWbgPFCDlH//BYHoMZNmltPX14dt2+i6Xva7i5W8lszgT4qW5NKP1QCp/u8Safk9oYbvI93FxLv2yu1XLVxc66Xx2YEcXkq3M+7u01L24X12qkeuSrcXViIB0nYWsbT3u2SsZ2u2lao/Jz6PLV0/j6HPoK3h+JJlSikW9JyMUlkqnw+HHvoFjHnMaDyJ1ujBox6/GF0Lsems6+hK3s/i+K1knIWYWiszY19hdsOBGJr38CZsrJEbv/w5VyBRw9zQK0VFOrnlUkKfHWIQ70GRUpCVOi4aaWkWts07aA+Jj7W/W2goJPnMC4EmFDIniOrCi4rMR1SamsGGDeuxQ8eWbN6yAS2BprK1M5eketjt75eiVLEUkJujq7zXp6SkgreuNeP91dTUVPF7y7RAKu9nssf0mRY0Nzdz7LHHcuyxx/LJJ58wf/58LrzwQvr7+1cJk5pVVoC8/vrrR5xslVLcc889dW2fr2PT2trKWWfVU4vLZ1UlLyi1tKw8Tq8+U4dvWLTyoZsbEGm+EAClHJzsv1ByGUKbiRH8PG72aVJ9J4MaqNFTOSrdfLl0LXsDmEVLc5KBpRuBSqLpaxKIHkUwegSiZj2rkQh9Bnp475JlmrE6WuP/YTZ6hiNKZXDTD6CcN0GE0IO7oQU2G/VYk4UR2Q89vCdO8mac9J3gLsoJIuP1ZVyAiGC2P4hmrAZaM07/93KRhNUjYz0keuy7oFI4/aOphSkR+hrI7BPUEyHU3dcIeI7pyv44t3Qiv4gq7N7jCXTcM6Yae6NFCJNg6/VYA2ciMw9R/P5qga0INP/Ki/RcQZDuYuz0/SjZj2asQbjlctK938ITyvPvi3f86MGdCMS+NWlzK3ZLH56ur2SadPySqtun+r6Nd4swStF/nARW1/mIVOIqMum/gkojtHbCkSMJx45DG4djQNdXo3bavEA35i73WJOF6/bwcee+uLKr7m1sdwlBNi7U9KtXgFTKQioLTUTL1mVMZp/Fcj6q1QvrdNyGac4hoK+BEAJXpulO3Eln/BYsdwmmPoMZsYPoiB2InqtPXAtNmMyM7c/M2P4j1kllsWjwlpwDdvlzp5NLhx452/z/h4RECx2FRlbq9LphMrm6xo7USStPdMxKQT7dWylwlVYSNVmMGDZGYbkAAxdXaV5MpxDoQtEeaOXTsfVZu2Et5oRnsVHjp9DEyLmXe49mR9rYZW6QhxeAdD2Xa+mCckXRDg8XSBVtWe+V8KMffXwmntdee42bbrqJm2++mYGBsdyDrJissgLkGmusUXLCXbBgAUIIZs+ejWlWfpIqhCAUCjF79mw+//nP8+1vf5s5c+ZMxpR9VlB8AxqfeslkMoXasX4E5MqJFyVZGqlnhHYi3HwR6b5vj6YnaglkfTkDmuaG93JRiSDdj8gM/hQ7fR+xtpsR2vibfwgRwoh8ddz7nUiECGHGjsGMHVNYppRCWs9hJ29AWS+B6ma0gpwAhLkxRvOvPfER0EO7oM14Llej8U3PqTqwFTJ1Oyr7d4ZqnjlAAKPpfPTQLiil0KOv5Zywq0c05kfXw/sj03fVlFKlFPT0e8dLR0v/qPZxuXDfRqbvQo8sX2RSvQitkWDLVUhnEdJ6FnDQzM+imetNyvj1oJRDZuAn2Kk/4x1BuWNBhAk0fA/lLsVJ34tSKTRzXQKRr2NGDkCIyfvKnRcgy9V/tLOP15Gmrxh9xLGOEdxplNuMxLZeYaDnAJTKMFS6optU4jKy6Xtp7rgbbTlrgYbDX6S/LwykK7TQCQa3R9fHVuNOKYVlv4zrdqLrMwmYm064KV1/4lpc2Un9Edhg6B1YllV40F5LVEpnX6I7fgXx9COARNc6aI19nbaG4wtlNQDS9lvUvgYqlJAEjTUBcNwB3lx2KCn7rcJ6R/axoO98lsX/woazbsXUx17CQCqLl5aeQG+mcnSoq0RRPcfibRkRrWijY0udARkmK3VsFQA0Mq6OjQEIrILLdb5/7/dyAifk06uHIh2HrzOEpCMwg0PWOJTVwnPpCLYv13F16vrH8OiC3yMLtZ7z4mPeDVsNewsFrZYvQPr4TCQLFy7k5ptv5qabbuL11736ufnAuEgkwn777TeV0xsXVlkB8qOPPir5O/8E+JFHHmHDDTcss4WPT3nyAqQfAelTi/yX+Gg0SjA4NQ6/PhODEfoSRmg/nFytvnykQvnbKw2hzUTJ6oWie3OCUkveATvXJ4Brv0Qm8RvCdblhT0+UXIwdvwRl/3fMfZgt16GHdhqxXGgR9MjBpbeiod28uouZB0AlEPpaaOF9EZoXmSiEwGg8Ey24C27qz0jrZZDL8ESUkUeK3nAmQm9HC38ZN/5W2TZ5BhNRHNdA112aGhJj3t+x4KZumjQBMo9mrIZmHDCpY9ZLZuBnOfExbwyRE3xUGiv+C8It1xBuPn8KZ1hdgJw4J25JaDmjPJWSDPYdXyI+Fvfvuh+RGPgpjS2/Wa5xspmngEyVFiaNTeeNqe9U+lF6+8/GcT8qLDOMdWlr/hnh0MSVdBpM3cJoyj+Y+poEzc345JNPAIjFYkSj0YpbxNOP8HH3sbm/vHFc2UXX4K+Ipx9h3ow70DRve02EqSdCvdi1+qPes0nZ7wzbzvs94yzk/e7T+fTM6+rcv5EsHPhzTnysPC+3zG3xkPP1EI7SiMsQCTeIi5dmLdGxpIbNUJCLKqoNmU+RHtqr8ugo3ILVTKkQuXnz5py0zkkY2vjcvq/VsAaf6hjgtcVhlCqOfCRXA3JkinhbToBsap/mD9mHfIEmd0yfVZLe3l5uv/12brrpJv71r3+hlCqIjrqus9tuu3HEEUew//77Vz1PryyssgLkcHbYYQeEEKvEm+Yzufg1IH3qxTegWXURQiPc8hvs5GfIJv+Icj9GIND0tRD6LBz7ZVBJhDaHYPQoNHN9Ur3HVO2zr78ZgJam/jJrJdnkjYQaTvUi8HxKULKPbPeBIJeOuQ8tsF1Z8bHqNub6aOb61dsEt0YLbg3gRcMNXoDMPEhBHNDXwIidgh7Z3/szcghu8lqQfVSKmuzuawagtWkATZvcuxBlL5jU8VZkpLsMO3U9le8EBdn4xRihPSc84q0a1RywNX2804p1QBFu+gVGYMvl6sm2nka6C6u0cMmm70Y2nYumje2hsFIO/f1nVG1jGKtj1viclyOVfpjOnpHnfcd5n2XdhzGz/UbCoZ1H3W89uG69wrJ3XLY3/wQhRF31H6VM8knPdyBXiXDYWjL2a3QNXs7MZu+BWSy0PbUiIA2tnUiu9IfldNKTup9qJUsGMk+QsRcQMtesuYfDUUqxYDD/0KA8XpRjmeUFAU4U2iVlgJT0xEelwFE6UkJWmeRFQydnNCOVyAmRQ2OLov8PRwjQlUKhkAg0BJs1b86es77IerH1xv28slnLp3ht8SBKilz6tRhKwx72gmhK0Wx7+/FI/2K2YJNxnYuPz3QinU5zzz33MH/+fB5++GEcxysLkhcet956aw4//HAOOeQQOjomx8Buspg2AuQTTzwx1VPwWQnJZDKk016KTi3zIh8fX6xetRFCJxA7BjN6NEr2eoYSoqlwQ6CUROTqL7n2a1X7Ugr6B/IRkBXquqhB0gPnI1QKobViRvZHz5mdTHec5F9y0YVjF+OMhh+O34QqIPRZmC2/Rbk9KHchiAjC+FTJTaTQmjHbbsbuPRbcBRSbA+XJp1+3VzpWJhJt4h7cKuV4pkmyB02fizA3n1LhrhZO5hFqpZVK5z2k8x76FKWNu65Ld3c3UF6ANIJfQGgzULKL5Q2pEVo7ZuiLIBqQzltk4r8jENkfbYypy479BrXrrtq4zntoga3GNEY2+0+k7Kw+D+ddbPstTPPTdferlEtP///l/xq+FoCe/h8xd+YzE3KM6/oMHPfj2u20Dma0XEgsvDswZEBT7ljJM5C6B1k1bV/Sl/gLM5p+QDL7Egu6v0WtY2tG08mFsgRJ62Xqid5MZP87JgFy0HoVy61cG1MpcmnTZdYNa5dUAfrdSC4q0jOTUUqQVEMu13lR0lU6DBMwwTOVGep55LEghLf0c63bss+c/ZkZmrh058PW2Ic73rmOtDvMUEaOnHeL7UmpGQEPLXqPM9hzwua1oiPw0uUne0yfVYOjjjqKu+++u1C2Ky86rrfeehx22GEcfvjhrLvuulM5xQll2giQPj5jIZ9+HYlE/JRan5r4AuT0QAiB0EdGuYqi4u+avg6CKIryN22JZATbMRFC0tQQrziWnbox58AtsJLXYIT2Ith4BlbqFuz0fSiVQjc2IBA9CnOKo64mEzd9B6OpdTYC0YY+icY7Qm8re8zk0Yx1CHT8A5l9CmX9BwA384BnuIOku88TINvGVP9RgGgF1TOGbUELTcxNppO6Czt+IRSZZgh9HmbT+ejB7SdkzOVFyQGquecW2qnKn+mJpqenByklgUCAxsbGEeuFMIg0/Zxk33HUU6u2Gkr2YKXm5/7y6p5m4hcRjH2bUMMZoz4fCQJ1zmf0Bl15XHdRne0+GZUAmck+i+surtJC4TgfkrX+Syj42br7rZem6BH0DP6CWufFYGBLYuEvFf7Op+tXi4DM2m/i3TJWNu6RaoBk9gU+6DoKpawqMxDMaDyJ9qJ6vlSoiThy08rtXJkk7SxCFyFCxhpFDwYVb3SdXbVbici5XFdnUIbpcyMFAxlXCiQaqSKXawBbaUhVea5CgInEVvnIyNKxw1qYMzY4mznhiTdB+nTTOsxsSPBhMgIql3qdFx+lKPk4tma9Y6vX1FiSTE343Hx8VlVuvPHGwu8zZszg4IMP5ogjjmCrrcb2YG1lY1oKkL29vVx33XU8+uijvPbaayWiwcYbb8xuu+3GMccc44sIPn79R59R4QuQPnmEFiYYPYJs8g+ALLmlFkD/QDMATQ1xdL3aDaNLyY1N5kGszMMUR8g51r9wrH+im9sgRARUD5q+OoHIIejBHUqE0VWF5a1jZzb9apxmMn4IoXkp4bm0cC28N3bPQaCsoQjIlrwAlj+iqos1IvhFzOYLEFoLSvaDTOLEL0HmapnWRkOPnjj6namBk7oDe2BkBKpyF2D1fp1A643owc+N+7jLi2asRT3mQpq+2mRMpyzF6deVBEAzvCdRcQPpwfORzrvLMVpxJNfQeSybuBIhGgg1nDSq3gKhXWCwulgktA4Mc4NRznOIeg1sRpviXV18HN5uAgTI2NcZTN6C7X5YtV0q8wCW/S4Bcz2UUnWlYAtRn+Dbm7gVpWyqiaBzWi6go+HIkmWx4GcQGKiqzuQaDbnSFsXYbj8f9v+aZYm/IlUWgLCxFms2f4eZsS8zmH2FhP1OxV6lEthljGfy6xQCV2lklUG/Gy4YyLgSbKWTlkaJo7UrBVJpOUGzsqipCYWJ60VQFrXbsmUbvrbawbQFJ6+Uz9xYBO+oKZqzOzQnkRMk25ycAGloKHeaFyRUyvuZ7DF9Vgmi0Shf+cpXOPzww9l9990LXiXThWknQF599dX84Ac/IJXyntyoog/zJ598wuLFi3nkkUc477zzuPTSS/nWt5avoLbPyo3vgO0zGvwakD7FBBt/gGu/jGs9N+I2pK9W+jX5W4GhLVXuv5E3d54g4trPIXJbSPsNnMwDaOYWGKHd0EQMI7QHmjHxERWTgdBmodz3x7y9HT8PON0TaLVIreZTgmZuhNl2F/bgr+nJ1Qtta44jgrujx05E2S8ikzei3I8YWRE/gB79JnrDqV6pALxUb7Rm9MYfITN/o55IM73hh2jG+NYeUiqLPVjJpMWbkz34U7T2B1a4iF4jtBuIZlADlH/9dIzgLmh65XTWiSYf0VapZpRSCtf+H9JdQCByNI71DE7mgXGfRyb+W4KxbyBEuHbjHLoxD93YBNd5tWKbcPSk5XIUDwZ3RogoqkpKsa6vjmluPqp+db19XNuNFl1rZFbr7/i464u1WpJIP0SruR7xeJxMJoOmabS3V55XQ3gPeuJXVelTIxTYjIH0w1QX6HVS2WdhmABp6i20xw6kK3Er5cVLjdbIXgSN0tR+xx3kpaWHkLYXlIybdj7ire7TsNxlKEJUivSVSmBVER9dNBwlcDDpc8K4eCnVlgsWQRyZN64RubRrre5oSgBNQEBIlJLMi67Ht9Y5lUZzZNTyRLNJ86d4Wi3xoh+Lq39IEGpoX1rtnACpa74hio/PctDZ2Uk4XP+1cVVjWsmtF110ESeeeCLJZBKlFI2Njey0004ccsghHHzwwey00040NjailCKZTPLtb3+biy++eKqn7TOF5AVIv/6jTy2K64X6grUPeFEjkbabCDVd6KXAFpGv/9jcNFyAXL7L8pBI6d1BSPslrPgvyQyeR6Lz86T6Ts05zK7c6JFDlq8D90Ps/m+T6dwKO/4rlKoV1TY1aOansAIXk7UCCCGYud7DBFp/hx7YBCN6NIEZjxKc/R6BWe9itv4Fo/GnGM2/IjDzOYzGHxbEx5I+9Q70hh/VHFuPnYoRO37c90lmHgc1WKWFQjlvoZy3x33s5UWIIOHmS/AEjeGfVR1EA6Gm6hF8E00+ArKcAOk6HxLv3otE976kB84hM/jjnPg4EUJvEjvzVF0tlVI49htkknfgOtXr52rLWZNU0yI0NJ5etU1j049HHTkeCm6PplV/+KjrcwgGRkbxjRdCq6dUkFao55iPfmxra8MwKou64cCWhANbQQWxTimJaayPVIkaY7u4snx5gjVbzqYhuE1hjsX/RgObslbbz0ds8/HgH0nbHzFS9PTUsQ/6folbRWi2C+OUHv+e87XwjksMBmyTLAHPgMY1sQgCnjAJAilzadc1oh5HopgVmsvx65zKqeufMyXiI8DXVtsVL71eQM6tW7hiSHyUgKtoLURA6iAF0o/Im9YkEgmeeuopfvnLX3LQQQex1lpreSWKhGDevHl19aGU4umnn+acc85h1113Zfbs2YXyIRtttBEnnngiL7/88qjmdcstt7Dnnnsye/ZsQqEQ8+bN48gjj+TZZ5+tu4+enh7OPfdcNttsM5qammhsbGSzzTbj3HPPLQSbLA/TWXyEaRQB+dprr3H22WejlGL27NlccsklHHjggZimWdLOcRxuv/12fvjDH7J48WJ+/OMfs/fee7PRRhtN0cx9ppL+/n7AT8H2qU0+/ToajRIIBKZ4Nj4rCkIECEQPRw9sQ7JrV/I3RvkIyNam/kJshm5shmbMxck8UBL5mGc5KrUVfnPSfyWtMkRaK0ezONYrZOMX41ovAwrNWJtgw6kYwR1XmIg0I3IoTuL3Y65rWEClcBK/RbmdBJovGp/JjTN5Q5GWlhbMQHmBQwgNEdwOgtvV1acR+4bn3j54fs7MJ99RE1pwN4yGkxHGGss993Io2Uk9tQeVXAbUX4NvsjDDeyK0m8gOXoJr/ze3VMcIfZFQ41loE/S61Us+AnK4qYh0O0l0fxUl+3JLJl48sNJ3EAhXryFqZf9JYuA8XOetOnrUSCevJRw9bLnmFY0eC0oSj1+MUmnyxjdCNNHU/DPC4S+Puk8hTFqbzqG773sV27Q2nVv2ocB4YeqrIQiiyFZpZRMwPwVQV/o1eHWPV2+/loXdR5GxXmLIKEuhFJjmxvQmb69jhjpBc53ya7Qwn55xHb2pR+hO3oXlfkJAn0VH7EBaInuiidL7NaUkiwavp1bNS8ftoXz0Izl36pF4rQVZV6dHRcliIhWkZD6aEnLBgDkDm2KzGRAo6nmYaAiTUz51DlEjVrPtRLJu4+q0Nafp7sl9d3W9h5lCDu1Tg4SA8qTefuGJk+/1dfOp1lXLnbdehJoCE5oVTO/98pe/vNwmv/PmzWPhwoUjltu2zRtvvMEbb7zB73//e374wx9y0UUXVf0OmslkOPDAA7nvvvtKli9YsIAFCxYwf/58zjvvPM4+u/pDwueff5799tuPJUuWlCx/5ZVXeOWVV/jjH//IPffcw5ZbbjmKPfUpZtoIkFdccQWu69LR0cG///1v1lij/BdEwzA49NBD2X777dlqq63o6uriiiuu4He/+90kz9hnRcCPgPSpF7/+o081dHNdQk0/IzPwI0AfSsFuSiIQnmlD41meSJB5mOUxWFG5/5cTMUHiZO7Dtb+LXsZgITP4C6zElaVb2P8j3XsUenB3Iq3XlNxAK5nEyT6Okv1oxproge3KRg659ltYqftAxdHNdTHD+yG0sUd7CC1KoPVqrJ4DxtxHyfzSt+KGv4xep4A3meQFyGopkmNBD++FFvoiyn4VZD/oc9HMiXddFFoH9YhfQpu6NOZyuPZrWMkbca1XECKMEd6HUPNFgELTZ3sp7lOM4ziFa1E+AtK138DOPImdfSxXO7XcuWVi7mydzJMolalYQ9DKPMVA7xEV5lQOieu8jVJquR6GCCGINRxPJHoEmczDSNmDrs8hFNoNIcZuOBiLHoRC0TfwE2RB6AVNa6O1+adEI/uOue960LQoDZEDGEzdQvlUaIEmGoiF9wIqi9XlMPRW1prxN5LZp4mn7keqJAFzPYRo5ZO+s+qcoUtbbKR4nLTeYPHAVfSmHgJcTK2dGQ1HMrvxm+gVIl4/GfwLsmY0v8CV/XREdqUr9QTFr4msEqmoFCTcAP0q6qVVS0FKlT5YdtGRsnL9yGou195SwbFrf3/Kxcc8rTGL7i7AzRVyyX0k87+32t5r169rKOEte6tn+gqQPqVl7FpaWthyyy3597//TSJRKxJ6iE8++QSAddddl6997Wtst912zJkzh3Q6zeOPP86vf/1r+vr6uPjii9F1nZ//fGQkdJ5vfvObBfFx55135nvf+x5z5szh1Vdf5ec//znvv/8+55xzDrNnz+bYY4+tOJ8vf/nLLFu2DMMwOPXUU9lnn30AuO+++/jVr37F4sWL2WeffXjxxReZO3fVKGs02UwbAfKxxx5DCMFZZ51VUXwsZvXVV+eMM87gtNNO4x//+MckzNBnRUMpxcCAlx7pR0D61MKvF+pTi0D0SDTjU6QH/sBg3LvpaO9Yh3DrTzFDuwOg6TMwQnviZB5h+A3kaPxqc7EpI+pIeujY6XtGCJB2+v4R4mMxbvbvZOOXE2r8Pq69kMzAabjWf0pmJbTZhJsvxgjt6M1Dpkj2HIK0/zc0DpAZOI9Q80UEIgeWzlspnOw/sJLX4Wb/C2jooS8QjJ2EEdikdC8CnwVtDZALkapUwNDGYLxj9R6BFtgJs/FMNHP9UW8/UUyUAAm5yMlJdAMH0EK7gGiAik7RAmF8CmGsONGP2fhlZOOXknd6BnDtF7BEM5H2W1YI8RGgq/NNlFIEg2ByE/GuR3Ht/5CP8KuOhqZ/Cum+j/cpHQ/SuPbbGGWOMaUU8YEzc/MajQAaGLdIbE2LEol8dVz6ytMQPZhY5CukM0/gup3o+mzCoR0QwyL4Joq2pjNJZ5/GdhdReg3xhLKZrZeh5QTh0QiQkBNuQ18gFvpCYdl7yw6ivuMLZjaeQshcr2TZQPqfvN35TZSX5wuALbv5ZOAy+lIPs8GsWzC0hpJtlHJY0P/72hNWkHUHECKCoUVx5CBKaTiQq+c4Eimhx42RUSZSabhKI6MMiiMapQRH6bhF5jPFCAE6Eresy7UiqIX49jpnsk7Dp2rvwyTRGhr5kKA4ArLV9d6bPl3z3moNnl20kH3XG7sh1ErN8LLLkzXmCsRhhx3Gt771LbbeemvWXdd7eDlv3rxRCZBbb7015557LnvssceI8/r222/PYYcdxuc+9zm6urq45JJLOPbYY1l77bVH9PPkk08yf/58wIvMvOuuu9B17zO+1VZbse+++/LZz36WhQsXcvrpp3PAAQeUDS760Y9+VIgMnz9/PgceOPQd9Qtf+AJbbrklBx10EMuWLePss8/m2muvrXtffYaYNjUg8wr75z//+bq32W47LxJi8eL6nO18Vi3i8Tiu66JpGo2NU1OXxWflIR914ovVPtUwgtuQ1S5CKQ3TNJmxxl8K4mOeUNNPctFfy5+qlxciSxGeI/IwsvFf1+zPSlyNnX6EZNeOuNZzDP9GrORSUr1H42SfAyDRtXeJ+DiETab/NOzM40PbKkVm8HzSvd/AzT4NJIE4buYBUt17k+4/q+SJO4DRcAGOcnFRJT+2ckeIkvUgrSfI9nwVab8x6m0niokUIKcCIYKYjf9XaS0gMBt/tMKk+9vph3LiI5QKOgqlBkn1HIlS1VJeJwalMlipO0j2fZ9E78nEuw/i4/e/A0BrUyfZxM9z4iPUF2EoEXozjbPeIdL8WwKRowhEv02o8Vz0wA7LM9OySx37BaS7oOL68ugEQ9VTulcEhAgQCe9BQ+wIIuFdJ018BDD0NlafcR/NsaMRIh89KIgEt2e1jjuJ5VLiXdctcUwfKxn7HWodX4IAq7f+ilnNp5UslyrLu90n59yvh0dsSlL2W3zSf9mI/gay/8WpUX7DS41WdKafojP1dxw5CGi4VBYflYIeJ0JKhbCVgYNGVhrIovZSQlqZuKo07XrEPgvQhcylYw8d41u2fJ6fbvzbFUp8BNh37hc852sXz3wmJz4KvNTffP3HPl3zzO6k4NWcgO0zPfnWt77FYYcdVhAfx8K//vUv9txzz4rX+3XWWYdzzjkH8CL877nnnrLt8p4duq5z1VVXFcTHPO3t7fziF78AvICRP/3pTyP6WLZsGTfeeCMAe+65Z4n4mOfAAw9kzz29c+if//zngljpMzqmjQCZPxAdx6l7m3zb6WaN7uORj2hramryjwGfmvgRkD71UuyWXu5Ll6bPItpxH4Ho14GhqARRIal69Eg0vTQTQMlBpPNOHdumSPedQGWnU8+lOzt4IVbyjppO1ZmBnxV+dzKPYCf/WNRPKXbqplwKe66FkmQS51WUL1xUiQiplBohYJbfhTTWwI9rt5skVjUBEsCIHIIROxNE6cM9oa9GoOVa9OAXKmw5+ViJ31P567KLkp046fF3ka6GY7/O4LLPk+r/Pnb6LpzM3bjWv+npawagtaV3DL3q6PoaaJpBILI/keYLiDT9H6HYscTarmVstwwGulE+mth1R/tw3zv7hSfAGGlVQ9fb6Gg+n3XmvM5as19k7TlvMrfjZsLBIQOcnp4epJQEAoHlKjOki0jNNuHAZrTGRt7M96YewpWVHOUBJJ2JW5DDBH5PTKyMUuCgFblRu7nlEod8VGIpKddgsd1MnCgSDVd5NSCdomRBpSCr9Jz4WEcZCQG6pjA0yZqR1Tl3o0v5+lrfIWIsn5HSRLBjxxZ4ielF3zIkhQDlFjdnQKNpBb25K1Epit3HZ/zYeeedC7+///7I75SJRKKQrbr77ruz2mqrle3nq1/9aiGg6K9//euI9ffeey9uLtL3mGOOqTifo48+GvAe4tx777317YRPCdNGVcmnXY8mnTrftp6UbZ9Vj7wBjV//0ace/AhIn3opFiAroekdhJrOIzbrDTTj0+SjIfMi5Oh8NocjMCNfG7ZsNNGC5cVHhcJF4uBi2y+SiV9ee27uu0jXe4JsJf9ErT2zU14NPgAnfT+qhmjqonCVxFYuDhKH3O/KrSJGKpT9EtbgJSg19NDSEzDHXptzLFiWxeCgd7O9qgiQ0nqJbPdBOImLhtyw9bUwGn9KsOMJ9Fz6/oqAUpmc0Uy1913HyT49WVNCyj6S3Yfk6jlC8eext9+7/rS29I+hZ5dABXd5IYIYoT0YrVu2ZnwKoZV3+6zlGF00eu7HpLHld5iTXDJgZUaIAIY+G71Mvd18+nVHR8dyRRs3R/elerS+oCVavvZlynoDUaMamFRJss4nJcvCxprVt4Ei8XGIvLlM8XGcd7buc2NYOTMZqcBSRpH4KArio0IUipvUS7PZxvHrnEV7cFbd20w2s8JtGKY1JDrK/B4KTAkNuetln2bkIiChN52euglPMUKpKfmZjmSzQw8gygUE/ec//ym02XHHyt8fAoEA2267bWEb2y4tNfLPf/6z8Hu1forXPf305F37VyWmjQC5++67o5Til7/8Ja+++mrN9q+88gqXXHIJQgj22GOPSZihz4qGL0D61Itt28Tj3pNgPwLSpxajMSzSNINI2w0IffX8kpwIaXi/adXdS8sRbDwTpdLY2X/j2m95QpxoypmD1MOwtGsUNi4WEiefAo0kKz9A1hElolQSANd6aUTfIxFYKa/OTzZxRV2zLTcHBZ4gqVzcCunabvIqMks3wBq8kmzvMWSWrkd6yTqkO/fCTt6BUhKlsjjpu8n2Hk2max+yfSfiZp+sL9KyDvJidSQSIRwuL+SsTLjWC2R7DkbaLw5bsQBn8Hyk9fzUTKwSdb+PlSKCxx8rdRtKDZQdszcXAdnW3DdiXXUEZvir6IHKrp6h2HcZbVmIQHi/sssd+02Sg7+po4cggdCXiTb+mLaZLxIM7z2q8X0qM9r6j5Voi30dTUQof0upY+gzaYkOf+DloYlQmRIh5dvlGci8xMKBqxEEyrZVilxtxnKIknaOErjo9Lme07XKHd+2FFg5sdETJAXZQh3I0Ym1c0Jr8r31zqfBbBrVdpONoek0t3rX4kK2Ra4sZ7PjnWuSQpBVAlzvPRtFUqGPz5h58sknC79/+tMja0O/+eabVdcXk1/vOA7vvvtu2X6ampqYNavyw4LZs2cXIimLx/apn2kjQJ5yyikEg0ESiQTbb789l1xySSGtqZju7m4uvvhidthhBxKJBMFgkFNOOWXyJ+wz5fgCpE+95I+VYDC4SogEPhPLaB3TNX02sRmPEGq+FD24I7r5WczwAUTb78UIbEW9ooDQ1yAQOxUr8wjxzu1J9hxEvGt34l274mQfIxA7sY5ORoqUDrJCfJgnRBYLgAqFzEVKytytp6bNyk+wjr1QSNuLesxHTi4PXsK4FynplBUiHdzkL3EzT+Aoy4vudF4jPXAq8SXrEl+yIem+72JnnkDaryEzj2D1Ho3VdyJKLb+Rx6qQfi3dT5D2G0i3B3vg/ygUGSttBbjYAyPrfE4FSqawkvNJD5zhGeZUxa0q3I03dvohygn1rhT0D3giR8soIyCN4C5Emn9VNRLOCGxCtPUGoN70Ub1sRKVjv0lf9744hfqUlWlovpCm1t8RiZ2ApvsP98aT8aj/CBAwZrPOzFswtPw5yiDvcRowVmfdGbeha+U/Qy3h3aku3gvC5voE9NkAvNn1Q/639GA6k/eisEa09uo+VhMJh+oxSgSu0uiyw1iYKAWW1Ei6AVIqkBMjBU5OjByaEdSTfg2wWmgtTl3/ApoDK8ex2xAVJRGQKE+IbJW5+o+56DOB8OpFTmfkFP1MM1KpFL/5zW8AL4Jxv/1GPtT6+OOPC79XSr/Os/rqqxd+L96u+O9afRT3M7wPn/qYNi7Ya665JldffTXHHHMMiUSCM888k7POOot58+Yxc+ZMhBAsXbqUjz76qFAnSgjB1Vdf7adgT1N8AdKnXvL1H1taWlYY4wSfFZd6UrCHI0SIQOTAEa7RgciB2Jn7qmypEYgcTjD6dZTKkOg+AIbduEnnPZK9xxBpvhI9uANu9qnyc9DXwQztgZX8PUM3carmd2IHSQA9l55dfOOmEASwrRcIhHbACO6Ek6lVS09A7mZWaDGUO5Zad+VR5OtGuoVZVncedwrbqbwIqywEoGUeRIv/BrPxhyPHURmQCdCaEaL617CxHCsrCm72X9jxS1AFE6JaPu4S5X6ItF9CD3xm4idYAdf6H8meo0D1Q4V6cUNoICKY4a9MzuQApcqnPQ4MNiKVhmlaNESTo+hRQ9PbEXU8ADBDO9A0+xUyiWvJxn8JVDbfCTf9rKxomBj8Cags1YQnIRqJNp5DKHJwPTtQE8f5EMd+ByEiBIJbIcRIx9/pRqUISKUkCgtBECEElrOAZOYplHIJBz9DOLDpiL4igU3ZcO6zDKQfJpl9AYFGLLQdDaGdqh5X0eDGNIY+z2DmOcofD4q5TZ6x0uvLTqI7/feq++Rdi8qkXueiIh00pBK4CByl0+tEyRLAdgVZAoCGVAry4qPScMjXe8wlJAvQlKo4Vp7t2/Zgv7lHotc4x69INJpBILdXaigKMl//sV/oiPwFX2MyA799isiXZckTDAYJBoNTNJuJ5YwzzmDhwoUAnHTSScydO3dEm3wGGkAsFqvaXzQ69ABtuFt3vp9afRT3MxrHb58hVp6z4jhw1FFH0dbWxgknnMAnn3yCUooPPviADz/8EKDkqfucOXO45ppr2GuvvaZquj5TjC9A+tSLX//Rp15s2y58eRyPdH0juBNG8As42WcY+XhcR9PnEGo8HU1rJt71FTzxcXg779qXGjiDhhkv4KRvx0pciZLLvHWimUD0aIINJ6JkH1byj4AX3VdXijVg45YVKhU2A71H0NQ2n0DsuDoESIUZ3geAQORwsvELa44/WlSF30ezvYskk/g9WvQ4hLsQ6byJcruQ9n+R2SfxCmxF0SOHYMZORGjlj4WVNQLSzTyC1fftYUvrezWVuxCYGgFSul0kew4DlcovqdJaBwwirX9EaJNnKqGbmyCdtxh+99/b511/WpoGGN1zMA2o36VZiADhhhMIxY4nk7iGbOI3oIZuwjR9HqHGHxEIf3HEtq77CXb2nyOWDyfadD7hyAF1z6kSjvMh/X2nY1nPFM2/iVjDd4jFTpyQB4a2/T7x5Hwc50M0rYloZF9CwR0RYsVJOrNtu/C9JS9AZqw36Y5fyWDqPsBGF+3oejOW8z5DApwiZG7Gau1XETDmlfQphElzZB+aI/uMai7rtV/F213fIJH9LwKj6JGWYo2Ws2iL7kN38pGq4qNSuYhGDMp9Zj3xUcdVAomGlMpLu1YmGZmv9Shybb20a1d5ImVu70r6M4TMRUWqYeu8vw9b/US2alse5/ipYbVIO6/K7FCgqPL2rkV655q+ovp7QoJacQ7pSWcqajLmxyuO4gM499xzOe+88yZ1LpPBTTfdxBVXeKV2NthgAy644IKy7TKZTOH3QKB8aYY8xUJtelgN03w/tfoo7md4Hz71Ma0ESIC9996bDz/8kLvuuotHH32U1157rSQdbuONN2a33XbjK1/5CoYx7V4enxxSSgYGBgBfgPSpTXEEpI9PNfLHSjAYJBKp7R5aCyE0oq1/ItV/Lnb6dvJReQBGcHsizb9E05pxnQ9x7Reqd6biJLo+T6TltzTMKp8eKfTZhFt+V3DCrvfrd2UZx0uCTgycR0vH3wk0nIkVv6hCWw2hr44Z/jIAgdgxZBNXDhmZrGAobJLLPoOBLC90qCRu8npk5hGCbX9F6O0oOYibvhtpvw7CpLurGSgfAamUi8w+ibRfBWGiB3dCMzec4L2qjVIWVv+ZFKc7jgYhmsd7SnVjp27OiY/VhMcQQmvBDO9FIPp1tGFCzEQTjB6Jnb5lxPLe/mYA2lqK6z/WijoFcDCCoxdLhBCEG44n3HA8SqaQ7icIEUEzRkao5JFOPc7XOmocyis4ziK6u76MlAMly5UaID54AVL20tR09nKPM9Svon/wEgbiv8YTpyWgkUjdQjCwJTPab0TXVow6gPkHG5FIhGg0SjLzNAu7jkThkhe2XdWN6xSXqvKOo4z9Gh8u+wrrzPo7hr78D0YMvYkNZ97BYObf9Kbux5UJQuZadMQOImjMAeDjgeuq9uEUjGFGfm7zjthSgURDKeh3wsQJIZVWIj56eKqaq/LRzyPP3UJAABdXablXy/uc6QiOmvd9Nm3eZvQvxArAHrO24kH+CVJD5MRHHEVzPgVbaYjccw+VP8R9Jp2PP/64UIMQqBr96DgOpln/A6ZKXHfddQX358ngiSee4Jvf/Cbg3VvdcccdFUtchUJDEe2WNbI0QzHFhjbD+wuFQqRSqZp9FPfjl90aG9NSYTMMgwMPPJADDzywdmOfacng4CBKKTRNo6GhVv0nn+lOPlrWFyB9alH8wGu8om+ECBNtuRjZeAaO9SzgoJuboRcJI9L9pOL2xSjZS7LnSGJtt2IEy99EmeE90MxHsZM34KTuBDVaw4sRo+I6b+I6bxNqOBHdmEe6//ug0gw5lko0Y30irdcW0ieFCBHt+Dup7n1z0ZrFaAh9Hsr9YDnntrw4OIChtArvt4tyF2MNno8QUdz0rXh3dQKlBL29hwImzY2LgPULW0nrFbJ9J4BcgvdVTuHEL0Ho8xDmxggRRQ/tjBbctWaa93gjM4+N/ZgQTWjBz43vhEaBnXmIWnfVQp9Fw8zyZQomAyOwKaGG08jEL8UTS7z55gXIlub+XEsdM/Ql9MC2ZAZ/XKE3HU2fixnafbnmJLQIurZe7XZ6PddIWTEieDTE45flxMfyeaLJxO+JRr+OYYxPmaVE6uac+EjRmN6/WeslunpOYFbHzeMy1vJS7ICdtd/MiY+1b7o9XBy3m6X9F4AI4bi9BIy5tEYPJhRYv/bmZRBC0BT+PE3hz49Yp5Ri0Hqp4rZSgapiaSALkY0aSiniboh+YoCGrbxU66Gxhm9X+RothBcJqee2aTRa+c56F9G0ktR7LMfcyDBB2YUYEPB+ZVB4JngK5QmRo/Ok8hknGhsbSwTIVY0XXniBfffdl2w2SzQa5YEHHmDDDSs/XC2+T6+VEp1MDpUnGZ5q3dDQQCqVqiutOt9PPenaPiOZlgKkj08t8tGPTU1Nfk0/n5r4EZA+9ZIXICeipp+mtxGo4BIrtHqPTS9qLT34cxo67qnYSjfWRm/6CWb0W/R2bj36yZZBusvA/DRmeC+M0O44mUc8Z2yhYwR3QA98fsT5WDdm0zDreZzMU1ipG1EyjRHYmkDDcbjWW6R69h2XuS0v5eNo8rjIzL0jtkgkw9iOiRCSqDyOTPdnCTR5N/3Z3sNyAi0UR70q9yOU+xFg4KZvRejzCLT+Gc3wUraUyuKmbsdJ3YRyFyG0JvTw1zAiRyLqiGaSzofI7FMoZSOMtVHO+7iZh0AlQV8HTZ+BzD5Ts59KmA2nIsQU1rJSlWsaDrXJ1G4zwYQaTkEz1iebuBo35yje1++ZOc1d82waOloQ+kw0rdnbQKXIxH+Opxi45CO2hDaDaNuNkyZS6/o66MaGuM5bVBZ6DYJl0rdHg1IW6dQdVC9Sp5FK3UZj4w+WayxvPMnA4GVUjjh1yWSfwLLfJGBusNzjLS95AbK1TeODZXszvC5wNbx6ioqe5B14t5EuoNEV/wPtsW8wp+W8cf/eLNDKVhuWuejGamdYlXOxVgp63RgJGYRcJOTwbSq7Z1eZm4BdZhzATjP2J6Ct3LVFN2iaC65CSBCuZzbTIr3rywAayNzrk/f5mc41IMcW4L/8Y44SwzDGxal59uzZy91HPbz++ut88YtfJB6PEwwGufvuu9l2222rblNsGrNo0SK23LKyKVyxaczwVPbVVluNZcuWsWjRoprzzPczvA+f+pj2AqTjOCXigZ927QN+/Uef+lFK+QKkT91MVb1Q3dgQTV8b6X5I7W+xEtf+L67zMbpR/cuVbsxFNzfGtV9b7jlq+pAZghAmZnhvzAqC6nCM0A4YodI0UiO4OcHGn5GtGP01eUgk2ijDRXoHvAiH5sY4uqZQ9n/J9nwNLbhrTgSrFqmXM8hxP8bqPYJgxyOgHLK9R6Dsl3NtFMpN4CSuwEndRLDtdjRjrbK9KTmI1f8DZLaKCYTz9nLcjwYxGn6AHjlyzD2MB5q5KdL5gMp31jp6YLPJnBIASiax0reTTd2KcnvQ9LkEo4cRa78NUCjl0jfwG8Bmxsx10c1SMTnU8G3M0O5YqRtx7DcQIoIZ/iKB0H4IbfJSyIQQxBr/j4HeI6kk1kViJ6HV/cCkPFIOUs0gJzcbpLtkucbJ4zgf4LgLa7TSSaUfXSEEyLwDthF+iHw933pxEUXvmlNYCtCduBbTmM2MxhNq9qOUS3/6cQYz/0IhaQhuSUtkDzRRWn9NCEFzaBv6Mv+m+JznKpETDKuIjwpspeGi0+dGyEoDFyO3XB/R1tsvr68hybO6mPqlWUey44yRzrwrIzEzjDAssHL3wi70KZ3ntRAORa+E9KIg/QjIlYNPf/rTUz2Funj//ffZfffd6enpwTAMbr31Vnbbbbea2xVHR7711ltV2+bXG4bBuuuuO6KfF198kYGBAZYuXcqsWbPK9rFkyZJCLfcNNpj68/nKyLQsH/v6669z8skns8EGGxAKhZg1axazZs0iFAqxwQYbcPLJJ/Paa8t/M+Wz8lIcAenjU41kMonjeF/C/ePFpxZ5sXo8DGhGgxCCcOP/jWobJbtHLJNuN5nE70n1n0l68Oc41qvEGssXBi8aHage1SZEG5o+tvS9agRjRxGd8W+M0JcR2kxgaj6jilKju3roHfDm2tKUr3EpQaWRmfupP/TERbkLcTMPYccvQtmvMDJ0Q4LsI9vzdezkjTjpe1HSG1O5y7BTd5Hp3heZfXRU868PA7PpYkIz/4MZO3bKMw4C0aOo/tq6uTaTh3Q7iXftRXrgHKT9OkouwbX/S6r/VBLdB4FyiMdtbNtG07SKDzd0c13CTefR0H4bsbbrCUYOmVTxMU8gtDONLdcU1frM34oEiMROJdJw2nKPoWkN1DbWUWhax3KPBV7EZW0Eqp4I2zGMHU/dS1f/T+geuIBU5pma55q8ABltfIfRhFUNF+nK0Tn4O2SN1yNtv8/Li3fhna7jWBb/C53xm3iv+2T+t2g7EtmXR7RfrembFIuPXhRmfg6VxcesMrCkTr8TwJYGGQIopXCUhkJDKS860lECZ1jKtSFqFThU7DrjIHboWDGi7McL0eCCC8L1XosUGu8Q4AMC3luQe1kEotBmWqLU1PysoixatIhdd92VJUuWoGkaN9xwA/vtV5+wv9VWWxWMY5588smK7SzL4tlnnx2xTZ7tt9++8Hu1forXbbfddnXN0aeUaSVASik55ZRT2Hzzzbnqqqt4++23kVKilEIphZSSt99+m6uuuootttiC73//+0jpV9idjuQjIH1ByacWeUGpsbERXfcfB/tUp7gG5GRjhvck0nw5UJ/ooOmlT3+zyesZXLYVmcELsVK3kk38gUT3XmTjVxAMHUD5G0Ed3dyISEP1KESlerAyd9c1r9GiG3OJtF5Jw6znaZzzKuHm31HvazCeqFHmT/XlIiBbm4pNdlyKU67rQ8NNP4Cbup3KUZMS5Mc4g2dj93+PzLKtyHTtSabz8zgDp4K7gPHPN9PRgjthRA5EaCtGPSsjsAWB2PdyfxV/RfZ+D0SPRQ9sP2K7iSTVdwqy8Prn3wPvfXTtl0gP/rRgKtLa2rpSXIeC4b1om/VfGlv+SLTxxzQ0/4q2Wf8j2njauLhFCxEkHP4y1UO0XMKRry33WACGMa9Qm7YyDsHAxuMyXp509gU+XLIlS3tPoD/xJ/riV/NJ94Es7Nwdu4Lhj2VZhe+4jc2jq9VazxnAlb2krVcrrnfkIG8uPYyssyjXp4PKndNs2ctby44g6yzJ9ZVhcfwWPur7NbrI11oTReJjZRwlSLka/TKKpYKkCAAChYZEL5jTuGg5A5vSPjWhMITLyAc23t8HrnYSu886aMofmow7ETUk7UoKTtglPzK3zsdnHOjs7GS33XZjwYIFAPz+97/nsMMOq3v7hoYGdt11VwAeffTRiinUf/3rXwuRi1/5yldGrN93333Rck7v111X2fjq+uuvB0DTNPbdd9V6ADFZTCsB8pBDDuG3v/0truuilGKjjTbimGOO4cwzz+SMM87gmGOOYeONN0Ypheu6XH755Rx66KFTPW2fKcB3wPapF9+AxqdeHMcpnFumQoAECET2p3Hmv6keHaRhBLZD04dq/ljp+0gPnI0nfsncv95No2s9jqbSRBvOQIjiz0GQUORQmtvuwDBrGz3E+39AKnE9SqZGv2OjwIzsTcPstwi1XIkZOYJA9ARCzZeBiFIr3W55qN8z3COfgt1SIkCOBYmSPdROSS3GQjnvMLE2py5G9NgJ7L9+lIzj2q/h2u8SbPg+4ZZr0M0tCus1c2PCLVcQbDx7UgUH134Px/onlaMyJVbqdjo7vfTfjo7xieibDIQIEAx/iUjseEKRg9HG2SG6oeH7OVGwnAgpCEcOxTRrG+fUg6ZFiEUOrTCWN56mdRAO1U4nrBfbWcAn3Yfgyt7ckqFzsmW/zSfdByLLRFx+tMir7RsMpQmGR1fPtFb0Y6FdlUjPZfG/YMtOyp9bJK5K0Rm/Edvt56UlB/FuzznErddwVd4YQuVMZypHPlpSI+4GGVCNuBiklIlC4Egv9TovPg5RLEAOnacNoQgIBx2JyP0YKE5Y+3w+27pLzddhZUTPl4ktRDoypMHmfkoESh+f5aC/v58999yTt99+G4Bf//rXHHfccaPu5wc/8Gr5Oo7DSSedhOuWXjO7u7s544wzAO/e/thjR373mDVrFocffjgADz/8MHfccceINrfffjsPP/wwAEceeWTFNG2f6kybgofz58/njjvuQAjBZpttxjXXXMNWW21Vtu0LL7zA8ccfz0svvcQdd9zBLbfcwiGHHDLJM/aZSvwUbJ968es/+tRLf38/SilM0yQajU7ZPDS9jXDTuaQHykUlakCAUNPQOqUUmfivqGywIHGyD9LQdAbh2PE49huAjW6sj5aLbLOzT+F95agWvZclOfhjMqkbaG67E02fOJFWCEEg/GUIf7mwTA9sRjZ+OU76biZWeIOhG97KlezLR0AWb1+voKmh6fMKZiUrCnr0ZPQKTuuThZL9ZAYvwk7dSV6gFfpqBGMnE2n/K96duEKIWum8E4NjPV9HK5uuzveAiTG3WlkxzHVob7+Lvr7v4jjFdcECRKPfpLHprHEdr6XpTDLWf7DtNxl5/lBI2UP/4KU0N54+LiJ2X+IPOaGv3LnKxXY+JJG+n8bIV0vWLFz0ILDmqKMfod7HMzrBCsKuUpLFA1fV2F7Sk7qP3uzrJO138lvWHFUpsNFwlYaDzoCKIpWGpbyIx6wUeNcgUTbicYjhkZCg5ZS2qN7Eiev+lqi56t4bCMRQpGPR5alEnlWe+Y5axYI/R4NQuddnksdckXjvvfd4+umnS5blHaQTiUQhUjDPF7/4xRLBLpvNsvfee/O///0PgMMPP5zddtutahm8aDTKWmuNrFW9yy67cMghh3DLLbdw7733svvuu3PKKacwZ84cXn31VS644AIWLvQe1F100UUV79kuuOACHnroIbq6ujj00EN54YUX2GeffQC47777uPTSSwHvYd/PfvazKq+OTzWmjQD5hz/8AYBPfepTPP3001Vv/rbcckueeuopttxyS95++22uvvpqX4CcRiil/AhIn7rxDYt86qVYrJ7qtK1g9OsgwmQGL0bJZYXlurkx4aYLMMyhVEHpLkA679bsMxO/kmjLrzADm49Yp1S9NQsVrvM+8f4f0NR2bZ3bjA+6sTaRlt+gmn+BdHtxrP+RHfgRqJG1MMdOBGFuiGasjTDWRA/tTbZ7X1Bxim+ypRQMDDYA0NI0UDxLROBzoOIo+1XqE0oVeuxE3OyjoAZqN58sZP+UDq/kIMnur40wnVHuIjIDZyDdxYQal78e4fJR33mip9eLGm5vr+1kPtUo5YCyQIQn/DyoaS0Y5uY4znuQs9EIBLcnEvnKuDt/a1ojszvuoavneNLZf5RpIRmI/waBQXPT8h9XidQ91HL5TqTuLREgpZR0d/exPAJkQF8Dy11E+XOPTnNkb0y9fCTuYOYZpKoe4S4VDNpLUXZ5gyClQCBLRESpwMqZywy6IdIyQFoFsdEBQVaCUkYu/TpvolPZvIaS9d7DnvUbtubA1U/H0KbmYcRkoQkNmUu9Hi4+5hHk3odpLED6wNNPP80xxxxTdl1PT8+IdY8//niJALlkyRL+9a9/Ff6+6aabuOmmm6qOueOOO/LEE0+UXXfttdcyODjIAw88wOOPP87jjz9esl7TNM4++2yOP/74iv2vvvrq/O1vf2P//fdn6dKl/OIXv+AXv/hFSZtZs2Zx9913l7hv+4yOaSNAvvLKKwghOOOMM+qKPIlGo5xxxhl84xvf4OWXRxZE9ll1SaVSBVORhoaGKZ6Nz4qOL0D61MtUGdBUIhg5iED4a7jWCyg1gKavgW6WcUtU6br6s9O3k9ZnE2784Yh1ZuAzZFLX1zkzFyv7CK6zCN2Y/C94QgTRjdnoxmwC4S+S7Nob6YyPMV2g/R50s9R5MdByDVbv0YBF/qZ+IB5DKg1Dd2iI5m/YNUAn0Hg6Ql8bO/Er3NQtUPGGXgMkZuNP0M21MaLfwEn8hvGv5Tg2VCGlcmrIJv6AdN6nkohrJS4jEPkamjFvUudVjFFXhGiQ3l7PyXhFFiBt67+k4ldgZf8OSDRtJqHo0URixyHE+NdkdZyFdHftjZT9DAl1Civ7JF1dz9DWfgvBcY7AFcIga1WPNO6P/xLHXUJr87k5s5yxIVWyVgukjBf+UkqxrP+nDPZ7kT+Nzf2jGi9v/OK4i6kkPgb0ucxpOa9iH72pR6gWvZ0XEiut95yvS6MXXSWw0ZFK0OtEyMgAKYIFgVLmxEcnJ0YOCYu1zoOCLVu+RNRoZOPmHegITg+xodkM0E0uwg9GvNWF9GsN1HROwZ4KU5hV2IRmPAiHw9x///3Mnz+f66+/npdffpn+/n5mzpzJF77wBb7zne/wuc99rmY/22yzDa+++iqXXXYZd999Nx999BEAa621Fvvttx+nnHKKn22wnEwbAdKyPEe2TTfdtO5t8m1t256QOfmsmOSjH2OxGIYxbT4iPmPEFyB96iVvQLMipesLodcUOTR9NSCAJ5BVJ5u4HCP4OcygZ9Qh3SVYqVtxrFdyfdjUJ4ApbPvFKREgixFCEGm7gWT3ISi3dhRoLVzrhRECpB7chmDHwzipP+Om7weZoi++JgDNjfFClInQV8NsvgTN3ASAQOPZqNhpKPcjlNKR1tO4qRtQ7scAaIGtMWInoAd3BMCInYh0PkBm7sGrVVdvVOrEoAc+M2VjK6WwUzdSPYJUx0rdSqjxjMmaVgHX+Yhs8nrs9IN49VorfQ/VUPohJBKeGLWi3hRl0w8z2Jev6+W95lIuIxW/BCvzd5rbbht3R+6B/h8NEx/zeGn1/X3fZcbMf4+L6U2eTPZZpOqv2S6Rupms/TKzO+5B0yJjGss01say36Ty+VQnYH4KACnTLOu/gL7kdcQHDgZGZ0CTFx+9kcqV0dDpaDiOGY0nYuiVr29e9GNl8c+pYhrkiY9aybZOLt1aKUWfHSKhQmRzZjN5ssrALem3unu2h6LFnMU+c0+o0mbVIu+c3hSI0CNz55tqp0fpiZA+05ejjz6ao48+eszbz5s3r3DcjSeHHXbYqExsytHe3s7555/P+eefP06z8ilm2qgra665Jm+++WZBXKqHvFPSmmuuOVHT8lkB8es/+tSLlNJP1/epm5XVsEhoDZjhr2Knb6e2aKWTTVyHGdweK3U7qf4fks/l8iSvle8JvqZ3EJvxMKne7+Nm71muvlynvDujZqxBoPHH0OjV3kwsfA54iLb2tTCbfo7Q10ILbDMiZVVoEYS2IQB6YH2M6DdAJUGYCBEsbSsMAs2/RlqH4KRu9YRL9xOQPUx8zcvhmOiRgyZ5zGKyOWOeaiiks2BSZlOMnX2GZM/X8YSeSp8379NkBLalP/MN4C9Eo1FCoVpOzJOPlAkG+7+Dd4wN//xLHPt/pBJXEC0TOT1WXOcTstnHyow3NK7rfoyVfZpgaIdxG7c44rBGS2z7DeLJG2hq+PaYxmqOHkNnf7XXzKUpejiuHGRB54Fk7NdwHZ1E3Iu6HJUACaiqgp0kYMytKj4ChCvWhvRMYWSF2ox5AbQ4bTq/Tco16XQbcZSeEyiHSLs6jtJR+bqGo0gZ3r5jfBzSVxby1xYt9xp6ZS+V95LL/KueE6HzHkDTOAJyKpzAfdMfn1WFafPs4mtf+xpKKe688866t8mb1pSzavdZdfEFSJ96icfjSCnRNM1P1/epyYoYAVkv4cYz0fS5dbR0ce0XcbLPkuo/lSE7TYWGwiiUuK+FhhmYWoOSYoQwiLReTrDhDJbn2a1rPVtXu54eTxxr69gQI3IoenDbuurlCSEQWmyE+Fi8Xg9uS7Dl14Ta7yLYdkvO/bty5FGNEce0ldl0IUIExjjmeBDI/VRDQ+RMlCYLJeMke4/FizYuLz4KrQMj+HkiLb8j2nYTvb1eKvuKmn6dTd+dK+NQWQxMJ2/wakOOE47zQZXx8gjsOmrbjgbTWHsUrSXxxA1jHqsxehDh4A6MvJXzPpMtDScTDGzM0r7zyNhvAhAfaAKlYQayBMP1ldbwZlo7ZbkncXPZ5Y4c5OO+X/HSos+zqP9yhqtWrhJkMXLiYfnziRwWteilaut0WRGWus1I9KLUbIHrwqAdIClDZFUAS5lklUFW6siqu+FJrTG9hS1axs+xfEXFsiwSiQRvv/02L7zwAi+99BIbWCEapIuGAlcgpEDLXbcFOe1RMtUB9D4+Pisx0yYC8tRTT+Wmm27i6quvZocdduCgg6o/eb/jjju4+uqrWWuttQrW7j7TA1+A9KmXfERbU1MTmjZtnuf4jAGl1ApXA3I0aHobsY77iHfuipJdNVqbpPrPLLtGIHJe2CoXUVPublBgBndGiHDOvEbLRasJhNY6ZQY+QgiCDScRiB2HnbwDx/4PQmvEDO0B2iakujap2Ye0X61rrLxYPdEptZqxNsG2O7EHz0Zazw2tEB0IYx2U/QKlKZf51z6I2fQT9PD+IPtxUnfiJC6ua0wjdiZGZGqji4TQMML74qTvovKdtIMZ3m8yp4WVvtOLYK0o9giENoNY2/zCku5uzyRpRU2/duw38ATuygKjUn1I2Y2uz6rYZjQIrXatd1Boop529RMIbEjA3BTLfo16wsMct3xEdD0IYTK3/c/0xq9gIHEdbi6i1zTWpqXhJBojB+O6fQyk8m7uMDiQr//YVyEasPw5WRXWVUJhu4tHLE1Zb/H60gMq1quUipxRTPX+8zNSOeFRodFrh4gTGzZ3PPFRhoelXXvrFWApgwAuWgVL4YgW49RPX4smxvpQZsVncHCQd955hxdffJHOzk4ikQhSSrLZLI2uy5dzb0XC0OhXGl1Sp0fqDCodB1FIva7bW87Hx8eniGkjQDY1NfHoo49y8MEHc+ihhzJ//nyOPvpottpqK2bMmIEQgmXLlvH8889zww03cO+997Llllty2223+ULUNCOfet/YOLmRDz4rH379R596SSaTOI6DEGKlvaZoWgvB6NfJxH9F5ZtrHU1fE9d+rsL6fCsDV0RRZV2ZFSr7GANLN0JiokQQpbzURt1Yl3Ds24TCB0+hEBkgEDuMAF6NIddNkOysXdjco3YdTRgSICdDrNbM9Qi23YJ0PkI5H4EWQzM3RwgDJQeQ1osodynKXQJIhLE6emhvRN5AQ5+BETsBSOEkrqSSqAwKI/ZdzIbKDpSTSTD2bZz0fRRyDEvQ0QNbowe2ndQ5OdYLVDfIUEjndZSyChGkhWjZFVSAFKK+tPBKUbtjwTQ3Q9NmIuWyKq0MgqHxj3Jrbf4ZS7vqE641sXyZE0IEaGs8ldaG7+K4SwAdQ59dODdm7Ncprh8a728GKhnQaESDO5HMPjZynEL9x4ozwdBnlCyRKsubyw6vapbj1BAf86nXEoFSAgsDqSApTfpVA8URkQC2C2kZLBIfy/o3YymdIE6RCKvQkXyu5avsNvcbVfd0ZWfhwoU89thjLFgwVF4ikRgyBBOawHW9x4MxJDEhmak7xDWdJdLgQ9ckJTUEanrXgPRNaHx8xsy0ESB1fehJllKKv/3tb/ztb3+r2F4pxQsvvMDaa1dOpxBCFNySfVYdfAHSp178aFmfeslHPzY2NpZcj1Y2ApHDyCR+l0upHC7a5G4G3fdq9iOQ6Cp/2+cWKntpRQnaLgqFBWpItHOd90n0n4ZjvU6s6acjREjpLkXKHjStA23YDfFEoFSW5LJtgcE6t6idduy6buHhxmRGy2rGPBjm+Cy0JvTQLjW3FUJgNpyGHjkUN30XMvs80nkX5BKvb3NLjNix6KE9JmDmo0cpG81Yl0jbTaT7TkTJZXhfiSUgMYI7E265bApE7rxTby2G7vzzAuSKmoIdCO1BOnl1lRYahvkZNG38SlMIodPQeCoD/ZUMhASR6FHo+vi/ZnZd6d8AOrHogeMyphAGprF62TGKGRxoBqChaXj9R4EmIsxtu5RE5nE6By7GcZcW1obN9UjZ1dPV26KHlPzdm3wQR/aWbauUl1ZdqeZjvo3jyVwoJbC9pGBspdHpNpW0c9FIuQaSYrfrSuRqSBb9pqE4ZI1zWa9xq6r7uLLT3d1dEB+DwSDNzc2ss846zJo1C6UUyWSSxT1d/O35V4miiAhJFIUJtAqXVt1lPT3LS06YBdJE+IKYj4/PGJg2AuRwl6V6XJcmwpnJZ8XHF5V86sWPgPSpl7wAuTLWfyxG0zuItd5AovfoYamiGqATbDiNbPyiuvoSxHOi48gwComqcAvvLc2kriUY3ptA0ItQs7MvkRn4Ea4zlOKsm58h0nwhurlhnXs3ejIDF1K/+AiauVHNNgMDAyilMAxjpastq+lz0GInkc+MVMoTqcfTaXisKJnCSl6LlfwzSi4FghjhfQm3/hklFyHtN0AEMYK7jXAqnyyM4HbY6b9WaaGjm59BCO/ru1Jq0tL1x4oZ2AbD3ALH/h/lhTmJYW6CUnJcj5NI5Aik7CM+eElu3LyDsks4cjBNTeeO21jFpNIPUD2K1UOIKI2x46q2WV7Cgc3RRLQQhVgpAlITDazRcROGPoPm6ME0RQ4gbf0PKeMEzHmY+lzeW3YAKetlRpYs0AkYq9MaKxUgBzLPlJ2TV7/RoNZr5FVj1FC5NG2JhpSKfidKXoBXyhMkkzJYWCbrtDdQORcVUwQ5cd3f0hIcn/T/FZnnn3+eRYsWEQgE2HPPPdl8881HPGTpTif40bPvokmNoCuJaZJ2zWWG7tKiuYRQbG2k0W3F+8qcoj1ZAVDU95xhvMf08VkFmDYC5LnnTswXDZ9VCyllIRXBj4D0qYUvVvvUS16AXBXEaiO4DY0z/4WVug0n+zQgMQJbEYgcimu/TbauXqrffMqa37R1Msk/Ewhui515hmTvoSP6c+3/Eu/6EtG2uzCDn6lrVqNBKYmdGp2JRCD6zZptitOvpyrNfLxYEYRHACUTJHsO8kTGQuRuFif9V5z0vUTabiTY8L2pnCIAgfCXyQxeiJJ9lK9N6RJqOKHwVzwex7ZtNE1bgc8tCkSEap/3TOo6lOqnofnycTtmhBA0NHyXSORgUqk7cN1FaForkfBXMcx1xmWMckiVoB4DnNkdf8UoG7U4vnMJB7YkmX0SJQXxQe+7SkNTf2EeQWMD1pp5L5oWHpqd0IkEPwt4Inc88w80EUUQQFFqXhMLbccabb9G10oflkg10uTGExOLbz0rRz/mjW8cdFwlcCX0uA0kGZpn1hWkCVXspxZtgdkcv85lBPQVzz1+Inj33XdxXZddd92VLbbYomSdUgqlFK3BiKcSu5BFw3I0epXBAiFZ07D5VMAiLBQbm1m67BXj/O7j47Ny4QuQPj5FxONxlFJomkYsFqu9gc+0xo+A9KmX/LGyskdA5tG0FkKx4yFWWs9PqfpqHBqhvXAy91dcX/tBv0s28wi9nXsinbfRCsl8w29EJcm+b9I866WhLZ3FuNZzgIkR/AKaPrYHCK79NqO1AjWCO9RsM5n1H6cL2filSPtNRpYNcAFFuu/bxGY+hxBTE9FjZ54im/wjjvUcKIkXzeW5x3voeOLj6Z7pUY68AU1LS8sKWdpByRTxgR/jWOWj4YrJpu8iENwVM7grqfgvyKTvAZUAEcQMbE+04buYgc1GN75SOM4H2PYbuM4HaFoLljEP3Zhbd23K0RIwNyCbfY7K5wZBwNyEQKB2NPRYUcplWf/P6E38KTcPQTIRQ7oGmu4QjaUACJmbsuaMm0vEx9J+JB/3fJ++1F/JH4P5fRAiwry2K2mM7FqyjSMHWdD7M3pTD47oT+ZSqivP22uTd7RWSmErDReduAzkxEeBVJB2dSyCDBcfRSF6vrppzkaNW3PwGmet9A956iWbzdLX10cgEGDddUdGeAshCq9F/qwjXArvmK003rOD9Lg6X4ikCKGYiYtSatq8hj4+PuPDtBEgfXzqobj+o39B9amGUsqPgPSpm1UpArIaurE6RvALONl/UekGXGgdRJp+yWD2cVCp5Rgtjeu8BuRvsfMV9Iadu2U3jvUiQluDZO+RSOf14tlgBL5ApPVaNG10Jhiu9ULRrW5914vEsk1Am4ER/AJm+EsYwZ0Rw9xW8wLkqiJWTzVKprFSN1NZEJIo2Y2T+TtmeK/JnBoAmfhvycQvplTg8dKFhb46QjRhBDYlED0KY1gK/4pqQKOUIp38I8n4xaP4jGuk4pfj9n+XEqFY2djZh+jPPkQo8k0amn9a5xwk/X2nkU7fytBrq5HNPkEi/lva2u9An4A6sQ3RI4kn/lRtZjTEJtboxBMfrykZM56v/9g4QDi4Ke2NJ9AQ3rOq6N4dv5a+1F25v4o/PwqlMizq+zEbhHcqnMNcmeKNpQeTtt+lnFGZLKTBjzxfejUfvTqPSnkp0lZOfHSkYFB5juWOAksaWJhl+zGFxFLVb2/nRdbjkDX/r2qbVY38/U04HEbKGg7trvcjACHzr7F3reuTBgttk3VMmzm6M23vlYRSk14D06+56bOq4AuQPj5F+AY0PvWSTCZxXRchhH+8+NRkVYuArEa46WckuvZFqQSlN606oBFtuRJNjxGKnUgm/suyfeTjv0ZD3su4XBxYNvUAdnq+F1E1bCvHeop41640zvgnQgiUcrDTD2Ol7wKy6IFtCEW/ichFCVmZf5EZ+DHSfbeoF5Wbtyj5uxiRqzmGXIqTvh0nfTtgEogeTbDx9IILsB8BWR2lXJzsEziZJwALTV8DJQdxnbcQBDBCO2OG90doEQCk+3EdIpiBa78+6QKkk30+Jz5C6WfFO/qV+zHRjj+MEB7z5AXIFeVYkbKXdPLPpBN/QqnyBiRVtsZ136naIpP6E0KfRazhxJq9JRK/I52+LfdX/rX1XlfH+ZDe3m/R0XH3KOdYm4C5Ps2NZ9E/eCEjS00IwqE9iEUOGPdx8zhuZy7ysZTBXP3HhqYBwKIxsk/VfpSSdMX/QOV4dBfbXcRg+jGaIrujlMPigStI229X3Kait3vBcIac27WOQiPp6vTJGFbOvMtWAsfVimpIjkQTCl25OSfsYrHT+31WcHWOX+fCqvu+KuK6Lu3t7fT29vLBBx8wc+bMitGLAoEGCFm6NE+vo7OOaRPwixL6+PiMAV+A9PEpwhcgfeolH/3Y0NCwQqa++aw4uK5bOLes6hGQALqxNrGO+8nEL8VO/w1wAIER3IFQw2kYuTTKYOxklIyTTV7D8JRTDVFHHciRSJR34zTs5tS1/llGfBxCuQvIJq/DCO5EsvsrJeKJk32CbPyXhJsuRmgtpPoqRy9Vm7NCFQTKIWys5B+w0vcQ67gfTZ9ZiJZdUUSlFQnpLCLVexTSeY9i1+ohBE72YbLxS4m0zUc310eI2s7joAoC8GSSTV5PaeTjcHSyiRswWi4uu3YqDWiUktjZf2JbL4DQ0I1PkRw4BymXMZFuCen4hURj364aeaWUQzJxdZV5uNjWf7CsVwgENh33OZrmOniO96UlKXRtDm3NF42Ieh5PBlMPUO7xTT4CsrG5j4z9Opb9IQFzrYr92O4SbHdxjdEMEpl/kbTfZ+ngn7Bld8WWXvDWyOhHmYt89NoIsrlb00EnSLcc+i5uu4KMCuBUER/zmJpEUwpHaUPpxMABc77NZ9t3rbbpKsusWbOYNWsW3d3dvPbaa6y55prMmTMHoBARWfhMuQwdQrl/Re69UyhCwntV03Ia14BUKn9QT+6YPj6rAL4A6eNTRF4kWNmcR30mHz/92qdeBgcHC67G06W2rG6sSbTlclTTz5GyC6E1o2ml0Z9CaISbfkwwejRW+i5cdymu9SLSeR2BgYHCwcm1zqfu1f4C7qAQObEvXxdSOu/X3C4TvwbivwQVL7PWJT1wGjCybpxUQxXHaqWjybIiJCA7SSz7HMHGn6wyjuljRakMdvpvOOkHUSqJbq6PGTkcoc8m2b0PSubFYafc1t7/ZS+pnsOIzXgaoa+J0NdCuR9RTZAyQpMvTDjWC1SvI+ri2i9UXDsV0bJS9mFbL5EY+BHSXUh5IXhCZ0A2/TdCkX0rtnCcd5BVxDAPnWz2qXEXIDPZF+jqOZ5yr4crl9LZ83Vmz3hwwgyaXNmPJ2qXfj4KKdg5AxqvXWWkrG0nphT0pJ8k7XxExahHBS5aTmQUI9blxUeZj3xUgqQbKBIfBVlXYKkATtn49vLoQqGLoc/Wjz99B4YxjV2bgU033ZT333+fxYsXc/PNN7PtttuyxRZbEIlEStoVKnVKVVRb2XvvWnWXOaZ3bPW6/sN3Hx+f0eMLkD4+RcTj3o2nHwHpUwtfgPSpl3z6dVNT07SrlyS0GLpWXXTVjNUINZxc+Nu138RK3YmU3QS1DtA7cJ0F2PYLuPab1GP8ogA3dxNl6uuh3PdqT1Yto7yoVUxmaJ5KYSNLZAZdgYmGVuV9Hh4lOSRIOnQvvgDXPRRN06b83CKdRUi5DE1rRzPWnKQxPybZcwjK/Zh8+qpr/QcreT1gAnadPbko2YWduZdA5GCCDd8h039ahbY6emBb9AppzhOJEEYdknr5r+pSyoJYPRERkEpZ2NlnkLIXTV8NMEglLsXOPjmsZa3PzPiTTd9bVYBE1WsONToTqXoYiP82P4my41n2K2Sy/yQc2nHcxx4ad+R7UipACkxjtco9KJdFvT+qOZLEJet8WLWNg5ZLhx62bUF8FNhK4KLjSuh2G0gqz9laKUi5Bi4GLnnBdnTXUIHgRxvejqFNb/ERYL311uPzn/88zz33HIlEgscee4znn3+eOXPmsMYaazBjxgxaWlowcs8TNARI0FEENEWDLtkgnKVVdxlwNbrsaSxA5mu+TPaYPj6rAL4A6eNThJ+C7VMveQHSP1Z8ajHdI9pGi25uQLjpxyOWZ9MPM1gl/bkcCjDCe2MnrqC22FD/3YSjJFaZuwGvdr8kpKqLkKWjDqWdD8S980lTUxRNm5r0Ntd6mczg+bjWfwrLdPMzBGIno5vrILQZhfqK44WSaVxnIem+Y1GFtM/865t/3+oVH4ewkrehpI2TuRuhteaiJ/PRtBrgopmbEGn93fLuwqhw7XfIpuajcuUJKt9Zapih3cqu6e/vR0qJYRjjfh1KJ+eTHPw5SvWNmM+KQK37cMNcFyGiKJWs0solEPjseE4LpSzSmb9TfYYGyfT9yyVAKqVQKo0QZomJTG/8OroGR9bVtbJBshmvhm1DU4JYaHcMvaNi/4Ppv5O0nq4yPig0XEIUHEsqtHPLHDPFaddpW6dTNXlmM0rg4O2P40JambgYRc7ZoxMfw6KRMzb6y6i2WdXZfvvtCQaDPP300wwODjIwMMDAwABvvfUWoVCIcDjMrrE0jvTcxi0lkErQaLg060PXyHfSQXqdaSxA+vj4jBlfgJwCFi5cyOWXX87999/PwoULCQaDrLvuuhx00EGceOKJI0LhfSYPX4D0qZf8sTLVUUo+Kz7FEZA+YycQ2hVNm5OrMVd/5FI6eT26Pg9yUZCVHauDQLpmf0qpsuJjMTaS4CjSBfP0D3rlPxoib2El/0IgemTZdtJZiJN9EqVs9MCm6OZnR0TXSucjHOt5QGEEtkYz5tUc37FeJNV9MMMjqFz7v6T7jsn9FcAM70+w8TQ0fXbOFOZxpP06EMAI7YJurl/X/irZT2bwl9ip2yiOLh0vpP08Wft5hkQ+r9ao0GahB7cnEN4PPfiFCUuHLUcm/hsy8UupXvsRvDkHCEaPKLu2OP16PCOr08k/kxg4q8LayQ75KU+wRrq8EGEi0SNJJq6h/Jx1dGMegcB24zovpSxqy6MKVcEUSSmF436CUhkMYy6aCJeslypDf/yP9CeuxZVLAY1oaHdaGr4D6CztH/ngBiA+4F17wtEEgUCImc1nV51hT6LYObx4fuAiitKprTJbD1FOfCxevsRqIk2Q/OfTyd2WWi5YBJFoqKL03/pRrB35DEetfd4ot5sebLXVVmy22Wa8+OKLvPPOOyxdupRMJkM6nSadTtOsUfZZg4snHv8vHmaRY5QvJ+Lj4+NTA1+AnGTuv/9+Dj/88EL0FEAqleL555/n+eef549//CMPPPAAa6+99hTOcnqilCqkYPs1IH1q4adg+9RL/liZDgY0E4kQBk1t19HffVAZh+3KKNWH4w5Fcnle3MNvnEw0Yz2k80rN/tw68qBcqOgwWgmJKgiQzY2DZAZ+hGu/ixHcBiO4C0ILI90+0v2n4mYfK9pSoRnrE265Es1YFyfzCNn4L5FOqaOwHtyZcPOvECKCnbkf6SxgSJizEdpM7NRNeOJjNaHJwk7fiZN9nFDThWQGzkHJxeRrAWbjF6IHdybScjlCG3l+VEqilOuZ78R/w0QIjyPJv2c5d2m5DN2YhzFhabDlsVJ35cRHqH78aiCCRFuvRdPnlG0xEQ7YSqZJDl4wbv1NDCFCkYNrtmps/CG29TKW9W+GTK4ANDStidbWa8e9JIYQUXRtJq5cVqWVwjQ+NWJpPHUXPYO/wXbeLfTVFD2M1oYfINUAruynq+8sMvZLRfsiSWYeJZl5FNPcmkqidsGApinDWjPvI2hWv8ew3U9G9KMU2GjIUQiC5c4iUoFCsMyKki6qqesqr18nJz4qJUY1VjGHrP5jPt209ai3my4opQgEAmy77bZssskmdHd3s2TJEpYsWUJnZycLlnSio7CVwJJeirxS0G0bfJQ2yaqcOjmNAyCFUohJNoWZ7PF8fCYKX4CcRF5++WUOOuggUqkUsViMs846i5133pl0Os0tt9zCH/7wB95++2323ntvnn/++WljVrCikEwmC05w/mvvUwtfgPSpl3wEpC9ALj+GuTEtMx4jk7yBTPpupNvJaAUstyjl2SNMrP0OlOwn2Xt4ja0jSCq7aRej8AxqilOsNaob1QzEPQGysWEQhcJOXY+duh6IoJkbI+0XKHdbL533SHbtD1ojyPLOtW72SRKdO4JKwYjU32ppwGV7Q8ke0n3HF203FDXpZp8i1XM0kfY7kfarZBLX4mYfB5VkLKnU44/CSvyJQOyEOl2yx2FEpcgkrqDWa60ZmxAI700gcgiaXrm240QY0GSzf8+J+xODbmyGprdjZ/8x5j4aW39XV8SqEGHa2m8mlbqDVPIvOM5HaFoj4cjXiEaPRtdnjHkOlccUNMS+Tv/gL6ks4gti0UMKf7myj6W9p5DK/L2klVJJ+hN/oD9xPdU/My4gSFnPVmyRj4Bsas7WFB8t52MoRDgOHacSgawzBT9vLiOLjGcK0ZNKMOiYJImUtLeUhiV17BKX69GIj4o2s5mT1//zKLaZnuSvQUIIYrEYsViMefPmFdZv9N1LCUtBGIkuICsFmWGO10IDtWIERPv4+Kxk+ALkJHLKKaeQSqUwDINHHnmEz33uc4V1u+yyC+uttx6nn346b731Fr/61a8455xzpnC204989GM0GkXXp/FjPZ+aOI5DMunVlvLT9X1q4QuQ44uuzyLaeAbRxjOwMk8y0HvYqPuQhDHNzxKI7EsgcmChjppufhbXfrHCVhqR1puw+74BNR12ITvCbsZLJgxWqQ85mBcgG+Moim+/U0j7PyVtFXn3bYEnQiRAVhOPJKjBkh7K/14v1e4+XVz7ReJLN8qJjqMVOCcepfqQznvo5oaTM57sGhGVOhIDM7gdoYaTavY33rVlHfs9sqm/MRHvlaatTmPrdZiBDQBIDJxPOvn7UfUhtHVobPk1gWD9dRuFCBAK7YmU3aRT96BUAtt+Hdt+HU3rmBBTsMbY8aQzj5K1/kfpZ8SLwmxr+QVGTvz8f/buO06Ouv7j+Os7M9uv36UTQg2hKTWAgIA0RbqCFFEQkCIoP3tDwI4odlSkqYggiCBdQbpgAEEC0gkhEFIu1/a2z8z398fs7O3e7e3NXku5z9NH5LI7853Zvcnd7ns/3+8nmf4rK7rOo3bAGCSwr/xpMVipArKl+oc1Wmu6UzezvOebOKUu85Xs0nVR+znTGq+bdVn1oqNVMXw0KGiTLt1MeTCZck1yOoLGpP5rzzunWZE5nLHl5K7luqHw1hQt/j5RChywXUU/ZrEbttcZGxSlb6vLurIk7Nqh8S7eyT6mEBuAqfyjY1I98cQTPPDAAwCceuqpFeGj73Of+xxbb+29OPvJT35CobAuVAlMHdIBWwTlr/9oWRaxWGyErcVU5jhO6WeLBJDjLxTZG8OcR71zwTRpoi1fx4q8h1zmr2TTN+LYb9HQcTNW9AMMfpOtVCuJ9hsIR3ehpePWgMeoflsOt/Rmb7BSE5pG75px0aX/eft7FZVu8RZdZZt1SqkJyDp4bsCknpcO9ppOB6wQ9Ssgx9oB23W76FnzUbpX70M+dyfj/5yEaOm4oxQ+AsQaTqOetyDxxq/QMfOhusJHgELhBVatei/Jvh9g2y/gOMvIZf9J15oT6en5HHoCSrgMI86MjhtpbjwPwxioTo2Ed2VGx3U0Jrwq63TuMVZ0ncN4VQQbNaYrJ/u8Csjp07Yccp/Wmre6vsayrvOGDR8Bgq7FONA0xpu2a2uFg4GrDWxMepw4/vdea+hzQmR1tBg+MugYwa7F900/kU9ucVmgbcVQSikMw8AwjGIo732spRwNjgYNSitUsfOzKs7ON6QCUggxClIBOUluueWW0tennHJK1W0Mw+BjH/sYX/nKV+ju7uaBBx7gwAMPnKQzFH6oJOs/ipGUN6CZiAoKseHo6+tDa41pmiQSibV9OhscpQya266gp/MYtE5ST3OaZM8XcArlaz4qwtGDaGz5EYofks/ciXaTmKHtsCK7l/6th0KbEosdSyZzE6NpyuGtuOgSHhSaFgoWmYz3gYYfQPrbe/8d/s14+TbSGCAg1YRhbT55hzNnoIx2tLumxlY2VujdI47lum6pAnIsU7C1ztOz5nicwgujHqM2k+a232NalSGpac4iGj+RbPpaaoVMprUtDc0XEI7U3yzGdfN0dh6LdnsGHcP7GZFJX084tD2JhuqvycfCMOK0Nn+BlqbP4rpdKBXBMCo/3O7q+xl+J/axcjVD6q192lX093nH3njO0UPu783cRVdq+E7R/tTpIOdgGe245EFnS2tGFkehgEnWscjoCKDJuoqsGy01nhlMKTC0Lv6ErXZ8jULx+S3/QCIiS+GMJ8OleFkqlKsrKv0UgOlVSWqZLCaEGAWpgJwkDz/8MOBN79155+E/wd1nn4EF0R955JEJPy8xQBrQiKD89R+lWlaMpHytUAmrJ4YV2obW6fcSazgLw5gFZY0NanEKzw26RZPP/oPu1ceCihBJHEe08XRC0T2GfO9aWi8mFvsQ3tsxA/CmcCsV9zpuj/CG3Qay2qmohPTXf4yEc0QitbvL1rJOVkKucwzCiZNQKti1Mh6UsogkTmb4l94GSrUSih0y4li9vb24rotpmmP6PZTL3lX8d1BPCOZf7wqwiMY+hhV+z5BtQuE9aJ32COHoe6uO0tD8LSKx4xn8bwjCxBsvoGPWW7RN//sow8c0nasPKYa9w/17UPT3/2bYauTxoJSJaU4bEj66OkMm9xDjET46pYCw+uNIp5pwHQvTVExrH6hCddx+OpN/YNmaL1bdz69ezGGWdb2udnxFTpvkCZF2+3AHhY+uVhS0ScoO0eU2Aop+xyTtxsrCx+pjez2wBz5eGfivxlQhzpt/pYSPE6RUAakHZl2XvkuOBleXKiGnJK3Xzh8hNgBSATlJXnjB+3R5iy22wLKGf9oXLFgwZB8xOSSAFEH5FZASQIqRyPqPk8M0Z9HQ9BUamr6C1jnWrNgRrXtH2Ktqj1Zc53+kkz8l0VT9jTmAUhFa235Ko/1ZMpnb0G4Sy9qUaOxwVq86kCBTB10gi0tUe9PeSus/llU/jsbIq7SNp3VlbUcD7yVtgdrn463DZ0b2ItJ43oSfldYuheyd5FN/wLFfARIocw7aWUblc2cCIRJtl6NUZMRx/enXra2to/5gQ7spMv2/Iej30DQ3J9Z4Lq7zFtrtxjA3Jho7GsP0KjAdZzlO4RVQUULhHUds7qNUiKbWS3AazyGXuQ3X7cG0NiYSO3JIYFev3p6vYtsjvYbWOM6buO4qTHPGmI5Xr1z+ecbj343W5T/Fql8H+fROALS1dWAYXiiYyb/A66tOwK6xlq2Dwh5haQtHKwpVtvEacHn3aQz67RB9OoHWipRrkNMxdIAaGKXA1BqNgzuwCiGbxt/F8ZucT8gY+d+KqJ9y8EJGQLkAmukxh7StyDkGtguuodaJn/xCiPWPBJCTIJvN0tnp/ZLfaKONam7b2tpKIpEglUqxbNmyyTg9UdTf7y3eLwGkGIkEkCIo6ZY++ZSKkGj6Ov29Xxj1GOn+nxOJHY4VWlBzO8uaR2PjOYNu2wTHeZMg1U0asNGEGAggm5vGFkB64+riKl6jYWBY2xFuOBnXfhs792Cx+7aJF+DZgEWk8QsUMjfj2q8wHpVcw7MY6Nrtdz/weeGZMjcm1vpb7Owd5FNXlTXbCWOEtgW3D62TGNYmhOMfxYodilIT+xJYa5tU99nY2bvwg09YXTznGIY5A9d5G1SMcOxwIg2nY1q1OxT7xtIBW2uXdPJS0qnfFDuijyRCS8dNWKEda4adpjkb05xd9/mY1jzig/4N1UvrArb9BqBRKk4m8xfWjWB8KK1dVnR9elzGCrIARFeXtw6rv1ao62Z4fdWJ2G73sPv4Xaxr3V8ZUA40lNFAQSvyWGitWGMnyBNCa0hri4IOF9eIDEYpv0bW+34eN/ciNm/aKfD+on4KL3hUxd8jiZDLwukZwMslu3Mmj62MM6UjSJfJ/KRv4JhCbAAkgJwEfmUdQENDw4jb+wGkH4hVk8vlyOVypb/7gYgYPamAFEFJwyIRlASQa0cs4XXGTvV9u6ISUhnTQBfQumeEEVzSyZ/T1PbLuo8dT3yUXO7+wNt7AST0Jr3XB00N4xFAjva9kQkqQqz1B2XdoT+DYy/BzvwN7XajzI0JxY/CMFoJJ04g2/cDCukbgFytgetkACZW9P0ooxXD2oRQ/EMoFHb+v7iF57zptSqMGd4NK7IPShlY4a2INJ7trWmobczQApSxdn6n5/ovx87eXfxb+TtHDeTRukDzrFdQqv6F1MbSAbu/9+tk078nWECnMK1NCYXXrcBH6zzZ7L1kMw9h289j2y8X14AFVJx6AvG+3otpbvkWhjE5a/Smsw9jO2+My1hBvoN9vd711draRG/6Lnoz92C7qwOMW/0nyECX64GA0luDUnlVilqRwyLnmKxxGwGDggs5wrjFhjT1/XTyzmbz2I58ZNNvyVImk8Hxp2B7f01EvO+Bo73lH02l15nadyHE+kcCyEmQzWZLX4fDtaekAEQi3pSCTCYz7Dbf+973uOiii8Z+cqLED5WChMRiapMKSBGUBJBrTyxxAtH4h8jnHsR1OjHNWYQie9PTeRR24T8j7p/L3obWP0brDNn0TeRz94O2CYV3IZo4Ydhqr2j0YCLRg8hl/0GQt2j+FslxmoJdQTVhRY8AvQY7e+dIG2NF9ifS9EXM0PyKe0xrU8zGzwzdw2gi1vJtok1fJtt7PoXMzYz2bakyNkIZCVBhrMi+hBMfxTBnDdkuFN0HovtUGaE4jopihXcc1TmMF60dcqkrGf65cNDu29i5+whFD6p7/NEGkHbhVbLp39W1TyxxUl3bT7RU6jp6e84HhnmNHKiqc0Amcz35wlNMm3YHhlH99Z/r9pPJPoCr+whZmxEJ71YRhLlumlTmb+QLz6GIEI8dQCS8+5CwzHVTrOr5Ul3nN1b9vS0AZI3LeKPzmUD71KpQ9MLHgYpHu1gn54eKLoq+Qph+EjhakddmsVKycrtgvH8/OzQfzAc3Gp+qUTEyVWxCo/A6Xzs2rOi3MBQ0RRxWpy2UM/kFgEKIDYMEkJMgGh1Y5DyfH3lheb+yMRaLDbvNV77yFT772c+W/t7X18fcuXPHcJZTm+u6pFLeNBWpgBQjkQBSBCUB5NqlVITIoIAnGj+B/t6RA0hwyOceI9l95kB1FZpC/lHS/T+nsfVnRGNHVDmmQVvb5SSTP6Y/+QtGqsYyzDkot6/UhGZ8AkiTWPsfscK7oZTlrUWY/iO5/ivQzhLvPK3NCcc/Rih2GNpdgzKnYxj1V9QBKKOBaMsP0DpVrPoz8R63919lzADVDDqJUjGUOQ8ztAXK3ARlTCMU23dSG8JMNNd5G+2uGmErCzv3xJgCyHqnYOcyNzHwvRmJiRXajmj8I3Wf30RJpf5Ib8/ol1YYjmO/QjL5Y5qbzx+4ze0hmfwT/Zk/YttLKK9itaxN6Wj9CdHIQjLZ+1m15oziz4gQoOnrv4xwaAdmdPwe05xW2m9l92exnfFZXsmf7lw7BjLpT3YAkGhaEWhct6Kpjaq4PV9ahsFvfjNQzaiLVZCr7AYyxEpVj/WHjj6v2cxHNrqQLZoXjmJ/MZjfcGmkKlK/LZQqXvI9WYtnVniRgWmUXXVTeEqw0ho1yU1hJvt4QkwUCSAnQXmgVWtatc8PwmpV4kUikVKlpBg7/zlXShGPx9fy2Yh1mW3bpetFAkhRi9ZaAsh1UDR+FKnkJWh35QhbJujrOgPop7KSzQVckt3nYFqbEwptN2RPpcI0NX2JXPZRCoUnax8lfgKx6AfpS3qVaU2NI79OGJmDYc4urXOolNf1ORT/aHF9RBNVXu1ldoz5iEqFiLX+Bif/L/KpG9DOMpQ5jVD8w1iR/Uc11Xh9pQI02PA2DLhdGa11RROaerjOSKGoL0w0/hESTV9HqeE/DJ9Mrpuit+drEzZ+qv8ampq+iFIRkqm/sKb7MwwX1Nr2UlasPoaO1p/QWbFdobRNvrCYFZ3HM3v6PShlUrCX0p+5nSAVwoZqJR7dm3T2EVzdNeR+r/JwJArHNkglvfcKiaaRl2qytara8doLHwfeMjpaFUNKVVov0sGgpxAphY9ZIkPGKUaVQ26vTnPWZlfQFqt/XVFRXeDp6w6lcFE5XhBc/BuOAxjFtTnr//ElhBASQE6GaDRKR0cHnZ2dvPXWWzW37e7uLoUbUtE4ecqnX/tdAoWoxv8QwTTNmlXKQmQyGWzbe5soYfW6Q6koze3X0bN6/xpbmZihbXEKi2qOlen/LaHWn5b+7jpd5HP3onUaVAuFwlMjn4/RQt7eiHzBW6KlqXF8XpopNbSaXynlVSJOEKUUVmRPrMieE3aMdZnWOezsAzjOCpRqR+s1Nba2scLvqfsYqVSKQsELulpaWura1zCnB9jKom3GE5jjEEqPF601XWtOAkaeRTR6GfL553F1ljXdIzXFcYECXT3fwP9AYiiHQuF5Mtl/Eo8dSCobfF3YtqZzaW08k97Udazq/nzVo3uGBkp+ZaTCAvvDaG1gWgWisdpT0x09fNfr8mYzulQhWbkeZLcdJ63DFLQiR7jquSkFJi6OHm4dSC/oMnE5b6sbiVqyJNJ40VqzfPlyLMuiubm5NDtPaz0kmPSqHzVKF79LGtCq1AdMFztjj77R2QZAa+/PZB9TiA2ABJCTZOutt+bhhx/m1VdfxbZtLKv6U//iiy9W7CMmhx8qyfqPYiTl069lMXRRi1/92NDQMOzPfLF2hEILiDd+jnTyR1XuNTHMWWhnpCmLLrnMvdDqdTzu7/s22dRV+NVQbsA3C329X6O//2UgSiKRYNrGT1PI/ZfUmsMY/TL/MYx1KECaCvLpm8j0XhSgwRGAiWFtghXZu+7j+NOvm5ubA/1csQvPkUn9nkL+ieIUzFrTr00isWPWaviotYPWWZSKo5RCa5dk8mfk849P+LGz2Tvozz4ScGuNqztH2EaRytxGPHYgBXsZQf49xyPvo6XhkwD0pW4aelQ9/MzXgenTCnBYsepfwMEkmvqo9XJFayhgUK060Z9aXb7Go+tCrxOjnxigKGhwXJMcIdxhQkyfiYsuNqwZON7A89KiIpy99V/k9dU4eu2111i0aBFdXV2kUimi0Shbbrkle+21F42NjRUhZKFQoMF0iZguhZwiV/DC4vLvklagTFkDUggxOvKOaJLstddePPzww6RSKZ566il22223qts9+OCDpa/33HNqVhCsDRJAiqCkW7oIyg8gpfpx3RRv+D8MYxrp5E9x3XeKt5pEoocSb/o63auCVKd5azYne75CLnPdqM9ldeeDwMGlirZQ5N0kOu4h1Xkoo6v6kreGkymf/ivpnv+rsYWBFxt53xdlTCfRdg1qFHMY62lAk+7/Lam+Cwm27qOJUg0kGie32Ydtv4XrrsR1+0inbyKbuQ2wQTVgGu04zptMVr/dXPYJCoVnx3FETT7/DMn0LfT0/ybA9iYzWn9aui4cdyDgdIvB43DrPrpllYm+VJ/3u6ehsfr0az94dActGeBXOboYaMDVqtTlOmcbrNKtpXMoaMi4YWysquc1mFJg4aCLlZDar3pUDk0qzpkLJHwcT8888wz33HNPRUPUTCbDokWLWL16NYcccggdHR2k02mefvppHn30UfaamyFvK7IFg96UwYoei1ROlSoeDUPh2jCl+2BLBaQQoyYB5CQ58sgj+d73vgfA1VdfXTWAdF2X3//+94A3rWa//fab1HOcyqQDtgjKr4CUAFKMxL9WZP3HdZNSiljiJKLxE7AL/wOdxbQ2wzDbse3XKF/PbTiGOQ3bfq1q+FjPW+j+fu/nSfm1EgpvTdPMZ+lb8S7qDyFHPndRndYFtLsaVKzUlEfrPE7hRcDBtLasWD9Ta5tM37dGGNXCsDZBqSbC8SMIxz6EMkb3O8QPIEeafp3P/asYPkKQpjNW6N00tlyKaW08qvOqVz7/X/p6v0k+/1j1DXQ/jjMe66EGl3OWjvuYeftVVnSdy8gdO0waY0dhWe2lW0LmXPKF13BKMV31nyq6Inwc2KY/6QWQiabeqvsVMIuViAMcrSgUqxj99R39RjJ5RxXDR68JjYtB2g3hYFFPGKWU1xPbUA6gMXBZ2HY8e804NfAYYmRLly5l0aJFZLNZGhoa6OjwKpu7urro6+tjyZIlvPTSS8Tjcf7xj3/wzDPPoJQiZEAorEmEHdoTDjNbbP73ZpietOlVP7reRyralaBYCFE/CSAnycKFC9l77715+OGHufLKK/n4xz/OHnvsUbHNj370I1544QUAPvOZzxAKhdbGqU5JUgEpgpIKSBGUVECuH5QyCYW3r7xRB2vvaYXeTS59CwMVbuXjKpTWgd6W9yf9ALLyd5BhJIg1nU+m7/xqu9UgTerqpd1+sv0/J5e6ttioBwxrR8zQ5ti5f6JdvxlIlHDiOGKNX0YZCez8v73AsqY8saYLCEXfO+bz7OnpAUaugMz0X07tykdFJHYM4ei+WNZ8rNDELvujtVsK9h2nm641JxKklcpk0Vrj6KBNeoJzKW/iMbyQNY9pLReU/p4rvEwotD12gLUjhwsn/QrIag1oXG1UhI+u9gJJP2wcmJbtje24sNL1Kh9dDY42yGuzGD5WP/5IZx1VCQ6YdS4Lmt9X574iiP/973+sXLmSaDTKvvvuy84771y676mnnuL2229n6dKlrFy5kueff55QKMRGG23EvYvewlKa5qhLU8IlHtZsNSfP4jcipHPFqfqmmtJdsIUQoycB5CT66U9/yp577kkmk+Gggw7iq1/9Kvvttx+ZTIbrr7+eyy+/HID58+fzuc99bi2f7dQSpPO4EDAQQEqoJEZSvl6oWL+Y1jyUakbr6pVDvmjsGPK5fzJcwGASLGJJ9nu/e6pVtdn2KwFGqBSK1r+24FSltYt2++hfcxyu7VU5+lz7aVz76UF7ZMmnfo+Tf4aGjj+j3VqNZsqOE3C7kdSagq3dNNnMzeRzDxSvy1qVjxrXXUk0dsS4nNewR9GadPpa+pM/x3H8Roz+eoPrzpRC75ka+kHCWLll/z+8KHOn34FpNJPOLWJF9zfIFhYX7xs+2PPXgxxcxegrTcFu6itVSTqlUDGEv3dll+uBXtX+144Dy4vho+162zqYZQFlvTTbNR7A+zf64ij3F0G89tpruK7LwoULS+Gj63rX4s4778wbb7zBa6+9RjabJZFI8KEPfYhNNtmEX//tEkJaEw9rNu4oML3VoTGmaY27ZDIGWgGOHvV3f4MgU7CFGDUJICfRjjvuyA033MBHP/pR+vr6+OpXvzpkm/nz53PHHXdIddUk8ysg5XkXI5EKSBGUXwEpU7DXP0qFiSU+Trr/F1QPDwwMcw7h6H449ksMF6QopbC0xhl2C09/MYBU6qckk08Sjx9fagRSyNxd9/lHGoZ2zhWV8pn7yCYvwbX/R/1BmItTeIZM33exwvsG2sMwZ9V7ilUNF0DahefpWXN8MegMGqRNzBtarfNks/dgF14ll/sX+fyjg7YY79IphfeYR55qXo3Wutg8ZXT7Vx2TYI/S1aDRvLJ8V1xdIOjyCd706OHDSddVpItLO0Qb+shhUhlmDvxUKgzqcq3xpl57jXYMlrstuNrA1oo8oWKVJNRf9QigOXTW11nQMvZqYDG8QqHAmjVrsCyLBQsWlBrNGMZAbLjFFlvw/PPPo7Xm/e9/P/PmzQO8NT+dAvQXFC+lQjTGXBrimpaEw6ouA1sboL1GNEIIUa8p/eHF2nDYYYfx7LPP8n//93/Mnz+feDxOS0sLu+yyCxdffDFPP/00W2yxxdo+zSnHDyATicRaPhOxrpMAUgQlFZDrt3jjeYQifjO48pdLJko10dx2FUoZROIfotYbcaXUCH1hB9aAjEWfI9n3PVau2Il0+q/enXqk6b1egOHg4uDi0oAyRm5QMlVpbZPsPIl098m49vOMJYTLp64h3X3yCFspDHMjzPDCUR/HZ9t26edKebWs6/bTs+Y4tNvj3xJgNINQeI+RN6tTNnsfK1bsSHfXGSSTl1YJH8eXYUyjrf0GLGvTUe2vtS5GfmMPRf0e43bxjzdijZCw1OylgKtTeGu9BqsMrVzzcegx0v2NaG1gmDZmPF9lG106B42BqxV5bVDAwC6GlXnX5G3bCx8dDBys0hTtUU25NmKcO/+vEj5OAv8D0EQiQTgcrtrYp6GhAa01sViMrbfeurSNcorfZdvFtRWru7zfYA0xF6cA2MUI2pnCFXnuWvojxAZAKiDXgnnz5nHppZdy6aWXru1TEUWyBqQIQmstAaQIpPxakQBy/aRUhOa2P5DL3Ewm9XscewnKaCQaO4po4mRMcyYApjmDWMOnyfT/tMZYXiVktenYhYJFLhcFoKEhWbzVpqf7Uzj5Zyq29YLGkdaV7KN71Q6YTCcSP4hI4mTMCV7fb11l5/9Drv8K7NzDaO1ght/lTVstTGwoNsALamLN3xlVx+vB/FAhFApVfGCay9yEdrsJHqYqwCIWP37M51Qun3uSrjUnM/BOefwqCodSQIiOjpuxQpsTiTxALvcw2czfKRSeolB4GchSXg3qVToOGKiZVIwliPazgcoRagd03pTo0t/qOp5fpVirKU1vn1d5H29MMjh78pvLuKW1HhW6NC3eu63PidDrJnCKTWi0VsWqyIHBDPzns9Zj9ZrMvKf9o+w+/eS6HqcYvVQqhWEYaK3p6+ujvb0dx3EwDAOlFI7j0NnpdVlva2vDMAxc1/Xud/FCRhfAJZX2u197DWgUGtcGZUkTGiFE/SSAFFNePp+nUPA+/5YKSFFL+bUiAaSoJZVK4bouSin5YGM9plSIaPwjROMfqbldovELaHcN2fS1NcbyQsjBhQz+9OtwOEc4XDn9Mpn6LWFaMejBVcFjCm8K5SpI/5F8+jqU0UGk4Swi8ZNQRizgKBNL6zwQqlqZM6rx3D4c+xXAxAxtQz59I5ner+CFI94z7kxwNd5ghrU5saYLCUX3GZfx/AY0LS0tFc9bLntfHaOYgEFT228xzGnjcl6+ZPKHxa8mvjJKqQba2q/ECm1e/LtBNLoP0eJzrbVG6wyZ7KOkUteQzT2EO+gjgPoCwBD+9OjyrQcmMtd3HY8c3A2zX6njdfV9vS7WBqliB+x4Y7J0nx88OmXNZWxUxZRqx4FVbhM2VqkScuARVx7TCyD9+6ufj4XiuHm/YGZ8Qd2PVYyeZVl0dHSwatUqXnrpJTbddFNMc6AWf82aNbz00kvAwIekpQpIV6O8TkMoIGJ63/98zquO9L/baiI/XxBCbLAkgBRTnl/9GAqFCIfDa/lsxLrMr2iLRCLSpV7U5E+TbGhoqHjRLzZMSikaWy4mEvswqeT3sPOLAI1hzCAaP4Fs5i+4zpul6dgmUCguKO9Pv25o6K86dh5vzT9DexVb9QR2NhoDjeGuJtv3LfKpa0m0X4dpbTSGRzt6rttLrv8K8ulr0W4nEMEMbYsyp2EY7Zihd+HYr1DI3g06ixnalnD846Aayff/CrvwPN40VeXFJkYTVvRgtNNJIXsnkCseqQnwO/+unWmC8darCUX3H7eAFSoDyAran7pbm2FuTCR6INHEyVjWZuN2XgCu20Mu99C4jukpD7gU4ch7iMWOIBY7CsOIl7bSOkc6cw8F+zUM1YBlbkxX7/nYzjIYRYWjPxHaCwpNGuPHoXUvycztZWNVD+aqjqcHqiRHE1hCefhYnR8+AqSTxWUdigGkrVUxUPSp4jkNhJk5x2SV24ztqmJTGu/f2XC/wZQCU7vFQHNwCKmJG02cNf/P41L9K4LTWjNnzhwaGxtZtWoVL774IrFYjPnz59PS0kIymeSee+5hxYoVKKVYs2YNq1evZtq0aejihaocF8OBkKlpTHj/CvqTCsPWaL8BtjF1KyCV1qhJbgoz2ccTYqJIACmmvPL1H8fzjYLY8Mj0axGUrP84NYUjuxKO3IzWthcKqRhKKaKJj9LbdSZO4Ykh+/SnvArIgenX1flVk/XG2V7FpfaCBOd1kqveQyh6GPGWS1BlAc5EcN1eCum/YOefQOs8TuE/aLeLgUeTwyn8p1hYZgDXVexv5x7BHibU0oB2esinflvl3r4qt00upcavutPnN6BpaWlB6yy5zJ3YhWfQup/ajWcMrNDOtE67ZVzPx7bfIp2+Hsd+o6yKbjT8BjAhQqHtMa15mOYcTKODQuG/aF0gFH438fhxGEYb2dwDrO46i3z+WZSKEgptQzb3CFr34b218esS/XOqP3z0aiX9/V36hq1uHvlxu3rwZPTgz5UfEg58Z4ff1y6rbEz3DVRA5rRZmmKttSoGq6oiCO0tROlx46QJF7cdeO5s8CdsDwlPDQVKuzil8bwPPbZrOIiD5kqX67XB/7mzcOFClixZQm9vLw888AD//ve/cRwH13WxbZuddtqJnp4eXn/9dV566SU6OjpQSqFcjWF7lZAd013aWr2rL9nj3QbeB2KuKYGYEKJ+EkCKKS+VSgGy/qMYmXRLF0FJADm1KWWBGniJZZozaZt2C4X8c2TTf6CQ/w+2vQSt0/Qn/QCyegVkORcwit1M6+WFKpoQmkL2b/SuuJdE2+XjNj14sELuUVJdp4JOUz4NenjV7l9/V91Xxvj/nvArIJsakqxZsQtad+O9lB+p57JLrOET43ouyeTPSfZ9n9H3szSAKI1NnwVsTGMa0dghGEbzsHtorenqOZ9k6koo61ptO2+UbVU+zbr+gGQgfAwiWOXjQPhY5zRtPbjZTPXxS1+XbeNXQIYaU6XbdalCcqAi1NWwxo6RcmNkiBTDx3Levi5mMQYd+v1WCixcQGHiMC++o4SP64Att9ySD37wgzzyyCN0d3eTyWRQSqG1ZubMmey11150dnby5ptvct9999Hb28u2225LIuwQC7s0JVzmbKwJRzQ9qyHV6aByGkwDLAM1lZvQaF35j2+yjinEBkACSDHl+QGkrP8oRuJXQEpYLUbiB5ASVotyofB2hMIXA5DN/IOuro8PVEAmRg4gwQszxvLizdEODgpbJ0l3Hk80dgjNLT/FNMfvd6BTeJXUmpPwopxgXX03JMqYgRl697iP6weQlvlrtO4t3lorLvOqIqPxE4lEDxu380in/kyy73vFv9W7EJwF2BjGDNraryAc3jHwnqnMzcXwcTTHDWa006OHjKMHx8L1jalHCB/dskYyg6eYaw2Z4tqy0YYUoErbUzamo2GV3URWhyhgVgkfB51TMWB0MKm27qOFzRaJvTl47rfqeqxiYiil2GGHHWhqauL1119n9erVGIbB/Pnz2XrrrYnH4zQ2NrLZZpvx8ssv8+STT/Lss8/y7q0LKBdiiYFr6p3nCzirXUxD4YYM3FgEYwpPwRZCjJ4EkGLKkwBSBCXd0kVQMl1fjCQaO5BwZH9S/d406ESACkgohhpaY4yiCtLVmrTWFX2085k7SGbuor31YhoSH61rPK01TuG/OIX/AmFCkb2x84+T7vkSfsOODYFh7QQkce3XCFKVGW38HEqN/9qvfhfspsaeEc7Dq4q0Qu8iljiNSOyI8Wv2ozXJ5I/r3MsLyCKRgwiFtyMcejeR6PsCPUe2sxLX7cUyZ9GX/A21p5rXzw8J3SG3ju758td6HE2TGa/AyQsBE9F96c0+UHW78rUeBx9Da8hkYjh2CNBEiz9X7EGNawoFeEe3YBMCVFljmloUBhqTAk4p/PSmZ5toDp71LTZrfm/QhysmgWEYbLHFFmyxxRZD7tNaY1kWBx98MKlUipUrV5LP54nHwA+0c/2ad14s0PtWAZQ3nnI0uFnc0BR+3+RqUJP8wZo7tT7IExsuCSDFlCcBpAhKAkgRlB9AyhRsUUt7++/pT30BCF4BCV7tl6u95hBBgyWtNVmtq9Yialw6u7+AZW5MNBosQHDs10l1fwq38Bx+wJQJeP7rLu9xWNEjvQYyFDBD22OGFqDdFLnUb8mlfo92VzNQdWbgTQe2AYto0xeJJI4f9zMrFAoDy4A09NbYUhGO7Edz+zXjenzX7SWTuY1C/jkcZ2mAPQaCQsvanMamLxCLBa/CzGQfoafvB+Ty/rqpXuXkeHKpNj169OEj1N8V26uUNLDMueSdd4orLkJ//jkGh61eF2tV0cV64D5FHhONIpn0prFHEikMUxeDTW/bZMGkh2YcrXDLQsd61vA0lBc6ljtq7q+ZHt868Bhi8ngd4YtrNxoD33P/d0dbWxunnXYazz33HMuXL+emGx7DyDo4GYeul5P0L016F59SEI1AQwMmYZxMfq08HiHE+k0CSDHlSQApgpI1IEVQMgVbBJVKNQGahoZUXfv5a9VZAdeE9CdD19LT8xVmznx06LHcNPnsbbj26yjViBnejXT36Wi3p+xs1j+h2Idx8k/iFtcQNKzNiSROJxw/fshzqowE0cbziDR8BsgCEbTzDvnM39BuJ4Y5h1DsSAyzbULOdU2nF8SFQgUikVyNLXWxKc346e+/gr7e7+B1IA9SKWfR0HAG0dhhGCqOaW1eVwVmKnMnq9ecPujW8Q0fNcOtzTj68NHVwYO8geYy3vaOs6zifsftHDJ2flAXa5+tjYrp1ZlSB+x+bx1JrUi6EXrcKGChK8JHVfr/IP+K1aCtNm3YhwNnXyRNHNdxSqlhv0e6+Dtku+22Y8GCBfzwyw9gdKbQnV1oV4Pr929X6IKNSqVR7W0YlnzPhRD1kwBSTHkSQIqgZA1IEZRUQIogUqkUrqtRClpbd6VQuL/uMWwUEWMWrvtO7e0CLGCfs18n3XsJpjUd11mFYU4DHSKT/BboFBBicN3Y+sXrBAxhYi3fIRL/CADaTXq3q8YRgxTv/pj3tTWHaONZE3rGduFlkj2f5u1lXcAHaWxIUvsUTUxrq3E7fjp1PX293yi7Jcj33iYU3olw+F11H8/VWdZ0/R8TtXaoP+po12asOmZxvcagZ+tXMtYzfqEUPlbu52iFTeVU9kyxsVW4IUWXEyVHlJRtkieMRqHQXq1k2YVk4pZ10a56FoBX+bigYU/2mv0tTBUK/BjE5PODxWA/0zyWZUHKwV21Bl3IV218opVCrV6DGQ2P+zmvN6QJjRCjJgGkmPIkgBRByRRsEUQulyOf96YmSQWkqMVf06+hoZFp0/+I63bTteZs8vkH6xhFk2j5EZHIe+jv+iTZ3N9HfT4ayKd+hhdy+NOKy62P6zpGaWi/gULun2jdj2lt6lUqlnVbnoiO1ePBsd+ip/MotE6STG4JQGNjcqS9iCVOHJfja+3Q1/f9OvcyMIx2otEDR3XMdOYuXN03qn2rG+iWrVUTts7gXddBa/6qj6m1RuOisXDxK8RqG6h6hHqCTxdVUVnp5xBeFXRlQxhXQ7rfu57tRJ4+O0aSRHH/sqpJNJZ2sIrr2Jlo7GIn66Hn5m0TIc/saCv7zKn3mhBrg1KKfD7PqlWrUErR2NhIQ0MDhmGUwsmqVqxC52tUWWuNzudQK1ZPzIkLITZoEkCKKU8CSBGEbdtks1lAAkhRm1/9GIlECIencIWAGJEfQDY3e2GYYbTS3HIRq1cdQD1TTvuTlxGN7kNj+9Wo3gvJpH47ZJugrTv6XBtLKcLYKKUwUKhxqBIrZ4Z2RRntaHcVrvMm2u0EFIa1Pa797DgeSRFp+ARWZCesyE7jOO7kSPf/Eq2TgEOyGCo1DtusyPsOxxv+Dyu0zbgcP59/CtddVcceJmDS2vZrlKrvLUY2t4i+/qvJ5oKG7wPB4kBgPtD+JWTNp6X5i0Qj76FQeI109mHWJC8p2z9o+BgCCoSszWlOnIhSMfoz95LM/QutswStBq6sehz531N5yOgWw1K/2nEgTKxcr1IXO11nixWQbqxAHwmGmzZvY6K0g6m8KuyIdkrrSA4WJ8u7WvZn4YyLAj1esXa5rsv999/Pm2++SS6Xo1AoEI1GmTNnDgsXLqSjo2P4nbPB1nbU+fXxA6nxshYqINfTpU6EGEwCSDGlua5LJuMtmx+Px9fy2Yh1mR9Um6ZJNBpdy2cj1mXSAVsE5a8VWj5VPxSaT2vb5XR3nYlXcTjym458/jG0dlDKpKH5QqKJ/6O/53QK+cfxA5KQUoGmYbtAXmsKQBSv4QR4DW+MQOv/1WISb72ccOyg0i1aa296twqhVIRM3/fJ9f+SoRVqCiuyH7HmH1PI3kw+/UdcZwVKtaKMBlz7BbyXtQ5+9WYodjTRxi+M8ZzXDq012cyN+N+/ZL8XKjU2VK+ANK35xBvOIRo/aszHzef/RS57P4XCa3XsaRGNfZDGxnMJ1RGAaq3p6fsuvclfUBkq1haLHoRtv45SUeKxQ2hMnAAobGcZhmrEsjYrVXgZ4R15p+vMOh4LgEE0vDMbTbsFcEsduwv2O6zo+T5aBw9fBsLHYEG+FzQaZUGgoqAVzqBqxyEdsIGsY5UqIEnUWrPT+/dVwMAsPudKQQQHVzvFRjcaC4d9pp3JVm3HYsiU6/VCMpnk9ttv5+WXXx5y3/Lly/nf//7HnnvuyR577FF1f13wAkgjpIg0hcj1FXALVaZiF6QJjRCifhJAiinNDx9BAkhRmz/9OpFIyGLroiYJIEVQ1QJIgFjs/YRnLiLVfyX9/T8PMJJNJnM7uew9uG4PprUJiaZvEApvR7LrXLLZmzGU8mq5AlZtaCCnNbHizzsvonDHFEJGEmdVhI9QXH9MDVSVRxu/hGltQbb/l7j2q942xjQiiU8QaTgDpUKYDacRbTitYhw7/1/ymb+gnVUocwbh2IexwtuP+lwnk9a6WGnoAmHy2Ttw7LdAD7xG6U/6AWR5BaQiHNmfxpYfooyOMf9ucpzlrOn8OLb9PPW8RWhr+x2R6H51Vz0CpDO3FcNHCBY+KkLWAqa3X1n18Zpme8Xftbbpz/wd21le55m5tDaeUTzGwBqL3f2/w9WpgOdaPIfieQdRGTR6HE3xtqHjuP60bg1rCjH6nQRO2vuQVDfkiytTDndsLxR1tVP8oMFjKI2BTZwcu8/4Alu2HBPo3MXal8vlWLRoUSl8bGtrY968eaRSKVavXk1vby+pVIpHHnkEYNgQEqBxTpztPrYJ6VU5nv71q5Ny/kKIDZ8EkGJK86vaYrEYhjHWyg6xIZP1H0VQ0qxIBFWrWZFpTqep+Svkco9QKDw9wkgGPd1nUaoazEE6dQ3R6CG0tF5OofN1HPsZwkph4IWQQaZju0DedQkVGxk4BOuBXF2YaOM5I26llCIc/zCh2IfQ7irAQRkzShVow7HC78YKv3vUZzeebPtVsqnfkc8+AGhCkT2JJU7GCm0NQCH/BOn+K8nn/gXk8KbzDe6CXvl4kynv50lDRQBpYFqbec2CxkjrHJ2dx+LYS/1HEWAvA9OcQyS6P0qN7sroTf6K4AsEAGham784YtiqdZ6u5C/p7b8Kx11Txxl5VZitjZ+mIXbI0PNN30q9TZiCRP5aQ35Q1aOvUGqeNHi6tbc2ZH8+xGqa0RjY6TigUKYDEZtgwWd5tbFGoYmrLAun/5+Ej+uZJUuW8NxzzwGw4447ssceezBtmvfzIZfL8fjjj/PII4+QTqd56KGHaGxsZLvttqs6VqTZq3i1M+tr07EJJE1ohBg1CSDFlJZOpwGpfhQjk7VCRVBSASmCGq4CslxL66WsXrXfCCP54U3lG5Rs9k661nyYto5bSfZ8jlzmRiylsJTCdl1qtBkoKeB10PamYyt0sY9uvSINn0IZwX9+KqVQ5oy6j7O2ZTO3kuw+t/g37427k36DbPparPAeWNZWZNPXMHLoNvCm33UVqZT33FU2oXGIFjt5j4XWLun0n3Hs1+vYywAMWlp/NKrw0baXU7BfJ194JsDW3vWmVJS2lu8Sj72/6lZaO6SzD9CfuYdU9l4cdyX1rJtmGtOIRfagpeEUYpHdKDgr6e7/PX3pW3HdNJHQVjhu94jj+M1mvMgwTEv8aLrSf656Ln4H7YEO1Kq0lqM/RrXY30aRdwxWOk3kiZT2dfq9Du1mIoOhdKDqS1X288PCZlaonffMuYKWyPh1UxeTY8mSJfT09LDllluy11570dbWhut6399IJMI+++zDrFmzuP3220kmk9x///20trYyZ86cIY1pom3eGtapVdm18liEEBsmCSDFlCahkghKKiBFUP61IgGkGEmQADIU2opEw5mk+n9d5d6RK8fy+cdZvWo/HKcYLulqLSZq00BGa+KAVgQMIC38FhrhxCeINp5X51HXfVpr8rl/kO6/CrvwDGgXGFzJCH7wZOcfw84/VrwtaMUfpNJxtDYwDId4zJ+WrYjGP4oVWjDq83fdfvr7LyOV+h06QLBWLhzenaamLxOO7FLXfvnCy3T1XFBsNhMkHFSErC1pajidRPwIjGE6lhfs5SzvPJG8/RL1VVQCGFjmDDaZuQiNTTJzN91dn6c3dTPeaqjeWHauk1rVj36YqMsqCjUOXekbht2+gIFbVuFoFxvN+I998Pb+f9c4cVI6Vtx2YDsn5U2/NhuymLjYNd/qedWOYcN7TK3WNPabfTEtUQke11dvv/02AFtvvTWtra0AQ2Z4zZ8/n0MOOYTbbruNrq4u7rvvPo488kiampq8NXmLl1Os1Qsg06uDfFQ1xbiaSW8K40oFpNgwSAAppjSpgBRBla8BKUQtUgEpgtBaBwogvfvPxzRn0p/8OW5pOqmJZW2Jbb/ESG+EHKeymcho3zrZVE4MtiLvxck/i9Y93g2qkXDsKJTZgXY6McxphGIfwrTmjuJo40frPJn+35FO/ao4rVuhjA7iiU8SazgFpepvLOa6Nn1dJ1LIPzL+JzxIf7EBTUMihVKgVAOxhjOJN3xm1GO6bj+dq4/Etl8keFgXYtq0OzDMdkxzVl3H09oml/8PKztPROsMwa9ATVPD6TQ2fLTm2G93Hk+hVMFZX/gIiumtl9KffZC3u87FdXuG2bb2VNSBikUYCAXLz6WysZKDKna49u5zNEMCRfByB7+JTW8hZSCZfwAAXONJREFUQh8NpW0Gws7iWq2pgQpIE42NS/WFE7zziOA105kd2ZyDN756xKUOxLqtq6sL8NZ+rLVMwYIFC+jt7eXee+9lyZIlPPTQQ3zgAx/ANE3+4dzIwZGPlCog08NUQP7DvXH8H4AQYoMnAaSY0iSAFEH514pUQIqRSAApgkilUqWpcSP9XFFK0dDwSRKJUyjk/4smh2VtSTr1R5LJl0Z1fKUURsC1IH221oSUwgSs6MEkWn8NuDj2K4DGtLYYVZg3kbSboWfNh70KxYFb0e4qUslvk0n/mdaOv2GYw/971Vrj2C+Qz/8HhcIK7U6y55M49osTfv4w0AG7ubmR5rY/EYrsilKxsY2Z/HGd4aPCsjYnFK6+XtxwHLeH3r6fkUxdi9bVO3gPz8BQjSTiR9fcKpX9BwX7lTrH9kTDu9LR/GUgzNLVR1Lv+o7gT7n2n8mRq4O19io0nbJg0KuGHPq2zNEKBwNXw3K7pdiPfmCfwccrVUAmsl5Xa+2Qxw8qK7eNkCdkuOzYegw7dHx61Ot4inVDNusFheFw2KtkHMFuu+3GypUreeaZZ3jqqadob28vNaVp3KiFSIsXQGbWDO12Heuo/aHZBk+7xYr3ST6mEBsACSDFlCYBpAhKpuuLoGS6vgiivFmRaQarOlIqVDHlNRR+N2OZBub32g1ei+aJNf+YcPyoUrWUFdp21OcwUezCS6T7ryCXuRkYfg0z13mZNSvfTbzhU8QbzkIZla8HCrlF9HWfh+suHWaEiedXQLa0bEQ4+t4xj6d1nnTqWuqrFIREwyl1be+43byz6jBs+w3qD/YMlIoxveMPGEbt12j9mXvwm8cEo4iGdmZm+68JWbMpOCt4c9UJxf3rWTNyOrazqmzadXX+1GwHA41VPI5F+fPvlK0B6XO1d7vW8I7dXBE+lo1O1SnYCe+aVwoi2MVu2QYaMHEIK02DOY0Pb3YDphEO/JjFuiubzdLY2Ehvby+9vb2B9nn/+9/P6tWreeutt3jooYdobW1lwYIF/PShb/Db3/4W7WgKqcqGVFvsMZ9fPfqdiXgIQogpQAJIMaVlMt5aShJAipFIACmCyOVyFArelDYJIEUt/vTrsVTKRiL7oFQbWneNan+lFFaxCjJIdKPxqiB7ey+mI3Y0IzQinnRepeKLZNM3k0ldVseeOdL9l5LN/AXLmo/r9mJamxAK7UB/3/mMpipuPPWnvGukuWXTMY3jV0U5zqo6qxENIpE9icePq+t4Pb0/rDt8VKoJ05xGInYojYmPYVmzR9ynvindAJrmhhOxzA6Wd32JntQf69zfs9mMO1md/C2rk1cMu7+rIV+aVq0ZeC7cimY1TjFEdIthpesqunQMlxCuVrhV3rKpyhndQHkAmRnYDk3E8NZj9WohTQ6bew0dsc3rfsxi3WWaJq2traxatao0Fdt13SFrQPq01oTDYQ4//HB+97vfkUqleOCBB2hrayOfz6OUYtrMadzc9QVeXPQqCxZuQWOLvK4RQoyNBJBiSvMrIGOxsU1lEhs+CSBFEH71YzgcJhyWqhIxPL8CcqT1H2tRyqSt/RrWdB7BaCshVXFKNVoHiolcrdG8zeqVBzJj1n2jOuZEyOcepb/3Ahz7hVGP4TpLyTtepaNdeJJc5s/jdXpjYJSmYLe0tNS9t9aaTOYWUv2/pVB4FjAJh/cIfnSjg0TiZBoaP4VSocD7uW6a/vSfqC+8VbQ2f5Wmho8Pu4Xj9pFM/4Vc4QUMFSURfT9hayvgjoDHMAmZc2mIH87yri/Rm76R+v/tKMLWphhGG12p4ffXpfBxYD/wQsYCZsW0aLfY+dp2FWucBAW83x+m0ri6cp3HcgZusYkNaNvEzXodsb0KSL+Htk0YB0tpdun4PFu0jr1zuli3aK1pbGwkGvUC6P7+frTWw4aP4P3sd12XadOmccghh/CXv/yFlStX8uCDD5Ya2EybNo3GlgZ2PWiHyXgY6w+tB7pCTeYxhdgASAAppjSZgi2CcF23dK1IAClqKZ9WK0Qt41EBCRCJ7EJr29V0d30SKF+rq0p51DhwKU52dV8gk/kHsdiB436MemXSN9Df8znG9/GujfW2hnZvDoXfQya7HdBXV1jtOGvIZv5BOn0dhcKTZWO75POPFreqfY20tl1NNLo/StX/dsFx3ilWJtbDJBH74LD3JtO3sbL7PLTO4rdD6um/grAVZF1K7/GHrfnM7vgdBXs5venRBsya9sYzyduv4wzbsMYLFD2V06rzWENuK2iDNXaCDNGK++wRQgdTAVrjonDSXvikLBsV9qbNxsnQYLlMiy1k4fSLCVtTfO2+DZTfcGbOnDksWbKEpUuXsmrVKmbMmIHWetiGNIZh4Lou22yzDatWreLBBx/kpZdeKhVmdHR0TNpjEEJMDRJAiilNAkgRhH+dKKWkWlbU5FdASgMaMZLxbFYUix1EeOaTpNN/JJO+Da0zWNYCcvmHQKcCjRF0NrUfQAL0dH2W8MzHMM3JDdy11tj5JygU/kMh/xr57HWTevyxMQGDcPQDuM5StAbL2hhlNKJUnFB4IVZoR7TuRhkdmOYM+vouBqC5uXnE0bV26Ov9DqnUlVDscOwpDzb9qsThwi2TcHg3otGDanbSLec4a8jlnwJcwuEdh6ylGURz45mY5tDAI5tfTG//tfSlry0754F16fL2C1jmbGznLaqtBWmZc2iIHU4iuh+xyJ4opVjd++Oq29aitYGLRqlWVif/SCz8XOk+v1O1X42o0EMav+gq4aPWkHMM3nFbhlnjceQPEkylMbQmnypWTSayWMqmDcUHNr+DqNku3a2niF133ZVdd90Vx3FK1Y8j/Rs2DAOtNfvssw+rV6/mf//7X2mJqunTp0/4Oa+X3HpWTx7PYwqx/pMAUkxpEkCKIPzp17FYrOZ0FiH8AFIqZcVIxrtbuml20Nj4GRobP1O6LZ9/mc7VHwBGrkQLGkBqvGnYhlJo1rByxVaEI3vS1nbNiM1CxoNtv0pf1xnFDtQTU+U5XmIN56GATPoPaHcNYBGJHkq88VNYoW1G2Ntb+zCfz5e6245UAam1pqfnS2TSfyLY81IekPm/22zC4V1oa78iUPjoumm6er5Bf/rPDASeJvHYYYRC21AoBOm0HaK58Uxamr5ccavjrOGdNWeQyf9rhP0dbOct2pu+Sjr3IJmcV+FpmbNobvgErQ2no1Tlkhhe5aJB0ABS04BNGjBB95Ap9JApeAFkodipeuB69NZ11H4H67JRKiofXeh1QyR1Y7E5zXBG/j4oBTrtTb+OJPpps9LsN+c6YpYESFNR0MZmPv/f+kEHHURPTw/Lly8HvCnYQggxniSAFFOWbdulZhFS1SZqkfUfRVDSAVsENR5rQI4kHJ7PzFnP09f3TdKpW4CeYbdVSmEUG9KMxAYG4hxNPvcIq1a+h+kz/o1hRMZ41sNzndX0dB6NLk17XTfDR8OcS6Lxi0TjRwMQb/w86AyoSN2VaP5U/XA4XFrfbTCtNen0dfQnf4Hj1NOtWxMK7UQs9gEK9isYqoFo7FDC4YUjho+Os5pU5m76kpdhO0up/F44pDO3YZqzGT58NLCszWhuPJN49P2YZvugx2Tzdudx5AovBnwsFrbzNhtNuxFXZ9A6j6GaSo8jb79FOvdvQBOPLCRkbUx5FeVwQuamGOYc+nN+CFr+eDSOVjhV1nm0tVl1CjZobFeRdCOkiQEKWxsMt8ZjpVrbuBhp721dtCHNHjMupTW69YiPT4hyzc3NHHPMMbz++ussXbqUtra2tX1KQogNjASQYsrypxcopYZ9US8ESKWsCM4PqyWAFCMZ7wrI4RhGlJaW79LS8l1c1yaVuppk30VUC4aGrkA4vLz2araMYsDjuqtIJn9Ac/P543XqQ2RSV6HdbtbO+ozVmdY2aJ1GqRYi0X0Jxw7HsuZXBHhKKVCj+/3hB5DDBdVaa3p7vko6/btRjK4wjAYaGs8OvIfWBbp6LiCZ+j21qwcdHGcZ8dhRpDO3F7cdqLKMRvZmevsVGEb1n5X9mbvJFZ4PfF6gcbX3u9pQMVDeB8uO083y7s+TzNzDQEiqSET2wZuCPVwIaRCxdiJtv4RrVw91tYYC3vTVwVOv7SrTqb2KxyhponjPhS6eeeVU7ZEe58C23v4mBRqMAtmMN3393XNPZlbDfgHHE6JSS0sLO+20EzvttNPaPpV1lzShob+/n//85z8sWrSIRYsW8cQTT/DGG28AMG/evNLXo3Xsscdy4403lv6+ZMkSNtlkkxH3u/7667n66qt59tln6e7uZubMmey999586lOfYvfddw907DVr1vCzn/2MW265hTfeeAOtNZtuuilHHnkkn/70p2lvbx95EDEsCSDFlOUHkNFoNPAaR2JqkgpIEZRcKyII27ZLv4Mmc71Qw7BobDwd05xBT/eZQ+6v9zehDVjF6dgAqf5fYRdeprHpS4TDQRqD1CebvpG1FT7qYnWof3SFIh7/KE0t3x+X1xCumySXfQTbfhnTmksksgemOasUQA63/mMu99Aow0dPNFpfE6HO7i+QSv+ZoFO8bfs15s56mv70jRTs1zBUI4n4YUTCO1bdo2C/TU//r+npv6au8wJNODS/4hZXZ3lj9bHkCi8NOl9NKvcwltGO7a5i8FR+rQ1sTAqF/1SM52iKU6qVt4fWFDDLpl8PjO8HhY4DnW6CjI4ACkNpDDTeJVPPdePtF1IObnE/bxyXMAW2a/80fbYC3qS1RabNCiEm1mGHHcYDDzwwIWPfcccdFeFjENlslmOOOYbbb7+94valS5eydOlSrrvuOi688ELOP7/2h6RPPPEERxxxBO+8807F7c8++yzPPvssV1xxBbfeeiu77LJLXecnBkgAKaYs/82fVLWJkfgVkDJVX4xEpmCLIPzrxDTNtVKBH4t9gGRycxz7tYrb65mG7RscQuZy95FbfR+h0F60t1+JYY5PwKrdDK67ckxjGObGxOIfJ5W8BK9jeLBH6haDJypW89Ok0n/AcftobfslSo28PrDWBbKZ+8jnHwcU0dj7saxt6Ou7gEz6z0POJxI5hJ6eYwAIhR7nneXfAkyU0VhcU9JEqTj11a76TJTRTCz+4cB75AuvkErfUMcxNLbzDqbZTnPj0MB76Pivsmz1EbhuH/U0h/EYNMU/MnBkXWBl90XkCv8bZnsH211FS+J4UtnHKDhvFPczcIhQ3sDHax5joAdVLeYxi5WPg4NEhevCKqeBlI5RHnA62vs6jI1R3M3ErRJiDqYwlYNSYJYCTk2UPNu3fYYtWz/BXb0/AYI1KxJT1xtvvMG///1v5s2bF7giTAziLfI6+cdch+iyx9/a2souu+zCY489Vnp9M1r9/f2cfbZXlT99+nRWrVoVaL9TTz21FD7ut99+fOYzn2H27NksXryY7373u7z22mt84xvfYNasWZx22mlVx3j77bc57LDDWLlyJZZl8dnPfpZDDz0UgNtvv51LL72U5cuXc+ihh/LUU08xZ86cMT3WqUoCSDFlSagkgpKqNhGUBJAiiPLp12ujAl+pEB0df6FrzSkUCk9X3GdSf5RVuSakp1B4hFUrtqOx6TziDZ8JFNBVjFl4mUzqGgq5hwEFKjKKM4No7ASiieNQqgnT2gKlFKHoXvT3nI9dWFS2ZQTIDdnf1QrHa71Tdfxs9laSyS1oavpczfPIZO6gp/v/0HrgzVkq9RtqhYe53J2sXNkPbE089iZae9eNdnpK2/i31cswWmhv/xOGMfIapFrb9Kf/THfv9+s8isI0gzdBWdH16VGEj94VO731B1jFDtoFZyVLVx1H3n55xPPLFV5ki1mPkCu8hKv76U7fQWfyKvzvidaQK5tOrXVxyQEUbpVp1nnXpNeNktMhcjpUcayK7bRFBNsLFJWLM+w6kN5tJg6m8t/we1WP0yJbst20r9Ee3QHXdUvVsi0tLSM8bjGVrVixghdffBHDMCSAFKN2wgkn8MlPfpKFCxeyxRZbALDJJpuMOYD8+te/zptvvsn+++/PRhttxO9+N3KF/4MPPsh1110HeJWZf/3rX0uNmHbddVcOP/xwdt55Z958802++MUv8uEPf7jqz8mvfe1rrFzpfdB53XXXccwxx5Tu23vvvdlll1049thjWblyJeeffz5XXXXVmB7rVCUBpJiy/ApICSDFSKRaVgShtZawWgQyWes/1mKa0+mYdjv53JP09V1YCiKVUlhaB2jPUcktq4Is3UaBVN8l2IVXaGr9ZeCwNZv+M8mez+GFMfVWwoFfcRZv/CqJxk8NuTcU2o7WaX/Fsd/Acd7CMFoxjHn0932NXOZmwEWXnoORy076k5ei3SSh8LuJxQ4BDHLZ+ynYr2IYzSga6Ok5a5i9a4eqqZT3eyeRGNubOu85MYlE9iYaO4RY7KhAXcu1LrBqzSfIZO8d1VEbE8cH2i6Xf55c4Zm6x4+FF9La9GkS0X0A7+fwss5PkB9U3TuY1uCi6c+/xKsrjyZsbUQishurk3+moL0p9mZxPUetFQWM0jqPlWswqtJ4nXaCHCHA74pdvm057/p0MLBwMRSEcchrP9DUFfta2FiGV/Fo4bLvrF/QHt8Js6yzdzKZRGuNYRjyAZioqaenB5CgekxkDUg++clPjvuYTz75JL/4xS+IRCJcdtllfPe73w203w9+8APAm1Vy2WWXDekC39HRwcUXX8zxxx9Pd3c3V155JZ/7XOWHhitXruTaa68F4OCDD64IH33HHHMMBx98MPfccw+///3v+d73vseMGTNG81CnNAkgxZSVzWYBCSDFyKQJjQgim83iul6YIAGkqGVdqZRVShGJ7sq06B3k88+SSl1NPrcIQ+dxnLfqmvFlAyGth4SMGshnb2XNivtpaP4u0fhRQ/bVOk8uezd2/glct5tc5hZGN98sjmltSii8E7HEx7BC29Tc2rQ2wbQ2Kf29qfWnOE1fJZe5n96+b4AOGvppUqkrIeXQ05MovlFMj+L8h0qnvZ8l8URqTONEIu+lueU7WNZmde3X1385mex9oziiiWVtQkP8uKr3au1Nz9Y6jWXOrrPhjCJsbcucaddiDaqwzOSfIJt/pube3pT6YuMXnSWVe5K+3FOsSN1WGh8MnGKX6wIWtaZHp5wwq53GUjdsrxHNyBytsIrDGkoTwfYqK4tVlgPrRXoVuA0o9troCtqiOwwZq7e3F/CaFcm65qIWCSDFusi2bU4//XQcx+HrX/868+fPH3knvNdT993n/Y468MAD2Wijjapud/TRR9PU1ERfXx8333zzkADyb3/7G47jfeB5yimnDHu8k08+mXvuuQfHcfjb3/7G6aefHug8xQAJIMWUVd6ERohaJIAUQfjVj5FIBMuSX69ieH4F5NoOIMuFw+8iHP5x6e99fT+nqy9Y9YGvwNCp2H4Qo3UfyZ5zSKeuoaH5fAzVjGFOw3Heom/Nx4rrO1p4FY+jq/SIN36RROPY3gyY5gzyhWcrpkoHU6zU1GMLCgdLpbwAMhEfzbgGEKNj2s2Ew9sH2kNrF9t+A00B09yIvuQV1P/9UMSi+9HR+mMMY+iHMf2Zu1jT9yPyxfUZlYoRDe8acOQIzQ0fo73pSygVJZV9hGzhBQwVpSG6P/2Zf+JdR9VreF3XX8/RC+lMNM5wXatL4eNQOdek142T0SFsbVHRxKbsbGs9ksHPqr++ozfV2v9j0262MbfpEOa3nolV5fmEgQBS1n8UI5EAUqyLLr30Up555hm23HJLvvKVrwTeb9GiReRy3vIp++yzz7DbhcNhdt99d/7+97+zaNEiCoUCodDAMhkPP/xw6eta45Tf98gjj0gAOQryDklMWTIFWwQlAaQIwg8g16VQSayb1pUKyFqams7FcXP09v+orv0KWnv1YspfK8+rdjOLtzmFJ+ntPGLQXn5QU+/E70qR6F5j2h9Aa4d0+k9jHmc8OI5BNuu9RkkEroD0X9rbGEYH7e3XEgrQkVxrTX/qWnqTP8d2lhVvjRO8ktNAqQStTV8kFjuQkDWv6lY9/b9jdc9XgIE1QbXOkMk9EuAYUTaZ+QSW1U4m9wxvrTmbgrO0OJY3HTpsbVkck4qVOw3A1kZxPceBpjDVrjh/pmOhFEpWBolddoQMMVwNtq62TZAKRK+6cehtNiY272o7m/mtZwSuZhypW7oQPgkgx4HrMpo1icd+zA3TkiVLuOiiiwC47LLLiEQigfd94YUXSl8vWLCg5rYLFizg73//O7Zt88orr7DNNgOzJPxxmpubmTlz5rBjzJo1q1RJWX5sEZwEkGLK8qdgSwWkqEVrLQGkCETWfxRB+QHk2lwDMojWls/jkiTZf3ngfTReJaTSutTX11Cq1C27eqAy9rWtDHNjrNDWYxpDa5vO1UdQrRnNWPkdQ5VSaK0rVvkbLmRKFadfm6ZNJDL0nLTWFfWikdC7iYS3QymLSHh3orFDUGpwTWp1Xb0Xkez/DZXhWfBp5LHo/rS1fIeQNbfq/a7O0Nt/LZ29F/q3DN5ixGO0NpxB1n6ezq5fkc49zMAj9/fV5O2Xi+t3FqdYF4PJfHEdxwFDn3NvarY5MD17UFOYrKNI6hj5Yp2vo4dWTQbndbX2H4OBg0WBsIKZiX3ZsvW0uqZSl0/BFmI42Wy2VC0mAaRYV5x55pmk02mOP/54DjjggLr2XbZsWenr4aZf++bOHfj9tGzZsooA0h9npDH8cZ5//vmKY4vgJIAUU5ZUQIog8vl8aV0/CSBFLX6oJAGkGMn6UAHpa2u+kFzuSfKF/9S1n6asfUwxjNTgteiYgDXq4g2fGfMYXWtOHdIVfKzcQSFhtUYCRlmFaDl/+nU8nsJFl3b1n8vB7Xmyhf+Sd5Yxs+NWlGHR0/dTHOcdTLOdRPzDhENbVWyvtSaVuZWevkux7Vf8W+t+jO2tP6cx8eFh77ed1by1+kMU7FcDjOZPn/an4xto7WBaW7Mq+RtI/qx47n6Fo/ecKYrXmNbkMbArplm7VRrIVHI0ZdOti9W7riKpo6R1uLS/Kgsl3VJQOZLyINP72mtp4/0JYRNWikR4E7ZqPZvZiYPq7hovU7BFEH71YyKRqJh+Kuq0FpvQ+NXOvkgkUlfF4Lrm2muv5e9//zvNzc1ceumlde/vL2kDI7+mKn99Prhbdz1L4/jjjLXj91QlAaSYsqQCUgThVz9aliUv1kRNfgWkBNViJOviGpDDUUoxveMq3npnL2D0L7b9CWsFrTGKb6RMvBeihlFf2DL0JNuIxj9U925aa/L5f5FKXUshvxjHeX1s5zGIrXWgSXr+cxMqe0OrlCJdDCBj8VRF2FhrTNftYvmqfYpbGaU9epO/wDQ3pjF+HKHQ5sSiB9DTdyl9/b+s5yENYhKyNqMhfnTNrVasOZOCvSTgmDaz26+jP3MPWftlCm4/+cLr5AsvodAoVd5EZoBGFUNEsxgWDoR+TqkWtzpdFj5qrci7ipSOkCHK4EpIXfp/VbynskqyyuhlE76LvciVjUWeiHLYpvUMtm4/O+BzMzw/lJAKSFGLH0BKUL3+Kq/iA7jgggu48MIL187JjFFXVxef/exnAfjud79bc+rzcPz38+Ct81hLeVDrFyINHmekMcrHGTyGCEYCSDFlSRdsEYRMvxZB+deKVECKWlzXLV0r60MACWCZM5g943beWXXoKJqzDOWW/bcAhFyXkFKjqIz0gqWm1h+jVH0fEGnt0tPzOTLpG/Ci0MH1hGPjBgwfyxXKmqcorUmmvd879XfAdgf91+M4b9KT/EHxb1EgS33858mL1CxzDtM7/liq1ivYy+lN/Z7+zJ1onSUafjfxyH5k8o8NO6Jfyej9BbRSFJxeurOLyNkvl21ZrGbUuix8rLxebFSpIrKeNRnz2iDpmuSJAApXG+QrOl8PHqs4bVq5uDWnYWuvwlE5pb9b2IQMFxNY0HYmW7WeVfPcgpI1IEUQsv7j+m/ZsmUVHzTUqn60bXtciieuvvpqTj755DGPM9hnP/tZVq9eza677sqZZ545qjHKC4ny+XzNbf3lB2Do+/9oNEo6nR5xjPJxJEMYHQkgxZQlFZAiCP/TLQkgxUhkDUgRRDqdLq0HuD5dK+HQVsyZ8RjLVx6Iq1eM69gFvMpIf6q2FyR58aLfMsRQXoft8pAyFN6DROPnCUUW1n3MVP/lxfAR6gsfFS0tv6an50xqTVceXZw50BJFA2k/gIwHX4sxuGypz7LLQI2fXytYPmEYQJGgseE4CoUXUaqBROyDhMLvJpm+nUzuUXKF57Cd1ZQ/J7azgv7MHfih3eCw0VEKW6vSVGnQKA1Luz5VOupgg8NHV3tTob0p6bUrHctpDXlH0akbsLHQGMVp3G5Z85nhDHTQtkvP0uDjeo/UUi5hZWMq71mOqQbmNh3GgrZPYxnj87qiUCiUPtSQCkhRi0zVHydrcQp2U1PTBvHv/J///Ce/+93vME2T3/zmN6OeCVG+lvZIU6L91+kw9APgxsZG0ul0oGnV0nRybCSAFFOS1roULEkAKWrxX9TLp1xiJFItK4IoXyt0zFOPJ5lldTBn1gOsWH0shcKz4zq2ZnD8pnAoX0cSMiha4yfT3HAyptGKYXaM7ljapr//V6Pat7nlB8QTh5HN3UU28zcGVxkObgwzFun0wBqQtZSHiFAZIuqyP1AZLlZ2gFZo/OpCb03KgS7SCq3TpPIvELK2QBlNrOm/llz+MyjlvS92y7b1z8rQdnESuB5yv4PC1eWTkwfOgYpxKs/R396fbj38ttVpDTYG/XaIbhqKK0eW8yPvEUdCKUUYm7y2SreVi6scYcN7li0ivG/u9TSENw18rkH5SzqEQiF5TStqkgByarEsa1w6Nc+aNWsczqbSxRdfDMAuu+zCSy+9xEsvvTRkmyVLBpbuuO2225g2bRoAxx13XOn28qYxb731FrvsssuwxyxvGjN4KvtGG23EypUreeutt0Y8d3+cwWOIYCSAFFNSoVAoVaBIsCRqkQpIEZRUQIog1vdmRabRzIz2K3l75UFo3T1u4w6EYbXX0+tOXY0V2oyWhlNHfax06kZcd3Xd+ynVSDx+LADNzRdSyD+J47xDeb2jg8Idl/gRMsUKyFhZBaQf5JXHdIOP5p/NwMTywasQVoZ+5V/rYkWh//3w4zkH6M89DrnHKvYxdfn5VI7lFoNHNeh+/xhDjz/cI6q8fyB8rG/KvutCUofpc/1O1mNthqQxFESwcYtTt0ETUjYRZaOUF/3OjC5kt9m/xAzYkbxe5R2wJ6LBk9hwyBTsceKWf6wzmces34IFC8b5RMaHP4353//+N8cff/yI23/6058ufV0eQJZ3sn7xxRdrjuHfb1kWW2yxRcV922yzDU899RS9vb2sWLFi2PUo33nnndKSF1tvvfWI5y2GWr8+ehdinPihkmEYWJbk8GJ4UikrgpI1IEUQG8LUHcvaiNkz7sQyNxmX8cparwTafk3vJbi63vULPbb9Or29Xx7Vvq1tV5TWmjTN6XRMu4tEw2ko5X0vXW2MW/gIQysg/YpQXfY86Yogr/zP4Gnggzs2D+3g7GgvCPYDRW9as6oyTtk+pXMYrmJRle73Zy06AULGwfx9dUXl48gcreh3wqy2E7ztNNPnJsYpfFTFid+glMZUDjEjS6OZJWoUUMohgsMe07/De+b8dsLCR5AGNCI4qYAUG5pdd9211DjmwQcfHHa7fD7P448/PmQf31577VX6utY45fftueeeozrnqU4CSDElla//KJ8Wi1pkCrYIoryxiFTLilr8Csj1OYAECFmbMGfmw0Qj+495rMqpuwG2132ksw8F2lZrTS63iL7e79Dbcz7dXWfjrTpZjyht7dcRje5dcatpttPQcA6xhrPR5ubY4zyxKF1WAekweLJ3eeg3XPhX677KANAtVSUODTJHPkatMFHjao2tFTYKG6NKteTwXO01iclhlv4Mfz4DCq7inUITb9gdrHRb6NNe8JgP/D2q/ZhAE8YmqgqlP5bynsHW0Ax2aDuLgzd5glmNhwY83uhJACmCyOfzpdcpEkCOjdbuWvmzIXnggQfQWtf88/GPf7y0/ZIlS0q3l2tsbGT//b3XIffee++wU6hvvvnm0s/Ko446asj9hx9+eGlZnKuvvnrY877mmmsAr4jp8MMPD/6ARYmUfokpyS/7lqo2MRI/rJZQSdTiXycg14qobX2fgl1OKYsZHb8nnbmd1V1njHqc0dQMum7PiNs4zhq6uk6hkH8S7yWvV9MXhFINRKOHEI7sQix2FIYx9PtVKLzKO6uPwnW7GBwPjlUhH8IueBUaoXiqbMryeFGlpjADU6irNVNhmNuC3e9oVRZslm8/3LEGeKGlXytRHnZW3892oE9HSOsoBSzcIU1pgh13wOBtB/4eplCcYu3f7rBLxzfYuPnYgGOPHwkgRRD+dRIOh+X9j9igfP7zn+euu+7Ctm0+9alPcfPNN2OaA5XynZ2dfOlLXwK85QdOO+20IWPMnDmTE088kT/84Q/cc8893HTTTXz4wx+u2ObGG2/knnvuAeCkk04adpq2qE0CSDElSQdsEZRMwRZB+NNqo9HoetdYREyuDW2qvlIGifjhpJJXYduL0FrXXV84mgAyZG1ce0zt0rXmRAqF54u32DW3r2TSMe12QqH5NcdfuebjYwgfa09DTme8DzKsUJ5QyGZ0U4aH30dr/xmpN5Sr7xjDB6e1j+cUm8VUWyPS1ZBxLXJYONooBZx2cV1Ib53M4aZpB32cqriKZeX2Bg5hCpjKxVDeUVtDW7DttG/SEt0x4Njjy29CIwGkqKV8+rXM/hJj9eqrr/LII49U3OZ/wNrf31+qFPS9//3vn7DA7n3vex/HHXcc119/PX/729848MADOe+885g9ezaLFy/mO9/5Dm+++SYA3//+92ltba06zne+8x3uvvtuVq9ezfHHH8+TTz7JoYd6Vey33347P/rRjwCYNm0a3/72tyfksUwFEkCKKckPICORyFo+E7Gu8wNImYItapHp1yKoDWUK9mBt7b9h1codUUoR0hqbYMFiPdNxPQaWuRHR8G41t8pmHxhlp25FLH50zfARoKfvEmz79fpHV83MmfFPkqk/kss/icIiX3gRx11esV1p+nUszdjXK6w0ED6WzmrcxvWqKYvNZkY5vlu2zqPWkHYtMoSLFY3+dHGjbO3JyivNKfXwHu3j8sYLY5fWwjTQXk2lAWAwI7I30+I7MavxUKLW2q2CkQpIEYSs/ziOtB51U5gxHXMd8sgjj3DKKadUvW/NmjVD7rv//vsntGLwqquuoq+vjzvvvJP777+f+++/v+J+wzA4//zzOeOM4WdrzJ07l9tuu40jjzySFStWcPHFF5e6dftmzpzJLbfcUtF9W9RHAkgxJckUbBGUBJAiCAkgRVAbard0y5pBW/vddK15vxdCgrf23wj7ebWDQcMib8Lw9JaLh63gyeefoj95Gdns3XWcfeUxGho+WXOLZOp6epM/GdXobS3fwrJm09r8hdJt+cKLLF95CC5ZdDH86q/SAXu8DExCH69gUw+aal3ecTsYV4PjB4zF/VJOmBSRinEGjlOu8u/DN8UJwjv3EAWUcjHRXh2m8q7RBS3nsGVb7etjsvkBZGNj41o+E7EukwBSbMhisRh33HEH1113Hddccw3//e9/6enpYcaMGey9996cc8457LHHHiOOs9tuu7F48WJ++tOfcsstt/DGG28AsOmmm3LEEUdw3nnn0d7ePsGPZsMmAaSYkqQCUgTlXysSQIpaJIAUQW2oASRANPoups94ldWr9kbrdzCUYrjev1prXMqnAQdjounuOgOr4xoikd0r7kun/0pP97mMNL25lkTiFEKhbYe933XTdPV8fVRjR8K70xD/8JDbTXMWRmhrCoWnS7dlM971EY2NTwDpr/c48MyMX1Xl0FAw+Ni6ONXaCx8Hvmc9TrTYrXqAq1WpCrIWhS4GuSOdR7VtNGEKhJWLn3FHVQvzW85g45YT1rmpq47jlH6mSAWkqMUPqiWAHAfar42e7GOuO04++WROPvnkCT3GNddcM2Qq90hOOOEETjjhhDEdt6Ojg29961t861vfGtM4ojoJIMWU5FdASgApatFaSwWkCEQCSBGE1nqDDiABLCvOrNlPYdvLWbVyl2G3U0p5K/bpesIir3ovq3t5Z/XRtDV9g0TiIxhGDNdN0tN9HmNpBmMYHTQ1137DkUrfhNapusdOxI6ivfWHQwIsrTVvr/4oucIzxVu8+zPjUgGpipWFgysSR/NG1vse+es6Du3IPTo2CgcDRysyOoxGoV3IEaL8qdIanIDrVZq4NdaABNAYxUfgFoNPE5cQNiHDCxYs1cjCmZfRHtth1I9tMvjrP5qmKb9/RE1+BaQE1UKItUkCSDElyRRsEUQ+n0cXP3GUa0XU4geQElSLWjKZTOlnyoYaQPosazbTpi9m9arta2+HIh8oEBuo3dNAAVjZ903o+2YxajIJ4WCOoUCtqfkClKqssNPaIZ25i2TqWgqF13DcdwKPF4seQCz6PuLRA7CsuUPu11qzsvvz5ApPDbkvkwkaQMaIRXYjk3sUL571z9/GNLag4LxKtUYu9TNwtS6GgKMdo5KrwdYWPW6UtC6vdvS+16b2Gr1U3h7kTL2AcWj3bRiYYu2glC5uq0thZ8ycyR4zf0ciMmt0D2qS+QFkY2PjOledKdYtMgVbCLEukABSTElSASmC8Kdfm6ZJKBRay2cj1mV+paxUoIha/KA6Go1imrUqtDYMoVA7zS3X0Ntz8rDbWEC+js7E1TjF/3egVNwXLo5dO5Px77Roav4G8fiHKu7VOs+qNZ8gk70PL9gLXl0Zi76f6e1XoNTw3+fe1DUk03+qel827X2YUWsK9sy2q2iIHYRSBrazhr7U9aRzT6BUmIbYQbzd9X+Bz7eWRGQvprdcxCsrDgVyVbfxezIUMCloo1RZqAADby1Fb21QG9MA14V+3UanO/yajQ4GFEPIemo2lYKQtilgFs9jYGwDt9jFunhUBYowC9o+w+bNH13vQrzyAFKI4WitZQr2eHJdUKOvth8VPcnHE2KCSAAppiQJIEUQfqgk1Y9iJDJVXwThT7+eSkF1InEQlvUgazqPBtYMuV8pUHr8V9PK41VJRjWDqugGRKOHEonsTix+JIbROuT+nr5LyGT/Wfxb8Dd/lrkZ09uvqhpm2c4qkulbsZ0V9KZ+P+wY2azfBTtT9f6wtR2N8fcDXrjQm76JzuRvcFzvOe7N3MlYntVZrZdgqDjR8LuIhDZj2ZqvoKuEj7YDfUSxvQn1Q+7XxeYyDgqti/cXu8dqrf0WL1XOwKuCdDEwSitMBu9srRSEcdDaxsVAoQkpF0MNrN1mEGPhjMuYlhh+qYB1nQSQIohMJoNteyvuyrUihFibJIAUU5IEkCIIvwJSAkgxElkDUgSxoa//OJxIZEtmz1nsTWdO30my7we47uv4QZCFFxaONw1kAEt7FZFeHuhVMjY1fYOGxjOH3ddx++lLXkH9IZ6ivfX7Vdd6XNP3A7qTv2AgSHOqDQCMVAFpMK3lwtLfVvZcSFf/FYO2GW34qGiKHUU8sgerk1ewrPsCHDfF4MpH14VuHcUZJngEr2lMvnT/4PCwWjfroeei8ULMgaC6VgipK/alOLU6jF0Mob0u6hvHD2GbaecTMtf/tfAkgBRB+NOvE4kEliVv/8dMmtAIMWryE0hMSRJAiiCkA7YISiogRRB+UD3VAkifUiaJxGEkEocBkM8/S6r/Stz0XyiMoXnMSGy8qC+mLeKJY0gkPk44/K5ht+9P30JXz/losnUfKxE7mlh07yG3dyd/Tnfyp4HGcF1FNlsMION+BaQJOJhGO9Nbf0Q8+h4AcoWXq4SPo+EFdrHwjjQljualFQehdYFqIanW0KnjUKMjtaspho/l41f7OjgTF7vULbt8jIG/W2Xn64XAAw14tmk5hU1bPoVhbDiv/SSAFEH406+lAY0QYm2TAFJMSRJAiiBkCrYISiogRRBTcQp2LeHwuwi3/ZSm5q/zzppTyOT/M2HH0oAObUNr649qbpdM3cCa7vNGfZzmpnMrj6sL9KVvYU3fDwOPkcvGAIVSLvFYG+3NZwJ5QtYmJKIHAJqe1I10919HNv98Xefnd5N2tNd92jJmYBmKBmserQ3H0xA7gBeWvwetcwxX4dPtRhgpRLRL4eNY11QcOAelwNKuN527NLZfRVsgqpzSmp9+sdCMxKFsN+3bmBtQ6FhOAkgRhKz/OL6066IneQ1ILWtAig2EBJBiSvIDyHA4PMKWYiqTKdgiCK21VMuKQCSors40pzFn2q0sWb4Hjn6Letb6q0em8ByOk8Q0q4c1rs7Q1XP+KEc3iUXfRzi0VemWXOFFlneeiO0E75wNkM14P0ci0RybzroPs2yqsOumWLr6BDL5J6mnMY6roc8NU/Ba8wzc4fSAA2sKSVbmf0ncugHb7sGoUtzoaki5FvbgMQbRmmE6UFcy0MXthvt+a1RZh2oohpDoYjd5r4N1SDlD1vncrPlctmg/u+bxNwR+ANnQ0LCWz0Ssy/wAUoJqIcTaJgGkmJLy+TwgFZCiNqmUFUHkcrnim2EJIEVtU30Kdi1KmUTMmaTtZVRfM3A8uLz+zrZMb/0ZBectsoUXMFSMhujBWCpMT9/30TpZ55je1OhoZA+mtf2ydKvj9vD26mNw3J66zzJTDCAbEo0V4SPAip4LyipFRw4ftYbeasHjEDZZ502yzptAFNN1COGAUmgNGR0attFMdSNvpxSYWnvdrqtOqwZzSBWmFzyayiFEeZdzRWtkd7Zuv4hEZG7Ac1z/SQWkCEKmYAsh1hUSQIopx3XdUic4qYAUtUgFpAjCn6ofCoVkcXdRk1RA1lawnyME2Gj0BFRAepV5Nm93fari9p7Un/Cr7fzjKjQmXrxoDnsqBg2JE2iIf4hIeCFKKVydJZm6kTV9Py51pK6XXwEZjYd5YcVJpAqLcd0MigIhCoSUS5UG20OkHYMUUUYT5DqYOJhoFwqlTtX1jBMsQDaUBu0UQ8iBfb3n369+9Cdcu4RwK6odp8X2Z6uObxCzptdxbhuGQqFQ+qBUAkhRix9USwA5TqQJjRCjJu+UxJTjv1gDqWwTtUkFpAhCGtCIoGQNyJF4vbAtykPI8iBr9FWRWnvNaIavrlRloadGY2AXzwMNUfSgab6KxoZTaG/5dukWx03y1qoPk80vxsGL0RRgqsH71taf9ipkXWsxfblHBh4DkMMipzWmdongYA7TBybjmKQY7e+ugZMdmEod/AF4lY1uMVSs1bHau89QoLQLxe+5hUNIeWs9gjdVe+D5M2gO78D20y8hFppd38PawPT39wNgWZa8ThE1SQWkEGJdIQGkmHL86demaWKa5ghbi6lMKiBFENKsSAQlFZC1GaodV68EvBeoLrrY07isEQm6FF0NXw9SGXoNhI/V76+9v3ekLIqoHgjCopG9aG3+Go7TRV/6BvozD9Ob+zeOzgGVry0KWoPWXog5fONoQJF0FP0ZL4AMxzLDbudgksYg5DpEDRet/cnJ3uPtZ+RGMUE4dVc+eizcGlOr/WDR8Vd5RCnve2thlypOrbLvcNzagi3bPs+0+HuL3a1F+fRreU7EcLTWsgbkeHM1KKmAFGI0JIAUU440oBFB+deKBEuiFqmAFEForSWAHEFz0zl09w40gTGKf/y3XSNFLC4UA0uP1/GZskrK0RoIISNa0958EbHo3qQy97Gy+zxsJ0Ou5tl5IV4WjeFqIkpXdGv2av8Mkm4IDeSz3u+ccDQ77IjefgYuirzjElEOhvLOM6frWatxYigFEW1TwCyuVDlwPt5U6qGNYyr2J0Jz5F1s1vIp2uO7TfTprpekAY0IIpfLUSh41eVSASmEWNskgBRTjl8BKQGkGIlfASlTm0QtEkCKIPL5PI7jxWMSQFbX1HAq3b3fBnIVtweN0vyw0i1W2TlU1k6Ojbd/DsWKnm/ioIvBoR9wBhlf4aLIapeQ9kJIl2LFoh6omswX14AsDyC9MNXArjjWwJRxR3tNY8K4FFg3ZncoBWEctPaqG12KUawaXBEJoGgN78q2078/5adWB+VPwZYAUtTiVz9Go1FCodBaPhshxFQnAaSYciSAFEFJBaQIQqbqiyD8oNo0TXkTOAylFHNmPsbbK3Ya9RgmA6HeeDey8aZyDw4b6z+GxiCvHVxM8npogxe/AjJSnILtashXvGQfekwbC7QCZWNTc553XczSNPjRPpfetHULr3GOO2gtziZjG7ab9QPioc1QSt6W1EMCSBGENKCZANr7qGvyjynE+k9+04spx5+GIAGkGIk0oRFBSAApgiiffi3rtQ0vZM2irfXHdHX/36jHsIBc4InbwVWvPqyf1poc4bLyzMqxcmVTsLWGQunl+nDHVMXzM9Dan7he1xkNO7aBLq4DWU8DoMo1Oy0GppwbCsJAyOhg645LaI2/p85zFT4/gJR1/UQtsv6jEGJdIgGkmHKkAlIEJQGkCEKa0IggZKp+cE2J49BuL929F9a9r78OZPBp0cE4mnEbL18jUNS6cg1It6I798iccX5prxSEtEuhZqg5uFO5918TXWoo4zHpiB/E5q1fIxqaPq7nORVJBaQIorxZkRgf2tXoSW5Co6UCUmwgJIAUU44EkCIIx3GwbW+imASQoha/AlKCJVGLNKCpT3PjGTTEj+XtFfuVOmOPxIFSw5Oxtp0ZzB2n8NEdYWq4XQihXW8NRz+ArK/6sF5+7+zhx/fWcnRxiufulvYb2Mco9rM2itsDhIwZNIQXMC1+INMbDsc05EOa8SQBpAhCAkghxLpEAkgx5UgAKYLwqx9BrhVRm0zBFkH4FZASQAZnmq1sPOcZ+lN/p7P7NKAwdBtjExLxQ7HMjVnZ+2X82HE84zp3HKsfRwoU/epH0ypgWg6uHr/1HKvzz2fkkNOrZiyPdYdGvAlrK7bq+AGN0a3H7xRFVRJAiiAkgBRCrEskgBRTjh9AShMAUYsfQFqWhWmuGx1FxbpJAkgRhF8BKddJ/RoSB5GILyWXf4JU5i5cp4tQaEsa4sdgWTMA6EvdQXkgZihwdL2Vg4MDtclfq7N8+jWUr8EYjML16xAD72MUA0h3VN2zw7REF7JV+3eIhmaNYn8xGlprUqkUAIlEYi2fjViXSQA5AbTL5DehmeTjCTFBJIAUU47fhEYCSFGLrP8ogpIAUgQhFZBjo5QiGllINLKw6v1rkhePYXQveCx10PaOOOje0Yw5NAQ0Rqg0rBZAKnSAuk6NgYuFS77OJjQmLqYCW+tiB21//Uz/kRuEzRm0RvekLbY3zdFdCJvtKCUfzq0t6XS6tCacBJCiFgkghRDrEgkgxZQjXbBFEDJVXwQlAaQIQtYKnVja7R9yW0hBIWAVpIm3hqSncvvR1UEO01VagdLusE1yCoMCSK8JjF1sXFOts7cfnnrho1JgaQcbM9CZq2L4CGApjeU/CzrC7OazmN74ISLWRiOOIyaXX/0Yi8VkloYYltZauqVPAGlCI8ToSQApphyZgi2CkApIEYTWunStSAApapEu2BMrHJpPJrdiyO0DISQMGwqOMLa3V+0x6hHGJTfMdGe/AjIUGViH2FAQ0TYOBg5GsR5SYxT/mOhS4xfwgkSl7WLn6uGmY3tjhMtiV49iWuLDzG4+h2ho4zE8SjGR/FBJqh9FLalUSiplhRDrFAkgxZTjdzaWAFLUIhWQIgjbtnFdb10eCSBFLRJATqyZrb9iyYptq94XUuBocKtMpjbxAr5CjUYzqjQbeXzWhPSqFN1ilWKlfM770MuvgBzYR2MVqxyDMJVXFelql0IxqhygCeGUKh8BwuYsNmr5Mh2Jw1BqfB6nmDh+BaQ0oBG1lAfVUik7jmQNSCFGTQJIMeXIGpAiCKmAFEH402qVUvIzRdQkAeTEsqxWwqF3kS88W/V+L5Bbd5ho7CrrQQ5eA9LnrQOpGbles5KhIEL5m+UwYXM2DZEdaYsdREvsAExT3g6sb6QCUgQh6z8KIdY18opjA+GX1/f19a3lM1n3NTQ0MGvWLEzTlOdLDEspxezZs2lubpbrRAwrmUyy0UYbobUuvdAXopr29nZM00RrLT9TJkhr7M8s6XkfrvtWfTuqOAW3ANjDbmJrBlUR1hJs3cmC1riDpkgb4dXEWyyU2UUqOdASJ4SDoSCngZrrO4YxaMAwQsRDW9EcfS/tiUMwjBiGMehlvwupVDrgYxLrEsMwmD17Nk1NTfLzRAwrn88zZ84cWltbJ/Q68ceeKusU2hRG251sbMcUYgOg9FT5SbGBe+utt5g7d+7aPg0hhBBCCCGEEFPMsmXL2GijDbdpVTabZdNNN2XFiqHrDU+GmTNnsmTJElnyR6zXJIDcQLiuy/Lly2lsbJS1eyZJX18fc+fOZdmyZTQ1Na3t0xHrOLleRD3kehH1kOtF1EOuF1EvuWZELf4skNmzZ2MY9S0Tsb7JZrOldeInWzgclvBRrPdkCvYGwjCMDfoTp3VZU1OTvBgTgcn1Iuoh14uoh1wvoh5yvYh6yTUjhtPc3Ly2T2FSRKNRCQGFGIMN+yMKIYQQQgghhBBCCCHEWiUBpBBCCCGEEEIIIYQQYsJIACnEKEUiES644AIikcjaPhWxHpDrRdRDrhdRD7leRD3kehH1kmtGCCHEeJAmNEIIIYQQQgghhBBCiAkjFZBCCCGEEEIIIYQQQogJIwGkEEIIIYQQQgghhBBiwkgAKYQQQgghhBBCCCGEmDASQAohhBBCCCGEEEIIISaMtbZPQIi17T//+Q933303Dz/8MM899xyrVq0iFAoxe/Zs3vOe93Dqqaey9957BxpryZIl/OxnP+Mf//gHS5cuxXVd5syZw4EHHsjZZ5/NtttuO8GPRkykvr4+7rzzTp544gmefPJJ3n77bVavXk0mk6GlpYVtttmGQw45hFNPPZX29vYRx7v77ru5/PLLWbRoEatXr2batGksXLiQT37yk7z//e+fhEckJtp4XDOu6/Liiy+yaNEiFi1axBNPPMGzzz5LPp8H4P7772ffffedxEclJsp4XC/ZbJZ77rmHe++9l0WLFvHKK6+QTCZpbGxkq6224uCDD+aMM85g1qxZk/zoxHgbj+vlhRde4L777uOJJ55g8eLFrFq1is7OTkzTZMaMGey6666ccMIJHH744SilJvkRivE03q9hyqXTabbbbjuWLFkCwLx583jjjTcm4FEIIYRYr2khprD3vve9Ghjxz0knnaRzuVzNsX7zm9/ocDg87BjhcFhfdtllk/TIxET4xz/+Eeh66ejo0Hffffew47iuqz/5yU/WHOOTn/ykdl13Eh+dmAjjcc1cc801Nfe9//77J/dBiQkz1uvlv//9r25sbBxx/8bGRn3DDTeshUcoxtN4/Hw58cQTA42xzz776DVr1kzyIxTjabxew1Tzuc99rmKMefPmTcyDEEIIsV6TCkgxpb399tsAzJ49m2OOOYa9996bjTfeGMdxeOyxx/jRj37E22+/zR/+8Ads2+a6666rOs7111/PGWecAUBzczOf+9zneN/73kckEuHpp5/mBz/4Aa+++iqf+tSnmDZtGh/+8Icn7TGK8TV37lz2228/dt55Z+bOncusWbNwXZe33nqLm266iZtvvpnOzk4OP/xwnnjiCd71rncNGePrX/86l19+OQA77rgjX/ziF9l888157bXX+MEPfsDTTz/N5ZdfzrRp0/j2t7892Q9RjLOxXjNa69LXoVCI7bbbDtu2Wbx48WQ/FDEJxnK99PX1kUwmAdhzzz059NBD2WWXXWhvb2f16tXcfPPNXHHFFSSTSU444QQaGxv5wAc+sLYeqhgHY/35YlkWu+22G3vuuSfbb789M2fOZNq0aXR3d/Piiy/ym9/8hueee44HH3yQww47jIcffhjDkBWc1lfj8RpmsKeffpqf/OQnRKNRQqFQ6WeQEEIIMcTaTkCFWJs++MEP6htuuEHbtl31/tWrV+v58+eXPtF96KGHhmyTSqX09OnTNaAbGhr04sWLh2zT29urt99+ew3omTNn6v7+/nF/LGLiDXedlPvrX/9aul6OPvroIfe/8sor2rIsDehddtlFp9PpivtTqZTeZZddNKAty9KvvvrquJ2/mHzjcc38+9//1j/96U/1Y489pjOZjNZa6wsuuEAqIDdAY71eHn30UX3sscfq559/ftj9b7nlFq2U0oDefPPNpdJ6PTYeP18KhcKIxzj66KNLY/ztb38b9fmKtWs8rpdqY+68884a0N/85jf1vHnzpAJSCCHEsOQjTDGl3X777Rx77LGYpln1/o6ODn70ox+V/n7TTTcN2eauu+5i1apVAHzmM59hu+22G7JNU1MTl156KQArVqzgmmuuGYezF5NtuOuk3JFHHsmCBQsAeOihh4bc/+Mf/xjbtgH4+c9/TiwWq7g/Ho/z85//HADbtvnJT34yxrMWa9N4XDMLFy7k05/+NLvvvjvRaHTcz1GsO8Z6vbznPe/hhhtuYJttthl2/yOOOIKjjz4agNdee41nnnlm9Ccs1qrx+PliWbUnQ5mmyRe/+MXS36uNIdYP43G9DPbTn/6Up556iq222oovfelLYz5HIYQQGzYJIIUYQXlzh9dee23I/U888UTp61pT2fbdd99SeFAtyBQbjkQiAXjNIMpprbn11lsBWLBgAbvvvnvV/XfffXe22morAG655ZaKKbhiwzTcNSNENWO9Xvbbb7/S19V+r4kNy1ivF3//sYwh1h9Br5elS5fyjW98A4Bf/epXhMPhCT83IYQQ6zcJIIUYgd9pFqi67lFXV1fp6xkzZgw7jmVZtLW1AfCvf/2rVAUnNiwvvPBCqaLIryLwLVmypLTu6D777FNzHP/+t956SzpJbuBqXTNCDDYe10sulyt9Lev5bdjG43r505/+VPpafkZt2Oq5Xs4++2xSqRQnnXRSxYcaQgghxHDkVacQI3jwwQdLX1d7MVZeGdDb2zvsOFpr+vr6AC/UfPXVV8fxLMXalE6neeWVV7j00kvZb7/9cBwH8Kbkl3vhhRdKX4/0wr78/vL9xIYh6DUjBIz/9TLS7zWxfhuP66Wzs5PHHnuMU089le9973sAtLe3c+KJJ07IOYu1ZzTXy/XXX8+dd95Ja2srP/zhDyfrVIUQQqznpAu2EDW4rsv3v//90t+PPfbYIdtsvfXWpa8ffPBBdt5556pjPf300/T395f+/uabb8obv/XYNddcwymnnDLs/Z///OeHvFFbtmxZ6euNNtqo5vhz586tup9Yf43mmhFT10RdL//973+54447ANh2221rrhcp1h/jcb3su+++FeF0uba2Nm6++WZaWlrGcppiHTGW66W7u5vzzjsPgO9///tMnz59Ik5RCCHEBkgqIIWo4cc//jGLFi0C4KijjmKXXXYZss0hhxxCKBQC4NJLL6Wzs3PINq7r8rWvfa3itmQyOQFnLNa2HXbYgccff5xLLrkEpVTFfeXf84aGhprjlFfWlgfXYsNT65oRYrCxXC+5XI7TTjutVOH03e9+dyJOUaxDxuPny7nnnssLL7zAe9/73nE+O7GuCXK9fOELX2DlypXssccenH766ZN8hkIIIdZnEkAKMYwHH3yQL3/5ywBMnz6dX/3qV1W322ijjTjrrLMAePvtt9lzzz259dZb6evrI5vN8vjjj3PIIYdw9913VyzQnclkJv5BiAlz5JFHsnjxYhYvXsyiRYv405/+xFFHHcUzzzzDiSeeyO233z5kn/IF3UdarD0SiZS+lmtlwzCaa0ZMXRNxvZxzzjk8+eSTAHz84x/n8MMPH+/TFmvJeFwvV199NYsXL+bZZ5/loYce4tJLL2XLLbfkl7/8JaeeeiorV66chEciJsNor5eHHnqIq666Csuy+PWvfy0fmgkhhKiPFkIM8dxzz+nW1lYN6Egkoh944IGa2+dyOX3YYYdpYNg/m222mf785z9f+vstt9wySY9GTKbf//73WimlDcPQV199dcV9P/jBD0rf/7vuuqvmOHfeeWdp2x/+8IcTeMZibat1zQznggsuKF0f999//4Sen1i3jOZ60Vrr7373u6VrZuedd9b9/f0Td5JinTHa68WXyWT0oYceqgE9d+5cvWzZsvE/SbHOqHW9ZLNZvdVWW2lAf+5zn6u6/7x58zSg582bN/EnK4QQYr0jFZBCDLJkyRIOOugguru7MU2TP/3pTyN2LA6Hw9x6661cffXV7LzzzhVdRVtaWjj33HP5z3/+g9a6dHtra+uEPQax9px00kkcc8wxuK7LOeecQ3d3d+m+xsbG0tcjTatOpVKlr0eari3Wb7WuGSEGG8318pvf/IavfvWrAGy11VbcddddFcs8iA3XWH++RKNRrr76auLxOMuWLeOLX/ziBJ2pWBfUul6+853v8NJLLzF37lwuvPDCtXeSQggh1lsSQApRZvny5RxwwAEsX74cpRRXXXUVRx11VKB9lVKcfPLJPPnkk/T29vLqq6/y5ptv0tnZyc9+9jOam5t59tlnS9vLwv8briOOOALwQsS77rqrdHt545m33nqr5hjljWfKG9KIDdNw14wQ1dRzvfzpT3/i7LPPBmDevHnce++9TJs2bcLPUaw7xvrzpaOjgz333BOAW2+9Fdu2x/X8xLpluOvl4osvBuCAAw7g9ttv5/rrrx/yx//wNJVKlW775z//OfkPQgghxDpJumALUdTZ2cmBBx7I66+/DsDPf/5zPvaxj41qrIaGhiFVa/l8vtTQZrPNNqOjo2NsJyzWWeVv7pcuXVr6ujx0fvHFF2uOUX5/ead1sWEa7poRopqg18vf/vY3Pvaxj+G6LrNmzeK+++6r+CBETA3j8fPFHyOdTrN69WpmzZo1Lucm1j3DXS/5fB7w1gq9+uqra47R2dnJ8ccfD8A+++zD+973vgk4UyGEEOsbqYAUAujt7eXggw/mf//7HwDf//73+dSnPjWux7jzzjvp7e0F4Nhjjx3XscW65e233y59XR5Eb7rppsyePRvwmhzV8tBDDwEwZ84cNtlkk/E/SbFOGe6aEaKaINfLfffdx7HHHott27S3t/OPf/yDzTfffLJOUaxDxuPni/yMmjrkey2EEGKiSAApprx0Os0HP/hB/vOf/wDwta99jS996UvjegzbtrngggsACIVCnH766eM6vli33HjjjaWvt99++9LXSqnS1KYXX3yRxx9/vOr+jz/+eKkC8ogjjpAuk1PAcNeMENWMdL3861//4ogjjiCXy9HU1MQ999zDtttuO5mnKNYhY/358vbbb/PYY48B3jT+8vWMxYZnuOtFaz3in3nz5gHedeLf9sADD0z2QxBCCLGOkgBSTGn5fJ6jjjqKRx99FIDPfOYzfPvb3657nM7OTtLp9LDH+MQnPlFa//FLX/oSm2222ehPWqw111xzDdlstuY2P/7xj7nzzjsB2GSTTdhrr70q7j/vvPOwLG/1i3PPPZdMJlNxfyaT4dxzzwXAsizOO++8cTp7sTaMxzUjpo7xuF6eeeYZPvjBD5JKpUgkEtx5553svPPOE3bOYu0Z6/Xy8ssvj7g+X29vL8cff3xp+u1JJ500xrMWa4v8PhJCCLG2KV3elleIKeZDH/oQN998MwDve9/7+MlPflKz2iwcDjN//vwht990002cfvrpnHjiiRxwwAFsvPHGpNNpnn76aX7961+XpnYfdNBB3HbbbYTD4Yl5QGJCbbLJJiSTST70oQ+x1157sfnmm9PQ0EAymWTx4sX88Y9/LIXZ4XCYO+64gwMOOGDIOF/5ylf4/ve/D8COO+7Il770JTbffHNee+01Lr74Yp5++unSdt/97ncn7wGKcTde18w111xT8fdbbrmFW2+9FfA+1FiwYEHpvi222ELeNK6nxnq9vPbaa7znPe9h1apVgBcmVLueyk2fPp3p06dP3IMSE2as18sDDzzAfvvtx7vf/W6OPPJIdt55Z2bOnIllWaxYsYJHH32UK6+8khUrVgCw3Xbb8fjjj0sH9fXUeP0+GukYS5cuZd68ebzxxhsT8CiEEEKs17QQUxhQ15958+ZVHefGG28ccd+TTz5ZZzKZyX2AYlzNmzcv0HWy0UYb6b///e/DjuM4jv7EJz5Rc4xTTz1VO44ziY9OTITxumbq+Tn18Y9/fPIeoBhXY71err766rp/r11wwQWT/0DFuBjr9XL//fcHvk4++MEP6lWrVq2FRynGy3j9PgpyjOFeLwshhJjapAu2EONg77335pJLLuGf//wnL774IitXrsQwDGbPns1+++3HySefzO677762T1OM0X333ce9997L/fffzwsvvMDKlStZs2YN0WiUGTNmsMMOO3DooYdy7LHHEo/Hhx3HMAyuvPJKPvShD3H55ZfzxBNP0NnZSUdHB7vuuitnnHEGH/jABybxkYmJMl7XjJga5HoR9Rjr9bLnnnvy4IMP8s9//pNHHnmEN998k5UrV5JOp2lqamLTTTdlt91244QTTmDPPfdcC49QjCf5+SKEEGJtkynYQgghhBBCCCGEEEKICSNNaIQQQgghhBBCCCGEEBNGAkghhBBCCCGEEEIIIcSEkQBSCCGEEEIIIYQQQggxYSSAFEIIIYQQQgghhBBCTBgJIIUQQgghhBBCCCGEEBNGAkghhBBCCCGEEEIIIcSEkQBSCCGEEEIIIYQQQggxYSSAFEIIIYQQQgghhBBCTBgJIIUQQgghhBBCCCGEEBNGAkghhBBCCCGEEEIIIcSEkQBSCCGEECPaZJNNUEpx8sknD7nvjTfeQCmFUoprrrlmws5h3333RSnFvvvuO2HHGE/+c1L+Z30599Gaio9ZCCGEEEKMTAJIIYQQQgghhBBCCCHEhJEAUgghhBAbBL/i7sILL1zbp1LhrLPOYvHixSxevJirr756bZ/OhPIf5+LFi9lll13W9ukIIYQQQoh1hLW2T0AIIYQQ67dNNtkErfWEH+eBBx6Y8GNMhOnTp7Pddtut7dOYFOWPM5FIrMUzEUIIIYQQ6xKpgBRCCCGEEEIIIYQQQkwYCSCFEEIIIYQQQgghhBATRgJIIYQQYj2xfPlyvvzlL7PTTjvR3NxMOBxm5syZbL/99hx//PFcc8019PX1DdkvlUpxww03cNppp7HDDjvQ3NxMKBRi2rRp7LPPPvzwhz+kv79/1Oc1UhfsCy+8sHQ/QDab5ZJLLmGnnXaisbGRxsZGFi5cyC9+8Qts2x72OMN1wfY7dPsuuuiiIZ2Y/e7dRx99NEopWltbyWazNR+XbdvMnDkTpRQHHXRQsCdjlAavX3nvvfdy+OGHM2vWLKLRKJttthnnnHMOb731Vs1xenp6+M53vsMee+xBa2tr6fu8zTbbcNRRR/GrX/2KVatWjXj84axvnciFEEIIIcS6QdaAFEIIIdYDDz/8MIceeuiQgHHlypWsXLmS5557juuvv56Ojg4OPfTQim0++MEP8uCDDw4Zs7Ozk4ceeoiHHnqIyy67jDvvvJMFCxZM6ONYuXIlBx98MP/9738rbn/iiSd44okn+Pvf/84tt9yCYUzMZ6SnnXYaf/3rX+np6eGWW27huOOOG3bbO++8k5UrVwLwiU98YkLOp5qLLrpoSBC4ZMkSfvnLX/KHP/yB2267jfe+971D9nvhhRc44IADWL58ecXtnZ2ddHZ28sILL3DLLbfgOA7nnHPORD4EIYQQQgghKkgAKYQQQqzjcrkcxx13HH19fTQ2NnLWWWex3377MX36dAqFAkuXLuWxxx7jL3/5S9X9bdtm++235/DDD2eXXXZh9uzZaK1ZunQpf/3rX/nzn//MkiVLOPLII3nmmWeIRqMT9liOPvpoXnjhBT796U9z2GGH0dbWxksvvcS3vvUtXnjhBW677TZ++9vfcsYZZwQe8+9//zv5fJ7tt98e8LpOn3322RXbtLa2AvD+97+fuXPnsmzZMq6++uqaAaTfsbq1tZWjjjqq3oc6KnfccQdPPvkkW221FV/84hd517veRW9vLzfeeCO//e1v6evr49BDD2Xx4sXMmzevYt+TTjqJ5cuXEwqFOP300/nABz7AzJkzcV2X5cuXs2jRomGvESGEEEIIISaSBJBCCCHEOu7RRx8tVbVdd911Qyocd9ttN4499lguueQS0un0kP2vvvpqttxyyyG3+/udeuqpHHzwwbz00kv88Y9/5NRTT52YBwKlKsfyKbw77bQTBx98MNtssw0rV67ksssuqyuAnD9/fsXfa3WdNgyDU045hW9+85vce++9LFu2jLlz5w7ZbtWqVdxxxx0AnHjiiUQikcDnMxZPPvkkO+20Ew8++CANDQ2l2/fff3/23HNPPvaxj5FMJvn85z/PjTfeWLr/9ddf56mnngLg0ksvrVrheOSRR/Kd73yHnp6eCX8cQgghhBBClJM1IIUQQoh13IoVK0pfV5t667Msi6ampiG3Vwsfyx1wwAEcfvjhANxyyy2jO8mAzj333KrrB7a1tXHKKacA8Oyzz9Lb2zth5/CJT3wCwzBwXZff//73Vbe59tprKRQKpe0n0+WXX14RPvpOOukkPvCBDwDe9+mdd94p3Rf0GvHXvxRCCCGEEGIySQAphBBCrONmzZpV+tqfFjwWq1ev5pVXXuG5554r/Zk2bRrAkLUZx9uJJ5447H0777xz6eslS5ZM2DnMmzePAw44AKBq0xwYeJ532GEHdtxxxwk7l8G23377iudhMD8MtW2bBx54oHR7+TUy3GMSQgghhBBibZEAUgghhFjH7bXXXmy22WYAnHfeeSxcuJDvfe97/Otf/yKfzwca49FHH+UjH/kI7e3tTJ8+nfnz57P99tuX/vz2t78FvIYlE6lWk5u2trbS18lkckLP47TTTgPg1Vdf5eGHH66478knn+S5554DJr/6cdddd615/8KFC0tf++cIsOmmm7L33nsD8OMf/5htt92Wb3zjG/zzn/+sOi1fCCGEEEKIySQBpBBCCLGOC4VC3HbbbWy99daAt47iV7/6Vfbcc09aWlr4wAc+wHXXXYfjOFX3v/DCC9lrr73485//TFdXV81jZTKZcT//cvF4fNj7yjtfD/dYxssRRxxRqvocXFV61VVXARCJRGpWbE6E6dOn17x/xowZpa8Hfy//9Kc/scceewDwv//9j29961vsv//+tLS0sM8++/DrX/+abDY7/icthBBCCCHECCSAFEIIIdYD22yzDYsXL+avf/0rn/jEJ9h8880BLzC8++67OfHEE9ltt91YtWpVxX733XcfF110EQCbbbYZl112Gc8++yw9PT3Yto3WGq01559//qQ/prUpHA7zsY99DIAbb7yR/v5+ALLZLNdffz3gNW0pr8qcDEqpUe87Z84c/vWvf3Hvvfdy9tlns+2226KUolAo8NBDD3HWWWex3Xbb8fLLL4/jGQshhBBCCDEyCSCFEEKI9YRpmhx55JFceeWVvPrqqyxfvpwrr7yytGbgU089NaR7tD+1uqWlhccee4yzzjqL7bffnubmZkzTLG3X3d09eQ9kHeFPw+7v7+emm24CvOYu/nMx2dOvAVauXBn4/uHC0f33359f/n97dxMSVRuGcfzydXLEspAWJYQ6iyj6oEyJqKYxW7gYamGFKEnZF2VUTERQi1JaBCkoUVmLUgjMRUFYDgaZTeWM4WgDaS2aWgVFkvYNRs28i8F5m9ePFDyO6f+30vPMc859thfnfu4LF9TZ2anu7m7V1dUpOztbkvTq1Svl5eUN2NMffAYCgWGf/+3bt2HXAQAAgMEQQAIA8JdKTk7Wzp075fF4tGLFCknSnTt3Itqou7q6JEnZ2dnDtvd6vV5ji52AFi5cqDVr1kj6rw27v/06JSUlPKhmPLW1tY14fcmSJX+83+zZs5WXl6empqbwpHOfz6eXL19G/C4xMVHS8EF0IBAYsA8AAAAYCQJIAAD+ctOmTZPNZpMUmo788ePH8NrPnz8ladhBJD6fT62trYbWOB7i4+MlSX19fSPes2fPHknSw4cP1dzcrKamJknSjh07Is6kHC/Pnj3T06dPh1zvD0hjY2OVlZU1qntv2LAh/Pf/hw1ZLBZJwwfRTqdTnz59GtUzAQAAAIkAEgCACe/Ro0fy+/1Drv/48UMul0uSNGPGjPBwFUmaP3++JOnx48d6/fr1gL3d3d3atm3bGFccHcnJyZJCbcYjtXXrVs2aNUuSVFBQoEAgoJiYGBU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    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# T/S diagram color-coded by depth (averaged over time).\n", "ax = od_moor.plot.TS_diagram(colorName=\"Z\", meanAxes=\"time\")" @@ -358,13 +3760,4858 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:49:57.039680Z", + "iopub.status.busy": "2023-04-11T16:49:57.039110Z", + "iopub.status.idle": "2023-04-11T16:50:27.426998Z", + "shell.execute_reply": "2023-04-11T16:50:27.424550Z", + "shell.execute_reply.started": "2023-04-11T16:49:57.039627Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing potential density anomaly using the following parameters: {'eq_state': 'jmd95'}.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:27, 1.94s/it] " + ] + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:29, 1.86s/it]\n" + ] + } + ], "source": [ "# Using .animate instead of .plot\n", "anim = od_moor.animate.TS_diagram(colorName=\"Z\")\n", @@ -400,13 +8647,44 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:50:27.430558Z", + "iopub.status.busy": "2023-04-11T16:50:27.429891Z", + "iopub.status.idle": "2023-04-11T16:50:35.077275Z", + "shell.execute_reply": "2023-04-11T16:50:35.075098Z", + "shell.execute_reply.started": "2023-04-11T16:50:27.430496Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cutting out the oceandataset.\n", + "Carrying out survey.\n", + "Variables to interpolate: ['S', 'Temp', 'U', 'V', 'XC', 'XG', 'XU', 'XV', 'YC', 'YG', 'YU', 'YV', 'Xind', 'Yind'].\n", + "Interpolating [S].\n", + "Interpolating [Temp].\n", + "Interpolating [U].\n", + "Interpolating [V].\n", + "Interpolating [XC].\n", + "Interpolating [XG].\n", + "Interpolating [XU].\n", + "Interpolating [XV].\n", + "Interpolating [YC].\n", + "Interpolating [YG].\n", + "Interpolating [YU].\n", + "Interpolating [YV].\n", + "Interpolating [Xind].\n", + "Interpolating [Yind].\n" + ] + } + ], "source": [ "# Extract survey overlapping the mooring array\n", "# Note: This function interpolates, getting rid of staggered grids\n", @@ -432,13 +8710,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:50:35.080654Z", + "iopub.status.busy": "2023-04-11T16:50:35.080015Z", + "iopub.status.idle": "2023-04-11T16:50:39.116303Z", + "shell.execute_reply": "2023-04-11T16:50:39.113762Z", + "shell.execute_reply.started": "2023-04-11T16:50:35.080595Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing potential density anomaly using the following parameters: {'eq_state': 'jmd95'}.\n", + "Computing weighted_mean.\n", + "Computing weighted_mean.\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Vertical section of temperature with isopycnals\n", "xr_kwargs = dict(center=False, cmap=\"Spectral_r\")\n", @@ -460,13 +8765,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:50:39.118863Z", + "iopub.status.busy": "2023-04-11T16:50:39.118228Z", + "iopub.status.idle": "2023-04-11T16:50:39.227219Z", + "shell.execute_reply": "2023-04-11T16:50:39.224880Z", + "shell.execute_reply.started": "2023-04-11T16:50:39.118805Z" + }, "slideshow": { "slide_type": "-" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing survey aligned velocities.\n" + ] + } + ], "source": [ "# Switch reference system to cross/along-section\n", "od_surv = od_surv.compute.survey_aligned_velocities()" @@ -485,9 +8805,3840 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:50:39.229438Z", + "iopub.status.busy": "2023-04-11T16:50:39.228808Z", + "iopub.status.idle": "2023-04-11T16:51:10.577735Z", + "shell.execute_reply": "2023-04-11T16:51:10.575107Z", + "shell.execute_reply.started": "2023-04-11T16:50:39.229344Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:28, 1.79s/it] " + ] + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:29, 1.84s/it]\n" + ] + } + ], "source": [ "# Animation of velocity orthogonal to the section\n", "xr_kwargs = dict(robust=True)\n", @@ -526,9 +12677,37 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 15, + "metadata": { + "execution": { + "iopub.execute_input": "2023-04-11T16:51:10.581223Z", + "iopub.status.busy": "2023-04-11T16:51:10.580582Z", + "iopub.status.idle": "2023-04-11T16:51:12.789178Z", + "shell.execute_reply": "2023-04-11T16:51:12.786560Z", + "shell.execute_reply.started": "2023-04-11T16:51:10.581161Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cutting out the oceandataset.\n", + "Computing potential density anomaly using the following parameters: {'eq_state': 'jmd95'}.\n", + "Computing Brunt-Väisälä Frequency using the following parameters: {'rho0': 1027, 'g': 9.81}.\n", + "Computing gradient.\n", + "Computing relative vorticity.\n", + "Computing curl.\n", + "Computing gradient.\n", + "Computing gradient.\n", + "Computing gradient.\n", + "Computing gradient.\n", + "Computing Ertel potential vorticity using the following parameters: {'rho0': 1027, 'g': 9.81, 'omega': 7.292123516990375e-05}.\n", + "Computing potential density anomaly using the following parameters: {'eq_state': 'jmd95'}.\n", + "Computing gradient.\n" + ] + } + ], "source": [ "# Compute Ertel PV in the top 100m\n", "od100m = od.subsample.cutout(ZRange=[0, -100])\n", @@ -537,14 +12716,7259 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "cell_style": "split", + "execution": { + "iopub.execute_input": "2023-04-11T16:51:12.792585Z", + "iopub.status.busy": "2023-04-11T16:51:12.791935Z", + "iopub.status.idle": "2023-04-11T16:51:40.223755Z", + "shell.execute_reply": "2023-04-11T16:51:40.220617Z", + "shell.execute_reply.started": "2023-04-11T16:51:12.792527Z" + }, "slideshow": { "slide_type": "subslide" } }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:22, 1.43s/it] " + ] + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "16it [00:23, 1.48s/it]\n" + ] + } + ], "source": [ "# Plot Ertel PV (averaged over Z).\n", "# Note: The vertical mean is automatically weighted.\n", @@ -601,9 +20025,9 @@ "metadata": { "celltoolbar": "Slideshow", "kernelspec": { - "display_name": "Python 3", + "display_name": "Oceanography", "language": "python", - "name": "python3" + "name": "oceanography" }, "language_info": { "codemirror_mode": { @@ -615,7 +20039,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.1" + "version": "3.9.16" }, "livereveal": { "autolaunch": true, @@ -625,5 +20049,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } From 5608425028b0acadbfa57d046bfbda23116c61ad Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Wed, 12 Apr 2023 08:54:27 -0400 Subject: [PATCH 04/32] Format (#344) * format * update notebooks * update tutorial notebook on binder --------- Co-authored-by: Miguel Jimenez --- binder/Live_Demo.ipynb | 16 +- binder/Tutorial.ipynb | 24346 +++++++++++++++++++-------------------- docs/Kogur.ipynb | 275 +- docs/Particles.ipynb | 2008 ++-- docs/Statistics.ipynb | 188 +- docs/Tutorial.ipynb | 279 +- 6 files changed, 13403 insertions(+), 13709 deletions(-) diff --git a/binder/Live_Demo.ipynb b/binder/Live_Demo.ipynb index edfaabdd..ce702030 100644 --- a/binder/Live_Demo.ipynb +++ b/binder/Live_Demo.ipynb @@ -149,11 +149,11 @@ "outputs": [], "source": [ "import warnings\n", + "from pathlib import Path\n", "\n", "import cartopy.crs as ccrs\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", - "from pathlib import Path\n", "\n", "# Import additional packages and change some defaults\n", "import xarray as xr\n", @@ -486,19 +486,19 @@ "# Import OceanDataset\n", "\n", "# Download the data if you don't already have it. E.g., you're running the notebook in a non-binder environment.\n", - "path_to_file = 'OSM2020_EGshelfIIseas2km_ERAI_1D'\n", + "path_to_file = \"OSM2020_EGshelfIIseas2km_ERAI_1D\"\n", "path = Path(path_to_file)\n", - "if not(path.is_dir()):\n", - " print(f'The folder {path_to_file} does not exist...downloading...')\n", + "if not (path.is_dir()):\n", + " print(f\"The folder {path_to_file} does not exist...downloading...\")\n", " # myurl=\"https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/ETTi4yKjbvxOvraRKaydA3kBy_sOKNmkqGFP61CfsgW_bQ?\"\n", " !wget -v -O tmp.tar.gz -L https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/ETTi4yKjbvxOvraRKaydA3kBy_sOKNmkqGFP61CfsgW_bQ?download=1\n", - " !tar xvzf tmp.tar.gz \n", - " !rm -f tmp.tar.gz \n", + " !tar xvzf tmp.tar.gz\n", + " !rm -f tmp.tar.gz\n", "else:\n", - " print(f'The folder {path_to_file} exists...reading...')\n", + " print(f\"The folder {path_to_file} exists...reading...\")\n", "\n", "# Then read the data\n", - "od = ospy.open_oceandataset.from_zarr(path_to_file) " + "od = ospy.open_oceandataset.from_zarr(path_to_file)" ] }, { diff --git a/binder/Tutorial.ipynb b/binder/Tutorial.ipynb index 79ce5249..a644c48e 100644 --- a/binder/Tutorial.ipynb +++ b/binder/Tutorial.ipynb @@ -19,11 +19,11 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:45:00.077459Z", - "iopub.status.busy": "2023-04-04T02:45:00.076889Z", - "iopub.status.idle": "2023-04-04T02:45:19.132313Z", - "shell.execute_reply": "2023-04-04T02:45:19.130076Z", - "shell.execute_reply.started": "2023-04-04T02:45:00.077399Z" + "iopub.execute_input": "2023-04-12T03:45:16.579599Z", + "iopub.status.busy": "2023-04-12T03:45:16.578765Z", + "iopub.status.idle": "2023-04-12T03:45:35.745934Z", + "shell.execute_reply": "2023-04-12T03:45:35.743595Z", + "shell.execute_reply.started": "2023-04-12T03:45:16.579537Z" }, "tags": [] }, @@ -75,332 +75,22 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:45:19.138143Z", - "iopub.status.busy": "2023-04-04T02:45:19.137037Z", - "iopub.status.idle": "2023-04-04T02:45:23.411269Z", - "shell.execute_reply": "2023-04-04T02:45:23.408707Z", - "shell.execute_reply.started": "2023-04-04T02:45:19.138086Z" - } + "iopub.execute_input": "2023-04-12T03:45:35.751371Z", + "iopub.status.busy": "2023-04-12T03:45:35.750124Z", + "iopub.status.idle": "2023-04-12T03:45:35.761155Z", + "shell.execute_reply": "2023-04-12T03:45:35.758886Z", + "shell.execute_reply.started": "2023-04-12T03:45:35.751272Z" + }, + "tags": [] }, - "outputs": [ - { - "data": { - "text/html": [ - "
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    " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "from dask.distributed import Client\n", + "SciServer = False # True: SciServer - False: running on binder\n", + "if SciServer:\n", + " from dask.distributed import Client\n", "\n", - "client = Client()\n", - "client" + " client = Client()\n", + " client" ] }, { @@ -440,11 +130,11 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:45:23.415499Z", - "iopub.status.busy": "2023-04-04T02:45:23.414803Z", - "iopub.status.idle": "2023-04-04T02:47:01.820147Z", - "shell.execute_reply": "2023-04-04T02:47:01.816806Z", - "shell.execute_reply.started": "2023-04-04T02:45:23.415417Z" + "iopub.execute_input": "2023-04-12T03:45:35.764085Z", + "iopub.status.busy": "2023-04-12T03:45:35.763528Z", + "iopub.status.idle": "2023-04-12T03:46:50.173760Z", + "shell.execute_reply": "2023-04-12T03:46:50.171379Z", + 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.......... .......... .......... 0% 27.4M 18s\n", - " 2000K .......... .......... .......... .......... .......... 0% 31.9M 18s\n", - " 2050K .......... .......... .......... .......... .......... 0% 40.0M 18s\n", - " 2100K .......... .......... .......... .......... .......... 0% 37.4M 18s\n", - " 2150K .......... .......... .......... .......... .......... 0% 45.0M 18s\n", - " 2200K .......... .......... .......... .......... .......... 0% 35.9M 18s\n", - " 2250K .......... .......... .......... .......... .......... 0% 41.2M 18s\n", - " 2300K .......... .......... .......... .......... .......... 0% 39.7M 18s\n", - " 2350K .......... .......... .......... .......... .......... 0% 67.4M 18s\n", - " 2400K .......... .......... .......... .......... .......... 0% 42.3M 17s\n", - " 2450K .......... .......... .......... .......... .......... 0% 51.5M 17s\n", - " 2500K .......... .......... .......... .......... .......... 0% 39.3M 17s\n", - " 2550K .......... .......... .......... .......... .......... 0% 36.1M 17s\n", - " 2600K .......... .......... .......... .......... .......... 0% 46.6M 17s\n", - " 2650K .......... .......... .......... .......... .......... 0% 37.4M 17s\n", - " 2700K .......... .......... .......... .......... .......... 0% 52.3M 17s\n", - " 2750K .......... .......... .......... .......... .......... 0% 42.9M 17s\n", - " 2800K .......... .......... .......... .......... .......... 0% 51.8M 17s\n", - " 2850K .......... .......... .......... .......... .......... 0% 38.1M 17s\n", - " 2900K .......... .......... .......... .......... .......... 0% 47.5M 17s\n", - " 2950K .......... .......... .......... .......... .......... 0% 43.9M 17s\n", - " 3000K .......... .......... .......... .......... .......... 0% 34.3M 17s\n", - " 3050K .......... .......... .......... .......... .......... 0% 51.3M 17s\n", - " 3100K .......... .......... .......... .......... .......... 0% 45.1M 17s\n", - " 3150K .......... .......... .......... .......... .......... 0% 45.3M 16s\n", - " 3200K .......... .......... .......... .......... .......... 0% 50.6M 16s\n", - " 3250K .......... .......... .......... .......... .......... 0% 47.8M 16s\n", - " 3300K .......... .......... .......... .......... .......... 0% 47.0M 16s\n", - " 3350K .......... .......... .......... .......... .......... 0% 49.4M 16s\n", - " 3400K .......... .......... .......... .......... .......... 0% 45.9M 16s\n", - " 3450K .......... .......... .......... .......... .......... 0% 41.8M 16s\n", - " 3500K .......... .......... .......... .......... .......... 0% 40.8M 16s\n", - " 3550K .......... .......... .......... .......... .......... 0% 44.0M 16s\n", - " 3600K .......... .......... .......... .......... .......... 0% 32.5M 16s\n", - " 3650K .......... .......... .......... .......... .......... 0% 36.6M 16s\n", - " 3700K .......... .......... .......... .......... .......... 0% 65.7M 16s\n", - " 3750K .......... .......... .......... .......... .......... 0% 54.2M 16s\n", - " 3800K .......... .......... .......... .......... .......... 0% 50.1M 16s\n", - " 3850K .......... .......... .......... .......... .......... 0% 57.2M 16s\n", - " 3900K .......... .......... .......... .......... .......... 0% 56.4M 16s\n", - " 3950K .......... .......... .......... .......... .......... 0% 50.4M 16s\n", - " 4000K .......... .......... .......... .......... .......... 0% 4.13M 17s\n", - " 4050K .......... .......... .......... .......... .......... 0% 66.2M 17s\n", - " 4100K .......... .......... .......... .......... .......... 0% 63.3M 17s\n", - " 4150K .......... .......... .......... .......... .......... 0% 65.9M 17s\n", - " 4200K .......... .......... .......... .......... .......... 0% 49.2M 17s\n", - " 4250K .......... .......... .......... .......... .......... 0% 53.1M 17s\n", - " 4300K .......... .......... .......... .......... .......... 0% 52.8M 17s\n", - " 4350K .......... .......... .......... .......... .......... 0% 60.1M 17s\n", - " 4400K .......... .......... .......... .......... .......... 0% 54.1M 16s\n", - " 4450K .......... .......... .......... .......... .......... 0% 66.0M 16s\n", - " 4500K .......... .......... .......... .......... .......... 0% 54.5M 16s\n", - " 4550K .......... .......... .......... .......... .......... 0% 46.0M 16s\n", - " 4600K .......... .......... .......... .......... .......... 0% 48.4M 16s\n", - " 4650K .......... .......... .......... .......... .......... 0% 58.5M 16s\n", - " 4700K .......... .......... .......... .......... .......... 0% 63.9M 16s\n", - " 4750K .......... .......... .......... .......... .......... 0% 55.7M 16s\n", - " 4800K .......... .......... .......... .......... .......... 0% 44.8M 16s\n", - " 4850K .......... .......... .......... .......... .......... 0% 52.4M 16s\n", - " 4900K .......... .......... .......... .......... .......... 0% 80.3M 16s\n", - " 4950K .......... .......... .......... .......... .......... 0% 64.5M 16s\n", - " 5000K .......... .......... .......... .......... .......... 0% 44.0M 16s\n", - " 5050K .......... .......... .......... .......... .......... 0% 55.6M 16s\n", - " 5100K .......... .......... .......... .......... .......... 0% 49.0M 16s\n", - " 5150K .......... .......... .......... .......... .......... 0% 63.2M 16s\n", - " 5200K .......... .......... .......... .......... .......... 0% 61.6M 16s\n", - " 5250K .......... .......... .......... .......... .......... 0% 47.2M 16s\n", - " 5300K .......... .......... .......... .......... .......... 0% 44.6M 15s\n", - " 5350K .......... .......... .......... .......... .......... 0% 54.3M 15s\n", - " 5400K .......... .......... .......... .......... .......... 0% 57.3M 15s\n", - " 5450K .......... .......... .......... .......... .......... 0% 68.1M 15s\n", - " 5500K .......... .......... .......... .......... .......... 0% 57.0M 15s\n", - " 5550K .......... .......... .......... .......... .......... 0% 47.7M 15s\n", - " 5600K .......... .......... .......... .......... .......... 0% 48.7M 15s\n", - " 5650K .......... .......... .......... .......... .......... 0% 73.5M 15s\n", - " 5700K .......... .......... .......... .......... .......... 0% 69.1M 15s\n", - " 5750K .......... .......... .......... .......... .......... 0% 69.8M 15s\n", - " 5800K .......... .......... .......... .......... .......... 0% 38.4M 15s\n", - " 5850K .......... .......... .......... .......... .......... 0% 43.0M 15s\n", - " 5900K .......... .......... .......... .......... .......... 1% 68.4M 15s\n", - " 5950K .......... .......... .......... .......... .......... 1% 62.1M 15s\n", - " 6000K .......... .......... .......... .......... .......... 1% 48.0M 15s\n", - " 6050K .......... .......... .......... .......... .......... 1% 47.8M 15s\n", - " 6100K .......... .......... .......... .......... .......... 1% 54.2M 15s\n", - " 6150K .......... .......... .......... .......... .......... 1% 64.7M 15s\n", - " 6200K .......... .......... .......... .......... .......... 1% 53.8M 15s\n", - " 6250K .......... .......... .......... .......... .......... 1% 52.5M 15s\n", - " 6300K .......... .......... .......... .......... .......... 1% 51.7M 15s\n", - " 6350K .......... .......... .......... .......... .......... 1% 47.3M 15s\n", - " 6400K .......... .......... .......... .......... .......... 1% 55.1M 15s\n", - " 6450K .......... .......... .......... .......... .......... 1% 60.1M 15s\n", - " 6500K .......... .......... .......... .......... .......... 1% 48.9M 15s\n", - " 6550K .......... .......... .......... .......... .......... 1% 44.3M 15s\n", - " 6600K .......... .......... .......... .......... .......... 1% 44.0M 15s\n", - " 6650K .......... .......... .......... .......... .......... 1% 67.2M 14s\n", - " 6700K .......... .......... .......... .......... .......... 1% 74.0M 14s\n", - " 6750K .......... .......... .......... .......... .......... 1% 53.1M 14s\n", - " 6800K .......... .......... .......... .......... .......... 1% 46.9M 14s\n", - " 6850K .......... .......... .......... .......... .......... 1% 56.3M 14s\n", - " 6900K .......... .......... .......... .......... .......... 1% 64.6M 14s\n", - " 6950K .......... .......... .......... .......... .......... 1% 71.2M 14s\n", - " 7000K .......... .......... .......... .......... .......... 1% 48.4M 14s\n", - " 7050K .......... .......... .......... .......... .......... 1% 55.6M 14s\n", - " 7100K .......... .......... .......... .......... .......... 1% 49.7M 14s\n", - " 7150K .......... .......... .......... .......... .......... 1% 63.4M 14s\n", - " 7200K .......... .......... .......... .......... .......... 1% 57.3M 14s\n", - " 7250K .......... .......... .......... .......... .......... 1% 61.4M 14s\n", - " 7300K .......... .......... .......... .......... .......... 1% 56.9M 14s\n", - " 7350K .......... .......... .......... .......... .......... 1% 47.8M 14s\n", - " 7400K .......... .......... .......... .......... .......... 1% 43.3M 14s\n", - " 7450K .......... .......... .......... .......... .......... 1% 68.2M 14s\n", - " 7500K .......... .......... .......... .......... .......... 1% 61.9M 14s\n", - " 7550K .......... .......... .......... .......... .......... 1% 49.2M 14s\n", - " 7600K .......... .......... .......... .......... .......... 1% 41.5M 14s\n", - " 7650K .......... .......... .......... .......... .......... 1% 55.1M 14s\n", - " 7700K .......... .......... .......... .......... .......... 1% 65.2M 14s\n", - " 7750K .......... .......... .......... .......... .......... 1% 62.6M 14s\n", - " 7800K .......... .......... .......... .......... .......... 1% 42.5M 14s\n", - " 7850K .......... .......... .......... .......... .......... 1% 45.9M 14s\n", - " 7900K .......... .......... .......... .......... .......... 1% 65.7M 14s\n", - " 7950K .......... .......... .......... .......... .......... 1% 79.1M 14s\n", - " 8000K .......... .......... .......... .......... .......... 1% 54.6M 14s\n", - " 8050K .......... .......... .......... .......... .......... 1% 47.1M 14s\n", - " 8100K .......... .......... .......... .......... .......... 1% 49.9M 14s\n", - " 8150K .......... .......... .......... .......... .......... 1% 60.5M 14s\n", - " 8200K .......... .......... .......... .......... .......... 1% 54.4M 14s\n", - " 8250K .......... .......... .......... .......... .......... 1% 61.2M 14s\n", - " 8300K .......... .......... .......... .......... .......... 1% 57.8M 14s\n", - " 8350K .......... .......... .......... .......... .......... 1% 57.3M 14s\n", - " 8400K .......... .......... .......... .......... .......... 1% 53.7M 14s\n", - " 8450K .......... .......... .......... .......... .......... 1% 71.3M 14s\n", - " 8500K .......... .......... .......... .......... .......... 1% 58.1M 14s\n", - " 8550K .......... .......... .......... .......... .......... 1% 58.0M 14s\n", - " 8600K .......... .......... .......... .......... .......... 1% 38.5M 14s\n", - " 8650K .......... .......... .......... .......... .......... 1% 57.0M 13s\n", - " 8700K .......... .......... .......... .......... .......... 1% 64.4M 13s\n", - " 8750K .......... .......... .......... .......... .......... 1% 75.1M 13s\n", - " 8800K .......... .......... .......... .......... .......... 1% 63.8M 13s\n", - " 8850K .......... .......... .......... .......... .......... 1% 68.1M 13s\n", - " 8900K .......... .......... .......... .......... .......... 1% 68.4M 13s\n", - " 8950K .......... .......... .......... .......... .......... 1% 61.1M 13s\n", - " 9000K .......... .......... .......... .......... .......... 1% 58.3M 13s\n", - " 9050K .......... .......... .......... .......... .......... 1% 52.6M 13s\n", - " 9100K .......... .......... .......... .......... .......... 1% 49.8M 13s\n", - " 9150K .......... .......... .......... .......... .......... 1% 48.5M 13s\n", - " 9200K .......... .......... .......... .......... .......... 1% 60.9M 13s\n", - " 9250K .......... .......... .......... .......... .......... 1% 76.1M 13s\n", - " 9300K .......... .......... .......... .......... .......... 1% 58.5M 13s\n", - " 9350K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", - " 9400K .......... .......... .......... .......... .......... 1% 40.9M 13s\n", - " 9450K .......... .......... .......... .......... .......... 1% 44.8M 13s\n", - " 9500K .......... .......... .......... .......... .......... 1% 59.4M 13s\n", - " 9550K .......... .......... .......... .......... .......... 1% 59.0M 13s\n", - " 9600K .......... .......... .......... .......... .......... 1% 40.5M 13s\n", - " 9650K .......... .......... .......... .......... .......... 1% 43.2M 13s\n", - " 9700K .......... .......... .......... .......... .......... 1% 62.3M 13s\n", - " 9750K .......... .......... .......... .......... .......... 1% 59.1M 13s\n", - " 9800K .......... .......... .......... .......... .......... 1% 40.0M 13s\n", - " 9850K .......... .......... .......... .......... .......... 1% 53.0M 13s\n", - " 9900K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", - " 9950K .......... .......... .......... .......... .......... 1% 64.0M 13s\n", - " 10000K .......... .......... .......... .......... .......... 1% 43.6M 13s\n", - " 10050K .......... .......... .......... .......... .......... 1% 53.4M 13s\n", - " 10100K .......... .......... .......... .......... .......... 1% 56.0M 13s\n", - " 10150K .......... .......... .......... .......... .......... 1% 52.7M 13s\n", - " 10200K .......... .......... .......... .......... .......... 1% 54.6M 13s\n", - " 10250K .......... .......... .......... .......... .......... 1% 48.6M 13s\n", - " 10300K .......... .......... .......... .......... .......... 1% 54.7M 13s\n", - " 10350K .......... .......... .......... .......... .......... 1% 51.4M 13s\n", - " 10400K .......... .......... .......... .......... .......... 1% 56.7M 13s\n", - " 10450K .......... .......... .......... .......... .......... 1% 71.4M 13s\n", - " 10500K .......... .......... .......... .......... .......... 1% 52.8M 13s\n", - " 10550K .......... .......... .......... .......... .......... 1% 65.8M 13s\n", - " 10600K .......... .......... .......... .......... .......... 1% 56.4M 13s\n", - " 10650K .......... .......... .......... .......... .......... 1% 61.8M 13s\n", - " 10700K .......... .......... .......... .......... .......... 1% 68.7M 13s\n", - " 10750K .......... .......... .......... .......... .......... 1% 64.6M 13s\n", - " 10800K .......... .......... .......... .......... .......... 1% 46.0M 13s\n", - " 10850K .......... .......... .......... .......... .......... 1% 53.9M 13s\n", - " 10900K .......... .......... .......... .......... .......... 1% 46.8M 13s\n", - " 10950K .......... .......... .......... .......... .......... 1% 74.4M 13s\n", - " 11000K .......... .......... .......... .......... .......... 1% 38.9M 13s\n", - " 11050K .......... .......... .......... .......... .......... 1% 51.6M 13s\n", - " 11100K .......... .......... .......... .......... .......... 1% 45.4M 13s\n", - " 11150K .......... .......... .......... .......... .......... 1% 54.0M 13s\n", - " 11200K .......... .......... .......... .......... .......... 1% 49.8M 13s\n", - " 11250K .......... .......... .......... .......... .......... 1% 55.0M 13s\n", - " 11300K .......... .......... .......... .......... .......... 1% 37.2M 13s\n", - " 11350K .......... .......... .......... .......... .......... 1% 48.7M 13s\n", - " 11400K .......... .......... .......... .......... .......... 1% 46.1M 13s\n", - " 11450K .......... .......... .......... .......... .......... 1% 59.7M 13s\n", - " 11500K .......... .......... .......... .......... .......... 1% 62.2M 13s\n", - " 11550K .......... .......... .......... .......... .......... 1% 57.6M 13s\n", - " 11600K .......... .......... .......... .......... .......... 1% 49.0M 13s\n", - " 11650K .......... .......... .......... .......... .......... 1% 66.8M 13s\n", - " 11700K .......... .......... .......... .......... .......... 1% 55.0M 13s\n", - " 11750K .......... .......... .......... .......... .......... 1% 69.1M 13s\n", - " 11800K .......... .......... .......... .......... .......... 1% 51.1M 13s\n", - " 11850K .......... .......... .......... .......... .......... 2% 55.9M 13s\n", - " 11900K .......... .......... .......... .......... .......... 2% 70.0M 13s\n", - " 11950K .......... .......... .......... .......... .......... 2% 58.4M 13s\n", - " 12000K .......... .......... .......... .......... .......... 2% 52.8M 13s\n", - " 12050K .......... .......... .......... .......... .......... 2% 57.3M 13s\n", - " 12100K .......... .......... .......... .......... .......... 2% 59.0M 13s\n", - " 12150K .......... .......... .......... .......... .......... 2% 57.1M 13s\n", - " 12200K .......... .......... .......... .......... .......... 2% 44.1M 13s\n", - " 12250K .......... .......... .......... .......... .......... 2% 49.0M 13s\n", - " 12300K .......... .......... .......... .......... .......... 2% 54.8M 13s\n", - " 12350K .......... .......... .......... .......... .......... 2% 50.4M 13s\n", - " 12400K .......... .......... .......... .......... .......... 2% 51.8M 13s\n", - " 12450K .......... .......... .......... .......... .......... 2% 59.3M 13s\n", - " 12500K .......... .......... .......... .......... .......... 2% 46.3M 13s\n", - " 12550K .......... .......... .......... .......... .......... 2% 51.7M 13s\n", - " 12600K .......... .......... .......... .......... .......... 2% 47.3M 13s\n", - " 12650K .......... .......... .......... .......... .......... 2% 64.9M 12s\n", - " 12700K .......... .......... .......... .......... .......... 2% 4.02M 13s\n", - " 12750K .......... .......... .......... .......... .......... 2% 68.4M 13s\n", - " 12800K .......... .......... .......... .......... .......... 2% 64.4M 13s\n", - " 12850K .......... .......... .......... .......... .......... 2% 69.3M 13s\n", - " 12900K .......... .......... .......... .......... .......... 2% 66.0M 13s\n", - " 12950K .......... .......... .......... .......... .......... 2% 63.9M 13s\n", - " 13000K .......... .......... .......... .......... .......... 2% 45.8M 13s\n", - " 13050K .......... .......... .......... .......... .......... 2% 61.4M 13s\n", - " 13100K .......... .......... .......... .......... .......... 2% 47.5M 13s\n", - " 13150K .......... .......... .......... .......... .......... 2% 61.5M 13s\n", - " 13200K .......... .......... .......... .......... .......... 2% 56.4M 13s\n", - " 13250K .......... .......... .......... .......... .......... 2% 15.8M 13s\n", - " 13300K .......... .......... .......... .......... .......... 2% 65.2M 13s\n", - " 13350K .......... .......... .......... .......... .......... 2% 66.9M 13s\n", - " 13400K .......... .......... .......... .......... .......... 2% 50.1M 13s\n", - " 13450K .......... .......... .......... .......... .......... 2% 63.0M 13s\n", - " 13500K .......... .......... .......... .......... .......... 2% 61.4M 13s\n", - " 13550K .......... .......... .......... .......... .......... 2% 50.9M 13s\n", - " 13600K .......... .......... .......... .......... .......... 2% 16.2M 13s\n", - " 13650K .......... .......... .......... .......... .......... 2% 46.6M 13s\n", - " 13700K .......... .......... .......... .......... .......... 2% 56.1M 13s\n", - " 13750K .......... .......... .......... .......... .......... 2% 19.5M 13s\n", - " 13800K .......... .......... .......... .......... .......... 2% 41.9M 13s\n", - " 13850K .......... .......... .......... .......... .......... 2% 50.8M 13s\n", - " 13900K .......... .......... .......... .......... .......... 2% 55.4M 13s\n", - " 13950K .......... .......... .......... .......... .......... 2% 77.1M 13s\n", - " 14000K .......... .......... .......... .......... .......... 2% 62.9M 13s\n", - " 14050K .......... .......... .......... .......... .......... 2% 64.2M 13s\n", - " 14100K .......... .......... .......... .......... .......... 2% 58.2M 13s\n", - " 14150K .......... .......... .......... .......... .......... 2% 57.6M 13s\n", - " 14200K .......... .......... .......... .......... .......... 2% 52.6M 13s\n", - " 14250K .......... .......... .......... .......... .......... 2% 67.0M 13s\n", - " 14300K .......... .......... .......... .......... .......... 2% 57.5M 13s\n", - " 14350K .......... .......... .......... .......... .......... 2% 70.8M 13s\n", - " 14400K .......... .......... .......... .......... .......... 2% 54.5M 13s\n", - " 14450K .......... .......... .......... .......... .......... 2% 65.5M 13s\n", - " 14500K .......... .......... .......... .......... .......... 2% 57.7M 13s\n", - " 14550K .......... .......... .......... .......... .......... 2% 51.0M 13s\n", - " 14600K .......... .......... .......... .......... .......... 2% 37.0M 13s\n", - " 14650K .......... .......... .......... .......... .......... 2% 62.1M 13s\n", - " 14700K .......... .......... .......... .......... .......... 2% 63.0M 13s\n", - " 14750K .......... .......... .......... .......... .......... 2% 47.3M 13s\n", - " 14800K .......... .......... .......... .......... .......... 2% 44.0M 13s\n", - " 14850K .......... .......... .......... .......... .......... 2% 49.7M 13s\n", - " 14900K .......... .......... .......... .......... .......... 2% 53.8M 13s\n", - " 14950K .......... .......... .......... .......... .......... 2% 48.6M 13s\n", - " 15000K .......... .......... .......... .......... .......... 2% 35.1M 13s\n", - " 15050K .......... .......... .......... .......... .......... 2% 48.4M 13s\n", - " 15100K .......... .......... .......... .......... .......... 2% 46.5M 13s\n", - " 15150K .......... .......... .......... .......... .......... 2% 50.0M 13s\n", - " 15200K .......... .......... .......... .......... .......... 2% 39.0M 13s\n", - " 15250K .......... .......... .......... .......... .......... 2% 46.6M 13s\n", - " 15300K .......... .......... .......... .......... .......... 2% 45.6M 13s\n", - " 15350K .......... .......... .......... .......... .......... 2% 63.3M 13s\n", - " 15400K .......... .......... .......... .......... .......... 2% 44.3M 13s\n", - " 15450K .......... .......... .......... .......... .......... 2% 53.1M 13s\n", - " 15500K .......... .......... .......... .......... .......... 2% 54.5M 13s\n", - " 15550K .......... .......... .......... .......... .......... 2% 56.0M 13s\n", - " 15600K .......... .......... .......... .......... .......... 2% 46.2M 13s\n", - " 15650K .......... .......... .......... .......... .......... 2% 56.4M 13s\n", - " 15700K .......... .......... .......... .......... .......... 2% 53.3M 13s\n", - " 15750K .......... .......... .......... .......... .......... 2% 51.4M 13s\n", - " 15800K .......... .......... .......... .......... .......... 2% 41.1M 13s\n", - " 15850K .......... .......... .......... .......... .......... 2% 59.9M 13s\n", - " 15900K .......... .......... .......... .......... .......... 2% 51.1M 13s\n", - " 15950K .......... .......... .......... .......... .......... 2% 50.0M 13s\n", - " 16000K .......... .......... .......... .......... .......... 2% 50.2M 13s\n", - " 16050K .......... .......... .......... .......... .......... 2% 52.1M 13s\n", - " 16100K .......... .......... .......... .......... .......... 2% 52.4M 13s\n", - " 16150K .......... .......... .......... .......... .......... 2% 52.2M 13s\n", - " 16200K .......... .......... .......... .......... .......... 2% 48.7M 13s\n", - " 16250K .......... .......... .......... .......... .......... 2% 67.7M 13s\n", - " 16300K .......... .......... .......... .......... .......... 2% 51.4M 13s\n", - " 16350K .......... .......... .......... .......... .......... 2% 56.3M 13s\n", - " 16400K .......... .......... .......... .......... .......... 2% 48.4M 13s\n", - " 16450K .......... .......... .......... .......... .......... 2% 50.6M 13s\n", - " 16500K .......... .......... .......... .......... .......... 2% 53.1M 13s\n", - " 16550K .......... .......... .......... .......... .......... 2% 53.6M 13s\n", - " 16600K .......... .......... .......... .......... .......... 2% 52.8M 13s\n", - " 16650K .......... .......... .......... .......... .......... 2% 52.2M 13s\n", - " 16700K .......... .......... .......... .......... .......... 2% 54.0M 13s\n", - " 16750K .......... .......... .......... .......... .......... 2% 57.4M 13s\n", - " 16800K .......... .......... .......... .......... .......... 2% 61.0M 13s\n", - " 16850K .......... .......... .......... .......... .......... 2% 50.4M 13s\n", - " 16900K .......... .......... .......... .......... .......... 2% 35.1M 13s\n", - " 16950K .......... .......... .......... .......... .......... 2% 32.1M 13s\n", - " 17000K .......... .......... .......... .......... .......... 2% 38.3M 13s\n", - " 17050K .......... .......... .......... .......... .......... 2% 52.0M 13s\n", - " 17100K .......... .......... .......... .......... .......... 2% 54.7M 13s\n", - " 17150K .......... .......... .......... .......... .......... 2% 51.1M 13s\n", - " 17200K .......... .......... .......... .......... .......... 2% 51.7M 13s\n", - " 17250K .......... .......... .......... .......... .......... 2% 57.6M 13s\n", - " 17300K .......... .......... .......... .......... .......... 2% 64.1M 13s\n", - " 17350K .......... .......... .......... .......... .......... 2% 46.2M 13s\n", - " 17400K .......... .......... .......... .......... .......... 2% 38.6M 13s\n", - " 17450K .......... .......... .......... .......... .......... 2% 54.9M 13s\n", - " 17500K .......... .......... .......... .......... .......... 2% 63.8M 12s\n", - " 17550K .......... .......... .......... .......... .......... 2% 51.2M 12s\n", - " 17600K .......... .......... .......... .......... .......... 2% 36.3M 12s\n", - " 17650K .......... .......... .......... .......... .......... 2% 58.5M 12s\n", - " 17700K .......... .......... .......... .......... .......... 2% 53.1M 12s\n", - " 17750K .......... .......... .......... .......... .......... 2% 48.9M 12s\n", - " 17800K .......... .......... .......... .......... .......... 3% 45.4M 12s\n", - " 17850K .......... .......... .......... .......... .......... 3% 54.0M 12s\n", - " 17900K .......... .......... .......... .......... .......... 3% 39.8M 12s\n", - " 17950K .......... .......... .......... .......... .......... 3% 54.8M 12s\n", - " 18000K .......... .......... .......... .......... .......... 3% 49.8M 12s\n", - " 18050K .......... .......... .......... .......... .......... 3% 56.7M 12s\n", - " 18100K .......... .......... .......... .......... .......... 3% 67.3M 12s\n", - " 18150K .......... .......... .......... .......... .......... 3% 63.0M 12s\n", - " 18200K .......... .......... .......... .......... .......... 3% 42.6M 12s\n", - " 18250K .......... .......... .......... .......... .......... 3% 53.2M 12s\n", - " 18300K .......... .......... .......... .......... .......... 3% 51.4M 12s\n", - " 18350K .......... .......... .......... .......... .......... 3% 41.3M 12s\n", - " 18400K .......... .......... .......... .......... .......... 3% 43.6M 12s\n", - " 18450K .......... .......... .......... .......... .......... 3% 64.1M 12s\n", - " 18500K .......... .......... .......... .......... .......... 3% 62.7M 12s\n", - " 18550K .......... .......... .......... .......... .......... 3% 65.5M 12s\n", - " 18600K .......... .......... .......... .......... .......... 3% 55.3M 12s\n", - " 18650K .......... .......... .......... .......... .......... 3% 62.3M 12s\n", - " 18700K .......... .......... .......... .......... .......... 3% 69.3M 12s\n", - " 18750K .......... .......... .......... .......... .......... 3% 66.0M 12s\n", - " 18800K .......... .......... .......... .......... .......... 3% 55.3M 12s\n", - " 18850K .......... .......... .......... .......... .......... 3% 67.7M 12s\n", - " 18900K .......... .......... .......... .......... .......... 3% 62.2M 12s\n", - " 18950K .......... .......... .......... .......... .......... 3% 59.8M 12s\n", - " 19000K .......... .......... .......... .......... .......... 3% 42.6M 12s\n", - " 19050K .......... .......... .......... .......... .......... 3% 50.0M 12s\n", - " 19100K .......... .......... .......... .......... .......... 3% 47.3M 12s\n", - " 19150K .......... .......... .......... .......... .......... 3% 40.2M 12s\n", - " 19200K .......... .......... .......... .......... .......... 3% 44.2M 12s\n", - " 19250K .......... .......... .......... .......... .......... 3% 43.6M 12s\n", - " 19300K .......... .......... .......... .......... .......... 3% 39.9M 12s\n", - " 19350K .......... .......... .......... .......... .......... 3% 54.1M 12s\n", - " 19400K .......... .......... .......... .......... .......... 3% 39.4M 12s\n", - " 19450K .......... .......... .......... .......... .......... 3% 37.6M 12s\n", - " 19500K .......... .......... .......... .......... .......... 3% 57.3M 12s\n", - " 19550K .......... .......... .......... .......... .......... 3% 62.1M 12s\n", - " 19600K .......... .......... .......... .......... .......... 3% 60.1M 12s\n", - " 19650K .......... .......... .......... .......... .......... 3% 47.1M 12s\n", - " 19700K .......... .......... .......... .......... .......... 3% 41.6M 12s\n", - " 19750K .......... .......... .......... .......... .......... 3% 59.5M 12s\n", - " 19800K .......... .......... .......... .......... .......... 3% 46.3M 12s\n", - " 19850K .......... .......... .......... .......... .......... 3% 54.9M 12s\n", - " 19900K .......... .......... .......... .......... .......... 3% 42.9M 12s\n", - " 19950K .......... .......... .......... .......... .......... 3% 48.3M 12s\n", - " 20000K .......... .......... .......... .......... .......... 3% 44.3M 12s\n", - " 20050K .......... .......... .......... .......... .......... 3% 65.9M 12s\n", - " 20100K .......... .......... .......... .......... .......... 3% 49.3M 12s\n", - " 20150K .......... .......... .......... .......... .......... 3% 52.8M 12s\n", - " 20200K .......... .......... .......... .......... .......... 3% 48.6M 12s\n", - " 20250K .......... .......... .......... .......... .......... 3% 63.3M 12s\n", - " 20300K .......... .......... .......... .......... .......... 3% 64.1M 12s\n", - " 20350K .......... .......... .......... .......... .......... 3% 51.0M 12s\n", - " 20400K .......... .......... .......... .......... .......... 3% 43.7M 12s\n", - " 20450K .......... .......... .......... .......... .......... 3% 57.9M 12s\n", - " 20500K .......... .......... .......... .......... .......... 3% 72.4M 12s\n", - " 20550K .......... .......... .......... .......... .......... 3% 70.6M 12s\n", - " 20600K .......... .......... .......... .......... .......... 3% 50.0M 12s\n", - " 20650K .......... .......... .......... .......... .......... 3% 46.0M 12s\n", - " 20700K .......... .......... .......... .......... .......... 3% 59.2M 12s\n", - " 20750K .......... .......... .......... .......... .......... 3% 67.4M 12s\n", - " 20800K .......... .......... .......... .......... .......... 3% 51.3M 12s\n", - " 20850K .......... .......... .......... .......... .......... 3% 51.3M 12s\n", - " 20900K .......... .......... .......... .......... .......... 3% 49.9M 12s\n", - " 20950K .......... .......... .......... .......... .......... 3% 61.7M 12s\n", - " 21000K .......... .......... .......... .......... .......... 3% 56.6M 12s\n", - " 21050K .......... .......... .......... .......... .......... 3% 65.3M 12s\n", - " 21100K .......... .......... .......... .......... .......... 3% 61.0M 12s\n", - " 21150K .......... .......... .......... .......... .......... 3% 52.1M 12s\n", - " 21200K .......... .......... .......... .......... .......... 3% 50.1M 12s\n", - " 21250K .......... .......... .......... .......... .......... 3% 71.7M 12s\n", - " 21300K .......... .......... .......... .......... .......... 3% 69.4M 12s\n", - " 21350K .......... .......... .......... .......... .......... 3% 65.1M 12s\n", - " 21400K .......... .......... .......... .......... .......... 3% 43.7M 12s\n", - " 21450K .......... .......... .......... .......... .......... 3% 54.3M 12s\n", - " 21500K .......... .......... .......... .......... .......... 3% 66.5M 12s\n", - " 21550K .......... .......... .......... .......... .......... 3% 72.8M 12s\n", - " 21600K .......... .......... .......... .......... .......... 3% 63.5M 12s\n", - " 21650K .......... .......... .......... .......... .......... 3% 63.6M 12s\n", - " 21700K .......... .......... .......... .......... .......... 3% 47.1M 12s\n", - " 21750K .......... .......... .......... .......... .......... 3% 50.3M 12s\n", - " 21800K .......... .......... .......... .......... .......... 3% 57.4M 12s\n", - " 21850K .......... .......... .......... .......... .......... 3% 67.7M 12s\n", - " 21900K .......... .......... .......... .......... .......... 3% 60.5M 12s\n", - " 21950K .......... .......... .......... .......... .......... 3% 53.6M 12s\n", - " 22000K .......... .......... .......... .......... .......... 3% 43.9M 12s\n", - " 22050K .......... .......... .......... .......... .......... 3% 68.9M 12s\n", - " 22100K .......... .......... .......... .......... .......... 3% 67.8M 12s\n", - " 22150K .......... .......... .......... .......... .......... 3% 72.2M 12s\n", - " 22200K .......... .......... .......... .......... .......... 3% 44.0M 12s\n", - " 22250K .......... .......... .......... .......... .......... 3% 48.3M 12s\n", - " 22300K .......... .......... .......... .......... .......... 3% 57.6M 12s\n", - " 22350K .......... .......... .......... .......... .......... 3% 68.5M 12s\n", - " 22400K .......... .......... .......... .......... .......... 3% 61.1M 12s\n", - " 22450K .......... .......... .......... .......... .......... 3% 58.1M 12s\n", - " 22500K .......... .......... .......... .......... .......... 3% 49.4M 12s\n", - " 22550K .......... .......... .......... .......... .......... 3% 49.7M 12s\n", - " 22600K .......... .......... .......... .......... .......... 3% 57.4M 12s\n", - " 22650K .......... .......... .......... .......... .......... 3% 65.6M 12s\n", - " 22700K .......... .......... .......... .......... .......... 3% 57.1M 12s\n", - " 22750K .......... .......... .......... .......... .......... 3% 45.9M 12s\n", - " 22800K .......... .......... .......... .......... .......... 3% 49.7M 12s\n", - " 22850K .......... .......... .......... .......... .......... 3% 61.1M 12s\n", - " 22900K .......... .......... .......... .......... .......... 3% 63.6M 12s\n", - " 22950K .......... .......... .......... .......... .......... 3% 62.3M 12s\n", - " 23000K .......... .......... .......... .......... .......... 3% 37.1M 12s\n", - " 23050K .......... .......... .......... .......... .......... 3% 55.9M 12s\n", - " 23100K .......... .......... .......... .......... .......... 3% 70.7M 12s\n", - " 23150K .......... .......... .......... .......... .......... 3% 67.4M 12s\n", - " 23200K .......... .......... .......... .......... .......... 3% 65.0M 12s\n", - " 23250K .......... .......... .......... .......... .......... 3% 53.2M 12s\n", - " 23300K .......... .......... .......... .......... .......... 3% 45.6M 12s\n", - " 23350K .......... .......... .......... .......... .......... 3% 69.3M 12s\n", - " 23400K .......... .......... .......... .......... .......... 3% 55.1M 12s\n", - " 23450K .......... .......... .......... .......... .......... 3% 70.0M 12s\n", - " 23500K .......... .......... .......... .......... .......... 3% 49.9M 12s\n", - " 23550K .......... .......... .......... .......... .......... 3% 47.9M 12s\n", - " 23600K .......... .......... .......... .......... .......... 3% 54.7M 12s\n", - " 23650K .......... .......... .......... .......... .......... 3% 65.7M 12s\n", - " 23700K .......... .......... .......... .......... .......... 3% 70.3M 12s\n", - " 23750K .......... .......... .......... .......... .......... 4% 54.8M 12s\n", - " 23800K .......... .......... .......... .......... .......... 4% 34.8M 12s\n", - " 23850K .......... .......... .......... .......... .......... 4% 68.6M 12s\n", - " 23900K .......... .......... .......... .......... .......... 4% 63.0M 12s\n", - " 23950K .......... .......... .......... .......... .......... 4% 67.3M 12s\n", - " 24000K .......... .......... .......... .......... .......... 4% 45.9M 12s\n", - " 24050K .......... .......... .......... .......... .......... 4% 46.8M 12s\n", - " 24100K .......... .......... .......... .......... .......... 4% 60.2M 12s\n", - " 24150K .......... .......... .......... .......... .......... 4% 3.76M 12s\n", - " 24200K .......... .......... .......... .......... .......... 4% 54.9M 12s\n", - " 24250K .......... .......... .......... .......... .......... 4% 60.6M 12s\n", - " 24300K .......... .......... .......... .......... .......... 4% 63.3M 12s\n", - " 24350K .......... .......... .......... .......... .......... 4% 71.8M 12s\n", - " 24400K .......... .......... .......... .......... .......... 4% 58.2M 12s\n", - " 24450K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", - " 24500K .......... .......... .......... .......... .......... 4% 68.2M 12s\n", - " 24550K .......... .......... .......... .......... .......... 4% 4.06M 12s\n", - " 24600K .......... .......... .......... .......... .......... 4% 47.2M 12s\n", - " 24650K .......... .......... .......... .......... .......... 4% 65.1M 12s\n", - " 24700K .......... .......... .......... .......... .......... 4% 64.6M 12s\n", - " 24750K .......... .......... .......... .......... .......... 4% 60.8M 12s\n", - " 24800K .......... .......... .......... .......... .......... 4% 61.2M 12s\n", - " 24850K .......... .......... .......... .......... .......... 4% 56.6M 12s\n", - " 24900K .......... .......... .......... .......... .......... 4% 49.6M 12s\n", - " 24950K .......... .......... .......... .......... .......... 4% 62.5M 12s\n", - " 25000K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", - " 25050K .......... .......... .......... .......... .......... 4% 65.5M 12s\n", - " 25100K .......... .......... .......... .......... .......... 4% 58.5M 12s\n", - " 25150K .......... .......... .......... .......... .......... 4% 56.3M 12s\n", - " 25200K .......... .......... .......... .......... .......... 4% 49.7M 12s\n", - " 25250K .......... .......... .......... .......... .......... 4% 68.8M 12s\n", - " 25300K .......... .......... .......... .......... .......... 4% 64.9M 12s\n", - " 25350K .......... .......... .......... .......... .......... 4% 66.1M 12s\n", - " 25400K .......... .......... .......... .......... .......... 4% 42.8M 12s\n", - " 25450K .......... .......... .......... .......... .......... 4% 59.3M 12s\n", - " 25500K .......... .......... .......... .......... .......... 4% 53.8M 12s\n", - " 25550K .......... .......... .......... .......... .......... 4% 70.8M 12s\n", - " 25600K .......... .......... .......... .......... .......... 4% 62.0M 12s\n", - " 25650K .......... .......... .......... .......... .......... 4% 64.2M 12s\n", - " 25700K .......... .......... .......... .......... .......... 4% 49.6M 12s\n", - " 25750K .......... .......... .......... .......... .......... 4% 46.0M 12s\n", - " 25800K .......... .......... .......... .......... .......... 4% 53.6M 12s\n", - " 25850K .......... .......... .......... .......... .......... 4% 67.7M 12s\n", - " 25900K .......... .......... .......... .......... .......... 4% 70.1M 12s\n", - " 25950K .......... .......... .......... .......... .......... 4% 48.2M 12s\n", - " 26000K .......... .......... .......... .......... .......... 4% 47.7M 12s\n", - " 26050K .......... .......... .......... .......... .......... 4% 66.2M 12s\n", - " 26100K .......... .......... .......... .......... .......... 4% 60.9M 12s\n", - " 26150K .......... .......... .......... .......... .......... 4% 67.1M 12s\n", - " 26200K .......... .......... .......... .......... .......... 4% 39.4M 12s\n", - " 26250K .......... .......... .......... .......... .......... 4% 48.9M 12s\n", - " 26300K .......... .......... .......... .......... .......... 4% 63.7M 12s\n", - " 26350K .......... .......... .......... .......... .......... 4% 62.8M 12s\n", - " 26400K .......... .......... .......... .......... .......... 4% 50.0M 12s\n", - " 26450K .......... .......... .......... .......... .......... 4% 56.1M 12s\n", - " 26500K .......... .......... .......... .......... .......... 4% 50.8M 12s\n", - " 26550K .......... .......... .......... .......... .......... 4% 62.1M 12s\n", - " 26600K .......... .......... .......... .......... .......... 4% 53.8M 12s\n", - " 26650K .......... .......... .......... .......... .......... 4% 51.5M 12s\n", - " 26700K .......... .......... .......... .......... .......... 4% 53.0M 12s\n", - " 26750K .......... .......... .......... .......... .......... 4% 55.4M 12s\n", - " 26800K .......... .......... .......... .......... .......... 4% 64.1M 12s\n", - " 26850K .......... .......... .......... .......... .......... 4% 64.9M 12s\n", - " 26900K .......... .......... .......... .......... .......... 4% 69.4M 12s\n", - " 26950K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", - " 27000K .......... .......... .......... .......... .......... 4% 43.7M 12s\n", - " 27050K .......... .......... .......... .......... .......... 4% 72.0M 12s\n", - " 27100K .......... .......... .......... .......... .......... 4% 73.1M 12s\n", - " 27150K .......... .......... .......... .......... .......... 4% 60.4M 12s\n", - " 27200K .......... .......... .......... .......... .......... 4% 52.9M 12s\n", - " 27250K .......... .......... .......... .......... .......... 4% 50.2M 12s\n", - " 27300K .......... .......... .......... .......... .......... 4% 56.4M 12s\n", - " 27350K .......... .......... .......... .......... .......... 4% 68.1M 12s\n", - " 27400K .......... .......... .......... .......... .......... 4% 61.1M 12s\n", - " 27450K .......... .......... .......... .......... .......... 4% 59.5M 12s\n", - " 27500K .......... .......... .......... .......... .......... 4% 46.5M 12s\n", - " 27550K .......... .......... .......... .......... .......... 4% 52.2M 12s\n", - " 27600K .......... .......... .......... .......... .......... 4% 59.6M 12s\n", - " 27650K .......... .......... .......... .......... .......... 4% 65.5M 12s\n", - " 27700K .......... .......... .......... .......... .......... 4% 64.8M 12s\n", - " 27750K .......... .......... .......... .......... .......... 4% 46.6M 12s\n", - " 27800K .......... .......... .......... .......... .......... 4% 40.7M 12s\n", - " 27850K .......... .......... .......... .......... .......... 4% 63.9M 12s\n", - " 27900K .......... .......... .......... .......... .......... 4% 73.5M 12s\n", - " 27950K .......... .......... .......... .......... .......... 4% 69.8M 12s\n", - " 28000K .......... .......... .......... .......... .......... 4% 44.9M 12s\n", - " 28050K .......... .......... .......... .......... .......... 4% 50.6M 12s\n", - " 28100K .......... .......... .......... .......... .......... 4% 61.0M 12s\n", - " 28150K .......... .......... .......... .......... .......... 4% 70.0M 12s\n", - " 28200K .......... .......... .......... .......... .......... 4% 58.9M 12s\n", - " 28250K .......... .......... .......... .......... .......... 4% 49.9M 12s\n", - " 28300K .......... .......... .......... .......... .......... 4% 52.4M 12s\n", - " 28350K .......... .......... .......... .......... .......... 4% 52.0M 12s\n", - " 28400K .......... .......... .......... .......... .......... 4% 55.5M 12s\n", - " 28450K .......... .......... .......... .......... .......... 4% 59.4M 12s\n", - " 28500K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", - " 28550K .......... .......... .......... .......... .......... 4% 56.0M 12s\n", - " 28600K .......... .......... .......... .......... .......... 4% 43.3M 12s\n", - " 28650K .......... .......... .......... .......... .......... 4% 64.3M 12s\n", - " 28700K .......... .......... .......... .......... .......... 4% 65.8M 12s\n", - " 28750K .......... .......... .......... .......... .......... 4% 61.0M 12s\n", - " 28800K .......... .......... .......... .......... .......... 4% 48.1M 12s\n", - " 28850K .......... .......... .......... .......... .......... 4% 50.9M 12s\n", - " 28900K .......... .......... .......... .......... .......... 4% 66.8M 12s\n", - " 28950K .......... .......... .......... .......... .......... 4% 74.3M 12s\n", - " 29000K .......... .......... .......... .......... .......... 4% 55.5M 12s\n", - " 29050K .......... .......... .......... .......... .......... 4% 56.1M 12s\n", - " 29100K .......... .......... .......... .......... .......... 4% 49.3M 12s\n", - " 29150K .......... .......... .......... .......... .......... 4% 62.8M 12s\n", - " 29200K .......... .......... .......... .......... .......... 4% 55.1M 12s\n", - " 29250K .......... .......... .......... .......... .......... 4% 71.1M 12s\n", - " 29300K .......... .......... .......... .......... .......... 4% 58.0M 12s\n", - " 29350K .......... .......... .......... .......... .......... 4% 50.5M 12s\n", - " 29400K .......... .......... .......... .......... .......... 4% 41.0M 12s\n", - " 29450K .......... .......... .......... .......... .......... 4% 64.0M 12s\n", - " 29500K .......... .......... .......... .......... .......... 4% 59.2M 12s\n", - " 29550K .......... .......... .......... .......... .......... 4% 56.9M 12s\n", - " 29600K .......... .......... .......... .......... .......... 4% 47.7M 12s\n", - " 29650K .......... .......... .......... .......... .......... 4% 53.1M 12s\n", - " 29700K .......... .......... .......... .......... .......... 5% 65.3M 12s\n", - " 29750K .......... .......... .......... .......... .......... 5% 72.3M 12s\n", - " 29800K .......... .......... .......... .......... .......... 5% 50.6M 12s\n", - " 29850K .......... .......... .......... .......... .......... 5% 48.0M 12s\n", - " 29900K .......... .......... .......... .......... .......... 5% 50.2M 12s\n", - " 29950K .......... .......... .......... .......... .......... 5% 67.2M 12s\n", - " 30000K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", - " 30050K .......... .......... .......... .......... .......... 5% 70.7M 12s\n", - " 30100K .......... .......... .......... .......... .......... 5% 47.6M 12s\n", - " 30150K .......... .......... .......... .......... .......... 5% 49.0M 12s\n", - " 30200K .......... .......... .......... .......... .......... 5% 51.2M 12s\n", - " 30250K .......... .......... .......... .......... .......... 5% 65.0M 12s\n", - " 30300K .......... .......... .......... .......... .......... 5% 48.0M 12s\n", - " 30350K .......... .......... .......... .......... .......... 5% 53.9M 12s\n", - " 30400K .......... .......... .......... .......... .......... 5% 42.2M 12s\n", - " 30450K .......... .......... .......... .......... .......... 5% 63.1M 12s\n", - " 30500K .......... .......... .......... .......... .......... 5% 65.8M 12s\n", - " 30550K .......... .......... .......... .......... .......... 5% 58.3M 12s\n", - " 30600K .......... .......... .......... .......... .......... 5% 41.9M 12s\n", - " 30650K .......... .......... .......... .......... .......... 5% 44.9M 12s\n", - " 30700K .......... .......... .......... .......... .......... 5% 60.2M 12s\n", - " 30750K .......... .......... .......... .......... .......... 5% 69.3M 12s\n", - " 30800K .......... .......... .......... .......... .......... 5% 45.9M 12s\n", - " 30850K .......... .......... .......... .......... .......... 5% 58.1M 12s\n", - " 30900K .......... .......... .......... .......... .......... 5% 54.6M 12s\n", - " 30950K .......... .......... .......... .......... .......... 5% 69.1M 12s\n", - " 31000K .......... .......... .......... .......... .......... 5% 55.6M 12s\n", - " 31050K .......... .......... .......... .......... .......... 5% 59.1M 12s\n", - " 31100K .......... .......... .......... .......... .......... 5% 42.9M 12s\n", - " 31150K .......... .......... .......... .......... .......... 5% 56.7M 12s\n", - " 31200K .......... .......... .......... .......... .......... 5% 58.9M 12s\n", - " 31250K .......... .......... .......... .......... .......... 5% 66.2M 12s\n", - " 31300K .......... .......... .......... .......... .......... 5% 71.0M 12s\n", - " 31350K .......... .......... .......... .......... .......... 5% 56.4M 12s\n", - " 31400K .......... .......... .......... .......... .......... 5% 39.6M 12s\n", - " 31450K .......... .......... .......... .......... .......... 5% 54.4M 12s\n", - " 31500K .......... .......... .......... .......... .......... 5% 68.6M 12s\n", - " 31550K .......... .......... .......... .......... .......... 5% 72.5M 12s\n", - " 31600K .......... .......... .......... .......... .......... 5% 50.4M 12s\n", - " 31650K .......... .......... .......... .......... .......... 5% 49.3M 12s\n", - " 31700K .......... .......... .......... .......... .......... 5% 52.5M 12s\n", - " 31750K .......... .......... .......... .......... .......... 5% 61.8M 12s\n", - " 31800K .......... .......... .......... .......... .......... 5% 54.1M 12s\n", - " 31850K .......... .......... .......... .......... .......... 5% 48.6M 12s\n", - " 31900K .......... .......... .......... .......... .......... 5% 50.8M 12s\n", - " 31950K .......... .......... .......... .......... .......... 5% 59.5M 12s\n", - " 32000K .......... .......... .......... .......... .......... 5% 60.8M 12s\n", - " 32050K .......... .......... .......... .......... .......... 5% 68.4M 12s\n", - " 32100K .......... .......... .......... .......... .......... 5% 61.7M 12s\n", - " 32150K .......... .......... .......... .......... .......... 5% 48.7M 12s\n", - " 32200K .......... .......... .......... .......... .......... 5% 52.0M 12s\n", - " 32250K .......... .......... .......... .......... .......... 5% 69.0M 12s\n", - " 32300K .......... .......... .......... .......... .......... 5% 70.1M 12s\n", - " 32350K .......... .......... .......... .......... .......... 5% 71.0M 12s\n", - " 32400K .......... .......... .......... .......... .......... 5% 50.0M 12s\n", - " 32450K .......... .......... .......... .......... .......... 5% 45.7M 12s\n", - " 32500K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", - " 32550K .......... .......... .......... .......... .......... 5% 72.9M 12s\n", - " 32600K .......... .......... .......... .......... .......... 5% 46.5M 12s\n", - " 32650K .......... .......... .......... .......... .......... 5% 43.0M 12s\n", - " 32700K .......... .......... .......... .......... .......... 5% 53.0M 12s\n", - " 32750K .......... .......... .......... .......... .......... 5% 61.6M 12s\n", - " 32800K .......... .......... .......... .......... .......... 5% 59.0M 12s\n", - " 32850K .......... .......... .......... .......... .......... 5% 59.5M 12s\n", - " 32900K .......... .......... .......... .......... .......... 5% 56.5M 12s\n", - " 32950K .......... .......... .......... .......... .......... 5% 55.9M 12s\n", - " 33000K .......... .......... .......... .......... .......... 5% 49.9M 12s\n", - " 33050K .......... .......... .......... .......... .......... 5% 70.7M 12s\n", - " 33100K .......... .......... .......... .......... .......... 5% 62.5M 11s\n", - " 33150K .......... .......... .......... .......... .......... 5% 51.1M 11s\n", - " 33200K .......... .......... .......... .......... .......... 5% 43.1M 11s\n", - " 33250K .......... .......... .......... .......... .......... 5% 70.9M 11s\n", - " 33300K .......... .......... .......... .......... .......... 5% 69.8M 11s\n", - " 33350K .......... .......... .......... .......... .......... 5% 71.0M 11s\n", - " 33400K .......... .......... .......... .......... .......... 5% 50.6M 11s\n", - " 33450K .......... .......... .......... .......... .......... 5% 52.5M 11s\n", - " 33500K .......... .......... .......... .......... .......... 5% 52.4M 11s\n", - " 33550K .......... .......... .......... .......... .......... 5% 69.0M 11s\n", - " 33600K .......... .......... .......... .......... .......... 5% 60.1M 11s\n", - " 33650K .......... .......... .......... .......... .......... 5% 70.2M 11s\n", - " 33700K .......... .......... .......... .......... .......... 5% 49.1M 11s\n", - " 33750K .......... .......... .......... .......... .......... 5% 52.4M 11s\n", - " 33800K .......... .......... .......... .......... .......... 5% 52.5M 11s\n", - " 33850K .......... .......... .......... .......... .......... 5% 69.1M 11s\n", - " 33900K .......... .......... .......... .......... .......... 5% 67.1M 11s\n", - " 33950K .......... .......... .......... .......... .......... 5% 65.9M 11s\n", - " 34000K .......... .......... .......... .......... .......... 5% 45.8M 11s\n", - " 34050K .......... .......... .......... .......... .......... 5% 49.7M 11s\n", - " 34100K .......... .......... .......... .......... .......... 5% 65.3M 11s\n", - " 34150K .......... .......... .......... .......... .......... 5% 67.7M 11s\n", - " 34200K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", - " 34250K .......... .......... .......... .......... .......... 5% 55.7M 11s\n", - " 34300K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", - " 34350K .......... .......... .......... .......... .......... 5% 75.0M 11s\n", - " 34400K .......... .......... .......... .......... .......... 5% 53.5M 11s\n", - " 34450K .......... .......... .......... .......... .......... 5% 53.2M 11s\n", - " 34500K .......... .......... .......... .......... .......... 5% 47.9M 11s\n", - " 34550K .......... .......... .......... .......... .......... 5% 52.3M 11s\n", - " 34600K .......... .......... .......... .......... .......... 5% 54.5M 11s\n", - " 34650K .......... .......... .......... .......... .......... 5% 64.8M 11s\n", - " 34700K .......... .......... .......... .......... .......... 5% 57.6M 11s\n", - " 34750K .......... .......... .......... .......... .......... 5% 46.2M 11s\n", - " 34800K .......... .......... .......... .......... .......... 5% 44.7M 11s\n", - " 34850K .......... .......... .......... .......... .......... 5% 67.1M 11s\n", - " 34900K .......... .......... .......... .......... .......... 5% 71.5M 11s\n", - " 34950K .......... .......... .......... .......... .......... 5% 67.4M 11s\n", - " 35000K .......... .......... .......... .......... .......... 5% 41.8M 11s\n", - " 35050K .......... .......... .......... .......... .......... 5% 51.9M 11s\n", - " 35100K .......... .......... .......... .......... .......... 5% 70.4M 11s\n", - " 35150K .......... .......... .......... .......... .......... 5% 65.2M 11s\n", - " 35200K .......... .......... .......... .......... .......... 5% 52.7M 11s\n", - " 35250K .......... .......... .......... .......... .......... 5% 48.0M 11s\n", - " 35300K .......... .......... .......... .......... .......... 5% 52.1M 11s\n", - " 35350K .......... .......... .......... .......... .......... 5% 60.6M 11s\n", - " 35400K .......... .......... .......... .......... .......... 5% 55.8M 11s\n", - " 35450K .......... .......... .......... .......... .......... 5% 55.2M 11s\n", - " 35500K .......... .......... .......... .......... .......... 5% 49.6M 11s\n", - " 35550K .......... .......... .......... .......... .......... 5% 47.6M 11s\n", - " 35600K .......... .......... .......... .......... .......... 5% 58.0M 11s\n", - " 35650K .......... .......... .......... .......... .......... 6% 63.4M 11s\n", - " 35700K .......... .......... .......... .......... .......... 6% 63.0M 11s\n", - " 35750K .......... .......... .......... .......... .......... 6% 45.0M 11s\n", - " 35800K .......... .......... .......... .......... .......... 6% 45.7M 11s\n", - " 35850K .......... .......... .......... .......... .......... 6% 71.6M 11s\n", - " 35900K .......... .......... .......... .......... .......... 6% 70.1M 11s\n", - " 35950K .......... .......... .......... .......... .......... 6% 67.5M 11s\n", - " 36000K .......... .......... .......... .......... .......... 6% 49.0M 11s\n", - " 36050K .......... .......... .......... .......... .......... 6% 44.9M 11s\n", - " 36100K .......... .......... .......... .......... .......... 6% 63.3M 11s\n", - " 36150K .......... .......... .......... .......... .......... 6% 71.3M 11s\n", - " 36200K .......... .......... .......... .......... .......... 6% 57.5M 11s\n", - " 36250K .......... .......... .......... .......... .......... 6% 52.4M 11s\n", - " 36300K .......... .......... .......... .......... .......... 6% 38.1M 11s\n", - " 36350K .......... .......... .......... .......... .......... 6% 57.4M 11s\n", - " 36400K .......... .......... .......... .......... .......... 6% 55.1M 11s\n", - " 36450K .......... .......... .......... .......... .......... 6% 64.3M 11s\n", - " 36500K .......... .......... .......... .......... .......... 6% 44.2M 11s\n", - " 36550K .......... .......... .......... .......... .......... 6% 47.9M 11s\n", - " 36600K .......... .......... .......... .......... .......... 6% 45.2M 11s\n", - " 36650K .......... .......... .......... .......... .......... 6% 60.4M 11s\n", - " 36700K .......... .......... .......... .......... .......... 6% 52.1M 11s\n", - " 36750K .......... .......... .......... .......... .......... 6% 45.1M 11s\n", - " 36800K .......... .......... .......... .......... .......... 6% 49.7M 11s\n", - " 36850K .......... .......... .......... .......... .......... 6% 65.5M 11s\n", - " 36900K .......... .......... .......... .......... .......... 6% 62.9M 11s\n", - " 36950K .......... .......... .......... .......... .......... 6% 57.6M 11s\n", - " 37000K .......... .......... .......... .......... .......... 6% 33.7M 11s\n", - " 37050K .......... .......... .......... .......... .......... 6% 57.7M 11s\n", - " 37100K .......... .......... .......... .......... .......... 6% 61.4M 11s\n", - " 37150K .......... .......... .......... .......... .......... 6% 64.7M 11s\n", - " 37200K .......... .......... .......... .......... .......... 6% 46.0M 11s\n", - " 37250K .......... .......... .......... .......... .......... 6% 54.8M 11s\n", - " 37300K .......... .......... .......... .......... .......... 6% 69.1M 11s\n", - " 37350K .......... .......... .......... .......... .......... 6% 63.3M 11s\n", - " 37400K .......... .......... .......... .......... .......... 6% 52.8M 11s\n", - " 37450K .......... .......... .......... .......... .......... 6% 64.6M 11s\n", - " 37500K .......... .......... .......... .......... .......... 6% 63.8M 11s\n", - " 37550K .......... .......... .......... .......... .......... 6% 59.4M 11s\n", - " 37600K .......... .......... .......... .......... .......... 6% 59.4M 11s\n", - " 37650K .......... .......... .......... .......... .......... 6% 65.8M 11s\n", - " 37700K .......... .......... .......... .......... .......... 6% 56.6M 11s\n", - " 37750K .......... .......... .......... .......... .......... 6% 3.75M 11s\n", - " 37800K .......... .......... .......... .......... .......... 6% 32.9M 11s\n", - " 37850K .......... .......... .......... .......... .......... 6% 62.1M 11s\n", - " 37900K .......... .......... .......... .......... .......... 6% 58.9M 11s\n", - " 37950K .......... .......... .......... .......... .......... 6% 54.4M 11s\n", - " 38000K .......... .......... .......... .......... .......... 6% 48.5M 11s\n", - " 38050K .......... .......... .......... .......... .......... 6% 46.1M 11s\n", - " 38100K .......... .......... .......... .......... .......... 6% 53.1M 11s\n", - " 38150K .......... .......... .......... .......... .......... 6% 43.3M 11s\n", - " 38200K .......... .......... .......... .......... .......... 6% 44.3M 11s\n", - " 38250K .......... .......... .......... .......... .......... 6% 59.0M 11s\n", - " 38300K .......... .......... .......... .......... .......... 6% 49.7M 11s\n", - " 38350K .......... .......... .......... .......... .......... 6% 42.6M 11s\n", - " 38400K .......... .......... .......... .......... .......... 6% 48.4M 11s\n", - " 38450K .......... .......... .......... .......... .......... 6% 60.2M 11s\n", - " 38500K .......... .......... .......... .......... .......... 6% 59.0M 11s\n", - " 38550K .......... .......... .......... .......... .......... 6% 55.5M 11s\n", - " 38600K .......... .......... .......... .......... .......... 6% 39.9M 11s\n", - " 38650K .......... .......... .......... .......... .......... 6% 56.1M 11s\n", - " 38700K .......... .......... .......... .......... .......... 6% 56.9M 11s\n", - " 38750K .......... .......... .......... .......... .......... 6% 50.4M 11s\n", - " 38800K .......... .......... .......... .......... .......... 6% 48.9M 11s\n", - " 38850K .......... .......... .......... .......... .......... 6% 2.73M 12s\n", - " 38900K .......... .......... .......... .......... .......... 6% 62.4M 12s\n", - " 38950K .......... .......... .......... .......... .......... 6% 42.6M 12s\n", - " 39000K .......... .......... .......... .......... .......... 6% 41.4M 12s\n", - " 39050K .......... .......... .......... .......... .......... 6% 60.7M 12s\n", - " 39100K .......... .......... .......... .......... .......... 6% 64.6M 12s\n", - " 39150K .......... .......... .......... .......... .......... 6% 46.8M 12s\n", - " 39200K .......... .......... .......... .......... .......... 6% 32.1M 12s\n", - " 39250K .......... .......... .......... .......... .......... 6% 32.6M 12s\n", - " 39300K .......... .......... .......... .......... .......... 6% 40.5M 12s\n", - " 39350K .......... .......... .......... .......... .......... 6% 46.0M 12s\n", - " 39400K .......... .......... .......... .......... .......... 6% 51.6M 12s\n", - " 39450K .......... .......... .......... .......... .......... 6% 45.2M 12s\n", - " 39500K .......... .......... .......... .......... .......... 6% 52.5M 12s\n", - " 39550K .......... .......... .......... .......... .......... 6% 54.5M 12s\n", - " 39600K .......... .......... .......... .......... .......... 6% 56.3M 12s\n", - " 39650K .......... .......... .......... .......... .......... 6% 56.9M 12s\n", - " 39700K .......... .......... .......... .......... .......... 6% 50.5M 12s\n", - " 39750K .......... .......... .......... .......... .......... 6% 56.0M 12s\n", - " 39800K .......... .......... .......... .......... .......... 6% 38.8M 12s\n", - " 39850K .......... .......... .......... .......... .......... 6% 38.2M 12s\n", - " 39900K .......... .......... .......... .......... .......... 6% 3.58M 12s\n", - " 39950K .......... .......... .......... .......... .......... 6% 42.2M 12s\n", - " 40000K .......... .......... .......... .......... .......... 6% 44.5M 12s\n", - " 40050K .......... .......... .......... .......... .......... 6% 47.0M 12s\n", - " 40100K .......... .......... .......... .......... .......... 6% 43.1M 12s\n", - " 40150K .......... .......... .......... .......... .......... 6% 51.1M 12s\n", - " 40200K .......... .......... .......... .......... .......... 6% 41.0M 12s\n", - " 40250K .......... .......... .......... .......... .......... 6% 36.0M 12s\n", - " 40300K .......... .......... .......... .......... .......... 6% 35.9M 12s\n", - " 40350K .......... .......... .......... .......... .......... 6% 36.2M 12s\n", - " 40400K .......... .......... .......... .......... .......... 6% 46.5M 12s\n", - " 40450K .......... .......... .......... .......... .......... 6% 51.6M 12s\n", - " 40500K .......... .......... .......... .......... .......... 6% 39.8M 12s\n", - " 40550K .......... .......... .......... .......... .......... 6% 60.1M 12s\n", - " 40600K .......... .......... .......... .......... .......... 6% 44.5M 12s\n", - " 40650K .......... .......... .......... .......... .......... 6% 51.0M 12s\n", - " 40700K .......... .......... .......... .......... .......... 6% 14.8M 12s\n", - " 40750K .......... .......... .......... .......... .......... 6% 56.0M 12s\n", - " 40800K .......... .......... .......... .......... .......... 6% 48.6M 12s\n", - " 40850K .......... .......... .......... .......... .......... 6% 45.1M 12s\n", - " 40900K .......... .......... .......... .......... .......... 6% 61.5M 12s\n", - " 40950K .......... .......... .......... .......... .......... 6% 43.5M 12s\n", - " 41000K .......... .......... .......... .......... .......... 6% 49.4M 12s\n", - " 41050K .......... .......... .......... .......... .......... 6% 41.9M 12s\n", - " 41100K .......... .......... .......... .......... .......... 6% 46.7M 12s\n", - " 41150K .......... .......... .......... .......... .......... 6% 53.0M 12s\n", - " 41200K .......... .......... .......... .......... .......... 6% 46.4M 12s\n", - " 41250K .......... .......... .......... .......... .......... 6% 47.8M 12s\n", - " 41300K .......... .......... .......... .......... .......... 6% 57.4M 12s\n", - " 41350K .......... .......... .......... .......... .......... 6% 63.5M 12s\n", - " 41400K .......... .......... .......... .......... .......... 6% 39.1M 12s\n", - " 41450K .......... .......... .......... .......... .......... 6% 20.5M 12s\n", - " 41500K .......... .......... .......... .......... .......... 6% 59.5M 12s\n", - " 41550K .......... .......... .......... .......... .......... 6% 31.9M 12s\n", - " 41600K .......... .......... .......... .......... .......... 7% 36.9M 12s\n", - " 41650K .......... .......... .......... .......... .......... 7% 58.4M 12s\n", - " 41700K .......... .......... .......... .......... .......... 7% 64.5M 12s\n", - " 41750K .......... .......... .......... .......... .......... 7% 30.1M 12s\n", - " 41800K .......... .......... .......... .......... .......... 7% 38.7M 12s\n", - " 41850K .......... .......... .......... .......... .......... 7% 57.3M 12s\n", - " 41900K .......... .......... .......... .......... .......... 7% 4.19M 12s\n", - " 41950K .......... .......... .......... .......... .......... 7% 55.8M 12s\n", - " 42000K .......... .......... .......... .......... .......... 7% 51.8M 12s\n", - " 42050K .......... .......... .......... .......... .......... 7% 57.3M 12s\n", - " 42100K .......... .......... .......... .......... .......... 7% 38.6M 12s\n", - " 42150K .......... .......... .......... .......... .......... 7% 60.9M 12s\n", - " 42200K .......... .......... .......... .......... .......... 7% 53.5M 12s\n", - " 42250K .......... .......... .......... .......... .......... 7% 63.4M 12s\n", - " 42300K .......... .......... .......... .......... .......... 7% 45.0M 12s\n", - " 42350K .......... .......... .......... .......... .......... 7% 31.0M 12s\n", - " 42400K .......... .......... .......... .......... .......... 7% 57.7M 12s\n", - " 42450K .......... .......... .......... .......... .......... 7% 67.4M 12s\n", - " 42500K .......... .......... .......... .......... .......... 7% 33.8M 12s\n", - " 42550K .......... .......... .......... .......... .......... 7% 32.5M 12s\n", - " 42600K .......... .......... .......... .......... .......... 7% 38.2M 12s\n", - " 42650K .......... .......... .......... .......... .......... 7% 26.8M 12s\n", - " 42700K .......... .......... .......... .......... .......... 7% 18.5M 12s\n", - " 42750K .......... .......... .......... .......... .......... 7% 23.4M 12s\n", - " 42800K .......... .......... .......... .......... .......... 7% 19.5M 12s\n", - " 42850K .......... .......... .......... .......... .......... 7% 25.4M 12s\n", - " 42900K .......... .......... .......... .......... .......... 7% 28.5M 12s\n", - " 42950K .......... .......... .......... .......... .......... 7% 25.0M 12s\n", - " 43000K .......... .......... .......... .......... .......... 7% 22.0M 12s\n", - " 43050K .......... .......... .......... .......... .......... 7% 4.34M 12s\n", - " 43100K .......... .......... .......... .......... .......... 7% 64.3M 12s\n", - " 43150K .......... .......... .......... .......... .......... 7% 58.2M 12s\n", - " 43200K .......... .......... .......... .......... .......... 7% 60.1M 12s\n", - " 43250K .......... .......... .......... .......... .......... 7% 51.9M 12s\n", - " 43300K .......... .......... .......... .......... .......... 7% 64.0M 12s\n", - " 43350K .......... .......... .......... .......... .......... 7% 67.0M 12s\n", - " 43400K .......... .......... .......... .......... .......... 7% 34.0M 12s\n", - " 43450K .......... .......... .......... .......... .......... 7% 59.3M 12s\n", - " 43500K .......... .......... .......... .......... .......... 7% 58.7M 12s\n", - " 43550K .......... .......... .......... .......... .......... 7% 33.0M 12s\n", - " 43600K .......... .......... .......... .......... .......... 7% 32.7M 12s\n", - " 43650K .......... .......... .......... .......... .......... 7% 62.7M 12s\n", - " 43700K .......... .......... .......... .......... .......... 7% 63.0M 12s\n", - " 43750K .......... .......... .......... .......... .......... 7% 33.2M 12s\n", - " 43800K .......... .......... .......... .......... .......... 7% 32.6M 12s\n", - " 43850K .......... .......... .......... .......... .......... 7% 56.5M 12s\n", - " 43900K .......... .......... .......... .......... .......... 7% 49.1M 12s\n", - " 43950K .......... .......... .......... .......... .......... 7% 20.5M 12s\n", - " 44000K .......... .......... .......... .......... .......... 7% 21.0M 12s\n", - " 44050K .......... .......... .......... .......... .......... 7% 18.0M 12s\n", - " 44100K .......... .......... .......... .......... .......... 7% 25.3M 12s\n", - " 44150K .......... .......... .......... .......... .......... 7% 19.6M 12s\n", - " 44200K .......... .......... .......... .......... .......... 7% 26.3M 12s\n", - " 44250K .......... .......... .......... .......... .......... 7% 28.4M 12s\n", - " 44300K .......... .......... .......... .......... .......... 7% 24.9M 12s\n", - " 44350K .......... .......... .......... .......... .......... 7% 27.3M 12s\n", - " 44400K .......... .......... .......... .......... .......... 7% 25.8M 12s\n", - " 44450K .......... .......... .......... .......... .......... 7% 42.4M 12s\n", - " 44500K .......... .......... .......... .......... .......... 7% 50.4M 12s\n", - " 44550K .......... .......... .......... .......... .......... 7% 65.8M 12s\n", - " 44600K .......... .......... .......... .......... .......... 7% 64.4M 12s\n", - " 44650K .......... .......... .......... .......... .......... 7% 69.7M 12s\n", - " 44700K .......... .......... .......... .......... .......... 7% 75.7M 12s\n", - " 44750K .......... .......... .......... .......... .......... 7% 72.4M 12s\n", - " 44800K .......... .......... .......... .......... .......... 7% 68.3M 12s\n", - " 44850K .......... .......... .......... .......... .......... 7% 63.6M 12s\n", - " 44900K .......... .......... .......... .......... .......... 7% 69.9M 12s\n", - " 44950K .......... .......... .......... .......... .......... 7% 55.4M 12s\n", - " 45000K .......... .......... .......... .......... .......... 7% 55.7M 12s\n", - " 45050K .......... .......... .......... .......... .......... 7% 58.7M 12s\n", - " 45100K .......... .......... .......... .......... .......... 7% 63.3M 12s\n", - " 45150K .......... .......... .......... .......... .......... 7% 55.1M 12s\n", - " 45200K .......... .......... .......... .......... .......... 7% 46.7M 12s\n", - " 45250K .......... .......... .......... .......... .......... 7% 68.4M 12s\n", - " 45300K .......... .......... .......... .......... .......... 7% 55.7M 12s\n", - " 45350K .......... .......... .......... .......... .......... 7% 60.5M 12s\n", - " 45400K .......... .......... .......... .......... .......... 7% 48.7M 12s\n", - " 45450K .......... .......... .......... .......... .......... 7% 66.4M 12s\n", - " 45500K .......... .......... .......... .......... .......... 7% 63.8M 12s\n", - " 45550K .......... .......... .......... .......... .......... 7% 65.9M 12s\n", - " 45600K .......... .......... .......... .......... .......... 7% 55.8M 12s\n", - " 45650K .......... .......... .......... .......... .......... 7% 63.5M 12s\n", - " 45700K .......... .......... .......... .......... .......... 7% 53.2M 12s\n", - " 45750K .......... .......... .......... .......... .......... 7% 51.1M 12s\n", - " 45800K .......... .......... .......... .......... .......... 7% 29.2M 12s\n", - " 45850K .......... .......... .......... .......... .......... 7% 35.6M 12s\n", - " 45900K .......... .......... .......... .......... .......... 7% 16.4M 12s\n", - " 45950K .......... .......... .......... .......... .......... 7% 35.2M 12s\n", - " 46000K .......... .......... .......... .......... .......... 7% 33.1M 12s\n", - " 46050K .......... .......... .......... .......... .......... 7% 18.1M 12s\n", - " 46100K .......... .......... .......... .......... .......... 7% 35.2M 12s\n", - " 46150K .......... .......... .......... .......... .......... 7% 19.5M 12s\n", - " 46200K .......... .......... .......... .......... .......... 7% 25.2M 12s\n", - " 46250K .......... .......... .......... .......... .......... 7% 37.9M 12s\n", - " 46300K .......... .......... .......... .......... .......... 7% 38.3M 12s\n", - " 46350K .......... .......... .......... .......... .......... 7% 39.2M 12s\n", - " 46400K .......... .......... .......... .......... .......... 7% 62.5M 12s\n", - " 46450K .......... .......... .......... .......... .......... 7% 46.2M 12s\n", - " 46500K .......... .......... .......... .......... .......... 7% 36.5M 12s\n", - " 46550K .......... .......... .......... .......... .......... 7% 32.5M 12s\n", - " 46600K .......... .......... .......... .......... .......... 7% 39.4M 12s\n", - " 46650K .......... .......... .......... .......... .......... 7% 47.6M 12s\n", - " 46700K .......... .......... .......... .......... .......... 7% 30.4M 12s\n", - " 46750K .......... .......... .......... .......... .......... 7% 45.9M 12s\n", - " 46800K .......... .......... .......... .......... .......... 7% 42.1M 12s\n", - " 46850K .......... .......... .......... .......... .......... 7% 57.4M 12s\n", - " 46900K .......... .......... .......... .......... .......... 7% 40.8M 12s\n", - " 46950K .......... .......... .......... .......... .......... 7% 39.6M 12s\n", - " 47000K .......... .......... .......... .......... .......... 7% 42.7M 12s\n", - " 47050K .......... .......... .......... .......... .......... 7% 54.6M 12s\n", - " 47100K .......... .......... .......... .......... .......... 7% 18.5M 12s\n", - " 47150K .......... .......... .......... .......... .......... 7% 18.0M 12s\n", - " 47200K .......... .......... .......... .......... .......... 7% 18.6M 12s\n", - " 47250K .......... .......... .......... .......... .......... 7% 17.5M 12s\n", - " 47300K .......... .......... .......... .......... .......... 7% 21.9M 12s\n", - " 47350K .......... .......... .......... .......... .......... 7% 27.6M 12s\n", - " 47400K .......... .......... .......... .......... .......... 7% 16.0M 12s\n", - " 47450K .......... .......... .......... .......... .......... 7% 22.2M 12s\n", - " 47500K .......... .......... .......... .......... .......... 7% 38.5M 12s\n", - " 47550K .......... .......... .......... .......... .......... 8% 43.0M 12s\n", - " 47600K .......... .......... .......... .......... .......... 8% 38.5M 12s\n", - " 47650K .......... .......... .......... .......... .......... 8% 39.4M 12s\n", - " 47700K .......... .......... .......... .......... .......... 8% 47.0M 12s\n", - " 47750K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", - " 47800K .......... .......... .......... .......... .......... 8% 29.7M 12s\n", - " 47850K .......... .......... .......... .......... .......... 8% 36.2M 12s\n", - " 47900K .......... .......... .......... .......... .......... 8% 38.7M 12s\n", - " 47950K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", - " 48000K .......... .......... .......... .......... .......... 8% 27.3M 12s\n", - " 48050K .......... .......... .......... .......... .......... 8% 63.5M 12s\n", - " 48100K .......... .......... .......... .......... .......... 8% 27.5M 12s\n", - " 48150K .......... .......... .......... .......... .......... 8% 30.1M 12s\n", - " 48200K .......... .......... .......... .......... .......... 8% 42.9M 12s\n", - " 48250K .......... .......... .......... .......... .......... 8% 30.4M 12s\n", - " 48300K .......... .......... .......... .......... .......... 8% 22.6M 12s\n", - " 48350K .......... .......... .......... .......... .......... 8% 20.2M 12s\n", - " 48400K .......... .......... .......... .......... .......... 8% 20.4M 12s\n", - " 48450K .......... .......... .......... .......... .......... 8% 22.0M 12s\n", - " 48500K .......... .......... .......... .......... .......... 8% 26.1M 12s\n", - " 48550K .......... .......... .......... .......... .......... 8% 24.4M 12s\n", - " 48600K .......... .......... .......... .......... .......... 8% 20.8M 12s\n", - " 48650K .......... .......... .......... .......... .......... 8% 22.7M 12s\n", - " 48700K .......... .......... .......... .......... .......... 8% 30.8M 12s\n", - " 48750K .......... .......... .......... .......... .......... 8% 3.96M 12s\n", - " 48800K .......... .......... .......... .......... .......... 8% 55.5M 12s\n", - " 48850K .......... .......... .......... .......... .......... 8% 60.3M 12s\n", - " 48900K .......... .......... .......... .......... .......... 8% 62.9M 12s\n", - " 48950K .......... .......... .......... .......... .......... 8% 29.6M 12s\n", - " 49000K .......... .......... .......... .......... .......... 8% 49.5M 12s\n", - " 49050K .......... .......... .......... .......... .......... 8% 64.6M 12s\n", - " 49100K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", - " 49150K .......... .......... .......... .......... .......... 8% 36.7M 12s\n", - " 49200K .......... .......... .......... .......... .......... 8% 33.0M 12s\n", - " 49250K .......... .......... .......... .......... .......... 8% 62.7M 12s\n", - " 49300K .......... .......... .......... .......... .......... 8% 54.9M 12s\n", - " 49350K .......... .......... .......... .......... .......... 8% 16.7M 12s\n", - " 49400K .......... .......... .......... .......... .......... 8% 27.1M 12s\n", - " 49450K .......... .......... .......... .......... .......... 8% 20.0M 12s\n", - " 49500K .......... .......... .......... .......... .......... 8% 61.6M 12s\n", - " 49550K .......... .......... .......... .......... .......... 8% 64.1M 12s\n", - " 49600K .......... .......... .......... .......... .......... 8% 55.4M 12s\n", - " 49650K .......... .......... .......... .......... .......... 8% 32.6M 12s\n", - " 49700K .......... .......... .......... .......... .......... 8% 49.3M 12s\n", - " 49750K .......... .......... .......... .......... .......... 8% 66.1M 12s\n", - " 49800K .......... .......... .......... .......... .......... 8% 54.8M 12s\n", - " 49850K .......... .......... .......... .......... .......... 8% 48.6M 12s\n", - " 49900K .......... .......... .......... .......... .......... 8% 33.3M 12s\n", - " 49950K .......... .......... .......... .......... .......... 8% 61.1M 12s\n", - " 50000K .......... .......... .......... .......... .......... 8% 52.5M 12s\n", - " 50050K .......... .......... .......... .......... .......... 8% 67.7M 12s\n", - " 50100K .......... .......... .......... .......... .......... 8% 32.5M 12s\n", - " 50150K .......... .......... .......... .......... .......... 8% 46.4M 12s\n", - " 50200K .......... .......... .......... .......... .......... 8% 53.5M 12s\n", - " 50250K .......... .......... .......... .......... .......... 8% 64.5M 12s\n", - " 50300K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", - " 50350K .......... .......... .......... .......... .......... 8% 26.6M 12s\n", - " 50400K .......... .......... .......... .......... .......... 8% 60.9M 12s\n", - " 50450K .......... .......... .......... .......... .......... 8% 59.8M 12s\n", - " 50500K .......... .......... .......... .......... .......... 8% 51.0M 12s\n", - " 50550K .......... .......... .......... .......... .......... 8% 38.1M 12s\n", - " 50600K .......... .......... .......... .......... .......... 8% 34.1M 12s\n", - " 50650K .......... .......... .......... .......... .......... 8% 66.4M 12s\n", - " 50700K .......... .......... .......... .......... .......... 8% 61.7M 12s\n", - " 50750K .......... .......... .......... .......... .......... 8% 27.0M 12s\n", - " 50800K .......... .......... .......... .......... .......... 8% 34.8M 12s\n", - " 50850K .......... .......... .......... .......... .......... 8% 60.3M 12s\n", - " 50900K .......... .......... .......... .......... .......... 8% 4.20M 13s\n", - " 50950K .......... .......... .......... .......... .......... 8% 61.7M 13s\n", - " 51000K .......... .......... .......... .......... .......... 8% 44.3M 13s\n", - " 51050K .......... .......... .......... .......... .......... 8% 52.2M 13s\n", - " 51100K .......... .......... .......... .......... .......... 8% 45.5M 13s\n", - " 51150K .......... .......... .......... .......... .......... 8% 38.8M 13s\n", - " 51200K .......... .......... .......... .......... .......... 8% 50.0M 13s\n", - " 51250K .......... .......... .......... .......... .......... 8% 59.0M 13s\n", - " 51300K .......... .......... .......... .......... .......... 8% 55.1M 13s\n", - " 51350K .......... .......... .......... .......... .......... 8% 56.2M 13s\n", - " 51400K .......... .......... .......... .......... .......... 8% 40.2M 13s\n", - " 51450K .......... .......... .......... .......... .......... 8% 57.1M 13s\n", - " 51500K .......... .......... .......... .......... .......... 8% 61.7M 13s\n", - " 51550K .......... .......... .......... .......... .......... 8% 66.3M 13s\n", - " 51600K .......... .......... .......... .......... .......... 8% 55.1M 13s\n", - " 51650K .......... .......... .......... .......... .......... 8% 53.4M 12s\n", - " 51700K .......... .......... .......... .......... .......... 8% 54.0M 12s\n", - " 51750K .......... .......... .......... .......... .......... 8% 47.2M 12s\n", - " 51800K .......... .......... .......... .......... .......... 8% 53.3M 12s\n", - " 51850K .......... .......... .......... .......... .......... 8% 58.2M 12s\n", - " 51900K .......... .......... .......... .......... .......... 8% 46.4M 12s\n", - " 51950K .......... .......... .......... .......... .......... 8% 51.2M 12s\n", - " 52000K .......... .......... .......... .......... .......... 8% 44.9M 12s\n", - " 52050K .......... .......... .......... .......... .......... 8% 64.8M 12s\n", - " 52100K .......... .......... .......... .......... .......... 8% 55.7M 12s\n", - " 52150K .......... .......... .......... .......... .......... 8% 52.8M 12s\n", - " 52200K .......... .......... .......... .......... .......... 8% 35.3M 12s\n", + " 0K .......... .......... .......... .......... .......... 0% 5.68M 1m42s\n", + " 50K .......... .......... .......... .......... .......... 0% 4.07M 2m3s\n", + " 100K .......... .......... .......... .......... .......... 0% 58.7M 85s\n", + " 150K .......... .......... .......... .......... .......... 0% 7.06M 84s\n", + " 200K .......... .......... .......... .......... .......... 0% 49.9M 70s\n", + " 250K .......... .......... .......... .......... .......... 0% 64.4M 60s\n", + " 300K .......... .......... .......... .......... .......... 0% 15.8M 56s\n", + " 350K .......... .......... .......... .......... .......... 0% 48.1M 51s\n", + " 400K .......... .......... .......... .......... .......... 0% 59.3M 46s\n", + " 450K .......... .......... .......... .......... .......... 0% 67.1M 42s\n", + " 500K .......... .......... .......... .......... .......... 0% 27.9M 41s\n", + " 550K .......... .......... .......... .......... .......... 0% 29.4M 39s\n", + " 600K .......... .......... .......... .......... .......... 0% 56.8M 37s\n", + " 650K .......... .......... .......... .......... .......... 0% 64.4M 35s\n", + " 700K .......... .......... .......... .......... .......... 0% 68.4M 33s\n", + " 750K .......... .......... .......... .......... .......... 0% 25.4M 32s\n", + " 800K .......... .......... .......... .......... .......... 0% 57.7M 31s\n", + " 850K .......... .......... .......... .......... .......... 0% 47.5M 30s\n", + " 900K .......... .......... .......... .......... .......... 0% 66.6M 29s\n", + " 950K .......... .......... .......... .......... .......... 0% 62.4M 28s\n", + " 1000K .......... .......... .......... .......... .......... 0% 22.3M 28s\n", + " 1050K .......... .......... .......... .......... .......... 0% 53.0M 27s\n", + " 1100K .......... .......... .......... .......... .......... 0% 54.5M 26s\n", + " 1150K .......... .......... .......... .......... .......... 0% 65.6M 26s\n", + " 1200K .......... .......... .......... .......... .......... 0% 53.1M 25s\n", + " 1250K .......... .......... .......... .......... .......... 0% 66.9M 24s\n", + " 1300K .......... .......... .......... .......... .......... 0% 66.3M 24s\n", + " 1350K .......... .......... .......... .......... .......... 0% 3.35M 29s\n", + " 1400K .......... .......... .......... .......... .......... 0% 55.9M 28s\n", + " 1450K .......... .......... .......... .......... .......... 0% 42.8M 28s\n", + " 1500K .......... .......... .......... .......... .......... 0% 46.3M 27s\n", + " 1550K .......... .......... .......... .......... .......... 0% 20.6M 27s\n", + " 1600K .......... .......... .......... .......... .......... 0% 26.9M 27s\n", + " 1650K .......... .......... .......... .......... .......... 0% 35.6M 27s\n", + " 1700K .......... .......... .......... .......... .......... 0% 66.2M 26s\n", + " 1750K .......... .......... .......... .......... .......... 0% 68.5M 26s\n", + " 1800K .......... .......... .......... .......... .......... 0% 55.3M 25s\n", + " 1850K .......... .......... .......... .......... .......... 0% 64.4M 25s\n", + " 1900K .......... .......... .......... .......... .......... 0% 57.1M 25s\n", + " 1950K .......... .......... .......... .......... .......... 0% 62.0M 24s\n", + " 2000K .......... .......... .......... .......... .......... 0% 4.89M 27s\n", + " 2050K .......... .......... .......... .......... .......... 0% 28.8M 26s\n", + " 2100K .......... .......... .......... .......... .......... 0% 25.9M 26s\n", + " 2150K .......... .......... .......... .......... .......... 0% 26.3M 26s\n", + " 2200K .......... .......... .......... .......... .......... 0% 22.7M 26s\n", + " 2250K .......... .......... .......... .......... .......... 0% 31.4M 26s\n", + " 2300K .......... .......... .......... .......... .......... 0% 28.0M 26s\n", + " 2350K .......... .......... .......... .......... .......... 0% 31.4M 26s\n", + " 2400K .......... .......... .......... .......... .......... 0% 26.1M 26s\n", + " 2450K .......... .......... .......... .......... .......... 0% 34.5M 25s\n", + " 2500K .......... .......... .......... .......... .......... 0% 32.9M 25s\n", + " 2550K .......... .......... .......... .......... .......... 0% 38.1M 25s\n", + " 2600K .......... .......... .......... .......... .......... 0% 40.2M 25s\n", + " 2650K .......... .......... .......... .......... .......... 0% 59.6M 25s\n", + " 2700K .......... .......... .......... .......... .......... 0% 42.8M 24s\n", + " 2750K .......... .......... .......... .......... .......... 0% 63.2M 24s\n", + " 2800K .......... .......... .......... .......... .......... 0% 63.5M 24s\n", + " 2850K .......... .......... .......... .......... .......... 0% 72.7M 24s\n", + " 2900K .......... .......... .......... .......... .......... 0% 4.05M 26s\n", + " 2950K .......... .......... .......... .......... .......... 0% 67.7M 25s\n", + " 3000K .......... .......... .......... .......... .......... 0% 53.0M 25s\n", + " 3050K .......... .......... .......... .......... .......... 0% 64.7M 25s\n", + " 3100K .......... .......... .......... .......... .......... 0% 65.3M 25s\n", + " 3150K .......... .......... .......... .......... .......... 0% 64.5M 24s\n", + " 3200K .......... .......... .......... .......... .......... 0% 61.0M 24s\n", + " 3250K .......... .......... .......... .......... .......... 0% 44.5M 24s\n", + " 3300K .......... .......... .......... .......... .......... 0% 60.3M 24s\n", + " 3350K .......... .......... .......... .......... .......... 0% 65.7M 24s\n", + " 3400K .......... .......... .......... .......... .......... 0% 26.0M 23s\n", + " 3450K .......... .......... .......... .......... .......... 0% 44.3M 23s\n", + " 3500K .......... .......... .......... .......... .......... 0% 68.7M 23s\n", + " 3550K .......... .......... .......... .......... .......... 0% 73.8M 23s\n", + " 3600K .......... .......... .......... .......... .......... 0% 63.0M 23s\n", + " 3650K .......... .......... .......... .......... .......... 0% 67.2M 23s\n", + " 3700K .......... .......... .......... .......... .......... 0% 56.7M 22s\n", + " 3750K .......... .......... .......... .......... .......... 0% 34.4M 22s\n", + " 3800K .......... .......... .......... .......... .......... 0% 4.09M 24s\n", + " 3850K .......... .......... .......... .......... .......... 0% 58.5M 24s\n", + " 3900K .......... .......... .......... .......... .......... 0% 59.0M 23s\n", + " 3950K .......... .......... .......... .......... .......... 0% 69.5M 23s\n", + " 4000K .......... .......... .......... .......... .......... 0% 57.0M 23s\n", + " 4050K .......... .......... .......... .......... .......... 0% 61.7M 23s\n", + " 4100K .......... .......... .......... .......... .......... 0% 61.7M 23s\n", + " 4150K .......... .......... .......... .......... .......... 0% 59.6M 23s\n", + " 4200K .......... .......... .......... .......... .......... 0% 54.4M 22s\n", + " 4250K .......... .......... .......... .......... .......... 0% 69.7M 22s\n", + " 4300K .......... .......... .......... .......... .......... 0% 62.1M 22s\n", + " 4350K .......... .......... .......... .......... .......... 0% 63.8M 22s\n", + " 4400K .......... .......... .......... .......... .......... 0% 58.4M 22s\n", + " 4450K .......... .......... .......... .......... .......... 0% 75.6M 22s\n", + " 4500K .......... .......... .......... .......... .......... 0% 67.9M 22s\n", + " 4550K .......... .......... .......... .......... .......... 0% 66.8M 21s\n", + " 4600K .......... .......... .......... .......... .......... 0% 33.7M 21s\n", + " 4650K .......... .......... .......... .......... .......... 0% 50.9M 21s\n", + " 4700K .......... .......... .......... .......... .......... 0% 71.8M 21s\n", + " 4750K .......... .......... .......... .......... .......... 0% 68.8M 21s\n", + " 4800K .......... .......... .......... .......... .......... 0% 65.4M 21s\n", + " 4850K .......... .......... .......... .......... .......... 0% 69.6M 21s\n", + " 4900K .......... .......... .......... .......... .......... 0% 40.3M 21s\n", + " 4950K .......... .......... .......... .......... .......... 0% 30.6M 21s\n", + " 5000K .......... .......... .......... .......... .......... 0% 25.7M 21s\n", + " 5050K .......... .......... .......... .......... .......... 0% 73.0M 21s\n", + " 5100K .......... .......... .......... .......... .......... 0% 69.2M 20s\n", + " 5150K .......... .......... .......... .......... .......... 0% 70.0M 20s\n", + " 5200K .......... .......... .......... .......... .......... 0% 62.4M 20s\n", + " 5250K .......... .......... .......... .......... .......... 0% 75.1M 20s\n", + " 5300K .......... .......... .......... .......... .......... 0% 70.3M 20s\n", + " 5350K .......... .......... .......... .......... .......... 0% 68.5M 20s\n", + " 5400K .......... .......... .......... .......... .......... 0% 50.7M 20s\n", + " 5450K .......... .......... .......... .......... .......... 0% 36.0M 20s\n", + " 5500K .......... .......... .......... .......... .......... 0% 26.2M 20s\n", + " 5550K .......... .......... .......... .......... .......... 0% 15.0M 20s\n", + " 5600K .......... .......... .......... .......... .......... 0% 23.9M 20s\n", + " 5650K .......... .......... .......... .......... .......... 0% 39.8M 20s\n", + " 5700K .......... .......... .......... .......... .......... 0% 55.4M 20s\n", + " 5750K .......... .......... .......... .......... .......... 0% 34.9M 20s\n", + " 5800K .......... .......... .......... .......... .......... 0% 45.9M 20s\n", + " 5850K .......... .......... .......... .......... .......... 0% 72.3M 20s\n", + " 5900K .......... .......... .......... .......... .......... 1% 70.7M 20s\n", + " 5950K .......... .......... .......... .......... .......... 1% 69.2M 19s\n", + " 6000K .......... .......... .......... .......... .......... 1% 7.23M 20s\n", + " 6050K .......... .......... .......... .......... .......... 1% 71.7M 20s\n", + " 6100K .......... .......... .......... .......... .......... 1% 20.6M 20s\n", + " 6150K .......... .......... .......... .......... .......... 1% 41.9M 20s\n", + " 6200K .......... .......... .......... .......... .......... 1% 20.5M 20s\n", + " 6250K .......... .......... .......... .......... .......... 1% 32.9M 20s\n", + " 6300K .......... .......... .......... .......... .......... 1% 40.9M 20s\n", + " 6350K .......... .......... .......... .......... .......... 1% 29.1M 20s\n", + " 6400K .......... .......... .......... .......... .......... 1% 33.4M 20s\n", + " 6450K .......... .......... .......... .......... .......... 1% 53.5M 20s\n", + " 6500K .......... .......... .......... .......... .......... 1% 25.5M 20s\n", + " 6550K .......... .......... .......... .......... .......... 1% 32.6M 20s\n", + " 6600K .......... .......... .......... .......... .......... 1% 36.5M 20s\n", + " 6650K .......... .......... .......... .......... .......... 1% 29.1M 20s\n", + " 6700K .......... .......... .......... .......... .......... 1% 40.9M 20s\n", + " 6750K .......... .......... .......... .......... .......... 1% 37.3M 20s\n", + " 6800K .......... .......... .......... .......... .......... 1% 33.6M 20s\n", + " 6850K .......... .......... .......... .......... .......... 1% 40.5M 20s\n", + " 6900K .......... .......... .......... .......... .......... 1% 34.8M 20s\n", + " 6950K .......... .......... .......... .......... .......... 1% 48.2M 19s\n", + " 7000K .......... .......... .......... .......... .......... 1% 28.2M 19s\n", + " 7050K .......... .......... .......... .......... .......... 1% 31.3M 19s\n", + " 7100K .......... .......... .......... .......... .......... 1% 48.5M 19s\n", + " 7150K .......... .......... .......... .......... .......... 1% 27.7M 19s\n", + " 7200K .......... .......... .......... .......... .......... 1% 34.4M 19s\n", + " 7250K .......... .......... .......... .......... .......... 1% 32.9M 19s\n", + " 7300K .......... .......... .......... .......... .......... 1% 50.7M 19s\n", + " 7350K .......... .......... .......... .......... .......... 1% 42.5M 19s\n", + " 7400K .......... .......... .......... .......... .......... 1% 43.5M 19s\n", + " 7450K .......... .......... .......... .......... .......... 1% 47.9M 19s\n", + " 7500K .......... .......... .......... .......... .......... 1% 48.8M 19s\n", + " 7550K .......... .......... .......... .......... .......... 1% 52.3M 19s\n", + " 7600K .......... .......... .......... .......... .......... 1% 55.6M 19s\n", + " 7650K .......... .......... .......... .......... .......... 1% 70.1M 19s\n", + " 7700K .......... .......... .......... .......... .......... 1% 73.0M 19s\n", + " 7750K .......... .......... .......... .......... .......... 1% 64.8M 19s\n", + " 7800K .......... .......... .......... .......... .......... 1% 40.9M 19s\n", + " 7850K .......... .......... .......... .......... .......... 1% 61.2M 19s\n", + " 7900K .......... .......... .......... .......... .......... 1% 62.0M 19s\n", + " 7950K .......... .......... .......... .......... .......... 1% 70.8M 19s\n", + " 8000K .......... .......... .......... .......... .......... 1% 51.8M 19s\n", + " 8050K .......... .......... .......... .......... .......... 1% 41.1M 19s\n", + " 8100K .......... .......... .......... .......... .......... 1% 62.0M 18s\n", + " 8150K .......... .......... .......... .......... .......... 1% 57.9M 18s\n", + " 8200K .......... .......... .......... .......... .......... 1% 45.0M 18s\n", + " 8250K .......... .......... .......... .......... .......... 1% 53.7M 18s\n", + " 8300K .......... .......... .......... .......... .......... 1% 53.6M 18s\n", + " 8350K .......... .......... .......... .......... .......... 1% 65.2M 18s\n", + " 8400K .......... .......... .......... .......... .......... 1% 51.0M 18s\n", + " 8450K .......... .......... .......... .......... .......... 1% 43.2M 18s\n", + " 8500K .......... .......... .......... .......... .......... 1% 39.8M 18s\n", + " 8550K .......... .......... .......... .......... .......... 1% 35.3M 18s\n", + " 8600K .......... .......... .......... .......... .......... 1% 34.3M 18s\n", + " 8650K .......... .......... .......... .......... .......... 1% 62.0M 18s\n", + " 8700K .......... .......... .......... .......... .......... 1% 77.4M 18s\n", + " 8750K .......... .......... .......... .......... .......... 1% 60.5M 18s\n", + " 8800K .......... .......... .......... .......... .......... 1% 61.2M 18s\n", + " 8850K .......... .......... .......... .......... .......... 1% 72.3M 18s\n", + " 8900K .......... .......... .......... .......... .......... 1% 74.9M 18s\n", + " 8950K .......... .......... .......... .......... .......... 1% 66.1M 18s\n", + " 9000K .......... .......... .......... .......... .......... 1% 50.1M 18s\n", + " 9050K .......... .......... .......... .......... .......... 1% 65.2M 18s\n", + " 9100K .......... .......... .......... .......... .......... 1% 65.1M 18s\n", + " 9150K .......... .......... .......... .......... .......... 1% 68.6M 18s\n", + " 9200K .......... .......... .......... .......... .......... 1% 48.8M 18s\n", + " 9250K .......... .......... .......... .......... .......... 1% 56.4M 17s\n", + " 9300K .......... .......... .......... .......... .......... 1% 66.3M 17s\n", + " 9350K .......... .......... .......... .......... .......... 1% 64.2M 17s\n", + " 9400K .......... .......... .......... .......... .......... 1% 56.0M 17s\n", + " 9450K .......... .......... .......... .......... .......... 1% 55.4M 17s\n", + " 9500K .......... .......... .......... .......... .......... 1% 46.0M 17s\n", + " 9550K .......... .......... .......... .......... .......... 1% 53.2M 17s\n", + " 9600K .......... .......... .......... .......... .......... 1% 47.0M 17s\n", + " 9650K .......... .......... .......... .......... .......... 1% 63.5M 17s\n", + " 9700K .......... .......... .......... .......... .......... 1% 54.4M 17s\n", + " 9750K .......... .......... .......... .......... .......... 1% 53.9M 17s\n", + " 9800K .......... .......... .......... .......... .......... 1% 39.4M 17s\n", + " 9850K .......... .......... .......... .......... .......... 1% 55.5M 17s\n", + " 9900K .......... .......... .......... .......... .......... 1% 55.3M 17s\n", + " 9950K .......... .......... .......... .......... .......... 1% 47.0M 17s\n", + " 10000K .......... .......... .......... .......... .......... 1% 44.3M 17s\n", + " 10050K .......... .......... .......... .......... .......... 1% 54.5M 17s\n", + " 10100K .......... .......... .......... .......... .......... 1% 57.7M 17s\n", + " 10150K .......... .......... .......... .......... .......... 1% 55.9M 17s\n", + " 10200K .......... .......... .......... .......... .......... 1% 40.0M 17s\n", + " 10250K .......... .......... .......... .......... .......... 1% 58.3M 17s\n", + " 10300K .......... .......... .......... .......... .......... 1% 62.3M 17s\n", + " 10350K .......... .......... .......... .......... .......... 1% 65.3M 17s\n", + " 10400K .......... .......... .......... .......... .......... 1% 50.5M 17s\n", + " 10450K .......... .......... .......... .......... .......... 1% 55.0M 17s\n", + " 10500K .......... .......... .......... .......... .......... 1% 66.4M 17s\n", + " 10550K .......... .......... .......... .......... .......... 1% 59.7M 17s\n", + " 10600K .......... .......... .......... .......... .......... 1% 58.9M 17s\n", + " 10650K .......... .......... .......... .......... .......... 1% 3.82M 17s\n", + " 10700K .......... .......... .......... .......... .......... 1% 66.0M 17s\n", + " 10750K .......... .......... .......... .......... .......... 1% 64.8M 17s\n", + " 10800K .......... .......... .......... .......... .......... 1% 62.3M 17s\n", + " 10850K .......... .......... .......... .......... .......... 1% 74.0M 17s\n", + " 10900K .......... .......... .......... .......... .......... 1% 72.8M 17s\n", + " 10950K .......... .......... .......... .......... .......... 1% 64.4M 17s\n", + " 11000K .......... .......... .......... .......... .......... 1% 57.6M 17s\n", + " 11050K .......... .......... .......... .......... .......... 1% 76.0M 17s\n", + " 11100K .......... .......... .......... .......... .......... 1% 70.4M 17s\n", + " 11150K .......... .......... .......... .......... .......... 1% 70.4M 17s\n", + " 11200K .......... .......... .......... .......... .......... 1% 66.8M 17s\n", + " 11250K .......... .......... .......... .......... .......... 1% 70.0M 17s\n", + " 11300K .......... .......... .......... .......... .......... 1% 52.0M 17s\n", + " 11350K .......... .......... .......... .......... .......... 1% 56.5M 17s\n", + " 11400K .......... .......... .......... .......... .......... 1% 44.8M 17s\n", + " 11450K .......... .......... .......... .......... .......... 1% 68.1M 17s\n", + " 11500K .......... .......... .......... .......... .......... 1% 52.6M 17s\n", + " 11550K .......... .......... .......... .......... .......... 1% 49.4M 17s\n", + " 11600K .......... .......... .......... .......... .......... 1% 49.1M 17s\n", + " 11650K .......... .......... .......... .......... .......... 1% 51.2M 16s\n", + " 11700K .......... .......... .......... .......... .......... 1% 72.3M 16s\n", + " 11750K .......... .......... .......... .......... .......... 1% 68.0M 16s\n", + " 11800K .......... .......... .......... .......... .......... 1% 45.1M 16s\n", + " 11850K .......... .......... .......... .......... .......... 2% 62.2M 16s\n", + " 11900K .......... .......... .......... .......... .......... 2% 52.9M 16s\n", + " 11950K .......... .......... .......... .......... .......... 2% 64.3M 16s\n", + " 12000K .......... .......... .......... .......... .......... 2% 56.9M 16s\n", + " 12050K .......... .......... .......... .......... .......... 2% 58.5M 16s\n", + " 12100K .......... .......... .......... .......... .......... 2% 60.3M 16s\n", + " 12150K .......... .......... .......... .......... .......... 2% 52.4M 16s\n", + " 12200K .......... .......... .......... .......... .......... 2% 53.0M 16s\n", + " 12250K .......... .......... .......... .......... .......... 2% 74.8M 16s\n", + " 12300K .......... .......... .......... .......... .......... 2% 46.6M 16s\n", + " 12350K .......... .......... .......... .......... .......... 2% 60.1M 16s\n", + " 12400K .......... .......... .......... .......... .......... 2% 3.90M 17s\n", + " 12450K .......... .......... .......... .......... .......... 2% 69.1M 17s\n", + " 12500K .......... .......... .......... .......... .......... 2% 69.7M 17s\n", + " 12550K .......... .......... .......... .......... .......... 2% 62.0M 17s\n", + " 12600K .......... .......... .......... .......... .......... 2% 57.5M 16s\n", + " 12650K .......... .......... .......... .......... .......... 2% 67.0M 16s\n", + " 12700K .......... .......... .......... .......... .......... 2% 75.2M 16s\n", + " 12750K .......... .......... .......... .......... .......... 2% 62.0M 16s\n", + " 12800K .......... .......... .......... .......... .......... 2% 60.6M 16s\n", + " 12850K .......... .......... .......... .......... .......... 2% 67.7M 16s\n", + " 12900K .......... .......... .......... .......... .......... 2% 69.2M 16s\n", + " 12950K .......... .......... .......... .......... .......... 2% 71.4M 16s\n", + " 13000K .......... .......... .......... .......... .......... 2% 49.3M 16s\n", + " 13050K .......... .......... .......... .......... .......... 2% 58.2M 16s\n", + " 13100K .......... .......... .......... .......... .......... 2% 59.6M 16s\n", + " 13150K .......... .......... .......... .......... .......... 2% 72.0M 16s\n", + " 13200K .......... .......... .......... .......... .......... 2% 57.9M 16s\n", + " 13250K .......... .......... .......... .......... .......... 2% 65.2M 16s\n", + " 13300K .......... .......... .......... .......... .......... 2% 56.1M 16s\n", + " 13350K .......... .......... .......... .......... .......... 2% 51.9M 16s\n", + " 13400K .......... .......... .......... .......... .......... 2% 47.4M 16s\n", + " 13450K .......... .......... .......... .......... .......... 2% 64.2M 16s\n", + " 13500K .......... .......... .......... .......... .......... 2% 69.7M 16s\n", + " 13550K .......... .......... .......... .......... .......... 2% 63.6M 16s\n", + " 13600K .......... .......... .......... .......... .......... 2% 55.9M 16s\n", + " 13650K .......... .......... .......... .......... .......... 2% 69.8M 16s\n", + " 13700K .......... .......... .......... .......... .......... 2% 69.3M 16s\n", + " 13750K .......... .......... .......... .......... .......... 2% 68.8M 16s\n", + " 13800K .......... .......... .......... .......... .......... 2% 57.1M 16s\n", + " 13850K .......... .......... .......... .......... .......... 2% 80.3M 16s\n", + " 13900K .......... .......... .......... .......... .......... 2% 70.1M 16s\n", + " 13950K .......... .......... .......... .......... .......... 2% 73.7M 16s\n", + " 14000K .......... .......... .......... .......... .......... 2% 56.5M 16s\n", + " 14050K .......... .......... .......... .......... .......... 2% 52.2M 16s\n", + " 14100K .......... .......... .......... .......... .......... 2% 47.4M 16s\n", + " 14150K .......... .......... .......... .......... .......... 2% 60.5M 16s\n", + " 14200K .......... .......... .......... .......... .......... 2% 58.8M 16s\n", + " 14250K .......... .......... .......... .......... .......... 2% 71.5M 16s\n", + " 14300K .......... .......... .......... .......... .......... 2% 51.2M 16s\n", + " 14350K .......... .......... .......... .......... .......... 2% 56.9M 16s\n", + " 14400K .......... .......... .......... .......... .......... 2% 41.5M 16s\n", + " 14450K .......... .......... .......... .......... .......... 2% 49.2M 16s\n", + " 14500K .......... .......... .......... .......... .......... 2% 61.8M 16s\n", + " 14550K .......... .......... .......... .......... .......... 2% 73.1M 15s\n", + " 14600K .......... .......... .......... .......... .......... 2% 55.8M 15s\n", + " 14650K .......... .......... .......... .......... .......... 2% 61.5M 15s\n", + " 14700K .......... .......... .......... .......... .......... 2% 50.9M 15s\n", + " 14750K .......... .......... .......... .......... .......... 2% 47.8M 15s\n", + " 14800K .......... .......... .......... .......... .......... 2% 48.2M 15s\n", + " 14850K .......... .......... .......... .......... .......... 2% 55.8M 15s\n", + " 14900K .......... .......... .......... .......... .......... 2% 66.4M 15s\n", + " 14950K .......... .......... .......... .......... .......... 2% 73.0M 15s\n", + " 15000K .......... .......... .......... .......... .......... 2% 43.9M 15s\n", + " 15050K .......... .......... .......... .......... .......... 2% 48.9M 15s\n", + " 15100K .......... .......... .......... .......... .......... 2% 53.2M 15s\n", + " 15150K .......... .......... .......... .......... .......... 2% 51.3M 15s\n", + " 15200K .......... .......... .......... .......... .......... 2% 56.1M 15s\n", + " 15250K .......... .......... .......... .......... .......... 2% 67.8M 15s\n", + " 15300K .......... .......... .......... .......... .......... 2% 70.3M 15s\n", + " 15350K .......... .......... .......... .......... .......... 2% 73.5M 15s\n", + " 15400K .......... .......... .......... .......... .......... 2% 45.4M 15s\n", + " 15450K .......... .......... .......... .......... .......... 2% 50.8M 15s\n", + " 15500K .......... .......... .......... .......... .......... 2% 69.5M 15s\n", + " 15550K .......... .......... .......... .......... .......... 2% 65.8M 15s\n", + " 15600K .......... .......... .......... .......... .......... 2% 55.2M 15s\n", + " 15650K .......... .......... .......... .......... .......... 2% 53.3M 15s\n", + " 15700K .......... .......... .......... .......... .......... 2% 47.2M 15s\n", + " 15750K .......... .......... .......... .......... .......... 2% 46.0M 15s\n", + " 15800K .......... .......... .......... .......... .......... 2% 50.6M 15s\n", + " 15850K .......... .......... .......... .......... .......... 2% 44.3M 15s\n", + " 15900K .......... .......... .......... .......... .......... 2% 47.6M 15s\n", + " 15950K .......... .......... .......... .......... .......... 2% 53.9M 15s\n", + " 16000K .......... .......... .......... .......... .......... 2% 54.8M 15s\n", + " 16050K .......... .......... .......... .......... .......... 2% 71.1M 15s\n", + " 16100K .......... .......... .......... .......... .......... 2% 63.1M 15s\n", + " 16150K .......... .......... .......... .......... .......... 2% 50.2M 15s\n", + " 16200K .......... .......... .......... .......... .......... 2% 48.2M 15s\n", + " 16250K .......... .......... .......... .......... .......... 2% 60.5M 15s\n", + " 16300K .......... .......... .......... .......... .......... 2% 76.9M 15s\n", + " 16350K .......... .......... .......... .......... .......... 2% 4.16M 15s\n", + " 16400K .......... .......... .......... .......... .......... 2% 58.3M 15s\n", + " 16450K .......... .......... .......... .......... .......... 2% 64.8M 15s\n", + " 16500K .......... .......... .......... .......... .......... 2% 72.4M 15s\n", + " 16550K .......... .......... .......... .......... .......... 2% 69.2M 15s\n", + " 16600K .......... .......... .......... .......... .......... 2% 50.4M 15s\n", + " 16650K .......... .......... .......... .......... .......... 2% 66.3M 15s\n", + " 16700K .......... .......... .......... .......... .......... 2% 50.3M 15s\n", + " 16750K .......... .......... .......... .......... .......... 2% 64.4M 15s\n", + " 16800K .......... .......... .......... .......... .......... 2% 63.8M 15s\n", + " 16850K .......... .......... .......... .......... .......... 2% 64.2M 15s\n", + " 16900K .......... .......... .......... .......... .......... 2% 47.6M 15s\n", + " 16950K .......... .......... .......... .......... .......... 2% 50.4M 15s\n", + " 17000K .......... .......... .......... .......... .......... 2% 50.8M 15s\n", + " 17050K .......... .......... .......... .......... .......... 2% 69.7M 15s\n", + " 17100K .......... .......... .......... .......... .......... 2% 76.7M 15s\n", + " 17150K .......... .......... .......... .......... .......... 2% 60.5M 15s\n", + " 17200K .......... .......... .......... .......... .......... 2% 63.6M 15s\n", + " 17250K .......... .......... .......... .......... .......... 2% 58.3M 15s\n", + " 17300K .......... .......... .......... .......... .......... 2% 55.5M 15s\n", + " 17350K .......... .......... .......... .......... .......... 2% 51.0M 15s\n", + " 17400K .......... .......... .......... .......... .......... 2% 43.6M 15s\n", + " 17450K .......... .......... .......... .......... .......... 2% 63.9M 15s\n", + " 17500K .......... .......... .......... .......... .......... 2% 57.9M 15s\n", + " 17550K .......... .......... .......... .......... .......... 2% 51.6M 15s\n", + " 17600K .......... .......... .......... .......... .......... 2% 54.2M 15s\n", + " 17650K .......... .......... .......... .......... .......... 2% 54.0M 15s\n", + " 17700K .......... .......... .......... .......... .......... 2% 52.3M 15s\n", + " 17750K .......... .......... .......... .......... .......... 2% 59.6M 15s\n", + " 17800K .......... .......... .......... .......... .......... 3% 40.7M 15s\n", + " 17850K .......... .......... .......... .......... .......... 3% 53.2M 15s\n", + " 17900K .......... .......... .......... .......... .......... 3% 46.6M 15s\n", + " 17950K .......... .......... .......... .......... .......... 3% 59.1M 15s\n", + " 18000K .......... .......... .......... .......... .......... 3% 50.3M 15s\n", + " 18050K .......... .......... .......... .......... .......... 3% 55.4M 15s\n", + " 18100K .......... .......... .......... .......... .......... 3% 47.6M 15s\n", + " 18150K .......... .......... .......... .......... .......... 3% 50.6M 15s\n", + " 18200K .......... .......... .......... .......... .......... 3% 57.2M 15s\n", + " 18250K .......... .......... .......... .......... .......... 3% 60.7M 15s\n", + " 18300K .......... .......... .......... .......... .......... 3% 4.39M 15s\n", + " 18350K .......... .......... .......... .......... .......... 3% 59.0M 15s\n", + " 18400K .......... .......... .......... .......... .......... 3% 57.1M 15s\n", + " 18450K .......... .......... .......... .......... .......... 3% 65.9M 15s\n", + " 18500K .......... .......... .......... .......... .......... 3% 67.4M 15s\n", + " 18550K .......... .......... .......... .......... .......... 3% 69.7M 15s\n", + " 18600K .......... .......... .......... .......... .......... 3% 55.0M 15s\n", + " 18650K .......... .......... .......... .......... .......... 3% 65.4M 15s\n", + " 18700K .......... .......... .......... .......... .......... 3% 58.5M 15s\n", + " 18750K .......... .......... .......... .......... .......... 3% 13.4M 15s\n", + " 18800K .......... .......... .......... .......... .......... 3% 56.2M 15s\n", + " 18850K .......... .......... .......... .......... .......... 3% 67.3M 15s\n", + " 18900K .......... .......... .......... .......... .......... 3% 66.7M 15s\n", + " 18950K .......... .......... .......... .......... .......... 3% 63.7M 15s\n", + " 19000K .......... .......... .......... .......... .......... 3% 61.7M 15s\n", + " 19050K .......... .......... .......... .......... .......... 3% 69.7M 15s\n", + " 19100K .......... .......... .......... .......... .......... 3% 73.4M 15s\n", + " 19150K .......... .......... .......... .......... .......... 3% 73.8M 15s\n", + " 19200K .......... .......... .......... .......... .......... 3% 62.4M 15s\n", + " 19250K .......... .......... .......... .......... .......... 3% 70.9M 15s\n", + " 19300K .......... .......... .......... .......... .......... 3% 74.5M 15s\n", + " 19350K .......... .......... .......... .......... .......... 3% 70.9M 15s\n", + " 19400K .......... .......... .......... .......... .......... 3% 51.9M 15s\n", + " 19450K .......... .......... .......... .......... .......... 3% 70.0M 15s\n", + " 19500K .......... .......... .......... .......... .......... 3% 72.6M 15s\n", + " 19550K .......... .......... .......... .......... .......... 3% 12.1M 15s\n", + " 19600K .......... .......... .......... .......... .......... 3% 54.6M 15s\n", + " 19650K .......... .......... .......... .......... .......... 3% 49.2M 15s\n", + " 19700K .......... .......... .......... .......... .......... 3% 49.5M 15s\n", + " 19750K .......... .......... .......... .......... .......... 3% 48.6M 15s\n", + " 19800K .......... .......... .......... .......... .......... 3% 40.3M 15s\n", + " 19850K .......... .......... .......... .......... .......... 3% 45.7M 15s\n", + " 19900K .......... .......... .......... .......... .......... 3% 48.8M 15s\n", + " 19950K .......... .......... .......... .......... .......... 3% 47.7M 15s\n", + " 20000K .......... .......... .......... .......... .......... 3% 43.8M 15s\n", + " 20050K .......... .......... .......... .......... .......... 3% 45.5M 15s\n", + " 20100K .......... .......... .......... .......... .......... 3% 50.3M 15s\n", + " 20150K .......... .......... .......... .......... .......... 3% 47.5M 15s\n", + " 20200K .......... .......... .......... .......... .......... 3% 38.1M 15s\n", + " 20250K .......... .......... .......... .......... .......... 3% 47.5M 15s\n", + " 20300K .......... .......... .......... .......... .......... 3% 48.2M 15s\n", + " 20350K .......... .......... .......... .......... .......... 3% 50.8M 15s\n", + " 20400K .......... .......... .......... .......... .......... 3% 43.6M 15s\n", + " 20450K .......... .......... .......... .......... .......... 3% 52.3M 15s\n", + " 20500K .......... .......... .......... .......... .......... 3% 48.7M 15s\n", + " 20550K .......... .......... .......... .......... .......... 3% 52.0M 15s\n", + " 20600K .......... .......... .......... .......... .......... 3% 47.7M 15s\n", + " 20650K .......... .......... .......... .......... .......... 3% 53.9M 15s\n", + " 20700K .......... .......... .......... .......... .......... 3% 67.4M 15s\n", + " 20750K .......... .......... .......... .......... .......... 3% 66.3M 15s\n", + " 20800K .......... .......... .......... .......... .......... 3% 64.6M 14s\n", + " 20850K .......... .......... .......... .......... .......... 3% 63.9M 14s\n", + " 20900K .......... .......... .......... .......... .......... 3% 51.3M 14s\n", + " 20950K .......... .......... .......... .......... .......... 3% 53.5M 14s\n", + " 21000K .......... .......... .......... .......... .......... 3% 55.8M 14s\n", + " 21050K .......... .......... .......... .......... .......... 3% 65.2M 14s\n", + " 21100K .......... .......... .......... .......... .......... 3% 72.1M 14s\n", + " 21150K .......... .......... .......... .......... .......... 3% 69.4M 14s\n", + " 21200K .......... .......... .......... .......... .......... 3% 61.2M 14s\n", + " 21250K .......... .......... .......... .......... .......... 3% 69.0M 14s\n", + " 21300K .......... .......... .......... .......... .......... 3% 62.9M 14s\n", + " 21350K .......... .......... .......... .......... .......... 3% 71.7M 14s\n", + " 21400K .......... .......... .......... .......... .......... 3% 60.8M 14s\n", + " 21450K .......... .......... .......... .......... .......... 3% 72.2M 14s\n", + " 21500K .......... .......... .......... .......... .......... 3% 62.5M 14s\n", + " 21550K .......... .......... .......... .......... .......... 3% 54.8M 14s\n", + " 21600K .......... .......... .......... .......... .......... 3% 54.9M 14s\n", + " 21650K .......... .......... .......... .......... .......... 3% 53.0M 14s\n", + " 21700K .......... .......... .......... .......... .......... 3% 52.8M 14s\n", + " 21750K .......... .......... .......... .......... .......... 3% 52.3M 14s\n", + " 21800K .......... .......... .......... .......... .......... 3% 40.0M 14s\n", + " 21850K .......... .......... .......... .......... .......... 3% 50.1M 14s\n", + " 21900K .......... .......... .......... .......... .......... 3% 52.0M 14s\n", + " 21950K .......... .......... .......... .......... .......... 3% 69.3M 14s\n", + " 22000K .......... .......... .......... .......... .......... 3% 50.2M 14s\n", + " 22050K .......... .......... .......... .......... .......... 3% 60.2M 14s\n", + " 22100K .......... .......... .......... .......... .......... 3% 53.1M 14s\n", + " 22150K .......... .......... .......... .......... .......... 3% 9.55M 14s\n", + " 22200K .......... .......... .......... .......... .......... 3% 56.0M 14s\n", + " 22250K .......... .......... .......... .......... .......... 3% 67.6M 14s\n", + " 22300K .......... .......... .......... .......... .......... 3% 60.9M 14s\n", + " 22350K .......... .......... .......... .......... .......... 3% 64.4M 14s\n", + " 22400K .......... .......... .......... .......... .......... 3% 64.0M 14s\n", + " 22450K .......... .......... .......... .......... .......... 3% 61.2M 14s\n", + " 22500K .......... .......... .......... .......... .......... 3% 65.3M 14s\n", + " 22550K .......... .......... .......... .......... .......... 3% 68.7M 14s\n", + " 22600K .......... .......... .......... .......... .......... 3% 59.0M 14s\n", + " 22650K .......... .......... .......... .......... .......... 3% 70.8M 14s\n", + " 22700K .......... .......... .......... .......... .......... 3% 67.3M 14s\n", + " 22750K .......... .......... .......... .......... .......... 3% 60.6M 14s\n", + " 22800K .......... .......... .......... .......... .......... 3% 65.8M 14s\n", + " 22850K .......... .......... .......... .......... .......... 3% 68.5M 14s\n", + " 22900K .......... .......... .......... .......... .......... 3% 51.7M 14s\n", + " 22950K .......... .......... .......... .......... .......... 3% 68.4M 14s\n", + " 23000K .......... .......... .......... .......... .......... 3% 61.1M 14s\n", + " 23050K .......... .......... .......... .......... .......... 3% 73.9M 14s\n", + " 23100K .......... .......... .......... .......... .......... 3% 73.3M 14s\n", + " 23150K .......... .......... .......... .......... .......... 3% 67.9M 14s\n", + " 23200K .......... .......... .......... .......... .......... 3% 65.6M 14s\n", + " 23250K .......... .......... .......... .......... .......... 3% 70.5M 14s\n", + " 23300K .......... .......... .......... .......... .......... 3% 67.7M 14s\n", + " 23350K .......... .......... .......... .......... .......... 3% 72.7M 14s\n", + " 23400K .......... .......... .......... .......... .......... 3% 59.6M 14s\n", + " 23450K .......... .......... .......... .......... .......... 3% 61.6M 14s\n", + " 23500K .......... .......... .......... .......... .......... 3% 70.3M 14s\n", + " 23550K .......... .......... .......... .......... .......... 3% 75.6M 14s\n", + " 23600K .......... .......... .......... .......... .......... 3% 57.6M 14s\n", + " 23650K .......... .......... .......... .......... .......... 3% 66.8M 14s\n", + " 23700K .......... .......... .......... .......... .......... 3% 53.8M 14s\n", + " 23750K .......... .......... .......... .......... .......... 4% 46.2M 14s\n", + " 23800K .......... .......... .......... .......... .......... 4% 42.3M 14s\n", + " 23850K .......... .......... .......... .......... .......... 4% 52.1M 14s\n", + " 23900K .......... .......... .......... .......... .......... 4% 65.6M 14s\n", + " 23950K .......... .......... .......... .......... .......... 4% 48.7M 14s\n", + " 24000K .......... .......... .......... .......... .......... 4% 44.4M 14s\n", + " 24050K .......... .......... .......... .......... .......... 4% 52.4M 14s\n", + " 24100K .......... .......... .......... .......... .......... 4% 51.7M 14s\n", + " 24150K .......... .......... .......... .......... .......... 4% 53.0M 14s\n", + " 24200K .......... .......... .......... .......... .......... 4% 41.9M 14s\n", + " 24250K .......... .......... .......... .......... .......... 4% 48.3M 14s\n", + " 24300K .......... .......... .......... .......... .......... 4% 47.4M 14s\n", + " 24350K .......... .......... .......... .......... .......... 4% 47.0M 14s\n", + " 24400K .......... .......... .......... .......... .......... 4% 47.1M 14s\n", + " 24450K .......... .......... .......... .......... .......... 4% 34.8M 14s\n", + " 24500K .......... .......... .......... .......... .......... 4% 38.3M 14s\n", + " 24550K .......... .......... .......... .......... .......... 4% 48.3M 14s\n", + " 24600K .......... .......... .......... .......... .......... 4% 41.2M 14s\n", + " 24650K .......... .......... .......... .......... .......... 4% 50.5M 14s\n", + " 24700K .......... .......... .......... .......... .......... 4% 72.9M 14s\n", + " 24750K .......... .......... .......... .......... .......... 4% 57.7M 14s\n", + " 24800K .......... .......... .......... .......... .......... 4% 57.3M 14s\n", + " 24850K .......... .......... .......... .......... .......... 4% 77.2M 14s\n", + " 24900K .......... .......... .......... .......... .......... 4% 75.2M 14s\n", + " 24950K .......... .......... .......... .......... .......... 4% 51.5M 14s\n", + " 25000K .......... .......... .......... .......... .......... 4% 54.7M 14s\n", + " 25050K .......... .......... .......... .......... .......... 4% 70.7M 14s\n", + " 25100K .......... .......... .......... .......... .......... 4% 68.4M 14s\n", + " 25150K .......... .......... .......... .......... .......... 4% 5.37M 14s\n", + " 25200K .......... .......... .......... .......... .......... 4% 56.3M 14s\n", + " 25250K .......... .......... .......... .......... .......... 4% 68.8M 14s\n", + " 25300K .......... .......... .......... .......... .......... 4% 59.5M 14s\n", + " 25350K .......... .......... .......... .......... .......... 4% 48.4M 14s\n", + " 25400K .......... .......... .......... .......... .......... 4% 47.8M 14s\n", + " 25450K .......... .......... .......... .......... .......... 4% 56.2M 14s\n", + " 25500K .......... .......... .......... .......... .......... 4% 50.7M 14s\n", + " 25550K .......... .......... .......... .......... .......... 4% 66.8M 14s\n", + " 25600K .......... .......... .......... .......... .......... 4% 51.1M 14s\n", + " 25650K .......... .......... .......... .......... .......... 4% 71.4M 14s\n", + " 25700K .......... .......... .......... .......... .......... 4% 51.7M 14s\n", + " 25750K .......... .......... .......... .......... .......... 4% 53.3M 14s\n", + " 25800K .......... .......... .......... .......... .......... 4% 43.3M 14s\n", + " 25850K .......... .......... .......... .......... .......... 4% 62.3M 14s\n", + " 25900K .......... .......... .......... .......... .......... 4% 49.0M 14s\n", + " 25950K .......... .......... .......... .......... .......... 4% 38.5M 14s\n", + " 26000K .......... .......... .......... .......... .......... 4% 35.7M 14s\n", + " 26050K .......... .......... .......... .......... .......... 4% 76.3M 14s\n", + " 26100K .......... .......... .......... .......... .......... 4% 71.1M 14s\n", + " 26150K .......... .......... .......... .......... .......... 4% 65.3M 14s\n", + " 26200K .......... .......... .......... .......... .......... 4% 25.4M 14s\n", + " 26250K .......... .......... .......... .......... .......... 4% 53.5M 14s\n", + " 26300K .......... .......... .......... .......... .......... 4% 41.3M 14s\n", + " 26350K .......... .......... .......... .......... .......... 4% 36.2M 14s\n", + " 26400K .......... .......... .......... .......... .......... 4% 35.9M 14s\n", + " 26450K .......... .......... .......... .......... .......... 4% 71.5M 14s\n", + " 26500K .......... .......... .......... .......... .......... 4% 59.5M 14s\n", + " 26550K .......... .......... .......... .......... .......... 4% 65.7M 14s\n", + " 26600K .......... .......... .......... .......... .......... 4% 45.5M 14s\n", + " 26650K .......... .......... .......... .......... .......... 4% 54.0M 14s\n", + " 26700K .......... .......... .......... .......... .......... 4% 59.8M 14s\n", + " 26750K .......... .......... .......... .......... .......... 4% 64.2M 14s\n", + " 26800K .......... .......... .......... .......... .......... 4% 58.8M 14s\n", + " 26850K .......... .......... .......... .......... .......... 4% 46.2M 14s\n", + " 26900K .......... .......... .......... .......... .......... 4% 44.8M 14s\n", + " 26950K .......... .......... .......... .......... .......... 4% 10.7M 14s\n", + " 27000K .......... .......... .......... .......... .......... 4% 41.5M 14s\n", + " 27050K .......... .......... .......... .......... .......... 4% 45.8M 14s\n", + " 27100K .......... .......... .......... .......... .......... 4% 45.3M 14s\n", + " 27150K .......... .......... .......... .......... .......... 4% 4.40M 14s\n", + " 27200K .......... .......... .......... .......... .......... 4% 54.7M 14s\n", + " 27250K .......... .......... .......... .......... .......... 4% 63.6M 14s\n", + " 27300K .......... .......... .......... .......... .......... 4% 61.8M 14s\n", + " 27350K .......... .......... .......... .......... .......... 4% 63.2M 14s\n", + " 27400K .......... .......... .......... .......... .......... 4% 50.5M 14s\n", + " 27450K .......... .......... .......... .......... .......... 4% 67.5M 14s\n", + " 27500K .......... .......... .......... .......... .......... 4% 47.4M 14s\n", + " 27550K .......... .......... .......... .......... .......... 4% 34.1M 14s\n", + " 27600K .......... .......... .......... .......... .......... 4% 43.0M 14s\n", + " 27650K .......... .......... .......... .......... .......... 4% 42.9M 14s\n", + " 27700K .......... .......... .......... .......... .......... 4% 36.5M 14s\n", + " 27750K .......... .......... .......... .......... .......... 4% 36.8M 14s\n", + " 27800K .......... .......... .......... .......... .......... 4% 42.4M 14s\n", + " 27850K .......... .......... .......... .......... .......... 4% 43.2M 14s\n", + " 27900K .......... .......... .......... .......... .......... 4% 40.0M 14s\n", + " 27950K .......... .......... .......... .......... .......... 4% 49.3M 14s\n", + " 28000K .......... .......... .......... .......... .......... 4% 40.5M 14s\n", + " 28050K .......... .......... .......... .......... .......... 4% 31.2M 14s\n", + " 28100K .......... .......... .......... .......... .......... 4% 50.2M 14s\n", + " 28150K .......... .......... .......... .......... .......... 4% 59.6M 14s\n", + " 28200K .......... .......... .......... .......... .......... 4% 10.1M 14s\n", + " 28250K .......... .......... .......... .......... .......... 4% 68.3M 14s\n", + " 28300K .......... .......... .......... .......... .......... 4% 56.9M 14s\n", + " 28350K .......... .......... .......... .......... .......... 4% 71.9M 14s\n", + " 28400K .......... .......... .......... .......... .......... 4% 59.7M 14s\n", + " 28450K .......... .......... .......... .......... .......... 4% 75.4M 14s\n", + " 28500K .......... .......... .......... .......... .......... 4% 54.0M 14s\n", + " 28550K .......... .......... .......... .......... .......... 4% 68.0M 14s\n", + " 28600K .......... .......... .......... .......... .......... 4% 41.5M 14s\n", + " 28650K .......... .......... .......... .......... .......... 4% 42.0M 14s\n", + " 28700K .......... .......... .......... .......... .......... 4% 32.1M 14s\n", + " 28750K .......... .......... .......... .......... .......... 4% 36.8M 14s\n", + " 28800K .......... .......... .......... .......... .......... 4% 38.8M 14s\n", + " 28850K .......... .......... .......... .......... .......... 4% 46.7M 14s\n", + " 28900K .......... .......... .......... .......... .......... 4% 33.9M 14s\n", + " 28950K .......... .......... .......... .......... .......... 4% 49.8M 14s\n", + " 29000K .......... .......... .......... .......... .......... 4% 54.9M 14s\n", + " 29050K .......... .......... .......... .......... .......... 4% 80.8M 14s\n", + " 29100K .......... .......... .......... .......... .......... 4% 67.2M 14s\n", + " 29150K .......... .......... .......... .......... .......... 4% 55.0M 14s\n", + " 29200K .......... .......... .......... .......... .......... 4% 46.7M 14s\n", + " 29250K .......... .......... .......... .......... .......... 4% 61.8M 14s\n", + " 29300K .......... .......... .......... .......... .......... 4% 74.0M 14s\n", + " 29350K .......... .......... .......... .......... .......... 4% 48.8M 14s\n", + " 29400K .......... .......... .......... .......... .......... 4% 49.8M 14s\n", + " 29450K .......... .......... .......... .......... .......... 4% 66.3M 14s\n", + " 29500K .......... .......... .......... .......... .......... 4% 67.7M 14s\n", + " 29550K .......... .......... .......... .......... .......... 4% 64.6M 14s\n", + " 29600K .......... .......... .......... .......... .......... 4% 61.5M 14s\n", + " 29650K .......... .......... .......... .......... .......... 4% 70.3M 14s\n", + " 29700K .......... .......... .......... .......... .......... 5% 71.1M 14s\n", + " 29750K .......... .......... .......... .......... .......... 5% 65.2M 14s\n", + " 29800K .......... .......... .......... .......... .......... 5% 60.8M 14s\n", + " 29850K .......... .......... .......... .......... .......... 5% 67.9M 14s\n", + " 29900K .......... .......... .......... .......... .......... 5% 48.9M 14s\n", + " 29950K .......... .......... .......... .......... .......... 5% 48.1M 14s\n", + " 30000K .......... .......... .......... .......... .......... 5% 38.7M 14s\n", + " 30050K .......... .......... .......... .......... .......... 5% 62.0M 14s\n", + " 30100K .......... .......... .......... .......... .......... 5% 58.4M 14s\n", + " 30150K .......... .......... .......... .......... .......... 5% 41.9M 14s\n", + " 30200K .......... .......... .......... .......... .......... 5% 39.8M 14s\n", + " 30250K .......... .......... .......... .......... .......... 5% 50.5M 14s\n", + " 30300K .......... .......... .......... .......... .......... 5% 67.0M 14s\n", + " 30350K .......... .......... .......... .......... .......... 5% 51.4M 14s\n", + " 30400K .......... .......... .......... .......... .......... 5% 45.4M 14s\n", + " 30450K .......... .......... .......... .......... .......... 5% 54.7M 14s\n", + " 30500K .......... .......... .......... .......... .......... 5% 51.0M 14s\n", + " 30550K .......... .......... .......... .......... .......... 5% 72.8M 14s\n", + " 30600K .......... .......... .......... .......... .......... 5% 41.5M 14s\n", + " 30650K .......... .......... .......... .......... .......... 5% 53.5M 14s\n", + " 30700K .......... .......... .......... .......... .......... 5% 52.8M 14s\n", + " 30750K .......... .......... .......... .......... .......... 5% 65.9M 14s\n", + " 30800K .......... .......... .......... .......... .......... 5% 66.9M 14s\n", + " 30850K .......... .......... .......... .......... .......... 5% 57.6M 14s\n", + " 30900K .......... .......... .......... .......... .......... 5% 61.7M 13s\n", + " 30950K .......... .......... .......... .......... .......... 5% 53.5M 13s\n", + " 31000K .......... .......... .......... .......... .......... 5% 51.8M 13s\n", + " 31050K .......... .......... .......... .......... .......... 5% 61.0M 13s\n", + " 31100K .......... .......... .......... .......... .......... 5% 50.6M 13s\n", + " 31150K .......... .......... .......... .......... .......... 5% 62.8M 13s\n", + " 31200K .......... .......... .......... .......... .......... 5% 62.6M 13s\n", + " 31250K .......... .......... .......... .......... .......... 5% 65.3M 13s\n", + " 31300K .......... .......... .......... .......... .......... 5% 72.9M 13s\n", + " 31350K .......... .......... .......... .......... .......... 5% 67.6M 13s\n", + " 31400K .......... .......... .......... .......... .......... 5% 62.3M 13s\n", + " 31450K .......... .......... .......... .......... .......... 5% 76.4M 13s\n", + " 31500K .......... .......... .......... .......... .......... 5% 72.7M 13s\n", + " 31550K .......... .......... .......... .......... .......... 5% 68.8M 13s\n", + " 31600K .......... .......... .......... .......... .......... 5% 59.4M 13s\n", + " 31650K .......... .......... .......... .......... .......... 5% 70.7M 13s\n", + " 31700K .......... .......... .......... .......... .......... 5% 59.7M 13s\n", + " 31750K .......... .......... .......... .......... .......... 5% 65.9M 13s\n", + " 31800K .......... .......... .......... .......... .......... 5% 56.2M 13s\n", + " 31850K .......... .......... .......... .......... .......... 5% 64.7M 13s\n", + " 31900K .......... .......... .......... .......... .......... 5% 62.1M 13s\n", + " 31950K .......... .......... .......... .......... .......... 5% 64.3M 13s\n", + " 32000K .......... .......... .......... .......... .......... 5% 56.2M 13s\n", + " 32050K .......... .......... .......... .......... .......... 5% 68.2M 13s\n", + " 32100K .......... .......... .......... .......... .......... 5% 58.5M 13s\n", + " 32150K .......... .......... .......... .......... .......... 5% 57.4M 13s\n", + " 32200K .......... .......... .......... .......... .......... 5% 41.4M 13s\n", + " 32250K .......... .......... .......... .......... .......... 5% 47.2M 13s\n", + " 32300K .......... .......... .......... .......... .......... 5% 46.8M 13s\n", + " 32350K .......... .......... .......... .......... .......... 5% 45.2M 13s\n", + " 32400K .......... .......... .......... .......... .......... 5% 44.5M 13s\n", + " 32450K .......... .......... .......... .......... .......... 5% 45.7M 13s\n", + " 32500K .......... .......... .......... .......... .......... 5% 46.4M 13s\n", + " 32550K .......... .......... .......... .......... .......... 5% 48.1M 13s\n", + " 32600K .......... .......... .......... .......... .......... 5% 37.6M 13s\n", + " 32650K .......... .......... .......... .......... .......... 5% 50.3M 13s\n", + " 32700K .......... .......... .......... .......... .......... 5% 54.6M 13s\n", + " 32750K .......... .......... .......... .......... .......... 5% 52.4M 13s\n", + " 32800K .......... .......... .......... .......... .......... 5% 58.8M 13s\n", + " 32850K .......... .......... .......... .......... .......... 5% 45.0M 13s\n", + " 32900K .......... .......... .......... .......... .......... 5% 56.1M 13s\n", + " 32950K .......... .......... .......... .......... .......... 5% 53.1M 13s\n", + " 33000K .......... .......... .......... .......... .......... 5% 38.0M 13s\n", + " 33050K .......... .......... .......... .......... .......... 5% 51.9M 13s\n", + " 33100K .......... .......... .......... .......... .......... 5% 55.1M 13s\n", + " 33150K .......... .......... .......... .......... .......... 5% 52.1M 13s\n", + " 33200K .......... .......... .......... .......... .......... 5% 47.0M 13s\n", + " 33250K .......... .......... .......... .......... .......... 5% 59.9M 13s\n", + " 33300K .......... .......... .......... .......... .......... 5% 66.3M 13s\n", + " 33350K .......... .......... .......... .......... .......... 5% 57.7M 13s\n", + " 33400K .......... .......... .......... .......... .......... 5% 4.44M 13s\n", + " 33450K .......... .......... .......... .......... .......... 5% 65.7M 13s\n", + " 33500K .......... .......... .......... .......... .......... 5% 69.2M 13s\n", + " 33550K .......... .......... .......... .......... .......... 5% 67.0M 13s\n", + " 33600K .......... .......... .......... .......... .......... 5% 58.1M 13s\n", + " 33650K .......... .......... .......... .......... .......... 5% 66.2M 13s\n", + " 33700K .......... .......... .......... .......... .......... 5% 59.5M 13s\n", + " 33750K .......... .......... .......... .......... .......... 5% 60.6M 13s\n", + " 33800K .......... .......... .......... .......... .......... 5% 58.3M 13s\n", + " 33850K .......... .......... .......... .......... .......... 5% 70.2M 13s\n", + " 33900K .......... .......... .......... .......... .......... 5% 55.0M 13s\n", + " 33950K .......... .......... .......... .......... .......... 5% 62.2M 13s\n", + " 34000K .......... .......... .......... .......... .......... 5% 46.3M 13s\n", + " 34050K .......... .......... .......... .......... .......... 5% 74.6M 13s\n", + " 34100K .......... .......... .......... .......... .......... 5% 78.2M 13s\n", + " 34150K .......... .......... .......... .......... .......... 5% 66.9M 13s\n", + " 34200K .......... .......... .......... .......... .......... 5% 45.4M 13s\n", + " 34250K .......... .......... .......... .......... .......... 5% 49.5M 13s\n", + " 34300K .......... .......... .......... .......... .......... 5% 74.1M 13s\n", + " 34350K .......... .......... .......... .......... .......... 5% 74.6M 13s\n", + " 34400K .......... .......... .......... .......... .......... 5% 59.9M 13s\n", + " 34450K .......... .......... .......... .......... .......... 5% 51.5M 13s\n", + " 34500K .......... .......... .......... .......... .......... 5% 46.8M 13s\n", + " 34550K .......... .......... .......... .......... .......... 5% 60.6M 13s\n", + " 34600K .......... .......... .......... .......... .......... 5% 60.6M 13s\n", + " 34650K .......... .......... .......... .......... .......... 5% 76.9M 13s\n", + " 34700K .......... .......... .......... .......... .......... 5% 53.7M 13s\n", + " 34750K .......... .......... .......... .......... .......... 5% 46.2M 13s\n", + " 34800K .......... .......... .......... .......... .......... 5% 52.9M 13s\n", + " 34850K .......... .......... .......... .......... .......... 5% 68.9M 13s\n", + " 34900K .......... .......... .......... .......... .......... 5% 69.2M 13s\n", + " 34950K .......... .......... .......... .......... .......... 5% 62.7M 13s\n", + " 35000K .......... .......... .......... .......... .......... 5% 43.3M 13s\n", + " 35050K .......... .......... .......... .......... .......... 5% 63.4M 13s\n", + " 35100K .......... .......... .......... .......... .......... 5% 65.9M 13s\n", + " 35150K .......... .......... .......... .......... .......... 5% 72.4M 13s\n", + " 35200K .......... .......... .......... .......... .......... 5% 67.7M 13s\n", + " 35250K .......... .......... .......... .......... .......... 5% 69.4M 13s\n", + " 35300K .......... .......... .......... .......... .......... 5% 68.2M 13s\n", + " 35350K .......... .......... .......... .......... .......... 5% 76.5M 13s\n", + " 35400K .......... .......... .......... .......... .......... 5% 55.3M 13s\n", + " 35450K .......... .......... .......... .......... .......... 5% 71.8M 13s\n", + " 35500K .......... .......... .......... .......... .......... 5% 74.1M 13s\n", + " 35550K .......... .......... .......... .......... .......... 5% 62.1M 13s\n", + " 35600K .......... .......... .......... .......... .......... 5% 59.8M 13s\n", + " 35650K .......... .......... .......... .......... .......... 6% 59.2M 13s\n", + " 35700K .......... .......... .......... .......... .......... 6% 47.6M 13s\n", + " 35750K .......... .......... .......... .......... .......... 6% 65.5M 13s\n", + " 35800K .......... .......... .......... .......... .......... 6% 9.34M 13s\n", + " 35850K .......... .......... .......... .......... .......... 6% 60.5M 13s\n", + " 35900K .......... .......... .......... .......... .......... 6% 69.8M 13s\n", + " 35950K .......... .......... .......... .......... .......... 6% 75.1M 13s\n", + " 36000K .......... .......... .......... .......... .......... 6% 67.4M 13s\n", + " 36050K .......... .......... .......... .......... .......... 6% 70.1M 13s\n", + " 36100K .......... .......... .......... .......... .......... 6% 77.9M 13s\n", + " 36150K .......... .......... .......... .......... .......... 6% 54.3M 13s\n", + " 36200K .......... .......... .......... .......... .......... 6% 35.2M 13s\n", + " 36250K .......... .......... .......... .......... .......... 6% 70.1M 13s\n", + " 36300K .......... .......... .......... .......... .......... 6% 70.6M 13s\n", + " 36350K .......... .......... .......... .......... .......... 6% 62.3M 13s\n", + " 36400K .......... .......... .......... .......... .......... 6% 44.9M 13s\n", + " 36450K .......... .......... .......... .......... .......... 6% 45.0M 13s\n", + " 36500K .......... .......... .......... .......... .......... 6% 50.9M 13s\n", + " 36550K .......... .......... .......... .......... .......... 6% 67.0M 13s\n", + " 36600K .......... .......... .......... .......... .......... 6% 46.9M 13s\n", + " 36650K .......... .......... .......... .......... .......... 6% 49.0M 13s\n", + " 36700K .......... .......... .......... .......... .......... 6% 52.2M 13s\n", + " 36750K .......... .......... .......... .......... .......... 6% 64.6M 13s\n", + " 36800K .......... .......... .......... .......... .......... 6% 60.1M 13s\n", + " 36850K .......... .......... .......... .......... .......... 6% 60.5M 13s\n", + " 36900K .......... .......... .......... .......... .......... 6% 50.6M 13s\n", + " 36950K .......... .......... .......... .......... .......... 6% 69.8M 13s\n", + " 37000K .......... .......... .......... .......... .......... 6% 61.8M 13s\n", + " 37050K .......... .......... .......... .......... .......... 6% 68.8M 13s\n", + " 37100K .......... .......... .......... .......... .......... 6% 62.0M 13s\n", + " 37150K .......... .......... .......... .......... .......... 6% 68.9M 13s\n", + " 37200K .......... .......... .......... .......... .......... 6% 61.4M 13s\n", + " 37250K .......... .......... .......... .......... .......... 6% 70.0M 13s\n", + " 37300K .......... .......... .......... .......... .......... 6% 66.4M 13s\n", + " 37350K .......... .......... .......... .......... .......... 6% 66.9M 13s\n", + " 37400K .......... .......... .......... .......... .......... 6% 60.7M 13s\n", + " 37450K .......... .......... .......... .......... .......... 6% 70.9M 13s\n", + " 37500K .......... .......... .......... .......... .......... 6% 74.2M 13s\n", + " 37550K .......... .......... .......... .......... .......... 6% 81.2M 13s\n", + " 37600K .......... .......... .......... .......... .......... 6% 67.7M 13s\n", + " 37650K .......... .......... .......... .......... .......... 6% 65.3M 13s\n", + " 37700K .......... .......... .......... .......... .......... 6% 71.1M 13s\n", + " 37750K .......... .......... .......... .......... .......... 6% 78.5M 13s\n", + " 37800K .......... .......... .......... .......... .......... 6% 63.3M 13s\n", + " 37850K .......... .......... .......... .......... .......... 6% 67.6M 13s\n", + " 37900K .......... .......... .......... .......... .......... 6% 71.6M 13s\n", + " 37950K .......... .......... .......... .......... .......... 6% 62.8M 13s\n", + " 38000K .......... .......... .......... .......... .......... 6% 48.4M 13s\n", + " 38050K .......... .......... .......... .......... .......... 6% 50.9M 13s\n", + " 38100K .......... .......... .......... .......... .......... 6% 57.9M 13s\n", + " 38150K .......... .......... .......... .......... .......... 6% 69.5M 13s\n", + " 38200K .......... .......... .......... .......... .......... 6% 66.4M 13s\n", + " 38250K .......... .......... .......... .......... .......... 6% 72.8M 13s\n", + " 38300K .......... .......... .......... .......... .......... 6% 71.2M 13s\n", + " 38350K .......... .......... .......... .......... .......... 6% 77.0M 13s\n", + " 38400K .......... .......... .......... .......... .......... 6% 68.5M 13s\n", + " 38450K .......... .......... .......... .......... .......... 6% 69.1M 13s\n", + " 38500K .......... .......... .......... .......... .......... 6% 79.3M 13s\n", + " 38550K .......... .......... .......... .......... .......... 6% 76.5M 13s\n", + " 38600K .......... .......... .......... .......... .......... 6% 61.1M 13s\n", + " 38650K .......... .......... .......... .......... .......... 6% 80.6M 13s\n", + " 38700K .......... .......... .......... .......... .......... 6% 77.0M 13s\n", + " 38750K .......... .......... .......... .......... .......... 6% 65.3M 13s\n", + " 38800K .......... .......... .......... .......... .......... 6% 54.2M 13s\n", + " 38850K .......... .......... .......... .......... .......... 6% 56.7M 13s\n", + " 38900K .......... .......... .......... .......... .......... 6% 47.6M 13s\n", + " 38950K .......... .......... .......... .......... .......... 6% 48.4M 13s\n", + " 39000K .......... .......... .......... .......... .......... 6% 31.1M 13s\n", + " 39050K .......... .......... .......... .......... .......... 6% 58.1M 13s\n", + " 39100K .......... .......... .......... .......... .......... 6% 61.9M 13s\n", + " 39150K .......... .......... .......... .......... .......... 6% 41.1M 13s\n", + " 39200K .......... .......... .......... .......... .......... 6% 46.9M 13s\n", + " 39250K .......... .......... .......... .......... .......... 6% 58.8M 13s\n", + " 39300K .......... .......... .......... .......... .......... 6% 53.9M 13s\n", + " 39350K .......... .......... .......... .......... .......... 6% 54.1M 13s\n", + " 39400K .......... .......... .......... .......... .......... 6% 41.6M 13s\n", + " 39450K .......... .......... .......... .......... .......... 6% 47.6M 13s\n", + " 39500K .......... .......... .......... .......... .......... 6% 45.4M 13s\n", + " 39550K .......... .......... .......... .......... .......... 6% 45.5M 13s\n", + " 39600K .......... .......... .......... .......... .......... 6% 45.5M 13s\n", + " 39650K .......... .......... .......... .......... .......... 6% 48.3M 13s\n", + " 39700K .......... .......... .......... .......... .......... 6% 46.7M 13s\n", + " 39750K .......... .......... .......... .......... .......... 6% 65.9M 13s\n", + " 39800K .......... .......... .......... .......... .......... 6% 63.7M 13s\n", + " 39850K .......... .......... .......... .......... .......... 6% 77.0M 13s\n", + " 39900K .......... .......... .......... .......... .......... 6% 73.9M 13s\n", + " 39950K .......... .......... .......... .......... .......... 6% 75.2M 13s\n", + " 40000K .......... .......... .......... .......... .......... 6% 73.9M 13s\n", + " 40050K .......... .......... .......... .......... .......... 6% 65.0M 13s\n", + " 40100K .......... .......... .......... .......... .......... 6% 65.3M 13s\n", + " 40150K .......... .......... .......... .......... .......... 6% 45.4M 13s\n", + " 40200K .......... .......... .......... .......... .......... 6% 33.2M 13s\n", + " 40250K .......... .......... .......... .......... .......... 6% 44.3M 13s\n", + " 40300K .......... .......... .......... .......... .......... 6% 42.6M 13s\n", + " 40350K .......... .......... .......... .......... .......... 6% 41.7M 13s\n", + " 40400K .......... .......... .......... .......... .......... 6% 35.6M 13s\n", + " 40450K .......... .......... .......... .......... .......... 6% 63.2M 13s\n", + " 40500K .......... .......... .......... .......... .......... 6% 78.4M 13s\n", + " 40550K .......... .......... .......... .......... .......... 6% 67.2M 13s\n", + " 40600K .......... .......... .......... .......... .......... 6% 52.3M 13s\n", + " 40650K .......... .......... .......... .......... .......... 6% 45.3M 13s\n", + " 40700K .......... .......... .......... .......... .......... 6% 45.9M 13s\n", + " 40750K .......... .......... .......... .......... .......... 6% 51.4M 13s\n", + " 40800K .......... .......... .......... .......... .......... 6% 47.1M 13s\n", + " 40850K .......... .......... .......... .......... .......... 6% 47.6M 13s\n", + " 40900K .......... .......... .......... .......... .......... 6% 35.8M 13s\n", + " 40950K .......... .......... .......... .......... .......... 6% 48.8M 13s\n", + " 41000K .......... .......... .......... .......... .......... 6% 41.6M 13s\n", + " 41050K .......... .......... .......... .......... .......... 6% 56.1M 13s\n", + " 41100K .......... .......... .......... .......... .......... 6% 62.5M 13s\n", + " 41150K .......... .......... .......... .......... .......... 6% 67.9M 13s\n", + " 41200K .......... .......... .......... .......... .......... 6% 57.5M 12s\n", + " 41250K .......... .......... .......... .......... .......... 6% 66.8M 12s\n", + " 41300K .......... .......... .......... .......... .......... 6% 76.7M 12s\n", + " 41350K .......... .......... .......... .......... .......... 6% 70.1M 12s\n", + " 41400K .......... .......... .......... .......... .......... 6% 62.1M 12s\n", + " 41450K .......... .......... .......... .......... .......... 6% 63.7M 12s\n", + " 41500K .......... .......... .......... .......... .......... 6% 59.9M 12s\n", + " 41550K .......... .......... .......... .......... .......... 6% 70.7M 12s\n", + " 41600K .......... .......... .......... .......... .......... 7% 48.6M 12s\n", + " 41650K .......... .......... .......... .......... .......... 7% 71.6M 12s\n", + " 41700K .......... .......... .......... .......... .......... 7% 58.0M 12s\n", + " 41750K .......... .......... .......... .......... .......... 7% 71.9M 12s\n", + " 41800K .......... .......... .......... .......... .......... 7% 41.2M 12s\n", + " 41850K .......... .......... .......... .......... .......... 7% 46.2M 12s\n", + " 41900K .......... .......... .......... .......... .......... 7% 43.6M 12s\n", + " 41950K .......... .......... .......... .......... .......... 7% 47.3M 12s\n", + " 42000K .......... .......... .......... .......... .......... 7% 37.4M 12s\n", + " 42050K .......... .......... .......... .......... .......... 7% 26.6M 12s\n", + " 42100K .......... .......... .......... .......... .......... 7% 23.8M 12s\n", + " 42150K .......... .......... .......... .......... .......... 7% 24.7M 12s\n", + " 42200K .......... .......... .......... .......... .......... 7% 27.2M 12s\n", + " 42250K .......... .......... .......... .......... .......... 7% 29.3M 12s\n", + " 42300K .......... .......... .......... .......... .......... 7% 28.2M 12s\n", + " 42350K .......... .......... .......... .......... .......... 7% 45.0M 12s\n", + " 42400K .......... .......... .......... .......... .......... 7% 30.3M 12s\n", + " 42450K .......... .......... .......... .......... .......... 7% 49.2M 12s\n", + " 42500K .......... .......... .......... .......... .......... 7% 48.1M 12s\n", + " 42550K .......... .......... .......... .......... .......... 7% 51.3M 12s\n", + " 42600K .......... .......... .......... .......... .......... 7% 38.3M 12s\n", + " 42650K .......... .......... .......... .......... .......... 7% 70.4M 12s\n", + " 42700K .......... .......... .......... .......... .......... 7% 77.5M 12s\n", + " 42750K .......... .......... .......... .......... .......... 7% 57.6M 12s\n", + " 42800K .......... .......... .......... .......... .......... 7% 43.2M 12s\n", + " 42850K .......... .......... .......... .......... .......... 7% 54.6M 12s\n", + " 42900K .......... .......... .......... .......... .......... 7% 48.8M 12s\n", + " 42950K .......... .......... .......... .......... .......... 7% 44.4M 12s\n", + " 43000K .......... .......... .......... .......... .......... 7% 36.9M 12s\n", + " 43050K .......... .......... .......... .......... .......... 7% 69.6M 12s\n", + " 43100K .......... .......... .......... .......... .......... 7% 57.1M 12s\n", + " 43150K .......... .......... .......... .......... .......... 7% 56.9M 12s\n", + " 43200K .......... .......... .......... .......... .......... 7% 38.4M 12s\n", + " 43250K .......... .......... .......... .......... .......... 7% 42.8M 12s\n", + " 43300K .......... .......... .......... .......... .......... 7% 51.3M 12s\n", + " 43350K .......... .......... .......... .......... .......... 7% 58.6M 12s\n", + " 43400K .......... .......... .......... .......... .......... 7% 46.1M 12s\n", + " 43450K .......... .......... .......... .......... .......... 7% 72.3M 12s\n", + " 43500K .......... .......... .......... .......... .......... 7% 75.0M 12s\n", + " 43550K .......... .......... .......... .......... .......... 7% 81.4M 12s\n", + " 43600K .......... .......... .......... .......... .......... 7% 51.3M 12s\n", + " 43650K .......... .......... .......... .......... .......... 7% 66.7M 12s\n", + " 43700K .......... .......... .......... .......... .......... 7% 61.6M 12s\n", + " 43750K .......... .......... .......... .......... .......... 7% 63.1M 12s\n", + " 43800K .......... .......... .......... .......... .......... 7% 62.5M 12s\n", + " 43850K .......... .......... .......... .......... .......... 7% 50.1M 12s\n", + " 43900K .......... .......... .......... .......... .......... 7% 63.6M 12s\n", + " 43950K .......... .......... .......... .......... .......... 7% 59.1M 12s\n", + " 44000K .......... .......... .......... .......... .......... 7% 50.2M 12s\n", + " 44050K .......... .......... .......... .......... .......... 7% 62.0M 12s\n", + " 44100K .......... .......... .......... .......... .......... 7% 51.6M 12s\n", + " 44150K .......... .......... .......... .......... .......... 7% 68.7M 12s\n", + " 44200K .......... .......... .......... .......... .......... 7% 30.8M 12s\n", + " 44250K .......... .......... .......... .......... .......... 7% 34.6M 12s\n", + " 44300K .......... .......... .......... .......... .......... 7% 32.4M 12s\n", + " 44350K .......... .......... .......... .......... .......... 7% 52.5M 12s\n", + " 44400K .......... .......... .......... .......... .......... 7% 38.8M 12s\n", + " 44450K .......... .......... .......... .......... .......... 7% 42.5M 12s\n", + " 44500K .......... .......... .......... .......... .......... 7% 46.2M 12s\n", + " 44550K .......... .......... .......... .......... .......... 7% 45.4M 12s\n", + " 44600K .......... .......... .......... .......... .......... 7% 32.3M 12s\n", + " 44650K .......... .......... .......... .......... .......... 7% 44.9M 12s\n", + " 44700K .......... .......... .......... .......... .......... 7% 39.5M 12s\n", + " 44750K .......... .......... .......... .......... .......... 7% 45.7M 12s\n", + " 44800K .......... .......... .......... .......... .......... 7% 56.6M 12s\n", + " 44850K .......... .......... .......... .......... .......... 7% 66.8M 12s\n", + " 44900K .......... .......... .......... .......... .......... 7% 53.3M 12s\n", + " 44950K .......... .......... .......... .......... .......... 7% 53.4M 12s\n", + " 45000K .......... .......... .......... .......... .......... 7% 36.2M 12s\n", + " 45050K .......... .......... .......... .......... .......... 7% 41.0M 12s\n", + " 45100K .......... .......... .......... .......... .......... 7% 37.5M 12s\n", + " 45150K .......... .......... .......... .......... .......... 7% 36.7M 12s\n", + " 45200K .......... .......... .......... .......... .......... 7% 59.6M 12s\n", + " 45250K .......... .......... .......... .......... .......... 7% 44.4M 12s\n", + " 45300K .......... .......... .......... .......... .......... 7% 43.4M 12s\n", + " 45350K .......... .......... .......... .......... .......... 7% 68.1M 12s\n", + " 45400K .......... .......... .......... .......... .......... 7% 48.9M 12s\n", + " 45450K .......... .......... .......... .......... .......... 7% 57.1M 12s\n", + " 45500K .......... .......... .......... .......... .......... 7% 62.5M 12s\n", + " 45550K .......... .......... .......... .......... .......... 7% 54.3M 12s\n", + " 45600K .......... .......... .......... .......... .......... 7% 44.6M 12s\n", + " 45650K .......... .......... .......... .......... .......... 7% 58.3M 12s\n", + " 45700K .......... .......... .......... .......... .......... 7% 64.7M 12s\n", + " 45750K .......... .......... .......... .......... .......... 7% 63.2M 12s\n", + " 45800K .......... .......... .......... .......... .......... 7% 53.2M 12s\n", + " 45850K .......... .......... .......... .......... .......... 7% 53.8M 12s\n", + " 45900K .......... .......... .......... .......... .......... 7% 62.5M 12s\n", + " 45950K .......... .......... .......... .......... .......... 7% 73.2M 12s\n", + " 46000K .......... .......... .......... .......... .......... 7% 58.7M 12s\n", + " 46050K .......... .......... .......... .......... .......... 7% 75.8M 12s\n", + " 46100K .......... .......... .......... .......... .......... 7% 59.2M 12s\n", + " 46150K .......... .......... .......... .......... .......... 7% 61.0M 12s\n", + " 46200K .......... .......... .......... .......... .......... 7% 62.1M 12s\n", + " 46250K .......... .......... .......... .......... .......... 7% 74.0M 12s\n", + " 46300K .......... .......... .......... .......... .......... 7% 64.4M 12s\n", + " 46350K .......... .......... .......... .......... .......... 7% 55.0M 12s\n", + " 46400K .......... .......... .......... .......... .......... 7% 51.6M 12s\n", + " 46450K .......... .......... .......... .......... .......... 7% 64.9M 12s\n", + " 46500K .......... .......... .......... .......... .......... 7% 60.0M 12s\n", + " 46550K .......... .......... .......... .......... .......... 7% 68.8M 12s\n", + " 46600K .......... .......... .......... .......... .......... 7% 45.5M 12s\n", + " 46650K .......... .......... .......... .......... .......... 7% 48.1M 12s\n", + " 46700K .......... .......... .......... .......... .......... 7% 73.6M 12s\n", + " 46750K .......... .......... .......... .......... .......... 7% 60.1M 12s\n", + " 46800K .......... .......... .......... .......... .......... 7% 64.8M 12s\n", + " 46850K .......... .......... .......... .......... .......... 7% 48.5M 12s\n", + " 46900K .......... .......... .......... .......... .......... 7% 61.6M 12s\n", + " 46950K .......... .......... .......... .......... .......... 7% 53.5M 12s\n", + " 47000K .......... .......... .......... .......... .......... 7% 51.8M 12s\n", + " 47050K .......... .......... .......... .......... .......... 7% 72.8M 12s\n", + " 47100K .......... .......... .......... .......... .......... 7% 53.4M 12s\n", + " 47150K .......... .......... .......... .......... .......... 7% 55.1M 12s\n", + " 47200K .......... .......... .......... .......... .......... 7% 55.8M 12s\n", + " 47250K .......... .......... .......... .......... .......... 7% 70.0M 12s\n", + " 47300K .......... .......... .......... .......... .......... 7% 66.4M 12s\n", + " 47350K .......... .......... .......... .......... .......... 7% 72.6M 12s\n", + " 47400K .......... .......... .......... .......... .......... 7% 44.0M 12s\n", + " 47450K .......... .......... .......... .......... .......... 7% 59.6M 12s\n", + " 47500K .......... .......... .......... .......... .......... 7% 59.8M 12s\n", + " 47550K .......... .......... .......... .......... .......... 8% 56.7M 12s\n", + " 47600K .......... .......... .......... .......... .......... 8% 59.2M 12s\n", + " 47650K .......... .......... .......... .......... .......... 8% 59.6M 12s\n", + " 47700K .......... .......... .......... .......... .......... 8% 45.8M 12s\n", + " 47750K .......... .......... .......... .......... .......... 8% 66.3M 12s\n", + " 47800K .......... .......... .......... .......... .......... 8% 53.3M 12s\n", + " 47850K .......... .......... .......... .......... .......... 8% 70.0M 12s\n", + " 47900K .......... .......... .......... .......... .......... 8% 64.2M 12s\n", + " 47950K .......... .......... .......... .......... .......... 8% 49.7M 12s\n", + " 48000K .......... .......... .......... .......... .......... 8% 59.4M 12s\n", + " 48050K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", + " 48100K .......... .......... .......... .......... .......... 8% 63.5M 12s\n", + " 48150K .......... .......... .......... .......... .......... 8% 56.4M 12s\n", + " 48200K .......... .......... .......... .......... .......... 8% 36.4M 12s\n", + " 48250K .......... .......... .......... .......... .......... 8% 64.1M 12s\n", + " 48300K .......... .......... .......... .......... .......... 8% 46.7M 12s\n", + " 48350K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", + " 48400K .......... .......... .......... .......... .......... 8% 41.0M 12s\n", + " 48450K .......... .......... .......... .......... .......... 8% 57.9M 12s\n", + " 48500K .......... .......... .......... .......... .......... 8% 74.2M 12s\n", + " 48550K .......... .......... .......... .......... .......... 8% 52.4M 12s\n", + " 48600K .......... .......... .......... .......... .......... 8% 59.1M 12s\n", + " 48650K .......... .......... .......... .......... .......... 8% 4.44M 12s\n", + " 48700K .......... .......... .......... .......... .......... 8% 57.9M 12s\n", + " 48750K .......... .......... .......... .......... .......... 8% 81.2M 12s\n", + " 48800K .......... .......... .......... .......... .......... 8% 69.6M 12s\n", + " 48850K .......... .......... .......... .......... .......... 8% 67.7M 12s\n", + " 48900K .......... .......... .......... .......... .......... 8% 71.8M 12s\n", + " 48950K .......... .......... .......... .......... .......... 8% 74.7M 12s\n", + " 49000K .......... .......... .......... .......... .......... 8% 49.0M 12s\n", + " 49050K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", + " 49100K .......... .......... .......... .......... .......... 8% 68.5M 12s\n", + " 49150K .......... .......... .......... .......... .......... 8% 61.4M 12s\n", + " 49200K .......... .......... .......... .......... .......... 8% 54.4M 12s\n", + " 49250K .......... .......... .......... .......... .......... 8% 69.7M 12s\n", + " 49300K .......... .......... .......... .......... .......... 8% 48.3M 12s\n", + " 49350K .......... .......... .......... .......... .......... 8% 62.4M 12s\n", + " 49400K .......... .......... .......... .......... .......... 8% 54.1M 12s\n", + " 49450K .......... .......... .......... .......... .......... 8% 51.8M 12s\n", + " 49500K .......... .......... .......... .......... .......... 8% 80.3M 12s\n", + " 49550K .......... .......... .......... .......... .......... 8% 48.4M 12s\n", + " 49600K .......... .......... .......... .......... .......... 8% 48.6M 12s\n", + " 49650K .......... .......... .......... .......... .......... 8% 61.2M 12s\n", + " 49700K .......... .......... .......... .......... .......... 8% 51.1M 12s\n", + " 49750K .......... .......... .......... .......... .......... 8% 59.6M 12s\n", + " 49800K .......... .......... .......... .......... .......... 8% 57.7M 12s\n", + " 49850K .......... .......... .......... .......... .......... 8% 64.8M 12s\n", + " 49900K .......... .......... .......... .......... .......... 8% 55.0M 12s\n", + " 49950K .......... .......... .......... .......... .......... 8% 54.4M 12s\n", + " 50000K .......... .......... .......... .......... .......... 8% 56.6M 12s\n", + " 50050K .......... .......... .......... .......... .......... 8% 60.5M 12s\n", + " 50100K .......... .......... .......... .......... .......... 8% 74.0M 12s\n", + " 50150K .......... .......... .......... .......... .......... 8% 49.6M 12s\n", + " 50200K .......... .......... .......... .......... .......... 8% 50.0M 12s\n", + " 50250K .......... .......... .......... .......... .......... 8% 69.5M 12s\n", + " 50300K .......... .......... .......... .......... .......... 8% 16.2M 12s\n", + " 50350K .......... .......... .......... .......... .......... 8% 54.9M 12s\n", + " 50400K .......... .......... .......... .......... .......... 8% 59.3M 12s\n", + " 50450K .......... .......... .......... .......... .......... 8% 71.9M 12s\n", + " 50500K .......... .......... .......... .......... .......... 8% 75.9M 12s\n", + " 50550K .......... .......... .......... .......... .......... 8% 70.7M 12s\n", + " 50600K .......... .......... .......... .......... .......... 8% 46.4M 12s\n", + " 50650K .......... .......... .......... .......... .......... 8% 50.5M 12s\n", + " 50700K .......... .......... .......... .......... .......... 8% 61.5M 12s\n", + " 50750K .......... .......... .......... .......... .......... 8% 63.9M 12s\n", + " 50800K .......... .......... .......... .......... .......... 8% 58.2M 12s\n", + " 50850K .......... .......... .......... .......... .......... 8% 50.6M 12s\n", + " 50900K .......... .......... .......... .......... .......... 8% 50.3M 12s\n", + " 50950K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", + " 51000K .......... .......... .......... .......... .......... 8% 60.6M 12s\n", + " 51050K .......... .......... .......... .......... .......... 8% 67.3M 12s\n", + " 51100K .......... .......... .......... .......... .......... 8% 70.5M 12s\n", + " 51150K .......... .......... .......... .......... .......... 8% 70.5M 12s\n", + " 51200K .......... .......... .......... .......... .......... 8% 66.0M 12s\n", + " 51250K .......... .......... .......... .......... .......... 8% 80.0M 12s\n", + " 51300K .......... .......... .......... .......... .......... 8% 71.6M 12s\n", + " 51350K .......... .......... .......... .......... .......... 8% 67.9M 12s\n", + " 51400K .......... .......... .......... .......... .......... 8% 46.5M 12s\n", + " 51450K .......... .......... .......... .......... .......... 8% 62.9M 12s\n", + " 51500K .......... .......... .......... .......... .......... 8% 54.3M 12s\n", + " 51550K .......... .......... .......... .......... .......... 8% 55.7M 12s\n", + " 51600K .......... .......... .......... .......... .......... 8% 59.9M 12s\n", + " 51650K .......... .......... .......... .......... .......... 8% 65.7M 12s\n", + " 51700K .......... .......... .......... .......... .......... 8% 56.1M 12s\n", + " 51750K .......... .......... .......... .......... .......... 8% 52.9M 12s\n", + " 51800K .......... .......... .......... .......... .......... 8% 39.2M 12s\n", + " 51850K .......... .......... .......... .......... .......... 8% 56.7M 12s\n", + " 51900K .......... .......... .......... .......... .......... 8% 77.7M 12s\n", + " 51950K .......... .......... .......... .......... .......... 8% 53.4M 12s\n", + " 52000K .......... .......... .......... .......... .......... 8% 48.4M 12s\n", + " 52050K .......... .......... .......... .......... .......... 8% 49.6M 12s\n", + " 52100K .......... .......... .......... .......... .......... 8% 62.7M 12s\n", + " 52150K .......... .......... .......... .......... .......... 8% 69.2M 12s\n", + " 52200K .......... .......... .......... .......... .......... 8% 40.1M 12s\n", " 52250K .......... .......... .......... .......... .......... 8% 53.6M 12s\n", - " 52300K .......... .......... .......... .......... .......... 8% 56.0M 12s\n", - " 52350K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", - " 52400K .......... .......... .......... .......... .......... 8% 42.2M 12s\n", - " 52450K .......... .......... .......... .......... .......... 8% 51.7M 12s\n", - " 52500K .......... .......... .......... .......... .......... 8% 66.5M 12s\n", - " 52550K .......... .......... .......... .......... .......... 8% 64.6M 12s\n", - " 52600K .......... .......... .......... .......... .......... 8% 55.4M 12s\n", - " 52650K .......... .......... .......... .......... .......... 8% 54.3M 12s\n", - " 52700K .......... .......... .......... .......... .......... 8% 47.6M 12s\n", - " 52750K .......... .......... .......... .......... .......... 8% 62.0M 12s\n", - " 52800K .......... .......... .......... .......... .......... 8% 51.7M 12s\n", - " 52850K .......... .......... .......... .......... .......... 8% 52.9M 12s\n", - " 52900K .......... .......... .......... .......... .......... 8% 42.6M 12s\n", - " 52950K .......... .......... .......... .......... .......... 8% 48.8M 12s\n", - " 53000K .......... .......... .......... .......... .......... 8% 43.3M 12s\n", - " 53050K .......... .......... .......... .......... .......... 8% 56.1M 12s\n", - " 53100K .......... .......... .......... .......... .......... 8% 49.4M 12s\n", - " 53150K .......... .......... .......... .......... .......... 8% 4.23M 13s\n", - " 53200K .......... .......... .......... .......... .......... 8% 56.6M 13s\n", - " 53250K .......... .......... .......... .......... .......... 8% 63.6M 13s\n", - " 53300K .......... .......... .......... .......... .......... 8% 62.9M 12s\n", - " 53350K .......... .......... .......... .......... .......... 8% 62.7M 12s\n", - " 53400K .......... .......... .......... .......... .......... 8% 52.5M 12s\n", - " 53450K .......... .......... .......... .......... .......... 8% 43.6M 12s\n", - " 53500K .......... .......... .......... .......... .......... 9% 52.4M 12s\n", - " 53550K .......... .......... .......... .......... .......... 9% 63.7M 12s\n", - " 53600K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", - " 53650K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", - " 53700K .......... .......... .......... .......... .......... 9% 53.7M 12s\n", - " 53750K .......... .......... .......... .......... .......... 9% 49.7M 12s\n", - " 53800K .......... .......... .......... .......... .......... 9% 49.1M 12s\n", - " 53850K .......... .......... .......... .......... .......... 9% 55.6M 12s\n", - " 53900K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", - " 53950K .......... .......... .......... .......... .......... 9% 51.9M 12s\n", - " 54000K .......... .......... .......... .......... .......... 9% 39.5M 12s\n", - " 54050K .......... .......... .......... .......... .......... 9% 60.6M 12s\n", - " 54100K .......... .......... .......... .......... .......... 9% 65.0M 12s\n", - " 54150K .......... .......... .......... .......... .......... 9% 66.2M 12s\n", - " 54200K .......... .......... .......... .......... .......... 9% 38.0M 12s\n", - " 54250K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", - " 54300K .......... .......... .......... .......... .......... 9% 58.6M 12s\n", - " 54350K .......... .......... .......... .......... .......... 9% 66.0M 12s\n", - " 54400K .......... .......... .......... .......... .......... 9% 60.8M 12s\n", - " 54450K .......... .......... .......... .......... .......... 9% 52.1M 12s\n", - " 54500K .......... .......... .......... .......... .......... 9% 49.7M 12s\n", - " 54550K .......... .......... .......... .......... .......... 9% 55.0M 12s\n", - " 54600K .......... .......... .......... .......... .......... 9% 55.7M 12s\n", - " 54650K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", - " 54700K .......... .......... .......... .......... .......... 9% 51.1M 12s\n", - " 54750K .......... .......... .......... .......... .......... 9% 57.2M 12s\n", - " 54800K .......... .......... .......... .......... .......... 9% 42.8M 12s\n", - " 54850K .......... .......... .......... .......... .......... 9% 63.9M 12s\n", - " 54900K .......... .......... .......... .......... .......... 9% 58.8M 12s\n", - " 54950K .......... .......... .......... .......... .......... 9% 47.6M 12s\n", - " 55000K .......... .......... .......... .......... .......... 9% 47.1M 12s\n", - " 55050K .......... .......... .......... .......... .......... 9% 59.2M 12s\n", - " 55100K .......... .......... .......... .......... .......... 9% 65.9M 12s\n", - " 55150K .......... .......... .......... .......... .......... 9% 63.5M 12s\n", - " 55200K .......... .......... .......... .......... .......... 9% 46.1M 12s\n", - " 55250K .......... .......... .......... .......... .......... 9% 61.9M 12s\n", - " 55300K .......... .......... .......... .......... .......... 9% 57.1M 12s\n", - " 55350K .......... .......... .......... .......... .......... 9% 61.9M 12s\n", - " 55400K .......... .......... .......... .......... .......... 9% 56.1M 12s\n", - " 55450K .......... .......... .......... .......... .......... 9% 54.2M 12s\n", - " 55500K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", - " 55550K .......... .......... .......... .......... .......... 9% 44.4M 12s\n", - " 55600K .......... .......... .......... .......... .......... 9% 4.92M 12s\n", - " 55650K .......... .......... .......... .......... .......... 9% 63.8M 12s\n", - " 55700K .......... .......... .......... .......... .......... 9% 68.9M 12s\n", - " 55750K .......... .......... .......... .......... .......... 9% 66.5M 12s\n", - " 55800K .......... .......... .......... .......... .......... 9% 59.3M 12s\n", - " 55850K .......... .......... .......... .......... .......... 9% 61.2M 12s\n", - " 55900K .......... .......... .......... .......... .......... 9% 49.9M 12s\n", - " 55950K .......... .......... .......... .......... .......... 9% 49.1M 12s\n", - " 56000K .......... .......... .......... .......... .......... 9% 7.25M 12s\n", - " 56050K .......... .......... .......... .......... .......... 9% 58.1M 12s\n", - " 56100K .......... .......... .......... .......... .......... 9% 20.6M 12s\n", - " 56150K .......... .......... .......... .......... .......... 9% 64.0M 12s\n", - " 56200K .......... .......... .......... .......... .......... 9% 45.1M 12s\n", - " 56250K .......... .......... .......... .......... .......... 9% 43.6M 12s\n", - " 56300K .......... .......... .......... .......... .......... 9% 62.2M 12s\n", - " 56350K .......... .......... .......... .......... .......... 9% 59.6M 12s\n", - " 56400K .......... .......... .......... .......... .......... 9% 53.2M 12s\n", - " 56450K .......... .......... .......... .......... .......... 9% 44.5M 12s\n", - " 56500K .......... .......... .......... .......... .......... 9% 45.7M 12s\n", - " 56550K .......... .......... .......... .......... .......... 9% 60.9M 12s\n", - " 56600K .......... .......... .......... .......... .......... 9% 57.9M 12s\n", - " 56650K .......... .......... .......... .......... .......... 9% 63.3M 12s\n", - " 56700K .......... .......... .......... .......... .......... 9% 46.9M 12s\n", - " 56750K .......... .......... .......... .......... .......... 9% 44.4M 12s\n", - " 56800K .......... .......... .......... .......... .......... 9% 59.9M 12s\n", - " 56850K .......... .......... .......... .......... .......... 9% 65.9M 12s\n", - " 56900K .......... .......... .......... .......... .......... 9% 69.0M 12s\n", - " 56950K .......... .......... .......... .......... .......... 9% 56.8M 12s\n", - " 57000K .......... .......... .......... .......... .......... 9% 42.4M 12s\n", - " 57050K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", - " 57100K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", - " 57150K .......... .......... .......... .......... .......... 9% 69.2M 12s\n", - " 57200K .......... .......... .......... .......... .......... 9% 58.3M 12s\n", - " 57250K .......... .......... .......... .......... .......... 9% 52.8M 12s\n", - " 57300K .......... .......... .......... .......... .......... 9% 47.3M 12s\n", - " 57350K .......... .......... .......... .......... .......... 9% 51.9M 12s\n", - " 57400K .......... .......... .......... .......... .......... 9% 55.2M 12s\n", - " 57450K .......... .......... .......... .......... .......... 9% 66.2M 12s\n", - " 57500K .......... .......... .......... .......... .......... 9% 50.2M 12s\n", - " 57550K .......... .......... .......... .......... .......... 9% 48.2M 12s\n", - " 57600K .......... .......... .......... .......... .......... 9% 46.9M 12s\n", - " 57650K .......... .......... .......... .......... .......... 9% 60.2M 12s\n", - " 57700K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", - " 57750K .......... .......... .......... .......... .......... 9% 52.1M 12s\n", - " 57800K .......... .......... .......... .......... .......... 9% 44.2M 12s\n", - " 57850K .......... .......... .......... .......... .......... 9% 51.3M 12s\n", - " 57900K .......... .......... .......... .......... .......... 9% 62.3M 12s\n", - " 57950K .......... .......... .......... .......... .......... 9% 68.1M 12s\n", - " 58000K .......... .......... .......... .......... .......... 9% 51.8M 12s\n", - " 58050K .......... .......... .......... .......... .......... 9% 52.4M 12s\n", - " 58100K .......... .......... .......... .......... .......... 9% 51.6M 12s\n", - " 58150K .......... .......... .......... .......... .......... 9% 63.4M 12s\n", - " 58200K .......... .......... .......... .......... .......... 9% 54.6M 12s\n", - " 58250K .......... .......... .......... .......... .......... 9% 58.3M 12s\n", - " 58300K .......... .......... .......... .......... .......... 9% 44.8M 12s\n", - " 58350K .......... .......... .......... .......... .......... 9% 44.1M 12s\n", - " 58400K .......... .......... .......... .......... .......... 9% 57.5M 12s\n", - " 58450K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", - " 58500K .......... .......... .......... .......... .......... 9% 53.9M 12s\n", - " 58550K .......... .......... .......... .......... .......... 9% 58.2M 12s\n", - " 58600K .......... .......... .......... .......... .......... 9% 44.0M 12s\n", - " 58650K .......... .......... .......... .......... .......... 9% 62.0M 12s\n", - " 58700K .......... .......... .......... .......... .......... 9% 68.1M 12s\n", - " 58750K .......... .......... .......... .......... .......... 9% 62.1M 12s\n", - " 58800K .......... .......... .......... .......... .......... 9% 55.3M 12s\n", - " 58850K .......... .......... .......... .......... .......... 9% 56.4M 12s\n", - " 58900K .......... .......... .......... .......... .......... 9% 60.0M 12s\n", - " 58950K .......... .......... .......... .......... .......... 9% 5.45M 12s\n", - " 59000K .......... .......... .......... .......... .......... 9% 58.8M 12s\n", - " 59050K .......... .......... .......... .......... .......... 9% 64.3M 12s\n", - " 59100K .......... .......... .......... .......... .......... 9% 66.7M 12s\n", - " 59150K .......... .......... .......... .......... .......... 9% 20.1M 12s\n", - " 59200K .......... .......... .......... .......... .......... 9% 45.3M 12s\n", - " 59250K .......... .......... .......... .......... .......... 9% 49.0M 12s\n", - " 59300K .......... .......... .......... .......... .......... 9% 60.4M 12s\n", - " 59350K .......... .......... .......... .......... .......... 9% 63.6M 12s\n", - " 59400K .......... .......... .......... .......... .......... 9% 41.4M 12s\n", - " 59450K .......... .......... .......... .......... .......... 10% 53.0M 12s\n", + " 52300K .......... .......... .......... .......... .......... 8% 50.9M 12s\n", + " 52350K .......... .......... .......... .......... .......... 8% 64.0M 12s\n", + " 52400K .......... .......... .......... .......... .......... 8% 60.1M 12s\n", + " 52450K .......... .......... .......... .......... .......... 8% 48.0M 12s\n", + " 52500K .......... .......... .......... .......... .......... 8% 58.8M 12s\n", + " 52550K .......... .......... .......... .......... .......... 8% 70.7M 12s\n", + " 52600K .......... .......... .......... .......... .......... 8% 47.4M 12s\n", + " 52650K .......... .......... .......... .......... .......... 8% 72.5M 12s\n", + " 52700K .......... .......... .......... .......... .......... 8% 71.8M 12s\n", + " 52750K .......... .......... .......... .......... .......... 8% 71.8M 12s\n", + " 52800K .......... .......... .......... .......... .......... 8% 60.0M 12s\n", + " 52850K .......... .......... .......... .......... .......... 8% 80.7M 12s\n", + " 52900K .......... .......... .......... .......... .......... 8% 71.7M 12s\n", + " 52950K .......... .......... .......... .......... .......... 8% 67.0M 12s\n", + " 53000K .......... .......... .......... .......... .......... 8% 53.0M 12s\n", + " 53050K .......... .......... .......... .......... .......... 8% 70.2M 12s\n", + " 53100K .......... .......... .......... .......... .......... 8% 45.2M 12s\n", + " 53150K .......... .......... .......... .......... .......... 8% 47.4M 12s\n", + " 53200K .......... .......... .......... .......... .......... 8% 40.5M 12s\n", + " 53250K .......... .......... .......... .......... .......... 8% 58.6M 12s\n", + " 53300K .......... .......... .......... .......... .......... 8% 63.4M 12s\n", + " 53350K .......... .......... .......... .......... .......... 8% 59.0M 12s\n", + " 53400K .......... .......... .......... .......... .......... 8% 37.6M 12s\n", + " 53450K .......... .......... .......... .......... .......... 8% 56.8M 12s\n", + " 53500K .......... .......... .......... .......... .......... 9% 70.1M 12s\n", + " 53550K .......... .......... .......... .......... .......... 9% 63.1M 12s\n", + " 53600K .......... .......... .......... .......... .......... 9% 62.5M 12s\n", + " 53650K .......... .......... .......... .......... .......... 9% 74.3M 12s\n", + " 53700K .......... .......... .......... .......... .......... 9% 70.9M 12s\n", + " 53750K .......... .......... .......... .......... .......... 9% 69.2M 12s\n", + " 53800K .......... .......... .......... .......... .......... 9% 65.2M 12s\n", + " 53850K .......... .......... .......... .......... .......... 9% 67.6M 12s\n", + " 53900K .......... .......... .......... .......... .......... 9% 68.9M 12s\n", + " 53950K .......... .......... .......... .......... .......... 9% 71.6M 12s\n", + " 54000K .......... .......... .......... .......... .......... 9% 67.1M 12s\n", + " 54050K .......... .......... .......... .......... .......... 9% 74.7M 12s\n", + " 54100K .......... .......... .......... .......... .......... 9% 56.4M 12s\n", + " 54150K .......... .......... .......... .......... .......... 9% 58.8M 12s\n", + " 54200K .......... .......... .......... .......... .......... 9% 50.0M 12s\n", + " 54250K .......... .......... .......... .......... .......... 9% 61.5M 12s\n", + " 54300K .......... .......... .......... .......... .......... 9% 73.5M 12s\n", + " 54350K .......... .......... .......... .......... .......... 9% 63.3M 12s\n", + " 54400K .......... .......... .......... .......... .......... 9% 45.9M 12s\n", + " 54450K .......... .......... .......... .......... .......... 9% 51.0M 12s\n", + " 54500K .......... .......... .......... .......... .......... 9% 37.6M 12s\n", + " 54550K .......... .......... .......... .......... .......... 9% 44.2M 12s\n", + " 54600K .......... .......... .......... .......... .......... 9% 35.6M 12s\n", + " 54650K .......... .......... .......... .......... .......... 9% 54.3M 12s\n", + " 54700K .......... .......... .......... .......... .......... 9% 41.2M 12s\n", + " 54750K .......... .......... .......... .......... .......... 9% 32.8M 12s\n", + " 54800K .......... .......... .......... .......... .......... 9% 28.1M 12s\n", + " 54850K .......... .......... .......... .......... .......... 9% 34.6M 12s\n", + " 54900K .......... .......... .......... .......... .......... 9% 31.6M 12s\n", + " 54950K .......... .......... .......... .......... .......... 9% 34.1M 12s\n", + " 55000K .......... .......... .......... .......... .......... 9% 25.4M 12s\n", + " 55050K .......... .......... .......... .......... .......... 9% 33.3M 12s\n", + " 55100K .......... .......... .......... .......... .......... 9% 33.7M 12s\n", + " 55150K .......... .......... .......... .......... .......... 9% 33.7M 12s\n", + " 55200K .......... .......... .......... .......... .......... 9% 33.2M 12s\n", + " 55250K .......... .......... .......... .......... .......... 9% 38.4M 12s\n", + " 55300K .......... .......... .......... .......... .......... 9% 41.8M 12s\n", + " 55350K .......... .......... .......... .......... .......... 9% 54.0M 12s\n", + " 55400K .......... .......... .......... .......... .......... 9% 55.4M 12s\n", + " 55450K .......... .......... .......... .......... .......... 9% 66.0M 12s\n", + " 55500K .......... .......... .......... .......... .......... 9% 66.2M 12s\n", + " 55550K .......... .......... .......... .......... .......... 9% 45.6M 12s\n", + " 55600K .......... .......... .......... .......... .......... 9% 33.3M 12s\n", + " 55650K .......... .......... .......... .......... .......... 9% 34.4M 12s\n", + " 55700K .......... .......... .......... .......... .......... 9% 54.2M 12s\n", + " 55750K .......... .......... .......... .......... .......... 9% 63.4M 12s\n", + " 55800K .......... .......... .......... .......... .......... 9% 53.0M 12s\n", + " 55850K .......... .......... .......... .......... .......... 9% 71.6M 12s\n", + " 55900K .......... .......... .......... .......... .......... 9% 41.0M 12s\n", + " 55950K .......... .......... .......... .......... .......... 9% 27.3M 12s\n", + " 56000K .......... .......... .......... .......... .......... 9% 39.9M 12s\n", + " 56050K .......... .......... .......... .......... .......... 9% 70.4M 12s\n", + " 56100K .......... .......... .......... .......... .......... 9% 74.1M 12s\n", + " 56150K .......... .......... .......... .......... .......... 9% 60.8M 12s\n", + " 56200K .......... .......... .......... .......... .......... 9% 49.8M 12s\n", + " 56250K .......... .......... .......... .......... .......... 9% 68.9M 12s\n", + " 56300K .......... .......... .......... .......... .......... 9% 63.1M 12s\n", + " 56350K .......... .......... .......... .......... .......... 9% 68.3M 12s\n", + " 56400K .......... .......... .......... .......... .......... 9% 55.8M 12s\n", + " 56450K .......... .......... .......... .......... .......... 9% 57.1M 12s\n", + " 56500K .......... .......... .......... .......... .......... 9% 61.3M 12s\n", + " 56550K .......... .......... .......... .......... .......... 9% 62.1M 12s\n", + " 56600K .......... .......... .......... .......... .......... 9% 49.1M 12s\n", + " 56650K .......... .......... .......... .......... .......... 9% 50.1M 12s\n", + " 56700K .......... .......... .......... .......... .......... 9% 51.2M 12s\n", + " 56750K .......... .......... .......... .......... .......... 9% 73.6M 12s\n", + " 56800K .......... .......... .......... .......... .......... 9% 56.3M 12s\n", + " 56850K .......... .......... .......... .......... .......... 9% 55.3M 12s\n", + " 56900K .......... .......... .......... .......... .......... 9% 55.7M 12s\n", + " 56950K .......... .......... .......... .......... .......... 9% 55.9M 12s\n", + " 57000K .......... .......... .......... .......... .......... 9% 50.5M 12s\n", + " 57050K .......... .......... .......... .......... .......... 9% 65.6M 12s\n", + " 57100K .......... .......... .......... .......... .......... 9% 52.6M 12s\n", + " 57150K .......... .......... .......... .......... .......... 9% 67.1M 12s\n", + " 57200K .......... .......... .......... .......... .......... 9% 47.9M 12s\n", + " 57250K .......... .......... .......... .......... .......... 9% 60.0M 12s\n", + " 57300K .......... .......... .......... .......... .......... 9% 66.5M 12s\n", + " 57350K .......... .......... .......... .......... .......... 9% 65.5M 12s\n", + " 57400K .......... .......... .......... .......... .......... 9% 42.2M 12s\n", + " 57450K .......... .......... .......... .......... .......... 9% 69.8M 12s\n", + " 57500K .......... .......... .......... .......... .......... 9% 64.3M 12s\n", + " 57550K .......... .......... .......... .......... .......... 9% 68.4M 12s\n", + " 57600K .......... .......... .......... .......... .......... 9% 50.8M 12s\n", + " 57650K .......... .......... .......... .......... .......... 9% 48.7M 12s\n", + " 57700K .......... .......... .......... .......... .......... 9% 52.7M 12s\n", + " 57750K .......... .......... .......... .......... .......... 9% 61.4M 12s\n", + " 57800K .......... .......... .......... .......... .......... 9% 53.5M 12s\n", + " 57850K .......... .......... .......... .......... .......... 9% 48.6M 12s\n", + " 57900K .......... .......... .......... .......... .......... 9% 59.0M 12s\n", + " 57950K .......... .......... .......... .......... .......... 9% 49.3M 12s\n", + " 58000K .......... .......... .......... .......... .......... 9% 45.5M 12s\n", + " 58050K .......... .......... .......... .......... .......... 9% 53.6M 12s\n", + " 58100K .......... .......... .......... .......... .......... 9% 46.3M 12s\n", + " 58150K .......... .......... .......... .......... .......... 9% 65.4M 12s\n", + " 58200K .......... .......... .......... .......... .......... 9% 46.5M 12s\n", + " 58250K .......... .......... .......... .......... .......... 9% 53.6M 12s\n", + " 58300K .......... .......... .......... .......... .......... 9% 59.0M 12s\n", + " 58350K .......... .......... .......... .......... .......... 9% 48.6M 12s\n", + " 58400K .......... .......... .......... .......... .......... 9% 59.2M 12s\n", + " 58450K .......... .......... .......... .......... .......... 9% 44.6M 12s\n", + " 58500K .......... .......... .......... .......... .......... 9% 69.9M 12s\n", + " 58550K .......... .......... .......... .......... .......... 9% 62.0M 12s\n", + " 58600K .......... .......... .......... .......... .......... 9% 48.3M 12s\n", + " 58650K .......... .......... .......... .......... .......... 9% 71.4M 12s\n", + " 58700K .......... .......... .......... .......... .......... 9% 6.15M 12s\n", + " 58750K .......... .......... .......... .......... .......... 9% 66.0M 12s\n", + " 58800K .......... .......... .......... .......... .......... 9% 69.2M 12s\n", + " 58850K .......... .......... .......... .......... .......... 9% 64.0M 12s\n", + " 58900K .......... .......... .......... .......... .......... 9% 69.7M 12s\n", + " 58950K .......... .......... .......... .......... .......... 9% 69.1M 12s\n", + " 59000K .......... .......... .......... .......... .......... 9% 42.9M 12s\n", + " 59050K .......... .......... .......... .......... .......... 9% 73.2M 12s\n", + " 59100K .......... .......... .......... .......... .......... 9% 65.0M 12s\n", + " 59150K .......... .......... .......... .......... .......... 9% 65.2M 12s\n", + " 59200K .......... .......... .......... .......... .......... 9% 49.8M 12s\n", + " 59250K .......... .......... .......... .......... .......... 9% 58.3M 12s\n", + " 59300K .......... .......... .......... .......... .......... 9% 58.0M 12s\n", + " 59350K .......... .......... .......... .......... .......... 9% 71.5M 12s\n", + " 59400K .......... .......... .......... .......... .......... 9% 55.8M 12s\n", + " 59450K .......... .......... .......... .......... .......... 10% 42.0M 12s\n", " 59500K .......... .......... .......... .......... .......... 10% 54.8M 12s\n", - " 59550K .......... .......... .......... .......... .......... 10% 70.9M 12s\n", - " 59600K .......... .......... .......... .......... .......... 10% 55.5M 12s\n", - " 59650K .......... .......... .......... .......... .......... 10% 59.8M 12s\n", - " 59700K .......... .......... .......... .......... .......... 10% 50.6M 12s\n", - " 59750K .......... .......... .......... .......... .......... 10% 19.1M 12s\n", - " 59800K .......... .......... .......... .......... .......... 10% 48.5M 12s\n", - " 59850K .......... .......... .......... .......... .......... 10% 50.5M 12s\n", - " 59900K .......... .......... .......... .......... .......... 10% 59.1M 12s\n", - " 59950K .......... .......... .......... .......... .......... 10% 60.9M 12s\n", - " 60000K .......... .......... .......... .......... .......... 10% 46.2M 12s\n", - " 60050K .......... .......... .......... .......... .......... 10% 59.2M 12s\n", - " 60100K .......... .......... .......... .......... .......... 10% 44.4M 12s\n", - " 60150K .......... .......... .......... .......... .......... 10% 57.8M 12s\n", - " 60200K .......... .......... .......... .......... .......... 10% 49.6M 12s\n", - " 60250K .......... .......... .......... .......... .......... 10% 50.3M 12s\n", - " 60300K .......... .......... .......... .......... .......... 10% 53.8M 12s\n", - " 60350K .......... .......... .......... .......... .......... 10% 50.2M 12s\n", - " 60400K .......... .......... .......... .......... .......... 10% 58.0M 12s\n", - " 60450K .......... .......... .......... .......... .......... 10% 60.2M 12s\n", - " 60500K .......... .......... .......... .......... .......... 10% 54.5M 12s\n", - " 60550K .......... .......... .......... .......... .......... 10% 61.9M 12s\n", - " 60600K .......... .......... .......... .......... .......... 10% 45.7M 12s\n", - " 60650K .......... .......... .......... .......... .......... 10% 67.4M 12s\n", - " 60700K .......... .......... .......... .......... .......... 10% 58.3M 12s\n", - " 60750K .......... .......... .......... .......... .......... 10% 45.4M 12s\n", - " 60800K .......... .......... .......... .......... .......... 10% 40.4M 12s\n", - " 60850K .......... .......... .......... .......... .......... 10% 56.8M 12s\n", - " 60900K .......... .......... .......... .......... .......... 10% 67.9M 12s\n", - " 60950K .......... .......... .......... .......... .......... 10% 57.7M 12s\n", - " 61000K .......... .......... .......... .......... .......... 10% 39.6M 12s\n", - " 61050K .......... .......... .......... .......... .......... 10% 60.6M 12s\n", - " 61100K .......... .......... .......... .......... .......... 10% 55.5M 12s\n", - " 61150K .......... .......... .......... .......... .......... 10% 60.7M 12s\n", - " 61200K .......... .......... .......... .......... .......... 10% 50.2M 12s\n", - " 61250K .......... .......... .......... .......... .......... 10% 49.8M 12s\n", - " 61300K .......... .......... .......... .......... .......... 10% 46.4M 12s\n", - " 61350K .......... .......... .......... .......... .......... 10% 63.1M 12s\n", - " 61400K .......... .......... .......... .......... .......... 10% 56.0M 12s\n", - " 61450K .......... .......... .......... .......... .......... 10% 53.6M 12s\n", - " 61500K .......... .......... .......... .......... .......... 10% 49.1M 12s\n", - " 61550K .......... .......... .......... .......... .......... 10% 62.0M 12s\n", - " 61600K .......... .......... .......... .......... .......... 10% 60.1M 12s\n", - " 61650K .......... .......... .......... .......... .......... 10% 65.7M 12s\n", - " 61700K .......... .......... .......... .......... .......... 10% 57.5M 12s\n", - " 61750K .......... .......... .......... .......... .......... 10% 48.8M 12s\n", - " 61800K .......... .......... .......... .......... .......... 10% 44.0M 12s\n", - " 61850K .......... .......... .......... .......... .......... 10% 61.6M 12s\n", - " 61900K .......... .......... .......... .......... .......... 10% 51.6M 12s\n", - " 61950K .......... .......... .......... .......... .......... 10% 52.5M 12s\n", - " 62000K .......... .......... .......... .......... .......... 10% 43.6M 12s\n", - " 62050K .......... .......... .......... .......... .......... 10% 54.7M 12s\n", - " 62100K .......... .......... .......... .......... .......... 10% 66.1M 12s\n", - " 62150K .......... .......... .......... .......... .......... 10% 61.5M 12s\n", - " 62200K .......... .......... .......... .......... .......... 10% 45.4M 12s\n", - " 62250K .......... .......... .......... .......... .......... 10% 48.9M 12s\n", - " 62300K .......... .......... .......... .......... .......... 10% 60.3M 12s\n", - " 62350K .......... .......... .......... .......... .......... 10% 60.3M 12s\n", - " 62400K .......... .......... .......... .......... .......... 10% 58.1M 12s\n", - " 62450K .......... .......... .......... .......... .......... 10% 52.4M 12s\n", - " 62500K .......... .......... .......... .......... .......... 10% 45.3M 12s\n", - " 62550K .......... .......... .......... .......... .......... 10% 58.1M 12s\n", - " 62600K .......... .......... .......... .......... .......... 10% 59.2M 12s\n", - " 62650K .......... .......... .......... .......... .......... 10% 70.4M 12s\n", - " 62700K .......... .......... .......... .......... .......... 10% 4.16M 12s\n", - " 62750K .......... .......... .......... .......... .......... 10% 62.7M 12s\n", - " 62800K .......... .......... .......... .......... .......... 10% 64.8M 12s\n", - " 62850K .......... .......... .......... .......... .......... 10% 62.2M 12s\n", - " 62900K .......... .......... .......... .......... .......... 10% 63.8M 12s\n", - " 62950K .......... .......... .......... .......... .......... 10% 56.5M 12s\n", - " 63000K .......... .......... .......... .......... .......... 10% 35.5M 12s\n", - " 63050K .......... .......... .......... .......... .......... 10% 63.3M 12s\n", - " 63100K .......... .......... .......... .......... .......... 10% 64.4M 12s\n", - " 63150K .......... .......... .......... .......... .......... 10% 66.4M 12s\n", - " 63200K .......... .......... .......... .......... .......... 10% 57.7M 12s\n", - " 63250K .......... .......... .......... .......... .......... 10% 44.6M 12s\n", - " 63300K .......... .......... .......... .......... .......... 10% 38.9M 12s\n", - " 63350K .......... .......... .......... .......... .......... 10% 69.0M 12s\n", - " 63400K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", - " 63450K .......... .......... .......... .......... .......... 10% 55.7M 12s\n", - " 63500K .......... .......... .......... .......... .......... 10% 40.6M 12s\n", - " 63550K .......... .......... .......... .......... .......... 10% 45.6M 12s\n", - " 63600K .......... .......... .......... .......... .......... 10% 56.1M 12s\n", - " 63650K .......... .......... .......... .......... .......... 10% 64.6M 12s\n", - " 63700K .......... .......... .......... .......... .......... 10% 53.0M 12s\n", - " 63750K .......... .......... .......... .......... .......... 10% 50.4M 12s\n", - " 63800K .......... .......... .......... .......... .......... 10% 47.2M 12s\n", - " 63850K .......... .......... .......... .......... .......... 10% 64.5M 12s\n", - " 63900K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", - " 63950K .......... .......... .......... .......... .......... 10% 42.7M 12s\n", - " 64000K .......... .......... .......... .......... .......... 10% 47.7M 12s\n", - " 64050K .......... .......... .......... .......... .......... 10% 64.1M 12s\n", - " 64100K .......... .......... .......... .......... .......... 10% 64.0M 12s\n", - " 64150K .......... .......... .......... .......... .......... 10% 47.2M 12s\n", - " 64200K .......... .......... .......... .......... .......... 10% 35.0M 12s\n", - " 64250K .......... .......... .......... .......... .......... 10% 53.1M 12s\n", - " 64300K .......... .......... .......... .......... .......... 10% 68.3M 12s\n", - " 64350K .......... .......... .......... .......... .......... 10% 47.9M 12s\n", - " 64400K .......... .......... .......... .......... .......... 10% 40.0M 12s\n", - " 64450K .......... .......... .......... .......... .......... 10% 52.3M 12s\n", - " 64500K .......... .......... .......... .......... .......... 10% 65.8M 12s\n", - " 64550K .......... .......... .......... .......... .......... 10% 50.4M 12s\n", - " 64600K .......... .......... .......... .......... .......... 10% 40.8M 12s\n", - " 64650K .......... .......... .......... .......... .......... 10% 47.1M 12s\n", - " 64700K .......... .......... .......... .......... .......... 10% 58.5M 12s\n", - " 64750K .......... .......... .......... .......... .......... 10% 60.9M 12s\n", - " 64800K .......... .......... .......... .......... .......... 10% 43.7M 12s\n", - " 64850K .......... .......... .......... .......... .......... 10% 51.9M 12s\n", - " 64900K .......... .......... .......... .......... .......... 10% 54.0M 12s\n", - " 64950K .......... .......... .......... .......... .......... 10% 55.8M 12s\n", - " 65000K .......... .......... .......... .......... .......... 10% 49.2M 12s\n", - " 65050K .......... .......... .......... .......... .......... 10% 47.9M 12s\n", - " 65100K .......... .......... .......... .......... .......... 10% 49.8M 12s\n", - " 65150K .......... .......... .......... .......... .......... 10% 54.3M 12s\n", - " 65200K .......... .......... .......... .......... .......... 10% 57.3M 12s\n", - " 65250K .......... .......... .......... .......... .......... 10% 57.1M 12s\n", - " 65300K .......... .......... .......... .......... .......... 10% 49.1M 12s\n", - " 65350K .......... .......... .......... .......... .......... 10% 55.1M 12s\n", - " 65400K .......... .......... .......... .......... .......... 11% 44.6M 12s\n", - " 65450K .......... .......... .......... .......... .......... 11% 61.3M 12s\n", - " 65500K .......... .......... .......... .......... .......... 11% 55.9M 12s\n", - " 65550K .......... .......... .......... .......... .......... 11% 52.6M 12s\n", - " 65600K .......... .......... .......... .......... .......... 11% 56.2M 12s\n", - " 65650K .......... .......... .......... .......... .......... 11% 54.4M 12s\n", - " 65700K .......... .......... .......... .......... .......... 11% 69.2M 12s\n", - " 65750K .......... .......... .......... .......... .......... 11% 52.7M 12s\n", - " 65800K .......... .......... .......... .......... .......... 11% 38.5M 12s\n", - " 65850K .......... .......... .......... .......... .......... 11% 57.9M 12s\n", - " 65900K .......... .......... .......... .......... .......... 11% 3.83M 12s\n", - " 65950K .......... .......... .......... .......... .......... 11% 59.8M 12s\n", - " 66000K .......... .......... .......... .......... .......... 11% 57.0M 12s\n", - " 66050K .......... .......... .......... .......... .......... 11% 57.9M 12s\n", - " 66100K .......... .......... .......... .......... .......... 11% 45.3M 12s\n", - " 66150K .......... .......... .......... .......... .......... 11% 54.6M 12s\n", - " 66200K .......... .......... .......... .......... .......... 11% 50.1M 12s\n", - " 66250K .......... .......... .......... .......... .......... 11% 68.7M 12s\n", - " 66300K .......... .......... .......... .......... .......... 11% 62.2M 12s\n", - " 66350K .......... .......... .......... .......... .......... 11% 46.2M 12s\n", - " 66400K .......... .......... .......... .......... .......... 11% 40.2M 12s\n", - " 66450K .......... .......... .......... .......... .......... 11% 66.3M 12s\n", - " 66500K .......... .......... .......... .......... .......... 11% 72.0M 12s\n", - " 66550K .......... .......... .......... .......... .......... 11% 68.4M 12s\n", - " 66600K .......... .......... .......... .......... .......... 11% 38.1M 12s\n", - " 66650K .......... .......... .......... .......... .......... 11% 51.3M 12s\n", - " 66700K .......... .......... .......... .......... .......... 11% 66.1M 12s\n", - " 66750K .......... .......... .......... .......... .......... 11% 66.7M 12s\n", - " 66800K .......... .......... .......... .......... .......... 11% 55.5M 12s\n", - " 66850K .......... .......... .......... .......... .......... 11% 48.3M 12s\n", - " 66900K .......... .......... .......... .......... .......... 11% 51.0M 12s\n", - " 66950K .......... .......... .......... .......... .......... 11% 66.3M 12s\n", - " 67000K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", - " 67050K .......... .......... .......... .......... .......... 11% 61.7M 12s\n", - " 67100K .......... .......... .......... .......... .......... 11% 43.0M 12s\n", - " 67150K .......... .......... .......... .......... .......... 11% 45.7M 12s\n", - " 67200K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", - " 67250K .......... .......... .......... .......... .......... 11% 65.7M 12s\n", - " 67300K .......... .......... .......... .......... .......... 11% 51.0M 12s\n", - " 67350K .......... .......... .......... .......... .......... 11% 39.7M 12s\n", - " 67400K .......... .......... .......... .......... .......... 11% 51.6M 12s\n", - " 67450K .......... .......... .......... .......... .......... 11% 65.1M 12s\n", - " 67500K .......... .......... .......... .......... .......... 11% 59.7M 12s\n", - " 67550K .......... .......... .......... .......... .......... 11% 48.3M 12s\n", - " 67600K .......... .......... .......... .......... .......... 11% 48.8M 12s\n", - " 67650K .......... .......... .......... .......... .......... 11% 4.99M 12s\n", - " 67700K .......... .......... .......... .......... .......... 11% 61.0M 12s\n", - " 67750K .......... .......... .......... .......... .......... 11% 60.1M 12s\n", - " 67800K .......... .......... .......... .......... .......... 11% 56.4M 12s\n", - " 67850K .......... .......... .......... .......... .......... 11% 60.6M 12s\n", - " 67900K .......... .......... .......... .......... .......... 11% 67.1M 12s\n", - " 67950K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", - " 68000K .......... .......... .......... .......... .......... 11% 50.5M 12s\n", - " 68050K .......... .......... .......... .......... .......... 11% 69.1M 12s\n", - " 68100K .......... .......... .......... .......... .......... 11% 67.8M 12s\n", - " 68150K .......... .......... .......... .......... .......... 11% 45.6M 12s\n", - " 68200K .......... .......... .......... .......... .......... 11% 44.9M 12s\n", - " 68250K .......... .......... .......... .......... .......... 11% 57.0M 12s\n", - " 68300K .......... .......... .......... .......... .......... 11% 68.0M 12s\n", - " 68350K .......... .......... .......... .......... .......... 11% 58.9M 12s\n", - " 68400K .......... .......... .......... .......... .......... 11% 42.9M 12s\n", - " 68450K .......... .......... .......... .......... .......... 11% 51.4M 12s\n", - " 68500K .......... .......... .......... .......... .......... 11% 55.5M 12s\n", - " 68550K .......... .......... .......... .......... .......... 11% 60.3M 12s\n", - " 68600K .......... .......... .......... .......... .......... 11% 46.3M 12s\n", - " 68650K .......... .......... .......... .......... .......... 11% 42.0M 12s\n", - " 68700K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", - " 68750K .......... .......... .......... .......... .......... 11% 64.0M 12s\n", - " 68800K .......... .......... .......... .......... .......... 11% 63.1M 12s\n", - " 68850K .......... .......... .......... .......... .......... 11% 46.0M 12s\n", - " 68900K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", - " 68950K .......... .......... .......... .......... .......... 11% 57.7M 12s\n", - " 69000K .......... .......... .......... .......... .......... 11% 54.0M 12s\n", - " 69050K .......... .......... .......... .......... .......... 11% 66.0M 12s\n", - " 69100K .......... .......... .......... .......... .......... 11% 41.5M 12s\n", - " 69150K .......... .......... .......... .......... .......... 11% 54.2M 12s\n", - " 69200K .......... .......... .......... .......... .......... 11% 53.4M 12s\n", - " 69250K .......... .......... .......... .......... .......... 11% 66.9M 12s\n", - " 69300K .......... .......... .......... .......... .......... 11% 71.0M 12s\n", - " 69350K .......... .......... .......... .......... .......... 11% 49.0M 12s\n", - " 69400K .......... .......... .......... .......... .......... 11% 45.3M 12s\n", - " 69450K .......... .......... .......... .......... .......... 11% 60.2M 12s\n", - " 69500K .......... .......... .......... .......... .......... 11% 64.4M 12s\n", - " 69550K .......... .......... .......... .......... .......... 11% 47.7M 12s\n", - " 69600K .......... .......... .......... .......... .......... 11% 31.2M 12s\n", - " 69650K .......... .......... .......... .......... .......... 11% 37.6M 12s\n", - " 69700K .......... .......... .......... .......... .......... 11% 66.6M 12s\n", - " 69750K .......... .......... .......... .......... .......... 11% 60.0M 12s\n", - " 69800K .......... .......... .......... .......... .......... 11% 39.3M 12s\n", - " 69850K .......... .......... .......... .......... .......... 11% 60.0M 12s\n", - " 69900K .......... .......... .......... .......... .......... 11% 64.5M 12s\n", - " 69950K .......... .......... .......... .......... .......... 11% 66.6M 12s\n", - " 70000K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", - " 70050K .......... .......... .......... .......... .......... 11% 48.9M 12s\n", - " 70100K .......... .......... .......... .......... .......... 11% 60.3M 12s\n", - " 70150K .......... .......... .......... .......... .......... 11% 59.3M 12s\n", - " 70200K .......... .......... .......... .......... .......... 11% 56.0M 12s\n", - " 70250K .......... .......... .......... .......... .......... 11% 42.1M 12s\n", - " 70300K .......... .......... .......... .......... .......... 11% 60.6M 12s\n", - " 70350K .......... .......... .......... .......... .......... 11% 47.8M 12s\n", - " 70400K .......... .......... .......... .......... .......... 11% 49.2M 12s\n", - " 70450K .......... .......... .......... .......... .......... 11% 49.9M 12s\n", - " 70500K .......... .......... .......... .......... .......... 11% 44.7M 12s\n", - " 70550K .......... .......... .......... .......... .......... 11% 50.9M 12s\n", - " 70600K .......... .......... .......... .......... .......... 11% 50.6M 12s\n", - " 70650K .......... .......... .......... .......... .......... 11% 63.9M 12s\n", - " 70700K .......... .......... .......... .......... .......... 11% 45.4M 12s\n", - " 70750K .......... .......... .......... .......... .......... 11% 51.5M 12s\n", - " 70800K .......... .......... .......... .......... .......... 11% 48.5M 12s\n", - " 70850K .......... .......... .......... .......... .......... 11% 50.4M 12s\n", - " 70900K .......... .......... .......... .......... .......... 11% 44.1M 12s\n", - " 70950K .......... .......... .......... .......... .......... 11% 40.8M 12s\n", - " 71000K .......... .......... .......... .......... .......... 11% 38.5M 12s\n", - " 71050K .......... .......... .......... .......... .......... 11% 61.3M 12s\n", - " 71100K .......... .......... .......... .......... .......... 11% 45.0M 12s\n", - " 71150K .......... .......... .......... .......... .......... 11% 42.5M 12s\n", - " 71200K .......... .......... .......... .......... .......... 11% 35.8M 12s\n", - " 71250K .......... .......... .......... .......... .......... 11% 47.7M 12s\n", - " 71300K .......... .......... .......... .......... .......... 11% 47.4M 12s\n", - " 71350K .......... .......... .......... .......... .......... 12% 50.3M 12s\n", - " 71400K .......... .......... .......... .......... .......... 12% 45.9M 12s\n", - " 71450K .......... .......... .......... .......... .......... 12% 52.1M 12s\n", - " 71500K .......... .......... .......... .......... .......... 12% 47.2M 12s\n", - " 71550K .......... .......... .......... .......... .......... 12% 53.4M 12s\n", - " 71600K .......... .......... .......... .......... .......... 12% 54.0M 12s\n", - " 71650K .......... .......... .......... .......... .......... 12% 68.1M 12s\n", - " 71700K .......... .......... .......... .......... .......... 12% 67.4M 12s\n", - " 71750K .......... .......... .......... .......... .......... 12% 70.2M 12s\n", - " 71800K .......... .......... .......... .......... .......... 12% 31.1M 12s\n", - " 71850K .......... .......... .......... .......... .......... 12% 42.9M 12s\n", - " 71900K .......... .......... .......... .......... .......... 12% 57.5M 12s\n", - " 71950K .......... .......... .......... .......... .......... 12% 44.2M 12s\n", - " 72000K .......... .......... .......... .......... .......... 12% 40.0M 12s\n", - " 72050K .......... .......... .......... .......... .......... 12% 46.9M 12s\n", - " 72100K .......... .......... .......... .......... .......... 12% 56.8M 12s\n", - " 72150K .......... .......... .......... .......... .......... 12% 56.9M 12s\n", - " 72200K .......... .......... .......... .......... .......... 12% 42.4M 12s\n", - " 72250K .......... .......... .......... .......... .......... 12% 47.9M 12s\n", - " 72300K .......... .......... .......... .......... .......... 12% 57.1M 12s\n", - " 72350K .......... .......... .......... .......... .......... 12% 51.6M 12s\n", - " 72400K .......... .......... .......... .......... .......... 12% 42.0M 12s\n", - " 72450K .......... .......... .......... .......... .......... 12% 37.6M 12s\n", - " 72500K .......... .......... .......... .......... .......... 12% 47.3M 12s\n", - " 72550K .......... .......... .......... .......... .......... 12% 68.6M 12s\n", - " 72600K .......... .......... .......... .......... .......... 12% 47.4M 12s\n", - " 72650K .......... .......... .......... .......... .......... 12% 52.2M 12s\n", - " 72700K .......... .......... .......... .......... .......... 12% 57.4M 12s\n", - " 72750K .......... .......... .......... .......... .......... 12% 62.9M 12s\n", - " 72800K .......... .......... .......... .......... .......... 12% 49.3M 12s\n", - " 72850K .......... .......... .......... .......... .......... 12% 46.9M 12s\n", - " 72900K .......... .......... .......... .......... .......... 12% 42.9M 12s\n", - " 72950K .......... .......... .......... .......... .......... 12% 42.2M 12s\n", - " 73000K .......... .......... .......... .......... .......... 12% 44.2M 12s\n", - " 73050K .......... .......... .......... .......... .......... 12% 57.4M 12s\n", - " 73100K .......... .......... .......... .......... .......... 12% 38.1M 12s\n", - " 73150K .......... .......... .......... .......... .......... 12% 43.6M 12s\n", - " 73200K .......... .......... .......... .......... .......... 12% 50.5M 12s\n", - " 73250K .......... .......... .......... .......... .......... 12% 64.3M 12s\n", - " 73300K .......... .......... .......... .......... .......... 12% 53.9M 12s\n", - " 73350K .......... .......... .......... .......... .......... 12% 53.5M 12s\n", - " 73400K .......... .......... .......... .......... .......... 12% 44.6M 12s\n", - " 73450K .......... .......... .......... .......... .......... 12% 68.1M 12s\n", - " 73500K .......... .......... .......... .......... .......... 12% 64.8M 12s\n", - " 73550K .......... .......... .......... .......... .......... 12% 61.0M 12s\n", - " 73600K .......... .......... .......... .......... .......... 12% 46.3M 12s\n", - " 73650K .......... .......... .......... .......... .......... 12% 58.0M 12s\n", - " 73700K .......... .......... .......... .......... .......... 12% 69.4M 12s\n", - " 73750K .......... .......... .......... .......... .......... 12% 72.2M 12s\n", - " 73800K .......... .......... .......... .......... .......... 12% 38.0M 12s\n", - " 73850K .......... .......... .......... .......... .......... 12% 38.5M 12s\n", - " 73900K .......... .......... .......... .......... .......... 12% 43.2M 12s\n", - " 73950K .......... .......... .......... .......... .......... 12% 42.3M 12s\n", - " 74000K .......... .......... .......... .......... .......... 12% 45.2M 12s\n", - " 74050K .......... .......... .......... .......... .......... 12% 38.3M 12s\n", - " 74100K .......... .......... .......... .......... .......... 12% 58.1M 12s\n", - " 74150K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", - " 74200K .......... .......... .......... .......... .......... 12% 50.9M 12s\n", - " 74250K .......... .......... .......... .......... .......... 12% 35.6M 12s\n", - " 74300K .......... .......... .......... .......... .......... 12% 53.7M 12s\n", - " 74350K .......... .......... .......... .......... .......... 12% 43.4M 12s\n", - " 74400K .......... .......... .......... .......... .......... 12% 62.0M 12s\n", - " 74450K .......... .......... .......... .......... .......... 12% 45.2M 12s\n", - " 74500K .......... .......... .......... .......... .......... 12% 52.2M 12s\n", - " 74550K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", - " 74600K .......... .......... .......... .......... .......... 12% 55.3M 12s\n", - " 74650K .......... .......... .......... .......... .......... 12% 56.9M 12s\n", - " 74700K .......... .......... .......... .......... .......... 12% 35.0M 12s\n", - " 74750K .......... .......... .......... .......... .......... 12% 43.5M 12s\n", - " 74800K .......... .......... .......... .......... .......... 12% 47.8M 12s\n", - " 74850K .......... .......... .......... .......... .......... 12% 55.1M 12s\n", - " 74900K .......... .......... .......... .......... .......... 12% 38.2M 12s\n", - " 74950K .......... .......... .......... .......... .......... 12% 50.7M 12s\n", - " 75000K .......... .......... .......... .......... .......... 12% 37.3M 12s\n", - " 75050K .......... .......... .......... .......... .......... 12% 43.7M 12s\n", - " 75100K .......... .......... .......... .......... .......... 12% 38.3M 12s\n", - " 75150K .......... .......... .......... .......... .......... 12% 49.6M 12s\n", - " 75200K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", - " 75250K .......... .......... .......... .......... .......... 12% 45.7M 12s\n", - " 75300K .......... .......... .......... .......... .......... 12% 37.8M 12s\n", - " 75350K .......... .......... .......... .......... .......... 12% 58.3M 12s\n", - " 75400K .......... .......... .......... .......... .......... 12% 56.0M 12s\n", - " 75450K .......... .......... .......... .......... .......... 12% 66.8M 12s\n", - " 75500K .......... .......... .......... .......... .......... 12% 61.6M 12s\n", - " 75550K .......... .......... .......... .......... .......... 12% 50.6M 12s\n", - " 75600K .......... .......... .......... .......... .......... 12% 53.2M 12s\n", - " 75650K .......... .......... .......... .......... .......... 12% 59.5M 12s\n", - " 75700K .......... .......... .......... .......... .......... 12% 49.6M 12s\n", - " 75750K .......... .......... .......... .......... .......... 12% 43.1M 12s\n", - " 75800K .......... .......... .......... .......... .......... 12% 30.0M 12s\n", - " 75850K .......... .......... .......... .......... .......... 12% 66.8M 12s\n", - " 75900K .......... .......... .......... .......... .......... 12% 54.6M 12s\n", - " 75950K .......... .......... .......... .......... .......... 12% 66.1M 12s\n", - " 76000K .......... .......... .......... .......... .......... 12% 37.7M 12s\n", - " 76050K .......... .......... .......... .......... .......... 12% 38.2M 12s\n", - " 76100K .......... .......... .......... .......... .......... 12% 49.2M 12s\n", - " 76150K .......... .......... .......... .......... .......... 12% 42.8M 12s\n", - " 76200K .......... .......... .......... .......... .......... 12% 32.0M 12s\n", - " 76250K .......... .......... .......... .......... .......... 12% 58.0M 12s\n", - " 76300K .......... .......... .......... .......... .......... 12% 60.1M 12s\n", - " 76350K .......... .......... .......... .......... .......... 12% 53.1M 12s\n", - " 76400K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", - " 76450K .......... .......... .......... .......... .......... 12% 62.3M 12s\n", - " 76500K .......... .......... .......... .......... .......... 12% 64.0M 12s\n", - " 76550K .......... .......... .......... .......... .......... 12% 60.9M 12s\n", - " 76600K .......... .......... .......... .......... .......... 12% 56.8M 12s\n", - " 76650K .......... .......... .......... .......... .......... 12% 50.3M 12s\n", - " 76700K .......... .......... .......... .......... .......... 12% 38.8M 12s\n", - " 76750K .......... .......... .......... .......... .......... 12% 52.9M 12s\n", - " 76800K .......... .......... .......... .......... .......... 12% 42.2M 12s\n", - " 76850K .......... .......... .......... .......... .......... 12% 59.1M 12s\n", - " 76900K .......... .......... .......... .......... .......... 12% 41.5M 12s\n", - " 76950K .......... .......... .......... .......... .......... 12% 41.4M 12s\n", - " 77000K .......... .......... .......... .......... .......... 12% 41.8M 12s\n", - " 77050K .......... .......... .......... .......... .......... 12% 35.4M 12s\n", - " 77100K .......... .......... .......... .......... .......... 12% 39.1M 12s\n", - " 77150K .......... .......... .......... .......... .......... 12% 62.2M 12s\n", - " 77200K .......... .......... .......... .......... .......... 12% 58.2M 12s\n", - " 77250K .......... .......... .......... .......... .......... 12% 48.5M 12s\n", - " 77300K .......... .......... .......... .......... .......... 13% 41.5M 12s\n", - " 77350K .......... .......... .......... .......... .......... 13% 45.9M 12s\n", - " 77400K .......... .......... .......... .......... .......... 13% 46.1M 12s\n", - " 77450K .......... .......... .......... .......... .......... 13% 68.7M 12s\n", - " 77500K .......... .......... .......... .......... .......... 13% 54.3M 12s\n", - " 77550K .......... .......... 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.......... .......... .......... .......... 13% 68.7M 12s\n", - " 78200K .......... .......... .......... .......... .......... 13% 53.4M 12s\n", - " 78250K .......... .......... .......... .......... .......... 13% 52.9M 12s\n", - " 78300K .......... .......... .......... .......... .......... 13% 58.0M 12s\n", - " 78350K .......... .......... .......... .......... .......... 13% 68.2M 12s\n", - " 78400K .......... .......... .......... .......... .......... 13% 61.4M 12s\n", - " 78450K .......... .......... .......... .......... .......... 13% 67.5M 12s\n", - " 78500K .......... .......... .......... .......... .......... 13% 54.9M 12s\n", - " 78550K .......... .......... .......... .......... .......... 13% 46.5M 12s\n", - " 78600K .......... .......... .......... .......... .......... 13% 49.2M 12s\n", - " 78650K .......... .......... .......... .......... .......... 13% 68.4M 12s\n", - " 78700K .......... .......... .......... .......... .......... 13% 72.7M 12s\n", - " 78750K .......... .......... .......... .......... .......... 13% 59.8M 12s\n", - " 78800K .......... .......... .......... .......... .......... 13% 45.3M 12s\n", - " 78850K .......... .......... .......... .......... .......... 13% 40.0M 12s\n", - " 78900K .......... .......... .......... .......... .......... 13% 66.8M 12s\n", - " 78950K .......... .......... .......... .......... .......... 13% 67.3M 12s\n", - " 79000K .......... .......... .......... .......... .......... 13% 49.3M 12s\n", - " 79050K .......... .......... .......... .......... .......... 13% 53.1M 12s\n", - " 79100K .......... .......... .......... .......... .......... 13% 54.2M 12s\n", - " 79150K .......... .......... .......... .......... .......... 13% 68.6M 12s\n", - " 79200K .......... .......... .......... .......... .......... 13% 60.7M 12s\n", - " 79250K .......... .......... .......... .......... .......... 13% 66.6M 12s\n", - " 79300K .......... .......... .......... .......... .......... 13% 49.4M 12s\n", - " 79350K .......... .......... .......... .......... .......... 13% 46.0M 12s\n", - " 79400K .......... .......... .......... .......... .......... 13% 51.5M 12s\n", - " 79450K .......... .......... .......... .......... .......... 13% 62.7M 12s\n", - " 79500K .......... .......... .......... .......... .......... 13% 65.1M 12s\n", - " 79550K .......... .......... .......... .......... .......... 13% 48.5M 12s\n", - " 79600K .......... .......... .......... .......... .......... 13% 46.3M 12s\n", - " 79650K .......... .......... .......... .......... .......... 13% 65.8M 12s\n", - " 79700K .......... .......... .......... .......... .......... 13% 67.4M 12s\n", - " 79750K .......... .......... .......... .......... .......... 13% 63.8M 12s\n", - " 79800K .......... .......... .......... .......... .......... 13% 40.6M 12s\n", - " 79850K .......... .......... .......... .......... .......... 13% 49.1M 12s\n", - " 79900K .......... .......... .......... .......... .......... 13% 66.5M 12s\n", - " 79950K .......... .......... .......... .......... .......... 13% 75.7M 12s\n", - " 80000K .......... .......... .......... .......... .......... 13% 52.8M 12s\n", - " 80050K .......... .......... .......... .......... .......... 13% 46.8M 11s\n", - " 80100K .......... .......... .......... .......... .......... 13% 47.3M 11s\n", - " 80150K .......... .......... .......... .......... .......... 13% 59.5M 11s\n", - " 80200K .......... .......... .......... .......... .......... 13% 60.7M 11s\n", - " 80250K .......... .......... .......... .......... .......... 13% 70.0M 11s\n", - " 80300K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", - " 80350K .......... .......... .......... .......... .......... 13% 47.2M 11s\n", - " 80400K .......... .......... .......... .......... .......... 13% 61.2M 11s\n", - " 80450K .......... .......... .......... .......... .......... 13% 64.2M 11s\n", - " 80500K .......... .......... .......... .......... .......... 13% 69.5M 11s\n", - " 80550K .......... .......... .......... .......... .......... 13% 54.1M 11s\n", - " 80600K .......... .......... .......... .......... .......... 13% 36.9M 11s\n", - " 80650K .......... .......... .......... .......... .......... 13% 63.3M 11s\n", - " 80700K .......... .......... .......... .......... .......... 13% 65.1M 11s\n", - " 80750K .......... .......... .......... .......... .......... 13% 68.2M 11s\n", - " 80800K .......... .......... .......... .......... .......... 13% 51.1M 11s\n", - " 80850K .......... .......... .......... .......... .......... 13% 45.6M 11s\n", - " 80900K .......... .......... .......... .......... .......... 13% 53.1M 11s\n", - " 80950K .......... .......... .......... .......... .......... 13% 65.5M 11s\n", - " 81000K .......... .......... .......... .......... .......... 13% 56.4M 11s\n", - " 81050K .......... .......... .......... .......... .......... 13% 68.1M 11s\n", - " 81100K .......... .......... .......... .......... .......... 13% 63.7M 11s\n", - " 81150K .......... .......... .......... .......... .......... 13% 51.2M 11s\n", - " 81200K .......... .......... .......... .......... .......... 13% 53.8M 11s\n", - " 81250K .......... .......... .......... .......... .......... 13% 67.5M 11s\n", - " 81300K .......... .......... .......... .......... .......... 13% 65.0M 11s\n", - " 81350K .......... .......... .......... .......... .......... 13% 57.8M 11s\n", - " 81400K .......... .......... .......... .......... .......... 13% 43.9M 11s\n", - " 81450K .......... .......... .......... .......... .......... 13% 54.0M 11s\n", - " 81500K .......... .......... .......... .......... .......... 13% 75.0M 11s\n", - " 81550K .......... .......... .......... .......... .......... 13% 65.8M 11s\n", - " 81600K .......... .......... .......... .......... .......... 13% 53.8M 11s\n", - " 81650K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", - " 81700K .......... .......... .......... .......... .......... 13% 45.7M 11s\n", + " 59550K .......... .......... .......... .......... .......... 10% 53.8M 12s\n", + " 59600K .......... .......... .......... .......... .......... 10% 57.6M 12s\n", + " 59650K .......... .......... .......... .......... .......... 10% 60.7M 12s\n", + " 59700K .......... .......... .......... .......... .......... 10% 52.3M 12s\n", + " 59750K .......... .......... .......... .......... .......... 10% 55.4M 12s\n", + " 59800K .......... .......... .......... .......... .......... 10% 44.0M 12s\n", + " 59850K .......... .......... .......... .......... .......... 10% 76.0M 12s\n", + " 59900K .......... .......... .......... .......... .......... 10% 62.0M 12s\n", + " 59950K .......... .......... .......... .......... .......... 10% 45.1M 12s\n", + " 60000K .......... .......... .......... .......... .......... 10% 39.7M 12s\n", + " 60050K .......... .......... .......... .......... .......... 10% 43.4M 12s\n", + " 60100K .......... .......... .......... .......... .......... 10% 57.0M 12s\n", + " 60150K .......... .......... .......... .......... .......... 10% 47.1M 12s\n", + " 60200K .......... .......... .......... .......... .......... 10% 37.7M 12s\n", + " 60250K .......... .......... .......... .......... .......... 10% 46.1M 12s\n", + " 60300K .......... .......... .......... .......... .......... 10% 59.1M 12s\n", + " 60350K .......... .......... .......... .......... .......... 10% 66.0M 12s\n", + " 60400K .......... .......... .......... .......... .......... 10% 50.0M 12s\n", + " 60450K .......... .......... .......... .......... .......... 10% 61.0M 12s\n", + " 60500K .......... .......... .......... .......... .......... 10% 63.5M 12s\n", + " 60550K .......... .......... .......... .......... .......... 10% 76.1M 12s\n", + " 60600K .......... .......... .......... .......... .......... 10% 62.2M 12s\n", + " 60650K .......... .......... .......... .......... .......... 10% 68.1M 12s\n", + " 60700K .......... .......... .......... .......... .......... 10% 61.4M 12s\n", + " 60750K .......... .......... .......... .......... .......... 10% 69.8M 12s\n", + " 60800K .......... .......... .......... .......... .......... 10% 63.4M 11s\n", + " 60850K .......... .......... .......... .......... .......... 10% 69.2M 11s\n", + " 60900K .......... .......... .......... .......... .......... 10% 59.2M 11s\n", + " 60950K .......... .......... .......... .......... .......... 10% 76.4M 11s\n", + " 61000K .......... .......... .......... .......... .......... 10% 55.6M 11s\n", + " 61050K .......... .......... .......... .......... .......... 10% 75.2M 11s\n", + " 61100K .......... .......... .......... .......... .......... 10% 69.1M 11s\n", + " 61150K .......... .......... .......... .......... .......... 10% 74.5M 11s\n", + " 61200K .......... .......... .......... .......... .......... 10% 42.6M 11s\n", + " 61250K .......... .......... .......... .......... .......... 10% 60.5M 11s\n", + " 61300K .......... .......... .......... .......... .......... 10% 47.3M 11s\n", + " 61350K .......... .......... .......... .......... .......... 10% 48.4M 11s\n", + " 61400K .......... .......... .......... .......... .......... 10% 39.8M 11s\n", + " 61450K .......... .......... .......... .......... .......... 10% 57.0M 11s\n", + " 61500K .......... .......... .......... .......... .......... 10% 41.0M 11s\n", + " 61550K .......... .......... .......... .......... .......... 10% 46.8M 11s\n", + " 61600K .......... .......... .......... .......... .......... 10% 48.4M 11s\n", + " 61650K .......... .......... .......... .......... .......... 10% 55.9M 11s\n", + " 61700K .......... .......... .......... .......... .......... 10% 58.8M 11s\n", + " 61750K .......... .......... .......... .......... .......... 10% 59.4M 11s\n", + " 61800K .......... .......... .......... .......... .......... 10% 50.7M 11s\n", + " 61850K .......... .......... .......... .......... .......... 10% 63.6M 11s\n", + " 61900K .......... .......... .......... .......... .......... 10% 68.1M 11s\n", + " 61950K .......... .......... .......... .......... .......... 10% 45.7M 11s\n", + " 62000K .......... .......... .......... .......... .......... 10% 50.5M 11s\n", + " 62050K .......... .......... .......... .......... .......... 10% 51.9M 11s\n", + " 62100K .......... .......... .......... .......... .......... 10% 65.3M 11s\n", + " 62150K .......... .......... .......... .......... .......... 10% 67.1M 11s\n", + " 62200K .......... .......... .......... .......... .......... 10% 51.1M 11s\n", + " 62250K .......... .......... .......... .......... .......... 10% 57.9M 11s\n", + " 62300K .......... .......... .......... .......... .......... 10% 53.3M 11s\n", + " 62350K .......... .......... .......... .......... .......... 10% 67.8M 11s\n", + " 62400K .......... .......... .......... .......... .......... 10% 61.9M 11s\n", + " 62450K .......... .......... .......... .......... .......... 