ICAAD_example.ipynb

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   "source": [
    "# Extract CMIP6 climate data for island nations"
   ]
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    "import xarray as xr\n",
    "import cartopy.crs as ccrs\n",
    "import xesmf as xe\n",
    "import intake\n",
    "from xmip.postprocessing import pick_first_member, concat_experiments\n",
    "from xmip.preprocessing import combined_preprocessing"
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    "## Lazy loading CMIP6 models in the cloud\n",
    "\n",
    "For more information see our [cmip6-feedstock](https://github.com/leap-stc/cmip6-leap-feedstock#how-to-access-the-newly-uploaded-data) and the [Pangeo CMIP6 Cloud Data Docs](https://pangeo-data.github.io/pangeo-cmip6-cloud/accessing_data.html#loading-an-esm-collection)"
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    "url = \"https://storage.googleapis.com/cmip6/cmip6-pgf-ingestion-test/catalog/catalog.json\" \n",
    "col = intake.open_esm_datastore(url)\n",
    "\n",
    "# search only for a subset of the full collection\n",
    "cat = col.search(\n",
    "    variable_id='tas',  #surface air temperature (find more variables and the specific names here: \n",
    "                        #https://docs.google.com/spreadsheets/d/1UUtoz6Ofyjlpx5LdqhKcwHFz2SGoTQV2_yekHyMfL9Y/edit?pli=1&gid=1221485271#gid=1221485271\n",
    "    experiment_id=['ssp245','ssp585'],  # extract a middle of the road, and business as usual scenario: \n",
    "                                        # more info here: https://en.wikipedia.org/wiki/Shared_Socioeconomic_Pathways\n",
    "    grid_label='gn', # chose the native model grid (vs regridded products)\n",
    "    table_id = 'Amon', # monthly output frequency\n",
    "    source_id = ['ACCESS-ESM1-5'] # For simplicity choose only two models (omit this line if you want to explore all of the climate models available)\n",
    ")"
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      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.sub_experiment_id.variant_label.version.zstore'\n"
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    "# Load all xarray datasets into a dictionary, and apply xmip (https://github.com/jbusecke/xMIP) preprocessing to align naming and other common cleaning tasks\n",
    "ddict = cat.to_dataset_dict(\n",
    "    preprocess=combined_preprocessing,\n",
    "    aggregate=False,\n",
    "    xarray_open_kwargs={'use_cftime':True}\n",
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   "id": "e679b625-795b-426a-8822-325666450fc7",
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   "source": [
    "from xmip.postprocessing import concat_members\n",
    "import dask"
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    "# Some members run beyond 2100, prune the time to facilitate alignment\n",
    "ddict_pruned = {k:ds.sel(time=slice(None, '2100')).squeeze() for k,ds in ddict.items()}\n",
    "with dask.config.set(**{'array.slicing.split_large_chunks': True}):\n",
    "    ddict_members_combined = concat_members(ddict_pruned)"
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       "    Conventions:                         CF-1.7 CMIP-6.2\n",
       "    activity_id:                         ScenarioMIP\n",
       "    branch_method:                       standard\n",
       "    branch_time_in_child:                60265.0\n",
       "    branch_time_in_parent:               60265.0\n",
       "    cmor_version:                        3.4.0\n",
       "    ...                                  ...\n",
       "    intake_esm_attrs:table_id:           Amon\n",
       "    intake_esm_attrs:variable_id:        tas\n",
       "    intake_esm_attrs:grid_label:         gn\n",
       "    intake_esm_attrs:sub_experiment_id:  none\n",
       "    intake_esm_attrs:version:            v20210712\n",
       "    intake_esm_attrs:_data_format_:      zarr</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-3ca9056c-e2e5-48a4-86ca-a8364dd13611' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3ca9056c-e2e5-48a4-86ca-a8364dd13611' 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'>member_id</span>: 10</li><li><span class='xr-has-index'>time</span>: 1032</li><li><span class='xr-has-index'>y</span>: 145</li><li><span class='xr-has-index'>x</span>: 192</li><li><span>bnds</span>: 2</li><li><span>vertex</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-de295b65-169c-4725-be96-e24e80f4efde' class='xr-section-summary-in' type='checkbox'  checked><label for='section-de295b65-169c-4725-be96-e24e80f4efde' class='xr-section-summary' >Coordinates: <span>(14)</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'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r34i1p1f1&#x27; ... &#x27;r31i1p1f1&#x27;</div><input id='attrs-722889ad-41cb-48d9-b3d1-48b2daecb78f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-722889ad-41cb-48d9-b3d1-48b2daecb78f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a34ac68e-d33d-47c4-be4e-d6c93276eccf' class='xr-var-data-in' type='checkbox'><label for='data-a34ac68e-d33d-47c4-be4e-d6c93276eccf' 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;r34i1p1f1&#x27;, &#x27;r32i1p1f1&#x27;, &#x27;r37i1p1f1&#x27;, &#x27;r33i1p1f1&#x27;, &#x27;r35i1p1f1&#x27;,\n",
       "       &#x27;r40i1p1f1&#x27;, &#x27;r39i1p1f1&#x27;, &#x27;r38i1p1f1&#x27;, &#x27;r36i1p1f1&#x27;, &#x27;r31i1p1f1&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-af2d66f7-d17c-438c-b30d-18e5c6c3e204' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af2d66f7-d17c-438c-b30d-18e5c6c3e204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75782bea-b0b5-408f-838a-b67e09bc2360' class='xr-var-data-in' type='checkbox'><label for='data-75782bea-b0b5-408f-838a-b67e09bc2360' 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>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-6d7dbbc3-f291-4f30-a5df-00bcb2191fc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d7dbbc3-f291-4f30-a5df-00bcb2191fc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0abf85e5-387d-4884-9863-73ab88cd81be' class='xr-var-data-in' type='checkbox'><label for='data-0abf85e5-387d-4884-9863-73ab88cd81be' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
