AR_detection.ipynb

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    "# Atmospheric Rivers: Filtering by Criteria\n",
    "\n",
    "This notebook will import functions from the `ar_detection.py` module to expose the processing flow and to show a few examples.\n",
    "Production runs could also be orchestrated from this notebook to leverage the use of an interactive Dask client if/when needed. Before executing this notebook be sure you've set your `AR_DATA_DIR` environment variable, and have executed both the `download.py` and `compute_ivt.py` scripts."
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    "import random\n",
    "\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import geopandas as gpd\n",
    "from tqdm import tqdm\n",
    "\n",
    "from config import ar_params, ard_fp, shp_fp, csv_fp, ak_shp, landfall_shp, landfall_csv, landfall_events_shp, landfall_events_csv, coastal_impact_shp, coastal_impact_csv\n",
    "\n",
    "# functions to create the binary \"blobs\" of IVT exceedance\n",
    "from ar_detection import compute_intensity_mask, label_contiguous_mask_regions\n",
    "# functions to measure the requisite blob properties\n",
    "from ar_detection import generate_region_properties, get_data_for_ar_criteria, get_azimuth_of_furthest_points, get_directional_coherence, get_length_width_ratio, get_major_axis_haversine_distance, get_poleward_strength\n",
    "# functions test whether or not criteria are met\n",
    "from ar_detection import apply_criteria, filter_ars\n",
    "# functions to generate vectorized output\n",
    "from ar_detection import create_geodataframe_with_all_ars, create_shapefile, landfall_ars_export"
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       "{'window': 75,\n",
       " 'ivt_percentile': 90,\n",
       " 'ivt_floor': 100,\n",
       " 'direction_deviation_threshold': 45,\n",
       " 'mean_meridional': 50,\n",
       " 'orientation_deviation_threshold': 45,\n",
       " 'min_axis_length': 2000}"
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   "source": [
    "# inspect criteria, note that `window` and `ivt_percentile` are used in the IVT computation, not in the AR filtering done here\n",
    "ar_params"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (time: 61364, latitude: 225, longitude: 237)\n",
       "Coordinates:\n",
       "  * time          (time) datetime64[ns] 1980-01-01 ... 2021-12-31T18:00:00\n",
       "  * longitude     (longitude) float32 -179.0 -178.8 -178.5 ... -120.2 -120.0\n",
       "  * latitude      (latitude) float32 66.0 65.75 65.5 65.25 ... 10.5 10.25 10.0\n",
       "    spatial_ref   int64 0\n",
       "Data variables:\n",
       "    p72.162       (time, latitude, longitude) float32 ...\n",
       "    ivt_mag       (time, latitude, longitude) float32 ...\n",
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       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2023-09-12 23:42:01 GMT by grib_to_netcdf-2.25.1: /opt/ecmw...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-47ca14d7-22bd-4d87-bb17-9bb3245f64ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-47ca14d7-22bd-4d87-bb17-9bb3245f64ea' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 61364</li><li><span class='xr-has-index'>latitude</span>: 225</li><li><span class='xr-has-index'>longitude</span>: 237</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e46ad997-fa30-4f6a-aa80-6391f87248f9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e46ad997-fa30-4f6a-aa80-6391f87248f9' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-01 ... 2021-12-31T18:00:00</div><input id='attrs-7d42709b-0a9c-43dc-929f-753224ba2955' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d42709b-0a9c-43dc-929f-753224ba2955' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9e0c13b-7ab1-43b9-ae6d-34cec4f0b5b7' class='xr-var-data-in' type='checkbox'><label for='data-e9e0c13b-7ab1-43b9-ae6d-34cec4f0b5b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-01T12:00:00.000000000&#x27;, ..., &#x27;2021-12-31T06:00:00.000000000&#x27;,\n",
       "       &#x27;2021-12-31T12:00:00.000000000&#x27;, &#x27;2021-12-31T18:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.0 -178.8 ... -120.2 -120.0</div><input id='attrs-c6922dce-c0bd-4738-8db2-786934bc87eb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6922dce-c0bd-4738-8db2-786934bc87eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eddc9dc9-52f8-423b-b6cc-7f16029a7aa0' class='xr-var-data-in' type='checkbox'><label for='data-eddc9dc9-52f8-423b-b6cc-7f16029a7aa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-179.  , -178.75, -178.5 , ..., -120.5 , -120.25, -120.  ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>66.0 65.75 65.5 ... 10.5 10.25 10.0</div><input id='attrs-fb5d6c7c-de03-4bf0-9a62-04e8cba567e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb5d6c7c-de03-4bf0-9a62-04e8cba567e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dabdf1e9-5379-4431-931c-467136a52ef4' class='xr-var-data-in' type='checkbox'><label for='data-dabdf1e9-5379-4431-931c-467136a52ef4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([66.  , 65.75, 65.5 , ..., 10.5 , 10.25, 10.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-23abf8bb-f970-4db8-a3cf-8261a9ddbb19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23abf8bb-f970-4db8-a3cf-8261a9ddbb19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a58e48b6-e13e-46f6-bae3-7efb217c388c' class='xr-var-data-in' type='checkbox'><label for='data-a58e48b6-e13e-46f6-bae3-7efb217c388c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-07d3a1b4-d26f-4e4e-84da-95eda5defc5d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07d3a1b4-d26f-4e4e-84da-95eda5defc5d' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>p72.162</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-19a4531d-8486-48e4-9f2d-46fde27896a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19a4531d-8486-48e4-9f2d-46fde27896a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc269465-7456-49c0-be7c-b8fd16e4ad5b' class='xr-var-data-in' type='checkbox'><label for='data-cc269465-7456-49c0-be7c-b8fd16e4ad5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m**-1 s**-1</dd><dt><span>long_name :</span></dt><dd>Vertical integral of northward water vapour flux</dd></dl></div><div class='xr-var-data'><pre>[3272235300 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ivt_mag</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a800a1d8-bdb7-484e-9a24-5a610ebf404f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a800a1d8-bdb7-484e-9a24-5a610ebf404f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eca6175f-8416-496c-9e52-e39094d8619c' class='xr-var-data-in' type='checkbox'><label for='data-eca6175f-8416-496c-9e52-e39094d8619c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[3272235300 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ivt_dir</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-14bb055a-36d2-48b1-9f02-56d2d099ecdc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-14bb055a-36d2-48b1-9f02-56d2d099ecdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6293c0de-74ce-494b-b281-f2d35361d5c0' class='xr-var-data-in' type='checkbox'><label for='data-6293c0de-74ce-494b-b281-f2d35361d5c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[3272235300 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ivt_quantile</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ab41cadc-f978-40e1-a64b-5c4d46c5b69d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab41cadc-f978-40e1-a64b-5c4d46c5b69d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b56f2715-0ce2-4664-a57c-08b1b4f4e2cf' class='xr-var-data-in' type='checkbox'><label for='data-b56f2715-0ce2-4664-a57c-08b1b4f4e2cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[3272235300 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f78b2e15-56be-47bb-b359-28b4c338b151' class='xr-section-summary-in' type='checkbox'  ><label for='section-f78b2e15-56be-47bb-b359-28b4c338b151' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4bf4f2c3-ae69-4bae-b778-b7b621dcfc50' class='xr-index-data-in' type='checkbox'/><label for='index-4bf4f2c3-ae69-4bae-b778-b7b621dcfc50' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-01 00:00:00&#x27;, &#x27;1980-01-01 06:00:00&#x27;,\n",
       "               &#x27;1980-01-01 12:00:00&#x27;, &#x27;1980-01-01 18:00:00&#x27;,\n",
       "               &#x27;1980-01-02 00:00:00&#x27;, &#x27;1980-01-02 06:00:00&#x27;,\n",
       "               &#x27;1980-01-02 12:00:00&#x27;, &#x27;1980-01-02 18:00:00&#x27;,\n",
       "               &#x27;1980-01-03 00:00:00&#x27;, &#x27;1980-01-03 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-12-29 12:00:00&#x27;, &#x27;2021-12-29 18:00:00&#x27;,\n",
       "               &#x27;2021-12-30 00:00:00&#x27;, &#x27;2021-12-30 06:00:00&#x27;,\n",
       "               &#x27;2021-12-30 12:00:00&#x27;, &#x27;2021-12-30 18:00:00&#x27;,\n",
       "               &#x27;2021-12-31 00:00:00&#x27;, &#x27;2021-12-31 06:00:00&#x27;,\n",
       "               &#x27;2021-12-31 12:00:00&#x27;, &#x27;2021-12-31 18:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=61364, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-55a534ec-e54a-490a-9c2a-f69f00a1143a' class='xr-index-data-in' type='checkbox'/><label for='index-55a534ec-e54a-490a-9c2a-f69f00a1143a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.0, -178.75,  -178.5, -178.25,  -178.0, -177.75,  -177.5, -177.25,\n",
       "        -177.0, -176.75,\n",
       "       ...\n",
       "       -122.25,  -122.0, -121.75,  -121.5, -121.25,  -121.0, -120.75,  -120.5,\n",
       "       -120.25,  -120.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;longitude&#x27;, length=237))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9e9f7e56-9cf6-4187-8d5e-100fe13cd479' class='xr-index-data-in' type='checkbox'/><label for='index-9e9f7e56-9cf6-4187-8d5e-100fe13cd479' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 66.0, 65.75,  65.5, 65.25,  65.0, 64.75,  64.5, 64.25,  64.0, 63.75,\n",
       "       ...\n",
       "       12.25,  12.0, 11.75,  11.5, 11.25,  11.0, 10.75,  10.5, 10.25,  10.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;latitude&#x27;, length=225))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-25baff1e-220f-4f74-b6b6-c1d6d8f0487b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-25baff1e-220f-4f74-b6b6-c1d6d8f0487b' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2023-09-12 23:42:01 GMT by grib_to_netcdf-2.25.1: /opt/ecmwf/mars-client/bin/grib_to_netcdf.bin -S param -o /cache/data7/adaptor.mars.internal-1694560550.488097-22547-11-56920c14-6c3e-45a7-aa03-da0ddda5ae07.nc /cache/tmp/56920c14-6c3e-45a7-aa03-da0ddda5ae07-adaptor.mars.internal-1694556717.6462297-22547-21-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 61364, latitude: 225, longitude: 237)\n",
       "Coordinates:\n",
       "  * time          (time) datetime64[ns] 1980-01-01 ... 2021-12-31T18:00:00\n",
       "  * longitude     (longitude) float32 -179.0 -178.8 -178.5 ... -120.2 -120.0\n",
       "  * latitude      (latitude) float32 66.0 65.75 65.5 65.25 ... 10.5 10.25 10.0\n",
       "    spatial_ref   int64 0\n",
       "Data variables:\n",
       "    p72.162       (time, latitude, longitude) float32 ...\n",
       "    ivt_mag       (time, latitude, longitude) float32 ...\n",
       "    ivt_dir       (time, latitude, longitude) float32 ...\n",
       "    ivt_quantile  (time, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2023-09-12 23:42:01 GMT by grib_to_netcdf-2.25.1: /opt/ecmw..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ivt_ds = xr.open_dataset(ard_fp)\n",
    "ivt_ds.rio.write_crs(\"epsg:4326\", inplace=True)\n",
    "ivt_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "93a333aa-eeb2-4128-bfd9-fb000e329b5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 25 s, sys: 31.8 s, total: 56.8 s\n",
      "Wall time: 58.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ivt_ds[\"thresholded\"] = compute_intensity_mask(ivt_ds[\"ivt_mag\"], ivt_ds[\"ivt_quantile\"], ar_params[\"ivt_floor\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "85c92935-c908-4e70-a278-7f901d4a714d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 28s, sys: 4.39 s, total: 1min 33s\n",
      "Wall time: 1min 33s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "labeled_regions = label_contiguous_mask_regions(ivt_ds[\"thresholded\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cac6f733-8dfb-4da5-bdc2-07408f48d5b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 10min 7s, sys: 1min 24s, total: 11min 32s\n",
      "Wall time: 11min 32s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ar_di = generate_region_properties(labeled_regions, ivt_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dc2f0865-b2aa-4599-8bff-2815010f9cc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Getting length/width ratio for each AR target:: 100%|██████████| 61364/61364 [04:49<00:00, 211.68it/s]\n",
      "Getting axis length (km) for each AR target:: 100%|██████████| 61364/61364 [09:52<00:00, 103.56it/s]\n",
      "Getting overall orientation (azimuth) for each AR target:: 100%|██████████| 61364/61364 [10:38<00:00, 96.14it/s] \n",
      "Getting mean poleward strength for each AR target:: 100%|██████████| 61364/61364 [01:00<00:00, 1012.61it/s]\n",
      "Getting directional coherence for each AR target:: 100%|██████████| 61364/61364 [02:44<00:00, 373.18it/s]\n",
      "Getting total IVT strength for each AR target:: 100%|██████████| 61364/61364 [00:22<00:00, 2708.97it/s]\n",
      "Getting relative IVT strength for each AR target:: 100%|██████████| 61364/61364 [00:24<00:00, 2515.46it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 28min 49s, sys: 1min 11s, total: 30min\n",
      "Wall time: 29min 52s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ar_di = get_data_for_ar_criteria(ar_di, ivt_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9c9b31de-7ed7-4bb3-b169-25e72aac31c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 61364/61364 [00:02<00:00, 20602.94it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.86 s, sys: 147 ms, total: 3.01 s\n",
      "Wall time: 2.98 s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ar_di = apply_criteria(ar_di)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fe06fe5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TOTAL CANDIDATE ARs: 627025\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 61364/61364 [00:00<00:00, 140937.53it/s]\n",
      "100%|██████████| 61364/61364 [00:00<00:00, 143858.19it/s]\n",
      "100%|██████████| 61364/61364 [00:00<00:00, 146756.54it/s]\n",
      "100%|██████████| 61364/61364 [00:00<00:00, 155723.37it/s]\n",
      "100%|██████████| 61364/61364 [00:00<00:00, 169216.47it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If requiring 1 AR criteria, we find 627025 ARs...\n",
      "If requiring 2 AR criteria, we find 601141 ARs...\n",
      "If requiring 3 AR criteria, we find 412981 ARs...\n",
      "If requiring 4 AR criteria, we find 143179 ARs...\n",
      "If requiring 5 AR criteria, we find 23384 ARs...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# criteria exploration\n",
    "# how many labeled regions meet the different numbers of criteria? \n",
    "# note that some criteria (overall orientation consistency) may oscillate between pass and fail depending on size of spatial domain\n",
    "\n",
    "\n",
    "blob_count = 0\n",
    "\n",
    "for b in ar_di:\n",
    "    no_blobs = len(ar_di[b][\"ar_targets\"])\n",
    "    blob_count = blob_count + no_blobs\n",
    "\n",
    "print(\"TOTAL CANDIDATE ARs: \" + str(blob_count))\n",
    "\n",
    "crit_no = [1,2,3,4,5]\n",
    "blob_crit = []\n",
    "\n",
    "for c in crit_no:\n",
    "    ars = filter_ars(ar_di, n_criteria_required=c)\n",
    "\n",
    "    crit_count = 0\n",
    "\n",
    "    for a in ars:\n",
    "        ar_count = len(ars[a])\n",
    "        crit_count = crit_count + ar_count\n",
    "    \n",
    "    blob_crit.append(crit_count)\n",
    "\n",
    "for c, b in zip(crit_no, blob_crit):\n",
    "    print(\"If requiring \" + str(c) + \" AR criteria, we find \" + str(b) + \" ARs...\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "41770735-288e-42ac-a866-705c4c5be779",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 61364/61364 [00:00<00:00, 169725.87it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 365 ms, sys: 5 ms, total: 370 ms\n",
      "Wall time: 366 ms\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# default criteria is the maximum (5)\n",
    "output_ars = filter_ars(ar_di, n_criteria_required=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2cf65f49-2a85-48b9-911f-5d50d252c8fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Labeled AR candidate regions')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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C8Fve8hb+yU9+Uhqnm/jivvvu4yzL+LzzzvP6uvfee7lWq/F73/tevuuuu/jGG2/k6dOnt0yccemll/J9993Hn/70p6OJM9ZlX+eddx5nWVa6Bvbff3/ebLPN+Oqrr+Z77rmHTzzxRAbAN9xwg1fvN7/5DW+yySb8jne8g2+//Xb+7ne/y7NmzWqZuOTTn/4033fffXzppZdyb29vNHHJzJkzefr06XzjjTfyXXfdxe9973ujiUuG45ysWLGCt9hiC549ezbfcsstfPvtt/M73vEOHjt2LP/mN7/x6l5//fUMgE866SS+9957+eqrr+ZNN920MnFJJ+c0ISFh+JAIc0LCOsBWW23FAKIvY6392te+xjvuuCOPHj2aN9lkE95777351ltvjbZ32GGH8RZbbMH1ep2nTp3KH/nIR6KE9OKLL+bddtuNN9tsM86yjCdOnMgHHnggf+973+t47Pfee2/l2EMLssk4GHtde+21bfvaZ599KvcPrb3dnC+DdoTZbI+9jjnmmI6OM7TAm/MXW1W48847eY899uC+vj6eMGECH3300dGkKAMDA3zuuefy61//eu7p6eEZM2bwv//7v5fqrcu+zj33XAbA9957r1f+8ssv82mnncZTp07lnp4e3nnnnfkb3/hGaX9m5kceeYT3228/Hj16NI8bN47f85738JNPPhmte/nll/OMGTO4p6eHX//61/O5557rZcA0WL58OR999NE8YcIE7uvr4z322IPvuuuuaJtr+5wwMz/55JP8nve8h8eNG8ejR4/m/fbbr3LF46abbuKdd96Ze3p6eOrUqXzaaafxyy+/XKrXzTlNSEgYHhAz81pQdiQkJCQkJCQkJCRslEhOfwkJCQkJCQkJCQktkAhzQkJCQkJCQkJCQgskwpyQkJCQkJCQkJDQAokwJyQkJCQkJCQkJLRAIswJCQkJCQkJCQkJLZAIc0JCQkJCQkJCQkILJMKckJCQkJCQkJCQ0AKJMCckJCQkJCQkJCS0QCLMCQkJCQkJCQkJCS2QCHNCQkJCQkJCQkJCCyTCnJCQkJCQkJCQkNACiTAnJCQkJCQkJCQktEAizAkJCQkJCQkJCQktkAhzQkJCQkJCQkJCQgskwpyQkJCQkJCQkJDQAokwJyQkJCQkJCQkJLRAIswJCQkJCQkJCQkJLZAIc0JCQkJCQkJCQkILJMKckJCQkJCQkJCQ0AKJMCckJCQkJCQkJCS0QCLMCQkJCQkJCQkJCS2QCHNCQkJCQkJCQkJCCyTCnJCQkJCQkJCQkNACiTAnJCQkJCQkJCQktEAizAkJCQkJCQkJCQktkAhzQkJCQkJCQkJCQgskwpyQkJCQkJCQkJDQAokwJyQkJCQkJCQkJLRAIswJCQkJCQkJCQkJLZAIc0JCQkJCQkJCQkILJMKckJCQkJCQkJCQ0AKJMCckJCQkJCQkJCS0QCLMCQkJCQkJCQkJCS2QCHNCQkJCQkJCQkJCCyTCnJCQkJCQkJCQkNACiTAnJCQkJCQkJCQktEAizAkJCQkJCQkJCQktkAhzQkJCQkJCQkJCQgskwpyQkJCQkJCQkJDQAokwJyQkJCQkJCQkJLRAIswJCQkJCQkJCQkJLZAIc0JCQkJCQkJCQkILJMKckJCQkJCQkJCQ0AKJMCckJCQkJCQkJCS0QCLMCQkJCQkJCQkJCS2QCHNCQkJCQkJCQkJCCyTCnJCQkJCQkJCQkNACiTC/BrBo0SIQER555BEAwC677IItt9wSeZ5X7vP2t78dkyZNwl577QUiavuaP3/+OjqadYs//OEPICIsWrTIli1duhTz58/Hiy++uNb7M9/VH/7wh7XedkJCQmdIc2ZnWLBgAW699dZS+X333Qciwn333WfL5s+fDyJa62P4r//6L2y++eZ4+eWXbdlnPvMZ7LLLLpgwYQL6+vqw7bbb4qSTTsIzzzxT2r/RaOC8887D1ltvjd7eXuywww5YuHDhWh9no9HAG97wBlx22WVrve2E1wZq63sACd3j+OOPx6mnnoof/vCHePe7313a/sQTT2Dp0qWYN28eTjzxRLz00kt22/e//31ccMEFuPbaa7HDDjvY8te97nXrZOzrGltssQUeeOABvOENb7BlS5cuxXnnnYePfOQj2HTTTdff4BISEtYJ0pwZx4IFC/C+970P73nPe7zyt7zlLXjggQew0047DWv/r776Kj796U/j7LPPxtixY235iy++iCOPPBI77rgjxo4di1//+te44IILcNttt+Gxxx7DxIkTbd1TTjkF119/Pf7t3/4Nu+22G374wx/i4x//OF5++WV8+tOfXmtjrdfr+PznP49PfOITOOqoo7wxJIwQcMIGj2uvvZYB8MMPP8zMzH/729+4r6+PjzjiiGj9s88+mwHwL3/5y7ZtjURceumlDICffvrptd62Ob/D0XZCQkJnSHNmZxgzZgwfc8wxHdU999xzeW1Thq9+9avc19fHK1eubFv39ttvZwB8zTXX2LJHH32UiYgXLFjg1T3xxBN51KhR/MILL6yVcb766qvMzNzf388TJkzgCy+8cK20m/DaQpJkvAax2Wab4b3vfS+WLFmCF154wduW5zmuv/567Lbbbpg9e/Za6W/OnDmYNWsWHnjgAey1114YNWoUtt56a1x77bUAlAXmLW95C0aPHo3Zs2fjjjvu8PZ/8sknceyxx2K77bbD6NGjseWWW+KQQw7Br371q1Jfjz32GA444ACMHj0am2++OT72sY/h+9//fml50Izp4Ycfxt57743Ro0dj2223xRe+8AVIKW29UJIxf/58fPKTnwQAbLPNNnZ51bRdtdS69dZb4yMf+YhX9uCDD+Ltb387+vr6MG3aNJxzzjloNBrRc/jNb34Te+65J8aMGYNNNtkEBx54IH7+85+3Ou0JCQlrCet6zmRmXHLJJdhqq63Q19eHt7zlLfjBD36AOXPmYM6cObZelYQrJom46667cNhhh+F1r3sd+vr68MY3vhEnn3wy/vrXv3r7GunEY489hiOPPBLjx4/HlClTcNxxx2HVqlW2HhHhlVdewXXXXWfnQTO2WP9VGMrcduWVV+KQQw7paKVv8803BwDUasXC+K233gpmxrHHHuvVPfbYY7F69Wp7L/q3f/s31Go1PPvss6V2jzvuOEycOBFr1qwBoOb6gw8+GN/97nexyy67oK+vD+eddx4AoKenBx/4wAdw9dVXg5k7OsaEjQeJML9Gcfzxx2NgYAA33HCDV/7DH/4Qf/rTn3D88cev1f6WL1+OY489FieccAL++7//G7Nnz8Zxxx2H888/H+eccw7OOuss3Hzzzdhkk03wnve8B3/605/svn/6058wceJEfOELX8Add9yBK664ArVaDbvvvjsef/xxW+/555/HPvvsg8cffxxXXnkl/uu//gsvv/wy/vVf/7VyTB/60Ifw4Q9/GLfddhve9a534ZxzzimdExcnnHACTj31VADAd7/7XTzwwAN44IEH8Ja3vKWr8/HrX/8a++23H1588UUsWrQIV111FX7+85/jggsuKNVdsGABjjzySOy000741re+heuvvx4vv/wy9t57b/z617/uqt+EhITBYV3Omeeddx7OPvts7L///rj11lvxL//yLzjxxBO9+a5bPPXUU9hzzz1x5ZVX4s4778TnP/95/PSnP8U//MM/RB/UjzjiCMyYMQM333wzPvWpT+Gmm27CJz7xCbv9gQcewKhRo/Dud7/bzoNf/epXuxrTUOa25557Dr/61a+w7777VtZpNptYvXo1fv7zn2PevHmYMWMGDj/8cLv90Ucfxeabb46pU6d6++288852OwCcfPLJqNVq+NrXvubV+9vf/obFixfj+OOPR19fny3/2c9+hk9+8pM47bTTcMcdd+CII46w2+bMmYNnnnnGtp0wgrCeLdwJHSC2JCil5G222YZ33nlnr+4RRxzBo0eP5lWrVnXcVjvss88+DIAfeeQRW/bCCy9wlmU8atQo/uMf/2jLf/GLXzAA/vd///fK9prNJg8MDPB2223Hn/jEJ2z5Jz/5SSYifuyxx7z6Bx54IAPge++9tzSmn/70p17dnXbaiQ888ED7+emnn2YAfO2119qyVpIMAHzuueeWyrfaaitv6fIDH/gAjxo1ipcvX+4d1w477OC1/X//939cq9X41FNP9dp7+eWXeerUqTx37txSXwkJCUPD+pwzV65cyX19ffze977XK//JT37CAHifffYptR3ORffee29pznMhpeRGo8HPPPMMA+D//u//ttuMdOKSSy7x9jnllFO4r6+PpZS2rEqSEes/lGQMdW775je/yQD4wQcfjG5//vnnGYB97b777t69hpl5//335+233z66f09PD5900kn28zHHHMOTJ0/m/v5+W3bxxRezEMI7/1tttRVnWcaPP/54tN3f/e53DICvvPLKlseXsPEhWZhfoyAiHHvssfjlL3+JZcuWAQBeeOEFLFmyBEcccQTGjRu3VvvbYostsOuuu9rPEyZMwOTJk/HmN78Z06ZNs+U77rgjAHjezM1mEwsWLMBOO+2Enp4e1Go19PT04He/+x1+85vf2Hr3338/Zs2aVXI0OfLII6Njmjp1Kt72trd5ZTvvvHPUk3pt495778V+++2HKVOm2LIsy/CBD3zAq/fDH/4QzWYTRx99NJrNpn319fVhn3326WjJMyEhYehYV3PmAw88gDVr1uBDH/qQV77XXnthq622GnS7K1aswEc/+lFMnz4dtVoN9XrdtufOowaHHnqo93nnnXfGmjVrsGLFikGPwcVQ5zazCjl58uTo9kmTJuHhhx/Gj3/8Y3z961/H3/72N+y77754/vnnvXqtIne42z7+8Y9jxYoV+Pa3vw0AkFLiyiuvxD/90z9h66239vbbeeedMWPGjGibZrx//OMfWx5fwsaHRJhfwzj22GMhhLBa4htvvBEDAwNrXY4BKIIcoqenp1Te09MDAFYPBgCnn346Pve5z+E973kPlixZgp/+9Kd4+OGH8aY3vQmrV6+29V544QWPgBrEygBEvZR7e3u9NocLL7zwQmkZEECp7M9//jMAYLfddkO9Xvde3/zmN0v6w4SEhOHDupgzjUa6k/mhU0gpccABB+C73/0uzjrrLPzoRz/CQw89hAcffBAAonNeOD/29vZW1h0Mhjq3mXG4UggXtVoNb33rW/H2t78dJ5xwAu655x78/ve/xxe+8AVbZ+LEiSVNOgC88sorGBgY8O5Pu+yyC/bee29cccUVAIDvfe97+MMf/hCV/G2xxRaV4zbjXRf3mYQNCyms3GsYr3vd63DAAQfgpptuwhe/+EVce+21eOMb34h3vOMd63toHm644QYcffTRWLBggVf+17/+1XP2mDhxop2EXSxfvny4h2jR29uL/v7+Unk4KU+cODE6rrBs0qRJAIDvfOc7Q7IuJSQkDB3rYs40RLVqfnCtmYZ8hXNOSDYfffRR/O///i8WLVqEY445xpY/+eSTa2vYXWOoc5vZ/29/+1tLgmrwute9DtOmTcMTTzxhy2bPno3Fixdj+fLl3sOIcSifNWuW18Zpp52G97///fjZz36Gr3zlK5gxYwb233//Ul+trNZ/+9vfvPEnjBwkC/NrHMcffzxWrlyJz3/+8/jFL36BY489dliCyw8FRGStGwbf//73S0ta++yzDx599NGSs8jixYvX6nhaWVq23npr/PKXv/TK7rnnHvz973/3yvbdd1/86Ec/8gh+nuf45je/6dU78MADUavV8NRTT+Gtb31r9JWQkLDuMNxz5h577IG+vj7ceOONXvnSpUtLcjFDnsM557bbbvM+m/GF82joxNYthrIiN9S5zcS0fuqppzrq78knn8Rzzz2HN77xjbbssMMOAxHhuuuu8+ouWrQIo0aNwkEHHeSVv/e978XrX/96nHHGGbj77rtxyimndP3d//73vweAYY9RnbDhIVmYX+M49NBDMWnSJFx66aXIssyzPmwoOPjgg7Fo0SLssMMO2HnnnbFs2TJceumlpcD/8+bNw3/+53/iXe96F84//3xMmTIFN910E377298CAIRYO893JnTU5ZdfjmOOOQb1eh3bb789xo4di6OOOgqf+9zn8PnPfx777LMPfv3rX+MrX/kKxo8f77Xx2c9+Frfddhv+8R//EZ///OcxevRoXHHFFXjllVe8eltvvTXOP/98fOYzn8Hvf/97HHTQQdhss83w5z//GQ899BDGjBljQxYlJCQMP4Z7ztxss81w5pln4oILLsAJJ5yA97///Xj22Wcxf/78kiRjt912w/bbb48zzzwTzWYTm222GW655Rb8+Mc/9urtsMMOeMMb3oBPfepTYGZMmDABS5YswV133TWksc6ePRv33XcflixZgi222AJjx47F9ttv39G+Q53bdt99d4waNQoPPvigp7f+5S9/iU984hN43/veh2233RZCCPzqV7/Cl7/8ZUycOBFnnnmmrTtz5kwcf/zxOPfcc5FlGXbbbTfceeeduPrqq3HBBReUJINZluFjH/sYzj77bIwZM6YUKrQTPPjgg8iybINbyU0YfiQL82scPT09OOqoo8DMOPDAA7Hllluu7yGVcPnll+PDH/4wLrroIhxyyCG47bbb8N3vftfLvgcA06ZNw/33348ZM2bgox/9KD70oQ+hp6cH559/PgCstax8c+bMwTnnnIMlS5bgH/7hH7DbbrtZJ6BPfvKT+OQnP4lFixbhkEMOwc0334xvfetbpb5nzZqFu+++G+PGjcMxxxyDk046CTvvvDM+97nPlfo755xz8J3vfAdPPPEEjjnmGBx44IE466yz8Mwzz6RJNyFhHWNdzJnnn38+LrroItx555049NBDsXDhQlx11VUlMpplGZYsWYIddtgBH/3oR3H00Uejt7cXX/nKV7x69XodS5YswYwZM3DyySfjyCOPxIoVK3D33XcPaZyXX345tttuO/zzP/8zdtttN5x88sld7T+Uua2npwfve9/78N///d9e+ZQpUzBt2jR88YtfxOGHH46DDz4YV1xxBQ4++GAsW7asJP/46le/ik996lNYuHAhDjjgAHznO9/B5ZdfXpnlzzhmH3XUUSVDSCe49dZb8e53vztliR2BIOYUfTthw8ZJJ52Eb3zjG3jhhResU2FCQkLCaw1uYpAE4JFHHsFuu+2GBx98ELvvvvs66XPhwoU47bTT8Oijj2LmzJld7fvUU09hu+22ww9/+MOo9jlh40aSZCRsUDj//PMxbdo0bLvttvj73/+O733ve/iP//gPfPazn01kOSEhIWEjwlvf+lbMnTsX//Zv/4bvfe97w9rXz3/+czz99NM4//zzcdhhh3VNlgHgggsuwH777ZfI8ghFIswJGxTq9TouvfRSPPfcc2g2m9huu+3wpS99CR//+MfX99ASEhISEtYyvvjFL+Kaa67Byy+/jLFjxw5bP+9973uxfPly7L333rjqqqu63r/ZbOINb3gDzjnnnGEYXcJrAUmSkZCQkJCQkJCQkNACyekvISEhISEhISEhoQUSYU5ISEhISEhISEhogUSYExISNkr8z//8Dw455BBMmzYNRIRbb73Vbms0Gjj77LMxe/ZsjBkzBtOmTcPRRx+NP/3pT14b/f39OPXUUzFp0iSMGTMGhx56KJ577jmvzsqVK22IqvHjx+Ooo47Ciy++uA6OMCEhISFhXWGjd/qTUuJPf/oTxo4du8FlwEtIeK2DmfHyyy9j2rRpXSWWWbNmDQYGBrrur6enx6YTbodXXnkFb3rTm3DsscfiiCOO8La9+uqr+NnPfobPfe5zeNOb3oSVK1di3rx5OPTQQ/HII4/YevPmzcOSJUuwePFiTJw4EWeccYaNB5tlGQDggx/8IJ577jnccccdAFQYxKOOOgpLlizp+vg2FqR5NyFh+DDYeRdYN3PvRgveyPHss88ygPRKr/Qaxtezzz7b8W9y9erVPHVyNqh+pk6dyqtXr+56HgDAt9xyS8s6Dz30EAPgZ555hpmZX3zxRa7X67x48WJb549//CMLIfiOO+5gZuZf//rXDIAffPBBW+eBBx5gAPzb3/6263FuLEjzbnql1/C/upl3mdfP3LsxYaO3MJswNe+ovwc1qoMle9tJdG79CPftBLH2K9th2XX77eD15bZP5adSd6ydHutg9hnUcUbGOxh0830Dg/vOu+67w2PrduwuujqOLr6fJjfw/+SSrsJBDQwMYPmKHE8v2wrjxnb+vb70ssQ2uz6DgYGBYbF0rFq1CkRkM3gtW7YMjUYDBxxwgK0zbdo0zJo1C0uXLsWBBx6IBx54AOPHj/eSLuyxxx4YP348li5d2nGa4Y0N5nqYs9XJqGW9gBuMaTC/KUGd75dlAJHap5V1m9lv046Ri/dmu/lNxH6r7rZOf6NhuyHcfkyd8Byaz6y3yUhbtk5wPK0QO4ZW+3U7L8W+E+e7YJb+ser6FJ77Vv12sqoRBggz+4T7Gguu3V7VXod9he0PIlBZUw7gvhWLug7Dt6HOva8VbPSE2SwH1qiOGtWBrFXlyCTlotW+Ve1F2mGq+oEMA2F2+6rka5ENWYcky20+i3dQaqdywmlxUxoEhkIwAT3utbiaHF2a7uBYh3ocANpeu9531E13LABZcWxtMGYT9eoUuR7iSy+95JX39vait7e36/5drFmzBp/61KfwwQ9+EOPGjQMALF++HD09Pdhss828ulOmTMHy5cttncmTJ5famzx5sq0zEmHn3axPEeZW4IC0xuYdQb7HjXu9hUQnUxWZnH0iUyvFyGRYJgKiaX6LMUOEIczu2Ew7RAExCvZvRQbDvtgY/XT75lV1//COqc2cLiKkkdk5j4Mgzu4+Ve0zg8l5MHCbEhWEucsxcHgvDo+lsh/9nZrqRAWJBvz3ayNKb+TclLbZh4jB3RsGO/eOdGz0hDmKTn547chzp+2GZSyrrbKD6bPtkKgl8a0iY9F9YhN7u326wSCI8lohkwHaHkcn302nx7KWHxIGi8GeR+LBn38Jhmx3Aw/qA8D06dO98nPPPRfz588f9DgajQb++Z//GVJKfPWrX21bn5m9G1XsphXWGbHIhCWwlVY/Q5ItSYX63O6aJFJt63bZtC8ifUUeGC3HtOTDIZYyICqZQ1RcAgkAUn8wZDlG5ksdu8cRIcvuflVk1bM4S5+4uXAtz1lAxsJxRh/qqaifOe+jfXW6ytghcfd26WDezf2PRAKc536f7vnwHmj0g1b06cr9Phxi7X7nQrT/7jvBOpg3Bjv3jnSMTMKckJCw3iEhu1pTMbWfffZZawUGMCTrcqPRwNy5c/H000/jnnvu8dqdOnUqBgYGsHLlSs/KvGLFCuy11162zp///OdSu3/5y18wZcqUQY8rISEhYbgw2Ll3pGPkEGai7q1+3v5DWA4CiifvwIpcqXGOWKYHC9OHazltZVEsWVjdvluNYx1aSYfDsgy0sS4Pg8a8k3PGkjs73uE4/8NxzBo5M/IuljBN3XHjxnnEdrAwZPl3v/sd7r33XkycONHbvuuuu6Jer+Ouu+7C3LlzAQDPP/88Hn30UVxyySUAgD333BOrVq3CQw89hLe97W0AgJ/+9KdYtWqVJdUjGSwEuMryaS2npKy7rmVXQC/Nk28RlFxYlfV/zgLraDcWOsfybC9FSSDIQuHgWiGBwpLrWsTdOkY/7e5TslrH5QDRY3Ct2lIAkPq9s38tuJV71vEsbl3NArN7qxUAA7O/KzGJ6KOrrMEknWvBPWahttn93BWGUGfe7vt1vgtG7uu7I/MNSwkSolSHA004udcxkfoGjVVZUGFxFiKie+7imjR6fUEAqLzasRYw2Ll3pGPkEOZOMBiiLIKJrbJerDCLLmFR5o8lSqBboWqy6oYk+zu2bbvttrCdIWC4yHIluiWNbRwqu623Nh0Pu0bb72zdSzI6xd///nc8+eST9vPTTz+NX/ziF5gwYQKmTZuG973vffjZz36G733ve8jz3GqOJ0yYgJ6eHowfPx7HH388zjjjDEycOBETJkzAmWeeidmzZ+Od73wnAGDHHXfEQQcdhBNPPBFf+9rXAKiwcgcffPCIdfjzIFCe+yJyCYZDwAwns4RMALksJAGaLLMQxeegTW5DUChGvCzRYtW21PVcXXVMg+vuq7eV9NMUkHCPFME/hlZjzwhwZVCh86AZa4zQGgTEz+s7dK50zxNzQb6lLPqwhJ7K97PgMyMvJA1WyhIcoxlvlXC21XcXK4s5Qzqg4AGIQ3JtJD8xAp3nVs7BxAATSDKQcfFA4n4Xse82dm9wy1zi7I5rCEiSjMEhEWYXVeSgMrqB/uF3EQcx/NGpCTB2MRZkmowhoAPi1pZcB210TcZM24OxPA4Toe7Uct5NO4NGcAztiHIn4y3VGeqDx9p84Biihjkfxkn7kUcewb777ms/n3766QCAY445BvPnz8dtt90GAHjzm9/s7Xfvvfdizpw5AIAvf/nLqNVqmDt3LlavXo399tsPixYtsjGYAeDGG2/EaaedZqNpHHroofjKV77S1Vg3WoSErKqOC31q2SU8QoAc6yZnhWbUI8edLiKGD3oShT7XIeysBuITw450ya4hRe/PBM+y7OpfXat0CEOAY/0b6zYbQmWszw65MgQ3JJChFdT