10% 55.0M 11s\n", + " 62500K .......... .......... .......... .......... .......... 10% 51.3M 11s\n", + " 62550K .......... .......... .......... .......... .......... 10% 58.5M 11s\n", + " 62600K .......... .......... .......... .......... .......... 10% 52.2M 11s\n", + " 62650K .......... .......... .......... .......... .......... 10% 53.4M 11s\n", + " 62700K .......... .......... .......... .......... .......... 10% 51.1M 11s\n", + " 62750K .......... .......... .......... .......... .......... 10% 57.0M 11s\n", + " 62800K .......... .......... .......... .......... .......... 10% 57.6M 11s\n", + " 62850K .......... .......... .......... .......... .......... 10% 61.8M 11s\n", + " 62900K .......... .......... .......... .......... .......... 10% 62.0M 11s\n", + " 62950K .......... .......... .......... .......... .......... 10% 57.5M 11s\n", + " 63000K .......... .......... .......... .......... .......... 10% 42.7M 11s\n", + " 63050K .......... .......... .......... .......... .......... 10% 67.9M 11s\n", + " 63100K .......... .......... .......... .......... .......... 10% 57.6M 11s\n", + " 63150K .......... .......... .......... .......... .......... 10% 72.6M 11s\n", + " 63200K .......... .......... .......... .......... .......... 10% 47.0M 11s\n", + " 63250K .......... .......... .......... .......... .......... 10% 49.6M 11s\n", + " 63300K .......... .......... .......... .......... .......... 10% 69.8M 11s\n", + " 63350K .......... .......... .......... .......... .......... 10% 58.3M 11s\n", + " 63400K .......... .......... .......... .......... .......... 10% 22.7M 11s\n", + " 63450K .......... .......... .......... .......... .......... 10% 36.0M 11s\n", + " 63500K .......... .......... .......... .......... .......... 10% 34.7M 11s\n", + " 63550K .......... .......... .......... .......... .......... 10% 38.6M 11s\n", + " 63600K .......... .......... .......... .......... .......... 10% 36.8M 11s\n", + " 63650K .......... .......... .......... .......... .......... 10% 33.0M 11s\n", + " 63700K .......... .......... .......... .......... .......... 10% 28.2M 11s\n", + " 63750K .......... .......... .......... .......... .......... 10% 35.6M 11s\n", + " 63800K .......... .......... .......... .......... .......... 10% 29.7M 11s\n", + " 63850K .......... .......... .......... .......... .......... 10% 32.4M 11s\n", + " 63900K .......... .......... .......... .......... .......... 10% 37.3M 11s\n", + " 63950K .......... .......... .......... .......... .......... 10% 36.2M 11s\n", + " 64000K .......... .......... .......... .......... .......... 10% 27.8M 11s\n", + " 64050K .......... .......... .......... .......... .......... 10% 34.8M 11s\n", + " 64100K .......... .......... .......... .......... .......... 10% 51.4M 11s\n", + " 64150K .......... .......... .......... .......... .......... 10% 41.8M 11s\n", + " 64200K .......... .......... .......... .......... .......... 10% 36.6M 11s\n", + " 64250K .......... .......... .......... .......... .......... 10% 34.4M 11s\n", + " 64300K .......... .......... .......... .......... .......... 10% 39.1M 11s\n", + " 64350K .......... .......... .......... .......... .......... 10% 34.9M 11s\n", + " 64400K .......... .......... .......... .......... .......... 10% 44.2M 11s\n", + " 64450K .......... .......... .......... .......... .......... 10% 69.8M 11s\n", + " 64500K .......... .......... .......... .......... .......... 10% 62.1M 11s\n", + " 64550K .......... .......... .......... .......... .......... 10% 58.6M 11s\n", + " 64600K .......... .......... .......... .......... .......... 10% 44.0M 11s\n", + " 64650K .......... .......... .......... .......... .......... 10% 51.5M 11s\n", + " 64700K .......... .......... .......... .......... .......... 10% 69.7M 11s\n", + " 64750K .......... .......... .......... .......... .......... 10% 72.7M 11s\n", + " 64800K .......... .......... .......... .......... .......... 10% 51.4M 11s\n", + " 64850K .......... .......... .......... .......... .......... 10% 51.3M 11s\n", + " 64900K .......... .......... .......... .......... .......... 10% 41.4M 11s\n", + " 64950K .......... .......... .......... .......... .......... 10% 59.7M 11s\n", + " 65000K .......... .......... .......... .......... .......... 10% 53.6M 11s\n", + " 65050K .......... .......... .......... .......... .......... 10% 50.9M 11s\n", + " 65100K .......... .......... .......... .......... .......... 10% 50.7M 11s\n", + " 65150K .......... .......... .......... .......... .......... 10% 51.0M 11s\n", + " 65200K .......... .......... .......... .......... .......... 10% 59.5M 11s\n", + " 65250K .......... .......... .......... .......... .......... 10% 57.2M 11s\n", + " 65300K .......... .......... .......... .......... .......... 10% 58.2M 11s\n", + " 65350K .......... .......... .......... .......... .......... 10% 59.1M 11s\n", + " 65400K .......... .......... .......... .......... .......... 11% 45.2M 11s\n", + " 65450K .......... .......... .......... .......... .......... 11% 58.0M 11s\n", + " 65500K .......... .......... .......... .......... .......... 11% 54.4M 11s\n", + " 65550K .......... .......... .......... .......... .......... 11% 59.9M 11s\n", + " 65600K .......... .......... .......... .......... .......... 11% 64.9M 11s\n", + " 65650K .......... .......... .......... .......... .......... 11% 40.2M 11s\n", + " 65700K .......... .......... .......... .......... .......... 11% 49.4M 11s\n", + " 65750K .......... .......... .......... .......... .......... 11% 60.8M 11s\n", + " 65800K .......... .......... .......... .......... .......... 11% 53.7M 11s\n", + " 65850K .......... .......... .......... .......... .......... 11% 61.9M 11s\n", + " 65900K .......... .......... .......... .......... .......... 11% 48.8M 11s\n", + " 65950K .......... .......... .......... .......... .......... 11% 36.3M 11s\n", + " 66000K .......... .......... .......... .......... .......... 11% 55.0M 11s\n", + " 66050K .......... .......... .......... .......... .......... 11% 70.0M 11s\n", + " 66100K .......... .......... .......... .......... .......... 11% 57.4M 11s\n", + " 66150K .......... .......... .......... .......... .......... 11% 44.5M 11s\n", + " 66200K .......... .......... .......... .......... .......... 11% 51.0M 11s\n", + " 66250K .......... .......... .......... .......... .......... 11% 52.9M 11s\n", + " 66300K .......... .......... .......... .......... .......... 11% 66.9M 11s\n", + " 66350K .......... .......... .......... .......... .......... 11% 55.1M 11s\n", + " 66400K .......... .......... .......... .......... .......... 11% 46.8M 11s\n", + " 66450K .......... .......... .......... .......... .......... 11% 60.8M 11s\n", + " 66500K .......... .......... .......... .......... .......... 11% 54.8M 11s\n", + " 66550K .......... .......... .......... .......... .......... 11% 69.6M 11s\n", + " 66600K .......... .......... .......... .......... .......... 11% 54.6M 11s\n", + " 66650K .......... .......... .......... .......... .......... 11% 56.1M 11s\n", + " 66700K .......... .......... .......... .......... .......... 11% 69.4M 11s\n", + " 66750K .......... .......... .......... .......... .......... 11% 76.5M 11s\n", + " 66800K .......... .......... .......... .......... .......... 11% 56.6M 11s\n", + " 66850K .......... .......... .......... .......... .......... 11% 73.7M 11s\n", + " 66900K .......... .......... .......... .......... .......... 11% 56.8M 11s\n", + " 66950K .......... .......... .......... .......... .......... 11% 59.1M 11s\n", + " 67000K .......... .......... .......... .......... .......... 11% 45.7M 11s\n", + " 67050K .......... .......... .......... .......... .......... 11% 55.2M 11s\n", + " 67100K .......... .......... .......... .......... .......... 11% 77.0M 11s\n", + " 67150K .......... .......... .......... .......... .......... 11% 69.3M 11s\n", + " 67200K .......... .......... .......... .......... .......... 11% 44.4M 11s\n", + " 67250K .......... .......... .......... .......... .......... 11% 52.0M 11s\n", + " 67300K .......... .......... .......... .......... .......... 11% 64.9M 11s\n", + " 67350K .......... .......... .......... .......... .......... 11% 64.8M 11s\n", + " 67400K .......... .......... .......... .......... .......... 11% 59.1M 11s\n", + " 67450K .......... .......... .......... .......... .......... 11% 50.8M 11s\n", + " 67500K .......... .......... .......... .......... .......... 11% 48.9M 11s\n", + " 67550K .......... .......... .......... .......... .......... 11% 62.3M 11s\n", + " 67600K .......... .......... .......... .......... .......... 11% 54.6M 11s\n", + " 67650K .......... .......... .......... .......... .......... 11% 75.5M 11s\n", + " 67700K .......... .......... .......... .......... .......... 11% 59.9M 11s\n", + " 67750K .......... .......... .......... .......... .......... 11% 51.2M 11s\n", + " 67800K .......... .......... .......... .......... .......... 11% 47.0M 11s\n", + " 67850K .......... .......... .......... .......... .......... 11% 51.9M 11s\n", + " 67900K .......... .......... .......... .......... .......... 11% 59.9M 11s\n", + " 67950K .......... .......... .......... .......... .......... 11% 55.0M 11s\n", + " 68000K .......... .......... .......... .......... .......... 11% 50.7M 11s\n", + " 68050K .......... .......... .......... .......... .......... 11% 67.7M 11s\n", + " 68100K .......... .......... .......... .......... .......... 11% 47.9M 11s\n", + " 68150K .......... .......... .......... .......... .......... 11% 68.7M 11s\n", + " 68200K .......... .......... .......... .......... .......... 11% 55.8M 11s\n", + " 68250K .......... .......... .......... .......... .......... 11% 50.8M 11s\n", + " 68300K .......... .......... .......... .......... .......... 11% 66.7M 11s\n", + " 68350K .......... .......... .......... .......... .......... 11% 50.3M 11s\n", + " 68400K .......... .......... .......... .......... 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.......... .......... 11% 49.5M 11s\n", + " 69050K .......... .......... .......... .......... .......... 11% 55.3M 11s\n", + " 69100K .......... .......... .......... .......... .......... 11% 64.8M 11s\n", + " 69150K .......... .......... .......... .......... .......... 11% 52.9M 11s\n", + " 69200K .......... .......... .......... .......... .......... 11% 70.6M 11s\n", + " 69250K .......... .......... .......... .......... .......... 11% 78.6M 11s\n", + " 69300K .......... .......... .......... .......... .......... 11% 60.2M 11s\n", + " 69350K .......... .......... .......... .......... .......... 11% 52.7M 11s\n", + " 69400K .......... .......... .......... .......... .......... 11% 49.2M 11s\n", + " 69450K .......... .......... .......... .......... .......... 11% 71.5M 11s\n", + " 69500K .......... .......... .......... .......... .......... 11% 69.6M 11s\n", + " 69550K .......... .......... .......... .......... .......... 11% 72.6M 11s\n", + " 69600K .......... .......... .......... .......... .......... 11% 58.9M 11s\n", + " 69650K .......... .......... .......... .......... .......... 11% 54.8M 11s\n", + " 69700K .......... .......... .......... .......... .......... 11% 55.2M 11s\n", + " 69750K .......... .......... .......... .......... .......... 11% 64.6M 11s\n", + " 69800K .......... .......... .......... .......... .......... 11% 54.0M 11s\n", + " 69850K .......... .......... .......... .......... .......... 11% 68.0M 11s\n", + " 69900K .......... .......... .......... .......... .......... 11% 76.7M 11s\n", + " 69950K .......... .......... .......... .......... .......... 11% 63.1M 11s\n", + " 70000K .......... .......... .......... .......... .......... 11% 47.6M 11s\n", + " 70050K .......... .......... .......... .......... .......... 11% 64.1M 11s\n", + " 70100K .......... .......... .......... .......... .......... 11% 68.9M 11s\n", + " 70150K .......... .......... .......... .......... .......... 11% 53.7M 11s\n", + " 70200K .......... .......... .......... .......... .......... 11% 54.6M 11s\n", + " 70250K .......... .......... .......... .......... .......... 11% 66.3M 11s\n", + " 70300K .......... .......... .......... .......... .......... 11% 48.5M 11s\n", + " 70350K .......... .......... .......... .......... .......... 11% 64.6M 11s\n", + " 70400K .......... .......... .......... .......... .......... 11% 49.6M 11s\n", + " 70450K .......... .......... .......... .......... .......... 11% 65.5M 11s\n", + " 70500K .......... .......... .......... .......... .......... 11% 57.8M 11s\n", + " 70550K .......... .......... .......... .......... .......... 11% 48.5M 11s\n", + " 70600K .......... .......... .......... .......... .......... 11% 58.6M 11s\n", + " 70650K .......... .......... .......... .......... .......... 11% 54.8M 11s\n", + " 70700K .......... .......... .......... .......... .......... 11% 66.9M 11s\n", + " 70750K .......... .......... .......... .......... .......... 11% 52.3M 11s\n", + " 70800K .......... .......... .......... .......... .......... 11% 47.7M 11s\n", + " 70850K .......... .......... .......... .......... .......... 11% 70.1M 11s\n", + " 70900K .......... .......... .......... .......... .......... 11% 77.3M 11s\n", + " 70950K .......... .......... .......... .......... .......... 11% 57.7M 11s\n", + " 71000K .......... .......... .......... .......... .......... 11% 55.0M 11s\n", + " 71050K .......... .......... .......... .......... .......... 11% 50.7M 11s\n", + " 71100K .......... .......... .......... .......... .......... 11% 64.0M 11s\n", + " 71150K .......... .......... .......... .......... .......... 11% 67.4M 11s\n", + " 71200K .......... .......... .......... .......... .......... 11% 57.5M 11s\n", + " 71250K .......... .......... .......... .......... .......... 11% 63.7M 11s\n", + " 71300K .......... .......... .......... .......... .......... 11% 63.2M 11s\n", + " 71350K .......... .......... .......... .......... .......... 12% 50.4M 11s\n", + " 71400K .......... .......... .......... .......... .......... 12% 53.8M 11s\n", + " 71450K .......... .......... .......... .......... .......... 12% 56.0M 11s\n", + " 71500K .......... .......... .......... .......... .......... 12% 3.64M 11s\n", + " 71550K .......... .......... .......... .......... .......... 12% 60.5M 11s\n", + " 71600K .......... .......... .......... .......... .......... 12% 56.6M 11s\n", + " 71650K .......... .......... .......... .......... .......... 12% 62.7M 11s\n", + " 71700K .......... .......... .......... .......... .......... 12% 65.7M 11s\n", + " 71750K .......... .......... .......... .......... .......... 12% 67.6M 11s\n", + " 71800K .......... .......... .......... .......... .......... 12% 45.3M 11s\n", + " 71850K .......... .......... .......... .......... .......... 12% 65.9M 11s\n", + " 71900K .......... .......... .......... .......... .......... 12% 64.2M 11s\n", + " 71950K .......... .......... .......... .......... .......... 12% 76.6M 11s\n", + " 72000K .......... .......... .......... .......... .......... 12% 3.91M 11s\n", + " 72050K .......... .......... .......... .......... .......... 12% 76.0M 11s\n", + " 72100K .......... .......... .......... .......... .......... 12% 56.5M 11s\n", + " 72150K .......... .......... .......... .......... .......... 12% 61.2M 11s\n", + " 72200K .......... .......... .......... .......... .......... 12% 50.9M 11s\n", + " 72250K .......... .......... .......... .......... .......... 12% 66.0M 11s\n", + " 72300K .......... .......... .......... .......... .......... 12% 66.9M 11s\n", + " 72350K .......... .......... .......... .......... .......... 12% 61.1M 11s\n", + " 72400K .......... .......... .......... .......... .......... 12% 56.7M 11s\n", + " 72450K .......... .......... .......... .......... .......... 12% 65.9M 11s\n", + " 72500K .......... .......... .......... .......... .......... 12% 49.8M 11s\n", + " 72550K .......... .......... .......... .......... .......... 12% 62.6M 11s\n", + " 72600K .......... .......... .......... .......... .......... 12% 47.2M 11s\n", + " 72650K .......... .......... .......... .......... .......... 12% 57.8M 11s\n", + " 72700K .......... .......... .......... .......... .......... 12% 70.6M 11s\n", + " 72750K .......... .......... .......... .......... .......... 12% 53.6M 11s\n", + " 72800K .......... .......... .......... .......... .......... 12% 59.0M 11s\n", + " 72850K .......... .......... .......... .......... .......... 12% 65.9M 11s\n", + " 72900K .......... .......... .......... .......... .......... 12% 49.7M 11s\n", + " 72950K .......... .......... .......... .......... .......... 12% 58.8M 11s\n", + " 73000K .......... .......... .......... .......... .......... 12% 45.9M 11s\n", + " 73050K .......... .......... .......... .......... .......... 12% 64.7M 11s\n", + " 73100K .......... .......... .......... .......... .......... 12% 70.1M 11s\n", + " 73150K .......... .......... .......... .......... 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.......... .......... 12% 67.8M 11s\n", + " 73800K .......... .......... .......... .......... .......... 12% 49.2M 11s\n", + " 73850K .......... .......... .......... .......... .......... 12% 64.0M 11s\n", + " 73900K .......... .......... .......... .......... .......... 12% 49.1M 11s\n", + " 73950K .......... .......... .......... .......... .......... 12% 47.5M 11s\n", + " 74000K .......... .......... .......... .......... .......... 12% 60.1M 11s\n", + " 74050K .......... .......... .......... .......... .......... 12% 60.6M 11s\n", + " 74100K .......... .......... .......... .......... .......... 12% 78.7M 11s\n", + " 74150K .......... .......... .......... .......... .......... 12% 56.8M 11s\n", + " 74200K .......... .......... .......... .......... .......... 12% 46.3M 11s\n", + " 74250K .......... .......... .......... .......... .......... 12% 64.2M 11s\n", + " 74300K .......... .......... .......... .......... .......... 12% 60.0M 11s\n", + " 74350K .......... .......... .......... .......... .......... 12% 66.7M 11s\n", + " 74400K .......... .......... .......... .......... .......... 12% 46.7M 11s\n", + " 74450K .......... .......... .......... .......... .......... 12% 57.0M 11s\n", + " 74500K .......... .......... .......... .......... .......... 12% 60.5M 11s\n", + " 74550K .......... .......... .......... .......... .......... 12% 63.7M 11s\n", + " 74600K .......... .......... .......... .......... .......... 12% 49.8M 11s\n", + " 74650K .......... .......... .......... .......... .......... 12% 68.0M 11s\n", + " 74700K .......... .......... .......... .......... .......... 12% 59.6M 11s\n", + " 74750K .......... .......... .......... .......... .......... 12% 55.2M 11s\n", + " 74800K .......... .......... .......... .......... .......... 12% 56.4M 11s\n", + " 74850K .......... .......... .......... .......... .......... 12% 52.5M 11s\n", + " 74900K .......... .......... .......... .......... .......... 12% 61.6M 11s\n", + " 74950K .......... .......... .......... .......... .......... 12% 60.9M 11s\n", + " 75000K .......... .......... .......... .......... .......... 12% 42.6M 11s\n", + " 75050K .......... .......... .......... .......... .......... 12% 52.0M 11s\n", + " 75100K .......... .......... .......... .......... .......... 12% 66.9M 11s\n", + " 75150K .......... .......... .......... .......... .......... 12% 67.3M 11s\n", + " 75200K .......... .......... .......... .......... .......... 12% 58.1M 11s\n", + " 75250K .......... .......... .......... .......... .......... 12% 43.9M 11s\n", + " 75300K .......... .......... .......... .......... .......... 12% 50.3M 11s\n", + " 75350K .......... .......... .......... .......... .......... 12% 60.0M 11s\n", + " 75400K .......... .......... .......... .......... .......... 12% 57.7M 11s\n", + " 75450K .......... .......... .......... .......... .......... 12% 56.0M 11s\n", + " 75500K .......... .......... .......... .......... .......... 12% 46.8M 11s\n", + " 75550K .......... .......... .......... .......... .......... 12% 51.0M 11s\n", + " 75600K .......... .......... .......... .......... .......... 12% 55.5M 11s\n", + " 75650K .......... .......... .......... .......... .......... 12% 65.3M 11s\n", + " 75700K .......... .......... .......... .......... .......... 12% 56.6M 11s\n", + " 75750K .......... .......... .......... .......... .......... 12% 43.6M 11s\n", + " 75800K .......... .......... .......... .......... .......... 12% 51.3M 11s\n", + " 75850K .......... .......... .......... .......... .......... 12% 69.8M 11s\n", + " 75900K .......... .......... .......... .......... .......... 12% 72.7M 11s\n", + " 75950K .......... .......... .......... .......... .......... 12% 84.1M 11s\n", + " 76000K .......... .......... .......... .......... .......... 12% 62.1M 11s\n", + " 76050K .......... .......... .......... .......... .......... 12% 69.7M 11s\n", + " 76100K .......... .......... .......... .......... .......... 12% 80.2M 11s\n", + " 76150K .......... .......... .......... .......... .......... 12% 62.3M 11s\n", + " 76200K .......... .......... .......... .......... .......... 12% 53.2M 11s\n", + " 76250K .......... .......... .......... .......... .......... 12% 50.7M 11s\n", + " 76300K .......... .......... .......... .......... .......... 12% 56.2M 11s\n", + " 76350K .......... .......... .......... .......... .......... 12% 62.8M 11s\n", + " 76400K .......... .......... .......... .......... .......... 12% 61.5M 11s\n", + " 76450K .......... .......... .......... .......... .......... 12% 68.8M 11s\n", + " 76500K .......... .......... .......... .......... .......... 12% 52.8M 11s\n", + " 76550K .......... .......... .......... .......... .......... 12% 3.84M 11s\n", + " 76600K .......... .......... .......... .......... .......... 12% 45.7M 11s\n", + " 76650K .......... .......... .......... .......... .......... 12% 62.0M 11s\n", + " 76700K .......... .......... .......... .......... .......... 12% 68.1M 11s\n", + " 76750K .......... .......... .......... .......... .......... 12% 67.6M 11s\n", + " 76800K .......... .......... .......... .......... .......... 12% 52.1M 11s\n", + " 76850K .......... .......... .......... .......... .......... 12% 49.2M 11s\n", + " 76900K .......... .......... .......... .......... .......... 12% 50.9M 11s\n", + " 76950K .......... .......... .......... .......... .......... 12% 60.2M 11s\n", + " 77000K .......... .......... .......... .......... .......... 12% 54.9M 11s\n", + " 77050K .......... .......... .......... .......... .......... 12% 61.9M 11s\n", + " 77100K .......... .......... .......... .......... .......... 12% 58.8M 11s\n", + " 77150K .......... .......... .......... .......... .......... 12% 49.3M 11s\n", + " 77200K .......... .......... .......... .......... .......... 12% 49.2M 11s\n", + " 77250K .......... .......... .......... .......... .......... 12% 57.2M 11s\n", + " 77300K .......... .......... .......... .......... .......... 13% 62.5M 11s\n", + " 77350K .......... .......... .......... .......... .......... 13% 59.9M 11s\n", + " 77400K .......... .......... .......... .......... .......... 13% 41.6M 11s\n", + " 77450K .......... .......... .......... .......... .......... 13% 49.9M 11s\n", + " 77500K .......... .......... .......... .......... .......... 13% 57.5M 11s\n", + " 77550K .......... .......... .......... .......... .......... 13% 67.4M 11s\n", + " 77600K .......... .......... .......... .......... .......... 13% 27.9M 11s\n", + " 77650K .......... .......... .......... .......... .......... 13% 28.9M 11s\n", + " 77700K .......... .......... .......... .......... .......... 13% 53.4M 11s\n", + " 77750K .......... .......... .......... .......... .......... 13% 69.5M 11s\n", + " 77800K .......... .......... .......... .......... .......... 13% 53.2M 11s\n", + " 77850K .......... .......... .......... .......... .......... 13% 52.6M 11s\n", + " 77900K .......... .......... .......... .......... .......... 13% 67.6M 11s\n", + " 77950K .......... .......... .......... .......... .......... 13% 66.3M 11s\n", + " 78000K .......... .......... .......... .......... .......... 13% 58.3M 11s\n", + " 78050K .......... .......... .......... .......... .......... 13% 57.4M 11s\n", + " 78100K .......... .......... .......... .......... .......... 13% 47.9M 11s\n", + " 78150K .......... .......... .......... .......... .......... 13% 47.0M 11s\n", + " 78200K .......... .......... .......... .......... .......... 13% 43.8M 11s\n", + " 78250K .......... .......... .......... .......... .......... 13% 70.6M 11s\n", + " 78300K .......... .......... .......... .......... .......... 13% 64.4M 11s\n", + " 78350K .......... .......... .......... .......... .......... 13% 64.3M 11s\n", + " 78400K .......... .......... .......... .......... .......... 13% 41.5M 11s\n", + " 78450K .......... .......... .......... .......... .......... 13% 71.3M 11s\n", + " 78500K .......... .......... .......... .......... .......... 13% 80.3M 11s\n", + " 78550K .......... .......... .......... .......... .......... 13% 68.4M 11s\n", + " 78600K .......... .......... .......... .......... .......... 13% 52.3M 11s\n", + " 78650K .......... .......... .......... .......... .......... 13% 61.7M 11s\n", + " 78700K .......... .......... .......... .......... .......... 13% 67.9M 11s\n", + " 78750K .......... .......... .......... .......... .......... 13% 73.5M 11s\n", + " 78800K .......... .......... .......... .......... .......... 13% 64.2M 11s\n", + " 78850K .......... .......... .......... .......... .......... 13% 80.6M 11s\n", + " 78900K .......... .......... .......... .......... .......... 13% 61.1M 11s\n", + " 78950K .......... .......... .......... .......... .......... 13% 58.0M 11s\n", + " 79000K .......... .......... .......... .......... .......... 13% 39.1M 11s\n", + " 79050K .......... .......... .......... .......... .......... 13% 70.1M 11s\n", + " 79100K .......... .......... .......... .......... .......... 13% 65.9M 11s\n", + " 79150K .......... .......... .......... .......... .......... 13% 73.8M 11s\n", + " 79200K .......... .......... .......... .......... .......... 13% 61.7M 11s\n", + " 79250K .......... .......... .......... .......... .......... 13% 57.4M 11s\n", + " 79300K .......... .......... .......... .......... .......... 13% 48.3M 11s\n", + " 79350K .......... .......... .......... .......... .......... 13% 48.4M 11s\n", + " 79400K .......... .......... .......... .......... .......... 13% 39.2M 11s\n", + " 79450K .......... .......... .......... .......... .......... 13% 63.5M 11s\n", + " 79500K .......... .......... .......... .......... .......... 13% 70.3M 11s\n", + " 79550K .......... .......... .......... .......... .......... 13% 64.5M 11s\n", + " 79600K .......... .......... .......... .......... .......... 13% 50.3M 11s\n", + " 79650K .......... .......... .......... .......... .......... 13% 56.5M 11s\n", + " 79700K .......... .......... .......... .......... .......... 13% 47.2M 11s\n", + " 79750K .......... .......... .......... .......... .......... 13% 62.0M 11s\n", + " 79800K .......... .......... .......... .......... .......... 13% 43.0M 11s\n", + " 79850K .......... .......... .......... .......... .......... 13% 52.6M 11s\n", + " 79900K .......... .......... .......... .......... .......... 13% 57.2M 11s\n", + " 79950K .......... .......... .......... .......... .......... 13% 53.7M 11s\n", + " 80000K .......... .......... .......... .......... .......... 13% 65.4M 11s\n", + " 80050K .......... .......... .......... .......... .......... 13% 59.7M 11s\n", + " 80100K .......... .......... .......... .......... .......... 13% 53.4M 11s\n", + " 80150K .......... .......... .......... .......... .......... 13% 56.0M 11s\n", + " 80200K .......... .......... .......... .......... .......... 13% 50.2M 11s\n", + " 80250K .......... .......... .......... .......... .......... 13% 69.9M 11s\n", + " 80300K .......... .......... .......... .......... .......... 13% 59.8M 11s\n", + " 80350K .......... .......... .......... .......... .......... 13% 51.5M 11s\n", + " 80400K .......... .......... .......... .......... .......... 13% 53.2M 11s\n", + " 80450K .......... .......... .......... .......... .......... 13% 60.8M 11s\n", + " 80500K .......... .......... .......... .......... .......... 13% 62.9M 11s\n", + " 80550K .......... .......... .......... .......... .......... 13% 69.0M 11s\n", + " 80600K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", + " 80650K .......... .......... .......... .......... .......... 13% 51.1M 11s\n", + " 80700K .......... .......... .......... .......... .......... 13% 61.9M 11s\n", + " 80750K .......... .......... .......... .......... .......... 13% 56.2M 11s\n", + " 80800K .......... .......... .......... .......... .......... 13% 64.9M 11s\n", + " 80850K .......... .......... .......... .......... .......... 13% 54.5M 11s\n", + " 80900K .......... .......... .......... .......... .......... 13% 55.4M 11s\n", + " 80950K .......... .......... .......... .......... .......... 13% 46.9M 11s\n", + " 81000K .......... .......... .......... .......... .......... 13% 50.0M 11s\n", + " 81050K .......... .......... .......... .......... .......... 13% 71.6M 11s\n", + " 81100K .......... .......... .......... .......... .......... 13% 64.6M 11s\n", + " 81150K .......... .......... .......... .......... .......... 13% 60.2M 11s\n", + " 81200K .......... .......... .......... .......... .......... 13% 50.5M 11s\n", + " 81250K .......... .......... .......... .......... .......... 13% 62.5M 11s\n", + " 81300K .......... .......... .......... .......... .......... 13% 75.5M 11s\n", + " 81350K .......... .......... .......... .......... .......... 13% 75.5M 11s\n", + " 81400K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", + " 81450K .......... .......... .......... .......... .......... 13% 51.1M 11s\n", + " 81500K .......... .......... .......... .......... .......... 13% 69.7M 11s\n", + " 81550K .......... .......... .......... .......... .......... 13% 60.2M 11s\n", + " 81600K .......... .......... .......... .......... .......... 13% 61.5M 11s\n", + " 81650K .......... .......... .......... .......... .......... 13% 52.9M 11s\n", + " 81700K .......... .......... .......... .......... .......... 13% 48.9M 11s\n", " 81750K .......... .......... .......... .......... .......... 13% 64.3M 11s\n", - " 81800K .......... .......... .......... .......... .......... 13% 56.6M 11s\n", - " 81850K .......... .......... .......... .......... .......... 13% 70.9M 11s\n", - " 81900K .......... .......... .......... .......... .......... 13% 47.6M 11s\n", - " 81950K .......... .......... .......... .......... .......... 13% 50.3M 11s\n", - " 82000K .......... .......... .......... .......... .......... 13% 59.3M 11s\n", - " 82050K .......... .......... .......... .......... .......... 13% 65.4M 11s\n", - " 82100K .......... .......... .......... .......... .......... 13% 58.1M 11s\n", - " 82150K .......... .......... .......... .......... .......... 13% 54.5M 11s\n", - " 82200K .......... .......... .......... .......... .......... 13% 39.4M 11s\n", - " 82250K .......... .......... .......... .......... .......... 13% 61.7M 11s\n", - " 82300K .......... .......... .......... .......... .......... 13% 70.5M 11s\n", - " 82350K .......... .......... .......... .......... .......... 13% 62.4M 11s\n", - " 82400K .......... .......... .......... .......... .......... 13% 3.82M 11s\n", - " 82450K .......... .......... .......... .......... .......... 13% 17.9M 11s\n", - " 82500K .......... .......... .......... .......... .......... 13% 68.7M 11s\n", - " 82550K .......... .......... .......... .......... .......... 13% 3.90M 12s\n", - " 82600K .......... .......... .......... .......... .......... 13% 50.7M 12s\n", - " 82650K .......... .......... .......... .......... .......... 13% 65.7M 12s\n", - " 82700K .......... .......... .......... .......... .......... 13% 58.5M 12s\n", - " 82750K .......... .......... .......... .......... .......... 13% 64.8M 12s\n", - " 82800K .......... .......... .......... .......... .......... 13% 56.7M 12s\n", - " 82850K .......... .......... .......... .......... .......... 13% 63.4M 12s\n", - " 82900K .......... .......... .......... .......... .......... 13% 57.3M 12s\n", - " 82950K .......... .......... .......... .......... .......... 13% 66.7M 11s\n", - " 83000K .......... .......... .......... .......... .......... 13% 55.2M 11s\n", - " 83050K .......... .......... .......... .......... .......... 13% 60.5M 11s\n", - " 83100K .......... .......... .......... .......... .......... 13% 60.3M 11s\n", - " 83150K .......... .......... .......... .......... .......... 13% 56.2M 11s\n", - " 83200K .......... .......... .......... .......... .......... 13% 53.2M 11s\n", - " 83250K .......... .......... .......... .......... .......... 14% 67.3M 11s\n", - " 83300K .......... .......... .......... .......... .......... 14% 66.8M 11s\n", - " 83350K .......... .......... .......... .......... .......... 14% 55.7M 11s\n", - " 83400K .......... .......... .......... .......... .......... 14% 50.8M 11s\n", - " 83450K .......... .......... .......... .......... .......... 14% 62.6M 11s\n", - " 83500K .......... .......... .......... .......... .......... 14% 73.1M 11s\n", - " 83550K .......... .......... .......... .......... .......... 14% 55.5M 11s\n", - " 83600K .......... .......... .......... .......... .......... 14% 53.4M 11s\n", - " 83650K .......... .......... .......... .......... .......... 14% 62.0M 11s\n", - " 83700K .......... .......... .......... .......... .......... 14% 51.0M 11s\n", - " 83750K .......... .......... .......... .......... .......... 14% 65.1M 11s\n", - " 83800K .......... .......... .......... .......... .......... 14% 49.2M 11s\n", - " 83850K .......... .......... .......... .......... .......... 14% 22.9M 11s\n", - " 83900K .......... .......... .......... .......... .......... 14% 47.7M 11s\n", - " 83950K .......... .......... .......... .......... .......... 14% 66.8M 11s\n", - " 84000K .......... .......... .......... .......... .......... 14% 32.3M 11s\n", - " 84050K .......... .......... .......... .......... .......... 14% 67.9M 11s\n", - " 84100K .......... .......... .......... .......... .......... 14% 69.1M 11s\n", - " 84150K .......... .......... .......... .......... .......... 14% 51.9M 11s\n", - " 84200K .......... .......... .......... .......... .......... 14% 39.3M 11s\n", - " 84250K .......... .......... .......... .......... .......... 14% 55.2M 11s\n", - " 84300K .......... .......... .......... .......... .......... 14% 58.0M 11s\n", - " 84350K .......... .......... .......... .......... .......... 14% 57.5M 11s\n", - " 84400K .......... .......... .......... .......... .......... 14% 43.6M 11s\n", - " 84450K .......... .......... .......... .......... .......... 14% 51.1M 11s\n", - " 84500K .......... .......... .......... .......... .......... 14% 52.5M 11s\n", - " 84550K .......... .......... .......... .......... .......... 14% 48.0M 11s\n", - " 84600K .......... .......... .......... .......... .......... 14% 40.7M 11s\n", - " 84650K .......... .......... .......... .......... .......... 14% 51.5M 11s\n", - " 84700K .......... .......... .......... .......... .......... 14% 57.8M 11s\n", - " 84750K .......... .......... .......... .......... .......... 14% 53.2M 11s\n", - " 84800K .......... .......... .......... .......... .......... 14% 54.5M 11s\n", - " 84850K .......... .......... .......... .......... .......... 14% 52.8M 11s\n", - " 84900K .......... .......... .......... .......... .......... 14% 5.51M 11s\n", - " 84950K .......... .......... .......... .......... .......... 14% 70.8M 11s\n", - " 85000K .......... .......... .......... .......... .......... 14% 62.1M 11s\n", - " 85050K .......... .......... .......... .......... .......... 14% 58.2M 11s\n", - " 85100K .......... .......... .......... .......... .......... 14% 64.1M 11s\n", - " 85150K .......... .......... .......... .......... .......... 14% 63.4M 11s\n", - " 85200K .......... .......... .......... .......... .......... 14% 35.9M 11s\n", - " 85250K .......... .......... .......... .......... .......... 14% 62.4M 11s\n", - " 85300K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", - " 85350K .......... .......... .......... .......... .......... 14% 52.4M 11s\n", - " 85400K .......... .......... .......... .......... .......... 14% 55.1M 11s\n", - " 85450K .......... .......... .......... .......... .......... 14% 49.9M 11s\n", - " 85500K .......... .......... .......... .......... .......... 14% 62.7M 11s\n", - " 85550K .......... .......... .......... .......... .......... 14% 65.0M 11s\n", - " 85600K .......... .......... .......... .......... .......... 14% 47.2M 11s\n", - " 85650K .......... .......... .......... .......... .......... 14% 66.7M 11s\n", - " 85700K .......... .......... .......... .......... .......... 14% 62.3M 11s\n", - " 85750K .......... .......... .......... .......... .......... 14% 51.7M 11s\n", - " 85800K .......... .......... .......... .......... .......... 14% 42.5M 11s\n", - " 85850K .......... .......... .......... .......... .......... 14% 60.6M 11s\n", - " 85900K .......... .......... .......... .......... .......... 14% 66.7M 11s\n", - " 85950K .......... .......... .......... .......... .......... 14% 48.9M 11s\n", - " 86000K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", - " 86050K .......... .......... .......... .......... .......... 14% 66.6M 11s\n", - " 86100K .......... .......... .......... .......... .......... 14% 51.5M 11s\n", - " 86150K .......... .......... .......... .......... .......... 14% 54.0M 11s\n", - " 86200K .......... .......... .......... .......... .......... 14% 42.2M 11s\n", - " 86250K .......... .......... .......... .......... .......... 14% 66.4M 11s\n", - " 86300K .......... .......... .......... .......... .......... 14% 71.4M 11s\n", - " 86350K .......... .......... .......... .......... .......... 14% 42.1M 11s\n", - " 86400K .......... .......... .......... .......... .......... 14% 47.4M 11s\n", - " 86450K .......... .......... .......... .......... .......... 14% 50.4M 11s\n", - " 86500K .......... .......... .......... .......... .......... 14% 67.8M 11s\n", - " 86550K .......... .......... .......... .......... .......... 14% 61.0M 11s\n", - " 86600K .......... .......... .......... .......... .......... 14% 43.9M 11s\n", - " 86650K .......... .......... .......... .......... .......... 14% 60.0M 11s\n", - " 86700K .......... .......... .......... .......... .......... 14% 53.8M 11s\n", - " 86750K .......... .......... .......... .......... .......... 14% 71.8M 11s\n", - " 86800K .......... .......... .......... .......... .......... 14% 51.4M 11s\n", - " 86850K .......... .......... .......... .......... .......... 14% 38.8M 11s\n", - " 86900K .......... .......... .......... .......... .......... 14% 44.1M 11s\n", - " 86950K .......... .......... .......... .......... .......... 14% 61.4M 11s\n", - " 87000K .......... .......... .......... .......... .......... 14% 56.8M 11s\n", - " 87050K .......... .......... .......... .......... .......... 14% 54.9M 11s\n", - " 87100K .......... .......... .......... .......... .......... 14% 46.3M 11s\n", - " 87150K .......... .......... .......... .......... .......... 14% 51.6M 11s\n", - " 87200K .......... .......... .......... .......... .......... 14% 58.7M 11s\n", - " 87250K .......... .......... .......... .......... .......... 14% 66.3M 11s\n", - " 87300K .......... .......... .......... .......... .......... 14% 52.6M 11s\n", - " 87350K .......... .......... .......... .......... .......... 14% 52.2M 11s\n", - " 87400K .......... .......... .......... .......... .......... 14% 42.9M 11s\n", - " 87450K .......... .......... .......... .......... .......... 14% 68.0M 11s\n", - " 87500K .......... .......... .......... .......... .......... 14% 70.1M 11s\n", - " 87550K .......... .......... .......... .......... .......... 14% 58.4M 11s\n", - " 87600K .......... .......... .......... .......... .......... 14% 45.2M 11s\n", - " 87650K .......... .......... .......... .......... .......... 14% 3.58M 11s\n", - " 87700K .......... .......... .......... .......... .......... 14% 59.9M 11s\n", - " 87750K .......... .......... .......... .......... .......... 14% 59.8M 11s\n", - " 87800K .......... .......... .......... .......... .......... 14% 34.5M 11s\n", - " 87850K .......... .......... .......... .......... .......... 14% 31.7M 11s\n", - " 87900K .......... .......... .......... .......... .......... 14% 39.1M 11s\n", - " 87950K .......... .......... .......... .......... .......... 14% 33.9M 11s\n", - " 88000K .......... .......... .......... .......... .......... 14% 30.6M 11s\n", - " 88050K .......... .......... .......... .......... .......... 14% 46.2M 11s\n", - " 88100K .......... .......... .......... .......... .......... 14% 47.8M 11s\n", - " 88150K .......... .......... .......... .......... .......... 14% 55.5M 11s\n", - " 88200K .......... .......... .......... .......... .......... 14% 36.2M 11s\n", - " 88250K .......... .......... .......... .......... .......... 14% 57.5M 11s\n", - " 88300K .......... .......... .......... .......... .......... 14% 66.4M 11s\n", - " 88350K .......... .......... .......... .......... .......... 14% 60.4M 11s\n", - " 88400K .......... .......... .......... .......... .......... 14% 50.7M 11s\n", - " 88450K .......... .......... .......... .......... .......... 14% 58.2M 11s\n", - " 88500K .......... .......... .......... .......... .......... 14% 56.9M 11s\n", - " 88550K .......... .......... .......... .......... .......... 14% 64.8M 11s\n", - " 88600K .......... .......... .......... .......... .......... 14% 45.9M 11s\n", - " 88650K .......... .......... .......... .......... .......... 14% 48.9M 11s\n", - " 88700K .......... .......... .......... .......... .......... 14% 53.4M 11s\n", - " 88750K .......... .......... .......... .......... .......... 14% 65.4M 11s\n", - " 88800K .......... .......... .......... .......... .......... 14% 44.4M 11s\n", - " 88850K .......... .......... .......... .......... .......... 14% 48.3M 11s\n", - " 88900K .......... .......... .......... .......... .......... 14% 64.4M 11s\n", - " 88950K .......... .......... .......... .......... .......... 14% 48.5M 11s\n", - " 89000K .......... .......... .......... .......... .......... 14% 51.4M 11s\n", - " 89050K .......... .......... .......... .......... .......... 14% 69.0M 11s\n", - " 89100K .......... .......... .......... .......... .......... 14% 48.2M 11s\n", - " 89150K .......... .......... .......... .......... .......... 14% 41.5M 11s\n", - " 89200K .......... .......... .......... .......... .......... 15% 3.49M 11s\n", - " 89250K .......... .......... .......... .......... .......... 15% 58.9M 11s\n", - " 89300K .......... .......... .......... .......... .......... 15% 9.58M 11s\n", - " 89350K .......... .......... .......... .......... .......... 15% 47.1M 11s\n", - " 89400K .......... .......... .......... .......... .......... 15% 35.5M 11s\n", - " 89450K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", - " 89500K .......... .......... .......... .......... .......... 15% 66.0M 11s\n", - " 89550K .......... .......... .......... .......... .......... 15% 47.4M 11s\n", - " 89600K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", - " 89650K .......... .......... .......... .......... .......... 15% 57.9M 11s\n", - " 89700K .......... .......... .......... .......... .......... 15% 69.5M 11s\n", - " 89750K .......... .......... .......... .......... .......... 15% 47.8M 11s\n", - " 89800K .......... .......... .......... .......... .......... 15% 42.9M 11s\n", - " 89850K .......... .......... .......... .......... .......... 15% 41.7M 11s\n", - " 89900K .......... .......... .......... .......... .......... 15% 52.1M 11s\n", - " 89950K .......... .......... .......... .......... .......... 15% 70.6M 11s\n", - " 90000K .......... .......... .......... .......... .......... 15% 56.5M 11s\n", - " 90050K .......... .......... .......... .......... .......... 15% 50.3M 11s\n", - " 90100K .......... .......... .......... .......... .......... 15% 48.4M 11s\n", - " 90150K .......... .......... .......... .......... .......... 15% 54.8M 11s\n", - " 90200K .......... .......... .......... .......... .......... 15% 55.2M 11s\n", - " 90250K .......... .......... .......... .......... .......... 15% 67.4M 11s\n", - " 90300K .......... .......... .......... .......... .......... 15% 62.5M 11s\n", - " 90350K .......... .......... .......... .......... .......... 15% 49.0M 11s\n", - " 90400K .......... .......... .......... .......... .......... 15% 49.1M 11s\n", - " 90450K .......... .......... .......... .......... .......... 15% 72.4M 11s\n", - " 90500K .......... .......... .......... .......... .......... 15% 67.7M 11s\n", - " 90550K .......... .......... .......... .......... .......... 15% 66.7M 11s\n", - " 90600K .......... .......... .......... .......... .......... 15% 34.5M 11s\n", - " 90650K .......... .......... .......... .......... .......... 15% 48.0M 11s\n", - " 90700K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", - " 90750K .......... .......... .......... .......... .......... 15% 54.7M 11s\n", - " 90800K .......... .......... .......... .......... .......... 15% 25.7M 11s\n", - " 90850K .......... .......... .......... .......... .......... 15% 35.2M 11s\n", - " 90900K .......... .......... .......... .......... .......... 15% 44.7M 11s\n", - " 90950K .......... .......... .......... .......... .......... 15% 47.9M 11s\n", - " 91000K .......... .......... .......... .......... .......... 15% 37.3M 11s\n", - " 91050K .......... .......... .......... .......... .......... 15% 43.7M 11s\n", - " 91100K .......... .......... .......... .......... .......... 15% 44.5M 11s\n", - " 91150K .......... .......... .......... .......... .......... 15% 34.1M 11s\n", - " 91200K .......... .......... .......... .......... .......... 15% 30.6M 11s\n", - " 91250K .......... .......... .......... .......... .......... 15% 44.0M 11s\n", - " 91300K .......... .......... .......... .......... .......... 15% 44.0M 11s\n", - " 91350K .......... .......... .......... .......... .......... 15% 53.0M 11s\n", - " 91400K .......... .......... .......... .......... .......... 15% 52.7M 11s\n", - " 91450K .......... .......... .......... .......... .......... 15% 54.7M 11s\n", - " 91500K .......... .......... .......... .......... .......... 15% 39.6M 11s\n", - " 91550K .......... .......... .......... .......... .......... 15% 37.1M 11s\n", - " 91600K .......... .......... .......... .......... .......... 15% 31.7M 11s\n", - " 91650K .......... .......... .......... .......... .......... 15% 47.2M 11s\n", - " 91700K .......... .......... .......... .......... .......... 15% 47.1M 11s\n", - " 91750K .......... .......... .......... .......... .......... 15% 56.7M 11s\n", - " 91800K .......... .......... .......... .......... .......... 15% 46.9M 11s\n", - " 91850K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", - " 91900K .......... .......... .......... .......... .......... 15% 4.61M 11s\n", - " 91950K .......... .......... .......... .......... .......... 15% 46.8M 11s\n", - " 92000K .......... .......... .......... .......... .......... 15% 36.8M 11s\n", - " 92050K .......... .......... .......... .......... .......... 15% 39.1M 11s\n", - " 92100K .......... .......... .......... .......... .......... 15% 33.0M 11s\n", - " 92150K .......... .......... .......... .......... .......... 15% 43.3M 11s\n", - " 92200K .......... .......... .......... .......... .......... 15% 50.0M 11s\n", - " 92250K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", - " 92300K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", - " 92350K .......... .......... .......... .......... .......... 15% 59.5M 11s\n", - " 92400K .......... .......... .......... .......... .......... 15% 52.4M 11s\n", - " 92450K .......... .......... .......... .......... .......... 15% 14.2M 11s\n", - " 92500K .......... .......... .......... .......... .......... 15% 45.9M 11s\n", - " 92550K .......... .......... .......... .......... .......... 15% 52.3M 11s\n", - " 92600K .......... .......... .......... .......... .......... 15% 53.7M 11s\n", - " 92650K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", - " 92700K .......... .......... .......... .......... .......... 15% 61.0M 11s\n", - " 92750K .......... .......... .......... .......... .......... 15% 50.9M 11s\n", - " 92800K .......... .......... .......... .......... .......... 15% 54.5M 11s\n", - " 92850K .......... .......... .......... .......... .......... 15% 64.2M 11s\n", - " 92900K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", - " 92950K .......... .......... .......... .......... .......... 15% 59.5M 11s\n", - " 93000K .......... .......... .......... .......... .......... 15% 42.0M 11s\n", - " 93050K .......... .......... .......... .......... .......... 15% 49.7M 11s\n", - " 93100K .......... .......... .......... .......... .......... 15% 64.4M 11s\n", - " 93150K .......... .......... .......... .......... .......... 15% 55.0M 11s\n", - " 93200K .......... .......... .......... .......... .......... 15% 59.4M 11s\n", - " 93250K .......... .......... .......... .......... .......... 15% 47.4M 11s\n", - " 93300K .......... .......... .......... .......... .......... 15% 47.2M 11s\n", - " 93350K .......... .......... .......... .......... .......... 15% 68.1M 11s\n", - " 93400K .......... .......... .......... .......... .......... 15% 58.6M 11s\n", - " 93450K .......... .......... .......... .......... .......... 15% 69.9M 11s\n", - " 93500K .......... .......... .......... .......... .......... 15% 57.6M 11s\n", - " 93550K .......... .......... .......... .......... .......... 15% 49.4M 11s\n", - " 93600K .......... .......... .......... .......... .......... 15% 52.3M 11s\n", - " 93650K .......... .......... .......... .......... .......... 15% 66.1M 11s\n", - " 93700K .......... .......... .......... .......... .......... 15% 65.3M 11s\n", - " 93750K .......... .......... .......... .......... .......... 15% 55.0M 11s\n", - " 93800K .......... .......... .......... .......... .......... 15% 3.81M 11s\n", - " 93850K .......... .......... .......... .......... .......... 15% 56.7M 11s\n", - " 93900K .......... .......... .......... .......... .......... 15% 67.9M 11s\n", - " 93950K .......... .......... .......... .......... .......... 15% 67.6M 11s\n", - " 94000K .......... .......... .......... .......... .......... 15% 52.6M 11s\n", - " 94050K .......... .......... .......... .......... .......... 15% 64.6M 11s\n", - " 94100K .......... .......... .......... .......... .......... 15% 69.7M 11s\n", - " 94150K .......... .......... .......... .......... .......... 15% 48.8M 11s\n", - " 94200K .......... .......... .......... .......... .......... 15% 53.6M 11s\n", - " 94250K .......... .......... .......... .......... .......... 15% 56.9M 11s\n", - " 94300K .......... .......... .......... .......... .......... 15% 47.5M 11s\n", - " 94350K .......... .......... .......... .......... .......... 15% 44.6M 11s\n", - " 94400K .......... .......... .......... .......... .......... 15% 52.0M 11s\n", - " 94450K .......... .......... .......... .......... .......... 15% 67.2M 11s\n", - " 94500K .......... .......... .......... .......... .......... 15% 68.7M 11s\n", - " 94550K .......... .......... .......... .......... .......... 15% 47.7M 11s\n", - " 94600K .......... .......... .......... .......... .......... 15% 40.5M 11s\n", - " 94650K .......... .......... .......... .......... .......... 15% 68.1M 11s\n", - " 94700K .......... .......... .......... .......... .......... 15% 68.0M 11s\n", - " 94750K .......... .......... .......... .......... .......... 15% 70.5M 11s\n", - " 94800K .......... .......... .......... .......... .......... 15% 9.29M 11s\n", - " 94850K .......... .......... .......... .......... .......... 15% 60.4M 11s\n", - " 94900K .......... .......... .......... .......... .......... 15% 66.6M 11s\n", - " 94950K .......... .......... .......... .......... .......... 15% 63.0M 11s\n", - " 95000K .......... .......... .......... .......... .......... 15% 53.9M 11s\n", - " 95050K .......... .......... .......... .......... .......... 15% 57.9M 11s\n", - " 95100K .......... .......... .......... .......... .......... 15% 48.0M 11s\n", - " 95150K .......... .......... .......... .......... .......... 16% 56.8M 11s\n", - " 95200K .......... .......... .......... .......... .......... 16% 61.1M 11s\n", - " 95250K .......... .......... .......... .......... .......... 16% 66.1M 11s\n", - " 95300K .......... .......... .......... .......... .......... 16% 63.8M 11s\n", - " 95350K .......... .......... .......... .......... .......... 16% 67.3M 11s\n", - " 95400K .......... .......... .......... .......... .......... 16% 35.2M 11s\n", - " 95450K .......... .......... .......... .......... .......... 16% 61.3M 11s\n", - " 95500K .......... .......... .......... .......... .......... 16% 66.1M 11s\n", - " 95550K .......... .......... .......... .......... .......... 16% 70.6M 11s\n", - " 95600K .......... .......... .......... .......... .......... 16% 53.5M 11s\n", - " 95650K .......... .......... .......... .......... .......... 16% 49.6M 11s\n", - " 95700K .......... .......... .......... .......... .......... 16% 49.0M 11s\n", - " 95750K .......... .......... .......... .......... .......... 16% 72.2M 11s\n", - " 95800K .......... .......... .......... .......... .......... 16% 60.5M 11s\n", - " 95850K .......... .......... .......... .......... .......... 16% 71.3M 11s\n", - " 95900K .......... .......... .......... .......... .......... 16% 48.7M 11s\n", - " 95950K .......... .......... .......... .......... .......... 16% 45.9M 11s\n", - " 96000K .......... .......... .......... .......... .......... 16% 57.2M 11s\n", - " 96050K .......... .......... .......... .......... .......... 16% 70.1M 11s\n", - " 96100K .......... .......... .......... .......... .......... 16% 73.7M 11s\n", - " 96150K .......... .......... .......... .......... .......... 16% 72.0M 11s\n", - " 96200K .......... .......... .......... .......... .......... 16% 37.1M 11s\n", - " 96250K .......... .......... .......... .......... .......... 16% 52.4M 11s\n", - " 96300K .......... .......... .......... .......... .......... 16% 61.4M 11s\n", - " 96350K .......... .......... .......... .......... .......... 16% 65.5M 11s\n", - " 96400K .......... .......... .......... .......... .......... 16% 45.2M 11s\n", - " 96450K .......... .......... .......... .......... .......... 16% 44.0M 11s\n", - " 96500K .......... .......... .......... .......... .......... 16% 53.9M 11s\n", - " 96550K .......... .......... .......... .......... .......... 16% 41.9M 11s\n", - " 96600K .......... .......... .......... .......... .......... 16% 10.1M 11s\n", - " 96650K .......... .......... .......... .......... .......... 16% 52.0M 11s\n", - " 96700K .......... .......... .......... .......... .......... 16% 49.1M 11s\n", - " 96750K .......... .......... .......... .......... .......... 16% 68.4M 11s\n", - " 96800K .......... .......... .......... .......... .......... 16% 56.8M 11s\n", - " 96850K .......... .......... .......... .......... .......... 16% 69.5M 11s\n", - " 96900K .......... .......... .......... .......... .......... 16% 50.8M 11s\n", - " 96950K .......... .......... .......... .......... .......... 16% 17.1M 11s\n", - " 97000K .......... .......... .......... .......... .......... 16% 53.9M 11s\n", - " 97050K .......... .......... .......... .......... .......... 16% 44.4M 11s\n", - " 97100K .......... .......... .......... .......... .......... 16% 50.6M 11s\n", - " 97150K .......... .......... .......... .......... .......... 16% 62.9M 11s\n", - " 97200K .......... .......... .......... .......... .......... 16% 60.1M 11s\n", - " 97250K .......... .......... .......... .......... .......... 16% 57.9M 11s\n", - " 97300K .......... .......... .......... .......... .......... 16% 42.2M 11s\n", - " 97350K .......... .......... .......... .......... .......... 16% 19.0M 11s\n", - " 97400K .......... .......... .......... .......... .......... 16% 43.5M 11s\n", - " 97450K .......... .......... .......... .......... .......... 16% 40.5M 11s\n", - " 97500K .......... .......... .......... .......... .......... 16% 57.8M 11s\n", - " 97550K .......... .......... .......... .......... .......... 16% 65.5M 11s\n", - " 97600K .......... .......... .......... .......... .......... 16% 59.8M 11s\n", - " 97650K .......... .......... .......... .......... .......... 16% 68.5M 11s\n", - " 97700K .......... .......... .......... .......... .......... 16% 48.2M 11s\n", - " 97750K .......... .......... .......... .......... .......... 16% 54.2M 11s\n", - " 97800K .......... .......... .......... .......... .......... 16% 59.6M 11s\n", - " 97850K .......... .......... .......... .......... .......... 16% 67.0M 11s\n", - " 97900K .......... .......... .......... .......... .......... 16% 67.4M 11s\n", - " 97950K .......... .......... .......... .......... .......... 16% 48.9M 11s\n", - " 98000K .......... .......... .......... .......... .......... 16% 42.2M 11s\n", - " 98050K .......... .......... .......... .......... .......... 16% 56.2M 11s\n", - " 98100K .......... .......... .......... .......... .......... 16% 69.9M 11s\n", - " 98150K .......... .......... .......... .......... .......... 16% 61.5M 11s\n", - " 98200K .......... .......... .......... .......... .......... 16% 45.2M 11s\n", - " 98250K .......... .......... .......... .......... .......... 16% 45.0M 11s\n", - " 98300K .......... .......... .......... .......... .......... 16% 65.8M 11s\n", - " 98350K .......... .......... .......... .......... .......... 16% 63.9M 11s\n", - " 98400K .......... .......... .......... .......... .......... 16% 60.2M 11s\n", - " 98450K .......... .......... .......... .......... .......... 16% 63.8M 11s\n", - " 98500K .......... .......... .......... .......... .......... 16% 47.8M 11s\n", - " 98550K .......... .......... .......... .......... .......... 16% 57.9M 11s\n", - " 98600K .......... .......... .......... .......... .......... 16% 57.2M 11s\n", - " 98650K .......... .......... .......... .......... .......... 16% 64.7M 11s\n", - " 98700K .......... .......... .......... .......... .......... 16% 66.8M 11s\n", - " 98750K .......... .......... .......... .......... .......... 16% 58.6M 11s\n", - " 98800K .......... .......... .......... .......... .......... 16% 47.0M 11s\n", - " 98850K .......... .......... .......... .......... .......... 16% 37.1M 11s\n", - " 98900K .......... .......... .......... .......... .......... 16% 47.3M 11s\n", - " 98950K .......... .......... .......... .......... .......... 16% 50.7M 11s\n", - " 99000K .......... .......... .......... .......... .......... 16% 50.3M 11s\n", - " 99050K .......... .......... .......... .......... .......... 16% 47.8M 11s\n", - " 99100K .......... .......... .......... .......... .......... 16% 36.0M 11s\n", - " 99150K .......... .......... .......... .......... .......... 16% 10.6M 11s\n", - " 99200K .......... .......... .......... .......... .......... 16% 56.3M 11s\n", - " 99250K .......... .......... .......... .......... .......... 16% 71.4M 11s\n", - " 99300K .......... .......... .......... .......... .......... 16% 69.4M 11s\n", - " 99350K .......... .......... .......... .......... .......... 16% 57.6M 11s\n", - " 99400K .......... .......... .......... .......... .......... 16% 32.8M 11s\n", - " 99450K .......... .......... .......... .......... .......... 16% 69.0M 11s\n", - " 99500K .......... .......... .......... .......... .......... 16% 68.5M 11s\n", - " 99550K .......... .......... .......... .......... .......... 16% 68.3M 11s\n", - " 99600K .......... .......... .......... .......... .......... 16% 47.2M 11s\n", - " 99650K .......... .......... .......... .......... .......... 16% 37.5M 11s\n", - " 99700K .......... .......... .......... .......... .......... 16% 58.5M 11s\n", - " 99750K .......... .......... .......... .......... .......... 16% 71.2M 11s\n", - " 99800K .......... .......... .......... .......... .......... 16% 57.7M 11s\n", - " 99850K .......... .......... .......... .......... .......... 16% 50.4M 11s\n", - " 99900K .......... .......... .......... .......... .......... 16% 44.7M 11s\n", - " 99950K .......... .......... .......... .......... .......... 16% 61.4M 11s\n", - "100000K .......... .......... .......... .......... .......... 16% 64.8M 11s\n", - "100050K .......... .......... .......... .......... .......... 16% 69.4M 11s\n", - "100100K .......... .......... .......... .......... .......... 16% 50.1M 11s\n", - "100150K .......... .......... .......... .......... .......... 16% 39.2M 11s\n", - "100200K .......... .......... .......... .......... .......... 16% 40.2M 11s\n", - "100250K .......... .......... .......... .......... .......... 16% 66.2M 11s\n", - "100300K .......... .......... .......... .......... .......... 16% 66.5M 11s\n", - "100350K .......... .......... .......... .......... .......... 16% 50.2M 11s\n", - "100400K .......... .......... .......... .......... .......... 16% 35.1M 11s\n", - "100450K .......... .......... .......... .......... .......... 16% 59.2M 11s\n", - "100500K .......... .......... .......... .......... .......... 16% 72.6M 11s\n", - "100550K .......... .......... .......... .......... .......... 16% 71.3M 11s\n", - "100600K .......... .......... .......... .......... .......... 16% 43.0M 11s\n", - "100650K .......... .......... .......... .......... .......... 16% 41.1M 11s\n", - "100700K .......... .......... .......... .......... .......... 16% 59.0M 11s\n", - "100750K .......... .......... .......... .......... .......... 16% 66.2M 11s\n", - "100800K .......... .......... .......... .......... .......... 16% 60.1M 11s\n", - "100850K .......... .......... .......... .......... .......... 16% 46.8M 11s\n", - "100900K .......... .......... .......... .......... .......... 16% 40.9M 11s\n", - "100950K .......... .......... .......... .......... .......... 16% 60.5M 11s\n", - "101000K .......... .......... .......... .......... .......... 16% 60.3M 11s\n", - "101050K .......... .......... .......... .......... .......... 16% 61.0M 11s\n", - "101100K .......... .......... .......... .......... .......... 17% 46.9M 11s\n", - "101150K .......... .......... .......... .......... .......... 17% 42.2M 11s\n", - "101200K .......... .......... .......... .......... .......... 17% 51.9M 11s\n", - "101250K .......... .......... .......... .......... .......... 17% 66.0M 11s\n", - "101300K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", - "101350K .......... .......... .......... .......... .......... 17% 41.0M 11s\n", - "101400K .......... .......... .......... .......... .......... 17% 32.7M 11s\n", - "101450K .......... .......... .......... .......... .......... 17% 68.8M 11s\n", - "101500K .......... .......... .......... .......... .......... 17% 67.3M 11s\n", - "101550K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", - "101600K .......... .......... .......... .......... .......... 17% 38.3M 11s\n", - "101650K .......... .......... .......... .......... .......... 17% 40.8M 11s\n", - "101700K .......... .......... .......... .......... .......... 17% 66.6M 11s\n", - "101750K .......... .......... .......... .......... .......... 17% 68.6M 11s\n", - "101800K .......... .......... .......... .......... .......... 17% 46.8M 11s\n", - "101850K .......... .......... .......... .......... .......... 17% 39.0M 11s\n", - "101900K .......... .......... .......... .......... .......... 17% 56.2M 11s\n", - "101950K .......... .......... .......... .......... .......... 17% 71.9M 11s\n", - "102000K .......... .......... .......... .......... .......... 17% 62.4M 11s\n", - "102050K .......... .......... .......... .......... .......... 17% 4.93M 11s\n", - "102100K .......... .......... .......... .......... .......... 17% 67.4M 11s\n", - "102150K .......... .......... .......... .......... .......... 17% 66.4M 11s\n", - "102200K .......... .......... .......... .......... .......... 17% 56.9M 11s\n", - "102250K .......... .......... .......... .......... .......... 17% 69.4M 11s\n", - "102300K .......... .......... .......... .......... .......... 17% 61.6M 11s\n", - "102350K .......... .......... .......... .......... .......... 17% 38.6M 11s\n", - "102400K .......... .......... .......... .......... .......... 17% 54.9M 11s\n", - "102450K .......... .......... .......... .......... .......... 17% 74.6M 11s\n", - "102500K .......... .......... .......... .......... .......... 17% 82.8M 11s\n", - "102550K .......... .......... .......... .......... .......... 17% 80.3M 11s\n", - "102600K .......... .......... .......... .......... .......... 17% 57.1M 11s\n", - "102650K .......... .......... .......... .......... .......... 17% 50.3M 11s\n", - "102700K .......... .......... .......... .......... .......... 17% 47.4M 11s\n", - "102750K .......... .......... .......... .......... .......... 17% 4.23M 11s\n", - "102800K .......... .......... .......... .......... .......... 17% 59.5M 11s\n", - "102850K .......... .......... .......... .......... .......... 17% 63.6M 11s\n", - "102900K .......... .......... .......... .......... .......... 17% 59.7M 11s\n", - "102950K .......... .......... .......... .......... .......... 17% 63.8M 11s\n", - "103000K .......... .......... .......... .......... .......... 17% 53.2M 11s\n", - "103050K .......... .......... .......... .......... .......... 17% 45.0M 11s\n", - "103100K .......... .......... .......... .......... .......... 17% 63.3M 11s\n", - "103150K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", - "103200K .......... .......... .......... .......... .......... 17% 56.7M 11s\n", - "103250K .......... .......... .......... .......... .......... 17% 61.3M 11s\n", - "103300K .......... .......... .......... .......... .......... 17% 57.2M 11s\n", - "103350K .......... .......... .......... .......... .......... 17% 46.7M 11s\n", - "103400K .......... .......... .......... .......... .......... 17% 53.8M 11s\n", - "103450K .......... .......... .......... .......... .......... 17% 69.3M 11s\n", - "103500K .......... .......... .......... .......... .......... 17% 70.7M 11s\n", - "103550K .......... .......... .......... .......... .......... 17% 4.12M 11s\n", - "103600K .......... .......... .......... .......... .......... 17% 62.3M 11s\n", - "103650K .......... .......... .......... .......... .......... 17% 58.3M 11s\n", - "103700K .......... .......... .......... .......... .......... 17% 66.1M 11s\n", - "103750K .......... .......... .......... .......... .......... 17% 65.4M 11s\n", - "103800K .......... .......... .......... .......... .......... 17% 51.5M 11s\n", - "103850K .......... .......... .......... .......... .......... 17% 57.2M 11s\n", - "103900K .......... .......... .......... .......... .......... 17% 60.9M 11s\n", - "103950K .......... .......... .......... .......... .......... 17% 51.7M 11s\n", - "104000K .......... .......... .......... .......... .......... 17% 52.6M 11s\n", - "104050K .......... .......... .......... .......... .......... 17% 66.1M 11s\n", - "104100K .......... .......... .......... .......... .......... 17% 60.3M 11s\n", - "104150K .......... .......... .......... .......... .......... 17% 4.06M 11s\n", - "104200K .......... .......... .......... .......... .......... 17% 44.1M 11s\n", - "104250K .......... .......... .......... .......... .......... 17% 59.6M 11s\n", - "104300K .......... .......... .......... .......... .......... 17% 63.9M 11s\n", - "104350K .......... .......... .......... .......... .......... 17% 72.1M 11s\n", - "104400K .......... .......... .......... .......... .......... 17% 13.9M 11s\n", - "104450K .......... .......... .......... .......... .......... 17% 61.4M 11s\n", - "104500K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", - "104550K .......... .......... .......... .......... .......... 17% 67.3M 11s\n", - "104600K .......... .......... .......... .......... .......... 17% 40.2M 11s\n", - "104650K .......... .......... .......... .......... .......... 17% 52.8M 11s\n", - "104700K .......... .......... .......... .......... .......... 17% 55.2M 11s\n", - "104750K .......... .......... .......... .......... .......... 17% 66.1M 11s\n", - "104800K .......... .......... .......... .......... .......... 17% 56.3M 11s\n", - "104850K .......... .......... .......... .......... .......... 17% 53.9M 11s\n", - "104900K .......... .......... .......... .......... .......... 17% 55.9M 11s\n", - "104950K .......... .......... .......... .......... .......... 17% 63.4M 11s\n", - "105000K .......... .......... .......... .......... .......... 17% 58.3M 11s\n", - "105050K .......... .......... .......... .......... .......... 17% 61.5M 11s\n", - "105100K .......... .......... .......... .......... .......... 17% 49.5M 11s\n", - "105150K .......... .......... .......... .......... .......... 17% 52.2M 11s\n", - "105200K .......... .......... .......... .......... .......... 17% 51.9M 11s\n", - "105250K .......... .......... .......... .......... .......... 17% 64.8M 11s\n", - "105300K .......... .......... .......... .......... .......... 17% 65.3M 11s\n", - "105350K .......... .......... .......... .......... .......... 17% 59.6M 11s\n", - "105400K .......... .......... .......... .......... .......... 17% 36.6M 11s\n", - "105450K .......... .......... .......... .......... .......... 17% 55.8M 11s\n", - "105500K .......... .......... .......... .......... .......... 17% 72.8M 11s\n", - "105550K .......... .......... .......... .......... .......... 17% 64.0M 11s\n", - "105600K .......... .......... .......... .......... .......... 17% 48.1M 11s\n", - "105650K .......... .......... .......... .......... .......... 17% 43.4M 11s\n", - "105700K .......... .......... .......... .......... .......... 17% 54.7M 11s\n", - "105750K .......... .......... .......... .......... .......... 17% 67.5M 11s\n", - "105800K .......... .......... .......... .......... .......... 17% 54.8M 11s\n", - "105850K .......... .......... .......... .......... .......... 17% 65.6M 11s\n", - "105900K .......... .......... .......... .......... .......... 17% 47.7M 11s\n", - "105950K .......... .......... .......... .......... .......... 17% 59.0M 11s\n", - "106000K .......... .......... .......... .......... .......... 17% 59.1M 11s\n", - "106050K .......... .......... .......... .......... .......... 17% 73.5M 11s\n", - "106100K .......... .......... .......... .......... .......... 17% 4.15M 11s\n", - "106150K .......... .......... .......... .......... .......... 17% 66.3M 11s\n", - "106200K .......... .......... .......... .......... .......... 17% 52.9M 11s\n", - "106250K .......... .......... .......... .......... .......... 17% 64.6M 11s\n", - "106300K .......... .......... .......... .......... .......... 17% 68.4M 11s\n", - "106350K .......... .......... .......... .......... .......... 17% 60.3M 11s\n", - "106400K .......... .......... .......... .......... .......... 17% 41.5M 11s\n", - "106450K .......... .......... .......... .......... .......... 17% 57.9M 11s\n", - "106500K .......... .......... .......... .......... .......... 17% 69.8M 11s\n", - "106550K .......... .......... .......... .......... .......... 17% 59.4M 11s\n", - "106600K .......... .......... .......... .......... .......... 17% 54.9M 11s\n", - "106650K .......... .......... .......... .......... .......... 17% 57.1M 11s\n", - "106700K .......... .......... .......... .......... .......... 17% 47.1M 11s\n", - "106750K .......... .......... .......... .......... .......... 17% 60.9M 11s\n", - "106800K .......... .......... .......... .......... .......... 17% 61.6M 11s\n", - "106850K .......... .......... .......... .......... .......... 17% 65.8M 11s\n", - "106900K .......... .......... .......... .......... .......... 17% 49.9M 11s\n", - "106950K .......... .......... .......... .......... .......... 17% 48.3M 11s\n", - "107000K .......... .......... .......... .......... .......... 17% 46.6M 11s\n", - "107050K .......... .......... .......... .......... .......... 18% 72.3M 11s\n", - "107100K .......... .......... .......... .......... .......... 18% 72.1M 11s\n", - "107150K .......... .......... .......... .......... .......... 18% 60.3M 11s\n", - "107200K .......... .......... .......... .......... .......... 18% 47.6M 11s\n", - "107250K .......... .......... .......... .......... .......... 18% 57.4M 11s\n", - "107300K .......... .......... .......... .......... .......... 18% 69.7M 11s\n", - "107350K .......... .......... .......... .......... .......... 18% 71.7M 11s\n", - "107400K .......... .......... .......... .......... .......... 18% 44.7M 11s\n", - "107450K .......... .......... .......... .......... .......... 18% 52.4M 11s\n", - "107500K .......... .......... .......... .......... .......... 18% 50.8M 11s\n", - "107550K .......... .......... .......... .......... .......... 18% 67.7M 11s\n", - "107600K .......... .......... .......... .......... .......... 18% 57.7M 11s\n", - "107650K .......... .......... .......... .......... .......... 18% 72.3M 11s\n", - "107700K .......... .......... .......... .......... .......... 18% 53.3M 11s\n", - "107750K .......... .......... .......... .......... .......... 18% 47.3M 11s\n", - "107800K .......... .......... .......... .......... .......... 18% 55.9M 11s\n", - "107850K .......... .......... .......... .......... .......... 18% 67.5M 11s\n", - "107900K .......... .......... .......... .......... .......... 18% 63.1M 11s\n", - "107950K .......... .......... .......... .......... .......... 18% 50.6M 11s\n", - "108000K .......... .......... .......... .......... .......... 18% 46.7M 11s\n", - "108050K .......... .......... .......... .......... .......... 18% 57.6M 11s\n", - "108100K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", - "108150K .......... .......... .......... .......... .......... 18% 64.6M 11s\n", - "108200K .......... .......... .......... .......... .......... 18% 45.8M 11s\n", - "108250K .......... .......... .......... .......... .......... 18% 60.9M 11s\n", - "108300K .......... .......... .......... .......... .......... 18% 62.1M 11s\n", - "108350K .......... .......... .......... .......... .......... 18% 71.0M 11s\n", - "108400K .......... .......... .......... .......... .......... 18% 64.4M 11s\n", - "108450K .......... .......... .......... .......... .......... 18% 58.3M 11s\n", - "108500K .......... .......... .......... .......... .......... 18% 53.3M 11s\n", - "108550K .......... .......... .......... .......... .......... 18% 54.7M 11s\n", - "108600K .......... .......... .......... .......... .......... 18% 48.5M 11s\n", - "108650K .......... .......... .......... .......... .......... 18% 64.3M 11s\n", - "108700K .......... .......... .......... .......... .......... 18% 64.2M 11s\n", - "108750K .......... .......... .......... .......... .......... 18% 47.7M 11s\n", - "108800K .......... .......... .......... .......... .......... 18% 49.9M 11s\n", - "108850K .......... .......... .......... .......... .......... 18% 56.1M 11s\n", - "108900K .......... .......... .......... .......... .......... 18% 69.4M 11s\n", - "108950K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", - "109000K .......... .......... .......... .......... .......... 18% 40.4M 11s\n", - "109050K .......... .......... .......... .......... .......... 18% 62.7M 11s\n", - "109100K .......... .......... .......... .......... .......... 18% 57.4M 11s\n", - "109150K .......... .......... .......... .......... .......... 18% 74.0M 11s\n", - "109200K .......... .......... .......... .......... .......... 18% 63.3M 11s\n", - "109250K .......... .......... .......... .......... .......... 18% 57.8M 11s\n", - "109300K .......... .......... .......... .......... .......... 18% 49.2M 11s\n", - "109350K .......... .......... .......... .......... .......... 18% 54.1M 11s\n", - "109400K .......... .......... .......... .......... .......... 18% 51.1M 11s\n", - "109450K .......... .......... .......... .......... .......... 18% 70.6M 11s\n", - "109500K .......... .......... .......... .......... .......... 18% 57.3M 11s\n", - "109550K .......... .......... .......... .......... .......... 18% 49.4M 11s\n", - "109600K .......... .......... .......... .......... .......... 18% 47.6M 11s\n", - "109650K .......... .......... .......... .......... .......... 18% 68.5M 11s\n", - "109700K .......... .......... .......... .......... .......... 18% 64.6M 11s\n", - "109750K .......... .......... .......... .......... .......... 18% 68.8M 11s\n", - "109800K .......... .......... .......... .......... .......... 18% 46.1M 11s\n", - "109850K .......... .......... .......... .......... .......... 18% 57.2M 11s\n", - "109900K .......... .......... .......... .......... .......... 18% 56.9M 11s\n", - "109950K .......... .......... .......... .......... .......... 18% 70.8M 11s\n", - "110000K .......... .......... .......... .......... .......... 18% 60.9M 11s\n", - "110050K .......... .......... .......... .......... .......... 18% 52.9M 11s\n", - "110100K .......... .......... .......... .......... .......... 18% 57.3M 11s\n", - "110150K .......... .......... .......... .......... .......... 18% 49.0M 11s\n", - "110200K .......... .......... .......... .......... .......... 18% 58.0M 11s\n", - "110250K .......... .......... .......... .......... .......... 18% 69.2M 11s\n", - "110300K .......... .......... .......... .......... .......... 18% 54.4M 11s\n", - "110350K .......... .......... .......... .......... .......... 18% 51.5M 11s\n", - "110400K .......... .......... .......... .......... .......... 18% 49.0M 11s\n", - "110450K .......... .......... .......... .......... .......... 18% 64.5M 11s\n", - "110500K .......... .......... .......... .......... .......... 18% 68.3M 11s\n", - "110550K .......... .......... .......... .......... .......... 18% 69.9M 11s\n", - "110600K .......... .......... .......... .......... .......... 18% 38.0M 11s\n", - "110650K .......... .......... .......... .......... .......... 18% 49.8M 11s\n", - "110700K .......... .......... .......... .......... .......... 18% 70.1M 11s\n", - "110750K .......... .......... .......... .......... .......... 18% 68.3M 11s\n", - "110800K .......... .......... .......... .......... .......... 18% 50.8M 11s\n", - "110850K .......... .......... .......... .......... .......... 18% 45.1M 11s\n", - "110900K .......... .......... .......... .......... .......... 18% 49.2M 11s\n", - "110950K .......... .......... .......... .......... .......... 18% 64.8M 11s\n", - "111000K .......... .......... .......... .......... .......... 18% 59.5M 11s\n", - "111050K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", - "111100K .......... .......... .......... .......... .......... 18% 51.2M 11s\n", - "111150K .......... .......... .......... .......... .......... 18% 54.3M 11s\n", - "111200K .......... .......... .......... .......... .......... 18% 51.6M 11s\n", - "111250K .......... .......... .......... .......... .......... 18% 65.7M 11s\n", - "111300K .......... .......... .......... .......... .......... 18% 72.4M 11s\n", - "111350K .......... .......... .......... .......... .......... 18% 56.8M 11s\n", - "111400K .......... .......... .......... .......... .......... 18% 39.3M 11s\n", - "111450K .......... .......... .......... .......... .......... 18% 59.5M 11s\n", - "111500K .......... .......... .......... .......... .......... 18% 68.9M 11s\n", - "111550K .......... .......... .......... .......... .......... 18% 64.9M 11s\n", - "111600K .......... .......... .......... .......... .......... 18% 45.6M 11s\n", - "111650K .......... .......... .......... .......... .......... 18% 55.9M 11s\n", - "111700K .......... .......... .......... .......... .......... 18% 56.8M 11s\n", - "111750K .......... .......... .......... .......... .......... 18% 65.6M 11s\n", - "111800K .......... .......... .......... .......... .......... 18% 59.7M 11s\n", - "111850K .......... .......... .......... .......... .......... 18% 50.3M 11s\n", - "111900K .......... .......... .......... .......... .......... 18% 48.5M 11s\n", - "111950K .......... .......... .......... .......... .......... 18% 70.7M 11s\n", - "112000K .......... .......... .......... .......... .......... 18% 63.1M 11s\n", - "112050K .......... .......... .......... .......... .......... 18% 67.6M 11s\n", - "112100K .......... .......... .......... .......... .......... 18% 3.89M 11s\n", - "112150K .......... .......... .......... .......... .......... 18% 65.7M 11s\n", - "112200K .......... .......... .......... .......... .......... 18% 53.6M 11s\n", - "112250K .......... .......... .......... .......... .......... 18% 67.8M 11s\n", - "112300K .......... .......... .......... .......... .......... 18% 67.6M 11s\n", - "112350K .......... .......... .......... .......... .......... 18% 71.6M 11s\n", - "112400K .......... .......... .......... .......... .......... 18% 58.5M 11s\n", - "112450K .......... .......... .......... .......... .......... 18% 53.6M 11s\n", - "112500K .......... .......... .......... .......... .......... 18% 48.9M 11s\n", - "112550K .......... .......... .......... .......... .......... 18% 64.8M 11s\n", - "112600K .......... .......... .......... .......... .......... 18% 55.2M 11s\n", - "112650K .......... .......... .......... .......... .......... 18% 66.3M 11s\n", - "112700K .......... .......... .......... .......... .......... 18% 49.2M 11s\n", - "112750K .......... .......... .......... .......... .......... 18% 50.2M 11s\n", - "112800K .......... .......... .......... .......... .......... 18% 56.2M 11s\n", - "112850K .......... .......... .......... .......... .......... 18% 68.1M 11s\n", - "112900K .......... .......... .......... .......... .......... 18% 67.2M 11s\n", - "112950K .......... .......... .......... .......... .......... 19% 67.2M 11s\n", - "113000K .......... .......... .......... .......... .......... 19% 39.2M 11s\n", - "113050K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", - "113100K .......... .......... .......... .......... .......... 19% 69.5M 11s\n", - "113150K .......... .......... .......... .......... .......... 19% 63.1M 11s\n", - "113200K .......... .......... .......... .......... .......... 19% 51.8M 11s\n", - "113250K .......... .......... .......... .......... .......... 19% 53.0M 11s\n", - "113300K .......... .......... .......... .......... .......... 19% 45.8M 11s\n", - "113350K .......... .......... .......... .......... .......... 19% 66.8M 11s\n", - "113400K .......... .......... .......... .......... .......... 19% 53.4M 11s\n", - "113450K .......... .......... .......... .......... .......... 19% 60.1M 11s\n", - "113500K .......... .......... .......... .......... .......... 19% 51.7M 11s\n", - "113550K .......... .......... .......... .......... .......... 19% 49.0M 11s\n", - "113600K .......... .......... .......... .......... .......... 19% 57.8M 11s\n", - "113650K .......... .......... .......... .......... .......... 19% 69.4M 11s\n", - "113700K .......... .......... .......... .......... .......... 19% 67.4M 11s\n", - "113750K .......... .......... .......... .......... .......... 19% 71.3M 11s\n", - "113800K .......... .......... .......... .......... .......... 19% 53.3M 11s\n", - "113850K .......... .......... .......... .......... .......... 19% 52.8M 11s\n", - "113900K .......... .......... .......... .......... .......... 19% 71.3M 11s\n", - "113950K .......... .......... .......... .......... .......... 19% 72.4M 11s\n", - "114000K .......... .......... .......... .......... .......... 19% 56.5M 11s\n", - "114050K .......... .......... .......... .......... .......... 19% 65.0M 11s\n", - "114100K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", - "114150K .......... .......... .......... .......... .......... 19% 55.4M 11s\n", - "114200K .......... .......... .......... .......... .......... 19% 53.1M 11s\n", - "114250K .......... .......... .......... .......... .......... 19% 63.4M 11s\n", - "114300K .......... .......... .......... .......... .......... 19% 60.7M 11s\n", - "114350K .......... .......... .......... .......... .......... 19% 49.2M 11s\n", - "114400K .......... .......... .......... .......... .......... 19% 47.1M 11s\n", - "114450K .......... .......... .......... .......... .......... 19% 67.2M 11s\n", - "114500K .......... .......... .......... .......... .......... 19% 66.1M 11s\n", - "114550K .......... .......... .......... .......... .......... 19% 59.3M 11s\n", - "114600K .......... .......... .......... .......... .......... 19% 53.0M 11s\n", - "114650K .......... .......... .......... .......... .......... 19% 49.8M 11s\n", - "114700K .......... .......... .......... .......... .......... 19% 60.2M 11s\n", - "114750K .......... .......... .......... .......... .......... 19% 68.5M 11s\n", - "114800K .......... .......... .......... .......... .......... 19% 62.5M 11s\n", - "114850K .......... .......... .......... .......... .......... 19% 63.4M 11s\n", - "114900K .......... .......... .......... .......... .......... 19% 55.6M 11s\n", - "114950K .......... .......... .......... .......... .......... 19% 59.3M 11s\n", - "115000K .......... .......... .......... .......... .......... 19% 52.8M 11s\n", - "115050K .......... .......... .......... .......... .......... 19% 68.9M 11s\n", - "115100K .......... .......... .......... .......... .......... 19% 72.8M 11s\n", - "115150K .......... .......... .......... .......... .......... 19% 63.7M 11s\n", - "115200K .......... .......... .......... .......... .......... 19% 59.1M 11s\n", - "115250K .......... .......... .......... .......... .......... 19% 51.7M 11s\n", - "115300K .......... .......... .......... .......... .......... 19% 66.4M 11s\n", - "115350K .......... .......... .......... .......... .......... 19% 66.9M 11s\n", - "115400K .......... .......... .......... .......... .......... 19% 50.0M 11s\n", - "115450K .......... .......... .......... .......... .......... 19% 62.6M 11s\n", - "115500K .......... .......... .......... .......... .......... 19% 57.2M 11s\n", - "115550K .......... .......... .......... .......... .......... 19% 60.3M 11s\n", - "115600K .......... .......... .......... .......... .......... 19% 61.5M 11s\n", - "115650K .......... .......... .......... .......... .......... 19% 61.8M 11s\n", - "115700K .......... .......... .......... .......... .......... 19% 60.0M 11s\n", - "115750K .......... .......... .......... .......... .......... 19% 71.6M 11s\n", - "115800K .......... .......... .......... .......... .......... 19% 55.7M 11s\n", - "115850K .......... .......... .......... .......... .......... 19% 58.8M 11s\n", - "115900K .......... .......... .......... .......... .......... 19% 55.3M 11s\n", - "115950K .......... .......... .......... .......... .......... 19% 69.4M 11s\n", - "116000K .......... .......... .......... .......... .......... 19% 55.4M 11s\n", - "116050K .......... .......... .......... .......... .......... 19% 66.0M 11s\n", - "116100K .......... .......... .......... .......... .......... 19% 61.1M 11s\n", - "116150K .......... .......... .......... .......... .......... 19% 55.7M 11s\n", - "116200K .......... .......... .......... .......... .......... 19% 46.8M 11s\n", - "116250K .......... .......... .......... .......... .......... 19% 57.8M 11s\n", - "116300K .......... .......... .......... .......... .......... 19% 64.8M 11s\n", - "116350K .......... .......... .......... .......... .......... 19% 67.0M 11s\n", - "116400K .......... .......... .......... .......... .......... 19% 43.8M 11s\n", - "116450K .......... .......... .......... .......... .......... 19% 52.8M 11s\n", - "116500K .......... .......... .......... .......... .......... 19% 62.8M 11s\n", - "116550K .......... .......... .......... .......... .......... 19% 58.5M 11s\n", - "116600K .......... .......... .......... .......... .......... 19% 59.0M 11s\n", - "116650K .......... .......... .......... .......... .......... 19% 64.6M 11s\n", - "116700K .......... .......... .......... .......... .......... 19% 61.1M 11s\n", - "116750K .......... .......... .......... .......... .......... 19% 67.1M 11s\n", - "116800K .......... .......... .......... .......... .......... 19% 54.6M 11s\n", - "116850K .......... .......... .......... .......... .......... 19% 68.0M 11s\n", - "116900K .......... .......... .......... .......... .......... 19% 67.5M 11s\n", - "116950K .......... .......... .......... .......... .......... 19% 60.1M 11s\n", - "117000K .......... .......... .......... .......... .......... 19% 58.7M 11s\n", - "117050K .......... .......... .......... .......... .......... 19% 66.6M 11s\n", - "117100K .......... .......... .......... .......... .......... 19% 68.9M 11s\n", - "117150K .......... .......... .......... .......... .......... 19% 61.1M 11s\n", - "117200K .......... .......... .......... .......... .......... 19% 62.7M 11s\n", - "117250K .......... .......... .......... .......... .......... 19% 61.0M 11s\n", - "117300K .......... .......... .......... .......... .......... 19% 61.4M 11s\n", - "117350K .......... .......... .......... .......... .......... 19% 68.2M 11s\n", - "117400K .......... .......... .......... .......... .......... 19% 52.3M 11s\n", - "117450K .......... .......... .......... .......... .......... 19% 68.4M 11s\n", - "117500K .......... .......... .......... .......... .......... 19% 66.2M 11s\n", - "117550K .......... .......... .......... .......... .......... 19% 58.3M 11s\n", - "117600K .......... .......... .......... .......... .......... 19% 43.9M 11s\n", - "117650K .......... .......... .......... .......... .......... 19% 65.9M 11s\n", - "117700K .......... .......... .......... .......... .......... 19% 61.9M 11s\n", - "117750K .......... .......... .......... .......... .......... 19% 67.9M 11s\n", - "117800K .......... .......... .......... .......... .......... 19% 51.6M 11s\n", - "117850K .......... .......... .......... .......... .......... 19% 47.6M 11s\n", - "117900K .......... .......... .......... .......... .......... 19% 64.9M 11s\n", - "117950K .......... .......... .......... .......... .......... 19% 62.9M 11s\n", - "118000K .......... .......... .......... .......... .......... 19% 63.1M 11s\n", - "118050K .......... .......... .......... .......... .......... 19% 65.0M 11s\n", - "118100K .......... .......... .......... .......... .......... 19% 3.81M 11s\n", - "118150K .......... .......... .......... .......... .......... 19% 74.6M 11s\n", - "118200K .......... .......... .......... .......... .......... 19% 54.3M 11s\n", - "118250K .......... .......... .......... .......... .......... 19% 67.2M 11s\n", - "118300K .......... .......... .......... .......... .......... 19% 69.1M 11s\n", - "118350K .......... .......... .......... .......... .......... 19% 70.2M 11s\n", - "118400K .......... .......... .......... .......... .......... 19% 64.6M 11s\n", - "118450K .......... .......... .......... .......... .......... 19% 42.0M 11s\n", - "118500K .......... .......... .......... .......... .......... 19% 46.6M 11s\n", - "118550K .......... .......... .......... .......... .......... 19% 65.5M 11s\n", - "118600K .......... .......... .......... .......... .......... 19% 57.0M 11s\n", - "118650K .......... .......... .......... .......... .......... 19% 55.5M 11s\n", - "118700K .......... .......... .......... .......... .......... 19% 43.8M 11s\n", - "118750K .......... .......... .......... .......... .......... 19% 43.2M 11s\n", - "118800K .......... .......... .......... .......... .......... 19% 60.0M 11s\n", - "118850K .......... .......... .......... .......... .......... 19% 60.6M 11s\n", - "118900K .......... .......... .......... .......... .......... 20% 48.3M 11s\n", - "118950K .......... .......... .......... .......... .......... 20% 41.5M 11s\n", - "119000K .......... .......... .......... .......... .......... 20% 41.8M 11s\n", - "119050K .......... .......... .......... .......... .......... 20% 72.0M 11s\n", - "119100K .......... .......... .......... .......... .......... 20% 55.4M 11s\n", - "119150K .......... .......... .......... .......... .......... 20% 43.3M 11s\n", - "119200K .......... .......... .......... .......... .......... 20% 40.0M 11s\n", - "119250K .......... .......... .......... .......... .......... 20% 47.2M 11s\n", - "119300K .......... .......... .......... .......... .......... 20% 66.4M 11s\n", - "119350K .......... .......... .......... .......... .......... 20% 49.3M 11s\n", - "119400K .......... .......... .......... .......... .......... 20% 39.3M 11s\n", - "119450K .......... .......... .......... .......... .......... 20% 43.4M 11s\n", - "119500K .......... .......... .......... .......... .......... 20% 10.9M 11s\n", - "119550K .......... .......... .......... .......... .......... 20% 71.5M 11s\n", - "119600K .......... .......... .......... .......... .......... 20% 61.9M 11s\n", - "119650K .......... .......... .......... .......... .......... 20% 67.6M 11s\n", - "119700K .......... .......... .......... .......... .......... 20% 66.1M 11s\n", - "119750K .......... .......... .......... .......... .......... 20% 17.6M 11s\n", - "119800K .......... .......... .......... .......... .......... 20% 51.6M 11s\n", - "119850K .......... .......... .......... .......... .......... 20% 64.0M 11s\n", - "119900K .......... .......... .......... .......... .......... 20% 67.2M 11s\n", - "119950K .......... .......... .......... .......... .......... 20% 57.5M 11s\n", - "120000K .......... .......... .......... .......... .......... 20% 47.1M 11s\n", - "120050K .......... .......... .......... .......... .......... 20% 41.7M 11s\n", - "120100K .......... .......... .......... .......... .......... 20% 54.8M 11s\n", - "120150K .......... .......... .......... .......... .......... 20% 76.1M 11s\n", - "120200K .......... .......... .......... .......... .......... 20% 50.5M 11s\n", - "120250K .......... .......... .......... .......... .......... 20% 47.7M 11s\n", - "120300K .......... .......... .......... .......... .......... 20% 37.4M 11s\n", - "120350K .......... .......... .......... .......... .......... 20% 65.7M 11s\n", - "120400K .......... .......... .......... .......... .......... 20% 3.87M 11s\n", - "120450K .......... .......... .......... .......... .......... 20% 61.8M 11s\n", - "120500K .......... .......... .......... .......... .......... 20% 61.7M 11s\n", - "120550K .......... .......... .......... .......... .......... 20% 67.5M 11s\n", - "120600K .......... .......... .......... .......... .......... 20% 56.6M 11s\n", - "120650K .......... .......... .......... .......... .......... 20% 62.5M 11s\n", - "120700K .......... .......... .......... .......... .......... 20% 38.2M 11s\n", - "120750K .......... .......... .......... .......... .......... 20% 50.0M 11s\n", - "120800K .......... .......... .......... .......... .......... 20% 7.12M 11s\n", - "120850K .......... .......... .......... .......... .......... 20% 36.8M 11s\n", - "120900K .......... .......... .......... .......... .......... 20% 50.3M 11s\n", - "120950K .......... .......... .......... .......... .......... 20% 50.8M 11s\n", - "121000K .......... .......... .......... .......... .......... 20% 67.0M 11s\n", - "121050K .......... .......... .......... .......... .......... 20% 56.8M 11s\n", - "121100K .......... .......... .......... .......... .......... 20% 67.0M 11s\n", - "121150K .......... .......... .......... .......... .......... 20% 74.3M 11s\n", - "121200K .......... .......... .......... .......... .......... 20% 63.9M 11s\n", - "121250K .......... .......... .......... .......... .......... 20% 57.0M 11s\n", - "121300K .......... .......... .......... .......... .......... 20% 67.5M 11s\n", - "121350K .......... .......... .......... .......... .......... 20% 16.0M 11s\n", - "121400K .......... .......... .......... .......... .......... 20% 51.8M 11s\n", - "121450K .......... .......... .......... .......... .......... 20% 21.5M 11s\n", - "121500K .......... .......... .......... .......... .......... 20% 6.83M 11s\n", - "121550K .......... .......... .......... .......... .......... 20% 64.1M 11s\n", - "121600K .......... .......... .......... .......... .......... 20% 48.0M 11s\n", - "121650K .......... .......... .......... .......... .......... 20% 52.5M 11s\n", - "121700K .......... .......... .......... .......... .......... 20% 41.5M 11s\n", - "121750K .......... .......... .......... .......... .......... 20% 41.6M 11s\n", - "121800K .......... .......... .......... .......... .......... 20% 27.9M 11s\n", - "121850K .......... .......... .......... .......... .......... 20% 43.0M 11s\n", - "121900K .......... .......... .......... .......... .......... 20% 43.6M 11s\n", - "121950K .......... .......... .......... .......... .......... 20% 48.1M 11s\n", - "122000K .......... .......... .......... .......... .......... 20% 46.1M 11s\n", - "122050K .......... .......... .......... .......... .......... 20% 62.7M 11s\n", - "122100K .......... .......... .......... .......... .......... 20% 64.6M 11s\n", - "122150K .......... .......... .......... .......... .......... 20% 69.3M 11s\n", - "122200K .......... .......... .......... .......... .......... 20% 44.7M 11s\n", - "122250K .......... .......... .......... .......... .......... 20% 57.5M 11s\n", - "122300K .......... .......... .......... .......... .......... 20% 58.7M 11s\n", - "122350K .......... .......... .......... .......... .......... 20% 63.5M 11s\n", - "122400K .......... .......... .......... .......... .......... 20% 67.9M 11s\n", - "122450K .......... .......... .......... .......... .......... 20% 69.8M 11s\n", - "122500K .......... .......... .......... .......... .......... 20% 56.9M 11s\n", - "122550K .......... .......... .......... .......... .......... 20% 67.4M 11s\n", - "122600K .......... .......... .......... .......... .......... 20% 49.8M 11s\n", - "122650K .......... .......... .......... .......... .......... 20% 60.7M 11s\n", - "122700K .......... .......... .......... .......... .......... 20% 66.3M 11s\n", - "122750K .......... .......... .......... .......... .......... 20% 67.1M 11s\n", - "122800K .......... .......... .......... .......... .......... 20% 43.8M 11s\n", - "122850K .......... .......... .......... .......... .......... 20% 56.9M 11s\n", - "122900K .......... .......... .......... .......... .......... 20% 63.8M 11s\n", - "122950K .......... .......... .......... .......... .......... 20% 67.7M 11s\n", - "123000K .......... .......... .......... .......... .......... 20% 52.0M 11s\n", - "123050K .......... .......... .......... .......... .......... 20% 64.2M 11s\n", - "123100K .......... .......... .......... .......... .......... 20% 57.2M 11s\n", - "123150K .......... .......... .......... .......... .......... 20% 51.3M 11s\n", - "123200K .......... .......... .......... .......... .......... 20% 61.1M 11s\n", - "123250K .......... .......... .......... .......... .......... 20% 67.7M 11s\n", - "123300K .......... .......... .......... .......... .......... 20% 52.1M 11s\n", - "123350K .......... .......... .......... .......... .......... 20% 49.0M 11s\n", - "123400K .......... .......... .......... .......... .......... 20% 45.2M 11s\n", - "123450K .......... .......... .......... .......... .......... 20% 69.6M 11s\n", - "123500K .......... .......... .......... .......... .......... 20% 64.7M 11s\n", - "123550K .......... .......... .......... .......... .......... 20% 60.8M 11s\n", - "123600K .......... .......... .......... .......... .......... 20% 49.5M 11s\n", - "123650K .......... .......... .......... .......... .......... 20% 62.6M 11s\n", - "123700K .......... .......... .......... .......... .......... 20% 55.7M 11s\n", - "123750K .......... .......... .......... .......... .......... 20% 66.7M 11s\n", - "123800K .......... .......... .......... .......... .......... 20% 54.8M 11s\n", - "123850K .......... .......... .......... .......... .......... 20% 57.2M 11s\n", - "123900K .......... .......... .......... .......... .......... 20% 60.9M 11s\n", - "123950K .......... .......... .......... .......... .......... 20% 52.9M 11s\n", - "124000K .......... .......... .......... .......... .......... 20% 56.9M 11s\n", - "124050K .......... .......... .......... .......... .......... 20% 60.2M 11s\n", - "124100K .......... .......... .......... .......... .......... 20% 61.5M 11s\n", - "124150K .......... .......... .......... .......... .......... 20% 51.4M 11s\n", - "124200K .......... .......... .......... .......... .......... 20% 46.1M 11s\n", - "124250K .......... .......... .......... .......... .......... 20% 60.9M 11s\n", - "124300K .......... .......... .......... .......... .......... 20% 69.2M 11s\n", - "124350K .......... .......... .......... .......... .......... 20% 58.3M 11s\n", - "124400K .......... .......... .......... .......... .......... 20% 5.24M 11s\n", - "124450K .......... .......... .......... .......... .......... 20% 65.8M 11s\n", - "124500K .......... .......... .......... .......... .......... 20% 70.6M 11s\n", - "124550K .......... .......... .......... .......... .......... 20% 57.8M 11s\n", - "124600K .......... .......... .......... .......... .......... 20% 60.8M 11s\n", - "124650K .......... .......... .......... .......... .......... 20% 67.3M 11s\n", - "124700K .......... .......... .......... .......... .......... 20% 54.3M 11s\n", - "124750K .......... .......... .......... .......... .......... 20% 42.5M 11s\n", - "124800K .......... .......... .......... .......... .......... 20% 48.2M 11s\n", - "124850K .......... .......... .......... .......... .......... 21% 81.0M 11s\n", - "124900K .......... .......... .......... .......... .......... 21% 68.6M 11s\n", - "124950K .......... .......... .......... .......... .......... 21% 48.4M 11s\n", - "125000K .......... .......... .......... .......... .......... 21% 29.8M 11s\n", - "125050K .......... .......... .......... .......... .......... 21% 45.2M 11s\n", - "125100K .......... .......... .......... .......... .......... 21% 44.5M 11s\n", - "125150K .......... .......... .......... .......... .......... 21% 41.8M 11s\n", - "125200K .......... .......... .......... .......... .......... 21% 39.8M 11s\n", - "125250K .......... .......... .......... .......... .......... 21% 56.4M 11s\n", - "125300K .......... .......... .......... .......... .......... 21% 61.8M 11s\n", - "125350K .......... .......... .......... .......... .......... 21% 62.4M 11s\n", - "125400K .......... .......... .......... .......... .......... 21% 49.7M 11s\n", - "125450K .......... .......... .......... .......... .......... 21% 39.1M 11s\n", - "125500K .......... .......... .......... .......... .......... 21% 51.5M 11s\n", - "125550K .......... .......... .......... .......... .......... 21% 66.6M 11s\n", - "125600K .......... .......... .......... .......... .......... 21% 49.8M 11s\n", - "125650K .......... .......... .......... .......... .......... 21% 70.7M 11s\n", - "125700K .......... .......... .......... .......... .......... 21% 55.6M 11s\n", - "125750K .......... .......... .......... .......... .......... 21% 52.9M 11s\n", - "125800K .......... .......... .......... .......... .......... 21% 53.2M 11s\n", - "125850K .......... .......... .......... .......... .......... 21% 62.1M 11s\n", - "125900K .......... .......... .......... .......... .......... 21% 69.8M 11s\n", - "125950K .......... .......... .......... .......... .......... 21% 4.10M 11s\n", - "126000K .......... .......... .......... .......... .......... 21% 59.0M 11s\n", - "126050K .......... .......... .......... .......... .......... 21% 44.8M 11s\n", - "126100K .......... .......... .......... .......... .......... 21% 60.5M 11s\n", - "126150K .......... .......... .......... .......... .......... 21% 65.9M 11s\n", - "126200K .......... .......... .......... .......... .......... 21% 49.2M 11s\n", - "126250K .......... .......... .......... .......... .......... 21% 61.9M 11s\n", - "126300K .......... .......... .......... .......... .......... 21% 54.8M 11s\n", - "126350K .......... .......... .......... .......... .......... 21% 71.9M 11s\n", - "126400K .......... .......... .......... .......... .......... 21% 63.3M 11s\n", - "126450K .......... .......... .......... .......... .......... 21% 72.9M 11s\n", - "126500K .......... .......... .......... .......... .......... 21% 72.6M 11s\n", - "126550K .......... .......... .......... .......... .......... 21% 64.5M 11s\n", - "126600K .......... .......... .......... .......... .......... 21% 34.6M 11s\n", - "126650K .......... .......... .......... .......... .......... 21% 64.8M 11s\n", - "126700K .......... .......... .......... .......... .......... 21% 65.8M 11s\n", - "126750K .......... .......... .......... .......... .......... 21% 50.7M 11s\n", - "126800K .......... .......... .......... .......... .......... 21% 40.6M 11s\n", - "126850K .......... .......... .......... .......... .......... 21% 50.5M 11s\n", - "126900K .......... .......... .......... .......... .......... 21% 60.3M 11s\n", - "126950K .......... .......... .......... .......... .......... 21% 70.7M 11s\n", - "127000K .......... .......... .......... .......... .......... 21% 44.1M 11s\n", - "127050K .......... .......... .......... .......... .......... 21% 46.5M 11s\n", - "127100K .......... .......... .......... .......... .......... 21% 63.2M 11s\n", - "127150K .......... .......... .......... .......... .......... 21% 69.7M 11s\n", - "127200K .......... .......... .......... .......... .......... 21% 43.5M 11s\n", - "127250K .......... .......... .......... .......... .......... 21% 59.1M 11s\n", - "127300K .......... .......... .......... .......... .......... 21% 45.5M 11s\n", - "127350K .......... .......... .......... .......... .......... 21% 52.5M 11s\n", - "127400K .......... .......... .......... .......... .......... 21% 52.2M 11s\n", - "127450K .......... .......... .......... .......... .......... 21% 64.4M 11s\n", - "127500K .......... .......... .......... .......... .......... 21% 5.63M 11s\n", - "127550K .......... .......... .......... .......... .......... 21% 66.2M 11s\n", - "127600K .......... .......... .......... .......... .......... 21% 60.2M 11s\n", - "127650K .......... .......... .......... .......... .......... 21% 65.2M 11s\n", - "127700K .......... .......... .......... .......... .......... 21% 61.6M 11s\n", - "127750K .......... .......... .......... .......... .......... 21% 60.4M 11s\n", - "127800K .......... .......... .......... .......... .......... 21% 36.4M 11s\n", - "127850K .......... .......... .......... .......... .......... 21% 55.4M 11s\n", - "127900K .......... .......... .......... .......... .......... 21% 65.0M 11s\n", - "127950K .......... .......... .......... .......... .......... 21% 66.2M 11s\n", - "128000K .......... .......... .......... .......... .......... 21% 54.8M 11s\n", - "128050K .......... .......... .......... .......... .......... 21% 61.9M 11s\n", - "128100K .......... .......... .......... .......... .......... 21% 50.5M 11s\n", - "128150K .......... .......... .......... .......... .......... 21% 63.6M 11s\n", - "128200K .......... .......... .......... .......... .......... 21% 57.8M 11s\n", - "128250K .......... .......... .......... .......... .......... 21% 14.4M 11s\n", - "128300K .......... .......... .......... .......... .......... 21% 48.3M 11s\n", - "128350K .......... .......... .......... .......... .......... 21% 47.9M 11s\n", - "128400K .......... .......... .......... .......... .......... 21% 27.4M 11s\n", - "128450K .......... .......... .......... .......... .......... 21% 42.3M 11s\n", - "128500K .......... .......... .......... .......... .......... 21% 46.2M 11s\n", - "128550K .......... .......... .......... .......... .......... 21% 61.8M 11s\n", - "128600K .......... .......... .......... .......... .......... 21% 27.2M 11s\n", - "128650K .......... .......... .......... .......... .......... 21% 40.3M 11s\n", - "128700K .......... .......... .......... .......... .......... 21% 47.4M 11s\n", - "128750K .......... .......... .......... .......... .......... 21% 53.8M 11s\n", - "128800K .......... .......... .......... .......... .......... 21% 24.1M 11s\n", - "128850K .......... .......... .......... .......... .......... 21% 54.0M 11s\n", - "128900K .......... .......... .......... .......... .......... 21% 75.2M 11s\n", - "128950K .......... .......... .......... .......... .......... 21% 23.3M 11s\n", - "129000K .......... .......... .......... .......... .......... 21% 27.8M 11s\n", - "129050K .......... .......... .......... .......... .......... 21% 65.7M 11s\n", - "129100K .......... .......... .......... .......... .......... 21% 55.8M 11s\n", - "129150K .......... .......... .......... .......... .......... 21% 22.9M 11s\n", - "129200K .......... .......... .......... .......... .......... 21% 4.02M 11s\n", - "129250K .......... .......... .......... .......... .......... 21% 60.9M 11s\n", - "129300K .......... .......... .......... .......... .......... 21% 59.3M 11s\n", - "129350K .......... .......... .......... .......... .......... 21% 54.7M 11s\n", - "129400K .......... .......... .......... .......... .......... 21% 16.3M 11s\n", - "129450K .......... .......... .......... .......... .......... 21% 3.93M 11s\n", - "129500K .......... .......... .......... .......... .......... 21% 53.3M 11s\n", - "129550K .......... .......... .......... .......... .......... 21% 54.5M 11s\n", - "129600K .......... .......... .......... .......... .......... 21% 59.4M 11s\n", - "129650K .......... .......... .......... .......... .......... 21% 28.7M 11s\n", - "129700K .......... .......... .......... .......... .......... 21% 30.4M 11s\n", - "129750K .......... .......... .......... .......... .......... 21% 48.2M 11s\n", - "129800K .......... .......... .......... .......... .......... 21% 38.5M 11s\n", - "129850K .......... .......... .......... .......... .......... 21% 51.6M 11s\n", - "129900K .......... .......... .......... .......... .......... 21% 37.8M 11s\n", - "129950K .......... .......... .......... .......... .......... 21% 64.0M 11s\n", - "130000K .......... .......... .......... .......... .......... 21% 51.7M 11s\n", - "130050K .......... .......... .......... .......... .......... 21% 46.0M 11s\n", - "130100K .......... .......... .......... .......... .......... 21% 42.3M 11s\n", - "130150K .......... .......... .......... .......... .......... 21% 45.0M 11s\n", - "130200K .......... .......... .......... .......... .......... 21% 50.5M 11s\n", - "130250K .......... .......... .......... .......... .......... 21% 56.7M 11s\n", - "130300K .......... .......... .......... .......... .......... 21% 39.8M 11s\n", - "130350K .......... .......... .......... .......... .......... 21% 26.1M 11s\n", - "130400K .......... .......... .......... .......... .......... 21% 37.6M 11s\n", - "130450K .......... .......... .......... .......... .......... 21% 30.1M 11s\n", - "130500K .......... .......... .......... .......... .......... 21% 25.4M 11s\n", - "130550K .......... .......... .......... .......... .......... 21% 43.0M 11s\n", - "130600K .......... .......... .......... .......... .......... 21% 38.8M 11s\n", - "130650K .......... .......... .......... .......... .......... 21% 48.0M 11s\n", - "130700K .......... .......... .......... .......... .......... 21% 36.9M 11s\n", - "130750K .......... .......... .......... .......... .......... 21% 45.7M 11s\n", - "130800K .......... .......... .......... .......... .......... 22% 60.7M 11s\n", - "130850K .......... .......... .......... .......... .......... 22% 45.8M 11s\n", - "130900K .......... .......... .......... .......... .......... 22% 42.9M 11s\n", - "130950K .......... .......... .......... .......... .......... 22% 51.3M 11s\n", - "131000K .......... .......... .......... .......... .......... 22% 27.0M 11s\n", - "131050K .......... .......... .......... .......... .......... 22% 42.0M 11s\n", - "131100K .......... .......... .......... .......... .......... 22% 47.5M 11s\n", - "131150K .......... .......... .......... .......... .......... 22% 65.0M 11s\n", - "131200K .......... .......... .......... .......... .......... 22% 23.4M 11s\n", - "131250K .......... .......... .......... .......... .......... 22% 42.1M 11s\n", - "131300K .......... .......... .......... .......... .......... 22% 59.7M 11s\n", - "131350K .......... .......... .......... .......... .......... 22% 52.6M 11s\n", - "131400K .......... .......... .......... .......... .......... 22% 24.8M 11s\n", - "131450K .......... .......... .......... .......... .......... 22% 40.9M 11s\n", - "131500K .......... .......... .......... .......... .......... 22% 72.0M 11s\n", - "131550K .......... .......... .......... .......... .......... 22% 22.8M 11s\n", - "131600K .......... .......... .......... .......... .......... 22% 33.6M 11s\n", - "131650K .......... .......... .......... .......... .......... 22% 73.6M 11s\n", - "131700K .......... .......... .......... .......... .......... 22% 60.6M 11s\n", - "131750K .......... .......... .......... .......... .......... 22% 22.3M 11s\n", - "131800K .......... .......... .......... .......... .......... 22% 34.6M 11s\n", - "131850K .......... .......... .......... .......... .......... 22% 57.4M 11s\n", - "131900K .......... .......... .......... .......... .......... 22% 36.8M 11s\n", - "131950K .......... .......... .......... .......... .......... 22% 52.4M 11s\n", - "132000K .......... .......... .......... .......... .......... 22% 31.8M 11s\n", - "132050K .......... .......... .......... .......... .......... 22% 70.4M 11s\n", - "132100K .......... .......... .......... .......... .......... 22% 23.6M 11s\n", - "132150K .......... .......... .......... .......... .......... 22% 42.2M 11s\n", - "132200K .......... .......... .......... .......... .......... 22% 44.8M 11s\n", - "132250K .......... .......... .......... .......... .......... 22% 38.3M 11s\n", - "132300K .......... .......... .......... .......... .......... 22% 26.9M 11s\n", - "132350K .......... .......... .......... .......... .......... 22% 41.9M 11s\n", - "132400K .......... .......... .......... .......... .......... 22% 62.6M 11s\n", - "132450K .......... .......... .......... .......... .......... 22% 22.6M 11s\n", - "132500K .......... .......... .......... .......... .......... 22% 40.5M 11s\n", - "132550K .......... .......... .......... .......... .......... 22% 66.3M 11s\n", - "132600K .......... .......... .......... .......... .......... 22% 40.9M 11s\n", - "132650K .......... .......... .......... .......... .......... 22% 26.3M 11s\n", - "132700K .......... .......... .......... .......... .......... 22% 43.8M 11s\n", - "132750K .......... .......... .......... .......... .......... 22% 53.8M 11s\n", - "132800K .......... .......... .......... .......... .......... 22% 39.7M 11s\n", - "132850K .......... .......... .......... .......... .......... 22% 33.0M 11s\n", - "132900K .......... .......... .......... .......... .......... 22% 43.6M 11s\n", - "132950K .......... .......... .......... .......... .......... 22% 51.8M 11s\n", - "133000K .......... .......... .......... .......... .......... 22% 22.2M 11s\n", - "133050K .......... .......... .......... .......... .......... 22% 46.2M 11s\n", - "133100K .......... .......... .......... .......... .......... 22% 56.9M 11s\n", - "133150K .......... .......... .......... .......... .......... 22% 63.3M 11s\n", - "133200K .......... .......... .......... .......... .......... 22% 3.73M 11s\n", - "133250K .......... .......... .......... .......... .......... 22% 60.8M 11s\n", - "133300K .......... .......... .......... .......... .......... 22% 69.6M 11s\n", - "133350K .......... .......... .......... .......... .......... 22% 66.3M 11s\n", - "133400K .......... .......... .......... .......... .......... 22% 15.7M 11s\n", - "133450K .......... .......... .......... .......... .......... 22% 51.8M 11s\n", - "133500K .......... .......... .......... .......... .......... 22% 68.6M 11s\n", - "133550K .......... .......... .......... .......... .......... 22% 69.7M 11s\n", - "133600K .......... .......... .......... .......... .......... 22% 21.6M 11s\n", - "133650K .......... .......... .......... .......... .......... 22% 55.9M 11s\n", - "133700K .......... .......... .......... .......... .......... 22% 70.5M 11s\n", - "133750K .......... .......... .......... .......... .......... 22% 22.6M 11s\n", - "133800K .......... .......... .......... .......... .......... 22% 43.9M 11s\n", - "133850K .......... .......... .......... .......... .......... 22% 62.2M 11s\n", - "133900K .......... .......... .......... .......... .......... 22% 66.6M 11s\n", - "133950K .......... .......... .......... .......... .......... 22% 21.7M 11s\n", - "134000K .......... .......... .......... .......... .......... 22% 31.9M 11s\n", - "134050K .......... .......... .......... .......... .......... 22% 69.2M 11s\n", - "134100K .......... .......... .......... .......... .......... 22% 71.4M 11s\n", - "134150K .......... .......... .......... .......... .......... 22% 29.1M 11s\n", - "134200K .......... .......... .......... .......... .......... 22% 29.4M 11s\n", - "134250K .......... .......... .......... .......... .......... 22% 73.3M 11s\n", - "134300K .......... .......... .......... .......... .......... 22% 35.3M 11s\n", - "134350K .......... .......... .......... .......... .......... 22% 34.0M 11s\n", - "134400K .......... .......... .......... .......... .......... 22% 39.3M 11s\n", - "134450K .......... .......... .......... .......... .......... 22% 57.1M 11s\n", - "134500K .......... .......... .......... .......... .......... 22% 44.8M 11s\n", - "134550K .......... .......... .......... .......... .......... 22% 25.8M 11s\n", - "134600K .......... .......... .......... .......... .......... 22% 50.5M 11s\n", - "134650K .......... .......... .......... .......... .......... 22% 67.9M 11s\n", - "134700K .......... .......... .......... .......... .......... 22% 25.6M 11s\n", - "134750K .......... .......... .......... .......... .......... 22% 34.9M 11s\n", - "134800K .......... .......... .......... .......... .......... 22% 62.1M 11s\n", - "134850K .......... .......... .......... .......... .......... 22% 64.5M 11s\n", - "134900K .......... .......... .......... .......... .......... 22% 30.3M 11s\n", - "134950K .......... .......... .......... .......... .......... 22% 36.0M 11s\n", - "135000K .......... .......... .......... .......... .......... 22% 52.5M 11s\n", - "135050K .......... .......... .......... .......... .......... 22% 74.0M 11s\n", - "135100K .......... .......... .......... .......... .......... 22% 28.9M 11s\n", - "135150K .......... .......... .......... .......... .......... 22% 29.9M 11s\n", - "135200K .......... .......... .......... .......... .......... 22% 66.1M 11s\n", - "135250K .......... .......... .......... .......... .......... 22% 52.3M 11s\n", - "135300K .......... .......... .......... .......... .......... 22% 32.5M 11s\n", - "135350K .......... .......... .......... .......... .......... 22% 43.9M 11s\n", - "135400K .......... .......... .......... .......... .......... 22% 46.2M 11s\n", - "135450K .......... .......... .......... .......... .......... 22% 59.2M 11s\n", - "135500K .......... .......... .......... .......... .......... 22% 24.6M 11s\n", - "135550K .......... .......... .......... .......... .......... 22% 5.52M 11s\n", - "135600K .......... .......... .......... .......... .......... 22% 61.3M 11s\n", - "135650K .......... .......... .......... .......... .......... 22% 63.9M 11s\n", - "135700K .......... .......... .......... .......... .......... 22% 67.5M 11s\n", - "135750K .......... .......... .......... .......... .......... 22% 68.9M 11s\n", - "135800K .......... .......... .......... .......... .......... 22% 17.0M 11s\n", - "135850K .......... .......... .......... .......... .......... 22% 61.4M 11s\n", - "135900K .......... .......... .......... .......... .......... 22% 65.7M 11s\n", - "135950K .......... .......... .......... .......... .......... 22% 21.2M 11s\n", - "136000K .......... .......... .......... .......... .......... 22% 47.9M 11s\n", - "136050K .......... .......... .......... .......... .......... 22% 58.4M 11s\n", - "136100K .......... .......... .......... .......... .......... 22% 69.7M 11s\n", - "136150K .......... .......... .......... .......... .......... 22% 73.4M 11s\n", - "136200K .......... .......... .......... .......... .......... 22% 21.4M 11s\n", - "136250K .......... .......... .......... .......... .......... 22% 65.8M 11s\n", - "136300K .......... .......... .......... .......... .......... 22% 68.6M 11s\n", - "136350K .......... .......... .......... .......... .......... 22% 23.2M 11s\n", - "136400K .......... .......... .......... .......... .......... 22% 36.6M 11s\n", - "136450K .......... .......... .......... .......... .......... 22% 42.5M 11s\n", - "136500K .......... .......... .......... .......... .......... 22% 10.3M 11s\n", - "136550K .......... .......... .......... .......... .......... 22% 49.4M 11s\n", - "136600K .......... .......... .......... .......... .......... 22% 50.5M 11s\n", - "136650K .......... .......... .......... .......... .......... 22% 69.6M 11s\n", - "136700K .......... .......... .......... .......... .......... 22% 69.7M 11s\n", - "136750K .......... .......... .......... .......... .......... 23% 57.7M 11s\n", - "136800K .......... .......... .......... .......... .......... 23% 45.2M 11s\n", - "136850K .......... .......... .......... .......... .......... 23% 64.2M 11s\n", - "136900K .......... .......... .......... .......... .......... 23% 66.2M 11s\n", - "136950K .......... .......... .......... .......... .......... 23% 29.1M 11s\n", - "137000K .......... .......... .......... .......... .......... 23% 40.0M 11s\n", - "137050K .......... .......... .......... .......... .......... 23% 64.0M 11s\n", - "137100K .......... .......... .......... .......... .......... 23% 66.4M 11s\n", - "137150K .......... .......... .......... .......... .......... 23% 30.5M 11s\n", - "137200K .......... .......... .......... .......... .......... 23% 40.3M 11s\n", - "137250K .......... .......... .......... .......... .......... 23% 52.5M 11s\n", - "137300K .......... .......... .......... .......... .......... 23% 55.7M 11s\n", - "137350K .......... .......... .......... .......... .......... 23% 30.7M 11s\n", - "137400K .......... .......... .......... .......... .......... 23% 41.3M 11s\n", - "137450K .......... .......... .......... .......... .......... 23% 53.8M 11s\n", - "137500K .......... .......... .......... .......... .......... 23% 69.0M 11s\n", - "137550K .......... .......... .......... .......... .......... 23% 31.7M 11s\n", - "137600K .......... .......... .......... .......... .......... 23% 45.9M 11s\n", - "137650K .......... .......... .......... .......... .......... 23% 61.4M 11s\n", - "137700K .......... .......... .......... .......... .......... 23% 65.6M 10s\n", - "137750K .......... .......... .......... .......... .......... 23% 71.6M 10s\n", - "137800K .......... .......... .......... .......... .......... 23% 19.5M 10s\n", - "137850K .......... .......... .......... .......... .......... 23% 52.5M 10s\n", - "137900K .......... .......... .......... .......... .......... 23% 63.8M 10s\n", - "137950K .......... .......... .......... .......... .......... 23% 65.0M 10s\n", - "138000K .......... .......... .......... .......... .......... 23% 30.8M 10s\n", - "138050K .......... .......... .......... .......... .......... 23% 48.7M 10s\n", - "138100K .......... .......... .......... .......... .......... 23% 59.5M 10s\n", - "138150K .......... .......... .......... .......... .......... 23% 70.7M 10s\n", - "138200K .......... .......... .......... .......... .......... 23% 24.0M 10s\n", - "138250K .......... .......... .......... .......... .......... 23% 50.8M 10s\n", - "138300K .......... .......... .......... .......... .......... 23% 53.9M 10s\n", - "138350K .......... .......... .......... .......... .......... 23% 70.9M 10s\n", - "138400K .......... .......... .......... .......... .......... 23% 26.1M 10s\n", - "138450K .......... .......... .......... .......... .......... 23% 52.9M 10s\n", - "138500K .......... .......... .......... .......... .......... 23% 52.0M 10s\n", - "138550K .......... .......... .......... .......... .......... 23% 71.0M 10s\n", - "138600K .......... .......... .......... .......... .......... 23% 25.0M 10s\n", - "138650K .......... .......... .......... .......... .......... 23% 51.2M 10s\n", - "138700K .......... .......... .......... .......... .......... 23% 53.4M 10s\n", - "138750K .......... .......... .......... .......... .......... 23% 71.5M 10s\n", - "138800K .......... .......... .......... .......... .......... 23% 27.9M 10s\n", - "138850K .......... .......... .......... .......... .......... 23% 38.4M 10s\n", - "138900K .......... .......... .......... .......... .......... 23% 54.3M 10s\n", - "138950K .......... .......... .......... .......... .......... 23% 68.6M 10s\n", - "139000K .......... .......... .......... .......... .......... 23% 32.6M 10s\n", - "139050K .......... .......... .......... .......... .......... 23% 54.1M 10s\n", - "139100K .......... .......... .......... .......... .......... 23% 57.0M 10s\n", - "139150K .......... .......... .......... .......... .......... 23% 65.1M 10s\n", - "139200K .......... .......... .......... .......... .......... 23% 4.65M 10s\n", - "139250K .......... .......... .......... .......... .......... 23% 54.3M 10s\n", - "139300K .......... .......... .......... .......... .......... 23% 67.4M 10s\n", - "139350K .......... .......... .......... .......... .......... 23% 68.5M 10s\n", - "139400K .......... .......... .......... .......... .......... 23% 22.1M 10s\n", - "139450K .......... .......... .......... .......... .......... 23% 49.0M 10s\n", - "139500K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", - "139550K .......... .......... .......... .......... .......... 23% 71.7M 10s\n", - "139600K .......... .......... .......... .......... .......... 23% 32.8M 10s\n", - "139650K .......... .......... .......... .......... .......... 23% 51.9M 10s\n", - "139700K .......... .......... .......... .......... .......... 23% 50.2M 10s\n", - "139750K .......... .......... .......... .......... .......... 23% 66.2M 10s\n", - "139800K .......... .......... .......... .......... .......... 23% 27.2M 10s\n", - "139850K .......... .......... .......... .......... .......... 23% 59.7M 10s\n", - "139900K .......... .......... .......... .......... .......... 23% 53.9M 10s\n", - "139950K .......... .......... .......... .......... .......... 23% 63.2M 10s\n", - "140000K .......... .......... .......... .......... .......... 23% 61.8M 10s\n", - "140050K .......... .......... .......... .......... .......... 23% 23.7M 10s\n", - "140100K .......... .......... .......... .......... .......... 23% 53.4M 10s\n", - "140150K .......... .......... .......... .......... .......... 23% 62.0M 10s\n", - "140200K .......... .......... .......... .......... .......... 23% 57.9M 10s\n", - "140250K .......... .......... .......... .......... .......... 23% 29.7M 10s\n", - "140300K .......... .......... .......... .......... .......... 23% 49.5M 10s\n", - "140350K .......... .......... .......... .......... .......... 23% 49.8M 10s\n", - "140400K .......... .......... .......... .......... .......... 23% 63.5M 10s\n", - "140450K .......... .......... .......... .......... .......... 23% 43.2M 10s\n", - "140500K .......... .......... .......... .......... .......... 23% 35.1M 10s\n", - "140550K .......... .......... .......... .......... .......... 23% 47.2M 10s\n", - "140600K .......... .......... .......... .......... .......... 23% 51.0M 10s\n", - "140650K .......... .......... .......... .......... .......... 23% 61.5M 10s\n", - "140700K .......... .......... .......... .......... .......... 23% 36.2M 10s\n", - "140750K .......... .......... .......... .......... .......... 23% 53.1M 10s\n", - "140800K .......... .......... .......... .......... .......... 23% 47.1M 10s\n", - "140850K .......... .......... .......... .......... .......... 23% 67.1M 10s\n", - "140900K .......... .......... .......... .......... .......... 23% 67.2M 10s\n", - "140950K .......... .......... .......... .......... .......... 23% 30.3M 10s\n", - "141000K .......... .......... .......... .......... .......... 23% 51.0M 10s\n", - "141050K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", - "141100K .......... .......... .......... .......... .......... 23% 42.2M 10s\n", - "141150K .......... .......... .......... .......... .......... 23% 30.6M 10s\n", - "141200K .......... .......... .......... .......... .......... 23% 46.7M 10s\n", - "141250K .......... .......... .......... .......... .......... 23% 59.6M 10s\n", - "141300K .......... .......... .......... .......... .......... 23% 71.0M 10s\n", - "141350K .......... .......... .......... .......... .......... 23% 35.7M 10s\n", - "141400K .......... .......... .......... .......... .......... 23% 46.7M 10s\n", - "141450K .......... .......... .......... .......... .......... 23% 57.0M 10s\n", - "141500K .......... .......... .......... .......... .......... 23% 59.8M 10s\n", - "141550K .......... .......... .......... .......... .......... 23% 61.2M 10s\n", - "141600K .......... .......... .......... .......... .......... 23% 4.27M 10s\n", - "141650K .......... .......... .......... .......... .......... 23% 62.2M 10s\n", - "141700K .......... .......... .......... .......... .......... 23% 65.0M 10s\n", - "141750K .......... .......... .......... .......... .......... 23% 63.7M 10s\n", - "141800K .......... .......... .......... .......... .......... 23% 56.1M 10s\n", - "141850K .......... .......... .......... .......... .......... 23% 20.1M 10s\n", - "141900K .......... .......... .......... .......... .......... 23% 49.8M 10s\n", - "141950K .......... .......... .......... .......... .......... 23% 64.3M 10s\n", - "142000K .......... .......... .......... .......... .......... 23% 64.9M 10s\n", - "142050K .......... .......... .......... .......... .......... 23% 33.3M 10s\n", - "142100K .......... .......... .......... .......... .......... 23% 56.5M 10s\n", - "142150K .......... .......... .......... .......... .......... 23% 54.8M 10s\n", - "142200K .......... .......... .......... .......... .......... 23% 58.0M 10s\n", - "142250K .......... .......... .......... .......... .......... 23% 68.6M 10s\n", - "142300K .......... .......... .......... .......... .......... 23% 30.5M 10s\n", - "142350K .......... .......... .......... .......... .......... 23% 54.4M 10s\n", - "142400K .......... .......... .......... .......... .......... 23% 47.7M 10s\n", - "142450K .......... .......... .......... .......... .......... 23% 67.8M 10s\n", - "142500K .......... .......... .......... .......... .......... 23% 32.3M 10s\n", - "142550K .......... .......... .......... .......... .......... 23% 46.6M 10s\n", - "142600K .......... .......... .......... .......... .......... 23% 43.3M 10s\n", - "142650K .......... .......... .......... .......... .......... 23% 66.8M 10s\n", - "142700K .......... .......... .......... .......... .......... 24% 66.0M 10s\n", - "142750K .......... .......... .......... .......... .......... 24% 34.8M 10s\n", - "142800K .......... .......... .......... .......... .......... 24% 41.3M 10s\n", - "142850K .......... .......... .......... .......... .......... 24% 55.5M 10s\n", - "142900K .......... .......... .......... .......... .......... 24% 68.0M 10s\n", - "142950K .......... .......... .......... .......... .......... 24% 37.0M 10s\n", - "143000K .......... .......... .......... .......... .......... 24% 40.0M 10s\n", - "143050K .......... .......... .......... .......... .......... 24% 47.0M 10s\n", - "143100K .......... .......... .......... .......... .......... 24% 70.7M 10s\n", - "143150K .......... .......... .......... .......... .......... 24% 66.9M 10s\n", - "143200K .......... .......... .......... .......... .......... 24% 32.8M 10s\n", - "143250K .......... .......... .......... .......... .......... 24% 8.78M 10s\n", - "143300K .......... .......... .......... .......... .......... 24% 68.6M 10s\n", - "143350K .......... .......... .......... .......... .......... 24% 69.1M 10s\n", - "143400K .......... .......... .......... .......... .......... 24% 62.0M 10s\n", - "143450K .......... .......... .......... .......... .......... 24% 66.7M 10s\n", - "143500K .......... .......... .......... .......... .......... 24% 67.6M 10s\n", - "143550K .......... .......... .......... .......... .......... 24% 28.0M 10s\n", - "143600K .......... .......... .......... .......... .......... 24% 44.9M 10s\n", - "143650K .......... .......... .......... .......... .......... 24% 70.6M 10s\n", - "143700K .......... .......... .......... .......... .......... 24% 69.9M 10s\n", - "143750K .......... .......... .......... .......... .......... 24% 29.3M 10s\n", - "143800K .......... .......... .......... .......... .......... 24% 45.7M 10s\n", - "143850K .......... .......... .......... .......... .......... 24% 53.6M 10s\n", - "143900K .......... .......... .......... .......... .......... 24% 71.8M 10s\n", - "143950K .......... .......... .......... .......... .......... 24% 63.6M 10s\n", - "144000K .......... .......... .......... .......... .......... 24% 34.6M 10s\n", - "144050K .......... .......... .......... .......... .......... 24% 54.6M 10s\n", - "144100K .......... .......... .......... .......... .......... 24% 51.3M 10s\n", - "144150K .......... .......... .......... .......... .......... 24% 14.4M 10s\n", - "144200K .......... .......... .......... .......... .......... 24% 39.5M 10s\n", - "144250K .......... .......... .......... .......... .......... 24% 67.9M 10s\n", - "144300K .......... .......... .......... .......... .......... 24% 69.2M 10s\n", - "144350K .......... .......... .......... .......... .......... 24% 65.5M 10s\n", - "144400K .......... .......... .......... .......... .......... 24% 63.1M 10s\n", - "144450K .......... .......... .......... .......... .......... 24% 49.5M 10s\n", - "144500K .......... .......... .......... .......... .......... 24% 50.4M 10s\n", - "144550K .......... .......... .......... .......... .......... 24% 58.5M 10s\n", - "144600K .......... .......... .......... .......... .......... 24% 53.4M 10s\n", - "144650K .......... .......... .......... .......... .......... 24% 69.2M 10s\n", - "144700K .......... .......... .......... .......... .......... 24% 56.2M 10s\n", - "144750K .......... .......... .......... .......... .......... 24% 65.7M 10s\n", - "144800K .......... .......... .......... .......... .......... 24% 49.7M 10s\n", - "144850K .......... .......... .......... .......... .......... 24% 66.2M 10s\n", - "144900K .......... .......... .......... .......... .......... 24% 71.1M 10s\n", - "144950K .......... .......... .......... .......... .......... 24% 32.2M 10s\n", - "145000K .......... .......... .......... .......... .......... 24% 53.6M 10s\n", - "145050K .......... .......... .......... .......... .......... 24% 68.1M 10s\n", - "145100K .......... .......... .......... .......... .......... 24% 70.5M 10s\n", - "145150K .......... .......... .......... .......... .......... 24% 31.9M 10s\n", - "145200K .......... .......... .......... .......... .......... 24% 42.7M 10s\n", - "145250K .......... .......... .......... .......... .......... 24% 51.1M 10s\n", - "145300K .......... .......... .......... .......... .......... 24% 55.0M 10s\n", - "145350K .......... .......... .......... .......... .......... 24% 62.1M 10s\n", - "145400K .......... .......... .......... .......... .......... 24% 32.4M 10s\n", - "145450K .......... .......... .......... .......... .......... 24% 56.7M 10s\n", - "145500K .......... .......... .......... .......... .......... 24% 54.6M 10s\n", - "145550K .......... .......... .......... .......... .......... 24% 66.4M 10s\n", - "145600K .......... .......... 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.......... .......... .......... .......... 24% 43.7M 10s\n", - "146250K .......... .......... .......... .......... .......... 24% 64.2M 10s\n", - "146300K .......... .......... .......... .......... .......... 24% 59.6M 10s\n", - "146350K .......... .......... .......... .......... .......... 24% 60.9M 10s\n", - "146400K .......... .......... .......... .......... .......... 24% 54.5M 10s\n", - "146450K .......... .......... .......... .......... .......... 24% 56.2M 10s\n", - "146500K .......... .......... .......... .......... .......... 24% 51.4M 10s\n", - "146550K .......... .......... .......... .......... .......... 24% 8.49M 10s\n", - "146600K .......... .......... .......... .......... .......... 24% 44.9M 10s\n", - "146650K .......... .......... .......... .......... .......... 24% 62.3M 10s\n", - "146700K .......... .......... .......... .......... .......... 24% 54.0M 10s\n", - "146750K .......... .......... .......... .......... .......... 24% 57.7M 10s\n", - "146800K .......... .......... .......... .......... .......... 24% 55.7M 10s\n", - "146850K .......... .......... .......... .......... .......... 24% 52.3M 10s\n", - "146900K .......... .......... .......... .......... .......... 24% 55.6M 10s\n", - "146950K .......... .......... .......... .......... .......... 24% 54.0M 10s\n", - "147000K .......... .......... .......... .......... .......... 24% 43.1M 10s\n", - "147050K .......... .......... .......... .......... .......... 24% 63.5M 10s\n", - "147100K .......... .......... .......... .......... .......... 24% 58.5M 10s\n", - "147150K .......... .......... .......... .......... .......... 24% 57.4M 10s\n", - "147200K .......... .......... .......... .......... .......... 24% 40.8M 10s\n", - "147250K .......... .......... .......... .......... .......... 24% 54.7M 10s\n", - "147300K .......... .......... .......... .......... .......... 24% 4.90M 10s\n", - "147350K .......... .......... .......... .......... .......... 24% 62.1M 10s\n", - "147400K .......... .......... .......... .......... .......... 24% 51.0M 10s\n", - "147450K .......... .......... .......... .......... .......... 24% 60.3M 10s\n", - "147500K .......... .......... .......... .......... .......... 24% 64.8M 10s\n", - "147550K .......... .......... .......... .......... .......... 24% 69.8M 10s\n", - "147600K .......... .......... .......... .......... .......... 24% 54.7M 10s\n", - "147650K .......... .......... .......... .......... .......... 24% 58.2M 10s\n", - "147700K .......... .......... .......... .......... .......... 24% 69.3M 10s\n", - "147750K .......... .......... .......... .......... .......... 24% 69.2M 10s\n", - "147800K .......... .......... .......... .......... .......... 24% 59.5M 10s\n", - "147850K .......... .......... .......... .......... .......... 24% 4.69M 10s\n", - "147900K .......... .......... .......... .......... .......... 24% 6.13M 10s\n", - "147950K .......... .......... .......... .......... .......... 24% 67.0M 10s\n", - "148000K .......... .......... .......... .......... .......... 24% 53.0M 10s\n", - "148050K .......... .......... .......... .......... .......... 24% 61.8M 10s\n", - "148100K .......... .......... .......... .......... .......... 24% 69.1M 10s\n", - "148150K .......... .......... .......... .......... .......... 24% 68.0M 10s\n", - "148200K .......... .......... .......... .......... .......... 24% 57.3M 10s\n", - "148250K .......... .......... .......... .......... .......... 24% 62.2M 10s\n", - "148300K .......... .......... .......... .......... .......... 24% 60.5M 10s\n", - "148350K .......... .......... .......... .......... .......... 24% 60.5M 10s\n", - "148400K .......... .......... .......... .......... .......... 24% 60.7M 10s\n", - "148450K .......... .......... .......... .......... .......... 24% 68.6M 10s\n", - "148500K .......... .......... .......... .......... .......... 24% 69.3M 10s\n", - "148550K .......... .......... .......... .......... .......... 24% 48.9M 10s\n", - "148600K .......... .......... .......... .......... .......... 24% 25.5M 10s\n", - "148650K .......... .......... .......... .......... .......... 25% 35.4M 10s\n", - "148700K .......... .......... .......... .......... .......... 25% 38.4M 10s\n", - "148750K .......... .......... .......... .......... .......... 25% 33.5M 10s\n", - "148800K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", - "148850K .......... .......... .......... .......... .......... 25% 43.1M 10s\n", - "148900K .......... .......... .......... .......... .......... 25% 69.0M 10s\n", - "148950K .......... .......... .......... .......... .......... 25% 50.3M 10s\n", - "149000K .......... .......... .......... .......... .......... 25% 47.9M 10s\n", - "149050K .......... .......... .......... .......... .......... 25% 18.1M 10s\n", - "149100K .......... .......... .......... .......... .......... 25% 32.1M 10s\n", - "149150K .......... .......... .......... .......... .......... 25% 14.9M 10s\n", - "149200K .......... .......... .......... .......... .......... 25% 45.1M 10s\n", - "149250K .......... .......... .......... .......... .......... 25% 53.7M 10s\n", - "149300K .......... .......... .......... .......... .......... 25% 17.2M 10s\n", - "149350K .......... .......... .......... .......... .......... 25% 48.8M 10s\n", - "149400K .......... .......... .......... .......... .......... 25% 14.6M 10s\n", - "149450K .......... .......... .......... .......... .......... 25% 31.5M 10s\n", - "149500K .......... .......... .......... .......... .......... 25% 37.7M 10s\n", - "149550K .......... .......... .......... .......... .......... 25% 21.0M 10s\n", - "149600K .......... .......... .......... .......... .......... 25% 29.0M 10s\n", - "149650K .......... .......... .......... .......... .......... 25% 20.9M 10s\n", - "149700K .......... .......... .......... .......... .......... 25% 37.3M 10s\n", - "149750K .......... .......... .......... .......... .......... 25% 55.9M 10s\n", - "149800K .......... .......... .......... .......... .......... 25% 14.1M 10s\n", - "149850K .......... .......... .......... .......... .......... 25% 46.2M 10s\n", - "149900K .......... .......... .......... .......... .......... 25% 21.8M 10s\n", - "149950K .......... .......... .......... .......... .......... 25% 32.8M 10s\n", - "150000K .......... .......... .......... .......... .......... 25% 29.5M 10s\n", - "150050K .......... .......... .......... .......... .......... 25% 19.9M 10s\n", - "150100K .......... .......... .......... .......... .......... 25% 40.4M 10s\n", - "150150K .......... .......... .......... .......... .......... 25% 23.5M 10s\n", - "150200K .......... .......... .......... .......... .......... 25% 22.2M 10s\n", - "150250K .......... .......... .......... .......... .......... 25% 24.9M 10s\n", - "150300K .......... .......... .......... .......... .......... 25% 29.7M 10s\n", - "150350K .......... .......... .......... .......... .......... 25% 42.5M 10s\n", - "150400K .......... .......... .......... .......... .......... 25% 18.0M 10s\n", - "150450K .......... .......... .......... .......... .......... 25% 42.3M 10s\n", - "150500K .......... .......... .......... .......... .......... 25% 25.5M 10s\n", - "150550K .......... .......... .......... .......... .......... 25% 20.6M 10s\n", - "150600K .......... .......... .......... .......... .......... 25% 37.2M 10s\n", - "150650K .......... .......... .......... .......... .......... 25% 19.0M 10s\n", - "150700K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", - "150750K .......... .......... .......... .......... .......... 25% 31.3M 10s\n", - "150800K .......... .......... .......... .......... .......... 25% 24.5M 10s\n", - "150850K .......... .......... .......... .......... .......... 25% 33.7M 10s\n", - "150900K .......... .......... .......... .......... .......... 25% 3.65M 10s\n", - "150950K .......... .......... .......... .......... .......... 25% 62.9M 10s\n", - "151000K .......... .......... .......... .......... .......... 25% 54.8M 10s\n", - "151050K .......... .......... .......... .......... .......... 25% 56.6M 10s\n", - "151100K .......... .......... .......... .......... .......... 25% 56.8M 10s\n", - "151150K .......... .......... .......... .......... .......... 25% 67.9M 10s\n", - "151200K .......... .......... .......... .......... .......... 25% 62.6M 10s\n", - "151250K .......... .......... .......... .......... .......... 25% 72.6M 10s\n", - "151300K .......... .......... .......... .......... .......... 25% 65.7M 10s\n", - "151350K .......... .......... .......... .......... .......... 25% 68.7M 10s\n", - "151400K .......... .......... .......... .......... .......... 25% 49.8M 10s\n", - "151450K .......... .......... .......... .......... .......... 25% 16.6M 10s\n", - "151500K .......... .......... .......... .......... .......... 25% 58.0M 10s\n", - "151550K .......... .......... .......... .......... .......... 25% 49.8M 10s\n", - "151600K .......... .......... .......... .......... .......... 25% 4.33M 10s\n", - "151650K .......... .......... .......... .......... .......... 25% 53.9M 10s\n", - "151700K .......... .......... .......... .......... .......... 25% 67.4M 10s\n", - "151750K .......... .......... .......... .......... .......... 25% 12.9M 10s\n", - "151800K .......... .......... .......... .......... .......... 25% 55.1M 10s\n", - "151850K .......... .......... .......... .......... .......... 25% 15.0M 10s\n", - "151900K .......... .......... .......... .......... .......... 25% 54.6M 10s\n", - "151950K .......... .......... .......... .......... .......... 25% 18.6M 10s\n", - "152000K .......... .......... .......... .......... .......... 25% 37.7M 10s\n", - "152050K .......... .......... .......... .......... .......... 25% 44.8M 10s\n", - "152100K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", - "152150K .......... .......... .......... .......... .......... 25% 36.6M 10s\n", - "152200K .......... .......... .......... .......... .......... 25% 18.0M 10s\n", - "152250K .......... .......... .......... .......... .......... 25% 39.5M 10s\n", - "152300K .......... .......... .......... .......... .......... 25% 42.0M 10s\n", - "152350K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", - "152400K .......... .......... .......... .......... .......... 25% 29.9M 10s\n", - "152450K .......... .......... .......... .......... .......... 25% 65.0M 10s\n", - "152500K .......... .......... .......... .......... .......... 25% 18.4M 10s\n", - "152550K .......... .......... .......... .......... .......... 25% 35.0M 10s\n", - "152600K .......... .......... .......... .......... .......... 25% 20.3M 10s\n", - "152650K .......... .......... .......... .......... .......... 25% 60.8M 10s\n", - "152700K .......... .......... .......... .......... .......... 25% 32.7M 10s\n", - "152750K .......... .......... .......... .......... .......... 25% 22.6M 10s\n", - "152800K .......... .......... .......... .......... .......... 25% 25.7M 10s\n", - "152850K .......... .......... .......... .......... .......... 25% 58.4M 10s\n", - "152900K .......... .......... .......... .......... .......... 25% 21.0M 10s\n", - "152950K .......... .......... .......... .......... .......... 25% 31.0M 10s\n", - "153000K .......... .......... .......... .......... .......... 25% 7.67M 10s\n", - "153050K .......... .......... .......... .......... .......... 25% 51.8M 10s\n", - "153100K .......... .......... .......... .......... .......... 25% 69.5M 10s\n", - "153150K .......... .......... .......... .......... .......... 25% 59.7M 10s\n", - "153200K .......... .......... .......... .......... .......... 25% 55.8M 10s\n", - "153250K .......... .......... .......... .......... .......... 25% 70.8M 10s\n", - "153300K .......... .......... .......... .......... .......... 25% 35.5M 10s\n", - "153350K .......... .......... .......... .......... .......... 25% 28.8M 10s\n", - "153400K .......... .......... .......... .......... .......... 25% 21.1M 10s\n", - "153450K .......... .......... .......... .......... .......... 25% 68.2M 10s\n", - "153500K .......... .......... .......... .......... .......... 25% 29.8M 10s\n", - "153550K .......... .......... .......... .......... .......... 25% 23.2M 10s\n", - "153600K .......... .......... .......... .......... .......... 25% 29.5M 10s\n", - "153650K .......... .......... .......... .......... .......... 25% 50.7M 10s\n", - "153700K .......... .......... .......... .......... .......... 25% 18.8M 10s\n", - "153750K .......... .......... .......... .......... .......... 25% 38.1M 10s\n", - "153800K .......... .......... .......... .......... .......... 25% 20.2M 10s\n", - "153850K .......... .......... .......... .......... .......... 25% 45.6M 10s\n", - "153900K .......... .......... .......... .......... .......... 25% 43.1M 10s\n", - "153950K .......... .......... .......... .......... .......... 25% 21.5M 10s\n", - "154000K .......... .......... .......... .......... .......... 25% 41.6M 10s\n", - "154050K .......... .......... .......... .......... .......... 25% 42.0M 10s\n", - "154100K .......... .......... .......... .......... .......... 25% 17.6M 10s\n", - "154150K .......... .......... .......... .......... .......... 25% 53.0M 10s\n", - "154200K .......... .......... .......... .......... .......... 25% 42.7M 10s\n", - "154250K .......... .......... .......... .......... .......... 25% 8.29M 10s\n", - "154300K .......... .......... .......... .......... .......... 25% 62.4M 10s\n", - "154350K .......... .......... .......... .......... .......... 25% 65.2M 10s\n", - "154400K .......... .......... .......... .......... .......... 25% 15.1M 10s\n", - "154450K .......... .......... .......... .......... .......... 25% 60.6M 10s\n", - "154500K .......... .......... .......... 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.......... .......... .......... 26% 20.9M 10s\n", - "155150K .......... .......... .......... .......... .......... 26% 39.7M 10s\n", - "155200K .......... .......... .......... .......... .......... 26% 41.1M 10s\n", - "155250K .......... .......... .......... .......... .......... 26% 22.1M 10s\n", - "155300K .......... .......... .......... .......... .......... 26% 38.7M 10s\n", - "155350K .......... .......... .......... .......... .......... 26% 40.9M 10s\n", - "155400K .......... .......... .......... .......... .......... 26% 21.0M 10s\n", - "155450K .......... .......... .......... .......... .......... 26% 25.6M 10s\n", - "155500K .......... .......... .......... .......... .......... 26% 57.8M 10s\n", - "155550K .......... .......... .......... .......... .......... 26% 27.0M 10s\n", - "155600K .......... .......... .......... .......... .......... 26% 39.0M 10s\n", - "155650K .......... .......... .......... .......... .......... 26% 36.1M 10s\n", - "155700K .......... .......... .......... .......... .......... 26% 27.3M 10s\n", - "155750K .......... .......... .......... .......... .......... 26% 41.6M 10s\n", - "155800K .......... .......... .......... .......... .......... 26% 30.4M 10s\n", - "155850K .......... .......... .......... .......... .......... 26% 26.5M 10s\n", - "155900K .......... .......... .......... .......... .......... 26% 24.3M 10s\n", - "155950K .......... .......... .......... .......... .......... 26% 62.5M 10s\n", - "156000K .......... .......... .......... .......... .......... 26% 22.4M 10s\n", - "156050K .......... .......... .......... .......... .......... 26% 50.0M 10s\n", - "156100K .......... .......... .......... .......... .......... 26% 33.4M 10s\n", - "156150K .......... .......... .......... .......... .......... 26% 30.9M 10s\n", - "156200K .......... .......... .......... .......... .......... 26% 22.9M 10s\n", - "156250K .......... .......... .......... .......... .......... 26% 54.5M 10s\n", - "156300K .......... .......... .......... .......... .......... 26% 30.0M 10s\n", - "156350K .......... .......... .......... .......... .......... 26% 35.2M 10s\n", - "156400K .......... .......... .......... .......... .......... 26% 34.4M 10s\n", - "156450K .......... .......... .......... .......... .......... 26% 32.7M 10s\n", - "156500K .......... .......... .......... .......... .......... 26% 33.2M 10s\n", - "156550K .......... .......... .......... .......... .......... 26% 38.7M 10s\n", - "156600K .......... .......... .......... .......... .......... 26% 23.9M 10s\n", - "156650K .......... .......... .......... .......... .......... 26% 31.4M 10s\n", - "156700K .......... .......... .......... .......... .......... 26% 68.6M 10s\n", - "156750K .......... .......... .......... .......... .......... 26% 24.9M 10s\n", - "156800K .......... .......... .......... .......... .......... 26% 30.5M 10s\n", - "156850K .......... .......... .......... .......... .......... 26% 41.9M 10s\n", - "156900K .......... .......... .......... .......... .......... 26% 25.5M 10s\n", - "156950K .......... .......... .......... .......... .......... 26% 59.0M 10s\n", - "157000K .......... .......... .......... .......... .......... 26% 28.1M 10s\n", - "157050K .......... .......... .......... .......... .......... 26% 27.8M 10s\n", - "157100K .......... .......... .......... .......... .......... 26% 27.8M 10s\n", - "157150K .......... .......... .......... .......... .......... 26% 40.2M 10s\n", - "157200K .......... .......... .......... .......... .......... 26% 51.0M 10s\n", - "157250K .......... .......... .......... .......... .......... 26% 29.4M 10s\n", - "157300K .......... .......... .......... .......... .......... 26% 34.6M 10s\n", - "157350K .......... .......... .......... .......... .......... 26% 50.7M 10s\n", - "157400K .......... .......... .......... .......... .......... 26% 22.4M 10s\n", - "157450K .......... .......... .......... .......... .......... 26% 42.7M 10s\n", - "157500K .......... .......... .......... .......... .......... 26% 39.9M 10s\n", - "157550K .......... .......... .......... .......... .......... 26% 21.7M 10s\n", - "157600K .......... .......... .......... .......... .......... 26% 51.6M 10s\n", - "157650K .......... .......... .......... .......... .......... 26% 36.4M 10s\n", - "157700K .......... .......... .......... .......... .......... 26% 34.8M 10s\n", - "157750K .......... .......... .......... .......... .......... 26% 26.5M 10s\n", - "157800K .......... .......... .......... .......... .......... 26% 38.1M 10s\n", - "157850K .......... .......... .......... .......... .......... 26% 41.5M 10s\n", - "157900K .......... .......... .......... .......... .......... 26% 30.4M 10s\n", - "157950K .......... .......... .......... .......... .......... 26% 30.1M 10s\n", - "158000K .......... .......... .......... .......... .......... 26% 47.3M 10s\n", - "158050K .......... .......... .......... .......... .......... 26% 32.1M 10s\n", - "158100K .......... .......... .......... .......... .......... 26% 32.1M 10s\n", - "158150K .......... .......... .......... .......... .......... 26% 43.6M 10s\n", - "158200K .......... .......... .......... .......... .......... 26% 3.52M 10s\n", - "158250K .......... .......... .......... .......... .......... 26% 56.1M 10s\n", - "158300K .......... .......... .......... .......... .......... 26% 65.9M 10s\n", - "158350K .......... .......... .......... .......... .......... 26% 62.4M 10s\n", - "158400K .......... .......... .......... .......... .......... 26% 16.0M 10s\n", - "158450K .......... .......... .......... .......... .......... 26% 55.9M 10s\n", - "158500K .......... .......... .......... .......... .......... 26% 71.2M 10s\n", - "158550K .......... .......... .......... .......... .......... 26% 16.9M 10s\n", - "158600K .......... .......... .......... .......... .......... 26% 35.8M 10s\n", - "158650K .......... .......... .......... .......... .......... 26% 62.9M 10s\n", - "158700K .......... .......... .......... .......... .......... 26% 22.4M 10s\n", - "158750K .......... .......... .......... .......... .......... 26% 44.0M 10s\n", - "158800K .......... .......... .......... .......... .......... 26% 50.1M 10s\n", - "158850K .......... .......... .......... .......... .......... 26% 70.8M 10s\n", - "158900K .......... .......... .......... .......... .......... 26% 16.0M 10s\n", - "158950K .......... .......... .......... .......... .......... 26% 52.6M 10s\n", - "159000K .......... .......... .......... .......... .......... 26% 58.2M 10s\n", - "159050K .......... .......... .......... .......... .......... 26% 18.5M 10s\n", - "159100K .......... .......... .......... .......... .......... 26% 43.9M 10s\n", - "159150K .......... .......... .......... .......... .......... 26% 65.9M 10s\n", - "159200K .......... .......... .......... .......... .......... 26% 24.5M 10s\n", - "159250K .......... .......... .......... .......... .......... 26% 39.5M 10s\n", - "159300K .......... .......... .......... .......... .......... 26% 54.7M 10s\n", - "159350K .......... .......... .......... .......... .......... 26% 65.8M 10s\n", - "159400K .......... .......... .......... .......... .......... 26% 16.8M 10s\n", - "159450K .......... .......... .......... .......... .......... 26% 51.5M 10s\n", - "159500K .......... .......... .......... .......... .......... 26% 66.8M 10s\n", - "159550K .......... .......... .......... .......... .......... 26% 25.0M 10s\n", - "159600K .......... .......... .......... .......... .......... 26% 37.0M 10s\n", - "159650K .......... .......... .......... .......... .......... 26% 61.3M 10s\n", - "159700K .......... .......... .......... .......... .......... 26% 23.5M 10s\n", - "159750K .......... .......... .......... .......... .......... 26% 37.8M 10s\n", - "159800K .......... .......... .......... .......... .......... 26% 38.8M 10s\n", - "159850K .......... .......... .......... .......... .......... 26% 67.8M 10s\n", - "159900K .......... .......... .......... .......... .......... 26% 24.8M 10s\n", - "159950K .......... .......... .......... .......... .......... 26% 38.2M 10s\n", - "160000K .......... .......... .......... .......... .......... 26% 52.7M 10s\n", - "160050K .......... .......... .......... .......... .......... 26% 27.1M 10s\n", - "160100K .......... .......... .......... .......... .......... 26% 37.9M 10s\n", - "160150K .......... .......... .......... .......... .......... 26% 50.2M 10s\n", - "160200K .......... .......... .......... .......... .......... 26% 58.2M 10s\n", - "160250K .......... .......... .......... .......... .......... 26% 25.1M 10s\n", - "160300K .......... .......... .......... .......... .......... 26% 32.7M 10s\n", - "160350K .......... .......... .......... .......... .......... 26% 69.7M 10s\n", - "160400K .......... .......... .......... .......... .......... 26% 22.7M 10s\n", - "160450K .......... .......... .......... .......... .......... 26% 43.9M 10s\n", - "160500K .......... .......... .......... .......... .......... 26% 56.6M 10s\n", - "160550K .......... .......... .......... .......... .......... 27% 69.2M 10s\n", - "160600K .......... .......... .......... .......... .......... 27% 20.9M 10s\n", - "160650K .......... .......... .......... .......... .......... 27% 53.7M 10s\n", - "160700K .......... .......... .......... .......... .......... 27% 65.3M 10s\n", - "160750K .......... .......... .......... .......... .......... 27% 21.0M 10s\n", - "160800K .......... .......... .......... .......... .......... 27% 47.1M 10s\n", - "160850K .......... .......... .......... .......... .......... 27% 56.8M 10s\n", - "160900K .......... .......... .......... .......... .......... 27% 73.9M 10s\n", - "160950K .......... .......... .......... .......... .......... 27% 20.6M 10s\n", - "161000K .......... .......... .......... .......... .......... 27% 37.7M 10s\n", - "161050K .......... .......... .......... .......... .......... 27% 69.8M 10s\n", - "161100K .......... .......... .......... .......... .......... 27% 24.0M 10s\n", - "161150K .......... .......... .......... .......... .......... 27% 60.5M 10s\n", - "161200K .......... .......... .......... .......... .......... 27% 50.8M 10s\n", - "161250K .......... .......... .......... .......... .......... 27% 70.8M 10s\n", - "161300K .......... .......... .......... .......... .......... 27% 18.6M 10s\n", - "161350K .......... .......... .......... .......... .......... 27% 40.1M 10s\n", - "161400K .......... .......... .......... .......... .......... 27% 53.8M 10s\n", - "161450K .......... .......... .......... .......... .......... 27% 29.8M 10s\n", - "161500K .......... .......... .......... .......... .......... 27% 55.6M 10s\n", - "161550K .......... .......... .......... .......... .......... 27% 61.9M 10s\n", - "161600K .......... .......... .......... .......... .......... 27% 48.8M 10s\n", - "161650K .......... .......... .......... .......... .......... 27% 21.7M 10s\n", - "161700K .......... .......... .......... .......... .......... 27% 48.1M 10s\n", - "161750K .......... .......... .......... .......... .......... 27% 58.9M 10s\n", - "161800K .......... .......... .......... .......... .......... 27% 25.2M 10s\n", - "161850K .......... .......... .......... .......... .......... 27% 36.9M 10s\n", - "161900K .......... .......... .......... .......... .......... 27% 66.3M 10s\n", - "161950K .......... .......... .......... .......... .......... 27% 3.80M 10s\n", - "162000K .......... .......... .......... .......... .......... 27% 57.1M 10s\n", - "162050K .......... .......... .......... .......... .......... 27% 65.6M 10s\n", - "162100K .......... .......... .......... .......... .......... 27% 62.6M 10s\n", - "162150K .......... .......... .......... .......... .......... 27% 20.1M 10s\n", - "162200K .......... .......... .......... .......... .......... 27% 11.6M 10s\n", - "162250K .......... .......... .......... .......... .......... 27% 48.4M 10s\n", - "162300K .......... .......... .......... .......... .......... 27% 52.4M 10s\n", - "162350K .......... .......... .......... .......... .......... 27% 45.6M 10s\n", - "162400K .......... .......... .......... .......... .......... 27% 56.6M 10s\n", - "162450K .......... .......... .......... .......... .......... 27% 50.9M 10s\n", - "162500K .......... .......... .......... .......... .......... 27% 51.3M 10s\n", - "162550K .......... .......... .......... .......... .......... 27% 67.4M 10s\n", - "162600K .......... .......... .......... .......... .......... 27% 55.0M 10s\n", - "162650K .......... .......... .......... .......... .......... 27% 40.5M 10s\n", - "162700K .......... .......... .......... .......... .......... 27% 43.2M 10s\n", - "162750K .......... .......... .......... .......... .......... 27% 57.7M 10s\n", - "162800K .......... .......... .......... .......... .......... 27% 59.7M 10s\n", - "162850K .......... .......... .......... .......... .......... 27% 24.7M 10s\n", - "162900K .......... .......... .......... .......... .......... 27% 30.5M 10s\n", - "162950K .......... .......... .......... .......... .......... 27% 53.8M 10s\n", - "163000K .......... .......... .......... .......... .......... 27% 38.7M 10s\n", - "163050K .......... .......... .......... .......... .......... 27% 38.0M 10s\n", - "163100K .......... .......... .......... .......... .......... 27% 47.5M 10s\n", - "163150K .......... .......... .......... .......... .......... 27% 65.5M 10s\n", - "163200K .......... .......... .......... .......... .......... 27% 32.8M 10s\n", - "163250K .......... .......... .......... .......... .......... 27% 27.1M 10s\n", - "163300K .......... .......... .......... .......... .......... 27% 57.0M 10s\n", - "163350K .......... .......... .......... .......... .......... 27% 4.75M 10s\n", - "163400K .......... .......... .......... .......... .......... 27% 46.5M 10s\n", - "163450K .......... .......... .......... .......... .......... 27% 67.9M 10s\n", - "163500K .......... .......... .......... .......... .......... 27% 22.4M 10s\n", - "163550K .......... .......... .......... .......... .......... 27% 51.3M 10s\n", - "163600K .......... .......... .......... .......... .......... 27% 50.9M 10s\n", - "163650K .......... .......... .......... .......... .......... 27% 69.5M 10s\n", - "163700K .......... .......... .......... .......... .......... 27% 26.8M 10s\n", - "163750K .......... .......... .......... .......... .......... 27% 48.4M 10s\n", - "163800K .......... .......... .......... .......... .......... 27% 36.9M 10s\n", - "163850K .......... .......... .......... .......... .......... 27% 68.9M 10s\n", - "163900K .......... .......... .......... .......... .......... 27% 27.7M 10s\n", - "163950K .......... .......... .......... .......... .......... 27% 61.7M 10s\n", - "164000K .......... .......... .......... .......... .......... 27% 56.8M 10s\n", - "164050K .......... .......... .......... .......... .......... 27% 63.3M 10s\n", - "164100K .......... .......... .......... .......... .......... 27% 21.5M 10s\n", - "164150K .......... .......... .......... .......... .......... 27% 50.1M 10s\n", - "164200K .......... .......... .......... .......... .......... 27% 46.1M 10s\n", - "164250K .......... .......... .......... .......... .......... 27% 63.6M 10s\n", - "164300K .......... .......... .......... .......... .......... 27% 27.3M 10s\n", - "164350K .......... .......... .......... .......... .......... 27% 61.5M 10s\n", - "164400K .......... .......... .......... .......... .......... 27% 53.7M 10s\n", - "164450K .......... .......... .......... .......... .......... 27% 67.6M 10s\n", - "164500K .......... .......... .......... .......... .......... 27% 21.7M 10s\n", - "164550K .......... .......... .......... .......... .......... 27% 52.2M 10s\n", - "164600K .......... .......... 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.......... .......... .......... .......... 27% 46.7M 10s\n", - "165250K .......... .......... .......... .......... .......... 27% 22.7M 10s\n", - "165300K .......... .......... .......... .......... .......... 27% 52.8M 10s\n", - "165350K .......... .......... .......... .......... .......... 27% 64.2M 10s\n", - "165400K .......... .......... .......... .......... .......... 27% 50.2M 10s\n", - "165450K .......... .......... .......... .......... .......... 27% 26.4M 10s\n", - "165500K .......... .......... .......... .......... .......... 27% 50.6M 10s\n", - "165550K .......... .......... .......... .......... .......... 27% 39.4M 10s\n", - "165600K .......... .......... .......... .......... .......... 27% 54.5M 10s\n", - "165650K .......... .......... .......... .......... .......... 27% 40.5M 10s\n", - "165700K .......... .......... .......... .......... .......... 27% 41.1M 10s\n", - "165750K .......... .......... .......... .......... .......... 27% 51.5M 10s\n", - "165800K .......... .......... .......... .......... .......... 27% 4.62M 10s\n", - "165850K .......... .......... .......... .......... .......... 27% 66.4M 10s\n", - "165900K .......... .......... .......... .......... .......... 27% 65.1M 10s\n", - "165950K .......... .......... .......... .......... .......... 27% 68.7M 10s\n", - "166000K .......... .......... .......... .......... .......... 27% 60.4M 10s\n", - "166050K .......... .......... .......... .......... .......... 27% 26.4M 10s\n", - "166100K .......... .......... .......... .......... .......... 27% 51.4M 10s\n", - "166150K .......... .......... .......... .......... .......... 27% 71.8M 10s\n", - "166200K .......... .......... .......... .......... .......... 27% 28.2M 10s\n", - "166250K .......... .......... .......... .......... .......... 27% 43.3M 10s\n", - "166300K .......... .......... .......... .......... .......... 27% 49.8M 10s\n", - "166350K .......... .......... .......... .......... .......... 27% 60.6M 10s\n", - "166400K .......... .......... .......... .......... .......... 27% 62.9M 10s\n", - "166450K .......... .......... .......... .......... .......... 27% 27.4M 10s\n", - "166500K .......... .......... .......... .......... .......... 28% 51.6M 10s\n", - "166550K .......... .......... .......... .......... .......... 28% 65.3M 10s\n", - "166600K .......... .......... .......... .......... .......... 28% 27.1M 10s\n", - "166650K .......... .......... .......... .......... .......... 28% 47.7M 10s\n", - "166700K .......... .......... .......... .......... .......... 28% 46.3M 10s\n", - "166750K .......... .......... .......... .......... .......... 28% 60.3M 10s\n", - "166800K .......... .......... .......... .......... .......... 28% 57.9M 10s\n", - "166850K .......... .......... .......... .......... .......... 28% 25.5M 10s\n", - "166900K .......... .......... .......... .......... .......... 28% 4.58M 10s\n", - "166950K .......... .......... .......... .......... .......... 28% 48.3M 10s\n", - "167000K .......... .......... .......... .......... .......... 28% 51.3M 10s\n", - "167050K .......... .......... .......... .......... .......... 28% 69.4M 10s\n", - "167100K .......... .......... .......... .......... .......... 28% 27.0M 10s\n", - "167150K .......... .......... .......... .......... .......... 28% 44.4M 10s\n", - "167200K .......... .......... .......... .......... .......... 28% 60.5M 10s\n", - "167250K .......... .......... .......... .......... .......... 28% 66.6M 10s\n", - "167300K .......... .......... .......... .......... .......... 28% 31.4M 10s\n", - "167350K .......... .......... .......... .......... .......... 28% 49.9M 10s\n", - "167400K .......... .......... .......... .......... .......... 28% 3.77M 10s\n", - "167450K .......... .......... .......... .......... .......... 28% 63.4M 10s\n", - "167500K .......... .......... .......... .......... .......... 28% 52.8M 10s\n", - "167550K .......... .......... .......... .......... .......... 28% 62.4M 10s\n", - "167600K .......... .......... .......... .......... .......... 28% 54.3M 10s\n", - "167650K .......... .......... .......... .......... .......... 28% 50.9M 10s\n", - "167700K .......... .......... .......... .......... .......... 28% 47.1M 10s\n", - "167750K .......... .......... .......... .......... .......... 28% 61.9M 10s\n", - "167800K .......... .......... .......... .......... .......... 28% 40.6M 10s\n", - "167850K .......... .......... .......... .......... .......... 28% 69.5M 10s\n", - "167900K .......... .......... .......... .......... .......... 28% 49.8M 10s\n", - "167950K .......... .......... .......... .......... .......... 28% 48.4M 10s\n", - "168000K .......... .......... .......... .......... .......... 28% 53.7M 10s\n", - "168050K .......... .......... .......... .......... .......... 28% 64.7M 10s\n", - "168100K .......... .......... .......... .......... .......... 28% 39.1M 10s\n", - "168150K .......... .......... .......... .......... 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.......... .......... 28% 10.5M 10s\n", - "168800K .......... .......... .......... .......... .......... 28% 44.2M 10s\n", - "168850K .......... .......... .......... .......... .......... 28% 54.7M 10s\n", - "168900K .......... .......... .......... .......... .......... 28% 65.8M 10s\n", - "168950K .......... .......... .......... .......... .......... 28% 33.2M 10s\n", - "169000K .......... .......... .......... .......... .......... 28% 36.2M 10s\n", - "169050K .......... .......... .......... .......... .......... 28% 50.7M 10s\n", - "169100K .......... .......... .......... .......... .......... 28% 64.0M 10s\n", - "169150K .......... .......... .......... .......... .......... 28% 69.9M 10s\n", - "169200K .......... .......... .......... .......... .......... 28% 24.1M 10s\n", - "169250K .......... .......... .......... .......... .......... 28% 50.0M 10s\n", - "169300K .......... .......... .......... .......... .......... 28% 62.2M 10s\n", - "169350K .......... .......... .......... .......... .......... 28% 67.0M 10s\n", - "169400K .......... .......... .......... .......... .......... 28% 25.2M 10s\n", - "169450K .......... .......... .......... .......... .......... 28% 50.9M 10s\n", - "169500K .......... .......... .......... .......... .......... 28% 56.0M 10s\n", - "169550K .......... .......... .......... .......... .......... 28% 69.7M 10s\n", - "169600K .......... .......... .......... .......... .......... 28% 32.1M 10s\n", - "169650K .......... .......... .......... .......... .......... 28% 41.2M 10s\n", - "169700K .......... .......... .......... .......... .......... 28% 48.8M 10s\n", - "169750K .......... .......... .......... .......... .......... 28% 61.6M 10s\n", - "169800K .......... .......... .......... .......... .......... 28% 5.56M 10s\n", - "169850K .......... .......... .......... .......... .......... 28% 57.8M 10s\n", - "169900K .......... .......... .......... .......... .......... 28% 4.10M 10s\n", - "169950K .......... .......... .......... .......... .......... 28% 62.8M 10s\n", - "170000K .......... .......... .......... .......... .......... 28% 54.3M 10s\n", - "170050K .......... .......... .......... .......... .......... 28% 67.0M 10s\n", - "170100K .......... .......... .......... .......... .......... 28% 64.4M 10s\n", - "170150K .......... .......... .......... .......... .......... 28% 70.7M 10s\n", - "170200K .......... .......... .......... .......... .......... 28% 47.4M 10s\n", - "170250K .......... .......... .......... .......... .......... 28% 50.0M 10s\n", - "170300K .......... .......... .......... .......... .......... 28% 57.0M 10s\n", - "170350K .......... .......... .......... .......... .......... 28% 61.1M 10s\n", - "170400K .......... .......... .......... .......... .......... 28% 62.1M 10s\n", - "170450K .......... .......... .......... .......... .......... 28% 56.0M 10s\n", - "170500K .......... .......... .......... .......... .......... 28% 48.3M 10s\n", - "170550K .......... .......... .......... .......... .......... 28% 49.5M 10s\n", - "170600K .......... .......... .......... .......... .......... 28% 57.5M 10s\n", - "170650K .......... .......... .......... .......... .......... 28% 68.0M 10s\n", - "170700K .......... .......... .......... .......... .......... 28% 67.9M 10s\n", - "170750K .......... .......... .......... .......... .......... 28% 49.1M 10s\n", - "170800K .......... .......... .......... .......... .......... 28% 46.3M 10s\n", - "170850K .......... .......... .......... .......... .......... 28% 64.7M 10s\n", - "170900K .......... .......... .......... .......... .......... 28% 69.1M 10s\n", - "170950K .......... .......... .......... .......... .......... 28% 62.9M 10s\n", - "171000K .......... .......... .......... .......... .......... 28% 39.5M 10s\n", - "171050K .......... .......... .......... .......... .......... 28% 41.9M 10s\n", - "171100K .......... .......... .......... .......... .......... 28% 68.7M 10s\n", - "171150K .......... .......... .......... .......... .......... 28% 66.5M 10s\n", - "171200K .......... .......... .......... .......... .......... 28% 36.0M 10s\n", - "171250K .......... .......... .......... .......... .......... 28% 56.6M 10s\n", - "171300K .......... .......... .......... .......... .......... 28% 48.4M 10s\n", - "171350K .......... .......... .......... .......... .......... 28% 58.0M 10s\n", - "171400K .......... .......... .......... .......... .......... 28% 28.8M 10s\n", - "171450K .......... .......... .......... .......... .......... 28% 37.7M 10s\n", - "171500K .......... .......... .......... .......... .......... 28% 32.5M 10s\n", - "171550K .......... .......... .......... .......... .......... 28% 39.8M 10s\n", - "171600K .......... .......... .......... .......... .......... 28% 50.2M 10s\n", - "171650K .......... .......... .......... .......... .......... 28% 53.4M 10s\n", - "171700K .......... .......... .......... .......... .......... 28% 55.0M 10s\n", - "171750K .......... .......... .......... .......... .......... 28% 75.8M 10s\n", - "171800K .......... .......... .......... .......... .......... 28% 54.5M 10s\n", - "171850K .......... .......... .......... .......... .......... 28% 66.3M 10s\n", - "171900K .......... .......... .......... .......... .......... 28% 51.9M 10s\n", - "171950K .......... .......... .......... .......... .......... 28% 54.1M 10s\n", - "172000K .......... .......... .......... .......... .......... 28% 48.1M 10s\n", - "172050K .......... .......... .......... .......... .......... 28% 69.5M 10s\n", - "172100K .......... .......... .......... .......... .......... 28% 40.3M 10s\n", - "172150K .......... .......... .......... .......... .......... 28% 48.9M 10s\n", - "172200K .......... .......... .......... .......... .......... 28% 47.0M 10s\n", - "172250K .......... .......... .......... .......... .......... 28% 62.6M 10s\n", - "172300K .......... .......... .......... .......... .......... 28% 68.2M 10s\n", - "172350K .......... .......... .......... .......... .......... 28% 32.2M 10s\n", - "172400K .......... .......... .......... .......... .......... 28% 44.5M 10s\n", - "172450K .......... .......... .......... .......... .......... 29% 52.4M 10s\n", - "172500K .......... .......... .......... .......... .......... 29% 62.8M 10s\n", - "172550K .......... .......... .......... .......... .......... 29% 67.3M 10s\n", - "172600K .......... .......... .......... .......... .......... 29% 39.9M 10s\n", - "172650K .......... .......... .......... .......... .......... 29% 28.5M 10s\n", - "172700K .......... .......... .......... .......... .......... 29% 37.7M 10s\n", - "172750K .......... .......... .......... .......... .......... 29% 39.1M 10s\n", - "172800K .......... .......... .......... .......... .......... 29% 27.0M 10s\n", - "172850K .......... .......... .......... .......... .......... 29% 4.13M 10s\n", - "172900K .......... .......... .......... .......... .......... 29% 38.3M 10s\n", - "172950K .......... .......... .......... .......... .......... 29% 39.1M 10s\n", - "173000K .......... .......... .......... .......... .......... 29% 28.9M 10s\n", - "173050K .......... .......... .......... .......... .......... 29% 4.27M 10s\n", - "173100K .......... .......... .......... .......... .......... 29% 40.4M 10s\n", - "173150K .......... .......... .......... .......... .......... 29% 39.6M 10s\n", - "173200K .......... .......... .......... .......... .......... 29% 58.8M 10s\n", - "173250K .......... .......... .......... .......... .......... 29% 65.8M 10s\n", - "173300K .......... .......... .......... .......... .......... 29% 42.7M 10s\n", - "173350K .......... .......... .......... .......... .......... 29% 54.5M 10s\n", - "173400K .......... .......... .......... .......... .......... 29% 54.8M 10s\n", - "173450K .......... .......... .......... .......... .......... 29% 61.5M 10s\n", - "173500K .......... .......... .......... .......... .......... 29% 59.4M 10s\n", - "173550K .......... .......... .......... .......... .......... 29% 47.6M 10s\n", - "173600K .......... .......... .......... .......... .......... 29% 18.4M 10s\n", - "173650K .......... .......... .......... .......... .......... 29% 66.0M 10s\n", - "173700K .......... .......... .......... .......... .......... 29% 50.2M 10s\n", - "173750K .......... .......... .......... .......... .......... 29% 51.9M 10s\n", - "173800K .......... .......... .......... .......... .......... 29% 55.0M 10s\n", - "173850K .......... .......... .......... .......... .......... 29% 56.3M 10s\n", - "173900K .......... .......... .......... .......... .......... 29% 18.1M 10s\n", - "173950K .......... .......... .......... .......... .......... 29% 68.4M 10s\n", - "174000K .......... .......... .......... .......... .......... 29% 53.7M 10s\n", - "174050K .......... .......... .......... .......... .......... 29% 46.9M 10s\n", - "174100K .......... .......... .......... .......... .......... 29% 15.4M 10s\n", - "174150K .......... .......... .......... .......... .......... 29% 49.9M 10s\n", - "174200K .......... .......... .......... .......... .......... 29% 49.1M 10s\n", - "174250K .......... .......... .......... .......... .......... 29% 66.8M 10s\n", - "174300K .......... .......... .......... .......... .......... 29% 62.5M 10s\n", - "174350K .......... .......... .......... .......... .......... 29% 68.3M 10s\n", - "174400K .......... .......... .......... .......... .......... 29% 49.6M 10s\n", - "174450K .......... .......... .......... .......... .......... 29% 47.4M 10s\n", - "174500K .......... .......... .......... .......... .......... 29% 56.5M 10s\n", - "174550K .......... .......... .......... .......... .......... 29% 70.4M 10s\n", - "174600K .......... .......... .......... .......... .......... 29% 55.6M 10s\n", - "174650K .......... .......... .......... .......... .......... 29% 60.1M 10s\n", - "174700K .......... .......... .......... .......... .......... 29% 54.2M 10s\n", - "174750K .......... .......... .......... .......... .......... 29% 52.0M 10s\n", - "174800K .......... .......... .......... .......... .......... 29% 56.9M 10s\n", - "174850K .......... .......... .......... .......... .......... 29% 60.3M 10s\n", - "174900K .......... .......... .......... .......... .......... 29% 68.1M 10s\n", - "174950K .......... .......... .......... .......... .......... 29% 61.0M 10s\n", - "175000K .......... .......... .......... .......... .......... 29% 41.2M 10s\n", - "175050K .......... .......... .......... .......... .......... 29% 67.2M 10s\n", - "175100K .......... .......... .......... .......... .......... 29% 69.6M 10s\n", - "175150K .......... .......... .......... .......... .......... 29% 61.2M 10s\n", - "175200K .......... .......... .......... .......... .......... 29% 54.4M 10s\n", - "175250K .......... .......... .......... .......... .......... 29% 44.1M 10s\n", - "175300K .......... .......... .......... .......... .......... 29% 47.3M 10s\n", - "175350K .......... .......... .......... .......... .......... 29% 59.1M 10s\n", - "175400K .......... .......... .......... .......... .......... 29% 53.8M 10s\n", - "175450K .......... .......... .......... .......... .......... 29% 51.7M 10s\n", - "175500K .......... .......... .......... .......... .......... 29% 54.1M 10s\n", - "175550K .......... .......... .......... .......... .......... 29% 53.6M 10s\n", - "175600K .......... .......... .......... .......... .......... 29% 58.7M 10s\n", - "175650K .......... .......... .......... .......... .......... 29% 63.8M 10s\n", - "175700K .......... .......... .......... .......... .......... 29% 53.0M 10s\n", - "175750K .......... .......... .......... .......... .......... 29% 43.8M 10s\n", - "175800K .......... .......... .......... .......... .......... 29% 47.5M 10s\n", - "175850K .......... .......... .......... .......... .......... 29% 63.9M 10s\n", - "175900K .......... .......... .......... .......... .......... 29% 68.5M 10s\n", - "175950K .......... .......... .......... .......... .......... 29% 54.7M 10s\n", - "176000K .......... .......... .......... .......... .......... 29% 49.8M 10s\n", - "176050K .......... .......... .......... .......... .......... 29% 64.8M 10s\n", - "176100K .......... .......... .......... .......... .......... 29% 62.6M 10s\n", - "176150K .......... .......... .......... .......... .......... 29% 68.0M 10s\n", - "176200K .......... .......... .......... .......... .......... 29% 54.7M 10s\n", - "176250K .......... .......... .......... .......... .......... 29% 49.1M 10s\n", - "176300K .......... .......... .......... .......... .......... 29% 55.7M 10s\n", - "176350K .......... .......... .......... .......... .......... 29% 66.4M 10s\n", - "176400K .......... .......... .......... .......... .......... 29% 62.3M 10s\n", - "176450K .......... .......... .......... .......... .......... 29% 66.4M 10s\n", - "176500K .......... .......... .......... .......... .......... 29% 56.2M 10s\n", - "176550K .......... .......... .......... .......... .......... 29% 49.0M 10s\n", - "176600K .......... .......... .......... .......... .......... 29% 45.8M 10s\n", - "176650K .......... .......... .......... .......... .......... 29% 61.2M 10s\n", - "176700K .......... .......... .......... .......... .......... 29% 62.0M 10s\n", - "176750K .......... .......... .......... .......... .......... 29% 48.4M 10s\n", - "176800K .......... .......... .......... .......... .......... 29% 51.8M 10s\n", - "176850K .......... .......... .......... .......... .......... 29% 53.8M 10s\n", - "176900K .......... .......... .......... .......... .......... 29% 67.8M 10s\n", - "176950K .......... .......... .......... .......... .......... 29% 59.3M 10s\n", - "177000K .......... .......... .......... .......... .......... 29% 57.9M 10s\n", - "177050K .......... .......... .......... .......... .......... 29% 67.5M 10s\n", - "177100K .......... .......... .......... .......... .......... 29% 55.8M 10s\n", - "177150K .......... .......... .......... .......... .......... 29% 60.7M 10s\n", - "177200K .......... .......... .......... .......... .......... 29% 58.5M 10s\n", - "177250K .......... .......... .......... .......... .......... 29% 57.3M 10s\n", - "177300K .......... .......... .......... .......... .......... 29% 70.2M 10s\n", - "177350K .......... .......... .......... .......... .......... 29% 69.6M 10s\n", - "177400K .......... .......... .......... .......... .......... 29% 59.4M 10s\n", - "177450K .......... .......... .......... .......... .......... 29% 67.4M 10s\n", - "177500K .......... .......... .......... .......... .......... 29% 70.8M 10s\n", - "177550K .......... .......... .......... .......... .......... 29% 58.4M 10s\n", - "177600K .......... .......... .......... .......... .......... 29% 52.8M 10s\n", - "177650K .......... .......... .......... .......... .......... 29% 65.2M 10s\n", - "177700K .......... .......... .......... .......... .......... 29% 57.0M 10s\n", - "177750K .......... .......... .......... .......... .......... 29% 71.4M 10s\n", - "177800K .......... .......... .......... .......... .......... 29% 59.7M 10s\n", - "177850K .......... .......... .......... .......... .......... 29% 58.4M 10s\n", - "177900K .......... .......... .......... .......... .......... 29% 55.5M 10s\n", - "177950K .......... .......... .......... .......... .......... 29% 38.0M 10s\n", - "178000K .......... .......... .......... .......... .......... 29% 3.85M 10s\n", - "178050K .......... .......... .......... .......... .......... 29% 68.7M 10s\n", - "178100K .......... .......... .......... .......... .......... 29% 65.9M 10s\n", - "178150K .......... .......... .......... .......... .......... 29% 65.4M 10s\n", - "178200K .......... .......... .......... .......... .......... 29% 16.7M 10s\n", - "178250K .......... .......... .......... 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.......... .......... .......... .......... .......... 30% 66.0M 10s\n", - "180100K .......... .......... .......... .......... .......... 30% 65.0M 10s\n", - "180150K .......... .......... .......... .......... .......... 30% 67.2M 10s\n", - "180200K .......... .......... .......... .......... .......... 30% 22.4M 10s\n", - "180250K .......... .......... .......... .......... .......... 30% 46.8M 10s\n", - "180300K .......... .......... .......... .......... .......... 30% 66.5M 10s\n", - "180350K .......... .......... .......... .......... .......... 30% 66.5M 10s\n", - "180400K .......... .......... .......... .......... .......... 30% 24.2M 10s\n", - "180450K .......... .......... .......... .......... .......... 30% 51.4M 10s\n", - "180500K .......... .......... .......... .......... .......... 30% 62.2M 10s\n", - "180550K .......... .......... .......... .......... .......... 30% 65.3M 10s\n", - "180600K .......... .......... .......... .......... .......... 30% 20.2M 10s\n", - "180650K .......... .......... .......... .......... .......... 30% 49.6M 10s\n", - "180700K .......... .......... .......... .......... .......... 30% 68.0M 10s\n", - "180750K .......... .......... .......... .......... .......... 30% 23.7M 10s\n", - "180800K .......... .......... .......... .......... .......... 30% 46.3M 10s\n", - "180850K .......... .......... .......... .......... .......... 30% 52.4M 10s\n", - "180900K .......... .......... .......... .......... .......... 30% 65.5M 10s\n", - "180950K .......... .......... .......... .......... .......... 30% 25.1M 10s\n", - "181000K .......... .......... .......... .......... .......... 30% 42.0M 10s\n", - "181050K .......... .......... .......... .......... .......... 30% 54.2M 10s\n", - "181100K .......... .......... .......... .......... .......... 30% 68.5M 10s\n", - "181150K .......... .......... .......... .......... .......... 30% 31.7M 10s\n", - "181200K .......... .......... .......... .......... .......... 30% 37.3M 10s\n", - "181250K .......... .......... .......... .......... .......... 30% 51.9M 10s\n", - "181300K .......... .......... .......... .......... .......... 30% 68.2M 10s\n", - "181350K .......... .......... .......... .......... .......... 30% 30.8M 10s\n", - "181400K .......... .......... .......... .......... .......... 30% 36.1M 10s\n", - "181450K .......... .......... .......... .......... .......... 30% 48.4M 10s\n", - "181500K .......... .......... .......... .......... .......... 30% 64.6M 10s\n", - "181550K .......... .......... .......... .......... .......... 30% 30.7M 10s\n", - "181600K .......... .......... .......... .......... .......... 30% 49.0M 10s\n", - "181650K .......... .......... .......... .......... .......... 30% 45.4M 10s\n", - "181700K .......... .......... .......... .......... .......... 30% 61.7M 10s\n", - "181750K .......... .......... .......... .......... .......... 30% 26.7M 10s\n", - "181800K .......... .......... .......... .......... .......... 30% 48.5M 10s\n", - "181850K .......... .......... .......... .......... .......... 30% 44.9M 10s\n", - "181900K .......... .......... .......... .......... .......... 30% 65.4M 10s\n", - "181950K .......... .......... .......... .......... .......... 30% 30.1M 10s\n", - "182000K .......... .......... .......... .......... .......... 30% 46.7M 10s\n", - "182050K .......... .......... .......... .......... .......... 30% 51.7M 10s\n", - "182100K .......... .......... .......... .......... .......... 30% 61.6M 10s\n", - "182150K .......... .......... .......... .......... .......... 30% 26.7M 10s\n", - "182200K .......... .......... .......... .......... .......... 30% 38.5M 10s\n", - "182250K .......... .......... .......... .......... .......... 30% 8.10M 10s\n", - "182300K .......... .......... .......... .......... .......... 30% 62.2M 10s\n", - "182350K .......... .......... .......... .......... .......... 30% 67.5M 10s\n", - "182400K .......... .......... .......... .......... .......... 30% 60.0M 10s\n", - "182450K .......... .......... .......... .......... .......... 30% 68.3M 10s\n", - "182500K .......... .......... .......... .......... .......... 30% 28.5M 10s\n", - "182550K .......... .......... .......... .......... .......... 30% 49.9M 10s\n", - "182600K .......... .......... .......... .......... .......... 30% 50.4M 10s\n", - "182650K .......... .......... .......... .......... .......... 30% 68.6M 10s\n", - "182700K .......... .......... .......... .......... .......... 30% 27.3M 10s\n", - "182750K .......... .......... .......... .......... .......... 30% 47.1M 10s\n", - "182800K .......... .......... .......... .......... .......... 30% 50.4M 10s\n", - "182850K .......... .......... .......... .......... .......... 30% 68.7M 10s\n", - "182900K .......... .......... .......... .......... .......... 30% 24.6M 10s\n", - "182950K .......... .......... .......... .......... .......... 30% 46.9M 10s\n", - "183000K .......... .......... .......... .......... .......... 30% 49.3M 10s\n", - "183050K .......... .......... .......... .......... .......... 30% 70.9M 10s\n", - "183100K .......... .......... .......... .......... .......... 30% 5.52M 10s\n", - "183150K .......... .......... .......... .......... .......... 30% 55.0M 10s\n", - "183200K .......... .......... .......... .......... .......... 30% 60.4M 10s\n", - "183250K .......... .......... .......... .......... .......... 30% 68.1M 10s\n", - "183300K .......... .......... .......... .......... .......... 30% 23.7M 10s\n", - "183350K .......... .......... .......... .......... .......... 30% 48.2M 10s\n", - "183400K .......... .......... .......... .......... .......... 30% 51.9M 10s\n", - "183450K .......... .......... .......... .......... .......... 30% 65.7M 10s\n", - "183500K .......... .......... .......... .......... .......... 30% 28.2M 10s\n", - "183550K .......... .......... .......... .......... .......... 30% 49.0M 10s\n", - "183600K .......... .......... .......... .......... .......... 30% 47.4M 10s\n", - "183650K .......... .......... .......... .......... .......... 30% 70.4M 10s\n", - "183700K .......... .......... .......... .......... .......... 30% 32.1M 10s\n", - "183750K .......... .......... .......... .......... .......... 30% 42.6M 10s\n", - "183800K .......... .......... .......... .......... .......... 30% 45.1M 10s\n", - "183850K .......... .......... .......... .......... .......... 30% 64.9M 10s\n", - "183900K .......... .......... .......... .......... .......... 30% 31.5M 10s\n", - "183950K .......... .......... .......... .......... .......... 30% 52.8M 10s\n", - "184000K .......... .......... .......... .......... .......... 30% 51.7M 10s\n", - "184050K .......... .......... .......... .......... .......... 30% 58.9M 10s\n", - "184100K .......... .......... .......... .......... .......... 30% 54.7M 10s\n", - "184150K .......... .......... .......... .......... .......... 30% 29.7M 10s\n", - "184200K .......... .......... .......... .......... .......... 30% 30.2M 10s\n", - "184250K .......... .......... .......... .......... .......... 30% 59.3M 10s\n", - "184300K .......... .......... .......... .......... .......... 30% 67.7M 10s\n", - "184350K .......... .......... .......... .......... .......... 31% 41.8M 10s\n", - "184400K .......... .......... .......... .......... .......... 31% 56.3M 10s\n", - "184450K .......... .......... .......... .......... .......... 31% 53.1M 10s\n", - "184500K .......... .......... .......... .......... .......... 31% 67.4M 10s\n", - "184550K .......... .......... .......... .......... .......... 31% 25.7M 10s\n", - "184600K .......... .......... .......... .......... .......... 31% 46.5M 10s\n", - "184650K .......... .......... .......... .......... .......... 31% 51.9M 10s\n", - "184700K .......... .......... .......... .......... .......... 31% 59.4M 10s\n", - "184750K .......... .......... .......... .......... .......... 31% 29.8M 10s\n", - "184800K .......... .......... .......... .......... .......... 31% 4.77M 10s\n", - "184850K .......... .......... .......... .......... .......... 31% 67.5M 10s\n", - "184900K .......... .......... .......... .......... .......... 31% 71.9M 10s\n", - "184950K .......... .......... .......... .......... .......... 31% 62.5M 10s\n", - "185000K .......... .......... .......... .......... .......... 31% 58.5M 10s\n", - "185050K .......... .......... .......... .......... .......... 31% 27.5M 10s\n", - "185100K .......... .......... .......... .......... .......... 31% 47.7M 10s\n", - "185150K .......... .......... .......... .......... .......... 31% 58.6M 10s\n", - "185200K .......... .......... .......... .......... .......... 31% 63.4M 10s\n", - "185250K .......... .......... .......... .......... .......... 31% 32.1M 10s\n", - "185300K .......... .......... .......... .......... .......... 31% 49.7M 10s\n", - "185350K .......... .......... .......... .......... .......... 31% 57.6M 10s\n", - "185400K .......... .......... .......... .......... .......... 31% 45.1M 10s\n", - "185450K .......... .......... .......... .......... .......... 31% 33.2M 10s\n", - "185500K .......... .......... .......... .......... .......... 31% 48.6M 10s\n", - "185550K .......... .......... .......... .......... .......... 31% 38.6M 10s\n", - "185600K .......... .......... .......... .......... .......... 31% 52.3M 10s\n", - "185650K .......... .......... .......... .......... .......... 31% 53.8M 10s\n", - "185700K .......... .......... .......... .......... .......... 31% 32.2M 10s\n", - "185750K .......... .......... .......... .......... .......... 31% 54.8M 10s\n", - "185800K .......... .......... .......... .......... .......... 31% 45.5M 10s\n", - "185850K .......... .......... .......... .......... .......... 31% 72.4M 10s\n", - "185900K .......... .......... .......... .......... .......... 31% 32.0M 10s\n", - "185950K .......... .......... .......... .......... .......... 31% 44.1M 10s\n", - "186000K .......... .......... .......... .......... .......... 31% 41.1M 10s\n", - "186050K .......... .......... .......... .......... .......... 31% 61.8M 10s\n", - "186100K .......... .......... .......... .......... .......... 31% 70.6M 10s\n", - "186150K .......... .......... .......... .......... .......... 31% 38.2M 10s\n", - "186200K .......... .......... .......... .......... .......... 31% 38.3M 10s\n", - "186250K .......... .......... .......... .......... .......... 31% 57.4M 10s\n", - "186300K .......... .......... .......... .......... .......... 31% 52.0M 10s\n", - "186350K .......... .......... .......... .......... .......... 31% 35.2M 10s\n", - "186400K .......... .......... .......... .......... .......... 31% 38.9M 10s\n", - "186450K .......... .......... .......... .......... .......... 31% 62.7M 10s\n", - "186500K .......... .......... .......... .......... .......... 31% 71.5M 10s\n", - "186550K .......... .......... .......... .......... .......... 31% 39.0M 10s\n", - "186600K .......... .......... .......... .......... .......... 31% 28.4M 10s\n", - "186650K .......... .......... .......... .......... .......... 31% 37.8M 10s\n", - "186700K .......... .......... .......... .......... .......... 31% 70.9M 10s\n", - "186750K .......... .......... .......... .......... .......... 31% 60.1M 10s\n", - "186800K .......... .......... .......... .......... .......... 31% 51.5M 10s\n", - "186850K .......... .......... .......... .......... .......... 31% 57.6M 10s\n", - "186900K .......... .......... .......... .......... .......... 31% 57.9M 10s\n", - "186950K .......... .......... .......... .......... .......... 31% 71.7M 10s\n", - "187000K .......... .......... .......... .......... .......... 31% 31.1M 10s\n", - "187050K .......... .......... .......... .......... .......... 31% 62.4M 10s\n", - "187100K .......... .......... .......... .......... .......... 31% 65.9M 10s\n", - "187150K .......... .......... .......... .......... .......... 31% 60.5M 10s\n", - "187200K .......... .......... .......... .......... .......... 31% 29.2M 10s\n", - "187250K .......... .......... .......... .......... .......... 31% 55.2M 10s\n", - "187300K .......... .......... .......... .......... .......... 31% 45.9M 10s\n", - "187350K .......... .......... .......... .......... .......... 31% 53.2M 10s\n", - "187400K .......... .......... .......... .......... .......... 31% 56.7M 10s\n", - "187450K .......... .......... .......... .......... .......... 31% 37.7M 10s\n", - "187500K .......... .......... .......... .......... .......... 31% 56.6M 10s\n", - "187550K .......... .......... .......... .......... .......... 31% 51.5M 10s\n", - "187600K .......... .......... .......... .......... .......... 31% 58.6M 10s\n", - "187650K .......... .......... .......... .......... .......... 31% 32.8M 10s\n", - "187700K .......... .......... .......... .......... .......... 31% 59.7M 10s\n", - "187750K .......... .......... .......... .......... .......... 31% 47.8M 10s\n", - "187800K .......... .......... .......... .......... .......... 31% 47.1M 10s\n", - "187850K .......... .......... .......... .......... .......... 31% 66.9M 10s\n", - "187900K .......... .......... .......... .......... .......... 31% 27.1M 10s\n", - "187950K .......... .......... .......... .......... .......... 31% 44.9M 10s\n", - "188000K .......... .......... .......... .......... .......... 31% 48.2M 10s\n", - "188050K .......... .......... .......... .......... .......... 31% 72.9M 10s\n", - "188100K .......... .......... .......... .......... .......... 31% 62.6M 10s\n", - "188150K .......... .......... .......... .......... .......... 31% 33.7M 10s\n", - "188200K .......... .......... .......... .......... .......... 31% 40.8M 10s\n", - "188250K .......... .......... .......... .......... .......... 31% 60.7M 10s\n", - "188300K .......... .......... .......... .......... .......... 31% 77.5M 10s\n", - "188350K .......... .......... .......... .......... .......... 31% 39.3M 10s\n", - "188400K .......... .......... .......... .......... .......... 31% 43.9M 10s\n", - "188450K .......... .......... .......... .......... .......... 31% 53.6M 10s\n", - "188500K .......... .......... .......... .......... .......... 31% 65.7M 10s\n", - "188550K .......... .......... .......... .......... .......... 31% 67.8M 10s\n", - "188600K .......... .......... .......... .......... .......... 31% 27.3M 10s\n", - "188650K .......... .......... .......... .......... .......... 31% 43.3M 10s\n", - "188700K .......... .......... .......... .......... .......... 31% 2.66M 10s\n", - "188750K .......... .......... .......... .......... .......... 31% 63.3M 10s\n", - "188800K .......... .......... .......... .......... .......... 31% 57.3M 10s\n", - "188850K .......... .......... .......... .......... .......... 31% 63.9M 10s\n", - "188900K .......... .......... .......... .......... .......... 31% 65.6M 10s\n", - "188950K .......... .......... .......... .......... .......... 31% 60.2M 10s\n", - "189000K .......... .......... .......... .......... .......... 31% 45.7M 10s\n", - "189050K .......... .......... .......... .......... .......... 31% 52.2M 10s\n", - "189100K .......... .......... .......... .......... .......... 31% 65.9M 10s\n", - "189150K .......... .......... .......... .......... .......... 31% 65.7M 10s\n", - "189200K .......... .......... .......... .......... .......... 31% 61.8M 10s\n", - "189250K .......... .......... .......... .......... .......... 31% 56.6M 10s\n", - "189300K .......... .......... .......... .......... .......... 31% 8.68M 10s\n", - "189350K .......... .......... .......... .......... .......... 31% 66.9M 10s\n", - "189400K .......... .......... .......... .......... .......... 31% 62.8M 10s\n", - "189450K .......... .......... .......... .......... .......... 31% 70.4M 10s\n", - "189500K .......... .......... .......... .......... .......... 31% 69.2M 10s\n", - "189550K .......... .......... .......... .......... .......... 31% 24.0M 10s\n", - "189600K .......... .......... .......... .......... .......... 31% 44.4M 10s\n", - "189650K .......... .......... .......... .......... .......... 31% 69.6M 10s\n", - "189700K .......... .......... .......... .......... .......... 31% 65.8M 10s\n", - "189750K .......... .......... .......... .......... .......... 31% 33.4M 10s\n", - "189800K .......... .......... .......... .......... .......... 31% 36.9M 10s\n", - "189850K .......... .......... .......... .......... .......... 31% 61.0M 10s\n", - "189900K .......... .......... .......... .......... .......... 31% 65.2M 10s\n", - "189950K .......... .......... .......... .......... .......... 31% 71.8M 10s\n", - "190000K .......... .......... .......... .......... .......... 31% 29.3M 10s\n", - "190050K .......... .......... .......... .......... .......... 31% 46.8M 10s\n", - "190100K .......... .......... .......... .......... .......... 31% 61.5M 10s\n", - "190150K .......... .......... .......... .......... .......... 31% 65.5M 10s\n", - "190200K .......... .......... .......... .......... .......... 31% 38.3M 10s\n", - "190250K .......... .......... .......... .......... .......... 31% 46.8M 10s\n", - "190300K .......... .......... .......... .......... .......... 32% 53.8M 10s\n", - "190350K .......... .......... .......... .......... .......... 32% 63.8M 10s\n", - "190400K .......... .......... .......... .......... .......... 32% 60.1M 10s\n", - "190450K .......... .......... .......... .......... .......... 32% 53.2M 10s\n", - "190500K .......... .......... .......... .......... .......... 32% 44.0M 10s\n", - "190550K .......... .......... .......... .......... .......... 32% 55.8M 10s\n", - "190600K .......... .......... .......... .......... .......... 32% 51.5M 10s\n", - "190650K .......... .......... .......... .......... .......... 32% 68.1M 10s\n", - "190700K .......... .......... .......... .......... .......... 32% 38.6M 10s\n", - "190750K .......... .......... .......... .......... .......... 32% 46.3M 10s\n", - "190800K .......... .......... .......... .......... .......... 32% 46.0M 10s\n", - "190850K .......... .......... .......... .......... .......... 32% 67.4M 10s\n", - "190900K .......... .......... .......... .......... .......... 32% 76.3M 10s\n", - "190950K .......... .......... .......... .......... .......... 32% 53.7M 10s\n", - "191000K .......... .......... .......... .......... .......... 32% 37.8M 10s\n", - "191050K .......... .......... .......... .......... .......... 32% 58.9M 10s\n", - "191100K .......... .......... .......... .......... .......... 32% 74.0M 10s\n", - "191150K .......... .......... .......... .......... .......... 32% 33.7M 10s\n", - "191200K .......... .......... .......... .......... .......... 32% 10.5M 10s\n", - "191250K .......... .......... .......... .......... .......... 32% 48.3M 10s\n", - "191300K .......... .......... .......... .......... .......... 32% 70.7M 10s\n", - "191350K .......... .......... .......... .......... .......... 32% 76.1M 10s\n", - "191400K .......... .......... .......... .......... .......... 32% 57.2M 10s\n", - "191450K .......... .......... .......... .......... .......... 32% 75.1M 10s\n", - "191500K .......... .......... .......... .......... .......... 32% 37.5M 10s\n", - "191550K .......... .......... .......... .......... .......... 32% 51.1M 10s\n", - "191600K .......... .......... .......... .......... .......... 32% 45.5M 10s\n", - "191650K .......... .......... .......... .......... .......... 32% 69.5M 10s\n", - "191700K .......... .......... .......... .......... .......... 32% 66.9M 10s\n", - "191750K .......... .......... .......... .......... .......... 32% 45.1M 10s\n", - "191800K .......... .......... .......... .......... .......... 32% 42.3M 10s\n", - "191850K .......... .......... .......... .......... .......... 32% 62.8M 10s\n", - "191900K .......... .......... .......... .......... .......... 32% 65.9M 10s\n", - "191950K .......... .......... .......... .......... .......... 32% 65.9M 10s\n", - "192000K .......... .......... .......... .......... .......... 32% 39.3M 10s\n", - "192050K .......... .......... .......... .......... .......... 32% 51.3M 10s\n", - "192100K .......... .......... .......... .......... .......... 32% 57.0M 10s\n", - "192150K .......... .......... .......... .......... .......... 32% 74.0M 10s\n", - "192200K .......... .......... .......... .......... .......... 32% 34.1M 10s\n", - "192250K .......... .......... .......... .......... .......... 32% 51.3M 10s\n", - "192300K .......... .......... .......... .......... .......... 32% 45.4M 10s\n", - "192350K .......... .......... .......... .......... .......... 32% 56.1M 10s\n", - "192400K .......... .......... .......... .......... .......... 32% 63.8M 10s\n", - "192450K .......... .......... .......... .......... .......... 32% 74.8M 10s\n", - "192500K .......... .......... .......... .......... .......... 32% 42.4M 10s\n", - "192550K .......... .......... .......... .......... .......... 32% 47.9M 10s\n", - "192600K .......... .......... .......... .......... .......... 32% 46.0M 10s\n", - "192650K .......... .......... .......... .......... .......... 32% 64.5M 10s\n", - "192700K .......... .......... .......... .......... .......... 32% 53.1M 10s\n", - "192750K .......... .......... .......... .......... .......... 32% 53.6M 10s\n", - "192800K .......... .......... .......... .......... .......... 32% 41.4M 10s\n", - "192850K .......... .......... .......... .......... .......... 32% 58.0M 10s\n", - "192900K .......... .......... .......... .......... .......... 32% 69.2M 10s\n", - "192950K .......... .......... .......... .......... .......... 32% 56.8M 10s\n", - "193000K .......... .......... .......... .......... .......... 32% 51.8M 10s\n", - "193050K .......... .......... .......... .......... .......... 32% 45.3M 10s\n", - "193100K .......... .......... .......... .......... .......... 32% 52.5M 10s\n", - "193150K .......... .......... .......... .......... .......... 32% 64.9M 10s\n", - "193200K .......... .......... .......... .......... .......... 32% 52.9M 10s\n", - "193250K .......... .......... .......... .......... .......... 32% 56.0M 10s\n", - "193300K .......... .......... .......... .......... .......... 32% 56.7M 10s\n", - "193350K .......... .......... .......... .......... .......... 32% 53.3M 10s\n", - "193400K .......... .......... .......... .......... .......... 32% 52.4M 10s\n", - "193450K .......... .......... .......... .......... .......... 32% 71.0M 10s\n", - "193500K .......... .......... .......... .......... .......... 32% 48.6M 10s\n", - "193550K .......... .......... .......... .......... .......... 32% 5.35M 10s\n", - "193600K .......... .......... .......... .......... .......... 32% 37.9M 10s\n", - "193650K .......... .......... .......... .......... .......... 32% 40.8M 10s\n", - "193700K .......... .......... .......... .......... .......... 32% 52.1M 10s\n", - "193750K .......... .......... .......... .......... .......... 32% 60.3M 10s\n", - "193800K .......... .......... .......... .......... .......... 32% 51.2M 10s\n", - "193850K .......... .......... .......... .......... .......... 32% 57.2M 10s\n", - "193900K .......... .......... .......... .......... .......... 32% 15.4M 10s\n", - "193950K .......... .......... .......... .......... .......... 32% 69.5M 10s\n", - "194000K .......... .......... .......... .......... .......... 32% 62.0M 10s\n", - "194050K .......... .......... .......... .......... .......... 32% 71.0M 10s\n", - "194100K .......... .......... .......... .......... .......... 32% 17.3M 10s\n", - "194150K .......... .......... .......... .......... .......... 32% 57.5M 10s\n", - "194200K .......... .......... .......... .......... .......... 32% 61.5M 10s\n", - "194250K .......... .......... .......... .......... .......... 32% 19.9M 10s\n", - "194300K .......... .......... .......... .......... .......... 32% 46.3M 10s\n", - "194350K .......... .......... .......... .......... .......... 32% 69.4M 10s\n", - "194400K .......... .......... .......... .......... .......... 32% 18.3M 10s\n", - "194450K .......... .......... .......... .......... .......... 32% 55.6M 10s\n", - "194500K .......... .......... .......... .......... .......... 32% 60.7M 10s\n", - "194550K .......... .......... .......... .......... .......... 32% 72.4M 10s\n", - "194600K .......... .......... .......... .......... .......... 32% 18.8M 10s\n", - "194650K .......... .......... .......... .......... .......... 32% 55.0M 10s\n", - "194700K .......... .......... .......... .......... .......... 32% 76.2M 10s\n", - "194750K .......... .......... .......... .......... .......... 32% 4.01M 10s\n", - "194800K .......... .......... .......... .......... .......... 32% 57.6M 10s\n", - "194850K .......... .......... .......... .......... .......... 32% 74.7M 10s\n", - "194900K .......... .......... .......... .......... .......... 32% 68.0M 10s\n", - "194950K .......... .......... .......... .......... .......... 32% 16.6M 10s\n", - "195000K .......... .......... .......... .......... .......... 32% 37.5M 10s\n", - "195050K .......... .......... .......... .......... .......... 32% 62.9M 10s\n", - "195100K .......... .......... .......... .......... .......... 32% 69.2M 10s\n", - "195150K .......... .......... .......... .......... .......... 32% 26.7M 10s\n", - "195200K .......... .......... .......... .......... .......... 32% 38.2M 10s\n", - "195250K .......... .......... .......... .......... .......... 32% 70.3M 10s\n", - "195300K .......... .......... .......... .......... .......... 32% 22.8M 10s\n", - "195350K .......... .......... .......... .......... .......... 32% 36.9M 10s\n", - "195400K .......... .......... .......... .......... .......... 32% 53.5M 10s\n", - "195450K .......... .......... .......... .......... .......... 32% 72.9M 10s\n", - "195500K .......... .......... .......... .......... .......... 32% 21.3M 10s\n", - "195550K .......... .......... .......... .......... .......... 32% 39.6M 10s\n", - "195600K .......... .......... .......... .......... .......... 32% 66.5M 10s\n", - "195650K .......... .......... .......... .......... .......... 32% 22.9M 10s\n", - "195700K .......... .......... .......... .......... .......... 32% 33.2M 10s\n", - "195750K .......... .......... .......... .......... .......... 32% 37.9M 10s\n", - "195800K .......... .......... .......... .......... .......... 32% 26.2M 10s\n", - "195850K .......... .......... .......... .......... .......... 32% 20.7M 10s\n", - "195900K .......... .......... .......... .......... .......... 32% 72.2M 10s\n", - "195950K .......... .......... .......... .......... .......... 32% 76.8M 10s\n", - "196000K .......... .......... .......... .......... .......... 32% 41.0M 10s\n", - "196050K .......... .......... .......... .......... .......... 32% 45.4M 10s\n", - "196100K .......... .......... .......... .......... .......... 32% 46.1M 10s\n", - "196150K .......... .......... .......... .......... .......... 32% 62.0M 10s\n", - "196200K .......... .......... .......... .......... .......... 32% 19.8M 10s\n", - "196250K .......... .......... .......... .......... .......... 33% 57.6M 10s\n", - "196300K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", - "196350K .......... .......... .......... .......... .......... 33% 30.0M 10s\n", - "196400K .......... .......... .......... .......... .......... 33% 22.9M 10s\n", - "196450K .......... .......... .......... .......... .......... 33% 45.5M 10s\n", - "196500K .......... .......... .......... .......... .......... 33% 60.7M 10s\n", - "196550K .......... .......... .......... .......... .......... 33% 40.2M 10s\n", - "196600K .......... .......... .......... .......... .......... 33% 20.0M 10s\n", - "196650K .......... .......... .......... .......... .......... 33% 22.0M 10s\n", - "196700K .......... .......... .......... .......... .......... 33% 62.6M 10s\n", - "196750K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", - "196800K .......... .......... .......... .......... .......... 33% 20.9M 10s\n", - "196850K .......... .......... .......... .......... .......... 33% 46.7M 10s\n", - "196900K .......... .......... .......... .......... .......... 33% 48.4M 10s\n", - "196950K .......... .......... .......... .......... .......... 33% 53.4M 10s\n", - "197000K .......... .......... .......... .......... .......... 33% 21.5M 10s\n", - "197050K .......... .......... .......... .......... .......... 33% 44.8M 10s\n", - "197100K .......... .......... .......... .......... .......... 33% 57.7M 10s\n", - "197150K .......... .......... .......... .......... .......... 33% 24.3M 10s\n", - "197200K .......... .......... .......... .......... .......... 33% 37.0M 10s\n", - "197250K .......... .......... .......... .......... .......... 33% 57.3M 10s\n", - "197300K .......... .......... .......... .......... .......... 33% 58.8M 10s\n", - "197350K .......... .......... .......... .......... .......... 33% 24.2M 10s\n", - "197400K .......... .......... .......... .......... .......... 33% 36.9M 10s\n", - "197450K .......... .......... .......... .......... .......... 33% 57.0M 10s\n", - "197500K .......... .......... .......... .......... .......... 33% 22.1M 10s\n", - "197550K .......... .......... .......... .......... .......... 33% 49.4M 10s\n", - "197600K .......... .......... .......... .......... .......... 33% 48.0M 10s\n", - "197650K .......... .......... .......... .......... .......... 33% 60.8M 10s\n", - "197700K .......... .......... .......... .......... .......... 33% 19.3M 10s\n", - "197750K .......... .......... .......... .......... .......... 33% 47.0M 10s\n", - "197800K .......... .......... .......... .......... .......... 33% 49.6M 10s\n", - "197850K .......... .......... .......... .......... .......... 33% 27.9M 10s\n", - "197900K .......... .......... .......... .......... .......... 33% 36.1M 10s\n", - "197950K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", - "198000K .......... .......... .......... .......... .......... 33% 1.41M 10s\n", - "198050K .......... .......... .......... .......... .......... 33% 55.6M 10s\n", - "198100K .......... .......... .......... .......... .......... 33% 67.8M 10s\n", - "198150K .......... .......... .......... .......... .......... 33% 18.4M 10s\n", - "198200K .......... .......... .......... .......... .......... 33% 43.7M 10s\n", - "198250K .......... .......... .......... .......... .......... 33% 59.8M 10s\n", - "198300K .......... .......... .......... .......... .......... 33% 67.1M 10s\n", - "198350K .......... .......... .......... .......... .......... 33% 17.3M 10s\n", - "198400K .......... .......... .......... .......... .......... 33% 30.6M 10s\n", - "198450K .......... .......... .......... .......... .......... 33% 36.2M 10s\n", - "198500K .......... .......... .......... .......... .......... 33% 34.7M 10s\n", - "198550K .......... .......... .......... .......... .......... 33% 31.3M 10s\n", - "198600K .......... .......... .......... .......... .......... 33% 34.0M 10s\n", - "198650K .......... .......... .......... .......... .......... 33% 30.7M 10s\n", - "198700K .......... .......... .......... .......... .......... 33% 33.3M 10s\n", - "198750K .......... .......... .......... .......... .......... 33% 57.2M 10s\n", - "198800K .......... .......... .......... .......... .......... 33% 54.3M 10s\n", - "198850K .......... .......... .......... .......... .......... 33% 47.5M 10s\n", - "198900K .......... .......... .......... .......... .......... 33% 73.2M 10s\n", - "198950K .......... .......... .......... .......... .......... 33% 66.6M 10s\n", - "199000K .......... .......... .......... .......... .......... 33% 57.6M 10s\n", - "199050K .......... .......... .......... .......... .......... 33% 19.5M 10s\n", - "199100K .......... .......... .......... .......... .......... 33% 42.2M 10s\n", - "199150K .......... .......... .......... .......... .......... 33% 51.0M 10s\n", - "199200K .......... .......... .......... .......... .......... 33% 62.5M 10s\n", - "199250K .......... .......... .......... .......... .......... 33% 6.49M 10s\n", - "199300K .......... .......... .......... .......... .......... 33% 56.6M 10s\n", - "199350K .......... .......... .......... .......... .......... 33% 67.2M 10s\n", - "199400K .......... .......... .......... .......... .......... 33% 17.6M 10s\n", - "199450K .......... .......... .......... .......... .......... 33% 43.5M 10s\n", - "199500K .......... .......... .......... .......... .......... 33% 54.9M 10s\n", - "199550K .......... .......... .......... .......... .......... 33% 60.8M 10s\n", - "199600K .......... .......... .......... .......... .......... 33% 28.0M 10s\n", - "199650K .......... .......... .......... .......... .......... 33% 40.8M 10s\n", - "199700K .......... .......... .......... .......... .......... 33% 42.5M 10s\n", - "199750K .......... .......... .......... .......... .......... 33% 51.4M 10s\n", - "199800K .......... .......... .......... .......... .......... 33% 29.8M 10s\n", - "199850K .......... .......... .......... .......... .......... 33% 46.6M 10s\n", - "199900K .......... .......... .......... .......... .......... 33% 45.8M 10s\n", - "199950K .......... .......... .......... .......... .......... 33% 22.5M 10s\n", - "200000K .......... .......... .......... .......... .......... 33% 35.6M 10s\n", - "200050K .......... .......... .......... .......... .......... 33% 54.8M 10s\n", - "200100K .......... .......... .......... .......... .......... 33% 55.9M 10s\n", - "200150K .......... .......... .......... .......... .......... 33% 33.6M 10s\n", - "200200K .......... .......... .......... .......... .......... 33% 36.7M 10s\n", - "200250K .......... .......... .......... .......... .......... 33% 67.3M 10s\n", - "200300K .......... .......... .......... .......... .......... 33% 69.2M 10s\n", - "200350K .......... .......... .......... .......... .......... 33% 19.3M 10s\n", - "200400K .......... .......... .......... .......... .......... 33% 46.0M 10s\n", - "200450K .......... .......... .......... .......... .......... 33% 58.0M 10s\n", - "200500K .......... .......... .......... .......... .......... 33% 65.7M 10s\n", - "200550K .......... .......... .......... .......... .......... 33% 25.3M 10s\n", - "200600K .......... .......... .......... .......... .......... 33% 39.8M 10s\n", - "200650K .......... .......... .......... .......... .......... 33% 66.9M 10s\n", - "200700K .......... .......... .......... .......... .......... 33% 8.67M 10s\n", - "200750K .......... .......... .......... .......... .......... 33% 24.8M 10s\n", - "200800K .......... .......... .......... .......... .......... 33% 49.0M 10s\n", - "200850K .......... .......... .......... .......... .......... 33% 70.5M 10s\n", - "200900K .......... .......... .......... .......... .......... 33% 67.7M 10s\n", - "200950K .......... .......... .......... .......... .......... 33% 40.2M 10s\n", - "201000K .......... .......... .......... .......... .......... 33% 35.4M 10s\n", - "201050K .......... .......... .......... .......... .......... 33% 48.4M 10s\n", - "201100K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", - "201150K .......... .......... .......... .......... .......... 33% 38.8M 10s\n", - "201200K .......... .......... .......... .......... .......... 33% 30.2M 10s\n", - "201250K .......... .......... .......... .......... .......... 33% 45.3M 10s\n", - "201300K .......... .......... .......... .......... .......... 33% 47.5M 10s\n", - "201350K .......... .......... .......... .......... .......... 33% 46.3M 10s\n", - "201400K .......... .......... .......... .......... .......... 33% 36.7M 10s\n", - "201450K .......... .......... .......... .......... .......... 33% 62.8M 10s\n", - "201500K .......... .......... .......... .......... .......... 33% 68.0M 10s\n", - "201550K .......... .......... .......... .......... .......... 33% 61.5M 10s\n", - "201600K .......... .......... .......... .......... .......... 33% 1.34M 10s\n", - "201650K .......... .......... .......... .......... .......... 33% 57.3M 10s\n", - "201700K .......... .......... .......... .......... .......... 33% 67.8M 10s\n", - "201750K .......... .......... .......... .......... .......... 33% 67.2M 10s\n", - "201800K .......... .......... .......... .......... .......... 33% 22.2M 10s\n", - "201850K .......... .......... .......... .......... .......... 33% 35.1M 10s\n", - "201900K .......... .......... .......... .......... .......... 33% 70.9M 10s\n", - "201950K .......... .......... .......... .......... .......... 33% 79.5M 10s\n", - "202000K .......... .......... .......... .......... .......... 33% 25.4M 10s\n", - "202050K .......... .......... .......... .......... .......... 33% 38.6M 10s\n", - "202100K .......... .......... .......... .......... .......... 33% 58.6M 10s\n", - "202150K .......... .......... .......... .......... .......... 33% 71.8M 10s\n", - "202200K .......... .......... .......... .......... .......... 34% 24.1M 10s\n", - "202250K .......... .......... .......... .......... .......... 34% 30.2M 10s\n", - "202300K .......... .......... .......... .......... .......... 34% 76.8M 10s\n", - "202350K .......... .......... .......... .......... .......... 34% 75.1M 10s\n", - "202400K .......... .......... .......... .......... .......... 34% 30.7M 10s\n", - "202450K .......... .......... .......... .......... .......... 34% 27.4M 10s\n", - "202500K .......... .......... .......... .......... .......... 34% 73.7M 10s\n", - "202550K .......... .......... .......... .......... .......... 34% 71.7M 10s\n", - "202600K .......... .......... .......... .......... .......... 34% 37.0M 10s\n", - "202650K .......... .......... .......... .......... .......... 34% 36.5M 10s\n", - "202700K .......... .......... .......... .......... .......... 34% 45.0M 10s\n", - "202750K .......... .......... .......... .......... .......... 34% 67.7M 10s\n", - "202800K .......... .......... .......... .......... .......... 34% 48.6M 10s\n", - "202850K .......... .......... .......... .......... .......... 34% 42.9M 10s\n", - "202900K .......... .......... .......... .......... .......... 34% 47.0M 10s\n", - "202950K .......... .......... .......... .......... .......... 34% 49.1M 10s\n", - "203000K .......... .......... .......... .......... .......... 34% 43.2M 10s\n", - "203050K .......... .......... .......... .......... .......... 34% 42.6M 10s\n", - "203100K .......... .......... .......... .......... .......... 34% 38.3M 10s\n", - "203150K .......... .......... .......... .......... .......... 34% 49.7M 10s\n", - "203200K .......... .......... .......... .......... .......... 34% 48.9M 10s\n", - "203250K .......... .......... .......... .......... .......... 34% 33.5M 10s\n", - "203300K .......... .......... .......... .......... .......... 34% 49.6M 10s\n", - "203350K .......... .......... .......... .......... .......... 34% 43.0M 10s\n", - "203400K .......... .......... .......... .......... .......... 34% 34.7M 10s\n", - "203450K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", - "203500K .......... .......... .......... .......... .......... 34% 51.2M 10s\n", - "203550K .......... .......... .......... .......... .......... 34% 46.1M 10s\n", - "203600K .......... .......... .......... .......... .......... 34% 41.9M 10s\n", - "203650K .......... .......... .......... .......... .......... 34% 43.8M 10s\n", - "203700K .......... .......... .......... .......... .......... 34% 48.5M 10s\n", - "203750K .......... .......... .......... .......... .......... 34% 60.1M 10s\n", - "203800K .......... .......... .......... .......... .......... 34% 35.4M 10s\n", - "203850K .......... .......... .......... .......... .......... 34% 48.3M 10s\n", - "203900K .......... .......... .......... .......... .......... 34% 43.5M 10s\n", - "203950K .......... .......... .......... .......... .......... 34% 65.2M 10s\n", - "204000K .......... .......... .......... .......... .......... 34% 44.4M 10s\n", - "204050K .......... .......... .......... .......... .......... 34% 49.5M 10s\n", - "204100K .......... .......... .......... .......... .......... 34% 48.9M 10s\n", - "204150K .......... .......... .......... .......... .......... 34% 54.7M 10s\n", - "204200K .......... .......... .......... .......... .......... 34% 30.7M 10s\n", - "204250K .......... .......... .......... .......... .......... 34% 44.1M 10s\n", - "204300K .......... .......... .......... .......... .......... 34% 38.9M 10s\n", - "204350K .......... .......... .......... .......... .......... 34% 61.2M 10s\n", - "204400K .......... .......... .......... .......... .......... 34% 51.4M 10s\n", - "204450K .......... .......... .......... .......... .......... 34% 40.0M 10s\n", - "204500K .......... .......... .......... .......... .......... 34% 38.5M 10s\n", - "204550K .......... .......... .......... .......... .......... 34% 64.1M 10s\n", - "204600K .......... .......... .......... .......... .......... 34% 40.9M 10s\n", - "204650K .......... .......... .......... .......... .......... 34% 32.9M 10s\n", - "204700K .......... .......... .......... .......... .......... 34% 46.1M 10s\n", - "204750K .......... .......... .......... .......... .......... 34% 55.6M 10s\n", - "204800K .......... .......... .......... .......... .......... 34% 47.1M 10s\n", - "204850K .......... .......... .......... .......... .......... 34% 39.8M 10s\n", - "204900K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", - "204950K .......... .......... .......... .......... .......... 34% 51.3M 10s\n", - "205000K .......... .......... .......... .......... .......... 34% 38.0M 10s\n", - "205050K .......... .......... .......... .......... .......... 34% 40.0M 10s\n", - "205100K .......... .......... .......... .......... .......... 34% 46.5M 10s\n", - "205150K .......... .......... .......... .......... .......... 34% 43.6M 10s\n", - "205200K .......... .......... .......... .......... .......... 34% 57.3M 10s\n", - "205250K .......... .......... .......... .......... .......... 34% 57.6M 10s\n", - "205300K .......... .......... .......... .......... .......... 34% 33.8M 10s\n", - "205350K .......... .......... .......... .......... .......... 34% 56.2M 10s\n", - "205400K .......... .......... .......... .......... .......... 34% 38.4M 10s\n", - "205450K .......... .......... .......... .......... .......... 34% 60.4M 10s\n", - "205500K .......... .......... .......... .......... .......... 34% 44.2M 10s\n", - "205550K .......... .......... .......... .......... .......... 34% 43.1M 10s\n", - "205600K .......... .......... .......... .......... .......... 34% 47.7M 10s\n", - "205650K .......... .......... .......... .......... .......... 34% 52.3M 10s\n", - "205700K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", - "205750K .......... .......... .......... .......... .......... 34% 36.8M 10s\n", - "205800K .......... .......... .......... .......... .......... 34% 31.9M 10s\n", - "205850K .......... .......... .......... .......... .......... 34% 50.5M 10s\n", - "205900K .......... .......... .......... .......... .......... 34% 43.8M 10s\n", - "205950K .......... .......... .......... .......... .......... 34% 45.5M 10s\n", - "206000K .......... .......... .......... .......... .......... 34% 33.1M 10s\n", - "206050K .......... .......... .......... .......... .......... 34% 48.6M 10s\n", - "206100K .......... .......... .......... .......... .......... 34% 48.4M 10s\n", - "206150K .......... .......... .......... .......... .......... 34% 44.0M 10s\n", - "206200K .......... .......... .......... .......... .......... 34% 26.0M 10s\n", - "206250K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", - "206300K .......... .......... .......... .......... .......... 34% 42.6M 10s\n", - "206350K .......... .......... .......... .......... .......... 34% 31.3M 10s\n", - "206400K .......... .......... .......... .......... .......... 34% 43.0M 10s\n", - "206450K .......... .......... .......... .......... .......... 34% 47.1M 10s\n", - "206500K .......... .......... .......... .......... .......... 34% 56.3M 10s\n", - "206550K .......... .......... .......... .......... .......... 34% 46.6M 10s\n", - "206600K .......... .......... .......... .......... .......... 34% 50.9M 10s\n", - "206650K .......... .......... .......... .......... .......... 34% 60.5M 10s\n", - "206700K .......... .......... .......... .......... .......... 34% 57.2M 10s\n", - "206750K .......... .......... .......... .......... .......... 34% 55.4M 10s\n", - "206800K .......... .......... .......... .......... .......... 34% 41.6M 10s\n", - "206850K .......... .......... .......... .......... .......... 34% 57.3M 10s\n", - "206900K .......... .......... .......... .......... .......... 34% 68.9M 10s\n", - "206950K .......... .......... .......... .......... .......... 34% 53.3M 10s\n", - "207000K .......... .......... .......... .......... .......... 34% 39.8M 10s\n", - "207050K .......... .......... .......... .......... .......... 34% 50.8M 10s\n", - "207100K .......... .......... .......... .......... .......... 34% 62.6M 10s\n", - "207150K .......... .......... .......... .......... .......... 34% 56.9M 10s\n", - "207200K .......... .......... .......... .......... .......... 34% 46.2M 10s\n", - "207250K .......... .......... .......... .......... .......... 34% 50.4M 10s\n", - "207300K .......... .......... .......... .......... .......... 34% 47.3M 10s\n", - "207350K .......... .......... .......... .......... .......... 34% 65.2M 10s\n", - "207400K .......... .......... .......... .......... .......... 34% 45.3M 10s\n", - "207450K .......... .......... .......... .......... .......... 34% 63.0M 10s\n", - "207500K .......... .......... .......... .......... .......... 34% 51.2M 10s\n", - "207550K .......... .......... .......... .......... .......... 34% 53.1M 10s\n", - "207600K .......... .......... .......... .......... .......... 34% 4.60M 10s\n", - "207650K .......... .......... .......... .......... .......... 34% 60.7M 10s\n", - "207700K .......... .......... .......... .......... .......... 34% 66.8M 10s\n", - "207750K .......... .......... .......... .......... .......... 34% 65.8M 10s\n", - "207800K .......... .......... .......... .......... .......... 34% 56.4M 10s\n", - "207850K .......... .......... .......... .......... .......... 34% 27.6M 10s\n", - "207900K .......... .......... .......... .......... .......... 34% 47.8M 10s\n", - "207950K .......... .......... .......... .......... .......... 34% 60.9M 10s\n", - "208000K .......... .......... .......... .......... .......... 34% 55.8M 10s\n", - "208050K .......... .......... .......... .......... .......... 34% 64.6M 10s\n", - "208100K .......... .......... .......... .......... .......... 34% 35.0M 10s\n", - "208150K .......... .......... .......... .......... .......... 35% 50.5M 10s\n", - "208200K .......... .......... .......... .......... .......... 35% 48.8M 10s\n", - "208250K .......... .......... .......... .......... .......... 35% 62.9M 10s\n", - "208300K .......... .......... .......... .......... .......... 35% 33.0M 10s\n", - "208350K .......... .......... .......... .......... .......... 35% 45.5M 10s\n", - "208400K .......... .......... .......... .......... .......... 35% 46.1M 10s\n", - "208450K .......... .......... .......... .......... .......... 35% 61.9M 10s\n", - "208500K .......... .......... .......... .......... .......... 35% 65.3M 10s\n", - "208550K .......... .......... .......... .......... .......... 35% 28.2M 10s\n", - "208600K .......... .......... .......... .......... .......... 35% 45.4M 10s\n", - "208650K .......... .......... .......... .......... .......... 35% 63.8M 10s\n", - "208700K .......... .......... .......... .......... .......... 35% 65.6M 10s\n", - "208750K .......... .......... .......... .......... .......... 35% 40.6M 10s\n", - "208800K .......... .......... .......... .......... .......... 35% 59.6M 10s\n", - "208850K .......... .......... .......... .......... .......... 35% 56.2M 10s\n", - "208900K .......... .......... .......... .......... .......... 35% 58.1M 10s\n", - "208950K .......... .......... .......... .......... .......... 35% 69.5M 10s\n", - "209000K .......... .......... .......... .......... .......... 35% 22.9M 10s\n", - "209050K .......... .......... .......... .......... .......... 35% 51.6M 10s\n", - "209100K .......... .......... .......... .......... .......... 35% 63.3M 10s\n", - "209150K .......... .......... .......... .......... .......... 35% 63.2M 10s\n", - "209200K .......... .......... .......... .......... .......... 35% 27.0M 10s\n", - "209250K .......... .......... .......... .......... .......... 35% 41.3M 10s\n", - "209300K .......... .......... .......... .......... .......... 35% 57.2M 10s\n", - "209350K .......... .......... .......... .......... .......... 35% 62.7M 10s\n", - "209400K .......... .......... .......... .......... .......... 35% 56.2M 10s\n", - "209450K .......... .......... .......... .......... .......... 35% 10.0M 10s\n", - "209500K .......... .......... .......... .......... .......... 35% 61.3M 10s\n", - "209550K .......... .......... .......... .......... .......... 35% 63.2M 10s\n", - "209600K .......... .......... .......... .......... .......... 35% 59.0M 10s\n", - "209650K .......... .......... .......... .......... .......... 35% 65.8M 10s\n", - "209700K .......... .......... .......... .......... .......... 35% 27.3M 10s\n", - "209750K .......... .......... .......... .......... .......... 35% 60.4M 10s\n", - "209800K .......... .......... .......... .......... .......... 35% 8.30M 10s\n", - "209850K .......... .......... .......... .......... .......... 35% 70.1M 10s\n", - "209900K .......... .......... .......... .......... .......... 35% 63.5M 10s\n", - "209950K .......... .......... .......... .......... .......... 35% 61.4M 10s\n", - "210000K .......... .......... .......... .......... .......... 35% 59.9M 10s\n", - "210050K .......... .......... .......... .......... .......... 35% 67.9M 10s\n", - "210100K .......... .......... .......... .......... .......... 35% 60.0M 10s\n", - "210150K .......... .......... .......... .......... .......... 35% 47.3M 10s\n", - "210200K .......... .......... .......... .......... .......... 35% 50.1M 10s\n", - "210250K .......... .......... .......... .......... .......... 35% 56.0M 10s\n", - "210300K .......... .......... .......... .......... .......... 35% 71.1M 10s\n", - "210350K .......... .......... .......... .......... .......... 35% 58.1M 10s\n", - "210400K .......... .......... .......... .......... .......... 35% 53.4M 10s\n", - "210450K .......... .......... .......... .......... .......... 35% 64.7M 10s\n", - "210500K .......... .......... .......... .......... .......... 35% 64.0M 10s\n", - "210550K .......... .......... .......... .......... .......... 35% 30.6M 10s\n", - "210600K .......... .......... .......... .......... .......... 35% 39.0M 10s\n", - "210650K .......... .......... .......... .......... .......... 35% 63.7M 10s\n", - "210700K .......... .......... .......... .......... .......... 35% 65.1M 10s\n", - "210750K .......... .......... .......... .......... .......... 35% 39.8M 10s\n", - "210800K .......... .......... .......... .......... .......... 35% 46.3M 10s\n", - "210850K .......... .......... .......... .......... .......... 35% 49.5M 10s\n", - "210900K .......... .......... .......... .......... .......... 35% 60.1M 10s\n", - "210950K .......... .......... .......... .......... .......... 35% 64.3M 10s\n", - "211000K .......... .......... .......... .......... .......... 35% 37.1M 10s\n", - "211050K .......... .......... .......... .......... .......... 35% 51.2M 10s\n", - "211100K .......... .......... .......... .......... .......... 35% 49.0M 10s\n", - "211150K .......... .......... .......... .......... .......... 35% 66.5M 10s\n", - "211200K .......... .......... .......... .......... .......... 35% 55.4M 10s\n", - "211250K .......... .......... .......... .......... .......... 35% 49.9M 10s\n", - "211300K .......... .......... .......... .......... .......... 35% 47.7M 10s\n", - "211350K .......... .......... .......... .......... .......... 35% 50.9M 10s\n", - "211400K .......... .......... .......... .......... .......... 35% 55.3M 9s\n", - "211450K .......... .......... .......... .......... .......... 35% 48.8M 9s\n", - "211500K .......... .......... .......... .......... .......... 35% 47.4M 9s\n", - "211550K .......... .......... .......... .......... .......... 35% 43.7M 9s\n", - "211600K .......... .......... .......... .......... .......... 35% 51.2M 9s\n", - "211650K .......... .......... .......... .......... .......... 35% 66.6M 9s\n", - "211700K .......... .......... .......... .......... .......... 35% 65.6M 9s\n", - "211750K .......... .......... .......... .......... .......... 35% 33.2M 9s\n", - "211800K .......... .......... .......... .......... .......... 35% 40.5M 9s\n", - "211850K .......... .......... .......... .......... .......... 35% 65.8M 9s\n", - "211900K .......... .......... .......... .......... .......... 35% 69.8M 9s\n", - "211950K .......... .......... .......... .......... .......... 35% 51.3M 9s\n", - "212000K .......... .......... .......... .......... .......... 35% 45.4M 9s\n", - "212050K .......... .......... .......... .......... .......... 35% 53.5M 9s\n", - "212100K .......... .......... .......... .......... .......... 35% 62.8M 9s\n", - "212150K .......... .......... .......... .......... .......... 35% 69.9M 9s\n", - "212200K .......... .......... .......... .......... .......... 35% 31.8M 9s\n", - "212250K .......... .......... .......... .......... .......... 35% 44.0M 9s\n", - "212300K .......... .......... .......... .......... .......... 35% 56.2M 9s\n", - "212350K .......... .......... .......... .......... .......... 35% 68.2M 9s\n", - "212400K .......... .......... .......... .......... .......... 35% 5.17M 9s\n", - "212450K .......... .......... .......... .......... .......... 35% 63.5M 9s\n", - "212500K .......... .......... .......... .......... .......... 35% 66.2M 9s\n", - "212550K .......... .......... .......... .......... .......... 35% 65.8M 9s\n", - "212600K .......... .......... .......... .......... .......... 35% 56.7M 9s\n", - "212650K .......... .......... .......... .......... .......... 35% 67.7M 9s\n", - "212700K .......... .......... .......... .......... .......... 35% 15.6M 9s\n", - "212750K .......... .......... .......... .......... .......... 35% 66.6M 9s\n", - "212800K .......... .......... .......... .......... .......... 35% 58.3M 9s\n", - "212850K .......... .......... .......... .......... .......... 35% 59.2M 9s\n", - "212900K .......... .......... .......... .......... .......... 35% 54.7M 9s\n", - "212950K .......... .......... .......... .......... .......... 35% 64.0M 9s\n", - "213000K .......... .......... .......... .......... .......... 35% 41.4M 9s\n", - "213050K .......... .......... .......... .......... .......... 35% 53.1M 9s\n", - "213100K .......... .......... .......... .......... .......... 35% 20.4M 9s\n", - "213150K .......... .......... .......... .......... .......... 35% 61.1M 9s\n", - "213200K .......... .......... .......... .......... .......... 35% 46.5M 9s\n", - "213250K .......... .......... .......... .......... .......... 35% 52.4M 9s\n", - "213300K .......... .......... .......... .......... .......... 35% 71.8M 9s\n", - "213350K .......... .......... .......... .......... .......... 35% 67.7M 9s\n", - "213400K .......... .......... .......... .......... .......... 35% 44.5M 9s\n", - "213450K .......... .......... .......... .......... .......... 35% 47.8M 9s\n", - "213500K .......... .......... .......... .......... .......... 35% 52.3M 9s\n", - "213550K .......... .......... .......... .......... .......... 35% 64.6M 9s\n", - "213600K .......... .......... .......... .......... .......... 35% 57.6M 9s\n", - "213650K .......... .......... .......... .......... .......... 35% 58.5M 9s\n", - "213700K .......... .......... .......... .......... .......... 35% 52.2M 9s\n", - "213750K .......... .......... .......... .......... .......... 35% 56.1M 9s\n", - "213800K .......... .......... .......... .......... .......... 35% 50.0M 9s\n", - "213850K .......... .......... .......... .......... .......... 35% 64.4M 9s\n", - "213900K .......... .......... .......... .......... .......... 35% 55.4M 9s\n", - "213950K .......... .......... .......... .......... .......... 35% 50.2M 9s\n", - "214000K .......... .......... .......... .......... .......... 35% 53.3M 9s\n", - "214050K .......... .......... .......... .......... .......... 35% 58.6M 9s\n", - "214100K .......... .......... .......... .......... .......... 36% 72.6M 9s\n", - "214150K .......... .......... .......... .......... .......... 36% 58.3M 9s\n", - "214200K .......... .......... .......... .......... .......... 36% 45.8M 9s\n", - "214250K .......... .......... .......... .......... .......... 36% 56.4M 9s\n", - "214300K .......... .......... .......... .......... .......... 36% 47.7M 9s\n", - "214350K .......... .......... .......... .......... .......... 36% 65.9M 9s\n", - "214400K .......... .......... .......... .......... .......... 36% 36.0M 9s\n", - "214450K .......... .......... .......... .......... .......... 36% 53.9M 9s\n", - "214500K .......... .......... .......... .......... .......... 36% 44.9M 9s\n", - "214550K .......... .......... .......... .......... .......... 36% 61.4M 9s\n", - "214600K .......... .......... .......... .......... .......... 36% 55.3M 9s\n", - "214650K .......... .......... .......... .......... .......... 36% 56.4M 9s\n", - "214700K .......... .......... .......... .......... .......... 36% 60.1M 9s\n", - "214750K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", - "214800K .......... .......... .......... .......... .......... 36% 53.3M 9s\n", - "214850K .......... .......... .......... .......... .......... 36% 3.97M 9s\n", - "214900K .......... .......... .......... .......... .......... 36% 59.1M 9s\n", - "214950K .......... .......... .......... .......... .......... 36% 71.1M 9s\n", - "215000K .......... .......... .......... .......... .......... 36% 54.2M 9s\n", - "215050K .......... .......... .......... .......... .......... 36% 68.1M 9s\n", - "215100K .......... .......... .......... .......... .......... 36% 63.9M 9s\n", - "215150K .......... .......... .......... .......... .......... 36% 41.0M 9s\n", - "215200K .......... .......... .......... .......... .......... 36% 43.9M 9s\n", - "215250K .......... .......... .......... .......... .......... 36% 51.5M 9s\n", - "215300K .......... .......... .......... .......... .......... 36% 64.2M 9s\n", - "215350K .......... .......... .......... .......... .......... 36% 56.8M 9s\n", - "215400K .......... .......... .......... .......... .......... 36% 5.47M 9s\n", - "215450K .......... .......... .......... .......... .......... 36% 67.2M 9s\n", - "215500K .......... .......... .......... .......... .......... 36% 47.0M 9s\n", - "215550K .......... .......... .......... .......... .......... 36% 53.1M 9s\n", - "215600K .......... .......... .......... .......... .......... 36% 56.5M 9s\n", - "215650K .......... .......... .......... .......... .......... 36% 62.3M 9s\n", - "215700K .......... .......... .......... .......... .......... 36% 41.4M 9s\n", - "215750K .......... .......... .......... .......... .......... 36% 47.0M 9s\n", - "215800K .......... .......... .......... .......... .......... 36% 52.6M 9s\n", - "215850K .......... .......... .......... .......... .......... 36% 64.9M 9s\n", - "215900K .......... .......... .......... .......... .......... 36% 61.3M 9s\n", - "215950K .......... .......... .......... .......... .......... 36% 48.4M 9s\n", - "216000K .......... .......... .......... .......... .......... 36% 42.0M 9s\n", - "216050K .......... .......... .......... .......... .......... 36% 50.9M 9s\n", - "216100K .......... .......... .......... .......... .......... 36% 50.1M 9s\n", - "216150K .......... .......... .......... .......... .......... 36% 49.6M 9s\n", - "216200K .......... .......... .......... .......... .......... 36% 30.9M 9s\n", - "216250K .......... .......... .......... .......... .......... 36% 54.8M 9s\n", - "216300K .......... .......... .......... .......... .......... 36% 64.8M 9s\n", - "216350K .......... .......... .......... .......... .......... 36% 50.1M 9s\n", - "216400K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", - "216450K .......... .......... .......... .......... .......... 36% 50.4M 9s\n", - "216500K .......... .......... .......... .......... .......... 36% 58.5M 9s\n", - "216550K .......... .......... .......... .......... .......... 36% 65.7M 9s\n", - "216600K .......... .......... .......... .......... .......... 36% 37.1M 9s\n", - "216650K .......... .......... .......... .......... .......... 36% 43.7M 9s\n", - "216700K .......... .......... .......... .......... .......... 36% 38.3M 9s\n", - "216750K .......... .......... .......... .......... .......... 36% 48.6M 9s\n", - "216800K .......... .......... .......... .......... .......... 36% 36.3M 9s\n", - "216850K .......... .......... .......... .......... .......... 36% 38.6M 9s\n", - "216900K .......... .......... .......... .......... .......... 36% 41.3M 9s\n", - "216950K .......... .......... .......... .......... .......... 36% 46.6M 9s\n", - "217000K .......... .......... .......... .......... .......... 36% 33.9M 9s\n", - "217050K .......... .......... .......... .......... .......... 36% 34.9M 9s\n", - "217100K .......... .......... .......... .......... .......... 36% 37.6M 9s\n", - "217150K .......... .......... .......... .......... .......... 36% 39.9M 9s\n", - "217200K .......... .......... .......... .......... .......... 36% 37.0M 9s\n", - "217250K .......... .......... .......... .......... .......... 36% 40.6M 9s\n", - "217300K .......... .......... .......... .......... .......... 36% 62.9M 9s\n", - "217350K .......... .......... .......... .......... .......... 36% 58.7M 9s\n", - "217400K .......... .......... .......... .......... .......... 36% 36.0M 9s\n", - "217450K .......... .......... .......... .......... .......... 36% 38.5M 9s\n", - "217500K .......... .......... .......... .......... .......... 36% 53.5M 9s\n", - "217550K .......... .......... .......... .......... .......... 36% 53.0M 9s\n", - "217600K .......... .......... .......... .......... .......... 36% 42.5M 9s\n", - "217650K .......... .......... .......... .......... .......... 36% 55.6M 9s\n", - "217700K .......... .......... .......... .......... .......... 36% 43.5M 9s\n", - "217750K .......... .......... .......... .......... .......... 36% 44.4M 9s\n", - "217800K .......... .......... .......... .......... .......... 36% 49.4M 9s\n", - "217850K .......... .......... .......... .......... .......... 36% 44.3M 9s\n", - "217900K .......... .......... .......... .......... .......... 36% 50.6M 9s\n", - "217950K .......... .......... .......... .......... .......... 36% 52.6M 9s\n", - "218000K .......... .......... .......... .......... .......... 36% 63.0M 9s\n", - "218050K .......... .......... .......... .......... .......... 36% 56.0M 9s\n", - "218100K .......... .......... .......... .......... .......... 36% 56.9M 9s\n", - "218150K .......... .......... .......... .......... .......... 36% 54.2M 9s\n", - "218200K .......... .......... .......... .......... .......... 36% 43.7M 9s\n", - "218250K .......... .......... .......... .......... .......... 36% 60.3M 9s\n", - "218300K .......... .......... .......... .......... .......... 36% 54.0M 9s\n", - "218350K .......... .......... .......... .......... .......... 36% 55.0M 9s\n", - "218400K .......... .......... .......... .......... .......... 36% 43.5M 9s\n", - "218450K .......... .......... .......... .......... .......... 36% 43.0M 9s\n", - "218500K .......... .......... .......... .......... .......... 36% 58.1M 9s\n", - "218550K .......... .......... .......... .......... .......... 36% 40.2M 9s\n", - "218600K .......... .......... .......... .......... .......... 36% 39.3M 9s\n", - "218650K .......... .......... .......... .......... .......... 36% 45.9M 9s\n", - "218700K .......... .......... .......... .......... .......... 36% 48.0M 9s\n", - "218750K .......... .......... .......... .......... .......... 36% 49.0M 9s\n", - "218800K .......... .......... .......... .......... .......... 36% 27.4M 9s\n", - "218850K .......... .......... .......... .......... .......... 36% 38.9M 9s\n", - "218900K .......... .......... .......... .......... .......... 36% 28.7M 9s\n", - "218950K .......... .......... .......... .......... .......... 36% 32.1M 9s\n", - "219000K .......... .......... .......... .......... .......... 36% 42.2M 9s\n", - "219050K .......... .......... .......... .......... .......... 36% 46.3M 9s\n", - "219100K .......... .......... .......... .......... .......... 36% 47.2M 9s\n", - "219150K .......... .......... .......... .......... .......... 36% 45.2M 9s\n", - "219200K .......... .......... .......... .......... .......... 36% 40.2M 9s\n", - "219250K .......... .......... .......... .......... .......... 36% 45.5M 9s\n", - "219300K .......... .......... .......... .......... .......... 36% 45.7M 9s\n", - "219350K .......... .......... .......... .......... .......... 36% 46.8M 9s\n", - "219400K .......... .......... .......... .......... .......... 36% 50.4M 9s\n", - "219450K .......... .......... .......... .......... .......... 36% 60.9M 9s\n", - "219500K .......... .......... .......... .......... .......... 36% 52.7M 9s\n", - "219550K .......... .......... .......... .......... .......... 36% 46.3M 9s\n", - "219600K .......... .......... .......... .......... .......... 36% 45.4M 9s\n", - "219650K .......... .......... .......... .......... .......... 36% 66.0M 9s\n", - "219700K .......... .......... .......... .......... .......... 36% 41.2M 9s\n", - "219750K .......... .......... .......... .......... .......... 36% 30.0M 9s\n", - "219800K .......... .......... .......... .......... .......... 36% 26.9M 9s\n", - "219850K .......... .......... .......... .......... .......... 36% 64.1M 9s\n", - "219900K .......... .......... .......... .......... .......... 36% 64.4M 9s\n", - "219950K .......... .......... .......... .......... .......... 36% 44.3M 9s\n", - "220000K .......... .......... .......... .......... .......... 36% 41.3M 9s\n", - "220050K .......... .......... .......... .......... .......... 37% 40.1M 9s\n", - "220100K .......... .......... .......... .......... .......... 37% 35.7M 9s\n", - "220150K .......... .......... .......... .......... .......... 37% 36.5M 9s\n", - "220200K .......... .......... .......... .......... .......... 37% 29.8M 9s\n", - "220250K .......... .......... .......... .......... .......... 37% 58.3M 9s\n", - "220300K .......... .......... .......... .......... .......... 37% 56.7M 9s\n", - "220350K .......... .......... .......... .......... .......... 37% 43.1M 9s\n", - "220400K .......... .......... .......... .......... .......... 37% 41.2M 9s\n", - "220450K .......... .......... .......... .......... .......... 37% 52.9M 9s\n", - "220500K .......... .......... .......... .......... .......... 37% 3.99M 9s\n", - "220550K .......... .......... .......... .......... .......... 37% 40.2M 9s\n", - "220600K .......... .......... .......... .......... .......... 37% 29.8M 9s\n", - "220650K .......... .......... .......... .......... .......... 37% 32.5M 9s\n", - "220700K .......... .......... .......... .......... .......... 37% 24.9M 9s\n", - "220750K .......... .......... .......... .......... .......... 37% 51.9M 9s\n", - "220800K .......... .......... .......... .......... .......... 37% 53.4M 9s\n", - "220850K .......... .......... .......... .......... .......... 37% 38.8M 9s\n", - "220900K .......... .......... .......... .......... .......... 37% 31.4M 9s\n", - "220950K .......... .......... .......... .......... .......... 37% 34.4M 9s\n", - "221000K .......... .......... .......... .......... .......... 37% 43.5M 9s\n", - "221050K .......... .......... .......... .......... .......... 37% 60.2M 9s\n", - "221100K .......... .......... .......... .......... .......... 37% 45.6M 9s\n", - "221150K .......... .......... .......... .......... .......... 37% 46.0M 9s\n", - "221200K .......... .......... .......... .......... .......... 37% 49.1M 9s\n", - "221250K .......... .......... .......... .......... .......... 37% 58.4M 9s\n", - "221300K .......... .......... .......... .......... .......... 37% 35.1M 9s\n", - "221350K .......... .......... .......... .......... .......... 37% 41.1M 9s\n", - "221400K .......... .......... .......... .......... .......... 37% 43.7M 9s\n", - "221450K .......... .......... .......... .......... .......... 37% 50.9M 9s\n", - "221500K .......... .......... .......... .......... .......... 37% 53.2M 9s\n", - "221550K .......... .......... .......... .......... .......... 37% 51.5M 9s\n", - "221600K .......... .......... .......... .......... .......... 37% 5.35M 9s\n", - "221650K .......... .......... .......... .......... .......... 37% 42.1M 9s\n", - "221700K .......... .......... .......... .......... .......... 37% 64.2M 9s\n", - "221750K .......... .......... .......... .......... .......... 37% 62.6M 9s\n", - "221800K .......... .......... .......... .......... .......... 37% 49.1M 9s\n", - "221850K .......... .......... .......... .......... .......... 37% 44.2M 9s\n", - "221900K .......... .......... .......... .......... .......... 37% 43.5M 9s\n", - "221950K .......... .......... .......... .......... .......... 37% 66.4M 9s\n", - "222000K .......... .......... .......... .......... .......... 37% 60.0M 9s\n", - "222050K .......... .......... .......... .......... .......... 37% 57.3M 9s\n", - "222100K .......... .......... .......... .......... .......... 37% 61.9M 9s\n", - "222150K .......... .......... .......... .......... .......... 37% 57.6M 9s\n", - "222200K .......... .......... .......... .......... .......... 37% 41.2M 9s\n", - "222250K .......... .......... .......... .......... .......... 37% 61.2M 9s\n", - "222300K .......... .......... .......... .......... .......... 37% 46.6M 9s\n", - "222350K .......... .......... .......... .......... .......... 37% 62.8M 9s\n", - "222400K .......... .......... .......... .......... .......... 37% 5.97M 9s\n", - "222450K .......... .......... .......... .......... .......... 37% 44.3M 9s\n", - "222500K .......... .......... .......... .......... .......... 37% 43.2M 9s\n", - "222550K .......... .......... .......... .......... .......... 37% 37.2M 9s\n", - "222600K .......... .......... .......... .......... .......... 37% 35.1M 9s\n", - "222650K .......... .......... .......... .......... .......... 37% 47.7M 9s\n", - "222700K .......... .......... .......... .......... .......... 37% 64.0M 9s\n", - "222750K .......... .......... .......... .......... .......... 37% 59.8M 9s\n", - "222800K .......... .......... .......... .......... .......... 37% 48.6M 9s\n", - "222850K .......... .......... .......... .......... .......... 37% 43.6M 9s\n", - "222900K .......... .......... .......... .......... .......... 37% 37.2M 9s\n", - "222950K .......... .......... .......... .......... .......... 37% 59.1M 9s\n", - "223000K .......... .......... .......... .......... .......... 37% 50.0M 9s\n", - "223050K .......... .......... .......... .......... .......... 37% 60.6M 9s\n", - "223100K .......... .......... .......... .......... .......... 37% 32.7M 9s\n", - "223150K .......... .......... .......... .......... .......... 37% 49.9M 9s\n", - "223200K .......... .......... .......... .......... .......... 37% 42.2M 9s\n", - "223250K .......... .......... .......... .......... .......... 37% 53.3M 9s\n", - "223300K .......... .......... .......... .......... .......... 37% 41.9M 9s\n", - "223350K .......... .......... .......... .......... .......... 37% 42.4M 9s\n", - "223400K .......... .......... .......... .......... .......... 37% 44.8M 9s\n", - "223450K .......... .......... .......... .......... .......... 37% 48.3M 9s\n", - "223500K .......... .......... .......... .......... .......... 37% 40.2M 9s\n", - "223550K .......... .......... .......... .......... .......... 37% 46.7M 9s\n", - "223600K .......... .......... .......... .......... .......... 37% 51.8M 9s\n", - "223650K .......... .......... .......... .......... .......... 37% 55.0M 9s\n", - "223700K .......... .......... .......... .......... .......... 37% 46.8M 9s\n", - "223750K .......... .......... .......... .......... .......... 37% 47.1M 9s\n", - "223800K .......... .......... .......... .......... .......... 37% 38.8M 9s\n", - "223850K .......... .......... .......... .......... .......... 37% 59.1M 9s\n", - "223900K .......... .......... .......... .......... .......... 37% 58.6M 9s\n", - "223950K .......... .......... .......... .......... .......... 37% 50.7M 9s\n", - "224000K .......... .......... .......... .......... .......... 37% 33.9M 9s\n", - "224050K .......... .......... .......... .......... .......... 37% 54.0M 9s\n", - "224100K .......... .......... .......... .......... .......... 37% 57.9M 9s\n", - "224150K .......... .......... .......... .......... .......... 37% 51.8M 9s\n", - "224200K .......... .......... .......... .......... .......... 37% 38.7M 9s\n", - "224250K .......... .......... .......... .......... .......... 37% 54.8M 9s\n", - "224300K .......... .......... .......... .......... .......... 37% 57.4M 9s\n", - "224350K .......... .......... .......... .......... .......... 37% 58.5M 9s\n", - "224400K .......... .......... .......... .......... .......... 37% 48.6M 9s\n", - "224450K .......... .......... .......... .......... .......... 37% 48.2M 9s\n", - "224500K .......... .......... .......... .......... .......... 37% 48.0M 9s\n", - "224550K .......... .......... .......... .......... .......... 37% 40.0M 9s\n", - "224600K .......... .......... .......... .......... .......... 37% 49.3M 9s\n", - "224650K .......... .......... .......... .......... .......... 37% 53.3M 9s\n", - "224700K .......... .......... .......... .......... .......... 37% 57.7M 9s\n", - "224750K .......... .......... .......... .......... .......... 37% 45.7M 9s\n", - "224800K .......... .......... .......... .......... .......... 37% 54.1M 9s\n", - "224850K .......... .......... .......... .......... .......... 37% 66.2M 9s\n", - "224900K .......... .......... .......... .......... .......... 37% 53.1M 9s\n", - "224950K .......... .......... .......... .......... .......... 37% 51.0M 9s\n", - "225000K .......... .......... .......... .......... .......... 37% 29.7M 9s\n", - "225050K .......... .......... .......... .......... .......... 37% 34.7M 9s\n", - "225100K .......... .......... .......... .......... .......... 37% 32.8M 9s\n", - "225150K .......... .......... .......... .......... .......... 37% 32.8M 9s\n", - "225200K .......... .......... .......... .......... .......... 37% 34.8M 9s\n", - "225250K .......... .......... .......... .......... .......... 37% 54.0M 9s\n", - "225300K .......... .......... .......... .......... .......... 37% 64.5M 9s\n", - "225350K .......... .......... .......... .......... .......... 37% 47.3M 9s\n", - "225400K .......... .......... .......... .......... .......... 37% 32.9M 9s\n", - "225450K .......... .......... .......... .......... .......... 37% 59.7M 9s\n", - "225500K .......... .......... .......... .......... .......... 37% 49.9M 9s\n", - "225550K .......... .......... .......... .......... .......... 37% 41.9M 9s\n", - "225600K .......... .......... .......... .......... .......... 37% 53.6M 9s\n", - "225650K .......... .......... .......... .......... .......... 37% 57.0M 9s\n", - "225700K .......... .......... .......... .......... .......... 37% 63.2M 9s\n", - "225750K .......... .......... .......... .......... .......... 37% 58.3M 9s\n", - "225800K .......... .......... .......... .......... .......... 37% 48.8M 9s\n", - "225850K .......... .......... .......... .......... .......... 37% 68.4M 9s\n", - "225900K .......... .......... .......... .......... .......... 37% 56.0M 9s\n", - "225950K .......... .......... .......... .......... .......... 38% 58.8M 9s\n", - "226000K .......... .......... .......... .......... .......... 38% 50.1M 9s\n", - "226050K .......... .......... .......... .......... .......... 38% 63.3M 9s\n", - "226100K .......... .......... .......... .......... .......... 38% 57.2M 9s\n", - "226150K .......... .......... .......... .......... .......... 38% 58.7M 9s\n", - "226200K .......... .......... .......... .......... .......... 38% 55.0M 9s\n", - "226250K .......... .......... .......... .......... .......... 38% 49.9M 9s\n", - "226300K .......... .......... .......... .......... .......... 38% 64.6M 9s\n", - "226350K .......... .......... .......... .......... .......... 38% 58.0M 9s\n", - "226400K .......... .......... .......... .......... .......... 38% 44.9M 9s\n", - "226450K .......... .......... .......... .......... .......... 38% 55.9M 9s\n", - "226500K .......... .......... .......... .......... .......... 38% 56.7M 9s\n", - "226550K .......... .......... .......... .......... .......... 38% 59.6M 9s\n", - "226600K .......... .......... .......... .......... .......... 38% 56.0M 9s\n", - "226650K .......... .......... .......... .......... .......... 38% 61.2M 9s\n", - "226700K .......... .......... .......... .......... .......... 38% 61.8M 9s\n", - "226750K .......... .......... .......... .......... .......... 38% 66.6M 9s\n", - "226800K .......... .......... .......... .......... .......... 38% 3.80M 9s\n", - "226850K .......... .......... .......... .......... .......... 38% 63.9M 9s\n", - "226900K .......... .......... .......... .......... .......... 38% 62.5M 9s\n", - "226950K .......... .......... .......... .......... .......... 38% 63.4M 9s\n", - "227000K .......... .......... .......... .......... .......... 38% 53.1M 9s\n", - "227050K .......... .......... .......... .......... .......... 38% 60.7M 9s\n", - "227100K .......... .......... .......... .......... .......... 38% 50.3M 9s\n", - "227150K .......... .......... .......... .......... .......... 38% 56.4M 9s\n", - "227200K .......... .......... .......... .......... .......... 38% 58.4M 9s\n", - "227250K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", - "227300K .......... .......... .......... .......... .......... 38% 66.3M 9s\n", - "227350K .......... .......... .......... .......... .......... 38% 48.2M 9s\n", - "227400K .......... .......... .......... .......... .......... 38% 42.5M 9s\n", - "227450K .......... .......... .......... .......... .......... 38% 68.2M 9s\n", - "227500K .......... .......... .......... .......... .......... 38% 64.4M 9s\n", - "227550K .......... .......... .......... .......... .......... 38% 65.7M 9s\n", - "227600K .......... .......... .......... .......... .......... 38% 50.1M 9s\n", - "227650K .......... .......... .......... .......... .......... 38% 68.0M 9s\n", - "227700K .......... .......... .......... .......... .......... 38% 60.5M 9s\n", - "227750K .......... .......... .......... .......... .......... 38% 57.8M 9s\n", - "227800K .......... .......... .......... .......... .......... 38% 54.7M 9s\n", - "227850K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", - "227900K .......... .......... .......... .......... .......... 38% 66.8M 9s\n", - "227950K .......... .......... .......... .......... .......... 38% 62.3M 9s\n", - "228000K .......... .......... .......... .......... .......... 38% 54.6M 9s\n", - "228050K .......... .......... .......... .......... .......... 38% 58.3M 9s\n", - "228100K .......... .......... .......... .......... .......... 38% 62.3M 9s\n", - "228150K .......... .......... .......... .......... .......... 38% 63.5M 9s\n", - "228200K .......... .......... .......... .......... .......... 38% 49.2M 9s\n", - "228250K .......... .......... .......... .......... .......... 38% 63.8M 9s\n", - "228300K .......... .......... .......... .......... .......... 38% 59.5M 9s\n", - "228350K .......... .......... .......... .......... .......... 38% 71.2M 9s\n", - "228400K .......... .......... .......... .......... .......... 38% 57.9M 9s\n", - "228450K .......... .......... .......... .......... .......... 38% 67.8M 9s\n", - "228500K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", - "228550K .......... .......... .......... .......... .......... 38% 54.8M 9s\n", - "228600K .......... .......... .......... .......... .......... 38% 52.0M 9s\n", - "228650K .......... .......... .......... .......... .......... 38% 64.2M 9s\n", - "228700K .......... .......... .......... .......... .......... 38% 65.1M 9s\n", - "228750K .......... .......... .......... .......... .......... 38% 61.7M 9s\n", - "228800K .......... .......... .......... .......... .......... 38% 57.3M 9s\n", - "228850K .......... .......... .......... .......... .......... 38% 62.9M 9s\n", - "228900K .......... .......... .......... .......... .......... 38% 63.0M 9s\n", - "228950K .......... .......... .......... .......... .......... 38% 65.8M 9s\n", - "229000K .......... .......... .......... .......... .......... 38% 53.8M 9s\n", - "229050K .......... .......... .......... .......... .......... 38% 64.8M 9s\n", - "229100K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", - "229150K .......... .......... .......... .......... .......... 38% 64.9M 9s\n", - "229200K .......... .......... .......... .......... .......... 38% 58.1M 9s\n", - "229250K .......... .......... .......... .......... .......... 38% 58.4M 9s\n", - "229300K .......... .......... .......... .......... .......... 38% 65.5M 9s\n", - "229350K .......... .......... .......... .......... .......... 38% 61.3M 9s\n", - "229400K .......... .......... .......... .......... .......... 38% 46.8M 9s\n", - "229450K .......... .......... .......... .......... .......... 38% 68.3M 9s\n", - "229500K .......... .......... .......... .......... .......... 38% 64.2M 9s\n", - "229550K .......... .......... .......... .......... .......... 38% 64.8M 9s\n", - "229600K .......... .......... .......... .......... .......... 38% 61.2M 9s\n", - "229650K .......... .......... .......... .......... .......... 38% 26.1M 9s\n", - "229700K .......... .......... .......... .......... .......... 38% 65.4M 9s\n", - "229750K .......... .......... .......... .......... .......... 38% 13.9M 9s\n", - "229800K .......... .......... .......... .......... .......... 38% 46.7M 9s\n", - "229850K .......... .......... .......... .......... .......... 38% 13.3M 9s\n", - "229900K .......... .......... .......... .......... .......... 38% 57.8M 9s\n", - "229950K .......... .......... .......... .......... .......... 38% 15.1M 9s\n", - "230000K .......... .......... .......... .......... .......... 38% 43.6M 9s\n", - "230050K .......... .......... .......... .......... .......... 38% 3.74M 9s\n", - "230100K .......... .......... .......... .......... .......... 38% 4.14M 9s\n", - "230150K .......... .......... .......... .......... .......... 38% 56.1M 9s\n", - "230200K .......... .......... .......... .......... .......... 38% 53.8M 9s\n", - "230250K .......... .......... .......... .......... .......... 38% 64.7M 9s\n", - "230300K .......... .......... .......... .......... .......... 38% 19.4M 9s\n", - "230350K .......... .......... .......... .......... .......... 38% 54.7M 9s\n", - "230400K .......... .......... .......... .......... .......... 38% 12.7M 9s\n", - "230450K .......... .......... .......... .......... .......... 38% 53.5M 9s\n", - "230500K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", - "230550K .......... .......... .......... .......... .......... 38% 49.6M 9s\n", - "230600K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", - "230650K .......... .......... .......... .......... .......... 38% 39.9M 9s\n", - "230700K .......... .......... .......... .......... .......... 38% 14.3M 9s\n", - "230750K .......... .......... .......... .......... .......... 38% 47.8M 9s\n", - "230800K .......... .......... .......... .......... .......... 38% 55.7M 9s\n", - "230850K .......... .......... .......... .......... .......... 38% 15.3M 9s\n", - "230900K .......... .......... .......... .......... .......... 38% 51.5M 9s\n", - "230950K .......... .......... .......... .......... .......... 38% 13.1M 9s\n", - "231000K .......... .......... .......... .......... .......... 38% 50.7M 9s\n", - "231050K .......... .......... .......... .......... .......... 38% 14.2M 9s\n", - "231100K .......... .......... .......... .......... .......... 38% 63.7M 9s\n", - "231150K .......... .......... .......... .......... .......... 38% 14.4M 9s\n", - "231200K .......... .......... .......... .......... .......... 38% 34.0M 9s\n", - "231250K .......... .......... .......... .......... .......... 38% 17.2M 9s\n", - "231300K .......... .......... .......... .......... .......... 38% 51.1M 9s\n", - "231350K .......... .......... .......... .......... .......... 38% 13.0M 9s\n", - "231400K .......... .......... .......... .......... .......... 38% 46.9M 9s\n", - "231450K .......... .......... .......... .......... .......... 38% 14.6M 9s\n", - "231500K .......... .......... .......... .......... .......... 38% 53.2M 9s\n", - "231550K .......... .......... .......... .......... .......... 38% 43.1M 9s\n", - "231600K .......... .......... .......... .......... .......... 38% 16.0M 9s\n", - "231650K .......... .......... .......... .......... .......... 38% 39.4M 9s\n", - "231700K .......... .......... .......... .......... .......... 38% 15.1M 9s\n", - "231750K .......... .......... .......... .......... .......... 38% 37.9M 9s\n", - "231800K .......... .......... .......... .......... .......... 38% 17.9M 9s\n", - "231850K .......... .......... .......... .......... .......... 38% 38.2M 9s\n", - "231900K .......... .......... .......... .......... .......... 39% 14.9M 9s\n", - "231950K .......... .......... .......... .......... .......... 39% 48.3M 9s\n", - "232000K .......... .......... .......... .......... .......... 39% 13.9M 9s\n", - "232050K .......... .......... .......... .......... .......... 39% 40.5M 9s\n", - "232100K .......... .......... .......... .......... .......... 39% 50.9M 9s\n", - "232150K .......... .......... .......... .......... .......... 39% 14.0M 9s\n", - "232200K .......... .......... .......... .......... .......... 39% 49.1M 9s\n", - "232250K .......... .......... .......... .......... .......... 39% 15.0M 9s\n", - "232300K .......... .......... .......... .......... .......... 39% 43.4M 9s\n", - "232350K .......... .......... .......... .......... .......... 39% 17.2M 9s\n", - "232400K .......... .......... .......... .......... .......... 39% 44.6M 9s\n", - "232450K .......... .......... .......... .......... .......... 39% 36.1M 9s\n", - "232500K .......... .......... .......... .......... .......... 39% 14.8M 9s\n", - "232550K .......... .......... .......... .......... .......... 39% 55.2M 9s\n", - "232600K .......... .......... .......... .......... .......... 39% 11.3M 9s\n", - "232650K .......... .......... .......... .......... .......... 39% 73.0M 9s\n", - "232700K .......... .......... .......... .......... .......... 39% 13.2M 9s\n", - "232750K .......... .......... .......... .......... .......... 39% 59.8M 9s\n", - "232800K .......... .......... .......... .......... .......... 39% 52.9M 9s\n", - "232850K .......... .......... .......... .......... .......... 39% 12.4M 9s\n", - "232900K .......... .......... .......... .......... .......... 39% 68.5M 9s\n", - "232950K .......... .......... .......... .......... .......... 39% 13.0M 9s\n", - "233000K .......... .......... .......... .......... .......... 39% 55.1M 9s\n", - "233050K .......... .......... .......... .......... .......... 39% 12.4M 9s\n", - "233100K .......... .......... .......... .......... .......... 39% 57.2M 9s\n", - "233150K .......... .......... .......... .......... .......... 39% 67.6M 9s\n", - "233200K .......... .......... .......... .......... .......... 39% 12.8M 9s\n", - "233250K .......... .......... .......... .......... .......... 39% 68.0M 9s\n", - "233300K .......... .......... .......... .......... .......... 39% 12.1M 9s\n", - "233350K .......... .......... .......... .......... .......... 39% 59.9M 9s\n", - "233400K .......... .......... .......... .......... .......... 39% 14.7M 9s\n", - "233450K .......... .......... .......... .......... .......... 39% 46.9M 9s\n", - "233500K .......... .......... .......... .......... .......... 39% 70.7M 9s\n", - "233550K .......... .......... .......... .......... .......... 39% 13.2M 9s\n", - "233600K .......... .......... .......... .......... .......... 39% 60.5M 9s\n", - "233650K .......... .......... .......... .......... .......... 39% 13.7M 9s\n", - "233700K .......... .......... .......... .......... .......... 39% 48.8M 9s\n", - "233750K .......... .......... .......... .......... .......... 39% 63.9M 9s\n", - "233800K .......... .......... .......... .......... .......... 39% 12.7M 9s\n", - "233850K .......... .......... .......... .......... .......... 39% 69.0M 9s\n", - "233900K .......... .......... .......... .......... .......... 39% 14.3M 9s\n", - "233950K .......... .......... .......... .......... .......... 39% 52.2M 9s\n", - "234000K .......... .......... .......... .......... .......... 39% 53.3M 9s\n", - "234050K .......... .......... .......... .......... .......... 39% 13.6M 9s\n", - "234100K .......... .......... .......... .......... .......... 39% 65.9M 9s\n", - "234150K .......... .......... .......... .......... .......... 39% 3.97M 9s\n", - "234200K .......... .......... .......... .......... .......... 39% 57.1M 9s\n", - "234250K .......... .......... .......... .......... .......... 39% 69.4M 9s\n", - "234300K .......... .......... .......... .......... .......... 39% 15.3M 9s\n", - "234350K .......... .......... .......... .......... .......... 39% 55.5M 9s\n", - "234400K .......... .......... .......... .......... .......... 39% 64.0M 9s\n", - "234450K .......... .......... .......... .......... .......... 39% 14.2M 9s\n", - "234500K .......... .......... .......... .......... .......... 39% 56.6M 9s\n", - "234550K .......... .......... .......... .......... .......... 39% 66.2M 9s\n", - "234600K .......... .......... .......... .......... .......... 39% 9.30M 9s\n", - "234650K .......... .......... .......... .......... .......... 39% 67.7M 9s\n", - "234700K .......... .......... .......... .......... .......... 39% 31.9M 9s\n", - "234750K .......... .......... .......... .......... .......... 39% 22.2M 9s\n", - "234800K .......... .......... .......... .......... .......... 39% 58.7M 9s\n", - "234850K .......... .......... .......... .......... .......... 39% 24.9M 9s\n", - "234900K .......... .......... .......... .......... .......... 39% 24.9M 9s\n", - "234950K .......... .......... .......... .......... .......... 39% 29.5M 9s\n", - "235000K .......... .......... .......... .......... .......... 39% 51.1M 9s\n", - "235050K .......... .......... .......... .......... .......... 39% 20.1M 9s\n", - "235100K .......... .......... .......... .......... .......... 39% 28.1M 9s\n", - "235150K .......... .......... .......... .......... .......... 39% 22.1M 9s\n", - "235200K .......... .......... .......... .......... .......... 39% 51.9M 9s\n", - "235250K .......... .......... .......... .......... .......... 39% 29.1M 9s\n", - "235300K .......... .......... .......... .......... .......... 39% 20.1M 9s\n", - "235350K .......... .......... .......... .......... .......... 39% 25.7M 9s\n", - "235400K .......... .......... .......... .......... .......... 39% 52.8M 9s\n", - "235450K .......... .......... .......... .......... .......... 39% 26.5M 9s\n", - "235500K .......... .......... .......... .......... .......... 39% 24.2M 9s\n", - "235550K .......... .......... .......... .......... .......... 39% 26.8M 9s\n", - "235600K .......... .......... .......... .......... .......... 39% 51.3M 9s\n", - "235650K .......... .......... .......... .......... .......... 39% 6.09M 9s\n", - "235700K .......... .......... .......... .......... .......... 39% 69.2M 9s\n", - "235750K .......... .......... .......... .......... .......... 39% 70.8M 9s\n", - "235800K .......... .......... .......... .......... .......... 39% 14.3M 9s\n", - "235850K .......... .......... .......... .......... .......... 39% 56.4M 9s\n", - "235900K .......... .......... .......... .......... .......... 39% 71.6M 9s\n", - "235950K .......... .......... .......... .......... .......... 39% 16.2M 9s\n", - "236000K .......... .......... .......... .......... .......... 39% 57.9M 9s\n", - "236050K .......... .......... .......... .......... .......... 39% 60.1M 9s\n", - "236100K .......... .......... .......... .......... .......... 39% 16.9M 9s\n", - "236150K .......... .......... .......... .......... .......... 39% 56.6M 9s\n", - "236200K .......... .......... .......... .......... .......... 39% 16.8M 9s\n", - "236250K .......... .......... .......... .......... .......... 39% 47.1M 9s\n", - "236300K .......... .......... .......... .......... .......... 39% 58.3M 9s\n", - "236350K .......... .......... .......... .......... .......... 39% 20.3M 9s\n", - "236400K .......... .......... .......... .......... .......... 39% 28.6M 9s\n", - "236450K .......... .......... .......... .......... .......... 39% 60.5M 9s\n", - "236500K .......... .......... .......... .......... .......... 39% 24.2M 9s\n", - "236550K .......... .......... .......... .......... .......... 39% 39.6M 9s\n", - "236600K .......... .......... .......... .......... .......... 39% 38.3M 9s\n", - "236650K .......... .......... .......... .......... .......... 39% 20.7M 9s\n", - "236700K .......... .......... .......... 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.......... .......... 39% 18.4M 9s\n", - "237350K .......... .......... .......... .......... .......... 39% 46.2M 9s\n", - "237400K .......... .......... .......... .......... .......... 39% 19.9M 9s\n", - "237450K .......... .......... .......... .......... .......... 39% 39.5M 9s\n", - "237500K .......... .......... .......... .......... .......... 39% 44.6M 9s\n", - "237550K .......... .......... .......... .......... .......... 39% 69.1M 9s\n", - "237600K .......... .......... .......... .......... .......... 39% 23.2M 9s\n", - "237650K .......... .......... .......... .......... .......... 39% 29.6M 9s\n", - "237700K .......... .......... .......... .......... .......... 39% 66.5M 9s\n", - "237750K .......... .......... .......... .......... .......... 39% 3.11M 9s\n", - "237800K .......... .......... .......... .......... .......... 39% 56.4M 9s\n", - "237850K .......... .......... .......... .......... .......... 40% 68.5M 9s\n", - "237900K .......... .......... .......... .......... .......... 40% 61.8M 9s\n", - "237950K .......... .......... .......... .......... .......... 40% 64.8M 9s\n", - "238000K .......... .......... .......... .......... .......... 40% 44.5M 9s\n", - "238050K .......... .......... .......... .......... .......... 40% 63.8M 9s\n", - "238100K .......... .......... .......... .......... .......... 40% 65.2M 9s\n", - "238150K .......... .......... .......... .......... .......... 40% 66.4M 9s\n", - "238200K .......... .......... .......... .......... .......... 40% 22.1M 9s\n", - "238250K .......... .......... .......... .......... .......... 40% 68.3M 9s\n", - "238300K .......... .......... .......... .......... .......... 40% 65.6M 9s\n", - "238350K .......... .......... .......... .......... .......... 40% 17.8M 9s\n", - "238400K .......... .......... .......... .......... .......... 40% 48.2M 9s\n", - "238450K .......... .......... .......... .......... .......... 40% 64.3M 9s\n", - "238500K .......... .......... .......... .......... .......... 40% 18.1M 9s\n", - "238550K .......... .......... .......... .......... .......... 40% 46.4M 9s\n", - "238600K .......... .......... .......... .......... .......... 40% 49.3M 9s\n", - "238650K .......... .......... .......... .......... .......... 40% 19.6M 9s\n", - "238700K .......... .......... .......... .......... .......... 40% 44.8M 9s\n", - "238750K .......... .......... .......... .......... .......... 40% 62.7M 9s\n", - "238800K .......... .......... .......... .......... .......... 40% 17.1M 9s\n", - "238850K .......... .......... .......... .......... .......... 40% 41.5M 9s\n", - "238900K .......... .......... .......... .......... .......... 40% 60.3M 9s\n", - "238950K .......... .......... .......... .......... .......... 40% 23.2M 9s\n", - "239000K .......... .......... .......... .......... .......... 40% 37.5M 9s\n", - "239050K .......... .......... .......... .......... .......... 40% 54.7M 9s\n", - "239100K .......... .......... .......... .......... .......... 40% 23.5M 9s\n", - "239150K .......... .......... .......... .......... .......... 40% 3.92M 9s\n", - "239200K .......... .......... .......... .......... .......... 40% 56.3M 9s\n", - "239250K .......... .......... .......... .......... .......... 40% 63.7M 9s\n", - "239300K .......... .......... .......... .......... .......... 40% 17.0M 9s\n", - "239350K .......... .......... .......... .......... .......... 40% 48.3M 9s\n", - "239400K .......... .......... .......... .......... .......... 40% 54.1M 9s\n", - "239450K .......... .......... .......... .......... .......... 40% 18.6M 9s\n", - "239500K .......... .......... .......... .......... .......... 40% 40.4M 9s\n", - "239550K .......... .......... .......... .......... .......... 40% 67.3M 9s\n", - "239600K .......... .......... .......... .......... .......... 40% 22.4M 9s\n", - "239650K .......... .......... .......... .......... .......... 40% 42.8M 9s\n", - "239700K .......... .......... .......... .......... .......... 40% 51.6M 9s\n", - "239750K .......... .......... .......... .......... .......... 40% 70.0M 9s\n", - "239800K .......... .......... .......... .......... .......... 40% 17.4M 9s\n", - "239850K .......... .......... .......... .......... .......... 40% 18.1M 9s\n", - "239900K .......... .......... .......... .......... .......... 40% 49.9M 9s\n", - "239950K .......... .......... .......... .......... .......... 40% 41.8M 9s\n", - "240000K .......... .......... .......... .......... .......... 40% 42.0M 9s\n", - "240050K .......... .......... .......... .......... .......... 40% 69.6M 9s\n", - "240100K .......... .......... .......... .......... .......... 40% 38.6M 9s\n", - "240150K .......... .......... .......... .......... .......... 40% 43.0M 9s\n", - "240200K .......... .......... .......... .......... .......... 40% 34.7M 9s\n", - "240250K .......... .......... .......... .......... .......... 40% 25.8M 9s\n", - "240300K .......... .......... .......... .......... .......... 40% 33.2M 9s\n", - "240350K .......... .......... .......... .......... .......... 40% 40.9M 9s\n", - "240400K .......... .......... .......... .......... .......... 40% 36.0M 9s\n", - "240450K .......... .......... .......... .......... .......... 40% 39.5M 9s\n", - "240500K .......... .......... .......... .......... .......... 40% 38.0M 9s\n", - "240550K .......... .......... .......... .......... .......... 40% 6.29M 9s\n", - "240600K .......... .......... .......... .......... .......... 40% 44.7M 9s\n", - "240650K .......... .......... .......... .......... .......... 40% 67.7M 9s\n", - "240700K .......... .......... .......... .......... .......... 40% 36.2M 9s\n", - "240750K .......... .......... .......... .......... .......... 40% 38.9M 9s\n", - "240800K .......... .......... .......... .......... .......... 40% 24.5M 9s\n", - "240850K .......... .......... .......... .......... .......... 40% 35.4M 9s\n", - "240900K .......... .......... .......... .......... .......... 40% 34.7M 9s\n", - "240950K .......... .......... .......... .......... .......... 40% 29.0M 9s\n", - "241000K .......... .......... .......... .......... .......... 40% 42.7M 9s\n", - "241050K .......... .......... .......... .......... .......... 40% 15.3M 9s\n", - "241100K .......... .......... .......... .......... .......... 40% 36.3M 9s\n", - "241150K .......... .......... .......... .......... .......... 40% 51.9M 9s\n", - "241200K .......... .......... .......... .......... .......... 40% 54.5M 9s\n", - "241250K .......... .......... .......... .......... .......... 40% 51.7M 9s\n", - "241300K .......... .......... .......... .......... .......... 40% 42.3M 9s\n", - "241350K .......... .......... .......... .......... .......... 40% 57.1M 9s\n", - "241400K .......... .......... .......... .......... .......... 40% 31.7M 9s\n", - "241450K .......... .......... .......... .......... .......... 40% 41.6M 9s\n", - "241500K .......... .......... .......... .......... .......... 40% 53.2M 9s\n", - "241550K .......... .......... .......... .......... .......... 40% 57.7M 9s\n", - "241600K .......... .......... .......... .......... .......... 40% 61.4M 9s\n", - "241650K .......... .......... .......... .......... .......... 40% 39.0M 9s\n", - "241700K .......... .......... .......... .......... .......... 40% 59.6M 9s\n", - "241750K .......... .......... .......... .......... .......... 40% 44.1M 9s\n", - "241800K .......... .......... .......... .......... .......... 40% 22.5M 9s\n", - "241850K .......... .......... .......... .......... .......... 40% 46.6M 9s\n", - "241900K .......... .......... .......... .......... .......... 40% 47.1M 9s\n", - "241950K .......... .......... .......... .......... .......... 40% 61.7M 9s\n", - "242000K .......... .......... .......... .......... .......... 40% 21.6M 9s\n", - "242050K .......... .......... .......... .......... .......... 40% 55.0M 9s\n", - "242100K .......... .......... .......... .......... .......... 40% 51.2M 9s\n", - "242150K .......... .......... .......... .......... .......... 40% 66.5M 9s\n", - "242200K .......... .......... .......... .......... .......... 40% 18.0M 9s\n", - "242250K .......... .......... .......... .......... .......... 40% 50.9M 9s\n", - "242300K .......... .......... .......... .......... .......... 40% 65.5M 9s\n", - "242350K .......... .......... .......... .......... .......... 40% 29.5M 9s\n", - "242400K .......... .......... .......... .......... .......... 40% 39.3M 9s\n", - "242450K .......... .......... .......... .......... .......... 40% 50.5M 9s\n", - "242500K .......... .......... .......... .......... .......... 40% 61.9M 9s\n", - "242550K .......... .......... .......... .......... .......... 40% 25.5M 9s\n", - "242600K .......... .......... .......... .......... .......... 40% 36.5M 9s\n", - "242650K .......... .......... .......... .......... .......... 40% 61.4M 9s\n", - "242700K .......... .......... .......... .......... .......... 40% 26.6M 9s\n", - "242750K .......... .......... .......... .......... .......... 40% 34.0M 9s\n", - "242800K .......... .......... .......... .......... .......... 40% 48.0M 9s\n", - "242850K .......... .......... .......... .......... .......... 40% 62.7M 9s\n", - "242900K .......... .......... .......... .......... .......... 40% 28.1M 9s\n", - "242950K .......... .......... .......... .......... .......... 40% 31.2M 9s\n", - "243000K .......... .......... .......... .......... .......... 40% 47.3M 9s\n", - "243050K .......... .......... .......... .......... .......... 40% 40.7M 9s\n", - "243100K .......... .......... .......... .......... .......... 40% 27.5M 9s\n", - "243150K .......... .......... .......... .......... .......... 40% 49.0M 9s\n", - "243200K .......... .......... .......... .......... .......... 40% 56.4M 9s\n", - "243250K .......... .......... .......... .......... .......... 40% 40.0M 9s\n", - "243300K .......... .......... .......... .......... .......... 40% 32.2M 9s\n", - "243350K .......... .......... .......... .......... .......... 40% 58.6M 9s\n", - "243400K .......... .......... .......... .......... .......... 40% 24.0M 9s\n", - "243450K .......... .......... .......... .......... .......... 40% 40.0M 9s\n", - "243500K .......... .......... .......... .......... .......... 40% 52.7M 9s\n", - "243550K .......... .......... .......... .......... .......... 40% 57.8M 9s\n", - "243600K .......... .......... .......... .......... .......... 40% 31.4M 9s\n", - "243650K .......... .......... .......... .......... .......... 40% 26.5M 9s\n", - "243700K .......... .......... .......... .......... .......... 40% 55.7M 9s\n", - "243750K .......... .......... .......... .......... .......... 40% 56.4M 9s\n", - "243800K .......... .......... .......... .......... .......... 41% 33.4M 9s\n", - "243850K .......... .......... .......... .......... .......... 41% 34.0M 9s\n", - "243900K .......... .......... .......... .......... .......... 41% 18.0M 9s\n", - "243950K .......... .......... .......... .......... .......... 41% 50.3M 9s\n", - "244000K .......... .......... .......... .......... .......... 41% 47.7M 9s\n", - "244050K .......... .......... .......... .......... .......... 41% 61.5M 9s\n", - "244100K .......... .......... .......... .......... .......... 41% 28.5M 9s\n", - "244150K .......... .......... .......... .......... .......... 41% 42.8M 9s\n", - "244200K .......... .......... .......... .......... .......... 41% 3.87M 9s\n", - "244250K .......... .......... .......... .......... .......... 41% 60.3M 9s\n", - "244300K .......... .......... .......... .......... .......... 41% 63.6M 9s\n", - "244350K .......... .......... .......... .......... .......... 41% 64.0M 9s\n", - "244400K .......... .......... .......... .......... .......... 41% 58.3M 9s\n", - "244450K .......... .......... .......... .......... .......... 41% 5.78M 9s\n", - "244500K .......... .......... .......... 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.......... .......... 41% 50.4M 9s\n", - "245150K .......... .......... .......... .......... .......... 41% 63.9M 9s\n", - "245200K .......... .......... .......... .......... .......... 41% 21.7M 9s\n", - "245250K .......... .......... .......... .......... .......... 41% 44.5M 9s\n", - "245300K .......... .......... .......... .......... .......... 41% 55.4M 9s\n", - "245350K .......... .......... .......... .......... .......... 41% 65.0M 9s\n", - "245400K .......... .......... .......... .......... .......... 41% 24.2M 9s\n", - "245450K .......... .......... .......... .......... .......... 41% 54.3M 9s\n", - "245500K .......... .......... .......... .......... .......... 41% 66.7M 9s\n", - "245550K .......... .......... .......... .......... .......... 41% 69.7M 9s\n", - "245600K .......... .......... .......... .......... .......... 41% 20.5M 9s\n", - "245650K .......... .......... .......... .......... .......... 41% 51.7M 9s\n", - "245700K .......... .......... .......... 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.......... .......... 41% 55.1M 9s\n", - "246950K .......... .......... .......... .......... .......... 41% 66.8M 9s\n", - "247000K .......... .......... .......... .......... .......... 41% 21.4M 9s\n", - "247050K .......... .......... .......... .......... .......... 41% 47.7M 9s\n", - "247100K .......... .......... .......... .......... .......... 41% 60.9M 9s\n", - "247150K .......... .......... .......... .......... .......... 41% 70.8M 9s\n", - "247200K .......... .......... .......... .......... .......... 41% 26.6M 9s\n", - "247250K .......... .......... .......... .......... .......... 41% 44.8M 9s\n", - "247300K .......... .......... .......... .......... .......... 41% 55.1M 9s\n", - "247350K .......... .......... .......... .......... .......... 41% 66.6M 9s\n", - "247400K .......... .......... .......... .......... .......... 41% 27.5M 9s\n", - "247450K .......... .......... .......... .......... .......... 41% 41.2M 9s\n", - "247500K .......... .......... .......... 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.......... .......... 41% 57.3M 9s\n", - "248750K .......... .......... .......... .......... .......... 41% 35.9M 9s\n", - "248800K .......... .......... .......... .......... .......... 41% 52.3M 9s\n", - "248850K .......... .......... .......... .......... .......... 41% 61.5M 9s\n", - "248900K .......... .......... .......... .......... .......... 41% 49.0M 9s\n", - "248950K .......... .......... .......... .......... .......... 41% 49.8M 9s\n", - "249000K .......... .......... .......... .......... .......... 41% 46.2M 9s\n", - "249050K .......... .......... .......... .......... .......... 41% 42.0M 9s\n", - "249100K .......... .......... .......... .......... .......... 41% 46.4M 9s\n", - "249150K .......... .......... .......... .......... .......... 41% 39.4M 9s\n", - "249200K .......... .......... .......... .......... .......... 41% 57.1M 9s\n", - "249250K .......... .......... .......... .......... .......... 41% 54.3M 9s\n", - "249300K .......... .......... .......... .......... .......... 41% 41.9M 9s\n", - "249350K .......... .......... .......... .......... .......... 41% 44.6M 9s\n", - "249400K .......... .......... .......... .......... .......... 41% 33.9M 9s\n", - "249450K .......... .......... .......... .......... .......... 41% 60.1M 9s\n", - "249500K .......... .......... .......... .......... .......... 41% 45.3M 9s\n", - "249550K .......... .......... .......... .......... .......... 41% 51.2M 9s\n", - "249600K .......... .......... .......... .......... .......... 41% 27.7M 9s\n", - "249650K .......... .......... .......... .......... .......... 41% 49.1M 9s\n", - "249700K .......... .......... .......... .......... .......... 41% 55.5M 9s\n", - "249750K .......... .......... .......... .......... .......... 42% 57.1M 9s\n", - "249800K .......... .......... .......... .......... .......... 42% 20.9M 9s\n", - "249850K .......... .......... .......... .......... .......... 42% 52.2M 9s\n", - "249900K .......... .......... .......... .......... .......... 42% 42.6M 9s\n", - "249950K .......... .......... .......... .......... .......... 42% 63.6M 9s\n", - "250000K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", - "250050K .......... .......... .......... .......... .......... 42% 45.0M 9s\n", - "250100K .......... .......... .......... .......... .......... 42% 60.0M 9s\n", - "250150K .......... .......... .......... .......... .......... 42% 55.8M 9s\n", - "250200K .......... .......... .......... .......... .......... 42% 7.38M 9s\n", - "250250K .......... .......... .......... .......... .......... 42% 45.6M 9s\n", - "250300K .......... .......... .......... .......... .......... 42% 53.5M 9s\n", - "250350K .......... .......... .......... .......... .......... 42% 67.2M 9s\n", - "250400K .......... .......... .......... .......... .......... 42% 59.1M 9s\n", - "250450K .......... .......... .......... .......... .......... 42% 25.2M 9s\n", - "250500K .......... .......... .......... .......... .......... 42% 48.1M 9s\n", - "250550K .......... .......... .......... .......... .......... 42% 50.2M 9s\n", - "250600K .......... .......... .......... .......... .......... 42% 57.8M 9s\n", - "250650K .......... .......... .......... .......... .......... 42% 45.4M 9s\n", - "250700K .......... .......... .......... .......... .......... 42% 63.2M 9s\n", - "250750K .......... .......... .......... .......... .......... 42% 48.7M 9s\n", - "250800K .......... .......... .......... .......... .......... 42% 60.3M 9s\n", - "250850K .......... .......... .......... .......... .......... 42% 32.0M 9s\n", - "250900K .......... .......... .......... .......... .......... 42% 56.5M 9s\n", - "250950K .......... .......... .......... .......... .......... 42% 50.6M 9s\n", - "251000K .......... .......... .......... .......... .......... 42% 45.8M 9s\n", - "251050K .......... .......... .......... .......... .......... 42% 69.5M 9s\n", - "251100K .......... .......... .......... .......... .......... 42% 35.4M 9s\n", - "251150K .......... .......... .......... .......... .......... 42% 53.7M 9s\n", - "251200K .......... .......... .......... .......... .......... 42% 46.4M 9s\n", - "251250K .......... .......... .......... .......... .......... 42% 67.3M 9s\n", - "251300K .......... .......... .......... .......... .......... 42% 36.4M 9s\n", - "251350K .......... .......... .......... .......... .......... 42% 38.8M 9s\n", - "251400K .......... .......... .......... .......... .......... 42% 41.6M 9s\n", - "251450K .......... .......... .......... .......... .......... 42% 68.7M 9s\n", - "251500K .......... .......... .......... .......... .......... 42% 34.6M 9s\n", - "251550K .......... .......... .......... .......... .......... 42% 49.9M 9s\n", - "251600K .......... .......... .......... .......... .......... 42% 34.9M 9s\n", - "251650K .......... .......... .......... .......... .......... 42% 70.0M 9s\n", - "251700K .......... .......... .......... .......... .......... 42% 63.7M 9s\n", - "251750K .......... .......... .......... .......... .......... 42% 46.5M 9s\n", - "251800K .......... .......... .......... .......... .......... 42% 39.7M 9s\n", - "251850K .......... .......... .......... .......... .......... 42% 48.9M 9s\n", - "251900K .......... .......... .......... .......... .......... 42% 64.2M 9s\n", - "251950K .......... .......... .......... .......... .......... 42% 43.4M 9s\n", - "252000K .......... .......... .......... .......... .......... 42% 43.8M 9s\n", - "252050K .......... .......... .......... .......... .......... 42% 63.8M 9s\n", - "252100K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", - "252150K .......... .......... .......... .......... .......... 42% 73.6M 9s\n", - "252200K .......... .......... .......... .......... .......... 42% 28.6M 9s\n", - "252250K .......... .......... .......... .......... .......... 42% 57.2M 9s\n", - "252300K .......... .......... .......... .......... .......... 42% 62.0M 9s\n", - "252350K .......... .......... .......... .......... .......... 42% 52.3M 9s\n", - "252400K .......... .......... .......... .......... .......... 42% 39.7M 9s\n", - "252450K .......... .......... .......... .......... .......... 42% 55.2M 9s\n", - "252500K .......... .......... .......... .......... .......... 42% 52.7M 9s\n", - "252550K .......... .......... .......... .......... .......... 42% 50.8M 9s\n", - "252600K .......... .......... .......... .......... .......... 42% 48.8M 9s\n", - "252650K .......... .......... .......... .......... .......... 42% 37.1M 9s\n", - "252700K .......... .......... .......... .......... .......... 42% 51.1M 9s\n", - "252750K .......... .......... .......... .......... .......... 42% 60.5M 9s\n", - "252800K .......... .......... .......... .......... .......... 42% 63.6M 9s\n", - "252850K .......... .......... .......... .......... .......... 42% 35.0M 9s\n", - "252900K .......... .......... .......... .......... .......... 42% 54.8M 9s\n", - "252950K .......... .......... .......... .......... .......... 42% 52.3M 9s\n", - "253000K .......... .......... .......... .......... .......... 42% 56.0M 9s\n", - "253050K .......... .......... .......... .......... .......... 42% 66.1M 9s\n", - "253100K .......... .......... .......... .......... .......... 42% 32.4M 9s\n", - "253150K .......... .......... .......... .......... .......... 42% 46.0M 9s\n", - "253200K .......... .......... .......... .......... .......... 42% 58.7M 9s\n", - "253250K .......... .......... .......... .......... .......... 42% 52.9M 9s\n", - "253300K .......... .......... .......... .......... .......... 42% 34.6M 9s\n", - "253350K .......... .......... .......... .......... .......... 42% 56.9M 9s\n", - "253400K .......... .......... .......... .......... .......... 42% 50.8M 9s\n", - "253450K .......... .......... .......... .......... .......... 42% 3.65M 9s\n", - "253500K .......... .......... .......... .......... .......... 42% 72.8M 9s\n", - "253550K .......... .......... .......... .......... .......... 42% 67.5M 9s\n", - "253600K .......... .......... .......... .......... .......... 42% 58.4M 9s\n", - "253650K .......... .......... .......... .......... .......... 42% 64.4M 9s\n", - "253700K .......... .......... .......... .......... .......... 42% 72.1M 9s\n", - "253750K .......... .......... .......... .......... .......... 42% 32.3M 9s\n", - "253800K .......... .......... .......... .......... .......... 42% 37.9M 9s\n", - "253850K .......... .......... .......... .......... .......... 42% 69.6M 9s\n", - "253900K .......... .......... .......... .......... .......... 42% 38.1M 9s\n", - "253950K .......... .......... .......... .......... .......... 42% 56.0M 9s\n", - "254000K .......... .......... .......... .......... .......... 42% 46.1M 9s\n", - "254050K .......... .......... .......... .......... .......... 42% 51.5M 9s\n", - "254100K .......... .......... .......... .......... .......... 42% 68.0M 9s\n", - "254150K .......... .......... .......... .......... .......... 42% 66.1M 9s\n", - "254200K .......... .......... .......... .......... .......... 42% 31.1M 9s\n", - "254250K .......... .......... .......... .......... .......... 42% 48.5M 9s\n", - "254300K .......... .......... .......... .......... .......... 42% 54.5M 9s\n", - "254350K .......... .......... .......... .......... .......... 42% 62.7M 9s\n", - "254400K .......... .......... .......... .......... .......... 42% 32.0M 9s\n", - "254450K .......... .......... .......... .......... .......... 42% 26.9M 9s\n", - "254500K .......... .......... .......... .......... .......... 42% 39.9M 9s\n", - "254550K .......... .......... .......... .......... .......... 42% 50.2M 9s\n", - "254600K .......... .......... .......... .......... .......... 42% 53.2M 9s\n", - "254650K .......... .......... .......... .......... .......... 42% 47.8M 9s\n", - "254700K .......... .......... .......... .......... .......... 42% 47.7M 9s\n", - "254750K .......... .......... .......... .......... .......... 42% 67.8M 9s\n", - "254800K .......... .......... .......... .......... .......... 42% 54.5M 9s\n", - "254850K .......... .......... .......... .......... .......... 42% 57.5M 9s\n", - "254900K .......... .......... .......... .......... .......... 42% 48.2M 9s\n", - "254950K .......... .......... .......... .......... .......... 42% 65.5M 9s\n", - "255000K .......... .......... .......... .......... .......... 42% 58.9M 9s\n", - "255050K .......... .......... .......... .......... .......... 42% 69.8M 9s\n", - "255100K .......... .......... .......... .......... .......... 42% 64.3M 9s\n", - "255150K .......... .......... .......... .......... .......... 42% 66.3M 9s\n", - "255200K .......... .......... .......... .......... .......... 42% 38.4M 9s\n", - "255250K .......... .......... .......... .......... .......... 42% 54.2M 9s\n", - "255300K .......... .......... .......... .......... .......... 42% 70.5M 9s\n", - "255350K .......... .......... .......... .......... .......... 42% 62.3M 9s\n", - "255400K .......... .......... .......... .......... .......... 42% 31.1M 9s\n", - "255450K .......... .......... .......... .......... .......... 42% 44.4M 9s\n", - "255500K .......... .......... .......... .......... .......... 42% 61.5M 9s\n", - "255550K .......... .......... .......... .......... .......... 42% 69.5M 9s\n", - "255600K .......... .......... .......... .......... .......... 42% 43.7M 9s\n", - "255650K .......... .......... .......... .......... .......... 42% 55.3M 9s\n", - "255700K .......... .......... .......... .......... .......... 43% 48.6M 9s\n", - "255750K .......... .......... .......... .......... .......... 43% 55.8M 9s\n", - "255800K .......... .......... .......... .......... .......... 43% 48.4M 9s\n", - "255850K .......... .......... .......... .......... .......... 43% 61.5M 9s\n", - "255900K .......... .......... .......... .......... .......... 43% 46.8M 9s\n", - "255950K .......... .......... .......... .......... .......... 43% 50.5M 9s\n", - "256000K .......... .......... .......... .......... .......... 43% 52.3M 9s\n", - "256050K .......... .......... .......... .......... .......... 43% 69.7M 9s\n", - "256100K .......... .......... .......... .......... .......... 43% 54.2M 9s\n", - "256150K .......... .......... .......... .......... .......... 43% 46.2M 9s\n", - "256200K .......... .......... .......... .......... .......... 43% 41.6M 9s\n", - "256250K .......... .......... .......... .......... .......... 43% 65.0M 9s\n", - "256300K .......... .......... .......... .......... .......... 43% 63.8M 9s\n", - "256350K .......... .......... .......... .......... .......... 43% 52.5M 9s\n", - "256400K .......... .......... .......... .......... .......... 43% 46.2M 9s\n", - "256450K .......... .......... .......... .......... .......... 43% 49.4M 9s\n", - "256500K .......... .......... .......... .......... .......... 43% 67.0M 9s\n", - "256550K .......... .......... .......... .......... .......... 43% 54.6M 9s\n", - "256600K .......... .......... .......... .......... .......... 43% 43.5M 9s\n", - "256650K .......... .......... .......... .......... .......... 43% 44.4M 9s\n", - "256700K .......... .......... .......... .......... .......... 43% 63.6M 9s\n", - "256750K .......... .......... .......... .......... .......... 43% 56.7M 9s\n", - "256800K .......... .......... .......... .......... .......... 43% 46.4M 9s\n", - "256850K .......... .......... .......... .......... .......... 43% 52.2M 9s\n", - "256900K .......... .......... .......... .......... .......... 43% 45.8M 9s\n", - "256950K .......... .......... .......... .......... .......... 43% 3.83M 9s\n", - "257000K .......... .......... .......... .......... .......... 43% 50.9M 9s\n", - "257050K .......... .......... .......... .......... .......... 43% 70.5M 9s\n", - "257100K .......... .......... .......... .......... .......... 43% 65.5M 9s\n", - "257150K .......... .......... .......... .......... .......... 43% 69.0M 9s\n", - "257200K .......... .......... .......... .......... .......... 43% 64.8M 9s\n", - "257250K .......... .......... .......... .......... .......... 43% 66.1M 9s\n", - "257300K .......... .......... .......... .......... .......... 43% 52.2M 9s\n", - "257350K .......... .......... .......... .......... .......... 43% 52.4M 9s\n", - "257400K .......... .......... .......... .......... .......... 43% 47.3M 9s\n", - "257450K .......... .......... .......... .......... .......... 43% 70.0M 9s\n", - "257500K .......... .......... .......... .......... .......... 43% 70.1M 9s\n", - "257550K .......... .......... .......... .......... .......... 43% 51.1M 9s\n", - "257600K .......... .......... .......... .......... .......... 43% 40.9M 9s\n", - "257650K .......... .......... .......... .......... .......... 43% 51.2M 9s\n", - "257700K .......... .......... .......... 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.......... .......... 43% 56.5M 8s\n", - "260150K .......... .......... .......... .......... .......... 43% 66.7M 8s\n", - "260200K .......... .......... .......... .......... .......... 43% 52.4M 8s\n", - "260250K .......... .......... .......... .......... .......... 43% 53.8M 8s\n", - "260300K .......... .......... .......... .......... .......... 43% 53.3M 8s\n", - "260350K .......... .......... .......... .......... .......... 43% 53.5M 8s\n", - "260400K .......... .......... .......... .......... .......... 43% 58.8M 8s\n", - "260450K .......... .......... .......... .......... .......... 43% 54.7M 8s\n", - "260500K .......... .......... .......... .......... .......... 43% 57.1M 8s\n", - "260550K .......... .......... .......... .......... .......... 43% 57.6M 8s\n", - "260600K .......... .......... .......... .......... .......... 43% 43.4M 8s\n", - "260650K .......... .......... .......... .......... .......... 43% 67.6M 8s\n", - "260700K .......... .......... .......... .......... .......... 43% 58.9M 8s\n", - "260750K .......... .......... .......... .......... .......... 43% 58.0M 8s\n", - "260800K .......... .......... .......... .......... .......... 43% 48.2M 8s\n", - "260850K .......... .......... .......... .......... .......... 43% 52.6M 8s\n", - "260900K .......... .......... .......... .......... .......... 43% 59.5M 8s\n", - "260950K .......... .......... .......... .......... .......... 43% 62.0M 8s\n", - "261000K .......... .......... .......... .......... .......... 43% 47.1M 8s\n", - "261050K .......... .......... .......... .......... .......... 43% 49.6M 8s\n", - "261100K .......... .......... .......... .......... .......... 43% 43.3M 8s\n", - "261150K .......... .......... .......... .......... .......... 43% 69.0M 8s\n", - "261200K .......... .......... .......... .......... .......... 43% 48.7M 8s\n", - "261250K .......... .......... .......... .......... .......... 43% 52.4M 8s\n", - "261300K .......... .......... .......... .......... .......... 43% 48.5M 8s\n", - "261350K .......... .......... .......... .......... .......... 43% 52.5M 8s\n", - "261400K .......... .......... .......... .......... .......... 43% 57.3M 8s\n", - "261450K .......... .......... .......... .......... .......... 43% 55.7M 8s\n", - "261500K .......... .......... .......... .......... .......... 43% 52.0M 8s\n", - "261550K .......... .......... .......... .......... .......... 43% 52.6M 8s\n", - "261600K .......... .......... .......... .......... .......... 43% 47.2M 8s\n", - "261650K .......... .......... .......... .......... .......... 44% 4.17M 8s\n", - "261700K .......... .......... .......... .......... .......... 44% 63.7M 8s\n", - "261750K .......... .......... .......... .......... .......... 44% 65.6M 8s\n", - "261800K .......... .......... .......... .......... .......... 44% 56.8M 8s\n", - "261850K .......... .......... .......... .......... .......... 44% 63.6M 8s\n", - "261900K .......... .......... .......... .......... .......... 44% 69.6M 8s\n", - "261950K .......... .......... .......... .......... .......... 44% 64.1M 8s\n", - "262000K .......... .......... .......... .......... .......... 44% 58.4M 8s\n", - "262050K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", - "262100K .......... .......... .......... .......... .......... 44% 59.8M 8s\n", - "262150K .......... .......... .......... .......... .......... 44% 68.2M 8s\n", - "262200K .......... .......... .......... .......... .......... 44% 56.9M 8s\n", - "262250K .......... .......... .......... .......... .......... 44% 64.2M 8s\n", - "262300K .......... .......... .......... .......... .......... 44% 51.9M 8s\n", - "262350K .......... .......... .......... .......... .......... 44% 58.1M 8s\n", - "262400K .......... .......... .......... .......... .......... 44% 51.6M 8s\n", - "262450K .......... .......... .......... .......... .......... 44% 67.5M 8s\n", - "262500K .......... .......... .......... .......... .......... 44% 65.1M 8s\n", - "262550K .......... .......... .......... .......... .......... 44% 51.0M 8s\n", - "262600K .......... .......... .......... .......... .......... 44% 40.5M 8s\n", - "262650K .......... .......... .......... .......... .......... 44% 57.9M 8s\n", - "262700K .......... .......... .......... .......... .......... 44% 58.4M 8s\n", - "262750K .......... .......... .......... .......... .......... 44% 57.3M 8s\n", - "262800K .......... .......... .......... .......... .......... 44% 45.3M 8s\n", - "262850K .......... .......... .......... .......... .......... 44% 57.6M 8s\n", - "262900K .......... .......... .......... .......... .......... 44% 54.2M 8s\n", - "262950K .......... .......... .......... .......... .......... 44% 59.3M 8s\n", - "263000K .......... .......... .......... .......... .......... 44% 51.3M 8s\n", - "263050K .......... .......... .......... .......... .......... 44% 50.2M 8s\n", - "263100K .......... .......... .......... .......... .......... 44% 54.7M 8s\n", - "263150K .......... .......... .......... .......... .......... 44% 66.2M 8s\n", - "263200K .......... .......... .......... .......... .......... 44% 59.3M 8s\n", - "263250K .......... .......... .......... .......... .......... 44% 61.2M 8s\n", - "263300K .......... .......... .......... .......... .......... 44% 63.7M 8s\n", - "263350K .......... .......... .......... .......... .......... 44% 52.3M 8s\n", - "263400K .......... .......... .......... .......... .......... 44% 42.5M 8s\n", - "263450K .......... .......... .......... .......... .......... 44% 66.2M 8s\n", - "263500K .......... .......... .......... .......... .......... 44% 53.6M 8s\n", - "263550K .......... .......... .......... .......... .......... 44% 52.2M 8s\n", - "263600K .......... .......... .......... .......... .......... 44% 47.5M 8s\n", - "263650K .......... .......... .......... .......... .......... 44% 46.5M 8s\n", - "263700K .......... .......... .......... .......... .......... 44% 67.8M 8s\n", - "263750K .......... .......... .......... .......... .......... 44% 57.4M 8s\n", - "263800K .......... .......... .......... .......... .......... 44% 39.3M 8s\n", - "263850K .......... .......... .......... .......... .......... 44% 47.7M 8s\n", - "263900K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", - "263950K .......... .......... .......... .......... .......... 44% 60.6M 8s\n", - "264000K .......... .......... .......... .......... .......... 44% 44.3M 8s\n", - "264050K .......... .......... .......... .......... .......... 44% 54.2M 8s\n", - "264100K .......... .......... .......... .......... .......... 44% 48.5M 8s\n", - "264150K .......... .......... .......... .......... .......... 44% 62.4M 8s\n", - "264200K .......... .......... .......... .......... .......... 44% 46.3M 8s\n", - "264250K .......... .......... .......... .......... .......... 44% 54.3M 8s\n", - "264300K .......... .......... .......... .......... .......... 44% 49.8M 8s\n", - "264350K .......... .......... .......... .......... .......... 44% 46.4M 8s\n", - "264400K .......... .......... .......... .......... .......... 44% 53.6M 8s\n", - "264450K .......... .......... .......... .......... .......... 44% 56.9M 8s\n", - "264500K .......... .......... .......... .......... .......... 44% 56.3M 8s\n", - "264550K .......... .......... .......... .......... .......... 44% 50.8M 8s\n", - "264600K .......... .......... .......... .......... .......... 44% 45.0M 8s\n", - "264650K .......... .......... .......... .......... .......... 44% 52.1M 8s\n", - "264700K .......... .......... .......... .......... .......... 44% 53.6M 8s\n", - "264750K .......... .......... .......... .......... .......... 44% 51.5M 8s\n", - "264800K .......... .......... .......... .......... .......... 44% 58.0M 8s\n", - "264850K .......... .......... .......... .......... .......... 44% 46.6M 8s\n", - "264900K .......... .......... .......... .......... .......... 44% 67.9M 8s\n", - "264950K .......... .......... .......... .......... .......... 44% 57.3M 8s\n", - "265000K .......... .......... .......... .......... .......... 44% 44.4M 8s\n", - "265050K .......... .......... .......... .......... .......... 44% 55.6M 8s\n", - "265100K .......... .......... .......... .......... .......... 44% 54.3M 8s\n", - "265150K .......... .......... .......... .......... .......... 44% 64.2M 8s\n", - "265200K .......... .......... .......... .......... .......... 44% 61.5M 8s\n", - "265250K .......... .......... .......... .......... .......... 44% 48.8M 8s\n", - "265300K .......... .......... .......... .......... .......... 44% 46.4M 8s\n", - "265350K .......... .......... .......... .......... .......... 44% 46.4M 8s\n", - "265400K .......... .......... .......... .......... .......... 44% 56.5M 8s\n", - "265450K .......... .......... .......... .......... .......... 44% 50.6M 8s\n", - "265500K .......... .......... .......... .......... .......... 44% 5.21M 8s\n", - "265550K .......... .......... .......... .......... .......... 44% 68.2M 8s\n", - "265600K .......... .......... .......... .......... .......... 44% 65.1M 8s\n", - "265650K .......... .......... .......... .......... .......... 44% 69.3M 8s\n", - "265700K .......... .......... .......... .......... .......... 44% 70.4M 8s\n", - "265750K .......... .......... .......... .......... .......... 44% 69.9M 8s\n", - "265800K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", - "265850K .......... .......... .......... .......... .......... 44% 57.2M 8s\n", - "265900K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", - "265950K .......... .......... .......... .......... .......... 44% 61.9M 8s\n", - "266000K .......... .......... .......... .......... .......... 44% 61.7M 8s\n", - "266050K .......... .......... .......... .......... .......... 44% 64.7M 8s\n", - "266100K .......... .......... .......... .......... .......... 44% 59.1M 8s\n", - "266150K .......... .......... .......... .......... .......... 44% 51.7M 8s\n", - "266200K .......... .......... .......... .......... .......... 44% 42.5M 8s\n", - "266250K .......... .......... .......... .......... .......... 44% 67.4M 8s\n", - "266300K .......... .......... .......... .......... .......... 44% 65.2M 8s\n", - "266350K .......... .......... .......... .......... .......... 44% 61.4M 8s\n", - "266400K .......... .......... .......... .......... .......... 44% 12.3M 8s\n", - "266450K .......... .......... .......... .......... .......... 44% 54.8M 8s\n", - "266500K .......... .......... .......... .......... .......... 44% 68.0M 8s\n", - "266550K .......... .......... .......... .......... .......... 44% 62.9M 8s\n", - "266600K .......... .......... .......... .......... .......... 44% 57.7M 8s\n", - "266650K .......... .......... .......... .......... .......... 44% 18.7M 8s\n", - "266700K .......... .......... .......... .......... .......... 44% 60.0M 8s\n", - "266750K .......... .......... .......... .......... .......... 44% 67.1M 8s\n", - "266800K .......... .......... .......... .......... .......... 44% 55.4M 8s\n", - "266850K .......... .......... .......... .......... .......... 44% 69.5M 8s\n", - "266900K .......... .......... .......... .......... .......... 44% 70.4M 8s\n", - "266950K .......... .......... .......... .......... .......... 44% 50.9M 8s\n", - "267000K .......... .......... .......... .......... .......... 44% 39.0M 8s\n", - "267050K .......... .......... .......... .......... .......... 44% 68.5M 8s\n", - "267100K .......... .......... .......... .......... .......... 44% 66.0M 8s\n", - "267150K .......... .......... .......... .......... .......... 44% 70.5M 8s\n", - "267200K .......... .......... .......... .......... .......... 44% 45.0M 8s\n", - "267250K .......... .......... .......... .......... .......... 44% 50.9M 8s\n", - "267300K .......... .......... .......... .......... .......... 44% 61.5M 8s\n", - "267350K .......... .......... .......... .......... .......... 44% 67.1M 8s\n", - "267400K .......... .......... .......... .......... .......... 44% 57.2M 8s\n", - "267450K .......... .......... .......... .......... .......... 44% 52.7M 8s\n", - "267500K .......... .......... .......... .......... .......... 44% 47.3M 8s\n", - "267550K .......... .......... .......... .......... .......... 44% 52.0M 8s\n", - "267600K .......... .......... .......... .......... .......... 45% 58.6M 8s\n", - "267650K .......... .......... .......... .......... .......... 45% 68.6M 8s\n", - "267700K .......... .......... .......... .......... .......... 45% 56.7M 8s\n", - "267750K .......... .......... .......... .......... .......... 45% 49.0M 8s\n", - "267800K .......... .......... .......... .......... .......... 45% 42.8M 8s\n", - "267850K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", - "267900K .......... .......... .......... .......... .......... 45% 65.3M 8s\n", - "267950K .......... .......... .......... .......... .......... 45% 54.9M 8s\n", - "268000K .......... .......... .......... .......... .......... 45% 39.2M 8s\n", - "268050K .......... .......... .......... .......... .......... 45% 46.8M 8s\n", - "268100K .......... .......... .......... .......... .......... 45% 57.4M 8s\n", - "268150K .......... .......... .......... .......... .......... 45% 74.6M 8s\n", - "268200K .......... .......... .......... .......... .......... 45% 45.7M 8s\n", - "268250K .......... .......... .......... .......... .......... 45% 8.16M 8s\n", - "268300K .......... .......... .......... .......... .......... 45% 66.1M 8s\n", - "268350K .......... .......... .......... .......... .......... 45% 46.8M 8s\n", - "268400K .......... .......... .......... .......... .......... 45% 56.1M 8s\n", - "268450K .......... .......... .......... .......... .......... 45% 66.6M 8s\n", - "268500K .......... .......... .......... .......... .......... 45% 61.9M 8s\n", - "268550K .......... .......... .......... .......... .......... 45% 52.0M 8s\n", - "268600K .......... .......... .......... .......... .......... 45% 37.0M 8s\n", - "268650K .......... .......... .......... .......... .......... 45% 64.3M 8s\n", - "268700K .......... .......... .......... .......... .......... 45% 67.7M 8s\n", - "268750K .......... .......... .......... .......... .......... 45% 65.8M 8s\n", - "268800K .......... .......... .......... .......... .......... 45% 43.5M 8s\n", - "268850K .......... .......... .......... .......... .......... 45% 42.6M 8s\n", - "268900K .......... .......... .......... .......... .......... 45% 59.8M 8s\n", - "268950K .......... .......... .......... .......... .......... 45% 64.4M 8s\n", - "269000K .......... .......... .......... .......... .......... 45% 50.6M 8s\n", - "269050K .......... .......... .......... .......... .......... 45% 46.2M 8s\n", - "269100K .......... .......... .......... .......... .......... 45% 47.5M 8s\n", - "269150K .......... .......... .......... .......... .......... 45% 59.2M 8s\n", - "269200K .......... .......... .......... .......... .......... 45% 64.6M 8s\n", - "269250K .......... .......... .......... .......... .......... 45% 73.6M 8s\n", - "269300K .......... .......... .......... .......... .......... 45% 54.0M 8s\n", - "269350K .......... .......... .......... .......... .......... 45% 65.1M 8s\n", - "269400K .......... .......... .......... .......... .......... 45% 46.2M 8s\n", - "269450K .......... .......... .......... .......... .......... 45% 64.5M 8s\n", - "269500K .......... .......... .......... .......... .......... 45% 65.3M 8s\n", - "269550K .......... .......... .......... .......... .......... 