       "        90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-fb85af47-7702-4e5a-81eb-3e4f863fa89b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb85af47-7702-4e5a-81eb-3e4f863fa89b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d04a1982-dd40-4504-80c6-166fe36a3ad7' class='xr-var-data-in' type='checkbox'><label for='data-d04a1982-dd40-4504-80c6-166fe36a3ad7' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([  0.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li><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'>object</div><div class='xr-var-preview xr-preview'>2015-01-16 12:00:00 ... 2100-12-...</div><input id='attrs-a3075798-109d-4abf-b339-d0b2ceeb1112' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3075798-109d-4abf-b339-d0b2ceeb1112' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4ce9651-714c-4cf6-ba8d-a50869d502b1' class='xr-var-data-in' type='checkbox'><label for='data-e4ce9651-714c-4cf6-ba8d-a50869d502b1' 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>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2015, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeProlepticGregorian(2015, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeProlepticGregorian(2015, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeProlepticGregorian(2100, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeProlepticGregorian(2100, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeProlepticGregorian(2100, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2015-01-01 00:00:00 ... 2101-01-...</div><input id='attrs-de5e7781-4942-457d-8886-9692d6af1a3a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de5e7781-4942-457d-8886-9692d6af1a3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4085c54-6ff2-4f00-95a3-b4d2376b25bf' class='xr-var-data-in' type='checkbox'><label for='data-c4085c54-6ff2-4f00-95a3-b4d2376b25bf' 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([[cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2015, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeProlepticGregorian(2015, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2015, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeProlepticGregorian(2015, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2015, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeProlepticGregorian(2100, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2100, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeProlepticGregorian(2100, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2100, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeProlepticGregorian(2100, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeProlepticGregorian(2101, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bounds</span></div><div class='xr-var-dims'>(y, bnds, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -90.0 -90.0 ... 90.0 90.0</div><input id='attrs-1a28e8a5-2bda-4719-9de6-fba1cd587af3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a28e8a5-2bda-4719-9de6-fba1cd587af3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7f4d13e-b6bf-4a84-b0b3-af26fc81bcb6' class='xr-var-data-in' type='checkbox'><label for='data-f7f4d13e-b6bf-4a84-b0b3-af26fc81bcb6' 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([[[-90.   , -90.   , -90.   , ..., -90.   , -90.   , -90.   ],\n",
       "        [-89.375, -89.375, -89.375, ..., -89.375, -89.375, -89.375]],\n",
       "\n",
       "       [[-89.375, -89.375, -89.375, ..., -89.375, -89.375, -89.375],\n",
       "        [-88.125, -88.125, -88.125, ..., -88.125, -88.125, -88.125]],\n",
       "\n",
       "       [[-88.125, -88.125, -88.125, ..., -88.125, -88.125, -88.125],\n",
       "        [-86.875, -86.875, -86.875, ..., -86.875, -86.875, -86.875]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 86.875,  86.875,  86.875, ...,  86.875,  86.875,  86.875],\n",
       "        [ 88.125,  88.125,  88.125, ...,  88.125,  88.125,  88.125]],\n",
       "\n",
       "       [[ 88.125,  88.125,  88.125, ...,  88.125,  88.125,  88.125],\n",
       "        [ 89.375,  89.375,  89.375, ...,  89.375,  89.375,  89.375]],\n",
       "\n",
       "       [[ 89.375,  89.375,  89.375, ...,  89.375,  89.375,  89.375],\n",
       "        [ 90.   ,  90.   ,  90.   , ...,  90.   ,  90.   ,  90.   ]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bounds</span></div><div class='xr-var-dims'>(x, bnds, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>359.1 359.1 359.1 ... 359.1 359.1</div><input id='attrs-f2485dbd-4006-42da-81de-154531cc070b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f2485dbd-4006-42da-81de-154531cc070b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fa9b953-f371-4428-b1c5-8d098319226a' class='xr-var-data-in' type='checkbox'><label for='data-0fa9b953-f371-4428-b1c5-8d098319226a' 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([[[359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625],\n",
       "        [  0.9375,   0.9375,   0.9375, ...,   0.9375,   0.9375,\n",
       "           0.9375]],\n",
       "\n",
       "       [[  0.9375,   0.9375,   0.9375, ...,   0.9375,   0.9375,\n",
       "           0.9375],\n",
       "        [  2.8125,   2.8125,   2.8125, ...,   2.8125,   2.8125,\n",
       "           2.8125]],\n",
       "\n",
       "       [[  2.8125,   2.8125,   2.8125, ...,   2.8125,   2.8125,\n",
       "           2.8125],\n",
       "        [  4.6875,   4.6875,   4.6875, ...,   4.6875,   4.6875,\n",
       "           4.6875]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[353.4375, 353.4375, 353.4375, ..., 353.4375, 353.4375,\n",
       "         353.4375],\n",
       "        [355.3125, 355.3125, 355.3125, ..., 355.3125, 355.3125,\n",
       "         355.3125]],\n",
       "\n",
       "       [[355.3125, 355.3125, 355.3125, ..., 355.3125, 355.3125,\n",
       "         355.3125],\n",
       "        [357.1875, 357.1875, 357.1875, ..., 357.1875, 357.1875,\n",
       "         357.1875]],\n",
       "\n",
       "       [[357.1875, 357.1875, 357.1875, ..., 357.1875, 357.1875,\n",
       "         357.1875],\n",
       "        [359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>360.0 360.0 360.0 ... 358.1 358.1</div><input id='attrs-8eab07d3-8611-4812-9ef5-9be4f4005541' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8eab07d3-8611-4812-9ef5-9be4f4005541' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc8f652-8b65-4480-a878-7d0b3dd28286' class='xr-var-data-in' type='checkbox'><label for='data-adc8f652-8b65-4480-a878-7d0b3dd28286' 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([[360.   , 360.   , 360.   , ..., 360.   , 360.   , 360.   ],\n",
       "       [  1.875,   1.875,   1.875, ...,   1.875,   1.875,   1.875],\n",
       "       [  3.75 ,   3.75 ,   3.75 , ...,   3.75 ,   3.75 ,   3.75 ],\n",
       "       ...,\n",
       "       [354.375, 354.375, 354.375, ..., 354.375, 354.375, 354.375],\n",
       "       [356.25 , 356.25 , 356.25 , ..., 356.25 , 356.25 , 356.25 ],\n",
       "       [358.125, 358.125, 358.125, ..., 358.125, 358.125, 358.125]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-2c6b845f-fe45-48c4-9388-43abaadc0961' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c6b845f-fe45-48c4-9388-43abaadc0961' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdcccdec-7ce8-49b3-8f9f-0956d04ad798' class='xr-var-data-in' type='checkbox'><label for='data-bdcccdec-7ce8-49b3-8f9f-0956d04ad798' 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([[-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ],\n",