0nwn/4SV2fzIW2ZDk62M1ZJhFQDJJWZGjDnyClJU5g29VjRHebmIPu3WrtN4xC7Trp9BJf8yA1A8FLNXDlrE2u7+B8HxKtDe8heMa4hQ+3HPvxopEmA1KpKQFGfYmrBY/pPCHzmzb84hz1Q8k9JSuIkoOEW1rRW4hCemKMFZEABkS2jgVqm7jToxrJSJGdaemUutG2pHlGFFe2zKKqpBQ69oq3wGG28oxZ86cgnRF0GqbQV9fHxYuXIiFCxdW1pkwYQJuuOGGrsY2YuAuT2u0s/5auYGpVxOaiASIReWpIrXtvmtXnaAjYxSkmhzLsFOvE99fp1/OAILwx1cV+s4drytNiB2X6+zoSjZiFtqq8xCOg6iw6sdIt6ljyGCJjMOzLrsEuWW0C02akTmyjlKEkQCdyB2M9ds86IZyD+cBgELnvVJbXczZ4cNJCPfBxIwpdv2aFQsr7RzafJ4szIPD+nXNT0hISEhISEhISNjAMbItzJFlECotU4lSndK+QFlfFAtd4yBqafYqBMs3MQeIorF4Gy5i1uTActq1fnZtW5k7dIBTVdeuxbSj8HpdWIOrrMtdW5aHcpzmGqqIj712MPi2k+PJxg929bwS7fXMBllQJ/SBNvM1c9li3So0Wlgcu6ZiFs1YHHMrlXOsfsF+DFJOhCbWMCQgneMx/8P5XvrjpcqQblTtFOa2afrP88I5Lc+VxVVKJelww//lUpXnuWNhZl9OIahIEmN1zMKzMpMbcq8KFfcY209FDPnQsTC0XJvttrweuYdaS3YgmejGah0rN/0IKqzzIbcw76tWGKqszOpD+/G1QJp7B4eRSZgDxw1vCSZGkIMfu9FhWbhkuYU3bgxV2ih2vZHd9loR59YdlaQblgy2iMgREr9yEpK1RJrXljSh21jWbeQW7Yh5N/ppjywPhggPcRmuI1Rdt8PQt0RHq9pe/YTXGIzTH1FBfCLXUluZhtueu1+MOIQXiktKY4Q2tp9DyNsiRmw8SQUX8YHD81B13MK5pzCDpTOemBbWaqFdPXPuyzIkA7lajLeRHXIJ1DKfzImiX7Deh6Ul5iYZFiErjjW897kP61VjNmOCT35bZvRzdcUcL/e2G9Lqbg8ePCypd8lzK7gSt6oEMyFakWZzflpJ58x9di3Nw2nuHRxGHmF2yHKJKFdYkN0fMLMsk+UOvXFdtAxZoz9Hdc5DIc4R0qzGMkQSPFTSPAiyXAq15hJf876bdgcZcrDTdNdD1iwPF1nu1HLQyoI1SORdOp50UzdhA0HE6a9Ejjv5SXRzrYlwPqOi3yix0vVjyU3c6B2tYOwbpQbY9u1toyCSRqk9TZCttZaVjtsljOaNsd7rdhUBc4myVKQ3z8EDA6qatgxzvQZi1yosytpn44wnpNXaUvjQ7+qbXSdJMybnuAcd5cFtrxPfoVbnNyT1potYBJIQwXVi+UDIGao0ya0iZlSR5vD+mube9YKRRZhdspyFT9V6gmqTr56c6BXMUi/LmLp6X9d7OLRoVJDqSmlGiBhx7pY0qw6doogjXQUJrswcOBTS3IGzXziGtY1O2uw2vF+U0A927J0uE7ZrowoVaWKHEzl3l3I1pWd97YEF+XGYO5VkmP2j8gqzsWKnqjYrikt9hO0Stbc0Z9DWWBSEsWJslijHCCX0/pogu/uFDwLW6gyUnRGN0zhrcikI6G9CrulX81KWgXp6yuML70O1mrWOEgfWUSPHAHwpRitY41L1+SxJKVxpQys5g70nVsgo232H7n0bKB46YpEznDIvfnQ4bgMzJBOGzuUe62LlMECaeweHkUWYExISNhikZcGEhISEdY809w4OI4cwOzomcmMjmuUlUwcoP8WW4jgCYHZCBDkWZ8ktLc0lqcVg4S5tVTkgttw/Hl5uWJJkxKyyg7RGt7UEh851pW7bHF8LCzJVOJ+0RTcxNtc2qtpudx7CRA0h1oJVRIKQd+G8IocafDRh3YNQdmxz0JF22a3izc1DGViH/WkwI2J5Lso8C3TsN5dRoZcmJ3a0O92YOV2SkmIIrUd253r3vbZqs3Qs4DEHQNeSzRKupoBIxO9xbn9C+Ek4zIoskXYa5GI+d0PRNZttLcpVGQHdbUSiLFWQUlm/zVjckHuh5KHT+bUqPnOra9Tc1yP3jfL4g3ZjeuZSxseI1NAtHyTS3Ds4jBzCbDTL+j0y4euM7ETQZqlECF+rJSXcYO1W52XqAi0lGsOCTpbTY9EfNHH2nAG7kWXEUPXDXpvxh9uQZGCQDwJDlSV0Sio7WTZs11bb5cYW2zs9zrW8dCi5OzXR+kx4mDBItNMvV11SLa417nbqqGorttTubnPIKUlypCAOISP1maE0ykzwM8e5+ulOHhxIZwRks1+xT0kWYsbGzg/J3JMMiTX71GqgHoYYPVrJEbMM1FMH6nX/PLj3NgMp/WgYtRpsCuha5vTLSnIw0LCkm/PcJ/H2QaFDI4+ggnhK4Z9Dl7jXYgL0gMS3m79iWuswDbo9VufcasIeJf+SbfIWNf6KMXRoCFpbSHPv4LB2v4UNGNbBTz8VW7LsPkGbSSHMzhOSZ7csyOJTIuFASVMVjYzheiV3+hoKWmSgi2pvOwUJ/zXcaNMHS1ZkmWX5Fd9hiOOJXC+27U4s/xS/7mL7hteCmQVjrxBC32yyyHVe9TJDFMJ7DRa5tnJ080p4bcGElWMisNAEk1BcfxXXGgvEX1ln16rSTusXIf5qVceU6TFypl96DO5nQ9xYELgmIOsZuCbA5r95CQHOhN+vCM4LUPQnhEraUhPKQp2R77jIXOiV8xxoNIFGQ1l2m00dGs5YozNgVB/EpuNB48aCNhkDjOpThLle84077Mwb7hyjDU3qlQG1TB2jftmwdHo8PNBQY2o21fjMS0fesH2ECVIq5klm5bhYqmPuucIdnx6jdQBvcQ+3vEDvV8uCdkSZE4TZ+wzazbvtYMfj3D/NsZnXWsBwz71//OMf8eEPfxgTJ07E6NGj8eY3vxnLli2z25kZ8+fPx7Rp0zBq1CjMmTMHjz32mNdGf38/Tj31VEyaNAljxozBoYceiueee26tHP9gMaIszB5xdSfrqou/REgkKr1z3aWhGAKniLUmzegGXfyAW1maW1prO3XgixHTDuMwxyzJXhQK3bYlyh2MgaUotzuYDHmtSLF5qAozn1VdBxUWpc7GUfE9xEIqtoK7BLyW0e1EnAjzaxABEYwhajGOWmFb9TPEayPc3TUoEsoWUrsbqVTOzLYRcoyPth2XDBuS7TmOFR0razP54d2s7EIqCYbdTypSuqY/ckwOETTyhVgdKdUAjISi2VTEFFBOjMKxbjvh1DhTDwhecwMApAQPNGxEDpB2sjeIZb9z58CKOakke3DOuXe8LgS046IM9ot2oP8bkm3qyyI8nnlAcfdxP0dC0Hph7Vy+YT9TuW+3LbMtd49haNxhOOfelStX4u1vfzv23Xdf/OAHP8DkyZPx1FNPYdNNN7V1LrnkEnzpS1/CokWLMGPGDFxwwQXYf//98fjjj2Ps2LEAgHnz5mHJkiVYvHgxJk6ciDPOOAMHH3wwli1bhiwbrD5yaBg5hDkhIWGDgmSCbMmCyvUTEhISEoaG4Zx7L774YkyfPh3XXnutLdt6663te2bGZZddhs985jM4/PDDAQDXXXcdpkyZgptuugknn3wyVq1ahWuuuQbXX3893vnOdwIAbrjhBkyfPh133303DjzwwI7HszYxYiQZ/nJKxdOefZqXammr0QD6B8D9/eD+fqCp9VnuEtMQrMQUSDWGBZ0uDw2nTKEV1rZ8w7Uud71rRL7hLiUaPV4nLxf6uotJGLpeZei4z9bWZTuWdsuUVeWtpCcJCQZGIpFVyyyikoqIhMKXwgUvY8nu4uVLMqhaPuL2HfRr99dSC3usNeHX92QdVByPhis5MS+YdjMt6cj0/UrA14JLLmQY4b3JtebWMnBvTb366urVW1OSDCM9CH/TWp7Bdg6UjpwC6uV9L0a+ELRhxuC+AJhsgpzn4GZTvYyshCPzmutsGM5dZj5zpRX1mpZYROQZRIDIileWKWu0lWGY767F/cldJSBRvLJMa8V9KWhrqacIrung5Y5rPVlYO8Ftt92Gt771rXj/+9+PyZMnY5dddsHXv/51u/3pp5/G8uXLccABB9iy3t5e7LPPPli6dCkAYNmyZWg0Gl6dadOmYdasWbbO+sDIszCbqBixG711mJDFJOH8IGyGJI4Ebu8GzjKOJ83odvl7bSnxA0LcjmyWUmx30n444axlfXMo1ejKMVE1ULzN0WJ8ufepKgV28Zl0cVE+KClOp+e5ahyxCDCAf72FjjHtHuiYK9bTO0OSZGz8sLrjsDws6uTBq6JKNNJGl5elm2obAMIkIdXOic5b1goMNm1W7ePM8+F7O57ip0Ws6+RCdZITiCQg9Wc3QYb7351nDHnLsuj5ImgdMykySwC42fQD8LqyDGZ1rvIckM6DTl+9eMbIMrDRMAdRqVwtcuEYaO6DAgyADAnWyVK8YzEEMrwPax21G4Wk2CrD6bs4nlCyaY6XubiWmLRMxrTtyCzdXUP5hVuGSL2q8qr/ACrzhXeIwc69L730klfe29uL3t5er+z3v/89rrzySpx++un49Kc/jYceeginnXYaent7cfTRR2P58uUAgClTpnj7TZkyBc888wwAYPny5ejp6cFmm21WqmP2Xx8YOYTZtSyHcCcYqR0Lcul7wto2BJCr9KCEDF4A+m7HU0Waw3HF0E5H3LZ/UX4/ZIe3QZCnQWqZ401Vn5Mq7XPV/iTanAs9xk7ajZLlTh+MBpMC3UUVUbb1Y2SjxSRf2nfwJDaHQN4Fs4nd6xI2cGhrcay8eN9ZU51mCOw4zXak/yJahbOZ2SPUXrY9z6BC2uKKIoW1q2F2f8qktczslxOjsG7bdlFYcnMGQYIhAMFAjUFN7eAW3q+MhdZGsJCF06QDFhk4y0B5DsoE0MwUsW1kamU1l4o4k4B1MNT3L2pK/2GDWZHW0aOAeh3UaBSkkkjt21TWam42LVF2/U0og35iKAg6UTAnERVk2Vq2qfgOvZUL9q28YcjM2EpZzAHR3dec11jCFkvWAzLvJTJx+g5D9pn3LefuoRmcBjv3Tp8+3Ss/99xzMX/+fK9MSom3vvWtWLBgAQBgl112wWOPPYYrr7wSRx99tK1H4XXIXCoL0Umd4cTIIcwaJccB92I34XhyhzgHT/92IhTmKbmFtTkMzVO1DQFpLgYbJ1YxEtUqnqUM+yLf6mvjWIqW7cTQkSW35KzRpo8uM/91glJq6jZOjNFz1r4T9T8y0Q3JqtzpA1ALh5GSc587qZfacq3MbY5bDn7y4i51dJw0zK85hNIDC2MUJSqR0EpELtWWmQA7GRtQnmeDz+wz6ur+GYXhz+xuuGJo/XWJuXnP5nxFrPJEznygQ9gZg03OoHqtiDZh+jHHoWUJXFPEuGTkYQbl7MljiAjo6fHbFQLoqQM9dTU+CZB0IvRyQCYzAWS9an9zj2k0dN2aIs9gO9d6pJkEmKTvLGjkDUKUJSShZVkW3wUT6XueIdfBeTUwc50b09mtx1yk0XY9OzPhRCMxxF4478n/Xtx+XZIczNmVvwkRXJODwGDn3meffRbjxo2z5aF1GQC22GIL7LTTTl7ZjjvuiJtvvhkAMHXqVADKirzFFlvYOitWrLBW56lTp2JgYAArV670rMwrVqzAXnvt1fG41zbWLitJSEhI6BAprFxCQkLCusdg595x48Z5rxhhfvvb347HH3/cK3viiSew1VZbAQC22WYbTJ06FXfddZfdPjAwgPvvv9+S4V133RX1et2r8/zzz+PRRx9dr4R5xFmYK6Gf/GzwcesAaJZvdLGUylpnlqWQgYVsHZS8jXV56GNvbYEMraNWRmAsud0s+0cstF3phYci+9DjjcogQv1uOyu1Y03vWu8cxquOxd62VWNmsUHILKrOWxsJRkvH0iHEUF4byFkg70IDna/ln03COkAgLwACy1kLa1moK+406UlL7bCtxL5cJGZRdD+20yWbNsNBmPoMUM4gqf4DXDj3AdZiax363H4YIMGFBVrvQwDAAtxTAzV6lNRB5v58ngmgrpz7uFbTzoixc6G00QCAmgCLHn0YY9S9T6p+ZV1Yi6loSNCaJijPg7ZIWb0bzWIMNZPjQFmD1RCEkmUMDCitsz3Zaj6Nzp1Gi12rWUtzWw27ABiqTxsqlCLZFq1yxLEGxzKeEqHSdyNmMbb7OBZ4OzbyvouWsiOi+PtBYDjn3k984hPYa6+9sGDBAsydOxcPPfQQrr76alx99dUAlBRj3rx5WLBgAbbbbjtst912WLBgAUaPHo0PfvCDAIDx48fj+OOPxxlnnIGJEydiwoQJOPPMMzF79mwbNWN9YL0T5j/+8Y84++yz8YMf/ACrV6/GjBkzcM0112DXXXcFoDQr5513Hq6++mqsXLkSu+++O6644grMnDlz6J2HxMXqk6RaQteOfyRIOVgA6scnDdHSxNklzSGGSparZBlenYgGuVWKZ1ef24n8IbY9IHEdpdbulCy3SqXtjjfUYXd4/N2gyqmPjPd0G42wJ8UYyoNSu+MJJ+dOUBVX3HX+axtdZfDHJEGQXSxyyVJu4oQNHewSExfCr1OCp3SIke4WnUbaizoZdvIz0VICFYsZ1ftw0K+5VJm1M6Dqj6AMMSQV+2VSUTAATZoJSsOsx0yStfyCgAxa4+z0mxEIAlyvKRlFTv5vtl4D96gIEFzPCp2vkV8wg6R6cKAM4KwGMCMfVQfXCDIjyB6ho3gUDwFMQNZg1F9qQgzk6njgPOQ0JcRApp0CzbmEkniY89/MQQNUSCFZqnj4dR0z2o2EYSJD1Ewki0wdl5WztJgbiADBKhGMfiix5R4JNUYz/VlSdA0+pqFteY2be7iJpW1iOpttsf3bEeUhEubhnHt322033HLLLTjnnHNw/vnnY5tttsFll12GD33oQ7bOWWedhdWrV+OUU06xvO7OO++0MZgB4Mtf/jJqtRrmzp2L1atXY7/99sOiRYvWWwxmYD0T5rUV4HpQCCMCxJ7+gOJHLBxrbMzarElzZV9Vw+hE2xqS5ipHglakyk2qEhLsgMh2bHGtsDarosj+7vhC8txq7BWOgWXLeXti3w0qE6S4WuWqiWuoqwjdWLwryHJHYQtjpHkdOVWkKBkjAALtyTHQkrx2mtik6KOD9t1IP+EzsWNNJlZEliI/R7M9fO8SbAKBwb6FOiNLMIkBMFtCXYTQ0/UFKS6uCTZq0H4DDguFBNUUqaUmeVZRrivdssrGJ7xzSblxbIPSIpvPAERDIq9l4IyQ96hQeLKux5PBOiwObCKQDQCiyRDNwiJLOSMbqCvi3JCgph7vQFMRzmbhc0Fu6uw8B2lCbL4j0pE7bNi3ek2R31hUC3eqF1yQYnO9BNpwo6H32rD7mxMVWIFjc3vFCoWr0Scp1b6xhCsdtOVxlqFamId57j344INx8MEHV24nIsyfP7/kMOiir68PCxcuxMKFC7vqezixXgnz2ghw3THaXWBkTAgRuKQZUNZmHVonJM3O4Mtey16TZRIXW4KKRs9w4T6ttkNItFtYcjtxcqvKBOjuX0m8B2MBdgg659B3qYI4U5ZVkOPMjqOUwVC3Fz4kRI/fONa1C9FWlYq6G7gPOJ201UoK0k6K0eq3UfVwthbQ/bJgsjC/1mAtzK0IcZTgdkmIgXgf4UN1ydIcNu7XMZdnVZ+mnEkbmR1LMzHAuSbLBM1tDTEuSJiJ+1zEZy6szWZMYD0/MUHkXERrEgzKSJFdKYGMLbGyKbkz4TsREikCyygiW2h5CgHFfUvCykZkDZC1gizLTFlfm6PVfiIHIAGhZSeKhAPZAEM0GFmDIQYYWX8OMSBBAzmokYOaTdDAKNDqNaCBgYIUmqgfQGFZrtfBPXXfadEYk1qsxLKZ7yoevJhho5DY8xHWqZBvVBppnfHZxQYIFFJPZ/+Y4c6FqdtKutEl0tw7OKxXEePaCHAdor+/Hy+99JL3SkhI2PCglgW7eyVsmEjzbkLCawdp7h0c1quFeW0EuA5x0UUX4bzzzitviD0huUsczGWHPxMfEgAJY2UmZcUMNM0khN+HY13uRHYRdXBoUV46lE7DlrnB56PIOrYkGos7u9bqFvKO8H10eBFJjN7BbdTWJSGdRCN5Zbuugx7Z0E9m/GULuedYaKzYbtxPr3JgWY6NOTqoinYMQutuSU9dIb+ItW3brLA8DzYJzxAgu4wFmjTMGy6q5l2bzS+GTqzIZuGvqmqL67adNCO23RbpPk1YvI4jcGmJhXlPoKLMnWIIVhfMmdIKc40q+1TSDd2spMKBUDKoqcLCUYOUWRdqf2lkGARwJpT1VHIhBzEyCZ19UPbV1BgAyJqArBNknZwEKvrQtPWYzQkjQNbUuHNQoLPW1nYJiAYgGjVkA0DWr63OTQY1JLJ+qbTQuQT15yApgaZU/42F140hHYYBtP/Zi8HMOjNiSa/sgkhb/6WOpR2pF8ozRIWVt6RbjvQFqMXo2O8iVCoah8zyoOPH0iHS3Ds4rFfCPBwBrs855xycfvrp9vNLL73kBdtmlvBiMZfITvHZxoV0pQAuaXY0zSxleZxhkorImFsSnSqyHJNzdCOEd2OMxoh2xzIP1ScRl8gnu+TRIbhAB2S5k6gfsUgV3UJLSRSR10TaGW+p7ZAsVxHl4oCqxxV1dIrcDNz2W+xvH9rawdUsVzn3hd/PWpZiGKRlwY0HlfNuC6LSVmvcLtFQK2lGhGR79b3lbaeOW8XIM6hcz++vkAUws87MZxrTBA6k9cea8JI6PpMyHMbhj2ATl9hAG1YmotrlDOCeQldNEpA9QpFnyVYCYyUeeleSgBiQahBENomJ7BHI6wKyVyCvk61fpC/305p78lsrZ/BPN4VToQBkHZB1Qt4L0GglLaEcEM1MvW+qB4CsoR4GsjVavtGUoIYmzwBMwhT3vqpiLQuYJCU2eQlg57tSNkczNl2XjGRCVMkIyZdnAGXSa8ZSNVcJv543Hma/PQlPumO7YB4qX05z7yCxXgnz2ghwHSKWqjEEcxAGzs3eYyJkeDs4RBmO9TEgzR4xdn8EQWi6lk+6QHuNaSfkuBOLofbAjiZY6cA6bglapusxg5Bbvbe1PDsWV89pziDQTbvn2unMeRu00S6bXQjvx69Jv3tKzURm0rlqrXqpjYAolzTQ3ZDlKsTCGpn+A2cQL3pLi4e0jvuMIZw400SagOp5V8tvfcQIrdHst3DG8/Y17yNwSa6/L7WtU0WeC71xvE8bdYNdJz09yJr+ibI+RgZIGvIFcI1s1AqrYSanT/i/ZVsHioiSBPK6nsfcQQfaXpGb+qLoNyOlTTaEOAv6cP4bsuxp0tn5StxzF5B9S6DN+ISSBRAp6zRpqzVJgk5tgqxfIBtgZGsksgGpLenGEs32uAzhVRkL9XkV6gRRUxaJccw5zuEny8kMeZWgHP7925zH8Ou290cq3dfJnXuzYH9Ht16cK71f2F/F7YNlReSZhGHHeiXM3QS43mWXXQAUAa4vvvji7jsMyYdDDJgDB72qEGVhLGCHNDMV0gy2jhOF9dWVcVR6wnaSljggT6VMg1Vth3BJPWDPB7MJ8+NY8iOkMW6dzrTFmfRs6TxsVBJI36Lrk9cIMW5xXIOVsFQ6yelyb/WAVbhBAPZ/ZCBOG11Mbt7DSwtLR6y+KYoRZ3dfc+yx7Z3CPlgNLgIJoJYFU1i5jRwuMW33OxAV0ocY4Q4QDRvXrk63+7k/u0qZCQr2aFYfNXkDNGnWodw8+YVw+4nMaww7HwgGbLg6fc6MdEK6xBvlgYsmWfLKmSHCZKu5x+pH6zDngrxtrsU59mDEbluAPQ8MbUuxH5xzpC3WzT5S0TcawjoP1lZL1F4h5WC4ZkAfFMA9NU2KVaxorpEi2DWCWJMXZJlIhc8DFYYG10Evg+8AGIFrESZo0my+GBnUC6Jx2QcJ14rd6n4dG4NAWerRJdLcOzisV8K8NgJcJyQkvDaRMyHvIj1rN3UTEhISEuJIc+/gsF4J89oKcN01JNuYyUSisKgCsA5/2oksFu/XoGRldi3Lup/QcbAjra21NkcsDa6e1tQlKlum3afUTi3M+j/lubWOd2pt9qATvSinQBVtv5MwdQiPzdsW37+tRblqvyyLLpV5qGjbJLUpxbGuyrrXKaqsyzE5RtW+rjUjZkV3941Zx9fhUl/epeNJnqwcrz0IKpJlVF1a1iqLzqzHVajQJbdtt8qpLzIua1luNSYCuAYgJ/+nqtsjJq01btM/HIkFOyHbctZ65WJMNrlIRpAZkPeqUHDhOGWNbLuubMLAk2KYY7H3FMfqTPG6LjzZi3nv9uW+ces651zmBPSpcyQaQM/fVYg8MVD4Ysi+OmRPBhOOj4WSmVDGAATqTUc3IqiwLrNvRTZ6YdLejTYDZeAEGMZtJmNFzosy3+GvkFjYlpw2vbB3gcyu9DncZ5BIc+/gsN4z/a2NANcdwbr3UlDskOUSwSB4sZVjzbpkWGqPXCNtCAiJieqgRL/lsYSgcFk/JMFGYytEuU4nkgCXlLmSFEOsmJWjhX7PeV6Q5ywrES6PoAnA0wd36ji2NslyqW1d3zi+VZH+Vu2GEVQCx76Oomm0++6H4mTX4iGg00gqHZ3XtUCsJQvILhxPZNJLv+ZgE3EYVBHXlgS0/bXWaWzmUPZQRfbC/UNnt8p+XYKTxeupiBfhMnykb4ay2YRMEyhSbAuAGrDxmCUV05EhxV5XQjXltua17KoBXPmF2Ub+9+VLSYLxe205/VfAjsNtLys25L1A3kdo9mZg0YvRzzUBUhKM5uhMabI1aXb7zPq1f41kJT8RVEQIkYY8h8dNvvYZjsQiR6WxSbXp1AVgNdF5ZN4nUl9Upk4sE0qSTev4R075EC2+ae4dHNY7YV7nsNbfSFkEnWa9s2TYjRIRyWbHktUTrHVwq4huYIijIV6uxtm1JgsCRJEVyavraXHbkGb3h1/jwoJqdNhSqgxM2vrMeV5MBEYzGzojuufVOAaG5eE4YuHTKhzYPK1uJzBEOXq+u9Q+k2NBNwiIMgkRP+YqIg10RpbDOl08ZHQCl1hXntsOHvjaIVk5RgACMtxtSuuW+4U8sgtCGyPxLflDFU8J5ySHkDMK623oTFiVOdA2y86bXA1A2Xy0blZAOahpyB5FHGVdJxUx54ZRhHmzxxmbLyrG45DXkBh7WQlb8TiKkOFInzH9tBttw3w//ZsS8r4agDGorZaQGaE5OrOZCN2xMwG1/pqyyrN+yCBliBMN3+DjOQISyo51jM60wwIqEgpQ3B+1xZkcTmCjcwj11MEZgYhUghOdpdAdj9G6u+disEhz7+Aw8gizQUVkCM8K54Qd83atIDU2LnAgxSiak7ZNa42OOJgVnx2ybIieIclEBUELCbR+X8pOFEPopKDPQ0mikks17lxlYCIhgGauLPSuV3EoJ3HacSUd6nw5nXcSyq6CpLV04Av36TRetYtwHyJrEbCfg345Fm0lhsDhshSKLuKgWh5f8JDhHG84pk7QteV+kFCry52T7iH6uSSsB5QtzF2SYhdVpLnVvlWE1t23A5lFJ86BYbutxtXKAdGVSwAEJoZolkmy3a9GyHt13OTMWLD1MKRPrsKsi1Hrf2x7BWH2rM6mXtheuA/K5V57Tn+G6JvsgUZm0iTg5ek11FbrtNPsSFTMmLRD5MBYAcpVG6LJEAMSWdO5LzmpudXDCPnfr7FAO1E5iq8nct9iZfm3lmhLltmrS4AfZcMqGFmVZ05FQ5ZjxrBBIM29g8PIJcwJCQnrFd17aq8bIp+QkJCwMSPNvYPDyCHMUqIUTd0gZvE0cUErMtgV+wah1nLHAt1pxjfAsx6Tazk25URAZt6L4j3gvfesyp08jbrWB+9AXGuz83ScS3Uu8xxoNAsHwVzHIg4Tw7g6vsC5krKsq7jPnaIkc+lEPuB99yJeHlgSqpLFeI6f0QoVEozwGuvUabAD63Lsc0t0YsEQYkhrg90Hz0+T9msOjkTMRpocjCVZI77k36XVmoLLtkoa0KaP6PF0YF2OjaeqfxsejgDOlNxC5Oxt54yQ60QmwtHXKr0ubPIR01coo4j2HVqEY5/dthBYlksrC9V9eAi/G1NmplqpzrmsATIDmqNIJT/JCWIAyAaUxZkFVKznTIWnM4Or9QMZCa0Bl0qiods1GQ9NLOfCCd6Mg2xSk8IhUJWH1mN1nFQ4WhOrza4DoblHm9Xg2PQWWJfNNTdUpLl3cBg5hNmgRdzarrWkpXYColwFR+tKQqhEJC5ZNgTYlLtE2ZVp6H2iXraulhkBkW6HUIHAOnS+dXhTqVhRa2oCnVsiTSFZdJegSEfwd6NvGNKptV7kfg7QDZku6ZsrdNBRdJCsJSq5COUVMVSR4MFIMcL2ItKQrpfuYqS6qg0dDWWwkCDIlt5e5foJry14kgzDWzr4GrslxqV9WpHuCglGK+lIW2lFSChduGXhz7kdWdfkM8/0B3MCCR55ygYAypV0w8xDsgeQREoFaL4HT54RH4tHggOC7O1LKJFkd3v0PHfyQBE7l+a9gI3dTFopQbmasjP9cGF141rOkfeQJeKyRsjqqoJoCnWqGlLFZs5UBI7C4R3OfUOTZKIi46AeD4BCs+zCBmKiwugUZhF0ybJLnjNHUjkMSHPv4DByCLOJkmE+trAclkhKB8kZOnEMtDBkOcusBVm9J58oC0Oe40TZ/XEBCKw5AUGuItAOigxFPuG1T9P6h6/alUU4HUlq1srJi7ChrPqRH5oASIebY3tunfFZ4ul/RzELadcW6XY66cFMUp0Q5co+zDkPjq2TtlqR5Vba+I7G5bdPFSHzSAx+CklWjhEAQ6yo+BiiE31wR9Zal4xVWevatefNkeX9YuOKOfbF+mzVVmxfcm5Zxrps2iDrJA2d8ppt2LmQ8LrOeVEyHBlfSHZLDwbmfdV2imzv4IEmJMnRCCqkBmBnyJr+XAPyHkA0oR8c1Oa8B8raLJR/vOwhiFxANDNkRMiYwXYlmf2FaM8/B4j6vmnLsxuGrpS0JEaeDQQAITzibLXmjqOfe46GGCQjzb2DxMghzIiQq1bRGrqEF00jIsEw4cZIaHJsiLH72SXLRECt1poom6dS82MDolKM2Lbo02tMhuGWy6INZdXWFuNch59z5RrGcTAWfsdYoTNSma8ALza2JeVurOSKB5yYU9uQnNaq5BudhNUxMh41mKLcjS9tVhVsszy4ay5IB14iyt1Yit32EJDjWDhDu00MzolSo3tP7TRpv9bgW5ir4w2H+0RRRbLakONom+0syJ2Q69j2NuQaCOwRQX2TIhpAYeEkQq6tpTY9tXlg1eRZ1qGy2+VarlBTWevyurpPtCXMLYgqh3UqHkxKDxhuO1Uk3ZDQVmMKCWLFOZYCQB3gAVWHcmV5b/aqBw7OFKmWOUBNAkmh6nGm7ne5BIFUiD7PWZKc7wLRGMjekDR5NlIOm/rakGg3BYC5l1YRZfc34zhscja0uTDNvYNDOgsJCQkJCQkJCQkJLTBiCLN1xHJfgI4x7LzKO7ZuOEha4b7ccvs/y+yL9AtGx1yrFTIM8zKOf/ozu0s3ehtn+nOmrc1CgGuqnGtC6aFqQmu09KtGxasuwHUBWdfbzP41Aa5n6pU5/2tC/e+pFa/eOrivDvTUgb5eoKcH6NWvWqZe7nHWatrCbvTaQp0PEs55IV/PHTpBlr4KX1/ciVyjUoscu1YifakPHZjNXOuyu2JgtnWDTq3Lbj8xuYXzIhL23NvyzDnf5nsz1697rQ4SkqnrVzf4n//5HxxyyCGYNm0aiAi33nqrt52ZMX/+fEybNg2jRo3CnDlz8Nhjj3l1+vv7ceqpp2LSpEkYM2YMDj30UDz33HNenZUrV+Koo47C+PHjMX78eBx11FF48cUXB3NKNj4E158rEfBeonhZi2TwcuvYV1ZRL2jf6kMF2XBjoVzBa8PdBpStqxVjbHWMladIW5VFrqyiJn6y0dzmPeq/rGkrqSgsprKusvo1Rgs0RhP6xwk0xgg0RxOao0jHZXb2C8+zgOMY6NRzx+3W0dtlptt1v4ewLfezZx2vfkXHFF4TKNpzj0udCyDvA5qjin6V9V39V9Z3oDkaGNhEYGATgcaYDHmfgOzNbKZA4/hnQsxx5jgDBnOnul6oeOk503wG9PFkahsLff8099JaeF8WaoVAX6sQZLfJmoDU9/ahYLjn3o0VI0eSoZdTLIaQTc0Q4EoJBkuvnq1jCEkm4s591sFP+FKMkFAZaYVdwnHeO9vDoOd2eO5Sj1uH9XIUR7xxjcewLD4r51/tyMCstMxGwyy1BzJzoGtmeAlR3G157sVjJmTaMRBa60zFPq4+uoVcolON82DkHNEYxwLFtRWTYhhtOlAcQydyD4PgWmhJljvZP5ZqPWzPJdwhyZcV/XQA2eWyYLehjV555RW86U1vwrHHHosjjjiitP2SSy7Bl770JSxatAgzZszABRdcgP333x+PP/44xo4dCwCYN28elixZgsWLF2PixIk444wzcPDBB2PZsmXItIPqBz/4QTz33HO44447AAAnnXQSjjrqKCxZsqSr8W6MKJFFAqqSjXSSOKSqD78uVW8nv7xSfxx89rS0rS75quMLf+Lsb3b74MwQQvI/Z86+wXnlzByQ/hyey+C43bKS5AJO++F+VWVue23aKY0pdo04qHpocR0LbbQS0lMSqcR6LADWRJlkMX4WilQDOtV2g1F/VYIFgXK20TOsw7tkJdfI/LHamNdBIjQbqzlwNueak0HQPUeGoBPs3GoMY6WMi2jzW+kAwz33bqwYOYRZardaN4NeVb0OUZnQJAxF5xBlY1kuEeUYMfY6K3vTRhEjy4BHykiqWZ0AsMkoZCbnmlAGjqB90rpm+56hUo0yg4Qmz1JNKErPLIBME2dDCqUh16IgyK7W2dZzIm1oAm3IMwuptdRx0ull1xsuuOcm7Nd8RyaenmsFdsky1DGoIPXSJ9q27RZhCTuxartopVF224sRZZck23qmjdap41uh+/Ss3U3a73rXu/Cud70ruo2Zcdlll+Ezn/kMDj/8cADAddddhylTpuCmm27CySefjFWrVuGaa67B9ddfj3e+850AgBtuuAHTp0/H3XffjQMPPBC/+c1vcMcdd+DBBx/E7rvvDgD4+te/jj333BOPP/44tt9++67GvNEhRpba3firCJPdHr/22+mQYyHgOKgXbafF2GJjIOc9oEmVQ6RJAlm/+iDriiSZhBzKekueZbZERM05c4+v1bhjxLjtOW5BhmOk2d0nGFuJEEfGVhpLpJ1KIk4mipP6kmUN2joLGJ9kuxKhIcmxTNcI2QAACGQZI2sovxyRM5g1gRaw0Tm8TImsLir1wMKeo6YdtDduAiNw5HOMVzYUoEuS7fai7aFG0BjuuXdjxcghzCGqLrgw41ynYbOCjIDsxHAms+ztRr8IM/eZMQXpldcq7IRdEFKTfc/KMYgga+W+rXMeq9mfGKAmK8In9ESRG8JLKr12rt8bQmvC0RmS7BJp1k6DLnEGfEIsAJKiIM2AT5xjltpOrLeu9b0qVXmkbvjZI836s1cvtP6GZNslza4UyIScayfFCN93EOWirUXZDWlo9nP3yQdPmHMQ8nYMJKgPAC+99JJX3tvbi97e3q76fvrpp7F8+XIccMABXjv77LMPli5dipNPPhnLli1Do9Hw6kybNg2zZs3C0qVLceCBB+KBBx7A+PHjLVkGgD322APjx4/H0qVLRzxhtkvqBs5NvyOi6v42O71UQoKpy8L9o5bPKoLWQX92v7Adp5poAqLByPrNvKYkFYa4uVKE0hgrjivsJzamdsQzGk+6giRXntdYnRbnsPI4ItZxb4y2bfaJpGD7ngUj79WWW20rY714S0J9D+yMVdaVkx5nBDnAEE0G5wxqsJoqnelYZmSJMYOsMYmMes95MDIPQarAuZZD4xihkINY8gwlx4g9VAxRIjHYuXekY+QSZgclYqOJjCUxBq2sz4FV2UTNMNExDGEiowENrcouKXHHEkbFcMHaSuws76lUm7o8JEMuT9M/OLs8ZI6boGNABl0Vg1ITgzk2HYaHLBkGSKr3nLHyRBbSSjRYaAuyhLJ0u1ZnNB0CrV8mUoaxGmd6YnMjarjLXjr8XFdW5iAyRlvSHNumiXJpv1ZSCfe8t0KELEfHLxxSi4AklyZoio8tvC6FE+4wKssYvOVhsFaO6dOne+Xnnnsu5s+f31Xfy5cvBwBMmTLFK58yZQqeeeYZW6enpwebbbZZqY7Zf/ny5Zg8eXKp/cmTJ9s6IxoBKa1eni8XdrRMjwjZC+rHiXib7RX9dgRLxPTv0MRAc4gU6zlWmhjBGVk9rm89rT62mHW8LanugKS2JOkVBLm0X9hXZIxtrcfBPuzEMC6N0SXVAlZqI+tsCTOkinYhoBcpmypWNUkADaAxhiAHAFEHsgapUH0Zg5usjEPayMM1HRHLtqvHkOvv2hqhnBtuKMEI7ucm2YpZ6YW2kEdXV5iHLslIFuZBIRHmhISE9YIc3VkuTMKtZ599FuPGjbPl3VqXXVBA1Ji5VBYirBOr30k7CQkJCesDg517RzpGDmFuIXMoWRSNZSDIOsdG2d8qfrNjabYSDWEy+rmOfiI+ntDZr8qi6PWtrMqAY2WG0ha7jgR2ycfVSemd3GUg63xCiPbPJoayhHIQlMrEQxlrj29tbZb6M5GyJhvnwFyApFTLSrmSdSCXKvJCzDEw1DcLFUOTWb23mubBONFVwLVQR63N4XlxpSHtUJXFz1gdqlKyd0LAXOty1fVTJb+IrXi412mF3GOwGKyVY9y4cR5hHgymTp0KQFmIt9hiC1u+YsUKa3WeOnUqBgYGsHLlSs/KvGLFCuy11162zp///OdS+3/5y19K1uuRCOu81kG9Eqqsyi2szZXygi768duOb3QTT7h1bNpqBoi4JEfJ6zrzHHQUBSfqhR0fucv4QGk2i1l/W5yTUE/s1WlxPkr66Sorc9hnOwtyVV9uWZD/OdZ2dAwCSiphxmu+DtbfWQ5IEASKqdVEG1HSDEA0HEvzAJANEESmLcwMT+YBCXAOa32GhNUf2xWFyP0o1CjbYwyty63m7yEgWZgHh5FDmF1iEIElzeHyiUOWKMsKQuTKNoCydIMCAk467bVLlmPOXOGY4UzIrtMd2G4jI0+wS4DF2DkjwIav0T9kvfTDoT5K/1grf8heRWfpyy41am1Xzoo8S6h0rUDhPGEkGFKTZcFW90smrau540lW62UhcdYnw5Jm53jN9zNUWYY90pgOudUk1iK1d6vrzxuvS6hbXCP2mnXGRaHWuIrYuyQ4JMpqQGXC7Wn7zf/BP5ysz2xT22yzDaZOnYq77roLu+yyCwBgYGAA999/Py6++GIAwK677op6vY677roLc+fOBQA8//zzePTRR3HJJZcAAPbcc0+sWrUKDz30EN72trcBAH76059i1apVllSPaFBEg+mQCftZoxWhbSvbDOq1kmmo7W0aDDc7Yy45VevtboY5L9qFUO4wXqi0cP+ABFrJRZsHh5gjnimvfHjotM2Ksdn9Yg6IsbbC/l3EyHErkm/K7HsuDtYdU9A8Q30XRDoSVNM5NgHwGK0xH1DEOesn+12p7IEEK0GEem8iToFJaZ5thAtnaOyPpeTIFwYPqCLLa8EQZJAy/Q0OI4cwd4OS5sh5n2VePUuiTbQDoCDPkh0tqCj+i8yPX+v9onyiU8oSJP1fIJl9zA/VZA2y8ZqFcmQk2Cdka/3QFk2jnwIRWGuw1D2tTCKLCUv35zgBWgKdafKcM0h7fBv9MkkTVUPoaBqKPJNQkw/l7Dj/sV4LcoRn7rk0pNk4AQ51QqkgzS1RaT0jx4HPNXO0u0lTUdfNHNhq/1h6ddNWK+t42Jb7ENeKLLsYwjlnEGQXy4LcRV0A+Pvf/44nn3zSfn766afxi1/8AhMmTMDrX/96zJs3DwsWLMB2222H7bbbDgsWLMDo0aPxwQ9+EAAwfvx4HH/88TjjjDMwceJETJgwAWeeeSZmz55to2bsuOOOOOigg3DiiSfia1/7GgAVVu7ggw8e8Q5/ADxi4+mOUS7zNrTZ5taJhobrlBy3uKTC/u1H95JX05+nn2WCTWXtRmdgQsni7OmV3abdbZFBlEipiBwLwfhoR/eJHq/bXunAg3rh2KNk2PwP9MctxlFFzmPtcdi+unF5D2XedSdYxTOWarvJxgdS8ZulBDAKqL1aPOxwBogGkDUUmSZ9D7YPZhmptORQpBmAuucCdvXVHrsZY8yKrKNslM5jl8aXTjDcc+/GikSYgfiSu0tO3PceQfKJB5kwaVDWP/OjKayAVPwXAWF2Hdd0nRJZNqmnm80ScVZJJjLtZKhepK3ZbBKa1DNFqLMgILuxNmdQv2hBzpyjJwLncD2rkSHOME/T+uldAJSRCj1HwrM4k1neyk0aUnIcFbW12RwvkbJGu9Zm5mrSbKzMrvPf2ngyr5LPACjFMgaKEHhqiHEIfQcNx+v2ZyQaBs616CVBEVRNlrtd1nPbaUuUN1wL8yOPPIJ9993Xfj799NMBAMcccwwWLVqEs846C6tXr8Ypp5yClStXYvfdd8edd95pYzADwJe//GXUajXMnTsXq1evxn777YdFixbZGMwAcOONN+K0006z0TQOPfRQfOUrX+lqrBsrOCR9IblyCJ1XHiNpLloRa0QIchfEuLKucW7WZMsWm+gWNaBprMmaKFfJFKz0ItZnZL+yZCEYfyuC7dYNf0Itzn2rtnzZHtBWQlHVl7vNvRZK2wOCHBtnmHPcJcqOlZlIOQNyBlCuvgRiQPY4laAJbU29aq+qe5JooLAq276c86AjTJk6FMz9oeXYt6aTtROpjRxPo74WJBnJwjw4JMKckJCwUWLOnDl6BSQOIsL8+fNbRtjo6+vDwoULsXDhwso6EyZMwA033DCUoSYkJCQkbOAYOYTZ6H6dp7OO4u1KCZuNLniys5ZFk4lO1Kzl1ybrcNty23bCxXlyC8CxROuhS12nmQONBtBogJtagKVlH+SGHjN9GEukTitNPXWd2tjRNhvrs07PKfVylbI8Q1ujI1Zm/d5mWpLmCbh4SlZJTZSDBaTReKGQawjf0mzqebpm48hnOsjzworcgZU5ev47tDi3Di3nWJcrZBlEgcY6tj3T49OrE2GfpdCGfgNFIpzQuhyrW9WG1S87Tn6uhXktaudcdJtyNaVnfQ0iZg0Nt6NFnYqvvKX+OGpxrq4e19XCt3hq67JoApTDyi9UkgzYudBIMEJtb6VFucqC7OzT9tw4lt5257fS0Q/B9pgFO/LZhnqr6LeVZVyV+frj0j6t2iSutGB7c5YrczB9Cah7Usb2S+FaYCU3of5Ifeeiqb5vN98CSaiYzRlFxoeSw2tcthIUaumkWaC0DobOcdMQfEdUF2nuHQxGDmEGOlvKaFVHBygvp6omuGmcVVXpyyZCTSipnPEg0svw5Gh04ZMWyOKXJiW42QSv6VfNaIJV+fNxHcLcbIM6ageJDKipF2eELMsgR9VVIpOaUP+FIrQqrqSZcEgtO0IVeWlb9T+SZBIhKTlGBojcJ86iKe12iayIpmGJMynnQElKomG+B3RGmqPOf7HvOHggikVNCRPNUOjYacfWHuVEIoXDoldPx6Hm3AnsY7TzQvhSDPe4WskxYlpoo6vXMh673chivBuQo8keApnOu0zP2k3dhA0DVpLRZuotkzJ3roQ/wYXPv8HnVlEyop9jYzH1qHgrSQ2EjE5ZkFqyt5+LfUrOe0F7LaUn7nkIneoq9m/l+Bf208oJMEq8CWVCG5L1EOFYYpKKYFs4Tq++COaZdteUcC4CT3PuZKU1kaV0Vc4K8p9nrGJkQ4AkkDcA0aMjQ7l+5k19j2IuDFwEO3+6zn/R43KPh4v3BHV9GWLMBJ0oTL9vDI0wp7l3cBhZhNlBZYKJENEkFRy3KhpHPtapnImthbFEkJx+uaa+BnIIiNEagxmUE5gkqJYBzUy1ZRJ6AGWdrqtxZVbWS0BZpR0C7WUfNJbKTCDr74WoZ0rzXM8ge1SUDdnUFui6uguQ8FN8Rr2bjVlab8uFPqXa4gwS2srMAKSqQMrqrGYqApFUye6IVLnRM+tz7XwxZdKc55WWYo9It7TAOuSzSrccCx3UwrrswQ2NBwQPAiiHy3OJPYnyNdrKMu4i1NU7ZNkSllrma+jVgXXWfhskK8cIgCGSbeoY2JBccMuKIutcV0XSUG1lbbWvjfZj6ggUD/8EcE19Ziepk0dmI0TWW5ELHhwqCX1AtmOW4Sp9cNWDSay9WDt+PY6OMXbMLhmOOmDG+vC2VcwnsXG7zn3hcThV1Fh8K7O7AxNb/bJ92LEPPOYeDOR9qp5o6NsoKwc/Q2ZZP0SJhnNdmIcO97p3de/u2EMaold3lfGMrXWZmipVNxgQzOBmFxGgIkhz7+AwcghzyyW8yLYOYu8yS0VYXALtWvqIQRA+0SlFnSAdxYKU3tLEJRYA17XZtimV4xuzJS8kCNwwmfGkT5Jjx+RaBY21kghsLIiiWcgLGk1QLbPWZ9FbA/fULHmW9QyyR6BJyvosawgmb//pWj04AJSraBpSc2ES5r0K9SPY1NUxpB1rsyLSOaxDoNSN5wG5DElzaB11h+nsZ8hz1LIcO5+2u+DhyVgEOiXLzj4W4XcohDq9biQWcy2Zh7QKC7UXwzo8HkuStbU6E0WUFcdizlJFTUEm4hbnQUJCQHZhueimbsKGgWj0BgQWZPh1Wjp2hdsr2vD7KrYbi7fH0VhPLfp3KM3yurufsFVbO865n1uRXVFtZa609lYR3nAMwdjDtjxS687RVUQ9HGOMUCMYqzeWiAXZ/OeKMqef8nFE5h4q9uPY2M39gjQJBQFNWEuzekgyYeKU1IOagOyRkA2BvE+HPSVA5qqtrJ/sebDXh3O9l76fqlUS5xxYx3vz8KYJOQhFfgPA/h8s0tw7OIwcwpyQkLBBIWdC3oXlopu6CQkJCQlxpLl3cBg5hJm50gLREWLCfEG+lTlzLHmuxc/VwLrjcSzPXFOWaKJiuYVJ5a0nQWr5SLdb6I8HwI0GKBdleUGYYMNYosNlfbP8nzNYr2URoELXGanGGgGq1YB6zVqbZW8NTD2QveqRmgnguj4W13LB0OHT9PnP1XERKcdIIkDk5mlcFMlNSMs0iJXDjc6aRWrNSks2CECztZWZKyyv7nkBqiU6VXIO870DnoW4K8tyZBzl/p2TGWqyPct2F/2G1mVjrTaOpubaMWPS6h/KUViZ1wLSsuDGDxXjnXxLYqmO86HK6tqyjxYbYxZZbbTz9KWsnLqYAAGGFATpOvOJcpsttclh3dBiTf5+3hgrrMqttOCl9qukcsShOsH2UWXJrgwZB6efiFSi2D/yvoVuudRX0DbF2mDydctmuzGpGw0065VchpJV5FCSx4ytRZu0lZlrqi/ZY+QYAK9RMZlJqwJFE9bHx/+enPlTl3mHaQ7JqNyMZVq3a9q3oeWCFZGhJIwC0tw7WIwcwgx4y9JeOux2CSWiko2izJKnsJ0YCXO3S6gU0Xq5gzMVNYEyhyxp0sw1AaoxqCb0KwPVaqA1/eBGMyBSmlC72dqM41gYvzl2jFJJQjwZh47/TI2a6ru3hh4A+egamqMypWsmgqzpB4ng5qQYNdQHNudCbZcEmNOnls+gibWeNGSmls2axbGA9BJZraYqyTDbvSbNxGU9cOxhJqIBb4e25Dg2qTnp0gF1nLbvULtsop8AQE1H3NDfdet+nesgBkuQWzgGRspV3FIUpHkwiV7c9rpMz8opFuhrDy45DMqj7+HUb0GyQ3RKmqPjE4B0HvY5c14hEQ6OpaV8pGpbCxLsSjYUqatoOxhLVI/skuSKMcXkG5UOeuE43SgVVWQ+QoxLWvJQYhG0UyLIsWMx9xXXOTD8rAtJ6kurxso3hqGkGdBToia/Oo0XZK8EoOWHdSDrh0pgkusY3PrG5ct8qpKQGCIcHKMbEUPqnAXSj8NsdNAkGaI5NMKc5t7BYWQRZsC36nZDml1UZXczRBMok5aStVdbk63lV804KpRNZidvSywB5QxQF6DeGkRPDbSmBpFloP4ByNWrgWYTTAImYUkR9UBpoa0ToEueg2PyrKbGMuySzGYTYAmSEhkRqNEDMaBIcz5KxVSS+qZjJ2QuXkza81ffqCh3rM01gHPD51ToOTWb6fNqRM/MyhFQQJHoSujzaicjhzyHZLKdhdZcH0N5so9E1yDSpN7oys25joQKJGRqnm004aGTa9fq6kk/RIlSVAxXV2qT5oT9hG0OKUoGIe/ClNhN3YQNA1UZ6Oz2im0lItcBeW7pEOi0Y8mJmZ8EwDVlSSwRWLNfO4LrHldsewWhbUmuRUWdyFgKIu5bNUtjd5wZ3fptnfRiFmS3T+c7in4PDrkOpw0K6wVj8N/7fZkir06UUDvIAMqU1ZmFAA+IIkyb4GIMQkdqgoTUUTOoScBLQpHlTD9oQYdFzeFF0bD3b0Dfdwuy7OrISxbkCBSJZlAutRFpaIQ5zb2Dw8ghzE7INxeVpDm09rVAZcSEkCSXlmlMX/ol1A9K1gjWsuwSZjsREKg3gxhVgxhVR40ZoqcOfvnv4IEBcLOpIl4AhUOXIBU+TrJd2reyEDf+czju8Hw40RKovwnBDMpzULOu0oOOypBLAfRSke3KPb3GEU+aAmh5hQ5+QVBWVzMZa2uzdeDL2coIqFlkJAQREPBIQE00ygGQy9+HiyortHsdtLPMt0IsFJ0pN14jRjJjnDht2D6y/RCg061ysVoQOy6XILsOgoaEi4IsmxTppePJSD3AhMcdpvweJCR3t9Q3xHtEwvqAvrRbhXqLXgKlOS++PURbh0A9HrPoZfsJ6niOWB2QW6//duQTwYNEZHtLi7Q5DreviBU5FpKOY+HZ3LHbcvb6Deu6BLhM6Nkbm2chJr9qtO0q9kgAhbGXW+3mEupgHyJWjmxCR5BqkLoPMdR9WGjDEitDDmoM1AjcJOQDpMKckqorMiAbUM7o5K4YaqOXsfmEIemMFTqazQ/OPk2TJVdaySJ1I8GLIM29g0OysyckJKwXSL0s2M0rISEhIWFoGM65d/78+do/qXhNnTrVbmdmzJ8/H9OmTcOoUaMwZ84cPPbYY14b/f39OPXUUzFp0iSMGTMGhx56KJ577rm1dvyDxcixMAO+JXWweuZAjhGNr+zpgSOW6lyHR5NafgHYcHGstVDK6FjIMlScSD1eoaUNLEB9Gbg+HtmroyFeGQtavaZYsjdWRTcphbEQy7zQoeosc3afTpJe6P2UJKKpFBM67A3lGYAMVAfyHu08A1iLhWmCtFyCie1SlQBZy7Inz9Ah95gAIUVhcSYCKFcyFECHD3JMzcJxAASKayA8NtdaGso23Kf58LvsRPtcFbtZn0fKssI4YvpiFcObjJnZuT4py4pEJq4MKAbXumxWGxynv1J4L6MPNwH+zSoEcyFtMfWGamEGQXax1NdN3YQNA1ENMNDe2tzC6tyqr1jEsVibHHwujUsEn2NtVFic22p/Tb3QAhwbtzuOmJXbteaG2wkoSS68OhH5Q6T9bmQWMWuy+h+xbLP/mdrEY6ZAFkIEsJ0uqVzPPY4IRE3tLGEcU0kl1BI6rCmg50FleWY1SB1SFTonAZC9ao5HHZTKZKvuh1kD8HTJEWtyOFxPpiGD+0vsXA4Cwz33zpw5E3fffbf9nGXF8v4ll1yCL33pS1i0aBFmzJiBCy64APvvvz8ef/xxjB07FgAwb948LFmyBIsXL8bEiRNxxhln4OCDD8ayZcu8ttY1RhZhDtGONLdIiw1UkOVO+7Xxj4XS4zIVJMSdzTVZNqk3LZEWelsvIHsFxLg6sjW9EP1jINbkEANNRxcLNfFKTYBqDOSZOj431XQsXnSrhwfJQFOrm0j1JYjsRZX3CSUhrkobaoizXt5iCUiY6Bk6vXju1lW6Zq6xTXDizrsEqGU1AJY0a7kBSe00Z8hquMbUikB7x9xCqtMFefbOL3OhZW6Xrt0krGECpEOqw76FsGnQrV65ZrTxZGUW5j9Ld7zq2vRiiAPqGsqdPhIS2qAUYcIgRiKD8rB+J459to4rqXDrmPLw596qrIL0R/sNtldpnDvVQntEWRPgmKOePcciIMjhGN1U1iH5derHtMuxGZGc9rzTZ4idS2LbTBklohtIKch5AFD+PyqClLo3uExUjyfsL2Sr+gkg68khMwLnBMrYI8yw92U9FsGQY3Jwv4CsE3i18K8LoZzRa5KRDaDQRgfSi9KQnHnWqyd0VA8BTer13L+Bz7+1Ws2zKhswMy677DJ85jOfweGHHw4AuO666zBlyhTcdNNNOPnkk7Fq1Spcc801uP766/HOd74TAHDDDTdg+vTpuPvuu3HggQeu02NxMTIJs5tsolNLs+v0FXP6i+l/XZQImUpGQlJlsUMuYEKn2f5Y/9ezhucESCphCAtA9ihik/UJiGYNYkBCNBiiISEaEpRLlRAlz5VXsNbmUq6Jc54XVuaII2DlMbF2qsuL50+hx5eZcyoyNPt0dXvOoSIuaA0za+22Z2E2FY3eOS8+s9SiSBPEHbAPEIrooTgO4xSoSbM6tdL/DmMCLddZI0wKEurHOtC6exFLYtDp1W1K9arxuNBWX5bNwknQWJLrNaBeL/TrRPqhS0+6YVARFxLqxhpGEnHGaq3Ng31oRIoFOiLgEL62Dnmx9xqh3titUvq1RAilbaNFvzFrcrcW5o6cAGMEvKqOADwrsUugnX3ZJcK2LpeJcaweij5c661XHh4TIts9cssoWY3D6a/lBeGMVbdXngLZBlyKIWaxLuqyvrWqOpkAOBNBXcVyCQBLAdL7UE0qh8GGUEGOdNhXYgASqBlbTc5Rkmzbd8hyVT3LjfV91dxDw7F2i8HOvS+99JJX3tvbi97e3lL93/3ud5g2bRp6e3ux++67Y8GCBdh2223x9NNPY/ny5TjggAO8NvbZZx8sXboUJ598MpYtW4ZGo+HVmTZtGmbNmoWlS5cmwrxOYBzMqrYBmowFpLkL5z/vl2veV6bWRslCq4gjaeupXhbXj/ZmicZzCpCuBYfQHAW1FNSXKcLcFJo4M0RTQvQrb2DW5Bk5K1lFLhyLs4Rd5wolBFXQFnPS8ghBJtoHIRuQEHmGvO7EZ7YThXGK0MSZVYQNypV1WWhnP3aszWrCIofwKac1Ey3DNE/MysicZYWlXZ9zIuGHhGsV9cQQzKpMekB31wgQfxDT4yMpys6pobXfPLg5GRvBAqgJRZJrGdDTA+7J4tckERjSl1i4w3ejipjjN0XmgURfc5Btro0W6FYblzTMrz2wQ+48kmemXIYnTaiSZHBQ5vGLsG6EtHZinY6OITb2WD9ufXbaqRpb2HYlYS5Ib8my7Dj6uRnqvPYDy64bL9gO2yXHpXNnHk/c/8V213IcJccBEzR1CnuES4pNmeaH7cLNsTc1FccY2LpKYzPjC/cVuVrpjdRn7a1nI61KKozPLCB7CNzv1jf37BaMuTTwYIiBQdwaPARDDmHeBQY/906fPt0rP/fcczF//nyvbPfdd8d//dd/YcaMGfjzn/+MCy64AHvttRcee+wxLF++HAAwZcoUb58pU6bgmWeeAQAsX74cPT092GyzzUp1zP7rCyOHMCckJGxQkOgyeH67Nd2EhISEhLYY7Nz77LPPYty4cbY8Zl1+17veZd/Pnj0be+65J97whjfguuuuwx577AEAhc+RBjOXykJ0Ume4MbIIM8vCahqTVrBZ8pd+cohQyxxm+QvRyrocjidX9ck6sKmXefK2lmXX2snFf2NlthaIjHTQfQI3GJwxZA8gBghZRqCGhGiyWmJqSpVBsCmBjJSlWcjqpfiwzHUIAwppBhFEphwpOCOdDYkhiQpHFmMtZ9g30iadIwhiSGgtswnho+tLVvIVAamcAJtQmRLNEAEwamosTV0esTKrQ9Ah8iLfY+EoiPZW5iq48ZRdbXgMWm/tfTZ6ZPPemjgY3FAxsZFloN5eta7Y1wvuq4N7auAsK5z2gELCYq7jKt+JVj4VAmrVQ2oddLvVhxZgdOd4wokwv/bg/N69MgNjjRUtrMau1bddX4hYmDuxMlf12cLC7G7z1AWhX3BoGUakbdfK65TZ8HOBRdkfIzthIWEtxaHcgoRjEXZ1LbbNiPXYKw9lG6512R0Xe5bkKie8khXXWHcj21yYJuz9w2vEWLZhj9Hqnc2Y3P1DcHxcRGzbVsQNyCUDdYZsoEh0U9P/9covSSp0zCjG68Zhdj+3it8mM5UZ13CGoWCwc++4ceM8wtwJxowZg9mzZ+N3v/sd3vOe9wBQVuQtttjC1lmxYoW1Ok+dOhUDAwNYuXKlZ2VesWIF9tprr676XtsYWYQZ8ElzCOciLJHmoaCdA52USj7gEGeVyINVFANDjjV5ti+pZgRBrLRN7sQLKKcEoQklqTuSECoNKOUSQpBykhNSkWYqone443UjKXgxed1YwFa+QkAjB2UEIQQ4kxADanw2LrNzEzXLakwEAS70zKQ9lnNYj2MVLaN4ZgAJUJMhIatJczPXyVa4ILtGDoMIUXYThRjNs3DkC91cE1VkMnwYc1HSC2uy7EY5MfuxhGw0IWo1HWe7BrnJKHBfDbJe1FeRS6SSfDCra7t0V+fqz2FsZ+Mo2O4BoA1SetaNH57Tn0vSTJGTTS8qd4iVVaEFKS1xAy7KS4SX4v2XiHtkbFGZhrtvOLZYFAuP/AJtpRcA4KZmdt5bWUTQnzfESFKSKjlESeogZFz+ELRFwXbTPrsnrBVJ1qTXHRvrL85tg8nhylRcckJIr50qss6RY7ePC7qbDBJSaodDwUDGyHsZYoAgGoCsqXuuzNQ9DdCkmaH8hpxrj3QHrbTOxbVC9uGIh2CoANbt3Nvf34/f/OY32HvvvbHNNttg6tSpuOuuu7DLLrsAAAYGBnD//ffj4osvBgDsuuuuqNfruOuuuzB37lwAwPPPP49HH30Ul1xyyaDHsTYwYggzu4lLDGkOE3Z0g3ZWZoNWZJkZgAS0Exs188KJmwiQQme7I/9B2hBoQP34rENc0KfjVAcQZI8iyCRYWZaF1Jn2NFHXIXXYdQgLSJEdhxNqTDkR6s+5VJNDQxPmuoDIleaKpJqsTBZAl/wTq2UfYgDESsssYa3NJrkJpLFEkw3+AYhK0qy8OZxoDzqkn0uaVRPeDK/LTDuZnphlYW2ugt3XSWvtWperCHes3F2pMKEBzbnPMiDLdAJEAarXgVF9yMf1Iu/LVPIbqAlaNPQDUpPBUlvsZV48/MRCxIWfQy209cYfCmFOGuaNHWzmH0Zl+MNK3XJY3uJSq6pb1XZ0nBGCHdMhe31adhbvp0TCXQJc1VeESHtE2RJqx5JsnewCwqpvEjZMmogQxsjUVxT484AIHPFca3NIihH5XEyPofVakTJBbMmZKLHI+GfJJlJG9dTsHlcmfCOF1OejFG0jGLsh1ep2rbMAkoraxDVG3qdWU6kJiCZB9gBoQKWxNqdKkHLA17yZJEPkkbmUiu+eQP4DWbgSOQgM59x75pln4pBDDsHrX/96rFixAhdccAFeeuklHHPMMSAizJs3DwsWLMB2