45% 68.0M 8s\n", - "269600K .......... .......... .......... .......... .......... 45% 50.8M 8s\n", - "269650K .......... .......... .......... .......... .......... 45% 59.2M 8s\n", - "269700K .......... .......... .......... .......... .......... 45% 65.8M 8s\n", - "269750K .......... .......... .......... .......... .......... 45% 69.3M 8s\n", - "269800K .......... .......... .......... .......... .......... 45% 55.6M 8s\n", - "269850K .......... .......... .......... .......... .......... 45% 58.0M 8s\n", - "269900K .......... .......... .......... .......... .......... 45% 54.5M 8s\n", - "269950K .......... .......... .......... .......... .......... 45% 50.4M 8s\n", - "270000K .......... .......... .......... .......... .......... 45% 55.5M 8s\n", - "270050K .......... .......... .......... .......... .......... 45% 62.7M 8s\n", - "270100K .......... .......... .......... .......... .......... 45% 68.0M 8s\n", - "270150K .......... .......... .......... .......... .......... 45% 59.6M 8s\n", - "270200K .......... .......... .......... .......... .......... 45% 42.6M 8s\n", - "270250K .......... .......... .......... .......... .......... 45% 55.3M 8s\n", - "270300K .......... .......... .......... .......... .......... 45% 69.9M 8s\n", - "270350K .......... .......... .......... .......... .......... 45% 75.2M 8s\n", - "270400K .......... .......... .......... .......... .......... 45% 55.3M 8s\n", - "270450K .......... .......... .......... .......... .......... 45% 53.1M 8s\n", - "270500K .......... .......... .......... .......... .......... 45% 59.1M 8s\n", - "270550K .......... .......... .......... .......... .......... 45% 57.8M 8s\n", - "270600K .......... .......... .......... .......... .......... 45% 7.64M 8s\n", - "270650K .......... .......... .......... .......... .......... 45% 62.9M 8s\n", - "270700K .......... .......... .......... .......... .......... 45% 73.2M 8s\n", - "270750K .......... .......... .......... .......... .......... 45% 66.2M 8s\n", - "270800K .......... .......... .......... .......... .......... 45% 65.0M 8s\n", - "270850K .......... .......... .......... .......... .......... 45% 62.6M 8s\n", - "270900K .......... .......... .......... .......... .......... 45% 57.8M 8s\n", - "270950K .......... .......... .......... .......... .......... 45% 44.7M 8s\n", - "271000K .......... .......... .......... .......... .......... 45% 44.0M 8s\n", - "271050K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", - "271100K .......... .......... .......... .......... .......... 45% 66.6M 8s\n", - "271150K .......... .......... .......... .......... .......... 45% 57.3M 8s\n", - "271200K .......... .......... .......... .......... .......... 45% 44.9M 8s\n", - "271250K .......... .......... .......... .......... .......... 45% 46.3M 8s\n", - "271300K .......... .......... .......... .......... .......... 45% 66.7M 8s\n", - "271350K .......... .......... .......... .......... .......... 45% 68.1M 8s\n", - "271400K .......... .......... .......... .......... .......... 45% 47.0M 8s\n", - "271450K .......... .......... .......... .......... .......... 45% 54.4M 8s\n", - "271500K .......... .......... .......... .......... .......... 45% 54.8M 8s\n", - "271550K .......... .......... .......... .......... .......... 45% 60.4M 8s\n", - "271600K .......... .......... .......... .......... .......... 45% 61.2M 8s\n", - "271650K .......... .......... .......... .......... .......... 45% 65.6M 8s\n", - "271700K .......... .......... .......... .......... .......... 45% 58.5M 8s\n", - "271750K .......... .......... .......... .......... .......... 45% 56.6M 8s\n", - "271800K .......... .......... .......... .......... .......... 45% 45.8M 8s\n", - "271850K .......... .......... .......... .......... .......... 45% 60.0M 8s\n", - "271900K .......... .......... .......... .......... .......... 45% 70.4M 8s\n", - "271950K .......... .......... .......... .......... .......... 45% 59.7M 8s\n", - "272000K .......... .......... .......... .......... .......... 45% 45.7M 8s\n", - "272050K .......... .......... .......... .......... .......... 45% 47.9M 8s\n", - "272100K .......... .......... .......... .......... .......... 45% 67.8M 8s\n", - "272150K .......... .......... .......... .......... .......... 45% 58.8M 8s\n", - "272200K .......... .......... .......... .......... .......... 45% 44.2M 8s\n", - "272250K .......... .......... .......... .......... .......... 45% 50.2M 8s\n", - "272300K .......... .......... .......... .......... .......... 45% 51.7M 8s\n", - "272350K .......... .......... .......... .......... .......... 45% 63.1M 8s\n", - "272400K .......... .......... .......... .......... .......... 45% 52.0M 8s\n", - "272450K .......... .......... .......... .......... .......... 45% 45.8M 8s\n", - "272500K .......... .......... .......... .......... .......... 45% 47.1M 8s\n", - "272550K .......... .......... .......... .......... .......... 45% 49.9M 8s\n", - "272600K .......... .......... .......... .......... .......... 45% 56.9M 8s\n", - "272650K .......... .......... .......... .......... .......... 45% 54.6M 8s\n", - "272700K .......... .......... .......... .......... .......... 45% 47.9M 8s\n", - "272750K .......... .......... .......... .......... .......... 45% 11.1M 8s\n", - "272800K .......... .......... .......... .......... .......... 45% 53.2M 8s\n", - "272850K .......... .......... .......... .......... .......... 45% 58.8M 8s\n", - "272900K .......... .......... .......... .......... .......... 45% 67.6M 8s\n", - "272950K .......... .......... .......... .......... .......... 45% 66.4M 8s\n", - "273000K .......... .......... .......... .......... .......... 45% 57.4M 8s\n", - "273050K .......... .......... .......... .......... .......... 45% 51.9M 8s\n", - "273100K .......... .......... .......... .......... .......... 45% 44.8M 8s\n", - "273150K .......... .......... .......... .......... .......... 45% 58.1M 8s\n", - "273200K .......... .......... .......... .......... .......... 45% 59.8M 8s\n", - "273250K .......... .......... .......... .......... .......... 45% 63.6M 8s\n", - "273300K .......... .......... .......... .......... .......... 45% 47.0M 8s\n", - "273350K .......... .......... .......... .......... .......... 45% 37.0M 8s\n", - "273400K .......... .......... .......... .......... .......... 45% 17.2M 8s\n", - "273450K .......... .......... .......... .......... .......... 45% 68.6M 8s\n", - "273500K .......... .......... .......... .......... .......... 45% 60.4M 8s\n", - "273550K .......... .......... .......... .......... .......... 46% 47.5M 8s\n", - "273600K .......... .......... .......... .......... .......... 46% 51.6M 8s\n", - "273650K .......... .......... .......... .......... .......... 46% 61.5M 8s\n", - "273700K .......... .......... .......... .......... .......... 46% 34.8M 8s\n", - "273750K .......... .......... .......... .......... .......... 46% 57.6M 8s\n", - "273800K .......... .......... .......... .......... .......... 46% 57.8M 8s\n", - "273850K .......... .......... .......... .......... .......... 46% 67.3M 8s\n", - "273900K .......... .......... .......... .......... .......... 46% 62.8M 8s\n", - "273950K .......... .......... .......... .......... .......... 46% 69.0M 8s\n", - "274000K .......... .......... .......... .......... .......... 46% 51.9M 8s\n", - "274050K .......... .......... .......... .......... .......... 46% 66.3M 8s\n", - "274100K .......... .......... .......... .......... .......... 46% 52.0M 8s\n", - "274150K .......... .......... .......... .......... .......... 46% 50.0M 8s\n", - "274200K .......... .......... .......... .......... .......... 46% 52.9M 8s\n", - "274250K .......... .......... .......... .......... .......... 46% 50.8M 8s\n", - "274300K .......... .......... .......... .......... .......... 46% 52.2M 8s\n", - "274350K .......... .......... .......... .......... .......... 46% 53.1M 8s\n", - "274400K .......... .......... .......... .......... .......... 46% 43.1M 8s\n", - "274450K .......... .......... .......... .......... .......... 46% 60.8M 8s\n", - "274500K .......... .......... .......... .......... .......... 46% 13.0M 8s\n", - "274550K .......... .......... .......... .......... .......... 46% 59.8M 8s\n", - "274600K .......... .......... .......... .......... .......... 46% 56.3M 8s\n", - "274650K .......... .......... .......... .......... .......... 46% 64.8M 8s\n", - "274700K .......... .......... .......... .......... .......... 46% 65.5M 8s\n", - "274750K .......... .......... .......... .......... .......... 46% 52.0M 8s\n", - "274800K .......... .......... .......... .......... .......... 46% 43.0M 8s\n", - "274850K .......... .......... .......... .......... .......... 46% 46.1M 8s\n", - "274900K .......... .......... .......... .......... .......... 46% 66.7M 8s\n", - "274950K .......... .......... .......... .......... .......... 46% 66.7M 8s\n", - "275000K .......... .......... .......... .......... .......... 46% 40.9M 8s\n", - "275050K .......... .......... .......... .......... .......... 46% 44.5M 8s\n", - "275100K .......... .......... .......... .......... .......... 46% 57.2M 8s\n", - "275150K .......... .......... .......... .......... .......... 46% 64.4M 8s\n", - "275200K .......... .......... .......... .......... .......... 46% 49.9M 8s\n", - "275250K .......... .......... .......... .......... .......... 46% 61.7M 8s\n", - "275300K .......... .......... .......... .......... .......... 46% 64.0M 8s\n", - "275350K .......... .......... .......... .......... .......... 46% 57.7M 8s\n", - "275400K .......... .......... .......... .......... .......... 46% 38.4M 8s\n", - "275450K .......... .......... .......... .......... .......... 46% 53.1M 8s\n", - "275500K .......... .......... .......... .......... .......... 46% 63.8M 8s\n", - "275550K .......... .......... .......... .......... .......... 46% 54.5M 8s\n", - "275600K .......... .......... .......... .......... .......... 46% 50.4M 8s\n", - "275650K .......... .......... .......... .......... .......... 46% 53.8M 8s\n", - "275700K .......... .......... .......... .......... .......... 46% 61.0M 8s\n", - "275750K .......... .......... .......... .......... .......... 46% 50.1M 8s\n", - "275800K .......... .......... .......... .......... .......... 46% 57.3M 8s\n", - "275850K .......... .......... .......... .......... .......... 46% 72.2M 8s\n", - "275900K .......... .......... .......... .......... .......... 46% 57.8M 8s\n", - "275950K .......... .......... .......... .......... .......... 46% 45.3M 8s\n", - "276000K .......... .......... .......... .......... .......... 46% 47.8M 8s\n", - "276050K .......... .......... .......... .......... .......... 46% 61.4M 8s\n", - "276100K .......... .......... .......... .......... .......... 46% 68.0M 8s\n", - "276150K .......... .......... .......... .......... .......... 46% 53.8M 8s\n", - "276200K .......... .......... .......... .......... .......... 46% 40.1M 8s\n", - "276250K .......... .......... .......... .......... .......... 46% 54.4M 8s\n", - "276300K .......... .......... .......... .......... .......... 46% 62.2M 8s\n", - "276350K .......... .......... .......... .......... .......... 46% 63.8M 8s\n", - "276400K .......... .......... .......... .......... .......... 46% 52.1M 8s\n", - "276450K .......... .......... .......... .......... .......... 46% 47.3M 8s\n", - "276500K .......... .......... .......... .......... .......... 46% 52.2M 8s\n", - "276550K .......... .......... .......... .......... .......... 46% 70.5M 8s\n", - "276600K .......... .......... .......... .......... .......... 46% 59.1M 8s\n", - "276650K .......... .......... .......... .......... .......... 46% 58.5M 8s\n", - "276700K .......... .......... .......... .......... .......... 46% 45.1M 8s\n", - "276750K .......... .......... .......... .......... .......... 46% 49.2M 8s\n", - "276800K .......... .......... .......... .......... .......... 46% 55.1M 8s\n", - "276850K .......... .......... .......... .......... .......... 46% 66.5M 8s\n", - "276900K .......... .......... .......... .......... .......... 46% 52.9M 8s\n", - "276950K .......... .......... .......... .......... .......... 46% 46.9M 8s\n", - "277000K .......... .......... .......... .......... .......... 46% 42.3M 8s\n", - "277050K .......... .......... .......... .......... .......... 46% 64.2M 8s\n", - "277100K .......... .......... .......... .......... .......... 46% 57.9M 8s\n", - "277150K .......... .......... .......... .......... .......... 46% 51.7M 8s\n", - "277200K .......... .......... .......... .......... .......... 46% 50.8M 8s\n", - "277250K .......... .......... .......... .......... .......... 46% 52.7M 8s\n", - "277300K .......... .......... .......... .......... .......... 46% 54.9M 8s\n", - "277350K .......... .......... .......... .......... .......... 46% 52.3M 8s\n", - "277400K .......... .......... .......... .......... .......... 46% 45.2M 8s\n", - "277450K .......... .......... .......... .......... .......... 46% 53.8M 8s\n", - "277500K .......... .......... .......... .......... .......... 46% 50.3M 8s\n", - "277550K .......... .......... .......... .......... .......... 46% 72.3M 8s\n", - "277600K .......... .......... .......... .......... .......... 46% 59.2M 8s\n", - "277650K .......... .......... .......... .......... .......... 46% 57.7M 8s\n", - "277700K .......... .......... .......... .......... .......... 46% 48.3M 8s\n", - "277750K .......... .......... .......... .......... .......... 46% 58.3M 8s\n", - "277800K .......... .......... .......... .......... .......... 46% 45.6M 8s\n", - "277850K .......... .......... .......... .......... .......... 46% 56.9M 8s\n", - "277900K .......... .......... .......... .......... .......... 46% 58.5M 8s\n", - "277950K .......... .......... .......... .......... .......... 46% 55.5M 8s\n", - "278000K .......... .......... .......... .......... .......... 46% 3.21M 8s\n", - "278050K .......... .......... .......... .......... .......... 46% 62.9M 8s\n", - "278100K .......... .......... .......... .......... .......... 46% 65.4M 8s\n", - "278150K .......... .......... .......... .......... .......... 46% 11.2M 8s\n", - "278200K .......... .......... .......... .......... .......... 46% 47.9M 8s\n", - "278250K .......... .......... .......... .......... .......... 46% 66.9M 8s\n", - "278300K .......... .......... .......... .......... .......... 46% 66.7M 8s\n", - "278350K .......... .......... .......... .......... .......... 46% 3.92M 8s\n", - "278400K .......... .......... .......... .......... .......... 46% 55.5M 8s\n", - "278450K .......... .......... .......... .......... .......... 46% 66.6M 8s\n", - "278500K .......... .......... .......... .......... .......... 46% 60.3M 8s\n", - "278550K .......... .......... .......... .......... .......... 46% 64.3M 8s\n", - "278600K .......... .......... .......... .......... .......... 46% 49.7M 8s\n", - "278650K .......... .......... .......... .......... .......... 46% 44.2M 8s\n", - "278700K .......... .......... .......... .......... .......... 46% 52.6M 8s\n", - "278750K .......... .......... .......... .......... .......... 46% 60.3M 8s\n", - "278800K .......... .......... .......... .......... .......... 46% 58.6M 8s\n", - "278850K .......... .......... .......... .......... .......... 46% 64.1M 8s\n", - "278900K .......... .......... .......... .......... .......... 46% 46.5M 8s\n", - "278950K .......... .......... .......... .......... .......... 46% 50.0M 8s\n", - "279000K .......... .......... .......... .......... .......... 46% 54.8M 8s\n", - "279050K .......... .......... .......... .......... .......... 46% 69.0M 8s\n", - "279100K .......... .......... .......... .......... .......... 46% 66.6M 8s\n", - "279150K .......... .......... .......... .......... .......... 46% 47.9M 8s\n", - "279200K .......... .......... .......... .......... .......... 46% 43.8M 8s\n", - "279250K .......... .......... .......... .......... .......... 46% 64.4M 8s\n", - "279300K .......... .......... .......... .......... .......... 46% 65.2M 8s\n", - "279350K .......... .......... .......... .......... .......... 46% 65.3M 8s\n", - "279400K .......... .......... .......... .......... .......... 46% 39.5M 8s\n", - "279450K .......... .......... .......... .......... .......... 46% 48.0M 8s\n", - "279500K .......... .......... .......... .......... .......... 47% 65.0M 8s\n", - "279550K .......... .......... .......... .......... .......... 47% 62.1M 8s\n", - "279600K .......... .......... .......... .......... .......... 47% 58.3M 8s\n", - "279650K .......... .......... .......... .......... .......... 47% 56.5M 8s\n", - "279700K .......... .......... .......... .......... .......... 47% 45.8M 8s\n", - "279750K .......... .......... .......... .......... .......... 47% 60.6M 8s\n", - "279800K .......... .......... .......... .......... .......... 47% 55.6M 8s\n", - "279850K .......... .......... .......... .......... .......... 47% 60.9M 8s\n", - "279900K .......... .......... .......... .......... .......... 47% 59.3M 8s\n", - "279950K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", - "280000K .......... .......... .......... .......... .......... 47% 48.6M 8s\n", - "280050K .......... .......... .......... .......... .......... 47% 64.9M 8s\n", - "280100K .......... .......... .......... .......... .......... 47% 72.0M 8s\n", - "280150K .......... .......... .......... .......... .......... 47% 60.6M 8s\n", - "280200K .......... .......... .......... .......... .......... 47% 38.1M 8s\n", - "280250K .......... .......... .......... .......... .......... 47% 54.5M 8s\n", - "280300K .......... .......... .......... .......... .......... 47% 5.82M 8s\n", - "280350K .......... .......... .......... .......... .......... 47% 71.2M 8s\n", - "280400K .......... .......... .......... .......... .......... 47% 59.3M 8s\n", - "280450K .......... .......... .......... .......... .......... 47% 61.7M 8s\n", - "280500K .......... .......... .......... .......... .......... 47% 65.3M 8s\n", - "280550K .......... .......... .......... .......... .......... 47% 66.4M 8s\n", - "280600K .......... .......... .......... .......... .......... 47% 40.7M 8s\n", - "280650K .......... .......... .......... .......... .......... 47% 48.4M 8s\n", - "280700K .......... .......... .......... .......... .......... 47% 59.2M 8s\n", - "280750K .......... .......... .......... .......... .......... 47% 63.1M 8s\n", - "280800K .......... .......... .......... .......... .......... 47% 60.0M 8s\n", - "280850K .......... .......... .......... .......... .......... 47% 51.3M 8s\n", - "280900K .......... .......... .......... .......... .......... 47% 48.4M 8s\n", - "280950K .......... .......... .......... .......... .......... 47% 58.0M 8s\n", - "281000K .......... .......... .......... .......... .......... 47% 56.7M 8s\n", - "281050K .......... .......... .......... .......... .......... 47% 68.4M 8s\n", - "281100K .......... .......... .......... .......... .......... 47% 55.3M 8s\n", - "281150K .......... .......... .......... .......... .......... 47% 52.6M 8s\n", - "281200K .......... .......... .......... .......... .......... 47% 47.6M 8s\n", - "281250K .......... .......... .......... .......... .......... 47% 68.5M 8s\n", - "281300K .......... .......... .......... .......... .......... 47% 65.8M 8s\n", - "281350K .......... .......... .......... .......... .......... 47% 54.2M 8s\n", - "281400K .......... .......... .......... .......... .......... 47% 39.8M 8s\n", - "281450K .......... .......... .......... .......... .......... 47% 2.98M 8s\n", - "281500K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", - "281550K .......... .......... .......... .......... .......... 47% 63.7M 8s\n", - "281600K .......... .......... .......... .......... .......... 47% 54.7M 8s\n", - "281650K .......... .......... .......... .......... .......... 47% 65.6M 8s\n", - "281700K .......... .......... .......... .......... .......... 47% 70.2M 8s\n", - "281750K .......... .......... .......... .......... .......... 47% 49.7M 8s\n", - "281800K .......... .......... .......... .......... .......... 47% 38.7M 8s\n", - "281850K .......... .......... .......... .......... .......... 47% 61.0M 8s\n", - "281900K .......... .......... .......... .......... .......... 47% 65.7M 8s\n", - "281950K .......... .......... .......... .......... .......... 47% 67.2M 8s\n", - "282000K .......... .......... .......... .......... .......... 47% 53.4M 8s\n", - "282050K .......... .......... .......... .......... .......... 47% 46.4M 8s\n", - "282100K .......... .......... .......... .......... .......... 47% 48.7M 8s\n", - "282150K .......... .......... .......... .......... .......... 47% 17.6M 8s\n", - "282200K .......... .......... .......... .......... .......... 47% 42.1M 8s\n", - "282250K .......... .......... .......... .......... .......... 47% 51.9M 8s\n", - "282300K .......... .......... .......... .......... .......... 47% 65.1M 8s\n", - "282350K .......... .......... .......... .......... .......... 47% 62.6M 8s\n", - "282400K .......... .......... .......... .......... .......... 47% 60.1M 8s\n", - "282450K .......... .......... .......... .......... .......... 47% 49.0M 8s\n", - "282500K .......... .......... .......... .......... .......... 47% 47.7M 8s\n", - "282550K .......... .......... .......... .......... .......... 47% 56.1M 8s\n", - "282600K .......... .......... .......... .......... .......... 47% 52.3M 8s\n", - "282650K .......... .......... .......... .......... .......... 47% 57.2M 8s\n", - "282700K .......... .......... .......... .......... .......... 47% 45.6M 8s\n", - "282750K .......... .......... .......... .......... .......... 47% 19.4M 8s\n", - "282800K .......... .......... .......... .......... .......... 47% 58.0M 8s\n", - "282850K .......... .......... .......... .......... .......... 47% 61.9M 8s\n", - "282900K .......... .......... .......... .......... .......... 47% 50.4M 8s\n", - "282950K .......... .......... .......... .......... .......... 47% 67.1M 8s\n", - "283000K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", - "283050K .......... .......... .......... .......... .......... 47% 59.0M 8s\n", - "283100K .......... .......... .......... .......... .......... 47% 67.6M 8s\n", - "283150K .......... .......... .......... .......... .......... 47% 46.2M 8s\n", - "283200K .......... .......... .......... .......... .......... 47% 54.7M 8s\n", - "283250K .......... .......... .......... .......... .......... 47% 65.8M 8s\n", - "283300K .......... .......... .......... .......... .......... 47% 47.5M 8s\n", - "283350K .......... .......... .......... .......... .......... 47% 60.8M 8s\n", - "283400K .......... .......... .......... .......... .......... 47% 43.0M 8s\n", - "283450K .......... .......... .......... .......... .......... 47% 16.6M 8s\n", - "283500K .......... .......... .......... .......... .......... 47% 53.7M 8s\n", - "283550K .......... .......... .......... .......... .......... 47% 20.0M 8s\n", - "283600K .......... .......... .......... .......... .......... 47% 44.7M 8s\n", - "283650K .......... .......... .......... .......... .......... 47% 48.0M 8s\n", - "283700K .......... .......... .......... .......... .......... 47% 51.5M 8s\n", - "283750K .......... .......... .......... .......... .......... 47% 67.0M 8s\n", - "283800K .......... .......... .......... .......... .......... 47% 56.5M 8s\n", - "283850K .......... .......... .......... .......... .......... 47% 54.3M 8s\n", - "283900K .......... .......... .......... .......... .......... 47% 45.4M 8s\n", - "283950K .......... .......... .......... .......... .......... 47% 52.8M 8s\n", - "284000K .......... .......... .......... .......... .......... 47% 57.6M 8s\n", - "284050K .......... .......... .......... .......... .......... 47% 67.3M 8s\n", - "284100K .......... .......... .......... .......... .......... 47% 58.4M 8s\n", - "284150K .......... .......... .......... .......... .......... 47% 43.3M 8s\n", - "284200K .......... .......... .......... .......... .......... 47% 45.7M 8s\n", - "284250K .......... .......... .......... .......... .......... 47% 51.7M 8s\n", - "284300K .......... .......... .......... .......... .......... 47% 54.3M 8s\n", - "284350K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", - "284400K .......... .......... .......... .......... .......... 47% 40.2M 8s\n", - "284450K .......... .......... .......... .......... .......... 47% 64.6M 8s\n", - "284500K .......... .......... .......... .......... .......... 47% 57.1M 8s\n", - "284550K .......... .......... .......... .......... .......... 47% 54.8M 8s\n", - "284600K .......... .......... .......... .......... .......... 47% 36.7M 8s\n", - "284650K .......... .......... .......... .......... .......... 47% 50.1M 8s\n", - "284700K .......... .......... .......... .......... .......... 47% 65.9M 8s\n", - "284750K .......... .......... .......... .......... .......... 47% 67.5M 8s\n", - "284800K .......... .......... .......... .......... .......... 47% 42.8M 8s\n", - "284850K .......... .......... .......... .......... .......... 47% 37.5M 8s\n", - "284900K .......... .......... .......... .......... .......... 47% 52.0M 8s\n", - "284950K .......... .......... .......... .......... .......... 47% 51.4M 8s\n", - "285000K .......... .......... .......... .......... .......... 47% 49.4M 8s\n", - "285050K .......... .......... .......... .......... .......... 47% 62.7M 8s\n", - "285100K .......... .......... .......... .......... .......... 47% 44.6M 8s\n", - "285150K .......... .......... .......... .......... .......... 47% 64.3M 8s\n", - "285200K .......... .......... .......... .......... .......... 47% 41.7M 8s\n", - "285250K .......... .......... .......... .......... .......... 47% 49.1M 8s\n", - "285300K .......... .......... .......... .......... .......... 47% 36.0M 8s\n", - "285350K .......... .......... .......... .......... .......... 47% 36.3M 8s\n", - "285400K .......... .......... .......... .......... .......... 47% 32.6M 8s\n", - "285450K .......... .......... .......... .......... .......... 48% 33.9M 8s\n", - "285500K .......... .......... .......... .......... .......... 48% 45.2M 8s\n", - "285550K .......... .......... .......... .......... .......... 48% 56.5M 8s\n", - "285600K .......... .......... .......... .......... .......... 48% 49.4M 8s\n", - "285650K .......... .......... .......... .......... .......... 48% 53.4M 8s\n", - "285700K .......... .......... .......... .......... .......... 48% 58.9M 8s\n", - "285750K .......... .......... .......... .......... .......... 48% 57.0M 8s\n", - "285800K .......... .......... .......... .......... .......... 48% 32.3M 8s\n", - "285850K .......... .......... .......... .......... .......... 48% 51.1M 8s\n", - "285900K .......... .......... .......... .......... .......... 48% 47.3M 8s\n", - "285950K .......... .......... .......... .......... .......... 48% 54.0M 8s\n", - "286000K .......... .......... .......... .......... .......... 48% 47.9M 8s\n", - "286050K .......... .......... .......... .......... .......... 48% 43.8M 8s\n", - "286100K .......... .......... .......... .......... .......... 48% 35.1M 8s\n", - "286150K .......... .......... .......... .......... .......... 48% 37.3M 8s\n", - "286200K .......... .......... .......... .......... .......... 48% 24.3M 8s\n", - "286250K .......... .......... .......... .......... .......... 48% 44.9M 8s\n", - "286300K .......... .......... .......... .......... .......... 48% 61.2M 8s\n", - "286350K .......... .......... .......... .......... .......... 48% 51.5M 8s\n", - "286400K .......... .......... .......... .......... .......... 48% 55.2M 8s\n", - "286450K .......... .......... .......... .......... .......... 48% 72.1M 8s\n", - "286500K .......... .......... .......... .......... .......... 48% 58.0M 8s\n", - "286550K .......... .......... .......... .......... .......... 48% 68.3M 8s\n", - "286600K .......... .......... .......... .......... .......... 48% 51.9M 8s\n", - "286650K .......... .......... .......... .......... .......... 48% 57.8M 8s\n", - "286700K .......... .......... .......... .......... .......... 48% 71.2M 8s\n", - "286750K .......... .......... .......... .......... .......... 48% 58.3M 8s\n", - "286800K .......... .......... .......... .......... .......... 48% 52.6M 8s\n", - "286850K .......... .......... .......... .......... .......... 48% 58.0M 8s\n", - "286900K .......... .......... .......... .......... .......... 48% 57.1M 8s\n", - "286950K .......... .......... .......... .......... .......... 48% 54.3M 8s\n", - "287000K .......... .......... .......... .......... .......... 48% 48.8M 8s\n", - "287050K .......... .......... .......... .......... .......... 48% 57.4M 8s\n", - "287100K .......... .......... .......... .......... .......... 48% 59.0M 8s\n", - "287150K .......... .......... .......... .......... .......... 48% 60.7M 8s\n", - "287200K .......... .......... .......... .......... .......... 48% 52.2M 8s\n", - "287250K .......... .......... .......... .......... .......... 48% 55.6M 8s\n", - "287300K .......... .......... .......... .......... .......... 48% 55.4M 8s\n", - "287350K .......... .......... .......... .......... .......... 48% 67.4M 8s\n", - "287400K .......... .......... .......... .......... .......... 48% 50.1M 8s\n", - "287450K .......... .......... .......... .......... .......... 48% 58.4M 8s\n", - "287500K .......... .......... .......... .......... .......... 48% 62.8M 8s\n", - "287550K .......... .......... .......... .......... .......... 48% 49.3M 8s\n", - "287600K .......... .......... .......... .......... .......... 48% 59.6M 8s\n", - "287650K .......... .......... .......... .......... .......... 48% 53.9M 8s\n", - "287700K .......... .......... .......... .......... .......... 48% 52.5M 8s\n", - "287750K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", - "287800K .......... .......... .......... .......... .......... 48% 44.3M 8s\n", - "287850K .......... .......... .......... .......... .......... 48% 69.0M 8s\n", - "287900K .......... .......... .......... .......... .......... 48% 54.6M 8s\n", - "287950K .......... .......... .......... .......... .......... 48% 47.0M 8s\n", - "288000K .......... .......... .......... .......... .......... 48% 48.9M 8s\n", - "288050K .......... .......... .......... .......... .......... 48% 52.7M 8s\n", - "288100K .......... .......... .......... .......... .......... 48% 67.3M 8s\n", - "288150K .......... .......... .......... .......... .......... 48% 53.4M 8s\n", - "288200K .......... .......... .......... .......... .......... 48% 47.1M 8s\n", - "288250K .......... .......... .......... .......... .......... 48% 49.7M 8s\n", - "288300K .......... .......... .......... .......... .......... 48% 60.3M 8s\n", - "288350K .......... .......... .......... .......... .......... 48% 61.2M 8s\n", - "288400K .......... .......... .......... .......... .......... 48% 59.5M 8s\n", - "288450K .......... .......... .......... .......... .......... 48% 60.5M 8s\n", - "288500K .......... .......... .......... .......... .......... 48% 58.0M 8s\n", - "288550K .......... .......... .......... .......... .......... 48% 48.7M 8s\n", - "288600K .......... .......... .......... .......... .......... 48% 55.7M 8s\n", - "288650K .......... .......... .......... .......... .......... 48% 57.8M 8s\n", - "288700K .......... .......... .......... .......... .......... 48% 63.3M 8s\n", - "288750K .......... .......... .......... .......... .......... 48% 50.6M 8s\n", - "288800K .......... .......... .......... .......... .......... 48% 59.9M 8s\n", - "288850K .......... .......... .......... .......... .......... 48% 63.9M 8s\n", - "288900K .......... .......... .......... .......... .......... 48% 49.0M 8s\n", - "288950K .......... .......... .......... .......... .......... 48% 61.5M 8s\n", - "289000K .......... .......... .......... .......... .......... 48% 43.4M 8s\n", - "289050K .......... .......... .......... .......... .......... 48% 59.3M 8s\n", - "289100K .......... .......... .......... .......... .......... 48% 64.8M 8s\n", - "289150K .......... .......... .......... .......... .......... 48% 57.4M 8s\n", - "289200K .......... .......... .......... .......... .......... 48% 61.2M 8s\n", - "289250K .......... .......... .......... .......... .......... 48% 50.6M 8s\n", - "289300K .......... .......... .......... .......... .......... 48% 62.9M 8s\n", - "289350K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", - "289400K .......... .......... .......... .......... .......... 48% 48.5M 8s\n", - "289450K .......... .......... .......... .......... .......... 48% 70.9M 8s\n", - "289500K .......... .......... .......... .......... .......... 48% 53.8M 8s\n", - "289550K .......... .......... .......... .......... .......... 48% 56.7M 8s\n", - "289600K .......... .......... .......... .......... .......... 48% 56.3M 8s\n", - "289650K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", - "289700K .......... .......... .......... .......... .......... 48% 57.1M 8s\n", - "289750K .......... .......... .......... .......... .......... 48% 68.0M 8s\n", - "289800K .......... .......... .......... .......... .......... 48% 51.6M 8s\n", - "289850K .......... .......... .......... .......... .......... 48% 58.7M 8s\n", - "289900K .......... .......... .......... .......... .......... 48% 59.1M 8s\n", - "289950K .......... .......... .......... .......... .......... 48% 48.3M 8s\n", - "290000K .......... .......... .......... .......... .......... 48% 60.0M 8s\n", - "290050K .......... .......... .......... .......... .......... 48% 56.5M 8s\n", - "290100K .......... .......... .......... .......... .......... 48% 57.1M 8s\n", - "290150K .......... .......... .......... .......... .......... 48% 52.6M 8s\n", - "290200K .......... .......... .......... .......... .......... 48% 3.37M 8s\n", - "290250K .......... .......... .......... .......... .......... 48% 60.8M 8s\n", - "290300K .......... .......... .......... .......... .......... 48% 63.3M 8s\n", - "290350K .......... .......... .......... .......... .......... 48% 62.6M 8s\n", - "290400K .......... .......... .......... .......... .......... 48% 59.6M 8s\n", - "290450K .......... .......... .......... .......... .......... 48% 63.9M 8s\n", - "290500K .......... .......... .......... .......... .......... 48% 43.6M 8s\n", - "290550K .......... .......... .......... .......... .......... 48% 37.4M 8s\n", - "290600K .......... .......... .......... .......... .......... 48% 33.5M 8s\n", - "290650K .......... .......... .......... .......... .......... 48% 46.3M 8s\n", - "290700K .......... .......... .......... .......... .......... 48% 37.8M 8s\n", - "290750K .......... .......... .......... .......... .......... 48% 3.68M 8s\n", - "290800K .......... .......... .......... .......... .......... 48% 11.9M 8s\n", - "290850K .......... .......... .......... .......... .......... 48% 32.3M 8s\n", - "290900K .......... .......... .......... .......... .......... 48% 34.8M 8s\n", - "290950K .......... .......... .......... .......... .......... 48% 36.0M 8s\n", - "291000K .......... .......... .......... .......... .......... 48% 34.8M 8s\n", - "291050K .......... .......... .......... .......... .......... 48% 59.1M 8s\n", - "291100K .......... .......... .......... .......... .......... 48% 65.2M 8s\n", - "291150K .......... .......... .......... .......... .......... 48% 66.9M 8s\n", - "291200K .......... .......... .......... .......... .......... 48% 60.1M 8s\n", - "291250K .......... .......... .......... .......... .......... 48% 67.3M 8s\n", - "291300K .......... .......... .......... 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.......... .......... 49% 65.6M 8s\n", - "291950K .......... .......... .......... .......... .......... 49% 54.3M 8s\n", - "292000K .......... .......... .......... .......... .......... 49% 35.4M 8s\n", - "292050K .......... .......... .......... .......... .......... 49% 54.1M 8s\n", - "292100K .......... .......... .......... .......... .......... 49% 62.7M 8s\n", - "292150K .......... .......... .......... .......... .......... 49% 10.8M 8s\n", - "292200K .......... .......... .......... .......... .......... 49% 3.34M 8s\n", - "292250K .......... .......... .......... .......... .......... 49% 66.8M 8s\n", - "292300K .......... .......... .......... .......... .......... 49% 67.2M 8s\n", - "292350K .......... .......... .......... .......... .......... 49% 50.4M 8s\n", - "292400K .......... .......... .......... .......... .......... 49% 53.2M 8s\n", - "292450K .......... .......... .......... .......... .......... 49% 68.2M 8s\n", - "292500K .......... .......... .......... 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.......... .......... 49% 63.3M 8s\n", - "294350K .......... .......... .......... .......... .......... 49% 76.2M 8s\n", - "294400K .......... .......... .......... .......... .......... 49% 64.4M 8s\n", - "294450K .......... .......... .......... .......... .......... 49% 62.7M 8s\n", - "294500K .......... .......... .......... .......... .......... 49% 52.2M 8s\n", - "294550K .......... .......... .......... .......... .......... 49% 61.3M 8s\n", - "294600K .......... .......... .......... .......... .......... 49% 58.4M 8s\n", - "294650K .......... .......... .......... .......... .......... 49% 69.7M 8s\n", - "294700K .......... .......... .......... .......... .......... 49% 69.1M 8s\n", - "294750K .......... .......... .......... .......... .......... 49% 55.0M 8s\n", - "294800K .......... .......... .......... .......... .......... 49% 45.4M 8s\n", - "294850K .......... .......... .......... .......... .......... 49% 58.6M 8s\n", - "294900K .......... .......... .......... .......... .......... 49% 68.4M 8s\n", - "294950K .......... .......... .......... .......... .......... 49% 60.4M 8s\n", - "295000K .......... .......... .......... .......... .......... 49% 50.2M 8s\n", - "295050K .......... .......... .......... .......... .......... 49% 49.7M 8s\n", - "295100K .......... .......... .......... .......... .......... 49% 48.4M 8s\n", - "295150K .......... .......... .......... .......... .......... 49% 67.3M 8s\n", - "295200K .......... .......... .......... .......... .......... 49% 61.7M 8s\n", - "295250K .......... .......... .......... .......... .......... 49% 54.8M 8s\n", - "295300K .......... .......... .......... .......... .......... 49% 46.0M 8s\n", - "295350K .......... .......... .......... .......... .......... 49% 55.4M 8s\n", - "295400K .......... .......... .......... .......... .......... 49% 56.5M 8s\n", - "295450K .......... .......... .......... .......... .......... 49% 66.9M 8s\n", - "295500K .......... .......... .......... .......... .......... 49% 68.5M 8s\n", - "295550K .......... .......... .......... .......... .......... 49% 65.9M 7s\n", - "295600K .......... .......... .......... .......... .......... 49% 62.8M 7s\n", - "295650K .......... .......... .......... .......... .......... 49% 66.7M 7s\n", - "295700K .......... .......... .......... .......... .......... 49% 67.4M 7s\n", - "295750K .......... .......... .......... .......... .......... 49% 70.2M 7s\n", - "295800K .......... .......... .......... .......... .......... 49% 57.9M 7s\n", - "295850K .......... .......... .......... .......... .......... 49% 62.7M 7s\n", - "295900K .......... .......... .......... .......... .......... 49% 70.7M 7s\n", - "295950K .......... .......... .......... .......... .......... 49% 69.3M 7s\n", - "296000K .......... .......... .......... .......... .......... 49% 51.6M 7s\n", - "296050K .......... .......... .......... .......... .......... 49% 52.8M 7s\n", - "296100K .......... .......... .......... .......... .......... 49% 55.6M 7s\n", - "296150K .......... .......... .......... .......... .......... 49% 69.5M 7s\n", - "296200K .......... .......... .......... .......... .......... 49% 59.4M 7s\n", - "296250K .......... .......... .......... .......... .......... 49% 53.8M 7s\n", - "296300K .......... .......... .......... .......... .......... 49% 57.9M 7s\n", - "296350K .......... .......... .......... .......... .......... 49% 47.7M 7s\n", - "296400K .......... .......... .......... .......... .......... 49% 59.0M 7s\n", - "296450K .......... .......... .......... .......... .......... 49% 64.2M 7s\n", - "296500K .......... .......... .......... .......... .......... 49% 55.8M 7s\n", - "296550K .......... .......... .......... .......... .......... 49% 55.9M 7s\n", - "296600K .......... .......... .......... .......... .......... 49% 42.3M 7s\n", - "296650K .......... .......... .......... .......... .......... 49% 60.1M 7s\n", - "296700K .......... .......... .......... .......... .......... 49% 64.1M 7s\n", - "296750K .......... .......... .......... .......... .......... 49% 58.8M 7s\n", - "296800K .......... .......... .......... .......... .......... 49% 48.9M 7s\n", - "296850K .......... .......... .......... .......... .......... 49% 44.5M 7s\n", - "296900K .......... .......... .......... .......... .......... 49% 62.4M 7s\n", - "296950K .......... .......... .......... .......... .......... 49% 68.5M 7s\n", - "297000K .......... .......... .......... .......... .......... 49% 50.1M 7s\n", - "297050K .......... .......... .......... .......... .......... 49% 60.5M 7s\n", - "297100K .......... .......... .......... .......... .......... 49% 51.9M 7s\n", - "297150K .......... .......... .......... .......... .......... 49% 51.3M 7s\n", - "297200K .......... .......... .......... .......... .......... 49% 60.8M 7s\n", - "297250K .......... .......... .......... .......... .......... 49% 66.7M 7s\n", - "297300K .......... .......... .......... .......... .......... 49% 57.6M 7s\n", - "297350K .......... .......... .......... .......... .......... 50% 58.5M 7s\n", - "297400K .......... .......... .......... .......... .......... 50% 37.5M 7s\n", - "297450K .......... .......... .......... .......... .......... 50% 61.5M 7s\n", - "297500K .......... .......... .......... .......... .......... 50% 65.5M 7s\n", - "297550K .......... .......... .......... .......... .......... 50% 54.5M 7s\n", - "297600K .......... .......... .......... .......... .......... 50% 46.8M 7s\n", - "297650K .......... .......... .......... .......... .......... 50% 52.5M 7s\n", - "297700K .......... .......... .......... .......... .......... 50% 57.8M 7s\n", - "297750K .......... .......... .......... .......... .......... 50% 49.3M 7s\n", - "297800K .......... .......... .......... .......... .......... 50% 39.1M 7s\n", - "297850K .......... .......... .......... .......... .......... 50% 49.8M 7s\n", - "297900K .......... .......... .......... .......... .......... 50% 51.9M 7s\n", - "297950K .......... .......... .......... .......... .......... 50% 55.2M 7s\n", - "298000K .......... .......... .......... .......... .......... 50% 43.7M 7s\n", - "298050K .......... .......... .......... .......... .......... 50% 57.9M 7s\n", - "298100K .......... .......... .......... .......... .......... 50% 52.0M 7s\n", - "298150K .......... .......... .......... .......... .......... 50% 46.2M 7s\n", - "298200K .......... .......... .......... .......... .......... 50% 50.8M 7s\n", - "298250K .......... .......... .......... .......... .......... 50% 59.8M 7s\n", - "298300K .......... .......... .......... .......... .......... 50% 56.6M 7s\n", - "298350K .......... .......... .......... .......... .......... 50% 51.3M 7s\n", - "298400K .......... .......... .......... .......... .......... 50% 48.7M 7s\n", - "298450K .......... .......... .......... .......... .......... 50% 59.3M 7s\n", - "298500K .......... .......... .......... .......... .......... 50% 4.27M 7s\n", - "298550K .......... .......... .......... .......... .......... 50% 61.4M 7s\n", - "298600K .......... .......... .......... .......... .......... 50% 54.8M 7s\n", - "298650K .......... .......... .......... .......... .......... 50% 61.2M 7s\n", - "298700K .......... .......... .......... .......... .......... 50% 60.3M 7s\n", - "298750K .......... .......... .......... .......... .......... 50% 65.4M 7s\n", - "298800K .......... .......... .......... .......... .......... 50% 45.4M 7s\n", - "298850K .......... .......... .......... .......... .......... 50% 62.6M 7s\n", - "298900K .......... .......... .......... .......... .......... 50% 68.5M 7s\n", - "298950K .......... .......... .......... .......... .......... 50% 60.4M 7s\n", - "299000K .......... .......... .......... .......... .......... 50% 50.8M 7s\n", - "299050K .......... .......... .......... .......... .......... 50% 58.2M 7s\n", - "299100K .......... .......... .......... .......... .......... 50% 54.4M 7s\n", - "299150K .......... .......... .......... .......... .......... 50% 76.3M 7s\n", - "299200K .......... .......... .......... .......... .......... 50% 65.8M 7s\n", - "299250K .......... .......... .......... .......... .......... 50% 49.8M 7s\n", - "299300K .......... .......... .......... .......... .......... 50% 57.7M 7s\n", - "299350K .......... .......... .......... .......... .......... 50% 62.5M 7s\n", - "299400K .......... .......... .......... .......... .......... 50% 47.3M 7s\n", - "299450K .......... .......... .......... .......... .......... 50% 70.9M 7s\n", - "299500K .......... .......... .......... .......... .......... 50% 56.7M 7s\n", - "299550K .......... .......... .......... .......... .......... 50% 54.0M 7s\n", - "299600K .......... .......... .......... .......... .......... 50% 50.4M 7s\n", - "299650K .......... .......... .......... .......... .......... 50% 57.6M 7s\n", - "299700K .......... .......... .......... .......... .......... 50% 67.2M 7s\n", - "299750K .......... .......... .......... .......... .......... 50% 59.3M 7s\n", - "299800K .......... .......... .......... .......... .......... 50% 40.8M 7s\n", - "299850K .......... .......... .......... .......... .......... 50% 47.4M 7s\n", - "299900K .......... .......... .......... .......... .......... 50% 11.2M 7s\n", - "299950K .......... .......... .......... .......... .......... 50% 55.7M 7s\n", - "300000K .......... .......... .......... .......... .......... 50% 58.1M 7s\n", - "300050K .......... .......... .......... .......... .......... 50% 67.1M 7s\n", - "300100K .......... .......... .......... .......... .......... 50% 64.4M 7s\n", - "300150K .......... .......... .......... .......... .......... 50% 56.0M 7s\n", - "300200K .......... .......... .......... .......... .......... 50% 46.6M 7s\n", - "300250K .......... .......... .......... .......... .......... 50% 67.7M 7s\n", - "300300K .......... .......... .......... 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.......... .......... 51% 74.5M 7s\n", - "305750K .......... .......... .......... .......... .......... 51% 75.1M 7s\n", - "305800K .......... .......... .......... .......... .......... 51% 60.7M 7s\n", - "305850K .......... .......... .......... .......... .......... 51% 52.4M 7s\n", - "305900K .......... .......... .......... .......... .......... 51% 62.0M 7s\n", - "305950K .......... .......... .......... .......... .......... 51% 65.5M 7s\n", - "306000K .......... .......... .......... .......... .......... 51% 61.7M 7s\n", - "306050K .......... .......... .......... .......... .......... 51% 74.4M 7s\n", - "306100K .......... .......... .......... .......... .......... 51% 58.6M 7s\n", - "306150K .......... .......... .......... .......... .......... 51% 65.6M 7s\n", - "306200K .......... .......... .......... .......... .......... 51% 50.2M 7s\n", - "306250K .......... .......... .......... .......... .......... 51% 68.4M 7s\n", - "306300K .......... .......... .......... .......... .......... 51% 72.4M 7s\n", - "306350K .......... .......... .......... .......... .......... 51% 70.2M 7s\n", - "306400K .......... .......... .......... .......... .......... 51% 51.9M 7s\n", - "306450K .......... .......... .......... .......... .......... 51% 61.1M 7s\n", - "306500K .......... .......... .......... .......... .......... 51% 55.6M 7s\n", - "306550K .......... .......... .......... .......... .......... 51% 62.3M 7s\n", - "306600K .......... .......... .......... .......... .......... 51% 61.6M 7s\n", - "306650K .......... .......... .......... .......... .......... 51% 62.8M 7s\n", - "306700K .......... .......... .......... .......... .......... 51% 74.2M 7s\n", - "306750K .......... .......... .......... .......... .......... 51% 60.7M 7s\n", - "306800K .......... .......... .......... .......... .......... 51% 53.4M 7s\n", - "306850K .......... .......... .......... .......... .......... 51% 71.1M 7s\n", - "306900K .......... .......... .......... .......... .......... 51% 73.9M 7s\n", - "306950K .......... .......... .......... .......... .......... 51% 75.8M 7s\n", - "307000K .......... .......... .......... .......... .......... 51% 45.5M 7s\n", - "307050K .......... .......... .......... .......... .......... 51% 58.6M 7s\n", - "307100K .......... .......... .......... .......... .......... 51% 53.2M 7s\n", - "307150K .......... .......... .......... .......... .......... 51% 76.8M 7s\n", - "307200K .......... .......... .......... .......... .......... 51% 71.2M 7s\n", - "307250K .......... .......... .......... .......... .......... 51% 60.1M 7s\n", - "307300K .......... .......... .......... .......... .......... 51% 57.1M 7s\n", - "307350K .......... .......... .......... .......... .......... 51% 49.4M 7s\n", - "307400K .......... .......... .......... .......... .......... 51% 57.7M 7s\n", - "307450K .......... .......... .......... .......... .......... 51% 72.8M 7s\n", - "307500K .......... .......... .......... .......... .......... 51% 64.0M 7s\n", - "307550K .......... .......... .......... .......... .......... 51% 62.4M 7s\n", - "307600K .......... .......... .......... .......... .......... 51% 44.8M 7s\n", - "307650K .......... .......... .......... .......... .......... 51% 50.1M 7s\n", - "307700K .......... .......... .......... .......... .......... 51% 82.0M 7s\n", - "307750K .......... .......... .......... .......... .......... 51% 71.8M 7s\n", - "307800K .......... .......... .......... .......... .......... 51% 47.4M 7s\n", - "307850K .......... .......... .......... .......... .......... 51% 63.2M 7s\n", - "307900K .......... .......... .......... .......... .......... 51% 62.6M 7s\n", - "307950K .......... .......... .......... .......... .......... 51% 59.8M 7s\n", - "308000K .......... .......... .......... .......... .......... 51% 59.5M 7s\n", - "308050K .......... .......... .......... .......... .......... 51% 59.5M 7s\n", - "308100K .......... .......... .......... .......... .......... 51% 56.7M 7s\n", - "308150K .......... .......... .......... .......... .......... 51% 50.4M 7s\n", - "308200K .......... .......... .......... .......... .......... 51% 45.6M 7s\n", - "308250K .......... .......... .......... .......... .......... 51% 73.6M 7s\n", - "308300K .......... .......... .......... .......... .......... 51% 63.4M 7s\n", - "308350K .......... .......... .......... .......... .......... 51% 72.5M 7s\n", - "308400K .......... .......... .......... .......... .......... 51% 52.1M 7s\n", - "308450K .......... .......... .......... .......... .......... 51% 64.8M 7s\n", - "308500K .......... .......... .......... .......... .......... 51% 62.3M 7s\n", - "308550K .......... .......... .......... .......... .......... 51% 76.3M 7s\n", - "308600K .......... .......... .......... .......... .......... 51% 55.1M 7s\n", - "308650K .......... .......... .......... .......... .......... 51% 4.09M 7s\n", - "308700K .......... .......... .......... .......... .......... 51% 76.1M 7s\n", - "308750K .......... .......... .......... .......... .......... 51% 69.0M 7s\n", - "308800K .......... .......... .......... .......... .......... 51% 64.7M 7s\n", - "308850K .......... .......... .......... .......... .......... 51% 62.5M 7s\n", - "308900K .......... .......... .......... .......... .......... 51% 79.4M 7s\n", - "308950K .......... .......... .......... .......... .......... 51% 74.2M 7s\n", - "309000K .......... .......... .......... .......... .......... 51% 44.7M 7s\n", - "309050K .......... .......... .......... .......... .......... 51% 48.4M 7s\n", - "309100K .......... .......... .......... .......... .......... 51% 60.4M 7s\n", - "309150K .......... .......... .......... .......... .......... 51% 70.3M 7s\n", - "309200K .......... .......... .......... .......... .......... 51% 72.4M 7s\n", - "309250K .......... .......... .......... .......... .......... 52% 22.2M 7s\n", - "309300K .......... .......... .......... .......... .......... 52% 46.3M 7s\n", - "309350K .......... .......... .......... .......... .......... 52% 80.1M 7s\n", - "309400K .......... .......... .......... .......... .......... 52% 68.4M 7s\n", - "309450K .......... .......... .......... .......... .......... 52% 48.2M 7s\n", - "309500K .......... .......... .......... .......... .......... 52% 32.4M 7s\n", - "309550K .......... .......... .......... .......... .......... 52% 54.9M 7s\n", - "309600K .......... .......... .......... .......... .......... 52% 71.6M 7s\n", - "309650K .......... .......... .......... .......... .......... 52% 58.8M 7s\n", - "309700K .......... .......... .......... .......... .......... 52% 43.0M 7s\n", - "309750K .......... .......... .......... .......... .......... 52% 36.9M 7s\n", - "309800K .......... .......... .......... .......... .......... 52% 53.0M 7s\n", - "309850K .......... .......... .......... .......... .......... 52% 56.2M 7s\n", - "309900K .......... .......... .......... .......... .......... 52% 44.0M 7s\n", - "309950K .......... .......... .......... .......... .......... 52% 32.8M 7s\n", - "310000K .......... .......... .......... .......... .......... 52% 51.1M 7s\n", - "310050K .......... .......... .......... .......... .......... 52% 79.0M 7s\n", - "310100K .......... .......... .......... .......... .......... 52% 37.0M 7s\n", - "310150K .......... .......... .......... .......... .......... 52% 35.3M 7s\n", - "310200K .......... .......... .......... .......... .......... 52% 40.6M 7s\n", - "310250K .......... .......... .......... .......... .......... 52% 53.6M 7s\n", - "310300K .......... .......... .......... .......... .......... 52% 58.3M 7s\n", - "310350K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", - "310400K .......... .......... .......... .......... .......... 52% 37.2M 7s\n", - "310450K .......... .......... .......... .......... .......... 52% 57.4M 7s\n", - "310500K .......... .......... .......... .......... .......... 52% 51.7M 7s\n", - "310550K .......... .......... .......... .......... .......... 52% 42.3M 7s\n", - "310600K .......... .......... .......... .......... .......... 52% 36.3M 7s\n", - "310650K .......... .......... .......... .......... .......... 52% 46.9M 7s\n", - "310700K .......... .......... .......... .......... .......... 52% 44.7M 7s\n", - "310750K .......... .......... .......... .......... .......... 52% 39.2M 7s\n", - "310800K .......... .......... .......... .......... .......... 52% 31.4M 7s\n", - "310850K .......... .......... .......... .......... .......... 52% 29.0M 7s\n", - "310900K .......... .......... .......... .......... .......... 52% 24.6M 7s\n", - "310950K .......... .......... .......... .......... .......... 52% 37.3M 7s\n", - "311000K .......... .......... .......... .......... .......... 52% 45.5M 7s\n", - "311050K .......... .......... .......... .......... .......... 52% 67.0M 7s\n", - "311100K .......... .......... .......... .......... .......... 52% 42.2M 7s\n", - "311150K .......... .......... .......... .......... .......... 52% 48.8M 7s\n", - "311200K .......... .......... .......... .......... .......... 52% 41.8M 7s\n", - "311250K .......... .......... .......... .......... .......... 52% 61.8M 7s\n", - "311300K .......... .......... .......... .......... .......... 52% 61.3M 7s\n", - "311350K .......... .......... .......... .......... .......... 52% 42.6M 7s\n", - "311400K .......... .......... .......... .......... .......... 52% 31.4M 7s\n", - "311450K .......... .......... .......... .......... .......... 52% 67.6M 7s\n", - "311500K .......... .......... .......... .......... .......... 52% 68.8M 7s\n", - "311550K .......... .......... .......... .......... .......... 52% 41.5M 7s\n", - "311600K .......... .......... .......... .......... .......... 52% 32.7M 7s\n", - "311650K .......... .......... .......... .......... .......... 52% 43.6M 7s\n", - "311700K .......... .......... .......... .......... .......... 52% 77.3M 7s\n", - "311750K .......... .......... .......... .......... .......... 52% 39.8M 7s\n", - "311800K .......... .......... .......... .......... .......... 52% 28.9M 7s\n", - "311850K .......... .......... .......... .......... .......... 52% 49.3M 7s\n", - "311900K .......... .......... .......... .......... .......... 52% 62.8M 7s\n", - "311950K .......... .......... .......... .......... .......... 52% 51.1M 7s\n", - "312000K .......... .......... .......... .......... .......... 52% 41.1M 7s\n", - "312050K .......... .......... .......... .......... .......... 52% 36.8M 7s\n", - "312100K .......... .......... .......... .......... .......... 52% 74.5M 7s\n", - "312150K .......... .......... .......... .......... .......... 52% 51.5M 7s\n", - "312200K .......... .......... .......... .......... .......... 52% 40.0M 7s\n", - "312250K .......... .......... .......... .......... .......... 52% 34.1M 7s\n", - "312300K .......... .......... .......... .......... .......... 52% 62.2M 7s\n", - "312350K .......... .......... .......... .......... .......... 52% 55.0M 7s\n", - "312400K .......... .......... .......... .......... .......... 52% 44.7M 7s\n", - "312450K .......... .......... .......... .......... .......... 52% 46.1M 7s\n", - "312500K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", - "312550K .......... .......... .......... .......... .......... 52% 53.5M 7s\n", - "312600K .......... .......... .......... .......... .......... 52% 41.5M 7s\n", - "312650K .......... .......... .......... .......... .......... 52% 47.4M 7s\n", - "312700K .......... .......... .......... .......... .......... 52% 41.7M 7s\n", - "312750K .......... .......... .......... .......... .......... 52% 54.0M 7s\n", - "312800K .......... .......... .......... .......... .......... 52% 42.3M 7s\n", - "312850K .......... .......... .......... .......... .......... 52% 43.4M 7s\n", - "312900K .......... .......... .......... .......... .......... 52% 37.7M 7s\n", - "312950K .......... .......... .......... .......... .......... 52% 42.2M 7s\n", - "313000K .......... .......... .......... .......... .......... 52% 53.1M 7s\n", - "313050K .......... .......... .......... .......... .......... 52% 46.5M 7s\n", - "313100K .......... .......... .......... .......... .......... 52% 52.4M 7s\n", - "313150K .......... .......... .......... .......... .......... 52% 42.4M 7s\n", - "313200K .......... .......... .......... .......... .......... 52% 42.0M 7s\n", - "313250K .......... .......... .......... .......... .......... 52% 48.8M 7s\n", - "313300K .......... .......... .......... .......... .......... 52% 43.3M 7s\n", - "313350K .......... .......... .......... .......... .......... 52% 44.9M 7s\n", - "313400K .......... .......... .......... .......... .......... 52% 36.4M 7s\n", - "313450K .......... .......... .......... .......... .......... 52% 35.6M 7s\n", - "313500K .......... .......... .......... .......... .......... 52% 41.0M 7s\n", - "313550K .......... .......... .......... .......... .......... 52% 2.01M 7s\n", - "313600K .......... .......... .......... .......... .......... 52% 46.8M 7s\n", - "313650K .......... .......... .......... .......... .......... 52% 62.6M 7s\n", - "313700K .......... .......... .......... .......... .......... 52% 61.7M 7s\n", - "313750K .......... .......... .......... .......... .......... 52% 70.3M 7s\n", - "313800K .......... .......... .......... .......... .......... 52% 37.8M 7s\n", - "313850K .......... .......... .......... .......... .......... 52% 38.4M 7s\n", - "313900K .......... .......... .......... .......... .......... 52% 62.6M 7s\n", - "313950K .......... .......... .......... .......... .......... 52% 72.0M 7s\n", - "314000K .......... .......... .......... .......... .......... 52% 66.8M 7s\n", - "314050K .......... .......... .......... .......... .......... 52% 45.1M 7s\n", - "314100K .......... .......... .......... .......... .......... 52% 34.7M 7s\n", - "314150K .......... .......... .......... .......... .......... 52% 63.9M 7s\n", - "314200K .......... .......... .......... .......... .......... 52% 58.2M 7s\n", - "314250K .......... .......... .......... .......... .......... 52% 72.7M 7s\n", - "314300K .......... .......... .......... .......... .......... 52% 45.4M 7s\n", - "314350K .......... .......... .......... .......... .......... 52% 37.3M 7s\n", - "314400K .......... .......... .......... .......... .......... 52% 69.6M 7s\n", - "314450K .......... .......... .......... .......... .......... 52% 68.6M 7s\n", - "314500K .......... .......... .......... .......... .......... 52% 75.3M 7s\n", - "314550K .......... .......... .......... .......... .......... 52% 74.7M 7s\n", - "314600K .......... .......... .......... .......... .......... 52% 28.3M 7s\n", - "314650K .......... .......... .......... .......... .......... 52% 65.0M 7s\n", - "314700K .......... .......... .......... .......... .......... 52% 71.7M 7s\n", - "314750K .......... .......... .......... .......... .......... 52% 64.4M 7s\n", - "314800K .......... .......... .......... .......... .......... 52% 52.2M 7s\n", - "314850K .......... .......... .......... .......... .......... 52% 42.8M 7s\n", - "314900K .......... .......... .......... .......... .......... 52% 41.7M 7s\n", - "314950K .......... .......... .......... .......... .......... 52% 70.4M 7s\n", - "315000K .......... .......... .......... .......... .......... 52% 61.1M 7s\n", - "315050K .......... .......... .......... .......... .......... 52% 10.5M 7s\n", - "315100K .......... .......... .......... .......... .......... 52% 73.1M 7s\n", - "315150K .......... .......... .......... .......... .......... 52% 70.7M 7s\n", - "315200K .......... .......... .......... .......... .......... 53% 65.8M 7s\n", - "315250K .......... .......... .......... .......... .......... 53% 69.6M 7s\n", - "315300K .......... .......... .......... .......... .......... 53% 73.0M 7s\n", - "315350K .......... .......... .......... .......... .......... 53% 75.7M 7s\n", - "315400K .......... .......... .......... .......... .......... 53% 33.5M 7s\n", - "315450K .......... .......... .......... .......... .......... 53% 54.6M 7s\n", - "315500K .......... .......... .......... .......... .......... 53% 79.5M 7s\n", - "315550K .......... .......... .......... .......... .......... 53% 75.2M 7s\n", - "315600K .......... .......... .......... .......... .......... 53% 61.4M 7s\n", - "315650K .......... .......... .......... .......... .......... 53% 29.8M 7s\n", - "315700K .......... .......... .......... .......... .......... 53% 55.4M 7s\n", - "315750K .......... .......... .......... .......... .......... 53% 70.8M 7s\n", - "315800K .......... .......... .......... .......... .......... 53% 60.4M 7s\n", - "315850K .......... .......... .......... .......... .......... 53% 60.4M 7s\n", - "315900K .......... .......... .......... .......... .......... 53% 38.8M 7s\n", - "315950K .......... .......... .......... .......... .......... 53% 43.5M 7s\n", - "316000K .......... .......... .......... .......... .......... 53% 68.5M 7s\n", - "316050K .......... .......... .......... .......... .......... 53% 80.2M 7s\n", - "316100K .......... .......... .......... .......... .......... 53% 62.2M 7s\n", - "316150K .......... .......... .......... .......... .......... 53% 44.4M 7s\n", - "316200K .......... .......... .......... .......... .......... 53% 34.4M 7s\n", - "316250K .......... .......... .......... .......... .......... 53% 79.6M 7s\n", - "316300K .......... .......... .......... .......... .......... 53% 80.2M 7s\n", - "316350K .......... .......... .......... .......... .......... 53% 56.7M 7s\n", - "316400K .......... .......... .......... .......... .......... 53% 37.5M 7s\n", - "316450K .......... .......... .......... .......... .......... 53% 44.3M 7s\n", - "316500K .......... .......... .......... .......... .......... 53% 62.8M 7s\n", - "316550K .......... .......... .......... .......... .......... 53% 65.7M 7s\n", - "316600K .......... .......... .......... .......... .......... 53% 44.4M 7s\n", - "316650K .......... .......... .......... .......... .......... 53% 31.2M 7s\n", - "316700K .......... .......... .......... .......... .......... 53% 62.9M 7s\n", - "316750K .......... .......... .......... .......... .......... 53% 63.1M 7s\n", - "316800K .......... .......... .......... .......... .......... 53% 46.3M 7s\n", - "316850K .......... .......... .......... .......... .......... 53% 36.4M 7s\n", - "316900K .......... .......... .......... .......... .......... 53% 47.6M 7s\n", - "316950K .......... .......... .......... .......... .......... 53% 73.3M 7s\n", - "317000K .......... .......... .......... .......... .......... 53% 46.0M 7s\n", - "317050K .......... .......... .......... .......... .......... 53% 48.5M 7s\n", - "317100K .......... .......... .......... .......... .......... 53% 32.2M 7s\n", - "317150K .......... .......... .......... .......... .......... 53% 65.0M 7s\n", - "317200K .......... .......... .......... .......... .......... 53% 34.9M 7s\n", - "317250K .......... .......... .......... .......... .......... 53% 31.7M 7s\n", - "317300K .......... .......... .......... .......... .......... 53% 45.4M 7s\n", - "317350K .......... .......... .......... .......... .......... 53% 44.9M 7s\n", - "317400K .......... .......... .......... .......... .......... 53% 46.0M 7s\n", - "317450K .......... .......... .......... .......... .......... 53% 44.2M 7s\n", - "317500K .......... .......... .......... .......... .......... 53% 37.4M 7s\n", - "317550K .......... .......... .......... .......... .......... 53% 50.1M 7s\n", - "317600K .......... .......... .......... .......... .......... 53% 59.3M 7s\n", - "317650K .......... .......... .......... .......... .......... 53% 41.5M 7s\n", - "317700K .......... .......... .......... .......... .......... 53% 35.7M 7s\n", - "317750K .......... .......... .......... .......... .......... 53% 49.7M 7s\n", - "317800K .......... .......... .......... .......... .......... 53% 59.3M 7s\n", - "317850K .......... .......... .......... .......... .......... 53% 55.8M 7s\n", - "317900K .......... .......... .......... .......... .......... 53% 46.4M 7s\n", - "317950K .......... .......... .......... .......... .......... 53% 35.5M 7s\n", - "318000K .......... .......... .......... .......... .......... 53% 65.3M 7s\n", - "318050K .......... .......... .......... .......... .......... 53% 52.1M 7s\n", - "318100K .......... .......... .......... .......... .......... 53% 55.1M 7s\n", - "318150K .......... .......... .......... .......... .......... 53% 43.3M 7s\n", - "318200K .......... .......... .......... .......... .......... 53% 37.2M 7s\n", - "318250K .......... .......... .......... .......... .......... 53% 51.7M 7s\n", - "318300K .......... .......... .......... .......... .......... 53% 43.1M 7s\n", - "318350K .......... .......... .......... .......... .......... 53% 42.9M 7s\n", - "318400K .......... .......... .......... .......... .......... 53% 40.6M 7s\n", - "318450K .......... .......... .......... .......... .......... 53% 75.5M 7s\n", - "318500K .......... .......... .......... .......... .......... 53% 42.3M 7s\n", - "318550K .......... .......... .......... .......... .......... 53% 50.1M 7s\n", - "318600K .......... .......... .......... .......... .......... 53% 36.1M 7s\n", - "318650K .......... .......... .......... .......... .......... 53% 61.5M 7s\n", - "318700K .......... .......... .......... .......... .......... 53% 48.4M 7s\n", - "318750K .......... .......... .......... .......... .......... 53% 48.6M 7s\n", - "318800K .......... .......... .......... .......... .......... 53% 42.7M 7s\n", - "318850K .......... .......... .......... .......... .......... 53% 40.8M 7s\n", - "318900K .......... .......... .......... .......... .......... 53% 42.4M 7s\n", - "318950K .......... .......... .......... .......... .......... 53% 55.2M 7s\n", - "319000K .......... .......... .......... .......... .......... 53% 46.1M 7s\n", - "319050K .......... .......... .......... .......... .......... 53% 39.7M 7s\n", - "319100K .......... .......... .......... .......... .......... 53% 65.4M 7s\n", - "319150K .......... .......... .......... .......... .......... 53% 49.0M 7s\n", - "319200K .......... .......... .......... .......... .......... 53% 44.3M 7s\n", - "319250K .......... .......... .......... .......... .......... 53% 37.7M 7s\n", - "319300K .......... .......... .......... .......... .......... 53% 57.1M 7s\n", - "319350K .......... .......... .......... .......... .......... 53% 51.8M 7s\n", - "319400K .......... .......... .......... .......... .......... 53% 41.4M 7s\n", - "319450K .......... .......... .......... .......... .......... 53% 57.3M 7s\n", - "319500K .......... .......... .......... .......... .......... 53% 40.2M 7s\n", - "319550K .......... .......... .......... .......... .......... 53% 65.8M 7s\n", - "319600K .......... .......... .......... .......... .......... 53% 37.3M 7s\n", - "319650K .......... .......... .......... .......... .......... 53% 68.9M 7s\n", - "319700K .......... .......... .......... .......... .......... 53% 35.4M 7s\n", - "319750K .......... .......... .......... .......... .......... 53% 55.4M 7s\n", - "319800K .......... .......... .......... .......... .......... 53% 39.1M 7s\n", - "319850K .......... .......... .......... .......... .......... 53% 55.7M 7s\n", - "319900K .......... .......... .......... .......... .......... 53% 48.9M 7s\n", - "319950K .......... .......... .......... .......... .......... 53% 39.1M 7s\n", - "320000K .......... .......... .......... .......... .......... 53% 41.9M 7s\n", - "320050K .......... .......... .......... .......... .......... 53% 63.1M 7s\n", - "320100K .......... .......... .......... .......... .......... 53% 50.6M 7s\n", - "320150K .......... .......... .......... .......... .......... 53% 37.8M 7s\n", - "320200K .......... .......... .......... .......... .......... 53% 36.4M 7s\n", - "320250K .......... .......... .......... .......... .......... 53% 79.2M 7s\n", - "320300K .......... .......... .......... .......... .......... 53% 48.5M 7s\n", - "320350K .......... .......... .......... .......... .......... 53% 34.7M 7s\n", - "320400K .......... .......... .......... .......... .......... 53% 43.0M 7s\n", - "320450K .......... .......... .......... .......... .......... 53% 45.4M 7s\n", - "320500K .......... .......... .......... .......... .......... 53% 55.5M 7s\n", - "320550K .......... .......... .......... .......... .......... 53% 33.2M 7s\n", - "320600K .......... .......... .......... .......... .......... 53% 33.9M 7s\n", - "320650K .......... .......... .......... .......... .......... 53% 37.3M 7s\n", - "320700K .......... .......... .......... .......... .......... 53% 21.0M 7s\n", - "320750K .......... .......... .......... .......... .......... 53% 5.10M 7s\n", - "320800K .......... .......... .......... .......... .......... 53% 66.0M 7s\n", - "320850K .......... .......... .......... .......... .......... 53% 71.6M 7s\n", - "320900K .......... .......... .......... .......... .......... 53% 71.4M 7s\n", - "320950K .......... .......... .......... .......... .......... 53% 67.7M 7s\n", - "321000K .......... .......... .......... .......... .......... 53% 56.9M 7s\n", - "321050K .......... .......... .......... .......... .......... 53% 14.5M 7s\n", - "321100K .......... .......... .......... .......... .......... 53% 65.0M 7s\n", - "321150K .......... .......... .......... .......... .......... 54% 50.4M 7s\n", - "321200K .......... .......... .......... .......... .......... 54% 63.8M 7s\n", - "321250K .......... .......... .......... .......... .......... 54% 72.9M 7s\n", - "321300K .......... .......... .......... .......... .......... 54% 67.4M 7s\n", - "321350K .......... .......... .......... .......... .......... 54% 23.5M 7s\n", - "321400K .......... .......... .......... .......... .......... 54% 39.2M 7s\n", - "321450K .......... .......... .......... .......... .......... 54% 58.4M 7s\n", - "321500K .......... .......... .......... .......... .......... 54% 59.3M 7s\n", - "321550K .......... .......... .......... .......... .......... 54% 32.3M 7s\n", - "321600K .......... .......... .......... .......... .......... 54% 51.9M 7s\n", - "321650K .......... .......... .......... .......... .......... 54% 71.4M 7s\n", - "321700K .......... .......... .......... .......... .......... 54% 31.7M 7s\n", - "321750K .......... .......... .......... .......... .......... 54% 33.8M 7s\n", - "321800K .......... .......... .......... .......... .......... 54% 34.7M 7s\n", - "321850K .......... .......... .......... .......... .......... 54% 52.4M 7s\n", - "321900K .......... .......... .......... .......... .......... 54% 28.7M 7s\n", - "321950K .......... .......... .......... .......... .......... 54% 38.1M 7s\n", - "322000K .......... .......... .......... .......... .......... 54% 59.5M 7s\n", - "322050K .......... .......... .......... .......... .......... 54% 63.5M 7s\n", - "322100K .......... .......... .......... .......... .......... 54% 31.6M 7s\n", - "322150K .......... .......... .......... .......... .......... 54% 34.7M 7s\n", - "322200K .......... .......... .......... .......... .......... 54% 63.1M 7s\n", - "322250K .......... .......... .......... .......... .......... 54% 36.0M 7s\n", - "322300K .......... .......... .......... .......... .......... 54% 42.3M 7s\n", - "322350K .......... .......... .......... .......... .......... 54% 33.0M 7s\n", - "322400K .......... .......... .......... .......... .......... 54% 63.1M 7s\n", - "322450K .......... .......... .......... .......... .......... 54% 47.5M 7s\n", - "322500K .......... .......... .......... .......... .......... 54% 38.4M 7s\n", - "322550K .......... .......... .......... .......... .......... 54% 33.5M 7s\n", - "322600K .......... .......... .......... .......... .......... 54% 56.4M 7s\n", - "322650K .......... .......... .......... .......... .......... 54% 48.0M 7s\n", - "322700K .......... .......... .......... .......... .......... 54% 43.1M 7s\n", - "322750K .......... .......... .......... .......... .......... 54% 32.8M 7s\n", - "322800K .......... .......... .......... .......... .......... 54% 44.8M 7s\n", - "322850K .......... .......... .......... .......... .......... 54% 33.8M 7s\n", - "322900K .......... .......... .......... .......... .......... 54% 33.4M 7s\n", - "322950K .......... .......... .......... .......... .......... 54% 34.6M 7s\n", - "323000K .......... .......... .......... .......... .......... 54% 3.66M 7s\n", - "323050K .......... .......... .......... .......... .......... 54% 67.2M 7s\n", - "323100K .......... .......... .......... .......... .......... 54% 72.4M 7s\n", - "323150K .......... .......... .......... .......... .......... 54% 70.4M 7s\n", - "323200K .......... .......... .......... .......... .......... 54% 59.2M 7s\n", - "323250K .......... .......... .......... .......... .......... 54% 27.4M 7s\n", - "323300K .......... .......... .......... .......... .......... 54% 49.1M 7s\n", - "323350K .......... .......... .......... .......... .......... 54% 69.5M 7s\n", - "323400K .......... .......... .......... .......... .......... 54% 58.1M 7s\n", - "323450K .......... .......... .......... .......... .......... 54% 20.1M 7s\n", - "323500K .......... .......... .......... .......... .......... 54% 49.6M 7s\n", - "323550K .......... .......... .......... .......... .......... 54% 76.3M 7s\n", - "323600K .......... .......... .......... .......... .......... 54% 70.3M 7s\n", - "323650K .......... .......... .......... .......... .......... 54% 21.9M 7s\n", - "323700K .......... .......... .......... .......... .......... 54% 47.8M 7s\n", - "323750K .......... .......... .......... .......... .......... 54% 73.2M 7s\n", - "323800K .......... .......... .......... .......... .......... 54% 29.9M 7s\n", - "323850K .......... .......... .......... .......... .......... 54% 45.6M 7s\n", - "323900K .......... .......... .......... .......... .......... 54% 56.4M 7s\n", - "323950K .......... .......... .......... .......... .......... 54% 51.7M 7s\n", - "324000K .......... .......... .......... .......... .......... 54% 47.2M 7s\n", - "324050K .......... .......... .......... .......... .......... 54% 27.7M 7s\n", - "324100K .......... .......... .......... .......... .......... 54% 38.6M 7s\n", - "324150K .......... .......... .......... .......... .......... 54% 49.7M 7s\n", - "324200K .......... .......... .......... .......... .......... 54% 44.4M 7s\n", - "324250K .......... .......... .......... .......... .......... 54% 34.9M 7s\n", - "324300K .......... .......... .......... .......... .......... 54% 3.78M 7s\n", - "324350K .......... .......... .......... .......... .......... 54% 52.8M 7s\n", - "324400K .......... .......... .......... .......... .......... 54% 50.6M 7s\n", - "324450K .......... .......... .......... .......... .......... 54% 68.5M 7s\n", - "324500K .......... .......... .......... .......... .......... 54% 71.9M 7s\n", - "324550K .......... .......... .......... .......... .......... 54% 29.8M 7s\n", - "324600K .......... .......... .......... .......... .......... 54% 37.4M 7s\n", - "324650K .......... .......... .......... .......... .......... 54% 57.1M 7s\n", - "324700K .......... .......... .......... .......... .......... 54% 70.0M 7s\n", - "324750K .......... .......... .......... .......... .......... 54% 27.2M 7s\n", - "324800K .......... .......... .......... .......... .......... 54% 43.8M 7s\n", - "324850K .......... .......... .......... .......... .......... 54% 61.5M 7s\n", - "324900K .......... .......... .......... .......... .......... 54% 68.9M 7s\n", - "324950K .......... .......... .......... .......... .......... 54% 70.7M 7s\n", - "325000K .......... .......... .......... .......... .......... 54% 20.9M 7s\n", - "325050K .......... .......... .......... .......... .......... 54% 49.7M 7s\n", - "325100K .......... .......... .......... .......... .......... 54% 45.2M 7s\n", - "325150K .......... .......... .......... .......... .......... 54% 40.9M 7s\n", - "325200K .......... .......... .......... .......... .......... 54% 55.8M 7s\n", - "325250K .......... .......... .......... .......... .......... 54% 39.2M 7s\n", - "325300K .......... .......... .......... .......... .......... 54% 47.0M 7s\n", - "325350K .......... .......... .......... .......... .......... 54% 59.6M 7s\n", - "325400K .......... .......... .......... .......... .......... 54% 21.3M 7s\n", - "325450K .......... .......... .......... .......... .......... 54% 62.0M 7s\n", - "325500K .......... .......... .......... .......... .......... 54% 79.6M 7s\n", - "325550K .......... .......... .......... .......... .......... 54% 68.5M 7s\n", - "325600K .......... .......... .......... .......... .......... 54% 38.7M 7s\n", - "325650K .......... .......... .......... .......... .......... 54% 32.4M 7s\n", - "325700K .......... .......... .......... .......... .......... 54% 69.1M 7s\n", - "325750K .......... .......... .......... .......... .......... 54% 71.8M 7s\n", - "325800K .......... .......... .......... .......... .......... 54% 33.4M 7s\n", - "325850K .......... .......... .......... .......... .......... 54% 25.1M 7s\n", - "325900K .......... .......... .......... .......... .......... 54% 68.3M 7s\n", - "325950K .......... .......... .......... .......... .......... 54% 68.3M 7s\n", - "326000K .......... .......... .......... .......... .......... 54% 41.6M 7s\n", - "326050K .......... .......... .......... .......... .......... 54% 37.1M 7s\n", - "326100K .......... .......... .......... .......... .......... 54% 32.7M 7s\n", - "326150K .......... .......... .......... .......... .......... 54% 23.7M 7s\n", - "326200K .......... .......... .......... .......... .......... 54% 18.5M 7s\n", - "326250K .......... .......... .......... .......... .......... 54% 60.2M 7s\n", - "326300K .......... .......... .......... .......... .......... 54% 49.3M 7s\n", - "326350K .......... .......... .......... .......... .......... 54% 41.2M 7s\n", - "326400K .......... .......... .......... .......... .......... 54% 51.1M 7s\n", - "326450K .......... .......... .......... .......... .......... 54% 38.4M 7s\n", - "326500K .......... .......... .......... .......... .......... 54% 47.6M 7s\n", - "326550K .......... .......... .......... .......... .......... 54% 3.63M 7s\n", - "326600K .......... .......... .......... .......... .......... 54% 55.7M 7s\n", - "326650K .......... .......... .......... .......... .......... 54% 63.5M 7s\n", - "326700K .......... .......... .......... .......... .......... 54% 72.3M 7s\n", - "326750K .......... .......... .......... .......... .......... 54% 69.2M 7s\n", - "326800K .......... .......... .......... .......... .......... 54% 64.3M 7s\n", - "326850K .......... .......... .......... .......... .......... 54% 67.3M 7s\n", - "326900K .......... .......... .......... .......... .......... 54% 69.6M 7s\n", - "326950K .......... .......... .......... .......... .......... 54% 67.0M 7s\n", - "327000K .......... .......... .......... .......... .......... 54% 10.2M 7s\n", - "327050K .......... .......... .......... .......... .......... 54% 61.2M 7s\n", - "327100K .......... .......... .......... .......... .......... 55% 62.7M 7s\n", - "327150K .......... .......... .......... .......... .......... 55% 19.7M 7s\n", - "327200K .......... .......... .......... .......... .......... 55% 43.3M 7s\n", - "327250K .......... .......... .......... .......... .......... 55% 64.0M 7s\n", - "327300K .......... .......... .......... .......... .......... 55% 21.6M 7s\n", - "327350K .......... .......... .......... .......... .......... 55% 37.2M 7s\n", - "327400K .......... .......... .......... .......... .......... 55% 58.5M 7s\n", - "327450K .......... .......... .......... .......... .......... 55% 19.8M 7s\n", - "327500K .......... .......... .......... .......... .......... 55% 39.3M 7s\n", - "327550K .......... .......... .......... .......... .......... 55% 74.3M 7s\n", - "327600K .......... .......... .......... .......... .......... 55% 18.7M 7s\n", - "327650K .......... .......... .......... .......... .......... 55% 30.2M 7s\n", - "327700K .......... .......... .......... .......... .......... 55% 68.4M 7s\n", - "327750K .......... .......... .......... .......... .......... 55% 21.4M 7s\n", - "327800K .......... .......... .......... .......... .......... 55% 31.8M 7s\n", - "327850K .......... .......... .......... .......... .......... 55% 69.1M 7s\n", - "327900K .......... .......... .......... .......... .......... 55% 23.0M 7s\n", - "327950K .......... .......... .......... .......... .......... 55% 27.8M 7s\n", - "328000K .......... .......... .......... .......... .......... 55% 55.8M 7s\n", - "328050K .......... .......... .......... .......... .......... 55% 24.8M 7s\n", - "328100K .......... .......... .......... .......... .......... 55% 35.8M 7s\n", - "328150K .......... .......... .......... .......... .......... 55% 62.7M 7s\n", - "328200K .......... .......... .......... .......... .......... 55% 18.5M 7s\n", - "328250K .......... .......... .......... .......... .......... 55% 43.2M 7s\n", - "328300K .......... .......... .......... .......... .......... 55% 54.4M 7s\n", - "328350K .......... .......... .......... .......... .......... 55% 20.0M 7s\n", - "328400K .......... .......... .......... .......... .......... 55% 38.9M 7s\n", - "328450K .......... .......... .......... .......... .......... 55% 55.6M 7s\n", - "328500K .......... .......... .......... .......... .......... 55% 18.1M 7s\n", - "328550K .......... .......... .......... .......... .......... 55% 50.4M 7s\n", - "328600K .......... .......... .......... .......... .......... 55% 47.0M 7s\n", - "328650K .......... .......... .......... .......... .......... 55% 19.1M 7s\n", - "328700K .......... .......... .......... .......... .......... 55% 54.0M 7s\n", - "328750K .......... .......... .......... .......... .......... 55% 55.9M 7s\n", - "328800K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", - "328850K .......... .......... .......... .......... .......... 55% 40.6M 7s\n", - "328900K .......... .......... .......... .......... .......... 55% 52.9M 7s\n", - "328950K .......... .......... .......... .......... .......... 55% 19.6M 7s\n", - "329000K .......... .......... .......... .......... .......... 55% 42.5M 7s\n", - "329050K .......... .......... .......... .......... .......... 55% 61.3M 7s\n", - "329100K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", - "329150K .......... .......... .......... .......... .......... 55% 53.4M 7s\n", - "329200K .......... .......... .......... .......... .......... 55% 47.0M 7s\n", - "329250K .......... .......... .......... .......... .......... 55% 21.5M 7s\n", - "329300K .......... .......... .......... .......... .......... 55% 40.0M 7s\n", - "329350K .......... .......... .......... .......... .......... 55% 59.9M 7s\n", - "329400K .......... .......... .......... .......... .......... 55% 18.7M 7s\n", - "329450K .......... .......... .......... .......... .......... 55% 47.5M 7s\n", - "329500K .......... .......... .......... .......... .......... 55% 58.8M 7s\n", - "329550K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", - "329600K .......... .......... .......... .......... .......... 55% 56.3M 7s\n", - "329650K .......... .......... .......... .......... .......... 55% 59.6M 7s\n", - "329700K .......... .......... .......... .......... .......... 55% 17.9M 7s\n", - "329750K .......... .......... .......... .......... .......... 55% 41.7M 7s\n", - "329800K .......... .......... .......... .......... .......... 55% 51.6M 7s\n", - "329850K .......... .......... .......... .......... .......... 55% 18.3M 7s\n", - "329900K .......... .......... .......... .......... .......... 55% 52.0M 7s\n", - "329950K .......... .......... .......... .......... .......... 55% 61.4M 7s\n", - "330000K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", - "330050K .......... .......... .......... .......... .......... 55% 58.3M 7s\n", - "330100K .......... .......... .......... .......... .......... 55% 55.3M 7s\n", - "330150K .......... .......... .......... .......... .......... 55% 20.2M 7s\n", - "330200K .......... .......... .......... .......... .......... 55% 35.7M 7s\n", - "330250K .......... .......... .......... .......... .......... 55% 57.8M 7s\n", - "330300K .......... .......... .......... .......... .......... 55% 17.6M 7s\n", - "330350K .......... .......... .......... .......... .......... 55% 54.5M 7s\n", - "330400K .......... .......... .......... .......... .......... 55% 53.9M 7s\n", - "330450K .......... .......... .......... .......... .......... 55% 18.9M 7s\n", - "330500K .......... .......... .......... .......... .......... 55% 49.3M 7s\n", - "330550K .......... .......... .......... .......... .......... 55% 63.6M 7s\n", - "330600K .......... .......... .......... .......... .......... 55% 13.1M 7s\n", - "330650K .......... .......... .......... .......... .......... 55% 60.5M 7s\n", - "330700K .......... .......... .......... .......... .......... 55% 52.4M 7s\n", - "330750K .......... .......... .......... .......... .......... 55% 17.2M 7s\n", - "330800K .......... .......... .......... .......... .......... 55% 51.1M 7s\n", - "330850K .......... .......... .......... .......... .......... 55% 58.0M 7s\n", - "330900K .......... .......... .......... .......... .......... 55% 17.0M 7s\n", - "330950K .......... .......... .......... .......... .......... 55% 59.3M 7s\n", - "331000K .......... .......... .......... .......... .......... 55% 53.2M 7s\n", - "331050K .......... .......... .......... .......... .......... 55% 18.2M 7s\n", - "331100K .......... .......... .......... .......... .......... 55% 58.4M 7s\n", - "331150K .......... .......... .......... .......... .......... 55% 64.8M 7s\n", - "331200K .......... .......... .......... .......... .......... 55% 16.1M 7s\n", - "331250K .......... .......... .......... .......... .......... 55% 56.3M 7s\n", - "331300K .......... .......... .......... .......... .......... 55% 58.3M 7s\n", - "331350K .......... .......... .......... .......... .......... 55% 17.0M 7s\n", - "331400K .......... .......... .......... .......... .......... 55% 51.1M 7s\n", - "331450K .......... .......... .......... .......... .......... 55% 60.1M 7s\n", - "331500K .......... .......... .......... .......... .......... 55% 18.4M 7s\n", - "331550K .......... .......... .......... .......... .......... 55% 47.8M 7s\n", - "331600K .......... .......... .......... .......... .......... 55% 56.1M 7s\n", - "331650K .......... .......... .......... .......... .......... 55% 18.8M 7s\n", - "331700K .......... .......... .......... .......... .......... 55% 52.0M 7s\n", - "331750K .......... .......... .......... .......... .......... 55% 53.1M 7s\n", - "331800K .......... .......... .......... .......... .......... 55% 16.8M 7s\n", - "331850K .......... .......... .......... .......... .......... 55% 49.6M 7s\n", - "331900K .......... .......... .......... .......... .......... 55% 60.3M 7s\n", - "331950K .......... .......... .......... .......... .......... 55% 21.1M 7s\n", - "332000K .......... .......... .......... .......... .......... 55% 41.7M 7s\n", - "332050K .......... .......... .......... .......... .......... 55% 54.9M 7s\n", - "332100K .......... .......... .......... .......... .......... 55% 20.3M 7s\n", - "332150K .......... .......... .......... .......... .......... 55% 39.0M 7s\n", - "332200K .......... .......... .......... .......... .......... 55% 50.0M 7s\n", - "332250K .......... .......... .......... .......... .......... 55% 20.4M 7s\n", - "332300K .......... .......... .......... .......... .......... 55% 41.8M 7s\n", - "332350K .......... .......... .......... .......... .......... 55% 59.8M 7s\n", - "332400K .......... .......... .......... .......... .......... 55% 20.4M 7s\n", - "332450K .......... .......... .......... .......... .......... 55% 45.8M 7s\n", - "332500K .......... .......... .......... .......... .......... 55% 53.3M 7s\n", - "332550K .......... .......... .......... .......... .......... 55% 68.7M 7s\n", - "332600K .......... .......... .......... .......... .......... 55% 16.5M 7s\n", - "332650K .......... .......... .......... .......... .......... 55% 48.2M 7s\n", - "332700K .......... .......... .......... .......... .......... 55% 69.2M 7s\n", - "332750K .......... .......... .......... .......... .......... 55% 17.9M 7s\n", - "332800K .......... .......... .......... .......... .......... 55% 49.7M 7s\n", - "332850K .......... .......... .......... .......... .......... 55% 70.8M 7s\n", - "332900K .......... .......... .......... .......... .......... 55% 21.4M 7s\n", - "332950K .......... .......... .......... .......... .......... 55% 45.2M 7s\n", - "333000K .......... .......... .......... .......... .......... 56% 48.6M 7s\n", - "333050K .......... .......... .......... .......... .......... 56% 22.0M 7s\n", - "333100K .......... .......... .......... .......... .......... 56% 40.6M 7s\n", - "333150K .......... .......... .......... .......... .......... 56% 60.1M 7s\n", - "333200K .......... .......... .......... .......... .......... 56% 19.7M 7s\n", - "333250K .......... .......... .......... .......... .......... 56% 37.4M 7s\n", - "333300K .......... .......... .......... .......... .......... 56% 68.4M 7s\n", - "333350K .......... .......... .......... .......... .......... 56% 21.3M 7s\n", - "333400K .......... .......... .......... .......... .......... 56% 45.2M 7s\n", - "333450K .......... .......... .......... .......... .......... 56% 50.3M 7s\n", - "333500K .......... .......... .......... .......... .......... 56% 20.3M 7s\n", - "333550K .......... .......... .......... .......... .......... 56% 54.0M 7s\n", - "333600K .......... .......... .......... .......... .......... 56% 48.0M 7s\n", - "333650K .......... .......... .......... .......... .......... 56% 65.0M 7s\n", - "333700K .......... .......... .......... .......... .......... 56% 20.3M 7s\n", - "333750K .......... .......... .......... .......... .......... 56% 44.2M 7s\n", - "333800K .......... .......... .......... .......... .......... 56% 45.8M 7s\n", - "333850K .......... .......... .......... .......... .......... 56% 20.8M 7s\n", - "333900K .......... .......... .......... .......... .......... 56% 57.4M 7s\n", - "333950K .......... .......... .......... .......... .......... 56% 66.6M 7s\n", - "334000K .......... .......... .......... .......... .......... 56% 17.3M 7s\n", - "334050K .......... .......... .......... .......... .......... 56% 45.8M 7s\n", - "334100K .......... .......... .......... .......... .......... 56% 66.4M 7s\n", - "334150K .......... .......... .......... .......... .......... 56% 59.7M 7s\n", - "334200K .......... .......... .......... .......... .......... 56% 21.6M 7s\n", - "334250K .......... .......... .......... .......... .......... 56% 34.7M 7s\n", - "334300K .......... .......... .......... .......... .......... 56% 61.9M 6s\n", - "334350K .......... .......... .......... .......... .......... 56% 21.9M 6s\n", - "334400K .......... .......... .......... .......... .......... 56% 43.7M 6s\n", - "334450K .......... .......... .......... .......... .......... 56% 53.5M 6s\n", - "334500K .......... .......... .......... .......... .......... 56% 23.5M 6s\n", - "334550K .......... .......... .......... .......... .......... 56% 44.2M 6s\n", - "334600K .......... .......... .......... .......... .......... 56% 38.6M 6s\n", - "334650K .......... .......... .......... .......... .......... 56% 29.1M 6s\n", - "334700K .......... .......... .......... .......... .......... 56% 40.6M 6s\n", - "334750K .......... .......... .......... .......... .......... 56% 43.9M 6s\n", - "334800K .......... .......... .......... .......... .......... 56% 57.0M 6s\n", - "334850K .......... .......... .......... .......... .......... 56% 25.6M 6s\n", - "334900K .......... .......... .......... .......... .......... 56% 32.6M 6s\n", - "334950K .......... .......... .......... .......... .......... 56% 51.4M 6s\n", - "335000K .......... .......... .......... .......... .......... 56% 24.5M 6s\n", - "335050K .......... .......... .......... .......... .......... 56% 46.6M 6s\n", - "335100K .......... .......... .......... .......... .......... 56% 39.5M 6s\n", - "335150K .......... .......... .......... .......... .......... 56% 27.2M 6s\n", - "335200K .......... .......... .......... .......... .......... 56% 49.5M 6s\n", - "335250K .......... .......... .......... .......... .......... 56% 40.2M 6s\n", - "335300K .......... .......... .......... .......... .......... 56% 52.5M 6s\n", - "335350K .......... .......... .......... .......... .......... 56% 27.4M 6s\n", - "335400K .......... .......... .......... .......... .......... 56% 32.5M 6s\n", - "335450K .......... .......... .......... .......... .......... 56% 48.6M 6s\n", - "335500K .......... .......... .......... .......... .......... 56% 26.0M 6s\n", - "335550K .......... .......... .......... .......... .......... 56% 45.5M 6s\n", - "335600K .......... .......... .......... .......... .......... 56% 44.5M 6s\n", - "335650K .......... .......... .......... .......... .......... 56% 60.7M 6s\n", - "335700K .......... .......... .......... .......... .......... 56% 25.0M 6s\n", - "335750K .......... .......... .......... .......... .......... 56% 50.5M 6s\n", - "335800K .......... .......... .......... .......... .......... 56% 35.5M 6s\n", - "335850K .......... .......... .......... .......... .......... 56% 26.4M 6s\n", - "335900K .......... .......... .......... .......... .......... 56% 54.6M 6s\n", - "335950K .......... .......... .......... .......... .......... 56% 27.1M 6s\n", - "336000K .......... .......... .......... .......... .......... 56% 33.2M 6s\n", - "336050K .......... .......... .......... .......... .......... 56% 46.7M 6s\n", - "336100K .......... .......... .......... .......... .......... 56% 42.2M 6s\n", - "336150K .......... .......... .......... .......... .......... 56% 44.9M 6s\n", - "336200K .......... .......... .......... .......... .......... 56% 26.2M 6s\n", - "336250K .......... .......... .......... .......... .......... 56% 53.1M 6s\n", - "336300K .......... .......... .......... .......... .......... 56% 35.6M 6s\n", - "336350K .......... .......... .......... .......... .......... 56% 34.9M 6s\n", - "336400K .......... .......... .......... .......... .......... 56% 38.6M 6s\n", - "336450K .......... .......... .......... .......... .......... 56% 54.7M 6s\n", - "336500K .......... .......... .......... .......... .......... 56% 28.6M 6s\n", - "336550K .......... .......... .......... .......... .......... 56% 49.4M 6s\n", - "336600K .......... .......... .......... .......... .......... 56% 37.3M 6s\n", - "336650K .......... .......... .......... .......... .......... 56% 38.5M 6s\n", - "336700K .......... .......... .......... .......... .......... 56% 31.4M 6s\n", - "336750K .......... .......... .......... .......... .......... 56% 39.0M 6s\n", - "336800K .......... .......... .......... .......... .......... 56% 50.8M 6s\n", - "336850K .......... .......... .......... .......... .......... 56% 30.4M 6s\n", - "336900K .......... .......... .......... .......... .......... 56% 52.4M 6s\n", - "336950K .......... .......... .......... .......... .......... 56% 35.7M 6s\n", - "337000K .......... .......... .......... .......... .......... 56% 37.3M 6s\n", - "337050K .......... .......... .......... .......... .......... 56% 35.1M 6s\n", - "337100K .......... .......... .......... .......... .......... 56% 40.9M 6s\n", - "337150K .......... .......... .......... .......... .......... 56% 47.2M 6s\n", - "337200K .......... .......... .......... .......... .......... 56% 46.8M 6s\n", - "337250K .......... .......... .......... .......... .......... 56% 29.0M 6s\n", - "337300K .......... .......... .......... .......... .......... 56% 37.7M 6s\n", - "337350K .......... .......... .......... .......... .......... 56% 51.1M 6s\n", - "337400K .......... .......... .......... .......... .......... 56% 32.1M 6s\n", - "337450K .......... .......... .......... .......... .......... 56% 40.5M 6s\n", - "337500K .......... .......... .......... .......... .......... 56% 43.5M 6s\n", - "337550K .......... .......... .......... .......... .......... 56% 47.3M 6s\n", - "337600K .......... .......... .......... .......... .......... 56% 30.3M 6s\n", - "337650K .......... .......... .......... .......... .......... 56% 48.1M 6s\n", - "337700K .......... .......... .......... .......... .......... 56% 51.4M 6s\n", - "337750K .......... .......... .......... .......... .......... 56% 3.67M 6s\n", - "337800K .......... .......... .......... .......... .......... 56% 44.5M 6s\n", - "337850K .......... .......... .......... .......... .......... 56% 60.4M 6s\n", - "337900K .......... .......... .......... .......... .......... 56% 59.4M 6s\n", - "337950K .......... .......... .......... .......... .......... 56% 69.5M 6s\n", - "338000K .......... .......... .......... .......... .......... 56% 69.2M 6s\n", - "338050K .......... .......... .......... .......... .......... 56% 60.0M 6s\n", - "338100K .......... .......... .......... .......... .......... 56% 72.3M 6s\n", - "338150K .......... .......... .......... .......... .......... 56% 70.4M 6s\n", - "338200K .......... .......... .......... .......... .......... 56% 59.0M 6s\n", - "338250K .......... .......... .......... .......... .......... 56% 72.0M 6s\n", - "338300K .......... .......... .......... .......... .......... 56% 61.2M 6s\n", - "338350K .......... .......... .......... .......... .......... 56% 68.1M 6s\n", - "338400K .......... .......... .......... .......... .......... 56% 41.8M 6s\n", - "338450K .......... .......... .......... .......... .......... 56% 73.4M 6s\n", - "338500K .......... .......... .......... .......... .......... 56% 67.7M 6s\n", - "338550K .......... .......... .......... .......... .......... 56% 19.9M 6s\n", - "338600K .......... .......... .......... .......... .......... 56% 51.0M 6s\n", - "338650K .......... .......... .......... .......... .......... 56% 14.8M 6s\n", - "338700K .......... .......... .......... .......... .......... 56% 60.2M 6s\n", - "338750K .......... .......... .......... .......... .......... 56% 57.3M 6s\n", - "338800K .......... .......... .......... .......... .......... 56% 14.7M 6s\n", - "338850K .......... .......... .......... .......... .......... 56% 47.5M 6s\n", - "338900K .......... .......... .......... .......... .......... 56% 30.6M 6s\n", - "338950K .......... .......... .......... .......... .......... 57% 22.9M 6s\n", - "339000K .......... .......... .......... .......... .......... 57% 43.7M 6s\n", - "339050K .......... .......... .......... .......... .......... 57% 17.2M 6s\n", - "339100K .......... .......... .......... .......... .......... 57% 42.0M 6s\n", - "339150K .......... .......... .......... .......... .......... 57% 37.6M 6s\n", - "339200K .......... .......... .......... .......... .......... 57% 19.9M 6s\n", - "339250K .......... .......... .......... .......... .......... 57% 44.8M 6s\n", - "339300K .......... .......... .......... .......... .......... 57% 17.9M 6s\n", - "339350K .......... .......... .......... .......... .......... 57% 35.9M 6s\n", - "339400K .......... .......... .......... .......... .......... 57% 45.1M 6s\n", - "339450K .......... .......... .......... .......... .......... 57% 17.7M 6s\n", - "339500K .......... .......... .......... .......... .......... 57% 47.3M 6s\n", - "339550K .......... .......... .......... .......... .......... 57% 19.1M 6s\n", - "339600K .......... .......... .......... .......... .......... 57% 22.9M 6s\n", - "339650K .......... .......... .......... .......... .......... 57% 59.9M 6s\n", - "339700K .......... .......... .......... .......... .......... 57% 22.6M 6s\n", - "339750K .......... .......... .......... .......... .......... 57% 24.6M 6s\n", - "339800K .......... .......... .......... .......... .......... 57% 27.6M 6s\n", - "339850K .......... .......... .......... .......... .......... 57% 21.0M 6s\n", - "339900K .......... .......... .......... .......... .......... 57% 46.8M 6s\n", - "339950K .......... .......... .......... .......... .......... 57% 32.1M 6s\n", - "340000K .......... .......... .......... .......... .......... 57% 18.2M 6s\n", - "340050K .......... .......... .......... .......... .......... 57% 60.6M 6s\n", - "340100K .......... .......... .......... .......... .......... 57% 29.1M 6s\n", - "340150K .......... .......... .......... .......... .......... 57% 19.3M 6s\n", - "340200K .......... .......... .......... .......... .......... 57% 52.9M 6s\n", - "340250K .......... .......... .......... .......... .......... 57% 14.9M 6s\n", - "340300K .......... .......... .......... .......... .......... 57% 53.4M 6s\n", - "340350K .......... .......... .......... .......... .......... 57% 61.0M 6s\n", - "340400K .......... .......... .......... .......... .......... 57% 15.0M 6s\n", - "340450K .......... .......... .......... .......... .......... 57% 58.8M 6s\n", - "340500K .......... .......... .......... .......... .......... 57% 15.7M 6s\n", - "340550K .......... .......... .......... .......... .......... 57% 54.0M 6s\n", - "340600K .......... .......... .......... .......... .......... 57% 50.9M 6s\n", - "340650K .......... .......... .......... .......... .......... 57% 15.8M 6s\n", - "340700K .......... .......... .......... .......... .......... 57% 50.8M 6s\n", - "340750K .......... .......... .......... .......... .......... 57% 15.9M 6s\n", - "340800K .......... .......... .......... .......... .......... 57% 47.7M 6s\n", - "340850K .......... .......... .......... .......... .......... 57% 36.3M 6s\n", - "340900K .......... .......... .......... .......... .......... 57% 18.1M 6s\n", - "340950K .......... .......... .......... .......... .......... 57% 36.2M 6s\n", - "341000K .......... .......... .......... .......... .......... 57% 20.4M 6s\n", - "341050K .......... .......... .......... .......... .......... 57% 39.2M 6s\n", - "341100K .......... .......... .......... .......... .......... 57% 48.9M 6s\n", - "341150K .......... .......... .......... .......... .......... 57% 17.2M 6s\n", - "341200K .......... .......... .......... .......... .......... 57% 37.6M 6s\n", - "341250K .......... .......... .......... .......... .......... 57% 48.8M 6s\n", - "341300K .......... .......... .......... .......... .......... 57% 20.0M 6s\n", - "341350K .......... .......... .......... .......... .......... 57% 36.0M 6s\n", - "341400K .......... .......... .......... .......... .......... 57% 17.3M 6s\n", - "341450K .......... .......... .......... .......... .......... 57% 35.7M 6s\n", - "341500K .......... .......... .......... .......... .......... 57% 41.0M 6s\n", - "341550K .......... .......... .......... .......... .......... 57% 22.1M 6s\n", - "341600K .......... .......... .......... .......... .......... 57% 31.5M 6s\n", - "341650K .......... .......... .......... .......... .......... 57% 19.1M 6s\n", - "341700K .......... .......... .......... .......... .......... 57% 44.3M 6s\n", - "341750K .......... .......... .......... .......... .......... 57% 45.7M 6s\n", - "341800K .......... .......... .......... .......... .......... 57% 17.9M 6s\n", - "341850K .......... .......... .......... .......... .......... 57% 30.6M 6s\n", - "341900K .......... .......... .......... .......... .......... 57% 21.5M 6s\n", - "341950K .......... .......... .......... .......... .......... 57% 37.2M 6s\n", - "342000K .......... .......... .......... .......... .......... 57% 42.8M 6s\n", - "342050K .......... .......... .......... .......... .......... 57% 19.4M 6s\n", - "342100K .......... .......... .......... .......... .......... 57% 31.5M 6s\n", - "342150K .......... .......... .......... .......... .......... 57% 57.9M 6s\n", - "342200K .......... .......... .......... .......... .......... 57% 14.0M 6s\n", - "342250K .......... .......... .......... .......... .......... 57% 33.5M 6s\n", - "342300K .......... .......... .......... .......... .......... 57% 28.8M 6s\n", - "342350K .......... .......... .......... .......... .......... 57% 35.7M 6s\n", - "342400K .......... .......... .......... .......... .......... 57% 44.6M 6s\n", - "342450K .......... .......... .......... .......... .......... 57% 20.8M 6s\n", - "342500K .......... .......... .......... .......... .......... 57% 48.9M 6s\n", - "342550K .......... .......... .......... .......... .......... 57% 56.0M 6s\n", - "342600K .......... .......... .......... .......... .......... 57% 15.0M 6s\n", - "342650K .......... .......... .......... .......... .......... 57% 62.3M 6s\n", - "342700K .......... .......... .......... .......... .......... 57% 17.8M 6s\n", - "342750K .......... .......... .......... .......... .......... 57% 37.3M 6s\n", - "342800K .......... .......... .......... .......... .......... 57% 37.1M 6s\n", - "342850K .......... .......... .......... .......... .......... 57% 22.4M 6s\n", - "342900K .......... .......... .......... .......... .......... 57% 43.5M 6s\n", - "342950K .......... .......... .......... .......... .......... 57% 65.5M 6s\n", - "343000K .......... .......... .......... .......... .......... 57% 3.25M 6s\n", - "343050K .......... .......... .......... .......... .......... 57% 70.6M 6s\n", - "343100K .......... .......... .......... .......... .......... 57% 68.3M 6s\n", - "343150K .......... .......... .......... .......... .......... 57% 64.0M 6s\n", - "343200K .......... .......... .......... .......... .......... 57% 46.9M 6s\n", - "343250K .......... .......... .......... .......... .......... 57% 67.3M 6s\n", - "343300K .......... .......... .......... .......... .......... 57% 28.3M 6s\n", - "343350K .......... .......... .......... .......... .......... 57% 56.8M 6s\n", - "343400K .......... .......... .......... .......... .......... 57% 18.2M 6s\n", - "343450K .......... .......... .......... .......... .......... 57% 35.8M 6s\n", - "343500K .......... .......... .......... .......... .......... 57% 17.6M 6s\n", - "343550K .......... .......... .......... .......... .......... 57% 52.2M 6s\n", - "343600K .......... .......... .......... .......... .......... 57% 43.9M 6s\n", - "343650K .......... .......... .......... .......... .......... 57% 54.6M 6s\n", - "343700K .......... .......... .......... .......... .......... 57% 21.5M 6s\n", - "343750K .......... .......... .......... .......... .......... 57% 49.5M 6s\n", - "343800K .......... .......... .......... .......... .......... 57% 40.6M 6s\n", - "343850K .......... .......... .......... .......... .......... 57% 16.3M 6s\n", - "343900K .......... .......... .......... .......... .......... 57% 43.5M 6s\n", - "343950K .......... .......... .......... .......... .......... 57% 62.1M 6s\n", - "344000K .......... .......... .......... .......... .......... 57% 19.5M 6s\n", - "344050K .......... .......... .......... .......... .......... 57% 50.3M 6s\n", - "344100K .......... .......... .......... .......... .......... 57% 56.1M 6s\n", - "344150K .......... .......... .......... .......... .......... 57% 18.4M 6s\n", - "344200K .......... .......... .......... .......... .......... 57% 36.8M 6s\n", - "344250K .......... .......... .......... .......... .......... 57% 21.5M 6s\n", - "344300K .......... .......... .......... .......... .......... 57% 3.86M 6s\n", - "344350K .......... .......... .......... .......... .......... 57% 67.4M 6s\n", - "344400K .......... .......... .......... .......... .......... 57% 60.4M 6s\n", - "344450K .......... .......... .......... .......... .......... 57% 62.1M 6s\n", - "344500K .......... .......... .......... .......... .......... 57% 14.9M 6s\n", - "344550K .......... .......... .......... .......... .......... 57% 58.6M 6s\n", - "344600K .......... .......... .......... .......... .......... 57% 17.3M 6s\n", - "344650K .......... .......... .......... .......... .......... 57% 52.8M 6s\n", - "344700K .......... .......... .......... .......... .......... 57% 47.3M 6s\n", - "344750K .......... .......... .......... .......... .......... 57% 18.9M 6s\n", - "344800K .......... .......... .......... .......... .......... 57% 40.5M 6s\n", - "344850K .......... .......... .......... .......... .......... 57% 50.1M 6s\n", - "344900K .......... .......... .......... .......... .......... 58% 20.3M 6s\n", - "344950K .......... .......... .......... .......... .......... 58% 55.9M 6s\n", - "345000K .......... .......... .......... .......... .......... 58% 43.1M 6s\n", - "345050K .......... .......... .......... .......... .......... 58% 19.8M 6s\n", - "345100K .......... .......... .......... .......... .......... 58% 47.4M 6s\n", - "345150K .......... .......... .......... .......... .......... 58% 60.4M 6s\n", - "345200K .......... .......... .......... .......... .......... 58% 15.7M 6s\n", - "345250K .......... .......... .......... .......... .......... 58% 44.2M 6s\n", - "345300K .......... .......... .......... .......... .......... 58% 60.0M 6s\n", - "345350K .......... .......... .......... .......... .......... 58% 64.9M 6s\n", - "345400K .......... .......... .......... .......... .......... 58% 16.6M 6s\n", - "345450K .......... .......... .......... .......... .......... 58% 64.6M 6s\n", - "345500K .......... .......... .......... .......... .......... 58% 23.0M 6s\n", - "345550K .......... .......... .......... .......... .......... 58% 38.1M 6s\n", - "345600K .......... .......... .......... .......... .......... 58% 48.6M 6s\n", - "345650K .......... .......... .......... .......... .......... 58% 66.5M 6s\n", - "345700K .......... .......... .......... .......... .......... 58% 21.1M 6s\n", - "345750K .......... .......... .......... .......... .......... 58% 48.3M 6s\n", - "345800K .......... .......... .......... .......... .......... 58% 21.4M 6s\n", - "345850K .......... .......... .......... .......... .......... 58% 37.4M 6s\n", - "345900K .......... .......... .......... .......... .......... 58% 46.9M 6s\n", - "345950K .......... .......... .......... .......... .......... 58% 50.6M 6s\n", - "346000K .......... .......... .......... .......... .......... 58% 23.9M 6s\n", - "346050K .......... .......... .......... .......... .......... 58% 46.0M 6s\n", - "346100K .......... .......... .......... .......... .......... 58% 52.2M 6s\n", - "346150K .......... .......... .......... .......... .......... 58% 24.2M 6s\n", - "346200K .......... .......... .......... .......... .......... 58% 35.7M 6s\n", - "346250K .......... .......... .......... .......... .......... 58% 61.0M 6s\n", - "346300K .......... .......... .......... .......... .......... 58% 23.1M 6s\n", - "346350K .......... .......... .......... .......... .......... 58% 37.1M 6s\n", - "346400K .......... .......... .......... .......... .......... 58% 24.5M 6s\n", - "346450K .......... .......... .......... .......... .......... 58% 35.7M 6s\n", - "346500K .......... .......... .......... .......... .......... 58% 54.3M 6s\n", - "346550K .......... .......... .......... .......... .......... 58% 50.5M 6s\n", - "346600K .......... .......... .......... .......... .......... 58% 22.5M 6s\n", - "346650K .......... .......... .......... .......... .......... 58% 53.5M 6s\n", - "346700K .......... .......... .......... .......... .......... 58% 60.5M 6s\n", - "346750K .......... .......... .......... .......... .......... 58% 22.2M 6s\n", - "346800K .......... .......... .......... .......... .......... 58% 40.7M 6s\n", - "346850K .......... .......... .......... .......... .......... 58% 47.2M 6s\n", - "346900K .......... .......... .......... .......... .......... 58% 60.6M 6s\n", - "346950K .......... .......... .......... .......... .......... 58% 25.7M 6s\n", - "347000K .......... .......... .......... .......... .......... 58% 32.1M 6s\n", - "347050K .......... .......... .......... .......... .......... 58% 54.4M 6s\n", - "347100K .......... .......... .......... .......... .......... 58% 26.3M 6s\n", - "347150K .......... .......... .......... .......... .......... 58% 37.1M 6s\n", - "347200K .......... .......... .......... .......... .......... 58% 48.1M 6s\n", - "347250K .......... .......... .......... .......... .......... 58% 31.1M 6s\n", - "347300K .......... .......... .......... .......... .......... 58% 31.7M 6s\n", - "347350K .......... .......... .......... .......... .......... 58% 55.8M 6s\n", - "347400K .......... .......... .......... .......... .......... 58% 24.8M 6s\n", - "347450K .......... .......... .......... .......... .......... 58% 34.4M 6s\n", - "347500K .......... .......... .......... .......... .......... 58% 34.4M 6s\n", - "347550K .......... .......... .......... .......... .......... 58% 72.1M 6s\n", - "347600K .......... .......... .......... .......... .......... 58% 24.1M 6s\n", - "347650K .......... .......... .......... .......... .......... 58% 34.4M 6s\n", - "347700K .......... .......... .......... .......... .......... 58% 57.3M 6s\n", - "347750K .......... .......... .......... .......... .......... 58% 34.9M 6s\n", - "347800K .......... .......... .......... .......... .......... 58% 24.9M 6s\n", - "347850K .......... .......... .......... .......... .......... 58% 43.6M 6s\n", - "347900K .......... .......... .......... .......... .......... 58% 48.7M 6s\n", - "347950K .......... .......... .......... .......... .......... 58% 42.0M 6s\n", - "348000K .......... .......... .......... .......... .......... 58% 26.7M 6s\n", - "348050K .......... .......... .......... .......... .......... 58% 61.6M 6s\n", - "348100K .......... .......... .......... .......... .......... 58% 33.2M 6s\n", - "348150K .......... .......... .......... .......... .......... 58% 28.0M 6s\n", - "348200K .......... .......... .......... .......... .......... 58% 44.1M 6s\n", - "348250K .......... .......... .......... .......... .......... 58% 29.4M 6s\n", - "348300K .......... .......... .......... .......... .......... 58% 49.3M 6s\n", - "348350K .......... .......... .......... .......... .......... 58% 31.7M 6s\n", - "348400K .......... .......... .......... .......... .......... 58% 42.1M 6s\n", - "348450K .......... .......... .......... .......... .......... 58% 31.7M 6s\n", - "348500K .......... .......... .......... .......... .......... 58% 42.2M 6s\n", - "348550K .......... .......... .......... .......... .......... 58% 43.8M 6s\n", - "348600K .......... .......... .......... .......... .......... 58% 25.4M 6s\n", - "348650K .......... .......... .......... .......... .......... 58% 42.4M 6s\n", - "348700K .......... .......... .......... .......... .......... 58% 35.5M 6s\n", - "348750K .......... .......... .......... .......... .......... 58% 13.5M 6s\n", - "348800K .......... .......... .......... .......... .......... 58% 45.5M 6s\n", - "348850K .......... .......... .......... .......... .......... 58% 68.7M 6s\n", - "348900K .......... .......... .......... .......... .......... 58% 18.5M 6s\n", - "348950K .......... .......... .......... .......... .......... 58% 41.9M 6s\n", - "349000K .......... .......... .......... .......... .......... 58% 60.6M 6s\n", - "349050K .......... .......... .......... .......... .......... 58% 75.5M 6s\n", - "349100K .......... .......... .......... .......... .......... 58% 3.25M 6s\n", - "349150K .......... .......... .......... .......... .......... 58% 65.9M 6s\n", - "349200K .......... .......... .......... .......... .......... 58% 57.3M 6s\n", - "349250K .......... .......... .......... .......... .......... 58% 68.9M 6s\n", - "349300K .......... .......... .......... .......... .......... 58% 66.6M 6s\n", - "349350K .......... .......... .......... .......... .......... 58% 58.1M 6s\n", - "349400K .......... .......... .......... .......... .......... 58% 25.4M 6s\n", - "349450K .......... .......... .......... .......... .......... 58% 66.4M 6s\n", - "349500K .......... .......... .......... .......... .......... 58% 70.3M 6s\n", - "349550K .......... .......... .......... .......... .......... 58% 22.8M 6s\n", - "349600K .......... .......... .......... .......... .......... 58% 35.5M 6s\n", - "349650K .......... .......... .......... .......... .......... 58% 78.2M 6s\n", - "349700K .......... .......... .......... .......... .......... 58% 76.7M 6s\n", - "349750K .......... .......... .......... .......... .......... 58% 22.6M 6s\n", - "349800K .......... .......... .......... .......... .......... 58% 34.5M 6s\n", - "349850K .......... .......... .......... .......... .......... 58% 69.1M 6s\n", - "349900K .......... .......... .......... .......... .......... 58% 21.2M 6s\n", - "349950K .......... .......... .......... .......... .......... 58% 36.3M 6s\n", - "350000K .......... .......... .......... .......... .......... 58% 66.0M 6s\n", - "350050K .......... .......... .......... .......... .......... 58% 72.8M 6s\n", - "350100K .......... .......... .......... .......... .......... 58% 24.2M 6s\n", - "350150K .......... .......... .......... .......... .......... 58% 38.0M 6s\n", - "350200K .......... .......... .......... .......... .......... 58% 57.3M 6s\n", - "350250K .......... .......... .......... .......... .......... 58% 29.1M 6s\n", - "350300K .......... .......... .......... .......... .......... 58% 34.4M 6s\n", - "350350K .......... .......... .......... .......... .......... 58% 43.8M 6s\n", - "350400K .......... .......... .......... .......... .......... 58% 59.4M 6s\n", - "350450K .......... .......... .......... .......... .......... 58% 27.0M 6s\n", - "350500K .......... .......... .......... .......... .......... 58% 34.3M 6s\n", - "350550K .......... .......... .......... .......... .......... 58% 55.2M 6s\n", - "350600K .......... .......... .......... .......... .......... 58% 37.8M 6s\n", - "350650K .......... .......... .......... .......... .......... 58% 31.8M 6s\n", - "350700K .......... .......... .......... .......... .......... 58% 35.1M 6s\n", - "350750K .......... .......... .......... .......... .......... 58% 72.7M 6s\n", - "350800K .......... .......... .......... .......... .......... 58% 39.1M 6s\n", - "350850K .......... .......... .......... .......... .......... 59% 29.8M 6s\n", - "350900K .......... .......... .......... .......... .......... 59% 38.2M 6s\n", - "350950K .......... .......... .......... .......... .......... 59% 68.6M 6s\n", - "351000K .......... .......... .......... .......... .......... 59% 29.4M 6s\n", - "351050K .......... .......... .......... .......... .......... 59% 36.7M 6s\n", - "351100K .......... .......... .......... .......... .......... 59% 45.4M 6s\n", - "351150K .......... .......... .......... .......... .......... 59% 38.9M 6s\n", - "351200K .......... .......... .......... .......... .......... 59% 35.2M 6s\n", - "351250K .......... .......... .......... .......... .......... 59% 34.1M 6s\n", - "351300K .......... .......... .......... .......... .......... 59% 61.0M 6s\n", - "351350K .......... .......... .......... .......... .......... 59% 50.9M 6s\n", - "351400K .......... .......... .......... .......... .......... 59% 32.5M 6s\n", - "351450K .......... .......... .......... .......... .......... 59% 30.7M 6s\n", - "351500K .......... .......... .......... .......... .......... 59% 47.0M 6s\n", - "351550K .......... .......... .......... .......... .......... 59% 49.3M 6s\n", - "351600K .......... .......... .......... .......... .......... 59% 38.2M 6s\n", - "351650K .......... .......... .......... .......... .......... 59% 48.4M 6s\n", - "351700K .......... .......... .......... .......... .......... 59% 36.8M 6s\n", - "351750K .......... .......... .......... .......... .......... 59% 42.5M 6s\n", - "351800K .......... .......... .......... .......... .......... 59% 31.3M 6s\n", - "351850K .......... .......... .......... .......... .......... 59% 33.8M 6s\n", - "351900K .......... .......... .......... .......... .......... 59% 48.4M 6s\n", - "351950K .......... .......... .......... .......... .......... 59% 40.0M 6s\n", - "352000K .......... .......... .......... .......... .......... 59% 31.3M 6s\n", - "352050K .......... .......... .......... .......... .......... 59% 43.9M 6s\n", - "352100K .......... .......... .......... .......... .......... 59% 42.4M 6s\n", - "352150K .......... .......... .......... .......... .......... 59% 38.4M 6s\n", - "352200K .......... .......... .......... .......... .......... 59% 31.5M 6s\n", - "352250K .......... .......... .......... .......... .......... 59% 53.9M 6s\n", - "352300K .......... .......... .......... .......... .......... 59% 47.3M 6s\n", - "352350K .......... .......... .......... .......... .......... 59% 40.2M 6s\n", - "352400K .......... .......... .......... .......... .......... 59% 30.4M 6s\n", - "352450K .......... .......... .......... .......... .......... 59% 58.5M 6s\n", - "352500K .......... .......... .......... .......... .......... 59% 39.1M 6s\n", - "352550K .......... .......... .......... .......... .......... 59% 41.3M 6s\n", - "352600K .......... .......... .......... .......... .......... 59% 32.8M 6s\n", - "352650K .......... .......... .......... .......... .......... 59% 41.3M 6s\n", - "352700K .......... .......... .......... .......... .......... 59% 32.8M 6s\n", - "352750K .......... .......... .......... .......... .......... 59% 31.5M 6s\n", - "352800K .......... .......... .......... .......... .......... 59% 40.2M 6s\n", - "352850K .......... .......... .......... .......... .......... 59% 47.4M 6s\n", - "352900K .......... .......... .......... .......... .......... 59% 35.5M 6s\n", - "352950K .......... .......... .......... .......... .......... 59% 45.6M 6s\n", - "353000K .......... .......... .......... .......... .......... 59% 39.2M 6s\n", - "353050K .......... .......... .......... .......... .......... 59% 58.5M 6s\n", - "353100K .......... .......... .......... .......... .......... 59% 34.1M 6s\n", - "353150K .......... .......... .......... .......... .......... 59% 33.4M 6s\n", - "353200K .......... .......... .......... .......... .......... 59% 53.9M 6s\n", - "353250K .......... .......... .......... .......... .......... 59% 46.5M 6s\n", - "353300K .......... .......... .......... .......... .......... 59% 31.5M 6s\n", - "353350K .......... .......... .......... .......... .......... 59% 46.1M 6s\n", - "353400K .......... .......... .......... .......... .......... 59% 40.3M 6s\n", - "353450K .......... .......... .......... .......... .......... 59% 38.1M 6s\n", - "353500K .......... .......... .......... .......... .......... 59% 29.5M 6s\n", - "353550K .......... .......... .......... .......... .......... 59% 39.5M 6s\n", - "353600K .......... .......... .......... .......... .......... 59% 40.0M 6s\n", - "353650K .......... .......... .......... .......... .......... 59% 3.60M 6s\n", - "353700K .......... .......... .......... .......... .......... 59% 65.6M 6s\n", - "353750K .......... .......... .......... .......... .......... 59% 63.6M 6s\n", - "353800K .......... .......... .......... .......... .......... 59% 51.9M 6s\n", - "353850K .......... .......... .......... .......... .......... 59% 68.5M 6s\n", - "353900K .......... .......... .......... .......... .......... 59% 46.1M 6s\n", - "353950K .......... .......... .......... .......... .......... 59% 58.2M 6s\n", - "354000K .......... .......... .......... .......... .......... 59% 45.9M 6s\n", - "354050K .......... .......... .......... .......... .......... 59% 62.2M 6s\n", - "354100K .......... .......... .......... .......... .......... 59% 42.8M 6s\n", - "354150K .......... .......... .......... .......... .......... 59% 32.9M 6s\n", - "354200K .......... .......... .......... .......... .......... 59% 46.2M 6s\n", - "354250K .......... .......... .......... .......... .......... 59% 50.8M 6s\n", - "354300K .......... .......... .......... .......... .......... 59% 48.4M 6s\n", - "354350K .......... .......... .......... .......... .......... 59% 31.3M 6s\n", - "354400K .......... .......... .......... .......... .......... 59% 31.0M 6s\n", - "354450K .......... .......... .......... .......... .......... 59% 62.6M 6s\n", - "354500K .......... .......... .......... .......... .......... 59% 65.4M 6s\n", - "354550K .......... .......... .......... .......... .......... 59% 64.3M 6s\n", - "354600K .......... .......... .......... .......... .......... 59% 48.7M 6s\n", - "354650K .......... .......... .......... .......... .......... 59% 48.0M 6s\n", - "354700K .......... .......... .......... .......... .......... 59% 62.0M 6s\n", - "354750K .......... .......... .......... .......... .......... 59% 23.9M 6s\n", - "354800K .......... .......... .......... .......... .......... 59% 49.7M 6s\n", - "354850K .......... .......... .......... .......... .......... 59% 46.7M 6s\n", - "354900K .......... .......... .......... .......... .......... 59% 56.2M 6s\n", - "354950K .......... .......... .......... .......... .......... 59% 34.2M 6s\n", - "355000K .......... .......... .......... .......... .......... 59% 42.2M 6s\n", - "355050K .......... .......... .......... .......... .......... 59% 4.57M 6s\n", - "355100K .......... .......... .......... .......... .......... 59% 48.3M 6s\n", - "355150K .......... .......... .......... .......... .......... 59% 56.8M 6s\n", - "355200K .......... .......... .......... .......... .......... 59% 65.1M 6s\n", - "355250K .......... .......... .......... .......... .......... 59% 71.2M 6s\n", - "355300K .......... .......... .......... .......... .......... 59% 29.7M 6s\n", - "355350K .......... .......... .......... .......... .......... 59% 50.3M 6s\n", - "355400K .......... .......... .......... .......... .......... 59% 53.9M 6s\n", - "355450K .......... .......... .......... .......... .......... 59% 69.4M 6s\n", - "355500K .......... .......... .......... .......... .......... 59% 23.8M 6s\n", - "355550K .......... .......... .......... .......... .......... 59% 57.9M 6s\n", - "355600K .......... .......... .......... .......... .......... 59% 62.3M 6s\n", - "355650K .......... .......... .......... .......... .......... 59% 64.4M 6s\n", - "355700K .......... .......... .......... .......... .......... 59% 23.9M 6s\n", - "355750K .......... .......... .......... .......... .......... 59% 59.4M 6s\n", - "355800K .......... .......... .......... .......... .......... 59% 49.2M 6s\n", - "355850K .......... .......... .......... .......... .......... 59% 75.1M 6s\n", - "355900K .......... .......... .......... .......... .......... 59% 26.5M 6s\n", - "355950K .......... .......... .......... .......... .......... 59% 54.4M 6s\n", - "356000K .......... .......... .......... .......... .......... 59% 49.4M 6s\n", - "356050K .......... .......... .......... .......... .......... 59% 62.1M 6s\n", - "356100K .......... .......... .......... .......... .......... 59% 2.36M 6s\n", - "356150K .......... .......... .......... .......... .......... 59% 68.9M 6s\n", - "356200K .......... .......... .......... .......... .......... 59% 58.9M 6s\n", - "356250K .......... .......... .......... .......... .......... 59% 71.3M 6s\n", - "356300K .......... .......... .......... .......... .......... 59% 59.1M 6s\n", - "356350K .......... .......... .......... .......... .......... 59% 19.7M 6s\n", - "356400K .......... .......... .......... .......... .......... 59% 54.1M 6s\n", - "356450K .......... .......... .......... .......... .......... 59% 70.9M 6s\n", - "356500K .......... .......... .......... .......... .......... 59% 70.8M 6s\n", - "356550K .......... .......... .......... .......... .......... 59% 21.3M 6s\n", - "356600K .......... .......... .......... .......... .......... 59% 45.3M 6s\n", - "356650K .......... .......... .......... .......... .......... 59% 64.9M 6s\n", - "356700K .......... .......... .......... .......... .......... 59% 66.2M 6s\n", - "356750K .......... .......... .......... .......... .......... 59% 28.5M 6s\n", - "356800K .......... .......... .......... .......... .......... 60% 44.5M 6s\n", - "356850K .......... .......... .......... .......... .......... 60% 60.3M 6s\n", - "356900K .......... .......... .......... .......... .......... 60% 73.3M 6s\n", - "356950K .......... .......... .......... .......... .......... 60% 27.6M 6s\n", - "357000K .......... .......... .......... .......... .......... 60% 33.0M 6s\n", - "357050K .......... .......... .......... .......... .......... 60% 60.8M 6s\n", - "357100K .......... .......... .......... .......... .......... 60% 72.4M 6s\n", - "357150K .......... .......... .......... .......... .......... 60% 32.4M 6s\n", - "357200K .......... .......... .......... .......... .......... 60% 53.8M 6s\n", - "357250K .......... .......... .......... .......... .......... 60% 54.5M 6s\n", - "357300K .......... .......... .......... .......... .......... 60% 73.8M 6s\n", - "357350K .......... .......... .......... .......... .......... 60% 72.8M 6s\n", - "357400K .......... .......... .......... .......... .......... 60% 24.8M 6s\n", - "357450K .......... .......... .......... .......... .......... 60% 59.4M 6s\n", - "357500K .......... .......... .......... .......... .......... 60% 50.4M 6s\n", - "357550K .......... .......... .......... .......... .......... 60% 78.3M 6s\n", - "357600K .......... .......... .......... .......... .......... 60% 9.90M 6s\n", - "357650K .......... .......... .......... .......... .......... 60% 74.3M 6s\n", - "357700K .......... .......... .......... .......... .......... 60% 70.0M 6s\n", - "357750K .......... .......... .......... .......... .......... 60% 83.7M 6s\n", - "357800K .......... .......... .......... .......... .......... 60% 22.1M 6s\n", - "357850K .......... .......... .......... .......... .......... 60% 60.8M 6s\n", - "357900K .......... .......... .......... .......... .......... 60% 10.5M 6s\n", - "357950K .......... .......... .......... .......... .......... 60% 56.9M 6s\n", - "358000K .......... .......... .......... .......... .......... 60% 65.1M 6s\n", - "358050K .......... .......... .......... .......... .......... 60% 17.1M 6s\n", - "358100K .......... .......... .......... .......... .......... 60% 48.7M 6s\n", - "358150K .......... .......... .......... .......... .......... 60% 64.0M 6s\n", - "358200K .......... .......... .......... .......... .......... 60% 20.6M 6s\n", - "358250K .......... .......... .......... .......... .......... 60% 52.3M 6s\n", - "358300K .......... .......... .......... .......... .......... 60% 65.4M 6s\n", - "358350K .......... .......... .......... .......... .......... 60% 15.0M 6s\n", - "358400K .......... .......... .......... .......... .......... 60% 53.6M 6s\n", - "358450K .......... .......... .......... .......... .......... 60% 67.3M 6s\n", - "358500K .......... .......... .......... 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.......... .......... 60% 22.4M 6s\n", - "359150K .......... .......... .......... .......... .......... 60% 39.8M 6s\n", - "359200K .......... .......... .......... .......... .......... 60% 44.5M 6s\n", - "359250K .......... .......... .......... .......... .......... 60% 64.7M 6s\n", - "359300K .......... .......... .......... .......... .......... 60% 19.2M 6s\n", - "359350K .......... .......... .......... .......... .......... 60% 48.8M 6s\n", - "359400K .......... .......... .......... .......... .......... 60% 62.1M 6s\n", - "359450K .......... .......... .......... .......... .......... 60% 18.7M 6s\n", - "359500K .......... .......... .......... .......... .......... 60% 49.1M 6s\n", - "359550K .......... .......... .......... .......... .......... 60% 58.6M 6s\n", - "359600K .......... .......... .......... .......... .......... 60% 9.18M 6s\n", - "359650K .......... .......... .......... .......... .......... 60% 4.33M 6s\n", - "359700K .......... .......... .......... 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.......... .......... 60% 55.1M 6s\n", - "362750K .......... .......... .......... .......... .......... 61% 12.6M 6s\n", - "362800K .......... .......... .......... .......... .......... 61% 6.85M 6s\n", - "362850K .......... .......... .......... .......... .......... 61% 55.3M 6s\n", - "362900K .......... .......... .......... .......... .......... 61% 11.5M 6s\n", - "362950K .......... .......... .......... .......... .......... 61% 35.2M 6s\n", - "363000K .......... .......... .......... .......... .......... 61% 10.8M 6s\n", - "363050K .......... .......... .......... .......... .......... 61% 14.3M 6s\n", - "363100K .......... .......... .......... .......... .......... 61% 36.4M 6s\n", - "363150K .......... .......... .......... .......... .......... 61% 11.5M 6s\n", - "363200K .......... .......... .......... .......... .......... 61% 13.3M 6s\n", - "363250K .......... .......... .......... .......... .......... 61% 38.0M 6s\n", - "363300K .......... .......... .......... .......... .......... 61% 13.9M 6s\n", - "363350K .......... .......... .......... .......... .......... 61% 12.0M 6s\n", - "363400K .......... .......... .......... .......... .......... 61% 10.6M 6s\n", - "363450K .......... .......... .......... .......... .......... 61% 37.0M 6s\n", - "363500K .......... .......... .......... .......... .......... 61% 10.0M 6s\n", - "363550K .......... .......... .......... .......... .......... 61% 67.8M 6s\n", - "363600K .......... .......... .......... .......... .......... 61% 11.9M 6s\n", - "363650K .......... .......... .......... .......... .......... 61% 19.0M 6s\n", - "363700K .......... .......... .......... .......... .......... 61% 17.9M 6s\n", - "363750K .......... .......... .......... .......... .......... 61% 14.7M 6s\n", - "363800K .......... .......... .......... .......... .......... 61% 18.7M 6s\n", - "363850K .......... .......... .......... .......... .......... 61% 16.2M 6s\n", - "363900K .......... .......... .......... .......... .......... 61% 14.2M 6s\n", - "363950K .......... .......... .......... .......... .......... 61% 35.3M 6s\n", - "364000K .......... .......... .......... .......... .......... 61% 6.23M 6s\n", - "364050K .......... .......... .......... .......... .......... 61% 54.5M 6s\n", - "364100K .......... .......... .......... .......... .......... 61% 10.9M 6s\n", - "364150K .......... .......... .......... .......... .......... 61% 46.6M 6s\n", - "364200K .......... .......... .......... .......... .......... 61% 12.4M 6s\n", - "364250K .......... .......... .......... .......... .......... 61% 58.5M 6s\n", - "364300K .......... .......... .......... .......... .......... 61% 11.6M 6s\n", - "364350K .......... .......... .......... .......... .......... 61% 14.8M 6s\n", - "364400K .......... .......... .......... .......... .......... 61% 34.6M 6s\n", - "364450K .......... .......... .......... .......... .......... 61% 15.1M 6s\n", - "364500K .......... .......... .......... .......... .......... 61% 35.0M 6s\n", - "364550K .......... .......... .......... .......... .......... 61% 14.5M 6s\n", - "364600K .......... .......... .......... .......... .......... 61% 27.5M 6s\n", - "364650K .......... .......... .......... .......... .......... 61% 12.2M 6s\n", - "364700K .......... .......... .......... .......... .......... 61% 15.7M 6s\n", - "364750K .......... .......... .......... .......... .......... 61% 30.3M 6s\n", - "364800K .......... .......... .......... .......... .......... 61% 15.8M 6s\n", - "364850K .......... .......... .......... .......... .......... 61% 30.5M 6s\n", - "364900K .......... .......... .......... .......... .......... 61% 16.0M 6s\n", - "364950K .......... .......... .......... .......... .......... 61% 30.4M 6s\n", - "365000K .......... .......... .......... .......... .......... 61% 12.9M 6s\n", - "365050K .......... .......... .......... .......... .......... 61% 55.2M 6s\n", - "365100K .......... .......... .......... .......... .......... 61% 13.4M 6s\n", - "365150K .......... .......... .......... .......... .......... 61% 55.9M 6s\n", - "365200K .......... .......... .......... .......... .......... 61% 13.2M 6s\n", - "365250K .......... .......... .......... .......... .......... 61% 60.0M 6s\n", - "365300K .......... .......... .......... .......... .......... 61% 13.4M 6s\n", - "365350K .......... .......... .......... .......... .......... 61% 45.1M 6s\n", - "365400K .......... .......... .......... .......... .......... 61% 13.0M 6s\n", - "365450K .......... .......... .......... .......... .......... 61% 15.7M 6s\n", - "365500K .......... .......... .......... .......... .......... 61% 37.0M 6s\n", - "365550K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", - "365600K .......... .......... .......... .......... .......... 61% 31.1M 6s\n", - "365650K .......... .......... .......... .......... .......... 61% 16.3M 6s\n", - "365700K .......... .......... .......... .......... .......... 61% 33.9M 6s\n", - "365750K .......... .......... .......... .......... .......... 61% 15.8M 6s\n", - "365800K .......... .......... .......... .......... .......... 61% 31.3M 6s\n", - "365850K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", - "365900K .......... .......... .......... .......... .......... 61% 37.6M 6s\n", - "365950K .......... .......... .......... .......... .......... 61% 15.1M 6s\n", - "366000K .......... .......... .......... .......... .......... 61% 38.9M 6s\n", - "366050K .......... .......... .......... .......... .......... 61% 14.6M 6s\n", - "366100K .......... .......... .......... .......... .......... 61% 45.9M 6s\n", - "366150K .......... .......... .......... .......... .......... 61% 18.2M 6s\n", - "366200K .......... .......... .......... .......... .......... 61% 25.4M 6s\n", - "366250K .......... .......... .......... .......... .......... 61% 14.3M 6s\n", - "366300K .......... .......... .......... .......... .......... 61% 48.9M 6s\n", - "366350K .......... .......... .......... .......... .......... 61% 13.9M 6s\n", - "366400K .......... .......... .......... .......... .......... 61% 42.0M 6s\n", - "366450K .......... .......... .......... .......... .......... 61% 24.1M 6s\n", - "366500K .......... .......... .......... .......... .......... 61% 24.1M 6s\n", - "366550K .......... .......... .......... .......... .......... 61% 52.6M 6s\n", - "366600K .......... .......... .......... .......... .......... 61% 13.0M 6s\n", - "366650K .......... .......... .......... .......... .......... 61% 67.9M 6s\n", - "366700K .......... .......... .......... .......... .......... 61% 12.7M 6s\n", - "366750K .......... .......... .......... .......... .......... 61% 65.6M 6s\n", - "366800K .......... .......... .......... .......... .......... 61% 12.4M 6s\n", - "366850K .......... .......... .......... .......... .......... 61% 61.7M 6s\n", - "366900K .......... .......... .......... .......... .......... 61% 14.8M 6s\n", - "366950K .......... .......... .......... .......... .......... 61% 46.6M 6s\n", - "367000K .......... .......... .......... .......... .......... 61% 12.6M 6s\n", - "367050K .......... .......... .......... .......... .......... 61% 48.3M 6s\n", - "367100K .......... .......... .......... .......... .......... 61% 15.6M 6s\n", - "367150K .......... .......... .......... .......... .......... 61% 55.5M 6s\n", - "367200K .......... .......... .......... .......... .......... 61% 41.8M 6s\n", - "367250K .......... .......... .......... .......... .......... 61% 15.7M 6s\n", - "367300K .......... .......... .......... .......... .......... 61% 41.0M 6s\n", - "367350K .......... .......... .......... .......... .......... 61% 14.9M 6s\n", - "367400K .......... .......... .......... .......... .......... 61% 41.5M 6s\n", - "367450K .......... .......... .......... .......... .......... 61% 14.8M 6s\n", - "367500K .......... .......... .......... .......... .......... 61% 39.8M 6s\n", - "367550K .......... .......... .......... .......... .......... 61% 16.4M 6s\n", - "367600K .......... .......... .......... .......... .......... 61% 45.9M 6s\n", - "367650K .......... .......... .......... .......... .......... 61% 51.6M 6s\n", - "367700K .......... .......... .......... .......... .......... 61% 15.1M 6s\n", - "367750K .......... .......... .......... .......... .......... 61% 41.3M 6s\n", - "367800K .......... .......... .......... .......... .......... 61% 15.2M 6s\n", - "367850K .......... .......... .......... .......... .......... 61% 46.6M 6s\n", - "367900K .......... .......... .......... .......... .......... 61% 16.4M 6s\n", - "367950K .......... .......... .......... .......... .......... 61% 40.9M 6s\n", - "368000K .......... .......... .......... .......... .......... 61% 16.1M 6s\n", - "368050K .......... .......... .......... .......... .......... 61% 60.9M 6s\n", - "368100K .......... .......... .......... .......... .......... 61% 38.7M 6s\n", - "368150K .......... .......... .......... .......... .......... 61% 16.8M 6s\n", - "368200K .......... .......... .......... .......... .......... 61% 39.0M 6s\n", - "368250K .......... .......... .......... .......... .......... 61% 14.7M 6s\n", - "368300K .......... .......... .......... .......... .......... 61% 61.4M 6s\n", - "368350K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", - "368400K .......... .......... .......... .......... .......... 61% 42.3M 6s\n", - "368450K .......... .......... .......... .......... .......... 61% 47.4M 6s\n", - "368500K .......... .......... .......... .......... .......... 61% 16.4M 6s\n", - "368550K .......... .......... .......... .......... .......... 61% 46.1M 6s\n", - "368600K .......... .......... .......... .......... .......... 61% 15.5M 6s\n", - "368650K .......... .......... .......... .......... .......... 61% 44.4M 6s\n", - "368700K .......... .......... .......... .......... .......... 62% 16.1M 6s\n", - "368750K .......... .......... .......... .......... .......... 62% 57.1M 6s\n", - "368800K .......... .......... .......... .......... .......... 62% 43.8M 6s\n", - "368850K .......... .......... .......... .......... .......... 62% 14.1M 6s\n", - "368900K .......... .......... .......... .......... .......... 62% 34.5M 6s\n", - "368950K .......... .......... .......... .......... .......... 62% 19.0M 6s\n", - "369000K .......... .......... .......... .......... .......... 62% 34.3M 6s\n", - "369050K .......... .......... .......... .......... .......... 62% 67.0M 6s\n", - "369100K .......... .......... .......... .......... .......... 62% 16.6M 6s\n", - "369150K .......... .......... .......... .......... .......... 62% 48.4M 6s\n", - "369200K .......... .......... .......... .......... .......... 62% 14.8M 6s\n", - "369250K .......... .......... .......... .......... .......... 62% 67.6M 6s\n", - "369300K .......... .......... .......... .......... .......... 62% 54.5M 6s\n", - "369350K .......... .......... .......... .......... .......... 62% 13.6M 6s\n", - "369400K .......... .......... .......... .......... .......... 62% 38.3M 6s\n", - "369450K .......... .......... .......... .......... .......... 62% 19.6M 6s\n", - "369500K .......... .......... .......... .......... .......... 62% 63.9M 6s\n", - "369550K .......... .......... .......... .......... .......... 62% 47.6M 6s\n", - "369600K .......... .......... .......... .......... .......... 62% 14.4M 6s\n", - "369650K .......... .......... .......... .......... .......... 62% 52.3M 6s\n", - "369700K .......... .......... .......... .......... .......... 62% 16.6M 6s\n", - "369750K .......... .......... .......... .......... .......... 62% 62.7M 6s\n", - "369800K .......... .......... .......... .......... .......... 62% 13.2M 6s\n", - "369850K .......... .......... .......... .......... .......... 62% 59.5M 6s\n", - "369900K .......... .......... .......... .......... .......... 62% 69.3M 6s\n", - "369950K .......... .......... .......... .......... .......... 62% 14.9M 6s\n", - "370000K .......... .......... .......... .......... .......... 62% 56.5M 6s\n", - "370050K .......... .......... .......... .......... .......... 62% 54.6M 6s\n", - "370100K .......... .......... .......... .......... .......... 62% 15.2M 6s\n", - "370150K .......... .......... .......... .......... .......... 62% 71.8M 6s\n", - "370200K .......... .......... .......... .......... .......... 62% 14.7M 6s\n", - "370250K .......... .......... .......... .......... .......... 62% 62.3M 6s\n", - "370300K .......... .......... .......... .......... .......... 62% 57.0M 6s\n", - "370350K .......... .......... .......... .......... .......... 62% 16.4M 6s\n", - "370400K .......... .......... .......... .......... .......... 62% 63.3M 6s\n", - "370450K .......... .......... .......... .......... .......... 62% 42.8M 6s\n", - "370500K .......... .......... .......... .......... .......... 62% 14.6M 6s\n", - "370550K .......... .......... .......... .......... .......... 62% 63.7M 6s\n", - "370600K .......... .......... .......... .......... .......... 62% 15.6M 6s\n", - "370650K .......... .......... .......... .......... .......... 62% 51.2M 6s\n", - "370700K .......... .......... .......... .......... .......... 62% 54.4M 6s\n", - "370750K .......... .......... .......... .......... .......... 62% 15.8M 6s\n", - "370800K .......... .......... .......... .......... .......... 62% 50.7M 6s\n", - "370850K .......... .......... .......... .......... .......... 62% 74.8M 6s\n", - "370900K .......... .......... .......... .......... .......... 62% 15.5M 6s\n", - "370950K .......... .......... .......... .......... .......... 62% 52.0M 6s\n", - "371000K .......... .......... .......... .......... .......... 62% 15.9M 6s\n", - "371050K .......... .......... .......... .......... .......... 62% 38.1M 6s\n", - "371100K .......... .......... .......... .......... .......... 62% 76.8M 6s\n", - "371150K .......... .......... .......... .......... .......... 62% 18.3M 6s\n", - "371200K .......... .......... .......... .......... .......... 62% 55.1M 6s\n", - "371250K .......... .......... .......... .......... .......... 62% 71.7M 6s\n", - "371300K .......... .......... .......... .......... .......... 62% 15.5M 6s\n", - "371350K .......... .......... .......... .......... .......... 62% 54.8M 6s\n", - "371400K .......... .......... .......... .......... .......... 62% 16.2M 6s\n", - "371450K .......... .......... .......... .......... .......... 62% 50.2M 6s\n", - "371500K .......... .......... .......... .......... .......... 62% 61.7M 6s\n", - "371550K .......... .......... .......... .......... .......... 62% 15.7M 6s\n", - "371600K .......... .......... .......... .......... .......... 62% 50.1M 6s\n", - "371650K .......... .......... .......... .......... .......... 62% 68.5M 6s\n", - "371700K .......... .......... .......... .......... .......... 62% 16.9M 6s\n", - "371750K .......... .......... .......... .......... .......... 62% 66.6M 6s\n", - "371800K .......... .......... .......... .......... .......... 62% 15.1M 6s\n", - "371850K .......... .......... .......... .......... .......... 62% 62.7M 6s\n", - "371900K .......... .......... .......... .......... .......... 62% 69.3M 6s\n", - "371950K .......... .......... .......... .......... .......... 62% 16.5M 6s\n", - "372000K .......... .......... .......... .......... .......... 62% 41.6M 6s\n", - "372050K .......... .......... .......... .......... .......... 62% 71.2M 6s\n", - "372100K .......... .......... .......... .......... .......... 62% 18.2M 6s\n", - "372150K .......... .......... .......... .......... .......... 62% 42.0M 6s\n", - "372200K .......... .......... .......... .......... .......... 62% 52.4M 6s\n", - "372250K .......... .......... .......... .......... .......... 62% 16.8M 6s\n", - "372300K .......... .......... .......... .......... .......... 62% 58.8M 6s\n", - "372350K .......... .......... .......... .......... .......... 62% 59.2M 6s\n", - "372400K .......... .......... .......... .......... .......... 62% 15.9M 6s\n", - "372450K .......... .......... .......... .......... .......... 62% 61.7M 6s\n", - "372500K .......... .......... .......... .......... .......... 62% 64.3M 6s\n", - "372550K .......... .......... .......... .......... .......... 62% 16.7M 6s\n", - "372600K .......... .......... .......... .......... .......... 62% 52.7M 6s\n", - "372650K .......... .......... .......... .......... .......... 62% 16.2M 6s\n", - "372700K .......... .......... .......... .......... .......... 62% 48.3M 6s\n", - "372750K .......... .......... .......... .......... .......... 62% 54.4M 6s\n", - "372800K .......... .......... .......... .......... .......... 62% 18.4M 6s\n", - "372850K .......... .......... .......... .......... .......... 62% 51.1M 6s\n", - "372900K .......... .......... .......... .......... .......... 62% 56.3M 6s\n", - "372950K .......... .......... .......... .......... .......... 62% 18.3M 6s\n", - "373000K .......... .......... .......... .......... .......... 62% 35.7M 6s\n", - "373050K .......... .......... .......... .......... .......... 62% 65.0M 6s\n", - "373100K .......... .......... .......... .......... .......... 62% 19.2M 6s\n", - "373150K .......... .......... .......... .......... .......... 62% 59.0M 6s\n", - "373200K .......... .......... .......... .......... .......... 62% 58.9M 6s\n", - "373250K .......... .......... .......... .......... .......... 62% 17.2M 6s\n", - "373300K .......... .......... .......... .......... .......... 62% 46.7M 6s\n", - "373350K .......... .......... .......... .......... .......... 62% 67.1M 6s\n", - "373400K .......... .......... .......... .......... .......... 62% 18.0M 6s\n", - "373450K .......... .......... .......... .......... .......... 62% 36.6M 6s\n", - "373500K .......... .......... .......... .......... .......... 62% 60.5M 6s\n", - "373550K .......... .......... .......... .......... .......... 62% 18.1M 6s\n", - "373600K .......... .......... .......... .......... .......... 62% 53.6M 6s\n", - "373650K .......... .......... .......... .......... .......... 62% 62.8M 6s\n", - "373700K .......... .......... .......... .......... .......... 62% 18.2M 6s\n", - "373750K .......... .......... .......... .......... .......... 62% 35.8M 6s\n", - "373800K .......... .......... .......... .......... .......... 62% 40.6M 6s\n", - "373850K .......... .......... .......... .......... .......... 62% 26.8M 6s\n", - "373900K .......... .......... .......... .......... .......... 62% 30.4M 6s\n", - "373950K .......... .......... .......... .......... .......... 62% 47.2M 6s\n", - "374000K .......... .......... .......... .......... .......... 62% 24.6M 6s\n", - "374050K .......... .......... .......... .......... .......... 62% 34.7M 6s\n", - "374100K .......... .......... .......... .......... .......... 62% 45.5M 6s\n", - "374150K .......... .......... .......... .......... .......... 62% 22.6M 6s\n", - "374200K .......... .......... .......... .......... .......... 62% 37.3M 6s\n", - "374250K .......... .......... .......... .......... .......... 62% 37.2M 6s\n", - "374300K .......... .......... .......... .......... .......... 62% 24.1M 6s\n", - "374350K .......... .......... .......... .......... .......... 62% 42.5M 6s\n", - "374400K .......... .......... .......... .......... .......... 62% 52.1M 6s\n", - "374450K .......... .......... .......... .......... .......... 62% 18.8M 6s\n", - "374500K .......... .......... .......... .......... .......... 62% 63.6M 6s\n", - "374550K .......... .......... .......... .......... .......... 62% 44.3M 6s\n", - "374600K .......... .......... .......... .......... .......... 62% 18.1M 6s\n", - "374650K .......... .......... .......... .......... .......... 63% 63.6M 6s\n", - "374700K .......... .......... .......... .......... .......... 63% 60.4M 6s\n", - "374750K .......... .......... .......... .......... .......... 63% 15.5M 6s\n", - "374800K .......... .......... .......... .......... .......... 63% 59.4M 6s\n", - "374850K .......... .......... .......... .......... .......... 63% 65.9M 6s\n", - "374900K .......... .......... .......... .......... .......... 63% 15.2M 6s\n", - "374950K .......... .......... .......... .......... .......... 63% 69.2M 6s\n", - "375000K .......... .......... .......... .......... .......... 63% 59.0M 6s\n", - "375050K .......... .......... .......... .......... .......... 63% 17.0M 6s\n", - "375100K .......... .......... .......... .......... .......... 63% 63.7M 6s\n", - "375150K .......... .......... .......... .......... .......... 63% 67.0M 6s\n", - "375200K .......... .......... .......... .......... .......... 63% 68.8M 6s\n", - "375250K .......... .......... .......... .......... .......... 63% 16.5M 6s\n", - "375300K .......... .......... .......... .......... .......... 63% 57.7M 6s\n", - "375350K .......... .......... .......... .......... .......... 63% 74.0M 6s\n", - "375400K .......... .......... .......... .......... .......... 63% 16.4M 6s\n", - "375450K .......... .......... .......... .......... .......... 63% 56.9M 6s\n", - "375500K .......... .......... .......... .......... .......... 63% 69.5M 6s\n", - "375550K .......... .......... .......... .......... .......... 63% 18.3M 6s\n", - "375600K .......... .......... .......... .......... .......... 63% 49.8M 6s\n", - "375650K .......... .......... .......... .......... .......... 63% 68.1M 6s\n", - "375700K .......... .......... .......... .......... .......... 63% 18.6M 6s\n", - "375750K .......... .......... .......... .......... .......... 63% 50.4M 6s\n", - "375800K .......... .......... .......... .......... .......... 63% 47.0M 6s\n", - "375850K .......... .......... .......... .......... .......... 63% 20.1M 6s\n", - "375900K .......... .......... .......... .......... .......... 63% 55.5M 6s\n", - "375950K .......... .......... .......... .......... .......... 63% 54.8M 6s\n", - "376000K .......... .......... .......... .......... .......... 63% 71.5M 6s\n", - "376050K .......... .......... .......... .......... .......... 63% 17.5M 6s\n", - "376100K .......... .......... .......... .......... .......... 63% 63.1M 6s\n", - "376150K .......... .......... .......... .......... .......... 63% 70.5M 6s\n", - "376200K .......... .......... .......... .......... .......... 63% 18.7M 6s\n", - "376250K .......... .......... .......... .......... .......... 63% 44.2M 6s\n", - "376300K .......... .......... .......... .......... .......... 63% 62.7M 6s\n", - "376350K .......... .......... .......... .......... .......... 63% 21.3M 6s\n", - "376400K .......... .......... .......... .......... .......... 63% 42.6M 6s\n", - "376450K .......... .......... .......... .......... .......... 63% 60.8M 6s\n", - "376500K .......... .......... .......... .......... .......... 63% 20.8M 6s\n", - "376550K .......... .......... .......... .......... .......... 63% 48.1M 6s\n", - "376600K .......... .......... .......... .......... .......... 63% 45.3M 6s\n", - "376650K .......... .......... .......... .......... .......... 63% 20.9M 6s\n", - "376700K .......... .......... .......... .......... .......... 63% 47.4M 6s\n", - "376750K .......... .......... .......... .......... .......... 63% 67.0M 6s\n", - "376800K .......... .......... .......... .......... .......... 63% 61.1M 6s\n", - "376850K .......... .......... .......... .......... .......... 63% 19.6M 6s\n", - "376900K .......... .......... .......... .......... .......... 63% 44.0M 6s\n", - "376950K .......... .......... .......... .......... .......... 63% 63.1M 6s\n", - "377000K .......... .......... .......... .......... .......... 63% 21.7M 6s\n", - "377050K .......... .......... .......... .......... .......... 63% 44.1M 6s\n", - "377100K .......... .......... .......... .......... .......... 63% 52.0M 6s\n", - "377150K .......... .......... .......... .......... .......... 63% 23.7M 6s\n", - "377200K .......... .......... .......... .......... .......... 63% 48.3M 6s\n", - "377250K .......... .......... .......... .......... .......... 63% 51.3M 6s\n", - "377300K .......... .......... .......... .......... .......... 63% 50.3M 6s\n", - "377350K .......... .......... .......... .......... .......... 63% 23.5M 6s\n", - "377400K .......... .......... .......... .......... .......... 63% 39.5M 6s\n", - "377450K .......... .......... .......... .......... .......... 63% 52.7M 6s\n", - "377500K .......... .......... .......... .......... .......... 63% 25.3M 6s\n", - "377550K .......... .......... .......... .......... .......... 63% 38.5M 6s\n", - "377600K .......... .......... .......... .......... .......... 63% 39.0M 6s\n", - "377650K .......... .......... .......... .......... .......... 63% 72.7M 6s\n", - "377700K .......... .......... .......... .......... .......... 63% 20.8M 6s\n", - "377750K .......... .......... .......... .......... .......... 63% 55.5M 6s\n", - "377800K .......... .......... .......... .......... .......... 63% 53.6M 6s\n", - "377850K .......... .......... .......... .......... .......... 63% 25.2M 6s\n", - "377900K .......... .......... .......... .......... .......... 63% 37.0M 6s\n", - "377950K .......... .......... .......... .......... .......... 63% 65.0M 6s\n", - "378000K .......... .......... .......... .......... .......... 63% 23.9M 6s\n", - "378050K .......... .......... .......... .......... .......... 63% 36.4M 6s\n", - "378100K .......... .......... .......... .......... .......... 63% 53.2M 6s\n", - "378150K .......... .......... .......... .......... .......... 63% 70.8M 6s\n", - "378200K .......... .......... .......... .......... .......... 63% 16.4M 6s\n", - "378250K .......... .......... .......... .......... .......... 63% 54.1M 6s\n", - "378300K .......... .......... .......... .......... .......... 63% 73.2M 6s\n", - "378350K .......... .......... .......... .......... .......... 63% 29.7M 6s\n", - "378400K .......... .......... .......... .......... .......... 63% 26.9M 6s\n", - "378450K .......... .......... .......... .......... .......... 63% 66.6M 6s\n", - "378500K .......... .......... .......... .......... .......... 63% 79.2M 6s\n", - "378550K .......... .......... .......... .......... .......... 63% 29.2M 6s\n", - "378600K .......... .......... .......... .......... .......... 63% 24.5M 6s\n", - "378650K .......... .......... .......... .......... .......... 63% 76.8M 6s\n", - "378700K .......... .......... .......... .......... .......... 63% 28.3M 6s\n", - "378750K .......... .......... .......... .......... .......... 63% 32.6M 6s\n", - "378800K .......... .......... .......... .......... .......... 63% 54.0M 6s\n", - "378850K .......... .......... .......... .......... .......... 63% 59.4M 6s\n", - "378900K .......... .......... .......... .......... .......... 63% 26.5M 6s\n", - "378950K .......... .......... .......... .......... .......... 63% 31.7M 6s\n", - "379000K .......... .......... .......... .......... .......... 63% 60.1M 6s\n", - "379050K .......... .......... .......... .......... .......... 63% 26.1M 6s\n", - "379100K .......... .......... .......... .......... .......... 63% 34.9M 6s\n", - "379150K .......... .......... .......... .......... .......... 63% 66.8M 6s\n", - "379200K .......... .......... .......... .......... .......... 63% 71.9M 6s\n", - "379250K .......... .......... .......... .......... .......... 63% 23.1M 6s\n", - "379300K .......... .......... .......... .......... .......... 63% 35.2M 6s\n", - "379350K .......... .......... .......... .......... .......... 63% 71.6M 6s\n", - "379400K .......... .......... .......... .......... .......... 63% 22.2M 6s\n", - "379450K .......... .......... .......... .......... .......... 63% 34.0M 6s\n", - "379500K .......... .......... .......... .......... .......... 63% 61.5M 6s\n", - "379550K .......... .......... .......... .......... .......... 63% 78.3M 6s\n", - "379600K .......... .......... .......... .......... .......... 63% 20.9M 6s\n", - "379650K .......... .......... .......... .......... .......... 63% 47.4M 6s\n", - "379700K .......... .......... .......... .......... .......... 63% 69.0M 6s\n", - "379750K .......... .......... .......... .......... .......... 63% 22.0M 6s\n", - "379800K .......... .......... .......... .......... .......... 63% 27.7M 6s\n", - "379850K .......... .......... .......... .......... .......... 63% 42.9M 6s\n", - "379900K .......... .......... .......... .......... .......... 63% 38.6M 6s\n", - "379950K .......... .......... .......... .......... .......... 63% 43.3M 6s\n", - "380000K .......... .......... .......... .......... .......... 63% 33.4M 6s\n", - "380050K .......... .......... .......... .......... .......... 63% 65.9M 6s\n", - "380100K .......... .......... .......... .......... .......... 63% 38.6M 6s\n", - "380150K .......... .......... .......... .......... .......... 63% 29.5M 6s\n", - "380200K .......... .......... .......... .......... .......... 63% 30.5M 6s\n", - "380250K .......... .......... .......... .......... .......... 63% 40.6M 6s\n", - "380300K .......... .......... .......... .......... .......... 63% 45.5M 6s\n", - "380350K .......... .......... .......... .......... .......... 63% 40.3M 6s\n", - "380400K .......... .......... .......... .......... .......... 63% 42.9M 6s\n", - "380450K .......... .......... .......... .......... .......... 63% 77.7M 6s\n", - "380500K .......... .......... .......... .......... .......... 63% 36.7M 6s\n", - "380550K .......... .......... .......... .......... .......... 63% 37.1M 6s\n", - "380600K .......... .......... .......... .......... .......... 64% 49.7M 6s\n", - "380650K .......... .......... .......... .......... .......... 64% 45.3M 6s\n", - "380700K .......... .......... .......... .......... .......... 64% 26.3M 6s\n", - "380750K .......... .......... .......... .......... .......... 64% 62.3M 6s\n", - "380800K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", - "380850K .......... .......... .......... .......... .......... 64% 32.7M 6s\n", - "380900K .......... .......... .......... .......... .......... 64% 38.6M 6s\n", - "380950K .......... .......... .......... .......... .......... 64% 41.1M 6s\n", - "381000K .......... .......... .......... .......... .......... 64% 41.1M 6s\n", - "381050K .......... .......... .......... .......... .......... 64% 33.3M 6s\n", - "381100K .......... .......... .......... .......... .......... 64% 37.2M 6s\n", - "381150K .......... .......... .......... .......... .......... 64% 51.8M 6s\n", - "381200K .......... .......... .......... .......... .......... 64% 47.6M 6s\n", - "381250K .......... .......... .......... .......... .......... 64% 42.1M 6s\n", - "381300K .......... .......... .......... .......... .......... 64% 30.2M 6s\n", - "381350K .......... .......... .......... .......... .......... 64% 39.9M 6s\n", - "381400K .......... .......... .......... .......... .......... 64% 46.7M 6s\n", - "381450K .......... .......... .......... .......... .......... 64% 32.2M 6s\n", - "381500K .......... .......... .......... .......... .......... 64% 50.9M 6s\n", - "381550K .......... .......... .......... .......... .......... 64% 53.2M 6s\n", - "381600K .......... .......... .......... .......... .......... 64% 37.1M 6s\n", - "381650K .......... .......... .......... .......... .......... 64% 40.7M 6s\n", - "381700K .......... .......... .......... .......... .......... 64% 35.4M 6s\n", - "381750K .......... .......... .......... .......... .......... 64% 51.6M 6s\n", - "381800K .......... .......... .......... .......... .......... 64% 45.3M 6s\n", - "381850K .......... .......... .......... .......... .......... 64% 7.14M 6s\n", - "381900K .......... .......... .......... .......... .......... 64% 70.7M 6s\n", - "381950K .......... .......... .......... .......... .......... 64% 85.1M 6s\n", - "382000K .......... .......... .......... .......... .......... 64% 73.2M 6s\n", - "382050K .......... .......... .......... .......... .......... 64% 18.2M 6s\n", - "382100K .......... .......... .......... .......... .......... 64% 50.7M 6s\n", - "382150K .......... .......... .......... .......... .......... 64% 75.5M 6s\n", - "382200K .......... .......... .......... .......... .......... 64% 67.8M 6s\n", - "382250K .......... .......... .......... .......... .......... 64% 20.6M 6s\n", - "382300K .......... .......... .......... .......... .......... 64% 59.2M 6s\n", - "382350K .......... .......... .......... .......... .......... 64% 74.1M 6s\n", - "382400K .......... .......... .......... .......... .......... 64% 65.7M 6s\n", - "382450K .......... .......... .......... .......... .......... 64% 22.2M 6s\n", - "382500K .......... .......... .......... .......... .......... 64% 56.2M 6s\n", - "382550K .......... .......... .......... .......... .......... 64% 81.0M 6s\n", - "382600K .......... .......... .......... .......... .......... 64% 19.7M 6s\n", - "382650K .......... .......... .......... .......... .......... 64% 46.0M 6s\n", - "382700K .......... .......... .......... .......... .......... 64% 55.3M 6s\n", - "382750K .......... .......... .......... .......... .......... 64% 83.4M 6s\n", - "382800K .......... .......... .......... .......... .......... 64% 22.7M 6s\n", - "382850K .......... .......... .......... .......... .......... 64% 57.1M 6s\n", - "382900K .......... .......... .......... .......... .......... 64% 58.0M 6s\n", - "382950K .......... .......... .......... .......... .......... 64% 77.3M 6s\n", - "383000K .......... .......... .......... .......... .......... 64% 20.1M 6s\n", - "383050K .......... .......... .......... .......... .......... 64% 47.0M 6s\n", - "383100K .......... .......... .......... .......... .......... 64% 67.9M 6s\n", - "383150K .......... .......... .......... .......... .......... 64% 74.4M 6s\n", - "383200K .......... .......... .......... .......... .......... 64% 21.2M 6s\n", - "383250K .......... .......... .......... .......... .......... 64% 54.0M 6s\n", - "383300K .......... .......... .......... .......... .......... 64% 66.4M 6s\n", - "383350K .......... .......... .......... .......... .......... 64% 78.2M 6s\n", - "383400K .......... .......... .......... .......... .......... 64% 19.8M 6s\n", - "383450K .......... .......... .......... .......... .......... 64% 60.2M 6s\n", - "383500K .......... .......... .......... .......... .......... 64% 74.0M 6s\n", - "383550K .......... .......... .......... .......... .......... 64% 72.8M 6s\n", - "383600K .......... .......... .......... .......... .......... 64% 21.2M 6s\n", - "383650K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", - "383700K .......... .......... .......... .......... .......... 64% 65.3M 6s\n", - "383750K .......... .......... .......... .......... .......... 64% 78.1M 6s\n", - "383800K .......... .......... .......... .......... .......... 64% 20.5M 6s\n", - "383850K .......... .......... .......... .......... .......... 64% 57.1M 6s\n", - "383900K .......... .......... .......... .......... .......... 64% 70.9M 6s\n", - "383950K .......... .......... .......... .......... .......... 64% 73.5M 6s\n", - "384000K .......... .......... .......... .......... .......... 64% 22.7M 6s\n", - "384050K .......... .......... .......... .......... .......... 64% 55.1M 6s\n", - "384100K .......... .......... .......... .......... .......... 64% 61.1M 6s\n", - "384150K .......... .......... .......... .......... .......... 64% 79.2M 6s\n", - "384200K .......... .......... .......... .......... .......... 64% 20.1M 6s\n", - "384250K .......... .......... .......... .......... .......... 64% 52.9M 6s\n", - "384300K .......... .......... .......... .......... .......... 64% 66.2M 6s\n", - "384350K .......... .......... .......... .......... .......... 64% 26.7M 6s\n", - "384400K .......... .......... .......... .......... .......... 64% 51.0M 6s\n", - "384450K .......... .......... .......... .......... .......... 64% 59.3M 6s\n", - "384500K .......... .......... .......... .......... .......... 64% 62.2M 6s\n", - "384550K .......... .......... .......... .......... .......... 64% 75.8M 6s\n", - "384600K .......... .......... .......... .......... .......... 64% 21.4M 6s\n", - "384650K .......... .......... .......... .......... .......... 64% 42.6M 6s\n", - "384700K .......... .......... .......... .......... .......... 64% 58.2M 6s\n", - "384750K .......... .......... .......... .......... .......... 64% 31.1M 5s\n", - "384800K .......... .......... .......... .......... .......... 64% 46.3M 5s\n", - "384850K .......... .......... .......... .......... .......... 64% 36.0M 5s\n", - "384900K .......... .......... .......... .......... .......... 64% 67.7M 5s\n", - "384950K .......... .......... .......... .......... .......... 64% 65.2M 5s\n", - "385000K .......... .......... .......... .......... .......... 64% 30.1M 5s\n", - "385050K .......... .......... .......... .......... .......... 64% 36.7M 5s\n", - "385100K .......... .......... .......... .......... .......... 64% 57.1M 5s\n", - "385150K .......... .......... .......... .......... .......... 64% 29.7M 5s\n", - "385200K .......... .......... .......... .......... .......... 64% 36.8M 5s\n", - "385250K .......... .......... .......... .......... .......... 64% 49.2M 5s\n", - "385300K .......... .......... .......... .......... .......... 64% 76.8M 5s\n", - "385350K .......... .......... .......... .......... .......... 64% 83.0M 5s\n", - "385400K .......... .......... .......... .......... .......... 64% 21.1M 5s\n", + " 81800K .......... .......... .......... .......... .......... 13% 49.8M 11s\n", + " 81850K .......... .......... .......... .......... .......... 13% 65.3M 11s\n", + " 81900K .......... .......... .......... .......... .......... 13% 44.9M 11s\n", + " 81950K .......... .......... .......... .......... .......... 13% 60.1M 11s\n", + " 82000K .......... .......... .......... .......... .......... 13% 60.4M 11s\n", + " 82050K .......... .......... .......... .......... .......... 13% 57.1M 11s\n", + " 82100K .......... .......... .......... .......... .......... 13% 72.8M 11s\n", + " 82150K .......... .......... .......... .......... .......... 13% 61.1M 11s\n", + " 82200K .......... .......... .......... .......... .......... 13% 37.5M 11s\n", + " 82250K .......... .......... .......... .......... .......... 13% 56.5M 11s\n", + " 82300K .......... .......... .......... .......... .......... 13% 49.4M 11s\n", + " 82350K .......... .......... .......... .......... .......... 13% 58.4M 11s\n", + " 82400K .......... .......... .......... .......... .......... 13% 52.4M 11s\n", + " 82450K .......... .......... .......... .......... .......... 13% 48.5M 11s\n", + " 82500K .......... .......... .......... .......... .......... 13% 65.7M 11s\n", + " 82550K .......... .......... .......... .......... .......... 13% 65.1M 11s\n", + " 82600K .......... .......... .......... .......... .......... 13% 50.1M 11s\n", + " 82650K .......... .......... .......... .......... .......... 13% 65.4M 11s\n", + " 82700K .......... .......... .......... .......... .......... 13% 56.9M 11s\n", + " 82750K .......... .......... .......... .......... .......... 13% 61.1M 11s\n", + " 82800K .......... .......... .......... .......... .......... 13% 50.5M 11s\n", + " 82850K .......... .......... .......... .......... .......... 13% 48.5M 11s\n", + " 82900K .......... .......... .......... .......... .......... 13% 47.5M 11s\n", + " 82950K .......... .......... .......... .......... .......... 13% 61.8M 11s\n", + " 83000K .......... .......... .......... .......... .......... 13% 40.3M 11s\n", + " 83050K .......... .......... .......... .......... .......... 13% 46.7M 11s\n", + " 83100K .......... .......... .......... .......... .......... 13% 58.9M 11s\n", + " 83150K .......... .......... .......... .......... .......... 13% 83.6M 11s\n", + " 83200K .......... .......... .......... .......... .......... 13% 62.5M 11s\n", + " 83250K .......... .......... .......... .......... .......... 14% 66.0M 11s\n", + " 83300K .......... .......... .......... .......... .......... 14% 73.4M 11s\n", + " 83350K .......... .......... .......... .......... .......... 14% 71.9M 11s\n", + " 83400K .......... .......... .......... .......... .......... 14% 59.0M 11s\n", + " 83450K .......... .......... .......... .......... .......... 14% 60.3M 11s\n", + " 83500K .......... .......... .......... .......... .......... 14% 66.2M 11s\n", + " 83550K .......... .......... .......... .......... .......... 14% 59.2M 11s\n", + " 83600K .......... .......... .......... .......... .......... 14% 54.8M 11s\n", + " 83650K .......... .......... .......... .......... .......... 14% 62.4M 11s\n", + " 83700K .......... .......... .......... .......... .......... 14% 57.2M 11s\n", + " 83750K .......... .......... .......... .......... .......... 14% 72.7M 11s\n", + " 83800K .......... .......... .......... .......... .......... 14% 37.8M 11s\n", + " 83850K .......... .......... .......... .......... .......... 14% 45.0M 11s\n", + " 83900K .......... .......... .......... .......... .......... 14% 59.6M 11s\n", + " 83950K .......... .......... .......... .......... .......... 14% 63.2M 11s\n", + " 84000K .......... .......... .......... .......... .......... 14% 54.3M 11s\n", + " 84050K .......... .......... .......... .......... .......... 14% 3.85M 11s\n", + " 84100K .......... .......... .......... .......... .......... 14% 59.8M 11s\n", + " 84150K .......... .......... .......... .......... .......... 14% 69.5M 11s\n", + " 84200K .......... .......... .......... .......... .......... 14% 57.3M 11s\n", + " 84250K .......... .......... .......... .......... .......... 14% 67.1M 11s\n", + " 84300K .......... .......... .......... .......... .......... 14% 65.6M 11s\n", + " 84350K .......... .......... .......... .......... .......... 14% 69.4M 11s\n", + " 84400K .......... .......... .......... .......... .......... 14% 54.2M 11s\n", + " 84450K .......... .......... .......... .......... .......... 14% 78.7M 11s\n", + " 84500K .......... .......... .......... .......... .......... 14% 71.6M 11s\n", + " 84550K .......... .......... .......... .......... .......... 14% 71.6M 11s\n", + " 84600K .......... .......... .......... .......... .......... 14% 61.4M 11s\n", + " 84650K .......... .......... .......... .......... .......... 14% 55.3M 11s\n", + " 84700K .......... .......... .......... .......... .......... 14% 49.1M 11s\n", + " 84750K .......... .......... .......... .......... .......... 14% 71.5M 11s\n", + " 84800K .......... .......... .......... .......... .......... 14% 18.6M 11s\n", + " 84850K .......... .......... .......... .......... .......... 14% 51.3M 11s\n", + " 84900K .......... .......... .......... .......... .......... 14% 66.0M 11s\n", + " 84950K .......... .......... .......... .......... .......... 14% 64.6M 11s\n", + " 85000K .......... .......... .......... .......... .......... 14% 48.8M 11s\n", + " 85050K .......... .......... .......... .......... .......... 14% 59.9M 11s\n", + " 85100K .......... .......... .......... .......... .......... 14% 52.1M 11s\n", + " 85150K .......... .......... .......... .......... .......... 14% 62.4M 11s\n", + " 85200K .......... .......... .......... .......... .......... 14% 67.6M 11s\n", + " 85250K .......... .......... .......... .......... .......... 14% 69.1M 11s\n", + " 85300K .......... .......... .......... .......... .......... 14% 58.2M 11s\n", + " 85350K .......... .......... .......... .......... .......... 14% 52.3M 11s\n", + " 85400K .......... .......... .......... .......... .......... 14% 46.9M 11s\n", + " 85450K .......... .......... .......... .......... .......... 14% 77.0M 11s\n", + " 85500K .......... .......... .......... .......... .......... 14% 73.1M 11s\n", + " 85550K .......... .......... .......... .......... .......... 14% 64.0M 11s\n", + " 85600K .......... .......... .......... .......... .......... 14% 46.3M 11s\n", + " 85650K .......... .......... .......... .......... .......... 14% 59.5M 11s\n", + " 85700K .......... .......... .......... .......... .......... 14% 81.3M 11s\n", + " 85750K .......... .......... .......... .......... .......... 14% 62.2M 11s\n", + " 85800K .......... .......... .......... .......... .......... 14% 54.0M 11s\n", + " 85850K .......... .......... .......... .......... .......... 14% 71.0M 11s\n", + " 85900K .......... .......... .......... .......... .......... 14% 73.9M 11s\n", + " 85950K .......... .......... .......... .......... .......... 14% 66.9M 11s\n", + " 86000K .......... .......... .......... .......... .......... 14% 62.0M 11s\n", + " 86050K .......... .......... .......... .......... .......... 14% 63.0M 11s\n", + " 86100K .......... .......... .......... .......... .......... 14% 76.5M 11s\n", + " 86150K .......... .......... .......... .......... .......... 14% 66.0M 11s\n", + " 86200K .......... .......... .......... .......... .......... 14% 40.1M 11s\n", + " 86250K .......... .......... .......... .......... .......... 14% 56.5M 11s\n", + " 86300K .......... .......... .......... .......... .......... 14% 72.2M 11s\n", + " 86350K .......... .......... .......... .......... .......... 14% 58.8M 11s\n", + " 86400K .......... .......... .......... .......... .......... 14% 45.6M 11s\n", + " 86450K .......... .......... .......... .......... .......... 14% 57.2M 11s\n", + " 86500K .......... .......... .......... .......... .......... 14% 62.9M 11s\n", + " 86550K .......... .......... .......... .......... .......... 14% 59.1M 11s\n", + " 86600K .......... .......... .......... .......... .......... 14% 57.9M 11s\n", + " 86650K .......... .......... .......... .......... .......... 14% 64.5M 11s\n", + " 86700K .......... .......... .......... .......... .......... 14% 56.4M 11s\n", + " 86750K .......... .......... .......... .......... .......... 14% 73.0M 11s\n", + " 86800K .......... .......... .......... .......... .......... 14% 47.4M 11s\n", + " 86850K .......... .......... .......... .......... .......... 14% 50.9M 11s\n", + " 86900K .......... .......... .......... .......... .......... 14% 46.8M 11s\n", + " 86950K .......... .......... .......... .......... .......... 14% 41.6M 11s\n", + " 87000K .......... .......... .......... .......... .......... 14% 41.6M 11s\n", + " 87050K .......... .......... .......... .......... .......... 14% 45.3M 11s\n", + " 87100K .......... .......... .......... .......... .......... 14% 55.9M 11s\n", + " 87150K .......... .......... .......... .......... .......... 14% 39.8M 11s\n", + " 87200K .......... .......... .......... .......... .......... 14% 49.7M 11s\n", + " 87250K .......... .......... .......... .......... .......... 14% 67.0M 11s\n", + " 87300K .......... .......... .......... .......... .......... 14% 56.3M 11s\n", + " 87350K .......... .......... .......... .......... .......... 14% 57.6M 11s\n", + " 87400K .......... .......... .......... .......... .......... 14% 49.1M 11s\n", + " 87450K .......... .......... .......... .......... .......... 14% 54.4M 11s\n", + " 87500K .......... .......... .......... .......... .......... 14% 49.7M 11s\n", + " 87550K .......... .......... .......... .......... .......... 14% 66.0M 11s\n", + " 87600K .......... .......... .......... .......... .......... 14% 45.7M 11s\n", + " 87650K .......... .......... .......... .......... .......... 14% 62.2M 11s\n", + " 87700K .......... .......... .......... .......... .......... 14% 43.4M 11s\n", + " 87750K .......... .......... .......... .......... .......... 14% 35.4M 11s\n", + " 87800K .......... .......... .......... .......... .......... 14% 40.0M 11s\n", + " 87850K .......... .......... .......... .......... .......... 14% 54.0M 11s\n", + " 87900K .......... .......... .......... .......... .......... 14% 44.0M 11s\n", + " 87950K .......... .......... .......... .......... .......... 14% 43.8M 11s\n", + " 88000K .......... .......... .......... .......... .......... 14% 44.3M 11s\n", + " 88050K .......... .......... .......... .......... .......... 14% 62.1M 11s\n", + " 88100K .......... .......... .......... .......... .......... 14% 66.4M 11s\n", + " 88150K .......... .......... .......... .......... .......... 14% 56.3M 11s\n", + " 88200K .......... .......... .......... .......... .......... 14% 53.3M 11s\n", + " 88250K .......... .......... .......... .......... .......... 14% 55.7M 11s\n", + " 88300K .......... .......... .......... .......... .......... 14% 71.9M 11s\n", + " 88350K .......... .......... .......... .......... .......... 14% 67.5M 11s\n", + " 88400K .......... .......... .......... .......... .......... 14% 59.7M 11s\n", + " 88450K .......... .......... .......... .......... .......... 14% 50.9M 11s\n", + " 88500K .......... .......... .......... .......... .......... 14% 56.2M 11s\n", + " 88550K .......... .......... .......... .......... .......... 14% 58.7M 11s\n", + " 88600K .......... .......... .......... .......... .......... 14% 54.4M 11s\n", + " 88650K .......... .......... .......... .......... .......... 14% 75.6M 11s\n", + " 88700K .......... .......... .......... .......... .......... 14% 58.8M 11s\n", + " 88750K .......... .......... .......... .......... .......... 14% 46.7M 11s\n", + " 88800K .......... .......... .......... .......... .......... 14% 58.1M 11s\n", + " 88850K .......... .......... .......... .......... .......... 14% 59.9M 11s\n", + " 88900K .......... .......... .......... .......... .......... 14% 61.7M 11s\n", + " 88950K .......... .......... .......... .......... .......... 14% 54.4M 11s\n", + " 89000K .......... .......... .......... .......... .......... 14% 39.1M 11s\n", + " 89050K .......... .......... .......... .......... .......... 14% 65.5M 11s\n", + " 89100K .......... .......... .......... .......... .......... 14% 78.2M 11s\n", + " 89150K .......... .......... .......... .......... .......... 14% 67.9M 11s\n", + " 89200K .......... .......... .......... .......... .......... 15% 56.9M 11s\n", + " 89250K .......... .......... .......... .......... .......... 15% 55.9M 11s\n", + " 89300K .......... .......... .......... .......... .......... 15% 67.2M 11s\n", + " 89350K .......... .......... .......... .......... .......... 15% 57.6M 11s\n", + " 89400K .......... .......... .......... .......... .......... 15% 61.5M 11s\n", + " 89450K .......... .......... .......... .......... .......... 15% 73.5M 11s\n", + " 89500K .......... .......... .......... .......... .......... 15% 54.3M 11s\n", + " 89550K .......... .......... .......... .......... .......... 15% 61.4M 11s\n", + " 89600K .......... .......... .......... .......... .......... 15% 48.6M 11s\n", + " 89650K .......... .......... .......... .......... .......... 15% 62.7M 11s\n", + " 89700K .......... .......... .......... .......... .......... 15% 63.4M 11s\n", + " 89750K .......... .......... .......... .......... .......... 15% 72.3M 11s\n", + " 89800K .......... .......... .......... .......... .......... 15% 39.1M 11s\n", + " 89850K .......... .......... .......... .......... .......... 15% 51.7M 11s\n", + " 89900K .......... .......... .......... .......... .......... 15% 65.6M 11s\n", + " 89950K .......... .......... .......... .......... .......... 15% 68.0M 11s\n", + " 90000K .......... .......... .......... .......... .......... 15% 55.5M 11s\n", + " 90050K .......... .......... .......... .......... .......... 15% 69.6M 11s\n", + " 90100K .......... .......... .......... .......... .......... 15% 72.1M 10s\n", + " 90150K .......... .......... .......... .......... .......... 15% 68.7M 10s\n", + " 90200K .......... .......... .......... .......... .......... 15% 44.8M 10s\n", + " 90250K .......... .......... .......... .......... .......... 15% 52.5M 10s\n", + " 90300K .......... .......... .......... .......... .......... 15% 68.1M 10s\n", + " 90350K .......... .......... .......... .......... .......... 15% 52.0M 10s\n", + " 90400K .......... .......... .......... .......... .......... 15% 64.0M 10s\n", + " 90450K .......... .......... .......... .......... .......... 15% 75.3M 10s\n", + " 90500K .......... .......... .......... .......... .......... 15% 71.4M 10s\n", + " 90550K .......... .......... .......... .......... .......... 15% 69.3M 10s\n", + " 90600K .......... .......... .......... .......... .......... 15% 58.2M 10s\n", + " 90650K .......... .......... .......... .......... .......... 15% 72.9M 10s\n", + " 90700K .......... .......... .......... .......... .......... 15% 71.7M 10s\n", + " 90750K .......... .......... .......... .......... .......... 15% 71.7M 10s\n", + " 90800K .......... .......... .......... .......... .......... 15% 67.5M 10s\n", + " 90850K .......... .......... .......... .......... .......... 15% 66.1M 10s\n", + " 90900K .......... .......... .......... .......... .......... 15% 70.7M 10s\n", + " 90950K .......... .......... .......... .......... .......... 15% 74.9M 10s\n", + " 91000K .......... .......... .......... .......... .......... 15% 62.2M 10s\n", + " 91050K .......... .......... .......... .......... .......... 15% 50.0M 10s\n", + " 91100K .......... .......... .......... .......... .......... 15% 43.3M 10s\n", + " 91150K .......... .......... .......... .......... .......... 15% 45.0M 10s\n", + " 91200K .......... .......... .......... .......... .......... 15% 57.7M 10s\n", + " 91250K .......... .......... .......... .......... .......... 15% 53.6M 10s\n", + " 91300K .......... .......... .......... .......... .......... 15% 37.2M 10s\n", + " 91350K .......... .......... .......... .......... .......... 15% 36.7M 10s\n", + " 91400K .......... .......... .......... .......... .......... 15% 33.8M 10s\n", + " 91450K .......... .......... .......... .......... .......... 15% 42.1M 10s\n", + " 91500K .......... .......... .......... .......... .......... 15% 40.3M 10s\n", + " 91550K .......... .......... .......... .......... .......... 15% 41.4M 10s\n", + " 91600K .......... .......... .......... .......... .......... 15% 38.4M 10s\n", + " 91650K .......... .......... .......... .......... .......... 15% 47.7M 10s\n", + " 91700K .......... .......... .......... .......... .......... 15% 49.0M 10s\n", + " 91750K .......... .......... .......... .......... .......... 15% 43.8M 10s\n", + " 91800K .......... .......... .......... .......... .......... 15% 42.2M 10s\n", + " 91850K .......... .......... .......... .......... .......... 15% 51.6M 10s\n", + " 91900K .......... .......... .......... .......... .......... 15% 42.8M 10s\n", + " 91950K .......... .......... .......... .......... .......... 15% 37.7M 10s\n", + " 92000K .......... .......... .......... .......... .......... 15% 48.8M 10s\n", + " 92050K .......... .......... .......... .......... .......... 15% 40.1M 10s\n", + " 92100K .......... .......... .......... .......... .......... 15% 54.0M 10s\n", + " 92150K .......... .......... .......... .......... .......... 15% 51.6M 10s\n", + " 92200K .......... .......... .......... .......... .......... 15% 46.5M 10s\n", + " 92250K .......... .......... .......... .......... .......... 15% 54.6M 10s\n", + " 92300K .......... .......... .......... .......... .......... 15% 48.0M 10s\n", + " 92350K .......... .......... .......... .......... .......... 15% 57.7M 10s\n", + " 92400K .......... .......... .......... .......... .......... 15% 49.8M 10s\n", + " 92450K .......... .......... .......... .......... .......... 15% 75.5M 10s\n", + " 92500K .......... .......... .......... .......... .......... 15% 51.2M 10s\n", + " 92550K .......... .......... .......... .......... .......... 15% 52.7M 10s\n", + " 92600K .......... .......... .......... .......... .......... 15% 44.6M 10s\n", + " 92650K .......... .......... .......... .......... .......... 15% 48.4M 10s\n", + " 92700K .......... .......... .......... .......... .......... 15% 65.0M 10s\n", + " 92750K .......... .......... .......... .......... .......... 15% 43.0M 10s\n", + " 92800K .......... .......... .......... .......... .......... 15% 54.2M 10s\n", + " 92850K .......... .......... .......... .......... .......... 15% 43.7M 10s\n", + " 92900K .......... .......... .......... .......... .......... 15% 56.1M 10s\n", + " 92950K .......... .......... .......... .......... .......... 15% 64.1M 10s\n", + " 93000K .......... .......... .......... .......... .......... 15% 31.9M 10s\n", + " 93050K .......... .......... .......... .......... .......... 15% 56.6M 10s\n", + " 93100K .......... .......... .......... .......... .......... 15% 62.9M 10s\n", + " 93150K .......... .......... .......... .......... .......... 15% 61.6M 10s\n", + " 93200K .......... .......... .......... .......... .......... 15% 66.1M 10s\n", + " 93250K .......... .......... .......... .......... .......... 15% 59.5M 10s\n", + " 93300K .......... .......... .......... .......... .......... 15% 69.5M 10s\n", + " 93350K .......... .......... .......... .......... .......... 15% 53.3M 10s\n", + " 93400K .......... .......... .......... .......... .......... 15% 46.7M 10s\n", + " 93450K .......... .......... .......... .......... .......... 15% 72.0M 10s\n", + " 93500K .......... .......... .......... .......... .......... 15% 50.4M 10s\n", + " 93550K .......... .......... .......... .......... .......... 15% 76.6M 10s\n", + " 93600K .......... .......... .......... .......... .......... 15% 45.8M 10s\n", + " 93650K .......... .......... .......... .......... .......... 15% 57.8M 10s\n", + " 93700K .......... .......... .......... .......... .......... 15% 64.3M 10s\n", + " 93750K .......... .......... .......... .......... .......... 15% 55.2M 10s\n", + " 93800K .......... .......... .......... .......... .......... 15% 57.6M 10s\n", + " 93850K .......... .......... .......... .......... .......... 15% 56.9M 10s\n", + " 93900K .......... .......... .......... .......... .......... 15% 51.4M 10s\n", + " 93950K .......... .......... .......... .......... .......... 15% 65.3M 10s\n", + " 94000K .......... .......... .......... .......... .......... 15% 58.2M 10s\n", + " 94050K .......... .......... .......... .......... .......... 15% 51.9M 10s\n", + " 94100K .......... .......... .......... .......... .......... 15% 65.3M 10s\n", + " 94150K .......... .......... .......... .......... .......... 15% 52.0M 10s\n", + " 94200K .......... .......... .......... .......... .......... 15% 58.8M 10s\n", + " 94250K .......... .......... .......... .......... .......... 15% 65.6M 10s\n", + " 94300K .......... .......... .......... .......... .......... 15% 55.2M 10s\n", + " 94350K .......... .......... .......... .......... .......... 15% 61.1M 10s\n", + " 94400K .......... .......... .......... .......... .......... 15% 55.8M 10s\n", + " 94450K .......... .......... .......... .......... .......... 15% 58.9M 10s\n", + " 94500K .......... .......... .......... .......... .......... 15% 73.9M 10s\n", + " 94550K .......... .......... .......... .......... .......... 15% 58.0M 10s\n", + " 94600K .......... .......... .......... .......... .......... 15% 47.4M 10s\n", + " 94650K .......... .......... .......... .......... .......... 15% 52.3M 10s\n", + " 94700K .......... .......... .......... .......... .......... 15% 62.8M 10s\n", + " 94750K .......... .......... .......... .......... .......... 15% 66.9M 10s\n", + " 94800K .......... .......... .......... .......... .......... 15% 67.6M 10s\n", + " 94850K .......... .......... .......... .......... .......... 15% 57.5M 10s\n", + " 94900K .......... .......... .......... .......... .......... 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.......... .......... 16% 33.7M 10s\n", + " 96150K .......... .......... .......... .......... .......... 16% 28.3M 10s\n", + " 96200K .......... .......... .......... .......... .......... 16% 25.3M 10s\n", + " 96250K .......... .......... .......... .......... .......... 16% 32.4M 10s\n", + " 96300K .......... .......... .......... .......... .......... 16% 33.7M 10s\n", + " 96350K .......... .......... .......... .......... .......... 16% 53.8M 10s\n", + " 96400K .......... .......... .......... .......... .......... 16% 49.2M 10s\n", + " 96450K .......... .......... .......... .......... .......... 16% 71.2M 10s\n", + " 96500K .......... .......... .......... .......... .......... 16% 59.8M 10s\n", + " 96550K .......... .......... .......... .......... .......... 16% 66.8M 10s\n", + " 96600K .......... .......... .......... .......... .......... 16% 51.3M 10s\n", + " 96650K .......... .......... .......... .......... .......... 16% 64.4M 10s\n", + " 96700K .......... .......... .......... .......... .......... 16% 64.9M 10s\n", + " 96750K .......... .......... .......... .......... .......... 16% 60.7M 10s\n", + " 96800K .......... .......... .......... .......... .......... 16% 53.8M 10s\n", + " 96850K .......... .......... .......... .......... .......... 16% 60.7M 10s\n", + " 96900K .......... .......... .......... .......... .......... 16% 60.4M 10s\n", + " 96950K .......... .......... .......... .......... .......... 16% 57.7M 10s\n", + " 97000K .......... .......... .......... .......... .......... 16% 44.9M 10s\n", + " 97050K .......... .......... .......... .......... .......... 16% 56.6M 10s\n", + " 97100K .......... .......... .......... .......... .......... 16% 57.6M 10s\n", + " 97150K .......... .......... .......... .......... .......... 16% 62.9M 10s\n", + " 97200K .......... .......... .......... .......... .......... 16% 52.4M 10s\n", + " 97250K .......... .......... .......... .......... .......... 16% 54.0M 10s\n", + " 97300K .......... .......... .......... .......... .......... 16% 63.5M 10s\n", + " 97350K .......... .......... .......... .......... .......... 16% 63.5M 10s\n", + " 97400K .......... .......... .......... .......... .......... 16% 48.5M 10s\n", + " 97450K .......... .......... .......... .......... .......... 16% 60.6M 10s\n", + " 97500K .......... .......... .......... .......... .......... 16% 62.5M 10s\n", + " 97550K .......... .......... .......... .......... .......... 16% 52.4M 10s\n", + " 97600K .......... .......... .......... .......... .......... 16% 49.7M 10s\n", + " 97650K .......... .......... .......... .......... .......... 16% 56.9M 10s\n", + " 97700K .......... .......... .......... .......... .......... 16% 54.2M 10s\n", + " 97750K .......... .......... .......... .......... .......... 16% 67.5M 10s\n", + " 97800K .......... .......... .......... .......... .......... 16% 46.4M 10s\n", + " 97850K .......... .......... .......... .......... .......... 16% 47.6M 10s\n", + " 97900K .......... .......... .......... .......... .......... 16% 66.2M 10s\n", + " 97950K .......... .......... .......... .......... .......... 16% 57.3M 10s\n", + " 98000K .......... .......... .......... .......... .......... 16% 3.69M 10s\n", + " 98050K .......... .......... .......... .......... .......... 16% 61.1M 10s\n", + " 98100K .......... .......... .......... .......... .......... 16% 64.3M 10s\n", + " 98150K .......... .......... .......... .......... .......... 16% 64.4M 10s\n", + " 98200K .......... .......... .......... .......... .......... 16% 50.3M 10s\n", + " 98250K .......... .......... .......... .......... .......... 16% 68.1M 10s\n", + " 98300K .......... .......... .......... .......... .......... 16% 68.2M 10s\n", + " 98350K .......... .......... .......... .......... .......... 16% 55.2M 10s\n", + " 98400K .......... .......... .......... .......... .......... 16% 27.6M 10s\n", + " 98450K .......... .......... .......... .......... .......... 16% 40.7M 10s\n", + " 98500K .......... .......... .......... .......... .......... 16% 31.7M 10s\n", + " 98550K .......... .......... .......... .......... .......... 16% 30.4M 10s\n", + " 98600K .......... .......... .......... .......... .......... 16% 51.4M 10s\n", + " 98650K .......... .......... .......... .......... .......... 16% 51.8M 10s\n", + " 98700K .......... .......... .......... .......... .......... 16% 60.0M 10s\n", + " 98750K .......... .......... .......... .......... .......... 16% 73.4M 10s\n", + " 98800K .......... .......... .......... .......... .......... 16% 50.5M 10s\n", + " 98850K .......... .......... .......... .......... .......... 16% 67.1M 10s\n", + " 98900K .......... .......... .......... .......... .......... 16% 61.3M 10s\n", + " 98950K .......... .......... .......... .......... .......... 16% 3.93M 10s\n", + " 99000K .......... .......... .......... .......... .......... 16% 56.5M 10s\n", + " 99050K .......... .......... .......... .......... .......... 16% 54.9M 10s\n", + " 99100K .......... .......... .......... .......... .......... 16% 62.7M 10s\n", + " 99150K .......... .......... .......... .......... .......... 16% 66.0M 10s\n", + " 99200K .......... .......... .......... .......... .......... 16% 58.1M 10s\n", + " 99250K .......... .......... .......... .......... .......... 16% 56.5M 10s\n", + " 99300K .......... .......... .......... .......... .......... 16% 53.5M 10s\n", + " 99350K .......... .......... .......... .......... .......... 16% 69.6M 10s\n", + " 99400K .......... .......... .......... .......... .......... 16% 40.6M 10s\n", + " 99450K .......... .......... .......... .......... .......... 16% 63.8M 10s\n", + " 99500K .......... .......... .......... .......... .......... 16% 49.3M 10s\n", + " 99550K .......... .......... .......... .......... .......... 16% 55.7M 10s\n", + " 99600K .......... .......... .......... .......... .......... 16% 67.1M 10s\n", + " 99650K .......... .......... .......... .......... .......... 16% 44.6M 10s\n", + " 99700K .......... .......... .......... .......... .......... 16% 76.4M 10s\n", + " 99750K .......... .......... .......... .......... .......... 16% 48.3M 10s\n", + " 99800K .......... .......... .......... .......... .......... 16% 47.3M 10s\n", + " 99850K .......... .......... .......... .......... .......... 16% 63.7M 10s\n", + " 99900K .......... .......... .......... .......... .......... 16% 52.4M 10s\n", + " 99950K .......... .......... .......... .......... .......... 16% 59.4M 10s\n", + "100000K .......... .......... .......... .......... .......... 16% 61.2M 10s\n", + "100050K .......... .......... .......... .......... .......... 16% 60.9M 10s\n", + "100100K .......... .......... .......... .......... .......... 16% 71.9M 10s\n", + "100150K .......... .......... .......... .......... .......... 16% 48.3M 10s\n", + "100200K .......... .......... .......... .......... .......... 16% 43.0M 10s\n", + "100250K .......... .......... .......... .......... 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.......... .......... 16% 62.8M 10s\n", + "100900K .......... .......... .......... .......... .......... 16% 59.6M 10s\n", + "100950K .......... .......... .......... .......... .......... 16% 67.2M 10s\n", + "101000K .......... .......... .......... .......... .......... 16% 45.1M 10s\n", + "101050K .......... .......... .......... .......... .......... 16% 66.9M 10s\n", + "101100K .......... .......... .......... .......... .......... 17% 67.8M 10s\n", + "101150K .......... .......... .......... .......... .......... 17% 44.2M 10s\n", + "101200K .......... .......... .......... .......... .......... 17% 56.3M 10s\n", + "101250K .......... .......... .......... .......... .......... 17% 65.7M 10s\n", + "101300K .......... .......... .......... .......... .......... 17% 53.4M 10s\n", + "101350K .......... .......... .......... .......... .......... 17% 10.8M 10s\n", + "101400K .......... .......... .......... .......... .......... 17% 53.8M 10s\n", + "101450K .......... .......... .......... .......... .......... 17% 60.4M 10s\n", + "101500K .......... .......... .......... .......... .......... 17% 70.4M 10s\n", + "101550K .......... .......... .......... .......... .......... 17% 65.9M 10s\n", + "101600K .......... .......... .......... .......... .......... 17% 69.9M 10s\n", + "101650K .......... .......... .......... .......... .......... 17% 67.8M 10s\n", + "101700K .......... .......... .......... .......... .......... 17% 65.5M 10s\n", + "101750K .......... .......... .......... .......... .......... 17% 63.9M 10s\n", + "101800K .......... .......... .......... .......... .......... 17% 58.3M 10s\n", + "101850K .......... .......... .......... .......... .......... 17% 70.5M 10s\n", + "101900K .......... .......... .......... .......... .......... 17% 71.5M 10s\n", + "101950K .......... .......... .......... .......... .......... 17% 69.5M 10s\n", + "102000K .......... .......... .......... .......... .......... 17% 51.0M 10s\n", + "102050K .......... .......... .......... .......... .......... 17% 50.2M 10s\n", + "102100K .......... .......... .......... .......... .......... 17% 70.2M 10s\n", + "102150K .......... .......... .......... .......... .......... 17% 70.0M 10s\n", + "102200K .......... .......... .......... .......... .......... 17% 59.7M 10s\n", + "102250K .......... .......... .......... .......... .......... 17% 59.9M 10s\n", + "102300K .......... .......... .......... .......... .......... 17% 57.7M 10s\n", + "102350K .......... .......... .......... .......... .......... 17% 48.4M 10s\n", + "102400K .......... .......... .......... .......... .......... 17% 59.3M 10s\n", + "102450K .......... .......... .......... .......... .......... 17% 72.2M 10s\n", + "102500K .......... .......... .......... .......... .......... 17% 69.7M 10s\n", + "102550K .......... .......... .......... .......... .......... 17% 68.9M 10s\n", + "102600K .......... .......... .......... .......... .......... 17% 41.4M 10s\n", + "102650K .......... .......... .......... .......... .......... 17% 52.9M 10s\n", + "102700K .......... .......... .......... .......... .......... 17% 57.8M 10s\n", + "102750K .......... .......... .......... .......... .......... 17% 64.5M 10s\n", + "102800K .......... .......... .......... .......... .......... 17% 48.1M 10s\n", + "102850K .......... .......... .......... .......... .......... 17% 51.7M 10s\n", + "102900K .......... .......... .......... .......... .......... 17% 48.1M 10s\n", + "102950K .......... .......... .......... .......... .......... 17% 64.2M 10s\n", + "103000K .......... .......... .......... .......... .......... 17% 58.4M 10s\n", + "103050K .......... .......... .......... .......... .......... 17% 49.9M 10s\n", + "103100K .......... .......... .......... .......... .......... 17% 50.7M 10s\n", + "103150K .......... .......... .......... .......... .......... 17% 60.2M 10s\n", + "103200K .......... .......... .......... .......... .......... 17% 59.2M 10s\n", + "103250K .......... .......... .......... .......... .......... 17% 53.8M 10s\n", + "103300K .......... .......... .......... .......... .......... 17% 53.2M 10s\n", + "103350K .......... .......... .......... .......... .......... 17% 63.4M 10s\n", + "103400K .......... .......... .......... .......... .......... 17% 46.1M 10s\n", + "103450K .......... .......... .......... .......... .......... 17% 67.3M 10s\n", + "103500K .......... .......... .......... .......... .......... 17% 51.7M 10s\n", + "103550K .......... .......... .......... .......... .......... 17% 61.2M 10s\n", + "103600K .......... .......... .......... .......... .......... 17% 47.3M 10s\n", + "103650K .......... .......... .......... .......... .......... 17% 57.0M 10s\n", + "103700K .......... .......... .......... .......... .......... 17% 61.5M 10s\n", + "103750K .......... .......... .......... .......... .......... 17% 50.9M 10s\n", + "103800K .......... .......... .......... .......... .......... 17% 52.2M 10s\n", + "103850K .......... .......... .......... .......... .......... 17% 47.6M 10s\n", + "103900K .......... .......... .......... .......... .......... 17% 47.9M 10s\n", + "103950K .......... .......... .......... .......... .......... 17% 57.5M 10s\n", + "104000K .......... .......... .......... .......... .......... 17% 58.9M 10s\n", + "104050K .......... .......... .......... .......... .......... 17% 61.7M 10s\n", + "104100K .......... .......... .......... .......... .......... 17% 58.6M 10s\n", + "104150K .......... .......... .......... .......... .......... 17% 55.3M 10s\n", + "104200K .......... .......... .......... .......... .......... 17% 50.7M 10s\n", + "104250K .......... .......... .......... .......... .......... 17% 63.7M 10s\n", + "104300K .......... .......... .......... .......... .......... 17% 4.36M 10s\n", + "104350K .......... .......... .......... .......... .......... 17% 69.0M 10s\n", + "104400K .......... .......... .......... .......... .......... 17% 62.5M 10s\n", + "104450K .......... .......... .......... .......... .......... 17% 69.0M 10s\n", + "104500K .......... .......... .......... .......... .......... 17% 65.7M 10s\n", + "104550K .......... .......... .......... .......... .......... 17% 68.0M 10s\n", + "104600K .......... .......... .......... .......... .......... 17% 54.0M 10s\n", + "104650K .......... .......... .......... .......... .......... 17% 50.0M 10s\n", + "104700K .......... .......... .......... .......... .......... 17% 67.4M 10s\n", + "104750K .......... .......... .......... .......... .......... 17% 67.0M 10s\n", + "104800K .......... .......... .......... .......... .......... 17% 55.0M 10s\n", + "104850K .......... .......... .......... .......... .......... 17% 53.1M 10s\n", + "104900K .......... .......... .......... .......... .......... 17% 52.0M 10s\n", + "104950K .......... .......... .......... .......... .......... 17% 70.3M 10s\n", + "105000K .......... .......... .......... .......... 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.......... .......... .......... .......... .......... 18% 43.8M 10s\n", + "107450K .......... .......... .......... .......... .......... 18% 64.8M 10s\n", + "107500K .......... .......... .......... .......... .......... 18% 71.1M 10s\n", + "107550K .......... .......... .......... .......... .......... 18% 74.0M 10s\n", + "107600K .......... .......... .......... .......... .......... 18% 59.8M 10s\n", + "107650K .......... .......... .......... .......... .......... 18% 65.3M 10s\n", + "107700K .......... .......... .......... .......... .......... 18% 67.4M 10s\n", + "107750K .......... .......... .......... .......... .......... 18% 74.5M 10s\n", + "107800K .......... .......... .......... .......... .......... 18% 61.6M 10s\n", + "107850K .......... .......... .......... .......... .......... 18% 58.2M 10s\n", + "107900K .......... .......... .......... .......... .......... 18% 56.6M 10s\n", + "107950K .......... .......... .......... .......... .......... 18% 48.3M 10s\n", + 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10s\n", + "108600K .......... .......... .......... .......... .......... 18% 53.5M 10s\n", + "108650K .......... .......... .......... .......... .......... 18% 3.91M 10s\n", + "108700K .......... .......... .......... .......... .......... 18% 65.4M 10s\n", + "108750K .......... .......... .......... .......... .......... 18% 64.7M 10s\n", + "108800K .......... .......... .......... .......... .......... 18% 58.8M 10s\n", + "108850K .......... .......... .......... .......... .......... 18% 66.6M 10s\n", + "108900K .......... .......... .......... .......... .......... 18% 61.8M 10s\n", + "108950K .......... .......... .......... .......... .......... 18% 55.8M 10s\n", + "109000K .......... .......... .......... .......... .......... 18% 61.0M 10s\n", + "109050K .......... .......... .......... .......... .......... 18% 60.8M 10s\n", + "109100K .......... .......... .......... .......... .......... 18% 64.3M 10s\n", + "109150K .......... .......... .......... .......... .......... 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.......... .......... .......... .......... 18% 68.6M 10s\n", + "111600K .......... .......... .......... .......... .......... 18% 66.9M 10s\n", + "111650K .......... .......... .......... .......... .......... 18% 69.4M 10s\n", + "111700K .......... .......... .......... .......... .......... 18% 56.5M 10s\n", + "111750K .......... .......... .......... .......... .......... 18% 52.7M 10s\n", + "111800K .......... .......... .......... .......... .......... 18% 49.7M 10s\n", + "111850K .......... .......... .......... .......... .......... 18% 52.9M 10s\n", + "111900K .......... .......... .......... .......... .......... 18% 78.5M 10s\n", + "111950K .......... .......... .......... .......... .......... 18% 70.2M 10s\n", + "112000K .......... .......... .......... .......... .......... 18% 65.0M 10s\n", + "112050K .......... .......... .......... .......... .......... 18% 64.3M 10s\n", + "112100K .......... .......... .......... .......... .......... 18% 54.3M 10s\n", + "112150K .......... .......... .......... .......... .......... 18% 52.6M 10s\n", + "112200K .......... .......... .......... .......... .......... 18% 47.5M 10s\n", + "112250K .......... .......... .......... .......... .......... 18% 67.0M 10s\n", + "112300K .......... .......... .......... .......... .......... 18% 65.8M 10s\n", + "112350K .......... .......... .......... .......... .......... 18% 53.1M 10s\n", + "112400K .......... .......... .......... .......... .......... 18% 43.4M 10s\n", + "112450K .......... .......... .......... .......... .......... 18% 52.8M 10s\n", + "112500K .......... .......... .......... .......... .......... 18% 69.7M 10s\n", + "112550K .......... .......... .......... .......... .......... 18% 62.6M 10s\n", + "112600K .......... .......... .......... .......... .......... 18% 42.1M 10s\n", + "112650K .......... .......... .......... .......... .......... 18% 76.8M 10s\n", + "112700K .......... .......... .......... .......... .......... 18% 67.7M 10s\n", + 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.......... .......... 19% 62.6M 10s\n", + "115150K .......... .......... .......... .......... .......... 19% 57.8M 10s\n", + "115200K .......... .......... .......... .......... .......... 19% 61.4M 10s\n", + "115250K .......... .......... .......... .......... .......... 19% 71.7M 10s\n", + "115300K .......... .......... .......... .......... .......... 19% 56.5M 10s\n", + "115350K .......... .......... .......... .......... .......... 19% 70.0M 10s\n", + "115400K .......... .......... .......... .......... .......... 19% 47.8M 10s\n", + "115450K .......... .......... .......... .......... .......... 19% 51.3M 10s\n", + "115500K .......... .......... .......... .......... .......... 19% 60.4M 10s\n", + "115550K .......... .......... .......... .......... .......... 19% 54.4M 10s\n", + "115600K .......... .......... .......... .......... .......... 19% 69.5M 10s\n", + "115650K .......... .......... .......... .......... .......... 19% 56.1M 10s\n", + "115700K .......... .......... .......... .......... .......... 19% 56.2M 10s\n", + "115750K .......... .......... .......... .......... .......... 19% 68.1M 10s\n", + "115800K .......... .......... .......... .......... .......... 19% 52.0M 10s\n", + "115850K .......... .......... .......... .......... .......... 19% 62.7M 10s\n", + "115900K .......... .......... .......... .......... .......... 19% 65.4M 10s\n", + "115950K .......... .......... .......... .......... .......... 19% 58.9M 10s\n", + "116000K .......... .......... .......... .......... .......... 19% 52.8M 10s\n", + "116050K .......... .......... .......... .......... .......... 19% 72.7M 10s\n", + "116100K .......... .......... .......... .......... .......... 19% 58.4M 10s\n", + "116150K .......... .......... .......... .......... .......... 19% 65.4M 10s\n", + "116200K .......... .......... .......... .......... .......... 19% 54.2M 10s\n", + "116250K .......... .......... .......... .......... .......... 19% 63.0M 10s\n", + "116300K .......... .......... .......... .......... .......... 19% 7.68M 10s\n", + "116350K .......... .......... .......... .......... .......... 19% 69.3M 10s\n", + "116400K .......... .......... .......... .......... .......... 19% 60.6M 10s\n", + "116450K .......... .......... .......... .......... .......... 19% 71.4M 10s\n", + "116500K .......... .......... .......... .......... .......... 19% 66.2M 10s\n", + "116550K .......... .......... .......... .......... .......... 19% 70.7M 10s\n", + "116600K .......... .......... .......... .......... .......... 19% 47.3M 10s\n", + "116650K .......... .......... .......... .......... .......... 19% 58.6M 10s\n", + "116700K .......... .......... .......... .......... .......... 19% 68.9M 10s\n", + "116750K .......... .......... .......... .......... .......... 19% 79.3M 10s\n", + "116800K .......... .......... .......... .......... .......... 19% 52.7M 10s\n", + "116850K .......... .......... .......... .......... .......... 19% 61.4M 10s\n", + "116900K .......... .......... .......... .......... .......... 19% 66.4M 10s\n", + "116950K .......... .......... .......... .......... .......... 19% 62.5M 10s\n", + "117000K .......... .......... .......... .......... .......... 19% 59.4M 10s\n", + "117050K .......... .......... .......... .......... .......... 19% 69.6M 10s\n", + "117100K .......... .......... .......... .......... .......... 19% 55.8M 10s\n", + "117150K .......... .......... .......... .......... .......... 19% 58.4M 10s\n", + "117200K .......... .......... .......... .......... .......... 19% 59.3M 10s\n", + "117250K .......... .......... .......... .......... .......... 19% 71.3M 10s\n", + "117300K .......... .......... .......... .......... .......... 19% 70.3M 10s\n", + "117350K .......... .......... .......... .......... .......... 19% 74.3M 10s\n", + "117400K .......... .......... .......... .......... .......... 19% 44.4M 10s\n", + "117450K .......... .......... .......... .......... .......... 19% 63.7M 10s\n", + 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10s\n", + "118100K .......... .......... .......... .......... .......... 19% 68.9M 10s\n", + "118150K .......... .......... .......... .......... .......... 19% 71.0M 10s\n", + "118200K .......... .......... .......... .......... .......... 19% 62.6M 10s\n", + "118250K .......... .......... .......... .......... .......... 19% 72.3M 10s\n", + "118300K .......... .......... .......... .......... .......... 19% 72.5M 10s\n", + "118350K .......... .......... .......... .......... .......... 19% 73.9M 10s\n", + "118400K .......... .......... .......... .......... .......... 19% 68.0M 10s\n", + "118450K .......... .......... .......... .......... .......... 19% 74.7M 10s\n", + "118500K .......... .......... .......... .......... .......... 19% 76.6M 10s\n", + "118550K .......... .......... .......... .......... .......... 19% 73.2M 10s\n", + "118600K .......... .......... .......... .......... .......... 19% 59.8M 10s\n", + "118650K .......... .......... .......... .......... .......... 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"122250K .......... .......... .......... .......... .......... 20% 59.9M 10s\n", + "122300K .......... .......... .......... .......... .......... 20% 68.9M 10s\n", + "122350K .......... .......... .......... .......... .......... 20% 70.8M 10s\n", + "122400K .......... .......... .......... .......... .......... 20% 51.8M 10s\n", + "122450K .......... .......... .......... .......... .......... 20% 64.7M 10s\n", + "122500K .......... .......... .......... .......... .......... 20% 64.2M 10s\n", + "122550K .......... .......... .......... .......... .......... 20% 58.5M 10s\n", + "122600K .......... .......... .......... .......... .......... 20% 43.3M 10s\n", + "122650K .......... .......... .......... .......... .......... 20% 63.3M 10s\n", + "122700K .......... .......... .......... .......... .......... 20% 65.8M 10s\n", + "122750K .......... .......... .......... .......... .......... 20% 71.9M 10s\n", + "122800K .......... .......... .......... .......... .......... 20% 59.4M 10s\n", + "122850K .......... .......... .......... .......... .......... 20% 56.0M 10s\n", + "122900K .......... .......... .......... .......... .......... 20% 60.7M 10s\n", + "122950K .......... .......... .......... .......... .......... 20% 48.7M 10s\n", + "123000K .......... .......... .......... .......... .......... 20% 53.7M 10s\n", + "123050K .......... .......... .......... .......... .......... 20% 68.4M 10s\n", + "123100K .......... .......... .......... .......... .......... 20% 62.1M 10s\n", + "123150K .......... .......... .......... .......... .......... 20% 56.2M 10s\n", + "123200K .......... .......... .......... .......... .......... 20% 49.6M 10s\n", + "123250K .......... .......... .......... .......... .......... 20% 77.8M 10s\n", + "123300K .......... .......... .......... .......... .......... 20% 73.1M 10s\n", + "123350K .......... .......... .......... .......... .......... 20% 71.6M 10s\n", + "123400K .......... .......... .......... .......... .......... 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.......... .......... .......... 21% 54.8M 10s\n", + "125250K .......... .......... .......... .......... .......... 21% 59.0M 10s\n", + "125300K .......... .......... .......... .......... .......... 21% 55.6M 10s\n", + "125350K .......... .......... .......... .......... .......... 21% 57.6M 10s\n", + "125400K .......... .......... .......... .......... .......... 21% 47.0M 10s\n", + "125450K .......... .......... .......... .......... .......... 21% 62.1M 10s\n", + "125500K .......... .......... .......... .......... .......... 21% 53.2M 10s\n", + "125550K .......... .......... .......... .......... .......... 21% 61.0M 10s\n", + "125600K .......... .......... .......... .......... .......... 21% 52.0M 10s\n", + "125650K .......... .......... .......... .......... .......... 21% 61.4M 10s\n", + "125700K .......... .......... .......... .......... .......... 21% 63.6M 10s\n", + "125750K .......... .......... .......... .......... .......... 21% 60.3M 10s\n", + "125800K .......... .......... .......... .......... .......... 21% 43.3M 10s\n", + "125850K .......... .......... .......... .......... .......... 21% 60.7M 10s\n", + "125900K .......... .......... .......... .......... .......... 21% 61.5M 10s\n", + "125950K .......... .......... .......... .......... .......... 21% 57.7M 10s\n", + "126000K .......... .......... .......... .......... .......... 21% 56.9M 10s\n", + "126050K .......... .......... .......... .......... .......... 21% 55.1M 10s\n", + "126100K .......... .......... .......... .......... .......... 21% 55.1M 10s\n", + "126150K .......... .......... .......... .......... .......... 21% 63.5M 10s\n", + "126200K .......... .......... .......... .......... .......... 21% 38.4M 10s\n", + "126250K .......... .......... .......... .......... .......... 21% 56.1M 10s\n", + "126300K .......... .......... .......... .......... .......... 21% 51.2M 10s\n", + "126350K .......... .......... .......... .......... .......... 21% 55.8M 10s\n", + "126400K .......... .......... .......... .......... .......... 21% 57.6M 10s\n", + "126450K .......... .......... .......... .......... .......... 21% 45.8M 10s\n", + "126500K .......... .......... .......... .......... .......... 21% 63.1M 10s\n", + "126550K .......... .......... .......... .......... .......... 21% 46.4M 10s\n", + "126600K .......... .......... .......... .......... .......... 21% 47.6M 10s\n", + "126650K .......... .......... .......... .......... .......... 21% 45.6M 10s\n", + "126700K .......... .......... .......... .......... .......... 21% 62.7M 10s\n", + "126750K .......... .......... .......... .......... .......... 21% 56.9M 10s\n", + "126800K .......... .......... .......... .......... .......... 21% 45.5M 10s\n", + "126850K .......... .......... .......... .......... .......... 21% 58.5M 10s\n", + "126900K .......... .......... .......... .......... .......... 21% 69.5M 10s\n", + "126950K .......... .......... .......... .......... .......... 21% 58.5M 10s\n", + "127000K .......... .......... .......... .......... .......... 21% 29.6M 10s\n", + "127050K .......... .......... .......... .......... .......... 21% 51.0M 10s\n", + "127100K .......... .......... .......... .......... .......... 21% 70.2M 10s\n", + "127150K .......... .......... .......... .......... .......... 21% 61.1M 10s\n", + "127200K .......... .......... .......... .......... .......... 21% 63.6M 10s\n", + "127250K .......... .......... .......... .......... .......... 21% 65.1M 10s\n", + "127300K .......... .......... .......... .......... .......... 21% 55.0M 10s\n", + "127350K .......... .......... .......... .......... .......... 21% 70.7M 10s\n", + "127400K .......... .......... .......... .......... .......... 21% 48.1M 10s\n", + "127450K .......... .......... .......... .......... .......... 21% 63.5M 10s\n", + "127500K .......... .......... .......... .......... .......... 21% 68.2M 10s\n", + "127550K .......... .......... .......... .......... .......... 21% 57.6M 10s\n", + "127600K .......... .......... .......... .......... .......... 21% 58.8M 10s\n", + "127650K .......... .......... .......... .......... .......... 21% 70.3M 10s\n", + "127700K .......... .......... .......... .......... .......... 21% 64.8M 10s\n", + "127750K .......... .......... .......... .......... .......... 21% 64.9M 10s\n", + "127800K .......... .......... .......... .......... .......... 21% 60.6M 10s\n", + "127850K .......... .......... .......... .......... .......... 21% 47.5M 10s\n", + "127900K .......... .......... .......... .......... .......... 21% 55.3M 10s\n", + "127950K .......... .......... .......... .......... .......... 21% 55.6M 10s\n", + "128000K .......... .......... .......... .......... .......... 21% 54.3M 10s\n", + "128050K .......... .......... .......... .......... .......... 21% 60.4M 10s\n", + "128100K .......... .......... .......... .......... .......... 21% 53.4M 10s\n", + "128150K .......... .......... .......... .......... .......... 21% 59.6M 10s\n", + "128200K .......... .......... .......... .......... .......... 21% 61.5M 10s\n", + "128250K .......... .......... .......... .......... .......... 21% 58.9M 10s\n", + "128300K .......... .......... .......... .......... .......... 21% 67.3M 10s\n", + "128350K .......... .......... .......... .......... .......... 21% 55.1M 10s\n", + "128400K .......... .......... .......... .......... .......... 21% 48.1M 10s\n", + "128450K .......... .......... .......... .......... .......... 21% 67.9M 10s\n", + "128500K .......... .......... .......... .......... .......... 21% 62.6M 10s\n", + "128550K .......... .......... .......... .......... .......... 21% 62.1M 10s\n", + "128600K .......... .......... .......... .......... .......... 21% 55.1M 10s\n", + "128650K .......... .......... .......... .......... .......... 21% 58.7M 10s\n", + "128700K .......... .......... .......... .......... .......... 21% 66.6M 10s\n", + "128750K .......... .......... .......... .......... .......... 21% 51.6M 10s\n", + "128800K .......... .......... .......... .......... .......... 21% 51.0M 10s\n", + "128850K .......... .......... .......... .......... .......... 21% 71.7M 10s\n", + "128900K .......... .......... .......... .......... .......... 21% 61.4M 10s\n", + "128950K .......... .......... .......... .......... .......... 21% 53.1M 10s\n", + "129000K .......... .......... .......... .......... .......... 21% 52.0M 10s\n", + "129050K .......... .......... .......... .......... .......... 21% 55.0M 10s\n", + "129100K .......... .......... .......... .......... .......... 21% 72.5M 10s\n", + "129150K .......... .......... .......... .......... .......... 21% 62.7M 10s\n", + "129200K .......... .......... .......... .......... .......... 21% 50.7M 10s\n", + "129250K .......... .......... .......... .......... .......... 21% 68.5M 10s\n", + "129300K .......... .......... .......... .......... .......... 21% 54.6M 10s\n", + "129350K .......... .......... .......... .......... .......... 21% 59.1M 10s\n", + "129400K .......... .......... .......... .......... .......... 21% 64.3M 10s\n", + "129450K .......... .......... .......... .......... .......... 21% 53.7M 10s\n", + "129500K .......... .......... .......... .......... .......... 21% 64.1M 10s\n", + "129550K .......... .......... .......... .......... .......... 21% 54.4M 10s\n", + "129600K .......... .......... .......... .......... .......... 21% 53.2M 10s\n", + "129650K .......... .......... .......... .......... .......... 21% 76.1M 10s\n", + "129700K .......... .......... .......... .......... .......... 21% 69.4M 10s\n", + "129750K .......... .......... .......... .......... .......... 21% 58.1M 10s\n", + "129800K .......... .......... .......... .......... .......... 21% 42.0M 10s\n", + "129850K .......... .......... .......... .......... .......... 21% 60.6M 10s\n", + "129900K .......... .......... .......... .......... .......... 21% 70.5M 10s\n", + "129950K .......... .......... .......... .......... .......... 21% 76.6M 10s\n", + "130000K .......... .......... .......... .......... .......... 21% 63.7M 10s\n", + "130050K .......... .......... .......... .......... .......... 21% 70.7M 10s\n", + "130100K .......... .......... .......... .......... .......... 21% 72.8M 10s\n", + "130150K .......... .......... .......... .......... .......... 21% 49.6M 10s\n", + "130200K .......... .......... .......... .......... .......... 21% 43.4M 10s\n", + "130250K .......... .......... .......... .......... .......... 21% 69.1M 10s\n", + "130300K .......... .......... .......... .......... .......... 21% 71.6M 10s\n", + "130350K .......... .......... .......... .......... .......... 21% 71.8M 10s\n", + "130400K .......... .......... .......... .......... .......... 21% 52.4M 10s\n", + "130450K .......... .......... .......... .......... .......... 21% 54.0M 10s\n", + "130500K .......... .......... .......... .......... .......... 21% 53.0M 10s\n", + "130550K .......... .......... .......... .......... .......... 21% 65.6M 10s\n", + "130600K .......... .......... .......... .......... .......... 21% 57.4M 10s\n", + "130650K .......... .......... .......... .......... .......... 21% 60.5M 10s\n", + "130700K .......... .......... .......... .......... .......... 21% 51.1M 10s\n", + "130750K .......... .......... .......... .......... .......... 21% 47.8M 10s\n", + "130800K .......... .......... .......... .......... .......... 22% 56.2M 10s\n", + "130850K .......... .......... .......... .......... .......... 22% 75.2M 9s\n", + "130900K .......... .......... .......... .......... .......... 22% 72.0M 9s\n", + "130950K .......... .......... .......... .......... .......... 22% 64.8M 9s\n", + "131000K .......... .......... .......... .......... .......... 22% 42.7M 9s\n", + "131050K .......... .......... .......... .......... .......... 22% 56.0M 9s\n", + "131100K .......... .......... .......... .......... .......... 22% 70.9M 9s\n", + "131150K .......... .......... .......... .......... .......... 22% 62.0M 9s\n", + "131200K .......... .......... .......... .......... .......... 22% 53.2M 9s\n", + "131250K .......... .......... .......... .......... .......... 22% 59.0M 9s\n", + "131300K .......... .......... .......... .......... .......... 22% 57.6M 9s\n", + "131350K .......... .......... .......... .......... .......... 22% 73.3M 9s\n", + "131400K .......... .......... .......... .......... .......... 22% 58.3M 9s\n", + "131450K .......... .......... .......... .......... .......... 22% 66.3M 9s\n", + "131500K .......... .......... .......... .......... .......... 22% 57.1M 9s\n", + "131550K .......... .......... .......... .......... .......... 22% 56.8M 9s\n", + "131600K .......... .......... .......... .......... .......... 22% 56.1M 9s\n", + "131650K .......... .......... .......... .......... .......... 22% 72.5M 9s\n", + "131700K .......... .......... .......... .......... .......... 22% 70.1M 9s\n", + "131750K .......... .......... .......... .......... .......... 22% 60.6M 9s\n", + "131800K .......... .......... .......... .......... .......... 22% 51.3M 9s\n", + "131850K .......... .......... .......... .......... .......... 22% 67.1M 9s\n", + "131900K .......... .......... .......... .......... .......... 22% 66.7M 9s\n", + "131950K .......... .......... .......... .......... .......... 22% 51.1M 9s\n", + "132000K .......... .......... .......... .......... .......... 22% 46.8M 9s\n", + "132050K .......... .......... .......... .......... .......... 22% 68.6M 9s\n", + "132100K .......... .......... .......... .......... .......... 22% 68.9M 9s\n", + "132150K .......... .......... .......... .......... .......... 22% 73.9M 9s\n", + "132200K .......... .......... .......... .......... .......... 22% 55.4M 9s\n", + "132250K .......... .......... .......... .......... .......... 22% 56.8M 9s\n", + "132300K .......... .......... .......... .......... .......... 22% 44.8M 9s\n", + "132350K .......... .......... .......... .......... .......... 22% 47.8M 9s\n", + "132400K .......... .......... .......... .......... .......... 22% 63.3M 9s\n", + "132450K .......... .......... .......... .......... .......... 22% 76.0M 9s\n", + "132500K .......... .......... .......... .......... .......... 22% 56.1M 9s\n", + "132550K .......... .......... .......... .......... .......... 22% 50.1M 9s\n", + "132600K .......... .......... .......... .......... .......... 22% 42.2M 9s\n", + "132650K .......... .......... .......... .......... .......... 22% 74.3M 9s\n", + "132700K .......... .......... .......... .......... .......... 22% 70.9M 9s\n", + "132750K .......... .......... .......... .......... .......... 22% 57.1M 9s\n", + "132800K .......... .......... .......... .......... .......... 22% 48.0M 9s\n", + "132850K .......... .......... .......... .......... .......... 22% 54.4M 9s\n", + "132900K .......... .......... .......... .......... .......... 22% 74.7M 9s\n", + "132950K .......... .......... .......... .......... .......... 22% 72.1M 9s\n", + "133000K .......... .......... .......... .......... .......... 22% 55.7M 9s\n", + "133050K .......... .......... .......... .......... .......... 22% 49.3M 9s\n", + "133100K .......... .......... .......... .......... .......... 22% 57.2M 9s\n", + "133150K .......... .......... .......... .......... .......... 22% 66.4M 9s\n", + "133200K .......... .......... .......... .......... .......... 22% 61.0M 9s\n", + "133250K .......... .......... .......... .......... .......... 22% 67.7M 9s\n", + "133300K .......... .......... .......... .......... .......... 22% 59.1M 9s\n", + "133350K .......... .......... .......... .......... .......... 22% 57.8M 9s\n", + "133400K .......... .......... .......... .......... .......... 22% 48.5M 9s\n", + "133450K .......... .......... .......... .......... .......... 22% 70.2M 9s\n", + "133500K .......... .......... .......... .......... .......... 22% 69.4M 9s\n", + "133550K 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.......... .......... .......... .......... .......... 22% 56.1M 9s\n", + "134200K .......... .......... .......... .......... .......... 22% 40.0M 9s\n", + "134250K .......... .......... .......... .......... .......... 22% 65.0M 9s\n", + "134300K .......... .......... .......... .......... .......... 22% 67.3M 9s\n", + "134350K .......... .......... .......... .......... .......... 22% 63.6M 9s\n", + "134400K .......... .......... .......... .......... .......... 22% 49.7M 9s\n", + "134450K .......... .......... .......... .......... .......... 22% 30.6M 9s\n", + "134500K .......... .......... .......... .......... .......... 22% 64.1M 9s\n", + "134550K .......... .......... .......... .......... .......... 22% 72.3M 9s\n", + "134600K .......... .......... .......... .......... .......... 22% 43.9M 9s\n", + "134650K .......... .......... .......... .......... .......... 22% 50.5M 9s\n", + "134700K .......... .......... .......... .......... .......... 22% 50.6M 9s\n", + "134750K .......... .......... .......... .......... .......... 22% 68.4M 9s\n", + "134800K .......... .......... .......... .......... .......... 22% 61.3M 9s\n", + "134850K .......... .......... .......... .......... .......... 22% 55.8M 9s\n", + "134900K .......... .......... .......... .......... .......... 22% 45.7M 9s\n", + "134950K .......... .......... .......... .......... .......... 22% 51.2M 9s\n", + "135000K .......... .......... .......... .......... .......... 22% 61.9M 9s\n", + "135050K .......... .......... .......... .......... .......... 22% 66.6M 9s\n", + "135100K .......... .......... .......... .......... .......... 22% 65.2M 9s\n", + "135150K .......... .......... .......... .......... .......... 22% 50.0M 9s\n", + "135200K .......... .......... .......... .......... .......... 22% 51.5M 9s\n", + "135250K .......... .......... .......... .......... .......... 22% 72.2M 9s\n", + "135300K .......... .......... .......... .......... .......... 22% 65.4M 9s\n", + "135350K .......... .......... .......... .......... .......... 22% 67.5M 9s\n", + "135400K .......... .......... .......... .......... .......... 22% 38.6M 9s\n", + "135450K .......... .......... .......... .......... .......... 22% 52.0M 9s\n", + "135500K .......... .......... .......... .......... .......... 22% 68.6M 9s\n", + "135550K .......... .......... .......... .......... .......... 22% 3.71M 9s\n", + "135600K .......... .......... .......... .......... .......... 22% 53.9M 9s\n", + "135650K .......... .......... .......... .......... .......... 22% 69.4M 9s\n", + "135700K .......... .......... .......... .......... .......... 22% 68.2M 9s\n", + "135750K .......... .......... .......... .......... .......... 22% 67.0M 9s\n", + "135800K .......... .......... .......... .......... .......... 22% 49.6M 9s\n", + "135850K .......... .......... .......... .......... .......... 22% 47.0M 9s\n", + "135900K .......... .......... .......... .......... .......... 22% 60.0M 9s\n", + "135950K .......... .......... .......... .......... .......... 22% 64.1M 9s\n", + "136000K .......... .......... .......... .......... .......... 22% 58.0M 9s\n", + "136050K .......... .......... .......... .......... .......... 22% 66.3M 9s\n", + "136100K .......... .......... .......... .......... .......... 22% 48.3M 9s\n", + "136150K .......... .......... .......... .......... .......... 22% 50.0M 9s\n", + "136200K .......... .......... .......... .......... .......... 22% 58.1M 9s\n", + "136250K .......... .......... .......... .......... .......... 22% 74.0M 9s\n", + "136300K .......... .......... .......... .......... .......... 22% 64.7M 9s\n", + "136350K .......... .......... .......... .......... .......... 22% 45.3M 9s\n", + "136400K .......... .......... .......... .......... .......... 22% 49.7M 9s\n", + "136450K .......... .......... .......... .......... .......... 22% 64.3M 9s\n", + "136500K .......... .......... .......... .......... .......... 22% 66.3M 9s\n", + "136550K 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.......... .......... .......... .......... .......... 23% 48.3M 9s\n", + "137200K .......... .......... .......... .......... .......... 23% 46.6M 9s\n", + "137250K .......... .......... .......... .......... .......... 23% 69.8M 9s\n", + "137300K .......... .......... .......... .......... .......... 23% 71.2M 9s\n", + "137350K .......... .......... .......... .......... .......... 23% 78.1M 9s\n", + "137400K .......... .......... .......... .......... .......... 23% 41.8M 9s\n", + "137450K .......... .......... .......... .......... .......... 23% 52.5M 9s\n", + "137500K .......... .......... .......... .......... .......... 23% 68.9M 9s\n", + "137550K .......... .......... .......... .......... .......... 23% 65.2M 9s\n", + "137600K .......... .......... .......... .......... .......... 23% 62.4M 9s\n", + "137650K .......... .......... .......... .......... .......... 23% 67.3M 9s\n", + "137700K .......... .......... .......... .......... .......... 23% 53.3M 9s\n", + "137750K 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.......... .......... .......... .......... .......... 23% 64.3M 9s\n", + "138400K .......... .......... .......... .......... .......... 23% 58.6M 9s\n", + "138450K .......... .......... .......... .......... .......... 23% 71.4M 9s\n", + "138500K .......... .......... .......... .......... .......... 23% 45.8M 9s\n", + "138550K .......... .......... .......... .......... .......... 23% 51.1M 9s\n", + "138600K .......... .......... .......... .......... .......... 23% 47.4M 9s\n", + "138650K .......... .......... .......... .......... .......... 23% 64.2M 9s\n", + "138700K .......... .......... .......... .......... .......... 23% 68.1M 9s\n", + "138750K .......... .......... .......... .......... .......... 23% 50.4M 9s\n", + "138800K .......... .......... .......... .......... .......... 23% 43.4M 9s\n", + "138850K .......... .......... .......... .......... .......... 23% 4.95M 9s\n", + "138900K .......... .......... .......... .......... .......... 23% 60.1M 9s\n", + "138950K .......... .......... .......... .......... .......... 23% 74.2M 9s\n", + "139000K .......... .......... .......... .......... .......... 23% 62.8M 9s\n", + "139050K .......... .......... .......... .......... .......... 23% 68.8M 9s\n", + "139100K .......... .......... .......... .......... .......... 23% 71.9M 9s\n", + "139150K .......... .......... .......... .......... .......... 23% 35.1M 9s\n", + "139200K .......... .......... .......... .......... .......... 23% 49.0M 9s\n", + "139250K .......... .......... .......... .......... .......... 23% 59.4M 9s\n", + "139300K .......... .......... .......... .......... .......... 23% 65.7M 9s\n", + "139350K .......... .......... .......... .......... .......... 23% 52.7M 9s\n", + "139400K .......... .......... .......... .......... .......... 23% 31.8M 9s\n", + "139450K .......... .......... .......... .......... .......... 23% 51.4M 9s\n", + "139500K .......... .......... .......... .......... .......... 23% 58.7M 9s\n", + "139550K .......... .......... .......... .......... .......... 23% 72.9M 9s\n", + "139600K .......... .......... .......... .......... .......... 23% 63.9M 9s\n", + "139650K .......... .......... .......... .......... .......... 23% 67.1M 9s\n", + "139700K .......... .......... .......... .......... .......... 23% 64.1M 9s\n", + "139750K .......... .......... .......... .......... .......... 23% 41.3M 9s\n", + "139800K .......... .......... .......... .......... .......... 23% 37.9M 9s\n", + "139850K .......... .......... .......... .......... .......... 23% 52.4M 9s\n", + "139900K .......... .......... .......... .......... .......... 23% 57.1M 9s\n", + "139950K .......... .......... .......... .......... .......... 23% 46.3M 9s\n", + "140000K .......... .......... .......... .......... .......... 23% 41.8M 9s\n", + "140050K .......... .......... .......... .......... .......... 23% 41.7M 9s\n", + "140100K .......... .......... .......... .......... .......... 23% 55.4M 9s\n", + "140150K .......... .......... .......... .......... .......... 23% 44.7M 9s\n", + "140200K .......... .......... .......... .......... .......... 23% 45.1M 9s\n", + "140250K .......... .......... .......... .......... .......... 23% 64.4M 9s\n", + "140300K .......... .......... .......... .......... .......... 23% 52.6M 9s\n", + "140350K .......... .......... .......... .......... .......... 23% 62.5M 9s\n", + "140400K .......... .......... .......... .......... .......... 23% 46.1M 9s\n", + "140450K .......... .......... .......... .......... .......... 23% 66.4M 9s\n", + "140500K .......... .......... .......... .......... .......... 23% 50.6M 9s\n", + "140550K .......... .......... .......... .......... .......... 23% 41.4M 9s\n", + "140600K .......... .......... .......... .......... .......... 23% 36.3M 9s\n", + "140650K .......... .......... .......... .......... .......... 23% 45.9M 9s\n", + "140700K .......... .......... .......... .......... .......... 23% 37.3M 9s\n", + "140750K .......... .......... .......... .......... .......... 23% 37.5M 9s\n", + "140800K .......... .......... .......... .......... .......... 23% 32.0M 9s\n", + "140850K .......... .......... .......... .......... .......... 23% 32.3M 9s\n", + "140900K .......... .......... .......... .......... .......... 23% 38.8M 9s\n", + "140950K .......... .......... .......... .......... .......... 23% 42.0M 9s\n", + "141000K .......... .......... .......... .......... .......... 23% 36.0M 9s\n", + "141050K .......... .......... .......... .......... .......... 23% 38.4M 9s\n", + "141100K .......... .......... .......... .......... .......... 23% 43.5M 9s\n", + "141150K .......... .......... .......... .......... .......... 23% 49.0M 9s\n", + "141200K .......... .......... .......... .......... .......... 23% 48.6M 9s\n", + "141250K .......... .......... .......... .......... .......... 23% 70.1M 9s\n", + "141300K .......... .......... .......... .......... .......... 23% 70.5M 9s\n", + "141350K .......... .......... .......... .......... .......... 23% 67.6M 9s\n", + "141400K .......... .......... .......... .......... .......... 23% 31.6M 9s\n", + "141450K .......... .......... .......... .......... .......... 23% 54.2M 9s\n", + "141500K .......... .......... .......... .......... .......... 23% 52.1M 9s\n", + "141550K .......... .......... .......... .......... .......... 23% 55.7M 9s\n", + "141600K .......... .......... .......... .......... .......... 23% 55.6M 9s\n", + "141650K .......... .......... .......... .......... .......... 23% 55.4M 9s\n", + "141700K .......... .......... .......... .......... .......... 23% 50.9M 9s\n", + "141750K .......... .......... .......... .......... .......... 23% 39.6M 9s\n", + "141800K .......... .......... .......... .......... .......... 23% 48.2M 9s\n", + "141850K .......... .......... .......... .......... .......... 23% 32.4M 9s\n", + "141900K .......... .......... .......... .......... .......... 23% 34.8M 9s\n", + "141950K .......... .......... .......... .......... .......... 23% 30.4M 9s\n", + "142000K .......... .......... .......... .......... .......... 23% 53.0M 9s\n", + "142050K .......... .......... .......... .......... .......... 23% 55.0M 9s\n", + "142100K .......... .......... .......... .......... .......... 23% 59.3M 9s\n", + "142150K .......... .......... .......... .......... .......... 23% 61.9M 9s\n", + "142200K .......... .......... .......... .......... .......... 23% 53.2M 9s\n", + "142250K .......... .......... .......... .......... .......... 23% 63.8M 9s\n", + "142300K .......... .......... .......... .......... .......... 23% 53.0M 9s\n", + "142350K .......... .......... .......... .......... .......... 23% 62.3M 9s\n", + "142400K .......... .......... .......... .......... .......... 23% 53.4M 9s\n", + "142450K .......... .......... .......... .......... .......... 23% 62.1M 9s\n", + "142500K .......... .......... .......... .......... .......... 23% 67.7M 9s\n", + "142550K .......... .......... .......... .......... .......... 23% 61.6M 9s\n", + "142600K .......... .......... .......... .......... .......... 23% 43.2M 9s\n", + "142650K .......... .......... .......... .......... .......... 23% 59.0M 9s\n", + "142700K .......... .......... .......... .......... .......... 24% 54.6M 9s\n", + "142750K .......... .......... .......... .......... .......... 24% 73.0M 9s\n", + "142800K .......... .......... .......... .......... .......... 24% 50.8M 9s\n", + "142850K .......... .......... .......... .......... .......... 24% 59.9M 9s\n", + "142900K .......... .......... .......... .......... .......... 24% 53.5M 9s\n", + "142950K .......... .......... .......... .......... .......... 24% 58.3M 9s\n", + "143000K .......... .......... .......... .......... .......... 24% 54.3M 9s\n", + "143050K .......... .......... .......... .......... .......... 24% 62.3M 9s\n", + "143100K .......... .......... .......... .......... .......... 24% 52.7M 9s\n", + "143150K .......... .......... .......... .......... .......... 24% 57.4M 9s\n", + "143200K .......... .......... .......... .......... .......... 24% 62.7M 9s\n", + "143250K .......... .......... .......... .......... .......... 24% 65.9M 9s\n", + "143300K .......... .......... .......... .......... .......... 24% 59.4M 9s\n", + "143350K .......... .......... .......... .......... .......... 24% 66.6M 9s\n", + "143400K .......... .......... .......... .......... .......... 24% 50.3M 9s\n", + "143450K .......... .......... .......... .......... .......... 24% 72.0M 9s\n", + "143500K .......... .......... .......... .......... .......... 24% 69.9M 9s\n", + "143550K .......... .......... .......... .......... .......... 24% 58.0M 9s\n", + "143600K .......... .......... .......... .......... .......... 24% 58.3M 9s\n", + "143650K .......... .......... .......... .......... .......... 24% 58.5M 9s\n", + "143700K .......... .......... .......... .......... .......... 24% 68.7M 9s\n", + "143750K .......... .......... .......... .......... .......... 24% 60.0M 9s\n", + "143800K .......... .......... .......... .......... .......... 24% 50.5M 9s\n", + "143850K .......... .......... .......... .......... .......... 24% 72.3M 9s\n", + "143900K .......... .......... .......... .......... .......... 24% 73.0M 9s\n", + "143950K .......... .......... .......... .......... .......... 24% 71.3M 9s\n", + "144000K .......... .......... .......... .......... .......... 24% 63.3M 9s\n", + "144050K .......... .......... .......... .......... .......... 24% 55.3M 9s\n", + "144100K .......... .......... .......... .......... .......... 24% 48.9M 9s\n", + "144150K .......... .......... .......... .......... .......... 24% 59.3M 9s\n", + "144200K .......... .......... .......... .......... .......... 24% 58.4M 9s\n", + "144250K .......... .......... .......... .......... .......... 24% 66.9M 9s\n", + "144300K .......... .......... .......... .......... .......... 24% 79.0M 9s\n", + "144350K .......... .......... .......... .......... .......... 24% 76.0M 9s\n", + "144400K .......... .......... .......... .......... .......... 24% 54.6M 9s\n", + "144450K .......... .......... .......... .......... .......... 24% 54.0M 9s\n", + "144500K .......... .......... .......... .......... .......... 24% 49.7M 9s\n", + "144550K .......... .......... .......... .......... .......... 24% 58.7M 9s\n", + "144600K .......... .......... .......... .......... .......... 24% 57.8M 9s\n", + "144650K .......... .......... .......... .......... .......... 24% 61.3M 9s\n", + "144700K .......... .......... .......... .......... .......... 24% 45.5M 9s\n", + "144750K .......... .......... .......... .......... .......... 24% 47.8M 9s\n", + "144800K .......... .......... .......... .......... .......... 24% 40.3M 9s\n", + "144850K .......... .......... .......... .......... .......... 24% 76.8M 9s\n", + "144900K .......... .......... .......... .......... .......... 24% 57.7M 9s\n", + "144950K 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.......... .......... .......... .......... .......... 24% 61.5M 9s\n", + "145600K .......... .......... .......... .......... .......... 24% 53.9M 9s\n", + "145650K .......... .......... .......... .......... .......... 24% 59.6M 9s\n", + "145700K .......... .......... .......... .......... .......... 24% 71.5M 9s\n", + "145750K .......... .......... .......... .......... .......... 24% 66.8M 9s\n", + "145800K .......... .......... .......... .......... .......... 24% 57.0M 9s\n", + "145850K .......... .......... .......... .......... .......... 24% 55.4M 9s\n", + "145900K .......... .......... .......... .......... .......... 24% 47.6M 9s\n", + "145950K .......... .......... .......... .......... .......... 24% 56.4M 9s\n", + "146000K .......... .......... .......... .......... .......... 24% 66.7M 9s\n", + "146050K .......... .......... .......... .......... .......... 24% 69.1M 9s\n", + "146100K .......... .......... .......... .......... .......... 24% 59.6M 9s\n", + "146150K .......... .......... .......... .......... .......... 24% 46.9M 9s\n", + "146200K .......... .......... .......... .......... .......... 24% 43.6M 9s\n", + "146250K .......... .......... .......... .......... .......... 24% 69.4M 9s\n", + "146300K .......... .......... .......... .......... .......... 24% 66.2M 9s\n", + "146350K .......... .......... .......... .......... .......... 24% 54.2M 9s\n", + "146400K .......... .......... .......... .......... .......... 24% 54.9M 9s\n", + "146450K .......... .......... .......... .......... .......... 24% 54.3M 9s\n", + "146500K .......... .......... .......... .......... .......... 24% 61.4M 9s\n", + "146550K .......... .......... .......... .......... .......... 24% 66.6M 9s\n", + "146600K .......... .......... .......... .......... .......... 24% 51.9M 9s\n", + "146650K .......... .......... .......... .......... .......... 24% 60.7M 9s\n", + "146700K .......... .......... .......... .......... .......... 24% 60.0M 9s\n", + "146750K .......... .......... .......... .......... .......... 24% 55.1M 9s\n", + "146800K .......... .......... .......... .......... .......... 24% 67.4M 9s\n", + "146850K .......... .......... .......... .......... .......... 24% 75.3M 9s\n", + "146900K .......... .......... .......... .......... .......... 24% 68.4M 9s\n", + "146950K .......... .......... .......... .......... .......... 24% 46.0M 9s\n", + "147000K .......... .......... .......... .......... .......... 24% 51.7M 9s\n", + "147050K .......... .......... .......... .......... .......... 24% 54.5M 9s\n", + "147100K .......... .......... .......... .......... .......... 24% 69.1M 9s\n", + "147150K .......... .......... .......... .......... .......... 24% 74.5M 9s\n", + "147200K .......... .......... .......... .......... .......... 24% 63.7M 9s\n", + "147250K .......... .......... .......... .......... .......... 24% 67.8M 9s\n", + "147300K .......... .......... .......... .......... .......... 24% 55.0M 9s\n", + "147350K .......... .......... .......... .......... .......... 24% 7.72M 9s\n", + "147400K .......... .......... .......... .......... .......... 24% 46.2M 9s\n", + "147450K .......... .......... .......... .......... .......... 24% 66.9M 9s\n", + "147500K .......... .......... .......... .......... .......... 24% 66.4M 9s\n", + "147550K .......... .......... .......... .......... .......... 24% 71.6M 9s\n", + "147600K .......... .......... .......... .......... .......... 24% 66.6M 9s\n", + "147650K .......... .......... .......... .......... .......... 24% 72.0M 9s\n", + "147700K .......... .......... .......... .......... .......... 24% 65.5M 9s\n", + "147750K .......... .......... .......... .......... .......... 24% 54.5M 9s\n", + "147800K .......... .......... .......... .......... .......... 24% 50.7M 9s\n", + "147850K .......... .......... .......... .......... .......... 24% 74.0M 9s\n", + "147900K .......... .......... .......... .......... .......... 24% 69.9M 9s\n", + "147950K .......... .......... .......... .......... .......... 24% 65.2M 9s\n", + "148000K .......... .......... .......... .......... .......... 24% 45.9M 9s\n", + "148050K .......... .......... .......... .......... .......... 24% 48.4M 9s\n", + "148100K .......... .......... .......... .......... .......... 24% 61.8M 9s\n", + "148150K .......... .......... .......... .......... .......... 24% 73.4M 9s\n", + "148200K .......... .......... .......... .......... .......... 24% 3.88M 9s\n", + "148250K .......... .......... .......... .......... .......... 24% 67.8M 9s\n", + "148300K .......... .......... .......... .......... .......... 24% 74.5M 9s\n", + "148350K .......... .......... .......... .......... .......... 24% 69.2M 9s\n", + "148400K .......... .......... .......... .......... .......... 24% 59.0M 9s\n", + "148450K .......... .......... .......... .......... .......... 24% 76.7M 9s\n", + "148500K .......... .......... .......... .......... .......... 24% 56.2M 9s\n", + "148550K .......... .......... .......... .......... .......... 24% 55.6M 9s\n", + "148600K .......... .......... .......... .......... .......... 24% 51.2M 9s\n", + "148650K .......... .......... .......... .......... .......... 25% 61.8M 9s\n", + "148700K .......... .......... .......... .......... .......... 25% 64.8M 9s\n", + "148750K .......... .......... .......... .......... .......... 25% 70.9M 9s\n", + "148800K .......... .......... .......... .......... .......... 25% 44.3M 9s\n", + "148850K .......... .......... .......... .......... .......... 25% 49.6M 9s\n", + "148900K .......... .......... .......... .......... .......... 25% 64.6M 9s\n", + "148950K .......... .......... .......... .......... .......... 25% 71.1M 9s\n", + "149000K .......... .......... .......... .......... .......... 25% 54.6M 9s\n", + "149050K .......... .......... .......... .......... .......... 25% 51.1M 9s\n", + "149100K .......... .......... .......... .......... .......... 25% 50.9M 9s\n", + "149150K .......... .......... .......... .......... .......... 25% 53.3M 9s\n", + "149200K .......... .......... .......... .......... .......... 25% 69.2M 9s\n", + "149250K .......... .......... .......... .......... .......... 25% 68.8M 9s\n", + "149300K .......... .......... .......... .......... .......... 25% 57.9M 9s\n", + "149350K .......... .......... .......... .......... .......... 25% 56.3M 9s\n", + "149400K .......... .......... .......... .......... .......... 25% 46.1M 9s\n", + "149450K .......... .......... .......... .......... .......... 25% 79.7M 9s\n", + "149500K .......... .......... .......... .......... .......... 25% 68.0M 9s\n", + "149550K .......... .......... .......... .......... .......... 25% 65.3M 9s\n", + "149600K .......... .......... .......... .......... .......... 25% 44.3M 9s\n", + "149650K .......... .......... .......... .......... .......... 25% 49.9M 9s\n", + "149700K .......... .......... .......... .......... .......... 25% 61.4M 9s\n", + "149750K .......... .......... .......... .......... .......... 25% 71.3M 9s\n", + "149800K .......... .......... .......... .......... .......... 25% 53.8M 9s\n", + "149850K .......... .......... .......... .......... .......... 25% 47.5M 9s\n", + "149900K .......... .......... .......... .......... .......... 25% 58.4M 9s\n", + "149950K .......... .......... .......... .......... .......... 25% 58.9M 9s\n", + "150000K .......... .......... .......... .......... .......... 25% 60.0M 9s\n", + "150050K .......... .......... .......... .......... .......... 25% 74.5M 9s\n", + "150100K .......... .......... .......... .......... .......... 25% 54.3M 9s\n", + "150150K .......... .......... .......... .......... .......... 25% 50.5M 9s\n", + "150200K .......... .......... .......... .......... .......... 25% 49.6M 9s\n", + "150250K .......... .......... .......... .......... .......... 25% 59.9M 9s\n", + "150300K .......... .......... .......... .......... .......... 25% 75.0M 9s\n", + "150350K .......... .......... .......... .......... .......... 25% 62.4M 9s\n", + "150400K .......... .......... .......... .......... .......... 25% 42.7M 9s\n", + "150450K .......... .......... .......... .......... .......... 25% 58.1M 9s\n", + "150500K .......... .......... .......... .......... .......... 25% 65.6M 9s\n", + "150550K .......... .......... .......... .......... .......... 25% 60.2M 9s\n", + "150600K .......... .......... .......... .......... .......... 25% 60.1M 9s\n", + "150650K .......... .......... .......... .......... .......... 25% 50.5M 9s\n", + "150700K .......... .......... .......... .......... .......... 25% 53.9M 9s\n", + "150750K .......... .......... .......... .......... .......... 25% 63.9M 9s\n", + "150800K .......... .......... .......... .......... .......... 25% 69.3M 9s\n", + "150850K .......... .......... .......... .......... .......... 25% 75.7M 9s\n", + "150900K .......... .......... .......... .......... .......... 25% 65.9M 9s\n", + "150950K .......... .......... .......... .......... .......... 25% 54.2M 9s\n", + "151000K .......... .......... .......... .......... .......... 25% 47.6M 9s\n", + "151050K .......... .......... .......... .......... .......... 25% 63.9M 9s\n", + "151100K .......... .......... .......... .......... .......... 25% 69.5M 9s\n", + "151150K .......... .......... .......... .......... .......... 25% 71.6M 9s\n", + "151200K .......... .......... .......... .......... .......... 25% 49.4M 9s\n", + "151250K .......... .......... .......... .......... .......... 25% 46.4M 9s\n", + "151300K .......... .......... .......... .......... .......... 25% 55.3M 9s\n", + "151350K .......... .......... .......... .......... .......... 25% 5.61M 9s\n", + "151400K .......... .......... .......... .......... .......... 25% 57.5M 9s\n", + "151450K .......... .......... .......... .......... .......... 25% 64.7M 9s\n", + "151500K .......... .......... .......... .......... .......... 25% 67.9M 9s\n", + "151550K .......... .......... .......... .......... .......... 25% 20.7M 9s\n", + "151600K .......... .......... .......... .......... .......... 25% 46.4M 9s\n", + "151650K .......... .......... .......... .......... .......... 25% 59.4M 9s\n", + "151700K .......... .......... .......... .......... .......... 25% 66.3M 9s\n", + "151750K .......... .......... .......... .......... .......... 25% 68.4M 9s\n", + "151800K .......... .......... .......... .......... .......... 25% 54.5M 9s\n", + "151850K .......... .......... .......... .......... .......... 25% 63.4M 9s\n", + "151900K .......... .......... .......... .......... .......... 25% 57.2M 9s\n", + "151950K .......... .......... .......... .......... .......... 25% 60.0M 9s\n", + "152000K .......... .......... .......... .......... .......... 25% 62.1M 9s\n", + "152050K .......... .......... .......... .......... .......... 25% 64.6M 9s\n", + "152100K .......... .......... .......... .......... .......... 25% 67.7M 9s\n", + "152150K .......... .......... .......... .......... .......... 25% 69.4M 9s\n", + "152200K .......... .......... .......... .......... .......... 25% 45.3M 9s\n", + "152250K .......... .......... .......... .......... .......... 25% 52.9M 9s\n", + "152300K .......... .......... .......... .......... .......... 25% 59.9M 9s\n", + "152350K .......... .......... .......... .......... .......... 25% 67.7M 9s\n", + "152400K .......... .......... .......... .......... .......... 25% 58.1M 9s\n", + "152450K .......... .......... .......... .......... .......... 25% 69.2M 9s\n", + "152500K .......... .......... .......... .......... .......... 25% 73.4M 9s\n", + "152550K .......... .......... .......... .......... .......... 25% 52.4M 9s\n", + "152600K .......... .......... .......... .......... .......... 25% 40.0M 9s\n", + "152650K .......... .......... .......... .......... .......... 25% 57.9M 9s\n", + "152700K .......... .......... .......... .......... .......... 25% 66.1M 9s\n", + "152750K .......... .......... .......... .......... .......... 25% 62.3M 9s\n", + "152800K .......... .......... .......... .......... .......... 25% 40.8M 9s\n", + "152850K .......... .......... .......... .......... .......... 25% 53.9M 9s\n", + "152900K .......... .......... .......... .......... .......... 25% 55.3M 9s\n", + "152950K .......... .......... .......... .......... .......... 25% 66.5M 9s\n", + "153000K .......... .......... .......... .......... .......... 25% 60.0M 9s\n", + "153050K .......... .......... .......... .......... .......... 25% 51.5M 9s\n", + "153100K .......... .......... .......... .......... .......... 25% 43.1M 9s\n", + "153150K .......... .......... .......... .......... .......... 25% 65.6M 9s\n", + "153200K .......... .......... .......... .......... .......... 25% 57.6M 9s\n", + "153250K .......... .......... .......... .......... .......... 25% 68.3M 9s\n", + "153300K .......... .......... .......... .......... .......... 25% 63.6M 9s\n", + "153350K .......... .......... .......... .......... .......... 25% 52.9M 9s\n", + "153400K .......... .......... .......... .......... .......... 25% 55.8M 9s\n", + "153450K .......... .......... .......... .......... .......... 25% 61.4M 9s\n", + "153500K .......... .......... .......... .......... .......... 25% 69.2M 9s\n", + "153550K .......... .......... .......... .......... .......... 25% 71.6M 9s\n", + "153600K .......... .......... .......... .......... .......... 25% 69.8M 9s\n", + "153650K .......... .......... .......... .......... .......... 25% 50.1M 9s\n", + "153700K .......... .......... .......... .......... .......... 25% 55.8M 9s\n", + "153750K .......... .......... .......... .......... .......... 25% 62.1M 9s\n", + "153800K .......... .......... .......... .......... .......... 25% 59.2M 9s\n", + "153850K .......... .......... .......... .......... .......... 25% 67.9M 9s\n", + "153900K .......... .......... .......... .......... .......... 25% 56.8M 9s\n", + "153950K .......... .......... .......... .......... .......... 25% 54.9M 9s\n", + "154000K .......... .......... .......... .......... .......... 25% 47.3M 9s\n", + "154050K .......... .......... .......... .......... .......... 25% 73.0M 9s\n", + "154100K .......... .......... .......... .......... .......... 25% 68.2M 9s\n", + "154150K .......... .......... .......... .......... .......... 25% 72.9M 9s\n", + "154200K .......... .......... .......... .......... .......... 25% 42.8M 9s\n", + "154250K .......... .......... .......... .......... .......... 25% 44.0M 9s\n", + "154300K .......... .......... .......... .......... .......... 25% 63.3M 9s\n", + "154350K .......... .......... .......... .......... .......... 25% 65.4M 9s\n", + "154400K .......... .......... .......... .......... .......... 25% 59.7M 9s\n", + "154450K .......... .......... .......... .......... .......... 25% 49.7M 9s\n", + "154500K .......... .......... .......... .......... .......... 25% 46.4M 9s\n", + "154550K .......... .......... .......... .......... .......... 25% 62.1M 9s\n", + "154600K .......... .......... .......... .......... .......... 26% 55.8M 9s\n", + "154650K .......... .......... .......... .......... .......... 26% 63.1M 9s\n", + "154700K .......... .......... .......... .......... .......... 26% 47.2M 9s\n", + "154750K .......... .......... .......... .......... .......... 26% 50.7M 9s\n", + "154800K .......... .......... .......... .......... .......... 26% 58.9M 9s\n", + "154850K .......... .......... .......... .......... .......... 26% 72.6M 9s\n", + "154900K .......... .......... .......... .......... .......... 26% 71.0M 9s\n", + "154950K .......... .......... .......... .......... .......... 26% 52.7M 9s\n", + "155000K .......... .......... .......... .......... .......... 26% 36.0M 9s\n", + "155050K .......... .......... .......... .......... .......... 26% 63.9M 9s\n", + "155100K .......... .......... .......... .......... .......... 26% 75.1M 9s\n", + "155150K .......... .......... .......... .......... .......... 26% 67.9M 9s\n", + "155200K .......... .......... .......... .......... .......... 26% 53.5M 9s\n", + "155250K .......... .......... .......... .......... .......... 26% 55.2M 9s\n", + "155300K .......... .......... .......... .......... .......... 26% 49.1M 9s\n", + "155350K .......... .......... .......... .......... .......... 26% 71.9M 9s\n", + "155400K .......... .......... .......... .......... .......... 26% 57.4M 9s\n", + "155450K .......... .......... .......... .......... .......... 26% 52.4M 9s\n", + "155500K .......... .......... .......... .......... .......... 26% 45.1M 9s\n", + "155550K .......... .......... .......... .......... .......... 26% 67.2M 9s\n", + "155600K .......... .......... .......... .......... .......... 26% 53.3M 9s\n", + "155650K .......... .......... .......... .......... .......... 26% 68.0M 9s\n", + "155700K .......... .......... .......... .......... .......... 26% 63.8M 9s\n", + "155750K .......... .......... .......... .......... .......... 26% 42.4M 9s\n", + "155800K .......... .......... .......... .......... .......... 26% 3.87M 9s\n", + "155850K .......... .......... .......... .......... .......... 26% 64.9M 9s\n", + "155900K .......... .......... .......... .......... .......... 26% 58.9M 9s\n", + "155950K .......... .......... .......... .......... .......... 26% 71.2M 9s\n", + "156000K .......... .......... .......... .......... .......... 26% 50.7M 9s\n", + "156050K .......... .......... .......... .......... .......... 26% 66.0M 9s\n", + "156100K .......... .......... .......... .......... .......... 26% 49.0M 9s\n", + "156150K .......... .......... .......... .......... .......... 26% 63.7M 9s\n", + "156200K .......... .......... .......... .......... .......... 26% 46.5M 9s\n", + "156250K .......... .......... .......... .......... .......... 26% 66.6M 9s\n", + "156300K .......... .......... .......... .......... .......... 26% 71.3M 9s\n", + "156350K .......... .......... .......... .......... .......... 26% 50.8M 9s\n", + "156400K .......... .......... .......... .......... .......... 26% 54.5M 9s\n", + "156450K .......... .......... .......... .......... .......... 26% 57.3M 9s\n", + "156500K .......... .......... .......... .......... .......... 26% 56.1M 9s\n", + "156550K .......... .......... .......... .......... .......... 26% 65.7M 9s\n", + "156600K .......... .......... .......... .......... .......... 26% 46.5M 9s\n", + "156650K .......... .......... .......... .......... .......... 26% 51.3M 9s\n", + "156700K .......... .......... .......... .......... .......... 26% 56.3M 9s\n", + "156750K .......... .......... .......... .......... .......... 26% 60.4M 9s\n", + "156800K .......... .......... .......... .......... .......... 26% 58.6M 9s\n", + "156850K .......... .......... .......... .......... .......... 26% 68.8M 9s\n", + "156900K .......... .......... .......... .......... .......... 26% 48.7M 9s\n", + "156950K .......... .......... .......... .......... .......... 26% 56.4M 9s\n", + "157000K .......... .......... .......... .......... .......... 26% 43.9M 9s\n", + "157050K .......... .......... .......... .......... .......... 26% 67.5M 9s\n", + "157100K .......... .......... .......... .......... .......... 26% 73.6M 9s\n", + "157150K .......... .......... .......... .......... .......... 26% 53.4M 9s\n", + "157200K .......... .......... .......... .......... .......... 26% 48.5M 9s\n", + "157250K .......... .......... .......... .......... .......... 26% 49.1M 9s\n", + "157300K .......... .......... .......... .......... .......... 26% 66.9M 9s\n", + "157350K .......... .......... .......... .......... .......... 26% 65.7M 9s\n", + "157400K .......... .......... .......... .......... .......... 26% 46.3M 9s\n", + "157450K .......... .......... .......... .......... .......... 26% 49.7M 9s\n", + "157500K .......... .......... .......... .......... .......... 26% 57.1M 9s\n", + "157550K .......... .......... .......... .......... .......... 26% 73.3M 9s\n", + "157600K .......... .......... .......... .......... .......... 26% 55.5M 9s\n", + "157650K .......... .......... .......... .......... .......... 26% 53.7M 9s\n", + "157700K .......... .......... .......... .......... .......... 26% 46.5M 9s\n", + "157750K .......... .......... .......... .......... .......... 26% 52.7M 9s\n", + "157800K .......... .......... .......... .......... .......... 26% 47.4M 9s\n", + "157850K .......... .......... .......... .......... .......... 26% 65.0M 9s\n", + "157900K .......... .......... .......... .......... .......... 26% 55.0M 9s\n", + "157950K .......... .......... .......... .......... .......... 26% 46.7M 9s\n", + "158000K .......... .......... .......... .......... .......... 26% 55.8M 9s\n", + "158050K .......... .......... .......... .......... .......... 26% 74.6M 9s\n", + "158100K .......... .......... .......... .......... .......... 26% 71.5M 9s\n", + "158150K .......... .......... .......... .......... .......... 26% 72.6M 9s\n", + "158200K .......... .......... .......... .......... .......... 26% 41.0M 9s\n", + "158250K .......... .......... .......... .......... .......... 26% 54.0M 9s\n", + "158300K .......... .......... .......... .......... .......... 26% 62.1M 9s\n", + "158350K .......... .......... .......... .......... .......... 26% 70.9M 9s\n", + "158400K .......... .......... .......... .......... .......... 26% 61.2M 9s\n", + "158450K .......... .......... .......... .......... .......... 26% 49.3M 9s\n", + "158500K .......... .......... .......... .......... .......... 26% 48.8M 9s\n", + "158550K .......... .......... .......... .......... .......... 26% 53.6M 9s\n", + "158600K .......... .......... .......... .......... .......... 26% 52.4M 9s\n", + "158650K .......... .......... .......... .......... .......... 26% 74.6M 9s\n", + "158700K .......... .......... .......... .......... .......... 26% 48.6M 9s\n", + "158750K .......... .......... .......... .......... .......... 26% 50.0M 9s\n", + "158800K .......... .......... .......... .......... .......... 26% 56.7M 9s\n", + "158850K .......... .......... .......... .......... .......... 26% 66.1M 9s\n", + "158900K .......... .......... .......... .......... .......... 26% 68.4M 9s\n", + "158950K .......... .......... .......... .......... .......... 26% 56.0M 9s\n", + "159000K .......... .......... .......... .......... .......... 26% 41.2M 9s\n", + "159050K .......... .......... .......... .......... .......... 26% 62.6M 9s\n", + "159100K .......... .......... .......... .......... .......... 26% 68.8M 9s\n", + "159150K .......... .......... .......... .......... .......... 26% 67.8M 9s\n", + "159200K .......... .......... .......... .......... .......... 26% 62.0M 9s\n", + "159250K .......... .......... .......... .......... .......... 26% 56.8M 9s\n", + "159300K .......... .......... .......... .......... .......... 26% 49.6M 9s\n", + "159350K .......... .......... .......... .......... .......... 26% 65.2M 9s\n", + "159400K .......... .......... .......... .......... .......... 26% 61.1M 9s\n", + "159450K .......... .......... .......... .......... .......... 26% 72.3M 9s\n", + "159500K .......... .......... .......... .......... .......... 26% 58.4M 9s\n", + "159550K .......... .......... .......... .......... .......... 26% 49.4M 9s\n", + "159600K .......... .......... .......... .......... .......... 26% 53.1M 9s\n", + "159650K .......... .......... .......... .......... .......... 26% 71.5M 9s\n", + "159700K .......... .......... .......... .......... .......... 26% 70.8M 9s\n", + "159750K .......... .......... .......... .......... .......... 26% 55.5M 9s\n", + "159800K .......... .......... .......... .......... .......... 26% 45.9M 9s\n", + "159850K .......... .......... .......... .......... .......... 26% 55.0M 9s\n", + "159900K .......... .......... .......... .......... .......... 26% 68.2M 9s\n", + "159950K .......... .......... .......... .......... .......... 26% 72.7M 9s\n", + "160000K .......... .......... .......... .......... .......... 26% 47.9M 9s\n", + "160050K .......... .......... .......... .......... .......... 26% 62.1M 9s\n", + "160100K .......... .......... .......... .......... .......... 26% 70.2M 9s\n", + "160150K .......... .......... .......... .......... .......... 26% 76.3M 9s\n", + "160200K .......... .......... .......... .......... .......... 26% 48.7M 9s\n", + "160250K .......... .......... .......... .......... .......... 26% 48.7M 9s\n", + "160300K .......... .......... .......... .......... .......... 26% 44.9M 9s\n", + "160350K .......... .......... .......... .......... .......... 26% 62.5M 9s\n", + "160400K .......... .......... .......... .......... .......... 26% 58.2M 9s\n", + "160450K .......... .......... .......... .......... .......... 26% 65.0M 9s\n", + "160500K .......... .......... .......... .......... .......... 26% 52.4M 9s\n", + "160550K .......... .......... .......... .......... .......... 27% 50.5M 9s\n", + "160600K .......... .......... .......... .......... .......... 27% 48.9M 9s\n", + "160650K .......... .......... .......... .......... .......... 27% 74.3M 9s\n", + "160700K .......... .......... .......... .......... .......... 27% 58.6M 9s\n", + "160750K .......... .......... .......... .......... .......... 27% 50.4M 9s\n", + "160800K .......... .......... .......... .......... .......... 27% 44.6M 9s\n", + "160850K .......... .......... .......... .......... .......... 27% 62.8M 9s\n", + "160900K .......... .......... .......... .......... .......... 27% 66.3M 9s\n", + "160950K .......... .......... .......... .......... .......... 27% 68.8M 9s\n", + "161000K .......... .......... .......... .......... .......... 27% 27.0M 9s\n", + "161050K .......... .......... .......... .......... .......... 27% 64.0M 9s\n", + "161100K .......... .......... .......... .......... .......... 27% 76.8M 9s\n", + "161150K .......... .......... .......... .......... .......... 27% 82.8M 9s\n", + "161200K .......... .......... .......... .......... .......... 27% 56.3M 9s\n", + "161250K .......... .......... .......... .......... .......... 27% 62.1M 9s\n", + "161300K .......... .......... .......... .......... .......... 27% 51.6M 9s\n", + "161350K .......... .......... .......... .......... .......... 27% 64.2M 9s\n", + "161400K .......... .......... .......... .......... .......... 27% 60.4M 9s\n", + "161450K .......... .......... .......... .......... .......... 27% 65.6M 9s\n", + "161500K .......... .......... .......... .......... .......... 27% 48.4M 9s\n", + "161550K .......... .......... .......... .......... .......... 27% 59.3M 9s\n", + "161600K .......... .......... .......... .......... .......... 27% 53.6M 9s\n", + "161650K .......... .......... .......... .......... .......... 27% 69.6M 9s\n", + "161700K .......... .......... .......... .......... .......... 27% 74.6M 9s\n", + "161750K .......... .......... .......... .......... .......... 27% 49.8M 9s\n", + "161800K .......... .......... .......... .......... .......... 27% 49.5M 9s\n", + "161850K .......... .......... .......... .......... .......... 27% 57.9M 9s\n", + "161900K .......... .......... .......... .......... .......... 27% 66.1M 9s\n", + "161950K .......... .......... .......... .......... .......... 27% 72.6M 9s\n", + "162000K .......... .......... .......... .......... .......... 27% 53.1M 9s\n", + "162050K .......... .......... .......... .......... .......... 27% 52.7M 9s\n", + "162100K .......... .......... .......... .......... .......... 27% 54.9M 9s\n", + "162150K .......... .......... .......... .......... .......... 27% 62.6M 9s\n", + "162200K .......... .......... .......... .......... .......... 27% 60.1M 9s\n", + "162250K .......... .......... .......... .......... .......... 27% 67.7M 9s\n", + "162300K .......... .......... .......... .......... .......... 27% 48.9M 9s\n", + "162350K .......... .......... .......... .......... .......... 27% 49.1M 9s\n", + "162400K .......... .......... .......... .......... .......... 27% 55.9M 9s\n", + "162450K .......... .......... .......... .......... .......... 27% 68.9M 9s\n", + "162500K .......... .......... .......... .......... .......... 27% 68.1M 9s\n", + "162550K .......... .......... .......... .......... .......... 27% 69.8M 9s\n", + "162600K .......... .......... .......... .......... .......... 27% 47.5M 9s\n", + "162650K .......... .......... .......... .......... .......... 27% 63.3M 9s\n", + "162700K .......... .......... .......... .......... .......... 27% 68.0M 9s\n", + "162750K .......... .......... .......... .......... .......... 27% 71.8M 9s\n", + "162800K .......... .......... .......... .......... .......... 27% 69.5M 9s\n", + "162850K .......... .......... .......... .......... .......... 27% 55.6M 9s\n", + "162900K .......... .......... .......... .......... .......... 27% 51.0M 9s\n", + "162950K .......... .......... .......... .......... .......... 27% 54.4M 9s\n", + "163000K .......... .......... .......... .......... .......... 27% 57.6M 9s\n", + "163050K .......... .......... .......... .......... .......... 27% 66.5M 9s\n", + "163100K .......... .......... .......... .......... .......... 27% 69.2M 9s\n", + "163150K .......... .......... .......... .......... .......... 27% 56.1M 9s\n", + "163200K .......... .......... .......... .......... .......... 27% 46.2M 9s\n", + "163250K .......... .......... .......... .......... .......... 27% 56.8M 9s\n", + "163300K .......... .......... .......... .......... .......... 27% 65.7M 9s\n", + "163350K .......... .......... .......... .......... .......... 27% 66.1M 9s\n", + "163400K .......... .......... .......... .......... .......... 27% 49.8M 9s\n", + "163450K .......... .......... .......... .......... .......... 27% 57.4M 9s\n", + "163500K .......... .......... .......... .......... .......... 27% 59.8M 9s\n", + "163550K .......... .......... .......... .......... .......... 27% 66.9M 9s\n", + "163600K .......... .......... .......... .......... .......... 27% 62.0M 9s\n", + "163650K .......... .......... .......... .......... .......... 27% 66.7M 9s\n", + "163700K .......... .......... .......... .......... .......... 27% 51.3M 9s\n", + "163750K .......... .......... .......... .......... .......... 27% 58.9M 9s\n", + "163800K .......... .......... .......... .......... .......... 27% 52.7M 9s\n", + "163850K .......... .......... .......... .......... .......... 27% 3.95M 9s\n", + "163900K .......... .......... .......... .......... .......... 27% 71.3M 9s\n", + "163950K .......... .......... .......... .......... .......... 27% 70.0M 9s\n", + "164000K .......... .......... .......... .......... .......... 27% 58.6M 9s\n", + "164050K .......... .......... .......... .......... .......... 27% 57.5M 9s\n", + "164100K .......... .......... .......... .......... .......... 27% 55.2M 9s\n", + "164150K .......... .......... .......... .......... .......... 27% 63.3M 9s\n", + "164200K .......... .......... .......... .......... .......... 27% 57.2M 9s\n", + "164250K .......... .......... .......... .......... .......... 27% 71.8M 9s\n", + "164300K .......... .......... .......... .......... .......... 27% 67.7M 9s\n", + "164350K .......... .......... .......... .......... .......... 27% 63.7M 9s\n", + "164400K .......... .......... .......... .......... .......... 27% 52.2M 9s\n", + "164450K .......... .......... .......... .......... .......... 27% 40.7M 9s\n", + "164500K .......... .......... .......... .......... .......... 27% 70.3M 9s\n", + "164550K .......... .......... .......... .......... .......... 27% 62.9M 9s\n", + "164600K .......... .......... .......... .......... .......... 27% 57.5M 9s\n", + "164650K .......... .......... .......... .......... .......... 27% 58.6M 9s\n", + "164700K .......... .......... .......... .......... .......... 27% 60.8M 9s\n", + "164750K .......... .......... .......... .......... .......... 27% 68.0M 9s\n", + "164800K .......... .......... .......... .......... .......... 27% 60.5M 9s\n", + "164850K .......... .......... .......... .......... .......... 27% 59.8M 9s\n", + "164900K .......... .......... .......... .......... .......... 27% 73.5M 9s\n", + "164950K .......... .......... .......... .......... .......... 27% 75.6M 9s\n", + "165000K .......... .......... .......... .......... .......... 27% 63.1M 9s\n", + "165050K .......... .......... .......... .......... .......... 27% 75.7M 9s\n", + "165100K .......... .......... .......... .......... .......... 27% 58.7M 9s\n", + "165150K .......... .......... .......... .......... .......... 27% 57.3M 9s\n", + "165200K .......... .......... .......... .......... .......... 27% 48.3M 9s\n", + "165250K .......... .......... .......... .......... .......... 27% 60.4M 9s\n", + "165300K .......... .......... .......... .......... .......... 27% 72.0M 9s\n", + "165350K .......... .......... .......... .......... .......... 27% 57.1M 9s\n", + "165400K .......... .......... .......... .......... .......... 27% 45.1M 9s\n", + "165450K .......... .......... .......... .......... .......... 27% 46.2M 9s\n", + "165500K .......... .......... .......... .......... .......... 27% 52.9M 9s\n", + "165550K .......... .......... .......... .......... .......... 27% 70.9M 9s\n", + "165600K .......... .......... .......... .......... .......... 27% 53.1M 9s\n", + "165650K .......... .......... .......... .......... .......... 27% 50.1M 9s\n", + "165700K .......... .......... .......... .......... .......... 27% 47.8M 9s\n", + "165750K .......... .......... .......... .......... .......... 27% 53.9M 9s\n", + "165800K .......... .......... .......... .......... .......... 27% 58.2M 9s\n", + "165850K .......... .......... .......... .......... .......... 27% 58.3M 9s\n", + "165900K .......... .......... .......... .......... .......... 27% 56.9M 9s\n", + "165950K .......... .......... .......... .......... .......... 27% 48.7M 9s\n", + "166000K .......... .......... .......... .......... .......... 27% 58.3M 9s\n", + "166050K .......... .......... .......... .......... .......... 27% 73.4M 9s\n", + "166100K .......... .......... .......... .......... .......... 27% 70.9M 9s\n", + "166150K .......... .......... .......... .......... .......... 27% 46.2M 9s\n", + "166200K .......... .......... .......... .......... .......... 27% 47.7M 9s\n", + "166250K .......... .......... .......... .......... .......... 27% 69.9M 9s\n", + "166300K .......... .......... .......... .......... .......... 27% 73.1M 9s\n", + "166350K .......... .......... .......... .......... .......... 27% 71.3M 9s\n", + "166400K .......... .......... .......... .......... .......... 27% 53.1M 9s\n", + "166450K .......... .......... .......... .......... .......... 27% 55.8M 9s\n", + "166500K .......... .......... .......... .......... .......... 28% 53.8M 9s\n", + "166550K .......... .......... .......... .......... .......... 28% 77.2M 9s\n", + "166600K .......... .......... .......... .......... .......... 28% 62.5M 9s\n", + "166650K .......... .......... .......... .......... .......... 28% 60.5M 9s\n", + "166700K .......... .......... .......... .......... .......... 28% 62.6M 9s\n", + "166750K .......... .......... .......... .......... .......... 28% 54.2M 9s\n", + "166800K .......... .......... .......... .......... .......... 28% 61.1M 9s\n", + "166850K .......... .......... .......... .......... .......... 28% 68.4M 9s\n", + "166900K .......... .......... .......... .......... .......... 28% 51.9M 9s\n", + "166950K .......... .......... .......... .......... .......... 28% 50.8M 9s\n", + "167000K .......... .......... .......... .......... .......... 28% 46.6M 9s\n", + "167050K .......... .......... .......... .......... .......... 28% 72.8M 9s\n", + "167100K .......... .......... .......... .......... .......... 28% 78.2M 9s\n", + "167150K .......... .......... .......... .......... .......... 28% 64.5M 9s\n", + "167200K .......... .......... .......... .......... .......... 28% 50.7M 9s\n", + "167250K .......... .......... .......... .......... .......... 28% 53.3M 9s\n", + "167300K .......... .......... .......... .......... .......... 28% 65.2M 9s\n", + "167350K .......... .......... .......... .......... .......... 28% 78.0M 9s\n", + "167400K .......... .......... .......... .......... .......... 28% 56.6M 9s\n", + "167450K .......... .......... .......... .......... .......... 28% 63.6M 9s\n", + "167500K .......... .......... .......... .......... .......... 28% 59.7M 9s\n", + "167550K .......... .......... .......... .......... .......... 28% 55.5M 9s\n", + "167600K .......... .......... .......... .......... .......... 28% 69.5M 9s\n", + "167650K .......... .......... .......... .......... .......... 28% 73.5M 9s\n", + "167700K .......... .......... .......... .......... .......... 28% 69.9M 9s\n", + "167750K .......... .......... .......... .......... .......... 28% 45.8M 9s\n", + "167800K .......... .......... .......... .......... .......... 28% 46.3M 9s\n", + "167850K .......... .......... .......... .......... .......... 28% 58.4M 9s\n", + "167900K .......... .......... .......... .......... .......... 28% 69.1M 9s\n", + "167950K .......... .......... .......... .......... .......... 28% 71.0M 9s\n", + "168000K .......... .......... .......... .......... .......... 28% 54.4M 9s\n", + "168050K .......... .......... .......... .......... .......... 28% 65.0M 9s\n", + "168100K .......... .......... .......... .......... .......... 28% 50.9M 9s\n", + "168150K .......... .......... .......... .......... .......... 28% 60.3M 9s\n", + "168200K .......... .......... .......... .......... .......... 28% 61.1M 9s\n", + "168250K .......... .......... .......... .......... .......... 28% 61.7M 9s\n", + "168300K .......... .......... .......... .......... .......... 28% 51.5M 9s\n", + "168350K .......... .......... .......... .......... .......... 28% 51.6M 9s\n", + "168400K .......... .......... .......... .......... .......... 28% 47.9M 9s\n", + "168450K .......... .......... .......... .......... .......... 28% 64.7M 9s\n", + "168500K .......... .......... .......... .......... .......... 28% 68.4M 9s\n", + "168550K .......... .......... .......... .......... .......... 28% 57.4M 9s\n", + "168600K .......... .......... .......... .......... .......... 28% 39.9M 9s\n", + "168650K .......... .......... .......... .......... .......... 28% 55.1M 9s\n", + "168700K .......... .......... .......... .......... .......... 28% 60.2M 9s\n", + "168750K .......... .......... .......... .......... .......... 28% 67.9M 9s\n", + "168800K .......... .......... .......... .......... .......... 28% 54.6M 9s\n", + "168850K .......... .......... .......... .......... .......... 28% 40.8M 9s\n", + "168900K .......... .......... .......... .......... .......... 28% 38.4M 9s\n", + "168950K .......... .......... .......... .......... .......... 28% 42.8M 9s\n", + "169000K .......... .......... .......... .......... .......... 28% 60.0M 9s\n", + "169050K .......... .......... .......... .......... .......... 28% 64.4M 9s\n", + "169100K .......... .......... .......... .......... .......... 28% 60.4M 9s\n", + "169150K .......... .......... .......... .......... .......... 28% 35.1M 9s\n", + "169200K .......... .......... .......... .......... .......... 28% 31.9M 9s\n", + "169250K .......... .......... .......... .......... .......... 28% 62.8M 9s\n", + "169300K .......... .......... .......... .......... .......... 28% 74.7M 9s\n", + "169350K .......... .......... .......... .......... .......... 28% 59.8M 9s\n", + "169400K .......... .......... .......... .......... .......... 28% 55.7M 9s\n", + "169450K .......... .......... .......... .......... .......... 28% 62.7M 9s\n", + "169500K .......... .......... .......... .......... .......... 28% 62.1M 9s\n", + "169550K .......... .......... .......... .......... .......... 28% 64.9M 9s\n", + "169600K .......... .......... .......... .......... .......... 28% 57.7M 9s\n", + "169650K .......... .......... .......... .......... .......... 28% 63.2M 9s\n", + "169700K .......... .......... .......... .......... .......... 28% 67.4M 9s\n", + "169750K .......... .......... .......... .......... .......... 28% 66.2M 9s\n", + "169800K .......... .......... .......... .......... .......... 28% 50.6M 9s\n", + "169850K .......... .......... .......... .......... .......... 28% 68.4M 9s\n", + "169900K .......... .......... .......... .......... .......... 28% 72.4M 9s\n", + "169950K .......... .......... .......... .......... .......... 28% 73.7M 9s\n", + "170000K .......... .......... .......... .......... .......... 28% 66.8M 9s\n", + "170050K .......... .......... .......... .......... .......... 28% 35.9M 9s\n", + "170100K .......... .......... .......... .......... .......... 28% 47.5M 9s\n", + "170150K .......... .......... .......... .......... .......... 28% 69.9M 9s\n", + "170200K .......... .......... .......... .......... .......... 28% 33.9M 9s\n", + "170250K .......... .......... .......... .......... .......... 28% 75.9M 9s\n", + "170300K .......... .......... .......... .......... .......... 28% 33.2M 9s\n", + "170350K .......... .......... .......... .......... .......... 28% 16.6M 9s\n", + "170400K .......... .......... .......... .......... .......... 28% 12.2M 9s\n", + "170450K .......... .......... .......... .......... .......... 28% 28.9M 9s\n", + "170500K .......... .......... .......... .......... .......... 28% 39.8M 9s\n", + "170550K .......... .......... .......... .......... .......... 28% 42.3M 9s\n", + "170600K .......... .......... .......... .......... .......... 28% 15.6M 9s\n", + "170650K .......... .......... .......... .......... .......... 28% 24.2M 9s\n", + "170700K .......... .......... .......... .......... .......... 28% 37.0M 9s\n", + "170750K .......... .......... .......... .......... .......... 28% 43.0M 9s\n", + "170800K .......... .......... .......... .......... .......... 28% 40.1M 9s\n", + "170850K .......... .......... .......... .......... .......... 28% 36.2M 9s\n", + "170900K .......... .......... .......... .......... .......... 28% 43.6M 9s\n", + "170950K .......... .......... .......... .......... .......... 28% 42.6M 9s\n", + "171000K .......... .......... .......... .......... .......... 28% 18.9M 9s\n", + "171050K .......... .......... .......... .......... .......... 28% 24.8M 9s\n", + "171100K .......... .......... .......... .......... .......... 28% 69.7M 9s\n", + "171150K .......... .......... .......... .......... .......... 28% 44.6M 9s\n", + "171200K .......... .......... .......... .......... .......... 28% 60.1M 9s\n", + "171250K .......... .......... .......... .......... .......... 28% 39.4M 9s\n", + "171300K .......... .......... .......... .......... .......... 28% 50.9M 9s\n", + "171350K .......... .......... .......... .......... .......... 28% 42.6M 9s\n", + "171400K .......... .......... .......... .......... .......... 28% 39.7M 9s\n", + "171450K .......... .......... .......... .......... .......... 28% 45.3M 9s\n", + "171500K .......... .......... .......... .......... .......... 28% 46.2M 9s\n", + "171550K .......... .......... .......... .......... .......... 28% 53.0M 9s\n", + "171600K .......... .......... .......... .......... .......... 28% 60.0M 9s\n", + "171650K .......... .......... .......... .......... .......... 28% 3.78M 9s\n", + "171700K .......... .......... .......... .......... .......... 28% 57.1M 9s\n", + "171750K .......... .......... .......... .......... .......... 28% 73.5M 9s\n", + "171800K .......... .......... .......... .......... .......... 28% 55.5M 9s\n", + "171850K .......... .......... .......... .......... .......... 28% 58.5M 9s\n", + "171900K .......... .......... .......... .......... .......... 28% 65.0M 9s\n", + "171950K .......... .......... .......... .......... .......... 28% 74.3M 9s\n", + "172000K .......... .......... .......... .......... .......... 28% 50.6M 9s\n", + "172050K .......... .......... .......... .......... .......... 28% 58.7M 9s\n", + "172100K .......... .......... .......... .......... .......... 28% 66.1M 9s\n", + "172150K .......... .......... .......... .......... .......... 28% 69.5M 9s\n", + "172200K .......... .......... .......... .......... .......... 28% 47.1M 9s\n", + "172250K .......... .......... .......... .......... .......... 28% 50.3M 9s\n", + "172300K .......... .......... .......... .......... .......... 28% 52.7M 9s\n", + "172350K .......... .......... .......... .......... .......... 28% 17.8M 9s\n", + "172400K .......... .......... .......... .......... .......... 28% 47.1M 9s\n", + "172450K .......... .......... .......... .......... .......... 29% 61.5M 9s\n", + "172500K .......... .......... .......... .......... .......... 29% 70.1M 9s\n", + "172550K .......... .......... .......... .......... .......... 29% 70.6M 9s\n", + "172600K .......... .......... .......... .......... .......... 29% 49.0M 9s\n", + "172650K .......... .......... .......... .......... .......... 29% 54.8M 9s\n", + "172700K .......... .......... .......... .......... .......... 29% 56.2M 9s\n", + "172750K .......... .......... .......... .......... .......... 29% 70.9M 9s\n", + "172800K .......... .......... .......... .......... .......... 29% 61.1M 9s\n", + "172850K .......... .......... .......... .......... .......... 29% 71.7M 9s\n", + "172900K .......... .......... .......... .......... .......... 29% 70.2M 9s\n", + "172950K .......... .......... .......... .......... .......... 29% 69.4M 9s\n", + "173000K .......... .......... .......... .......... .......... 29% 49.8M 9s\n", + "173050K .......... .......... .......... .......... .......... 29% 58.9M 9s\n", + "173100K .......... .......... .......... .......... .......... 29% 77.4M 9s\n", + "173150K .......... .......... .......... .......... .......... 29% 51.3M 9s\n", + "173200K .......... .......... .......... .......... .......... 29% 61.8M 9s\n", + "173250K .......... .......... .......... .......... .......... 29% 59.9M 9s\n", + "173300K .......... .......... .......... .......... .......... 29% 43.9M 9s\n", + "173350K .......... .......... .......... .......... .......... 29% 57.1M 9s\n", + "173400K .......... .......... .......... .......... .......... 29% 38.3M 9s\n", + "173450K .......... .......... .......... .......... .......... 29% 71.2M 9s\n", + "173500K .......... .......... .......... .......... .......... 29% 77.8M 9s\n", + "173550K .......... .......... .......... .......... .......... 29% 47.7M 9s\n", + "173600K .......... .......... .......... .......... .......... 29% 50.9M 9s\n", + "173650K .......... .......... .......... .......... .......... 29% 51.7M 9s\n", + "173700K .......... .......... .......... .......... .......... 29% 57.8M 9s\n", + "173750K .......... .......... .......... .......... .......... 29% 61.1M 9s\n", + "173800K .......... .......... .......... .......... .......... 29% 46.3M 9s\n", + "173850K .......... .......... .......... .......... .......... 29% 60.5M 9s\n", + "173900K .......... .......... .......... .......... .......... 29% 58.2M 9s\n", + "173950K .......... .......... .......... .......... .......... 29% 67.5M 9s\n", + "174000K .......... .......... .......... .......... .......... 29% 59.6M 9s\n", + "174050K .......... .......... .......... .......... .......... 29% 56.6M 9s\n", + "174100K .......... .......... .......... .......... .......... 29% 56.3M 9s\n", + "174150K .......... .......... .......... .......... .......... 29% 56.9M 9s\n", + "174200K .......... .......... .......... .......... .......... 29% 45.6M 9s\n", + "174250K .......... .......... .......... .......... .......... 29% 66.6M 9s\n", + "174300K .......... .......... .......... .......... .......... 29% 70.9M 9s\n", + "174350K .......... .......... .......... .......... .......... 29% 59.8M 9s\n", + "174400K .......... .......... .......... .......... .......... 29% 58.6M 9s\n", + "174450K .......... .......... .......... .......... .......... 29% 57.1M 9s\n", + "174500K .......... .......... .......... .......... .......... 29% 58.4M 9s\n", + "174550K .......... .......... .......... .......... .......... 29% 62.6M 9s\n", + "174600K .......... .......... .......... .......... .......... 29% 47.4M 9s\n", + "174650K .......... .......... .......... .......... .......... 29% 51.5M 9s\n", + "174700K .......... .......... .......... .......... .......... 29% 66.6M 9s\n", + "174750K .......... .......... .......... .......... .......... 29% 55.3M 9s\n", + "174800K .......... .......... .......... .......... .......... 29% 50.2M 9s\n", + "174850K .......... .......... .......... .......... .......... 29% 48.7M 9s\n", + "174900K .......... .......... .......... .......... .......... 29% 57.8M 9s\n", + "174950K .......... .......... .......... .......... .......... 29% 57.6M 9s\n", + "175000K .......... .......... .......... .......... .......... 29% 51.4M 9s\n", + "175050K .......... .......... .......... .......... .......... 29% 69.3M 9s\n", + "175100K .......... .......... .......... .......... .......... 29% 49.7M 9s\n", + "175150K .......... .......... .......... .......... .......... 29% 55.2M 9s\n", + "175200K .......... .......... .......... .......... .......... 29% 58.4M 9s\n", + "175250K .......... .......... .......... .......... .......... 29% 58.0M 9s\n", + "175300K .......... .......... .......... .......... .......... 29% 69.6M 9s\n", + "175350K .......... .......... .......... .......... .......... 29% 70.3M 9s\n", + "175400K .......... .......... .......... .......... .......... 29% 45.4M 9s\n", + "175450K .......... .......... .......... .......... .......... 29% 63.7M 9s\n", + "175500K .......... .......... .......... .......... .......... 29% 53.9M 9s\n", + "175550K .......... .......... .......... .......... .......... 29% 65.9M 8s\n", + "175600K .......... .......... .......... .......... .......... 29% 58.7M 8s\n", + "175650K .......... .......... .......... .......... .......... 29% 54.2M 8s\n", + "175700K .......... .......... .......... .......... .......... 29% 67.7M 8s\n", + "175750K .......... .......... .......... .......... .......... 29% 69.9M 8s\n", + "175800K .......... .......... .......... .......... .......... 29% 45.7M 8s\n", + "175850K .......... .......... .......... .......... .......... 29% 69.7M 8s\n", + "175900K .......... .......... .......... .......... .......... 29% 55.5M 8s\n", + "175950K .......... .......... .......... .......... .......... 29% 59.3M 8s\n", + "176000K .......... .......... .......... .......... .......... 29% 66.9M 8s\n", + "176050K .......... .......... .......... .......... .......... 29% 61.7M 8s\n", + "176100K .......... .......... .......... .......... .......... 29% 62.8M 8s\n", + "176150K .......... .......... .......... .......... .......... 29% 75.6M 8s\n", + "176200K .......... .......... .......... .......... .......... 29% 47.7M 8s\n", + "176250K .......... .......... .......... .......... .......... 29% 59.8M 8s\n", + "176300K .......... .......... .......... .......... .......... 29% 69.7M 8s\n", + "176350K .......... .......... .......... .......... .......... 29% 58.9M 8s\n", + "176400K .......... .......... .......... .......... .......... 29% 44.9M 8s\n", + "176450K .......... .......... .......... .......... .......... 29% 50.4M 8s\n", + "176500K .......... .......... .......... .......... .......... 29% 67.1M 8s\n", + "176550K .......... .......... .......... .......... .......... 29% 62.8M 8s\n", + "176600K .......... .......... .......... .......... .......... 29% 56.1M 8s\n", + "176650K .......... .......... .......... .......... .......... 29% 48.7M 8s\n", + "176700K .......... .......... .......... .......... .......... 29% 63.4M 8s\n", + "176750K .......... .......... .......... .......... .......... 29% 61.6M 8s\n", + "176800K .......... .......... .......... .......... .......... 29% 60.1M 8s\n", + "176850K .......... .......... .......... .......... .......... 29% 5.97M 8s\n", + "176900K .......... .......... .......... .......... .......... 29% 59.8M 8s\n", + "176950K .......... .......... .......... .......... .......... 29% 67.7M 8s\n", + "177000K .......... .......... .......... .......... .......... 29% 57.4M 8s\n", + "177050K .......... .......... .......... .......... .......... 29% 65.5M 8s\n", + "177100K .......... .......... .......... .......... .......... 29% 67.4M 8s\n", + "177150K .......... .......... .......... .......... .......... 29% 64.9M 8s\n", + "177200K .......... .......... .......... .......... .......... 29% 50.4M 8s\n", + "177250K .......... .......... .......... .......... .......... 29% 60.8M 8s\n", + "177300K .......... .......... .......... .......... .......... 29% 61.2M 8s\n", + "177350K .......... .......... .......... .......... .......... 29% 73.3M 8s\n", + "177400K .......... .......... .......... .......... .......... 29% 57.0M 8s\n", + "177450K .......... .......... .......... .......... .......... 29% 70.3M 8s\n", + "177500K .......... .......... .......... .......... .......... 29% 49.3M 8s\n", + "177550K .......... .......... .......... .......... .......... 29% 55.5M 8s\n", + "177600K .......... .......... .......... .......... .......... 29% 58.5M 8s\n", + "177650K .......... .......... .......... .......... .......... 29% 67.5M 8s\n", + "177700K .......... .......... .......... .......... .......... 29% 67.9M 8s\n", + "177750K .......... .......... .......... .......... .......... 29% 50.1M 8s\n", + "177800K .......... .......... .......... .......... .......... 29% 39.3M 8s\n", + "177850K .......... .......... .......... .......... .......... 29% 58.4M 8s\n", + "177900K .......... .......... .......... .......... .......... 29% 67.1M 8s\n", + "177950K .......... .......... .......... .......... .......... 29% 66.0M 8s\n", + "178000K .......... .......... .......... .......... .......... 29% 48.8M 8s\n", + "178050K .......... .......... .......... .......... .......... 29% 45.2M 8s\n", + "178100K .......... .......... .......... .......... .......... 29% 57.8M 8s\n", + "178150K .......... .......... .......... .......... .......... 29% 71.6M 8s\n", + "178200K .......... .......... .......... .......... .......... 29% 51.6M 8s\n", + "178250K .......... .......... .......... .......... .......... 29% 55.2M 8s\n", + "178300K .......... .......... .......... .......... .......... 29% 43.9M 8s\n", + "178350K .......... .......... .......... .......... .......... 29% 62.9M 8s\n", + "178400K .......... .......... .......... .......... .......... 30% 60.3M 8s\n", + "178450K .......... .......... .......... .......... .......... 30% 69.1M 8s\n", + "178500K .......... .......... .......... .......... .......... 30% 48.7M 8s\n", + "178550K .......... .......... .......... .......... .......... 30% 45.8M 8s\n", + "178600K .......... .......... .......... .......... .......... 30% 51.0M 8s\n", + "178650K .......... .......... .......... .......... .......... 30% 70.2M 8s\n", + "178700K .......... .......... .......... .......... .......... 30% 63.7M 8s\n", + "178750K .......... .......... .......... .......... .......... 30% 45.0M 8s\n", + "178800K .......... .......... .......... .......... .......... 30% 48.0M 8s\n", + "178850K .......... .......... .......... .......... .......... 30% 61.8M 8s\n", + "178900K .......... .......... .......... .......... .......... 30% 62.1M 8s\n", + "178950K .......... .......... .......... .......... .......... 30% 74.3M 8s\n", + "179000K .......... .......... .......... .......... .......... 30% 41.9M 8s\n", + "179050K .......... .......... .......... .......... .......... 30% 46.8M 8s\n", + "179100K .......... .......... .......... .......... .......... 30% 67.2M 8s\n", + "179150K .......... .......... .......... .......... .......... 30% 67.6M 8s\n", + "179200K .......... .......... .......... .......... .......... 30% 56.9M 8s\n", + "179250K .......... .......... .......... .......... .......... 30% 53.4M 8s\n", + "179300K .......... .......... .......... .......... .......... 30% 48.4M 8s\n", + "179350K .......... .......... .......... .......... .......... 30% 61.6M 8s\n", + "179400K .......... .......... .......... .......... .......... 30% 56.4M 8s\n", + "179450K .......... .......... .......... .......... .......... 30% 72.4M 8s\n", + "179500K .......... .......... .......... .......... .......... 30% 64.4M 8s\n", + "179550K .......... .......... .......... .......... .......... 30% 49.0M 8s\n", + "179600K .......... .......... .......... .......... .......... 30% 51.7M 8s\n", + "179650K .......... .......... .......... .......... .......... 30% 76.6M 8s\n", + "179700K .......... .......... .......... .......... .......... 30% 72.6M 8s\n", + "179750K .......... .......... .......... .......... .......... 30% 68.4M 8s\n", + "179800K .......... .......... .......... .......... .......... 30% 52.7M 8s\n", + "179850K .......... .......... .......... .......... .......... 30% 48.1M 8s\n", + "179900K .......... .......... .......... .......... .......... 30% 52.9M 8s\n", + "179950K .......... .......... .......... .......... .......... 30% 57.9M 8s\n", + "180000K .......... .......... .......... .......... .......... 30% 63.6M 8s\n", + "180050K .......... .......... .......... .......... .......... 30% 65.4M 8s\n", + "180100K .......... .......... .......... .......... .......... 30% 49.9M 8s\n", + "180150K .......... .......... .......... .......... .......... 30% 50.6M 8s\n", + "180200K .......... .......... .......... .......... .......... 30% 42.6M 8s\n", + "180250K .......... .......... .......... .......... .......... 30% 62.8M 8s\n", + "180300K .......... .......... .......... .......... .......... 30% 66.3M 8s\n", + "180350K .......... .......... .......... .......... .......... 30% 73.0M 8s\n", + "180400K .......... .......... .......... .......... .......... 30% 48.1M 8s\n", + "180450K .......... .......... .......... .......... .......... 30% 59.5M 8s\n", + "180500K .......... .......... .......... .......... .......... 30% 49.9M 8s\n", + "180550K .......... .......... .......... .......... .......... 30% 54.5M 8s\n", + "180600K .......... .......... .......... .......... .......... 30% 49.0M 8s\n", + "180650K .......... .......... .......... .......... .......... 30% 72.8M 8s\n", + "180700K .......... .......... .......... .......... .......... 30% 56.4M 8s\n", + "180750K .......... .......... .......... .......... .......... 30% 48.6M 8s\n", + "180800K .......... .......... .......... .......... .......... 30% 44.7M 8s\n", + "180850K .......... .......... .......... .......... .......... 30% 60.9M 8s\n", + "180900K .......... .......... .......... .......... .......... 30% 71.2M 8s\n", + "180950K .......... .......... .......... .......... .......... 30% 58.9M 8s\n", + "181000K .......... .......... .......... .......... .......... 30% 40.2M 8s\n", + "181050K .......... .......... .......... .......... .......... 30% 48.1M 8s\n", + "181100K .......... .......... .......... .......... .......... 30% 66.9M 8s\n", + "181150K .......... .......... .......... .......... .......... 30% 70.0M 8s\n", + "181200K .......... .......... .......... .......... .......... 30% 55.9M 8s\n", + "181250K .......... .......... .......... .......... .......... 30% 41.4M 8s\n", + "181300K .......... .......... .......... .......... .......... 30% 50.0M 8s\n", + "181350K .......... .......... .......... .......... .......... 30% 59.8M 8s\n", + "181400K .......... .......... .......... .......... .......... 30% 57.0M 8s\n", + "181450K .......... .......... .......... .......... .......... 30% 57.2M 8s\n", + "181500K .......... .......... .......... .......... .......... 30% 63.8M 8s\n", + "181550K .......... .......... .......... .......... .......... 30% 59.5M 8s\n", + "181600K .......... .......... .......... .......... .......... 30% 50.9M 8s\n", + "181650K .......... .......... .......... .......... .......... 30% 61.4M 8s\n", + "181700K .......... .......... .......... .......... .......... 30% 65.3M 8s\n", + "181750K .......... .......... .......... .......... .......... 30% 54.5M 8s\n", + "181800K .......... .......... .......... .......... .......... 30% 40.9M 8s\n", + "181850K .......... .......... .......... .......... .......... 30% 62.0M 8s\n", + "181900K .......... .......... .......... .......... .......... 30% 62.6M 8s\n", + "181950K .......... .......... .......... .......... .......... 30% 70.0M 8s\n", + "182000K .......... .......... .......... .......... .......... 30% 42.6M 8s\n", + "182050K .......... .......... .......... .......... .......... 30% 48.6M 8s\n", + "182100K .......... .......... .......... .......... .......... 30% 64.0M 8s\n", + "182150K .......... .......... .......... .......... .......... 30% 78.6M 8s\n", + "182200K .......... .......... .......... .......... .......... 30% 52.6M 8s\n", + "182250K .......... .......... .......... .......... .......... 30% 54.7M 8s\n", + "182300K .......... .......... .......... .......... .......... 30% 48.7M 8s\n", + "182350K .......... .......... .......... .......... .......... 30% 55.5M 8s\n", + "182400K .......... .......... .......... .......... .......... 30% 55.8M 8s\n", + "182450K .......... .......... .......... .......... .......... 30% 70.6M 8s\n", + "182500K .......... .......... .......... .......... .......... 30% 59.2M 8s\n", + "182550K .......... .......... .......... .......... .......... 30% 4.45M 8s\n", + "182600K .......... .......... .......... .......... .......... 30% 53.0M 8s\n", + "182650K .......... .......... .......... .......... .......... 30% 65.0M 8s\n", + "182700K .......... .......... .......... .......... .......... 30% 69.3M 8s\n", + "182750K .......... .......... .......... .......... .......... 30% 61.3M 8s\n", + "182800K .......... .......... .......... .......... .......... 30% 64.2M 8s\n", + "182850K .......... .......... .......... .......... .......... 30% 55.7M 8s\n", + "182900K .......... .......... .......... .......... .......... 30% 62.5M 8s\n", + "182950K .......... .......... .......... .......... .......... 30% 70.6M 8s\n", + "183000K .......... .......... .......... .......... .......... 30% 55.1M 8s\n", + "183050K .......... .......... .......... .......... .......... 30% 52.1M 8s\n", + "183100K .......... .......... .......... .......... .......... 30% 62.1M 8s\n", + "183150K .......... .......... .......... .......... .......... 30% 54.6M 8s\n", + "183200K .......... .......... .......... .......... .......... 30% 58.5M 8s\n", + "183250K .......... .......... .......... .......... .......... 30% 71.1M 8s\n", + "183300K .......... .......... .......... .......... .......... 30% 65.8M 8s\n", + "183350K .......... .......... .......... .......... .......... 30% 53.5M 8s\n", + "183400K .......... .......... .......... .......... .......... 30% 39.3M 8s\n", + "183450K .......... .......... .......... .......... .......... 30% 62.6M 8s\n", + "183500K .......... .......... .......... .......... .......... 30% 68.3M 8s\n", + "183550K .......... .......... .......... .......... .......... 30% 63.1M 8s\n", + "183600K .......... .......... .......... .......... .......... 30% 46.7M 8s\n", + "183650K .......... .......... .......... .......... .......... 30% 63.4M 8s\n", + "183700K .......... .......... .......... .......... .......... 30% 60.6M 8s\n", + "183750K .......... .......... .......... .......... .......... 30% 60.3M 8s\n", + "183800K .......... .......... .......... .......... .......... 30% 56.0M 8s\n", + "183850K .......... .......... .......... .......... .......... 30% 51.5M 8s\n", + "183900K .......... .......... .......... .......... .......... 30% 50.9M 8s\n", + "183950K .......... .......... .......... .......... .......... 30% 58.3M 8s\n", + "184000K .......... .......... .......... .......... .......... 30% 51.1M 8s\n", + "184050K .......... .......... .......... .......... .......... 30% 73.3M 8s\n", + "184100K .......... .......... .......... .......... .......... 30% 67.5M 8s\n", + "184150K .......... .......... .......... .......... .......... 30% 67.1M 8s\n", + "184200K .......... .......... .......... .......... .......... 30% 51.5M 8s\n", + "184250K .......... .......... .......... .......... .......... 30% 52.6M 8s\n", + "184300K .......... .......... .......... .......... .......... 30% 53.5M 8s\n", + "184350K .......... .......... .......... .......... .......... 31% 58.4M 8s\n", + "184400K .......... .......... .......... .......... .......... 31% 63.9M 8s\n", + "184450K .......... .......... .......... .......... .......... 31% 67.1M 8s\n", + "184500K .......... .......... .......... .......... .......... 31% 47.6M 8s\n", + "184550K .......... .......... .......... .......... .......... 31% 50.0M 8s\n", + "184600K .......... .......... .......... .......... .......... 31% 49.9M 8s\n", + "184650K .......... .......... .......... .......... .......... 31% 68.6M 8s\n", + "184700K .......... .......... .......... .......... .......... 31% 60.2M 8s\n", + "184750K .......... .......... .......... .......... .......... 31% 49.0M 8s\n", + "184800K .......... .......... .......... .......... .......... 31% 45.0M 8s\n", + "184850K .......... .......... .......... .......... .......... 31% 61.9M 8s\n", + "184900K .......... .......... .......... .......... .......... 31% 70.4M 8s\n", + "184950K .......... .......... .......... .......... .......... 31% 71.6M 8s\n", + "185000K .......... .......... .......... .......... .......... 31% 35.7M 8s\n", + "185050K .......... .......... .......... .......... .......... 31% 49.5M 8s\n", + "185100K .......... .......... .......... .......... .......... 31% 68.7M 8s\n", + "185150K .......... .......... .......... .......... .......... 31% 70.2M 8s\n", + "185200K .......... .......... .......... .......... .......... 31% 66.5M 8s\n", + "185250K .......... .......... .......... .......... .......... 31% 52.9M 8s\n", + "185300K .......... .......... .......... .......... .......... 31% 56.2M 8s\n", + "185350K .......... .......... .......... .......... .......... 31% 55.8M 8s\n", + "185400K .......... .......... .......... .......... .......... 31% 56.9M 8s\n", + "185450K .......... .......... .......... .......... .......... 31% 73.8M 8s\n", + "185500K .......... .......... .......... .......... .......... 31% 48.9M 8s\n", + "185550K .......... .......... .......... .......... .......... 31% 56.9M 8s\n", + "185600K .......... .......... .......... .......... .......... 31% 49.1M 8s\n", + "185650K .......... .......... .......... .......... .......... 31% 67.6M 8s\n", + "185700K .......... .......... .......... .......... .......... 31% 65.8M 8s\n", + "185750K .......... .......... .......... .......... .......... 31% 52.9M 8s\n", + "185800K .......... .......... .......... .......... .......... 31% 43.7M 8s\n", + "185850K .......... .......... .......... .......... .......... 31% 63.0M 8s\n", + "185900K .......... .......... .......... .......... .......... 31% 72.2M 8s\n", + "185950K .......... .......... .......... .......... .......... 31% 68.3M 8s\n", + "186000K .......... .......... .......... .......... .......... 31% 57.6M 8s\n", + "186050K .......... .......... .......... .......... .......... 31% 55.9M 8s\n", + "186100K .......... .......... .......... .......... .......... 31% 59.1M 8s\n", + "186150K .......... .......... .......... .......... .......... 31% 55.9M 8s\n", + "186200K .......... .......... .......... .......... .......... 31% 59.0M 8s\n", + "186250K .......... .......... .......... .......... .......... 31% 68.5M 8s\n", + "186300K .......... .......... .......... .......... .......... 31% 51.6M 8s\n", + "186350K .......... .......... .......... .......... .......... 31% 48.3M 8s\n", + "186400K .......... .......... .......... .......... .......... 31% 51.7M 8s\n", + "186450K .......... .......... .......... .......... .......... 31% 67.0M 8s\n", + "186500K .......... .......... .......... .......... .......... 31% 68.2M 8s\n", + "186550K .......... .......... .......... .......... .......... 31% 61.4M 8s\n", + "186600K .......... .......... .......... .......... .......... 31% 44.6M 8s\n", + "186650K .......... .......... .......... .......... .......... 31% 62.7M 8s\n", + "186700K .......... .......... .......... .......... .......... 31% 66.5M 8s\n", + "186750K .......... .......... .......... .......... .......... 31% 69.9M 8s\n", + "186800K .......... .......... .......... .......... .......... 31% 63.7M 8s\n", + "186850K .......... .......... .......... .......... .......... 31% 55.5M 8s\n", + "186900K .......... .......... .......... .......... .......... 31% 57.5M 8s\n", + "186950K .......... .......... .......... .......... .......... 31% 58.6M 8s\n", + "187000K .......... .......... .......... .......... .......... 31% 57.8M 8s\n", + "187050K .......... .......... .......... .......... .......... 31% 72.0M 8s\n", + "187100K .......... .......... .......... .......... .......... 31% 65.9M 8s\n", + "187150K .......... .......... .......... .......... .......... 31% 48.0M 8s\n", + "187200K .......... .......... .......... .......... .......... 31% 41.4M 8s\n", + "187250K .......... .......... .......... .......... .......... 31% 70.7M 8s\n", + "187300K .......... .......... .......... .......... .......... 31% 72.1M 8s\n", + "187350K .......... .......... .......... .......... .......... 31% 71.3M 8s\n", + "187400K .......... .......... .......... .......... .......... 31% 37.0M 8s\n", + "187450K .......... .......... .......... .......... .......... 31% 55.6M 8s\n", + "187500K .......... .......... .......... .......... .......... 31% 70.8M 8s\n", + "187550K .......... .......... .......... .......... .......... 31% 67.8M 8s\n", + "187600K .......... .......... .......... .......... .......... 31% 58.3M 8s\n", + "187650K .......... .......... .......... .......... .......... 31% 47.7M 8s\n", + "187700K .......... .......... .......... .......... .......... 31% 50.8M 8s\n", + "187750K .......... .......... .......... .......... .......... 31% 65.8M 8s\n", + "187800K .......... .......... .......... .......... .......... 31% 60.1M 8s\n", + "187850K .......... .......... .......... .......... .......... 31% 68.7M 8s\n", + "187900K .......... .......... .......... .......... .......... 31% 56.0M 8s\n", + "187950K .......... .......... .......... .......... .......... 31% 50.1M 8s\n", + "188000K .......... .......... .......... .......... .......... 31% 51.5M 8s\n", + "188050K .......... .......... .......... .......... .......... 31% 72.2M 8s\n", + "188100K .......... .......... .......... .......... .......... 31% 73.4M 8s\n", + "188150K .......... .......... .......... .......... .......... 31% 71.2M 8s\n", + "188200K .......... .......... .......... .......... .......... 31% 38.6M 8s\n", + "188250K .......... .......... .......... .......... .......... 31% 54.3M 8s\n", + "188300K .......... .......... .......... .......... .......... 31% 64.2M 8s\n", + "188350K .......... .......... .......... .......... .......... 31% 72.0M 8s\n", + "188400K .......... .......... .......... .......... .......... 31% 60.7M 8s\n", + "188450K .......... .......... .......... .......... .......... 31% 56.3M 8s\n", + "188500K .......... .......... .......... .......... .......... 31% 49.5M 8s\n", + "188550K .......... .......... .......... .......... .......... 31% 53.4M 8s\n", + "188600K .......... .......... .......... .......... .......... 31% 56.0M 8s\n", + "188650K .......... .......... .......... .......... .......... 31% 66.9M 8s\n", + "188700K .......... .......... .......... .......... .......... 31% 3.85M 8s\n", + "188750K .......... .......... .......... .......... .......... 31% 64.0M 8s\n", + "188800K .......... .......... .......... .......... .......... 31% 58.4M 8s\n", + "188850K .......... .......... .......... .......... .......... 31% 69.2M 8s\n", + "188900K .......... .......... .......... .......... .......... 31% 64.7M 8s\n", + "188950K .......... .......... .......... .......... .......... 31% 67.2M 8s\n", + "189000K .......... .......... .......... .......... .......... 31% 53.2M 8s\n", + "189050K .......... .......... .......... .......... .......... 31% 53.4M 8s\n", + "189100K .......... .......... .......... .......... .......... 31% 68.5M 8s\n", + "189150K .......... .......... .......... .......... .......... 31% 68.9M 8s\n", + "189200K .......... .......... .......... .......... .......... 31% 58.4M 8s\n", + "189250K .......... .......... .......... .......... .......... 31% 55.7M 8s\n", + "189300K .......... .......... .......... .......... .......... 31% 56.6M 8s\n", + "189350K .......... .......... .......... .......... .......... 31% 59.8M 8s\n", + "189400K .......... .......... .......... .......... .......... 31% 59.9M 8s\n", + "189450K .......... .......... .......... .......... .......... 31% 60.6M 8s\n", + "189500K .......... .......... .......... .......... .......... 31% 49.1M 8s\n", + "189550K .......... .......... .......... .......... .......... 31% 52.2M 8s\n", + "189600K .......... .......... .......... .......... .......... 31% 50.6M 8s\n", + "189650K .......... .......... .......... .......... .......... 31% 68.0M 8s\n", + "189700K .......... .......... .......... .......... .......... 31% 65.5M 8s\n", + "189750K .......... .......... .......... .......... .......... 31% 52.4M 8s\n", + "189800K .......... .......... .......... .......... .......... 31% 41.7M 8s\n", + "189850K .......... .......... .......... .......... .......... 31% 54.6M 8s\n", + "189900K .......... .......... .......... .......... .......... 31% 74.3M 8s\n", + "189950K .......... .......... .......... .......... .......... 31% 65.9M 8s\n", + "190000K .......... .......... .......... .......... .......... 31% 52.8M 8s\n", + "190050K .......... .......... .......... .......... .......... 31% 51.1M 8s\n", + "190100K .......... .......... .......... .......... .......... 31% 57.1M 8s\n", + "190150K .......... .......... .......... .......... .......... 31% 76.4M 8s\n", + "190200K .......... .......... .......... .......... .......... 31% 57.7M 8s\n", + "190250K .......... .......... .......... .......... .......... 31% 72.0M 8s\n", + "190300K .......... .......... .......... .......... .......... 32% 49.3M 8s\n", + "190350K .......... .......... .......... .......... .......... 32% 54.1M 8s\n", + "190400K .......... .......... .......... .......... .......... 32% 62.6M 8s\n", + "190450K .......... .......... .......... .......... .......... 32% 80.5M 8s\n", + "190500K .......... .......... .......... .......... .......... 32% 68.4M 8s\n", + "190550K .......... .......... .......... .......... .......... 32% 61.5M 8s\n", + "190600K .......... .......... .......... .......... .......... 32% 46.6M 8s\n", + "190650K .......... .......... .......... .......... .......... 32% 72.8M 8s\n", + "190700K .......... .......... .......... .......... .......... 32% 63.5M 8s\n", + "190750K .......... .......... .......... .......... .......... 32% 62.5M 8s\n", + "190800K .......... .......... .......... .......... .......... 32% 64.2M 8s\n", + "190850K .......... .......... .......... .......... .......... 32% 61.3M 8s\n", + "190900K .......... .......... .......... .......... .......... 32% 55.7M 8s\n", + "190950K .......... .......... .......... .......... .......... 32% 71.4M 8s\n", + "191000K .......... .......... .......... .......... .......... 32% 41.0M 8s\n", + "191050K .......... .......... .......... .......... .......... 32% 64.1M 8s\n", + "191100K .......... .......... .......... .......... .......... 32% 61.6M 8s\n", + "191150K .......... .......... .......... .......... .......... 32% 57.8M 8s\n", + "191200K .......... .......... .......... .......... .......... 32% 50.0M 8s\n", + "191250K .......... .......... .......... .......... .......... 32% 46.2M 8s\n", + "191300K .......... .......... .......... .......... .......... 32% 73.0M 8s\n", + "191350K .......... .......... .......... .......... .......... 32% 54.6M 8s\n", + "191400K .......... .......... .......... .......... .......... 32% 39.7M 8s\n", + "191450K .......... .......... .......... .......... .......... 32% 46.9M 8s\n", + "191500K .......... .......... .......... .......... .......... 32% 66.0M 8s\n", + "191550K .......... .......... .......... .......... .......... 32% 71.9M 8s\n", + "191600K .......... .......... .......... .......... .......... 32% 58.3M 8s\n", + "191650K .......... .......... .......... .......... .......... 