       "       [-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ],\n",
       "       [-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ],\n",
       "       ...,\n",
       "       [-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ],\n",
       "       [-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ],\n",
       "       [-90.  , -88.75, -87.5 , ...,  87.5 ,  88.75,  90.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_verticies</span></div><div class='xr-var-dims'>(vertex, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>359.1 359.1 359.1 ... 359.1 359.1</div><input id='attrs-5c64ad5f-3e8b-452e-8565-7d5d077a23f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c64ad5f-3e8b-452e-8565-7d5d077a23f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15d5170d-cc83-4200-b1bf-bf2e54a4a68d' class='xr-var-data-in' type='checkbox'><label for='data-15d5170d-cc83-4200-b1bf-bf2e54a4a68d' 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([[[359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625],\n",
       "        [  0.9375,   0.9375,   0.9375, ...,   0.9375,   0.9375,\n",
       "           0.9375],\n",
       "        [  2.8125,   2.8125,   2.8125, ...,   2.8125,   2.8125,\n",
       "           2.8125],\n",
       "        ...,\n",
       "        [353.4375, 353.4375, 353.4375, ..., 353.4375, 353.4375,\n",
       "         353.4375],\n",
       "        [355.3125, 355.3125, 355.3125, ..., 355.3125, 355.3125,\n",
       "         355.3125],\n",
       "        [357.1875, 357.1875, 357.1875, ..., 357.1875, 357.1875,\n",
       "         357.1875]],\n",
       "\n",
       "       [[359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625],\n",
       "        [  0.9375,   0.9375,   0.9375, ...,   0.9375,   0.9375,\n",
       "           0.9375],\n",
       "        [  2.8125,   2.8125,   2.8125, ...,   2.8125,   2.8125,\n",
       "           2.8125],\n",
       "...\n",
       "        [355.3125, 355.3125, 355.3125, ..., 355.3125, 355.3125,\n",
       "         355.3125],\n",
       "        [357.1875, 357.1875, 357.1875, ..., 357.1875, 357.1875,\n",
       "         357.1875],\n",
       "        [359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625]],\n",
       "\n",
       "       [[  0.9375,   0.9375,   0.9375, ...,   0.9375,   0.9375,\n",
       "           0.9375],\n",
       "        [  2.8125,   2.8125,   2.8125, ...,   2.8125,   2.8125,\n",
       "           2.8125],\n",
       "        [  4.6875,   4.6875,   4.6875, ...,   4.6875,   4.6875,\n",
       "           4.6875],\n",
       "        ...,\n",
       "        [355.3125, 355.3125, 355.3125, ..., 355.3125, 355.3125,\n",
       "         355.3125],\n",
       "        [357.1875, 357.1875, 357.1875, ..., 357.1875, 357.1875,\n",
       "         357.1875],\n",
       "        [359.0625, 359.0625, 359.0625, ..., 359.0625, 359.0625,\n",
       "         359.0625]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_verticies</span></div><div class='xr-var-dims'>(vertex, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.38 -88.12 ... 88.12 89.38</div><input id='attrs-c2e18b45-3c11-4b4b-991d-ee2267614a64' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2e18b45-3c11-4b4b-991d-ee2267614a64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5b0bd0d-c511-498e-8bfc-126265dcf71b' class='xr-var-data-in' type='checkbox'><label for='data-b5b0bd0d-c511-498e-8bfc-126265dcf71b' 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([[[-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        ...,\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375]],\n",
       "\n",
       "       [[-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        ...,\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ]],\n",
       "\n",
       "       [[-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        ...,\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ],\n",
       "        [-89.375, -88.125, -86.875, ...,  88.125,  89.375,  90.   ]],\n",
       "\n",
       "       [[-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        ...,\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375],\n",
       "        [-90.   , -89.375, -88.125, ...,  86.875,  88.125,  89.375]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>variant_label</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;r34i1p1f1&#x27; ... &#x27;r31i1p1f1&#x27;</div><input id='attrs-bcb3164b-09a9-43fa-9d39-efcaeef7aa09' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bcb3164b-09a9-43fa-9d39-efcaeef7aa09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72938d2e-c137-422e-ac89-daabc774942a' class='xr-var-data-in' type='checkbox'><label for='data-72938d2e-c137-422e-ac89-daabc774942a' 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;r34i1p1f1&#x27;, &#x27;r32i1p1f1&#x27;, &#x27;r37i1p1f1&#x27;, &#x27;r33i1p1f1&#x27;, &#x27;r35i1p1f1&#x27;,\n",
       "       &#x27;r40i1p1f1&#x27;, &#x27;r39i1p1f1&#x27;, &#x27;r38i1p1f1&#x27;, &#x27;r36i1p1f1&#x27;, &#x27;r31i1p1f1&#x27;],\n",
       "      dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sub_experiment_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;none&#x27;</div><input id='attrs-4572a127-be6b-4c0c-bf19-95d24d062ccf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4572a127-be6b-4c0c-bf19-95d24d062ccf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-692bf258-1bdd-4ca7-a074-ce73eb15d58b' class='xr-var-data-in' type='checkbox'><label for='data-692bf258-1bdd-4ca7-a074-ce73eb15d58b' 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;none&#x27;, dtype=&#x27;&lt;U4&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8a0bb68f-f8a2-4256-8213-156157b9e6dc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8a0bb68f-f8a2-4256-8213-156157b9e6dc' class='xr-section-summary' >Data variables: <span>(1)</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>tas</span></div><div class='xr-var-dims'>(member_id, time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 516, 145, 192), meta=np.ndarray&gt;</div><input id='attrs-a3c74ad6-c7fe-4927-96f1-b9b75965b04e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3c74ad6-c7fe-4927-96f1-b9b75965b04e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7119617-5a55-42dd-a610-b1bb890b728a' class='xr-var-data-in' type='checkbox'><label for='data-e7119617-5a55-42dd-a610-b1bb890b728a' 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>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.07 GiB </td>\n",
       "                        <td> 54.80 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (10, 1032, 145, 192) </td>\n",