222H7bbbDgsWLMDo0aPxwQ9+EAAwfvx4HH/88TjjjDMwceJETJgwAWeeeSZmz55to2asL4wYwkwl+UVEnlERPq4jGEe+cP+wTaI4QdcWUJI6u1qDIBoCkkiRUkGFLEM/aKolKU2ec+j+UZo1zA2LBRVh2wTAQpFZxeMUmUazvFDDFT9Qyll5C0v93sR1ZgY1JSByUCMrshOZx39L4vXp0REyzM2HBemsSNoz2lqbFdE3/maA8jlrSZrrziVuwjNbeUZwpOH35M7AQhFnNnHu2qQ+akmW3Qcat6xKAmNCwhkrszmuXD1gKYsxwD11NMbU0BwtbEi/bICR9UuIAYGsIVXWqJyQ5QxuSp80hyieSPzreIjxl23zycK80UPFjIdPJKtIZbidgm2xeuxvayujCOFsa9VXdFtsnBS3WLeMl+yO383EZ+o5jn9VJNmPiOEQWcEl6YQ1v1SQw8LGE5BrQ8YduKTW7CssOW5hzY7A3D4z+FNMq1uyjrjmW6ojfcac+ZgJzIRMqLCuUq/WunBJvCXOOUFkxsqsSXPGkD2MvJfsvYxyUnaNBkBNsrGYBQFosv1MNtqTMzZzjzZWZe+pZsO2MD/33HM48sgj8de//hWbb7459thjDzz44IPYaqutAABnnXUWVq9ejVNOOQUrV67E7rvvjjvvvNPGYAaAL3/5y6jVapg7dy5Wr16N/fbbD4sWLVqvMZiBEUSYExISNiykxCUJCQkJ6x7DOfcuXry45XYiwvz580vRNVz09fVh4cKFWLhwYcf9rgusV8I8f/58nHfeeV6ZGzqEmXHeeefh6quvtk8iV1xxBWbOnNl9Z0RoGTN2bViZDcLEJ25ZtL6WZQg4MY2boEYGQQQJHaOZCh2zcXgwBgW1vFNYbtUx6zomG5IxzTpWGGl101JnOdIW3MiSfGn5nZRFmXICIwdBeFZm5DlEI9eh7QDqgdUCl8YpneNgFA4TpKwuIoe2jKunbZPYRFBh3AdUuDgCgEyZsbkmQJwVYzIwVuZQnxtz2JTSWpspy1TCkGBZLyrviTn6he+LGErx1QeRaX1yBs70dwUAPbnWxTHk6tXAmNGqPCPkvYRmn8pE1ewjZAOE2hqGHBAQTYYYUJZmAW2dDmMy23NQsc65lizNycI8AkCR33qsjmuVNS8u129ljbZ1hF9WedlUTcdt+ojJNEqaZLcd16rsWsBF+Lty93HkF+2syro+edplp57Z7liPvW5jIdfIJIVS/6ml1VhZlQudsCovSyrKfboWbAGuJGYikjbF1GUmfftmaxGO9WM+F9ZoduQc7CymFWMQKLZJpw1y22Lt98NKv0w9ajFT5MqPKG+Qmneb6j8AZPo+DntfZ//+aqzLDlS2X6HdlzZcC/PGjPVuYR5qCsWO0SppRIgwWkZIfk17QGv9ctCefS9RJkaAJl160gFADZ09r+hUbXWJltdPQJrdOcaZvNmMvwYd5xhQDnQEElK1ExLMiAMgpH6RlgQgV7KLnNWxSNgEKSptNvnewc4NiIyznzldmjQLgspCpyd75ZCoJh+Qk2ND/7eTHZOK/CEEuMYgaa4rJ2220TMHx1iSTpjsemYfLc9wZRkugY5GxTDXkduX+x0ashw+2GVCTZI1tb9J0EKyR+0mCDQwoOrWM6Xv1teBaBRLqXkPQdbVsmDWT6CmekCkXConzdgaaPgwEb5nVg8mg0SatDd+cAZPzlVJRuHItEIS7NYxPxcO2ooR5qA8OobwvUPSq8ZalphwUR4eg9nPIa5lXTP79dy6DmGukl5QiSwXbRKxrzsOSXpwGix5NT4KXBBiBHXIK1Pa4JDYtrrlmjYNyfXJrNtGeczMzr1EywwF2E5H7vTK7B83G+0zCFnQp6tn9iJr6AvOxD9W2wBRk8gbQhl1mKy8kFjZwFBXv4GclUNg1oB1hBUZIBr6vmUMWWqAzsEr+QUTVOQroa/9Icy75jjT3Ns91jthHkoKxa5QpRHtBCHhjbXTCSFvZ2U2RMk4zzWbIGZNBs2vSCjOXaeC/BpUNe1EnmBjlma1g0kKIkmTL51a2uirWonJ2Fi+IYCaItmqL2cfCa1Hhh/lg/TNFEUZu3OGJn3G+U+6OmbWWmypJ5vMiZ7B+qQYC3OmM+jVdNs2VSkrImxSgseIbYzguvtkZM+PiagRPVet2gz3Mdn6zOdMgIUmzVa/TADXVZ1MgBpNsM7UmPcIyBrZ800M6zgKZsgaIe8hgGuov0LI1uTaUk9+xA5p7snFuamMljJIpEl744eNkhF8dSWdL/w6rYg1zM8u0mZlO1Xb7FzYYj+3L5cch2OKEN7Ssbgk2e2jRaY+cjXMDkkuyDK8aBVVmmOC/xnBZ2sfELJSaxxaj13rcCaCsogDX2gBBoCaawWOEHO3vmlPEWbS+wAZyvuFYzAEmPW8k8HP9mdiB7mWZHb2NWW5nutNCm2qSyAncJPBTVI2GXObNbd0Acg6kOeEWo0ga6z8SzLWFh/L/r2EJyxIhYoVKuqGWY0dqv9zmnsHh/VOmIeSQjGG/v5+9PcXKXdMKkfKMhA5lsJO4VlUHStzVYrscB+D0I3XWJlDEl3oC0BNqZzLBwDmTBNLBtcFLHHOYK2OAErLkaoQhae6lnUwWKWn1jGODalWzRSOeu75cm9wxNCRJvQk1wRQY22ZVlEpjJXaWqtZpwAlsjcO1hZRQ5BZj9f0ZSzPxX+1fCXMgmGmYlar5So1waibCanPWQYg10tmQnXYBGzq53axlaMPR+YacLMFVuwbkuXQQmvr6YP1nARJkeWMPEdGZgD1TFnQmzX7PTGr70zqCRZQFg1AP2hIQOonk4Fx6mGiLhRpBinST03zMKCtHnlxPboPjWziMK8lB8CE1zaq5t1WhFk/s0cJa/i5EymGVzfY3pJMexZp/3qucvaLEnHXehzsU8qw5/ZprLkxK7HSx3nk1xBo9Xwt9XThEGi3e/JjIoeyhVbW4jCahoBfJ7Q6C+JSBIp6ILOolyzQjoU3JPymXzLSCYdsE9BswRrd48zgE22QdkA3n812Vn1nmhQbqUYRh7k4Dnbqi5qErAnIPllEsWBCtqZ8eTZHKdlGrU6Qa7TVmJSzujEo6W/ErrKyKAgzOfwgYd1jvZ56k0Lxhz/8Ib7+9a9j+fLl2GuvvfDCCy+0TKHYKj3iRRddhPHjx9tXmMoxISFhw4CxcnTzStgwkebdhITXDtLcOzisVwvzcKRQPOecc3D66afbzy+99JKavLMMcC3MMavi2khUEi7Fx8oNQkdDNz604wDIEsqqKiWIa5BSJaOQUlsfhba2Cv9Jvehb/VMWZf2g7DzVM6snbhawqhASUE/hrPqGtv6apXjWT8NGeqWc65TVGrl2GDHH7MgDTJmxLkMoIzUAT/9l2leSAue/gM4cqBrhTFk7WUBZRaV6ajfWeBKAkmboPqy127ESGytz+H0V64/2OOw2NyRc7FpqZ102ZaZ9T8PsvM9UO0qWAW8clJOyoNeE+n6yDPVX1Mb+8ULLdhiiQaitVtbnTBLyXnXOBzYhMGWo1wi1VwAxIJUDSmg5N9dEXliU7XnsMvGhC0Z33tfJlr3homre9RKXAFHLcNRQ2MFlEbMal9pzrcGlfjla7vlWcKQf+7+cec+Oy9UlA4XznmnUs1IXFuMiAUloTY5blW18ZfjWYtcCHFqRjfy1KvybK6+whxbIHMJyQQwBtpZmF24gsFaOgG4dV8oRxme2fXO15tmEiyv2E15oOKtdNu3DTGc6gRYpy7hrZbbZZ1XnjkwDoJ4crB3ymplaGcz6CbVXoe5jubIsGylic5SyGKv7kgA3uCTHAFFxnwSsj4+VNw4Bae4dHNa7JMNFtykUY+jt7Y3mNyeRgUQGkwq5Yz3zYOMdho5jdiDB51ak2TgAetn0AJFn4DoDkkGZIs3SpObUxNddBnVXvNidvWwXZB3tQIDsgYpQkZsfsRqfkkyQJdBWN0yaiLMizcjIlz6zXWcqvIFJ9+U4Bbkk2RJnqZ5zoPks5VrLxaz0y9JZ9nWWsGAItSbDljhr3RnceI6dygoExQliTNYRI8vhteRqvUmUyDJnzv+siFKidONZMYOaejWBrD+3y4KNMUBjtM72mCtpj8k4ZcaW95K+3jKVOr2pTqKdkPW5EQ2p7/WaJDOrB6NuU4V7h590dBsLquZdpc8tPlaR3BAd1aN4Pa+slcTCddCrMjLEdMix/gFLfIu+g/5Jk3Sr9Q320/W9uMmiIMVCx1QmUURpCOUWVRILlxwrYqtPQQVpdqUVMZJr5BluvZomqGa7BJU0y2Y/Q0wNaTPv7X9i1PT8Zn73Zjug5Bi2PEKuTXnRdxFUPtQoKyIM5cvBzvlg8lSULgj6vkfQfkAAMgnuA3hAIIdEc7SSUdbW6KnaXFO1os2Gnsaph5x7n3PDhnLetvdEPffSEAwV5hykubd7bFCEudsUil1BRxsgCBTsUMGS6Ag6ioLRCalu5exVDKQgzYB2s7XCYk8TzDmB8gxcy1TUhpoA19RTrKt7YlHM4TF9nfG6LULTqUmCGKCsIMrEBNYZimB+/Po96X05E0rzmmUgHbZNpfYu+gj7hx6jMbzAVHOJs3YatElKzMOAJoYs2CY7YW1lhqPPtg6AUupjEv4smBdh46Lfh/udKa+Q4rN1Iw+szTGyHOqXRdC2U9+knbYOf2Z//cBBgH4YgB0XCwEwIJqM2qu5Ir65QHMUoTGKkNWgnDr1jV7kxTXQHKUs0qLhT8ZiQIJyCRYEofXNijTrpCd5IswJ1ShZmNHCYhvu627neN1yWxGCW9GPp62uIsax/lzrMTt1RLDNG58mYqZOQOpdfbK95VAR4SIkykKwJchuuLhWVmMA6Kn5MSRjjnXGUuztX/G5pgmzgBpPjFy7xDXmwNcOpg+3vmD2iHQsO2DpvYR1ErRjACxpZmLkbh+OVbtwbgRYSLW6q0Gk5nLWNy6qq/myMY7AmYDsgQqrau5PBGtxFgAam5C9j7oQA2ouJ0kQ/SojoMoMCHA+NJtvmnsHh/VKmIeaQrEr1GpQpkoNE+kAKEh0K3RikXYjLXS6TzuybeQZUmkpCNrqKvWPrKmt0DUJrgtNnAky0w5xoljWMU/F4dhsmYlyYTPtoSCsrCd7CZWJUBrTMqzFklkCNaGsjly2urpEjA1vFcUkwnAmDS6eazhTE4zhqopgqwgfxVM+rONi8d+QTygHOV2JMwZZSYa2+HQ6IZBh7SjIquvQGcvcF4ugEhJ0V5YBwKa90seqyDMAkJXVEAATK5nNvqzkOoKAWj+DWFlW8l5lbTZkOeuHzjalD0Go5cHckfUwAT2SlUOKZBsiEHmurrtmXjzcDQJp0t74Ucr0R61JaZUlt1zmGDwiBLxKhlEpp3C2hVKJ8r4V4zH9uvIJd6zeeXCILWmiTChHuyBYmYMrtRC6nikPHfKAMnkWxKiL3KlXJpdVxDj8bKy/LnEOLcYASp/NPrJEXMmrE4N05lB37nDbis0RTS3HMJZk4U27DElk5Rq1TDn8CWZroHGlGUQMyRmsc6X5IyQEBMxiMAHgPokmqVU8lTK7SJ1NJmGsNnKFh54NKJItmtrCnLMizw2TITAR5vWB9UqY10YKxYSEhNcm0qSdkJCQsO6R5t7BYb0S5rWRQrFjCAKE4/TnLqkbuBbR0OJc5czXCaKhySIWxyq4oWRyqa272iouBQQRKBfgJheW5kxpX5W1mQpnOL0MqeIxU2CJcayLQksxtEMdSeVsqawZOuu9NI/S2nIpCWRCoZF2zhTOMdh+UEgxMqNj5kKWYZ0NYcPNAdqy7limjcXGtzKreM3KUs46RrM+ViEAbV228aIzUR5fbLUhlGcYSUXMyuxdK877krxHRstLGRVhjpf0+0LTVpJ5QIcekgA1JDIIsI7LJzMgHwXkdVhrNQYYmRsjG4CsEWTdtfazTkYDZWU21uVc+uetSzBT1GmnVf2E1xj0bxxA3Lqsy6u8mCq/cue375V5//02Y3Vdi7Dbrt3f6kl9qUWpzVaSi6K258RXOFhXh4YzVs1M+PILkyQkZk12tcyuppiICwlFlUUZvqzCWGbdMleGYdoQgag2dNKLxWR2ERIyyaLUpikHtAyDyhrpaHtSWZnNGEKyqJPHKkc/Lpz7jJXZDTNnYLP/6VVXQOc0UFFM9b2NwaNyUF1A5gDlBDGgXpxBr9wBNjeBvm+JAXUJefI4IgBcyBYH61ulkebewWGD0jAPK2q1gpgwxwlSiXy0QKht7RTtnABbaaYD3a2NbEG5IvtZhkwHUKcagesC3CRFnmvk6ZuRoVhGDKJraNqlpBLC/GjJbmFmtR3FPYUk62V91R8kqYQmZl3SI44+WeZMR9cwfNM6lgGQ5eyA9r/RPmsdM8lCpqHqUbFdL3tCKuJMmfPQIaggvyHhBQrHzPB7iz18GSmGK6+oukbMd12VQtvVTZOOhqLPvX1QMLp2QDlkSh2T2qQVz1nFYl5tYlWr66A5GrBxq/XkLHKzTK36ZqiYzkI7UZIlzlwc+xAmbgnqylO7m7oJGwbYxomHmT7QUk6B+OdKoh3JXNdSalFFjhFss+1wsc3sw/5+nvOe0Pt424t9DSkWmU+SQ4e90IlPCPYy6VnSHJFdFHV8kmuIb5XeuBMSLQIphrs9JL22P5KQLAp5hlNWnCRvV8gKqZfU/SrSWzjouH1LEGokPafDGqQ3f9SERFMWJJpYEXDDf409wRht3KgZmZBFnGYAJtWs61ICCaCm72NCKuWaJOR1guzVxLlfSTQyHb7cHAILRcTzPj0AIhtHX13DNBQlnD1Hae7tHiOHMGcZIBz3VMmF/tKzMrNf1mkEhdCq2MryVpnwRHRWzx4DQJBKU8z61yoVqRJSgDWJpUxoJ0FFnFkAnKNwDMzY/hABbakl575Gxkqk7hbqadP5AbMea6aszEykrcvGil3oqEvWU6HJcuZoCjVRVsenA8dr6R0TCuu0cfgzlmfNzf0bIhUWWW1lJs4Vcc6o0DIba7hrMW71HZlOjbDatBF+d0qY6Je510ZIqmPk2hB5h8hCW841fS6GZxwy9aqEyLWzpGBk/eoBRfSq0HJ5j2pbNIFsjd7fWPbNuasrxxVzTkhK9XAWO+YukZYFN36wYHAW/JYCktwya5lLRgE7MbWyPPuW5Ii11yHOpbpOPYptqzwOY2EOyLFTl3S/YbSLLPOJr+vE51qSTR2TiS+0HhvUgggXrt5YaCtzqCl24Vp2XQLuO9FJZMRoyMwh0b5lOHP2jYZ18PqRnvUYgOeAZyBNdAwCBOVOOdn9bZ96yqwJWViWHcu0KXcfFCSKkHNS3wiJgAwSRGSJsooOIsCswruqIbFPmiELp3fj/6Mf8nJSq5w8QMq5L4e1MkMAslfl16KciigZzn0jpcZePxg5hLmWKUkGoKUE+jnSJdBA8SMOyzshzi75iV3Q3YQvq4K79A8oUplz4W7BahsJBrOKrsBSRdUAZ+CcbbpNmWmrcA5LLE3GvCgMiTJLh8442YYrU+M3pJkz5+VE7nBfyFi/N8dUPFmbSBxGdmEty16kjDhZ9hwcbR12iLNjEc4yIHc8C6tkFfZcCHiP+TGLc4wsl9qJ9BOcfzIh/UQxXkuaJWyc7uLLUN8F5eqhgiQgmoowc0aQPUBjdHGe7DnTZNlcY0xQIfzcdt2xGn3MIJGWBTd+cAZ4oSyBEnF1H87bfcWWfLclsO5/h2i4l6uVQARlsTbU3k5h2WoMwJNawCPBRT0juTCOe7Us9wixyTaniFkR29j89x38Cmtx6JAH+CTZ3VYTeSnEm7uP+q9IsQs3/BsA9Iqmv78lz8VDQN0jturk5PqEZSj6crep2MjFl2W2N+BPpU2Z2TB0gBt3uSDwzXBCZUOOSY9Jj4UkBAhNFlZyAW1NJlLGIKGvVxPnWc1JEtCk2bM0M0AmT4C+QRHpLKmSQf2KLNdfUadN1oDGGIBrsAYiOaB+P7IO5L3CruTm+dDmwjT3Dg6Dv9slJCQkJCQkJCQkjACMGMLM9Uy9akLFLq5l6lEw0/9rmXIAq9V0mX5lIq4xLXXAcWs0ieJl2qRIezHtslsvto/pS4cSQ1MWob+aEtTIQQ0JYV4DObIBiawhIQYksn5G1i+RDbCuw+rVLBwS3NByJnteYWku5BvmHFnJhc52xEJo6zKK5CqhlZm05SiDknU4FufQkgxtdHY1zK4O0huPU2bhhGuDtoAX36/WXBtNM9x2KqzMrlbZrdfOQu32EX6vrizEyDFMKCHXik1kdclWh24z8envLVfXBjWVRlkMMLJ+Vw+n6+nskf4x6H/m+nKv8Xa/hw4w3OlZm80mPvvZz2KbbbbBqFGjsO222+L888+HdJx7mRnz58/HtGnTMGrUKMyZMwePPfaY105/fz9OPfVUTJo0CWPGjMGhhx6K5557bkjHPmKQsV1mRsZqNcm8nN93bOWJ3br6BcG6HZRfbh81vU9N6v/qBcGgTL9q6j/clwheWqNEQtokIiSkbUNk+r1giJpUr0y9skwiq6mXyKSNnZwJiXott69aJlEXOXoy9aoLiUxI9NRy9NSaqGc56kK9MlLb6lmO3lrT7tMjnFfmv/qyJmok0Zc10COa9n9N5KiJ3L7vzZrozZqoixy9oole0VTbKC9eTn3zGiUa9n2vaGJUNmD3H501UBcSvaKp/mdNW2901rCfBXHRP+Wok/T6UFZytV+dJOra+l0TOWqkJCY9+r37EnqblaI4/8NyY8U3ofdCx0lXLmNlNeQ4ZAL2GhEmnjYVZUbjTvra4kwXNdRPJe/RlmT9X9aUtdn4HckaIe8RyHsJsmfDnns3VowYSQbXM7DIlISBWckQ3KXskPCapagcqqJO4lHSuIbL8GHmPgOPNGXVGucqEhU9KN2H1qsSoI6Lc5AQYGi9Lgsg0+k/tUMeaQc9JnJkGqqqDbEs/SgadnXOJc5OEQFWX0w59I3SkGXtdJg5E0FNjZuz4j/ZhlDoLIhL56LkLGS0ylpeAvj72AQtjiNgQToFiKRewzNiMy4TXRJ+WfgdWic9KurH0ImjnHv9mGQhZmXTeTAgFA6PZpnYyjfMg47ZraGWePMGqUnatKOvhbxXXUTNPk3EGSpYvnkAKxFq6uxYKg9xeJcFL774Ylx11VW47rrrMHPmTDzyyCM49thjMX78eHz84x8HAFxyySX40pe+hEWLFmHGjBm44IILsP/+++Pxxx+34SvnzZuHJUuWYPHixZg4cSLOOOMMHHzwwVi2bBmyLNQbJLiwD8OumgHu7zcigeDgM8p1S9pjU+DKLMK2Q5Q0y760grlIpRy2Ydp3M+21inJh6pgYyplgZOTHUvay5hkdsOPYBziOdIHjnvc+cNLz6xf64hrlnuZYEHsSCVMWc+YzbRidca/t25eDZF5q1Bw5BGoErzwP5kkhJBqceeTEaJQzYuRkol1kqJO0joBmLEaK4UX4YO0M6OiWm1LY6zIWGcSL3Qxz+3cyCYKc27/+jqEpgoCKgS+FDmaktquw+ASuMWRdQtYzNDZR98XGGED2qGtIgmwwLptzwDjG6zl7KEiSjMFh5BDmmgBnmQ2NBdJOU9pCa8iwiToAwCHQmpRC+k5eoW7UQP8oVJkK6VWKtJAJfx8XIVHuxJLnkmapfrakx85SRdRQ4xQ67BoXxJl0RAzJBbEWOkwO+fciq3MF4mRaj9dNtsE6TJkJVybrsNpGlSoW1qLDgBoXlIaPjHOfQxJjWsVCw1wQx3YInROt5dklzZ2ef4OQLHc6sZmHMWMB12XESvOGvLgJqyQ0wQOEUA84dsVBE2iTxMUMhU0AfCZIbSCXdWBgE0LWIH1eYHWl1GBQQ+pkNM75MCsKsuKhoKND7s5y0e2k/cADD+Cwww7DP/3TPwEAtt56a3zjG9/AI488ottjXHbZZfjMZz6Dww8/HABw3XXXYcqUKbjppptw8sknY9WqVbjmmmtw/fXX453vfCcA4IYbbsD06dNx991348ADD+xqTCMNxpIMIPq7tXAnkJBUu3XcOcckHDITk7u/rVcmvBS0Y8ug5xs7HcjydvI/hwTZ6JIBRwvslAGKBBsrsqtLdvXINrpDxEHPe0Uc8mraQirA9n3m1ZUFOdZWWNNGWbMsIUnY9942YtT0cdUDBzw3QYoZiwShjnh57qS6Bgn0UtN+lnoh3Dj5CSZbptow/12nQeOjZMh/QY5BBSk24y2FwYMhrrAXorpVsParN2XmuiD9kAUVvQrKCi2NA46dUPXzoF4VyUdL9JOwRiNZV3N3tlqv8uaakxBsaFH1EIohYbjn3o0VI4Ywy7rQFmY1yRLJgiwboizYLyOHPAsg+K0rxOI1W/JTQZpbRURw2wnrhNbNim2WZOm02kQqxBsZwm+tzPqHR4pAcUaFEV0rR1g41KzqWKPj17sI0tZlRZZzTZhlvVg2hVA3VeNhzoCaYLTkwjj7uc5pdkguQSa3PG5YYqLiRmtvuJoAmknBJc32eERxzAamHudxWQZQflCKIYzxHGwjAJBSf4f6cI31wQwrdEJ3SLP9LliHJ8pVfdIyGeoB1J2f7QNR4Sho4i7rDnTEDCu9GYKoi1F9+VTVB4CXXnrJK+/t7UVvb2+p/j/8wz/gqquuwhNPPIEZM2bgf//3f/HjH/8Yl112GQDg6aefxvLly3HAAQd4be2zzz5YunQpTj75ZCxbtgyNRsOrM23aNMyaNQtLly5NhLkdjHwCgA0B51iQS5ZiAKj4KUUz79mVroBMB4Q2tBZHp15LcCPkmJw2zeF4S/WFpdhIL8w2NxQcACupEGDPghySYKAIB2e3R2Ifm3ITTk2VKdmCeW8IchgWzhBkoR3m6pR78ZIVmWwicyaYnIX3GfAJcwxu5A3Xqi21/kZQDkmKOAuoMRh/49zevdzJRqKOwnlQ9ZFrZ0FFnqW2gDdz058okcQqC7oEbHxm4/in7gjkWaWlXhJxrc42RjMIQrC2YehJm7iwxfTm6mHEsUjZWM0NIFutohdl/SjCtuoVXDlE/jrYuXekY8QQ5oSEhA0LElSylLerDwDTp0/3ys8999xocqOzzz4bq1atwg477IAsy5DnOS688EIceeSRAIDly5cDAKZMmeLtN2XKFDzzzDO2Tk9PDzbbbLNSHbN/QkJCwmsJg517RzpGDGHmmoAUKsQWcgA1UViCMxSyDOPgpK3NBOiMZrIIPRZ73pI6noxrLcy5WObnXK9/i8Iq14ml2W3PtVZ2s9QPgKRUWl1jqRSsNc5KhuEYfYqlfaPbBhD+XkI5BsUeQbXl1pNi1AGuaSuz4+RnHCQA6JB4ehyRvkuH6FiTC21vxXhayWAcKYQeiF+nVWi4mHwjZnVu91hvkpBIgpeUQcdANt8dWIfuC5tj/wPlWsKhww+iTraecZqUGaz0RejwgCSBbAAQjRyUK+sRC+faNRiCqWOwOrpnn30W48aNs+Ux6zIAfPOb38QNN9yAm266CTNnzsQvfvELzJs3D9OmTcMxxxxj61Goj2culZXH0r5OAqzjXZVV1xa51uXoaY38bgg2c54tCmUbdgopJqlQXuE1GVim7ZAcLbJBmH1PSRp8SYbrOObKL+pZHtUdl7LqGQ1yYBmukR9DuO7IMAAlywgtynXKPYuqqzE2YzdWb0Bbkr2Yzr5V2ViKM+e7CROSmM+ehdkZFyhHgzOlT3bGL0MnaB3GU0IUVnHKlTyDhbU0F+dOAizQ4Mwvg6iUY7hymCqrcyHPUKsWxsosdIg5UVTREkHYVTupw89RxkqTLNV9l/sFKNervlJZlLPVQG0NUOtnZANqrHkvbMKvoUokkoZ5cBgxhFnWBJhEwe6M17/5bTtSDOU1pYgzZwwylaRexxZ6f1NmSFCeF7OwUewbEbCRDlgZgPGqqlp/dFBFmrs+CQCETj7BBECT6LyQQpibA4RboPfX/RpCynBSNLsRHADlXKijUMgeQt5D1gM479FSjLoEG091ckfg9EnBsm0Acgh9JVGOwMaJJocwCfIfcoBq58zSQFoNcmjfF6DIrjo+qcmyIQvmOyE/FjOgSDGRvo6DIUnnvDIgcrXsZ6KhiKbSOtvxu9rqVg8e3RweU6Gt77A+AIwbN84jzFX45Cc/iU996lP453/+ZwDA7Nmz8cwzz+Ciiy7CMcccg6lTpwJQVuQtttjC7rdixQprdZ46dSoGBgawcuVKz8q8YsUK7LXXXh2PfaSCaioaRfmHaX7rbP+pHfS/EvENrrdw2nS2h4TYDyxTbteTa+imhUMUXbkFM9ltngwDKlqC0SUDvq44c+IS14R0iHDguAefMPeIZqktEx9ZBIS4iiDbMWjZBQiepEJAk2VNfg3JNTILlwRbp0H9vcVIdBbsl1HutZGF8g3KIcHIQb5UA4q010XukWbVNhyJhtSyDmdfUuW9ognImk12olx9ihjM9txraY8nR0Ehy7COf7o+s2MrYIrYTNjObQzVhtE0sxTaFqN8dkgTZRYANdV70gaNvEe1zwLIewsn/CFn+hvk3DvSMXIIs06cAW1hVhp85yo3VlUjXdXEWWVTkwVptg0awi0UUXajZhCVybOdvUnrQPUVLyNWuxjBCp0KDVoRbvMr1/tbbbOTIIQC0gxWejYTCk4z6OKHSih0s5osq5Bj+rMZmyHLGSmS3AvkfYDsAWQvg3sYqDMok0V2LHuY1T9Oc7+zRH0twRJO9xzGImWEMJE1zAwWOvsZy7V9IGN/37BP3S/pMdlZ25Tl6jPpB7HCTyZ+MhQXcdoXxVMFcWSlQIcSFA1FmqnJ/hhdS7z5PEi4/rWd1u8Gr776KoTwf1xZltmwcttssw2mTp2Ku+66C7vssgsAYGBgAPfffz8uvvhiAMCuu+6Ker2Ou+66C3PnzgUAPP/883j00UdxySWXdDegEQjKJChT1jfSkVvUBmg/EoLI2PtuS7plRAgz3EvSZB9tTbTDK7WwJpcjWQBl0gwYsiqDMo468AF+SmqDGkmbSCQWwSJWBgD1wEEP8BN/1E2bkA7ZZTteY731yLJ+X6fca6vhtA0AdR37LINErm8qloBrZJDIKdAJe1OPr2O2ZZpUu5pkQ6BVXW0lZunomvWcq+fbumg6UTJyvWymWnL1y54DYEiQW5BCQYyGFEVdR8tsEph4LjAguA9j5vonJkB/T8zK+KaiO6lstqKhXtQ08zOBM4asafKsz+kQ85YM+9y7sWLEEGauq5SYlCuLoo0ra54C9cWssuYJa8lTM6jwSTOzdX4yETdsufnvPnKauK/m5p1LMzMrBmQszp0QZ7d9oCBggryr2j78ugTZXe7PYAk0aedA40zGggoCLXRWOWcslihby7KxTupYwdDEOiPIHoFmH6E5SpPmUZos9+agmo5h6j41y2D5h4v+ql4ueTYLCFGJSDvYKBlBeVW0DM+sEPF+i8k8XISrBYGzqN2SAyyVwyYJURBlQ5yBqBmeSX/3joOefeAx5w72vmJlGyoOtyLLZFddIsceOyddYLiXBQ855BBceOGFeP3rX4+ZM2fi5z//Ob70pS/huOOOA6DmgXnz5mHBggXYbrvtsN1222HBggUYPXo0PvjBDwIAxo8fj+OPPx5nnHEGJk6ciAkTJuDMM8/E7NmzbdSMhGqQiXsMRkiEC4ttjAyb31VFu8EPXBhrnbPNI8tBO65cImzTJc0uubSyC014MidEWWhBdqUWpj9vO1zLsoxk5yusyDbSRSB9cB33amTqSF9eEZDjMLOecg7MPfJrrLEhIS7OtaofOv6Z/nPnRuY6MJrtDRXmx8pBTDsNrqGuJRqAIvENAHXdjpFpGMfABjII5MYV2puDpTXZOufLLkH6pNkecwAz3wgwmiy0dZ6tY6EaS7FfJhh5eP8yXQTXYnELJy3HKKqoyFJKOcoCaI7SD4OGroiCUgwWSZIxOIwYwpyQkLBhYbgn7YULF+Jzn/scTjnlFKxYsQLTpk3DySefjM9//vO2zllnnYXVq1fjlFNOwcqVK7H77rvjzjvvtDGYAeDLX/4yarUa5s6di9WrV2O//fbDokWLUgzmhISE1yQSYR4cRgxhljWCFAQhVKIOZcQzT25cSDKgnwiNFY+0L6nRuwptopNc6JGF8LXMQHyp3TgG2s/6v9AfchSW5naWu3ANM9TaGtkEjJXZ2YdIaXXdpX29gsUcjF0/hasVMW31FE5/1roM3zIrVFaiZp9AczSQjwKaoxmyVwJ9OUQ911mxtEVaqpBCtk9G8dQtC7mAcUgzOq/Qulx5jmKfzXnSIexKYQN9U0BRFrZnrMQy+E5C67LksnTDbStcNSjiFxXfo7GCAVZa5H23zhi97x7a4myMMc65o9xolvVyoLNSAEA7hZYt6F7M8kFguHV0Y8eOxWWXXWbDyMVARJg/f340yoZBX18fFi5ciIULF3bVfwJs1jv/J8SIhnuDb1D2LcStrzPf1zZmYS5bm9167jgE/DBxgJ9AxDjGqXjDZWc9ZRUuSzHMNhVfOfc+x6QXbiIRP56yb43OID2nv4ykpz+OOeUJtZxkrbx1UklFlOUYqCOPWpBNH2os/nYTbq5OuZ3LM5TrKMlJXrJG19HUX1AhyahrfbNqK+gLwVyq51YJgbqQ6M8FMrBNsGISmLhWZgFGE8Juc53+XKlPjaQKe6dlGSZ0HACrZw63eQulgbOgvWXnpOQXWhDNmZJeMCmna6kP2sod11JYuaRhHhxGHGE23tpWaqvv+WSW4g1hlFpz5xIp8ysgKiQZQEGOuiEQ4TJ/TD/bybJ32GfoHBjIMAAopz+ikp4ZocFMoojIACeLnmQnXwDbpXxDoFgQmn0Z8j6BxiaEgXFAYxOGHCWB0TmynhxZLUeWSTuBSCLkzYIwkyQ1JknKKcLEDnZkGGTkIC5xDrXCZps5PS2+H89xLkaWY3BlGVV6ZzMe11PD0d+V6oaQUBFLYqoPG3Pba6Qg0Vmm6pBanmQqHjzsg4aE4/THdunPmyPdhzgTSSYhoQ1U+ugidTAQl0yoz+p/GMGgSjoBwCO6IWmuItlhXGSg0Ctn1qFPE1UqtMmm3ZAcu326Dn2qLMjU50k0CtkFAE96YbXFXva/QnZh2jAENZRb1B0y7EaBMElFeqhZGpNJKmKIsCHALkE35DNMcKLakV5cZ8B1zAManKnU3mZcYDinDxkV2mQJRXaNI6DRN0tWJBekiH3Oqr4vA1H7m4eDGuUQEGiYrTZKhrTtqSQs0kov3IgZuZOcycZYdrTPufPezf5n6ktpRSOKr1dclyovAZSeWT3PKGOGVpcwwc7bohltImGYMXIIc90nzMK5+KyTH2BJMTnk2EZSYNaJLzSbMKTZPGlnWdnSDHRGvELEyHKMkHWoZVJZDYO2w75cMEAwGmeXvJtoDeSTZe0EyZlQmf16BfrHCfSPJzQ3YchNcqBPkeV6PUe9lsOEZJJSoNFUbJ2lIvLGc9hMGsaybLS25uHGEmjJUVJtD9GQROd82EPVETNgjlPNiD4Zjp7UgFT77vh+me2sxbUQ60vX5dj1EDmWwunUHJeErNW8ZFNeRAKXPDO0Yyzb82HPTWxsQ7QwJ8eTjR+1TCLL8iiZbeXIBzj5TjqwNLtW4XKbqsyzIjv9u+TXbd8lTkVCEJ882zL9o+rJmiV9sj2eCMmOhX8zVmQJRfZCC3LRnrTkuB6Q6TrlAfHVRJgKK7Rqz+iIfSJsHPhKFmII9ARRMArHwaJepglsrsebM6GXChJtyLg7RuNIJ5GhTk0ommuiXkjknBXn08vY5DsAumTWRNAozr9EzdRxFkrtd62jZfRkuUqdjeL6EQwvHrFrgTb9lqd731LtMmd7rQuAhUrkBUkQA4oQU9MYMvz6NADI1RgSRtLc+9RTT+Haa6/FU089hcsvvxyTJ0/GHXfcgenTp2PmzJldtTViCDNnKlKGcjbRS9Me4dIXKADnGVWlJLaOeQQvOxyg5QmiiOVM5EfNsAPQ24wswyVUxtGrFdyoCy6yCjIzBKjVKYaixZo0Cy5IGxxrZM7urAPOCM3RGdZsJtC/KaF/M6A5volsdBO1nhx9PQ3UtGVZgNVEaeZAqVmdJKBJ2nOYCtIsiwnEkxQ4/4nhkWY7M7gOmd04TEQiWNjykCxXEeGSdbnLB6jQMbCKqAfv1SVeXDf23Ei2FguB4nnPpNFmE14PKGQX3ZD8DqGa7vw8vJYn7ZGKei1HrV5EbHBj4FKEQKpyv42QBLtE123PbAstqjFZhCvDqArvZt+32AYUluGaJbD+BBPKK0yZ24YJAecSVEFNS3yNBdnIFIDCEp1Bok8Y+2n5R9Ir+r3PWakfHUZOSCuTyPT9L9NWY5dMexZmyu1nzwGOpCa8OpwcCbtvnXLPGp0bZzxDjO1dWB2nhETO9dLxWwkfjKW3dOiOpdh30POPPXOkMhJNqci75wTp9VNcW2ZbbB5T1zHHt7mRoWpcRNho6le/sixTDuukLZoojEj9Q5sMR8rce//99+Nd73oX3v72t+N//ud/cOGFF2Ly5Mn45S9/if/4j//Ad77zna7aGzGEWWaaNMNYGdTFYkiE9ZY1vFio1JrCkEGSoCaUFdVEzMgN+WUl28gc8shcuLKG0TPcMjtAoKRldmUfnt4Z/l0lpqsNtnEnBM1EDWFWVDm2iyWmDGpIm7ITADgjDIzLMDBOYM1miiwPbCZRHzuA0aMG0Ftr2lilANDIM2VR0BMPSwLnVMSi1ETZapY1aTakryDG7JSp70BJC9jXPrf71QtoizoKK3OI2HmPEcqYVbb0WUJlbqkgpK6lOmwnbN+9xiras7pkckIGmm3mwcNpz6waeOMx+0MWEp1BIjmebPzoyXLUssI5IGYtriLEIVyyGtM/uwTYEJl6EIHDjWBh27WSiEA+ESHHrsTC1R+7Id/qJJGDPImEG9GiEw2yscD2iobXThbZ18oyIpaAGDkOrcYA0GP7V8S8Tk0vBbZrPa4HP0NhHWZCvwxFfuvUVNRZk3KgsEADQK7XEjITYs4h7YCxOCstszCyDGOt1jKP3NnPHAdIeCS5ThINLtJkGz1zTeQ6RXdcqxsLOSeducuN6Rwj5YB/vbIl2fo0EayGWTSUhVkljVL3Lgk9P2vCLHIGhijJGClz76c+9SlccMEFOP300z1H7n333ReXX3551+1FVJEJCQkJww8exCshISEhYWgYKXPvr371K7z3ve8tlW+++eZ44YUXum5vxFiYOSPImrYe5wQJLhz+cm2ZcExuklQZ5VobZaxpTamTSigrHklZ6F2bcNa3AyugGzgxTKNt6pgscwC8tMiuHMN90nNlITG00yqH0TiMVIVMhBCnHuA49mlrblPaffLeDAPja1izqcCaCUD/BKC5aQ4xbgCbjX0VvfUmaiStd3lDZsWyltYtQ+qYlMbK3KRiiUrruYS1MKOQ0jifrdaZofW56ku20gLpyAzczzGYaCCt5DKSy+e1Cq000aETqLEuC7MSEiSdqWrDXmasZEL6+yGprBLUZJWiPIN3/tyZ0VrvI9KVUkbBZGFOaIFMSNS1hdl1ngPgWYtduHXclMXuNl+nisr9iwj66r/vkFcej29hltbKHJZnnpW5kFyY9zUUmuWYsx4Ax3pbaIJVPbaOfH3UsPVDRz13/9Bq7Gqne7RswlhtTX/2HGvphGmvB0qHHdYzY3alEBJqfjHWXaVFLjTDmXEkRI7ckXcU8Y91qmub9lpCguzxmKgaSqMMgJUdPYPOxIcgax9LSC0oyR3JRJF1kO3IXStzbDGxRhJNuMcKxJddCxRqOYbJAGhkGbFVEW9fc59rOPOy1Pc8BrIBZ15uxtvoFCNl7t10003x/PPPY5tttvHKf/7zn2PLLbfsur0RRJiVhlkFQId23NNLHYIhGgRm/etRewAgyHoGEhKCSF/FpGPIMEymKhgiCWhNhwBkDpsNUEcrqHScCj///+z9fbQlRXkvjn+quvc+Z868wQwwAzIR0EHlxYSLRiUuEXkxRowu15WsBUZFV0KCGiYwgS8QdVAcIveukQQFgxIhIpKVCDfmroQL3vASwuUnjhgVDd4oKuYyGTUwr+fs3V1Vvz+qnqqnqqv32WefOcBw9jNrz967urqquk/v6k9/6vM8j3AaUgJrGgmwTbLJUZSEhlzA7c+lA04/zZ3IjBA2dJirS+H0fFMu21sIHxeOV3cl6qkS/eUFpg+SmFkN9FYb6JU1uit6OGDpNFZOTvtg/bWR3plCaQuWtRHQSsJ4kByAspdlkDSDpXAWDhCHdxMkGvSai145ZzmwHJ3PlokkzehH2QBzf8dc+wwsR38vspZoGsI9mBkWvlBoA1Qa6EiXbtWB8OjcGh9ezj4MkT6d9Z8kdTFCRP3M2eZKXeyvNMcitsmyQlnIBuBt+8w1uAR0uaURNAa1xY3qh5TUsbSCg2outUgd9bjsgiwN+ca1yBwc8/Y7LswBd/iLP9t2JkXl97fjCE56wcGvzuqLOQiOHfKajnwWYhoXxcIeR4UCHago0oXtW3nJSd8UXmtsJyBEv1Pu1EfprAlI27E6XyGUvgwoIjkIHzePfhE5ACZAnkwKg8K48y6CAyCFltMuSYptqwjXjglSi2FCqqXZJg3TOfOy6PQQYUenrhYNCaLQzHfIExz7YCJcJHPv2WefjUsuuQR//dd/DSEEtNb453/+Z2zcuBHvete75tze4gHM0oFmEYAyYC8+WdsnXqMcSJOAKCgboPB6ZiEtuAYxfS52s5AGxjj3KuO0zVoEZy8fVox+jLNcfXw7eTJEgEkHIE3b2lIyuwdpy4rbOh78SBnAsqvv5xwWASPSszJGVi0pUS0rMbOqxMwqgZmDgN4qDXlgDyuWz2DFkhms7M5EjhS1llBaolYFKl2gVhJaSWglIGrpmGWn5SLQzF+RrjkAZ69nVibErKTTyEiF+cYObtWOpyaBhheKcKCZPgMxg53q2zUGAPLM0Og6kyKEkoMdhzQaquMimLBfPWnirEOJ/TtLZctIBw7DQhPyY+epjkexObIcs7E7Y3vu2WRZoyyLCPgGZzndYIpTR70UrHBdcQpuKd2y1aQ2rxXOFnMwHIPMGBhz5piPE4gBMhBArnfK8/sEQEzfc7pkioXcFbUHr8Qee1ArtI9SYfeJxazS7c+PJWWFCRRT6ukOWFpsD8i1XaRKNM/EIBesbW/GPlFn4ze7P0cBNhamMaZj5BE0ouMSxmcALBxyVO47j1xBdSlqRpTO2ghwkK3Isc802yBrXH8wUbj+cEsXUd0YQA++5VDYVKnC/U5WRF641WwEgsh22N7eULZI5t6Pf/zjeM973oMXvOAFMMbgmGOOgVIKZ599Nv74j/94zu0tHsAsLGCmpWj6zUplQSLlc9elvXAFXbyGwLKxYK4I0SGMlhBa29iJ3MFP2nKbJ9NJL5QK24cFz2lEBjLB1pB8SmzXv5aDJQRp+65tC4gc416bWMKQhsoTArpbon9gF3sPKtA7UGD6YKA6qMLkgTM4cOk0lnT6OGBiBlNlH31lL7O9dQdKS1S6QOVCydV1AVVJmFrayBi1gKzck3YNiIrJMVInQMMZZ+4EiFh2kTvPs0XLyJ3z9PQNAMwCsE6bKj13CQsy7N8KaDC8vsn0GLWBKaVlf7WGD4koBXRpVxLo95A1RQyzjs5hVooxL0nG3J5d9ldP7cVsHamxpKz89zIBkdqEuLhcRjAIMPvPDYe8CjnjwHiQcx6NKxddg6JYpAA/l4qaADGPbJFjj3lq6DTUG4FiYo+JLY4c+BI23kbUYP2xujnWWSYg2o4tnFN+XhQDlDzGcsRAC40CyDO9UNBwshAPWgEIiQIKfQB9XUAyyQjVB7gEx0krYKCZLMOOMZZl0HFoQyB7MFsshfGrn7xP+myMiIB1Pp12Xr7QWkY5BpSwILkPFA4se4ncvmSWo3HOrf7+aJ1OB1/84hfx0Y9+FI888gi01jjhhBOwfv36kdpbNIB5bGMb23PLFouObmxjG9vYnku22ObeF73oRXjRi14073YWDWA2EnYpWji22UWDM0QCF/SkZ6C1gFRwzLGTaGgBFCYsVTuNsTAysM2OWRa1dg5ajGkmxlK7x0XGBtoBDvkI1xp+jEkyBHt5XTJbLmIOZMIYn2JZwDQc4qg+4DSrnQKmlFBLS+xeW2LmYGDmYANzUA8HHrAXB0xO48DJaUwWFUqhUUqFvip96LhKF5ipS/Sr0jLMVQFdFzCVROHYZVkhvJjTnw3kzkLIKc4owzP3wjOi8fizp3PgWln7JNHKLvtkhSKEXfP6X9bXMMwy/Q0K0qpnhpiyy8ZYZluGsYSVCqtf1iWgu06i1HfXv4Q/n5bRMF67Hnc4hJZ6WDNibkt9+/mkvRhtquxjooilEDpiIK18gnTAqemErexIlcg7glRiEBtNlsuiR7KKaH/RZJGpnJuPfywoHFvqwGez1NF4uPyiI2rmcMd1z9rHP+6IOtqHjsEfYzIpFML21xE6Oh6FEB/al3smPHeedMi8B3gJQBE5ApKWmWQW4VhUcqIUZdRLmWaDyEkQAComkUjTZ9P5qUzhswBS+1x6Qswy1des3J4D259O5Bi566jNpHAOh2Y4nTM3krgJ5+Be9GFjL7t7XpSEy+80i7ZjLvYMzr1XXXUVLrvsMlxwwQW45pprbHPG4IorrsANN9yAp556Cq961avw6U9/Okok0uv1sHHjRnzpS1/C9PQ0Tj31VFx33XU4/PDDB/Z34YUXDj22LVu2zOlYFg1g1iVgJuDjz1KSBqsRcuC4thINC3RcfGEDyFq4JX8B1A5IFMYDCzgAJ6WwwLm0oJmAs8+UptwvwDBJhV+eYj+E2ZZeONgisMyd+3JgOY2IAVgAprXVOCfgODVTCJhuCd2RqJZ3MH1wid2/BPQPUpg4eC8OXrEbK7szOGhyDyZk7TzSFXq6RG0k+tpqlvt1gX5VoleVqPsFdCVhKgHh4k/KPtNwMcDswbIK70HHbCKZRkO/3BIdIxxcfMyNSBDpufDRSVoqUOzrAjZeN8J5ztXLd2JiTXNL3daoFUl9UxTQHQldCqgJQC2xl2ExbZ1hDY++4R08E4TurqV9FyVjcSwLLmabKvqYLMxAYBs5cLnvKYCudeHlEqmm2C/XyyDjSEFgLpXzhItAwR3TbN0wFg6AOXhPZRehLNY08zZCm8FJr4vKH0vXxVLm0TCshtl4mUYqIQnjifssYKDYb3PSyxaEk0EEIE/1c+354iTrn4KV0lBsYwK/aXspcM5phXnsYp9mmkW/8ONhKbBJkhFLRSwZ5R35oH2MZ99/S1/UjI/clIwzx7DyzH5SGCidXtf2u07KBW1T8X2vcBn+ZGX9SKI/iUB0T5uvM/szNfc+/PDDuOGGG/Dyl788Kr/66quxZcsW3HTTTTj66KNx5ZVX4vTTT8djjz3m4yVv2LABf/d3f4fbbrsNq1evxkUXXYQzzzwTW7duRVG06QltBIxhTIxw71o0gLleCoipAJgh4B3IjARM3+FQhzWNEI7NtGBCGOHrilI4J7jAbAoNmNI5CmppBftKQ1QuFhrTkgbgbOATwHKQnAPR3DwoyrDKtD3DLEea5QigJ9tZH0YImIkCppBQUyVmVnVs6LiDgOqFM1i1ag9WTk7jsKU7sbyc8U4v2kjsVl30dYm9dQfTdQfT/Q5mqk4MlmsJ0ZcuYLtllws3gaRgWQ5w+vPsso5Z8lnZ5SFnggajnEsgEzXeAppT8DsKY8uBt3agmW9L2jcdBpa7gO4Aqut27yCwZv7ayIyDg+Uxch3bkDZV9LGkbL+758LDpeBWGYEJiirBtLje0p8gY4d9AhMGWmkbZ4e1kZiQsQY6BcQEQHka6gZQdXrk8Dk4F6YMcjouAJHDHwfKaRSRAhyoNzXXdt8YXCuK0NHivOEd+RwQrYxkTLWOthEDDTA2mDLwQaMyZdRmzEvzUG3Sge+YTQhtBiCuUcTJSZjjH9+Htw3EqxT0mUfA0AgOezoB0WmUCzLDwDJ3+ONSB9IzR/vBMstaC6CSkH0RkpSo8B45+Dnz97p9AJifCdu9ezfOOeccfPazn8WVV17py40xuOaaa3D55Zfj7W9/OwDg5ptvxpo1a3DrrbfivPPOw44dO3DjjTfiC1/4Ak477TQAwC233IJ169bhq1/9Kt74xje29nvPPfcs2DEtHsA8BYilNiUwOU9JF42BLsAUCxgjoAubSpukGT5+reISB0Aog6IS1mFKGxhlIGoJWUiIWrmYxcoCZ6Dp+EezTxuIzlkaEcMznyIGTXwuig8wfM6wmaaUVn4x1UG1vMTMAQWmD7LRMPqHVHjhof+JFyzdgaVlH0tk5VmhWheY1h3MqA721l3s7k9g2gHlqi6gqgK6DmBZ1AKiBSzbCcQER0wuyaB302SXBZ9UMuyySM/DMIxyavzhIj2X9DIsMyQAH497Nqe5ZMVBCJMfB62Y5kILwv4NdUdCTZbQXWkd/tx17FcVyIGSpEbpqXBtNhwp57tEaNDsa7b6Y9uvbElRYSKzEtMW2ixnijnKpnUoQ17qaOazv3nZBQOxiXzC9hEc84jxJkBsmVQVAb3JxMGQwLH9bHxECz5mnmKaoltQODfeDmXas/0EtjnnkGfH3FRrSQF0kh9MYZpSibRtbiThsE6HMZNLANFHmnCmjXDyCx2cAWkbayPnGGjruFjMDghTvZwsQ7E61HY+tByXZNjPnNVuxHJmx0JlqQOgB9jsmDg4JidBY0Qgho3FGloLqH4B0ZMoZhzD7IByuHfx+5Mbp8s0DCTbR7ER596dO3dGxRMTE5iYmMju8v73vx9vfvObcdppp0WA+fHHH8e2bdtwxhlnRO2cfPLJePDBB3Heeedh69atqKoqqnPYYYfhuOOOw4MPPjgQMC+kLRrAPLaxje25ZYvN8WSQfeUrX8mWCyEwOTmJF7/4xY3g+2Mb29jGNoqNOveuW7cuKv/IRz6CTZs2Nerfdttt+MY3voGHH364sW3btm0AgDVr1kTla9aswY9//GNfp9vt4sADD2zUof3b7O1vfztuuukmrFixwjPYbXb77bcP3J7ayID5n/7pn/Dnf/7n+MEPfoC/+Zu/wQte8AJ84QtfwJFHHonXvva1oza7YKaXaIgJ45JyuBByFJO5toybcZILevqistAIPKtLK0FGwDue6VL4xA9GwWVVk5CVhKw0RCkd01w3dbVAzCgbY9nDYZzSOLPMvg+V7CLTnumWlpnsFugf0EF/eYGZAy2zPHOQRnHQDFYvn8bRK3+GrqwxVVQ20L0pPLu8q5rE3rqD3VUXe/pd9CsXQo7CyFUSopJOwyVQ9AWKHvzTdnD2I90yMaAJu6zhWf1UjhHJMtq0yzlpCq8ygNXN/g1y51TYMG5CCrszl2Wkzn+0FBetEMzCcNO1ko7HJRYxhZVjaHfNErEmtDuvpAlXJDNiDDJPTNJcghkcmm8YG7PGAIC3ve1tEIKSJwWjMiEEXvva1+J//I//0biJ7CtbiDl9UsYMc5qIhFsaL3g2I7aYzDKHXGcc4iFT5jy/r2NxiT2ccKywgvV+JWkEAGghYkkHk1nYtoJMgJz0UukIOfd1pPaschrKjeqTBIPLLjqRVpqdAxi7YNqyoGj7JiaY2OF4e8c56fk8WSZIL7LnHSY49hnqIbDAhQiSDCDomCUMKpeUhM6JyoA2zyozR74CdolXGxFiNhvpsvdZRjq9diTbp3EMju2342Bsc8Im5zT3swFN0jYTu+wlGtqW2yRd0vpGJQ5+JLlIfyZ037MN7SNJxghz7xNPPIEVK1b47zl2+YknnsAFF1yAu+66C5OTk61tpRpimucG2TB1Vq5c6eusWLFiJK1ym40EmL/85S/jt3/7t3HOOefgkUceQa/XAwDs2rULmzdvxt///d/vswHuKzMAII1XOxgCBgKghB30oh2MAYxLAkG6ZwN4z1X63dj9KIazgOw7SYbTNJtCWH1zLSGUhiyl0zprF/s4Wer2ANq+NXS4LZELss5og0BzCq4KC5DqZV3Uy0r0VkjMrHKprg/SwIF9rDxgLw5fsQOrJvbigM50dEPo6RJ76gkrw6i7mK462Ft10euXDixL6FoCtQPLfQeWe25ZqudiUJKeqzYB0OkwafjvBh4sg+QYTKLhy+i4+flMz/cwE9Cg85r++HlUEiGAAk5VqOFFl21gPKNfo3Eb4dZf6WEq1a7z8Qjhr1u7v9OCK5sUJpyPoI/j5zdrqSZ+HjZmmIPdfffduPzyy/Hxj38cv/qrvwoA+NrXvoY//uM/xoc+9CGsXLkS5513HjZu3Igbb7xxn/e/UHP6ElmhI+OkHUCsKyVAVcBgQlYNPSvt14iY4TWzdIGrhgMhySxyaZ67orZSC9ZuBwFk5yQWvH0uDyEHOhsLmfcfPhMAJ+c+DwYFB8YhEgaXXnTYZxptwX8Oxn6nXEm0TflnaeP3I3BN580DWkFgGKiS3xoH9fyzZjppfobj6B3Wq7xqDfwOl1Y7lknQJNSMfiEaEos0oYiXjLi6yumUtQfjonE9USba1Lj8IpJmMB108xYdwDLJ5bQWMMp+pzI/9yqSIrp7ng5YxN/riMdIJRsj2Khz74oVKyLAnLOtW7di+/btOPHEE32ZUgr3338/PvWpT+Gxxx4DYFnkQw891NfZvn27Z53Xrl2Lfr+Pp556KiIItm/fjpNOOmlg/5///Of955tuumm4AxzSRgLMV155JT7zmc/gXe96F2677TZfftJJJ+GjH/3oPhvcvjRBYVS8cNP/FyKmCAaYSzuxCAVEKVoNe5G5i5660B04gAyIAjCFcJnsDISWkJ3CM6LWUQ0OwDEwx4C0AWYH0UNYxJYyRtJICRTCa133HNbBzIECvVUuc9+qHg5cuRerp/bgoMk9WNmZxpKiQikUamOTkEyrLvaorgXLVRfTtdUs92oGlisJKAn0HVjmjn49eOeHAJRzETFognHni8p8ZjraFtJj89ms4bTWAkwblnPyywDV3EOLgQsvKI397Nr30UuApq665am4AZp5fe7kGTkG2nCIWiNEH+knqyTaQFYGRU9DVhqglKyFCA8TLLzdPnH+yzAps9Z/ntoFF1yAG264IboZnHrqqZicnMTv/u7v4tFHH8U111yD9773vQvS/0LN6ROywiSLwMJZXMAC54nk6axw+uBU10xa5giEMuc+apenpeZ1Q2IQEwHiTktIO65DnhSV1eQ2mGYOegNzrIz0yUd4ZAvq0ycmkXUMvBnrzMEypbZWJvwMOwTY4MAyDLpC+GduAJ7dIahaQEDBOCBtfD0+XVTsAYY/zNhzGuopAx8lI8dG8wQlFK3CMsW22DvgOQa5iuJ2xNpiOqc5tphrmP11ANJDG9Q0fmFL6wHAnYx0ytyZjxsxyPwzOf9RVAzSLPvtWkArGQCHwwtFHyinDYq+u3fBRvXiINkQL0Jgeb5z4QLOvaeeeiq+/e1vR2XnnnsuXvrSl+KSSy7BUUcdhbVr1+Luu+/GCSecAADo9/u477778IlPfAIAcOKJJ6LT6eDuu+/GWWedBQB48skn8Z3vfAdXX3310GN5wxvegNtvvx0HHHBAVL5z50687W1vwz/+4z8Of2AYETA/9thjeN3rXtcoX7FiBZ5++ulRmlx4c09pIQSlsIjYCF9OYJkuTgFAlG6ZSggPziw7HVjMKLscGANdAICAhrHL8aXtS0+wpRUD5wAID/hgAgAEb9ML/t0xGd5O+xUdQJT7IbtICkZakKwnJOoJgWqpRG+lwO4XGtQHVphY0cPBS6examovDujOYHlnBkuLno9fOq066OkS0w4ozygbEWNv1UWvdqHjlISqpI21XIsss1zM2EnDAuYWVjlxTKOHDA6WYykG4u8pyMsAvvQcDsrk12Bah1n2EcKCZqJ4+F1K2iU7QeU8k2PaTASak75TYM+vT2WBs+xbhlnTMyRtq7XN7qftzcUUAmIGPvIGnQ8BHdNJIxujv4eu//y0H/zgB1nmZsWKFfjhD38IAFi/fj1+/vOfL0j/CzWnT4gKk0nUiw6YAx0DoEUCQHmKZGWkZ387QkUkhoadrHlYuBQU+z6SeMe87xSgR7ILFtmi4XjIWGXKfNcRlT8GklPkQr+lkS3IiY+zuASWCwh02LNywSRZ2m335YYAuki5XuvAlwBpxf5EHRhUrm0u4Uinoo6LY6yEcaA4HAfY343SXXMAnMonFPKOgrRP6vzXJhdJjVhr5QF1XgYCBAaZZ/uz+4RIGkrHoJ0D6lSKAQakjRbunkTvAISNvuWjQWm7Ug3hSKO+Acn5gDBX+zl9XrZwc+/y5ctx3HHHRWVLly7F6tWrffmGDRuwefNmrF+/HuvXr8fmzZsxNTWFs88+G4CVVbzvfe/DRRddhNWrV2PVqlXYuHEjjj/+eB81Yxi799570e/3G+UzMzP4p3/6p6HbIRsJMB966KH4t3/7NxxxxBFR+QMPPICjjjpqlCbHNraxLTYbM8zeTjzxRPzRH/0R/vIv/xIHH3wwAOBnP/sZLr74Yrzyla8EAPzf//t/Zw3aP6qN5/SxjW0R2bM891588cWYnp7G+eef7xOX3HXXXT4GMwB88pOfRFmWOOuss3zikptuumlgDGayb33rW/7zd7/73chRUCmFO++8Ey94wQvmPO6RAPN5552HCy64AH/xF38BIQT+3//7f/g//+f/YOPGjfjwhz88SpMLbn55w/3hib2EY5d9yDiBoCMVgNFOmiFhs/J4VtlEbXCdUcQ8OzMCgLRPnrqMn9YCY5ywzPQZSXvJkkz6tMklJp5VdoyhkYAuhI3FOyGgJgSqJUC1HKiWG6jlCitfsAMrl8xgZXcGqyb2YknRhxTGJiQxAj1VQkFgVzWJvi4xo+xrunZxluvCZvFzTn66YuxyxdjlHmOXe0DRb0tMAiexoLKwLCVUkF2Euo4tpvOaY5e5pXIIf15bQrnN5uiXtN2oW7AxROywZZ+FMTGdk8TTJqlJK8ucyjNoH2Ws/KUyEJWw1zRnLDS7FhHOrRHSMR8idkydr+PJGDB7u/HGG/HWt74Vhx9+ONatWwchBH7yk5/gqKOOwt/+7d8CsHFNP/ShDy1I/ws1p3eEwqQ0DUaxw5Yo0sQhHRcPmeuOfQKRQRcdMbEDWGTOGqdt5cZE+/GwdKGcWNygtbUMMU88ohsxk2lfLnnIaZQBoOuZXjZOX2ZXLwshoI2JWGd6V0k5lXUc86z8ccUsc5vTHzkGFjCojMjWUYxFThljKg91g8xGoXCOeqEOZ5eJza1MEck5wtiET6iS65eY4kIYVLqwbLIh58FYghHrk4V/T80YQDvWOXL0c7GWiV32umUNeO2mY5ujex0Q/HcqY+WdhWWd/Qprbbx0Y2R7hufee++9N/ouhMCmTZuyETbIJicnce211+Laa6+dc3+/8iu/YsMBC4E3vOENje1LliwZqd2RAPPFF1+MHTt24JRTTsHMzAxe97rXYWJiAhs3bsQHPvCBUZp8Zo0uVjig4OQYfsmDQJlwF7Ng3x1osxn8ACEsSJMIYC4Ct2653jsVFi5aQRiCN7uPCKC+5aLm0hLQLqL5Tss7xj0EqI59KNAdQE0CagKolxroKQW5rMLEkgpTk30csfIpTBYVlpczvgttBHbVk36ioYQkfV2grwrM1B0vw6jqAloJaHLyc7GWZWXjLRczNiIGB8uyshMELU2lQJnAcdAtM5kFy/YHFikjq7PNgOU52SDd8rD70ueslMOEbdyY