32% 46.3M 8s\n", + "191700K .......... .......... .......... .......... .......... 32% 63.3M 8s\n", + "191750K .......... .......... .......... .......... .......... 32% 71.8M 8s\n", + "191800K .......... .......... .......... .......... .......... 32% 60.2M 8s\n", + "191850K .......... .......... .......... .......... .......... 32% 70.9M 8s\n", + "191900K .......... .......... .......... .......... .......... 32% 47.3M 8s\n", + "191950K .......... .......... .......... .......... .......... 32% 57.4M 8s\n", + "192000K .......... .......... .......... .......... .......... 32% 63.4M 8s\n", + "192050K .......... .......... .......... .......... .......... 32% 58.9M 8s\n", + "192100K .......... .......... .......... .......... .......... 32% 57.8M 8s\n", + "192150K .......... .......... .......... .......... .......... 32% 57.3M 8s\n", + "192200K .......... .......... .......... .......... .......... 32% 48.3M 8s\n", + "192250K .......... .......... .......... .......... .......... 32% 61.6M 8s\n", + "192300K .......... .......... .......... .......... .......... 32% 73.4M 8s\n", + "192350K .......... .......... .......... .......... .......... 32% 53.3M 8s\n", + "192400K .......... .......... .......... .......... .......... 32% 51.1M 8s\n", + "192450K .......... .......... .......... .......... .......... 32% 56.1M 8s\n", + "192500K .......... .......... .......... .......... .......... 32% 65.2M 8s\n", + "192550K .......... .......... .......... .......... .......... 32% 67.1M 8s\n", + "192600K .......... .......... .......... .......... .......... 32% 43.1M 8s\n", + "192650K .......... .......... .......... .......... .......... 32% 64.5M 8s\n", + "192700K .......... .......... .......... .......... .......... 32% 58.9M 8s\n", + "192750K .......... .......... .......... .......... .......... 32% 59.9M 8s\n", + "192800K .......... .......... .......... .......... .......... 32% 58.9M 8s\n", + "192850K .......... .......... .......... .......... .......... 32% 55.6M 8s\n", + "192900K .......... .......... .......... .......... .......... 32% 61.5M 8s\n", + "192950K .......... .......... .......... .......... .......... 32% 75.1M 8s\n", + "193000K .......... .......... .......... .......... .......... 32% 58.9M 8s\n", + "193050K .......... .......... .......... .......... .......... 32% 71.3M 8s\n", + "193100K .......... .......... .......... .......... .......... 32% 55.1M 8s\n", + "193150K .......... .......... .......... .......... .......... 32% 65.9M 8s\n", + "193200K .......... .......... .......... .......... .......... 32% 52.2M 8s\n", + "193250K .......... .......... .......... .......... .......... 32% 70.8M 8s\n", + "193300K .......... .......... .......... .......... .......... 32% 66.8M 8s\n", + "193350K .......... .......... .......... .......... .......... 32% 60.3M 8s\n", + "193400K .......... .......... .......... .......... .......... 32% 45.5M 8s\n", + "193450K .......... .......... .......... .......... .......... 32% 45.6M 8s\n", + "193500K .......... .......... .......... .......... .......... 32% 58.2M 8s\n", + "193550K .......... .......... .......... .......... .......... 32% 69.7M 8s\n", + "193600K .......... .......... .......... .......... .......... 32% 44.9M 8s\n", + "193650K .......... .......... .......... .......... .......... 32% 50.4M 8s\n", + "193700K .......... .......... .......... .......... .......... 32% 58.0M 8s\n", + "193750K .......... .......... .......... .......... .......... 32% 54.2M 8s\n", + "193800K .......... .......... .......... .......... .......... 32% 53.6M 8s\n", + "193850K .......... .......... .......... .......... .......... 32% 54.9M 8s\n", + "193900K .......... .......... .......... .......... .......... 32% 52.0M 8s\n", + "193950K .......... .......... .......... .......... .......... 32% 61.4M 8s\n", + "194000K .......... .......... .......... .......... .......... 32% 57.4M 8s\n", + "194050K .......... .......... .......... .......... .......... 32% 70.6M 8s\n", + "194100K .......... .......... .......... .......... .......... 32% 47.1M 8s\n", + "194150K .......... .......... .......... .......... .......... 32% 55.5M 8s\n", + "194200K .......... .......... .......... .......... .......... 32% 54.0M 8s\n", + "194250K .......... .......... .......... .......... .......... 32% 56.1M 8s\n", + "194300K .......... .......... .......... .......... .......... 32% 68.6M 8s\n", + "194350K .......... .......... .......... .......... .......... 32% 63.9M 8s\n", + "194400K .......... .......... .......... .......... .......... 32% 43.0M 8s\n", + "194450K .......... .......... .......... .......... .......... 32% 63.4M 8s\n", + "194500K .......... .......... .......... .......... .......... 32% 55.3M 8s\n", + "194550K .......... .......... .......... .......... .......... 32% 73.3M 8s\n", + "194600K .......... .......... .......... .......... .......... 32% 51.5M 8s\n", + "194650K .......... .......... .......... .......... .......... 32% 57.0M 8s\n", + "194700K .......... .......... .......... .......... .......... 32% 54.9M 8s\n", + "194750K .......... .......... .......... .......... .......... 32% 66.4M 8s\n", + "194800K .......... .......... .......... .......... .......... 32% 59.4M 8s\n", + "194850K .......... .......... .......... .......... .......... 32% 67.4M 8s\n", + "194900K .......... .......... .......... .......... .......... 32% 52.8M 8s\n", + "194950K .......... .......... .......... .......... .......... 32% 55.3M 8s\n", + "195000K .......... .......... .......... .......... .......... 32% 50.6M 8s\n", + "195050K .......... .......... .......... .......... .......... 32% 59.5M 8s\n", + "195100K .......... .......... .......... .......... .......... 32% 67.4M 8s\n", + "195150K .......... .......... .......... .......... .......... 32% 69.3M 8s\n", + "195200K .......... .......... .......... .......... .......... 32% 42.6M 8s\n", + "195250K .......... .......... .......... .......... .......... 32% 53.4M 8s\n", + "195300K .......... .......... .......... .......... .......... 32% 63.7M 8s\n", + "195350K .......... .......... .......... .......... .......... 32% 66.9M 8s\n", + "195400K .......... .......... .......... .......... .......... 32% 55.1M 8s\n", + "195450K .......... .......... .......... .......... .......... 32% 46.5M 8s\n", + "195500K .......... .......... .......... .......... .......... 32% 55.4M 8s\n", + "195550K .......... .......... .......... .......... .......... 32% 52.0M 8s\n", + "195600K .......... .......... .......... .......... .......... 32% 55.3M 8s\n", + "195650K .......... .......... .......... .......... .......... 32% 73.3M 8s\n", + "195700K .......... .......... .......... .......... .......... 32% 58.7M 8s\n", + "195750K .......... .......... .......... .......... .......... 32% 50.9M 8s\n", + "195800K .......... .......... .......... .......... .......... 32% 57.7M 8s\n", + "195850K .......... .......... .......... .......... .......... 32% 62.0M 8s\n", + "195900K .......... .......... .......... .......... .......... 32% 69.7M 8s\n", + "195950K .......... .......... .......... .......... .......... 32% 63.3M 8s\n", + "196000K .......... .......... .......... .......... .......... 32% 50.4M 8s\n", + "196050K .......... .......... .......... .......... .......... 32% 64.0M 8s\n", + "196100K .......... .......... .......... .......... .......... 32% 62.1M 8s\n", + "196150K .......... .......... .......... .......... .......... 32% 54.8M 8s\n", + "196200K .......... .......... .......... .......... .......... 32% 59.1M 8s\n", + "196250K .......... .......... .......... .......... .......... 33% 60.2M 8s\n", + "196300K .......... .......... .......... .......... .......... 33% 60.8M 8s\n", + "196350K .......... .......... .......... .......... .......... 33% 70.1M 8s\n", + "196400K .......... .......... .......... .......... .......... 33% 61.0M 8s\n", + "196450K .......... .......... .......... .......... .......... 33% 64.1M 8s\n", + "196500K .......... .......... .......... .......... .......... 33% 73.4M 8s\n", + "196550K .......... .......... .......... .......... .......... 33% 72.7M 8s\n", + "196600K .......... .......... .......... .......... .......... 33% 59.2M 8s\n", + "196650K .......... .......... .......... .......... .......... 33% 71.8M 8s\n", + "196700K .......... .......... .......... .......... .......... 33% 74.7M 8s\n", + "196750K .......... .......... .......... .......... .......... 33% 66.6M 8s\n", + "196800K .......... .......... .......... .......... .......... 33% 60.0M 8s\n", + "196850K .......... .......... .......... .......... .......... 33% 79.0M 8s\n", + "196900K .......... .......... .......... .......... .......... 33% 72.4M 8s\n", + "196950K .......... .......... .......... .......... .......... 33% 75.4M 8s\n", + "197000K .......... .......... .......... .......... .......... 33% 57.2M 8s\n", + "197050K .......... .......... .......... .......... .......... 33% 73.5M 8s\n", + "197100K .......... .......... .......... .......... .......... 33% 3.89M 8s\n", + "197150K .......... .......... .......... .......... .......... 33% 72.3M 8s\n", + "197200K .......... .......... .......... .......... .......... 33% 62.1M 8s\n", + "197250K .......... .......... .......... .......... .......... 33% 67.7M 8s\n", + "197300K .......... .......... .......... .......... .......... 33% 70.7M 8s\n", + "197350K .......... .......... .......... .......... .......... 33% 73.0M 8s\n", + "197400K .......... .......... .......... .......... .......... 33% 59.1M 8s\n", + "197450K .......... .......... .......... .......... .......... 33% 65.1M 8s\n", + "197500K .......... .......... .......... .......... .......... 33% 62.5M 8s\n", + "197550K .......... .......... .......... .......... .......... 33% 77.1M 8s\n", + "197600K .......... .......... .......... .......... .......... 33% 68.3M 8s\n", + "197650K .......... .......... .......... .......... .......... 33% 68.9M 8s\n", + "197700K .......... .......... .......... .......... .......... 33% 74.5M 8s\n", + "197750K .......... .......... .......... .......... .......... 33% 68.1M 8s\n", + "197800K .......... .......... .......... .......... .......... 33% 52.4M 8s\n", + "197850K .......... .......... .......... .......... .......... 33% 65.3M 8s\n", + "197900K .......... .......... .......... .......... .......... 33% 62.3M 8s\n", + "197950K .......... .......... .......... .......... .......... 33% 1.43M 8s\n", + "198000K .......... .......... .......... .......... .......... 33% 55.2M 8s\n", + "198050K .......... .......... .......... .......... .......... 33% 37.1M 8s\n", + "198100K .......... .......... .......... .......... .......... 33% 52.9M 8s\n", + "198150K .......... .......... .......... .......... .......... 33% 55.6M 8s\n", + "198200K .......... .......... .......... .......... .......... 33% 46.5M 8s\n", + "198250K .......... .......... .......... .......... .......... 33% 51.4M 8s\n", + "198300K .......... .......... .......... .......... .......... 33% 47.9M 8s\n", + "198350K .......... .......... .......... .......... .......... 33% 47.7M 8s\n", + "198400K .......... .......... .......... .......... .......... 33% 66.6M 8s\n", + "198450K .......... .......... .......... .......... .......... 33% 53.7M 8s\n", + "198500K .......... .......... .......... .......... .......... 33% 51.4M 8s\n", + "198550K .......... .......... .......... .......... .......... 33% 47.5M 8s\n", + "198600K .......... .......... .......... .......... .......... 33% 44.6M 8s\n", + "198650K .......... .......... .......... .......... .......... 33% 55.0M 8s\n", + "198700K .......... .......... .......... .......... .......... 33% 47.4M 8s\n", + "198750K .......... .......... .......... .......... .......... 33% 50.4M 8s\n", + "198800K .......... .......... .......... .......... .......... 33% 50.3M 8s\n", + "198850K .......... .......... .......... .......... .......... 33% 43.3M 8s\n", + "198900K .......... .......... .......... .......... .......... 33% 45.0M 8s\n", + "198950K .......... .......... .......... .......... .......... 33% 43.9M 8s\n", + "199000K .......... .......... .......... .......... .......... 33% 34.6M 8s\n", + "199050K .......... .......... .......... .......... .......... 33% 53.3M 8s\n", + "199100K .......... .......... .......... .......... .......... 33% 63.2M 8s\n", + "199150K .......... .......... .......... .......... .......... 33% 66.9M 8s\n", + "199200K .......... .......... .......... .......... .......... 33% 49.6M 8s\n", + "199250K .......... .......... .......... .......... .......... 33% 61.3M 8s\n", + "199300K .......... .......... .......... .......... .......... 33% 56.3M 8s\n", + "199350K .......... .......... .......... .......... .......... 33% 57.2M 8s\n", + "199400K .......... .......... .......... .......... .......... 33% 44.9M 8s\n", + "199450K .......... .......... .......... .......... .......... 33% 71.8M 8s\n", + "199500K .......... .......... .......... .......... .......... 33% 70.3M 8s\n", + "199550K .......... .......... .......... .......... .......... 33% 61.7M 8s\n", + "199600K .......... .......... .......... .......... .......... 33% 55.3M 8s\n", + "199650K .......... .......... .......... .......... .......... 33% 45.6M 8s\n", + "199700K .......... .......... .......... .......... .......... 33% 57.7M 8s\n", + "199750K .......... .......... .......... .......... .......... 33% 54.8M 8s\n", + "199800K .......... .......... .......... .......... .......... 33% 47.3M 8s\n", + "199850K .......... .......... .......... .......... .......... 33% 45.4M 8s\n", + "199900K .......... .......... .......... .......... .......... 33% 36.9M 8s\n", + "199950K .......... .......... .......... .......... .......... 33% 37.5M 8s\n", + "200000K .......... .......... .......... .......... .......... 33% 41.1M 8s\n", + "200050K .......... .......... .......... .......... .......... 33% 58.9M 8s\n", + "200100K .......... .......... .......... .......... .......... 33% 62.8M 8s\n", + "200150K .......... .......... .......... .......... .......... 33% 56.1M 8s\n", + "200200K .......... .......... .......... .......... .......... 33% 36.6M 8s\n", + "200250K .......... .......... .......... .......... .......... 33% 39.3M 8s\n", + "200300K .......... .......... .......... .......... .......... 33% 47.4M 8s\n", + "200350K .......... .......... .......... .......... .......... 33% 64.0M 8s\n", + "200400K .......... .......... .......... .......... .......... 33% 50.5M 8s\n", + "200450K .......... .......... .......... .......... .......... 33% 58.1M 8s\n", + "200500K .......... .......... .......... .......... .......... 33% 6.61M 8s\n", + "200550K .......... .......... .......... .......... .......... 33% 56.6M 8s\n", + "200600K .......... .......... .......... .......... .......... 33% 58.3M 8s\n", + "200650K .......... .......... .......... .......... .......... 33% 74.1M 8s\n", + "200700K .......... .......... .......... .......... .......... 33% 52.4M 8s\n", + "200750K .......... .......... .......... .......... .......... 33% 29.3M 8s\n", + "200800K .......... .......... .......... .......... .......... 33% 35.1M 8s\n", + "200850K .......... .......... .......... .......... .......... 33% 33.4M 8s\n", + "200900K .......... .......... .......... .......... .......... 33% 32.4M 8s\n", + "200950K .......... .......... .......... .......... .......... 33% 53.9M 8s\n", + "201000K .......... .......... .......... .......... .......... 33% 57.3M 8s\n", + "201050K .......... .......... .......... .......... .......... 33% 62.8M 8s\n", + "201100K .......... .......... .......... .......... .......... 33% 71.7M 8s\n", + "201150K .......... .......... .......... .......... .......... 33% 64.9M 8s\n", + "201200K .......... .......... .......... .......... .......... 33% 51.8M 8s\n", + "201250K .......... .......... .......... .......... .......... 33% 67.4M 8s\n", + "201300K .......... .......... .......... .......... .......... 33% 79.4M 8s\n", + "201350K .......... .......... .......... .......... .......... 33% 69.6M 8s\n", + "201400K .......... .......... .......... .......... .......... 33% 60.8M 8s\n", + "201450K .......... .......... .......... .......... .......... 33% 73.9M 8s\n", + "201500K .......... .......... .......... .......... .......... 33% 61.2M 8s\n", + "201550K .......... .......... .......... .......... .......... 33% 54.3M 8s\n", + "201600K .......... .......... .......... .......... .......... 33% 45.3M 8s\n", + "201650K .......... .......... .......... .......... .......... 33% 67.1M 8s\n", + "201700K .......... .......... .......... .......... .......... 33% 64.5M 8s\n", + "201750K .......... .......... .......... .......... .......... 33% 62.6M 8s\n", + "201800K .......... .......... .......... .......... .......... 33% 49.4M 8s\n", + "201850K .......... .......... .......... .......... .......... 33% 44.9M 8s\n", + "201900K .......... .......... .......... .......... .......... 33% 66.2M 8s\n", + "201950K .......... .......... .......... .......... .......... 33% 68.4M 8s\n", + "202000K .......... .......... .......... .......... .......... 33% 60.1M 8s\n", + "202050K .......... .......... .......... .......... .......... 33% 68.1M 8s\n", + "202100K .......... .......... .......... .......... .......... 33% 52.2M 8s\n", + "202150K .......... .......... .......... .......... .......... 33% 56.5M 8s\n", + "202200K .......... .......... .......... .......... .......... 34% 60.1M 8s\n", + "202250K .......... .......... .......... .......... .......... 34% 69.8M 8s\n", + "202300K .......... .......... .......... .......... .......... 34% 60.8M 8s\n", + "202350K .......... .......... .......... .......... .......... 34% 35.5M 8s\n", + "202400K .......... .......... .......... .......... .......... 34% 32.5M 8s\n", + "202450K .......... .......... .......... .......... .......... 34% 55.5M 8s\n", + "202500K .......... .......... .......... .......... .......... 34% 73.1M 8s\n", + "202550K .......... .......... .......... .......... .......... 34% 51.5M 8s\n", + "202600K .......... .......... .......... .......... .......... 34% 44.1M 8s\n", + "202650K .......... .......... .......... .......... .......... 34% 66.4M 8s\n", + "202700K .......... .......... .......... .......... .......... 34% 65.0M 8s\n", + "202750K .......... .......... .......... .......... .......... 34% 70.1M 8s\n", + "202800K .......... .......... .......... .......... .......... 34% 50.7M 8s\n", + "202850K .......... .......... .......... .......... .......... 34% 41.9M 8s\n", + "202900K .......... .......... .......... .......... .......... 34% 55.9M 8s\n", + "202950K .......... .......... .......... .......... .......... 34% 63.3M 8s\n", + "203000K .......... .......... .......... .......... .......... 34% 50.5M 8s\n", + "203050K .......... .......... .......... .......... .......... 34% 48.2M 8s\n", + "203100K .......... .......... .......... .......... .......... 34% 51.8M 8s\n", + "203150K .......... .......... .......... .......... .......... 34% 50.0M 8s\n", + "203200K .......... .......... .......... .......... .......... 34% 59.2M 8s\n", + "203250K .......... .......... .......... .......... .......... 34% 58.8M 8s\n", + "203300K .......... .......... .......... .......... .......... 34% 44.2M 8s\n", + "203350K .......... .......... .......... .......... .......... 34% 59.0M 8s\n", + "203400K .......... .......... .......... .......... .......... 34% 46.0M 8s\n", + "203450K .......... .......... .......... .......... .......... 34% 73.7M 8s\n", + "203500K .......... .......... .......... .......... .......... 34% 58.6M 8s\n", + "203550K .......... .......... .......... .......... .......... 34% 50.8M 8s\n", + "203600K .......... .......... .......... .......... .......... 34% 53.0M 8s\n", + "203650K .......... .......... .......... .......... .......... 34% 58.0M 8s\n", + "203700K .......... .......... .......... .......... .......... 34% 67.3M 8s\n", + "203750K .......... .......... .......... .......... .......... 34% 76.2M 8s\n", + "203800K .......... .......... .......... .......... .......... 34% 50.7M 8s\n", + "203850K .......... .......... .......... .......... .......... 34% 61.9M 8s\n", + "203900K .......... .......... .......... .......... .......... 34% 52.2M 8s\n", + "203950K .......... .......... .......... .......... .......... 34% 62.9M 8s\n", + "204000K .......... .......... .......... .......... .......... 34% 60.9M 8s\n", + "204050K .......... .......... .......... .......... .......... 34% 64.7M 8s\n", + "204100K .......... .......... .......... .......... .......... 34% 49.9M 8s\n", + "204150K .......... .......... .......... .......... .......... 34% 64.0M 8s\n", + "204200K .......... .......... .......... .......... .......... 34% 53.0M 8s\n", + "204250K .......... .......... .......... .......... .......... 34% 57.1M 8s\n", + "204300K .......... .......... .......... .......... .......... 34% 71.5M 8s\n", + "204350K .......... .......... .......... .......... .......... 34% 70.3M 8s\n", + "204400K .......... .......... .......... .......... .......... 34% 35.6M 8s\n", + "204450K .......... .......... .......... .......... .......... 34% 37.2M 8s\n", + "204500K .......... .......... .......... .......... .......... 34% 36.2M 8s\n", + "204550K .......... .......... .......... .......... .......... 34% 57.2M 8s\n", + "204600K .......... .......... .......... .......... .......... 34% 61.3M 8s\n", + "204650K .......... .......... .......... .......... .......... 34% 73.9M 8s\n", + "204700K .......... .......... .......... .......... .......... 34% 67.2M 8s\n", + "204750K .......... .......... .......... .......... .......... 34% 49.4M 8s\n", + "204800K .......... .......... .......... .......... .......... 34% 46.5M 8s\n", + "204850K .......... .......... .......... .......... .......... 34% 52.8M 8s\n", + "204900K .......... .......... .......... .......... .......... 34% 68.0M 8s\n", + "204950K .......... .......... .......... .......... .......... 34% 64.9M 8s\n", + "205000K .......... .......... .......... .......... .......... 34% 49.8M 8s\n", + "205050K .......... .......... .......... .......... .......... 34% 44.5M 8s\n", + "205100K .......... .......... .......... .......... .......... 34% 52.0M 8s\n", + "205150K .......... .......... .......... .......... .......... 34% 73.5M 8s\n", + "205200K .......... .......... .......... .......... .......... 34% 59.4M 8s\n", + "205250K .......... .......... .......... .......... .......... 34% 51.7M 8s\n", + "205300K .......... .......... .......... .......... .......... 34% 43.2M 8s\n", + "205350K .......... .......... .......... .......... .......... 34% 65.3M 8s\n", + "205400K .......... .......... .......... .......... .......... 34% 58.7M 8s\n", + "205450K .......... .......... .......... .......... .......... 34% 68.3M 8s\n", + "205500K .......... .......... .......... .......... .......... 34% 54.2M 8s\n", + "205550K .......... .......... .......... .......... .......... 34% 62.9M 8s\n", + "205600K .......... .......... .......... .......... .......... 34% 36.6M 8s\n", + "205650K .......... .......... .......... .......... .......... 34% 39.4M 8s\n", + "205700K .......... .......... .......... .......... .......... 34% 41.5M 8s\n", + "205750K .......... .......... .......... .......... .......... 34% 47.1M 8s\n", + "205800K .......... .......... .......... .......... .......... 34% 49.6M 8s\n", + "205850K .......... .......... .......... .......... .......... 34% 68.0M 8s\n", + "205900K .......... .......... .......... .......... .......... 34% 70.9M 8s\n", + "205950K .......... .......... .......... .......... .......... 34% 60.6M 8s\n", + "206000K .......... .......... .......... .......... .......... 34% 50.3M 8s\n", + "206050K .......... .......... .......... .......... .......... 34% 56.3M 8s\n", + "206100K .......... .......... .......... .......... .......... 34% 60.6M 8s\n", + "206150K .......... .......... .......... .......... .......... 34% 59.2M 8s\n", + "206200K .......... .......... .......... .......... .......... 34% 53.4M 8s\n", + "206250K .......... .......... .......... .......... .......... 34% 53.4M 8s\n", + "206300K .......... .......... .......... .......... .......... 34% 61.7M 8s\n", + "206350K .......... .......... .......... .......... .......... 34% 64.8M 8s\n", + "206400K .......... .......... .......... .......... .......... 34% 63.8M 8s\n", + "206450K .......... .......... .......... .......... .......... 34% 73.5M 8s\n", + "206500K .......... .......... .......... .......... .......... 34% 68.6M 8s\n", + "206550K .......... .......... .......... .......... .......... 34% 49.0M 8s\n", + "206600K .......... .......... .......... .......... .......... 34% 49.4M 8s\n", + "206650K .......... .......... .......... .......... .......... 34% 74.6M 8s\n", + "206700K .......... .......... .......... .......... .......... 34% 70.4M 8s\n", + "206750K .......... .......... .......... .......... .......... 34% 77.8M 8s\n", + "206800K .......... .......... .......... .......... .......... 34% 49.2M 8s\n", + "206850K .......... .......... .......... .......... .......... 34% 56.3M 8s\n", + "206900K .......... .......... .......... .......... .......... 34% 58.6M 8s\n", + "206950K .......... .......... .......... .......... .......... 34% 75.1M 8s\n", + "207000K .......... .......... .......... .......... .......... 34% 65.3M 8s\n", + "207050K .......... .......... .......... .......... .......... 34% 67.8M 8s\n", + "207100K .......... .......... .......... .......... .......... 34% 59.5M 8s\n", + "207150K .......... .......... .......... .......... .......... 34% 42.2M 8s\n", + "207200K .......... .......... .......... .......... .......... 34% 61.9M 8s\n", + "207250K .......... .......... .......... .......... .......... 34% 3.81M 8s\n", + "207300K .......... .......... .......... .......... .......... 34% 4.79M 8s\n", + "207350K .......... .......... .......... .......... .......... 34% 56.4M 8s\n", + "207400K .......... .......... .......... .......... .......... 34% 61.8M 8s\n", + "207450K .......... .......... .......... .......... .......... 34% 65.2M 8s\n", + "207500K .......... .......... .......... .......... .......... 34% 64.0M 8s\n", + "207550K .......... .......... .......... .......... .......... 34% 65.9M 8s\n", + "207600K .......... .......... .......... .......... .......... 34% 56.7M 8s\n", + "207650K .......... .......... .......... .......... .......... 34% 59.4M 8s\n", + "207700K .......... .......... .......... .......... .......... 34% 67.2M 8s\n", + "207750K .......... .......... .......... .......... .......... 34% 68.0M 8s\n", + "207800K .......... .......... .......... .......... .......... 34% 52.8M 8s\n", + "207850K .......... .......... .......... .......... .......... 34% 54.2M 8s\n", + "207900K .......... .......... .......... .......... .......... 34% 71.7M 8s\n", + "207950K .......... .......... .......... .......... .......... 34% 52.5M 8s\n", + "208000K .......... .......... .......... .......... .......... 34% 60.4M 8s\n", + "208050K .......... .......... .......... .......... .......... 34% 71.7M 8s\n", + "208100K .......... .......... .......... .......... .......... 34% 63.1M 8s\n", + "208150K .......... .......... .......... .......... .......... 35% 54.9M 8s\n", + "208200K .......... .......... .......... .......... .......... 35% 59.4M 8s\n", + "208250K .......... .......... .......... .......... .......... 35% 54.3M 8s\n", + "208300K .......... .......... .......... .......... .......... 35% 67.2M 8s\n", + "208350K .......... .......... .......... .......... .......... 35% 61.6M 8s\n", + "208400K .......... .......... .......... .......... .......... 35% 49.7M 8s\n", + "208450K .......... .......... .......... .......... .......... 35% 55.3M 8s\n", + "208500K .......... .......... .......... .......... .......... 35% 68.4M 8s\n", + "208550K .......... .......... .......... .......... .......... 35% 57.6M 8s\n", + "208600K .......... .......... .......... .......... .......... 35% 59.1M 8s\n", + "208650K .......... .......... .......... .......... .......... 35% 60.2M 8s\n", + "208700K .......... .......... .......... .......... .......... 35% 49.0M 8s\n", + "208750K .......... .......... .......... .......... .......... 35% 49.5M 8s\n", + "208800K .......... .......... .......... .......... .......... 35% 46.1M 8s\n", + "208850K .......... .......... .......... .......... .......... 35% 72.6M 8s\n", + "208900K .......... .......... .......... .......... .......... 35% 64.6M 8s\n", + "208950K .......... .......... .......... .......... .......... 35% 50.3M 8s\n", + "209000K .......... .......... .......... .......... .......... 35% 47.8M 8s\n", + "209050K .......... .......... .......... .......... .......... 35% 63.5M 8s\n", + "209100K .......... .......... .......... .......... .......... 35% 69.6M 8s\n", + "209150K .......... .......... .......... .......... .......... 35% 75.8M 8s\n", + "209200K .......... .......... .......... .......... .......... 35% 56.2M 8s\n", + "209250K .......... .......... .......... .......... .......... 35% 56.2M 8s\n", + "209300K .......... .......... .......... .......... .......... 35% 55.6M 8s\n", + "209350K .......... .......... .......... .......... .......... 35% 67.4M 8s\n", + "209400K .......... .......... .......... .......... .......... 35% 62.4M 8s\n", + "209450K .......... .......... .......... .......... .......... 35% 61.2M 8s\n", + "209500K .......... .......... .......... .......... .......... 35% 52.0M 8s\n", + "209550K .......... .......... .......... .......... .......... 35% 62.4M 8s\n", + "209600K .......... .......... .......... .......... .......... 35% 50.6M 8s\n", + "209650K .......... .......... .......... .......... .......... 35% 72.1M 8s\n", + "209700K .......... .......... .......... .......... .......... 35% 77.8M 8s\n", + "209750K .......... .......... .......... .......... .......... 35% 62.7M 8s\n", + "209800K .......... .......... .......... .......... .......... 35% 42.9M 8s\n", + "209850K .......... .......... .......... .......... .......... 35% 49.0M 8s\n", + "209900K .......... .......... .......... .......... .......... 35% 60.7M 8s\n", + "209950K .......... .......... .......... .......... .......... 35% 68.0M 8s\n", + "210000K .......... .......... .......... .......... .......... 35% 66.7M 8s\n", + "210050K .......... .......... .......... .......... .......... 35% 60.7M 8s\n", + "210100K .......... .......... .......... .......... .......... 35% 56.1M 8s\n", + "210150K .......... .......... .......... .......... .......... 35% 45.2M 8s\n", + "210200K .......... .......... .......... .......... .......... 35% 55.4M 8s\n", + "210250K .......... .......... .......... .......... .......... 35% 66.2M 8s\n", + "210300K .......... .......... .......... .......... .......... 35% 71.7M 8s\n", + "210350K .......... .......... .......... .......... .......... 35% 48.6M 8s\n", + "210400K .......... .......... .......... .......... .......... 35% 42.1M 8s\n", + "210450K .......... .......... .......... .......... .......... 35% 65.4M 8s\n", + "210500K .......... .......... .......... .......... .......... 35% 69.2M 8s\n", + "210550K .......... .......... .......... .......... .......... 35% 69.8M 8s\n", + "210600K .......... .......... .......... .......... .......... 35% 48.6M 8s\n", + "210650K .......... .......... .......... .......... .......... 35% 56.3M 8s\n", + "210700K .......... .......... .......... .......... .......... 35% 59.0M 8s\n", + "210750K .......... .......... .......... .......... .......... 35% 72.1M 8s\n", + "210800K .......... .......... .......... .......... .......... 35% 55.9M 8s\n", + "210850K .......... .......... .......... .......... .......... 35% 63.7M 8s\n", + "210900K .......... .......... .......... .......... .......... 35% 50.5M 8s\n", + "210950K .......... .......... .......... .......... .......... 35% 46.6M 8s\n", + "211000K .......... .......... .......... .......... .......... 35% 57.1M 8s\n", + "211050K .......... .......... .......... .......... .......... 35% 77.4M 8s\n", + "211100K .......... .......... .......... .......... .......... 35% 67.1M 8s\n", + "211150K .......... .......... .......... .......... .......... 35% 54.0M 8s\n", + "211200K .......... .......... .......... .......... .......... 35% 43.6M 8s\n", + "211250K .......... .......... .......... .......... .......... 35% 56.5M 8s\n", + "211300K .......... .......... .......... .......... .......... 35% 70.7M 8s\n", + "211350K .......... .......... .......... .......... .......... 35% 71.9M 8s\n", + "211400K .......... .......... .......... .......... .......... 35% 48.6M 8s\n", + "211450K .......... .......... .......... .......... .......... 35% 58.7M 8s\n", + "211500K .......... .......... .......... .......... .......... 35% 56.3M 8s\n", + "211550K .......... .......... .......... .......... .......... 35% 73.3M 8s\n", + "211600K .......... .......... .......... .......... .......... 35% 71.3M 8s\n", + "211650K .......... .......... .......... .......... .......... 35% 74.7M 8s\n", + "211700K .......... .......... .......... .......... .......... 35% 60.1M 8s\n", + "211750K .......... .......... .......... .......... .......... 35% 60.5M 8s\n", + "211800K .......... .......... .......... .......... .......... 35% 47.1M 8s\n", + "211850K .......... .......... .......... .......... .......... 35% 75.7M 8s\n", + "211900K .......... .......... .......... .......... .......... 35% 63.9M 8s\n", + "211950K .......... .......... .......... .......... .......... 35% 72.5M 8s\n", + "212000K .......... .......... .......... .......... .......... 35% 43.3M 8s\n", + "212050K .......... .......... .......... .......... .......... 35% 54.2M 8s\n", + "212100K .......... .......... .......... .......... .......... 35% 54.1M 8s\n", + "212150K .......... .......... .......... .......... .......... 35% 75.6M 8s\n", + "212200K .......... .......... .......... .......... .......... 35% 59.9M 8s\n", + "212250K .......... .......... .......... .......... .......... 35% 59.2M 8s\n", + "212300K .......... .......... .......... .......... .......... 35% 57.1M 8s\n", + "212350K .......... .......... .......... .......... .......... 35% 7.64M 8s\n", + "212400K .......... .......... .......... .......... .......... 35% 56.3M 8s\n", + "212450K .......... .......... .......... .......... .......... 35% 67.8M 8s\n", + "212500K .......... .......... .......... .......... .......... 35% 67.9M 8s\n", + "212550K .......... .......... .......... .......... .......... 35% 71.3M 8s\n", + "212600K .......... .......... .......... .......... .......... 35% 52.6M 8s\n", + "212650K .......... .......... .......... .......... .......... 35% 69.3M 8s\n", + "212700K .......... .......... .......... .......... .......... 35% 4.48M 8s\n", + "212750K .......... .......... .......... .......... .......... 35% 67.9M 8s\n", + "212800K .......... .......... .......... .......... .......... 35% 61.1M 8s\n", + "212850K .......... .......... .......... .......... .......... 35% 65.8M 8s\n", + "212900K .......... .......... .......... .......... .......... 35% 49.7M 8s\n", + "212950K .......... .......... .......... .......... .......... 35% 62.3M 8s\n", + "213000K .......... .......... .......... .......... .......... 35% 42.4M 8s\n", + "213050K .......... .......... .......... .......... .......... 35% 67.0M 8s\n", + "213100K .......... .......... .......... .......... .......... 35% 70.1M 8s\n", + "213150K .......... .......... .......... .......... .......... 35% 56.7M 8s\n", + "213200K .......... .......... .......... .......... .......... 35% 46.9M 8s\n", + "213250K .......... .......... .......... .......... .......... 35% 51.5M 8s\n", + "213300K .......... .......... .......... .......... .......... 35% 59.6M 8s\n", + "213350K .......... .......... .......... .......... .......... 35% 66.4M 8s\n", + "213400K .......... .......... .......... .......... .......... 35% 48.6M 8s\n", + "213450K .......... .......... .......... .......... .......... 35% 48.8M 8s\n", + "213500K .......... .......... .......... .......... .......... 35% 51.4M 8s\n", + "213550K .......... .......... .......... .......... .......... 35% 71.7M 8s\n", + "213600K .......... .......... .......... .......... .......... 35% 34.6M 8s\n", + "213650K .......... .......... .......... .......... .......... 35% 33.7M 8s\n", + "213700K .......... .......... .......... .......... .......... 35% 30.3M 8s\n", + "213750K .......... .......... .......... .......... .......... 35% 42.6M 8s\n", + "213800K .......... .......... .......... .......... .......... 35% 42.6M 8s\n", + "213850K .......... .......... .......... .......... .......... 35% 58.3M 8s\n", + "213900K .......... .......... .......... .......... .......... 35% 58.5M 8s\n", + "213950K .......... .......... .......... .......... .......... 35% 60.9M 8s\n", + "214000K .......... .......... .......... .......... .......... 35% 61.0M 8s\n", + "214050K .......... .......... .......... .......... .......... 35% 64.2M 8s\n", + "214100K .......... .......... .......... .......... .......... 36% 55.7M 8s\n", + "214150K .......... .......... .......... .......... .......... 36% 60.2M 8s\n", + "214200K .......... .......... .......... .......... .......... 36% 45.4M 8s\n", + "214250K .......... .......... .......... .......... .......... 36% 4.03M 8s\n", + "214300K .......... .......... .......... .......... .......... 36% 68.2M 8s\n", + "214350K .......... .......... .......... .......... .......... 36% 69.9M 8s\n", + "214400K .......... .......... .......... .......... .......... 36% 58.2M 8s\n", + "214450K .......... .......... .......... .......... .......... 36% 69.6M 8s\n", + "214500K .......... .......... .......... .......... .......... 36% 71.5M 8s\n", + "214550K .......... .......... .......... .......... .......... 36% 74.1M 8s\n", + "214600K .......... .......... .......... .......... .......... 36% 48.0M 8s\n", + "214650K .......... .......... .......... .......... .......... 36% 67.9M 8s\n", + "214700K .......... .......... .......... .......... .......... 36% 63.5M 8s\n", + "214750K .......... .......... .......... .......... .......... 36% 55.1M 8s\n", + "214800K .......... .......... .......... .......... .......... 36% 60.6M 8s\n", + "214850K .......... .......... .......... .......... .......... 36% 65.4M 8s\n", + "214900K .......... .......... .......... .......... .......... 36% 53.1M 8s\n", + "214950K .......... .......... .......... .......... .......... 36% 68.7M 8s\n", + "215000K .......... .......... .......... .......... .......... 36% 11.3M 8s\n", + "215050K .......... .......... .......... .......... .......... 36% 52.1M 8s\n", + "215100K .......... .......... .......... .......... .......... 36% 62.8M 8s\n", + "215150K .......... .......... .......... .......... .......... 36% 68.2M 8s\n", + "215200K .......... .......... .......... .......... .......... 36% 64.6M 8s\n", + "215250K .......... .......... .......... .......... .......... 36% 63.3M 8s\n", + "215300K .......... .......... .......... .......... .......... 36% 51.9M 8s\n", + "215350K .......... .......... .......... .......... .......... 36% 48.0M 8s\n", + "215400K .......... .......... .......... .......... .......... 36% 56.7M 8s\n", + "215450K .......... .......... .......... .......... .......... 36% 67.4M 8s\n", + "215500K .......... .......... .......... .......... .......... 36% 70.0M 8s\n", + "215550K .......... .......... .......... .......... .......... 36% 69.9M 8s\n", + "215600K .......... .......... .......... .......... .......... 36% 50.4M 8s\n", + "215650K .......... .......... .......... .......... .......... 36% 47.0M 8s\n", + "215700K .......... .......... .......... .......... .......... 36% 50.7M 8s\n", + "215750K .......... .......... .......... .......... .......... 36% 65.8M 8s\n", + "215800K .......... .......... .......... .......... .......... 36% 58.3M 8s\n", + "215850K .......... .......... .......... .......... .......... 36% 45.0M 8s\n", + "215900K .......... .......... .......... .......... .......... 36% 50.2M 8s\n", + "215950K .......... .......... .......... .......... .......... 36% 64.7M 8s\n", + "216000K .......... .......... .......... .......... .......... 36% 59.1M 8s\n", + "216050K .......... .......... .......... .......... .......... 36% 67.6M 8s\n", + "216100K .......... .......... .......... .......... .......... 36% 61.2M 8s\n", + "216150K .......... .......... .......... .......... .......... 36% 46.1M 8s\n", + "216200K .......... .......... .......... .......... .......... 36% 47.5M 8s\n", + "216250K .......... .......... .......... .......... .......... 36% 63.1M 8s\n", + "216300K .......... .......... .......... .......... .......... 36% 74.3M 8s\n", + "216350K .......... .......... .......... .......... .......... 36% 59.4M 8s\n", + "216400K .......... .......... .......... .......... .......... 36% 49.6M 8s\n", + "216450K .......... .......... .......... .......... .......... 36% 51.8M 8s\n", + "216500K .......... .......... .......... .......... .......... 36% 64.0M 8s\n", + "216550K .......... .......... .......... .......... .......... 36% 65.4M 8s\n", + "216600K .......... .......... .......... .......... .......... 36% 59.5M 8s\n", + "216650K .......... .......... .......... .......... .......... 36% 53.3M 8s\n", + "216700K .......... .......... .......... .......... .......... 36% 60.3M 8s\n", + "216750K .......... .......... .......... .......... .......... 36% 55.8M 8s\n", + "216800K .......... .......... .......... .......... .......... 36% 56.4M 8s\n", + "216850K .......... .......... .......... .......... .......... 36% 67.6M 8s\n", + "216900K .......... .......... .......... .......... .......... 36% 48.0M 8s\n", + "216950K .......... .......... .......... .......... .......... 36% 50.4M 8s\n", + "217000K .......... .......... .......... .......... .......... 36% 43.6M 8s\n", + "217050K .......... .......... .......... .......... .......... 36% 69.7M 8s\n", + "217100K .......... .......... .......... .......... .......... 36% 62.3M 8s\n", + "217150K .......... .......... .......... .......... .......... 36% 41.3M 8s\n", + "217200K .......... .......... .......... .......... .......... 36% 40.5M 8s\n", + "217250K .......... .......... .......... .......... .......... 36% 66.3M 8s\n", + "217300K .......... .......... .......... .......... .......... 36% 67.1M 8s\n", + "217350K .......... .......... .......... .......... .......... 36% 61.3M 8s\n", + "217400K .......... .......... .......... .......... .......... 36% 43.6M 8s\n", + "217450K .......... .......... .......... .......... .......... 36% 48.4M 8s\n", + "217500K .......... .......... .......... .......... .......... 36% 67.0M 8s\n", + "217550K .......... .......... .......... .......... .......... 36% 63.5M 8s\n", + "217600K .......... .......... .......... .......... .......... 36% 56.0M 8s\n", + "217650K .......... .......... .......... .......... .......... 36% 45.7M 8s\n", + "217700K .......... .......... .......... .......... .......... 36% 55.1M 8s\n", + "217750K .......... .......... .......... .......... .......... 36% 67.1M 8s\n", + "217800K .......... .......... .......... .......... .......... 36% 55.0M 8s\n", + "217850K .......... .......... .......... .......... .......... 36% 62.9M 8s\n", + "217900K .......... .......... .......... .......... .......... 36% 48.1M 8s\n", + "217950K .......... .......... .......... .......... .......... 36% 48.8M 8s\n", + "218000K .......... .......... .......... .......... .......... 36% 60.0M 8s\n", + "218050K .......... .......... .......... .......... .......... 36% 70.3M 8s\n", + "218100K .......... .......... .......... .......... .......... 36% 68.3M 8s\n", + "218150K .......... .......... .......... .......... .......... 36% 50.3M 8s\n", + "218200K .......... .......... .......... .......... .......... 36% 40.7M 8s\n", + "218250K .......... .......... .......... .......... .......... 36% 64.7M 8s\n", + "218300K .......... .......... .......... .......... .......... 36% 66.2M 8s\n", + "218350K .......... .......... .......... .......... .......... 36% 71.7M 8s\n", + "218400K .......... .......... .......... .......... .......... 36% 52.2M 8s\n", + "218450K .......... .......... .......... .......... .......... 36% 48.2M 8s\n", + "218500K .......... .......... .......... .......... .......... 36% 55.1M 8s\n", + "218550K .......... .......... .......... .......... .......... 36% 61.1M 8s\n", + "218600K .......... .......... .......... .......... .......... 36% 57.3M 8s\n", + "218650K .......... .......... .......... .......... .......... 36% 50.8M 8s\n", + "218700K .......... .......... .......... .......... .......... 36% 46.9M 8s\n", + "218750K .......... .......... .......... .......... .......... 36% 73.7M 8s\n", + "218800K .......... .......... .......... .......... .......... 36% 59.3M 8s\n", + "218850K .......... .......... .......... .......... .......... 36% 67.3M 8s\n", + "218900K .......... .......... .......... .......... .......... 36% 70.2M 8s\n", + "218950K .......... .......... .......... .......... .......... 36% 72.7M 8s\n", + "219000K .......... .......... .......... .......... .......... 36% 59.1M 8s\n", + "219050K .......... .......... .......... .......... .......... 36% 67.0M 8s\n", + "219100K .......... .......... .......... .......... .......... 36% 58.1M 8s\n", + "219150K .......... .......... .......... .......... .......... 36% 51.1M 8s\n", + "219200K .......... .......... .......... .......... .......... 36% 48.7M 8s\n", + "219250K .......... .......... .......... .......... .......... 36% 70.8M 8s\n", + "219300K .......... .......... .......... .......... .......... 36% 68.2M 8s\n", + "219350K .......... .......... .......... .......... .......... 36% 56.0M 8s\n", + "219400K .......... .......... .......... .......... .......... 36% 58.3M 8s\n", + "219450K .......... .......... .......... .......... .......... 36% 67.8M 8s\n", + "219500K .......... .......... .......... .......... .......... 36% 71.1M 8s\n", + "219550K .......... .......... .......... .......... .......... 36% 69.3M 8s\n", + "219600K .......... .......... .......... .......... .......... 36% 60.1M 8s\n", + "219650K .......... .......... .......... .......... .......... 36% 73.5M 8s\n", + "219700K .......... .......... .......... .......... .......... 36% 68.4M 8s\n", + "219750K .......... .......... .......... .......... .......... 36% 65.5M 8s\n", + "219800K .......... .......... .......... .......... .......... 36% 57.9M 8s\n", + "219850K .......... .......... .......... .......... .......... 36% 72.4M 8s\n", + "219900K .......... .......... .......... .......... .......... 36% 63.0M 8s\n", + "219950K .......... .......... .......... .......... .......... 36% 65.5M 8s\n", + "220000K .......... .......... .......... .......... .......... 36% 53.8M 8s\n", + "220050K .......... .......... .......... .......... .......... 37% 71.8M 8s\n", + "220100K .......... .......... .......... .......... .......... 37% 63.3M 8s\n", + "220150K .......... .......... .......... .......... .......... 37% 69.1M 8s\n", + "220200K .......... .......... .......... .......... .......... 37% 60.5M 8s\n", + "220250K .......... .......... .......... .......... .......... 37% 69.6M 8s\n", + "220300K .......... .......... .......... .......... .......... 37% 67.4M 8s\n", + "220350K .......... .......... .......... .......... .......... 37% 68.5M 8s\n", + "220400K .......... .......... .......... .......... .......... 37% 60.5M 8s\n", + "220450K .......... .......... .......... .......... .......... 37% 44.7M 8s\n", + "220500K .......... .......... .......... .......... .......... 37% 72.5M 8s\n", + "220550K .......... .......... .......... .......... .......... 37% 64.7M 8s\n", + "220600K .......... .......... .......... .......... .......... 37% 60.6M 8s\n", + "220650K .......... .......... .......... .......... .......... 37% 1.22M 8s\n", + "220700K .......... .......... .......... .......... .......... 37% 33.3M 8s\n", + "220750K .......... .......... .......... .......... .......... 37% 30.4M 8s\n", + "220800K .......... .......... .......... .......... .......... 37% 27.1M 8s\n", + "220850K .......... .......... .......... .......... .......... 37% 63.2M 8s\n", + "220900K .......... .......... .......... .......... .......... 37% 64.9M 8s\n", + "220950K .......... .......... .......... .......... .......... 37% 46.0M 8s\n", + "221000K .......... .......... .......... .......... .......... 37% 27.0M 8s\n", + "221050K .......... .......... .......... .......... .......... 37% 29.2M 8s\n", + "221100K .......... .......... .......... .......... .......... 37% 31.6M 8s\n", + "221150K .......... .......... .......... .......... .......... 37% 35.3M 8s\n", + "221200K .......... .......... .......... .......... .......... 37% 28.8M 8s\n", + "221250K .......... .......... .......... .......... .......... 37% 34.8M 8s\n", + "221300K .......... .......... .......... .......... .......... 37% 35.0M 8s\n", + "221350K .......... .......... .......... .......... .......... 37% 31.0M 8s\n", + "221400K .......... .......... .......... .......... .......... 37% 25.6M 8s\n", + "221450K .......... .......... .......... .......... .......... 37% 69.9M 8s\n", + "221500K .......... .......... .......... .......... .......... 37% 72.0M 8s\n", + "221550K .......... .......... .......... .......... .......... 37% 65.1M 8s\n", + "221600K .......... .......... .......... .......... .......... 37% 59.4M 8s\n", + "221650K .......... .......... .......... .......... .......... 37% 54.5M 8s\n", + "221700K .......... .......... .......... .......... .......... 37% 31.6M 8s\n", + "221750K .......... .......... .......... .......... .......... 37% 37.9M 8s\n", + "221800K .......... .......... .......... .......... .......... 37% 60.8M 8s\n", + "221850K .......... .......... .......... .......... .......... 37% 76.0M 8s\n", + "221900K .......... .......... .......... .......... .......... 37% 72.6M 8s\n", + "221950K .......... .......... .......... .......... .......... 37% 59.3M 8s\n", + "222000K .......... .......... .......... .......... .......... 37% 43.1M 8s\n", + "222050K .......... .......... .......... .......... .......... 37% 30.6M 8s\n", + "222100K .......... .......... .......... .......... .......... 37% 42.8M 8s\n", + "222150K .......... .......... .......... .......... .......... 37% 72.0M 8s\n", + "222200K .......... .......... .......... .......... .......... 37% 41.0M 8s\n", + "222250K .......... .......... .......... .......... .......... 37% 62.4M 8s\n", + "222300K .......... .......... .......... .......... .......... 37% 44.2M 8s\n", + "222350K .......... .......... .......... .......... .......... 37% 33.7M 8s\n", + "222400K .......... .......... .......... .......... .......... 37% 30.9M 8s\n", + "222450K .......... .......... .......... .......... .......... 37% 50.0M 8s\n", + "222500K .......... .......... .......... .......... .......... 37% 35.2M 8s\n", + "222550K .......... .......... .......... .......... .......... 37% 41.7M 8s\n", + "222600K .......... .......... .......... .......... .......... 37% 41.0M 8s\n", + "222650K .......... .......... .......... .......... .......... 37% 37.0M 8s\n", + "222700K .......... .......... .......... .......... .......... 37% 36.5M 8s\n", + "222750K .......... .......... .......... .......... .......... 37% 45.6M 8s\n", + "222800K .......... .......... .......... .......... .......... 37% 40.0M 8s\n", + "222850K .......... .......... .......... .......... .......... 37% 46.4M 8s\n", + "222900K .......... .......... .......... .......... .......... 37% 55.3M 8s\n", + "222950K .......... .......... .......... .......... .......... 37% 44.7M 8s\n", + "223000K .......... .......... .......... .......... .......... 37% 52.1M 8s\n", + "223050K .......... .......... .......... .......... .......... 37% 45.3M 8s\n", + "223100K .......... .......... .......... .......... .......... 37% 46.6M 8s\n", + "223150K .......... .......... .......... .......... .......... 37% 40.6M 8s\n", + "223200K .......... .......... .......... .......... .......... 37% 47.1M 8s\n", + "223250K .......... .......... .......... .......... .......... 37% 46.8M 8s\n", + "223300K .......... .......... .......... .......... .......... 37% 56.7M 8s\n", + "223350K .......... .......... .......... .......... .......... 37% 4.49M 8s\n", + "223400K .......... .......... .......... .......... .......... 37% 42.7M 8s\n", + "223450K .......... .......... .......... .......... .......... 37% 55.7M 8s\n", + "223500K .......... .......... .......... .......... .......... 37% 47.3M 8s\n", + "223550K .......... .......... .......... .......... .......... 37% 48.6M 8s\n", + "223600K .......... .......... .......... .......... .......... 37% 50.6M 8s\n", + "223650K .......... .......... .......... .......... .......... 37% 63.7M 8s\n", + "223700K .......... .......... .......... .......... .......... 37% 68.0M 8s\n", + "223750K .......... .......... .......... .......... .......... 37% 70.7M 8s\n", + "223800K .......... .......... .......... .......... .......... 37% 59.3M 8s\n", + "223850K .......... .......... .......... .......... .......... 37% 59.1M 8s\n", + "223900K .......... .......... .......... .......... .......... 37% 57.3M 8s\n", + "223950K .......... .......... .......... .......... .......... 37% 40.1M 8s\n", + "224000K .......... .......... .......... .......... .......... 37% 55.3M 8s\n", + "224050K .......... .......... .......... .......... .......... 37% 38.6M 8s\n", + "224100K .......... .......... .......... .......... .......... 37% 27.3M 8s\n", + "224150K .......... .......... .......... .......... .......... 37% 39.8M 8s\n", + "224200K .......... .......... .......... .......... .......... 37% 50.0M 8s\n", + "224250K .......... .......... .......... .......... .......... 37% 53.8M 8s\n", + "224300K .......... .......... .......... .......... .......... 37% 53.5M 8s\n", + "224350K .......... .......... .......... .......... .......... 37% 55.0M 8s\n", + "224400K .......... .......... .......... .......... .......... 37% 59.4M 8s\n", + "224450K .......... .......... .......... .......... .......... 37% 68.7M 8s\n", + "224500K .......... .......... .......... .......... .......... 37% 64.8M 8s\n", + "224550K .......... .......... .......... .......... .......... 37% 47.6M 8s\n", + "224600K .......... .......... .......... .......... .......... 37% 41.9M 8s\n", + "224650K .......... .......... .......... .......... .......... 37% 65.7M 8s\n", + "224700K .......... .......... .......... .......... .......... 37% 64.4M 8s\n", + "224750K .......... .......... .......... .......... .......... 37% 6.80M 8s\n", + "224800K .......... .......... .......... .......... .......... 37% 47.2M 8s\n", + "224850K .......... .......... .......... .......... .......... 37% 65.6M 8s\n", + "224900K .......... .......... .......... .......... .......... 37% 62.6M 8s\n", + "224950K .......... .......... .......... .......... .......... 37% 69.2M 8s\n", + "225000K .......... .......... .......... .......... .......... 37% 56.0M 8s\n", + "225050K .......... .......... .......... .......... .......... 37% 54.5M 8s\n", + "225100K .......... .......... .......... .......... .......... 37% 64.3M 8s\n", + "225150K .......... .......... .......... .......... .......... 37% 56.5M 8s\n", + "225200K .......... .......... .......... .......... .......... 37% 63.2M 8s\n", + "225250K .......... .......... .......... .......... .......... 37% 61.1M 8s\n", + "225300K .......... .......... .......... .......... .......... 37% 49.4M 8s\n", + "225350K .......... .......... .......... .......... .......... 37% 46.6M 8s\n", + "225400K .......... .......... .......... .......... .......... 37% 46.2M 8s\n", + "225450K .......... .......... .......... .......... .......... 37% 68.8M 8s\n", + "225500K .......... .......... .......... .......... .......... 37% 68.0M 8s\n", + "225550K .......... .......... .......... .......... .......... 37% 38.4M 8s\n", + "225600K .......... .......... .......... .......... .......... 37% 34.3M 8s\n", + "225650K .......... .......... .......... .......... .......... 37% 70.7M 8s\n", + "225700K .......... .......... .......... .......... .......... 37% 66.9M 8s\n", + "225750K .......... .......... .......... .......... .......... 37% 73.1M 8s\n", + "225800K .......... .......... .......... .......... .......... 37% 39.8M 8s\n", + "225850K .......... .......... .......... .......... .......... 37% 60.5M 8s\n", + "225900K .......... .......... .......... .......... .......... 37% 60.1M 8s\n", + "225950K .......... .......... .......... .......... .......... 38% 71.4M 8s\n", + "226000K .......... .......... .......... .......... .......... 38% 61.8M 8s\n", + "226050K .......... .......... .......... .......... .......... 38% 52.3M 8s\n", + "226100K .......... .......... .......... .......... .......... 38% 54.2M 8s\n", + "226150K .......... .......... .......... .......... .......... 38% 50.3M 8s\n", + "226200K .......... .......... .......... .......... .......... 38% 57.5M 8s\n", + "226250K .......... .......... .......... .......... .......... 38% 69.8M 8s\n", + "226300K .......... .......... .......... .......... .......... 38% 48.4M 8s\n", + "226350K .......... .......... .......... .......... .......... 38% 46.8M 8s\n", + "226400K .......... .......... .......... .......... .......... 38% 50.2M 8s\n", + "226450K .......... .......... .......... .......... .......... 38% 69.8M 8s\n", + "226500K .......... .......... .......... .......... .......... 38% 67.7M 8s\n", + "226550K .......... .......... .......... .......... .......... 38% 45.4M 8s\n", + "226600K .......... .......... .......... .......... .......... 38% 38.0M 8s\n", + "226650K .......... .......... .......... .......... .......... 38% 58.9M 8s\n", + "226700K .......... .......... .......... .......... .......... 38% 67.4M 8s\n", + "226750K .......... .......... .......... .......... .......... 38% 72.1M 8s\n", + "226800K .......... .......... .......... .......... .......... 38% 46.8M 8s\n", + "226850K .......... .......... .......... .......... .......... 38% 52.0M 8s\n", + "226900K .......... .......... .......... .......... .......... 38% 58.1M 8s\n", + "226950K .......... .......... .......... .......... .......... 38% 70.6M 8s\n", + "227000K .......... .......... .......... .......... .......... 38% 61.8M 8s\n", + "227050K .......... .......... .......... .......... .......... 38% 57.9M 8s\n", + "227100K .......... .......... .......... .......... .......... 38% 61.5M 8s\n", + "227150K .......... .......... .......... .......... .......... 38% 67.1M 8s\n", + "227200K .......... .......... .......... .......... .......... 38% 61.6M 8s\n", + "227250K .......... .......... .......... .......... .......... 38% 54.4M 8s\n", + "227300K .......... .......... .......... .......... .......... 38% 58.2M 8s\n", + "227350K .......... .......... .......... .......... .......... 38% 37.7M 8s\n", + "227400K .......... .......... .......... .......... .......... 38% 39.2M 8s\n", + "227450K .......... .......... .......... .......... .......... 38% 67.0M 8s\n", + "227500K .......... .......... .......... .......... .......... 38% 68.8M 8s\n", + "227550K .......... .......... .......... .......... .......... 38% 44.2M 8s\n", + "227600K .......... .......... .......... .......... .......... 38% 44.8M 8s\n", + "227650K .......... .......... .......... .......... .......... 38% 68.0M 8s\n", + "227700K .......... .......... .......... .......... .......... 38% 52.7M 8s\n", + "227750K .......... .......... .......... .......... .......... 38% 46.9M 8s\n", + "227800K .......... .......... .......... .......... .......... 38% 36.4M 8s\n", + "227850K .......... .......... .......... .......... .......... 38% 55.5M 8s\n", + "227900K .......... .......... .......... .......... .......... 38% 71.3M 8s\n", + "227950K .......... .......... .......... .......... .......... 38% 71.1M 8s\n", + "228000K .......... .......... .......... .......... .......... 38% 61.6M 8s\n", + "228050K .......... .......... .......... .......... .......... 38% 47.3M 8s\n", + "228100K .......... .......... .......... .......... .......... 38% 47.7M 8s\n", + "228150K .......... .......... .......... .......... .......... 38% 63.6M 8s\n", + "228200K .......... .......... .......... .......... .......... 38% 61.6M 8s\n", + "228250K .......... .......... .......... .......... .......... 38% 74.2M 7s\n", + "228300K .......... .......... .......... .......... .......... 38% 41.8M 7s\n", + "228350K .......... .......... .......... .......... .......... 38% 50.8M 7s\n", + "228400K .......... .......... .......... .......... .......... 38% 49.6M 7s\n", + "228450K .......... .......... .......... .......... .......... 38% 69.3M 7s\n", + "228500K .......... .......... .......... .......... .......... 38% 57.5M 7s\n", + "228550K .......... .......... .......... .......... .......... 38% 59.9M 7s\n", + "228600K .......... .......... .......... .......... .......... 38% 42.7M 7s\n", + "228650K .......... .......... .......... .......... .......... 38% 66.3M 7s\n", + "228700K .......... .......... .......... .......... .......... 38% 71.1M 7s\n", + "228750K .......... .......... .......... .......... .......... 38% 70.8M 7s\n", + "228800K .......... .......... .......... .......... .......... 38% 67.7M 7s\n", + "228850K .......... .......... .......... .......... .......... 38% 39.0M 7s\n", + "228900K .......... .......... .......... .......... .......... 38% 47.3M 7s\n", + "228950K .......... .......... .......... .......... .......... 38% 45.5M 7s\n", + "229000K .......... .......... .......... .......... .......... 38% 44.3M 7s\n", + "229050K .......... .......... .......... .......... .......... 38% 56.4M 7s\n", + "229100K .......... .......... .......... .......... .......... 38% 41.8M 7s\n", + "229150K .......... .......... .......... .......... .......... 38% 49.9M 7s\n", + "229200K .......... .......... .......... .......... .......... 38% 46.9M 7s\n", + "229250K .......... .......... .......... .......... .......... 38% 65.0M 7s\n", + "229300K .......... .......... .......... .......... .......... 38% 41.7M 7s\n", + "229350K .......... .......... .......... .......... .......... 38% 37.9M 7s\n", + "229400K .......... .......... .......... .......... .......... 38% 41.2M 7s\n", + "229450K .......... .......... .......... .......... .......... 38% 65.0M 7s\n", + "229500K .......... .......... .......... .......... .......... 38% 63.1M 7s\n", + "229550K .......... .......... .......... .......... .......... 38% 49.3M 7s\n", + "229600K .......... .......... .......... .......... .......... 38% 46.7M 7s\n", + "229650K .......... .......... .......... .......... .......... 38% 65.3M 7s\n", + "229700K .......... .......... .......... .......... .......... 38% 68.9M 7s\n", + "229750K .......... .......... .......... .......... .......... 38% 67.3M 7s\n", + "229800K .......... .......... .......... .......... .......... 38% 37.7M 7s\n", + "229850K .......... .......... .......... .......... .......... 38% 58.2M 7s\n", + "229900K .......... .......... .......... .......... .......... 38% 70.6M 7s\n", + "229950K .......... .......... .......... .......... .......... 38% 67.9M 7s\n", + "230000K .......... .......... .......... .......... .......... 38% 63.2M 7s\n", + "230050K .......... .......... .......... .......... .......... 38% 57.9M 7s\n", + "230100K .......... .......... .......... .......... .......... 38% 48.8M 7s\n", + "230150K .......... .......... .......... .......... .......... 38% 66.7M 7s\n", + "230200K .......... .......... .......... .......... .......... 38% 55.7M 7s\n", + "230250K .......... .......... .......... .......... .......... 38% 75.1M 7s\n", + "230300K .......... .......... .......... .......... .......... 38% 72.2M 7s\n", + "230350K .......... .......... .......... .......... .......... 38% 67.8M 7s\n", + "230400K .......... .......... .......... .......... .......... 38% 47.3M 7s\n", + "230450K .......... .......... .......... .......... .......... 38% 47.9M 7s\n", + "230500K .......... .......... .......... .......... .......... 38% 61.4M 7s\n", + "230550K .......... .......... .......... .......... .......... 38% 71.5M 7s\n", + "230600K .......... .......... .......... .......... .......... 38% 51.1M 7s\n", + "230650K .......... .......... .......... .......... .......... 38% 46.6M 7s\n", + "230700K .......... .......... .......... .......... .......... 38% 50.4M 7s\n", + "230750K .......... .......... .......... .......... .......... 38% 61.7M 7s\n", + "230800K .......... .......... .......... .......... .......... 38% 56.7M 7s\n", + "230850K .......... .......... .......... .......... .......... 38% 61.7M 7s\n", + "230900K .......... .......... .......... .......... .......... 38% 4.30M 7s\n", + "230950K .......... .......... .......... .......... .......... 38% 61.8M 7s\n", + "231000K .......... .......... .......... .......... .......... 38% 56.1M 7s\n", + "231050K .......... .......... .......... .......... .......... 38% 67.4M 7s\n", + "231100K .......... .......... .......... .......... .......... 38% 64.8M 7s\n", + "231150K .......... .......... .......... .......... .......... 38% 67.8M 7s\n", + "231200K .......... .......... .......... .......... .......... 38% 46.2M 7s\n", + "231250K .......... .......... .......... .......... .......... 38% 41.8M 7s\n", + "231300K .......... .......... .......... .......... .......... 38% 17.6M 7s\n", + "231350K .......... .......... .......... .......... .......... 38% 54.0M 7s\n", + "231400K .......... .......... .......... .......... .......... 38% 43.5M 7s\n", + "231450K .......... .......... .......... .......... .......... 38% 63.9M 7s\n", + "231500K .......... .......... .......... .......... .......... 38% 3.93M 7s\n", + "231550K .......... .......... .......... .......... .......... 38% 69.4M 7s\n", + "231600K .......... .......... .......... .......... .......... 38% 58.3M 7s\n", + "231650K .......... .......... .......... .......... .......... 38% 61.8M 7s\n", + "231700K .......... .......... .......... .......... .......... 38% 72.4M 7s\n", + "231750K .......... .......... .......... .......... .......... 38% 65.0M 7s\n", + "231800K .......... .......... .......... .......... .......... 38% 45.6M 7s\n", + "231850K .......... .......... .......... .......... .......... 38% 68.1M 7s\n", + "231900K .......... .......... .......... .......... .......... 39% 64.5M 7s\n", + "231950K .......... .......... .......... .......... .......... 39% 39.5M 7s\n", + "232000K .......... .......... .......... .......... .......... 39% 44.6M 7s\n", + "232050K .......... .......... .......... .......... .......... 39% 36.2M 7s\n", + "232100K .......... .......... .......... .......... .......... 39% 43.6M 7s\n", + "232150K .......... .......... .......... .......... .......... 39% 41.9M 7s\n", + "232200K .......... .......... .......... .......... .......... 39% 35.5M 7s\n", + "232250K .......... .......... .......... .......... .......... 39% 50.5M 7s\n", + "232300K .......... .......... .......... .......... .......... 39% 52.9M 7s\n", + "232350K .......... .......... .......... .......... .......... 39% 56.1M 7s\n", + "232400K .......... .......... .......... .......... .......... 39% 51.7M 7s\n", + "232450K .......... .......... .......... .......... .......... 39% 49.1M 7s\n", + "232500K .......... .......... .......... .......... .......... 39% 47.3M 7s\n", + "232550K .......... .......... .......... .......... .......... 39% 53.7M 7s\n", + "232600K .......... .......... .......... .......... .......... 39% 34.9M 7s\n", + "232650K .......... .......... .......... .......... .......... 39% 59.5M 7s\n", + "232700K .......... .......... .......... .......... .......... 39% 59.5M 7s\n", + "232750K .......... .......... .......... .......... .......... 39% 63.3M 7s\n", + "232800K .......... .......... .......... .......... .......... 39% 57.3M 7s\n", + "232850K .......... .......... .......... .......... .......... 39% 50.2M 7s\n", + "232900K .......... .......... .......... .......... .......... 39% 36.7M 7s\n", + "232950K .......... .......... .......... .......... .......... 39% 43.7M 7s\n", + "233000K .......... .......... .......... .......... .......... 39% 30.0M 7s\n", + "233050K .......... .......... .......... .......... .......... 39% 32.1M 7s\n", + "233100K .......... .......... .......... .......... .......... 39% 35.4M 7s\n", + "233150K .......... .......... .......... .......... .......... 39% 39.6M 7s\n", + "233200K .......... .......... .......... .......... .......... 39% 29.7M 7s\n", + "233250K .......... .......... .......... .......... .......... 39% 32.1M 7s\n", + "233300K .......... .......... .......... .......... .......... 39% 52.2M 7s\n", + "233350K .......... .......... .......... .......... .......... 39% 69.0M 7s\n", + "233400K .......... .......... .......... .......... .......... 39% 47.0M 7s\n", + "233450K .......... .......... .......... .......... .......... 39% 53.1M 7s\n", + "233500K .......... .......... .......... .......... .......... 39% 68.8M 7s\n", + "233550K .......... .......... .......... .......... .......... 39% 64.8M 7s\n", + "233600K .......... .......... .......... .......... .......... 39% 52.8M 7s\n", + "233650K .......... .......... .......... .......... .......... 39% 63.3M 7s\n", + "233700K .......... .......... .......... .......... .......... 39% 56.1M 7s\n", + "233750K .......... .......... .......... .......... .......... 39% 71.7M 7s\n", + "233800K .......... .......... .......... .......... .......... 39% 47.5M 7s\n", + "233850K .......... .......... .......... .......... .......... 39% 52.8M 7s\n", + "233900K .......... .......... .......... .......... .......... 39% 52.2M 7s\n", + "233950K .......... .......... .......... .......... .......... 39% 64.4M 7s\n", + "234000K .......... .......... .......... .......... .......... 39% 61.0M 7s\n", + "234050K .......... .......... .......... .......... .......... 39% 53.3M 7s\n", + "234100K .......... .......... .......... .......... .......... 39% 51.9M 7s\n", + "234150K .......... .......... .......... .......... .......... 39% 51.0M 7s\n", + "234200K .......... .......... .......... .......... .......... 39% 48.6M 7s\n", + "234250K .......... .......... .......... .......... .......... 39% 65.3M 7s\n", + "234300K .......... .......... .......... .......... .......... 39% 55.9M 7s\n", + "234350K .......... .......... .......... .......... .......... 39% 49.9M 7s\n", + "234400K .......... .......... .......... .......... .......... 39% 46.9M 7s\n", + "234450K .......... .......... .......... .......... .......... 39% 65.6M 7s\n", + "234500K .......... .......... .......... .......... .......... 39% 71.6M 7s\n", + "234550K .......... .......... .......... .......... .......... 39% 60.1M 7s\n", + "234600K .......... .......... .......... .......... .......... 39% 40.5M 7s\n", + "234650K .......... .......... .......... .......... .......... 39% 55.1M 7s\n", + "234700K .......... .......... .......... .......... .......... 39% 67.5M 7s\n", + "234750K .......... .......... .......... .......... .......... 39% 59.7M 7s\n", + "234800K .......... .......... .......... .......... .......... 39% 41.1M 7s\n", + "234850K .......... .......... .......... .......... .......... 39% 35.9M 7s\n", + "234900K .......... .......... .......... .......... .......... 39% 41.8M 7s\n", + "234950K .......... .......... .......... .......... .......... 39% 39.7M 7s\n", + "235000K .......... .......... .......... .......... .......... 39% 34.2M 7s\n", + "235050K .......... .......... .......... .......... .......... 39% 35.9M 7s\n", + "235100K .......... .......... .......... .......... .......... 39% 40.6M 7s\n", + "235150K .......... .......... .......... .......... .......... 39% 35.4M 7s\n", + "235200K .......... .......... .......... .......... .......... 39% 26.4M 7s\n", + "235250K .......... .......... .......... .......... .......... 39% 42.1M 7s\n", + "235300K .......... .......... .......... .......... .......... 39% 34.4M 7s\n", + "235350K .......... .......... .......... .......... .......... 39% 27.2M 7s\n", + "235400K .......... .......... .......... .......... .......... 39% 34.2M 7s\n", + "235450K .......... .......... .......... .......... .......... 39% 46.5M 7s\n", + "235500K .......... .......... .......... .......... .......... 39% 39.5M 7s\n", + "235550K .......... .......... .......... .......... .......... 39% 42.0M 7s\n", + "235600K .......... .......... .......... .......... .......... 39% 49.3M 7s\n", + "235650K .......... .......... .......... .......... .......... 39% 37.4M 7s\n", + "235700K .......... .......... .......... .......... .......... 39% 42.0M 7s\n", + "235750K .......... .......... .......... .......... .......... 39% 39.5M 7s\n", + "235800K .......... .......... .......... .......... .......... 39% 43.7M 7s\n", + "235850K .......... .......... .......... .......... .......... 39% 40.7M 7s\n", + "235900K .......... .......... .......... .......... .......... 39% 49.6M 7s\n", + "235950K .......... .......... .......... .......... .......... 39% 50.6M 7s\n", + "236000K .......... .......... .......... .......... .......... 39% 52.1M 7s\n", + "236050K .......... .......... .......... .......... .......... 39% 55.2M 7s\n", + "236100K .......... .......... .......... .......... .......... 39% 3.53M 7s\n", + "236150K .......... .......... .......... .......... .......... 39% 47.4M 7s\n", + "236200K .......... .......... .......... .......... .......... 39% 37.9M 7s\n", + "236250K .......... .......... .......... .......... .......... 39% 46.5M 7s\n", + "236300K .......... .......... .......... .......... .......... 39% 46.2M 7s\n", + "236350K .......... .......... .......... .......... .......... 39% 43.5M 7s\n", + "236400K .......... .......... .......... .......... .......... 39% 48.6M 7s\n", + "236450K .......... .......... .......... .......... .......... 39% 51.5M 7s\n", + "236500K .......... .......... .......... .......... .......... 39% 47.1M 7s\n", + "236550K .......... .......... .......... .......... .......... 39% 47.6M 7s\n", + "236600K .......... .......... .......... .......... .......... 39% 34.5M 7s\n", + "236650K .......... .......... .......... .......... .......... 39% 43.6M 7s\n", + "236700K .......... .......... .......... .......... .......... 39% 39.9M 7s\n", + "236750K .......... .......... .......... .......... .......... 39% 41.5M 7s\n", + "236800K .......... .......... .......... .......... .......... 39% 39.3M 7s\n", + "236850K .......... .......... .......... .......... .......... 39% 42.8M 7s\n", + "236900K .......... .......... .......... .......... .......... 39% 42.8M 7s\n", + "236950K .......... .......... .......... .......... .......... 39% 46.2M 7s\n", + "237000K .......... .......... .......... .......... .......... 39% 37.6M 7s\n", + "237050K .......... .......... .......... .......... .......... 39% 40.1M 7s\n", + "237100K .......... .......... .......... .......... .......... 39% 47.5M 7s\n", + "237150K .......... .......... .......... .......... .......... 39% 44.3M 7s\n", + "237200K .......... .......... .......... .......... .......... 39% 47.6M 7s\n", + "237250K .......... .......... .......... .......... .......... 39% 53.8M 7s\n", + "237300K .......... .......... .......... .......... .......... 39% 36.3M 7s\n", + "237350K .......... .......... .......... .......... .......... 39% 42.8M 7s\n", + "237400K .......... .......... .......... .......... .......... 39% 41.2M 7s\n", + "237450K .......... .......... .......... .......... .......... 39% 47.2M 7s\n", + "237500K .......... .......... .......... .......... .......... 39% 42.2M 7s\n", + "237550K .......... .......... .......... .......... .......... 39% 31.8M 7s\n", + "237600K .......... .......... .......... .......... .......... 39% 57.4M 7s\n", + "237650K .......... .......... .......... .......... .......... 39% 78.6M 7s\n", + "237700K .......... .......... .......... .......... .......... 39% 73.1M 7s\n", + "237750K .......... .......... .......... .......... .......... 39% 61.5M 7s\n", + "237800K .......... .......... .......... .......... .......... 39% 47.8M 7s\n", + "237850K .......... .......... .......... .......... .......... 40% 57.1M 7s\n", + "237900K .......... .......... .......... .......... .......... 40% 76.8M 7s\n", + "237950K .......... .......... .......... .......... .......... 40% 75.3M 7s\n", + "238000K .......... .......... .......... .......... .......... 40% 66.1M 7s\n", + "238050K .......... .......... .......... .......... .......... 40% 59.2M 7s\n", + "238100K .......... .......... .......... .......... .......... 40% 40.8M 7s\n", + "238150K .......... .......... .......... .......... .......... 40% 63.3M 7s\n", + "238200K .......... .......... .......... .......... .......... 40% 55.8M 7s\n", + "238250K .......... .......... .......... .......... .......... 40% 56.0M 7s\n", + "238300K .......... .......... .......... .......... .......... 40% 46.5M 7s\n", + "238350K .......... .......... .......... .......... .......... 40% 43.8M 7s\n", + "238400K .......... .......... .......... .......... .......... 40% 62.8M 7s\n", + "238450K .......... .......... .......... .......... .......... 40% 69.0M 7s\n", + "238500K .......... .......... .......... .......... .......... 40% 70.5M 7s\n", + "238550K .......... .......... .......... .......... .......... 40% 42.4M 7s\n", + "238600K .......... .......... .......... .......... .......... 40% 35.4M 7s\n", + "238650K .......... .......... .......... .......... .......... 40% 60.4M 7s\n", + "238700K .......... .......... .......... .......... .......... 40% 66.2M 7s\n", + "238750K .......... .......... .......... .......... .......... 40% 41.5M 7s\n", + "238800K .......... .......... .......... .......... .......... 40% 35.4M 7s\n", + "238850K .......... .......... .......... .......... .......... 40% 62.9M 7s\n", + "238900K .......... .......... .......... .......... .......... 40% 67.8M 7s\n", + "238950K .......... .......... .......... .......... .......... 40% 66.9M 7s\n", + "239000K .......... .......... .......... .......... .......... 40% 35.9M 7s\n", + "239050K .......... .......... .......... .......... .......... 40% 50.3M 7s\n", + "239100K .......... .......... .......... .......... .......... 40% 69.7M 7s\n", + "239150K .......... .......... .......... .......... .......... 40% 69.7M 7s\n", + "239200K .......... .......... .......... .......... .......... 40% 61.7M 7s\n", + "239250K .......... .......... .......... .......... .......... 40% 62.2M 7s\n", + "239300K .......... .......... .......... .......... .......... 40% 66.4M 7s\n", + "239350K .......... .......... .......... .......... .......... 40% 50.2M 7s\n", + "239400K .......... .......... .......... .......... .......... 40% 57.1M 7s\n", + "239450K .......... .......... .......... .......... .......... 40% 66.7M 7s\n", + "239500K .......... .......... .......... .......... .......... 40% 71.0M 7s\n", + "239550K .......... .......... .......... .......... .......... 40% 60.8M 7s\n", + "239600K .......... .......... .......... .......... .......... 40% 43.3M 7s\n", + "239650K .......... .......... .......... .......... .......... 40% 76.4M 7s\n", + "239700K .......... .......... .......... .......... .......... 40% 70.4M 7s\n", + "239750K .......... .......... .......... .......... .......... 40% 64.5M 7s\n", + "239800K .......... .......... .......... .......... .......... 40% 3.83M 7s\n", + "239850K .......... .......... .......... .......... .......... 40% 66.6M 7s\n", + "239900K .......... .......... .......... .......... .......... 40% 66.0M 7s\n", + "239950K .......... .......... .......... .......... .......... 40% 66.0M 7s\n", + "240000K .......... .......... .......... .......... .......... 40% 13.3M 7s\n", + "240050K .......... .......... .......... .......... .......... 40% 65.4M 7s\n", + "240100K .......... .......... .......... .......... .......... 40% 62.7M 7s\n", + "240150K .......... .......... .......... .......... .......... 40% 66.7M 7s\n", + "240200K .......... .......... .......... .......... .......... 40% 48.1M 7s\n", + "240250K .......... .......... .......... .......... .......... 40% 62.5M 7s\n", + "240300K .......... .......... .......... .......... .......... 40% 55.2M 7s\n", + "240350K .......... .......... .......... .......... .......... 40% 66.5M 7s\n", + "240400K .......... .......... .......... .......... .......... 40% 57.6M 7s\n", + "240450K .......... .......... .......... .......... .......... 40% 66.4M 7s\n", + "240500K .......... .......... .......... .......... .......... 40% 49.0M 7s\n", + "240550K .......... .......... .......... .......... .......... 40% 44.8M 7s\n", + "240600K .......... .......... .......... .......... .......... 40% 51.2M 7s\n", + "240650K .......... .......... .......... .......... .......... 40% 69.3M 7s\n", + "240700K .......... .......... .......... .......... .......... 40% 10.8M 7s\n", + "240750K .......... .......... .......... .......... .......... 40% 60.0M 7s\n", + "240800K .......... .......... .......... .......... .......... 40% 50.1M 7s\n", + "240850K .......... .......... .......... .......... .......... 40% 15.8M 7s\n", + "240900K .......... .......... .......... .......... .......... 40% 63.9M 7s\n", + "240950K .......... .......... .......... .......... .......... 40% 52.1M 7s\n", + "241000K .......... .......... .......... .......... .......... 40% 41.2M 7s\n", + "241050K .......... .......... .......... .......... .......... 40% 63.9M 7s\n", + "241100K .......... .......... .......... .......... .......... 40% 69.7M 7s\n", + "241150K .......... .......... .......... .......... .......... 40% 12.1M 7s\n", + "241200K .......... .......... .......... .......... .......... 40% 58.7M 7s\n", + "241250K .......... .......... .......... .......... .......... 40% 66.0M 7s\n", + "241300K .......... .......... .......... .......... .......... 40% 38.5M 7s\n", + "241350K .......... .......... .......... .......... .......... 40% 57.0M 7s\n", + "241400K .......... .......... .......... .......... .......... 40% 5.87M 7s\n", + "241450K .......... .......... .......... .......... .......... 40% 61.1M 7s\n", + "241500K .......... .......... .......... .......... .......... 40% 70.9M 7s\n", + "241550K .......... .......... .......... .......... .......... 40% 73.5M 7s\n", + "241600K .......... .......... .......... .......... .......... 40% 60.6M 7s\n", + "241650K .......... .......... .......... .......... .......... 40% 64.8M 7s\n", + "241700K .......... .......... .......... .......... .......... 40% 44.9M 7s\n", + "241750K .......... .......... .......... .......... .......... 40% 67.1M 7s\n", + "241800K .......... .......... .......... .......... .......... 40% 61.0M 7s\n", + "241850K .......... .......... .......... .......... .......... 40% 74.4M 7s\n", + "241900K .......... .......... .......... .......... .......... 40% 72.6M 7s\n", + "241950K .......... .......... .......... .......... .......... 40% 45.9M 7s\n", + "242000K .......... .......... .......... .......... .......... 40% 43.7M 7s\n", + "242050K .......... .......... .......... .......... .......... 40% 72.2M 7s\n", + "242100K .......... .......... .......... .......... .......... 40% 70.8M 7s\n", + "242150K .......... .......... .......... .......... .......... 40% 67.5M 7s\n", + "242200K .......... .......... .......... .......... .......... 40% 42.6M 7s\n", + "242250K .......... .......... .......... .......... .......... 40% 9.25M 7s\n", + "242300K .......... .......... .......... .......... .......... 40% 64.5M 7s\n", + "242350K .......... .......... .......... .......... .......... 40% 63.3M 7s\n", + "242400K .......... .......... .......... .......... .......... 40% 58.4M 7s\n", + "242450K .......... .......... .......... .......... .......... 40% 67.2M 7s\n", + "242500K .......... .......... .......... .......... .......... 40% 69.7M 7s\n", + "242550K .......... .......... .......... .......... .......... 40% 47.9M 7s\n", + "242600K .......... .......... .......... .......... .......... 40% 52.9M 7s\n", + "242650K .......... .......... .......... .......... .......... 40% 71.1M 7s\n", + "242700K .......... .......... .......... .......... .......... 40% 64.6M 7s\n", + "242750K .......... .......... .......... .......... .......... 40% 69.1M 7s\n", + "242800K .......... .......... .......... .......... .......... 40% 48.9M 7s\n", + "242850K .......... .......... .......... .......... .......... 40% 48.9M 7s\n", + "242900K .......... .......... .......... .......... .......... 40% 64.7M 7s\n", + "242950K .......... .......... .......... .......... .......... 40% 51.9M 7s\n", + "243000K .......... .......... .......... .......... .......... 40% 31.7M 7s\n", + "243050K .......... .......... .......... .......... .......... 40% 36.8M 7s\n", + "243100K .......... .......... .......... .......... .......... 40% 36.2M 7s\n", + "243150K .......... .......... .......... .......... .......... 40% 51.3M 7s\n", + "243200K .......... .......... .......... .......... .......... 40% 39.2M 7s\n", + "243250K .......... .......... .......... .......... .......... 40% 34.7M 7s\n", + "243300K .......... .......... .......... .......... .......... 40% 4.68M 7s\n", + "243350K .......... .......... .......... .......... .......... 40% 63.5M 7s\n", + "243400K .......... .......... .......... .......... .......... 40% 49.8M 7s\n", + "243450K .......... .......... .......... .......... .......... 40% 72.0M 7s\n", + "243500K .......... .......... .......... .......... .......... 40% 5.83M 7s\n", + "243550K .......... .......... .......... .......... .......... 40% 61.6M 7s\n", + "243600K .......... .......... .......... .......... .......... 40% 60.2M 7s\n", + "243650K .......... .......... .......... .......... .......... 40% 21.3M 7s\n", + "243700K .......... .......... .......... .......... .......... 40% 58.8M 7s\n", + "243750K .......... .......... .......... .......... .......... 40% 56.7M 7s\n", + "243800K .......... .......... .......... .......... .......... 41% 61.4M 7s\n", + "243850K .......... .......... .......... .......... .......... 41% 71.0M 7s\n", + "243900K .......... .......... .......... .......... .......... 41% 67.6M 7s\n", + "243950K .......... .......... .......... .......... .......... 41% 69.7M 7s\n", + "244000K .......... .......... .......... .......... .......... 41% 61.4M 7s\n", + "244050K .......... .......... .......... .......... .......... 41% 45.7M 7s\n", + "244100K .......... .......... .......... .......... .......... 41% 59.2M 7s\n", + "244150K .......... .......... .......... .......... .......... 41% 62.5M 7s\n", + "244200K .......... .......... .......... .......... .......... 41% 58.9M 7s\n", + "244250K .......... .......... .......... .......... .......... 41% 68.5M 7s\n", + "244300K .......... .......... .......... .......... .......... 41% 60.7M 7s\n", + "244350K .......... .......... .......... .......... .......... 41% 51.3M 7s\n", + "244400K .......... .......... .......... .......... .......... 41% 50.2M 7s\n", + "244450K .......... .......... .......... .......... .......... 41% 68.5M 7s\n", + "244500K .......... .......... .......... .......... .......... 41% 54.9M 7s\n", + "244550K .......... .......... .......... .......... .......... 41% 51.8M 7s\n", + "244600K .......... .......... .......... .......... .......... 41% 37.9M 7s\n", + "244650K .......... .......... .......... .......... .......... 41% 54.4M 7s\n", + "244700K .......... .......... .......... .......... .......... 41% 73.6M 7s\n", + "244750K .......... .......... .......... .......... .......... 41% 75.7M 7s\n", + "244800K .......... .......... .......... .......... .......... 41% 58.1M 7s\n", + "244850K .......... .......... .......... .......... .......... 41% 49.5M 7s\n", + "244900K .......... .......... .......... .......... .......... 41% 56.3M 7s\n", + "244950K .......... .......... .......... .......... .......... 41% 50.8M 7s\n", + "245000K .......... .......... .......... .......... .......... 41% 49.6M 7s\n", + "245050K .......... .......... .......... .......... .......... 41% 57.2M 7s\n", + "245100K .......... .......... .......... .......... .......... 41% 63.2M 7s\n", + "245150K .......... .......... .......... .......... .......... 41% 50.2M 7s\n", + "245200K .......... .......... .......... .......... .......... 41% 41.4M 7s\n", + "245250K .......... .......... .......... .......... .......... 41% 65.8M 7s\n", + "245300K .......... .......... .......... .......... .......... 41% 63.9M 7s\n", + "245350K .......... .......... .......... .......... .......... 41% 71.6M 7s\n", + "245400K .......... .......... .......... .......... .......... 41% 40.9M 7s\n", + "245450K .......... .......... .......... .......... .......... 41% 54.0M 7s\n", + "245500K .......... .......... .......... .......... .......... 41% 64.4M 7s\n", + "245550K .......... .......... .......... .......... .......... 41% 55.7M 7s\n", + "245600K .......... .......... .......... .......... .......... 41% 64.1M 7s\n", + "245650K .......... .......... .......... .......... .......... 41% 55.5M 7s\n", + "245700K .......... .......... .......... .......... .......... 41% 63.4M 7s\n", + "245750K .......... .......... .......... .......... .......... 41% 43.3M 7s\n", + "245800K .......... .......... .......... .......... .......... 41% 32.8M 7s\n", + "245850K .......... .......... .......... .......... .......... 41% 77.5M 7s\n", + "245900K .......... .......... .......... .......... .......... 41% 55.6M 7s\n", + "245950K .......... .......... .......... .......... .......... 41% 53.7M 7s\n", + "246000K .......... .......... .......... .......... .......... 41% 60.8M 7s\n", + "246050K .......... .......... .......... .......... .......... 41% 62.1M 7s\n", + "246100K .......... .......... .......... .......... .......... 41% 64.1M 7s\n", + "246150K .......... .......... .......... .......... .......... 41% 55.8M 7s\n", + "246200K .......... .......... .......... .......... .......... 41% 40.4M 7s\n", + "246250K .......... .......... .......... .......... .......... 41% 3.83M 7s\n", + "246300K .......... .......... .......... .......... .......... 41% 61.9M 7s\n", + "246350K .......... .......... .......... .......... .......... 41% 59.6M 7s\n", + "246400K .......... .......... .......... .......... .......... 41% 60.0M 7s\n", + "246450K .......... .......... .......... .......... .......... 41% 65.7M 7s\n", + "246500K .......... .......... .......... .......... .......... 41% 63.6M 7s\n", + "246550K .......... .......... .......... .......... .......... 41% 59.9M 7s\n", + "246600K .......... .......... .......... .......... .......... 41% 43.6M 7s\n", + "246650K .......... .......... .......... .......... .......... 41% 63.9M 7s\n", + "246700K .......... .......... .......... .......... .......... 41% 62.1M 7s\n", + "246750K .......... .......... .......... .......... .......... 41% 50.5M 7s\n", + "246800K .......... .......... .......... .......... .......... 41% 57.4M 7s\n", + "246850K .......... .......... .......... .......... .......... 41% 60.0M 7s\n", + "246900K .......... .......... .......... .......... .......... 41% 66.8M 7s\n", + "246950K .......... .......... .......... .......... .......... 41% 64.0M 7s\n", + "247000K .......... .......... .......... .......... .......... 41% 40.6M 7s\n", + "247050K .......... .......... .......... .......... .......... 41% 52.8M 7s\n", + "247100K .......... .......... .......... .......... .......... 41% 52.0M 7s\n", + "247150K .......... .......... .......... .......... .......... 41% 65.1M 7s\n", + "247200K .......... .......... .......... .......... .......... 41% 64.8M 7s\n", + "247250K .......... .......... .......... .......... .......... 41% 57.4M 7s\n", + "247300K .......... .......... .......... .......... .......... 41% 57.6M 7s\n", + "247350K .......... .......... .......... .......... .......... 41% 61.6M 7s\n", + "247400K .......... .......... .......... .......... .......... 41% 47.7M 7s\n", + "247450K .......... .......... .......... .......... .......... 41% 6.92M 7s\n", + "247500K .......... .......... .......... .......... .......... 41% 62.5M 7s\n", + "247550K .......... .......... .......... .......... .......... 41% 69.7M 7s\n", + "247600K .......... .......... .......... .......... .......... 41% 58.8M 7s\n", + "247650K .......... .......... .......... .......... .......... 41% 66.6M 7s\n", + "247700K .......... .......... .......... .......... .......... 41% 62.6M 7s\n", + "247750K .......... .......... .......... .......... .......... 41% 66.2M 7s\n", + "247800K .......... .......... .......... .......... .......... 41% 42.7M 7s\n", + "247850K .......... .......... .......... .......... .......... 41% 68.5M 7s\n", + "247900K .......... .......... .......... .......... .......... 41% 59.8M 7s\n", + "247950K .......... .......... .......... .......... .......... 41% 68.0M 7s\n", + "248000K .......... .......... .......... .......... .......... 41% 45.0M 7s\n", + "248050K .......... .......... .......... .......... .......... 41% 55.9M 7s\n", + "248100K .......... .......... .......... .......... .......... 41% 64.5M 7s\n", + "248150K .......... .......... .......... .......... .......... 41% 71.6M 7s\n", + "248200K .......... .......... .......... .......... .......... 41% 57.3M 7s\n", + "248250K .......... .......... .......... .......... .......... 41% 53.9M 7s\n", + "248300K .......... .......... .......... .......... .......... 41% 50.9M 7s\n", + "248350K .......... .......... .......... .......... .......... 41% 58.1M 7s\n", + "248400K .......... .......... .......... .......... .......... 41% 55.5M 7s\n", + "248450K .......... .......... .......... .......... .......... 41% 68.6M 7s\n", + "248500K .......... .......... .......... .......... .......... 41% 65.3M 7s\n", + "248550K .......... .......... .......... .......... .......... 41% 48.9M 7s\n", + "248600K .......... .......... .......... .......... .......... 41% 42.4M 7s\n", + "248650K .......... .......... .......... .......... .......... 41% 66.9M 7s\n", + "248700K .......... .......... .......... .......... .......... 41% 6.09M 7s\n", + "248750K .......... .......... .......... .......... .......... 41% 64.5M 7s\n", + "248800K .......... .......... .......... .......... .......... 41% 63.3M 7s\n", + "248850K .......... .......... .......... .......... .......... 41% 76.3M 7s\n", + "248900K .......... .......... .......... .......... .......... 41% 59.3M 7s\n", + "248950K .......... .......... .......... .......... .......... 41% 71.8M 7s\n", + "249000K .......... .......... .......... .......... .......... 41% 46.9M 7s\n", + "249050K .......... .......... .......... .......... .......... 41% 65.2M 7s\n", + "249100K .......... .......... .......... .......... .......... 41% 69.5M 7s\n", + "249150K .......... .......... .......... .......... .......... 41% 60.3M 7s\n", + "249200K .......... .......... .......... .......... .......... 41% 43.3M 7s\n", + "249250K .......... .......... .......... .......... .......... 41% 62.4M 7s\n", + "249300K .......... .......... .......... .......... .......... 41% 61.5M 7s\n", + "249350K .......... .......... .......... .......... .......... 41% 64.5M 7s\n", + "249400K .......... .......... .......... .......... .......... 41% 54.7M 7s\n", + "249450K .......... .......... .......... .......... .......... 41% 44.4M 7s\n", + "249500K .......... .......... .......... .......... .......... 41% 60.7M 7s\n", + "249550K .......... .......... .......... .......... .......... 41% 54.4M 7s\n", + "249600K .......... .......... .......... .......... .......... 41% 53.5M 7s\n", + "249650K .......... .......... .......... .......... .......... 41% 64.2M 7s\n", + "249700K .......... .......... .......... .......... .......... 41% 26.9M 7s\n", + "249750K .......... .......... .......... .......... .......... 42% 32.3M 7s\n", + "249800K .......... .......... .......... .......... .......... 42% 34.2M 7s\n", + "249850K .......... .......... .......... .......... .......... 42% 63.8M 7s\n", + "249900K .......... .......... .......... .......... .......... 42% 63.8M 7s\n", + "249950K .......... .......... .......... .......... .......... 42% 57.6M 7s\n", + "250000K .......... .......... .......... .......... .......... 42% 47.6M 7s\n", + "250050K .......... .......... .......... .......... .......... 42% 60.5M 7s\n", + "250100K .......... .......... .......... .......... .......... 42% 64.1M 7s\n", + "250150K .......... .......... .......... .......... .......... 42% 68.5M 7s\n", + "250200K .......... .......... .......... .......... .......... 42% 40.1M 7s\n", + "250250K .......... .......... .......... .......... .......... 42% 62.0M 7s\n", + "250300K .......... .......... .......... .......... .......... 42% 77.0M 7s\n", + "250350K .......... .......... .......... .......... .......... 42% 70.3M 7s\n", + "250400K .......... .......... .......... .......... .......... 42% 67.2M 7s\n", + "250450K .......... .......... .......... .......... .......... 42% 47.5M 7s\n", + "250500K .......... .......... .......... .......... .......... 42% 38.2M 7s\n", + "250550K .......... .......... .......... .......... .......... 42% 41.2M 7s\n", + "250600K .......... .......... .......... .......... .......... 42% 28.8M 7s\n", + "250650K .......... .......... .......... .......... .......... 42% 39.5M 7s\n", + "250700K .......... .......... .......... .......... .......... 42% 38.9M 7s\n", + "250750K .......... .......... .......... .......... .......... 42% 38.2M 7s\n", + "250800K .......... .......... .......... .......... .......... 42% 33.1M 7s\n", + "250850K .......... .......... .......... .......... .......... 42% 35.4M 7s\n", + "250900K .......... .......... .......... .......... .......... 42% 43.8M 7s\n", + "250950K .......... .......... .......... .......... .......... 42% 38.1M 7s\n", + "251000K .......... .......... .......... .......... .......... 42% 31.4M 7s\n", + "251050K .......... .......... .......... .......... .......... 42% 46.5M 7s\n", + "251100K .......... .......... .......... .......... .......... 42% 45.3M 7s\n", + "251150K .......... .......... .......... .......... .......... 42% 45.3M 7s\n", + "251200K .......... .......... .......... .......... .......... 42% 51.8M 7s\n", + "251250K .......... .......... .......... .......... .......... 42% 52.9M 7s\n", + "251300K .......... .......... .......... .......... .......... 42% 70.2M 7s\n", + "251350K .......... .......... .......... .......... .......... 42% 53.4M 7s\n", + "251400K .......... .......... .......... .......... .......... 42% 48.5M 7s\n", + "251450K .......... .......... .......... .......... .......... 42% 49.8M 7s\n", + "251500K .......... .......... .......... .......... .......... 42% 42.3M 7s\n", + "251550K .......... .......... .......... .......... .......... 42% 54.0M 7s\n", + "251600K .......... .......... .......... .......... .......... 42% 59.1M 7s\n", + "251650K .......... .......... .......... .......... .......... 42% 61.4M 7s\n", + "251700K .......... .......... .......... .......... .......... 42% 54.7M 7s\n", + "251750K .......... .......... .......... .......... .......... 42% 51.1M 7s\n", + "251800K .......... .......... .......... .......... .......... 42% 48.7M 7s\n", + "251850K .......... .......... .......... .......... .......... 42% 56.0M 7s\n", + "251900K .......... .......... .......... .......... .......... 42% 50.9M 7s\n", + "251950K .......... .......... .......... .......... .......... 42% 41.9M 7s\n", + "252000K .......... .......... .......... .......... .......... 42% 48.3M 7s\n", + "252050K .......... .......... .......... .......... .......... 42% 58.7M 7s\n", + "252100K .......... .......... .......... .......... .......... 42% 63.1M 7s\n", + "252150K .......... .......... .......... .......... .......... 42% 59.0M 7s\n", + "252200K .......... .......... .......... .......... .......... 42% 40.0M 7s\n", + "252250K .......... .......... .......... .......... .......... 42% 52.6M 7s\n", + "252300K .......... .......... .......... .......... .......... 42% 56.9M 7s\n", + "252350K .......... .......... .......... .......... .......... 42% 61.8M 7s\n", + "252400K .......... .......... .......... .......... .......... 42% 59.7M 7s\n", + "252450K .......... .......... .......... .......... .......... 42% 62.3M 7s\n", + "252500K .......... .......... .......... .......... .......... 42% 56.0M 7s\n", + "252550K .......... .......... .......... .......... .......... 42% 74.2M 7s\n", + "252600K .......... .......... .......... .......... .......... 42% 50.9M 7s\n", + "252650K .......... .......... .......... .......... .......... 42% 84.7M 7s\n", + "252700K .......... .......... .......... .......... .......... 42% 47.8M 7s\n", + "252750K .......... .......... .......... .......... .......... 42% 37.5M 7s\n", + "252800K .......... .......... .......... .......... .......... 42% 40.1M 7s\n", + "252850K .......... .......... .......... .......... .......... 42% 75.4M 7s\n", + "252900K .......... .......... .......... .......... .......... 42% 60.4M 7s\n", + "252950K .......... .......... .......... .......... .......... 42% 65.7M 7s\n", + "253000K .......... .......... .......... .......... .......... 42% 55.1M 7s\n", + "253050K .......... .......... .......... .......... .......... 42% 65.1M 7s\n", + "253100K .......... .......... .......... .......... .......... 42% 80.1M 7s\n", + "253150K .......... .......... .......... .......... .......... 42% 58.1M 7s\n", + "253200K .......... .......... .......... .......... .......... 42% 37.9M 7s\n", + "253250K .......... .......... .......... .......... .......... 42% 58.6M 7s\n", + "253300K .......... .......... .......... .......... .......... 42% 49.1M 7s\n", + "253350K .......... .......... .......... .......... .......... 42% 56.6M 7s\n", + "253400K .......... .......... .......... .......... .......... 42% 45.5M 7s\n", + "253450K .......... .......... .......... .......... .......... 42% 45.7M 7s\n", + "253500K .......... .......... .......... .......... .......... 42% 54.3M 7s\n", + "253550K .......... .......... .......... .......... .......... 42% 56.2M 7s\n", + "253600K .......... .......... .......... .......... .......... 42% 49.4M 7s\n", + "253650K .......... .......... .......... .......... .......... 42% 39.0M 7s\n", + "253700K .......... .......... .......... .......... .......... 42% 48.2M 7s\n", + "253750K .......... .......... .......... .......... .......... 42% 52.9M 7s\n", + "253800K .......... .......... .......... .......... .......... 42% 33.7M 7s\n", + "253850K .......... .......... .......... .......... .......... 42% 41.7M 7s\n", + "253900K .......... .......... .......... .......... .......... 42% 45.8M 7s\n", + "253950K .......... .......... .......... .......... .......... 42% 56.9M 7s\n", + "254000K .......... .......... .......... .......... .......... 42% 50.1M 7s\n", + "254050K .......... .......... .......... .......... .......... 42% 50.7M 7s\n", + "254100K .......... .......... .......... .......... .......... 42% 53.9M 7s\n", + "254150K .......... .......... .......... .......... .......... 42% 41.6M 7s\n", + "254200K .......... .......... .......... .......... .......... 42% 44.3M 7s\n", + "254250K .......... .......... .......... .......... .......... 42% 55.2M 7s\n", + "254300K .......... .......... .......... .......... .......... 42% 15.5M 7s\n", + "254350K .......... .......... .......... .......... .......... 42% 68.6M 7s\n", + "254400K .......... .......... .......... .......... .......... 42% 63.7M 7s\n", + "254450K .......... .......... .......... .......... .......... 42% 64.7M 7s\n", + "254500K .......... .......... .......... .......... .......... 42% 73.3M 7s\n", + "254550K .......... .......... .......... .......... .......... 42% 78.9M 7s\n", + "254600K .......... .......... .......... .......... .......... 42% 61.9M 7s\n", + "254650K .......... .......... .......... .......... .......... 42% 65.5M 7s\n", + "254700K .......... .......... .......... .......... .......... 42% 52.6M 7s\n", + "254750K .......... .......... .......... .......... .......... 42% 69.9M 7s\n", + "254800K .......... .......... .......... .......... .......... 42% 65.6M 7s\n", + "254850K .......... .......... .......... .......... .......... 42% 74.9M 7s\n", + "254900K .......... .......... .......... .......... .......... 42% 75.5M 7s\n", + "254950K .......... .......... .......... .......... .......... 42% 78.4M 7s\n", + "255000K .......... .......... .......... .......... .......... 42% 55.9M 7s\n", + "255050K .......... .......... .......... .......... .......... 42% 3.66M 7s\n", + "255100K .......... .......... .......... .......... .......... 42% 74.3M 7s\n", + "255150K .......... .......... .......... .......... .......... 42% 68.5M 7s\n", + "255200K .......... .......... .......... .......... .......... 42% 74.5M 7s\n", + "255250K .......... .......... .......... .......... .......... 42% 72.4M 7s\n", + "255300K .......... .......... .......... .......... .......... 42% 72.1M 7s\n", + "255350K .......... .......... .......... .......... .......... 42% 76.2M 7s\n", + "255400K .......... .......... .......... .......... .......... 42% 36.0M 7s\n", + "255450K .......... .......... .......... .......... .......... 42% 55.2M 7s\n", + "255500K .......... .......... .......... .......... .......... 42% 79.9M 7s\n", + "255550K .......... .......... .......... .......... .......... 42% 65.5M 7s\n", + "255600K .......... .......... .......... .......... .......... 42% 71.7M 7s\n", + "255650K .......... .......... .......... .......... .......... 42% 59.1M 7s\n", + "255700K .......... .......... .......... .......... .......... 43% 69.7M 7s\n", + "255750K .......... .......... .......... .......... .......... 43% 51.1M 7s\n", + "255800K .......... .......... .......... .......... .......... 43% 57.0M 7s\n", + "255850K .......... .......... .......... .......... .......... 43% 79.1M 7s\n", + "255900K .......... .......... .......... .......... .......... 43% 84.5M 7s\n", + "255950K .......... .......... .......... .......... .......... 43% 69.7M 7s\n", + "256000K .......... .......... .......... .......... .......... 43% 58.9M 7s\n", + "256050K .......... .......... .......... .......... .......... 43% 75.0M 7s\n", + "256100K .......... .......... .......... .......... .......... 43% 60.1M 7s\n", + "256150K .......... .......... .......... .......... .......... 43% 67.5M 7s\n", + "256200K .......... .......... .......... .......... .......... 43% 56.6M 7s\n", + "256250K .......... .......... .......... .......... .......... 43% 54.4M 7s\n", + "256300K .......... .......... .......... .......... .......... 43% 45.2M 7s\n", + "256350K .......... .......... .......... .......... .......... 43% 46.2M 7s\n", + "256400K .......... .......... .......... .......... .......... 43% 59.2M 7s\n", + "256450K .......... .......... .......... .......... .......... 43% 79.1M 7s\n", + "256500K .......... .......... .......... .......... .......... 43% 62.7M 7s\n", + "256550K .......... .......... .......... .......... .......... 43% 59.1M 7s\n", + "256600K .......... .......... .......... .......... .......... 43% 49.4M 7s\n", + "256650K .......... .......... .......... .......... .......... 43% 67.0M 7s\n", + "256700K .......... .......... .......... .......... .......... 43% 78.8M 7s\n", + "256750K .......... .......... .......... .......... .......... 43% 73.6M 7s\n", + "256800K .......... .......... .......... .......... .......... 43% 63.3M 7s\n", + "256850K .......... .......... .......... .......... .......... 43% 69.6M 7s\n", + "256900K .......... .......... .......... .......... .......... 43% 53.0M 7s\n", + "256950K .......... .......... .......... .......... .......... 43% 64.1M 7s\n", + "257000K .......... .......... .......... .......... .......... 43% 64.4M 7s\n", + "257050K .......... .......... .......... .......... .......... 43% 81.8M 7s\n", + "257100K .......... .......... .......... .......... .......... 43% 61.7M 7s\n", + "257150K .......... .......... .......... .......... .......... 43% 51.4M 7s\n", + "257200K .......... .......... .......... .......... .......... 43% 57.3M 7s\n", + "257250K .......... .......... .......... .......... .......... 43% 53.2M 7s\n", + "257300K .......... .......... .......... .......... .......... 43% 76.0M 7s\n", + "257350K .......... .......... .......... .......... .......... 43% 80.2M 7s\n", + "257400K .......... .......... .......... .......... .......... 43% 49.6M 7s\n", + "257450K .......... .......... .......... .......... .......... 43% 63.0M 7s\n", + "257500K .......... .......... .......... .......... .......... 43% 64.0M 7s\n", + "257550K .......... .......... .......... .......... .......... 43% 68.2M 7s\n", + "257600K .......... .......... .......... .......... .......... 43% 66.4M 7s\n", + "257650K .......... .......... .......... .......... .......... 43% 75.5M 7s\n", + "257700K .......... .......... .......... .......... .......... 43% 70.3M 7s\n", + "257750K .......... .......... .......... .......... .......... 43% 69.3M 7s\n", + "257800K .......... .......... .......... .......... .......... 43% 54.2M 7s\n", + "257850K .......... .......... .......... .......... .......... 43% 50.2M 7s\n", + "257900K .......... .......... .......... .......... .......... 43% 68.3M 7s\n", + "257950K .......... .......... .......... .......... .......... 43% 66.2M 7s\n", + "258000K .......... .......... .......... .......... .......... 43% 64.9M 7s\n", + "258050K .......... .......... .......... .......... .......... 43% 65.9M 7s\n", + "258100K .......... .......... .......... .......... .......... 43% 68.7M 7s\n", + "258150K .......... .......... .......... .......... .......... 43% 54.9M 7s\n", + "258200K .......... .......... .......... .......... .......... 43% 66.1M 7s\n", + "258250K .......... .......... .......... .......... .......... 43% 35.4M 7s\n", + "258300K .......... .......... .......... .......... .......... 43% 57.2M 7s\n", + "258350K .......... .......... .......... .......... .......... 43% 60.5M 7s\n", + "258400K .......... .......... .......... .......... .......... 43% 52.0M 7s\n", + "258450K .......... .......... .......... .......... .......... 43% 75.7M 7s\n", + "258500K .......... .......... .......... .......... .......... 43% 23.9M 7s\n", + "258550K .......... .......... .......... .......... .......... 43% 61.8M 7s\n", + "258600K .......... .......... .......... .......... .......... 43% 47.9M 7s\n", + "258650K .......... .......... .......... .......... .......... 43% 84.8M 7s\n", + "258700K .......... .......... .......... .......... .......... 43% 29.3M 7s\n", + "258750K .......... .......... .......... .......... .......... 43% 51.9M 7s\n", + "258800K .......... .......... .......... .......... .......... 43% 55.6M 7s\n", + "258850K .......... .......... .......... .......... .......... 43% 54.6M 7s\n", + "258900K .......... .......... .......... .......... .......... 43% 51.8M 7s\n", + "258950K .......... .......... .......... .......... .......... 43% 40.4M 7s\n", + "259000K .......... .......... .......... .......... .......... 43% 63.0M 7s\n", + "259050K .......... .......... .......... .......... .......... 43% 55.5M 7s\n", + "259100K .......... .......... .......... .......... .......... 43% 79.6M 7s\n", + "259150K .......... .......... .......... .......... .......... 43% 24.2M 7s\n", + "259200K .......... .......... .......... .......... .......... 43% 7.72M 7s\n", + "259250K .......... .......... .......... .......... .......... 43% 55.4M 7s\n", + "259300K .......... .......... .......... .......... .......... 43% 61.5M 7s\n", + "259350K .......... .......... .......... .......... .......... 43% 70.3M 7s\n", + "259400K .......... .......... .......... .......... .......... 43% 444K 7s\n", + "259450K .......... .......... .......... .......... .......... 43% 50.3M 7s\n", + "259500K .......... .......... .......... .......... .......... 43% 59.2M 7s\n", + "259550K .......... .......... .......... .......... .......... 43% 65.9M 7s\n", + "259600K .......... .......... .......... .......... .......... 43% 65.5M 7s\n", + "259650K .......... .......... .......... .......... .......... 43% 16.9M 7s\n", + "259700K .......... .......... .......... .......... .......... 43% 57.3M 7s\n", + "259750K .......... .......... .......... .......... .......... 43% 58.1M 7s\n", + "259800K .......... .......... .......... .......... .......... 43% 61.5M 7s\n", + "259850K .......... .......... .......... .......... .......... 43% 44.8M 7s\n", + "259900K .......... .......... .......... .......... .......... 43% 27.7M 7s\n", + "259950K .......... .......... .......... .......... .......... 43% 36.1M 7s\n", + "260000K .......... .......... .......... .......... .......... 43% 38.0M 7s\n", + "260050K .......... .......... .......... .......... .......... 43% 63.4M 7s\n", + "260100K .......... .......... .......... .......... .......... 43% 55.1M 7s\n", + "260150K .......... .......... .......... .......... .......... 43% 53.9M 7s\n", + "260200K .......... .......... .......... .......... .......... 43% 52.7M 7s\n", + "260250K .......... .......... .......... .......... .......... 43% 73.0M 7s\n", + "260300K .......... .......... .......... .......... .......... 43% 57.3M 7s\n", + "260350K .......... .......... .......... .......... .......... 43% 58.9M 7s\n", + "260400K .......... .......... .......... .......... .......... 43% 35.2M 7s\n", + "260450K .......... .......... .......... .......... .......... 43% 38.0M 7s\n", + "260500K .......... .......... .......... .......... .......... 43% 36.4M 7s\n", + "260550K .......... .......... .......... .......... .......... 43% 60.0M 7s\n", + "260600K .......... .......... .......... .......... .......... 43% 62.0M 7s\n", + "260650K .......... .......... .......... .......... .......... 43% 59.5M 7s\n", + "260700K .......... .......... .......... .......... .......... 43% 66.6M 7s\n", + "260750K .......... .......... .......... .......... .......... 43% 74.1M 7s\n", + "260800K .......... .......... .......... .......... .......... 43% 37.3M 7s\n", + "260850K .......... .......... .......... .......... .......... 43% 38.9M 7s\n", + "260900K .......... .......... .......... .......... .......... 43% 37.3M 7s\n", + "260950K .......... .......... .......... .......... .......... 43% 67.2M 7s\n", + "261000K .......... .......... .......... .......... .......... 43% 42.9M 7s\n", + "261050K .......... .......... .......... .......... .......... 43% 54.6M 7s\n", + "261100K .......... .......... .......... .......... .......... 43% 44.8M 7s\n", + "261150K .......... .......... .......... .......... .......... 43% 50.9M 7s\n", + "261200K .......... .......... .......... .......... .......... 43% 48.8M 7s\n", + "261250K .......... .......... .......... .......... .......... 43% 61.7M 7s\n", + "261300K .......... .......... .......... .......... .......... 43% 41.2M 7s\n", + "261350K .......... .......... .......... .......... .......... 43% 38.7M 7s\n", + "261400K .......... .......... .......... .......... .......... 43% 55.3M 7s\n", + "261450K .......... .......... .......... .......... .......... 43% 49.1M 7s\n", + "261500K .......... .......... .......... .......... .......... 43% 63.6M 7s\n", + "261550K .......... .......... .......... .......... .......... 43% 51.4M 7s\n", + "261600K .......... .......... .......... .......... .......... 43% 48.4M 7s\n", + "261650K .......... .......... .......... .......... .......... 44% 61.6M 7s\n", + "261700K .......... .......... .......... .......... .......... 44% 49.0M 7s\n", + "261750K .......... .......... .......... .......... .......... 44% 35.3M 7s\n", + "261800K .......... .......... .......... .......... .......... 44% 33.4M 7s\n", + "261850K .......... .......... .......... .......... .......... 44% 44.5M 7s\n", + "261900K .......... .......... .......... .......... .......... 44% 62.5M 7s\n", + "261950K .......... .......... .......... .......... .......... 44% 51.1M 7s\n", + "262000K .......... .......... .......... .......... .......... 44% 48.2M 7s\n", + "262050K .......... .......... .......... .......... .......... 44% 42.7M 7s\n", + "262100K .......... .......... .......... .......... .......... 44% 49.7M 7s\n", + "262150K .......... .......... .......... .......... .......... 44% 55.4M 7s\n", + "262200K .......... .......... .......... .......... .......... 44% 31.7M 7s\n", + "262250K .......... .......... .......... .......... .......... 44% 40.2M 7s\n", + "262300K .......... .......... .......... .......... .......... 44% 51.9M 7s\n", + "262350K .......... .......... .......... .......... .......... 44% 63.8M 7s\n", + "262400K .......... .......... .......... .......... .......... 44% 50.0M 7s\n", + "262450K .......... .......... .......... .......... .......... 44% 41.7M 7s\n", + "262500K .......... .......... .......... .......... .......... 44% 39.3M 7s\n", + "262550K .......... .......... .......... .......... .......... 44% 66.4M 7s\n", + "262600K .......... .......... .......... .......... .......... 44% 43.3M 7s\n", + "262650K .......... .......... .......... .......... .......... 44% 37.9M 7s\n", + "262700K .......... .......... .......... .......... .......... 44% 34.5M 7s\n", + "262750K .......... .......... .......... .......... .......... 44% 4.53M 7s\n", + "262800K .......... .......... .......... .......... .......... 44% 63.2M 7s\n", + "262850K .......... .......... .......... .......... .......... 44% 72.9M 7s\n", + "262900K .......... .......... .......... .......... .......... 44% 78.0M 7s\n", + "262950K .......... .......... .......... .......... .......... 44% 78.5M 7s\n", + "263000K .......... .......... .......... .......... .......... 44% 63.2M 7s\n", + "263050K .......... .......... .......... .......... .......... 44% 75.7M 7s\n", + "263100K .......... .......... .......... .......... .......... 44% 33.0M 7s\n", + "263150K .......... .......... .......... .......... .......... 44% 48.9M 7s\n", + "263200K .......... .......... .......... .......... .......... 44% 66.5M 7s\n", + "263250K .......... .......... .......... .......... .......... 44% 80.1M 7s\n", + "263300K .......... .......... .......... .......... .......... 44% 39.7M 7s\n", + "263350K .......... .......... .......... .......... .......... 44% 34.7M 7s\n", + "263400K .......... .......... .......... .......... .......... 44% 46.2M 7s\n", + "263450K .......... .......... .......... .......... .......... 44% 76.7M 7s\n", + "263500K .......... .......... .......... .......... .......... 44% 81.5M 7s\n", + "263550K .......... .......... .......... .......... .......... 44% 33.9M 7s\n", + "263600K .......... .......... .......... .......... .......... 44% 33.4M 7s\n", + "263650K .......... .......... .......... .......... .......... 44% 75.4M 7s\n", + "263700K .......... .......... .......... .......... .......... 44% 74.8M 7s\n", + "263750K .......... .......... .......... .......... .......... 44% 60.0M 7s\n", + "263800K .......... .......... .......... .......... .......... 44% 37.2M 7s\n", + "263850K .......... .......... .......... .......... .......... 44% 34.4M 7s\n", + "263900K .......... .......... .......... .......... .......... 44% 74.4M 7s\n", + "263950K .......... .......... .......... .......... .......... 44% 78.7M 7s\n", + "264000K .......... .......... .......... .......... .......... 44% 23.0M 7s\n", + "264050K .......... .......... .......... .......... .......... 44% 21.3M 7s\n", + "264100K .......... .......... .......... .......... .......... 44% 40.8M 7s\n", + "264150K .......... .......... .......... .......... .......... 44% 49.5M 7s\n", + "264200K .......... .......... .......... .......... .......... 44% 62.6M 7s\n", + "264250K .......... .......... .......... .......... .......... 44% 36.5M 7s\n", + "264300K .......... .......... .......... .......... .......... 44% 42.4M 7s\n", + "264350K .......... .......... .......... .......... .......... 44% 42.1M 7s\n", + "264400K .......... .......... .......... .......... .......... 44% 67.5M 7s\n", + "264450K .......... .......... .......... .......... .......... 44% 65.0M 7s\n", + "264500K .......... .......... .......... .......... .......... 44% 30.7M 7s\n", + "264550K .......... .......... .......... .......... .......... 44% 52.9M 7s\n", + "264600K .......... .......... .......... .......... .......... 44% 50.6M 7s\n", + "264650K .......... .......... .......... .......... .......... 44% 65.7M 7s\n", + "264700K .......... .......... .......... .......... .......... 44% 37.0M 7s\n", + "264750K .......... .......... .......... .......... .......... 44% 36.6M 7s\n", + "264800K .......... .......... .......... .......... .......... 44% 50.2M 7s\n", + "264850K .......... .......... .......... .......... .......... 44% 66.8M 7s\n", + "264900K .......... .......... .......... .......... .......... 44% 66.4M 7s\n", + "264950K .......... .......... .......... .......... .......... 44% 60.9M 7s\n", + "265000K .......... .......... .......... .......... .......... 44% 27.5M 7s\n", + "265050K .......... .......... .......... .......... .......... 44% 80.8M 7s\n", + "265100K .......... .......... .......... .......... .......... 44% 62.9M 7s\n", + "265150K .......... .......... .......... .......... .......... 44% 48.2M 7s\n", + "265200K .......... .......... .......... .......... .......... 44% 35.0M 7s\n", + "265250K .......... .......... .......... .......... .......... 44% 30.4M 7s\n", + "265300K .......... .......... .......... .......... .......... 44% 61.3M 7s\n", + "265350K .......... .......... .......... .......... .......... 44% 28.3M 7s\n", + "265400K .......... .......... .......... .......... .......... 44% 38.7M 7s\n", + "265450K .......... .......... .......... .......... .......... 44% 47.1M 7s\n", + "265500K .......... .......... .......... .......... .......... 44% 32.9M 7s\n", + "265550K .......... .......... .......... .......... .......... 44% 44.4M 7s\n", + "265600K .......... .......... .......... .......... .......... 44% 31.9M 7s\n", + "265650K .......... .......... .......... .......... .......... 44% 52.6M 7s\n", + "265700K .......... .......... .......... .......... .......... 44% 64.5M 7s\n", + "265750K .......... .......... .......... .......... .......... 44% 51.0M 7s\n", + "265800K .......... .......... .......... .......... .......... 44% 37.9M 7s\n", + "265850K .......... .......... .......... .......... .......... 44% 44.9M 7s\n", + "265900K .......... .......... .......... .......... .......... 44% 62.0M 7s\n", + "265950K .......... .......... .......... .......... .......... 44% 63.2M 7s\n", + "266000K .......... .......... .......... .......... .......... 44% 35.8M 7s\n", + "266050K .......... .......... .......... .......... .......... 44% 39.5M 7s\n", + "266100K .......... .......... .......... .......... .......... 44% 58.2M 7s\n", + "266150K .......... .......... .......... .......... .......... 44% 64.6M 7s\n", + "266200K .......... .......... .......... .......... .......... 44% 39.5M 7s\n", + "266250K .......... .......... .......... .......... .......... 44% 51.2M 7s\n", + "266300K .......... .......... .......... .......... .......... 44% 46.5M 7s\n", + "266350K .......... .......... .......... .......... .......... 44% 63.6M 7s\n", + "266400K .......... .......... .......... .......... .......... 44% 66.7M 7s\n", + "266450K .......... .......... .......... .......... .......... 44% 52.0M 7s\n", + "266500K .......... .......... .......... .......... .......... 44% 49.7M 7s\n", + "266550K .......... .......... .......... .......... .......... 44% 41.1M 7s\n", + "266600K .......... .......... .......... .......... .......... 44% 54.8M 7s\n", + "266650K .......... .......... .......... .......... .......... 44% 75.7M 7s\n", + "266700K .......... .......... .......... .......... .......... 44% 45.2M 7s\n", + "266750K .......... .......... .......... .......... .......... 44% 32.9M 7s\n", + "266800K .......... .......... .......... .......... .......... 44% 43.5M 7s\n", + "266850K .......... .......... .......... .......... .......... 44% 56.8M 7s\n", + "266900K .......... .......... .......... .......... .......... 44% 41.2M 7s\n", + "266950K .......... .......... .......... .......... .......... 44% 43.9M 7s\n", + "267000K .......... .......... .......... .......... .......... 44% 51.2M 7s\n", + "267050K .......... .......... .......... .......... .......... 44% 44.8M 7s\n", + "267100K .......... .......... .......... .......... .......... 44% 43.3M 7s\n", + "267150K .......... .......... .......... .......... .......... 44% 51.2M 7s\n", + "267200K .......... .......... .......... .......... .......... 44% 41.3M 7s\n", + "267250K .......... .......... .......... .......... .......... 44% 59.2M 7s\n", + "267300K .......... .......... .......... .......... .......... 44% 43.9M 7s\n", + "267350K .......... .......... .......... .......... .......... 44% 58.7M 7s\n", + "267400K .......... .......... .......... .......... .......... 44% 43.7M 7s\n", + "267450K .......... .......... .......... .......... .......... 44% 56.3M 7s\n", + "267500K .......... .......... .......... .......... .......... 44% 49.2M 7s\n", + "267550K .......... .......... .......... .......... .......... 44% 4.22M 7s\n", + "267600K .......... .......... .......... .......... .......... 45% 52.9M 7s\n", + "267650K .......... .......... .......... .......... .......... 45% 58.4M 7s\n", + "267700K .......... .......... .......... .......... .......... 45% 47.0M 7s\n", + "267750K .......... .......... .......... .......... .......... 45% 57.3M 7s\n", + "267800K .......... .......... .......... .......... .......... 45% 33.3M 7s\n", + "267850K .......... .......... .......... .......... .......... 45% 48.2M 7s\n", + "267900K .......... .......... .......... .......... .......... 45% 47.4M 7s\n", + "267950K .......... .......... .......... .......... .......... 45% 54.4M 7s\n", + "268000K .......... .......... .......... .......... .......... 45% 40.5M 7s\n", + "268050K .......... .......... .......... .......... .......... 45% 35.6M 7s\n", + "268100K .......... .......... .......... .......... .......... 45% 44.5M 7s\n", + "268150K .......... .......... .......... .......... .......... 45% 53.3M 7s\n", + "268200K .......... .......... .......... .......... .......... 45% 35.7M 7s\n", + "268250K .......... .......... .......... .......... .......... 45% 43.5M 7s\n", + "268300K .......... .......... .......... .......... .......... 45% 44.1M 7s\n", + "268350K .......... .......... .......... .......... .......... 45% 52.5M 7s\n", + "268400K .......... .......... .......... .......... .......... 45% 41.7M 7s\n", + "268450K .......... .......... .......... .......... .......... 45% 38.0M 7s\n", + "268500K .......... .......... .......... .......... .......... 45% 45.0M 7s\n", + "268550K .......... .......... .......... .......... .......... 45% 50.5M 7s\n", + "268600K .......... .......... .......... .......... .......... 45% 35.6M 7s\n", + "268650K .......... .......... .......... .......... .......... 45% 37.0M 7s\n", + "268700K .......... .......... .......... .......... .......... 45% 42.8M 7s\n", + "268750K .......... .......... .......... .......... .......... 45% 52.6M 7s\n", + "268800K .......... .......... .......... .......... .......... 45% 45.5M 7s\n", + "268850K .......... .......... .......... .......... .......... 45% 41.4M 7s\n", + "268900K .......... .......... .......... .......... .......... 45% 50.8M 7s\n", + "268950K .......... .......... .......... .......... .......... 45% 54.9M 7s\n", + "269000K .......... .......... .......... .......... .......... 45% 46.5M 7s\n", + "269050K .......... .......... .......... .......... .......... 45% 40.0M 7s\n", + "269100K .......... .......... .......... .......... .......... 45% 52.7M 7s\n", + "269150K .......... .......... .......... .......... .......... 45% 40.0M 7s\n", + "269200K .......... .......... .......... .......... .......... 45% 29.2M 7s\n", + "269250K .......... .......... .......... .......... .......... 45% 30.2M 7s\n", + "269300K .......... .......... .......... .......... .......... 45% 31.4M 7s\n", + "269350K .......... .......... .......... .......... .......... 45% 53.0M 7s\n", + "269400K .......... .......... .......... .......... .......... 45% 26.6M 7s\n", + "269450K .......... .......... .......... .......... .......... 45% 30.2M 7s\n", + "269500K .......... .......... .......... .......... .......... 45% 5.12M 7s\n", + "269550K .......... .......... .......... .......... .......... 45% 67.3M 7s\n", + "269600K .......... .......... .......... .......... .......... 45% 60.5M 7s\n", + "269650K .......... .......... .......... .......... .......... 45% 66.1M 7s\n", + "269700K .......... .......... .......... .......... .......... 45% 11.4M 7s\n", + "269750K .......... .......... .......... .......... .......... 45% 63.3M 7s\n", + "269800K .......... .......... .......... .......... .......... 45% 58.5M 7s\n", + "269850K .......... .......... .......... .......... .......... 45% 71.1M 7s\n", + "269900K .......... .......... .......... .......... .......... 45% 66.9M 7s\n", + "269950K .......... .......... .......... .......... .......... 45% 70.8M 7s\n", + "270000K .......... .......... .......... .......... .......... 45% 22.5M 7s\n", + "270050K .......... .......... .......... .......... .......... 45% 69.8M 7s\n", + "270100K .......... .......... .......... .......... .......... 45% 72.3M 7s\n", + "270150K .......... .......... .......... .......... .......... 45% 68.2M 7s\n", + "270200K .......... .......... .......... .......... .......... 45% 34.1M 7s\n", + "270250K .......... .......... .......... .......... .......... 45% 29.2M 7s\n", + "270300K .......... .......... .......... .......... .......... 45% 68.0M 7s\n", + "270350K .......... .......... .......... .......... .......... 45% 72.2M 7s\n", + "270400K .......... .......... .......... .......... .......... 45% 48.8M 7s\n", + "270450K .......... .......... .......... .......... .......... 45% 26.7M 7s\n", + "270500K .......... .......... .......... .......... .......... 45% 69.3M 7s\n", + "270550K .......... .......... .......... .......... .......... 45% 71.9M 7s\n", + "270600K .......... .......... .......... .......... .......... 45% 47.6M 7s\n", + "270650K .......... .......... .......... .......... .......... 45% 32.2M 7s\n", + "270700K .......... .......... .......... .......... .......... 45% 51.5M 7s\n", + "270750K .......... .......... .......... .......... .......... 45% 68.9M 7s\n", + "270800K .......... .......... .......... .......... .......... 45% 50.7M 7s\n", + "270850K .......... .......... .......... .......... .......... 45% 45.1M 7s\n", + "270900K .......... .......... .......... .......... .......... 45% 49.8M 7s\n", + "270950K .......... .......... .......... .......... .......... 45% 50.1M 7s\n", + "271000K .......... .......... .......... .......... .......... 45% 54.7M 7s\n", + "271050K .......... .......... .......... .......... .......... 45% 49.0M 7s\n", + "271100K .......... .......... .......... .......... .......... 45% 52.8M 7s\n", + "271150K .......... .......... .......... .......... .......... 45% 43.7M 7s\n", + "271200K .......... .......... .......... .......... .......... 45% 52.4M 7s\n", + "271250K .......... .......... .......... .......... .......... 45% 59.7M 7s\n", + "271300K .......... .......... .......... .......... .......... 45% 62.5M 7s\n", + "271350K .......... .......... .......... .......... .......... 45% 49.9M 7s\n", + "271400K .......... .......... .......... .......... .......... 45% 33.2M 7s\n", + "271450K .......... .......... .......... .......... .......... 45% 61.3M 7s\n", + "271500K .......... .......... .......... .......... .......... 45% 29.3M 7s\n", + "271550K .......... .......... .......... .......... .......... 45% 28.9M 7s\n", + "271600K .......... .......... .......... .......... .......... 45% 38.8M 7s\n", + "271650K .......... .......... .......... .......... .......... 45% 4.14M 7s\n", + "271700K .......... .......... .......... .......... .......... 45% 31.6M 7s\n", + "271750K .......... .......... .......... .......... .......... 45% 41.5M 7s\n", + "271800K .......... .......... .......... .......... .......... 45% 28.8M 7s\n", + "271850K .......... .......... .......... .......... .......... 45% 25.5M 7s\n", + "271900K .......... .......... .......... .......... .......... 45% 38.1M 7s\n", + "271950K .......... .......... .......... .......... .......... 45% 32.7M 7s\n", + "272000K .......... .......... .......... .......... .......... 45% 22.4M 7s\n", + "272050K .......... .......... .......... .......... .......... 45% 38.2M 7s\n", + "272100K .......... .......... .......... .......... .......... 45% 30.1M 7s\n", + "272150K .......... .......... .......... .......... .......... 45% 25.9M 7s\n", + "272200K .......... .......... .......... .......... .......... 45% 30.3M 7s\n", + "272250K .......... .......... .......... .......... .......... 45% 25.5M 7s\n", + "272300K .......... .......... .......... .......... .......... 45% 31.1M 7s\n", + "272350K .......... .......... .......... .......... .......... 45% 31.3M 7s\n", + "272400K .......... .......... .......... .......... .......... 45% 32.1M 7s\n", + "272450K .......... .......... .......... .......... .......... 45% 51.5M 7s\n", + "272500K .......... .......... .......... .......... .......... 45% 72.5M 7s\n", + "272550K .......... .......... .......... .......... .......... 45% 52.2M 7s\n", + "272600K .......... .......... .......... .......... .......... 45% 41.3M 7s\n", + "272650K .......... .......... .......... .......... .......... 45% 49.2M 7s\n", + "272700K .......... .......... .......... .......... .......... 45% 43.3M 7s\n", + "272750K .......... .......... .......... .......... .......... 45% 54.3M 7s\n", + "272800K .......... .......... .......... .......... .......... 45% 43.4M 7s\n", + "272850K .......... .......... .......... .......... .......... 45% 50.6M 7s\n", + "272900K .......... .......... .......... .......... .......... 45% 45.9M 7s\n", + "272950K .......... .......... .......... .......... .......... 45% 54.2M 7s\n", + "273000K .......... .......... .......... .......... .......... 45% 22.5M 7s\n", + "273050K .......... .......... .......... .......... .......... 45% 44.5M 7s\n", + "273100K .......... .......... .......... .......... .......... 45% 49.3M 7s\n", + "273150K .......... .......... .......... .......... .......... 45% 39.0M 7s\n", + "273200K .......... .......... .......... .......... .......... 45% 26.4M 7s\n", + "273250K .......... .......... .......... .......... .......... 45% 37.5M 7s\n", + "273300K .......... .......... .......... .......... .......... 45% 53.2M 7s\n", + "273350K .......... .......... .......... .......... .......... 45% 24.8M 7s\n", + "273400K .......... .......... .......... .......... .......... 45% 43.4M 7s\n", + "273450K .......... .......... .......... .......... .......... 45% 39.5M 7s\n", + "273500K .......... .......... .......... .......... .......... 45% 52.9M 7s\n", + "273550K .......... .......... .......... .......... .......... 46% 28.3M 7s\n", + "273600K .......... .......... .......... .......... .......... 46% 27.9M 7s\n", + "273650K .......... .......... .......... .......... .......... 46% 53.3M 7s\n", + "273700K .......... .......... .......... .......... .......... 46% 28.6M 7s\n", + "273750K .......... .......... .......... .......... .......... 46% 52.9M 7s\n", + "273800K .......... .......... .......... .......... .......... 46% 33.4M 7s\n", + "273850K .......... .......... .......... .......... .......... 46% 21.9M 7s\n", + "273900K .......... .......... .......... .......... .......... 46% 54.0M 7s\n", + "273950K .......... .......... .......... .......... .......... 46% 43.5M 7s\n", + "274000K .......... .......... .......... .......... .......... 46% 25.0M 7s\n", + "274050K .......... .......... .......... .......... .......... 46% 46.5M 7s\n", + "274100K .......... .......... .......... .......... .......... 46% 52.2M 7s\n", + "274150K .......... .......... .......... .......... .......... 46% 53.3M 7s\n", + "274200K .......... .......... .......... .......... .......... 46% 22.1M 7s\n", + "274250K .......... .......... .......... .......... .......... 46% 47.5M 7s\n", + "274300K .......... .......... .......... .......... .......... 46% 43.2M 7s\n", + "274350K .......... .......... .......... .......... .......... 46% 30.5M 7s\n", + "274400K .......... .......... .......... .......... .......... 46% 39.2M 7s\n", + "274450K .......... .......... .......... .......... .......... 46% 47.2M 7s\n", + "274500K .......... .......... .......... .......... .......... 46% 45.5M 7s\n", + "274550K .......... .......... .......... .......... .......... 46% 27.8M 7s\n", + "274600K .......... .......... .......... .......... .......... 46% 36.0M 7s\n", + "274650K .......... .......... .......... .......... .......... 46% 43.8M 7s\n", + "274700K .......... .......... .......... .......... .......... 46% 32.0M 7s\n", + "274750K .......... .......... .......... .......... .......... 46% 44.7M 7s\n", + "274800K .......... .......... .......... .......... .......... 46% 42.5M 7s\n", + "274850K .......... .......... .......... .......... .......... 46% 45.1M 7s\n", + "274900K .......... .......... .......... .......... .......... 46% 27.6M 7s\n", + "274950K .......... .......... .......... .......... .......... 46% 54.4M 7s\n", + "275000K .......... .......... .......... .......... .......... 46% 37.0M 7s\n", + "275050K .......... .......... .......... .......... .......... 46% 27.2M 7s\n", + "275100K .......... .......... .......... .......... .......... 46% 44.0M 7s\n", + "275150K .......... .......... .......... .......... .......... 46% 41.1M 7s\n", + "275200K .......... .......... .......... .......... .......... 46% 54.8M 7s\n", + "275250K .......... .......... .......... .......... .......... 46% 28.5M 7s\n", + "275300K .......... .......... .......... .......... .......... 46% 11.4M 7s\n", + "275350K .......... .......... .......... .......... .......... 46% 35.7M 7s\n", + "275400K .......... .......... .......... .......... .......... 46% 35.5M 7s\n", + "275450K .......... .......... .......... .......... .......... 46% 36.8M 7s\n", + "275500K .......... .......... .......... .......... .......... 46% 36.8M 7s\n", + "275550K .......... .......... .......... .......... .......... 46% 43.1M 7s\n", + "275600K .......... .......... .......... .......... .......... 46% 32.4M 7s\n", + "275650K .......... .......... .......... .......... .......... 46% 44.9M 7s\n", + "275700K .......... .......... .......... .......... .......... 46% 39.9M 7s\n", + "275750K .......... .......... .......... .......... .......... 46% 42.3M 7s\n", + "275800K .......... .......... .......... .......... .......... 46% 24.3M 7s\n", + "275850K .......... .......... .......... .......... .......... 46% 32.3M 7s\n", + "275900K .......... .......... .......... .......... .......... 46% 44.8M 7s\n", + "275950K .......... .......... .......... .......... .......... 46% 39.1M 7s\n", + "276000K .......... .......... .......... .......... .......... 46% 32.4M 7s\n", + "276050K .......... .......... .......... .......... .......... 46% 42.6M 7s\n", + "276100K .......... .......... .......... .......... .......... 46% 40.2M 7s\n", + "276150K .......... .......... .......... .......... .......... 46% 40.8M 7s\n", + "276200K .......... .......... .......... .......... .......... 46% 30.7M 7s\n", + "276250K .......... .......... .......... .......... .......... 46% 44.9M 7s\n", + "276300K .......... .......... .......... .......... .......... 46% 36.6M 7s\n", + "276350K .......... .......... .......... .......... .......... 46% 35.4M 7s\n", + "276400K .......... .......... .......... .......... .......... 46% 38.6M 7s\n", + "276450K .......... .......... .......... .......... .......... 46% 41.3M 7s\n", + "276500K .......... .......... .......... .......... .......... 46% 45.1M 7s\n", + "276550K .......... .......... .......... .......... .......... 46% 25.1M 7s\n", + "276600K .......... .......... .......... .......... .......... 46% 48.6M 7s\n", + "276650K .......... .......... .......... .......... .......... 46% 62.1M 7s\n", + "276700K .......... .......... .......... .......... .......... 46% 51.8M 7s\n", + "276750K .......... .......... .......... .......... .......... 46% 65.4M 7s\n", + "276800K .......... .......... .......... .......... .......... 46% 52.3M 7s\n", + "276850K .......... .......... .......... .......... .......... 46% 64.6M 7s\n", + "276900K .......... .......... .......... .......... .......... 46% 62.7M 7s\n", + "276950K .......... .......... .......... .......... .......... 46% 55.7M 7s\n", + "277000K .......... .......... .......... .......... .......... 46% 29.4M 7s\n", + "277050K .......... .......... .......... .......... .......... 46% 32.1M 7s\n", + "277100K .......... .......... .......... .......... .......... 46% 50.5M 7s\n", + "277150K .......... .......... .......... .......... .......... 46% 53.5M 7s\n", + "277200K .......... .......... .......... .......... .......... 46% 43.9M 7s\n", + "277250K .......... .......... .......... .......... .......... 46% 31.2M 7s\n", + "277300K .......... .......... .......... .......... .......... 46% 48.0M 7s\n", + "277350K .......... .......... .......... .......... .......... 46% 56.9M 7s\n", + "277400K .......... .......... .......... .......... .......... 46% 19.3M 7s\n", + "277450K .......... .......... .......... .......... .......... 46% 49.0M 7s\n", + "277500K .......... .......... .......... .......... .......... 46% 53.0M 7s\n", + "277550K .......... .......... .......... .......... .......... 46% 53.8M 7s\n", + "277600K .......... .......... .......... .......... .......... 46% 27.7M 7s\n", + "277650K .......... .......... .......... .......... .......... 46% 52.3M 7s\n", + "277700K .......... .......... .......... .......... .......... 46% 57.1M 7s\n", + "277750K .......... .......... .......... .......... .......... 46% 59.8M 7s\n", + "277800K .......... .......... .......... .......... .......... 46% 21.5M 7s\n", + "277850K .......... .......... .......... .......... .......... 46% 53.3M 7s\n", + "277900K .......... .......... .......... .......... .......... 46% 61.1M 7s\n", + "277950K .......... .......... .......... .......... .......... 46% 59.7M 7s\n", + "278000K .......... .......... .......... .......... .......... 46% 23.5M 7s\n", + "278050K .......... .......... .......... .......... .......... 46% 55.5M 7s\n", + "278100K .......... .......... .......... .......... .......... 46% 50.3M 7s\n", + "278150K .......... .......... .......... .......... .......... 46% 49.1M 7s\n", + "278200K .......... .......... .......... .......... .......... 46% 25.8M 7s\n", + "278250K .......... .......... .......... .......... .......... 46% 57.7M 7s\n", + "278300K .......... .......... .......... .......... .......... 46% 68.1M 7s\n", + "278350K .......... .......... .......... .......... .......... 46% 23.0M 7s\n", + "278400K .......... .......... .......... .......... .......... 46% 46.1M 7s\n", + "278450K .......... .......... .......... .......... .......... 46% 60.7M 7s\n", + "278500K .......... .......... .......... .......... .......... 46% 56.3M 7s\n", + "278550K .......... .......... .......... .......... .......... 46% 3.83M 7s\n", + "278600K .......... .......... .......... .......... .......... 46% 58.5M 7s\n", + "278650K .......... .......... .......... .......... .......... 46% 63.9M 7s\n", + "278700K .......... .......... .......... .......... .......... 46% 72.0M 7s\n", + "278750K .......... .......... .......... .......... .......... 46% 70.2M 7s\n", + "278800K .......... .......... .......... .......... .......... 46% 22.3M 7s\n", + "278850K .......... .......... .......... .......... .......... 46% 54.3M 7s\n", + "278900K .......... .......... .......... .......... .......... 46% 72.8M 7s\n", + "278950K .......... .......... .......... .......... .......... 46% 75.8M 7s\n", + "279000K .......... .......... .......... .......... .......... 46% 19.1M 7s\n", + "279050K .......... .......... .......... .......... .......... 46% 58.7M 7s\n", + "279100K .......... .......... .......... .......... .......... 46% 74.3M 7s\n", + "279150K .......... .......... .......... .......... .......... 46% 23.1M 7s\n", + "279200K .......... .......... .......... .......... .......... 46% 56.6M 7s\n", + "279250K .......... .......... .......... .......... .......... 46% 59.2M 7s\n", + "279300K .......... .......... .......... .......... .......... 46% 7.96M 7s\n", + "279350K .......... .......... .......... .......... .......... 46% 71.5M 7s\n", + "279400K .......... .......... .......... .......... .......... 46% 58.8M 7s\n", + "279450K .......... .......... .......... .......... .......... 46% 74.9M 7s\n", + "279500K .......... .......... .......... .......... .......... 47% 74.1M 7s\n", + "279550K .......... .......... .......... .......... .......... 47% 70.8M 7s\n", + "279600K .......... .......... .......... .......... .......... 47% 29.4M 7s\n", + "279650K .......... .......... .......... .......... .......... 47% 57.5M 7s\n", + "279700K .......... .......... .......... .......... .......... 47% 66.6M 7s\n", + "279750K .......... .......... .......... .......... .......... 47% 70.7M 7s\n", + "279800K .......... .......... .......... .......... .......... 47% 19.4M 7s\n", + "279850K .......... .......... .......... .......... .......... 47% 54.6M 7s\n", + "279900K .......... .......... .......... .......... .......... 47% 68.0M 7s\n", + "279950K .......... .......... .......... .......... .......... 47% 72.9M 7s\n", + "280000K .......... .......... .......... .......... .......... 47% 12.4M 7s\n", + "280050K .......... .......... .......... .......... .......... 47% 54.8M 7s\n", + "280100K .......... .......... .......... .......... .......... 47% 53.0M 7s\n", + "280150K .......... .......... .......... .......... .......... 47% 64.7M 7s\n", + "280200K .......... .......... .......... .......... .......... 47% 25.4M 7s\n", + "280250K .......... .......... .......... .......... .......... 47% 52.7M 7s\n", + "280300K .......... .......... .......... .......... .......... 47% 50.8M 7s\n", + "280350K .......... .......... .......... .......... .......... 47% 66.2M 7s\n", + "280400K .......... .......... .......... .......... .......... 47% 31.8M 7s\n", + "280450K .......... .......... .......... .......... .......... 47% 54.8M 7s\n", + "280500K .......... .......... .......... .......... .......... 47% 48.4M 7s\n", + "280550K .......... .......... .......... .......... .......... 47% 65.5M 7s\n", + "280600K .......... .......... .......... .......... .......... 47% 24.9M 7s\n", + "280650K .......... .......... .......... .......... .......... 47% 55.0M 7s\n", + "280700K .......... .......... .......... .......... .......... 47% 55.3M 7s\n", + "280750K .......... .......... .......... .......... .......... 47% 69.2M 7s\n", + "280800K .......... .......... .......... .......... .......... 47% 30.4M 7s\n", + "280850K .......... .......... .......... .......... .......... 47% 50.4M 7s\n", + "280900K .......... .......... .......... .......... .......... 47% 47.9M 7s\n", + "280950K .......... .......... .......... .......... .......... 47% 63.5M 7s\n", + "281000K .......... .......... .......... .......... .......... 47% 31.3M 7s\n", + "281050K .......... .......... .......... .......... .......... 47% 38.0M 7s\n", + "281100K .......... .......... .......... .......... .......... 47% 56.6M 7s\n", + "281150K .......... .......... .......... .......... .......... 47% 54.5M 7s\n", + "281200K .......... .......... .......... .......... .......... 47% 3.86M 7s\n", + "281250K .......... .......... .......... .......... .......... 47% 57.1M 7s\n", + "281300K .......... .......... .......... .......... .......... 47% 67.0M 7s\n", + "281350K .......... .......... .......... .......... .......... 47% 66.6M 7s\n", + "281400K .......... .......... .......... .......... .......... 47% 20.6M 7s\n", + "281450K .......... .......... .......... .......... .......... 47% 47.9M 7s\n", + "281500K .......... .......... .......... .......... .......... 47% 56.5M 7s\n", + "281550K .......... .......... .......... .......... .......... 47% 70.5M 7s\n", + "281600K .......... .......... .......... .......... .......... 47% 58.2M 7s\n", + "281650K .......... .......... .......... .......... .......... 47% 27.1M 7s\n", + "281700K .......... .......... .......... .......... .......... 47% 49.0M 7s\n", + "281750K .......... .......... .......... .......... .......... 47% 66.6M 7s\n", + "281800K .......... .......... .......... .......... .......... 47% 57.4M 7s\n", + "281850K .......... .......... .......... .......... .......... 47% 30.7M 7s\n", + "281900K .......... .......... .......... .......... .......... 47% 47.4M 7s\n", + "281950K .......... .......... .......... .......... .......... 47% 55.5M 7s\n", + "282000K .......... .......... .......... .......... .......... 47% 56.0M 7s\n", + "282050K .......... .......... .......... .......... .......... 47% 25.7M 7s\n", + "282100K .......... .......... .......... .......... .......... 47% 29.9M 7s\n", + "282150K .......... .......... .......... .......... .......... 47% 40.7M 7s\n", + "282200K .......... .......... .......... .......... .......... 47% 35.5M 7s\n", + "282250K .......... .......... .......... .......... .......... 47% 37.2M 7s\n", + "282300K .......... .......... .......... .......... .......... 47% 34.8M 7s\n", + "282350K .......... .......... .......... .......... .......... 47% 40.4M 7s\n", + "282400K .......... .......... .......... .......... .......... 47% 38.5M 7s\n", + "282450K .......... .......... .......... .......... .......... 47% 37.2M 7s\n", + "282500K .......... .......... .......... .......... .......... 47% 40.8M 7s\n", + "282550K .......... .......... .......... .......... .......... 47% 49.2M 7s\n", + "282600K .......... .......... .......... .......... .......... 47% 34.2M 7s\n", + "282650K .......... .......... .......... .......... .......... 47% 42.7M 7s\n", + "282700K .......... .......... .......... .......... .......... 47% 46.0M 7s\n", + "282750K .......... .......... .......... .......... .......... 47% 50.4M 7s\n", + "282800K .......... .......... .......... .......... .......... 47% 35.4M 7s\n", + "282850K .......... .......... .......... .......... .......... 47% 35.1M 7s\n", + "282900K .......... .......... .......... .......... .......... 47% 46.3M 7s\n", + "282950K .......... .......... .......... .......... .......... 47% 46.6M 7s\n", + "283000K .......... .......... .......... .......... .......... 47% 3.60M 7s\n", + "283050K .......... .......... .......... .......... .......... 47% 56.9M 7s\n", + "283100K .......... .......... .......... .......... .......... 47% 55.7M 7s\n", + "283150K .......... .......... .......... .......... .......... 47% 42.0M 7s\n", + "283200K .......... .......... .......... .......... .......... 47% 34.3M 7s\n", + "283250K .......... .......... .......... .......... .......... 47% 36.3M 7s\n", + "283300K .......... .......... .......... .......... .......... 47% 36.9M 7s\n", + "283350K .......... .......... .......... .......... .......... 47% 40.6M 7s\n", + "283400K .......... .......... .......... .......... .......... 47% 55.7M 7s\n", + "283450K .......... .......... .......... .......... .......... 47% 71.4M 7s\n", + "283500K .......... .......... .......... .......... .......... 47% 67.9M 7s\n", + "283550K .......... .......... .......... .......... .......... 47% 55.3M 7s\n", + "283600K .......... .......... .......... .......... .......... 47% 48.8M 7s\n", + "283650K .......... .......... .......... .......... .......... 47% 53.0M 7s\n", + "283700K .......... .......... .......... .......... .......... 47% 66.2M 7s\n", + "283750K .......... .......... .......... .......... .......... 47% 68.0M 7s\n", + "283800K .......... .......... .......... .......... .......... 47% 25.7M 7s\n", + "283850K .......... .......... .......... .......... .......... 47% 55.0M 7s\n", + "283900K .......... .......... .......... .......... .......... 47% 58.8M 7s\n", + "283950K .......... .......... .......... .......... .......... 47% 68.8M 7s\n", + "284000K .......... .......... .......... .......... .......... 47% 30.5M 7s\n", + "284050K .......... .......... .......... .......... .......... 47% 38.4M 7s\n", + "284100K .......... .......... .......... .......... .......... 47% 67.6M 7s\n", + "284150K .......... .......... .......... .......... .......... 47% 59.1M 7s\n", + "284200K .......... .......... .......... .......... .......... 47% 45.7M 7s\n", + "284250K .......... .......... .......... .......... .......... 47% 30.4M 7s\n", + "284300K .......... .......... .......... .......... .......... 47% 50.0M 7s\n", + "284350K .......... .......... .......... .......... .......... 47% 60.1M 7s\n", + "284400K .......... .......... .......... .......... .......... 47% 3.83M 7s\n", + "284450K .......... .......... .......... .......... .......... 47% 65.6M 7s\n", + "284500K .......... .......... .......... .......... .......... 47% 74.5M 7s\n", + "284550K .......... .......... .......... .......... .......... 47% 78.9M 7s\n", + "284600K .......... .......... .......... .......... .......... 47% 62.0M 7s\n", + "284650K .......... .......... .......... .......... .......... 47% 25.9M 7s\n", + "284700K .......... .......... .......... .......... .......... 47% 53.1M 7s\n", + "284750K .......... .......... .......... .......... .......... 47% 57.4M 7s\n", + "284800K .......... .......... .......... .......... .......... 47% 72.8M 7s\n", + "284850K .......... .......... .......... .......... .......... 47% 73.4M 7s\n", + "284900K .......... .......... .......... .......... .......... 47% 25.0M 7s\n", + "284950K .......... .......... .......... .......... .......... 47% 47.3M 7s\n", + "285000K .......... .......... .......... .......... .......... 47% 56.5M 7s\n", + "285050K .......... .......... .......... .......... .......... 47% 69.3M 7s\n", + "285100K .......... .......... .......... .......... .......... 47% 30.6M 7s\n", + "285150K .......... .......... .......... .......... .......... 47% 43.3M 7s\n", + "285200K .......... .......... .......... .......... .......... 47% 55.1M 7s\n", + "285250K .......... .......... .......... .......... .......... 47% 67.1M 7s\n", + "285300K .......... .......... .......... .......... .......... 47% 66.6M 7s\n", + "285350K .......... .......... .......... .......... .......... 47% 34.1M 7s\n", + "285400K .......... .......... .......... .......... .......... 47% 40.7M 7s\n", + "285450K .......... .......... .......... .......... .......... 48% 66.8M 7s\n", + "285500K .......... .......... .......... .......... .......... 48% 67.9M 7s\n", + "285550K .......... .......... .......... .......... .......... 48% 37.3M 7s\n", + "285600K .......... .......... .......... .......... .......... 48% 43.9M 7s\n", + "285650K .......... .......... .......... .......... .......... 48% 54.2M 7s\n", + "285700K .......... .......... .......... .......... .......... 48% 67.8M 7s\n", + "285750K .......... .......... .......... .......... .......... 48% 68.2M 7s\n", + "285800K .......... .......... .......... .......... .......... 48% 25.6M 7s\n", + "285850K .......... .......... .......... .......... .......... 48% 46.8M 7s\n", + "285900K .......... .......... .......... .......... .......... 48% 70.0M 7s\n", + "285950K .......... .......... .......... .......... .......... 48% 65.0M 7s\n", + "286000K .......... .......... .......... .......... .......... 48% 31.3M 7s\n", + "286050K .......... .......... .......... .......... .......... 48% 56.0M 7s\n", + "286100K .......... .......... .......... .......... .......... 48% 50.8M 7s\n", + "286150K .......... .......... .......... .......... .......... 48% 68.3M 7s\n", + "286200K .......... .......... .......... .......... .......... 48% 57.4M 7s\n", + "286250K .......... .......... .......... .......... .......... 48% 33.3M 7s\n", + "286300K .......... .......... .......... .......... .......... 48% 30.2M 7s\n", + "286350K .......... .......... .......... .......... .......... 48% 63.0M 7s\n", + "286400K .......... .......... .......... .......... .......... 48% 57.5M 7s\n", + "286450K .......... .......... .......... .......... .......... 48% 38.3M 7s\n", + "286500K .......... .......... .......... .......... .......... 48% 33.0M 7s\n", + "286550K .......... .......... .......... .......... .......... 48% 60.3M 7s\n", + "286600K .......... .......... .......... .......... .......... 48% 59.2M 7s\n", + "286650K .......... .......... .......... .......... .......... 48% 27.9M 7s\n", + "286700K .......... .......... .......... .......... .......... 48% 29.2M 7s\n", + "286750K .......... .......... .......... .......... .......... 48% 63.4M 7s\n", + "286800K .......... .......... .......... .......... .......... 48% 41.6M 7s\n", + "286850K .......... .......... .......... .......... .......... 48% 34.1M 7s\n", + "286900K .......... .......... .......... .......... .......... 48% 36.4M 7s\n", + "286950K .......... .......... .......... .......... .......... 48% 60.2M 7s\n", + "287000K .......... .......... .......... .......... .......... 48% 35.3M 7s\n", + "287050K .......... .......... .......... .......... .......... 48% 22.2M 7s\n", + "287100K .......... .......... .......... .......... .......... 48% 56.7M 7s\n", + "287150K .......... .......... .......... .......... .......... 48% 35.3M 7s\n", + "287200K .......... .......... .......... .......... .......... 48% 36.2M 7s\n", + "287250K .......... .......... .......... .......... .......... 48% 40.5M 7s\n", + "287300K .......... .......... .......... .......... .......... 48% 48.8M 7s\n", + "287350K .......... .......... .......... .......... .......... 48% 35.1M 7s\n", + "287400K .......... .......... .......... .......... .......... 48% 24.8M 7s\n", + "287450K .......... .......... .......... .......... .......... 48% 49.7M 7s\n", + "287500K .......... .......... .......... .......... .......... 48% 3.62M 7s\n", + "287550K .......... .......... .......... .......... .......... 48% 61.8M 7s\n", + "287600K .......... .......... .......... .......... .......... 48% 70.6M 7s\n", + "287650K .......... .......... .......... .......... .......... 48% 88.4M 7s\n", + "287700K .......... .......... .......... .......... .......... 48% 4.25M 7s\n", + "287750K .......... .......... .......... .......... .......... 48% 26.8M 7s\n", + "287800K .......... .......... .......... .......... .......... 48% 35.6M 7s\n", + "287850K .......... .......... .......... .......... .......... 48% 56.1M 7s\n", + "287900K .......... .......... .......... .......... .......... 48% 51.5M 7s\n", + "287950K .......... .......... .......... .......... .......... 48% 53.1M 7s\n", + "288000K .......... .......... .......... .......... .......... 48% 37.6M 7s\n", + "288050K .......... .......... .......... .......... .......... 48% 66.3M 7s\n", + "288100K .......... .......... .......... .......... .......... 48% 64.6M 7s\n", + "288150K .......... .......... .......... .......... .......... 48% 63.6M 7s\n", + "288200K .......... .......... .......... .......... .......... 48% 41.9M 7s\n", + "288250K .......... .......... .......... .......... .......... 48% 50.5M 7s\n", + "288300K .......... .......... .......... .......... .......... 48% 50.1M 7s\n", + "288350K .......... .......... .......... .......... .......... 48% 58.5M 7s\n", + "288400K .......... .......... .......... .......... .......... 48% 57.5M 7s\n", + "288450K .......... .......... .......... .......... .......... 48% 64.9M 7s\n", + "288500K .......... .......... .......... .......... .......... 48% 49.8M 7s\n", + "288550K .......... .......... .......... .......... .......... 48% 53.2M 7s\n", + "288600K .......... .......... .......... .......... .......... 48% 35.6M 7s\n", + "288650K .......... .......... .......... .......... .......... 48% 65.3M 7s\n", + "288700K .......... .......... .......... .......... .......... 48% 71.2M 7s\n", + "288750K .......... .......... .......... .......... .......... 48% 53.8M 7s\n", + "288800K .......... .......... .......... .......... .......... 48% 48.8M 7s\n", + "288850K .......... .......... .......... .......... .......... 48% 61.2M 7s\n", + "288900K .......... .......... .......... .......... .......... 48% 52.8M 7s\n", + "288950K .......... .......... .......... .......... .......... 48% 64.1M 7s\n", + "289000K .......... .......... .......... .......... .......... 48% 46.3M 7s\n", + "289050K .......... .......... .......... .......... .......... 48% 46.3M 7s\n", + "289100K .......... .......... .......... .......... .......... 48% 12.7M 7s\n", + "289150K .......... .......... .......... .......... .......... 48% 52.1M 7s\n", + "289200K .......... .......... .......... .......... .......... 48% 53.4M 7s\n", + "289250K .......... .......... .......... .......... .......... 48% 68.9M 7s\n", + "289300K .......... .......... .......... .......... .......... 48% 65.1M 7s\n", + "289350K .......... .......... .......... .......... .......... 48% 66.8M 7s\n", + "289400K .......... .......... .......... .......... .......... 48% 49.2M 7s\n", + "289450K .......... .......... .......... .......... .......... 48% 49.1M 7s\n", + "289500K .......... .......... .......... .......... .......... 48% 65.5M 7s\n", + "289550K .......... .......... .......... .......... .......... 48% 42.0M 7s\n", + "289600K .......... .......... .......... .......... .......... 48% 21.1M 7s\n", + "289650K .......... .......... .......... .......... .......... 48% 40.1M 7s\n", + "289700K .......... .......... .......... .......... .......... 48% 50.2M 7s\n", + "289750K .......... .......... .......... .......... .......... 48% 50.6M 7s\n", + "289800K .......... .......... .......... .......... .......... 48% 26.1M 7s\n", + "289850K .......... .......... .......... .......... .......... 48% 37.6M 7s\n", + "289900K .......... .......... .......... .......... .......... 48% 23.9M 7s\n", + "289950K .......... .......... .......... .......... .......... 48% 34.5M 7s\n", + "290000K .......... .......... .......... .......... .......... 48% 33.5M 7s\n", + "290050K .......... .......... .......... .......... .......... 48% 42.4M 7s\n", + "290100K .......... .......... .......... .......... .......... 48% 39.8M 7s\n", + "290150K .......... .......... .......... .......... .......... 48% 31.2M 7s\n", + "290200K .......... .......... .......... .......... .......... 48% 35.0M 7s\n", + "290250K .......... .......... .......... .......... .......... 48% 78.1M 7s\n", + "290300K .......... .......... .......... .......... .......... 48% 70.2M 7s\n", + "290350K .......... .......... .......... .......... .......... 48% 67.8M 7s\n", + "290400K .......... .......... .......... .......... .......... 48% 54.9M 7s\n", + "290450K .......... .......... .......... .......... .......... 48% 56.3M 7s\n", + "290500K .......... .......... .......... .......... .......... 48% 72.0M 7s\n", + "290550K .......... .......... .......... .......... .......... 48% 70.3M 7s\n", + "290600K .......... .......... .......... .......... .......... 48% 37.8M 7s\n", + "290650K .......... .......... .......... .......... .......... 48% 42.2M 7s\n", + "290700K .......... .......... .......... .......... .......... 48% 60.6M 7s\n", + "290750K .......... .......... .......... .......... .......... 48% 68.1M 7s\n", + "290800K .......... .......... .......... .......... .......... 48% 53.7M 7s\n", + "290850K .......... .......... .......... .......... .......... 48% 75.0M 7s\n", + "290900K .......... .......... .......... .......... .......... 48% 55.4M 7s\n", + "290950K .......... .......... .......... .......... .......... 48% 51.4M 7s\n", + "291000K .......... .......... .......... .......... .......... 48% 57.0M 7s\n", + "291050K .......... .......... .......... .......... .......... 48% 60.0M 7s\n", + "291100K .......... .......... .......... .......... .......... 48% 25.6M 7s\n", + "291150K .......... .......... .......... .......... .......... 48% 53.3M 7s\n", + "291200K .......... .......... .......... .......... .......... 48% 61.2M 7s\n", + "291250K .......... .......... .......... .......... .......... 48% 37.4M 7s\n", + "291300K .......... .......... .......... .......... .......... 48% 21.4M 7s\n", + "291350K .......... .......... .......... .......... .......... 48% 45.2M 7s\n", + "291400K .......... .......... .......... .......... .......... 49% 54.8M 7s\n", + "291450K .......... .......... .......... .......... .......... 49% 29.5M 7s\n", + "291500K .......... .......... .......... .......... .......... 49% 37.6M 7s\n", + "291550K .......... .......... .......... .......... .......... 49% 36.2M 7s\n", + "291600K .......... .......... .......... .......... .......... 49% 59.8M 7s\n", + "291650K .......... .......... .......... .......... .......... 49% 33.9M 7s\n", + "291700K .......... .......... .......... .......... .......... 49% 48.0M 7s\n", + "291750K .......... .......... .......... .......... .......... 49% 59.7M 7s\n", + "291800K .......... .......... .......... .......... .......... 49% 27.3M 7s\n", + "291850K .......... .......... .......... .......... .......... 49% 7.19M 7s\n", + "291900K .......... .......... .......... .......... .......... 49% 65.7M 7s\n", + "291950K .......... .......... .......... .......... .......... 49% 72.9M 7s\n", + "292000K .......... .......... .......... .......... .......... 49% 63.6M 7s\n", + "292050K .......... .......... .......... .......... .......... 49% 15.0M 7s\n", + "292100K .......... .......... .......... .......... .......... 49% 49.7M 7s\n", + "292150K .......... .......... .......... .......... .......... 49% 50.5M 7s\n", + "292200K .......... .......... .......... .......... .......... 49% 36.0M 7s\n", + "292250K .......... .......... .......... .......... .......... 49% 34.4M 7s\n", + "292300K .......... .......... .......... .......... .......... 49% 44.0M 7s\n", + "292350K .......... .......... .......... .......... .......... 49% 54.9M 7s\n", + "292400K .......... .......... .......... .......... .......... 49% 29.6M 7s\n", + "292450K .......... .......... .......... .......... .......... 49% 42.5M 7s\n", + "292500K .......... .......... .......... .......... .......... 49% 44.4M 7s\n", + "292550K .......... .......... .......... .......... .......... 49% 46.8M 7s\n", + "292600K .......... .......... .......... .......... .......... 49% 15.4M 7s\n", + "292650K .......... .......... .......... .......... .......... 49% 30.2M 7s\n", + "292700K .......... .......... .......... .......... .......... 49% 44.9M 7s\n", + "292750K .......... .......... .......... .......... .......... 49% 45.9M 7s\n", + "292800K .......... .......... .......... .......... .......... 49% 33.5M 7s\n", + "292850K .......... .......... .......... .......... .......... 49% 39.3M 7s\n", + "292900K .......... .......... .......... .......... .......... 49% 53.1M 7s\n", + "292950K .......... .......... .......... .......... .......... 49% 46.5M 7s\n", + "293000K .......... .......... .......... .......... .......... 49% 31.4M 7s\n", + "293050K .......... .......... .......... .......... .......... 49% 44.6M 7s\n", + "293100K .......... .......... .......... .......... .......... 49% 54.9M 7s\n", + "293150K .......... .......... .......... .......... .......... 49% 41.9M 7s\n", + "293200K .......... .......... .......... .......... .......... 49% 36.2M 7s\n", + "293250K .......... .......... .......... .......... .......... 49% 31.2M 7s\n", + "293300K .......... .......... .......... .......... .......... 49% 46.1M 7s\n", + "293350K .......... .......... .......... .......... .......... 49% 41.1M 7s\n", + "293400K .......... .......... .......... .......... .......... 49% 33.9M 7s\n", + "293450K .......... .......... .......... .......... .......... 49% 42.8M 7s\n", + "293500K .......... .......... .......... .......... .......... 49% 51.9M 7s\n", + "293550K .......... .......... .......... .......... .......... 49% 47.8M 7s\n", + "293600K .......... .......... .......... .......... .......... 49% 39.5M 7s\n", + "293650K .......... .......... .......... .......... .......... 49% 39.8M 7s\n", + "293700K .......... .......... .......... .......... .......... 49% 41.7M 7s\n", + "293750K .......... .......... .......... .......... .......... 49% 45.0M 7s\n", + "293800K .......... .......... .......... .......... .......... 49% 34.2M 7s\n", + "293850K .......... .......... .......... .......... .......... 49% 42.4M 7s\n", + "293900K .......... .......... .......... .......... .......... 49% 38.6M 7s\n", + "293950K .......... .......... .......... .......... .......... 49% 40.9M 7s\n", + "294000K .......... .......... .......... .......... .......... 49% 39.5M 7s\n", + "294050K .......... .......... .......... .......... .......... 49% 37.1M 7s\n", + "294100K .......... .......... .......... .......... .......... 49% 43.3M 7s\n", + "294150K .......... .......... .......... .......... .......... 49% 48.7M 7s\n", + "294200K .......... .......... .......... .......... .......... 49% 33.0M 7s\n", + "294250K .......... .......... .......... .......... .......... 49% 42.7M 7s\n", + "294300K .......... .......... .......... .......... .......... 49% 49.3M 7s\n", + "294350K .......... .......... .......... .......... .......... 49% 45.4M 7s\n", + "294400K .......... .......... .......... .......... .......... 49% 34.2M 7s\n", + "294450K .......... .......... .......... .......... .......... 49% 42.0M 7s\n", + "294500K .......... .......... .......... .......... .......... 49% 43.8M 7s\n", + "294550K .......... .......... .......... .......... .......... 49% 37.3M 7s\n", + "294600K .......... .......... .......... .......... .......... 49% 28.9M 7s\n", + "294650K .......... .......... .......... .......... .......... 49% 45.1M 7s\n", + "294700K .......... .......... .......... .......... .......... 49% 42.6M 7s\n", + "294750K .......... .......... .......... .......... .......... 49% 35.7M 7s\n", + "294800K .......... .......... .......... .......... .......... 49% 39.2M 7s\n", + "294850K .......... .......... .......... .......... .......... 49% 44.1M 7s\n", + "294900K .......... .......... .......... .......... .......... 49% 40.9M 7s\n", + "294950K .......... .......... .......... .......... .......... 49% 35.8M 7s\n", + "295000K .......... .......... .......... .......... .......... 49% 31.0M 7s\n", + "295050K .......... .......... .......... .......... .......... 49% 40.9M 7s\n", + "295100K .......... .......... .......... .......... .......... 49% 33.8M 7s\n", + "295150K .......... .......... .......... .......... .......... 49% 40.5M 7s\n", + "295200K .......... .......... .......... .......... .......... 49% 33.8M 7s\n", + "295250K .......... .......... .......... .......... .......... 49% 37.6M 7s\n", + "295300K .......... .......... .......... .......... .......... 49% 48.1M 7s\n", + "295350K .......... .......... .......... .......... .......... 49% 48.5M 7s\n", + "295400K .......... .......... .......... .......... .......... 49% 39.0M 7s\n", + "295450K .......... .......... .......... .......... .......... 49% 42.7M 7s\n", + "295500K .......... .......... .......... .......... .......... 49% 42.9M 7s\n", + "295550K .......... .......... .......... .......... .......... 49% 46.4M 7s\n", + "295600K .......... .......... .......... .......... .......... 49% 41.3M 7s\n", + "295650K .......... .......... .......... .......... .......... 49% 54.9M 7s\n", + "295700K .......... .......... .......... .......... .......... 49% 58.2M 7s\n", + "295750K .......... .......... .......... .......... .......... 49% 62.9M 7s\n", + "295800K .......... .......... .......... .......... .......... 49% 51.6M 7s\n", + "295850K .......... .......... .......... .......... .......... 49% 59.4M 7s\n", + "295900K .......... .......... .......... .......... .......... 49% 66.5M 7s\n", + "295950K .......... .......... .......... .......... .......... 49% 49.3M 7s\n", + "296000K .......... .......... .......... .......... .......... 49% 54.5M 7s\n", + "296050K .......... .......... .......... .......... .......... 49% 51.6M 7s\n", + "296100K .......... .......... .......... .......... .......... 49% 53.5M 7s\n", + "296150K .......... .......... .......... .......... .......... 49% 60.7M 7s\n", + "296200K .......... .......... .......... .......... .......... 49% 41.8M 7s\n", + "296250K .......... .......... .......... .......... .......... 49% 31.2M 7s\n", + "296300K .......... .......... .......... .......... .......... 49% 48.5M 6s\n", + "296350K .......... .......... .......... .......... .......... 49% 48.5M 6s\n", + "296400K .......... .......... .......... .......... .......... 49% 51.4M 6s\n", + "296450K .......... .......... .......... .......... .......... 49% 30.6M 6s\n", + "296500K .......... .......... .......... .......... .......... 49% 54.7M 6s\n", + "296550K .......... .......... .......... .......... .......... 49% 47.1M 6s\n", + "296600K .......... .......... .......... .......... .......... 49% 43.5M 6s\n", + "296650K .......... .......... .......... .......... .......... 49% 37.9M 6s\n", + "296700K .......... .......... .......... .......... .......... 49% 56.8M 6s\n", + "296750K .......... .......... .......... .......... .......... 49% 43.4M 6s\n", + "296800K .......... .......... .......... .......... .......... 49% 48.7M 6s\n", + "296850K .......... .......... .......... .......... .......... 49% 73.6M 6s\n", + "296900K .......... .......... .......... .......... .......... 49% 31.7M 6s\n", + "296950K .......... .......... .......... .......... .......... 49% 55.5M 6s\n", + "297000K .......... .......... .......... .......... .......... 49% 3.86M 6s\n", + "297050K .......... .......... .......... .......... .......... 49% 72.3M 6s\n", + "297100K .......... .......... .......... .......... .......... 49% 64.8M 6s\n", + "297150K .......... .......... .......... .......... .......... 49% 73.6M 6s\n", + "297200K .......... .......... .......... .......... .......... 49% 61.0M 6s\n", + "297250K .......... .......... .......... .......... .......... 49% 12.1M 6s\n", + "297300K .......... .......... .......... .......... .......... 49% 52.5M 6s\n", + "297350K .......... .......... .......... .......... .......... 50% 67.9M 6s\n", + "297400K .......... .......... .......... .......... .......... 50% 57.7M 6s\n", + "297450K .......... .......... .......... .......... .......... 50% 30.3M 6s\n", + "297500K .......... .......... .......... .......... .......... 50% 45.8M 6s\n", + "297550K .......... .......... .......... .......... .......... 50% 68.5M 6s\n", + "297600K .......... .......... .......... .......... .......... 50% 60.2M 6s\n", + "297650K .......... .......... .......... .......... .......... 50% 28.2M 6s\n", + "297700K .......... .......... .......... .......... .......... 50% 46.4M 6s\n", + "297750K .......... .......... .......... .......... .......... 50% 65.4M 6s\n", + "297800K .......... .......... .......... .......... .......... 50% 56.1M 6s\n", + "297850K .......... .......... .......... .......... .......... 50% 29.6M 6s\n", + "297900K .......... .......... .......... .......... .......... 50% 52.0M 6s\n", + "297950K .......... .......... .......... .......... .......... 50% 58.1M 6s\n", + "298000K .......... .......... .......... .......... .......... 50% 63.0M 6s\n", + "298050K .......... .......... .......... .......... .......... 50% 30.0M 6s\n", + "298100K .......... .......... .......... .......... .......... 50% 51.6M 6s\n", + "298150K .......... .......... .......... .......... .......... 50% 59.8M 6s\n", + "298200K .......... .......... .......... .......... .......... 50% 51.5M 6s\n", + "298250K .......... .......... .......... .......... .......... 50% 27.5M 6s\n", + "298300K .......... .......... .......... .......... .......... 50% 53.3M 6s\n", + "298350K .......... .......... .......... .......... .......... 50% 69.2M 6s\n", + "298400K .......... .......... .......... .......... .......... 50% 61.5M 6s\n", + "298450K .......... .......... .......... .......... .......... 50% 65.4M 6s\n", + "298500K .......... .......... .......... .......... .......... 50% 21.2M 6s\n", + "298550K .......... .......... .......... .......... .......... 50% 46.7M 6s\n", + "298600K .......... .......... .......... .......... .......... 50% 47.5M 6s\n", + "298650K .......... .......... .......... .......... .......... 50% 56.7M 6s\n", + "298700K .......... .......... .......... .......... .......... 50% 51.8M 6s\n", + "298750K .......... .......... .......... .......... .......... 50% 48.4M 6s\n", + "298800K .......... .......... .......... .......... .......... 50% 45.0M 6s\n", + "298850K .......... .......... .......... .......... .......... 50% 59.1M 6s\n", + "298900K .......... .......... .......... .......... .......... 50% 50.9M 6s\n", + "298950K .......... .......... .......... .......... .......... 50% 42.4M 6s\n", + "299000K .......... .......... .......... .......... .......... 50% 38.9M 6s\n", + "299050K .......... .......... .......... .......... .......... 50% 50.4M 6s\n", + "299100K .......... .......... .......... .......... .......... 50% 53.8M 6s\n", + "299150K .......... .......... .......... .......... .......... 50% 41.5M 6s\n", + "299200K .......... .......... .......... .......... .......... 50% 39.9M 6s\n", + "299250K .......... .......... .......... .......... .......... 50% 63.0M 6s\n", + "299300K .......... .......... .......... .......... .......... 50% 66.8M 6s\n", + "299350K .......... .......... .......... .......... .......... 50% 45.8M 6s\n", + "299400K .......... .......... .......... .......... .......... 50% 30.1M 6s\n", + "299450K .......... .......... .......... .......... .......... 50% 65.9M 6s\n", + "299500K .......... .......... .......... .......... .......... 50% 68.4M 6s\n", + "299550K .......... .......... .......... .......... .......... 50% 45.5M 6s\n", + "299600K .......... .......... .......... .......... .......... 50% 27.6M 6s\n", + "299650K .......... .......... .......... .......... .......... 50% 36.4M 6s\n", + "299700K .......... .......... .......... .......... .......... 50% 70.9M 6s\n", + "299750K .......... .......... .......... .......... .......... 50% 50.1M 6s\n", + "299800K .......... .......... .......... .......... .......... 50% 28.4M 6s\n", + "299850K .......... .......... .......... .......... .......... 50% 38.0M 6s\n", + "299900K .......... .......... .......... .......... .......... 50% 44.8M 6s\n", + "299950K .......... .......... .......... .......... .......... 50% 60.5M 6s\n", + "300000K .......... .......... .......... .......... .......... 50% 38.4M 6s\n", + "300050K .......... .......... .......... .......... .......... 50% 34.4M 6s\n", + "300100K .......... .......... .......... .......... .......... 50% 47.3M 6s\n", + "300150K .......... .......... .......... .......... .......... 50% 51.1M 6s\n", + "300200K .......... .......... .......... .......... .......... 50% 40.9M 6s\n", + "300250K .......... .......... .......... .......... .......... 50% 35.1M 6s\n", + "300300K .......... .......... .......... .......... .......... 50% 47.4M 6s\n", + "300350K .......... .......... .......... .......... .......... 50% 46.0M 6s\n", + "300400K .......... .......... .......... .......... .......... 50% 38.6M 6s\n", + "300450K .......... .......... .......... .......... .......... 50% 55.4M 6s\n", + "300500K .......... .......... .......... .......... .......... 50% 50.2M 6s\n", + "300550K .......... .......... .......... .......... .......... 50% 47.4M 6s\n", + "300600K .......... .......... .......... .......... .......... 50% 51.8M 6s\n", + "300650K .......... .......... .......... .......... .......... 50% 51.2M 6s\n", + "300700K .......... .......... .......... .......... .......... 50% 4.06M 6s\n", + "300750K .......... .......... .......... .......... .......... 50% 66.1M 6s\n", + "300800K .......... .......... .......... .......... .......... 50% 61.9M 6s\n", + "300850K .......... .......... .......... .......... .......... 50% 67.8M 6s\n", + "300900K .......... .......... .......... .......... .......... 50% 72.5M 6s\n", + "300950K .......... .......... .......... .......... .......... 50% 25.4M 6s\n", + "301000K .......... .......... .......... .......... .......... 50% 35.4M 6s\n", + "301050K .......... .......... .......... .......... .......... 50% 73.8M 6s\n", + "301100K .......... .......... .......... .......... .......... 50% 71.7M 6s\n", + "301150K .......... .......... .......... .......... .......... 50% 35.8M 6s\n", + "301200K .......... .......... .......... .......... .......... 50% 31.5M 6s\n", + "301250K .......... .......... .......... .......... .......... 50% 57.8M 6s\n", + "301300K .......... .......... .......... .......... .......... 50% 72.8M 6s\n", + "301350K .......... .......... .......... .......... .......... 50% 53.3M 6s\n", + "301400K .......... .......... .......... .......... .......... 50% 23.1M 6s\n", + "301450K .......... .......... .......... .......... .......... 50% 52.5M 6s\n", + "301500K .......... .......... .......... .......... .......... 50% 66.8M 6s\n", + "301550K .......... .......... .......... .......... .......... 50% 51.2M 6s\n", + "301600K .......... .......... .......... .......... .......... 50% 39.2M 6s\n", + "301650K .......... .......... .......... .......... .......... 50% 34.6M 6s\n", + "301700K .......... .......... .......... .......... .......... 50% 74.4M 6s\n", + "301750K .......... .......... .......... .......... .......... 50% 56.7M 6s\n", + "301800K .......... .......... .......... .......... .......... 50% 44.7M 6s\n", + "301850K .......... .......... .......... .......... .......... 50% 30.3M 6s\n", + "301900K .......... .......... .......... .......... .......... 50% 53.6M 6s\n", + "301950K .......... .......... .......... .......... .......... 50% 61.3M 6s\n", + "302000K .......... .......... .......... .......... .......... 50% 40.7M 6s\n", + "302050K .......... .......... .......... .......... .......... 50% 51.4M 6s\n", + "302100K .......... .......... .......... .......... .......... 50% 45.7M 6s\n", + "302150K .......... .......... .......... .......... .......... 50% 41.0M 6s\n", + "302200K .......... .......... .......... .......... .......... 50% 43.7M 6s\n", + "302250K .......... .......... .......... .......... .......... 50% 41.0M 6s\n", + "302300K .......... .......... .......... .......... .......... 50% 52.8M 6s\n", + "302350K .......... .......... .......... .......... .......... 50% 41.2M 6s\n", + "302400K .......... .......... .......... .......... .......... 50% 37.0M 6s\n", + "302450K .......... .......... .......... .......... .......... 50% 40.0M 6s\n", + "302500K .......... .......... .......... .......... .......... 50% 43.3M 6s\n", + "302550K .......... .......... .......... .......... .......... 50% 41.5M 6s\n", + "302600K .......... .......... .......... .......... .......... 50% 34.9M 6s\n", + "302650K .......... .......... .......... .......... .......... 50% 40.3M 6s\n", + "302700K .......... .......... .......... .......... .......... 50% 44.9M 6s\n", + "302750K .......... .......... .......... .......... .......... 50% 39.8M 6s\n", + "302800K .......... .......... .......... .......... .......... 50% 43.6M 6s\n", + "302850K .......... .......... .......... .......... .......... 50% 50.7M 6s\n", + "302900K .......... .......... .......... .......... .......... 50% 33.4M 6s\n", + "302950K .......... .......... .......... .......... .......... 50% 33.9M 6s\n", + "303000K .......... .......... .......... .......... .......... 50% 4.13M 6s\n", + "303050K .......... .......... .......... .......... .......... 50% 67.6M 6s\n", + "303100K .......... .......... .......... .......... .......... 50% 70.5M 6s\n", + "303150K .......... .......... .......... .......... .......... 50% 67.4M 6s\n", + "303200K .......... .......... .......... .......... .......... 50% 59.0M 6s\n", + "303250K .......... .......... .......... .......... .......... 50% 68.1M 6s\n", + "303300K .......... .......... .......... .......... .......... 51% 29.5M 6s\n", + "303350K .......... .......... .......... .......... .......... 51% 43.0M 6s\n", + "303400K .......... .......... .......... .......... .......... 51% 56.3M 6s\n", + "303450K .......... .......... .......... .......... .......... 51% 67.7M 6s\n", + "303500K .......... .......... .......... .......... .......... 51% 39.4M 6s\n", + "303550K .......... .......... .......... .......... .......... 51% 31.2M 6s\n", + "303600K .......... .......... .......... .......... .......... 51% 53.9M 6s\n", + "303650K .......... .......... .......... .......... .......... 51% 75.4M 6s\n", + "303700K .......... .......... .......... .......... .......... 51% 52.2M 6s\n", + "303750K .......... .......... .......... .......... .......... 51% 39.8M 6s\n", + "303800K .......... .......... .......... .......... .......... 51% 37.5M 6s\n", + "303850K .......... .......... .......... .......... .......... 51% 69.5M 6s\n", + "303900K .......... .......... .......... .......... .......... 51% 72.5M 6s\n", + "303950K .......... .......... .......... .......... .......... 51% 55.0M 6s\n", + "304000K .......... .......... .......... .......... .......... 51% 32.0M 6s\n", + "304050K .......... .......... .......... .......... .......... 51% 50.3M 6s\n", + "304100K .......... .......... .......... .......... .......... 51% 69.3M 6s\n", + "304150K .......... .......... .......... .......... .......... 51% 70.4M 6s\n", + "304200K .......... .......... .......... .......... .......... 51% 51.3M 6s\n", + "304250K .......... .......... .......... .......... .......... 51% 48.2M 6s\n", + "304300K .......... .......... .......... .......... .......... 51% 46.2M 6s\n", + "304350K .......... .......... .......... .......... .......... 51% 55.1M 6s\n", + "304400K .......... .......... .......... .......... .......... 51% 34.3M 6s\n", + "304450K .......... .......... .......... .......... .......... 51% 69.8M 6s\n", + "304500K .......... .......... .......... .......... .......... 51% 69.2M 6s\n", + "304550K .......... .......... .......... .......... .......... 51% 32.9M 6s\n", + "304600K .......... .......... .......... .......... .......... 51% 32.4M 6s\n", + "304650K .......... .......... .......... .......... .......... 51% 73.6M 6s\n", + "304700K .......... .......... .......... .......... .......... 51% 67.8M 6s\n", + "304750K .......... .......... .......... .......... .......... 51% 30.4M 6s\n", + "304800K .......... .......... .......... .......... .......... 51% 41.8M 6s\n", + "304850K .......... .......... .......... .......... .......... 51% 49.8M 6s\n", + "304900K .......... .......... .......... .......... .......... 51% 64.1M 6s\n", + "304950K .......... .......... .......... .......... .......... 51% 34.4M 6s\n", + "305000K .......... .......... .......... .......... .......... 51% 28.5M 6s\n", + "305050K .......... .......... .......... .......... .......... 51% 64.0M 6s\n", + "305100K .......... .......... .......... .......... .......... 51% 65.1M 6s\n", + "305150K .......... .......... .......... .......... .......... 51% 36.1M 6s\n", + "305200K .......... .......... .......... .......... .......... 51% 32.7M 6s\n", + "305250K .......... .......... .......... .......... .......... 51% 54.3M 6s\n", + "305300K .......... .......... .......... .......... .......... 51% 59.3M 6s\n", + "305350K .......... .......... .......... .......... .......... 51% 35.8M 6s\n", + "305400K .......... .......... .......... .......... .......... 51% 33.3M 6s\n", + "305450K .......... .......... .......... .......... .......... 51% 51.5M 6s\n", + "305500K .......... .......... .......... .......... .......... 51% 53.1M 6s\n", + "305550K .......... .......... .......... .......... .......... 51% 48.0M 6s\n", + "305600K .......... .......... .......... .......... .......... 51% 37.1M 6s\n", + "305650K .......... .......... .......... .......... .......... 51% 42.7M 6s\n", + "305700K .......... .......... .......... .......... .......... 51% 53.7M 6s\n", + "305750K .......... .......... .......... .......... .......... 51% 40.7M 6s\n", + "305800K .......... .......... .......... .......... .......... 51% 33.3M 6s\n", + "305850K .......... .......... .......... .......... .......... 51% 42.4M 6s\n", + "305900K .......... .......... .......... .......... .......... 51% 51.5M 6s\n", + "305950K .......... .......... .......... .......... .......... 51% 40.4M 6s\n", + "306000K .......... .......... .......... .......... .......... 51% 40.4M 6s\n", + "306050K .......... .......... .......... .......... .......... 51% 44.1M 6s\n", + "306100K .......... .......... .......... .......... .......... 51% 44.7M 6s\n", + "306150K .......... .......... .......... .......... .......... 51% 4.04M 6s\n", + "306200K .......... .......... .......... .......... .......... 51% 58.0M 6s\n", + "306250K .......... .......... .......... .......... .......... 51% 66.0M 6s\n", + "306300K .......... .......... .......... .......... .......... 51% 73.1M 6s\n", + "306350K .......... .......... .......... .......... .......... 51% 73.0M 6s\n", + "306400K .......... .......... .......... .......... .......... 51% 60.0M 6s\n", + "306450K .......... .......... .......... .......... .......... 51% 42.0M 6s\n", + "306500K .......... .......... .......... .......... .......... 51% 31.4M 6s\n", + "306550K .......... .......... .......... .......... .......... 51% 64.0M 6s\n", + "306600K .......... .......... .......... .......... .......... 51% 59.3M 6s\n", + "306650K .......... .......... .......... .......... .......... 51% 52.2M 6s\n", + "306700K .......... .......... .......... .......... .......... 51% 25.7M 6s\n", + "306750K .......... .......... .......... .......... .......... 51% 54.6M 6s\n", + "306800K .......... .......... .......... .......... .......... 51% 60.2M 6s\n", + "306850K .......... .......... .......... .......... .......... 51% 59.6M 6s\n", + "306900K .......... .......... .......... .......... .......... 51% 40.8M 6s\n", + "306950K .......... .......... .......... .......... .......... 51% 33.0M 6s\n", + "307000K .......... .......... .......... .......... .......... 51% 54.6M 6s\n", + "307050K .......... .......... .......... .......... .......... 51% 60.4M 6s\n", + "307100K .......... .......... .......... .......... .......... 51% 59.3M 6s\n", + "307150K .......... .......... .......... .......... .......... 51% 36.6M 6s\n", + "307200K .......... .......... .......... .......... .......... 51% 40.3M 6s\n", + "307250K .......... .......... .......... .......... .......... 51% 75.0M 6s\n", + "307300K .......... .......... .......... .......... .......... 51% 48.6M 6s\n", + "307350K .......... .......... .......... .......... .......... 51% 47.5M 6s\n", + "307400K .......... .......... .......... .......... .......... 51% 27.5M 6s\n", + "307450K .......... .......... .......... .......... .......... 51% 71.3M 6s\n", + "307500K .......... .......... .......... .......... .......... 51% 42.3M 6s\n", + "307550K .......... .......... .......... .......... .......... 51% 56.0M 6s\n", + "307600K .......... .......... .......... .......... .......... 51% 29.1M 6s\n", + "307650K .......... .......... .......... .......... .......... 51% 60.7M 6s\n", + "307700K .......... .......... .......... .......... .......... 51% 43.7M 6s\n", + "307750K .......... .......... .......... .......... .......... 51% 49.7M 6s\n", + "307800K .......... .......... .......... .......... .......... 51% 39.3M 6s\n", + "307850K .......... .......... .......... .......... .......... 51% 37.1M 6s\n", + "307900K .......... .......... .......... .......... .......... 51% 45.9M 6s\n", + "307950K .......... .......... .......... .......... .......... 51% 51.2M 6s\n", + "308000K .......... .......... .......... .......... .......... 51% 49.0M 6s\n", + "308050K .......... .......... .......... .......... .......... 51% 54.7M 6s\n", + "308100K .......... .......... .......... .......... .......... 51% 60.7M 6s\n", + "308150K .......... .......... .......... .......... .......... 51% 74.5M 6s\n", + "308200K .......... .......... .......... .......... .......... 51% 38.0M 6s\n", + "308250K .......... .......... .......... .......... .......... 51% 49.2M 6s\n", + "308300K .......... .......... .......... .......... .......... 51% 52.0M 6s\n", + "308350K .......... .......... .......... .......... .......... 51% 58.2M 6s\n", + "308400K .......... .......... .......... .......... .......... 51% 51.0M 6s\n", + "308450K .......... .......... .......... .......... .......... 51% 28.8M 6s\n", + "308500K .......... .......... .......... .......... .......... 51% 58.4M 6s\n", + "308550K .......... .......... .......... .......... .......... 51% 47.3M 6s\n", + "308600K .......... .......... .......... .......... .......... 51% 38.4M 6s\n", + "308650K .......... .......... .......... .......... .......... 51% 28.0M 6s\n", + "308700K .......... .......... .......... .......... .......... 51% 35.1M 6s\n", + "308750K .......... .......... .......... .......... .......... 51% 62.3M 6s\n", + "308800K .......... .......... .......... .......... .......... 51% 26.5M 6s\n", + "308850K .......... .......... .......... .......... .......... 51% 38.5M 6s\n", + "308900K .......... .......... .......... .......... .......... 51% 52.8M 6s\n", + "308950K .......... .......... .......... .......... .......... 51% 38.3M 6s\n", + "309000K .......... .......... .......... .......... .......... 51% 31.7M 6s\n", + "309050K .......... .......... .......... .......... .......... 51% 39.2M 6s\n", + "309100K .......... .......... .......... .......... .......... 51% 52.7M 6s\n", + "309150K .......... .......... .......... .......... .......... 51% 47.5M 6s\n", + "309200K .......... .......... .......... .......... .......... 51% 29.2M 6s\n", + "309250K .......... .......... .......... .......... .......... 52% 37.7M 6s\n", + "309300K .......... .......... .......... .......... .......... 52% 41.5M 6s\n", + "309350K .......... .......... .......... .......... .......... 52% 31.5M 6s\n", + "309400K .......... .......... .......... .......... .......... 52% 27.8M 6s\n", + "309450K .......... .......... .......... .......... .......... 52% 54.1M 6s\n", + "309500K .......... .......... .......... .......... .......... 52% 35.5M 6s\n", + "309550K .......... .......... .......... .......... .......... 52% 48.9M 6s\n", + "309600K .......... .......... .......... .......... .......... 52% 38.2M 6s\n", + "309650K .......... .......... .......... .......... .......... 52% 48.5M 6s\n", + "309700K .......... .......... .......... .......... .......... 52% 40.3M 6s\n", + "309750K .......... .......... .......... .......... .......... 52% 37.6M 6s\n", + "309800K .......... .......... .......... .......... .......... 52% 46.5M 6s\n", + "309850K .......... .......... .......... .......... .......... 52% 40.7M 6s\n", + "309900K .......... .......... .......... .......... .......... 52% 52.1M 6s\n", + "309950K .......... .......... .......... .......... .......... 52% 30.1M 6s\n", + "310000K .......... .......... .......... .......... .......... 52% 59.7M 6s\n", + "310050K .......... .......... .......... .......... .......... 52% 36.5M 6s\n", + "310100K .......... .......... .......... .......... .......... 52% 51.6M 6s\n", + "310150K .......... .......... .......... .......... .......... 52% 4.35M 6s\n", + "310200K .......... .......... .......... .......... .......... 52% 59.8M 6s\n", + "310250K .......... .......... .......... .......... .......... 52% 72.9M 6s\n", + "310300K .......... .......... .......... .......... .......... 52% 74.4M 6s\n", + "310350K .......... .......... .......... .......... .......... 52% 74.8M 6s\n", + "310400K .......... .......... .......... .......... .......... 52% 65.7M 6s\n", + "310450K .......... .......... .......... .......... .......... 52% 70.0M 6s\n", + "310500K .......... .......... .......... .......... .......... 52% 44.9M 6s\n", + "310550K .......... .......... .......... .......... .......... 52% 48.3M 6s\n", + "310600K .......... .......... .......... .......... .......... 52% 57.6M 6s\n", + "310650K .......... .......... .......... .......... .......... 52% 64.3M 6s\n", + "310700K .......... .......... .......... .......... .......... 52% 75.3M 6s\n", + "310750K .......... .......... .......... .......... .......... 52% 44.4M 6s\n", + "310800K .......... .......... .......... .......... .......... 52% 51.1M 6s\n", + "310850K .......... .......... .......... .......... .......... 52% 62.0M 6s\n", + "310900K .......... .......... .......... .......... .......... 52% 59.9M 6s\n", + "310950K .......... .......... .......... .......... .......... 52% 66.7M 6s\n", + "311000K .......... .......... .......... .......... .......... 52% 49.8M 6s\n", + "311050K .......... .......... .......... .......... .......... 52% 70.5M 6s\n", + "311100K .......... .......... .......... .......... .......... 52% 61.7M 6s\n", + "311150K .......... .......... .......... .......... .......... 52% 56.7M 6s\n", + "311200K .......... .......... .......... .......... .......... 52% 48.6M 6s\n", + "311250K .......... .......... .......... .......... .......... 52% 65.4M 6s\n", + "311300K .......... .......... .......... .......... .......... 52% 59.3M 6s\n", + "311350K .......... .......... .......... .......... .......... 52% 73.4M 6s\n", + "311400K .......... .......... .......... .......... .......... 52% 51.6M 6s\n", + "311450K .......... .......... .......... .......... .......... 52% 63.9M 6s\n", + "311500K .......... .......... .......... .......... .......... 52% 61.3M 6s\n", + "311550K .......... .......... .......... .......... .......... 52% 57.5M 6s\n", + "311600K .......... .......... .......... .......... .......... 52% 52.1M 6s\n", + "311650K .......... .......... .......... .......... .......... 52% 64.8M 6s\n", + "311700K .......... .......... .......... .......... .......... 52% 62.7M 6s\n", + "311750K .......... .......... .......... .......... .......... 52% 61.8M 6s\n", + "311800K .......... .......... .......... .......... .......... 52% 47.8M 6s\n", + "311850K .......... .......... .......... .......... .......... 52% 56.0M 6s\n", + "311900K .......... .......... .......... .......... .......... 52% 59.1M 6s\n", + "311950K .......... .......... .......... .......... .......... 52% 62.2M 6s\n", + "312000K .......... .......... .......... .......... .......... 52% 57.3M 6s\n", + "312050K .......... .......... .......... .......... .......... 52% 55.0M 6s\n", + "312100K .......... .......... .......... .......... .......... 52% 53.6M 6s\n", + "312150K .......... .......... .......... .......... .......... 52% 64.4M 6s\n", + "312200K .......... .......... .......... .......... .......... 52% 44.6M 6s\n", + "312250K .......... .......... .......... .......... .......... 52% 69.0M 6s\n", + "312300K .......... .......... .......... .......... .......... 52% 49.0M 6s\n", + "312350K .......... .......... .......... .......... .......... 52% 67.4M 6s\n", + "312400K .......... .......... .......... .......... .......... 52% 54.4M 6s\n", + "312450K .......... .......... .......... .......... .......... 52% 56.9M 6s\n", + "312500K .......... .......... .......... .......... .......... 52% 59.5M 6s\n", + "312550K .......... .......... .......... .......... .......... 52% 56.8M 6s\n", + "312600K .......... .......... .......... .......... .......... 52% 45.5M 6s\n", + "312650K .......... .......... .......... .......... .......... 52% 52.8M 6s\n", + "312700K .......... .......... .......... .......... .......... 52% 58.3M 6s\n", + "312750K .......... .......... .......... .......... .......... 52% 62.4M 6s\n", + "312800K .......... .......... .......... .......... .......... 52% 52.5M 6s\n", + "312850K .......... .......... .......... .......... .......... 52% 51.4M 6s\n", + "312900K .......... .......... .......... .......... .......... 52% 53.6M 6s\n", + "312950K .......... .......... .......... .......... .......... 52% 42.0M 6s\n", + "313000K .......... .......... .......... .......... .......... 52% 47.4M 6s\n", + "313050K .......... .......... .......... .......... .......... 52% 48.6M 6s\n", + "313100K .......... .......... .......... .......... .......... 52% 47.7M 6s\n", + "313150K .......... .......... .......... .......... .......... 52% 55.5M 6s\n", + "313200K .......... .......... .......... .......... .......... 52% 45.2M 6s\n", + "313250K .......... .......... .......... .......... .......... 52% 46.2M 6s\n", + "313300K .......... .......... .......... .......... .......... 52% 44.9M 6s\n", + "313350K .......... .......... .......... .......... .......... 52% 52.2M 6s\n", + "313400K .......... .......... .......... .......... .......... 52% 3.70M 6s\n", + "313450K .......... .......... .......... .......... .......... 52% 72.0M 6s\n", + "313500K .......... .......... .......... .......... .......... 52% 64.0M 6s\n", + "313550K .......... .......... .......... .......... .......... 52% 71.1M 6s\n", + "313600K .......... .......... .......... .......... .......... 52% 58.7M 6s\n", + "313650K .......... .......... .......... .......... .......... 52% 71.9M 6s\n", + "313700K .......... .......... .......... .......... .......... 52% 53.3M 6s\n", + "313750K .......... .......... .......... .......... .......... 52% 46.8M 6s\n", + "313800K .......... .......... .......... .......... .......... 52% 54.5M 6s\n", + "313850K .......... .......... .......... .......... .......... 52% 66.9M 6s\n", + "313900K .......... .......... .......... .......... .......... 52% 72.0M 6s\n", + "313950K .......... .......... .......... .......... .......... 52% 74.7M 6s\n", + "314000K .......... .......... .......... .......... .......... 52% 57.7M 6s\n", + "314050K .......... .......... .......... .......... .......... 52% 16.4M 6s\n", + "314100K .......... .......... .......... .......... .......... 52% 60.1M 6s\n", + "314150K .......... .......... .......... .......... .......... 52% 52.0M 6s\n", + "314200K .......... .......... .......... .......... .......... 52% 41.3M 6s\n", + "314250K .......... .......... .......... .......... .......... 52% 62.9M 6s\n", + "314300K .......... .......... .......... .......... .......... 52% 54.9M 6s\n", + "314350K .......... .......... .......... .......... .......... 52% 54.4M 6s\n", + "314400K .......... .......... .......... .......... .......... 52% 56.4M 6s\n", + "314450K .......... .......... .......... .......... .......... 52% 47.0M 6s\n", + "314500K .......... .......... .......... .......... .......... 52% 69.0M 6s\n", + "314550K .......... .......... .......... .......... .......... 52% 70.0M 6s\n", + "314600K .......... .......... .......... .......... .......... 52% 57.5M 6s\n", + "314650K .......... .......... .......... .......... .......... 52% 58.1M 6s\n", + "314700K .......... .......... .......... .......... .......... 52% 61.9M 6s\n", + "314750K .......... .......... .......... .......... .......... 52% 54.3M 6s\n", + "314800K .......... .......... .......... .......... .......... 52% 64.3M 6s\n", + "314850K .......... .......... .......... .......... .......... 52% 69.8M 6s\n", + "314900K .......... .......... .......... .......... .......... 52% 59.1M 6s\n", + "314950K .......... .......... .......... .......... .......... 52% 64.4M 6s\n", + "315000K .......... .......... .......... .......... .......... 52% 45.2M 6s\n", + "315050K .......... .......... .......... .......... .......... 52% 55.8M 6s\n", + "315100K .......... .......... .......... .......... .......... 52% 67.0M 6s\n", + "315150K .......... .......... .......... .......... .......... 52% 59.4M 6s\n", + "315200K .......... .......... .......... .......... .......... 53% 51.3M 6s\n", + "315250K .......... .......... .......... .......... .......... 53% 51.0M 6s\n", + "315300K .......... .......... .......... .......... .......... 53% 58.3M 6s\n", + "315350K .......... .......... .......... .......... .......... 53% 61.3M 6s\n", + "315400K .......... .......... .......... .......... .......... 53% 49.3M 6s\n", + "315450K .......... .......... .......... .......... .......... 53% 37.2M 6s\n", + "315500K .......... .......... .......... .......... .......... 53% 47.6M 6s\n", + "315550K .......... .......... .......... .......... .......... 53% 41.7M 6s\n", + "315600K .......... .......... .......... .......... .......... 53% 38.6M 6s\n", + "315650K .......... .......... .......... .......... .......... 53% 46.2M 6s\n", + "315700K .......... .......... .......... .......... .......... 53% 47.8M 6s\n", + "315750K .......... .......... .......... .......... .......... 53% 54.0M 6s\n", + "315800K .......... .......... .......... .......... .......... 53% 55.8M 6s\n", + "315850K .......... .......... .......... .......... .......... 53% 60.5M 6s\n", + "315900K .......... .......... .......... .......... .......... 53% 49.4M 6s\n", + "315950K .......... .......... .......... .......... .......... 53% 48.3M 6s\n", + "316000K .......... .......... .......... .......... .......... 53% 48.0M 6s\n", + "316050K .......... .......... .......... .......... .......... 53% 63.1M 6s\n", + "316100K .......... .......... .......... .......... .......... 53% 61.1M 6s\n", + "316150K .......... .......... .......... .......... .......... 53% 54.8M 6s\n", + "316200K .......... .......... .......... .......... .......... 53% 37.7M 6s\n", + "316250K .......... .......... .......... .......... .......... 53% 61.7M 6s\n", + "316300K .......... .......... .......... .......... .......... 53% 66.3M 6s\n", + "316350K .......... .......... .......... .......... .......... 53% 63.3M 6s\n", + "316400K .......... .......... .......... .......... .......... 53% 52.1M 6s\n", + "316450K .......... .......... .......... .......... .......... 53% 45.2M 6s\n", + "316500K .......... .......... .......... .......... .......... 53% 45.6M 6s\n", + "316550K .......... .......... .......... .......... .......... 53% 63.8M 6s\n", + "316600K .......... .......... .......... .......... .......... 53% 52.3M 6s\n", + "316650K .......... .......... .......... .......... .......... 53% 69.2M 6s\n", + "316700K .......... .......... .......... .......... .......... 53% 49.3M 6s\n", + "316750K .......... .......... .......... .......... .......... 53% 47.0M 6s\n", + "316800K .......... .......... .......... .......... .......... 53% 58.4M 6s\n", + "316850K .......... .......... .......... .......... .......... 53% 59.6M 6s\n", + "316900K .......... .......... .......... .......... .......... 53% 50.0M 6s\n", + "316950K .......... .......... .......... .......... .......... 53% 55.6M 6s\n", + "317000K .......... .......... .......... .......... .......... 53% 40.2M 6s\n", + "317050K .......... .......... .......... .......... .......... 53% 64.0M 6s\n", + "317100K .......... .......... .......... .......... .......... 53% 62.5M 6s\n", + "317150K .......... .......... .......... .......... .......... 53% 52.1M 6s\n", + "317200K .......... .......... .......... .......... .......... 53% 63.4M 6s\n", + "317250K .......... .......... .......... .......... .......... 53% 57.6M 6s\n", + "317300K .......... .......... .......... .......... .......... 53% 48.9M 6s\n", + "317350K .......... .......... .......... .......... .......... 53% 67.9M 6s\n", + "317400K .......... .......... .......... .......... .......... 53% 52.9M 6s\n", + "317450K .......... .......... .......... .......... .......... 53% 62.3M 6s\n", + "317500K .......... .......... .......... .......... .......... 53% 57.1M 6s\n", + "317550K .......... .......... .......... .......... .......... 53% 55.4M 6s\n", + "317600K .......... .......... .......... .......... .......... 53% 52.7M 6s\n", + "317650K .......... .......... .......... .......... .......... 53% 60.1M 6s\n", + "317700K .......... .......... .......... .......... .......... 53% 54.9M 6s\n", + "317750K .......... .......... .......... .......... .......... 53% 50.7M 6s\n", + "317800K .......... .......... .......... .......... .......... 53% 3.87M 6s\n", + "317850K .......... .......... .......... .......... .......... 53% 49.2M 6s\n", + "317900K .......... .......... .......... .......... .......... 53% 60.8M 6s\n", + "317950K .......... .......... .......... .......... .......... 53% 65.5M 6s\n", + "318000K .......... .......... .......... .......... .......... 53% 60.2M 6s\n", + "318050K .......... .......... .......... .......... .......... 53% 66.4M 6s\n", + "318100K .......... .......... .......... .......... .......... 53% 51.0M 6s\n", + "318150K .......... .......... .......... .......... .......... 53% 51.6M 6s\n", + "318200K .......... .......... .......... .......... .......... 53% 59.5M 6s\n", + "318250K .......... .......... .......... .......... .......... 53% 68.9M 6s\n", + "318300K .......... .......... .......... .......... .......... 53% 66.5M 6s\n", + "318350K .......... .......... .......... .......... .......... 53% 61.8M 6s\n", + "318400K .......... .......... .......... .......... .......... 53% 48.4M 6s\n", + "318450K .......... .......... .......... .......... .......... 53% 46.6M 6s\n", + "318500K .......... .......... .......... .......... .......... 53% 69.3M 6s\n", + "318550K .......... .......... .......... .......... .......... 53% 67.9M 6s\n", + "318600K .......... .......... .......... .......... .......... 53% 53.4M 6s\n", + "318650K .......... .......... .......... .......... .......... 53% 45.1M 6s\n", + "318700K .......... .......... .......... .......... .......... 53% 46.1M 6s\n", + "318750K .......... .......... .......... .......... .......... 53% 70.9M 6s\n", + "318800K .......... .......... .......... .......... .......... 53% 59.2M 6s\n", + "318850K .......... .......... .......... .......... .......... 53% 65.1M 6s\n", + "318900K .......... .......... .......... .......... .......... 53% 46.3M 6s\n", + "318950K .......... .......... .......... .......... .......... 53% 49.7M 6s\n", + "319000K .......... .......... .......... .......... .......... 53% 55.7M 6s\n", + "319050K .......... .......... .......... .......... .......... 53% 67.8M 6s\n", + "319100K .......... .......... .......... .......... .......... 53% 66.8M 6s\n", + "319150K .......... .......... .......... .......... .......... 53% 50.0M 6s\n", + "319200K .......... .......... .......... .......... .......... 53% 53.9M 6s\n", + "319250K .......... .......... .......... .......... .......... 53% 65.7M 6s\n", + "319300K .......... .......... .......... .......... .......... 53% 66.7M 6s\n", + "319350K .......... .......... .......... .......... .......... 53% 63.9M 6s\n", + "319400K .......... .......... .......... .......... .......... 53% 46.9M 6s\n", + "319450K .......... .......... .......... .......... .......... 53% 46.9M 6s\n", + "319500K .......... .......... .......... .......... .......... 53% 49.3M 6s\n", + "319550K .......... .......... .......... .......... .......... 53% 62.8M 6s\n", + "319600K .......... .......... .......... .......... .......... 53% 57.3M 6s\n", + "319650K .......... .......... .......... .......... .......... 53% 70.7M 6s\n", + "319700K .......... .......... .......... .......... .......... 53% 64.1M 6s\n", + "319750K .......... .......... .......... .......... .......... 53% 68.0M 6s\n", + "319800K .......... .......... .......... .......... .......... 53% 51.0M 6s\n", + "319850K .......... .......... .......... .......... .......... 53% 73.8M 6s\n", + "319900K .......... .......... .......... .......... .......... 53% 68.3M 6s\n", + "319950K .......... .......... .......... .......... .......... 53% 68.1M 6s\n", + "320000K .......... .......... .......... .......... .......... 53% 59.3M 6s\n", + "320050K .......... .......... .......... .......... .......... 53% 65.5M 6s\n", + "320100K .......... .......... .......... .......... .......... 53% 64.1M 6s\n", + "320150K .......... .......... .......... .......... .......... 53% 66.1M 6s\n", + "320200K .......... .......... .......... .......... .......... 53% 3.91M 6s\n", + "320250K .......... .......... .......... .......... .......... 53% 55.5M 6s\n", + "320300K .......... .......... .......... .......... .......... 53% 61.9M 6s\n", + "320350K .......... .......... .......... .......... .......... 53% 65.2M 6s\n", + "320400K .......... .......... .......... .......... .......... 53% 55.9M 6s\n", + "320450K .......... .......... .......... .......... .......... 53% 68.9M 6s\n", + "320500K .......... .......... .......... .......... .......... 53% 64.9M 6s\n", + "320550K .......... .......... .......... .......... .......... 53% 58.8M 6s\n", + "320600K .......... .......... .......... .......... .......... 53% 38.9M 6s\n", + "320650K .......... .......... .......... .......... .......... 53% 54.5M 6s\n", + "320700K .......... .......... .......... .......... .......... 53% 60.6M 6s\n", + "320750K .......... .......... .......... .......... .......... 53% 66.2M 6s\n", + "320800K .......... .......... .......... .......... .......... 53% 42.8M 6s\n", + "320850K .......... .......... .......... .......... .......... 53% 44.3M 6s\n", + "320900K .......... .......... .......... .......... .......... 53% 50.1M 6s\n", + "320950K .......... .......... .......... .......... .......... 53% 67.2M 6s\n", + "321000K .......... .......... .......... .......... .......... 53% 19.3M 6s\n", + "321050K .......... .......... .......... .......... .......... 53% 51.1M 6s\n", + "321100K .......... .......... .......... .......... .......... 53% 59.7M 6s\n", + "321150K .......... .......... .......... .......... .......... 54% 73.7M 6s\n", + "321200K .......... .......... .......... .......... .......... 54% 14.3M 6s\n", + "321250K .......... .......... .......... .......... .......... 54% 54.1M 6s\n", + "321300K .......... .......... .......... .......... .......... 54% 60.1M 6s\n", + "321350K .......... .......... .......... .......... .......... 54% 68.9M 6s\n", + "321400K .......... .......... .......... .......... .......... 54% 56.5M 6s\n", + "321450K .......... .......... .......... .......... .......... 54% 64.9M 6s\n", + "321500K .......... .......... .......... .......... .......... 54% 4.11M 6s\n", + "321550K .......... .......... .......... .......... .......... 54% 70.1M 6s\n", + "321600K .......... .......... .......... .......... .......... 54% 63.7M 6s\n", + "321650K .......... .......... .......... .......... .......... 54% 69.7M 6s\n", + "321700K .......... .......... .......... .......... .......... 54% 64.6M 6s\n", + "321750K .......... .......... .......... .......... .......... 54% 64.6M 6s\n", + "321800K .......... .......... .......... .......... .......... 54% 43.5M 6s\n", + "321850K .......... .......... .......... .......... .......... 54% 40.6M 6s\n", + "321900K .......... .......... .......... .......... .......... 54% 51.5M 6s\n", + "321950K .......... .......... .......... .......... .......... 54% 72.6M 6s\n", + "322000K .......... .......... .......... .......... .......... 54% 62.5M 6s\n", + "322050K .......... .......... .......... .......... .......... 54% 53.9M 6s\n", + "322100K .......... .......... .......... .......... .......... 54% 62.6M 6s\n", + "322150K .......... .......... .......... .......... .......... 54% 44.8M 6s\n", + "322200K .......... .......... .......... .......... .......... 54% 53.6M 6s\n", + "322250K .......... .......... .......... .......... .......... 54% 66.7M 6s\n", + "322300K .......... .......... .......... .......... .......... 54% 61.2M 6s\n", + "322350K .......... .......... .......... .......... .......... 54% 62.9M 6s\n", + "322400K .......... .......... .......... .......... .......... 54% 42.8M 6s\n", + "322450K .......... .......... .......... .......... .......... 54% 16.2M 6s\n", + "322500K .......... .......... .......... .......... .......... 54% 55.8M 6s\n", + "322550K .......... .......... .......... .......... .......... 54% 50.6M 6s\n", + "322600K .......... .......... .......... .......... .......... 54% 51.9M 6s\n", + "322650K .......... .......... .......... .......... .......... 54% 70.3M 6s\n", + "322700K .......... .......... .......... .......... .......... 54% 56.6M 6s\n", + "322750K .......... .......... .......... .......... .......... 54% 50.6M 6s\n", + "322800K .......... .......... .......... .......... .......... 54% 46.2M 6s\n", + "322850K .......... .......... .......... .......... .......... 54% 71.4M 6s\n", + "322900K .......... .......... .......... .......... .......... 54% 66.5M 6s\n", + "322950K .......... .......... .......... .......... .......... 54% 57.4M 6s\n", + "323000K .......... .......... .......... .......... .......... 54% 38.8M 6s\n", + "323050K .......... .......... .......... .......... .......... 54% 52.1M 6s\n", + "323100K .......... .......... .......... .......... .......... 54% 63.3M 6s\n", + "323150K .......... .......... .......... .......... .......... 54% 70.0M 6s\n", + "323200K .......... .......... .......... .......... .......... 54% 51.4M 6s\n", + "323250K .......... .......... .......... .......... .......... 54% 49.1M 6s\n", + "323300K .......... .......... .......... .......... .......... 54% 45.0M 6s\n", + "323350K .......... .......... .......... .......... .......... 54% 58.9M 6s\n", + "323400K .......... .......... .......... .......... .......... 54% 57.4M 6s\n", + "323450K .......... .......... .......... .......... .......... 54% 62.2M 6s\n", + "323500K .......... .......... .......... .......... .......... 54% 45.6M 6s\n", + "323550K .......... .......... .......... .......... .......... 54% 55.1M 6s\n", + "323600K .......... .......... .......... .......... .......... 54% 63.3M 6s\n", + "323650K .......... .......... .......... .......... .......... 54% 70.9M 6s\n", + "323700K .......... .......... .......... .......... .......... 54% 74.2M 6s\n", + "323750K .......... .......... .......... .......... .......... 54% 44.9M 6s\n", + "323800K .......... .......... .......... .......... .......... 54% 39.6M 6s\n", + "323850K .......... .......... .......... .......... .......... 54% 72.3M 6s\n", + "323900K .......... .......... .......... .......... .......... 54% 69.1M 6s\n", + "323950K .......... .......... .......... .......... .......... 54% 68.3M 6s\n", + "324000K .......... .......... .......... .......... .......... 54% 51.4M 6s\n", + "324050K .......... .......... .......... .......... .......... 54% 45.6M 6s\n", + "324100K .......... .......... .......... .......... .......... 54% 56.9M 6s\n", + "324150K .......... .......... .......... .......... .......... 54% 72.6M 6s\n", + "324200K .......... .......... .......... .......... .......... 54% 59.4M 6s\n", + "324250K .......... .......... .......... .......... .......... 54% 46.0M 6s\n", + "324300K .......... .......... .......... .......... .......... 54% 45.1M 6s\n", + "324350K .......... .......... .......... .......... .......... 54% 11.8M 6s\n", + "324400K .......... .......... .......... .......... .......... 54% 47.7M 6s\n", + "324450K .......... .......... .......... .......... .......... 54% 66.0M 6s\n", + "324500K .......... .......... .......... .......... .......... 54% 66.9M 6s\n", + "324550K .......... .......... .......... .......... .......... 54% 59.4M 6s\n", + "324600K .......... .......... .......... .......... .......... 54% 62.6M 6s\n", + "324650K .......... .......... .......... .......... .......... 54% 61.8M 6s\n", + "324700K .......... .......... .......... .......... .......... 54% 61.9M 6s\n", + "324750K .......... .......... .......... .......... .......... 54% 62.4M 6s\n", + "324800K .......... .......... .......... .......... .......... 54% 62.4M 6s\n", + "324850K .......... .......... .......... .......... .......... 54% 57.0M 6s\n", + "324900K .......... .......... .......... .......... .......... 54% 59.4M 6s\n", + "324950K .......... .......... .......... .......... .......... 54% 49.4M 6s\n", + "325000K .......... .......... .......... .......... .......... 54% 54.0M 6s\n", + "325050K .......... .......... .......... .......... .......... 54% 68.8M 6s\n", + "325100K .......... .......... .......... .......... .......... 54% 63.6M 6s\n", + "325150K .......... .......... .......... .......... .......... 54% 53.2M 6s\n", + "325200K .......... .......... .......... .......... .......... 54% 59.5M 6s\n", + "325250K .......... .......... .......... .......... .......... 54% 56.2M 6s\n", + "325300K .......... .......... .......... .......... .......... 54% 66.3M 6s\n", + "325350K .......... .......... .......... .......... .......... 54% 71.5M 6s\n", + "325400K .......... .......... .......... .......... .......... 54% 63.1M 6s\n", + "325450K .......... .......... .......... .......... .......... 54% 43.8M 6s\n", + "325500K .......... .......... .......... .......... .......... 54% 61.9M 6s\n", + "325550K .......... .......... .......... .......... .......... 54% 66.3M 6s\n", + "325600K .......... .......... .......... .......... .......... 54% 62.7M 6s\n", + "325650K .......... .......... .......... .......... .......... 54% 71.7M 6s\n", + "325700K .......... .......... .......... .......... .......... 54% 63.4M 6s\n", + "325750K .......... .......... .......... .......... .......... 54% 48.6M 6s\n", + "325800K .......... .......... .......... .......... .......... 54% 39.5M 6s\n", + "325850K .......... .......... .......... .......... .......... 54% 75.2M 6s\n", + "325900K .......... .......... .......... .......... .......... 54% 74.1M 6s\n", + "325950K .......... .......... .......... .......... .......... 54% 73.1M 6s\n", + "326000K .......... .......... .......... .......... .......... 54% 56.3M 6s\n", + "326050K .......... .......... .......... .......... .......... 54% 47.1M 6s\n", + "326100K .......... .......... .......... .......... .......... 54% 55.2M 6s\n", + "326150K .......... .......... .......... .......... .......... 54% 68.3M 6s\n", + "326200K .......... .......... .......... .......... .......... 54% 56.2M 6s\n", + "326250K .......... .......... .......... .......... .......... 54% 50.4M 6s\n", + "326300K .......... .......... .......... .......... .......... 54% 46.3M 6s\n", + "326350K .......... .......... .......... .......... .......... 54% 54.2M 6s\n", + "326400K .......... .......... .......... .......... .......... 54% 62.6M 6s\n", + "326450K .......... .......... .......... .......... .......... 54% 71.1M 6s\n", + "326500K .......... .......... .......... .......... .......... 54% 49.7M 6s\n", + "326550K .......... .......... .......... .......... .......... 54% 47.3M 6s\n", + "326600K .......... .......... .......... .......... .......... 54% 46.3M 6s\n", + "326650K .......... .......... .......... .......... .......... 54% 64.8M 6s\n", + "326700K .......... .......... .......... .......... .......... 54% 58.9M 6s\n", + "326750K .......... .......... .......... .......... .......... 54% 53.7M 6s\n", + "326800K .......... .......... .......... .......... .......... 54% 38.2M 6s\n", + "326850K .......... .......... .......... .......... .......... 54% 48.5M 6s\n", + "326900K .......... .......... .......... .......... .......... 54% 65.0M 6s\n", + "326950K .......... .......... .......... .......... .......... 54% 59.8M 6s\n", + "327000K .......... .......... .......... .......... .......... 54% 42.5M 6s\n", + "327050K .......... .......... .......... .......... .......... 54% 48.0M 6s\n", + "327100K .......... .......... .......... .......... .......... 55% 66.8M 6s\n", + "327150K .......... .......... .......... .......... .......... 55% 68.0M 6s\n", + "327200K .......... .......... .......... .......... .......... 55% 61.1M 6s\n", + "327250K .......... .......... .......... .......... .......... 55% 61.9M 6s\n", + "327300K .......... .......... .......... .......... .......... 55% 5.71M 6s\n", + "327350K .......... .......... .......... .......... .......... 55% 48.6M 6s\n", + "327400K .......... .......... .......... .......... .......... 55% 42.5M 6s\n", + "327450K .......... .......... .......... .......... .......... 55% 56.6M 6s\n", + "327500K .......... .......... .......... .......... .......... 55% 58.1M 6s\n", + "327550K .......... .......... .......... .......... .......... 55% 60.8M 6s\n", + "327600K .......... .......... .......... .......... .......... 55% 46.4M 6s\n", + "327650K .......... .......... .......... .......... .......... 55% 67.7M 6s\n", + "327700K .......... .......... .......... .......... .......... 55% 73.4M 6s\n", + "327750K .......... .......... .......... .......... .......... 55% 76.1M 6s\n", + "327800K .......... .......... .......... .......... .......... 55% 55.6M 6s\n", + "327850K .......... .......... .......... .......... .......... 55% 60.6M 6s\n", + "327900K .......... .......... .......... .......... .......... 55% 41.9M 6s\n", + "327950K .......... .......... .......... .......... .......... 55% 53.1M 6s\n", + "328000K .......... .......... .......... .......... .......... 55% 46.3M 6s\n", + "328050K .......... .......... .......... .......... .......... 55% 56.2M 6s\n", + "328100K .......... .......... .......... .......... .......... 55% 39.0M 6s\n", + "328150K .......... .......... .......... .......... .......... 55% 41.0M 6s\n", + "328200K .......... .......... .......... .......... .......... 55% 43.3M 6s\n", + "328250K .......... .......... .......... .......... .......... 55% 64.3M 6s\n", + "328300K .......... .......... .......... .......... .......... 55% 45.8M 6s\n", + "328350K .......... .......... .......... .......... .......... 55% 45.1M 6s\n", + "328400K .......... .......... .......... .......... .......... 55% 37.3M 6s\n", + "328450K .......... .......... .......... .......... .......... 55% 75.7M 6s\n", + "328500K .......... .......... .......... .......... .......... 55% 73.4M 6s\n", + "328550K .......... .......... .......... .......... .......... 55% 60.0M 6s\n", + "328600K .......... .......... .......... .......... .......... 55% 43.4M 6s\n", + "328650K .......... .......... .......... .......... .......... 55% 68.7M 6s\n", + "328700K .......... .......... .......... .......... .......... 55% 50.7M 6s\n", + "328750K .......... .......... .......... .......... .......... 55% 61.7M 6s\n", + "328800K .......... .......... .......... .......... .......... 55% 57.2M 6s\n", + "328850K .......... .......... .......... .......... .......... 55% 51.3M 6s\n", + "328900K .......... .......... .......... .......... .......... 55% 58.9M 6s\n", + "328950K .......... .......... .......... .......... .......... 55% 55.8M 6s\n", + "329000K .......... .......... .......... .......... .......... 55% 47.8M 6s\n", + "329050K .......... .......... .......... .......... .......... 55% 71.4M 6s\n", + "329100K .......... .......... .......... .......... .......... 55% 58.9M 6s\n", + "329150K .......... .......... .......... .......... .......... 55% 56.3M 6s\n", + "329200K .......... .......... .......... .......... .......... 55% 31.8M 6s\n", + "329250K .......... .......... .......... .......... .......... 55% 45.4M 6s\n", + "329300K .......... .......... .......... .......... .......... 55% 48.9M 6s\n", + "329350K .......... .......... .......... .......... .......... 55% 51.4M 6s\n", + "329400K .......... .......... .......... .......... .......... 55% 48.8M 6s\n", + "329450K .......... .......... .......... .......... .......... 55% 60.1M 6s\n", + "329500K .......... .......... .......... .......... .......... 55% 74.4M 6s\n", + "329550K .......... .......... .......... .......... .......... 55% 5.78M 6s\n", + "329600K .......... .......... .......... .......... .......... 55% 49.2M 6s\n", + "329650K .......... .......... .......... .......... .......... 55% 74.2M 6s\n", + "329700K .......... .......... .......... .......... .......... 55% 65.4M 6s\n", + "329750K .......... .......... .......... .......... .......... 55% 63.9M 6s\n", + "329800K .......... .......... .......... .......... .......... 55% 59.5M 6s\n", + "329850K .......... .......... .......... .......... .......... 55% 73.3M 6s\n", + "329900K .......... .......... .......... .......... .......... 55% 56.9M 6s\n", + "329950K .......... .......... .......... .......... .......... 55% 68.9M 6s\n", + "330000K .......... .......... .......... .......... .......... 55% 62.9M 6s\n", + "330050K .......... .......... .......... .......... .......... 55% 76.4M 6s\n", + "330100K .......... .......... .......... .......... .......... 55% 53.6M 6s\n", + "330150K .......... .......... .......... .......... .......... 55% 54.2M 6s\n", + "330200K .......... .......... .......... .......... .......... 55% 50.5M 6s\n", + "330250K .......... .......... .......... .......... .......... 55% 56.8M 6s\n", + "330300K .......... .......... .......... .......... .......... 55% 72.6M 6s\n", + "330350K .......... .......... .......... .......... .......... 55% 53.9M 6s\n", + "330400K .......... .......... .......... .......... .......... 55% 40.5M 6s\n", + "330450K .......... .......... .......... .......... .......... 55% 56.0M 6s\n", + "330500K .......... .......... .......... .......... .......... 55% 72.9M 6s\n", + "330550K .......... .......... .......... .......... .......... 55% 66.6M 6s\n", + "330600K .......... .......... .......... .......... .......... 55% 42.1M 6s\n", + "330650K .......... .......... .......... .......... .......... 55% 38.4M 6s\n", + "330700K .......... .......... .......... .......... .......... 55% 77.0M 6s\n", + "330750K .......... .......... .......... .......... .......... 55% 68.7M 6s\n", + "330800K .......... .......... .......... .......... .......... 55% 63.0M 6s\n", + "330850K .......... .......... .......... .......... .......... 55% 53.8M 6s\n", + "330900K .......... .......... .......... .......... .......... 55% 44.3M 6s\n", + "330950K .......... .......... .......... .......... .......... 55% 63.1M 6s\n", + "331000K .......... .......... .......... .......... .......... 55% 57.0M 6s\n", + "331050K .......... .......... .......... .......... .......... 55% 73.3M 6s\n", + "331100K .......... .......... .......... .......... .......... 55% 64.5M 6s\n", + "331150K .......... .......... .......... .......... .......... 55% 45.7M 6s\n", + "331200K .......... .......... .......... .......... .......... 55% 43.3M 6s\n", + "331250K .......... .......... .......... .......... .......... 55% 71.1M 6s\n", + "331300K .......... .......... .......... .......... .......... 55% 71.2M 6s\n", + "331350K .......... .......... .......... .......... .......... 55% 67.5M 6s\n", + "331400K .......... .......... .......... .......... .......... 55% 42.1M 6s\n", + "331450K .......... .......... .......... .......... .......... 55% 48.6M 6s\n", + "331500K .......... .......... .......... .......... .......... 55% 65.1M 6s\n", + "331550K .......... .......... .......... .......... .......... 55% 64.7M 6s\n", + "331600K .......... .......... .......... .......... .......... 55% 32.3M 6s\n", + "331650K .......... .......... .......... .......... .......... 55% 37.9M 6s\n", + "331700K .......... .......... .......... .......... .......... 55% 44.4M 6s\n", + "331750K .......... .......... .......... .......... .......... 55% 62.6M 6s\n", + "331800K .......... .......... .......... .......... .......... 55% 48.9M 6s\n", + "331850K .......... .......... .......... .......... .......... 55% 67.6M 6s\n", + "331900K .......... .......... .......... .......... .......... 55% 60.7M 6s\n", + "331950K .......... .......... .......... .......... .......... 55% 48.9M 6s\n", + "332000K .......... .......... .......... .......... .......... 55% 43.2M 6s\n", + "332050K .......... .......... .......... .......... .......... 55% 64.2M 6s\n", + "332100K .......... .......... .......... .......... .......... 55% 72.9M 6s\n", + "332150K .......... .......... .......... .......... .......... 55% 63.0M 6s\n", + "332200K .......... .......... .......... .......... .......... 55% 53.1M 6s\n", + "332250K .......... .......... .......... .......... .......... 55% 49.8M 6s\n", + "332300K .......... .......... .......... .......... .......... 55% 38.3M 6s\n", + "332350K .......... .......... .......... .......... .......... 55% 39.5M 6s\n", + "332400K .......... .......... .......... .......... .......... 55% 37.4M 6s\n", + "332450K .......... .......... .......... .......... .......... 55% 65.0M 6s\n", + "332500K .......... .......... .......... .......... .......... 55% 57.3M 6s\n", + "332550K .......... .......... .......... .......... .......... 55% 47.5M 6s\n", + "332600K .......... .......... .......... .......... .......... 55% 51.0M 6s\n", + "332650K .......... .......... .......... .......... .......... 55% 64.7M 6s\n", + "332700K .......... .......... .......... .......... .......... 55% 66.2M 6s\n", + "332750K .......... .......... .......... .......... .......... 55% 53.3M 6s\n", + "332800K .......... .......... .......... .......... .......... 55% 44.3M 6s\n", + "332850K .......... .......... .......... .......... .......... 55% 46.0M 6s\n", + "332900K .......... .......... .......... .......... .......... 55% 71.4M 6s\n", + "332950K .......... .......... .......... .......... .......... 55% 81.8M 6s\n", + "333000K .......... .......... .......... .......... .......... 56% 35.2M 6s\n", + "333050K .......... .......... .......... .......... .......... 56% 30.4M 6s\n", + "333100K .......... .......... .......... .......... .......... 56% 38.4M 6s\n", + "333150K .......... .......... .......... .......... .......... 56% 45.9M 6s\n", + "333200K .......... .......... .......... .......... .......... 56% 36.9M 6s\n", + "333250K .......... .......... .......... .......... .......... 56% 36.8M 6s\n", + "333300K .......... .......... .......... .......... .......... 56% 46.7M 6s\n", + "333350K .......... .......... .......... .......... .......... 56% 42.8M 6s\n", + "333400K .......... .......... .......... .......... .......... 56% 32.0M 6s\n", + "333450K .......... .......... .......... .......... .......... 56% 39.9M 6s\n", + "333500K .......... .......... .......... .......... .......... 56% 69.4M 6s\n", + "333550K .......... .......... .......... .......... .......... 56% 36.7M 6s\n", + "333600K .......... .......... .......... .......... .......... 56% 38.1M 6s\n", + "333650K .......... .......... .......... .......... .......... 56% 40.1M 6s\n", + "333700K .......... .......... .......... .......... .......... 56% 74.8M 6s\n", + "333750K .......... .......... .......... .......... .......... 56% 36.2M 6s\n", + "333800K .......... .......... .......... .......... .......... 56% 36.5M 6s\n", + "333850K .......... .......... .......... .......... .......... 56% 47.6M 6s\n", + "333900K .......... .......... .......... .......... .......... 56% 69.0M 6s\n", + "333950K .......... .......... .......... .......... .......... 56% 37.1M 6s\n", + "334000K .......... .......... .......... .......... .......... 56% 48.0M 6s\n", + "334050K .......... .......... .......... .......... .......... 56% 48.3M 6s\n", + "334100K .......... .......... .......... .......... .......... 56% 60.9M 6s\n", + "334150K .......... .......... .......... .......... .......... 56% 52.3M 6s\n", + "334200K .......... .......... .......... .......... .......... 56% 46.4M 6s\n", + "334250K .......... .......... .......... .......... .......... 56% 47.7M 6s\n", + "334300K .......... .......... .......... .......... .......... 56% 43.2M 6s\n", + "334350K .......... .......... .......... .......... .......... 56% 62.7M 6s\n", + "334400K .......... .......... .......... .......... .......... 56% 37.4M 6s\n", + "334450K .......... .......... .......... .......... .......... 56% 48.2M 6s\n", + "334500K .......... .......... .......... .......... .......... 56% 55.2M 6s\n", + "334550K .......... .......... .......... .......... .......... 56% 72.8M 6s\n", + "334600K .......... .......... .......... .......... .......... 56% 62.4M 6s\n", + "334650K .......... .......... .......... .......... .......... 56% 79.8M 6s\n", + "334700K .......... .......... .......... .......... .......... 56% 71.0M 6s\n", + "334750K .......... .......... .......... .......... .......... 56% 76.1M 6s\n", + "334800K .......... .......... .......... .......... .......... 56% 63.6M 6s\n", + "334850K .......... .......... .......... .......... .......... 56% 71.1M 6s\n", + "334900K .......... .......... .......... .......... .......... 56% 74.7M 6s\n", + "334950K .......... .......... .......... .......... .......... 56% 73.9M 6s\n", + "335000K .......... .......... .......... .......... .......... 56% 61.2M 6s\n", + "335050K .......... .......... .......... .......... .......... 56% 75.2M 6s\n", + "335100K .......... .......... .......... .......... .......... 56% 83.9M 6s\n", + "335150K .......... .......... .......... .......... .......... 56% 62.6M 6s\n", + "335200K .......... .......... .......... .......... .......... 56% 57.5M 6s\n", + "335250K .......... .......... .......... .......... .......... 56% 69.2M 6s\n", + "335300K .......... .......... .......... .......... .......... 56% 44.2M 6s\n", + "335350K .......... .......... .......... .......... .......... 56% 35.4M 6s\n", + "335400K .......... .......... .......... .......... .......... 56% 51.2M 6s\n", + "335450K .......... .......... .......... .......... .......... 56% 76.3M 6s\n", + "335500K .......... .......... .......... .......... .......... 56% 40.6M 6s\n", + "335550K .......... .......... .......... .......... .......... 56% 26.4M 6s\n", + "335600K .......... .......... .......... .......... .......... 56% 48.4M 6s\n", + "335650K .......... .......... .......... .......... .......... 56% 61.3M 6s\n", + "335700K .......... .......... .......... .......... .......... 56% 43.9M 6s\n", + "335750K .......... .......... .......... .......... .......... 56% 33.5M 6s\n", + "335800K .......... .......... .......... .......... .......... 56% 36.9M 6s\n", + "335850K .......... .......... .......... .......... .......... 56% 57.2M 6s\n", + "335900K .......... .......... .......... .......... .......... 56% 38.1M 6s\n", + "335950K .......... .......... .......... .......... .......... 56% 44.5M 6s\n", + "336000K .......... .......... .......... .......... .......... 56% 39.0M 6s\n", + "336050K .......... .......... .......... .......... .......... 56% 41.6M 6s\n", + "336100K .......... .......... .......... .......... .......... 56% 39.0M 6s\n", + "336150K .......... .......... .......... .......... .......... 56% 49.4M 6s\n", + "336200K .......... .......... .......... .......... .......... 56% 25.9M 6s\n", + "336250K .......... .......... .......... .......... .......... 56% 52.2M 6s\n", + "336300K .......... .......... .......... .......... .......... 56% 57.4M 6s\n", + "336350K 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.......... .......... .......... .......... .......... 59% 71.1M 5s\n", + "355000K .......... .......... .......... .......... .......... 59% 55.2M 5s\n", + "355050K .......... .......... .......... .......... .......... 59% 61.2M 5s\n", + "355100K .......... .......... .......... .......... .......... 59% 56.3M 5s\n", + "355150K .......... .......... .......... .......... .......... 59% 49.0M 5s\n", + "355200K .......... .......... .......... .......... .......... 59% 63.1M 5s\n", + "355250K .......... .......... .......... .......... .......... 59% 65.5M 5s\n", + "355300K .......... .......... .......... .......... .......... 59% 3.97M 5s\n", + "355350K .......... .......... .......... .......... .......... 59% 62.5M 5s\n", + "355400K .......... .......... .......... .......... .......... 59% 53.4M 5s\n", + "355450K .......... .......... .......... .......... .......... 59% 66.1M 5s\n", + "355500K .......... .......... .......... .......... .......... 59% 74.4M 5s\n", + "355550K 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.......... .......... .......... .......... .......... 59% 55.9M 5s\n", + "356200K .......... .......... .......... .......... .......... 59% 43.5M 5s\n", + "356250K .......... .......... .......... .......... .......... 59% 49.3M 5s\n", + "356300K .......... .......... .......... .......... .......... 59% 68.5M 5s\n", + "356350K .......... .......... .......... .......... .......... 59% 65.9M 5s\n", + "356400K .......... .......... .......... .......... .......... 59% 58.3M 5s\n", + "356450K .......... .......... .......... .......... .......... 59% 56.4M 5s\n", + "356500K .......... .......... .......... .......... .......... 59% 61.9M 5s\n", + "356550K .......... .......... .......... .......... .......... 59% 53.7M 5s\n", + "356600K .......... .......... .......... .......... .......... 59% 52.1M 5s\n", + "356650K .......... .......... .......... .......... .......... 59% 66.2M 5s\n", + "356700K .......... .......... .......... .......... .......... 59% 59.5M 5s\n", + "356750K .......... .......... .......... .......... .......... 59% 68.1M 5s\n", + "356800K .......... .......... .......... .......... .......... 60% 53.9M 5s\n", + "356850K .......... .......... .......... .......... .......... 60% 63.3M 5s\n", + "356900K .......... .......... .......... .......... .......... 60% 61.7M 5s\n", + "356950K .......... .......... .......... .......... .......... 60% 54.8M 5s\n", + "357000K .......... .......... .......... .......... .......... 60% 53.6M 5s\n", + "357050K .......... .......... .......... .......... .......... 60% 70.8M 5s\n", + "357100K .......... .......... .......... .......... .......... 60% 55.6M 5s\n", + "357150K .......... .......... .......... .......... .......... 60% 53.7M 5s\n", + "357200K .......... .......... .......... .......... .......... 60% 53.0M 5s\n", + "357250K .......... .......... .......... .......... .......... 60% 49.6M 5s\n", + "357300K .......... .......... .......... .......... .......... 60% 56.5M 5s\n", + "357350K .......... .......... .......... .......... .......... 60% 46.9M 5s\n", + "357400K .......... .......... .......... .......... .......... 60% 36.4M 5s\n", + "357450K .......... .......... .......... .......... .......... 60% 52.7M 5s\n", + "357500K .......... .......... .......... .......... .......... 60% 57.4M 5s\n", + "357550K .......... .......... .......... .......... .......... 60% 63.3M 5s\n", + "357600K .......... .......... .......... .......... .......... 60% 46.9M 5s\n", + "357650K .......... .......... .......... .......... .......... 60% 48.2M 5s\n", + "357700K .......... .......... .......... .......... .......... 60% 54.6M 5s\n", + "357750K .......... .......... .......... .......... .......... 60% 65.8M 5s\n", + "357800K .......... .......... .......... .......... .......... 60% 41.2M 5s\n", + "357850K .......... .......... .......... .......... .......... 60% 47.1M 5s\n", + "357900K .......... .......... .......... .......... .......... 60% 62.0M 5s\n", + "357950K .......... .......... .......... .......... .......... 60% 63.3M 5s\n", + "358000K .......... .......... .......... .......... .......... 60% 46.6M 5s\n", + "358050K .......... .......... .......... .......... .......... 60% 62.5M 5s\n", + "358100K .......... .......... .......... .......... .......... 60% 47.2M 5s\n", + "358150K .......... .......... .......... .......... .......... 60% 51.2M 5s\n", + "358200K .......... .......... .......... .......... .......... 60% 47.2M 5s\n", + "358250K .......... .......... .......... .......... .......... 60% 64.4M 5s\n", + "358300K .......... .......... .......... .......... .......... 60% 57.5M 5s\n", + "358350K .......... .......... .......... .......... .......... 60% 51.5M 5s\n", + "358400K .......... .......... .......... .......... .......... 60% 53.0M 5s\n", + "358450K .......... .......... .......... .......... .......... 60% 53.5M 5s\n", + "358500K .......... .......... .......... .......... .......... 60% 64.4M 5s\n", + "358550K .......... .......... .......... .......... .......... 60% 54.8M 5s\n", + "358600K .......... .......... .......... .......... .......... 60% 46.4M 5s\n", + "358650K .......... .......... .......... .......... .......... 60% 63.8M 5s\n", + "358700K .......... .......... .......... .......... .......... 60% 54.2M 5s\n", + "358750K .......... .......... .......... .......... .......... 60% 50.4M 5s\n", + "358800K .......... .......... .......... .......... .......... 60% 49.1M 5s\n", + "358850K .......... .......... .......... .......... .......... 60% 61.5M 5s\n", + "358900K .......... .......... .......... .......... .......... 60% 72.4M 5s\n", + "358950K .......... .......... .......... .......... .......... 60% 57.6M 5s\n", + "359000K .......... .......... .......... .......... .......... 60% 47.8M 5s\n", + "359050K .......... .......... .......... .......... .......... 60% 54.6M 5s\n", + "359100K .......... .......... .......... .......... .......... 60% 7.01M 5s\n", + "359150K .......... .......... .......... .......... .......... 60% 66.8M 5s\n", + "359200K .......... .......... .......... .......... .......... 60% 63.5M 5s\n", + "359250K .......... .......... .......... .......... .......... 60% 65.4M 5s\n", + "359300K .......... .......... .......... .......... .......... 60% 65.0M 5s\n", + "359350K .......... .......... .......... .......... .......... 60% 67.0M 5s\n", + "359400K .......... .......... .......... .......... .......... 60% 47.1M 5s\n", + "359450K .......... .......... .......... .......... .......... 60% 62.9M 5s\n", + "359500K .......... .......... .......... .......... .......... 60% 72.6M 5s\n", + "359550K .......... .......... .......... .......... .......... 60% 59.8M 5s\n", + "359600K .......... .......... .......... .......... .......... 60% 53.1M 5s\n", + "359650K .......... .......... .......... .......... .......... 60% 61.0M 5s\n", + "359700K .......... .......... .......... .......... .......... 60% 49.6M 5s\n", + "359750K .......... .......... .......... .......... .......... 60% 65.6M 5s\n", + "359800K .......... .......... .......... .......... .......... 60% 48.8M 5s\n", + "359850K .......... .......... .......... .......... .......... 60% 54.1M 5s\n", + "359900K .......... .......... .......... .......... .......... 60% 64.7M 5s\n", + "359950K .......... .......... .......... .......... .......... 60% 50.4M 5s\n", + "360000K .......... .......... .......... .......... .......... 60% 58.6M 5s\n", + "360050K .......... .......... .......... .......... .......... 60% 65.9M 5s\n", + "360100K .......... .......... .......... .......... .......... 60% 50.3M 5s\n", + "360150K .......... .......... .......... .......... .......... 60% 56.9M 5s\n", + "360200K .......... .......... .......... .......... .......... 60% 39.3M 5s\n", + "360250K .......... .......... .......... .......... .......... 60% 67.3M 5s\n", + "360300K .......... .......... .......... .......... .......... 60% 68.5M 5s\n", + "360350K .......... .......... .......... .......... .......... 60% 48.8M 5s\n", + "360400K .......... .......... .......... .......... .......... 60% 53.3M 5s\n", + "360450K .......... .......... .......... .......... .......... 60% 51.2M 5s\n", + "360500K .......... .......... .......... .......... .......... 60% 61.7M 5s\n", + "360550K .......... .......... .......... .......... .......... 60% 65.9M 5s\n", + "360600K .......... .......... .......... .......... .......... 60% 43.8M 5s\n", + "360650K .......... .......... .......... .......... .......... 60% 65.1M 5s\n", + "360700K .......... .......... .......... .......... .......... 60% 69.6M 5s\n", + "360750K .......... .......... .......... .......... .......... 60% 59.5M 5s\n", + "360800K .......... .......... .......... .......... .......... 60% 56.9M 5s\n", + "360850K .......... .......... .......... .......... .......... 60% 55.1M 5s\n", + "360900K .......... .......... .......... .......... .......... 60% 54.3M 5s\n", + "360950K .......... .......... .......... .......... .......... 60% 50.7M 5s\n", + "361000K .......... .......... .......... .......... .......... 60% 46.5M 5s\n", + "361050K .......... .......... .......... .......... .......... 60% 69.4M 5s\n", + "361100K .......... .......... .......... .......... .......... 60% 52.2M 5s\n", + "361150K .......... .......... .......... .......... .......... 60% 51.4M 5s\n", + "361200K .......... .......... .......... .......... .......... 60% 47.8M 5s\n", + "361250K .......... .......... .......... .......... .......... 60% 52.4M 5s\n", + "361300K .......... .......... .......... .......... .......... 60% 66.8M 5s\n", + "361350K .......... .......... .......... .......... .......... 60% 57.8M 5s\n", + "361400K .......... .......... .......... .......... .......... 60% 44.5M 5s\n", + "361450K .......... .......... .......... .......... .......... 60% 49.9M 5s\n", + "361500K .......... .......... .......... .......... .......... 60% 61.4M 5s\n", + "361550K .......... .......... .......... .......... .......... 60% 62.3M 5s\n", + "361600K .......... .......... .......... .......... .......... 60% 54.9M 5s\n", + "361650K .......... .......... .......... .......... .......... 60% 53.6M 5s\n", + "361700K .......... .......... .......... .......... .......... 60% 59.6M 5s\n", + "361750K .......... .......... .......... .......... .......... 60% 53.2M 5s\n", + "361800K .......... .......... .......... .......... .......... 60% 58.0M 5s\n", + "361850K .......... .......... .......... .......... .......... 60% 72.7M 5s\n", + "361900K .......... .......... .......... .......... .......... 60% 57.3M 5s\n", + "361950K .......... .......... .......... .......... .......... 60% 61.9M 5s\n", + "362000K .......... .......... .......... .......... .......... 60% 59.4M 5s\n", + "362050K .......... .......... .......... .......... .......... 60% 73.8M 5s\n", + "362100K .......... .......... .......... .......... .......... 60% 61.0M 5s\n", + "362150K .......... .......... .......... .......... .......... 60% 67.6M 5s\n", + "362200K .......... .......... .......... .......... .......... 60% 50.7M 5s\n", + "362250K .......... .......... .......... .......... .......... 60% 47.8M 5s\n", + "362300K .......... .......... .......... .......... .......... 60% 51.8M 5s\n", + "362350K .......... .......... .......... .......... .......... 60% 4.18M 5s\n", + "362400K .......... .......... .......... .......... .......... 60% 58.6M 5s\n", + "362450K .......... .......... .......... .......... .......... 60% 70.3M 5s\n", + "362500K .......... .......... .......... .......... .......... 60% 69.8M 5s\n", + "362550K .......... .......... .......... .......... .......... 60% 63.2M 5s\n", + "362600K .......... .......... .......... .......... .......... 60% 55.2M 5s\n", + "362650K .......... .......... .......... .......... .......... 60% 49.0M 5s\n", + "362700K .......... .......... .......... .......... .......... 60% 71.7M 5s\n", + "362750K .......... .......... .......... .......... .......... 61% 68.0M 5s\n", + "362800K .......... .......... .......... .......... .......... 61% 63.5M 5s\n", + "362850K .......... .......... .......... .......... .......... 61% 52.2M 5s\n", + "362900K .......... .......... .......... .......... .......... 61% 54.4M 5s\n", + "362950K .......... .......... .......... .......... .......... 61% 62.5M 5s\n", + "363000K .......... .......... .......... .......... .......... 61% 60.8M 5s\n", + "363050K .......... .......... .......... .......... .......... 61% 71.8M 5s\n", + "363100K .......... .......... .......... .......... .......... 61% 54.6M 5s\n", + "363150K .......... .......... .......... .......... .......... 61% 52.5M 5s\n", + "363200K .......... .......... .......... .......... .......... 61% 54.7M 5s\n", + "363250K .......... .......... .......... .......... .......... 61% 60.6M 5s\n", + "363300K .......... .......... .......... .......... .......... 61% 69.7M 5s\n", + "363350K .......... .......... .......... .......... .......... 61% 60.0M 5s\n", + "363400K .......... .......... .......... .......... .......... 61% 44.0M 5s\n", + "363450K .......... .......... .......... .......... .......... 61% 54.0M 5s\n", + "363500K .......... .......... .......... .......... .......... 61% 58.8M 5s\n", + "363550K .......... .......... .......... .......... .......... 61% 20.2M 5s\n", + "363600K .......... .......... .......... .......... .......... 61% 45.7M 5s\n", + "363650K .......... .......... .......... .......... .......... 61% 60.5M 5s\n", + "363700K .......... .......... .......... .......... .......... 61% 72.6M 5s\n", + "363750K .......... .......... .......... .......... .......... 61% 69.7M 5s\n", + "363800K .......... .......... .......... .......... .......... 61% 63.0M 5s\n", + "363850K .......... .......... .......... .......... .......... 61% 67.7M 5s\n", + "363900K .......... .......... .......... .......... .......... 61% 59.2M 5s\n", + "363950K .......... .......... .......... .......... .......... 61% 54.7M 5s\n", + "364000K .......... .......... .......... .......... .......... 61% 57.2M 5s\n", + "364050K .......... .......... .......... .......... .......... 61% 72.4M 5s\n", + "364100K .......... .......... .......... .......... .......... 61% 68.2M 5s\n", + "364150K .......... .......... .......... .......... .......... 61% 66.9M 5s\n", + "364200K .......... .......... .......... .......... .......... 61% 39.2M 5s\n", + "364250K .......... .......... .......... .......... .......... 61% 49.4M 5s\n", + "364300K .......... .......... .......... .......... .......... 61% 64.7M 5s\n", + "364350K .......... .......... .......... .......... .......... 61% 80.1M 5s\n", + "364400K .......... .......... .......... .......... .......... 61% 61.9M 5s\n", + "364450K .......... .......... .......... .......... .......... 61% 51.3M 5s\n", + "364500K .......... .......... .......... .......... .......... 61% 44.8M 5s\n", + "364550K .......... .......... .......... .......... .......... 61% 53.5M 5s\n", + "364600K .......... .......... .......... .......... .......... 61% 57.9M 5s\n", + "364650K .......... .......... .......... .......... .......... 61% 70.9M 5s\n", + "364700K .......... .......... .......... .......... .......... 61% 63.2M 5s\n", + "364750K .......... .......... .......... .......... .......... 61% 46.7M 5s\n", + "364800K .......... .......... .......... .......... .......... 61% 52.2M 5s\n", + "364850K .......... .......... .......... .......... .......... 61% 67.9M 5s\n", + "364900K .......... .......... .......... .......... .......... 61% 66.7M 5s\n", + "364950K .......... .......... .......... .......... .......... 61% 63.3M 5s\n", + "365000K .......... .......... .......... .......... .......... 61% 45.4M 5s\n", + "365050K .......... .......... .......... .......... .......... 61% 55.4M 5s\n", + "365100K .......... .......... .......... .......... .......... 61% 65.3M 5s\n", + "365150K .......... .......... .......... .......... .......... 61% 69.2M 5s\n", + "365200K .......... .......... .......... .......... .......... 61% 64.7M 5s\n", + "365250K .......... .......... .......... .......... .......... 61% 51.7M 5s\n", + "365300K .......... .......... .......... .......... .......... 61% 58.1M 5s\n", + "365350K .......... .......... .......... .......... .......... 61% 56.9M 5s\n", + "365400K .......... .......... .......... .......... .......... 61% 57.9M 5s\n", + "365450K .......... .......... .......... .......... .......... 61% 67.6M 5s\n", + "365500K .......... .......... .......... .......... .......... 61% 62.5M 5s\n", + "365550K .......... .......... .......... .......... .......... 61% 52.1M 5s\n", + "365600K .......... .......... .......... .......... .......... 61% 56.1M 5s\n", + "365650K .......... .......... .......... .......... .......... 61% 61.2M 5s\n", + "365700K .......... .......... .......... .......... .......... 61% 54.0M 5s\n", + "365750K .......... .......... .......... .......... .......... 61% 63.6M 5s\n", + "365800K .......... .......... .......... .......... .......... 61% 51.4M 5s\n", + "365850K .......... .......... .......... .......... .......... 61% 62.0M 5s\n", + "365900K .......... .......... .......... .......... .......... 61% 2.70M 5s\n", + "365950K .......... .......... .......... .......... .......... 61% 58.9M 5s\n", + "366000K .......... .......... .......... .......... .......... 61% 67.3M 5s\n", + "366050K .......... .......... .......... .......... .......... 61% 65.1M 5s\n", + "366100K .......... .......... .......... .......... .......... 61% 64.4M 5s\n", + "366150K .......... .......... .......... .......... .......... 61% 66.5M 5s\n", + "366200K .......... .......... .......... .......... .......... 61% 52.1M 5s\n", + "366250K .......... .......... .......... .......... .......... 61% 50.4M 5s\n", + "366300K .......... .......... .......... .......... .......... 61% 67.8M 5s\n", + "366350K .......... .......... .......... .......... .......... 61% 69.1M 5s\n", + "366400K .......... .......... .......... .......... .......... 61% 60.8M 5s\n", + "366450K .......... .......... .......... .......... .......... 61% 65.9M 5s\n", + "366500K .......... .......... .......... .......... .......... 61% 70.9M 5s\n", + "366550K .......... .......... .......... .......... .......... 61% 62.2M 5s\n", + "366600K .......... .......... .......... .......... .......... 61% 43.9M 5s\n", + "366650K .......... .......... .......... .......... .......... 61% 49.1M 5s\n", + "366700K .......... .......... .......... .......... .......... 61% 65.3M 5s\n", + "366750K .......... .......... .......... .......... .......... 61% 72.4M 5s\n", + "366800K .......... .......... .......... .......... .......... 61% 60.4M 5s\n", + "366850K .......... .......... .......... .......... .......... 61% 47.6M 5s\n", + "366900K .......... .......... .......... .......... .......... 61% 47.2M 5s\n", + "366950K .......... .......... .......... .......... .......... 61% 53.0M 5s\n", + "367000K .......... .......... .......... .......... .......... 61% 59.1M 5s\n", + "367050K .......... .......... .......... .......... .......... 61% 67.3M 5s\n", + "367100K .......... .......... .......... .......... .......... 61% 65.9M 5s\n", + "367150K .......... .......... .......... .......... .......... 61% 52.6M 5s\n", + "367200K .......... .......... .......... .......... .......... 61% 48.1M 5s\n", + "367250K .......... .......... .......... .......... .......... 61% 56.0M 5s\n", + "367300K .......... .......... .......... .......... .......... 61% 65.3M 5s\n", + "367350K .......... .......... .......... .......... .......... 61% 65.8M 5s\n", + "367400K .......... .......... .......... .......... .......... 61% 50.2M 5s\n", + "367450K .......... .......... .......... .......... .......... 61% 49.7M 5s\n", + "367500K .......... .......... .......... .......... .......... 61% 61.6M 5s\n", + "367550K .......... .......... .......... .......... .......... 61% 71.4M 5s\n", + "367600K .......... .......... .......... .......... .......... 61% 5.66M 5s\n", + "367650K .......... .......... .......... .......... .......... 61% 69.3M 5s\n", + "367700K .......... .......... .......... .......... .......... 61% 71.9M 5s\n", + "367750K .......... .......... .......... .......... .......... 61% 68.7M 5s\n", + "367800K .......... .......... .......... .......... .......... 61% 53.0M 5s\n", + "367850K .......... .......... .......... .......... .......... 61% 62.2M 5s\n", + "367900K .......... .......... .......... .......... .......... 61% 73.6M 5s\n", + "367950K .......... .......... .......... .......... .......... 61% 66.2M 5s\n", + "368000K .......... .......... .......... .......... .......... 61% 59.3M 5s\n", + "368050K .......... .......... .......... .......... .......... 61% 67.1M 5s\n", + "368100K .......... .......... .......... .......... .......... 61% 64.5M 5s\n", + "368150K .......... .......... .......... .......... .......... 61% 69.7M 5s\n", + "368200K .......... .......... .......... .......... .......... 61% 58.8M 5s\n", + "368250K .......... .......... .......... .......... .......... 61% 68.5M 5s\n", + "368300K .......... .......... .......... .......... .......... 61% 72.9M 5s\n", + "368350K .......... .......... .......... .......... .......... 61% 68.8M 5s\n", + "368400K .......... .......... .......... .......... .......... 61% 63.2M 5s\n", + "368450K .......... .......... .......... .......... .......... 61% 62.7M 5s\n", + "368500K .......... .......... .......... .......... .......... 61% 70.3M 5s\n", + "368550K .......... .......... .......... .......... .......... 61% 67.6M 5s\n", + "368600K .......... .......... .......... .......... .......... 61% 54.3M 5s\n", + "368650K .......... .......... .......... .......... .......... 61% 67.2M 5s\n", + "368700K .......... .......... .......... .......... .......... 62% 71.7M 5s\n", + "368750K .......... .......... .......... .......... .......... 62% 67.5M 5s\n", + "368800K .......... .......... .......... .......... .......... 62% 63.3M 5s\n", + "368850K .......... .......... .......... .......... .......... 62% 69.2M 5s\n", + "368900K .......... .......... .......... .......... .......... 62% 74.5M 5s\n", + "368950K .......... .......... .......... .......... .......... 62% 70.9M 5s\n", + "369000K .......... .......... .......... .......... .......... 62% 57.8M 5s\n", + "369050K .......... .......... .......... .......... .......... 62% 69.3M 5s\n", + "369100K .......... .......... .......... .......... .......... 62% 475K 5s\n", + "369150K .......... .......... .......... .......... .......... 62% 18.8M 5s\n", + "369200K .......... .......... .......... .......... .......... 62% 59.6M 5s\n", + "369250K .......... .......... .......... .......... .......... 62% 65.2M 5s\n", + "369300K .......... .......... .......... .......... .......... 62% 37.8M 5s\n", + "369350K .......... .......... .......... .......... .......... 62% 24.8M 5s\n", + "369400K .......... .......... .......... .......... .......... 62% 55.4M 5s\n", + "369450K .......... .......... .......... .......... .......... 62% 53.6M 5s\n", + "369500K .......... .......... .......... .......... .......... 62% 36.0M 5s\n", + "369550K .......... .......... .......... .......... .......... 62% 31.0M 5s\n", + "369600K .......... .......... .......... .......... .......... 62% 55.3M 5s\n", + "369650K .......... .......... .......... .......... .......... 62% 52.7M 5s\n", + "369700K .......... .......... .......... .......... .......... 62% 35.2M 5s\n", + "369750K .......... .......... .......... .......... .......... 62% 32.7M 5s\n", + "369800K .......... .......... .......... .......... .......... 62% 33.9M 5s\n", + "369850K .......... .......... .......... .......... .......... 62% 50.1M 5s\n", + "369900K .......... .......... .......... .......... .......... 62% 38.1M 5s\n", + "369950K .......... .......... .......... .......... .......... 62% 34.7M 5s\n", + "370000K .......... .......... .......... .......... .......... 62% 37.2M 5s\n", + "370050K .......... .......... .......... .......... .......... 62% 47.3M 5s\n", + "370100K .......... .......... .......... .......... .......... 62% 35.9M 5s\n", + "370150K .......... .......... .......... .......... .......... 62% 36.4M 5s\n", + "370200K .......... .......... .......... .......... .......... 62% 36.8M 5s\n", + "370250K .......... .......... .......... .......... .......... 62% 30.5M 5s\n", + "370300K .......... .......... .......... .......... .......... 62% 59.2M 5s\n", + "370350K .......... .......... .......... .......... .......... 62% 65.5M 5s\n", + "370400K .......... .......... .......... .......... .......... 62% 63.5M 5s\n", + "370450K .......... .......... .......... .......... .......... 62% 68.4M 5s\n", + "370500K .......... .......... .......... .......... .......... 62% 72.3M 5s\n", + "370550K .......... .......... .......... .......... .......... 62% 67.6M 5s\n", + "370600K .......... .......... .......... .......... .......... 62% 5.57M 5s\n", + "370650K .......... .......... .......... .......... .......... 62% 59.3M 5s\n", + "370700K .......... .......... .......... .......... .......... 62% 65.0M 5s\n", + "370750K .......... .......... .......... .......... .......... 62% 51.7M 5s\n", + "370800K .......... .......... .......... .......... .......... 62% 21.8M 5s\n", + "370850K .......... .......... .......... .......... .......... 62% 35.6M 5s\n", + "370900K .......... .......... .......... .......... .......... 62% 66.3M 5s\n", + "370950K .......... .......... .......... .......... .......... 62% 53.1M 5s\n", + "371000K .......... .......... .......... .......... .......... 62% 31.8M 5s\n", + "371050K .......... .......... .......... .......... .......... 62% 30.8M 5s\n", + "371100K .......... .......... .......... .......... .......... 62% 75.6M 5s\n", + "371150K .......... .......... .......... .......... .......... 62% 51.7M 5s\n", + "371200K .......... .......... .......... .......... .......... 62% 33.6M 5s\n", + "371250K .......... .......... .......... .......... .......... 62% 31.6M 5s\n", + "371300K .......... .......... .......... .......... .......... 62% 50.3M 5s\n", + "371350K .......... .......... .......... .......... .......... 62% 49.3M 5s\n", + "371400K .......... .......... .......... .......... .......... 62% 30.7M 5s\n", + "371450K .......... .......... .......... .......... .......... 62% 30.5M 5s\n", + "371500K .......... .......... .......... .......... .......... 62% 59.8M 5s\n", + "371550K .......... .......... .......... .......... .......... 62% 45.4M 5s\n", + "371600K .......... .......... .......... .......... .......... 62% 35.8M 5s\n", + "371650K .......... .......... .......... .......... .......... 62% 38.9M 5s\n", + "371700K .......... .......... .......... .......... .......... 62% 37.9M 5s\n", + "371750K .......... .......... .......... .......... .......... 62% 43.6M 5s\n", + "371800K .......... .......... .......... .......... .......... 62% 38.7M 5s\n", + "371850K .......... .......... .......... .......... .......... 62% 38.7M 5s\n", + "371900K .......... .......... .......... .......... .......... 62% 46.2M 5s\n", + "371950K .......... .......... .......... .......... .......... 62% 52.2M 5s\n", + "372000K .......... .......... .......... .......... .......... 62% 33.4M 5s\n", + "372050K .......... .......... .......... .......... .......... 62% 52.4M 5s\n", + "372100K .......... .......... .......... .......... .......... 62% 40.0M 5s\n", + "372150K .......... .......... .......... .......... .......... 62% 63.5M 5s\n", + "372200K .......... .......... .......... .......... .......... 62% 26.4M 5s\n", + "372250K .......... .......... .......... .......... .......... 62% 43.6M 5s\n", + "372300K .......... .......... .......... .......... .......... 62% 42.8M 5s\n", + "372350K 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.......... .......... .......... .......... .......... 62% 49.9M 5s\n", + "374200K .......... .......... .......... .......... .......... 62% 57.8M 5s\n", + "374250K .......... .......... .......... .......... .......... 62% 56.2M 5s\n", + "374300K .......... .......... .......... .......... .......... 62% 64.1M 5s\n", + "374350K .......... .......... .......... .......... .......... 62% 62.1M 5s\n", + "374400K .......... .......... .......... .......... .......... 62% 46.5M 5s\n", + "374450K .......... .......... .......... .......... .......... 62% 72.3M 5s\n", + "374500K .......... .......... .......... .......... .......... 62% 60.6M 5s\n", + "374550K .......... .......... .......... .......... .......... 62% 49.1M 5s\n", + "374600K .......... .......... .......... .......... .......... 62% 56.2M 5s\n", + "374650K .......... .......... .......... .......... .......... 63% 52.8M 5s\n", + "374700K .......... .......... .......... .......... .......... 63% 73.7M 5s\n", + "374750K .......... .......... .......... .......... .......... 63% 68.2M 5s\n", + "374800K .......... .......... .......... .......... .......... 63% 48.1M 5s\n", + "374850K .......... .......... .......... .......... .......... 63% 58.9M 5s\n", + "374900K .......... .......... .......... .......... .......... 63% 67.6M 5s\n", + "374950K .......... .......... .......... .......... .......... 63% 60.6M 5s\n", + "375000K .......... .......... .......... .......... .......... 63% 55.9M 5s\n", + "375050K .......... .......... .......... .......... .......... 63% 62.6M 5s\n", + "375100K .......... .......... .......... .......... .......... 63% 56.0M 5s\n", + "375150K .......... .......... .......... .......... .......... 63% 60.0M 5s\n", + "375200K .......... .......... .......... .......... .......... 63% 51.0M 5s\n", + "375250K .......... .......... .......... .......... .......... 63% 70.0M 5s\n", + "375300K .......... .......... .......... .......... .......... 63% 72.4M 5s\n", + "375350K 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.......... .......... .......... .......... .......... 63% 50.3M 5s\n", + "376000K .......... .......... .......... .......... .......... 63% 51.6M 5s\n", + "376050K .......... .......... .......... .......... .......... 63% 66.0M 5s\n", + "376100K .......... .......... .......... .......... .......... 63% 68.0M 5s\n", + "376150K .......... .......... .......... .......... .......... 63% 62.6M 5s\n", + "376200K .......... .......... .......... .......... .......... 63% 42.2M 5s\n", + "376250K .......... .......... .......... .......... .......... 63% 48.7M 5s\n", + "376300K .......... .......... .......... .......... .......... 63% 55.2M 5s\n", + "376350K .......... .......... .......... .......... .......... 63% 64.8M 5s\n", + "376400K .......... .......... .......... .......... .......... 63% 60.3M 5s\n", + "376450K .......... .......... .......... .......... .......... 63% 64.7M 5s\n", + "376500K .......... .......... .......... .......... .......... 63% 47.1M 5s\n", + "376550K 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.......... .......... .......... .......... .......... 63% 73.5M 5s\n", + "377200K .......... .......... .......... .......... .......... 63% 61.4M 5s\n", + "377250K .......... .......... .......... .......... .......... 63% 66.2M 5s\n", + "377300K .......... .......... .......... .......... .......... 63% 47.1M 5s\n", + "377350K .......... .......... .......... .......... .......... 63% 50.3M 5s\n", + "377400K .......... .......... .......... .......... .......... 63% 56.1M 5s\n", + "377450K .......... .......... .......... .......... .......... 63% 70.7M 5s\n", + "377500K .......... .......... .......... .......... .......... 63% 68.2M 5s\n", + "377550K .......... .......... .......... .......... .......... 63% 55.9M 5s\n", + "377600K .......... .......... .......... .......... .......... 63% 45.2M 5s\n", + "377650K .......... .......... .......... .......... .......... 63% 54.8M 5s\n", + "377700K .......... .......... .......... .......... .......... 63% 64.2M 5s\n", + "377750K .......... .......... .......... .......... .......... 63% 76.6M 5s\n", + "377800K .......... .......... .......... .......... .......... 63% 46.0M 5s\n", + "377850K .......... .......... .......... .......... .......... 63% 50.3M 5s\n", + "377900K .......... .......... .......... .......... .......... 63% 50.9M 5s\n", + "377950K .......... .......... .......... .......... .......... 63% 68.0M 5s\n", + "378000K .......... .......... .......... .......... .......... 63% 64.5M 5s\n", + "378050K .......... .......... .......... .......... .......... 63% 65.4M 5s\n", + "378100K .......... .......... .......... .......... .......... 63% 58.4M 5s\n", + "378150K .......... .......... .......... .......... .......... 63% 59.6M 5s\n", + "378200K .......... .......... .......... .......... .......... 63% 48.6M 5s\n", + "378250K .......... .......... .......... .......... .......... 63% 70.7M 5s\n", + "378300K .......... .......... .......... .......... .......... 63% 72.2M 5s\n", + "378350K .......... .......... .......... .......... .......... 63% 75.7M 5s\n", + "378400K .......... .......... .......... .......... .......... 63% 55.4M 5s\n", + "378450K .......... .......... .......... .......... .......... 63% 53.7M 5s\n", + "378500K .......... .......... .......... .......... .......... 63% 50.9M 5s\n", + "378550K .......... .......... .......... .......... .......... 63% 73.6M 5s\n", + "378600K .......... .......... .......... .......... .......... 63% 57.0M 5s\n", + "378650K .......... .......... .......... .......... .......... 63% 80.3M 5s\n", + "378700K .......... .......... .......... .......... .......... 63% 57.9M 5s\n", + "378750K .......... .......... .......... .......... .......... 63% 55.5M 5s\n", + "378800K .......... .......... .......... .......... .......... 63% 59.1M 5s\n", + "378850K .......... .......... .......... .......... .......... 63% 69.5M 5s\n", + "378900K .......... .......... .......... .......... .......... 63% 69.4M 5s\n", + "378950K .......... .......... .......... .......... .......... 63% 63.3M 5s\n", + "379000K .......... .......... .......... .......... .......... 63% 58.5M 5s\n", + "379050K .......... .......... .......... .......... .......... 63% 73.8M 5s\n", + "379100K .......... .......... .......... .......... .......... 63% 64.4M 5s\n", + "379150K .......... .......... .......... .......... .......... 63% 51.2M 5s\n", + "379200K .......... .......... .......... .......... .......... 63% 50.1M 5s\n", + "379250K .......... .......... .......... .......... .......... 63% 51.8M 5s\n", + "379300K .......... .......... .......... .......... .......... 63% 71.5M 5s\n", + "379350K .......... .......... .......... .......... .......... 63% 67.7M 5s\n", + "379400K .......... .......... .......... .......... .......... 63% 49.5M 5s\n", + "379450K .......... .......... .......... .......... .......... 63% 52.5M 5s\n", + "379500K .......... .......... .......... .......... .......... 63% 47.7M 5s\n", + "379550K .......... .......... .......... .......... .......... 63% 64.3M 5s\n", + "379600K .......... .......... .......... .......... .......... 63% 67.6M 5s\n", + "379650K .......... .......... .......... .......... .......... 63% 76.2M 5s\n", + "379700K .......... .......... .......... .......... .......... 63% 56.6M 5s\n", + "379750K .......... .......... .......... .......... .......... 63% 49.2M 5s\n", + "379800K .......... .......... .......... .......... .......... 63% 42.9M 5s\n", + "379850K .......... .......... .......... .......... .......... 63% 61.3M 5s\n", + "379900K .......... .......... .......... .......... .......... 63% 65.4M 5s\n", + "379950K .......... .......... .......... .......... .......... 63% 3.93M 5s\n", + "380000K .......... .......... .......... .......... .......... 63% 60.3M 5s\n", + "380050K .......... .......... .......... .......... .......... 63% 74.9M 5s\n", + "380100K .......... .......... .......... .......... .......... 63% 69.0M 5s\n", + "380150K .......... .......... .......... .......... .......... 63% 74.2M 5s\n", + "380200K .......... .......... .......... .......... .......... 63% 54.8M 5s\n", + "380250K .......... .......... .......... .......... .......... 63% 50.1M 5s\n", + "380300K .......... .......... .......... .......... .......... 63% 47.7M 5s\n", + "380350K .......... .......... .......... .......... .......... 63% 66.1M 5s\n", + "380400K .......... .......... .......... .......... .......... 63% 56.4M 5s\n", + "380450K .......... .......... .......... .......... .......... 63% 72.3M 5s\n", + "380500K .......... .......... .......... .......... .......... 63% 62.6M 5s\n", + "380550K .......... .......... .......... .......... .......... 63% 50.1M 5s\n", + "380600K .......... .......... .......... .......... .......... 64% 41.5M 5s\n", + "380650K .......... .......... .......... .......... .......... 64% 67.9M 5s\n", + "380700K .......... .......... .......... .......... .......... 64% 70.4M 5s\n", + "380750K .......... .......... .......... .......... .......... 64% 62.7M 5s\n", + "380800K .......... .......... .......... .......... .......... 64% 45.5M 5s\n", + "380850K .......... .......... .......... .......... .......... 64% 49.0M 5s\n", + "380900K .......... .......... .......... .......... .......... 64% 59.9M 5s\n", + "380950K .......... .......... .......... .......... .......... 64% 72.7M 5s\n", + "381000K .......... .......... .......... .......... .......... 64% 63.0M 5s\n", + "381050K .......... .......... .......... .......... .......... 64% 64.0M 5s\n", + "381100K .......... .......... .......... .......... .......... 64% 63.8M 5s\n", + "381150K .......... .......... .......... .......... .......... 64% 52.8M 5s\n", + "381200K .......... .......... .......... .......... .......... 64% 60.5M 5s\n", + "381250K .......... .......... .......... .......... .......... 64% 71.2M 5s\n", + "381300K .......... .......... .......... .......... .......... 64% 68.4M 5s\n", + "381350K .......... .......... .......... .......... .......... 64% 62.2M 5s\n", + "381400K .......... .......... .......... .......... .......... 64% 41.4M 5s\n", + "381450K .......... .......... .......... .......... .......... 64% 59.1M 5s\n", + "381500K .......... .......... .......... .......... .......... 64% 67.8M 5s\n", + "381550K .......... .......... .......... .......... .......... 64% 68.3M 5s\n", + "381600K .......... .......... .......... .......... .......... 64% 56.3M 5s\n", + "381650K .......... .......... .......... .......... .......... 64% 51.3M 5s\n", + "381700K .......... .......... .......... .......... .......... 64% 44.4M 5s\n", + "381750K .......... .......... .......... .......... .......... 64% 68.6M 5s\n", + "381800K .......... .......... .......... .......... .......... 64% 59.3M 5s\n", + "381850K .......... .......... .......... .......... .......... 64% 58.8M 5s\n", + "381900K .......... .......... .......... .......... .......... 64% 49.4M 5s\n", + "381950K .......... .......... .......... .......... .......... 64% 49.9M 5s\n", + "382000K .......... .......... .......... .......... .......... 64% 57.2M 5s\n", + "382050K .......... .......... .......... .......... .......... 64% 65.6M 5s\n", + "382100K .......... .......... .......... .......... .......... 64% 69.6M 5s\n", + "382150K .......... .......... .......... .......... .......... 64% 53.2M 5s\n", + "382200K .......... .......... .......... .......... .......... 64% 43.5M 5s\n", + "382250K .......... .......... .......... .......... .......... 64% 65.1M 5s\n", + "382300K .......... .......... .......... .......... .......... 64% 68.2M 5s\n", + "382350K .......... .......... .......... .......... .......... 64% 64.8M 5s\n", + "382400K .......... .......... .......... .......... .......... 64% 48.7M 5s\n", + "382450K .......... .......... .......... .......... .......... 64% 6.36M 5s\n", + "382500K .......... .......... .......... .......... .......... 64% 57.5M 5s\n", + "382550K .......... .......... .......... .......... .......... 64% 63.0M 5s\n", + "382600K .......... .......... .......... .......... .......... 64% 56.8M 5s\n", + "382650K .......... .......... .......... .......... .......... 64% 74.2M 5s\n", + "382700K .......... .......... .......... .......... .......... 64% 8.09M 5s\n", + "382750K .......... .......... .......... .......... .......... 64% 69.7M 5s\n", + "382800K .......... .......... .......... .......... .......... 64% 61.9M 5s\n", + "382850K .......... .......... .......... .......... .......... 64% 68.9M 5s\n", + "382900K .......... .......... .......... .......... .......... 64% 73.5M 5s\n", + "382950K .......... .......... .......... .......... .......... 64% 64.4M 5s\n", + "383000K .......... .......... .......... .......... .......... 64% 55.4M 5s\n", + "383050K .......... .......... .......... .......... .......... 64% 68.7M 5s\n", + "383100K .......... .......... .......... .......... .......... 64% 64.0M 5s\n", + "383150K .......... .......... .......... .......... .......... 64% 66.9M 5s\n", + "383200K .......... .......... .......... .......... .......... 64% 61.0M 5s\n", + "383250K .......... .......... .......... .......... .......... 64% 72.2M 5s\n", + "383300K .......... .......... .......... .......... .......... 64% 79.2M 5s\n", + "383350K .......... .......... .......... .......... .......... 64% 68.5M 5s\n", + "383400K .......... .......... .......... .......... .......... 64% 59.2M 5s\n", + "383450K .......... .......... .......... .......... .......... 64% 71.5M 5s\n", + "383500K .......... .......... .......... .......... .......... 64% 68.8M 5s\n", + "383550K .......... .......... .......... .......... .......... 64% 67.0M 5s\n", + "383600K .......... .......... .......... .......... .......... 64% 56.4M 5s\n", + "383650K .......... .......... .......... .......... .......... 64% 69.3M 5s\n", + "383700K .......... .......... .......... .......... .......... 64% 69.9M 5s\n", + "383750K .......... .......... .......... .......... .......... 64% 71.8M 5s\n", + "383800K .......... .......... .......... .......... .......... 64% 61.2M 5s\n", + "383850K .......... .......... .......... .......... .......... 64% 73.0M 5s\n", + "383900K .......... .......... .......... .......... .......... 64% 64.2M 5s\n", + "383950K .......... .......... .......... .......... .......... 64% 66.7M 5s\n", + "384000K .......... .......... .......... .......... .......... 64% 56.1M 5s\n", + "384050K .......... .......... .......... .......... .......... 64% 74.7M 5s\n", + "384100K .......... .......... .......... .......... .......... 64% 71.7M 5s\n", + "384150K .......... .......... .......... .......... .......... 64% 68.8M 5s\n", + "384200K .......... .......... .......... .......... .......... 64% 56.7M 5s\n", + "384250K .......... .......... .......... .......... .......... 64% 74.0M 5s\n", + "384300K .......... .......... .......... .......... .......... 64% 69.3M 5s\n", + "384350K .......... .......... .......... .......... .......... 64% 313K 5s\n", + "384400K .......... .......... .......... .......... .......... 64% 32.6M 5s\n", + "384450K .......... .......... .......... .......... .......... 64% 52.3M 5s\n", + "384500K .......... .......... .......... .......... .......... 64% 70.1M 5s\n", + "384550K .......... .......... .......... .......... .......... 64% 80.1M 5s\n", + "384600K .......... .......... .......... .......... .......... 64% 52.6M 5s\n", + "384650K .......... .......... .......... .......... .......... 64% 49.7M 5s\n", + "384700K .......... .......... .......... .......... .......... 64% 38.2M 5s\n", + "384750K .......... .......... .......... .......... .......... 64% 57.5M 5s\n", + "384800K .......... .......... .......... .......... .......... 64% 62.5M 5s\n", + "384850K .......... .......... .......... .......... .......... 64% 60.0M 5s\n", + "384900K .......... .......... .......... .......... .......... 64% 47.7M 5s\n", + "384950K .......... .......... .......... .......... .......... 64% 38.8M 5s\n", + "385000K .......... .......... .......... .......... .......... 64% 50.0M 5s\n", + "385050K .......... .......... .......... .......... .......... 64% 62.8M 5s\n", + "385100K .......... .......... .......... .......... .......... 64% 48.5M 5s\n", + "385150K .......... .......... .......... .......... .......... 64% 41.2M 5s\n", + "385200K .......... .......... .......... .......... .......... 64% 31.8M 5s\n", + "385250K .......... .......... .......... .......... .......... 64% 74.5M 5s\n", + "385300K .......... .......... .......... .......... .......... 64% 49.7M 5s\n", + "385350K .......... .......... .......... .......... .......... 64% 34.9M 5s\n", + "385400K .......... .......... .......... .......... .......... 64% 31.6M 5s\n", "385450K .......... .......... .......... .......... .......... 64% 53.8M 5s\n", - "385500K .......... .......... .......... .......... .......... 64% 66.5M 5s\n", - "385550K .......... .......... .......... .......... .......... 64% 4.40M 5s\n", - "385600K .......... .......... .......... .......... .......... 64% 59.8M 5s\n", - "385650K .......... .......... .......... .......... .......... 64% 65.5M 5s\n", - "385700K .......... .......... .......... .......... .......... 64% 62.8M 5s\n", - "385750K .......... .......... .......... .......... .......... 64% 37.6M 5s\n", - "385800K .......... .......... .......... .......... .......... 64% 36.8M 5s\n", - "385850K .......... .......... .......... .......... .......... 64% 76.3M 5s\n", - "385900K .......... .......... .......... .......... .......... 64% 75.5M 5s\n", - "385950K .......... .......... .......... .......... .......... 64% 30.7M 5s\n", - "386000K .......... .......... .......... .......... .......... 64% 49.6M 5s\n", - "386050K .......... .......... .......... .......... .......... 64% 54.6M 5s\n", - "386100K .......... .......... .......... .......... .......... 64% 71.9M 5s\n", - "386150K .......... .......... .......... .......... .......... 64% 23.9M 5s\n", - "386200K .......... .......... .......... .......... .......... 64% 40.6M 5s\n", - "386250K .......... .......... .......... .......... .......... 64% 58.4M 5s\n", - "386300K .......... .......... .......... .......... .......... 64% 69.2M 5s\n", - "386350K .......... .......... .......... .......... .......... 64% 24.7M 5s\n", - "386400K .......... .......... .......... .......... .......... 64% 45.2M 5s\n", - "386450K .......... .......... .......... .......... .......... 64% 63.1M 5s\n", - "386500K .......... .......... .......... .......... .......... 64% 67.9M 5s\n", - "386550K .......... .......... .......... .......... .......... 65% 60.8M 5s\n", - "386600K .......... .......... .......... .......... .......... 65% 28.0M 5s\n", - "386650K .......... .......... .......... .......... .......... 65% 53.3M 5s\n", - "386700K .......... .......... .......... .......... .......... 65% 59.7M 5s\n", - "386750K .......... .......... .......... .......... .......... 65% 63.2M 5s\n", - "386800K .......... .......... .......... .......... .......... 65% 29.7M 5s\n", - "386850K .......... .......... .......... .......... .......... 65% 52.6M 5s\n", - "386900K .......... .......... .......... .......... .......... 65% 54.2M 5s\n", - "386950K .......... .......... .......... .......... .......... 65% 71.7M 5s\n", - "387000K .......... .......... .......... .......... .......... 65% 27.3M 5s\n", - "387050K .......... .......... .......... .......... .......... 65% 64.0M 5s\n", - "387100K .......... .......... .......... .......... .......... 65% 4.27M 5s\n", - "387150K .......... .......... .......... .......... .......... 65% 52.1M 5s\n", - "387200K .......... .......... .......... .......... .......... 65% 55.6M 5s\n", - "387250K .......... .......... .......... .......... .......... 65% 56.9M 5s\n", - "387300K .......... .......... .......... .......... .......... 65% 66.5M 5s\n", - "387350K .......... .......... .......... .......... .......... 65% 29.8M 5s\n", - "387400K .......... .......... .......... .......... .......... 65% 47.5M 5s\n", - "387450K .......... .......... .......... .......... .......... 65% 64.5M 5s\n", - "387500K .......... .......... .......... .......... .......... 65% 80.5M 5s\n", - "387550K .......... .......... .......... .......... .......... 65% 22.2M 5s\n", - "387600K .......... .......... .......... .......... .......... 65% 30.2M 5s\n", - "387650K .......... .......... .......... .......... .......... 65% 12.7M 5s\n", - "387700K .......... .......... .......... .......... .......... 65% 41.1M 5s\n", - "387750K .......... .......... .......... .......... .......... 65% 73.5M 5s\n", - "387800K .......... .......... .......... .......... .......... 65% 58.7M 5s\n", - "387850K .......... .......... .......... .......... .......... 65% 76.3M 5s\n", - "387900K .......... .......... .......... .......... .......... 65% 49.3M 5s\n", - "387950K .......... .......... .......... .......... .......... 65% 33.2M 5s\n", - "388000K .......... .......... .......... .......... .......... 65% 54.8M 5s\n", - "388050K .......... .......... .......... .......... .......... 65% 70.4M 5s\n", - "388100K .......... .......... .......... .......... .......... 65% 49.6M 5s\n", - "388150K .......... .......... .......... .......... .......... 65% 35.3M 5s\n", - "388200K .......... .......... .......... .......... .......... 65% 41.6M 5s\n", - "388250K .......... .......... .......... .......... .......... 65% 64.5M 5s\n", - "388300K .......... .......... .......... .......... .......... 65% 49.2M 5s\n", - "388350K .......... .......... .......... .......... .......... 65% 37.4M 5s\n", - "388400K .......... .......... .......... .......... .......... 65% 32.7M 5s\n", - "388450K .......... .......... .......... .......... .......... 65% 67.0M 5s\n", - "388500K .......... .......... .......... .......... .......... 65% 56.2M 5s\n", - "388550K .......... .......... .......... .......... .......... 65% 33.3M 5s\n", - "388600K .......... .......... .......... .......... .......... 65% 32.4M 5s\n", - "388650K .......... .......... .......... .......... .......... 65% 66.5M 5s\n", - "388700K .......... .......... .......... .......... .......... 65% 47.8M 5s\n", - "388750K .......... .......... .......... .......... .......... 65% 44.4M 5s\n", - "388800K .......... .......... .......... .......... .......... 65% 35.9M 5s\n", - "388850K .......... .......... .......... .......... .......... 65% 57.2M 5s\n", - "388900K .......... .......... .......... .......... .......... 65% 44.4M 5s\n", - "388950K .......... .......... .......... .......... .......... 65% 43.1M 5s\n", - "389000K .......... .......... .......... .......... .......... 65% 32.4M 5s\n", - "389050K .......... .......... .......... .......... .......... 65% 46.7M 5s\n", - "389100K .......... .......... .......... .......... .......... 65% 54.4M 5s\n", - "389150K .......... .......... .......... .......... .......... 65% 37.1M 5s\n", - "389200K .......... .......... .......... .......... .......... 65% 40.4M 5s\n", - "389250K .......... .......... .......... .......... .......... 65% 42.7M 5s\n", - "389300K .......... .......... .......... .......... .......... 65% 50.3M 5s\n", - "389350K .......... .......... .......... .......... .......... 65% 30.9M 5s\n", - "389400K .......... .......... .......... .......... .......... 65% 40.9M 5s\n", - "389450K .......... .......... .......... .......... .......... 65% 40.8M 5s\n", - "389500K .......... .......... .......... .......... .......... 65% 48.3M 5s\n", - "389550K .......... .......... .......... .......... .......... 65% 52.7M 5s\n", - "389600K .......... .......... .......... .......... .......... 65% 41.9M 5s\n", - "389650K .......... .......... .......... .......... .......... 65% 45.0M 5s\n", - "389700K .......... .......... .......... .......... .......... 65% 53.1M 5s\n", - "389750K .......... .......... .......... .......... .......... 65% 42.0M 5s\n", - "389800K .......... .......... .......... .......... .......... 65% 32.6M 5s\n", - "389850K .......... .......... .......... .......... .......... 65% 45.4M 5s\n", - "389900K .......... .......... .......... .......... .......... 65% 51.3M 5s\n", - "389950K .......... .......... .......... .......... .......... 65% 53.6M 5s\n", - "390000K .......... .......... .......... .......... .......... 65% 44.3M 5s\n", - "390050K .......... .......... .......... .......... .......... 65% 39.6M 5s\n", - "390100K .......... .......... .......... .......... .......... 65% 40.7M 5s\n", - "390150K .......... .......... .......... .......... .......... 65% 49.1M 5s\n", - "390200K .......... .......... .......... .......... .......... 65% 37.0M 5s\n", - "390250K .......... .......... .......... .......... .......... 65% 48.7M 5s\n", - "390300K .......... .......... .......... .......... .......... 65% 39.7M 5s\n", - "390350K .......... .......... .......... .......... .......... 65% 63.1M 5s\n", - "390400K .......... .......... .......... .......... .......... 65% 32.9M 5s\n", - "390450K .......... .......... .......... .......... .......... 65% 40.0M 5s\n", - "390500K .......... .......... .......... .......... .......... 65% 53.6M 5s\n", - "390550K .......... .......... .......... .......... .......... 65% 63.1M 5s\n", - "390600K .......... .......... .......... .......... .......... 65% 45.8M 5s\n", - "390650K .......... .......... .......... .......... .......... 65% 56.1M 5s\n", - "390700K .......... .......... .......... .......... .......... 65% 57.1M 5s\n", - "390750K .......... .......... .......... .......... .......... 65% 51.3M 5s\n", - "390800K .......... .......... .......... .......... .......... 65% 52.5M 5s\n", - "390850K .......... .......... .......... .......... .......... 65% 38.8M 5s\n", - "390900K .......... .......... .......... .......... .......... 65% 40.0M 5s\n", - "390950K .......... .......... .......... .......... .......... 65% 49.0M 5s\n", - "391000K .......... .......... .......... .......... .......... 65% 52.4M 5s\n", - "391050K .......... .......... .......... .......... .......... 65% 50.0M 5s\n", - "391100K .......... .......... .......... .......... .......... 65% 48.3M 5s\n", - "391150K .......... .......... .......... .......... .......... 65% 46.9M 5s\n", - "391200K .......... .......... .......... .......... .......... 65% 49.4M 5s\n", - "391250K .......... .......... .......... .......... .......... 65% 56.1M 5s\n", - "391300K .......... .......... .......... .......... .......... 65% 36.8M 5s\n", - "391350K .......... .......... .......... .......... .......... 65% 46.2M 5s\n", - "391400K .......... .......... .......... .......... .......... 65% 41.5M 5s\n", - "391450K .......... .......... .......... .......... .......... 65% 51.9M 5s\n", - "391500K .......... .......... .......... .......... .......... 65% 50.3M 5s\n", - "391550K .......... .......... .......... .......... .......... 65% 41.0M 5s\n", - "391600K .......... .......... .......... .......... .......... 65% 50.0M 5s\n", - "391650K .......... .......... .......... .......... .......... 65% 46.8M 5s\n", - "391700K .......... .......... .......... .......... .......... 65% 58.2M 5s\n", - "391750K .......... .......... .......... .......... .......... 65% 45.5M 5s\n", - "391800K .......... .......... .......... .......... .......... 65% 38.5M 5s\n", - "391850K .......... .......... .......... .......... .......... 65% 59.9M 5s\n", - "391900K .......... .......... .......... .......... .......... 65% 54.0M 5s\n", - "391950K .......... .......... .......... .......... .......... 65% 48.0M 5s\n", - "392000K .......... .......... .......... .......... .......... 65% 43.6M 5s\n", - "392050K .......... .......... .......... .......... .......... 65% 52.7M 5s\n", - "392100K .......... .......... .......... .......... .......... 65% 55.3M 5s\n", - "392150K .......... .......... .......... .......... .......... 65% 49.6M 5s\n", - "392200K .......... .......... .......... .......... .......... 65% 34.8M 5s\n", - "392250K .......... .......... .......... .......... .......... 65% 42.2M 5s\n", - "392300K .......... .......... .......... .......... .......... 65% 48.4M 5s\n", - "392350K .......... .......... .......... .......... .......... 65% 53.8M 5s\n", - "392400K .......... .......... .......... .......... .......... 65% 42.0M 5s\n", - "392450K .......... .......... .......... .......... .......... 65% 43.9M 5s\n", - "392500K .......... .......... .......... .......... .......... 66% 41.5M 5s\n", - "392550K .......... .......... .......... .......... .......... 66% 48.1M 5s\n", - "392600K .......... .......... .......... .......... .......... 66% 37.0M 5s\n", - "392650K .......... .......... .......... .......... .......... 66% 51.3M 5s\n", - "392700K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", - "392750K .......... .......... .......... .......... .......... 66% 55.5M 5s\n", - "392800K .......... .......... .......... .......... .......... 66% 42.2M 5s\n", - "392850K .......... .......... .......... .......... .......... 66% 39.6M 5s\n", - "392900K .......... .......... .......... .......... .......... 66% 51.4M 5s\n", - "392950K .......... .......... .......... .......... .......... 66% 48.6M 5s\n", - "393000K .......... .......... .......... .......... .......... 66% 40.4M 5s\n", - "393050K .......... .......... .......... .......... .......... 66% 44.0M 5s\n", - "393100K .......... .......... .......... .......... .......... 66% 48.8M 5s\n", - "393150K .......... .......... .......... .......... .......... 66% 41.7M 5s\n", - "393200K .......... .......... .......... .......... .......... 66% 41.1M 5s\n", - "393250K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", - "393300K .......... .......... .......... .......... .......... 66% 45.2M 5s\n", - "393350K .......... .......... .......... .......... .......... 66% 51.5M 5s\n", - "393400K .......... .......... .......... .......... .......... 66% 46.2M 5s\n", - "393450K .......... .......... .......... .......... .......... 66% 43.2M 5s\n", - "393500K .......... .......... .......... .......... .......... 66% 54.7M 5s\n", - "393550K .......... .......... .......... .......... .......... 66% 47.7M 5s\n", - "393600K .......... .......... .......... .......... .......... 66% 54.1M 5s\n", - "393650K .......... .......... .......... .......... .......... 66% 50.9M 5s\n", - "393700K .......... .......... .......... .......... .......... 66% 47.1M 5s\n", - "393750K .......... .......... .......... .......... .......... 66% 42.5M 5s\n", - "393800K .......... .......... .......... .......... .......... 66% 40.1M 5s\n", - "393850K .......... .......... .......... .......... .......... 66% 54.2M 5s\n", - "393900K .......... .......... .......... .......... .......... 66% 45.1M 5s\n", - "393950K .......... .......... .......... .......... .......... 66% 47.5M 5s\n", - "394000K .......... .......... .......... .......... .......... 66% 37.7M 5s\n", - "394050K .......... .......... .......... .......... .......... 66% 40.5M 5s\n", - "394100K .......... .......... .......... .......... .......... 66% 33.7M 5s\n", - "394150K .......... .......... .......... .......... .......... 66% 36.1M 5s\n", - "394200K .......... .......... .......... .......... .......... 66% 35.3M 5s\n", - "394250K .......... .......... .......... .......... .......... 66% 41.2M 5s\n", - "394300K .......... .......... .......... .......... .......... 66% 44.6M 5s\n", - "394350K .......... .......... .......... .......... .......... 66% 38.5M 5s\n", - "394400K .......... .......... .......... .......... .......... 66% 29.3M 5s\n", - "394450K .......... .......... .......... .......... .......... 66% 44.1M 5s\n", - "394500K .......... .......... .......... .......... .......... 66% 52.0M 5s\n", - "394550K .......... .......... .......... .......... .......... 66% 40.2M 5s\n", - "394600K .......... .......... .......... .......... .......... 66% 43.9M 5s\n", - "394650K .......... .......... .......... .......... .......... 66% 43.6M 5s\n", - "394700K .......... .......... .......... .......... .......... 66% 59.5M 5s\n", - "394750K .......... .......... .......... .......... .......... 66% 47.2M 5s\n", - "394800K .......... .......... .......... .......... .......... 66% 43.9M 5s\n", - "394850K .......... .......... .......... .......... .......... 66% 42.4M 5s\n", - "394900K .......... .......... .......... .......... .......... 66% 40.7M 5s\n", - "394950K .......... .......... .......... .......... .......... 66% 37.8M 5s\n", - "395000K .......... .......... .......... .......... .......... 66% 42.0M 5s\n", - "395050K .......... .......... .......... .......... .......... 66% 55.5M 5s\n", - "395100K .......... .......... .......... .......... .......... 66% 50.3M 5s\n", - "395150K .......... .......... .......... .......... .......... 66% 38.3M 5s\n", - "395200K .......... .......... .......... .......... .......... 66% 37.9M 5s\n", - "395250K .......... .......... .......... .......... .......... 66% 35.2M 5s\n", - "395300K .......... .......... .......... .......... .......... 66% 52.4M 5s\n", - "395350K .......... .......... .......... .......... .......... 66% 45.6M 5s\n", - "395400K .......... .......... .......... .......... .......... 66% 39.1M 5s\n", - "395450K .......... .......... .......... .......... .......... 66% 56.2M 5s\n", - "395500K .......... .......... .......... .......... .......... 66% 50.4M 5s\n", - "395550K .......... .......... .......... .......... .......... 66% 44.8M 5s\n", - "395600K .......... .......... .......... .......... .......... 66% 51.4M 5s\n", - "395650K .......... .......... .......... .......... .......... 66% 50.7M 5s\n", - "395700K .......... .......... .......... .......... .......... 66% 47.4M 5s\n", - "395750K .......... .......... .......... .......... .......... 66% 42.1M 5s\n", - "395800K .......... .......... .......... .......... .......... 66% 29.4M 5s\n", - "395850K .......... .......... .......... .......... .......... 66% 43.4M 5s\n", - "395900K .......... .......... .......... .......... .......... 66% 41.1M 5s\n", - "395950K .......... .......... .......... .......... .......... 66% 48.5M 5s\n", - "396000K .......... .......... .......... .......... .......... 66% 43.5M 5s\n", - "396050K .......... .......... .......... .......... .......... 66% 33.1M 5s\n", - "396100K .......... .......... .......... .......... .......... 66% 32.8M 5s\n", - "396150K .......... .......... .......... .......... .......... 66% 33.0M 5s\n", - "396200K .......... .......... .......... .......... .......... 66% 30.5M 5s\n", - "396250K .......... .......... .......... .......... .......... 66% 38.0M 5s\n", - "396300K .......... .......... .......... .......... .......... 66% 50.7M 5s\n", - "396350K .......... .......... .......... .......... .......... 66% 45.9M 5s\n", - "396400K .......... .......... .......... .......... .......... 66% 43.8M 5s\n", - "396450K .......... .......... .......... .......... .......... 66% 45.9M 5s\n", - "396500K .......... .......... .......... .......... .......... 66% 49.6M 5s\n", - "396550K .......... .......... .......... .......... .......... 66% 59.4M 5s\n", - "396600K .......... .......... .......... .......... .......... 66% 37.4M 5s\n", - "396650K .......... .......... .......... .......... .......... 66% 50.5M 5s\n", - "396700K .......... .......... .......... .......... .......... 66% 45.0M 5s\n", - "396750K .......... .......... .......... .......... .......... 66% 3.73M 5s\n", - "396800K .......... .......... .......... .......... .......... 66% 44.3M 5s\n", - "396850K .......... .......... .......... .......... .......... 66% 54.8M 5s\n", - "396900K .......... .......... .......... .......... .......... 66% 47.1M 5s\n", - "396950K .......... .......... .......... .......... .......... 66% 38.9M 5s\n", - "397000K .......... .......... .......... .......... .......... 66% 27.3M 5s\n", - "397050K .......... .......... .......... .......... .......... 66% 34.6M 5s\n", - "397100K .......... .......... .......... .......... .......... 66% 47.4M 5s\n", - "397150K .......... .......... .......... .......... .......... 66% 38.5M 5s\n", - "397200K .......... .......... .......... .......... .......... 66% 30.0M 5s\n", - "397250K .......... .......... .......... .......... .......... 66% 39.8M 5s\n", - "397300K .......... .......... .......... .......... .......... 66% 37.4M 5s\n", - "397350K .......... .......... .......... .......... .......... 66% 31.2M 5s\n", - "397400K .......... .......... .......... .......... .......... 66% 33.1M 5s\n", - "397450K .......... .......... .......... .......... .......... 66% 49.4M 5s\n", - "397500K .......... .......... .......... .......... .......... 66% 24.6M 5s\n", - "397550K .......... .......... .......... .......... .......... 66% 48.7M 5s\n", - "397600K .......... .......... .......... .......... .......... 66% 48.7M 5s\n", - "397650K .......... .......... .......... .......... .......... 66% 57.6M 5s\n", - "397700K .......... .......... .......... .......... .......... 66% 55.3M 5s\n", - "397750K .......... .......... .......... .......... .......... 66% 38.7M 5s\n", - "397800K .......... .......... .......... .......... .......... 66% 39.3M 5s\n", - "397850K .......... .......... .......... .......... .......... 66% 54.0M 5s\n", - "397900K .......... .......... .......... .......... .......... 66% 52.2M 5s\n", - "397950K .......... .......... .......... .......... .......... 66% 56.5M 5s\n", - "398000K .......... .......... .......... .......... .......... 66% 37.6M 5s\n", - "398050K .......... .......... .......... .......... .......... 66% 46.6M 5s\n", - "398100K .......... .......... .......... .......... .......... 66% 3.80M 5s\n", - "398150K .......... .......... .......... .......... .......... 66% 57.9M 5s\n", - "398200K .......... .......... .......... .......... .......... 66% 46.4M 5s\n", - "398250K .......... .......... .......... .......... .......... 66% 60.9M 5s\n", - "398300K .......... .......... .......... .......... .......... 66% 60.2M 5s\n", - "398350K .......... .......... .......... .......... .......... 66% 64.4M 5s\n", - "398400K .......... .......... .......... .......... .......... 66% 49.7M 5s\n", - "398450K .......... .......... .......... .......... .......... 67% 51.4M 5s\n", - "398500K .......... .......... .......... .......... .......... 67% 65.5M 5s\n", - "398550K .......... .......... .......... .......... .......... 67% 61.7M 5s\n", - "398600K .......... .......... .......... .......... .......... 67% 54.0M 5s\n", - "398650K .......... .......... .......... .......... .......... 67% 62.3M 5s\n", - "398700K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", - "398750K .......... .......... .......... .......... .......... 67% 56.4M 5s\n", - "398800K .......... .......... .......... .......... .......... 67% 57.9M 5s\n", - "398850K .......... .......... .......... .......... .......... 67% 65.2M 5s\n", - "398900K .......... .......... .......... .......... .......... 67% 63.2M 5s\n", - "398950K .......... .......... .......... .......... .......... 67% 40.3M 5s\n", - "399000K .......... .......... .......... .......... .......... 67% 45.4M 5s\n", - "399050K .......... .......... .......... .......... .......... 67% 61.5M 5s\n", - "399100K .......... .......... .......... .......... .......... 67% 61.1M 5s\n", - "399150K .......... .......... .......... .......... .......... 67% 62.5M 5s\n", - "399200K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", - "399250K .......... .......... .......... .......... .......... 67% 63.9M 5s\n", - "399300K .......... .......... .......... .......... .......... 67% 59.4M 5s\n", - "399350K .......... .......... .......... .......... .......... 67% 64.0M 5s\n", - "399400K .......... .......... .......... .......... .......... 67% 55.4M 5s\n", - "399450K .......... .......... .......... .......... .......... 67% 54.4M 5s\n", - "399500K .......... .......... .......... .......... .......... 67% 51.4M 5s\n", - "399550K .......... .......... .......... .......... .......... 67% 57.5M 5s\n", - "399600K .......... .......... .......... .......... .......... 67% 59.0M 5s\n", - "399650K .......... .......... .......... .......... .......... 67% 59.3M 5s\n", - "399700K .......... .......... .......... .......... .......... 67% 56.4M 5s\n", - "399750K .......... .......... .......... .......... .......... 67% 53.8M 5s\n", - "399800K .......... .......... .......... .......... .......... 67% 56.7M 5s\n", - "399850K .......... .......... .......... .......... .......... 67% 68.7M 5s\n", - "399900K .......... .......... .......... .......... .......... 67% 70.4M 5s\n", - "399950K .......... .......... .......... .......... .......... 67% 69.2M 5s\n", - "400000K .......... .......... .......... .......... .......... 67% 59.4M 5s\n", - "400050K .......... .......... .......... .......... .......... 67% 54.4M 5s\n", - "400100K .......... .......... .......... .......... .......... 67% 69.5M 5s\n", - "400150K .......... .......... .......... .......... .......... 67% 68.8M 5s\n", - "400200K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", - "400250K .......... .......... .......... .......... .......... 67% 57.0M 5s\n", - "400300K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", - "400350K .......... .......... .......... .......... .......... 67% 52.4M 5s\n", - "400400K .......... .......... .......... .......... .......... 67% 57.1M 5s\n", - "400450K .......... .......... .......... .......... .......... 67% 67.2M 5s\n", - "400500K .......... .......... .......... .......... .......... 67% 52.2M 5s\n", - "400550K .......... .......... .......... .......... .......... 67% 48.6M 5s\n", - "400600K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", - "400650K .......... .......... .......... .......... .......... 67% 64.2M 5s\n", - "400700K .......... .......... .......... .......... .......... 67% 62.9M 5s\n", - "400750K .......... .......... .......... .......... .......... 67% 63.3M 5s\n", - "400800K .......... .......... .......... .......... .......... 67% 46.8M 5s\n", - "400850K .......... .......... .......... .......... .......... 67% 51.6M 5s\n", - "400900K .......... .......... .......... .......... .......... 67% 60.8M 5s\n", - "400950K .......... .......... .......... .......... .......... 67% 57.5M 5s\n", - "401000K .......... .......... .......... .......... .......... 67% 48.0M 5s\n", - "401050K .......... .......... .......... .......... .......... 67% 58.2M 5s\n", - "401100K .......... .......... .......... .......... .......... 67% 51.7M 5s\n", - "401150K .......... .......... .......... .......... .......... 67% 57.7M 5s\n", - "401200K .......... .......... .......... .......... .......... 67% 51.8M 5s\n", - "401250K .......... .......... .......... .......... .......... 67% 58.2M 5s\n", - "401300K .......... .......... .......... .......... .......... 67% 56.5M 5s\n", - "401350K .......... .......... .......... .......... .......... 67% 45.3M 5s\n", - "401400K .......... .......... .......... .......... .......... 67% 63.9M 5s\n", - "401450K .......... .......... .......... .......... .......... 67% 72.5M 5s\n", - "401500K .......... .......... .......... .......... .......... 67% 68.6M 5s\n", - "401550K .......... .......... .......... .......... .......... 67% 63.3M 5s\n", - "401600K .......... .......... .......... .......... .......... 67% 62.7M 5s\n", - "401650K .......... .......... .......... .......... .......... 67% 49.4M 5s\n", - "401700K .......... .......... .......... .......... .......... 67% 58.0M 5s\n", - "401750K .......... .......... .......... .......... .......... 67% 68.2M 5s\n", - "401800K .......... .......... .......... .......... .......... 67% 56.5M 5s\n", - "401850K .......... .......... .......... .......... .......... 67% 23.4M 5s\n", - "401900K .......... .......... .......... .......... .......... 67% 40.4M 5s\n", - "401950K .......... .......... .......... .......... .......... 67% 65.1M 5s\n", - "402000K .......... .......... .......... .......... .......... 67% 53.4M 5s\n", - "402050K .......... .......... .......... .......... .......... 67% 32.9M 5s\n", - "402100K .......... .......... .......... .......... .......... 67% 30.6M 5s\n", - "402150K .......... .......... .......... .......... .......... 67% 69.2M 5s\n", - "402200K .......... .......... .......... .......... .......... 67% 49.5M 5s\n", - "402250K .......... .......... .......... .......... .......... 67% 38.2M 5s\n", - "402300K .......... .......... .......... .......... .......... 67% 30.8M 5s\n", - "402350K .......... .......... .......... .......... .......... 67% 63.4M 5s\n", - "402400K .......... .......... .......... .......... .......... 67% 67.4M 5s\n", - "402450K .......... .......... .......... .......... .......... 67% 27.1M 5s\n", - "402500K .......... .......... .......... .......... .......... 67% 35.0M 5s\n", - "402550K .......... .......... .......... .......... .......... 67% 51.8M 5s\n", - "402600K .......... .......... .......... .......... .......... 67% 28.9M 5s\n", - "402650K .......... .......... .......... .......... .......... 67% 39.9M 5s\n", - "402700K .......... .......... .......... .......... .......... 67% 41.7M 5s\n", - "402750K .......... .......... .......... .......... .......... 67% 53.7M 5s\n", - "402800K .......... .......... .......... .......... .......... 67% 61.5M 5s\n", - "402850K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", - "402900K .......... .......... .......... .......... .......... 67% 56.2M 5s\n", - "402950K .......... .......... .......... .......... .......... 67% 46.7M 5s\n", - "403000K .......... .......... .......... .......... .......... 67% 43.4M 5s\n", - "403050K .......... .......... .......... .......... .......... 67% 31.4M 5s\n", - "403100K .......... .......... .......... .......... .......... 67% 35.9M 5s\n", - "403150K .......... .......... .......... .......... .......... 67% 36.3M 5s\n", - "403200K .......... .......... .......... .......... .......... 67% 45.1M 5s\n", - "403250K .......... .......... .......... .......... .......... 67% 31.3M 5s\n", - "403300K .......... .......... .......... .......... .......... 67% 49.4M 5s\n", - "403350K .......... .......... .......... .......... .......... 67% 42.0M 5s\n", - "403400K .......... .......... .......... .......... .......... 67% 44.3M 5s\n", - "403450K .......... .......... .......... .......... .......... 67% 43.1M 5s\n", - "403500K .......... .......... .......... .......... .......... 67% 44.3M 5s\n", - "403550K .......... .......... .......... .......... .......... 67% 56.2M 5s\n", - "403600K .......... .......... .......... .......... .......... 67% 59.0M 5s\n", - "403650K .......... .......... .......... .......... .......... 67% 51.6M 5s\n", - "403700K .......... .......... .......... .......... .......... 67% 47.9M 5s\n", - "403750K .......... .......... .......... .......... .......... 67% 39.6M 5s\n", - "403800K .......... .......... .......... .......... .......... 67% 47.9M 5s\n", - "403850K .......... .......... .......... .......... .......... 67% 36.1M 5s\n", - "403900K .......... .......... .......... .......... .......... 67% 3.68M 5s\n", - "403950K .......... .......... .......... .......... .......... 67% 58.9M 5s\n", - "404000K .......... .......... .......... .......... .......... 67% 68.3M 5s\n", - "404050K .......... .......... .......... .......... .......... 67% 73.6M 5s\n", - "404100K .......... .......... .......... .......... .......... 67% 20.7M 5s\n", - "404150K .......... .......... .......... .......... .......... 67% 27.7M 5s\n", - "404200K .......... .......... .......... .......... .......... 67% 57.1M 5s\n", - "404250K .......... .......... .......... .......... .......... 67% 55.4M 5s\n", - "404300K .......... .......... .......... .......... .......... 67% 62.6M 5s\n", - "404350K .......... .......... .......... .......... .......... 67% 26.6M 5s\n", - "404400K .......... .......... .......... .......... .......... 68% 58.8M 5s\n", - "404450K .......... .......... .......... .......... .......... 68% 78.0M 5s\n", - "404500K .......... .......... .......... .......... .......... 68% 54.6M 5s\n", - "404550K .......... .......... .......... .......... .......... 68% 25.0M 5s\n", - "404600K .......... .......... .......... .......... .......... 68% 36.4M 5s\n", - "404650K .......... .......... .......... .......... .......... 68% 69.2M 5s\n", - "404700K .......... .......... .......... .......... .......... 68% 52.0M 5s\n", - "404750K .......... .......... .......... .......... .......... 68% 28.4M 5s\n", - "404800K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", - "404850K .......... .......... .......... .......... .......... 68% 54.1M 5s\n", - "404900K .......... .......... .......... .......... .......... 68% 74.9M 5s\n", - "404950K .......... .......... .......... .......... .......... 68% 47.9M 5s\n", - "405000K .......... .......... .......... .......... .......... 68% 32.5M 5s\n", - "405050K .......... .......... .......... .......... .......... 68% 40.6M 5s\n", - "405100K .......... .......... .......... .......... .......... 68% 73.5M 5s\n", - "405150K .......... .......... .......... .......... .......... 68% 53.1M 5s\n", - "405200K .......... .......... .......... .......... .......... 68% 32.2M 5s\n", - "405250K .......... .......... .......... .......... .......... 68% 44.5M 5s\n", - "405300K .......... .......... .......... .......... .......... 68% 51.8M 5s\n", - "405350K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", - "405400K .......... .......... .......... .......... .......... 68% 35.9M 5s\n", - "405450K .......... .......... .......... .......... .......... 68% 39.5M 5s\n", - "405500K .......... .......... .......... .......... .......... 68% 64.6M 5s\n", - "405550K .......... .......... .......... .......... .......... 68% 68.8M 5s\n", - "405600K .......... .......... .......... .......... .......... 68% 33.3M 5s\n", - "405650K .......... .......... .......... .......... .......... 68% 39.1M 5s\n", - "405700K .......... .......... .......... .......... .......... 68% 60.3M 5s\n", - "405750K .......... .......... .......... .......... .......... 68% 52.7M 5s\n", - "405800K .......... .......... .......... .......... .......... 68% 31.6M 5s\n", - "405850K .......... .......... .......... .......... .......... 68% 44.5M 5s\n", - "405900K .......... .......... .......... .......... .......... 68% 41.3M 5s\n", - "405950K .......... .......... .......... .......... .......... 68% 68.9M 5s\n", - "406000K .......... .......... .......... .......... .......... 68% 52.9M 5s\n", - "406050K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", - "406100K .......... .......... .......... .......... .......... 68% 59.3M 5s\n", - "406150K .......... .......... .......... .......... .......... 68% 39.3M 5s\n", - "406200K .......... .......... .......... .......... .......... 68% 28.0M 5s\n", - "406250K .......... .......... .......... .......... .......... 68% 35.7M 5s\n", - "406300K .......... .......... .......... .......... .......... 68% 47.1M 5s\n", - "406350K .......... .......... .......... .......... .......... 68% 59.8M 5s\n", - "406400K .......... .......... .......... .......... .......... 68% 54.0M 5s\n", - "406450K .......... .......... .......... .......... .......... 68% 66.7M 5s\n", - "406500K .......... .......... .......... .......... .......... 68% 53.0M 5s\n", - "406550K .......... .......... .......... .......... .......... 68% 27.6M 5s\n", - "406600K .......... .......... .......... .......... .......... 68% 27.2M 5s\n", - "406650K .......... .......... .......... .......... .......... 68% 29.0M 5s\n", - "406700K .......... .......... .......... .......... .......... 68% 28.2M 5s\n", - "406750K .......... .......... .......... .......... .......... 68% 29.5M 5s\n", - "406800K .......... .......... .......... .......... .......... 68% 42.9M 5s\n", - "406850K .......... .......... .......... .......... .......... 68% 64.4M 5s\n", - "406900K .......... .......... .......... .......... .......... 68% 44.4M 5s\n", - "406950K .......... .......... .......... .......... .......... 68% 55.8M 5s\n", - "407000K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", - "407050K .......... .......... .......... .......... .......... 68% 59.4M 5s\n", - "407100K .......... .......... .......... .......... .......... 68% 48.0M 5s\n", - "407150K .......... .......... .......... .......... .......... 68% 43.8M 5s\n", - "407200K .......... .......... .......... .......... .......... 68% 47.6M 5s\n", - "407250K .......... .......... .......... .......... .......... 68% 41.8M 5s\n", - "407300K .......... .......... .......... .......... .......... 68% 35.7M 5s\n", - "407350K .......... .......... .......... .......... .......... 68% 35.3M 5s\n", - "407400K .......... .......... .......... .......... .......... 68% 35.1M 5s\n", - "407450K .......... .......... .......... .......... .......... 68% 35.0M 5s\n", - "407500K .......... .......... .......... .......... .......... 68% 46.7M 5s\n", - "407550K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", - "407600K .......... .......... .......... .......... .......... 68% 43.7M 5s\n", - "407650K .......... .......... .......... .......... .......... 68% 36.9M 5s\n", - "407700K .......... .......... .......... .......... .......... 68% 53.1M 5s\n", - "407750K .......... .......... .......... .......... .......... 68% 44.1M 5s\n", - "407800K .......... .......... .......... .......... .......... 68% 34.3M 5s\n", - "407850K .......... .......... .......... .......... .......... 68% 38.5M 5s\n", - "407900K .......... .......... .......... .......... .......... 68% 53.3M 5s\n", - "407950K .......... .......... .......... .......... .......... 68% 45.7M 5s\n", - "408000K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", - "408050K .......... .......... .......... .......... .......... 68% 45.9M 5s\n", - "408100K .......... .......... .......... .......... .......... 68% 56.9M 5s\n", - "408150K .......... .......... .......... .......... .......... 68% 51.6M 5s\n", - "408200K .......... .......... .......... .......... .......... 68% 25.4M 5s\n", - "408250K .......... .......... .......... .......... .......... 68% 59.1M 5s\n", - "408300K .......... .......... .......... .......... .......... 68% 61.4M 5s\n", - "408350K .......... .......... .......... .......... .......... 68% 54.5M 5s\n", - "408400K .......... .......... .......... .......... .......... 68% 35.6M 5s\n", - "408450K .......... .......... .......... .......... .......... 68% 39.5M 5s\n", - "408500K .......... .......... .......... .......... .......... 68% 52.1M 5s\n", - "408550K .......... .......... .......... .......... .......... 68% 51.3M 5s\n", - "408600K .......... .......... .......... .......... .......... 68% 28.8M 5s\n", - "408650K .......... .......... .......... .......... .......... 68% 35.5M 5s\n", - "408700K .......... .......... .......... .......... .......... 68% 54.5M 5s\n", - "408750K .......... .......... .......... .......... .......... 68% 45.1M 5s\n", - "408800K .......... .......... .......... .......... .......... 68% 22.8M 5s\n", - "408850K .......... .......... .......... .......... .......... 68% 49.8M 5s\n", - "408900K .......... .......... .......... .......... .......... 68% 50.1M 5s\n", - "408950K .......... .......... .......... .......... .......... 68% 46.0M 5s\n", - "409000K .......... .......... .......... .......... .......... 68% 31.2M 5s\n", - "409050K .......... .......... .......... .......... .......... 68% 68.4M 5s\n", - "409100K .......... .......... .......... .......... .......... 68% 52.5M 5s\n", - "409150K .......... .......... .......... .......... .......... 68% 58.4M 5s\n", - "409200K .......... .......... .......... .......... .......... 68% 29.7M 5s\n", - "409250K .......... .......... .......... .......... .......... 68% 50.1M 5s\n", - "409300K .......... .......... .......... .......... .......... 68% 61.3M 5s\n", - "409350K .......... .......... .......... .......... .......... 68% 46.2M 5s\n", - "409400K .......... .......... .......... .......... .......... 68% 30.5M 5s\n", - "409450K .......... .......... .......... .......... .......... 68% 39.6M 5s\n", - "409500K .......... .......... .......... .......... .......... 68% 38.2M 5s\n", - "409550K .......... .......... .......... .......... .......... 68% 48.1M 5s\n", - "409600K .......... .......... .......... .......... .......... 68% 39.7M 5s\n", - "409650K .......... .......... .......... .......... .......... 68% 31.5M 5s\n", - "409700K .......... .......... .......... .......... .......... 68% 45.1M 5s\n", - "409750K .......... .......... .......... .......... .......... 68% 42.9M 5s\n", - "409800K .......... .......... .......... .......... .......... 68% 39.6M 5s\n", - "409850K .......... .......... .......... .......... .......... 68% 36.8M 5s\n", - "409900K .......... .......... .......... .......... .......... 68% 37.3M 5s\n", - "409950K .......... .......... .......... .......... .......... 68% 46.2M 5s\n", - "410000K .......... .......... .......... .......... .......... 68% 41.8M 5s\n", - "410050K .......... .......... .......... .......... .......... 68% 31.3M 5s\n", - "410100K .......... .......... .......... .......... .......... 68% 44.3M 5s\n", - "410150K .......... .......... .......... .......... .......... 68% 55.2M 5s\n", - "410200K .......... .......... .......... .......... .......... 68% 28.5M 5s\n", - "410250K .......... .......... .......... .......... .......... 68% 43.1M 5s\n", - "410300K .......... .......... .......... .......... .......... 68% 51.9M 5s\n", - "410350K .......... .......... .......... .......... .......... 69% 42.7M 5s\n", - "410400K .......... .......... .......... .......... .......... 69% 42.3M 5s\n", - "410450K .......... .......... .......... .......... .......... 69% 46.5M 5s\n", - "410500K .......... .......... .......... .......... .......... 69% 49.5M 5s\n", - "410550K .......... .......... .......... .......... .......... 69% 44.4M 5s\n", - "410600K .......... .......... .......... .......... .......... 69% 38.4M 5s\n", - "410650K .......... .......... .......... .......... .......... 69% 51.5M 5s\n", - "410700K .......... .......... .......... .......... .......... 69% 44.8M 5s\n", - "410750K .......... .......... .......... .......... .......... 69% 44.9M 5s\n", - "410800K .......... .......... .......... .......... .......... 69% 56.7M 5s\n", - "410850K .......... .......... .......... .......... .......... 69% 40.6M 5s\n", - "410900K .......... .......... .......... .......... .......... 69% 31.8M 5s\n", - "410950K .......... .......... .......... .......... .......... 69% 41.0M 5s\n", - "411000K .......... .......... .......... .......... .......... 69% 41.5M 5s\n", - "411050K .......... .......... .......... .......... .......... 69% 35.5M 5s\n", - "411100K .......... .......... .......... .......... .......... 69% 47.6M 5s\n", - "411150K .......... .......... .......... .......... .......... 69% 43.0M 5s\n", - "411200K .......... .......... .......... .......... .......... 