       "                        <td> (1, 516, 145, 192) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 20 chunks in 51 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-25b82778-34ee-4f52-8675-7fc3bff5e0af' class='xr-section-summary-in' type='checkbox'  ><label for='section-25b82778-34ee-4f52-8675-7fc3bff5e0af' class='xr-section-summary' >Indexes: <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-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5b262c69-4ab3-4946-b5ce-31c9d48cec13' class='xr-index-data-in' type='checkbox'/><label for='index-5b262c69-4ab3-4946-b5ce-31c9d48cec13' 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([&#x27;r34i1p1f1&#x27;, &#x27;r32i1p1f1&#x27;, &#x27;r37i1p1f1&#x27;, &#x27;r33i1p1f1&#x27;, &#x27;r35i1p1f1&#x27;,\n",
       "       &#x27;r40i1p1f1&#x27;, &#x27;r39i1p1f1&#x27;, &#x27;r38i1p1f1&#x27;, &#x27;r36i1p1f1&#x27;, &#x27;r31i1p1f1&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9b4ff30a-cbdd-4dff-8dc7-c2f59c2894d8' class='xr-index-data-in' type='checkbox'/><label for='index-9b4ff30a-cbdd-4dff-8dc7-c2f59c2894d8' 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([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
       "       -78.75,\n",
       "       ...\n",
       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
       "         90.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c04d2f7a-37f2-4365-98a7-988c4b72f537' class='xr-index-data-in' type='checkbox'/><label for='index-c04d2f7a-37f2-4365-98a7-988c4b72f537' 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([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
       "          15.0,  16.875,\n",
       "       ...\n",
       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
       "        356.25, 358.125],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=192))</pre></div></li><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-fe1b7f11-dac3-4fb0-b416-1655941e2863' class='xr-index-data-in' type='checkbox'/><label for='index-fe1b7f11-dac3-4fb0-b416-1655941e2863' 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(CFTimeIndex([2015-01-16 12:00:00, 2015-02-15 00:00:00, 2015-03-16 12:00:00,\n",
       "             2015-04-16 00:00:00, 2015-05-16 12:00:00, 2015-06-16 00:00:00,\n",
       "             2015-07-16 12:00:00, 2015-08-16 12:00:00, 2015-09-16 00:00:00,\n",
       "             2015-10-16 12:00:00,\n",
       "             ...\n",
       "             2100-03-16 12:00:00, 2100-04-16 00:00:00, 2100-05-16 12:00:00,\n",
       "             2100-06-16 00:00:00, 2100-07-16 12:00:00, 2100-08-16 12:00:00,\n",
       "             2100-09-16 00:00:00, 2100-10-16 12:00:00, 2100-11-16 00:00:00,\n",
       "             2100-12-16 12:00:00],\n",
       "            dtype=&#x27;object&#x27;,\n",
       "            length=1032,\n",
       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
       "            freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da6adcc6-ef46-49a2-beac-f276ef9090c5' class='xr-section-summary-in' type='checkbox'  ><label for='section-da6adcc6-ef46-49a2-beac-f276ef9090c5' class='xr-section-summary' >Attributes: <span>(52)</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-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>ScenarioMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>60265.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>60265.0</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>update of RCP4.5 based on SSP2</dd><dt><span>experiment_id :</span></dt><dd>ssp245</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>historical</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-1-1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
       "aerosol: CLASSIC (v1.0)\n",
       "atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m)\n",
       "atmosChem: none\n",
       "land: CABLE2.4\n",
       "landIce: none\n",
       "ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m)\n",
       "ocnBgchem: WOMBAT (same grid as ocean)\n",
       "seaIce: CICE4.1 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>status :</span></dt><dd>2021-11-15;created; by gcs.cmip6.ldeo@gmail.com</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(30 April 2019) MD5:12ec21eb48eb992c2e353382c1c903b1</dd><dt><span>title :</span></dt><dd>ACCESS-ESM1-5 output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>version :</span></dt><dd>v20210712</dd><dt><span>version_id :</span></dt><dd>v20210712</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>ScenarioMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>CSIRO</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>ssp245</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:sub_experiment_id :</span></dt><dd>none</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>v20210712</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 1GB\n",
       "Dimensions:            (member_id: 10, time: 1032, y: 145, x: 192, bnds: 2,\n",
       "                        vertex: 4)\n",
       "Coordinates: (12/14)\n",
       "  * member_id          (member_id) object 80B 'r34i1p1f1' ... 'r31i1p1f1'\n",
       "    height             float64 8B 2.0\n",
       "  * y                  (y) float64 1kB -90.0 -88.75 -87.5 ... 87.5 88.75 90.0\n",
       "  * x                  (x) float64 2kB 0.0 1.875 3.75 ... 354.4 356.2 358.1\n",
       "  * time               (time) object 8kB 2015-01-16 12:00:00 ... 2100-12-16 1...\n",
       "    time_bounds        (time, bnds) object 17kB 2015-01-01 00:00:00 ... 2101-...\n",
       "    ...                 ...\n",
       "    lon                (x, y) float64 223kB 360.0 360.0 360.0 ... 358.1 358.1\n",
       "    lat                (x, y) float64 223kB -90.0 -88.75 -87.5 ... 88.75 90.0\n",
       "    lon_verticies      (vertex, x, y) float64 891kB 359.1 359.1 ... 359.1 359.1\n",
       "    lat_verticies      (vertex, x, y) float64 891kB -90.0 -89.38 ... 88.12 89.38\n",
       "    variant_label      (member_id) <U9 360B 'r34i1p1f1' ... 'r31i1p1f1'\n",
       "    sub_experiment_id  <U4 16B 'none'\n",
       "Dimensions without coordinates: bnds, vertex\n",
       "Data variables:\n",
       "    tas                (member_id, time, y, x) float32 1GB dask.array<chunksize=(1, 516, 145, 192), meta=np.ndarray>\n",
       "Attributes: (12/52)\n",
       "    Conventions:                         CF-1.7 CMIP-6.2\n",
       "    activity_id:                         ScenarioMIP\n",
       "    branch_method:                       standard\n",
       "    branch_time_in_child:                60265.0\n",
       "    branch_time_in_parent:               60265.0\n",
       "    cmor_version:                        3.4.0\n",
       "    ...                                  ...\n",
       "    intake_esm_attrs:table_id:           Amon\n",
       "    intake_esm_attrs:variable_id:        tas\n",
       "    intake_esm_attrs:grid_label:         gn\n",
       "    intake_esm_attrs:sub_experiment_id:  none\n",