1pkSiESAPtdWpGOGP3eydk5/MnnQ8w8e9qSYwkZKMaWEccuEYZhMIz6qmcyPYLb6z1N7yUtegu9973v4X//rf+H73/8+jDF46UtfitNPPx3SRSp529vetmD9L9Sc3hE1OqLIOt2ReYmDaMbb5VIJio0cg6xm/GYeoaLI7NPIIteCBtLMeiQZCO2aaDtl5fPtMhBs+ybQzM6Pg3YEWLkjX+GjS1jAS7GQqVwhxEfuNH76NE/FZXoA8qExWCBNgDFEzrD9mEgjzQEzRbJQJoBcOmfccS8XDUU5vTHtm0o3bCrsEBkj7TtnygjUuogc/nxkDAeWaxc6qOHQxwC0RgyaLRcjEjDN5BdMphGBZSfJMNqSbx5nKCczrO38bAorw1AT0mYolk6yQfkI6P43H3uez72PP/44jDE46qij8LWvfc2v2gFAt9vFIYccMhRTndrIYeU+/vGP4/LLL8d3v/tdaK1xzDHHYNmyZaM2t+DmRfNpudd8AiTQFxJekOVZZweqA8MJN7PYHTVgddFw7C/5OzjQqgthw9Q5hjcCzHxcJvnOtkfOiRwYF+w7RfqgcvouLUDWXWNfSxTkhEJ3qsKyJT0s6VQ4cGIayzo9LC37kDDoaXt51Lrwk4t9l6iNxJ6qi0oVeaCsJKCFZZb7NoSO7DGgTGB5xj1NU5KSJGRcpPE28EwyPMucB8tZdnmQs98QDnfp9oFAmYSGpItPEosIArj8Ha5+G7ZwGuiovcYxpE9h7KM7T9apUrjQhzGrTGMXxsAUQL204/XN0bHN1+EPzT/JMPWfzyaEwK//+q/j13/915+V/hdiTp8QNTpMu8vDeZEpMAc55rRFQHiSAWBbzkFoYJ4JzFJqac4KT6HfYB1jsBeDYsCCfemc9wIwVpEWuZPsz532qA+uS04jXBR8DKIZEs6WN8GyhPAA2Loj5ucivp919rPjol8z71/5c2CnIALLQGCVlbtR8nNHQNNuDxrmXIhAhTj0n3cCNEA/ccbLJS1JQTKB60pbQF37ZCZx9j5tJCrXHt3HUnaaA2RtYkAMwANhDadl1gk4proEnh1INuQsYhCDZcpaa+KXLoB6UlqgrCyZ5HFHvW8mwef73PvCF74QAKB1enObn80rccnU1BRe8YpX7KuxLKxJwJC3toG7Oi1lbIGlCKCMAIsJYFT6/eCBaghyYNvR2t70hIF/MrRg2bZP4Js7F3pjn305OdQS6cxBsQjbKb2xB87EZkvAFO74CgOzTEF0FDqTNSa6NZZN9jDV6WOyqLGia9NaSxj0VOknlNotVxFIrrV99VUZ4isrGwXDKBGAshJWwlJb+UUxEyQYZc+xyn3jYy37mMs8LJwyEVPfyEYXyTBisNxgmXNyDCK25hNxJL0n5NzOXVg53reBmzR5Hd92Zkw8fBzggXPDrPdPMlhig4VjMmyad+GcTdpMTZbQExLlHoobbtlnsY8nobFZ27NnD+677z785Cc/aTiq/MEf/MEzMoZ9PadPigqTLDyYLXMSDAeeeNa8lCkFEDHE9D3dDuTDtpFZ57s6jtMMREwxb4+Ar39HzB4DIcQZl1mEYyNgazxQLkSTNVbsd15kHsA9gwzZqJ/WCeNvb0cnbSh2TMQuS4TwcvxYKFYzhIiUWXQe2hhf6eQWaepqbgSWc1IKCkfXSJ/N4jXb78RKM0YZ9j1ILOTAcfB2UnaZM8kElnXymWItc3bZ3qQtcBZKAO6+KGvhyQqbgdWuGNYTAqorrIN2zwRH+JrySFiH/bENZ9///vdx7733Yvv27Q0APVe52dCAebaMKdzmmj0FAK666ipcdtlluOCCC3DNNdcAAIwxuOKKK3DDDTd4YfinP/1pHHvssXNuf2xjG9tzzJwUZE71n6f2yCOP4Dd+4zewd+9e7NmzB6tWrcLPf/5zTE1N4ZBDDlkQwLzQc/rYxja256gtkrn3s5/9LH7/938fBx10ENauXRslMRFCLBxgXrlypf9sjMEdd9yBlStXejZi69atePrpp+c0CZM9/PDDuOGGG/Dyl788Kr/66quxZcsW3HTTTTj66KNx5ZVX4vTTT8djjz0WeVPOyWhpxDGxcYgX+NiJAIAiSDI0SB7gqju2VzviTzhpBgUcN8JJMEgWkcovkgfESG5BZVzrzFll9oJjmA0x6F6CYWxZx8AUBqKrMbmsh8mJCks6FZZ1e+hKhamyQikpJqpAbQrMqDJanqqdU4PSEpUu0K+tbnl6pou6KnwwdrgnakHscmXfy90iyDAqejfBucFpt6Ri0opUv8yZY+8YycPLNdnlgbKLQSQp0wNHOuFBGmFeljr65fZnT7qGyzTImFzDtCUnaWPGuZ7ZX0z25eNVK0BKWhY07joLyyZG22Q7urT9Sx3+Bum4R7bnuY5uLvaHf/iHeMtb3oLrr78eBxxwAB566CF0Oh28853vxAUXXLAgfS7knE7WEXWDYQbgwowpH5It1bcWiU6oA5Vd4k+z5dlMe83fRUGyCsYok0OeggQMkhBvabvNCaOAgXK/gQ7b147Sxk4mXTKFfLNjCRILmfyGuD6Zf/fnQRTQICdJNzY2EWmmax7GSKoRjz2exoBYnkHsMslNeKxmribjzpzp345n+bPZ+mgFUCcSDBej2cRQpSHNgPRt8gQltq/8+UjlF7SayuUYZPyzyrDLBojYZZgWdtk7+gkfEx+Al1YC4R2GVgEtwwwgyDOzRzQHWyRz75VXXomPf/zjuOSSS/ZJe0MDZp495ZJLLsFZZ52Fz3zmM144rZTC+eefP2sWmNR2796Nc845B5/97Gdx5ZVX+nJjDK655hpcfvnlfsK++eabsWbNGtx6660477zz5tRPFErCAU1IA2NEiJts6D/h5Q/aWFABwi9Mv2yEnUSMgE1QorlzHwO1gL/CG5EzojGycpJuJO9ck0ySC13SdwuSURiYjoYoDWRHoewqTHRrrFgy4yUYUhh0pdXj1brwwLjW0gNme07sRGKMwExtdcr9qkRdS9QzHXtcOjgyCG2Xm6yTHyB7At2d8GmvC5JhMCcH78hQpxExGACmc0jgGJgdLJPWloPnYdUEWYc8BAA7yDJAOo1YkStvOPtx2cdscZ9TyUbG7Lmx17usYS9zbZcDrcbeXr+UmVAXDjCXTouu3FhMMs4RjTR7c6n/fLVvfvOb+PM//3MURYGiKNDr9XDUUUfh6quvxrvf/e55gdY2W6g5ndty2cOkiG8zhYhBkXUK4xExKqRGsY1Jp5y214xC0ZRadBD0sFYqEdrJOSVS/OTYkY/1yzTJ9N2OJ6iiKJFIxyddsQC1AxmB2/Qz1ZUQDmBzKYn0Y6lMPG6vWWZRMnibqamknCvKpK/jtpk4CYvdJhqfpYvLTGU5mUXYx2VOpCaFVZFrL8MQvk4uAyTV0UZ4AC4ds2WjaYTxeQc/I6LPUXQMakvLhiOgPT+hXnxbiqUYnohLpBjQASx7ck025zb/nSQYwoTEJabBt83ZFsvc+9RTT+Ed73jHPmtvJA3zX/zFX+CBBx6IvAyLosCFF16Ik046Cf/tv/23odt6//vfjze/+c047bTTIsD8+OOPY9u2bTjjjDN82cTEBE4++WQ8+OCDrYC51+v5tK6AzegCMFbYfSFQKgrTmEqMu9CFsoBGuox93quVg2YHogGHI0qnX07PbMsSSNuFSOPjmmUPwgvHJBcOJJcG8C+NoqvQ6ShMTlSYLGt0yxoTRe2BMt1UamOZFdIn95WdYCo3mRjPKkv0K5eIpF/YjH1aAJX0gFkQYHYRGLiDX2eXBcpF5RhOnoyEZ+pTGaBMINkzpXFmRP8Hy4Dlhg6Y3WeH0i23gObWbHvUh39IagHdvG++v0q2ARG7HBKHZCxirwEf/qXRlquubDKdxsNdBOzttaxLAVkImEJadl8pfx4wHz1zy29iYP3nqXU6Hb9cuGbNGvzkJz/By172MqxcuRI/+clPFrz/+c7pbfNuKbTVFLsfcJVJ5FElQIi2kT7YvteojETXOd0RM0x12hhhyQCOBXtx39oIdEQdASOKbpFz1iPTcHpr9nuVCAAZCKBVQsTOfQ4EI5oGEibZaZYlZCtjTCHluFH6D99Xi+4ZgM/4Z+uFY7CpsalOrFfOsfeNcZGWGAK5EHJASCgSjydE2JAw6EM68M2jnBiPNCunRyZ2mfdNoeKoLwLb5LzOmWXaL3X8S4/HGDhnP7eGYFjYODoe79wn/IorfJI0WEKJMgFKhxUcEqZohLK2Ea24476PvsWz2c7HFsnc+453vAN33XUXfu/3fm+ftDcSYK7rGt/73vfwkpe8JCr/3ve+NyevxNtuuw3f+MY38PDDDze2UaBpyi1OtmbNGvz4xz9ubfOqq67CFVdc0dwgks/CWKE9Pa7RiztTKQHTF1DKOUkpEWf4o3ciLzuA7pjgfEfd0ZMolTHgHsdujidRC5ZNxCYTg4zCSS1Kg+5UH52OwlS3j4lOjSVlha5UKKX2AJlPDiSx4A59nElWWkJpO3H1qhJVVVig3C9gaum9fD1QNrBAmae5nnHvPaCz18UAdoyy/+ETUHYAWCoGdFPZBYDokR4MIOeYZbB9khvGXJ38hHHZ+aRpguDc5Z4D0rxv2r9AYJUzY/KpsxNWm8LK5ULbNWJH82tOwIcs8jHEQQ9nxDAHcC5cxj81If21LnsqHKMxcfDWudoiWRYcxk444QR8/etfx9FHH41TTjkFH/7wh/Hzn/8cX/jCF3D88ccveP/zndPb5t0ulI9ywSURdF1aBlI05BBc7lAIckJrOvt1GQFgy5qh3JRbMfRRM/h2Cv3GLq0cSCZZRZBKWONZ+Oz3OKKFgvFMMbG8NsKFtOHaEnlFIYSrz5wchYQyth5nou27A4quncooD7Q5cE5DyqXMMjf6SXNnv6ZjZHjgkMJuowcYvm/BmOHUeZPMOuelkg3h6+f2oToU5jSOihGc/eh7kF/EabQB+Mx+gyJjKC2QssshzJxjl7WEcYyyYWDZSjHgQTOtTnuyorCBASQxyAoQpfvNdITP9VBUSYjV+dgimXtf/OIX40Mf+hAeeughHH/88eh04vTrc/UNGQkwn3vuuXjve9+Lf/u3f8OrX/1qAMBDDz2EP/mTP8G55547VBtPPPEELrjgAtx1112YnJxsrSeSJ2hjTKOM26WXXooLL7zQf9+5cyfWrVs31JjGNraxPYO2SFiOYWzz5s3YtWsXAOBjH/sY3v3ud+P3f//38eIXvziSTiyUzXdOH8+7YxvbfmSLZO694YYbsGzZMtx333247777om1CiGcGMP/3//7fsXbtWnzyk5/Ek08+CcCmVr344otx0UUXDdXG1q1bsX37dpx44om+TCmF+++/H5/61Kfw2GOPAbBM86GHHurrbN++vcE6c5uYmMDExESj3NBqNP3hJSw1Kh1TW9jPwr1Ih+TDpDkGWPAnRcc4w61+6yXKxnAmxsMz1waCmGx24ZFzgNcBU1v0NCfCuGRHo9NV6JQKk90K3UJhsrSSixWdHkqpUAodLSdFcZO1RF8Xnk1uBl4XnlWu6gK1kpZZ7pUwlYRwyUci7ZNy8ouK9MpoZO6TtUHRCzGVowx9Ov1uvPzCho5z22Zx3muVYmRY28a2XJKQtK9BsowhbDZ2mI4jCjvH2GUAMWOtMXTfANxKivAxwQEb35P+kFIldQvXmbseTSGguwJCScjKslZCa6CeZ4i5RTJpD2M8lNvBBx+Mv//7v39G+5/vnN4273aE9o5tnOGlZBIAMCnqKDQbYBlKnlCkSJzZ0nButq/mBaKNLe/ARI5rfD9uQU5BdYQv1+w7Mcd8v46QUZzkQghIY7wsItUX23pBj5wzCZFll+mzhEAdZSik7TFzHZ0TJGx5S99pYhZ73PZ7343byi7Y8QjTkNjITKzLbDxu09Q7c9Y4lEkv98ixz/zaqlhoVG6cVQbgfXgMu3/y1dY49jK8LAN069EyaJjpvq6Df5TXHutwD+U+SZG/E+wKoPUrMVAT7rqZgQ+rqtU85l03nsUw9z7++OP7tL2RALOUEhdffDEuvvhir1Wbq2PIqaeeim9/+9tR2bnnnouXvvSluOSSS3DUUUdh7dq1uPvuu3HCCScAAPr9Pu677z584hOfmPugvS6CvsMusZcGotCQHY2yoyCkQSF1Fkf55RcQ2A1LNkWhMdG1zioe4xBQRrhZCMHiVprwI1Ra+n0AQEqNZRN9rJiw6amXlzNYUc5gQtboCAUNgRltlxf21BNQEJhWHdSmRN+lqiaAXOnC/fBDCk8APsYkef3WyuqzetMdGJehD5VAUYv44cCdx3JaQNRBemFfVnpRVMypr2ZJSJhOuTWmciYBSQqaPfC0f5jm33uAfnlgvWgfd4c1xj3rNCUQ9o+FIMPg/bQ44jXGbjJZCWXY30gZ2knHmwDpRt8J4PbPYkyS4TXh0oJ0XYaJXtZ2mwXS9kXjIOnMyLZIJu39wfbFnJ6zjjDoQkfL+h6AiRCnGCDtsr2kcqmZu5ETAht7AoKjnwTbxmM8c4kFj2Th2wSvSxIL1lZUVzSAcmNf5rjHQS4vA4DaurhFZbwfwIJlzXRfXL6hk4ku1TBTqmztt6NhGrEzn3UubI+zDFj9MQFlHuWkkdHPxOmySY7BwTJPhx3qxHKLSvNITnFdnqiEA+2cdjknSwTg78dEQCkGiLW2d3PSLgdJhgiEF51ySofNHQGBMBHL4CeiO06ezSSdRli5BroiXL/7JNMfxnPvCDavxCXA6JPq8uXLcdxxx0VlS5cuxerVq335hg0bsHnzZqxfvx7r16/H5s2bMTU1hbPPPnvuHbonPm+FDQIuHHtbdhXKwjK4ZWEzUpGzXLegyc1eNdqxH6QPLqXGZFGh25IFgjscAEDfJQbhyUAoakUpNVZ0ZrCquwe/NPGfWFnsxQHFHjtk91S+Sy/BjO5gl57EbjWJp80S7KonMaM62Ft3bDQL7RKKONaYh8CxYwpevUpJKJelz9QS2Fu45BYWEHtWHUFzLWvnzEdAuW8sy8zCxHmnPh79wjHAQhn/w/fSRJcYwzpX6nYwywEnAPYEkC9vXAtD/PpzE1KqTc59bncI9zbIGdG3wcEyb1MIZJOW5Jwc2T5GiFhXr41vhtKRQxvoQkBq6c8RaeVogibgLAZor4e2RaKjG8Z+8Ytf4MMf/jDuueeebID9//zP/3zGxrIvgDI3KcLcGSXycNcOaYbJKOMdj5UxyNmMs8JpmLQCccrplDHm+3VaEofkQr3xzxzYdgQl4OD64dhxz7LDTVDMy+OyHHCO9w/66Fi7rIzx2xRzEtTGNI6LzgVMyPRnt7MHAPf3q4jlRZO9BRCFgSOduh0ngWqBypSt+mTbRuE0zBmwDGGjYCAOJddMVCJ8VAwCy+TDk/vOV1yJ1PLpsB3bTISZT2DCUl8bB5CN8+8hYOpXZhlQFQYhVGwJKAomwE3A+TIBuiPsaq4Za5jnYj/96U/xla98JZsQasuWLXNqayTAfOSRRw7UEf/whz8cpdmGXXzxxZiensb555/vE5fcddddI8VgFsnFaJgkg1jlTqnQLZR3nJssahw0uRtLisozu1IYTMrKTvyuwSlp/wgTsrJRJkyZxKYUbpKxk+mOegl6poOeKv22UipMyBory71YWUxjdbEbB5c70YHCXtMFAOzRE9ijJzxY3lFPYWc9iZ/1lmNv3cF01cFM3UGlJWolUasiihMJBGbc/tAlVCVtuJvKssmydvGT68Ao03mjCcA78+0CSscoC2VYCs/Yoc9GvzAOCJvAJjt2OXLe09qx0C1gLAF+WdsHIc+8peu4mfFk+07CyGVjLfP66X5SxrIMzjDz5Q/OwNM2dg9KIzHxidtKX2yIP8kmYFM4NkTAl3sWGoCREkbOJdpr3hZLaKNh7J3vfCd+8IMf4H3vex/WrFkzcH5dCFuoOZ0zyNx4JjlbLwBYitTg5RkJ4E2z03W95COWGxAgjCNAMAc8JpOgsG/URxiXyEaasABbQpk4UgUl6Cbgq90/MNAcM8X5uMk0xrn8ynjfqcNflTyVp4thBQQgjI+OwcEyv5cBwIwpIrAchZbLhH5LU1zz9Of0ndclqYVtX0ZAmKfCrljoOQohx1NgE3AO7zE45rIMZfgKrPAyjFSyGEfGQMQmG03o1pU58Cw48wwE0EznunSrfUZAUuprzvsIp+Z0UY3o/jkfWyxz7//+3/8bv/mbv4kjjzwSjz32GI477jj86Ec/gjEG/+W//Jc5tzcSYN6wYUP0vaoqPPLII7jzzjvxR3/0R6M0CQC49957o+9CCGzatAmbNm0auc2xjW1sz1EbLwt6e+CBB/DAAw/gl3/5l5+V/hdqTh/b2Mb2HLRFMvdeeumluOiii/DRj34Uy5cvx5e//GUccsghOOecc/Drv/7rc25vJMDclnnq05/+NL7+9a+P0uSCG8UItl9gYxk7k9JASoNCGnRLhYmixrJOHwd09+LwyaexvJjBlOxheTGDSVGhIyzb3BV1xDTTElJlSq8vBgDpMkrZOiW2yZXYrSZRuZinEpa1npI9rCz2YqnsoSMUKlNglwnyiz16ArvVJPaqLnarCeysJ7G3nsDPppeiX5c+sYhS7klZ2yUjkG7ZLRn52JCOVbaB1B2rrOHjQXrfRQopVoUEJOUM0N2lPUPJmeWGTrl2rDItJdETchoSjjPLtCTNaRBHSoi2zHeDLKVU5mptMZVTG1Bn1nB27Jiy7DIfS8osJ2M01AaLvRz2d9pkwDtb0t/YuNhGpNe2fzv2tyXtMndIfA7bv//7v+OSSy7BP/zDP2B6ehpHH300brzxRu9sbIzBFVdcgRtuuMGvYn3605/Gscce69vo9XrYuHEjvvSlL2F6ehqnnnoqrrvuOhx++OH7bJwvfelLMT09vc/am6st1JxuneHsZx7ztzJN+f2kiJlhMs4QW+MSiKDTtSHZXDlExP7yUG/EtvKMe7QtjDskDEnZ2vCZAuTGluqI+X4kjyA2mJfxurysEMTMNsdBIed4ezS23DhsO8Zv8bGYhX3PJSKxsap1FGYulVJkmWWmRe47iUYqxeDaZWKPibn2zn0Zdpn2r7Vlu0lyQTGXeXxlkj3y73w7lymSVtmz4prYZfs9+C4hhJFz91qA5BgJq5yu6nF2V1iNsujAgVLhE6XR/SJid9t8WcaWte9973v40pe+BAAoyxLT09NYtmwZPvrRj+Ktb30rfv/3f39O7c1bw8ztTW96Ey699NJnJAzSXI2iOQAAhLHLziqASYs1rDRjqqywrOzhgM401nR2YHkxgwOKvVgup7FU9DElK3Shrfe1CBPtjDGYMRIzxi4X9Z3GikxBYMZ08LM6lpQUQqMjKE2s/SFUpsDTagp79QR2qCnsUpPYrSYwrTqYVl3srbvYXXcxXXWwuzdhk4ooCa2cJ6/i2ir3I1ch45DPxlfD6ZWZxgrsB+4AtKxg01pPA+WMQdE3KGcYECagrFMZhnX6iyJekIY5jWxBQJl/56YRJBkkwI1iDrcAuNSDc7bIGEBWhiGMgRkWOLPxzBbRwkfNcO+mIKDL9uPnIz0/OedHaY/BStUYaKbJ2kUnsRkXTbwEyNbKvazG/c2EdvKSooApFRByVTzn7KmnnsKv/dqv4ZRTTsE//MM/4JBDDsEPfvADHHDAAb7O1VdfjS1btuCmm27C0UcfjSuvvBKnn346HnvsMS/92rBhA/7u7/4Ot912G1avXo2LLroIZ555JrZu3Rol+piPXXfddfj//r//Dx/+8Idx3HHHNeKF7mtd8bA23zl9UrCkHezOz+dNgLsAcHkD1yczAJwBwlKIBtDuiCZQBYAJFLGuN9EhU0KQoD22wDjon4PcgozHUeYWO+SZVhAb6sSOEoVoSiz4NgLRTe1z4vznHRyNqx9ruJXJ8wkKIc4yEKJKhBjJogGWtSsnyQRPLNIWV9mDZdcWyRq9JCMBy6RLTsEyjTE498VgmTv9ce11iKkM7/PjfXx4BAwEOWMElg2BZZeYhGIw02VHMg3/PbxMARhldcxemacBAxGiSBl4LbMZJBEcW2RLly71CZUOO+ww/OAHP/BkyM9//vM5t7dPAfPf/M3fYNWqVfuyyX1mohaQlKtdWIBoXPQH435Q3UJhSVlhRXcGB03sxkGd3VhV7sEBxR4sFX0cIKexXNaYFAITQmJSFJFDR89Y2q6CRs/UEYAmL2KaEDpC+c9SaMtCk2cxJGZ0B/+plmG3msSOegl21pPYU08Exz5Voqds9r3pXid23KMsQwSQnZZK1pS6GgEsk7Y7AcsURcHmsreMcsGAsqzZDzkFylynrAGhdBMYc81yFjhnADP9LW2oEfoSAKmcBcxKN6GlOuC5Wg40z9Jell12x0xRM7yDn3RsBjk3pueH9mXl/viEsPpnKS3wdZEvfHQMB5Z90h2XYZGOwQgHmOmU1gay1qEeMcwATKeYF8ssaDxzqD8X+8QnPoF169ZFYO+II47wn40xuOaaa3D55Zf71NM333wz1qxZg1tvvRXnnXceduzYgRtvvBFf+MIXcNpppwEAbrnlFqxbtw5f/epX8cY3vnGOo8rbAQccgB07duANb3hDVE5x55Vqpm5+Jmy+c3ohrDOdBWoxQE7BZY4R5kCXwrZ5xpqBXa4z5glCaAzewc3E29KoFgA58kl0ROHZ25KB7BxQTo+BQC4xvzVUdHzK2Ek2BbocjKfbApuc1zbTuGi/XFps3j/P9EeRMayvjYi0y759rjV2oLUyJShVOQFlIKy22r6kZ5bjcyWc054Fw8RC93THg+XKBK0ygeXaFE4HbcFypFn2+mS7D7HJKVgm4wm7eEjWHFimVVsOlj2L7MByMxpGYJs9saSTv50DwloCKNzjEmejU/+rws7v87GFnnufK/bqV78a//zP/4xjjjkGb37zm3HRRRfh29/+Nm6//XYfb34uNhJgPuGEEyIHEWMMtm3bhp/97Ge47rrrRmlywU1QemvYe7x2InsAEFKj21GY6vRx0OQeHDq5Ey/oPoWDyp1YV/4Ck7LGpKixVKgILJcoPAMAAB0RTmfPVNhrKkitUMBgxtin4EJo6zQoDDoi3ASJYaYJYo+ewM+r5RYoqwnsqbseLPdqC5b7qkC/KlHXBVQtoWsZgHIdwLJwS0SicqBZsR+hjpeLgBgo25jKxgLmnoGstI3by5foGVAOYJm2mVhqwYGfzgBpzeo1GGb3XYow6QgRALQh9pn/4Zs/9SisG2+X2h7FeHsJY9waEo9FvDCwjDKPiuFZeGXieMcpUOYmLeA1ZQgDp4mxdscqIPzfjxgMCMDAeAmHoXB62kDU2kY6YasD1jFQwpTzYFhH9NSmsGdkbTGAv/KVr+CNb3wj3vGOd+C+++7DC17wApx//vn4nd/5HQA2Rue2bdtwxhlnRG2dfPLJePDBB3Heeedh69atqKoqqnPYYYfhuOOOw4MPPrjPAPM555yDbreLW2+99Vlx+luoOZ1iBUOEsGwp2NMw6EBGYd8UA73kYMeN4hpzcNoRhQWNBgx4N1NFx+PjMoZYClEZ1ajDv1O7HKzzOMgeTAuNNLSbf3egOWWES5BcT7q2dEO6YfuTfpxkvO90HyqvBkUdEUA/+V1y5z4eQs72QeyxiGQVOePlBJbtuJgDHsiJzwJm5d61B9gWEBNY1mzf2sgEONPfqsksp2CZImJw5z7uNE8SRyvHEAwwA1HcZS7DAFgd+9WDYBPuvUbA5nCQAHy4Txt5itJhA2xuL+c5PyySKBlbtmzB7t27AQCbNm3C7t278Vd/9Vd48YtfjE9+8pNzbm8kwPzWt741mlyllDj44IPx+te/Hi996UtHaXJsYxvbYjPOxAxbH2hkkPvIRz6SdQz+4Q9/iOuvvx4XXnghLrvsMnzta1/DH/zBH2BiYgLvete7sG3bNgBoJEJas2YNfvzjHwOwiZO63S4OPPDARh3af1/Yd77zHTzyyCON1NTPlI3n9LGNbRHZiHPv/mZHHXWU/zw1NTVvQnckwLw/Rq2QNSAL+PztumtgJjSKyRpTS/pYPbUHa6d24QWTT+OXJn6BNZ0dOKTYhdXFtM8URfFBNQwqo61g3xi/JMXZZmJGKK4lWQGDCVFBGYmOqP0TtzYCe7RlyXq6g11qEj/rL8OeegJ7VRczdellGLUq0FcFqrpAvy5Q9wuYWnoJhtcpa9jvTl4hq5CXnksx/LsBoK1WWfYZuzxtUPQds6wMY6JNxCw3svMRe6xUU44xiFlWznOCzGt3GcPsHeRkYJyFgCiC/sDkYhZz8V5ORsH74DYs4zeLzIPkI42Mf1y7zNshdpmz1oxd9vIIp3k2nQKmLGBKCV1KFz7RraQ4MjmV0EBahptfqjaUkV1qFLWB7NfRGIRxY21LEzbUuWIdDlsfwBNPPBFpenPsMgBorfGKV7wCmzdvBmBZ1EcffRTXX3893vWud/l6KZtLMoiBQxmizlzsFa94BZ544olnDTAv9JzeaWEcaRuPX8zZ2CCdSOMjxsxsmHclSs/ymmhbKqXoiCJilUnqkHPC49n0eBv8Pd3m22Gbq4zjHo0xlWHY+0w+tr/tQ7O6Ouo3dxzhOGl/1hZz6NPG3o8owRaV2wx/RTbuMpdvkLSCJIYaIUycMiLK8ke6ZS/fgBzILleahZnzGudYs8zZZcp1kDr5pZluKbFXmxQDJmiXYVI5hs0EHGUBTldt6T6bSjZaTBiHWVxeg7ABcTbWUW2RAOZ9bSMB5qIo8OSTT+KQQw6Jyn/xi1/gkEMOedb0doNMKHdtdwE1aYAD+5ha2seqZXtxyNRurJncibUTO3Fo52ms7ezAKrkbBxQzmBTBbc96Edu4ojPQKAxN5k6rZ6SfqPYahT3GpuacMQVmTInKlNipJ/GfahnS7EWAnXR6uoPdahK76y5+1lveAMoUY9lLMSoJ3SscMBaAgv8sFBxgDaDZyzDYywNot73ca+MrF/SqTABZfpWREpIMAMpsCX9OQDnVMKfvDhx7SQOtZ8kgg4AQEFLAIEgcuEWyDEovNosZBm7zFeY2q/goFg7UcudAB6vzzn1My8yjaZjCgmXdkUz/HD8UUA9BYgH7KoCGcyJJMig2NslC3Dm28pHRJ+5RY4GuWLFiKCe4Qw89FMccc0xU9rKXvQxf/vKXAQBr164FYFnkQw891NfZvn27Z53Xrl2Lfr+Pp556KmKZt2/fjpNOOmn4wc9iH/zgB3HBBRfgj/7oj3D88cc3nP5e/vKX77O+crZQc3oJ2Yg+QYCOpAxTshvJCrjmGAAmRCeSJth2gsAjp+cthIT2kgrqk12rSXQLqpPqlG2/8UXKAXJ6LASI1SwII3Yy5H3pqE/edwzc4+NOQTvfj8tb0iQl5OwX0pW71hlYBttu23Pv7L5FUgzbrvbxlElCUXkQbbx2mQAxgeWe7lhJIiUmcbGWeXISHm+ZymovyZCRZrnWzQQmHCwrl90vxFwGNMVp1qE+AeRsRj8CywlQ9kbAWtvPUZSMNtBqwBJ/IZq/jXCk3zwlGYslDrOUciCxMdd5bSTAbFqAQa/XQ7fbHaXJBTc1AZiVBmpKQyyv8MK1v8Caqd04ZGIXDu7uwqpyNw4ud2F5MY3lYgYrpPWsnPFB05MA7ZA+VJxN6WrQhfJZqxQEdunShoMzXezRE6hMib26a0PKmSIOj2MsGO7p0kfBeLo32QDKVW0z+NX9ArqSMJWE6Ev/A/assmLvBI7Jyc/Ag2lJ7267rIDubu0jYRAo9mDYg11AVtqDqmwEB2JCB2mVtXaftQPMbF+4fcm8JlAEoEbguUiAs5S2P2FcyJ8Wy7HMnF3mkS54KLVBYdU0sg6Ihu+bts2rCjsJQ1jWN2KdOVCmtqSEKaVllwsR/h7ajVkiBuPKWEfMUGLHLBwLTRO2QTwu0lMbq2GeNUzebLbALMev/dqv4bHHHovKvv/97+OFL3whAJusY+3atbj77rtxwgknAAD6/T7uu+8+fOITnwAAnHjiieh0Orj77rtx1llnAQCefPJJfOc738HVV189twENsN/6rd8CALz3ve/1ZUKIZ8zpbyHn9BTQkh5ZQkIKy5TmQK0FonzVTkKKFDjnf4PUZtsY6EeYc6DjTHTKeMf1bDmBZQ3jAWkbu5tj2j1TDYVCiEafQRed7z8eL7VloiQvnF2mMkpSwoFyn614+vEx7bJnnAkMJ2A5Hp+MkpTwEHIcLIdoGoF15mCZxpMmJwnZ++geyhz8GDDuq6LBKockJSEqRgMsawaSfTQMsKgYKVgOoFn4aBnhnpvTMnPnPtIyUyQM3bEreRKWafbtAPOPlLHAc+9zxe64447oO8WXv/nmm3HFFVfMub05AeY/+7M/A2An8s997nNYtmyZ36aUwv333/+c1bv1VyvIg/tYumIGBy/bjV9e9e9YO7EDK4tpLJfTOKDYi0lRYVJU6AqFPaaDwhjsMV0XIq70EwA3GwpOowOFSVGFSBdG4mk9hafVlI92QSB5t7JLyJxZrnWBadVBX5fYW1vnvj39CfRV4bL22SWjuiqgeoUFypWErEX4AWoCyjFYhgPIIQWyBcqeVVbk4Gc8YJZ9ywzLmgNWWIBsGOhKgTAQl6WZ+9oYZQ6WeVrsVI4BOEZYB5a5KFxeUcc4o4BDy4AUMebz8oQBIJksB5YTJjg0HB4YcubbcO16kEx9RNtoknVpqFXYZtFseHAwUgKF8Nn34vHHxwwgSGjc3zKXOZFP7tH5Mg4sCwewSwHTAliGsgWetP/wD/8QJ510EjZv3oyzzjoLX/va13DDDTfghhtuAGDnsQ0bNmDz5s1Yv3491q9fj82bN2Nqagpnn302AGDlypV43/veh4suugirV6/GqlWrsHHjRhx//PE+asa+sMcff3yftTUXeybndHLQA2IHO4r+ELPPXJpAcyot8ceSgyiWMotZzNvi+zajXpikHxvNokpAd87pTlkEBcXYaWojquOOXyVjrhLgX7HzkB4bdyzMRdFIAXs63sqEyBgWOMeguPk9ad+RRoPAspcYsnulZ4MRImJwsOxTXpMUgxFJALwMg9oiR79WBz8TYi/XWrIwcXHWPsrkR05+tQoOgIFVho2KQfNhApYDSHZzomEAmgNlcr7ncx6byr0RYC7gVYme8CI5pBTQY8A8lL31rW9tlP3X//pfceyxx+Kv/uqv8L73vW9O7c0JMJNXoTEGn/nMZ6IYpN1uF0cccQQ+85nPzGkAYxvb2BanLfSy4Ctf+UrccccduPTSS/HRj34URx55JK655hqcc845vs7FF1+M6elpnH/++T5xyV133eVjMAN23ivLEmeddZZPXHLTTTftsxjMADzrPZu9+c1vxuc+97lIQjIfG8/pYxvb4rPFIslos1e96lU+WtJcbE6AmViQU045BbfffnvDc/y5bJNr9uCQNQrrlj2NtZM78dIlT2JK9rBU9jApK19vxnSwy0xCGWk/qyWgGJHBAcLKMaQwKGCTjkxKmwEQAGZ0BxoST6sp7Kin8FQ9hWnVQU+X/klZMg1drQv0tdUqz6gS03UHM1UHMy4ZSa1s2DjVL7wEQ7oMfUIjMJJcjkH6J1+OKO4yZ5ZlZWxSkp6BrAzKvco79HH2kVhJq0lGNlwcgGZsZS+7SJjlVIKhVINRNtz5j0wBQjBtslJWgiEEfFwe45hn7R6l3RN59FzeJing4bVysoo22e5s7DJnpx27bMOzGVYX1qFDGMswFIXTaROD75gMas+FoTNSWnZCADZhifDxlI2TWlhmmbflzoGbPDlbLPzf0v29XUIZbz65Ssu5GMaegdBGZ555Js4888zW7UIIbNq0aaDT2+TkJK699lpce+21c+5/X9v999+/TzMCLvScTnKCOBGINYpzzNnf1GhbIZpsKsBjLTd/lDl22ZbHumTO1hK7TGHruGQj1SWnDDWPs0w/UXrn+1C7vD2e4TAem3GO5eE88nFTv9ReynIHuYjtozJM+mCob8qmJ9h3kk6k4fxidjmMX0Z1SIpB2mVil3l85ijGMnf0A8V4Lnw8ZR5zmdhl2kbsstcuG0psQhrllGF2zoZa+rBxiskwgHZ22WjrXB8xyRl2WVCIOR0+R+Fbcy+4d8cy25VhFv++NmG+nY+zNfCMzL3PVZuensa11147UqbWkTTM99xzzyi7Pav20kN+hhcdtBsHlntxUGeXS3PdBwAfnaIyJZQR6JkO+qZET3ewV3eDxiqZPAqhIWHQkTUKmCiO8o56CXarCeyqJlEbib62cZOlMCilRumSlWgj0deFBcpVxyYjcSmue/3SJiOpBXS/CEC5FiFrIZz+mMCxQRMwu+8eMCsryZCVcRn8jAfLRU9D9lQATLA/Xo/vCXQp46NfAMDACBgcGBMozkkwlA4AOeeExzTMxoFikTr7AQ4sS9uGcNIMGn8O7OoAqKPuUr1yxikutJFplxuXYdD3dCxOQkLxk/1wmfQFAA9o69pxk3wR9qfYy36e0/b8iGHW1ig2Myxg5jpynwVwX0SIWCTLgvuDLeScPsHi0xOAsrM3CgABAABJREFUjSUXARBy3bKGjgAvGQey9J7WoXbhpBmD0kQDVj8c2grAUyXvvt2kjSghia/XNC+9SOQf6bgpyhI/XgDQxjTK0vZ43zwqB4FlzUBzFYHeWIZB2/h9L5Vi8OQkfruh9NYxMCYZhvZgmiclCY5+lJikpx3YpugXEEy3LCLNMoCGw58y0ke/4HplAFHKa3L2I82yJtBMmmWvX87JLsJ7AxDT/ZjuxWy+ixjblnnNSLFw1O4imXsPPPDARnz5Xbt2YWpqCrfccsuc2xsaMF944YX42Mc+hqVLl+LCCy8cWHfLli1zHshC2y+veAIHTSqsKnaj60Shu/QS/9RbmQIzJnjpUln6owVi7RdtI6/i2hToqRK76wnMqDJyOiBb2umjlNr/uPu6wHTdQa+yYLlfldBaoD/d8Yxy0XfJSCoBqcIDHwfInk3OscvaOvQFZtk69RV967xX9AxkX0MoDVnpiAn1oehIx6ridwB5oDzIsU/rAJRdXUOOTW3MLwE37/CHAJxpKVkpxiyrJhBuA7YtoDk1YZwTId1DdLJtECOdguUk6oZ96A+gWnfsjqIQELVugn0Rt2XZaQuWjRSBhXBgGS4lvAAaE6AftzEgb27K8OfNORhGQ1D76Uw6tmdkTk91tgRsldFRqDbN6iqjoTI/1DgVtIjeQztNFjhEnohBZVv9lEnmzG1bCuwUqDbHnq/PU343gDgD6+TA50F9AuB5/zyDXygjgBy0ymkykoZj+5BAOXXu0yaEkCNmWUXssWywywC8o1+sWQ5guXJgudaFB8W+DkIYOXLwI7CstGA6ZmKPg3bZs8/EINMtjQHmKJuf0zATKCZnewBRaLkozBzgy6J7c276pP5LQHWETyJmXXPG8+1c7JOf/GQ2vvyrXvWqkVbThgbMjzzyCKrKShe+8Y1vPOOZqOZrh3R2YnWpoYzAjOngaTUVwtiYwsoocp647mk3TbuZi/XYq0vU7Km2dj9WT1QKg4myRqdQ6Ls2Kl2gX5eYqUv0q8Jl7bPh4rCnRNEXkD3hU1mT+bNvHBD2T74xYJZMflH0TeTgV/QtSLZMswXKQmnLHlP8Yg6kCAxrHZbpmbNba7a+lFWm7wSUDZNs6JZbTsTm5oGzENIyy74dxzJLBAaaM9HchAigOVeHsdseNNOubGweNCeMNA9Jx8EyySUah+tws+5IuywnHNubGbdxwNku5QWw7B+qpI224J0MC8SAWcCx1XR8XIoRXwfkWBgcOkeP3rDYdXTPtj0Tc3rqNBfCtzV/59zZjzPGuTLeHv9u35vsbS5OcQUdha8DmINeEmGiwRwzuYMvQyytSOvT9ugoWLuVMZCAdziM5RdhDLwNkn1QOTn02e8xm2z7kA0mOZJiOABMAe54CLk0gx/JFm0bobzvgbBljamej59sAvim+62tb6NihHoiuv/ae6aM2WUwRtndhwFEcZUrXURAuTVsXJryGg4gg4Nl2DwHxCAzQBxl+SMgzRhnLsXgWQCjMHNU7OZkmzPCtqO1u941m5dHtMUy977nPe/Zp+0NDZj5kt299967TwcxtrGNbRFacpMYqv7Y9pmN5/SxjW2R2iKZe7/1rW8NXXeYWPcjaZjf+9734k//9E8jT3IA2LNnDz74wQ/iL/7iL0ZpdkFNwnhWea/u4ql6KSotI0bZPg3HcR2tQ17hWWQeqqZShX2SdSFpqrqwsRxdznmtHBsnAFlolKWC0la+Adin4ErbJCT9urAh4/oFoATQK1DuLCD7IVayN4HAJlMYOcPKDNMxkwRDGRQ9K8WQVWCXi75li0WlIWrNklOQg5oda9Ajm2a4OCDPLHMZho/FrL1EI2KWgYFspWHMsyAHP840a8BIHUKwFYXrx+lXhPOiIAaZ/jDcOMsMxhaT5w5zlgsMv2m2wW1AvGZigCOGuAiMsVfxCNeQC5LsY3EyiQecnMPq3qhNV4+GQLIMMJmIa9qk4eX89aRBzoXCGOZoaY9d1BFfNjebI8uxv07a+4Mt5JyeMsHSL2m0G5dfNJ328lnsSHqhItZWN+pzFtnXg0YHMmKWqd00DjOxuto05RvUPm+ngEDF6vF+udZYGaArhNcpU/vpmOw5ofMUPle8XWNjKqcZ+3imviDTCDAgSDQsS0wMsjLSJyThIeMqYwP0EatsjymWYMQOfSJ8NiEGM3fyI8c+L8Mwwt+LOaNMq7TaBMkFJSOxZUxq4SQYgNMrA3GcZWKXmdNfSDqSxFvWyGiWObOMaLXXlyNmkn3d1OjPaABd0v3KOvkbbV2z5834LpK591d+5VeGzto6TKz7wbNWi918881ZT+3p6Wn85V/+5ShNLrhtq1bi33sH4kczq/Hj6dX4j5nl+Hl/GZ7qT2FHtcS++kuws1qCndUknu4vwc7+JH4+M4VfzEzh59NL8fM9S/GzPcvwiz1L8fNdS/HU7ik8vWcJdu5egt17JjG9ZwIzu7vo7+6i2t2F2ltCTZdQMwWq6RK9mQ6mZ7rYOT2Jp/cuwY69k9i1dxJ79kygt6cLNV0C0wXErhLFLolyj826V8xY2YWsXFSLPlD0wovKC6rTD+8kvSh6QDmt7WuvRjmtUMwoK8noK8hKQVTKAiDSKGvtX6gZoOaZ3xR7+W1uqV6rUK6UK8uAZbfdaJ1/cQkHHHhm3wMYd+2mMhClgbp246FxmNjxEIjBLwFjQw8IcC+2T6rfTtqI9MwEWIEYQHv5hgPLXI8sACNhHfiYZKLNwZn259ExWk3CLfkJJ+Ng4zIs5TndjX27cR1ECVDmaGaE1/PU7r//ftR1Mw1yXde4//77/ffLLrsMq1at2uf9L9Sc3pZ2WkI09McEklPpReETnQjfFm+/hkJlFGymPQWKQVwhxEdW7nsF7b/zMtIFK7avBbEm/PQBVDCoXL2+sRIIelXuRRlhqZzqRdtYG31jo1douLpsuzLAjNvO+6HxkASj8uBXRGDZxjeW6IOyzVq5g/XXKTFjOuibwr84kKU69mVli/Q+Y7qYMV0vcQz1gv+P9QHqtILlni5RG+vkl4LlykibtMs5zNdevywHgmXSLNdcv+zeecQMrWJii8AySTPgko4YJWAoi657UXSqSKfMZJDCgesULPM5LNqfADa/6BmZYgpAl2Fep5jM87JFMvfefvvtOPLII3HdddfhkUcewSOPPILrrrsOL3rRi/DlL38ZP/zhD/H444/jhz/84VDtzYlh3rlzJ4wx3tNwcnLSb1NK4e///u8bqVWfK/bj6dVQWIq++xH6MDRgmYHoyduxyUpLTFcdVHUBxX5g/GmUOwSgCj80nyVNAJAGpjDQSqJfFehPd9xF6H6EtQCUc+jrCRQzAkXfAmUfNs5149ljE36gQPgeEpOYEA2jttEwymntPjvwW1uGUCgVNMmAZWdz2uTUsY/AUsoop2wzA69ZvbIxAQTnLEpa4nbR2jLNOb0x6ZapfR49g75TJj4Fyz7zx21/vzYR22wz8Ll922y2p1kaf8Qec+BK/fkRWGLZgWob5SJhyRnYzoFlfmikjfYh5DwbLaL6uUQ0AEKEDiqfTwa6uU7E++mkPYydcsop2dTUO3bswCmnnOLZj0svvXSf9vtMzenaL9M0tcYUbo6SjQAAT2tdGYU4LXRwEORZ8XIsci6Bh21TR5EtQv2mpSwvgVSZ1Jcg4GqiKYtY28LtXyXXcexEbvz0VcUQyh89909WsCCZt+WjW0BEWfR4SDh7HE0HvsLdQAgM232DEx5gNcrEIttzFoeYS537FISPggEgyuJHDn5cs2wjZYSwcaRX7qvwva+KKCEJgWJy9uOaZXvrkV6brNl9m2uWvUMffWYssr/Hc4e+HKvsAHQj9TWrF4PteH6OtMwOP9iVQwPdgQXrIkkoNootkrl38+bN+LM/+zP8xm/8hi97+ctfjnXr1uFDH/oQtm7dOqf25gSYDzjgAAghIITA0Ucf3dguhBgp3eAzYU9OrwCwJAo340X/gPeg1bDyCq2txKKqChjl5BV8iYZ+IP7JEzaKBWEMAkKS1SNTLOuPi5ssaxFY5L4LAafgQJLtVoLJLNhyTiTHUDaFplT2s2WfjQ0dNxOiYAjlHPc4a+zuAhYMu7F6GUUCojggbgPKgyQYDCAbxhB7y8VfFjK6W3jQ3GapAyHV9U8fwrWl7fHSXYiDcMU+S/e3INCcMsXpcI2BQbM83YfAsi6EXWPVpjk/Cdu/gYgmWYq3nAPLIbyRia8V3mZqxoTJn6Kg0N8egFFgkhzH3I9oi8XxZBijZcHUfvGLX2Dp0qUL1u9Cz+kElIMbWYhWwY3AcCp/oPjNcSQIA5mwzEAMksly7VVe6hHiEwPB0U+ZEGCGiDwOqBUEChj/2fcF+1MjYChFPKVBCKSPlzwWckcY76hHZQVMA3DTfjw7XxwezjK0bVEuKvbUS3IMn5UPEpX7zoEyj3ph6/OU1iFUnB1bzChz577Kg23hvwOI2GUrgYzlF6mTPUkiG/ILJsHQHCxr0QDKACe94MBwKr9g70C4b/t4y4gANGeTG5/pHq3T/dAOSAk0SyvPECUgS5G938zFFsvc++1vfxtHHnlko/zII4/Ed7/73Tm3NyfAfM8998AYgze84Q348pe/HC0NdrtdvPCFL8Rhhx0250GMbWxjG9titLe//e0ALDB9z3veg4mJCb9NKYVvfetbOOmkkxas//GcPraxje35ai972ctw5ZVX4sYbb/SrZ71eD1deeSVe9rKXzbm9OQHmk08+GYDNDrVu3TrIQezec8z+c+9SAJM+u49yMRxp6QZwLLMWUEoGVrm2n9OlGf5E6ZdhHCMMwGlETVjGgdM1KUD2RT4Ln9Mhp0HOARcejp5U6QmVmETHIErv6Ges1rk29tW3Sziy1ta5T5Mkg/TFwXkvkhyQkx+xidxIkkHMsj2BTXaZa4tnY5fdY79pCZkjpBuDloOd6YyG0C6hCZdlKMXYYhkzzQVrN9u5o4t4hiViogc97WvEMgbenpdSsFBw7rj8Ez2xzQLOYREQ0nimmbPLphQNdpmyMlKWxoHmHApJvwxDZWG/1rCCo9ggZqWt/vPMVq5cCcAyzMuXL8eSJUv8tm63i1e/+tUjpXAd1hZ6Tq+MRmUYryoCuwsQ42u3pzGQC1gHOGKTK8ZMc5lEI0Zxck1qVp8n8khloNwxL52COPMrRfydtqemTGCJAfjfCjHDBUzEIKescQGDPg/jlumDdMrEKtt+LYtMbZP0AoDNWBuFhgtMshTW8ZDHUbbnL2WrRSMJCQ8ZB8TJSkIdETPNJoRvpex9llEuoiQkwenPtaEts1yrcLykUU5ZZgNYjbKBWyVOJBgQfh4irTLXJVNouGiFjumT/eoxY5QjZ76UXTZ8P/YZaJ0PvRO4k2UoI4EluZvKHGyRzL2f+cxn8Ja3vAXr1q3DL//yLwMA/uVf/gVCCPzP//k/59zeSFEyXvjCFwIA9u7di5/85Cfo9/vR9mHCczzTtmN6AtJMhh8SSSTSH5C224RyUgsFiJYfDV9i4UjFSFtmjE0SQSmrSWYh+0y/pEg+EaQWkUetG6MtN/GP0QNm2te4PozVLveZZlkZyL6yAJhrlnl66yh5BXPq4oCZJ/cYJMNgco0oIckAKYYHyjk5BmCdMQCIQXMFF/hltM+hno6TcBj3ByFNs082kpFpINnW9p23TeLhJBoFRacwpPhhc7gwAGSYnEngYSBCxAoBC7hLB7q97rgJltuW1TiYto5+LnIKyXRSUMylOfOwxbIsOMg+//nPAwCOOOIIbNy4cUHlF4NsoeZ00hD79NIMKHOJBZdTpKmoK6dTJs0xdxZMwbJGiFHMNceFsA518diCpfIHXydzzaXANpSHCEi8jKpx+YSVdAgoF8FCCtNIQ639eYj7IelDAe2B6IzpeHBM+1asLumX7WcRtRMAcqJDZm1RG7RfDij742OJv8gvKJVhcL1ymt+AO/TxNNepc1+qV+aprjXd0w1z6ssBZS6vVAJcqzzonh8BZdqfg+EUEHtiLSnn93jeVwbQkiwDMDCT83uwXSxz76/+6q/i8ccfxy233IJ//dd/hTEGv/Vbv4Wzzz57pLl2JMD8s5/9DOeeey7+4R/+Ibt9mPAcz7T193QhVRfEEht/USZPlFp4NhcAvG6Z/zDoyZOL+AGYwgIgYn8lbXcMMrHIsg7tNYAy/+E4ls+HisuAZcAyyUIRMxhCxxGjLGsLSolRjsByLlEIgWiKdkFOe3Q+fD0GjIE8WI4Y6NCXSfsNojL3Fv9ChRR2m5D23bHBXsdMAJh0wa4dQSl425KScHacWGvf/gCwPB9jYeAIREOGG6sH1QRkJftzG4TVACEaSUoANhkaB4DZpBxZ8t1HxiDQTPr2NsdKOpb52H46ES+Ebdu2DS960Yuelb4Xck7PhV6DseC4Yo5+nhnmUwwDuWlGvHQ/SuiRy3RHl2tHhBTR3Eh7PBsQjhnhOFNeAZsYq0iON1vPg1BifgvXvoZKnu61iccTNNTBoW/GlEiTirQBZNumbPTDM/PlQDKNpTJlxCbntMoKIelX2C9JCsZ0yiExidMsI2iXuRM+AWRilTVLe90WLk6rBCgzgsvwe7kjyRrh4oAEKLN9MkAZQFgJ5uXJd/8ZTZDcAKhEpjjQrLuYvy3Q3Hv99dfj+uuvx49+9CMAwLHHHosPf/jDeNOb3mS7NQZXXHEFbrjhBjz11FN41atehU9/+tM49thjfRu9Xg8bN27El770JUxPT+PUU0/Fddddh8MPP3zO45mamsLv/u7vDqzz5je/GZ/73Odw6KGHDqw30mPKhg0b8NRTT+Ghhx7CkiVLcOedd+Lmm2/G+vXr8ZWvfGWUJhfe9pbAngLYU0LsKSD3FJB7CxR7JeSeAsUeiWJaophxmfX67uUd8QRkX6Do0XsI9UaAl74XLuybdJEuymmgoBcLB1fMuHcX/k1W1jnPA94qbCt6BIKTV+UkF27foqddqDj3Ige/HFhuYQkjsFzXCGHjTAyS+YuHjVM2FJyh8G1AAMu8z5b+I6bZvWZjnyNjmZCM0R48Z+mitox++9jSc00psz2rnLEo1Fu2UVuH1/MPVsrELMKAwxKGh5EL0VMovKDdn/2th/gTjG1udvvtt+Poo4/Gq1/9anzqU5/Cz372s2e0/4Wa04lhpjBpZDzkGwBEqZ2NcSHi4pBuSLbRO+1XIYR6074sBsEzRvjQa/y9D4k+QrSGikkCAMsKV0ZixtjwbPxl2dQQd7iPAn0Uvt8gmQj10hf1RXVoDDO6jMK+9R3z23dh3/aYLnbpSc8Q89BufRcCToHkE2F7PzMGHhKub0r0KZyc6fgQcfSZGGUqD2Hk7D61S3Fda1s2rbro6xI996pZJIy+LkOuAxcybqYuUakCPVXaqBmqQK0sS13pwoaOozIlUavCh4jz78qCZaNYqDhlV5B9uDhls+jCvXunPCUcgA6kFtg2oRAD4URukTLP3lE/Jb8YSAZYG2T8s+CvfUjg7GM7/PDD8Sd/8if4+te/jq9//et4wxvegLe+9a149NFHAQBXX301tmzZgk996lN4+OGHsXbtWpx++unYtWuXb2PDhg244447cNttt+GBBx7A7t27ceaZZy4YGXv//fdnw2qmNhLD/I//+I/427/9W7zyla+ElBIvfOELcfrpp2PFihW46qqr8OY3v3mUZhfUimkJqWWQTyQXtBHhHQAoNEXj6ZE/aXLsJzLLKyS5qBPZhWeUTYM5jn9kxkstIuOxcDUxzIbpl1nYOALJJLEguUVuWd0wZlnrAJa5ZIMSeRCbzHWsOb0yEDHLjePIAFQhbYB2zyaLOTzXcTaUyzOA+PMo7c1lmzOfRrtw9VMdomebZxkGXV8CoMgbRtoIGX4soEnZxJpl0wTskXm5jwlgWTN2OXNMXkozyjn1B4W5sRwLxIg8F+xf/uVf8Oijj+KLX/witmzZggsvvBCnnXYa3vnOd+Jtb3sbpqamFrT/hZzTlTGNyz6XblqyzykrTck/KhPqFQLoICQF4Wmheag1ilaRY5AJIPPv9j0EjSMJArHMaeIPCrMGUQMmlOukHwrb1jeFTwKSGsURUe5zNCYf9g2eBVaeEZZ+LHaM4XvBeDEutaAIFWGMMjkXIekI399vpzEwZpmHiiNtst2vySiTLhmAZ5W1EaiUBdM+AgZjlbk+uVYhVBwlKAEcw+xeJLvwkTF4JAsfP5nhgURm4e/LrLyhUU7wga2fAcWmCawb7HLaXmJesjdfV4MFnHvf8pa3RN8//vGP4/rrr8dDDz2EY445Btdccw0uv/xy7/B88803Y82aNbj11ltx3nnnYceOHbjxxhvxhS98AaeddhoA4JZbbsG6devw1a9+FW984xvnMPB9ayOd9j179vjYnKtWrfJsyPHHH49vfOMb+250Yxvb2J63Rgz4XF7PZzv22GOxefNm/PCHP8Q999yDI488Ehs2bMDatWsXvO/xnD62sS0eG3Xu3blzZ/Tq9XoD+1FK4bbbbsOePXvwmte8Bo8//ji2bduGM844w9eZmJjAySefjAcffBAAsHXrVlRVFdU57LDDcNxxx/k6z5aNxDC/5CUvwWOPPYYjjjgCv/Irv4I///M/xxFHHIHPfOYzs2pAni2TewVKJeInN3pnDF+DMEwY5TbBfkMP6p4wpbLEg2eYnWNe/LTp2EH+FOrY4nx0g8AmCgMX+YIYae0YZx1YZe68lVtSTxlsn5lPBxYZCE5ynDlO9cpeOjELu8xNCkBLCKmDYx9FxEhDTLSxzcR483ECjroahVlOdMysHwG4aCKsb2LLU320sA56VjNPjLorg9Me8z5Iv0zEMUmbaRmO6Tx5EhTPUkTRLdDODLA/izDELuuQyIYiqCR/viiJDZCXuQxrY4a51ZYuXYolS5ag2+1GS5ULZQs1pyt3vac6YyAk/vARLJj2mNcBAIhYl2zbjiNb2PbjOMZULzUeXaJ17CxbXoHYKY+zurysiqJahB8PxUEmhrbB7jIHOwnj30M6ahExwNxJjycKIfNMM2T0EyWGOY2dHBwIE12y12tz50ER9Z1jlgGgpmNlUS/S+MoA0NcsPbYqnOTCjY9FviCdMmmXG6mt3XxC0TC8Ttk589nVN8HYXs4mi0hjHJXze789qc3VZM4uU920vQy73MY+tzn+7TMbce5dt25dVPyRj3wEmzZtalT/9re/jde85jWYmZnBsmXLcMcdd+CYY47xgHfNmjVR/TVr1uDHP/4xAOvL0e12ceCBBzbqbNu2bQ6D3vc2EmDesGEDnnzySQD2hL3xjW/ELbfcgm63i5tvvnmfDnBfWdkDihS7MfmFX+rg2IWD5RQoZ96jpkmO4QAzRbjwEgq+ZIMAnKlPWh7PmmH1CShz/SmTYRBAbgAdMi6doO0kxSDgzLcJEQPnQWA5Zw70CSmt4x+BQALNBSxYdUC5LcTcQEsjYPBj5eCUOwrSg0TOMZAslVRohAQmbB8PkPkxa0AIYydsYaKMfkYbK0MhkCwBI4WX5XjQHIFl4R0Fs9cj796D2+YhCff3o4ctCjno9e65c+BlOvMTMy8WT+1h7fHHH8ett96KL37xi/j+97+P173uddi0aRPe8Y53LHjfCzWnR/pjNkny5CBAiGBhAXRwnKPv2hgmlwg2KCxbYyxMSpECZQJ53GGPR50giYSE9ok/mpKKAIILoaFQeBlFGnEiNR7NIuwfAG6QaiTJSAzpo+MEJJUpPeimfkk6QVKL6Nww+YfXKCeh5Gh8PExcT5cJyI5DxfEIGFGGXSMi4KwSSQaXYHCg7MGzC//Ks/V5CQZz7PNJSFSQZzSc+hr3+USWgdy9OgOuc/VaQDCB5Ygk4/sxa4Bzd4jzsVHn3ieeeAIrVqzw5TxuPLeXvOQl+OY3v4mnn34aX/7yl/Hud78b9913X2gvub+2JW6aa52FtpEA8znnnOM/n3DCCfjRj36Ef/3Xf8Uv/dIv4aCDDtpng9uXJntAQXiOg2PGLHtgAnbxpuJ+JN9N/CPx+2qXnpqcBnxd68zndckc/FJb5LCVA4uGQA4DOwR4KBJGwiQLHZdFGtTImcuBIA6WqRxgIkPX8GxgmQBpC8scgWbePgrfXmsIOQZ8ozTZgAOoDDRrAyN1iJjRVg/IM9JRfRMy/pGem4Nm3w4dkzsOaoaicbjJ2557x4QQa8w16jSZcnbCXasN3TO7XsIkza6Dhmbd9kErEkKZJrOc7sOvDaWjPuds7IY0dP3nqb3mNa/B1772NRx//PE499xzcfbZZ+MFL3jBM9b/Qs3pfWMd8bIzQLg0ASACvhDCA2AgXw8I6aN55IpcPV8/SRXNjfTFqXaY9rPgs2iAXgKxHQflK1gHOGJtfZ8cDHsAHSJZUAQNKufRLWxbTc1xZcpGvGQec5naC8x26bPw+eOGQcWjXjhgneqsOVCm8VWm8CmseeprDoi1kZhRpQfKPMYyRcAALOhVmoFqHYeNo8y8PmufCuFheVrrSK9sANQEihNGmYHV5vYYzHrj31NQnQLoFCzrUC8FwY1V7xRkpzbfuXDEuXfFihURYG6zbreLF7/4xQCAV7ziFXj44Yfxp3/6p7jkkksAWBaZr1xt377ds85r165Fv9/HU089FbHM27dvX9AkTsPY0ID5wgsvHLrRLVu2jDSYhTRK6uHwhmXmQF/yYDl68kvAcSzTaAIRnkQkChmnHUCJfkjGb/PtEbBN2g1L7RST2ckvdADGETMYAWLONlKZDkCZwDF35iNADEAMSuxBfUUnXcbvgG2XA0K2LQo1lzizNYw9abamx9YaKBLEzVlmYoXTegRqkcgyfP0W0MyH544zSgSjBWOZ6dgCWIagJCYI1x57GKJJiz/oRZM1vXuJD/ubZ06jb5uiqDCw3HAK5dcLl+sMWk2YzcaA2dspp5yCz33uc1FopYW2Z2JO1wigllsAac2w6RbMxoCVf07DrHFrk1lE7HJGTgEgArYpKO6bstVRz5uAB7CFMKhoTGy8hTA2hBoD1Dz9tPYAF76sgGYgXvr9eBi4yBmPyS2IDSfWOAXvAFDBgvjo+I2AZqmv6Rxy6YWCQF+XLr5yqFM32OUkZJwDvjnHPhtb2UbAIGbZTmnOkc/Ayi80k144RtkzzCS/IFCsg6NfmmQkcvrjpATQBM9UpuNt3nhZ2p5JyDbqm7UHZEC3Lw8d7ZOVtmd47jXGoNfr4