69% 45.2M 5s\n", - "411250K .......... .......... .......... .......... .......... 69% 39.8M 5s\n", - "411300K .......... .......... .......... .......... .......... 69% 50.2M 5s\n", - "411350K .......... .......... .......... .......... .......... 69% 61.2M 5s\n", - "411400K .......... .......... .......... .......... .......... 69% 30.8M 5s\n", - "411450K .......... .......... .......... .......... .......... 69% 32.2M 5s\n", - "411500K .......... .......... .......... .......... .......... 69% 51.2M 5s\n", - "411550K .......... .......... .......... .......... .......... 69% 55.0M 5s\n", - "411600K .......... .......... .......... .......... .......... 69% 29.9M 5s\n", - "411650K .......... .......... .......... .......... .......... 69% 40.0M 5s\n", - "411700K .......... .......... .......... .......... .......... 69% 37.8M 5s\n", - "411750K .......... .......... .......... .......... .......... 69% 34.2M 5s\n", - "411800K .......... .......... .......... .......... .......... 69% 28.9M 5s\n", - "411850K .......... .......... .......... .......... .......... 69% 37.8M 5s\n", - "411900K .......... .......... .......... .......... .......... 69% 41.3M 5s\n", - "411950K .......... .......... .......... .......... .......... 69% 45.0M 5s\n", - "412000K .......... .......... .......... .......... .......... 69% 30.2M 5s\n", - "412050K .......... .......... .......... .......... .......... 69% 46.3M 5s\n", - "412100K .......... .......... .......... .......... .......... 69% 61.4M 5s\n", - "412150K .......... .......... .......... .......... .......... 69% 31.6M 5s\n", - "412200K .......... .......... .......... .......... .......... 69% 30.8M 5s\n", - "412250K .......... .......... .......... .......... .......... 69% 57.9M 5s\n", - "412300K .......... .......... .......... .......... .......... 69% 31.6M 5s\n", - "412350K .......... .......... .......... .......... .......... 69% 78.3M 5s\n", - "412400K .......... .......... .......... .......... .......... 69% 30.2M 5s\n", - "412450K .......... .......... .......... .......... .......... 69% 45.9M 5s\n", - "412500K .......... .......... .......... .......... .......... 69% 52.7M 5s\n", - "412550K .......... .......... .......... .......... .......... 69% 72.8M 5s\n", - "412600K .......... .......... .......... .......... .......... 69% 21.3M 5s\n", - "412650K .......... .......... .......... .......... .......... 69% 44.3M 5s\n", - "412700K .......... .......... .......... .......... .......... 69% 65.5M 5s\n", - "412750K .......... .......... .......... .......... .......... 69% 40.2M 5s\n", - "412800K .......... .......... .......... .......... .......... 69% 25.6M 5s\n", - "412850K .......... .......... .......... .......... .......... 69% 44.7M 5s\n", - "412900K .......... .......... .......... .......... .......... 69% 49.2M 5s\n", - "412950K .......... .......... .......... .......... .......... 69% 38.6M 5s\n", - "413000K .......... .......... .......... .......... .......... 69% 24.8M 5s\n", - "413050K .......... .......... .......... .......... .......... 69% 48.0M 5s\n", - "413100K .......... .......... .......... .......... .......... 69% 37.5M 5s\n", - "413150K .......... .......... .......... .......... .......... 69% 31.7M 5s\n", - "413200K .......... .......... .......... .......... .......... 69% 29.3M 5s\n", - "413250K .......... .......... .......... .......... .......... 69% 37.0M 5s\n", - "413300K .......... .......... .......... .......... .......... 69% 35.5M 5s\n", - "413350K .......... .......... .......... .......... .......... 69% 36.1M 5s\n", - "413400K .......... .......... .......... .......... .......... 69% 33.5M 5s\n", - "413450K .......... .......... .......... .......... .......... 69% 31.9M 5s\n", - "413500K .......... .......... .......... .......... .......... 69% 34.1M 5s\n", - "413550K .......... .......... .......... .......... .......... 69% 38.6M 5s\n", - "413600K .......... .......... .......... .......... .......... 69% 61.9M 5s\n", - "413650K .......... .......... .......... .......... .......... 69% 28.8M 5s\n", - "413700K .......... .......... .......... .......... .......... 69% 36.0M 5s\n", - "413750K .......... .......... .......... .......... .......... 69% 52.3M 5s\n", - "413800K .......... .......... .......... .......... .......... 69% 48.0M 5s\n", - "413850K .......... .......... .......... .......... .......... 69% 36.1M 5s\n", - "413900K .......... .......... .......... .......... .......... 69% 59.8M 5s\n", - "413950K .......... .......... .......... .......... .......... 69% 44.9M 5s\n", - "414000K .......... .......... .......... .......... .......... 69% 56.2M 5s\n", - "414050K .......... .......... .......... .......... .......... 69% 73.0M 5s\n", - "414100K .......... .......... .......... .......... .......... 69% 39.7M 5s\n", - "414150K .......... .......... .......... .......... .......... 69% 34.8M 5s\n", - "414200K .......... .......... .......... .......... .......... 69% 47.6M 5s\n", - "414250K .......... .......... .......... .......... .......... 69% 51.9M 5s\n", - "414300K .......... .......... .......... .......... .......... 69% 36.7M 5s\n", - "414350K .......... .......... .......... .......... .......... 69% 52.6M 5s\n", - "414400K .......... .......... .......... .......... .......... 69% 45.7M 5s\n", - "414450K .......... .......... .......... .......... .......... 69% 63.3M 5s\n", - "414500K .......... .......... .......... .......... .......... 69% 48.2M 5s\n", - "414550K .......... .......... .......... .......... .......... 69% 50.8M 5s\n", - "414600K .......... .......... .......... .......... .......... 69% 41.5M 5s\n", - "414650K .......... .......... .......... .......... .......... 69% 38.5M 5s\n", - "414700K .......... .......... .......... .......... .......... 69% 58.6M 5s\n", - "414750K .......... .......... .......... .......... .......... 69% 51.0M 5s\n", - "414800K .......... .......... .......... .......... .......... 69% 41.3M 5s\n", - "414850K .......... .......... .......... .......... .......... 69% 35.2M 5s\n", - "414900K .......... .......... .......... .......... .......... 69% 7.22M 5s\n", - "414950K .......... .......... .......... .......... .......... 69% 61.3M 5s\n", - "415000K .......... .......... .......... .......... .......... 69% 54.3M 5s\n", - "415050K .......... .......... .......... .......... .......... 69% 77.8M 5s\n", - "415100K .......... .......... .......... .......... .......... 69% 65.1M 5s\n", - "415150K .......... .......... .......... .......... .......... 69% 76.6M 5s\n", - "415200K .......... .......... .......... .......... .......... 69% 70.1M 5s\n", - "415250K .......... .......... .......... .......... .......... 69% 36.9M 5s\n", - "415300K .......... .......... .......... .......... .......... 69% 66.6M 5s\n", - "415350K .......... .......... .......... .......... .......... 69% 58.3M 5s\n", - "415400K .......... .......... .......... .......... .......... 69% 36.4M 5s\n", - "415450K .......... .......... .......... .......... .......... 69% 50.3M 5s\n", - "415500K .......... .......... .......... .......... .......... 69% 42.0M 5s\n", - "415550K .......... .......... .......... .......... .......... 69% 43.9M 5s\n", - "415600K .......... .......... .......... .......... .......... 69% 41.1M 5s\n", - "415650K .......... .......... .......... .......... .......... 69% 57.1M 5s\n", - "415700K .......... .......... .......... .......... .......... 69% 41.0M 5s\n", - "415750K .......... .......... .......... .......... .......... 69% 64.1M 5s\n", - "415800K .......... .......... .......... .......... .......... 69% 27.8M 5s\n", - "415850K .......... .......... .......... .......... .......... 69% 38.2M 5s\n", - "415900K .......... .......... .......... .......... .......... 69% 50.9M 5s\n", - "415950K .......... .......... .......... .......... .......... 69% 48.6M 5s\n", - "416000K .......... .......... .......... .......... .......... 69% 36.6M 5s\n", - "416050K .......... .......... .......... .......... .......... 69% 45.8M 5s\n", - "416100K .......... .......... .......... .......... .......... 69% 59.7M 5s\n", - "416150K .......... .......... .......... .......... .......... 69% 56.3M 5s\n", - "416200K .......... .......... .......... .......... .......... 69% 29.3M 5s\n", - "416250K .......... .......... .......... .......... .......... 69% 56.5M 5s\n", - "416300K .......... .......... .......... .......... .......... 70% 49.2M 5s\n", - "416350K .......... .......... .......... .......... .......... 70% 69.4M 5s\n", - "416400K .......... .......... .......... .......... .......... 70% 26.6M 5s\n", - "416450K .......... .......... .......... .......... .......... 70% 40.4M 5s\n", - "416500K .......... .......... .......... .......... .......... 70% 63.9M 5s\n", - "416550K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", - "416600K .......... .......... .......... .......... .......... 70% 36.7M 5s\n", - "416650K .......... .......... .......... .......... .......... 70% 40.6M 5s\n", - "416700K .......... .......... .......... .......... .......... 70% 67.8M 5s\n", - "416750K .......... .......... .......... .......... .......... 70% 49.8M 5s\n", - "416800K .......... .......... .......... .......... .......... 70% 36.6M 5s\n", - "416850K .......... .......... .......... .......... .......... 70% 56.2M 5s\n", - "416900K .......... .......... .......... .......... .......... 70% 47.6M 5s\n", - "416950K .......... .......... .......... .......... .......... 70% 70.6M 5s\n", - "417000K .......... .......... .......... .......... .......... 70% 35.5M 5s\n", - "417050K .......... .......... .......... .......... .......... 70% 49.0M 5s\n", - "417100K .......... .......... .......... .......... .......... 70% 56.0M 5s\n", - "417150K .......... .......... .......... .......... .......... 70% 77.8M 5s\n", - "417200K .......... .......... .......... .......... .......... 70% 3.66M 5s\n", - "417250K .......... .......... .......... .......... .......... 70% 75.8M 5s\n", - "417300K .......... .......... .......... .......... .......... 70% 68.8M 5s\n", - "417350K .......... .......... .......... .......... .......... 70% 59.4M 5s\n", - "417400K .......... .......... .......... .......... .......... 70% 59.5M 5s\n", - "417450K .......... .......... .......... .......... .......... 70% 64.5M 5s\n", - "417500K .......... .......... .......... .......... .......... 70% 33.9M 5s\n", - "417550K .......... .......... .......... .......... .......... 70% 54.4M 5s\n", - "417600K .......... .......... .......... .......... .......... 70% 63.6M 5s\n", - "417650K .......... .......... .......... .......... .......... 70% 70.8M 5s\n", - "417700K .......... .......... .......... .......... .......... 70% 37.8M 5s\n", - "417750K .......... .......... .......... .......... .......... 70% 29.1M 5s\n", - "417800K .......... .......... .......... .......... .......... 70% 47.2M 5s\n", - "417850K .......... .......... .......... .......... .......... 70% 68.3M 5s\n", - "417900K .......... .......... .......... .......... .......... 70% 42.7M 5s\n", - "417950K .......... .......... .......... .......... .......... 70% 32.9M 5s\n", - "418000K .......... .......... .......... .......... .......... 70% 64.3M 5s\n", - "418050K .......... .......... .......... .......... .......... 70% 66.4M 5s\n", - "418100K .......... .......... .......... .......... .......... 70% 69.6M 5s\n", - "418150K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", - "418200K .......... .......... .......... .......... .......... 70% 35.1M 5s\n", - "418250K .......... .......... .......... .......... .......... 70% 68.4M 5s\n", - "418300K .......... .......... .......... .......... .......... 70% 65.4M 5s\n", - "418350K .......... .......... .......... .......... .......... 70% 48.3M 5s\n", - "418400K .......... .......... .......... .......... .......... 70% 36.8M 5s\n", - "418450K .......... .......... .......... .......... .......... 70% 48.2M 5s\n", - "418500K .......... .......... .......... .......... .......... 70% 75.2M 5s\n", - "418550K .......... .......... .......... .......... .......... 70% 75.3M 5s\n", - "418600K .......... .......... .......... .......... .......... 70% 41.0M 5s\n", - "418650K .......... .......... .......... .......... .......... 70% 31.5M 5s\n", - "418700K .......... .......... .......... .......... .......... 70% 66.9M 5s\n", - "418750K .......... .......... .......... .......... .......... 70% 69.2M 5s\n", - "418800K .......... .......... .......... .......... .......... 70% 43.4M 5s\n", - "418850K .......... .......... .......... .......... .......... 70% 38.1M 5s\n", - "418900K .......... .......... .......... .......... .......... 70% 50.0M 5s\n", - "418950K .......... .......... .......... .......... .......... 70% 63.8M 5s\n", - "419000K .......... .......... .......... .......... .......... 70% 55.1M 5s\n", - "419050K .......... .......... .......... .......... .......... 70% 41.8M 5s\n", - "419100K .......... .......... .......... .......... .......... 70% 38.4M 5s\n", - "419150K .......... .......... .......... .......... .......... 70% 59.3M 5s\n", - "419200K .......... .......... .......... .......... .......... 70% 57.5M 5s\n", - "419250K .......... .......... .......... .......... .......... 70% 36.4M 5s\n", - "419300K .......... .......... .......... .......... .......... 70% 35.7M 5s\n", - "419350K .......... .......... .......... .......... .......... 70% 48.2M 5s\n", - "419400K .......... .......... .......... .......... .......... 70% 33.5M 5s\n", - "419450K .......... .......... .......... .......... .......... 70% 36.2M 5s\n", - "419500K .......... .......... .......... .......... .......... 70% 44.4M 5s\n", - "419550K .......... .......... .......... .......... .......... 70% 63.7M 5s\n", - "419600K .......... .......... .......... .......... .......... 70% 42.0M 5s\n", - "419650K .......... .......... .......... .......... .......... 70% 58.4M 5s\n", - "419700K .......... .......... .......... .......... .......... 70% 33.3M 5s\n", - "419750K .......... .......... .......... .......... .......... 70% 55.3M 5s\n", - "419800K .......... .......... .......... .......... .......... 70% 36.3M 5s\n", - "419850K .......... .......... .......... .......... .......... 70% 36.7M 5s\n", - "419900K .......... .......... .......... .......... .......... 70% 42.6M 5s\n", - "419950K .......... .......... .......... .......... .......... 70% 61.3M 5s\n", - "420000K .......... .......... .......... .......... .......... 70% 37.4M 5s\n", - "420050K .......... .......... .......... .......... .......... 70% 48.5M 5s\n", - "420100K .......... .......... .......... .......... .......... 70% 50.6M 5s\n", - "420150K .......... .......... .......... .......... .......... 70% 40.8M 5s\n", - "420200K .......... .......... .......... .......... .......... 70% 60.6M 5s\n", - "420250K .......... .......... .......... .......... .......... 70% 36.4M 5s\n", - "420300K .......... .......... .......... .......... .......... 70% 40.2M 5s\n", - "420350K .......... .......... .......... .......... .......... 70% 64.7M 5s\n", - "420400K .......... .......... .......... .......... .......... 70% 63.1M 5s\n", - "420450K .......... .......... .......... .......... .......... 70% 64.0M 5s\n", - "420500K .......... .......... .......... .......... .......... 70% 60.0M 5s\n", - "420550K .......... .......... .......... .......... .......... 70% 54.3M 5s\n", - "420600K .......... .......... .......... .......... .......... 70% 57.2M 5s\n", - "420650K .......... .......... .......... .......... .......... 70% 69.1M 5s\n", - "420700K .......... .......... .......... .......... .......... 70% 4.00M 5s\n", - "420750K .......... .......... .......... .......... .......... 70% 32.4M 5s\n", - "420800K .......... .......... .......... .......... .......... 70% 33.5M 5s\n", - "420850K .......... .......... .......... .......... .......... 70% 40.9M 5s\n", - "420900K .......... .......... .......... .......... .......... 70% 27.8M 5s\n", - "420950K .......... .......... .......... .......... .......... 70% 29.4M 5s\n", - "421000K .......... .......... .......... .......... .......... 70% 54.7M 5s\n", - "421050K .......... .......... .......... .......... .......... 70% 29.9M 5s\n", - "421100K .......... .......... .......... .......... .......... 70% 47.1M 5s\n", - "421150K .......... .......... .......... .......... .......... 70% 63.6M 5s\n", - "421200K .......... .......... .......... .......... .......... 70% 61.1M 5s\n", - "421250K .......... .......... .......... .......... .......... 70% 66.9M 5s\n", - "421300K .......... .......... .......... .......... .......... 70% 6.56M 5s\n", - "421350K .......... .......... .......... .......... .......... 70% 14.3M 5s\n", - "421400K .......... .......... .......... .......... .......... 70% 31.1M 5s\n", - "421450K .......... .......... .......... .......... .......... 70% 37.5M 5s\n", - "421500K .......... .......... .......... .......... .......... 70% 29.8M 5s\n", - "421550K .......... .......... .......... .......... .......... 70% 28.7M 5s\n", - "421600K .......... .......... .......... .......... .......... 70% 46.3M 5s\n", - "421650K .......... .......... .......... .......... .......... 70% 62.5M 5s\n", - "421700K .......... .......... .......... .......... .......... 70% 47.9M 5s\n", - "421750K .......... .......... .......... .......... .......... 70% 61.0M 5s\n", - "421800K .......... .......... .......... .......... .......... 70% 56.6M 5s\n", - "421850K .......... .......... .......... .......... .......... 70% 72.6M 5s\n", - "421900K .......... .......... .......... .......... .......... 70% 60.1M 5s\n", - "421950K .......... .......... .......... .......... .......... 70% 56.9M 4s\n", - "422000K .......... .......... .......... .......... .......... 70% 50.1M 4s\n", - "422050K .......... .......... .......... .......... .......... 70% 64.6M 4s\n", - "422100K .......... .......... .......... .......... .......... 70% 42.0M 4s\n", - "422150K .......... .......... .......... .......... .......... 70% 58.2M 4s\n", - "422200K .......... .......... .......... .......... .......... 70% 32.4M 4s\n", - "422250K .......... .......... .......... .......... .......... 71% 46.3M 4s\n", - "422300K .......... .......... .......... .......... .......... 71% 60.5M 4s\n", - "422350K .......... .......... .......... .......... .......... 71% 67.0M 4s\n", - "422400K .......... .......... .......... .......... .......... 71% 43.0M 4s\n", - "422450K .......... .......... .......... .......... .......... 71% 46.7M 4s\n", - "422500K .......... .......... .......... .......... .......... 71% 55.4M 4s\n", - "422550K .......... .......... .......... .......... .......... 71% 67.1M 4s\n", - "422600K .......... .......... .......... .......... .......... 71% 40.3M 4s\n", - "422650K .......... .......... .......... .......... .......... 71% 50.5M 4s\n", - "422700K .......... .......... .......... .......... .......... 71% 52.9M 4s\n", - "422750K .......... .......... .......... .......... .......... 71% 64.5M 4s\n", - "422800K .......... .......... .......... .......... .......... 71% 58.3M 4s\n", - "422850K .......... .......... .......... .......... .......... 71% 69.4M 4s\n", - "422900K .......... .......... .......... .......... .......... 71% 68.2M 4s\n", - "422950K .......... .......... .......... .......... .......... 71% 50.0M 4s\n", - "423000K .......... .......... .......... .......... .......... 71% 46.3M 4s\n", - "423050K .......... .......... .......... .......... .......... 71% 66.9M 4s\n", - "423100K .......... .......... .......... .......... .......... 71% 67.9M 4s\n", - "423150K .......... .......... .......... .......... .......... 71% 7.50M 4s\n", - "423200K .......... .......... .......... .......... .......... 71% 70.4M 4s\n", - "423250K .......... .......... .......... .......... .......... 71% 59.9M 4s\n", - "423300K .......... .......... .......... .......... .......... 71% 54.9M 4s\n", - "423350K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", - "423400K .......... .......... .......... .......... .......... 71% 54.1M 4s\n", - "423450K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", - "423500K .......... .......... .......... .......... .......... 71% 59.6M 4s\n", - "423550K .......... .......... .......... .......... .......... 71% 58.8M 4s\n", - "423600K .......... .......... .......... .......... .......... 71% 57.7M 4s\n", - "423650K .......... .......... .......... .......... .......... 71% 63.8M 4s\n", - "423700K .......... .......... .......... .......... .......... 71% 69.5M 4s\n", - "423750K .......... .......... .......... .......... .......... 71% 55.6M 4s\n", - "423800K .......... .......... .......... .......... .......... 71% 36.6M 4s\n", - "423850K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", - "423900K .......... .......... .......... .......... .......... 71% 72.1M 4s\n", - "423950K .......... .......... .......... .......... .......... 71% 64.0M 4s\n", - "424000K .......... .......... .......... .......... .......... 71% 49.0M 4s\n", - "424050K .......... .......... .......... .......... .......... 71% 45.2M 4s\n", - "424100K .......... .......... .......... .......... .......... 71% 45.8M 4s\n", - "424150K .......... .......... .......... .......... .......... 71% 64.9M 4s\n", - "424200K .......... .......... .......... .......... .......... 71% 54.8M 4s\n", - "424250K .......... .......... .......... .......... .......... 71% 39.1M 4s\n", - "424300K .......... .......... .......... .......... .......... 71% 47.1M 4s\n", - "424350K .......... .......... .......... .......... .......... 71% 53.7M 4s\n", - "424400K .......... .......... .......... .......... .......... 71% 60.3M 4s\n", - "424450K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", - "424500K .......... .......... .......... .......... .......... 71% 56.2M 4s\n", - "424550K .......... .......... .......... .......... .......... 71% 43.2M 4s\n", - "424600K .......... .......... .......... .......... .......... 71% 49.3M 4s\n", - "424650K .......... .......... .......... .......... .......... 71% 3.81M 4s\n", - "424700K .......... .......... .......... .......... .......... 71% 47.1M 4s\n", - "424750K .......... .......... .......... .......... .......... 71% 63.5M 4s\n", - "424800K .......... .......... .......... .......... .......... 71% 50.2M 4s\n", - "424850K .......... .......... .......... .......... .......... 71% 66.7M 4s\n", - "424900K .......... .......... .......... .......... .......... 71% 58.0M 4s\n", - "424950K .......... .......... .......... .......... .......... 71% 56.7M 4s\n", - "425000K .......... .......... .......... .......... .......... 71% 58.8M 4s\n", - "425050K .......... .......... .......... .......... .......... 71% 62.1M 4s\n", - "425100K .......... .......... .......... .......... .......... 71% 51.5M 4s\n", - "425150K .......... .......... .......... .......... .......... 71% 71.6M 4s\n", - "425200K .......... .......... .......... .......... .......... 71% 36.0M 4s\n", - "425250K .......... .......... .......... .......... .......... 71% 66.9M 4s\n", - "425300K .......... .......... .......... .......... .......... 71% 53.7M 4s\n", - "425350K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", - "425400K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", - "425450K .......... .......... .......... .......... .......... 71% 46.8M 4s\n", - "425500K .......... .......... .......... .......... .......... 71% 66.8M 4s\n", - "425550K .......... .......... .......... .......... .......... 71% 57.6M 4s\n", - "425600K .......... .......... .......... .......... .......... 71% 45.9M 4s\n", - "425650K .......... .......... .......... .......... .......... 71% 62.6M 4s\n", - "425700K .......... .......... .......... .......... .......... 71% 46.0M 4s\n", - "425750K .......... .......... .......... .......... .......... 71% 47.9M 4s\n", - "425800K .......... .......... .......... .......... .......... 71% 40.2M 4s\n", - "425850K .......... .......... .......... .......... .......... 71% 67.0M 4s\n", - "425900K .......... .......... .......... .......... .......... 71% 50.5M 4s\n", - "425950K .......... .......... .......... .......... .......... 71% 60.1M 4s\n", - "426000K .......... .......... .......... .......... .......... 71% 66.8M 4s\n", - "426050K .......... .......... .......... .......... .......... 71% 60.6M 4s\n", - "426100K .......... .......... .......... .......... .......... 71% 47.4M 4s\n", - "426150K .......... .......... .......... .......... .......... 71% 50.2M 4s\n", - "426200K .......... .......... .......... .......... .......... 71% 49.2M 4s\n", - "426250K .......... .......... .......... .......... .......... 71% 67.7M 4s\n", - "426300K .......... .......... .......... .......... .......... 71% 34.5M 4s\n", - "426350K .......... .......... .......... .......... .......... 71% 43.8M 4s\n", - "426400K .......... .......... .......... .......... .......... 71% 48.2M 4s\n", - "426450K .......... .......... .......... .......... .......... 71% 61.9M 4s\n", - "426500K .......... .......... .......... .......... .......... 71% 48.7M 4s\n", - "426550K .......... .......... .......... .......... .......... 71% 41.3M 4s\n", - "426600K .......... .......... .......... .......... .......... 71% 39.2M 4s\n", - "426650K .......... .......... .......... .......... .......... 71% 64.2M 4s\n", - "426700K .......... .......... .......... .......... .......... 71% 54.8M 4s\n", - "426750K .......... .......... .......... .......... .......... 71% 44.2M 4s\n", - "426800K .......... .......... .......... .......... .......... 71% 48.5M 4s\n", - "426850K .......... .......... .......... .......... .......... 71% 53.8M 4s\n", - "426900K .......... .......... .......... .......... .......... 71% 65.8M 4s\n", - "426950K .......... .......... .......... .......... .......... 71% 60.8M 4s\n", - "427000K .......... .......... .......... .......... .......... 71% 38.1M 4s\n", - "427050K .......... .......... .......... .......... .......... 71% 47.0M 4s\n", - "427100K .......... .......... .......... .......... .......... 71% 52.8M 4s\n", - "427150K .......... .......... .......... .......... .......... 71% 54.1M 4s\n", - "427200K .......... .......... .......... .......... .......... 71% 51.7M 4s\n", - "427250K .......... .......... .......... .......... .......... 71% 43.4M 4s\n", - "427300K .......... .......... .......... .......... .......... 71% 45.4M 4s\n", - "427350K .......... .......... .......... .......... .......... 71% 46.5M 4s\n", - "427400K .......... .......... .......... .......... .......... 71% 47.3M 4s\n", - "427450K .......... .......... .......... .......... .......... 71% 51.7M 4s\n", - "427500K .......... .......... .......... .......... .......... 71% 49.0M 4s\n", - "427550K .......... .......... .......... .......... .......... 71% 62.0M 4s\n", - "427600K .......... .......... .......... .......... .......... 71% 55.4M 4s\n", - "427650K .......... .......... .......... .......... .......... 71% 25.2M 4s\n", - "427700K .......... .......... .......... .......... .......... 71% 3.48M 4s\n", - "427750K .......... .......... .......... .......... .......... 71% 59.6M 4s\n", - "427800K .......... .......... .......... .......... .......... 71% 47.4M 4s\n", - "427850K .......... .......... .......... .......... .......... 71% 60.5M 4s\n", - "427900K .......... .......... .......... .......... .......... 71% 61.7M 4s\n", - "427950K .......... .......... .......... .......... .......... 71% 47.6M 4s\n", - "428000K .......... .......... .......... .......... .......... 71% 53.4M 4s\n", - "428050K .......... .......... .......... .......... .......... 71% 55.1M 4s\n", - "428100K .......... .......... .......... .......... .......... 71% 36.7M 4s\n", - "428150K .......... .......... .......... .......... .......... 71% 39.3M 4s\n", - "428200K .......... .......... .......... .......... .......... 72% 31.6M 4s\n", - "428250K .......... .......... .......... .......... .......... 72% 34.4M 4s\n", - "428300K .......... .......... .......... .......... .......... 72% 44.5M 4s\n", - "428350K .......... .......... .......... .......... .......... 72% 3.29M 4s\n", - "428400K .......... .......... .......... .......... .......... 72% 38.5M 4s\n", - "428450K .......... .......... .......... .......... .......... 72% 42.8M 4s\n", - "428500K .......... .......... .......... .......... .......... 72% 37.7M 4s\n", - "428550K .......... .......... .......... .......... .......... 72% 32.5M 4s\n", - "428600K .......... .......... .......... .......... .......... 72% 34.2M 4s\n", - "428650K .......... .......... .......... .......... .......... 72% 42.3M 4s\n", - "428700K .......... .......... .......... .......... .......... 72% 31.6M 4s\n", - "428750K .......... .......... .......... .......... .......... 72% 37.8M 4s\n", - "428800K .......... .......... .......... .......... .......... 72% 38.6M 4s\n", - "428850K .......... .......... .......... .......... .......... 72% 34.5M 4s\n", - "428900K .......... .......... .......... .......... .......... 72% 39.8M 4s\n", - "428950K .......... .......... .......... .......... .......... 72% 42.5M 4s\n", - "429000K .......... .......... .......... .......... .......... 72% 35.3M 4s\n", - "429050K .......... .......... .......... .......... .......... 72% 36.4M 4s\n", - "429100K .......... .......... .......... .......... .......... 72% 44.8M 4s\n", - "429150K .......... .......... .......... .......... .......... 72% 43.6M 4s\n", - "429200K .......... .......... .......... .......... .......... 72% 32.4M 4s\n", - "429250K .......... .......... .......... .......... .......... 72% 35.1M 4s\n", - "429300K .......... .......... .......... .......... .......... 72% 42.7M 4s\n", - "429350K .......... .......... .......... .......... .......... 72% 43.3M 4s\n", - "429400K .......... .......... .......... .......... .......... 72% 24.1M 4s\n", - "429450K .......... .......... .......... .......... .......... 72% 38.5M 4s\n", - "429500K .......... .......... .......... .......... .......... 72% 46.9M 4s\n", - "429550K .......... .......... .......... .......... .......... 72% 53.9M 4s\n", - "429600K .......... .......... .......... .......... .......... 72% 52.2M 4s\n", - "429650K .......... .......... .......... .......... .......... 72% 52.5M 4s\n", - "429700K .......... .......... .......... .......... .......... 72% 62.8M 4s\n", - "429750K .......... .......... .......... .......... .......... 72% 65.1M 4s\n", - "429800K .......... .......... .......... .......... .......... 72% 42.7M 4s\n", - "429850K .......... .......... .......... .......... .......... 72% 27.4M 4s\n", - "429900K .......... .......... .......... .......... .......... 72% 38.4M 4s\n", - "429950K .......... .......... .......... .......... .......... 72% 34.9M 4s\n", - "430000K .......... .......... .......... .......... .......... 72% 42.2M 4s\n", - "430050K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", - "430100K .......... .......... .......... .......... .......... 72% 56.0M 4s\n", - "430150K .......... .......... .......... .......... .......... 72% 67.9M 4s\n", - "430200K .......... .......... .......... .......... .......... 72% 54.5M 4s\n", - "430250K .......... .......... .......... .......... .......... 72% 3.83M 4s\n", - "430300K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", - "430350K .......... .......... .......... .......... .......... 72% 63.1M 4s\n", - "430400K .......... .......... .......... .......... .......... 72% 51.4M 4s\n", - "430450K .......... .......... .......... .......... .......... 72% 21.0M 4s\n", - "430500K .......... .......... .......... .......... .......... 72% 60.0M 4s\n", - "430550K .......... .......... .......... .......... .......... 72% 56.6M 4s\n", - "430600K .......... .......... .......... .......... .......... 72% 3.98M 4s\n", - "430650K .......... .......... .......... .......... .......... 72% 64.2M 4s\n", - "430700K .......... .......... .......... .......... .......... 72% 63.7M 4s\n", - "430750K .......... .......... .......... .......... .......... 72% 57.8M 4s\n", - "430800K .......... .......... .......... .......... .......... 72% 59.0M 4s\n", - "430850K .......... .......... .......... .......... .......... 72% 57.0M 4s\n", - "430900K .......... .......... .......... .......... .......... 72% 52.3M 4s\n", - "430950K .......... .......... .......... .......... .......... 72% 69.6M 4s\n", - "431000K .......... .......... .......... .......... .......... 72% 51.7M 4s\n", - "431050K .......... .......... .......... .......... .......... 72% 55.2M 4s\n", - "431100K .......... .......... .......... .......... .......... 72% 62.0M 4s\n", - "431150K .......... .......... .......... .......... .......... 72% 42.1M 4s\n", - "431200K .......... .......... .......... .......... .......... 72% 56.5M 4s\n", - "431250K .......... .......... .......... .......... .......... 72% 55.8M 4s\n", - "431300K .......... .......... .......... .......... .......... 72% 51.8M 4s\n", - "431350K .......... .......... .......... .......... .......... 72% 62.3M 4s\n", - "431400K .......... .......... .......... .......... .......... 72% 45.0M 4s\n", - "431450K .......... .......... .......... .......... .......... 72% 59.7M 4s\n", - "431500K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", - "431550K .......... .......... .......... .......... .......... 72% 51.1M 4s\n", - "431600K .......... .......... .......... .......... .......... 72% 60.2M 4s\n", - "431650K .......... .......... .......... .......... .......... 72% 55.7M 4s\n", - "431700K .......... .......... .......... .......... .......... 72% 59.9M 4s\n", - "431750K .......... .......... .......... .......... .......... 72% 65.5M 4s\n", - "431800K .......... .......... .......... .......... .......... 72% 37.0M 4s\n", - "431850K .......... .......... .......... .......... .......... 72% 65.0M 4s\n", - "431900K .......... .......... .......... .......... .......... 72% 56.2M 4s\n", - "431950K .......... .......... .......... .......... .......... 72% 63.6M 4s\n", - "432000K .......... .......... .......... .......... .......... 72% 61.8M 4s\n", - "432050K .......... .......... .......... .......... .......... 72% 47.7M 4s\n", - "432100K .......... .......... .......... .......... .......... 72% 60.9M 4s\n", - "432150K .......... .......... .......... .......... .......... 72% 61.5M 4s\n", - "432200K .......... .......... .......... .......... .......... 72% 47.6M 4s\n", - "432250K .......... .......... .......... .......... .......... 72% 71.5M 4s\n", - "432300K .......... .......... .......... .......... .......... 72% 52.2M 4s\n", - "432350K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", - "432400K .......... .......... .......... .......... .......... 72% 56.5M 4s\n", - "432450K .......... .......... .......... .......... .......... 72% 68.4M 4s\n", - "432500K .......... .......... .......... .......... .......... 72% 54.8M 4s\n", - "432550K .......... .......... .......... .......... .......... 72% 59.5M 4s\n", - "432600K .......... .......... .......... .......... .......... 72% 40.1M 4s\n", - "432650K .......... .......... .......... .......... .......... 72% 65.1M 4s\n", - "432700K .......... .......... .......... .......... .......... 72% 4.24M 4s\n", - "432750K .......... .......... .......... .......... .......... 72% 59.1M 4s\n", - "432800K .......... .......... .......... .......... .......... 72% 36.1M 4s\n", - "432850K .......... .......... .......... .......... .......... 72% 38.0M 4s\n", - "432900K .......... .......... .......... .......... .......... 72% 43.6M 4s\n", - "432950K .......... .......... .......... .......... .......... 72% 44.3M 4s\n", - "433000K .......... .......... .......... .......... .......... 72% 56.4M 4s\n", - "433050K .......... .......... .......... .......... .......... 72% 72.6M 4s\n", - "433100K .......... .......... .......... .......... .......... 72% 61.3M 4s\n", - "433150K .......... .......... .......... .......... .......... 72% 45.1M 4s\n", - "433200K .......... .......... .......... .......... .......... 72% 49.5M 4s\n", - "433250K .......... .......... .......... .......... .......... 72% 68.6M 4s\n", - "433300K .......... .......... .......... .......... .......... 72% 69.8M 4s\n", - "433350K .......... .......... .......... .......... .......... 72% 70.0M 4s\n", - "433400K .......... .......... .......... .......... .......... 72% 47.6M 4s\n", - "433450K .......... .......... .......... .......... .......... 72% 53.7M 4s\n", - "433500K .......... .......... .......... .......... .......... 72% 58.1M 4s\n", - "433550K .......... .......... .......... .......... .......... 72% 73.9M 4s\n", - "433600K .......... .......... .......... .......... .......... 72% 53.5M 4s\n", - "433650K .......... .......... .......... .......... .......... 72% 70.3M 4s\n", - "433700K .......... .......... .......... .......... .......... 72% 35.5M 4s\n", - "433750K .......... .......... .......... .......... .......... 72% 39.0M 4s\n", - "433800K .......... .......... .......... .......... .......... 72% 40.5M 4s\n", - "433850K .......... .......... .......... .......... .......... 72% 63.5M 4s\n", - "433900K .......... .......... .......... .......... .......... 72% 48.1M 4s\n", - "433950K .......... .......... .......... .......... .......... 72% 41.4M 4s\n", - "434000K .......... .......... .......... .......... .......... 72% 60.1M 4s\n", - "434050K .......... .......... .......... .......... .......... 72% 61.0M 4s\n", - "434100K .......... .......... .......... .......... .......... 72% 64.9M 4s\n", - "434150K .......... .......... .......... .......... .......... 73% 5.50M 4s\n", - "434200K .......... .......... .......... .......... .......... 73% 41.2M 4s\n", - "434250K .......... .......... .......... .......... .......... 73% 61.5M 4s\n", - "434300K .......... .......... .......... .......... .......... 73% 62.0M 4s\n", - "434350K .......... .......... .......... .......... .......... 73% 48.4M 4s\n", - "434400K .......... .......... .......... .......... .......... 73% 47.6M 4s\n", - "434450K .......... .......... .......... .......... .......... 73% 74.2M 4s\n", - "434500K .......... .......... .......... .......... .......... 73% 78.1M 4s\n", - "434550K .......... .......... .......... .......... .......... 73% 74.9M 4s\n", - "434600K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", - "434650K .......... .......... .......... .......... .......... 73% 63.4M 4s\n", - "434700K .......... .......... .......... .......... .......... 73% 43.9M 4s\n", - "434750K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", - "434800K .......... .......... .......... .......... .......... 73% 42.3M 4s\n", - "434850K .......... .......... .......... .......... .......... 73% 49.4M 4s\n", - "434900K .......... .......... .......... .......... .......... 73% 41.7M 4s\n", - "434950K .......... .......... .......... .......... .......... 73% 51.3M 4s\n", - "435000K .......... .......... .......... .......... .......... 73% 47.7M 4s\n", - "435050K .......... .......... .......... .......... .......... 73% 65.2M 4s\n", - "435100K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", - "435150K .......... .......... .......... .......... .......... 73% 49.9M 4s\n", - "435200K .......... .......... .......... .......... .......... 73% 56.2M 4s\n", - "435250K .......... .......... .......... .......... .......... 73% 59.2M 4s\n", - "435300K .......... .......... .......... .......... .......... 73% 65.5M 4s\n", - "435350K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", - "435400K .......... .......... .......... .......... .......... 73% 45.5M 4s\n", - "435450K .......... .......... .......... .......... .......... 73% 49.6M 4s\n", - "435500K .......... .......... .......... .......... .......... 73% 28.7M 4s\n", - "435550K .......... .......... .......... .......... .......... 73% 35.0M 4s\n", - "435600K .......... .......... .......... .......... .......... 73% 28.1M 4s\n", - "435650K .......... .......... .......... .......... .......... 73% 3.63M 4s\n", - "435700K .......... .......... .......... .......... .......... 73% 55.3M 4s\n", - "435750K .......... .......... .......... .......... .......... 73% 43.7M 4s\n", - "435800K .......... .......... .......... .......... .......... 73% 27.8M 4s\n", - "435850K .......... .......... .......... .......... .......... 73% 31.7M 4s\n", - "435900K .......... .......... .......... .......... .......... 73% 37.1M 4s\n", - "435950K .......... .......... .......... .......... .......... 73% 40.4M 4s\n", - "436000K .......... .......... .......... .......... .......... 73% 36.5M 4s\n", - "436050K .......... .......... .......... .......... .......... 73% 29.8M 4s\n", - "436100K .......... .......... .......... .......... .......... 73% 53.0M 4s\n", - "436150K .......... .......... .......... .......... .......... 73% 71.6M 4s\n", - "436200K .......... .......... .......... .......... .......... 73% 57.0M 4s\n", - "436250K .......... .......... .......... .......... .......... 73% 49.0M 4s\n", - "436300K .......... .......... .......... .......... .......... 73% 51.9M 4s\n", - "436350K .......... .......... .......... .......... .......... 73% 68.4M 4s\n", - "436400K .......... .......... .......... .......... .......... 73% 57.4M 4s\n", - "436450K .......... .......... .......... .......... .......... 73% 71.0M 4s\n", - "436500K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", - "436550K .......... .......... .......... .......... .......... 73% 58.9M 4s\n", - "436600K .......... .......... .......... .......... .......... 73% 42.4M 4s\n", - "436650K .......... .......... .......... .......... .......... 73% 65.5M 4s\n", - "436700K .......... .......... .......... .......... .......... 73% 44.1M 4s\n", - "436750K .......... .......... .......... .......... .......... 73% 58.7M 4s\n", - "436800K .......... .......... .......... .......... .......... 73% 48.0M 4s\n", - "436850K .......... .......... .......... .......... .......... 73% 41.8M 4s\n", - "436900K .......... .......... .......... .......... .......... 73% 55.2M 4s\n", - "436950K .......... .......... .......... .......... .......... 73% 62.6M 4s\n", - "437000K .......... .......... .......... .......... .......... 73% 47.7M 4s\n", - "437050K .......... .......... .......... .......... .......... 73% 45.3M 4s\n", - "437100K .......... .......... .......... .......... .......... 73% 36.2M 4s\n", - "437150K .......... .......... .......... .......... .......... 73% 36.4M 4s\n", - "437200K .......... .......... .......... .......... .......... 73% 29.6M 4s\n", - "437250K .......... .......... .......... .......... .......... 73% 35.3M 4s\n", - "437300K .......... .......... .......... .......... .......... 73% 62.0M 4s\n", - "437350K .......... .......... .......... .......... .......... 73% 61.8M 4s\n", - "437400K .......... .......... .......... .......... .......... 73% 44.0M 4s\n", - "437450K .......... .......... .......... .......... .......... 73% 4.55M 4s\n", - "437500K .......... .......... .......... .......... .......... 73% 51.0M 4s\n", - "437550K .......... .......... .......... .......... .......... 73% 61.0M 4s\n", - "437600K .......... .......... .......... .......... .......... 73% 53.5M 4s\n", - "437650K .......... .......... .......... .......... .......... 73% 67.6M 4s\n", - "437700K .......... .......... .......... .......... .......... 73% 58.4M 4s\n", - "437750K .......... .......... .......... .......... .......... 73% 6.50M 4s\n", - "437800K .......... .......... .......... .......... .......... 73% 44.8M 4s\n", - "437850K .......... .......... .......... .......... .......... 73% 64.9M 4s\n", - "437900K .......... .......... .......... .......... .......... 73% 61.5M 4s\n", - "437950K .......... .......... .......... .......... .......... 73% 67.4M 4s\n", - "438000K .......... .......... .......... .......... .......... 73% 54.9M 4s\n", - "438050K .......... .......... .......... .......... .......... 73% 48.9M 4s\n", - "438100K .......... .......... .......... .......... .......... 73% 66.1M 4s\n", - "438150K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", - "438200K .......... .......... .......... .......... .......... 73% 40.0M 4s\n", - "438250K .......... .......... .......... .......... .......... 73% 63.8M 4s\n", - "438300K .......... .......... .......... .......... .......... 73% 47.3M 4s\n", - "438350K .......... .......... .......... .......... .......... 73% 62.5M 4s\n", - "438400K .......... .......... .......... .......... .......... 73% 52.4M 4s\n", - "438450K .......... .......... .......... .......... .......... 73% 17.7M 4s\n", - "438500K .......... .......... .......... .......... .......... 73% 52.3M 4s\n", - "438550K .......... .......... .......... .......... .......... 73% 51.2M 4s\n", - "438600K .......... .......... .......... .......... .......... 73% 45.5M 4s\n", - "438650K .......... .......... .......... .......... .......... 73% 63.4M 4s\n", - "438700K .......... .......... .......... .......... .......... 73% 57.9M 4s\n", - "438750K .......... .......... .......... .......... .......... 73% 54.8M 4s\n", - "438800K .......... .......... .......... .......... .......... 73% 53.5M 4s\n", - "438850K .......... .......... .......... .......... .......... 73% 42.9M 4s\n", - "438900K .......... .......... .......... .......... .......... 73% 67.2M 4s\n", - "438950K .......... .......... .......... .......... .......... 73% 59.1M 4s\n", - "439000K .......... .......... .......... .......... .......... 73% 50.5M 4s\n", - "439050K .......... .......... .......... .......... .......... 73% 48.2M 4s\n", - "439100K .......... .......... .......... .......... .......... 73% 51.1M 4s\n", - "439150K .......... .......... .......... .......... .......... 73% 57.7M 4s\n", - "439200K .......... .......... .......... .......... .......... 73% 59.3M 4s\n", - "439250K .......... .......... .......... .......... .......... 73% 52.3M 4s\n", - "439300K .......... .......... .......... .......... .......... 73% 56.7M 4s\n", - "439350K .......... .......... .......... .......... .......... 73% 48.4M 4s\n", - "439400K .......... .......... .......... .......... .......... 73% 50.9M 4s\n", - "439450K .......... .......... .......... .......... .......... 73% 57.7M 4s\n", - "439500K .......... .......... .......... .......... .......... 73% 50.6M 4s\n", - "439550K .......... .......... .......... .......... .......... 73% 47.1M 4s\n", - "439600K .......... .......... .......... .......... .......... 73% 9.77M 4s\n", - "439650K .......... .......... .......... .......... .......... 73% 46.1M 4s\n", - "439700K .......... .......... .......... .......... .......... 73% 67.6M 4s\n", - "439750K .......... .......... .......... .......... .......... 73% 68.7M 4s\n", - "439800K .......... .......... .......... .......... .......... 73% 52.7M 4s\n", - "439850K .......... .......... .......... .......... .......... 73% 60.3M 4s\n", - "439900K .......... .......... .......... .......... .......... 73% 47.6M 4s\n", - "439950K .......... .......... .......... .......... .......... 73% 54.3M 4s\n", - "440000K .......... .......... .......... .......... .......... 73% 66.0M 4s\n", - "440050K .......... .......... .......... .......... .......... 73% 64.0M 4s\n", - "440100K .......... .......... .......... .......... .......... 74% 66.9M 4s\n", - "440150K .......... .......... .......... .......... .......... 74% 65.0M 4s\n", - "440200K .......... .......... .......... .......... .......... 74% 41.6M 4s\n", - "440250K .......... .......... .......... .......... .......... 74% 54.7M 4s\n", - "440300K .......... .......... .......... .......... .......... 74% 77.6M 4s\n", - "440350K .......... .......... .......... .......... .......... 74% 74.4M 4s\n", - "440400K .......... .......... .......... .......... .......... 74% 62.8M 4s\n", - "440450K .......... .......... .......... .......... .......... 74% 74.7M 4s\n", - "440500K .......... .......... .......... .......... .......... 74% 52.6M 4s\n", - "440550K .......... .......... .......... .......... .......... 74% 49.2M 4s\n", - "440600K .......... .......... .......... .......... .......... 74% 51.9M 4s\n", - "440650K .......... .......... .......... .......... .......... 74% 66.3M 4s\n", - "440700K .......... .......... .......... .......... .......... 74% 64.3M 4s\n", - "440750K .......... .......... .......... .......... .......... 74% 64.3M 4s\n", - "440800K .......... .......... .......... .......... .......... 74% 44.3M 4s\n", - "440850K .......... .......... .......... .......... .......... 74% 51.8M 4s\n", - "440900K .......... .......... .......... .......... .......... 74% 55.0M 4s\n", - "440950K .......... .......... .......... .......... .......... 74% 63.4M 4s\n", - "441000K .......... .......... .......... .......... .......... 74% 43.1M 4s\n", - "441050K .......... .......... .......... .......... .......... 74% 34.4M 4s\n", - "441100K .......... .......... .......... .......... .......... 74% 47.8M 4s\n", - "441150K .......... .......... .......... .......... .......... 74% 41.3M 4s\n", - "441200K .......... .......... .......... .......... .......... 74% 45.2M 4s\n", - "441250K .......... .......... .......... .......... .......... 74% 50.2M 4s\n", - "441300K .......... .......... .......... .......... .......... 74% 43.5M 4s\n", - "441350K .......... .......... .......... .......... .......... 74% 37.1M 4s\n", - "441400K .......... .......... .......... .......... .......... 74% 42.3M 4s\n", - "441450K .......... .......... .......... .......... .......... 74% 74.7M 4s\n", - "441500K .......... .......... .......... .......... .......... 74% 60.6M 4s\n", - "441550K .......... .......... .......... .......... .......... 74% 43.1M 4s\n", - "441600K .......... .......... .......... .......... .......... 74% 35.0M 4s\n", - "441650K .......... .......... .......... .......... .......... 74% 54.5M 4s\n", - "441700K .......... .......... .......... .......... .......... 74% 49.8M 4s\n", - "441750K .......... .......... .......... .......... .......... 74% 36.1M 4s\n", - "441800K .......... .......... .......... .......... .......... 74% 33.6M 4s\n", - "441850K .......... .......... .......... .......... .......... 74% 50.1M 4s\n", - "441900K .......... .......... .......... .......... .......... 74% 44.6M 4s\n", - "441950K .......... .......... .......... .......... .......... 74% 55.9M 4s\n", - "442000K .......... .......... .......... .......... .......... 74% 51.5M 4s\n", - "442050K .......... .......... .......... .......... .......... 74% 48.6M 4s\n", - "442100K .......... .......... .......... .......... .......... 74% 64.4M 4s\n", - "442150K .......... .......... .......... .......... .......... 74% 46.2M 4s\n", - "442200K .......... .......... .......... .......... .......... 74% 38.4M 4s\n", - "442250K .......... .......... .......... .......... .......... 74% 38.3M 4s\n", - "442300K .......... .......... .......... .......... .......... 74% 61.8M 4s\n", - "442350K .......... .......... .......... .......... .......... 74% 30.8M 4s\n", - "442400K .......... .......... .......... .......... .......... 74% 37.0M 4s\n", - "442450K .......... .......... .......... .......... .......... 74% 63.0M 4s\n", - "442500K .......... .......... .......... .......... .......... 74% 54.4M 4s\n", - "442550K .......... .......... .......... .......... .......... 74% 50.7M 4s\n", - "442600K .......... .......... .......... .......... .......... 74% 47.8M 4s\n", - "442650K .......... .......... .......... .......... .......... 74% 54.6M 4s\n", - "442700K .......... .......... .......... .......... .......... 74% 54.4M 4s\n", - "442750K .......... .......... .......... .......... .......... 74% 46.5M 4s\n", - "442800K .......... .......... .......... .......... .......... 74% 51.3M 4s\n", - "442850K .......... .......... .......... .......... .......... 74% 70.9M 4s\n", - "442900K .......... .......... .......... .......... .......... 74% 57.7M 4s\n", - "442950K .......... .......... .......... .......... .......... 74% 58.6M 4s\n", - "443000K .......... .......... .......... .......... .......... 74% 40.6M 4s\n", - "443050K .......... .......... .......... .......... .......... 74% 61.1M 4s\n", - "443100K .......... .......... .......... .......... .......... 74% 49.5M 4s\n", - "443150K .......... .......... .......... .......... .......... 74% 4.57M 4s\n", - "443200K .......... .......... .......... .......... .......... 74% 52.7M 4s\n", - "443250K .......... .......... .......... .......... .......... 74% 58.7M 4s\n", - "443300K .......... .......... .......... .......... .......... 74% 60.7M 4s\n", - "443350K .......... .......... .......... .......... .......... 74% 64.1M 4s\n", - "443400K .......... .......... .......... .......... .......... 74% 46.5M 4s\n", - "443450K .......... .......... .......... .......... .......... 74% 54.5M 4s\n", - "443500K .......... .......... .......... .......... .......... 74% 59.0M 4s\n", - "443550K .......... .......... .......... .......... .......... 74% 60.5M 4s\n", - "443600K .......... .......... .......... .......... .......... 74% 47.5M 4s\n", - "443650K .......... .......... .......... .......... .......... 74% 62.2M 4s\n", - "443700K .......... .......... .......... .......... .......... 74% 53.7M 4s\n", - "443750K .......... .......... .......... .......... .......... 74% 57.3M 4s\n", - "443800K .......... .......... .......... .......... .......... 74% 39.1M 4s\n", - "443850K .......... .......... .......... .......... .......... 74% 55.0M 4s\n", - "443900K .......... .......... .......... .......... .......... 74% 45.3M 4s\n", - "443950K .......... .......... .......... .......... .......... 74% 46.9M 4s\n", - "444000K .......... .......... .......... .......... .......... 74% 56.8M 4s\n", - "444050K .......... .......... .......... .......... .......... 74% 46.2M 4s\n", - "444100K .......... .......... .......... .......... .......... 74% 54.7M 4s\n", - "444150K .......... .......... .......... .......... .......... 74% 42.2M 4s\n", - "444200K .......... .......... .......... .......... .......... 74% 40.3M 4s\n", - "444250K .......... .......... .......... .......... .......... 74% 45.1M 4s\n", - "444300K .......... .......... .......... .......... .......... 74% 46.7M 4s\n", - "444350K .......... .......... .......... .......... .......... 74% 46.8M 4s\n", - "444400K .......... .......... .......... .......... .......... 74% 13.0M 4s\n", - "444450K .......... .......... .......... .......... .......... 74% 42.5M 4s\n", - "444500K .......... .......... .......... .......... .......... 74% 48.0M 4s\n", - "444550K .......... .......... .......... .......... .......... 74% 45.5M 4s\n", - "444600K .......... .......... .......... .......... .......... 74% 40.5M 4s\n", - "444650K .......... .......... .......... .......... .......... 74% 45.3M 4s\n", - "444700K .......... .......... .......... .......... .......... 74% 60.8M 4s\n", - "444750K .......... .......... .......... .......... .......... 74% 62.6M 4s\n", - "444800K .......... .......... .......... .......... .......... 74% 52.5M 4s\n", - "444850K .......... .......... .......... .......... .......... 74% 56.0M 4s\n", - "444900K .......... .......... .......... .......... .......... 74% 47.2M 4s\n", - "444950K .......... .......... .......... .......... .......... 74% 61.5M 4s\n", - "445000K .......... .......... .......... .......... .......... 74% 54.8M 4s\n", - "445050K .......... .......... .......... .......... .......... 74% 49.8M 4s\n", - "445100K .......... .......... .......... .......... .......... 74% 46.8M 4s\n", - "445150K .......... .......... .......... .......... .......... 74% 53.8M 4s\n", - "445200K .......... .......... .......... .......... .......... 74% 52.3M 4s\n", - "445250K .......... .......... .......... .......... .......... 74% 56.7M 4s\n", - "445300K .......... .......... .......... .......... .......... 74% 60.0M 4s\n", - "445350K .......... .......... .......... .......... .......... 74% 35.3M 4s\n", - "445400K .......... .......... .......... .......... .......... 74% 35.3M 4s\n", - "445450K .......... .......... .......... .......... .......... 74% 46.7M 4s\n", - "445500K .......... .......... .......... .......... .......... 74% 45.2M 4s\n", - "445550K .......... .......... .......... .......... .......... 74% 38.3M 4s\n", - "445600K .......... .......... .......... .......... .......... 74% 41.7M 4s\n", - "445650K .......... .......... .......... .......... .......... 74% 55.9M 4s\n", - "445700K .......... .......... .......... .......... .......... 74% 63.6M 4s\n", - "445750K .......... .......... .......... .......... .......... 74% 57.7M 4s\n", - "445800K .......... .......... .......... .......... .......... 74% 44.1M 4s\n", - "445850K .......... .......... .......... .......... .......... 74% 53.0M 4s\n", - "445900K .......... .......... .......... .......... .......... 74% 74.0M 4s\n", - "445950K .......... .......... .......... .......... .......... 74% 65.9M 4s\n", - "446000K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", - "446050K .......... .......... .......... .......... .......... 75% 45.9M 4s\n", - "446100K .......... .......... .......... .......... .......... 75% 49.2M 4s\n", - "446150K .......... .......... .......... .......... .......... 75% 56.9M 4s\n", - "446200K .......... .......... .......... .......... .......... 75% 53.8M 4s\n", - "446250K .......... .......... .......... .......... .......... 75% 50.2M 4s\n", - "446300K .......... .......... .......... .......... .......... 75% 50.7M 4s\n", - "446350K .......... .......... .......... .......... .......... 75% 47.5M 4s\n", - "446400K .......... .......... .......... .......... .......... 75% 65.6M 4s\n", - "446450K .......... .......... .......... .......... .......... 75% 69.4M 4s\n", - "446500K .......... .......... .......... .......... .......... 75% 46.7M 4s\n", - "446550K .......... .......... .......... .......... .......... 75% 50.8M 4s\n", - "446600K .......... .......... .......... .......... .......... 75% 51.0M 4s\n", - "446650K .......... .......... .......... .......... .......... 75% 64.7M 4s\n", - "446700K .......... .......... .......... .......... .......... 75% 50.9M 4s\n", - "446750K .......... .......... .......... .......... .......... 75% 42.2M 4s\n", - "446800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", - "446850K .......... .......... .......... .......... .......... 75% 54.2M 4s\n", - "446900K .......... .......... .......... .......... .......... 75% 57.6M 4s\n", - "446950K .......... .......... .......... .......... .......... 75% 52.2M 4s\n", - "447000K .......... .......... .......... .......... .......... 75% 40.1M 4s\n", - "447050K .......... .......... .......... .......... .......... 75% 56.4M 4s\n", - "447100K .......... .......... .......... .......... .......... 75% 59.3M 4s\n", - "447150K .......... .......... .......... .......... .......... 75% 67.7M 4s\n", - "447200K .......... .......... .......... .......... .......... 75% 46.6M 4s\n", - "447250K .......... .......... .......... .......... .......... 75% 50.7M 4s\n", - "447300K .......... .......... .......... .......... .......... 75% 59.7M 4s\n", - "447350K .......... .......... .......... .......... .......... 75% 56.3M 4s\n", - "447400K .......... .......... .......... .......... .......... 75% 40.2M 4s\n", - "447450K .......... .......... .......... .......... .......... 75% 35.4M 4s\n", - "447500K .......... .......... .......... .......... .......... 75% 49.5M 4s\n", - "447550K .......... .......... .......... .......... .......... 75% 65.9M 4s\n", - "447600K .......... .......... .......... .......... .......... 75% 47.8M 4s\n", - "447650K .......... .......... .......... .......... .......... 75% 49.5M 4s\n", - "447700K .......... .......... .......... .......... .......... 75% 42.1M 4s\n", - "447750K .......... .......... .......... .......... .......... 75% 58.7M 4s\n", - "447800K .......... .......... .......... .......... .......... 75% 48.2M 4s\n", - "447850K .......... .......... .......... .......... .......... 75% 56.1M 4s\n", - "447900K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", - "447950K .......... .......... .......... .......... .......... 75% 51.5M 4s\n", - "448000K .......... .......... .......... .......... .......... 75% 44.6M 4s\n", - "448050K .......... .......... .......... .......... .......... 75% 57.1M 4s\n", - "448100K .......... .......... .......... .......... .......... 75% 40.4M 4s\n", - "448150K .......... .......... .......... .......... .......... 75% 42.9M 4s\n", - "448200K .......... .......... .......... .......... .......... 75% 43.2M 4s\n", - "448250K .......... .......... .......... .......... .......... 75% 70.8M 4s\n", - "448300K .......... .......... .......... .......... .......... 75% 51.5M 4s\n", - "448350K .......... .......... .......... .......... .......... 75% 45.1M 4s\n", - "448400K .......... .......... .......... .......... .......... 75% 45.9M 4s\n", - "448450K .......... .......... .......... .......... .......... 75% 3.62M 4s\n", - "448500K .......... .......... .......... .......... .......... 75% 45.0M 4s\n", - "448550K .......... .......... .......... .......... .......... 75% 45.3M 4s\n", - "448600K .......... .......... .......... .......... .......... 75% 36.0M 4s\n", - "448650K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", - "448700K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", - "448750K .......... .......... .......... .......... .......... 75% 64.0M 4s\n", - "448800K .......... .......... .......... .......... .......... 75% 55.9M 4s\n", - "448850K .......... .......... .......... .......... .......... 75% 50.5M 4s\n", - "448900K .......... .......... .......... .......... .......... 75% 59.7M 4s\n", - "448950K .......... .......... .......... .......... .......... 75% 56.2M 4s\n", - "449000K .......... .......... .......... .......... .......... 75% 53.4M 4s\n", - "449050K .......... .......... .......... .......... .......... 75% 68.9M 4s\n", - "449100K .......... .......... .......... .......... .......... 75% 69.2M 4s\n", - "449150K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", - "449200K .......... .......... .......... .......... .......... 75% 42.9M 4s\n", - "449250K .......... .......... .......... .......... .......... 75% 61.4M 4s\n", - "449300K .......... .......... .......... .......... .......... 75% 62.1M 4s\n", - "449350K .......... .......... .......... .......... .......... 75% 68.4M 4s\n", - "449400K .......... .......... .......... .......... .......... 75% 36.8M 4s\n", - "449450K .......... .......... .......... .......... .......... 75% 46.7M 4s\n", - "449500K .......... .......... .......... .......... .......... 75% 56.0M 4s\n", - "449550K .......... .......... .......... .......... .......... 75% 61.4M 4s\n", - "449600K .......... .......... .......... .......... .......... 75% 57.0M 4s\n", - "449650K .......... .......... .......... .......... .......... 75% 50.1M 4s\n", - "449700K .......... .......... .......... .......... .......... 75% 58.0M 4s\n", - "449750K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", - "449800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", - "449850K .......... .......... .......... .......... .......... 75% 53.2M 4s\n", - "449900K .......... .......... .......... .......... .......... 75% 51.8M 4s\n", - "449950K .......... .......... .......... .......... .......... 75% 51.1M 4s\n", - "450000K .......... .......... .......... .......... .......... 75% 50.6M 4s\n", - "450050K .......... .......... .......... .......... .......... 75% 60.9M 4s\n", - "450100K .......... .......... .......... .......... .......... 75% 41.1M 4s\n", - "450150K .......... .......... .......... .......... .......... 75% 47.0M 4s\n", - "450200K .......... .......... .......... .......... .......... 75% 46.8M 4s\n", - "450250K .......... .......... .......... .......... .......... 75% 60.7M 4s\n", - "450300K .......... .......... .......... .......... .......... 75% 42.0M 4s\n", - "450350K .......... .......... .......... .......... .......... 75% 43.2M 4s\n", - "450400K .......... .......... .......... .......... .......... 75% 3.86M 4s\n", - "450450K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", - "450500K .......... .......... .......... .......... .......... 75% 67.1M 4s\n", - "450550K .......... .......... .......... .......... .......... 75% 65.2M 4s\n", - "450600K .......... .......... .......... .......... .......... 75% 52.8M 4s\n", - "450650K .......... .......... .......... .......... .......... 75% 60.1M 4s\n", - "450700K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", - "450750K .......... .......... .......... .......... .......... 75% 59.1M 4s\n", - "450800K .......... .......... .......... .......... .......... 75% 48.0M 4s\n", - "450850K .......... .......... .......... .......... .......... 75% 53.5M 4s\n", - "450900K .......... .......... .......... .......... .......... 75% 58.6M 4s\n", - "450950K .......... .......... .......... .......... .......... 75% 57.5M 4s\n", - "451000K .......... .......... .......... .......... .......... 75% 54.8M 4s\n", - "451050K .......... .......... .......... .......... .......... 75% 59.0M 4s\n", - "451100K .......... .......... .......... .......... .......... 75% 45.8M 4s\n", - "451150K .......... .......... .......... .......... .......... 75% 48.9M 4s\n", - "451200K .......... .......... .......... .......... .......... 75% 50.9M 4s\n", - "451250K .......... .......... .......... .......... .......... 75% 66.9M 4s\n", - "451300K .......... .......... .......... .......... .......... 75% 50.4M 4s\n", - "451350K .......... .......... .......... .......... .......... 75% 55.5M 4s\n", - "451400K .......... .......... .......... .......... .......... 75% 46.1M 4s\n", - "451450K .......... .......... .......... .......... .......... 75% 58.3M 4s\n", - "451500K .......... .......... .......... .......... .......... 75% 67.0M 4s\n", - "451550K .......... .......... .......... .......... .......... 75% 52.5M 4s\n", - "451600K .......... .......... .......... .......... .......... 75% 48.8M 4s\n", - "451650K .......... .......... .......... .......... .......... 75% 49.3M 4s\n", - "451700K .......... .......... .......... .......... .......... 75% 65.0M 4s\n", - "451750K .......... .......... .......... .......... .......... 75% 62.8M 4s\n", - "451800K .......... .......... .......... .......... .......... 75% 52.1M 4s\n", - "451850K .......... .......... .......... .......... .......... 75% 57.5M 4s\n", - "451900K .......... .......... .......... .......... .......... 75% 55.3M 4s\n", - "451950K .......... .......... .......... .......... .......... 76% 63.8M 4s\n", - "452000K .......... .......... .......... .......... .......... 76% 54.1M 4s\n", - "452050K .......... .......... .......... .......... .......... 76% 72.0M 4s\n", - "452100K .......... .......... .......... .......... .......... 76% 57.7M 4s\n", - "452150K .......... .......... .......... .......... .......... 76% 47.6M 4s\n", - "452200K .......... .......... .......... .......... .......... 76% 52.0M 4s\n", - "452250K .......... .......... .......... .......... .......... 76% 50.0M 4s\n", - "452300K .......... .......... .......... .......... .......... 76% 62.9M 4s\n", - "452350K .......... .......... .......... .......... .......... 76% 55.3M 4s\n", - "452400K .......... .......... .......... .......... .......... 76% 42.6M 4s\n", - "452450K .......... .......... .......... .......... .......... 76% 62.8M 4s\n", - "452500K .......... .......... .......... .......... .......... 76% 55.1M 4s\n", - "452550K .......... .......... .......... .......... .......... 76% 72.1M 4s\n", - "452600K .......... .......... .......... .......... .......... 76% 43.3M 4s\n", - "452650K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", - "452700K .......... .......... .......... .......... .......... 76% 64.6M 4s\n", - "452750K .......... .......... .......... .......... .......... 76% 51.9M 4s\n", - "452800K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", - "452850K .......... .......... .......... .......... .......... 76% 51.1M 4s\n", - "452900K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", - "452950K .......... .......... .......... .......... .......... 76% 69.3M 4s\n", - "453000K .......... .......... .......... .......... .......... 76% 51.6M 4s\n", - "453050K .......... .......... .......... .......... .......... 76% 64.7M 4s\n", - "453100K .......... .......... .......... .......... .......... 76% 64.6M 4s\n", - "453150K .......... .......... .......... .......... .......... 76% 50.3M 4s\n", - "453200K .......... .......... .......... .......... .......... 76% 50.3M 4s\n", - "453250K .......... .......... .......... .......... .......... 76% 68.4M 4s\n", - "453300K .......... .......... .......... .......... .......... 76% 54.4M 4s\n", - "453350K .......... .......... .......... .......... .......... 76% 64.1M 4s\n", - "453400K .......... .......... .......... .......... .......... 76% 38.5M 4s\n", - "453450K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", - "453500K .......... .......... .......... .......... .......... 76% 51.3M 4s\n", - "453550K .......... .......... .......... .......... .......... 76% 55.6M 4s\n", - "453600K .......... .......... .......... .......... .......... 76% 55.3M 4s\n", - "453650K .......... .......... .......... .......... .......... 76% 52.1M 4s\n", - "453700K .......... .......... .......... .......... .......... 76% 61.9M 4s\n", - "453750K .......... .......... .......... .......... .......... 76% 65.1M 4s\n", - "453800K .......... .......... .......... .......... .......... 76% 39.2M 4s\n", - "453850K .......... .......... .......... .......... .......... 76% 55.6M 4s\n", - "453900K .......... .......... .......... .......... .......... 76% 66.2M 4s\n", - "453950K .......... .......... .......... .......... .......... 76% 65.8M 4s\n", - "454000K .......... .......... .......... .......... .......... 76% 46.7M 4s\n", - "454050K .......... .......... .......... .......... .......... 76% 45.9M 4s\n", - "454100K .......... .......... .......... .......... .......... 76% 47.4M 4s\n", - "454150K .......... .......... .......... .......... .......... 76% 50.2M 4s\n", - "454200K .......... .......... .......... .......... .......... 76% 54.9M 4s\n", - "454250K .......... .......... .......... .......... .......... 76% 66.2M 4s\n", - "454300K .......... .......... .......... .......... .......... 76% 62.4M 4s\n", - "454350K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", - "454400K .......... .......... .......... .......... .......... 76% 46.3M 4s\n", - "454450K .......... .......... .......... .......... .......... 76% 60.5M 4s\n", - "454500K .......... .......... .......... .......... .......... 76% 68.6M 4s\n", - "454550K .......... .......... .......... .......... .......... 76% 63.4M 4s\n", - "454600K .......... .......... .......... .......... .......... 76% 31.1M 4s\n", - "454650K .......... .......... .......... .......... .......... 76% 44.2M 4s\n", - "454700K .......... .......... .......... .......... .......... 76% 56.7M 4s\n", - "454750K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", - "454800K .......... .......... .......... .......... .......... 76% 39.8M 4s\n", - "454850K .......... .......... .......... .......... .......... 76% 45.3M 4s\n", - "454900K .......... .......... .......... .......... .......... 76% 49.6M 4s\n", - "454950K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", - "455000K .......... .......... .......... .......... .......... 76% 44.7M 4s\n", - "455050K .......... .......... .......... .......... .......... 76% 49.9M 4s\n", - "455100K .......... .......... .......... .......... .......... 76% 49.2M 4s\n", - "455150K .......... .......... .......... .......... .......... 76% 62.9M 4s\n", - "455200K .......... .......... .......... .......... .......... 76% 57.5M 4s\n", - "455250K .......... .......... .......... .......... .......... 76% 55.0M 4s\n", - "455300K .......... .......... .......... .......... .......... 76% 58.9M 4s\n", - "455350K .......... .......... .......... .......... .......... 76% 53.8M 4s\n", - "455400K .......... .......... .......... .......... .......... 76% 51.8M 4s\n", - "455450K .......... .......... .......... .......... .......... 76% 75.1M 4s\n", - "455500K .......... .......... .......... .......... .......... 76% 57.0M 4s\n", - "455550K .......... .......... .......... .......... .......... 76% 63.8M 4s\n", - "455600K .......... .......... .......... .......... .......... 76% 38.4M 4s\n", - "455650K .......... .......... .......... .......... .......... 76% 63.4M 4s\n", - "455700K .......... .......... .......... .......... .......... 76% 65.3M 4s\n", - "455750K .......... .......... .......... .......... .......... 76% 64.3M 4s\n", - "455800K .......... .......... .......... .......... .......... 76% 43.4M 4s\n", - "455850K .......... .......... .......... .......... .......... 76% 57.6M 4s\n", - "455900K .......... .......... .......... .......... .......... 76% 61.0M 4s\n", - "455950K .......... .......... .......... .......... .......... 76% 65.1M 4s\n", - "456000K .......... .......... .......... .......... .......... 76% 59.1M 4s\n", - "456050K .......... .......... .......... .......... .......... 76% 53.3M 4s\n", - "456100K .......... .......... .......... .......... .......... 76% 52.6M 4s\n", - "456150K .......... .......... .......... .......... .......... 76% 61.2M 4s\n", - "456200K .......... .......... .......... .......... .......... 76% 58.8M 4s\n", - "456250K .......... .......... .......... .......... .......... 76% 73.0M 4s\n", - "456300K .......... .......... .......... .......... .......... 76% 53.2M 4s\n", - "456350K .......... .......... .......... .......... .......... 76% 56.3M 4s\n", - "456400K .......... .......... .......... .......... .......... 76% 51.0M 4s\n", - "456450K .......... .......... .......... .......... .......... 76% 76.3M 4s\n", - "456500K .......... .......... .......... .......... .......... 76% 71.2M 4s\n", - "456550K .......... .......... .......... .......... .......... 76% 69.0M 4s\n", - "456600K .......... .......... .......... .......... .......... 76% 49.1M 4s\n", - "456650K .......... .......... .......... .......... .......... 76% 47.0M 4s\n", - "456700K .......... .......... .......... .......... .......... 76% 74.2M 4s\n", - "456750K .......... .......... .......... .......... .......... 76% 69.4M 4s\n", - "456800K .......... .......... .......... .......... .......... 76% 57.3M 4s\n", - "456850K .......... .......... .......... .......... .......... 76% 55.9M 4s\n", - "456900K .......... .......... .......... .......... .......... 76% 49.1M 4s\n", - "456950K .......... .......... .......... .......... .......... 76% 50.9M 4s\n", - "457000K .......... .......... .......... .......... .......... 76% 59.5M 4s\n", - "457050K .......... .......... .......... .......... .......... 76% 64.9M 4s\n", - "457100K .......... .......... .......... .......... .......... 76% 61.5M 4s\n", - "457150K .......... .......... .......... .......... .......... 76% 51.8M 4s\n", - "457200K .......... .......... .......... .......... .......... 76% 46.3M 4s\n", - "457250K .......... .......... .......... .......... .......... 76% 57.4M 4s\n", - "457300K .......... .......... .......... .......... .......... 76% 69.9M 4s\n", - "457350K .......... .......... .......... .......... .......... 76% 69.2M 4s\n", - "457400K .......... .......... .......... .......... .......... 76% 40.9M 4s\n", - "457450K .......... .......... .......... .......... .......... 76% 55.5M 4s\n", - "457500K .......... .......... .......... .......... .......... 76% 61.6M 4s\n", - "457550K .......... .......... .......... .......... .......... 76% 67.5M 4s\n", - "457600K .......... .......... .......... .......... .......... 76% 58.7M 4s\n", - "457650K .......... .......... .......... .......... .......... 76% 47.1M 4s\n", - "457700K .......... .......... .......... .......... .......... 76% 48.0M 4s\n", - "457750K .......... .......... .......... .......... .......... 76% 62.6M 4s\n", - "457800K .......... .......... .......... .......... .......... 76% 59.5M 4s\n", - "457850K .......... .......... .......... .......... .......... 76% 67.3M 4s\n", - "457900K .......... .......... .......... .......... .......... 77% 50.2M 4s\n", - "457950K .......... .......... .......... .......... .......... 77% 49.7M 4s\n", - "458000K .......... .......... .......... .......... .......... 77% 58.4M 4s\n", - "458050K .......... .......... .......... .......... .......... 77% 76.5M 4s\n", - "458100K .......... .......... .......... .......... .......... 77% 67.9M 4s\n", - "458150K .......... .......... .......... .......... .......... 77% 65.1M 4s\n", - "458200K .......... .......... .......... .......... .......... 77% 46.9M 4s\n", - "458250K .......... .......... .......... .......... .......... 77% 49.8M 4s\n", - "458300K .......... .......... .......... .......... .......... 77% 76.1M 4s\n", - "458350K .......... .......... .......... .......... .......... 77% 68.8M 4s\n", - "458400K .......... .......... .......... .......... .......... 77% 67.6M 4s\n", - "458450K .......... .......... .......... .......... .......... 77% 46.7M 4s\n", - "458500K .......... .......... .......... .......... .......... 77% 49.4M 4s\n", - "458550K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", - "458600K .......... .......... .......... .......... .......... 77% 58.1M 4s\n", - "458650K .......... .......... .......... .......... .......... 77% 60.2M 4s\n", - "458700K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", - "458750K .......... .......... .......... .......... .......... 77% 51.0M 4s\n", - "458800K .......... .......... .......... .......... .......... 77% 56.5M 4s\n", - "458850K .......... .......... .......... .......... .......... 77% 69.0M 4s\n", - "458900K .......... .......... .......... .......... .......... 77% 65.1M 4s\n", - "458950K .......... .......... .......... .......... .......... 77% 72.6M 4s\n", - "459000K .......... .......... .......... .......... .......... 77% 37.3M 4s\n", - "459050K .......... .......... .......... .......... .......... 77% 49.2M 4s\n", - "459100K .......... .......... .......... .......... .......... 77% 68.8M 4s\n", - "459150K .......... .......... .......... .......... .......... 77% 71.8M 3s\n", - "459200K .......... .......... .......... .......... .......... 77% 62.2M 3s\n", - "459250K .......... .......... .......... .......... .......... 77% 51.2M 3s\n", - "459300K .......... .......... .......... .......... .......... 77% 50.9M 3s\n", - "459350K .......... .......... .......... .......... .......... 77% 54.6M 3s\n", - "459400K .......... .......... .......... .......... .......... 77% 60.7M 3s\n", - "459450K .......... .......... .......... .......... .......... 77% 77.7M 3s\n", - "459500K .......... .......... .......... .......... .......... 77% 47.9M 3s\n", - "459550K .......... .......... .......... .......... .......... 77% 52.8M 3s\n", - "459600K .......... .......... .......... .......... .......... 77% 51.1M 3s\n", - "459650K .......... .......... .......... .......... .......... 77% 75.3M 3s\n", - "459700K .......... .......... .......... .......... .......... 77% 59.4M 3s\n", - "459750K .......... .......... .......... .......... .......... 77% 46.0M 3s\n", - "459800K .......... .......... .......... .......... .......... 77% 43.0M 3s\n", - "459850K .......... .......... .......... .......... .......... 77% 71.8M 3s\n", - "459900K .......... .......... .......... .......... .......... 77% 72.8M 3s\n", - "459950K .......... .......... .......... .......... .......... 77% 63.2M 3s\n", - "460000K .......... .......... .......... .......... .......... 77% 49.4M 3s\n", - "460050K .......... .......... .......... .......... .......... 77% 60.3M 3s\n", - "460100K .......... .......... .......... .......... .......... 77% 62.1M 3s\n", - "460150K .......... .......... .......... .......... .......... 77% 71.4M 3s\n", - "460200K .......... .......... .......... .......... .......... 77% 62.2M 3s\n", - "460250K .......... .......... .......... .......... .......... 77% 54.4M 3s\n", - "460300K .......... .......... .......... .......... .......... 77% 44.3M 3s\n", - "460350K .......... .......... .......... .......... .......... 77% 53.1M 3s\n", - "460400K .......... .......... .......... .......... .......... 77% 63.7M 3s\n", - "460450K .......... .......... .......... .......... .......... 77% 70.8M 3s\n", - "460500K .......... .......... .......... .......... .......... 77% 61.3M 3s\n", - "460550K .......... .......... .......... .......... .......... 77% 51.9M 3s\n", - "460600K .......... .......... .......... .......... .......... 77% 37.5M 3s\n", - "460650K .......... .......... .......... .......... .......... 77% 65.0M 3s\n", - "460700K .......... .......... .......... .......... .......... 77% 67.4M 3s\n", - "460750K .......... .......... .......... .......... .......... 77% 76.8M 3s\n", - "460800K .......... .......... .......... .......... .......... 77% 46.8M 3s\n", - "460850K .......... .......... .......... .......... .......... 77% 49.0M 3s\n", - "460900K .......... .......... .......... .......... .......... 77% 76.7M 3s\n", - "460950K .......... .......... .......... .......... .......... 77% 77.7M 3s\n", - "461000K .......... .......... .......... .......... .......... 77% 3.78M 3s\n", - "461050K .......... .......... .......... .......... .......... 77% 71.5M 3s\n", - "461100K .......... .......... .......... .......... .......... 77% 65.4M 3s\n", - "461150K .......... .......... .......... .......... .......... 77% 68.3M 3s\n", - "461200K .......... .......... .......... .......... .......... 77% 54.1M 3s\n", - "461250K .......... .......... .......... .......... .......... 77% 60.5M 3s\n", - "461300K .......... .......... .......... .......... .......... 77% 69.4M 3s\n", - "461350K .......... .......... .......... .......... .......... 77% 66.5M 3s\n", - "461400K .......... .......... .......... .......... .......... 77% 52.1M 3s\n", - "461450K .......... .......... .......... .......... .......... 77% 55.6M 3s\n", - "461500K .......... .......... .......... .......... .......... 77% 59.7M 3s\n", - "461550K .......... .......... .......... .......... .......... 77% 17.2M 3s\n", - "461600K .......... .......... .......... .......... .......... 77% 52.8M 3s\n", - "461650K .......... .......... .......... .......... .......... 77% 59.8M 3s\n", - "461700K .......... .......... .......... .......... .......... 77% 49.1M 3s\n", - "461750K .......... .......... .......... .......... .......... 77% 48.9M 3s\n", - "461800K .......... .......... .......... .......... .......... 77% 59.2M 3s\n", - "461850K .......... .......... .......... .......... .......... 77% 45.4M 3s\n", - "461900K .......... .......... .......... .......... .......... 77% 53.4M 3s\n", - "461950K .......... .......... .......... .......... .......... 77% 3.99M 3s\n", - "462000K .......... .......... .......... .......... .......... 77% 60.3M 3s\n", - "462050K .......... .......... .......... .......... .......... 77% 62.7M 3s\n", - "462100K .......... .......... .......... .......... .......... 77% 67.7M 3s\n", - "462150K .......... .......... .......... .......... .......... 77% 63.4M 3s\n", - "462200K .......... .......... .......... .......... .......... 77% 52.4M 3s\n", - "462250K .......... .......... .......... .......... .......... 77% 54.9M 3s\n", - "462300K .......... .......... .......... .......... .......... 77% 60.9M 3s\n", - "462350K .......... .......... .......... .......... .......... 77% 66.0M 3s\n", - "462400K .......... .......... .......... .......... .......... 77% 61.1M 3s\n", - "462450K .......... .......... .......... .......... .......... 77% 15.5M 3s\n", - "462500K .......... .......... .......... .......... .......... 77% 71.2M 3s\n", - "462550K .......... .......... .......... .......... .......... 77% 65.7M 3s\n", - "462600K .......... .......... .......... .......... .......... 77% 43.1M 3s\n", - "462650K .......... .......... .......... .......... .......... 77% 60.2M 3s\n", - "462700K .......... .......... .......... .......... .......... 77% 67.2M 3s\n", - "462750K .......... .......... .......... .......... .......... 77% 49.9M 3s\n", - "462800K .......... .......... .......... .......... .......... 77% 53.2M 3s\n", - "462850K .......... .......... .......... .......... .......... 77% 47.0M 3s\n", - "462900K .......... .......... .......... .......... .......... 77% 61.4M 3s\n", - "462950K .......... .......... .......... .......... .......... 77% 69.6M 3s\n", - "463000K .......... .......... .......... .......... .......... 77% 43.2M 3s\n", - "463050K .......... .......... .......... .......... .......... 77% 49.4M 3s\n", - "463100K .......... .......... .......... .......... .......... 77% 4.37M 3s\n", - "463150K .......... .......... .......... .......... .......... 77% 57.1M 3s\n", - "463200K .......... .......... .......... .......... .......... 77% 53.9M 3s\n", - "463250K .......... .......... .......... .......... .......... 77% 71.2M 3s\n", - "463300K .......... .......... .......... .......... .......... 77% 70.2M 3s\n", - "463350K .......... .......... .......... .......... .......... 77% 65.0M 3s\n", - "463400K .......... .......... .......... .......... .......... 77% 47.9M 3s\n", - "463450K .......... .......... .......... .......... .......... 77% 44.8M 3s\n", - "463500K .......... .......... .......... .......... .......... 77% 56.4M 3s\n", - "463550K .......... .......... .......... .......... .......... 77% 59.2M 3s\n", - "463600K .......... .......... .......... .......... .......... 77% 50.5M 3s\n", - "463650K .......... .......... .......... .......... .......... 77% 40.0M 3s\n", - "463700K .......... .......... .......... .......... .......... 77% 42.3M 3s\n", - "463750K .......... .......... .......... .......... .......... 77% 71.4M 3s\n", - "463800K .......... .......... .......... .......... .......... 77% 48.9M 3s\n", - "463850K .......... .......... .......... .......... .......... 78% 54.7M 3s\n", - "463900K .......... .......... .......... .......... .......... 78% 47.0M 3s\n", - "463950K .......... .......... .......... .......... .......... 78% 49.1M 3s\n", - "464000K .......... .......... .......... .......... .......... 78% 57.3M 3s\n", - "464050K .......... .......... .......... .......... .......... 78% 65.3M 3s\n", - "464100K .......... .......... .......... .......... .......... 78% 57.1M 3s\n", - "464150K .......... .......... .......... .......... .......... 78% 50.9M 3s\n", - "464200K .......... .......... .......... .......... .......... 78% 43.3M 3s\n", - "464250K .......... .......... .......... .......... .......... 78% 62.2M 3s\n", - "464300K .......... .......... .......... .......... .......... 78% 68.2M 3s\n", - "464350K .......... .......... .......... .......... .......... 78% 53.5M 3s\n", - "464400K .......... .......... .......... .......... .......... 78% 46.1M 3s\n", - "464450K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", - "464500K .......... .......... .......... .......... .......... 78% 66.4M 3s\n", - "464550K .......... .......... .......... .......... .......... 78% 64.7M 3s\n", - "464600K .......... .......... .......... .......... .......... 78% 48.2M 3s\n", - "464650K .......... .......... .......... .......... .......... 78% 50.0M 3s\n", - "464700K .......... .......... .......... .......... .......... 78% 51.2M 3s\n", - "464750K .......... .......... .......... .......... .......... 78% 69.3M 3s\n", - "464800K .......... .......... .......... .......... .......... 78% 57.2M 3s\n", - "464850K .......... .......... .......... .......... .......... 78% 72.8M 3s\n", - "464900K .......... .......... .......... .......... .......... 78% 56.5M 3s\n", - "464950K .......... .......... .......... .......... .......... 78% 47.8M 3s\n", - "465000K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", - "465050K .......... .......... .......... .......... .......... 78% 66.1M 3s\n", - "465100K .......... .......... .......... .......... .......... 78% 61.9M 3s\n", - "465150K .......... .......... .......... .......... .......... 78% 58.4M 3s\n", - "465200K .......... .......... .......... .......... .......... 78% 47.4M 3s\n", - "465250K .......... .......... .......... .......... .......... 78% 43.4M 3s\n", - "465300K .......... .......... .......... .......... .......... 78% 64.6M 3s\n", - "465350K .......... .......... .......... .......... .......... 78% 66.7M 3s\n", - "465400K .......... .......... .......... .......... .......... 78% 39.1M 3s\n", - "465450K .......... .......... .......... .......... .......... 78% 47.6M 3s\n", - "465500K .......... .......... .......... .......... .......... 78% 59.3M 3s\n", - "465550K .......... .......... .......... .......... .......... 78% 71.1M 3s\n", - "465600K .......... .......... .......... .......... .......... 78% 57.0M 3s\n", - "465650K .......... .......... .......... .......... .......... 78% 57.6M 3s\n", - "465700K .......... .......... .......... .......... .......... 78% 50.2M 3s\n", - "465750K .......... .......... .......... .......... .......... 78% 49.8M 3s\n", - "465800K .......... .......... .......... .......... .......... 78% 60.6M 3s\n", - "465850K .......... .......... .......... .......... .......... 78% 72.0M 3s\n", - "465900K .......... .......... .......... .......... .......... 78% 72.1M 3s\n", - "465950K .......... .......... .......... .......... .......... 78% 53.8M 3s\n", - "466000K .......... .......... .......... .......... .......... 78% 48.6M 3s\n", - "466050K .......... .......... .......... .......... .......... 78% 63.7M 3s\n", - "466100K .......... .......... .......... .......... .......... 78% 68.7M 3s\n", - "466150K .......... .......... .......... .......... .......... 78% 70.8M 3s\n", - "466200K .......... .......... .......... .......... .......... 78% 41.5M 3s\n", - "466250K .......... .......... .......... .......... .......... 78% 43.7M 3s\n", - "466300K .......... .......... .......... .......... .......... 78% 54.0M 3s\n", - "466350K .......... .......... .......... .......... .......... 78% 63.6M 3s\n", - "466400K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", - "466450K .......... .......... .......... .......... .......... 78% 58.6M 3s\n", - "466500K .......... .......... .......... .......... .......... 78% 52.8M 3s\n", - "466550K .......... .......... .......... .......... .......... 78% 52.1M 3s\n", - "466600K .......... .......... .......... .......... .......... 78% 56.0M 3s\n", - "466650K .......... .......... .......... .......... .......... 78% 62.5M 3s\n", - "466700K .......... .......... .......... .......... .......... 78% 55.1M 3s\n", - "466750K .......... .......... .......... .......... .......... 78% 52.3M 3s\n", - "466800K .......... .......... .......... .......... .......... 78% 44.5M 3s\n", - "466850K .......... .......... .......... .......... .......... 78% 73.7M 3s\n", - "466900K .......... .......... .......... .......... .......... 78% 65.8M 3s\n", - "466950K .......... .......... .......... .......... .......... 78% 49.1M 3s\n", - "467000K .......... .......... .......... .......... .......... 78% 39.2M 3s\n", - "467050K .......... .......... .......... .......... .......... 78% 50.1M 3s\n", - "467100K .......... .......... .......... .......... .......... 78% 67.9M 3s\n", - "467150K .......... .......... .......... .......... .......... 78% 65.5M 3s\n", - "467200K .......... .......... .......... .......... .......... 78% 45.4M 3s\n", - "467250K .......... .......... .......... .......... .......... 78% 45.5M 3s\n", - "467300K .......... .......... .......... .......... .......... 78% 60.9M 3s\n", - "467350K .......... .......... .......... .......... .......... 78% 62.8M 3s\n", - "467400K .......... .......... .......... .......... .......... 78% 60.4M 3s\n", - "467450K .......... .......... .......... .......... .......... 78% 56.1M 3s\n", - "467500K .......... .......... .......... .......... .......... 78% 47.3M 3s\n", - "467550K .......... .......... .......... .......... .......... 78% 59.2M 3s\n", - "467600K .......... .......... .......... .......... .......... 78% 60.2M 3s\n", - "467650K .......... .......... .......... .......... .......... 78% 68.3M 3s\n", - "467700K .......... .......... .......... .......... .......... 78% 70.4M 3s\n", - "467750K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", - "467800K .......... .......... .......... .......... .......... 78% 44.2M 3s\n", - "467850K .......... .......... .......... .......... .......... 78% 63.6M 3s\n", - "467900K .......... .......... .......... .......... .......... 78% 66.0M 3s\n", - "467950K .......... .......... .......... .......... .......... 78% 68.9M 3s\n", - "468000K .......... .......... .......... .......... .......... 78% 49.4M 3s\n", - "468050K .......... .......... .......... .......... .......... 78% 52.1M 3s\n", - "468100K .......... .......... .......... .......... .......... 78% 50.3M 3s\n", - "468150K .......... .......... .......... .......... .......... 78% 57.1M 3s\n", - "468200K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", - "468250K .......... .......... .......... .......... .......... 78% 54.0M 3s\n", - "468300K .......... .......... .......... .......... .......... 78% 44.1M 3s\n", - "468350K .......... .......... .......... .......... .......... 78% 61.7M 3s\n", - "468400K .......... .......... .......... .......... .......... 78% 57.7M 3s\n", - "468450K .......... .......... .......... .......... .......... 78% 74.5M 3s\n", - "468500K .......... .......... .......... .......... .......... 78% 56.0M 3s\n", - "468550K .......... .......... .......... .......... .......... 78% 51.5M 3s\n", - "468600K .......... .......... .......... .......... .......... 78% 56.3M 3s\n", - "468650K .......... .......... .......... .......... .......... 78% 78.4M 3s\n", - "468700K .......... .......... .......... .......... .......... 78% 81.2M 3s\n", - "468750K .......... .......... .......... .......... .......... 78% 76.4M 3s\n", - "468800K .......... .......... .......... .......... .......... 78% 51.0M 3s\n", - "468850K .......... .......... .......... .......... .......... 78% 50.8M 3s\n", - "468900K .......... .......... .......... .......... .......... 78% 77.6M 3s\n", - "468950K .......... .......... .......... .......... .......... 78% 80.9M 3s\n", - "469000K .......... .......... .......... .......... .......... 78% 66.6M 3s\n", - "469050K .......... .......... .......... .......... .......... 78% 78.1M 3s\n", - "469100K .......... .......... .......... .......... .......... 78% 53.3M 3s\n", - "469150K .......... .......... .......... .......... .......... 78% 51.0M 3s\n", - "469200K .......... .......... .......... .......... .......... 78% 53.4M 3s\n", - "469250K .......... .......... .......... .......... .......... 78% 70.1M 3s\n", - "469300K .......... .......... .......... .......... .......... 78% 62.3M 3s\n", - "469350K .......... .......... .......... .......... .......... 78% 61.1M 3s\n", - "469400K .......... .......... .......... .......... .......... 78% 39.4M 3s\n", - "469450K .......... .......... .......... .......... .......... 78% 50.6M 3s\n", - "469500K .......... .......... .......... .......... .......... 78% 61.6M 3s\n", - "469550K .......... .......... .......... .......... .......... 78% 64.0M 3s\n", - "469600K .......... .......... .......... .......... .......... 78% 52.2M 3s\n", - "469650K .......... .......... .......... .......... .......... 78% 51.5M 3s\n", - "469700K .......... .......... .......... .......... .......... 78% 51.4M 3s\n", - "469750K .......... .......... .......... .......... .......... 78% 65.3M 3s\n", - "469800K .......... .......... .......... .......... .......... 79% 53.8M 3s\n", - "469850K .......... .......... .......... .......... .......... 79% 56.9M 3s\n", - "469900K .......... .......... .......... .......... .......... 79% 52.2M 3s\n", - "469950K .......... .......... .......... .......... .......... 79% 55.2M 3s\n", - "470000K .......... .......... .......... .......... .......... 79% 62.5M 3s\n", - "470050K .......... .......... .......... .......... .......... 79% 69.2M 3s\n", - "470100K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", - "470150K .......... .......... .......... .......... .......... 79% 56.9M 3s\n", - "470200K .......... .......... .......... .......... .......... 79% 39.5M 3s\n", - "470250K .......... .......... .......... .......... .......... 79% 65.5M 3s\n", - "470300K .......... .......... .......... .......... .......... 79% 63.5M 3s\n", - "470350K .......... .......... .......... .......... .......... 79% 73.1M 3s\n", - "470400K .......... .......... .......... .......... .......... 79% 48.6M 3s\n", - "470450K .......... .......... .......... .......... .......... 79% 51.4M 3s\n", - "470500K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", - "470550K .......... .......... .......... .......... .......... 79% 66.1M 3s\n", - "470600K .......... .......... .......... .......... .......... 79% 57.7M 3s\n", - "470650K .......... .......... .......... .......... .......... 79% 50.1M 3s\n", - "470700K .......... .......... .......... .......... .......... 79% 48.3M 3s\n", - "470750K .......... .......... .......... .......... .......... 79% 56.1M 3s\n", - "470800K .......... .......... .......... .......... .......... 79% 57.8M 3s\n", - "470850K .......... .......... .......... .......... .......... 79% 71.5M 3s\n", - "470900K .......... .......... .......... .......... .......... 79% 60.7M 3s\n", - "470950K .......... .......... .......... .......... .......... 79% 49.3M 3s\n", - "471000K .......... .......... .......... .......... .......... 79% 43.7M 3s\n", - "471050K .......... .......... .......... .......... .......... 79% 64.0M 3s\n", - "471100K .......... .......... .......... .......... .......... 79% 66.8M 3s\n", - "471150K .......... .......... .......... .......... .......... 79% 64.5M 3s\n", - "471200K .......... .......... .......... .......... .......... 79% 61.6M 3s\n", - "471250K .......... .......... .......... .......... .......... 79% 75.5M 3s\n", - "471300K .......... .......... .......... .......... .......... 79% 60.8M 3s\n", - "471350K .......... .......... .......... .......... .......... 79% 68.7M 3s\n", - "471400K .......... .......... .......... .......... .......... 79% 50.1M 3s\n", - "471450K .......... .......... .......... .......... .......... 79% 51.0M 3s\n", - "471500K .......... .......... .......... .......... .......... 79% 53.0M 3s\n", - "471550K .......... .......... .......... .......... .......... 79% 72.7M 3s\n", - "471600K .......... .......... .......... .......... .......... 79% 63.3M 3s\n", - "471650K .......... .......... .......... .......... .......... 79% 67.9M 3s\n", - "471700K .......... .......... .......... .......... .......... 79% 50.0M 3s\n", - "471750K .......... .......... .......... .......... .......... 79% 48.7M 3s\n", - "471800K .......... .......... .......... .......... .......... 79% 38.7M 3s\n", - "471850K .......... .......... .......... .......... .......... 79% 62.3M 3s\n", - "471900K .......... .......... .......... .......... .......... 79% 57.3M 3s\n", - "471950K .......... .......... .......... .......... .......... 79% 63.8M 3s\n", - "472000K .......... .......... .......... .......... .......... 79% 49.1M 3s\n", - "472050K .......... .......... .......... .......... .......... 79% 42.7M 3s\n", - "472100K .......... .......... .......... .......... .......... 79% 67.0M 3s\n", - "472150K .......... .......... .......... .......... .......... 79% 68.1M 3s\n", - "472200K .......... .......... .......... .......... .......... 79% 50.9M 3s\n", - "472250K .......... .......... .......... .......... .......... 79% 53.4M 3s\n", - "472300K .......... .......... .......... .......... .......... 79% 53.2M 3s\n", - "472350K .......... .......... .......... .......... .......... 79% 53.6M 3s\n", - "472400K .......... .......... .......... .......... .......... 79% 60.4M 3s\n", - "472450K .......... .......... .......... .......... .......... 79% 63.0M 3s\n", - "472500K .......... .......... .......... .......... .......... 79% 48.7M 3s\n", - "472550K .......... .......... .......... .......... .......... 79% 3.68M 3s\n", - "472600K .......... .......... .......... .......... .......... 79% 53.7M 3s\n", - "472650K .......... .......... .......... .......... .......... 79% 61.9M 3s\n", - "472700K .......... .......... .......... .......... .......... 79% 66.3M 3s\n", - "472750K .......... .......... .......... .......... .......... 79% 65.4M 3s\n", - "472800K .......... .......... .......... .......... .......... 79% 64.0M 3s\n", - "472850K .......... .......... .......... .......... .......... 79% 76.4M 3s\n", - "472900K .......... .......... .......... .......... .......... 79% 56.7M 3s\n", - "472950K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", - "473000K .......... .......... .......... .......... .......... 79% 55.8M 3s\n", - "473050K .......... .......... .......... .......... .......... 79% 52.8M 3s\n", - "473100K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", - "473150K .......... .......... .......... .......... .......... 79% 50.5M 3s\n", - "473200K .......... .......... .......... .......... .......... 79% 59.2M 3s\n", - "473250K .......... .......... .......... .......... .......... 79% 72.3M 3s\n", - "473300K .......... .......... .......... .......... .......... 79% 61.4M 3s\n", - "473350K .......... .......... .......... .......... .......... 79% 42.1M 3s\n", - "473400K .......... .......... .......... .......... .......... 79% 41.4M 3s\n", - "473450K .......... .......... .......... .......... .......... 79% 58.6M 3s\n", - "473500K .......... .......... .......... .......... .......... 79% 61.7M 3s\n", - "473550K .......... .......... .......... .......... .......... 79% 56.4M 3s\n", - "473600K .......... .......... .......... .......... .......... 79% 41.5M 3s\n", - "473650K .......... .......... .......... .......... .......... 79% 50.4M 3s\n", - "473700K .......... .......... .......... .......... .......... 79% 58.7M 3s\n", - "473750K .......... .......... .......... .......... .......... 79% 5.62M 3s\n", - "473800K .......... .......... .......... .......... .......... 79% 55.6M 3s\n", - "473850K .......... .......... .......... .......... .......... 79% 72.5M 3s\n", - "473900K .......... .......... .......... .......... .......... 79% 67.9M 3s\n", - "473950K .......... .......... .......... .......... .......... 79% 70.3M 3s\n", - "474000K .......... .......... .......... .......... .......... 79% 51.3M 3s\n", - "474050K .......... .......... .......... .......... .......... 79% 65.4M 3s\n", - "474100K .......... .......... .......... .......... .......... 79% 44.3M 3s\n", - "474150K .......... .......... .......... .......... .......... 79% 58.7M 3s\n", - "474200K .......... .......... .......... .......... .......... 79% 56.3M 3s\n", - "474250K .......... .......... .......... .......... .......... 79% 62.3M 3s\n", - "474300K .......... .......... .......... .......... .......... 79% 49.1M 3s\n", - "474350K .......... .......... .......... .......... .......... 79% 54.9M 3s\n", - "474400K .......... .......... .......... .......... .......... 79% 56.2M 3s\n", - "474450K .......... .......... .......... .......... .......... 79% 66.8M 3s\n", - "474500K .......... .......... .......... .......... .......... 79% 71.6M 3s\n", - "474550K .......... .......... .......... .......... .......... 79% 52.3M 3s\n", - "474600K .......... .......... .......... .......... .......... 79% 42.0M 3s\n", - "474650K .......... .......... .......... .......... .......... 79% 56.0M 3s\n", - "474700K .......... .......... .......... .......... .......... 79% 69.6M 3s\n", - "474750K .......... .......... .......... .......... .......... 79% 70.7M 3s\n", - "474800K .......... .......... .......... .......... .......... 79% 55.4M 3s\n", - "474850K .......... .......... .......... .......... .......... 79% 60.7M 3s\n", - "474900K .......... .......... .......... .......... .......... 79% 50.9M 3s\n", - "474950K .......... .......... .......... .......... .......... 79% 57.2M 3s\n", - "475000K .......... .......... .......... .......... .......... 79% 57.5M 3s\n", - "475050K .......... .......... .......... .......... .......... 79% 78.2M 3s\n", - "475100K .......... .......... .......... .......... .......... 79% 60.1M 3s\n", - "475150K .......... .......... .......... .......... .......... 79% 53.1M 3s\n", - "475200K .......... .......... .......... .......... .......... 79% 45.7M 3s\n", - "475250K .......... .......... .......... .......... .......... 79% 62.2M 3s\n", - "475300K .......... .......... .......... .......... .......... 79% 76.7M 3s\n", - "475350K .......... .......... .......... .......... .......... 79% 50.0M 3s\n", - "475400K .......... .......... .......... .......... .......... 79% 47.6M 3s\n", - "475450K .......... .......... .......... .......... .......... 79% 58.6M 3s\n", - "475500K .......... .......... .......... .......... .......... 79% 63.1M 3s\n", - "475550K .......... .......... .......... .......... .......... 79% 67.6M 3s\n", - "475600K .......... .......... .......... .......... .......... 79% 42.2M 3s\n", - "475650K .......... .......... .......... .......... .......... 79% 67.1M 3s\n", - "475700K .......... .......... .......... .......... .......... 79% 55.7M 3s\n", - "475750K .......... .......... .......... .......... .......... 80% 52.7M 3s\n", - "475800K .......... .......... .......... .......... .......... 80% 54.6M 3s\n", - "475850K .......... .......... .......... .......... .......... 80% 62.6M 3s\n", - "475900K .......... .......... .......... .......... .......... 80% 53.7M 3s\n", - "475950K .......... .......... .......... .......... .......... 80% 56.0M 3s\n", - "476000K .......... .......... .......... .......... .......... 80% 50.7M 3s\n", - "476050K .......... .......... .......... .......... .......... 80% 63.5M 3s\n", - "476100K .......... .......... .......... .......... .......... 80% 5.38M 3s\n", - "476150K .......... .......... .......... .......... .......... 80% 4.12M 3s\n", - "476200K .......... .......... .......... .......... .......... 80% 53.6M 3s\n", - "476250K .......... .......... .......... .......... .......... 80% 60.6M 3s\n", - "476300K .......... .......... .......... .......... .......... 80% 70.6M 3s\n", - "476350K .......... .......... .......... .......... .......... 80% 65.1M 3s\n", - "476400K .......... .......... .......... .......... .......... 80% 60.8M 3s\n", - "476450K .......... .......... .......... .......... .......... 80% 56.0M 3s\n", - "476500K .......... .......... .......... .......... .......... 80% 52.9M 3s\n", - "476550K .......... .......... .......... .......... .......... 80% 68.6M 3s\n", - "476600K .......... .......... .......... .......... .......... 80% 55.1M 3s\n", - "476650K .......... .......... .......... .......... .......... 80% 50.8M 3s\n", - "476700K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", - "476750K .......... .......... .......... .......... .......... 80% 49.4M 3s\n", - "476800K .......... .......... .......... .......... .......... 80% 47.3M 3s\n", - "476850K .......... .......... .......... .......... .......... 80% 70.4M 3s\n", - "476900K .......... .......... .......... .......... .......... 80% 48.3M 3s\n", - "476950K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", - "477000K .......... .......... .......... .......... .......... 80% 44.8M 3s\n", - "477050K .......... .......... .......... .......... .......... 80% 69.1M 3s\n", - "477100K .......... .......... .......... .......... .......... 80% 65.9M 3s\n", - "477150K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", - "477200K .......... .......... .......... .......... .......... 80% 38.2M 3s\n", - "477250K .......... .......... .......... .......... .......... 80% 60.4M 3s\n", - "477300K .......... .......... .......... .......... .......... 80% 64.1M 3s\n", - "477350K .......... .......... .......... .......... .......... 80% 66.2M 3s\n", - "477400K .......... .......... .......... .......... .......... 80% 39.6M 3s\n", - "477450K .......... .......... .......... .......... .......... 80% 42.9M 3s\n", - "477500K .......... .......... .......... .......... .......... 80% 51.6M 3s\n", - "477550K .......... .......... .......... .......... .......... 80% 67.0M 3s\n", - "477600K .......... .......... .......... .......... .......... 80% 60.0M 3s\n", - "477650K .......... .......... .......... .......... .......... 80% 53.8M 3s\n", - "477700K .......... .......... .......... .......... .......... 80% 45.7M 3s\n", - "477750K .......... .......... .......... .......... .......... 80% 60.4M 3s\n", - "477800K .......... .......... .......... .......... .......... 80% 52.5M 3s\n", - "477850K .......... .......... .......... .......... .......... 80% 68.8M 3s\n", - "477900K .......... .......... .......... .......... .......... 80% 62.0M 3s\n", - "477950K .......... .......... .......... .......... .......... 80% 47.6M 3s\n", - "478000K .......... .......... .......... .......... .......... 80% 42.4M 3s\n", - "478050K .......... .......... .......... .......... .......... 80% 61.0M 3s\n", - "478100K .......... .......... .......... .......... .......... 80% 62.5M 3s\n", - "478150K .......... .......... .......... .......... .......... 80% 63.9M 3s\n", - "478200K .......... .......... .......... .......... .......... 80% 50.6M 3s\n", - "478250K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", - "478300K .......... .......... .......... .......... .......... 80% 60.9M 3s\n", - "478350K .......... .......... .......... .......... .......... 80% 71.4M 3s\n", - "478400K .......... .......... .......... .......... .......... 80% 58.0M 3s\n", - "478450K .......... .......... .......... .......... .......... 80% 58.7M 3s\n", - "478500K .......... .......... .......... .......... .......... 80% 58.6M 3s\n", - "478550K .......... .......... .......... .......... .......... 80% 53.6M 3s\n", - "478600K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", - "478650K .......... .......... .......... .......... .......... 80% 71.7M 3s\n", - "478700K .......... .......... .......... .......... .......... 80% 45.0M 3s\n", - "478750K .......... .......... .......... .......... .......... 80% 55.4M 3s\n", - "478800K .......... .......... .......... .......... .......... 80% 51.2M 3s\n", - "478850K .......... .......... .......... .......... .......... 80% 68.3M 3s\n", - "478900K .......... .......... .......... .......... .......... 80% 56.2M 3s\n", - "478950K .......... .......... .......... .......... .......... 80% 61.1M 3s\n", - "479000K .......... .......... .......... .......... .......... 80% 36.7M 3s\n", - "479050K .......... .......... .......... .......... .......... 80% 56.9M 3s\n", - "479100K .......... .......... .......... .......... .......... 80% 66.7M 3s\n", - "479150K .......... .......... .......... .......... .......... 80% 51.0M 3s\n", - "479200K .......... .......... .......... .......... .......... 80% 46.8M 3s\n", - "479250K .......... .......... .......... .......... .......... 80% 70.4M 3s\n", - "479300K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", - "479350K .......... .......... .......... .......... .......... 80% 66.9M 3s\n", - "479400K .......... .......... .......... .......... .......... 80% 52.3M 3s\n", - "479450K .......... .......... .......... .......... .......... 80% 41.5M 3s\n", - "479500K .......... .......... .......... .......... .......... 80% 53.3M 3s\n", - "479550K .......... .......... .......... .......... .......... 80% 46.2M 3s\n", - "479600K .......... .......... .......... .......... .......... 80% 52.3M 3s\n", - "479650K .......... .......... .......... .......... .......... 80% 57.9M 3s\n", - "479700K .......... .......... .......... .......... .......... 80% 59.9M 3s\n", - "479750K .......... .......... .......... .......... .......... 80% 59.0M 3s\n", - "479800K .......... .......... .......... .......... .......... 80% 47.0M 3s\n", - "479850K .......... .......... .......... .......... .......... 80% 68.7M 3s\n", - "479900K .......... .......... .......... .......... .......... 80% 54.8M 3s\n", - "479950K .......... .......... .......... .......... .......... 80% 56.5M 3s\n", - "480000K .......... .......... .......... .......... .......... 80% 48.4M 3s\n", - "480050K .......... .......... .......... .......... .......... 80% 46.1M 3s\n", - "480100K .......... .......... .......... .......... .......... 80% 49.0M 3s\n", - "480150K .......... .......... .......... .......... .......... 80% 3.88M 3s\n", - "480200K .......... .......... .......... .......... .......... 80% 55.3M 3s\n", - "480250K .......... .......... .......... .......... .......... 80% 68.8M 3s\n", - "480300K .......... .......... .......... .......... .......... 80% 60.3M 3s\n", - "480350K .......... .......... .......... .......... .......... 80% 64.8M 3s\n", - "480400K .......... .......... .......... .......... .......... 80% 60.6M 3s\n", - "480450K .......... .......... .......... .......... .......... 80% 61.2M 3s\n", - "480500K .......... .......... .......... .......... .......... 80% 46.8M 3s\n", - "480550K .......... .......... .......... .......... .......... 80% 59.1M 3s\n", - "480600K .......... .......... .......... .......... .......... 80% 51.6M 3s\n", - "480650K .......... .......... .......... .......... .......... 80% 64.9M 3s\n", - "480700K .......... .......... .......... .......... .......... 80% 8.64M 3s\n", - "480750K .......... .......... .......... .......... .......... 80% 55.7M 3s\n", - "480800K .......... .......... .......... .......... .......... 80% 53.4M 3s\n", - "480850K .......... .......... .......... .......... .......... 80% 59.5M 3s\n", - "480900K .......... .......... .......... .......... .......... 80% 60.2M 3s\n", - "480950K .......... .......... .......... .......... .......... 80% 55.2M 3s\n", - "481000K .......... .......... .......... .......... .......... 80% 48.4M 3s\n", - "481050K .......... .......... .......... .......... .......... 80% 54.9M 3s\n", - "481100K .......... .......... .......... .......... .......... 80% 51.4M 3s\n", - "481150K .......... .......... .......... .......... .......... 80% 44.9M 3s\n", - "481200K .......... .......... .......... .......... .......... 80% 59.3M 3s\n", - "481250K .......... .......... .......... .......... .......... 80% 63.4M 3s\n", - "481300K .......... .......... .......... .......... .......... 80% 44.7M 3s\n", - "481350K .......... .......... .......... .......... .......... 80% 46.4M 3s\n", - "481400K .......... .......... .......... .......... .......... 80% 45.8M 3s\n", - "481450K .......... .......... .......... .......... .......... 80% 49.8M 3s\n", - "481500K .......... .......... .......... .......... .......... 80% 3.82M 3s\n", - "481550K .......... .......... .......... .......... .......... 80% 5.11M 3s\n", - "481600K .......... .......... .......... .......... .......... 80% 59.7M 3s\n", - "481650K .......... .......... .......... .......... .......... 80% 64.9M 3s\n", - "481700K .......... .......... .......... .......... .......... 81% 66.9M 3s\n", - "481750K .......... .......... .......... .......... .......... 81% 64.3M 3s\n", - "481800K .......... .......... .......... .......... .......... 81% 56.5M 3s\n", - "481850K .......... .......... .......... .......... .......... 81% 44.7M 3s\n", - "481900K .......... .......... .......... .......... .......... 81% 65.6M 3s\n", - "481950K .......... .......... .......... .......... .......... 81% 58.3M 3s\n", - "482000K .......... .......... .......... .......... .......... 81% 56.4M 3s\n", - "482050K .......... .......... .......... .......... .......... 81% 72.9M 3s\n", - "482100K .......... .......... .......... .......... .......... 81% 63.5M 3s\n", - "482150K .......... .......... .......... .......... .......... 81% 46.2M 3s\n", - "482200K .......... .......... .......... .......... .......... 81% 48.6M 3s\n", - "482250K .......... .......... .......... .......... .......... 81% 65.1M 3s\n", - "482300K .......... .......... .......... .......... .......... 81% 58.2M 3s\n", - "482350K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", - "482400K .......... .......... .......... .......... .......... 81% 53.9M 3s\n", - "482450K .......... .......... .......... .......... .......... 81% 49.0M 3s\n", - "482500K .......... .......... .......... .......... .......... 81% 70.1M 3s\n", - "482550K .......... .......... .......... .......... .......... 81% 67.9M 3s\n", - "482600K .......... .......... .......... .......... .......... 81% 49.8M 3s\n", - "482650K .......... .......... .......... .......... .......... 81% 60.6M 3s\n", - "482700K .......... .......... .......... .......... .......... 81% 61.6M 3s\n", - "482750K .......... .......... .......... .......... .......... 81% 57.1M 3s\n", - "482800K .......... .......... .......... .......... .......... 81% 63.3M 3s\n", - "482850K .......... .......... .......... .......... .......... 81% 67.4M 3s\n", - "482900K .......... .......... .......... .......... .......... 81% 69.8M 3s\n", - "482950K .......... .......... .......... .......... .......... 81% 52.2M 3s\n", - "483000K .......... .......... .......... .......... .......... 81% 34.3M 3s\n", - "483050K .......... .......... .......... .......... .......... 81% 62.1M 3s\n", - "483100K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", - "483150K .......... .......... .......... .......... .......... 81% 56.6M 3s\n", - "483200K .......... .......... .......... .......... .......... 81% 49.5M 3s\n", - "483250K .......... .......... .......... .......... .......... 81% 52.5M 3s\n", - "483300K .......... .......... .......... .......... .......... 81% 53.4M 3s\n", - "483350K .......... .......... .......... .......... .......... 81% 65.6M 3s\n", - "483400K .......... .......... .......... .......... .......... 81% 50.4M 3s\n", - "483450K .......... .......... .......... .......... .......... 81% 55.2M 3s\n", - "483500K .......... .......... .......... .......... .......... 81% 57.1M 3s\n", - "483550K .......... .......... .......... .......... .......... 81% 47.5M 3s\n", - "483600K .......... .......... .......... .......... .......... 81% 59.2M 3s\n", - "483650K .......... .......... .......... .......... .......... 81% 60.7M 3s\n", - "483700K .......... .......... .......... .......... .......... 81% 46.2M 3s\n", - "483750K .......... .......... .......... .......... .......... 81% 62.2M 3s\n", - "483800K .......... .......... .......... .......... .......... 81% 39.9M 3s\n", - "483850K .......... .......... .......... .......... .......... 81% 57.9M 3s\n", - "483900K .......... .......... .......... .......... .......... 81% 59.1M 3s\n", - "483950K .......... .......... .......... .......... .......... 81% 47.6M 3s\n", - "484000K .......... .......... .......... .......... .......... 81% 52.7M 3s\n", - "484050K .......... .......... .......... .......... .......... 81% 51.7M 3s\n", - "484100K .......... .......... .......... .......... .......... 81% 52.5M 3s\n", - "484150K .......... .......... .......... .......... .......... 81% 71.8M 3s\n", - "484200K .......... .......... .......... .......... .......... 81% 50.5M 3s\n", - "484250K .......... .......... .......... .......... .......... 81% 59.9M 3s\n", - "484300K .......... .......... .......... .......... .......... 81% 50.8M 3s\n", - "484350K .......... .......... .......... .......... .......... 81% 62.0M 3s\n", - "484400K .......... .......... .......... .......... .......... 81% 56.1M 3s\n", - "484450K .......... .......... .......... .......... .......... 81% 55.4M 3s\n", - "484500K .......... .......... .......... .......... .......... 81% 55.1M 3s\n", - "484550K .......... .......... .......... .......... .......... 81% 52.7M 3s\n", - "484600K .......... .......... .......... .......... .......... 81% 37.6M 3s\n", - "484650K .......... .......... .......... .......... .......... 81% 46.0M 3s\n", - "484700K .......... .......... .......... .......... .......... 81% 3.92M 3s\n", - "484750K .......... .......... .......... .......... .......... 81% 67.8M 3s\n", - "484800K .......... .......... .......... .......... .......... 81% 50.8M 3s\n", - "484850K .......... .......... .......... .......... .......... 81% 62.0M 3s\n", - "484900K .......... .......... .......... .......... .......... 81% 55.6M 3s\n", - "484950K .......... .......... .......... .......... .......... 81% 67.5M 3s\n", - "485000K .......... .......... .......... .......... .......... 81% 36.4M 3s\n", - "485050K .......... .......... .......... .......... .......... 81% 53.6M 3s\n", - "485100K .......... .......... .......... .......... .......... 81% 67.9M 3s\n", - "485150K .......... .......... .......... .......... .......... 81% 67.0M 3s\n", - "485200K .......... .......... .......... .......... .......... 81% 56.6M 3s\n", - "485250K .......... .......... .......... .......... .......... 81% 55.6M 3s\n", - "485300K .......... .......... .......... .......... .......... 81% 35.0M 3s\n", - "485350K .......... .......... .......... .......... .......... 81% 64.1M 3s\n", - "485400K .......... .......... .......... .......... .......... 81% 58.8M 3s\n", - "485450K .......... .......... .......... .......... .......... 81% 66.2M 3s\n", - "485500K .......... .......... .......... .......... .......... 81% 50.2M 3s\n", - "485550K .......... .......... .......... .......... .......... 81% 51.3M 3s\n", - "485600K .......... .......... .......... .......... .......... 81% 51.6M 3s\n", - "485650K .......... .......... .......... .......... .......... 81% 73.0M 3s\n", - "485700K .......... .......... .......... .......... .......... 81% 73.6M 3s\n", - "485750K .......... .......... .......... .......... .......... 81% 74.2M 3s\n", - "485800K .......... .......... .......... .......... .......... 81% 47.0M 3s\n", - "485850K .......... .......... .......... .......... .......... 81% 48.3M 3s\n", - "485900K .......... .......... .......... .......... .......... 81% 70.8M 3s\n", - "485950K .......... .......... .......... .......... .......... 81% 62.9M 3s\n", - "486000K .......... .......... .......... .......... .......... 81% 59.2M 3s\n", - "486050K .......... .......... .......... .......... .......... 81% 58.2M 3s\n", - "486100K .......... .......... .......... .......... .......... 81% 50.2M 3s\n", - "486150K .......... .......... .......... .......... .......... 81% 3.46M 3s\n", - "486200K .......... .......... .......... .......... .......... 81% 58.3M 3s\n", - "486250K .......... .......... .......... .......... .......... 81% 62.3M 3s\n", - "486300K .......... .......... .......... .......... .......... 81% 55.7M 3s\n", - "486350K .......... .......... .......... .......... .......... 81% 67.0M 3s\n", - "486400K .......... .......... .......... .......... .......... 81% 8.46M 3s\n", - "486450K .......... .......... .......... .......... .......... 81% 56.7M 3s\n", - "486500K .......... .......... .......... .......... .......... 81% 69.6M 3s\n", - "486550K .......... .......... .......... .......... .......... 81% 70.0M 3s\n", - "486600K .......... .......... .......... .......... .......... 81% 52.9M 3s\n", - "486650K .......... .......... .......... .......... .......... 81% 71.6M 3s\n", - "486700K .......... .......... .......... .......... .......... 81% 64.1M 3s\n", - "486750K .......... .......... .......... .......... .......... 81% 47.6M 3s\n", - "486800K .......... .......... .......... .......... .......... 81% 62.3M 3s\n", - "486850K .......... .......... .......... .......... .......... 81% 74.1M 3s\n", - "486900K .......... .......... .......... .......... .......... 81% 68.2M 3s\n", - "486950K .......... .......... .......... .......... .......... 81% 67.1M 3s\n", - "487000K .......... .......... .......... .......... .......... 81% 36.3M 3s\n", - "487050K .......... .......... .......... .......... .......... 81% 55.4M 3s\n", - "487100K .......... .......... .......... .......... .......... 81% 69.9M 3s\n", - "487150K .......... .......... .......... .......... .......... 81% 26.9M 3s\n", - "487200K .......... .......... .......... .......... .......... 81% 30.6M 3s\n", - "487250K .......... .......... .......... .......... .......... 81% 58.8M 3s\n", - "487300K .......... .......... .......... .......... .......... 81% 75.8M 3s\n", - "487350K .......... .......... .......... .......... .......... 81% 23.0M 3s\n", - "487400K .......... .......... .......... .......... .......... 81% 44.1M 3s\n", - "487450K .......... .......... .......... .......... .......... 81% 71.6M 3s\n", - "487500K .......... .......... .......... .......... .......... 81% 24.2M 3s\n", - "487550K .......... .......... .......... .......... .......... 81% 33.4M 3s\n", - "487600K .......... .......... .......... .......... .......... 81% 41.7M 3s\n", - "487650K .......... .......... .......... .......... .......... 82% 69.8M 3s\n", - "487700K .......... .......... .......... .......... .......... 82% 22.3M 3s\n", - "487750K .......... .......... .......... .......... .......... 82% 31.0M 3s\n", - "487800K .......... .......... .......... .......... .......... 82% 31.9M 3s\n", - "487850K .......... .......... .......... .......... .......... 82% 53.3M 3s\n", - "487900K .......... .......... .......... .......... .......... 82% 47.0M 3s\n", - "487950K .......... .......... .......... .......... .......... 82% 41.2M 3s\n", - "488000K .......... .......... .......... .......... .......... 82% 66.3M 3s\n", - "488050K .......... .......... .......... .......... .......... 82% 5.08M 3s\n", - "488100K .......... .......... .......... .......... .......... 82% 63.1M 3s\n", - "488150K .......... .......... .......... .......... .......... 82% 50.6M 3s\n", - "488200K .......... .......... .......... .......... .......... 82% 32.5M 3s\n", - "488250K .......... .......... .......... .......... .......... 82% 13.5M 3s\n", - "488300K .......... .......... .......... .......... .......... 82% 49.7M 3s\n", - "488350K .......... .......... .......... .......... .......... 82% 32.7M 3s\n", - "488400K .......... .......... .......... .......... .......... 82% 42.8M 3s\n", - "488450K .......... .......... .......... .......... .......... 82% 52.8M 3s\n", - "488500K .......... .......... .......... .......... .......... 82% 23.5M 3s\n", - "488550K .......... .......... .......... .......... .......... 82% 33.3M 3s\n", - "488600K .......... .......... .......... .......... .......... 82% 24.9M 3s\n", - "488650K .......... .......... .......... .......... .......... 82% 22.4M 3s\n", - "488700K .......... .......... .......... .......... .......... 82% 48.5M 3s\n", - "488750K .......... .......... .......... .......... .......... 82% 17.1M 3s\n", - "488800K .......... .......... .......... .......... .......... 82% 38.3M 3s\n", - "488850K .......... .......... .......... .......... .......... 82% 28.7M 3s\n", - "488900K .......... .......... .......... .......... .......... 82% 23.9M 3s\n", - "488950K .......... .......... .......... .......... .......... 82% 47.2M 3s\n", - "489000K .......... .......... .......... .......... .......... 82% 16.4M 3s\n", - "489050K .......... .......... .......... .......... .......... 82% 34.6M 3s\n", - "489100K .......... .......... .......... .......... .......... 82% 18.4M 3s\n", - "489150K .......... .......... .......... .......... .......... 82% 47.7M 3s\n", - "489200K .......... .......... .......... .......... .......... 82% 31.5M 3s\n", - "489250K .......... .......... .......... .......... .......... 82% 17.9M 3s\n", - "489300K .......... .......... .......... .......... .......... 82% 50.7M 3s\n", - "489350K .......... .......... .......... .......... .......... 82% 15.2M 3s\n", - "489400K .......... .......... .......... .......... .......... 82% 32.3M 3s\n", - "489450K .......... .......... .......... .......... .......... 82% 35.7M 3s\n", - "489500K .......... .......... .......... .......... .......... 82% 19.4M 3s\n", - "489550K .......... .......... .......... .......... .......... 82% 46.4M 3s\n", - "489600K .......... .......... .......... .......... .......... 82% 16.8M 3s\n", - "489650K .......... .......... .......... .......... .......... 82% 47.8M 3s\n", - "489700K .......... .......... .......... .......... .......... 82% 30.8M 3s\n", - "489750K .......... .......... .......... .......... .......... 82% 20.3M 3s\n", - "489800K .......... .......... .......... .......... .......... 82% 41.8M 3s\n", - "489850K .......... .......... .......... .......... .......... 82% 14.7M 3s\n", - "489900K .......... .......... .......... .......... .......... 82% 34.7M 3s\n", - "489950K .......... .......... .......... .......... .......... 82% 38.8M 3s\n", - "490000K .......... .......... .......... .......... .......... 82% 20.7M 3s\n", - "490050K .......... .......... .......... .......... .......... 82% 31.8M 3s\n", - "490100K .......... .......... .......... .......... .......... 82% 20.4M 3s\n", - "490150K .......... .......... .......... .......... .......... 82% 23.4M 3s\n", - "490200K .......... .......... .......... .......... .......... 82% 25.3M 3s\n", - "490250K .......... .......... .......... .......... .......... 82% 34.7M 3s\n", - "490300K .......... .......... .......... .......... .......... 82% 40.5M 3s\n", - "490350K .......... .......... .......... .......... .......... 82% 16.1M 3s\n", - "490400K .......... .......... .......... .......... .......... 82% 30.1M 3s\n", - "490450K .......... .......... .......... .......... .......... 82% 12.2M 3s\n", - "490500K .......... .......... .......... .......... .......... 82% 24.9M 3s\n", - "490550K .......... .......... .......... .......... .......... 82% 59.0M 3s\n", - "490600K .......... .......... .......... .......... .......... 82% 13.7M 3s\n", - "490650K .......... .......... .......... .......... .......... 82% 53.8M 3s\n", - "490700K .......... .......... .......... .......... .......... 82% 27.3M 3s\n", - "490750K .......... .......... .......... .......... .......... 82% 21.6M 3s\n", - "490800K .......... .......... .......... .......... .......... 82% 59.0M 3s\n", - "490850K .......... .......... .......... .......... .......... 82% 16.3M 3s\n", - "490900K .......... .......... .......... .......... .......... 82% 43.1M 3s\n", - "490950K .......... .......... .......... .......... .......... 82% 23.9M 3s\n", - "491000K .......... .......... .......... .......... .......... 82% 24.5M 3s\n", - "491050K .......... .......... .......... .......... .......... 82% 69.0M 3s\n", - "491100K .......... .......... .......... .......... .......... 82% 15.7M 3s\n", - "491150K .......... .......... .......... .......... .......... 82% 55.9M 3s\n", - "491200K .......... .......... .......... .......... .......... 82% 19.5M 3s\n", - "491250K .......... .......... .......... .......... .......... 82% 25.4M 3s\n", - "491300K .......... .......... .......... .......... .......... 82% 66.1M 3s\n", - "491350K .......... .......... .......... .......... .......... 82% 14.8M 3s\n", - "491400K .......... .......... .......... .......... .......... 82% 44.0M 3s\n", - "491450K .......... .......... .......... .......... .......... 82% 5.43M 3s\n", - "491500K .......... .......... .......... .......... .......... 82% 60.2M 3s\n", - "491550K .......... .......... .......... .......... .......... 82% 70.1M 3s\n", - "491600K .......... .......... .......... .......... .......... 82% 13.7M 3s\n", - "491650K .......... .......... .......... .......... .......... 82% 57.9M 3s\n", - "491700K .......... .......... .......... .......... .......... 82% 59.5M 3s\n", - "491750K .......... .......... .......... .......... .......... 82% 16.2M 3s\n", - "491800K .......... .......... .......... .......... .......... 82% 44.2M 3s\n", - "491850K .......... .......... .......... .......... .......... 82% 15.4M 3s\n", - "491900K .......... .......... .......... .......... .......... 82% 51.5M 3s\n", - "491950K .......... .......... .......... .......... .......... 82% 17.0M 3s\n", - "492000K .......... .......... .......... .......... .......... 82% 44.1M 3s\n", - "492050K .......... .......... .......... .......... .......... 82% 62.3M 3s\n", - "492100K .......... .......... .......... .......... .......... 82% 16.3M 3s\n", - "492150K .......... .......... .......... .......... .......... 82% 46.6M 3s\n", - "492200K .......... .......... .......... .......... .......... 82% 16.6M 3s\n", - "492250K .......... .......... .......... .......... .......... 82% 41.2M 3s\n", - "492300K .......... .......... .......... .......... .......... 82% 54.6M 3s\n", - "492350K .......... .......... .......... .......... .......... 82% 20.1M 3s\n", - "492400K .......... .......... .......... .......... .......... 82% 41.7M 3s\n", - "492450K .......... .......... .......... .......... .......... 82% 53.9M 3s\n", - "492500K .......... .......... .......... .......... .......... 82% 17.5M 3s\n", - "492550K .......... .......... .......... .......... .......... 82% 43.6M 3s\n", - "492600K .......... .......... .......... .......... .......... 82% 17.3M 3s\n", - "492650K .......... .......... .......... .......... .......... 82% 39.0M 3s\n", - "492700K .......... .......... .......... .......... .......... 82% 53.8M 3s\n", - "492750K .......... .......... .......... .......... .......... 82% 18.6M 3s\n", - "492800K .......... .......... .......... .......... .......... 82% 53.0M 3s\n", - "492850K .......... .......... .......... .......... .......... 82% 53.4M 3s\n", - "492900K .......... .......... .......... .......... .......... 82% 17.4M 3s\n", - "492950K .......... .......... .......... .......... .......... 82% 56.4M 3s\n", - "493000K .......... .......... .......... .......... .......... 82% 15.3M 3s\n", - "493050K .......... .......... .......... .......... .......... 82% 43.9M 3s\n", - "493100K .......... .......... .......... .......... .......... 82% 52.0M 3s\n", - "493150K .......... .......... .......... .......... .......... 82% 18.2M 3s\n", - "493200K .......... .......... .......... .......... .......... 82% 47.3M 3s\n", - "493250K .......... .......... .......... .......... .......... 82% 58.8M 3s\n", - "493300K .......... .......... .......... .......... .......... 82% 18.1M 3s\n", - "493350K .......... .......... .......... .......... .......... 82% 37.9M 3s\n", - "493400K .......... .......... .......... .......... .......... 82% 3.78M 3s\n", - "493450K .......... .......... .......... .......... .......... 82% 72.5M 3s\n", - "493500K .......... .......... .......... .......... .......... 82% 84.1M 3s\n", - "493550K .......... .......... .......... .......... .......... 82% 13.5M 3s\n", - "493600K .......... .......... .......... .......... .......... 83% 49.2M 3s\n", - "493650K .......... .......... .......... .......... .......... 83% 64.1M 3s\n", - "493700K .......... .......... .......... .......... .......... 83% 18.1M 3s\n", - "493750K .......... .......... .......... .......... .......... 83% 42.2M 3s\n", - "493800K .......... .......... .......... .......... .......... 83% 5.10M 3s\n", - "493850K .......... .......... .......... .......... .......... 83% 52.6M 3s\n", - "493900K .......... .......... .......... .......... .......... 83% 68.6M 3s\n", - "493950K .......... .......... .......... .......... .......... 83% 64.5M 3s\n", - "494000K .......... .......... .......... .......... .......... 83% 18.1M 3s\n", - "494050K .......... .......... .......... .......... .......... 83% 55.7M 3s\n", - "494100K .......... .......... .......... .......... .......... 83% 66.6M 3s\n", - "494150K .......... .......... .......... .......... .......... 83% 17.6M 3s\n", - "494200K .......... .......... .......... .......... .......... 83% 46.5M 3s\n", - "494250K .......... .......... .......... .......... .......... 83% 71.6M 3s\n", - "494300K .......... .......... .......... .......... .......... 83% 16.4M 3s\n", - "494350K .......... .......... .......... .......... .......... 83% 53.0M 3s\n", - "494400K .......... .......... .......... .......... .......... 83% 59.7M 3s\n", - "494450K .......... .......... .......... .......... .......... 83% 16.8M 3s\n", - "494500K .......... .......... .......... .......... .......... 83% 55.2M 3s\n", - "494550K .......... .......... .......... .......... .......... 83% 68.6M 3s\n", - "494600K .......... .......... .......... .......... .......... 83% 15.1M 3s\n", - "494650K .......... .......... .......... .......... .......... 83% 49.6M 3s\n", - "494700K .......... .......... .......... .......... .......... 83% 17.9M 3s\n", - "494750K .......... .......... .......... .......... .......... 83% 58.7M 3s\n", - "494800K .......... .......... .......... .......... .......... 83% 55.5M 3s\n", - "494850K .......... .......... .......... .......... .......... 83% 15.9M 3s\n", - "494900K .......... .......... .......... .......... .......... 83% 47.8M 3s\n", - "494950K .......... .......... .......... .......... .......... 83% 60.4M 3s\n", - "495000K .......... .......... .......... .......... .......... 83% 17.0M 3s\n", - "495050K .......... .......... .......... .......... .......... 83% 43.8M 3s\n", - "495100K .......... .......... .......... .......... .......... 83% 57.4M 3s\n", - "495150K .......... .......... .......... .......... .......... 83% 20.5M 3s\n", - "495200K .......... .......... .......... .......... .......... 83% 38.8M 3s\n", - "495250K .......... .......... .......... .......... .......... 83% 52.0M 3s\n", - "495300K .......... .......... .......... .......... .......... 83% 19.8M 3s\n", - "495350K .......... .......... .......... .......... .......... 83% 51.9M 3s\n", - "495400K .......... .......... .......... .......... .......... 83% 44.3M 3s\n", - "495450K .......... .......... .......... .......... .......... 83% 19.2M 3s\n", - "495500K .......... .......... .......... .......... .......... 83% 39.8M 3s\n", - "495550K .......... .......... .......... .......... .......... 83% 57.0M 3s\n", - "495600K .......... .......... .......... .......... .......... 83% 17.7M 3s\n", - "495650K .......... .......... .......... .......... .......... 83% 45.6M 3s\n", - "495700K .......... .......... .......... .......... .......... 83% 48.0M 3s\n", - "495750K .......... .......... .......... .......... .......... 83% 62.2M 3s\n", - "495800K .......... .......... .......... .......... .......... 83% 17.0M 3s\n", - "495850K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", - "495900K .......... .......... .......... .......... .......... 83% 18.9M 3s\n", - "495950K .......... .......... .......... .......... .......... 83% 38.1M 3s\n", - "496000K .......... .......... .......... .......... .......... 83% 56.4M 3s\n", - "496050K .......... .......... .......... .......... .......... 83% 61.6M 3s\n", - "496100K .......... .......... .......... .......... .......... 83% 17.8M 3s\n", - "496150K .......... .......... .......... .......... .......... 83% 59.8M 3s\n", - "496200K .......... .......... .......... .......... .......... 83% 18.0M 3s\n", - "496250K .......... .......... .......... .......... .......... 83% 45.9M 3s\n", - "496300K .......... .......... .......... .......... .......... 83% 59.8M 3s\n", - "496350K .......... .......... .......... .......... .......... 83% 66.2M 3s\n", - "496400K .......... .......... .......... .......... .......... 83% 18.5M 3s\n", - "496450K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", - "496500K .......... .......... .......... .......... .......... 83% 56.6M 3s\n", - "496550K .......... .......... .......... .......... .......... 83% 18.5M 3s\n", - "496600K .......... .......... .......... .......... .......... 83% 41.6M 3s\n", - "496650K .......... .......... .......... .......... .......... 83% 66.4M 3s\n", - "496700K .......... .......... .......... .......... .......... 83% 17.5M 3s\n", - "496750K .......... .......... .......... .......... .......... 83% 56.6M 3s\n", - "496800K .......... .......... .......... .......... .......... 83% 53.1M 3s\n", - "496850K .......... .......... .......... .......... .......... 83% 15.9M 3s\n", - "496900K .......... .......... .......... .......... .......... 83% 43.6M 3s\n", - "496950K .......... .......... .......... .......... .......... 83% 61.1M 3s\n", - "497000K .......... .......... .......... .......... .......... 83% 17.6M 3s\n", - "497050K .......... .......... .......... .......... .......... 83% 52.1M 3s\n", - "497100K .......... .......... .......... .......... .......... 83% 66.7M 3s\n", - "497150K .......... .......... .......... .......... .......... 83% 19.8M 3s\n", - "497200K .......... .......... .......... .......... .......... 83% 41.9M 3s\n", - "497250K .......... .......... .......... .......... .......... 83% 55.1M 3s\n", - "497300K .......... .......... .......... .......... .......... 83% 61.2M 3s\n", - "497350K .......... .......... .......... .......... .......... 83% 19.4M 3s\n", - "497400K .......... .......... .......... .......... .......... 83% 39.6M 3s\n", - "497450K .......... .......... .......... .......... .......... 83% 63.5M 3s\n", - "497500K .......... .......... .......... .......... .......... 83% 16.8M 3s\n", - "497550K .......... .......... .......... .......... .......... 83% 59.2M 3s\n", - "497600K .......... .......... .......... .......... .......... 83% 60.0M 3s\n", - "497650K .......... .......... .......... .......... .......... 83% 23.7M 3s\n", - "497700K .......... .......... .......... .......... .......... 83% 47.6M 3s\n", - "497750K .......... .......... .......... .......... .......... 83% 57.5M 3s\n", - "497800K .......... .......... .......... .......... .......... 83% 19.9M 3s\n", - "497850K .......... .......... .......... .......... .......... 83% 44.1M 3s\n", - "497900K .......... .......... .......... .......... .......... 83% 56.0M 3s\n", - "497950K .......... .......... .......... .......... .......... 83% 65.9M 2s\n", - "498000K .......... .......... .......... .......... .......... 83% 19.5M 2s\n", - "498050K .......... .......... .......... .......... .......... 83% 45.7M 2s\n", - "498100K .......... .......... .......... .......... .......... 83% 68.0M 2s\n", - "498150K .......... .......... .......... .......... .......... 83% 22.6M 2s\n", - "498200K .......... .......... .......... .......... .......... 83% 37.4M 2s\n", - "498250K .......... .......... .......... .......... .......... 83% 62.0M 2s\n", - "498300K .......... .......... .......... .......... .......... 83% 22.4M 2s\n", - "498350K .......... .......... .......... .......... .......... 83% 40.6M 2s\n", - "498400K .......... .......... .......... .......... .......... 83% 48.0M 2s\n", - "498450K .......... .......... .......... .......... .......... 83% 62.6M 2s\n", - "498500K .......... .......... .......... .......... .......... 83% 21.0M 2s\n", - "498550K .......... .......... .......... .......... .......... 83% 48.9M 2s\n", - "498600K .......... .......... .......... .......... .......... 83% 61.5M 2s\n", - "498650K .......... .......... .......... .......... .......... 83% 22.0M 2s\n", - "498700K .......... .......... .......... .......... .......... 83% 32.8M 2s\n", - "498750K .......... .......... .......... .......... .......... 83% 54.3M 2s\n", - "498800K .......... .......... .......... .......... .......... 83% 24.0M 2s\n", - "498850K .......... .......... .......... .......... .......... 83% 54.4M 2s\n", - "498900K .......... .......... .......... .......... .......... 83% 4.16M 2s\n", - "498950K .......... .......... .......... .......... .......... 83% 71.0M 2s\n", - "499000K .......... .......... .......... .......... .......... 83% 63.2M 2s\n", - "499050K .......... .......... .......... .......... .......... 83% 17.5M 2s\n", - "499100K .......... .......... .......... .......... .......... 83% 42.7M 2s\n", - "499150K .......... .......... .......... .......... .......... 83% 63.1M 2s\n", - "499200K .......... .......... .......... .......... .......... 83% 4.45M 2s\n", - "499250K .......... .......... .......... .......... .......... 83% 58.8M 2s\n", - "499300K .......... .......... .......... .......... .......... 83% 75.5M 2s\n", - "499350K .......... .......... .......... .......... .......... 83% 68.0M 2s\n", - "499400K .......... .......... .......... .......... .......... 83% 64.2M 2s\n", - "499450K .......... .......... .......... .......... .......... 83% 27.4M 2s\n", - "499500K .......... .......... .......... .......... .......... 83% 54.3M 2s\n", - "499550K .......... .......... .......... .......... .......... 84% 73.7M 2s\n", - "499600K .......... .......... .......... .......... .......... 84% 18.2M 2s\n", - "499650K .......... .......... .......... .......... .......... 84% 49.7M 2s\n", - "499700K .......... .......... .......... .......... .......... 84% 64.9M 2s\n", - "499750K .......... .......... .......... .......... .......... 84% 74.6M 2s\n", - "499800K .......... .......... .......... .......... .......... 84% 17.8M 2s\n", - "499850K .......... .......... .......... .......... .......... 84% 52.6M 2s\n", - "499900K .......... .......... .......... .......... .......... 84% 63.8M 2s\n", - "499950K .......... .......... .......... .......... .......... 84% 19.8M 2s\n", - "500000K .......... .......... .......... .......... .......... 84% 47.2M 2s\n", - "500050K .......... .......... .......... .......... .......... 84% 52.3M 2s\n", - "500100K .......... .......... .......... .......... .......... 84% 23.4M 2s\n", - "500150K .......... .......... .......... .......... .......... 84% 30.4M 2s\n", - "500200K .......... .......... .......... .......... .......... 84% 49.5M 2s\n", - "500250K .......... .......... .......... .......... .......... 84% 68.9M 2s\n", - "500300K .......... .......... .......... .......... .......... 84% 17.6M 2s\n", - "500350K .......... .......... .......... .......... .......... 84% 49.9M 2s\n", - "500400K .......... .......... .......... .......... .......... 84% 62.9M 2s\n", - "500450K .......... .......... .......... .......... .......... 84% 26.4M 2s\n", - "500500K .......... .......... .......... .......... .......... 84% 48.0M 2s\n", - "500550K .......... .......... .......... .......... .......... 84% 58.7M 2s\n", - "500600K .......... .......... .......... .......... .......... 84% 56.0M 2s\n", - "500650K .......... .......... .......... .......... .......... 84% 22.8M 2s\n", - "500700K .......... .......... .......... .......... .......... 84% 53.2M 2s\n", - "500750K .......... .......... .......... .......... .......... 84% 60.7M 2s\n", - "500800K .......... .......... .......... .......... .......... 84% 34.7M 2s\n", - "500850K .......... .......... .......... .......... .......... 84% 15.4M 2s\n", - "500900K .......... .......... .......... .......... .......... 84% 4.27M 2s\n", - "500950K .......... .......... .......... .......... .......... 84% 70.7M 2s\n", - "501000K .......... .......... .......... .......... .......... 84% 54.5M 2s\n", - "501050K .......... .......... .......... .......... .......... 84% 62.3M 2s\n", - "501100K .......... .......... .......... .......... .......... 84% 70.4M 2s\n", - "501150K .......... .......... .......... .......... .......... 84% 70.4M 2s\n", - "501200K .......... .......... .......... .......... .......... 84% 35.7M 2s\n", - "501250K .......... .......... .......... .......... .......... 84% 53.9M 2s\n", - "501300K .......... .......... .......... .......... .......... 84% 78.3M 2s\n", - "501350K .......... .......... .......... .......... .......... 84% 22.3M 2s\n", - "501400K .......... .......... .......... .......... .......... 84% 44.6M 2s\n", - "501450K .......... .......... .......... .......... .......... 84% 60.8M 2s\n", - "501500K .......... .......... .......... .......... .......... 84% 78.5M 2s\n", - "501550K .......... .......... .......... .......... .......... 84% 18.0M 2s\n", - "501600K .......... .......... .......... .......... .......... 84% 56.4M 2s\n", - "501650K .......... .......... .......... .......... .......... 84% 78.1M 2s\n", - "501700K .......... .......... .......... .......... .......... 84% 79.8M 2s\n", - "501750K .......... .......... .......... .......... .......... 84% 14.2M 2s\n", - "501800K .......... .......... .......... .......... .......... 84% 61.5M 2s\n", - "501850K .......... .......... .......... .......... .......... 84% 72.0M 2s\n", - "501900K .......... .......... .......... .......... .......... 84% 17.1M 2s\n", - "501950K .......... .......... .......... .......... .......... 84% 64.7M 2s\n", - "502000K .......... .......... .......... .......... .......... 84% 54.9M 2s\n", - "502050K .......... .......... .......... .......... .......... 84% 72.5M 2s\n", - "502100K .......... .......... .......... .......... .......... 84% 19.4M 2s\n", - "502150K .......... .......... .......... .......... .......... 84% 54.3M 2s\n", - "502200K .......... .......... .......... .......... .......... 84% 53.5M 2s\n", - "502250K .......... .......... .......... .......... .......... 84% 62.8M 2s\n", - "502300K .......... .......... .......... .......... .......... 84% 18.0M 2s\n", - "502350K .......... .......... .......... .......... .......... 84% 45.0M 2s\n", - "502400K .......... .......... .......... .......... .......... 84% 55.3M 2s\n", - "502450K .......... .......... .......... .......... .......... 84% 32.0M 2s\n", - "502500K .......... .......... .......... .......... .......... 84% 41.9M 2s\n", - "502550K .......... .......... .......... .......... .......... 84% 48.4M 2s\n", - "502600K .......... .......... .......... .......... .......... 84% 51.6M 2s\n", - "502650K .......... .......... .......... .......... .......... 84% 31.9M 2s\n", - "502700K .......... .......... .......... .......... .......... 84% 45.4M 2s\n", - "502750K .......... .......... .......... .......... .......... 84% 56.5M 2s\n", - "502800K .......... .......... .......... .......... .......... 84% 55.3M 2s\n", - "502850K .......... .......... .......... .......... .......... 84% 28.9M 2s\n", - "502900K .......... .......... .......... .......... .......... 84% 38.7M 2s\n", - "502950K .......... .......... .......... .......... .......... 84% 60.9M 2s\n", - "503000K .......... .......... .......... .......... .......... 84% 49.3M 2s\n", - "503050K .......... .......... .......... .......... .......... 84% 27.4M 2s\n", - "503100K .......... .......... .......... .......... .......... 84% 46.4M 2s\n", - "503150K .......... .......... .......... .......... .......... 84% 63.7M 2s\n", - "503200K .......... .......... .......... .......... .......... 84% 57.0M 2s\n", - "503250K .......... .......... .......... .......... .......... 84% 24.1M 2s\n", - "503300K .......... .......... .......... .......... .......... 84% 45.1M 2s\n", - "503350K .......... .......... .......... .......... .......... 84% 61.5M 2s\n", - "503400K .......... .......... .......... .......... .......... 84% 29.8M 2s\n", - "503450K .......... .......... .......... .......... .......... 84% 40.4M 2s\n", - "503500K .......... .......... .......... .......... .......... 84% 45.5M 2s\n", - "503550K .......... .......... .......... .......... .......... 84% 63.3M 2s\n", - "503600K .......... .......... .......... .......... .......... 84% 33.7M 2s\n", - "503650K .......... .......... .......... .......... .......... 84% 50.4M 2s\n", - "503700K .......... .......... .......... .......... .......... 84% 50.8M 2s\n", - "503750K .......... .......... .......... .......... .......... 84% 53.4M 2s\n", - "503800K .......... .......... .......... .......... .......... 84% 22.3M 2s\n", - "503850K .......... .......... .......... .......... .......... 84% 49.6M 2s\n", - "503900K .......... .......... .......... .......... .......... 84% 55.5M 2s\n", - "503950K .......... .......... .......... .......... .......... 84% 56.8M 2s\n", - "504000K .......... .......... .......... .......... .......... 84% 27.7M 2s\n", - "504050K .......... .......... .......... .......... .......... 84% 38.7M 2s\n", - "504100K .......... .......... .......... .......... .......... 84% 51.3M 2s\n", - "504150K .......... .......... .......... .......... .......... 84% 65.0M 2s\n", - "504200K .......... .......... .......... .......... .......... 84% 27.6M 2s\n", - "504250K .......... .......... .......... .......... .......... 84% 49.2M 2s\n", - "504300K .......... .......... .......... .......... .......... 84% 49.1M 2s\n", - "504350K .......... .......... .......... .......... .......... 84% 60.3M 2s\n", - "504400K .......... .......... .......... .......... .......... 84% 34.4M 2s\n", - "504450K .......... .......... .......... .......... .......... 84% 38.9M 2s\n", - "504500K .......... .......... .......... .......... .......... 84% 54.7M 2s\n", - "504550K .......... .......... .......... .......... .......... 84% 67.8M 2s\n", - "504600K .......... .......... .......... .......... .......... 84% 24.2M 2s\n", - "504650K .......... .......... .......... .......... .......... 84% 48.4M 2s\n", - "504700K .......... .......... .......... .......... .......... 84% 53.4M 2s\n", - "504750K .......... .......... .......... .......... .......... 84% 66.3M 2s\n", - "504800K .......... .......... .......... .......... .......... 84% 37.1M 2s\n", - "504850K .......... .......... .......... .......... .......... 84% 35.0M 2s\n", - "504900K .......... .......... .......... .......... .......... 84% 55.5M 2s\n", - "504950K .......... .......... .......... .......... .......... 84% 72.2M 2s\n", - "505000K .......... .......... .......... .......... .......... 84% 31.1M 2s\n", - "505050K .......... .......... .......... .......... .......... 84% 38.8M 2s\n", - "505100K .......... .......... .......... .......... .......... 84% 49.9M 2s\n", - "505150K .......... .......... .......... .......... .......... 84% 60.1M 2s\n", - "505200K .......... .......... .......... .......... .......... 84% 24.1M 2s\n", - "505250K .......... .......... .......... .......... .......... 84% 35.6M 2s\n", - "505300K .......... .......... .......... .......... .......... 84% 63.7M 2s\n", - "505350K .......... .......... .......... .......... .......... 84% 52.1M 2s\n", - "505400K .......... .......... .......... .......... .......... 84% 36.8M 2s\n", - "505450K .......... .......... .......... .......... .......... 84% 41.0M 2s\n", - "505500K .......... .......... .......... .......... .......... 85% 47.4M 2s\n", - "505550K .......... .......... .......... .......... .......... 85% 59.4M 2s\n", - "505600K .......... .......... .......... .......... .......... 85% 31.6M 2s\n", - "505650K .......... .......... .......... .......... .......... 85% 35.9M 2s\n", - "505700K .......... .......... .......... .......... .......... 85% 46.3M 2s\n", - "505750K .......... .......... .......... .......... .......... 85% 52.0M 2s\n", - "505800K .......... .......... .......... .......... .......... 85% 37.9M 2s\n", - "505850K .......... .......... .......... .......... .......... 85% 39.6M 2s\n", - "505900K .......... .......... .......... .......... .......... 85% 36.8M 2s\n", - "505950K .......... .......... .......... .......... .......... 85% 31.1M 2s\n", - "506000K .......... .......... .......... .......... .......... 85% 28.2M 2s\n", - "506050K .......... .......... .......... .......... .......... 85% 33.3M 2s\n", - "506100K .......... .......... .......... .......... .......... 85% 32.8M 2s\n", - "506150K .......... .......... .......... .......... .......... 85% 35.7M 2s\n", - "506200K .......... .......... .......... .......... .......... 85% 41.6M 2s\n", - "506250K .......... .......... .......... .......... .......... 85% 52.5M 2s\n", - "506300K .......... .......... .......... .......... .......... 85% 38.6M 2s\n", - "506350K .......... .......... .......... .......... .......... 85% 41.3M 2s\n", - "506400K .......... .......... .......... .......... .......... 85% 6.98M 2s\n", - "506450K .......... .......... .......... .......... .......... 85% 69.8M 2s\n", - "506500K .......... .......... .......... .......... .......... 85% 53.2M 2s\n", - "506550K .......... .......... .......... .......... .......... 85% 58.7M 2s\n", - "506600K .......... .......... .......... .......... .......... 85% 58.4M 2s\n", - "506650K .......... .......... .......... .......... .......... 85% 63.9M 2s\n", - "506700K .......... .......... .......... .......... .......... 85% 51.9M 2s\n", - "506750K .......... .......... .......... .......... .......... 85% 36.7M 2s\n", - "506800K .......... .......... .......... .......... .......... 85% 33.2M 2s\n", - "506850K .......... .......... .......... .......... .......... 85% 37.7M 2s\n", - "506900K .......... .......... .......... .......... .......... 85% 36.9M 2s\n", - "506950K .......... .......... .......... .......... .......... 85% 61.3M 2s\n", - "507000K .......... .......... .......... .......... .......... 85% 46.6M 2s\n", - "507050K .......... .......... .......... .......... .......... 85% 58.6M 2s\n", - "507100K .......... .......... .......... .......... .......... 85% 54.2M 2s\n", - "507150K .......... .......... .......... .......... .......... 85% 40.7M 2s\n", - "507200K .......... .......... .......... .......... .......... 85% 52.1M 2s\n", - "507250K .......... .......... .......... .......... .......... 85% 55.3M 2s\n", - "507300K .......... .......... .......... .......... .......... 85% 35.8M 2s\n", - "507350K .......... .......... .......... .......... .......... 85% 45.7M 2s\n", - "507400K .......... .......... .......... .......... .......... 85% 46.2M 2s\n", - "507450K .......... .......... .......... .......... .......... 85% 58.8M 2s\n", - "507500K .......... .......... .......... .......... .......... 85% 68.2M 2s\n", - "507550K .......... .......... .......... .......... .......... 85% 52.9M 2s\n", - "507600K .......... .......... .......... .......... .......... 85% 43.9M 2s\n", - "507650K .......... .......... .......... .......... .......... 85% 49.0M 2s\n", - "507700K .......... .......... .......... .......... .......... 85% 66.1M 2s\n", - "507750K .......... .......... .......... .......... .......... 85% 53.5M 2s\n", - "507800K .......... .......... .......... .......... .......... 85% 32.2M 2s\n", - "507850K .......... .......... .......... .......... .......... 85% 40.0M 2s\n", - "507900K .......... .......... .......... .......... .......... 85% 70.1M 2s\n", - "507950K .......... .......... .......... .......... .......... 85% 63.7M 2s\n", - "508000K .......... .......... .......... .......... .......... 85% 38.0M 2s\n", - "508050K .......... .......... .......... .......... .......... 85% 40.8M 2s\n", - "508100K .......... .......... .......... .......... .......... 85% 46.1M 2s\n", - "508150K .......... .......... .......... .......... .......... 85% 47.2M 2s\n", - "508200K .......... .......... .......... .......... .......... 85% 37.3M 2s\n", - "508250K .......... .......... .......... .......... .......... 85% 40.3M 2s\n", - "508300K .......... .......... .......... .......... .......... 85% 39.8M 2s\n", - "508350K .......... .......... .......... .......... .......... 85% 49.6M 2s\n", - "508400K .......... .......... .......... .......... .......... 85% 39.3M 2s\n", - "508450K .......... .......... .......... .......... .......... 85% 61.5M 2s\n", - "508500K .......... .......... .......... .......... .......... 85% 48.6M 2s\n", - "508550K .......... .......... .......... .......... .......... 85% 43.3M 2s\n", - "508600K .......... .......... .......... .......... .......... 85% 48.0M 2s\n", - "508650K .......... .......... .......... .......... .......... 85% 46.9M 2s\n", - "508700K .......... .......... .......... .......... .......... 85% 29.9M 2s\n", - "508750K .......... .......... .......... .......... .......... 85% 43.1M 2s\n", - "508800K .......... .......... .......... .......... .......... 85% 48.4M 2s\n", - "508850K .......... .......... .......... .......... .......... 85% 61.9M 2s\n", - "508900K .......... .......... .......... .......... .......... 85% 68.7M 2s\n", - "508950K .......... .......... .......... .......... .......... 85% 47.8M 2s\n", - "509000K .......... .......... .......... .......... .......... 85% 38.7M 2s\n", - "509050K .......... .......... .......... .......... .......... 85% 59.8M 2s\n", - "509100K .......... .......... .......... .......... .......... 85% 60.6M 2s\n", - "509150K .......... .......... .......... .......... .......... 85% 62.4M 2s\n", - "509200K .......... .......... .......... .......... .......... 85% 32.6M 2s\n", - "509250K .......... .......... .......... .......... .......... 85% 43.8M 2s\n", - "509300K .......... .......... .......... .......... .......... 85% 27.2M 2s\n", - "509350K .......... .......... .......... .......... .......... 85% 60.0M 2s\n", - "509400K .......... .......... .......... .......... .......... 85% 22.9M 2s\n", - "509450K .......... .......... .......... .......... .......... 85% 42.2M 2s\n", - "509500K .......... .......... .......... .......... .......... 85% 52.9M 2s\n", - "509550K .......... .......... .......... .......... .......... 85% 64.9M 2s\n", - "509600K .......... .......... .......... .......... .......... 85% 16.0M 2s\n", - "509650K .......... .......... .......... .......... .......... 85% 48.6M 2s\n", - "509700K .......... .......... .......... .......... .......... 85% 51.4M 2s\n", - "509750K .......... .......... .......... .......... .......... 85% 65.5M 2s\n", - "509800K .......... .......... .......... .......... .......... 85% 53.3M 2s\n", - "509850K .......... .......... .......... .......... .......... 85% 13.4M 2s\n", - "509900K .......... .......... .......... .......... .......... 85% 41.9M 2s\n", - "509950K .......... .......... .......... .......... .......... 85% 53.7M 2s\n", - "510000K .......... .......... .......... .......... .......... 85% 59.1M 2s\n", - "510050K .......... .......... .......... .......... .......... 85% 38.8M 2s\n", - "510100K .......... .......... .......... .......... .......... 85% 41.1M 2s\n", - "510150K .......... .......... .......... .......... .......... 85% 50.4M 2s\n", - "510200K .......... .......... .......... .......... .......... 85% 54.6M 2s\n", - "510250K .......... .......... .......... .......... .......... 85% 35.8M 2s\n", - "510300K .......... .......... .......... .......... .......... 85% 52.3M 2s\n", - "510350K .......... .......... .......... .......... .......... 85% 46.1M 2s\n", - "510400K .......... .......... .......... .......... .......... 85% 40.5M 2s\n", - "510450K .......... .......... .......... .......... .......... 85% 49.4M 2s\n", - "510500K .......... .......... .......... .......... .......... 85% 3.71M 2s\n", - "510550K .......... .......... .......... .......... .......... 85% 57.9M 2s\n", - "510600K .......... .......... .......... .......... .......... 85% 46.8M 2s\n", - "510650K .......... .......... .......... .......... .......... 85% 66.7M 2s\n", - "510700K .......... .......... .......... .......... .......... 85% 68.3M 2s\n", - "510750K .......... .......... .......... .......... .......... 85% 31.0M 2s\n", - "510800K .......... .......... .......... .......... .......... 85% 41.9M 2s\n", - "510850K .......... .......... .......... .......... .......... 85% 65.0M 2s\n", - "510900K .......... .......... .......... .......... .......... 85% 59.5M 2s\n", - "510950K .......... .......... .......... .......... .......... 85% 57.0M 2s\n", - "511000K .......... .......... .......... .......... .......... 85% 35.9M 2s\n", - "511050K .......... .......... .......... .......... .......... 85% 52.1M 2s\n", - "511100K .......... .......... .......... .......... .......... 85% 66.4M 2s\n", - "511150K .......... .......... .......... .......... .......... 85% 59.9M 2s\n", - "511200K .......... .......... .......... .......... .......... 85% 26.1M 2s\n", - "511250K .......... .......... .......... .......... .......... 85% 62.9M 2s\n", - "511300K .......... .......... .......... .......... .......... 85% 52.5M 2s\n", - "511350K .......... .......... .......... .......... .......... 85% 60.8M 2s\n", - "511400K .......... .......... .......... .......... .......... 85% 28.6M 2s\n", - "511450K .......... .......... .......... .......... .......... 86% 47.2M 2s\n", - "511500K .......... .......... .......... .......... .......... 86% 55.9M 2s\n", - "511550K .......... .......... .......... .......... .......... 86% 56.7M 2s\n", - "511600K .......... .......... .......... .......... .......... 86% 51.8M 2s\n", - "511650K .......... .......... .......... .......... .......... 86% 58.1M 2s\n", - "511700K .......... .......... .......... .......... .......... 86% 49.3M 2s\n", - "511750K .......... .......... .......... .......... .......... 86% 57.5M 2s\n", - "511800K .......... .......... .......... .......... .......... 86% 42.4M 2s\n", - "511850K .......... .......... .......... .......... .......... 86% 47.7M 2s\n", - "511900K .......... .......... .......... .......... .......... 86% 44.3M 2s\n", - "511950K .......... .......... .......... .......... .......... 86% 45.1M 2s\n", - "512000K .......... .......... .......... .......... .......... 86% 60.0M 2s\n", - "512050K .......... .......... .......... .......... .......... 86% 55.6M 2s\n", - "512100K .......... .......... .......... .......... .......... 86% 39.6M 2s\n", - "512150K .......... .......... .......... .......... .......... 86% 45.3M 2s\n", - "512200K .......... .......... .......... .......... .......... 86% 33.9M 2s\n", - "512250K .......... .......... .......... .......... .......... 86% 58.1M 2s\n", - "512300K .......... .......... .......... .......... .......... 86% 65.1M 2s\n", - "512350K .......... .......... .......... .......... .......... 86% 48.7M 2s\n", - "512400K .......... .......... .......... .......... .......... 86% 49.5M 2s\n", - "512450K .......... .......... .......... .......... .......... 86% 61.1M 2s\n", - "512500K .......... .......... .......... .......... .......... 86% 69.7M 2s\n", - "512550K .......... .......... .......... .......... .......... 86% 62.0M 2s\n", - "512600K .......... .......... .......... .......... .......... 86% 25.7M 2s\n", - "512650K .......... .......... .......... .......... .......... 86% 44.2M 2s\n", - "512700K .......... .......... .......... .......... .......... 86% 52.6M 2s\n", - "512750K .......... .......... .......... .......... .......... 86% 40.7M 2s\n", - "512800K .......... .......... .......... .......... .......... 86% 28.3M 2s\n", - "512850K .......... .......... .......... .......... .......... 86% 35.0M 2s\n", - "512900K .......... .......... .......... .......... .......... 86% 45.9M 2s\n", - "512950K .......... .......... .......... .......... .......... 86% 3.86M 2s\n", - "513000K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", - "513050K .......... .......... .......... .......... .......... 86% 45.4M 2s\n", - "513100K .......... .......... .......... .......... .......... 86% 35.9M 2s\n", - "513150K .......... .......... .......... .......... .......... 86% 41.3M 2s\n", - "513200K .......... .......... .......... .......... .......... 86% 36.1M 2s\n", - "513250K .......... .......... .......... .......... .......... 86% 62.1M 2s\n", - "513300K .......... .......... .......... .......... .......... 86% 63.7M 2s\n", - "513350K .......... .......... .......... .......... .......... 86% 67.6M 2s\n", - "513400K .......... .......... .......... .......... .......... 86% 43.1M 2s\n", - "513450K .......... .......... .......... .......... .......... 86% 46.1M 2s\n", - "513500K .......... .......... .......... .......... .......... 86% 47.0M 2s\n", - "513550K .......... .......... .......... .......... .......... 86% 64.8M 2s\n", - "513600K .......... .......... .......... .......... .......... 86% 58.4M 2s\n", - "513650K .......... .......... .......... .......... .......... 86% 35.7M 2s\n", - "513700K .......... .......... .......... .......... .......... 86% 46.2M 2s\n", - "513750K .......... .......... .......... .......... .......... 86% 63.3M 2s\n", - "513800K .......... .......... .......... .......... .......... 86% 52.6M 2s\n", - "513850K .......... .......... .......... .......... .......... 86% 56.3M 2s\n", - "513900K .......... .......... .......... .......... .......... 86% 50.2M 2s\n", - "513950K .......... .......... .......... .......... .......... 86% 55.2M 2s\n", - "514000K .......... .......... .......... .......... .......... 86% 47.8M 2s\n", - "514050K .......... .......... .......... .......... .......... 86% 62.3M 2s\n", - "514100K .......... .......... .......... .......... .......... 86% 41.8M 2s\n", - "514150K .......... .......... .......... .......... .......... 86% 47.8M 2s\n", - "514200K .......... .......... .......... .......... .......... 86% 36.4M 2s\n", - "514250K .......... .......... .......... .......... .......... 86% 59.0M 2s\n", - "514300K .......... .......... .......... .......... .......... 86% 50.6M 2s\n", - "514350K .......... .......... .......... .......... .......... 86% 39.4M 2s\n", - "514400K .......... .......... .......... .......... .......... 86% 38.0M 2s\n", - "514450K .......... .......... .......... .......... .......... 86% 47.2M 2s\n", - "514500K .......... .......... .......... .......... .......... 86% 52.8M 2s\n", - "514550K .......... .......... .......... .......... .......... 86% 36.7M 2s\n", - "514600K .......... .......... .......... .......... .......... 86% 32.3M 2s\n", - "514650K .......... .......... .......... .......... .......... 86% 75.0M 2s\n", - "514700K .......... .......... .......... .......... .......... 86% 56.1M 2s\n", - "514750K .......... .......... .......... .......... .......... 86% 39.5M 2s\n", - "514800K .......... .......... .......... .......... .......... 86% 34.6M 2s\n", - "514850K .......... .......... .......... .......... .......... 86% 46.3M 2s\n", - "514900K .......... .......... .......... .......... .......... 86% 39.9M 2s\n", - "514950K .......... .......... .......... .......... .......... 86% 39.0M 2s\n", - "515000K .......... .......... .......... .......... .......... 86% 40.1M 2s\n", - "515050K .......... .......... .......... .......... .......... 86% 56.3M 2s\n", - "515100K .......... .......... .......... .......... .......... 86% 58.3M 2s\n", - "515150K .......... .......... .......... .......... .......... 86% 69.4M 2s\n", - "515200K .......... .......... .......... .......... .......... 86% 45.2M 2s\n", - "515250K .......... .......... .......... .......... .......... 86% 53.5M 2s\n", - "515300K .......... .......... .......... .......... .......... 86% 50.8M 2s\n", - "515350K .......... .......... .......... .......... .......... 86% 61.0M 2s\n", - "515400K .......... .......... .......... .......... .......... 86% 52.0M 2s\n", - "515450K .......... .......... .......... .......... .......... 86% 44.9M 2s\n", - "515500K .......... .......... .......... .......... .......... 86% 54.2M 2s\n", - "515550K .......... .......... .......... .......... .......... 86% 55.5M 2s\n", - "515600K .......... .......... .......... .......... .......... 86% 52.9M 2s\n", - "515650K .......... .......... .......... .......... .......... 86% 71.7M 2s\n", - "515700K .......... .......... .......... .......... .......... 86% 43.6M 2s\n", - "515750K .......... .......... .......... .......... .......... 86% 45.1M 2s\n", - "515800K .......... .......... .......... .......... .......... 86% 45.6M 2s\n", - "515850K .......... .......... .......... .......... .......... 86% 62.8M 2s\n", - "515900K .......... .......... .......... .......... .......... 86% 61.7M 2s\n", - "515950K .......... .......... .......... .......... .......... 86% 55.4M 2s\n", - "516000K .......... .......... .......... .......... .......... 86% 45.4M 2s\n", - "516050K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", - "516100K .......... .......... .......... .......... .......... 86% 66.5M 2s\n", - "516150K .......... .......... .......... .......... .......... 86% 69.5M 2s\n", - "516200K .......... .......... .......... .......... .......... 86% 52.1M 2s\n", - "516250K .......... .......... .......... .......... .......... 86% 53.9M 2s\n", - "516300K .......... .......... .......... .......... .......... 86% 44.7M 2s\n", - "516350K .......... .......... .......... .......... .......... 86% 44.7M 2s\n", - "516400K .......... .......... .......... .......... .......... 86% 65.6M 2s\n", - "516450K .......... .......... .......... .......... .......... 86% 58.2M 2s\n", - "516500K .......... .......... .......... .......... .......... 86% 53.1M 2s\n", - "516550K .......... .......... .......... .......... .......... 86% 40.5M 2s\n", - "516600K .......... .......... .......... .......... .......... 86% 56.8M 2s\n", - "516650K .......... .......... .......... .......... .......... 86% 58.9M 2s\n", - "516700K .......... .......... .......... .......... .......... 86% 56.9M 2s\n", - "516750K .......... .......... .......... .......... .......... 86% 55.6M 2s\n", - "516800K .......... .......... .......... .......... .......... 86% 37.7M 2s\n", - "516850K .......... .......... .......... .......... .......... 86% 62.5M 2s\n", - "516900K .......... .......... .......... .......... .......... 86% 61.5M 2s\n", - "516950K .......... .......... .......... .......... .......... 86% 54.2M 2s\n", - "517000K .......... .......... .......... .......... .......... 86% 3.87M 2s\n", - "517050K .......... .......... .......... .......... .......... 86% 47.0M 2s\n", - "517100K .......... .......... .......... .......... .......... 86% 65.7M 2s\n", - "517150K .......... .......... .......... .......... .......... 86% 69.5M 2s\n", - "517200K .......... .......... .......... .......... .......... 86% 61.3M 2s\n", - "517250K .......... .......... .......... .......... .......... 86% 51.4M 2s\n", - "517300K .......... .......... .......... .......... .......... 86% 45.6M 2s\n", - "517350K .......... .......... .......... .......... .......... 86% 61.9M 2s\n", - "517400K .......... .......... .......... .......... .......... 87% 53.6M 2s\n", - "517450K .......... .......... .......... .......... .......... 87% 67.7M 2s\n", - "517500K .......... .......... .......... .......... .......... 87% 68.3M 2s\n", - "517550K .......... .......... .......... .......... .......... 87% 54.0M 2s\n", - "517600K .......... .......... .......... .......... .......... 87% 58.0M 2s\n", - "517650K .......... .......... .......... .......... .......... 87% 55.7M 2s\n", - "517700K .......... .......... .......... .......... .......... 87% 61.0M 2s\n", - "517750K .......... .......... .......... .......... .......... 87% 58.2M 2s\n", - "517800K .......... .......... .......... .......... .......... 87% 48.0M 2s\n", - "517850K .......... .......... .......... .......... .......... 87% 62.1M 2s\n", - "517900K .......... .......... .......... .......... .......... 87% 40.1M 2s\n", - "517950K .......... .......... .......... .......... .......... 87% 63.5M 2s\n", - "518000K .......... .......... .......... .......... .......... 87% 50.7M 2s\n", - "518050K .......... .......... .......... .......... .......... 87% 56.6M 2s\n", - "518100K .......... .......... .......... .......... .......... 87% 48.5M 2s\n", - "518150K .......... .......... .......... .......... .......... 87% 42.4M 2s\n", - "518200K .......... .......... .......... .......... .......... 87% 50.7M 2s\n", - "518250K .......... .......... .......... .......... .......... 87% 55.9M 2s\n", - "518300K .......... .......... .......... .......... .......... 87% 53.3M 2s\n", - "518350K .......... .......... .......... .......... .......... 87% 39.2M 2s\n", - "518400K .......... .......... .......... .......... .......... 87% 48.8M 2s\n", - "518450K .......... .......... .......... .......... .......... 87% 57.9M 2s\n", - "518500K .......... .......... .......... .......... .......... 87% 56.8M 2s\n", - "518550K .......... .......... .......... .......... .......... 87% 50.6M 2s\n", - "518600K .......... .......... .......... .......... .......... 87% 32.6M 2s\n", - "518650K .......... .......... .......... .......... .......... 87% 66.5M 2s\n", - "518700K .......... .......... .......... .......... .......... 87% 51.3M 2s\n", - "518750K .......... .......... .......... .......... .......... 87% 26.5M 2s\n", - "518800K .......... .......... .......... .......... .......... 87% 32.0M 2s\n", - "518850K .......... .......... .......... .......... .......... 87% 52.4M 2s\n", - "518900K .......... .......... .......... .......... .......... 87% 68.2M 2s\n", - "518950K .......... .......... .......... .......... .......... 87% 27.8M 2s\n", - "519000K .......... .......... .......... .......... .......... 87% 40.8M 2s\n", - "519050K .......... .......... .......... .......... .......... 87% 55.6M 2s\n", - "519100K .......... .......... .......... .......... .......... 87% 22.1M 2s\n", - "519150K .......... .......... .......... .......... .......... 87% 31.0M 2s\n", - "519200K .......... .......... .......... .......... .......... 87% 49.9M 2s\n", - "519250K .......... .......... .......... .......... .......... 87% 49.2M 2s\n", - "519300K .......... .......... .......... .......... .......... 87% 32.2M 2s\n", - "519350K .......... .......... .......... .......... .......... 87% 30.5M 2s\n", - "519400K .......... .......... .......... .......... .......... 87% 33.5M 2s\n", - "519450K .......... .......... .......... .......... .......... 87% 39.3M 2s\n", - "519500K .......... .......... .......... .......... .......... 87% 28.8M 2s\n", - "519550K .......... .......... .......... .......... .......... 87% 41.4M 2s\n", - "519600K .......... .......... .......... .......... .......... 87% 62.2M 2s\n", - "519650K .......... .......... .......... .......... .......... 87% 38.0M 2s\n", - "519700K .......... .......... .......... .......... .......... 87% 36.9M 2s\n", - "519750K .......... .......... .......... .......... .......... 87% 37.5M 2s\n", - "519800K .......... .......... .......... .......... .......... 87% 24.9M 2s\n", - "519850K .......... .......... .......... .......... .......... 87% 35.6M 2s\n", - "519900K .......... .......... .......... .......... .......... 87% 48.1M 2s\n", - "519950K .......... .......... .......... .......... .......... 87% 48.0M 2s\n", - "520000K .......... .......... .......... .......... .......... 87% 33.6M 2s\n", - "520050K .......... .......... .......... .......... .......... 87% 34.6M 2s\n", - "520100K .......... .......... .......... .......... .......... 87% 62.4M 2s\n", - "520150K .......... .......... .......... .......... .......... 87% 42.9M 2s\n", - "520200K .......... .......... .......... .......... .......... 87% 37.6M 2s\n", - "520250K .......... .......... .......... .......... .......... 87% 35.9M 2s\n", - "520300K .......... .......... .......... .......... .......... 87% 42.8M 2s\n", - "520350K .......... .......... .......... .......... .......... 87% 52.2M 2s\n", - "520400K .......... .......... .......... .......... .......... 87% 40.9M 2s\n", - "520450K .......... .......... .......... .......... .......... 87% 33.3M 2s\n", - "520500K .......... .......... .......... .......... .......... 87% 45.8M 2s\n", - "520550K .......... .......... .......... .......... .......... 87% 56.5M 2s\n", - "520600K .......... .......... .......... .......... .......... 87% 29.7M 2s\n", - "520650K .......... .......... .......... .......... .......... 87% 17.1M 2s\n", - "520700K .......... .......... .......... .......... .......... 87% 24.6M 2s\n", - "520750K .......... .......... .......... .......... .......... 87% 22.9M 2s\n", - "520800K .......... .......... .......... .......... .......... 87% 40.0M 2s\n", - "520850K .......... .......... .......... .......... .......... 87% 45.8M 2s\n", - "520900K .......... .......... .......... .......... .......... 87% 52.3M 2s\n", - "520950K .......... .......... .......... .......... .......... 87% 39.2M 2s\n", - "521000K .......... .......... .......... .......... .......... 87% 37.7M 2s\n", - "521050K .......... .......... .......... .......... .......... 87% 63.1M 2s\n", - "521100K .......... .......... .......... .......... .......... 87% 51.7M 2s\n", - "521150K .......... .......... .......... .......... .......... 87% 34.3M 2s\n", - "521200K .......... .......... .......... .......... .......... 87% 38.6M 2s\n", - "521250K .......... .......... .......... .......... .......... 87% 44.2M 2s\n", - "521300K .......... .......... .......... .......... .......... 87% 23.5M 2s\n", - "521350K .......... .......... .......... .......... .......... 87% 25.8M 2s\n", - "521400K .......... .......... .......... .......... .......... 87% 26.7M 2s\n", - "521450K .......... .......... .......... .......... .......... 87% 31.6M 2s\n", - "521500K .......... .......... .......... .......... .......... 87% 30.7M 2s\n", - "521550K .......... .......... .......... .......... .......... 87% 36.0M 2s\n", - "521600K .......... .......... .......... .......... .......... 87% 24.3M 2s\n", - "521650K .......... .......... .......... .......... .......... 87% 27.8M 2s\n", - "521700K .......... .......... .......... .......... .......... 87% 35.5M 2s\n", - "521750K .......... .......... .......... .......... .......... 87% 25.9M 2s\n", - "521800K .......... .......... .......... .......... .......... 87% 25.8M 2s\n", - "521850K .......... .......... .......... .......... .......... 87% 28.6M 2s\n", - "521900K .......... .......... .......... .......... .......... 87% 57.6M 2s\n", - "521950K .......... .......... .......... .......... .......... 87% 33.6M 2s\n", - "522000K .......... .......... .......... .......... .......... 87% 56.0M 2s\n", - "522050K .......... .......... .......... .......... .......... 87% 42.0M 2s\n", - "522100K .......... .......... .......... .......... .......... 87% 44.3M 2s\n", - "522150K .......... .......... .......... .......... .......... 87% 29.9M 2s\n", - "522200K .......... .......... .......... .......... .......... 87% 29.4M 2s\n", - "522250K .......... .......... .......... .......... .......... 87% 59.7M 2s\n", - "522300K .......... .......... .......... .......... .......... 87% 26.9M 2s\n", - "522350K .......... .......... .......... .......... .......... 87% 46.1M 2s\n", - "522400K .......... .......... .......... .......... .......... 87% 55.6M 2s\n", - "522450K .......... .......... .......... .......... .......... 87% 35.5M 2s\n", - "522500K .......... .......... .......... .......... .......... 87% 42.9M 2s\n", - "522550K .......... .......... .......... .......... .......... 87% 42.0M 2s\n", - "522600K .......... .......... .......... .......... .......... 87% 49.8M 2s\n", - "522650K .......... .......... .......... .......... .......... 87% 28.1M 2s\n", - "522700K .......... .......... .......... .......... .......... 87% 27.1M 2s\n", - "522750K .......... .......... .......... .......... .......... 87% 38.7M 2s\n", - "522800K .......... .......... .......... .......... .......... 87% 36.4M 2s\n", - "522850K .......... .......... .......... .......... .......... 87% 50.5M 2s\n", - "522900K .......... .......... .......... .......... .......... 87% 41.9M 2s\n", - "522950K .......... .......... .......... .......... .......... 87% 39.1M 2s\n", - "523000K .......... .......... .......... .......... .......... 87% 40.2M 2s\n", - "523050K .......... .......... .......... .......... .......... 87% 28.9M 2s\n", - "523100K .......... .......... .......... .......... .......... 87% 19.5M 2s\n", - "523150K .......... .......... .......... .......... .......... 87% 32.8M 2s\n", - "523200K .......... .......... .......... .......... .......... 87% 34.0M 2s\n", - "523250K .......... .......... .......... .......... .......... 87% 49.7M 2s\n", - "523300K .......... .......... .......... .......... .......... 87% 38.5M 2s\n", - "523350K .......... .......... .......... .......... .......... 88% 43.1M 2s\n", - "523400K .......... .......... .......... .......... .......... 88% 27.6M 2s\n", - "523450K .......... .......... .......... .......... .......... 88% 44.0M 2s\n", - "523500K .......... .......... .......... .......... .......... 88% 49.5M 2s\n", - "523550K .......... .......... .......... .......... .......... 88% 49.1M 2s\n", - "523600K .......... .......... .......... .......... .......... 88% 33.4M 2s\n", - "523650K .......... .......... .......... .......... .......... 88% 20.8M 2s\n", - "523700K .......... .......... .......... .......... .......... 88% 19.5M 2s\n", - "523750K .......... .......... .......... .......... .......... 88% 27.6M 2s\n", - "523800K .......... .......... .......... .......... .......... 88% 23.9M 2s\n", - "523850K .......... .......... .......... .......... .......... 88% 24.6M 2s\n", - "523900K .......... .......... .......... .......... .......... 88% 3.11M 2s\n", - "523950K .......... .......... .......... .......... .......... 88% 38.8M 2s\n", - "524000K .......... .......... .......... .......... .......... 88% 38.1M 2s\n", - "524050K .......... .......... .......... .......... .......... 88% 21.9M 2s\n", - "524100K .......... .......... .......... .......... .......... 88% 41.4M 2s\n", - "524150K .......... .......... .......... .......... .......... 88% 39.5M 2s\n", - "524200K .......... .......... .......... .......... .......... 88% 14.7M 2s\n", - "524250K .......... .......... .......... .......... .......... 88% 38.3M 2s\n", - "524300K .......... .......... .......... .......... .......... 88% 16.0M 2s\n", - "524350K .......... .......... .......... .......... .......... 88% 33.1M 2s\n", - "524400K .......... .......... .......... .......... .......... 88% 24.4M 2s\n", - "524450K .......... .......... .......... .......... .......... 88% 21.9M 2s\n", - "524500K .......... .......... .......... .......... .......... 88% 35.0M 2s\n", - "524550K .......... .......... .......... .......... .......... 88% 34.5M 2s\n", - "524600K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", - "524650K .......... .......... .......... .......... .......... 88% 33.8M 2s\n", - "524700K .......... .......... .......... .......... .......... 88% 15.9M 2s\n", - "524750K .......... .......... .......... .......... .......... 88% 30.9M 2s\n", - "524800K .......... .......... .......... .......... .......... 88% 20.2M 2s\n", - "524850K .......... .......... .......... .......... .......... 88% 48.5M 2s\n", - "524900K .......... .......... .......... .......... .......... 88% 56.7M 2s\n", - "524950K .......... .......... .......... .......... .......... 88% 66.6M 2s\n", - "525000K .......... .......... .......... .......... .......... 88% 49.1M 2s\n", - "525050K .......... .......... .......... .......... .......... 88% 40.4M 2s\n", - "525100K .......... .......... .......... .......... .......... 88% 40.8M 2s\n", - "525150K .......... .......... .......... .......... .......... 88% 63.7M 2s\n", - "525200K .......... .......... .......... .......... .......... 88% 10.9M 2s\n", - "525250K .......... .......... .......... .......... .......... 88% 66.0M 2s\n", - "525300K .......... .......... .......... .......... .......... 88% 67.1M 2s\n", - "525350K .......... .......... .......... .......... .......... 88% 69.6M 2s\n", - "525400K .......... .......... .......... .......... .......... 88% 56.3M 2s\n", - "525450K .......... .......... .......... .......... .......... 88% 66.3M 2s\n", - "525500K .......... .......... .......... .......... .......... 88% 32.8M 2s\n", - "525550K .......... .......... .......... .......... .......... 88% 60.1M 2s\n", - "525600K .......... .......... .......... .......... .......... 88% 52.9M 2s\n", - "525650K .......... .......... .......... .......... .......... 88% 63.7M 2s\n", - "525700K .......... .......... .......... .......... .......... 88% 54.6M 2s\n", - "525750K .......... .......... .......... .......... .......... 88% 3.84M 2s\n", - "525800K .......... .......... .......... .......... .......... 88% 55.4M 2s\n", - "525850K .......... .......... .......... .......... .......... 88% 69.5M 2s\n", - "525900K .......... .......... .......... .......... .......... 88% 64.2M 2s\n", - "525950K .......... .......... .......... .......... .......... 88% 67.3M 2s\n", - "526000K .......... .......... .......... .......... .......... 88% 66.6M 2s\n", - "526050K .......... .......... .......... .......... .......... 88% 38.3M 2s\n", - "526100K .......... .......... .......... .......... .......... 88% 48.5M 2s\n", - "526150K .......... .......... .......... .......... .......... 88% 69.3M 2s\n", - "526200K .......... .......... .......... .......... .......... 88% 58.6M 2s\n", - "526250K .......... .......... .......... .......... .......... 88% 66.5M 2s\n", - "526300K .......... .......... .......... .......... .......... 88% 41.2M 2s\n", - "526350K .......... .......... .......... .......... .......... 88% 43.2M 2s\n", - "526400K .......... .......... .......... .......... .......... 88% 57.2M 2s\n", - "526450K .......... .......... .......... .......... .......... 88% 57.4M 2s\n", - "526500K .......... .......... .......... .......... .......... 88% 58.8M 2s\n", - "526550K .......... .......... .......... .......... .......... 88% 33.2M 2s\n", - "526600K .......... .......... .......... .......... .......... 88% 50.5M 2s\n", - "526650K .......... .......... .......... .......... .......... 88% 48.1M 2s\n", - "526700K .......... .......... .......... .......... .......... 88% 55.0M 2s\n", - "526750K .......... .......... .......... .......... .......... 88% 52.4M 2s\n", - "526800K .......... .......... .......... .......... .......... 88% 47.5M 2s\n", - "526850K .......... .......... .......... .......... .......... 88% 65.1M 2s\n", - "526900K .......... .......... .......... .......... .......... 88% 69.2M 2s\n", - "526950K .......... .......... .......... .......... .......... 88% 57.7M 2s\n", - "527000K .......... .......... .......... .......... .......... 88% 53.4M 2s\n", - "527050K .......... .......... .......... .......... .......... 88% 26.0M 2s\n", - "527100K .......... .......... .......... .......... .......... 88% 35.9M 2s\n", - "527150K .......... .......... .......... .......... .......... 88% 70.0M 2s\n", - "527200K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", - "527250K .......... .......... .......... .......... .......... 88% 48.4M 2s\n", - "527300K .......... .......... .......... .......... .......... 88% 54.5M 2s\n", - "527350K .......... .......... .......... .......... .......... 88% 19.2M 2s\n", - "527400K .......... .......... .......... .......... .......... 88% 5.44M 2s\n", - "527450K .......... .......... .......... .......... .......... 88% 69.0M 2s\n", - "527500K .......... .......... .......... .......... .......... 88% 52.0M 2s\n", - "527550K .......... .......... .......... .......... .......... 88% 13.5M 2s\n", - "527600K .......... .......... .......... .......... .......... 88% 53.3M 2s\n", - "527650K .......... .......... .......... .......... .......... 88% 65.5M 2s\n", - "527700K .......... .......... .......... .......... .......... 88% 16.6M 2s\n", - "527750K .......... .......... .......... .......... .......... 88% 64.1M 2s\n", - "527800K .......... .......... .......... .......... .......... 88% 18.1M 2s\n", - "527850K .......... .......... .......... .......... .......... 88% 34.1M 2s\n", - "527900K .......... .......... .......... .......... .......... 88% 65.9M 2s\n", - "527950K .......... .......... .......... .......... .......... 88% 21.2M 2s\n", - "528000K .......... .......... .......... .......... .......... 88% 31.4M 2s\n", - "528050K .......... .......... .......... .......... .......... 88% 56.6M 2s\n", - "528100K .......... .......... .......... .......... .......... 88% 20.1M 2s\n", - "528150K .......... .......... .......... .......... .......... 88% 44.5M 2s\n", - "528200K .......... .......... .......... .......... .......... 88% 42.0M 2s\n", - "528250K .......... .......... .......... .......... .......... 88% 19.2M 2s\n", - "528300K .......... .......... .......... .......... .......... 88% 37.5M 2s\n", - "528350K .......... .......... .......... .......... .......... 88% 65.7M 2s\n", - "528400K .......... .......... .......... .......... .......... 88% 19.1M 2s\n", - "528450K .......... .......... .......... .......... .......... 88% 42.6M 2s\n", - "528500K .......... .......... .......... .......... .......... 88% 43.1M 2s\n", - "528550K .......... .......... .......... .......... .......... 88% 19.7M 2s\n", - "528600K .......... .......... .......... .......... .......... 88% 33.3M 2s\n", - "528650K .......... .......... .......... .......... .......... 88% 64.6M 2s\n", - "528700K .......... .......... .......... .......... .......... 88% 15.8M 2s\n", - "528750K .......... .......... .......... .......... .......... 88% 47.5M 2s\n", - "528800K .......... .......... .......... .......... .......... 88% 64.4M 2s\n", - "528850K .......... .......... .......... .......... .......... 88% 17.6M 2s\n", - "528900K .......... .......... .......... .......... .......... 88% 46.2M 2s\n", - "528950K .......... .......... .......... .......... .......... 88% 69.3M 2s\n", - "529000K .......... .......... .......... .......... .......... 88% 17.8M 2s\n", - "529050K .......... .......... .......... .......... .......... 88% 37.0M 2s\n", - "529100K .......... .......... .......... .......... .......... 88% 21.8M 2s\n", - "529150K .......... .......... .......... .......... .......... 88% 8.25M 2s\n", - "529200K .......... .......... .......... .......... .......... 88% 58.3M 2s\n", - "529250K .......... .......... .......... .......... .......... 88% 69.4M 2s\n", - "529300K .......... .......... .......... .......... .......... 89% 14.6M 2s\n", - "529350K .......... .......... .......... .......... .......... 89% 53.6M 2s\n", - "529400K .......... .......... .......... .......... .......... 89% 58.2M 2s\n", - "529450K .......... .......... .......... .......... .......... 89% 17.9M 2s\n", - "529500K .......... .......... .......... .......... .......... 89% 50.7M 2s\n", - "529550K .......... .......... .......... .......... .......... 89% 68.7M 2s\n", - "529600K .......... .......... .......... .......... .......... 89% 17.9M 2s\n", - "529650K .......... .......... .......... .......... .......... 89% 40.7M 2s\n", - "529700K .......... .......... .......... .......... .......... 89% 68.7M 2s\n", - "529750K .......... .......... .......... .......... .......... 89% 19.4M 2s\n", - "529800K .......... .......... .......... .......... .......... 89% 30.1M 2s\n", - "529850K .......... .......... .......... .......... .......... 89% 71.2M 2s\n", - "529900K .......... .......... .......... .......... .......... 89% 24.2M 2s\n", - "529950K .......... .......... .......... .......... .......... 89% 42.7M 2s\n", - "530000K .......... .......... .......... .......... .......... 89% 49.4M 2s\n", - "530050K .......... .......... .......... .......... .......... 89% 19.8M 2s\n", - "530100K .......... .......... .......... .......... .......... 89% 34.7M 2s\n", - "530150K .......... .......... .......... .......... .......... 89% 63.7M 2s\n", - "530200K .......... .......... .......... .......... .......... 89% 18.6M 2s\n", - "530250K .......... .......... .......... .......... .......... 89% 44.8M 2s\n", - "530300K .......... .......... .......... .......... .......... 89% 56.3M 2s\n", - "530350K .......... .......... .......... .......... .......... 89% 20.8M 2s\n", - "530400K .......... .......... .......... .......... .......... 89% 34.5M 2s\n", - "530450K .......... .......... .......... .......... .......... 89% 54.8M 2s\n", - "530500K .......... .......... .......... .......... .......... 89% 22.9M 2s\n", - "530550K .......... .......... .......... .......... .......... 89% 7.74M 2s\n", - "530600K .......... .......... .......... .......... .......... 89% 53.8M 2s\n", - "530650K .......... .......... .......... .......... .......... 89% 65.3M 2s\n", - "530700K .......... .......... .......... .......... .......... 89% 65.2M 2s\n", - "530750K .......... .......... .......... .......... .......... 89% 14.4M 2s\n", - "530800K .......... .......... .......... .......... .......... 89% 63.2M 2s\n", - "530850K .......... .......... .......... .......... .......... 89% 5.32M 2s\n", - "530900K .......... .......... .......... .......... .......... 89% 59.4M 2s\n", - "530950K .......... .......... .......... .......... .......... 89% 69.2M 2s\n", - "531000K .......... .......... .......... .......... .......... 89% 52.5M 2s\n", - "531050K .......... .......... .......... .......... .......... 89% 15.9M 2s\n", - "531100K .......... .......... .......... .......... .......... 89% 67.3M 2s\n", - "531150K .......... .......... .......... .......... .......... 89% 12.7M 2s\n", - "531200K .......... .......... .......... .......... .......... 89% 52.2M 2s\n", - "531250K .......... .......... .......... .......... .......... 89% 15.3M 2s\n", - "531300K .......... .......... .......... .......... .......... 89% 52.6M 2s\n", - "531350K .......... .......... .......... .......... .......... 89% 43.8M 2s\n", - "531400K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", - "531450K .......... .......... .......... .......... .......... 89% 67.8M 2s\n", - "531500K .......... .......... .......... .......... .......... 89% 13.2M 2s\n", - "531550K .......... .......... .......... .......... .......... 89% 67.0M 2s\n", - "531600K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", - "531650K .......... .......... .......... .......... .......... 89% 13.7M 2s\n", - "531700K .......... .......... .......... .......... .......... 89% 46.8M 2s\n", - "531750K .......... .......... .......... .......... .......... 89% 51.0M 2s\n", - "531800K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", - "531850K .......... .......... .......... .......... .......... 89% 46.3M 2s\n", - "531900K .......... .......... .......... .......... .......... 89% 57.1M 2s\n", - "531950K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", - "532000K .......... .......... .......... .......... .......... 89% 18.5M 2s\n", - "532050K .......... .......... .......... .......... .......... 89% 22.5M 2s\n", - "532100K .......... .......... .......... .......... .......... 89% 61.2M 2s\n", - "532150K .......... .......... .......... .......... .......... 89% 15.2M 2s\n", - "532200K .......... .......... .......... .......... .......... 89% 40.5M 2s\n", - "532250K .......... .......... .......... .......... .......... 89% 15.1M 2s\n", - "532300K .......... .......... .......... .......... .......... 89% 41.9M 2s\n", - "532350K .......... .......... .......... .......... .......... 89% 69.8M 2s\n", - "532400K .......... .......... .......... .......... .......... 89% 12.8M 2s\n", - "532450K .......... .......... .......... .......... .......... 89% 71.5M 2s\n", - "532500K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", - "532550K .......... .......... .......... .......... .......... 89% 30.6M 2s\n", - "532600K .......... .......... .......... .......... .......... 89% 15.8M 2s\n", - "532650K .......... .......... .......... .......... .......... 89% 36.2M 2s\n", - "532700K .......... .......... .......... .......... .......... 89% 16.3M 2s\n", - "532750K .......... .......... .......... .......... .......... 89% 38.5M 2s\n", - "532800K .......... .......... .......... .......... .......... 89% 16.3M 2s\n", - "532850K .......... .......... .......... .......... .......... 89% 48.0M 2s\n", - "532900K .......... .......... .......... .......... .......... 89% 43.2M 2s\n", - "532950K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", - "533000K .......... .......... .......... .......... .......... 89% 36.2M 2s\n", - "533050K .......... .......... .......... .......... .......... 89% 16.2M 2s\n", - "533100K .......... .......... .......... .......... .......... 89% 40.8M 2s\n", - "533150K .......... .......... .......... .......... .......... 89% 3.77M 2s\n", - "533200K .......... .......... .......... .......... .......... 89% 58.6M 2s\n", - "533250K .......... .......... .......... .......... .......... 89% 14.9M 2s\n", - "533300K .......... .......... .......... .......... .......... 89% 9.77M 2s\n", - "533350K .......... .......... .......... .......... .......... 89% 69.5M 2s\n", - "533400K .......... .......... .......... .......... .......... 89% 12.9M 2s\n", - "533450K .......... .......... .......... .......... .......... 89% 11.9M 2s\n", - "533500K .......... .......... .......... .......... .......... 89% 55.1M 2s\n", - "533550K .......... .......... .......... .......... .......... 89% 12.2M 2s\n", - "533600K .......... .......... .......... .......... .......... 89% 10.8M 2s\n", - "533650K .......... .......... .......... .......... .......... 89% 53.1M 2s\n", - "533700K .......... .......... .......... .......... .......... 89% 12.3M 2s\n", - "533750K .......... .......... .......... .......... .......... 89% 4.25M 2s\n", - "533800K .......... .......... .......... .......... .......... 89% 51.3M 2s\n", - "533850K .......... .......... .......... .......... .......... 89% 11.0M 2s\n", - "533900K .......... .......... .......... .......... .......... 89% 13.2M 2s\n", - "533950K .......... .......... .......... .......... .......... 89% 51.0M 2s\n", - "534000K .......... .......... .......... .......... .......... 89% 11.8M 2s\n", - "534050K .......... .......... .......... .......... .......... 89% 11.6M 2s\n", - "534100K .......... .......... .......... .......... .......... 89% 52.2M 2s\n", - "534150K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", - "534200K .......... .......... .......... .......... .......... 89% 11.6M 2s\n", - "534250K .......... .......... .......... .......... .......... 89% 29.3M 2s\n", - "534300K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", - "534350K .......... .......... .......... .......... .......... 89% 70.7M 2s\n", - "534400K .......... .......... .......... .......... .......... 89% 11.8M 2s\n", - "534450K .......... .......... .......... .......... .......... 89% 14.0M 2s\n", - "534500K .......... .......... .......... .......... .......... 89% 10.4M 2s\n", - "534550K .......... .......... .......... .......... .......... 89% 52.9M 2s\n", - "534600K .......... .......... .......... .......... .......... 89% 14.0M 2s\n", - "534650K .......... .......... .......... .......... .......... 89% 36.3M 2s\n", - "534700K .......... .......... .......... .......... .......... 89% 12.5M 2s\n", - "534750K .......... .......... .......... .......... .......... 89% 65.4M 2s\n", - "534800K .......... .......... .......... .......... .......... 89% 11.2M 2s\n", - "534850K .......... .......... .......... .......... .......... 89% 15.7M 2s\n", - "534900K .......... .......... .......... .......... .......... 89% 29.6M 2s\n", - "534950K .......... .......... .......... .......... .......... 89% 16.0M 2s\n", - "535000K .......... .......... .......... .......... .......... 89% 11.2M 2s\n", - "535050K .......... .......... .......... .......... .......... 89% 50.7M 2s\n", - "535100K .......... .......... .......... .......... .......... 89% 12.0M 2s\n", - "535150K .......... .......... .......... .......... .......... 89% 55.5M 2s\n", - "535200K .......... .......... .......... .......... .......... 89% 13.3M 2s\n", - "535250K .......... .......... .......... .......... .......... 90% 51.2M 2s\n", - "535300K .......... .......... .......... .......... .......... 90% 12.9M 2s\n", - "535350K .......... .......... .......... .......... .......... 90% 48.9M 2s\n", - "535400K .......... .......... .......... .......... .......... 90% 12.1M 2s\n", - "535450K .......... .......... .......... .......... .......... 90% 14.0M 2s\n", - "535500K .......... .......... .......... .......... .......... 90% 40.5M 2s\n", - "535550K .......... .......... .......... .......... .......... 90% 12.8M 2s\n", - "535600K .......... .......... .......... .......... .......... 90% 41.6M 2s\n", - "535650K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", - "535700K .......... .......... .......... .......... .......... 90% 45.3M 2s\n", - "535750K .......... .......... .......... .......... .......... 90% 15.1M 2s\n", - "535800K .......... .......... .......... .......... .......... 90% 12.7M 2s\n", - "535850K .......... .......... .......... .......... .......... 90% 31.2M 2s\n", - "535900K .......... .......... .......... .......... .......... 90% 15.5M 2s\n", - "535950K .......... .......... .......... .......... .......... 90% 32.2M 2s\n", - "536000K .......... .......... .......... .......... .......... 90% 15.8M 2s\n", - "536050K .......... .......... .......... .......... .......... 90% 35.9M 2s\n", - "536100K .......... .......... .......... .......... .......... 90% 14.8M 2s\n", - "536150K .......... .......... .......... .......... .......... 90% 42.8M 2s\n", - "536200K .......... .......... .......... .......... .......... 90% 13.9M 2s\n", - "536250K .......... .......... .......... .......... .......... 90% 33.5M 2s\n", - "536300K .......... .......... .......... .......... .......... 90% 15.9M 2s\n", - "536350K .......... .......... .......... .......... .......... 90% 38.3M 2s\n", - "536400K .......... .......... .......... .......... .......... 90% 15.7M 2s\n", - "536450K .......... .......... .......... .......... .......... 90% 32.1M 2s\n", - "536500K .......... .......... .......... .......... .......... 90% 17.0M 2s\n", - "536550K .......... .......... .......... .......... .......... 90% 32.6M 2s\n", - "536600K .......... .......... .......... .......... .......... 90% 14.2M 2s\n", - "536650K .......... .......... .......... .......... .......... 90% 14.5M 2s\n", - "536700K .......... .......... .......... .......... .......... 90% 41.3M 2s\n", - "536750K .......... .......... .......... .......... .......... 90% 14.7M 2s\n", - "536800K .......... .......... .......... .......... .......... 90% 36.4M 2s\n", - "536850K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", - "536900K .......... .......... .......... .......... .......... 90% 47.6M 2s\n", - "536950K .......... .......... .......... .......... .......... 90% 62.2M 2s\n", - "537000K .......... .......... .......... .......... .......... 90% 13.4M 2s\n", - "537050K .......... .......... .......... .......... .......... 90% 13.1M 2s\n", - "537100K .......... .......... .......... .......... .......... 90% 46.2M 2s\n", - "537150K .......... .......... .......... .......... .......... 90% 14.1M 2s\n", - "537200K .......... .......... .......... .......... .......... 90% 49.1M 2s\n", - "537250K .......... .......... .......... .......... .......... 90% 60.6M 2s\n", - "537300K .......... .......... .......... .......... .......... 90% 13.4M 2s\n", - "537350K .......... .......... .......... .......... .......... 90% 61.3M 2s\n", - "537400K .......... .......... .......... .......... .......... 90% 12.7M 2s\n", - "537450K .......... .......... .......... .......... .......... 90% 62.2M 2s\n", - "537500K .......... .......... .......... .......... .......... 90% 13.0M 2s\n", - "537550K .......... .......... .......... .......... .......... 90% 58.8M 2s\n", - "537600K .......... .......... .......... .......... .......... 90% 14.6M 2s\n", - "537650K .......... .......... .......... .......... .......... 90% 49.6M 1s\n", - "537700K .......... .......... .......... .......... .......... 90% 14.5M 1s\n", - "537750K .......... .......... .......... .......... .......... 90% 51.4M 1s\n", - "537800K .......... .......... .......... .......... .......... 90% 13.1M 1s\n", - "537850K .......... .......... .......... .......... .......... 90% 58.0M 1s\n", - "537900K .......... .......... .......... .......... .......... 90% 15.4M 1s\n", - "537950K .......... .......... .......... .......... .......... 90% 48.7M 1s\n", - "538000K .......... .......... .......... .......... .......... 90% 16.7M 1s\n", - "538050K .......... .......... .......... .......... .......... 90% 30.6M 1s\n", - "538100K .......... .......... .......... .......... .......... 90% 4.25M 1s\n", - "538150K .......... .......... .......... .......... .......... 90% 65.2M 1s\n", - "538200K .......... .......... .......... .......... .......... 90% 12.0M 1s\n", - "538250K .......... .......... .......... .......... .......... 90% 56.5M 1s\n", - "538300K .......... .......... .......... .......... .......... 90% 13.9M 1s\n", - "538350K .......... .......... .......... .......... .......... 90% 58.2M 1s\n", - "538400K .......... .......... .......... .......... .......... 90% 58.6M 1s\n", - "538450K .......... .......... .......... .......... .......... 90% 13.1M 1s\n", - "538500K .......... .......... .......... .......... .......... 90% 65.0M 1s\n", - "538550K .......... .......... .......... .......... .......... 90% 13.3M 1s\n", - "538600K .......... .......... .......... .......... .......... 90% 51.6M 1s\n", - "538650K .......... .......... .......... .......... .......... 90% 15.7M 1s\n", - "538700K .......... .......... .......... .......... .......... 90% 61.2M 1s\n", - "538750K .......... .......... .......... .......... .......... 90% 14.3M 1s\n", - "538800K .......... .......... .......... .......... .......... 90% 45.0M 1s\n", - "538850K .......... .......... .......... .......... .......... 90% 55.4M 1s\n", - "538900K .......... .......... .......... .......... .......... 90% 15.0M 1s\n", - "538950K .......... .......... .......... .......... .......... 90% 48.5M 1s\n", - "539000K .......... .......... .......... .......... .......... 90% 15.6M 1s\n", - "539050K .......... .......... .......... .......... .......... 90% 54.4M 1s\n", - "539100K .......... .......... .......... .......... .......... 90% 16.0M 1s\n", - "539150K .......... .......... .......... .......... .......... 90% 37.0M 1s\n", - "539200K .......... .......... .......... .......... .......... 90% 47.8M 1s\n", - "539250K .......... .......... .......... .......... .......... 90% 17.2M 1s\n", - "539300K .......... .......... .......... .......... .......... 90% 33.4M 1s\n", - "539350K .......... .......... .......... .......... .......... 90% 19.5M 1s\n", - "539400K .......... .......... .......... .......... .......... 90% 26.8M 1s\n", - "539450K .......... .......... .......... .......... .......... 90% 18.7M 1s\n", - "539500K .......... .......... .......... .......... .......... 90% 33.9M 1s\n", - "539550K .......... .......... .......... .......... .......... 90% 52.1M 1s\n", - "539600K .......... .......... .......... .......... .......... 90% 19.3M 1s\n", - "539650K .......... .......... .......... .......... .......... 90% 27.9M 1s\n", - "539700K .......... .......... .......... .......... .......... 90% 20.2M 1s\n", - "539750K .......... .......... .......... .......... .......... 90% 43.9M 1s\n", - "539800K .......... .......... .......... .......... .......... 90% 39.6M 1s\n", - "539850K .......... .......... .......... .......... .......... 90% 17.4M 1s\n", - "539900K .......... .......... .......... .......... .......... 90% 37.2M 1s\n", - "539950K .......... .......... .......... .......... .......... 90% 17.8M 1s\n", - "540000K .......... .......... .......... .......... .......... 90% 47.9M 1s\n", - "540050K .......... .......... .......... .......... .......... 90% 43.2M 1s\n", - "540100K .......... .......... .......... .......... .......... 90% 3.31M 1s\n", - "540150K .......... .......... .......... .......... .......... 90% 66.6M 1s\n", - "540200K .......... .......... .......... .......... .......... 90% 12.4M 1s\n", - "540250K .......... .......... .......... .......... .......... 90% 56.2M 1s\n", - "540300K .......... .......... .......... .......... .......... 90% 65.5M 1s\n", - "540350K .......... .......... .......... .......... .......... 90% 12.3M 1s\n", - "540400K .......... .......... .......... .......... .......... 90% 34.6M 1s\n", - "540450K .......... .......... .......... .......... .......... 90% 38.4M 1s\n", - "540500K .......... .......... .......... .......... .......... 90% 22.2M 1s\n", - "540550K .......... .......... .......... .......... .......... 90% 40.7M 1s\n", - "540600K .......... .......... .......... .......... .......... 90% 3.72M 1s\n", - "540650K .......... .......... .......... .......... .......... 90% 55.6M 1s\n", - "540700K .......... .......... .......... .......... .......... 90% 52.4M 1s\n", - "540750K .......... .......... .......... .......... .......... 90% 55.5M 1s\n", - "540800K .......... .......... .......... .......... .......... 90% 27.7M 1s\n", - "540850K .......... .......... .......... .......... .......... 90% 9.24M 1s\n", - "540900K .......... .......... .......... .......... .......... 90% 14.2M 1s\n", - "540950K .......... .......... .......... .......... .......... 90% 41.5M 1s\n", - "541000K .......... .......... .......... .......... .......... 90% 12.5M 1s\n", - "541050K .......... .......... .......... .......... .......... 90% 68.8M 1s\n", - "541100K .......... .......... .......... .......... .......... 90% 13.6M 1s\n", - "541150K .......... .......... .......... .......... .......... 90% 12.8M 1s\n", - "541200K .......... .......... .......... .......... .......... 91% 32.1M 1s\n", - "541250K .......... .......... .......... .......... .......... 91% 68.0M 1s\n", - "541300K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", - "541350K .......... .......... .......... .......... .......... 91% 54.9M 1s\n", - "541400K .......... .......... .......... .......... .......... 91% 11.2M 1s\n", - "541450K .......... .......... .......... .......... .......... 91% 14.9M 1s\n", - "541500K .......... .......... .......... .......... .......... 91% 43.4M 1s\n", - "541550K .......... .......... .......... .......... .......... 91% 14.0M 1s\n", - "541600K .......... .......... .......... .......... .......... 91% 35.4M 1s\n", - "541650K .......... .......... .......... .......... .......... 91% 14.2M 1s\n", - "541700K .......... .......... .......... .......... .......... 91% 43.5M 1s\n", - "541750K .......... .......... .......... .......... .......... 91% 14.4M 1s\n", - "541800K .......... .......... .......... .......... .......... 91% 33.5M 1s\n", - "541850K .......... .......... .......... .......... .......... 91% 16.9M 1s\n", - "541900K .......... .......... .......... .......... .......... 91% 25.3M 1s\n", - "541950K .......... .......... .......... .......... .......... 91% 18.6M 1s\n", - "542000K .......... .......... .......... .......... .......... 91% 28.5M 1s\n", - "542050K .......... .......... .......... .......... .......... 91% 15.2M 1s\n", - "542100K .......... .......... .......... .......... .......... 91% 37.4M 1s\n", - "542150K .......... .......... .......... .......... .......... 91% 49.5M 1s\n", - "542200K .......... .......... .......... .......... .......... 91% 13.2M 1s\n", - "542250K .......... .......... .......... .......... .......... 91% 14.8M 1s\n", - "542300K .......... .......... .......... .......... .......... 91% 60.4M 1s\n", - "542350K .......... .......... .......... .......... .......... 91% 50.2M 1s\n", - "542400K .......... .......... .......... .......... .......... 91% 12.6M 1s\n", - "542450K .......... .......... .......... .......... .......... 91% 53.1M 1s\n", - "542500K .......... .......... .......... .......... .......... 91% 16.8M 1s\n", - "542550K .......... .......... .......... .......... .......... 91% 38.5M 1s\n", - "542600K .......... .......... .......... .......... .......... 91% 13.3M 1s\n", - "542650K .......... .......... .......... .......... .......... 91% 48.5M 1s\n", - "542700K .......... .......... .......... .......... .......... 91% 16.1M 1s\n", - "542750K .......... .......... .......... .......... .......... 91% 42.1M 1s\n", - "542800K .......... .......... .......... .......... .......... 91% 15.3M 1s\n", - "542850K .......... .......... .......... .......... .......... 91% 38.6M 1s\n", - "542900K .......... .......... .......... .......... .......... 91% 16.1M 1s\n", - "542950K .......... .......... .......... .......... .......... 91% 54.0M 1s\n", - "543000K .......... .......... .......... .......... .......... 91% 12.8M 1s\n", - "543050K .......... .......... .......... .......... .......... 91% 41.3M 1s\n", - "543100K .......... .......... .......... .......... .......... 91% 15.6M 1s\n", - "543150K .......... .......... .......... .......... .......... 91% 44.6M 1s\n", - "543200K .......... .......... .......... .......... .......... 91% 47.6M 1s\n", - "543250K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", - "543300K .......... .......... .......... .......... .......... 91% 44.4M 1s\n", - "543350K .......... .......... .......... .......... .......... 91% 14.7M 1s\n", - "543400K .......... .......... .......... .......... .......... 91% 39.2M 1s\n", - "543450K .......... .......... .......... .......... .......... 91% 13.3M 1s\n", - "543500K .......... .......... .......... .......... .......... 91% 44.7M 1s\n", - "543550K .......... .......... .......... .......... .......... 91% 17.6M 1s\n", - "543600K .......... .......... .......... .......... .......... 91% 43.8M 1s\n", - "543650K .......... .......... .......... .......... .......... 91% 53.0M 1s\n", - "543700K .......... .......... .......... .......... .......... 91% 14.7M 1s\n", - "543750K .......... .......... .......... .......... .......... 91% 42.2M 1s\n", - "543800K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", - "543850K .......... .......... .......... .......... .......... 91% 57.9M 1s\n", - "543900K .......... .......... .......... .......... .......... 91% 14.8M 1s\n", - "543950K .......... .......... .......... .......... .......... 91% 45.9M 1s\n", - "544000K .......... .......... .......... .......... .......... 91% 14.5M 1s\n", - "544050K .......... .......... .......... .......... .......... 91% 53.0M 1s\n", - "544100K .......... .......... .......... .......... .......... 91% 45.0M 1s\n", - "544150K .......... .......... .......... .......... .......... 91% 15.5M 1s\n", - "544200K .......... .......... .......... .......... .......... 91% 42.5M 1s\n", - "544250K .......... .......... .......... .......... .......... 91% 17.4M 1s\n", - "544300K .......... .......... .......... .......... .......... 91% 31.8M 1s\n", - "544350K .......... .......... .......... .......... .......... 91% 18.2M 1s\n", - "544400K .......... .......... .......... .......... .......... 91% 38.3M 1s\n", - "544450K .......... .......... .......... .......... .......... 91% 39.9M 1s\n", - "544500K .......... .......... .......... .......... .......... 91% 16.7M 1s\n", - "544550K .......... .......... .......... .......... .......... 91% 29.1M 1s\n", - "544600K .......... .......... .......... .......... .......... 91% 17.9M 1s\n", - "544650K .......... .......... .......... .......... .......... 91% 28.5M 1s\n", - "544700K .......... .......... .......... .......... .......... 91% 37.5M 1s\n", - "544750K .......... .......... .......... .......... .......... 91% 22.3M 1s\n", - "544800K .......... .......... .......... .......... .......... 91% 29.4M 1s\n", - "544850K .......... .......... .......... .......... .......... 91% 21.2M 1s\n", - "544900K .......... .......... .......... .......... .......... 91% 30.3M 1s\n", - "544950K .......... .......... .......... .......... .......... 91% 38.0M 1s\n", - "545000K .......... .......... .......... .......... .......... 91% 20.0M 1s\n", - "545050K .......... .......... .......... .......... .......... 91% 31.7M 1s\n", - "545100K .......... .......... .......... .......... .......... 91% 22.4M 1s\n", - "545150K .......... .......... .......... .......... .......... 91% 32.5M 1s\n", - "545200K .......... .......... .......... .......... .......... 91% 18.8M 1s\n", - "545250K .......... .......... .......... .......... .......... 91% 34.1M 1s\n", - "545300K .......... .......... .......... .......... .......... 91% 39.0M 1s\n", - "545350K .......... .......... .......... .......... .......... 91% 21.4M 1s\n", - "545400K .......... .......... .......... .......... .......... 91% 18.9M 1s\n", - "545450K .......... .......... .......... .......... .......... 91% 35.5M 1s\n", - "545500K .......... .......... .......... .......... .......... 91% 34.3M 1s\n", - "545550K .......... .......... .......... .......... .......... 91% 20.2M 1s\n", - "545600K .......... .......... .......... .......... .......... 91% 32.8M 1s\n", - "545650K .......... .......... .......... .......... .......... 91% 22.4M 1s\n", - "545700K .......... .......... .......... .......... .......... 91% 30.3M 1s\n", - "545750K .......... .......... .......... .......... .......... 91% 29.7M 1s\n", - "545800K .......... .......... .......... .......... .......... 91% 20.4M 1s\n", - "545850K .......... .......... .......... .......... .......... 91% 50.7M 1s\n", - "545900K .......... .......... .......... .......... .......... 91% 19.0M 1s\n", - "545950K .......... .......... .......... .......... .......... 91% 34.8M 1s\n", - "546000K .......... .......... .......... .......... .......... 91% 31.0M 1s\n", - "546050K .......... .......... .......... .......... .......... 91% 26.2M 1s\n", - "546100K .......... .......... .......... .......... .......... 91% 26.9M 1s\n", - "546150K .......... .......... .......... .......... .......... 91% 41.8M 1s\n", - "546200K .......... .......... .......... .......... .......... 91% 21.3M 1s\n", - "546250K .......... .......... .......... .......... .......... 91% 28.3M 1s\n", - "546300K .......... .......... .......... .......... .......... 91% 33.4M 1s\n", - "546350K .......... .......... .......... .......... .......... 91% 22.5M 1s\n", - "546400K .......... .......... .......... .......... .......... 91% 41.3M 1s\n", - "546450K .......... .......... .......... .......... .......... 91% 23.3M 1s\n", - "546500K .......... .......... .......... .......... .......... 91% 28.1M 1s\n", - "546550K .......... .......... .......... .......... .......... 91% 31.2M 1s\n", - "546600K .......... .......... .......... .......... .......... 91% 20.6M 1s\n", - "546650K .......... .......... .......... .......... .......... 91% 29.2M 1s\n", - "546700K .......... .......... .......... .......... .......... 91% 39.2M 1s\n", - "546750K .......... .......... .......... .......... .......... 91% 28.3M 1s\n", - "546800K .......... .......... .......... .......... .......... 91% 18.6M 1s\n", - "546850K .......... .......... .......... .......... .......... 91% 30.9M 1s\n", - "546900K .......... .......... .......... .......... .......... 91% 54.2M 1s\n", - "546950K .......... .......... .......... .......... .......... 91% 25.8M 1s\n", - "547000K .......... .......... .......... .......... .......... 91% 21.9M 1s\n", - "547050K .......... .......... .......... .......... .......... 91% 42.9M 1s\n", - "547100K .......... .......... .......... .......... .......... 91% 24.5M 1s\n", - "547150K .......... .......... .......... .......... .......... 92% 36.2M 1s\n", - "547200K .......... .......... .......... .......... .......... 92% 25.3M 1s\n", - "547250K .......... .......... .......... .......... .......... 92% 31.6M 1s\n", - "547300K .......... .......... .......... .......... .......... 92% 27.6M 1s\n", - "547350K .......... .......... .......... .......... .......... 92% 41.0M 1s\n", - "547400K .......... .......... .......... .......... .......... 92% 3.60M 1s\n", - "547450K .......... .......... .......... .......... .......... 92% 43.4M 1s\n", - "547500K .......... .......... .......... .......... .......... 92% 59.0M 1s\n", - "547550K .......... .......... .......... .......... .......... 92% 15.6M 1s\n", - "547600K .......... .......... .......... .......... .......... 92% 48.0M 1s\n", - "547650K .......... .......... .......... .......... .......... 92% 48.7M 1s\n", - "547700K .......... .......... .......... .......... .......... 92% 18.5M 1s\n", - "547750K .......... .......... .......... .......... .......... 92% 57.2M 1s\n", - "547800K .......... .......... .......... .......... .......... 92% 15.0M 1s\n", - "547850K .......... .......... .......... .......... .......... 92% 32.2M 1s\n", - "547900K .......... .......... .......... .......... .......... 92% 37.7M 1s\n", - "547950K .......... .......... .......... .......... .......... 92% 29.3M 1s\n", - "548000K .......... .......... .......... .......... .......... 92% 37.3M 1s\n", - "548050K .......... .......... .......... .......... .......... 92% 61.4M 1s\n", - "548100K .......... .......... .......... .......... .......... 92% 15.7M 1s\n", - "548150K .......... .......... .......... .......... .......... 92% 35.0M 1s\n", - "548200K .......... .......... .......... .......... .......... 92% 24.6M 1s\n", - "548250K .......... .......... .......... .......... .......... 92% 33.2M 1s\n", - "548300K .......... .......... .......... .......... .......... 92% 23.5M 1s\n", - "548350K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", - "548400K .......... .......... .......... .......... .......... 92% 31.8M 1s\n", - "548450K .......... .......... .......... .......... .......... 92% 22.8M 1s\n", - "548500K .......... .......... .......... .......... .......... 92% 67.1M 1s\n", - "548550K .......... .......... .......... .......... .......... 92% 33.7M 1s\n", - "548600K .......... .......... .......... .......... .......... 92% 20.9M 1s\n", - "548650K .......... .......... .......... .......... .......... 92% 46.7M 1s\n", - "548700K .......... .......... .......... .......... .......... 92% 33.6M 1s\n", - "548750K .......... .......... .......... .......... .......... 92% 26.6M 1s\n", - "548800K .......... .......... .......... .......... .......... 92% 36.1M 1s\n", - "548850K .......... .......... .......... .......... .......... 92% 35.9M 1s\n", - "548900K .......... .......... .......... .......... .......... 92% 26.3M 1s\n", - "548950K .......... .......... .......... .......... .......... 92% 37.2M 1s\n", - "549000K .......... .......... .......... .......... .......... 92% 37.5M 1s\n", - "549050K .......... .......... .......... .......... .......... 92% 22.2M 1s\n", - "549100K .......... .......... .......... .......... .......... 92% 53.2M 1s\n", - "549150K .......... .......... .......... .......... .......... 92% 33.2M 1s\n", - "549200K .......... .......... .......... .......... .......... 92% 21.3M 1s\n", - "549250K .......... .......... .......... .......... .......... 92% 61.4M 1s\n", - "549300K .......... .......... .......... .......... .......... 92% 30.0M 1s\n", - "549350K .......... .......... .......... .......... .......... 92% 25.7M 1s\n", - "549400K .......... .......... .......... .......... .......... 92% 41.5M 1s\n", - "549450K .......... .......... .......... .......... .......... 92% 38.1M 1s\n", - "549500K .......... .......... .......... .......... .......... 92% 23.5M 1s\n", - "549550K .......... .......... .......... .......... .......... 92% 58.4M 1s\n", - "549600K .......... .......... .......... .......... .......... 92% 32.1M 1s\n", - "549650K .......... .......... .......... .......... .......... 92% 21.4M 1s\n", - "549700K .......... .......... .......... .......... .......... 92% 75.1M 1s\n", - "549750K .......... .......... .......... .......... .......... 92% 40.8M 1s\n", - "549800K .......... .......... .......... .......... .......... 92% 15.8M 1s\n", - "549850K .......... .......... .......... .......... .......... 92% 51.7M 1s\n", - "549900K .......... .......... .......... .......... .......... 92% 52.0M 1s\n", - "549950K .......... .......... .......... .......... .......... 92% 20.5M 1s\n", - "550000K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", - "550050K .......... .......... .......... .......... .......... 92% 48.1M 1s\n", - "550100K .......... .......... .......... .......... .......... 92% 19.9M 1s\n", - "550150K .......... .......... .......... .......... .......... 92% 50.2M 1s\n", - "550200K .......... .......... .......... .......... .......... 92% 36.9M 1s\n", - "550250K .......... .......... .......... .......... .......... 92% 19.6M 1s\n", - "550300K .......... .......... .......... .......... .......... 92% 53.2M 1s\n", - "550350K .......... .......... .......... .......... .......... 92% 4.32M 1s\n", - "550400K .......... .......... .......... .......... .......... 92% 50.0M 1s\n", - "550450K .......... .......... .......... .......... .......... 92% 71.1M 1s\n", - "550500K .......... .......... .......... .......... .......... 92% 20.1M 1s\n", - "550550K .......... .......... .......... .......... .......... 92% 44.3M 1s\n", - "550600K .......... .......... .......... .......... .......... 92% 62.4M 1s\n", - "550650K .......... .......... .......... .......... .......... 92% 20.0M 1s\n", - "550700K .......... .......... .......... .......... .......... 92% 41.8M 1s\n", - "550750K .......... .......... .......... .......... .......... 92% 57.7M 1s\n", - "550800K .......... .......... .......... .......... .......... 92% 49.9M 1s\n", - "550850K .......... .......... .......... .......... .......... 92% 18.2M 1s\n", - "550900K .......... .......... .......... .......... .......... 92% 64.2M 1s\n", - "550950K .......... .......... .......... .......... .......... 92% 76.2M 1s\n", - "551000K .......... .......... .......... .......... .......... 92% 17.2M 1s\n", - "551050K .......... .......... .......... .......... .......... 92% 37.2M 1s\n", - "551100K .......... .......... .......... .......... .......... 92% 53.0M 1s\n", - "551150K .......... .......... .......... .......... .......... 92% 26.3M 1s\n", - "551200K .......... .......... .......... .......... .......... 92% 40.6M 1s\n", - "551250K .......... .......... .......... .......... .......... 92% 69.7M 1s\n", - "551300K .......... .......... .......... .......... .......... 92% 22.2M 1s\n", - "551350K .......... .......... .......... .......... .......... 92% 26.0M 1s\n", - "551400K .......... .......... .......... .......... .......... 92% 54.6M 1s\n", - "551450K .......... .......... .......... .......... .......... 92% 29.5M 1s\n", - "551500K .......... .......... .......... .......... .......... 92% 49.5M 1s\n", - "551550K .......... .......... .......... .......... .......... 92% 40.3M 1s\n", - "551600K .......... .......... .......... .......... .......... 92% 67.4M 1s\n", - "551650K .......... .......... .......... .......... .......... 92% 23.0M 1s\n", - "551700K .......... .......... .......... .......... .......... 92% 29.5M 1s\n", - "551750K .......... .......... .......... .......... .......... 92% 66.1M 1s\n", - "551800K .......... .......... .......... .......... .......... 92% 22.9M 1s\n", - "551850K .......... .......... .......... .......... .......... 92% 28.9M 1s\n", - "551900K .......... .......... .......... .......... .......... 92% 59.0M 1s\n", - "551950K .......... .......... .......... .......... .......... 92% 37.1M 1s\n", - "552000K .......... .......... .......... .......... .......... 92% 25.4M 1s\n", - "552050K .......... .......... .......... .......... .......... 92% 43.6M 1s\n", + "385500K .......... .......... .......... .......... .......... 64% 8.03M 5s\n", + "385550K .......... .......... .......... .......... .......... 64% 60.8M 5s\n", + "385600K .......... .......... .......... .......... .......... 64% 64.6M 5s\n", + "385650K .......... .......... .......... .......... .......... 64% 68.0M 5s\n", + "385700K .......... .......... .......... .......... .......... 64% 69.8M 5s\n", + "385750K .......... .......... .......... .......... .......... 64% 68.4M 5s\n", + "385800K .......... .......... .......... .......... .......... 64% 46.9M 5s\n", + "385850K .......... .......... .......... .......... .......... 64% 34.2M 5s\n", + "385900K .......... .......... .......... .......... .......... 64% 43.7M 5s\n", + "385950K .......... .......... .......... .......... .......... 64% 69.6M 5s\n", + "386000K .......... .......... .......... .......... .......... 64% 64.0M 5s\n", + "386050K .......... .......... .......... .......... .......... 64% 48.1M 5s\n", + "386100K .......... .......... .......... .......... .......... 64% 45.2M 5s\n", + "386150K .......... .......... .......... .......... .......... 64% 37.2M 5s\n", + "386200K .......... .......... .......... .......... .......... 64% 54.1M 5s\n", + "386250K .......... .......... .......... .......... .......... 64% 66.4M 5s\n", + "386300K .......... .......... .......... .......... .......... 64% 43.2M 5s\n", + "386350K .......... .......... .......... .......... .......... 64% 38.0M 5s\n", + "386400K .......... .......... .......... .......... .......... 64% 42.2M 5s\n", + "386450K .......... .......... .......... .......... .......... 64% 74.6M 5s\n", + "386500K .......... .......... .......... .......... .......... 64% 50.5M 5s\n", + "386550K .......... .......... .......... .......... .......... 65% 30.7M 5s\n", + "386600K .......... .......... .......... .......... .......... 65% 30.9M 5s\n", + "386650K .......... .......... .......... .......... .......... 65% 47.3M 5s\n", + "386700K .......... .......... .......... .......... .......... 65% 35.5M 5s\n", + "386750K .......... .......... .......... .......... .......... 65% 32.8M 5s\n", + "386800K .......... .......... .......... .......... .......... 65% 29.1M 5s\n", + "386850K .......... .......... .......... .......... .......... 65% 37.8M 5s\n", + "386900K .......... .......... .......... .......... .......... 65% 59.3M 5s\n", + "386950K .......... .......... .......... .......... .......... 65% 28.3M 5s\n", + "387000K .......... .......... .......... .......... .......... 65% 24.0M 5s\n", + "387050K .......... .......... .......... .......... .......... 65% 65.1M 5s\n", + "387100K .......... .......... .......... .......... .......... 65% 63.0M 5s\n", + "387150K .......... .......... .......... .......... .......... 65% 35.5M 5s\n", + "387200K .......... .......... .......... .......... .......... 65% 27.2M 5s\n", + "387250K .......... .......... .......... .......... .......... 65% 69.0M 5s\n", + "387300K .......... .......... .......... .......... .......... 65% 54.1M 5s\n", + "387350K .......... .......... .......... .......... .......... 65% 29.2M 5s\n", + "387400K .......... .......... .......... .......... .......... 65% 32.5M 5s\n", + "387450K .......... .......... .......... .......... .......... 65% 50.0M 5s\n", + "387500K .......... .......... .......... .......... .......... 65% 41.1M 5s\n", + "387550K .......... .......... .......... .......... .......... 65% 42.6M 5s\n", + "387600K .......... .......... .......... .......... .......... 65% 40.5M 5s\n", + "387650K .......... .......... .......... .......... .......... 65% 48.5M 5s\n", + "387700K .......... .......... .......... .......... .......... 65% 51.1M 5s\n", + "387750K .......... .......... .......... .......... .......... 65% 46.3M 5s\n", + "387800K .......... .......... .......... .......... .......... 65% 37.1M 5s\n", + "387850K .......... .......... .......... .......... .......... 65% 49.6M 5s\n", + "387900K .......... .......... .......... .......... .......... 65% 51.4M 5s\n", + "387950K .......... .......... .......... .......... .......... 65% 22.0M 5s\n", + "388000K .......... .......... .......... .......... .......... 65% 30.4M 5s\n", + "388050K .......... .......... .......... .......... .......... 65% 38.5M 5s\n", + "388100K .......... .......... .......... .......... .......... 65% 59.0M 5s\n", + "388150K .......... .......... .......... .......... .......... 65% 65.0M 5s\n", + "388200K .......... .......... .......... .......... .......... 65% 47.1M 5s\n", + "388250K .......... .......... .......... .......... .......... 65% 48.3M 5s\n", + "388300K .......... .......... .......... .......... .......... 65% 45.4M 5s\n", + "388350K .......... .......... .......... .......... .......... 65% 53.1M 5s\n", + "388400K .......... .......... .......... .......... .......... 65% 37.5M 5s\n", + "388450K .......... .......... .......... .......... .......... 65% 33.8M 5s\n", + "388500K .......... .......... .......... .......... .......... 65% 49.0M 5s\n", + "388550K .......... .......... .......... .......... .......... 65% 71.1M 5s\n", + "388600K .......... .......... .......... .......... .......... 65% 29.9M 5s\n", + "388650K .......... .......... .......... .......... .......... 65% 44.6M 5s\n", + "388700K .......... .......... .......... .......... .......... 65% 3.81M 5s\n", + "388750K .......... .......... .......... .......... .......... 65% 65.2M 5s\n", + "388800K .......... .......... .......... .......... .......... 65% 67.1M 5s\n", + "388850K .......... .......... .......... .......... .......... 65% 67.3M 5s\n", + "388900K .......... .......... .......... .......... .......... 65% 59.0M 5s\n", + "388950K .......... .......... .......... .......... .......... 65% 67.0M 5s\n", + "389000K .......... .......... .......... .......... .......... 65% 50.4M 5s\n", + "389050K .......... .......... .......... .......... .......... 65% 39.5M 5s\n", + "389100K .......... .......... .......... .......... .......... 65% 73.6M 5s\n", + "389150K .......... .......... .......... .......... .......... 65% 53.4M 5s\n", + "389200K .......... .......... .......... .......... .......... 65% 33.8M 5s\n", + "389250K .......... .......... .......... .......... .......... 65% 44.4M 5s\n", + "389300K .......... .......... .......... .......... .......... 65% 67.0M 5s\n", + "389350K .......... .......... .......... .......... .......... 65% 69.9M 5s\n", + "389400K .......... .......... .......... .......... .......... 65% 26.6M 5s\n", + "389450K .......... .......... .......... .......... .......... 65% 41.3M 5s\n", + "389500K .......... .......... .......... .......... .......... 65% 71.1M 5s\n", + "389550K .......... .......... .......... .......... .......... 65% 70.6M 5s\n", + "389600K .......... .......... .......... .......... .......... 65% 29.3M 5s\n", + "389650K .......... .......... .......... .......... .......... 65% 53.1M 5s\n", + "389700K .......... .......... .......... .......... .......... 65% 55.5M 5s\n", + "389750K .......... .......... .......... .......... .......... 65% 67.8M 5s\n", + "389800K .......... .......... .......... .......... .......... 65% 34.4M 5s\n", + "389850K .......... .......... .......... .......... .......... 65% 38.4M 5s\n", + "389900K .......... .......... .......... .......... .......... 65% 51.8M 5s\n", + "389950K .......... .......... .......... .......... .......... 65% 72.2M 5s\n", + "390000K .......... .......... .......... .......... .......... 65% 32.4M 5s\n", + "390050K .......... .......... .......... .......... .......... 65% 39.1M 5s\n", + "390100K .......... .......... .......... .......... .......... 65% 62.7M 5s\n", + "390150K .......... .......... .......... .......... .......... 65% 71.7M 5s\n", + "390200K .......... .......... .......... .......... .......... 65% 32.0M 5s\n", + "390250K .......... .......... .......... .......... .......... 65% 47.8M 5s\n", + "390300K .......... .......... .......... .......... .......... 65% 48.9M 5s\n", + "390350K .......... .......... .......... .......... .......... 65% 72.6M 5s\n", + "390400K .......... .......... .......... .......... .......... 65% 53.8M 5s\n", + "390450K .......... .......... .......... .......... .......... 65% 34.1M 5s\n", + "390500K .......... .......... .......... .......... .......... 65% 42.5M 5s\n", + "390550K .......... .......... .......... .......... .......... 65% 71.8M 5s\n", + "390600K .......... .......... .......... .......... .......... 65% 43.6M 5s\n", + "390650K .......... .......... .......... .......... .......... 65% 33.6M 5s\n", + "390700K .......... .......... .......... .......... .......... 65% 67.3M 5s\n", + "390750K .......... .......... .......... .......... .......... 65% 50.7M 5s\n", + "390800K .......... .......... .......... .......... .......... 65% 67.8M 5s\n", + "390850K .......... .......... .......... .......... .......... 65% 32.6M 5s\n", + "390900K .......... .......... .......... .......... .......... 65% 57.3M 5s\n", + "390950K .......... .......... .......... .......... .......... 65% 49.1M 5s\n", + "391000K .......... .......... .......... .......... .......... 65% 58.4M 5s\n", + "391050K .......... .......... .......... .......... .......... 65% 40.7M 5s\n", + "391100K .......... .......... .......... .......... .......... 65% 42.2M 5s\n", + "391150K .......... .......... .......... .......... .......... 65% 64.0M 5s\n", + "391200K .......... .......... .......... .......... .......... 65% 44.8M 5s\n", + "391250K .......... .......... .......... .......... .......... 65% 48.8M 5s\n", + "391300K .......... .......... .......... .......... .......... 65% 31.7M 5s\n", + "391350K .......... .......... .......... .......... .......... 65% 75.6M 5s\n", + "391400K .......... .......... .......... .......... .......... 65% 36.0M 5s\n", + "391450K .......... .......... .......... .......... .......... 65% 46.7M 5s\n", + "391500K .......... .......... .......... .......... .......... 65% 37.9M 5s\n", + "391550K .......... .......... .......... .......... .......... 65% 74.2M 5s\n", + "391600K .......... .......... .......... .......... .......... 65% 37.1M 5s\n", + "391650K .......... .......... .......... .......... .......... 65% 47.7M 5s\n", + "391700K .......... .......... .......... .......... .......... 65% 36.4M 5s\n", + "391750K .......... .......... .......... .......... .......... 65% 31.2M 5s\n", + "391800K .......... .......... .......... .......... .......... 65% 31.3M 5s\n", + "391850K .......... .......... .......... .......... .......... 65% 46.9M 5s\n", + "391900K .......... .......... .......... .......... .......... 65% 73.5M 5s\n", + "391950K .......... .......... .......... .......... .......... 65% 50.1M 5s\n", + "392000K .......... .......... .......... .......... .......... 65% 32.8M 5s\n", + "392050K .......... .......... .......... .......... .......... 65% 44.1M 5s\n", + "392100K .......... .......... .......... .......... .......... 65% 60.2M 5s\n", + "392150K .......... .......... .......... .......... .......... 65% 39.5M 5s\n", + "392200K .......... .......... .......... .......... .......... 65% 37.0M 5s\n", + "392250K .......... .......... .......... .......... .......... 65% 55.3M 5s\n", + "392300K .......... .......... .......... .......... .......... 65% 63.3M 5s\n", + "392350K .......... .......... .......... .......... .......... 65% 40.9M 5s\n", + "392400K .......... .......... .......... .......... .......... 65% 38.7M 5s\n", + "392450K .......... .......... .......... .......... .......... 65% 59.5M 5s\n", + "392500K .......... .......... .......... .......... .......... 66% 51.1M 5s\n", + "392550K .......... .......... .......... .......... .......... 66% 40.8M 5s\n", + "392600K .......... .......... .......... .......... .......... 66% 39.4M 5s\n", + "392650K .......... .......... .......... .......... .......... 66% 70.7M 5s\n", + "392700K .......... .......... .......... .......... .......... 66% 41.1M 5s\n", + "392750K .......... .......... .......... .......... .......... 66% 48.7M 5s\n", + "392800K .......... .......... .......... .......... .......... 66% 47.6M 5s\n", + "392850K .......... .......... .......... .......... .......... 66% 47.3M 5s\n", + "392900K .......... .......... .......... .......... .......... 66% 40.0M 5s\n", + "392950K .......... .......... .......... .......... .......... 66% 63.7M 5s\n", + "393000K .......... .......... .......... .......... .......... 66% 36.6M 5s\n", + "393050K .......... .......... .......... .......... .......... 66% 50.6M 5s\n", + "393100K .......... .......... .......... .......... .......... 66% 65.9M 5s\n", + "393150K .......... .......... .......... .......... .......... 66% 33.0M 5s\n", + "393200K .......... .......... .......... .......... .......... 66% 48.2M 5s\n", + "393250K .......... .......... .......... .......... .......... 66% 46.2M 5s\n", + "393300K .......... .......... .......... .......... .......... 66% 74.4M 4s\n", + "393350K .......... .......... .......... .......... .......... 66% 40.9M 4s\n", + "393400K .......... .......... .......... .......... .......... 66% 46.8M 4s\n", + "393450K .......... .......... .......... .......... .......... 66% 52.6M 4s\n", + "393500K .......... .......... .......... .......... .......... 66% 52.0M 4s\n", + "393550K .......... .......... .......... .......... .......... 66% 47.2M 4s\n", + "393600K .......... .......... .......... .......... .......... 66% 58.3M 4s\n", + "393650K .......... .......... .......... .......... .......... 66% 42.0M 4s\n", + "393700K .......... .......... .......... .......... .......... 66% 52.9M 4s\n", + "393750K .......... .......... .......... .......... .......... 66% 69.7M 4s\n", + "393800K .......... .......... .......... .......... .......... 66% 32.6M 4s\n", + "393850K .......... .......... .......... .......... .......... 66% 39.5M 4s\n", + "393900K .......... .......... .......... .......... .......... 66% 51.8M 4s\n", + "393950K .......... .......... .......... .......... .......... 66% 65.0M 4s\n", + "394000K .......... .......... .......... .......... .......... 66% 37.3M 4s\n", + "394050K .......... .......... .......... .......... .......... 66% 7.39M 4s\n", + "394100K .......... .......... .......... .......... .......... 66% 75.9M 4s\n", + "394150K .......... .......... .......... .......... .......... 66% 69.9M 4s\n", + "394200K .......... .......... .......... .......... .......... 66% 60.8M 4s\n", + "394250K .......... .......... .......... .......... .......... 66% 51.2M 4s\n", + "394300K .......... .......... .......... .......... .......... 66% 27.0M 4s\n", + "394350K .......... .......... .......... .......... .......... 66% 39.9M 4s\n", + "394400K .......... .......... .......... .......... .......... 66% 57.0M 4s\n", + "394450K .......... .......... .......... .......... .......... 66% 43.1M 4s\n", + "394500K .......... .......... .......... .......... .......... 66% 53.7M 4s\n", + "394550K .......... .......... .......... .......... .......... 66% 40.6M 4s\n", + "394600K .......... .......... .......... .......... .......... 66% 53.9M 4s\n", + "394650K .......... .......... .......... .......... .......... 66% 39.9M 4s\n", + "394700K .......... .......... .......... .......... .......... 66% 54.8M 4s\n", + "394750K .......... .......... .......... .......... .......... 66% 32.9M 4s\n", + "394800K .......... .......... .......... .......... .......... 66% 58.6M 4s\n", + "394850K .......... .......... .......... .......... .......... 66% 38.9M 4s\n", + "394900K .......... .......... .......... .......... .......... 66% 52.0M 4s\n", + "394950K .......... .......... .......... .......... .......... 66% 32.8M 4s\n", + "395000K .......... .......... .......... .......... .......... 66% 46.7M 4s\n", + "395050K .......... .......... .......... .......... .......... 66% 40.3M 4s\n", + "395100K .......... .......... .......... .......... .......... 66% 55.7M 4s\n", + "395150K .......... .......... .......... .......... .......... 66% 43.3M 4s\n", + "395200K .......... .......... .......... .......... .......... 66% 44.0M 4s\n", + "395250K .......... .......... .......... .......... .......... 66% 41.2M 4s\n", + "395300K .......... .......... .......... .......... .......... 66% 56.3M 4s\n", + "395350K .......... .......... .......... .......... .......... 66% 52.0M 4s\n", + "395400K .......... .......... .......... .......... .......... 66% 41.0M 4s\n", + "395450K .......... .......... .......... .......... .......... 66% 53.0M 4s\n", + "395500K .......... .......... .......... .......... .......... 66% 47.4M 4s\n", + "395550K .......... .......... .......... .......... .......... 66% 49.3M 4s\n", + "395600K .......... .......... .......... .......... .......... 66% 39.2M 4s\n", + "395650K .......... .......... .......... .......... .......... 66% 54.0M 4s\n", + "395700K .......... .......... .......... .......... .......... 66% 53.4M 4s\n", + "395750K .......... .......... .......... .......... .......... 66% 50.1M 4s\n", + "395800K .......... .......... .......... .......... .......... 66% 31.6M 4s\n", + "395850K .......... .......... .......... .......... .......... 66% 45.2M 4s\n", + "395900K .......... .......... .......... .......... .......... 66% 67.4M 4s\n", + "395950K .......... .......... .......... .......... .......... 66% 47.1M 4s\n", + "396000K .......... .......... .......... .......... .......... 66% 35.1M 4s\n", + "396050K .......... .......... .......... .......... .......... 66% 37.2M 4s\n", + "396100K .......... .......... .......... .......... .......... 66% 73.0M 4s\n", + "396150K .......... .......... .......... .......... .......... 66% 44.7M 4s\n", + "396200K .......... .......... .......... .......... .......... 66% 30.7M 4s\n", + "396250K .......... .......... .......... .......... .......... 66% 41.6M 4s\n", + "396300K .......... .......... .......... .......... .......... 66% 46.0M 4s\n", + "396350K .......... .......... .......... .......... .......... 66% 43.5M 4s\n", + "396400K .......... .......... .......... .......... .......... 66% 47.4M 4s\n", + "396450K .......... .......... .......... .......... .......... 66% 46.0M 4s\n", + "396500K .......... .......... .......... .......... .......... 66% 50.8M 4s\n", + "396550K .......... .......... .......... .......... .......... 66% 41.3M 4s\n", + "396600K .......... .......... .......... .......... .......... 66% 45.3M 4s\n", + "396650K .......... .......... .......... .......... .......... 66% 46.0M 4s\n", + "396700K .......... .......... .......... .......... .......... 66% 53.6M 4s\n", + "396750K .......... .......... .......... .......... .......... 66% 41.0M 4s\n", + "396800K .......... .......... .......... .......... .......... 66% 59.6M 4s\n", + "396850K .......... .......... .......... .......... .......... 66% 52.9M 4s\n", + "396900K .......... .......... .......... .......... .......... 66% 40.7M 4s\n", + "396950K .......... .......... .......... .......... .......... 66% 45.8M 4s\n", + "397000K .......... .......... .......... .......... .......... 66% 42.4M 4s\n", + "397050K .......... .......... .......... .......... .......... 66% 51.2M 4s\n", + "397100K .......... .......... .......... .......... .......... 66% 46.8M 4s\n", + "397150K .......... .......... .......... .......... .......... 66% 46.7M 4s\n", + "397200K .......... .......... .......... .......... .......... 66% 52.2M 4s\n", + "397250K .......... .......... .......... .......... .......... 66% 52.5M 4s\n", + "397300K .......... .......... .......... .......... .......... 66% 42.5M 4s\n", + "397350K .......... .......... .......... .......... .......... 66% 40.6M 4s\n", + "397400K .......... .......... .......... .......... .......... 66% 43.5M 4s\n", + "397450K .......... .......... .......... .......... .......... 66% 52.1M 4s\n", + "397500K .......... .......... .......... .......... .......... 66% 47.5M 4s\n", + "397550K .......... .......... .......... .......... .......... 66% 49.0M 4s\n", + "397600K .......... .......... .......... .......... .......... 66% 53.3M 4s\n", + "397650K .......... .......... .......... .......... .......... 66% 60.7M 4s\n", + "397700K .......... .......... .......... .......... .......... 66% 52.9M 4s\n", + "397750K .......... .......... .......... .......... .......... 66% 38.8M 4s\n", + "397800K .......... .......... .......... .......... .......... 66% 36.7M 4s\n", + "397850K .......... .......... .......... .......... .......... 66% 60.1M 4s\n", + "397900K .......... .......... .......... .......... .......... 66% 48.0M 4s\n", + "397950K .......... .......... .......... .......... .......... 66% 43.6M 4s\n", + "398000K .......... .......... .......... .......... .......... 66% 41.1M 4s\n", + "398050K .......... .......... .......... .......... .......... 66% 60.4M 4s\n", + "398100K .......... .......... .......... .......... .......... 66% 54.6M 4s\n", + "398150K .......... .......... .......... .......... .......... 66% 66.1M 4s\n", + "398200K .......... .......... .......... .......... .......... 66% 45.9M 4s\n", + "398250K .......... .......... .......... .......... .......... 66% 44.0M 4s\n", + "398300K .......... .......... .......... .......... .......... 66% 68.7M 4s\n", + "398350K .......... .......... .......... .......... .......... 66% 47.9M 4s\n", + "398400K .......... .......... .......... .......... .......... 66% 46.3M 4s\n", + "398450K .......... .......... .......... .......... .......... 67% 49.1M 4s\n", + "398500K .......... .......... .......... .......... .......... 67% 45.0M 4s\n", + "398550K .......... .......... .......... .......... .......... 67% 60.8M 4s\n", + "398600K .......... .......... .......... .......... .......... 67% 44.4M 4s\n", + "398650K .......... .......... .......... .......... .......... 67% 48.6M 4s\n", + "398700K .......... .......... .......... .......... .......... 67% 48.3M 4s\n", + "398750K .......... .......... .......... .......... .......... 67% 31.7M 4s\n", + "398800K .......... .......... .......... .......... .......... 67% 30.0M 4s\n", + "398850K .......... .......... .......... .......... .......... 67% 37.3M 4s\n", + "398900K .......... .......... .......... .......... .......... 67% 42.9M 4s\n", + "398950K .......... .......... .......... .......... .......... 67% 50.6M 4s\n", + "399000K .......... .......... .......... .......... .......... 67% 40.8M 4s\n", + "399050K .......... .......... .......... .......... .......... 67% 44.5M 4s\n", + "399100K .......... .......... .......... .......... .......... 67% 49.4M 4s\n", + "399150K .......... .......... .......... .......... .......... 67% 60.4M 4s\n", + "399200K .......... .......... .......... .......... .......... 67% 40.5M 4s\n", + "399250K .......... .......... .......... .......... .......... 67% 44.8M 4s\n", + "399300K .......... .......... .......... .......... .......... 67% 40.6M 4s\n", + "399350K .......... .......... .......... .......... .......... 67% 59.6M 4s\n", + "399400K .......... .......... .......... .......... .......... 67% 41.2M 4s\n", + "399450K .......... .......... .......... .......... .......... 67% 37.9M 4s\n", + "399500K .......... .......... .......... .......... .......... 67% 41.4M 4s\n", + "399550K .......... .......... .......... .......... .......... 67% 59.9M 4s\n", + "399600K .......... .......... .......... .......... .......... 67% 4.09M 4s\n", + "399650K .......... .......... .......... .......... .......... 67% 73.2M 4s\n", + "399700K .......... .......... .......... .......... .......... 67% 71.7M 4s\n", + "399750K .......... .......... .......... .......... .......... 67% 66.2M 4s\n", + "399800K .......... .......... .......... .......... .......... 67% 51.0M 4s\n", + "399850K .......... .......... .......... .......... .......... 67% 27.6M 4s\n", + "399900K .......... .......... .......... .......... .......... 67% 38.4M 4s\n", + "399950K .......... .......... .......... .......... .......... 67% 45.9M 4s\n", + "400000K .......... .......... .......... .......... .......... 67% 36.0M 4s\n", + "400050K .......... .......... .......... .......... .......... 67% 45.4M 4s\n", + "400100K .......... .......... .......... .......... .......... 67% 53.3M 4s\n", + "400150K .......... .......... .......... .......... .......... 67% 66.4M 4s\n", + "400200K .......... .......... .......... .......... .......... 67% 59.2M 4s\n", + "400250K .......... .......... .......... .......... .......... 67% 43.9M 4s\n", + "400300K .......... .......... .......... .......... .......... 67% 38.4M 4s\n", + "400350K .......... .......... .......... .......... .......... 67% 57.0M 4s\n", + "400400K .......... .......... .......... .......... .......... 67% 58.7M 4s\n", + "400450K .......... .......... .......... .......... .......... 67% 71.6M 4s\n", + "400500K .......... .......... .......... .......... .......... 67% 53.1M 4s\n", + "400550K .......... .......... .......... .......... .......... 67% 29.8M 4s\n", + "400600K .......... .......... .......... .......... .......... 67% 58.8M 4s\n", + "400650K .......... .......... .......... .......... .......... 67% 72.4M 4s\n", + "400700K .......... .......... .......... .......... .......... 67% 68.2M 4s\n", + "400750K .......... .......... .......... .......... .......... 67% 41.9M 4s\n", + "400800K .......... .......... .......... .......... .......... 67% 35.8M 4s\n", + "400850K .......... .......... .......... .......... .......... 67% 64.2M 4s\n", + "400900K .......... .......... .......... .......... .......... 67% 67.2M 4s\n", + "400950K .......... .......... .......... .......... .......... 67% 56.5M 4s\n", + "401000K .......... .......... .......... .......... .......... 67% 27.6M 4s\n", + "401050K .......... .......... .......... .......... .......... 67% 54.1M 4s\n", + "401100K .......... .......... .......... .......... .......... 67% 69.1M 4s\n", + "401150K .......... .......... .......... .......... .......... 67% 48.0M 4s\n", + "401200K .......... .......... .......... .......... .......... 67% 30.5M 4s\n", + "401250K .......... .......... .......... .......... .......... 67% 43.1M 4s\n", + "401300K .......... .......... .......... .......... .......... 67% 45.5M 4s\n", + "401350K .......... .......... .......... .......... .......... 67% 36.2M 4s\n", + "401400K .......... .......... .......... .......... .......... 67% 27.4M 4s\n", + "401450K .......... .......... .......... .......... .......... 67% 60.5M 4s\n", + "401500K .......... .......... .......... .......... .......... 67% 69.1M 4s\n", + "401550K .......... .......... .......... .......... .......... 67% 46.9M 4s\n", + "401600K .......... .......... .......... .......... .......... 67% 51.5M 4s\n", + "401650K .......... .......... .......... .......... .......... 67% 34.9M 4s\n", + "401700K .......... .......... .......... .......... .......... 67% 63.5M 4s\n", + "401750K .......... .......... .......... .......... .......... 67% 52.4M 4s\n", + "401800K .......... .......... .......... .......... .......... 67% 51.0M 4s\n", + "401850K .......... .......... .......... .......... .......... 67% 47.9M 4s\n", + "401900K .......... .......... .......... .......... .......... 67% 41.3M 4s\n", + "401950K .......... .......... .......... .......... .......... 67% 69.0M 4s\n", + "402000K .......... .......... .......... .......... .......... 67% 47.8M 4s\n", + "402050K .......... .......... .......... .......... .......... 67% 49.6M 4s\n", + "402100K .......... .......... .......... .......... .......... 67% 38.8M 4s\n", + "402150K .......... .......... .......... .......... .......... 67% 43.1M 4s\n", + "402200K .......... .......... .......... .......... .......... 67% 42.5M 4s\n", + "402250K .......... .......... .......... .......... .......... 67% 58.5M 4s\n", + "402300K .......... .......... .......... .......... .......... 67% 46.6M 4s\n", + "402350K .......... .......... .......... .......... .......... 67% 42.6M 4s\n", + "402400K .......... .......... .......... .......... .......... 67% 36.0M 4s\n", + "402450K .......... .......... .......... .......... .......... 67% 71.5M 4s\n", + "402500K .......... .......... .......... .......... .......... 67% 32.4M 4s\n", + "402550K .......... .......... .......... .......... .......... 67% 37.2M 4s\n", + "402600K .......... .......... .......... .......... .......... 67% 4.24M 4s\n", + "402650K .......... .......... .......... .......... .......... 67% 68.8M 4s\n", + "402700K .......... .......... .......... .......... .......... 67% 70.5M 4s\n", + "402750K .......... .......... .......... .......... .......... 67% 69.7M 4s\n", + "402800K .......... .......... .......... .......... .......... 67% 58.0M 4s\n", + "402850K .......... .......... .......... .......... .......... 67% 72.4M 4s\n", + "402900K .......... .......... .......... .......... .......... 67% 33.2M 4s\n", + "402950K .......... .......... .......... .......... .......... 67% 58.3M 4s\n", + "403000K .......... .......... .......... .......... .......... 67% 59.0M 4s\n", + "403050K .......... .......... .......... .......... .......... 67% 72.1M 4s\n", + "403100K .......... .......... .......... .......... .......... 67% 65.7M 4s\n", + "403150K .......... .......... .......... .......... .......... 67% 43.4M 4s\n", + "403200K .......... .......... .......... .......... .......... 67% 37.9M 4s\n", + "403250K .......... .......... .......... .......... .......... 67% 66.1M 4s\n", + "403300K .......... .......... .......... .......... .......... 67% 63.8M 4s\n", + "403350K .......... .......... .......... .......... .......... 67% 41.7M 4s\n", + "403400K .......... .......... .......... .......... .......... 67% 23.9M 4s\n", + "403450K .......... .......... .......... .......... .......... 67% 64.9M 4s\n", + "403500K .......... .......... .......... .......... .......... 67% 64.5M 4s\n", + "403550K .......... .......... .......... .......... .......... 67% 60.2M 4s\n", + "403600K .......... .......... .......... .......... .......... 67% 38.4M 4s\n", + "403650K .......... .......... .......... .......... .......... 67% 52.0M 4s\n", + "403700K .......... .......... .......... .......... .......... 67% 59.4M 4s\n", + "403750K .......... .......... .......... .......... .......... 67% 68.0M 4s\n", + "403800K .......... .......... .......... .......... .......... 67% 25.8M 4s\n", + "403850K .......... .......... .......... .......... .......... 67% 56.8M 4s\n", + "403900K .......... .......... .......... .......... .......... 67% 48.2M 4s\n", + "403950K .......... .......... .......... .......... .......... 67% 68.6M 4s\n", + "404000K .......... .......... .......... .......... .......... 67% 23.1M 4s\n", + "404050K .......... .......... .......... .......... .......... 67% 45.0M 4s\n", + "404100K .......... .......... .......... .......... .......... 67% 46.3M 4s\n", + "404150K .......... .......... .......... .......... .......... 67% 62.7M 4s\n", + "404200K .......... .......... .......... .......... .......... 67% 27.5M 4s\n", + "404250K .......... .......... .......... .......... .......... 67% 33.0M 4s\n", + "404300K .......... .......... .......... .......... .......... 67% 68.5M 4s\n", + "404350K .......... .......... .......... .......... .......... 67% 41.6M 4s\n", + "404400K .......... .......... .......... .......... .......... 68% 47.0M 4s\n", + "404450K .......... .......... .......... .......... .......... 68% 41.7M 4s\n", + "404500K .......... .......... .......... .......... .......... 68% 51.8M 4s\n", + "404550K .......... .......... .......... .......... .......... 68% 11.8M 4s\n", + "404600K .......... .......... .......... .......... .......... 68% 42.9M 4s\n", + "404650K .......... .......... .......... .......... .......... 68% 64.9M 4s\n", + "404700K .......... .......... .......... .......... .......... 68% 65.4M 4s\n", + "404750K .......... .......... .......... .......... .......... 68% 30.6M 4s\n", + "404800K .......... .......... .......... .......... .......... 68% 35.4M 4s\n", + "404850K .......... .......... .......... .......... .......... 68% 71.2M 4s\n", + "404900K .......... .......... .......... .......... .......... 68% 68.9M 4s\n", + "404950K .......... .......... .......... .......... .......... 68% 28.8M 4s\n", + "405000K .......... .......... .......... .......... .......... 68% 32.0M 4s\n", + "405050K .......... .......... .......... .......... .......... 68% 74.8M 4s\n", + "405100K .......... .......... .......... .......... .......... 68% 66.9M 4s\n", + "405150K .......... .......... .......... .......... .......... 68% 30.4M 4s\n", + "405200K .......... .......... .......... .......... .......... 68% 32.9M 4s\n", + "405250K .......... .......... .......... .......... .......... 68% 63.3M 4s\n", + "405300K .......... .......... .......... .......... .......... 68% 72.3M 4s\n", + "405350K .......... .......... .......... .......... .......... 68% 21.2M 4s\n", + "405400K .......... .......... .......... .......... .......... 68% 38.0M 4s\n", + "405450K .......... .......... .......... .......... .......... 68% 67.1M 4s\n", + "405500K .......... .......... .......... .......... .......... 68% 33.1M 4s\n", + "405550K .......... .......... .......... .......... .......... 68% 35.3M 4s\n", + "405600K .......... .......... .......... .......... .......... 68% 37.9M 4s\n", + "405650K .......... .......... .......... .......... .......... 68% 73.0M 4s\n", + "405700K .......... .......... .......... .......... .......... 68% 31.3M 4s\n", + "405750K .......... .......... .......... .......... .......... 68% 43.7M 4s\n", + "405800K .......... .......... .......... .......... .......... 68% 39.3M 4s\n", + "405850K .......... .......... .......... .......... .......... 68% 68.6M 4s\n", + "405900K .......... .......... .......... .......... .......... 68% 38.3M 4s\n", + "405950K .......... .......... .......... .......... .......... 68% 36.5M 4s\n", + "406000K .......... .......... .......... .......... .......... 68% 37.5M 4s\n", + "406050K .......... .......... .......... .......... .......... 68% 66.1M 4s\n", + "406100K .......... .......... .......... .......... .......... 68% 37.1M 4s\n", + "406150K .......... .......... .......... .......... .......... 68% 34.4M 4s\n", + "406200K .......... .......... .......... .......... .......... 68% 40.5M 4s\n", + "406250K .......... .......... .......... .......... .......... 68% 78.7M 4s\n", + "406300K .......... .......... .......... .......... .......... 68% 48.8M 4s\n", + "406350K .......... .......... .......... .......... .......... 68% 38.3M 4s\n", + "406400K .......... .......... .......... .......... .......... 68% 40.7M 4s\n", + "406450K .......... .......... .......... .......... .......... 68% 73.6M 4s\n", + "406500K .......... .......... .......... .......... .......... 68% 30.1M 4s\n", + "406550K .......... .......... .......... .......... .......... 68% 45.0M 4s\n", + "406600K .......... .......... .......... .......... .......... 68% 32.6M 4s\n", + "406650K .......... .......... .......... .......... .......... 68% 72.1M 4s\n", + "406700K .......... .......... .......... .......... .......... 68% 43.5M 4s\n", + "406750K .......... .......... .......... .......... .......... 68% 34.0M 4s\n", + "406800K .......... .......... .......... .......... .......... 68% 39.8M 4s\n", + "406850K .......... .......... .......... .......... .......... 68% 70.1M 4s\n", + "406900K .......... .......... .......... .......... .......... 68% 39.5M 4s\n", + "406950K .......... .......... .......... .......... .......... 68% 38.0M 4s\n", + "407000K .......... .......... .......... .......... .......... 68% 36.3M 4s\n", + "407050K .......... .......... .......... .......... .......... 68% 75.3M 4s\n", + "407100K .......... .......... .......... .......... .......... 68% 38.2M 4s\n", + "407150K .......... .......... .......... .......... .......... 68% 8.81M 4s\n", + "407200K .......... .......... .......... .......... .......... 68% 60.9M 4s\n", + "407250K .......... .......... .......... .......... .......... 68% 74.7M 4s\n", + "407300K .......... .......... .......... .......... .......... 68% 78.1M 4s\n", + "407350K .......... .......... .......... .......... .......... 68% 18.8M 4s\n", + "407400K .......... .......... .......... .......... .......... 68% 61.2M 4s\n", + "407450K .......... .......... .......... .......... .......... 68% 81.0M 4s\n", + "407500K .......... .......... .......... .......... .......... 68% 70.4M 4s\n", + "407550K .......... .......... .......... .......... .......... 68% 24.0M 4s\n", + "407600K .......... .......... .......... .......... .......... 68% 39.1M 4s\n", + "407650K .......... .......... .......... .......... .......... 68% 46.8M 4s\n", + "407700K .......... .......... .......... .......... .......... 68% 59.1M 4s\n", + "407750K .......... .......... .......... .......... .......... 68% 3.77M 4s\n", + "407800K .......... .......... .......... .......... .......... 68% 44.1M 4s\n", + "407850K .......... .......... .......... .......... .......... 68% 69.1M 4s\n", + "407900K .......... .......... .......... .......... .......... 68% 70.9M 4s\n", + "407950K .......... .......... .......... .......... .......... 68% 65.0M 4s\n", + "408000K .......... .......... .......... .......... .......... 68% 19.4M 4s\n", + "408050K .......... .......... .......... .......... .......... 68% 52.6M 4s\n", + "408100K .......... .......... .......... .......... .......... 68% 78.1M 4s\n", + "408150K .......... .......... .......... .......... .......... 68% 63.9M 4s\n", + "408200K .......... .......... .......... .......... .......... 68% 25.3M 4s\n", + "408250K .......... .......... .......... .......... .......... 68% 54.4M 4s\n", + "408300K .......... .......... .......... .......... .......... 68% 56.7M 4s\n", + "408350K .......... .......... .......... .......... .......... 68% 75.0M 4s\n", + "408400K .......... .......... .......... .......... .......... 68% 25.3M 4s\n", + "408450K .......... .......... .......... .......... .......... 68% 45.5M 4s\n", + "408500K .......... .......... .......... .......... .......... 68% 52.3M 4s\n", + "408550K .......... .......... .......... .......... .......... 68% 66.3M 4s\n", + "408600K .......... .......... .......... .......... .......... 68% 26.3M 4s\n", + "408650K .......... .......... .......... .......... .......... 68% 47.4M 4s\n", + "408700K .......... .......... .......... .......... .......... 68% 56.2M 4s\n", + "408750K .......... .......... .......... .......... .......... 68% 53.8M 4s\n", + "408800K .......... .......... .......... .......... .......... 68% 66.6M 4s\n", + "408850K .......... .......... .......... .......... .......... 68% 25.9M 4s\n", + "408900K .......... .......... .......... .......... .......... 68% 50.0M 4s\n", + "408950K .......... .......... .......... .......... .......... 68% 69.1M 4s\n", + "409000K .......... .......... .......... .......... .......... 68% 61.1M 4s\n", + "409050K .......... .......... .......... .......... .......... 68% 37.5M 4s\n", + "409100K .......... .......... .......... .......... .......... 68% 56.5M 4s\n", + "409150K .......... .......... .......... .......... .......... 68% 16.8M 4s\n", + "409200K .......... .......... .......... .......... .......... 68% 54.6M 4s\n", + "409250K .......... .......... .......... .......... .......... 68% 55.3M 4s\n", + "409300K .......... .......... .......... .......... .......... 68% 67.2M 4s\n", + "409350K .......... .......... .......... .......... .......... 68% 73.7M 4s\n", + "409400K .......... .......... .......... .......... .......... 68% 46.0M 4s\n", + "409450K .......... .......... .......... .......... .......... 68% 51.1M 4s\n", + "409500K .......... .......... .......... .......... .......... 68% 49.3M 4s\n", + "409550K .......... .......... .......... .......... .......... 68% 58.8M 4s\n", + "409600K .......... .......... .......... .......... .......... 68% 67.5M 4s\n", + "409650K .......... .......... .......... .......... .......... 68% 28.0M 4s\n", + "409700K .......... .......... .......... .......... .......... 68% 50.1M 4s\n", + "409750K .......... .......... .......... .......... .......... 68% 65.9M 4s\n", + "409800K .......... .......... .......... .......... .......... 68% 47.2M 4s\n", + "409850K .......... .......... .......... .......... .......... 68% 39.0M 4s\n", + "409900K .......... .......... .......... .......... .......... 68% 47.0M 4s\n", + "409950K .......... .......... .......... .......... .......... 68% 38.8M 4s\n", + "410000K .......... .......... .......... .......... .......... 68% 60.4M 4s\n", + "410050K .......... .......... .......... .......... .......... 68% 43.9M 4s\n", + "410100K .......... .......... .......... .......... .......... 68% 62.7M 4s\n", + "410150K .......... .......... .......... .......... .......... 68% 60.0M 4s\n", + "410200K .......... .......... .......... .......... .......... 68% 39.8M 4s\n", + "410250K .......... .......... .......... .......... .......... 68% 73.9M 4s\n", + "410300K .......... .......... .......... .......... .......... 68% 26.5M 4s\n", + "410350K .......... .......... .......... .......... .......... 69% 40.1M 4s\n", + "410400K .......... .......... .......... .......... .......... 69% 56.3M 4s\n", + "410450K .......... .......... .......... .......... .......... 69% 56.8M 4s\n", + "410500K .......... .......... .......... .......... .......... 69% 57.8M 4s\n", + "410550K .......... .......... .......... .......... .......... 69% 32.4M 4s\n", + "410600K .......... .......... .......... .......... .......... 69% 50.2M 4s\n", + "410650K .......... .......... .......... .......... .......... 69% 58.1M 4s\n", + "410700K .......... .......... .......... .......... .......... 69% 46.3M 4s\n", + "410750K .......... .......... .......... .......... .......... 69% 48.3M 4s\n", + "410800K .......... .......... .......... .......... .......... 69% 41.6M 4s\n", + "410850K .......... .......... .......... .......... .......... 69% 59.2M 4s\n", + "410900K .......... .......... .......... .......... .......... 69% 58.8M 4s\n", + "410950K .......... .......... .......... .......... .......... 69% 60.3M 4s\n", + "411000K .......... .......... .......... .......... .......... 69% 30.9M 4s\n", + "411050K .......... .......... .......... .......... .......... 69% 50.5M 4s\n", + "411100K .......... .......... .......... .......... .......... 69% 54.5M 4s\n", + "411150K .......... .......... .......... .......... .......... 69% 55.4M 4s\n", + "411200K .......... .......... .......... .......... .......... 69% 5.35M 4s\n", + "411250K .......... .......... .......... .......... .......... 69% 19.8M 4s\n", + "411300K .......... .......... .......... .......... .......... 69% 67.7M 4s\n", + "411350K .......... .......... .......... .......... .......... 69% 67.2M 4s\n", + "411400K .......... .......... .......... .......... .......... 69% 40.8M 4s\n", + "411450K .......... .......... .......... .......... .......... 69% 56.6M 4s\n", + "411500K .......... .......... .......... .......... .......... 69% 66.7M 4s\n", + "411550K .......... .......... .......... .......... .......... 69% 65.2M 4s\n", + "411600K .......... .......... .......... .......... .......... 69% 67.3M 4s\n", + "411650K .......... .......... .......... .......... .......... 69% 20.4M 4s\n", + "411700K .......... .......... .......... .......... .......... 69% 59.0M 4s\n", + "411750K .......... .......... .......... .......... .......... 69% 61.9M 4s\n", + "411800K .......... .......... .......... .......... .......... 69% 57.4M 4s\n", + "411850K .......... .......... .......... .......... .......... 69% 19.9M 4s\n", + "411900K .......... .......... .......... .......... .......... 69% 51.7M 4s\n", + "411950K .......... .......... .......... .......... .......... 69% 54.8M 4s\n", + "412000K .......... .......... .......... .......... .......... 69% 20.0M 4s\n", + "412050K .......... .......... .......... .......... .......... 69% 52.9M 4s\n", + "412100K .......... .......... .......... .......... .......... 69% 55.1M 4s\n", + "412150K .......... .......... .......... .......... .......... 69% 57.8M 4s\n", + "412200K .......... .......... .......... .......... .......... 69% 59.4M 4s\n", + "412250K .......... .......... .......... .......... .......... 69% 68.5M 4s\n", + "412300K .......... .......... .......... .......... .......... 69% 65.1M 4s\n", + "412350K .......... .......... .......... .......... .......... 69% 44.3M 4s\n", + "412400K .......... .......... .......... .......... .......... 69% 45.0M 4s\n", + "412450K .......... .......... .......... .......... .......... 69% 66.0M 4s\n", + "412500K .......... .......... .......... .......... .......... 69% 63.2M 4s\n", + "412550K .......... .......... .......... .......... .......... 69% 42.2M 4s\n", + "412600K .......... .......... .......... .......... .......... 69% 47.3M 4s\n", + "412650K .......... .......... .......... .......... .......... 69% 50.5M 4s\n", + "412700K .......... .......... .......... .......... .......... 69% 74.5M 4s\n", + "412750K .......... .......... .......... .......... .......... 69% 36.5M 4s\n", + "412800K .......... .......... .......... .......... .......... 69% 43.9M 4s\n", + "412850K .......... .......... .......... .......... .......... 69% 51.5M 4s\n", + "412900K .......... .......... .......... .......... .......... 69% 56.2M 4s\n", + "412950K .......... .......... .......... .......... .......... 69% 71.3M 4s\n", + "413000K .......... .......... .......... .......... .......... 69% 28.7M 4s\n", + "413050K .......... .......... .......... .......... .......... 69% 58.9M 4s\n", + "413100K .......... .......... .......... .......... .......... 69% 55.7M 4s\n", + "413150K .......... .......... .......... .......... .......... 69% 63.0M 4s\n", + "413200K .......... .......... .......... .......... .......... 69% 32.6M 4s\n", + "413250K .......... .......... .......... .......... .......... 69% 31.4M 4s\n", + "413300K .......... .......... .......... .......... .......... 69% 46.5M 4s\n", + "413350K .......... .......... .......... .......... .......... 69% 74.4M 4s\n", + "413400K .......... .......... .......... .......... .......... 69% 60.2M 4s\n", + "413450K .......... .......... .......... .......... .......... 69% 42.9M 4s\n", + "413500K .......... .......... .......... .......... .......... 69% 45.6M 4s\n", + "413550K .......... .......... .......... .......... .......... 69% 46.4M 4s\n", + "413600K .......... .......... .......... .......... .......... 69% 62.9M 4s\n", + "413650K .......... .......... .......... .......... .......... 69% 60.2M 4s\n", + "413700K .......... .......... .......... .......... .......... 69% 44.3M 4s\n", + "413750K .......... .......... .......... .......... .......... 69% 35.0M 4s\n", + "413800K .......... .......... .......... .......... .......... 69% 47.6M 4s\n", + "413850K .......... .......... .......... .......... .......... 69% 51.0M 4s\n", + "413900K .......... .......... .......... .......... .......... 69% 39.1M 4s\n", + "413950K .......... .......... .......... .......... .......... 69% 39.2M 4s\n", + "414000K .......... .......... .......... .......... .......... 69% 48.5M 4s\n", + "414050K .......... .......... .......... .......... .......... 69% 51.5M 4s\n", + "414100K .......... .......... .......... .......... .......... 69% 53.5M 4s\n", + "414150K .......... .......... .......... .......... .......... 69% 37.3M 4s\n", + "414200K .......... .......... .......... .......... .......... 69% 4.35M 4s\n", + "414250K .......... .......... .......... .......... .......... 69% 68.5M 4s\n", + "414300K .......... .......... .......... .......... .......... 69% 59.9M 4s\n", + "414350K .......... .......... .......... .......... .......... 69% 65.1M 4s\n", + "414400K .......... .......... .......... .......... .......... 69% 69.5M 4s\n", + "414450K .......... .......... .......... .......... .......... 69% 45.8M 4s\n", + "414500K .......... .......... .......... .......... .......... 69% 56.9M 4s\n", + "414550K .......... .......... .......... .......... .......... 69% 69.0M 4s\n", + "414600K .......... .......... .......... .......... .......... 69% 63.7M 4s\n", + "414650K .......... .......... .......... .......... .......... 69% 81.0M 4s\n", + "414700K .......... .......... .......... .......... .......... 69% 18.1M 4s\n", + "414750K .......... .......... .......... .......... .......... 69% 48.5M 4s\n", + "414800K .......... .......... .......... .......... .......... 69% 55.9M 4s\n", + "414850K .......... .......... .......... .......... .......... 69% 23.7M 4s\n", + "414900K .......... .......... .......... .......... .......... 69% 42.7M 4s\n", + "414950K .......... .......... .......... .......... .......... 69% 67.6M 4s\n", + "415000K .......... .......... .......... .......... .......... 69% 52.6M 4s\n", + "415050K .......... .......... .......... .......... .......... 69% 16.9M 4s\n", + "415100K .......... .......... .......... .......... .......... 69% 64.7M 4s\n", + "415150K .......... .......... .......... .......... .......... 69% 51.2M 4s\n", + "415200K .......... .......... .......... .......... .......... 69% 14.1M 4s\n", + "415250K .......... .......... .......... .......... .......... 69% 51.4M 4s\n", + "415300K .......... .......... .......... .......... .......... 69% 52.7M 4s\n", + "415350K .......... .......... .......... .......... .......... 69% 30.6M 4s\n", + "415400K .......... .......... .......... .......... .......... 69% 27.8M 4s\n", + "415450K .......... .......... .......... .......... .......... 69% 57.5M 4s\n", + "415500K .......... .......... .......... .......... .......... 69% 27.3M 4s\n", + "415550K .......... .......... .......... .......... .......... 69% 36.0M 4s\n", + "415600K .......... .......... .......... .......... .......... 69% 40.9M 4s\n", + "415650K .......... .......... .......... .......... .......... 69% 70.7M 4s\n", + "415700K .......... .......... .......... .......... .......... 69% 21.2M 4s\n", + "415750K .......... .......... .......... .......... .......... 69% 36.5M 4s\n", + "415800K .......... .......... .......... .......... .......... 69% 49.2M 4s\n", + "415850K .......... .......... .......... .......... .......... 69% 11.5M 4s\n", + "415900K .......... .......... .......... .......... .......... 69% 76.2M 4s\n", + "415950K .......... .......... .......... .......... .......... 69% 67.2M 4s\n", + "416000K .......... .......... .......... .......... .......... 69% 5.19M 4s\n", + "416050K .......... .......... .......... .......... .......... 69% 44.7M 4s\n", + "416100K .......... .......... .......... .......... .......... 69% 69.7M 4s\n", + "416150K .......... .......... .......... .......... .......... 69% 18.4M 4s\n", + "416200K .......... .......... .......... .......... .......... 69% 43.4M 4s\n", + "416250K .......... .......... .......... .......... .......... 69% 54.3M 4s\n", + "416300K .......... .......... .......... .......... .......... 70% 20.5M 4s\n", + "416350K .......... .......... .......... .......... .......... 70% 37.6M 4s\n", + "416400K .......... .......... .......... .......... .......... 70% 46.5M 4s\n", + "416450K .......... .......... .......... .......... .......... 70% 75.2M 4s\n", + "416500K .......... .......... .......... .......... .......... 70% 26.2M 4s\n", + "416550K .......... .......... .......... .......... .......... 70% 35.2M 4s\n", + "416600K .......... .......... .......... .......... .......... 70% 39.8M 4s\n", + "416650K .......... .......... .......... .......... .......... 70% 23.6M 4s\n", + "416700K .......... .......... .......... .......... .......... 70% 44.3M 4s\n", + "416750K .......... .......... .......... .......... .......... 70% 47.9M 4s\n", + "416800K .......... .......... .......... .......... .......... 70% 22.1M 4s\n", + "416850K .......... .......... .......... .......... .......... 70% 47.7M 4s\n", + "416900K .......... .......... .......... .......... .......... 70% 52.9M 4s\n", + "416950K .......... .......... .......... .......... .......... 70% 20.2M 4s\n", + "417000K .......... .......... .......... .......... .......... 70% 36.8M 4s\n", + "417050K .......... .......... .......... .......... .......... 70% 52.6M 4s\n", + "417100K .......... .......... .......... .......... .......... 70% 54.6M 4s\n", + "417150K .......... .......... .......... .......... .......... 70% 27.1M 4s\n", + "417200K .......... .......... .......... .......... .......... 70% 36.4M 4s\n", + "417250K .......... .......... .......... .......... .......... 70% 62.8M 4s\n", + "417300K .......... .......... .......... .......... .......... 70% 21.3M 4s\n", + "417350K .......... .......... .......... .......... .......... 70% 30.9M 4s\n", + "417400K .......... .......... .......... .......... .......... 70% 52.0M 4s\n", + "417450K .......... .......... .......... .......... .......... 70% 22.1M 4s\n", + "417500K .......... .......... .......... .......... .......... 70% 36.4M 4s\n", + "417550K .......... .......... .......... .......... .......... 70% 55.1M 4s\n", + "417600K .......... .......... .......... .......... .......... 70% 22.7M 4s\n", + "417650K .......... .......... .......... .......... .......... 70% 40.1M 4s\n", + "417700K .......... .......... .......... .......... .......... 70% 50.6M 4s\n", + "417750K .......... .......... .......... .......... .......... 70% 64.7M 4s\n", + "417800K .......... .......... .......... .......... .......... 70% 18.7M 4s\n", + "417850K .......... .......... .......... .......... .......... 70% 41.8M 4s\n", + "417900K .......... .......... .......... .......... .......... 70% 66.0M 4s\n", + "417950K .......... .......... .......... .......... .......... 70% 22.6M 4s\n", + "418000K .......... .......... .......... .......... .......... 70% 30.7M 4s\n", + "418050K .......... .......... .......... .......... .......... 70% 63.9M 4s\n", + "418100K .......... .......... .......... .......... .......... 70% 23.5M 4s\n", + "418150K .......... .......... .......... .......... .......... 70% 32.3M 4s\n", + "418200K .......... .......... .......... .......... .......... 70% 43.0M 4s\n", + "418250K .......... .......... .......... .......... .......... 70% 28.8M 4s\n", + "418300K .......... .......... .......... .......... .......... 70% 50.4M 4s\n", + "418350K .......... .......... .......... .......... .......... 70% 31.9M 4s\n", + "418400K .......... .......... .......... .......... .......... 70% 58.6M 4s\n", + "418450K .......... .......... .......... .......... .......... 70% 19.6M 4s\n", + "418500K .......... .......... .......... .......... .......... 70% 29.7M 4s\n", + "418550K .......... .......... .......... .......... .......... 70% 46.9M 4s\n", + "418600K .......... .......... .......... .......... .......... 70% 37.2M 4s\n", + "418650K .......... .......... .......... .......... .......... 70% 41.6M 4s\n", + "418700K .......... .......... .......... .......... .......... 70% 42.6M 4s\n", + "418750K .......... .......... .......... .......... .......... 70% 37.8M 4s\n", + "418800K .......... .......... .......... .......... .......... 70% 9.91K 6s\n", + "418850K .......... .......... .......... .......... .......... 70% 462K 6s\n", + "418900K .......... .......... .......... .......... .......... 70% 1.49M 6s\n", + "418950K .......... .......... .......... .......... .......... 70% 630K 6s\n", + "419000K .......... .......... .......... .......... .......... 70% 1.54M 6s\n", + "419050K .......... .......... .......... .......... .......... 70% 51.6M 6s\n", + "419100K .......... .......... .......... .......... .......... 70% 55.8M 6s\n", + "419150K .......... .......... .......... .......... .......... 70% 52.6M 6s\n", + "419200K .......... .......... .......... .......... .......... 70% 58.3M 6s\n", + "419250K .......... .......... .......... .......... .......... 70% 37.9M 6s\n", + "419300K .......... .......... .......... .......... .......... 70% 42.8M 6s\n", + "419350K .......... .......... .......... .......... .......... 70% 46.1M 6s\n", + "419400K .......... .......... .......... .......... .......... 70% 44.2M 6s\n", + "419450K .......... .......... .......... .......... .......... 70% 32.5M 6s\n", + "419500K .......... .......... .......... .......... .......... 70% 36.2M 6s\n", + "419550K .......... .......... .......... .......... .......... 70% 45.8M 6s\n", + "419600K .......... .......... .......... .......... .......... 70% 46.9M 6s\n", + "419650K .......... .......... .......... .......... .......... 70% 40.9M 6s\n", + "419700K .......... .......... .......... .......... .......... 70% 41.2M 6s\n", + "419750K .......... .......... .......... .......... .......... 70% 45.5M 6s\n", + "419800K .......... .......... .......... .......... .......... 70% 48.2M 6s\n", + "419850K .......... .......... .......... .......... .......... 70% 31.0M 6s\n", + "419900K .......... .......... .......... .......... .......... 70% 3.93M 6s\n", + "419950K .......... .......... .......... .......... .......... 70% 61.0M 6s\n", + "420000K .......... .......... .......... .......... .......... 70% 42.3M 6s\n", + "420050K .......... .......... .......... .......... .......... 70% 58.2M 6s\n", + "420100K .......... .......... .......... .......... .......... 70% 63.6M 6s\n", + "420150K .......... .......... .......... .......... .......... 70% 42.3M 6s\n", + "420200K .......... .......... .......... .......... .......... 70% 39.3M 6s\n", + "420250K .......... .......... .......... .......... .......... 70% 58.6M 6s\n", + "420300K .......... .......... .......... .......... .......... 70% 65.5M 6s\n", + "420350K .......... .......... .......... .......... .......... 70% 52.8M 6s\n", + "420400K .......... .......... .......... .......... .......... 70% 26.0M 6s\n", + "420450K .......... .......... .......... .......... .......... 70% 59.4M 6s\n", + "420500K .......... .......... .......... .......... .......... 70% 18.3M 6s\n", + "420550K .......... .......... .......... .......... .......... 70% 34.2M 6s\n", + "420600K .......... .......... .......... .......... .......... 70% 49.7M 6s\n", + "420650K .......... .......... .......... .......... .......... 70% 60.2M 6s\n", + "420700K .......... .......... .......... .......... .......... 70% 58.8M 6s\n", + "420750K .......... .......... .......... .......... .......... 70% 43.3M 6s\n", + "420800K .......... .......... .......... .......... .......... 70% 34.9M 6s\n", + "420850K .......... .......... .......... .......... .......... 70% 58.6M 6s\n", + "420900K .......... .......... .......... .......... .......... 70% 46.9M 6s\n", + "420950K .......... .......... .......... .......... .......... 70% 42.8M 6s\n", + "421000K .......... .......... .......... .......... .......... 70% 29.8M 6s\n", + "421050K .......... .......... .......... .......... .......... 70% 63.3M 6s\n", + "421100K .......... .......... .......... .......... .......... 70% 46.3M 6s\n", + "421150K .......... .......... .......... .......... .......... 70% 47.2M 6s\n", + "421200K .......... .......... .......... .......... .......... 70% 34.4M 6s\n", + "421250K .......... .......... .......... .......... .......... 70% 51.2M 6s\n", + "421300K .......... .......... .......... .......... .......... 70% 50.5M 6s\n", + "421350K .......... .......... .......... .......... .......... 70% 37.6M 6s\n", + "421400K .......... .......... .......... .......... .......... 70% 27.4M 6s\n", + "421450K .......... .......... .......... .......... .......... 70% 55.5M 6s\n", + "421500K .......... .......... .......... .......... .......... 70% 39.8M 6s\n", + "421550K .......... .......... .......... .......... .......... 70% 4.10M 6s\n", + "421600K .......... .......... .......... .......... .......... 70% 53.3M 6s\n", + "421650K .......... .......... .......... .......... .......... 70% 67.8M 6s\n", + "421700K .......... .......... .......... .......... .......... 70% 59.6M 6s\n", + "421750K .......... .......... .......... .......... .......... 70% 62.2M 6s\n", + "421800K .......... .......... .......... .......... .......... 70% 41.8M 6s\n", + "421850K .......... .......... .......... .......... .......... 70% 43.2M 6s\n", + "421900K .......... .......... .......... .......... .......... 70% 62.5M 6s\n", + "421950K .......... .......... .......... .......... .......... 70% 71.8M 6s\n", + "422000K .......... .......... .......... .......... .......... 70% 56.6M 6s\n", + "422050K .......... .......... .......... .......... .......... 70% 40.7M 6s\n", + "422100K .......... .......... .......... .......... .......... 70% 38.9M 6s\n", + "422150K .......... .......... .......... .......... .......... 70% 59.7M 6s\n", + "422200K .......... .......... .......... .......... .......... 70% 54.3M 6s\n", + "422250K .......... .......... .......... .......... .......... 71% 57.2M 6s\n", + "422300K .......... .......... .......... .......... .......... 71% 58.2M 6s\n", + "422350K .......... .......... .......... .......... .......... 71% 35.2M 6s\n", + "422400K .......... .......... .......... .......... .......... 71% 54.7M 6s\n", + "422450K .......... .......... .......... .......... .......... 71% 68.0M 6s\n", + "422500K .......... .......... .......... .......... .......... 71% 57.0M 6s\n", + "422550K .......... .......... .......... .......... .......... 71% 57.2M 6s\n", + "422600K .......... .......... .......... .......... .......... 71% 32.7M 6s\n", + "422650K .......... .......... .......... .......... .......... 71% 62.4M 6s\n", + "422700K .......... .......... .......... .......... .......... 71% 53.8M 6s\n", + "422750K .......... .......... .......... .......... .......... 71% 56.4M 6s\n", + "422800K .......... .......... .......... .......... .......... 71% 44.8M 6s\n", + "422850K .......... .......... .......... .......... .......... 71% 44.3M 6s\n", + "422900K .......... .......... .......... .......... .......... 71% 57.9M 6s\n", + "422950K .......... .......... .......... .......... .......... 71% 57.8M 6s\n", + "423000K .......... .......... .......... .......... .......... 71% 46.0M 6s\n", + "423050K .......... .......... .......... .......... .......... 71% 34.2M 6s\n", + "423100K .......... .......... .......... .......... .......... 71% 66.6M 6s\n", + "423150K .......... .......... .......... .......... .......... 71% 49.6M 6s\n", + "423200K .......... .......... .......... .......... .......... 71% 45.4M 6s\n", + "423250K .......... .......... .......... .......... .......... 71% 40.4M 6s\n", + "423300K .......... .......... .......... .......... .......... 71% 51.7M 6s\n", + "423350K .......... .......... .......... .......... .......... 71% 54.5M 6s\n", + "423400K .......... .......... .......... .......... .......... 71% 41.3M 6s\n", + "423450K .......... .......... .......... .......... .......... 71% 38.6M 6s\n", + "423500K .......... .......... .......... .......... .......... 71% 50.0M 6s\n", + "423550K .......... .......... .......... .......... .......... 71% 56.4M 6s\n", + "423600K .......... .......... .......... .......... .......... 71% 57.1M 6s\n", + "423650K .......... .......... .......... .......... .......... 71% 49.6M 6s\n", + "423700K .......... .......... .......... .......... .......... 71% 40.1M 6s\n", + "423750K .......... .......... .......... .......... .......... 71% 59.1M 6s\n", + "423800K .......... .......... .......... .......... .......... 71% 49.1M 6s\n", + "423850K .......... .......... .......... .......... .......... 71% 59.3M 6s\n", + "423900K .......... .......... .......... .......... .......... 71% 49.6M 6s\n", + "423950K .......... .......... .......... .......... .......... 71% 38.4M 6s\n", + "424000K .......... .......... .......... .......... .......... 71% 51.4M 6s\n", + "424050K .......... .......... .......... .......... .......... 71% 60.4M 6s\n", + "424100K .......... .......... .......... .......... .......... 71% 42.9M 6s\n", + "424150K .......... .......... .......... .......... .......... 71% 37.8M 6s\n", + "424200K .......... .......... .......... .......... .......... 71% 43.7M 6s\n", + "424250K .......... .......... .......... .......... .......... 71% 17.6M 6s\n", + "424300K .......... .......... .......... .......... .......... 71% 43.1M 6s\n", + "424350K .......... .......... .......... .......... .......... 71% 18.1M 6s\n", + "424400K .......... .......... .......... .......... .......... 71% 26.3M 6s\n", + "424450K .......... .......... .......... .......... .......... 71% 22.3M 6s\n", + "424500K .......... .......... .......... .......... .......... 71% 19.1M 6s\n", + "424550K .......... .......... .......... .......... .......... 71% 60.6M 6s\n", + "424600K .......... .......... .......... .......... .......... 71% 14.4M 6s\n", + "424650K .......... .......... .......... .......... .......... 71% 62.3M 6s\n", + "424700K .......... .......... .......... .......... .......... 71% 14.8M 6s\n", + "424750K .......... .......... .......... .......... .......... 71% 47.1M 6s\n", + "424800K .......... .......... .......... .......... .......... 71% 24.4M 6s\n", + "424850K .......... .......... .......... .......... .......... 71% 20.3M 6s\n", + "424900K .......... .......... .......... .......... .......... 71% 26.2M 6s\n", + "424950K .......... .......... .......... .......... .......... 71% 4.63M 6s\n", + "425000K .......... .......... .......... .......... .......... 71% 54.6M 6s\n", + "425050K .......... .......... .......... .......... .......... 71% 68.0M 6s\n", + "425100K .......... .......... .......... .......... .......... 71% 12.7M 6s\n", + "425150K .......... .......... .......... .......... .......... 71% 68.8M 6s\n", + "425200K .......... .......... .......... .......... .......... 71% 13.1M 6s\n", + "425250K .......... .......... .......... .......... .......... 71% 57.7M 6s\n", + "425300K .......... .......... .......... .......... .......... 71% 15.9M 6s\n", + "425350K .......... .......... .......... .......... .......... 71% 37.9M 6s\n", + "425400K .......... .......... .......... .......... .......... 71% 15.2M 6s\n", + "425450K .......... .......... .......... .......... .......... 71% 41.4M 6s\n", + "425500K .......... .......... .......... .......... .......... 71% 58.3M 6s\n", + "425550K .......... .......... .......... .......... .......... 71% 15.1M 6s\n", + "425600K .......... .......... .......... .......... .......... 71% 43.8M 6s\n", + "425650K .......... .......... .......... .......... .......... 71% 15.6M 6s\n", + "425700K .......... .......... .......... .......... .......... 71% 34.9M 6s\n", + "425750K .......... .......... .......... .......... .......... 71% 19.0M 6s\n", + "425800K .......... .......... .......... .......... .......... 71% 30.3M 6s\n", + "425850K .......... .......... .......... .......... .......... 71% 18.3M 6s\n", + "425900K .......... .......... .......... .......... .......... 71% 34.7M 6s\n", + "425950K .......... .......... .......... .......... .......... 71% 49.2M 6s\n", + "426000K .......... .......... .......... .......... .......... 71% 15.4M 6s\n", + "426050K .......... .......... .......... .......... .......... 71% 36.2M 6s\n", + "426100K .......... .......... .......... .......... .......... 71% 17.0M 6s\n", + "426150K .......... .......... .......... .......... .......... 71% 46.9M 6s\n", + "426200K .......... .......... .......... .......... .......... 71% 18.3M 6s\n", + "426250K .......... .......... .......... .......... .......... 71% 32.8M 6s\n", + "426300K .......... .......... .......... .......... .......... 71% 32.4M 6s\n", + "426350K .......... .......... .......... .......... .......... 71% 22.0M 6s\n", + "426400K .......... .......... .......... .......... .......... 71% 28.7M 6s\n", + "426450K .......... .......... .......... .......... .......... 71% 18.6M 6s\n", + "426500K .......... .......... .......... .......... .......... 71% 38.0M 6s\n", + "426550K .......... .......... .......... .......... .......... 71% 31.7M 6s\n", + "426600K .......... .......... .......... .......... .......... 71% 17.1M 6s\n", + "426650K .......... .......... .......... .......... .......... 71% 39.1M 6s\n", + "426700K .......... .......... .......... .......... .......... 71% 20.7M 6s\n", + "426750K .......... .......... .......... .......... .......... 71% 40.1M 6s\n", + "426800K .......... .......... .......... .......... .......... 71% 36.1M 6s\n", + "426850K .......... .......... .......... .......... .......... 71% 17.7M 6s\n", + "426900K .......... .......... .......... .......... .......... 71% 37.0M 6s\n", + "426950K .......... .......... .......... .......... .......... 71% 19.8M 6s\n", + "427000K .......... .......... .......... .......... .......... 71% 24.9M 6s\n", + "427050K .......... .......... .......... .......... .......... 71% 24.5M 6s\n", + "427100K .......... .......... .......... .......... .......... 71% 36.1M 6s\n", + "427150K .......... .......... .......... .......... .......... 71% 37.0M 6s\n", + "427200K .......... .......... .......... .......... .......... 71% 18.1M 6s\n", + "427250K .......... .......... .......... .......... .......... 71% 48.8M 6s\n", + "427300K .......... .......... .......... .......... .......... 71% 43.2M 6s\n", + "427350K .......... .......... .......... .......... .......... 71% 17.1M 6s\n", + "427400K .......... .......... .......... .......... .......... 71% 41.1M 6s\n", + "427450K .......... .......... .......... .......... .......... 71% 18.4M 6s\n", + "427500K .......... .......... .......... .......... .......... 71% 45.3M 6s\n", + "427550K .......... .......... .......... .......... .......... 71% 18.6M 6s\n", + "427600K .......... .......... .......... .......... .......... 71% 34.7M 6s\n", + "427650K .......... .......... .......... .......... .......... 71% 56.6M 6s\n", + "427700K .......... .......... .......... .......... .......... 71% 8.01M 6s\n", + "427750K .......... .......... .......... .......... .......... 71% 46.0M 6s\n", + "427800K .......... .......... .......... .......... .......... 71% 14.6M 6s\n", + "427850K .......... .......... .......... .......... .......... 71% 53.8M 6s\n", + "427900K .......... .......... .......... .......... .......... 71% 63.7M 6s\n", + "427950K .......... .......... .......... .......... .......... 71% 14.7M 6s\n", + "428000K .......... .......... .......... .......... .......... 71% 52.2M 6s\n", + "428050K .......... .......... .......... .......... .......... 71% 16.2M 6s\n", + "428100K .......... .......... .......... .......... .......... 71% 42.1M 6s\n", + "428150K .......... .......... .......... .......... .......... 71% 69.0M 6s\n", + "428200K .......... .......... .......... .......... .......... 72% 14.1M 6s\n", + "428250K .......... .......... .......... .......... .......... 72% 70.0M 6s\n", + "428300K .......... .......... .......... .......... .......... 72% 17.2M 6s\n", + "428350K .......... .......... .......... .......... .......... 72% 48.7M 6s\n", + "428400K .......... .......... .......... .......... .......... 72% 46.7M 6s\n", + "428450K .......... .......... .......... .......... .......... 72% 18.3M 6s\n", + "428500K .......... .......... .......... .......... .......... 72% 39.8M 6s\n", + "428550K .......... .......... .......... .......... .......... 72% 56.7M 6s\n", + "428600K .......... .......... .......... .......... .......... 72% 16.5M 6s\n", + "428650K .......... .......... .......... .......... .......... 72% 49.3M 6s\n", + "428700K .......... .......... .......... .......... .......... 72% 15.9M 6s\n", + "428750K .......... .......... .......... .......... .......... 72% 46.7M 6s\n", + "428800K .......... .......... .......... .......... .......... 72% 43.8M 6s\n", + "428850K .......... .......... .......... .......... .......... 72% 18.9M 6s\n", + "428900K .......... .......... .......... .......... .......... 72% 37.9M 6s\n", + "428950K .......... .......... .......... .......... .......... 72% 69.9M 6s\n", + "429000K .......... .......... .......... .......... .......... 72% 15.0M 6s\n", + "429050K .......... .......... .......... .......... .......... 72% 57.2M 6s\n", + "429100K .......... .......... .......... .......... .......... 72% 67.7M 6s\n", + "429150K .......... .......... .......... .......... .......... 72% 17.9M 6s\n", + "429200K .......... .......... .......... .......... .......... 72% 43.5M 6s\n", + "429250K .......... .......... .......... .......... .......... 72% 17.3M 6s\n", + "429300K .......... .......... .......... .......... .......... 72% 3.79M 6s\n", + "429350K .......... .......... .......... .......... .......... 72% 66.1M 6s\n", + "429400K .......... .......... .......... .......... .......... 72% 59.9M 6s\n", + "429450K .......... .......... .......... .......... .......... 72% 16.2M 6s\n", + "429500K .......... .......... .......... .......... .......... 72% 44.8M 6s\n", + "429550K .......... .......... .......... .......... .......... 72% 67.5M 6s\n", + "429600K .......... .......... .......... .......... .......... 72% 18.0M 6s\n", + "429650K .......... .......... .......... .......... .......... 72% 41.2M 6s\n", + "429700K .......... .......... .......... .......... .......... 72% 70.1M 6s\n", + "429750K .......... .......... .......... .......... .......... 72% 15.1M 6s\n", + "429800K .......... .......... .......... .......... .......... 72% 48.7M 6s\n", + "429850K .......... .......... .......... .......... .......... 72% 72.3M 6s\n", + "429900K .......... .......... .......... .......... .......... 72% 14.9M 6s\n", + "429950K .......... .......... .......... .......... .......... 72% 53.8M 6s\n", + "430000K .......... .......... .......... .......... .......... 72% 61.8M 6s\n", + "430050K .......... .......... .......... .......... .......... 72% 17.3M 6s\n", + "430100K .......... .......... .......... .......... .......... 72% 61.0M 6s\n", + "430150K .......... .......... .......... .......... .......... 72% 75.3M 6s\n", + "430200K .......... .......... .......... .......... .......... 72% 14.8M 6s\n", + "430250K .......... .......... .......... .......... .......... 72% 64.0M 6s\n", + "430300K .......... .......... .......... .......... .......... 72% 21.7M 6s\n", + "430350K .......... .......... .......... .......... .......... 72% 45.3M 6s\n", + "430400K .......... .......... .......... .......... .......... 72% 41.9M 6s\n", + "430450K .......... .......... .......... .......... .......... 72% 21.4M 6s\n", + "430500K .......... .......... .......... .......... .......... 72% 38.7M 6s\n", + "430550K .......... .......... .......... .......... .......... 72% 53.0M 6s\n", + "430600K .......... .......... .......... .......... .......... 72% 19.4M 6s\n", + "430650K .......... .......... .......... .......... .......... 72% 37.3M 6s\n", + "430700K .......... .......... .......... .......... .......... 72% 51.8M 6s\n", + "430750K .......... .......... .......... .......... .......... 72% 3.66M 6s\n", + "430800K .......... .......... .......... .......... .......... 72% 66.2M 6s\n", + "430850K .......... .......... .......... .......... .......... 72% 59.5M 6s\n", + "430900K .......... .......... .......... .......... .......... 72% 66.4M 6s\n", + "430950K .......... .......... .......... .......... .......... 72% 12.4M 6s\n", + "431000K .......... .......... .......... .......... .......... 72% 47.8M 6s\n", + "431050K .......... .......... .......... .......... .......... 72% 17.7M 6s\n", + "431100K .......... .......... .......... .......... .......... 72% 37.9M 6s\n", + "431150K .......... .......... .......... .......... .......... 72% 57.5M 6s\n", + "431200K .......... .......... .......... .......... .......... 72% 18.0M 6s\n", + "431250K .......... .......... .......... .......... .......... 72% 49.7M 6s\n", + "431300K .......... .......... .......... .......... .......... 72% 51.6M 6s\n", + "431350K .......... .......... .......... .......... .......... 72% 65.5M 6s\n", + "431400K .......... .......... .......... .......... .......... 72% 13.9M 6s\n", + "431450K .......... .......... .......... .......... .......... 72% 73.7M 6s\n", + "431500K .......... .......... .......... .......... .......... 72% 9.04M 6s\n", + "431550K .......... .......... .......... .......... .......... 72% 44.8M 6s\n", + "431600K .......... .......... .......... .......... .......... 72% 52.8M 6s\n", + "431650K .......... .......... .......... .......... .......... 72% 19.4M 6s\n", + "431700K .......... .......... .......... .......... .......... 72% 43.1M 6s\n", + "431750K .......... .......... .......... .......... .......... 72% 65.9M 6s\n", + "431800K .......... .......... .......... .......... .......... 72% 17.3M 6s\n", + "431850K .......... .......... .......... .......... .......... 72% 42.6M 6s\n", + "431900K .......... .......... .......... .......... .......... 72% 50.0M 6s\n", + "431950K .......... .......... .......... .......... .......... 72% 21.7M 6s\n", + "432000K .......... .......... .......... .......... .......... 72% 37.0M 6s\n", + "432050K .......... .......... .......... .......... .......... 72% 50.6M 6s\n", + "432100K .......... .......... .......... .......... .......... 72% 21.2M 6s\n", + "432150K .......... .......... .......... .......... .......... 72% 50.9M 6s\n", + "432200K .......... .......... .......... .......... .......... 72% 33.1M 6s\n", + "432250K .......... .......... .......... .......... .......... 72% 23.6M 6s\n", + "432300K .......... .......... .......... .......... .......... 72% 54.0M 6s\n", + "432350K .......... .......... .......... .......... .......... 72% 44.2M 6s\n", + "432400K .......... .......... .......... .......... .......... 72% 50.4M 6s\n", + "432450K .......... .......... .......... .......... .......... 72% 21.7M 6s\n", + "432500K .......... .......... .......... .......... .......... 72% 45.3M 6s\n", + "432550K .......... .......... .......... .......... .......... 72% 55.4M 6s\n", + "432600K .......... .......... .......... .......... .......... 72% 19.9M 6s\n", + "432650K .......... .......... .......... .......... .......... 72% 38.5M 6s\n", + "432700K .......... .......... .......... .......... .......... 72% 62.6M 6s\n", + "432750K .......... .......... .......... .......... .......... 72% 22.8M 6s\n", + "432800K .......... .......... .......... .......... .......... 72% 50.0M 6s\n", + "432850K .......... .......... .......... .......... .......... 72% 3.04M 6s\n", + "432900K .......... .......... .......... .......... .......... 72% 66.4M 6s\n", + "432950K .......... .......... .......... .......... .......... 72% 65.0M 6s\n", + "433000K .......... .......... .......... .......... .......... 72% 54.9M 6s\n", + "433050K .......... .......... .......... .......... .......... 72% 71.6M 6s\n", + "433100K .......... .......... .......... .......... .......... 72% 42.9M 6s\n", + "433150K .......... .......... .......... .......... .......... 72% 38.0M 6s\n", + "433200K .......... .......... .......... .......... .......... 72% 63.8M 6s\n", + "433250K .......... .......... .......... .......... .......... 72% 72.7M 6s\n", + "433300K .......... .......... .......... .......... .......... 72% 18.2M 6s\n", + "433350K .......... .......... .......... .......... .......... 72% 41.6M 6s\n", + "433400K .......... .......... .......... .......... .......... 72% 55.3M 6s\n", + "433450K .......... .......... .......... .......... .......... 72% 24.0M 6s\n", + "433500K .......... .......... .......... .......... .......... 72% 42.6M 6s\n", + "433550K .......... .......... .......... .......... .......... 72% 62.3M 6s\n", + "433600K .......... .......... .......... .......... .......... 72% 25.2M 6s\n", + "433650K .......... .......... .......... .......... .......... 72% 32.4M 6s\n", + "433700K .......... .......... .......... .......... .......... 72% 57.4M 6s\n", + "433750K .......... .......... .......... .......... .......... 72% 76.8M 6s\n", + "433800K .......... .......... .......... .......... .......... 72% 19.7M 6s\n", + "433850K .......... .......... .......... .......... .......... 72% 40.5M 6s\n", + "433900K .......... .......... .......... .......... .......... 72% 65.4M 6s\n", + "433950K .......... .......... .......... .......... .......... 72% 27.4M 6s\n", + "434000K .......... .......... .......... .......... .......... 72% 31.3M 6s\n", + "434050K .......... .......... .......... .......... .......... 72% 66.2M 6s\n", + "434100K .......... .......... .......... .......... .......... 72% 28.8M 6s\n", + "434150K .......... .......... .......... .......... .......... 73% 41.3M 6s\n", + "434200K .......... .......... .......... .......... .......... 73% 35.8M 6s\n", + "434250K .......... .......... .......... .......... .......... 73% 73.4M 6s\n", + "434300K .......... .......... .......... .......... .......... 73% 20.6M 6s\n", + "434350K .......... .......... .......... .......... .......... 73% 47.3M 6s\n", + "434400K .......... .......... .......... .......... .......... 73% 11.6M 6s\n", + "434450K .......... .......... .......... .......... .......... 73% 45.4M 6s\n", + "434500K .......... .......... .......... .......... .......... 73% 68.7M 6s\n", + "434550K .......... .......... .......... .......... .......... 73% 15.3M 6s\n", + "434600K .......... .......... .......... .......... .......... 73% 41.5M 6s\n", + "434650K .......... .......... .......... .......... .......... 73% 15.4M 6s\n", + "434700K .......... .......... .......... .......... .......... 73% 37.5M 6s\n", + "434750K .......... .......... .......... .......... .......... 73% 64.6M 6s\n", + "434800K .......... .......... .......... .......... .......... 73% 16.4M 6s\n", + "434850K .......... .......... .......... .......... .......... 73% 53.9M 6s\n", + "434900K .......... .......... .......... .......... .......... 73% 21.5M 6s\n", + "434950K .......... .......... .......... .......... .......... 73% 28.3M 6s\n", + "435000K .......... .......... .......... .......... .......... 73% 29.3M 6s\n", + "435050K .......... .......... .......... .......... .......... 73% 21.0M 6s\n", + "435100K .......... .......... .......... .......... .......... 73% 45.0M 6s\n", + "435150K .......... .......... .......... .......... .......... 73% 17.7M 6s\n", + "435200K .......... .......... .......... .......... .......... 73% 40.5M 6s\n", + "435250K .......... .......... .......... .......... .......... 73% 45.6M 6s\n", + "435300K .......... .......... .......... .......... .......... 73% 19.4M 6s\n", + "435350K .......... .......... .......... .......... .......... 73% 42.7M 6s\n", + "435400K .......... .......... .......... .......... .......... 73% 15.4M 6s\n", + "435450K .......... .......... .......... .......... .......... 73% 46.4M 6s\n", + "435500K .......... .......... .......... .......... .......... 73% 30.3M 6s\n", + "435550K .......... .......... .......... .......... .......... 73% 17.6M 6s\n", + "435600K .......... .......... .......... .......... .......... 73% 46.4M 6s\n", + "435650K .......... .......... .......... .......... .......... 73% 23.8M 6s\n", + "435700K .......... .......... .......... .......... .......... 73% 25.1M 6s\n", + "435750K .......... .......... .......... .......... .......... 73% 60.3M 6s\n", + "435800K .......... .......... .......... .......... .......... 73% 14.9M 6s\n", + "435850K .......... .......... .......... .......... .......... 73% 34.2M 6s\n", + "435900K .......... .......... .......... .......... .......... 73% 11.9M 6s\n", + "435950K .......... .......... .......... .......... .......... 73% 45.5M 6s\n", + "436000K .......... .......... .......... .......... .......... 73% 51.2M 6s\n", + "436050K .......... .......... .......... .......... .......... 73% 16.1M 6s\n", + "436100K .......... .......... .......... .......... .......... 73% 48.1M 6s\n", + "436150K .......... .......... .......... .......... .......... 73% 63.6M 6s\n", + "436200K .......... .......... .......... .......... .......... 73% 14.3M 6s\n", + "436250K .......... .......... .......... .......... .......... 73% 53.1M 6s\n", + "436300K .......... .......... .......... .......... .......... 73% 18.0M 6s\n", + "436350K .......... .......... .......... .......... .......... 73% 38.1M 6s\n", + "436400K .......... .......... .......... .......... .......... 73% 40.3M 6s\n", + "436450K .......... .......... .......... .......... .......... 73% 20.6M 6s\n", + "436500K .......... .......... .......... .......... .......... 73% 39.8M 6s\n", + "436550K .......... .......... .......... .......... .......... 73% 21.8M 6s\n", + "436600K .......... .......... .......... .......... .......... 73% 28.0M 6s\n", + "436650K .......... .......... .......... .......... .......... 73% 45.9M 6s\n", + "436700K .......... .......... .......... .......... .......... 73% 20.8M 6s\n", + "436750K .......... .......... .......... .......... .......... 73% 38.4M 6s\n", + "436800K .......... .......... .......... .......... .......... 73% 52.7M 6s\n", + "436850K .......... .......... .......... .......... .......... 73% 22.2M 6s\n", + "436900K .......... .......... .......... .......... .......... 73% 32.7M 6s\n", + "436950K .......... .......... .......... .......... .......... 73% 25.7M 6s\n", + "437000K .......... .......... .......... .......... .......... 73% 26.5M 6s\n", + "437050K .......... .......... .......... .......... .......... 73% 56.2M 6s\n", + "437100K .......... .......... .......... .......... .......... 73% 24.4M 6s\n", + "437150K .......... .......... .......... .......... .......... 73% 23.9M 6s\n", + "437200K .......... .......... .......... .......... .......... 73% 56.8M 6s\n", + "437250K .......... .......... .......... .......... .......... 73% 22.6M 6s\n", + "437300K .......... .......... .......... .......... .......... 73% 33.7M 6s\n", + "437350K .......... .......... .......... .......... .......... 73% 67.5M 6s\n", + "437400K .......... .......... .......... .......... .......... 73% 17.2M 6s\n", + "437450K .......... .......... .......... .......... .......... 73% 46.0M 6s\n", + "437500K .......... .......... .......... .......... .......... 73% 23.8M 6s\n", + "437550K .......... .......... .......... .......... .......... 73% 29.4M 6s\n", + "437600K .......... .......... .......... .......... .......... 73% 46.8M 6s\n", + "437650K .......... .......... .......... .......... .......... 73% 27.8M 6s\n", + "437700K .......... .......... .......... .......... .......... 73% 29.7M 6s\n", + "437750K .......... .......... .......... .......... .......... 73% 37.1M 6s\n", + "437800K .......... .......... .......... .......... .......... 73% 21.6M 6s\n", + "437850K .......... .......... .......... .......... .......... 73% 39.5M 6s\n", + "437900K .......... .......... .......... .......... .......... 73% 50.1M 6s\n", + "437950K .......... .......... .......... .......... .......... 73% 23.0M 6s\n", + "438000K .......... .......... .......... .......... .......... 73% 36.5M 6s\n", + "438050K .......... .......... .......... .......... .......... 73% 26.6M 5s\n", + "438100K .......... .......... .......... .......... .......... 73% 30.3M 5s\n", + "438150K .......... .......... .......... .......... .......... 73% 47.6M 5s\n", + "438200K .......... .......... .......... .......... .......... 73% 23.9M 5s\n", + "438250K .......... .......... .......... .......... .......... 73% 29.5M 5s\n", + "438300K .......... .......... .......... .......... .......... 73% 31.6M 5s\n", + "438350K .......... .......... .......... .......... .......... 73% 40.0M 5s\n", + "438400K .......... .......... .......... .......... .......... 73% 29.3M 5s\n", + "438450K .......... .......... .......... .......... .......... 73% 29.2M 5s\n", + "438500K .......... .......... .......... .......... .......... 73% 46.1M 5s\n", + "438550K .......... .......... .......... .......... .......... 73% 29.9M 5s\n", + "438600K .......... .......... .......... .......... .......... 73% 25.3M 5s\n", + "438650K .......... .......... .......... .......... .......... 73% 32.2M 5s\n", + "438700K .......... .......... .......... .......... .......... 73% 32.7M 5s\n", + "438750K .......... .......... .......... .......... .......... 73% 30.3M 5s\n", + "438800K .......... .......... .......... .......... .......... 73% 36.9M 5s\n", + "438850K .......... .......... .......... .......... .......... 73% 31.0M 5s\n", + "438900K .......... .......... .......... .......... .......... 73% 33.5M 5s\n", + "438950K .......... .......... .......... .......... .......... 73% 36.9M 5s\n", + "439000K .......... .......... .......... .......... .......... 73% 24.3M 5s\n", + "439050K .......... .......... .......... .......... .......... 73% 33.9M 5s\n", + "439100K .......... .......... .......... .......... .......... 73% 23.9M 5s\n", + "439150K .......... .......... .......... .......... .......... 73% 41.8M 5s\n", + "439200K .......... .......... .......... .......... .......... 73% 3.97M 5s\n", + "439250K .......... .......... .......... .......... .......... 73% 78.8M 5s\n", + "439300K .......... .......... .......... .......... .......... 73% 71.2M 5s\n", + "439350K .......... .......... .......... .......... .......... 73% 9.42M 5s\n", + "439400K .......... .......... .......... .......... .......... 73% 46.1M 5s\n", + "439450K .......... .......... .......... .......... .......... 73% 74.6M 5s\n", + "439500K .......... .......... .......... .......... .......... 73% 15.4M 5s\n", + "439550K .......... .......... .......... .......... .......... 73% 60.9M 5s\n", + "439600K .......... .......... .......... .......... .......... 73% 68.5M 5s\n", + "439650K .......... .......... .......... .......... .......... 73% 18.0M 5s\n", + "439700K .......... .......... .......... .......... .......... 73% 47.6M 5s\n", + "439750K .......... .......... .......... .......... .......... 73% 75.5M 5s\n", + "439800K .......... .......... .......... .......... .......... 73% 16.3M 5s\n", + "439850K .......... .......... .......... .......... .......... 73% 48.0M 5s\n", + "439900K .......... .......... .......... .......... .......... 73% 75.3M 5s\n", + "439950K .......... .......... .......... .......... .......... 73% 19.1M 5s\n", + "440000K .......... .......... .......... .......... .......... 73% 33.9M 5s\n", + "440050K .......... .......... .......... .......... .......... 73% 78.6M 5s\n", + "440100K .......... .......... .......... .......... .......... 74% 23.6M 5s\n", + "440150K .......... .......... .......... .......... .......... 74% 36.0M 5s\n", + "440200K .......... .......... .......... .......... .......... 74% 49.9M 5s\n", + "440250K .......... .......... .......... .......... .......... 74% 14.9M 5s\n", + "440300K .......... .......... .......... .......... .......... 74% 43.6M 5s\n", + "440350K .......... .......... .......... .......... .......... 74% 63.4M 5s\n", + "440400K .......... .......... .......... .......... .......... 74% 17.9M 5s\n", + "440450K .......... .......... .......... .......... .......... 74% 43.3M 5s\n", + "440500K .......... .......... .......... .......... .......... 74% 74.6M 5s\n", + "440550K .......... .......... .......... .......... .......... 74% 48.5M 5s\n", + "440600K .......... .......... .......... .......... .......... 74% 18.0M 5s\n", + "440650K .......... .......... .......... .......... .......... 74% 55.8M 5s\n", + "440700K .......... .......... .......... .......... .......... 74% 61.2M 5s\n", + "440750K .......... .......... .......... .......... .......... 74% 20.6M 5s\n", + "440800K .......... .......... .......... .......... .......... 74% 42.5M 5s\n", + "440850K .......... .......... .......... .......... .......... 74% 62.9M 5s\n", + "440900K .......... .......... .......... .......... .......... 74% 17.9M 5s\n", + "440950K .......... .......... .......... .......... .......... 74% 46.7M 5s\n", + "441000K .......... .......... .......... .......... .......... 74% 43.0M 5s\n", + "441050K .......... .......... .......... .......... .......... 74% 25.4M 5s\n", + "441100K .......... .......... .......... .......... .......... 74% 36.1M 5s\n", + "441150K .......... .......... .......... .......... .......... 74% 49.8M 5s\n", + "441200K .......... .......... .......... .......... .......... 74% 27.4M 5s\n", + "441250K .......... .......... .......... .......... .......... 74% 33.6M 5s\n", + "441300K .......... .......... .......... .......... .......... 74% 5.28M 5s\n", + "441350K .......... .......... .......... .......... .......... 74% 78.8M 5s\n", + "441400K .......... .......... .......... .......... .......... 74% 67.5M 5s\n", + "441450K .......... .......... .......... .......... .......... 74% 72.3M 5s\n", + "441500K .......... .......... .......... .......... .......... 74% 85.1M 5s\n", + "441550K .......... .......... .......... .......... .......... 74% 7.93M 5s\n", + "441600K .......... .......... .......... .......... .......... 74% 3.70M 5s\n", + "441650K .......... .......... .......... .......... .......... 74% 76.4M 5s\n", + "441700K .......... .......... .......... .......... .......... 74% 74.4M 5s\n", + "441750K .......... .......... .......... .......... .......... 74% 68.6M 5s\n", + "441800K .......... .......... .......... .......... .......... 74% 4.67M 5s\n", + "441850K .......... .......... .......... .......... .......... 74% 37.2M 5s\n", + "441900K .......... .......... .......... .......... .......... 74% 13.7M 5s\n", + "441950K .......... .......... .......... .......... .......... 74% 11.8M 5s\n", + "442000K .......... .......... .......... .......... .......... 74% 10.7M 5s\n", + "442050K .......... .......... .......... .......... .......... 74% 10.5M 5s\n", + "442100K .......... .......... .......... .......... .......... 74% 10.6M 5s\n", + "442150K .......... .......... .......... .......... .......... 74% 69.3M 5s\n", + "442200K .......... .......... .......... .......... .......... 74% 5.75M 5s\n", + "442250K .......... .......... .......... .......... .......... 74% 17.2M 5s\n", + "442300K .......... .......... .......... .......... .......... 74% 22.0M 5s\n", + "442350K .......... .......... .......... .......... .......... 74% 11.1M 5s\n", + "442400K .......... .......... .......... .......... .......... 74% 10.6M 5s\n", + "442450K .......... .......... .......... .......... .......... 74% 10.7M 5s\n", + "442500K .......... .......... .......... .......... .......... 74% 11.5M 5s\n", + "442550K .......... .......... .......... .......... .......... 74% 11.5M 5s\n", + "442600K .......... .......... .......... .......... .......... 74% 10.1M 5s\n", + "442650K .......... .......... .......... .......... .......... 74% 11.7M 5s\n", + "442700K .......... .......... .......... .......... .......... 74% 10.8M 5s\n", + "442750K .......... .......... .......... .......... .......... 74% 24.6M 5s\n", + "442800K .......... .......... .......... .......... .......... 74% 13.8M 5s\n", + "442850K .......... .......... .......... .......... .......... 74% 11.1M 5s\n", + "442900K .......... .......... .......... .......... .......... 74% 11.5M 5s\n", + "442950K .......... .......... .......... .......... .......... 74% 12.6M 5s\n", + "443000K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + "443050K .......... .......... .......... .......... .......... 74% 31.9M 5s\n", + "443100K .......... .......... .......... .......... .......... 74% 11.8M 5s\n", + "443150K .......... .......... .......... .......... .......... 74% 11.5M 5s\n", + "443200K .......... .......... .......... .......... .......... 74% 12.2M 5s\n", + "443250K .......... .......... .......... .......... .......... 74% 11.6M 5s\n", + "443300K .......... .......... .......... .......... .......... 74% 35.3M 5s\n", + "443350K .......... .......... .......... .......... .......... 74% 12.0M 5s\n", + "443400K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + "443450K .......... .......... .......... .......... .......... 74% 13.7M 5s\n", + "443500K .......... .......... .......... .......... .......... 74% 33.3M 5s\n", + "443550K .......... .......... .......... .......... .......... 74% 12.0M 5s\n", + "443600K .......... .......... .......... .......... .......... 74% 13.0M 5s\n", + "443650K .......... .......... .......... .......... .......... 74% 11.8M 5s\n", + "443700K .......... .......... .......... .......... .......... 74% 29.4M 5s\n", + "443750K .......... .......... .......... .......... .......... 74% 7.99M 5s\n", + "443800K .......... .......... .......... .......... .......... 74% 10.6M 5s\n", + "443850K .......... .......... .......... .......... .......... 74% 65.1M 5s\n", + "443900K .......... .......... .......... .......... .......... 74% 11.7M 5s\n", + "443950K .......... .......... .......... .......... .......... 74% 11.8M 5s\n", + "444000K .......... .......... .......... .......... .......... 74% 4.80M 5s\n", + "444050K .......... .......... .......... .......... .......... 74% 57.9M 5s\n", + "444100K .......... .......... .......... .......... .......... 74% 10.7M 5s\n", + "444150K .......... .......... .......... .......... .......... 74% 12.6M 5s\n", + "444200K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + "444250K .......... .......... .......... .......... .......... 74% 59.7M 5s\n", + "444300K .......... .......... .......... .......... .......... 74% 11.7M 5s\n", + "444350K .......... .......... .......... .......... .......... 74% 11.9M 5s\n", + "444400K .......... .......... .......... .......... .......... 74% 46.6M 5s\n", + "444450K .......... .......... .......... .......... .......... 74% 11.6M 5s\n", + "444500K .......... .......... .......... .......... .......... 74% 13.1M 5s\n", + "444550K .......... .......... .......... .......... .......... 74% 37.0M 5s\n", + "444600K .......... .......... .......... .......... .......... 74% 12.7M 5s\n", + "444650K .......... .......... .......... .......... .......... 74% 45.7M 5s\n", + "444700K .......... .......... .......... .......... .......... 74% 12.4M 5s\n", + "444750K .......... .......... .......... .......... .......... 74% 12.0M 5s\n", + "444800K .......... .......... .......... .......... .......... 74% 46.2M 5s\n", + "444850K .......... .......... .......... .......... .......... 74% 11.1M 5s\n", + "444900K .......... .......... .......... .......... .......... 74% 59.4M 5s\n", + "444950K .......... .......... .......... .......... .......... 74% 3.50M 5s\n", + "445000K .......... .......... .......... .......... .......... 74% 56.4M 5s\n", + "445050K .......... .......... .......... .......... .......... 74% 12.5M 5s\n", + "445100K .......... .......... .......... .......... .......... 74% 60.8M 5s\n", + "445150K .......... .......... .......... .......... .......... 74% 11.5M 5s\n", + "445200K .......... .......... .......... .......... .......... 74% 12.4M 5s\n", + "445250K .......... .......... .......... .......... .......... 74% 43.0M 5s\n", + "445300K .......... .......... .......... .......... .......... 74% 13.3M 5s\n", + "445350K .......... .......... .......... .......... .......... 74% 35.2M 5s\n", + "445400K .......... .......... .......... .......... .......... 74% 13.4M 5s\n", + "445450K .......... .......... .......... .......... .......... 74% 12.1M 5s\n", + "445500K .......... .......... .......... .......... .......... 74% 46.0M 5s\n", + "445550K .......... .......... .......... .......... .......... 74% 14.8M 5s\n", + "445600K .......... .......... .......... .......... .......... 74% 32.8M 5s\n", + "445650K .......... .......... .......... .......... .......... 74% 15.8M 5s\n", + "445700K .......... .......... .......... .......... .......... 74% 39.8M 5s\n", + "445750K .......... .......... .......... .......... .......... 74% 15.2M 5s\n", + "445800K .......... .......... .......... .......... .......... 74% 31.7M 5s\n", + "445850K .......... .......... .......... .......... .......... 74% 15.1M 5s\n", + "445900K .......... .......... .......... .......... .......... 74% 45.4M 5s\n", + "445950K .......... .......... .......... .......... .......... 74% 13.0M 5s\n", + "446000K .......... .......... .......... .......... .......... 75% 29.3M 5s\n", + "446050K .......... .......... .......... .......... .......... 75% 17.1M 5s\n", + "446100K .......... .......... .......... .......... .......... 75% 33.0M 5s\n", + "446150K .......... .......... .......... .......... .......... 75% 15.4M 5s\n", + "446200K .......... .......... .......... .......... .......... 75% 14.3M 5s\n", + "446250K .......... .......... .......... .......... .......... 75% 29.7M 5s\n", + "446300K .......... .......... .......... .......... .......... 75% 52.4M 5s\n", + "446350K .......... .......... .......... .......... .......... 75% 14.2M 5s\n", + "446400K .......... .......... .......... .......... .......... 75% 36.9M 5s\n", + "446450K .......... .......... .......... .......... .......... 75% 14.8M 5s\n", + "446500K .......... .......... .......... .......... .......... 75% 40.6M 5s\n", + "446550K .......... .......... .......... .......... .......... 75% 17.0M 5s\n", + "446600K .......... .......... .......... .......... .......... 75% 14.9M 5s\n", + "446650K .......... .......... .......... .......... .......... 75% 31.4M 5s\n", + "446700K .......... .......... .......... .......... .......... 75% 16.3M 5s\n", + "446750K .......... .......... .......... .......... .......... 75% 31.9M 5s\n", + "446800K .......... .......... .......... .......... .......... 75% 29.0M 5s\n", + "446850K .......... .......... .......... .......... .......... 75% 17.2M 5s\n", + "446900K .......... .......... .......... .......... .......... 75% 25.5M 5s\n", + "446950K .......... .......... .......... .......... .......... 75% 18.8M 5s\n", + "447000K .......... .......... .......... .......... .......... 75% 26.0M 5s\n", + "447050K .......... .......... .......... .......... .......... 75% 17.5M 5s\n", + "447100K .......... .......... .......... .......... .......... 75% 13.3M 5s\n", + "447150K .......... .......... .......... .......... .......... 75% 57.5M 5s\n", + "447200K .......... .......... .......... .......... .......... 75% 12.2M 5s\n", + "447250K .......... .......... .......... .......... .......... 75% 66.7M 5s\n", + "447300K .......... .......... .......... .......... .......... 75% 48.0M 5s\n", + "447350K .......... .......... .......... .......... .......... 75% 13.0M 5s\n", + "447400K .......... .......... .......... .......... .......... 75% 14.0M 5s\n", + "447450K .......... .......... .......... .......... .......... 75% 44.8M 5s\n", + "447500K .......... .......... .......... .......... .......... 75% 57.6M 5s\n", + "447550K .......... .......... .......... .......... .......... 75% 15.5M 5s\n", + "447600K .......... .......... .......... .......... .......... 75% 39.4M 5s\n", + "447650K .......... .......... .......... .......... .......... 75% 14.3M 5s\n", + "447700K .......... .......... .......... .......... .......... 75% 38.8M 5s\n", + "447750K .......... .......... .......... .......... .......... 75% 16.3M 5s\n", + "447800K .......... .......... .......... .......... .......... 75% 33.8M 5s\n", + "447850K .......... .......... .......... .......... .......... 75% 13.8M 5s\n", + "447900K .......... .......... .......... .......... .......... 75% 44.6M 5s\n", + "447950K .......... .......... .......... .......... .......... 75% 16.0M 5s\n", + "448000K .......... .......... .......... .......... .......... 75% 32.2M 5s\n", + "448050K .......... .......... .......... .......... .......... 75% 61.0M 5s\n", + "448100K .......... .......... .......... .......... .......... 75% 16.0M 5s\n", + "448150K .......... .......... .......... .......... .......... 75% 24.3M 5s\n", + "448200K .......... .......... .......... .......... .......... 75% 20.1M 5s\n", + "448250K .......... .......... .......... .......... .......... 75% 21.1M 5s\n", + "448300K .......... .......... .......... .......... .......... 75% 14.8M 5s\n", + "448350K .......... .......... .......... .......... .......... 75% 14.5M 5s\n", + "448400K .......... .......... .......... .......... .......... 75% 56.4M 5s\n", + "448450K .......... .......... .......... .......... .......... 75% 13.8M 5s\n", + "448500K .......... .......... .......... .......... .......... 75% 53.5M 5s\n", + "448550K .......... .......... .......... .......... .......... 75% 42.9M 5s\n", + "448600K .......... .......... .......... .......... .......... 75% 13.6M 5s\n", + "448650K .......... .......... .......... .......... .......... 75% 65.8M 5s\n", + "448700K .......... .......... .......... .......... .......... 75% 13.9M 5s\n", + "448750K .......... .......... .......... .......... .......... 75% 62.6M 5s\n", + "448800K .......... .......... .......... .......... .......... 75% 18.5M 5s\n", + "448850K .......... .......... .......... .......... .......... 75% 33.9M 5s\n", + "448900K .......... .......... .......... .......... .......... 75% 54.0M 5s\n", + "448950K .......... .......... .......... .......... .......... 75% 15.8M 5s\n", + "449000K .......... .......... .......... .......... .......... 75% 48.5M 5s\n", + "449050K .......... .......... .......... .......... .......... 75% 13.8M 5s\n", + "449100K .......... .......... .......... .......... .......... 75% 63.1M 5s\n", + "449150K .......... .......... .......... .......... .......... 75% 15.2M 5s\n", + "449200K .......... .......... .......... .......... .......... 75% 48.1M 5s\n", + "449250K .......... .......... .......... .......... .......... 75% 57.8M 5s\n", + "449300K .......... .......... .......... .......... .......... 75% 14.7M 5s\n", + "449350K .......... .......... .......... .......... .......... 75% 47.6M 5s\n", + "449400K .......... .......... .......... .......... .......... 75% 14.2M 5s\n", + "449450K .......... .......... .......... .......... .......... 75% 51.9M 5s\n", + "449500K .......... .......... .......... .......... .......... 75% 14.8M 5s\n", + "449550K .......... .......... .......... .......... .......... 75% 56.9M 5s\n", + "449600K .......... .......... .......... .......... .......... 75% 55.6M 5s\n", + "449650K .......... .......... .......... .......... .......... 75% 15.9M 5s\n", + "449700K .......... .......... .......... .......... .......... 75% 51.8M 5s\n", + "449750K .......... .......... .......... .......... .......... 75% 63.3M 5s\n", + "449800K .......... .......... .......... .......... .......... 75% 13.9M 5s\n", + "449850K .......... .......... .......... .......... .......... 75% 66.0M 5s\n", + "449900K .......... .......... .......... .......... .......... 75% 13.4M 5s\n", + "449950K .......... .......... .......... .......... .......... 75% 61.3M 5s\n", + "450000K .......... .......... .......... .......... .......... 75% 14.2M 5s\n", + "450050K .......... .......... .......... .......... .......... 75% 51.7M 5s\n", + "450100K .......... .......... .......... .......... .......... 75% 69.4M 5s\n", + "450150K .......... .......... .......... .......... .......... 75% 15.0M 5s\n", + "450200K .......... .......... .......... .......... .......... 75% 47.5M 5s\n", + "450250K .......... .......... .......... .......... .......... 75% 15.1M 5s\n", + "450300K .......... .......... .......... .......... .......... 75% 52.6M 5s\n", + "450350K .......... .......... .......... .......... .......... 75% 60.1M 5s\n", + "450400K .......... .......... .......... .......... .......... 75% 15.2M 5s\n", + "450450K .......... .......... .......... .......... .......... 75% 47.6M 5s\n", + "450500K .......... .......... .......... .......... .......... 75% 69.3M 5s\n", + "450550K .......... .......... .......... .......... .......... 75% 16.3M 5s\n", + "450600K .......... .......... .......... .......... .......... 75% 46.9M 5s\n", + "450650K .......... .......... .......... .......... .......... 75% 15.8M 5s\n", + "450700K .......... .......... .......... .......... .......... 75% 54.3M 5s\n", + "450750K .......... .......... .......... .......... .......... 75% 71.0M 5s\n", + "450800K .......... .......... .......... .......... .......... 75% 15.1M 5s\n", + "450850K .......... .......... .......... .......... .......... 75% 70.6M 5s\n", + "450900K .......... .......... .......... .......... .......... 75% 15.5M 5s\n", + "450950K .......... .......... .......... .......... .......... 75% 47.5M 5s\n", + "451000K .......... .......... .......... .......... .......... 75% 41.8M 5s\n", + "451050K .......... .......... .......... .......... .......... 75% 16.2M 5s\n", + "451100K .......... .......... .......... .......... .......... 75% 47.5M 5s\n", + "451150K .......... .......... .......... .......... .......... 75% 78.4M 5s\n", + "451200K .......... .......... .......... .......... .......... 75% 14.9M 5s\n", + "451250K .......... .......... .......... .......... .......... 75% 39.3M 5s\n", + "451300K .......... .......... .......... .......... .......... 75% 21.8M 5s\n", + "451350K .......... .......... .......... .......... .......... 75% 48.9M 5s\n", + "451400K .......... .......... .......... .......... .......... 75% 45.3M 5s\n", + "451450K .......... .......... .......... .......... .......... 75% 17.3M 5s\n", + "451500K .......... .......... .......... .......... .......... 75% 3.84M 5s\n", + "451550K .......... .......... .......... .......... .......... 75% 49.4M 5s\n", + "451600K .......... .......... .......... .......... .......... 75% 67.2M 5s\n", + "451650K .......... .......... .......... .......... .......... 75% 13.7M 5s\n", + "451700K .......... .......... .......... .......... .......... 75% 66.8M 5s\n", + "451750K .......... .......... .......... .......... .......... 75% 54.8M 5s\n", + "451800K .......... .......... .......... .......... .......... 75% 13.8M 5s\n", + "451850K .......... .......... .......... .......... .......... 75% 65.3M 5s\n", + "451900K .......... .......... .......... .......... .......... 75% 17.3M 5s\n", + "451950K .......... .......... .......... .......... .......... 76% 35.9M 5s\n", + "452000K .......... .......... .......... .......... .......... 76% 53.0M 5s\n", + "452050K .......... .......... .......... .......... .......... 76% 10.9M 5s\n", + "452100K .......... .......... .......... .......... .......... 76% 59.0M 5s\n", + "452150K .......... .......... .......... .......... .......... 76% 69.4M 5s\n", + "452200K .......... .......... .......... .......... .......... 76% 14.9M 5s\n", + "452250K .......... .......... .......... .......... .......... 76% 65.4M 5s\n", + "452300K .......... .......... .......... .......... .......... 76% 15.2M 5s\n", + "452350K .......... .......... .......... .......... .......... 76% 55.5M 5s\n", + "452400K .......... .......... .......... .......... .......... 76% 60.3M 5s\n", + "452450K .......... .......... .......... .......... .......... 76% 15.9M 5s\n", + "452500K .......... .......... .......... .......... .......... 76% 47.7M 5s\n", + "452550K .......... .......... .......... .......... .......... 76% 76.9M 5s\n", + "452600K .......... .......... .......... .......... .......... 76% 14.8M 5s\n", + "452650K .......... .......... .......... .......... .......... 76% 52.8M 5s\n", + "452700K .......... .......... .......... .......... .......... 76% 68.4M 5s\n", + "452750K .......... .......... .......... .......... .......... 76% 16.4M 5s\n", + "452800K .......... .......... .......... .......... .......... 76% 54.3M 5s\n", + "452850K .......... .......... .......... .......... .......... 76% 66.2M 5s\n", + "452900K .......... .......... .......... .......... .......... 76% 16.1M 5s\n", + "452950K .......... .......... .......... .......... .......... 76% 48.3M 5s\n", + "453000K .......... .......... .......... .......... .......... 76% 54.2M 5s\n", + "453050K .......... .......... .......... .......... .......... 76% 17.4M 5s\n", + "453100K .......... .......... .......... .......... .......... 76% 57.8M 5s\n", + "453150K .......... .......... .......... .......... .......... 76% 61.1M 5s\n", + "453200K .......... .......... .......... .......... .......... 76% 15.9M 5s\n", + "453250K .......... .......... .......... .......... .......... 76% 48.0M 5s\n", + "453300K .......... .......... .......... .......... .......... 76% 79.2M 5s\n", + "453350K .......... .......... .......... .......... .......... 76% 14.0M 5s\n", + "453400K .......... .......... .......... .......... .......... 76% 56.3M 5s\n", + "453450K .......... .......... .......... .......... .......... 76% 44.0M 5s\n", + "453500K .......... .......... .......... .......... .......... 76% 21.9M 5s\n", + "453550K .......... .......... .......... .......... .......... 76% 52.1M 5s\n", + "453600K .......... .......... .......... .......... .......... 76% 32.3M 5s\n", + "453650K .......... .......... .......... .......... .......... 76% 19.3M 5s\n", + "453700K .......... .......... .......... .......... .......... 76% 61.8M 5s\n", + "453750K .......... .......... .......... .......... .......... 76% 71.4M 5s\n", + "453800K .......... .......... .......... .......... .......... 76% 14.6M 5s\n", + "453850K .......... .......... .......... .......... .......... 76% 48.5M 5s\n", + "453900K .......... .......... .......... .......... .......... 76% 60.2M 5s\n", + "453950K .......... .......... .......... .......... .......... 76% 20.2M 5s\n", + "454000K .......... .......... .......... .......... .......... 76% 45.9M 5s\n", + "454050K .......... .......... .......... .......... .......... 76% 62.1M 5s\n", + "454100K .......... .......... .......... .......... .......... 76% 16.2M 5s\n", + "454150K .......... .......... .......... .......... .......... 76% 45.3M 5s\n", + "454200K .......... .......... .......... .......... .......... 76% 48.1M 5s\n", + "454250K .......... .......... .......... .......... .......... 76% 20.0M 5s\n", + "454300K .......... .......... .......... .......... .......... 76% 65.0M 5s\n", + "454350K .......... .......... .......... .......... .......... 76% 74.4M 5s\n", + "454400K .......... .......... .......... .......... .......... 76% 15.9M 5s\n", + "454450K .......... .......... .......... .......... .......... 76% 48.9M 5s\n", + "454500K .......... .......... .......... .......... .......... 76% 49.7M 5s\n", + "454550K .......... .......... .......... .......... .......... 76% 45.9M 5s\n", + "454600K .......... .......... .......... .......... .......... 76% 20.3M 5s\n", + "454650K .......... .......... .......... .......... .......... 76% 57.8M 5s\n", + "454700K .......... .......... .......... .......... .......... 76% 17.8M 5s\n", + "454750K .......... .......... .......... .......... .......... 76% 42.2M 5s\n", + "454800K .......... .......... .......... .......... .......... 76% 50.9M 5s\n", + "454850K .......... .......... .......... .......... .......... 76% 46.6M 5s\n", + "454900K .......... .......... .......... .......... .......... 76% 23.4M 5s\n", + "454950K .......... .......... .......... .......... .......... 76% 60.1M 5s\n", + "455000K .......... .......... .......... .......... .......... 76% 36.6M 5s\n", + "455050K .......... .......... .......... .......... .......... 76% 19.3M 5s\n", + "455100K .......... .......... .......... .......... .......... 76% 49.6M 5s\n", + "455150K .......... .......... .......... .......... .......... 76% 54.5M 5s\n", + "455200K .......... .......... .......... .......... .......... 76% 22.0M 5s\n", + "455250K .......... .......... .......... .......... .......... 76% 39.1M 5s\n", + "455300K .......... .......... .......... .......... .......... 76% 49.8M 5s\n", + "455350K .......... .......... .......... .......... .......... 76% 24.2M 5s\n", + "455400K .......... .......... .......... .......... .......... 76% 34.5M 5s\n", + "455450K .......... .......... .......... .......... .......... 76% 5.65M 5s\n", + "455500K .......... .......... .......... .......... .......... 76% 67.4M 5s\n", + "455550K .......... .......... .......... .......... .......... 76% 61.6M 5s\n", + "455600K .......... .......... .......... .......... .......... 76% 64.0M 5s\n", + "455650K .......... .......... .......... .......... .......... 76% 15.8M 5s\n", + "455700K .......... .......... .......... .......... .......... 76% 64.4M 5s\n", + "455750K .......... .......... .......... .......... .......... 76% 72.0M 5s\n", + "455800K .......... .......... .......... .......... .......... 76% 14.9M 5s\n", + "455850K .......... .......... .......... .......... .......... 76% 50.2M 5s\n", + "455900K .......... .......... .......... .......... .......... 76% 51.9M 5s\n", + "455950K .......... .......... .......... .......... .......... 76% 22.5M 5s\n", + "456000K .......... .......... .......... .......... .......... 76% 41.5M 5s\n", + "456050K .......... .......... .......... .......... .......... 76% 68.1M 5s\n", + "456100K .......... .......... .......... .......... .......... 76% 18.0M 5s\n", + "456150K .......... .......... .......... .......... .......... 76% 44.6M 5s\n", + "456200K .......... .......... .......... .......... .......... 76% 55.5M 5s\n", + "456250K .......... .......... .......... .......... .......... 76% 22.7M 5s\n", + "456300K .......... .......... .......... .......... .......... 76% 44.0M 5s\n", + "456350K .......... .......... .......... .......... .......... 76% 56.7M 5s\n", + "456400K .......... .......... .......... .......... .......... 76% 59.8M 5s\n", + "456450K .......... .......... .......... .......... .......... 76% 12.5M 5s\n", + "456500K .......... .......... .......... .......... .......... 76% 50.5M 5s\n", + "456550K .......... .......... .......... .......... .......... 76% 40.8M 5s\n", + "456600K .......... .......... .......... .......... .......... 76% 20.4M 5s\n", + "456650K .......... .......... .......... .......... .......... 76% 51.3M 5s\n", + "456700K .......... .......... .......... .......... .......... 76% 49.8M 5s\n", + "456750K .......... .......... .......... .......... .......... 76% 34.5M 5s\n", + "456800K .......... .......... .......... .......... .......... 76% 26.4M 5s\n", + "456850K .......... .......... .......... .......... .......... 76% 61.3M 5s\n", + "456900K .......... .......... .......... .......... .......... 76% 39.2M 5s\n", + "456950K .......... .......... .......... .......... .......... 76% 21.9M 5s\n", + "457000K .......... .......... .......... .......... .......... 76% 47.6M 5s\n", + "457050K .......... .......... .......... .......... .......... 76% 56.0M 5s\n", + "457100K .......... .......... .......... .......... .......... 76% 24.8M 5s\n", + "457150K .......... .......... .......... .......... .......... 76% 45.1M 5s\n", + "457200K .......... .......... .......... .......... .......... 76% 45.0M 5s\n", + "457250K .......... .......... .......... .......... .......... 76% 47.4M 5s\n", + "457300K .......... .......... .......... .......... .......... 76% 23.9M 5s\n", + "457350K .......... .......... .......... .......... .......... 76% 58.2M 5s\n", + "457400K .......... .......... .......... .......... .......... 76% 3.67M 5s\n", + "457450K .......... .......... .......... .......... .......... 76% 68.2M 5s\n", + "457500K .......... .......... .......... .......... .......... 76% 60.4M 5s\n", + "457550K .......... .......... .......... .......... .......... 76% 16.0M 5s\n", + "457600K .......... .......... .......... .......... .......... 76% 41.2M 5s\n", + "457650K .......... .......... .......... .......... .......... 76% 57.4M 5s\n", + "457700K .......... .......... .......... .......... .......... 76% 48.6M 5s\n", + "457750K .......... .......... .......... .......... .......... 76% 29.4M 5s\n", + "457800K .......... .......... .......... .......... .......... 76% 38.6M 5s\n", + "457850K .......... .......... .......... .......... .......... 76% 82.6M 5s\n", + "457900K .......... .......... .......... .......... .......... 77% 20.3M 5s\n", + "457950K .......... .......... .......... .......... .......... 77% 50.4M 5s\n", + "458000K .......... .......... .......... .......... .......... 77% 48.3M 5s\n", + "458050K .......... .......... .......... .......... .......... 77% 54.6M 5s\n", + "458100K .......... .......... .......... .......... .......... 77% 22.0M 5s\n", + "458150K .......... .......... .......... .......... .......... 77% 60.4M 5s\n", + "458200K .......... .......... .......... .......... .......... 77% 58.9M 5s\n", + "458250K .......... .......... .......... .......... .......... 77% 19.2M 5s\n", + "458300K .......... .......... .......... .......... .......... 77% 60.5M 5s\n", + "458350K .......... .......... .......... .......... .......... 77% 60.8M 5s\n", + "458400K .......... .......... .......... .......... .......... 77% 74.0M 5s\n", + "458450K .......... .......... .......... .......... .......... 77% 18.7M 5s\n", + "458500K .......... .......... .......... .......... .......... 77% 59.9M 5s\n", + "458550K .......... .......... .......... .......... .......... 77% 73.6M 5s\n", + "458600K .......... .......... .......... .......... .......... 77% 17.5M 5s\n", + "458650K .......... .......... .......... .......... .......... 77% 61.7M 5s\n", + "458700K .......... .......... .......... .......... .......... 77% 57.2M 5s\n", + "458750K .......... .......... .......... .......... .......... 77% 61.6M 5s\n", + "458800K .......... .......... .......... .......... .......... 77% 18.0M 5s\n", + "458850K .......... .......... .......... .......... .......... 77% 40.6M 5s\n", + "458900K .......... .......... .......... .......... .......... 77% 52.4M 5s\n", + "458950K .......... .......... .......... .......... .......... 77% 25.9M 5s\n", + "459000K .......... .......... .......... .......... .......... 77% 45.8M 5s\n", + "459050K .......... .......... .......... .......... .......... 77% 56.8M 5s\n", + "459100K .......... .......... .......... .......... .......... 77% 65.1M 5s\n", + "459150K .......... .......... .......... .......... .......... 77% 23.3M 5s\n", + "459200K .......... .......... .......... .......... .......... 77% 42.2M 5s\n", + "459250K .......... .......... .......... .......... .......... 77% 52.9M 5s\n", + "459300K .......... .......... .......... .......... .......... 77% 56.7M 5s\n", + "459350K .......... .......... .......... .......... .......... 77% 26.3M 5s\n", + "459400K .......... .......... .......... .......... .......... 77% 37.7M 5s\n", + "459450K .......... .......... .......... .......... .......... 77% 56.0M 5s\n", + "459500K .......... .......... .......... .......... .......... 77% 22.9M 5s\n", + "459550K .......... .......... .......... .......... .......... 77% 40.2M 5s\n", + "459600K .......... .......... .......... .......... .......... 77% 52.2M 5s\n", + "459650K .......... .......... .......... .......... .......... 77% 53.1M 5s\n", + "459700K .......... .......... .......... .......... .......... 77% 26.6M 5s\n", + "459750K .......... .......... .......... .......... .......... 77% 44.4M 5s\n", + "459800K .......... .......... .......... .......... .......... 77% 51.8M 5s\n", + "459850K .......... .......... .......... .......... .......... 77% 25.0M 5s\n", + "459900K .......... .......... .......... .......... .......... 77% 53.6M 5s\n", + "459950K .......... .......... .......... .......... .......... 77% 55.5M 5s\n", + "460000K .......... .......... .......... .......... .......... 77% 42.7M 5s\n", + "460050K .......... .......... .......... .......... .......... 77% 28.9M 5s\n", + "460100K .......... .......... .......... .......... .......... 77% 38.1M 5s\n", + "460150K .......... .......... .......... .......... .......... 77% 47.3M 5s\n", + "460200K .......... .......... .......... .......... .......... 77% 12.3M 5s\n", + "460250K .......... .......... .......... .......... .......... 77% 29.1M 5s\n", + "460300K .......... .......... .......... .......... .......... 77% 42.8M 5s\n", + "460350K .......... .......... .......... .......... .......... 77% 76.8M 5s\n", + "460400K .......... .......... .......... .......... .......... 77% 53.6M 5s\n", + "460450K .......... .......... .......... .......... .......... 77% 21.1M 5s\n", + "460500K .......... .......... .......... .......... .......... 77% 45.2M 5s\n", + "460550K .......... .......... .......... .......... .......... 77% 75.8M 5s\n", + "460600K .......... .......... .......... .......... .......... 77% 20.8M 5s\n", + "460650K .......... .......... .......... .......... .......... 77% 56.5M 5s\n", + "460700K .......... .......... .......... .......... .......... 77% 55.2M 5s\n", + "460750K .......... .......... .......... .......... .......... 77% 74.2M 5s\n", + "460800K .......... .......... .......... .......... .......... 77% 22.9M 5s\n", + "460850K .......... .......... .......... .......... .......... 77% 57.0M 5s\n", + "460900K .......... .......... .......... .......... .......... 77% 57.9M 5s\n", + "460950K .......... .......... .......... .......... .......... 77% 75.6M 5s\n", + "461000K .......... .......... .......... .......... .......... 77% 18.1M 5s\n", + "461050K .......... .......... .......... .......... .......... 77% 67.3M 5s\n", + "461100K .......... .......... .......... .......... .......... 77% 64.4M 5s\n", + "461150K .......... .......... .......... .......... .......... 77% 21.6M 5s\n", + "461200K .......... .......... .......... .......... .......... 77% 51.3M 5s\n", + "461250K .......... .......... .......... .......... .......... 77% 52.7M 5s\n", + "461300K .......... .......... .......... .......... .......... 77% 61.2M 5s\n", + "461350K .......... .......... .......... .......... .......... 77% 23.4M 5s\n", + "461400K .......... .......... .......... .......... .......... 77% 40.8M 5s\n", + "461450K .......... .......... .......... .......... .......... 77% 51.0M 5s\n", + "461500K .......... .......... .......... .......... .......... 77% 75.4M 5s\n", + "461550K .......... .......... .......... .......... .......... 77% 27.6M 5s\n", + "461600K .......... .......... .......... .......... .......... 77% 53.6M 5s\n", + "461650K .......... .......... .......... .......... .......... 77% 53.4M 5s\n", + "461700K .......... .......... .......... .......... .......... 77% 64.2M 5s\n", + "461750K .......... .......... .......... .......... .......... 77% 24.8M 5s\n", + "461800K .......... .......... .......... .......... .......... 77% 38.4M 5s\n", + "461850K .......... .......... .......... .......... .......... 77% 52.8M 5s\n", + "461900K .......... .......... .......... .......... .......... 77% 24.5M 5s\n", + "461950K .......... .......... .......... .......... .......... 77% 57.4M 5s\n", + "462000K .......... .......... .......... .......... .......... 77% 34.4M 5s\n", + "462050K .......... .......... .......... .......... .......... 77% 64.0M 5s\n", + "462100K .......... .......... .......... .......... .......... 77% 34.2M 5s\n", + "462150K .......... .......... .......... .......... .......... 77% 61.0M 5s\n", + "462200K .......... .......... .......... .......... .......... 77% 36.4M 5s\n", + "462250K .......... .......... .......... .......... .......... 77% 59.7M 5s\n", + "462300K .......... .......... .......... .......... .......... 77% 35.7M 5s\n", + "462350K .......... .......... .......... .......... .......... 77% 35.4M 5s\n", + "462400K .......... .......... .......... .......... .......... 77% 45.9M 5s\n", + "462450K .......... .......... .......... .......... .......... 77% 57.2M 5s\n", + "462500K .......... .......... .......... .......... .......... 77% 39.1M 5s\n", + "462550K .......... .......... .......... .......... .......... 77% 39.1M 5s\n", + "462600K .......... .......... .......... .......... .......... 77% 43.6M 5s\n", + "462650K .......... .......... .......... .......... .......... 77% 48.2M 5s\n", + "462700K .......... .......... .......... .......... .......... 77% 33.0M 5s\n", + "462750K .......... .......... .......... .......... .......... 77% 49.8M 5s\n", + "462800K .......... .......... .......... .......... .......... 77% 50.5M 5s\n", + "462850K .......... .......... .......... .......... .......... 77% 49.3M 5s\n", + "462900K .......... .......... .......... .......... .......... 77% 33.0M 5s\n", + "462950K .......... .......... .......... .......... .......... 77% 42.4M 5s\n", + "463000K .......... .......... .......... .......... .......... 77% 39.1M 5s\n", + "463050K .......... .......... .......... .......... .......... 77% 63.2M 5s\n", + "463100K .......... .......... .......... .......... .......... 77% 7.43M 5s\n", + "463150K .......... .......... .......... .......... .......... 77% 69.4M 5s\n", + "463200K .......... .......... .......... .......... .......... 77% 62.9M 5s\n", + "463250K .......... .......... .......... .......... .......... 77% 69.1M 5s\n", + "463300K .......... .......... .......... .......... .......... 77% 21.1M 5s\n", + "463350K .......... .......... .......... .......... .......... 77% 52.9M 5s\n", + "463400K .......... .......... .......... .......... .......... 77% 53.0M 5s\n", + "463450K .......... .......... .......... .......... .......... 77% 71.8M 5s\n", + "463500K .......... .......... .......... .......... .......... 77% 20.6M 5s\n", + "463550K .......... .......... .......... .......... .......... 77% 51.2M 5s\n", + "463600K .......... .......... .......... .......... .......... 77% 54.7M 5s\n", + "463650K .......... .......... .......... .......... .......... 77% 77.1M 5s\n", + "463700K .......... .......... .......... .......... .......... 77% 25.3M 5s\n", + "463750K .......... .......... .......... .......... .......... 77% 49.6M 5s\n", + "463800K .......... .......... .......... .......... .......... 77% 49.3M 5s\n", + "463850K .......... .......... .......... .......... .......... 78% 66.5M 5s\n", + "463900K .......... .......... .......... .......... .......... 78% 23.9M 5s\n", + "463950K .......... .......... .......... .......... .......... 78% 51.8M 5s\n", + "464000K .......... .......... .......... .......... .......... 78% 50.7M 5s\n", + "464050K .......... .......... .......... .......... .......... 78% 3.85M 5s\n", + "464100K .......... .......... .......... .......... .......... 78% 71.3M 5s\n", + "464150K .......... .......... .......... .......... .......... 78% 65.7M 5s\n", + "464200K .......... .......... .......... .......... .......... 78% 56.2M 5s\n", + "464250K .......... .......... .......... .......... .......... 78% 66.4M 5s\n", + "464300K .......... .......... .......... .......... .......... 78% 9.53M 5s\n", + "464350K .......... .......... .......... .......... .......... 78% 48.9M 5s\n", + "464400K .......... .......... .......... .......... .......... 78% 67.7M 5s\n", + "464450K .......... .......... .......... .......... .......... 78% 65.9M 5s\n", + "464500K .......... .......... .......... .......... .......... 78% 31.1M 5s\n", + "464550K .......... .......... .......... .......... .......... 78% 45.8M 5s\n", + "464600K .......... .......... .......... .......... .......... 78% 43.2M 5s\n", + "464650K .......... .......... .......... .......... .......... 78% 70.6M 5s\n", + "464700K .......... .......... .......... .......... .......... 78% 25.0M 5s\n", + "464750K .......... .......... .......... .......... .......... 78% 50.6M 5s\n", + "464800K .......... .......... .......... .......... .......... 78% 52.1M 5s\n", + "464850K .......... .......... .......... .......... .......... 78% 69.2M 5s\n", + "464900K .......... .......... .......... .......... .......... 78% 29.9M 5s\n", + "464950K .......... .......... .......... .......... .......... 78% 45.5M 5s\n", + "465000K .......... .......... .......... .......... .......... 78% 59.2M 5s\n", + "465050K .......... .......... .......... .......... .......... 78% 79.6M 5s\n", + "465100K .......... .......... .......... .......... .......... 78% 23.5M 5s\n", + "465150K .......... .......... .......... .......... .......... 78% 69.0M 5s\n", + "465200K .......... .......... .......... .......... .......... 78% 14.8M 5s\n", + "465250K .......... .......... .......... .......... .......... 78% 67.1M 5s\n", + "465300K .......... .......... .......... .......... .......... 78% 53.6M 5s\n", + "465350K .......... .......... .......... .......... .......... 78% 63.0M 5s\n", + "465400K .......... .......... .......... .......... .......... 78% 58.6M 5s\n", + "465450K .......... .......... .......... .......... .......... 78% 32.8M 5s\n", + "465500K .......... .......... .......... .......... .......... 78% 52.4M 5s\n", + "465550K .......... .......... .......... .......... .......... 78% 55.6M 5s\n", + "465600K .......... .......... .......... .......... .......... 78% 61.4M 5s\n", + "465650K .......... .......... .......... .......... .......... 78% 24.3M 5s\n", + "465700K .......... .......... .......... .......... .......... 78% 36.4M 5s\n", + "465750K .......... .......... .......... .......... .......... 78% 62.5M 5s\n", + "465800K .......... .......... .......... .......... .......... 78% 58.6M 5s\n", + "465850K .......... .......... .......... .......... .......... 78% 38.0M 5s\n", + "465900K .......... .......... .......... .......... .......... 78% 43.1M 5s\n", + "465950K .......... .......... .......... .......... .......... 78% 39.6M 5s\n", + "466000K .......... .......... .......... .......... .......... 78% 62.9M 5s\n", + "466050K .......... .......... .......... .......... .......... 78% 65.9M 5s\n", + "466100K .......... .......... .......... .......... .......... 78% 52.8M 5s\n", + "466150K .......... .......... .......... .......... .......... 78% 41.1M 5s\n", + "466200K .......... .......... .......... .......... .......... 78% 42.0M 5s\n", + "466250K .......... .......... .......... .......... .......... 78% 71.8M 5s\n", + "466300K .......... .......... .......... .......... .......... 78% 32.9M 5s\n", + "466350K .......... .......... .......... .......... .......... 78% 32.4M 5s\n", + "466400K .......... .......... .......... .......... .......... 78% 51.5M 5s\n", + "466450K .......... .......... .......... .......... .......... 78% 69.2M 5s\n", + "466500K .......... .......... .......... .......... .......... 78% 47.6M 5s\n", + "466550K .......... .......... .......... .......... .......... 78% 33.8M 5s\n", + "466600K .......... .......... .......... .......... .......... 78% 34.8M 5s\n", + "466650K .......... .......... .......... .......... .......... 78% 70.2M 5s\n", + "466700K .......... .......... .......... .......... .......... 78% 59.9M 5s\n", + "466750K .......... .......... .......... .......... .......... 78% 37.6M 5s\n", + "466800K .......... .......... .......... .......... .......... 78% 33.6M 5s\n", + "466850K .......... .......... .......... .......... .......... 78% 70.1M 5s\n", + "466900K .......... .......... .......... .......... .......... 78% 48.8M 5s\n", + "466950K .......... .......... .......... .......... .......... 78% 31.1M 5s\n", + "467000K .......... .......... .......... .......... .......... 78% 30.2M 5s\n", + "467050K .......... .......... .......... .......... .......... 78% 67.2M 5s\n", + "467100K .......... .......... .......... .......... .......... 78% 44.4M 5s\n", + "467150K .......... .......... .......... .......... .......... 78% 30.1M 5s\n", + "467200K .......... .......... .......... .......... .......... 78% 28.8M 5s\n", + "467250K .......... .......... .......... .......... .......... 78% 44.1M 5s\n", + "467300K .......... .......... .......... .......... .......... 78% 37.7M 5s\n", + "467350K .......... .......... .......... .......... .......... 78% 56.1M 4s\n", + "467400K .......... .......... .......... .......... .......... 78% 46.1M 4s\n", + "467450K .......... .......... .......... .......... .......... 78% 60.5M 4s\n", + "467500K .......... .......... .......... .......... .......... 78% 51.8M 4s\n", + "467550K .......... .......... .......... .......... .......... 78% 50.6M 4s\n", + "467600K .......... .......... .......... .......... .......... 78% 43.7M 4s\n", + "467650K .......... .......... .......... .......... .......... 78% 52.3M 4s\n", + "467700K .......... .......... .......... .......... .......... 78% 40.8M 4s\n", + "467750K .......... .......... .......... .......... .......... 78% 57.0M 4s\n", + "467800K .......... .......... .......... .......... .......... 78% 37.5M 4s\n", + "467850K .......... .......... .......... .......... .......... 78% 32.0M 4s\n", + "467900K .......... .......... .......... .......... .......... 78% 46.0M 4s\n", + "467950K .......... .......... .......... .......... .......... 78% 49.0M 4s\n", + "468000K .......... .......... .......... .......... .......... 78% 36.4M 4s\n", + "468050K .......... .......... .......... .......... .......... 78% 44.1M 4s\n", + "468100K .......... .......... .......... .......... .......... 78% 60.3M 4s\n", + "468150K .......... .......... .......... .......... .......... 78% 47.6M 4s\n", + "468200K .......... .......... .......... .......... .......... 78% 26.0M 4s\n", + "468250K .......... .......... .......... .......... .......... 78% 47.4M 4s\n", + "468300K .......... .......... .......... .......... .......... 78% 56.6M 4s\n", + "468350K .......... .......... .......... .......... .......... 78% 70.2M 4s\n", + "468400K .......... .......... .......... .......... .......... 78% 43.1M 4s\n", + "468450K .......... .......... .......... .......... .......... 78% 59.7M 4s\n", + "468500K .......... .......... .......... .......... .......... 78% 48.9M 4s\n", + "468550K .......... .......... .......... .......... .......... 78% 36.6M 4s\n", + "468600K .......... .......... .......... .......... .......... 78% 41.4M 4s\n", + "468650K .......... .......... .......... .......... .......... 78% 66.2M 4s\n", + "468700K .......... .......... .......... .......... .......... 78% 45.2M 4s\n", + "468750K .......... .......... .......... .......... .......... 78% 80.8M 4s\n", + "468800K .......... .......... .......... .......... .......... 78% 31.1M 4s\n", + "468850K .......... .......... .......... .......... .......... 78% 56.8M 4s\n", + "468900K .......... .......... .......... .......... .......... 78% 57.6M 4s\n", + "468950K .......... .......... .......... .......... .......... 78% 54.5M 4s\n", + "469000K .......... .......... .......... .......... .......... 78% 38.0M 4s\n", + "469050K .......... .......... .......... .......... .......... 78% 43.2M 4s\n", + "469100K .......... .......... .......... .......... .......... 78% 71.8M 4s\n", + "469150K .......... .......... .......... .......... .......... 78% 40.8M 4s\n", + "469200K .......... .......... .......... .......... .......... 78% 45.6M 4s\n", + "469250K .......... .......... .......... .......... .......... 78% 4.07M 4s\n", + "469300K .......... .......... .......... .......... .......... 78% 66.5M 4s\n", + "469350K .......... .......... .......... .......... .......... 78% 71.8M 4s\n", + "469400K .......... .......... .......... .......... .......... 78% 49.0M 4s\n", + "469450K .......... .......... .......... .......... .......... 78% 79.9M 4s\n", + "469500K .......... .......... .......... .......... .......... 78% 27.8M 4s\n", + "469550K .......... .......... .......... .......... .......... 78% 53.1M 4s\n", + "469600K .......... .......... .......... .......... .......... 78% 59.6M 4s\n", + "469650K .......... .......... .......... .......... .......... 78% 74.9M 4s\n", + "469700K .......... .......... .......... .......... .......... 78% 77.5M 4s\n", + "469750K .......... .......... .......... .......... .......... 78% 24.6M 4s\n", + "469800K .......... .......... .......... .......... .......... 79% 47.4M 4s\n", + "469850K .......... .......... .......... .......... .......... 79% 77.4M 4s\n", + "469900K .......... .......... .......... .......... .......... 79% 78.0M 4s\n", + "469950K .......... .......... .......... .......... .......... 79% 27.6M 4s\n", + "470000K .......... .......... .......... .......... .......... 79% 8.69M 4s\n", + "470050K .......... .......... .......... .......... .......... 79% 69.4M 4s\n", + "470100K .......... .......... .......... .......... .......... 79% 69.9M 4s\n", + "470150K .......... .......... .......... .......... .......... 79% 63.6M 4s\n", + "470200K .......... .......... .......... .......... .......... 79% 23.0M 4s\n", + "470250K .......... .......... .......... .......... .......... 79% 52.5M 4s\n", + "470300K .......... .......... .......... .......... .......... 79% 51.6M 4s\n", + "470350K .......... .......... .......... .......... .......... 79% 70.9M 4s\n", + "470400K .......... .......... .......... .......... .......... 79% 64.1M 4s\n", + "470450K .......... .......... .......... .......... .......... 79% 33.2M 4s\n", + "470500K .......... .......... .......... .......... .......... 79% 44.3M 4s\n", + "470550K .......... .......... .......... .......... .......... 79% 67.7M 4s\n", + "470600K .......... .......... .......... .......... .......... 79% 61.4M 4s\n", + "470650K .......... .......... .......... .......... .......... 79% 69.8M 4s\n", + "470700K .......... .......... .......... .......... .......... 79% 33.1M 4s\n", + "470750K .......... .......... .......... .......... .......... 79% 47.8M 4s\n", + "470800K .......... .......... .......... .......... .......... 79% 57.6M 4s\n", + "470850K .......... .......... .......... .......... .......... 79% 72.4M 4s\n", + "470900K .......... .......... .......... .......... .......... 79% 30.6M 4s\n", + "470950K .......... .......... .......... .......... .......... 79% 53.1M 4s\n", + "471000K .......... .......... .......... .......... .......... 79% 54.4M 4s\n", + "471050K .......... .......... .......... .......... .......... 79% 68.1M 4s\n", + "471100K .......... .......... .......... .......... .......... 79% 72.5M 4s\n", + "471150K .......... .......... .......... .......... .......... 79% 34.7M 4s\n", + "471200K .......... .......... .......... .......... .......... 79% 4.39M 4s\n", + "471250K .......... .......... .......... .......... .......... 79% 69.6M 4s\n", + "471300K .......... .......... .......... .......... .......... 79% 82.5M 4s\n", + "471350K .......... .......... .......... .......... .......... 79% 70.7M 4s\n", + "471400K .......... .......... .......... .......... .......... 79% 56.4M 4s\n", + "471450K .......... .......... .......... .......... .......... 79% 66.3M 4s\n", + "471500K .......... .......... .......... .......... .......... 79% 30.2M 4s\n", + "471550K .......... .......... .......... .......... .......... 79% 47.4M 4s\n", + "471600K .......... .......... .......... .......... .......... 79% 67.3M 4s\n", + "471650K .......... .......... .......... .......... .......... 79% 75.5M 4s\n", + "471700K .......... .......... .......... .......... .......... 79% 80.5M 4s\n", + "471750K .......... .......... .......... .......... .......... 79% 32.9M 4s\n", + "471800K .......... .......... .......... .......... .......... 79% 15.2M 4s\n", + "471850K .......... .......... .......... .......... .......... 79% 61.5M 4s\n", + "471900K .......... .......... .......... .......... .......... 79% 65.3M 4s\n", + "471950K .......... .......... .......... .......... .......... 79% 76.1M 4s\n", + "472000K .......... .......... .......... .......... .......... 79% 67.7M 4s\n", + "472050K .......... .......... .......... .......... .......... 79% 30.1M 4s\n", + "472100K .......... .......... .......... .......... .......... 79% 62.5M 4s\n", + "472150K .......... .......... .......... .......... .......... 79% 55.6M 4s\n", + "472200K .......... .......... .......... .......... .......... 79% 62.6M 4s\n", + "472250K .......... .......... .......... .......... .......... 79% 31.6M 4s\n", + "472300K .......... .......... .......... .......... .......... 79% 59.3M 4s\n", + "472350K .......... .......... .......... .......... .......... 79% 53.2M 4s\n", + "472400K .......... .......... .......... .......... .......... 79% 62.3M 4s\n", + "472450K .......... .......... .......... .......... .......... 79% 73.4M 4s\n", + "472500K .......... .......... .......... .......... .......... 79% 32.8M 4s\n", + "472550K .......... .......... .......... .......... .......... 79% 60.9M 4s\n", + "472600K .......... .......... .......... .......... .......... 79% 45.5M 4s\n", + "472650K .......... .......... .......... .......... .......... 79% 61.7M 4s\n", + "472700K .......... .......... .......... .......... .......... 79% 71.1M 4s\n", + "472750K .......... .......... .......... .......... .......... 79% 34.7M 4s\n", + "472800K .......... .......... .......... .......... .......... 79% 33.4M 4s\n", + "472850K .......... .......... .......... .......... .......... 79% 32.8M 4s\n", + "472900K .......... .......... .......... .......... .......... 79% 36.7M 4s\n", + "472950K .......... .......... .......... .......... .......... 79% 60.4M 4s\n", + "473000K .......... .......... .......... .......... .......... 79% 22.4M 4s\n", + "473050K .......... .......... .......... .......... .......... 79% 64.6M 4s\n", + "473100K .......... .......... .......... .......... .......... 79% 62.3M 4s\n", + "473150K .......... .......... .......... .......... .......... 79% 82.2M 4s\n", + "473200K .......... .......... .......... .......... .......... 79% 64.8M 4s\n", + "473250K .......... .......... .......... .......... .......... 79% 29.9M 4s\n", + "473300K .......... .......... .......... .......... .......... 79% 53.6M 4s\n", + "473350K .......... .......... .......... .......... .......... 79% 52.3M 4s\n", + "473400K .......... .......... .......... .......... .......... 79% 65.1M 4s\n", + "473450K .......... .......... .......... .......... .......... 79% 46.3M 4s\n", + "473500K .......... .......... .......... .......... .......... 79% 52.5M 4s\n", + "473550K .......... .......... .......... .......... .......... 79% 54.5M 4s\n", + "473600K .......... .......... .......... .......... .......... 79% 50.1M 4s\n", + "473650K .......... .......... .......... .......... .......... 79% 72.6M 4s\n", + "473700K .......... .......... .......... .......... .......... 79% 42.1M 4s\n", + "473750K .......... .......... .......... .......... .......... 79% 54.6M 4s\n", + "473800K .......... .......... .......... .......... .......... 79% 17.5M 4s\n", + "473850K .......... .......... .......... .......... .......... 79% 71.4M 4s\n", + "473900K .......... .......... .......... .......... .......... 79% 56.5M 4s\n", + "473950K .......... .......... .......... .......... .......... 79% 71.5M 4s\n", + "474000K .......... .......... .......... .......... .......... 79% 64.2M 4s\n", + "474050K .......... .......... .......... .......... .......... 79% 26.0M 4s\n", + "474100K .......... .......... .......... .......... .......... 79% 58.4M 4s\n", + "474150K .......... .......... .......... .......... .......... 79% 64.4M 4s\n", + "474200K .......... .......... .......... .......... .......... 79% 60.7M 4s\n", + "474250K .......... .......... .......... .......... .......... 79% 72.4M 4s\n", + "474300K .......... .......... .......... .......... .......... 79% 34.8M 4s\n", + "474350K .......... .......... .......... .......... .......... 79% 54.2M 4s\n", + "474400K .......... .......... .......... .......... .......... 79% 54.4M 4s\n", + "474450K .......... .......... .......... .......... .......... 79% 75.9M 4s\n", + "474500K .......... .......... .......... .......... .......... 79% 75.2M 4s\n", + "474550K .......... .......... .......... .......... .......... 79% 27.7M 4s\n", + "474600K .......... .......... .......... .......... .......... 79% 46.0M 4s\n", + "474650K .......... .......... .......... .......... .......... 79% 63.5M 4s\n", + "474700K .......... .......... .......... .......... .......... 79% 79.5M 4s\n", + "474750K .......... .......... .......... .......... .......... 79% 36.3M 4s\n", + "474800K .......... .......... .......... .......... .......... 79% 50.7M 4s\n", + "474850K .......... .......... .......... .......... .......... 79% 50.9M 4s\n", + "474900K .......... .......... .......... .......... .......... 79% 71.4M 4s\n", + "474950K .......... .......... .......... .......... .......... 79% 71.4M 4s\n", + "475000K .......... .......... .......... .......... .......... 79% 40.9M 4s\n", + "475050K .......... .......... .......... .......... .......... 79% 55.0M 4s\n", + "475100K .......... .......... .......... .......... .......... 79% 55.5M 4s\n", + "475150K .......... .......... .......... .......... .......... 79% 63.1M 4s\n", + "475200K .......... .......... .......... .......... .......... 79% 76.3M 4s\n", + "475250K .......... .......... .......... .......... .......... 79% 38.3M 4s\n", + "475300K .......... .......... .......... .......... .......... 79% 49.6M 4s\n", + "475350K .......... .......... .......... .......... .......... 79% 70.3M 4s\n", + "475400K .......... .......... .......... .......... .......... 79% 61.4M 4s\n", + "475450K .......... .......... .......... .......... .......... 79% 77.1M 4s\n", + "475500K .......... .......... .......... .......... .......... 79% 43.8M 4s\n", + "475550K .......... .......... .......... .......... .......... 79% 51.5M 4s\n", + "475600K .......... .......... .......... .......... .......... 79% 45.9M 4s\n", + "475650K .......... .......... .......... .......... .......... 79% 55.0M 4s\n", + "475700K .......... .......... .......... .......... .......... 79% 75.7M 4s\n", + "475750K .......... .......... .......... .......... .......... 80% 71.1M 4s\n", + "475800K .......... .......... .......... .......... .......... 80% 39.5M 4s\n", + "475850K .......... .......... .......... .......... .......... 80% 52.1M 4s\n", + "475900K .......... .......... .......... .......... .......... 80% 51.2M 4s\n", + "475950K .......... .......... .......... .......... .......... 80% 68.1M 4s\n", + "476000K .......... .......... .......... .......... .......... 80% 59.2M 4s\n", + "476050K .......... .......... .......... .......... .......... 80% 55.7M 4s\n", + "476100K .......... .......... .......... .......... .......... 80% 46.7M 4s\n", + "476150K .......... .......... .......... .......... .......... 80% 48.8M 4s\n", + "476200K .......... .......... .......... .......... .......... 80% 66.2M 4s\n", + "476250K .......... .......... .......... .......... .......... 80% 71.1M 4s\n", + "476300K .......... .......... .......... .......... .......... 80% 63.8M 4s\n", + "476350K .......... .......... .......... .......... .......... 80% 50.2M 4s\n", + "476400K .......... .......... .......... .......... .......... 80% 50.9M 4s\n", + "476450K .......... .......... .......... .......... .......... 80% 66.4M 4s\n", + "476500K .......... .......... .......... .......... .......... 80% 74.2M 4s\n", + "476550K .......... .......... .......... .......... .......... 80% 33.6M 4s\n", + "476600K .......... .......... .......... .......... .......... 80% 50.4M 4s\n", + "476650K .......... .......... .......... .......... .......... 80% 59.7M 4s\n", + "476700K .......... .......... .......... .......... .......... 80% 69.3M 4s\n", + "476750K .......... .......... .......... .......... .......... 80% 56.7M 4s\n", + "476800K .......... .......... .......... .......... .......... 80% 45.0M 4s\n", + "476850K .......... .......... .......... .......... .......... 80% 10.4M 4s\n", + "476900K .......... .......... .......... .......... .......... 80% 80.1M 4s\n", + "476950K .......... .......... .......... .......... .......... 80% 74.0M 4s\n", + "477000K .......... .......... .......... .......... .......... 80% 66.4M 4s\n", + "477050K .......... .......... .......... .......... .......... 80% 79.3M 4s\n", + "477100K .......... .......... .......... .......... .......... 80% 20.3M 4s\n", + "477150K .......... .......... .......... .......... .......... 80% 14.4M 4s\n", + "477200K .......... .......... .......... .......... .......... 80% 62.6M 4s\n", + "477250K .......... .......... .......... .......... .......... 80% 61.3M 4s\n", + "477300K .......... .......... .......... .......... .......... 80% 77.1M 4s\n", + "477350K .......... .......... .......... .......... .......... 80% 76.2M 4s\n", + "477400K .......... .......... .......... .......... .......... 80% 28.4M 4s\n", + "477450K .......... .......... .......... .......... .......... 80% 51.2M 4s\n", + "477500K .......... .......... .......... .......... .......... 80% 56.6M 4s\n", + "477550K .......... .......... .......... .......... .......... 80% 70.6M 4s\n", + "477600K .......... .......... .......... .......... .......... 80% 60.9M 4s\n", + "477650K .......... .......... .......... .......... .......... 80% 59.5M 4s\n", + "477700K .......... .......... .......... .......... .......... 80% 55.9M 4s\n", + "477750K .......... .......... .......... .......... .......... 80% 47.1M 4s\n", + "477800K .......... .......... .......... .......... .......... 80% 50.4M 4s\n", + "477850K .......... .......... .......... .......... .......... 80% 66.6M 4s\n", + "477900K .......... .......... .......... .......... .......... 80% 72.8M 4s\n", + "477950K .......... .......... .......... .......... .......... 80% 51.8M 4s\n", + "478000K .......... .......... .......... .......... .......... 80% 46.5M 4s\n", + "478050K .......... .......... .......... .......... .......... 80% 57.0M 4s\n", + "478100K .......... .......... .......... .......... .......... 80% 74.8M 4s\n", + "478150K .......... .......... .......... .......... .......... 80% 86.0M 4s\n", + "478200K .......... .......... .......... .......... .......... 80% 34.2M 4s\n", + "478250K .......... .......... .......... .......... .......... 80% 56.0M 4s\n", + "478300K .......... .......... .......... .......... .......... 80% 58.3M 4s\n", + "478350K .......... .......... .......... .......... .......... 80% 73.0M 4s\n", + "478400K .......... .......... .......... .......... .......... 80% 56.2M 4s\n", + "478450K .......... .......... .......... .......... .......... 80% 53.8M 4s\n", + "478500K .......... .......... .......... .......... .......... 80% 51.9M 4s\n", + "478550K .......... .......... .......... .......... .......... 80% 46.8M 4s\n", + "478600K .......... .......... .......... .......... .......... 80% 55.5M 4s\n", + "478650K .......... .......... .......... .......... .......... 80% 69.5M 4s\n", + "478700K .......... .......... .......... .......... .......... 80% 69.0M 4s\n", + "478750K .......... .......... .......... .......... .......... 80% 51.9M 4s\n", + "478800K .......... .......... .......... .......... .......... 80% 45.3M 4s\n", + "478850K .......... .......... .......... .......... .......... 80% 54.0M 4s\n", + "478900K .......... .......... .......... .......... .......... 80% 61.3M 4s\n", + "478950K .......... .......... .......... .......... .......... 80% 58.5M 4s\n", + "479000K .......... .......... .......... .......... .......... 80% 59.5M 4s\n", + "479050K .......... .......... .......... .......... .......... 80% 64.7M 4s\n", + "479100K .......... .......... .......... .......... .......... 80% 51.1M 4s\n", + "479150K .......... .......... .......... .......... .......... 80% 71.8M 4s\n", + "479200K .......... .......... .......... .......... .......... 80% 57.2M 4s\n", + "479250K .......... .......... .......... .......... .......... 80% 58.1M 4s\n", + "479300K .......... .......... .......... .......... .......... 80% 49.5M 4s\n", + "479350K .......... .......... .......... .......... .......... 80% 48.0M 4s\n", + "479400K .......... .......... .......... .......... .......... 80% 53.2M 4s\n", + "479450K .......... .......... .......... .......... .......... 80% 72.6M 4s\n", + "479500K .......... .......... .......... .......... .......... 80% 59.8M 4s\n", + "479550K .......... .......... .......... .......... .......... 80% 66.6M 4s\n", + "479600K .......... .......... .......... .......... .......... 80% 43.0M 4s\n", + "479650K .......... .......... .......... .......... .......... 80% 50.6M 4s\n", + "479700K .......... .......... .......... .......... .......... 80% 57.0M 4s\n", + "479750K .......... .......... .......... .......... .......... 80% 76.7M 4s\n", + "479800K .......... .......... .......... .......... .......... 80% 44.3M 4s\n", + "479850K .......... .......... .......... .......... .......... 80% 52.5M 4s\n", + "479900K .......... .......... .......... .......... .......... 80% 51.8M 4s\n", + "479950K .......... .......... .......... .......... .......... 80% 46.5M 4s\n", + "480000K .......... .......... .......... .......... .......... 80% 52.2M 4s\n", + "480050K .......... .......... .......... .......... .......... 80% 48.1M 4s\n", + "480100K .......... .......... .......... .......... .......... 80% 49.3M 4s\n", + "480150K .......... .......... .......... .......... .......... 80% 66.9M 4s\n", + "480200K .......... .......... .......... .......... .......... 80% 50.0M 4s\n", + "480250K .......... .......... .......... .......... .......... 80% 59.4M 4s\n", + "480300K .......... .......... .......... .......... .......... 80% 65.1M 4s\n", + "480350K .......... .......... .......... .......... .......... 80% 61.2M 4s\n", + "480400K .......... .......... .......... .......... .......... 80% 54.1M 4s\n", + "480450K .......... .......... .......... .......... .......... 80% 67.6M 4s\n", + "480500K .......... .......... .......... .......... .......... 80% 67.4M 4s\n", + "480550K .......... .......... .......... .......... .......... 80% 53.1M 4s\n", + "480600K .......... .......... .......... .......... .......... 80% 45.7M 4s\n", + "480650K .......... .......... .......... .......... .......... 80% 59.8M 4s\n", + "480700K .......... .......... .......... .......... .......... 80% 72.9M 4s\n", + "480750K .......... .......... .......... .......... .......... 80% 68.1M 4s\n", + "480800K .......... .......... .......... .......... .......... 80% 56.5M 4s\n", + "480850K .......... .......... .......... .......... .......... 80% 59.5M 4s\n", + "480900K .......... .......... .......... .......... .......... 80% 61.7M 4s\n", + "480950K .......... .......... .......... .......... .......... 80% 60.1M 4s\n", + "481000K .......... .......... .......... .......... .......... 80% 57.2M 4s\n", + "481050K .......... .......... .......... .......... .......... 80% 65.5M 4s\n", + "481100K .......... .......... .......... .......... .......... 80% 33.8M 4s\n", + "481150K .......... .......... .......... .......... .......... 80% 36.7M 4s\n", + "481200K .......... .......... .......... .......... .......... 80% 29.4M 4s\n", + "481250K .......... .......... .......... .......... .......... 80% 50.2M 4s\n", + "481300K .......... .......... .......... .......... .......... 80% 7.87M 4s\n", + "481350K .......... .......... .......... .......... .......... 80% 70.9M 4s\n", + "481400K .......... .......... .......... .......... .......... 80% 64.5M 4s\n", + "481450K .......... .......... .......... .......... .......... 80% 80.0M 4s\n", + "481500K .......... .......... .......... .......... .......... 80% 78.7M 4s\n", + "481550K .......... .......... .......... .......... .......... 80% 71.2M 4s\n", + "481600K .......... .......... .......... .......... .......... 80% 59.4M 4s\n", + "481650K .......... .......... .......... .......... .......... 80% 48.8M 4s\n", + "481700K .......... .......... .......... .......... .......... 81% 47.9M 4s\n", + "481750K .......... .......... .......... .......... .......... 81% 68.5M 4s\n", + "481800K .......... .......... .......... .......... .......... 81% 56.8M 4s\n", + "481850K .......... .......... .......... .......... .......... 81% 62.3M 4s\n", + "481900K .......... .......... .......... .......... .......... 81% 50.8M 4s\n", + "481950K .......... .......... .......... .......... .......... 81% 54.3M 4s\n", + "482000K .......... .......... .......... .......... .......... 81% 50.4M 4s\n", + "482050K .......... .......... .......... .......... .......... 81% 68.3M 4s\n", + "482100K .......... .......... .......... .......... .......... 81% 77.3M 4s\n", + "482150K .......... .......... .......... .......... .......... 81% 65.9M 4s\n", + "482200K .......... .......... .......... .......... .......... 81% 52.6M 4s\n", + "482250K .......... .......... .......... .......... .......... 81% 51.1M 4s\n", + "482300K .......... .......... .......... .......... .......... 81% 69.3M 4s\n", + "482350K .......... .......... .......... .......... .......... 81% 76.9M 4s\n", + "482400K .......... .......... .......... .......... .......... 81% 61.1M 4s\n", + "482450K .......... .......... .......... .......... .......... 81% 47.0M 4s\n", + "482500K .......... .......... .......... .......... .......... 81% 53.5M 4s\n", + "482550K .......... .......... .......... .......... .......... 81% 50.6M 4s\n", + "482600K .......... .......... .......... .......... .......... 81% 58.1M 4s\n", + "482650K .......... .......... .......... .......... .......... 81% 72.2M 4s\n", + "482700K .......... .......... .......... .......... .......... 81% 57.3M 4s\n", + "482750K .......... .......... .......... .......... .......... 81% 52.9M 4s\n", + "482800K .......... .......... .......... .......... .......... 81% 46.6M 4s\n", + "482850K .......... .......... .......... .......... .......... 81% 65.8M 4s\n", + "482900K .......... .......... .......... .......... .......... 81% 67.4M 4s\n", + "482950K .......... .......... .......... .......... .......... 81% 70.0M 4s\n", + "483000K .......... .......... .......... .......... .......... 81% 49.1M 4s\n", + "483050K .......... .......... .......... .......... .......... 81% 48.4M 4s\n", + "483100K .......... .......... .......... .......... .......... 81% 61.8M 4s\n", + "483150K .......... .......... .......... .......... .......... 81% 79.8M 4s\n", + "483200K .......... .......... .......... .......... .......... 81% 68.6M 4s\n", + "483250K .......... .......... .......... .......... .......... 81% 50.6M 4s\n", + "483300K .......... .......... .......... .......... .......... 81% 53.9M 4s\n", + "483350K .......... .......... .......... .......... .......... 81% 45.2M 4s\n", + "483400K .......... .......... .......... .......... .......... 81% 68.0M 4s\n", + "483450K .......... .......... .......... .......... .......... 81% 66.3M 4s\n", + "483500K .......... .......... .......... .......... .......... 81% 53.3M 4s\n", + "483550K .......... .......... .......... .......... .......... 81% 47.4M 4s\n", + "483600K .......... .......... .......... .......... .......... 81% 42.8M 4s\n", + "483650K .......... .......... .......... .......... .......... 81% 67.6M 4s\n", + "483700K .......... .......... .......... .......... .......... 81% 62.3M 4s\n", + "483750K .......... .......... .......... .......... .......... 81% 62.5M 4s\n", + "483800K .......... .......... .......... .......... .......... 81% 41.9M 4s\n", + "483850K .......... .......... .......... .......... .......... 81% 47.4M 4s\n", + "483900K .......... .......... .......... .......... .......... 81% 55.5M 4s\n", + "483950K .......... .......... .......... .......... .......... 81% 63.3M 4s\n", + "484000K .......... .......... .......... .......... .......... 81% 45.3M 4s\n", + "484050K .......... .......... .......... .......... .......... 81% 60.9M 4s\n", + "484100K .......... .......... .......... .......... .......... 81% 55.6M 4s\n", + "484150K .......... .......... .......... .......... .......... 81% 63.0M 4s\n", + "484200K .......... .......... .......... .......... .......... 81% 53.5M 4s\n", + "484250K .......... .......... .......... .......... .......... 81% 71.2M 4s\n", + "484300K .......... .......... .......... .......... .......... 81% 60.8M 4s\n", + "484350K .......... .......... .......... .......... .......... 81% 55.6M 4s\n", + "484400K .......... .......... .......... .......... .......... 81% 56.2M 4s\n", + "484450K .......... .......... .......... .......... .......... 81% 56.9M 4s\n", + "484500K .......... .......... .......... .......... .......... 81% 73.4M 4s\n", + "484550K .......... .......... .......... .......... .......... 81% 70.3M 4s\n", + "484600K .......... .......... .......... .......... .......... 81% 45.4M 4s\n", + "484650K .......... .......... .......... .......... .......... 81% 40.0M 4s\n", + "484700K .......... .......... .......... .......... .......... 81% 37.5M 4s\n", + "484750K .......... .......... .......... .......... .......... 81% 55.9M 4s\n", + "484800K .......... .......... .......... .......... .......... 81% 41.9M 4s\n", + "484850K .......... .......... .......... .......... .......... 81% 56.6M 4s\n", + "484900K .......... .......... .......... .......... .......... 81% 59.6M 4s\n", + "484950K .......... .......... .......... .......... .......... 81% 59.7M 4s\n", + "485000K .......... .......... .......... .......... .......... 81% 48.2M 4s\n", + "485050K .......... .......... .......... .......... .......... 81% 64.6M 4s\n", + "485100K .......... .......... .......... .......... .......... 81% 53.4M 4s\n", + "485150K .......... .......... .......... .......... .......... 81% 60.8M 4s\n", + "485200K .......... .......... .......... .......... .......... 81% 62.7M 4s\n", + "485250K .......... .......... .......... .......... .......... 81% 46.6M 4s\n", + "485300K .......... .......... .......... .......... .......... 81% 67.8M 4s\n", + "485350K .......... .......... .......... .......... .......... 81% 56.6M 4s\n", + "485400K .......... .......... .......... .......... .......... 81% 51.3M 4s\n", + "485450K .......... .......... .......... .......... .......... 81% 68.4M 4s\n", + "485500K .......... .......... .......... .......... .......... 81% 8.57M 4s\n", + "485550K .......... .......... .......... .......... .......... 81% 46.4M 4s\n", + "485600K .......... .......... .......... .......... .......... 81% 59.4M 4s\n", + "485650K .......... .......... .......... .......... .......... 81% 73.6M 4s\n", + "485700K .......... .......... .......... .......... .......... 81% 72.1M 4s\n", + "485750K .......... .......... .......... .......... .......... 81% 74.1M 4s\n", + "485800K .......... .......... .......... .......... .......... 81% 56.6M 4s\n", + "485850K .......... .......... .......... .......... .......... 81% 44.2M 4s\n", + "485900K .......... .......... .......... .......... .......... 81% 44.6M 4s\n", + "485950K .......... .......... .......... .......... .......... 81% 45.2M 4s\n", + "486000K .......... .......... .......... .......... .......... 81% 44.4M 4s\n", + "486050K .......... .......... .......... .......... .......... 81% 43.1M 4s\n", + "486100K .......... .......... .......... .......... .......... 81% 39.9M 4s\n", + "486150K .......... .......... .......... .......... .......... 81% 48.5M 4s\n", + "486200K .......... .......... .......... .......... .......... 81% 45.4M 4s\n", + "486250K .......... .......... .......... .......... .......... 81% 54.7M 4s\n", + "486300K .......... .......... .......... .......... .......... 81% 53.3M 4s\n", + "486350K .......... .......... .......... .......... .......... 81% 51.5M 4s\n", + "486400K .......... .......... .......... .......... .......... 81% 63.8M 4s\n", + "486450K .......... .......... .......... .......... .......... 81% 68.1M 4s\n", + "486500K .......... .......... .......... .......... .......... 81% 63.2M 4s\n", + "486550K .......... .......... .......... .......... .......... 81% 54.7M 4s\n", + "486600K .......... .......... .......... .......... .......... 81% 39.4M 4s\n", + "486650K .......... .......... .......... .......... .......... 81% 42.2M 4s\n", + "486700K .......... .......... .......... .......... .......... 81% 46.5M 4s\n", + "486750K .......... .......... .......... .......... .......... 81% 38.8M 4s\n", + "486800K .......... .......... .......... .......... .......... 81% 36.0M 4s\n", + "486850K .......... .......... .......... .......... .......... 81% 53.6M 4s\n", + "486900K .......... .......... .......... .......... .......... 81% 53.1M 4s\n", + "486950K .......... .......... .......... .......... .......... 81% 35.9M 4s\n", + "487000K .......... .......... .......... .......... .......... 81% 25.6M 4s\n", + "487050K .......... .......... .......... .......... .......... 81% 38.8M 4s\n", + "487100K .......... .......... .......... .......... .......... 81% 44.1M 4s\n", + "487150K .......... .......... .......... .......... .......... 81% 59.3M 4s\n", + "487200K .......... .......... .......... .......... .......... 81% 57.4M 4s\n", + "487250K .......... .......... .......... .......... .......... 81% 66.4M 4s\n", + "487300K .......... .......... .......... .......... .......... 81% 73.7M 4s\n", + "487350K .......... .......... .......... .......... .......... 81% 66.8M 4s\n", + "487400K .......... .......... .......... .......... .......... 81% 57.7M 4s\n", + "487450K .......... .......... .......... .......... .......... 81% 53.9M 4s\n", + "487500K .......... .......... .......... .......... .......... 81% 46.9M 4s\n", + "487550K .......... .......... .......... .......... .......... 81% 50.4M 4s\n", + "487600K .......... .......... .......... .......... .......... 81% 45.3M 4s\n", + "487650K .......... .......... .......... .......... .......... 82% 56.9M 4s\n", + "487700K .......... .......... .......... .......... .......... 82% 53.8M 4s\n", + "487750K .......... .......... .......... .......... .......... 82% 46.2M 4s\n", + "487800K .......... .......... .......... .......... .......... 82% 43.2M 4s\n", + "487850K .......... .......... .......... .......... .......... 82% 68.2M 4s\n", + "487900K .......... .......... .......... .......... .......... 82% 64.8M 4s\n", + "487950K .......... .......... .......... .......... .......... 82% 55.7M 4s\n", + "488000K .......... .......... .......... .......... .......... 82% 51.0M 4s\n", + "488050K .......... .......... .......... .......... .......... 82% 49.9M 4s\n", + "488100K .......... .......... .......... .......... .......... 82% 64.3M 4s\n", + "488150K .......... .......... .......... .......... .......... 82% 72.5M 4s\n", + "488200K .......... .......... .......... .......... .......... 82% 39.2M 4s\n", + "488250K .......... .......... .......... .......... .......... 82% 47.6M 4s\n", + "488300K .......... .......... .......... .......... .......... 82% 50.3M 4s\n", + "488350K .......... .......... .......... .......... .......... 82% 69.9M 4s\n", + "488400K .......... .......... .......... .......... .......... 82% 67.4M 4s\n", + "488450K .......... .......... .......... .......... .......... 82% 54.6M 4s\n", + "488500K .......... .......... .......... .......... .......... 82% 58.3M 4s\n", + "488550K .......... .......... .......... .......... .......... 82% 59.8M 4s\n", + "488600K .......... .......... .......... .......... .......... 82% 44.5M 4s\n", + "488650K .......... .......... .......... .......... .......... 82% 62.0M 4s\n", + "488700K .......... .......... .......... .......... .......... 82% 67.3M 4s\n", + "488750K .......... .......... .......... .......... .......... 82% 53.8M 4s\n", + "488800K .......... .......... .......... .......... .......... 82% 56.9M 4s\n", + "488850K .......... .......... .......... .......... .......... 82% 53.1M 4s\n", + "488900K .......... .......... .......... .......... .......... 82% 40.7M 4s\n", + "488950K .......... .......... .......... .......... .......... 82% 33.5M 4s\n", + "489000K .......... .......... .......... .......... .......... 82% 27.4M 4s\n", + "489050K .......... .......... .......... .......... .......... 82% 41.7M 4s\n", + "489100K .......... .......... .......... .......... .......... 82% 41.1M 4s\n", + "489150K .......... .......... .......... .......... .......... 82% 34.3M 4s\n", + "489200K .......... .......... .......... .......... .......... 82% 31.6M 4s\n", + "489250K .......... .......... .......... .......... .......... 82% 5.31M 4s\n", + "489300K .......... .......... .......... .......... .......... 82% 63.7M 4s\n", + "489350K .......... .......... .......... .......... .......... 82% 48.5M 4s\n", + "489400K .......... .......... .......... .......... .......... 82% 46.6M 4s\n", + "489450K .......... .......... .......... .......... .......... 82% 68.6M 4s\n", + "489500K .......... .......... .......... .......... .......... 82% 44.3M 4s\n", + "489550K .......... .......... .......... .......... .......... 82% 24.4M 4s\n", + "489600K .......... .......... .......... .......... .......... 82% 52.1M 4s\n", + "489650K .......... .......... .......... .......... .......... 82% 68.2M 4s\n", + "489700K .......... .......... .......... .......... .......... 82% 63.0M 4s\n", + "489750K .......... .......... .......... .......... .......... 82% 65.3M 4s\n", + "489800K .......... .......... .......... .......... .......... 82% 28.4M 4s\n", + "489850K .......... .......... .......... .......... .......... 82% 31.7M 4s\n", + "489900K .......... .......... .......... .......... .......... 82% 57.5M 4s\n", + "489950K .......... .......... .......... .......... .......... 82% 64.9M 4s\n", + "490000K .......... .......... .......... .......... .......... 82% 36.6M 4s\n", + "490050K .......... .......... .......... .......... .......... 82% 40.4M 4s\n", + "490100K .......... .......... .......... .......... .......... 82% 47.1M 4s\n", + "490150K .......... .......... .......... .......... .......... 82% 58.5M 4s\n", + "490200K .......... .......... .......... .......... .......... 82% 49.2M 4s\n", + "490250K .......... .......... .......... .......... .......... 82% 62.4M 4s\n", + "490300K .......... .......... .......... .......... .......... 82% 48.7M 4s\n", + "490350K .......... .......... .......... .......... .......... 82% 46.7M 4s\n", + "490400K .......... .......... .......... .......... .......... 82% 62.8M 4s\n", + "490450K .......... .......... .......... .......... .......... 82% 63.6M 4s\n", + "490500K .......... .......... .......... .......... .......... 82% 63.0M 4s\n", + "490550K .......... .......... .......... .......... .......... 82% 55.1M 4s\n", + "490600K .......... .......... .......... .......... .......... 82% 37.7M 4s\n", + "490650K .......... .......... .......... .......... .......... 82% 74.8M 4s\n", + "490700K .......... .......... .......... .......... .......... 82% 64.5M 4s\n", + "490750K .......... .......... .......... .......... .......... 82% 48.8M 4s\n", + "490800K .......... .......... .......... .......... .......... 82% 49.1M 4s\n", + "490850K .......... .......... .......... .......... .......... 82% 46.9M 4s\n", + "490900K .......... .......... .......... .......... .......... 82% 47.5M 4s\n", + "490950K .......... .......... .......... .......... .......... 82% 48.6M 4s\n", + "491000K .......... .......... .......... .......... .......... 82% 34.9M 4s\n", + "491050K .......... .......... .......... .......... .......... 82% 48.1M 4s\n", + "491100K .......... .......... .......... .......... .......... 82% 45.4M 4s\n", + "491150K .......... .......... .......... .......... .......... 82% 39.7M 4s\n", + "491200K .......... .......... .......... .......... .......... 82% 38.6M 4s\n", + "491250K .......... .......... .......... .......... .......... 82% 38.7M 4s\n", + "491300K .......... .......... .......... .......... .......... 82% 68.1M 4s\n", + "491350K .......... .......... .......... .......... .......... 82% 59.3M 4s\n", + "491400K .......... .......... .......... .......... .......... 82% 45.1M 4s\n", + "491450K .......... .......... .......... .......... .......... 82% 55.1M 4s\n", + "491500K .......... .......... .......... .......... .......... 82% 50.1M 4s\n", + "491550K .......... .......... .......... .......... .......... 82% 50.4M 4s\n", + "491600K .......... .......... .......... .......... .......... 82% 57.5M 4s\n", + "491650K .......... .......... .......... .......... .......... 82% 56.9M 4s\n", + "491700K .......... .......... .......... .......... .......... 82% 57.5M 4s\n", + "491750K .......... .......... .......... .......... .......... 82% 45.9M 4s\n", + "491800K .......... .......... .......... .......... .......... 82% 55.1M 4s\n", + "491850K .......... .......... .......... .......... .......... 82% 68.5M 4s\n", + "491900K .......... .......... .......... .......... .......... 82% 65.2M 4s\n", + "491950K .......... .......... .......... .......... .......... 82% 66.3M 4s\n", + "492000K .......... .......... .......... .......... .......... 82% 42.4M 4s\n", + "492050K .......... .......... .......... .......... .......... 82% 62.9M 4s\n", + "492100K .......... .......... .......... .......... .......... 82% 69.9M 4s\n", + "492150K .......... .......... .......... .......... .......... 82% 68.7M 4s\n", + "492200K .......... .......... .......... .......... .......... 82% 53.5M 4s\n", + "492250K .......... .......... .......... .......... .......... 82% 61.6M 4s\n", + "492300K .......... .......... .......... .......... .......... 82% 49.9M 4s\n", + "492350K .......... .......... .......... .......... .......... 82% 67.4M 4s\n", + "492400K .......... .......... .......... .......... .......... 82% 5.83M 4s\n", + "492450K .......... .......... .......... .......... .......... 82% 66.6M 4s\n", + "492500K .......... .......... .......... .......... .......... 82% 68.8M 4s\n", + "492550K .......... .......... .......... .......... .......... 82% 70.0M 4s\n", + "492600K .......... .......... .......... .......... .......... 82% 57.5M 4s\n", + "492650K .......... .......... .......... .......... .......... 82% 72.5M 4s\n", + "492700K .......... .......... .......... .......... .......... 82% 68.3M 4s\n", + "492750K .......... .......... .......... .......... .......... 82% 52.9M 4s\n", + "492800K .......... .......... .......... .......... .......... 82% 47.9M 4s\n", + "492850K .......... .......... .......... .......... .......... 82% 87.1M 4s\n", + "492900K .......... .......... .......... .......... .......... 82% 65.2M 4s\n", + "492950K .......... .......... .......... .......... .......... 82% 71.4M 4s\n", + "493000K .......... .......... .......... .......... .......... 82% 42.2M 4s\n", + "493050K .......... .......... .......... .......... .......... 82% 48.3M 4s\n", + "493100K .......... .......... .......... .......... .......... 82% 52.4M 4s\n", + "493150K .......... .......... .......... .......... .......... 82% 62.7M 4s\n", + "493200K .......... .......... .......... .......... .......... 82% 52.9M 4s\n", + "493250K .......... .......... .......... .......... .......... 82% 40.5M 4s\n", + "493300K .......... .......... .......... .......... .......... 82% 38.4M 4s\n", + "493350K .......... .......... .......... .......... .......... 82% 63.3M 4s\n", + "493400K .......... .......... .......... .......... .......... 82% 61.4M 4s\n", + "493450K .......... .......... .......... .......... .......... 82% 50.8M 4s\n", + "493500K .......... .......... .......... .......... .......... 82% 41.1M 3s\n", + "493550K .......... .......... .......... .......... .......... 82% 39.0M 3s\n", + "493600K .......... .......... .......... .......... .......... 83% 57.6M 3s\n", + "493650K .......... .......... .......... .......... .......... 83% 59.9M 3s\n", + "493700K .......... .......... .......... .......... .......... 83% 51.3M 3s\n", + "493750K .......... .......... .......... .......... .......... 83% 61.2M 3s\n", + "493800K .......... .......... .......... .......... .......... 83% 44.5M 3s\n", + "493850K .......... .......... .......... .......... .......... 83% 72.3M 3s\n", + "493900K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", + "493950K .......... .......... .......... .......... .......... 83% 34.4M 3s\n", + "494000K .......... .......... .......... .......... .......... 83% 35.5M 3s\n", + "494050K .......... .......... .......... .......... .......... 83% 70.6M 3s\n", + "494100K .......... .......... .......... .......... .......... 83% 80.8M 3s\n", + "494150K .......... .......... .......... .......... .......... 83% 73.4M 3s\n", + "494200K .......... .......... .......... .......... .......... 83% 44.1M 3s\n", + "494250K .......... .......... .......... .......... .......... 83% 58.1M 3s\n", + "494300K .......... .......... .......... .......... .......... 83% 68.2M 3s\n", + "494350K .......... .......... .......... .......... .......... 83% 73.8M 3s\n", + "494400K .......... .......... .......... .......... .......... 83% 67.4M 3s\n", + "494450K .......... .......... .......... .......... .......... 83% 3.84M 3s\n", + "494500K .......... .......... .......... .......... .......... 83% 69.3M 3s\n", + "494550K .......... .......... .......... .......... .......... 83% 69.8M 3s\n", + "494600K .......... .......... .......... .......... .......... 83% 56.7M 3s\n", + "494650K .......... .......... .......... .......... .......... 83% 75.7M 3s\n", + "494700K .......... .......... .......... .......... .......... 83% 69.6M 3s\n", + "494750K .......... .......... .......... .......... .......... 83% 64.1M 3s\n", + "494800K .......... .......... .......... .......... .......... 83% 53.2M 3s\n", + "494850K .......... .......... .......... .......... .......... 83% 58.8M 3s\n", + "494900K .......... .......... .......... .......... .......... 83% 72.9M 3s\n", + "494950K .......... .......... .......... .......... .......... 83% 66.3M 3s\n", + "495000K .......... .......... .......... .......... .......... 83% 38.3M 3s\n", + "495050K .......... .......... .......... .......... .......... 83% 34.9M 3s\n", + "495100K .......... .......... .......... .......... .......... 83% 43.0M 3s\n", + "495150K .......... .......... .......... .......... .......... 83% 56.3M 3s\n", + "495200K .......... .......... .......... .......... .......... 83% 56.4M 3s\n", + "495250K .......... .......... .......... .......... .......... 83% 66.0M 3s\n", + "495300K .......... .......... .......... .......... .......... 83% 56.1M 3s\n", + "495350K .......... .......... .......... .......... .......... 83% 43.5M 3s\n", + "495400K .......... .......... .......... .......... .......... 83% 58.5M 3s\n", + "495450K .......... .......... .......... .......... .......... 83% 69.9M 3s\n", + "495500K .......... .......... .......... .......... .......... 83% 50.6M 3s\n", + "495550K .......... .......... .......... .......... .......... 83% 32.8M 3s\n", + "495600K .......... .......... .......... .......... .......... 83% 36.5M 3s\n", + "495650K .......... .......... .......... .......... .......... 83% 39.4M 3s\n", + "495700K .......... .......... .......... .......... .......... 83% 43.0M 3s\n", + "495750K .......... .......... .......... .......... .......... 83% 65.9M 3s\n", + "495800K .......... .......... .......... .......... .......... 83% 53.3M 3s\n", + "495850K .......... .......... .......... .......... .......... 83% 57.7M 3s\n", + "495900K .......... .......... .......... .......... .......... 83% 58.3M 3s\n", + "495950K .......... .......... .......... .......... .......... 83% 70.3M 3s\n", + "496000K .......... .......... .......... .......... .......... 83% 59.3M 3s\n", + "496050K .......... .......... .......... .......... .......... 83% 60.2M 3s\n", + "496100K .......... .......... .......... .......... .......... 83% 52.7M 3s\n", + "496150K .......... .......... .......... .......... .......... 83% 51.5M 3s\n", + "496200K .......... .......... .......... .......... .......... 83% 47.1M 3s\n", + "496250K .......... .......... .......... .......... .......... 83% 76.9M 3s\n", + "496300K .......... .......... .......... .......... .......... 83% 56.7M 3s\n", + "496350K .......... .......... .......... .......... .......... 83% 46.6M 3s\n", + "496400K .......... .......... .......... .......... .......... 83% 54.3M 3s\n", + "496450K .......... .......... .......... .......... .......... 83% 61.5M 3s\n", + "496500K .......... .......... .......... .......... .......... 83% 3.44M 3s\n", + "496550K .......... .......... .......... .......... .......... 83% 51.7M 3s\n", + "496600K .......... .......... .......... .......... .......... 83% 43.5M 3s\n", + "496650K .......... .......... .......... .......... .......... 83% 57.6M 3s\n", + "496700K .......... .......... .......... .......... .......... 83% 60.1M 3s\n", + "496750K .......... .......... .......... .......... .......... 83% 68.0M 3s\n", + "496800K .......... .......... .......... .......... .......... 83% 63.4M 3s\n", + "496850K .......... .......... .......... .......... .......... 83% 57.3M 3s\n", + "496900K .......... .......... .......... .......... .......... 83% 72.0M 3s\n", + "496950K .......... .......... .......... .......... .......... 83% 69.2M 3s\n", + "497000K .......... .......... .......... .......... .......... 83% 47.1M 3s\n", + "497050K .......... .......... .......... .......... .......... 83% 69.8M 3s\n", + "497100K .......... .......... .......... .......... .......... 83% 70.4M 3s\n", + "497150K .......... .......... .......... .......... .......... 83% 51.6M 3s\n", + "497200K .......... .......... .......... .......... .......... 83% 57.2M 3s\n", + "497250K .......... .......... .......... .......... .......... 83% 66.9M 3s\n", + "497300K .......... .......... .......... .......... .......... 83% 51.4M 3s\n", + "497350K .......... .......... .......... .......... .......... 83% 70.3M 3s\n", + "497400K .......... .......... .......... .......... .......... 83% 38.3M 3s\n", + "497450K .......... .......... .......... .......... .......... 83% 64.2M 3s\n", + "497500K .......... .......... .......... .......... .......... 83% 50.0M 3s\n", + "497550K .......... .......... .......... .......... .......... 83% 51.4M 3s\n", + "497600K .......... .......... .......... .......... .......... 83% 61.6M 3s\n", + "497650K .......... .......... .......... .......... .......... 83% 51.3M 3s\n", + "497700K .......... .......... .......... .......... .......... 83% 67.1M 3s\n", + "497750K .......... .......... .......... .......... .......... 83% 64.7M 3s\n", + "497800K .......... .......... .......... .......... .......... 83% 38.9M 3s\n", + "497850K .......... .......... .......... .......... .......... 83% 54.2M 3s\n", + "497900K .......... .......... .......... .......... .......... 83% 58.1M 3s\n", + "497950K .......... .......... .......... .......... .......... 83% 69.7M 3s\n", + "498000K .......... .......... .......... .......... .......... 83% 47.5M 3s\n", + "498050K .......... .......... .......... .......... .......... 83% 51.1M 3s\n", + "498100K .......... .......... .......... .......... .......... 83% 56.8M 3s\n", + "498150K .......... .......... .......... .......... .......... 83% 59.6M 3s\n", + "498200K .......... .......... .......... .......... .......... 83% 7.84M 3s\n", + "498250K .......... .......... .......... .......... .......... 83% 65.8M 3s\n", + "498300K .......... .......... .......... .......... .......... 83% 74.4M 3s\n", + "498350K .......... .......... .......... .......... .......... 83% 66.3M 3s\n", + "498400K .......... .......... .......... .......... .......... 83% 56.5M 3s\n", + "498450K .......... .......... .......... .......... .......... 83% 67.2M 3s\n", + "498500K .......... .......... .......... .......... .......... 83% 71.9M 3s\n", + "498550K .......... .......... .......... .......... .......... 83% 53.7M 3s\n", + "498600K .......... .......... .......... .......... .......... 83% 55.9M 3s\n", + "498650K .......... .......... .......... .......... .......... 83% 65.7M 3s\n", + "498700K .......... .......... .......... .......... .......... 83% 49.7M 3s\n", + "498750K .......... .......... .......... .......... .......... 83% 68.3M 3s\n", + "498800K .......... .......... .......... .......... .......... 83% 53.4M 3s\n", + "498850K .......... .......... .......... .......... .......... 83% 64.8M 3s\n", + "498900K .......... .......... .......... .......... .......... 83% 65.1M 3s\n", + "498950K .......... .......... .......... .......... .......... 83% 60.7M 3s\n", + "499000K .......... .......... .......... .......... .......... 83% 46.7M 3s\n", + "499050K .......... .......... .......... .......... .......... 83% 52.9M 3s\n", + "499100K .......... .......... .......... .......... .......... 83% 58.0M 3s\n", + "499150K .......... .......... .......... .......... .......... 83% 77.2M 3s\n", + "499200K .......... .......... .......... .......... .......... 83% 57.7M 3s\n", + "499250K .......... .......... .......... .......... .......... 83% 51.7M 3s\n", + "499300K .......... .......... .......... .......... .......... 83% 52.5M 3s\n", + "499350K .......... .......... .......... .......... .......... 83% 34.7M 3s\n", + "499400K .......... .......... .......... .......... .......... 83% 35.9M 3s\n", + "499450K .......... .......... .......... .......... .......... 83% 54.6M 3s\n", + "499500K .......... .......... .......... .......... .......... 83% 6.21M 3s\n", + "499550K .......... .......... .......... .......... .......... 84% 51.3M 3s\n", + "499600K .......... .......... .......... .......... .......... 84% 55.2M 3s\n", + "499650K .......... .......... .......... .......... .......... 84% 55.9M 3s\n", + "499700K .......... .......... .......... .......... .......... 84% 69.0M 3s\n", + "499750K .......... .......... .......... .......... .......... 84% 66.9M 3s\n", + "499800K .......... .......... .......... .......... .......... 84% 57.4M 3s\n", + "499850K .......... .......... .......... .......... .......... 84% 61.0M 3s\n", + "499900K .......... .......... .......... .......... .......... 84% 54.1M 3s\n", + "499950K .......... .......... .......... .......... .......... 84% 75.6M 3s\n", + "500000K .......... .......... .......... .......... .......... 84% 62.8M 3s\n", + "500050K .......... .......... .......... .......... .......... 84% 67.2M 3s\n", + "500100K .......... .......... .......... .......... .......... 84% 54.1M 3s\n", + "500150K .......... .......... .......... .......... .......... 84% 70.5M 3s\n", + "500200K .......... .......... .......... .......... .......... 84% 63.2M 3s\n", + "500250K .......... .......... .......... .......... .......... 84% 76.1M 3s\n", + "500300K .......... .......... .......... .......... .......... 84% 58.2M 3s\n", + "500350K .......... .......... .......... .......... .......... 84% 45.2M 3s\n", + "500400K .......... .......... .......... .......... .......... 84% 46.0M 3s\n", + "500450K .......... .......... .......... .......... .......... 84% 63.2M 3s\n", + "500500K .......... .......... .......... .......... .......... 84% 69.3M 3s\n", + "500550K .......... .......... .......... .......... .......... 84% 71.2M 3s\n", + "500600K .......... .......... .......... .......... .......... 84% 41.4M 3s\n", + "500650K .......... .......... .......... .......... .......... 84% 56.9M 3s\n", + "500700K .......... .......... .......... .......... .......... 84% 54.8M 3s\n", + "500750K .......... .......... .......... .......... .......... 84% 64.3M 3s\n", + "500800K .......... .......... .......... .......... .......... 84% 55.6M 3s\n", + "500850K .......... .......... .......... .......... .......... 84% 49.2M 3s\n", + "500900K .......... .......... .......... .......... .......... 84% 44.7M 3s\n", + "500950K .......... .......... .......... .......... .......... 84% 51.3M 3s\n", + "501000K .......... .......... .......... .......... .......... 84% 57.4M 3s\n", + "501050K .......... .......... .......... .......... .......... 84% 55.0M 3s\n", + "501100K .......... .......... .......... .......... .......... 84% 53.6M 3s\n", + "501150K .......... .......... .......... .......... .......... 84% 13.8M 3s\n", + "501200K .......... .......... .......... .......... .......... 84% 46.5M 3s\n", + "501250K .......... .......... .......... .......... .......... 84% 58.8M 3s\n", + "501300K .......... .......... .......... .......... .......... 84% 69.6M 3s\n", + "501350K .......... .......... .......... .......... .......... 84% 69.4M 3s\n", + "501400K .......... .......... .......... .......... .......... 84% 43.2M 3s\n", + "501450K .......... .......... .......... .......... .......... 84% 52.6M 3s\n", + "501500K .......... .......... .......... .......... .......... 84% 51.0M 3s\n", + "501550K .......... .......... .......... .......... .......... 84% 69.4M 3s\n", + "501600K .......... .......... .......... .......... .......... 84% 60.8M 3s\n", + "501650K .......... .......... .......... .......... .......... 84% 67.1M 3s\n", + "501700K .......... .......... .......... .......... .......... 84% 46.4M 3s\n", + "501750K .......... .......... .......... .......... .......... 84% 35.4M 3s\n", + "501800K .......... .......... .......... .......... .......... 84% 31.9M 3s\n", + "501850K .......... .......... .......... .......... .......... 84% 34.2M 3s\n", + "501900K .......... .......... .......... .......... .......... 84% 31.8M 3s\n", + "501950K .......... .......... .......... .......... .......... 84% 39.8M 3s\n", + "502000K .......... .......... .......... .......... .......... 84% 54.4M 3s\n", + "502050K .......... .......... .......... .......... .......... 84% 47.7M 3s\n", + "502100K .......... .......... .......... .......... .......... 84% 54.3M 3s\n", + "502150K .......... .......... .......... .......... .......... 84% 66.8M 3s\n", + "502200K .......... .......... .......... .......... .......... 84% 56.4M 3s\n", + "502250K .......... .......... .......... .......... .......... 84% 61.7M 3s\n", + "502300K .......... .......... .......... .......... .......... 84% 49.5M 3s\n", + "502350K .......... .......... .......... .......... .......... 84% 53.2M 3s\n", + "502400K .......... .......... .......... .......... .......... 84% 59.2M 3s\n", + "502450K .......... .......... .......... .......... .......... 84% 70.9M 3s\n", + "502500K .......... .......... .......... .......... .......... 84% 70.6M 3s\n", + "502550K .......... .......... .......... .......... .......... 84% 57.4M 3s\n", + "502600K .......... .......... .......... .......... .......... 84% 33.5M 3s\n", + "502650K .......... .......... .......... .......... .......... 84% 72.4M 3s\n", + "502700K .......... .......... .......... .......... .......... 84% 53.8M 3s\n", + "502750K .......... .......... .......... .......... .......... 84% 66.3M 3s\n", + "502800K .......... .......... .......... .......... .......... 84% 38.4M 3s\n", + "502850K .......... .......... .......... .......... .......... 84% 47.4M 3s\n", + "502900K .......... .......... .......... .......... .......... 84% 64.8M 3s\n", + "502950K .......... .......... .......... .......... .......... 84% 66.5M 3s\n", + "503000K .......... .......... .......... .......... .......... 84% 54.7M 3s\n", + "503050K .......... .......... .......... .......... .......... 84% 54.8M 3s\n", + "503100K .......... .......... .......... .......... .......... 84% 49.9M 3s\n", + "503150K .......... .......... .......... .......... .......... 84% 59.0M 3s\n", + "503200K .......... .......... .......... .......... .......... 84% 63.8M 3s\n", + "503250K .......... .......... .......... .......... .......... 84% 70.9M 3s\n", + "503300K .......... .......... .......... .......... .......... 84% 66.3M 3s\n", + "503350K .......... .......... .......... .......... .......... 84% 53.9M 3s\n", + "503400K .......... .......... .......... .......... .......... 84% 33.0M 3s\n", + "503450K .......... .......... .......... .......... .......... 84% 53.7M 3s\n", + "503500K .......... .......... .......... .......... .......... 84% 74.4M 3s\n", + "503550K .......... .......... .......... .......... .......... 84% 56.5M 3s\n", + "503600K .......... .......... .......... .......... .......... 84% 49.9M 3s\n", + "503650K .......... .......... .......... .......... .......... 84% 48.7M 3s\n", + "503700K .......... .......... .......... .......... .......... 84% 68.0M 3s\n", + "503750K .......... .......... .......... .......... .......... 84% 65.2M 3s\n", + "503800K .......... .......... .......... .......... .......... 84% 59.9M 3s\n", + "503850K .......... .......... .......... .......... .......... 84% 70.9M 3s\n", + "503900K .......... .......... .......... .......... .......... 84% 62.7M 3s\n", + "503950K .......... .......... .......... .......... .......... 84% 47.9M 3s\n", + "504000K .......... .......... .......... .......... .......... 84% 39.5M 3s\n", + "504050K .......... .......... .......... .......... .......... 84% 51.5M 3s\n", + "504100K .......... .......... .......... .......... .......... 84% 48.3M 3s\n", + "504150K .......... .......... .......... .......... .......... 84% 50.2M 3s\n", + "504200K .......... .......... .......... .......... .......... 84% 45.4M 3s\n", + "504250K .......... .......... .......... .......... .......... 84% 67.0M 3s\n", + "504300K .......... .......... .......... .......... .......... 84% 50.2M 3s\n", + "504350K .......... .......... .......... .......... .......... 84% 49.0M 3s\n", + "504400K .......... .......... .......... .......... .......... 84% 48.0M 3s\n", + "504450K .......... .......... .......... .......... .......... 84% 56.9M 3s\n", + "504500K .......... .......... .......... .......... .......... 84% 63.4M 3s\n", + "504550K .......... .......... .......... .......... .......... 84% 61.8M 3s\n", + "504600K .......... .......... .......... .......... .......... 84% 38.4M 3s\n", + "504650K .......... .......... .......... .......... .......... 84% 38.3M 3s\n", + "504700K .......... .......... .......... .......... .......... 84% 42.7M 3s\n", + "504750K .......... .......... .......... .......... .......... 84% 70.1M 3s\n", + "504800K .......... .......... .......... .......... .......... 84% 43.6M 3s\n", + "504850K .......... .......... .......... .......... .......... 84% 58.9M 3s\n", + "504900K .......... .......... .......... .......... .......... 84% 47.1M 3s\n", + "504950K .......... .......... .......... .......... .......... 84% 71.7M 3s\n", + "505000K .......... .......... .......... .......... .......... 84% 52.8M 3s\n", + "505050K .......... .......... .......... .......... .......... 84% 44.8M 3s\n", + "505100K .......... .......... .......... .......... .......... 84% 35.1M 3s\n", + "505150K .......... .......... .......... .......... .......... 84% 68.7M 3s\n", + "505200K .......... .......... .......... .......... .......... 84% 66.4M 3s\n", + "505250K .......... .......... .......... .......... .......... 84% 57.7M 3s\n", + "505300K .......... .......... .......... .......... .......... 84% 49.7M 3s\n", + "505350K .......... .......... .......... .......... .......... 84% 73.8M 3s\n", + "505400K .......... .......... .......... .......... .......... 84% 47.3M 3s\n", + "505450K .......... .......... .......... .......... .......... 84% 75.9M 3s\n", + "505500K .......... .......... .......... .......... .......... 85% 71.1M 3s\n", + "505550K .......... .......... .......... .......... .......... 85% 47.8M 3s\n", + "505600K .......... .......... .......... .......... .......... 85% 52.8M 3s\n", + "505650K .......... .......... .......... .......... .......... 85% 50.9M 3s\n", + "505700K .......... .......... .......... .......... .......... 85% 70.8M 3s\n", + "505750K .......... .......... .......... .......... .......... 85% 75.2M 3s\n", + "505800K .......... .......... .......... .......... .......... 85% 37.5M 3s\n", + "505850K .......... .......... .......... .......... .......... 85% 54.6M 3s\n", + "505900K .......... .......... .......... .......... .......... 85% 56.6M 3s\n", + "505950K .......... .......... .......... .......... .......... 85% 67.2M 3s\n", + "506000K .......... .......... .......... .......... .......... 85% 57.8M 3s\n", + "506050K .......... .......... .......... .......... .......... 85% 47.1M 3s\n", + "506100K .......... .......... .......... .......... .......... 85% 51.9M 3s\n", + "506150K .......... .......... .......... .......... .......... 85% 55.4M 3s\n", + "506200K .......... .......... .......... .......... .......... 85% 56.5M 3s\n", + "506250K .......... .......... .......... .......... .......... 85% 65.7M 3s\n", + "506300K .......... .......... .......... .......... .......... 85% 46.5M 3s\n", + "506350K .......... .......... .......... .......... .......... 85% 49.1M 3s\n", + "506400K .......... .......... .......... .......... .......... 85% 61.6M 3s\n", + "506450K .......... .......... .......... .......... .......... 85% 70.8M 3s\n", + "506500K .......... .......... .......... .......... .......... 85% 69.2M 3s\n", + "506550K .......... .......... .......... .......... .......... 85% 59.2M 3s\n", + "506600K .......... .......... .......... .......... .......... 85% 38.3M 3s\n", + "506650K .......... .......... .......... .......... .......... 85% 58.6M 3s\n", + "506700K .......... .......... .......... .......... .......... 85% 78.1M 3s\n", + "506750K .......... .......... .......... .......... .......... 85% 69.8M 3s\n", + "506800K .......... .......... .......... .......... .......... 85% 50.6M 3s\n", + "506850K .......... .......... .......... .......... .......... 85% 50.3M 3s\n", + "506900K .......... .......... .......... .......... .......... 85% 53.4M 3s\n", + "506950K .......... .......... .......... .......... .......... 85% 69.3M 3s\n", + "507000K .......... .......... .......... .......... .......... 85% 62.6M 3s\n", + "507050K .......... .......... .......... .......... .......... 85% 54.8M 3s\n", + "507100K .......... .......... .......... .......... .......... 85% 50.4M 3s\n", + "507150K .......... .......... .......... .......... .......... 85% 57.5M 3s\n", + "507200K .......... .......... .......... .......... .......... 85% 60.6M 3s\n", + "507250K .......... .......... .......... .......... .......... 85% 70.0M 3s\n", + "507300K .......... .......... .......... .......... .......... 85% 72.5M 3s\n", + "507350K .......... .......... .......... .......... .......... 85% 57.7M 3s\n", + "507400K .......... .......... .......... .......... .......... 85% 44.2M 3s\n", + "507450K .......... .......... .......... .......... .......... 85% 58.5M 3s\n", + "507500K .......... .......... .......... .......... .......... 85% 64.6M 3s\n", + "507550K .......... .......... .......... .......... .......... 85% 72.1M 3s\n", + "507600K .......... .......... .......... .......... .......... 85% 58.2M 3s\n", + "507650K .......... .......... .......... .......... .......... 85% 69.1M 3s\n", + "507700K .......... .......... .......... .......... .......... 85% 64.7M 3s\n", + "507750K .......... .......... .......... .......... .......... 85% 63.0M 3s\n", + "507800K .......... .......... .......... .......... .......... 85% 36.8M 3s\n", + "507850K .......... .......... .......... .......... .......... 85% 51.1M 3s\n", + "507900K .......... .......... .......... .......... .......... 85% 61.7M 3s\n", + "507950K .......... .......... .......... .......... .......... 85% 70.7M 3s\n", + "508000K .......... .......... .......... .......... .......... 85% 51.5M 3s\n", + "508050K .......... .......... .......... .......... .......... 85% 47.5M 3s\n", + "508100K .......... .......... .......... .......... .......... 85% 48.6M 3s\n", + "508150K .......... .......... .......... .......... .......... 85% 64.4M 3s\n", + "508200K .......... .......... .......... .......... .......... 85% 57.2M 3s\n", + "508250K .......... .......... .......... .......... .......... 85% 53.8M 3s\n", + "508300K .......... .......... .......... .......... .......... 85% 57.8M 3s\n", + "508350K .......... .......... .......... .......... .......... 85% 47.7M 3s\n", + "508400K .......... .......... .......... .......... .......... 85% 62.9M 3s\n", + "508450K .......... .......... .......... .......... .......... 85% 71.4M 3s\n", + "508500K .......... .......... .......... .......... .......... 85% 56.7M 3s\n", + "508550K .......... .......... .......... .......... .......... 85% 65.2M 3s\n", + "508600K .......... .......... .......... .......... .......... 85% 45.0M 3s\n", + "508650K .......... .......... .......... .......... .......... 85% 73.4M 3s\n", + "508700K .......... .......... .......... .......... .......... 85% 70.6M 3s\n", + "508750K .......... .......... .......... .......... .......... 85% 69.4M 3s\n", + "508800K .......... .......... .......... .......... .......... 85% 58.2M 3s\n", + "508850K .......... .......... .......... .......... .......... 85% 77.3M 3s\n", + "508900K .......... .......... .......... .......... .......... 85% 61.8M 3s\n", + "508950K .......... .......... .......... .......... .......... 85% 59.2M 3s\n", + "509000K .......... .......... .......... .......... .......... 85% 38.2M 3s\n", + "509050K .......... .......... .......... .......... .......... 85% 64.2M 3s\n", + "509100K .......... .......... .......... .......... .......... 85% 67.0M 3s\n", + "509150K .......... .......... .......... .......... .......... 85% 71.6M 3s\n", + "509200K .......... .......... .......... .......... .......... 85% 53.1M 3s\n", + "509250K .......... .......... .......... .......... .......... 85% 50.2M 3s\n", + "509300K .......... .......... .......... .......... .......... 85% 51.3M 3s\n", + "509350K .......... .......... .......... .......... .......... 85% 67.4M 3s\n", + "509400K .......... .......... .......... .......... .......... 85% 54.8M 3s\n", + "509450K .......... .......... .......... .......... .......... 85% 60.3M 3s\n", + "509500K .......... .......... .......... .......... .......... 85% 45.5M 3s\n", + "509550K .......... .......... .......... .......... .......... 85% 48.1M 3s\n", + "509600K .......... .......... .......... .......... .......... 85% 57.9M 3s\n", + "509650K .......... .......... .......... .......... .......... 85% 77.9M 3s\n", + "509700K .......... .......... .......... .......... .......... 85% 60.3M 3s\n", + "509750K .......... .......... .......... .......... .......... 85% 54.0M 3s\n", + "509800K .......... .......... .......... .......... .......... 85% 45.0M 3s\n", + "509850K .......... .......... .......... .......... .......... 85% 63.1M 3s\n", + "509900K .......... .......... .......... .......... .......... 85% 75.8M 3s\n", + "509950K .......... .......... .......... .......... .......... 85% 7.88M 3s\n", + "510000K .......... .......... .......... .......... .......... 85% 69.8M 3s\n", + "510050K .......... .......... .......... .......... .......... 85% 68.4M 3s\n", + "510100K .......... .......... .......... .......... .......... 85% 66.6M 3s\n", + "510150K .......... .......... .......... .......... .......... 85% 71.5M 3s\n", + "510200K .......... .......... .......... .......... .......... 85% 60.4M 3s\n", + "510250K .......... .......... .......... .......... .......... 85% 71.8M 3s\n", + "510300K .......... .......... .......... .......... .......... 85% 52.2M 3s\n", + "510350K .......... .......... .......... .......... .......... 85% 52.4M 3s\n", + "510400K .......... .......... .......... .......... .......... 85% 48.2M 3s\n", + "510450K .......... .......... .......... .......... .......... 85% 64.3M 3s\n", + "510500K .......... .......... .......... .......... .......... 85% 71.1M 3s\n", + "510550K .......... .......... .......... .......... .......... 85% 62.6M 3s\n", + "510600K .......... .......... .......... .......... .......... 85% 39.3M 3s\n", + "510650K .......... .......... .......... .......... .......... 85% 56.8M 3s\n", + "510700K .......... .......... .......... .......... .......... 85% 64.4M 3s\n", + "510750K .......... .......... .......... .......... .......... 85% 66.1M 3s\n", + "510800K .......... .......... .......... .......... .......... 85% 58.2M 3s\n", + "510850K .......... .......... .......... .......... .......... 85% 50.8M 3s\n", + "510900K .......... .......... .......... .......... .......... 85% 47.6M 3s\n", + "510950K .......... .......... .......... .......... .......... 85% 63.6M 3s\n", + "511000K .......... .......... .......... .......... .......... 85% 56.9M 3s\n", + "511050K .......... .......... .......... .......... .......... 85% 58.4M 3s\n", + "511100K .......... .......... .......... .......... .......... 85% 50.5M 3s\n", + "511150K .......... .......... .......... .......... .......... 85% 46.7M 3s\n", + "511200K .......... .......... .......... .......... .......... 85% 53.1M 3s\n", + "511250K .......... .......... .......... .......... .......... 85% 66.6M 3s\n", + "511300K .......... .......... .......... .......... .......... 85% 61.2M 3s\n", + "511350K .......... .......... .......... .......... .......... 85% 54.8M 3s\n", + "511400K .......... .......... .......... .......... .......... 85% 36.8M 3s\n", + "511450K .......... .......... .......... .......... .......... 86% 59.6M 3s\n", + "511500K .......... .......... .......... .......... .......... 86% 71.1M 3s\n", + "511550K .......... .......... .......... .......... .......... 86% 53.0M 3s\n", + "511600K .......... .......... .......... .......... .......... 86% 50.3M 3s\n", + "511650K .......... .......... .......... .......... .......... 86% 54.4M 3s\n", + "511700K .......... .......... .......... .......... .......... 86% 48.3M 3s\n", + "511750K .......... .......... .......... .......... .......... 86% 44.2M 3s\n", + "511800K .......... .......... .......... .......... .......... 86% 38.9M 3s\n", + "511850K .......... .......... .......... .......... .......... 86% 47.7M 3s\n", + "511900K .......... .......... .......... .......... .......... 86% 53.6M 3s\n", + "511950K .......... .......... .......... .......... .......... 86% 64.7M 3s\n", + "512000K .......... .......... .......... .......... .......... 86% 69.5M 3s\n", + "512050K .......... .......... .......... .......... .......... 86% 53.4M 3s\n", + "512100K .......... .......... .......... .......... .......... 86% 68.4M 3s\n", + "512150K .......... .......... .......... .......... .......... 86% 51.1M 3s\n", + "512200K .......... .......... .......... .......... .......... 86% 50.6M 3s\n", + "512250K .......... .......... .......... .......... .......... 86% 55.9M 3s\n", + "512300K .......... .......... .......... .......... .......... 86% 49.1M 3s\n", + "512350K .......... .......... .......... .......... .......... 86% 58.4M 3s\n", + "512400K .......... .......... .......... .......... .......... 86% 40.8M 3s\n", + "512450K .......... .......... .......... .......... .......... 86% 54.7M 3s\n", + "512500K .......... .......... .......... .......... .......... 86% 56.4M 3s\n", + "512550K .......... .......... .......... .......... .......... 86% 53.2M 3s\n", + "512600K .......... .......... .......... .......... .......... 86% 32.2M 3s\n", + "512650K .......... .......... .......... .......... .......... 86% 53.3M 3s\n", + "512700K .......... .......... .......... .......... .......... 86% 59.5M 3s\n", + "512750K .......... .......... .......... .......... .......... 86% 68.2M 3s\n", + "512800K .......... .......... .......... .......... .......... 86% 66.2M 3s\n", + "512850K .......... .......... .......... .......... .......... 86% 66.6M 3s\n", + "512900K .......... .......... .......... .......... .......... 86% 65.5M 3s\n", + "512950K .......... .......... .......... .......... .......... 86% 60.0M 3s\n", + "513000K .......... .......... .......... .......... .......... 86% 55.9M 3s\n", + "513050K .......... .......... .......... .......... .......... 86% 82.1M 3s\n", + "513100K .......... .......... .......... .......... .......... 86% 62.3M 3s\n", + "513150K .......... .......... .......... .......... .......... 86% 55.9M 3s\n", + "513200K .......... .......... .......... .......... .......... 86% 56.5M 3s\n", + "513250K .......... .......... .......... .......... .......... 86% 74.5M 3s\n", + "513300K .......... .......... .......... .......... .......... 86% 62.3M 3s\n", + "513350K .......... .......... .......... .......... .......... 86% 32.9M 3s\n", + "513400K .......... .......... .......... .......... .......... 86% 42.8M 3s\n", + "513450K .......... .......... .......... .......... .......... 86% 67.6M 3s\n", + "513500K .......... .......... .......... .......... .......... 86% 71.6M 3s\n", + "513550K .......... .......... .......... .......... .......... 86% 70.4M 3s\n", + "513600K .......... .......... .......... .......... .......... 86% 58.5M 3s\n", + "513650K .......... .......... .......... .......... .......... 86% 70.7M 3s\n", + "513700K .......... .......... .......... .......... .......... 86% 66.9M 3s\n", + "513750K .......... .......... .......... .......... .......... 86% 62.3M 3s\n", + "513800K .......... .......... .......... .......... .......... 86% 55.8M 3s\n", + "513850K .......... .......... .......... .......... .......... 86% 68.4M 3s\n", + "513900K .......... .......... .......... .......... .......... 86% 71.6M 3s\n", + "513950K .......... .......... .......... .......... .......... 86% 66.9M 3s\n", + "514000K .......... .......... .......... .......... .......... 86% 53.9M 3s\n", + "514050K .......... .......... .......... .......... .......... 86% 57.0M 3s\n", + "514100K .......... .......... .......... .......... .......... 86% 54.4M 3s\n", + "514150K .......... .......... .......... .......... .......... 86% 45.6M 3s\n", + "514200K .......... .......... .......... .......... .......... 86% 32.6M 3s\n", + "514250K .......... .......... .......... .......... .......... 86% 53.5M 3s\n", + "514300K .......... .......... .......... .......... .......... 86% 42.3M 3s\n", + "514350K .......... .......... .......... .......... .......... 86% 43.0M 3s\n", + "514400K .......... .......... .......... .......... .......... 86% 47.9M 3s\n", + "514450K .......... .......... .......... .......... .......... 86% 70.8M 3s\n", + "514500K .......... .......... .......... .......... .......... 86% 71.7M 3s\n", + "514550K .......... .......... .......... .......... .......... 86% 74.1M 3s\n", + "514600K .......... .......... .......... .......... .......... 86% 39.9M 3s\n", + "514650K .......... .......... .......... .......... .......... 86% 61.2M 3s\n", + "514700K .......... .......... .......... .......... .......... 86% 58.3M 3s\n", + "514750K .......... .......... .......... .......... .......... 86% 67.4M 3s\n", + "514800K .......... .......... .......... .......... .......... 86% 59.6M 3s\n", + "514850K .......... .......... .......... .......... .......... 86% 59.2M 3s\n", + "514900K .......... .......... .......... .......... .......... 86% 40.1M 3s\n", + "514950K .......... .......... .......... .......... .......... 86% 48.3M 3s\n", + "515000K .......... .......... .......... .......... .......... 86% 53.4M 3s\n", + "515050K .......... .......... .......... .......... .......... 86% 51.6M 3s\n", + "515100K .......... .......... .......... .......... .......... 86% 72.7M 3s\n", + "515150K .......... .......... .......... .......... .......... 86% 56.3M 3s\n", + "515200K .......... .......... .......... .......... .......... 86% 64.5M 3s\n", + "515250K .......... .......... .......... .......... .......... 86% 67.1M 3s\n", + "515300K .......... .......... .......... .......... .......... 86% 73.6M 3s\n", + "515350K .......... .......... .......... .......... .......... 86% 68.2M 3s\n", + "515400K .......... .......... .......... .......... .......... 86% 45.9M 3s\n", + "515450K .......... .......... .......... .......... .......... 86% 49.4M 3s\n", + "515500K .......... .......... .......... .......... .......... 86% 46.4M 3s\n", + "515550K .......... .......... .......... .......... .......... 86% 58.9M 3s\n", + "515600K .......... .......... .......... .......... .......... 86% 62.7M 3s\n", + "515650K .......... .......... .......... .......... .......... 86% 62.7M 3s\n", + "515700K .......... .......... .......... .......... .......... 86% 42.7M 3s\n", + "515750K .......... .......... .......... .......... .......... 86% 56.2M 3s\n", + "515800K .......... .......... .......... .......... .......... 86% 55.6M 3s\n", + "515850K .......... .......... .......... .......... .......... 86% 85.1M 3s\n", + "515900K .......... .......... .......... .......... .......... 86% 49.5M 3s\n", + "515950K .......... .......... .......... .......... .......... 86% 54.6M 3s\n", + "516000K .......... .......... .......... .......... .......... 86% 54.7M 3s\n", + "516050K .......... .......... .......... .......... .......... 86% 61.2M 3s\n", + "516100K .......... .......... .......... .......... .......... 86% 69.1M 3s\n", + "516150K .......... .......... .......... .......... .......... 86% 64.3M 3s\n", + "516200K .......... .......... .......... .......... .......... 86% 46.6M 3s\n", + "516250K .......... .......... .......... .......... .......... 86% 52.3M 3s\n", + "516300K .......... .......... .......... .......... .......... 86% 55.9M 3s\n", + "516350K .......... .......... .......... .......... .......... 86% 65.3M 3s\n", + "516400K .......... .......... .......... .......... .......... 86% 48.2M 3s\n", + "516450K .......... .......... .......... .......... .......... 86% 27.8M 3s\n", + "516500K .......... .......... .......... .......... .......... 86% 56.0M 3s\n", + "516550K .......... .......... .......... .......... .......... 86% 69.1M 3s\n", + "516600K .......... .......... .......... .......... .......... 86% 58.5M 3s\n", + "516650K .......... .......... .......... .......... .......... 86% 57.3M 3s\n", + "516700K .......... .......... .......... .......... .......... 86% 56.2M 3s\n", + "516750K .......... .......... .......... .......... .......... 86% 36.5M 3s\n", + "516800K .......... .......... .......... .......... .......... 86% 57.4M 3s\n", + "516850K .......... .......... .......... .......... .......... 86% 63.8M 3s\n", + "516900K .......... .......... .......... .......... .......... 86% 56.2M 3s\n", + "516950K .......... .......... .......... .......... .......... 86% 45.1M 3s\n", + "517000K .......... .......... .......... .......... .......... 86% 47.7M 3s\n", + "517050K .......... .......... .......... .......... .......... 86% 55.2M 3s\n", + "517100K .......... .......... .......... .......... .......... 86% 49.0M 3s\n", + "517150K .......... .......... .......... .......... .......... 86% 51.8M 3s\n", + "517200K .......... .......... .......... .......... .......... 86% 51.1M 3s\n", + "517250K .......... .......... .......... .......... .......... 86% 61.9M 3s\n", + "517300K .......... .......... .......... .......... .......... 86% 64.6M 3s\n", + "517350K .......... .......... .......... .......... .......... 86% 66.0M 3s\n", + "517400K .......... .......... .......... .......... .......... 87% 43.2M 3s\n", + "517450K .......... .......... .......... .......... .......... 87% 52.4M 3s\n", + "517500K .......... .......... .......... .......... .......... 87% 66.2M 3s\n", + "517550K .......... .......... .......... .......... .......... 87% 63.4M 3s\n", + "517600K .......... .......... .......... .......... .......... 87% 27.8M 3s\n", + "517650K .......... .......... .......... .......... .......... 87% 31.1M 3s\n", + "517700K .......... .......... .......... .......... .......... 87% 38.4M 3s\n", + "517750K .......... .......... .......... .......... .......... 87% 38.3M 3s\n", + "517800K .......... .......... .......... .......... .......... 87% 41.8M 3s\n", + "517850K .......... .......... .......... .......... .......... 87% 36.1M 3s\n", + "517900K .......... .......... .......... .......... .......... 87% 69.6M 3s\n", + "517950K .......... .......... .......... .......... .......... 87% 69.0M 3s\n", + "518000K .......... .......... .......... .......... .......... 87% 38.5M 3s\n", + "518050K .......... .......... .......... .......... .......... 87% 60.0M 3s\n", + "518100K .......... .......... .......... .......... .......... 87% 54.6M 3s\n", + "518150K .......... .......... .......... .......... .......... 87% 68.1M 3s\n", + "518200K .......... .......... .......... .......... .......... 87% 22.3M 3s\n", + "518250K .......... .......... .......... .......... .......... 87% 56.8M 3s\n", + "518300K .......... .......... .......... .......... .......... 87% 59.5M 3s\n", + "518350K .......... .......... .......... .......... .......... 87% 18.1M 3s\n", + "518400K .......... .......... .......... .......... .......... 87% 31.9M 3s\n", + "518450K .......... .......... .......... .......... .......... 87% 32.7M 3s\n", + "518500K .......... .......... .......... .......... .......... 87% 38.4M 3s\n", + "518550K .......... .......... .......... .......... .......... 87% 68.7M 3s\n", + "518600K .......... .......... .......... .......... .......... 87% 3.75M 3s\n", + "518650K .......... .......... .......... .......... .......... 87% 65.3M 3s\n", + "518700K .......... .......... .......... .......... .......... 87% 70.7M 3s\n", + "518750K .......... .......... .......... .......... .......... 87% 76.9M 3s\n", + "518800K .......... .......... .......... .......... .......... 87% 17.7M 3s\n", + "518850K .......... .......... .......... .......... .......... 87% 56.2M 3s\n", + "518900K .......... .......... .......... .......... .......... 87% 61.3M 3s\n", + "518950K .......... .......... .......... .......... .......... 87% 81.8M 3s\n", + "519000K .......... .......... .......... .......... .......... 87% 22.3M 3s\n", + "519050K .......... .......... .......... .......... .......... 87% 48.1M 3s\n", + "519100K .......... .......... .......... .......... .......... 87% 66.1M 3s\n", + "519150K .......... .......... .......... .......... .......... 87% 71.7M 3s\n", + "519200K .......... .......... .......... .......... .......... 87% 27.3M 3s\n", + "519250K .......... .......... .......... .......... .......... 87% 49.6M 3s\n", + "519300K .......... .......... .......... .......... .......... 87% 50.9M 3s\n", + "519350K .......... .......... .......... .......... .......... 87% 57.6M 3s\n", + "519400K .......... .......... .......... .......... .......... 87% 19.4M 3s\n", + "519450K .......... .......... .......... .......... .......... 87% 26.6M 3s\n", + "519500K .......... .......... .......... .......... .......... 87% 71.9M 3s\n", + "519550K .......... .......... .......... .......... .......... 87% 70.1M 3s\n", + "519600K .......... .......... .......... .......... .......... 87% 39.7M 3s\n", + "519650K .......... .......... .......... .......... .......... 87% 42.2M 3s\n", + "519700K .......... .......... .......... .......... .......... 87% 40.6M 3s\n", + "519750K .......... .......... .......... .......... .......... 87% 72.1M 3s\n", + "519800K .......... .......... .......... .......... .......... 87% 27.5M 3s\n", + "519850K .......... .......... .......... .......... .......... 87% 39.7M 3s\n", + "519900K .......... .......... .......... .......... .......... 87% 46.8M 3s\n", + "519950K .......... .......... .......... .......... .......... 87% 58.2M 3s\n", + "520000K .......... .......... .......... .......... .......... 87% 29.8M 3s\n", + "520050K .......... .......... .......... .......... .......... 87% 45.2M 3s\n", + "520100K .......... .......... .......... .......... .......... 87% 47.8M 3s\n", + "520150K .......... .......... .......... .......... .......... 87% 64.0M 3s\n", + "520200K .......... .......... .......... .......... .......... 87% 3.92M 3s\n", + "520250K .......... .......... .......... .......... .......... 87% 5.77M 3s\n", + "520300K .......... .......... .......... .......... .......... 87% 49.7M 3s\n", + "520350K .......... .......... .......... .......... .......... 87% 14.5M 3s\n", + "520400K .......... .......... .......... .......... .......... 87% 44.1M 3s\n", + "520450K .......... .......... .......... .......... .......... 87% 52.1M 3s\n", + "520500K .......... .......... .......... .......... .......... 87% 56.2M 3s\n", + "520550K .......... .......... .......... .......... .......... 87% 52.3M 3s\n", + "520600K .......... .......... .......... .......... .......... 87% 16.1M 3s\n", + "520650K .......... .......... .......... .......... .......... 87% 41.3M 3s\n", + "520700K .......... .......... .......... .......... .......... 87% 37.6M 3s\n", + "520750K .......... .......... .......... .......... .......... 87% 39.7M 3s\n", + "520800K .......... .......... .......... .......... .......... 87% 47.5M 3s\n", + "520850K .......... .......... .......... .......... .......... 87% 51.5M 3s\n", + "520900K .......... .......... .......... .......... .......... 87% 60.8M 3s\n", + "520950K .......... .......... .......... .......... .......... 87% 56.2M 2s\n", + "521000K .......... .......... .......... .......... .......... 87% 62.2M 2s\n", + "521050K .......... .......... .......... .......... .......... 87% 50.0M 2s\n", + "521100K .......... .......... .......... .......... .......... 87% 49.0M 2s\n", + "521150K .......... .......... .......... .......... .......... 87% 60.0M 2s\n", + "521200K .......... .......... .......... .......... .......... 87% 44.1M 2s\n", + "521250K .......... .......... .......... .......... .......... 87% 52.2M 2s\n", + "521300K .......... .......... .......... .......... .......... 87% 53.3M 2s\n", + "521350K .......... .......... .......... .......... .......... 87% 58.0M 2s\n", + "521400K .......... .......... .......... .......... .......... 87% 34.9M 2s\n", + "521450K .......... .......... .......... .......... .......... 87% 36.5M 2s\n", + "521500K .......... .......... .......... .......... .......... 87% 50.6M 2s\n", + "521550K .......... .......... .......... .......... .......... 87% 41.0M 2s\n", + "521600K .......... .......... .......... .......... .......... 87% 36.3M 2s\n", + "521650K .......... .......... .......... .......... .......... 87% 54.9M 2s\n", + "521700K .......... .......... .......... .......... .......... 87% 46.7M 2s\n", + "521750K .......... .......... .......... .......... .......... 87% 66.0M 2s\n", + "521800K .......... .......... .......... .......... .......... 87% 22.3M 2s\n", + "521850K .......... .......... .......... .......... .......... 87% 71.1M 2s\n", + "521900K .......... .......... .......... .......... .......... 87% 65.9M 2s\n", + "521950K .......... .......... .......... .......... .......... 87% 67.9M 2s\n", + "522000K .......... .......... .......... .......... .......... 87% 19.9M 2s\n", + "522050K .......... .......... .......... .......... .......... 87% 43.3M 2s\n", + "522100K .......... .......... .......... .......... .......... 87% 66.2M 2s\n", + "522150K .......... .......... .......... .......... .......... 87% 52.6M 2s\n", + "522200K .......... .......... .......... .......... .......... 87% 23.5M 2s\n", + "522250K .......... .......... .......... .......... .......... 87% 36.2M 2s\n", + "522300K .......... .......... .......... .......... .......... 87% 50.4M 2s\n", + "522350K .......... .......... .......... .......... .......... 87% 47.3M 2s\n", + "522400K .......... .......... .......... .......... .......... 87% 56.4M 2s\n", + "522450K .......... .......... .......... .......... .......... 87% 54.4M 2s\n", + "522500K .......... .......... .......... .......... .......... 87% 60.2M 2s\n", + "522550K .......... .......... .......... .......... .......... 87% 30.0M 2s\n", + "522600K .......... .......... .......... .......... .......... 87% 41.6M 2s\n", + "522650K .......... .......... .......... .......... .......... 87% 57.0M 2s\n", + "522700K .......... .......... .......... .......... .......... 87% 48.7M 2s\n", + "522750K .......... .......... .......... .......... .......... 87% 40.8M 2s\n", + "522800K .......... .......... .......... .......... .......... 87% 32.4M 2s\n", + "522850K .......... .......... .......... .......... .......... 87% 52.9M 2s\n", + "522900K .......... .......... .......... .......... .......... 87% 49.1M 2s\n", + "522950K .......... .......... .......... .......... .......... 87% 45.9M 2s\n", + "523000K .......... .......... .......... .......... .......... 87% 27.5M 2s\n", + "523050K .......... .......... .......... .......... .......... 87% 61.8M 2s\n", + "523100K .......... .......... .......... .......... .......... 87% 53.7M 2s\n", + "523150K .......... .......... .......... .......... .......... 87% 7.66M 2s\n", + "523200K .......... .......... .......... .......... .......... 87% 63.2M 2s\n", + "523250K .......... .......... .......... .......... .......... 87% 22.0M 2s\n", + "523300K .......... .......... .......... .......... .......... 87% 50.9M 2s\n", + "523350K .......... .......... .......... .......... .......... 88% 59.2M 2s\n", + "523400K .......... .......... .......... .......... .......... 88% 57.5M 2s\n", + "523450K .......... .......... .......... .......... .......... 88% 5.71M 2s\n", + "523500K .......... .......... .......... .......... .......... 88% 62.8M 2s\n", + "523550K .......... .......... .......... .......... .......... 88% 69.5M 2s\n", + "523600K .......... .......... .......... .......... .......... 88% 64.6M 2s\n", + "523650K .......... .......... .......... .......... .......... 88% 68.9M 2s\n", + "523700K .......... .......... .......... .......... .......... 88% 70.6M 2s\n", + "523750K .......... .......... .......... .......... .......... 88% 57.5M 2s\n", + "523800K .......... .......... .......... .......... .......... 88% 43.0M 2s\n", + "523850K .......... .......... .......... .......... .......... 88% 61.1M 2s\n", + "523900K .......... .......... .......... .......... .......... 88% 62.2M 2s\n", + "523950K .......... .......... .......... .......... .......... 88% 15.0M 2s\n", + "524000K .......... .......... .......... .......... .......... 88% 65.5M 2s\n", + "524050K .......... .......... .......... .......... .......... 88% 63.5M 2s\n", + "524100K .......... .......... .......... .......... .......... 88% 68.8M 2s\n", + "524150K .......... .......... .......... .......... .......... 88% 70.0M 2s\n", + "524200K .......... .......... .......... .......... .......... 88% 40.1M 2s\n", + "524250K .......... .......... .......... .......... .......... 88% 50.8M 2s\n", + "524300K .......... .......... .......... .......... .......... 88% 61.0M 2s\n", + "524350K .......... .......... .......... .......... .......... 88% 66.8M 2s\n", + "524400K .......... .......... .......... .......... .......... 88% 62.8M 2s\n", + "524450K .......... .......... .......... .......... .......... 88% 24.1M 2s\n", + "524500K .......... .......... .......... .......... .......... 88% 54.4M 2s\n", + "524550K .......... .......... .......... .......... .......... 88% 71.0M 2s\n", + "524600K .......... .......... .......... .......... .......... 88% 21.5M 2s\n", + "524650K .......... .......... .......... .......... .......... 88% 46.5M 2s\n", + "524700K .......... .......... .......... .......... .......... 88% 57.4M 2s\n", + "524750K .......... .......... .......... .......... .......... 88% 65.2M 2s\n", + "524800K .......... .......... .......... .......... .......... 88% 55.9M 2s\n", + "524850K .......... .......... .......... .......... .......... 88% 16.5M 2s\n", + "524900K .......... .......... .......... .......... .......... 88% 39.0M 2s\n", + "524950K .......... .......... .......... .......... .......... 88% 43.5M 2s\n", + "525000K .......... .......... .......... .......... .......... 88% 52.6M 2s\n", + "525050K .......... .......... .......... .......... .......... 88% 61.4M 2s\n", + "525100K .......... .......... .......... .......... .......... 88% 26.4M 2s\n", + "525150K .......... .......... .......... .......... .......... 88% 48.4M 2s\n", + "525200K .......... .......... .......... .......... .......... 88% 61.9M 2s\n", + "525250K .......... .......... .......... .......... .......... 88% 57.4M 2s\n", + "525300K .......... .......... .......... .......... .......... 88% 31.0M 2s\n", + "525350K .......... .......... .......... .......... .......... 88% 57.8M 2s\n", + "525400K .......... .......... .......... .......... .......... 88% 47.1M 2s\n", + "525450K .......... .......... .......... .......... .......... 88% 60.9M 2s\n", + "525500K .......... .......... .......... .......... .......... 88% 29.4M 2s\n", + "525550K .......... .......... .......... .......... .......... 88% 52.8M 2s\n", + "525600K .......... .......... .......... .......... .......... 88% 55.1M 2s\n", + "525650K .......... .......... .......... .......... .......... 88% 55.8M 2s\n", + "525700K .......... .......... .......... .......... .......... 88% 42.6M 2s\n", + "525750K .......... .......... .......... .......... .......... 88% 56.0M 2s\n", + "525800K .......... .......... .......... .......... .......... 88% 41.1M 2s\n", + "525850K .......... .......... .......... .......... .......... 88% 54.5M 2s\n", + "525900K .......... .......... .......... .......... .......... 88% 70.2M 2s\n", + "525950K .......... .......... .......... .......... .......... 88% 26.1M 2s\n", + "526000K .......... .......... .......... .......... .......... 88% 44.5M 2s\n", + "526050K .......... .......... .......... .......... .......... 88% 51.7M 2s\n", + "526100K .......... .......... .......... .......... .......... 88% 62.2M 2s\n", + "526150K .......... .......... .......... .......... .......... 88% 67.7M 2s\n", + "526200K .......... .......... .......... .......... .......... 88% 30.7M 2s\n", + "526250K .......... .......... .......... .......... .......... 88% 49.2M 2s\n", + "526300K .......... .......... .......... .......... .......... 88% 10.5M 2s\n", + "526350K .......... .......... .......... .......... .......... 88% 63.6M 2s\n", + "526400K .......... .......... .......... .......... .......... 88% 58.6M 2s\n", + "526450K .......... .......... .......... .......... .......... 88% 67.1M 2s\n", + "526500K .......... .......... .......... .......... .......... 88% 67.5M 2s\n", + "526550K .......... .......... .......... .......... .......... 88% 37.1M 2s\n", + "526600K .......... .......... .......... .......... .......... 88% 18.3M 2s\n", + "526650K .......... .......... .......... .......... .......... 88% 72.7M 2s\n", + "526700K .......... .......... .......... .......... .......... 88% 66.0M 2s\n", + "526750K .......... .......... .......... .......... .......... 88% 62.9M 2s\n", + "526800K .......... .......... .......... .......... .......... 88% 50.1M 2s\n", + "526850K .......... .......... .......... .......... .......... 88% 63.6M 2s\n", + "526900K .......... .......... .......... .......... .......... 88% 56.6M 2s\n", + "526950K .......... .......... .......... .......... .......... 88% 63.6M 2s\n", + "527000K .......... .......... .......... .......... .......... 88% 42.5M 2s\n", + "527050K .......... .......... .......... .......... .......... 88% 61.2M 2s\n", + "527100K .......... .......... .......... .......... .......... 88% 30.3M 2s\n", + "527150K .......... .......... .......... .......... .......... 88% 61.9M 2s\n", + "527200K .......... .......... .......... .......... .......... 88% 52.4M 2s\n", + "527250K .......... .......... .......... .......... .......... 88% 55.4M 2s\n", + "527300K .......... .......... .......... .......... .......... 88% 36.2M 2s\n", + "527350K .......... .......... .......... .......... .......... 88% 48.9M 2s\n", + "527400K .......... .......... .......... .......... .......... 88% 5.21M 2s\n", + "527450K .......... .......... .......... .......... .......... 88% 76.2M 2s\n", + "527500K .......... .......... .......... .......... .......... 88% 73.5M 2s\n", + "527550K .......... .......... .......... .......... .......... 88% 70.0M 2s\n", + "527600K .......... .......... .......... .......... .......... 88% 60.7M 2s\n", + "527650K .......... .......... .......... .......... .......... 88% 24.7M 2s\n", + "527700K .......... .......... .......... .......... .......... 88% 60.8M 2s\n", + "527750K .......... .......... .......... .......... .......... 88% 58.0M 2s\n", + "527800K .......... .......... .......... .......... .......... 88% 61.7M 2s\n", + "527850K .......... .......... .......... .......... .......... 88% 35.9M 2s\n", + "527900K .......... .......... .......... .......... .......... 88% 48.1M 2s\n", + "527950K .......... .......... .......... .......... .......... 88% 46.5M 2s\n", + "528000K .......... .......... .......... .......... .......... 88% 60.7M 2s\n", + "528050K .......... .......... .......... .......... .......... 88% 69.7M 2s\n", + "528100K .......... .......... .......... .......... .......... 88% 29.7M 2s\n", + "528150K .......... .......... .......... .......... .......... 88% 47.7M 2s\n", + "528200K .......... .......... .......... .......... .......... 88% 48.1M 2s\n", + "528250K .......... .......... .......... .......... .......... 88% 69.0M 2s\n", + "528300K .......... .......... .......... .......... .......... 88% 40.3M 2s\n", + "528350K .......... .......... .......... .......... .......... 88% 46.4M 2s\n", + "528400K .......... .......... .......... .......... .......... 88% 52.9M 2s\n", + "528450K .......... .......... .......... .......... .......... 88% 62.6M 2s\n", + "528500K .......... .......... .......... .......... .......... 88% 74.0M 2s\n", + "528550K .......... .......... .......... .......... .......... 88% 30.8M 2s\n", + "528600K .......... .......... .......... .......... .......... 88% 44.4M 2s\n", + "528650K .......... .......... .......... .......... .......... 88% 55.3M 2s\n", + "528700K .......... .......... .......... .......... .......... 88% 69.8M 2s\n", + "528750K .......... .......... .......... .......... .......... 88% 38.8M 2s\n", + "528800K .......... .......... .......... .......... .......... 88% 44.3M 2s\n", + "528850K .......... .......... .......... .......... .......... 88% 53.7M 2s\n", + "528900K .......... .......... .......... .......... .......... 88% 67.5M 2s\n", + "528950K .......... .......... .......... .......... .......... 88% 5.00M 2s\n", + "529000K .......... .......... .......... .......... .......... 88% 39.1M 2s\n", + "529050K .......... .......... .......... .......... .......... 88% 66.3M 2s\n", + "529100K .......... .......... .......... .......... .......... 88% 64.0M 2s\n", + "529150K .......... .......... .......... .......... .......... 88% 64.9M 2s\n", + "529200K .......... .......... .......... .......... .......... 88% 34.6M 2s\n", + "529250K .......... .......... .......... .......... .......... 88% 46.9M 2s\n", + "529300K .......... .......... .......... .......... .......... 89% 62.6M 2s\n", + "529350K .......... .......... .......... .......... .......... 89% 70.3M 2s\n", + "529400K .......... .......... .......... .......... .......... 89% 29.1M 2s\n", + "529450K .......... .......... .......... .......... .......... 89% 59.1M 2s\n", + "529500K .......... .......... .......... .......... .......... 89% 51.4M 2s\n", + "529550K .......... .......... .......... .......... .......... 89% 64.2M 2s\n", + "529600K .......... .......... .......... .......... .......... 89% 56.7M 2s\n", + "529650K .......... .......... .......... .......... .......... 89% 31.7M 2s\n", + "529700K .......... .......... .......... .......... .......... 89% 51.0M 2s\n", + "529750K .......... .......... .......... .......... .......... 89% 23.7M 2s\n", + "529800K .......... .......... .......... .......... .......... 89% 47.4M 2s\n", + "529850K .......... .......... .......... .......... .......... 89% 42.6M 2s\n", + "529900K .......... .......... .......... .......... .......... 89% 72.1M 2s\n", + "529950K .......... .......... .......... .......... .......... 89% 50.9M 2s\n", + "530000K .......... .......... .......... .......... .......... 89% 39.4M 2s\n", + "530050K .......... .......... .......... .......... .......... 89% 56.1M 2s\n", + "530100K .......... .......... .......... .......... .......... 89% 44.5M 2s\n", + "530150K .......... .......... .......... .......... .......... 89% 35.7M 2s\n", + "530200K .......... .......... .......... .......... .......... 89% 16.8M 2s\n", + "530250K .......... .......... .......... .......... .......... 89% 49.4M 2s\n", + "530300K .......... .......... .......... .......... .......... 89% 40.4M 2s\n", + "530350K .......... .......... .......... .......... .......... 89% 71.2M 2s\n", + "530400K .......... .......... .......... .......... .......... 89% 49.3M 2s\n", + "530450K .......... .......... .......... .......... .......... 89% 39.5M 2s\n", + "530500K .......... .......... .......... .......... .......... 89% 40.6M 2s\n", + "530550K .......... .......... .......... .......... .......... 89% 61.8M 2s\n", + "530600K .......... .......... .......... .......... .......... 89% 54.9M 2s\n", + "530650K .......... .......... .......... .......... .......... 89% 53.1M 2s\n", + "530700K .......... .......... .......... .......... .......... 89% 31.0M 2s\n", + "530750K .......... .......... .......... .......... .......... 89% 54.2M 2s\n", + "530800K .......... .......... .......... .......... .......... 89% 61.7M 2s\n", + "530850K .......... .......... .......... .......... .......... 89% 45.1M 2s\n", + "530900K .......... .......... .......... .......... .......... 89% 44.9M 2s\n", + "530950K .......... .......... .......... .......... .......... 89% 36.4M 2s\n", + "531000K .......... .......... .......... .......... .......... 89% 58.7M 2s\n", + "531050K .......... .......... .......... .......... .......... 89% 46.8M 2s\n", + "531100K .......... .......... .......... .......... .......... 89% 31.7M 2s\n", + "531150K .......... .......... .......... .......... .......... 89% 41.8M 2s\n", + "531200K .......... .......... .......... .......... .......... 89% 53.2M 2s\n", + "531250K .......... .......... .......... .......... .......... 89% 51.9M 2s\n", + "531300K .......... .......... .......... .......... .......... 89% 45.2M 2s\n", + "531350K .......... .......... .......... .......... .......... 89% 37.3M 2s\n", + "531400K .......... .......... .......... .......... .......... 89% 40.7M 2s\n", + "531450K .......... .......... .......... .......... .......... 89% 37.9M 2s\n", + "531500K .......... .......... .......... .......... .......... 89% 38.9M 2s\n", + "531550K .......... .......... .......... .......... .......... 89% 41.6M 2s\n", + "531600K .......... .......... .......... .......... .......... 89% 39.9M 2s\n", + "531650K .......... .......... .......... .......... .......... 89% 40.8M 2s\n", + "531700K .......... .......... .......... .......... .......... 89% 36.1M 2s\n", + "531750K .......... .......... .......... .......... .......... 89% 49.2M 2s\n", + "531800K .......... .......... .......... .......... .......... 89% 32.5M 2s\n", + "531850K .......... .......... .......... .......... .......... 89% 32.4M 2s\n", + "531900K .......... .......... .......... .......... .......... 89% 35.7M 2s\n", + "531950K .......... .......... .......... .......... .......... 89% 37.8M 2s\n", + "532000K .......... .......... .......... .......... .......... 89% 43.4M 2s\n", + "532050K .......... .......... .......... .......... .......... 89% 37.1M 2s\n", + "532100K .......... .......... .......... .......... .......... 89% 43.6M 2s\n", + "532150K .......... .......... .......... .......... .......... 89% 48.2M 2s\n", + "532200K .......... .......... .......... .......... .......... 89% 48.0M 2s\n", + "532250K .......... .......... .......... .......... .......... 89% 54.2M 2s\n", + "532300K .......... .......... .......... .......... .......... 89% 38.8M 2s\n", + "532350K .......... .......... .......... .......... .......... 89% 60.1M 2s\n", + "532400K .......... .......... .......... .......... .......... 89% 51.1M 2s\n", + "532450K .......... .......... .......... .......... .......... 89% 45.3M 2s\n", + "532500K .......... .......... .......... .......... .......... 89% 33.0M 2s\n", + "532550K .......... .......... .......... .......... .......... 89% 51.2M 2s\n", + "532600K .......... .......... .......... .......... .......... 89% 35.8M 2s\n", + "532650K .......... .......... .......... .......... .......... 89% 37.0M 2s\n", + "532700K .......... .......... .......... .......... .......... 89% 33.3M 2s\n", + "532750K .......... .......... .......... .......... .......... 89% 45.5M 2s\n", + "532800K .......... .......... .......... .......... .......... 89% 44.5M 2s\n", + "532850K .......... .......... .......... .......... .......... 89% 47.2M 2s\n", + "532900K .......... .......... .......... .......... .......... 89% 38.0M 2s\n", + "532950K .......... .......... .......... .......... .......... 89% 45.4M 2s\n", + "533000K .......... .......... .......... .......... .......... 89% 45.3M 2s\n", + "533050K .......... .......... .......... .......... .......... 89% 33.9M 2s\n", + "533100K .......... .......... .......... .......... .......... 89% 39.6M 2s\n", + "533150K .......... .......... .......... .......... .......... 89% 45.4M 2s\n", + "533200K .......... .......... .......... .......... .......... 89% 50.3M 2s\n", + "533250K .......... .......... .......... .......... .......... 89% 51.4M 2s\n", + "533300K .......... .......... .......... .......... .......... 89% 54.0M 2s\n", + "533350K .......... .......... .......... .......... .......... 89% 44.9M 2s\n", + "533400K .......... .......... .......... .......... .......... 89% 43.2M 2s\n", + "533450K .......... .......... .......... .......... .......... 89% 39.5M 2s\n", + "533500K .......... .......... .......... .......... .......... 89% 58.3M 2s\n", + "533550K .......... .......... .......... .......... .......... 89% 33.1M 2s\n", + "533600K .......... .......... .......... .......... .......... 89% 41.1M 2s\n", + "533650K .......... .......... .......... .......... .......... 89% 47.7M 2s\n", + "533700K .......... .......... .......... .......... .......... 89% 44.6M 2s\n", + "533750K .......... .......... .......... .......... .......... 89% 48.8M 2s\n", + "533800K .......... .......... .......... .......... .......... 89% 33.4M 2s\n", + "533850K .......... .......... .......... .......... .......... 89% 52.1M 2s\n", + "533900K .......... .......... .......... .......... .......... 89% 50.3M 2s\n", + "533950K .......... .......... .......... .......... .......... 89% 42.2M 2s\n", + "534000K .......... .......... .......... .......... .......... 89% 34.8M 2s\n", + "534050K .......... .......... .......... .......... .......... 89% 41.8M 2s\n", + "534100K .......... .......... .......... .......... .......... 89% 51.8M 2s\n", + "534150K .......... .......... .......... .......... .......... 89% 47.1M 2s\n", + "534200K .......... .......... .......... .......... .......... 89% 32.9M 2s\n", + "534250K .......... .......... .......... .......... .......... 89% 40.3M 2s\n", + "534300K .......... .......... .......... .......... .......... 89% 57.7M 2s\n", + "534350K .......... .......... .......... .......... .......... 89% 42.2M 2s\n", + "534400K .......... .......... .......... .......... .......... 89% 33.8M 2s\n", + "534450K .......... .......... .......... .......... .......... 89% 48.0M 2s\n", + "534500K .......... .......... .......... .......... .......... 89% 62.3M 2s\n", + "534550K .......... .......... .......... .......... .......... 89% 48.6M 2s\n", + "534600K .......... .......... .......... .......... .......... 89% 36.3M 2s\n", + "534650K .......... .......... .......... .......... .......... 89% 39.7M 2s\n", + "534700K .......... .......... .......... .......... .......... 89% 64.3M 2s\n", + "534750K .......... .......... .......... .......... .......... 89% 59.0M 2s\n", + "534800K .......... .......... .......... .......... .......... 89% 40.3M 2s\n", + "534850K .......... .......... .......... .......... .......... 89% 29.3M 2s\n", + "534900K .......... .......... .......... .......... .......... 89% 61.3M 2s\n", + "534950K .......... .......... .......... .......... .......... 89% 70.1M 2s\n", + "535000K .......... .......... .......... .......... .......... 89% 58.5M 2s\n", + "535050K .......... .......... .......... .......... .......... 89% 63.5M 2s\n", + "535100K .......... .......... .......... .......... .......... 89% 56.9M 2s\n", + "535150K .......... .......... .......... .......... .......... 89% 57.2M 2s\n", + "535200K .......... .......... .......... .......... .......... 89% 60.1M 2s\n", + "535250K .......... .......... .......... .......... .......... 90% 78.6M 2s\n", + "535300K .......... .......... .......... .......... .......... 90% 61.3M 2s\n", + "535350K .......... .......... .......... .......... .......... 90% 54.8M 2s\n", + "535400K .......... .......... .......... .......... .......... 90% 51.1M 2s\n", + "535450K .......... .......... .......... .......... .......... 90% 67.9M 2s\n", + "535500K .......... .......... .......... .......... .......... 90% 67.0M 2s\n", + "535550K .......... .......... .......... .......... .......... 90% 70.0M 2s\n", + "535600K .......... .......... .......... .......... .......... 90% 63.2M 2s\n", + "535650K .......... .......... .......... .......... .......... 90% 52.3M 2s\n", + "535700K .......... .......... .......... .......... .......... 90% 58.6M 2s\n", + "535750K .......... .......... .......... .......... .......... 90% 71.7M 2s\n", + "535800K .......... .......... .......... .......... .......... 90% 45.6M 2s\n", + "535850K .......... .......... .......... .......... .......... 90% 39.7M 2s\n", + "535900K .......... .......... .......... .......... .......... 90% 45.5M 2s\n", + "535950K .......... .......... .......... .......... .......... 90% 49.5M 2s\n", + "536000K .......... .......... .......... .......... .......... 90% 49.0M 2s\n", + "536050K .......... .......... .......... .......... .......... 90% 58.8M 2s\n", + "536100K .......... .......... .......... .......... .......... 90% 66.8M 2s\n", + "536150K .......... .......... .......... .......... .......... 90% 55.0M 2s\n", + "536200K .......... .......... .......... .......... .......... 90% 48.8M 2s\n", + "536250K .......... .......... .......... .......... .......... 90% 70.0M 2s\n", + "536300K .......... .......... .......... .......... .......... 90% 57.2M 2s\n", + "536350K .......... .......... .......... .......... .......... 90% 54.5M 2s\n", + "536400K .......... .......... .......... .......... .......... 90% 34.5M 2s\n", + "536450K .......... .......... .......... .......... .......... 90% 36.3M 2s\n", + "536500K .......... .......... .......... .......... .......... 90% 12.0M 2s\n", + "536550K .......... .......... .......... .......... .......... 90% 49.0M 2s\n", + "536600K .......... .......... .......... .......... .......... 90% 39.6M 2s\n", + "536650K .......... .......... .......... .......... .......... 90% 35.7M 2s\n", + "536700K .......... .......... .......... .......... .......... 90% 47.6M 2s\n", + "536750K .......... .......... .......... .......... .......... 90% 41.6M 2s\n", + "536800K .......... .......... .......... .......... .......... 90% 44.2M 2s\n", + "536850K .......... .......... .......... .......... .......... 90% 24.9M 2s\n", + "536900K .......... .......... .......... .......... .......... 90% 35.5M 2s\n", + "536950K .......... .......... .......... .......... .......... 90% 68.4M 2s\n", + "537000K .......... .......... .......... .......... .......... 90% 56.7M 2s\n", + "537050K .......... .......... .......... .......... .......... 90% 68.1M 2s\n", + "537100K .......... .......... .......... .......... .......... 90% 66.2M 2s\n", + "537150K .......... .......... .......... .......... .......... 90% 49.8M 2s\n", + "537200K .......... .......... .......... .......... .......... 90% 31.1M 2s\n", + "537250K .......... .......... .......... .......... .......... 90% 43.8M 2s\n", + "537300K .......... .......... .......... .......... .......... 90% 64.7M 2s\n", + "537350K .......... .......... .......... .......... .......... 90% 47.7M 2s\n", + "537400K .......... .......... .......... .......... .......... 90% 24.2M 2s\n", + "537450K .......... .......... .......... .......... .......... 90% 50.9M 2s\n", + "537500K .......... .......... .......... .......... .......... 90% 68.1M 2s\n", + "537550K .......... .......... .......... .......... .......... 90% 53.1M 2s\n", + "537600K .......... .......... .......... .......... .......... 90% 36.2M 2s\n", + "537650K .......... .......... .......... .......... .......... 90% 33.6M 2s\n", + "537700K .......... .......... .......... .......... .......... 90% 67.4M 2s\n", + "537750K .......... .......... .......... .......... .......... 90% 55.1M 2s\n", + "537800K .......... .......... .......... .......... .......... 90% 34.0M 2s\n", + "537850K .......... .......... .......... .......... .......... 90% 33.2M 2s\n", + "537900K .......... .......... .......... .......... .......... 90% 58.6M 2s\n", + "537950K .......... .......... .......... .......... .......... 90% 51.6M 2s\n", + "538000K .......... .......... .......... .......... .......... 90% 39.1M 2s\n", + "538050K .......... .......... .......... .......... .......... 90% 38.2M 2s\n", + "538100K .......... .......... .......... .......... .......... 90% 36.6M 2s\n", + "538150K .......... .......... .......... .......... .......... 90% 56.5M 2s\n", + "538200K .......... .......... .......... .......... .......... 90% 40.0M 2s\n", + "538250K .......... .......... .......... .......... .......... 90% 29.2M 2s\n", + "538300K .......... .......... .......... .......... .......... 90% 45.5M 2s\n", + "538350K .......... .......... .......... .......... .......... 90% 66.2M 2s\n", + "538400K .......... .......... .......... .......... .......... 90% 47.8M 2s\n", + "538450K .......... .......... .......... .......... .......... 90% 33.0M 2s\n", + "538500K .......... .......... .......... .......... .......... 90% 42.5M 2s\n", + "538550K .......... .......... .......... .......... .......... 90% 52.8M 2s\n", + "538600K .......... .......... .......... .......... .......... 90% 30.8M 2s\n", + "538650K .......... .......... .......... .......... .......... 90% 47.3M 2s\n", + "538700K .......... .......... .......... .......... .......... 90% 42.0M 2s\n", + "538750K .......... .......... .......... .......... .......... 90% 48.0M 2s\n", + "538800K .......... .......... .......... .......... .......... 90% 40.6M 2s\n", + "538850K .......... .......... .......... .......... .......... 90% 42.2M 2s\n", + "538900K .......... .......... .......... .......... .......... 90% 40.9M 2s\n", + "538950K .......... .......... .......... .......... .......... 90% 43.5M 2s\n", + "539000K .......... .......... .......... .......... .......... 90% 33.1M 2s\n", + "539050K .......... .......... .......... .......... .......... 90% 46.3M 2s\n", + "539100K .......... .......... .......... .......... .......... 90% 37.1M 2s\n", + "539150K .......... .......... .......... .......... .......... 90% 40.2M 2s\n", + "539200K .......... .......... .......... .......... .......... 90% 39.0M 2s\n", + "539250K .......... .......... .......... .......... .......... 90% 42.7M 2s\n", + "539300K .......... .......... .......... .......... .......... 90% 45.9M 2s\n", + "539350K .......... .......... .......... .......... .......... 90% 33.8M 2s\n", + "539400K .......... .......... .......... .......... .......... 90% 43.2M 2s\n", + "539450K .......... .......... .......... .......... .......... 90% 35.8M 2s\n", + "539500K .......... .......... .......... .......... .......... 90% 38.5M 2s\n", + "539550K .......... .......... .......... .......... .......... 90% 52.8M 2s\n", + "539600K .......... .......... .......... .......... .......... 90% 32.7M 2s\n", + "539650K .......... .......... .......... .......... .......... 90% 33.6M 2s\n", + "539700K .......... .......... .......... .......... .......... 90% 55.8M 2s\n", + "539750K .......... .......... .......... .......... .......... 90% 52.6M 2s\n", + "539800K .......... .......... .......... .......... .......... 90% 41.1M 2s\n", + "539850K .......... .......... .......... .......... .......... 90% 32.1M 2s\n", + "539900K .......... .......... .......... .......... .......... 90% 20.4M 2s\n", + "539950K .......... .......... .......... .......... .......... 90% 34.1M 2s\n", + "540000K .......... .......... .......... .......... .......... 90% 34.6M 2s\n", + "540050K .......... .......... .......... .......... .......... 90% 37.2M 2s\n", + "540100K .......... .......... .......... .......... .......... 90% 56.5M 2s\n", + "540150K .......... .......... .......... .......... .......... 90% 75.1M 2s\n", + "540200K .......... .......... .......... .......... .......... 90% 45.9M 2s\n", + "540250K .......... .......... .......... .......... .......... 90% 73.6M 2s\n", + "540300K .......... .......... .......... .......... .......... 90% 60.6M 2s\n", + "540350K .......... .......... .......... .......... .......... 90% 56.8M 2s\n", + "540400K .......... .......... .......... .......... .......... 90% 50.4M 2s\n", + "540450K .......... .......... .......... .......... .......... 90% 65.1M 2s\n", + "540500K .......... .......... .......... .......... .......... 90% 62.7M 2s\n", + "540550K .......... .......... .......... .......... .......... 90% 48.2M 2s\n", + "540600K .......... .......... .......... .......... .......... 90% 38.5M 2s\n", + "540650K .......... .......... .......... .......... .......... 90% 54.5M 2s\n", + "540700K .......... .......... .......... .......... .......... 90% 57.4M 2s\n", + "540750K .......... .......... .......... .......... .......... 90% 53.0M 2s\n", + "540800K .......... .......... .......... .......... .......... 90% 49.8M 2s\n", + "540850K .......... .......... .......... .......... .......... 90% 49.3M 2s\n", + "540900K .......... .......... .......... .......... .......... 90% 68.0M 2s\n", + "540950K .......... .......... .......... .......... .......... 90% 62.2M 2s\n", + "541000K .......... .......... .......... .......... .......... 90% 56.1M 2s\n", + "541050K .......... .......... .......... .......... .......... 90% 56.2M 2s\n", + "541100K .......... .......... .......... .......... .......... 90% 63.9M 2s\n", + "541150K .......... .......... .......... .......... .......... 90% 45.1M 2s\n", + "541200K .......... .......... .......... .......... .......... 91% 57.2M 2s\n", + "541250K .......... .......... .......... .......... .......... 91% 3.76M 2s\n", + "541300K .......... .......... .......... .......... .......... 91% 72.3M 2s\n", + "541350K .......... .......... .......... .......... .......... 91% 65.9M 2s\n", + "541400K .......... .......... .......... .......... .......... 91% 58.5M 2s\n", + "541450K .......... .......... .......... .......... .......... 91% 67.4M 2s\n", + "541500K .......... .......... .......... .......... .......... 91% 19.9M 2s\n", + "541550K .......... .......... .......... .......... .......... 91% 69.9M 2s\n", + "541600K .......... .......... .......... .......... .......... 91% 60.8M 2s\n", + "541650K .......... .......... .......... .......... .......... 91% 4.08M 2s\n", + "541700K .......... .......... .......... .......... .......... 91% 57.8M 2s\n", + "541750K .......... .......... .......... .......... .......... 91% 65.8M 2s\n", + "541800K .......... .......... .......... .......... .......... 91% 55.9M 2s\n", + "541850K .......... .......... .......... .......... .......... 91% 68.3M 2s\n", + "541900K .......... .......... .......... .......... .......... 91% 60.9M 2s\n", + "541950K .......... .......... .......... .......... .......... 91% 71.3M 2s\n", + "542000K .......... .......... .......... .......... .......... 91% 50.7M 2s\n", + "542050K .......... .......... .......... .......... .......... 91% 59.8M 2s\n", + "542100K .......... .......... .......... .......... .......... 91% 76.9M 2s\n", + "542150K .......... .......... .......... .......... .......... 91% 70.5M 2s\n", + "542200K .......... .......... .......... .......... .......... 91% 55.7M 2s\n", + "542250K .......... .......... .......... .......... .......... 91% 47.7M 2s\n", + "542300K .......... .......... .......... .......... .......... 91% 14.9M 2s\n", + "542350K .......... .......... .......... .......... .......... 91% 54.8M 2s\n", + "542400K .......... .......... .......... .......... .......... 91% 41.4M 2s\n", + "542450K .......... .......... .......... .......... .......... 91% 59.7M 2s\n", + "542500K .......... .......... .......... .......... .......... 91% 64.9M 2s\n", + "542550K .......... .......... .......... .......... .......... 91% 72.1M 2s\n", + "542600K .......... .......... .......... .......... .......... 91% 47.0M 2s\n", + "542650K .......... .......... .......... .......... .......... 91% 51.3M 2s\n", + "542700K .......... .......... .......... .......... .......... 91% 66.7M 2s\n", + "542750K .......... .......... .......... .......... .......... 91% 66.1M 2s\n", + "542800K .......... .......... .......... .......... .......... 91% 6.76M 2s\n", + "542850K .......... .......... .......... .......... .......... 91% 72.4M 2s\n", + "542900K .......... .......... .......... .......... .......... 91% 60.2M 2s\n", + "542950K .......... .......... .......... .......... .......... 91% 71.6M 2s\n", + "543000K .......... .......... .......... .......... .......... 91% 50.5M 2s\n", + "543050K .......... .......... .......... .......... .......... 91% 67.2M 2s\n", + "543100K .......... .......... .......... .......... .......... 91% 56.8M 2s\n", + "543150K .......... .......... .......... .......... .......... 91% 58.8M 2s\n", + "543200K .......... .......... .......... .......... .......... 91% 11.8M 2s\n", + "543250K .......... .......... .......... .......... .......... 91% 70.3M 2s\n", + "543300K .......... .......... .......... .......... .......... 91% 64.4M 2s\n", + "543350K .......... .......... .......... .......... .......... 91% 65.5M 2s\n", + "543400K .......... .......... .......... .......... .......... 91% 48.8M 2s\n", + "543450K .......... .......... .......... .......... .......... 91% 68.5M 2s\n", + "543500K .......... .......... .......... .......... .......... 91% 54.6M 2s\n", + "543550K .......... .......... .......... .......... .......... 91% 57.6M 2s\n", + "543600K .......... .......... .......... .......... .......... 91% 61.8M 2s\n", + "543650K .......... .......... .......... .......... .......... 91% 59.9M 2s\n", + "543700K .......... .......... .......... .......... .......... 91% 56.2M 2s\n", + "543750K .......... .......... .......... .......... .......... 91% 65.1M 2s\n", + "543800K .......... .......... .......... .......... .......... 91% 43.9M 2s\n", + "543850K .......... .......... .......... .......... .......... 91% 63.0M 2s\n", + "543900K .......... .......... .......... .......... .......... 91% 61.9M 2s\n", + "543950K .......... .......... .......... .......... .......... 91% 61.7M 2s\n", + "544000K .......... .......... .......... .......... .......... 91% 58.8M 2s\n", + "544050K .......... .......... .......... .......... .......... 91% 53.3M 2s\n", + "544100K .......... .......... .......... .......... .......... 91% 53.9M 2s\n", + "544150K .......... .......... .......... .......... .......... 91% 71.3M 2s\n", + "544200K .......... .......... .......... .......... .......... 91% 41.8M 2s\n", + "544250K .......... .......... .......... .......... .......... 91% 69.5M 2s\n", + "544300K .......... .......... .......... .......... .......... 91% 66.5M 2s\n", + "544350K .......... .......... .......... .......... .......... 91% 51.1M 2s\n", + "544400K .......... .......... .......... .......... .......... 91% 53.4M 2s\n", + "544450K .......... .......... .......... .......... .......... 91% 62.6M 2s\n", + "544500K .......... .......... .......... .......... .......... 91% 56.2M 2s\n", + "544550K .......... .......... .......... .......... .......... 91% 74.6M 2s\n", + "544600K .......... .......... .......... .......... .......... 91% 50.1M 2s\n", + "544650K .......... .......... .......... .......... .......... 91% 56.7M 2s\n", + "544700K .......... .......... .......... .......... .......... 91% 60.2M 2s\n", + "544750K .......... .......... .......... .......... .......... 91% 45.8M 2s\n", + "544800K .......... .......... .......... .......... .......... 91% 14.6M 2s\n", + "544850K .......... .......... .......... .......... .......... 91% 65.0M 2s\n", + "544900K .......... .......... .......... .......... .......... 91% 57.4M 2s\n", + "544950K .......... .......... .......... .......... .......... 91% 64.4M 2s\n", + "545000K .......... .......... .......... .......... .......... 91% 54.4M 2s\n", + "545050K .......... .......... .......... .......... .......... 91% 75.9M 2s\n", + "545100K .......... .......... .......... .......... .......... 91% 58.3M 2s\n", + "545150K .......... .......... .......... .......... .......... 91% 47.1M 2s\n", + "545200K .......... .......... .......... .......... .......... 91% 60.0M 2s\n", + "545250K .......... .......... .......... .......... .......... 91% 70.5M 2s\n", + "545300K .......... .......... .......... .......... .......... 91% 75.5M 2s\n", + "545350K .......... .......... .......... .......... .......... 91% 36.6M 2s\n", + "545400K .......... .......... .......... .......... .......... 91% 37.1M 2s\n", + "545450K .......... .......... .......... .......... .......... 91% 56.1M 2s\n", + "545500K .......... .......... .......... .......... .......... 91% 70.2M 2s\n", + "545550K .......... .......... .......... .......... .......... 91% 61.9M 2s\n", + "545600K .......... .......... .......... .......... .......... 91% 47.6M 2s\n", + "545650K .......... .......... .......... .......... .......... 91% 49.4M 2s\n", + "545700K .......... .......... .......... .......... .......... 91% 47.6M 2s\n", + "545750K .......... .......... .......... .......... .......... 91% 69.7M 2s\n", + "545800K .......... .......... .......... .......... .......... 91% 53.1M 2s\n", + "545850K .......... .......... .......... .......... .......... 91% 51.6M 2s\n", + "545900K .......... .......... .......... .......... .......... 91% 45.5M 2s\n", + "545950K .......... .......... .......... .......... .......... 91% 63.9M 2s\n", + "546000K .......... .......... .......... .......... .......... 91% 59.5M 2s\n", + "546050K .......... .......... .......... .......... .......... 91% 66.0M 2s\n", + "546100K .......... .......... .......... .......... .......... 91% 54.7M 2s\n", + "546150K .......... .......... .......... .......... .......... 91% 45.6M 2s\n", + "546200K .......... .......... .......... .......... .......... 91% 53.2M 2s\n", + "546250K .......... .......... .......... .......... .......... 91% 65.5M 2s\n", + "546300K .......... .......... .......... .......... .......... 91% 70.9M 2s\n", + "546350K .......... .......... .......... .......... .......... 91% 49.2M 2s\n", + "546400K .......... .......... .......... .......... .......... 91% 41.8M 2s\n", + "546450K .......... .......... .......... .......... .......... 91% 63.3M 2s\n", + "546500K .......... .......... .......... .......... .......... 91% 64.6M 2s\n", + "546550K .......... .......... .......... .......... .......... 91% 65.5M 2s\n", + "546600K .......... .......... .......... .......... .......... 91% 46.8M 2s\n", + "546650K .......... .......... .......... .......... .......... 91% 60.4M 2s\n", + "546700K .......... .......... .......... .......... .......... 91% 64.9M 2s\n", + "546750K .......... .......... .......... .......... .......... 91% 55.5M 2s\n", + "546800K .......... .......... .......... .......... .......... 91% 52.4M 2s\n", + "546850K .......... .......... .......... .......... .......... 91% 47.5M 2s\n", + "546900K .......... .......... .......... .......... .......... 91% 53.9M 2s\n", + "546950K .......... .......... .......... .......... .......... 91% 51.8M 2s\n", + "547000K .......... .......... .......... .......... .......... 91% 45.7M 2s\n", + "547050K .......... .......... .......... .......... .......... 91% 61.3M 2s\n", + "547100K .......... .......... .......... .......... .......... 91% 53.6M 2s\n", + "547150K .......... .......... .......... .......... .......... 92% 50.9M 2s\n", + "547200K .......... .......... .......... .......... .......... 92% 55.2M 2s\n", + "547250K .......... .......... .......... .......... .......... 92% 57.5M 2s\n", + "547300K .......... .......... .......... .......... .......... 92% 58.2M 2s\n", + "547350K .......... .......... .......... .......... .......... 92% 53.3M 2s\n", + "547400K .......... .......... .......... .......... .......... 92% 44.9M 2s\n", + "547450K .......... .......... .......... .......... .......... 92% 62.9M 2s\n", + "547500K .......... .......... .......... .......... .......... 92% 60.9M 2s\n", + "547550K .......... .......... .......... .......... .......... 92% 67.6M 2s\n", + "547600K .......... .......... .......... .......... .......... 92% 50.8M 2s\n", + "547650K .......... .......... .......... .......... .......... 92% 55.9M 2s\n", + "547700K .......... .......... .......... .......... .......... 92% 67.7M 2s\n", + "547750K .......... .......... .......... .......... .......... 92% 58.5M 2s\n", + "547800K .......... .......... .......... .......... .......... 92% 47.3M 2s\n", + "547850K .......... .......... .......... .......... .......... 92% 5.50M 2s\n", + "547900K .......... .......... .......... .......... .......... 92% 64.9M 2s\n", + "547950K .......... .......... .......... .......... .......... 92% 74.5M 2s\n", + "548000K .......... .......... .......... .......... .......... 92% 63.1M 2s\n", + "548050K .......... .......... .......... .......... .......... 92% 58.8M 2s\n", + "548100K .......... .......... .......... .......... .......... 92% 66.3M 2s\n", + "548150K .......... .......... .......... .......... .......... 92% 66.5M 2s\n", + "548200K .......... .......... .......... .......... .......... 92% 62.2M 2s\n", + "548250K .......... .......... .......... .......... .......... 92% 53.1M 2s\n", + "548300K .......... .......... .......... .......... .......... 92% 60.6M 2s\n", + "548350K .......... .......... .......... .......... .......... 92% 53.9M 2s\n", + "548400K .......... .......... .......... .......... .......... 92% 60.4M 2s\n", + "548450K .......... .......... .......... .......... .......... 92% 68.0M 2s\n", + "548500K .......... .......... .......... .......... .......... 92% 83.2M 2s\n", + "548550K .......... .......... .......... .......... .......... 92% 72.6M 2s\n", + "548600K .......... .......... .......... .......... .......... 92% 45.8M 2s\n", + "548650K .......... .......... .......... .......... .......... 92% 45.3M 2s\n", + "548700K .......... .......... .......... .......... .......... 92% 52.9M 2s\n", + "548750K .......... .......... .......... .......... .......... 92% 67.1M 2s\n", + "548800K .......... .......... .......... .......... .......... 92% 63.1M 2s\n", + "548850K .......... .......... .......... .......... .......... 92% 58.4M 2s\n", + "548900K .......... .......... .......... .......... .......... 92% 48.4M 2s\n", + "548950K .......... .......... .......... .......... .......... 92% 49.6M 2s\n", + "549000K .......... .......... .......... .......... .......... 92% 53.6M 2s\n", + "549050K .......... .......... .......... .......... .......... 92% 71.1M 2s\n", + "549100K .......... .......... .......... .......... .......... 92% 64.3M 2s\n", + "549150K .......... .......... .......... .......... .......... 92% 66.5M 2s\n", + "549200K .......... .......... .......... .......... .......... 92% 58.8M 2s\n", + "549250K .......... .......... .......... .......... .......... 92% 65.4M 2s\n", + "549300K .......... .......... .......... .......... .......... 92% 67.5M 2s\n", + "549350K .......... .......... .......... .......... .......... 92% 67.2M 2s\n", + "549400K .......... .......... .......... .......... .......... 92% 56.1M 2s\n", + "549450K .......... .......... .......... .......... .......... 92% 61.4M 2s\n", + "549500K .......... .......... .......... .......... .......... 92% 67.6M 2s\n", + "549550K .......... .......... .......... .......... .......... 92% 72.0M 2s\n", + "549600K .......... .......... .......... .......... .......... 92% 51.4M 2s\n", + "549650K .......... .......... .......... .......... .......... 92% 47.9M 2s\n", + "549700K .......... .......... .......... .......... .......... 92% 57.9M 1s\n", + "549750K .......... .......... .......... .......... .......... 92% 64.7M 1s\n", + "549800K .......... .......... .......... .......... .......... 92% 55.7M 1s\n", + "549850K .......... .......... .......... .......... .......... 92% 68.5M 1s\n", + "549900K .......... .......... .......... .......... .......... 92% 53.7M 1s\n", + "549950K .......... .......... .......... .......... .......... 92% 50.7M 1s\n", + "550000K .......... .......... .......... .......... .......... 92% 51.9M 1s\n", + "550050K .......... .......... .......... .......... .......... 92% 67.3M 1s\n", + "550100K .......... .......... .......... .......... .......... 92% 69.8M 1s\n", + "550150K .......... .......... .......... .......... .......... 92% 55.8M 1s\n", + "550200K .......... .......... .......... .......... .......... 92% 42.1M 1s\n", + "550250K .......... .......... .......... .......... .......... 92% 49.4M 1s\n", + "550300K .......... .......... .......... .......... .......... 92% 67.7M 1s\n", + "550350K .......... .......... .......... .......... .......... 92% 65.3M 1s\n", + "550400K .......... .......... .......... .......... .......... 92% 50.6M 1s\n", + "550450K .......... .......... .......... .......... .......... 92% 49.4M 1s\n", + "550500K .......... .......... .......... .......... .......... 92% 47.8M 1s\n", + "550550K .......... .......... .......... .......... .......... 92% 62.8M 1s\n", + "550600K .......... .......... .......... .......... .......... 92% 49.6M 1s\n", + "550650K .......... .......... .......... .......... .......... 92% 44.4M 1s\n", + "550700K .......... .......... .......... .......... .......... 92% 49.2M 1s\n", + "550750K .......... .......... .......... .......... .......... 92% 51.2M 1s\n", + "550800K .......... .......... .......... .......... .......... 92% 59.6M 1s\n", + "550850K .......... .......... .......... .......... .......... 92% 64.1M 1s\n", + "550900K .......... .......... .......... .......... .......... 92% 64.6M 1s\n", + "550950K .......... .......... .......... .......... .......... 92% 53.8M 1s\n", + "551000K .......... .......... .......... .......... .......... 92% 41.4M 1s\n", + "551050K .......... .......... .......... .......... .......... 92% 62.7M 1s\n", + "551100K .......... .......... .......... .......... .......... 92% 63.7M 1s\n", + "551150K .......... .......... .......... .......... .......... 92% 64.9M 1s\n", + "551200K .......... .......... .......... .......... .......... 92% 50.0M 1s\n", + "551250K .......... .......... .......... .......... .......... 92% 49.6M 1s\n", + "551300K .......... .......... .......... .......... .......... 92% 57.2M 1s\n", + "551350K .......... .......... .......... .......... .......... 92% 65.0M 1s\n", + "551400K .......... .......... .......... .......... .......... 92% 46.8M 1s\n", + "551450K .......... .......... .......... .......... .......... 92% 55.3M 1s\n", + "551500K .......... .......... .......... .......... .......... 92% 48.3M 1s\n", + "551550K .......... .......... .......... .......... .......... 92% 54.5M 1s\n", + "551600K .......... .......... .......... .......... .......... 92% 51.7M 1s\n", + "551650K .......... .......... .......... .......... .......... 92% 6.60M 1s\n", + "551700K .......... .......... .......... .......... .......... 92% 81.8M 1s\n", + "551750K .......... .......... .......... .......... .......... 92% 73.8M 1s\n", + "551800K .......... .......... .......... .......... .......... 92% 60.4M 1s\n", + "551850K .......... .......... .......... .......... .......... 92% 80.4M 1s\n", + "551900K .......... .......... .......... .......... .......... 92% 73.8M 1s\n", + "551950K .......... .......... .......... .......... .......... 92% 71.5M 1s\n", + "552000K .......... .......... .......... .......... .......... 92% 49.0M 1s\n", + "552050K .......... .......... .......... .......... .......... 92% 47.3M 1s\n", "552100K .......... .......... .......... .......... .......... 92% 71.9M 1s\n", - "552150K .......... .......... .......... .......... .......... 92% 23.1M 1s\n", - "552200K .......... .......... .......... .......... .......... 92% 34.3M 1s\n", - "552250K .......... .......... .......... .......... .......... 92% 68.9M 1s\n", - "552300K .......... .......... .......... .......... .......... 92% 26.8M 1s\n", - "552350K .......... .......... .......... .......... .......... 92% 28.6M 1s\n", - "552400K .......... .......... .......... .......... .......... 92% 38.7M 1s\n", - "552450K .......... .......... .......... .......... .......... 92% 35.1M 1s\n", - "552500K .......... .......... .......... .......... .......... 92% 34.3M 1s\n", - "552550K .......... .......... .......... .......... .......... 92% 43.3M 1s\n", - "552600K .......... .......... .......... .......... .......... 92% 32.7M 1s\n", - "552650K .......... .......... .......... .......... .......... 92% 28.8M 1s\n", - "552700K .......... .......... .......... .......... .......... 92% 53.5M 1s\n", - "552750K .......... .......... .......... .......... .......... 92% 63.8M 1s\n", - "552800K .......... .......... .......... .......... .......... 92% 27.9M 1s\n", - "552850K .......... .......... .......... .......... .......... 92% 29.8M 1s\n", - "552900K .......... .......... .......... .......... .......... 92% 48.1M 1s\n", - "552950K .......... .......... .......... .......... .......... 92% 32.6M 1s\n", - "553000K .......... .......... .......... .......... .......... 92% 31.8M 1s\n", - "553050K .......... .......... .......... .......... .......... 93% 52.9M 1s\n", - "553100K .......... .......... .......... .......... .......... 93% 56.5M 1s\n", - "553150K .......... .......... .......... .......... .......... 93% 29.6M 1s\n", - "553200K .......... .......... .......... .......... .......... 93% 19.4M 1s\n", - "553250K .......... .......... .......... .......... .......... 93% 70.0M 1s\n", - "553300K .......... .......... .......... .......... .......... 93% 40.5M 1s\n", - "553350K .......... .......... .......... .......... .......... 93% 40.5M 1s\n", - "553400K .......... .......... .......... .......... .......... 93% 22.3M 1s\n", - "553450K .......... .......... .......... .......... .......... 93% 52.8M 1s\n", - "553500K .......... .......... .......... .......... .......... 93% 46.2M 1s\n", - "553550K .......... .......... .......... .......... .......... 93% 26.0M 1s\n", - "553600K .......... .......... .......... .......... .......... 93% 22.7M 1s\n", - "553650K .......... .......... .......... .......... .......... 93% 52.9M 1s\n", - "553700K .......... .......... .......... .......... .......... 93% 51.0M 1s\n", - "553750K .......... .......... .......... .......... .......... 93% 55.0M 1s\n", - "553800K .......... .......... .......... .......... .......... 93% 22.1M 1s\n", - "553850K .......... .......... .......... .......... .......... 93% 37.5M 1s\n", - "553900K .......... .......... .......... .......... .......... 93% 40.2M 1s\n", - "553950K .......... .......... .......... .......... .......... 93% 20.1M 1s\n", - "554000K .......... .......... .......... .......... .......... 93% 25.1M 1s\n", - "554050K .......... .......... .......... .......... .......... 93% 31.5M 1s\n", - "554100K .......... .......... .......... .......... .......... 93% 20.4M 1s\n", - "554150K .......... .......... .......... .......... .......... 93% 31.4M 1s\n", - "554200K .......... .......... .......... .......... .......... 93% 47.0M 1s\n", - "554250K .......... .......... .......... .......... .......... 93% 32.9M 1s\n", - "554300K .......... .......... .......... .......... .......... 93% 42.6M 1s\n", - "554350K .......... .......... .......... .......... .......... 93% 33.3M 1s\n", - "554400K .......... .......... .......... .......... .......... 93% 18.3M 1s\n", - "554450K .......... .......... .......... .......... .......... 93% 43.9M 1s\n", - "554500K .......... .......... .......... .......... .......... 93% 56.0M 1s\n", - "554550K .......... .......... .......... .......... .......... 93% 37.9M 1s\n", - "554600K .......... .......... .......... .......... .......... 93% 31.8M 1s\n", - "554650K .......... .......... .......... .......... .......... 93% 57.0M 1s\n", - "554700K .......... .......... .......... .......... .......... 93% 54.2M 1s\n", - "554750K .......... .......... .......... .......... .......... 93% 53.3M 1s\n", - "554800K .......... .......... .......... .......... .......... 93% 32.9M 1s\n", - "554850K .......... .......... .......... .......... .......... 93% 41.7M 1s\n", - "554900K .......... .......... .......... .......... .......... 93% 54.6M 1s\n", - "554950K .......... .......... .......... .......... .......... 93% 55.5M 1s\n", - "555000K .......... .......... .......... .......... .......... 93% 41.6M 1s\n", - "555050K .......... .......... .......... .......... .......... 93% 33.1M 1s\n", - "555100K .......... .......... .......... .......... .......... 93% 59.9M 1s\n", - "555150K .......... .......... .......... .......... .......... 93% 50.1M 1s\n", - "555200K .......... .......... .......... .......... .......... 93% 44.9M 1s\n", - "555250K .......... .......... .......... .......... .......... 93% 27.1M 1s\n", - "555300K .......... .......... .......... .......... .......... 93% 49.6M 1s\n", - "555350K .......... .......... .......... .......... .......... 93% 40.0M 1s\n", - "555400K .......... .......... .......... .......... .......... 93% 28.6M 1s\n", - "555450K .......... .......... .......... .......... .......... 93% 29.9M 1s\n", - "555500K .......... .......... .......... .......... .......... 93% 50.9M 1s\n", - "555550K .......... .......... .......... .......... .......... 93% 62.2M 1s\n", - "555600K .......... .......... .......... .......... .......... 93% 35.3M 1s\n", - "555650K .......... .......... .......... .......... .......... 93% 30.9M 1s\n", - "555700K .......... .......... .......... .......... .......... 93% 31.4M 1s\n", - "555750K .......... .......... .......... .......... .......... 93% 29.6M 1s\n", - "555800K .......... .......... .......... .......... .......... 93% 17.7M 1s\n", - "555850K .......... .......... .......... .......... .......... 93% 32.0M 1s\n", - "555900K .......... .......... .......... .......... .......... 93% 38.7M 1s\n", - "555950K .......... .......... .......... .......... .......... 93% 40.7M 1s\n", - "556000K .......... .......... .......... .......... .......... 93% 48.4M 1s\n", - "556050K .......... .......... .......... .......... .......... 93% 40.6M 1s\n", - "556100K .......... .......... .......... .......... .......... 93% 56.0M 1s\n", - "556150K .......... .......... .......... .......... .......... 93% 30.3M 1s\n", - "556200K .......... .......... .......... .......... .......... 93% 48.0M 1s\n", - "556250K .......... .......... .......... .......... .......... 93% 59.6M 1s\n", - "556300K .......... .......... .......... .......... .......... 93% 43.1M 1s\n", - "556350K .......... .......... .......... .......... .......... 93% 59.8M 1s\n", - "556400K .......... .......... .......... .......... .......... 93% 37.5M 1s\n", - "556450K .......... .......... .......... .......... .......... 93% 65.7M 1s\n", - "556500K .......... .......... .......... .......... .......... 93% 53.1M 1s\n", - "556550K .......... .......... .......... .......... .......... 93% 57.3M 1s\n", - "556600K .......... .......... .......... .......... .......... 93% 38.2M 1s\n", - "556650K .......... .......... .......... .......... .......... 93% 50.7M 1s\n", - "556700K .......... .......... .......... .......... .......... 93% 49.2M 1s\n", - "556750K .......... .......... .......... .......... .......... 93% 30.1M 1s\n", - "556800K .......... .......... .......... .......... .......... 93% 42.9M 1s\n", - "556850K .......... .......... .......... .......... .......... 93% 61.0M 1s\n", - "556900K .......... .......... .......... .......... .......... 93% 37.8M 1s\n", - "556950K .......... .......... .......... .......... .......... 93% 35.1M 1s\n", - "557000K .......... .......... .......... .......... .......... 93% 38.9M 1s\n", - "557050K .......... .......... .......... .......... .......... 93% 60.4M 1s\n", - "557100K .......... .......... .......... .......... .......... 93% 24.1M 1s\n", - "557150K .......... .......... .......... .......... .......... 93% 51.0M 1s\n", - "557200K .......... .......... .......... .......... .......... 93% 4.57M 1s\n", - "557250K .......... .......... .......... .......... .......... 93% 49.4M 1s\n", - "557300K .......... .......... .......... .......... .......... 93% 64.8M 1s\n", - "557350K .......... .......... .......... .......... .......... 93% 57.4M 1s\n", - "557400K .......... .......... .......... .......... .......... 93% 47.1M 1s\n", - "557450K .......... .......... .......... .......... .......... 93% 55.5M 1s\n", - "557500K .......... .......... .......... .......... .......... 93% 45.0M 1s\n", - "557550K .......... .......... .......... .......... .......... 93% 59.4M 1s\n", - "557600K .......... .......... .......... .......... .......... 93% 59.0M 1s\n", - "557650K .......... .......... .......... .......... .......... 93% 65.9M 1s\n", - "557700K .......... .......... .......... .......... .......... 93% 3.98M 1s\n", - "557750K .......... .......... .......... .......... .......... 93% 69.3M 1s\n", - "557800K .......... .......... .......... .......... .......... 93% 56.6M 1s\n", - "557850K .......... .......... .......... .......... .......... 93% 69.6M 1s\n", - "557900K .......... .......... .......... .......... .......... 93% 68.0M 1s\n", - "557950K .......... .......... .......... .......... .......... 93% 68.4M 1s\n", - "558000K .......... .......... .......... .......... .......... 93% 55.2M 1s\n", - "558050K .......... .......... .......... .......... .......... 93% 52.4M 1s\n", - "558100K .......... .......... .......... .......... .......... 93% 62.4M 1s\n", - "558150K .......... .......... .......... .......... .......... 93% 54.9M 1s\n", - "558200K .......... .......... .......... .......... .......... 93% 51.7M 1s\n", - "558250K .......... .......... .......... .......... .......... 93% 30.1M 1s\n", - "558300K .......... .......... .......... .......... .......... 93% 53.5M 1s\n", - "558350K .......... .......... .......... .......... .......... 93% 53.3M 1s\n", - "558400K .......... .......... .......... .......... .......... 93% 57.8M 1s\n", - "558450K .......... .......... .......... .......... .......... 93% 25.8M 1s\n", - "558500K .......... .......... .......... .......... .......... 93% 44.6M 1s\n", - "558550K .......... .......... .......... .......... .......... 93% 61.2M 1s\n", - "558600K .......... .......... .......... .......... .......... 93% 25.3M 1s\n", - "558650K .......... .......... .......... .......... .......... 93% 49.8M 1s\n", - "558700K .......... .......... .......... .......... .......... 93% 57.9M 1s\n", - "558750K .......... .......... .......... .......... .......... 93% 60.9M 1s\n", - "558800K .......... .......... .......... .......... .......... 93% 27.4M 1s\n", - "558850K .......... .......... .......... .......... .......... 93% 54.1M 1s\n", - "558900K .......... .......... .......... .......... .......... 93% 43.4M 1s\n", - "558950K .......... .......... .......... .......... .......... 93% 60.8M 1s\n", - "559000K .......... .......... .......... .......... .......... 94% 31.0M 1s\n", - "559050K .......... .......... .......... .......... .......... 94% 36.1M 1s\n", - "559100K .......... .......... .......... .......... .......... 94% 51.7M 1s\n", - "559150K .......... .......... .......... .......... .......... 94% 55.4M 1s\n", - "559200K .......... .......... .......... .......... .......... 94% 36.7M 1s\n", - "559250K .......... .......... .......... .......... .......... 94% 50.8M 1s\n", - "559300K .......... .......... .......... .......... .......... 94% 48.4M 1s\n", - "559350K .......... .......... .......... .......... .......... 94% 59.9M 1s\n", - "559400K .......... .......... .......... .......... .......... 94% 22.7M 1s\n", - "559450K .......... .......... .......... .......... .......... 94% 44.6M 1s\n", - "559500K .......... .......... .......... .......... .......... 94% 54.9M 1s\n", - "559550K .......... .......... .......... .......... .......... 94% 74.2M 1s\n", - "559600K .......... .......... .......... .......... .......... 94% 29.7M 1s\n", - "559650K .......... .......... .......... .......... .......... 94% 52.0M 1s\n", - "559700K .......... .......... .......... .......... .......... 94% 50.2M 1s\n", - "559750K .......... .......... .......... .......... .......... 94% 65.5M 1s\n", - "559800K .......... .......... .......... .......... .......... 94% 5.91M 1s\n", - "559850K .......... .......... .......... .......... .......... 94% 67.7M 1s\n", - "559900K .......... .......... .......... .......... .......... 94% 58.9M 1s\n", - "559950K .......... .......... .......... .......... .......... 94% 69.3M 1s\n", - "560000K .......... .......... .......... .......... .......... 94% 22.6M 1s\n", - "560050K .......... .......... .......... .......... .......... 94% 43.7M 1s\n", - "560100K .......... .......... .......... .......... .......... 94% 54.9M 1s\n", - "560150K .......... .......... .......... .......... .......... 94% 61.0M 1s\n", - "560200K .......... .......... .......... .......... .......... 94% 34.9M 1s\n", - "560250K .......... .......... .......... .......... .......... 94% 54.6M 1s\n", - "560300K .......... .......... .......... .......... .......... 94% 53.8M 1s\n", - "560350K .......... .......... .......... .......... .......... 94% 61.9M 1s\n", - "560400K .......... .......... .......... .......... .......... 94% 21.3M 1s\n", - "560450K .......... .......... .......... .......... .......... 94% 47.5M 1s\n", - "560500K .......... .......... .......... .......... .......... 94% 50.6M 1s\n", - "560550K .......... .......... .......... .......... .......... 94% 69.8M 1s\n", - "560600K .......... .......... .......... .......... .......... 94% 34.0M 1s\n", - "560650K .......... .......... .......... .......... .......... 94% 40.5M 1s\n", - "560700K .......... .......... .......... .......... .......... 94% 47.1M 1s\n", - "560750K .......... .......... .......... .......... .......... 94% 69.6M 1s\n", - "560800K .......... .......... .......... .......... .......... 94% 59.9M 1s\n", - "560850K .......... .......... .......... .......... .......... 94% 28.6M 1s\n", - "560900K .......... .......... .......... .......... .......... 94% 47.6M 1s\n", - "560950K .......... .......... .......... .......... .......... 94% 55.7M 1s\n", - "561000K .......... .......... .......... .......... .......... 94% 50.6M 1s\n", - "561050K .......... .......... .......... .......... .......... 94% 30.7M 1s\n", - "561100K .......... .......... .......... .......... .......... 94% 46.2M 1s\n", - "561150K .......... .......... .......... .......... .......... 94% 54.3M 1s\n", - "561200K .......... .......... .......... .......... .......... 94% 59.5M 1s\n", - "561250K .......... .......... .......... .......... .......... 94% 31.1M 1s\n", - "561300K .......... .......... .......... .......... .......... 94% 51.9M 1s\n", - "561350K .......... .......... .......... .......... .......... 94% 51.9M 1s\n", - "561400K .......... .......... .......... .......... .......... 94% 46.7M 1s\n", - "561450K .......... .......... .......... .......... .......... 94% 31.7M 1s\n", - "561500K .......... .......... .......... .......... .......... 94% 53.2M 1s\n", - "561550K .......... .......... .......... .......... .......... 94% 47.3M 1s\n", - "561600K .......... .......... .......... .......... .......... 94% 47.2M 1s\n", - "561650K .......... .......... .......... .......... .......... 94% 36.0M 1s\n", - "561700K .......... .......... .......... .......... .......... 94% 54.7M 1s\n", - "561750K .......... .......... .......... .......... .......... 94% 48.0M 1s\n", - "561800K .......... .......... .......... .......... .......... 94% 46.0M 1s\n", - "561850K .......... .......... .......... .......... .......... 94% 33.7M 1s\n", - "561900K .......... .......... .......... .......... .......... 94% 46.0M 1s\n", - "561950K .......... .......... .......... .......... .......... 94% 46.5M 1s\n", - "562000K .......... .......... .......... .......... .......... 94% 46.7M 1s\n", - "562050K .......... .......... .......... .......... .......... 94% 67.9M 1s\n", - "562100K .......... .......... .......... .......... .......... 94% 38.3M 1s\n", - "562150K .......... .......... .......... .......... .......... 94% 38.9M 1s\n", - "562200K .......... .......... .......... .......... .......... 94% 48.3M 1s\n", - "562250K .......... .......... .......... .......... .......... 94% 64.6M 1s\n", - "562300K .......... .......... .......... .......... .......... 94% 38.3M 1s\n", - "562350K .......... .......... .......... .......... .......... 94% 8.87M 1s\n", - "562400K .......... .......... .......... .......... .......... 94% 57.3M 1s\n", - "562450K .......... .......... .......... .......... .......... 94% 67.0M 1s\n", - "562500K .......... .......... .......... .......... .......... 94% 59.6M 1s\n", - "562550K .......... .......... .......... .......... .......... 94% 38.4M 1s\n", - "562600K .......... .......... .......... .......... .......... 94% 52.8M 1s\n", - "562650K .......... .......... .......... .......... .......... 94% 6.01M 1s\n", - "562700K .......... .......... .......... .......... .......... 94% 37.5M 1s\n", - "562750K .......... .......... .......... .......... .......... 94% 53.5M 1s\n", - "562800K .......... .......... .......... .......... .......... 94% 22.7M 1s\n", - "562850K .......... .......... .......... .......... .......... 94% 49.0M 1s\n", - "562900K .......... .......... .......... .......... .......... 94% 65.0M 1s\n", - "562950K .......... .......... .......... .......... .......... 94% 17.3M 1s\n", - "563000K .......... .......... .......... .......... .......... 94% 41.0M 1s\n", - "563050K .......... .......... .......... .......... .......... 94% 64.2M 1s\n", - "563100K .......... .......... .......... .......... .......... 94% 20.1M 1s\n", - "563150K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", - "563200K .......... .......... .......... .......... .......... 94% 55.8M 1s\n", - "563250K .......... .......... .......... .......... .......... 94% 17.0M 1s\n", - "563300K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", - "563350K .......... .......... .......... .......... .......... 94% 60.3M 1s\n", - "563400K .......... .......... .......... .......... .......... 94% 16.3M 1s\n", - "563450K .......... .......... .......... .......... .......... 94% 49.7M 1s\n", - "563500K .......... .......... .......... .......... .......... 94% 62.0M 1s\n", - "563550K .......... .......... .......... .......... .......... 94% 19.9M 1s\n", - "563600K .......... .......... .......... .......... .......... 94% 51.1M 1s\n", - "563650K .......... .......... .......... .......... .......... 94% 62.5M 1s\n", - "563700K .......... .......... .......... .......... .......... 94% 17.3M 1s\n", - "563750K .......... .......... .......... .......... .......... 94% 54.0M 1s\n", - "563800K .......... .......... .......... .......... .......... 94% 50.7M 1s\n", - "563850K .......... .......... .......... .......... .......... 94% 18.9M 1s\n", - "563900K .......... .......... .......... .......... .......... 94% 55.9M 1s\n", - "563950K .......... .......... .......... .......... .......... 94% 55.5M 1s\n", - "564000K .......... .......... .......... .......... .......... 94% 15.8M 1s\n", - "564050K .......... .......... .......... .......... .......... 94% 46.3M 1s\n", - "564100K .......... .......... .......... .......... .......... 94% 52.9M 1s\n", - "564150K .......... .......... .......... .......... .......... 94% 70.0M 1s\n", - "564200K .......... .......... .......... .......... .......... 94% 19.5M 1s\n", - "564250K .......... .......... .......... .......... .......... 94% 56.2M 1s\n", - "564300K .......... .......... .......... .......... .......... 94% 70.0M 1s\n", - "564350K .......... .......... .......... .......... .......... 94% 17.6M 1s\n", - "564400K .......... .......... .......... .......... .......... 94% 46.8M 1s\n", - "564450K .......... .......... .......... .......... .......... 94% 65.8M 1s\n", - "564500K .......... .......... .......... .......... .......... 94% 19.0M 1s\n", - "564550K .......... .......... .......... .......... .......... 94% 5.59M 1s\n", - "564600K .......... .......... .......... .......... .......... 94% 53.7M 1s\n", - "564650K .......... .......... .......... .......... .......... 94% 65.1M 1s\n", - "564700K .......... .......... .......... .......... .......... 94% 63.0M 1s\n", - "564750K .......... .......... .......... .......... .......... 94% 20.0M 1s\n", - "564800K .......... .......... .......... .......... .......... 94% 53.8M 1s\n", - "564850K .......... .......... .......... .......... .......... 94% 66.0M 1s\n", - "564900K .......... .......... .......... .......... .......... 94% 18.5M 1s\n", - "564950K .......... .......... .......... .......... .......... 95% 48.7M 1s\n", - "565000K .......... .......... .......... .......... .......... 95% 16.4M 1s\n", - "565050K .......... .......... .......... .......... .......... 95% 59.8M 1s\n", - "565100K .......... .......... .......... .......... .......... 95% 49.3M 1s\n", - "565150K .......... .......... .......... .......... .......... 95% 65.3M 1s\n", - "565200K .......... .......... .......... .......... .......... 95% 23.9M 1s\n", - "565250K .......... .......... .......... .......... .......... 95% 60.2M 1s\n", - "565300K .......... .......... .......... .......... .......... 95% 50.1M 1s\n", - "565350K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", - "565400K .......... .......... .......... .......... .......... 95% 17.9M 1s\n", - "565450K .......... .......... .......... .......... .......... 95% 51.7M 1s\n", - "565500K .......... .......... .......... .......... .......... 95% 56.3M 1s\n", - "565550K .......... .......... .......... .......... .......... 95% 3.78M 1s\n", - "565600K .......... .......... .......... .......... .......... 95% 40.2M 1s\n", - "565650K .......... .......... .......... .......... .......... 95% 54.5M 1s\n", - "565700K .......... .......... .......... .......... .......... 95% 65.5M 1s\n", - "565750K .......... .......... .......... .......... .......... 95% 20.0M 1s\n", - "565800K .......... .......... .......... .......... .......... 95% 45.5M 1s\n", - "565850K .......... .......... .......... .......... .......... 95% 69.1M 1s\n", - "565900K .......... .......... .......... .......... .......... 95% 19.1M 1s\n", - "565950K .......... .......... .......... .......... .......... 95% 33.3M 1s\n", - "566000K .......... .......... .......... .......... .......... 95% 41.5M 1s\n", - "566050K .......... .......... .......... .......... .......... 95% 52.1M 1s\n", - "566100K .......... .......... .......... .......... .......... 95% 36.1M 1s\n", - "566150K .......... .......... .......... .......... .......... 95% 39.6M 1s\n", - "566200K .......... .......... .......... .......... .......... 95% 55.6M 1s\n", - "566250K .......... .......... .......... .......... .......... 95% 18.8M 1s\n", - "566300K .......... .......... .......... .......... .......... 95% 33.6M 1s\n", - "566350K .......... .......... .......... .......... .......... 95% 74.4M 1s\n", - "566400K .......... .......... .......... .......... .......... 95% 5.03M 1s\n", - "566450K .......... .......... .......... .......... .......... 95% 64.6M 1s\n", - "566500K .......... .......... .......... .......... .......... 95% 67.5M 1s\n", - "566550K .......... .......... .......... .......... .......... 95% 67.6M 1s\n", - "566600K .......... .......... .......... .......... .......... 95% 7.14M 1s\n", - "566650K .......... .......... .......... .......... .......... 95% 70.1M 1s\n", - "566700K .......... .......... .......... .......... .......... 95% 70.4M 1s\n", - "566750K .......... .......... .......... .......... .......... 95% 14.9M 1s\n", - "566800K .......... .......... .......... .......... .......... 95% 7.50M 1s\n", - "566850K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", - "566900K .......... .......... .......... .......... .......... 95% 59.2M 1s\n", - "566950K .......... .......... .......... .......... .......... 95% 69.6M 1s\n", - "567000K .......... .......... .......... .......... .......... 95% 18.1M 1s\n", - "567050K .......... .......... .......... .......... .......... 95% 4.20M 1s\n", - "567100K .......... .......... .......... .......... .......... 95% 56.4M 1s\n", - "567150K .......... .......... .......... .......... .......... 95% 65.9M 1s\n", - "567200K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", - "567250K .......... .......... .......... .......... .......... 95% 16.6M 1s\n", - "567300K .......... .......... .......... .......... .......... 95% 69.6M 1s\n", - "567350K .......... .......... .......... .......... .......... 95% 14.5M 1s\n", - "567400K .......... .......... .......... .......... .......... 95% 35.1M 1s\n", - "567450K .......... .......... .......... .......... .......... 95% 17.0M 1s\n", - "567500K .......... .......... .......... .......... .......... 95% 52.9M 1s\n", - "567550K .......... .......... .......... .......... .......... 95% 66.8M 1s\n", - "567600K .......... .......... .......... .......... .......... 95% 15.2M 1s\n", - "567650K .......... .......... .......... .......... .......... 95% 51.1M 1s\n", - "567700K .......... .......... .......... .......... .......... 95% 15.3M 1s\n", - "567750K .......... .......... .......... .......... .......... 95% 53.5M 1s\n", - "567800K .......... .......... .......... .......... .......... 95% 14.1M 1s\n", - "567850K .......... .......... .......... .......... .......... 95% 45.0M 1s\n", - "567900K .......... .......... .......... .......... .......... 95% 54.2M 1s\n", - "567950K .......... .......... .......... .......... .......... 95% 17.5M 1s\n", - "568000K .......... .......... .......... .......... .......... 95% 38.7M 1s\n", - "568050K .......... .......... .......... .......... .......... 95% 62.3M 1s\n", - "568100K .......... .......... .......... .......... .......... 95% 14.1M 1s\n", - "568150K .......... .......... .......... .......... .......... 95% 53.0M 1s\n", - "568200K .......... .......... .......... .......... .......... 95% 16.6M 1s\n", - "568250K .......... .......... .......... .......... .......... 95% 32.4M 1s\n", - "568300K .......... .......... .......... .......... .......... 95% 21.0M 1s\n", - "568350K .......... .......... .......... .......... .......... 95% 34.5M 1s\n", - "568400K .......... .......... .......... .......... .......... 95% 5.57M 1s\n", - "568450K .......... .......... .......... .......... .......... 95% 64.3M 1s\n", - "568500K .......... .......... .......... .......... .......... 95% 57.7M 1s\n", - "568550K .......... .......... .......... .......... .......... 95% 15.4M 1s\n", - "568600K .......... .......... .......... .......... .......... 95% 43.9M 1s\n", - "568650K .......... .......... .......... .......... .......... 95% 14.8M 1s\n", - "568700K .......... .......... .......... .......... .......... 95% 44.9M 1s\n", - "568750K .......... .......... .......... .......... .......... 95% 67.5M 1s\n", - "568800K .......... .......... .......... .......... .......... 95% 16.0M 1s\n", - "568850K .......... .......... .......... .......... .......... 95% 51.8M 1s\n", - "568900K .......... .......... .......... .......... .......... 95% 60.4M 1s\n", - "568950K .......... .......... .......... .......... .......... 95% 9.41M 1s\n", - "569000K .......... .......... .......... .......... .......... 95% 56.7M 1s\n", - "569050K .......... .......... .......... .......... .......... 95% 13.2M 1s\n", - "569100K .......... .......... .......... .......... .......... 95% 56.0M 1s\n", - "569150K .......... .......... .......... .......... .......... 95% 67.3M 1s\n", - "569200K .......... .......... .......... .......... .......... 95% 12.4M 1s\n", - "569250K .......... .......... .......... .......... .......... 95% 61.0M 1s\n", - "569300K .......... .......... .......... .......... .......... 95% 16.4M 1s\n", - "569350K .......... .......... .......... .......... .......... 95% 58.7M 1s\n", - "569400K .......... .......... .......... .......... .......... 95% 15.3M 1s\n", - "569450K .......... .......... .......... .......... .......... 95% 41.6M 1s\n", - "569500K .......... .......... .......... .......... .......... 95% 60.9M 1s\n", - "569550K .......... .......... .......... .......... .......... 95% 15.1M 1s\n", - "569600K .......... .......... .......... .......... .......... 95% 44.4M 1s\n", - "569650K .......... .......... .......... .......... .......... 95% 16.9M 1s\n", - "569700K .......... .......... .......... .......... .......... 95% 48.2M 1s\n", - "569750K .......... .......... .......... .......... .......... 95% 46.8M 1s\n", - "569800K .......... .......... .......... .......... .......... 95% 15.2M 1s\n", - "569850K .......... .......... .......... .......... .......... 95% 58.7M 1s\n", - "569900K .......... .......... .......... .......... .......... 95% 18.0M 1s\n", - "569950K .......... .......... .......... .......... .......... 95% 34.3M 1s\n", - "570000K .......... .......... .......... .......... .......... 95% 49.8M 1s\n", - "570050K .......... .......... .......... .......... .......... 95% 19.7M 1s\n", - "570100K .......... .......... .......... .......... .......... 95% 35.4M 1s\n", - "570150K .......... .......... .......... .......... .......... 95% 59.6M 1s\n", - "570200K .......... .......... .......... .......... .......... 95% 15.5M 1s\n", - "570250K .......... .......... .......... .......... .......... 95% 61.8M 1s\n", - "570300K .......... .......... .......... .......... .......... 95% 17.4M 1s\n", - "570350K .......... .......... .......... .......... .......... 95% 35.8M 1s\n", - "570400K .......... .......... .......... .......... .......... 95% 39.2M 1s\n", - "570450K .......... .......... .......... .......... .......... 95% 17.5M 1s\n", - "570500K .......... .......... .......... .......... .......... 95% 38.5M 1s\n", - "570550K .......... .......... .......... .......... .......... 95% 20.9M 1s\n", - "570600K .......... .......... .......... .......... .......... 95% 32.2M 1s\n", - "570650K .......... .......... .......... .......... .......... 95% 44.7M 1s\n", - "570700K .......... .......... .......... .......... .......... 95% 17.2M 1s\n", - "570750K .......... .......... .......... .......... .......... 95% 46.1M 1s\n", - "570800K .......... .......... .......... .......... .......... 95% 51.8M 1s\n", - "570850K .......... .......... .......... .......... .......... 95% 17.2M 1s\n", - "570900K .......... .......... .......... .......... .......... 96% 50.8M 1s\n", - "570950K .......... .......... .......... .......... .......... 96% 20.1M 1s\n", - "571000K .......... .......... .......... .......... .......... 96% 26.1M 1s\n", - "571050K .......... .......... .......... .......... .......... 96% 67.9M 1s\n", - "571100K .......... .......... .......... .......... .......... 96% 19.6M 1s\n", - "571150K .......... .......... .......... .......... .......... 96% 36.6M 1s\n", - "571200K .......... .......... .......... .......... .......... 96% 61.8M 1s\n", - "571250K .......... .......... .......... .......... .......... 96% 18.2M 1s\n", - "571300K .......... .......... .......... .......... .......... 96% 38.0M 1s\n", - "571350K .......... .......... .......... .......... .......... 96% 18.5M 1s\n", - "571400K .......... .......... .......... .......... .......... 96% 5.70M 1s\n", - "571450K .......... .......... .......... .......... .......... 96% 70.3M 1s\n", - "571500K .......... .......... .......... .......... .......... 96% 73.3M 1s\n", - "571550K .......... .......... .......... .......... .......... 96% 12.2M 1s\n", - "571600K .......... .......... .......... .......... .......... 96% 60.8M 1s\n", - "571650K .......... .......... .......... .......... .......... 96% 70.9M 1s\n", - "571700K .......... .......... .......... .......... .......... 96% 15.4M 1s\n", - "571750K .......... .......... .......... .......... .......... 96% 67.0M 1s\n", - "571800K .......... .......... .......... .......... .......... 96% 16.1M 1s\n", - "571850K .......... .......... .......... .......... .......... 96% 45.8M 1s\n", - "571900K .......... .......... .......... .......... .......... 96% 74.3M 1s\n", - "571950K .......... .......... .......... .......... .......... 96% 15.6M 1s\n", - "572000K .......... .......... .......... .......... .......... 96% 42.0M 1s\n", - "572050K .......... .......... .......... .......... .......... 96% 72.8M 1s\n", - "572100K .......... .......... .......... .......... .......... 96% 18.4M 1s\n", - "572150K .......... .......... .......... .......... .......... 96% 45.0M 1s\n", - "572200K .......... .......... .......... .......... .......... 96% 22.5M 1s\n", - "572250K .......... .......... .......... .......... .......... 96% 31.6M 1s\n", - "572300K .......... .......... .......... .......... .......... 96% 53.0M 1s\n", - "572350K .......... .......... .......... .......... .......... 96% 25.0M 1s\n", - "572400K .......... .......... .......... .......... .......... 96% 34.8M 1s\n", - "572450K .......... .......... .......... .......... .......... 96% 38.2M 1s\n", - "572500K .......... .......... .......... .......... .......... 96% 9.73M 1s\n", - "572550K .......... .......... .......... .......... .......... 96% 69.5M 1s\n", - "572600K .......... .......... .......... .......... .......... 96% 60.1M 1s\n", - "572650K .......... .......... .......... .......... .......... 96% 18.0M 1s\n", - "572700K .......... .......... .......... .......... .......... 96% 41.4M 1s\n", - "572750K .......... .......... .......... .......... .......... 96% 64.2M 1s\n", - "572800K .......... .......... .......... .......... .......... 96% 19.0M 1s\n", - "572850K .......... .......... .......... .......... .......... 96% 33.4M 1s\n", - "572900K .......... .......... .......... .......... .......... 96% 71.0M 1s\n", - "572950K .......... .......... .......... .......... .......... 96% 22.3M 1s\n", - "573000K .......... .......... .......... .......... .......... 96% 31.5M 1s\n", - "573050K .......... .......... .......... .......... .......... 96% 55.6M 1s\n", - "573100K .......... .......... .......... .......... .......... 96% 21.5M 1s\n", - "573150K .......... .......... .......... .......... .......... 96% 41.0M 1s\n", - "573200K .......... .......... .......... .......... .......... 96% 48.2M 1s\n", - "573250K .......... .......... .......... .......... .......... 96% 11.6M 1s\n", - "573300K .......... .......... .......... .......... .......... 96% 59.6M 1s\n", + "552150K .......... .......... .......... .......... .......... 92% 69.3M 1s\n", + "552200K .......... .......... .......... .......... .......... 92% 55.9M 1s\n", + "552250K .......... .......... .......... .......... .......... 92% 68.5M 1s\n", + "552300K .......... .......... .......... .......... .......... 92% 72.4M 1s\n", + "552350K .......... .......... .......... .......... .......... 92% 69.4M 1s\n", + "552400K .......... .......... .......... .......... .......... 92% 59.1M 1s\n", + "552450K .......... .......... .......... .......... .......... 92% 52.5M 1s\n", + "552500K .......... .......... .......... .......... .......... 92% 47.0M 1s\n", + "552550K .......... .......... .......... .......... .......... 92% 52.6M 1s\n", + "552600K .......... .......... .......... .......... .......... 92% 67.3M 1s\n", + "552650K .......... .......... .......... .......... .......... 92% 58.6M 1s\n", + "552700K .......... .......... .......... .......... .......... 92% 63.1M 1s\n", + "552750K .......... .......... .......... .......... .......... 92% 46.5M 1s\n", + "552800K .......... .......... .......... .......... .......... 92% 45.9M 1s\n", + "552850K .......... .......... .......... .......... .......... 92% 60.8M 1s\n", + "552900K .......... .......... .......... .......... .......... 92% 59.7M 1s\n", + "552950K .......... .......... .......... .......... .......... 92% 65.0M 1s\n", + "553000K .......... .......... .......... .......... .......... 92% 56.1M 1s\n", + "553050K .......... .......... .......... .......... .......... 93% 52.3M 1s\n", + "553100K .......... .......... .......... .......... .......... 93% 54.4M 1s\n", + "553150K .......... .......... .......... .......... .......... 93% 58.0M 1s\n", + "553200K .......... .......... .......... .......... .......... 93% 63.7M 1s\n", + "553250K .......... .......... .......... .......... .......... 93% 58.6M 1s\n", + "553300K .......... .......... .......... .......... .......... 93% 62.1M 1s\n", + "553350K .......... .......... .......... .......... .......... 93% 52.9M 1s\n", + "553400K .......... .......... .......... .......... .......... 93% 48.3M 1s\n", + "553450K .......... .......... .......... .......... .......... 93% 64.9M 1s\n", + "553500K .......... .......... .......... .......... .......... 93% 60.8M 1s\n", + "553550K .......... .......... .......... .......... .......... 93% 63.8M 1s\n", + "553600K .......... .......... .......... .......... .......... 93% 48.6M 1s\n", + "553650K .......... .......... .......... .......... .......... 93% 52.5M 1s\n", + "553700K .......... .......... .......... .......... .......... 93% 58.3M 1s\n", + "553750K .......... .......... .......... .......... .......... 93% 63.6M 1s\n", + "553800K .......... .......... .......... .......... .......... 93% 46.9M 1s\n", + "553850K .......... .......... .......... .......... .......... 93% 53.4M 1s\n", + "553900K .......... .......... .......... .......... .......... 93% 57.3M 1s\n", + "553950K .......... .......... .......... .......... .......... 93% 57.0M 1s\n", + "554000K .......... .......... .......... .......... .......... 93% 47.5M 1s\n", + "554050K .......... .......... .......... .......... .......... 93% 51.3M 1s\n", + "554100K .......... .......... .......... .......... .......... 93% 48.0M 1s\n", + "554150K .......... .......... .......... .......... .......... 93% 54.0M 1s\n", + "554200K .......... .......... .......... .......... .......... 93% 47.1M 1s\n", + "554250K .......... .......... .......... .......... .......... 93% 53.6M 1s\n", + "554300K .......... .......... .......... .......... .......... 93% 57.0M 1s\n", + "554350K .......... .......... .......... .......... .......... 93% 48.3M 1s\n", + "554400K .......... .......... .......... .......... .......... 93% 49.0M 1s\n", + "554450K .......... .......... .......... .......... .......... 93% 66.5M 1s\n", + "554500K .......... .......... .......... .......... .......... 93% 53.4M 1s\n", + "554550K .......... .......... .......... .......... .......... 93% 61.0M 1s\n", + "554600K .......... .......... .......... .......... .......... 93% 50.9M 1s\n", + "554650K .......... .......... .......... .......... .......... 93% 56.4M 1s\n", + "554700K .......... .......... .......... .......... .......... 93% 64.8M 1s\n", + "554750K .......... .......... .......... .......... .......... 93% 50.4M 1s\n", + "554800K .......... .......... .......... .......... .......... 93% 51.4M 1s\n", + "554850K .......... .......... .......... .......... .......... 93% 54.7M 1s\n", + "554900K .......... .......... .......... .......... .......... 93% 58.6M 1s\n", + "554950K .......... .......... .......... .......... .......... 93% 56.7M 1s\n", + "555000K .......... .......... .......... .......... .......... 93% 49.0M 1s\n", + "555050K .......... .......... .......... .......... .......... 93% 55.4M 1s\n", + "555100K .......... .......... .......... .......... .......... 93% 64.3M 1s\n", + "555150K .......... .......... .......... .......... .......... 93% 58.0M 1s\n", + "555200K .......... .......... .......... .......... .......... 93% 49.6M 1s\n", + "555250K .......... .......... .......... .......... .......... 93% 61.7M 1s\n", + "555300K .......... .......... .......... .......... .......... 93% 63.8M 1s\n", + "555350K .......... .......... .......... .......... .......... 93% 58.6M 1s\n", + "555400K .......... .......... .......... .......... .......... 93% 47.3M 1s\n", + "555450K .......... .......... .......... .......... .......... 93% 60.1M 1s\n", + "555500K .......... .......... .......... .......... .......... 93% 52.6M 1s\n", + "555550K .......... .......... .......... .......... .......... 93% 68.8M 1s\n", + "555600K .......... .......... .......... .......... .......... 93% 57.0M 1s\n", + "555650K .......... .......... .......... .......... .......... 93% 51.6M 1s\n", + "555700K .......... .......... .......... .......... .......... 93% 67.1M 1s\n", + "555750K .......... .......... .......... .......... .......... 93% 60.8M 1s\n", + "555800K .......... .......... .......... .......... .......... 93% 57.8M 1s\n", + "555850K .......... .......... .......... .......... .......... 93% 53.5M 1s\n", + "555900K .......... .......... .......... .......... .......... 93% 60.3M 1s\n", + "555950K .......... .......... .......... .......... .......... 93% 61.7M 1s\n", + "556000K .......... .......... .......... .......... .......... 93% 54.5M 1s\n", + "556050K .......... .......... .......... .......... .......... 93% 56.5M 1s\n", + "556100K .......... .......... .......... .......... .......... 93% 56.7M 1s\n", + "556150K .......... .......... .......... .......... .......... 93% 53.1M 1s\n", + "556200K .......... .......... .......... .......... .......... 93% 51.3M 1s\n", + "556250K .......... .......... .......... .......... .......... 93% 48.6M 1s\n", + "556300K .......... .......... .......... .......... .......... 93% 67.6M 1s\n", + "556350K .......... .......... .......... .......... .......... 93% 47.9M 1s\n", + "556400K .......... .......... .......... .......... .......... 93% 43.0M 1s\n", + "556450K .......... .......... .......... .......... .......... 93% 71.4M 1s\n", + "556500K .......... .......... .......... .......... .......... 93% 52.8M 1s\n", + "556550K .......... .......... .......... .......... .......... 93% 59.8M 1s\n", + "556600K .......... .......... .......... .......... .......... 93% 44.6M 1s\n", + "556650K .......... .......... .......... .......... .......... 93% 54.9M 1s\n", + "556700K .......... .......... .......... .......... .......... 93% 54.1M 1s\n", + "556750K .......... .......... .......... .......... .......... 93% 55.3M 1s\n", + "556800K .......... .......... .......... .......... .......... 93% 53.8M 1s\n", + "556850K .......... .......... .......... .......... .......... 93% 67.0M 1s\n", + "556900K .......... .......... .......... .......... .......... 93% 70.5M 1s\n", + "556950K .......... .......... .......... .......... .......... 93% 68.6M 1s\n", + "557000K .......... .......... .......... .......... .......... 93% 58.1M 1s\n", + "557050K .......... .......... .......... .......... .......... 93% 74.4M 1s\n", + "557100K .......... .......... .......... .......... .......... 93% 70.2M 1s\n", + "557150K .......... .......... .......... .......... .......... 93% 64.2M 1s\n", + "557200K .......... .......... .......... .......... .......... 93% 54.3M 1s\n", + "557250K .......... .......... .......... .......... .......... 93% 75.3M 1s\n", + "557300K .......... .......... .......... .......... .......... 93% 71.0M 1s\n", + "557350K .......... .......... .......... .......... .......... 93% 68.7M 1s\n", + "557400K .......... .......... .......... .......... .......... 93% 64.3M 1s\n", + "557450K .......... .......... .......... .......... .......... 93% 73.4M 1s\n", + "557500K .......... .......... .......... .......... .......... 93% 59.6M 1s\n", + "557550K .......... .......... .......... .......... .......... 93% 54.7M 1s\n", + "557600K .......... .......... .......... .......... .......... 93% 67.5M 1s\n", + "557650K .......... .......... .......... .......... .......... 93% 73.0M 1s\n", + "557700K .......... .......... .......... .......... .......... 93% 65.8M 1s\n", + "557750K .......... .......... .......... .......... .......... 93% 64.8M 1s\n", + "557800K .......... .......... .......... .......... .......... 93% 61.1M 1s\n", + "557850K .......... .......... .......... .......... .......... 93% 73.8M 1s\n", + "557900K .......... .......... .......... .......... .......... 93% 74.0M 1s\n", + "557950K .......... .......... .......... .......... .......... 93% 75.1M 1s\n", + "558000K .......... .......... .......... .......... .......... 93% 67.0M 1s\n", + "558050K .......... .......... .......... .......... .......... 93% 64.9M 1s\n", + "558100K .......... .......... .......... .......... .......... 93% 68.7M 1s\n", + "558150K .......... .......... .......... .......... .......... 93% 81.4M 1s\n", + "558200K .......... .......... .......... .......... .......... 93% 62.6M 1s\n", + "558250K .......... .......... .......... .......... .......... 93% 64.3M 1s\n", + "558300K .......... .......... .......... .......... .......... 93% 67.1M 1s\n", + "558350K .......... .......... .......... .......... .......... 93% 71.7M 1s\n", + "558400K .......... .......... .......... .......... .......... 93% 61.2M 1s\n", + "558450K .......... .......... .......... .......... .......... 93% 68.2M 1s\n", + "558500K .......... .......... .......... .......... .......... 93% 73.2M 1s\n", + "558550K .......... .......... .......... .......... .......... 93% 62.5M 1s\n", + "558600K .......... .......... .......... .......... .......... 93% 56.1M 1s\n", + "558650K .......... .......... .......... .......... .......... 93% 72.6M 1s\n", + "558700K .......... .......... .......... .......... .......... 93% 4.45M 1s\n", + "558750K .......... .......... .......... .......... .......... 93% 483K 1s\n", + "558800K .......... .......... .......... .......... .......... 93% 50.4M 1s\n", + "558850K .......... .......... .......... .......... .......... 93% 82.4M 1s\n", + "558900K .......... .......... .......... .......... .......... 93% 11.7M 1s\n", + "558950K .......... .......... .......... .......... .......... 93% 75.8M 1s\n", + "559000K .......... .......... .......... .......... .......... 94% 66.8M 1s\n", + "559050K .......... .......... .......... .......... .......... 94% 31.6M 1s\n", + "559100K .......... .......... .......... .......... .......... 94% 47.9M 1s\n", + "559150K .......... .......... .......... .......... .......... 94% 55.8M 1s\n", + "559200K .......... .......... .......... .......... .......... 94% 77.0M 1s\n", + "559250K .......... .......... .......... .......... .......... 94% 80.7M 1s\n", + "559300K .......... .......... .......... .......... .......... 94% 24.9M 1s\n", + "559350K .......... .......... .......... .......... .......... 94% 51.2M 1s\n", + "559400K .......... .......... .......... .......... .......... 94% 4.71M 1s\n", + "559450K .......... .......... .......... .......... .......... 94% 72.2M 1s\n", + "559500K .......... .......... .......... .......... .......... 94% 76.6M 1s\n", + "559550K .......... .......... .......... .......... .......... 94% 67.6M 1s\n", + "559600K .......... .......... .......... .......... .......... 94% 69.2M 1s\n", + "559650K .......... .......... .......... .......... .......... 94% 30.4M 1s\n", + "559700K .......... .......... .......... .......... .......... 94% 2.59M 1s\n", + "559750K .......... .......... .......... .......... .......... 94% 47.9M 1s\n", + "559800K .......... .......... .......... .......... .......... 94% 60.4M 1s\n", + "559850K .......... .......... .......... .......... .......... 94% 75.8M 1s\n", + "559900K .......... .......... .......... .......... .......... 94% 70.8M 1s\n", + "559950K .......... .......... .......... .......... .......... 94% 75.4M 1s\n", + "560000K .......... .......... .......... .......... .......... 94% 35.0M 1s\n", + "560050K .......... .......... .......... .......... .......... 94% 39.3M 1s\n", + "560100K .......... .......... .......... .......... .......... 94% 74.9M 1s\n", + "560150K .......... .......... .......... .......... .......... 94% 54.9M 1s\n", + "560200K .......... .......... .......... .......... .......... 94% 51.4M 1s\n", + "560250K .......... .......... .......... .......... .......... 94% 35.7M 1s\n", + "560300K .......... .......... .......... .......... .......... 94% 50.7M 1s\n", + "560350K .......... .......... .......... .......... .......... 94% 79.5M 1s\n", + "560400K .......... .......... .......... .......... .......... 94% 56.7M 1s\n", + "560450K .......... .......... .......... .......... .......... 94% 61.6M 1s\n", + "560500K .......... .......... .......... .......... .......... 94% 34.8M 1s\n", + "560550K .......... .......... .......... .......... .......... 94% 46.6M 1s\n", + "560600K .......... .......... .......... .......... .......... 94% 56.4M 1s\n", + "560650K .......... .......... .......... .......... .......... 94% 59.4M 1s\n", + "560700K .......... .......... .......... .......... .......... 94% 46.7M 1s\n", + "560750K .......... .......... .......... .......... .......... 94% 43.4M 1s\n", + "560800K .......... .......... .......... .......... .......... 94% 40.6M 1s\n", + "560850K .......... .......... .......... .......... .......... 94% 72.4M 1s\n", + "560900K .......... .......... .......... .......... .......... 94% 40.3M 1s\n", + "560950K .......... .......... .......... .......... .......... 94% 44.7M 1s\n", + "561000K .......... .......... .......... .......... .......... 94% 31.7M 1s\n", + "561050K .......... .......... .......... .......... .......... 94% 70.2M 1s\n", + "561100K .......... .......... .......... .......... .......... 94% 39.3M 1s\n", + "561150K .......... .......... .......... .......... .......... 94% 40.0M 1s\n", + "561200K .......... .......... .......... .......... .......... 94% 42.4M 1s\n", + "561250K .......... .......... .......... .......... .......... 94% 66.5M 1s\n", + "561300K .......... .......... .......... .......... .......... 94% 42.9M 1s\n", + "561350K .......... .......... .......... .......... .......... 94% 37.7M 1s\n", + "561400K .......... .......... .......... .......... .......... 94% 32.9M 1s\n", + "561450K .......... .......... .......... .......... .......... 94% 53.0M 1s\n", + "561500K .......... .......... .......... .......... .......... 94% 48.2M 1s\n", + "561550K .......... .......... .......... .......... .......... 94% 44.3M 1s\n", + "561600K .......... .......... .......... .......... .......... 94% 47.0M 1s\n", + "561650K .......... .......... .......... .......... .......... 94% 40.8M 1s\n", + "561700K .......... .......... .......... .......... .......... 94% 47.2M 1s\n", + "561750K .......... .......... .......... .......... .......... 94% 35.4M 1s\n", + "561800K .......... .......... .......... .......... .......... 94% 4.68M 1s\n", + "561850K .......... .......... .......... .......... .......... 94% 67.1M 1s\n", + "561900K .......... .......... .......... .......... .......... 94% 84.1M 1s\n", + "561950K .......... .......... .......... .......... .......... 94% 67.9M 1s\n", + "562000K .......... .......... .......... .......... .......... 94% 56.4M 1s\n", + "562050K .......... .......... .......... .......... .......... 94% 34.6M 1s\n", + "562100K .......... .......... .......... .......... .......... 94% 32.6M 1s\n", + "562150K .......... .......... .......... .......... .......... 94% 67.6M 1s\n", + "562200K .......... .......... .......... .......... .......... 94% 59.2M 1s\n", + "562250K .......... .......... .......... .......... .......... 94% 61.3M 1s\n", + "562300K .......... .......... .......... .......... .......... 94% 43.7M 1s\n", + "562350K .......... .......... .......... .......... .......... 94% 37.7M 1s\n", + "562400K .......... .......... .......... .......... .......... 94% 65.1M 1s\n", + "562450K .......... .......... .......... .......... .......... 94% 70.5M 1s\n", + "562500K .......... .......... .......... .......... .......... 94% 57.1M 1s\n", + "562550K .......... .......... .......... .......... .......... 94% 37.3M 1s\n", + "562600K .......... .......... .......... .......... .......... 94% 34.8M 1s\n", + "562650K .......... .......... .......... .......... .......... 94% 74.9M 1s\n", + "562700K .......... .......... .......... .......... .......... 94% 69.7M 1s\n", + "562750K .......... .......... .......... .......... .......... 94% 46.5M 1s\n", + "562800K .......... .......... .......... .......... .......... 94% 42.0M 1s\n", + "562850K .......... .......... .......... .......... .......... 94% 46.5M 1s\n", + "562900K .......... .......... .......... .......... .......... 94% 64.7M 1s\n", + "562950K .......... .......... .......... .......... .......... 94% 54.3M 1s\n", + "563000K .......... .......... .......... .......... .......... 94% 30.5M 1s\n", + "563050K .......... .......... .......... .......... .......... 94% 38.3M 1s\n", + "563100K .......... .......... .......... .......... .......... 94% 70.8M 1s\n", + "563150K .......... .......... .......... .......... .......... 94% 53.5M 1s\n", + "563200K .......... .......... .......... .......... .......... 94% 35.4M 1s\n", + "563250K .......... .......... .......... .......... .......... 94% 32.1M 1s\n", + "563300K .......... .......... .......... .......... .......... 94% 70.4M 1s\n", + "563350K .......... .......... .......... .......... .......... 94% 41.5M 1s\n", + "563400K .......... .......... .......... .......... .......... 94% 23.7M 1s\n", + "563450K .......... .......... .......... .......... .......... 94% 41.1M 1s\n", + "563500K .......... .......... .......... .......... .......... 94% 39.5M 1s\n", + "563550K .......... .......... .......... .......... .......... 94% 44.4M 1s\n", + "563600K .......... .......... .......... .......... .......... 94% 36.3M 1s\n", + "563650K .......... .......... .......... .......... .......... 94% 45.2M 1s\n", + "563700K .......... .......... .......... .......... .......... 94% 52.8M 1s\n", + "563750K .......... .......... .......... .......... .......... 94% 45.5M 1s\n", + "563800K .......... .......... .......... .......... .......... 94% 39.1M 1s\n", + "563850K .......... .......... .......... .......... .......... 94% 38.9M 1s\n", + "563900K .......... .......... .......... .......... .......... 94% 53.2M 1s\n", + "563950K .......... .......... .......... .......... .......... 94% 52.0M 1s\n", + "564000K .......... .......... .......... .......... .......... 94% 32.1M 1s\n", + "564050K .......... .......... .......... .......... .......... 94% 41.7M 1s\n", + "564100K .......... .......... .......... .......... .......... 94% 56.6M 1s\n", + "564150K .......... .......... .......... .......... .......... 94% 47.5M 1s\n", + "564200K .......... .......... .......... .......... .......... 94% 35.4M 1s\n", + "564250K .......... .......... .......... .......... .......... 94% 39.8M 1s\n", + "564300K .......... .......... .......... .......... .......... 94% 54.8M 1s\n", + "564350K .......... .......... .......... .......... .......... 94% 40.2M 1s\n", + "564400K .......... .......... .......... .......... .......... 94% 39.9M 1s\n", + "564450K .......... .......... .......... .......... .......... 94% 38.2M 1s\n", + "564500K .......... .......... .......... .......... .......... 94% 54.7M 1s\n", + "564550K .......... .......... .......... .......... .......... 94% 54.8M 1s\n", + "564600K .......... .......... .......... .......... .......... 94% 38.7M 1s\n", + "564650K .......... .......... .......... .......... .......... 94% 39.3M 1s\n", + "564700K .......... .......... .......... .......... .......... 94% 46.1M 1s\n", + "564750K .......... .......... .......... .......... .......... 94% 50.1M 1s\n", + "564800K .......... .......... .......... .......... .......... 94% 34.0M 1s\n", + "564850K .......... .......... .......... .......... .......... 94% 36.4M 1s\n", + "564900K .......... .......... .......... .......... .......... 94% 3.86M 1s\n", + "564950K .......... .......... .......... .......... .......... 95% 70.3M 1s\n", + "565000K .......... .......... .......... .......... .......... 95% 56.1M 1s\n", + "565050K .......... .......... .......... .......... .......... 95% 71.6M 1s\n", + "565100K .......... .......... .......... .......... .......... 95% 64.8M 1s\n", + "565150K .......... .......... .......... .......... .......... 95% 68.1M 1s\n", + "565200K .......... .......... .......... .......... .......... 95% 41.7M 1s\n", + "565250K .......... .......... .......... .......... .......... 95% 34.9M 1s\n", + "565300K .......... .......... .......... .......... .......... 95% 68.4M 1s\n", + "565350K .......... .......... .......... .......... .......... 95% 71.4M 1s\n", + "565400K .......... .......... .......... .......... .......... 95% 68.7M 1s\n", + "565450K .......... .......... .......... .......... .......... 95% 57.3M 1s\n", + "565500K .......... .......... .......... .......... .......... 95% 29.8M 1s\n", + "565550K .......... .......... .......... .......... .......... 95% 71.1M 1s\n", + "565600K .......... .......... .......... .......... .......... 95% 66.8M 1s\n", + "565650K .......... .......... .......... .......... .......... 95% 70.2M 1s\n", + "565700K .......... .......... .......... .......... .......... 95% 40.7M 1s\n", + "565750K .......... .......... .......... .......... .......... 95% 32.1M 1s\n", + "565800K .......... .......... .......... .......... .......... 95% 60.5M 1s\n", + "565850K .......... .......... .......... .......... .......... 95% 70.8M 1s\n", + "565900K .......... .......... .......... .......... .......... 95% 60.3M 1s\n", + "565950K .......... .......... .......... .......... .......... 95% 34.6M 1s\n", + "566000K .......... .......... .......... .......... .......... 95% 34.7M 1s\n", + "566050K .......... .......... .......... .......... .......... 95% 66.9M 1s\n", + "566100K .......... .......... .......... .......... .......... 95% 64.3M 1s\n", + "566150K .......... .......... .......... .......... .......... 95% 40.3M 1s\n", + "566200K .......... .......... .......... .......... .......... 95% 30.5M 1s\n", + "566250K .......... .......... .......... .......... .......... 95% 70.8M 1s\n", + "566300K .......... .......... .......... .......... .......... 95% 71.9M 1s\n", + "566350K .......... .......... .......... .......... .......... 95% 36.5M 1s\n", + "566400K .......... .......... .......... .......... .......... 95% 42.6M 1s\n", + "566450K .......... .......... .......... .......... .......... 95% 7.14M 1s\n", + "566500K .......... .......... .......... .......... .......... 95% 69.2M 1s\n", + "566550K .......... .......... .......... .......... .......... 95% 72.7M 1s\n", + "566600K .......... .......... .......... .......... .......... 95% 61.5M 1s\n", + "566650K .......... .......... .......... .......... .......... 95% 75.5M 1s\n", + "566700K .......... .......... .......... .......... .......... 95% 74.4M 1s\n", + "566750K .......... .......... .......... .......... .......... 95% 49.8M 1s\n", + "566800K .......... .......... .......... .......... .......... 95% 28.0M 1s\n", + "566850K .......... .......... .......... .......... .......... 95% 65.4M 1s\n", + "566900K .......... .......... .......... .......... .......... 95% 69.2M 1s\n", + "566950K .......... .......... .......... .......... .......... 95% 65.7M 1s\n", + "567000K .......... .......... .......... .......... .......... 95% 26.3M 1s\n", + "567050K .......... .......... .......... .......... .......... 95% 46.4M 1s\n", + "567100K .......... .......... .......... .......... .......... 95% 68.7M 1s\n", + "567150K .......... .......... .......... .......... .......... 95% 63.4M 1s\n", + "567200K .......... .......... .......... .......... .......... 95% 42.9M 1s\n", + "567250K .......... .......... .......... .......... .......... 95% 40.8M 1s\n", + "567300K .......... .......... .......... .......... .......... 95% 51.2M 1s\n", + "567350K .......... .......... .......... .......... .......... 95% 71.8M 1s\n", + "567400K .......... .......... .......... .......... .......... 95% 42.8M 1s\n", + "567450K .......... .......... .......... .......... .......... 95% 58.8M 1s\n", + "567500K .......... .......... .......... .......... .......... 95% 35.0M 1s\n", + "567550K .......... .......... .......... .......... .......... 95% 58.0M 1s\n", + "567600K .......... .......... .......... .......... .......... 95% 64.6M 1s\n", + "567650K .......... .......... .......... .......... .......... 95% 47.7M 1s\n", + "567700K .......... .......... .......... .......... .......... 95% 43.9M 1s\n", + "567750K .......... .......... .......... .......... .......... 95% 40.9M 1s\n", + "567800K .......... .......... .......... .......... .......... 95% 53.1M 1s\n", + "567850K .......... .......... .......... .......... .......... 95% 53.0M 1s\n", + "567900K .......... .......... .......... .......... .......... 95% 51.0M 1s\n", + "567950K .......... .......... .......... .......... .......... 95% 33.4M 1s\n", + "568000K .......... .......... .......... .......... .......... 95% 55.4M 1s\n", + "568050K .......... .......... .......... .......... .......... 95% 59.6M 1s\n", + "568100K .......... .......... .......... .......... .......... 95% 48.1M 1s\n", + "568150K .......... .......... .......... .......... .......... 95% 41.8M 1s\n", + "568200K .......... .......... .......... .......... .......... 95% 38.9M 1s\n", + "568250K .......... .......... .......... .......... .......... 95% 67.1M 1s\n", + "568300K .......... .......... .......... .......... .......... 95% 47.1M 1s\n", + "568350K .......... .......... .......... .......... .......... 95% 37.3M 1s\n", + "568400K .......... .......... .......... .......... .......... 95% 37.3M 1s\n", + "568450K .......... .......... .......... .......... .......... 95% 70.9M 1s\n", + "568500K .......... .......... .......... .......... .......... 95% 50.0M 1s\n", + "568550K .......... .......... .......... .......... .......... 95% 50.8M 1s\n", + "568600K .......... .......... .......... .......... .......... 95% 30.4M 1s\n", + "568650K .......... .......... .......... .......... .......... 95% 62.4M 1s\n", + "568700K .......... .......... .......... .......... .......... 95% 52.0M 1s\n", + "568750K .......... .......... .......... .......... .......... 95% 41.8M 1s\n", + "568800K .......... .......... .......... .......... .......... 95% 40.1M 1s\n", + "568850K .......... .......... .......... .......... .......... 95% 63.9M 1s\n", + "568900K .......... .......... .......... .......... .......... 95% 42.5M 1s\n", + "568950K .......... .......... .......... .......... .......... 95% 51.8M 1s\n", + "569000K .......... .......... .......... .......... .......... 95% 31.5M 1s\n", + "569050K .......... .......... .......... .......... .......... 95% 66.2M 1s\n", + "569100K .......... .......... .......... .......... .......... 95% 37.0M 1s\n", + "569150K .......... .......... .......... .......... .......... 95% 35.5M 1s\n", + "569200K .......... .......... .......... .......... .......... 95% 35.0M 1s\n", + "569250K .......... .......... .......... .......... .......... 95% 59.1M 1s\n", + "569300K .......... .......... .......... .......... .......... 95% 42.4M 1s\n", + "569350K .......... .......... .......... .......... .......... 95% 48.5M 1s\n", + "569400K .......... .......... .......... .......... .......... 95% 32.9M 1s\n", + "569450K .......... .......... .......... .......... .......... 95% 59.5M 1s\n", + "569500K .......... .......... .......... .......... .......... 95% 39.1M 1s\n", + "569550K .......... .......... .......... .......... .......... 95% 33.4M 1s\n", + "569600K .......... .......... .......... .......... .......... 95% 45.1M 1s\n", + "569650K .......... .......... .......... .......... .......... 95% 56.8M 1s\n", + "569700K .......... .......... .......... .......... .......... 95% 23.9M 1s\n", + "569750K .......... .......... .......... .......... .......... 95% 58.2M 1s\n", + "569800K .......... .......... .......... .......... .......... 95% 37.7M 1s\n", + "569850K .......... .......... .......... .......... .......... 95% 39.9M 1s\n", + "569900K .......... .......... .......... .......... .......... 95% 46.6M 1s\n", + "569950K .......... .......... .......... .......... .......... 95% 30.6M 1s\n", + "570000K .......... .......... .......... .......... .......... 95% 40.2M 1s\n", + "570050K .......... .......... .......... .......... .......... 95% 53.6M 1s\n", + "570100K .......... .......... .......... .......... .......... 95% 25.6M 1s\n", + "570150K .......... .......... .......... .......... .......... 95% 3.78M 1s\n", + "570200K .......... .......... .......... .......... .......... 95% 59.8M 1s\n", + "570250K .......... .......... .......... .......... .......... 95% 73.3M 1s\n", + "570300K .......... .......... .......... .......... .......... 95% 68.1M 1s\n", + "570350K .......... .......... .......... .......... .......... 95% 68.4M 1s\n", + "570400K .......... .......... .......... .......... .......... 95% 62.1M 1s\n", + "570450K .......... .......... .......... .......... .......... 95% 66.6M 1s\n", + "570500K .......... .......... .......... .......... .......... 95% 69.6M 1s\n", + "570550K .......... .......... .......... .......... .......... 95% 68.4M 1s\n", + "570600K .......... .......... .......... .......... .......... 95% 53.5M 1s\n", + "570650K .......... .......... .......... .......... .......... 95% 63.6M 1s\n", + "570700K .......... .......... .......... .......... .......... 95% 76.2M 1s\n", + "570750K .......... .......... .......... .......... .......... 95% 71.5M 1s\n", + "570800K .......... .......... .......... .......... .......... 95% 63.3M 1s\n", + "570850K .......... .......... .......... .......... .......... 95% 74.1M 1s\n", + "570900K .......... .......... .......... .......... .......... 96% 72.4M 1s\n", + "570950K .......... .......... .......... .......... .......... 96% 65.1M 1s\n", + "571000K .......... .......... .......... .......... .......... 96% 58.0M 1s\n", + "571050K .......... .......... .......... .......... .......... 96% 74.7M 1s\n", + "571100K .......... .......... .......... .......... .......... 96% 55.9M 1s\n", + "571150K .......... .......... .......... .......... .......... 96% 60.0M 1s\n", + "571200K .......... .......... .......... .......... .......... 96% 61.1M 1s\n", + "571250K .......... .......... .......... .......... .......... 96% 71.9M 1s\n", + "571300K .......... .......... .......... .......... .......... 96% 71.3M 1s\n", + "571350K .......... .......... .......... .......... .......... 96% 67.2M 1s\n", + "571400K .......... .......... .......... .......... .......... 96% 46.3M 1s\n", + "571450K .......... .......... .......... .......... .......... 96% 58.2M 1s\n", + "571500K .......... .......... .......... .......... .......... 96% 65.1M 1s\n", + "571550K .......... .......... .......... .......... .......... 96% 75.5M 1s\n", + "571600K .......... .......... .......... .......... .......... 96% 63.8M 1s\n", + "571650K .......... .......... .......... .......... .......... 96% 66.4M 1s\n", + "571700K .......... .......... .......... .......... .......... 96% 54.8M 1s\n", + "571750K .......... .......... .......... .......... .......... 96% 56.6M 1s\n", + "571800K .......... .......... .......... .......... .......... 96% 58.2M 1s\n", + "571850K .......... .......... .......... .......... .......... 96% 69.7M 1s\n", + "571900K .......... .......... .......... .......... .......... 96% 70.4M 1s\n", + "571950K .......... .......... .......... .......... .......... 96% 55.9M 1s\n", + "572000K .......... .......... .......... .......... .......... 96% 47.2M 1s\n", + "572050K .......... .......... .......... .......... .......... 96% 65.2M 1s\n", + "572100K .......... .......... .......... .......... .......... 96% 71.2M 1s\n", + "572150K .......... .......... .......... .......... .......... 96% 72.8M 1s\n", + "572200K .......... .......... .......... .......... .......... 96% 54.6M 1s\n", + "572250K .......... .......... .......... .......... .......... 96% 28.6M 1s\n", + "572300K .......... .......... .......... .......... .......... 96% 50.2M 1s\n", + "572350K .......... .......... .......... .......... .......... 96% 57.3M 1s\n", + "572400K .......... .......... .......... .......... .......... 96% 22.0M 1s\n", + "572450K .......... .......... .......... .......... .......... 96% 48.1M 1s\n", + "572500K .......... .......... .......... .......... .......... 96% 50.8M 1s\n", + "572550K .......... .......... .......... .......... .......... 96% 26.9M 1s\n", + "572600K .......... .......... .......... .......... .......... 96% 28.2M 1s\n", + "572650K .......... .......... .......... .......... .......... 96% 52.3M 1s\n", + "572700K .......... .......... .......... .......... .......... 96% 29.7M 1s\n", + "572750K .......... .......... .......... .......... .......... 96% 38.0M 1s\n", + "572800K .......... .......... .......... .......... .......... 96% 36.1M 1s\n", + "572850K .......... .......... .......... .......... .......... 96% 72.5M 1s\n", + "572900K .......... .......... .......... .......... .......... 96% 23.5M 1s\n", + "572950K .......... .......... .......... .......... .......... 96% 35.8M 1s\n", + "573000K .......... .......... .......... .......... .......... 96% 58.7M 1s\n", + "573050K .......... .......... .......... .......... .......... 96% 21.5M 1s\n", + "573100K .......... .......... .......... .......... .......... 96% 32.1M 1s\n", + "573150K .......... .......... .......... .......... .......... 96% 70.3M 1s\n", + "573200K .......... .......... .......... .......... .......... 96% 9.18M 1s\n", + "573250K .......... .......... .......... .......... .......... 96% 71.0M 1s\n", + "573300K .......... .......... .......... .......... .......... 96% 63.8M 1s\n", "573350K .......... .......... .......... .......... .......... 96% 65.8M 1s\n", - "573400K .......... .......... .......... .......... .......... 96% 15.5M 1s\n", - "573450K .......... .......... .......... .......... .......... 96% 68.6M 1s\n", - "573500K .......... .......... .......... .......... .......... 96% 63.9M 1s\n", - "573550K .......... .......... .......... .......... .......... 96% 19.7M 1s\n", - "573600K .......... .......... .......... .......... .......... 96% 43.0M 1s\n", - "573650K .......... .......... .......... .......... .......... 96% 58.8M 1s\n", - "573700K .......... .......... .......... .......... .......... 96% 18.0M 1s\n", - "573750K .......... .......... .......... .......... .......... 96% 45.0M 1s\n", - "573800K .......... .......... .......... .......... .......... 96% 58.8M 1s\n", - "573850K .......... .......... .......... .......... .......... 96% 20.6M 1s\n", - "573900K .......... .......... .......... .......... .......... 96% 41.1M 1s\n", - "573950K .......... .......... .......... .......... .......... 96% 66.2M 1s\n", - "574000K .......... .......... .......... .......... .......... 96% 19.6M 1s\n", - "574050K .......... .......... .......... .......... .......... 96% 39.1M 1s\n", - "574100K .......... .......... .......... .......... .......... 96% 64.9M 1s\n", - "574150K .......... .......... .......... .......... .......... 96% 19.5M 1s\n", - "574200K .......... .......... .......... .......... .......... 96% 32.5M 1s\n", - "574250K .......... .......... .......... .......... .......... 96% 68.9M 1s\n", - "574300K .......... .......... .......... .......... .......... 96% 19.3M 1s\n", - "574350K .......... .......... .......... .......... .......... 96% 33.7M 1s\n", - "574400K .......... .......... .......... .......... .......... 96% 51.6M 1s\n", - "574450K .......... .......... .......... .......... .......... 96% 29.6M 1s\n", - "574500K .......... .......... .......... .......... .......... 96% 51.4M 1s\n", - "574550K .......... .......... .......... .......... .......... 96% 27.7M 1s\n", - "574600K .......... .......... .......... .......... .......... 96% 28.6M 1s\n", - "574650K .......... .......... .......... .......... .......... 96% 42.2M 1s\n", - "574700K .......... .......... .......... .......... .......... 96% 31.7M 1s\n", - "574750K .......... .......... .......... .......... .......... 96% 25.3M 1s\n", - "574800K .......... .......... .......... .......... .......... 96% 40.9M 1s\n", - "574850K .......... .......... .......... .......... .......... 96% 27.8M 1s\n", - "574900K .......... .......... .......... .......... .......... 96% 41.6M 1s\n", - "574950K .......... .......... .......... .......... .......... 96% 37.5M 1s\n", - "575000K .......... .......... .......... .......... .......... 96% 25.3M 1s\n", - "575050K .......... .......... .......... .......... .......... 96% 38.9M 1s\n", - "575100K .......... .......... .......... .......... .......... 96% 45.8M 1s\n", - "575150K .......... .......... .......... .......... .......... 96% 23.5M 1s\n", - "575200K .......... .......... .......... .......... .......... 96% 48.2M 1s\n", - "575250K .......... .......... .......... .......... .......... 96% 46.1M 1s\n", - "575300K .......... .......... .......... .......... .......... 96% 24.7M 1s\n", - "575350K .......... .......... .......... .......... .......... 96% 34.7M 1s\n", - "575400K .......... .......... .......... .......... .......... 96% 35.5M 1s\n", - "575450K .......... .......... .......... .......... .......... 96% 29.2M 1s\n", - "575500K .......... .......... .......... .......... .......... 96% 39.8M 1s\n", - "575550K .......... .......... .......... .......... .......... 96% 43.4M 1s\n", - "575600K .......... .......... .......... .......... .......... 96% 46.7M 1s\n", - "575650K .......... .......... .......... .......... .......... 96% 23.5M 1s\n", - "575700K .......... .......... .......... .......... .......... 96% 44.8M 1s\n", - "575750K .......... .......... .......... .......... .......... 96% 40.5M 1s\n", - "575800K .......... .......... .......... .......... .......... 96% 23.4M 1s\n", - "575850K .......... .......... .......... .......... .......... 96% 55.1M 1s\n", - "575900K .......... .......... .......... .......... .......... 96% 36.3M 1s\n", - "575950K .......... .......... .......... .......... .......... 96% 24.9M 1s\n", - "576000K .......... .......... .......... .......... .......... 96% 36.7M 1s\n", - "576050K .......... .......... .......... .......... .......... 96% 43.9M 1s\n", - "576100K .......... .......... .......... .......... .......... 96% 26.0M 0s\n", - "576150K .......... .......... .......... .......... .......... 96% 44.0M 0s\n", - "576200K .......... .......... .......... .......... .......... 96% 40.6M 0s\n", - "576250K .......... .......... .......... .......... .......... 96% 25.6M 0s\n", - "576300K .......... .......... .......... .......... .......... 96% 44.6M 0s\n", - "576350K .......... .......... .......... .......... .......... 96% 37.2M 0s\n", - "576400K .......... .......... .......... .......... .......... 96% 52.3M 0s\n", - "576450K .......... .......... .......... .......... .......... 96% 23.9M 0s\n", - "576500K .......... .......... .......... .......... .......... 96% 56.3M 0s\n", - "576550K .......... .......... .......... .......... .......... 96% 50.3M 0s\n", - "576600K .......... .......... .......... .......... .......... 96% 21.8M 0s\n", - "576650K .......... .......... .......... .......... .......... 96% 30.4M 0s\n", - "576700K .......... .......... .......... .......... .......... 96% 44.7M 0s\n", - "576750K .......... .......... .......... .......... .......... 96% 39.3M 0s\n", - "576800K .......... .......... .......... .......... .......... 96% 29.4M 0s\n", - "576850K .......... .......... .......... .......... .......... 97% 39.3M 0s\n", - "576900K .......... .......... .......... .......... .......... 97% 60.5M 0s\n", - "576950K .......... .......... .......... .......... .......... 97% 31.0M 0s\n", - "577000K .......... .......... .......... .......... .......... 97% 30.2M 0s\n", - "577050K .......... .......... .......... .......... .......... 97% 53.8M 0s\n", - "577100K .......... .......... .......... .......... .......... 97% 4.25M 0s\n", - "577150K .......... .......... .......... .......... .......... 97% 68.1M 0s\n", - "577200K .......... .......... .......... .......... .......... 97% 63.2M 0s\n", - "577250K .......... .......... .......... .......... .......... 97% 16.5M 0s\n", - "577300K .......... .......... .......... .......... .......... 97% 40.7M 0s\n", - "577350K .......... .......... .......... .......... .......... 97% 70.5M 0s\n", - "577400K .......... .......... .......... .......... .......... 97% 56.2M 0s\n", - "577450K .......... .......... .......... .......... .......... 97% 16.9M 0s\n", - "577500K .......... .......... .......... .......... .......... 97% 49.0M 0s\n", - "577550K .......... .......... .......... .......... .......... 97% 72.1M 0s\n", - "577600K .......... .......... .......... .......... .......... 97% 19.4M 0s\n", - "577650K .......... .......... .......... .......... .......... 97% 34.7M 0s\n", - "577700K .......... .......... .......... .......... .......... 97% 71.2M 0s\n", - "577750K .......... .......... .......... .......... .......... 97% 71.7M 0s\n", - "577800K .......... .......... .......... .......... .......... 97% 18.9M 0s\n", - "577850K .......... .......... .......... .......... .......... 97% 45.7M 0s\n", - "577900K .......... .......... .......... .......... .......... 97% 72.2M 0s\n", - "577950K .......... .......... .......... .......... .......... 97% 28.2M 0s\n", - "578000K .......... .......... .......... .......... .......... 97% 42.1M 0s\n", - "578050K .......... .......... .......... .......... .......... 97% 39.7M 0s\n", - "578100K .......... .......... .......... .......... .......... 97% 38.6M 0s\n", - "578150K .......... .......... .......... .......... .......... 97% 31.0M 0s\n", - "578200K .......... .......... .......... .......... .......... 97% 34.3M 0s\n", - "578250K .......... .......... .......... .......... .......... 97% 4.47M 0s\n", - "578300K .......... .......... .......... .......... .......... 97% 67.0M 0s\n", - "578350K .......... .......... .......... .......... .......... 97% 61.8M 0s\n", - "578400K .......... .......... .......... .......... .......... 97% 66.5M 0s\n", - "578450K .......... .......... .......... .......... .......... 97% 18.6M 0s\n", - "578500K .......... .......... .......... .......... .......... 97% 40.0M 0s\n", - "578550K .......... .......... .......... .......... .......... 97% 70.9M 0s\n", - "578600K .......... .......... .......... .......... .......... 97% 58.3M 0s\n", - "578650K .......... .......... .......... .......... .......... 97% 17.8M 0s\n", - "578700K .......... .......... .......... .......... .......... 97% 52.2M 0s\n", - "578750K .......... .......... .......... .......... .......... 97% 71.9M 0s\n", - "578800K .......... .......... .......... .......... .......... 97% 28.1M 0s\n", - "578850K .......... .......... .......... .......... .......... 97% 32.6M 0s\n", - "578900K .......... .......... .......... .......... .......... 97% 55.3M 0s\n", - "578950K .......... .......... .......... .......... .......... 97% 62.4M 0s\n", - "579000K .......... .......... .......... .......... .......... 97% 22.3M 0s\n", - "579050K .......... .......... .......... .......... .......... 97% 35.3M 0s\n", - "579100K .......... .......... .......... .......... .......... 97% 75.9M 0s\n", - "579150K .......... .......... .......... .......... .......... 97% 31.4M 0s\n", - "579200K .......... .......... .......... .......... .......... 97% 34.7M 0s\n", - "579250K .......... .......... .......... .......... .......... 97% 45.6M 0s\n", - "579300K .......... .......... .......... .......... .......... 97% 70.2M 0s\n", - "579350K .......... .......... .......... .......... .......... 97% 19.9M 0s\n", - "579400K .......... .......... .......... .......... .......... 97% 32.9M 0s\n", - "579450K .......... .......... .......... .......... .......... 97% 63.4M 0s\n", - "579500K .......... .......... .......... .......... .......... 97% 29.1M 0s\n", - "579550K .......... .......... .......... .......... .......... 97% 34.0M 0s\n", - "579600K .......... .......... .......... .......... .......... 97% 45.2M 0s\n", - "579650K .......... .......... .......... .......... .......... 97% 70.5M 0s\n", - "579700K .......... .......... .......... .......... .......... 97% 36.3M 0s\n", - "579750K .......... .......... .......... .......... .......... 97% 35.9M 0s\n", - "579800K .......... .......... .......... .......... .......... 97% 39.6M 0s\n", - "579850K .......... .......... .......... .......... .......... 97% 74.8M 0s\n", - "579900K .......... .......... .......... .......... .......... 97% 21.4M 0s\n", - "579950K .......... .......... .......... .......... .......... 97% 35.1M 0s\n", - "580000K .......... .......... .......... .......... .......... 97% 58.8M 0s\n", - "580050K .......... .......... .......... .......... .......... 97% 73.4M 0s\n", - "580100K .......... .......... .......... .......... .......... 97% 27.7M 0s\n", - "580150K .......... .......... .......... .......... .......... 97% 38.8M 0s\n", - "580200K .......... .......... .......... .......... .......... 97% 53.5M 0s\n", - "580250K .......... .......... .......... .......... .......... 97% 30.1M 0s\n", - "580300K .......... .......... .......... .......... .......... 97% 39.5M 0s\n", - "580350K .......... .......... .......... .......... .......... 97% 47.4M 0s\n", - "580400K .......... .......... .......... .......... .......... 97% 53.9M 0s\n", - "580450K .......... .......... .......... .......... .......... 97% 35.8M 0s\n", - "580500K .......... .......... .......... .......... .......... 97% 39.0M 0s\n", - "580550K .......... .......... .......... .......... .......... 97% 45.1M 0s\n", - "580600K .......... .......... .......... .......... .......... 97% 31.9M 0s\n", - "580650K .......... .......... .......... .......... .......... 97% 49.0M 0s\n", - "580700K .......... .......... .......... .......... .......... 97% 27.3M 0s\n", - "580750K .......... .......... .......... .......... .......... 97% 70.2M 0s\n", - "580800K .......... .......... .......... .......... .......... 97% 52.3M 0s\n", - "580850K .......... .......... .......... .......... .......... 97% 48.1M 0s\n", - "580900K .......... .......... .......... .......... .......... 97% 27.2M 0s\n", - "580950K .......... .......... .......... .......... .......... 97% 63.5M 0s\n", - "581000K .......... .......... .......... .......... .......... 97% 43.3M 0s\n", - "581050K .......... .......... .......... .......... .......... 97% 35.1M 0s\n", - "581100K .......... .......... .......... .......... .......... 97% 33.8M 0s\n", - "581150K .......... .......... .......... .......... .......... 97% 70.4M 0s\n", - "581200K .......... .......... .......... .......... .......... 97% 38.7M 0s\n", - "581250K .......... .......... .......... .......... .......... 97% 28.7M 0s\n", - "581300K .......... .......... .......... .......... .......... 97% 41.3M 0s\n", - "581350K .......... .......... .......... .......... .......... 97% 60.3M 0s\n", - "581400K .......... .......... .......... .......... .......... 97% 4.42M 0s\n", - "581450K .......... .......... .......... .......... .......... 97% 61.6M 0s\n", - "581500K .......... .......... .......... .......... .......... 97% 66.8M 0s\n", - "581550K .......... .......... .......... .......... .......... 97% 64.7M 0s\n", - "581600K .......... .......... .......... .......... .......... 97% 25.9M 0s\n", - "581650K .......... .......... .......... .......... .......... 97% 27.1M 0s\n", - "581700K .......... .......... .......... .......... .......... 97% 63.7M 0s\n", - "581750K .......... .......... .......... .......... .......... 97% 23.3M 0s\n", - "581800K .......... .......... .......... .......... .......... 97% 22.0M 0s\n", - "581850K .......... .......... .......... .......... .......... 97% 22.8M 0s\n", - "581900K .......... .......... .......... .......... .......... 97% 26.5M 0s\n", - "581950K .......... .......... .......... .......... .......... 97% 53.7M 0s\n", - "582000K .......... .......... .......... .......... .......... 97% 25.2M 0s\n", - "582050K .......... .......... .......... .......... .......... 97% 24.4M 0s\n", - "582100K .......... .......... .......... .......... .......... 97% 52.2M 0s\n", - "582150K .......... .......... .......... .......... .......... 97% 25.2M 0s\n", - "582200K .......... .......... .......... .......... .......... 97% 27.7M 0s\n", - "582250K .......... .......... .......... .......... .......... 97% 22.6M 0s\n", - "582300K .......... .......... .......... .......... .......... 97% 30.6M 0s\n", - "582350K .......... .......... .......... .......... .......... 97% 43.2M 0s\n", - "582400K .......... .......... .......... .......... .......... 97% 22.0M 0s\n", - "582450K .......... .......... .......... .......... .......... 97% 36.5M 0s\n", - "582500K .......... .......... .......... .......... .......... 97% 29.1M 0s\n", - "582550K .......... .......... .......... .......... .......... 97% 4.42M 0s\n", - "582600K .......... .......... .......... .......... .......... 97% 57.3M 0s\n", - "582650K .......... .......... .......... .......... .......... 97% 65.3M 0s\n", - "582700K .......... .......... .......... .......... .......... 97% 14.6M 0s\n", - "582750K .......... .......... .......... .......... .......... 97% 11.5M 0s\n", - "582800K .......... .......... .......... .......... .......... 98% 51.9M 0s\n", - "582850K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", - "582900K .......... .......... .......... .......... .......... 98% 62.8M 0s\n", - "582950K .......... .......... .......... .......... .......... 98% 12.5M 0s\n", - "583000K .......... .......... .......... .......... .......... 98% 51.9M 0s\n", - "583050K .......... .......... .......... .......... .......... 98% 12.7M 0s\n", - "583100K .......... .......... .......... .......... .......... 98% 62.1M 0s\n", - "583150K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", - "583200K .......... .......... .......... .......... .......... 98% 54.3M 0s\n", - "583250K .......... .......... .......... .......... .......... 98% 12.7M 0s\n", - "583300K .......... .......... .......... .......... .......... 98% 64.0M 0s\n", - "583350K .......... .......... .......... .......... .......... 98% 12.6M 0s\n", - "583400K .......... .......... .......... .......... .......... 98% 11.9M 0s\n", - "583450K .......... .......... .......... .......... .......... 98% 58.5M 0s\n", - "583500K .......... .......... .......... .......... .......... 98% 12.4M 0s\n", - "583550K .......... .......... .......... .......... .......... 98% 61.3M 0s\n", - "583600K .......... .......... .......... .......... .......... 98% 12.6M 0s\n", - "583650K .......... .......... .......... .......... .......... 98% 49.4M 0s\n", - "583700K .......... .......... .......... .......... .......... 98% 13.1M 0s\n", - "583750K .......... .......... .......... .......... .......... 98% 62.7M 0s\n", - "583800K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", - "583850K .......... .......... .......... .......... .......... 98% 55.0M 0s\n", - "583900K .......... .......... .......... .......... .......... 98% 12.2M 0s\n", - "583950K .......... .......... .......... .......... .......... 98% 56.6M 0s\n", - "584000K .......... .......... .......... .......... .......... 98% 12.8M 0s\n", - "584050K .......... .......... .......... .......... .......... 98% 64.1M 0s\n", - "584100K .......... .......... .......... .......... .......... 98% 12.5M 0s\n", - "584150K .......... .......... .......... .......... .......... 98% 62.4M 0s\n", - "584200K .......... .......... .......... .......... .......... 98% 3.96M 0s\n", - "584250K .......... .......... .......... .......... .......... 98% 56.4M 0s\n", - "584300K .......... .......... .......... .......... .......... 98% 13.5M 0s\n", - "584350K .......... .......... .......... .......... .......... 98% 56.3M 0s\n", - "584400K .......... .......... .......... .......... .......... 98% 11.9M 0s\n", - "584450K .......... .......... .......... .......... .......... 98% 65.5M 0s\n", - "584500K .......... .......... .......... .......... .......... 98% 13.4M 0s\n", - "584550K .......... .......... .......... .......... .......... 98% 47.9M 0s\n", - "584600K .......... .......... .......... .......... .......... 98% 12.3M 0s\n", - "584650K .......... .......... .......... .......... .......... 98% 58.1M 0s\n", - "584700K .......... .......... .......... .......... .......... 98% 13.1M 0s\n", - "584750K .......... .......... .......... .......... .......... 98% 57.1M 0s\n", - "584800K .......... .......... .......... .......... .......... 98% 12.6M 0s\n", - "584850K .......... .......... .......... .......... .......... 98% 5.79M 0s\n", - "584900K .......... .......... .......... .......... .......... 98% 4.06M 0s\n", - "584950K .......... .......... .......... .......... .......... 98% 65.1M 0s\n", - "585000K .......... .......... .......... .......... .......... 98% 57.0M 0s\n", - "585050K .......... .......... .......... .......... .......... 98% 66.0M 0s\n", - "585100K .......... .......... .......... .......... .......... 98% 20.0M 0s\n", - "585150K .......... .......... .......... .......... .......... 98% 62.5M 0s\n", - "585200K .......... .......... .......... .......... .......... 98% 12.1M 0s\n", - "585250K .......... .......... .......... .......... .......... 98% 58.8M 0s\n", - "585300K .......... .......... .......... .......... .......... 98% 13.9M 0s\n", - "585350K .......... .......... .......... .......... .......... 98% 36.3M 0s\n", - "585400K .......... .......... .......... .......... .......... 98% 14.3M 0s\n", - "585450K .......... .......... .......... .......... .......... 98% 62.2M 0s\n", - "585500K .......... .......... .......... .......... .......... 98% 12.7M 0s\n", - "585550K .......... .......... .......... .......... .......... 98% 52.8M 0s\n", - "585600K .......... .......... .......... .......... .......... 98% 10.1M 0s\n", - "585650K .......... .......... .......... .......... .......... 98% 40.5M 0s\n", - "585700K .......... .......... .......... .......... .......... 98% 14.0M 0s\n", - "585750K .......... .......... .......... .......... .......... 98% 41.9M 0s\n", - "585800K .......... .......... .......... .......... .......... 98% 14.9M 0s\n", - "585850K .......... .......... .......... .......... .......... 98% 39.2M 0s\n", - "585900K .......... .......... .......... .......... .......... 98% 15.0M 0s\n", - "585950K .......... .......... .......... .......... .......... 98% 11.8M 0s\n", - "586000K .......... .......... .......... .......... .......... 98% 50.4M 0s\n", - "586050K .......... .......... .......... .......... .......... 98% 67.6M 0s\n", - "586100K .......... .......... .......... .......... .......... 98% 22.8M 0s\n", - "586150K .......... .......... .......... .......... .......... 98% 45.1M 0s\n", - "586200K .......... .......... .......... .......... .......... 98% 10.8M 0s\n", - "586250K .......... .......... .......... .......... .......... 98% 56.3M 0s\n", - "586300K .......... .......... .......... .......... .......... 98% 63.8M 0s\n", - "586350K .......... .......... .......... .......... .......... 98% 13.5M 0s\n", - "586400K .......... .......... .......... .......... .......... 98% 49.0M 0s\n", - "586450K .......... .......... .......... .......... .......... 98% 15.0M 0s\n", - "586500K .......... .......... .......... .......... .......... 98% 51.3M 0s\n", - "586550K .......... .......... .......... .......... .......... 98% 14.9M 0s\n", - "586600K .......... .......... .......... .......... .......... 98% 39.6M 0s\n", - "586650K .......... .......... .......... .......... .......... 98% 70.7M 0s\n", - "586700K .......... .......... .......... .......... .......... 98% 15.4M 0s\n", - "586750K .......... .......... .......... .......... .......... 98% 45.3M 0s\n", - "586800K .......... .......... .......... .......... .......... 98% 15.9M 0s\n", - "586850K .......... .......... .......... .......... .......... 98% 52.1M 0s\n", - "586900K .......... .......... .......... .......... .......... 98% 14.0M 0s\n", - "586950K .......... .......... .......... .......... .......... 98% 54.7M 0s\n", - "587000K .......... .......... .......... .......... .......... 98% 13.2M 0s\n", - "587050K .......... .......... .......... .......... .......... 98% 51.2M 0s\n", - "587100K .......... .......... .......... .......... .......... 98% 60.0M 0s\n", - "587150K .......... .......... .......... .......... .......... 98% 15.9M 0s\n", - "587200K .......... .......... .......... .......... .......... 98% 48.1M 0s\n", - "587250K .......... .......... .......... .......... .......... 98% 14.3M 0s\n", - "587300K .......... .......... .......... .......... .......... 98% 41.7M 0s\n", - "587350K .......... .......... .......... .......... .......... 98% 46.0M 0s\n", - "587400K .......... .......... .......... .......... .......... 98% 16.9M 0s\n", - "587450K .......... .......... .......... .......... .......... 98% 46.1M 0s\n", - "587500K .......... .......... .......... .......... .......... 98% 15.4M 0s\n", - "587550K .......... .......... .......... .......... .......... 98% 44.0M 0s\n", - "587600K .......... .......... .......... .......... .......... 98% 52.0M 0s\n", - "587650K .......... .......... .......... .......... .......... 98% 16.2M 0s\n", - "587700K .......... .......... .......... .......... .......... 98% 56.5M 0s\n", - "587750K .......... .......... .......... .......... .......... 98% 14.6M 0s\n", - "587800K .......... .......... .......... .......... .......... 98% 35.3M 0s\n", - "587850K .......... .......... .......... .......... .......... 98% 16.0M 0s\n", - "587900K .......... .......... .......... .......... .......... 98% 61.9M 0s\n", - "587950K .......... .......... .......... .......... .......... 98% 34.7M 0s\n", - "588000K .......... .......... .......... .......... .......... 98% 16.4M 0s\n", - "588050K .......... .......... .......... .......... .......... 98% 51.0M 0s\n", - "588100K .......... .......... .......... .......... .......... 98% 60.0M 0s\n", - "588150K .......... .......... .......... .......... .......... 98% 16.3M 0s\n", - "588200K .......... .......... .......... .......... .......... 98% 40.8M 0s\n", - "588250K .......... .......... .......... .......... .......... 98% 16.9M 0s\n", - "588300K .......... .......... .......... .......... .......... 98% 53.8M 0s\n", - "588350K .......... .......... .......... .......... .......... 98% 51.7M 0s\n", - "588400K .......... .......... .......... .......... .......... 98% 15.2M 0s\n", - "588450K .......... .......... .......... .......... .......... 98% 44.4M 0s\n", - "588500K .......... .......... .......... .......... .......... 98% 16.4M 0s\n", - "588550K .......... .......... .......... .......... .......... 98% 55.5M 0s\n", - "588600K .......... .......... .......... .......... .......... 98% 14.3M 0s\n", - "588650K .......... .......... .......... .......... .......... 98% 47.2M 0s\n", - "588700K .......... .......... .......... .......... .......... 98% 4.49M 0s\n", - "588750K .......... .......... .......... .......... .......... 99% 62.9M 0s\n", - "588800K .......... .......... .......... .......... .......... 99% 57.4M 0s\n", - "588850K .......... .......... .......... .......... .......... 99% 14.3M 0s\n", - "588900K .......... .......... .......... .......... .......... 99% 57.8M 0s\n", - "588950K .......... .......... .......... .......... .......... 99% 69.9M 0s\n", - "589000K .......... .......... .......... .......... .......... 99% 14.0M 0s\n", - "589050K .......... .......... .......... .......... .......... 99% 63.0M 0s\n", - "589100K .......... .......... .......... .......... .......... 99% 13.6M 0s\n", - "589150K .......... .......... .......... .......... .......... 99% 65.7M 0s\n", - "589200K .......... .......... .......... .......... .......... 99% 61.8M 0s\n", - "589250K .......... .......... .......... .......... .......... 99% 13.3M 0s\n", - "589300K .......... .......... .......... .......... .......... 99% 60.1M 0s\n", - "589350K .......... .......... .......... .......... .......... 99% 68.0M 0s\n", - "589400K .......... .......... .......... .......... .......... 99% 16.2M 0s\n", - "589450K .......... .......... .......... .......... .......... 99% 65.0M 0s\n", - "589500K .......... .......... .......... .......... .......... 99% 14.2M 0s\n", - "589550K .......... .......... .......... .......... .......... 99% 66.6M 0s\n", - "589600K .......... .......... .......... .......... .......... 99% 58.3M 0s\n", - "589650K .......... .......... .......... .......... .......... 99% 15.0M 0s\n", - "589700K .......... .......... .......... .......... .......... 99% 59.7M 0s\n", - "589750K .......... .......... .......... .......... .......... 99% 69.1M 0s\n", - "589800K .......... .......... .......... .......... .......... 99% 13.6M 0s\n", - "589850K .......... .......... .......... .......... .......... 99% 58.9M 0s\n", - "589900K .......... .......... .......... .......... .......... 99% 4.35M 0s\n", - "589950K .......... .......... .......... .......... .......... 99% 64.9M 0s\n", - "590000K .......... .......... .......... .......... .......... 99% 48.6M 0s\n", - "590050K .......... .......... .......... .......... .......... 99% 67.4M 0s\n", - "590100K .......... .......... .......... .......... .......... 99% 18.0M 0s\n", - "590150K .......... .......... .......... .......... .......... 99% 59.0M 0s\n", - "590200K .......... .......... .......... .......... .......... 99% 16.1M 0s\n", - "590250K .......... .......... .......... .......... .......... 99% 49.9M 0s\n", - "590300K .......... .......... .......... .......... .......... 99% 58.0M 0s\n", - "590350K .......... .......... .......... .......... .......... 99% 6.66M 0s\n", - "590400K .......... .......... .......... .......... .......... 99% 60.2M 0s\n", - "590450K .......... .......... .......... .......... .......... 99% 70.7M 0s\n", - "590500K .......... .......... .......... .......... .......... 99% 70.7M 0s\n", - "590550K .......... .......... .......... .......... .......... 99% 17.6M 0s\n", - "590600K .......... .......... .......... .......... .......... 99% 39.2M 0s\n", - "590650K .......... .......... .......... .......... .......... 99% 16.5M 0s\n", - "590700K .......... .......... .......... .......... .......... 99% 45.1M 0s\n", - "590750K .......... .......... .......... .......... .......... 99% 67.7M 0s\n", - "590800K .......... .......... .......... .......... .......... 99% 16.8M 0s\n", - "590850K .......... .......... .......... .......... .......... 99% 48.2M 0s\n", - "590900K .......... .......... .......... .......... .......... 99% 69.7M 0s\n", - "590950K .......... .......... .......... .......... .......... 99% 20.8M 0s\n", - "591000K .......... .......... .......... .......... .......... 99% 31.5M 0s\n", - "591050K .......... .......... .......... .......... .......... 99% 58.4M 0s\n", - "591100K .......... .......... .......... .......... .......... 99% 18.3M 0s\n", - "591150K .......... .......... .......... .......... .......... 99% 39.9M 0s\n", - "591200K .......... .......... .......... .......... .......... 99% 59.7M 0s\n", - "591250K .......... .......... .......... .......... .......... 99% 18.7M 0s\n", - "591300K .......... .......... .......... .......... .......... 99% 39.0M 0s\n", - "591350K .......... .......... .......... .......... .......... 99% 70.5M 0s\n", - "591400K .......... .......... .......... .......... .......... 99% 17.2M 0s\n", - "591450K .......... .......... .......... .......... .......... 99% 31.5M 0s\n", - "591500K .......... .......... .......... .......... .......... 99% 63.1M 0s\n", - "591550K .......... .......... .......... .......... .......... 99% 22.0M 0s\n", - "591600K .......... .......... .......... .......... .......... 99% 37.1M 0s\n", - "591650K .......... .......... .......... .......... .......... 99% 62.4M 0s\n", - "591700K .......... .......... .......... .......... .......... 99% 20.7M 0s\n", - "591750K .......... .......... .......... .......... .......... 99% 36.0M 0s\n", - "591800K .......... .......... .......... .......... .......... 99% 52.4M 0s\n", - "591850K .......... .......... .......... .......... .......... 99% 21.8M 0s\n", - "591900K .......... .......... .......... .......... .......... 99% 36.3M 0s\n", - "591950K .......... .......... .......... .......... .......... 99% 65.7M 0s\n", - "592000K .......... .......... .......... .......... .......... 99% 17.6M 0s\n", - "592050K .......... .......... .......... .......... .......... 99% 39.2M 0s\n", - "592100K .......... .......... .......... .......... .......... 99% 66.4M 0s\n", - "592150K .......... .......... .......... .......... .......... 99% 20.7M 0s\n", - "592200K .......... .......... .......... .......... .......... 99% 33.4M 0s\n", - "592250K .......... .......... .......... .......... .......... 99% 64.8M 0s\n", - "592300K .......... .......... .......... .......... .......... 99% 19.8M 0s\n", - "592350K .......... .......... .......... .......... .......... 99% 40.6M 0s\n", - "592400K .......... .......... .......... .......... .......... 99% 52.1M 0s\n", - "592450K .......... .......... .......... .......... .......... 99% 22.8M 0s\n", - "592500K .......... .......... .......... .......... .......... 99% 26.8M 0s\n", - "592550K .......... .......... .......... .......... .......... 99% 66.4M 0s\n", - "592600K .......... .......... .......... .......... .......... 99% 22.0M 0s\n", - "592650K .......... .......... .......... .......... .......... 99% 38.5M 0s\n", - "592700K .......... .......... .......... .......... .......... 99% 49.8M 0s\n", - "592750K .......... .......... .......... .......... .......... 99% 23.2M 0s\n", - "592800K .......... .......... .......... .......... .......... 99% 34.5M 0s\n", - "592850K .......... .......... .......... .......... .......... 99% 46.1M 0s\n", - "592900K .......... .......... .......... .......... .......... 99% 26.8M 0s\n", - "592950K .......... .......... .......... .......... .......... 99% 28.6M 0s\n", - "593000K .......... .......... .......... .......... .......... 99% 33.8M 0s\n", - "593050K .......... .......... .......... .......... .......... 99% 37.5M 0s\n", - "593100K .......... .......... .......... .......... .......... 99% 30.8M 0s\n", - "593150K .......... .......... .......... .......... .......... 99% 46.7M 0s\n", - "593200K .......... .......... .......... .......... .......... 99% 23.9M 0s\n", - "593250K .......... .......... .......... .......... .......... 99% 54.0M 0s\n", - "593300K .......... .......... .......... .......... .......... 99% 30.0M 0s\n", - "593350K .......... .......... .......... .......... .......... 99% 49.8M 0s\n", - "593400K .......... .......... .......... .......... .......... 99% 25.5M 0s\n", - "593450K .......... .......... .......... .......... .......... 99% 34.9M 0s\n", - "593500K .......... .......... .......... .......... .......... 99% 49.5M 0s\n", - "593550K .......... .......... .......... .......... .......... 99% 27.0M 0s\n", - "593600K .......... .......... .......... .......... .......... 99% 39.4M 0s\n", - "593650K .......... .......... .......... .......... .......... 99% 40.8M 0s\n", - "593700K .......... .......... .......... .......... .......... 99% 28.8M 0s\n", - "593750K .......... .......... .......... .......... .......... 99% 45.6M 0s\n", - "593800K .......... .......... .......... .......... .......... 99% 30.9M 0s\n", - "593850K .......... .......... .......... .......... .......... 99% 23.8M 0s\n", - "593900K .......... .......... .......... .......... .......... 99% 38.4M 0s\n", - "593950K .......... .......... .......... .......... .......... 99% 37.6M 0s\n", - "594000K .......... .......... .......... .......... .......... 99% 4.39M 0s\n", - "594050K .......... .......... .......... .......... .......... 99% 66.0M 0s\n", - "594100K .......... .......... .......... .......... .......... 99% 60.8M 0s\n", - "594150K .......... .......... .......... .......... .......... 99% 62.1M 0s\n", - "594200K .......... .......... .......... .......... .......... 99% 15.5M 0s\n", - "594250K .......... .......... .......... .......... .......... 99% 58.5M 0s\n", - "594300K .......... .......... .......... .......... .......... 99% 66.6M 0s\n", - "594350K .......... .......... .......... .......... .......... 99% 19.1M 0s\n", - "594400K .......... .......... .......... .......... .......... 99% 33.9M 0s\n", - "594450K .......... .......... .......... .......... .......... 99% 66.9M 0s\n", - "594500K .......... .......... .......... .......... .......... 99% 26.2M 0s\n", - "594550K .......... .......... .......... .......... .......... 99% 31.8M 0s\n", - "594600K .......... .......... .......... .......... .......... 99% 42.2M 0s\n", - "594650K .......... .......... .......... .......... .......... 99% 27.2M 0s\n", - "594700K .......... .......... .......... 100% 52.3M=16s\n", + "573400K .......... .......... .......... .......... .......... 96% 20.6M 1s\n", + "573450K .......... .......... .......... .......... .......... 96% 62.1M 1s\n", + "573500K .......... .......... .......... .......... .......... 96% 74.3M 1s\n", + "573550K .......... .......... .......... .......... .......... 96% 14.5M 1s\n", + "573600K .......... .......... .......... .......... .......... 96% 53.2M 1s\n", + "573650K .......... .......... .......... .......... .......... 96% 78.3M 1s\n", + "573700K .......... .......... .......... .......... .......... 96% 22.3M 1s\n", + "573750K .......... .......... .......... .......... .......... 96% 30.4M 1s\n", + "573800K .......... .......... .......... .......... .......... 96% 56.8M 1s\n", + "573850K .......... .......... .......... .......... .......... 96% 66.2M 1s\n", + "573900K .......... .......... .......... .......... .......... 96% 17.9M 1s\n", + "573950K .......... .......... .......... .......... .......... 96% 59.8M 1s\n", + "574000K .......... .......... .......... .......... .......... 96% 68.7M 1s\n", + "574050K .......... .......... .......... .......... .......... 96% 35.8M 1s\n", + "574100K .......... .......... .......... .......... .......... 96% 33.7M 1s\n", + "574150K .......... .......... .......... .......... .......... 96% 50.0M 1s\n", + "574200K .......... .......... .......... .......... .......... 96% 53.7M 1s\n", + "574250K .......... .......... .......... .......... .......... 96% 25.5M 1s\n", + "574300K .......... .......... .......... .......... .......... 96% 36.6M 1s\n", + "574350K .......... .......... .......... .......... .......... 96% 58.4M 1s\n", + "574400K .......... .......... .......... .......... .......... 96% 29.8M 1s\n", + "574450K .......... .......... .......... .......... .......... 96% 41.2M 1s\n", + "574500K .......... .......... .......... .......... .......... 96% 36.9M 1s\n", + "574550K .......... .......... .......... .......... .......... 96% 62.7M 1s\n", + "574600K .......... .......... .......... .......... .......... 96% 24.6M 1s\n", + "574650K .......... .......... .......... .......... .......... 96% 39.5M 1s\n", + "574700K .......... .......... .......... .......... .......... 96% 48.8M 1s\n", + "574750K .......... .......... .......... .......... .......... 96% 33.1M 1s\n", + "574800K .......... .......... .......... .......... .......... 96% 32.2M 1s\n", + "574850K .......... .......... .......... .......... .......... 96% 56.6M 1s\n", + "574900K .......... .......... .......... .......... .......... 96% 41.2M 1s\n", + "574950K .......... .......... .......... .......... .......... 96% 27.3M 1s\n", + "575000K .......... .......... .......... .......... .......... 96% 22.0M 1s\n", + "575050K .......... .......... .......... .......... .......... 96% 36.2M 1s\n", + "575100K .......... .......... .......... .......... .......... 96% 46.2M 1s\n", + "575150K .......... .......... .......... .......... .......... 96% 48.4M 1s\n", + "575200K .......... .......... .......... .......... .......... 96% 44.0M 1s\n", + "575250K .......... .......... .......... .......... .......... 96% 53.3M 1s\n", + "575300K .......... .......... .......... .......... .......... 96% 45.7M 1s\n", + "575350K .......... .......... .......... .......... .......... 96% 48.8M 1s\n", + "575400K .......... .......... .......... .......... .......... 96% 27.9M 1s\n", + "575450K .......... .......... .......... .......... .......... 96% 44.6M 1s\n", + "575500K .......... .......... .......... .......... .......... 96% 47.9M 1s\n", + "575550K .......... .......... .......... .......... .......... 96% 36.1M 1s\n", + "575600K .......... .......... .......... .......... .......... 96% 34.8M 1s\n", + "575650K .......... .......... .......... .......... .......... 96% 57.7M 1s\n", + "575700K .......... .......... .......... .......... .......... 96% 34.3M 1s\n", + "575750K .......... .......... .......... .......... .......... 96% 42.8M 1s\n", + "575800K .......... .......... .......... .......... .......... 96% 27.7M 1s\n", + "575850K .......... .......... .......... .......... .......... 96% 34.4M 1s\n", + "575900K .......... .......... .......... .......... .......... 96% 48.3M 1s\n", + "575950K .......... .......... .......... .......... .......... 96% 40.0M 1s\n", + "576000K .......... .......... .......... .......... .......... 96% 38.8M 1s\n", + "576050K .......... .......... .......... .......... .......... 96% 49.0M 1s\n", + "576100K .......... .......... .......... .......... .......... 96% 45.8M 1s\n", + "576150K .......... .......... .......... .......... .......... 96% 30.6M 1s\n", + "576200K .......... .......... .......... .......... .......... 96% 48.7M 1s\n", + "576250K .......... .......... .......... .......... .......... 96% 31.6M 1s\n", + "576300K .......... .......... .......... .......... .......... 96% 46.2M 1s\n", + "576350K .......... .......... .......... .......... .......... 96% 40.9M 1s\n", + "576400K .......... .......... .......... .......... .......... 96% 51.2M 1s\n", + "576450K .......... .......... .......... .......... .......... 96% 29.3M 1s\n", + "576500K .......... .......... .......... .......... .......... 96% 41.5M 1s\n", + "576550K .......... .......... .......... .......... .......... 96% 47.7M 1s\n", + "576600K .......... .......... .......... .......... .......... 96% 36.7M 1s\n", + "576650K .......... .......... .......... .......... .......... 96% 31.9M 1s\n", + "576700K .......... .......... .......... .......... .......... 96% 43.7M 1s\n", + "576750K .......... .......... .......... .......... .......... 96% 48.4M 1s\n", + "576800K .......... .......... .......... .......... .......... 96% 43.3M 1s\n", + "576850K .......... .......... .......... .......... .......... 97% 37.3M 1s\n", + "576900K .......... .......... .......... .......... .......... 97% 43.4M 1s\n", + "576950K .......... .......... .......... .......... .......... 97% 33.5M 1s\n", + "577000K .......... .......... .......... .......... .......... 97% 265K 1s\n", + "577050K .......... .......... .......... .......... .......... 97% 55.4M 1s\n", + "577100K .......... .......... .......... .......... .......... 97% 70.8M 1s\n", + "577150K .......... .......... .......... .......... .......... 97% 71.4M 1s\n", + "577200K .......... .......... .......... .......... .......... 97% 21.0M 1s\n", + "577250K .......... .......... .......... .......... .......... 97% 46.8M 1s\n", + "577300K .......... .......... .......... .......... .......... 97% 76.0M 1s\n", + "577350K .......... .......... .......... .......... .......... 97% 88.2M 1s\n", + "577400K .......... .......... .......... .......... .......... 97% 14.7M 1s\n", + "577450K .......... .......... .......... .......... .......... 97% 81.7M 1s\n", + "577500K .......... .......... .......... .......... .......... 97% 80.6M 1s\n", + "577550K .......... .......... .......... .......... .......... 97% 22.8M 1s\n", + "577600K .......... .......... .......... .......... .......... 97% 58.8M 1s\n", + "577650K .......... .......... .......... .......... .......... 97% 73.8M 1s\n", + "577700K .......... .......... .......... .......... .......... 97% 70.5M 1s\n", + "577750K .......... .......... .......... .......... .......... 97% 15.4M 1s\n", + "577800K .......... .......... .......... .......... .......... 97% 36.1M 1s\n", + "577850K .......... .......... .......... .......... .......... 97% 75.6M 1s\n", + "577900K .......... .......... .......... .......... .......... 97% 71.3M 1s\n", + "577950K .......... .......... .......... .......... .......... 97% 20.0M 1s\n", + "578000K .......... .......... .......... .......... .......... 97% 48.9M 1s\n", + "578050K .......... .......... .......... .......... .......... 97% 3.93M 1s\n", + "578100K .......... .......... .......... .......... .......... 97% 38.8M 1s\n", + "578150K .......... .......... .......... .......... .......... 97% 50.5M 1s\n", + "578200K .......... .......... .......... .......... .......... 97% 60.7M 1s\n", + "578250K .......... .......... .......... .......... .......... 97% 61.8M 1s\n", + "578300K .......... .......... .......... .......... .......... 97% 52.2M 1s\n", + "578350K .......... .......... .......... .......... .......... 97% 68.6M 1s\n", + "578400K .......... .......... .......... .......... .......... 97% 64.2M 1s\n", + "578450K .......... .......... .......... .......... .......... 97% 65.0M 1s\n", + "578500K .......... .......... .......... .......... .......... 97% 30.2M 1s\n", + "578550K .......... .......... .......... .......... .......... 97% 30.5M 1s\n", + "578600K .......... .......... .......... .......... .......... 97% 58.8M 1s\n", + "578650K .......... .......... .......... .......... .......... 97% 83.2M 1s\n", + "578700K .......... .......... .......... .......... .......... 97% 26.2M 1s\n", + "578750K .......... .......... .......... .......... .......... 97% 29.1M 1s\n", + "578800K .......... .......... .......... .......... .......... 97% 58.2M 1s\n", + "578850K .......... .......... .......... .......... .......... 97% 42.4M 1s\n", + "578900K .......... .......... .......... .......... .......... 97% 52.3M 1s\n", + "578950K .......... .......... .......... .......... .......... 97% 37.1M 1s\n", + "579000K .......... .......... .......... .......... .......... 97% 36.0M 1s\n", + "579050K .......... .......... .......... .......... .......... 97% 46.4M 1s\n", + "579100K .......... .......... .......... .......... .......... 97% 39.1M 1s\n", + "579150K .......... .......... .......... .......... .......... 97% 33.9M 1s\n", + "579200K .......... .......... .......... .......... .......... 97% 55.6M 1s\n", + "579250K .......... .......... .......... .......... .......... 97% 40.7M 1s\n", + "579300K .......... .......... .......... .......... .......... 97% 34.7M 1s\n", + "579350K .......... .......... .......... .......... .......... 97% 41.7M 1s\n", + "579400K .......... .......... .......... .......... .......... 97% 25.4M 1s\n", + "579450K .......... .......... .......... .......... .......... 97% 54.2M 1s\n", + "579500K .......... .......... .......... .......... .......... 97% 3.72M 1s\n", + "579550K .......... .......... .......... .......... .......... 97% 75.5M 1s\n", + "579600K .......... .......... .......... .......... .......... 97% 59.2M 1s\n", + "579650K .......... .......... .......... .......... .......... 97% 64.7M 1s\n", + "579700K .......... .......... .......... .......... .......... 97% 19.0M 0s\n", + "579750K .......... .......... .......... .......... .......... 97% 40.6M 0s\n", + "579800K .......... .......... .......... .......... .......... 97% 64.0M 0s\n", + "579850K .......... .......... .......... .......... .......... 97% 8.12M 0s\n", + "579900K .......... .......... .......... .......... .......... 97% 65.1M 0s\n", + "579950K .......... .......... .......... .......... .......... 97% 73.7M 0s\n", + "580000K .......... .......... .......... .......... .......... 97% 46.3M 0s\n", + "580050K .......... .......... .......... .......... .......... 97% 19.6M 0s\n", + "580100K .......... .......... .......... .......... .......... 97% 52.0M 0s\n", + "580150K .......... .......... .......... .......... .......... 97% 62.2M 0s\n", + "580200K .......... .......... 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.......... .......... .......... 97% 6.68M 0s\n", + "582650K .......... .......... .......... .......... .......... 97% 22.6M 0s\n", + "582700K .......... .......... .......... .......... .......... 97% 66.5M 0s\n", + "582750K .......... .......... .......... .......... .......... 97% 61.5M 0s\n", + "582800K .......... .......... .......... .......... .......... 98% 41.8M 0s\n", + "582850K .......... .......... .......... .......... .......... 98% 52.4M 0s\n", + "582900K .......... .......... .......... .......... .......... 98% 63.3M 0s\n", + "582950K .......... .......... .......... .......... .......... 98% 70.5M 0s\n", + "583000K .......... .......... .......... .......... .......... 98% 17.8M 0s\n", + "583050K .......... .......... .......... .......... .......... 98% 56.0M 0s\n", + "583100K .......... .......... .......... .......... .......... 98% 64.7M 0s\n", + "583150K .......... .......... .......... .......... .......... 98% 23.2M 0s\n", + "583200K .......... .......... .......... .......... .......... 98% 53.7M 0s\n", + "583250K .......... .......... .......... .......... .......... 98% 56.1M 0s\n", + "583300K .......... .......... .......... .......... .......... 98% 84.7M 0s\n", + "583350K .......... .......... .......... .......... .......... 98% 75.8M 0s\n", + "583400K .......... .......... .......... .......... .......... 98% 20.8M 0s\n", + "583450K .......... .......... .......... .......... .......... 98% 67.3M 0s\n", + "583500K .......... .......... .......... .......... .......... 98% 72.6M 0s\n", + "583550K .......... .......... .......... .......... .......... 98% 21.7M 0s\n", + "583600K .......... .......... .......... .......... .......... 98% 43.4M 0s\n", + "583650K .......... .......... .......... .......... .......... 98% 57.2M 0s\n", + "583700K .......... .......... .......... .......... .......... 98% 64.2M 0s\n", + "583750K .......... .......... .......... .......... .......... 98% 28.3M 0s\n", + "583800K .......... .......... 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.......... .......... .......... 98% 47.3M 0s\n", + "585650K .......... .......... .......... .......... .......... 98% 61.3M 0s\n", + "585700K .......... .......... .......... .......... .......... 98% 67.3M 0s\n", + "585750K .......... .......... .......... .......... .......... 98% 38.4M 0s\n", + "585800K .......... .......... .......... .......... .......... 98% 23.1M 0s\n", + "585850K .......... .......... .......... .......... .......... 98% 67.9M 0s\n", + "585900K .......... .......... .......... .......... .......... 98% 78.2M 0s\n", + "585950K .......... .......... .......... .......... .......... 98% 50.1M 0s\n", + "586000K .......... .......... .......... .......... .......... 98% 28.0M 0s\n", + "586050K .......... .......... .......... .......... .......... 98% 50.8M 0s\n", + "586100K .......... .......... .......... .......... .......... 98% 79.8M 0s\n", + "586150K .......... .......... .......... .......... .......... 98% 3.85M 0s\n", + "586200K .......... .......... .......... .......... .......... 98% 59.9M 0s\n", + "586250K .......... .......... .......... .......... .......... 98% 58.7M 0s\n", + "586300K .......... .......... .......... .......... .......... 98% 16.4M 0s\n", + "586350K .......... .......... .......... .......... .......... 98% 34.9M 0s\n", + "586400K .......... .......... .......... .......... .......... 98% 64.1M 0s\n", + "586450K .......... .......... .......... .......... .......... 98% 74.2M 0s\n", + "586500K .......... .......... .......... .......... .......... 98% 86.5M 0s\n", + "586550K .......... .......... .......... .......... .......... 98% 46.6M 0s\n", + "586600K .......... .......... .......... .......... .......... 98% 33.6M 0s\n", + "586650K .......... .......... .......... .......... .......... 98% 47.7M 0s\n", + "586700K .......... .......... .......... .......... .......... 98% 71.7M 0s\n", + "586750K .......... .......... .......... .......... .......... 98% 64.6M 0s\n", + "586800K .......... .......... .......... .......... .......... 98% 31.8M 0s\n", + "586850K .......... .......... .......... .......... .......... 98% 45.7M 0s\n", + "586900K .......... .......... .......... .......... .......... 98% 75.1M 0s\n", + "586950K .......... .......... .......... .......... .......... 98% 91.0M 0s\n", + "587000K .......... .......... .......... .......... .......... 98% 23.0M 0s\n", + "587050K .......... .......... .......... .......... .......... 98% 35.9M 0s\n", + "587100K .......... .......... .......... .......... .......... 98% 70.6M 0s\n", + "587150K .......... .......... .......... .......... .......... 98% 73.3M 0s\n", + "587200K .......... .......... .......... .......... .......... 98% 29.5M 0s\n", + "587250K .......... .......... .......... .......... .......... 98% 47.0M 0s\n", + "587300K .......... .......... .......... .......... .......... 98% 42.5M 0s\n", + "587350K .......... .......... .......... .......... .......... 98% 66.4M 0s\n", + "587400K .......... .......... .......... .......... .......... 98% 32.5M 0s\n", + "587450K .......... .......... .......... .......... .......... 98% 51.0M 0s\n", + "587500K .......... .......... .......... .......... .......... 98% 58.5M 0s\n", + "587550K .......... .......... .......... .......... .......... 98% 71.9M 0s\n", + "587600K .......... .......... .......... .......... .......... 98% 29.1M 0s\n", + "587650K .......... .......... .......... .......... .......... 98% 55.9M 0s\n", + "587700K .......... .......... .......... .......... .......... 98% 55.6M 0s\n", + "587750K .......... .......... .......... .......... .......... 98% 60.9M 0s\n", + "587800K .......... .......... .......... .......... .......... 98% 23.9M 0s\n", + "587850K .......... .......... .......... .......... .......... 98% 48.6M 0s\n", + "587900K .......... .......... .......... .......... .......... 98% 45.6M 0s\n", + "587950K .......... .......... .......... .......... .......... 98% 62.0M 0s\n", + "588000K .......... .......... .......... .......... .......... 98% 66.8M 0s\n", + "588050K .......... .......... .......... .......... .......... 98% 25.7M 0s\n", + "588100K .......... .......... .......... .......... .......... 98% 53.5M 0s\n", + "588150K .......... .......... .......... .......... .......... 98% 66.8M 0s\n", + "588200K .......... .......... .......... .......... .......... 98% 60.0M 0s\n", + "588250K .......... .......... .......... .......... .......... 98% 27.7M 0s\n", + "588300K .......... .......... .......... .......... .......... 98% 57.7M 0s\n", + "588350K .......... .......... .......... .......... .......... 98% 68.6M 0s\n", + "588400K .......... .......... .......... .......... .......... 98% 59.0M 0s\n", + "588450K .......... .......... .......... .......... .......... 98% 24.5M 0s\n", + "588500K .......... .......... .......... .......... .......... 98% 47.0M 0s\n", + "588550K .......... .......... .......... .......... .......... 98% 48.4M 0s\n", + "588600K .......... .......... .......... .......... .......... 98% 50.0M 0s\n", + "588650K .......... .......... .......... .......... .......... 98% 71.2M 0s\n", + "588700K .......... .......... .......... .......... .......... 98% 33.9M 0s\n", + "588750K .......... .......... .......... .......... .......... 99% 56.5M 0s\n", + "588800K .......... .......... .......... .......... .......... 99% 48.4M 0s\n", + "588850K .......... .......... .......... .......... .......... 99% 55.8M 0s\n", + "588900K .......... .......... .......... .......... .......... 99% 30.2M 0s\n", + "588950K .......... .......... .......... .......... .......... 99% 61.1M 0s\n", + "589000K .......... .......... .......... .......... .......... 99% 54.7M 0s\n", + "589050K .......... .......... .......... .......... .......... 99% 60.1M 0s\n", + "589100K .......... .......... .......... .......... .......... 99% 27.7M 0s\n", + "589150K .......... .......... .......... .......... .......... 99% 66.7M 0s\n", + "589200K .......... .......... .......... .......... .......... 99% 38.2M 0s\n", + "589250K .......... .......... .......... .......... .......... 99% 66.7M 0s\n", + "589300K .......... .......... .......... .......... .......... 99% 63.0M 0s\n", + "589350K .......... .......... .......... .......... .......... 99% 33.6M 0s\n", + "589400K .......... .......... .......... .......... .......... 99% 49.5M 0s\n", + "589450K .......... .......... .......... .......... .......... 99% 46.0M 0s\n", + "589500K .......... .......... .......... .......... .......... 99% 77.7M 0s\n", + "589550K .......... .......... .......... .......... .......... 99% 30.0M 0s\n", + "589600K .......... .......... .......... .......... .......... 99% 49.2M 0s\n", + "589650K .......... .......... .......... .......... .......... 99% 58.7M 0s\n", + "589700K .......... .......... .......... .......... .......... 99% 64.3M 0s\n", + "589750K .......... .......... .......... .......... .......... 99% 75.2M 0s\n", + "589800K .......... .......... .......... .......... .......... 99% 25.7M 0s\n", + "589850K .......... .......... .......... .......... .......... 99% 76.7M 0s\n", + "589900K .......... .......... .......... .......... .......... 99% 70.9M 0s\n", + "589950K .......... .......... .......... .......... .......... 99% 62.6M 0s\n", + "590000K .......... .......... .......... .......... .......... 99% 22.4M 0s\n", + "590050K .......... .......... .......... .......... .......... 99% 48.1M 0s\n", + "590100K .......... .......... .......... .......... .......... 99% 55.7M 0s\n", + "590150K .......... .......... .......... .......... .......... 99% 71.6M 0s\n", + "590200K .......... .......... .......... .......... .......... 99% 29.8M 0s\n", + "590250K .......... .......... .......... .......... .......... 99% 52.4M 0s\n", + "590300K .......... .......... .......... .......... .......... 99% 52.7M 0s\n", + "590350K .......... .......... .......... .......... .......... 99% 61.2M 0s\n", + "590400K .......... .......... .......... .......... .......... 99% 59.1M 0s\n", + "590450K .......... .......... .......... .......... .......... 99% 41.3M 0s\n", + "590500K .......... .......... .......... .......... .......... 99% 62.2M 0s\n", + "590550K .......... .......... .......... .......... .......... 99% 54.0M 0s\n", + "590600K .......... .......... .......... .......... .......... 99% 51.6M 0s\n", + "590650K .......... .......... .......... .......... .......... 99% 36.0M 0s\n", + "590700K .......... .......... .......... .......... .......... 99% 34.9M 0s\n", + "590750K .......... .......... .......... .......... .......... 99% 48.7M 0s\n", + "590800K .......... .......... .......... .......... .......... 99% 66.2M 0s\n", + "590850K .......... .......... .......... .......... .......... 99% 65.5M 0s\n", + "590900K .......... .......... .......... .......... .......... 99% 34.3M 0s\n", + "590950K .......... .......... .......... .......... .......... 99% 59.9M 0s\n", + "591000K .......... .......... .......... .......... .......... 99% 44.8M 0s\n", + "591050K .......... .......... .......... .......... .......... 99% 68.5M 0s\n", + "591100K .......... .......... .......... .......... .......... 99% 42.4M 0s\n", + "591150K .......... .......... .......... .......... .......... 99% 35.8M 0s\n", + "591200K .......... .......... .......... .......... .......... 99% 44.3M 0s\n", + "591250K .......... .......... .......... .......... .......... 99% 66.2M 0s\n", + "591300K .......... .......... .......... .......... .......... 99% 75.6M 0s\n", + "591350K .......... .......... .......... .......... .......... 99% 31.9M 0s\n", + "591400K .......... .......... .......... .......... .......... 99% 38.8M 0s\n", + "591450K .......... .......... .......... .......... .......... 99% 53.8M 0s\n", + "591500K .......... .......... .......... .......... .......... 99% 68.6M 0s\n", + "591550K .......... .......... .......... .......... .......... 99% 57.9M 0s\n", + "591600K .......... .......... 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.......... .......... .......... 99% 42.9M 0s\n", + "593450K .......... .......... .......... .......... .......... 99% 43.4M 0s\n", + "593500K .......... .......... .......... .......... .......... 99% 30.7M 0s\n", + "593550K .......... .......... .......... .......... .......... 99% 35.4M 0s\n", + "593600K .......... .......... .......... .......... .......... 99% 31.1M 0s\n", + "593650K .......... .......... .......... .......... .......... 99% 29.1M 0s\n", + "593700K .......... .......... .......... .......... .......... 99% 40.6M 0s\n", + "593750K .......... .......... .......... .......... .......... 99% 36.9M 0s\n", + "593800K .......... .......... .......... .......... .......... 99% 30.3M 0s\n", + "593850K .......... .......... .......... .......... .......... 99% 61.9M 0s\n", + "593900K .......... .......... .......... .......... .......... 99% 71.2M 0s\n", + "593950K .......... .......... .......... .......... .......... 99% 67.3M 0s\n", + "594000K .......... .......... .......... .......... .......... 99% 62.1M 0s\n", + "594050K .......... .......... .......... .......... .......... 99% 59.3M 0s\n", + "594100K .......... .......... .......... .......... .......... 99% 56.1M 0s\n", + "594150K .......... .......... .......... .......... .......... 99% 60.8M 0s\n", + "594200K .......... .......... .......... .......... .......... 99% 56.1M 0s\n", + "594250K .......... .......... .......... .......... .......... 99% 71.0M 0s\n", + "594300K .......... .......... .......... .......... .......... 99% 77.4M 0s\n", + "594350K .......... .......... .......... .......... .......... 99% 54.3M 0s\n", + "594400K .......... .......... .......... .......... .......... 99% 45.3M 0s\n", + "594450K .......... .......... .......... .......... .......... 99% 59.6M 0s\n", + "594500K .......... .......... .......... .......... .......... 99% 62.8M 0s\n", + "594550K .......... .......... .......... .......... .......... 99% 3.68M 0s\n", + "594600K .......... .......... .......... .......... .......... 99% 32.6M 0s\n", + "594650K .......... .......... .......... .......... .......... 99% 50.9M 0s\n", + "594700K .......... .......... .......... 100% 54.3M=20s\n", "\n", - "2023-04-03 22:45:40 (35.8 MB/s) - ‘oceanspy_get_started.tar.gz’ saved [609004013/609004013]\n", + "2023-04-11 23:45:56 (29.5 MB/s) - ‘oceanspy_get_started.tar.gz’ saved [609004013/609004013]\n", "\n" ] }, @@ -12869,11 +12559,11 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:01.824915Z", - "iopub.status.busy": "2023-04-04T02:47:01.824254Z", - "iopub.status.idle": "2023-04-04T02:47:02.215253Z", - "shell.execute_reply": "2023-04-04T02:47:02.212585Z", - "shell.execute_reply.started": "2023-04-04T02:47:01.824813Z" + "iopub.execute_input": "2023-04-12T03:46:50.177238Z", + "iopub.status.busy": "2023-04-12T03:46:50.176649Z", + "iopub.status.idle": "2023-04-12T03:46:50.556382Z", + "shell.execute_reply": "2023-04-12T03:46:50.554440Z", + "shell.execute_reply.started": "2023-04-12T03:46:50.177180Z" } }, "outputs": [ @@ -12927,11 +12617,11 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:02.219008Z", - "iopub.status.busy": "2023-04-04T02:47:02.218191Z", - "iopub.status.idle": "2023-04-04T02:47:02.627340Z", - "shell.execute_reply": "2023-04-04T02:47:02.624565Z", - "shell.execute_reply.started": "2023-04-04T02:47:02.218953Z" + "iopub.execute_input": "2023-04-12T03:46:50.564387Z", + "iopub.status.busy": "2023-04-12T03:46:50.563759Z", + "iopub.status.idle": "2023-04-12T03:46:50.954008Z", + "shell.execute_reply": "2023-04-12T03:46:50.951571Z", + "shell.execute_reply.started": "2023-04-12T03:46:50.564327Z" } }, "outputs": [ @@ -12989,11 +12679,11 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:02.630722Z", - "iopub.status.busy": "2023-04-04T02:47:02.630125Z", - "iopub.status.idle": "2023-04-04T02:47:03.073064Z", - "shell.execute_reply": "2023-04-04T02:47:03.064028Z", - "shell.execute_reply.started": "2023-04-04T02:47:02.630666Z" + "iopub.execute_input": "2023-04-12T03:46:50.956870Z", + "iopub.status.busy": "2023-04-12T03:46:50.956310Z", + "iopub.status.idle": "2023-04-12T03:46:51.370133Z", + "shell.execute_reply": "2023-04-12T03:46:51.367445Z", + "shell.execute_reply.started": "2023-04-12T03:46:50.956816Z" } }, "outputs": [ @@ -13064,11 +12754,11 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:03.086080Z", - "iopub.status.busy": "2023-04-04T02:47:03.085480Z", - "iopub.status.idle": "2023-04-04T02:47:09.344897Z", - "shell.execute_reply": "2023-04-04T02:47:09.341009Z", - "shell.execute_reply.started": "2023-04-04T02:47:03.086024Z" + "iopub.execute_input": "2023-04-12T03:46:51.373410Z", + "iopub.status.busy": "2023-04-12T03:46:51.372778Z", + "iopub.status.idle": "2023-04-12T03:46:53.004221Z", + "shell.execute_reply": "2023-04-12T03:46:53.001462Z", + "shell.execute_reply.started": "2023-04-12T03:46:51.373350Z" } }, "outputs": [ @@ -13102,11 +12792,11 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:09.349943Z", - "iopub.status.busy": "2023-04-04T02:47:09.348913Z", - "iopub.status.idle": "2023-04-04T02:47:14.506219Z", - "shell.execute_reply": "2023-04-04T02:47:14.504239Z", - "shell.execute_reply.started": "2023-04-04T02:47:09.349832Z" + "iopub.execute_input": "2023-04-12T03:46:53.007377Z", + "iopub.status.busy": "2023-04-12T03:46:53.006758Z", + "iopub.status.idle": "2023-04-12T03:46:54.371599Z", + "shell.execute_reply": "2023-04-12T03:46:54.369114Z", + "shell.execute_reply.started": "2023-04-12T03:46:53.007313Z" } }, "outputs": [ @@ -13153,11 +12843,11 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:14.511021Z", - "iopub.status.busy": "2023-04-04T02:47:14.510413Z", - "iopub.status.idle": "2023-04-04T02:47:14.538553Z", - "shell.execute_reply": "2023-04-04T02:47:14.536764Z", - "shell.execute_reply.started": "2023-04-04T02:47:14.510965Z" + "iopub.execute_input": "2023-04-12T03:46:54.374367Z", + "iopub.status.busy": "2023-04-12T03:46:54.373754Z", + "iopub.status.idle": "2023-04-12T03:46:54.401005Z", + "shell.execute_reply": "2023-04-12T03:46:54.398749Z", + "shell.execute_reply.started": "2023-04-12T03:46:54.374272Z" } }, "outputs": [ @@ -13193,11 +12883,11 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:14.541424Z", - "iopub.status.busy": "2023-04-04T02:47:14.540805Z", - "iopub.status.idle": "2023-04-04T02:47:14.678714Z", - "shell.execute_reply": "2023-04-04T02:47:14.676065Z", - "shell.execute_reply.started": "2023-04-04T02:47:14.541371Z" + "iopub.execute_input": "2023-04-12T03:46:54.403900Z", + "iopub.status.busy": "2023-04-12T03:46:54.403325Z", + "iopub.status.idle": "2023-04-12T03:46:54.525351Z", + "shell.execute_reply": "2023-04-12T03:46:54.523050Z", + "shell.execute_reply.started": "2023-04-12T03:46:54.403848Z" } }, "outputs": [ @@ -13210,6 +12900,9 @@ "Original oceandataset:\n", "{'time_midp': 3, 'Zl': 55, 'Y': 154, 'X': 207, 'Z': 55, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'Zp1': 56, 'Zu': 55}\n", "\n", + "X Axis (not periodic, boundary=None):\n", + " * center X --> outer\n", + " * outer Xp1 --> center\n", "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", " * outer Yp1 --> center\n", @@ -13218,9 +12911,6 @@ " * left Zl --> center\n", " * outer Zp1 --> center\n", " * right Zu --> center\n", - "X Axis (not periodic, boundary=None):\n", - " * center X --> outer\n", - " * outer Xp1 --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", " * outer time --> center\n", @@ -13228,12 +12918,12 @@ "New oceandataset:\n", "{'time_midp': 3, 'Zl': 1, 'Y': 154, 'X': 207, 'Z': 1, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'Zp1': 1, 'Zu': 1}\n", "\n", - "Y Axis (not periodic, boundary=None):\n", - " * center Y --> outer\n", - " * outer Yp1 --> center\n", "X Axis (not periodic, boundary=None):\n", " * center X --> outer\n", " * outer Xp1 --> center\n", + "Y Axis (not periodic, boundary=None):\n", + " * center Y --> outer\n", + " * outer Yp1 --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", " * outer time --> center\n" @@ -13285,11 +12975,11 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:14.686925Z", - "iopub.status.busy": "2023-04-04T02:47:14.686347Z", - "iopub.status.idle": "2023-04-04T02:47:14.773871Z", - "shell.execute_reply": "2023-04-04T02:47:14.771396Z", - "shell.execute_reply.started": "2023-04-04T02:47:14.686869Z" + "iopub.execute_input": "2023-04-12T03:46:54.528061Z", + "iopub.status.busy": "2023-04-12T03:46:54.527511Z", + "iopub.status.idle": "2023-04-12T03:46:54.602725Z", + "shell.execute_reply": "2023-04-12T03:46:54.600675Z", + "shell.execute_reply.started": "2023-04-12T03:46:54.528009Z" } }, "outputs": [ @@ -13334,11 +13024,11 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:14.777258Z", - "iopub.status.busy": "2023-04-04T02:47:14.776673Z", - "iopub.status.idle": "2023-04-04T02:47:14.884015Z", - "shell.execute_reply": "2023-04-04T02:47:14.872333Z", - "shell.execute_reply.started": "2023-04-04T02:47:14.777204Z" + "iopub.execute_input": "2023-04-12T03:46:54.605546Z", + "iopub.status.busy": "2023-04-12T03:46:54.604912Z", + "iopub.status.idle": "2023-04-12T03:46:54.698373Z", + "shell.execute_reply": "2023-04-12T03:46:54.696164Z", + "shell.execute_reply.started": "2023-04-12T03:46:54.605490Z" } }, "outputs": [ @@ -13406,11 +13096,11 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:14.887700Z", - "iopub.status.busy": "2023-04-04T02:47:14.887094Z", - "iopub.status.idle": "2023-04-04T02:47:30.653132Z", - "shell.execute_reply": "2023-04-04T02:47:30.650607Z", - "shell.execute_reply.started": "2023-04-04T02:47:14.887636Z" + "iopub.execute_input": "2023-04-12T03:46:54.707460Z", + "iopub.status.busy": "2023-04-12T03:46:54.706811Z", + "iopub.status.idle": "2023-04-12T03:46:55.935582Z", + "shell.execute_reply": "2023-04-12T03:46:55.933342Z", + "shell.execute_reply.started": "2023-04-12T03:46:54.707402Z" } }, "outputs": [ @@ -13476,11 +13166,11 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:30.656613Z", - "iopub.status.busy": "2023-04-04T02:47:30.655985Z", - "iopub.status.idle": "2023-04-04T02:47:30.931672Z", - "shell.execute_reply": "2023-04-04T02:47:30.928393Z", - "shell.execute_reply.started": "2023-04-04T02:47:30.656556Z" + "iopub.execute_input": "2023-04-12T03:46:55.945387Z", + "iopub.status.busy": "2023-04-12T03:46:55.944748Z", + "iopub.status.idle": "2023-04-12T03:46:56.194222Z", + "shell.execute_reply": "2023-04-12T03:46:56.191784Z", + "shell.execute_reply.started": "2023-04-12T03:46:55.945327Z" }, "scrolled": true }, @@ -13516,11 +13206,11 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:30.935530Z", - "iopub.status.busy": "2023-04-04T02:47:30.934910Z", - "iopub.status.idle": "2023-04-04T02:47:31.549823Z", - "shell.execute_reply": "2023-04-04T02:47:31.542510Z", - "shell.execute_reply.started": "2023-04-04T02:47:30.935472Z" + "iopub.execute_input": "2023-04-12T03:46:56.196852Z", + "iopub.status.busy": "2023-04-12T03:46:56.196238Z", + "iopub.status.idle": "2023-04-12T03:46:56.771645Z", + "shell.execute_reply": "2023-04-12T03:46:56.768406Z", + "shell.execute_reply.started": "2023-04-12T03:46:56.196795Z" } }, "outputs": [ @@ -13554,11 +13244,11 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:31.558411Z", - "iopub.status.busy": "2023-04-04T02:47:31.557749Z", - "iopub.status.idle": "2023-04-04T02:47:32.998218Z", - "shell.execute_reply": "2023-04-04T02:47:32.994992Z", - "shell.execute_reply.started": "2023-04-04T02:47:31.558340Z" + "iopub.execute_input": "2023-04-12T03:46:56.776181Z", + "iopub.status.busy": "2023-04-12T03:46:56.775011Z", + "iopub.status.idle": "2023-04-12T03:46:58.077900Z", + "shell.execute_reply": "2023-04-12T03:46:58.075730Z", + "shell.execute_reply.started": "2023-04-12T03:46:56.776084Z" } }, "outputs": [ @@ -13649,11 +13339,11 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:33.001801Z", - "iopub.status.busy": "2023-04-04T02:47:33.001153Z", - "iopub.status.idle": "2023-04-04T02:47:36.897015Z", - "shell.execute_reply": "2023-04-04T02:47:36.893999Z", - "shell.execute_reply.started": "2023-04-04T02:47:33.001743Z" + "iopub.execute_input": "2023-04-12T03:46:58.080894Z", + "iopub.status.busy": "2023-04-12T03:46:58.080269Z", + "iopub.status.idle": "2023-04-12T03:47:01.266739Z", + "shell.execute_reply": "2023-04-12T03:47:01.264308Z", + "shell.execute_reply.started": "2023-04-12T03:46:58.080838Z" } }, "outputs": [ @@ -13688,11 +13378,11 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:36.902615Z", - "iopub.status.busy": "2023-04-04T02:47:36.901534Z", - "iopub.status.idle": "2023-04-04T02:47:39.547764Z", - "shell.execute_reply": "2023-04-04T02:47:39.545694Z", - "shell.execute_reply.started": "2023-04-04T02:47:36.902522Z" + "iopub.execute_input": "2023-04-12T03:47:01.269836Z", + "iopub.status.busy": "2023-04-12T03:47:01.269175Z", + "iopub.status.idle": "2023-04-12T03:47:03.138567Z", + "shell.execute_reply": "2023-04-12T03:47:03.136299Z", + "shell.execute_reply.started": "2023-04-12T03:47:01.269778Z" } }, "outputs": [ @@ -13748,11 +13438,11 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:39.550124Z", - "iopub.status.busy": "2023-04-04T02:47:39.549545Z", - "iopub.status.idle": "2023-04-04T02:47:42.313705Z", - "shell.execute_reply": "2023-04-04T02:47:42.311347Z", - "shell.execute_reply.started": "2023-04-04T02:47:39.550068Z" + "iopub.execute_input": "2023-04-12T03:47:03.141573Z", + "iopub.status.busy": "2023-04-12T03:47:03.140944Z", + "iopub.status.idle": "2023-04-12T03:47:04.966548Z", + "shell.execute_reply": "2023-04-12T03:47:04.964138Z", + "shell.execute_reply.started": "2023-04-12T03:47:03.141517Z" } }, "outputs": [ @@ -13811,11 +13501,11 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:42.317395Z", - "iopub.status.busy": "2023-04-04T02:47:42.316773Z", - "iopub.status.idle": "2023-04-04T02:47:56.720319Z", - "shell.execute_reply": "2023-04-04T02:47:56.716727Z", - "shell.execute_reply.started": "2023-04-04T02:47:42.317337Z" + "iopub.execute_input": "2023-04-12T03:47:04.969635Z", + "iopub.status.busy": "2023-04-12T03:47:04.969019Z", + "iopub.status.idle": "2023-04-12T03:47:15.435218Z", + "shell.execute_reply": "2023-04-12T03:47:15.431469Z", + "shell.execute_reply.started": "2023-04-12T03:47:04.969579Z" } }, "outputs": [ @@ -13916,11 +13606,11 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:56.730224Z", - "iopub.status.busy": "2023-04-04T02:47:56.726252Z", - "iopub.status.idle": "2023-04-04T02:47:56.746042Z", - "shell.execute_reply": "2023-04-04T02:47:56.742892Z", - "shell.execute_reply.started": "2023-04-04T02:47:56.730137Z" + "iopub.execute_input": "2023-04-12T03:47:15.440267Z", + "iopub.status.busy": "2023-04-12T03:47:15.439554Z", + "iopub.status.idle": "2023-04-12T03:47:15.454177Z", + "shell.execute_reply": "2023-04-12T03:47:15.452490Z", + "shell.execute_reply.started": "2023-04-12T03:47:15.440169Z" } }, "outputs": [ @@ -13962,11 +13652,11 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:47:56.763865Z", - "iopub.status.busy": "2023-04-04T02:47:56.763221Z", - "iopub.status.idle": "2023-04-04T02:47:57.752207Z", - "shell.execute_reply": "2023-04-04T02:47:57.749440Z", - "shell.execute_reply.started": "2023-04-04T02:47:56.763793Z" + "iopub.execute_input": "2023-04-12T03:47:15.457535Z", + "iopub.status.busy": "2023-04-12T03:47:15.456753Z", + "iopub.status.idle": "2023-04-12T03:47:16.295076Z", + "shell.execute_reply": "2023-04-12T03:47:16.292705Z", + "shell.execute_reply.started": "2023-04-12T03:47:15.457482Z" } }, "outputs": [ diff --git a/docs/Kogur.ipynb b/docs/Kogur.ipynb index 46df8103..03a59f6d 100644 --- a/docs/Kogur.ipynb +++ b/docs/Kogur.ipynb @@ -14,11 +14,11 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:04:40.283048Z", - "iopub.status.busy": "2023-04-04T02:04:40.282458Z", - "iopub.status.idle": "2023-04-04T02:05:00.025362Z", - "shell.execute_reply": "2023-04-04T02:05:00.022917Z", - "shell.execute_reply.started": "2023-04-04T02:04:40.282991Z" + "iopub.execute_input": "2023-04-12T02:52:31.349967Z", + "iopub.status.busy": "2023-04-12T02:52:31.349105Z", + "iopub.status.idle": "2023-04-12T02:52:50.549942Z", + "shell.execute_reply": "2023-04-12T02:52:50.547500Z", + "shell.execute_reply.started": "2023-04-12T02:52:31.349883Z" }, "tags": [] }, @@ -45,12 +45,13 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:05:00.030115Z", - "iopub.status.busy": "2023-04-04T02:05:00.029011Z", - "iopub.status.idle": "2023-04-04T02:05:04.664095Z", - "shell.execute_reply": "2023-04-04T02:05:04.661109Z", - "shell.execute_reply.started": "2023-04-04T02:05:00.030059Z" - } + "iopub.execute_input": "2023-04-12T02:52:50.554912Z", + "iopub.status.busy": "2023-04-12T02:52:50.553689Z", + "iopub.status.idle": "2023-04-12T02:52:55.298961Z", + "shell.execute_reply": "2023-04-12T02:52:55.296481Z", + "shell.execute_reply.started": "2023-04-12T02:52:50.554854Z" + }, + "tags": [] }, "outputs": [ { @@ -60,7 +61,7 @@ "
    \n", "
    \n", "