       "    intake_esm_attrs:version:            v20210712\n",
       "    intake_esm_attrs:_data_format_:      zarr"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# note how you have a new dimension 'member_id' indicating that we have 10 ensemble members\n",
    "ddict_members_combined['ACCESS-ESM1-5.gn.ssp245.Amon.tas']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "ba5865db-002e-428a-8b14-60cda9b31a95",
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert cell bound conventions compatible with out regridder (xesmf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "155e688f-eccd-4e0a-9b7e-ab6cb4dbbef2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1251/2173723817.py:11: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
      "  ds = ds.drop(['lon_bounds', 'lat_bounds'])\n"
     ]
    }
   ],
   "source": [
    "import cf_xarray\n",
    "# special processing for xesmf: the lat/lon bounds need to be in the\n",
    "def convert_bounds(ds):\n",
    "    ds = ds.copy()\n",
    "    \"\"\"Produces lon/lat bounds in the appropriate format for xESMF\"\"\"\n",
    "    ## for this we actually need to use the vertices (need to correct that typo!) variable (which indicates the 4 corners of the cell)\n",
    "    lon_vert = ds.lon_verticies.load()\n",
    "    lat_vert = ds.lat_verticies.load()\n",
    "    \n",
    "    # drop the old bounds to avoid confusion\n",
    "    ds = ds.drop(['lon_bounds', 'lat_bounds'])\n",
    "    \n",
    "    # convert using cf_xarray\n",
    "    lon_bounds = cf_xarray.bounds_to_vertices(lon_vert, 'vertex')\n",
    "    lat_bounds = cf_xarray.bounds_to_vertices(lat_vert, 'vertex')\n",
    "    \n",
    "    ds = ds.assign_coords(lon_b=lon_bounds, lat_b=lat_bounds)\n",
    "    return ds\n",
    "\n",
    "ddict_fixed_bounds = {k:convert_bounds(ds) for k,ds in ddict_members_combined.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "574ef46e-a13d-4659-a1ba-c65ee8aab3ad",
   "metadata": {},
   "source": [
    "## Load island geometry and regrid coarse climate model output\n",
    "\n",
    "The geometry that is loaded was picked at random (and does not include all the desired islands). This needs some further research to find appropriate input data. Just using the below as an example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9cc52888-595b-46cd-ae3c-942b54628032",
   "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>scalerank</th>\n",
       "      <th>labelrank</th>\n",
       "      <th>sovereignt</th>\n",
       "      <th>sov_a3</th>\n",
       "      <th>adm0_dif</th>\n",
       "      <th>level</th>\n",
       "      <th>type</th>\n",
       "      <th>admin</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>geou_dif</th>\n",
       "      <th>...</th>\n",
       "      <th>region_un</th>\n",
       "      <th>subregion</th>\n",
       "      <th>region_wb</th>\n",
       "      <th>name_len</th>\n",
       "      <th>long_len</th>\n",
       "      <th>abbrev_len</th>\n",
       "      <th>tiny</th>\n",
       "      <th>homepart</th>\n",
       "      <th>featureclass</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Melanesia</td>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-99</td>\n",
       "      <td>1</td>\n",
       "      <td>Admin-0 country</td>\n",
       "      <td>MULTIPOLYGON (((178.37360 -17.33992, 178.71806...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>SLB</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>SLB</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Melanesia</td>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>-99</td>\n",
       "      <td>1</td>\n",
       "      <td>Admin-0 country</td>\n",
       "      <td>MULTIPOLYGON (((162.11902 -10.48272, 162.39865...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     scalerank  labelrank       sovereignt sov_a3  adm0_dif  level  \\\n",
       "53           1          6             Fiji    FJI         0      2   \n",
       "142          1          3  Solomon Islands    SLB         0      2   \n",
       "\n",
       "                  type            admin adm0_a3  geou_dif  ... region_un  \\\n",
       "53   Sovereign country             Fiji     FJI         0  ...   Oceania   \n",
       "142  Sovereign country  Solomon Islands     SLB         0  ...   Oceania   \n",
       "\n",
       "     subregion            region_wb name_len long_len  abbrev_len tiny  \\\n",
       "53   Melanesia  East Asia & Pacific        4        4           4  -99   \n",
       "142  Melanesia  East Asia & Pacific       11       15           6  -99   \n",
       "\n",
       "    homepart     featureclass  \\\n",
       "53         1  Admin-0 country   \n",
       "142        1  Admin-0 country   \n",
       "\n",
       "                                              geometry  \n",
       "53   MULTIPOLYGON (((178.37360 -17.33992, 178.71806...  \n",
       "142  MULTIPOLYGON (((162.11902 -10.48272, 162.39865...  \n",
       "\n",
       "[2 rows x 64 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "countries = gpd.read_file('https://d2ad6b4ur7yvpq.cloudfront.net/naturalearth-3.3.0/ne_110m_admin_0_countries.geojson')\n",
    "# filter out some of the islands we are interested int\n",
    "study_countries = countries[countries['sovereignt'].isin(['Fiji', 'Solomon Islands', 'Marshall Islands'])] # not all cou\n",
    "study_countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "32b57786-4bbd-4476-a9df-5d07f86a2737",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_on_geometry(ds: xr.Dataset, countries: gpd.geodataframe.GeoDataFrame)-> tuple[xr.Dataset, xr.DataArray]:\n",
    "    # create spatial regridder for every source_id (and plot how well these islands are represented\n",
    "    savg = xe.SpatialAverager(ds, countries.geometry)\n",
    "    out = savg(ds).rename({'geom':'country'})\n",
    "    out = out.assign_coords(country=xr.DataArray(study_countries['sovereignt'].values, dims=['country']))\n",
    "    # create the weights to confirm which grid cells are used to construct the average\n",
    "    w = xr.DataArray(\n",
    "        savg.weights.data.todense().reshape(countries.geometry.size, *ds.lon.shape),\n",
    "        dims=(\"country\", *ds.lon.dims),\n",
    "        coords=dict(state='country_dim', **ds.lon.coords),\n",
    "    )\n",
    "    out.attrs = ds.attrs|out.attrs\n",
    "    return out, w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "6a14e42d-c159-4471-8388-f891a5cf57f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/srv/conda/envs/notebook/lib/python3.11/site-packages/xesmf/frontend.py:1220: UserWarning: `polys` contains large (> 1°) segments. This could lead to errors over large regions. For a more accurate average, segmentize (densify) your shapes with  `shapely.segmentize(polys, 1)`\n",
      "  self._check_polys_length(polys)\n",