cgjj8TatWtx991344QTTgAA9Pt93HffffjEJz4BADjxxBPR6XRw991346yzzgIAPPnkk/jOd76Dq6++ek793n///TjppJNQljHUresaDz74IF73utcBAC677LIoy2mbDQ2YH3nkkaHqPduU+djGNrb9wxa7JOPCCy/Exz72MSxduhTT09O48cYbW+suBAkxntPHNrbFaQs591522WV405vehHXr1mHXrl247bbbcO+99+LOO++EEAIbNmzA5s2bsX79eqxfvx6bN2/G1NQUzj77bAA2++n73vc+XHTRRVi9ejVWrVqFjRs34vjjj/dRM4a1U045BU8++aR3aCbbsWMHTjnlFB+m7tJLLx2qvaEB8z333DOHYT73zIdzS1fbSZLB6/InRJV8JzaYPQX6xCUifLfsHQILzMtr3kbCKjsmL7pAGZvsl9n5UrtSeVYwrZdqlT2jrGJ5BjHMidzCSB2zzIx9th0ksoRcWco286qzpOUlBnpgPf4HnkuaXz7GXJIOn9TExOy2MYFltg1FLLwAYDIMW4Mkc3IMI8J1ItPVCWN8Gm1T8DHEx0HXE2X6y7HADRkPS1ISXUc8jrYxgV3m18qotsgZ5kceeQRVZXnIb37zm631FgqwPhNzes9ITLK/m3egg/R64cqIrKSCWzPxRzuLzPfh0oc2bTMQs8pp1jsdsbntbVAsY9tG83ehjcSMCbKLCqVvVzoWuUqdnGElHpJJNSrEoeFSZ8Cc417qtMePGwB6uoyY5PTYqZwnH9EQWfkFl1zUTnLRVzF7bRnl4MzH9cpVXTSSkGgWGo7KyIHPeIY4MMyWWYZnmwWFkEsZXK5p5swx2OeEXeaSDCBhgjNyjayvU4NBzmwDbTPN/edrCzj3/sd//Ad++7d/G08++SRWrlyJl7/85bjzzjtx+umnAwAuvvhiTE9P4/zzz/eJS+666y4sX77ct/HJT34SZVnirLPO8olLbrrpJhTpivFsw27RPf/iF7945jL97Y8WebnyizGpA7AfDgfIiY6Ug92g83DbXDQMHgUjlmcw4MtBso6BcRhXAL6R8176nRtz9IqAMhDAsdIAj5kcAWaX0jpalmegmcYmpAXNFOw0d3Nvc6BLAe0s4EsM82PhbXpt9ADAYVrGTNugMTAyh4uCERVT3GXAgmkai4TLzse2CWEz9TmnP5LlyNrFRCY9uzIh/XVBkg6+vBcmVQ+WdfLgxcYdOYcSWObOolyTTq9UijGWZMzLOGDd3wmJNquMRN+BKSlsGmgvVXDfyQYCWp5pLnPbSgEuby8f7zgATKrDZRqkKY5jECMC6hy4kwyDwGWRAHoCxjSuykk8gpQidhAsRDoXNh0I0xTV1HaUrpo/CJhmnOU0dTUA/7cCgFoHvTNplcmhLwBjGYFmAskcNFe6iHTISgvkUlvb25L0OmUAXoLhYytzCYarE0swGHgGbEISKmeAOtUoZ7XJOeDLJBRp/Wi+1XaabovbDCS4pNGW8WUD+xnFFnDuHbRSBlgCYNOmTdnoGmSTk5O49tprce211w7fMTOK8SyEwHve857IOVEphW9961sj6aEXD2AmhpldfJExsMH1R7QPL4+fCuOGCNwE7TPtR2Ux8+dBsmbMXsoI53Sl7DNplk3CfIZj46A3AdccEBEoSsEyD9dGoFnEoBmw5UNbrupcGOE2ixhmN5lywDtMiDn6G+Sc/4Zl+wgMO2bag2MRbzP0Evyas5kbKZmIHQu8o5/hYDla8SAgbPxDGJBOyLa+rFS4rgaBZdK40yoEZ5rnaYtdkrEYjNI2A0DhVqN4Gmnu6JaGceNtNKNNNB3zgBQ4x6w0AB+yDbC65NS5DgDa0kZzQAwAM2YiSiRCuuNCaFR6UHQMC35nTKdxvioddMMc3EphrCOeidl1AtwhQUhgcsM2EbWZPhgQ6KXzrmABJZXT+IlNTjXKPuoFc+hLI1/UqmiwyVmnPnLoY2HiUqDso18oEr8TsxyAsgfGRHRpoBkhg31GQqh5PIAmYNVo4IgU9AJsfkv7RBOEN8sDWBbJtn1hz/e5d+XKlQAAYwyWL1+OJUuW+G3dbhevfvWr8Tu/8ztzbndRAWYf/zgCjPHFG5bAHbNHIeGSizVimHlbykT7U39ZkGwCsInCwJERSPaMHvXN6vHICFHItJYrvI0RZMvrkcwiZX3dOIzUDcZXZJYTc+PwjHRabz5LzxkgPBRQ3kfL3YbiLWdBcmCXfX8ifcABYBxQZlkbqU1dBHbZX0uIr0MfWpCvVACsLnsgq3V0bUVgmT+U0YOT0vF32j5mmMc2wGoG2jSfHwQBvCR2MQE/JlMgs5EnTMQc50CxyrRHeLXPmOR+ksXOZuALoDh1DNQGDca2ShzjCmgvk6DrNZWQ8PjH2khIoaNxKAgUjRVDdw7YOUzBMo+RnItoQX2HcYRU4NRGDfagkWGPObMMIES0YOyyjZ8cSy8q907Z+ShEHAFlEGim6BdGRE589B5l62OZ/DxLnHy392ThgW/KKkfzaGMFecBnxOUAvFNfuq1NepHHFDRPszLk683Lnudz7+c//3kAwBFHHIGNGzeOJL/I2T6g9MY2trGNbWxjG9vYxja255bty2Qni4ZhlrWxuiwTP7WFJ07SiiYMszLxUycZC/Pl+3DMHzGDnlGmd9pumqxylmH2GmfN+szUA0DJMQbabGyqZyDpfUiJxaB2C5Gw5iZifj2bPUI2PtGmLeaWtsvHOsxnsjTpCTNiihvssoy3A/DyC14GY69PKHL0YysSgvZzcg6W/TG6jt01x/eNtOtc0qOMdRRNyzm7TFKMNs0yvc+DoX++LwuOzUkydOY2k/wtNaTPThfMfufShoqFjUt1x1Wyt9cTC8NY2KD55f1RO5XOSSiC9U3Z0AHHx9EMa9dj0gvSFkeschIX2bZjfH1i1TmTzDMAUhnQzLwHoMFek1HWPX6ucoxy0Dm3yy/SUHHKl9mxcWZZ0zYWJg5ASECinPzC3Xe5Ux8xyNyhD2BSDLplMb0yrSw35BcJDshJMiJHQSTMMeL9+b68bgNvAI2+41XAjOQjw1bPxxbL3Hv77bfjox/9KF75ylfine98J37rt34LBx988MjtLSLA7PCOv+gYECYnPfrR8G11ACjcmsspFP2iHSCnTnoRSObbyXg0Ag9oMo5WQiDrmDaKDGHYRBTa2PuZlxwM4cBnEtCZgOc52VwA9iBHxJyT4DCWA9DUVFt/uebpGnNRMbwTKK/iImLED28EbNkk6yKwDHW9KV6PAWVeplVTszwfCUbm2J/Py4Jjg9UvM8DIwW+a9jktJ30wT7qRaonbomYQSJRCh3TbTpvM4xfzNM9kqXyCl3HnujjLoAXBFWKZBwFjDngBWJCc0TdTOuwqOv4wTjo3BIz52GzWvTAeLrfgAN22lQfDtC932qPzQEAaCFIM0jUrAr3Moc/HWFY2Sx/JM7xDH0W9YJIMklj4ZE7kwOflF/BAOdIpcyDLdMwU6co2Zt9as/al7WQAb2MfIJrHWnXKbP8G+cbn8wwoTjXMOTwyZ1skc++//Mu/4NFHH8UXv/hFbNmyBRdeeCFOO+00vPOd78Tb3vY2TE1Nzam9ZxUwX3/99bj++uvxox/9CABw7LHH4sMf/jDe9KY3AQCMMbjiiitwww03+PAjn/70p0cK7i9r49OERjplnYDlxIlK+tk2tBUlgiDHKgMWmSAPWBrfeZlKgHAOJHOGOTo4GQ/QZwJADN6KAo0wb1xnK4Tddxh/Lg4WCXSmfXG2MtvGEP2MYoOAby7sXKQtJiA9oA1j2vvIlPtU2W6i5/dNf+3VsaMetWUKG1WDmOc46gkaD2iCO4hyp77cNQg0r6lUt0yfcxO0cEzQqLZIJu3FbD3TAUwngGA2T83oTjZUWwDIsT4YsGCuYteBTc4RW9RewiJzkJwLTddIGZ0409k+hTu2JlNs+2+yzlTOnQRt+7HjIzn3pechzRpIId7COEUDJBMwtmMLkTRyDDJnjwEHiJNQf7UDxakzn9LhfHOHPq5VpsgXxCjb9ySdtQPLPEsfZ5SjyBcGgArRL4CYZY4iX3AQmgLhHGBGZjtYOWengSYwTvdPywB2HCY+prRe0lbWd2oUW0Rz77HHHovNmzdj8+bN+Od//mfceuut2LBhA37v934PO3funFNbzypgPvzww/Enf/InPoXizTffjLe+9a145JFHcOyxx+Lqq6/Gli1bcNNNN+Hoo4/GlVdeidNPPx2PPfZYFLNvGJN9A8mYY4pxC+6A5y9KBiwoRXN0ARu2fMMueHKkGgSQgbyDFS2Bc0vjI6fL4kAeuHGgzAEgjyccnRz3RE/ppaVb8uKgl/fHwSTvJ22Xb5sNPC+U5c7PsKxyJuKGL58FUNuHIEeUFABl+UtjMkuVhIBz58nHWxYWZMtae4AMsImTnPsMQpg4YpA9O2xieQYQrrXcCgY9vHGgnZ4Xv6ow+t9zrnB7HtB8bM+SVaaENEUWBPMMd2QcUMfOeyFeMbdBGfu45UKx+TYYaxy1bWTEIPN2PAjWHfCQeY1+M7GNqS4/HnKIlAkyoXo1CIyLCCwHuYZwDxMxMA7nKXbuS0FyzaQoKUAmuQWFgfPfmRwDgAfJHDAbWGCslPTgODj0BdkFnHwjctjj0S9cRIxIesFY5lwGXiApixwDE0BLQLsNJKftIew7m+TC1yFsgfy2tK1s2wynzMcW69y7dOlSLFmyBN1uF7t27Zrz/s+q099b3vIW/MZv/AaOPvpoHH300fj4xz+OZcuW4aGHHoIxBtdccw0uv/xyvP3tb8dxxx2Hm2++GXv37sWtt976bA57bGMb274wM8JrbGMb29jGNj9bRHPv448/jo9//OM45phj8IpXvALf+MY3sGnTppGcAZ8zGmalFP76r/8ae/bswWte8xo8/vjj2LZtG8444wxfZ2JiAieffDIefPBBnHfeeXNqv6gMCno6oyxn/uk176QHwMc4jpZQgJhBpu9cF8pYZr9fKquIlsU1Guxf6myVbpcilKdSg7RMwz4aa4no6heOJSxYXGUTHpV5pr8orrHMMMq8T3rPjW2QDcNAt8oDBljab87Jj7PxvkwGNrmlD7oGbKxQYx9DtY5Zd0mssW3Ha94pZjIQ5BpsP39tJvX8eSDWgurxcHH8egTiFYw2GQaPtZxbzSBZjxD2mjHzYJg5IzNk/bHtX7ZHT8CYojVDXsoQ87BpuZjKNiWIQc4pL2WRfXmSgISzxpxV1omUIu2fYiRTm3Yfkd3X7s/bbpufZMROy+Qir3URyT6IQdYQkDA+DBwfG08oEo0RImKNc3GUqa5h21J9shAsnByTXvj9vENfU6ucMss8dJxnThUr43ILL6UMUo3gtM/KkZS1aZMZU9zqoJd+B9sPYXta15dF381gJplPtdnt+4ZdpvYWw9z7mte8Bl/72tdw/PHH49xzz8XZZ5+NF7zgBSO396wD5m9/+9t4zWteg5mZGSxbtgx33HEHjjnmGDz44IMAgDVr1kT116xZgx//+Met7fV6PfR6Pf+dNCqyMiiU9gAjGxcZiEEIA7wAYvDRJrnIaUR9uww0A4i0ybwOGdeSwoFXbk5rLFJQpxRbMkcM9NI2hHQvxHV9mmThJAWmCRyjdk2QXrSlyB7GhnEeHKatNmA+SDYC5KUWqYOfA6h2n/AwIdyxGy2AkkClgJESRsoANP01BpuWOh5QSNfupRbMYQ9oXJ+RY59Pa444ugofO717gDxA+sPlF/ReyPAgkXt4GdbmOvnvp5P2YrC2eXfadABdeqkBz26Xz2gXA19uPAMdd/RL4xr7dljWu9R4FjwOwAfpjHnSjzSucQ4w83HwYwDQkHB4oGzgk7Z4qYWLMsKd9dLzUpsAvGdz2kvLFJNjKAaoA1BG5MQHBPlFrYJEg8bv4ymz1NUeKANWp+xBa9iPHPiiuMotEgwYnlcBvo3Y+Y/aYN9bwLGfj9n+QF4u0QDMKQj2YzHJd7YP5vLdRGOJ0nOPaotk7j3llFPwuc99biS/t5w964D5JS95Cb75zW/i6aefxpe//GW8+93vxn333ee3p3nA23KDk1111VW44oorGuVFT0EWBALBIgZkwIftiIFeN5aUGU73ccC2UQcILLLfLwOkgQAQXZlxmfeitrgJYTPsKQecwcCd1jFw5Gwv/0z1ZcnYZBmDJ4mm9pfGk2OaR7UUbM8xffbQQHlYM9qCQ9J/584hA90UTs5IGcByaR9IjNtfKsTXHuCSmtBEaPwDDF2nIgW9OYdSrQPDzK8x2od/prTo/jP7W/NzRoxyQYBfss8CMPPM+LefTsRji61t3u2bEl0j0U9YX7KcY1+agCSOLoEoGgWBUZ7UhMAwWRqFYlCqaD6mFCBT3bivJmAmEJ7rn8ZQp+fChG19t39Oj1w3wHJTkww0E4rwcgK3nEE2DESnADncyuIyY6w2mVJY+zo6vGyhAFQAyRGbTGwzd/TToTwCuwmjPLRDX07DTNvQ3oavy+uwv1UeBJvke/NvPJxm2TS255jtednzdO698MIL8bGPfQxLly7F9PT0wFTdW7ZsmVPbzzpg7na73unvFa94BR5++GH86Z/+KS655BIANuj0oYce6utv3769wTpzu/TSS3HhhRf67zt37sS6desg+xqyUOHCJAcpIAYdKYAlywHqXDguIGaQaVtUzoFOBmS7ul4OkYLp1Iz0wHmoMG0RmNcA2DK7MABKROx3jqnm7QzqY7Z6+9p4Gu90PDnQnDLjxCZHYyam1rVJTScSDuMYZc4s2++uehpmkJp2BL+h/0nawYEyq591LKUVgZRVTh/cfDtJquv0vHHZhXTLvRwok2xFZc7pkLZYlgUXg7XNu33dwV5dZllebjwMHMkycuxwAQMfjYKBYx4eri1OcspKA4iidBTuAuPpokM7MTjuZ7LhEUvMP8fH2KzT5jDII1SkoDhtk+9LkovayCg+cnBSZMfEYiW3McjUBwFk78jnAK2qizC1kCwj59CnRAQUG0CZg1mVSC00B9IM+Cq0g+QEMDfYZLTvM0iW4ccYfTcR+ByZSQZAhF747uokjobztefz3PvII4+gqmzsnG9+85ut9QYRr232rAPm1Iwx6PV6OPLII7F27VrcfffdOOGEEwAA/X4f9913Hz7xiU+07j8xMYGJiYlnarhjG9vYRjV+Mxq2/tiekzaed8c2tv3Insdz7z333JP9vC/sWQXMl112Gd70pjdh3bp12LVrF2677Tbce++9uPPOOyGEwIYNG7B582asX78e69evx+bNmzE1NYWzzz57zn2JSllWmZi51EEPaLLM3FolFIxNThhib2l7xgR9clI30innMu61sbVu7EZqCO2YzbZ6OeOxmAHLAHgZgpMlRO3o9nOU9pfTNM81vNwgljobWo+1T6wpb6NNfw0E3TpJVVL5ShK32kgZJCs+drItM0JkWeVIikFDMjbsnOCrDlwORGW51RDFji2nifcrIq7BnAyD66yJRS7LcL5SdjkZ/1ztmWY5rrrqKlx22WW44IILcM011wCwD+izxXrv9XrYuHEjvvSlL2F6ehqnnnoqrrvuOhx++OHzG9AisBlTAMZpcFt0vjxhCY+bXJkikjZQQg8gMLDk7NaIn+yYY0pyUgiDGkWkPU7HU4M7BMbbKy65MIHFpboAAGO3SaFjSQbXKrtycuaj/Xi7uXBwvDx95/VysZJJchEc+pqSC2KPqd02RtnXcSyyVqzcscmeVWYMM4WFC6wzmnGVnYZZqPA9kl5wTTLT8VKYuNAOYsaY9mfnepCMY2QHPrD9Wd38/nwfE48JaJVfiNz+I9jzmWFeSHtWAfN//Md/4Ld/+7fx5JNPYuXKlXj5y1+OO++8E6effjoA4OKLL8b09DTOP/98fzO766675hyDGQBEpSFVbb8YAzhnqzjKBQOBXJ/Lga3JgNe25e+oTtI2l1wMawSyErApuIMfMFKa6QgURvIMIB99UAYQZgcVQLoxABzgTsHysDKOUbanxh0Ygaaem9dpk2yQbhew59U7vzVlGB44cxDME4lkjkEAdglT0qSZgOSGlCIByil4HhRfmcuIvHRDN4Eyd+pLrwl2bc0HLD/T9vDDD+OGG27Ay1/+8qh8mFjvGzZswN/93d/htttuw+rVq3HRRRfhzDPPxNatW1EUzZi/YwvW1x0I3ck60wFBmlAIjUp3ojIg5FBKJQvcCa9NQsGNZ+Wj9nQCvv2+iS6ZSyGCFjgF6LZcwkA3wHvzd2J1zOH225BkJI55vK1GmQPFfIwcJA8CyPw7wABxxomPZ9/z9ZX0wNMwAOx1yqRj5hpk1y534Isd80JZ5ODGyqJ9EoCbjYqBuIx/b5V0ILRp62dAcmvdAWXsHtAA0hnpRQOs5gi9sT0j9qwC5kFibMACwU2bNmHTpk3z7kvUNSAKxjAn2uG2tNPccs53OSDEGUJ6d/s2dMnRIFsAGyUQScN85Y5zrqmmc/VnixzBw94VBIiL5nbBzkN6zLmkKK0a7Qy4HbQ9Z4PCyvHvnEGlc0Mh95jzGzn3EZD0YJmac0A5Gh8/vFQH3eZYOgg858ByG6uc2w40w8TlwuilYHlfAWV+oxu2/gi2e/dunHPOOfjsZz+LK6+8MjRn4ljvgE2etGbNGtx6660477zzsGPHDtx44434whe+gNNOOw0AcMstt2DdunX46le/ije+8Y2jDWqR2IzuwDggzJ3pIuNTJ/0wDCChs4lJUge8Nse7NlOzgF7/nbWbguacA2NOo8z1ybmoGHxbm5Y5DfmWhn5TaYIRY6NptAHiHINM2+yHWMPcTDhCO1htcgMkMyDcyMJHdfl3Ar85pz4EYNwAzHxfxGWRTpn2R8LiDgLKs4Dk9PucAHIyj80KkhcCHD9Dc+/zzZ5zGuaFMtFXELIOgEE57qINaAABKLSwgwDy4BhoAuRoW0YukJoUHvzaNlxdrSGkbLDMKfsXhQLzYzX5+MlkxLLOsuQu6NdM2QPT80KH5FPGsnOSxpvm+7YBYj9+HeqldXLHNEzsZfrMwSBnV7lMRSbAON3u/yR8gmw5FgUYx8i3yi2ojG/jpgmYs+s3txrCV0/Sa5uOXRZ5QEznMHPdCMOcDEewUZcF03Sms+ln3//+9+PNb34zTjvttAgwDxPrfevWraiqKqpz2GGH4bjjjsODDz44BsyzWE+XgC6zoBZAkCU4y8k2KA5xyhDXhme/a8oZBllN8Yxb6usGGx3kDm31LGssveyCxz9OgXHURgv4pncCrjx0HI9sAQBKC88iKy2g2VhzoNm4d/jpJYmGoVjdNH21A8TGIAK5YO3xqBdAzBx7gOmZYBGB4IYzn87t0wKEOVAeVC/5HJhp47/7OqN8tycvC6T9+UjK20Bybo6cb1i5sSRjNJsjHTm2sY1tbPvIzAgvAOvWrcPKlSv966qrrmrt4rbbbsM3vvGNbB3K9JSL9U7btm3bhm63iwMPPLC1ztjGNrax7Vc24ty72G3RMMyo68BMUjgtAJGecxBr2cYUMkZvVoc9bm2h2oDALlNmPRSAcO27YxCcjR1WbhCVJcxh6sQGtD5OmZDlJGZDo0qZskGOk7M5EeaOc5ilqrZzkbKppEXljHFOhsA1yuxvMPQ5SPvI6ZBzkh9uvG7kvEfnNyOFSZl8yVn0FhkGWZsmnvc5is11InZ1n3jiCaxYscIXt7HLTzzxBC644ALcddddmJycbG12rrHeh60zNmBGldCq0+rwBwQGuc0oYYf/nslgxzXJ1F7K3HIZBGd9Q7uiIY1I4x/n9vHSCzS1xfRukv2EML5soHxEx/3WiS4ZgJdZ8Kx7KZtMn+2HJqPMnfRaWWWgmZmPa5R5OcI+vl6DLc5n6osy9HF2mEszEuY4xyxH9dLxsO1+fye/aLDQbN+0bBhdsh87MuWD9k/q7lMbce5d7LZ4AHNVMcDcBBlpFr0oex7QCgz8fmm85EFgicBZCxDxfUeJQlzWPQ6cyZh8IyQhSRy5cv1lwHLYhhagnbZhwUPzeDP7slOcjWfdpk2O2kjrJA8kg7Th6TmKtonGOZ01EsQwcoS0SnpeebQW74jH6rLvjXPGr7NUguHLMmB5kF6Zf06dG3NjeBZSY69YsSICzG22detWbN++HSeeeKIvU0rh/vvvx6c+9Sk89thjAAbHel+7di36/T6eeuqpiGXevn07TjrppOEHv0htWnVhdNkAxIP0vOl3v08mUUg2NrEu8u3rJghO02y3gWgOegns+iyB7CJOQTDfLzcmpaWXuBkjIiAd9m+CY/s59GclGoDWMiu34PWFMDCuvt0An8o6ANAAjAlICy1CpIlIy4wo4gUQpBYeeKq4Xlu6anfyhktMogNIDn1m6qXtN0CxadZN281+N9nt/hzoTFkEhk1zWw5MZ2y+EomxJGM0W0SA2THMaXSKFmBrhEFI5Tm4LgGXhq4YgEiz4wGBOWYaZZFjfLkHPgEqYSAoQkXOUoY00SQPYpajMQ6yHIBKdcVZsM1vLO6DFkETHW0YYG2pnlPjY0vH1QD+zfIsUNbAMI/bEbBsA95egxxH0vD1Ui1zTqsMNM9HmlDHD4pfD5koGNEBhHLv4MidGNscV+diyQ1iqPpzsFNPPRXf/va3o7Jzzz0XL33pS3HJJZfgqKOOmjXW+4knnohOp4O7774bZ511FgDgySefxHe+8x1cffXVcxvQIrTKFIDqNMo5A5xL5kHGk3vUSXQN/p4ryzG3qfPcIJCeZsQLGxhQBaL5KzjVxWOJfq5JJkAgBv20jTIRRtpiI5Ix2nevaTbhwSAwyqy+BgwCOI7qeMA5S1Y+AsyImVOR1ImYWOcc6BlfnWxnYFeq8Dmbzpp9HgiEU6dBoB0o5+oh932WxCK5fdx+qTVAqIn7GWjP8bn3+WqLBjCbqrJ/80R+wUGu4DIJKUNs2wGMsd9fsV+MFBAUfYAbA888moVIncx86LIkDBpPV50eiwfjQ4QICx0P/s7bHWQcLLc51rXtI02QeOhZ9iGTCZAkSx9sUjCYY5YzxzgoXFqrE5/fmf42rN4gGQdPZe22N0AyfU5lLL5Pdn2moRF5v2l6az6e6CDD+TK5eN4Ryz/E36vFRJuUZUD9udjy5ctx3HHHRWVLly7F6tWrfflssd5XrlyJ973vfbjooouwevVqrFq1Chs3bsTxxx/vo2aMrd1mVAdGN8OncaCaMr+DLA2x1rrN5CUXADw7TGVSGCjTZIB1BqDS/rzNFGwTIyxhGum3aTufMjlzbd/ppy5QKxl9530HbGUlFFHoNwaIImY8YpKHBMnUmU62oQUkNwCsYLGVEUkkhnLsAyI5BvXbLq1IxpICaQeUw/iTdyDZbsJnvm2I6BZZZjYpm4uz3zDbhrGFnnufr7ZoAPPYxja255g9B1iOYWK9f/KTn0RZljjrrLN84pKbbrppHIN5bGMb2/5pz4G5d3+0xQOY69o9QWcYOmcmw/KZyDkwc9U4DafRBkJaGYVnlwc443kZRsos83pFsn/KOOZY0lSGURRxso30GBIpQoNdbZE6NByecqxmyt62sZm0rxzyV6ntOEVK1eRsELvcMiZhTCMDX6ul11MqgeAaYK9JDlrlRli2nKSi7Zo1yepGpIPW8fVUyBA6LtVr585huiLBHQ3JCgmI0UHjs6Gju/fee+M2xeyx3icnJ3Httdfi2muvnf8AFpn1VQFTl7EjXYYZbtMtp/XaynJSCt5X23YAqDLh4uohJBXKWP2x8nViNlohyCMa49ai0Tb/uaWMsknH7be79lwCEe7YFx2rgV3J49sTVhngrKxgEizMziw3WGMRM7cKMQuc6pOByNmvlSnmfWg+lkx9pOWmUda6P/vDNLTFiTa5VdNMNohRnsN+Q28bwsYa5tFs0QBmU9XNMgdABIEp7QAs6ZE5UGHAmMzvJ6TFDYW0so5UfwwEwKYZ6C0Q6mZ1thnHQwk0YhnzPmjJnT5Lu/ye6lBTEOgB4myBBgdphjlQpu+DZB2zbR/Qf0OSkWpqOZh22vUo1XWbpdrslv59n1SWPjC4KBRpQpPIyY+3wdsfJL3g9VJNM79mc1KMHFhuOx8E8nMxoQF/bPPK9pfciIaqP7b9yiotYRInPG45IMsd3xr64BZdMrc4PnHe2TCXJMT/5HjWPsSyjOZPJYDltO/82Nx0pOOkIamlES3SMUaRLQAYJZCCZZDkwu+MBkiOZAaRjhkBRHNgirheDG5D/w3nvEHfkZTlnP3YMQySUeQ0zB4s5+pm22T3+Nb26HNSF6x+dO7bJ6+cJrpRPmifUWw8945kiwYww5jAIKebiB0GArBK6wrpAYtInKYETxCSJgthgFcICSN16EMmDHBqRVJOvxLujMjvB1HyDeHBkikEY5mNOxdJX23OX0AMBjOAO4Bt/mtnYHU20DzIUhDM+04Zd/6eOx6qm4t+Mpd04m2Jbqg/B04NX2HgDG26ShCBXoNs5IkUqFN9noCHHzvXsgNoZHTMnS++OoGW8ww0j21sY2uxnipR1Z0oWQcBUZ2AzFxSjzRqBNUjS/XEodyVUSSLTPrr2cCtAv2sRGs/Qesc9msDz4Zvz9RPjfq2XzKgmWXg85pk6igCYWx8OmaKkYJsrxmOxyjSqBgR8GVscm47EGmQowgZCGU5VrgNLOe1ybljT8ByCmbZuAksD9Iqt7LJOaA7jB55SIA8tueGLR7ALEQsIyAAwcEJW4YmB0BD6Z8BwAiI0gFkzgrPEn6OR8CgmMqQAihL204qvWBjbpUPmAQsp3VICuDAsmc6deJUlrTbYJo5QDZuFuTREiL5Cn9QaAHPg2yQvIKB9WjsuT5yf5c2GxYoU39pxrx0DO7FAaVQGaBMplQAySnwbgPJnE3OgNnsw4LRAIrmPkbb30KRnLM2BpweEumGUT/zYeXGtv9YpQqUWkIl5blQawAa9YCYDbbTQMwAp4A4Bbe5Nqmt3D70PRehAgB4GDhq27S00waMPRiexdGxGTUzAFc73xJ5wisxgEyAFgRiE4Cc1JvVoc/V5Zn7mgx0BmQy572sMx77HO3LxpjWHQSWIxkGbzsFwxxgRxdEGG9c1zT3QzI3tUkskraz+w4b134+8e8xnntHtcUDmMc2trE9tyy56QxVf2xjG9vYxjY/G8+9I9niAcxSIHJQ8npbESQSwoWDYxKJhpbV10nYX8faecmF63OgY19ZxI5YrJ1IFpKwxrOZybDSwrjwbRIwguI4Z9oj7Sp95RIO7Vh6ocP3aNmJM6c0DhO02rnx8X1T5jasqzYlIIwJb9Vjp+3zNhsVBkhRgMDwpk56KZvrJA3Z+Mm5tpWKGV/6G3OGl/pNWOU02Q4Au4KROx4u3+D9MwmG13q3nYP0Gk3bnKONWY7nvyktoVXhYwun7DCQYWWdEZPL5ROpUx29p2xxLrMet1xykLZ9TTrGhlY47btZlu4bMcCuDslPIhmKQfQ56p8NMFrdM6FO5MQXsalxO03HtoRZ5oyrG0OkNfZtMomDRqONVKc8kP3ln02z/cbYkzb8Klhb+xmGuDE+Xo/aSxl1ti1tL3eNNOaxyE8lrdzcf1/YeO4dzRYNYBZFASEysZGNA3SAl0dEWf7S5W4pY82xBzY2GrvQVqccZetr6EmFlWGUZVxO7fGrk2QGuWgLs4E8+u6lCoVdehcCpmyXgRgmUzA08RgDoZwO3HlQC63hs/xloigI5MFr1B0DyqJuiXfNj5s/dNAY0+POnAN/QxExyG+1FLCmGuHMgwaAcN20xUOm7wQ2axX2Tx+IuPxDKUBpRJklU8s9xAE2njg9vDTqy/w1mI6dQLxi54KnmB/Fkpv0UPXHtl9ZXxUolP29plOm/TwILMcyi7a6ZG2OefbSb+qM05jGbXKKVEoR3A7ipEs5vXFjPASAM+eA4tEbjpIaYJmVCROlqnZF8fjbHPkygC7SI2c1xWHcg4FlE8TmAHIOSHsZBm8HmX0z/WStpbw5VjMcWJ6lvK3vhuyCR6waNK/ltu0LED2ee0eyRQOYLThNDjdhzwTpiSOnPXrPAAveDiUVkY7lI6DMQ7r5Nl0/MkkoQjpdzjDm+kvBNx8H3zcFkQ5wmtJFNxBhf8NAOJ/vhQGMMRAaMKVtRxCIrIUH0pAusgixzgSCk2FEgDXS5LJjoyELEQA+abBTfXCmjUb7QgRNtc6D+GzUDd4GjS3n7Mb7ye3H2/VAU4W6HCxzIEpA2RgYr3VuuwPw60vmr4X0gY0SmPDrj4Nh315yXqIoLaMzzMCYuXi+m9YSRhUNZz6/PQGybc/XBFAHWS6pR7qH4XWjn2cebOd0xhwrGYjY3YB3bFgbbOeGkx5MZqSIQU2qSwYAIxNAmbLM8bZW3W3CPkeaY8O2g4Ff165In5cZiI0Se6SAl9fLgV5envmeapjj42HzOd8XyPeBzLaoPcPORVzeuKxz4yHjc2oGLM82Fxp+ueyDeXM8987dFg1gFrKAIPkDEC1pCwIO5MjXNmvn2DsqbwCSogmIKdIGgWXn7BfFFE6c7XxfGogyxrl+onBxbewpOaIVlmE2hbQAmcCxHx9iBhvud9kAonZMsrbASmhtQbN7Nxx4cUvBJxsbJN1DhD8nEUAuRAD5bgxeZkKh2kCh/9j5pH7pb8TxbmOy56CQA8YknTgByvR4UoCcHj8HmxQ7OQXLKgbKnlVWOs/msgcyH/87rcdXRKg/7rTKQXLqfGj/GDGI5tvnxTBnztFs9ce2X1mtBAot3CWUyA1gy1Jw2wIfBxNxBOpEXNHQd/eeC9Hm948aZAB6UL3cuDIDTQF6DMLbt/n+c8zwIICMZB8OhmlbCkZZO4I5Bw5yrkuPl8B2ljnOfG6A3kyfKbBN9xn0OQcKmyA3AN+mzCQGy3yfuI0BfTRkbgPGMsCorhH538ecbDz3jmSLBjCPbWxje27ZWEc3trGNbWzPvI3n3tFs8QBmYnU902YgiG5Ms+GRpfplXt4mfaC2aKk7jX8LNPrJxrvVCdMn7NKgEG5pTsTOeXQoRovANHO2tnC6ZWlDzQ1ilo1ksoyc5tuePpjCyjOElo5htmyzz2BHco3MmquXWyR9RMxyi2zELvVZdlk0zpHx7QzUKufkG/zvTaH+2Hn28o9B+uRGP5ye0qEfrnkWIrRJzn1ah1UQYpfTY3XXbOSE2ra+7Zl8YSVBNHYgdjzMrQJQ3dz5nE94o5S1Gab+2PYr00ZAOFlDVlLBWN+2hCWDrI0xHlQvFDYd9LJsckoQDpKGZMfQIrdwYwjtNvcXjTBw6fd8ew1GlMqS9vKyBzGQWU5lDG3SiSy7nB4/b4ePM22fb0uPGWkdk/87ZMfdZJdDHcYuj2otDn15zfMs95JB+87VxnPvSLaIAHMBFO5wU40wTxvM49PONTcDl2G0Rb8gAM2TjqQgOU1eIYJ+124XPjpEFDECsA6MJFWg4xMOJJfOoa9Fw2tcuwSm7Ts8uLdzsdXC+WQvxuqbBckitLQgWtl3owxEGklBumQqIpFZ0HgBLxmJjEkmQhIQBmR9+/BaZZHuC+TBMthx8ux8/O+n0IzDnOrJcwCc/pZUlqQjbwXLHsi2O0NGbeUmXK6jJ90yXecExv2DwAA9chsamYeGWWg0NZCz1B/b/mVGSRgdxzDOxiO2W9mec1x0zjja8Z9EQ/+LNhCdbPffubZj0DhY1ZZ2abxNTTInUdi2hpwjaS+jT47bENF+rSCZf0e+bmqNtnSzPJVx+FjM2WNpKU/6b9MkN8bG6yafZ227zWYB0oMcAIVpXKrZtvMNz1uIEZoaz70j2eIBzBSxgj779NQyAF0gXO0KduKbDRBwJzBiJVMttJ+5TWALhUCUAARoAiwASMPSJRrjbMSMjOOc4funRj9mONBcuB91EUBzKpdDIdzEJ2y68FI4ttmB59KCQ1kboEY4VkmAVDR11MlkETlXaHeeDCx7DTTCzWUtBdONRCzhnBGIbzjNkUabM8vp3zft03/WcdmIYNlo7ZPp+DHysIUp4+3rJKsdUviIG9A6sMsD2fhkG19tmY+2LXdTnK3+2PYr01oAik9Y/NpxD6htAEMk37llQGkDADtwbpL9Wxni7PXFweYgZpl+16ZRt/X4cgCZjyPRGbfuy28XCZBO928m4kiAcgpykZQ1xsj25WNIy5M6fN+GtQDjYQBq6/1gtrHMZsk5yAL2ZCw5xz4jcufhWZjYxnPvSLZ48tsWMryIbaNMezwCBr2KJLSc0uGVtlmWQLdj2yrLuD1fh0k1tAHq2r6Ui9tMzCO1Ry8C9GUBUxZOViEjgGccYxu9SmnrElieS+pnbgSWiamW7FUI6ALQHQHTETAdCV0K6I6A7kiYQtp3N25T2jJTCujSOR96J0QRMfKWpbah5kRtIJS2LwdePaMNtE44UQQNZTzA9uWCnb9OAVOW9r1wjoYElmsdP+hI9/ekv23u3OZSXKcPLZ4lH45ZNvSgwKRFxrDrJ5IQJWDZNuCuOwVUlX3VCqauYZSyr6q2L/quFIzR8Ytv2wdxmOfyGtv+ZUYLGCXCO39puJdovgz7rDLbkzKtrNdwWhbVdW3CJC/tXmm5C59pX/Z7Og5fRlONTr8jgBODqK/ouo5ejKFIt/F9GUsY/T78+MN+VD98pnGEdoj5FXTMhpXxtnTL7zGtlwOoCTAH7CNJYwbNgfNMW8PUH8r2HXk7uJv5zGGz3O/mOo6FmnuvuuoqvPKVr8Ty5ctxyCGH4G1vexsee+yx5FAMNm3ahMMOOwxLlizB61//ejz66KNRnV6vhw9+8IM46KCDsHTpUvzmb/4mfvrTn8772Odjiwcwj21sYxvb2MY2trGNbcHsvvvuw/vf/3489NBDuPvuu1HXNc444wzs2bPH17n66quxZcsWfOpTn8LDDz+MtWvX4vTTT8euXbt8nQ0bNuCOO+7AbbfdhgceeAC7d+/GmWeeCTUPkma+tngkGXxJGgiMLmf75mJcD8qXyrnxZCMAREGsJf+D65jlJiMGtJCD4xGTxCF7zJmy1KErU4cYAKMMBISjAIwLZ+OYTcY8k/OEcafTkOTFOfWZIpGReKYVsXOeNl7WkeqU7bgGPGH7NhizDFhmOd2Xzh0/p5TIhZwWlbLh6jRbVSiL+O+Zjocz2jl2uTFWxi47fXMue5+h7XTetLbXi0tIYqCCPIOfX+pDIjj0kQyDwtW1xXZWs/wevIRmHmzHbFKQXP2x7Vfm9csDLpXZtMTIioJTSx34GEObthmVMSkFmuUmtz8vSttqEalScZ4dHXD8Jq7TJgXIOQPmHO1y4eJ8m23SDiT1ODusk+2Z/RpjSo8x1wf/kyd//qysAWw+HsIabbC+DDLtt41hyLENtIwcsX3g+4hlXsC5984774y+f/7zn8chhxyCrVu34nWvex2MMbjmmmtw+eWX4+1vfzsA4Oabb8aaNWtw66234rzzzsOOHTtw44034gtf+AJOO+00AMAtt9yCdevW4atf/Sre+MY3Dj/2fWiLCDAnS+eDJAqRA1lhZ4VIu5roikm7nIuqYZz7nXfmMwysMsBNsgmmrSb5RQ4k56JItB4DfTcW8HIfmzTuso1w4erS79itmQnAOwUKtmqYTryNe48UmcnRNuyzCBq4TH8IkTYiLfBgkGz7ZaAwLQfCg4d055bOJ9XxWmUVNMtAeHAhjTP1TTl502yAw0SO4ADW7RcBWKZdRu48ZOQZ2XNDDxxKNSNv8HbaJsTZHE3mscY416W+sSRj/7Mgg5itJn+gnGV7WkckH3L7JwC4gVEacZhbylus4WCXGacY1G4bkBwAlLOaYPfecLRLgbMZoh6S8hxYb2k/DBLNv8e++h03wCpFh2Ll7DMHs1lA3Gi/CWQ9aRT5v6TjcO3T/bxlDLP1NdDm6QA46ty7c+fOqHxiYgITExMD992xYwcAYNWqVQCAxx9/HNu2bcMZZ5wRtXPyySfjwQcfxHnnnYetW7eiqqqozmGHHYbjjjsODz744BgwL7i1AeTZnrSkQMidDQZ2RQC5OVNNptDv1+mEz2k4MMZKm7K0GmTOJDOAbNqIZY3sD1BowEgTg2aJALyNPVShDCidgIDxdYyEZV2do57/zfIfnzHx5CoB4xC3D/djiEkmkOkAK2eDBz1JczDNgarb5k3CgmN3rr0DJLHLZMoAtY5ZZR3+HpyNtn1op/EbASzn9sntR2CZriOK4OEArkiBsjY2JbuW9o/Bl604m+zHEIC410ZnTLStXvhxzsN9ml8nw9Yf2/5lqR531vqZ/WfbRQ/BGTR/Xs1+GDs8kAkdOJhBREzL91xfNI50oaoNcGeiUwRAnLDK0bbMuJIxtZ2LVsCOuJ+hbL6gephFCN78LEww356tKwQM3SMNAuBO63ESDIP7fEZtxLl33bp1UfFHPvIRbNq0qX03Y3DhhRfita99LY477jgAwLZt2wAAa9asiequWbMGP/7xj32dbreLAw88sFGH9n82bPEA5tTS+LjcOBvdxuABzdjMs4HvlJEGfypmWfucY5npFJHTXgMgt9wlQrxiEZXDGAgX/UMoW08oCjWHJN4wGAh1GbpoLA4C80lK5AArL4etS858BJobkosE/DbK6FjIGgAZwSlSCIDSgOeiiRgTMhTWdYgZzeQ6phDxNaAUfJzpNrDcBiJzYJkbY5cjsEzbcsfAz4cyMMLE/XPGmtU3szHLrp9BYNrWGf0OMGaYF4ElAK69XnMu84qfNjCS1h3Q5lDXzqBsfLn9af7jYK2tXrqt5cFg6HFSGzT/sugXUTvsmAY63mX6HfahoXXMc/m9zhHw8vZHkkHwZuhZSRLZxMbCiaeWMUb9uzptY+KX1EjSjX1ko869TzzxBFasWOHLZ2OXP/CBD+Bb3/oWHnjggWabyfEYYxplqQ1TZyFt7PQ3trGN7dmxlGUf5jW2sY1tbGObn404965YsSJ6DQLMH/zgB/GVr3wF99xzDw4//HBfvnbtWgBoMMXbt2/3rPPatWvR7/fx1FNPtdZ5NmzxAmYKYyaFZZT5i2QSRQHTKV1YtPDy4cTI+FJ3ajwmrtvPiBD+DSwMHErp+iwCuyxdwhGSBLBXLgoShXyDk1CYlJU08CHIRG3Dtsm+guxrFD0FWVn9LkkmvHTC1Zc1C+tW23dfVrv6SkPWOq6rKDSca0tpFzLOhYoj5zeqWymIugYqZeUStd1G4eHC3xFWLkHnzoWG090SZqKA7hQwHasD96HijAtXV6nw4hkJC+lD9UWaZQppV7M4xmmymUEShTZ2mTv7aR3CygGhTR4+jmubo5B0zqGvqu2rX8H0+zBV1QwFNwwAHQK4zspAD7CFDG00tueIEZPJwrY1QrJRGDYdv/w+PBSbbr74BBhtMwih10zyIl01/57250PKUZ3MdwPry8DDzzXaZnX9KxmvyY8zuv5pfEi2J+HiBD+OpE6DXR7mN5XU5b/FhvQibW+WfubMFYqWz23Gmd9sG+2NRAsM9FnwzyJbl3x+GmWzWdtYuBM39TdEcwO7WsC51xiDD3zgA7j99tvxj//4jzjyyCOj7UceeSTWrl2Lu+++25f1+33cd999OOmkkwAAJ554IjqdTlTnySefxHe+8x1f59mwxSPJELIpr/C6YV5PBN2qhI1gwesbY3fT7DcgGx/cV+HbjOQWHvCKeDcpo3o2PjHtnx4PtY1m1AY6ND5ZMDmG1wyD1XGALerGOxY63bI0gBA2wYlA41xyHTMAr7+LUlobG/3CA9ScJIOc76it9FxxyUV67nySFnYcdLw+G6GO+6fPpA3nfysaA40zTVM9mwyDnY+B27SJk4iwOM7G9SGkBk+1ngWrCRDP9xm3M1KMbjpf82F9+TU6bP2x7V/GNMyppth/b9H9DtLIDqzH+26U0U4AdMt1z0FtmyWAsRFsg46ZladO0oOsoVXOgNahtMqZsWbbSo5tViA8zNiHMIPhQfMw0oso6hKAVEbBo1sYGqvTIwtgoCwj1TXb5hlo5ppmbtz5D6HdNm10kIAsoPRgAefe97///bj11lvxt3/7t1i+fLlnkleuXIklS5ZACIENGzZg8+bNWL9+PdavX4/NmzdjamoKZ599tq/7vve9DxdddBFWr16NVatWYePGjTj++ON91IxnwxYNYDadEqYoZ+fUST/MHcTAwJwDTkJrGM+2ZS5s/lRIWlhW3qar5ZEvaJ/GEy0Dyd5pDyBlMdMT28kjaAHtj9EH/TDsuFJHOnLsk+HHKxQD5ylgpv1yp9SHMjKItNG8X2KXOYMpRBQVpPF34dFC3HlpapR10BwzwMyBOoAQmo9fHxzMk2Y5B5aBGIACAUDn6pLxRCUOLBulIrAcN2ksaNYS2RmM7WPawDINl54D08yDc7V5TOpjDfPz3xoLGdHncO0MrYMdMmrFrE5kgwBD27gGXH/5yAcM2CZsZWu0hswYGsCYyvh3TXN/pm7U7uDjGKizHlR3NosAaGbfBnBsls36+28Bx4OAdm6bB818OwfNbMyxfjnUSYcjuPMf29AKmlvG6vefJ5ZeyLn3+uuvBwC8/vWvj8o///nP4z3veQ8A4OKLL8b09DTOP/98PPXUU3jVq16Fu+66C8uXL/f1P/nJT6IsS5x11lmYnp7GqaeeiptuugkFJzGfYVs8gLlbwnTKBqCKjIPZhKk07j8P6JSMgR/tz94jtjgBdW0RLvhYGiyu29+wsaX3DztBuMfnwg1cux2VthEypHEg1j5XC2Ms8Nbx+G38Xn+yvHOiMMafIzrOXKppfw5YuUiAKn8QEbUK0SDSOMm5aCHUT4ZV9aHpFJNbDAo3J3Nt8b83H7TrvEhOPhD2V6xuGwtrAlgO2f3oWpIxaPZsswSg7AScNtcCtBtG4J6B5VmjYbQ1NeuFPMDS7ITD1B/b/mVpSLlkwooAYMLA5eo3tudsNjA221iG6Iczxrk2jANF2eODJRGEApPMZfrmACkFstS2c+pLGeHWKBWzgdA2YJsDuam1PDRkGd4h2x/kPOejUyTA1bhVUBqSB81I6kb9B5YZJgHNfohETJlG3wAD1gDDBKxPngOCXeuzhAKPjcpGzdxLtoBzrxli1VEIgU2bNg2MsDE5OYlrr70W11577dB9L7QtHsA8UUBTODdnkYQhB2hzoJWkB46ppTK7L4E9xN/Ta5v35Sc2B/T4hJsDyxHLzNqLJBHN44vGr4ydZGttwa9L2mFK/vgMq12WJgKOgsKaOb2ekdKHnsvJKISTcfD+YTGfP79+a8EkKaQ5LiVLAZ6ZJJIEJ55Bps8UXi2nXuAPBhzYcqCcJvbI6MmiY/P13EVAAJYYBiY7yeqCo0k1Bs2WNbZg2QLnMAnnGOW0TDi9vmBpyD1Qdgz+nEzT2uWI5m78c6o/tv3PMsA0AkKN9yFBcisQbu+b+h+qnYH7iIHtiMxnqdxxa4GiB6gugMLAtBFmKaijsgQs820DmcDZwHKmTlo+sP10rINANmdZwfBjC0COJRSIz00GeEfSDA5awT6bpF0guh+l8gwuw/DyCzZEPwQHnFuBdRpdC/H2xnni5uf7TN252HjuHckWDWAe29jG9twygVluwJn6Yxvb2MY2tvnZeO4dzRYNYNbdApLSH9NSPF0GKRPMNcVSJLpnt9jDNb9UN8c80r6ZJ0Kflci1a8fUchVnluzCBU/sdGBIo++OEZe1ZUwFOb3VmqWvlk7q4fbVJjDXwsAoYm8RM7pCx3ps6l+6eIlGNBkUTctmAApHSKPwToVcp2wz8iFa6uLxmwXTIwvO2uZkF8DgWMYN58PM34LvlzLe6YpDtI2xyC6ihZdj5Jz3PNMsIaSG0TLojoGGJMOyzhlGOXwJ34UM7DIxy0LMbZlPG+sQqxdvoJ2xzc1yrGtWo5zqHdrqRvslbbT0O2s72frpXNHeXpszntCAUJaxlBUg+7aK6gq7imcQy/Q4c2pYuxl2WfDyWcbXeoxtlrDEwznetbPETd2vK4ObWjPMcd5RjzHTnB3OMM683kCWGfZ+F5Vzh/Wojfh+nWWSZ2GiAQAFW6nI3W/YnDysfH9sC2eLBjD7cGssGkIkjUAAVY0IEmwbmZBO8aQRZ8vzOyQDKJqANmpT0HYHUk0Knt3YYADlYXvLwfLP7AftmrEh0wCzpPQh6FJ5iPGJUlzII2UsaKt5+Debbjk6M3RM2rZrCgHhvbfj4/e7EKglRz4X0i3SKjuHQaFDiLnIETMDkv055hEvsucreRAg897NIpTz7cqgITfh2w0POede7pxZsKwDWGbtRHriAjB0jtscCPn6XOp8CHgpRiTDKAoPkkVG0xwdU2rauAcdPb9ZvOERNkT9se13NqtDXwOQinh7237Zbex3FM2DQ4yt7VqeDSDz8gTQejCrw366A9RLAFNS8igHwjSsb4kw0HRnlhaBGYrKlIxF+DkvGRsHpGysc/65pu2kU08KUjMgl3bLgdnGuU2BcAto5seT3nZDvXDPzILmzFAaQJjqsWlVaL5fvn4YfrydKvEHq6xUA5m/lWj5PIqN596RbNEA5uBA4S7gBnMMBpoQgKYyNtpE9jG9CaTTicIW0jZXmNGsCWNgqB9DZaHNANgGHWPmV8TYc/sDdHUki9yh4Vlb0mcbacPa2dTWrillIJT0MZUxAx8/OYpjzPvOsc85kxYoGkhAuBB4vDLTJ4taxz946qegUySaD0URkGX7pqxyzlKdMT8+/gCWA9V8/wQsQ+sYHHMdMQfQ1AYx6A5E+7ZJz5zTQqaOfQ4oi6II8cbTvlNLsgSicA91WuavuSFtHCVjcdis0QpGQnKs8UxzcZ38rgFkpoA910/bvvF7iAiUdmZf2rGWpuMe0msBqWx9Wdt33bGO2aZ0QM0Yy1a6aJBGx8cYsdpp33zaG+UUZ0Btq8PdHEBzBKDdxuhrAoRn7QehLML4Bt4JMOnOVxImas4V2zmOR6bw9+NBDoHsXi38d/h50rcBE7UJXtcPPrZo0WWegHk8945miwcwA8FpTAKaRTgQxgFGXzGOKSwSRs8mBHEzIIFmES7igU+G6Sb/A7IOckYLi8NgvCyC309iRsOE44qcAdtAaij3ThEMLNPYTVlE4er8MXckpKIEJgJCCM/4GmKclQkh2OgZP2Euo4eMJDa1MFb+ARiIOj1XCXAtiuaxJscsckA5I6fJWlvq65x0IQXLxC4relc+jFwcjk5EkgjBE+ewtk1VB0DrgLbR2j0oZEBD6syXti+TuOTpOz8W/kDAwbOEBc2jWnqjH6b+2PZbGxyRIYPsGuimZb8RwsA1+srVbwPJLW23SiLSe4MARCUimQVgmWcjAVM4MKXoXmMbFUa4ucvuw/sT/Jk2d68YUD7omOb8m0sAdiq/GAo0twDuHNMseDmNNwOkOWgGaxLp2HixiB07OYscOQQmp2k21jmqwwB2ozLoZMRmBPIO8HOx8dw7ki0qwDy2sY3tuWPCmOEeXFj9sY1tbGMb2/xsPPeOZosGMOtSQhYisMP8UZKYXL+uxkLCJGYYI2qcrMGX8XrsayStSMv4U6tjmd3jLQY+1uUuYMYup3psLzUh5hWmwaQH04ACpDY+Ox89fusJu+5v5RwSUC60nDEwqvAsc5SIBAnrzRhlvw1oOEh6J77oGEUjI2KbJCKncRYpE9xm3rFQx4zwME/2tC9nl+k8cL2xS5cuhHRp04v4eABQumtRFHZfbex+WltZRc4idtnJL7w8hjn68ePJSSuIVeca7qII50WIOEX8XE2jXaLTVn9s+5eJsHKVKW7fJxvkGBkWuDnviiGuk7ky0QPrzxVLOEaY65o9C20AoQRkH0HTbADdtdV0x54bQayybp7L7H2LscvDOO6FxpLjy7G/uTZnuX3xcaUSxkjlhsx2ILqnNlhmJHX99jg+sx8mnXd22aWLGxQqLgwQ1pmdk8NDyjSA5NQkTLYfe+5WM+R5ndXGc+9I9qy6uF911VV45StfieXLl+OQQw7B2972Njz22GNRHWMMNm3ahMMOOwxLlizB61//ejz66KNz7ssUArojoLsSpmM/m1K4aAzul8ad9zwYFtCl+1wwkFy6F4vXzF9gL7+sRmXIg2c/VpJ4MHDWpjkSfonOuB+9A4bKsJeVTci+guyFV9FTtqyvICvtP5d7KpS7eih29VHsmrGvHdModk6j3NWHUAa6lO7lzkMhYToSpltCd0ubKIa90ClgSlbWKWA6ha3rPpuicCBSsAQlovFqOPJp5ohY22MlbTWVZ8EyySNSJzouxQCchEHEYHmQhIHaSMuAIIkoJERZQnQ6wEQX6HaBTuneO0BZxMddSIiisOCXwHX66pRAp7Ttdjv21ekAZWnb7HR8HZQDXtSedH258UZg2/+tRs+6RCzHXF5j289MIExebALj2tAmypnDcnMyKTb8R2bfpb3+MMMgjiU3N2eAtdA2HjNFzPCnRlsNs6yAYhoop4FyDzDxn8DkL4CJXwCiRpBsAE5OF4B3BMBbxjLw1PKpbIhjj/6GuXb4vY7fD3Pb0/6Tfgy/TpLvJml7cN0YETeuw6Qdum8bicY9PjouNO/zcT26d4V2o7oSrduQ9JP9zczRxnPvaPasMsz33Xcf3v/+9+OVr3wl6rrG5ZdfjjPOOAPf/e53sXTpUgDA1VdfjS1btuCmm27C0UcfjSuvvBKnn346HnvssSiN4mymOwKiw5JfCHqSteHPNNw1LUHK2wiARpeLY6kbWqK5zvMRw+veREbLTIA4YVK9h7QyDkDSU7bxfVinRRZKrk3H60GkDglIaFNpQayZ6EBNdfwDhimEzxjo6xKw1AIoTQjg0Ejm0jxZPo23ttpoSAPT9kynAUE6YWMsKObtpBFP+DECeZCc1pstWkSOleXZ9iJtmqtbCAjyziuKAIw5C6y1c+Rzx+cYZQBWN2xDroS2UyCfMslSWPDL2eQc4G8cv6Nc6Jhc1JSQjZDf/UYwg7mxJeM5e/80ukSIGjQ0B7jNDZDLf4si3j/bftxmqnud8xgz5ZzVzHXfaimgdte8SN456+zBtAZ0AdQrgHrKMpqmhJ0WpA2gQY6CNrrQgGGI5ve8A2YYZ8q2xrRs0o5gmw2rE98emv2L0NcgpjmnU/bVTcvxpOP0Tbl7A2Ob00UNfrpMWsZ9e1KdskEzFB0/BakuWoDNtxja5uv0N557R7NnFTDfeeed0ffPf/7zOOSQQ7B161a87nWvgzEG11xzDS6//HK8/e1vBwDcfPPNWLNmDW699Vacd955Q/elSwFRxleZAFwWOTgRv7uYtWETnQjAlv1y/FNjm7Ut3Q+RYtJnyEsvamPi5UYGyAQ5ytk3CxTJAY+kEZUKMoU0gx21x4+pCAwvxUQu9vRhpESxB9CThVsW5MDQNUVOkRLDTQTUxBAOeWm8ZXuMPLSayKaOtu23AOioA9E8F9FYTfze1lYiPYnKCsbSOukEgHAchoFlPiYfhi4D6jkjT3+7ImGqB0kw0mPRrj8JAEUTOPNzPoqZzDU4W/2x7VdGl53hYCjo0eyboP8SsBXVZegtBdgJmjVgoCQD2AY6v7UAvEjKkNSJwBoHyAZ5oAwEOQWtEDKmmDICGgmoKaBaahlnI4GJX9ioGmrSgmlZhbqN85Icb1v5MMC5+Xdp356LZuH/RLPs55um/fg0R3XY+U6a9NsM67splaDvATjzff25MWl9Z5IVcKd8J9Xg0TQap5VH4vQDSnBJAt6pLC6YJ2Iez70j2bMqyUhtx44dAIBVq1YBAB5//HFs27YNZ5xxhq8zMTGBk08+GQ8++GC2jV6vh507d0avsY1tbM894yv1w77G9ty08bw7trHtPzaee0ez5wxgNsbgwgsvxGtf+1ocd9xxAIBt27YBANasWRPVXbNmjd+W2lVXXYWVK1f617p162z7PkFHeJGsQheWadale3UETKepUW5osBzz3LigZFPT7F/EaAv4ZCqpFipnQatmvO5W0EtpiMq+ZK+G7FWQ0xXkTB+iV0H2KoheBTHdA6Znmq+Znn1VlX2R9rdXAdMzEE/tgnxqJ4rHn4T44b9D/vCnKJ74D3S27USxY6/tz7PX/I/K3tlL8LH7l9MeKwWQDtlpka2cRPlXQ5dMjmmcRSUmmeuUB7HLKVvMJQspUzzM033hHPnKoC1Gt2v1ypMT9tUp7XZig1PWvyyCnpnCwHHNMtcbl6XdTvvQy2mbTaeEKQuYUlq9eCmDLp+/hAja8TT8HCVAEez8zod5SJ0yh3nNwfaVj0Sv18MHP/hBHHTQQVi6dCl+8zd/Ez/96U9HP+7nobXNuzQ55hZbYn2m/dvmtKGhnXSfzMvV9e0gaYeZnYMzaGBYlpazyaxStBpJ9UwoJ9mF1zI77bKsncSCaZNlD1j2BLDsCYNDHlFY+/+bxtqH9mLV9xSmtrt96+YhtPnTNM4Vq5s1ds/jml4k53agLrmtLDdGNOv4U52OsaWNnI55UJ9GBD8mriVuO3Zfp/E9xhU5LbIp3EuGz43xZfTL1BZ/zcsWeO59vtpzBjB/4AMfwLe+9S186UtfamwTaQQKYxplZJdeeil27NjhX0888USjTgRgCbQ6Zz5dIAaxoB8PSxvN51h+MbFrauATmRTWsU0027b7mqA9Ngja4xRc1hqiUhA9BdmvAzCeqe17r4bo1UC/soC4roFa2ZdS9ntVAf2+fVWu7p69wK7dME89Df3kf0A9uQ1mxy6gKCBWLINYsQKQEvqJ/wfxnzshpyufVCMkfkFwGNAM+FKWPj7+fg3Rc+/uOyoLnP1LGb8fZVeEtA8gplvELyltLOlwwTT/BrOBYL6PTOrmzEf6EMwJjwHXbheY6MBMdGEmO8HRMW2TdMce8BJIlsHxjjvdEUguOFi2QNx0Sns+nAYdZbJf7kUOl5RpMX3QTM9RLq33c8TIR+Khhx7C3XffjbquccYZZ2DPnj2+DvlIfOpTn8LDDz+MtWvX4vTTT8euXbt8nQ0bNuCOO+7AbbfdhgceeAC7d+/GmWeeCaXUs3FYz0lrnXf9TT8wC0K6F7+keB3kwVVog5Uh8xloB+ApMKO+UuYjUy+y2bbTEDJgGaRTVg7sqvi7rIGiD3R2Ayt/pLHyhxVWPboby76zHd3H/h3Fo49j+Xd/gSU/Uyh6A8aU+547BnafawXPQwDSVuDK+h60L31v7Ef7ttQf2D8BTA5EW4EvEQYiai/nyDcQTJOPEwfQ/MXqRSCag2mZfN7XgHlsI9lzIqzcBz/4QXzlK1/B/fffj8MPP9yXr127Fv9/9s48Pooi/f+f6p7JhBwEEyAhyCUGOUTFi0N3AQERxQuVVVxFZV2U9UBFlJ+rBldBUBG/oKIuCh6Iu6u4ul6oq7gYUEBxPVDBRUQlgtxHkpnprt8f3VVd3dMzmcnB5Hjer9dApru6urqnp+bTTz8HYFma27VrJ5dv3bo1xuosCIVCCIVCsSuEsGXuQiDql9Hl98bs1HIacwWUqf5qfr5G4LBTf/mnipGYzsTMAYjKQtY6p38hlmVxEeGzqwbuGYbVTqQxU31sTQ6YhrNOLjedqnNiPDxsLYtGrfOk69Bycx2raDBgpZCLGsCBA5aYapFpW82ZLWSViFoxPq/Pr7rcNJPyWxbCkutMWjxdqerUQiVMnAdmfSB+vruuAEDPexVZ7Ib5+597fYhFW79sHiIdnhinLTZlxUVPqT55joSvsMnj3+IKYRvQnRLjfplFVEz3xcuEZV3sV+P+6YTqyOogn5qk0D4V6iJGYvfu3Zg/fz6eeeYZDB06FADw7LPPokOHDnjnnXcwfPjw1AbVRIk776qiLOZy4XYT5vZxlsFYnutT/sGVvhKoVqWd9FdV53hnV25/XtfEzVzjjhss57Eux4hldZ247tX/uVswM4MjUAWEdkahV0at+Z0x8CprjjYzM1DVSoMZAMyAW0QlfGLp93vlXc4THKfSNuYjY55t/dqp/Xu29fto/AIBAXua8jsk5TfZ1Y/4W/wkeA7J5fPM7euFOb9LMesZYg+Mu/92tVORvwEe/eAX/OcZaMz1W0Pqe+5tqqRVMHPOce2112LJkiV4//330aVLF9f6Ll26oKioCG+//Tb69OkDAAiHw1i2bBlmzJiR0r7ifvmVCS0muA/2F1tn4CaXZU/ddeETX7m+zvsu1wAxkXJnEtEAbtrfTA12QJ/YPlZ0SrEshbRoY7hTpAlxXI3YYfajfpnCLBIBqsJ2SWfDOnpdBzusA4wWITkm5nWVkPt178s38FAEqsERxxI1wwZjlsVUNU9xbpXF5hzwGv28VfO8xAvC9AbqiXHYQaAuy7RXIHsFvSpa7fPEDYAxyzquin71vHH7R9RJ5eZzHOpYNPe5iRHOMcfIXf1wWDc9TFkmo23Ee5ELui44yIEnqcZIjB8/HmvWrEEkEnG1KS4uxpFHHomysjISzNWhTqhM/uO8t1WR1UzMr8q2rqmSuTZ1+hf9wFFiccS5b4ChstOY+dqriqoTk+ruXL8tzns/DxAmhLQiqsE5zJAGxnWrumpAB2udDzMvC1tPbIkDRU5britCWTlBcV0tvMevjlsRur7bKAN3iVqfbcW6eLtCNcvjtlGmPVcbdbpS+1GWu977fJYcznKuKHPmuoYSDFz8zX2WQ7lkYz4b5n/Sle3ENrWv9Hdw596mQloF85/+9CcsWrQI//znP5Gbmyv9kvPy8tCiRQswxjBx4kRMmzYNJSUlKCkpwbRp05CVlYUxY8akc+gEQdQWz81pUu2BmICyuNZNddMUYyQ2bdok22RkZOCQQw6JaRMvjoIgCKJBU8O5t7mTVsH86KOPAgAGDRrkWv7UU0/hsssuAwBMnjwZFRUVmDBhAnbu3Im+ffti6dKlKeVgBuB+RAIfC4F6ByXviN2mCseNI84jFfG3ffcX9+5esSq7xuJzJypT4jDmMqBA5GrmVs5hpjFlh4olULUuq9ZcO+UYy8iIHZ+uWXl7lYA0aS3VdRk0Fs0JQj8QBQzFN9l29XDlclatyd47VSVQz9dtQLRR23qty15XFfu9a1vRVuC1kvpZYDWfbdXAQnFebDcR6ZrCmPxbFsIBbGuQCQ4NjHGYzPYvBmSebG5b5IXLBtcBBi3W6u6Hbd32Wpb93TGs9TGuMMp15UJ9cqGeM83vA0uOmpZnlQFlNnfeeSdKS0sTbitiJJYvXx7bbwoxEqm0IQBm+yxz19zkaqBY67hcpD5Xdy4RZS5Wrc0uax9XJkl1P8rmwr9ZsWq7mnsvSV/fO2cja/eeNuo6xdSpukswBulHyxisGgAmgCDAOEMEDFV5GoAAzEAIXM+GkQGEWwGRVga0Sg1ahEGLuPcJwP93yXNsvk8/E/xmeQ2g0npcnbUW1ViL42zvsvT6HYoyJav9VNd/vPdyO/t9bDvXB+6C2U+IXeu9FmfvOfGb+hJNhx7rfm2g0tg1I+0uGdXBGENpaWm1P4hJ7U/9YtmTFWCLUu7Op+ia5AAnr68iGhJe215hboiAvSQuPqWNyA8tZwfbXYMxzzdSuDTI7AX2AITvsih+IfLyBpTMCp7CF8JPmGsaENDsjAoazAwNZlCDaQcs6mHTLWY18WPFrOhf+1jAGBgTQlYZs+JXLCcjb6ET35OriGTV9cPrriLaAqm7EcRz5RBuI+o50h1XCBnoobtvmoQ/OmcaEGAw7cAQ4RutRWDdaACADumyAcCqSFkdHqEeI9oB1yQuPg9uegSDn1BWl3HPNVebR4M1fCy4efNmtGzZUi6uzrpcmxiJoqIihMNh7Ny502Vl3rp1KwYMGJD82JszTFxv1lseo+A81xCHPZfYmwsBrYpntT8pVBhUv1OXmwaAGBEjGnF3QLd6gyuX+wzRT/CoHiEx+kmIZRHsZa909SNEqO2TbAYAMwiYmRxmhglkmlLlmXbdAFN1MUmA332E3CfgEtBxxTNzt3f51HL3qfbuQj0fopFfdg+vv6xLOHvFNXfOI2DfhHg+ANVlJNZXOfa4XP0LzRBH/DruFcyzLXedT1+xEO/zSmK5WfMCq3ZfNZt7mzsNIujvoMBgZ8Jw/gaULz0XGSngfKtMq638jnm+NPF9kSAtrFYKIbtEtRCMPiJDtSDGpGezx+/vVMYswcZhVchj3AlQY/bsI3yZY8oqK1ZR0RfgEoE8oFvlr4NWKWzOYFlUDQ4Wtb90tkC2LKH2rKQG4XHu3BwpojbmUNQvpaGeE64ki+cQxWTi9eUSy6kI5URFPTxBh/JmQrfLguuKWNZYTDAiOHdlYxGR1Mzk0KvM2M9WZKlQUWuzeCYwYUW2yovDEcriUFyi2fZXVm5kpFVZvRFTi9Ko5hxNGUttrKwcvtdBwvYAWrZs6RLMcZvXQYzEcccdh2AwiLfffhujR48GAGzZsgVffPEFZs6cmcLgmydWJVVx7QCcM5d4BhTBw+xG8ppVGtjbOFOCR0ArE7RTkEL0E0dAu0fg3jZm/lWVobs7OQ5uxblIUSZecP/NOayYC1f/cIQyA7jOwQOAGeRA0LQMJxkiBoWBR+0njhqAIAczrHNb3aPzGFHsPiRf8extoraNEc3ubtxde8WuZ5kYk1qEJUbsqp2bPm3g6U9pXm1/3L1tzLkUl7F67cZp4yqe49eX2FV1QtR7bGJxbRP01HDube40G8EsxLIUK8qkzAFrouP2BG/aK6CIM1dnjsgWWTfsxRaGLb5NS1Qyw3QsjJrdzhVU5vniiL45d3Ivx0zgzHl8rmn2WHiscAYcAa1kUnBZI9XxCOFli0KuWdu7ggwMJWsHY45VRRwHYzIIj4M5gWtiHeeuDAzy2D2V41zV+rzhxl7LcXWWTq9l1IvqYiGaKdsI1wuu687NhK658xkzJ293zH6ZZqcKsk6WqVtiOVChCH8R7KkzJ3WewIRV/VF26zkX0s3GEe6uw1efpiiimNuORzGuGOr/fpO6PN81F8z1/ViwLmIk8vLyMG7cONx0000oKChAfn4+Jk2ahN69e8usGUQCbCHoerJhLxduGsx+Hs5jvuNKH6rlAnAL6DjWZzXAT3YT27F7f6roVoWd3MK9bexje2UD7uyf++1S7EsRy9bca58PnYNnmFbqc/H0DgA3GJhh/62LOdXaSfzg9tjvqW9TVQArDX0t8J5+vAGBcrc8dpZwfdSqWGZijlL26xHZcp3mbONnFfaKTHk5ePtTj8Pn5iHmvY8QjnvT4N3Gc4knjMpMQG2D/sglo2Y0G8FMEEQDQ9wYptI+BeoqRuLBBx9EIBDA6NGjUVFRgSFDhmDBggXQ9do+FyUIgkgD9Tz3NlWajWCOSfztvUETj4HcZgxwkVPZdN+uWkYNdycu1w7Vumxw567WtK0hLqcrdaBc9iWty/FQrczqMqakJAvotnXZ7kd3zJaWT604dmGusY5b5gk2NHDNdr/QHeOkVZDEtoKLQDURdCfw+hgrxxeTo9kvKDDe3bffORGRM4Dboq6el3h408IpgZbWObPXaxp4SHdcMHTNrgYpXoCo8mifRgDWOlEQRyy3XHSYlS4qyqVlXvore7wxGOPycbHrHKj+7sxx+Yg5ZsUnHoDbLz4OvlYFpvpjwAoOrSn17EdXVzESmZmZmDNnDubMmZPS/gnnwUeMLyh3rM3SDUL1S/Y63KouQbJzuMx4wtrMXVZQ0SFz3AcUC2T8BySesbl7A9RUeD7H5uohznQlre/M+W5y8V6DNWeL91zZUORPZ1zO92AeK7syDqZYzt34H7zX0M/irGNqA+6znWJV9bo/+Kb0ExtqzvK4LhTCou+14PLYNn4uDa4D8KxwPVXwsTLHnE5lmW/KwTjTEPOOycdKHa8fTj7MaaGZCWbFHcPvaRyEoHCeI3Fuiy+5zHbBMLnzuEkIZVu8SJ9lWa1PnXytvtQAQy9qBg0xOJe4lHmahd+pLaYM92MWrsNxz4CnT9v9QWTX4CJoD7aQNk3LHcUEdJNbj/7k+bHFvBkrlmVVQrE/zmNdL1yi2kdM+7VT8QYOqhkzVNHsh4+IjskioeZ9FsVGbJ9iM8MWzBpTxDJcfsnW41W7olMAMkhSXCtaxDnPzHDyGkufY9V9xcZbxEG46TDphgNPZgzlMDnc58h1/LG/JHEfv8nAV+Vk1WYeFY9eU2lPNC6YmCDtt8KVQW2ivHMEqv2diIki81yvrptCa3++WTaEm4bqoywVjhxI7PXsde9QBBGXHbmbe/H7irhvqmG5YQAyINA6b+7Glp+0siM5fyFWZPrtyzsYu6G/G4cy93jFrro8jniOsyvneH3Er58bhiqAY/pQzkfMT5z6P4d6OLFtvcLdc68mUfblJ6bFMvUjiov3MlbEtvo/PG3k5rUVzDT31ohmI5jl3byK+kViHtHMLLFoTWTKN1j4EzPmSp0mfJSZ6ViVmSoGRS+KGHJ9KcRy1/h8fhwU0WwdgmVxYJw72RXUtoqgkkGHom9ACi0m+rIty8w+fsZMiJR2LiGp7kMVyorYledH3a9473e86nGqYwSSC95TszZI4ezpE4pA9vpve/qSAX5KmWgzqIMHmCWCFZEsS6rbQaVGUAhpa3+aYQXmaBHrxkqPcGhhE1rEKhnONU2KZXnTJoRvTIi+4ltvWjd0zG92Fj+owgKnCmdVpDA/GRPbj9i366ajFhMp+dE1fVxBf4A9HzF/UQtFKKtWZ2uBhIvJWqzwfXrkqB81gQGU/pk9Hnf/ikBXBRV32jqizL1fP5ET10XVdU6U/71i2WSOX7Q4Hu50LC2aqo+z91BcvyGinzhj9Kg9X79k7pxQn+7cAtheGRNgB3cbXz9k73bqTsS+fX4qfIWtz3q/9z6XW8x1UJ2gVt9WJ5pdf3LnPPhdN66fw1oKZpp7a0azEczMgC3g3FYCgdfq7ArEEF9gBrhKWIuy2VwRyiZ3XDD88E5UqWYZ8A1Y41aFO+XRvPcCl2I50YUvrJSGNcPIPlTxmUhkKhZl32p+3rapHLs3zZx41qtalD1BezFj92znm59YXacrWS1sq7IRst0wbLFs6u5gUks4A6YtmK0bKQAc0AyARQEtYkILc8vSLEQsgxVAKCzUIvjSld1CfI5Mnmf7crbyt8bDRzhb6QoTn3LORPrCeA1oEiUSo35FAfG1V6UrfEStI5ydjiCzQMS4J8ln4qKh+Nu1F2vultO3pw8p1DhcAskeX4yAFgfjHkVy+H2lpGhWb2ThSq8nV6vjYFb2HWsucFdMFIPyF8Se3fstj7utMo949iWX+23nPrwYa7B6usVyl1uHR/S6BKmf6PX27yeG1QXePuO0i3Gl8PajjjHO9JnSr75yAyEX1Tz9PVELmo1gJgiigUF+dARBEAcfmntrRLMRzMywikNw+9G+FoUTyMdgPVYPwJ0WrLqLxFSKkRhW8Jb061VdHgCfwDrAz8Kq+kNLi6KCn8VRVtnz+g6rrhJqUF0cK7HljwynPWAFPIp9m8wORPHe7osGHjeMeHj9jGV/nvPhdeNQt/cG6nn79r5X2ypmL3k+PbmLZV5l28Js2qnjjJDmWJMDsNcBXLd9lZXAUnDLomxdG4AW5tDDJvRK03LNMEwrv7Xwh2ZuP2jXObJTFUrfMy4syxzQPeGn8az39nn2DUxRNxeWZY1bQaLiszGVz74uJlCatJs+GrdTollvmbAUAxALXZZm27XAzwqoWpZdfs+uZ+Q+84jaCVRLs9tU6OenbG0QzzSpbgj3RokcUOMhfnY81mYm3O84LBdBbj9B5PZG3DZlCoum6k7hPRWKO4XfYmeBs22M9Zkr23Aes557O+M+f3vG5hfAJz6OeH3F+BL7WJvFe1+rMI9t47e5dyGP04gp54V5j9N7vpHcJREPCvpLD81HMHNLIGv243G9yvIz1gxu+SrbgsgMMqtQh65UfzK5jF2R2S+ESI6YlitGlEOLGLEXluomEO/xNlcmOCGW1dV+wtrklogyDEswe90hRIU/pX+J6dmB6Z3clfGq4/d7DKTcGDDvl1AVvD4i2S12vWI5zv7EONRnvV7xG6dtjO+ysg0PiDaQItnyTWaAFMUMRkjJeqHDulaEr7ISUMoMywVDi3LoEUCv4ghUmdCqTOuaA8B1zfJ11pWXksFFPH4VQfNcBJ8Ktwzdnovl5Oycb+sHQlEpXhizsp+Y1mzO4YgV6Q+paeAwHR95bzEWIC2V/ojGg5p3WS6D4scMIEY4M+lhbC1XRIc3s4boz2qnKjq5QcwiKSiFPxPUS8vuy+VSoBgpnCHKVTFV3cQI41yuqfg1V+u1Jsav+DAnFH4JA/2UASqnMsa9wit0vTuLcQdUVykbc2e9nxuGn1+yejPj5/bhPx73W+bTb1w3C5++kmnm285HNFfbr4/YBixjTa2gubdGNBvBDA4pRJlpWYMtsctdwXuWWNYsH1TdTvPFYQfxuUWyFjEtsRo17UnTba2MJ9KYHUwohbG0KMfOdF4RyEzTEqcRA8wwnAwVqgXZMAFuxl7kqmXYr0S1aCPKZ9vt5VxmMsdSrlKdz7KfRdjjgxxznPEs6/GsyXF+WdQUa64sFIB8msCZJV4hM6mIDBi2j7KdBcMqU+uIZyGSTTvQT/2R0aK2WA4DgQrLssyi1jEZQSvAjweYFMzW0w3m/M4rN09a1P6b2Su9kSHC6mw621mfm6MG4lmVZel1W1xY2fnsyo2i4IxmW/ZU4VwXlf4oUrvJY33dvILWvUxMS2pwoKNfY/2bXcJZ8S92i2mP6vI8mfP06AQhxgho+H5xEmooP0HnRxw7RWJLtbUD59ttK1hlXlaDEmOGnszYlI3c4pLFjJlzZwhxuvD8HDjK1CXsVct3nDEnI6TjZgRRxhXz8SvLqrX6Jqkblfuy1PvxOZ/e5bWu9Edzb41oNoJZMzg0zRYOtrsDFHEhLmAtzAHNdt+wH8kDcNwvopYLBDMMx93BRygDcIlDlyA0xXTn7Ns35ZonWoYZ3BLnwqpsmJa1WApV9W9Pfy7Lr+fq1zTlB8X+X9chA8t0dexiG88JFvsV41H700SWCeX8MKXSoI9olqNN5G5RDapAVl1tuFzGpEhWs16oIlm4WghxbGR4LMrefMmmJTS1KIdeBQQq7RssE4CmCmRLJBsZom8lTyy3rldmMnlzBc6spyP29cuZ8llIyxkDDNNlnXM9vQD8A/08j6blebLLncvviH1JyFSFnCO2xm/yUKR288C5PFVBC5fIVX+9fQMDATB4ciyr2zNHkPulqXOrIvG/x9qpqKna3AdWr5QV/LJlxFkvAvq4/YZzsS9hcPGITsbduowjqbHF6PUEajJWkDsyPt5dhVsoexqogtnjPhIzDF/h7b9P0c738JV+1F37Cl7vNSSuR5+2McI8Dr6uHH67Vn+GaymYae6tGc1GMBME0cCgx4IEQRAHH5p7a0SzEcwsauUDlQaJGEuuaoG1fZYNxforguqipmt71XIq/7b79Aboyd3Z/UlU32OxSGeOVZmLwD7bshw14luV41mUbVcNbucfYyKSRJPPQy1LsxwPdz8DU00unsBImbJOtXZ7U9CJ955CIN5gO+fz8FhvE5l84n2ZhU+y8jlYvumOxVm6WwSdIiTCPcJxuXCsymbQHhdz3/GL9HHMBLQIEKi0/JaFu49h+8abQdutwy5oYmY4/UifZdun3uqPQ9PsnN1Ru397PzBh5d02bdMJAxhnLp9mkQYxpmqk93qMcx5ljmamXCfCugUGXpv8Ruo1lmx7olEh8zArlker2I7yfVctyi7fZrGFbT1mcYqSKPsSFj9pbfZLEyf6U02XLLZNas+sY8fs+9brMsDUPxJd3/b5UoPsOIOoZsmhpBJ1WVn9fCgS78rXMurxj/Zr4tdAHasw8cZYgmP2Jd67xyovI48F2nUNJLBqx4zV0zbh+nokzrSceJvappWjubdGNB/BbOdHlqJEcadwipMo7UXhEeEjDFgiV2hKTY91uVDFGZyLmsnMBva3kvPYbBIeUcoMWAVEoiZYxLBEsmmJ5pjAOjE+6Z9sxvZtcvBo1FqnaeCM2yW/FZFvmpYrhjwAZ0wx/tmJENX3GAPsMtLC7cOvGIgjXpUbDDGEJJ+N+j0ycuUytgUu15ir4IgQxGYGkzmUuVKExFtSXQZbKBO3zGhiAloY0MPccu2BJXyNTMsVQ4hlI2idR9PelzV+uw+7H2YAzPYvFhk3NDt3sks4a7CKG9jZWkymyetbeE1In3lDGbPXwuCtxgjA7b9svRclvOW2gVrM3GTlaPI498x2oB8c0SxwBfDFKBumbO8IZ1f/rjtX0am/CnEJaZ/1KnV2ucWbwpg6Dv+duQIZrROnzD3ODQTXuDNe1VfcexCJxLTvAJQ/vB+Nz/5UXALXsVS51seMhSvdxRHVzpCcAcUT02rTeGOMOZ44uxf78Lqs1Cbbhe+OvOt8Ti9lyUgPzUYwWz/2UMSytVhaID3+wtb/sCK6Nc0K6gtpjjgWmRQ8IjkGzmUBC7lvE5Y4VUQKF1ZuoT8MDq0qAkSiQCSSuAAI94hmKZxt0cbtoEDDdnxShbEqbjWP+FED87yZKUQ/pk978bcurMm6y6rMA5r7/Gm21VcG6CU4nXHWMe8EKeZfIZCZ1a8qkkXBEVP3+CarQpnBSRUn/mZukWx9ropYjlqWaDAGI8Pq28iAVSY7YAt3MeGpVja7HymW7f1ozP54mSWgmRDOhv3etjBbWWAYWJTLYD5xY2ZZrZVrX14j6jn0iGXxv+2/DGUzkVmlVhZmpDhpHyyTD1FnWNMKl37JUjR7H8+4NvIIW+6skKXgXe3FPKcKb/sPTyBfTEXMOILE2pu7X2kZT3i8zjbyeD3LUkLV0x6LuvspH+Skx5VGMecqkZiubgw+fbjmEr/NfEW8Z5EqqD1tYvtTf39ix6jehsWdLuLcK8X9aFS/bPicjjibxSWJDfz8ml2nvdbKjebemtBsBLOwLjKTO8JMnSmVlFlyjg4AIgmmaQeoySwKumO1VFENBsyOUGGG/YMhxItwwVBErqyoZotpZnDgQIXjfgH4C3uuCGHhDgFI1wsptMW+hDDWGJjIhuE6AAZoupV/V9McC7Eqnv2+aJqtSOUNBRyrclAVzMyqaCeEstdFIoE1xr0vOMdnH7psY68XwlgVyjKIz/O3mWG/12BZf3VIcSz/Z+Jzted44YJhALoQy4a1PpppWa2jmZZ4tnI2I/aaUQWzqdyfROEWqcw9FqYxK60cV7Y1GHiUW6c96jln9j4AWzxDszNecPnDE2PNl98Jnx9Zn2CtlCErR5NHYxwa4zDtgD0hGF0i0m7rzaKh6GS7ndjW6T9mGx8x7QhezzqfrA9+qEGEPhmi7XGIMbjbJbNtQhTjjRTc8cQzF78v6vZeS6tLUjp/qNZZ1wZ+50jZTzUi02nuCNi4Z0ER1z4a2l6nLNScNglvZJI57T76mnHPSlXgy0bKsuqupSQEvN8i39Og13IupLm3RtTWE4YgCKJmmDz1F0EQBFE76nnu/eCDD3DmmWeiuLgYjDG8/PLLrvWcc5SWlqK4uBgtWrTAoEGD8OWXX7raVFVV4dprr0Xr1q2RnZ2Ns846Cz/++GNtj7xWNB8LsyhGYlsA3X6yiqVO4+CmnRtUg2UN1RXLsgbbhcDe2HPXyThsq65t9ROP0tVgCxEop97lyUfndrq4SASoClvrRNo372Ny1wHGsS6rCOuyrrmty2K5NG/a/3v9j+32zNWfqL7FXGON64KhKencPMF3fkUwvOc5xqKvbKO6xwgXCjNDKTQiXCsUC7P43wi634vAPmnZFdZlO9iO2ZZmYV3WIlz6uBkhINzSdsMQ1mUlUNAvN6q01vg8/IBqyVG25Zr9ljHH8h0BeJSB6VZRHhaF9IVmBpcDZwC48EtmynWofrYC4T7C/fyZYz4ygpAIS7LGrGvF9HyBVauw1+WBQbEc2turrg5q/wCs74DnekzkBsE913y8h2fJUB9fA28ApOtryi2LNecM8um6sBIzdURu06lrnDHzkD05eZIZ+54TDhlbkShXW1wX7Xi+BoA8SNcx+Y3ZPnbXirq8p/YbcyrE5OdL0H88C7bsy7NpA1du+/fvx9FHH43LL78c5513Xsz6mTNnYtasWViwYAG6deuGu+++G8OGDcM333yD3NxcAMDEiRPx6quvYvHixSgoKMBNN92EkSNHYs2aNdD12jpx14wGftrrDtP2VWW2uOAiF7PAFrKigppwuTAzNCdATBVQiJ0MmGk9RmRMiBM/dWRvwpjjhiEEtGEH9YUj1v9C1OpCzIqIQ8VfWeRiBuTzAmZqjmhW3TFsMSszZKgoQXrQdX+xLHZviybmEfFCJIvgPhnUp95w6B73CwaXC4X7HCntAN9fJdUVQwb1MUh3CzPodsFw+SkzZ5mpCGawOAJXFr6BLCiiha3c3ZrhCPRoJhDNdjJquNw6AOdxoxDgom+xTPmfKeLcJ25GjtX5rbMycGgGYBpMlmzXDIBFTDCTQYs61wsT9W1i7kS8JxqOSNa4vA6q8+lMCDedaznZ9kSjQmbJsNF9/IBNT9CfE6vsiF3mfS9cOlw78xlAHLGHOFNz3HCUZPtOtG289l5RCPXGwL07GeRoi3vhoiHFs9OB7Ceuu4VLWKsD9BHZiY41zjquduNjJPB7kygIz1rmPkYetx3in/d458PTf2wTz01ASng/4Jr0oWyu1baD+p17R4wYgREjRvh3xTlmz56N2267DaNGjQIALFy4EIWFhVi0aBHGjx+P3bt3Y/78+XjmmWcwdOhQAMCzzz6LDh064J133sHw4cNTGk9d0WwEs/BjlZOBmpGCwyo7zJljWbStkmZQUwLGlO5EfQ4OO+jKWS6thZz7flm5poHBtP43uJP5QmTBACzRGggoYtkR15ZC4o4FmevO9pxbwjbZxOZClNuWZwQC4AHdEr4iBZw34M8OAuNCQdv+yqqfsiOa7ap5PtZkX+uxsBB7bk7i+jer4lb4Kds+yFy3rbxCJAuBLISxEszHA4qwVX2W7cNlpm2pjVovrQrQK63CJFYWCju4LxOIZlpWZlf6OfVYAEcci+sFjhCXL7u8NotC+ksz8ZnLDCDKeVD+NjQGpkOmqDMNDk3XoEU4wDRosAM2lR8PtaiJK8OLsCTbgtz1MSSZxcQX8qNrFrgyYnAGTTNd4s57+y4EtOPnDM97JaDOfu/dl9cC7RXWMVpRjM9p4vvefWDufqv9Jqg3zD5jcr+1j08VzPJGQvyhikdmb+MZeDUCVA3GrH7sYtQ+d9N+Nx9x9ulOZyHGUI3Adu3L/mzjHVt1gjie4hXjincRVDe06kh005Do/McEqrLap5Wr4dy7Z88e1+JQKIRQKJTSrjdu3Ijy8nKceuqprn4GDhyIsrIyjB8/HmvWrEEkEnG1KS4uxpFHHomysjISzAcNr/Cy71LFo31hpRRWZTPobCfaM1uzWmm6nLtOzYDjjiFfnotSiEpoYKZpfX/VgLpAwA42ZOBB++PR4ORpFkLZNO1yqIqQ1TQpmhnTwIVqFtkvdM2yLgsrshDJdiYLaBoQ0AElSM9rXbYPwhJbYplXJNs3HGI7U6xXs1V45wfmWae+1zzbeNwuwGyBLFLB6UIwK+4QXguzsJargtNlXVbKSYtGIm1cpZVnOVDhXAtGiCHawhLLIoDQJbrF3/YjTw5AE1ZlkSLOsKzW4n9NiPOoZSV2BdkwpRS7ghD98neNMZjgLtcVAJaLBuzLN4EqsEq4u3851DRgyab988VUd55se6IxoWvc7VbAnIwZ8YjRAuLr5xHBako2b4IXr7uFINVMFX5ivCb9el1NANtNxbPem11DnSeliAYgTKvOdh4RLc6V16XC+3ME7j9230MR++OxIttHQ7uXe6wFynppMEi4b0/nqiW4uvY87puE/cYjkadFwksrRjB7LShJ7FiI+toG/dVw7u3QoYNr8Z133onS0tKUdl1eXg4AKCwsdC0vLCzEpk2bZJuMjAwccsghMW3E9umg+QlmgiAaBmRhJgiCOPjUcO7dvHkzWrZsKRenal1WYR5jC1ezhcUdRvVt6pNmK5hjrJXixlx5rK/62lrWPbXwiWJFNuxKarIwiscaCGdfXOOAqaRIEr5mjAGqRVm4SQD2xWpawYjWAqVPzf0sXRyTBjAZrQXLT1jzWpZVC7MIzrP+j1uFTyBSnqnWZWHF9Ab0BZhiDXafb9dnYlugXenXYizPUD4fJi2qwqLsVOeDr1XZ9dmK06VaDBTrsrpeuEnEsy5HWgBGC8u6LHIty48qxppuW23t60i4XajWZZGPWTO4rOwncj5b5wqWz7zG3NcZc3bJ7fewXZG4zmTqUmYw6WsvY2/EP570VFxcYuK5qXo8tZm7lH0l3Z5oVDDGoXtcMEzPReP11fWz1HLOoCdpGXZVEfQgHlJoSVuZub0dq2ablMycvsGPgBAEjsXY6yohf1aY26ptBQQyVz+yb7Etj320V9Pc1Orfsan9lI2580dci3Q863RCHBN1wikolTlDToDVtYt9WuDbLIFlP8HCavZrn/NALSfDGs69LVu2dAnmmlBUVATAsiK3a9dOLt+6dau0OhcVFSEcDmPnzp0uK/PWrVsxYMCAWu2/NjRLweznHyuW+4m1uGLZrq6mBmTF7ouBaVw+7WFgYNyELI8tLlq1YpriBiErEgqXDMOMvdA15iRx1/XY9dLdQ3d8lpVgQul7rFu+yzJvsjgH3mek4nzpnjzKnnNpBd857i0u9wSf/qwgOVs0K24YMT7KivgFcyrmqS+5H9VPWQpqW/TZ8w9XPz+vf5zJpHjVqxyxDDhiOeoRy96AIilc1ahwW4SrYtkllKPKjZgi2CW23zRTnm5yEZTnOrdQPkfrIhQFW+QvI3f6ZODW5+Fxf3B8msWHWAfqlSzMTR4dHJrtoyaEsp/wrc6HNhlvHHF5aEpAVMxUGWdbVs1lXVuX0Zj9JThet+DnUlxLX254xLFcqPbv2zM4Zx4h5xlHgpsNn4OA8J12LZZCWu7Ws9yeY5NwYfH6v3vfuw46wTWSdHCyo8Pjr/Pdkfc8xjmN8fr3u0nx7kb9fBtxHuYuXbqgqKgIb7/9Nvr06QMACIfDWLZsGWbMmAEAOO644xAMBvH2229j9OjRAIAtW7bgiy++wMyZM+tsLKnSbASzFF6KZvGuF+JCtYQKsSxwgvq4+7vKAKYzGTzoqBhuZd6wNSr3fgts8eoqPS2W+6WO826rAVYFCyUrhsxcoSGmTLWwWiuBfFzTZAo4SzhrnkwWbsuAqMonM17EpHZT/05gXRbtRKBegDnBebJktrNe+CILv2QnTZwjor2ucvLzlO25/Fu0sYI+7c9VTavEIa27WsT2X65yZkJDZMSw/ZZNNdON6XTFxHUlhLItgIX/sqzuF08sC7OSE/0Um2lEnn/7B0xMwOolI8YhCu8Ii4oYl0ipmECdxFiba4Np5+hLqT3RmNA0E7otYP30kcZsQegrop2/dea2THsFULJ+yfGsobFCrH5JdAPgrtTHnMwiyn2saoEWo3V1yRCrt2zB6RdIKP9WVsb7iqvLmciY49cOnnOp+FXHRWZFUX6o1WXiPWdgzHT9kCeajpz+4jZIKLhVfK8Pn53HvY78xLEYRlwLvYfaZsmo57l337592LBhg3y/ceNGrF27Fvn5+ejYsSMmTpyIadOmoaSkBCUlJZg2bRqysrIwZswYAEBeXh7GjRuHm266CQUFBcjPz8ekSZPQu3dvmTUjHTQfwSzy/3qER/UbKhOMEC4CMSmJgEHOAZ3JfJmMw85W4XxDmMGlRZdBcwenqMIZcIICASfAzw4AdCFFM3OOSQhkNcuFmvVCtPGmgNMArmtSGAv3Cnm8tuCCnaZPPYeu+YE5713WZUXUyr4Y7Iwk8S3IqtuFGYQ7m4US/CcFpmm/VcQyVLGsiHb5WXHlIISoFdkqbAuw+MzNoJURw8hw0se5tlOsQfJvJYUcU4WyJzOGfHKhZNCQn5f3PMeBM7gt0uqPsHJzGA/vjWK1JriaQBbmJo+umdA160IUVlXh2iAsp/FcLVxuHJwhyEzHlSFR0CDjMS4PEpcwdgSfuiyZvGFCvGteVwtludf1RCXhMSubiUKtQkiJ7Zxz45xLb6CjnzsH4Jk/1K+4z3hihinmWC12sbc/dUGMNThpeMKboZhjrIMpotry59XYsZx2NRtMTIpAZUdyea3TytXv3Lt69WoMHjxYvr/xxhsBAGPHjsWCBQswefJkVFRUYMKECdi5cyf69u2LpUuXyhzMAPDggw8iEAhg9OjRqKiowJAhQ7BgwYK05WAGmpFgJgiigUGCmSAI4uBTz3PvoEGDYm7gVBhjKC0tTZhhIzMzE3PmzMGcOXNS2nd90jwFczyrKADhe8QRG7jnja2TfroQd53C0mw/NRIRnVHlbpMxO+WaZvugKheuYmFmtt8yAJkujuuwfGqFCdvkzrEItwjbYuyyKHvTw0lLpWXNEO2ltTegKRZhd4ERNdjO8oP1nA/XeXasuaq/uNsv2U47p1vWWmiKT7LH3UItMmJtqzw+tK3DzLQ/D00xGDPFGu3aQBm0+t3mcFl4VWswZww8YFuWAwC3xyJ91lQLN3dbvlULuBPU57Ewe59iKJZelysLU/r2QQakevvlcPKGe+czNXWhqzPm+ttKNQf3E42aQGnlmjwBZiKgGTDhCkEG4BSQ9LMGc4+bhq78H9d6DMe6HM+Cm9D67N1/AnTlulX7U5frPtd2tQ9tFF9vy3rtzMXuy98TKOlyTXCsz6Zrudc6be0v4bEy19Qll/n8afUdbz7yPReppfiL169fyj5rBz4DTGZdPJc2tUWcA42nEeO1982B7fELd3/OcdIApgrNvTWi2Qhm6zF37IfOoORltoUMxFMxLhu5EMF78m/umSjs3M6aYX3jnABBzxiYLVpdTqieAWqw/Eo1TSpxmQc3TnCfzHDhKTwS45sMuPIlOwF3zBHIijiTVfSkYI49P25R6vaxdfcF2w/adrWwRag3j7JLNOvcGr/uyZEsXCeUrBHcOy7hjuEVmeq8ofoYuwSm00bmdg4o2TAUkSzFtuERzOo+Xe4XzkvuzyvYE81Vrh9b5XjkOLgU6K6+xXK5Tx7bn/0ZilPjzSbivYEkCC/CJUN1x/AKVs1PubDYbBqqC4faj5q9IpFYFm0TBdypJOvL7BX+8UR53OwdUhDbx+cS3c6XLDYNl/Ne/VlRLXua0k787/0ZTGQJVLeLdzZcBWXirPOO11oZ626h+pQnnds63j68u/NpF7doC/P8H7t35V+fMcUO1n+5EBquz0+9yXGGIMfMUfs8zESNaEaC2ecHnsGxJKuTEXcLBI8BwGmmWvoUYWMJFA4tzKFHTGhhEyxq2pY9bgla5uzTW0HQEtwM0DRLyGjKGPwCAaUlGo5oliLY2ZcZ1JyALzFu5rYgq+PxrncJZb/t1fMCZ5nrPIl+hPBUxLGR6bw3gwAPcKsCn8bBde4ITw4rkFL18WVi3N7z4x6bM/swt7BUxKrrqYJHkMpAQ3Wu5rB81YUgFdX5TGc7dTxM3a8isoX11yWUEz3WEvOsxwIhsm9oUe4SysIf3/GR9rmJtM+v+GwTUdtqU5yb4CmUXE2lLdEwCGgmAlrs52a6xJ7/dea1mnrTumk+gstXfHtwCWwrksS3nRnn+lfHq/alWtCrE+V+wsrPeu6ynsZMbc4CVUx7fb+9qeb8xhZP6Lm3TzwlJCxGY096Ij1f/DR9PM7ffmOL9YeHYnn3jtU9fvWYRCo/jwxI0I/7vVNsxj94Nc6NEhTBLn4rAWlddt2AcHFs1gTNfb5TqUBzb81oNoIZ8BG7ckXs1ay29RMuaiCbs9AWK1EOvcqEVmVAC5vQIoYVZSotwHD/77KE2hMa5+ABXZZd9j0ew1JMLOq5mGX/9v7sXMlmhgZTZ7Linm8qOMARt951Yht7vSuThSKaYwWzI9BVq7GwLAuLrZEJmEFuv7dFcoA7AXuAfbx2uhNuuwcwZcL3zLfe+SvmpkmIZZO5RbPoQj025fjlvlTRLq23dqYLNfjPJYqVcTLPtlxtEyeftx/KdlIsR21RrBxXQrEs8OZ2hjUWv9+DWolm4VaUSnuiUaEzjoDypRMCVRWjiVwkxLp4bbzWZXjeJ8qdbHImrbmxwsvfpcI6pthl3gp9XuHuFebi+L3HJazn6jrHsli9mFaDFk14ggQV9RWTqi6O0EsUnJiKW4BoK6aLVKcNP/cVtQ8Zc53CjYq31HptUIMaY69VHnfqsn67nJXeio8QvQoDjS2a6yStHM29KdOsBDNBEA0InuzdgNqeIAiCqBU099aIZiOYvVZi4VZvP+Dwbw/4W9WYYwlUrYCawcGiHHpYWJcNy/rLuVMURNdgBoSlmbnTtsl9J7g4FQspC1h3iRqDtBZ6C45Y+2AwA5ptYXYsw7Iyn2pthjwpnhPitjq7rMXeY/C6Z6g5k1XrsmJhNgOAkclhBrllXQ5y6y7atiBbncHOaW0/uNKsinnWzb17wNK/2fAcC/esF+89lmI/pJFGseSayvlSfY+FhdlVeMRw0sWJ86Tmbpbbu8boXubjBuhYlw1uBxNyWSXQa6lmHFbBHIHqzmP7y1tDU83sgHxmKfYrj6H6R+BxMf38pBJAjwUbHcIlQ30UD7jTscX4KivvEz++R0JfZvE+UZtk9+Mlxg/bPkb3l9fB6+csUuQJa7WfZVRjdgAgcwcyen13xTrViqxaz71WZwC+7b0ktrrypF0YxLHUCerPjI//sWo09f+sY8ftv8yf+P7pzr6E37jf+LxPIryfgXPO3VZpr+WZ1/Z80txbI5qPYDa4lTuSeUQHj/WsULWC11VIXt+m4w8qhIhWZUKL2v7KUXuy0jTwoFVuWrhE+LpzAK4CILaDlvu9S0hZYpEZ3CqWovqwKa4eXNesksgBBkPmOXYXCLE6dc6Lr3D0uFvIYDzGYtap7YUolEVHNEskCx9my1cZMDI4jEwTPIODBUwwjVs5UhWxzE0mgxMZOGAya+KQ47XFnum9qfEcl+J+4ZxPz/EiVsCqy4U7hibuugDpnuEqby1cIEQBFEMZLwNYwOMDrtyIiWOJccv2Ps/kztwns24YqusFnF8SdRJm7mhsqwN7nRDOIupEaSb97HVWu3mUrBxNnoBmQlPcDLzCyStSTe64LviJXD9i+oS/v3N12/mNLdl9JjNOL97+/d5LlxHlB8PrzuKIX+WGVnXnYO6AQvk18nHdUElU8trvvdgm1q/c5/MBd/2dyJc8kX+xd3JmzL8fb8BkTdHAY4roOGPyCAvlf1Wwe/+XNxoJfMvVfNwAXBmiagTNvTWi2QhmWQgDkGLSWWkv9l4TatESCLHMFLEMQGYh4JZFWQgTjYFrOsygZr8sH2IxFnW/1s7FOJm9Xyb3CcASx7ZA57Yok9sYbgEuj01YsHUGHmC2cIZTrtoWaq6Ua8r3Or7PtyW2Yktme9vY/6uWaDugT/otZwA8aFuWM01LLOuWWLYSiHCAO8KMmwA0KyhSVn4S55JbIhrwWF65fQDcEcExQtpPFNtWZCF2Xccl+oZnP8KHOBIrlGU/LlMMd4IntdjzruLypfbOraJL07MfjtibLRVPIRyZ1lBU8DKZWzR70s5xveZOzNw0wVOwclDgSeNDg+PD7GedMxlLmF0imRRwsVk3kvtx99uv6j+ctLXZnvjUYiXJjMFkDH4FTtTjiZr290u1JkMRq3Ledgsz1RodY532nNKYJ6hCnMpt4jS037u0aIInAQK/1Hs6/C388bJoxAuii+t3rj7RiHMj5rf/eNeFb1pB5u+r7L0h8VaX9CtC47R1Cta4gjlrqf9p7q0ZzUYwR1toQFCT6b5UC57rvecGUD4K14Qg4vKxtpPRgFsBeHAEBA/AEsoZmrTuuvC8dSrbKeZGzyNw+Zjf4FYbbieYY8ztVuLKM+1YMC3XB6bsSxXNzCXIYvAR93K5es5UQWf/r7phmBni3FhWZR4EzKBlWdZCBpjGoemmHR9pTRLW4y5LTVoWDFiWZaaYPhVBDMCyIpvWjYbLrcH+3qufs1juWiZcKYT4FHmVdWd3Mdur6eJEjmVDFc6eID7GoUXEkwCOZH7nvTd9rhsdv8+IWTdIIkDUz8VI9q0+LQBzuwapNxtika45TyhqAlk5mjwZehRBe040OUNAc2dKMLkmLaAa4y5rKJB6porq2qqo2yVjkY7XryqOkxXroq1qUffu2wRzZRhxubUINw3pdhErAk0wmIBHLMcKveqsy9W5QcQrMe49nupwZRlJcptE+Y3jtdOVNqprhF/9uHi5wwWJ0hjKmxVfa0zsjYhzs6X0j9gsJ5wzWT2zxtDcWyOaj2DOYkCASeGphS0Bo/qfOuKHx4gPaVm2H3Nbbe1Gpi1MFQsy1xmMkG1ZDij9i6wXXish81h9GaRV2YK7ct8yjrjCJ54zmczwIESRKpYVES39at03vjE3E5rhXs69/apiOQAYIThFPzIsP2Ue5ECGCaab0HQhlrnct/A0t3y2PMcj9J3ffKScb1XwxhyPt51HQLtyMKszmZ9QlgKbS7Hs+DJzZxuo47Buejh3fwbqZyaKsaifm6+12f4soTs/YJyL65zJJyLO+LnLuuw+iXCs+KIj+YL1xEJjVtaVmmImuoh9oEm70cHApSAUwkmIQMs/15RCwbHmOdubPmlYfC2B8UyONn5ZMLyW5WSs2cn0Hc9POtG2KqoQt0Qvi9nG6xPuK4ThydbB3OepuiIwAq+bRTzBHOOKkaKLivfGIZHodRol2Xm8dvZy741ZvJLnrmU+YtlbFCZhqkCxb6+7jNInY8wl6oWfs5niufUZPM29NaDZCGaCIBoY3L7jSKk9QRAEUSto7q0RaRXMH3zwAe677z6sWbMGW7ZswZIlS3DOOefI9ZxzTJ06FY8//jh27tyJvn374uGHH0avXr1S3lc007Iwa1Hrcb4WdiyILuufIR6b248/7Jy0LMrt6mi2VU4W92DyOY0ZcHyFjSCDmcFg6ool0vC56DwFUxg8lmco1kvFmildQmyrn9/NIje5DHbkPnfItnuwy1opciN7DOzSEgvTbqrmFAYUa7Xzv+VqYFuUQ7YbRohb1mWRCSNoWZctv+UEX2Af64Kf77HrvRifmt/YY2X2+jXHWJqV/oTvMoPzmWqqy4bpti47fSnXl6c2ruPi4FjQvVZmq636hIC5zrHXIg0wmIyDGUw+0WAmnPywUe64Edm79bs+rHPMY86RGAMPWMGkNYWbqUV7V1eRjGh4BJiBgHgU5UFjlgVZuiZ4Hk1bbaxt3ZZh2Msc63Pc4iN2v359W31x37+ro6aBhX5jq9bKK57oMdvizN0ZQERf6j79LM/WW/e+EmXpAMRTAA6/HNKuYD3vb1YNLKDxAkMTkfQ5TNCvGccdw70+1sLu+5TDY+lXK0v6ZTcB4PZPZp7P0q7uK9017G31Wgb90dxbM9IqmPfv34+jjz4al19+Oc4777yY9TNnzsSsWbOwYMECdOvWDXfffTeGDRuGb775Brm5uantLEaExskiIBtYGwiR47gdMNdZcx6HOwLCDDIYIUUse0WcCNjzVKZjQrzafrqyvcmhRaxiFFZBCqfMNlMEfowPv86gBhCqPrxSgMnjgsxk4RJiikh2+SrHCCi4UseJYD/TruBnZlhimQc5eIYJHuBgAUsku4L8YLsnCNcTBucxFbMfTbk+J8/5tQ9Guqyo/4tjj/Pd9xXg6n7EMDy+ytKPXXXPsNfLfv26dF1z4kDsyVVxi3H8luFyn/ETzKYOMA2W77ZuX9+cybGCAZp93aiZMxgA6LZwFjcGslw2d14ARDEcs5aC2fqQKbVRUybITAR9gouc9GYGDM6keAY8KefiiBMA1T6WNu1+VZJxuXcJcWY641L/rkagx1vnHguXwtsVMKgIKlUMSn9nFtuXcLeoLrNIPBeU6qotqu11ODcgfkIz3o1EMoGUUjTHO79wj9nr5qOu8xuLt43fDYdfu+qWJ/InV9MDutp73CzEtl4/dMASzmqgX20LrdDcWzPSKphHjBiBESNG+K7jnGP27Nm47bbbMGrUKADAwoULUVhYiEWLFmH8+PEp7UuLALrtU6pFoQhgWMJVzKSqaJKChgl3U8VCyV3WYcua6ghmVyYMrgh0VYAL656wGtp9WqWgIQO0pFgOm0oQmV2pTVoKHfEjcFmrOcCisGrQc+V47X1wcQyK8JVCSgwNbsHoFdsiG4YQeaLEtZnh5FhGhgkErbRxWsC0xJ1mWhOHoTmxCMw+vcpEKG8obPHscgWr5ofQZVn2tOVK3944QnmjYB+/E3gJ9w2XKqRFpgr7s5b7V58EKNeS5a/OrZsxLi4KZZzMaad+PjL/tfIZQ+fua5WrFQyZVYVS06BXmpb1QjxJsU8wExlIxJMU5cZMnhedOZlfaiOYiSaPlYfZbWG2hJ+DZr/zCmAhpOMRz79Z9ltTUaH4VVv9GL5/++8zkT907HjVFHqaLURdotZjyY4ncsX2vr628D8n8fJWe/uOR7LnV4pfny7jienqhC7gWPnj+bTH8w+Xy5m7vfq/GLfaj98Nj9/Y1X2pNxkCIYqliDadoFhvUKU4PsZsa7PoI5WAPaLOaLA+zBs3bkR5eTlOPfVUuSwUCmHgwIEoKyuLK5irqqpQVVUl3+/ZsweALTg1O+Avwh2hDCbv3NwWSQ4ENCWfryOMrKBAVa3BTiPnWAYdNwo78MuTF1e6Q+jMTgDhuHzIktPc6YNFuF2IwhEvQjBDuGZ44LZIsqza1vacW0GIjip1rJDieByruWJA5nAFuEmxr6SLU62eIhOGaQf4SbGcobpgcDAmLMscpmEFOMi5QOMANCcQEJZQNkzmTiYibkQS5NqMm7LN+56523L72Bk8FmX1s1QEs8izHHNj5C0eoliXGazrQATnuZJTyM/CsSyL4jOuz0p+Xk6gaMwVwQEWtFyHtIiOQAWUmzAOzk0rx7XSgXyKIQS9KIJjW5d5LYL+6LFg0yHevKvDnYLLAEOQmTBc6slOOwevdTdWBKnoPuLVSELoxcPPxcPXKhxHOMW0i3H/cMYb24frnWscfu4qXiGXSg5p3zbe5ixOOw9Ji+YU3VXirU8l3V8i/NLF+WYsgX/RG9lPHEGtugJ5lwtRLAR5vJzWADzLgbqaAmnurRkNVjCXl5cDAAoLC13LCwsLsWnTprjbTZ8+HVOnTo1ZboQroWmAKXLkGtxl4QN8BLNtxVQFsxQ74vpRBLPBrBc3mXysDV6NYDYda7QYU1zBbPoLZhaNI5g1K0bd0HWYYDDsNGAmF5Zgq4CJaVpfZIMD3AAMUzkue5kQiuJvKShVwSwENLPamab9CnKYJrc6NmzBrLkFM+eAGdViJg6mAdCV1EomgxnRAZNB3OlwE2AGAwwGFmUuFwQeVvyE/QSzcoyqr7PXlYNxuz+lgp+fYDbta0OLwi2SzfiC2ToGWxCbDKZpu6S4bl6YFPNxBbNoGm9uE9dMBIhGDCBqWIV2REpE7imqwwFmmDGC2dB1GBEN0YAGwwzb26Y+oUZ5FVJ51BdFJOV9EAeHePNueL/7MzNgPbpWBbP6VfCzGst11T1GQt0J5nj7jGfF9SNeXIC1r0TrNM/7WFHmdU1Ipf9U2lTXLh2CuS6IJ5gTtfWDx2lX3d9c+RxNzqRrRkz/9jrv/owDVfb6mglZmntrRoMVzAJvhR7OecKqPVOmTMGNN94o3//000/o2bMnPn/hL/U2RoJo7uzduxd5eXlJtc3IyEBRURGWl7+e8n6KioqQkZGR8nZE/RJv3l1w+svpGxRBNHG2b9+e9LwL0NxbWxqsYC4qKgJgWZrbtWsnl2/dujXG6qwSCoUQCoXk+5ycHGzevBm5ubl1Vh6zKbBnzx506NABmzdvRsuWLdM9nAYHnZ/qEefoq6++QnFxcdLbZWZmYuPGjQiHwynvMyMjA5mZmSlvR9QvNO8mB80r1UPnqHp2796Njh07Ij8/P6XtaO6tHQ1WMHfp0gVFRUV4++230adPHwBAOBzGsmXLMGPGjKT70TQNhx56aH0Ns9HTsmVLmpQSQOenetq3bw9NS61EdmZmZrOffJsyNO8mhuaV6qFzVD2pzrsAzb21Ia2Ced++fdiwYYN8v3HjRqxduxb5+fno2LEjJk6ciGnTpqGkpAQlJSWYNm0asrKyMGbMmDSOmiAIgiAIgmhOpFUwr169GoMHD5bvhQ/c2LFjsWDBAkyePBkVFRWYMGGCLFyydOnS1HMwEwRBEARBEEQNSatgHjRoUMIoT8YYSktLUVpaevAG1UwIhUK48847XX6HhAOdn+qhc0QQqUHfmeqhc1Q9dI7SA+OUYI8gCIIgCIIg4pK6xzhBEARBEARBNCNIMBMEQRAEQRBEAkgwEwRBEARBEEQCSDATMQwaNAgTJ05sMvu87LLLcM4559RL3wRBEHUFzb0E0XBpsIVLiObFSy+9hGAwKN937twZEydOPOg/HgRBEM0JmnsJIjlIMBMNglRLfBIEQRC1h+ZegkgOcskgErJz505ceumlOOSQQ5CVlYURI0Zg/fr1cv2CBQvQqlUrvPXWW+jRowdycnJw2mmnYcuWLbJNNBrFddddh1atWqGgoAC33HILxo4d63pUpz4WHDRoEDZt2oQbbrgBjDEwxgAApaWlOOaYY1zjmz17Njp37izfG4aBG2+8Ue5r8uTJMbm+OeeYOXMmDjvsMLRo0QJHH300/vGPf9TNCSMIgqgDaO4liIYFCWYiIZdddhlWr16NV155BStWrADnHKeffjoikYhsc+DAAdx///145pln8MEHH+CHH37ApEmT5PoZM2bgueeew1NPPYUPP/wQe/bswcsvvxx3ny+99BIOPfRQ3HXXXdiyZYvrB6A6HnjgATz55JOYP38+li9fjh07dmDJkiWuNn/+85/x1FNP4dFHH8WXX36JG264Ab///e+xbNmy5E8MQRBEPUJzL0E0LMglg4jL+vXr8corr+DDDz/EgAEDAADPPfccOnTogJdffhkXXHABACASiWDevHno2rUrAOCaa67BXXfdJfuZM2cOpkyZgnPPPRcAMHfuXLz++utx95ufnw9d15Gbm4uioqKUxjx79mxMmTIF5513HgBg3rx5eOutt+T6/fv3Y9asWfj3v/+N/v37AwAOO+wwLF++HI899hgGDhyY0v4IgiDqGpp7CaLhQYKZiMu6desQCATQt29fuaygoABHHHEE1q1bJ5dlZWXJCRsA2rVrh61btwIAdu/ejV9++QUnnniiXK/rOo477jiYplmn4929eze2bNkiJ2MACAQCOP744+Wjwa+++gqVlZUYNmyYa9twOIw+ffrU6XgIgiBqAs29BNHwIMFMxCVe1XTOufRtA+CKsAYAxljMtmr7RH0nQtO0mO3Ux5PJIH4oXnvtNbRv3961LhQKpTwmgiCIuobmXoJoeJAPMxGXnj17IhqN4qOPPpLLtm/fjm+//RY9evRIqo+8vDwUFhbi448/lssMw8Cnn36acLuMjAwYhuFa1qZNG5SXl7sm7rVr17r21a5dO6xcuVIui0ajWLNmjeuYQqEQfvjhBxx++OGuV4cOHZI6JoIgiPqE5l6CaHiQhZmIS0lJCc4++2xceeWVeOyxx5Cbm4tbb70V7du3x9lnn510P9deey2mT5+Oww8/HN27d8ecOXOwc+fOGMuHSufOnfHBBx/gwgsvRCgUQuvWrTFo0CBs27YNM2fOxPnnn48333wTb7zxBlq2bCm3u/7663HvvfeipKQEPXr0wKxZs7Br1y65Pjc3F5MmTcINN9wA0zRx8sknY8+ePSgrK0NOTg7Gjh1bo3NFEARRV9DcSxAND7IwEwl56qmncNxxx2HkyJHo378/OOd4/fXXYx4FJuKWW27BRRddhEsvvRT9+/dHTk4Ohg8fjszMzLjb3HXXXfj+++/RtWtXtGnTBgDQo0cPPPLII3j44Ydx9NFH4+OPP3ZFhAPATTfdhEsvvRSXXXYZ+vfvj9zcXBnwIvjLX/6CO+64A9OnT0ePHj0wfPhwvPrqq+jSpUsKZ4YgCKL+oLmXIBoWjNfEoYkgaoFpmujRowdGjx6Nv/zlL+keDkEQRLOA5l6CqDnkkkHUO5s2bcLSpUsxcOBAVFVVYe7cudi4cSPGjBmT7qERBEE0WWjuJYi6g1wyiHpH0zQsWLAAJ5xwAk466SR8/vnneOedd5IOXiEIgiBSh+Zegqg7yCWDIAiCIAiCIBJAFmaCIAiCIAiCSAAJZoIgCIIgCIJIAAlmgiAIgiAIgkgACWaCIAiCIAiCSAAJZoIgCIIgCIJIAAlmgiAIgiAIgkgACWaCIAiCIAiCSAAJZoIgCIIgCIJIAAlmgiAIgiAIgkgACWaCIAiCIAiCSAAJZoIgCIIgCIJIQJMUzAsWLABjDKtXrwYA9OnTB+3bt4dhGHG3Oemkk9C6dWsMGDAAjLFqX6WlpQnH8Nxzz6FPnz7IzMxE69atMWbMGGzevNm37eLFi3HMMccgMzMTxcXFmDhxIvbt2+dqU1ZWhtLSUuzatStm+86dO2PkyJGJT0oz55FHHsGCBQtiln///fdgjLnWievn+++/P2jjq0s6d+6Myy67LN3DIJoA3rm0tjDGcM0119RJX2qf1c3HqeA3J1THK6+8AsYYCgoKUFVV5dumc+fOrt+Q7OxsHHvssZg7dy4453U0+oPH+++/D8YY3n//fbnssssuQ+fOnZPavqaf288//4zS0lKsXbs25W0bEoMGDcKgQYPSPQwiBZqkYPYybtw4/Pzzz3jrrbd813/77bcoKyvDJZdcgr/+9a9YsWKFfP35z38GADz11FOu5X/4wx/i7m/OnDn4/e9/j+OPPx7//Oc/MWPGDLz//vv4zW9+g507d7raPvfcc7joootwwgkn4I033sCdd96JBQsWYNSoUa52ZWVlmDp1qq9gJqonnmBu164dVqxYgTPOOOPgD6qeWLJkCW6//fZ0D4Mgmg3z588HAOzYsQMvv/xy3HYnnXSS/A155plnkJWVhWuvvRbTp08/SCOtX26//XYsWbKkXvfx888/Y+rUqY1eMD/yyCN45JFH0j0MIgUC6R7AweDiiy/GzTffjCeffBKnn356zPonn3wSAHDFFVegZ8+ernVff/01AODII4/E8ccfX+2+qqqqcPvtt+PMM8/EE088IZf37NkTAwYMwP3334977rkHAGAYBm6++Waceuqpsu3gwYORm5uLiy++GG+88QZGjBhRs4NuYEQiETDGEAg0rEsuFAqhX79+B32/9Xk++vTpU+d9EgThT3l5OV5//XWccsopKCsrw/z58/G73/3Ot22rVq1c883QoUPRsWNHPPbYY/h//+//Hawh1xtdu3ZN9xDqFMMwEI1GEQqF6rxvr9YgGj7NwsJ8yCGH4Nxzz8Wrr76K7du3u9YZhoFnnnkGJ5xwAnr37l3rfX3xxRfYvXt3jDDv378/8vPz8eKLL8plK1euxJYtW3D55Ze72l5wwQXIycmRd+qlpaW4+eabAQBdunSRj/TUR2EA8Oabb+LYY49FixYt0L17d3kjkAjx+HHmzJm455570LFjR2RmZuL444/Hu+++G9N+/fr1GDNmDNq2bYtQKIQePXrg4YcfdrURj+qeeeYZ3HTTTWjfvj1CoRA2bNggxzlkyBDk5eUhKysLPXr0iLGwrF69GmeddRby8/ORmZmJPn364G9/+5urjXhc/N577+Hqq69G69atUVBQgFGjRuHnn3+W7Tp37owvv/wSy5Ytk+dOPDZM5fHrO++8gyFDhqBly5bIysrCSSed5HuOvFR3PpLt95///CeOOuoohEIhHHbYYXjooYdQWloKxpirnZ9Lxg8//IDf//73rs/tgQcegGmaso04F/fffz9mzZqFLl26ICcnB/3798fKlStd/f3vf//DhRdeiOLiYoRCIRQWFmLIkCGN3upDpE5lZSVuuukmHHPMMcjLy0N+fj769++Pf/7zn3G3eeyxx9CtWzeEQiH07NkTixcvjmlTXl6O8ePH49BDD0VGRga6dOmCqVOnIhqNVjumZLf9+eefMXr0aOTm5iIvLw+/+93vUF5entLxL1y4ENFoFDfccANGjRqFd999F5s2bUpq25YtW6Jbt2745ZdfkmpfVVWFu+66Cz169EBmZiYKCgowePBglJWVyTYPP/wwfvvb36Jt27bIzs5G7969MXPmTEQiEVdfgwYNwpFHHolVq1bhN7/5DbKysnDYYYfh3nvvdc0LgGU4Ou2005CVlYXWrVvjqquuwt69e2PG5+eSsWfPHlx55ZUoKChATk4OTjvtNHz77bcx227YsAGXX345SkpKkJWVhfbt2+PMM8/E559/Ltu8//77OOGEEwAAl19+ua+LZDK/HX6ov4V33303unTpglAohPfeey+lfpcvX47+/fsjMzMT7du3x+23346//vWvMW5+fi4ZO3bswIQJE9C+fXtkZGTgsMMOw2233Rbj5iNcm5555hn06NEDWVlZOProo/Gvf/3L1W7btm344x//iA4dOiAUCqFNmzY46aST8M4771R7PohYGpa5rx4ZN24cnn/+eTz77LO4/vrr5fK33noLP//8M+6444462U84HAYA3zvSUCiE9evXo7KyEpmZmfjiiy8AAEcddZSrXTAYRPfu3eX6P/zhD9ixYwfmzJmDl156Ce3atQPgvkP97LPPcNNNN+HWW29FYWEh/vrXv2LcuHE4/PDD8dvf/rbacc+dOxedOnXC7NmzYZomZs6ciREjRmDZsmXo378/AOCrr77CgAED0LFjRzzwwAMoKirCW2+9heuuuw6//vor7rzzTlefU6ZMQf/+/TFv3jxomoa2bdti/vz5uPLKKzFw4EDMmzcPbdu2xbfffiuPFQDee+89nHbaaejbty/mzZuHvLw8LF68GL/73e9w4MCBGDH4hz/8AWeccQYWLVqEzZs34+abb8bvf/97/Pvf/wZguSicf/75yMvLk4/AUrUYPPvss7j00ktx9tlnY+HChQgGg3jssccwfPhwvPXWWxgyZEi1ffidj2T7ffPNNzFq1Cj89re/xQsvvIBoNIr7778/qR/abdu2YcCAAQiHw/jLX/6Czp0741//+hcmTZqE7777Luax4MMPP4zu3btj9uzZAKzHrKeffjo2btyIvLw8AMDpp58OwzAwc+ZMdOzYEb/++ivKysrIZagZUlVVhR07dmDSpElo3749wuEw3nnnHYwaNQpPPfUULr30Ulf7V155Be+99x7uuusuZGdn45FHHsFFF12EQCCA888/H4AleE888URomoY77rgDXbt2xYoVK3D33Xfj+++/x1NPPRV3PMluW1FRgaFDh+Lnn3/G9OnT0a1bN7z22mtxrcPxePLJJ9GuXTuMGDECLVq0wKJFi7BgwYKY+dCPaDSKzZs3o1u3bkm1HTFiBP7zn/9g4sSJOOWUUxCNRrFy5Ur88MMPGDBgAADgu+++w5gxY9ClSxdkZGTgs88+wz333IOvv/46xohSXl6Oiy++GDfddBPuvPNOLFmyBFOmTEFxcbH83H755RcMHDgQwWAQjzzyCAoLC/Hcc88l5YvOOcc555yDsrIy3HHHHTjhhBPw4Ycf+j45/fnnn1FQUIB7770Xbdq0wY4dO7Bw4UL07dsXn376KY444ggce+yxeOqpp3D55Zfjz3/+s3SlO/TQQwGk/tvhx//93/+hW7duuP/++9GyZUuUlJQk3e9///tfDBs2DN26dcPChQuRlZWFefPm4dlnn612v5WVlRg8eDC+++47TJ06FUcddRT+85//YPr06Vi7di1ee+01V/vXXnsNq1atwl133YWcnBzMnDkT5557Lr755hscdthhAIBLLrkEn3zyCe655x5069YNu3btwieffBJjOCSShDdBnnrqKQ6Ar1q1Si4zTZN36dKFH3XUUa625513Hs/KyuK7d+9Ouq9EbN++nWuaxseNG+davmHDBg6AA+A///wz55zze+65hwPgW7Zsienn1FNP5d26dZPv77vvPg6Ab9y4MaZtp06deGZmJt+0aZNcVlFRwfPz8/n48eMTjnfjxo0cAC8uLuYVFRVy+Z49e3h+fj4fOnSoXDZ8+HB+6KGHxpyra665hmdmZvIdO3Zwzjl/7733OAD+29/+1tVu7969vGXLlvzkk0/mpmnGHVP37t15nz59eCQScS0fOXIkb9euHTcMg3PufDYTJkxwtZs5c2bMee3VqxcfOHBg3ON/6qmn5DLRrzjX+/fv5/n5+fzMM890bWsYBj/66KP5iSeeGPdYOI9/PlLp94QTTuAdOnTgVVVVctnevXt5QUEB936NO3XqxMeOHSvf33rrrRwA/+ijj1ztrr76as4Y4998843rXPTu3ZtHo1HZ7uOPP+YA+PPPP8855/zXX3/lAPjs2bMTHjfR+El1/uOc82g0yiORCB83bhzv06ePax0A3qJFC15eXu5q3717d3744YfLZePHj+c5OTmuOY1zzu+//34OgH/55ZeuPu+8886Ut3300Uc5AP7Pf/7T1e7KK6+MmRPi8cEHH3AA/NZbb+WcO78znTp1ipnjOnXqxE8//XQeiUR4JBLhmzZt4ldeeSUPBoP8X//6V7X7evrppzkA/sQTT1TbVmAYBo9EIvzpp5/muq7LOZpzzgcOHOg7L/Ts2ZMPHz5cvr/llls4Y4yvXbvW1W7YsGEcAH/vvffksrFjx/JOnTrJ92+88QYHwB966CHXtuK3T/3cvESjUR4Oh3lJSQm/4YYb5PJVq1bF/XyS/e3wQ8x/Xbt25eFwuEb9XnDBBTw7O5tv27ZNtjEMg/fs2TPm93vgwIGu36R58+ZxAPxvf/ubax8zZszgAPjSpUvlMgC8sLCQ79mzRy4rLy/nmqbx6dOny2U5OTl84sSJcY+ZSI1m4ZIBWI8wLr/8cvz3v//FmjVrAADbt2/Hq6++ivPOOw8tW7ask/3k5+fj4osvxtNPP43HHnsMO3bswH//+19cfPHF0HUdAKBp7tPufaRe3XI/jjnmGHTs2FG+z8zMRLdu3ZJ+NDhq1ChkZmbK97m5uTjzzDPxwQcfwDAMVFZW4t1338W5556LrKwsRKNR+Tr99NNRWVkZ89j+vPPOc70vKyvDnj17MGHChLjHtmHDBnz99de4+OKLASBmP1u2bME333zj2uass85yvRcW+2SPvTrKysqwY8cOjB071jUe0zRx2mmnYdWqVdi/f3+1/fidj2T63b9/P1avXo1zzjkHGRkZcvucnByceeaZ1e733//+N3r27IkTTzzRtfyyyy4D51xa4gVnnHGGvFaB2POZn5+Prl274r777sOsWbPw6aefxjzCJZoXf//733HSSSchJycHgUAAwWAQ8+fPx7p162LaDhkyBIWFhfK9ruv43e9+hw0bNuDHH38EAPzrX//C4MGDUVxc7PpuCMvksmXL4o4l2W3fe+895ObmxswfY8aMSfq4RbDfFVdcAcCasy+77DJs2rTJ163q9ddfRzAYRDAYRKdOnfDEE09gzpw5SQUdv/HGG8jMzJT7isenn36Ks846CwUFBdB1HcFgEJdeeikMw4hxhSgqKoqZF4466ijX3Pnee++hV69eOProo13tkjlPwp1BzOeJto1Go5g2bRp69uyJjIwMBAIBZGRkYP369b7XkZea/Hb4cdZZZyEYDNao32XLluGUU05B69at5faapmH06NHV7vff//43srOz5VMWgbBee68nEe8kKCwsRNu2bV2f3YknnogFCxbg7rvvxsqVK2PccojUaDaCGbB8njRNk4/knnvuOYTDYYwbN65O9/Poo4/id7/7HSZMmICCggL06dMH3bt3xxlnnIFQKISCggIAkP/7PR7ZsWMH8vPzk96n6EslFAqhoqIiqe2Liop8l4XDYezbtw/bt29HNBrFnDlz5IQvXsJf+9dff3VtL1xHBNu2bQPgPD7zQ7gYTJo0KWY/EyZM8N2P99iFu0Wyx14dYkznn39+zJhmzJgBzjl27NhRbT/e85Fsvzt37gTn3CUyBH7LvGzfvj1m3wBQXFws16tUdz4ZY3j33XcxfPhwzJw5E8ceeyzatGmD6667ztevkWjavPTSSxg9ejTat2+PZ599FitWrMCqVatwxRVXoLKyMqZ9vLkGcK7FX375Ba+++mrM96JXr14AYucAlWS33b59u+/3x298fuzduxd///vfceKJJ6JNmzbYtWsXdu3ahXPPPReMMSmmVU4++WSsWrUKK1euxDPPPIPOnTvjmmuuwfLly6vd37Zt21BcXBxjcFH54Ycf8Jvf/AY//fQTHnroIfznP//BqlWrZJyJd05M5ndj+/btCT+zRGzfvh2BQCBmP37b3njjjbj99ttxzjnn4NVXX8VHH32EVatW4eijj05qLq/Jb4cf8ebpZPqNd00lO08XFRXFGJPatm2LQCBQ7TwNxH52L7zwAsaOHYu//vWvMo7q0ksvTdlPn7BoNj7MgCXUTj31VCxatAgPPPAAnnrqqaR9fFMhOzsbzzzzDP7v//4PmzdvRnFxMVq3bo3u3btjwIABMjOCCDL8/PPPXf7I0WgUX3/9NS666KI6HVci/L5A5eXlyMjIQE5ODoLBIHRdxyWXXII//elPvn106dLF9d77xW/Tpg0ASCuSH+LOfMqUKTGp9QRHHHFE/AOpB8SY5syZEzejRjITovd8JNuvyKjh56+czMRXUFCALVu2xCwXgZGqNSRZOnXqJAXBt99+i7/97W8oLS1FOBzGvHnzUu6PaLw8++yz6NKlC1544QXXNR4vH3G8uQZwREDr1q1x1FFHyYxCXsTNnh/JbltQUICPP/44qfH58fzzz+PAgQP4+OOPccghh8SsX7JkCXbu3Olal5eXJ7Mt9e3bF3379sXRRx+NCRMmYO3atQnFcJs2bbB8+XKYphm33csvv4z9+/fjpZdeQqdOneTy2gTjFhQUJPzMqts2Go1i+/btLoHnt62I55g2bZpr+a+//opWrVpVu6+6+u2IN08n029BQUGt5umPPvoInHPXGLZu3YpoNFqjebp169aYPXs2Zs+ejR9++AGvvPIKbr31VmzduhVvvvlmyv01d5qVYAas4L8333wTd9xxB9auXYt77rknJdeHVDjkkEPkZPnKK6/gm2++wYwZM+T6vn37ol27dliwYIEr0OQf//gH9u3b5/py1rXV1MtLL72E++67T7pl7N27F6+++ip+85vfQNd1ZGVlYfDgwfj0009x1FFHuVwDkmXAgAHIy8vDvHnzcOGFF/qe9yOOOAIlJSX47LPPYibO2pCKtd3LSSedhFatWuGrr76q06ILyfabkZGB448/Hi+//DLuv/9+ee737dsXExXtx5AhQzB9+nR88sknOPbYY+Xyp59+GowxDB48uFbH0a1bN/z5z3/Giy++iE8++aRWfRGND8YYMjIyXN/n8vLyuFky3n33Xfzyyy/yJtMwDLzwwgvo2rWrfPo0cuRIvP766+jatauvGE1EstsOHjwYf/vb3/DKK6+43DIWLVqU1H7mz5+P3NxcvPzyyzECdvXq1bj55purDY4rKSnB5MmTMXXqVLzwwgsJjSQjRozA888/jwULFsR1yxCfgRrUzDl3pThNlcGDB2PmzJn47LPPXG4ZyZwnse1zzz2H6667LuG2jLGYYOzXXnsNP/30Ew4//HC5LN5vYX39dqTS78CBA/H666/j119/lQLXNE38/e9/r3Y/Q4YMwd/+9je8/PLLOPfcc+Xyp59+Wq6vDR07dsQ111yDd999Fx9++GGt+mquNDvBfNZZZ6F169a47777oOs6xo4dW+f7ePHFF/Hzzz+jR48eqKysxPvvv4+HHnoIV111Fc4++2zZTtd1zJw5E5dccgnGjx+Piy66COvXr8fkyZMxbNgwnHbaabKtsEY/9NBDGDt2LILBII444giXD1Nt0HUdw4YNw4033gjTNDFjxgzs2bMHU6dOlW0eeughnHzyyfjNb36Dq6++Gp07d8bevXuxYcMGvPrqqzG+sF5ycnLwwAMP4A9/+AOGDh2KK6+8EoWFhdiwYQM+++wzzJ07F4CVcmrEiBEYPnw4LrvsMrRv3x47duzAunXr8MknnyQ1+Xjp3bs3Fi9ejBdeeAGHHXYYMjMzk04jmJOTgzlz5mDs2LHYsWMHzj//fLRt2xbbtm3DZ599hm3btuHRRx9NeUyp9HvXXXfhjDPOwPDhw3H99dfDMAzcd999yMnJqdYd5IYbbsDTTz+NM844A3fddRc6deqE1157DY888giuvvrqpCL0Vf773//immuuwQUXXICSkhJkZGTg3//+N/773//i1ltvTfk8EA2ff//7376VL08//XSMHDkSL730EiZMmIDzzz8fmzdvxl/+8he0a9cO69evj9mmdevWOOWUU3D77bfLLBlff/21K7XcXXfdhbfffhsDBgzAddddhyOOOAKVlZX4/vvv8frrr2PevHlxXbuS3fbSSy/Fgw8+iEsvvRT33HMPSkpK8Prrr8ctcKXyxRdf4OOPP8bVV1+NU045JWb9SSedhAceeADz58+v9iZ70qRJmDdvHqZOnYrRo0e74gdULrroIjz11FO46qqr8M0332Dw4MEwTRMfffQRevTogQsvvBDDhg1DRkYGLrroIkyePBmVlZV49NFHYwpmpcLEiRPx5JNP4owzzsDdd98ts2SIGgWJOPXUU/Hb3/4WkydPxv79+3H88cfjww8/xDPPPBPTduTIkViwYAG6d++Oo446CmvWrMF9990X8zl37doVLVq0wHPPPYcePXogJycHxcXFKC4urpffDiD536TbbrsNr776KoYMGYLbbrsNLVq0wLx582SMS6InCJdeeikefvhhjB07Ft9//z169+6N5cuXY9q0aTj99NMxdOjQlMa8e/duDB48GGPGjEH37t2Rm5uLVatWyYxLRA1IZ8RhfVFdZPcNN9zAAfDTTz+91n35sWTJEn7MMcfw7Oxs3qJFC3788cfz+fPnx80MsWjRIn7UUUfxjIwMXlRUxK+77jq+d+/emHZTpkzhxcXFXNM0V3Ryp06d+BlnnBHT3huF64eIDJ4xYwafOnUqP/TQQ3lGRgbv06cPf+utt3zbX3HFFbx9+/Y8GAzyNm3a8AEDBvC7775bthFZIf7+97/77vP111/nAwcO5NnZ2TwrK4v37NmTz5gxw9Xms88+46NHj+Zt27blwWCQFxUV8VNOOYXPmzdPton32Yj9q9Hb33//PT/11FN5bm4uByAjuZPJkiFYtmwZP+OMM3h+fj4PBoO8ffv2/Iwzzoh7nMmej2T7XbJkCe/duzfPyMjgHTt25Pfeey+/7rrr+CGHHOJq582SwTnnmzZt4mPGjOEFBQU8GAzyI444gt93332uqHFxLu67776YMUKJaP/ll1/4ZZddxrt3786zs7N5Tk4OP+qoo/iDDz7oyq5BNH7EdyHeS3xH7r33Xt65c2ceCoV4jx49+BNPPMHvvPPOmAwuAPif/vQn/sgjj/CuXbvyYDDIu3fvzp977rmYfW/bto1fd911vEuXLjwYDPL8/Hx+3HHH8dtuu43v27fP1ac320Ky2/7444/8vPPO4zk5OTw3N5efd955vKysrNosGRMnTuQAYjJHqIjsNGvWrOGcx5+nOef84Ycf5gD4woUL4/bHuZX96I477uAlJSU8IyODFxQU8FNOOYWXlZXJNq+++io/+uijeWZmJm/fvj2/+eabZbYKdU4cOHAg79WrV8w+vJkuOOf8q6++4sOGDeOZmZk8Pz+fjxs3jv/zn/+sNksG55zv2rWLX3HFFbxVq1Y8KyuLDxs2jH/99dcxn9vOnTv5uHHjeNu2bXlWVhY/+eST+X/+8x/f37Hnn3+ed+/enQeDwZh+kvnt8CPR/JdKv//5z3943759eSgU4kVFRfzmm2+WmS527dol2/kd1/bt2/lVV13F27VrxwOBAO/UqROfMmUKr6ysdLUT3yMv6txfWVnJr7rqKn7UUUfxli1b8hYtWvAjjjiC33nnnXz//v0JzwXhD+O8ERaxJ+qM77//Hl26dMF9992HSZMmpXs4RApEIhEcc8wxaN++PZYuXZru4RAEQRA+nHrqqfj+++99C7YQjYdm55JBEI2VcePGYdiwYWjXrh3Ky8sxb948rFu3Dg899FC6h0YQBEHAyvbRp08fdOjQATt27MBzzz2Ht99+2zdrCtG4IMFMEI2EvXv3YtKkSdi2bRuCwSCOPfZYvP766yn7thEEQRD1g2EYuOOOO1BeXg7GGHr27IlnnnkGv//979M9NKKWkEsGQRAEQRAEUSf89NNPuOWWW/DGG2+goqIC3bp1w/z583Hcccele2i1gizMBEEQBEEQRK3ZuXMnTjrpJAwePBhvvPEG2rZti++++y6pXNoNHbIwEwRBEARBELXm1ltvxYcffoj//Oc/6R5KndOsSmMTBNF8+OCDD3DmmWeiuLgYjDG8/PLLcl0kEsEtt9yC3r17Izs7G8XFxbj00ktl9UNBVVUVrr32WrRu3RrZ2dk466yzYipV7ty5E5dccgny8vKQl5eHSy65BLt27ToIR0gQBNGweOWVV3D88cfjggsuQNu2bdGnT59aFc5pSDR5C7Npmvj555+Rm5tbbxX9CKK5wjnH3r17UVxcnDApv5fKykqEw+GU95eRkSGrUVbHG2+8gQ8//BDHHnsszjvvPCxZsgTnnHMOACup//nnn48rr7wSRx99NHbu3ImJEyciGo1i9erVso+rr74ar776KhYsWICCggLcdNNN2LFjB9asWSMLTIwYMQI//vgjHn/8cQDAH//4R3Tu3BmvvvpqysfXVKB5lyDqj5rOu0DN517uKdkNWFUXvdUZxfx844034oILLsDHH3+MiRMn4rHHHsOll16a8n4bFGnK/3zQ2Lx5c8LE+/SiF71q/9q8eXPS38mKigpe1Fav0X6Kiop4RUVFyvMAAL5kyZKEbT7++GMOgG/atIlzbhVcCAaDfPHixbLNTz/9xDVN42+++Sbn3CroAICvXLlStlmxYgUHwL/++uuUx9lUoHmXXvSq/1cq8y7n1tyb16ZtjfaVk5MTs8xbMIhzzoPBIO/fv79r2bXXXsv79etXmymlQdDkg/5E6eiTcToCCKZ5NATRtIgiguV4PaUS7eFwGOVbDWxc0wktc5O3juzZa6LLcZsQDoeTtjKnwu7du8EYk8Epa9asQSQSwamnnirbFBcX48gjj0RZWRmGDx+OFStWIC8vD3379pVt+vXrh7y8PJSVleGII46o83E2BsT10P7qBdBCWWkeDUE0LcyqA/jp0ctSmncBa+7dvW0r7v9gFVrkJL9txb69mPTbE7B582a0bNlSLvdalwGgXbt26Nmzp2tZjx498OKLL6Y01oZIkxfM4hFCAEEEGAlmgqhTuPVfTR67Z+dYr2Qx7H3t2bPHtdzvsWCqVFZW4tZbb8WYMWPkD0J5eTkyMjJwyCGHuNoWFhaivLxctmnbtm1Mf23btpVtmiPietBCWSSYCaKeqKm7U4uc3JQEs6Bly5YuwezHSSedhG+++ca17Ntvv0WnTp1S3l9Dg4L+CIJICyZ4yi8A6NChgwywy8vLw/Tp02s1jkgkggsvvBCmaeKRRx6ptj33+PL5/Wh52xAEQTQHbrjhBqxcuRLTpk3Dhg0bsGjRIjz++OP405/+lO6h1Zomb2EmCKJhYsKEmWJ7AEk9FkyWSCSC0aNHY+PGjfj3v//t6reoqAjhcBg7d+50WZm3bt2KAQMGyDa//PJLTL/btm1DYWFhjcdFEATRGDnhhBOwZMkSTJkyBXfddRe6dOmC2bNn4+KLL0730GoNWZgJgkgLBucpvwDnsaB41VQwC7G8fv16vPPOOygoKHCtP+644xAMBvH222/LZVu2bMEXX3whBXP//v2xe/dufPzxx7LNRx99hN27d8s2BEEQzYmRI0fi888/R2VlJdatW4crr7wy3UOqE8jCTBBEWlDdLJJtnwr79u3Dhg0b5PuNGzdi7dq1yM/PR3FxMc4//3x88skn+Ne//gXDMKTPcX5+PjIyMpCXl4dx48bhpptuQkFBAfLz8zFp0iT07t0bQ4cOBWAFs5x22mm48sor8dhjjwGw0sqNHDmy2Qb8EQRBNEVIMBMEkRZMcBj1KJhXr16NwYMHy/c33ngjAGDs2LEoLS3FK6+8AgA45phjXNu99957GDRoEADgwQcfRCAQwOjRo1FRUYEhQ4ZgwYIFMgczADz33HO47rrrZDaNs846C3Pnzk1prARBEETDhgQzQRBpob4tzIMGDQJPUJcp0TpBZmYm5syZgzlz5sRtk5+fj2effTalsREEQRCNC/JhJgiCIAiCIIgEkIWZIIi0oAbyJdueIAiCINIBCWaCINKCab9SaU8QBEEQ6YAEM0EQacFIMegvlbYEQRAEUZeQYCYIIi0Y3Cl3nWx7giAIgkgHJJgJgkgL5JJBEARx8Cn9aRu07Iqk25v799XjaBoPJJgJgkgLJhgMsJTaEwRBEEQ6IMFMEERaMLn1SqU9QRAEQaQDEswEQaQFI0ULcyptCYIgCKIuIcFMEERaIMFMEARBNBZIMBMEkRZMzmDyFHyYU2hLEARBEHUJlcYmCIIgCIIgiASQhZkgiLRALhkEQRBEY4EEM0EQacGABiOFh1xGPY6FIAiCIBJBgpkgiLTAU/Rh5uTDTBAEQaQJEswEQaQFcskgCIIgGgskmAmCSAsG12DwFFwyqHAJQRAEkSbSniXjp59+wu9//3sUFBQgKysLxxxzDNasWSPXc85RWlqK4uJitGjRAoMGDcKXX36ZxhETBFEXmGAwoaXwIgszQRAEkR7SKph37tyJk046CcFgEG+88Qa++uorPPDAA2jVqpVsM3PmTMyaNQtz587FqlWrUFRUhGHDhmHv3r3pGzhBELVGuGSk8iIIgiCIdJBWl4wZM2agQ4cOeOqpp+Syzp07y78555g9ezZuu+02jBo1CgCwcOFCFBYWYtGiRRg/fvzBHjJBEHVE6i4Z5JNBEARRW95q/wFyczOTbr93byWOrcfxNBbSamF+5ZVXcPzxx+OCCy5A27Zt0adPHzzxxBNy/caNG1FeXo5TTz1VLguFQhg4cCDKysp8+6yqqsKePXtcL4IgGh6WS0ZqL6JhQvMuQRBNnbQK5v/973949NFHUVJSgrfeegtXXXUVrrvuOjz99NMAgPLycgBAYWGha7vCwkK5zsv06dORl5cnXx06dKjfgyAIokaYdh7mZF9m+kMuiDjQvEsQRFMnrb9Apmni2GOPxbRp09CnTx+MHz8eV155JR599FFXO8bcliXOecwywZQpU7B792752rx5c72NnyCImiNcMlJ5EQ0TmncJgmjqpNWHuV27dujZs6drWY8ePfDiiy8CAIqKigBYluZ27drJNlu3bo2xOgtCoRBCoVA9jZggCILwQvMuQRBNnbSabE466SR88803rmXffvstOnXqBADo0qULioqK8Pbbb8v14XAYy5Ytw4ABAw7qWAmCqFtSSylHLhkEQRBE+kirhfmGG27AgAEDMG3aNIwePRoff/wxHn/8cTz++OMALFeMiRMnYtq0aSgpKUFJSQmmTZuGrKwsjBkzJp1DJwiilhicwUih3HUqbQmCIAiiLkmrYD7hhBOwZMkSTJkyBXfddRe6dOmC2bNn4+KLL5ZtJk+ejIqKCkyYMAE7d+5E3759sXTpUuTm5qZx5ARB1BYRzJd8e0orRxAEQaSHtJfGHjlyJEaOHBl3PWMMpaWlKC0tPXiDIgii3jG5BjOFQD6T8jATBEEQaSLtgpkgiOYJWZgJgiCIxgIJZoIg0oKJ1PySzfobCkEQBEEkhAQzQRBpIdXMF5QlgyAIgkgXJJgJgkgLqRYjocIlBEEQRLogwUwQRFowwWAiFZcMSitHEARBpAcSzARBpAWyMBMEQRx8Nv/4BLKzk59P9+9PPoKktLQUU6dOdS0rLCxEeXl50n00VEgwEwSRFlLPkkGCmSAIoqHTq1cvvPPOO/K9rutpHE3dQYKZIAiCIAiCqBMCgQCKiorSPYw6h0w2BEGkBZOzlF+p8MEHH+DMM89EcXExGGN4+eWXXes55ygtLUVxcTFatGiBQYMG4csvv3S1qaqqwrXXXovWrVsjOzsbZ511Fn788UdXm507d+KSSy5BXl4e8vLycMkll2DXrl01OSUEQRANlj179rheVVVVvu3Wr1+P4uJidOnSBRdeeCH+97//HeSR1g8kmJs55sBjYQ6yXwOPTfdwiGaEabtkJPtKNa3c/v37cfTRR2Pu3Lm+62fOnIlZs2Zh7ty5WLVqFYqKijBs2DDs3btXtpk4cSKWLFmCxYsXY/ny5di3bx9GjhwJwzBkmzFjxmDt2rV488038eabb2Lt2rW45JJLanZSiGbB90OXu14E0Rjo0KGDNAzk5eVh+vTpMW369u2Lp59+Gm+99RaeeOIJlJeXY8CAAdi+fXsaRly3kEtGM4cZJsAYuM4ABhhDjgMAcMYQeGd1mkdHNGVSL42dmmAeMWIERowY4buOc47Zs2fjtttuw6hRowAACxcuRGFhIRYtWoTx48dj9+7dmD9/Pp555hkMHToUAPDss8+iQ4cOeOeddzB8+HCsW7cOb775JlauXIm+ffsCAJ544gn0798f33zzDY444oiUxkw0T7yiufM7J6dpJAQRn82bN6Nly5byfSgUimmjzrm9e/dG//790bVrVyxcuBA33njjQRlnfUGCuZnDlq+1/jj5GHBdA2cMZsB69B0+7QSAAeAA40DwrVVpGyfR9DDAYKSQKk603bNnj2t5KBTynbgTsXHjRpSXl+PUU0919TNw4ECUlZVh/PjxWLNmDSKRiKtNcXExjjzySJSVlWH48OFYsWIF8vLypFgGgH79+iEvLw9lZWUkmAlfhCCOZ11Wl5N4JhoKLVu2dAnmZMjOzkbv3r2xfv36ehrVwYNcMggAtnDm3BLIOgMP2C+dgQcZzCBD1cgTUTXyRITPOBHhESeke8hEI0dYmFN5Ack9FqwOkeKosLDQtVxNf1ReXo6MjAwccsghCdu0bds2pv+2bds2iTRKRP2SjBgm9w2iMVNVVYV169ahXbt26R5KrSELM0EQacEAUrQwWyTzWDBZGHPvn3Mes8yLt41f+2T6IQiCaGpMmjQJZ555Jjp27IitW7fi7rvvxp49ezB27Nh0D63WkGBuhhiDjwM0y08ZAMAAzmD5Mmvib2eZF27/UzXyRABA6F8fH6SRE02Jmvow1+SxoBeR8qi8vNxl+di6dau0OhcVFSEcDmPnzp0uK/PWrVsxYMAA2eaXX36J6X/btm0x1muCqAsLMblrEA2ZH3/8ERdddBF+/fVXtGnTBv369cPKlSvRqVOndA+t1pBLRjNEf28N9HfXgOuWv7KpM3DNEsvQWIxY5gyWkFZf9rZcZ6g8uy8qzzoxrcdEND5Epb9UXnVFly5dUFRUhLffflsuC4fDWLZsmRTDxx13HILBoKvNli1b8MUXX8g2/fv3x+7du/Hxx85N40cffYTdu3fLNgQh6PzOyXUqcslNg2hoLF68GD///DPC4TB++uknvPjii+jZs2e6h1UnkIW5GRMviK9q5Il2rB93WZhdaXCFmObcessZKs7pC8aBzH9+VF9DJpoQHAxmCi4ZPIW2ALBv3z5s2LBBvt+4cSPWrl2L/Px8dOzYERMnTsS0adNQUlKCkpISTJs2DVlZWRgzZgwAIC8vD+PGjcNNN92EgoIC5OfnY9KkSejdu7fMmtGjRw+cdtppuPLKK/HYY48BAP74xz9i5MiRFPBHxMVPNNdG+H4/dDlZmwminiHBTMQQ+tfHLtHMwMBhJ8wQrhtCuwjhDCuTBuccFef2BTjQ4mUSzkR8UrUap2phXr16NQYPHizfi5RGY8eOxYIFCzB58mRUVFRgwoQJ2LlzJ/r27YulS5ciNzdXbvPggw8iEAhg9OjRqKiowJAhQ7BgwQJXqdfnnnsO1113ncymcdZZZ8XN/UwQ8aguc0Z1iO1IOBNE/UCCmSCIJsmgQYPkExA/GGMoLS1FaWlp3DaZmZmYM2cO5syZE7dNfn4+nn322doMlSAIgmjgkGAmfFED+SrPOlFamV1PxW3fZgBgpnDZYFZ2Og4cGGW5aLRYQpZmIpZUy12nWhqbIBojqoW4JtZmsjQT1ZGd9VdkZ2UnvwHfD2BovY2nsUCCmaiWzFcc8VxxTl9LDWsMpngqzQAu/ubOf8y0xDNB+CFKXqfSniCaE7Vx0yC/ZoKoW0gwEymh+iXvv6AfVLdSkY5OYlcJ3H9+P2T/Y+XBGiLRSCALM0EkR02tziSaCaLuIJMNUWOy/74SWhTSqixhzM7pbFcKDAD7ftcvHUMkGjAmtJRfBNHcSTU1HaWdI4i6gSzMBEGkBYMzGClYjVNpSxAEQRB1CZlsiFqR9eJK5LywEkzULbZTzskCJwyyKMq+C8nKTDgIl4xUXgRBWKRiaSYrM0HUHhLMRJ3guGdwWSnQXSHQctEgCAG3S2Mn++J1WOmPIJoK5KNMEAcH+gUi6ozsv69E7vMrwUx7gU9J7T0X90/rGImGgwGW8osgiFiSEc1kZSaI2kGCmahzchetgGYAojwg16y0c6Zui+bfk2gmAJOn6paR7hETRMOFLM0EUb9Q0B9BEGlBuFqk0p4gCIIg0gH9AjVSKs86Md1DSEjuohXIe2aFrADIPZbm3ZeQlbm5Y4Kl/CKIdPLGy5PSPYSEVBcISG4ZBFFzyMLcyKg860SZdeLAef3AGRp0UZC8p1dg5+X9ZUETmeiAAbvG9kerhSvSNjaCIIhkUIWy+veIc+5Px3CqpfM7J8cVx1TMhCBqBgnmxgZjlvhkDGbAstruHdMf4Bx62Erz1lCRWTK4ZWlmVDe7WUN5mInGTkMWz4lEM0EQqUMuGY2MzH86palFNgrL1YEh2oJh70X9sO93/XBgVN80jTCWQ55aAe7Nz2ynmtsxbkC6h0ekiVRSyqXq70wQdUkyYviNlyc1OJeNeJZkEtIEkTpkYSYIIi2YSK0YCfkwEwRB1J533nkHoVAo6fZVVVX1OJrGA5lsGiEtlnxkFQjhtpXZ9mzgzLI0m0EGI1PD/gsaTmW9/PllYMIDQ7NewtK84w9kZW6O8BQD/jgJZiKNJOtyQVZmgmiakGBupGS99BGYycEMWP+bjouGwAwy7PtdAxLNfy1zqgDaYlkI5+1XkmhublBpbKKxQaKZIJov5JLRiMl6yfJn3n9BP3Cdy0wUYCK4zlq2/4J+yP57AwkGtAP+wKy/xYtR/F+dEx5xApjBoUU4mGFCi3KrWsjKz9I9NACUh5lonAjRXJ0ofuPlSQ0uEJA4OFy78dGYZXO6XJ2GkRB1Cf0CNQGy/77StjRbwtOyOHMpQhuMWAZQ8HiZb/U/0kJ1y94x/VGZH0A4L4BIro5oVgBGCx1mSAc/+Zh0Dw8AWZiJxs2Ic+5PKIgbmlgmK/PBwU8si+Xx1hGNA7IwEwSRFlItRkJBfwRBEES6SKtgLi0txdSpU13LCgsLUV5eDgDgnGPq1Kl4/PHHsXPnTvTt2xcPP/wwevXqlY7hNmgakhU5GVwWZWZ5j2ybYPkxt3mkLD2DaiLsvagfopmAGWCIZjLoYYZAJYcZ1qBFObSwiUC/o9PumpGq1ZgszERDpKFZkmuCsDJTQZPakYwF+dqNj5J7RiMl7Q/Ce/XqhS1btsjX559/LtfNnDkTs2bNwty5c7Fq1SoUFRVh2LBh2Lt3bxpHTNQFauCfqVvuGeK19RoKAKwNzM6eokUs1xwwwMhgiGRrCOdqCOfqMFoEgAHHpHWc5JJBEA0Lcs84OJBrRuMk7YI5EAigqKhIvtq0aQPAsi7Pnj0bt912G0aNGoUjjzwSCxcuxIEDB7Bo0aI0j5qoDW0etv2YPULZFD7NAeCX60k01xQzwCzBHAX0iC2cOQDOYQYYIjkawnkBRLMD4L/pk75xkmAmiAYHieaDA4nmxkfaBfP69etRXFyMLl264MILL8T//vc/AMDGjRtRXl6OU089VbYNhUIYOHAgysriP7KvqqrCnj17XC+iAWKnlzMDlkAW//OAY3EunziAhHMNEDcepuJwxUwOLQoww0pFGG6pIdwygEh2AObAY9M3WKJJQPNu04JE88GBRHPjIq2CuW/fvnj66afx1ltv4YknnkB5eTkGDBiA7du3Sz/mwsJC1zaqj7Mf06dPR15ennx16NChXo+BIIiaQRbmpgPNuwRBNHXSKphHjBiB8847D71798bQoUPx2muvAQAWLlwo2zDm/pHknMcsU5kyZQp2794tX5s3b66fwRO1gtsuGdAsS6gZtF+KxVksK7+BrMyp0GrhCgBW4Rojw3bRsK3LetjyceYMCOcwRHJ0RHMCMAcdfCszB1Ks9Ec0VGjebXqQlTl1KJivaZN2lwyV7Oxs9O7dG+vXr0dRUREAxFiTt27dGmN1VgmFQmjZsqXrRTRAmPUSPstcFc32i9sC2swAfr55AMpvJOGcLIc8tQKBSg4jg8EIMZgZDFyz05HYBW3AACPEEMnSEG2hwxhy3EEdI1mYmw407zZNvh+6nIRziqQqmskto/HQoPIwV1VVYd26dfjNb36DLl26oKioCG+//Tb69LECk8LhMJYtW4YZM2akeaREncAgS2Nz5lT74/Y/TFQBtMt+m6SXUiLvacvSvOMPAxBpwaAHAGYw6T+uGZBFZKItNMsiPeIEMNP5PIJvraq38VFaOYIgmiJzulydkhD2tiVLdcMkrYJ50qRJOPPMM9GxY0ds3boVd999N/bs2YOxY8eCMYaJEydi2rRpKCkpQUlJCaZNm4asrCyMGTMmncMm6gA1rRzX7fdQSmQLQ6hdSpsZ1uOQn28egOL7KE9zKuT/tQw7r+iPSJYjlvUqAFEOZlptuMbAdcDQbFFqt2PDjkfg7dX1Mi4SzATROPh+6HLK0ZwiqYpmFbFdfQnnG44/Cy2zcpJuv+fAPtyLe+tlLI2JtArmH3/8ERdddBF+/fVXtGnTBv369cPKlSvRqVMnAMDkyZNRUVGBCRMmyMIlS5cuRW5ubjqHTRBEHUCCmSAIgmgspFUwL168OOF6xhhKS0tRWlp6cAZEHDwU67KpA9C445Zhm5uZsDILK6gJsAbldd94OOTJFdh+5QAYLQAjKCotMiDMoZuO+wtgBQmaQcXaX09wzsBTEMGptCUIgkg3tbEyEw0Pkh9EWlDFMte5Jx8zB9ftlwbL1xmWji6eQe4YNaXgiTLoVZYQjmYB0WwgmslgBqwT3OLlj9Di5Y+sxoxZebL1+hOpqWTIEC+CIA4+5I5Rc6pzq5jT5WryWW4kkGAm0ovGrfRyQiAHxEuknbNFM1EnFDxWBi1qnVsjAzBCtsVZ0aIi7RzXGHiwHgUzZckgCKIZQIK4aUBShEgLMuBPgyWWNbisytbfTgYNbqdBI2qPXgXpfgHlvFaNPBHhM06Uaee4Vr8WZuGSkcqLIAiiKXHtxkebtNvG9OnTZRKHxg4JZoIgCIIgCKJOWbVqFR5//HEcddRR6R5KnUCCmUgLqoXZqvrHAR2A7dNsrVN8mMnCXGcUPFYmcy2DQQZYMsM2O4tKmgyOT3M9UN8uGdFoFH/+85/RpUsXtGjRAocddhjuuusumKYp23DOUVpaiuLiYrRo0QKDBg3Cl19+6eqnqqoK1157LVq3bo3s7GycddZZ+PHHH+vkHBAE0TxI1S2jsbtx7Nu3DxdffDGeeOIJHHLIIekeTp1AgplIC9wO7oPtfuH8zwHxvxTKXOYFJuoGLWIVLpG+yhpghDQYGQzRTOt9fdeirm+XjBkzZmDevHmYO3cu1q1bh5kzZ+K+++7DnDlzZJuZM2di1qxZmDt3LlatWoWioiIMGzYMe/fulW0mTpyIJUuWYPHixVi+fDn27duHkSNHwjCMOjsXBEEQDZ09e/a4XlVVVXHb/ulPf8IZZ5yBoUOHHsQR1i8kmIm0wHX7pVliGRq3AwC54tfMZbo5Est1iwjsA7PKkIdzGCI5GiLZmrT61zc8RetyqoJ5xYoVOPvss3HGGWegc+fOOP/883Hqqadi9erV9v45Zs+ejdtuuw2jRo3CkUceiYULF+LAgQNYtGgRAGD37t2YP38+HnjgAQwdOhR9+vTBs88+i88//xzvvPNOnZ8TgiCaLslajRuqdblDhw7Iy8uTr+nTp/u2W7x4MT755JO46xsrJJiJg84PpQNgBrlMH2dlwuBg4iVEs6a4DZBLRp3C7NzLpg6YGYARYlbWjKBdWZEDWrR+TcwcVnxh0i97u2StHCeffDLeffddfPvttwCAzz77DMuXL8fpp58OANi4cSPKy8tx6qmnym1CoRAGDhyIsjIrfeGaNWsQiURcbYqLi3HkkUfKNgRBEM2BzZs3Y/fu3fI1ZcoU3zbXX389nn32WWRmZqZhlPVHWguXEATRfDHBwFK4CxJ5mDt06OBafuedd/oWN7rllluwe/dudO/eHbquwzAM3HPPPbjooosAAOXl5QCAwsJC13aFhYXYtGmTbJORkRHjg1dYWCi3JwiCaA60bNkSLVu2TNhmzZo12Lp1K4477ji5zDAMfPDBB5g7dy6qqqqg63p9D7VeIMFMHHR4wHIDMJUgP6YUKLGi0OAKPgOAjneSRa/O4E7ApalbFRQ5Y9BMy5TLTMvPuV6HUMNKf5s3b3ZN2qFQyLf9Cy+8gGeffRaLFi1Cr169sHbtWkycOBHFxcUYO3asbMeYewyc85hlsWOpvg1BNAWoaAmRCkOGDMHnn3/uWnb55Zeje/fuuOWWWxqtWAZIMBMHmR9KB8DIsF0xgiZ4wHLBsEQxh1THQouQ/3L9wJXzyq0AQGZyqwy57Y6R/Y+V9ToEkzOwFD5ckSUjGSsHANx888249dZbceGFFwIAevfujU2bNmH69OkYO3YsioqKAFhW5Hbt2snttm7dKq3ORUVFCIfD2Llzp8vKvHXrVgwYMCDpsRNEuvl+6PJ0D4FIgobqv5wsubm5OPLII13LsrOzUVBQELO8sUGCmTiomBmAGeLgGRwIcjDdBNMcX1nOAXJWrn8YVwL/1GWm9cpZXL9iGXB8k1NpnwoHDhyAprnDNHRdl2nlunTpgqKiIrz99tvo06cPACAcDmPZsmWYMWMGAOC4445DMBjE22+/jdGjRwMAtmzZgi+++AIzZ85MbUAEQRAJOFhiefvy3QiHokm331u1vx5H03ggwUwcNDb9ZQCMFrZYDhlgQUssiyfb3ARgwv2Y3hZ29Z3irNlhn1MZS2kLZWZw5D5f/2IZqLlLRrKceeaZuOeee9CxY0f06tULn376KWbNmoUrrrgCAGT1qWnTpqGkpAQlJSWYNm0asrKyMGbMGABAXl4exo0bh5tuugkFBQXIz8/HpEmT0Lt37yaVLolo2pB1ueHT2C3LiXj//ffTPYQ6gQQzQRBpob4F85w5c3D77bdjwoQJ2Lp1K4qLizF+/Hjccccdss3kyZNRUVGBCRMmYOfOnejbty+WLl2K3Nxc2ebBBx9EIBDA6NGjUVFRgSFDhmDBggWN2hePIAiCSA0SzMRBI5rFYYZMINOAFjSgBUxoumU65iaDwe3H58KibKc+gwl0vo0C/uoSpljumWH5LGtRHDTrMlBzH+Zkyc3NxezZszF79uy4bRhjKC0t9c2yIcjMzMScOXNcBU9qy//93/8l3fa6666rs/0SRCpQwN/BoSlbl5sSJJiJg8J3D/SH2cIEsgzoGQb0gAFdN6FpHKbJYDIGI+oIZmYywH4xk3ya65rWj5ah/AYraE34LecuWpHmUTUfHnzwQdf7bdu24cCBA2jVqhUAYNeuXcjKykLbtm1JMBO1gtwxGhZzulyNazc+6npPNA6ocAlR7/zv/v4wcwwgOwo9FEUwI4pQRhTBgIGAbiCgmzLMj5sMXAply/rZ5VayLtcLDI4vs3nwd59S0ZIUAwQbOhs3bpSve+65B8cccwzWrVuHHTt2YMeOHVi3bh2OPfZY/OUvf0n3UIlGTG3EMlmXCcINWZiJeieaF4WeFUUwFEUoGLUEMuPQwGFwDXbSAksoc9uyHGVgBsNhN5PVsz7YNmEAOLPumNMhlgEhglPxYa7HwaSR22+/Hf/4xz9wxBFHyGVHHHEEHnzwQZx//vm4+OKL0zg6orFCYrlholqXicYFCWaiXlk/px+CuRXIahFGKBCFrnHomqXQIoYOcMs31eSWZZkbDCzqWJeJ+oG7CsUAec8c/BuT+g76ayxs2bIFkUhslRjDMPDLL7+kYUREY4fcMAii7iGXDIIg0gKvwaspMmTIEFx55ZVYvXo1uG1GX716NcaPH0+p6wiCIBoIJJiJemP9o32h5VfhkNwDaNmiEtkZYWRnVCFDj1ouGYxb1mXVb9lggG1lJneM+oPrkL7L6XPJYCm/miJPPvkk2rdvjxNPPBGZmZkIhULo27cv2rVrh7/+9a/pHh7RyCDrMkHUD+SSQdQ5383qDzMvioyWFWiVXYG8zAoENBMaOEwwhA0rf61hWmLZ5AymoYFHLaGsRRm63kRiub5hdqGYtLm+pGo2bqIm5jZt2uD111/Ht99+i6+//hqcc/To0QPdunVL99CIRkRdCWXyXyYIf0gwE3XK+jn9oB1SiZa5lWjZohJ5GZUIaCaipibFsmFqiBo6IqaOqKHBNDSYBgOLamBRhq43kFg+KHBAM4D8+WnKQpKq1biJWpgFnTt3BuccXbt2RSBAUzORPCSWGyeUUq5xQS4ZRJ3x7RMnINRuPwpb70FB9n60abEfrUIVyNAMKZoNU0PE1BExNUSiOqJRHUZEA49qVmaMaNMWRQ0FrtluGekcQzNOK6dy4MABjBs3DllZWejVqxd++OEHAFbBknvvvTfNoyMIoq6gDBmNGxLMBEGkBfJhtpgyZQo+++wzvP/++8jMzJTLhw4dihdeeCGNIyMIgiAE9NyPqDXfPdgfvHUVDmm1F60yK3BIZgUy9QgCzERAMxA2AjJ1XMTUURkNIBwJWBbmiA4zqoNHNOjku3zQMIOWhdkMAzuv6I9DnkzDeecsNTeLJiqYX375Zbzwwgvo168fGHOOsWfPnvjuu+/SODKioVOXAX7kjnHwuXbjo2lxy9jc9Qtkt2iRdPv9FRX1OJrGA1mYiVqx/tG+CHbYh/aFO9E+dzc65e5Em9A+ZAfCyA5UAQCiXEPYtHyWw1Ed4UgAVZEAomEdZkQDjzCwCPkuHyx+uX4AjBaAEQJMHTB1hr0X9Tvo4yCXDItt27ahbdu2Mcv379/vEtAEoUJiuXFB7hiNn2ZlYf6hdIBTsIFZ2QGYAXS4i0ov14QNTx+L/PxdyMusQHH2HuQGKqExjiAzYHIN+4wMhM0ADkSDqIgGUREOojISRFUkACNii+WoBhbWoEVIGBwszCBgZDh/iwImB87rh6wXV6ZtXM2VE044Aa+99hquvfZaAJAi+YknnkD//v3TObQ6IZGwI6FWM0gsNx3SZWUmUqfZCOZNpX3BsrklmDUAJqBFQUKthnz7xAno1G4b2mfvRnYgjBZaBAHNyk8WNXVUmEFUGkEciGZgXziEClsoR6I6jIgT6MfCdmaMiSTUDhYi4E/kX2YmwDjAzINswqW0cgCA6dOn47TTTsNXX32FaDSKhx56CF9++SVWrFiBZcuWpXt4teKLQSsAhNI9jCZDXedYJrFMEMlDLhkEQaQFCvqzGDBgAD788EMcOHAAXbt2xdKlS1FYWIgVK1bguOOOS/fwCIIgCNTCwvyf//wHjz32GL777jv84x//QPv27fHMM8+gS5cuOPnkhnfXarYwwULcihtiHMxkMBlrslar+mL9nH7QW1eiIHcPuuVtQ4YWRZYegQYTEa5L6/LeSCYORIPYF8nA/nAGwhE7hZydRg5RDSyigUUYDr+erMsHE1GohJlWHmZmcNs9KQ1fBvr+AQB69+6NhQsXpnUMjW1Ob07UR/U+si4TRGrUyML84osvYvjw4WjRogU+/fRTVFVZwV179+7FtGnT6nSAdQUHwDUOBDig239r3HoWTVTLhof6YcPTxyKv0y50b/cLehWUo1WwAjl6FTSYMKGhygxgTzQTu8MtsCcSwt5wCPvDIVSFA4hEAohGHLGMsAYWJrGcDjTDckeCcMlIU4ns5mxh3rNnT9Kvg0FjnNObA98PXU5imWh2VFRU4MCBA/L9pk2bMHv2bCxdujSNo6qhhfnuu+/GvHnzcOmll2Lx4sVy+YABA3DXXXfV2eDqEiZSWElV0HR+fOuT9XP6QcuvwiF5O1GQtR+tM/cjL6EeV6YAAFBRSURBVFiBFnoEAWYgyq0iJBVGBvYbGZbPciQDFVHLZ7kqGrAtyxrMiAYYllguufqjdB9as0WLAFrYKVxifS04tAj5MB8sWrVqlXQGDMOo/9rljXFOb+qQUCaaK2effTZGjRqFq666Crt27ULfvn0RDAbx66+/YtasWbj66vQESdZIMH/zzTf47W9/G7O8ZcuW2LVrV23HVD/YgU3CSMVMBpgp5oFtRnz71xMQalmFNtnbkZ91AK0yKpEbrES2XoWgZt10VBhBVJkBVNhCudKwMmIciGSgKmoF+IVtFwwzqoNHGViExHK6afNwGX76fwPk5c+45Y4RfGvVQR6Jna4mpfZNg/fee0/+/f333+PWW2/FZZddJrNirFixAgsXLsT06dMPynga5ZzeRKkPoUyknzldrvZNLUcZMmL55JNP8OCDDwIA/vGPf6CwsBCffvopXnzxRdxxxx2NSzC3a9cOGzZsQOfOnV3Lly9fjsMOO6wuxkUQRFOnGVuYBw4cKP++6667MGvWLFx00UVy2VlnnYXevXvj8ccfx9ixY+t9PDSnEwTRUDhw4AByc3MBAEuXLsWoUaOgaRr69euHTZs2pW1cNfJhHj9+PK6//np89NFHYIzh559/xnPPPYdJkyZhwoQJdT3GOoGJH2f7xUw7+KkJ/QjXBesf7Yutr3RHp07bcEThVvQs+AVdcrajILQPuYFKAECVEcABI4gd4WzsDGdjl+2zvDucib1VmTgQDqIyHEBVOIBoOAAzolvFScgVo8HAInYecvF9SMf3gNfg1QRZsWIFjj/++Jjlxx9/PD7++OODMobGOKc3JYSvcn1al8kdg2gsHH744Xj55ZexefNmvPXWWzj11FMBAFu3bkXLli3TNq4aWZgnT56M3bt3Y/DgwaisrMRvf/tbhEIhTJo0Cddcc01dj7HuUUrydplCRUvWzzsRWk4EoRYRFGTuROe8ncjUI1Iga4zD5Ax7o5mImDpMzmRBkrCpI2zoqIwGURUNyFzLpsFgRjWYIsAvylDyJxLLDQUtCkBzcjAnEqP8N33AGaBFOVC2tu4GQaWxAQAdOnTAvHnz8MADD7iWP/bYY+jQocNBGUM65vTmLuAOputFcz/XjRXVhaM5uW7ccccdGDNmDG644QYMGTJEuqotXboUffr0Sdu4apxW7p577sFtt92Gr776CqZpomfPnsjJyanLsdUpnAFUZdZiw//1g9nCgBYykJEVQUGLXcjOCCMvoxI5wSpkB8LQwFFlWpdH1NQR5Zryv4Yo17A/koGIofsLZUMDTAYeZeg2/uBYyYjk0QyA25UuE2XHiA49Hszg0KJ2o35HAys/q5MxpFruuqmWxn7wwQdx3nnn4a233kK/flaJ8pUrV+K7777Diy++eNDG0djm9MbIwfZPJqHcOGnuZbTPP/98nHzyydiyZQuOPvpouXzIkCE499xz0zauWlX6y8rK8n2U2CDR7FRygGVNY7xZKegND/UDzzHAggaCmQcQyogiJ7MKORlVyNAMtMywylpr4KgyAohyDSbX7P+ZFMlR03qFjYCTX9mwsmBwgzlC2WBgBgOLNp9z3JhgBsCitqXZxhh8HPT31rjemyENgf1RS62aHMw0m6pnRNo4/fTT8e233+LRRx/F119/Dc45zj77bFx11VUHzcIsaFRzeiMgnQF8JJYbB97S2M1dLAuKiopQVFTkWnbiiSemaTQWSQvmUaNGJd3pSy+9lPJApk+fjv/3//4frr/+esyePRsAwDnH1KlT8fjjj2Pnzp3o27cvHn74YfTq1Svl/gmCaGA046A/Lx06dDjo+Y7re04nCKJhsurfbyMzGEy6fWUkUo+jiWX//v2499578e6772Lr1q0wTfdj0P/9738HdTyCpAVzXl6e/JtzjiVLliAvL09aI9asWYNdu3alNAkLVq1ahccffxxHHXWUa/nMmTMxa9YsLFiwAN26dcPdd9+NYcOG4ZtvvpERlCnDrep+nAHQgP/d1x+H3byiZn01cDb8Xz/wIAfXOVhGFJk5VcgMRdAiGJGW5axABAHNyvNqcoYo11FpBGByZr1gWZdNzmCYGiKmlSoubOioqMxANKKDGwzcTtPHTduybDCUTCCf5YYKMwBNs6zMzOBWxjZPCDAPMBhBBp0xaCbAOJfFTuqEZuzD/N///jfptt55sa6ozzk9Gb4furxJWkHTnRauKZ7TpkK81HKEmz/84Q9YtmwZLrnkErRr1y7pnPX1TdKC+amnnpJ/33LLLRg9ejTmzZsHXbeqHxiGgQkTJqQcwbhv3z5cfPHFeOKJJ3D33XfL5ZxzzJ49G7fddpucsBcuXIjCwkIsWrQI48ePT2k/rjQAGmyBwJtU9bAND/UD1wDoHDxoggWi0IIGAhkGQhlRtGxRiaxgGJl6FBrjyNAMaIwjaupSGEdNTQpmwKrGFuUaOGeoFLmVIwFEoxqilUHL6mcycBOWUDZJKDcGtCgAu44P1xhMnYF7JiVTZ+A6Aw9YvujMQA3z6vjDUszO0ZSKch5zzDFgjIFX45jNGKu3wiX1Nac3R9ItkgESykTT4Y033sBrr72Gk046Kd1DcVEjH+Ynn3wSy5cvlxMrAOi6jhtvvBEDBgzAfffdl3Rff/rTn3DGGWdg6NChLsG8ceNGlJeXy3QiABAKhTBw4ECUlZXFFcxVVVWyrCsAWVqWw+2yzO2aCUzn+G52P3cnnKHrDY3H6rz+4b5Wye+AAQRM6BkGgkEDmaEIMgNRZASiCOlRKZQ1W3lEuQZwSP/ksGFlwIiY1ufKpVVZQzhiBfZFw7pVsc9kQESTgrkbieRGBTM4mMbANaviH9esl6sNB8wAYAYYWECzLNEmh3bckTDXfFH7QTRjl4yNGzemewguajunx5t3q8MrNBuT6GsIIhloXOeMqDleX+emzCGHHIL8/Px0DyOGGgnmaDSKdevW4YgjjnAtX7duXYyvSSIWL16MTz75BKtWxVYYKy8vBwAUFha6lhcWFiZMXD19+nRMnTo1doXXkMw4uMbAGXcKjtlWZwBY/9iJgMGghRm6TlyZ9DHVN+vn9AN0blmRdQ4W4MjIqkAwaCArI4xQMIoWgQgyNAMBzZQCWbhYAJAuFmpAn2pJNkwNhslgcM3KfhHRLaEc1sGjmuVuQfmUGzUyDznEzaNlTTYHHgtt2Sd2G+u7YYQ0q73JoVUZdSOWxY6bqUtGp06d0j0EF7Wd0+POuynSUAU0iWOiPklGDDcXsQwAf/nLX3DHHXdg4cKFyMrKSvdwJDUSzJdffjmuuOIKbNiwwZUG6d5778Xll1+eVB+bN2/G9ddfj6VLlyIzMzNuO6/vCuc8oT/LlClTcOONN8r3e/bsOeiR5gRBJEEztjB7+e677zB79mysW7cOjDH06NED119/Pbp27XpQ9l/bOZ3mXYIg6ooHHngA3333HQoLC9G5c2cEPQGKn3zySVrGVSPBfP/996OoqAgPPvggtmzZAsAqrTp58mTcdNNNSfWxZs0abN26Fccdd5xcZhgGPvjgA8ydOxfffPMNAMvS3K5dO9lm69atMVZnlVAohFAoFLOcM9vILH50NVjPnDXbUqtbfzP7xU0rONA0NKyffwK4aXUiizyYDDCU9wwwWxhgol/AtlpbVjomLNnKjz4XFjbhBywrmtk3BMwZlxY0EcgwkB3Yi8yMCDJ0A5kBy+WiZbAKAc1AgJkyUA+AO2+yqSFs6tKabMKyOHPu/C+sylFDQySqW5blqgB4REO3P8Q+BSAaL5oBeZ1qwkVWY+Ca6rdkvbjOYGYwMEODFqnDqD8SzACAt956C2eddRaOOeYYnHTSSeCco6ysDL169cKrr76KYcOG1fsYajunx5t3a0tDseymC7IoE82Rc845J91D8KVGglnTNEyePBmTJ0+WvmqpBoYMGTIEn3/+uWvZ5Zdfju7du+OWW27BYYcdhqKiIrz99tuysks4HMayZcswY8aM1ActRKz40RXuFwEOFjChBUwEggaYxqFrJhiLLZTAbWHJIcQuZNCgrpsIZVipV4QBXGPcEsoANHvHjDmV8wzb/cE0HeEq/Is1zUROKIyWoUrkhw4gN1CJloFKhLQogsyACYZK07rrqjCCiHAdFUYQUR5A2Aig0s6lHDZ0REzddrPQbHFsjc+EI5Q5Z4gaGkxTQ1VFENyu0FdCRUeaJKpLBjPhXOy2HzP/TR+A2cGB3HZf0hnMAKu7uD8SzACAW2+9FTfccAPuvffemOW33HLLQRHMdTGnE3ULieXmB2XQsLjzzjvTPQRfalW4BKj5pJqbm4sjjzzStSw7OxsFBQVy+cSJEzFt2jSUlJSgpKQE06ZNQ1ZWFsaMGZP6DrmV9kyic8vqrHFLLGcYCOgGggEDAd1EUDMR0A2E9CgydEtZCNFrgkEDl/7BAc1Eph5BhloFQsG0o6mi9v9hW8yqxUBE1oqAZqJlsBL5GfvRMbQDefoBtNL3W0NmHAZn2Gu2QKUZxF4zE/uMTOyKtMDeaCYqjSAORINWNgvTLihiW41NzqQwt8bE7EprDIahwbCr9PGohpLLV6d+folGRe6iFdg7pj/AObSoLZpNDlNnwODjrBRy3E45B9ufGajbYj/N2IdZZd26dfjb3/4Ws/yKK66QOekPJiSU0weJ5KZPvNRyJJZjWbNmjXRT69mzZ1rLYgM1FMxdunRJ6EdcV0mlJ0+ejIqKCkyYMEEWLlm6dGmNcjB3vXkVAsyyyG54qB+4DumSIazKwYCBDN2QgXOZehStM/ehhR6Rll2NcWRqEWjg0JkJjZnIZJZQDmkRK8sED8Cw3SJ0cBhg8n+Ta9gdbYEqHkSVEZDrApqBkBZFXuAA8vQKFOj70CawB0EYOMAzAAD7zRD2myEplndHs7AnmoltVbk4EA2iIhJEZTSIiGm5VUQNXYpkYZwTlnHTZOCmBiOiAYaV8YKsyc2L3EX+mWCiQ4+XbkaaFMxwrNB1VB67OaeVU2nTpg3Wrl2LkpIS1/K1a9eibdu2B2UM9TWnH/l+f2ghK2inubtXxINEcvPDL4CvOsHcnLJkbN26FRdeeCHef/99tGrVCpxz7N69G4MHD8bixYvRpk2btIyrRoJ54sSJrveRSASffvop3nzzTdx88801Hsz777/ves8YQ2lpKUpLS2vcJ0EQDRRyyQAAXHnllfjjH/+I//3vfxgwYAAYY1i+fDlmzJiRdExIbamvOZ0giObFo48+ikcffRTff/89AKBXr1644447MGLEiKT7uPbaa7Fnzx58+eWX6NGjBwDgq6++wtixY3Hdddfh+eefr4+hV0uNBPP111/vu/zhhx/G6tUN/3H+4devxPq5feV7TePQNA5d48gIWG4YOcEwWmUcwKGZu5CrVyJLq0KuXolMFkGQRZGpRaDDlJZmAIhwHQY0RHhA+hcDgMZM6BBtAijX8rDPyETEznmqwbJaZ2lVyNMPIFurQpAZiHAde7njfrHfDGGfkYkDRgb2GSHsiWbiQDSEbRXZCEcDsrCIYdi+yqblhgHuBBRy06nKR1Zlwg8rPbdlbWRR2zXD5I6VuQ6syweLn376CbfccgveeOMNVFRUoFu3bpg/f74MNuacY+rUqXj88cflU6yHH34YvXr1kn1UVVVh0qRJeP7551FRUYEhQ4bgkUcewaGHHlonY7z99tuRm5uLBx54AFOmTAEAFBcXo7S0FNddd12d7KM6DsacLiypZGkmqzKROo3FunzooYfi3nvvxeGHHw7AKjh39tln49NPP3XNq4l488038c4770ixDAA9e/bEww8/7KrNcbCpw7pdwIgRI/Diiy/WZZf1Rsk1H4EZjpjk3MpkoWsmsgIR5ASq0CpYgcLgbhQGd6NDxg50CG5H5+CvKMnYhq6BHSgJ7kT3jF3oHtyL7sG9KAnuROfATnQI7EDn4K8oDuxEUWA32up7UaDvRyv9AHL1CimeBTozEWQGgsyAbj93jnAdW6MtUR7Jw6Zwa2yqao3vK1tjc+Uh+LHyEPxc0QrlFS3xy4Ec7KsKYW9lCBVVQYTDdt7kKutl2C+zSodREQA/EAD2B1ByxWoSy4QvXFT40xmYwaFFOTSDQ4ua0peZHd87zaOsnp07d+Kkk05CMBjEG2+8ga+++goPPPAAWrVqJdvMnDkTs2bNwty5c7Fq1SoUFRVh2LBh2Lt3r2wzceJELFmyBIsXL8by5cuxb98+jBw5ss4q8DHGcMMNN+DHH3/E7t27sXv3bvz444+4/vrr014Stj7m9OYuFpv78RM15+uBHdM9hGo588wzcfrpp6Nbt27o1q0b7rnnHuTk5GDlyuTrWZimGZNKDgCCwWBKtT7qmloH/an84x//aJDVWeIStVLDcdO6b8jQDbQIRNAyoxKtQ/vQOrgP+YH9aKXvRzYLo5VWgVwtikzGEGIaMpkODRo02xpXxS1f5ghMVPEoKjlHJddQKS3PGgw78C/IDPm3ZvtCC0u1AQ2VZhA7jBzsMzKxO9oCe6KZ2B8NOYF9RgBVhlV9r6Iq6A7csy3I3LD+ZwYDTKDbn6jYCFE9XBc5GAEtyhF4x9/CqPXpCXxSc2uzyLqYSvtUmDFjBjp06OAqAd25c2f5N+ccs2fPxm233YZRo0YBsKwhhYWFWLRoEcaPH4/du3dj/vz5eOaZZzB06FAAwLPPPosOHTrgnXfewfDhw1McVWJqEp9RnzS6Ob0BQgKZqCl+VuWvB3ZEt6Vfp2E0sRU8q0snaRgG/v73v2P//v3o379/0vs55ZRTcP311+P5559HcXExAOtp4Q033IAhQ4bUbPB1QI0Ec58+fVyWD845ysvLsW3bNjzyyCN1Nrj6puSaj7B+/glgmomMoIGsYBitM/ejXeYetM/YidaBPegQ2I5MLYpMFkU2M1xiOQAdOrMkMwAEmXM6q3gEB3gEmmlAB0cl12GCQWemFTTIOILMsVAJC3OE64hwHfvNEH6N5FpC2QhhfzQDlYYllCsiVsBg2NARjgQQjeowohrMqCaFMotaQrmERDKRKgwyH7PMjuGBr/4c7LgjfdclTQ2zZCQ7ab/yyisYPnw4LrjgAixbtgzt27fHhAkTcOWVVwKwylOXl5e7HvGFQiEMHDgQZWVlGD9+PNasWYNIJOJqU1xcjCOPPBJlZWV1Iph/+eUXTJo0Ce+++y62bt0K7slnWVeW7EQc7Dm98zsnN2nXDBLJRH3QfdkPdWJlPvGCvyA7Kyfp9vsP7AOWLI0pRnTnnXf6xph9/vnn6N+/PyorK5GTk4MlS5agZ8+eSe9v7ty5OPvss9G5c+f/3969x0dR3f0D/8zsNQlJIFxygXBRI4QCasFi0BpAgdJiUfoUFSqg1Pr8ABWCD4q0ElCJoAICFbFSUCn1aRXUtorEBwRRKcjlEbACViDIkxi55UbYy8z5/TG7k91cd5Pdnd3k83695kUyM7t7Mi2Hjyffcw4yMzMhSRKKiorQv39/bNiwIeD3CbVmBeaxY8f6da6yLKNz584YOnQo+vTpE7LGEVEr1sxJf4F22t988w1Wr16NvLw8PP7449izZw8eeugh2Gw2TJo0CSUlJQBQZyOk1NRUnDp1CoC2cZLVakWHDh3q3ON9fUtNmTIFRUVF+N3vfof09HRDyjDYpxNRU06fPu237GRDo8u9e/fGwYMHcfHiRbz11luYPHkyduzYEXBozszMxP79+1FYWIivvvoKQgj07dtX/y2fUZoVmFvLqhXHXv4RTHYXEuId6BhfhbT4CnS1X0R32zmkWry1x9WwSAIWCJgkrehbhYBLqNrufkJA9tQk+442y5BgggRTrd39TBCwSS4oQoZFckPx3K8KCVWq9n8+h2pBhWLH9852qHLbcEmx4rLbrJdhuBWTtiGJ2wSn2wS30wShyBCeUWVJkZA1jSPL1HxC8pRLNFIupu473MIPQbMCc6CdtqqqGDRoEBYtWgRAG0U9cuQIVq9ejUmTJun31Q6oQogmQ2sg9wRq165d+Pjjj3HttdeG5P2aI9J9emsdXebIMoVbnx1Fhn12UlJSQOu0W61WfdLfoEGDsHfvXrzwwgtYs2ZNUJ83YsSIiGzcFKhmBWaTyYTi4uI6a4SeO3cOXbp0icivEFvq69d+iPiES0hpdwld4iuRai9Hmq0c6ZaLSLOUIUWuRHvTZdglVZ8ZqQhAgdBKLKDC5PkVsQzAJEmwCK2eWYXAJaGgSgAuTw3zZWGGS5hRrtpxXmkHVcj6Ws3ejU0USHCoFlQqdlS6rfjekVgnKHvXWNZLMVwyVIdJC8qqBChaqQlRiwnRYElGKDR3HeZAO+309PQ6IxrZ2dn6JLa0tDQA2ihyenq6fk9paak+6pyWlgan04kLFy74jTKXlpZiyJAhgTe+EZmZmXXKMCItUn16aw3KRNQwIQQcDkej96xYsQK/+c1vYLfbsWLFikbvjdTqQbU1KzA31Lk7HA5YrdYWNSjcjr84GFKiCz3SziE1vhJdbBXobK1AirkSnc0VSDRVI1G6jCRZ+x/3sifYqkLSAy6gTczzrnZh8uz6Z4UCWarZrKRCNWvLwQkrqlQbXMKMS6pVW1JOeLashncXQC0MO1QzqhUrLrmtuOiw1wnKLre2g5/baYLqkiFcMiSnzFplCh1RE2blHfvD+jnhXIf5xhtvxNGjR/3OHTt2DD169ACgbdaRlpaGwsJCfQcpp9OJHTt2YPHixQCAgQMHwmKxoLCwEOPHjwcAFBcX4/Dhw1iyZElwDWrA8uXL8dhjj2HNmjV+kxIjKdx9emsOyhxVpnCIlWXkanv88ccxevRoZGZmoqKiAm+88QY++ugjbNmypdHXLVu2DBMnToTdbseyZcsavE+SpNgIzN7UL0kSXnnlFbRrV1M0rigKdu7cGbX1bv9+fhDkzmYkJFWic7tKXJNyBmm2MiSbqpEoV6O96RLskgt2yQWrpKBKWGASAlXCCpcwwSnMUCFDqTVJSVsKToUFCuySq2alCyHjohqPi0q8vtqFNyRXKtqvkH1Hlt2qCdWKBU7VjEtubSWMKqcNTsXk2bVPhqLKcLu0ZeKES4bkknE1Sy8oxLRSDBH+jULCHJhnzZqFIUOGYNGiRRg/fjz27NmDl19+GS+//DIArR+bOXMmFi1ahKysLGRlZWHRokWIj4/HhAkTAADJycmYOnUqZs+ejY4dOyIlJQWPPPII+vfv36J6ug4dOviVdFRVVeHKK69EfHx8neWUzp8/3+zPaUq4+/TDQz9DUkLDs+hjFUMyUf2+++473HPPPSguLkZycjIGDBiALVu2NFlaceLEiXq/jiZBBWZv6hdC4KWXXoLJs/EGoNWs9OzZEy+99FJoW0hErVK4t8a+/vrrsXnzZsydOxcLFy5Er169sHz5ckycOFG/Z86cOaiursa0adP0jUu2bt3qt7zbsmXLYDabMX78eH3jkvXr1/v1f8Favnx5s18bSuzTiSiU1q5da3QTwiaowOxN/cOGDcOmTZvqzByPZvbUKnRJVZDZ7iLS7OXoE1eMeNmBBNkBu+zS77ssLKgQdihC1r5W4qBC0kaYPaPL3nIMWRIwQdt0xC5rOwACwGXVAhUyLirxKHPH44I7HtWKBQ7VrI8qy1LNbCq3aoJT1WqVLytmVLstuOyy4LLL7Bld1paNU5wmvQSDI8sULtZ/7IFjzI+CDqhBa+aycsEYM2YMxowZ0+B1SZKQn5/f6KQ3u92OlStXYuXKlUF/fkMmT54csvdqiVju043AkWUKl5W9/h8ePLHa6GZEhby8vHrPS5IEu92Oq666CmPHjo34GvHNqmHevn17qNsRdn26fI8rO1Wig/kSOlkqPNtcOwFAX53CJcxQhASHsMApzHCoFlxStZIMAPpGI14mSdsa2yK7YYLwW0e5zB2HSsWGCpcdbiHDqWrrJsuSgFlWYfZsVqIKGU7V5Le+ssOzxbXDadY2I3FLUJ0mBmWKGNvf98D5k+vD+yFhLsmIFfv374fFYkH//truie+88w7WrVuHvn37Ij8/PyLzQmKxT48kBmWKBG9ojtX65VA5cOAA9u/fD0VR0Lt3bwghcPz4cZhMJvTp0wcvvvgiZs+ejV27dgW1vnNLBRyY8/Ly8OSTTyIhIaHB9O+1dOnSFjcs1K5JOo1OdgUppkpYPRuGVKhxUISsh9zLwuKpMzbr5xyq9ohUIfnVHPtShQRZElCFBLcwwaGYUem24bKijUo7FROEz+hYgsUJs6x63lOCUzWh2m2Bw6WFZafLDFWV4Ky2cESZDGPdstfoJrQJDzzwAB577DH0798f33zzDe68806MGzcOf/3rX3Hp0qWwlW/Eep8eKQzLFEltPSwD0EeP161bp6+IVF5ejqlTp+Kmm27C/fffjwkTJmDWrFn44IMPItaugAPzgQMH4HJppQv79+83ZHH9luhiKUdHswpFSLgsLLioxMOhWmrCsmqBKiS4hEkPxy4hwy1MUDzfq0KC6pmgV/O1rB1C1tZGVk1QVM8EPVWGokrwPipZErCZ3bCYFDg97+FSTXC6zbjsNsPpMnl27dOWi0OVmUGZWq1w1zDHimPHjulrMP/1r39Fbm4uNm7ciE8++QR33XVX2AJzrPfp4cagTGSMZ599FoWFhX7LhyYlJSE/Px8jR47Eww8/jCeeeMJvB9ZICDgw+/7K7qOPPgpHW4ioLWFJBgBtwp2qanMaPvzwQ73mOjMzE2fPng3b57JPJ6JoVFZWhtLS0jrlFt9//z3Ky8sBAO3bt4fT6Yxou+Smb6nrvvvuQ0VFRZ3zVVVVuO+++1rcqHCQIXBRicdZdxK+dabgtKMjzjja44yjPUocSTjvTMB5VwIuuuJw0RWPcrcdFW47Klx2XHTG47wjHmcdCSitbofS6gR8V90O/1eZhOLKJJRUJaKkIhHflSfibHk7nCtPwPnyeFwsi0dFRRwqKuJQdcmGaocFl5wWXHJZccllRZXThiqnFVUOK6odFjgcFjirLVAum4BLZu7WR62bz3rPgRytNTAPGjQITz31FF5//XXs2LEDP/vZzwBoE/Jqb9sdLrHYp4dLzw9v4ugykYHGjh2L++67D5s3b8a3336LM2fOYPPmzZg6dSpuv/12AMCePXtw9dVXR7RdzZr09+qrr+KZZ57xW3oJAKqrq/Haa6/hj3/8Y0gaF0olrmSojgRUKjZUK1ZUKxaong1JAPiVXHhri1Uh4ZLbApdqgsuzHrJLNUFVJbgVGaqqvUaoElRVguqWIRQJULVzEAAkQJIFFFmGYpGh+LxOVSWtdMNpguqWAUUCnDKy/nOPsQ+LKBI4wgwA+lJ3b7/9NubNm6dvKfvmm2+GbDfBpsRinx5qDMlE0WHNmjWYNWsW7rrrLrjd2upjZrMZkydP1pfC7NOnD1555ZWItiuowFxeXg4hBIQQqKiogN1u168pioL33nuvztaq0eJUdUcoSIBTMcMttPri+gIyAC3ECq0Oudplgctt8gRdLeQKVYZQAaFK2mQ+IQEqAJcMqNrXkicsQwIgCwiTgKrIcLpMcFZbPGFBC9dwS4AicUSZ2hYGZgDAgAEDcOjQoTrnn3322Rat9RyIWO7TQ4VBmdqa/y38DnHWyoDvr3ZWhbE1dbVr1w5/+MMfsGzZMnzzzTcQQuDKK6/021jJO+8jkoIKzO3bt4ckSZAkqd6hcEmSsGDBgpA1LpSKq5MAxGkT8TxhWBWSvnqF9jW0iXyeUWC3IsPpNEMoElRF9qwbC20E2fOPvaRKekhuaHvq478frN3npUjIenB32H9momjGSX81Ll68iDfffBP//ve/8V//9V9ISUnBl19+idTUVHTt2jVsnxvLfbpXQ4G3oe24GZCJYkNJSQmKi4tx8803Iy4uDkIIQycnBxWYt2/fDiEEhg8fjrfeestv0Wir1YoePXogIyMj5I0kImqtvvjiC9xyyy1o3749Tp48ifvvvx8pKSnYvHkzTp06hddeey1sn80+nYiizblz5zB+/Hhs374dkiTh+PHjuOKKK/DrX/8a7du3x/PPP29Iu4IKzLm5uQC0ySiZmZmQ5WbNGTTE+UsJAOzayLKndhgAhID/KLMqQVHkmlFlT12yPulI1JRcZM0IrISioZFnojaNJRkAtPWQ7733XixZssSvhnj06NGYMGFCWD87Fvv0QEeIOZJMFJtmzZoFi8WCoqIiZGdn6+fvvPNOzJo1KzYCs1ePHj0AAJcuXUJRUVGdpT0GDBjQ8paFWFm1DbKwazXInmAMQP9HWHgn6nn+lDyT96AAVwcYjIkocCzJ0Ozduxdr1qypc75r164oKSmJSBuitU9n6CVqe7Zu3YoPPvgA3bp18zuflZWFU6dOGdSqZgbm77//Hvfeey/ef//9eq8ritKiRoWDs8oKWbHqo8TCZ8RY8tQlQ9X+vJr1xUSR0UpDcDDsdru+tqivo0ePonPnzhFpQzT06QzHRARoy1nGx8fXOX/27FnYbDYDWqRpVmCeOXMmLly4gN27d2PYsGHYvHkzvvvuOzz11FOGDZU36ZIZUEwBl1EQEUXC2LFjsXDhQvzlL38BoE20KyoqwmOPPYZf/OIXEWlDuPt0hmEiCtTNN9+M1157DU8++SQArU9UVRXPPvsshg0bZli7mhWYt23bhnfeeQfXX389ZFlGjx49MGLECCQlJaGgoEBfeD+aXJn3OcySxehmEJEXa5gBAM899xx++tOfokuXLqiurkZubi5KSkqQk5ODp59+OiJtCFef3u+jHMi2uiNFREQNee6555Cbm4vPP/8cTqcTc+bMwZEjR3D+/Hl88sknhrWrWYG5qqpKX5szJSUF33//Pa6++mr0798f+/fvD2kDiah1Yg2zJikpCbt27cK2bduwf/9+qKqKH/7wh7j11lsj1gb26UQUDVwuF6ZNm4Z3330X77//PkwmE6qqqjBu3DhMnz4d6enphrWtWYG5d+/eOHr0KHr27Ilrr70Wa9asQc+ePfHSSy8Z+sMQUQzhCDPcbjfsdjsOHjyI4cOHY/jw4Ya0g306EUUDi8WCw4cPo2PHjlG3Bnyza5iLi4sBAPPnz8eoUaOwYcMGWK1WvPrqqyFtIBG1Thxh1rZ77dGjh+ETpdmnE1G0mDRpEtauXYtnnnnG6Kb4aVZgnjhxov71ddddh5MnT+Krr75C9+7d0alTp5A1johaMY4wAwB++9vfYu7cudiwYYPfxiGRxD6diKKF0+nEK6+8gsLCQgwaNAgJCQl+15cuXWpIuwIOzHl5eQG/qVE/DBHFEAZmAMCKFSvw9ddfIyMjAz169Kjzj0O4aojZpxNRNDp8+DB++MMfAgCOHTvmdy0mtsY+cOBAQPcZ+cMQUexgSYbm9ttvN+Rz2acTUTTavn270U2oV8CBOVp/ACKKURxhBqDVDBuBfTpR2/SbAceRFBcX8P3l1dX4rzC2J1Y0q4aZiKjFGJj9OJ1OlJaWQlVVv/Pdu3c3qEVEROTFwExEhmBJhubYsWOYOnUqPv30U7/zQghIkmT4ChpERMTATERG4QgzAODee++F2WzG3//+d6Snp7NmmIgoCjEwExEZ6ODBg9i3bx/69OljdFOIiKgBDMxEZAiWZGj69u2Ls2fPGt0MIiJqhGx0A4iojRLNOFqJ8vJy/Vi8eDHmzJmDjz76COfOnfO7Vl5ebnRTiYgIBgfm1atXY8CAAUhKSkJSUhJycnLw/vvv69eFEMjPz0dGRgbi4uIwdOhQHDlyxMAWE1HItOHA3L59e3To0AEdOnTAiBEjsHv3btxyyy3o0qWLft57DxERGc/Qkoxu3brhmWeewVVXXQUAePXVVzF27FgcOHAAP/jBD7BkyRIsXboU69evx9VXX42nnnoKI0aMwNGjR5GYmGhk04mohSTPEcz9rYXvGsgnT55EZmYmTCaT3z2qqqKoqCjSTSMionoYGphvu+02v++ffvpprF69Grt370bfvn2xfPlyzJs3D+PGjQOgBerU1FRs3LgRDzzwgBFNJqJQacOrZOTm5upfDx8+HMXFxejSpYvfPefOncOtt96KyZMnR7p5RERUS9TUMCuKgjfeeANVVVXIycnBiRMnUFJSgpEjR+r32Gw25Obm1lmvlIhij3fSXzBHa+Rdb7m2yspK2O12A1pERES1Gb5KxqFDh5CTk4PLly+jXbt22Lx5M/r27auH4tTUVL/7U1NTcerUqQbfz+FwwOFw6N9z0gxRlGrDI8wAkJeXBwCQJAm/+93vEB8fr19TFAX//Oc/ce211xrUuuCw3yWi1s7wwNy7d28cPHgQFy9exFtvvYXJkydjx44d+vXaIy8NjcZ4FRQUYMGCBWFrLxGFUCsLwcE4cOAAAK1PO3ToEKxWq37NarXimmuuwSOPPGJU84LCfpeIWjvDA7PVatUn/Q0aNAh79+7FCy+8gEcffRQAUFJSgvT0dP3+0tLSOqPOvubOnauP3ADaSEdmZmaYWk9EzdXW12H2Tvy799578cILLyApKcngFjUf+10iau0MD8y1CSHgcDjQq1cvpKWlobCwENdddx0AwOl0YseOHVi8eHGDr7fZbLDZbJFqLhE1VxsvyfBat26d0U1oMfa7RLHj6O9fQrtaq/I0plJRAr63oKAAmzZtwldffYW4uDgMGTIEixcvRu/evZvT1Khi6KS/xx9/HB9//DFOnjyJQ4cOYd68efjoo48wceJESJKEmTNnYtGiRdi8eTMOHz6MKVOmID4+HhMmTDCy2UQUApGe9FdQUKD3K16BrPXucDjw4IMPolOnTkhISMDPf/5zfPvtty1rDBFRK7Rjxw5Mnz4du3fvRmFhIdxuN0aOHImqqiqjm9Ziho4wf/fdd7jnnntQXFyM5ORkDBgwAFu2bMGIESMAAHPmzEF1dTWmTZuGCxcuYPDgwdi6dSvXYCaioOzduxcvv/wyBgwY4Hc+kLXeZ86cib/97W9444030LFjR8yePRtjxozBvn376qydTETUlm3ZssXv+3Xr1qFLly7Yt28fbr75ZoNaFRqGBua1a9c2el2SJOTn5yM/Pz8yDSKiyIlQSUZlZSUmTpyIP/zhD3jqqadq3k6IJtd6Lysrw9q1a/H666/j1ltvBQBs2LABmZmZ+PDDDzFq1KjmNYqIKMbUXv0mkFKssrIyAEBKSkrY2hUpUbMOMxG1Lc0tySgvL/c7fJczq8/06dPxs5/9TA+8XoGs9b5v3z64XC6/ezIyMtCvXz+uB09EbUpmZiaSk5P1o6CgoNH7hRDIy8vDTTfdhH79+kWoleETdZP+iKiNaOYIc+3VF+bPn9/gb6HeeOMN7N+/H3v37q1zraSkBEDja72XlJTAarWiQ4cOde7xvp6IqC04ffq032o+TY0uz5gxA1988QV27doV7qZFBAMzERmjmYE50E779OnTePjhh7F169ZGd8wLdq33QO8hImpNkpKSAl7+8sEHH8S7776LnTt3olu3bmFuWWSwJIOIDNHckgxvp+09GgrM+/btQ2lpKQYOHAiz2Qyz2YwdO3ZgxYoVMJvN+shy7ZFi37Xe09LS4HQ6ceHChQbvISIijRACM2bMwKZNm7Bt2zb06tXL6CaFDAMzERlDNOMIwi233IJDhw7h4MGD+jFo0CBMnDgRBw8exBVXXKGv9e7lXet9yJAhAICBAwfCYrH43VNcXIzDhw/r9xARkWb69OnYsGEDNm7ciMTERJSUlKCkpATV1dVGN63FWJJBRIaQhIAkAk/BwdwLAImJiXUmmiQkJKBjx476ee9a71lZWcjKysKiRYv81npPTk7G1KlTMXv2bHTs2BEpKSl45JFH0L9//zqTCImI2rrVq1cDAIYOHep3ft26dZgyZUrkGxRCDMxEZIwo2OkvkLXely1bBrPZjPHjx6O6uhq33HIL1q9fzzWYiYhqEUEObMQSBmYiMkSwu/e1dKc/APjoo4/83zOAtd7tdjtWrlyJlStXtrwBREQUkxiYicgYUTDCTEREFAhO+iMiIiIiagRHmInIEEaUZBARtXWfbLoHcYkNr01fW3XFZWDAE2FsUWxgYCYiY7Akg4iIYgQDMxEZgiPMREQUKxiYicgYHGEmIqIYwcBMRIbhqDEREcUCBmYiMoYQ2hHM/URERAZgYCYiQ7CGmYiIYgUDMxEZgzXMREQUIxiYicgQkqodwdxPRERkBAZmIjIGR5iJiChGMDATkSFYw0xERLFCNroBRERERETRjCPMRGQMLitHREQxgoGZiAzBkgwiIooVDMxEZAxO+iMiiriXP/kzTHGmgO9XqpUwtiZ2MDATkSE4wkxERLGCgZmIjMEaZiIiihEMzERkCI4wExFRrGBgJiJjsIaZiIhiBAMzERmCI8xERBQrGJiJyBiq0I5g7iciIjIAAzMRGYMlGUREFCMYmInIEBKCLMkIW0uIiIgaJxvdACIiIiKiaMYRZiIyBtdhJiKiGMHATESG4CoZREQUKxiYicgYnPRHREQxgoGZiAwhCQEpiDKLYO4lIiIKJQZmIjKG6jmCuZ+IiFpkd/pPkJRgC/j+8ioHkvGvMLYoNhi6SkZBQQGuv/56JCYmokuXLrj99ttx9OhRv3uEEMjPz0dGRgbi4uIwdOhQHDlyxKAWE1GoeEeYgzmIiIiMYGhg3rFjB6ZPn47du3ejsLAQbrcbI0eORFVVlX7PkiVLsHTpUqxatQp79+5FWloaRowYgYqKCgNbTkQtJppxEBERGcDQkowtW7b4fb9u3Tp06dIF+/btw8033wwhBJYvX4558+Zh3LhxAIBXX30Vqamp2LhxIx544AEjmk1EocBl5YiIKEZE1cYlZWVlAICUlBQAwIkTJ1BSUoKRI0fq99hsNuTm5uLTTz+t9z0cDgfKy8v9DiKKPt5l5YI5KDqx3yWi1i5qArMQAnl5ebjpppvQr18/AEBJSQkAIDU11e/e1NRU/VptBQUFSE5O1o/MzMzwNpyImsc7whzMEYRQzZFwOBx48MEH0alTJyQkJODnP/85vv322xb/+K0J+10i8tq5cyduu+02ZGRkQJIkvP3220Y3KSSiJjDPmDEDX3zxBf785z/XuSZJkt/3Qog657zmzp2LsrIy/Th9+nRY2ktE0S1UcyRmzpyJzZs344033sCuXbtQWVmJMWPGQFEUI36sqMR+l4i8qqqqcM0112DVqlVGNyWkomJZuQcffBDvvvsudu7ciW7duunn09LSAGgjzenp6fr50tLSOqPOXjabDTZb4MulUHBM2VdDcitwH/+30U2hGCep2hHM/cEIxRyJsrIyrF27Fq+//jpuvfVWAMCGDRuQmZmJDz/8EKNGjQquUa0U+93wWjvyIQDA1K0rDG4JUdNGjx6N0aNHG92MkDN0hFkIgRkzZmDTpk3Ytm0bevXq5Xe9V69eSEtLQ2FhoX7O6XRix44dGDJkSKSbSwCUfx1jWKbQCHNJRm3NmSOxb98+uFwuv3syMjLQr1+/BudREIXa1K0rGJbJcLXnKTgcDqObFFGGBubp06djw4YN2LhxIxITE1FSUoKSkhJUV1cD0EoxZs6ciUWLFmHz5s04fPgwpkyZgvj4eEyYMMHIphNRSzVzWbnmdNrNnSNRUlICq9WKDh06NHgPEVFbkJmZ6TdXoaCgwOgmRZShJRmrV68GAAwdOtTv/Lp16zBlyhQAwJw5c1BdXY1p06bhwoULGDx4MLZu3YrExMQIt5aIQqm5W2PXnlA2f/585OfnN/pa7xyJXbt21X3fIOZIBHMPEVFrcvr0aSQlJenft7UyLEMDswjgH0tJkpCfn9/kP4hEFGOauQ5zsJ12S+ZIpKWlwel04sKFC36jzKWlpSwLI6I2JSkpya/vbWuiZpUMorbGOfp6o5tgLAFADeLwZGtvp+09GgrMoZgjMXDgQFgsFr97iouLcfjwYQZmohg0f+p1mD/1OqObQTEoKlbJIGorHGN+BEiAapIgqW17J47mlmQEavr06di4cSPeeecdfY4EACQnJyMuLs5vjkRWVhaysrKwaNEivzkSycnJmDp1KmbPno2OHTsiJSUFjzzyCPr376+vmkFE0Y0BObIqKyvx9ddf69+fOHECBw8eREpKCrp3725gy1qGgZmIjCEQZElGcG8fqjkSy5Ytg9lsxvjx41FdXY1bbrkF69evh8lkCq5BRETRYPcrgC2IORiO4Drfzz//HMOGDdO/z8vLAwBMnjwZ69evD+q9ogkDM1EYeEeSAUDIElST9icAQAIkRUASbXzSWDNrmAO/PTRzJOx2O1auXImVK1cG9flEFFmBjiQvWHsgzC1p24YOHRpQ/xtrGJiJQqj69sGApIVjIQHCrJVfQAIgAEkAskvrSCSl9XUoQVGh/0dFwPcTEdXCkguKBAZmohC4NG6wFpJNACRAsUgQMqCatUQoKwKSooVlSQVkt4Dt73uMbbTBwl3DTEStW3OCMkeXqbkYmImaqfqOwVBNWkgWJk9ANkH70xOYJQFICgAByAoguQHZpcL+btsOy0REzdXcEWWGZWoJBmYiMkaYa5iJiIhChYGZKEiXfnEDVLM2kixMngl9Jk+tsuw5L0OrWXZrtcqyG5CdAglv7ja6+dGDgZmIgsCRZTISAzNRECrvuqFm1QuTVqMsTDUhWUjwrIKhlWDIbgGTCzA5AgvL1XcMhnfxDElAnyhof+efYf25DMHATEQBCndYru/9GbTJFwMzUYAq7r4BqsUblmuCsuqZ6Kev+CCgjSi7BUxOwFwtEP9W/WH50rjB2ii12bPsnM9qGhDeCYKR+fkijqtkEFETwrUCRiDvO3/qdQzNpGNgJmpE5V031EzskwHFKnlKMXxKL4CaoKtCXwXD5ACS/vRZve9b9UutrEOxet9bW4bOO6osKwKSKkFSASG3zpFVrpJBRPUJRUiuL+hy+TlqCQZmIjIGSzKIiChGMDAT1aN8Yo5PyUXNqLJq8YwqS4DvRn2S7+iyEzBfBhI31h1d1ss6PBuaqNaaumffEWphkiApgKQKyLKEyrtugORG65o0qHprT4K4n4hatXCMLrfkPb2vZWkGMTATeZTdk+NTblFrMp/nUL1/YzwBF9ACrjfsyk7A5BR+YbnyrhugWCSoFm19ZsUCQAZUz2cB/hP8JFWbNCjJgKRK+oobsqy9V7s3Wklo5ggzESG0pRK+wTaU78t6ZmJgJgJwfuqQmrDsDcomTyb2XQHD86dvSIZncxLZpYVl7yS9igk5UKxanbJi9WyTbdZe7w3KvhMFvZuc6GHZ8zmyBKieCXKSKqFiQg4kVbSC4BxkYAYDM1FrEuqaYm+gDedEQYbmtouBmdqsi1Ny9HIL1eopufCZ0IdaIdl3BQsBT7BVteXjTJ6RZVnRJvpduDcHqlWC266Vcahm6Ntm+5Zy+AVm1ROSJc/KGJ5QLYTP67yBXZZQPjEHkqi/9CMmcISZqM0JV5hdsPZARCb1tYYSjb/duh/xCYkB33+pqgJ4JiuMLYoNDMxEZAzVU4cS1P1ERESRx8BMbcqFe3O0NZR9l4YzAYqlVimGZ2KfPrLrMykPqqd8QtSMLssubc1kIWmf4UzylGF4R5d9JgrWmeemr7uMmhFnyf+6nit9Xitk7duySTn6eyRtiNHRZiJqtSI58hspvp8Xy6PNFDgGZmr1/OqTfeuUpZpzqsU/KNdeCUMS0DfOqFlrWZvkJzsFOqz7DBcn15RhuBNqVtSo/V4CNaFZUjyN9NRC+4ZnfQKgqDmSX/cPxGWTcvT66mAWnIgKQtWOYO4nopgR7hAbqTIM72d51f5M1ja3DQzM1Gqd//UQbZRXrhWQfWuUPWFTmH1qhH1rlgEtyKqeiXhu7ZAdgOky0OmlT/XPU2wSFDvgtgOKrVZQrl277A3FPqe8QVw/PNtrS26g/fr6R46TX/sMF6fk6O9/cUpOg/dGHdYwE7U6RgTYSH9OfUGdobn1Y2CmVuXcb4Zok/c8wVgvh6g9wuzZoU/4lED4jy4Ln533PDd5l427rK2z7BuWzz0wBO44LSx7JxD6hm79a0kAQqoZZRY+wVjRRq310WtPOE9ZW/M59Wm//jNcuC/H/+eJBaxhJmoVIl0OEe7VMHw/o7Hr3DmwbWFgJiJjcISZiIhiBAMzxbxzDwzRR5RrdueDtjmIGdqocT2bkHj51v76ji77XveWSTQ0uuyKA5Q4bXTZu9ay9obwr7vwvKGkSvr7essuZLfPOsyeo6nRZa8Of4yRMgxfAkEG5rC1hIiawYgR1mgYXQ72PmodGJgp5pz9f0P8JtOpvhP5fCb0AfCvU9YDtdBXwPDunaGHZs8L9e9VSQ+vJkdgYRm1JuAJoKYcw/sZwqcEw+1TguH5LN/PaLU4wkwUU4wuQQh3QGUApsYwMFNM+H7aEL0W2VuXrB++E/lqT6zz3fBD9oRl3xFm70YkntUovDXG3muyd3MSl1a/XDvIuu2A4qlbVk0+F3wWdJC8k/68Qdlnh0CodUeV20RYBjzbFwax8oXKVTKIIsnogOyLYZmMxsBMUen76TWjyN7Aq0/ks6De7ap9d+LzrpnsG5bhG5Z9J+D5roPsE5b1NZeVmhFgX6UPaatweJeP83uddzBUqvla8uY9n1UwvLsFeo82E5YBjjATRaFoCsletcNsNLaRWj8GZiIyBgMzERHFCAZmihqlM4ZoI8n1bTLic061wLP8m3+AklRJG1WGZ2DXZ2k3fTRav7lW+BL+X+ujvsJ/NNi3raoZEBbUjGx7X+sttfBWd8jwaZTnPb3LyPmMMHda3YZGlwEuK0cUJWJpxDYcbWU5BgWCgZmigre8wRuQ1dpB2QQIk9BKH0y11kj2BE5IAkLW6oT1iXYeeu2y5H/ef9tpnxpjUXPNr8TCe6vZfzUMfSdAn4CtN6H2Z/qWZHi+7vz7NhaWichwsRSUw4VhmQLFwEyGKn2oZkk4xV4zoU+1AMIstB34ZAFh8l/ZAqqkj+ICqNlwRC8YRk0Y9g2s+nJvkl8g9t2O2jcc+w5Ed1lVE2rr2zLbb/TY7VOz7Jl4WPszJBXosrLtBmUhVIggtrsO5l4ialgsBeVwBdq2HJTn/v0AZFt8wPerjkthbE3sYGAmw5TMHFIzUmv2BGaL8HzvCclmUTNhD9CCpttT4yAkCFlA8q5A4bmuE6hTeSHVzlzesOxZF7nOSLLP1talDw1BlxU+Aden9EL/PJ9Jgm09EDdJiODKLFjDTNRisRSWgeZvOd2WAzGFBwMzERlDBFnDzMBMREQGYWCmiPtups/OfJ4RZtUMKHYB1SK00WWLgGQSgGcEGUBNKYa2YLI2uqxK2ghwrTCl1zcrqDPq7Hfdc06qNVJcH7/d/zw79KmA/2Q+T01y6gscWW6SqtYz5N8IlmQQtUisjS4Hi6PKFE4MzBRR3jIMYfIEZYunHMMqoMSpWlA2q5BkAcm7Ix+gVWCokmcdZQkSBKBKEJKoCbjeXfpUn5phz2uBWrv3iVrn6xnslGoFad8QnPrCp/hu5hCtUsTbRhVIW86gHDCOMBNFTKyG5doheMHaA3V+FgZligQGZoqYkllD9I1H9LplKyAsnpFlm6qFZZMWliXfzUU8g4tCBSALCHhCs2/tstBCNOATglWf0WSfUWD4hOn6Rpa9k/lkn81FaktlOG4RoaoQQYwwc9IfUfPEalhuCAMyGYGBmSKiJE8rw1CtnjIMizaqLCyAalEhrAKyTYEkC8gmFZIESJKAEBKEEPAuZiyEpE3yk4Rnz2nvZEDJP/x61mSWVKnOShi1Q7Lvusn6Oe8ScZ6wnLaU4TjkOMJMFHaxHJYZjCmaMDATkTHUepYxaQwDMxERGYSBmcKuJE/bFU+x1ZRhqFZtYp+wCMCqQjKpkE3e0eWa2mXJs5CykHyLhTVCqtldz1ftTUckFXVGkBu8r9aIc/pzHFkOG+G7iHWg9xNRoGJ1dJkjyxSNZCM/fOfOnbjtttuQkZEBSZLw9ttv+10XQiA/Px8ZGRmIi4vD0KFDceTIEWMaS82mWAElDlBtgDteQIlXodq1A3YFkkWBbFEhyY2EJyHVOVXfusn1bXENn3IM3+2ufcsz9LDsWUc549lPGZbDTKgi6KM5XnzxRfTq1Qt2ux0DBw7Exx9/HOKfhIhChWG5dWiN/a6hgbmqqgrXXHMNVq1aVe/1JUuWYOnSpVi1ahX27t2LtLQ0jBgxAhUVFRFuKbWEYtdGl91xAqpNm9wnbCokz8iy3yQ/aJuQqIp2aDXM8KRara7ZT+0cLQEQkt/21r5h2TsRsKFVMQCOKkeMUIM/gvTf//3fmDlzJubNm4cDBw7gxz/+MUaPHo2ioqIw/EBE0SMWR5cZlluH1trvGhqYR48ejaeeegrjxo2rc00IgeXLl2PevHkYN24c+vXrh1dffRWXLl3Cxo0bDWgtNceZx4ZAtXrWWLZqYRlWFZJFhWxWIJu1MgwAUBUZiluG4pKhKjKEKvv9Fl7ybnHtCc++u/D5Lj9XH7+cLfkfwvdPalWWLl2KqVOn4te//jWys7OxfPlyZGZmYvXq1UY3jShsYjEsU+vRWvtdQwNzY06cOIGSkhKMHDlSP2ez2ZCbm4tPP214BNDhcKC8vNzvIGOcmTsEqk2rV1Y9tcqwakvHyfrycT4rYqjaWstClSAUyfO9DEkCZM/qGbJZBUzapibeQ8hCD9ENEbJ21A7LdTA0R0y4SzKcTif27dvn14cAwMiRIxvtQyh47HejB8MyGak197tRO+mvpKQEAJCamup3PjU1FadOnWrwdQUFBViwYEGd8264glrBilpOcVyGqgKqRUBVBaCogOIpw5C9ZRhaKYYQgOqWIXyGeSVJQJIBmGp+Fa+qElSXSVtv2bPmslABSZEARYLkliAJSVsOTgGEU6pZQ7mhRRkEIBTotc5u4QrbM2lt3NCelWjGhDy3cARVZuH9rNphzGazwWaz1bn/7NmzUBSl3j7E279QaDTU76qOSwa0pm2rrozdkkX+/yUw3ufUnH7X9/XB3h9I39ua+92oDcxekuQ/5CeEqHPO19y5c5GXl6d/f+bMGfTt2xe78F7Y2kgNeP4do1vQLEeNbkAMqqioQHJyckD3Wq1WpKWlYVdJ8H8n27Vrh8zMTL9z8+fPR35+foOvCbYPoeA11O+eWT3FuEa1UdOXG90CipRz584F3O8CNX1vc/5eBtv3tsZ+N2oDc1paGgBtpDk9PV0/X1paWue/XHzV/i+edu3a4fTp00hMTIz5/7FCqby8HJmZmTh9+jSSkpKMbk7U4fNpmvcZffnll8jIyAj4dXa7HSdOnIDT6Qz6M+vrdOsbXQaATp06wWQy1RnVaKoPoeCx3w0M+5Wm8Rk1raysDN27d0dKSkpQr4tE39ua+92oDcy9evVCWloaCgsLcd11Wk2W0+nEjh07sHjx4oDfR5ZldOvWLVzNjHlJSUnslBrB59O0rl27QpaDmw5ht9tht9vD1CKN1WrFwIEDUVhYiDvuuEM/X1hYiLFjx4b1s9s69ruNY7/SND6jpgXb7wLh73tbc79raGCurKzE119/rX9/4sQJHDx4ECkpKejevTtmzpyJRYsWISsrC1lZWVi0aBHi4+MxYcIEA1tNRLEiLy8P99xzDwYNGoScnBy8/PLLKCoqwn/+538a3TQiolaptfa7hgbmzz//HMOGDdO/99bATZ48GevXr8ecOXNQXV2NadOm4cKFCxg8eDC2bt2KxMREo5pMRDHkzjvvxLlz57Bw4UIUFxejX79+eO+999CjRw+jm0ZE1Cq11n5XEs2dZkkxzeFwoKCgAHPnzm2wBrQt4/NpGp8RUXD4d6ZpfEZN4zMyBgMzEREREVEjonbjEiIiIiKiaMDATERERETUCAZmIiIiIqJGMDATERERETWCgbmVe/rppzFkyBDEx8ejffv2Dd63fv16DBgwAHa7HWlpaZgxY4bf9UOHDiE3NxdxcXHo2rUrFi5c2Ox97KNNoM8I0LYi7datGyRJwsWLF/2uteVn9L//+7+4++67kZmZibi4OGRnZ+OFF16oc19rfkZEXux3m8Z+t2nsd6NL1O70R6HhdDrxy1/+Ejk5OVi7dm299yxduhTPP/88nn32WQwePBiXL1/GN998o18vLy/HiBEjMGzYMOzduxfHjh3DlClTkJCQgNmzZ0fqRwmbQJ6R19SpUzFgwACcOXPG73xbf0b79u1D586dsWHDBmRmZuLTTz/Fb37zG5hMJj0EtPZnROTFfrdp7Hebxn43yghqE9atWyeSk5PrnD9//ryIi4sTH374YYOvffHFF0VycrK4fPmyfq6goEBkZGQIVVXD0VxDNPSMvF588UWRm5sr/ud//kcAEBcuXPC7xmfkb9q0aWLYsGH6923lGRF5sd9tGvvdprHfjQ4syWjjCgsLoaoqzpw5g+zsbHTr1g3jx4/H6dOn9Xs+++wz5Obm+i2QPmrUKPzf//0fTp48aUCrI+/LL7/EwoUL8dprr0GW6/614TOqq6ysDCkpKfr3fEZEGva7gWG/Gzz2u+HDwNzGffPNN1BVFYsWLcLy5cvx5ptv4vz58xgxYgScTicAoKSkBKmpqX6v835fUlIS8TZHmsPhwN13341nn30W3bt3r/eetv6Mavvss8/wl7/8BQ888IB+js+ISMN+t2nsd4PHfje8GJhjUH5+PiRJavT4/PPPA3ovVVXhcrmwYsUKjBo1CjfccAP+/Oc/4/jx49i+fbt+nyRJfq8TngkDtc9Hi1A+o7lz5yI7Oxu/+tWvGr2vLT8jX0eOHMHYsWPxxBNPYMSIEX7XYu0ZEXmx320a+92msd+NXZz0F4NmzJiBu+66q9F7evbsGdB7paenAwD69u2rn+vcuTM6deqEoqIiAEBaWlqd/xItLS0FgDr/5RotQvmMtm3bhkOHDuHNN98EUNPZdOrUCfPmzcOCBQva/DPy+vLLLzF8+HDcf//9+O1vf+t3LRafEZEX+92msd9tGvvd2MXAHIM6deqETp06heS9brzxRgDA0aNH0a1bNwDA+fPncfbsWfTo0QMAkJOTg8cffxxOpxNWqxUAsHXrVmRkZAT9FztSQvmM3nrrLVRXV+vf7927F/fddx8+/vhjXHnllQD4jABthGP48OGYPHkynn766TrXY/EZEXmx320a+92msd+NYcbNN6RIOHXqlDhw4IBYsGCBaNeunThw4IA4cOCAqKio0O8ZO3as+MEPfiA++eQTcejQITFmzBjRt29f4XQ6hRBCXLx4UaSmpoq7775bHDp0SGzatEkkJSWJ5557zqgfK6QCeUa+tm/fXme2dlt/RocPHxadO3cWEydOFMXFxfpRWlqqv0drf0ZEXux3m8Z+t2nsd6MLA3MrN3nyZAGgzrF9+3b9nrKyMnHfffeJ9u3bi5SUFHHHHXeIoqIiv/f54osvxI9//GNhs9lEWlqayM/PbzVL0gTyjHzV13EL0baf0fz58+u93qNHD7/3ac3PiMiL/W7T2O82jf1udJGE4HYvREREREQN4SoZRERERESNYGAmIiIiImoEAzMRERERUSMYmImIiIiIGsHATERERETUCAZmIiIiIqJGMDATERERETWCgZnqGDp0KGbOnNlqPnPKlCm4/fbbw/LeREShwr6XKHqZjW4AEQBs2rQJFotF/75nz56YOXNmxP/xICJqS9j3EgWGgZmiQkpKitFNICJqc9j3EgWGJRnUqAsXLmDSpEno0KED4uPjMXr0aBw/fly/vn79erRv3x4ffPABsrOz0a5dO/zkJz9BcXGxfo/b7cZDDz2E9u3bo2PHjnj00UcxefJkv1/V+f5acOjQoTh16hRmzZoFSZIgSRIAID8/H9dee61f+5YvX46ePXvq3yuKgry8PP2z5syZg9q7vwshsGTJElxxxRWIi4vDNddcgzfffDM0D4yIKATY9xJFFwZmatSUKVPw+eef491338Vnn30GIQR++tOfwuVy6fdcunQJzz33HF5//XXs3LkTRUVFeOSRR/Trixcvxp/+9CesW7cOn3zyCcrLy/H22283+JmbNm1Ct27dsHDhQhQXF/v9A9CU559/Hn/84x+xdu1a7Nq1C+fPn8fmzZv97vntb3+LdevWYfXq1Thy5AhmzZqFX/3qV9ixY0fgD4aIKIzY9xJFF5ZkUIOOHz+Od999F5988gmGDBkCAPjTn/6EzMxMvP322/jlL38JAHC5XHjppZdw5ZVXAgBmzJiBhQsX6u+zcuVKzJ07F3fccQcAYNWqVXjvvfca/NyUlBSYTCYkJiYiLS0tqDYvX74cc+fOxS9+8QsAwEsvvYQPPvhAv15VVYWlS5di27ZtyMnJAQBcccUV2LVrF9asWYPc3NygPo+IKNTY9xJFHwZmatC//vUvmM1mDB48WD/XsWNH9O7dG//617/0c/Hx8XqHDQDp6ekoLS0FAJSVleG7777Dj370I/26yWTCwIEDoapqSNtbVlaG4uJivTMGALPZjEGDBum/Gvzyyy9x+fJljBgxwu+1TqcT1113XUjbQ0TUHOx7iaIPAzM1qHb9me95b20bAL8Z1gAgSVKd1/re39h7N0aW5Tqv8/31ZCC8/1D84x//QNeuXf2u2Wy2oNtERBRq7HuJog9rmKlBffv2hdvtxj//+U/93Llz53Ds2DFkZ2cH9B7JyclITU3Fnj179HOKouDAgQONvs5qtUJRFL9znTt3RklJiV/HffDgQb/PSk9Px+7du/Vzbrcb+/bt8/uZbDYbioqKcNVVV/kdmZmZAf1MREThxL6XKPpwhJkalJWVhbFjx+L+++/HmjVrkJiYiMceewxdu3bF2LFjA36fBx98EAUFBbjqqqvQp08frFy5EhcuXKgz8uGrZ8+e2LlzJ+666y7YbDZ06tQJQ4cOxffff48lS5bgP/7jP7Blyxa8//77SEpK0l/38MMP45lnnkFWVhays7OxdOlSXLx4Ub+emJiIRx55BLNmzYKqqrjppptQXl6OTz/9FO3atcPkyZOb9ayIiEKFfS9R9OEIMzVq3bp1GDhwIMaMGYOcnBwIIfDee+/V+VVgYx599FHcfffdmDRpEnJyctCuXTuMGjUKdru9wdcsXLgQJ0+exJVXXonOnTsDALKzs/Hiiy/i97//Pa655hrs2bPHb0Y4AMyePRuTJk3ClClTkJOTg8TERH3Ci9eTTz6JJ554AgUFBcjOzsaoUaPwt7/9Db169QriyRARhQ/7XqLoIonmFDQRtYCqqsjOzsb48ePx5JNPGt0cIqI2gX0vUfOxJIPC7tSpU9i6dStyc3PhcDiwatUqnDhxAhMmTDC6aURErRb7XqLQYUkGhZ0sy1i/fj2uv/563HjjjTh06BA+/PDDgCevEBFR8Nj3EoUOSzKIiIiIiBrBEWYiIiIiokYwMBMRERERNYKBmYiIiIioEQzMRERERESNYGAmIiIiImoEAzMRERERUSMYmImIiIiIGsHATERERETUCAZmIiIiIqJG/H+pOgV9tx/oWgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x800 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot a random timestep from the filtered ARs\n",
    "\n",
    "random_date = random.choice(list(output_ars.keys()))\n",
    "fig, axes = plt.subplots(2, 2, sharey=True, sharex=True, figsize=(8,8))\n",
    "plt.subplots_adjust(wspace=0.3)\n",
    "plt.suptitle(random_date)\n",
    "\n",
    "ivt_ds[\"ivt_mag\"].sel(time=random_date).plot(ax=axes[0,0])\n",
    "ivt_ds[\"ivt_quantile\"].sel(time=random_date).plot(ax=axes[0,1])\n",
    "ivt_ds[\"thresholded\"].sel(time=random_date).plot(ax=axes[1,0])\n",
    "labeled_regions.sel(time=random_date).plot(ax=axes[1,1], cmap=\"tab20\")\n",
    "\n",
    "axes[0,0].set_title(\"IVT magnitude\")\n",
    "axes[0,1].set_title(\"IVT quantile (30yr)\")\n",
    "\n",
    "axes[1,0].set_title(\"IVT \" + str(ar_params['ivt_percentile']) + \"th percentile regions\")\n",
    "axes[1,1].set_title(\"Labeled AR candidate regions\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "876be0aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  4%|▍         | 832/21812 [00:19<07:33, 46.31it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 21812/21812 [08:56<00:00, 40.67it/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8min 11s, sys: 28.1 s, total: 8min 39s\n",
      "Wall time: 9min 10s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#create a master geodataframe of filtered ARs\n",
    "gdf = create_geodataframe_with_all_ars(output_ars, ar_di, labeled_regions, ivt_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2d3ad4b1-094f-4ee1-a244-d68264ad42ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "ivt_ds.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3a273618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>blob_label</th>\n",
       "      <th>geometry</th>\n",
       "      <th>length/width ratio</th>\n",
       "      <th>major axis length (km)</th>\n",
       "      <th>overall orientation</th>\n",
       "      <th>mean poleward strength</th>\n",
       "      <th>directional_coherence</th>\n",
       "      <th>mean_of_ivt_dir</th>\n",
       "      <th>total ivt strength</th>\n",
       "      <th>relative ivt strength</th>\n",
       "      <th>Coherence in IVT Direction</th>\n",
       "      <th>Mean Meridional IVT</th>\n",
       "      <th>Consistency Between Mean IVT Direction and Overall Orientation</th>\n",
       "      <th>Length</th>\n",
       "      <th>Length/Width Ratio</th>\n",
       "      <th>Criteria Passed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22736</th>\n",
       "      <td>2020-12-01T00:00:00.000000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>POLYGON ((-149.62500 61.12500, -149.62500 60.8...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4113</td>\n",
       "      <td>19</td>\n",
       "      <td>240</td>\n",
       "      <td>81</td>\n",
       "      <td>359</td>\n",
       "      <td>3151694</td>\n",
       "      <td>743</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                time  blob_label  \\\n",
       "22736  2020-12-01T00:00:00.000000000         1.0   \n",
       "\n",
       "                                                geometry  length/width ratio  \\\n",
       "22736  POLYGON ((-149.62500 61.12500, -149.62500 60.8...                 3.0   \n",
       "\n",
       "       major axis length (km)  overall orientation  mean poleward strength  \\\n",
       "22736                    4113                   19                     240   \n",
       "\n",
       "       directional_coherence  mean_of_ivt_dir  total ivt strength  \\\n",
       "22736                     81              359             3151694   \n",
       "\n",
       "       relative ivt strength  Coherence in IVT Direction  Mean Meridional IVT  \\\n",
       "22736                    743                        True                 True   \n",
       "\n",
       "       Consistency Between Mean IVT Direction and Overall Orientation  Length  \\\n",
       "22736                                               True                 True   \n",
       "\n",
       "       Length/Width Ratio  Criteria Passed  \n",
       "22736                True                5  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking out the Haines 2020 AR event....the region property values seems reasonable when compared to the image! \n",
    "display(gdf.loc[gdf['time']=='2020-12-01T00:00:00.000000000'])\n",
    "gdf.loc[gdf['time']=='2020-12-01T00:00:00.000000000', 'geometry'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "74ce3fe4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#if not already run from terminal via ar_detection.py....\n",
    "#export the gdf to shapefile, then filter/export the raw AR shapefile to landfalling ARs, event ARs, and coastal impact point shapefiles.\n",
    "\n",
    "#create_shapefile(gdf, shp_fp, csv_fp)\n",
    "#landfall_ars_export(\n",
    "    # shp_fp,\n",
    "    # csv_fp,\n",
    "    # ak_shp,\n",
    "    # landfall_shp,\n",
    "    # landfall_csv,\n",
    "    # landfall_events_shp,\n",
    "    # landfall_events_csv,\n",
    "    # coastal_impact_shp,\n",
    "    # coastal_impact_csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d5092889",
   "metadata": {},
   "outputs": [],
   "source": [
    "#read outputs and AK shp as geodataframes\n",
    "e_polys = gpd.read_file(landfall_events_shp)\n",
    "e_pts = gpd.read_file(coastal_impact_shp)\n",
    "ak = gpd.read_file(ak_shp).to_crs(e_polys.crs)\n",
    "\n",
    "#join coastal impact points to using event id\n",
    "e = gpd.GeoDataFrame(e_polys.merge(e_pts, how='left', on='event_id'), geometry='geometry_x', crs=e_polys.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "12f3ea7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      event_id                start                  end  sumtot_str  \\\n",
      "2223      2223  2020-11-29 00:00:00  2020-12-01 12:00:00    14751224   \n",
      "\n",
      "      sumrel_str  ratio_m  len_km_m  orient_m  poleward_m  dircoher_m  \\\n",
      "2223        4129      3.0    3015.0      17.0       238.0        78.0   \n",
      "\n",
      "      mean_dir_m  dur_hrs  tintensity  rintensity  \\\n",
      "2223         3.0     66.0    223503.0        63.0   \n",
      "\n",
      "                                             geometry_x  \\\n",
      "2223  POLYGON ((-129.87500 65.62500, -129.87500 65.3...   \n",
      "\n",
      "                       geometry_y  \n",
      "2223  POINT (-143.95137 60.03367)  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-180.0, -120.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#view properties and plot aggregated Haines 2020 AR Event and coastal impact point with AK shp for context\n",
    "print(e.loc[[2223]])\n",
    "\n",
    "ax = ak.plot(color='purple', zorder=1)\n",
    "e.loc[[2223], 'geometry_x'].boundary.plot(ax=ax, zorder=2)\n",
    "e.loc[[2223], 'geometry_y'].plot(ax=ax, color='black', zorder=3)\n",
    "ax.set_xlim([-180, -120])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}