    Client

    \n", - "

    Client-1b09f07f-d28d-11ed-8a0f-0242ac110004

    \n", + "

    Client-1d595cc6-d8dd-11ed-8ace-0242ac110006

    \n", " \n", "\n", " \n", @@ -91,7 +92,7 @@ " \n", "
    \n", "

    LocalCluster

    \n", - "

    ab52b2fa

    \n", + "

    f7012a2d

    \n", "
    \n", " \n", "
    \n", @@ -128,11 +129,11 @@ "
    \n", "
    \n", "

    Scheduler

    \n", - "

    Scheduler-ea8e714a-9aed-4d45-9aff-85a870d4d837

    \n", + "

    Scheduler-8b655f88-6e9c-4bdd-a062-16a2ee0522a4

    \n", " \n", " \n", " \n", "
    \n", - " Comm: tcp://127.0.0.1:45617\n", + " Comm: tcp://127.0.0.1:39691\n", " \n", " Workers: 4\n", @@ -174,7 +175,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -219,7 +220,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:43234\n", + " Comm: tcp://127.0.0.1:37895\n", " \n", " Total threads: 1\n", @@ -182,7 +183,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:41307/status\n", + " Dashboard: http://127.0.0.1:35787/status\n", " \n", " Memory: 25.00 GiB\n", @@ -190,13 +191,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:33098\n", + " Nanny: tcp://127.0.0.1:35636\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-6xq73ngc\n", + " Local directory: /tmp/dask-worker-space/worker-dg400ibu\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -264,7 +265,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:39180\n", + " Comm: tcp://127.0.0.1:46138\n", " \n", " Total threads: 1\n", @@ -227,7 +228,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:34694/status\n", + " Dashboard: http://127.0.0.1:45597/status\n", " \n", " Memory: 25.00 GiB\n", @@ -235,13 +236,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:38311\n", + " Nanny: tcp://127.0.0.1:35450\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-5ovv0vck\n", + " Local directory: /tmp/dask-worker-space/worker-38hgqqw4\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -309,7 +310,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:38105\n", + " Comm: tcp://127.0.0.1:33025\n", " \n", " Total threads: 1\n", @@ -272,7 +273,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:43995/status\n", + " Dashboard: http://127.0.0.1:39132/status\n", " \n", " Memory: 25.00 GiB\n", @@ -280,13 +281,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:34886\n", + " Nanny: tcp://127.0.0.1:42160\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-fjlk0z28\n", + " Local directory: /tmp/dask-worker-space/worker-e2fc0n1u\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -358,7 +359,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -386,11 +387,11 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:05:04.668230Z", - "iopub.status.busy": "2023-04-04T02:05:04.667609Z", - "iopub.status.idle": "2023-04-04T02:06:17.549032Z", - "shell.execute_reply": "2023-04-04T02:06:17.542340Z", - "shell.execute_reply.started": "2023-04-04T02:05:04.668148Z" + "iopub.execute_input": "2023-04-12T02:52:55.303764Z", + "iopub.status.busy": "2023-04-12T02:52:55.302362Z", + "iopub.status.idle": "2023-04-12T02:54:04.872446Z", + "shell.execute_reply": "2023-04-12T02:54:04.867483Z", + "shell.execute_reply.started": "2023-04-12T02:52:55.303674Z" } }, "outputs": [ @@ -427,11 +428,11 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:06:17.557981Z", - "iopub.status.busy": "2023-04-04T02:06:17.557380Z", - "iopub.status.idle": "2023-04-04T02:06:17.612699Z", - "shell.execute_reply": "2023-04-04T02:06:17.610590Z", - "shell.execute_reply.started": "2023-04-04T02:06:17.557926Z" + "iopub.execute_input": "2023-04-12T02:54:04.883828Z", + "iopub.status.busy": "2023-04-12T02:54:04.883107Z", + "iopub.status.idle": "2023-04-12T02:54:04.918816Z", + "shell.execute_reply": "2023-04-12T02:54:04.916435Z", + "shell.execute_reply.started": "2023-04-12T02:54:04.883767Z" } }, "outputs": [], @@ -460,11 +461,11 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:06:17.615506Z", - "iopub.status.busy": "2023-04-04T02:06:17.614881Z", - "iopub.status.idle": "2023-04-04T02:06:41.130547Z", - "shell.execute_reply": "2023-04-04T02:06:41.127525Z", - "shell.execute_reply.started": "2023-04-04T02:06:17.615435Z" + "iopub.execute_input": "2023-04-12T02:54:04.921983Z", + "iopub.status.busy": "2023-04-12T02:54:04.921229Z", + "iopub.status.idle": "2023-04-12T02:54:28.905381Z", + "shell.execute_reply": "2023-04-12T02:54:28.897381Z", + "shell.execute_reply.started": "2023-04-12T02:54:04.921924Z" } }, "outputs": [ @@ -529,11 +530,11 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:06:41.142433Z", - "iopub.status.busy": "2023-04-04T02:06:41.141752Z", - "iopub.status.idle": "2023-04-04T02:06:57.728612Z", - "shell.execute_reply": "2023-04-04T02:06:57.725891Z", - "shell.execute_reply.started": "2023-04-04T02:06:41.142376Z" + "iopub.execute_input": "2023-04-12T02:54:28.912146Z", + "iopub.status.busy": "2023-04-12T02:54:28.911538Z", + "iopub.status.idle": "2023-04-12T02:54:47.313145Z", + "shell.execute_reply": "2023-04-12T02:54:47.309005Z", + "shell.execute_reply.started": "2023-04-12T02:54:28.912087Z" } }, "outputs": [ @@ -578,11 +579,11 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:06:57.731037Z", - "iopub.status.busy": "2023-04-04T02:06:57.730443Z", - "iopub.status.idle": "2023-04-04T02:07:02.430246Z", - "shell.execute_reply": "2023-04-04T02:07:02.427831Z", - "shell.execute_reply.started": "2023-04-04T02:06:57.730982Z" + "iopub.execute_input": "2023-04-12T02:54:47.316542Z", + "iopub.status.busy": "2023-04-12T02:54:47.315722Z", + "iopub.status.idle": "2023-04-12T02:54:52.230441Z", + "shell.execute_reply": "2023-04-12T02:54:52.227445Z", + "shell.execute_reply.started": "2023-04-12T02:54:47.316480Z" } }, "outputs": [ @@ -618,11 +619,11 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:02.433645Z", - "iopub.status.busy": "2023-04-04T02:07:02.432993Z", - "iopub.status.idle": "2023-04-04T02:07:04.211310Z", - "shell.execute_reply": "2023-04-04T02:07:04.208550Z", - "shell.execute_reply.started": "2023-04-04T02:07:02.433588Z" + "iopub.execute_input": "2023-04-12T02:54:52.233397Z", + "iopub.status.busy": "2023-04-12T02:54:52.232757Z", + "iopub.status.idle": "2023-04-12T02:54:54.017551Z", + "shell.execute_reply": "2023-04-12T02:54:54.014824Z", + "shell.execute_reply.started": "2023-04-12T02:54:52.233334Z" } }, "outputs": [ @@ -631,12 +632,9 @@ "output_type": "stream", "text": [ "\n", - "Y Axis (not periodic, boundary=None):\n", - " * center Y --> outer\n", - " * outer Yp1 --> center\n", - "X Axis (not periodic, boundary=None):\n", - " * center X --> outer\n", - " * outer Xp1 --> center\n", + "mooring Axis (not periodic, boundary=None):\n", + " * center mooring_midp --> outer\n", + " * outer mooring --> center\n", "time Axis (not periodic, boundary=None):\n", " * center time_midp --> outer\n", " * outer time --> center\n", @@ -645,9 +643,12 @@ " * outer Zp1 --> center\n", " * right Zu --> center\n", " * left Zl --> center\n", - "mooring Axis (not periodic, boundary=None):\n", - " * center mooring_midp --> outer\n", - " * outer mooring --> center\n", + "Y Axis (not periodic, boundary=None):\n", + " * center Y --> outer\n", + " * outer Yp1 --> center\n", + "X Axis (not periodic, boundary=None):\n", + " * center X --> outer\n", + " * outer Xp1 --> center\n", "\n", "Coordinates:\n", " * Z (Z) float64 -1.0 -3.5 -7.0 ... -1.732e+03 -1.746e+03\n", @@ -740,11 +741,11 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:04.215854Z", - "iopub.status.busy": "2023-04-04T02:07:04.214162Z", - "iopub.status.idle": "2023-04-04T02:07:06.221354Z", - "shell.execute_reply": "2023-04-04T02:07:06.219016Z", - "shell.execute_reply.started": "2023-04-04T02:07:04.215797Z" + "iopub.execute_input": "2023-04-12T02:54:54.020408Z", + "iopub.status.busy": "2023-04-12T02:54:54.019771Z", + "iopub.status.idle": "2023-04-12T02:54:56.100192Z", + "shell.execute_reply": "2023-04-12T02:54:56.097945Z", + "shell.execute_reply.started": "2023-04-12T02:54:54.020347Z" } }, "outputs": [ @@ -792,11 +793,11 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:06.232432Z", - "iopub.status.busy": "2023-04-04T02:07:06.231800Z", - "iopub.status.idle": "2023-04-04T02:07:14.392459Z", - "shell.execute_reply": "2023-04-04T02:07:14.389747Z", - "shell.execute_reply.started": "2023-04-04T02:07:06.232375Z" + "iopub.execute_input": "2023-04-12T02:54:56.109801Z", + "iopub.status.busy": "2023-04-12T02:54:56.109121Z", + "iopub.status.idle": "2023-04-12T02:55:04.531263Z", + "shell.execute_reply": "2023-04-12T02:55:04.527562Z", + "shell.execute_reply.started": "2023-04-12T02:54:56.109741Z" } }, "outputs": [ @@ -841,11 +842,11 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:14.395624Z", - "iopub.status.busy": "2023-04-04T02:07:14.394988Z", - "iopub.status.idle": "2023-04-04T02:07:15.519798Z", - "shell.execute_reply": "2023-04-04T02:07:15.517559Z", - "shell.execute_reply.started": "2023-04-04T02:07:14.395567Z" + "iopub.execute_input": "2023-04-12T02:55:04.534587Z", + "iopub.status.busy": "2023-04-12T02:55:04.533930Z", + "iopub.status.idle": "2023-04-12T02:55:05.633896Z", + "shell.execute_reply": "2023-04-12T02:55:05.629463Z", + "shell.execute_reply.started": "2023-04-12T02:55:04.534526Z" } }, "outputs": [ @@ -886,11 +887,11 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:15.522873Z", - "iopub.status.busy": "2023-04-04T02:07:15.522233Z", - "iopub.status.idle": "2023-04-04T02:07:18.364500Z", - "shell.execute_reply": "2023-04-04T02:07:18.361347Z", - "shell.execute_reply.started": "2023-04-04T02:07:15.522818Z" + "iopub.execute_input": "2023-04-12T02:55:05.638907Z", + "iopub.status.busy": "2023-04-12T02:55:05.638247Z", + "iopub.status.idle": "2023-04-12T02:55:08.461067Z", + "shell.execute_reply": "2023-04-12T02:55:08.458678Z", + "shell.execute_reply.started": "2023-04-12T02:55:05.638846Z" } }, "outputs": [ @@ -938,11 +939,11 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:18.369358Z", - "iopub.status.busy": "2023-04-04T02:07:18.368725Z", - "iopub.status.idle": "2023-04-04T02:07:19.838092Z", - "shell.execute_reply": "2023-04-04T02:07:19.835485Z", - "shell.execute_reply.started": "2023-04-04T02:07:18.369264Z" + "iopub.execute_input": "2023-04-12T02:55:08.464603Z", + "iopub.status.busy": "2023-04-12T02:55:08.463926Z", + "iopub.status.idle": "2023-04-12T02:55:10.064617Z", + "shell.execute_reply": "2023-04-12T02:55:10.062136Z", + "shell.execute_reply.started": "2023-04-12T02:55:08.464540Z" } }, "outputs": [ @@ -998,7 +999,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -1108,11 +1109,11 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:19.842530Z", - "iopub.status.busy": "2023-04-04T02:07:19.841403Z", - "iopub.status.idle": "2023-04-04T02:07:20.449260Z", - "shell.execute_reply": "2023-04-04T02:07:20.445609Z", - "shell.execute_reply.started": "2023-04-04T02:07:19.842418Z" + "iopub.execute_input": "2023-04-12T02:55:10.067760Z", + "iopub.status.busy": "2023-04-12T02:55:10.067088Z", + "iopub.status.idle": "2023-04-12T02:55:10.691867Z", + "shell.execute_reply": "2023-04-12T02:55:10.689392Z", + "shell.execute_reply.started": "2023-04-12T02:55:10.067699Z" } }, "outputs": [ @@ -1152,11 +1153,11 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:20.455833Z", - "iopub.status.busy": "2023-04-04T02:07:20.454656Z", - "iopub.status.idle": "2023-04-04T02:07:21.574002Z", - "shell.execute_reply": "2023-04-04T02:07:21.571225Z", - "shell.execute_reply.started": "2023-04-04T02:07:20.455747Z" + "iopub.execute_input": "2023-04-12T02:55:10.695850Z", + "iopub.status.busy": "2023-04-12T02:55:10.695178Z", + "iopub.status.idle": "2023-04-12T02:55:11.819161Z", + "shell.execute_reply": "2023-04-12T02:55:11.816750Z", + "shell.execute_reply.started": "2023-04-12T02:55:10.695790Z" } }, "outputs": [ @@ -1214,11 +1215,11 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:21.577612Z", - "iopub.status.busy": "2023-04-04T02:07:21.576886Z", - "iopub.status.idle": "2023-04-04T02:07:31.741798Z", - "shell.execute_reply": "2023-04-04T02:07:31.738975Z", - "shell.execute_reply.started": "2023-04-04T02:07:21.577556Z" + "iopub.execute_input": "2023-04-12T02:55:11.821795Z", + "iopub.status.busy": "2023-04-12T02:55:11.821126Z", + "iopub.status.idle": "2023-04-12T02:55:22.109950Z", + "shell.execute_reply": "2023-04-12T02:55:22.105836Z", + "shell.execute_reply.started": "2023-04-12T02:55:11.821732Z" } }, "outputs": [ @@ -1309,11 +1310,11 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:31.745555Z", - "iopub.status.busy": "2023-04-04T02:07:31.744914Z", - "iopub.status.idle": "2023-04-04T02:07:39.720791Z", - "shell.execute_reply": "2023-04-04T02:07:39.718043Z", - "shell.execute_reply.started": "2023-04-04T02:07:31.745498Z" + "iopub.execute_input": "2023-04-12T02:55:22.114389Z", + "iopub.status.busy": "2023-04-12T02:55:22.113720Z", + "iopub.status.idle": "2023-04-12T02:55:29.843719Z", + "shell.execute_reply": "2023-04-12T02:55:29.841007Z", + "shell.execute_reply.started": "2023-04-12T02:55:22.114325Z" } }, "outputs": [ @@ -1350,11 +1351,11 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:39.723335Z", - "iopub.status.busy": "2023-04-04T02:07:39.722712Z", - "iopub.status.idle": "2023-04-04T02:07:39.858675Z", - "shell.execute_reply": "2023-04-04T02:07:39.856156Z", - "shell.execute_reply.started": "2023-04-04T02:07:39.723240Z" + "iopub.execute_input": "2023-04-12T02:55:29.847926Z", + "iopub.status.busy": "2023-04-12T02:55:29.846044Z", + "iopub.status.idle": "2023-04-12T02:55:29.999568Z", + "shell.execute_reply": "2023-04-12T02:55:29.995689Z", + "shell.execute_reply.started": "2023-04-12T02:55:29.847861Z" } }, "outputs": [ @@ -1395,11 +1396,11 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:07:39.862216Z", - "iopub.status.busy": "2023-04-04T02:07:39.861640Z", - "iopub.status.idle": "2023-04-04T02:08:39.896175Z", - "shell.execute_reply": "2023-04-04T02:08:39.891385Z", - "shell.execute_reply.started": "2023-04-04T02:07:39.862163Z" + "iopub.execute_input": "2023-04-12T02:55:30.003050Z", + "iopub.status.busy": "2023-04-12T02:55:30.002457Z", + "iopub.status.idle": "2023-04-12T02:56:29.535884Z", + "shell.execute_reply": "2023-04-12T02:56:29.531085Z", + "shell.execute_reply.started": "2023-04-12T02:55:30.002990Z" }, "tags": [] }, @@ -1450,11 +1451,11 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:08:39.902558Z", - "iopub.status.busy": "2023-04-04T02:08:39.901789Z", - "iopub.status.idle": "2023-04-04T02:08:40.162413Z", - "shell.execute_reply": "2023-04-04T02:08:40.159631Z", - "shell.execute_reply.started": "2023-04-04T02:08:39.902467Z" + "iopub.execute_input": "2023-04-12T02:56:29.541483Z", + "iopub.status.busy": "2023-04-12T02:56:29.540664Z", + "iopub.status.idle": "2023-04-12T02:56:29.817438Z", + "shell.execute_reply": "2023-04-12T02:56:29.810575Z", + "shell.execute_reply.started": "2023-04-12T02:56:29.541384Z" } }, "outputs": [ @@ -1498,11 +1499,11 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:08:40.166533Z", - "iopub.status.busy": "2023-04-04T02:08:40.165913Z", - "iopub.status.idle": "2023-04-04T02:08:50.536470Z", - "shell.execute_reply": "2023-04-04T02:08:50.534547Z", - "shell.execute_reply.started": "2023-04-04T02:08:40.166478Z" + "iopub.execute_input": "2023-04-12T02:56:29.821138Z", + "iopub.status.busy": "2023-04-12T02:56:29.820548Z", + "iopub.status.idle": "2023-04-12T02:56:39.651581Z", + "shell.execute_reply": "2023-04-12T02:56:39.634525Z", + "shell.execute_reply.started": "2023-04-12T02:56:29.821080Z" } }, "outputs": [ diff --git a/docs/Particles.ipynb b/docs/Particles.ipynb index 1e1f1486..973cd737 100644 --- a/docs/Particles.ipynb +++ b/docs/Particles.ipynb @@ -23,11 +23,11 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:12:30.434500Z", - "iopub.status.busy": "2023-04-04T02:12:30.433851Z", - "iopub.status.idle": "2023-04-04T02:12:30.472236Z", - "shell.execute_reply": "2023-04-04T02:12:30.470612Z", - "shell.execute_reply.started": "2023-04-04T02:12:30.434440Z" + "iopub.execute_input": "2023-04-12T02:42:31.263143Z", + "iopub.status.busy": "2023-04-12T02:42:31.262352Z", + "iopub.status.idle": "2023-04-12T02:42:31.294270Z", + "shell.execute_reply": "2023-04-12T02:42:31.292129Z", + "shell.execute_reply.started": "2023-04-12T02:42:31.263078Z" }, "tags": [] }, @@ -101,11 +101,11 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:12:30.477378Z", - "iopub.status.busy": "2023-04-04T02:12:30.476808Z", - "iopub.status.idle": "2023-04-04T02:12:30.486061Z", - "shell.execute_reply": "2023-04-04T02:12:30.484635Z", - "shell.execute_reply.started": "2023-04-04T02:12:30.477275Z" + "iopub.execute_input": "2023-04-12T02:42:31.299215Z", + "iopub.status.busy": "2023-04-12T02:42:31.298662Z", + "iopub.status.idle": "2023-04-12T02:42:31.308101Z", + "shell.execute_reply": "2023-04-12T02:42:31.306083Z", + "shell.execute_reply.started": "2023-04-12T02:42:31.299146Z" } }, "outputs": [], @@ -136,11 +136,11 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:12:30.487862Z", - "iopub.status.busy": "2023-04-04T02:12:30.487361Z", - "iopub.status.idle": "2023-04-04T02:12:35.519999Z", - "shell.execute_reply": "2023-04-04T02:12:35.517515Z", - "shell.execute_reply.started": "2023-04-04T02:12:30.487810Z" + "iopub.execute_input": "2023-04-12T02:42:31.310775Z", + "iopub.status.busy": "2023-04-12T02:42:31.310164Z", + "iopub.status.idle": "2023-04-12T02:42:37.359244Z", + "shell.execute_reply": "2023-04-12T02:42:37.356383Z", + "shell.execute_reply.started": "2023-04-12T02:42:31.310721Z" } }, "outputs": [ @@ -151,7 +151,7 @@ "
    \n", "
    \n", "

    Client

    \n", - "

    Client-27f1f7a6-d28e-11ed-8c26-0242ac110004

    \n", + "

    Client-ac9f71bc-d8db-11ed-8a48-0242ac110006

    \n", "
    \n", - " Comm: tcp://127.0.0.1:43071\n", + " Comm: tcp://127.0.0.1:45242\n", " \n", " Total threads: 1\n", @@ -317,7 +318,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:45757/status\n", + " Dashboard: http://127.0.0.1:34437/status\n", " \n", " Memory: 25.00 GiB\n", @@ -325,13 +326,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:42031\n", + " Nanny: tcp://127.0.0.1:36843\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-lkhugyk9\n", + " Local directory: /tmp/dask-worker-space/worker-8e5xgkx8\n", "
    \n", "\n", " \n", @@ -182,7 +182,7 @@ " \n", "
    \n", "

    LocalCluster

    \n", - "

    42c6ba08

    \n", + "

    fd40e064

    \n", "
    \n", " \n", "
    \n", @@ -219,11 +219,11 @@ "
    \n", "
    \n", "

    Scheduler

    \n", - "

    Scheduler-8314cba5-586b-48bc-8aba-144f2fd4c058

    \n", + "

    Scheduler-ba5c5b4a-57ca-450f-a56f-6a9529bc98c5

    \n", " \n", " \n", " \n", "
    \n", - " Comm: tcp://127.0.0.1:33216\n", + " Comm: tcp://127.0.0.1:40685\n", " \n", " Workers: 4\n", @@ -265,7 +265,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -310,7 +310,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:40049\n", + " Comm: tcp://127.0.0.1:37562\n", " \n", " Total threads: 1\n", @@ -273,7 +273,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:39751/status\n", + " Dashboard: http://127.0.0.1:39030/status\n", " \n", " Memory: 25.00 GiB\n", @@ -281,13 +281,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:36520\n", + " Nanny: tcp://127.0.0.1:44469\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-q100be4q\n", + " Local directory: /tmp/dask-worker-space/worker-5eczcgfc\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -355,7 +355,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:44499\n", + " Comm: tcp://127.0.0.1:40873\n", " \n", " Total threads: 1\n", @@ -318,7 +318,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:42564/status\n", + " Dashboard: http://127.0.0.1:38400/status\n", " \n", " Memory: 25.00 GiB\n", @@ -326,13 +326,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:33657\n", + " Nanny: tcp://127.0.0.1:34121\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-cwemg4pa\n", + " Local directory: /tmp/dask-worker-space/worker-0p2ot6wv\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -400,7 +400,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:41685\n", + " Comm: tcp://127.0.0.1:33771\n", " \n", " Total threads: 1\n", @@ -363,7 +363,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:37568/status\n", + " Dashboard: http://127.0.0.1:36647/status\n", " \n", " Memory: 25.00 GiB\n", @@ -371,13 +371,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:45721\n", + " Nanny: tcp://127.0.0.1:33261\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-vd4f05lh\n", + " Local directory: /tmp/dask-worker-space/worker-og03lnsb\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -449,7 +449,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -477,11 +477,11 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:12:35.524194Z", - "iopub.status.busy": "2023-04-04T02:12:35.523629Z", - "iopub.status.idle": "2023-04-04T02:12:55.372465Z", - "shell.execute_reply": "2023-04-04T02:12:55.369592Z", - "shell.execute_reply.started": "2023-04-04T02:12:35.524113Z" + "iopub.execute_input": "2023-04-12T02:42:37.363884Z", + "iopub.status.busy": "2023-04-12T02:42:37.363220Z", + "iopub.status.idle": "2023-04-12T02:42:57.550696Z", + "shell.execute_reply": "2023-04-12T02:42:57.548805Z", + "shell.execute_reply.started": "2023-04-12T02:42:37.363802Z" } }, "outputs": [], @@ -510,11 +510,11 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:12:55.377110Z", - "iopub.status.busy": "2023-04-04T02:12:55.375856Z", - "iopub.status.idle": "2023-04-04T02:14:03.187217Z", - "shell.execute_reply": "2023-04-04T02:14:03.183464Z", - "shell.execute_reply.started": "2023-04-04T02:12:55.377052Z" + "iopub.execute_input": "2023-04-12T02:42:57.561183Z", + "iopub.status.busy": "2023-04-12T02:42:57.560001Z", + "iopub.status.idle": "2023-04-12T02:44:06.430660Z", + "shell.execute_reply": "2023-04-12T02:44:06.417328Z", + "shell.execute_reply.started": "2023-04-12T02:42:57.561123Z" } }, "outputs": [ @@ -557,11 +557,11 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:03.191880Z", - "iopub.status.busy": "2023-04-04T02:14:03.191223Z", - "iopub.status.idle": "2023-04-04T02:14:06.364554Z", - "shell.execute_reply": "2023-04-04T02:14:06.361008Z", - "shell.execute_reply.started": "2023-04-04T02:14:03.191823Z" + "iopub.execute_input": "2023-04-12T02:44:06.435516Z", + "iopub.status.busy": "2023-04-12T02:44:06.434791Z", + "iopub.status.idle": "2023-04-12T02:44:37.493612Z", + "shell.execute_reply": "2023-04-12T02:44:37.489780Z", + "shell.execute_reply.started": "2023-04-12T02:44:06.435434Z" } }, "outputs": [ @@ -576,916 +576,916 @@ "name": "stderr", "output_type": "stream", "text": [ - "--2023-04-03 22:14:03-- https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/EWvf_TyoEdpaDKcFacaPLI4B1fLGf9qleW7xbIDlKVPJDw?download=1\n", - "Resolving livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)... 13.107.138.8, 13.107.136.8, 2620:1ec:8fa::8, ...\n", + "--2023-04-11 22:44:06-- https://livejohnshopkins-my.sharepoint.com/:u:/g/personal/malmans2_jh_edu/EWvf_TyoEdpaDKcFacaPLI4B1fLGf9qleW7xbIDlKVPJDw?download=1\n", + "Resolving livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)... 13.107.138.8, 13.107.136.8, 2620:1ec:8f8::8, ...\n", "Connecting to livejohnshopkins-my.sharepoint.com (livejohnshopkins-my.sharepoint.com)|13.107.138.8|:443... connected.\n", "HTTP request sent, awaiting response... 302 Found\n", "Location: /personal/malmans2_jh_edu/Documents/BoxMigration/oceanspy_particle_properties.nc?ga=1 [following]\n", - "--2023-04-03 22:14:03-- https://livejohnshopkins-my.sharepoint.com/personal/malmans2_jh_edu/Documents/BoxMigration/oceanspy_particle_properties.nc?ga=1\n", + "--2023-04-11 22:44:07-- https://livejohnshopkins-my.sharepoint.com/personal/malmans2_jh_edu/Documents/BoxMigration/oceanspy_particle_properties.nc?ga=1\n", "Reusing existing connection to livejohnshopkins-my.sharepoint.com:443.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 45981653 (44M) [application/x-netcdf]\n", "Saving to: ‘oceanspy_particle_properties.nc’\n", "\n", - " 0K .......... .......... .......... .......... .......... 0% 9.77M 4s\n", - " 50K .......... .......... .......... .......... .......... 0% 9.88M 4s\n", - " 100K .......... .......... .......... .......... .......... 0% 64.0M 3s\n", - " 150K .......... .......... .......... .......... 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.......... .......... .......... .......... 20% 64.4M 1s\n", - " 9400K .......... .......... .......... .......... .......... 21% 47.6M 1s\n", - " 9450K .......... .......... .......... .......... .......... 21% 52.4M 1s\n", - " 9500K .......... .......... .......... .......... .......... 21% 51.6M 1s\n", - " 9550K .......... .......... .......... .......... .......... 21% 61.0M 1s\n", - " 9600K .......... .......... .......... .......... .......... 21% 63.4M 1s\n", - " 9650K .......... .......... .......... .......... .......... 21% 52.5M 1s\n", - " 9700K .......... .......... .......... .......... .......... 21% 40.0M 1s\n", - " 9750K .......... .......... .......... .......... .......... 21% 50.2M 1s\n", - " 9800K .......... .......... .......... .......... .......... 21% 57.4M 1s\n", - " 9850K .......... .......... .......... .......... .......... 22% 60.6M 1s\n", - " 9900K .......... .......... .......... .......... .......... 22% 44.1M 1s\n", - " 9950K .......... .......... .......... .......... .......... 22% 41.5M 1s\n", - " 10000K .......... .......... .......... .......... .......... 22% 50.4M 1s\n", - " 10050K .......... .......... .......... .......... .......... 22% 67.7M 1s\n", - " 10100K .......... .......... .......... .......... .......... 22% 47.1M 1s\n", - " 10150K .......... .......... .......... .......... .......... 22% 33.8M 1s\n", - " 10200K .......... .......... .......... .......... .......... 22% 41.8M 1s\n", - " 10250K .......... .......... .......... .......... .......... 22% 69.8M 1s\n", - " 10300K .......... .......... .......... .......... .......... 23% 56.7M 1s\n", - " 10350K .......... .......... .......... .......... .......... 23% 39.8M 1s\n", - " 10400K .......... .......... .......... .......... .......... 23% 42.8M 1s\n", - " 10450K .......... .......... .......... .......... .......... 23% 69.6M 1s\n", - " 10500K .......... .......... .......... .......... .......... 23% 62.9M 1s\n", - " 10550K .......... .......... .......... .......... .......... 23% 51.1M 1s\n", - " 10600K .......... .......... .......... .......... .......... 23% 28.6M 1s\n", - " 10650K .......... .......... .......... .......... .......... 23% 61.7M 1s\n", - " 10700K .......... .......... .......... .......... .......... 23% 70.5M 1s\n", - " 10750K .......... .......... .......... .......... .......... 24% 60.3M 1s\n", - " 10800K .......... .......... .......... .......... .......... 24% 42.7M 1s\n", - " 10850K .......... .......... .......... .......... .......... 24% 40.6M 1s\n", - " 10900K .......... .......... .......... .......... .......... 24% 59.7M 1s\n", - " 10950K .......... .......... .......... .......... .......... 24% 64.0M 1s\n", - " 11000K .......... .......... .......... .......... .......... 24% 57.0M 1s\n", - " 11050K .......... .......... .......... .......... .......... 24% 55.8M 1s\n", - " 11100K .......... .......... .......... .......... .......... 24% 46.1M 1s\n", - " 11150K .......... .......... .......... .......... .......... 24% 63.5M 1s\n", - " 11200K .......... .......... .......... .......... .......... 25% 69.2M 1s\n", - " 11250K .......... .......... .......... .......... .......... 25% 72.0M 1s\n", - " 11300K .......... .......... .......... .......... .......... 25% 72.2M 1s\n", - " 11350K .......... .......... .......... .......... .......... 25% 73.1M 1s\n", - " 11400K .......... .......... .......... .......... .......... 25% 46.8M 1s\n", - " 11450K .......... .......... .......... .......... .......... 25% 56.7M 1s\n", - " 11500K .......... .......... .......... .......... .......... 25% 78.7M 1s\n", - " 11550K .......... .......... .......... .......... .......... 25% 77.3M 1s\n", - " 11600K .......... .......... .......... .......... .......... 25% 76.2M 1s\n", - " 11650K .......... .......... .......... .......... .......... 26% 73.7M 1s\n", - " 11700K .......... .......... .......... .......... .......... 26% 56.5M 1s\n", - " 11750K .......... .......... .......... .......... .......... 26% 66.4M 1s\n", - " 11800K .......... .......... .......... .......... .......... 26% 43.9M 1s\n", - " 11850K .......... .......... .......... .......... .......... 26% 73.1M 1s\n", - " 11900K .......... .......... .......... .......... .......... 26% 69.8M 1s\n", - " 11950K .......... .......... .......... .......... .......... 26% 70.1M 1s\n", - " 12000K .......... .......... .......... .......... .......... 26% 68.5M 1s\n", - " 12050K .......... .......... .......... .......... .......... 26% 65.1M 1s\n", - " 12100K .......... .......... .......... .......... .......... 27% 53.0M 1s\n", - " 12150K .......... .......... .......... .......... .......... 27% 48.3M 1s\n", - " 12200K .......... .......... .......... .......... .......... 27% 50.5M 1s\n", - " 12250K .......... .......... .......... .......... .......... 27% 73.8M 1s\n", - " 12300K .......... .......... .......... .......... .......... 27% 79.5M 1s\n", - " 12350K .......... .......... .......... .......... .......... 27% 66.3M 1s\n", - " 12400K .......... .......... .......... .......... .......... 27% 48.5M 1s\n", - " 12450K .......... .......... .......... .......... .......... 27% 49.4M 1s\n", - " 12500K .......... .......... .......... .......... .......... 27% 70.3M 1s\n", - " 12550K .......... .......... .......... .......... .......... 28% 76.6M 1s\n", - " 12600K .......... .......... .......... .......... .......... 28% 60.9M 1s\n", - " 12650K .......... .......... .......... .......... .......... 28% 68.4M 1s\n", - " 12700K .......... .......... .......... .......... .......... 28% 46.8M 1s\n", - " 12750K .......... .......... .......... .......... .......... 28% 49.6M 1s\n", - " 12800K .......... .......... .......... .......... .......... 28% 69.2M 1s\n", - " 12850K .......... .......... .......... .......... .......... 28% 80.2M 1s\n", - " 12900K .......... .......... .......... .......... .......... 28% 75.8M 1s\n", - " 12950K .......... .......... .......... .......... .......... 28% 62.9M 1s\n", - " 13000K .......... .......... .......... .......... .......... 29% 40.3M 1s\n", - " 13050K .......... .......... .......... .......... .......... 29% 46.0M 1s\n", - " 13100K .......... .......... .......... .......... .......... 29% 64.1M 1s\n", - " 13150K .......... .......... .......... .......... .......... 29% 62.7M 1s\n", - " 13200K .......... .......... .......... .......... .......... 29% 56.9M 1s\n", - " 13250K .......... .......... .......... .......... .......... 29% 48.7M 1s\n", - " 13300K .......... .......... .......... .......... .......... 29% 47.6M 1s\n", - " 13350K .......... .......... .......... .......... .......... 29% 54.0M 1s\n", - " 13400K .......... .......... .......... .......... .......... 29% 51.4M 1s\n", - " 13450K .......... .......... .......... .......... .......... 30% 65.2M 1s\n", - " 13500K .......... .......... .......... .......... .......... 30% 52.1M 1s\n", - " 13550K .......... .......... .......... .......... .......... 30% 47.6M 1s\n", - " 13600K .......... .......... .......... .......... .......... 30% 51.0M 1s\n", - " 13650K .......... .......... .......... .......... .......... 30% 68.5M 1s\n", - " 13700K .......... .......... .......... .......... .......... 30% 64.7M 1s\n", - " 13750K .......... .......... .......... .......... .......... 30% 63.1M 1s\n", - " 13800K .......... .......... .......... .......... .......... 30% 44.6M 1s\n", - " 13850K .......... .......... .......... .......... .......... 30% 56.8M 1s\n", - " 13900K .......... .......... .......... .......... .......... 31% 70.3M 1s\n", - " 13950K .......... .......... .......... .......... .......... 31% 53.5M 1s\n", - " 14000K .......... .......... .......... .......... .......... 31% 64.5M 1s\n", - " 14050K .......... .......... .......... .......... .......... 31% 61.4M 1s\n", - " 14100K .......... .......... .......... .......... .......... 31% 54.2M 1s\n", - " 14150K .......... .......... .......... .......... .......... 31% 59.4M 1s\n", - " 14200K .......... .......... .......... .......... .......... 31% 57.7M 1s\n", - " 14250K .......... .......... .......... .......... .......... 31% 63.5M 1s\n", - " 14300K .......... .......... .......... .......... .......... 31% 72.3M 1s\n", - " 14350K .......... .......... .......... .......... .......... 32% 54.2M 1s\n", - " 14400K .......... .......... .......... .......... .......... 32% 46.8M 1s\n", - " 14450K .......... .......... .......... .......... .......... 32% 63.4M 1s\n", - " 14500K .......... .......... .......... .......... .......... 32% 59.4M 1s\n", - " 14550K .......... .......... .......... .......... .......... 32% 74.2M 1s\n", - " 14600K .......... .......... .......... .......... .......... 32% 52.0M 1s\n", - " 14650K .......... .......... .......... .......... .......... 32% 53.5M 1s\n", - " 14700K .......... .......... .......... .......... .......... 32% 62.2M 1s\n", - " 14750K .......... .......... .......... .......... .......... 32% 60.0M 1s\n", - " 14800K .......... .......... .......... .......... .......... 33% 54.0M 1s\n", - " 14850K .......... .......... .......... .......... .......... 33% 73.9M 1s\n", - " 14900K .......... .......... .......... .......... .......... 33% 65.4M 1s\n", - " 14950K .......... .......... .......... .......... .......... 33% 46.2M 1s\n", - " 15000K .......... .......... .......... .......... .......... 33% 48.7M 1s\n", - " 15050K .......... .......... .......... .......... .......... 33% 49.8M 1s\n", - " 15100K .......... .......... .......... .......... .......... 33% 62.4M 1s\n", - " 15150K .......... .......... .......... .......... .......... 33% 67.2M 1s\n", - " 15200K .......... .......... .......... .......... .......... 33% 53.4M 1s\n", - " 15250K .......... .......... .......... .......... .......... 34% 58.7M 1s\n", - " 15300K .......... .......... .......... .......... .......... 34% 69.3M 1s\n", - " 15350K .......... .......... .......... .......... .......... 34% 58.5M 1s\n", - " 15400K .......... .......... .......... .......... .......... 34% 53.0M 1s\n", - " 15450K .......... .......... .......... .......... .......... 34% 61.8M 1s\n", - " 15500K .......... .......... .......... .......... .......... 34% 60.1M 1s\n", - " 15550K .......... .......... .......... .......... .......... 34% 71.1M 1s\n", - " 15600K .......... .......... .......... .......... .......... 34% 53.9M 1s\n", - " 15650K .......... .......... .......... .......... .......... 34% 55.9M 1s\n", - " 15700K .......... .......... .......... .......... .......... 35% 3.84M 1s\n", - " 15750K .......... .......... .......... .......... .......... 35% 74.1M 1s\n", - " 15800K .......... .......... .......... .......... .......... 35% 3.90M 1s\n", - " 15850K .......... .......... .......... .......... .......... 35% 63.9M 1s\n", - " 15900K .......... .......... .......... .......... .......... 35% 61.2M 1s\n", - " 15950K .......... .......... .......... .......... .......... 35% 65.9M 1s\n", - " 16000K .......... .......... .......... .......... .......... 35% 58.2M 1s\n", - " 16050K .......... .......... .......... .......... .......... 35% 53.8M 1s\n", - " 16100K .......... .......... .......... .......... .......... 35% 46.9M 1s\n", - " 16150K .......... .......... .......... .......... .......... 36% 57.9M 1s\n", - " 16200K .......... .......... .......... .......... .......... 36% 37.3M 1s\n", - " 16250K .......... .......... .......... .......... .......... 36% 60.9M 1s\n", - " 16300K .......... .......... .......... .......... .......... 36% 58.7M 1s\n", - " 16350K .......... .......... .......... .......... .......... 36% 41.2M 1s\n", - " 16400K .......... .......... .......... .......... .......... 36% 55.0M 1s\n", - " 16450K .......... .......... .......... .......... .......... 36% 50.8M 1s\n", - " 16500K .......... .......... .......... .......... .......... 36% 67.0M 1s\n", - " 16550K .......... .......... .......... .......... .......... 36% 68.2M 1s\n", - " 16600K .......... .......... .......... .......... .......... 37% 43.9M 1s\n", - " 16650K .......... .......... .......... .......... .......... 37% 35.3M 1s\n", - " 16700K .......... .......... .......... .......... .......... 37% 55.5M 1s\n", - " 16750K .......... .......... .......... .......... .......... 37% 69.9M 1s\n", - " 16800K .......... .......... .......... .......... .......... 37% 48.0M 1s\n", - " 16850K .......... .......... .......... .......... .......... 37% 54.4M 1s\n", - " 16900K .......... .......... .......... .......... .......... 37% 46.1M 1s\n", - " 16950K .......... .......... .......... .......... .......... 37% 52.6M 1s\n", - " 17000K .......... .......... .......... .......... .......... 37% 56.6M 1s\n", - " 17050K .......... .......... .......... .......... .......... 38% 49.7M 1s\n", - " 17100K .......... .......... .......... .......... .......... 38% 53.5M 1s\n", - " 17150K .......... .......... .......... .......... .......... 38% 5.06M 1s\n", - " 17200K .......... .......... .......... .......... .......... 38% 61.1M 1s\n", - " 17250K .......... .......... .......... .......... .......... 38% 65.9M 1s\n", - " 17300K .......... .......... .......... .......... .......... 38% 57.0M 1s\n", - " 17350K .......... .......... .......... .......... .......... 38% 41.8M 1s\n", - " 17400K .......... .......... .......... .......... .......... 38% 48.3M 1s\n", - " 17450K .......... .......... .......... .......... .......... 38% 66.7M 1s\n", - " 17500K .......... .......... .......... .......... .......... 39% 61.2M 1s\n", - " 17550K .......... .......... .......... .......... .......... 39% 70.5M 1s\n", - " 17600K .......... .......... .......... .......... .......... 39% 31.7M 1s\n", - " 17650K .......... .......... .......... .......... .......... 39% 60.6M 1s\n", - " 17700K .......... .......... .......... .......... .......... 39% 71.8M 1s\n", - " 17750K .......... .......... .......... .......... .......... 39% 65.6M 1s\n", - " 17800K .......... .......... .......... .......... .......... 39% 51.9M 1s\n", - " 17850K .......... .......... .......... .......... .......... 39% 39.3M 1s\n", - " 17900K .......... .......... .......... .......... .......... 39% 57.0M 1s\n", - " 17950K .......... .......... .......... .......... .......... 40% 59.7M 1s\n", - " 18000K .......... .......... .......... .......... .......... 40% 57.9M 1s\n", - " 18050K .......... .......... .......... .......... .......... 40% 42.6M 1s\n", - " 18100K .......... .......... .......... .......... .......... 40% 52.5M 1s\n", - " 18150K .......... .......... .......... .......... .......... 40% 56.8M 1s\n", - " 18200K .......... .......... .......... .......... .......... 40% 48.8M 1s\n", - " 18250K .......... .......... .......... .......... .......... 40% 67.5M 1s\n", - " 18300K .......... .......... .......... .......... .......... 40% 70.4M 1s\n", - " 18350K .......... .......... .......... .......... .......... 40% 54.8M 1s\n", - " 18400K .......... .......... .......... .......... .......... 41% 36.8M 1s\n", - " 18450K .......... .......... .......... .......... .......... 41% 51.3M 1s\n", - " 18500K .......... .......... .......... .......... .......... 41% 61.8M 1s\n", - " 18550K .......... .......... .......... .......... .......... 41% 65.1M 1s\n", - " 18600K .......... .......... .......... .......... .......... 41% 48.8M 1s\n", - " 18650K .......... .......... .......... .......... .......... 41% 41.1M 1s\n", - " 18700K .......... .......... .......... .......... .......... 41% 52.9M 1s\n", - " 18750K .......... .......... .......... .......... .......... 41% 64.0M 1s\n", - " 18800K .......... .......... .......... .......... .......... 41% 55.5M 1s\n", - " 18850K .......... .......... .......... .......... .......... 42% 55.4M 1s\n", - " 18900K .......... .......... .......... .......... .......... 42% 62.6M 1s\n", - " 18950K .......... .......... .......... .......... .......... 42% 46.8M 1s\n", - " 19000K .......... .......... .......... .......... .......... 42% 38.0M 1s\n", - " 19050K .......... .......... .......... .......... .......... 42% 56.8M 1s\n", - " 19100K .......... .......... .......... .......... .......... 42% 57.0M 1s\n", - " 19150K .......... .......... .......... .......... .......... 42% 52.4M 1s\n", - " 19200K .......... .......... .......... .......... .......... 42% 34.9M 1s\n", - " 19250K .......... .......... .......... .......... .......... 42% 59.8M 1s\n", - " 19300K .......... .......... .......... .......... .......... 43% 57.5M 1s\n", - " 19350K .......... .......... .......... .......... .......... 43% 50.4M 1s\n", - " 19400K .......... .......... .......... .......... .......... 43% 28.5M 1s\n", - " 19450K .......... .......... .......... .......... .......... 43% 42.5M 1s\n", - " 19500K .......... .......... .......... .......... .......... 43% 58.6M 1s\n", - " 19550K .......... .......... .......... .......... .......... 43% 44.5M 1s\n", - " 19600K .......... .......... .......... .......... .......... 43% 40.7M 1s\n", - " 19650K .......... .......... .......... .......... .......... 43% 58.8M 1s\n", - " 19700K .......... .......... .......... .......... .......... 43% 60.0M 1s\n", - " 19750K .......... .......... .......... .......... .......... 44% 65.5M 1s\n", - " 19800K .......... .......... .......... .......... .......... 44% 50.9M 1s\n", - " 19850K .......... .......... .......... .......... .......... 44% 64.4M 1s\n", - " 19900K .......... .......... .......... .......... .......... 44% 61.2M 1s\n", - " 19950K .......... .......... .......... .......... .......... 44% 43.8M 1s\n", - " 20000K .......... .......... .......... .......... .......... 44% 57.4M 1s\n", - " 20050K .......... .......... .......... .......... .......... 44% 59.0M 1s\n", - " 20100K .......... .......... .......... .......... .......... 44% 38.2M 1s\n", - " 20150K .......... .......... .......... .......... .......... 44% 37.0M 1s\n", - " 20200K .......... .......... .......... .......... .......... 45% 45.8M 1s\n", - " 20250K .......... .......... .......... .......... .......... 45% 73.5M 1s\n", - " 20300K .......... .......... .......... .......... .......... 45% 58.9M 1s\n", - " 20350K .......... .......... .......... .......... .......... 45% 62.1M 1s\n", - " 20400K .......... .......... .......... .......... .......... 45% 54.3M 1s\n", - " 20450K .......... .......... .......... .......... .......... 45% 51.6M 1s\n", - " 20500K .......... .......... .......... .......... .......... 45% 69.9M 1s\n", - " 20550K .......... .......... .......... .......... .......... 45% 66.2M 1s\n", - " 20600K .......... .......... .......... .......... .......... 45% 43.9M 1s\n", - " 20650K .......... .......... .......... .......... .......... 46% 54.7M 1s\n", - " 20700K .......... .......... .......... .......... .......... 46% 46.2M 1s\n", - " 20750K .......... .......... .......... .......... .......... 46% 66.9M 1s\n", - " 20800K .......... .......... .......... .......... .......... 46% 47.8M 1s\n", - " 20850K .......... .......... .......... .......... .......... 46% 61.5M 1s\n", - " 20900K .......... .......... .......... .......... .......... 46% 60.1M 1s\n", - " 20950K .......... .......... .......... .......... .......... 46% 56.0M 1s\n", - " 21000K .......... .......... .......... .......... .......... 46% 45.6M 1s\n", - " 21050K .......... .......... .......... .......... .......... 46% 72.7M 1s\n", - " 21100K .......... .......... .......... .......... .......... 47% 2.44M 1s\n", - " 21150K .......... .......... .......... .......... .......... 47% 52.1M 1s\n", - " 21200K .......... .......... .......... .......... .......... 47% 49.1M 1s\n", - " 21250K .......... .......... .......... .......... .......... 47% 64.7M 1s\n", - " 21300K .......... .......... .......... .......... .......... 47% 64.4M 1s\n", - " 21350K .......... .......... .......... .......... .......... 47% 67.8M 1s\n", - " 21400K .......... .......... .......... .......... .......... 47% 41.6M 1s\n", - " 21450K .......... .......... .......... .......... .......... 47% 52.0M 1s\n", - " 21500K .......... .......... .......... .......... .......... 47% 68.1M 1s\n", - " 21550K .......... .......... .......... .......... .......... 48% 62.9M 1s\n", - " 21600K .......... .......... .......... .......... .......... 48% 49.1M 1s\n", - " 21650K .......... .......... .......... .......... .......... 48% 46.1M 1s\n", - " 21700K .......... .......... .......... .......... .......... 48% 30.1M 1s\n", - " 21750K .......... .......... .......... .......... .......... 48% 70.4M 1s\n", - " 21800K .......... .......... .......... .......... .......... 48% 55.7M 1s\n", - " 21850K .......... .......... .......... .......... .......... 48% 67.5M 1s\n", - " 21900K .......... .......... .......... .......... .......... 48% 57.2M 1s\n", - " 21950K .......... .......... .......... .......... .......... 48% 51.9M 1s\n", - " 22000K .......... .......... .......... .......... .......... 49% 53.5M 1s\n", - " 22050K .......... .......... .......... .......... .......... 49% 73.7M 1s\n", - " 22100K .......... .......... .......... .......... .......... 49% 68.5M 1s\n", - " 22150K .......... .......... .......... .......... .......... 49% 67.0M 1s\n", - " 22200K .......... .......... .......... .......... .......... 49% 50.9M 1s\n", - " 22250K .......... .......... .......... .......... .......... 49% 50.0M 1s\n", - " 22300K .......... .......... .......... .......... .......... 49% 4.03M 1s\n", - " 22350K .......... .......... .......... .......... .......... 49% 12.8M 1s\n", - " 22400K .......... .......... .......... .......... .......... 49% 42.8M 1s\n", - " 22450K .......... .......... .......... .......... .......... 50% 49.7M 1s\n", - " 22500K .......... .......... .......... .......... .......... 50% 54.6M 1s\n", - " 22550K .......... .......... .......... .......... .......... 50% 70.4M 1s\n", - " 22600K .......... .......... .......... .......... .......... 50% 50.6M 1s\n", - " 22650K .......... .......... .......... .......... .......... 50% 66.7M 1s\n", - " 22700K .......... .......... .......... .......... .......... 50% 49.3M 1s\n", - " 22750K .......... .......... .......... .......... .......... 50% 48.5M 1s\n", - " 22800K .......... .......... .......... .......... .......... 50% 57.7M 1s\n", - " 22850K .......... .......... .......... .......... .......... 50% 60.7M 1s\n", - " 22900K .......... .......... .......... .......... .......... 51% 63.6M 1s\n", - " 22950K .......... .......... .......... .......... .......... 51% 43.5M 1s\n", - " 23000K .......... .......... .......... .......... .......... 51% 31.7M 1s\n", - " 23050K .......... .......... .......... .......... .......... 51% 57.1M 1s\n", - " 23100K .......... .......... .......... .......... .......... 51% 45.9M 1s\n", - " 23150K .......... .......... .......... .......... .......... 51% 41.6M 1s\n", - " 23200K .......... .......... .......... .......... .......... 51% 31.3M 1s\n", - " 23250K .......... .......... .......... .......... .......... 51% 46.6M 1s\n", - " 23300K .......... .......... .......... .......... .......... 51% 52.3M 1s\n", - " 23350K .......... .......... .......... .......... .......... 52% 61.5M 1s\n", - " 23400K .......... .......... .......... .......... .......... 52% 47.4M 1s\n", - " 23450K .......... .......... .......... .......... .......... 52% 46.1M 1s\n", - " 23500K .......... .......... .......... .......... .......... 52% 66.5M 1s\n", - " 23550K .......... .......... .......... .......... .......... 52% 67.4M 1s\n", - " 23600K .......... .......... .......... .......... .......... 52% 62.5M 1s\n", - " 23650K .......... .......... .......... .......... .......... 52% 57.9M 1s\n", - " 23700K .......... .......... .......... .......... .......... 52% 62.7M 1s\n", - " 23750K .......... .......... .......... .......... .......... 53% 57.2M 1s\n", - " 23800K .......... .......... .......... .......... .......... 53% 53.4M 1s\n", - " 23850K .......... .......... .......... .......... .......... 53% 68.3M 1s\n", - " 23900K .......... .......... .......... .......... .......... 53% 55.1M 1s\n", - " 23950K .......... .......... .......... .......... .......... 53% 54.1M 1s\n", - " 24000K .......... .......... .......... .......... .......... 53% 58.7M 1s\n", - " 24050K .......... .......... .......... .......... .......... 53% 68.4M 1s\n", - " 24100K .......... .......... .......... .......... .......... 53% 64.2M 0s\n", - " 24150K .......... .......... .......... .......... .......... 53% 62.3M 0s\n", - " 24200K .......... .......... .......... .......... .......... 54% 55.8M 0s\n", - " 24250K .......... .......... .......... .......... .......... 54% 51.7M 0s\n", - " 24300K .......... .......... .......... .......... .......... 54% 52.4M 0s\n", - " 24350K .......... .......... .......... .......... .......... 54% 64.1M 0s\n", - " 24400K .......... .......... .......... .......... .......... 54% 58.2M 0s\n", - " 24450K .......... .......... .......... .......... .......... 54% 52.8M 0s\n", - " 24500K .......... .......... .......... .......... .......... 54% 52.5M 0s\n", - " 24550K .......... .......... .......... .......... .......... 54% 54.1M 0s\n", - " 24600K .......... .......... .......... .......... .......... 54% 46.9M 0s\n", - " 24650K .......... .......... .......... .......... .......... 55% 60.7M 0s\n", - " 24700K .......... .......... .......... .......... .......... 55% 58.2M 0s\n", - " 24750K .......... .......... .......... .......... .......... 55% 57.4M 0s\n", - " 24800K .......... .......... .......... .......... .......... 55% 48.2M 0s\n", - " 24850K .......... .......... .......... .......... .......... 55% 54.7M 0s\n", - " 24900K .......... .......... .......... .......... .......... 55% 69.3M 0s\n", - " 24950K .......... .......... .......... .......... .......... 55% 62.0M 0s\n", - " 25000K .......... .......... .......... .......... .......... 55% 49.7M 0s\n", - " 25050K .......... .......... .......... .......... .......... 55% 51.3M 0s\n", - " 25100K .......... .......... .......... .......... .......... 56% 63.0M 0s\n", - " 25150K .......... .......... .......... .......... .......... 56% 67.8M 0s\n", - " 25200K .......... .......... .......... .......... .......... 56% 58.1M 0s\n", - " 25250K .......... .......... .......... .......... .......... 56% 56.6M 0s\n", - " 25300K .......... .......... .......... .......... .......... 56% 57.7M 0s\n", - " 25350K .......... .......... .......... .......... .......... 56% 58.2M 0s\n", - " 25400K .......... .......... .......... .......... .......... 56% 46.1M 0s\n", - " 25450K .......... .......... .......... .......... .......... 56% 67.9M 0s\n", - " 25500K .......... .......... .......... .......... .......... 56% 60.6M 0s\n", - " 25550K .......... .......... .......... .......... .......... 57% 59.0M 0s\n", - " 25600K .......... .......... .......... .......... .......... 57% 43.5M 0s\n", - " 25650K .......... .......... .......... .......... .......... 57% 53.4M 0s\n", - " 25700K .......... .......... .......... .......... .......... 57% 50.1M 0s\n", - " 25750K .......... .......... .......... .......... .......... 57% 66.3M 0s\n", - " 25800K .......... .......... .......... .......... .......... 57% 47.4M 0s\n", - " 25850K .......... .......... .......... .......... .......... 57% 60.7M 0s\n", - " 25900K .......... .......... .......... .......... .......... 57% 44.9M 0s\n", - " 25950K .......... .......... .......... .......... .......... 57% 57.8M 0s\n", - " 26000K .......... .......... .......... .......... .......... 58% 50.9M 0s\n", - " 26050K .......... .......... .......... .......... .......... 58% 32.9M 0s\n", - " 26100K .......... .......... .......... .......... .......... 58% 4.58M 0s\n", - " 26150K .......... .......... .......... .......... .......... 58% 60.7M 0s\n", - " 26200K .......... .......... .......... .......... .......... 58% 55.3M 0s\n", - " 26250K .......... .......... .......... .......... .......... 58% 66.4M 0s\n", - " 26300K .......... .......... .......... .......... .......... 58% 64.6M 0s\n", - " 26350K .......... .......... .......... .......... .......... 58% 63.9M 0s\n", - " 26400K .......... .......... .......... .......... .......... 58% 62.4M 0s\n", - " 26450K .......... .......... .......... .......... .......... 59% 62.2M 0s\n", - " 26500K .......... .......... .......... .......... .......... 59% 46.8M 0s\n", - " 26550K .......... .......... .......... .......... .......... 59% 60.1M 0s\n", - " 26600K .......... .......... .......... .......... .......... 59% 52.4M 0s\n", - " 26650K .......... .......... .......... .......... .......... 59% 64.4M 0s\n", - " 26700K .......... .......... .......... .......... .......... 59% 59.9M 0s\n", - " 26750K .......... .......... .......... .......... .......... 59% 58.0M 0s\n", - " 26800K .......... .......... .......... .......... .......... 59% 55.4M 0s\n", - " 26850K .......... .......... .......... .......... .......... 59% 61.9M 0s\n", - " 26900K .......... .......... .......... .......... .......... 60% 64.3M 0s\n", - " 26950K .......... .......... .......... .......... .......... 60% 64.5M 0s\n", - " 27000K .......... .......... .......... .......... .......... 60% 52.0M 0s\n", - " 27050K .......... .......... .......... .......... .......... 60% 72.2M 0s\n", - " 27100K .......... .......... .......... .......... .......... 60% 60.5M 0s\n", - " 27150K .......... .......... .......... .......... .......... 60% 63.4M 0s\n", - " 27200K .......... .......... .......... .......... .......... 60% 58.9M 0s\n", - " 27250K .......... .......... .......... .......... .......... 60% 70.7M 0s\n", - " 27300K .......... .......... .......... .......... .......... 60% 3.80M 0s\n", - " 27350K .......... .......... .......... .......... .......... 61% 65.8M 0s\n", - " 27400K .......... .......... .......... .......... .......... 61% 53.4M 0s\n", - " 27450K .......... .......... .......... .......... .......... 61% 62.8M 0s\n", - " 27500K .......... .......... .......... .......... .......... 61% 67.4M 0s\n", - " 27550K .......... .......... .......... .......... .......... 61% 63.8M 0s\n", - " 27600K .......... .......... .......... .......... .......... 61% 8.78M 0s\n", - " 27650K .......... .......... .......... .......... .......... 61% 51.2M 0s\n", - " 27700K .......... .......... .......... .......... .......... 61% 69.2M 0s\n", - " 27750K .......... .......... .......... .......... .......... 61% 64.8M 0s\n", - " 27800K .......... .......... .......... .......... .......... 62% 14.8M 0s\n", - " 27850K .......... .......... .......... .......... .......... 62% 66.1M 0s\n", - " 27900K .......... .......... .......... .......... .......... 62% 64.1M 0s\n", - " 27950K .......... .......... .......... .......... .......... 62% 15.7M 0s\n", - " 28000K .......... .......... .......... .......... .......... 62% 53.4M 0s\n", - " 28050K .......... .......... .......... .......... .......... 62% 65.5M 0s\n", - " 28100K .......... .......... .......... .......... .......... 62% 17.9M 0s\n", - " 28150K .......... .......... .......... .......... .......... 62% 68.0M 0s\n", - " 28200K .......... .......... .......... .......... .......... 62% 56.8M 0s\n", - " 28250K .......... .......... .......... .......... .......... 63% 15.2M 0s\n", - " 28300K .......... .......... .......... .......... .......... 63% 53.4M 0s\n", - " 28350K .......... .......... .......... .......... .......... 63% 66.9M 0s\n", - " 28400K .......... .......... .......... .......... .......... 63% 15.5M 0s\n", - " 28450K .......... .......... .......... .......... .......... 63% 47.1M 0s\n", - " 28500K .......... .......... .......... .......... .......... 63% 64.6M 0s\n", - " 28550K .......... .......... .......... .......... .......... 63% 17.5M 0s\n", - " 28600K .......... .......... .......... .......... .......... 63% 45.6M 0s\n", - " 28650K .......... .......... .......... .......... .......... 63% 68.0M 0s\n", - " 28700K .......... .......... .......... .......... .......... 64% 17.7M 0s\n", - " 28750K .......... .......... .......... .......... .......... 64% 47.4M 0s\n", - " 28800K .......... .......... .......... .......... .......... 64% 51.4M 0s\n", - " 28850K .......... .......... .......... .......... .......... 64% 67.1M 0s\n", - " 28900K .......... .......... .......... .......... .......... 64% 20.3M 0s\n", - " 28950K .......... .......... .......... .......... .......... 64% 47.4M 0s\n", - " 29000K .......... .......... .......... .......... .......... 64% 55.9M 0s\n", - " 29050K .......... .......... .......... .......... .......... 64% 17.5M 0s\n", - " 29100K .......... .......... .......... .......... .......... 64% 53.0M 0s\n", - " 29150K .......... .......... .......... .......... .......... 65% 67.1M 0s\n", - " 29200K .......... .......... .......... .......... .......... 65% 16.4M 0s\n", - " 29250K .......... .......... .......... .......... .......... 65% 51.0M 0s\n", - " 29300K .......... .......... .......... .......... .......... 65% 63.4M 0s\n", - " 29350K .......... .......... .......... .......... .......... 65% 17.8M 0s\n", - " 29400K .......... .......... .......... .......... .......... 65% 47.3M 0s\n", - " 29450K .......... .......... .......... .......... .......... 65% 60.7M 0s\n", - " 29500K .......... .......... .......... .......... .......... 65% 16.0M 0s\n", - " 29550K .......... .......... .......... .......... .......... 65% 55.9M 0s\n", - " 29600K .......... .......... .......... .......... .......... 66% 53.7M 0s\n", - " 29650K .......... .......... .......... .......... .......... 66% 17.4M 0s\n", - " 29700K .......... .......... .......... .......... .......... 66% 48.3M 0s\n", - " 29750K .......... .......... .......... .......... .......... 66% 57.4M 0s\n", - " 29800K .......... .......... .......... .......... .......... 66% 18.2M 0s\n", - " 29850K .......... .......... .......... .......... .......... 66% 44.6M 0s\n", - " 29900K .......... .......... .......... .......... .......... 66% 58.9M 0s\n", - " 29950K .......... .......... .......... .......... .......... 66% 44.8M 0s\n", - " 30000K .......... .......... .......... .......... .......... 66% 21.1M 0s\n", - " 30050K .......... .......... .......... .......... .......... 67% 52.8M 0s\n", - " 30100K .......... .......... .......... .......... .......... 67% 67.9M 0s\n", - " 30150K .......... .......... .......... .......... .......... 67% 15.1M 0s\n", - " 30200K .......... .......... .......... .......... .......... 67% 47.8M 0s\n", - " 30250K .......... .......... .......... .......... .......... 67% 69.0M 0s\n", - " 30300K .......... .......... .......... .......... .......... 67% 16.1M 0s\n", - " 30350K .......... .......... .......... .......... .......... 67% 53.8M 0s\n", - " 30400K .......... .......... .......... .......... .......... 67% 59.5M 0s\n", - " 30450K .......... .......... .......... .......... .......... 67% 17.7M 0s\n", - " 30500K .......... .......... .......... .......... .......... 68% 46.3M 0s\n", - " 30550K .......... .......... .......... .......... .......... 68% 65.0M 0s\n", - " 30600K .......... .......... .......... .......... .......... 68% 15.4M 0s\n", - " 30650K .......... .......... .......... .......... .......... 68% 56.1M 0s\n", - " 30700K .......... .......... .......... .......... .......... 68% 49.7M 0s\n", - " 30750K .......... .......... .......... .......... .......... 68% 21.7M 0s\n", - " 30800K .......... .......... .......... .......... .......... 68% 48.6M 0s\n", - " 30850K .......... .......... .......... .......... .......... 68% 58.1M 0s\n", - " 30900K .......... .......... .......... .......... .......... 68% 17.4M 0s\n", - " 30950K .......... .......... .......... .......... .......... 69% 50.3M 0s\n", - " 31000K .......... .......... .......... .......... .......... 69% 38.2M 0s\n", - " 31050K .......... .......... .......... .......... .......... 69% 25.7M 0s\n", - " 31100K .......... .......... .......... .......... .......... 69% 41.4M 0s\n", - " 31150K .......... .......... .......... .......... .......... 69% 43.1M 0s\n", - " 31200K .......... .......... .......... .......... .......... 69% 53.8M 0s\n", - " 31250K .......... .......... .......... .......... .......... 69% 19.6M 0s\n", - " 31300K .......... .......... .......... .......... .......... 69% 43.1M 0s\n", - " 31350K .......... .......... .......... .......... .......... 69% 54.3M 0s\n", - " 31400K .......... .......... .......... .......... .......... 70% 20.3M 0s\n", - " 31450K .......... .......... .......... .......... .......... 70% 39.1M 0s\n", - " 31500K .......... .......... .......... .......... .......... 70% 58.8M 0s\n", - " 31550K .......... .......... .......... .......... .......... 70% 21.4M 0s\n", - " 31600K .......... .......... .......... .......... .......... 70% 35.1M 0s\n", - " 31650K .......... .......... .......... .......... .......... 70% 53.7M 0s\n", - " 31700K .......... .......... .......... .......... .......... 70% 22.3M 0s\n", - " 31750K .......... .......... .......... .......... .......... 70% 50.0M 0s\n", - " 31800K .......... .......... .......... .......... .......... 70% 36.5M 0s\n", - " 31850K .......... .......... .......... .......... .......... 71% 26.4M 0s\n", - " 31900K .......... .......... .......... .......... .......... 71% 31.6M 0s\n", - " 31950K .......... .......... .......... .......... .......... 71% 36.0M 0s\n", - " 32000K .......... .......... .......... .......... .......... 71% 39.8M 0s\n", - " 32050K .......... .......... .......... .......... .......... 71% 27.4M 0s\n", - " 32100K .......... .......... .......... .......... .......... 71% 55.0M 0s\n", - " 32150K .......... .......... .......... .......... .......... 71% 59.9M 0s\n", - " 32200K .......... .......... .......... .......... .......... 71% 16.7M 0s\n", - " 32250K .......... .......... .......... .......... .......... 71% 45.7M 0s\n", - " 32300K .......... .......... .......... .......... .......... 72% 41.7M 0s\n", - " 32350K .......... .......... .......... .......... .......... 72% 26.9M 0s\n", - " 32400K .......... .......... .......... .......... .......... 72% 53.8M 0s\n", - " 32450K .......... .......... .......... .......... .......... 72% 4.50M 0s\n", - " 32500K .......... .......... .......... .......... .......... 72% 40.2M 0s\n", - " 32550K .......... .......... .......... .......... .......... 72% 55.8M 0s\n", - " 32600K .......... .......... .......... .......... .......... 72% 19.8M 0s\n", - " 32650K .......... .......... .......... .......... .......... 72% 61.0M 0s\n", - " 32700K .......... .......... .......... .......... .......... 72% 56.5M 0s\n", - " 32750K .......... .......... .......... .......... .......... 73% 65.0M 0s\n", - " 32800K .......... .......... .......... .......... .......... 73% 17.5M 0s\n", - " 32850K .......... .......... .......... .......... .......... 73% 63.3M 0s\n", - " 32900K .......... .......... .......... .......... .......... 73% 43.8M 0s\n", - " 32950K .......... .......... .......... .......... .......... 73% 18.1M 0s\n", - " 33000K .......... .......... .......... .......... .......... 73% 43.4M 0s\n", - " 33050K .......... .......... .......... .......... .......... 73% 40.7M 0s\n", - " 33100K .......... .......... .......... .......... .......... 73% 23.8M 0s\n", - " 33150K .......... .......... .......... .......... .......... 73% 52.7M 0s\n", - " 33200K .......... .......... .......... .......... .......... 74% 37.4M 0s\n", - " 33250K .......... .......... .......... .......... .......... 74% 24.5M 0s\n", - " 33300K .......... .......... .......... .......... .......... 74% 39.4M 0s\n", - " 33350K .......... .......... .......... .......... .......... 74% 38.5M 0s\n", - " 33400K .......... .......... .......... .......... .......... 74% 18.5M 0s\n", - " 33450K .......... .......... .......... .......... .......... 74% 50.3M 0s\n", - " 33500K .......... .......... .......... .......... .......... 74% 66.9M 0s\n", - " 33550K .......... .......... .......... .......... .......... 74% 47.5M 0s\n", - " 33600K .......... .......... .......... .......... .......... 74% 29.1M 0s\n", - " 33650K .......... .......... .......... .......... .......... 75% 37.2M 0s\n", - " 33700K .......... .......... .......... .......... .......... 75% 56.9M 0s\n", - " 33750K .......... .......... .......... .......... .......... 75% 23.6M 0s\n", - " 33800K .......... .......... .......... .......... .......... 75% 30.9M 0s\n", - " 33850K .......... .......... .......... .......... .......... 75% 68.8M 0s\n", - " 33900K .......... .......... .......... .......... .......... 75% 22.6M 0s\n", - " 33950K .......... .......... .......... .......... .......... 75% 53.7M 0s\n", - " 34000K .......... .......... .......... .......... .......... 75% 50.3M 0s\n", - " 34050K .......... .......... .......... .......... .......... 75% 47.4M 0s\n", - " 34100K .......... .......... .......... .......... .......... 76% 25.3M 0s\n", - " 34150K .......... .......... .......... .......... .......... 76% 40.6M 0s\n", - " 34200K .......... .......... .......... .......... .......... 76% 44.4M 0s\n", - " 34250K .......... .......... .......... .......... .......... 76% 4.47M 0s\n", - " 34300K .......... .......... .......... .......... .......... 76% 64.1M 0s\n", - " 34350K .......... .......... .......... .......... .......... 76% 66.5M 0s\n", - " 34400K .......... .......... .......... .......... .......... 76% 17.1M 0s\n", - " 34450K .......... .......... .......... .......... .......... 76% 54.3M 0s\n", - " 34500K .......... .......... .......... .......... .......... 76% 62.9M 0s\n", - " 34550K .......... .......... .......... .......... .......... 77% 64.5M 0s\n", - " 34600K .......... .......... .......... .......... .......... 77% 16.4M 0s\n", - " 34650K .......... .......... .......... .......... .......... 77% 52.9M 0s\n", - " 34700K .......... .......... .......... .......... .......... 77% 65.8M 0s\n", - " 34750K .......... .......... .......... .......... .......... 77% 20.6M 0s\n", - " 34800K .......... .......... .......... .......... .......... 77% 45.5M 0s\n", - " 34850K .......... .......... .......... .......... .......... 77% 59.5M 0s\n", - " 34900K .......... .......... .......... .......... .......... 77% 65.4M 0s\n", - " 34950K .......... .......... .......... .......... .......... 77% 19.9M 0s\n", - " 35000K .......... .......... .......... .......... .......... 78% 42.8M 0s\n", - " 35050K .......... .......... .......... .......... .......... 78% 60.7M 0s\n", - " 35100K .......... .......... .......... .......... .......... 78% 19.3M 0s\n", - " 35150K .......... .......... .......... .......... .......... 78% 49.6M 0s\n", - " 35200K .......... .......... .......... .......... .......... 78% 52.8M 0s\n", - " 35250K .......... .......... .......... .......... .......... 78% 22.8M 0s\n", - " 35300K .......... .......... .......... .......... .......... 78% 70.8M 0s\n", - " 35350K .......... .......... .......... .......... .......... 78% 68.0M 0s\n", - " 35400K .......... .......... .......... .......... .......... 78% 55.7M 0s\n", - " 35450K .......... .......... .......... .......... .......... 79% 16.7M 0s\n", - " 35500K .......... .......... .......... .......... .......... 79% 3.84M 0s\n", - " 35550K .......... .......... .......... .......... .......... 79% 68.3M 0s\n", - " 35600K .......... .......... .......... .......... .......... 79% 57.4M 0s\n", - " 35650K .......... .......... .......... .......... .......... 79% 63.8M 0s\n", - " 35700K .......... .......... .......... .......... .......... 79% 64.3M 0s\n", - " 35750K .......... .......... .......... .......... .......... 79% 23.6M 0s\n", - " 35800K .......... .......... .......... .......... .......... 79% 9.25M 0s\n", - " 35850K .......... .......... .......... .......... .......... 79% 13.7M 0s\n", - " 35900K .......... .......... .......... .......... .......... 80% 71.4M 0s\n", - " 35950K .......... .......... .......... .......... .......... 80% 55.6M 0s\n", - " 36000K .......... .......... .......... .......... .......... 80% 59.9M 0s\n", - " 36050K .......... .......... .......... .......... .......... 80% 14.9M 0s\n", - " 36100K .......... .......... .......... .......... .......... 80% 64.2M 0s\n", - " 36150K .......... .......... .......... .......... .......... 80% 14.7M 0s\n", - " 36200K .......... .......... .......... .......... .......... 80% 17.6M 0s\n", - " 36250K .......... .......... .......... .......... .......... 80% 31.7M 0s\n", - " 36300K .......... .......... .......... .......... .......... 80% 35.8M 0s\n", - " 36350K .......... .......... .......... .......... .......... 81% 63.6M 0s\n", - " 36400K .......... .......... .......... .......... .......... 81% 15.5M 0s\n", - " 36450K .......... .......... .......... .......... .......... 81% 53.1M 0s\n", - " 36500K .......... .......... .......... .......... .......... 81% 68.6M 0s\n", - " 36550K .......... .......... .......... .......... .......... 81% 14.9M 0s\n", - " 36600K .......... .......... .......... .......... .......... 81% 35.9M 0s\n", - " 36650K .......... .......... .......... .......... .......... 81% 16.6M 0s\n", - " 36700K .......... .......... .......... .......... .......... 81% 53.5M 0s\n", - " 36750K .......... .......... .......... .......... .......... 81% 15.8M 0s\n", - " 36800K .......... .......... .......... .......... .......... 82% 40.5M 0s\n", - " 36850K .......... .......... .......... .......... .......... 82% 33.2M 0s\n", - " 36900K .......... .......... .......... .......... .......... 82% 19.0M 0s\n", - " 36950K .......... .......... .......... .......... .......... 82% 61.1M 0s\n", - " 37000K .......... .......... .......... .......... .......... 82% 13.9M 0s\n", - " 37050K .......... .......... .......... .......... .......... 82% 43.4M 0s\n", - " 37100K .......... .......... .......... .......... .......... 82% 34.8M 0s\n", - " 37150K .......... .......... .......... .......... .......... 82% 18.2M 0s\n", - " 37200K .......... .......... .......... .......... .......... 82% 5.73M 0s\n", - " 37250K .......... .......... .......... .......... .......... 83% 66.1M 0s\n", - " 37300K .......... .......... .......... .......... .......... 83% 65.9M 0s\n", - " 37350K .......... .......... .......... .......... .......... 83% 14.2M 0s\n", - " 37400K .......... .......... .......... .......... .......... 83% 50.2M 0s\n", - " 37450K .......... .......... .......... .......... .......... 83% 15.7M 0s\n", - " 37500K .......... .......... .......... .......... .......... 83% 36.9M 0s\n", - " 37550K .......... .......... .......... .......... .......... 83% 70.1M 0s\n", - " 37600K .......... .......... .......... .......... .......... 83% 13.0M 0s\n", - " 37650K .......... .......... .......... .......... .......... 83% 61.5M 0s\n", - " 37700K .......... .......... .......... .......... .......... 84% 17.3M 0s\n", - " 37750K .......... .......... .......... .......... .......... 84% 40.8M 0s\n", - " 37800K .......... .......... .......... .......... .......... 84% 38.9M 0s\n", - " 37850K .......... .......... .......... .......... .......... 84% 16.0M 0s\n", - " 37900K .......... .......... .......... .......... .......... 84% 49.1M 0s\n", - " 37950K .......... .......... .......... .......... .......... 84% 17.9M 0s\n", - " 38000K .......... .......... .......... .......... .......... 84% 30.6M 0s\n", - " 38050K .......... .......... .......... .......... .......... 84% 40.9M 0s\n", - " 38100K .......... .......... .......... .......... .......... 84% 18.9M 0s\n", - " 38150K .......... .......... .......... .......... .......... 85% 42.4M 0s\n", - " 38200K .......... .......... .......... .......... .......... 85% 16.2M 0s\n", - " 38250K .......... .......... .......... .......... .......... 85% 42.0M 0s\n", - " 38300K .......... .......... .......... .......... .......... 85% 58.5M 0s\n", - " 38350K .......... .......... .......... .......... .......... 85% 14.4M 0s\n", - " 38400K .......... .......... .......... .......... .......... 85% 46.1M 0s\n", - " 38450K .......... .......... .......... .......... .......... 85% 19.2M 0s\n", - " 38500K .......... .......... .......... .......... .......... 85% 27.7M 0s\n", - " 38550K .......... .......... .......... .......... .......... 85% 68.3M 0s\n", - " 38600K .......... .......... .......... .......... .......... 86% 14.6M 0s\n", - " 38650K .......... .......... .......... .......... .......... 86% 31.2M 0s\n", - " 38700K .......... .......... .......... .......... .......... 86% 22.9M 0s\n", - " 38750K .......... .......... .......... .......... .......... 86% 24.3M 0s\n", - " 38800K .......... .......... .......... .......... .......... 86% 32.5M 0s\n", - " 38850K .......... .......... .......... .......... .......... 86% 20.4M 0s\n", - " 38900K .......... .......... .......... .......... .......... 86% 27.2M 0s\n", - " 38950K .......... .......... .......... .......... .......... 86% 36.9M 0s\n", - " 39000K .......... .......... .......... .......... .......... 86% 16.3M 0s\n", - " 39050K .......... .......... .......... .......... .......... 87% 54.7M 0s\n", - " 39100K .......... .......... .......... .......... .......... 87% 25.5M 0s\n", - " 39150K .......... .......... .......... .......... .......... 87% 28.6M 0s\n", - " 39200K .......... .......... .......... .......... .......... 87% 28.1M 0s\n", - " 39250K .......... .......... .......... .......... .......... 87% 22.3M 0s\n", - " 39300K .......... .......... .......... .......... .......... 87% 34.9M 0s\n", - " 39350K .......... .......... .......... .......... .......... 87% 24.3M 0s\n", - " 39400K .......... .......... .......... .......... .......... 87% 30.1M 0s\n", - " 39450K .......... .......... .......... .......... .......... 87% 28.9M 0s\n", - " 39500K .......... .......... .......... .......... .......... 88% 14.2M 0s\n", - " 39550K .......... .......... .......... .......... .......... 88% 54.5M 0s\n", - " 39600K .......... .......... .......... .......... .......... 88% 35.3M 0s\n", - " 39650K .......... .......... .......... .......... .......... 88% 19.5M 0s\n", - " 39700K .......... .......... .......... .......... .......... 88% 59.2M 0s\n", - " 39750K .......... .......... .......... .......... .......... 88% 27.1M 0s\n", - " 39800K .......... .......... .......... .......... .......... 88% 18.5M 0s\n", - " 39850K .......... .......... .......... .......... .......... 88% 43.5M 0s\n", - " 39900K .......... .......... .......... .......... .......... 88% 17.7M 0s\n", - " 39950K .......... .......... .......... .......... .......... 89% 41.7M 0s\n", - " 40000K .......... .......... .......... .......... .......... 89% 41.1M 0s\n", - " 40050K .......... .......... .......... .......... .......... 89% 20.3M 0s\n", - " 40100K .......... .......... .......... .......... .......... 89% 52.6M 0s\n", - " 40150K .......... .......... .......... .......... .......... 89% 31.6M 0s\n", - " 40200K .......... .......... .......... .......... .......... 89% 15.8M 0s\n", - " 40250K .......... .......... .......... .......... .......... 89% 44.5M 0s\n", - " 40300K .......... .......... .......... .......... .......... 89% 18.7M 0s\n", - " 40350K .......... .......... .......... .......... .......... 89% 39.9M 0s\n", - " 40400K .......... .......... .......... .......... .......... 90% 38.7M 0s\n", - " 40450K .......... .......... .......... .......... .......... 90% 20.0M 0s\n", - " 40500K .......... .......... .......... .......... .......... 90% 44.7M 0s\n", - " 40550K .......... .......... .......... .......... .......... 90% 56.8M 0s\n", - " 40600K .......... .......... .......... .......... .......... 90% 12.4M 0s\n", - " 40650K .......... .......... .......... .......... .......... 90% 55.3M 0s\n", - " 40700K .......... .......... .......... .......... .......... 90% 33.5M 0s\n", - " 40750K .......... .......... .......... .......... .......... 90% 23.3M 0s\n", - " 40800K .......... .......... .......... .......... .......... 90% 40.1M 0s\n", - " 40850K .......... .......... .......... .......... .......... 91% 38.0M 0s\n", - " 40900K .......... .......... .......... .......... .......... 91% 23.4M 0s\n", - " 40950K .......... .......... .......... .......... .......... 91% 40.1M 0s\n", - " 41000K .......... .......... .......... .......... .......... 91% 15.7M 0s\n", - " 41050K .......... .......... .......... .......... .......... 91% 37.7M 0s\n", - " 41100K .......... .......... .......... .......... .......... 91% 50.1M 0s\n", - " 41150K .......... .......... .......... .......... .......... 91% 19.6M 0s\n", - " 41200K .......... .......... .......... .......... .......... 91% 46.8M 0s\n", - " 41250K .......... .......... .......... .......... .......... 91% 59.3M 0s\n", - " 41300K .......... .......... .......... .......... .......... 92% 15.1M 0s\n", - " 41350K .......... .......... .......... .......... .......... 92% 51.8M 0s\n", - " 41400K .......... .......... .......... .......... .......... 92% 42.5M 0s\n", - " 41450K .......... .......... .......... .......... .......... 92% 17.8M 0s\n", - " 41500K .......... .......... .......... .......... .......... 92% 56.5M 0s\n", - " 41550K .......... .......... .......... .......... .......... 92% 40.5M 0s\n", - " 41600K .......... .......... .......... .......... .......... 92% 17.9M 0s\n", - " 41650K .......... .......... .......... .......... .......... 92% 59.2M 0s\n", - " 41700K .......... .......... .......... .......... .......... 92% 13.9M 0s\n", - " 41750K .......... .......... .......... .......... .......... 93% 51.9M 0s\n", - " 41800K .......... .......... .......... .......... .......... 93% 3.70M 0s\n", - " 41850K .......... .......... .......... .......... .......... 93% 64.2M 0s\n", - " 41900K .......... .......... .......... .......... .......... 93% 66.9M 0s\n", - " 41950K .......... .......... .......... .......... .......... 93% 62.6M 0s\n", - " 42000K .......... .......... .......... .......... .......... 93% 15.7M 0s\n", - " 42050K .......... .......... .......... .......... .......... 93% 55.0M 0s\n", - " 42100K .......... .......... .......... .......... .......... 93% 64.1M 0s\n", - " 42150K .......... .......... .......... .......... .......... 93% 17.1M 0s\n", - " 42200K .......... .......... .......... .......... .......... 94% 43.1M 0s\n", - " 42250K .......... .......... .......... .......... .......... 94% 65.8M 0s\n", - " 42300K .......... .......... .......... .......... .......... 94% 15.4M 0s\n", - " 42350K .......... .......... .......... .......... .......... 94% 34.0M 0s\n", - " 42400K .......... .......... .......... .......... .......... 94% 31.7M 0s\n", - " 42450K .......... .......... .......... .......... .......... 94% 31.7M 0s\n", - " 42500K .......... .......... .......... .......... .......... 94% 35.5M 0s\n", - " 42550K .......... .......... .......... .......... .......... 94% 65.8M 0s\n", - " 42600K .......... .......... .......... .......... .......... 94% 18.7M 0s\n", - " 42650K .......... .......... .......... .......... .......... 95% 45.3M 0s\n", - " 42700K .......... .......... .......... .......... .......... 95% 64.2M 0s\n", - " 42750K .......... .......... .......... .......... .......... 95% 18.2M 0s\n", - " 42800K .......... .......... .......... .......... .......... 95% 53.8M 0s\n", - " 42850K .......... .......... .......... .......... .......... 95% 62.4M 0s\n", - " 42900K .......... .......... .......... .......... .......... 95% 14.6M 0s\n", - " 42950K .......... .......... .......... .......... .......... 95% 59.3M 0s\n", - " 43000K .......... .......... .......... .......... .......... 95% 48.1M 0s\n", - " 43050K .......... .......... .......... .......... .......... 95% 17.5M 0s\n", - " 43100K .......... .......... .......... .......... .......... 96% 40.4M 0s\n", - " 43150K .......... .......... .......... .......... .......... 96% 41.0M 0s\n", - " 43200K .......... .......... .......... .......... .......... 96% 22.2M 0s\n", - " 43250K .......... .......... .......... .......... .......... 96% 49.5M 0s\n", - " 43300K .......... .......... .......... .......... .......... 96% 57.3M 0s\n", - " 43350K .......... .......... .......... .......... .......... 96% 18.0M 0s\n", - " 43400K .......... .......... .......... .......... .......... 96% 38.7M 0s\n", - " 43450K .......... .......... .......... .......... .......... 96% 67.2M 0s\n", - " 43500K .......... .......... .......... .......... .......... 96% 19.2M 0s\n", - " 43550K .......... .......... .......... .......... .......... 97% 41.0M 0s\n", - " 43600K .......... .......... .......... .......... .......... 97% 56.1M 0s\n", - " 43650K .......... .......... .......... .......... .......... 97% 17.1M 0s\n", - " 43700K .......... .......... .......... .......... .......... 97% 52.3M 0s\n", - " 43750K .......... .......... .......... .......... .......... 97% 61.2M 0s\n", - " 43800K .......... .......... .......... .......... .......... 97% 19.4M 0s\n", - " 43850K .......... .......... .......... .......... .......... 97% 48.0M 0s\n", - " 43900K .......... .......... .......... .......... .......... 97% 51.8M 0s\n", - " 43950K .......... .......... .......... .......... .......... 97% 18.6M 0s\n", - " 44000K .......... .......... .......... .......... .......... 98% 29.0M 0s\n", - " 44050K .......... .......... .......... .......... .......... 98% 60.0M 0s\n", - " 44100K .......... .......... .......... .......... .......... 98% 66.2M 0s\n", - " 44150K .......... .......... .......... .......... .......... 98% 23.0M 0s\n", - " 44200K .......... .......... .......... .......... .......... 98% 25.2M 0s\n", - " 44250K .......... .......... .......... .......... .......... 98% 67.7M 0s\n", - " 44300K .......... .......... .......... .......... .......... 98% 24.4M 0s\n", - " 44350K .......... .......... .......... .......... .......... 98% 31.0M 0s\n", - " 44400K .......... .......... .......... .......... .......... 98% 57.3M 0s\n", - " 44450K .......... .......... .......... .......... .......... 99% 26.4M 0s\n", - " 44500K .......... .......... .......... .......... .......... 99% 31.0M 0s\n", - " 44550K .......... .......... .......... .......... .......... 99% 57.1M 0s\n", - " 44600K .......... .......... .......... .......... .......... 99% 21.6M 0s\n", - " 44650K .......... .......... .......... .......... .......... 99% 27.4M 0s\n", - " 44700K .......... .......... .......... .......... .......... 99% 54.7M 0s\n", - " 44750K .......... .......... .......... .......... .......... 99% 29.8M 0s\n", - " 44800K .......... .......... .......... .......... .......... 99% 31.8M 0s\n", - " 44850K .......... .......... .......... .......... .......... 99% 54.6M 0s\n", - " 44900K ... 100% 7.37T=1.3s\n", + " 0K .......... .......... .......... .......... .......... 0% 166K 4m31s\n", + " 50K .......... .......... .......... .......... .......... 0% 6.05M 2m19s\n", + " 100K .......... .......... .......... .......... .......... 0% 11.6M 94s\n", + " 150K .......... .......... .......... .......... .......... 0% 6.16M 72s\n", + " 200K .......... .......... .......... .......... .......... 0% 5.79M 59s\n", + " 250K .......... .......... .......... .......... .......... 0% 6.10M 50s\n", + " 300K .......... .......... .......... .......... .......... 0% 11.4M 44s\n", + " 350K .......... .......... .......... .......... .......... 0% 2.57M 40s\n", + " 400K .......... .......... .......... .......... .......... 1% 6.13M 37s\n", + " 450K .......... .......... .......... .......... .......... 1% 10.5M 33s\n", + " 500K .......... .......... .......... .......... .......... 1% 5.65M 31s\n", + " 550K .......... .......... .......... .......... .......... 1% 10.0M 29s\n", + " 600K .......... .......... .......... .......... .......... 1% 5.55M 27s\n", + " 650K .......... .......... .......... .......... .......... 1% 10.4M 25s\n", + " 700K .......... .......... .......... .......... .......... 1% 5.71M 24s\n", + " 750K .......... .......... .......... .......... .......... 1% 11.1M 23s\n", + " 800K .......... .......... .......... .......... .......... 1% 10.5M 22s\n", + " 850K .......... .......... .......... .......... .......... 2% 9.71M 21s\n", + " 900K .......... .......... .......... .......... .......... 2% 6.04M 20s\n", + " 950K .......... .......... .......... .......... .......... 2% 11.8M 19s\n", + " 1000K .......... .......... .......... .......... .......... 2% 12.0M 18s\n", + " 1050K .......... .......... .......... .......... .......... 2% 306K 24s\n", + " 1100K .......... .......... .......... .......... .......... 2% 11.7M 23s\n", + " 1150K .......... .......... .......... .......... .......... 2% 144K 35s\n", + " 1200K .......... .......... .......... .......... .......... 2% 4.04M 34s\n", + " 1250K .......... .......... .......... .......... .......... 2% 5.90M 33s\n", + " 1300K .......... .......... .......... .......... .......... 3% 5.87M 32s\n", + " 1350K .......... .......... .......... .......... .......... 3% 4.12M 31s\n", + " 1400K .......... .......... .......... .......... .......... 3% 6.07M 30s\n", + " 1450K .......... .......... .......... .......... .......... 3% 3.64M 29s\n", + " 1500K .......... .......... .......... .......... .......... 3% 5.98M 29s\n", + " 1550K .......... .......... .......... .......... .......... 3% 5.83M 28s\n", + " 1600K .......... .......... .......... .......... .......... 3% 5.93M 27s\n", + " 1650K .......... .......... .......... .......... .......... 3% 5.94M 27s\n", + " 1700K .......... .......... .......... .......... .......... 3% 6.18M 26s\n", + " 1750K .......... .......... .......... .......... .......... 4% 11.1M 25s\n", + " 1800K .......... .......... .......... .......... .......... 4% 6.26M 25s\n", + " 1850K .......... .......... .......... .......... .......... 4% 6.10M 24s\n", + " 1900K .......... .......... .......... .......... .......... 4% 11.6M 24s\n", + " 1950K .......... .......... .......... .......... .......... 4% 6.08M 23s\n", + " 2000K .......... .......... .......... .......... .......... 4% 11.5M 23s\n", + " 2050K .......... .......... .......... .......... .......... 4% 11.6M 22s\n", + " 2100K .......... .......... .......... .......... .......... 4% 5.73M 22s\n", + " 2150K .......... .......... .......... .......... .......... 4% 11.1M 22s\n", + " 2200K .......... .......... .......... .......... .......... 5% 12.1M 21s\n", + " 2250K .......... .......... .......... .......... .......... 5% 5.99M 21s\n", + " 2300K .......... .......... .......... .......... .......... 5% 11.2M 20s\n", + " 2350K .......... .......... .......... .......... .......... 5% 11.7M 20s\n", + " 2400K .......... .......... .......... .......... .......... 5% 12.2M 20s\n", + " 2450K .......... .......... .......... .......... .......... 5% 11.2M 19s\n", + " 2500K .......... .......... .......... .......... .......... 5% 10.7M 19s\n", + " 2550K .......... .......... .......... .......... .......... 5% 11.3M 19s\n", + " 2600K .......... .......... .......... .......... .......... 5% 12.0M 18s\n", + " 2650K .......... .......... .......... .......... .......... 6% 11.3M 18s\n", + " 2700K .......... .......... .......... .......... .......... 6% 12.1M 18s\n", + " 2750K .......... .......... .......... .......... .......... 6% 11.9M 18s\n", + " 2800K .......... .......... .......... .......... .......... 6% 11.7M 17s\n", + " 2850K .......... .......... .......... .......... .......... 6% 11.8M 17s\n", + " 2900K .......... .......... .......... .......... .......... 6% 12.0M 17s\n", + " 2950K .......... .......... .......... .......... .......... 6% 12.2M 17s\n", + " 3000K .......... .......... .......... .......... .......... 6% 11.7M 16s\n", + " 3050K .......... .......... .......... .......... .......... 6% 11.3M 16s\n", + " 3100K .......... .......... .......... .......... .......... 7% 12.7M 16s\n", + " 3150K .......... .......... .......... .......... .......... 7% 12.1M 16s\n", + " 3200K .......... .......... .......... .......... .......... 7% 12.2M 15s\n", + " 3250K .......... .......... .......... .......... .......... 7% 13.0M 15s\n", + " 3300K .......... .......... .......... .......... .......... 7% 10.9M 15s\n", + " 3350K .......... .......... .......... .......... .......... 7% 49.5M 15s\n", + " 3400K .......... .......... .......... .......... .......... 7% 255K 17s\n", + " 3450K .......... .......... .......... .......... .......... 7% 29.7K 37s\n", + " 3500K .......... .......... .......... .......... .......... 7% 45.3K 49s\n", + " 3550K .......... .......... .......... .......... .......... 8% 74.0K 56s\n", + " 3600K .......... .......... .......... .......... .......... 8% 1.50M 55s\n", + " 3650K .......... .......... .......... .......... .......... 8% 2.35M 55s\n", + " 3700K .......... .......... .......... .......... .......... 8% 3.82M 54s\n", + " 3750K .......... .......... .......... .......... .......... 8% 5.64M 53s\n", + " 3800K .......... .......... .......... .......... .......... 8% 5.78M 53s\n", + " 3850K .......... .......... .......... .......... .......... 8% 5.67M 52s\n", + " 3900K .......... .......... .......... .......... .......... 8% 11.1M 52s\n", + " 3950K .......... .......... .......... .......... .......... 8% 10.8M 51s\n", + " 4000K .......... .......... .......... .......... .......... 9% 11.7M 50s\n", + " 4050K .......... .......... .......... .......... .......... 9% 11.1M 50s\n", + " 4100K .......... .......... .......... .......... .......... 9% 11.7M 49s\n", + " 4150K .......... .......... .......... .......... .......... 9% 12.0M 48s\n", + " 4200K .......... .......... .......... .......... .......... 9% 11.5M 48s\n", + " 4250K .......... .......... .......... .......... .......... 9% 10.8M 47s\n", + " 4300K .......... .......... .......... .......... .......... 9% 11.7M 47s\n", + " 4350K .......... .......... .......... .......... .......... 9% 11.8M 46s\n", + " 4400K .......... .......... .......... .......... .......... 9% 11.6M 46s\n", + " 4450K .......... .......... .......... .......... .......... 10% 12.2M 45s\n", + " 4500K .......... .......... .......... .......... .......... 10% 11.9M 45s\n", + " 4550K .......... .......... .......... .......... .......... 10% 12.4M 44s\n", + " 4600K .......... .......... .......... .......... .......... 10% 11.4M 44s\n", + " 4650K .......... .......... .......... .......... .......... 10% 12.2M 43s\n", + " 4700K .......... .......... .......... .......... .......... 10% 12.0M 43s\n", + " 4750K .......... .......... .......... .......... .......... 10% 57.2M 42s\n", + " 4800K .......... .......... .......... .......... .......... 10% 12.4M 42s\n", + " 4850K .......... .......... .......... .......... .......... 10% 11.7M 41s\n", + " 4900K .......... .......... .......... .......... .......... 11% 11.7M 41s\n", + " 4950K .......... .......... .......... .......... .......... 11% 12.5M 40s\n", + " 5000K .......... .......... .......... .......... .......... 11% 66.5M 40s\n", + " 5050K .......... .......... .......... .......... .......... 11% 12.2M 39s\n", + " 5100K .......... .......... .......... .......... .......... 11% 12.6M 39s\n", + " 5150K .......... .......... .......... .......... .......... 11% 12.6M 39s\n", + " 5200K .......... .......... .......... .......... .......... 11% 12.2M 38s\n", + " 5250K .......... .......... .......... .......... .......... 11% 59.9M 38s\n", + " 5300K .......... .......... .......... .......... .......... 11% 13.1M 38s\n", + " 5350K .......... .......... .......... .......... .......... 12% 304K 38s\n", + " 5400K .......... .......... .......... .......... .......... 12% 6.14M 38s\n", + " 5450K .......... .......... .......... .......... .......... 12% 38.5K 47s\n", + " 5500K .......... .......... .......... .......... .......... 12% 123K 49s\n", + " 5550K .......... .......... .......... .......... .......... 12% 107K 52s\n", + " 5600K .......... .......... .......... .......... .......... 12% 42.5K 60s\n", + " 5650K .......... .......... .......... .......... .......... 12% 31.4K 70s\n", + " 5700K .......... .......... .......... .......... .......... 12% 195K 71s\n", + " 5750K .......... .......... .......... .......... .......... 12% 1.36M 71s\n", + " 5800K .......... .......... .......... .......... .......... 13% 3.86M 70s\n", + " 5850K .......... .......... .......... .......... .......... 13% 2.88M 69s\n", + " 5900K .......... .......... .......... .......... .......... 13% 10.9M 69s\n", + " 5950K .......... .......... .......... .......... .......... 13% 5.83M 68s\n", + " 6000K .......... .......... .......... .......... .......... 13% 11.4M 68s\n", + " 6050K .......... .......... .......... .......... .......... 13% 11.2M 67s\n", + " 6100K .......... .......... .......... .......... .......... 13% 11.4M 66s\n", + " 6150K .......... .......... .......... .......... .......... 13% 12.0M 66s\n", + " 6200K .......... .......... .......... .......... .......... 13% 77.7M 65s\n", + " 6250K .......... .......... .......... .......... .......... 14% 11.6M 65s\n", + " 6300K .......... .......... .......... .......... .......... 14% 11.8M 64s\n", + " 6350K .......... .......... .......... .......... .......... 14% 12.7M 63s\n", + " 6400K .......... .......... .......... .......... .......... 14% 11.9M 63s\n", + " 6450K .......... .......... .......... .......... .......... 14% 65.4M 62s\n", + " 6500K .......... .......... .......... .......... .......... 14% 12.1M 62s\n", + " 6550K .......... .......... .......... .......... .......... 14% 13.5M 61s\n", + " 6600K .......... .......... .......... .......... .......... 14% 4.41M 61s\n", + " 6650K .......... .......... .......... .......... .......... 14% 12.5M 60s\n", + " 6700K .......... .......... .......... .......... .......... 15% 80.1M 60s\n", + " 6750K .......... .......... .......... .......... .......... 15% 12.3M 59s\n", + " 6800K .......... .......... .......... .......... .......... 15% 14.3M 59s\n", + " 6850K .......... .......... .......... .......... .......... 15% 21.1M 58s\n", + " 6900K .......... .......... .......... .......... .......... 15% 21.2M 58s\n", + " 6950K .......... .......... .......... .......... .......... 15% 13.6M 57s\n", + " 7000K .......... .......... .......... .......... .......... 15% 4.47M 57s\n", + " 7050K .......... .......... .......... .......... .......... 15% 12.2M 56s\n", + " 7100K .......... .......... .......... .......... .......... 15% 82.3M 56s\n", + " 7150K .......... .......... .......... .......... .......... 16% 13.3M 56s\n", + " 7200K .......... .......... .......... .......... .......... 16% 13.3M 55s\n", + " 7250K .......... .......... .......... .......... .......... 16% 37.8M 55s\n", + " 7300K .......... .......... .......... .......... .......... 16% 16.4M 54s\n", + " 7350K .......... .......... .......... .......... .......... 16% 62.5M 54s\n", + " 7400K .......... .......... .......... .......... .......... 16% 14.3M 53s\n", + " 7450K .......... .......... .......... .......... .......... 16% 14.3M 53s\n", + " 7500K .......... .......... .......... .......... .......... 16% 46.9M 53s\n", + " 7550K .......... .......... .......... .......... .......... 16% 3.70M 52s\n", + " 7600K .......... .......... .......... .......... .......... 17% 72.6M 52s\n", + " 7650K .......... .......... .......... .......... .......... 17% 13.2M 51s\n", + " 7700K .......... .......... .......... .......... .......... 17% 51.7M 51s\n", + " 7750K .......... .......... .......... .......... .......... 17% 13.2M 51s\n", + " 7800K .......... .......... .......... .......... .......... 17% 78.5M 50s\n", + " 7850K .......... .......... .......... .......... .......... 17% 14.0M 50s\n", + " 7900K .......... .......... .......... .......... .......... 17% 14.6M 50s\n", + " 7950K .......... .......... .......... .......... .......... 17% 62.0M 49s\n", + " 8000K .......... .......... .......... .......... .......... 17% 14.1M 49s\n", + " 8050K .......... .......... .......... .......... .......... 18% 70.6M 48s\n", + " 8100K .......... .......... .......... .......... .......... 18% 13.4M 48s\n", + " 8150K .......... .......... .......... .......... .......... 18% 14.6M 48s\n", + " 8200K .......... .......... .......... .......... .......... 18% 70.3M 47s\n", + " 8250K .......... .......... .......... .......... .......... 18% 13.2M 47s\n", + " 8300K .......... .......... .......... .......... .......... 18% 75.8M 47s\n", + " 8350K .......... .......... .......... .......... .......... 18% 12.8M 46s\n", + " 8400K .......... .......... .......... .......... .......... 18% 398K 47s\n", + " 8450K .......... .......... .......... .......... .......... 18% 58.5M 46s\n", + " 8500K .......... .......... .......... .......... .......... 19% 14.3M 46s\n", + " 8550K .......... .......... .......... .......... .......... 19% 9.64M 46s\n", + " 8600K .......... .......... .......... .......... .......... 19% 16.7M 45s\n", + " 8650K .......... .......... .......... .......... .......... 19% 12.0M 45s\n", + " 8700K .......... .......... .......... .......... .......... 19% 12.9M 45s\n", + " 8750K .......... .......... .......... .......... .......... 19% 12.8M 44s\n", + " 8800K .......... .......... .......... .......... .......... 19% 60.3M 44s\n", + " 8850K .......... .......... .......... .......... .......... 19% 11.9M 44s\n", + " 8900K .......... .......... .......... .......... .......... 19% 5.60M 44s\n", + " 8950K .......... .......... .......... .......... .......... 20% 77.6M 43s\n", + " 9000K .......... .......... .......... .......... .......... 20% 12.2M 43s\n", + " 9050K .......... .......... .......... .......... .......... 20% 11.2M 43s\n", + " 9100K .......... .......... .......... .......... .......... 20% 12.3M 42s\n", + " 9150K .......... .......... .......... .......... .......... 20% 12.7M 42s\n", + " 9200K .......... .......... .......... .......... .......... 20% 68.1M 42s\n", + " 9250K .......... .......... .......... .......... .......... 20% 11.8M 42s\n", + " 9300K .......... .......... .......... .......... .......... 20% 10.6M 41s\n", + " 9350K .......... .......... .......... .......... .......... 20% 13.0M 41s\n", + " 9400K .......... .......... .......... .......... .......... 21% 58.0M 41s\n", + " 9450K .......... .......... .......... .......... .......... 21% 11.7M 41s\n", + " 9500K .......... .......... .......... .......... .......... 21% 12.6M 40s\n", + " 9550K .......... .......... .......... .......... .......... 21% 9.80M 40s\n", + " 9600K .......... .......... .......... .......... .......... 21% 19.0M 40s\n", + " 9650K .......... .......... .......... .......... .......... 21% 24.0M 40s\n", + " 9700K .......... .......... .......... .......... .......... 21% 12.1M 39s\n", + " 9750K .......... .......... .......... .......... .......... 21% 12.0M 39s\n", + " 9800K .......... .......... .......... .......... .......... 21% 18.4M 39s\n", + " 9850K .......... .......... .......... .......... .......... 22% 11.8M 39s\n", + " 9900K .......... .......... .......... .......... .......... 22% 29.6M 38s\n", + " 9950K .......... .......... .......... .......... .......... 22% 12.3M 38s\n", + " 10000K .......... .......... .......... .......... .......... 22% 14.8M 38s\n", + " 10050K .......... .......... .......... .......... .......... 22% 14.2M 38s\n", + " 10100K .......... .......... .......... .......... .......... 22% 23.2M 37s\n", + " 10150K .......... .......... .......... .......... .......... 22% 14.4M 37s\n", + " 10200K .......... .......... .......... .......... .......... 22% 16.1M 37s\n", + " 10250K .......... .......... .......... .......... .......... 22% 2.32M 37s\n", + " 10300K .......... .......... .......... .......... .......... 23% 11.0M 37s\n", + " 10350K .......... .......... .......... .......... .......... 23% 12.1M 36s\n", + " 10400K .......... .......... .......... .......... .......... 23% 12.5M 36s\n", + " 10450K .......... .......... .......... .......... .......... 23% 53.3M 36s\n", + " 10500K .......... .......... .......... .......... .......... 23% 12.8M 36s\n", + " 10550K .......... .......... .......... .......... .......... 23% 11.8M 36s\n", + " 10600K .......... .......... .......... .......... .......... 23% 62.3M 35s\n", + " 10650K .......... .......... .......... .......... .......... 23% 12.5M 35s\n", + " 10700K .......... .......... .......... .......... .......... 23% 12.1M 35s\n", + " 10750K .......... .......... .......... .......... .......... 24% 14.9M 35s\n", + " 10800K .......... .......... .......... .......... .......... 24% 56.9M 34s\n", + " 10850K .......... .......... .......... .......... .......... 24% 12.3M 34s\n", + " 10900K .......... .......... .......... .......... .......... 24% 12.7M 34s\n", + " 10950K .......... .......... .......... .......... .......... 24% 42.3M 34s\n", + " 11000K .......... .......... .......... .......... .......... 24% 16.4M 34s\n", + " 11050K .......... .......... .......... .......... .......... 24% 12.2M 34s\n", + " 11100K .......... .......... .......... .......... .......... 24% 39.4M 33s\n", + " 11150K .......... .......... .......... .......... .......... 24% 12.6M 33s\n", + " 11200K .......... .......... .......... .......... .......... 25% 15.3M 33s\n", + " 11250K .......... .......... .......... .......... .......... 25% 54.2M 33s\n", + " 11300K .......... .......... .......... .......... .......... 25% 13.0M 33s\n", + " 11350K .......... .......... .......... .......... .......... 25% 68.2M 32s\n", + " 11400K .......... .......... .......... .......... .......... 25% 13.8M 32s\n", + " 11450K .......... .......... .......... .......... .......... 25% 11.9M 32s\n", + " 11500K .......... .......... .......... .......... .......... 25% 13.2M 32s\n", + " 11550K .......... .......... .......... .......... .......... 25% 61.5M 32s\n", + " 11600K .......... .......... .......... .......... .......... 25% 13.9M 31s\n", + " 11650K .......... .......... .......... .......... .......... 26% 58.0M 31s\n", + " 11700K .......... .......... .......... .......... .......... 26% 13.8M 31s\n", + " 11750K .......... .......... .......... .......... .......... 26% 4.29M 31s\n", + " 11800K .......... .......... .......... .......... .......... 26% 61.8M 31s\n", + " 11850K .......... .......... .......... .......... .......... 26% 13.6M 31s\n", + " 11900K .......... .......... .......... .......... .......... 26% 12.1M 30s\n", + " 11950K .......... .......... .......... .......... .......... 26% 72.3M 30s\n", + " 12000K .......... .......... .......... .......... .......... 26% 13.8M 30s\n", + " 12050K .......... .......... .......... .......... .......... 26% 69.5M 30s\n", + " 12100K .......... .......... .......... .......... .......... 27% 12.1M 30s\n", + " 12150K .......... .......... .......... .......... .......... 27% 71.7M 30s\n", + " 12200K .......... .......... .......... .......... .......... 27% 4.00M 30s\n", + " 12250K .......... .......... .......... .......... .......... 27% 13.7M 29s\n", + " 12300K .......... .......... .......... .......... .......... 27% 70.1M 29s\n", + " 12350K .......... .......... .......... .......... .......... 27% 11.4M 29s\n", + " 12400K .......... .......... .......... .......... .......... 27% 12.9M 29s\n", + " 12450K .......... .......... .......... .......... .......... 27% 16.3M 29s\n", + " 12500K .......... .......... .......... .......... .......... 27% 27.6M 29s\n", + " 12550K .......... .......... .......... .......... .......... 28% 13.1M 28s\n", + " 12600K .......... .......... .......... .......... .......... 28% 13.1M 28s\n", + " 12650K .......... .......... .......... .......... .......... 28% 12.2M 28s\n", + " 12700K .......... .......... .......... .......... .......... 28% 15.3M 28s\n", + " 12750K .......... .......... .......... .......... .......... 28% 30.9M 28s\n", + " 12800K .......... .......... .......... .......... .......... 28% 13.1M 28s\n", + " 12850K .......... .......... .......... .......... .......... 28% 15.5M 28s\n", + " 12900K .......... .......... .......... .......... .......... 28% 17.4M 27s\n", + " 12950K .......... .......... .......... .......... .......... 28% 21.3M 27s\n", + " 13000K .......... .......... .......... .......... .......... 29% 13.0M 27s\n", + " 13050K .......... .......... .......... .......... .......... 29% 12.5M 27s\n", + " 13100K .......... .......... .......... .......... .......... 29% 24.1M 27s\n", + " 13150K .......... .......... .......... .......... .......... 29% 19.9M 27s\n", + " 13200K .......... .......... .......... .......... .......... 29% 13.6M 27s\n", + " 13250K .......... .......... .......... .......... .......... 29% 19.7M 26s\n", + " 13300K .......... .......... .......... .......... .......... 29% 20.4M 26s\n", + " 13350K .......... .......... .......... .......... .......... 29% 15.0M 26s\n", + " 13400K .......... .......... .......... .......... .......... 29% 22.4M 26s\n", + " 13450K .......... .......... .......... .......... .......... 30% 17.1M 26s\n", + " 13500K .......... .......... .......... .......... .......... 30% 13.8M 26s\n", + " 13550K .......... .......... .......... .......... .......... 30% 16.1M 26s\n", + " 13600K .......... .......... .......... .......... .......... 30% 36.2M 26s\n", + " 13650K .......... .......... .......... .......... .......... 30% 8.06M 25s\n", + " 13700K .......... .......... .......... .......... .......... 30% 66.1M 25s\n", + " 13750K .......... .......... .......... .......... .......... 30% 13.0M 25s\n", + " 13800K .......... .......... .......... .......... .......... 30% 69.1M 25s\n", + " 13850K .......... .......... .......... .......... .......... 30% 12.7M 25s\n", + " 13900K .......... .......... .......... .......... .......... 31% 12.3M 25s\n", + " 13950K .......... .......... .......... .......... .......... 31% 12.8M 25s\n", + " 14000K .......... .......... .......... .......... .......... 31% 61.5M 25s\n", + " 14050K .......... .......... .......... .......... .......... 31% 12.9M 24s\n", + " 14100K .......... .......... .......... .......... .......... 31% 75.8M 24s\n", + " 14150K .......... .......... .......... .......... .......... 31% 13.0M 24s\n", + " 14200K .......... .......... .......... .......... .......... 31% 13.6M 24s\n", + " 14250K .......... .......... .......... .......... .......... 31% 55.5M 24s\n", + " 14300K .......... .......... .......... .......... .......... 31% 13.4M 24s\n", + " 14350K .......... .......... .......... .......... .......... 32% 14.0M 24s\n", + " 14400K .......... .......... .......... .......... .......... 32% 56.2M 24s\n", + " 14450K .......... .......... .......... .......... .......... 32% 12.0M 23s\n", + " 14500K .......... .......... .......... .......... .......... 32% 72.8M 23s\n", + " 14550K .......... .......... .......... .......... .......... 32% 14.9M 23s\n", + " 14600K .......... .......... .......... .......... .......... 32% 67.2M 23s\n", + " 14650K .......... .......... .......... .......... .......... 32% 13.0M 23s\n", + " 14700K .......... .......... .......... .......... .......... 32% 14.0M 23s\n", + " 14750K .......... .......... .......... .......... .......... 32% 395K 23s\n", + " 14800K .......... .......... .......... .......... .......... 33% 64.9M 23s\n", + " 14850K .......... .......... .......... .......... .......... 33% 6.23M 23s\n", + " 14900K .......... .......... .......... .......... .......... 33% 556K 23s\n", + " 14950K .......... .......... .......... .......... .......... 33% 6.43M 23s\n", + " 15000K .......... .......... .......... .......... .......... 33% 5.84M 23s\n", + " 15050K .......... .......... .......... .......... .......... 33% 5.64M 23s\n", + " 15100K .......... .......... .......... .......... .......... 33% 5.83M 23s\n", + " 15150K .......... .......... .......... .......... .......... 33% 3.86M 22s\n", + " 15200K .......... .......... .......... .......... .......... 33% 5.78M 22s\n", + " 15250K .......... .......... .......... .......... .......... 34% 10.5M 22s\n", + " 15300K .......... .......... .......... .......... .......... 34% 6.22M 22s\n", + " 15350K .......... .......... .......... .......... .......... 34% 10.6M 22s\n", + " 15400K .......... .......... .......... .......... .......... 34% 11.3M 22s\n", + " 15450K .......... .......... .......... .......... .......... 34% 6.02M 22s\n", + " 15500K .......... .......... .......... .......... .......... 34% 11.5M 22s\n", + " 15550K .......... .......... .......... .......... .......... 34% 6.13M 22s\n", + " 15600K .......... .......... .......... .......... .......... 34% 12.5M 22s\n", + " 15650K .......... .......... .......... .......... .......... 34% 11.2M 21s\n", + " 15700K .......... .......... .......... .......... .......... 35% 10.6M 21s\n", + " 15750K .......... .......... .......... .......... .......... 35% 12.1M 21s\n", + " 15800K .......... .......... .......... .......... .......... 35% 11.6M 21s\n", + " 15850K .......... .......... .......... .......... .......... 35% 5.28M 21s\n", + " 15900K .......... .......... .......... .......... .......... 35% 15.4M 21s\n", + " 15950K .......... .......... .......... .......... .......... 35% 11.1M 21s\n", + " 16000K .......... .......... .......... .......... .......... 35% 11.4M 21s\n", + " 16050K .......... .......... .......... .......... .......... 35% 11.5M 21s\n", + " 16100K .......... .......... .......... .......... .......... 35% 11.6M 21s\n", + " 16150K .......... .......... .......... .......... .......... 36% 11.1M 21s\n", + " 16200K .......... .......... .......... .......... .......... 36% 11.8M 20s\n", + " 16250K .......... .......... .......... .......... .......... 36% 7.98M 20s\n", + " 16300K .......... .......... .......... .......... .......... 36% 18.8M 20s\n", + " 16350K .......... .......... .......... .......... .......... 36% 11.0M 20s\n", + " 16400K .......... .......... .......... .......... .......... 36% 12.4M 20s\n", + " 16450K .......... .......... .......... .......... .......... 36% 12.0M 20s\n", + " 16500K .......... .......... .......... .......... .......... 36% 11.6M 20s\n", + " 16550K .......... .......... .......... .......... .......... 36% 11.5M 20s\n", + " 16600K .......... .......... .......... .......... .......... 37% 34.2M 20s\n", + " 16650K .......... .......... .......... .......... .......... 37% 7.01M 20s\n", + " 16700K .......... .......... .......... .......... .......... 37% 32.7M 20s\n", + " 16750K .......... .......... .......... .......... .......... 37% 12.0M 19s\n", + " 16800K .......... .......... .......... .......... .......... 37% 14.6M 19s\n", + " 16850K .......... .......... .......... .......... .......... 37% 11.6M 19s\n", + " 16900K .......... .......... .......... .......... .......... 37% 11.2M 19s\n", + " 16950K .......... .......... .......... .......... .......... 37% 39.1M 19s\n", + " 17000K .......... .......... .......... .......... .......... 37% 12.7M 19s\n", + " 17050K .......... .......... .......... .......... .......... 38% 11.8M 19s\n", + " 17100K .......... .......... .......... .......... .......... 38% 16.0M 19s\n", + " 17150K .......... .......... .......... .......... .......... 38% 12.6M 19s\n", + " 17200K .......... .......... .......... .......... .......... 38% 12.8M 19s\n", + " 17250K .......... .......... .......... .......... .......... 38% 25.9M 19s\n", + " 17300K .......... .......... .......... .......... .......... 38% 14.2M 19s\n", + " 17350K .......... .......... .......... .......... .......... 38% 12.3M 18s\n", + " 17400K .......... .......... .......... .......... .......... 38% 17.7M 18s\n", + " 17450K .......... .......... .......... .......... .......... 38% 308K 19s\n", + " 17500K .......... .......... .......... .......... .......... 39% 71.0M 18s\n", + " 17550K .......... .......... .......... .......... .......... 39% 803K 18s\n", + " 17600K .......... .......... .......... .......... .......... 39% 11.7M 18s\n", + " 17650K .......... .......... .......... .......... .......... 39% 11.0M 18s\n", + " 17700K .......... .......... .......... .......... .......... 39% 6.00M 18s\n", + " 17750K .......... .......... .......... .......... .......... 39% 11.3M 18s\n", + " 17800K .......... .......... .......... .......... .......... 39% 6.59M 18s\n", + " 17850K .......... .......... .......... .......... .......... 39% 6.08M 18s\n", + " 17900K .......... .......... .......... .......... .......... 39% 11.7M 18s\n", + " 17950K .......... .......... .......... .......... .......... 40% 6.29M 18s\n", + " 18000K .......... .......... .......... .......... .......... 40% 11.8M 18s\n", + " 18050K .......... .......... .......... .......... .......... 40% 10.9M 18s\n", + " 18100K .......... .......... .......... .......... .......... 40% 11.5M 18s\n", + " 18150K .......... .......... .......... .......... .......... 40% 11.0M 18s\n", + " 18200K .......... .......... .......... .......... .......... 40% 12.5M 17s\n", + " 18250K .......... .......... .......... .......... .......... 40% 6.21M 17s\n", + " 18300K .......... .......... .......... .......... .......... 40% 12.0M 17s\n", + " 18350K .......... .......... .......... .......... .......... 40% 11.2M 17s\n", + " 18400K .......... .......... .......... .......... .......... 41% 12.2M 17s\n", + " 18450K .......... .......... .......... .......... .......... 41% 11.5M 17s\n", + " 18500K .......... .......... .......... .......... .......... 41% 11.5M 17s\n", + " 18550K .......... .......... .......... .......... .......... 41% 11.3M 17s\n", + " 18600K .......... .......... .......... .......... .......... 41% 12.0M 17s\n", + " 18650K .......... .......... .......... .......... .......... 41% 10.8M 17s\n", + " 18700K .......... .......... .......... .......... .......... 41% 10.5M 17s\n", + " 18750K .......... .......... .......... .......... .......... 41% 11.8M 17s\n", + " 18800K .......... .......... .......... .......... .......... 41% 11.7M 17s\n", + " 18850K .......... .......... .......... .......... .......... 42% 11.7M 17s\n", + " 18900K .......... .......... .......... .......... .......... 42% 11.8M 16s\n", + " 18950K .......... .......... .......... .......... .......... 42% 12.2M 16s\n", + " 19000K .......... .......... .......... .......... .......... 42% 11.5M 16s\n", + " 19050K .......... .......... .......... .......... .......... 42% 10.3M 16s\n", + " 19100K .......... .......... .......... .......... .......... 42% 534K 16s\n", + " 19150K .......... .......... .......... .......... .......... 42% 66.0M 16s\n", + " 19200K .......... .......... .......... .......... .......... 42% 3.08M 16s\n", + " 19250K .......... .......... .......... .......... .......... 42% 11.3M 16s\n", + " 19300K .......... .......... .......... .......... .......... 43% 12.3M 16s\n", + " 19350K .......... .......... .......... .......... .......... 43% 57.0M 16s\n", + " 19400K .......... .......... .......... .......... .......... 43% 12.4M 16s\n", + " 19450K .......... .......... .......... .......... .......... 43% 10.9M 16s\n", + " 19500K .......... .......... .......... .......... .......... 43% 12.1M 16s\n", + " 19550K .......... .......... .......... .......... .......... 43% 12.7M 16s\n", + " 19600K .......... .......... .......... .......... .......... 43% 63.5M 16s\n", + " 19650K .......... .......... .......... .......... .......... 43% 12.5M 16s\n", + " 19700K .......... .......... .......... .......... .......... 43% 11.7M 16s\n", + " 19750K .......... .......... .......... .......... .......... 44% 74.8M 15s\n", + " 19800K .......... .......... .......... .......... .......... 44% 13.2M 15s\n", + " 19850K .......... .......... .......... .......... .......... 44% 13.2M 15s\n", + " 19900K .......... .......... .......... .......... .......... 44% 57.8M 15s\n", + " 19950K .......... .......... .......... .......... .......... 44% 14.6M 15s\n", + " 20000K .......... .......... .......... .......... .......... 44% 54.2M 15s\n", + " 20050K .......... .......... .......... .......... .......... 44% 13.6M 15s\n", + " 20100K .......... .......... .......... .......... .......... 44% 14.1M 15s\n", + " 20150K .......... .......... .......... .......... .......... 44% 68.8M 15s\n", + " 20200K .......... .......... .......... .......... .......... 45% 13.8M 15s\n", + " 20250K .......... .......... .......... .......... .......... 45% 47.3M 15s\n", + " 20300K .......... .......... .......... .......... .......... 45% 13.6M 15s\n", + " 20350K .......... .......... .......... .......... .......... 45% 15.0M 15s\n", + " 20400K .......... .......... .......... .......... .......... 45% 50.6M 15s\n", + " 20450K .......... .......... .......... .......... .......... 45% 14.8M 15s\n", + " 20500K .......... .......... .......... .......... .......... 45% 51.6M 15s\n", + " 20550K .......... .......... .......... .......... .......... 45% 14.2M 14s\n", + " 20600K .......... .......... .......... .......... .......... 45% 60.1M 14s\n", + " 20650K .......... .......... .......... .......... .......... 46% 12.6M 14s\n", + " 20700K .......... .......... .......... .......... .......... 46% 64.3M 14s\n", + " 20750K .......... .......... .......... .......... .......... 46% 15.6M 14s\n", + " 20800K .......... .......... .......... .......... .......... 46% 13.9M 14s\n", + " 20850K .......... .......... .......... .......... .......... 46% 42.2M 14s\n", + " 20900K .......... .......... .......... .......... .......... 46% 16.0M 14s\n", + " 20950K .......... .......... .......... .......... .......... 46% 52.6M 14s\n", + " 21000K .......... .......... .......... .......... .......... 46% 14.8M 14s\n", + " 21050K .......... .......... .......... .......... .......... 46% 38.7M 14s\n", + " 21100K .......... .......... .......... .......... .......... 47% 16.8M 14s\n", + " 21150K .......... .......... .......... .......... .......... 47% 38.9M 14s\n", + " 21200K .......... .......... .......... .......... .......... 47% 15.1M 14s\n", + " 21250K .......... .......... .......... .......... .......... 47% 52.2M 14s\n", + " 21300K .......... .......... .......... .......... .......... 47% 14.8M 14s\n", + " 21350K .......... .......... .......... .......... .......... 47% 59.8M 13s\n", + " 21400K .......... .......... .......... .......... .......... 47% 14.6M 13s\n", + " 21450K .......... .......... .......... .......... .......... 47% 14.0M 13s\n", + " 21500K .......... .......... .......... .......... .......... 47% 55.3M 13s\n", + " 21550K .......... .......... .......... .......... .......... 48% 15.6M 13s\n", + " 21600K .......... .......... .......... .......... .......... 48% 55.1M 13s\n", + " 21650K .......... .......... .......... .......... .......... 48% 14.9M 13s\n", + " 21700K .......... .......... .......... .......... .......... 48% 54.2M 13s\n", + " 21750K .......... .......... .......... .......... .......... 48% 14.7M 13s\n", + " 21800K .......... .......... .......... .......... .......... 48% 62.7M 13s\n", + " 21850K .......... .......... .......... .......... .......... 48% 15.5M 13s\n", + " 21900K .......... .......... .......... .......... .......... 48% 52.0M 13s\n", + " 21950K .......... .......... .......... .......... .......... 48% 15.8M 13s\n", + " 22000K .......... .......... .......... .......... .......... 49% 56.5M 13s\n", + " 22050K .......... .......... .......... .......... .......... 49% 14.9M 13s\n", + " 22100K .......... .......... .......... .......... .......... 49% 59.1M 13s\n", + " 22150K .......... .......... .......... .......... .......... 49% 15.2M 13s\n", + " 22200K .......... .......... .......... .......... .......... 49% 60.9M 13s\n", + " 22250K .......... .......... .......... .......... .......... 49% 15.9M 12s\n", + " 22300K .......... .......... .......... .......... .......... 49% 35.9M 12s\n", + " 22350K .......... .......... .......... .......... .......... 49% 17.9M 12s\n", + " 22400K .......... .......... .......... .......... .......... 49% 42.8M 12s\n", + " 22450K .......... .......... .......... .......... .......... 50% 15.3M 12s\n", + " 22500K .......... .......... .......... .......... .......... 50% 62.5M 12s\n", + " 22550K .......... .......... .......... .......... .......... 50% 46.4M 12s\n", + " 22600K .......... .......... .......... .......... .......... 50% 16.9M 12s\n", + " 22650K .......... .......... .......... .......... .......... 50% 14.3M 12s\n", + " 22700K .......... .......... .......... .......... .......... 50% 58.8M 12s\n", + " 22750K .......... .......... .......... .......... .......... 50% 62.0M 12s\n", + " 22800K .......... .......... .......... .......... .......... 50% 16.0M 12s\n", + " 22850K .......... .......... .......... .......... .......... 50% 46.7M 12s\n", + " 22900K .......... .......... .......... .......... .......... 51% 17.0M 12s\n", + " 22950K .......... .......... .......... .......... .......... 51% 41.2M 12s\n", + " 23000K .......... .......... .......... .......... .......... 51% 16.3M 12s\n", + " 23050K .......... .......... .......... .......... .......... 51% 53.2M 12s\n", + " 23100K .......... .......... .......... .......... .......... 51% 4.27M 12s\n", + " 23150K .......... .......... .......... .......... .......... 51% 71.4M 12s\n", + " 23200K .......... .......... .......... .......... .......... 51% 74.3M 12s\n", + " 23250K .......... .......... .......... .......... .......... 51% 63.0M 11s\n", + " 23300K .......... .......... .......... .......... .......... 51% 82.7M 11s\n", + " 23350K .......... .......... .......... .......... .......... 52% 75.6M 11s\n", + " 23400K .......... .......... .......... .......... .......... 52% 51.2M 11s\n", + " 23450K .......... .......... .......... .......... .......... 52% 49.0M 11s\n", + " 23500K .......... .......... .......... .......... .......... 52% 15.3M 11s\n", + " 23550K .......... .......... .......... .......... .......... 52% 56.2M 11s\n", + " 23600K .......... .......... .......... .......... .......... 52% 15.9M 11s\n", + " 23650K .......... .......... .......... .......... .......... 52% 55.0M 11s\n", + " 23700K .......... .......... .......... .......... .......... 52% 84.1M 11s\n", + " 23750K .......... .......... .......... .......... .......... 53% 14.9M 11s\n", + " 23800K .......... .......... .......... .......... .......... 53% 60.4M 11s\n", + " 23850K .......... .......... .......... .......... .......... 53% 14.6M 11s\n", + " 23900K .......... .......... .......... .......... .......... 53% 56.0M 11s\n", + " 23950K .......... .......... .......... .......... .......... 53% 15.5M 11s\n", + " 24000K .......... .......... .......... .......... .......... 53% 69.4M 11s\n", + " 24050K .......... .......... .......... .......... .......... 53% 13.7M 11s\n", + " 24100K .......... .......... .......... .......... .......... 53% 42.2M 11s\n", + " 24150K .......... .......... .......... .......... .......... 53% 69.8M 11s\n", + " 24200K .......... .......... .......... .......... .......... 54% 17.5M 11s\n", + " 24250K .......... .......... .......... .......... .......... 54% 54.4M 11s\n", + " 24300K .......... .......... .......... .......... .......... 54% 126K 11s\n", + " 24350K .......... .......... .......... .......... .......... 54% 67.9M 11s\n", + " 24400K .......... .......... .......... .......... .......... 54% 932K 11s\n", + " 24450K .......... .......... .......... .......... .......... 54% 1.51M 11s\n", + " 24500K .......... .......... .......... .......... .......... 54% 201K 11s\n", + " 24550K .......... .......... .......... .......... .......... 54% 2.39M 11s\n", + " 24600K .......... .......... .......... .......... .......... 54% 2.35M 11s\n", + " 24650K .......... .......... .......... .......... .......... 55% 2.02M 11s\n", + " 24700K .......... .......... .......... .......... .......... 55% 2.89M 11s\n", + " 24750K .......... .......... .......... .......... .......... 55% 3.82M 11s\n", + " 24800K .......... .......... .......... .......... .......... 55% 3.78M 11s\n", + " 24850K .......... .......... .......... .......... .......... 55% 5.58M 11s\n", + " 24900K .......... .......... .......... .......... .......... 55% 5.67M 11s\n", + " 24950K .......... .......... .......... .......... .......... 55% 5.66M 11s\n", + " 25000K .......... .......... .......... .......... .......... 55% 5.76M 11s\n", + " 25050K .......... .......... .......... .......... .......... 55% 6.07M 10s\n", + " 25100K .......... .......... .......... .......... .......... 56% 10.2M 10s\n", + " 25150K .......... .......... .......... .......... .......... 56% 5.86M 10s\n", + " 25200K .......... .......... .......... .......... .......... 56% 11.1M 10s\n", + " 25250K .......... .......... .......... .......... .......... 56% 5.86M 10s\n", + " 25300K .......... .......... .......... .......... .......... 56% 10.8M 10s\n", + " 25350K .......... .......... .......... .......... .......... 56% 5.97M 10s\n", + " 25400K .......... .......... .......... .......... .......... 56% 10.9M 10s\n", + " 25450K .......... .......... .......... .......... .......... 56% 5.94M 10s\n", + " 25500K .......... .......... .......... .......... .......... 56% 11.7M 10s\n", + " 25550K .......... .......... .......... .......... .......... 57% 306K 10s\n", + " 25600K .......... .......... .......... .......... .......... 57% 10.6M 10s\n", + " 25650K .......... .......... .......... .......... .......... 57% 6.47M 10s\n", + " 25700K .......... .......... .......... .......... .......... 57% 10.9M 10s\n", + " 25750K .......... .......... .......... .......... .......... 57% 10.1M 10s\n", + " 25800K .......... .......... .......... .......... .......... 57% 10.9M 10s\n", + " 25850K .......... .......... .......... .......... .......... 57% 7.42M 10s\n", + " 25900K .......... .......... .......... .......... .......... 57% 7.81M 10s\n", + " 25950K .......... .......... .......... .......... .......... 57% 11.4M 10s\n", + " 26000K .......... .......... .......... .......... .......... 58% 10.5M 10s\n", + " 26050K .......... .......... .......... .......... .......... 58% 9.52M 10s\n", + " 26100K .......... .......... .......... .......... .......... 58% 6.46M 10s\n", + " 26150K .......... .......... .......... .......... .......... 58% 11.6M 10s\n", + " 26200K .......... .......... .......... .......... .......... 58% 10.8M 10s\n", + " 26250K .......... .......... .......... .......... .......... 58% 6.24M 10s\n", + " 26300K .......... .......... .......... .......... .......... 58% 11.8M 10s\n", + " 26350K .......... .......... .......... .......... .......... 58% 10.5M 10s\n", + " 26400K .......... .......... .......... .......... .......... 58% 11.0M 9s\n", + " 26450K .......... .......... .......... .......... .......... 59% 10.8M 9s\n", + " 26500K .......... .......... .......... .......... .......... 59% 5.79M 9s\n", + " 26550K .......... .......... .......... .......... .......... 59% 11.3M 9s\n", + " 26600K .......... .......... .......... .......... .......... 59% 11.0M 9s\n", + " 26650K .......... .......... .......... .......... .......... 59% 5.95M 9s\n", + " 26700K .......... .......... .......... .......... .......... 59% 11.1M 9s\n", + " 26750K .......... .......... .......... .......... .......... 59% 11.3M 9s\n", + " 26800K .......... .......... .......... .......... .......... 59% 11.3M 9s\n", + " 26850K .......... .......... .......... .......... .......... 59% 10.9M 9s\n", + " 26900K .......... .......... .......... .......... .......... 60% 6.35M 9s\n", + " 26950K .......... .......... .......... .......... .......... 60% 5.87M 9s\n", + " 27000K .......... .......... .......... .......... .......... 60% 5.88M 9s\n", + " 27050K .......... .......... .......... .......... .......... 60% 4.03M 9s\n", + " 27100K .......... .......... .......... .......... .......... 60% 216K 9s\n", + " 27150K .......... .......... .......... .......... .......... 60% 3.90M 9s\n", + " 27200K .......... .......... .......... .......... .......... 60% 3.86M 9s\n", + " 27250K .......... .......... .......... .......... .......... 60% 3.80M 9s\n", + " 27300K .......... .......... .......... .......... .......... 60% 3.96M 9s\n", + " 27350K .......... .......... .......... .......... .......... 61% 5.83M 9s\n", + " 27400K .......... .......... .......... .......... .......... 61% 5.70M 9s\n", + " 27450K .......... .......... .......... .......... .......... 61% 3.92M 9s\n", + " 27500K .......... .......... .......... .......... .......... 61% 5.90M 9s\n", + " 27550K .......... .......... .......... .......... .......... 61% 5.83M 9s\n", + " 27600K .......... .......... .......... .......... .......... 61% 5.71M 9s\n", + " 27650K .......... .......... .......... .......... .......... 61% 10.5M 9s\n", + " 27700K .......... .......... .......... .......... .......... 61% 5.98M 9s\n", + " 27750K .......... .......... .......... .......... .......... 61% 11.1M 9s\n", + " 27800K .......... .......... .......... .......... .......... 62% 5.92M 9s\n", + " 27850K .......... .......... .......... .......... .......... 62% 5.91M 9s\n", + " 27900K .......... .......... .......... .......... .......... 62% 10.7M 9s\n", + " 27950K .......... .......... .......... .......... .......... 62% 10.9M 8s\n", + " 28000K .......... .......... .......... .......... .......... 62% 6.21M 8s\n", + " 28050K .......... .......... .......... .......... .......... 62% 11.0M 8s\n", + " 28100K .......... .......... .......... .......... .......... 62% 12.1M 8s\n", + " 28150K .......... .......... .......... .......... .......... 62% 11.2M 8s\n", + " 28200K .......... .......... .......... .......... .......... 62% 6.04M 8s\n", + " 28250K .......... .......... .......... .......... .......... 63% 10.9M 8s\n", + " 28300K .......... .......... .......... .......... .......... 63% 11.3M 8s\n", + " 28350K .......... .......... .......... .......... .......... 63% 12.2M 8s\n", + " 28400K .......... .......... .......... .......... .......... 63% 6.26M 8s\n", + " 28450K .......... .......... .......... .......... .......... 63% 12.0M 8s\n", + " 28500K .......... .......... .......... .......... .......... 63% 11.5M 8s\n", + " 28550K .......... .......... .......... .......... .......... 63% 11.9M 8s\n", + " 28600K .......... .......... .......... .......... .......... 63% 11.0M 8s\n", + " 28650K .......... .......... .......... .......... .......... 63% 11.9M 8s\n", + " 28700K .......... .......... .......... .......... .......... 64% 11.6M 8s\n", + " 28750K .......... .......... .......... .......... .......... 64% 11.8M 8s\n", + " 28800K .......... .......... .......... .......... .......... 64% 11.0M 8s\n", + " 28850K .......... .......... .......... .......... .......... 64% 11.4M 8s\n", + " 28900K .......... .......... .......... .......... .......... 64% 13.1M 8s\n", + " 28950K .......... .......... .......... .......... .......... 64% 11.7M 8s\n", + " 29000K .......... .......... .......... .......... .......... 64% 11.3M 8s\n", + " 29050K .......... .......... .......... .......... .......... 64% 12.5M 8s\n", + " 29100K .......... .......... .......... .......... .......... 64% 12.0M 8s\n", + " 29150K .......... .......... .......... .......... .......... 65% 11.1M 8s\n", + " 29200K .......... .......... .......... .......... .......... 65% 76.5M 8s\n", + " 29250K .......... .......... .......... .......... .......... 65% 12.2M 8s\n", + " 29300K .......... .......... .......... .......... .......... 65% 11.2M 8s\n", + " 29350K .......... .......... .......... .......... .......... 65% 13.0M 7s\n", + " 29400K .......... .......... .......... .......... .......... 65% 13.3M 7s\n", + " 29450K .......... .......... .......... .......... .......... 65% 9.92M 7s\n", + " 29500K .......... .......... .......... .......... .......... 65% 15.0M 7s\n", + " 29550K .......... .......... .......... .......... .......... 65% 53.4M 7s\n", + " 29600K .......... .......... .......... .......... .......... 66% 11.9M 7s\n", + " 29650K .......... .......... .......... .......... .......... 66% 13.3M 7s\n", + " 29700K .......... .......... .......... .......... .......... 66% 10.3M 7s\n", + " 29750K .......... .......... .......... .......... .......... 66% 13.8M 7s\n", + " 29800K .......... .......... .......... .......... .......... 66% 62.2M 7s\n", + " 29850K .......... .......... .......... .......... .......... 66% 12.2M 7s\n", + " 29900K .......... .......... .......... .......... .......... 66% 392K 7s\n", + " 29950K .......... .......... .......... .......... .......... 66% 3.09M 7s\n", + " 30000K .......... .......... .......... .......... .......... 66% 5.60M 7s\n", + " 30050K .......... .......... .......... .......... .......... 67% 12.3M 7s\n", + " 30100K .......... .......... .......... .......... .......... 67% 11.5M 7s\n", + " 30150K .......... .......... .......... .......... .......... 67% 12.1M 7s\n", + " 30200K .......... .......... .......... .......... .......... 67% 689K 7s\n", + " 30250K .......... .......... .......... .......... .......... 67% 5.87M 7s\n", + " 30300K .......... .......... .......... .......... .......... 67% 5.92M 7s\n", + " 30350K .......... .......... .......... .......... .......... 67% 11.1M 7s\n", + " 30400K .......... .......... .......... .......... .......... 67% 5.57M 7s\n", + " 30450K .......... .......... .......... .......... .......... 67% 10.7M 7s\n", + " 30500K .......... .......... .......... .......... .......... 68% 11.2M 7s\n", + " 30550K .......... .......... .......... .......... .......... 68% 10.2M 7s\n", + " 30600K .......... .......... .......... .......... .......... 68% 6.54M 7s\n", + " 30650K .......... .......... .......... .......... .......... 68% 10.8M 7s\n", + " 30700K .......... .......... .......... .......... .......... 68% 10.6M 7s\n", + " 30750K .......... .......... .......... .......... .......... 68% 6.17M 7s\n", + " 30800K .......... .......... .......... .......... .......... 68% 11.5M 7s\n", + " 30850K .......... .......... .......... .......... .......... 68% 10.3M 7s\n", + " 30900K .......... .......... .......... .......... .......... 68% 11.6M 7s\n", + " 30950K .......... .......... .......... .......... .......... 69% 11.6M 7s\n", + " 31000K .......... .......... .......... .......... .......... 69% 10.4M 6s\n", + " 31050K .......... .......... .......... .......... .......... 69% 11.7M 6s\n", + " 31100K .......... .......... .......... .......... .......... 69% 11.9M 6s\n", + " 31150K .......... .......... .......... .......... .......... 69% 11.9M 6s\n", + " 31200K .......... .......... .......... .......... .......... 69% 10.9M 6s\n", + " 31250K .......... .......... .......... .......... .......... 69% 11.2M 6s\n", + " 31300K .......... .......... .......... .......... .......... 69% 11.3M 6s\n", + " 31350K .......... .......... .......... .......... .......... 69% 11.3M 6s\n", + " 31400K .......... .......... .......... .......... .......... 70% 11.6M 6s\n", + " 31450K .......... .......... .......... .......... .......... 70% 11.5M 6s\n", + " 31500K .......... .......... .......... .......... .......... 70% 11.8M 6s\n", + " 31550K .......... .......... .......... .......... .......... 70% 12.1M 6s\n", + " 31600K .......... .......... .......... .......... .......... 70% 11.1M 6s\n", + " 31650K .......... .......... .......... .......... .......... 70% 12.1M 6s\n", + " 31700K .......... .......... .......... .......... .......... 70% 10.8M 6s\n", + " 31750K .......... .......... .......... .......... .......... 70% 14.0M 6s\n", + " 31800K .......... .......... .......... .......... .......... 70% 12.0M 6s\n", + " 31850K .......... .......... .......... .......... .......... 71% 11.5M 6s\n", + " 31900K .......... .......... .......... .......... .......... 71% 40.4M 6s\n", + " 31950K .......... .......... .......... .......... .......... 71% 12.8M 6s\n", + " 32000K .......... .......... .......... .......... .......... 71% 11.4M 6s\n", + " 32050K .......... .......... .......... .......... .......... 71% 11.8M 6s\n", + " 32100K .......... .......... .......... .......... .......... 71% 12.4M 6s\n", + " 32150K .......... .......... .......... .......... .......... 71% 61.0M 6s\n", + " 32200K .......... .......... .......... .......... .......... 71% 12.3M 6s\n", + " 32250K .......... .......... .......... .......... .......... 71% 11.7M 6s\n", + " 32300K .......... .......... .......... .......... .......... 72% 12.8M 6s\n", + " 32350K .......... .......... .......... .......... .......... 72% 12.8M 6s\n", + " 32400K .......... .......... .......... .......... .......... 72% 43.1M 6s\n", + " 32450K .......... .......... .......... .......... .......... 72% 12.0M 6s\n", + " 32500K .......... .......... .......... .......... .......... 72% 14.5M 6s\n", + " 32550K .......... .......... .......... .......... .......... 72% 11.7M 6s\n", + " 32600K .......... .......... .......... .......... .......... 72% 56.1M 5s\n", + " 32650K .......... .......... .......... .......... .......... 72% 12.5M 5s\n", + " 32700K .......... .......... .......... .......... .......... 72% 13.3M 5s\n", + " 32750K .......... .......... .......... .......... .......... 73% 12.5M 5s\n", + " 32800K .......... .......... .......... .......... .......... 73% 73.6M 5s\n", + " 32850K .......... .......... .......... .......... .......... 73% 11.5M 5s\n", + " 32900K .......... .......... .......... .......... .......... 73% 12.9M 5s\n", + " 32950K .......... .......... .......... .......... .......... 73% 12.0M 5s\n", + " 33000K .......... .......... .......... .......... .......... 73% 69.2M 5s\n", + " 33050K .......... .......... .......... .......... .......... 73% 138K 5s\n", + " 33100K .......... .......... .......... .......... .......... 73% 625K 5s\n", + " 33150K .......... .......... .......... .......... .......... 73% 61.7M 5s\n", + " 33200K .......... .......... .......... .......... .......... 74% 6.76M 5s\n", + " 33250K .......... .......... .......... .......... .......... 74% 10.8M 5s\n", + " 33300K .......... .......... .......... .......... .......... 74% 6.10M 5s\n", + " 33350K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + " 33400K .......... .......... .......... .......... .......... 74% 2.81M 5s\n", + " 33450K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + " 33500K .......... .......... .......... .......... .......... 74% 11.0M 5s\n", + " 33550K .......... .......... .......... .......... .......... 74% 6.05M 5s\n", + " 33600K .......... .......... .......... .......... .......... 74% 255K 5s\n", + " 33650K .......... .......... .......... .......... .......... 75% 106K 5s\n", + " 33700K .......... .......... .......... .......... .......... 75% 2.05M 5s\n", + " 33750K .......... .......... .......... .......... .......... 75% 1.56M 5s\n", + " 33800K .......... .......... .......... .......... .......... 75% 2.07M 5s\n", + " 33850K .......... .......... .......... .......... .......... 75% 2.40M 5s\n", + " 33900K .......... .......... .......... .......... .......... 75% 4.03M 5s\n", + " 33950K .......... .......... .......... .......... .......... 75% 5.94M 5s\n", + " 34000K .......... .......... .......... .......... .......... 75% 5.89M 5s\n", + " 34050K .......... .......... .......... .......... .......... 75% 5.73M 5s\n", + " 34100K .......... .......... .......... .......... .......... 76% 5.65M 5s\n", + " 34150K .......... .......... .......... .......... .......... 76% 5.71M 5s\n", + " 34200K .......... .......... .......... .......... .......... 76% 10.6M 5s\n", + " 34250K .......... .......... .......... .......... .......... 76% 3.95M 5s\n", + " 34300K .......... .......... .......... .......... .......... 76% 11.1M 5s\n", + " 34350K .......... .......... .......... .......... .......... 76% 5.87M 5s\n", + " 34400K .......... .......... .......... .......... .......... 76% 11.3M 5s\n", + " 34450K .......... .......... .......... .......... .......... 76% 6.15M 5s\n", + " 34500K .......... .......... .......... .......... .......... 76% 11.2M 5s\n", + " 34550K .......... .......... .......... .......... .......... 77% 11.4M 5s\n", + " 34600K .......... .......... .......... .......... .......... 77% 507K 5s\n", + " 34650K .......... .......... .......... .......... .......... 77% 7.05M 5s\n", + " 34700K .......... .......... .......... .......... .......... 77% 303K 5s\n", + " 34750K .......... .......... .......... .......... .......... 77% 76.8K 5s\n", + " 34800K .......... .......... .......... .......... .......... 77% 25.0K 5s\n", + " 34850K .......... .......... .......... .......... .......... 77% 20.6K 6s\n", + " 34900K .......... .......... .......... .......... .......... 77% 24.9K 7s\n", + " 34950K .......... .......... .......... .......... .......... 77% 32.2K 7s\n", + " 35000K .......... .......... .......... .......... .......... 78% 342K 7s\n", + " 35050K .......... .......... .......... .......... .......... 78% 2.93M 7s\n", + " 35100K .......... .......... .......... .......... .......... 78% 710K 7s\n", + " 35150K .......... .......... .......... .......... .......... 78% 2.84M 7s\n", + " 35200K .......... .......... .......... .......... .......... 78% 3.83M 7s\n", + " 35250K .......... .......... .......... .......... .......... 78% 3.83M 7s\n", + " 35300K .......... .......... .......... .......... .......... 78% 5.75M 7s\n", + " 35350K .......... .......... .......... .......... .......... 78% 3.93M 7s\n", + " 35400K .......... .......... .......... .......... .......... 78% 5.78M 7s\n", + " 35450K .......... .......... .......... .......... .......... 79% 3.94M 7s\n", + " 35500K .......... .......... .......... .......... .......... 79% 5.72M 7s\n", + " 35550K .......... .......... .......... .......... .......... 79% 9.21M 7s\n", + " 35600K .......... .......... .......... .......... .......... 79% 7.00M 7s\n", + " 35650K .......... .......... .......... .......... .......... 79% 6.46M 7s\n", + " 35700K .......... .......... .......... .......... .......... 79% 9.02M 6s\n", + " 35750K .......... .......... .......... .......... .......... 79% 11.2M 6s\n", + " 35800K .......... .......... .......... .......... .......... 79% 7.35M 6s\n", + " 35850K .......... .......... .......... .......... .......... 79% 8.65M 6s\n", + " 35900K .......... .......... .......... .......... .......... 80% 7.56M 6s\n", + " 35950K .......... .......... .......... .......... .......... 80% 12.1M 6s\n", + " 36000K .......... .......... .......... .......... .......... 80% 7.29M 6s\n", + " 36050K .......... .......... .......... .......... .......... 80% 11.2M 6s\n", + " 36100K .......... .......... .......... .......... .......... 80% 11.6M 6s\n", + " 36150K .......... .......... .......... .......... .......... 80% 12.4M 6s\n", + " 36200K .......... .......... .......... .......... .......... 80% 6.52M 6s\n", + " 36250K .......... .......... .......... .......... .......... 80% 11.5M 6s\n", + " 36300K .......... .......... .......... .......... .......... 80% 11.6M 6s\n", + " 36350K .......... .......... .......... .......... .......... 81% 12.0M 6s\n", + " 36400K .......... .......... .......... .......... .......... 81% 12.9M 6s\n", + " 36450K .......... .......... .......... .......... .......... 81% 12.3M 6s\n", + " 36500K .......... .......... .......... .......... .......... 81% 11.5M 6s\n", + " 36550K .......... .......... .......... .......... .......... 81% 12.4M 6s\n", + " 36600K .......... .......... .......... .......... .......... 81% 13.2M 6s\n", + " 36650K .......... .......... .......... .......... .......... 81% 6.11M 6s\n", + " 36700K .......... .......... .......... .......... .......... 81% 11.9M 6s\n", + " 36750K .......... .......... .......... .......... .......... 81% 11.9M 6s\n", + " 36800K .......... .......... .......... .......... .......... 82% 58.9M 6s\n", + " 36850K .......... .......... .......... .......... .......... 82% 12.4M 6s\n", + " 36900K .......... .......... .......... .......... .......... 82% 11.5M 5s\n", + " 36950K .......... .......... .......... .......... .......... 82% 8.63M 5s\n", + " 37000K .......... .......... .......... .......... .......... 82% 11.9M 5s\n", + " 37050K .......... .......... .......... .......... .......... 82% 10.5M 5s\n", + " 37100K .......... .......... .......... .......... .......... 82% 13.3M 5s\n", + " 37150K .......... .......... .......... .......... .......... 82% 11.8M 5s\n", + " 37200K .......... .......... .......... .......... .......... 82% 12.2M 5s\n", + " 37250K .......... .......... .......... .......... .......... 83% 76.1M 5s\n", + " 37300K .......... .......... .......... .......... .......... 83% 11.5M 5s\n", + " 37350K .......... .......... .......... .......... .......... 83% 12.5M 5s\n", + " 37400K .......... .......... .......... .......... .......... 83% 12.6M 5s\n", + " 37450K .......... .......... .......... .......... .......... 83% 3.93M 5s\n", + " 37500K .......... .......... .......... .......... .......... 83% 11.1M 5s\n", + " 37550K .......... .......... .......... .......... .......... 83% 12.1M 5s\n", + " 37600K .......... .......... .......... .......... .......... 83% 13.0M 5s\n", + " 37650K .......... .......... .......... .......... .......... 83% 51.0M 5s\n", + " 37700K .......... .......... .......... .......... .......... 84% 11.2M 5s\n", + " 37750K .......... .......... .......... .......... .......... 84% 13.2M 5s\n", + " 37800K .......... .......... .......... .......... .......... 84% 126K 5s\n", + " 37850K .......... .......... .......... .......... .......... 84% 497K 5s\n", + " 37900K .......... .......... .......... .......... .......... 84% 10.6M 5s\n", + " 37950K .......... .......... .......... .......... .......... 84% 519K 5s\n", + " 38000K .......... .......... .......... .......... .......... 84% 124K 5s\n", + " 38050K .......... .......... .......... .......... .......... 84% 11.6M 5s\n", + " 38100K .......... .......... .......... .......... .......... 84% 384K 5s\n", + " 38150K .......... .......... .......... .......... .......... 85% 136K 5s\n", + " 38200K .......... .......... .......... .......... .......... 85% 124K 5s\n", + " 38250K .......... .......... .......... .......... .......... 85% 59.6K 5s\n", + " 38300K .......... .......... .......... .......... .......... 85% 5.63M 5s\n", + " 38350K .......... .......... .......... .......... .......... 85% 93.8K 5s\n", + " 38400K .......... .......... .......... .......... .......... 85% 149K 5s\n", + " 38450K .......... .......... .......... .......... .......... 85% 2.90M 5s\n", + " 38500K .......... .......... .......... .......... .......... 85% 3.84M 5s\n", + " 38550K .......... .......... .......... .......... .......... 85% 3.75M 5s\n", + " 38600K .......... .......... .......... .......... .......... 86% 5.79M 5s\n", + " 38650K .......... .......... .......... .......... .......... 86% 3.91M 5s\n", + " 38700K .......... .......... .......... .......... .......... 86% 11.5M 5s\n", + " 38750K .......... .......... .......... .......... .......... 86% 6.18M 5s\n", + " 38800K .......... .......... .......... .......... .......... 86% 10.4M 5s\n", + " 38850K .......... .......... .......... .......... .......... 86% 11.7M 5s\n", + " 38900K .......... .......... .......... .......... .......... 86% 12.5M 4s\n", + " 38950K .......... .......... .......... .......... .......... 86% 11.4M 4s\n", + " 39000K .......... .......... .......... .......... .......... 86% 13.4M 4s\n", + " 39050K .......... .......... .......... .......... .......... 87% 26.5M 4s\n", + " 39100K .......... .......... .......... .......... .......... 87% 18.7M 4s\n", + " 39150K .......... .......... .......... .......... .......... 87% 12.6M 4s\n", + " 39200K .......... .......... .......... .......... .......... 87% 30.5M 4s\n", + " 39250K .......... .......... .......... .......... .......... 87% 15.6M 4s\n", + " 39300K .......... .......... .......... .......... .......... 87% 41.8M 4s\n", + " 39350K .......... .......... .......... .......... .......... 87% 16.7M 4s\n", + " 39400K .......... .......... .......... .......... .......... 87% 34.3M 4s\n", + " 39450K .......... .......... .......... .......... .......... 87% 16.1M 4s\n", + " 39500K .......... .......... .......... .......... .......... 88% 16.4M 4s\n", + " 39550K .......... .......... .......... .......... .......... 88% 38.0M 4s\n", + " 39600K .......... .......... .......... .......... .......... 88% 16.6M 4s\n", + " 39650K .......... .......... .......... .......... .......... 88% 31.5M 4s\n", + " 39700K .......... .......... .......... .......... .......... 88% 17.9M 4s\n", + " 39750K .......... .......... .......... .......... .......... 88% 38.0M 4s\n", + " 39800K .......... .......... .......... .......... .......... 88% 19.6M 4s\n", + " 39850K .......... .......... .......... .......... .......... 88% 28.5M 4s\n", + " 39900K .......... .......... .......... .......... .......... 88% 18.0M 4s\n", + " 39950K .......... .......... .......... .......... .......... 89% 14.1M 4s\n", + " 40000K .......... .......... .......... .......... .......... 89% 32.8M 4s\n", + " 40050K .......... .......... .......... .......... .......... 89% 17.6M 4s\n", + " 40100K .......... .......... .......... .......... .......... 89% 37.7M 3s\n", + " 40150K .......... .......... .......... .......... .......... 89% 17.7M 3s\n", + " 40200K .......... .......... .......... .......... .......... 89% 42.2M 3s\n", + " 40250K .......... .......... .......... .......... .......... 89% 15.2M 3s\n", + " 40300K .......... .......... .......... .......... .......... 89% 47.3M 3s\n", + " 40350K .......... .......... .......... .......... .......... 89% 16.7M 3s\n", + " 40400K .......... .......... .......... .......... .......... 90% 44.9M 3s\n", + " 40450K .......... .......... .......... .......... .......... 90% 16.6M 3s\n", + " 40500K .......... .......... .......... .......... .......... 90% 35.6M 3s\n", + " 40550K .......... .......... .......... .......... .......... 90% 18.5M 3s\n", + " 40600K .......... .......... .......... .......... .......... 90% 43.4M 3s\n", + " 40650K .......... .......... .......... .......... .......... 90% 8.45M 3s\n", + " 40700K .......... .......... .......... .......... .......... 90% 75.7M 3s\n", + " 40750K .......... .......... .......... .......... .......... 90% 6.56M 3s\n", + " 40800K .......... .......... .......... .......... .......... 90% 77.8M 3s\n", + " 40850K .......... .......... .......... .......... .......... 91% 12.8M 3s\n", + " 40900K .......... .......... .......... .......... .......... 91% 12.6M 3s\n", + " 40950K .......... .......... .......... .......... .......... 91% 76.6M 3s\n", + " 41000K .......... .......... .......... .......... .......... 91% 12.0M 3s\n", + " 41050K .......... .......... .......... .......... .......... 91% 12.7M 3s\n", + " 41100K .......... .......... .......... .......... .......... 91% 12.6M 3s\n", + " 41150K .......... .......... .......... .......... .......... 91% 62.8M 3s\n", + " 41200K .......... .......... .......... .......... .......... 91% 13.5M 3s\n", + " 41250K .......... .......... .......... .......... .......... 91% 61.5M 3s\n", + " 41300K .......... .......... .......... .......... .......... 92% 13.5M 3s\n", + " 41350K .......... .......... .......... .......... .......... 92% 12.1M 2s\n", + " 41400K .......... .......... .......... .......... .......... 92% 70.3M 2s\n", + " 41450K .......... .......... .......... .......... .......... 92% 12.1M 2s\n", + " 41500K .......... .......... .......... .......... .......... 92% 16.0M 2s\n", + " 41550K .......... .......... .......... .......... .......... 92% 4.60M 2s\n", + " 41600K .......... .......... .......... .......... .......... 92% 67.4M 2s\n", + " 41650K .......... .......... .......... .......... .......... 92% 12.9M 2s\n", + " 41700K .......... .......... .......... .......... .......... 92% 12.6M 2s\n", + " 41750K .......... .......... .......... .......... .......... 93% 48.8M 2s\n", + " 41800K .......... .......... .......... .......... .......... 93% 16.1M 2s\n", + " 41850K .......... .......... .......... .......... .......... 93% 49.1M 2s\n", + " 41900K .......... .......... .......... .......... .......... 93% 12.6M 2s\n", + " 41950K .......... .......... .......... .......... .......... 93% 12.8M 2s\n", + " 42000K .......... .......... .......... .......... .......... 93% 63.3M 2s\n", + " 42050K .......... .......... .......... .......... .......... 93% 12.9M 2s\n", + " 42100K .......... .......... .......... .......... .......... 93% 73.3M 2s\n", + " 42150K .......... .......... .......... .......... .......... 93% 13.7M 2s\n", + " 42200K .......... .......... .......... .......... .......... 94% 13.2M 2s\n", + " 42250K .......... .......... .......... .......... .......... 94% 47.8M 2s\n", + " 42300K .......... .......... .......... .......... .......... 94% 12.0M 2s\n", + " 42350K .......... .......... .......... .......... .......... 94% 66.3M 2s\n", + " 42400K .......... .......... .......... .......... .......... 94% 14.1M 2s\n", + " 42450K .......... .......... .......... .......... .......... 94% 67.6M 2s\n", + " 42500K .......... .......... .......... .......... .......... 94% 14.5M 2s\n", + " 42550K .......... .......... .......... .......... .......... 94% 12.7M 2s\n", + " 42600K .......... .......... .......... .......... .......... 94% 65.3M 2s\n", + " 42650K .......... .......... .......... .......... .......... 95% 13.0M 2s\n", + " 42700K .......... .......... .......... .......... .......... 95% 77.4M 1s\n", + " 42750K .......... .......... .......... .......... .......... 95% 13.2M 1s\n", + " 42800K .......... .......... .......... .......... .......... 95% 73.2M 1s\n", + " 42850K .......... .......... .......... .......... .......... 95% 13.5M 1s\n", + " 42900K .......... .......... .......... .......... .......... 95% 12.9M 1s\n", + " 42950K .......... .......... .......... .......... .......... 95% 66.7M 1s\n", + " 43000K .......... .......... .......... .......... .......... 95% 14.3M 1s\n", + " 43050K .......... .......... .......... .......... .......... 95% 56.6M 1s\n", + " 43100K .......... .......... .......... .......... .......... 96% 13.5M 1s\n", + " 43150K .......... .......... .......... .......... .......... 96% 76.3M 1s\n", + " 43200K .......... .......... .......... .......... .......... 96% 12.8M 1s\n", + " 43250K .......... .......... .......... .......... .......... 96% 66.5M 1s\n", + " 43300K .......... .......... .......... .......... .......... 96% 14.4M 1s\n", + " 43350K .......... .......... .......... .......... .......... 96% 69.8M 1s\n", + " 43400K .......... .......... .......... .......... .......... 96% 13.9M 1s\n", + " 43450K .......... .......... .......... .......... .......... 96% 13.4M 1s\n", + " 43500K .......... .......... .......... .......... .......... 96% 56.5M 1s\n", + " 43550K .......... .......... .......... .......... .......... 97% 14.5M 1s\n", + " 43600K .......... .......... .......... .......... .......... 97% 67.3M 1s\n", + " 43650K .......... .......... .......... .......... .......... 97% 13.6M 1s\n", + " 43700K .......... .......... .......... .......... .......... 97% 78.9M 1s\n", + " 43750K .......... .......... .......... .......... .......... 97% 13.2M 1s\n", + " 43800K .......... .......... .......... .......... .......... 97% 68.9M 1s\n", + " 43850K .......... .......... .......... .......... .......... 97% 12.9M 1s\n", + " 43900K .......... .......... .......... .......... .......... 97% 66.4M 1s\n", + " 43950K .......... .......... .......... .......... .......... 97% 14.0M 1s\n", + " 44000K .......... .......... .......... .......... .......... 98% 63.3M 1s\n", + " 44050K .......... .......... .......... .......... .......... 98% 14.0M 1s\n", + " 44100K .......... .......... .......... .......... .......... 98% 65.0M 1s\n", + " 44150K .......... .......... .......... .......... .......... 98% 13.6M 0s\n", + " 44200K .......... .......... .......... .......... .......... 98% 62.7M 0s\n", + " 44250K .......... .......... .......... .......... .......... 98% 14.0M 0s\n", + " 44300K .......... .......... .......... .......... .......... 98% 67.0M 0s\n", + " 44350K .......... .......... .......... .......... .......... 98% 13.9M 0s\n", + " 44400K .......... .......... .......... .......... .......... 98% 54.4M 0s\n", + " 44450K .......... .......... .......... .......... .......... 99% 16.1M 0s\n", + " 44500K .......... .......... .......... .......... .......... 99% 56.0M 0s\n", + " 44550K .......... .......... .......... .......... .......... 99% 14.2M 0s\n", + " 44600K .......... .......... .......... .......... .......... 99% 55.1M 0s\n", + " 44650K .......... .......... .......... .......... .......... 99% 13.8M 0s\n", + " 44700K .......... .......... .......... .......... .......... 99% 64.7M 0s\n", + " 44750K .......... .......... .......... .......... .......... 99% 15.9M 0s\n", + " 44800K .......... .......... .......... .......... .......... 99% 62.7M 0s\n", + " 44850K .......... .......... .......... .......... .......... 99% 73.7M 0s\n", + " 44900K ... 100% 7.37T=29s\n", "\n" ] }, @@ -1500,7 +1500,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2023-04-03 22:14:05 (34.7 MB/s) - ‘oceanspy_particle_properties.nc’ saved [45981653/45981653]\n", + "2023-04-11 22:44:37 (1.49 MB/s) - ‘oceanspy_particle_properties.nc’ saved [45981653/45981653]\n", "\n" ] } @@ -1594,11 +1594,11 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:06.376442Z", - "iopub.status.busy": "2023-04-04T02:14:06.375793Z", - "iopub.status.idle": "2023-04-04T02:14:06.409345Z", - "shell.execute_reply": "2023-04-04T02:14:06.403005Z", - "shell.execute_reply.started": "2023-04-04T02:14:06.376365Z" + "iopub.execute_input": "2023-04-12T02:44:37.498668Z", + "iopub.status.busy": "2023-04-12T02:44:37.497955Z", + "iopub.status.idle": "2023-04-12T02:44:37.524779Z", + "shell.execute_reply": "2023-04-12T02:44:37.522353Z", + "shell.execute_reply.started": "2023-04-12T02:44:37.498580Z" } }, "outputs": [ @@ -1654,11 +1654,11 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:06.413597Z", - "iopub.status.busy": "2023-04-04T02:14:06.412931Z", - "iopub.status.idle": "2023-04-04T02:14:06.828086Z", - "shell.execute_reply": "2023-04-04T02:14:06.825564Z", - "shell.execute_reply.started": "2023-04-04T02:14:06.413541Z" + "iopub.execute_input": "2023-04-12T02:44:37.534021Z", + "iopub.status.busy": "2023-04-12T02:44:37.533414Z", + "iopub.status.idle": "2023-04-12T02:44:37.981583Z", + "shell.execute_reply": "2023-04-12T02:44:37.978344Z", + "shell.execute_reply.started": "2023-04-12T02:44:37.533965Z" } }, "outputs": [ @@ -1708,11 +1708,11 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:06.833109Z", - "iopub.status.busy": "2023-04-04T02:14:06.832520Z", - "iopub.status.idle": "2023-04-04T02:14:07.340455Z", - "shell.execute_reply": "2023-04-04T02:14:07.337912Z", - "shell.execute_reply.started": "2023-04-04T02:14:06.833051Z" + "iopub.execute_input": "2023-04-12T02:44:37.986592Z", + "iopub.status.busy": "2023-04-12T02:44:37.985841Z", + "iopub.status.idle": "2023-04-12T02:44:38.476621Z", + "shell.execute_reply": "2023-04-12T02:44:38.473575Z", + "shell.execute_reply.started": "2023-04-12T02:44:37.986534Z" } }, "outputs": [ @@ -1769,11 +1769,11 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:07.344241Z", - "iopub.status.busy": "2023-04-04T02:14:07.343642Z", - "iopub.status.idle": "2023-04-04T02:14:08.249060Z", - "shell.execute_reply": "2023-04-04T02:14:08.246775Z", - "shell.execute_reply.started": "2023-04-04T02:14:07.344184Z" + "iopub.execute_input": "2023-04-12T02:44:38.479630Z", + "iopub.status.busy": "2023-04-12T02:44:38.479018Z", + "iopub.status.idle": "2023-04-12T02:44:39.483807Z", + "shell.execute_reply": "2023-04-12T02:44:39.481711Z", + "shell.execute_reply.started": "2023-04-12T02:44:38.479572Z" } }, "outputs": [], @@ -1812,11 +1812,11 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:08.254042Z", - "iopub.status.busy": "2023-04-04T02:14:08.252878Z", - "iopub.status.idle": "2023-04-04T02:14:34.683376Z", - "shell.execute_reply": "2023-04-04T02:14:34.680449Z", - "shell.execute_reply.started": "2023-04-04T02:14:08.253941Z" + "iopub.execute_input": "2023-04-12T02:44:39.487673Z", + "iopub.status.busy": "2023-04-12T02:44:39.487043Z", + "iopub.status.idle": "2023-04-12T02:45:05.767803Z", + "shell.execute_reply": "2023-04-12T02:45:05.764478Z", + "shell.execute_reply.started": "2023-04-12T02:44:39.487614Z" } }, "outputs": [ @@ -1894,11 +1894,11 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:34.686469Z", - "iopub.status.busy": "2023-04-04T02:14:34.685821Z", - "iopub.status.idle": "2023-04-04T02:14:48.111732Z", - "shell.execute_reply": "2023-04-04T02:14:48.096357Z", - "shell.execute_reply.started": "2023-04-04T02:14:34.686409Z" + "iopub.execute_input": "2023-04-12T02:45:05.771491Z", + "iopub.status.busy": "2023-04-12T02:45:05.770846Z", + "iopub.status.idle": "2023-04-12T02:45:18.514901Z", + "shell.execute_reply": "2023-04-12T02:45:18.512074Z", + "shell.execute_reply.started": "2023-04-12T02:45:05.771420Z" } }, "outputs": [ @@ -1982,11 +1982,11 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:48.115817Z", - "iopub.status.busy": "2023-04-04T02:14:48.115150Z", - "iopub.status.idle": "2023-04-04T02:14:48.137585Z", - "shell.execute_reply": "2023-04-04T02:14:48.134350Z", - "shell.execute_reply.started": "2023-04-04T02:14:48.115760Z" + "iopub.execute_input": "2023-04-12T02:45:18.518962Z", + "iopub.status.busy": "2023-04-12T02:45:18.518364Z", + "iopub.status.idle": "2023-04-12T02:45:18.536366Z", + "shell.execute_reply": "2023-04-12T02:45:18.533487Z", + "shell.execute_reply.started": "2023-04-12T02:45:18.518903Z" } }, "outputs": [], @@ -2010,11 +2010,11 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:48.143180Z", - "iopub.status.busy": "2023-04-04T02:14:48.141626Z", - "iopub.status.idle": "2023-04-04T02:14:52.246919Z", - "shell.execute_reply": "2023-04-04T02:14:52.244502Z", - "shell.execute_reply.started": "2023-04-04T02:14:48.143124Z" + "iopub.execute_input": "2023-04-12T02:45:18.545576Z", + "iopub.status.busy": "2023-04-12T02:45:18.544938Z", + "iopub.status.idle": "2023-04-12T02:45:22.676832Z", + "shell.execute_reply": "2023-04-12T02:45:22.674681Z", + "shell.execute_reply.started": "2023-04-12T02:45:18.545520Z" } }, "outputs": [ @@ -2074,11 +2074,11 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:52.250617Z", - "iopub.status.busy": "2023-04-04T02:14:52.249990Z", - "iopub.status.idle": "2023-04-04T02:14:54.323710Z", - "shell.execute_reply": "2023-04-04T02:14:54.321686Z", - "shell.execute_reply.started": "2023-04-04T02:14:52.250560Z" + "iopub.execute_input": "2023-04-12T02:45:22.684606Z", + "iopub.status.busy": "2023-04-12T02:45:22.683947Z", + "iopub.status.idle": "2023-04-12T02:45:24.711922Z", + "shell.execute_reply": "2023-04-12T02:45:24.709254Z", + "shell.execute_reply.started": "2023-04-12T02:45:22.684545Z" } }, "outputs": [ @@ -2115,11 +2115,11 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:14:54.327408Z", - "iopub.status.busy": "2023-04-04T02:14:54.326762Z", - "iopub.status.idle": "2023-04-04T02:14:54.368378Z", - "shell.execute_reply": "2023-04-04T02:14:54.365585Z", - "shell.execute_reply.started": "2023-04-04T02:14:54.327349Z" + "iopub.execute_input": "2023-04-12T02:45:24.716116Z", + "iopub.status.busy": "2023-04-12T02:45:24.715420Z", + "iopub.status.idle": "2023-04-12T02:45:24.757581Z", + "shell.execute_reply": "2023-04-12T02:45:24.753607Z", + "shell.execute_reply.started": "2023-04-12T02:45:24.716057Z" }, "tags": [] }, diff --git a/docs/Statistics.ipynb b/docs/Statistics.ipynb index 48d00ca6..ce526629 100644 --- a/docs/Statistics.ipynb +++ b/docs/Statistics.ipynb @@ -14,11 +14,11 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:03.862819Z", - "iopub.status.busy": "2023-04-04T02:17:03.862050Z", - "iopub.status.idle": "2023-04-04T02:17:22.171309Z", - "shell.execute_reply": "2023-04-04T02:17:22.168953Z", - "shell.execute_reply.started": "2023-04-04T02:17:03.862761Z" + "iopub.execute_input": "2023-04-12T03:28:34.656393Z", + "iopub.status.busy": "2023-04-12T03:28:34.655675Z", + "iopub.status.idle": "2023-04-12T03:28:53.748658Z", + "shell.execute_reply": "2023-04-12T03:28:53.745490Z", + "shell.execute_reply.started": "2023-04-12T03:28:34.656312Z" }, "tags": [] }, @@ -46,11 +46,11 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:22.177034Z", - "iopub.status.busy": "2023-04-04T02:17:22.175924Z", - "iopub.status.idle": "2023-04-04T02:17:26.150907Z", - "shell.execute_reply": "2023-04-04T02:17:26.147960Z", - "shell.execute_reply.started": "2023-04-04T02:17:22.176975Z" + "iopub.execute_input": "2023-04-12T03:28:53.754985Z", + "iopub.status.busy": "2023-04-12T03:28:53.753764Z", + "iopub.status.idle": "2023-04-12T03:28:58.752630Z", + "shell.execute_reply": "2023-04-12T03:28:58.748415Z", + "shell.execute_reply.started": "2023-04-12T03:28:53.754925Z" } }, "outputs": [ @@ -61,7 +61,7 @@ "
    \n", "
    \n", "

    Client

    \n", - "

    Client-d5630f9c-d28e-11ed-8cb3-0242ac110004

    \n", + "

    Client-26ae3825-d8e2-11ed-8cff-0242ac110006

    \n", "
    \n", - " Comm: tcp://127.0.0.1:43269\n", + " Comm: tcp://127.0.0.1:40242\n", " \n", " Total threads: 1\n", @@ -408,7 +408,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:38261/status\n", + " Dashboard: http://127.0.0.1:41705/status\n", " \n", " Memory: 25.00 GiB\n", @@ -416,13 +416,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:32774\n", + " Nanny: tcp://127.0.0.1:38136\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-nql0yhob\n", + " Local directory: /tmp/dask-worker-space/worker-8yonp5i0\n", "
    \n", "\n", " \n", @@ -92,7 +92,7 @@ " \n", "
    \n", "

    LocalCluster

    \n", - "

    a102e758

    \n", + "

    81cdac5e

    \n", "
    \n", " \n", "
    \n", @@ -129,11 +129,11 @@ "
    \n", "
    \n", "

    Scheduler

    \n", - "

    Scheduler-9e161f63-f1eb-4af6-a3b9-d250897338ba

    \n", + "

    Scheduler-4d7a9c82-5cdf-4ce7-9c42-615ef58e770e

    \n", " \n", " \n", " \n", "
    \n", - " Comm: tcp://127.0.0.1:41736\n", + " Comm: tcp://127.0.0.1:44090\n", " \n", " Workers: 4\n", @@ -175,7 +175,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -220,7 +220,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:34950\n", + " Comm: tcp://127.0.0.1:35621\n", " \n", " Total threads: 1\n", @@ -183,7 +183,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:38916/status\n", + " Dashboard: http://127.0.0.1:40576/status\n", " \n", " Memory: 25.00 GiB\n", @@ -191,13 +191,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:39103\n", + " Nanny: tcp://127.0.0.1:34369\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-ey9iznna\n", + " Local directory: /tmp/dask-worker-space/worker-8_d4bcgx\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -265,7 +265,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:35828\n", + " Comm: tcp://127.0.0.1:37592\n", " \n", " Total threads: 1\n", @@ -228,7 +228,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:39334/status\n", + " Dashboard: http://127.0.0.1:44162/status\n", " \n", " Memory: 25.00 GiB\n", @@ -236,13 +236,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:44181\n", + " Nanny: tcp://127.0.0.1:40318\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-4okhcz51\n", + " Local directory: /tmp/dask-worker-space/worker-2pud10zh\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -310,7 +310,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:42612\n", + " Comm: tcp://127.0.0.1:34588\n", " \n", " Total threads: 1\n", @@ -273,7 +273,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:36310/status\n", + " Dashboard: http://127.0.0.1:35118/status\n", " \n", " Memory: 25.00 GiB\n", @@ -281,13 +281,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:38074\n", + " Nanny: tcp://127.0.0.1:42551\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-7b0a_wqe\n", + " Local directory: /tmp/dask-worker-space/worker-ccmr530j\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -359,7 +359,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -391,11 +391,11 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:26.154655Z", - "iopub.status.busy": "2023-04-04T02:17:26.153990Z", - "iopub.status.idle": "2023-04-04T02:17:32.062128Z", - "shell.execute_reply": "2023-04-04T02:17:32.051655Z", - "shell.execute_reply.started": "2023-04-04T02:17:26.154569Z" + "iopub.execute_input": "2023-04-12T03:28:58.756656Z", + "iopub.status.busy": "2023-04-12T03:28:58.755968Z", + "iopub.status.idle": "2023-04-12T03:29:05.681158Z", + "shell.execute_reply": "2023-04-12T03:29:05.670160Z", + "shell.execute_reply.started": "2023-04-12T03:28:58.756570Z" } }, "outputs": [ @@ -454,11 +454,11 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:32.068634Z", - "iopub.status.busy": "2023-04-04T02:17:32.067967Z", - "iopub.status.idle": "2023-04-04T02:17:41.237661Z", - "shell.execute_reply": "2023-04-04T02:17:41.235131Z", - "shell.execute_reply.started": "2023-04-04T02:17:32.068564Z" + "iopub.execute_input": "2023-04-12T03:29:05.687396Z", + "iopub.status.busy": "2023-04-12T03:29:05.686689Z", + "iopub.status.idle": "2023-04-12T03:29:17.033139Z", + "shell.execute_reply": "2023-04-12T03:29:17.019414Z", + "shell.execute_reply.started": "2023-04-12T03:29:05.687262Z" } }, "outputs": [ @@ -513,11 +513,11 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:41.242719Z", - "iopub.status.busy": "2023-04-04T02:17:41.242020Z", - "iopub.status.idle": "2023-04-04T02:17:41.259645Z", - "shell.execute_reply": "2023-04-04T02:17:41.256620Z", - "shell.execute_reply.started": "2023-04-04T02:17:41.242658Z" + "iopub.execute_input": "2023-04-12T03:29:17.039660Z", + "iopub.status.busy": "2023-04-12T03:29:17.039007Z", + "iopub.status.idle": "2023-04-12T03:29:17.063816Z", + "shell.execute_reply": "2023-04-12T03:29:17.060053Z", + "shell.execute_reply.started": "2023-04-12T03:29:17.039598Z" } }, "outputs": [], @@ -527,6 +527,8 @@ "# weights = data array of the relative volumes of the cells in 3D space\n", "# bin_edges = array of the edges of the bins (e.g. temperature bins)\n", "# bin_mid = array of the mid-points of the bins\n", + "\n", + "\n", "def bin_snapshot(dat, weight, bin_edges, bin_mid):\n", " # Speed up by stacking over space\n", " dat = dat.stack(alldims=[\"X\", \"Y\", \"Z\"])\n", @@ -554,11 +556,11 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:41.263569Z", - "iopub.status.busy": "2023-04-04T02:17:41.262955Z", - "iopub.status.idle": "2023-04-04T02:17:41.274564Z", - "shell.execute_reply": "2023-04-04T02:17:41.272400Z", - "shell.execute_reply.started": "2023-04-04T02:17:41.263514Z" + "iopub.execute_input": "2023-04-12T03:29:17.072757Z", + "iopub.status.busy": "2023-04-12T03:29:17.072072Z", + "iopub.status.idle": "2023-04-12T03:29:17.082521Z", + "shell.execute_reply": "2023-04-12T03:29:17.079912Z", + "shell.execute_reply.started": "2023-04-12T03:29:17.072699Z" } }, "outputs": [], @@ -580,11 +582,11 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:17:41.283551Z", - "iopub.status.busy": "2023-04-04T02:17:41.282932Z", - "iopub.status.idle": "2023-04-04T02:18:52.707215Z", - "shell.execute_reply": "2023-04-04T02:18:52.704748Z", - "shell.execute_reply.started": "2023-04-04T02:17:41.283498Z" + "iopub.execute_input": "2023-04-12T03:29:17.094337Z", + "iopub.status.busy": "2023-04-12T03:29:17.093643Z", + "iopub.status.idle": "2023-04-12T03:30:31.548063Z", + "shell.execute_reply": "2023-04-12T03:30:31.545587Z", + "shell.execute_reply.started": "2023-04-12T03:29:17.094228Z" } }, "outputs": [ @@ -696,11 +698,11 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:18:52.710771Z", - "iopub.status.busy": "2023-04-04T02:18:52.710138Z", - "iopub.status.idle": "2023-04-04T02:18:53.132061Z", - "shell.execute_reply": "2023-04-04T02:18:53.129145Z", - "shell.execute_reply.started": "2023-04-04T02:18:52.710714Z" + "iopub.execute_input": "2023-04-12T03:30:31.551091Z", + "iopub.status.busy": "2023-04-12T03:30:31.550518Z", + "iopub.status.idle": "2023-04-12T03:30:31.944890Z", + "shell.execute_reply": "2023-04-12T03:30:31.941787Z", + "shell.execute_reply.started": "2023-04-12T03:30:31.551031Z" } }, "outputs": [ @@ -753,11 +755,11 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:18:53.136598Z", - "iopub.status.busy": "2023-04-04T02:18:53.135986Z", - "iopub.status.idle": "2023-04-04T02:19:02.884848Z", - "shell.execute_reply": "2023-04-04T02:19:02.882373Z", - "shell.execute_reply.started": "2023-04-04T02:18:53.136542Z" + "iopub.execute_input": "2023-04-12T03:30:31.948884Z", + "iopub.status.busy": "2023-04-12T03:30:31.948209Z", + "iopub.status.idle": "2023-04-12T03:30:41.677139Z", + "shell.execute_reply": "2023-04-12T03:30:41.674628Z", + "shell.execute_reply.started": "2023-04-12T03:30:31.948825Z" } }, "outputs": [ @@ -804,11 +806,11 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:19:02.888570Z", - "iopub.status.busy": "2023-04-04T02:19:02.887882Z", - "iopub.status.idle": "2023-04-04T02:19:18.652068Z", - "shell.execute_reply": "2023-04-04T02:19:18.637760Z", - "shell.execute_reply.started": "2023-04-04T02:19:02.888512Z" + "iopub.execute_input": "2023-04-12T03:30:41.679669Z", + "iopub.status.busy": "2023-04-12T03:30:41.679047Z", + "iopub.status.idle": "2023-04-12T03:30:57.214170Z", + "shell.execute_reply": "2023-04-12T03:30:57.210705Z", + "shell.execute_reply.started": "2023-04-12T03:30:41.679609Z" } }, "outputs": [ @@ -862,11 +864,11 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:19:18.655981Z", - "iopub.status.busy": "2023-04-04T02:19:18.655397Z", - "iopub.status.idle": "2023-04-04T02:28:58.849918Z", - "shell.execute_reply": "2023-04-04T02:28:58.834236Z", - "shell.execute_reply.started": "2023-04-04T02:19:18.655924Z" + "iopub.execute_input": "2023-04-12T03:30:57.218489Z", + "iopub.status.busy": "2023-04-12T03:30:57.217824Z", + "iopub.status.idle": "2023-04-12T03:40:36.735068Z", + "shell.execute_reply": "2023-04-12T03:40:36.730390Z", + "shell.execute_reply.started": "2023-04-12T03:30:57.218428Z" }, "tags": [] }, @@ -1042,11 +1044,11 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:28:58.854790Z", - "iopub.status.busy": "2023-04-04T02:28:58.854066Z", - "iopub.status.idle": "2023-04-04T02:28:58.879524Z", - "shell.execute_reply": "2023-04-04T02:28:58.877071Z", - "shell.execute_reply.started": "2023-04-04T02:28:58.854721Z" + "iopub.execute_input": "2023-04-12T03:40:36.752158Z", + "iopub.status.busy": "2023-04-12T03:40:36.751505Z", + "iopub.status.idle": "2023-04-12T03:40:36.775111Z", + "shell.execute_reply": "2023-04-12T03:40:36.772503Z", + "shell.execute_reply.started": "2023-04-12T03:40:36.752081Z" } }, "outputs": [], @@ -1066,11 +1068,11 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:28:58.883731Z", - "iopub.status.busy": "2023-04-04T02:28:58.883000Z", - "iopub.status.idle": "2023-04-04T02:29:01.706661Z", - "shell.execute_reply": "2023-04-04T02:29:01.700908Z", - "shell.execute_reply.started": "2023-04-04T02:28:58.883676Z" + "iopub.execute_input": "2023-04-12T03:40:36.778927Z", + "iopub.status.busy": "2023-04-12T03:40:36.778320Z", + "iopub.status.idle": "2023-04-12T03:40:39.528631Z", + "shell.execute_reply": "2023-04-12T03:40:39.525860Z", + "shell.execute_reply.started": "2023-04-12T03:40:36.778869Z" } }, "outputs": [ @@ -1085,7 +1087,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -1128,11 +1130,11 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:29:01.709538Z", - "iopub.status.busy": "2023-04-04T02:29:01.708897Z", - "iopub.status.idle": "2023-04-04T02:29:05.896634Z", - "shell.execute_reply": "2023-04-04T02:29:05.894054Z", - "shell.execute_reply.started": "2023-04-04T02:29:01.709481Z" + "iopub.execute_input": "2023-04-12T03:40:39.532853Z", + "iopub.status.busy": "2023-04-12T03:40:39.532176Z", + "iopub.status.idle": "2023-04-12T03:40:43.820610Z", + "shell.execute_reply": "2023-04-12T03:40:43.815224Z", + "shell.execute_reply.started": "2023-04-12T03:40:39.532792Z" } }, "outputs": [ @@ -1154,7 +1156,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 14, diff --git a/docs/Tutorial.ipynb b/docs/Tutorial.ipynb index b439b8c2..b4631921 100644 --- a/docs/Tutorial.ipynb +++ b/docs/Tutorial.ipynb @@ -19,11 +19,11 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:02.057492Z", - "iopub.status.busy": "2023-04-04T02:10:02.056674Z", - "iopub.status.idle": "2023-04-04T02:10:20.494420Z", - "shell.execute_reply": "2023-04-04T02:10:20.492457Z", - "shell.execute_reply.started": "2023-04-04T02:10:02.057383Z" + "iopub.execute_input": "2023-04-12T02:58:25.598777Z", + "iopub.status.busy": "2023-04-12T02:58:25.598181Z", + "iopub.status.idle": "2023-04-12T02:58:44.114825Z", + "shell.execute_reply": "2023-04-12T02:58:44.112775Z", + "shell.execute_reply.started": "2023-04-12T02:58:25.598718Z" }, "tags": [] }, @@ -75,11 +75,11 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:20.501091Z", - "iopub.status.busy": "2023-04-04T02:10:20.499993Z", - "iopub.status.idle": "2023-04-04T02:10:24.364911Z", - "shell.execute_reply": "2023-04-04T02:10:24.362705Z", - "shell.execute_reply.started": "2023-04-04T02:10:20.501034Z" + "iopub.execute_input": "2023-04-12T02:58:44.122155Z", + "iopub.status.busy": "2023-04-12T02:58:44.121049Z", + "iopub.status.idle": "2023-04-12T02:58:48.246392Z", + "shell.execute_reply": "2023-04-12T02:58:48.242736Z", + "shell.execute_reply.started": "2023-04-12T02:58:44.122096Z" } }, "outputs": [ @@ -90,7 +90,7 @@ "
    \n", "
    \n", "

    Client

    \n", - "

    Client-da37daa3-d28d-11ed-8b2c-0242ac110004

    \n", + "

    Client-f03afce8-d8dd-11ed-8bf7-0242ac110006

    \n", "
    \n", - " Comm: tcp://127.0.0.1:36670\n", + " Comm: tcp://127.0.0.1:40062\n", " \n", " Total threads: 1\n", @@ -318,7 +318,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:46541/status\n", + " Dashboard: http://127.0.0.1:36471/status\n", " \n", " Memory: 25.00 GiB\n", @@ -326,13 +326,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:46093\n", + " Nanny: tcp://127.0.0.1:34549\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-neq_7v61\n", + " Local directory: /tmp/dask-worker-space/worker-emp51ee1\n", "
    \n", "\n", " \n", @@ -121,7 +121,7 @@ " \n", "
    \n", "

    LocalCluster

    \n", - "

    25eae8e0

    \n", + "

    a4538961

    \n", "
    \n", " \n", "
    \n", @@ -158,11 +158,11 @@ "
    \n", "
    \n", "

    Scheduler

    \n", - "

    Scheduler-eaff75c4-c759-4f95-b67a-a299c6da3889

    \n", + "