      "/srv/conda/envs/notebook/lib/python3.11/site-packages/xesmf/frontend.py:1220: UserWarning: `polys` contains large (> 1°) segments. This could lead to errors over large regions. For a more accurate average, segmentize (densify) your shapes with  `shapely.segmentize(polys, 1)`\n",
      "  self._check_polys_length(polys)\n"
     ]
    }
   ],
   "source": [
    "ddict_extracted = {k:extract_on_geometry(ds, study_countries) for k,ds in ddict_fixed_bounds.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a798a1f-98dd-474e-9fce-2df4d74936ce",
   "metadata": {},
   "source": [
    "## A word of caution: These climate model outputs are very coarse!\n",
    "An example visualization of the grid cells that are used to construct the average timeseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "06c3b336-5fff-437a-b39e-ccaabe09e9a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the weights\n",
    "p = ddict_extracted['ACCESS-ESM1-5.gn.ssp585.Amon.tas'][1].plot(col='country', x='x', y='y')\n",
    "for ax in p.axs.flat:\n",
    "    ax.set_ylim(-25, 5)\n",
    "    ax.set_xlim(150, 190)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "945a6813-a513-4fbb-a54f-d5a79f3a09a7",
   "metadata": {},
   "source": [
    "## Vizualizing what we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "3636f3ad-4c39-4dc7-8277-8423cfa320da",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask.diagnostics import ProgressBar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "530f0fa9-6f5d-4d7b-a32f-934864fedb7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 1.52 sms\n",
      "[########################################] | 100% Completed | 4.86 ss\n"
     ]
    }
   ],
   "source": [
    "with ProgressBar():\n",
    "    timeseries = {k:a[0].squeeze().load() for k,a in ddict_extracted.items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "dbd4b5c3-bddb-4012-829d-8ad5c44cb4aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hDfa6rJBmHqVjgxASyYJBwWpKtxZCZFjR8Yes3pTbSN4Z6vjHIK3c0fNzMbAqY6woQBh0W0UkAzAzHV6v2ZMwvQOZrE2sBNW3ZARCza3ZZ4hMZjIyMjIy3viInn0jzc1eBTFywwZeQ89H5HZnY7lDKCkvlo+jO+pbnzEgM6rMaOeVsZITsy/JvGLqDWtpu664fKS39VDzfouZbEu+2hWfdyH+GwNRcqTLqTsE2iUQPDC+KkpSLepRx2UsY/kY/BGX7trrTGzOEJnMZGRkZGS88ZHKOHGzNTspIS9BZijeeZTAHfc5CKOD6ecb2ULamqVs5Fe8fJDcF6JNzwzA/hpqOfSOSBSSKOpOwx4ga3nbbsz77haSH2PEOCzG3vV1IVGr/jgJgHXA8jmguS4lMIgSNJdOqI63b8fA+gaH5bWHTIBoMADzDJDJTEZGRkbGGx+a9eImg5A6oFdmjo0H6I76XBaAVZ36xr0RmnafSzhq1NWwO7Jgo63kuJjQE5i4ZvUokRpVYGqeUk1r8KwkYhJDgclGWANdzYSEpDwUW26nBvH+QQCceG4s0swlY4FyBpixqD6Rjb+xZaIVayAu2StTXwfWL0gL+ELGK3jAnu3U7ExmMjIyMjLe+NB5RWHFpKLa3VRAhspM9KJcSMcT0JOd8BIKhF/1AXIpdE6mU4P6mUia5UKiigznJ62eA5ZfkhLOPpOPbiHEQiJ8o5h7QyekRjqKjBXyZPukXzPq9+lKJk8wQJROJFMAoytcloqt+G2OpRG3h3KMc1Fj9mUu05K36aov95V5VZC7mTIyMjIyHmyoemLuYuZVhSQ20s48SNgFNpUZGqgvdMoMpdMQGjbK6vamj/Bj65tslnVT3m7QadWVmG+VnHSAPwDqipWZ8cOsDK1e7Es+quxED4SjPtBOs2pArM5ACIqel5FAPOPYW0OUZk6mY7CuLzcZKWOB+uVDw+UqayQNuO4Ny9ED8WwHTWZlJiMjIyPjwQVFLv80N+++XOzAqbuiXBglMRpON4jj3/DPDNWbO9ywQ8PEY32tL0PFIKrKbVYzYs2PbWxHPC/asRRJykKS8RI00K7l8lNsWR0JayYUYTUgM4Xk5UgJKo0mkCnYXidtm0GujnQ+WSMcTEiNMX35yCkp8qIq1bx/Q+zNCQEIh30ezRkhKzMZGRkZGa8fQisKgXt1tueXfalmY2jjADq6gIIoFpQElERUtFRjzCaZUZNtbFl5MTjZhhxWSOMJtAspdr0515Z9+UeXIZLjkpKWsUCxhSSZxMCKjo4O0PMLHVAYAB0bmV3Dc5KKiZR6LK9biEpFvh9rEAioLop5WMYRxA7wHc9Y6kQ1IsmqUbXGOHC7dgtEC8QFQK5v7/YdzlobyWQmIyMjI+P1QWg4F8UYYPLwq7PNjfLQnciMelOoN8iqeVaVCKIB2TmmzCAy4QDYLzJ99PTt+yWv7yomELHuy1tE4lcx2Bgi2c25O8gYoBgLYRFC1d5kdUTbqpXYuAkAC6xeYNWnmwvpsEISJU+mKOWaRN5OWUro3h4TmXZPlCTLKks3R5r7pOSEWpn/1DJ5Kie8LTNoIw8t4Eav4EV85chkJiMjIyPj9YGaZ1+OB+XlYqML6Q7bVQ+METWBOi5NtQfA+DKTEDftW4/vVGYCcHpsvxh7/Yq330Uhbrd6b0r0THKMRZpi3R2yOReaxku99ySugbbjYzclKyHtEZMlWwFdA7RP83EDbGg2TpaNvD075d9TiJ7MU9KhkDo00h/J/tUk3TFpgZSljEzuDrWQFi8EzfAycX2XhOXXB5nMZGRkZGS8TngNTKLDVuk7ZcUcJzO+5jbkpCx0gKn75Y6XmYYEZiNBWP06t4H1i/KYlS6jJZMAMrJfKWHBSS6MlqGWAFqACik1TXib1EjwXYFEKIyQFFMCJKF1ZsTbtSMmNsYOcmMKAB0rPRDjbnPAKhPJkMjQsDIUWnCpTIdKBlZgVFUyhsUaEm9PaJkshSO+PuZs6UQ2AGdkZGRkvD54LVJ2X44yo4THaL5LQCIoRHzTj92AzBzbpj/q2631OSJg8bR4TlYy9whAORLj7lzamyVZFwYwFftn4rr30LS3hbSIOtPc4FLQ8nlpyT7sfT5azjLg8g9FAJ34aVqkkQXWSPnMIQ2XBGR8QcdfaiCmAFQzKTFFnsYdowysPJTrJyZilED9HLD3m8DqqQGxaZiMnSEymcnIyMjIeJ3wKiszMWz+fkdlRsonqh7ETiZML6WM4+TGrGRmoPZ4ISbdge5UHl8w2Wj2pHQj63QdB8s1e0JwJPm3OsclLVuxWuPG0mEF9IqIqCKdZMusrwnh6Hj7fsndTgZClGxPbqKst3iOn9Phk+2hKDEB/dwlOa/oJXBP1KdO1kEQv48X4iTqDK0Bvy/rHwL+Jh+3MYDRczkbZDKTkZGRkfH64MSQx1e6vZdLZpScGCQy0twGIKZdW/bqg964FSn4bnDcRGyGbQ+YuPgaKc+leZHHBdQ3mDBZUWXcWOYkgQmD2+JjocgEpTvkY+kWogIJ0YARP84RUp6MKkx6vGmQpOFtGyP+HTE3+7WoJ2Li1Y6t2MqXKFVGzNEGojgtpVxVynEsNq9re8DLekkfPkNkz0xGRkZGxuuE411Cr3Bi9VBB0W2Sdh4ZniK90Wqt7coRQACKHe4g0vJLHKbpSmcTyY3eL2Uy9Q77TsK6V1bCIVJ7+NHnuUvIH3FGy+Rh3o6SEO2qUsOv5sKU27LNNZd4UheUkJqikmUjB/Ep2bCmL0MZNzABB2m9Bvtj2n3pajri0QW2kP3ryIRS5i6NmPQYA8QVYHflermTJt/uNlBeEBUoh+ZlZGRkZHwl4LjC8UoRj5c2pNV5+SVg+QyrHfo40HMn8uwZafeA+jarE6boBzb6I1YdwprXDYPSUX0DWDy1uW9Vb9TQ6xesVuh21TMDcOgdIqstUKPuWGZGlaKU1H1CMQnpUx8LBZ6NFNasvuh8JO0wCqLy6LH7pSgzMl07NLwtCz4OFLw/W0p4nrZfFYOJ3IW0YrcnX4PV54H9/wZc/z++7Jfx1UAmMxkZGRkZrz2Gc5D4gVe+TSUUVlNqo5AIifnXVvDhnCEdHQBRLtrbwOFTYP+J5zKNX/HvfoHeANyJ6Tbw4zQwFasqQdr2TJLSK11B0CwbISjdEScWR1F/ClFKDNiAiyAqkZSunLRvo+Pr6CouTenxqN+mXQiZ0gnXUn7SxF5jWPnRc9cWbjfhYwlrwEjAIDR7p+ZlVl/oL+H0bazg6OtIHfBHP8kenzNCJjMZGRkZGa89TvhZXg3PjJIZHXJ4bI5SmtWkBlYtMwU2vXaHPJ2625MbfegzWIym7kobchQzbHfYKzi8ILgkJS3YmtSbSkSH0qZte9NuaGW1htWQbi4ErJF03ihErOtD7YzndnJTSBmp7U282pbtD6R6JwRrdVPKWQPPUJAxBck8bCVXRkYc2IJJUPMCb687AI4+I0F64H1vvRXY/ZrN1+Lc+5BmR50BsmcmIyMjI+N1wDEy80rLTNGjzz8pB9s8zQQs3TrG9h4akhlDgJRh6j6DhmSukZHZRlGGNw73Hdo+YM9oacZhc8ZT2y+PgslXWMlj0iKNiglNeyCdTr736dgSaZxAlHlSBJ6I7VtWYNxY1hHz7nAGVbfXm5Vh5fmWlaWw7M3P6hfS/R1+ticvx7H9Lj6Xna8Gjv5vVq2KXeBr/zdgfOWeXsJXE1mZycjIyMh47XG88+iVKjO6PePQR+/HXtVobgGdkJU4DL5zSEZaQAhO1d+8g3hZUiZNBJqjzeNVpaM81ysl5aw/BoWGzlnLx9jckjLYirup2qUoJ6poiJFX96vKibGi3ATAOQAlgE6ImWf1xB9wmSeVntB3IUEIUozcLVXfQprWbXVWlZTEVk/fmci4LWB0mclPUQDnvx6YvBXY+RpWjs4QmcxkZGRkZLz2eNXLTLq+7ctJSma6I/GQDCdpD5QZjrLtfR+GhJQUfZCcsUgR/92B+FB0W10/Z2l0gT0vbpvLWFFya4wFd0zNgOo87y/UvXG32eNjCm0fuEeO9xFaPqYovphQM/nxa4BkjlI6Lc8EpTvg9ShIR5Im+Nai6gipgeyvOwATOymPhRUPoty4ZgPYMXD1r3DqL6Tdu9zm4ZhFwUMqzxC5zJSRkZGR8drjOJl5pWUmXT+RE4hiEntlQj01mueiJSZbAN706yeTrpUcFvG+tGL8bW5sKksx9sSmmIoCEvtuqWLKhCq2POOo2JLjlJKVqSQPpgCoYHIRt5n4GAiJ0XTdjtuqg5SHijEH1qXp3EJ2IsCESQL8DAFoeBuaR+PGolLJZGwr5M6NxT/0Yn/NygvA1tuErOzy7KfJVWD+WSZtuh87YoLj1Ld0NshkJiMjIyPjtceJMtMrHW2gZMgMlBkvpRSZ/lztDsy4moAbBkbVYe6MhMbFtSggntWQbqDUjM6xYRga7x8k5K4FnBV1Iop/Rco469tMWELDy0KMxVG2W8ggSN8CI8cKCAJv31j+Xf09JG3S7YG0aYv52I3FT9Pw/mPDM56iqDvaAk5BPDsToJzyMcQAjHYluG+/v7zjR4Cdd3OnU3OLSU20fG7GCSHbZzJT7fYG4jNCLjNlZGRkZLwOuIsy82WpNENlRkiJzlfS7cVGSi20qcyoD8VCSjLSZQTiEhBJ6cav2eBqZaYSOb5xF7v9OAOSrii/EEIhHpnYCIGZs5ISWv65XfGuWikNaXAd1NBcSWu0qCaG2JOjHVletqvEBhiQFDcI0CsAO+nPPY0oiEx6Dp8URccDbsaqUP1if3knD/F1Jc+kyVj261TbUpJToiSeI38sUO91RlZmMjIyMjJee+gcJWMGN3BIOF3NnTDmHj5f01CZ0fWkjVrR7HPppDuQ8oqWlLTtGpzSC+qJiJe26e42l1wo9N1SJoBvm0IeNHFXDoP3Tb0SpMnC6+eB4gKfJ3kuHUGTgA2vE8WbE2XWkin7nBgNw4OUmowoMuQAOKRuJldyuac7ApZPMlGbvpXXjx37dIodYPFHgJ+zoffSN/I+2jnQXOdzcTPA7fD1CdKSbkd8ncttsPoTei9OudO/nmeETGYyMjIyMl4HaPeQtCjrzc+v+u/l1j1sT9WXwKRFU3i13RrgG7Yab3UukybqKomwFX+PEaAjVmIQJUgOQiLEi+IbVkNCkHmNjtuq+cR4XU0Qhs45cpIns5JzlVC6ei6mWw+4wCpHuw+gBXcryX4pcLt46PgYC1FL7IiJmJeZTEFSi2//tqQMA8ARq0HjR4D1l/ghO5HgPPByy6eA838WWDzZX9PxI3xdXMUkyBTSNh6ZZLltIO7J9gqg2splpoyMjIyMNxBCw5/y1zc4+l8VFDUAq5Lha6AedM5EL11I+qn/pVp9JSBv/QLflJs9fixKXox6ZVY3ZbK1KCHqnTFOhkCWYpYV/0t9TUomBXcSaRovef7djcTvMlAitMQS1kys2jmTjXLaK1LR98SApKuIiFua2z0mSGHNhAmQTiorHVBLpJZrW0ppqGQ/jdWgPstjBRKR0cvU9UQG6ImMYn2NX6fbv9M/Nn0EqHZk+6JEEfG+nXh8UDDZsVLOctOXeL1eW2RlJiMjIyPj1UNzmxUGW7EPQzuFlFw0e1wqKbdZ/VC0e9Jt0/VjCCZX71x6ImJlw8tsIiOhcCHw+n4pXTdLPoY4iP43BcQwwz6QKAQjioF49QJQXZTkXxn6aMSPYgzgO1ZTIF09kJ/Vb6NmWxRybJr1omm+DjAjwBxxFo4rgHAAuCv9uRGEJJVsAO6WTJD2nuASWHUZuPhNfBzGAN2NTQPvy0VYAjf/M491UIwf75WfrpbEYDFIWzElmyMhUgYYXekngp8RMpnJyMjIyHh1EdtegaHQqzI6AoAik57pY5vruLH4SjT11t+l5VdUFlOkX7ku1PUpvLHulQ7Nd4GRjBgx/JoCsFHamaWEE9ZSVjoStQhSZpGZRp2oQFvb4pMRY7ESJop6QLx+WQHBsvJjDKsY6h3yC8BdAroOKBretr/NJME5Ji5Hn8aJCeHtTdn2Nqs4y4H64raAc+8H1s8Bqy++9Ou1fKr/eetdwOQKd0Op0diU/HM5YWJT7ADdLX6N3JSD9OzZ0olcZsrIyMjIePVAofelpN+HAyF1evQgqRZA8tTosMiX3pEQErmNmciqSmhZbeiOZLE1UpBec5M5RrmDNGARhZSOtOtJjldzYrQF21USnCflodByK3Z7Q5QWGUlAHe/DGPm5ZRUmzY8SNSgpQTLniRouu7ULpAGQMJJxc4eSW7cnnp04mBAO4Pyf5jC/yWOby48eAopzfCzV5ZPbm/4J4PyfAjDia+nrdMg8wykwsalmPVl1FZeu7sW8/RogKzMZGRkZGa8OiHriskFmBqMHNPaeOr55l1tMXrRjCFI+opZJh5NW5bDkLhsrN9FuzuTCoPevmCjrgtcPEaj3ZCI19SUjN2P1whZAMeJyTrmDNOTRr3g7UVu6i340gM5/iq0oOLWUoyR7JhL7d2MHeAKKFUA7AKpeBWKpp98eiem3nYsiBaAcSalpfufr3R3wMt2axxkA0nVU8fanjwH7Y/EROWDrHaKATXm5Wx9HGl1QngfO/WkRlDwblK0Q0wi+PlZGQbiKjxcWKXzvjLWRTGYyMjIyMk5Hah1+ucsPSkr9g3xjB3rfCdA/Vt+Qic8dUJ3j5bs5UGwD9XUmO+1tpOGO40v8vV2wGmEKKbds9cSCZI5RXAHxIt+EY8fKyeiS3OwJnMuihlYAsAPDa+T7sw89oTG2346pOHNGW8u9lMes6c8tLoB2Aow6wLZCAiJgxkwOmttCepZAdQmgI16famB5jfc7NPRWl1lZWX2ej7m9KQnBt/sSXnmOz8MUrM5c/avA/L8D08d5XIF2bxUjJi/r53i9rXdyaUnLb7EFyDGJM3I91fdkxTtkLJj47DEhre6lG+3VRSYzGRkZGRknERo25Za7HM//cqA3OwAbZaNUTrIDL42SHOk8SqF61G8j1NwdFMREmzw3OigysppBHdBJB5RfMBkyI/Z3xA6gEe8nrFlBsY73o11TBFZimrlM0O5423YCdM8hqSjGAmFfjk/3dShqSs2emAigqgAUTESiTOGOnvdZ7PZdQDqJoVv1rdt+zTkwx0tL1VVg+ij7U8Kcy0/+SLwze/1y40eY2I0uidJjgK2vYjWqeZ5NvdWUS0Z2CkzeLCSs4nJbdZ7P31omlJ2U88JCkoZlnpMdgctRjcyaunGmZCZ7ZjIyMjIyTqLd45twe/DSy2o7tSbnAkhlpiE5AaSkomRlxWSgvtmbdofmWTXhhsEQQ03cJWnN7la8z3afFRp/yGpLrKXlecnbSyMMJGCOSHJhZMaQb9hTExpet7ktXhrNxJHSkHZLUQusb3Jq7voGtzh3c348GgnjkzwbCkwsukMmC2bESo6qTWj5+CmyB+eER8YC7jybiI0Dtt/VP7X64mYn0vRNwOiitFDr6ATxJzmIabfikpwOsYwtH2dY83lql5mRUQdu2putNYBvdA4YzXhaeLUlYxjODmdKZn76p38a73vf+7Czs4OdnR188IMfxK/92q+l54kIP/ZjP4ZHHnkEk8kE3/It34LPfOYzZ3jEGRkZGV8huJcRA+0+l4Tagb9Dy1Oas6Jo9sUga6VTSDw1nZp+NUFX82kGpStjhMioMkO95wNGvCtgktDMZZzAkktC6slp94DuppSOJMGXPHtTCNIa7lntCY1MqFYyI6m30fMQyu5AiE3NJCpKsJ21Eoa3hTS0MsgcpG7OXUEmypiDTkpjMlfptLEA1RVOA7ZCymZvHVzP6zJ4EtxlNL7Y+4oo/Q+J0DnDBDD6/jxJ2rtRgEcXSHkxxMHqooQZw+dSnuPSWPUoX5dwtuMMzpTMPPbYY/jIRz6CT3ziE/jEJz6Bb/3Wb8V3fdd3JcLyEz/xE/jJn/xJ/Kt/9a/we7/3e7h69Sq+/du/HUdHR2d52BkZGRlvbFDkm76m874UsfFrviEOA9mSoXdARPTO6ApRRXTEgOaYSFbMsOyk4wcUoelVmTg0F8u+dDYTkShFcyFE4gVpj3hkQVxxqSdKB1PU9vGmbwsHuMSmHph2gTQgMhmAWz4Ov+DfjaTklmPevxnxd82saff599u/y+Wkg98VRWkt3wf3t4f/OnDxW7hkRBLiF8X3Ul44+TqMH+FjMYX4nYSUuEp8QoZVKUBIoFxDWAAyrgDymhjHJA3g7aRZWJZ/LLZYldl6GJg8yuXIM8SZkpm/9tf+Gv7KX/kreMc73oF3vOMd+Of//J9ja2sLTzzxBIgI//Jf/kv803/6T/E3/sbfwHvf+1787M/+LFarFX7u537uLA87IyMj440NvUmrCuLv8gGSiIlPfRMbqb22ZNUipfxKCzEATt2VzhgAaf6Q+jESoYGE0sV+G2pQBZBamI1BCuYLCzEALyVnZsWEpNqWG3wE/B4rRN2Clw9CxqhjQkZeFBJVLIZ+Huk+0pKaKhu+5uVi5PWCpvXW0mElIwmIgMPPA+tnZJOec2Tm/z9g/4m+K8lUQHUBKCqpcIlxuNpiJebKtx57IQyw/U4hXkocDV9rSCigG0uY4Vie1vZ2AJA2cpJymg7jhJId+TKGTcpGSnUESQoucZa4bzwzIQT8wi/8ApbLJT74wQ/ii1/8Il588UV8x3d8R1pmNBrhz//5P4/f+Z3fucuWMjIyMjJeETY8LqFP5D0N0fckJojvpRj3fpuknNi+5GSLvv25mA5KSXZQ1gisVqyvM1nijfDXhslY1Ac7YVOqKibGiuIjYwis4/JKcyBdTyv2mujspNhxaao9FHJDTCjUuLuhFkE8L7KenouOKuhWSOMK1BQdIxOlsAIWg5C6dB2bzd+r8wACD6g0DkAhZTHLpSBbccCdYuurgPFlJFcxGS53lbuczusKJjPFVJQnMT+bsu/UIjFMW4s0gdtW/DUMGSx3+Lpqvk530Kt4Z4Qz72b69Kc/jQ9+8IOo6xpbW1v45V/+ZbznPe9JhOWhhx7aWP6hhx7Cl770pdM2BQBomgZN078pDg8P77hsRkZGRsYpGCosx8s8xzEc7DhscU7qyfC7qi1StumW0m2kfgxZj8Q7EiWNl2SIoRkMiAREhRASNFQSVF0gjxTiZ0aswpiJdCxJeSjU4o3xvdmYIisNpFOw0V+DbiW+mhUv4xtuXXYjJKKlU6atEp22v6bd4Wbi7p1QnOdW9aIB1jt8jKZg8lFMeB/TtwlZ2eZSjxvx+dhSVCrHxLGc8UDK0vL6biqm6VrIiwHqW9IF9RCTODfi62NdnwPkxjLOYMrXxaBX0844NO/MlZl3vvOd+NSnPoUnnngC3//934/v/d7vxWc/+9n0vDmWcUBEJx4b4sMf/jB2d3fT1+OPP/6aHXtGRkbGGxLqEQGQWqhDe/qyw86b7lBu5hqYN+hMgnT1xEaIwOjYcupZ6Th7JtRMLuobwOo5MQurV0Y+sPq1eEgKJBKkRCklDXt+rH5ejLtLVozafaC9xQpLd4sNrOp3IepJDkkWjXZsFZIVo0QprvnLOCFOnktLZor+Jh+YnGm3UFJmDDB7e3+sbotJl9sCRud7348BqyOjS9JCLQm81rFKUl3goZblOWmjFzVI50bZERMWO+bjKXdEoZHrFj0rWrHjslk568kJiafJSolpdBmYPda/XtYK6Tq7tmzgPiAzVVXh7W9/Oz7wgQ/gwx/+ML7ma74GP/VTP4WrV68CAF588cWN5W/cuHFCrRniQx/6EObzefp69tlnX9Pjz8jIyLhvcbyT6OUi1EJKNAMGQHPr9GU3SlJeWrkllyV1AQGpRTnqvB8JZENk74aWo/yRlGOWSG3AAHD0VF/SaaTlOgqhMNqGPJi2TQCXSsAm4MUzsq3AmSjaCt1JaSl2MhJAcnHcSI4pAHEBrJ7dFKj8EZuJI4QItH0pLXqeOl3tim9H8m3aPeCZ/9C3mhfbTEAufAOw89XA9nuBc18PTN/C19BWPbmhwC3TVlurbU9QVB1TA3XUwZgyUiHK+Wi5SMmRsb3aZR3vU4MHzYivhZM0Ycg6o8vA6Crvt7zAitD5r2FP0hnizMnMcRARmqbBW9/6Vly9ehW//uu/np5r2xa/8Ru/gW/4hm+44/qj0Si1eutXRkZGxlccQiPt0gd3X44isH6xXy52TFw0ZwbxbmtvKjM620jzTTBosYYk4yYvixGPSeiPQ7cXA1L7NqQNmyITITUjxwBAFAVY6biBGHI956zocMjusCcQ1HKGjHZQhZqPJaxlJpSQI7fTK0GaYhxqgCxPku7WvG8now5I8miUAAESgifBfwAw/9TmtauuCrFwwOStff6LkcC6YsLemWKLCUc55ceNeoeANM5Br7NO7rZDxUrKaUZnY1kmN67qPTOwUkqa8LkWE2DysATlFX05qZjweuUWH3d1QTw0Z4sz9cz86I/+KL7zO78Tjz/+OI6OjvALv/AL+PjHP46PfexjMMbgh3/4h/HjP/7j+Kqv+ip81Vd9FX78x38c0+kUf/tv/+2zPOyMjIyM+x9ewuv8SsYE3AFBBjHqclHKJDpnycz6ZdVDMcTG+IJBNox2/ujN1o6RhjmGRlQBHSUwUGaG+TKu7EtV5MUPom3HTkpEcz7XYixmW113jFTmCetBqaxjE7CV0QT+QPJf1tKdJFks0I4mz6UWRN63tTzJOq5YvSBiUkMlf0GyWxafB17435mA2RFQXdw0+U7fBowfYnIVPU/WNob3FbwYbbeB0RVg8TQTGTeRid/jvpxHljudYmBCqoMwTdGTF2rlOKREZaVTqj3gLJko5S8NviMpTVU7YJJzoy87mVKuccfG4mLGBOeMcaZk5vr16/ie7/keXLt2Dbu7u3jf+96Hj33sY/j2b/92AMA/+Sf/BOv1Gv/wH/5D7O/v4+u+7uvwn/7Tf8L29tnKWRkZGRn3PYaGzHuZsRSUyAhJKc/16gt5cIzsAMPJ1yn3RRUd2e/4EqB5MqFhtaE9YKKTplVL5kl9Q7weHsnYGyOXhdY3+vlNtmCS0kn30eQhTuSljk25WjYBhMisef6TK3qCpb6Y2DEpUk9LsS0Kj44xkBLW+jo/51d8HcJC8mQk0A6WU4SXf7x5jWID1C/0v++8F5i9g5dFycdTzNjDo9PAbcEheFuPcQmnvSWJyEugLPmxYluIWt2fJ7V9dc9aIJCcl0XK0CmmfH5uxB4g3/DzVpQy6gC7xR1isRYfjhBTPwdaMQe7yX2hygBnTGb+7b/9t3d93hiDH/uxH8OP/diPvT4HlJGRkXG/wK9kAOGFk2rIy8KAvJC04L7UcoAoM5JUayyw9RbubonS2XMcwzJRu9f7XHSitSoEw7A745h8rF4EaN0/7oVQhDWXcpyoEcmk2om6IW3TqRQWer9Ks8835fFD4hcpByWkCKBgEhCXQNtwt1Ax6YP/7Iivtyn7ClscqEntLZlLJOZjEJMGMsD6i4Dfv/vLMnkc2Ho7b8uNhLgZJhXWAlT0eTDWgcmjzJKykBwbx+digpATKUPZQenJjQBsAeGADdBugo0MmRiknV2Se620Z7dzJoxa1ooVD7gMy0FHlZS5NGvmPsB955nJyMjIyICUDDpWJL4cHM+KuSOGpCcCkHKOtkmHdtB1dBqZGQTKgZiAqEck+V6EcAD992JLfC46mgBAc8TEqzti1cMv+IYZpdsptqKYyHFHw9OfiXifUXJlgJ4MUCuBdq3sS+/2A++OnQKFeF80gM+V8jVm1USvRXfInhE36u+ghrhUs/zC5rWpLrMKoyh2gMvfxudezJgwKVFV4uZGfBzW9dzRyaBMI8dlnVybCRMxVdKiF