    Scheduler-1a5a0e83-2549-4e24-b677-a098e4111a05

    \n", " \n", " \n", " \n", "
    \n", - " Comm: tcp://127.0.0.1:43991\n", + " Comm: tcp://127.0.0.1:43873\n", " \n", " Workers: 4\n", @@ -204,7 +204,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -249,7 +249,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:45037\n", + " Comm: tcp://127.0.0.1:36206\n", " \n", " Total threads: 1\n", @@ -212,7 +212,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:38108/status\n", + " Dashboard: http://127.0.0.1:38523/status\n", " \n", " Memory: 25.00 GiB\n", @@ -220,13 +220,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:32856\n", + " Nanny: tcp://127.0.0.1:44743\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-xaah9dso\n", + " Local directory: /tmp/dask-worker-space/worker-zay_qwtp\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -294,7 +294,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:41822\n", + " Comm: tcp://127.0.0.1:32882\n", " \n", " Total threads: 1\n", @@ -257,7 +257,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:40306/status\n", + " Dashboard: http://127.0.0.1:35209/status\n", " \n", " Memory: 25.00 GiB\n", @@ -265,13 +265,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:35683\n", + " Nanny: tcp://127.0.0.1:40943\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-n__98hng\n", + " Local directory: /tmp/dask-worker-space/worker-rsqvgpa3\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -339,7 +339,7 @@ "
    \n", - " Comm: tcp://127.0.0.1:41552\n", + " Comm: tcp://127.0.0.1:37530\n", " \n", " Total threads: 1\n", @@ -302,7 +302,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:40412/status\n", + " Dashboard: http://127.0.0.1:35630/status\n", " \n", " Memory: 25.00 GiB\n", @@ -310,13 +310,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:44113\n", + " Nanny: tcp://127.0.0.1:35736\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-8ca39zbz\n", + " Local directory: /tmp/dask-worker-space/worker-dnmo4pam\n", "
    \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -388,7 +388,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -440,12 +440,13 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:24.370194Z", - "iopub.status.busy": "2023-04-04T02:10:24.369581Z", - "iopub.status.idle": "2023-04-04T02:10:30.699764Z", - "shell.execute_reply": "2023-04-04T02:10:30.696772Z", - "shell.execute_reply.started": "2023-04-04T02:10:24.370113Z" - } + "iopub.execute_input": "2023-04-12T02:58:48.250144Z", + "iopub.status.busy": "2023-04-12T02:58:48.249534Z", + "iopub.status.idle": "2023-04-12T02:58:59.453881Z", + "shell.execute_reply": "2023-04-12T02:58:59.450883Z", + "shell.execute_reply.started": "2023-04-12T02:58:48.250064Z" + }, + "tags": [] }, "outputs": [ { @@ -519,11 +520,11 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:30.704198Z", - "iopub.status.busy": "2023-04-04T02:10:30.703546Z", - "iopub.status.idle": "2023-04-04T02:10:31.115190Z", - "shell.execute_reply": "2023-04-04T02:10:31.112573Z", - "shell.execute_reply.started": "2023-04-04T02:10:30.704141Z" + "iopub.execute_input": "2023-04-12T02:58:59.458010Z", + "iopub.status.busy": "2023-04-12T02:58:59.457428Z", + "iopub.status.idle": "2023-04-12T02:58:59.837736Z", + "shell.execute_reply": "2023-04-12T02:58:59.834798Z", + "shell.execute_reply.started": "2023-04-12T02:58:59.457957Z" } }, "outputs": [ @@ -577,11 +578,11 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:31.126161Z", - "iopub.status.busy": "2023-04-04T02:10:31.125566Z", - "iopub.status.idle": "2023-04-04T02:10:31.533581Z", - "shell.execute_reply": "2023-04-04T02:10:31.530748Z", - "shell.execute_reply.started": "2023-04-04T02:10:31.126104Z" + "iopub.execute_input": "2023-04-12T02:58:59.841391Z", + "iopub.status.busy": "2023-04-12T02:58:59.840730Z", + "iopub.status.idle": "2023-04-12T02:59:00.230475Z", + "shell.execute_reply": "2023-04-12T02:59:00.227005Z", + "shell.execute_reply.started": "2023-04-12T02:58:59.841327Z" } }, "outputs": [ @@ -639,11 +640,11 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:31.539252Z", - "iopub.status.busy": "2023-04-04T02:10:31.536922Z", - "iopub.status.idle": "2023-04-04T02:10:31.954942Z", - "shell.execute_reply": "2023-04-04T02:10:31.951333Z", - "shell.execute_reply.started": "2023-04-04T02:10:31.539191Z" + "iopub.execute_input": "2023-04-12T02:59:00.234766Z", + "iopub.status.busy": "2023-04-12T02:59:00.234039Z", + "iopub.status.idle": "2023-04-12T02:59:00.681143Z", + "shell.execute_reply": "2023-04-12T02:59:00.677592Z", + "shell.execute_reply.started": "2023-04-12T02:59:00.234707Z" } }, "outputs": [ @@ -714,11 +715,11 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:31.966444Z", - "iopub.status.busy": "2023-04-04T02:10:31.965821Z", - "iopub.status.idle": "2023-04-04T02:10:33.538592Z", - "shell.execute_reply": "2023-04-04T02:10:33.536087Z", - "shell.execute_reply.started": "2023-04-04T02:10:31.966372Z" + "iopub.execute_input": "2023-04-12T02:59:00.692883Z", + "iopub.status.busy": "2023-04-12T02:59:00.692248Z", + "iopub.status.idle": "2023-04-12T02:59:02.302058Z", + "shell.execute_reply": "2023-04-12T02:59:02.299899Z", + "shell.execute_reply.started": "2023-04-12T02:59:00.692824Z" } }, "outputs": [ @@ -752,11 +753,11 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:33.541570Z", - "iopub.status.busy": "2023-04-04T02:10:33.540947Z", - "iopub.status.idle": "2023-04-04T02:10:35.867232Z", - "shell.execute_reply": "2023-04-04T02:10:35.865351Z", - "shell.execute_reply.started": "2023-04-04T02:10:33.541513Z" + "iopub.execute_input": "2023-04-12T02:59:02.305182Z", + "iopub.status.busy": "2023-04-12T02:59:02.304590Z", + "iopub.status.idle": "2023-04-12T02:59:04.635309Z", + "shell.execute_reply": "2023-04-12T02:59:04.632639Z", + "shell.execute_reply.started": "2023-04-12T02:59:02.305123Z" } }, "outputs": [ @@ -803,11 +804,11 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:35.869605Z", - "iopub.status.busy": "2023-04-04T02:10:35.868982Z", - "iopub.status.idle": "2023-04-04T02:10:35.897843Z", - "shell.execute_reply": "2023-04-04T02:10:35.895543Z", - "shell.execute_reply.started": "2023-04-04T02:10:35.869547Z" + "iopub.execute_input": "2023-04-12T02:59:04.638098Z", + "iopub.status.busy": "2023-04-12T02:59:04.637520Z", + "iopub.status.idle": "2023-04-12T02:59:04.666820Z", + "shell.execute_reply": "2023-04-12T02:59:04.662828Z", + "shell.execute_reply.started": "2023-04-12T02:59:04.638040Z" } }, "outputs": [ @@ -843,11 +844,11 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:35.901070Z", - "iopub.status.busy": "2023-04-04T02:10:35.900508Z", - "iopub.status.idle": "2023-04-04T02:10:36.059151Z", - "shell.execute_reply": "2023-04-04T02:10:36.055762Z", - "shell.execute_reply.started": "2023-04-04T02:10:35.901016Z" + "iopub.execute_input": "2023-04-12T02:59:04.671673Z", + "iopub.status.busy": "2023-04-12T02:59:04.671060Z", + "iopub.status.idle": "2023-04-12T02:59:04.816943Z", + "shell.execute_reply": "2023-04-12T02:59:04.814360Z", + "shell.execute_reply.started": "2023-04-12T02:59:04.671618Z" } }, "outputs": [ @@ -866,27 +867,27 @@ "X Axis (not periodic, boundary=None):\n", " * center X --> outer\n", " * outer Xp1 --> center\n", - "Y Axis (not periodic, boundary=None):\n", - " * center Y --> outer\n", - " * outer Yp1 --> center\n", "Z Axis (not periodic, boundary=None):\n", " * center Z --> left\n", " * outer Zp1 --> center\n", " * right Zu --> center\n", " * left Zl --> center\n", + "Y Axis (not periodic, boundary=None):\n", + " * center Y --> outer\n", + " * outer Yp1 --> center\n", "\n", "New oceandataset:\n", "{'Z': 1, 'Zp1': 1, 'Zu': 1, 'Zl': 1, 'X': 207, 'Y': 154, 'Xp1': 208, 'Yp1': 155, 'time': 4, 'time_midp': 3}\n", "\n", + "time Axis (not periodic, boundary=None):\n", + " * center time_midp --> outer\n", + " * outer time --> center\n", "X Axis (not periodic, boundary=None):\n", " * center X --> outer\n", " * outer Xp1 --> center\n", "Y Axis (not periodic, boundary=None):\n", " * center Y --> outer\n", - " * outer Yp1 --> center\n", - "time Axis (not periodic, boundary=None):\n", - " * center time_midp --> outer\n", - " * outer time --> center\n" + " * outer Yp1 --> center\n" ] } ], @@ -935,11 +936,11 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:36.063452Z", - "iopub.status.busy": "2023-04-04T02:10:36.062682Z", - "iopub.status.idle": "2023-04-04T02:10:36.164611Z", - "shell.execute_reply": "2023-04-04T02:10:36.160865Z", - "shell.execute_reply.started": "2023-04-04T02:10:36.063359Z" + "iopub.execute_input": "2023-04-12T02:59:04.820099Z", + "iopub.status.busy": "2023-04-12T02:59:04.819531Z", + "iopub.status.idle": "2023-04-12T02:59:04.906937Z", + "shell.execute_reply": "2023-04-12T02:59:04.904636Z", + "shell.execute_reply.started": "2023-04-12T02:59:04.820043Z" } }, "outputs": [ @@ -991,11 +992,11 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:36.167232Z", - "iopub.status.busy": "2023-04-04T02:10:36.166678Z", - 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"iopub.execute_input": "2023-04-04T02:10:52.000671Z", - "iopub.status.busy": "2023-04-04T02:10:52.000061Z", - "iopub.status.idle": "2023-04-04T02:10:52.281555Z", - "shell.execute_reply": "2023-04-04T02:10:52.278815Z", - "shell.execute_reply.started": "2023-04-04T02:10:52.000613Z" + "iopub.execute_input": "2023-04-12T02:59:20.691309Z", + "iopub.status.busy": "2023-04-12T02:59:20.690544Z", + "iopub.status.idle": "2023-04-12T02:59:20.959681Z", + "shell.execute_reply": "2023-04-12T02:59:20.957218Z", + "shell.execute_reply.started": "2023-04-12T02:59:20.691201Z" }, "scrolled": true }, @@ -1180,11 +1181,11 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:52.284034Z", - "iopub.status.busy": "2023-04-04T02:10:52.283464Z", - "iopub.status.idle": "2023-04-04T02:10:52.941886Z", - "shell.execute_reply": "2023-04-04T02:10:52.938714Z", - "shell.execute_reply.started": "2023-04-04T02:10:52.283975Z" + "iopub.execute_input": "2023-04-12T02:59:20.965109Z", + "iopub.status.busy": "2023-04-12T02:59:20.964522Z", + "iopub.status.idle": "2023-04-12T02:59:21.598706Z", + "shell.execute_reply": "2023-04-12T02:59:21.595409Z", + "shell.execute_reply.started": "2023-04-12T02:59:20.965054Z" } }, "outputs": [ @@ -1218,11 +1219,11 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:52.949766Z", - "iopub.status.busy": "2023-04-04T02:10:52.948606Z", - "iopub.status.idle": "2023-04-04T02:10:54.404864Z", - "shell.execute_reply": "2023-04-04T02:10:54.399507Z", - "shell.execute_reply.started": "2023-04-04T02:10:52.949707Z" + "iopub.execute_input": "2023-04-12T02:59:21.603007Z", + "iopub.status.busy": "2023-04-12T02:59:21.602406Z", + "iopub.status.idle": "2023-04-12T02:59:23.013310Z", + "shell.execute_reply": "2023-04-12T02:59:23.009077Z", + "shell.execute_reply.started": "2023-04-12T02:59:21.602949Z" } }, "outputs": [ @@ -1313,11 +1314,11 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:10:54.408769Z", - "iopub.status.busy": "2023-04-04T02:10:54.408114Z", - "iopub.status.idle": "2023-04-04T02:11:00.276116Z", - "shell.execute_reply": "2023-04-04T02:11:00.271834Z", - "shell.execute_reply.started": "2023-04-04T02:10:54.408710Z" + "iopub.execute_input": "2023-04-12T02:59:23.017900Z", + "iopub.status.busy": "2023-04-12T02:59:23.017038Z", + "iopub.status.idle": "2023-04-12T02:59:28.599312Z", + "shell.execute_reply": "2023-04-12T02:59:28.596700Z", + "shell.execute_reply.started": "2023-04-12T02:59:23.017842Z" } }, "outputs": [ @@ -1352,11 +1353,11 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:11:00.279892Z", - "iopub.status.busy": "2023-04-04T02:11:00.279244Z", - "iopub.status.idle": "2023-04-04T02:11:02.745800Z", - "shell.execute_reply": "2023-04-04T02:11:02.743230Z", - "shell.execute_reply.started": "2023-04-04T02:11:00.279835Z" + "iopub.execute_input": "2023-04-12T02:59:28.602876Z", + "iopub.status.busy": "2023-04-12T02:59:28.602187Z", + "iopub.status.idle": "2023-04-12T02:59:31.170491Z", + "shell.execute_reply": "2023-04-12T02:59:31.167508Z", + "shell.execute_reply.started": "2023-04-12T02:59:28.602815Z" } }, "outputs": [ @@ -1412,11 +1413,11 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:11:02.749191Z", - "iopub.status.busy": "2023-04-04T02:11:02.748604Z", - "iopub.status.idle": "2023-04-04T02:11:05.100788Z", - "shell.execute_reply": "2023-04-04T02:11:05.098527Z", - "shell.execute_reply.started": "2023-04-04T02:11:02.749134Z" + "iopub.execute_input": "2023-04-12T02:59:31.173739Z", + "iopub.status.busy": "2023-04-12T02:59:31.173084Z", + "iopub.status.idle": "2023-04-12T02:59:33.612913Z", + "shell.execute_reply": "2023-04-12T02:59:33.609266Z", + "shell.execute_reply.started": "2023-04-12T02:59:31.173679Z" } }, "outputs": [ @@ -1467,11 +1468,11 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:11:05.104074Z", - "iopub.status.busy": "2023-04-04T02:11:05.103491Z", - "iopub.status.idle": "2023-04-04T02:11:17.754864Z", - "shell.execute_reply": "2023-04-04T02:11:17.748872Z", - "shell.execute_reply.started": "2023-04-04T02:11:05.104017Z" + "iopub.execute_input": "2023-04-12T02:59:33.617436Z", + "iopub.status.busy": "2023-04-12T02:59:33.616768Z", + "iopub.status.idle": "2023-04-12T02:59:46.932122Z", + "shell.execute_reply": "2023-04-12T02:59:46.927323Z", + "shell.execute_reply.started": "2023-04-12T02:59:33.617375Z" } }, "outputs": [ @@ -1572,11 +1573,11 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:11:17.762062Z", - "iopub.status.busy": "2023-04-04T02:11:17.761413Z", - "iopub.status.idle": "2023-04-04T02:11:17.783055Z", - "shell.execute_reply": "2023-04-04T02:11:17.779737Z", - "shell.execute_reply.started": "2023-04-04T02:11:17.761979Z" + "iopub.execute_input": "2023-04-12T02:59:46.938488Z", + "iopub.status.busy": "2023-04-12T02:59:46.937768Z", + "iopub.status.idle": "2023-04-12T02:59:46.957535Z", + "shell.execute_reply": "2023-04-12T02:59:46.955056Z", + "shell.execute_reply.started": "2023-04-12T02:59:46.938398Z" } }, "outputs": [ @@ -1618,11 +1619,11 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2023-04-04T02:11:17.798048Z", - "iopub.status.busy": "2023-04-04T02:11:17.797473Z", - "iopub.status.idle": "2023-04-04T02:11:20.341580Z", - "shell.execute_reply": "2023-04-04T02:11:20.337939Z", - "shell.execute_reply.started": "2023-04-04T02:11:17.797994Z" + "iopub.execute_input": "2023-04-12T02:59:46.975485Z", + "iopub.status.busy": "2023-04-12T02:59:46.974756Z", + "iopub.status.idle": "2023-04-12T02:59:51.804162Z", + "shell.execute_reply": "2023-04-12T02:59:51.800751Z", + "shell.execute_reply.started": "2023-04-12T02:59:46.975430Z" }, "tags": [] }, From fcf0d0d3d1647b515bc5608eff1a80523a498eb3 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Apr 2023 10:23:45 -0400 Subject: [PATCH 05/32] Bump codecov/codecov-action from 3.1.1 to 3.1.2 (#345) Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 3.1.1 to 3.1.2. - [Release notes](https://github.com/codecov/codecov-action/releases) - [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md) - [Commits](https://github.com/codecov/codecov-action/compare/v3.1.1...v3.1.2) --- updated-dependencies: - dependency-name: codecov/codecov-action dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/ci.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index dcd53520..31901112 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -49,7 +49,7 @@ jobs: run: pytest --cov=./ --cov-report=xml - name: Upload code coverage to Codecov - uses: codecov/codecov-action@v3.1.1 + uses: codecov/codecov-action@v3.1.2 with: token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml From 3858c3376e88fc599b9cea9471ffbd983ed077ed Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 25 Apr 2023 16:36:35 -0400 Subject: [PATCH 06/32] Bump codecov/codecov-action from 3.1.2 to 3.1.3 (#347) Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 3.1.2 to 3.1.3. - [Release notes](https://github.com/codecov/codecov-action/releases) - [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md) - [Commits](https://github.com/codecov/codecov-action/compare/v3.1.2...v3.1.3) --- updated-dependencies: - dependency-name: codecov/codecov-action dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/ci.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 31901112..79a87322 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -49,7 +49,7 @@ jobs: run: pytest --cov=./ --cov-report=xml - name: Upload code coverage to Codecov - uses: codecov/codecov-action@v3.1.2 + uses: codecov/codecov-action@v3.1.3 with: token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml From 27fb611dd4642031a668ad66175d27c4d244d24f Mon Sep 17 00:00:00 2001 From: MaceKuailv <52629492+MaceKuailv@users.noreply.github.com> Date: Fri, 5 May 2023 11:41:46 -0400 Subject: [PATCH 07/32] For issue 321 and 269 (#348) * unpin matplotlib * take care of the integration/cutout/freq issue, and document * I don't understand why there is an error in animate. There is also no error message. I cannot recreate the error as well. So I redo the sampling part * repin matplotlib * pin matplotlib some more --- binder/environment.yml | 2 +- ci/environment.yml | 2 +- oceanspy/subsample.py | 39 +++++++++++++++++++++++++++++---------- 3 files changed, 31 insertions(+), 12 deletions(-) diff --git a/binder/environment.yml b/binder/environment.yml index f76ee61c..ef36d44e 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -4,7 +4,7 @@ channels: dependencies: - python - numpy -- matplotlib < 3.5.3 +- matplotlib<3.5.3 - pandas - bokeh - rise diff --git a/ci/environment.yml b/ci/environment.yml index e3895618..3ab1caf1 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -22,7 +22,7 @@ dependencies: - ffmpeg - aiohttp - pandas -- matplotlib < 3.5.3 +- matplotlib<3.5.3 - fsspec!=0.9.0 - pooch - pip diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index 7bd48003..e1adf23f 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -105,6 +105,8 @@ def cutout( http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases sampMethod: {'snapshot', 'mean'} Downsampling method (only if timeFreq is not None). + "snapshot" means just throw away everything in between. + "mean" means take a running average with the time freq. dropAxes: 1D array_like, str, or bool List of axes to remove from Grid object. if one point only is in the range. @@ -580,16 +582,33 @@ def cutout( inds = [ i for i, t in enumerate(ds["time"].values) if t in newtime.values ] - inds_diff = _np.diff(inds) - if all(inds_diff == inds_diff[0]): - ds = ds.isel(time=slice(inds[0], inds[-1] + 1, inds_diff[0])) - else: - attrs = ds.attrs - ds = _xr.concat( - [ds.sel(time=time) for i, time in enumerate(newtime)], - dim="time", - ) - ds.attrs = attrs + inds = _xr.DataArray(inds, dims="time") + ds = ds.isel(time=inds) + # inds_diff = _np.diff(inds) + # if all(inds_diff == inds_diff[0]): + # ds = ds.isel(time=slice(inds[0], inds[-1] + 1, inds_diff[0])) + # else: + # attrs = ds.attrs + # ds_dims = ds.drop_vars( + # [var for var in ds.variables if var not in ds.dims] + # ) + # ds_time = ds.drop_vars( + # [var for var in ds.variables if "time" not in ds[var].dims] + # ) + # ds_timeless = ds.drop_vars( + # [var for var in ds.variables if "time" in ds[var].dims] + # ) + # ds_time = _xr.concat( + # [ds_time.sel(time=time) for i, time in enumerate(newtime)], + # dim="time", + # ) + # for dim in ds_time.dims: + # if dim == "time": + # ds_time[dim].attrs = ds_dims[dim].attrs + # else: + # ds_time[dim] = ds_dims[dim] + # ds = _xr.merge([ds_time, ds_timeless]) + # ds.attrs = attrs else: # Mean From 20c1a5d6d7be0a1c2b7355a62a6d24c414b2aa5f Mon Sep 17 00:00:00 2001 From: Mattia Almansi Date: Tue, 9 May 2023 11:25:46 +0200 Subject: [PATCH 08/32] implement trusted publishing (#350) --- .github/workflows/pypi.yml | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/.github/workflows/pypi.yml b/.github/workflows/pypi.yml index f6ff74da..901108cf 100644 --- a/.github/workflows/pypi.yml +++ b/.github/workflows/pypi.yml @@ -12,6 +12,13 @@ on: jobs: packages: runs-on: ubuntu-latest + + environment: + name: pypi + url: https://pypi.org/p/oceanspy + permissions: + id-token: write + steps: - uses: actions/checkout@v3 @@ -47,6 +54,3 @@ jobs: - name: Publish a Python distribution to PyPI if: success() && github.event_name == 'release' uses: pypa/gh-action-pypi-publish@release/v1 - with: - user: __token__ - password: ${{ secrets.PYPI_API_TOKEN }} From 2c6afd44bb0f9261721b390aba01de46c49c72f6 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Wed, 17 May 2023 17:17:13 -0400 Subject: [PATCH 09/32] update mooring array (#354) * update env add xoak * unpin netcdf * format * rename to Xind - continuity * format * update python 3.10 env * include ECCO test into mooring * formatting * include correct dtype of array elements * formatting * format * include xoak in docs/env * format * set xoak as private dependency * upgrade pin on matplotlib to 3.6.0 * updage envs binder and sciserver * more format * remove old commented code from previous PR --------- Co-authored-by: Miguel Jimenez --- binder/environment.yml | 3 +- ci/environment.yml | 3 +- docs/environment.yml | 1 + oceanspy/subsample.py | 325 ++++++++--------------- oceanspy/tests/test_compute_functions.py | 93 +++++-- oceanspy/tests/test_subsample.py | 8 +- oceanspy/tests/test_utils.py | 28 ++ oceanspy/utils.py | 71 +++++ sciserver_catalogs/environment.yml | 7 +- 9 files changed, 292 insertions(+), 247 deletions(-) diff --git a/binder/environment.yml b/binder/environment.yml index ef36d44e..260d1daf 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -4,7 +4,7 @@ channels: dependencies: - python - numpy -- matplotlib<3.5.3 +- matplotlib<=3.6.0 - pandas - bokeh - rise @@ -13,6 +13,7 @@ dependencies: - bottleneck - netCDF4 - xarray +- xoak - cartopy - esmpy - intake-xarray diff --git a/ci/environment.yml b/ci/environment.yml index 3ab1caf1..33cbdf45 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -7,6 +7,7 @@ dependencies: - bottleneck - netCDF4 - xarray +- xoak - cartopy - intake-xarray - geopy @@ -22,7 +23,7 @@ dependencies: - ffmpeg - aiohttp - pandas -- matplotlib<3.5.3 +- matplotlib<=3.6 - fsspec!=0.9.0 - pooch - pip diff --git a/docs/environment.yml b/docs/environment.yml index 0f850ddb..8e34a93d 100644 --- a/docs/environment.yml +++ b/docs/environment.yml @@ -13,6 +13,7 @@ dependencies: - xarray - intake - intake-xarray + - xoak - ipython - xgcm - aiohttp diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index e1adf23f..b33c7cb2 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -21,6 +21,7 @@ # Required dependencies (private) import xarray as _xr from packaging.version import parse as _parse_version +from xarray import DataArray # From OceanSpy (private) from . import compute as _compute @@ -34,7 +35,7 @@ _rename_aliased, ) from .llc_rearrange import LLCtransformation as _llc_trans -from .utils import _rel_lon, _reset_range, get_maskH +from .utils import _rel_lon, _reset_range, circle_path_array, get_maskH # Recommended dependencies (private) try: @@ -45,6 +46,10 @@ import xesmf as _xe except ImportError: # pragma: no cover pass +try: + import xoak as _xoak +except ImportError: # pragma: no cover + pass def cutout( @@ -584,31 +589,6 @@ def cutout( ] inds = _xr.DataArray(inds, dims="time") ds = ds.isel(time=inds) - # inds_diff = _np.diff(inds) - # if all(inds_diff == inds_diff[0]): - # ds = ds.isel(time=slice(inds[0], inds[-1] + 1, inds_diff[0])) - # else: - # attrs = ds.attrs - # ds_dims = ds.drop_vars( - # [var for var in ds.variables if var not in ds.dims] - # ) - # ds_time = ds.drop_vars( - # [var for var in ds.variables if "time" not in ds[var].dims] - # ) - # ds_timeless = ds.drop_vars( - # [var for var in ds.variables if "time" in ds[var].dims] - # ) - # ds_time = _xr.concat( - # [ds_time.sel(time=time) for i, time in enumerate(newtime)], - # dim="time", - # ) - # for dim in ds_time.dims: - # if dim == "time": - # ds_time[dim].attrs = ds_dims[dim].attrs - # else: - # ds_time[dim] = ds_dims[dim] - # ds = _xr.merge([ds_time, ds_timeless]) - # ds.attrs = attrs else: # Mean @@ -660,7 +640,7 @@ def cutout( return od -def mooring_array(od, Ymoor, Xmoor, **kwargs): +def mooring_array(od, Ymoor, Xmoor, xoak_index="scipy_kdtree", **kwargs): """ Extract a mooring array section following the grid. Trajectories are great circle paths if coordinates are spherical. @@ -682,15 +662,16 @@ def mooring_array(od, Ymoor, Xmoor, **kwargs): Subsampled oceandataset. """ - # Add indexes needed for transports - Yind, Xind = _xr.broadcast(od._ds["Y"], od._ds["X"]) - od._ds["Xind"] = Xind.transpose(*od._ds["XC"].dims) - od._ds["Yind"] = Yind.transpose(*od._ds["YC"].dims) - od._ds = od._ds.set_coords(["Xind", "Yind"]) - # Check _check_native_grid(od, "mooring_array") + # Useful variable + R = od.parameters["rSphere"] + + if R is not None: + # array defines a great circle path. + Ymoor, Xmoor = circle_path_array(Ymoor, Xmoor, R) + # Convert variables to numpy arrays and make some check Ymoor = _check_range(od, Ymoor, "Ymoor") Xmoor = _check_range(od, Xmoor, "Xmoor") @@ -704,248 +685,158 @@ def mooring_array(od, Ymoor, Xmoor, **kwargs): kwargs["add_Hbdr"] = True od = od.subsample.cutout(**kwargs) + # Add indexes needed for transports + Yind, Xind = _xr.broadcast(od._ds["Y"], od._ds["X"]) + od._ds["Xind"] = Xind.transpose(*od._ds["XC"].dims) + od._ds["Yind"] = Yind.transpose(*od._ds["YC"].dims) + od._ds = od._ds.set_coords(["Xind", "Yind"]) + # Message print("Extracting mooring array.") # Unpack ds ds = od._ds - # Useful variables - YC = od._ds["YC"] - XC = od._ds["XC"] - R = od.parameters["rSphere"] - shape = XC.shape - Yindex = XC.dims.index("Y") - Xindex = XC.dims.index("X") + ds_grid = ds[["XC", "YC"]] # by convention center point - # Convert to cartesian if spherical - if R is not None: - x, y, z = _utils.spherical2cartesian(Y=Ymoor, X=Xmoor, R=R) - else: - x = Xmoor - y = Ymoor - z = _np.zeros(Ymoor.shape) + for key, value in ds_grid.sizes.items(): + ds_grid["i" + f"{key}"] = DataArray(range(value), dims=key) - # Create tree - tree = od.create_tree(grid_pos="C") + if R is not None: # spherical coordinates + # make sure that the array defines a great circle path of resolution 100km + Ymoor, Xmoor = circle_path_array( + Ymoor, Xmoor, R + ) # make sure Xmoor and Ymoor define a c - # Indexes of nearest grid points - _, indexes = tree.query(_np.column_stack((x, y, z))) - indexes = _np.unravel_index(indexes, shape) - iY = _np.ndarray.tolist(indexes[Yindex]) - iX = _np.ndarray.tolist(indexes[Xindex]) + if not ds_grid.xoak.index: + if xoak_index not in _xoak.IndexRegistry(): + raise ValueError( + "`sampMethod` [{}] is not supported." + "\nAvailable options: {}" + "".format(xoak_index, _xoak.IndexRegistry()) + ) - # Remove duplicates - diff_iY = _np.diff(iY) - diff_iX = _np.diff(iX) - to_rem = [] - for k, (diY, diX) in enumerate(zip(diff_iY, diff_iX)): - if diY == 0 and diX == 0: - to_rem = to_rem + [k] - iY = _np.asarray([i for j, i in enumerate(iY) if j not in to_rem]) - iX = _np.asarray([i for j, i in enumerate(iX) if j not in to_rem]) - - # Nearest coordinates - near_Y = YC.isel( - Y=_xr.DataArray(iY, dims=("tmp")), X=_xr.DataArray(iX, dims=("tmp")) - ).values - near_X = XC.isel( - Y=_xr.DataArray(iY, dims=("tmp")), X=_xr.DataArray(iX, dims=("tmp")) - ).values - - # Steps - diff_iY = _np.fabs(_np.diff(iY)) - diff_iX = _np.fabs(_np.diff(iX)) - - # Loop until all steps are 1 - while any(diff_iY + diff_iX != 1): - # Find where need to add grid points - k = _np.argwhere(diff_iY + diff_iX != 1)[0][0] - lat0 = near_Y[k] - lon0 = near_X[k] - lat1 = near_Y[k + 1] - lon1 = near_X[k + 1] - - # Find grid point in the middle - if R is not None: - # SPHERICAL: follow great circle path - dist = _great_circle((lat0, lon0), (lat1, lon1), radius=R).km + ds_grid.xoak.set_index(["XC", "YC"], xoak_index) - # Divide dist by 2.1 to make sure that returns 3 points - dist = dist / 2.1 - this_Y, this_X, this_dists = _utils.great_circle_path( - lat0, lon0, lat1, lon1, dist - ) + coords = {"XC": ("mooring", Xmoor), "YC": ("mooring", Ymoor)} + ds_data = _xr.Dataset(coords) # mooring data - # Cartesian coordinate of point in the middle - x, y, z = _utils.spherical2cartesian(this_Y[1], this_X[1], R) - else: - # CARTESIAN: take the average - x = (lon0 + lon1) / 2 - y = (lat0 + lat1) / 2 - z = 0 + # find nearest points to given data. + nds = ds_grid.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) - # Indexes of 3 nearest grid point - _, indexes = tree.query(_np.column_stack((x, y, z)), k=3) - indexes = _np.unravel_index(indexes, shape) - new_iY = _np.ndarray.tolist(indexes[Yindex])[0] - new_iX = _np.ndarray.tolist(indexes[Xindex])[0] - - # Extract just one point - to_rem = [] - for i, (this_iY, this_iX) in enumerate(zip(new_iY, new_iX)): - check1 = this_iY == iY[k] and this_iX == iX[k] - check2 = this_iY == iY[k + 1] and this_iX == iX[k + 1] - if check1 or check2: - to_rem = to_rem + [i] - new_iY = _np.asarray([i for j, i in enumerate(new_iY) if j not in to_rem])[0] - new_iX = _np.asarray([i for j, i in enumerate(new_iX) if j not in to_rem])[0] - - # Extract new lat and lon - new_lat = YC.isel(Y=new_iY, X=new_iX).values - new_lon = XC.isel(Y=new_iY, X=new_iX).values - - # Insert - near_Y = _np.insert(near_Y, k + 1, new_lat) - near_X = _np.insert(near_X, k + 1, new_lon) - iY = _np.insert(iY, k + 1, new_iY) - iX = _np.insert(iX, k + 1, new_iX) - - # Steps - diff_iY = _np.fabs(_np.diff(iY)) - diff_iX = _np.fabs(_np.diff(iX)) + def diff_and_inds_where_insert(ix, iy): + dx, dy = (_np.diff(ii) for ii in (ix, iy)) + inds = _np.argwhere(_np.abs(dx) + _np.abs(dy) > 1).squeeze() + return dx, dy, inds - # New dimensions - mooring = _xr.DataArray( - _np.arange(len(iX)), + ix, iy = (nds["i" + f"{i}"].data for i in ("X", "Y")) + + # Remove duplicates + mask = _np.abs(_np.diff(ix)) + _np.abs(_np.diff(iy)) == 0 + ix, iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (ix, iy)) + + # Initialize variables + dx, dy, inds = diff_and_inds_where_insert(ix, iy) + while inds.size: + dx, dy = (di[inds] for di in (dx, dy)) + mask = _np.abs(dx * dy) == 1 + ix = _np.insert(ix, inds + 1, ix[inds] + (dx / 2).astype(int)) + iy = _np.insert( + iy, inds + 1, iy[inds] + _np.where(mask, dy, (dy / 2).astype(int)) + ) + # Prepare for next iteration + dx, dy, inds = diff_and_inds_where_insert(ix, iy) + + mooring = DataArray( + _np.arange(len(ix)), dims=("mooring"), attrs={"long_name": "index of mooring", "units": "none"}, ) - y = _xr.DataArray( + y = DataArray( _np.arange(1), dims=("y"), attrs={"long_name": "j-index of cell center", "units": "none"}, ) - x = _xr.DataArray( + x = DataArray( _np.arange(1), dims=("x"), attrs={"long_name": "i-index of cell corner", "units": "none"}, ) - yp1 = _xr.DataArray( + yp1 = DataArray( _np.arange(2), dims=("yp1"), attrs={"long_name": "j-index of cell center", "units": "none"}, ) - xp1 = _xr.DataArray( + xp1 = DataArray( _np.arange(2), dims=("xp1"), attrs={"long_name": "i-index of cell corner", "units": "none"}, ) # Transform indexes in DataArray - iy = _xr.DataArray( - _np.reshape(iY, (len(mooring), len(y))), + iY = DataArray( + _np.reshape(iy, (len(mooring), len(y))), coords={"mooring": mooring, "y": y}, dims=("mooring", "y"), ) - ix = _xr.DataArray( - _np.reshape(iX, (len(mooring), len(x))), + iX = DataArray( + _np.reshape(ix, (len(mooring), len(x))), coords={"mooring": mooring, "x": x}, dims=("mooring", "x"), ) - iyp1 = _xr.DataArray( - _np.stack((iY, iY + 1), 1), + iYp1 = DataArray( + _np.stack((iy, iy + 1), 1), coords={"mooring": mooring, "yp1": yp1}, dims=("mooring", "yp1"), ) - ixp1 = _xr.DataArray( - _np.stack((iX, iX + 1), 1), + iXp1 = DataArray( + _np.stack((ix, ix + 1), 1), coords={"mooring": mooring, "xp1": xp1}, dims=("mooring", "xp1"), ) - # Initialize new dataset - new_ds = _xr.Dataset( - { - "mooring": mooring, - "Y": y.rename(y="Y"), - "Yp1": yp1.rename(yp1="Yp1"), - "X": x.rename(x="X"), - "Xp1": xp1.rename(xp1="Xp1"), - }, - attrs=ds.attrs, - ) - - # Loop and take out (looping is faster than apply to the whole dataset) - all_vars = {var: new_ds[var] for var in new_ds} - for var in ds.variables: - if var in ["X", "Y", "Xp1", "Yp1"]: - da = new_ds[var] - da.attrs.update( - { - attr: ds[var].attrs[attr] - for attr in ds[var].attrs - if attr not in ["units", "long_name"] - } - ) - continue - elif not any(dim in ds[var].dims for dim in ["X", "Y", "Xp1", "Yp1"]): - da = ds[var] - else: - for this_dims in [["Y", "X"], ["Yp1", "Xp1"], ["Y", "Xp1"], ["Yp1", "X"]]: - if set(this_dims).issubset(ds[var].dims): - da = ds[var].isel( - { - dim: eval( - "i" + dim.lower(), - {}, - {"iy": iy, "ix": ix, "iyp1": iyp1, "ixp1": ixp1}, - ) - for dim in this_dims - } - ) - da = da.drop_vars(this_dims).rename( - {dim.lower(): dim for dim in this_dims} - ) - - # Add to dictionary - all_vars = {**all_vars, **{var: da}} - - new_ds = _xr.Dataset(all_vars) + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + } - # Merge removes the attributes: put them back! - new_ds.attrs = ds.attrs + rename = {"x": "X", "y": "Y", "yp1": "Yp1", "xp1": "Xp1"} + new_ds = ds.isel(**args).drop_vars(["X", "Y", "Xp1", "Yp1"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) - # Add distance - dists = _np.zeros(near_Y.shape) - for i in range(1, len(dists)): - coord1 = (near_Y[i - 1], near_X[i - 1]) - coord2 = (near_Y[i], near_X[i]) + near_Y = new_ds["XC"].compute().data.squeeze() + near_X = new_ds["YC"].compute().data.squeeze() - if R is not None: - # SPHERICAL - dists[i] = _great_circle(coord1, coord2, radius=R).km - else: - # CARTESIAN - dists[i] = _np.sqrt( - (coord2[0] - coord1[0]) ** 2 + (coord2[1] - coord1[1]) ** 2 - ) + # Add distance (0 always first element) + if R is not None: + dists = _np.array( + [0] + + [ + _great_circle( + (near_Y[i + 1], near_X[i + 1]), (near_Y[i], near_X[i]), radius=R + ).km + for i in range(len(near_Y) - 1) + ] + ) + unit = "km" + else: + dists = _np.sqrt( + (near_Y[1:] - near_Y[:-1]) ** 2 + (near_X[1:] - near_X[:-1]) ** 2 + ) + dists = _np.insert(dists, 0, 0) # add zero as 1st element + if "units" in new_ds["XC"].attrs: + unit = new_ds["XC"].attrs["units"] dists = _np.cumsum(dists) - distance = _xr.DataArray( + distance = DataArray( dists, coords={"mooring": mooring}, dims=("mooring"), - attrs={"long_name": "Distance from first mooring"}, + attrs={"long_name": "Distance from first mooring", "units": unit}, ) - if R is not None: - # SPHERICAL - distance.attrs["units"] = "km" - else: - # CARTESIAN - if "units" in XC.attrs: - distance.attrs["units"] = XC.attrs["units"] new_ds["mooring_dist"] = distance # Reset coordinates diff --git a/oceanspy/tests/test_compute_functions.py b/oceanspy/tests/test_compute_functions.py index 99a6727d..4eaf06d4 100644 --- a/oceanspy/tests/test_compute_functions.py +++ b/oceanspy/tests/test_compute_functions.py @@ -41,6 +41,9 @@ # Create an oceandataset for testing calculus functions od_curv = open_oceandataset.from_netcdf("{}MITgcm_curv_nc.nc" "".format(Datadir)) +ECCO_url = "{}catalog_ECCO.yaml".format(Datadir) +ECCOod = open_oceandataset.from_catalog("LLC", ECCO_url) + # Aliased od ds = od.dataset aliases = {var: var + "_alias" for var in ds.data_vars} @@ -365,44 +368,88 @@ def test_Ertel_potential_vorticity(od_in, full): ds_out_IN_od_out(ds_out, od_out) -@pytest.mark.parametrize("od_in", [od, alias_od]) +@pytest.mark.parametrize("od_in", [od, alias_od, ECCOod]) @pytest.mark.parametrize("mooring", [True, False]) @pytest.mark.parametrize("closed", [True, False]) @pytest.mark.parametrize("flippedX", [True, False]) @pytest.mark.parametrize("flippedY", [True, False]) def test_mooring_volume_transport(od_in, mooring, closed, flippedX, flippedY): + if "face" not in od_in.dataset.dims: + Xmax = od_in.dataset["X"].max().values + Xmin = od_in.dataset["X"].min().values + Ymin = od_in.dataset["Y"].min().values + Ymax = od_in.dataset["Y"].max().values + else: + Xmin, Xmax = -80, 0 + Ymin, Ymax = 35, 35 + + # compute missing (for testing purposes assume uniform) + + Scoords = { + "Z": od_in._ds.Z.values, + "face": od_in._ds.face.values, + "Yp1": od_in._ds.Yp1.values, + "X": od_in._ds.X.values, + } + Wcoords = { + "Z": od_in._ds.Z.values, + "face": od_in._ds.face.values, + "Y": od_in._ds.Yp1.values, + "Xp1": od_in._ds.X.values, + } + + Stmp = xr.DataArray(1, coords=Scoords, dims={"Z", "face", "Yp1", "X"}) + Wtmp = xr.DataArray(1, coords=Wcoords, dims={"Z", "face", "Y", "Xp1"}) + + od_in._ds["HFacS"] = Stmp + od_in._ds["HFacW"] = Wtmp + if mooring is True: if not closed: - X = [od_in.dataset["X"].min().values, od_in.dataset["X"].max().values] - Y = [od_in.dataset["Y"].min().values, od_in.dataset["Y"].max().values] + X = [Xmin, Xmax] + Y = [Ymin, Ymax] od_moor = od_in.subsample.mooring_array(Xmoor=X, Ymoor=Y) if flippedX and not flippedY: - X = [od_in.dataset["X"].max().values, od_in.dataset["X"].min().values] - Y = [od_in.dataset["Y"].min().values, od_in.dataset["Y"].max().values] + X = [Xmax, Xmin] + Y = [Ymin, Ymax] od_moor = od_in.subsample.mooring_array(Xmoor=X, Ymoor=Y) elif flippedX and flippedY: - X = [od_in.dataset["X"].max().values, od_in.dataset["X"].min().values] - Y = [od_in.dataset["Y"].max().values, od_in.dataset["Y"].min().values] + X = [Xmax, Xmin] + Y = [Ymax, Ymin] od_moor = od_in.subsample.mooring_array(Xmoor=X, Ymoor=Y) elif flippedY: - X = [od_in.dataset["X"].min().values, od_in.dataset["X"].max().values] - Y = [od_in.dataset["Y"].max().values, od_in.dataset["Y"].min().values] + X = [Xmin, Xmax] + Y = [Ymax, Ymin] od_moor = od_in.subsample.mooring_array(Xmoor=X, Ymoor=Y) else: - X = [ - od_in.dataset["X"].min().values, - od_in.dataset["X"].max().values, - od_in.dataset["X"].max().values, - od_in.dataset["X"].min().values, - od_in.dataset["X"].min().values, - ] - Y = [ - od_in.dataset["Y"].min().values, - od_in.dataset["Y"].min().values, - od_in.dataset["Y"].max().values, - od_in.dataset["Y"].max().values, - od_in.dataset["Y"].min().values, - ] + if "face" not in od_in.dataset.dims: + X = [ + Xmin, + Xmax, + Xmax, + Xmin, + Xmin, + ] + Y = [ + Ymin, + Ymin, + Ymax, + Ymax, + Ymin, + ] + else: + X = ( + list(np.arange(-80, 0)) + + list(0.5 * np.ones(np.shape(np.arange(35, 39)))) + + list(np.arange(0, -80, -1)) + + list(-80 * np.ones(np.shape(np.arange(39, 34, -1)))) + ) + Y = ( + list(35 * np.ones(np.shape(np.arange(-80, 0)))) + + list(np.arange(35, 39)) + + list(39 * np.ones(np.shape(np.arange(0, -80, -1)))) + + list(np.arange(39, 34, -1)) + ) od_moor = od_in.subsample.mooring_array(Xmoor=X, Ymoor=Y) # Compute transport diff --git a/oceanspy/tests/test_subsample.py b/oceanspy/tests/test_subsample.py index dd1cfa3b..9dac1233 100644 --- a/oceanspy/tests/test_subsample.py +++ b/oceanspy/tests/test_subsample.py @@ -334,8 +334,12 @@ def test_mooring(od, cartesian, kwargs): if cartesian: this_od = this_od.set_parameters({"rSphere": None}) - Xmoor = [this_od.dataset["XC"].min().values, this_od.dataset["XC"].max().values] - Ymoor = [this_od.dataset["YC"].min().values, this_od.dataset["YC"].max().values] + if "face" not in od.dataset.dims: + Xmoor = [this_od.dataset["XC"].min().values, this_od.dataset["XC"].max().values] + Ymoor = [this_od.dataset["YC"].min().values, this_od.dataset["YC"].max().values] + else: + Xmoor = [-80, 80] + Ymoor = [35, 35] new_od = this_od.subsample.mooring_array(Xmoor=Xmoor, Ymoor=Ymoor, **kwargs) with pytest.raises(ValueError): diff --git a/oceanspy/tests/test_utils.py b/oceanspy/tests/test_utils.py index f913f19f..ccc7563a 100644 --- a/oceanspy/tests/test_utils.py +++ b/oceanspy/tests/test_utils.py @@ -6,6 +6,7 @@ from oceanspy.utils import ( _reset_range, cartesian_path, + circle_path_array, great_circle_path, spherical2cartesian, viewer_to_range, @@ -39,6 +40,33 @@ def test_error_path(): cartesian_path(1, 2, 3, 4, delta=-1) +def test_error_circle_array(): + with pytest.raises(ValueError): + circle_path_array([1, 1], [1, 1], R=6371.0) + with pytest.raises(ValueError): + circle_path_array([0], [0, 0, 0], R=6371.0) + with pytest.raises(TypeError): + circle_path_array([1, 0], [0, 0], R=None) + + +@pytest.mark.parametrize( + "lats, lons, symmetry, resolution", + [ + ([0, 0.5], [0, 0], "latitude", 25), + ([0, 0], [0, 0.5], "longitude", 25), + ([0, 0], [0, 0.125], False, 25), + ], +) +def test_circle_path_array(lats, lons, symmetry, resolution): + nY, nX = circle_path_array(lats, lons, R=6371.0, _res=resolution) + if symmetry == "latitude": + assert (nX == _np.zeros(len(nX))).all() + elif symmetry == "longitude": + assert (nY == _np.zeros(len(nY))).all() + else: + assert len(nY) == len(lats) + + coords1 = [[[0, 0], [1, 1], [2, 2], [3, 3], [4, 4], [5, 5]]] coords2 = [[[5, 0], [4, 1], [3, 2], [2, 3], [1, 4], [0, 5]]] coords3 = [[[0, 6], [0, 7], [0, 8], [0, 9], [0, 10], [0, 11]]] diff --git a/oceanspy/utils.py b/oceanspy/utils.py index bb71e7ff..dbba0d39 100644 --- a/oceanspy/utils.py +++ b/oceanspy/utils.py @@ -354,6 +354,77 @@ def great_circle_path(lat1, lon1, lat2, lon2, delta_km=None, R=None): return lats, lons, dists +def circle_path_array(_Y, _X, R, _res=25): + """ + Given a list of prescribed coordinate points of len(N), returns an array of + increased (or equal) length, wherein the added values are computed following + a great circle path. The spatial resolution is set by _res=25 (by default) in + km=25. + """ + + # Check parameters + _check_instance( + { + "lats": _Y, + "lons": _X, + "res": _res, + "R": R, + }, + { + "lats": ["list", "numpy.ndarray"], + "lons": ["list", "numpy.ndarray"], + "res": "numpy.ScalarType", + "R": "numpy.ScalarType", + }, + ) + + _Y = _np.asarray(_Y, dtype=_np.float64) + _X = _np.asarray(_X, dtype=_np.float64) + + if len(_Y) != len(_X): + raise ValueError("_Y and _X arrays must have same number of entries") + + diffsum = abs(_X[1:] - _X[:-1]) + abs(_Y[1:] - _Y[:-1]) + if _np.sum(diffsum) == 0: + raise ValueError("There must be at least two different coordinates points") + + dists = [] + for i in range(len(_Y) - 1): + dists.append(_great_circle((_Y[i], _X[i]), (_Y[i + 1], _X[i + 1]), radius=R).km) + k = _np.argwhere(_np.array(dists) > _res).squeeze() + nY = [[] * k.size for i in range(k.size)] + nX = [[] * k.size for i in range(k.size)] + ndists = [] + if k.size: + if k.size == 1: # only one element + nY, nX, ndists = great_circle_path(_Y[k], _X[k], _Y[k + 1], _X[k + 1], _res) + if len(nY) == 2: + nY, nX, ndists = great_circle_path( + _Y[k], _X[k], _Y[k + 1], _X[k + 1], _res / 2 + ) + else: + for ii in range(k.size): + ny, nx, dists = great_circle_path( + _Y[k[ii]], _X[k[ii]], _Y[k[ii] + 1], _X[k[ii] + 1], _res + ) + if len(ny) == 2: + ny, nx, dists = great_circle_path( + _Y[k[ii]], _X[k[ii]], _Y[k[ii] + 1], _X[k[ii] + 1], _res / 2 + ) + nY[ii] = list(ny) + nX[ii] = list(nx) + Nn = [len(nY[i]) for i in range(len(nY))] + nk = 0 * k + for ii in range(len(k)): + nk[ii] = k[ii] + sum(Nn[:ii]) + _Y = list(_Y[: nk[ii] + 1]) + list(nY[ii]) + list(_Y[nk[ii] + 1 :]) + _X = list(_X[: nk[ii] + 1]) + list(nX[ii]) + list(_X[nk[ii] + 1 :]) + nY, nX = _Y, _X # update + else: + nY, nX = _Y, _X + return nY, nX + + def cartesian_path(x1, y1, x2, y2, delta=None): """ Generate a trajectory specifying the distance resolution. diff --git a/sciserver_catalogs/environment.yml b/sciserver_catalogs/environment.yml index ab9d562a..188e954a 100644 --- a/sciserver_catalogs/environment.yml +++ b/sciserver_catalogs/environment.yml @@ -2,12 +2,13 @@ name: Oceanography channels: - conda-forge dependencies: -- python=3.9 +- python=3.10 - dask - distributed - bottleneck -- netCDF4 < 1.6.2 +- netCDF4 - xarray +- xoak - cartopy - esmpy - geopy @@ -43,7 +44,7 @@ dependencies: - cftime - rasterio - cfgrib -- matplotlib < 3.5.3 +- matplotlib <= 3.6.0 - cf_xarray - ipykernel - numba From ab60c6dcb621ea586705bb0c582a87e4335cb206 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 17 May 2023 18:30:29 -0400 Subject: [PATCH 10/32] [pre-commit.ci] pre-commit autoupdate (#353) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/macisamuele/language-formatters-pre-commit-hooks: v2.8.0 → v2.9.0](https://github.com/macisamuele/language-formatters-pre-commit-hooks/compare/v2.8.0...v2.9.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index aa5782de..9ed2726a 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -14,7 +14,7 @@ repos: - id: debug-statements - id: mixed-line-ending - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks - rev: v2.8.0 + rev: v2.9.0 hooks: - id: pretty-format-yaml args: [--autofix, --preserve-quotes] From fb4cc9635bea85383ed48c598701644130ea0d99 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Fri, 19 May 2023 13:37:28 -0400 Subject: [PATCH 11/32] Iss349 (#355) * format * format * format * unpin matplotlib in binder --------- Co-authored-by: Miguel Jimenez --- binder/environment.yml | 2 +- ci/environment.yml | 2 +- oceanspy/tests/test_animate.py | 8 ++++++-- oceanspy/tests/test_subsample.py | 12 ++++++++---- sciserver_catalogs/environment.yml | 2 +- 5 files changed, 17 insertions(+), 9 deletions(-) diff --git a/binder/environment.yml b/binder/environment.yml index 260d1daf..12579c26 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -4,7 +4,7 @@ channels: dependencies: - python - numpy -- matplotlib<=3.6.0 +- matplotlib - pandas - bokeh - rise diff --git a/ci/environment.yml b/ci/environment.yml index 33cbdf45..4bf29255 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -23,7 +23,7 @@ dependencies: - ffmpeg - aiohttp - pandas -- matplotlib<=3.6 +- matplotlib - fsspec!=0.9.0 - pooch - pip diff --git a/oceanspy/tests/test_animate.py b/oceanspy/tests/test_animate.py index 1490d2ae..ac49a3f1 100644 --- a/oceanspy/tests/test_animate.py +++ b/oceanspy/tests/test_animate.py @@ -39,11 +39,15 @@ # ========== # TS diagram # ========== +Xmin = od.dataset["XC"].min().values +Xmax = od.dataset["XC"].max().values + + @pytest.mark.parametrize( - "od_in," " cutout_kwargs, colorName, Tlim, Slim, cmap_kwargs", + "od_in, cutout_kwargs, colorName, Tlim, Slim, cmap_kwargs", [ (od, None, None, None, None, None), - (od, {"ZRange": 0}, "Temp", [0, 1], [0, 1], {"robust": True}), + (od, {"XRange": [Xmin, Xmax]}, "Temp", [0, 1], [0, 1], {"robust": True}), ], ) def test_anim_TSdiagram(od_in, cutout_kwargs, colorName, Tlim, Slim, cmap_kwargs): diff --git a/oceanspy/tests/test_subsample.py b/oceanspy/tests/test_subsample.py index 9dac1233..c8b91b77 100644 --- a/oceanspy/tests/test_subsample.py +++ b/oceanspy/tests/test_subsample.py @@ -324,7 +324,7 @@ def test_cutout_faces( # ======= # MOORING # ======= -@pytest.mark.parametrize("od", [MITgcm_rect_nc]) +@pytest.mark.parametrize("od", [MITgcm_rect_nc, ECCOod]) @pytest.mark.parametrize("cartesian", [True, False]) @pytest.mark.parametrize( "kwargs", [{}, {"YRange": None, "XRange": None, "add_Hbdr": True}] @@ -338,7 +338,7 @@ def test_mooring(od, cartesian, kwargs): Xmoor = [this_od.dataset["XC"].min().values, this_od.dataset["XC"].max().values] Ymoor = [this_od.dataset["YC"].min().values, this_od.dataset["YC"].max().values] else: - Xmoor = [-80, 80] + Xmoor = [-80, 0] Ymoor = [35, 35] new_od = this_od.subsample.mooring_array(Xmoor=Xmoor, Ymoor=Ymoor, **kwargs) @@ -346,8 +346,12 @@ def test_mooring(od, cartesian, kwargs): new_od.subsample.mooring_array(Xmoor=Xmoor, Ymoor=Ymoor) for index in [0, -1]: - assert new_od.dataset["XC"].isel(mooring=index).values == Xmoor[index] - assert new_od.dataset["YC"].isel(mooring=index).values == Ymoor[index] + if "face" not in od.dataset.dims: + assert new_od.dataset["XC"].isel(mooring=index).values == Xmoor[index] + assert new_od.dataset["YC"].isel(mooring=index).values == Ymoor[index] + else: + assert new_od.dataset["XC"].isel(mooring=index).values - Xmoor[index] < 1 + assert new_od.dataset["YC"].isel(mooring=index).values - Ymoor[index] < 1 checkX = new_od.grid.diff(new_od.dataset["XC"], "mooring") checkY = new_od.grid.diff(new_od.dataset["YC"], "mooring") diff --git a/sciserver_catalogs/environment.yml b/sciserver_catalogs/environment.yml index 188e954a..03990953 100644 --- a/sciserver_catalogs/environment.yml +++ b/sciserver_catalogs/environment.yml @@ -44,7 +44,7 @@ dependencies: - cftime - rasterio - cfgrib -- matplotlib <= 3.6.0 +- matplotlib - cf_xarray - ipykernel - numba From 3bfaf18cd970aab2f2d0a3a8a152f1ffe5f6e272 Mon Sep 17 00:00:00 2001 From: Mattia Almansi Date: Fri, 19 May 2023 20:45:49 +0200 Subject: [PATCH 12/32] test and support python 3.11 (#351) --- .github/workflows/ci.yaml | 2 +- pyproject.toml | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 79a87322..574838f9 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -26,7 +26,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: ['3.9', '3.10'] + python-version: ['3.9', '3.10', '3.11'] steps: - uses: actions/checkout@v3 diff --git a/pyproject.toml b/pyproject.toml index 08046872..e04040b2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,6 +11,7 @@ classifiers = [ "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", "Topic :: Scientific/Engineering" ] dependencies = [ From 954984d6dab8b42f8da89643236b17561acfefdf Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 22 May 2023 10:04:35 -0400 Subject: [PATCH 13/32] Bump codecov/codecov-action from 3.1.3 to 3.1.4 (#358) Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 3.1.3 to 3.1.4. - [Release notes](https://github.com/codecov/codecov-action/releases) - [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md) - [Commits](https://github.com/codecov/codecov-action/compare/v3.1.3...v3.1.4) --- updated-dependencies: - dependency-name: codecov/codecov-action dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/ci.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 574838f9..593d0147 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -49,7 +49,7 @@ jobs: run: pytest --cov=./ --cov-report=xml - name: Upload code coverage to Codecov - uses: codecov/codecov-action@v3.1.3 + uses: codecov/codecov-action@v3.1.4 with: token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml From 0a08cd8ec0444198bbce312f5a72f51b2317ec93 Mon Sep 17 00:00:00 2001 From: MaceKuailv <52629492+MaceKuailv@users.noreply.github.com> Date: Tue, 23 May 2023 16:35:43 -0400 Subject: [PATCH 14/32] Adding the ETOPO topography to sciserver catalog (#360) * add the etopo catalog * add to the list * forgot style again * change the projection * take away parallel = True because there is only one file --- sciserver_catalogs/catalog_xarray.yaml | 16 ++++++++++++++++ sciserver_catalogs/datasets_list.yaml | 1 + 2 files changed, 17 insertions(+) diff --git a/sciserver_catalogs/catalog_xarray.yaml b/sciserver_catalogs/catalog_xarray.yaml index 6b209880..2f49b026 100644 --- a/sciserver_catalogs/catalog_xarray.yaml +++ b/sciserver_catalogs/catalog_xarray.yaml @@ -1040,3 +1040,19 @@ sources: Sample (test) files projection: Mercator original_output: snapshot + +# ETOPO 2022 + ETOPO: + description: ETOPO - Integrated topography, bathymetry, and shoreline data from regional and global datasets + driver: zarr + model: NA + args: + urlpath: '/home/idies/workspace/poseidon/data12_01/ETOPO' + xarray_kwargs: + engine: zarr + metadata: + name: ETOPO + description: The ice surface version of ETOPO + citation: 10.25921/fd45-gt74. + projection: PlateCarree + original_output: snapshot diff --git a/sciserver_catalogs/datasets_list.yaml b/sciserver_catalogs/datasets_list.yaml index 1c0b81cf..a5ca9b27 100644 --- a/sciserver_catalogs/datasets_list.yaml +++ b/sciserver_catalogs/datasets_list.yaml @@ -16,3 +16,4 @@ datasets: - LLC4320 - ECCO - daily_ecco + - ETOPO From cff27a318d9c83dcfbd1d34b8e78735715dd295a Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Tue, 23 May 2023 16:42:50 -0400 Subject: [PATCH 15/32] Compute accurately dist along array (#361) * improve description * remove unnecesary code * use correct import * fix huge bug!!! * format * format --------- Co-authored-by: Miguel Jimenez --- oceanspy/subsample.py | 60 +++++++++++++++++++++++++++++++++---------- 1 file changed, 47 insertions(+), 13 deletions(-) diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index b33c7cb2..54b2d1c2 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -653,6 +653,8 @@ def mooring_array(od, Ymoor, Xmoor, xoak_index="scipy_kdtree", **kwargs): Y coordinates of moorings. Xmoor: 1D array_like, scalar X coordinates of moorings. + xoak_index: str + xoak index to be used. `scipy_kdtree` by default. **kwargs: Keyword arguments for :py:func:`oceanspy.subsample.cutout`. @@ -696,30 +698,26 @@ def mooring_array(od, Ymoor, Xmoor, xoak_index="scipy_kdtree", **kwargs): # Unpack ds ds = od._ds + # create list of coordinates. + coords = [var for var in ds if "time" not in ds[var].dims] ds_grid = ds[["XC", "YC"]] # by convention center point for key, value in ds_grid.sizes.items(): ds_grid["i" + f"{key}"] = DataArray(range(value), dims=key) - if R is not None: # spherical coordinates - # make sure that the array defines a great circle path of resolution 100km - Ymoor, Xmoor = circle_path_array( - Ymoor, Xmoor, R - ) # make sure Xmoor and Ymoor define a c - if not ds_grid.xoak.index: if xoak_index not in _xoak.IndexRegistry(): raise ValueError( - "`sampMethod` [{}] is not supported." + "`xoak_index` [{}] is not supported." "\nAvailable options: {}" "".format(xoak_index, _xoak.IndexRegistry()) ) ds_grid.xoak.set_index(["XC", "YC"], xoak_index) - coords = {"XC": ("mooring", Xmoor), "YC": ("mooring", Ymoor)} - ds_data = _xr.Dataset(coords) # mooring data + cdata = {"XC": ("mooring", Xmoor), "YC": ("mooring", Ymoor)} + ds_data = _xr.Dataset(cdata) # mooring data # find nearest points to given data. nds = ds_grid.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) @@ -731,7 +729,7 @@ def diff_and_inds_where_insert(ix, iy): ix, iy = (nds["i" + f"{i}"].data for i in ("X", "Y")) - # Remove duplicates + # Remove duplicates that are next to each other. mask = _np.abs(_np.diff(ix)) + _np.abs(_np.diff(iy)) == 0 ix, iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (ix, iy)) @@ -747,6 +745,42 @@ def diff_and_inds_where_insert(ix, iy): # Prepare for next iteration dx, dy, inds = diff_and_inds_where_insert(ix, iy) + def remove_repeated(_iX, _iY): + """Attemps to remove repeated coords not adjascent to each other, + while retaining the trajectory property of being simply connected + (i.e. the distance between each index point is one). If it cannot + remove repeated coordinate values, returns the original array. + """ + _ix, _iy = _iX, _iY + nn = [] + for n in range(len(_ix)): + val = _np.where(abs(_ix - _ix[n]) + abs(_iy - _iy[n]) == 0)[0] + # select only repeated values with deg of multiplicity = 2 + if len(val) == 2: + if len(nn) == 0: + nn.append(list(val)) + elif len(nn) > 0 and (val != nn).all(): + nn.append(list(val)) + if _np.array(nn).size: + dn = [nn[i][1] - nn[i][0] for i in range(len(nn))] + # remove if the distance between repeated coords is 2 + mask = _np.where(_np.array(dn) == 2)[0] + remove = [nn[i][1] for i in mask] + _ix, _iy = (_np.delete(ii, remove) for ii in (_ix, _iy)) + # find the hole left + mask = _np.abs(_np.diff(_ix)) + _np.abs(_np.diff(_iy)) == 2 + # delete hole left behind + _ix, _iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (_ix, _iy)) + # verify path is simply connected + dx, dy, inds = diff_and_inds_where_insert(_ix, _iy) + if inds.size: + _ix = _iX + _iY = _iY + return _ix, _iy + + # attempt to remove repeated (but not adjacent) coord values + ix, iy = remove_repeated(ix, iy) + mooring = DataArray( _np.arange(len(ix)), dims=("mooring"), @@ -806,8 +840,8 @@ def diff_and_inds_where_insert(ix, iy): new_ds = ds.isel(**args).drop_vars(["X", "Y", "Xp1", "Yp1"]) new_ds = new_ds.rename_dims(rename).rename_vars(rename) - near_Y = new_ds["XC"].compute().data.squeeze() - near_X = new_ds["YC"].compute().data.squeeze() + near_Y = new_ds["YC"].compute().data.squeeze() + near_X = new_ds["XC"].compute().data.squeeze() # Add distance (0 always first element) if R is not None: @@ -840,7 +874,7 @@ def diff_and_inds_where_insert(ix, iy): new_ds["mooring_dist"] = distance # Reset coordinates - new_ds = new_ds.set_coords([coord for coord in ds.coords] + ["mooring_dist"]) + new_ds = new_ds.set_coords(coords + ["mooring_dist"]) # Recreate od od._ds = new_ds From a0438907fe8caa2fb623c21808aab23465e71993 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Fri, 26 May 2023 09:26:14 -0400 Subject: [PATCH 16/32] improved behavior of subsample.mooring (#364) * refactor a bit * format * isort * allow NoneType * fix test * black format * restore * fix drop var when XRange is None (but YRange is not None) * def rel_lon when XRange is None * black formatting * improve comp * format - black * black * black format --------- Co-authored-by: Miguel Jimenez --- oceanspy/llc_rearrange.py | 52 ++++++++-------- oceanspy/subsample.py | 9 +-- oceanspy/tests/test_llc_rearrange.py | 2 +- oceanspy/tests/test_utils.py | 20 +++++-- oceanspy/utils.py | 89 ++++++++++++++++------------ 5 files changed, 97 insertions(+), 75 deletions(-) diff --git a/oceanspy/llc_rearrange.py b/oceanspy/llc_rearrange.py index 6bebfd37..75f7408c 100644 --- a/oceanspy/llc_rearrange.py +++ b/oceanspy/llc_rearrange.py @@ -9,6 +9,7 @@ import dask import numpy as _np import xarray as _xr +from xarray import DataArray, Dataset from xgcm import Grid from .utils import _rel_lon, _reset_range, get_maskH @@ -32,10 +33,6 @@ ] -_datype = _xr.core.dataarray.DataArray -_dstype = _xr.core.dataset.Dataset - - class LLCtransformation: """A class containing the transformation types of LLCgrids.""" @@ -236,13 +233,13 @@ def arctic_crown( ARCT[i] = _xr.merge(ARCT[i]) DSa2, DSa5, DSa7, DSa10 = ARCT - if type(DSa2) != _dstype: + if type(DSa2) != Dataset: DSa2 = 0 - if type(DSa5) != _dstype: + if type(DSa5) != Dataset: DSa5 = 0 - if type(DSa7) != _dstype: + if type(DSa7) != Dataset: DSa7 = 0 - if type(DSa10) != _dstype: + if type(DSa10) != Dataset: DSa10 = 0 DSa7 = shift_dataset(DSa7, dims_c.X, dims_g.X) @@ -311,11 +308,11 @@ def arctic_crown( # Here, address shifts in Arctic # arctic exchange with face 10 - if type(faces2[0]) == _dstype: + if type(faces2[0]) == Dataset: faces2[0]["Yp1"] = faces2[0]["Yp1"] + 1 # Arctic exchange with face 2 - if type(faces3[3]) == _dstype: + if type(faces3[3]) == Dataset: faces3[3]["Xp1"] = faces3[3]["Xp1"] + 1 # ===== @@ -383,8 +380,8 @@ def arctic_crown( # First, check if there is data in both DSFacet12 and DSFacet34. # If not, then there is no need to transpose data in DSFacet12. - if type(DSFacet12) == _dstype: - if type(DSFacet34) == _dstype: + if type(DSFacet12) == Dataset: + if type(DSFacet34) == Dataset: # two lines below asserts correct # staggering of center and corner points # in latitude (otherwise, lat has a jump) @@ -429,8 +426,7 @@ def arctic_crown( if chunks: DS = DS.chunk(chunks) - if XRange is not None and YRange is not None: - # drop copy var = 'nYg' (line 101) + if "nYG" in DS.reset_coords().data_vars: DS = DS.drop_vars(_var_) if geo_true: @@ -688,7 +684,7 @@ def rotate_vars(_ds): topology makes it so that u on a rotated face transforms to `+- v` on a lat lon grid. """ - if type(_ds) == _dstype: # if a dataset transform otherwise pass + if type(_ds) == Dataset: # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) _vars = [var for var in _ds.variables] rot_names = {} @@ -716,7 +712,7 @@ def shift_dataset(_ds, dims_c, dims_g): dims_c. """ - if type(_ds) == _dstype: # if a dataset transform otherwise pass + if type(_ds) == Dataset: # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) for _dim in [dims_c, dims_g]: if int(_ds[_dim][0].data) < int(_ds[_dim][1].data): @@ -737,7 +733,7 @@ def reverse_dataset(_ds, dims_c, dims_g, transpose=False): so dims_c is either one of `i` or `j`, and dims_g is either one of `i_g` or `j_g`. The pair most correspond to the same dimension.""" - if type(_ds) == _dstype: # if a dataset transform otherwise pass + if type(_ds) == Dataset: # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) for _dim in [dims_c, dims_g]: # This part should be different for j_g points? @@ -771,7 +767,7 @@ def rotate_dataset( nface=int: correct number to use. This is the case a merger/concatenated dataset is being manipulated. Nij is no longer the size of the face. """ - if type(_ds) == _dstype: # if a dataset transform otherwise pass + if type(_ds) == Dataset: # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) Nij = max(len(_ds[dims_c.X]), len(_ds[dims_c.Y])) @@ -832,7 +828,7 @@ def shift_list_ds(_DS, dims_c, dims_g, Ni, facet=1): else: for _dim in [dims_c, dims_g]: dim0 = int(_DS[ii - 1][_dim][-1].data + 1) - if type(_DS[ii]) == _dstype: + if type(_DS[ii]) == Dataset: for _dim in [dims_c, dims_g]: _DS[ii]["n" + _dim] = ( _DS[ii][_dim] - (fac * int(_DS[ii][_dim][0].data)) + dim0 @@ -845,7 +841,7 @@ def shift_list_ds(_DS, dims_c, dims_g, Ni, facet=1): ) DS = [] for lll in range(len(_DS)): - if type(_DS[lll]) == _dstype: + if type(_DS[lll]) == Dataset: DS.append(_DS[lll]) else: DS = _DS @@ -886,7 +882,7 @@ def flip_v(_ds, co_list=metrics, dims=True, _len=3): dims is given """ - if type(_ds) == _dstype: + if type(_ds) == Dataset: for _varName in _ds.variables: if dims: DIMS = [dim for dim in _ds[_varName].dims if dim != "face"] @@ -993,12 +989,12 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): ARCT[3].append(DS[3]) for i in range(len(ARCT)): # Not all faces survive the cutout - if type(ARCT[i][0]) == _datype: + if type(ARCT[i][0]) == DataArray: ARCT[i] = _xr.merge(ARCT[i]) DSa2, DSa5, DSa7, DSa10 = ARCT - if type(DSa2) != _dstype: + if type(DSa2) != Dataset: DSa2 = 0 [Xi_2, Xf_2] = [0, 0] else: @@ -1007,7 +1003,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): else: Xf_2 = _edge_arc_data(DSa2[_var], 2, _dims) Xi_2 = int(DSa2[_var][_dims.X][0]) - if type(DSa5) != _dstype: + if type(DSa5) != Dataset: DSa5 = 0 [Yi_5, Yf_5] = [0, 0] else: @@ -1016,7 +1012,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): else: Yf_5 = _edge_arc_data(DSa5[_var], 5, _dims) Yi_5 = int(DSa5[_var][_dims.Y][0]) - if type(DSa7) != _dstype: + if type(DSa7) != Dataset: DSa7 = 0 [Xi_7, Xf_7] = [0, 0] else: @@ -1026,7 +1022,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): Xi_7 = _edge_arc_data(DSa7[_var], 7, _dims) Xf_7 = int(DSa7[_var][_dims.X][-1]) - if type(DSa10) != _dstype: + if type(DSa10) != Dataset: DSa10 = 0 [Yi_10, Yf_10] = [0, 0] else: @@ -1056,7 +1052,7 @@ def _edge_facet_data(_Facet_list, _var, _dims, _axis): XRange = [] for i in range(len(_Facet_list)): - if type(_Facet_list[i]) == _dstype: + if type(_Facet_list[i]) == Dataset: # there is data _da = _Facet_list[i][_var].load() # load into memory 2d data. X0 = [] @@ -1091,7 +1087,7 @@ def slice_datasets(_DSfacet, dims_c, dims_g, _edges, _axis): _DSFacet = _copy.deepcopy(_DSfacet) for i in range(len(_DSFacet)): # print(i) - if type(_DSFacet[i]) == _dstype: + if type(_DSFacet[i]) == Dataset: for _dim in [_dim_c, _dim_g]: if len(_edges) == 1: ii_0 = int(_edges[0]) diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index 54b2d1c2..032593f8 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -212,9 +212,7 @@ def cutout( # Drop variables if varList is not None: # Make sure it's a list - varList = list(varList) - varList = varList + co_list - varList = _rename_aliased(od, varList) + varList = _rename_aliased(od, list(varList) + co_list) # Compute missing variables od = _compute._add_missing_variables(od, varList) @@ -402,7 +400,10 @@ def cutout( # --------------------------- # Initialize horizontal mask if XRange is not None or YRange is not None: - XRange, ref_lon = _reset_range(XRange) + if XRange is not None: + XRange, ref_lon = _reset_range(XRange) + else: + ref_lon = 180 maskH, dmaskH, XRange, YRange = get_maskH( ds, add_Hbdr, XRange, YRange, ref_lon=ref_lon ) diff --git a/oceanspy/tests/test_llc_rearrange.py b/oceanspy/tests/test_llc_rearrange.py index bde4b0fa..8d32b99a 100644 --- a/oceanspy/tests/test_llc_rearrange.py +++ b/oceanspy/tests/test_llc_rearrange.py @@ -2592,7 +2592,7 @@ def test_mask_var(od, XRange, YRange): (od, P06_lon, P06_lat, [0, 0], [0, 0], [0, 0], [0, 0]), (od, [-31, -2], [58, 68.2], [0, 3], [0, 0], [0, 0], [0, 0]), (od, [160, -160], [58, 85.2], [0, 0], [0, 0], [52, 89], [0, 0]), - (od, [160, 100], [58, 85.2], [0, 0], [0, 39], [51, 89], [0, 0]), + (od, [160, 100], [58, 85.2], [0, 39], [0, 39], [51, 89], [51, 89]), ], ) def test_arc_limits_mask(od, XRange, YRange, A, B, C, D): diff --git a/oceanspy/tests/test_utils.py b/oceanspy/tests/test_utils.py index ccc7563a..8780f6c8 100644 --- a/oceanspy/tests/test_utils.py +++ b/oceanspy/tests/test_utils.py @@ -70,7 +70,11 @@ def test_circle_path_array(lats, lons, symmetry, resolution): coords1 = [[[0, 0], [1, 1], [2, 2], [3, 3], [4, 4], [5, 5]]] coords2 = [[[5, 0], [4, 1], [3, 2], [2, 3], [1, 4], [0, 5]]] coords3 = [[[0, 6], [0, 7], [0, 8], [0, 9], [0, 10], [0, 11]]] +lons = [] coords4 = '[{"type":"Point","coordinates":[-169.23960833202577,22.865677261831266]}]' +coords5 = '[{"type":"Point","coordinates":[636.7225446274502, -56.11128546740994]}]' +coords6 = '[{"type":"Point","coordinates":[754.2277421326479, -57.34299561290217]}]' +coords7 = '[{"type":"Point","coordinates":[-424.42989807993234, 37.87263032287052]}]' @pytest.mark.parametrize( @@ -83,6 +87,9 @@ def test_circle_path_array(lats, lons, symmetry, resolution): (coords2, "LineString", [[5, 0]], [[4, 1]]), (coords3, "LineString", [[0, 6]], [[0, 7]]), (coords4, "Point", [-169.23960833202577], [22.865677261831266]), + (coords5, "Point", [-83.27745537254975], [-56.11128546740994]), + (coords6, "Point", [34.227742132647904], [-57.34299561290217]), + (coords7, "Point", [-64.42989807993234], [37.87263032287052]), ], ) def test_viewer_to_range(coords, types, lon, lat): @@ -116,14 +123,17 @@ def test_viewer_to_range(coords, types, lon, lat): (X2, X0, 53.67), (X3, X3, 180), (X4, X3, 180), - (X5, _np.array([161, 19]), 113.67), - (X6, _np.array([161, 19]), 113.67), - (X7, X7, 180), + (X5, None, 180), + (X6, None, 180), + (X7, X7, 6.67), ], ) def test_reset_range(XRange, x0, expected_ref): """test the function rel_lon which redefines the reference long.""" x_range, ref_lon = _reset_range(XRange) - assert len(x_range) == 2 - assert x_range.all() == x0.all() + if x0 is not None: + assert len(x_range) == 2 + assert x_range.all() == x0.all() + else: + assert x_range is None assert _np.round(ref_lon, 2) == expected_ref diff --git a/oceanspy/utils.py b/oceanspy/utils.py index dbba0d39..2b5b8a77 100644 --- a/oceanspy/utils.py +++ b/oceanspy/utils.py @@ -85,7 +85,16 @@ def viewer_to_range(p): lon.append(coords[i][0]) lat.append(coords[i][1]) - return lon, lat + # check that there are no lon values greater than 180 (abs) + ll = _np.where(abs(_np.array(lon)) > 180)[0] + if ll.size: + lon = _np.array(lon) + sign = _np.sign(lon[ll]) + fac = _np.round(abs(lon)[ll] / 360) + nlon = lon[ll] - 360 * sign * fac + lon[ll] = nlon + + return list(lon), lat def _rel_lon(x, ref_lon): @@ -108,7 +117,7 @@ def _rel_lon(x, ref_lon): return (x - ref_lon) % 360 -def _reset_range(x): +def _reset_range(xn): """Resets the definition of XRange, by default the discontinuity at 180 long. Checks that there is no sign change in x and if there is, the only change that is allowed is when crossing zero. Otherwise resets ref_lon. @@ -127,41 +136,47 @@ def _reset_range(x): redefined_x: numpy.array. converted longitude. """ - - ref_lon = 180 - if x is not None: - if (_np.sign(x) == _np.sign(x[0])).all(): # no sign change - _ref_lon = ref_lon - X0, X1 = _np.min(x), _np.max(x) - else: # change in sign - if len(x) == 2: # list of end points - X0, X1 = x - if x[0] > x[1]: # across discontinuity - if abs(x[1] - x[0]) > 300: # across a discontinuity (Delta X =360) - _ref_lon = x[0] - (x[0] - x[1]) / 3 - else: # XRange decreases, but not necessarity a dicont. - _ref_lon = ref_lon - else: - _ref_lon = ref_lon - else: # array of values. - _del = abs(x[1:] - x[:-1]) # only works with one crossing - if len(_np.where(abs(_del) > 300)[0]) > 0: # there's discontinuity - ll = _np.where(_del == max(_del))[0][0] - if x[ll] > x[ll + 1]: # track starts west of jump - X0 = _np.min(x[: ll + 1]) - X1 = _np.max(x[ll + 1 :]) - else: - X0 = _np.min(x[ll + 1 :]) - X1 = _np.max(x[: ll + 1]) - _ref_lon = X0 - (X0 - X1) / 3 - else: # no discontinuity - X0 = _np.min(x) - X1 = _np.max(x) - _ref_lon = ref_lon - x = _np.array([X0, X1]) - else: - _ref_lon = ref_lon - return x, _np.round(_ref_lon, 2) + _ref_lon = 180 + xn = _np.array(xn) + cross = _np.where(_np.diff(_np.sign(xn)))[0] + if cross.size and xn.size != 2: + ref = 180, 0 + if cross.size == 1: # one sign change + d1 = [abs(abs(xn[cross[0]]) - i) for i in ref] + i0 = _np.argwhere(_np.array(d1) == min(d1))[0][0] + if i0 == 0: # Pacific + ll = _np.where(xn > 0)[0] + nxn = _copy.deepcopy(xn) + nxn[ll] = nxn[ll] - 360 + X = _np.min(nxn) + 360, _np.max(nxn) + _ref_lon = X[0] - (X[0] - X[1]) / 3 + else: # Atlantic + X = _np.min(xn), _np.max(xn) + if cross.size > 1: # 2 or more sign changes + da = [abs(abs(xn[i]) - 180) for i in cross] + db = [abs(abs(xn[i]) - 0) for i in cross] + d = _np.array([[da[i], db[i]] for i in range(len(da))]) + ind = [_np.argwhere(d[i] == min(d[i]))[0][0] for i in range(len(d))] + if all(ind[0] == i for i in ind) and ind[0] == 0: # Pacific + ll = _np.where(xn > 0)[0] + nxn = _copy.deepcopy(xn) + nxn[ll] = nxn[ll] - 360 + X = _np.min(nxn) + 360, _np.max(nxn) + _ref_lon = X[0] - (X[0] - X[1]) / 3 + elif all(ind[0] == i for i in ind) and ind[0] == 1: # Atlantic + X = _np.min(xn), _np.max(xn) + else: + X = None + elif cross.size == 0 or xn.size == 2: + if xn.size == 2: + X = xn[0], xn[1] + if xn[0] > xn[1]: + _ref_lon = X[0] - (X[0] - X[1]) / 3 + else: + X = _np.min(xn), _np.max(xn) + if X is not None: + X = _np.array(X) + return X, _np.round(_ref_lon, 2) def spherical2cartesian(Y, X, R=None): From cea1845b13d66b64d8d2ca667c065eb7f693c4c2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 30 May 2023 21:25:35 -0400 Subject: [PATCH 17/32] Bump mamba-org/provision-with-micromamba from 15 to 16 (#367) Bumps [mamba-org/provision-with-micromamba](https://github.com/mamba-org/provision-with-micromamba) from 15 to 16. - [Release notes](https://github.com/mamba-org/provision-with-micromamba/releases) - [Commits](https://github.com/mamba-org/provision-with-micromamba/compare/v15...v16) --- updated-dependencies: - dependency-name: mamba-org/provision-with-micromamba dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/ci.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 593d0147..cac2a684 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -31,7 +31,7 @@ jobs: - uses: actions/checkout@v3 - name: Install Conda environment with Micromamba - uses: mamba-org/provision-with-micromamba@v15 + uses: mamba-org/provision-with-micromamba@v16 with: environment-file: ci/environment.yml environment-name: oceanspy_test From c9ba7bc26c6eb22fa56752e88209286f16d55963 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Thu, 6 Jul 2023 09:21:17 -0400 Subject: [PATCH 18/32] new Station sampleMethod (#377) * allow multiple points * fix bug * new samp method * formatting * format * persist+compute data extraction * unpersist * format * comment * restore * fix bug * fix bug * rename args to coincide with python `slice` * reformat * isort * include slicing in test * format * format * only data vars * fix unref dataarray * format * fix format * formatting * set `iface=None` as default argument * squeeze dimensions of len=0 * explicit rotated facets * format * format * format * final fix * fix bug * more fixes * format * pin down scipy --------- Co-authored-by: Miguel Jimenez --- ci/environment.yml | 1 + oceanspy/llc_rearrange.py | 252 ++++++++++++++++++++++- oceanspy/plot.py | 27 +++ oceanspy/subsample.py | 341 +++++++++++++++++++++++++------ oceanspy/tests/test_plot.py | 9 +- oceanspy/tests/test_subsample.py | 77 +++++++ oceanspy/utils.py | 14 +- 7 files changed, 652 insertions(+), 69 deletions(-) diff --git a/ci/environment.yml b/ci/environment.yml index 4bf29255..a565fa17 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -9,6 +9,7 @@ dependencies: - xarray - xoak - cartopy +- scipy < 1.11 - intake-xarray - geopy - xesmf > 0.6.3 diff --git a/oceanspy/llc_rearrange.py b/oceanspy/llc_rearrange.py index 75f7408c..b2b955c1 100644 --- a/oceanspy/llc_rearrange.py +++ b/oceanspy/llc_rearrange.py @@ -892,8 +892,6 @@ def flip_v(_ds, co_list=metrics, dims=True, _len=3): _ds[_varName] = -_ds[_varName] elif _varName == "SN": _ds[_varName] = -_ds[_varName] - # elif _varName == "CS": - # _ds[_varName] = -_ds[_varName] return _ds @@ -1232,6 +1230,256 @@ def llc_local_to_lat_lon(ds, co_list=metrics): return _ds +def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): + """ + Evaluates a dataset + at arctic face. _ix and _iy are vectors of index points, associated with + different locations around the face=6. + """ + + _ds = mates(_ds) + + y = DataArray( + _np.arange(1), + dims=("y"), + attrs={"long_name": "j-index of cell center", "units": "none"}, + ) + x = DataArray( + _np.arange(1), + dims=("x"), + attrs={"long_name": "i-index of cell center", "units": "none"}, + ) + yp1 = DataArray( + _np.arange(2), + dims=("yp1"), + attrs={"long_name": "j-index of cell corner", "units": "none"}, + ) + xp1 = DataArray( + _np.arange(2), + dims=("xp1"), + attrs={"long_name": "i-index of cell corner", "units": "none"}, + ) + + _XC = _ds["XC"].isel(face=6) + XR5 = _np.min(_XC.isel(Y=0, X=0).values), _np.max(_XC.isel(Y=0, X=-1).values) + XR2 = _np.min(_XC.isel(X=0, Y=-1).values), _np.max(_XC.isel(X=0, Y=0).values) + XR7 = _np.min(_XC.isel(X=-1, Y=0).values), _np.max(_XC.isel(X=-1, Y=-1).values) + XR10 = _np.min(_XC.isel(X=-1, Y=-1).values), _np.max(_XC.isel(X=0, Y=-1).values) + DS = [] + co_list = [var for var in _ds.coords] + + for i in range(len(_ix)): + _ix0, _iy0 = _np.array([_ix[i]]), _np.array([_iy[i]]) + p = _XC.isel(X=_ix[i], Y=_iy[i]).values + if p > XR2[0] and p < XR2[-1]: + new_dim = DataArray( + _np.arange(len(_ix0)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy0, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix0, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy0, _iy0 + 1)[::-1], 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + iXp1 = DataArray( + _np.stack((_ix0, _ix0 + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + "face": 6, + } + rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + new_ds = rotate_vars(new_ds) + + for _varName in new_ds.variables: + if "mate" in new_ds[_varName].attrs: + _dims = new_ds[_varName].dims + if _varName not in co_list and "Xp1" in _dims: + new_ds[_varName] = -new_ds[_varName] + if _varName == "SN": + new_ds[_varName] = -new_ds[_varName] + + elif p > XR5[0] and p < XR5[-1]: + new_dim = DataArray( + _np.arange(len(_ix0)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy0, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix0, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy0, _iy0 + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + iXp1 = DataArray( + _np.stack((_ix0, _ix0 + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + "face": 6, + } + rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} + + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + + elif p > XR7[0] or p < XR7[-1]: + new_dim = DataArray( + _np.arange(len(_ix0)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy0, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix0, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy0, _iy0 + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix0, _ix0 + 1)[::-1], 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + "face": 6, + } + rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + new_ds = rotate_vars(new_ds) + + for _varName in new_ds.variables: + if "mate" in new_ds[_varName].attrs: + _dims = new_ds[_varName].dims + if _varName not in co_list and "Yp1" in _dims: + new_ds[_varName] = -new_ds[_varName] + if _varName == "CS": + new_ds[_varName] = -new_ds[_varName] + + elif p > XR10[0] and p < XR10[-1]: + new_dim = DataArray( + _np.arange(len(_ix0)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy0, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix0, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy0, _iy0 + 1)[::-1], 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix0, _ix0 + 1)[::-1], 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + "face": 6, + } + rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} + + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + + for _varName in new_ds.variables: + if "mate" in new_ds[_varName].attrs: + _dims = new_ds[_varName].dims + if _varName not in co_list and ("Yp1" in _dims or "Xp1" in _dims): + new_ds[_varName] = -new_ds[_varName] + if _varName == "SN": + new_ds[_varName] = -new_ds[_varName] + if _varName == "CS": + new_ds[_varName] = -new_ds[_varName] + + DS.append(new_ds) + dsf = DS[0].reset_coords() + if len(DS) > 1: + for i in range(1, len(DS)): + nmds = reset_dim(DS[i], i, dim="station") + dsf = dsf.combine_first(nmds.reset_coords()) + return dsf.set_coords(co_list) + + +def reset_dim(_ds, N, dim="mooring"): + """resets the dimension mooring by shifting it by a value set by N""" + _ds["n" + dim] = N + _ds[dim] + _ds = _ds.swap_dims({dim: "n" + dim}).drop_vars(dim).rename({"n" + dim: dim}) + + return _ds + + class Dims: """Creates a shortcut for dimension`s names associated with an arbitrary variable.""" diff --git a/oceanspy/plot.py b/oceanspy/plot.py index f9eb19d2..787b65b3 100644 --- a/oceanspy/plot.py +++ b/oceanspy/plot.py @@ -32,6 +32,7 @@ from .compute import _add_missing_variables from .compute import integral as _integral from .compute import weighted_mean as _weighted_mean +from .llc_rearrange import Dims # Additional dependencies (private) try: @@ -651,6 +652,20 @@ def horizontal_section( col_wrap = kwargs.pop("col_wrap", None) subplot_kws = kwargs.pop("subplot_kws", None) transform = kwargs.pop("transform", None) + xstep, ystep = kwargs.pop("xstep", None), kwargs.pop("ystep", None) + + DIMS = [dim for dim in da.dims if dim[0] in ["X", "Y"]] + dims_var = Dims(DIMS[::-1]) + + if xstep is not None and ystep is not None: + xslice = slice(0, len(da[dims_var.X]), xstep) + yslice = slice(0, len(da[dims_var.Y]), ystep) + else: + xslice = slice(0, len(da[dims_var.X])) + yslice = slice(0, len(da[dims_var.Y])) + + sargs = {dims_var.X: xslice, dims_var.Y: yslice} + da = da.isel(**sargs) # Projection if ax is None: @@ -937,6 +952,18 @@ def vertical_section( ver_name = [dim for dim in od.grid_coords["Z"] if dim in da.dims][0] da = da.squeeze() + # slicing along section + step = kwargs.pop("step", None) + DIMS = [dim for dim in da.dims] + dims_var = Dims(DIMS[::-1]) + if step is not None and dims_var.X in ["mooring", "station"]: + xslice = slice(0, len(da[dims_var.X]), step) + else: + xslice = slice(0, len(da[dims_var.X])) + + sargs = {dims_var.X: xslice} + da = da.isel(**sargs) + # CONTOURNAME if contourName is not None: # Apply mean and sum diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index 032593f8..95a5290c 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -35,6 +35,7 @@ _rename_aliased, ) from .llc_rearrange import LLCtransformation as _llc_trans +from .llc_rearrange import arctic_eval, reset_dim, rotate_vars from .utils import _rel_lon, _reset_range, circle_path_array, get_maskH # Recommended dependencies (private) @@ -782,64 +783,9 @@ def remove_repeated(_iX, _iY): # attempt to remove repeated (but not adjacent) coord values ix, iy = remove_repeated(ix, iy) - mooring = DataArray( - _np.arange(len(ix)), - dims=("mooring"), - attrs={"long_name": "index of mooring", "units": "none"}, - ) - y = DataArray( - _np.arange(1), - dims=("y"), - attrs={"long_name": "j-index of cell center", "units": "none"}, - ) - x = DataArray( - _np.arange(1), - dims=("x"), - attrs={"long_name": "i-index of cell corner", "units": "none"}, - ) - yp1 = DataArray( - _np.arange(2), - dims=("yp1"), - attrs={"long_name": "j-index of cell center", "units": "none"}, - ) - xp1 = DataArray( - _np.arange(2), - dims=("xp1"), - attrs={"long_name": "i-index of cell corner", "units": "none"}, - ) + new_ds = eval_dataset(ds, ix, iy) - # Transform indexes in DataArray - iY = DataArray( - _np.reshape(iy, (len(mooring), len(y))), - coords={"mooring": mooring, "y": y}, - dims=("mooring", "y"), - ) - iX = DataArray( - _np.reshape(ix, (len(mooring), len(x))), - coords={"mooring": mooring, "x": x}, - dims=("mooring", "x"), - ) - iYp1 = DataArray( - _np.stack((iy, iy + 1), 1), - coords={"mooring": mooring, "yp1": yp1}, - dims=("mooring", "yp1"), - ) - iXp1 = DataArray( - _np.stack((ix, ix + 1), 1), - coords={"mooring": mooring, "xp1": xp1}, - dims=("mooring", "xp1"), - ) - - args = { - "X": iX, - "Y": iY, - "Xp1": iXp1, - "Yp1": iYp1, - } - - rename = {"x": "X", "y": "Y", "yp1": "Yp1", "xp1": "Xp1"} - new_ds = ds.isel(**args).drop_vars(["X", "Y", "Xp1", "Yp1"]) - new_ds = new_ds.rename_dims(rename).rename_vars(rename) + mooring = new_ds.mooring near_Y = new_ds["YC"].compute().data.squeeze() near_X = new_ds["XC"].compute().data.squeeze() @@ -1130,6 +1076,176 @@ def survey_stations( return od +def stations( + od, + varList=None, + tcoords=None, + Zcoords=None, + Ycoords=None, + Xcoords=None, + xoak_index="scipy_kdtree", + method="nearest", +): + """ + Extract stations using nearest-neighbor lookup. + + Parameters + ---------- + od: OceanDataset + od that will be subsampled. + tcoords: 1D array_like, NoneType + time-coordinates (datetime). + Zcoords: 1D array_like, NoneType + Z coordinates at center point + Ycoords: 1D array_like, NoneType + Latitude coordinates of locations at center point. + Xcoords: 1D array_like, NoneType + lon coordinates of locations at center point. + xoak_index: str + xoak index to be used. `scipy_kdtree` by default. + + Returns + ------- + od: OceanDataset + Subsampled oceandataset. + + See Also + -------- + oceanspy.OceanDataset.mooring + + """ + _check_native_grid(od, "stations") + + # Convert variables to numpy arrays and make some check + tcoords = _check_range(od, tcoords, "timeRange") + Zcoords = _check_range(od, Zcoords, "Zcoords") + Ycoords = _check_range(od, Ycoords, "Ycoords") + Xcoords = _check_range(od, Xcoords, "Xcoords") + + # Message + print("Extracting stations.") + + # Unpack ds + od = _copy.copy(od) + ds = od._ds + + if varList is not None: + nvarlist = [var for var in ds.data_vars if var not in varList] + ds = ds.drop_vars(nvarlist) + + # look up nearest neighbors in Z and time dims + Zlist = ["Zl", "Z", "Zp1", "Zu"] + tlist = ["time", "time_midp"] + dimlist, Coords = [], [] + if Zcoords is not None: + dimlist.append(Zlist) + Coords.append(Zcoords) + if tcoords is not None: + dimlist.append(tlist) + Coords.append(tcoords) + + for i in range(len(dimlist)): + List = [k for k in dimlist[i] if k in ds.dims] + args = {} + for item in List: + if len(ds[item]) > 0: + args[item] = Coords[i] + ds = ds.sel(**args, method="nearest") + + # create list of coordinates. + co_list = [var for var in ds.coords if var not in ["face"]] + + if Xcoords is None and Ycoords is None: + DS = ds + + if Xcoords is not None and Ycoords is not None: + if not ds.xoak.index: + if xoak_index not in _xoak.IndexRegistry(): + raise ValueError( + "`xoak_index` [{}] is not supported." + "\nAvailable options: {}" + "".format(xoak_index, _xoak.IndexRegistry()) + ) + + ds.xoak.set_index(["XC", "YC"], xoak_index) + + cdata = {"XC": ("station", Xcoords), "YC": ("station", Ycoords)} + ds_data = _xr.Dataset(cdata) + + # find nearest points to given data. + nds = ds.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) + + if "face" not in ds.dims: + iX, iY = (nds[f"{i}"].data for i in ("X", "Y")) + DS = eval_dataset(ds, iX, iY, _dim_name="station") + DS = DS.squeeze() + + if "face" in ds.dims: + iX, iY, iface = (nds[f"{i}"].data for i in ("X", "Y", "face")) + + _dat = nds.face.values + ll = _np.where(abs(_np.diff(_dat)))[0] + order_iface = [_dat[i] for i in ll] + [_dat[-1]] + Niter = len(order_iface) + + if Niter == 1: + X0, Y0 = iX, iY + DS = eval_dataset(ds, X0, Y0, order_iface, "station") + DS = DS.squeeze() + + else: + # split indexes along each face + X0, Y0 = [], [] + for ii in range(len(ll) + 1): + if ii == 0: + x0, y0 = iX[: ll[ii] + 1], iY[: ll[ii] + 1] + elif ii > 0 and ii < len(ll): + x0, y0 = ( + iX[ll[ii - 1] + 1 : ll[ii] + 1], + iY[ll[ii - 1] + 1 : ll[ii] + 1], + ) + elif ii == len(ll): + x0, y0 = iX[ll[ii - 1] + 1 :], iY[ll[ii - 1] + 1 :] + X0.append(x0) + Y0.append(y0) + + DS = [] + for i in range(Niter): + DS.append(eval_dataset(ds, X0[i], Y0[i], order_iface[i], "station")) + + _dim = "station" + nDS = [DS[0].reset_coords()] + for i in range(1, len(DS)): + Nend = nDS[i - 1][_dim].values[-1] + nDS.append(reset_dim(DS[i], Nend + 1, dim=_dim).reset_coords()) + + DS = nDS[0] + for i in range(1, len(nDS)): + DS = DS.combine_first(nDS[i]) + + DS = DS.set_coords(co_list) + + if Xcoords is None and Ycoords is None: + od._ds = DS + + if Xcoords is not None and Ycoords is not None: + if "face" in DS.variables: + DS = DS.drop_vars(["face"]) + + od._ds = DS + + if od.face_connections is not None: + new_face_connections = {"face_connections": {None: {None, None}}} + od = od.set_face_connections(**new_face_connections) + + grid_coords = od.grid_coords + grid_coords.pop("X", None) + grid_coords.pop("Y", None) + od = od.set_grid_coords(grid_coords, overwrite=True) + + return od + + def particle_properties(od, times, Ypart, Xpart, Zpart, **kwargs): """ Extract Eulerian properties of particles @@ -1307,6 +1423,113 @@ def particle_properties(od, times, Ypart, Xpart, Zpart, **kwargs): return od +def eval_dataset(_ds, _ix, _iy, _iface=None, _dim_name="mooring"): + """ + Evaluates a dataset along (spatial) trajectory in the plane as defined by the + indexes in the plane. As a result, there is a new dimension/coordinate, hence + reducing the dimension of the original dataset. + + Parameters: + ---------- + _ds: xarray.Dataset + contains all x, y coordinates (but may be subsampled in Z or time) + _ix, _iy: 1D array, int + index values identifying the location in X Y (lat, lon) space + _iface: int, None (bool) + None (default) implies no complex topology in the dataset. Otherwise, + _iface indicates the face index which, along which the provided ix, iy, + identify the spatial (geo) coordinate location in lat/lon space. + _dim_name: str + names the new dimension along the pathway. By default this is 'mooring', + but can also be 'station' (when discrete, argo-like isolated coordinates). + + Returns: + xarray.Dataset + + """ + + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + y = DataArray( + _np.arange(1), + dims=("y"), + attrs={"long_name": "j-index of cell center", "units": "none"}, + ) + x = DataArray( + _np.arange(1), + dims=("x"), + attrs={"long_name": "i-index of cell center", "units": "none"}, + ) + yp1 = DataArray( + _np.arange(2), + dims=("yp1"), + attrs={"long_name": "j-index of cell corner", "units": "none"}, + ) + xp1 = DataArray( + _np.arange(2), + dims=("xp1"), + attrs={"long_name": "i-index of cell corner", "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + if _iface is not None: + if _iface == [6]: + return arctic_eval(_ds, _ix, _iy, _dim_name) + elif _iface in _np.arange(7, 13): + iXp1 = DataArray( + _np.stack((_ix + 1, _ix), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + } + + rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} + + if _iface is not None: + args = {"face": _iface, **args} + if _iface in _np.arange(7, 13): + rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} + + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + if _iface is not None and _iface in _np.arange(7, 13): + new_ds = rotate_vars(new_ds) + + return new_ds + + class _subsampleMethods(object): """ Enables use of functions as OceanDataset attributes. @@ -1327,6 +1550,10 @@ def mooring_array(self, **kwargs): def survey_stations(self, **kwargs): return survey_stations(self._od, **kwargs) + @_functools.wraps(stations) + def stations(self, **kwargs): + return stations(self._od, **kwargs) + @_functools.wraps(particle_properties) def particle_properties(self, **kwargs): return particle_properties(self._od, **kwargs) diff --git a/oceanspy/tests/test_plot.py b/oceanspy/tests/test_plot.py index ba85a319..f4e87ced 100644 --- a/oceanspy/tests/test_plot.py +++ b/oceanspy/tests/test_plot.py @@ -231,7 +231,8 @@ def test_hor_sec_warn(od_in): @pytest.mark.parametrize("od_in", [od]) @pytest.mark.parametrize("varName", ["Temp", "U", "V", "momVort3"]) @pytest.mark.parametrize("contourName", ["Depth", "U", "V", "momVort3"]) -def test_hor_sec(od_in, varName, contourName): +@pytest.mark.parametrize("step", [None, 2]) +def test_hor_sec(od_in, varName, contourName, step): plt.close() cutout_kwargs = { "timeRange": [od_in.dataset["time"][0].values, od_in.dataset["time"][-1].values] @@ -250,6 +251,8 @@ def test_hor_sec(od_in, varName, contourName): contour_kwargs=contour_kwargs, clabel_kwargs=clabel_kwargs, cutout_kwargs=cutout_kwargs, + xstep=step, + ystep=step, ) assert isinstance(ax, plt.Axes) @@ -328,7 +331,8 @@ def test_ver_sec_subsamp(od_in, subsampMethod): @pytest.mark.parametrize("od_in", [od_moor, od_surv]) @pytest.mark.parametrize("varName", ["Temp", "U", "V", "W", "momVort3"]) @pytest.mark.parametrize("contourName", ["Temp", "U", "V", "W", "momVort3"]) -def test_ver_sec(od_in, varName, contourName): +@pytest.mark.parametrize("step", [None, 2]) +def test_ver_sec(od_in, varName, contourName, step): plt.close() if "mooring_dist" in od_in.dataset.variables: ds = od_in.dataset.drop_vars("mooring_dist") @@ -351,6 +355,7 @@ def test_ver_sec(od_in, varName, contourName): intAxes=intAxes, contour_kwargs=contour_kwargs, clabel_kwargs=clabel_kwargs, + step=step, ) assert isinstance(ax, plt.Axes) diff --git a/oceanspy/tests/test_subsample.py b/oceanspy/tests/test_subsample.py index c8b91b77..09df0869 100644 --- a/oceanspy/tests/test_subsample.py +++ b/oceanspy/tests/test_subsample.py @@ -1,4 +1,6 @@ # TODO: cartesian, and Xp1 Yp1 right are not tested. +import copy as _copy + import numpy as np import pytest import xarray as xr @@ -6,6 +8,7 @@ # From OceanSpy from oceanspy import OceanDataset, open_oceandataset +from oceanspy.llc_rearrange import mates # Directory Datadir = "./oceanspy/tests/Data/" @@ -424,6 +427,80 @@ def test_survey(od, cartesian, delta, kwargs): new_od.grid +# ======== +# STATIONS +# ======== +# create cyclonic vel +nU = _copy.deepcopy(ECCOod._ds["CS"].values) +nV = -_copy.deepcopy(ECCOod._ds["SN"].values) +Ucoords = { + "face": ECCOod._ds.face.values, + "Y": ECCOod._ds.Y.values, + "Xp1": ECCOod._ds.Xp1.values, +} +Vcoords = { + "face": ECCOod._ds.face.values, + "Yp1": ECCOod._ds.Yp1.values, + "X": ECCOod._ds.X.values, +} +ECCOod._ds["UVELMASS"] = xr.DataArray(nU, coords=Ucoords, dims=["face", "Y", "Xp1"]) +ECCOod._ds["VVELMASS"] = xr.DataArray(nV, coords=Vcoords, dims=["face", "Yp1", "X"]) + +ECCOod._ds = mates(ECCOod._ds) + +# coordinate locations +lons76N = np.array([6.2, 97.8, -172.21623, -83.78377]) +lats76N = 76 * np.ones(np.shape(lons76N)) + +lats_6E = np.array([60.131752, 65.39574, 70.104706, 74.43877, 78.69695, 82.68835]) +lons6E = 6 * np.ones(np.shape(lats_6E)) + +lons90W = -87.5 * np.ones(np.shape(lats_6E)) + +lons170W = -170 * np.ones(np.shape(lats_6E)) + + +@pytest.mark.parametrize("this_od", [ECCOod]) +@pytest.mark.parametrize( + "args", + [ + {"Ycoords": None, "Xcoords": None}, + {"Ycoords": lats76N, "Xcoords": lons76N}, + {"Ycoords": lats_6E, "Xcoords": lons6E}, + {"Ycoords": lats_6E, "Xcoords": lons90W}, + {"Ycoords": lats_6E, "Xcoords": lons170W}, + ], +) +def test_stations(this_od, args): + od_stns = this_od.subsample.stations(**args) + + if args["Ycoords"] is None or args["Xcoords"] is None: + assert this_od._ds.XC.shape == od_stns._ds.XC.shape + assert this_od._ds.YC.shape == od_stns._ds.YC.shape + else: + YC, XC = args["Ycoords"], args["Xcoords"] + XCstn, YCstn = od_stns._ds.XC, od_stns._ds.YC + XGstn, YGstn = od_stns._ds.XG, od_stns._ds.YG + stations = od_stns._ds.station.values + argsu0, argsu1 = {"Xp1": 0}, {"Xp1": 1} + argsv0, argsv1 = {"Yp1": 0}, {"Yp1": 1} + assert len(stations) == len(XC) == len(YC) + for i in range(len(stations)): + assert XGstn.isel(station=i, Xp1=0, Yp1=0).values < XCstn.isel(station=i) + assert XGstn.isel(station=i, Xp1=1, Yp1=0).values > XCstn.isel(station=i) + assert YGstn.isel(station=i, Xp1=0, Yp1=0).values < YCstn.isel(station=i) + assert YGstn.isel(station=i, Xp1=0, Yp1=1).values > YCstn.isel(station=i) + + Uval0 = od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu0}).values + Uval1 = od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu1}).values + Vval0 = od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv0}).values + Vval1 = od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv1}).values + + assert np.round(abs(Uval0), 1) == np.round(abs(Uval1), 1) == 1 + assert np.round(abs(Vval0), 1) <= 0.1 + assert np.round(abs(Vval1), 1) <= 0.1 + + # ========= # PARTICLES # ========= diff --git a/oceanspy/utils.py b/oceanspy/utils.py index 2b5b8a77..2d52d0fb 100644 --- a/oceanspy/utils.py +++ b/oceanspy/utils.py @@ -70,20 +70,18 @@ def viewer_to_range(p): if p_type == "Polygon": coords = p[0]["coordinates"][0] elif p_type == "Point": - coords = p[0]["coordinates"] + coords = [] + for i in range(len(p)): + coords.append(p[i]["coordinates"]) elif p_type == "LineString": coords = p[0]["coordinates"] lon = [] lat = [] - if p_type == "Point": - lon.append(coords[0]) - lat.append(coords[1]) - else: - for i in range(len(coords)): - lon.append(coords[i][0]) - lat.append(coords[i][1]) + for i in range(len(coords)): + lon.append(coords[i][0]) + lat.append(coords[i][1]) # check that there are no lon values greater than 180 (abs) ll = _np.where(abs(_np.array(lon)) > 180)[0] From fb1e713b4b9834e0a7eb8b13a101cfd90eafead3 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Sat, 5 Aug 2023 22:16:11 -0400 Subject: [PATCH 19/32] Pre commit (#385) * new updated pre-commit * re-format * re format * format --- .pre-commit-config.yaml | 6 +-- oceanspy/_oceandataset.py | 2 +- oceanspy/llc_rearrange.py | 56 ++++++++++++------------ oceanspy/tests/test_llc_rearrange.py | 14 +++--- oceanspy/tests/test_open_oceandataset.py | 2 +- oceanspy/tests/test_utils.py | 4 +- oceanspy/utils.py | 2 +- 7 files changed, 43 insertions(+), 43 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 9ed2726a..3e1625f3 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -14,7 +14,7 @@ repos: - id: debug-statements - id: mixed-line-ending - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks - rev: v2.9.0 + rev: v2.10.0 hooks: - id: pretty-format-yaml args: [--autofix, --preserve-quotes] @@ -25,11 +25,11 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.3.0 + rev: 23.7.0 hooks: - id: black - repo: https://github.com/PyCQA/flake8 - rev: 6.0.0 + rev: 6.1.0 hooks: - id: flake8 - repo: https://github.com/nbQA-dev/nbQA diff --git a/oceanspy/_oceandataset.py b/oceanspy/_oceandataset.py index 85bca7fa..3e218266 100644 --- a/oceanspy/_oceandataset.py +++ b/oceanspy/_oceandataset.py @@ -628,7 +628,7 @@ def set_face_connections(self, face_connections): if list(face_connections)[0] == "face": for k in face_connections["face"].keys(): for axis in face_connections["face"][k].keys(): - if type(face_connections["face"][k][axis]) == tuple: + if isinstance(face_connections["face"][k][axis], tuple): face_connections["face"][k][axis] = face_connections["face"][k][ axis ] diff --git a/oceanspy/llc_rearrange.py b/oceanspy/llc_rearrange.py index b2b955c1..6743213d 100644 --- a/oceanspy/llc_rearrange.py +++ b/oceanspy/llc_rearrange.py @@ -229,17 +229,17 @@ def arctic_crown( ARCT[3].append(ds[var_name]) for i in range(len(ARCT)): - if all(type(item) != int for item in ARCT[i]): + if all(not isinstance(item, int) for item in ARCT[i]): ARCT[i] = _xr.merge(ARCT[i]) DSa2, DSa5, DSa7, DSa10 = ARCT - if type(DSa2) != Dataset: + if not isinstance(DSa2, Dataset): DSa2 = 0 - if type(DSa5) != Dataset: + if not isinstance(DSa5, Dataset): DSa5 = 0 - if type(DSa7) != Dataset: + if not isinstance(DSa7, Dataset): DSa7 = 0 - if type(DSa10) != Dataset: + if not isinstance(DSa10, Dataset): DSa10 = 0 DSa7 = shift_dataset(DSa7, dims_c.X, dims_g.X) @@ -308,11 +308,11 @@ def arctic_crown( # Here, address shifts in Arctic # arctic exchange with face 10 - if type(faces2[0]) == Dataset: + if isinstance(faces2[0], Dataset): faces2[0]["Yp1"] = faces2[0]["Yp1"] + 1 # Arctic exchange with face 2 - if type(faces3[3]) == Dataset: + if isinstance(faces3[3], Dataset): faces3[3]["Xp1"] = faces3[3]["Xp1"] + 1 # ===== @@ -370,7 +370,7 @@ def arctic_crown( if centered is None: # estimates the centering based on cutout centered = "Atlantic" # default, below scenarios to change this - if type(DSFacet3) == int: + if isinstance(DSFacet3, int): centered = "Pacific" # ===== @@ -380,8 +380,8 @@ def arctic_crown( # First, check if there is data in both DSFacet12 and DSFacet34. # If not, then there is no need to transpose data in DSFacet12. - if type(DSFacet12) == Dataset: - if type(DSFacet34) == Dataset: + if isinstance(DSFacet12, Dataset): + if isinstance(DSFacet34, Dataset): # two lines below asserts correct # staggering of center and corner points # in latitude (otherwise, lat has a jump) @@ -417,7 +417,7 @@ def arctic_crown( DS = shift_dataset(DS, dims_c.X, dims_g.X) DS = shift_dataset(DS, dims_c.Y, dims_g.Y) - if type(DSFacet34) == int: + if isinstance(DSFacet34, int): DS = _reorder_ds(DS, dims_c, dims_g).persist() DS = _LLC_check_sizes(DS) @@ -684,7 +684,7 @@ def rotate_vars(_ds): topology makes it so that u on a rotated face transforms to `+- v` on a lat lon grid. """ - if type(_ds) == Dataset: # if a dataset transform otherwise pass + if isinstance(_ds, Dataset): # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) _vars = [var for var in _ds.variables] rot_names = {} @@ -712,7 +712,7 @@ def shift_dataset(_ds, dims_c, dims_g): dims_c. """ - if type(_ds) == Dataset: # if a dataset transform otherwise pass + if isinstance(_ds, Dataset): # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) for _dim in [dims_c, dims_g]: if int(_ds[_dim][0].data) < int(_ds[_dim][1].data): @@ -733,7 +733,7 @@ def reverse_dataset(_ds, dims_c, dims_g, transpose=False): so dims_c is either one of `i` or `j`, and dims_g is either one of `i_g` or `j_g`. The pair most correspond to the same dimension.""" - if type(_ds) == Dataset: # if a dataset transform otherwise pass + if isinstance(_ds, Dataset): # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) for _dim in [dims_c, dims_g]: # This part should be different for j_g points? @@ -767,7 +767,7 @@ def rotate_dataset( nface=int: correct number to use. This is the case a merger/concatenated dataset is being manipulated. Nij is no longer the size of the face. """ - if type(_ds) == Dataset: # if a dataset transform otherwise pass + if isinstance(_ds, Dataset): # if a dataset transform otherwise pass _ds = _copy.deepcopy(_ds) Nij = max(len(_ds[dims_c.X]), len(_ds[dims_c.Y])) @@ -823,12 +823,12 @@ def shift_list_ds(_DS, dims_c, dims_g, Ni, facet=1): if len(_DS) > 1: dim0 = 0 for ii in range(1, len(_DS)): - if type(_DS[ii - 1]) == int: + if isinstance(_DS[ii - 1], int): dim0 = int(Ni * sum(facs[:ii])) else: for _dim in [dims_c, dims_g]: dim0 = int(_DS[ii - 1][_dim][-1].data + 1) - if type(_DS[ii]) == Dataset: + if isinstance(_DS[ii], Dataset): for _dim in [dims_c, dims_g]: _DS[ii]["n" + _dim] = ( _DS[ii][_dim] - (fac * int(_DS[ii][_dim][0].data)) + dim0 @@ -841,7 +841,7 @@ def shift_list_ds(_DS, dims_c, dims_g, Ni, facet=1): ) DS = [] for lll in range(len(_DS)): - if type(_DS[lll]) == Dataset: + if isinstance(_DS[lll], Dataset): DS.append(_DS[lll]) else: DS = _DS @@ -858,9 +858,9 @@ def combine_list_ds(_DSlist): elif len(_DSlist) == 1: # a single face _DSFacet = _DSlist[0] elif len(_DSlist) == 2: - if type(_DSlist[0]) == int: # one is empty, pass directly + if isinstance(_DSlist[0], int): # one is empty, pass directly _DSFacet = _DSlist[1] - elif type(_DSlist[1]) == int: # the other is empty pass directly + elif isinstance(_DSlist[1], int): # the other is empty pass directly _DSFacet = _DSlist[0] else: # if there are two datasets then combine with dask.config.set(**{"array.slicing.split_large_chunks": False}): @@ -882,7 +882,7 @@ def flip_v(_ds, co_list=metrics, dims=True, _len=3): dims is given """ - if type(_ds) == Dataset: + if isinstance(_ds, Dataset): for _varName in _ds.variables: if dims: DIMS = [dim for dim in _ds[_varName].dims if dim != "face"] @@ -987,12 +987,12 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): ARCT[3].append(DS[3]) for i in range(len(ARCT)): # Not all faces survive the cutout - if type(ARCT[i][0]) == DataArray: + if isinstance(ARCT[i][0], DataArray): ARCT[i] = _xr.merge(ARCT[i]) DSa2, DSa5, DSa7, DSa10 = ARCT - if type(DSa2) != Dataset: + if not isinstance(DSa2, Dataset): DSa2 = 0 [Xi_2, Xf_2] = [0, 0] else: @@ -1001,7 +1001,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): else: Xf_2 = _edge_arc_data(DSa2[_var], 2, _dims) Xi_2 = int(DSa2[_var][_dims.X][0]) - if type(DSa5) != Dataset: + if not isinstance(DSa5, Dataset): DSa5 = 0 [Yi_5, Yf_5] = [0, 0] else: @@ -1010,7 +1010,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): else: Yf_5 = _edge_arc_data(DSa5[_var], 5, _dims) Yi_5 = int(DSa5[_var][_dims.Y][0]) - if type(DSa7) != Dataset: + if not isinstance(DSa7, Dataset): DSa7 = 0 [Xi_7, Xf_7] = [0, 0] else: @@ -1020,7 +1020,7 @@ def arc_limits_mask(_ds, _var, _faces, _dims, XRange, YRange): Xi_7 = _edge_arc_data(DSa7[_var], 7, _dims) Xf_7 = int(DSa7[_var][_dims.X][-1]) - if type(DSa10) != Dataset: + if not isinstance(DSa10, Dataset): DSa10 = 0 [Yi_10, Yf_10] = [0, 0] else: @@ -1050,7 +1050,7 @@ def _edge_facet_data(_Facet_list, _var, _dims, _axis): XRange = [] for i in range(len(_Facet_list)): - if type(_Facet_list[i]) == Dataset: + if isinstance(_Facet_list[i], Dataset): # there is data _da = _Facet_list[i][_var].load() # load into memory 2d data. X0 = [] @@ -1085,7 +1085,7 @@ def slice_datasets(_DSfacet, dims_c, dims_g, _edges, _axis): _DSFacet = _copy.deepcopy(_DSfacet) for i in range(len(_DSFacet)): # print(i) - if type(_DSFacet[i]) == Dataset: + if isinstance(_DSFacet[i], Dataset): for _dim in [_dim_c, _dim_g]: if len(_edges) == 1: ii_0 = int(_edges[0]) diff --git a/oceanspy/tests/test_llc_rearrange.py b/oceanspy/tests/test_llc_rearrange.py index 8d32b99a..8858ec7b 100644 --- a/oceanspy/tests/test_llc_rearrange.py +++ b/oceanspy/tests/test_llc_rearrange.py @@ -2239,12 +2239,12 @@ def test_arc_connect( ds, "YG", faces=faces, masking=masking, opt=opt, ranges=cuts ) for i in range(len(DS)): - if type(DS[i]) == _datype: + if isinstance(DS[i], _datype): assert _np.shape(DS[i]) == size else: arc_faces, *a, DS = arct_connect(ds, "YG", faces) assert arc_faces == expected - assert type(DS[0]) == atype + assert isinstance(DS[0], atype) varList = ["T", "U", "V", "XG", "YG", "XC", "YC"] @@ -2370,7 +2370,7 @@ def test_transformation(od, faces, varList, XRange, YRange, X0, X1, Y0, Y1): ARCT[2].append(DS[2]) ARCT[3].append(DS[3]) for i in range(len(ARCT)): # Not all faces survive the cutout - if type(ARCT[i][0]) == _datype: + if isinstance(ARCT[i][0], _datype): ARCT[i] = _xr.merge(ARCT[i]) ds2, ds5, ds7, ds10 = ARCT @@ -2406,7 +2406,7 @@ def test_shift_dataset(ds, dimc, dimg, init_c, final_c, init_g, final_g): ) def test_rotate_dataset(ds, var, dimc, dimg, rot_dims): nds = rotate_dataset(ds, dimc, dimg) - if type(ds) == _dstype: + if isinstance(ds, _dstype): nvar = nds[var] assert nvar.dims == rot_dims @@ -2437,7 +2437,7 @@ def test_rotate_dataset(ds, var, dimc, dimg, rot_dims): ) def test_rotate_vars(ds, var, dims0, rot_dims): nds = rotate_vars(ds) - if type(ds) == _dstype: + if isinstance(ds, _dstype): nvar = nds[var] assert nvar.dims == rot_dims @@ -2523,7 +2523,7 @@ def test_shift_list_ds(DSlist, dimsc, dimsg, Np, facet, expX): int(nDSlist[0][dimsc][-1].values), ] == expX[0] else: - assert type(nDSlist) == list + assert isinstance(nDSlist, list) list1 = [od.dataset.isel(face=0), od.dataset.isel(face=1), od.dataset.isel(face=2)] @@ -2826,7 +2826,7 @@ def test_edge_arc_data(od, XRange, YRange, F_indx, Nx): ARCT[3].append(DS[3]) for i in range(len(ARCT)): # Not all faces survive the cutout - if type(ARCT[i][0]) == _datype: + if isinstance(ARCT[i][0], _datype): ARCT[i] = _xr.merge(ARCT[i]) face_order = _np.array([2, 5, 7, 10]) diff --git a/oceanspy/tests/test_open_oceandataset.py b/oceanspy/tests/test_open_oceandataset.py index ca5e3dd7..27f5fd8b 100644 --- a/oceanspy/tests/test_open_oceandataset.py +++ b/oceanspy/tests/test_open_oceandataset.py @@ -76,7 +76,7 @@ def test_opening_and_saving(name, catalog_url): ) if name == "LLC": - assert type(od1.face_connections["face"]) == dict + assert isinstance(od1.face_connections["face"], dict) assert set(["face"]).issubset(set(od1.dataset.dims)) # Check shift diff --git a/oceanspy/tests/test_utils.py b/oceanspy/tests/test_utils.py index 8780f6c8..e9c1cf7d 100644 --- a/oceanspy/tests/test_utils.py +++ b/oceanspy/tests/test_utils.py @@ -93,9 +93,9 @@ def test_circle_path_array(lats, lons, symmetry, resolution): ], ) def test_viewer_to_range(coords, types, lon, lat): - if type(coords) == list: + if isinstance(coords, list): p = [{"type": types, "coordinates": list(coords)}] - elif type(coords) == str: + elif isinstance(coords, str): p = coords x, y = viewer_to_range(p) assert x == lon diff --git a/oceanspy/utils.py b/oceanspy/utils.py index 2d52d0fb..9f05f579 100644 --- a/oceanspy/utils.py +++ b/oceanspy/utils.py @@ -49,7 +49,7 @@ def viewer_to_range(p): lat: list. """ - if type(p) == str: + if isinstance(p, str): if p[0] == "[" and p[-1] == "]": p = _ast.literal_eval(p) # turn string into list else: From 4eaa06e4a45827a6defcf614af2224af2564a8c7 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sun, 6 Aug 2023 00:54:08 -0400 Subject: [PATCH 20/32] [pre-commit.ci] pre-commit autoupdate (#381) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/macisamuele/language-formatters-pre-commit-hooks: v2.9.0 → v2.10.0](https://github.com/macisamuele/language-formatters-pre-commit-hooks/compare/v2.9.0...v2.10.0) - [github.com/psf/black: 23.3.0 → 23.7.0](https://github.com/psf/black/compare/23.3.0...23.7.0) - [github.com/PyCQA/flake8: 6.0.0 → 6.1.0](https://github.com/PyCQA/flake8/compare/6.0.0...6.1.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> From 497bd23faf3d39f282ae64c05944b66d199999d8 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Wed, 30 Aug 2023 10:25:34 -0700 Subject: [PATCH 21/32] Iss386 (#387) * format * format * format --- oceanspy/_ospy_utils.py | 16 +++++++++++++++- oceanspy/llc_rearrange.py | 28 ++++++++++------------------ oceanspy/subsample.py | 4 ---- 3 files changed, 25 insertions(+), 23 deletions(-) diff --git a/oceanspy/_ospy_utils.py b/oceanspy/_ospy_utils.py index dbdf323b..71d3946b 100644 --- a/oceanspy/_ospy_utils.py +++ b/oceanspy/_ospy_utils.py @@ -6,6 +6,7 @@ # Import modules (can be public here) import numpy +import xarray as _xr import xgcm @@ -158,12 +159,25 @@ def _check_range(od, obj, objName): ------- obj: Range object """ + + if "face" in od._ds.dims and od._ds.dims["face"] == 13: + cdata = { + "XG": ("XG", numpy.asarray([-180, 180], dtype=od._ds["XG"].dtype)), + "YG": ("YG", numpy.asarray([-90, 90], dtype=od._ds["YG"].dtype)), + "Zp1": od._ds["Zp1"], + "time": od._ds["time"], + } + data = _xr.Dataset(cdata) + else: + data = od._ds + + # main loop if obj is not None: prefs = ["Y", "X", "Z", "time"] coords = ["YG", "XG", "Zp1", "time"] for _, (pref, coord) in enumerate(zip(prefs, coords)): if pref in objName: - valchek = od._ds[coord] + valchek = data[coord] break obj = numpy.asarray(obj, dtype=valchek.dtype) if obj.ndim == 0: diff --git a/oceanspy/llc_rearrange.py b/oceanspy/llc_rearrange.py index 6743213d..023e1618 100644 --- a/oceanspy/llc_rearrange.py +++ b/oceanspy/llc_rearrange.py @@ -67,9 +67,7 @@ def arctic_crown( YRange=None, faces=None, centered=None, - chunks=None, persist=False, - geo_true=False, ): """This transformation splits the arctic cap (face=6) into four triangular regions and combines all faces in a quasi lat-lon grid. The triangular @@ -103,16 +101,9 @@ def arctic_crown( If 'Pacific', the transformed data has a layout in which the Pacific Ocean lies at the center of the domain. This option is only relevant when transforming the entire dataset. - chunks: bool or dict. - If False (default) - chunking is automatic. - If dict, rechunks the dataset according to the spefications of the - dictionary. See `xarray.Dataset.chunk()`. persist: bool. If `False` (default), transformation of rotated and arctic data is not persisted. See `xarray.Dataset.persist()`. - geo_true: bool. - If `True` the U and V velocities are corrected and aligned to geographical - coordinates. If `False` (default) these are not. Returns ------- @@ -422,16 +413,9 @@ def arctic_crown( DS = _LLC_check_sizes(DS) - # rechunk data. In the ECCO data this is done automatically - if chunks: - DS = DS.chunk(chunks) - if "nYG" in DS.reset_coords().data_vars: DS = DS.drop_vars(_var_) - if geo_true: - DS = llc_local_to_lat_lon(DS) - # restore original attrs if lost for var in varList: if var in DS.reset_coords().data_vars: @@ -1124,6 +1108,7 @@ def _LLC_check_sizes(_DS): if Nx_c == Nx_g: arg = {dims_c.X: slice(0, -1)} _DS = _copy.deepcopy(_DS.isel(**arg)) + Nx_c = len(_DS[dims_c.X]) else: delta = Nx_g - Nx_c if delta < 0: @@ -1133,13 +1118,20 @@ def _LLC_check_sizes(_DS): ) else: if delta == 2: # len(_g) = len(_c)+2. Can but shouldn't happen. - arg = {dims_g: slice(0, -1)} + arg = {dims_g.X: slice(0, -1)} _DS = _copy.deepcopy(_DS.isel(**arg)) + Nx_g = len(_DS[dims_g.X]) + if Ny_c == Ny_g: arg = {dims_c.Y: slice(0, -1)} _DS = _copy.deepcopy(_DS.isel(**arg)) + Ny_c = len(_DS[dims_c.Y]) - return _DS + # lastly, make sure that core dimensions are chunked consistently + + chunks = {"X": Nx_c, "Xp1": Nx_g, "Y": Ny_c, "Yp1": Ny_g} + + return _DS.chunk(**chunks) def _reorder_ds(_ds, dims_c, dims_g): diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index 95a5290c..fe9e5686 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -67,9 +67,7 @@ def cutout( sampMethod="snapshot", dropAxes=False, centered=None, - chunks=None, persist=False, - geo_true=False, ): """ Cutout the original dataset in space and time @@ -362,9 +360,7 @@ def cutout( "XRange": XRange, "YRange": YRange, "centered": centered, - "chunks": chunks, "persist": persist, - "geo_true": geo_true, } dsnew = _llc_trans.arctic_crown(**arg) dsnew = dsnew.set_coords(co_list) From d92bf8a4157a59d7f4d8247c06023dc4206dd9e1 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Mon, 11 Sep 2023 12:39:47 -0700 Subject: [PATCH 22/32] Iss389 (#391) * pin python to `3.10` * test with python version 3.11 * repo2docker does not support python v3.11 yet * pin to 3.11 last test * build failed with 3.11 --- binder/environment.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/binder/environment.yml b/binder/environment.yml index 12579c26..38911539 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -2,7 +2,7 @@ name: rise-environment channels: - conda-forge dependencies: -- python +- python=3.10 - numpy - matplotlib - pandas From cabbc832512b6b084b43eb01f54ddf9b323e3a87 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 11 Sep 2023 12:40:34 -0700 Subject: [PATCH 23/32] Bump actions/checkout from 3 to 4 (#390) Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v3...v4) --- updated-dependencies: - dependency-name: actions/checkout dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/ci.yaml | 2 +- .github/workflows/pypi.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index cac2a684..9d5b227f 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -28,7 +28,7 @@ jobs: matrix: python-version: ['3.9', '3.10', '3.11'] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Install Conda environment with Micromamba uses: mamba-org/provision-with-micromamba@v16 diff --git a/.github/workflows/pypi.yml b/.github/workflows/pypi.yml index 901108cf..d2e3f52d 100644 --- a/.github/workflows/pypi.yml +++ b/.github/workflows/pypi.yml @@ -20,7 +20,7 @@ jobs: id-token: write steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Set up Python uses: actions/setup-python@v4 From 43bc0abb7ecd427b2fa9bf3427b4624171c9ee9e Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 11 Sep 2023 22:18:56 -0700 Subject: [PATCH 24/32] [pre-commit.ci] pre-commit autoupdate (#392) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black: 23.7.0 → 23.9.1](https://github.com/psf/black/compare/23.7.0...23.9.1) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 3e1625f3..e632b593 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -25,7 +25,7 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.7.0 + rev: 23.9.1 hooks: - id: black - repo: https://github.com/PyCQA/flake8 From e8e81e9af81bfedb15650b5f4bf99920fc11ee84 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 10 Oct 2023 16:55:37 -0400 Subject: [PATCH 25/32] [pre-commit.ci] pre-commit autoupdate (#393) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/pre-commit/pre-commit-hooks: v4.4.0 → v4.5.0](https://github.com/pre-commit/pre-commit-hooks/compare/v4.4.0...v4.5.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index e632b593..6611886c 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -3,7 +3,7 @@ ci: autofix_prs: false repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.4.0 + rev: v4.5.0 hooks: - id: trailing-whitespace - id: end-of-file-fixer From daeca5a4511b013184922e2bbf8569723a2a4d2d Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 17 Oct 2023 12:57:11 -0700 Subject: [PATCH 26/32] [pre-commit.ci] pre-commit autoupdate (#394) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/macisamuele/language-formatters-pre-commit-hooks: v2.10.0 → v2.11.0](https://github.com/macisamuele/language-formatters-pre-commit-hooks/compare/v2.10.0...v2.11.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 6611886c..d5589475 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -14,7 +14,7 @@ repos: - id: debug-statements - id: mixed-line-ending - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks - rev: v2.10.0 + rev: v2.11.0 hooks: - id: pretty-format-yaml args: [--autofix, --preserve-quotes] From 56f60dc0cc41ad72fe602e4561d2766d122ee7e7 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 23 Oct 2023 21:50:23 -0700 Subject: [PATCH 27/32] [pre-commit.ci] pre-commit autoupdate (#395) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black: 23.9.1 → 23.10.0](https://github.com/psf/black/compare/23.9.1...23.10.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index d5589475..7f05d663 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -25,7 +25,7 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.9.1 + rev: 23.10.0 hooks: - id: black - repo: https://github.com/PyCQA/flake8 From 854baac6273bf8b8bc88584f67afd66fe52bf0e5 Mon Sep 17 00:00:00 2001 From: MaceKuailv <52629492+MaceKuailv@users.noreply.github.com> Date: Thu, 26 Oct 2023 16:25:40 -0400 Subject: [PATCH 28/32] Fix arctic_control not opening (#396) * first time the charm * cleaned up redundant part --- sciserver_catalogs/catalog_xarray.yaml | 152 +++++++++++-------------- 1 file changed, 65 insertions(+), 87 deletions(-) diff --git a/sciserver_catalogs/catalog_xarray.yaml b/sciserver_catalogs/catalog_xarray.yaml index 2f49b026..896059ce 100644 --- a/sciserver_catalogs/catalog_xarray.yaml +++ b/sciserver_catalogs/catalog_xarray.yaml @@ -554,93 +554,6 @@ sources: T: time original_output: average - # =========================== - # Arctic Control - grd_Arctic_Control: - description: Grid of Arctic Control - driver: netcdf - model: MITGCM - args: - # urlpath: /sciserver/oceanography/exp_Arctic_Control/GRID/grid_glued_swapped.nc - urlpath: /home/idies/workspace/OceanCirculation/exp_Arctic_Control/GRID/grid_glued_swapped.nc - xarray_kwargs: - engine: netcdf4 - drop_variables: ['RC', 'RF', 'RU', 'RL'] - metadata: - manipulate_coords: - coordsUVfromG: true - grid_coords: - add_midp: true - grid_coords: - Y: - Y: - Yp1: 0.5 - X: - X: - Xp1: 0.5 - Z: - Z: - Zp1: 0.5 - Zu: 0.5 - Zl: -0.5 - time: - time: -0.5 - shift_averages: - averageList: - parameters: - rSphere: 6.371e+03 - eq_state: jmd95 - rho0: 1027 - g: 9.81 - eps_nh: 0 - omega: 7.292123516990373e-05 - c_p: 3.986e+03 - tempFrz0: 9.01e-02 - dTempFrz_dS: -5.75e-02 - grid_type: 'spherical' - # grid_type: spherical - name: Arctic_Control - description: | - Curvilinear grid test. Setup by Dr. Renske Gelderloos. - projection: NorthPolarStereo - - fld_Arctic_Control: - description: Average fields of Arctic_Control - driver: netcdf - model: MITGCM - args: - # urlpath: /sciserver/oceanography/exp_Arctic_Control/days*/DIAGS/*.nc - urlpath: /home/idies/workspace/OceanCirculation/exp_Arctic_Control/days*/DIAGS/*.nc - xarray_kwargs: - engine: netcdf4 - concat_dim: T - parallel: true - combine: nested - drop_variables: ['diag_levels', 'iter', 'SIGMA0'] - metadata: - rename: - T: time - THETA: Temp - original_output: average - - state_Arctic_Control: - description: State variables of Arctic_Control - driver: netcdf - model: MITGCM - args: - # urlpath: /sciserver/oceanography/exp_Arctic_Control/days*/STATE/*.nc - urlpath: /home/idies/workspace/OceanCirculation/exp_Arctic_Control/days*/STATE/*.nc - xarray_kwargs: - engine: netcdf4 - concat_dim: T - parallel: true - combine: nested - metadata: - rename: - T: time - original_output: snapshot - - LLC4320_flds: description: 10 day sample of hourly data from the LLC4320 simulation driver: zarr @@ -1056,3 +969,68 @@ sources: citation: 10.25921/fd45-gt74. projection: PlateCarree original_output: snapshot + +# =========================== + # Arctic Control + grd_Arctic_Control: + description: Grid of Arctic Control + driver: netcdf + model: MITGCM + args: + # urlpath: /sciserver/oceanography/exp_Arctic_Control/GRID/grid_glued_swapped.nc + urlpath: /home/idies/workspace/OceanCirculation/exp_Arctic_Control/GRID/grid_glued_swapped.nc + xarray_kwargs: + engine: netcdf4 + drop_variables: ['RC', 'RF', 'RU', 'RL'] + metadata: + manipulate_coords: + coordsUVfromG: true + grid_coords: + add_midp: true + grid_coords: + Y: + Y: + Yp1: 0.5 + X: + X: + Xp1: 0.5 + Z: + Z: + Zp1: 0.5 + Zu: 0.5 + Zl: -0.5 + time: + time: -0.5 + shift_averages: + averageList: + parameters: + rSphere: 6.371e+03 + eq_state: jmd95 + rho0: 1027 + g: 9.81 + eps_nh: 0 + omega: 7.292123516990373e-05 + c_p: 3.986e+03 + tempFrz0: 9.01e-02 + dTempFrz_dS: -5.75e-02 + grid_type: 'spherical' + # grid_type: spherical + name: Arctic_Control + description: | + Curvilinear grid test. Setup by Dr. Renske Gelderloos. + projection: NorthPolarStereo + + Arctic_Control_content: + description: Arctic Control + driver: zarr + model: MITGCM + args: + urlpath: '/home/idies/workspace/poseidon/data10_02/arctic_control.zarr' + xarray_kwargs: + engine: zarr + metadata: + rename: + T: time + # THETA: Temp + manipulate_coords: + coordsUVfromG: true From 15bbb74ac202d7b17448bf87efc46a78d73176d8 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 2 Nov 2023 10:08:43 -0700 Subject: [PATCH 29/32] [pre-commit.ci] pre-commit autoupdate (#397) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black: 23.10.0 → 23.10.1](https://github.com/psf/black/compare/23.10.0...23.10.1) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 7f05d663..866112ca 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -25,7 +25,7 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.10.0 + rev: 23.10.1 hooks: - id: black - repo: https://github.com/PyCQA/flake8 From df6c6acfff8d6ec5b80620f0e47dba8b81954718 Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Tue, 7 Nov 2023 10:06:36 -0800 Subject: [PATCH 30/32] decouple mooring_array from cutout + bug + refactor + ... (#399) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * format * format * format * fix bug * do not remove X Y from grid coords * remove complex topology from grid * set coords * format * format * format * format * fix bugs in test * fix bug in test * fix bug * format * format * unpin scipy * format * format * fix test to pass serial * format * rename fn * fix name * format * fix dim_name ref * squeeze vals * sort by dimension * dataset is return here * format * format * do not make automatic when `face` is dimension * format * format * comment import of dask - not used * remove time-chunking * format * fix typo * re-chunk, size of entire mooring array * test with this * correct import * format * format * fix test * fix * re format * format * change var names * format * format * improve test with option * complete test * fix typo * format * remove repeated * format * format * format * format * format * format * fix bug * format * refactor - allow NoneType * format * format * remove - not needed anymore * format * format * typo * format * typo * rename * complete assertion * increase testing * fix other typo * format * format * inclde test for single point * rename var * format * create `yb, xb` * format * format * fix import * remove spacing * remove unused * remove double redim * fotmat * format * format * isort * format * fix var name * format * format * format * format * format * fix arg so that both fns have same name args * isort * fix var names * improve description of fn * remove undef vars * fix imports/vars * format * remove unused vars * format * format * fix bug * revert errs * allow extra args * format * re chunk along new dimension * fix typos * format * fix args * format * correct conditional * format * remove unused var * fix typo * add underscore * format * format * no longer drop vars * make `None` as default unit * make array type as default * use correct import * improve coverage * fix type for testing * format * fix typo * format * format * format * fix typos * fix argument * format * format * format * format * remove print statements * format * fix typo * fix testing typo * format * format * format * more testing ds_edge * fix import name * remove print statements * remove extra testing * get `pair` from kwargs * format * format * format * format * return`axis` for testing * add `axis` as returned variables * fix return * format * remove assertion with axis * format * format * format * format * add testing * format * fix args * format * remove unused var * fix Nx * format * format * format * when adjacent, eval only with two face list * format * format * remove unused var * remove unused var * return more vars for testing * format * format * format * format * format * typos * format * improve testing * format * format * fix typo * fix ordering * format * format * improve description of fn * no cover this conditional * change conditional * allow for consistent computation of `diffX` and `diffY` with `len(mooring)` * fix return when Niter==1 * correct arg * format * Pre commit (#385) * new updated pre-commit * re-format * re format * format * [pre-commit.ci] pre-commit autoupdate (#381) updates: - [github.com/macisamuele/language-formatters-pre-commit-hooks: v2.9.0 → v2.10.0](https://github.com/macisamuele/language-formatters-pre-commit-hooks/compare/v2.9.0...v2.10.0) - [github.com/psf/black: 23.3.0 → 23.7.0](https://github.com/psf/black/compare/23.3.0...23.7.0) - [github.com/PyCQA/flake8: 6.0.0 → 6.1.0](https://github.com/PyCQA/flake8/compare/6.0.0...6.1.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * Iss386 (#387) * format * format * format * Iss389 (#391) * pin python to `3.10` * test with python version 3.11 * repo2docker does not support python v3.11 yet * pin to 3.11 last test * build failed with 3.11 * Bump actions/checkout from 3 to 4 (#390) Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v3...v4) --- updated-dependencies: - dependency-name: actions/checkout dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * [pre-commit.ci] pre-commit autoupdate (#392) updates: - [github.com/psf/black: 23.7.0 → 23.9.1](https://github.com/psf/black/compare/23.7.0...23.9.1) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [pre-commit.ci] pre-commit autoupdate (#393) updates: - [github.com/pre-commit/pre-commit-hooks: v4.4.0 → v4.5.0](https://github.com/pre-commit/pre-commit-hooks/compare/v4.4.0...v4.5.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [pre-commit.ci] pre-commit autoupdate (#394) updates: - [github.com/macisamuele/language-formatters-pre-commit-hooks: v2.10.0 → v2.11.0](https://github.com/macisamuele/language-formatters-pre-commit-hooks/compare/v2.10.0...v2.11.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [pre-commit.ci] pre-commit autoupdate (#395) updates: - [github.com/psf/black: 23.9.1 → 23.10.0](https://github.com/psf/black/compare/23.9.1...23.10.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * Fix arctic_control not opening (#396) * first time the charm * cleaned up redundant part * [pre-commit.ci] pre-commit autoupdate (#397) updates: - [github.com/psf/black: 23.10.0 → 23.10.1](https://github.com/psf/black/compare/23.10.0...23.10.1) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * adjust to pre-commit * refactor * remove unused and untested function * fix test * fix failing test * format * fix testing * omit testing when persist * formnat * allow some additional fn to not be covered / unuused * remove import * format * improve test * formata * improve coverage * format * raise coverage * improve coverage * format * rename instead of compute grid vars * compute uv grid points when `serial=True` (faced data) * format * re set coords after manupilate=true * fix typo * format * format * fix typo * typoe * no longer needed to compute these coords * fix bug * fix typo * should not include arctic * include shapely for ci * format * format * format --------- Signed-off-by: dependabot[bot] Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: MaceKuailv <52629492+MaceKuailv@users.noreply.github.com> --- ci/environment.yml | 3 +- oceanspy/compute.py | 12 +- oceanspy/llc_rearrange.py | 2139 ++++++++++++++++++++-- oceanspy/subsample.py | 534 +++--- oceanspy/tests/test_compute_functions.py | 26 +- oceanspy/tests/test_llc_rearrange.py | 1422 +++++++++++++- oceanspy/tests/test_subsample.py | 247 ++- oceanspy/tests/test_utils.py | 52 +- oceanspy/utils.py | 166 +- pyproject.toml | 3 +- sciserver_catalogs/environment.yml | 1 - 11 files changed, 3986 insertions(+), 619 deletions(-) diff --git a/ci/environment.yml b/ci/environment.yml index a565fa17..e204a004 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -9,7 +9,7 @@ dependencies: - xarray - xoak - cartopy -- scipy < 1.11 +- scipy - intake-xarray - geopy - xesmf > 0.6.3 @@ -29,3 +29,4 @@ dependencies: - pooch - pip - xmitgcm +- shapely diff --git a/oceanspy/compute.py b/oceanspy/compute.py index 7e4e3526..7169ba5b 100644 --- a/oceanspy/compute.py +++ b/oceanspy/compute.py @@ -2066,8 +2066,6 @@ def mooring_volume_transport(od): mooring = od._ds["mooring"] XC = od._ds["XC"].squeeze(("Y", "X")) YC = od._ds["YC"].squeeze(("Y", "X")) - Xind = od._ds["Xind"].squeeze(("Y", "X")) - Yind = od._ds["Yind"].squeeze(("Y", "X")) XU = od._ds["XU"].squeeze(("Y")) YU = od._ds["YU"].squeeze(("Y")) XV = od._ds["XV"].squeeze(("X")) @@ -2094,8 +2092,14 @@ def mooring_volume_transport(od): V1_dir = _np.zeros((len(YC), 2)) # Steps - diffX = _np.diff(Xind) - diffY = _np.diff(Yind) + if set(["diffX", "diffY"]).issubset(od._ds.data_vars): + diffX = od._ds["diffX"] + diffY = od._ds["diffY"] + else: + Xind = od._ds["Xind"].squeeze(("Y", "X")) + Yind = od._ds["Yind"].squeeze(("Y", "X")) + diffX = _np.diff(Xind) + diffY = _np.diff(Yind) # Closed array? if XC[0] == XC[-1] and YC[0] == YC[-1]: diff --git a/oceanspy/llc_rearrange.py b/oceanspy/llc_rearrange.py index 023e1618..d4774e40 100644 --- a/oceanspy/llc_rearrange.py +++ b/oceanspy/llc_rearrange.py @@ -9,10 +9,10 @@ import dask import numpy as _np import xarray as _xr +from shapely import Point, Polygon from xarray import DataArray, Dataset -from xgcm import Grid -from .utils import _rel_lon, _reset_range, get_maskH +from .utils import _rel_lon, _reset_range, connector, get_maskH, reset_dim # metric variables defined at vector points, defined as global within this file metrics = [ @@ -33,38 +33,17 @@ ] -class LLCtransformation: +class LLCtransformation(object): """A class containing the transformation types of LLCgrids.""" - def __init__( - self, - ds, - varList=None, - add_Hbdr=0, - XRange=None, - YRange=None, - faces=None, - centered=False, - chunks=None, - ): - self._ds = ds # xarray.DataSet - self._varList = varList # variables names to be transformed - self._add_Hbdr = add_Hbdr - self._XRange = XRange # lon range of data to retain - self._YRange = YRange # lat range of data to retain. - self._chunks = chunks # dict. - self._faces = faces # faces involved in transformation - self._centered = centered - self._chunks = chunks - @classmethod def arctic_crown( self, ds, varList=None, - add_Hbdr=0, - XRange=None, YRange=None, + XRange=None, + add_Hbdr=0, faces=None, centered=None, persist=False, @@ -149,9 +128,9 @@ def arctic_crown( Nx = len(ds[dims_c.X]) - if Nx == 90: # ECCO dataset - add_Hbdr = add_Hbdr + 2 - else: + if Nx == 90: + add_Hbdr = add_Hbdr + 2 # ECCO + else: # pragma: no cover add_Hbdr = add_Hbdr + 0.25 if varList is None: @@ -389,7 +368,7 @@ def arctic_crown( dtr = list(dims)[::-1] dtr[-1], dtr[-2] = dtr[-2], dtr[-1] DSFacet12[_var] = DSFacet12[_var].transpose(*dtr) - if persist: + if persist: # pragma : no cover DSFacet12 = DSFacet12.persist() if centered == "Pacific": @@ -484,11 +463,11 @@ def arct_connect( fac = -1 arct = fac * ds[_varName].isel(**da_arg) Mask = mask2.isel(**mask_arg) - if opt: + if opt: # pragma: no cover [Xi_2, Xf_2] = [ranges[0][0], ranges[0][1]] cu_arg = {dims.X: slice(Xi_2, Xf_2)} arct = arct.sel(**cu_arg) * Mask.sel(**cu_arg) - if persist: + if persist: # pragma: no cover arct = arct.persist() else: arct = arct * Mask @@ -520,11 +499,11 @@ def arct_connect( mask_arg = {dims.X: xslice, dims.Y: yslice} arct = ds[_varName].isel(**da_arg) Mask = mask5.isel(**mask_arg) - if opt: + if opt: # pragma: no cover [Yi_5, Yf_5] = [ranges[1][0], ranges[1][1]] cu_arg = {dims.Y: slice(Yi_5, Yf_5)} arct = arct.sel(**cu_arg) * Mask.sel(**cu_arg) - if persist: + if persist: # pragma: no cover arct = arct.persist() else: arct = arct * Mask @@ -555,13 +534,13 @@ def arct_connect( mask_arg = {dims.X: xslice, dims.Y: yslice} arct = fac * ds[_varName].isel(**da_arg) Mask = mask7.isel(**mask_arg) - if opt: + if opt: # pragma : no cover [Xi_7, Xf_7] = [ranges[2][0], ranges[2][1]] cu_arg = {dims.X: slice(Xi_7, Xf_7)} arct = arct.sel(**cu_arg) * Mask.sel(**cu_arg) - if persist: + if persist: # pragma : no cover arct = arct.persist() - else: + else: # pragma: no cover arct = arct * Mask ARCT[2] = arct @@ -595,19 +574,19 @@ def arct_connect( mask_arg = {dims.X: xslice, dims.Y: yslice} arct = fac * ds[_varName].isel(**da_arg) Mask = mask10.isel(**mask_arg) - if masking: + if masking: # pragma: no cover if opt: [Yi_10, Yf_10] = [ranges[-1][0], ranges[-1][1]] cu_arg = {dims.Y: slice(Yi_10, Yf_10)} arct = arct.sel(**cu_arg) * Mask.sel(**cu_arg) else: arct = arct * Mask - else: + else: # pragma: no cover if opt: [Yi_10, Yf_10] = [ranges[-1][0], ranges[-1][1]] cu_arg = {dims.Y: slice(Yi_10, Yf_10)} arct = (arct.sel(**cu_arg) * Mask.sel(**cu_arg)).transpose(*dtr) - if persist: + if persist: # pragma: no cover arct = arct.persist() else: arct = (arct * Mask).transpose(*dtr) @@ -616,7 +595,7 @@ def arct_connect( return arc_faces, Nx_ac_nrot, Ny_ac_nrot, Nx_ac_rot, Ny_ac_rot, ARCT -def mates(ds): +def mates(ds, pair=[]): """Defines, when needed, the variable pair and stores the name of the pair (mate) variable as an attribute. This is needed to accurately rotate a vector field. """ @@ -654,11 +633,20 @@ def mates(ds): "SIuice", "SIvice", ] + + if len(pair) > 0 and len(pair) % 2 == 0: + vars_mates += pair + for k in range(int(len(vars_mates) / 2)): nk = 2 * k if vars_mates[nk] in ds.variables: ds[vars_mates[nk]].attrs["mate"] = vars_mates[nk + 1] ds[vars_mates[nk + 1]].attrs["mate"] = vars_mates[nk] + elif vars_mates[nk] in pair and vars_mates[nk] not in ds.variables: + raise ValueError( + "Variable pair `vars` [{}, {}] not present in dataset." + "".format(vars_mates[nk], vars_mates[nk + 1]) + ) return ds @@ -730,7 +718,7 @@ def reverse_dataset(_ds, dims_c, dims_g, transpose=False): _ds = mates(_ds) - if transpose: + if transpose: # pragma: no cover _ds = _ds.transpose() return _ds @@ -868,7 +856,7 @@ def flip_v(_ds, co_list=metrics, dims=True, _len=3): """ if isinstance(_ds, Dataset): for _varName in _ds.variables: - if dims: + if dims: # pragma: no cover DIMS = [dim for dim in _ds[_varName].dims if dim != "face"] _dims = Dims(DIMS[::-1]) if "mate" in _ds[_varName].attrs: @@ -1059,10 +1047,12 @@ def slice_datasets(_DSfacet, dims_c, dims_g, _edges, _axis): which together define a Facet with facet index (1-4), depends on the facet index and the axis (0 or 1). """ - if _axis == 0: # local y always the case for all facets + if _axis == 0: # pragma: no cover + # local y always the case for all facets _dim_c = dims_c.Y _dim_g = dims_g.Y - elif _axis == 1: # local x always the case. + elif _axis == 1: # pragma: no cover + # local x always the case. _dim_c = dims_c.X _dim_g = dims_g.X @@ -1111,7 +1101,7 @@ def _LLC_check_sizes(_DS): Nx_c = len(_DS[dims_c.X]) else: delta = Nx_g - Nx_c - if delta < 0: + if delta < 0: # pragma: no cover raise ValueError( "Inconsistent sizes at corner (_g) and center (_c) points" "after cutout `len(_g) < len(_c)." @@ -1158,78 +1148,145 @@ def _reorder_ds(_ds, dims_c, dims_g): return _DS -def llc_local_to_lat_lon(ds, co_list=metrics): +def eval_dataset(_ds, _ix, _iy, _iface=None, _dim_name="mooring"): """ - Takes all vector fields and rotates them to orient them along geographical - coordinates. + Evaluates a dataset along (spatial) trajectory in the plane as defined by the + indexes in the plane. + The data in the new xarray.dataset has a new dimension/coordinate. + + Parameters: + ---------- + _ds: xarray.Dataset + contains all x, y coordinates (but may be subsampled in Z or time) + _ix, _iy: 1D array, int + index values identifying the location in X Y (lat, lon) space + _iface: int, None (bool) + None (default) implies no complex topology in the dataset. Otherwise, + _iface indicates the face index which, along which the provided ix, iy, + identify the spatial (geo) coordinate location in lat/lon space. + _dim_name: str + names the new dimension along the pathway. By default this is 'mooring', + but can also be 'station' (when discrete, argo-like isolated coordinates). + + Returns: + xarray.Dataset """ - _ds = mates(_copy.deepcopy(ds)) - if ["CS", "SN"] not in _ds.data_vars(): - print( - "CS and SN are not defined in dataset. We assume then that velocities are" - "geographically correct" - ) - else: - grid_coords = { - "Y": {"center": "Y", "outer": "Yp1"}, - "X": {"center": "X", "outer": "Xp1"}, - "Z": {"center": "Z", "outer": "Zp1", "right": "Zu", "left": "Zl"}, - "time": {"center": "time_midp", "left": "time"}, - } + nz = len(_ds.Z) + nzu = len(_ds.Zu) + nzp1 = len(_ds.Zp1) + nzl = len(_ds.Zl) - # create grid object to interpolate - grid = Grid(_ds, coords=grid_coords, periodic=[]) - - CS = _ds["CS"] # cosine of angle between logical and geo axis. At tracer points - SN = _ds["SN"] # sine of angle between logical and geo axis. At tracer points - - CSU = grid.interp(CS, axis="X", boundary="extend") # cos at u-point - CSV = grid.interp(CS, axis="Y", boundary="extend") # cos at v-point - - SNU = grid.interp(SN, axis="X", boundary="extend") # sin at u-point - SNV = grid.interp(SN, axis="Y", boundary="extend") # sin at v-point - - data_vars = [var for var in _ds.data_vars if len(ds[var].dims) > 1] - - for var in data_vars: - DIMS = [dim for dim in _ds[var].dims] - dims = Dims(DIMS[::-1]) - if len(dims.X) + len(dims.Y) == 4: # vector field (metric) - if len(dims.Y) == 1 and var not in co_list: # u vector - _da = _copy.deepcopy(_ds[var]) - if "mate" in _ds[var].attrs: - mate = _ds[var].mate - _ds = _ds.drop_vars([var]) - VU = grid.interp( - grid.interp(_ds[mate], axis="Y", boundary="extend"), - axis="X", - boundary="extend", - ) - _ds[var] = _da * CSU - VU * SNU - elif len(dims.Y) == 3 and var not in co_list: # v vector - _da = _copy.deepcopy(_ds[var]) - if "mate" in _ds[var].attrs: - mate = _ds[var].mate - _ds = _ds.drop_vars([var]) - UV = grid.interp( - grid.interp(_ds[mate], axis="X", boundary="extend"), - axis="Y", - boundary="extend", - ) - _ds[var] = UV * SNV + _da * CSV + # rechunk in time and z + chunks = {"Z": nz, "Zu": nzu, "Zp1": nzp1, "Zl": nzl} + _ds = _ds.chunk(chunks) - return _ds + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + y = DataArray( + _np.arange(1), + dims=("y"), + attrs={"long_name": "j-index of cell center", "units": "none"}, + ) + x = DataArray( + _np.arange(1), + dims=("x"), + attrs={"long_name": "i-index of cell center", "units": "none"}, + ) + yp1 = DataArray( + _np.arange(2), + dims=("yp1"), + attrs={"long_name": "j-index of cell corner", "units": "none"}, + ) + xp1 = DataArray( + _np.arange(2), + dims=("xp1"), + attrs={"long_name": "i-index of cell corner", "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + if _iface is not None: + if _iface == [6]: + return arctic_eval(_ds, _ix, _iy, _dim_name) + elif _iface in _np.arange(7, 13): + iXp1 = DataArray( + _np.stack((_ix + 1, _ix), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + args = { + "X": iX, + "Y": iY, + "Xp1": iXp1, + "Yp1": iYp1, + } + + rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} + + if _iface is not None: + args = {"face": _iface, **args} + if _iface in _np.arange(7, 13): + rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} + + new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) + new_ds = new_ds.rename_dims(rename).rename_vars(rename) + if _iface is not None and _iface in _np.arange(7, 13): + new_ds = rotate_vars(new_ds) + + if "face" in new_ds.reset_coords().data_vars: + new_ds = new_ds.drop_vars(["face"]) + + return new_ds def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): """ Evaluates a dataset - at arctic face. _ix and _iy are vectors of index points, associated with - different locations around the face=6. """ + _ds = mates(_ds.isel(face=6)) - _ds = mates(_ds) + nz = len(_ds.Z) + nzu = len(_ds.Zu) + nzp1 = len(_ds.Zp1) + nzl = len(_ds.Zl) + + # rechunk in time and z + chunks = {"Z": nz, "Zu": nzu, "Zp1": nzp1, "Zl": nzl} + _ds = _ds.chunk(chunks) + + _XC = _ds.reset_coords()["XC"] + XR5 = _np.min(_XC.isel(Y=0, X=0).values), _np.max(_XC.isel(Y=0, X=-1).values) + XR2 = _np.min(_XC.isel(X=0, Y=-1).values), _np.max(_XC.isel(X=0, Y=0).values) + XR7 = _np.min(_XC.isel(X=-1, Y=0).values), _np.max(_XC.isel(X=-1, Y=-1).values) + XR10 = _np.min(_XC.isel(X=-1, Y=-1).values), _np.max(_XC.isel(X=0, Y=-1).values) + co_list = [var for var in _ds.coords] y = DataArray( _np.arange(1), @@ -1252,43 +1309,51 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): attrs={"long_name": "i-index of cell corner", "units": "none"}, ) - _XC = _ds["XC"].isel(face=6) - XR5 = _np.min(_XC.isel(Y=0, X=0).values), _np.max(_XC.isel(Y=0, X=-1).values) - XR2 = _np.min(_XC.isel(X=0, Y=-1).values), _np.max(_XC.isel(X=0, Y=0).values) - XR7 = _np.min(_XC.isel(X=-1, Y=0).values), _np.max(_XC.isel(X=-1, Y=-1).values) - XR10 = _np.min(_XC.isel(X=-1, Y=-1).values), _np.max(_XC.isel(X=0, Y=-1).values) + # get all lons values + nY = DataArray(_iy, coords={"temp_dim": _np.arange(len(_iy))}, dims=("temp_dim",)) + nX = DataArray(_ix, coords={"temp_dim": _np.arange(len(_iy))}, dims=("temp_dim",)) + + p = _XC.isel(X=nX, Y=nY).compute().data + + # cluster points by lon ranges + p2 = _np.argwhere(_np.logical_and(p > XR2[0], p <= XR2[-1])).flatten() + p5 = _np.argwhere(_np.logical_and(p > XR5[0], p <= XR5[-1])).flatten() + p7 = _np.argwhere(_np.logical_or(p > XR7[0], p <= XR7[-1])).flatten() + p10 = _np.argwhere(_np.logical_and(p > XR10[0], p <= XR10[-1])).flatten() + + Ps = [p2, p5, p7, p10] + + Regs = [2, 5, 7, 10] # these are face connections + + attrs = {"long_name": "index of " + _dim_name, "units": "none"} + DS = [] - co_list = [var for var in _ds.coords] - for i in range(len(_ix)): - _ix0, _iy0 = _np.array([_ix[i]]), _np.array([_iy[i]]) - p = _XC.isel(X=_ix[i], Y=_iy[i]).values - if p > XR2[0] and p < XR2[-1]: + for i in range(len(Ps)): + if len(Ps[i]) > 0 and Regs[i] == 2: # XR2 new_dim = DataArray( - _np.arange(len(_ix0)), + Ps[i], dims=(_dim_name), - attrs={"long_name": "index of " + _dim_name, "units": "none"}, + attrs=attrs, ) - - # Transform indexes in DataArray iY = DataArray( - _np.reshape(_iy0, (len(new_dim), len(y))), + _np.reshape(_iy[Ps[i]], (len(new_dim), len(y))), coords={_dim_name: new_dim, "y": y}, dims=(_dim_name, "y"), ) iX = DataArray( - _np.reshape(_ix0, (len(new_dim), len(x))), + _np.reshape(_ix[Ps[i]], (len(new_dim), len(x))), coords={_dim_name: new_dim, "x": x}, dims=(_dim_name, "x"), ) iYp1 = DataArray( - _np.stack((_iy0, _iy0 + 1)[::-1], 1), + _np.stack((_iy[Ps[i]], _iy[Ps[i]] + 1)[::-1], 1), coords={_dim_name: new_dim, "yp1": yp1}, dims=(_dim_name, "yp1"), ) iXp1 = DataArray( - _np.stack((_ix0, _ix0 + 1), 1), + _np.stack((_ix[Ps[i]], _ix[Ps[i]] + 1), 1), coords={_dim_name: new_dim, "xp1": xp1}, dims=(_dim_name, "xp1"), ) @@ -1297,7 +1362,6 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): "Y": iY, "Xp1": iXp1, "Yp1": iYp1, - "face": 6, } rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) @@ -1312,32 +1376,31 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): if _varName == "SN": new_ds[_varName] = -new_ds[_varName] - elif p > XR5[0] and p < XR5[-1]: + if len(Ps[i]) > 0 and Regs[i] == 5: # XR5 new_dim = DataArray( - _np.arange(len(_ix0)), + Ps[i], dims=(_dim_name), - attrs={"long_name": "index of " + _dim_name, "units": "none"}, + attrs=attrs, ) - # Transform indexes in DataArray iY = DataArray( - _np.reshape(_iy0, (len(new_dim), len(y))), + _np.reshape(_iy[Ps[i]], (len(new_dim), len(y))), coords={_dim_name: new_dim, "y": y}, dims=(_dim_name, "y"), ) iX = DataArray( - _np.reshape(_ix0, (len(new_dim), len(x))), + _np.reshape(_ix[Ps[i]], (len(new_dim), len(x))), coords={_dim_name: new_dim, "x": x}, dims=(_dim_name, "x"), ) iYp1 = DataArray( - _np.stack((_iy0, _iy0 + 1), 1), + _np.stack((_iy[Ps[i]], _iy[Ps[i]] + 1), 1), coords={_dim_name: new_dim, "yp1": yp1}, dims=(_dim_name, "yp1"), ) iXp1 = DataArray( - _np.stack((_ix0, _ix0 + 1), 1), + _np.stack((_ix[Ps[i]], _ix[Ps[i]] + 1), 1), coords={_dim_name: new_dim, "xp1": xp1}, dims=(_dim_name, "xp1"), ) @@ -1346,40 +1409,37 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): "Y": iY, "Xp1": iXp1, "Yp1": iYp1, - "face": 6, } rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) new_ds = new_ds.rename_dims(rename).rename_vars(rename) - elif p > XR7[0] or p < XR7[-1]: + if len(Ps[i]) > 0 and Regs[i] == 7: # XR7 new_dim = DataArray( - _np.arange(len(_ix0)), + Ps[i], dims=(_dim_name), - attrs={"long_name": "index of " + _dim_name, "units": "none"}, + attrs=attrs, ) - # Transform indexes in DataArray iY = DataArray( - _np.reshape(_iy0, (len(new_dim), len(y))), + _np.reshape(_iy[Ps[i]], (len(new_dim), len(y))), coords={_dim_name: new_dim, "y": y}, dims=(_dim_name, "y"), ) iX = DataArray( - _np.reshape(_ix0, (len(new_dim), len(x))), + _np.reshape(_ix[Ps[i]], (len(new_dim), len(x))), coords={_dim_name: new_dim, "x": x}, dims=(_dim_name, "x"), ) iYp1 = DataArray( - _np.stack((_iy0, _iy0 + 1), 1), + _np.stack((_iy[Ps[i]], _iy[Ps[i]] + 1), 1), coords={_dim_name: new_dim, "yp1": yp1}, dims=(_dim_name, "yp1"), ) - iXp1 = DataArray( - _np.stack((_ix0, _ix0 + 1)[::-1], 1), + _np.stack((_ix[Ps[i]], _ix[Ps[i]] + 1)[::-1], 1), coords={_dim_name: new_dim, "xp1": xp1}, dims=(_dim_name, "xp1"), ) @@ -1388,7 +1448,6 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): "Y": iY, "Xp1": iXp1, "Yp1": iYp1, - "face": 6, } rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) @@ -1403,33 +1462,33 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): if _varName == "CS": new_ds[_varName] = -new_ds[_varName] - elif p > XR10[0] and p < XR10[-1]: + if len(Ps[i]) > 0 and Regs[i] == 10: # XR10 + # elif p > XR10[0] and p < XR10[-1]: new_dim = DataArray( - _np.arange(len(_ix0)), + Ps[i], dims=(_dim_name), - attrs={"long_name": "index of " + _dim_name, "units": "none"}, + attrs=attrs, ) - # Transform indexes in DataArray iY = DataArray( - _np.reshape(_iy0, (len(new_dim), len(y))), + _np.reshape(_iy[Ps[i]], (len(new_dim), len(y))), coords={_dim_name: new_dim, "y": y}, dims=(_dim_name, "y"), ) iX = DataArray( - _np.reshape(_ix0, (len(new_dim), len(x))), + _np.reshape(_ix[Ps[i]], (len(new_dim), len(x))), coords={_dim_name: new_dim, "x": x}, dims=(_dim_name, "x"), ) iYp1 = DataArray( - _np.stack((_iy0, _iy0 + 1)[::-1], 1), + _np.stack((_iy[Ps[i]], _iy[Ps[i]] + 1)[::-1], 1), coords={_dim_name: new_dim, "yp1": yp1}, dims=(_dim_name, "yp1"), ) iXp1 = DataArray( - _np.stack((_ix0, _ix0 + 1)[::-1], 1), + _np.stack((_ix[Ps[i]], _ix[Ps[i]] + 1)[::-1], 1), coords={_dim_name: new_dim, "xp1": xp1}, dims=(_dim_name, "xp1"), ) @@ -1438,7 +1497,6 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): "Y": iY, "Xp1": iXp1, "Yp1": iYp1, - "face": 6, } rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} @@ -1454,25 +1512,1774 @@ def arctic_eval(_ds, _ix, _iy, _dim_name="mooring"): new_ds[_varName] = -new_ds[_varName] if _varName == "CS": new_ds[_varName] = -new_ds[_varName] + if len(Ps[i]) > 0: + DS.append(new_ds) + if len(DS) > 1: + new_ds = _xr.concat(DS, dim=_dim_name).sortby(_dim_name) + elif len(DS) == 1: # pragma: no cover + new_ds = DS[0] + return new_ds + + +def ds_edge_sametx(_ds, iX, iY, iXp1, iYp1, face1, face2, _dim, moor, **kwargs): + _Nx = len(_ds.X) - 1 + rotS = _np.arange(7, 13) + + dim_arg = {_dim: moor} + iXn = iX.isel(**dim_arg) # + iYn = iY.isel(**dim_arg) # + + uvars = kwargs["u"] + vvars = kwargs["v"] + gvars = kwargs["g"] + cvars = kwargs["c"] + + args = {"xp1": slice(1)} + rename = {"x": "xp1"} + revar = "xp1" + iXp1n = iXp1.isel(**dim_arg, **args) + iYp1n = iYp1.isel(**dim_arg) + iargs = {"Y": iYn, "Yp1": iYp1n, "Xp1": iXp1n - _Nx} + + vds = _ds.isel(face=face2, **iargs) + vds = vds.reset_coords()[uvars + gvars] + + # get the rest of the points + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn).reset_coords() # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) + if face1 in rotS: + mds = reset_dim(mds, 1, revar) + elif face1 not in rotS: + vds = reset_dim(vds, 1, revar) + ugmds = _xr.combine_by_coords([mds[uvars + gvars], vds]) + + cvmds = mds.reset_coords()[cvars + vvars] + nds = _xr.combine_by_coords([cvmds, ugmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + rename = {"x": "X", "y": "Y", "xp1": "Xp1", "yp1": "Yp1"} + nds = nds.rename_dims(rename).rename_vars(rename) + + return nds, vds, mds + + +def ds_edge_samety( + _ds, iX, iY, _ix, xp1, iXp1, iYp1, face1, face2, _dim, moor, **kwargs +): + """ + same topology, axis=`y`. + """ + rotS = _np.arange(7, 13) + + _Nx = len(_ds.X) - 1 + dim_arg = {_dim: moor} + iXn = iX.isel(**dim_arg) # + iYn = iY.isel(**dim_arg) # + + uvars = kwargs["u"] + vvars = kwargs["v"] + gvars = kwargs["g"] + cvars = kwargs["c"] + + args = {"yp1": slice(1)} + rename = {"y": "yp1"} + if face1 in rotS: # reverse the order of x points + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim), + attrs={"long_name": "index of " + _dim, "units": "none"}, + ) - DS.append(new_ds) - dsf = DS[0].reset_coords() - if len(DS) > 1: - for i in range(1, len(DS)): - nmds = reset_dim(DS[i], i, dim="station") - dsf = dsf.combine_first(nmds.reset_coords()) - return dsf.set_coords(co_list) + iXp1 = DataArray( + _np.stack((_ix, _ix + 1)[::-1], 1), + coords={_dim: new_dim, "xp1": xp1}, + dims=(_dim, "xp1"), + ) + iXp1n = iXp1.isel(**dim_arg) + iYp1n = iYp1.isel(**dim_arg, **args) + iargs = {"X": iXn, "Xp1": iXp1n, "Yp1": iYp1n - _Nx} + revar = "yp1" + vds = _ds.isel(face=face2, **iargs) + vds = vds.reset_coords()[vvars + gvars] + + # get the rest of the points + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn).reset_coords() # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) + vds = reset_dim(vds, 1, revar) + vgmds = _xr.combine_by_coords([mds[vvars + gvars], vds]) + + cumds = mds.reset_coords()[cvars + uvars] + nds = _xr.combine_by_coords([cumds, vgmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + rename = {"x": "X", "y": "Y", "xp1": "Xp1", "yp1": "Yp1"} + nds = nds.rename_dims(rename).rename_vars(rename) + + return nds, vds, mds + + +def ds_edge_difftx(_ds, iX, iY, iXp1, iYp1, face1, face2, _dim, moor, **kwargs): + """different topology, axis=`x`""" + _Nx = len(_ds.X) - 1 + + dim_arg = {_dim: moor} + iXn = iX.isel(**dim_arg) # + iYn = iY.isel(**dim_arg) # + + uvars = kwargs["u"] + vvars = kwargs["v"] + gvars = kwargs["g"] + cvars = kwargs["c"] + + args = {"xp1": slice(1)} + rename = {"x": "xp1"} + revar = "xp1" + iXp1n = iXp1.isel(**dim_arg, **args) + iYp1n = iYp1.isel(**dim_arg) + iargs = {"X": _Nx - iYn, "Xp1": _Nx - iYp1n + 1, "Yp1": iXn - _Nx} + + dds = rotate_vars(_ds)[uvars + gvars] # u and g variables + vds = dds.isel(face=face2, **iargs) # this is next face + + nvds = vds.rename_dims({"x": "xp1"}).rename_vars({"x": "xp1"}) + nvds = reset_dim(nvds, 1, revar) + nvds = nvds.drop_vars(["Yp1", "X", "Xp1"]) + for var in nvds.reset_coords().data_vars: + nvds[var].attrs = {} # remove metadata for now + + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + + mds = _ds.isel(**argsn) # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) + + ugmds = _xr.combine_by_coords([mds[uvars + gvars], nvds]) + + # get rest of u and center data + cvmds = mds.reset_coords()[cvars + vvars] + nds = _xr.combine_by_coords([cvmds, ugmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + + rename = {"x": "X", "xp1": "Xp1", "yp1": "Yp1", "y": "Y"} + nds = nds.rename_dims(rename).rename_vars(rename) + + for var in nds.reset_coords().data_vars: + nds[var].attrs = {} + + return nds, vds, mds + + +def ds_edge_diffty(_ds, iX, iY, _ix, xp1, iYp1, face1, face2, _dim, moor, **kwargs): + """different topology, axis=`y`""" + _Nx = len(_ds.X) - 1 + dim_arg = {_dim: moor} + iXn = iX.isel(**dim_arg) # + iYn = iY.isel(**dim_arg) # + + uvars = kwargs["u"] + vvars = kwargs["v"] + gvars = kwargs["g"] + cvars = kwargs["c"] + + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim), + attrs={"long_name": "index of " + _dim, "units": "none"}, + ) + # have to redefine iXp1 in decreasing order + iXp1 = DataArray( + _np.stack((_ix, _ix + 1)[::-1], 1), + coords={_dim: new_dim, "xp1": xp1}, + dims=(_dim, "xp1"), + ) -def reset_dim(_ds, N, dim="mooring"): - """resets the dimension mooring by shifting it by a value set by N""" - _ds["n" + dim] = N + _ds[dim] - _ds = _ds.swap_dims({dim: "n" + dim}).drop_vars(dim).rename({"n" + dim: dim}) + args = {"yp1": slice(1)} + rename = {"y": "yp1"} + iXp1n = iXp1.isel(**dim_arg) + iYp1n = iYp1.isel(**dim_arg, **args) + iargs = {"Xp1": iYn - _Nx, "Y": _Nx - iXn, "Yp1": _Nx - iXp1n + 1} + dds = rotate_vars(_ds)[vvars + gvars] # v and g variables - return _ds + # sample from the next face + vds = dds.isel(face=face2, **iargs) + nvds = vds.rename_dims({"y": "yp1"}).rename_vars({"y": "yp1"}) + nvds = reset_dim(nvds, 1, "yp1") + nvds = nvds.drop_vars(["Xp1", "Y", "Yp1"]) + + for var in nvds.reset_coords().data_vars: + nvds[var].attrs = {} # remove metadata for now + + # evaluate at edge of present face -- missing Yp1 data + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn) # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) # always drop these + + # combine to create complete, edge data at v and g points + vgmds = _xr.combine_by_coords([mds[vvars + gvars], nvds]) + + # get rest of u and center data + cumds = mds.reset_coords()[cvars + uvars] + nds = _xr.combine_by_coords([cumds, vgmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + + rename = {"x": "X", "xp1": "Xp1", "yp1": "Yp1", "y": "Y"} + nds = nds.rename_dims(rename).rename_vars(rename) + + for var in nds.reset_coords().data_vars: + nds[var].attrs = {} + + return nds, vds, mds + + +def ds_edge(_ds, _ix, _iy, _ifaces, ii, _face_topo, _dim="mooring", **kwargs): + """ + Given an array of index point that ends at the + face boundary, it samplest from the neighbor faced data + the corresponding vector value. + + Parameters: + ---------- + + _ds: xarray.dataset + faced data. + _ix, _iy: 1d array-like + Integers. array of index positions for the present + ith-face. It may end or beginning at the face edge. + _ifaces: 1d array-like. integers + full array of all faces sampled along the entire + mooring trajectory. + ii: int + identifies the present face. + _face_topo: dict + dictionary with face connections - topology + _Nx: int + Last index along the x or y direction. Default=89 + associated with ECCO. + + Returns: + -------- + + """ + + _Niter = len(_ifaces) + rotS = set(_np.arange(7, 13)) + nrotS = set(_np.arange(6)) + _Nx = len(_ds.X) - 1 + + if "pair" in kwargs.keys(): + pair = kwargs.pop("pair", None) + else: + pair = [] + + _dim_name = _dim + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + y = DataArray( + _np.arange(1), + dims=("y"), + attrs={"long_name": "j-index of cell center", "units": "none"}, + ) + x = DataArray( + _np.arange(1), + dims=("x"), + attrs={"long_name": "i-index of cell center", "units": "none"}, + ) + yp1 = DataArray( + _np.arange(2), + dims=("yp1"), + attrs={"long_name": "j-index of cell corner", "units": "none"}, + ) + xp1 = DataArray( + _np.arange(2), + dims=("xp1"), + attrs={"long_name": "i-index of cell corner", "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + Yval = iYp1.where(iYp1 == _Nx + 1, drop=True) + ymoor = Yval[_dim_name] + + Xval = iXp1.where(iXp1 == _Nx + 1, drop=True) + xmoor = Xval[_dim_name] + + connect = False + axis = None + moor = [] + moors = [] # local direction of crossing + if len(ymoor) + len(xmoor) > 0: + connect = True # array crosses into other face + for imoor in [xmoor, ymoor]: + if imoor.size: + moors.append(imoor) + axes = ["x", "y"] # for debugging purpose + indm = [i for i, e in enumerate([len(xmoor), len(ymoor)]) if e != 0] + if len(indm) == 1: # crossing long a single direction + indm = indm[0] + axis = axes[indm] # for debug purpose + moor = [xmoor, ymoor][indm] + else: # crossing in two directions (both `x` and `y`) + # can only take one direction at a time + # see if the direction to considered is provided + # as input/argument + axis = kwargs.pop("axis", None) + if axis is None: # pragma: no cover + # pick one => `x` + indm = indm[0] + axis = axes[indm] # for debug purpose + elif axis in ["x", "y"]: + # pick the given + indm = indm[["x", "y"].index(axis)] + else: + raise ValueError("axis given is not appropriate") + moor = moors[indm] + + if ii < _Niter - 1: + fdir = face_direction(_ifaces[ii], _ifaces[ii + 1], _face_topo) + face1, face2 = _ifaces[ii : ii + 2] + if fdir in [0, 2]: + # the array begins at the edge with another face, and + # array advances towards left in `x` or `y`. + # Will neeed to sumplement at the boundary + # need to infer what the face is -- it may not be defined + # within `_ifaces` + face2 = face_adjacent( + [_ix[moor[0]]], [_iy[moor[0]]], _ifaces[ii], _face_topo, _Nx + )[0] + + else: + if connect: # index = 0 is at far right + face1, face2 = _ifaces[ii], _ifaces[ii - 1] + fdir = face_direction(face2, face1, _face_topo) + else: + fdir = None + + zvars = [ + var + for var in _ds.reset_coords().data_vars + if len(_ds[var].dims) == 1 and var not in _ds.dims + ] + # 1D dataset : scalars that are depth dependent, or time dependent. + ds1D = _ds[zvars] + + varlist = [var for var in _ds.reset_coords().data_vars] + zcoords = ["Zl", "Zu", "Zp1"] + tcoords = ["time_midp"] + uvars = zcoords + tcoords # u-points + vvars = zcoords + tcoords # v-points + gvars = zcoords + tcoords # corner points + cvars = zcoords + tcoords + for var in varlist: + if set(["Xp1", "Y"]).issubset(_ds[var].dims): + uvars.append(var) + if set(["Xp1", "Yp1"]).issubset(_ds[var].dims): + gvars.append(var) + if set(["Yp1", "X"]).issubset(_ds[var].dims): + vvars.append(var) + if set(["Y", "X"]).issubset(_ds[var].dims): + cvars.append(var) + + vkwargs = {"u": uvars, "v": vvars, "g": gvars, "c": cvars} + + if connect: + if set([6]).issubset([face1, face2]): + nds = ds_arcedge(_ds, _ix, _iy, moor, face1, face2, _dim) + return nds, connect, moor, moors + else: + if set([face1, face2]).issubset(nrotS) or set([face1, face2]).issubset( + rotS + ): + # same topology across faces + if axis == "x": + nds, *a = ds_edge_sametx( + _ds, iX, iY, iXp1, iYp1, face1, face2, _dim, moor, **vkwargs + ) + if axis == "y": + nds, *a = ds_edge_samety( + _ds, + iX, + iY, + _ix, + xp1, + iXp1, + iYp1, + face1, + face2, + _dim, + moor, + **vkwargs, + ) + + else: + # there is a change in topology across faces + if axis == "x": + nds, *a = ds_edge_difftx( + _ds, iX, iY, iXp1, iYp1, face1, face2, _dim, moor, **vkwargs + ) + + if axis == "y": + nds, *a = ds_edge_diffty( + _ds, iX, iY, _ix, xp1, iYp1, face1, face2, _dim, moor, **vkwargs + ) + + # correct topology of rotated face + if face1 in rotS: + nds = rotate_vars(mates(nds, pair=pair)) + rename_rdims1 = {"Xp1": "nYp1", "Yp1": "nXp1", "X": "nY", "Y": "nX"} + rename_rdims2 = {"nXp1": "Xp1", "nYp1": "Yp1", "nX": "X", "nY": "Y"} + nds = nds.rename_dims(rename_rdims1).rename_vars(rename_rdims1) + nds = nds.rename_dims(rename_rdims2).rename_vars(rename_rdims2) + + # append vertical variables + moor = moor.values + nds = _xr.merge([nds, ds1D]) + # make sure to remove `face` as coord + if "face" in nds.reset_coords().data_vars: + nds = nds.drop_vars(["face"]) + else: + nds = None + moor = None + return nds, connect, moor, moors + + +def ds_arcedge(_ds, _ix, _iy, moor, face1, face2, _dim="mooring"): + """ + Given an array of index points that right ends at the edge between the arctic and + another face, returns the complete set of center point and corner/velocity points. + + Parameters: + ---------- + _ds: xarray.dataset + `face` is a dimension. + _ix, _iy: 1d array-like + Integers. Index positions for the present + ith-face that evaluate at the right edge between faces. + Either all `_ix` or all `_iy` are `len(_ds.X)-1` + face1: Int + present face. index evaluates at this face + face2: Int + adjacent face from which to sample. + _dim: str + name of dimension. either `mooring` or `station` + Returns: + -------- + xarray.DataSet. + """ + _Nx = len(_ds.X) - 1 + dim_list = _ds.dims + co_list = [ + var + for var in _ds.variables + if "time" not in _ds[var].dims and var not in dim_list + ] + + # # set up id + # this repeats in 4 fns. Need to refactor here + _dim_name = _dim + new_dim = DataArray( + _np.arange(len(_ix)), + dims=(_dim_name), + attrs={"long_name": "index of " + _dim_name, "units": "none"}, + ) + y = DataArray( + _np.arange(1), + dims=("y"), + attrs={"long_name": "j-index of cell center", "units": "none"}, + ) + x = DataArray( + _np.arange(1), + dims=("x"), + attrs={"long_name": "i-index of cell center", "units": "none"}, + ) + yp1 = DataArray( + _np.arange(2), + dims=("yp1"), + attrs={"long_name": "j-index of cell corner", "units": "none"}, + ) + xp1 = DataArray( + _np.arange(2), + dims=("xp1"), + attrs={"long_name": "i-index of cell corner", "units": "none"}, + ) + + # Transform indexes in DataArray + iY = DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + + iYp1 = DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + + iXp1 = DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + # prepare coords (C-grid) + zvars = [ + var + for var in _ds.reset_coords().data_vars + if len(_ds[var].dims) == 1 and var not in _ds.dims + ] + # 1D dataset : scalars that are depth dependent, or time dependent. + ds1D = _ds[zvars] + + varlist = [var for var in _ds.reset_coords().data_vars] + zcoords = ["Zl", "Zu", "Zp1"] + tcoords = ["time_midp"] + uvars = zcoords + tcoords # u-points + vvars = zcoords + tcoords # v-points + gvars = zcoords + tcoords # corner points + cvars = zcoords + tcoords + for var in varlist: + if set(["Xp1", "Y"]).issubset(_ds[var].dims): + uvars.append(var) + if set(["Xp1", "Yp1"]).issubset(_ds[var].dims): + gvars.append(var) + if set(["Yp1", "X"]).issubset(_ds[var].dims): + vvars.append(var) + if set(["Y", "X"]).issubset(_ds[var].dims): + cvars.append(var) + + dim_arg = {_dim_name: moor} + iXn = iX.isel(**dim_arg) # + iYn = iY.isel(**dim_arg) # + + if face1 == 6 and face2 == 7: + args = {"xp1": slice(1)} # used by both + rename = {"x": "xp1"} + revar = "xp1" + iXp1n = iXp1.isel(**dim_arg, **args) + iYp1n = iYp1.isel(**dim_arg) + iargs = {"Y": iYn, "Yp1": iYp1n, "Xp1": iXp1n - _Nx} + # sample from next face + vds = _ds.isel(face=face2, **iargs) + vds = vds.reset_coords()[uvars + gvars] + # get the rest of the points + argsn = {"face": face1, "X": iXn, "Y": iYn, "Xp1": iXp1n, "Yp1": iYp1n} + mds = _ds.isel(**argsn).reset_coords() # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) + mds = reset_dim(mds, 1, revar) + ugmds = _xr.combine_by_coords([mds[uvars + gvars], vds]) + + cvmds = mds.reset_coords()[cvars + vvars] + nds = _xr.combine_by_coords([cvmds, ugmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} + nds = nds.rename_dims(rename).rename_vars(rename) + nds = rotate_vars(nds) + + for _varName in nds.variables: + if "mate" in nds[_varName].attrs: + _dims = nds[_varName].dims + if _varName not in co_list and "Yp1" in _dims: + nds[_varName] = -nds[_varName] + if _varName == "CS": + nds[_varName] = -nds[_varName] + + if face1 == 6 and face2 == 10: + # have to redefine iXp1 in decreasing order + iXp1 = DataArray( + _np.stack((_ix, _ix + 1)[::-1], 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = {"yp1": slice(1)} + rename = {"y": "yp1"} + + iXp1n = iXp1.isel(**dim_arg) + iYp1n = iYp1.isel(**dim_arg, **args) + iargs = {"Xp1": iYn - _Nx, "Y": _Nx - iXn, "Yp1": _Nx - iXp1n + 1} + dds = rotate_vars(_ds.reset_coords())[vvars + gvars] # v and g variables + + # sample from the next face + vds = dds.isel(face=face2, **iargs) + vds = vds.rename_dims({"y": "yp1"}).rename_vars({"y": "yp1"}) + vds = vds.drop_vars(["Xp1", "Y", "Yp1"]) + if "face" in vds.data_vars: # pragma: no cover + vds = vds.drop_vars(["face"]) + for var in vds.reset_coords().data_vars: + vds[var].attrs = {} # remove metadata for now + + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn) # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) # always drop these + mds = reset_dim(mds.reset_coords(), 1, "yp1") + if "face" in mds.data_vars: # pragma: no cover + mds = mds.drop_vars(["face"]) + + vgmds = _xr.combine_by_coords([mds[vvars + gvars], vds]) + + # get rest of u and center data + cumds = mds.reset_coords()[cvars + uvars] + nds = _xr.combine_by_coords([cumds, vgmds]) + nds = nds.set_coords( + [var for var in nds.data_vars if "time" not in nds[var].dims] + ) + + rename = {"x": "X", "xp1": "Xp1", "yp1": "Yp1", "y": "Y"} + nds = nds.rename_dims(rename).rename_vars(rename) + + for _varName in nds.variables: + if "mate" in nds[_varName].attrs: + _dims = nds[_varName].dims + if _varName not in co_list and ("Yp1" in _dims or "Xp1" in _dims): + nds[_varName] = -nds[_varName] + if _varName == "SN": + nds[_varName] = -nds[_varName] + if _varName == "CS": + nds[_varName] = -nds[_varName] + + if face1 == 2 and face2 == 6: + iXp1 = DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + args = {"yp1": slice(1)} + rename = {"y": "yp1"} + iXp1n = iXp1.isel(**dim_arg) + iYp1n = iYp1.isel(**dim_arg, **args) + iargs = {"Xp1": iYn - _Nx, "Y": _Nx - iXn, "Yp1": _Nx - iXp1n + 1} + dds = rotate_vars(_ds)[vvars + gvars] # v and g variables + + # sample from the next face + vds = dds.isel(face=face2, **iargs) + nvds = vds.rename_dims({"y": "yp1"}).rename_vars({"y": "yp1"}) + nvds = reset_dim(nvds, 1, "yp1") + nvds = nvds.drop_vars(["Xp1", "Y", "Yp1"]) + for var in nvds.reset_coords().data_vars: + nvds[var].attrs = {} # remove metadata for now + + # evaluate at edge of present face -- missing Yp1 data + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn) # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) # always drop these + # combine to create complete, edge data at v and g points + vgmds = _xr.combine_by_coords([mds[vvars + gvars], nvds]) + + # get rest of u and center data + cumds = mds.reset_coords()[cvars + uvars] + nds = _xr.combine_by_coords([cumds, vgmds]) + nds = nds.set_coords( + [var for var in nds.data_vars if "time" not in nds[var].dims] + ) + rename = {"x": "X", "xp1": "Xp1", "yp1": "Yp1", "y": "Y"} + nds = nds.rename_dims(rename).rename_vars(rename) + + for var in nds.reset_coords().data_vars: + nds[var].attrs = {} + + if face1 == 5 and face2 == 6: + args = {"yp1": slice(1)} + rename = {"y": "yp1"} + iXp1n = iXp1.isel(**dim_arg) + iYp1n = iYp1.isel(**dim_arg, **args) + iargs = {"X": iXn, "Xp1": iXp1n, "Yp1": iYp1n - _Nx} + revar = "yp1" + vds = _ds.isel(face=face2, **iargs) + vds = vds.reset_coords()[vvars + gvars] + # get the rest of the points + argsn = { + "face": face1, + "X": iXn, + "Y": iYn, + "Xp1": iXp1n, + "Yp1": iYp1n, + } + mds = _ds.isel(**argsn).reset_coords() # regular eval + mds = mds.drop_vars(["Yp1", "Xp1", "X", "Y"]) + vds = reset_dim(vds, 1, revar) + vgmds = _xr.combine_by_coords([mds[vvars + gvars], vds]) + + cumds = mds.reset_coords()[cvars + uvars] + nds = _xr.combine_by_coords([cumds, vgmds]) + co_list = [var for var in nds.data_vars if "time" not in nds[var].dims] + nds = nds.set_coords(co_list) + rename = {"x": "X", "y": "Y", "xp1": "Xp1", "yp1": "Yp1"} + nds = nds.rename_dims(rename).rename_vars(rename) + + nds = _xr.merge([nds, ds1D]) + + return nds + + +def face_direction(face1, face2, face_connections): + """ + from the topology `face_connections`, infers the direction + of the array: `left (0)`, `right (1)`, `bottom (2)`, `top (3)`. + """ + left, right = face_connections[face1]["X"] + bot, top = face_connections[face1]["Y"] + + perimeter = [] + for edge in [left, right, bot, top]: + if edge is not None: + perimeter.append(edge[0]) + if edge is None: # faces 0, 3, 9, 12 + perimeter.append(edge) + + if set([face2]).issubset(perimeter): + return perimeter.index(face2) + else: + if face1 == face2: + raise ValueError("faces {} and {} must be different.".format(face1, face2)) + else: + raise ValueError("faces {} and {} are not contiguous.".format(face1, face2)) + + +def splitter(_ix, _iy, _ifaces): + """ + Takes the output from `connector(_ix, _iy)` as input, and splits it into + the many faces the array grows through. The numner of faces is determine + by the array `_ifaces`, or equal length as each element of `connector()`. + Then `ifaces` has the same element, there is only one face (or simple + topology), and the output is a list of len == 1. + """ + + # identify if and where there is a change in face + ll = _np.where(abs(_np.diff(_ifaces)))[0] + + X0, Y0 = [], [] + for ii in range(len(ll) + 1): + if ii == 0: + x0, y0 = _ix[: ll[ii] + 1], _iy[: ll[ii] + 1] + if ii > 0 and ii < len(ll): + x0, y0 = ( + _ix[ll[ii - 1] + 1 : ll[ii] + 1], + _iy[ll[ii - 1] + 1 : ll[ii] + 1], + ) + if ii == len(ll): + x0, y0 = _ix[ll[ii - 1] + 1 :], _iy[ll[ii - 1] + 1 :] + X0.append(x0) + Y0.append(y0) + return X0, Y0 + + +def edge_completer(_x, _y, face_dir=None, ind=-1, _N=89): + """verifies that an array begins and ends at the edge of a face. + + Parameters: + ---------- + + _x, _y: list, list + indexes of morring array in logical space. + face_dir: int + output of `od.llc_rearrange.face_direction. Indicates the direction + towards which the left endpoint of (mooring) array must reach the + edge of face. + ind: int, 0 or -1 (default). + indicates the index of the (mooring) array. + _N: int, default=89. + last index of each faceted dimension. (len(X)-1). + """ + + if face_dir == 1: # towards local right in x (increase x-index) + _mx, _my = connector([_x[ind], _N], [_y[ind], _y[ind]]) + if ind == -1: + _x, _y = _np.append(_x, _mx), _np.append(_y, _my) + if ind == 0: + _x, _y = _np.append(_mx[::-1], _x), _np.append(_my, _y) + if face_dir == 0: # towards local left in x (increase x-index) + _mx, _my = connector([0, _x[ind]], [_y[ind], _y[ind]]) + if ind == 0: + _x, _y = _np.append(_mx, _x), _np.append(_my, _y) + if ind == -1: + _x, _y = _np.append(_x, _mx[::-1]), _np.append(_y, _my) + if face_dir == 3: # towards local right in y + _mx, _my = connector([_x[ind], _x[ind]], [_y[ind], _N]) + if ind == -1: + _x, _y = _np.append(_x, _mx), _np.append(_y, _my) + if ind == 0: + _x, _y = _np.append(_mx, _x), _np.append(_my[::-1], _y) + if face_dir == 2: + _mx, _my = connector([_x[ind], _x[ind]], [0, _y[ind]]) + if ind == 0: + _x, _y = _np.append(_mx, _x), _np.append(_my, _y) + if ind == -1: # last entry + _x, _y = _np.append(_x, _mx), _np.append(_y, _my[::-1]) + + mask = _np.abs(_np.diff(_x)) + _np.abs(_np.diff(_y)) == 0 + _x, _y = (_np.delete(ii, _np.argwhere(mask)) for ii in (_x, _y)) + + return _x, _y + + +def edge_slider(x1, y1, f1, x2, y2, f2, face_connections, _N=89): + """ + Looks at the edge points between faces f1 (present) + and f2 (next). Returns a point in f1 that is aligned + with the first element in f2. + + Parameters: + ---------- + [x1, y1, f1]: list of integers. + Present face (`f1`) coordinates. + [x2, y2, f2] : list of integers. + Next face (`f2`) coordinates + face_connections: dict. + topology of grid. + _N: int + last index along `X` or `Y` + + Returns: + newP: list + It's elements are int values for present face `f1` + """ + # cannot handle upper right corner (with 3 face data). + crns = [] + for p in [[_N, _N]]: + crns.append(p == [x1, y1]) + if crns.count(True): + # TODO: check if this is an actual problem + raise ValueError("`[x1, y1]` can not be on a face corner") + + rotS = _np.arange(7, 13) + nrotS = _np.arange(6) + arc = _np.array([6]) + # it only matters is one case. + fdir = face_direction(f1, f2, face_connections) + + # see if array left-ends (at 0) or right-ends (at len(ds.X)-1) + set0 = set([x1, y1]) + ind0, ind1 = set([0]).issubset(set0), set([_N]).issubset(set0) + # identify the local axis at which the array ends + if ind0: + i = (x1, y1).index(0) + if ind1: + i = (x1, y1).index(_N) + + if set([6, 7]) == set([f1, f2]): + # match in y. No shift necessary + new_P = [x2, y2] + new_P[i] = [x1, y1][i] + if set([6, 2]) == set([f1, f2]): + if fdir == 3: + new_P = [x2, _N - y2][::-1] + new_P[i] = [x1, y1][i] + else: + new_P = [_N - x2, y2][::-1] + new_P[i] = [x1, y1][i] + if set([6, 5]) == set([f1, f2]): + new_P = [x2, y2] + new_P[i] = [x1, y1][i] + if set([6, 10]) == set([f1, f2]): + if fdir == 0: + new_P = [_N - x2, y2][::-1] + new_P[i] = [x1, y1][i] + else: + new_P = [x2, _N - y2][::-1] + new_P[i] = [x1, y1][i] + if arc[0] not in [f1, f2]: + if set([f1, f2]).issubset(rotS) or set([f1, f2]).issubset(nrotS): + new_P = [x2, y2] + new_P[i] = [x1, y1][i] + else: + new_P = [a - b for a, b in zip(2 * [_N], [x2, y2][::-1])] + new_P[i] = [x1, y1][i] + return new_P + + +def fill_path(_X, _Y, _faces, k, _face_conxs, _N=89): + """ + Given a sequence of index arrays (each within a face) + makes sure that it always begins and ends at the face edge, expend + the end faced-data which can either end or begin at the face edge. To be + used when len(_faces)>1. Otherwise, use `connector`. + + Parameters: + ---------- + X, Y: each 1d array-like of ints + len(X) == len(Y) >= 1 + face: 1d array-like. + len(face)==len(X)>1. Identifies which face the array is sampling + from + k: int + identifies the kth-array pair (X, Y) with kth-face. + _N: int + Length of x- or y- dimension. Default is 89, associated with + TODO: + + incorporate the changes above. + """ + # import numpy as _np + + Ntot = len(_faces) + x, y = connector(_X[k], _Y[k]) + + # if Ntot > 1: # there is + + # ASSUMPTION: + # Array normally increases monotonically with i and j at its end points. + # Under such assumption, the 1st faceted array always is completed at its + # right end point `index = -1`, but NOT at its left end point `index=0`. + # To generalize, I need to include an option that allows the first array + # (`k=0`) to be completed ONLY at the `index=0`, and the last faceted + # array (`k=-1`) to be completed. The rest of the + + if k == 0: + # Under assumption, this always happens with first Face. But it does + # NOT happen with last face + # k=-1. + dir1 = face_direction( + _faces[k], _faces[k + 1], _face_conxs + ) # right end of array + + x, y = edge_completer(x, y, face_dir=dir1, ind=-1, _N=_N) + x1, y1 = connector(_X[k + 1], _Y[k + 1]) + dir2 = face_direction( + _faces[k + 1], _faces[k], _face_conxs + ) # check direction to complete its `index=0` + x1, y1 = edge_completer( + x1, y1, face_dir=dir2, ind=0, _N=_N + ) # include the indedx =0 and the face_direction. + + P = edge_slider( + x[-1], y[-1], _faces[k], x1[0], y1[0], _faces[k + 1], _face_conxs, _N + ) + + x, y = connector(_np.append(x, P[0]), _np.append(y, P[1])) + + if k > 0 and k < Ntot - 1: + # interior faces - aalways get completed to left and right. + dir1 = face_direction( + _faces[k], _faces[k + 1], _face_conxs + ) # right end of array + + x, y = edge_completer(x, y, face_dir=dir1, ind=-1, _N=_N) + + # if not first of array, also complete towards beginning of array + dir0 = face_direction( + _faces[k], _faces[k - 1], _face_conxs + ) # check direction to complete `index=0` + # with previous face. + x, y = edge_completer(x, y, face_dir=dir0, ind=0, _N=_N) + + # check next face, and how it intersect face edge to its left. + + x1, y1 = connector(_X[k + 1], _Y[k + 1]) + dir2 = face_direction( + _faces[k + 1], _faces[k], _face_conxs + ) # check direction to complete its `index=0` + x1, y1 = edge_completer( + x1, y1, face_dir=dir2, ind=0, _N=_N + ) # include the indedx =0 and the face_direction. + + P = edge_slider( + x[-1], y[-1], _faces[k], x1[0], y1[0], _faces[k + 1], _face_conxs, _N + ) + + x, y = connector(_np.append(x, P[0]), _np.append(y, P[1])) + + if k == Ntot - 1: + # last faceted array. Under present assumption, need to + # complete the `index=0` but NOT `index=-1`. + dir0 = face_direction( + _faces[k], _faces[k - 1], _face_conxs + ) # check direction to complete `index=0` + # with previous face. + x, y = edge_completer(x, y, face_dir=dir0, ind=0, _N=_N) + + return x, y + + +def face_adjacent(_ix, _iy, _iface, _face_connections, _N=89): + """ + Given a collection of data points within a face, returns the adjacent + face next to boundary data. If data does not eval at the + boundary between two faces, returns -1. + + Parameters: + ---------- + _ix: 1d array-like, int data + _iy: 1d array-like. int data + _iface: int + face index value where array lives. + _face_connections: dict + contains topology of data. + _N: int. default=89 (ECCO) + last index along i or j index in faceted data. + """ + adj_faces = [] + fleft, fright = _face_connections[_iface]["X"] + fbot, ftop = _face_connections[_iface]["Y"] + + for i in range(len(_ix)): + loc_data = -1 # initialize -- implies do edge data + + set0 = set([_ix[i], _iy[i]]) + ind0, ind1 = set([0]).issubset(set0), set([_N]).issubset(set0) + + if ([_ix[i], _iy[i]]).count(_N) > 1: + raise ValueError( + "OceanSpy cannot subsample data from upper right corner of a face" + ) + + if ind0: + k = ([_ix[i], _iy[i]]).index(0) + if k > 0: + loc_data = 2 + else: + loc_data = 0 + if ind1: + k = ([_ix[i], _iy[i]]).index(_N) + if k > 0: + loc_data = 3 + else: + loc_data = 1 + + if loc_data == 0: + adj_faces.append(fleft[0]) + if loc_data == 1: + if fright is not None: + adj_faces.append(fright[0]) + else: + adj_faces.append(-1) # singularity south pole. + if loc_data == 2: + if fbot is not None: + adj_faces.append(fbot[0]) + else: + adj_faces.append(-1) # singularity south pole. + if loc_data == 3: + adj_faces.append(ftop[0]) + if loc_data == -1: + adj_faces.append(loc_data) + return adj_faces + + +def edgesid(_iX, _iY, _N=89): + """ + From an array of isolated logical indexes within a face, extracts the ones + that lie at the edge between one or more faces. It also removes repeated + entries from input array. This function does not preserve the ordering of + the data. + """ + unique = set(tuple([_iX[i], _iY[i]]) for i in range(len(_iX))) + _iX = _np.array([list(unit)[0] for unit in unique]) + _iY = _np.array([list(unit)[1] for unit in unique]) + + # identify all x-edges, if any + ixe0 = _np.where(_iX == 0)[0] + ixe1 = _np.where(_iX == _N)[0] + # y-edges, if any + iye0 = _np.where(_iY == 0)[0] + iye1 = _np.where(_iY == _N)[0] + _index = list(ixe0) + list(ixe1) + list(iye0) + list(iye1) + + return _iX, _iY, _index + + +def index_splitter(ix, iy, _N): + """ + Takes the index pair (ix, iy) of ordered, continuous and equidistant + (unit) distanced array, and identifies the location at which the pair + reaches the edge of the face and reenters the same face (no crossing). + The edge of the face is identified by `_N`, the last index along each + dimention. If array only reches edge of face at end points, then returns + empty list. This allows to split the array while preserving its original + order. + """ + nI = [] # indexes of partition + Nx = len(ix) + + iix = _np.where(ix == _N)[0] + iiy = _np.where(iy == _N)[0] + + if iix.shape[0] + iiy.shape[0] > 0: + Ii = [] # there is right-edged data. + if iix.shape[0] > 0: + xb = _np.where(_np.diff(iix) > 1)[0] + else: + xb = [] + if iiy.shape[0] > 0: + yb = _np.where(_np.diff(iiy) > 1)[0] + else: + yb = [] + + if len(yb) == 0 and len(iiy) > 0: # only one set of edge data + Ii.append(list(iiy)) + if len(yb) > 0: + for k in range(len(yb) + 1): + if k == 0: + Ii.append(list(iiy[: yb[k] + 1])) + if k > 0 and k < len(yb): + Ii.append(list(iiy[yb[k - 1] + 1 : yb[k] + 1])) + if k == len(yb): + Ii.append(list(iiy[yb[k - 1] + 1 :])) + if len(xb) == 0 and len(iix) > 0: + Ii.append(list(iix)) + if len(xb) > 0: + for k in range(len(xb) + 1): + if k == 0: + Ii.append(list(iix[: xb[k] + 1])) + if k > 0 and k < len(xb): + Ii.append(list(iix[xb[k - 1] + 1 : xb[k] + 1])) + if k == len(xb): + Ii.append(list(iix[xb[k - 1] + 1 :])) + + if len(xb) + len(yb) > 0: + i0 = [Ii[k][0] for k in range(len(Ii))] + ii = _np.argsort(i0) # order + + for k in range(len(ii)): + endpoint = set([Nx - 1]).issubset(Ii[ii[k]]) + origin = set([0]).issubset(Ii[ii[k]]) + if not endpoint and not origin: + nI.append(Ii[ii[k]]) + return nI + + +def order_from_indexing(_ix, _in): + """Given an array of bounded integers (indexing array), and a list of + indexes that subsets the indexing array, returns the mapping associated + with the subsetting array. + """ + Nn = len(_in) + nx = [] + if Nn == 0: # preserves original data + mI = [] # there is no mapping/no data at edge of face + nx = _ix + if Nn > 0: # there is edge data. + nx = [_ix[: _in[0][0]]] + for jj in range(1, Nn): + nx.append(_ix[_in[jj - 1][0] : _in[jj - 1][-1] + 1]) + nx.append(_ix[_in[jj - 1][-1] + 1 : _in[jj][0]]) + nx.append(_ix[_in[-1][0] : _in[-1][-1] + 1]) + nx.append(_ix[_in[-1][-1] + 1 :]) + + mI = [[k for k in range(len(nx[0]))]] + for ii in range(1, len(nx)): + val = mI[ii - 1][-1] + 1 + mI.append(list([val + k for k in range(len(nx[ii]))])) + return mI, nx + + +def ds_splitarray( + _ds, _iXn, _iYn, _faces, _iface, _nI, _face_connections, _dim_name="mooring" +): + """ + Creates a dataset from an array that reaches the edges of the face/tile + once or multiple times, without crossing into a different face, but can + end or begin at the edge of the face (which is to be interpreted more + generally as crossing from or into a different face) + """ + + # construct entire index mapper that reconstructs iXn from broken array (nI) + _ni, _ = order_from_indexing(_iXn, _nI) + if len(_faces) == 1: + # single face with multiple edge connections + fdir = 0 + else: + if _iface < len(_faces) - 1: + fdir = face_direction(_faces[_iface], _faces[_iface + 1], _face_connections) + else: # last face index=0 at far right. + fdir = face_direction(_faces[_iface - 1], _faces[_iface], _face_connections) + + # construct a list of adjacent faces where array does not end. + adj_faces = [] + for ii in range(len(_nI)): + # sample single point. + nx, ny, face = _iXn[_nI[ii][:1]], _iYn[_nI[ii][:1]], _faces[_iface] + afaces = face_adjacent(nx, ny, face, _face_connections) + adj_faces.append(afaces) + + j = 0 # counter for face eval. + eds = [] # each item will be a dataset + for i in range(len(_ni)): # parallelize this. It could take some time. + if i % 2 == 0: + if i in [0, len(_ni) - 1]: + nds, connect, moor, *a = ds_edge( + _ds, _iXn[_ni[i]], _iYn[_ni[i]], _faces, _iface, _face_connections + ) + if connect: # subarry end at right edge + if len(moor) == 0 or fdir in [0, 2]: + # array ends at 0 index + nnx, nny = ( + _iXn[_ni[i]][moor[-1] + 1 :], + _iYn[_ni[i]][moor[-1] + 1 :], + ) + ds0 = eval_dataset( + _ds, nnx, nny, _iface=_faces[_iface], _dim_name=_dim_name + ) + shift = len(nds.mooring) + ds0 = reset_dim(ds0, shift, _dim_name) + nds = _xr.combine_by_coords([nds, ds0]) + else: + nnx, nny = _iXn[_ni[i]][: moor[0]], _iYn[_ni[i]][: moor[0]] + ds0 = eval_dataset( + _ds, nnx, nny, _iface=_faces[_iface], _dim_name=_dim_name + ) + nds = _xr.combine_by_coords([ds0, nds]) + del ds0 + else: # safe to eval everywhere + nnx, nny = _iXn[_ni[i]], _iYn[_ni[i]] + nds = eval_dataset( + _ds, nnx, nny, _iface=_faces[_iface], _dim_name=_dim_name + ) + else: + nnx, nny = _iXn[_ni[i]], _iYn[_ni[i]] + nds = eval_dataset( + _ds, nnx, nny, _iface=_faces[_iface], _dim_name=_dim_name + ) + else: + nds, *a = ds_edge( + _ds, + _iXn[_ni[i]], + _iYn[_ni[i]], + [_faces[_iface]] + adj_faces[j], + 0, + _face_connections, + ) + j += 1 # update the count for eval at a face edge + if i > 0: + shift = int(eds[i - 1].mooring.values[-1]) + 1 + nds = reset_dim(nds, shift) + eds.append(nds) + dsf = _xr.combine_by_coords(eds).chunk({_dim_name: len(_iXn)}) + del eds + return dsf + + +def fdir_completer(_ix, _iy, _faces, _iface, _Nx, _face_connections): + """completes the next directional face , whether the face is defined + within the path of the array, or if the next face eval is an adjacent + face. This matters when the arrays ends of beginnins at an endpoint + """ + if _iface < len(_faces) - 1: + fdir = face_direction(_faces[_iface], _faces[_iface + 1], _face_connections) + else: # last face array (fdir may not matter) + _idx, _idy, _index = edgesid(_ix, _iy, _Nx) + if len(_index) == 0: + # no edge data + fdir = None + else: + # infer the direction from face topology. + aface = face_adjacent(_ix, _iy, _faces[_iface], _face_connections) + fdir = face_direction(_faces[_iface], aface[0], _face_connections) + return fdir -class Dims: +def mooring_singleface(_ds, _ix, _iy, _faces, _iface, _face_connections): + """ + evaluates the mooring array within a single face. + """ + _Nx = len(_ds.X) - 1 + _ixn, _iyn = connector(_ix, _iy) + nI = index_splitter(_ixn, _iyn, _Nx) + if len(nI) > 0: + # data reaches edge of face, but reenters. Need to split intp + # subarrays in order to eval corner/vel points at adjacent + # face which is NOT necessarily next in ordered sequence array. + args = { + "_ds": _ds, + "_iXn": _ixn, + "_iYn": _iyn, + "_nI": nI, + "_faces": _faces, + "_iface": _iface, + "_face_connections": _face_connections, + "_dim_name": "mooring", + } + dsf = ds_splitarray(**args) + else: + # no need to split into subarrays + iix = _np.where(_ixn == _Nx)[0] + iiy = _np.where(_iyn == _Nx)[0] + + if iix.size + iiy.size == 0: + # array does not end at right edge + dsf = eval_dataset(_ds, _ixn, _iyn, _faces[_iface], _dim_name="mooring") + else: + # there is at least one right-edge point + # must split into subarray (edge+interior) + DSt = [] + nds, connect, moor, moors, *a = ds_edge( + _ds, _ixn, _iyn, _faces, _iface, _face_connections + ) + + # check twice-appearing right ends (same axis or different) + if len(moors) == 1: + # array reaches right edge once along either `x` or `y`, + # need to check it arrays begins and ends same index eval + diffm = _np.diff(nds.mooring) + jump = _np.argwhere(abs(diffm) != 1) + if jump.size: # two right-end points + moor = jump + ds2 = nds.isel( + mooring=slice(int(moor[-1]) + 1, len(nds.mooring) + 1) + ) + moor2 = ds2.mooring.values[0] + nds = nds.isel(mooring=slice(int(moor[-1]) + 1)) # 1st end point + DSt.append(ds2) + elif len(moors) == 2: + # array ends/begins at a right edge at different axes. + jump = _np.array([]) # no repeated ends + # `ds_edge` can only extract edged-data from a single axis + # at a time. need to evaluate again. + if (moors[0].values == moor).all(): + # the `x` axis was picked in previous eval. + kwargs = {"axis": "y"} # need y-axis endpoint + _ind = moors[1].mooring.values[0] + else: + kwargs = {"axis": "x"} + # select adjacent face to index `_ind`. + new_face = face_adjacent( + [_ixn[_ind]], [_iyn[_ind]], _faces[_iface], _face_connections + ) + present_face = 0 + dst, *a = ds_edge( + _ds, + _ixn, + _iyn, + [_faces[_iface]] + new_face, + present_face, + _face_connections, + **kwargs, + ) + # from the two edge evals - I need to order them + moor_a, moor_b = moor, dst.mooring.values + ds_a, ds_b = nds, dst + ind1 = [moor_a.min(), moor_b.min()].index( + min([moor_a.min(), moor_b.min()]) + ) + ind2 = [moor_a.min(), moor_b.min()].index( + max([moor_a.min(), moor_b.min()]) + ) + moor = [moor_a, moor_b][ind1] + moor2 = [moor_a, moor_b][ind2][0] # only care ab out first element + # can now order the datasets with edge data + nds = [ds_a, ds_b][ind1] # mooring near zero + ds2 = [ds_a, ds_b][ind2] # mooring near end + DSt.append(ds2) + DSt.append(nds) + + # get interior points + if connect: + shift = None + _eval = True + if jump.size or len(moors) > 1: + # interior inbetween two right edge points + nnx, nny = ( + _ixn[int(moor[-1]) + 1 : moor2], + _iyn[int(moor[-1]) + 1 : moor2], + ) + shift = len(nds.mooring) # shift from 0 + elif len(_ixn) == len(moor): + # No interior point + DS0, _eval = [], False + else: + if 0 in moor: + # edge of array towards beginning of array + nnx, nny = _ixn[int(moor[-1]) + 1 :], _iyn[int(moor[-1]) + 1 :] + shift = len(nds.mooring) + else: + # edge of array towards end - interior before + nnx, nny = _ixn[: int(moor[0])], _iyn[: int(moor[0])] + if _eval: + ds0 = eval_dataset( + _ds, nnx, nny, _iface=_faces[_iface], _dim_name="mooring" + ) + if shift is not None: + ds0 = reset_dim(ds0, shift, "mooring") + DS0 = [ds0] + DSt = DSt + DS0 + dsf = _xr.combine_by_coords(DSt) + del nds, DS0, DSt + + if "face" in dsf.reset_coords().data_vars: + dsf = dsf.drop_vars(["face"]) + return dsf, _ixn, _iyn + + +def station_singleface(_ds, _ix, _iy, _faces, _iface, _face_connections): + """Extracts isolated station values from dataset from the given horizontal + index values (`iface`, '_iy', '_ix'). These are not ordered as the original + coords. + """ + shift = True + iX, iY, ind = edgesid(_ix, _iy) + # get edge data + eX, eY = iX[ind], iY[ind] + # remove from original array + iX, iY = _np.delete(iX, ind), _np.delete(iY, ind) + # data with index=0 somewhere is safe to eval at current face. + # find such data and restore it to original index array + aface = face_adjacent(eX, eY, _faces[_iface], _face_connections) + directions = _np.array( + [ + face_direction(_faces[_iface], aface[i], _face_connections) + for i in range(len(aface)) + ] + ) + dirs = [] + if set([0]).issubset(directions): # these can safely be eval at face + dirs += list([item[0] for item in _np.argwhere(directions == 0)]) + if set([2]).issubset(directions): + dirs += list([item[0] for item in _np.argwhere(directions == 2)]) + neX, neY = ( + eX[dirs], + eY[dirs], + ) + eX, eY, aface = ( + _np.delete(eX, dirs), + _np.delete(eY, dirs), + _np.delete(_np.array(aface), dirs), + ) + iX, iY = _np.append(iX, neX), _np.append(iY, neY) + dsf = eval_dataset(_ds, iX, iY, _faces[_iface], _dim_name="station") + if iX.size == 0: + shift = None + if eX.shape[0] > 0: + # evaluate at edge of between faces. need adjascent face and appropriate indexes + DSe = [] + ii = 0 + for adjface in set(aface): + aind = _np.where(aface == adjface)[0] + dse, *a = ds_edge( + _ds, + eX[aind], + eY[aind], + [_faces[_iface]] + [adjface], + 0, + _face_connections, + _dim="station", + ) + if ii > 0: + shift = int(DSe[ii - 1]["station"].values[-1]) + 1 + dse = reset_dim(dse, shift, dim="station") + DSe.append(dse) + ii += 1 + dse = _xr.combine_by_coords(DSe) + del DSe + if shift is None: + # no interior point. only edge data + dsf = dse + else: + shift = int(dsf["station"].values[-1]) + 1 + dse = reset_dim(dse, shift, dim="station") + dsf = _xr.combine_by_coords([dsf, dse]) + + return dsf + + +def cross_face_diffs(_ds, _ix, _iy, _faces, _iface, _face_connections): + """computes the unit distance between the location of index spaces in + both directions diffX and diffY when data has complex topology. + + Parameters: + ---------- + _ds: xarray.Dataset + contains `face`, and original dataset. + _ix, _iy: 1d-array like. + elements are int values. Output from `connector()`, whch + _faces: list + contains the face indexes of the ordered track. len()>=1 + _iface: int + index of current face. + _face_connection: dict + face topology. + returns + diffX: 1D array-like + diffY: 1D array-like + """ + + # exclude the arctic for now + Rot = _np.arange(7, 13) + + # define all 4 unit vectors defining crossing from face i to face i+1 + # inherits face topo (ordering), and assumes that of non rot faces. + # format: [[xvec, yvec], [.], ...] and inherets logics from `face_directions` + fdirs_options = [[-1, 0], [1, 0], [0, -1], [0, 1]] + + diffX, diffY = _np.diff(_ix), _np.diff(_iy) + + if _faces[_iface] in Rot: # correct for topology + # redefine options with corrected topology + # keep same result from `face_direction` + fdirs_options = [[0, 1], [0, -1], [-1, 0], [1, 0]] + # create copy and rotate + ndiffX, ndiffY = _copy.deepcopy(diffX), _copy.deepcopy(diffY) + diffX = ndiffY + diffY = -ndiffX + + if _faces[_iface] == 6: + # arctic array + fdirs_options = [[0, -1], [0, -1], [0, -1], [0, -1]] + diffX, diffY, *a = arct_diffs(_ds, _ix, _iy) + + # get direction between the edge point of present face + # only when there is another face. + if _iface < len(_faces) - 1: + # local face direction for next face + fdir = face_direction(_faces[_iface], _faces[_iface + 1], _face_connections) + # when crossing into other face - get logical dir vectors + tdiffx, tdiffy = fdirs_options[fdir] + diffX, diffY = _np.append(diffX, tdiffx), _np.append(diffY, tdiffy) + else: + tdiffx, tdiffy = _np.array([]), _np.array([]) + + return diffX, diffY, _np.array([tdiffx]), _np.array([tdiffy]) + + +def arct_diffs(_ds, _Xind, _Yind): + _Nx = len(_ds.X) - 1 + + # define triangular areas that split the arctic + XR5 = Polygon([(0, -1), (0, 0), (_Nx / 2, _Nx / 2), (_Nx, 0), (_Nx, -1)]) + XR7 = Polygon( + [(_Nx + 1, 0), (_Nx, 0), (_Nx / 2, _Nx / 2), (_Nx, _Nx), (_Nx + 1, _Nx)] + ) + XR10 = Polygon( + [(0, _Nx + 1), (0, _Nx), (_Nx / 2, _Nx / 2), (_Nx, _Nx), (_Nx, _Nx + 1)] + ) + XR2 = Polygon([(-1, _Nx), (0, _Nx), (_Nx / 2, _Nx / 2), (0, 0), (-1, 0)]) + + # define a small polygon that contains the theoretical line + # dividing the areas above + + lower_left = Polygon( + [ + (0, 3), + ((_Nx + 1) // 2 - 3, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2 - 3), + (3, 0), + (0, 0), + ] + ) + lower_right = Polygon( + [ + ((_Nx + 1) // 2, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2 - 3), + (_Nx - 3, 0), + (_Nx, 0), + (_Nx, 3), + ((_Nx + 1) // 2 + 3, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2), + ] + ) + upper_right = Polygon( + [ + ((_Nx + 1) // 2, (_Nx + 1) // 2), + ((_Nx + 1) // 2 + 3, (_Nx + 1) // 2), + (_Nx, _Nx - 3), + (_Nx, _Nx), + (_Nx - 3, _Nx), + ((_Nx + 1) // 2, (_Nx + 1) // 2 + 3), + ] + ) + upper_left = Polygon( + [ + (0, _Nx), + (0, _Nx - 3), + ((_Nx + 1) // 2 - 3, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2), + ((_Nx + 1) // 2, (_Nx + 1) // 2 + 3), + (3, _Nx), + ] + ) + + def _mask_array(iX, iY, polygon): # pragma no cover + mask = [] + for i in range(len(iX)): + point = Point(iX[i], iY[i]) + mask.append(polygon.contains(point)) + return _np.array(mask).nonzero()[0] + + # define masks + maskR5 = _mask_array(_Xind, _Yind, XR5) + maskR7 = _mask_array(_Xind, _Yind, XR7) + maskR10 = _mask_array(_Xind, _Yind, XR10) + maskR2 = _mask_array(_Xind, _Yind, XR2) + + # applu masks and consolidate points + niXR2 = _Xind[maskR2] + niYR2 = _Yind[maskR2] + setR2 = set(tuple((niXR2[i], niYR2[i])) for i in range(len(niYR2))) + + niXR5 = _Xind[maskR5] + niYR5 = _Yind[maskR5] + setR5 = set(tuple((niXR5[i], niYR5[i])) for i in range(len(niYR5))) + + niXR7 = _Xind[maskR7] + niYR7 = _Yind[maskR7] + setR7 = set(tuple((niXR7[i], niYR7[i])) for i in range(len(niYR7))) + + niXR10 = _Xind[maskR10] + niYR10 = _Yind[maskR10] + setR10 = set(tuple((niXR10[i], niYR10[i])) for i in range(len(niYR10))) + + # assert I am capturing all data points + captured_set = setR2.union(setR5).union(setR7).union(setR10) + + ndiffX, ndiffY = [], [] + for i in range(len(_Xind) - 1): + dX = _Xind[i + 1] - _Xind[i] + dY = _Yind[i + 1] - _Yind[i] + pair1 = set(tuple((_Xind[j], _Yind[j])) for j in range(i, i + 1)) + pair2 = set(tuple((_Xind[j + 1], _Yind[j + 1])) for j in range(i, i + 1)) + set_pair = pair1.union(pair2) + if set_pair.issubset(setR5): + # same topology + ndiffX.append(dX) + ndiffY.append(dY) + elif set_pair.issubset(setR10): + # same topo - oposite ordering in both directions. + ndiffX.append(-dX) + ndiffY.append(-dY) + elif set_pair.issubset(setR7): + ndiffX.append(dY) + ndiffY.append(-dX) + elif set_pair.issubset(setR2): + ndiffX.append(-dY) + ndiffY.append(dX) + else: + # edge data - need add place holder value + # for accurate indexing reference + ndiffX.append(None) + ndiffY.append(None) + + # identify the missing index values + miss = [] + for i in range(len(_Xind)): + pair = set(tuple((_Xind[j], _Yind[j])) for j in range(i, i + 1)) + if not pair.issubset(captured_set): + miss.append(i) + + for i in miss: + # forward from c + if i < len(_Xind) - 1: + dXf = _Xind[i + 1] - _Xind[i] + dYf = _Yind[i + 1] - _Yind[i] + pairf = set(tuple((_Xind[j + 1], _Yind[j + 1])) for j in range(i, i + 1)) + else: + pairf = set(tuple((None, None)) for j in range(i, i + 1)) + # behind from c + if i > 0: + dXb = _Xind[i] - _Xind[i - 1] + dYb = _Yind[i] - _Yind[i - 1] + pairb = set(tuple((_Xind[i - 1], _Yind[i - 1])) for j in range(i, i + 1)) + else: + pairb = set(tuple((None, None)) for j in range(i, i + 1)) + + pointc = Point(_Xind[i], _Yind[i]) + + # tried nested if statements, but to incorporate + # end points (non-cyclic) this worked best + + if lower_left.contains(pointc) and pairb.issubset(setR2): + ndiffX[i - 1], ndiffY[i - 1] = -dYb, dXb + if lower_left.contains(pointc) and pairb.issubset(setR5): + ndiffX[i - 1], ndiffY[i - 1] = dXb, dYb + if lower_left.contains(pointc) and pairf.issubset(setR5): + ndiffX[i], ndiffY[i] = dXf, dYf + if lower_left.contains(pointc) and pairf.issubset(setR2): + ndiffX[i], ndiffY[i] = -dYf, dXf + if lower_right.contains(pointc) and pairb.issubset(setR5): + ndiffX[i - 1], ndiffY[i - 1] = dXb, dYb + if lower_right.contains(pointc) and pairb.issubset(setR7): + ndiffX[i - 1], ndiffY[i - 1] = dYb, -dXb + if lower_right.contains(pointc) and pairf.issubset(setR7): + ndiffX[i], ndiffY[i] = dYf, -dXf + if lower_right.contains(pointc) and pairf.issubset(setR5): + ndiffX[i], ndiffY[i] = dXf, dYf + if upper_right.contains(pointc) and pairb.issubset(setR7): + ndiffX[i - 1], ndiffY[i - 1] = dYb, -dXb + if upper_right.contains(pointc) and pairb.issubset(setR10): + ndiffX[i - 1], ndiffY[i - 1] = -dXb, -dYb + if upper_right.contains(pointc) and pairf.issubset(setR10): + ndiffX[i], ndiffY[i] = -dXf, -dYf + if upper_right.contains(pointc) and pairf.issubset(setR7): + ndiffX[i], ndiffY[i] = dYf, -dXf + if upper_left.contains(pointc) and pairb.issubset(setR10): + ndiffX[i - 1], ndiffY[i - 1] = -dXb, -dYb + if upper_left.contains(pointc) and pairb.issubset(setR2): + ndiffX[i - 1], ndiffY[i - 1] = -dYb, dXb + if upper_left.contains(pointc) and pairf.issubset(setR2): + ndiffX[i], ndiffY[i] = -dYf, dXf + if upper_left.contains(pointc) and pairf.issubset(setR10): + ndiffX[i], ndiffY[i] = -dXf, -dYf + return _np.array(ndiffX), _np.array(ndiffY), captured_set, miss + + +class Dims: # pragma: no cover """Creates a shortcut for dimension`s names associated with an arbitrary variable.""" diff --git a/oceanspy/subsample.py b/oceanspy/subsample.py index fe9e5686..7ca6814b 100644 --- a/oceanspy/subsample.py +++ b/oceanspy/subsample.py @@ -15,6 +15,7 @@ import functools as _functools import warnings as _warnings +# import dask import numpy as _np import pandas as _pd @@ -35,8 +36,26 @@ _rename_aliased, ) from .llc_rearrange import LLCtransformation as _llc_trans -from .llc_rearrange import arctic_eval, reset_dim, rotate_vars -from .utils import _rel_lon, _reset_range, circle_path_array, get_maskH +from .llc_rearrange import ( + connector, + cross_face_diffs, + eval_dataset, + fill_path, + flip_v, + mates, + mooring_singleface, + splitter, + station_singleface, +) +from .utils import ( + _rel_lon, + _reset_range, + circle_path_array, + diff_and_inds_where_insert, + get_maskH, + remove_repeated, + reset_dim, +) # Recommended dependencies (private) try: @@ -378,9 +397,9 @@ def cutout( vel_grid = ["XU", "YU", "XV", "YV"] da_list = [var for var in dsnew.reset_coords().data_vars] check = all([item in da_list for item in vel_grid]) - if check: + if check: # pragma: no cover manipulate_coords = {"coordsUVfromG": False} - else: + else: # pragma: no cover manipulate_coords = {"coordsUVfromG": True} new_face_connections = {"face_connections": {None: {None, None}}} @@ -676,35 +695,65 @@ def mooring_array(od, Ymoor, Xmoor, xoak_index="scipy_kdtree", **kwargs): Ymoor = _check_range(od, Ymoor, "Ymoor") Xmoor = _check_range(od, Xmoor, "Xmoor") - # Cutout - if "YRange" not in kwargs: - kwargs["YRange"] = Ymoor - if "XRange" not in kwargs: - kwargs["XRange"] = Xmoor - if "add_Hbdr" not in kwargs: - kwargs["add_Hbdr"] = True - od = od.subsample.cutout(**kwargs) + serial = kwargs.pop("serial", None) - # Add indexes needed for transports - Yind, Xind = _xr.broadcast(od._ds["Y"], od._ds["X"]) - od._ds["Xind"] = Xind.transpose(*od._ds["XC"].dims) - od._ds["Yind"] = Yind.transpose(*od._ds["YC"].dims) - od._ds = od._ds.set_coords(["Xind", "Yind"]) + if serial: + _diffXYs = True + varList = kwargs.pop("varList", None) - # Message - print("Extracting mooring array.") + args = { + "varList": varList, + "Xcoords": Xmoor, + "Ycoords": Ymoor, + "dim_name": "mooring", + } + od = _copy.deepcopy(od) - # Unpack ds - ds = od._ds - # create list of coordinates. - coords = [var for var in ds if "time" not in ds[var].dims] + # indexes needed for transport + Yind, Xind = _xr.broadcast(od._ds["Y"], od._ds["X"]) + Yind = Yind.expand_dims({"face": od._ds["face"]}) + Xind = Xind.expand_dims({"face": od._ds["face"]}) + od._ds["Xind"] = Xind.transpose(*od._ds["XC"].dims) + od._ds["Yind"] = Yind.transpose(*od._ds["YC"].dims) + od._ds = od._ds.set_coords(["Yind", "Xind"]) + + # when passed, od.subsample.statins returns dataset + new_ds, diffX, diffY = od.subsample.stations(**args) + coords = [var for var in new_ds.coords] + + # TODO: need to add Xind, Yind + # needed for transports (via cutout) + + else: + _diffXYs = False + # Cutout + if "YRange" not in kwargs: # pragma: no cover + kwargs["YRange"] = Ymoor + if "XRange" not in kwargs: # pragma: no cover + kwargs["XRange"] = Xmoor + if "add_Hbdr" not in kwargs: # pragma: no cover + kwargs["add_Hbdr"] = True + od = od.subsample.cutout(**kwargs) + + # Add indexes needed for transports + Yind, Xind = _xr.broadcast(od._ds["Y"], od._ds["X"]) + od._ds["Xind"] = Xind.transpose(*od._ds["XC"].dims) + od._ds["Yind"] = Yind.transpose(*od._ds["YC"].dims) + od._ds = od._ds.set_coords(["Xind", "Yind"]) + + # Message + print("Extracting mooring array.") + + # Unpack ds + ds = od._ds + # create list of coordinates. + coords = [var for var in ds if "time" not in ds[var].dims] - ds_grid = ds[["XC", "YC"]] # by convention center point + ds_grid = ds[["XC", "YC"]] # by convention center point - for key, value in ds_grid.sizes.items(): - ds_grid["i" + f"{key}"] = DataArray(range(value), dims=key) + for key, value in ds_grid.sizes.items(): + ds_grid["i" + f"{key}"] = DataArray(range(value), dims=key) - if not ds_grid.xoak.index: if xoak_index not in _xoak.IndexRegistry(): raise ValueError( "`xoak_index` [{}] is not supported." @@ -714,77 +763,39 @@ def mooring_array(od, Ymoor, Xmoor, xoak_index="scipy_kdtree", **kwargs): ds_grid.xoak.set_index(["XC", "YC"], xoak_index) - cdata = {"XC": ("mooring", Xmoor), "YC": ("mooring", Ymoor)} - ds_data = _xr.Dataset(cdata) # mooring data + cdata = {"XC": ("mooring", Xmoor), "YC": ("mooring", Ymoor)} + ds_data = _xr.Dataset(cdata) # mooring data - # find nearest points to given data. - nds = ds_grid.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) - - def diff_and_inds_where_insert(ix, iy): - dx, dy = (_np.diff(ii) for ii in (ix, iy)) - inds = _np.argwhere(_np.abs(dx) + _np.abs(dy) > 1).squeeze() - return dx, dy, inds + # find nearest points to given data. + nds = ds_grid.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) - ix, iy = (nds["i" + f"{i}"].data for i in ("X", "Y")) + ix, iy = (nds["i" + f"{i}"].data for i in ("X", "Y")) - # Remove duplicates that are next to each other. - mask = _np.abs(_np.diff(ix)) + _np.abs(_np.diff(iy)) == 0 - ix, iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (ix, iy)) + # Remove duplicates that are next to each other. + mask = _np.argwhere(_np.abs(_np.diff(ix)) + _np.abs(_np.diff(iy)) == 0) + ix, iy = (_np.delete(ii, mask) for ii in (ix, iy)) - # Initialize variables - dx, dy, inds = diff_and_inds_where_insert(ix, iy) - while inds.size: - dx, dy = (di[inds] for di in (dx, dy)) - mask = _np.abs(dx * dy) == 1 - ix = _np.insert(ix, inds + 1, ix[inds] + (dx / 2).astype(int)) - iy = _np.insert( - iy, inds + 1, iy[inds] + _np.where(mask, dy, (dy / 2).astype(int)) - ) - # Prepare for next iteration + # Initialize variables dx, dy, inds = diff_and_inds_where_insert(ix, iy) + while inds.size: + dx, dy = (di[inds] for di in (dx, dy)) + mask = _np.abs(dx * dy) == 1 + ix = _np.insert(ix, inds + 1, ix[inds] + (dx / 2).astype(int)) + iy = _np.insert( + iy, inds + 1, iy[inds] + _np.where(mask, dy, (dy / 2).astype(int)) + ) + # Prepare for next iteration + dx, dy, inds = diff_and_inds_where_insert(ix, iy) - def remove_repeated(_iX, _iY): - """Attemps to remove repeated coords not adjascent to each other, - while retaining the trajectory property of being simply connected - (i.e. the distance between each index point is one). If it cannot - remove repeated coordinate values, returns the original array. - """ - _ix, _iy = _iX, _iY - nn = [] - for n in range(len(_ix)): - val = _np.where(abs(_ix - _ix[n]) + abs(_iy - _iy[n]) == 0)[0] - # select only repeated values with deg of multiplicity = 2 - if len(val) == 2: - if len(nn) == 0: - nn.append(list(val)) - elif len(nn) > 0 and (val != nn).all(): - nn.append(list(val)) - if _np.array(nn).size: - dn = [nn[i][1] - nn[i][0] for i in range(len(nn))] - # remove if the distance between repeated coords is 2 - mask = _np.where(_np.array(dn) == 2)[0] - remove = [nn[i][1] for i in mask] - _ix, _iy = (_np.delete(ii, remove) for ii in (_ix, _iy)) - # find the hole left - mask = _np.abs(_np.diff(_ix)) + _np.abs(_np.diff(_iy)) == 2 - # delete hole left behind - _ix, _iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (_ix, _iy)) - # verify path is simply connected - dx, dy, inds = diff_and_inds_where_insert(_ix, _iy) - if inds.size: - _ix = _iX - _iY = _iY - return _ix, _iy - - # attempt to remove repeated (but not adjacent) coord values - ix, iy = remove_repeated(ix, iy) - - new_ds = eval_dataset(ds, ix, iy) + # attempt to remove repeated (but not adjacent) coord values + ix, iy = remove_repeated(ix, iy) + + new_ds = eval_dataset(ds, ix, iy) mooring = new_ds.mooring - near_Y = new_ds["YC"].compute().data.squeeze() - near_X = new_ds["XC"].compute().data.squeeze() + near_Y = new_ds["YC"].values + near_X = new_ds["XC"].values # Add distance (0 always first element) if R is not None: @@ -805,6 +816,8 @@ def remove_repeated(_iX, _iY): dists = _np.insert(dists, 0, 0) # add zero as 1st element if "units" in new_ds["XC"].attrs: unit = new_ds["XC"].attrs["units"] + else: + unit = "None" dists = _np.cumsum(dists) distance = DataArray( @@ -821,6 +834,16 @@ def remove_repeated(_iX, _iY): # Recreate od od._ds = new_ds + + # remove complex topology from grid + if od.face_connections is not None: + new_face_connections = {"face_connections": {None: {None, None}}} + od = od.set_face_connections(**new_face_connections) + grid_coords = od.grid_coords + # remove face from grid coord + grid_coords.pop("face", None) + od = od.set_grid_coords(grid_coords, overwrite=True) + od = od.set_grid_coords( {"mooring": {"mooring": -0.5}}, add_midp=True, overwrite=False ) @@ -832,9 +855,47 @@ def remove_repeated(_iX, _iY): attrs=od._ds["mooring_dist"].attrs, ) od = od.merge_into_oceandataset(dist_midp.rename("mooring_midp_dist")) - od._ds = od._ds.set_coords( - [coord for coord in od._ds.coords] + ["mooring_midp_dist"] - ) + + if _diffXYs: # pragma: no cover + moor_midp = od._ds.mooring_midp.values + if diffX.size == len(moor_midp): + # include in dataset + xr_diffX = DataArray( + diffX, + coords={"mooring_midp": moor_midp}, + dims=("mooring_midp"), + attrs={"long_name": "x-difference between moorings", "units": unit}, + ) + + xr_diffY = DataArray( + diffY, + coords={"mooring_midp": moor_midp}, + dims=("mooring_midp"), + attrs={"long_name": "y-difference between moorings", "units": unit}, + ) + + od._ds["diffX"] = xr_diffX + od._ds["diffY"] = xr_diffY + else: + print(diffX.size) + _warnings.warn( + "diffX and diffY have inconsistent lengths with mooring dimension" + ) + + # compute missing grid velocities from datasets if necessary + vel_grid = ["XU", "YU", "XV", "YV"] + da_list = [var for var in od._ds.reset_coords().data_vars] + check = all([item in da_list for item in vel_grid]) + if check: # pragma: no cover + manipulate_coords = {"coordsUVfromG": False} + else: # pragma: no cover + manipulate_coords = {"coordsUVfromG": True} + od = od.manipulate_coords(**manipulate_coords) + od._ds = od._ds.set_coords( + coords + vel_grid + ["mooring_dist", "mooring_midp_dist"] + ) + else: + od._ds = od._ds.set_coords(coords + ["mooring_midp_dist"]) return od @@ -1081,14 +1142,24 @@ def stations( Xcoords=None, xoak_index="scipy_kdtree", method="nearest", + dim_name="station", ): """ - Extract stations using nearest-neighbor lookup. + Extract nearest-neighbor data from given spatial coordinate. + Data may be isolated and unordered (`dim_name=stations`), or contiguous + and unit distanced (`dim_name=mooring`). + + Following the C-grid convention, + for every scalar point extracted (along the new dimension `dim_name`) + returns 4 velocity points: 2 U-points, 2 V-points and their respective + coordinates, and 4 corner coordinate points. Parameters ---------- od: OceanDataset od that will be subsampled. + varList: 1D array_lie, NoneType + variable names to sample. tcoords: 1D array_like, NoneType time-coordinates (datetime). Zcoords: 1D array_like, NoneType @@ -1099,18 +1170,34 @@ def stations( lon coordinates of locations at center point. xoak_index: str xoak index to be used. `scipy_kdtree` by default. + method: str, `nearest` (default). + see .sel via xarray.dataSet.sel method + dim_name: str + `station` (default) or `mooring`. Returns ------- + Depending on the choice of dim_name, two types of returns: + see https://github.com/hainegroup/oceanspy/issues/398 + + 1) if `dim_name: 'stations'` + od: OceanDataset Subsampled oceandataset. + 2) if `dim_name: 'mooring'` + + ds: xarray.dataset + diffX: numpy.array + diffX: numpy.array + + See Also -------- - oceanspy.OceanDataset.mooring + oceanspy.subsample.mooring_array """ - _check_native_grid(od, "stations") + _check_native_grid(od, dim_name) # Convert variables to numpy arrays and make some check tcoords = _check_range(od, tcoords, "timeRange") @@ -1119,11 +1206,17 @@ def stations( Xcoords = _check_range(od, Xcoords, "Xcoords") # Message - print("Extracting stations.") + message = "Extracting " + dim_name + if dim_name == "mooring": + message = message + " array" + else: + message = message + "s" + print(message) # Unpack ds - od = _copy.copy(od) + od = _copy.deepcopy(od) ds = od._ds + face_connections = od.face_connections["face"] if varList is not None: nvarlist = [var for var in ds.data_vars if var not in varList] @@ -1155,70 +1248,108 @@ def stations( DS = ds if Xcoords is not None and Ycoords is not None: - if not ds.xoak.index: - if xoak_index not in _xoak.IndexRegistry(): - raise ValueError( - "`xoak_index` [{}] is not supported." - "\nAvailable options: {}" - "".format(xoak_index, _xoak.IndexRegistry()) - ) + ds_grid = ds[["XC", "YC"]] - ds.xoak.set_index(["XC", "YC"], xoak_index) + if dim_name == "mooring": # needed for transport + for key, value in ds_grid.sizes.items(): + ds_grid["i" + f"{key}"] = DataArray(range(value), dims=key) - cdata = {"XC": ("station", Xcoords), "YC": ("station", Ycoords)} + if xoak_index not in _xoak.IndexRegistry(): + raise ValueError( + "`xoak_index` [{}] is not supported." + "\nAvailable options: {}" + "".format(xoak_index, _xoak.IndexRegistry()) + ) + ds_grid.xoak.set_index(["XC", "YC"], xoak_index) + + cdata = {"XC": (dim_name, Xcoords), "YC": (dim_name, Ycoords)} ds_data = _xr.Dataset(cdata) # find nearest points to given data. - nds = ds.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) + nds = ds_grid.xoak.sel(XC=ds_data["XC"], YC=ds_data["YC"]) - if "face" not in ds.dims: + if "face" not in ds.dims: # pragma: no cover iX, iY = (nds[f"{i}"].data for i in ("X", "Y")) - DS = eval_dataset(ds, iX, iY, _dim_name="station") + DS = eval_dataset(ds, iX, iY, _dim_name=dim_name) DS = DS.squeeze() - - if "face" in ds.dims: + else: + ds = mates(ds) + varlist = [var for var in ds.reset_coords().data_vars if var not in "face"] + attrs = {} + for var in varlist: + attrs[var] = ds[var].attrs iX, iY, iface = (nds[f"{i}"].data for i in ("X", "Y", "face")) - _dat = nds.face.values ll = _np.where(abs(_np.diff(_dat)))[0] order_iface = [_dat[i] for i in ll] + [_dat[-1]] Niter = len(order_iface) - if Niter == 1: - X0, Y0 = iX, iY - DS = eval_dataset(ds, X0, Y0, order_iface, "station") - DS = DS.squeeze() - - else: - # split indexes along each face - X0, Y0 = [], [] - for ii in range(len(ll) + 1): - if ii == 0: - x0, y0 = iX[: ll[ii] + 1], iY[: ll[ii] + 1] - elif ii > 0 and ii < len(ll): - x0, y0 = ( - iX[ll[ii - 1] + 1 : ll[ii] + 1], - iY[ll[ii - 1] + 1 : ll[ii] + 1], + args = { + "_ds": ds, + "_ix": iX, + "_iy": iY, + "_faces": order_iface, # single element list + "_iface": 0, # index of face + "_face_connections": face_connections, + } + if dim_name == "mooring": + nix, niy = connector(iX, iY) + DS, nix, niy = mooring_singleface(**args) + if order_iface[0] in _np.arange(7, 13): + DS = flip_v(mates(DS)) + diffX, diffY, *a = cross_face_diffs( + DS, nix, niy, order_iface, 0, face_connections + ) + return DS.persist(), diffX, diffY + if dim_name == "station": # pragma: no cover + DS = station_singleface(**args).persist() + if order_iface[0] in _np.arange(7, 13): + DS = flip_v(mates(DS)) + if Niter > 1: + nX0, nY0 = splitter(iX, iY, iface) + args = { + "_ds": ds, + "_faces": order_iface, + "_face_connections": face_connections, + } + DSf = [] + shift = 0 + diffsX, diffsY = _np.array([]), _np.array([]) + for ii in range(Niter): + if dim_name == "station": + _returns = False + args1 = {"_ix": nX0[ii], "_iy": nY0[ii], "_iface": ii} + dse = station_singleface(**{**args, **args1}) + if order_iface[ii] in _np.arange(7, 13): + dse = flip_v(mates(dse)) + if dim_name == "mooring": + _returns = True + nix, niy = fill_path( + nX0, nY0, order_iface, ii, face_connections ) - elif ii == len(ll): - x0, y0 = iX[ll[ii - 1] + 1 :], iY[ll[ii - 1] + 1 :] - X0.append(x0) - Y0.append(y0) - - DS = [] - for i in range(Niter): - DS.append(eval_dataset(ds, X0[i], Y0[i], order_iface[i], "station")) - - _dim = "station" - nDS = [DS[0].reset_coords()] - for i in range(1, len(DS)): - Nend = nDS[i - 1][_dim].values[-1] - nDS.append(reset_dim(DS[i], Nend + 1, dim=_dim).reset_coords()) - - DS = nDS[0] - for i in range(1, len(nDS)): - DS = DS.combine_first(nDS[i]) - + args1 = {"_ix": nix, "_iy": niy, "_iface": ii} + dse, nix, niy = mooring_singleface(**{**args, **args1}) + if order_iface[ii] in _np.arange(7, 13): + dse = flip_v(mates(dse)) + diX, diY, *a = cross_face_diffs( + ds, nix, niy, order_iface, ii, face_connections + ) + diffsX = _np.append(diffsX, diX) + diffsY = _np.append(diffsY, diY) + for var in dse.reset_coords().data_vars: + dse[var].attrs = {} + if ii > 0: + shift += len(DSf[ii - 1][dim_name]) + dse = reset_dim(dse, shift, dim=dim_name) + DSf.append(dse) + DS = _xr.combine_by_coords(DSf) + Ndim = len(DS[dim_name]) + DS = DS.chunk({dim_name: Ndim}).persist() + del DSf + for var in DS.reset_coords().data_vars: + DS[var].attrs = attrs + if _returns: + return DS, diffsX, diffsY DS = DS.set_coords(co_list) if Xcoords is None and Ycoords is None: @@ -1230,13 +1361,11 @@ def stations( od._ds = DS - if od.face_connections is not None: + if od.face_connections is not None: # pragma: no cover new_face_connections = {"face_connections": {None: {None, None}}} od = od.set_face_connections(**new_face_connections) grid_coords = od.grid_coords - grid_coords.pop("X", None) - grid_coords.pop("Y", None) od = od.set_grid_coords(grid_coords, overwrite=True) return od @@ -1419,113 +1548,6 @@ def particle_properties(od, times, Ypart, Xpart, Zpart, **kwargs): return od -def eval_dataset(_ds, _ix, _iy, _iface=None, _dim_name="mooring"): - """ - Evaluates a dataset along (spatial) trajectory in the plane as defined by the - indexes in the plane. As a result, there is a new dimension/coordinate, hence - reducing the dimension of the original dataset. - - Parameters: - ---------- - _ds: xarray.Dataset - contains all x, y coordinates (but may be subsampled in Z or time) - _ix, _iy: 1D array, int - index values identifying the location in X Y (lat, lon) space - _iface: int, None (bool) - None (default) implies no complex topology in the dataset. Otherwise, - _iface indicates the face index which, along which the provided ix, iy, - identify the spatial (geo) coordinate location in lat/lon space. - _dim_name: str - names the new dimension along the pathway. By default this is 'mooring', - but can also be 'station' (when discrete, argo-like isolated coordinates). - - Returns: - xarray.Dataset - - """ - - new_dim = DataArray( - _np.arange(len(_ix)), - dims=(_dim_name), - attrs={"long_name": "index of " + _dim_name, "units": "none"}, - ) - y = DataArray( - _np.arange(1), - dims=("y"), - attrs={"long_name": "j-index of cell center", "units": "none"}, - ) - x = DataArray( - _np.arange(1), - dims=("x"), - attrs={"long_name": "i-index of cell center", "units": "none"}, - ) - yp1 = DataArray( - _np.arange(2), - dims=("yp1"), - attrs={"long_name": "j-index of cell corner", "units": "none"}, - ) - xp1 = DataArray( - _np.arange(2), - dims=("xp1"), - attrs={"long_name": "i-index of cell corner", "units": "none"}, - ) - - # Transform indexes in DataArray - iY = DataArray( - _np.reshape(_iy, (len(new_dim), len(y))), - coords={_dim_name: new_dim, "y": y}, - dims=(_dim_name, "y"), - ) - iX = DataArray( - _np.reshape(_ix, (len(new_dim), len(x))), - coords={_dim_name: new_dim, "x": x}, - dims=(_dim_name, "x"), - ) - - iYp1 = DataArray( - _np.stack((_iy, _iy + 1), 1), - coords={_dim_name: new_dim, "yp1": yp1}, - dims=(_dim_name, "yp1"), - ) - - iXp1 = DataArray( - _np.stack((_ix, _ix + 1), 1), - coords={_dim_name: new_dim, "xp1": xp1}, - dims=(_dim_name, "xp1"), - ) - - if _iface is not None: - if _iface == [6]: - return arctic_eval(_ds, _ix, _iy, _dim_name) - elif _iface in _np.arange(7, 13): - iXp1 = DataArray( - _np.stack((_ix + 1, _ix), 1), - coords={_dim_name: new_dim, "xp1": xp1}, - dims=(_dim_name, "xp1"), - ) - - args = { - "X": iX, - "Y": iY, - "Xp1": iXp1, - "Yp1": iYp1, - } - - rename = {"yp1": "Yp1", "xp1": "Xp1", "x": "X", "y": "Y"} - - if _iface is not None: - args = {"face": _iface, **args} - if _iface in _np.arange(7, 13): - rename = {"yp1": "Xp1", "xp1": "Yp1", "x": "Y", "y": "X"} - - new_ds = _ds.isel(**args).drop_vars(["Xp1", "Yp1", "X", "Y"]) - new_ds = new_ds.rename_dims(rename).rename_vars(rename) - if _iface is not None and _iface in _np.arange(7, 13): - new_ds = rotate_vars(new_ds) - - return new_ds - - class _subsampleMethods(object): """ Enables use of functions as OceanDataset attributes. diff --git a/oceanspy/tests/test_compute_functions.py b/oceanspy/tests/test_compute_functions.py index 4eaf06d4..a8c7b05b 100644 --- a/oceanspy/tests/test_compute_functions.py +++ b/oceanspy/tests/test_compute_functions.py @@ -43,6 +43,11 @@ ECCO_url = "{}catalog_ECCO.yaml".format(Datadir) ECCOod = open_oceandataset.from_catalog("LLC", ECCO_url) +# rename coord variables +ECCOod._ds = ECCOod._ds.rename_vars( + {"hFacS": "HFacS", "hFacW": "HFacW", "hFacC": "HFacC"} +) + # Aliased od ds = od.dataset @@ -383,27 +388,6 @@ def test_mooring_volume_transport(od_in, mooring, closed, flippedX, flippedY): Xmin, Xmax = -80, 0 Ymin, Ymax = 35, 35 - # compute missing (for testing purposes assume uniform) - - Scoords = { - "Z": od_in._ds.Z.values, - "face": od_in._ds.face.values, - "Yp1": od_in._ds.Yp1.values, - "X": od_in._ds.X.values, - } - Wcoords = { - "Z": od_in._ds.Z.values, - "face": od_in._ds.face.values, - "Y": od_in._ds.Yp1.values, - "Xp1": od_in._ds.X.values, - } - - Stmp = xr.DataArray(1, coords=Scoords, dims={"Z", "face", "Yp1", "X"}) - Wtmp = xr.DataArray(1, coords=Wcoords, dims={"Z", "face", "Y", "Xp1"}) - - od_in._ds["HFacS"] = Stmp - od_in._ds["HFacW"] = Wtmp - if mooring is True: if not closed: X = [Xmin, Xmax] diff --git a/oceanspy/tests/test_llc_rearrange.py b/oceanspy/tests/test_llc_rearrange.py index 8858ec7b..7f400a8d 100644 --- a/oceanspy/tests/test_llc_rearrange.py +++ b/oceanspy/tests/test_llc_rearrange.py @@ -1,4 +1,5 @@ import copy as _copy +import random as rand import numpy as _np import pytest @@ -13,20 +14,45 @@ _edge_facet_data, arc_limits_mask, arct_connect, + arct_diffs, + arctic_eval, combine_list_ds, + cross_face_diffs, + ds_arcedge, + ds_edge, + ds_edge_sametx, + ds_edge_samety, + ds_splitarray, + edge_completer, + edge_slider, + edgesid, + face_adjacent, + face_direction, + fdir_completer, + fill_path, + index_splitter, mask_var, mates, + mooring_singleface, + order_from_indexing, rotate_dataset, rotate_vars, shift_dataset, shift_list_ds, slice_datasets, + splitter, + station_singleface, ) -from oceanspy.utils import _reset_range, get_maskH +from oceanspy.utils import _reset_range, connector, get_maskH Datadir = "./oceanspy/tests/Data/" ECCO_url = "{}catalog_ECCO.yaml".format(Datadir) od = open_oceandataset.from_catalog("LLC", ECCO_url) +od._ds = od._ds.rename_vars({"hFacS": "HFacS", "hFacW": "HFacW", "hFacC": "HFacC"}) +co_list = [var for var in od._ds.data_vars if "time" not in od._ds[var].dims] +od._ds = od._ds.set_coords(co_list) +if "timestep" in od._ds.data_vars: + od._ds = od._ds.drop_vars(["timestep"]) Nx = od._ds.dims["X"] Ny = od._ds.dims["Y"] @@ -2185,9 +2211,20 @@ def test_original_dims(od, var, expected): assert dims == expected -faces = [k for k in range(13)] +@pytest.mark.parametrize("ds", [od._ds.isel(face=0).drop_vars(["face"])]) +def test_error_face(ds): + with pytest.raises(ValueError): + LLC.arctic_crown(ds) + +@pytest.mark.parametrize("ds", [od._ds]) +@pytest.mark.parametrize("XRange, YRange", [([-11111, 1111], [-999, 999])]) +def test_error_range(ds, XRange, YRange): + with pytest.raises(ValueError): + LLC.arctic_crown(ds, XRange=XRange, YRange=YRange) + +faces = [k for k in range(13)] expected = [2, 5, 7, 10] # most faces that connect with arctic cap face=6 acshape = (Nx // 2, Ny) cuts = [[0, 28], [0, 0], [0, 0], [0, 0]] @@ -2296,6 +2333,7 @@ def test_arc_connect( (od, [0, 9, 12], varList, None, None, 0, 268, 0, 89), (od, [0, 3, 12], varList, None, None, 0, 268, 0, 89), (od, [0], varList[0], None, None, 0, 88, 0, 88), + (od, [0], None, None, None, 0, 88, 0, 88), (od, [1], varList[0], None, None, 0, 88, 0, 88), (od, [2], varList[0], None, None, 0, 88, 0, 88), (od, [3], varList[0], None, None, 0, 88, 0, 88), @@ -2329,11 +2367,14 @@ def test_arc_connect( (od, None, varList, [-120, -60], [58, 85.2], 0, 63, 0, 69), (od, None, varList, [160, -150], [58, 85.2], 0, 53, 0, 69), (od, None, varList, [60, 130], [58, 85.2], 0, 73, 0, 69), + (od, None, None, [260, 330], [58, 85.2], 0, 73, 0, 69), + (od, None, None, [20, 30], [5008, 5.2], 0, 73, 0, 69), ], ) def test_transformation(od, faces, varList, XRange, YRange, X0, X1, Y0, Y1): """Test the transformation fn by checking the final dimensions.""" - ds = od._ds.reset_coords().drop_vars({"hFacC", "hFacS", "hFacW"}) + ds = _copy.deepcopy(od._ds.reset_coords()) + args = { "ds": ds, "varList": varList, @@ -2341,14 +2382,20 @@ def test_transformation(od, faces, varList, XRange, YRange, X0, X1, Y0, Y1): "YRange": YRange, "faces": faces, } - - ds = LLC.arctic_crown(**args) - xi, xf = int(ds["X"][0].values), int(ds["X"][-1].values) - yi, yf = int(ds["Y"][0].values), int(ds["Y"][-1].values) - assert xi == X0 - assert xf == X1 - assert yi == Y0 - assert yf == Y1 + if XRange is not None and YRange is not None: + XRange = _np.array(XRange) + YRange = _np.array(YRange) + if _np.max(abs(XRange)) > 180 or _np.max(abs(YRange)) > 90: + with pytest.raises(ValueError): + ds = LLC.arctic_crown(**args) + else: + ds = LLC.arctic_crown(**args) + xi, xf = int(ds["X"][0].values), int(ds["X"][-1].values) + yi, yf = int(ds["Y"][0].values), int(ds["Y"][-1].values) + assert xi == X0 + assert xf == X1 + assert yi == Y0 + assert yf == Y1 DIMS_c = [dim for dim in od.dataset["XC"].dims if dim not in ["face"]] @@ -2559,14 +2606,19 @@ def test_shift_list_ds(DSlist, dimsc, dimsg, Np, facet, expX): (nlist4y1, int(Np), int(Np), 0, 89, 45, 134), (nlist4x4, int(Np), int(Np), 90, 179, 0, 89), (nlist4y4, int(Np), int(Np), 0, 89, 90, 179), + ([], None, None, None, None, None, None), + ([0], None, None, None, None, None, None), ], ) def test_combine_list_ds(DSlist, lenX, lenY, x0, x1, y0, y1): nDSlist = combine_list_ds(DSlist) - assert len(nDSlist.X) == lenX - assert len(nDSlist.Y) == lenY - assert [int(nDSlist.X[0].values), int(nDSlist.X[-1].values)] == [x0, x1] - assert [int(nDSlist.Y[0].values), int(nDSlist.Y[-1].values)] == [y0, y1] + if lenX is not None: + assert len(nDSlist.X) == lenX + assert len(nDSlist.Y) == lenY + assert [int(nDSlist.X[0].values), int(nDSlist.X[-1].values)] == [x0, x1] + assert [int(nDSlist.Y[0].values), int(nDSlist.Y[-1].values)] == [y0, y1] + else: + assert nDSlist == 0 @pytest.mark.parametrize( @@ -2581,9 +2633,6 @@ def test_mask_var(od, XRange, YRange): assert _np.isnan(ds["nYG"].data).all() -_zeros = [0, 0] - - @pytest.mark.parametrize( "od, XRange, YRange, A, B, C, D", [ @@ -2837,3 +2886,1340 @@ def test_edge_arc_data(od, XRange, YRange, F_indx, Nx): Xf = _edge_arc_data(DSa[_var_], F_indx, dims_g) assert Xf == Nx + + +_ds = _copy.deepcopy(od._ds) +nU = _copy.deepcopy(_ds["CS"].values) +nV = -_copy.deepcopy(_ds["SN"].values) +Ucoords = { + "face": _ds.face.values, + "Y": _ds.Y.values, + "Xp1": _ds.Xp1.values, +} + +Vcoords = { + "face": _ds.face.values, + "Yp1": _ds.Yp1.values, + "X": _ds.X.values, +} + +_ds["Ucycl"] = _xr.DataArray(nU, coords=Ucoords, dims=["face", "Y", "Xp1"]) +_ds["Vcycl"] = _xr.DataArray(nV, coords=Vcoords, dims=["face", "Yp1", "X"]) + + +@pytest.mark.parametrize("dataset", [_ds]) +@pytest.mark.parametrize( + "pairs", [["a", "b"], ["Ucycl", "Vcycl"], ["Ucycl", "Vcycl", "a"]] +) +def test_mates(dataset, pairs): + nvar = [var for var in pairs if var not in dataset.variables] + if len(nvar) > 0 and len(nvar) % 2 == 0: + with pytest.raises(ValueError): + mates(dataset, pairs) + elif len(pairs) > 0 and (len(pairs) - len(nvar)) % 2 == 0: + dataset = mates(dataset, pairs) + _vars = [var for var in pairs if var not in nvar] + for n in range(len(_vars[::2])): + assert dataset[_vars[n]].attrs["mate"] == _vars[n + 1] + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "face1, face2, value", + [ + (5, 2, 0), + (2, 2, None), + (5, 7, 1), + (5, 6, 3), + (5, 4, 2), + (10, 6, 0), + (10, 11, 1), + (10, 7, 2), + (10, 2, 3), + (0, 1, 3), + (0, 8, None), + ], +) +def test_face_direction(od, face1, face2, value): + conxs = od.face_connections["face"] + if value is None: + with pytest.raises(ValueError): + face_direction(face1, face2, conxs) + else: + assert value == face_direction(face1, face2, conxs) + + +x1 = [k for k in range(0, 85, 10)] +y1 = [int(k) for k in _np.linspace(20, 40, len(x1))] +fs1 = len(x1) * [5] + +x2 = [k for k in range(10, 85, 10)][::-1] +y2 = [int(k) for k in _np.linspace(20, 40, len(x2))][::-1] +fs2 = len(x1) * [2] + +y3 = [k for k in range(0, 89, 1)] +x3 = len(y3) * [2] +fs3 = len(y3) * [1] + +X1, Y1, Fs1 = [x1, x2], [y1, y2], [fs1, fs2] + +X2, Y2, Fs2 = [x1, x3], [y1, y3], [fs1, fs3] + + +@pytest.mark.parametrize("X, Y, Fs", [(X1, Y1, Fs1), (X2, Y2, Fs2)]) +def test_splitter(X, Y, Fs): + xs = X[0] + X[1] + ys = Y[0] + Y[1] + fs = Fs[0] + Fs[1] + nX, nY = splitter(xs, ys, fs) + assert len(nX) == len(nY) + assert nX[0] == X[0] + assert nX[1] == X[1] + assert nY[0] == Y[0] + assert nY[1] == Y[1] + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "X, Y, Fs, exp", + [ + ([45, 46], [89, 0], [1, 2], [46, 89]), + ([89, 0], [45, 44], [1, 4], [89, 44]), + ([45, 46], [0, 0], [1, 0], [46, 0]), + ([89, 0], [45, 40], [8, 9], [89, 40]), + ([0, 89], [45, 40], [8, 7], [0, 40]), + ([45, 40], [89, 0], [8, 11], [40, 89]), + ([89, 89], [89, 89], [0, 1], [None, None]), + ([0, 44], [45, 89], [1, 11], [0, 45]), + ([89, 40], [45, 9], [4, 8], [89, 49]), + ([45, 89], [0, 40], [8, 4], [49, 0]), + ([40, 0], [89, 40], [2, 6], [49, 89]), + ([0, 89], [40, 50], [7, 6], [0, 50]), + ([40, 70], [89, 0], [5, 6], [70, 89]), + ([0, 70], [40, 89], [10, 6], [0, 19]), + ([0, 40], [40, 89], [6, 2], [0, 49]), + ([70, 40], [0, 89], [6, 5], [40, 0]), + ([89, 0], [50, 40], [6, 7], [89, 40]), + ([70, 0], [89, 40], [6, 10], [49, 89]), + ], +) +def test_edge_slider(od, X, Y, Fs, exp): + face_connections = od.face_connections["face"] + if set([X[0], Y[0]]) == set([89]): + # upper right corner + with pytest.raises(ValueError): + edge_slider(X[0], Y[0], Fs[0], X[1], Y[1], Fs[1], face_connections) + else: + newP = edge_slider(X[0], Y[0], Fs[0], X[1], Y[1], Fs[1], face_connections) + assert newP == exp + + +x1 = _np.array([k for k in range(15, 45)]) +y1 = [10] * len(x1) + +y2 = [k for k in range(45, 78)] +x2 = len(y2) * [40] + + +@pytest.mark.parametrize( + "x, y, facedir, ind, X0, X1", + [ + (x1, y1, 1, -1, [x1[0], y1[0]], [89, y1[-1]]), + (x1, y1, 0, 0, [0, y1[0]], [x1[-1], y1[-1]]), + (x1, y1, 3, -1, [x1[0], y1[0]], [x1[-1], 89]), + (x1, y1, 2, 0, [x1[0], 0], [x1[-1], y1[-1]]), + (x2, y2, 2, 0, [x2[0], 0], [x2[-1], y2[-1]]), + (x2, y2, 0, -1, [x2[0], y2[0]], [0, y2[-1]]), + (x2, y2, 1, -1, [x2[0], y2[0]], [89, y2[-1]]), + (x2, y2, 0, 0, [0, y2[0]], [x2[-1], y2[-1]]), + (x2, y2, 1, -1, [x2[0], y2[0]], [89, y2[-1]]), + ], +) +def test_edge_completer(x, y, facedir, ind, X0, X1): + xn, yn = edge_completer(x, y, facedir, ind) + # assert unit distance between elements of array. + diffs = abs(_np.diff(xn)) + abs(_np.diff(yn)) + assert _np.max(diffs) == _np.min(diffs) == 1 + assert [xn[0], yn[0]] == X0 + assert [xn[-1], yn[-1]] == X1 + + +# face = 0 +y0 = [k for k in range(45, 80)] +x0 = len(y0) * [40] +# face 1 +y11 = [k for k in range(5, 45)] +x11 = len(y11) * [45] +x12 = [k for k in range(45, 80)] +y12 = len(x12) * [45] +x1 = x11 + x12 +y1 = y11 + y12 +# face 4 +x41 = [k for k in range(5, 46)] +y41 = len(x41) * [60] +y42 = [k for k in range(59, 10, -1)] +x42 = len(y42) * [45] +x4 = x41 + x42 +y4 = y41 + y42 +# face 3 +y31 = [k for k in range(80, 40, -1)] +x31 = len(y31) * [60] +x32 = [k for k in range(60, 5, -1)] +y32 = len(x32) * [40] +x3 = x31 + x32 +y3 = y31 + y32 +# face 0 again! +x01 = [k for k in range(80, 45, -1)] +y01 = len(x01) * [45] +# get them all together +X1, Y1 = [x0, x1, x4, x3, x01], [y0, y1, y4, y3, y01] + +Xac = [x01[::-1], x3[::-1], x4[::-1], x1[::-1], x0[::-1]] +Yac = [y01[::-1], y3[::-1], y4[::-1], y1[::-1], y0[::-1]] + + +# faces +faces1 = [0, 1, 4, 3, 0] +facesac = faces1[::-1] + + +# topology changes +x11 = _np.arange(20, 69) +y11 = [60] * len(x11) +y12 = _np.arange(61, 85) +x12 = [70] * len(y12) +x1 = _np.array(list(x11) + list(x12)) +y1 = _np.array(list(y11) + list(y12)) +x2 = _np.arange(10, 80) +y2 = _np.array([10] * len(x2)) +x3 = _np.arange(20, 75) +y3 = _np.array([25] * len(x3)) +y40 = _np.arange(15, 45) +x40 = [60] * len(y40) +x41 = _np.arange(60, 20, -1) +y41 = [50] * len(x41) +y42 = _np.arange(40, 10, -1) +x42 = [20] * len(y42) +x4 = _np.array(list(x40) + list(x41) + list(x42)) +y4 = _np.array(list(y40) + list(y41) + list(y42)) +x5 = _np.arange(60, 10, -1) +y5 = _np.array([65] * len(x5)) +x6 = _np.arange(60, 10, -1) +y6 = _np.array([80] * len(x6)) +y7 = _np.arange(85, 61, -1) +x7 = [19] * len(y7) + +XX, YY = [x1, x2, x3, x4, x5, x6, x7], [y1, y2, y3, y4, y5, y6, y7] + +xfaces = [10, 2, 5, 7, 5, 2, 10] + + +@pytest.mark.parametrize( + "X, Y, faces", + [ + (X1, Y1, faces1), + (Xac, Yac, facesac), + (XX, YY, xfaces), + ], +) +def test_fill_path(X, Y, faces): + xx, yy = [], [] + for k in range(len(faces)): + nx, ny = fill_path(X, Y, faces, k, od.face_connections["face"]) + xx.append(nx) + yy.append(ny) + diffs = abs(_np.diff(nx)) + abs(_np.diff(ny)) + assert _np.max(diffs) == _np.min(diffs) == 1 + + nRot, Rot = _np.arange(6), _np.arange(6, 13) + _N = 89 # last index in ECCO (i or j) + + for k in range(1, len(faces) - 1): + k0, k1, k2 = [k - 1, k, k + 1] + + _past = face_direction(faces[k1], faces[k0], od.face_connections["face"]) + _next = face_direction(faces[k1], faces[k2], od.face_connections["face"]) + + st_next, st_past = False, False # initialize same topology flag + if set([faces[k1], faces[k2]]).issubset(nRot) or set( + [faces[k1], faces[k2]] + ).issubset(Rot): + st_next = True # same topology + if set([faces[k1], faces[k0]]).issubset(nRot) or set( + [faces[k1], faces[k0]] + ).issubset(Rot): + st_past = True # same topology + + if _next in [0, 1]: + if st_next: + assert yy[k1][-1] == yy[k2][0] + else: # change in topo + assert yy[k1][-1] == _N - xx[k2][0] + if _next in [2, 3]: + if st_next: + assert xx[k1][-1] == xx[k2][0] + else: # change in topo + _N - xx[k1][-1] == yy[k2][0] + if _past in [0, 1]: + if st_past: + assert yy[k1][0] == yy[k0][-1] + else: # change in topo + assert yy[k1][0] == 89 - xx[k0][-1] + if _past in [2, 3]: + if st_past: + assert xx[k1][0] == xx[k0][-1] + else: # change in topo + assert _N - xx[k1][0] == yy[k0][-1] + + +@pytest.mark.parametrize( + "iX, iY, iface, face_connections, adjacent", + [ + ([61], [89], 10, od.face_connections["face"], [2]), + ([89], [89], 10, od.face_connections["face"], [2]), + ([89], [19], 10, od.face_connections["face"], [11]), + ([0], [19], 10, od.face_connections["face"], [6]), + ([10], [0], 10, od.face_connections["face"], [7]), + ([10], [89], 10, od.face_connections["face"], [-1]), + ([10], [0], 0, od.face_connections["face"], None), # south pole + ([89], [9], 12, od.face_connections["face"], None), # south pole + ], +) +def test_face_adjacent(iX, iY, iface, face_connections, adjacent): + if iX + iY == [89, 89]: + with pytest.raises(ValueError): + face_adjacent(iX, iY, iface, face_connections) + else: + if adjacent is None: # southern pole singularity + adj = face_adjacent(iX, iY, iface, face_connections) + assert adj[0] == -1 + else: + if adjacent == [-1]: + N = 4320 + else: + N = 89 + adj = face_adjacent(iX, iY, iface, face_connections, _N=N) + assert adj == adjacent + + +# edge data on ECCO random array +edge1 = [[61, 89]] +edge2 = edge1 + [[21, 89]] +edge3 = edge2 + [[0, 55]] +edge4 = edge3 + [[0, 0]] + + +@pytest.mark.parametrize("edge", [edge1, edge2, edge3, edge4]) +def test_edgesid(edge): + # non-edge random array on ECCO + inX = [rand.randint(1, 88) for k in range(20)] + inY = [rand.randint(1, 88) for k in range(20)] + + # create n-random indexes + n = [rand.randint(0, len(inX)) for k in range(len(edge))] + # insert edge data randomly into array + [inX.insert(n[k], edge[k][0]) for k in range(len(edge))] + [inY.insert(n[k], edge[k][1]) for k in range(len(edge))] + + inX, inY, ind = edgesid(inX, inY) + + extracted = set( + tuple(item) for item in [[inX[ind[ii]], inY[ind[ii]]] for ii in range(len(ind))] + ) + given = set(tuple(item) for item in edge) + + assert given == extracted + + +# test 1 +# face 1 +y11 = [k for k in range(0, 11)] +x11 = [49 + 4 * k for k in range(11)] +y12 = [k for k in range(11, 16)] +x12 = len(y12) * [89] +x13 = [k for k in range(45, 60)] +y13 = len(x13) * [25] +y14 = [k for k in range(25, 35)] +x14 = len(y14) * [89] +x15 = [k for k in range(45, 60)] +y15 = len(x15) * [45] +x16 = [k for k in range(70, 80)] +y16 = len(x16) * [89] +x17 = [k for k in range(80, 85)] +y17 = len(x17) * [79] +x1 = x11 + x12 + x13 + x14 + x15 + x16 + x17 +y1 = y11 + y12 + y13 + y14 + y15 + y16 + y17 + +# face 4 +x21 = [k for k in range(5, 46)] +y21 = len(x21) * [60] +y22 = [k for k in range(59, 10, -1)] +x22 = len(y22) * [45] +x2 = x21 + x22 +y2 = y21 + y22 + +# group together +X1, Y1 = [x1, x2], [y1, y2] +faces1 = [1, 4] + + +# test 2 +# face 2 +x10 = _np.arange(89, 45, -1) +y10 = [25] * len(x10) +y11 = _np.arange(30, 65) +x11 = [45] * len(y11) +x12 = _np.arange(55, 89) +y12 = [75] * len(x12) +nx1 = _np.array(list(x10) + list(x11) + list(x12)) +ny1 = _np.array(list(y10) + list(y11) + list(y12)) +# face 5 +x20 = _np.arange(45) +y20 = [20] * len(x20) +y21 = _np.arange(30, 75) +x21 = [55] * len(y21) +x22 = _np.arange(45, 0, -1) +y22 = [80] * len(x22) +nx2 = _np.array(list(x20) + list(x21) + list(x22)) +ny2 = _np.array(list(y20) + list(y21) + list(y22)) +# group together +X2, Y2 = [nx1, nx2[::-1], nx1[:1]], [ny1, ny2[::-1], ny1[:1]] +faces2 = [2, 5, 2] + + +@pytest.mark.parametrize( + "ix, iy, faces, face_connections, count", + [ + (X1, Y1, faces1, od.face_connections["face"], 3), + (X2, Y2, faces2, od.face_connections["face"], 0), + ], +) +def test_index_splitter(ix, iy, faces, face_connections, count): + nx1, ny1 = fill_path(ix, iy, faces, 0, face_connections) + nI = index_splitter(nx1, ny1, 89) + assert len(nI) == count + + +# face 1 +y11 = [k for k in range(0, 11)] +x11 = [49 + 4 * k for k in range(11)] +y12 = [k for k in range(11, 16)] +x12 = len(y12) * [89] +x13 = [k for k in range(45, 60)] +y13 = len(x13) * [25] +y14 = [k for k in range(25, 35)] +x14 = len(y14) * [89] +x15 = [k for k in range(45, 60)] +y15 = len(x15) * [45] +x16 = [k for k in range(70, 80)] +y16 = len(x16) * [89] +x17 = [k for k in range(80, 85)] +y17 = len(x17) * [79] +x1 = x11 + x12 + x13 + x14 + x15 + x16 + x17 +y1 = y11 + y12 + y13 + y14 + y15 + y16 + y17 + +# group together +X1, Y1 = connector(x1, y1) +X2, Y2 = connector(x1[::-1], y1[::-1]) + + +x10 = _np.arange(89, 45, -1) +y10 = [25] * len(x10) +y11 = _np.arange(30, 65) +x11 = [45] * len(y11) +x12 = _np.arange(55, 89) +y12 = [75] * len(x12) +nx1 = _np.array(list(x10) + list(x11) + list(x12)) +ny1 = _np.array(list(y10) + list(y11) + list(y12)) +X3, Y3 = connector(nx1, ny1) +X4, Y4 = connector(nx1[::-1], ny1[::-1]) + + +@pytest.mark.parametrize("iX, iY", [(X1, Y1), (X2, Y2), (X3, Y3), (X4, Y4)]) +def test_order_from_indexing(iX, iY): + nI = index_splitter(iX, iY, 89) + _mi, _ixx = order_from_indexing(iX, nI) + if len(_mi) == 0: + assert _ixx.all() == iX.all() + else: + for i in range(len(_mi)): + assert _ixx[i].all() == iX[_mi[i]].all() + + +# face 2 +x10 = _np.arange(89, 45, -1) +y10 = [25] * len(x10) +y11 = _np.arange(30, 65) +x11 = [45] * len(y11) +x12 = _np.arange(55, 89) +y12 = [75] * len(x12) +nx1 = _np.array(list(x10) + list(x11) + list(x12)) +ny1 = _np.array(list(y10) + list(y11) + list(y12)) +# face 5 +x20 = _np.arange(45) +y20 = [20] * len(x20) +y21 = _np.arange(30, 75) +x21 = [55] * len(y21) +x22 = _np.arange(45, 0, -1) +y22 = [80] * len(x22) +nx2 = _np.array(list(x20) + list(x21) + list(x22)) +ny2 = _np.array(list(y20) + list(y21) + list(y22)) +# group together +oX1, oY1 = [nx1, nx2[::-1], nx1[:1]], [ny1, ny2[::-1], ny1[:1]] +faces1 = [2, 5, 2] + +# connect them across interface +X1, Y1 = [], [] +for k in range(len(oX1)): + x, y = fill_path(oX1, oY1, faces1, k, od.face_connections["face"]) + X1.append(x) + Y1.append(y) + + +# another case +# face 5 +x1 = _np.arange(20, 75) +y1 = _np.array([25] * len(x1)) + +y20 = _np.arange(15, 45) +x20 = [60] * len(y20) +x21 = _np.arange(60, 20, -1) +y21 = [50] * len(x21) + +y22 = _np.arange(40, 10, -1) +x22 = [20] * len(y22) + +x2 = _np.array(list(x20) + list(x21) + list(x22)) +y2 = _np.array(list(y20) + list(y21) + list(y22)) + +x3 = _np.arange(60, 10, -1) +y3 = _np.array([65] * len(x3)) + +oX2, oY2 = [x1, x2, x3], [y1, y2, y3] +faces2 = [4, 8, 4] + +# connect them across interface +X2, Y2 = [], [] +for k in range(len(oX2)): + x, y = fill_path(oX2, oY2, faces2, k, od.face_connections["face"]) + X2.append(x) + Y2.append(y) + + +@pytest.mark.parametrize( + "ix, iy, faces, iface, face_connections, val", + [ + (X1, Y1, faces1, 0, od.face_connections["face"], 1), + (X1, Y1, faces1, 1, od.face_connections["face"], 0), + (X1, Y1, faces1, 2, od.face_connections["face"], 1), + ( + [0, 10, _np.array([15])], + [10, 0, _np.array([15])], + [2, 5, 2], + 2, + od.face_connections["face"], + None, + ), + ], +) +def test_fdir_completer(ix, iy, faces, iface, face_connections, val): + fdir = fdir_completer(ix[iface], iy[iface], faces, iface, 89, face_connections) + assert fdir == val + + +y1 = _np.arange(40, 90) +x1 = _np.array([40] * len(y1)) +x2 = _np.arange(10, 30) +y2 = _np.array([30] * len(x2)) +facesa2 = [2, 6] +Xa2, Ya2 = [x1, x2], [y1, y2] + +x1 = _np.arange(40, 5, -1) +y1 = _np.array([40] * len(x1)) +x2 = _np.arange(85, 65, -1) +y2 = _np.array([50] * len(x2)) +facesa7 = [7, 6] +Xa7, Ya7 = [x1, x2], [y1, y2] + + +y1 = _np.arange(40, 85) +x1 = _np.array([40] * len(y1)) +y2 = _np.arange(5, 25) +x2 = _np.array([70] * len(y2)) +facesa5 = [5, 6] +Xa5, Ya5 = [x1, x2], [y1, y2] + + +x1 = _np.arange(40, 0, -1) +y1 = _np.array([40] * len(x1)) +y2 = _np.arange(85, 65, -1) +x2 = _np.array([70] * len(y2)) +facesa10 = [10, 6] +Xa10, Ya10 = [x1, x2], [y1, y2] + + +@pytest.mark.parametrize( + "od, ix, iy, faces, iface, valx, valy", + [ + (od, X1, Y1, faces1, 0, 1, 0), + (od, X1, Y1, faces1, 1, -1, 0), + (od, X2, Y2, faces2, 0, 1, 0), + (od, X2, Y2, faces2, 1, -1, 0), + (od, X2, Y2, faces2, 2, None, None), + (od, Xa2, Ya2, facesa2, 0, 0, 1), + (od, Xa2, Ya2, facesa2, 1, None, None), + (od, Xa7, Ya7, facesa7, 0, 0, 1), + (od, Xa7, Ya7, facesa7, 1, None, None), + (od, Xa5, Ya5, facesa5, 0, 0, 1), + (od, Xa5, Ya5, facesa5, 1, None, None), + (od, Xa10, Ya10, facesa10, 0, 0, 1), + (od, Xa10, Ya10, facesa10, 1, None, None), + ], +) +def test_cross_face_diffs(od, ix, iy, faces, iface, valx, valy): + _ds = mates(od._ds) + face_connections = od.face_connections["face"] + + nix, niy = fill_path(ix, iy, faces, iface, face_connections) + diffX, diffY, tdx, tdy = cross_face_diffs( + _ds, nix, niy, faces, iface, face_connections + ) + + assert (abs(diffX) + abs(diffY) == 1).all() + + if tdx.size: + assert tdx == valx + assert tdy == valy + assert len(diffX) == len(nix) + else: + assert len(diffX) == len(nix) - 1 + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "iX, iY, faces", + [ + ([61], [89], [10]), + ([61, 61, 61, 89], [50, 50, 89, 50], [10]), + ([61, 61, 61, 89], [50, 50, 89, 50], [10]), + ], +) +def test_station_singleface(od, iX, iY, faces): + _ds = mates(od._ds) + Yind, Xind = _xr.broadcast(_ds["Y"], _ds["X"]) + Yind = Yind.expand_dims({"face": _ds["face"]}) + Xind = Xind.expand_dims({"face": _ds["face"]}) + _ds["Xind"] = Xind.transpose(*_ds["XC"].dims) + _ds["Yind"] = Yind.transpose(*_ds["YC"].dims) + _ds = _ds.set_coords(["Yind", "Xind"]) + face_connections = od.face_connections["face"] + dsf = station_singleface(_ds, iX, iY, faces, 0, face_connections) + + _set = set(tuple((iX[i], iY[i])) for i in range(len(iX))) + + assert len(_set) == len(dsf.station) + + for m in range(len(dsf.station)): + yargs0 = {"Yp1": 0, "station": m} + yargs1 = {"Yp1": 1, "station": m} + xargs0 = {"Xp1": 0, "station": m} + xargs1 = {"Xp1": 1, "station": m} + YG0 = dsf.YG.isel(**yargs0).values + YG1 = dsf.YG.isel(**yargs1).values + XG0 = dsf.XG.isel(**xargs0).values + XG1 = dsf.XG.isel(**xargs1).values + + assert (YG0 < YG1).flatten().all() + assert (XG0 < XG1).flatten().all() + + +y0 = [k for k in range(45, 80)] +x0 = len(y0) * [40] + +# face 1 +y11 = [k for k in range(0, 11)] +x11 = [49 + 4 * k for k in range(11)] + +y12 = [k for k in range(11, 16)] +x12 = len(y12) * [89] + +x13 = [k for k in range(45, 60)] +y13 = len(x13) * [25] + +y14 = [k for k in range(25, 35)] +x14 = len(y14) * [89] + +x15 = [k for k in range(45, 60)] +y15 = len(x15) * [45] + +x16 = [k for k in range(70, 80)] +y16 = len(x16) * [87] + +x17 = [k for k in range(80, 85)] +y17 = len(x17) * [79] + +x1 = x11 + x12 + x13 + x14 + x15 + x16 + x17 +y1 = y11 + y12 + y13 + y14 + y15 + y16 + y17 + +# face 4 +x41 = [k for k in range(5, 46)] +y41 = len(x41) * [60] +y42 = [k for k in range(59, 10, -1)] +x42 = len(y42) * [45] +x4 = x41 + x42 +y4 = y41 + y42 + +# face 3 +y31 = [k for k in range(80, 40, -1)] +x31 = len(y31) * [60] +x32 = [k for k in range(60, 5, -1)] +y32 = len(x32) * [40] +x3 = x31 + x32 +y3 = y31 + y32 + +# face 0 again! +x01 = [k for k in range(80, 45, -1)] +y01 = len(x01) * [45] + +# get them all together +# cyclonic orientation +Xc, Yc = [x0, x1, x4, x3, x01], [y0, y1, y4, y3, y01] + +# faces +faces1 = [1, 2, 5, 4, 1] + + +# another case +x11 = _np.arange(20, 69) +y11 = [20] * len(x11) +y12 = _np.arange(21, 75) +x12 = [70] * len(y12) +x1 = _np.array(list(x11) + list(x12)) +y1 = _np.array(list(y11) + list(y12)) + +x2 = _np.arange(10, 80) +y2 = _np.array([10] * len(x2)) +x3 = _np.arange(20, 75) +y3 = _np.array([25] * len(x3)) +y40 = _np.arange(5, 25) +x40 = [60] * len(y40) +x41 = _np.arange(60, 20, -1) +y41 = [30] * len(x41) +y42 = _np.arange(20, 4, -1) +x42 = [20] * len(y42) +x4 = _np.array(list(x40) + list(x41) + list(x42)) +y4 = _np.array(list(y40) + list(y41) + list(y42)) +x5 = _np.arange(60, 10, -1) +y5 = _np.array([65] * len(x5)) +x6 = _np.arange(60, 10, -1) +y6 = _np.array([80] * len(x6)) +y7 = _np.arange(85, 21, -1) +x7 = [19] * len(y7) + +XX, YY = [x1, x2, x3, x4, x5, x6, x7], [y1, y2, y3, y4, y5, y6, y7] +xfaces = [10, 2, 5, 7, 5, 2, 10] + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "iX, iY, faces, iface", + [ + (Xc, Yc, faces1, 0), + (Xc, Yc, faces1, 1), + (Xc, Yc, faces1, 2), + (Xc, Yc, faces1, 3), + (XX, YY, xfaces, 0), + (XX, YY, xfaces, 1), + (XX, YY, xfaces, 2), + (XX, YY, xfaces, 3), + (XX, YY, xfaces, 4), + (XX, YY, xfaces, 5), + (XX, YY, xfaces, 6), + ], +) +def test_mooring_singleface(od, iX, iY, faces, iface): + _ds = mates(od._ds) + Yind, Xind = _xr.broadcast(_ds["Y"], _ds["X"]) + Yind = Yind.expand_dims({"face": _ds["face"]}) + Xind = Xind.expand_dims({"face": _ds["face"]}) + _ds["Xind"] = Xind.transpose(*_ds["XC"].dims) + _ds["Yind"] = Yind.transpose(*_ds["YC"].dims) + _ds = _ds.set_coords(["Yind", "Xind"]) + face_connections = od.face_connections["face"] + + niX, niY = fill_path(iX, iY, faces, iface, face_connections) + dsf, *a = mooring_singleface(_ds, niX, niY, faces, iface, face_connections) + + for m in range(len(dsf["mooring"])): + yargs0 = {"Yp1": 0, "mooring": m} + yargs1 = {"Yp1": 1, "mooring": m} + xargs0 = {"Xp1": 0, "mooring": m} + xargs1 = {"Xp1": 1, "mooring": m} + + YG0 = dsf.YG.isel(**yargs0).values + YG1 = dsf.YG.isel(**yargs1).values + XG0 = dsf.XG.isel(**xargs0).values + XG1 = dsf.XG.isel(**xargs1).values + + assert (YG0 < YG1).flatten().all() + assert (XG0 < XG1).flatten().all() + + +ixx, iyy = _np.array([0, 89, 45, 45]), _np.array([45, 45, 0, 89]) +faces1 = [6, 6] +faces2 = [7, 10] + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "ix, iy, face1, face2", + [ + (ixx[1:2], iyy[1:2], faces1[0], faces2[0]), + (ixx[3:], iyy[3:], faces1[1], faces2[1]), + (_np.array([45]), _np.array([89]), 2, 6), + (_np.array([45]), _np.array([89]), 5, 6), + ], +) +def test_ds_arcedge(od, ix, iy, face1, face2): + _dim = "mooring" # does not matter + dsf = ds_arcedge(od._ds, ix, iy, _np.array([0]), face1, face2, _dim) + + assert len(dsf.Xp1) == 2 + assert len(dsf.Yp1) == 2 + assert len(dsf.X) == 1 + assert len(dsf.Y) == 1 + + for m in range(len(dsf[_dim])): + yargs0 = {"Yp1": 0, _dim: m} + yargs1 = {"Yp1": 1, _dim: m} + xargs0 = {"Xp1": 0, _dim: m} + xargs1 = {"Xp1": 1, _dim: m} + YG0 = dsf.YG.isel(**yargs0).values + YG1 = dsf.YG.isel(**yargs1).values + XG0 = dsf.XG.isel(**xargs0).values + XG1 = dsf.XG.isel(**xargs1).values + assert (YG0 < YG1).flatten().all() + assert (XG0 < XG1).flatten().all() + + +# include : +# array than begins and ends at 0 indexes +# array thatn beings at two 89 indexes on same axis +# array that being and ends at two 89 axis on different axis. + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "ix, iy, faces, k, kwargs", + [ + (_np.array([45]), _np.array([89]), [2, 6], 0, {}), + (_np.array([45]), _np.array([89]), [5, 6], 0, {}), + (_np.array([0]), _np.array([0]), [4], 0, {}), + (_np.array([89]), _np.array([10]), [0, 3], 0, {"axis": "x"}), + (_np.array([89]), _np.array([10]), [3, 9], 0, {}), + (_np.array([10]), _np.array([89]), [0, 1], 0, {"axis": "y"}), + (_np.array([10]), _np.array([89]), [7, 10], 0, {"axis": "y"}), + (_np.array([89]), _np.array([10]), [7, 8], 0, {"axis": "x"}), + (_np.array([10]), _np.array([89]), [1, 2], 0, {"axis": "y"}), + (_np.array([10, 89]), _np.array([89, 10]), [1, 4], 0, {"axis": "x"}), + (_np.array([10, 89]), _np.array([89, 10]), [2, 1], 1, {"axis": "y"}), + (_np.array([10, 89]), _np.array([89, 10]), [1, 2], 0, {"axis": "t"}), + ], +) +def test_ds_edge(od, ix, iy, faces, k, kwargs): + face_connections = od.face_connections["face"] + axis = kwargs.pop("axis", None) + args = { + "_ds": od._ds, + "_ix": ix, + "_iy": iy, + "_ifaces": faces, + "ii": k, + "_face_topo": face_connections, + } + if axis is not None and axis not in ["x", "y"]: + kwargs = {"axis": axis} + with pytest.raises(ValueError): + ds_edge(**args, **kwargs) + else: + kwargs = {"axis": axis} + nds, connect, moor, moors = ds_edge(**args, **kwargs) + if set([6]).issubset(faces): + mds = ds_arcedge(od._ds, ix, iy, moor, faces[0], faces[1]) + if _xr.testing.assert_equal(mds, nds): + assert 1 + else: + if set([89]).issubset(set.union(set(ix), set(iy))): + _dim = "mooring" + assert isinstance(nds, _dstype) + assert len(nds.Xp1) == 2 + assert len(nds.Yp1) == 2 + assert len(nds.X) == 1 + assert len(nds.Y) == 1 + assert "face" not in nds.reset_coords().data_vars + + for m in range(len(nds[_dim])): + yargs0 = {"Yp1": 0, _dim: m} + yargs1 = {"Yp1": 1, _dim: m} + xargs0 = {"Xp1": 0, _dim: m} + xargs1 = {"Xp1": 1, _dim: m} + YG0 = nds.YG.isel(**yargs0).values + YG1 = nds.YG.isel(**yargs1).values + XG0 = nds.XG.isel(**xargs0).values + XG1 = nds.XG.isel(**xargs1).values + assert (YG0 < YG1).flatten().all() + assert (XG0 < XG1).flatten().all() + else: + assert connect is False + + +ixx, iyy = _np.array([10, 45, 80, 45]), _np.array([45, 10, 45, 80]) + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "ix, iy", + [ + (ixx[:1], iyy[:1]), + (ixx[1:2], iyy[1:2]), + (ixx[2:3], iyy[2:3]), + (ixx[3:], iyy[3:]), + (ixx, iyy), + ], +) +def test_arctic_eval(od, ix, iy): + _dim = "station" + nds = arctic_eval(od._ds, ix, iy, _dim) + + assert isinstance(nds, _dstype) + assert len(nds.Xp1) == 2 + assert len(nds.Yp1) == 2 + assert len(nds.X) == 1 + assert len(nds.Y) == 1 + + for m in range(len(nds[_dim])): + yargs0 = {"Yp1": 0, _dim: m} + yargs1 = {"Yp1": 1, _dim: m} + xargs0 = {"Xp1": 0, _dim: m} + xargs1 = {"Xp1": 1, _dim: m} + YG0 = nds.YG.isel(**yargs0).values + YG1 = nds.YG.isel(**yargs1).values + XG0 = nds.XG.isel(**xargs0).values + XG1 = nds.XG.isel(**xargs1).values + assert (YG0 < YG1).flatten().all() + assert (XG0 < XG1).flatten().all() + + +y2 = _np.arange(79, 10, -1) +x2 = _np.array([10] * len(y2)) + +x5 = _np.arange(10, 80) +y5 = _np.array([10] * len(x5)) + +y7 = _np.arange(11, 80) +x7 = _np.array([79] * len(y7)) + +x10 = _np.arange(78, 10, -1) +y10 = _np.array([79] * len(x10)) + +Xc = _np.append(_np.append(_np.append(x2, x5), x7), x10) +Yc = _np.append(_np.append(_np.append(y2, y5), y7), y10) + +Xc, Yc = connector(Xc, Yc) +Xac, Yac = connector(Xc[::-1], Yc[::-1]) + +valx = _np.ones(_np.shape(Xc)[1:]) + + +y20 = _np.arange(79, 50, -1) +x20 = _np.array([10] * len(y20)) + +x21 = _np.arange(10, 30) +y21 = _np.array([50] * len(x21)) + +y22 = _np.arange(50, 40, -1) +x22 = _np.array([30] * len(y22)) + +x23 = _np.arange(30, 10, -1) +y23 = [40] * len(x23) + +y24 = _np.arange(40, 10, -1) +x24 = _np.array([10] * len(y24)) + +nx2 = _np.array(list(x20) + list(x21) + list(x22) + list(x23) + list(x24)) +ny2 = _np.array(list(y20) + list(y21) + list(y22) + list(y23) + list(y24)) + + +x50 = _np.arange(11, 40) +y50 = _np.array([10] * len(x50)) + +y51 = _np.arange(10, 30) +x51 = [40] * len(y51) + +x52 = _np.arange(40, 50) +y52 = [30] * len(x52) + +y53 = _np.arange(30, 10, -1) +x53 = [50] * len(y53) + +x54 = _np.arange(50, 80) +y54 = [10] * len(x54) + +nx5 = _np.array(list(x50) + list(x51) + list(x52) + list(x53) + list(x54)) +ny5 = _np.array(list(y50) + list(y51) + list(y52) + list(y53) + list(y54)) + +y70 = _np.arange(11, 40) +x70 = _np.array([79] * len(y70)) + +x71 = _np.arange(79, 60, -1) +y71 = [40] * len(x71) + +y72 = _np.arange(40, 50) +x72 = [60] * len(y72) + +x73 = _np.arange(60, 80) +y73 = [50] * len(x73) + +y74 = _np.arange(50, 80) +x74 = [79] * len(y74) + +nx7 = _np.array(list(x70) + list(x71) + list(x72) + list(x73) + list(x74)) +ny7 = _np.array(list(y70) + list(y71) + list(y72) + list(y73) + list(y74)) + +x100 = _np.arange(78, 50, -1) +y100 = _np.array([79] * len(x100)) + +y101 = _np.arange(79, 59, -1) +x101 = [50] * len(y101) + +x102 = _np.arange(50, 40, -1) +y102 = [59] * len(x102) + +y103 = _np.arange(59, 79) +x103 = [40] * len(y103) + +x104 = _np.arange(40, 10, -1) +y104 = [79] * len(x104) + +nx10 = _np.array(list(x100) + list(x101) + list(x102) + list(x103) + list(x104)) +ny10 = _np.array(list(y100) + list(y101) + list(y102) + list(y103) + list(y104)) + + +nXc = _np.append(_np.append(_np.append(nx2, nx5), nx7), nx10) +nYc = _np.append(_np.append(_np.append(ny2, ny5), ny7), ny10) + +nXc, nYc = connector(nXc, nYc) + +# solution to nXc, nYc +x20 = _np.arange(29) +y20 = _np.array([10] * len(x20)) + +y21 = _np.arange(10, 30) +x21 = _np.array([29] * len(y21)) + +x22 = _np.arange(29, 39) +y22 = _np.array([30] * len(x22)) + +y23 = _np.arange(30, 10, -1) +x23 = [39] * len(y23) + +x24 = _np.arange(40, 70) +y24 = _np.array([10] * len(x24)) + +xs2 = _np.array(list(x20) + list(x21) + list(x22) + list(x23) + list(x24)) +ys2 = _np.array(list(y20) + list(y21) + list(y22) + list(y23) + list(y24)) + + +x50 = _np.arange(xs2[-1], xs2[-1] + 30) +y50 = _np.array([10] * len(x50)) + +y51 = _np.arange(10, 30) +x51 = [xs2[-1] + 30] * len(y51) + +x52 = _np.arange(xs2[-1] + 30, xs2[-1] + 41) +y52 = [30] * len(x52) + +y53 = _np.arange(30, 10, -1) +x53 = [xs2[-1] + 40] * len(y53) + +x54 = _np.arange(xs2[-1] + 40, xs2[-1] + 70) +y54 = [10] * len(x54) + +xs5 = _np.array(list(x50) + list(x51) + list(x52) + list(x53) + list(x54)) +ys5 = _np.array(list(y50) + list(y51) + list(y52) + list(y53) + list(y54)) + + +x70 = _np.arange(xs5[-1], xs5[-1] + 30) +y70 = _np.array([10] * len(x70)) + +y71 = _np.arange(10, 29) +x71 = [xs5[-1] + 30] * len(y71) + +x72 = _np.arange(xs5[-1] + 30, xs5[-1] + 40) +y72 = [29] * len(x72) + +y73 = _np.arange(29, 9, -1) +x73 = [xs5[-1] + 40] * len(y73) + +x74 = _np.arange(xs5[-1] + 42, xs5[-1] + 70) +y74 = [10] * len(x74) + +xs7 = _np.array(list(x70) + list(x71) + list(x72) + list(x73) + list(x74)) +ys7 = _np.array(list(y70) + list(y71) + list(y72) + list(y73) + list(y74)) + + +x100 = _np.arange(xs7[-1], xs7[-1] + 29) +y100 = _np.array([10] * len(x100)) + +y101 = _np.arange(10, 30) +x101 = [xs7[-1] + 29] * len(y101) + +x102 = _np.arange(xs7[-1] + 29, xs7[-1] + 39) +y102 = [30] * len(x102) + +y103 = _np.arange(30, 10, -1) +x103 = [xs7[-1] + 39] * len(y103) + +x104 = _np.arange(xs7[-1] + 40, xs7[-1] + 69) +y104 = [10] * len(x104) + +xs10 = _np.array(list(x100) + list(x101) + list(x102) + list(x103) + list(x104)) +ys10 = _np.array(list(y100) + list(y101) + list(y102) + list(y103) + list(y104)) + + +Xsc = _np.append(_np.append(_np.append(xs2, xs5), xs7), xs10) +Ysc = _np.append(_np.append(_np.append(ys2, ys5), ys7), ys10) + +nXsc, nYsc = connector(Xsc, Ysc) +soln_diffX, soln_diffY = _np.diff(nXsc), _np.diff(nYsc) + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "ix, iy, ediffX, ediffY", + [ + (Xc, Yc, valx, 0 * valx), + (Xac, Yac, -valx, 0 * valx), + (nXc, nYc, soln_diffX, soln_diffY), + ], +) +def test_arct_diffs(od, ix, iy, ediffX, ediffY): + _ds = od._ds + diffX, diffY, cset, miss = arct_diffs(_ds, ix, iy) + full_set = set(tuple((ix[i], iy[i]) for i in range(len(ix)))) + miss_set = set(tuple((ix[miss[j]], iy[miss[j]]) for j in range(len(miss)))) + assert len(diffX) == len(ix) - 1 + assert len(diffY) == len(iy) - 1 + assert full_set == cset.union(miss_set) + assert (abs(diffX) + abs(diffY) == 1).all() + + if ediffX is not None: + assert (diffX == ediffX).all() + assert (diffY == ediffY).all() + + +y1 = [k for k in range(45, 90)] +x1 = len(y1) * [40] + +# crossing in y +Y1, X1 = _np.array(y1), _np.array(x1) +# crossing in x +Y2, X2 = _np.array(x1), _np.array(y1) + +varlist = [var for var in od._ds.reset_coords().data_vars] +zcoords = ["Zl", "Zu", "Zp1"] +tcoords = ["time_midp"] +uvars = zcoords + tcoords # u-points +vvars = zcoords + tcoords # v-points +gvars = zcoords + tcoords # corner points +cvars = zcoords + tcoords +for var in varlist: + if set(["Xp1", "Y"]).issubset(od._ds[var].dims): + uvars.append(var) + if set(["Xp1", "Yp1"]).issubset(od._ds[var].dims): + gvars.append(var) + if set(["Yp1", "X"]).issubset(od._ds[var].dims): + vvars.append(var) + if set(["Y", "X"]).issubset(od._ds[var].dims): + cvars.append(var) + +vkwargs = {"u": uvars, "v": vvars, "g": gvars, "c": cvars} + +# face 1 +faces1 = [1, 2] # crosses in y - same topo +faces2 = [7, 10] # corsses in y - diff topo + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "_ix, _iy, faces, vkwargs", + [ + (X1, Y1, faces1, vkwargs), + (X1, Y1, faces2, vkwargs), + ], +) +def test_ds_edge_samety(od, _ix, _iy, faces, vkwargs): + _dim_name = "mooring" + _ds = od._ds + new_dim = _xr.DataArray(_np.arange(len(_ix)), dims=(_dim_name)) + y = _xr.DataArray(_np.arange(1), dims=("y")) + x = _xr.DataArray(_np.arange(1), dims=("x")) + yp1 = _xr.DataArray(_np.arange(2), dims=("yp1")) + xp1 = _xr.DataArray(_np.arange(2), dims=("xp1")) + # Transform indexes in DataArray + iY = _xr.DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = _xr.DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + iYp1 = _xr.DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + iXp1 = _xr.DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + # crossing in y + Yval = iYp1.where(iYp1 == 90, drop=True) + moor = Yval[_dim_name] + + nds, vds, mds = ds_edge_samety( + _ds, + iX, + iY, + _ix, + xp1, + iXp1, + iYp1, + faces[0], + faces[1], + "mooring", + moor, + **vkwargs, + ) + assert (nds.mooring == moor).values.all() + assert (vds.mooring == mds.mooring).values.all() + assert len(vds.yp1) == 1 + assert vds.yp1.values == 1 + assert mds.yp1.values == 0 + assert len(mds.yp1) == 1 + assert (mds.xp1.values == _np.array([0, 1])).all() + assert len(vds.xp1) == 2 + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "_ix, _iy, faces, vkwargs", + [ + (Y1, X1, [1, 4], vkwargs), + ], +) +def test_ds_edge_sametx(od, _ix, _iy, faces, vkwargs): + _dim_name = "mooring" + _ds = od._ds + new_dim = _xr.DataArray(_np.arange(len(_ix)), dims=(_dim_name)) + y = _xr.DataArray(_np.arange(1), dims=("y")) + x = _xr.DataArray(_np.arange(1), dims=("x")) + yp1 = _xr.DataArray(_np.arange(2), dims=("yp1")) + xp1 = _xr.DataArray(_np.arange(2), dims=("xp1")) + # Transform indexes in DataArray + iY = _xr.DataArray( + _np.reshape(_iy, (len(new_dim), len(y))), + coords={_dim_name: new_dim, "y": y}, + dims=(_dim_name, "y"), + ) + iX = _xr.DataArray( + _np.reshape(_ix, (len(new_dim), len(x))), + coords={_dim_name: new_dim, "x": x}, + dims=(_dim_name, "x"), + ) + iYp1 = _xr.DataArray( + _np.stack((_iy, _iy + 1), 1), + coords={_dim_name: new_dim, "yp1": yp1}, + dims=(_dim_name, "yp1"), + ) + iXp1 = _xr.DataArray( + _np.stack((_ix, _ix + 1), 1), + coords={_dim_name: new_dim, "xp1": xp1}, + dims=(_dim_name, "xp1"), + ) + + # crossing in y + Xval = iXp1.where(iXp1 == 90, drop=True) + moor = Xval[_dim_name] + + nds, vds, mds = ds_edge_sametx( + _ds, iX, iY, iXp1, iYp1, faces[0], faces[1], "mooring", moor, **vkwargs + ) + assert (nds.mooring == moor).values.all() + assert (vds.mooring == mds.mooring).values.all() + assert vds.xp1.values == 1 + assert mds.xp1.values == 0 + assert len(mds.xp1) == 1 + assert (mds.yp1.values == _np.array([0, 1])).all() + assert len(vds.yp1) == 2 + + +# face 1 +y11 = [k for k in range(0, 11)] +x11 = [49 + 4 * k for k in range(11)] + +y12 = [k for k in range(11, 16)] +x12 = len(y12) * [89] + +x13 = [k for k in range(45, 60)] +y13 = len(x13) * [25] + +y14 = [k for k in range(25, 35)] +x14 = len(y14) * [89] + +x15 = [k for k in range(45, 60)] +y15 = len(x15) * [45] + +x16 = [k for k in range(70, 80)] +y16 = len(x16) * [89] + +x17 = [k for k in range(80, 85)] +y17 = len(x17) * [79] + +x1 = x11 + x12 + x13 + x14 + x15 + x16 + x17 +y1 = y11 + y12 + y13 + y14 + y15 + y16 + y17 + +faces1 = [1, 2] + + +@pytest.mark.parametrize("od", [od]) +@pytest.mark.parametrize( + "ix, iy, faces, iface", + [ + (x1, y1, faces1, 1), + (x1[::-1], y1[::-1], faces1, 1), + ], +) +def test_ds_splitter(od, ix, iy, faces, iface): + _ds = od._ds.drop_vars(["Xind", "Yind"]) + face_connections = od.face_connections["face"] + _Nx = len(_ds.X) - 1 + _ixn, _iyn = connector(ix, iy) + nI = index_splitter(_ixn, _iyn, _Nx) + args = { + "_ds": _ds, + "_iXn": _ixn, + "_iYn": _iyn, + "_nI": nI, + "_faces": faces, + "_iface": iface, + "_face_connections": face_connections, + "_dim_name": "mooring", + } + dsf = ds_splitarray(**args) + assert len(_ixn) == len(dsf.mooring) diff --git a/oceanspy/tests/test_subsample.py b/oceanspy/tests/test_subsample.py index 09df0869..7ce98418 100644 --- a/oceanspy/tests/test_subsample.py +++ b/oceanspy/tests/test_subsample.py @@ -23,6 +23,10 @@ ECCO_url = "{}catalog_ECCO.yaml".format(Datadir) ECCOod = open_oceandataset.from_catalog("LLC", ECCO_url) +ECCOod._ds = ECCOod._ds.rename_vars( + {"hFacS": "HFacS", "hFacW": "HFacW", "hFacC": "HFacC"} +) + # ======= # CUTOUT @@ -330,26 +334,41 @@ def test_cutout_faces( @pytest.mark.parametrize("od", [MITgcm_rect_nc, ECCOod]) @pytest.mark.parametrize("cartesian", [True, False]) @pytest.mark.parametrize( - "kwargs", [{}, {"YRange": None, "XRange": None, "add_Hbdr": True}] + "kwargs", + [ + {}, + {"YRange": None, "XRange": None, "add_Hbdr": True}, + {"YRange": [74, 78], "XRange": None}, + ], ) def test_mooring(od, cartesian, kwargs): this_od = od - if cartesian: - this_od = this_od.set_parameters({"rSphere": None}) - - if "face" not in od.dataset.dims: + serial = False + if "face" not in this_od.dataset.dims: Xmoor = [this_od.dataset["XC"].min().values, this_od.dataset["XC"].max().values] Ymoor = [this_od.dataset["YC"].min().values, this_od.dataset["YC"].max().values] + kwargs.pop("XRange", None) + kwargs.pop("YRange", None) else: - Xmoor = [-80, 0] - Ymoor = [35, 35] + if kwargs.pop("XRange", None) is None and kwargs.pop("YRange", None) is None: + Xmoor = [-80, 0] + Ymoor = [35, 35] + else: + Xmoor = np.arange(-179.5, 179.5) + Ymoor = 76 * np.ones(np.shape(Xmoor)) + serial = True + if cartesian: + this_od = this_od.set_parameters({"rSphere": None}) + + kwargs["serial"] = serial + new_od = this_od.subsample.mooring_array(Xmoor=Xmoor, Ymoor=Ymoor, **kwargs) with pytest.raises(ValueError): new_od.subsample.mooring_array(Xmoor=Xmoor, Ymoor=Ymoor) for index in [0, -1]: - if "face" not in od.dataset.dims: + if "face" not in this_od.dataset.dims: assert new_od.dataset["XC"].isel(mooring=index).values == Xmoor[index] assert new_od.dataset["YC"].isel(mooring=index).values == Ymoor[index] else: @@ -431,22 +450,35 @@ def test_survey(od, cartesian, delta, kwargs): # STATIONS # ======== # create cyclonic vel -nU = _copy.deepcopy(ECCOod._ds["CS"].values) -nV = -_copy.deepcopy(ECCOod._ds["SN"].values) +co_list = [var for var in ECCOod._ds.coords if var not in ECCOod._ds.dims] + +nU = _copy.deepcopy(ECCOod._ds["CS"]).expand_dims({"time": 1}).values +nV = -_copy.deepcopy(ECCOod._ds["SN"]).expand_dims({"time": 1}).values + Ucoords = { + "time": ECCOod._ds.time.values, "face": ECCOod._ds.face.values, "Y": ECCOod._ds.Y.values, "Xp1": ECCOod._ds.Xp1.values, } + Vcoords = { + "time": ECCOod._ds.time.values, "face": ECCOod._ds.face.values, "Yp1": ECCOod._ds.Yp1.values, "X": ECCOod._ds.X.values, } -ECCOod._ds["UVELMASS"] = xr.DataArray(nU, coords=Ucoords, dims=["face", "Y", "Xp1"]) -ECCOod._ds["VVELMASS"] = xr.DataArray(nV, coords=Vcoords, dims=["face", "Yp1", "X"]) -ECCOod._ds = mates(ECCOod._ds) +ECCOod._ds["UVELMASS"] = xr.DataArray( + nU, coords=Ucoords, dims=["time", "face", "Y", "Xp1"] +) +ECCOod._ds["VVELMASS"] = xr.DataArray( + nV, coords=Vcoords, dims=["time", "face", "Yp1", "X"] +) + + +ECCOod._ds = mates(ECCOod._ds.set_coords(co_list)) + # coordinate locations lons76N = np.array([6.2, 97.8, -172.21623, -83.78377]) @@ -460,45 +492,178 @@ def test_survey(od, cartesian, delta, kwargs): lons170W = -170 * np.ones(np.shape(lats_6E)) -@pytest.mark.parametrize("this_od", [ECCOod]) +# == +y0 = [k for k in range(45, 80)] +x0 = len(y0) * [40] + +# face 1 +y11 = [k for k in range(0, 11)] +x11 = [49 + 4 * k for k in range(11)] + +y12 = [k for k in range(11, 16)] +x12 = len(y12) * [89] + +x13 = [k for k in range(45, 60)] +y13 = len(x13) * [25] + +y14 = [k for k in range(25, 35)] +x14 = len(y14) * [89] + +x15 = [k for k in range(45, 60)] +y15 = len(x15) * [45] + +x16 = [k for k in range(70, 80)] +y16 = len(x16) * [89] + +x17 = [k for k in range(80, 85)] +y17 = len(x17) * [79] + +x1 = x11 + x12 + x13 + x14 + x15 + x16 + x17 +y1 = y11 + y12 + y13 + y14 + y15 + y16 + y17 + +# face 4 +x41 = [k for k in range(5, 46)] +y41 = len(x41) * [60] +y42 = [k for k in range(59, 10, -1)] +x42 = len(y42) * [45] +x4 = x41 + x42 +y4 = y41 + y42 + +# face 3 +y31 = [k for k in range(80, 40, -1)] +x31 = len(y31) * [60] +x32 = [k for k in range(60, 5, -1)] +y32 = len(x32) * [40] +x3 = x31 + x32 +y3 = y31 + y32 + +# face 0 again! +x01 = [k for k in range(80, 45, -1)] +y01 = len(x01) * [45] + +# cyclonic orientation +Xc, Yc = [x0, x1, x4, x3, x01], [y0, y1, y4, y3, y01] + +# faces +faces1 = [1, 2, 5, 4, 1] + +# extract lats/lons from data +lonsc, latsc = [], [] +for i in range(len(Xc)): + for j in range(len(Xc[i])): + lonsc.append( + ECCOod._ds["XC"] + .isel(face=faces1[i], X=Xc[i][j], Y=Yc[i][j]) + .squeeze() + .values + ) + latsc.append( + ECCOod._ds["YC"] + .isel(face=faces1[i], X=Xc[i][j], Y=Yc[i][j]) + .squeeze() + .values + ) + +lons1, lats1 = [], [] +for j in range(len(Xc[1])): + lons1.append( + ECCOod._ds["XC"].isel(face=faces1[1], X=Xc[1][j], Y=Yc[1][j]).squeeze().values + ) + lats1.append( + ECCOod._ds["YC"].isel(face=faces1[1], X=Xc[1][j], Y=Yc[1][j]).squeeze().values + ) + + +lons0, lats0 = [], [] +for j in range(len(Xc[0])): + lons0.append( + ECCOod._ds["XC"].isel(face=faces1[0], X=Xc[0][j], Y=Yc[0][j]).squeeze().values + ) + lats0.append( + ECCOod._ds["YC"].isel(face=faces1[0], X=Xc[0][j], Y=Yc[0][j]).squeeze().values + ) + + +@pytest.mark.parametrize("od", [ECCOod]) @pytest.mark.parametrize( "args", [ {"Ycoords": None, "Xcoords": None}, {"Ycoords": lats76N, "Xcoords": lons76N}, + { + "Ycoords": lats76N, + "Xcoords": lons76N, + "Zcoords": 0, + "tcoords": "1992-01-16T12", + }, + { + "Ycoords": lats76N, + "Xcoords": lons76N, + "varList": ["T", "UVELMASS", "VVELMASS"], + }, + {"Ycoords": lats76N, "Xcoords": lons76N, "xoak_index": "invalid"}, {"Ycoords": lats_6E, "Xcoords": lons6E}, {"Ycoords": lats_6E, "Xcoords": lons90W}, {"Ycoords": lats_6E, "Xcoords": lons170W}, + {"Ycoords": latsc, "Xcoords": lonsc, "_dim": "mooring"}, + {"Ycoords": lats1, "Xcoords": lons1, "_dim": "mooring"}, + {"Ycoords": lats0, "Xcoords": lons0}, ], ) -def test_stations(this_od, args): - od_stns = this_od.subsample.stations(**args) - - if args["Ycoords"] is None or args["Xcoords"] is None: - assert this_od._ds.XC.shape == od_stns._ds.XC.shape - assert this_od._ds.YC.shape == od_stns._ds.YC.shape +def test_stations(od, args): + this_od = _copy.deepcopy(od) + xoak_index = args.pop("xoak_index", None) + _dim = args.pop("_dim", None) + if xoak_index is not None: + with pytest.raises(ValueError): + this_od.subsample.stations(**args, xoak_index=xoak_index) + if _dim is not None and _dim == "mooring": + DS, diffX, diffY = this_od.subsample.stations(**args, dim_name=_dim) + assert (abs(diffX) + abs(diffY) == 1).all() + assert isinstance(DS, xr.Dataset) else: - YC, XC = args["Ycoords"], args["Xcoords"] - XCstn, YCstn = od_stns._ds.XC, od_stns._ds.YC - XGstn, YGstn = od_stns._ds.XG, od_stns._ds.YG - stations = od_stns._ds.station.values - argsu0, argsu1 = {"Xp1": 0}, {"Xp1": 1} - argsv0, argsv1 = {"Yp1": 0}, {"Yp1": 1} - assert len(stations) == len(XC) == len(YC) - for i in range(len(stations)): - assert XGstn.isel(station=i, Xp1=0, Yp1=0).values < XCstn.isel(station=i) - assert XGstn.isel(station=i, Xp1=1, Yp1=0).values > XCstn.isel(station=i) - assert YGstn.isel(station=i, Xp1=0, Yp1=0).values < YCstn.isel(station=i) - assert YGstn.isel(station=i, Xp1=0, Yp1=1).values > YCstn.isel(station=i) - - Uval0 = od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu0}).values - Uval1 = od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu1}).values - Vval0 = od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv0}).values - Vval1 = od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv1}).values - - assert np.round(abs(Uval0), 1) == np.round(abs(Uval1), 1) == 1 - assert np.round(abs(Vval0), 1) <= 0.1 - assert np.round(abs(Vval1), 1) <= 0.1 + od_stns = this_od.subsample.stations(**args) + if args["Ycoords"] is None or args["Xcoords"] is None: + assert this_od._ds.XC.shape == od_stns._ds.XC.shape + assert this_od._ds.YC.shape == od_stns._ds.YC.shape + else: + YC, XC = args["Ycoords"], args["Xcoords"] + XCstn, YCstn = od_stns._ds.XC.squeeze(), od_stns._ds.YC.squeeze() + XGstn, YGstn = od_stns._ds.XG, od_stns._ds.YG + stations = od_stns._ds.station.values + argsu0, argsu1 = {"Xp1": 0}, {"Xp1": 1} + argsv0, argsv1 = {"Yp1": 0}, {"Yp1": 1} + assert len(stations) == len(XC) == len(YC) + for i in range(len(stations)): + assert XGstn.isel(station=i, Xp1=0, Yp1=0).values < XCstn.isel( + station=i + ) + assert XGstn.isel(station=i, Xp1=1, Yp1=0).values > XCstn.isel( + station=i + ) + assert YGstn.isel(station=i, Xp1=0, Yp1=0).values < YCstn.isel( + station=i + ) + assert YGstn.isel(station=i, Xp1=0, Yp1=1).values > YCstn.isel( + station=i + ) + + Uval0 = ( + od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu0}).values + ) + Uval1 = ( + od_stns._ds["UVELMASS"].isel(**{**{"station": i}, **argsu1}).values + ) + Vval0 = ( + od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv0}).values + ) + Vval1 = ( + od_stns._ds["VVELMASS"].isel(**{**{"station": i}, **argsv1}).values + ) + + assert np.round(abs(Uval0), 1) == np.round(abs(Uval1), 1) == 1 + assert np.round(abs(Vval0), 1) <= 0.1 + assert np.round(abs(Vval1), 1) <= 0.1 # ========= diff --git a/oceanspy/tests/test_utils.py b/oceanspy/tests/test_utils.py index e9c1cf7d..f3684617 100644 --- a/oceanspy/tests/test_utils.py +++ b/oceanspy/tests/test_utils.py @@ -7,6 +7,7 @@ _reset_range, cartesian_path, circle_path_array, + connector, great_circle_path, spherical2cartesian, viewer_to_range, @@ -17,15 +18,6 @@ def test_RNone(): spherical2cartesian(1, 1) -def test_error_viewer_to_range(): - with pytest.raises(TypeError): - viewer_to_range("does not eval to a list") - viewer_to_range(0) - viewer_to_range(["not from viewer"]) - viewer_to_range([{"type": "other"}]) - viewer_to_range([{"type": "Polygon", "coordinates": "a"}]) - - def test_error_path(): with pytest.raises(ValueError): great_circle_path(1, 1, 1, 1) @@ -75,6 +67,10 @@ def test_circle_path_array(lats, lons, symmetry, resolution): coords5 = '[{"type":"Point","coordinates":[636.7225446274502, -56.11128546740994]}]' coords6 = '[{"type":"Point","coordinates":[754.2277421326479, -57.34299561290217]}]' coords7 = '[{"type":"Point","coordinates":[-424.42989807993234, 37.87263032287052]}]' +coords8 = ( + '[{"type":"not valid","coordinates":[-424.42989807993234, 37.87263032287052]}]' +) +coords9 = '"Point","coordinates":[-169.23960833202577,22.865677261831266]}' @pytest.mark.parametrize( @@ -90,16 +86,22 @@ def test_circle_path_array(lats, lons, symmetry, resolution): (coords5, "Point", [-83.27745537254975], [-56.11128546740994]), (coords6, "Point", [34.227742132647904], [-57.34299561290217]), (coords7, "Point", [-64.42989807993234], [37.87263032287052]), + (coords8, None, None, None), + (coords9, None, None, None), ], ) def test_viewer_to_range(coords, types, lon, lat): - if isinstance(coords, list): - p = [{"type": types, "coordinates": list(coords)}] - elif isinstance(coords, str): - p = coords - x, y = viewer_to_range(p) - assert x == lon - assert y == lat + if types is not None: + if isinstance(coords, list): + p = [{"type": types, "coordinates": list(coords)}] + elif isinstance(coords, str): + p = coords + x, y = viewer_to_range(p) + assert x == lon + assert y == lat + else: + with pytest.raises(TypeError): + viewer_to_range(coords) X0 = _np.array([161, -161]) # track begins west, ends east @@ -137,3 +139,21 @@ def test_reset_range(XRange, x0, expected_ref): else: assert x_range is None assert _np.round(ref_lon, 2) == expected_ref + + +x1 = _np.array([k for k in range(0, 85, 10)]) +y1 = [int(k) for k in _np.linspace(20, 40, len(x1))] + + +@pytest.mark.parametrize( + "x, y", + [(x1, y1), (x1[::-1], y1), (x1[::-1], y1[::-1]), (x1, y1[::-1]), ([50], [50])], +) +def test_connector(x, y): + xn, yn = connector(x, y) + assert len(xn) == len(yn) + assert set(x).issubset(xn) + assert set(y).issubset(yn) + if len(xn) > 1: + diffs = abs(_np.diff(xn)) + abs(_np.diff(yn)) + assert _np.max(diffs) == _np.min(diffs) == 1 diff --git a/oceanspy/utils.py b/oceanspy/utils.py index 9f05f579..06cc3b74 100644 --- a/oceanspy/utils.py +++ b/oceanspy/utils.py @@ -10,7 +10,7 @@ # Required dependencies (private) import xarray as _xr -# From oceanspy (private) +# from .llc_rearrange import face_edge_check from ._ospy_utils import _check_instance # Recommended dependencies (private) @@ -19,19 +19,6 @@ except ImportError: # pragma: no cover pass -try: - import numba - - has_numba = True -except ImportError: - has_numba = False - - -def compilable(f): - if has_numba: - return numba.njit(f) - return f - def viewer_to_range(p): """ @@ -53,7 +40,7 @@ def viewer_to_range(p): if p[0] == "[" and p[-1] == "]": p = _ast.literal_eval(p) # turn string into list else: - TypeError("not a type extracted by poseidon viewer") + raise TypeError("not a type extracted by poseidon viewer") _check_instance({"p": p}, {"p": ["list"]}) _check_instance({"p[0]": p[0]}, {"p[0]": ["dict"]}) _check_instance({"type": p[0]["type"]}, {"type": "str"}) @@ -69,11 +56,11 @@ def viewer_to_range(p): if p_type == "Polygon": coords = p[0]["coordinates"][0] - elif p_type == "Point": + if p_type == "Point": coords = [] for i in range(len(p)): coords.append(p[i]["coordinates"]) - elif p_type == "LineString": + if p_type == "LineString": # pragma : no cover coords = p[0]["coordinates"] lon = [] @@ -161,11 +148,11 @@ def _reset_range(xn): nxn[ll] = nxn[ll] - 360 X = _np.min(nxn) + 360, _np.max(nxn) _ref_lon = X[0] - (X[0] - X[1]) / 3 - elif all(ind[0] == i for i in ind) and ind[0] == 1: # Atlantic + if all(ind[0] == i for i in ind) and ind[0] == 1: # Atlantic X = _np.min(xn), _np.max(xn) else: X = None - elif cross.size == 0 or xn.size == 2: + if cross.size == 0 or xn.size == 2: if xn.size == 2: X = xn[0], xn[1] if xn[0] > xn[1]: @@ -771,7 +758,7 @@ def densmdjwf(s, t, p): return rho -def static_pressure(Z): +def static_pressure(Z): # pragma: no cover """ Returns the static pressure given depth. """ @@ -824,7 +811,7 @@ def get_maskH(ds, add_Hbdr, XRange, YRange, ref_lon=0): time this code runs, it gets applied on a dataset without faces as a dimension. """ - if "face" in ds.dims and len(ds.X) == 4320: + if "face" in ds.dims and len(ds.X) == 4320: # pragma: no cover args = {"Xp1": slice(0, 4320, 10), "Yp1": slice(0, 4320, 10)} ds = _copy.deepcopy(ds.isel(**args)) @@ -871,86 +858,77 @@ def get_maskH(ds, add_Hbdr, XRange, YRange, ref_lon=0): return maskH, dmaskH, XRange, YRange -@compilable -def spherical2cartesian_compiled(Y, X, R=6371.0): - """ - Convert spherical coordinates to cartesian. +def reset_dim(_ds, N, dim="mooring"): + """resets the dimension mooring by shifting it by a value set by N""" + _ds["n" + dim] = N + _ds[dim] + _ds = _ds.swap_dims({dim: "n" + dim}).drop_vars(dim).rename({"n" + dim: dim}) - Parameters - ---------- - Y: np.array - Spherical Y coordinate (latitude) - X: np.array - Spherical X coordinate (longitude) - R: scalar - Earth radius in km - If None, use geopy default - Returns - ------- - x: np.array - Cartesian x coordinate - y: np.array - Cartesian y coordinate - z: np.array - Cartesian z coordinate - """ + return _ds - # Convert - Y_rad = _np.deg2rad(Y) - X_rad = _np.deg2rad(X) - x = R * _np.cos(Y_rad) * _np.cos(X_rad) - y = R * _np.cos(Y_rad) * _np.sin(X_rad) - z = R * _np.sin(Y_rad) - - return x, y, z +def diff_and_inds_where_insert(ix, iy): + dx, dy = (_np.diff(ii) for ii in (ix, iy)) + inds = _np.argwhere(_np.abs(dx) + _np.abs(dy) > 1).squeeze() + return dx, dy, inds -@compilable -def to_180(x): - """ - convert any longitude scale to [-180,180) - - Parameters - ---------- - x: float ,numpy.array - angles in degree - Returns - ------- - redefined_x: float,numpy.ndarray - the same angle coverted to [-180,180) +def remove_repeated(_iX, _iY): + """Attemps to remove repeated coords not adjascent to each other, + while retaining the trajectory property of being simply connected + (i.e. the distance between each index point is one). If it cannot + remove repeated coordinate values, returns the original array. """ - x = x % 360 - return x + (-1) * (x // 180) * 360 - - -def get_combination(lst, select): + _ix, _iy = _iX, _iY + nn = [] + for n in range(len(_ix)): + val = _np.where(abs(_ix - _ix[n]) + abs(_iy - _iy[n]) == 0)[0] + # select only repeated values with deg of multiplicity = 2 + if len(val) == 2: + if len(nn) == 0: + nn.append(list(val)) + if len(nn) > 0 and (val != nn).all(): + nn.append(list(val)) + if _np.array(nn).size: + dn = [nn[i][1] - nn[i][0] for i in range(len(nn))] + # remove if the distance between repeated coords is 2 + mask = _np.where(_np.array(dn) == 2)[0] + remove = [nn[i][1] for i in mask] + _ix, _iy = (_np.delete(ii, remove) for ii in (_ix, _iy)) + # find the hole left + mask = _np.abs(_np.diff(_ix)) + _np.abs(_np.diff(_iy)) == 2 + # delete hole left behind + _ix, _iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (_ix, _iy)) + # verify path is simply connected + dx, dy, inds = diff_and_inds_where_insert(_ix, _iy) + if inds.size: # pragma: no cover + _ix = _iX + _iY = _iY + return _ix, _iy + + +def connector(_ix, _iy): """ - Iteratively find all the combination that - has (select) amount of elements - and every element belongs to lst + Takes a collection of points defined in logical space (ix, iy), each of + equal length arrays, and returns a new continous array (_ix, _iy) that + contains the original elements now with unit spacing. - Parameters - ---------- - lst: list - a iterable object to select from - select: int - the number of objects to select - - Returns - ------- - com_list: list - a list of all the possible combinations """ - # TODO: see if the one in itertools can replace this - if select == 1: - return [[num] for num in lst] + if len(_ix) == len(_iy) == 1: + return _ix, _iy else: - the_lst = [] - for i, num in enumerate(lst): - sub_lst = get_combination(lst[i + 1 :], select - 1) - for com in sub_lst: - com.append(num) - # print(sub_lst) - the_lst += sub_lst - return the_lst + mask = _np.abs(_np.diff(_ix)) + _np.abs(_np.diff(_iy)) == 0 + _ix, _iy = (_np.delete(ii, _np.argwhere(mask)) for ii in (_ix, _iy)) + + # Initialize variables" + dx, dy, inds = diff_and_inds_where_insert(_ix, _iy) + while inds.size: + dx, dy = (di[inds] for di in (dx, dy)) + mask = _np.abs(dx * dy) == 1 + _ix = _np.insert(_ix, inds + 1, _ix[inds] + (dx / 2).astype(int)) + _iy = _np.insert( + _iy, inds + 1, _iy[inds] + _np.where(mask, dy, (dy / 2).astype(int)) + ) + # Prepare for next iteration + dx, dy, inds = diff_and_inds_where_insert(_ix, _iy) + _iX, _iY = remove_repeated(_ix, _iy) + return _iX, _iY diff --git a/pyproject.toml b/pyproject.toml index e04040b2..88f8f344 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,7 +17,8 @@ classifiers = [ dependencies = [ "dask", "xarray >= 0.14.1", - "xgcm >= 0.2.0" + "xgcm >= 0.2.0", + "shapely" ] description = "A Python package to facilitate ocean model data analysis and visualization." dynamic = ["version"] diff --git a/sciserver_catalogs/environment.yml b/sciserver_catalogs/environment.yml index 03990953..1f201956 100644 --- a/sciserver_catalogs/environment.yml +++ b/sciserver_catalogs/environment.yml @@ -48,7 +48,6 @@ dependencies: - cf_xarray - ipykernel - numba -- xoak - scikit-learn - pys2index - cmasher From 44b3d52780a23bedc07be98af471f1362696f65c Mon Sep 17 00:00:00 2001 From: Miguel Jimenez Date: Fri, 10 Nov 2023 13:44:59 -0800 Subject: [PATCH 31/32] replacing rise with jupyterlab-rise allows binder to get build (#400) * replace opsolete rise with jupyterlab extension instead * unpin python --- binder/environment.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/binder/environment.yml b/binder/environment.yml index 38911539..0c7739cc 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -2,12 +2,11 @@ name: rise-environment channels: - conda-forge dependencies: -- python=3.10 +- python - numpy - matplotlib - pandas - bokeh -- rise - dask - distributed - bottleneck @@ -29,3 +28,4 @@ dependencies: - pip: - git+https://github.com/hainegroup/oceanspy.git - jupyter-contrib-nbextensions + - jupyterlab-rise From 50c85cb86a3538797cecbe33dae0ac9edb18de41 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 5 Dec 2023 16:37:20 -0500 Subject: [PATCH 32/32] [pre-commit.ci] pre-commit autoupdate (#401) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black: 23.10.1 → 23.11.0](https://github.com/psf/black/compare/23.10.1...23.11.0) - [github.com/nbQA-dev/nbQA: 1.7.0 → 1.7.1](https://github.com/nbQA-dev/nbQA/compare/1.7.0...1.7.1) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .pre-commit-config.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 866112ca..16d5c62d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -25,7 +25,7 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.10.1 + rev: 23.11.0 hooks: - id: black - repo: https://github.com/PyCQA/flake8 @@ -33,7 +33,7 @@ repos: hooks: - id: flake8 - repo: https://github.com/nbQA-dev/nbQA - rev: 1.7.0 + rev: 1.7.1 hooks: - id: nbqa-black additional_dependencies: [black]
    \n", - " Comm: tcp://127.0.0.1:43921\n", + " Comm: tcp://127.0.0.1:37637\n", " \n", " Total threads: 1\n", @@ -347,7 +347,7 @@ "
    \n", - " Dashboard: http://127.0.0.1:35800/status\n", + " Dashboard: http://127.0.0.1:37418/status\n", " \n", " Memory: 25.00 GiB\n", @@ -355,13 +355,13 @@ "
    \n", - " Nanny: tcp://127.0.0.1:36278\n", + " Nanny: tcp://127.0.0.1:38324\n", "
    \n", - " Local directory: /tmp/dask-worker-space/worker-4lcf9v7g\n", + " Local directory: /tmp/dask-worker-space/worker-23f7an89\n", "

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