1WnZPXLyvbUP2Sr3tBrnahUIy4vVdsAOr7G3REvEzs+VufYy1NsicdGXldjZQbV2eP+OIqMjIyMjNOhk6LvFUMCoz9rl9LGFOwBQdHpziTTrJOXRQnPaWZgeWx8Rco1R+A5Q9qqO8iOAfrveoOOAZzeG4DVl4D6NoDAN12SG7Ov0c9NCnxzLbd4CGJYActneT31+gBy04Ycj+xz9hgThtWLfE5FidRZRYZ9N53s2455e1aUIb25R9+TAp3CbQzQXu/LcdUV4NG/zv4Uf8gKW3cAnP+zonZ0sq8V4GWUgrXA7FFWpPyK91dMeNuTh7n8ZksmSESstrRS5nIy6yk4aXkXY26okWZfxZb3UUyQzNduCpglZ8sUMylXCeGLDXt3nBAaNSV3h2IKRk+Q7qWM+Rohk5mMjIyMNyJOU2YaSdLVUsoJxN4zoQMSKfT+m1OVmcFIAp1MHQf73pi3BCTyZIRseJmiTdSbef0RAMcGVFPwTTbKdOduH3BX5YaqN92u796KHjBNf6waWFdsAyiYPEBC8cxMfDFyXBp450TxaJZcdmlroCyQzL0k3VbkAWdZIdJrCwCTR0TRKACzA1z4eiYSvpFyFwFmCxhfAOqaCVqIYPNxxWTNFUxItr8KmD/JSsv4CisozSGfrzV8HppSbGKv7GjLenVB9ttKx7y2zYPJTDXh5cpzogJKR5ebijoU+VpXu6LSScu3scBICFN9nc3KxcAs/jojl5kyMjIy3og4rsycSPVNvwx+lK4hTeXVYZNpkVOUmagBcoNylLZJm7I3jw6VGSImLM0e76O5zaQh1OKZ8ZwODCMKToUU6Nbu9x07QTuODK8bWy73kLRa6zwoNcai4y836ZUbE/i4g+TfEES1GEnpRkpUfskdT6EeeJCk+wgRaHUGlQPsDlCNmSC4qr8eOlJAu5bcmEtcruyvnS25HFXsAKOLfH00G8aNpTV6sDyMZMZUfRChrbjbykm5qZoy0SHDZSVj+jJadYlJ0tZjwOxNot7sCBmTawALTK7y8RQzpNKcjnvQkQ1niKzMZGRkZLzRcDwsjyI282CGRGeotsQ+5j9KSao7AMxjpyw7WCd1/tieEBHxjVTVGki5wxikAYeazxI9gJoViSjLaDnHlLxsqHl2EnVcUipmrMo0e2yatUIqyHNrtWajkHht4hjwEbCeFYfiHEC3RBkCk7aoKpTcwGGlxCXZMWbEKpAds1ensUyo1l/or6mbyflN2Eirnic7knNRElNJu3QBUMnPkxxLOWFCUWlXFZAC7oopgP2eFJLn9m1jAXig8XwdfcvHaOUcNHxQ03xpzOSmKoDyIqtJZDiwb3xByluP8vLrF0WJOY/euzPpFRqAlZwzRCYzGRkZGW80HDf8alLu8edD248OAGQez2BKtXWyblrxlH3Jp3I1hBqS1eNAPdBQtyiqywIozw9KXeLjCdodJKoJhPhQLbOElqxQFFOuhjR7TBbcdn8ckZgcmFJUHc2pES9MWEgZaQZ0N+WYpIOKvJCLDuzjISZJIfQqzfoZoL0BbL1bbvRf7CdgwwLFrphyAx8reVYwTCm1kMgq0Ogi0nBKCyYzThSi7mgw6wm9ZckUAEQ1MiX7bmCYZBRTTjLuFgAq2e+Ejyllz0iXlh0xubEOQMmt87PHuVXcFnJ9tpgMRQ02dPK6GMkjanh/enBfVsfdq4dMZjIyMjLuNxyX7JUsvGzI+mkcwfEygPwc1nzjVjKjGS/aLUShz1457bjStiSDRFWY417QVL7y3OLrJ/2NHJCbpZUb6Fafm0KeDbnL53gEQRj4cmzJN1+K4C4cI0MiWwnXs9LNI2F9VshNXPbkIUiJpFsiqTFByjHzPwQO/5CnVscOOPpDbh1XHH7q5KWYvJnVG1Uv9NythgMOPUWWj9FY6RRybOCNogKVO+hTlGX7xRbSwMfqHBDE3GwcP0Z7vJ/yHL9uxTmZwaSdRzLzqZhJ+dDwtSh32POSgvGk7bqY8sgGfe2jZ0JYXQDqF/tl7wNkMpORkZFxv+F4OUeTdO91fVMA6JDm9aTnB2bcYeJue9h/ircGaNeclnvcvDvcj6buaruvcbKvoRcnMlFKJllRSoyk+UK6c0rdhpR6ls8Ckwuc7WIqHghZ7vb+lW6FFP5G4PJTaEXJWSJ5ddJAyBaAAaIFnv4Znl69+zWcxovA5txyB2hvA9f+3/dwwSGTq9/M3plkPq6ldKTkcsqESxWjIMm8al91E77esEy2Jld5JhVJcJ2bcvmJnkcKwIudkA+9llbKWGDiM7nK5l2/5sfdVNqpxYejKclGDMf1Lb5mVsYXuBEvF1aA3RWDsao06I/9jJHJTEZGRsZZojvkm215brMsswENSnuZ0KyQ0UW5yXXHWrzp2HeI9yRKpxOEwKiBduC3OQ4lI8NZSzofSM8n1OLDabExVVtLKXqOxYzLHHA8ZsCOgHih76ABeNvlFrdx66ynKMeqXh2ACQDAqb8UeZn2ELjxa72qAAAHv88eGPLsLbET4OZ/fvnXGmCCce5rB+cm18NWTNL0HEfngLrlcwg1Epl0FXtcDMA5ObI+daKcnGO1anSRyZYdSxLxEqmt3BR8DSFEhcCdVm7KnprQ8NTtYiR+Jctd2JoZA8OPlRLAV50XklNJ6U0JWYkN5SmRmrNFJjMZGRkZZ4lOZijZcT/j5kSZ6R5TVptbfKNzI5ncLGQmlXVo8J24fIGbUlZqkdqVtUyV/B/HlRn14VCvDnQLLnGsrrHSMLrCn+rbOX/qjw3nmmjpzDrJ0XNI3UR+zTfQokZSNVoJ0UMF2AMgXAeo4ZstIpMlJU3qd0kmY8uP3fz/bBIZxeoLQPUI+2+O/vtdLqzlqdaTK0D9LE/injzOJRo3FQKn107Up2LKnVtuC6l0Z6WbyYjHhiRbxpV995g1vfJlSEhmNQjAK/grisJiCjEeExOWdsWlNytfkCnlBNm3pAiTpPmSEEM3kbZs8fmMzwOrXSRCZqR9vNqV91QuM2VkZGRkKGIDQAf2HSMzYcUKTrUr/ouXgpKVYfZLGKS1DpWZgek2tlzKGU5JJulWSkMhh8es7daDNmHNYPFH0kXUMJHxh/yYLeVchSBZ6RqK4nVBZA+Jbs+30v4t85WMB+oITipecvdQaJlQkIw6iKEvdRUj9pYgDIy6x1C/2KcOD3Hxm4H187zf6ZtFeZJuL3JM1EaXeL+uZKOwkTIZyTUvZ+yjcVI6U/WKopiUSz7+sOZzIt2GTrwWT5IqJ8b1v7sZe22q8/L6xZ70pNeDmChb25NZHUegc6cA2a7tQ/fUZ1PMkFrDgf79V8wAd3jvRPs1wv1R7MrIyMj4SsTwRrARcneMzPgV3+ybW5uPH+9GOm27+md+ozV7oMwMA+1i4H10+/Lp/aXKTKLMGKAnOnKz1TJV7MTQSzKHCNL2LTWOKPshmQmlN99izDdOLwbU2PC2g+TNxKY/bpK5UVYUGCvHoC3qMZ4kMpf+HLD1Dr0gJ4lMeR4YPcwtyzvvFbIUWAnSAZVBiZYQDm2/Pk4miylSJxGEqFghK9YxKYGRkECdnh0H25GLnGYhyWuq6oyb9SRGt5HOa8XrlbtMhnV7yaAsi5piUK4C70OJSyo5AmmyNsD7BO4LdSaTmYyMjIwzA53+850CyI5/Cu7mTDSG6bPDbRH6sofG2ndHTAbSAkJoiimTgrASpWAB9l6IB+bE8WJgKrb9c67ot5vITCvR/UsuQ1HH+3CzXkWwJVLXVXfE/pV2webfbg9p7lDs+Bj9UlqmB63cQdJ9I/G6OoSSPNBc74/1HT8CXPlmYPYWnOqsvvzNwLs/xOUfNUSTQerYik1vvHW2H/RojBiYZdk0mDEICZDr7LQracoEo5gA1RYTKB1hYJ34nCRPJqk16J8vx0yyqh1Wh2LN52crXtYv+tfluGJjR71/xo169eV4R1MS3ZTMDGhDdU7GSlw+eQ1fZ+QyU0ZGRsZZ4U7KzKkzkE5b/07LDcpIQzLTzqX0I2UjLxOTDYRMSK5JaPiTvJVW4e4AGF88SaaiKC3qxQDkE75kqXjxubS3ZdRAzf7W5hCYEpcqRrvA+lm5wY/4mLsFUootlWzctYXckIWwBFFmjGEzbDESnwqAw08Ce3Ng9nagugjUT/cEbvIIACv5NFNWX5oX+LliF3jkfwAe/26gvinelZJLW3YEYCwETo4l6p2+BKcUN0IkxnJsFfiEKy43dQu+poUYjovdvo2ausH1lXKSpuumF0nLRhIkSGLQJbBa1B4C4xmH3nV7/bEZGYxZbnNpzpRAHAFhAhRaupKyVbcUDxWQJm1r15Mem8JYNiTfB8hkJiMjI+PM8BJlppQTcwcYUU4AnDrsj2QsgA4c1HJRt89zddp5/+nbGCnhhP6maqt+3Xaflxlf4e9akiIZKVDMJBXWgtUQ4n13R7Ltmr+0pOSX4pNpWfUIS/RpwCRZMSNelgLQtXzj9w3S+AEYJhBFJaWaAvA3xCMDYPl5/hpi56v5+Jo5qzfTNyHNW9p+Nw9ybI/EPCshdTGIj0d9JgUTkjBQo8ptfrqNPfEqL7B65kwf7GccEws3k2GaMkOJpG1c1RFNbdZy0/iCPCdzk5TMQHJ2SAZEGvTlunLKz1fb0pa9DW7dFm9WN2c/j5qlp1eZELptHm1Q7vSTy1Ob9tmXlE5DJjMZGRkZZ4ah0hFPPq6G041VTiEtQH+jVB8MIP4X8YJ0c84R0W2k/VDvoSCZT+TU41FwWSEGViqqc0xA3EhmKu3zdzeWkheYAGkarz/kfBcCkr/GTqRE5JGmeBuwN8ave39QKIBi0C0FcFdOitD3AEZMfmJkFScc9kTmNBS73H1E4pHRELzZO3if5UVRIxo+H903eTl+B6DjO2dbiEIi16ic8bXQ18JWrMKMzveGW1sizTqyhq/b6KoMgvwCX6vkmWmRfESa+AvLJTTj+FiMmIXVbMxvGlk38P6qc6KU1UBR9O3YEB8NeSYwMPzaVBc5EXh8qT+X8jwvUw66mu4zZM9MRkZGxllho8xEkvUyICOnRcTf0ShMg8dkG6rEBMmdObkxpE/zpP4W+eQf1kB7XVQD33cHUWAiMv8csHpWfCEV78/v8b6KKdDd5vbs0DDp6aSjaKg6wIrCoudh5XHtSGrAHT6QZYyoRaF/zEAM0G1vFj4VFrj4Db3nI/gBCRBlwhVIWTWhlmGU4lkJkgNjCgAy2dqOebtKNJJRt0DKmxldFPJR9KQBAWkYJrV87BSkY22bfShRyF5skFrMgV6Jq87LMMgxE7BYIxl/o2bWSAlp8qgcj1z7GFhxsQVS6Up9Pnqt0lskyEDKc0gdTvchsjKTkZGRcWY45kHRqdFJmTmNzMiNMA1E1MeHKb1COobDBU8bkUCynBMFqJv3wXbdkdwoDT9mZUJybLh9uztk8jW6xDe72DF5aW5ySahbIOW9tAdcuiHPrdalZJxYMZ6GDuw7kXZlvXHHBoBMnfZyLqOHAbfHx+Bb8eY0fEMPy/78Hv/bbBQ+eprJ1GiHFYZQS1ifeE9izeUakmsb16wQkZfrXLICosubkgkRVeAp3KrYaGlQSAEVfN5OWp2tA7zhc9Fk5ujFw6SqSmC/jRVSGTqeKK7DNgHJlmmZ8FRb4oPy/agDkKwjSpD6a0wFJinS1g4I6VKvzkBxGSp/QUzFicTcn8pMJjMZGRkZZwY6+VB7gL5r5RQys77GN6jJw5vKDgZkJg11XAE416sdG7uW5cOSiYo/YvXBr6Vbp+H1ixlSiajZk1bwtvdoAP2NrtkTL8018cdUTHL8SlSihktBJH4XI101iHwcqxe4XATHN/1uCZi1lKMkobcqZSillHKMEa8N9YZmN5Xp0qKOWFU2Yk9IYssEg8bsGwH4nOo9OaaiLxfpXClts45r+S4kSpUUSBCgIVa1yp3+PDXHBRaws4FXBv1xxoa7o2KJvvMM7NdR1cWv+Zi6uXQ+aRCiHJ8by7HJ0MyUtqzJwEFGPYgniAa5NcnEreqVtPxrF1f65f5DJjMZGRkZZ4Wh0baY8KdsQMoEdpPMGMPeECUtw1lLw21pqq9f8JwfKybQDVMxMQHo5rydYptv4mGNjcA6mD5PxYiKEj3fZLsjKVcs+xJVyp2xvP9OJlQHISjBA7QCJhOkQD2joXlroBFSQ56/QsPHqr4fagAz4zZv4wBLfZmofrG/NuV52b6SOFEWSNqpyy2+3t4DwbCB2MuyFryd7pBLZSRlJBrk2jiZRl1scSnKzURFkpKdm4mCM2Ui5STQrpiymDO5KGUk8UMZKfeYMasxtuDjbff5uloS9SxyZ1l3wGSukGtHnfhtxIdjR0ImXe+jUmVNPTa2EOVtLMTKsI8nvfbyPky/DwP37j9kMpORkZFxZlBlw7AC0kmiKnn5JC6PqwoSV/0NNY0SUAzKSEEGRPojMe7uoJ+8bXjZdp9vpmpaDWvxcBgu31jxWIRahh+SdBOtgcXTwPoF3kZSQ6QdmSTnJYp3J7bcPaVKRzEB4LiT6PCPkTplgphsYysln44JFIl3xo7Fm1JIzsw+G3jdi4D5k8Dhp/vzH19lwqNdRaZmwhA7pG4ivd624m1aKfmQ6Y87NqyiWDHOqm/IWFY0xlf4XIzl10ZD86wDUIFzaqL4awpg/BAwNkxuQgPQIb8W4/PA6ukBgdXW7BacdAyksQ3qqRpyiihGYRgZmwDxAE35+CCm7njIx+hEoZk8CjQv9i3gdIzM6HtNc3QA3K9W20xmMjIyMs4MSdfnb24is3kG6oimtnZHAC370kYy94rHhuQmFlv2p/gl33wpyGgBSfJ1FS/vB6nB6+vsmSFpKzYBydhKNSsMwQPOi8dEVIX6FuBWMvxQtkuelQRI141fAu1SBhjqjTDwdOm4BFByB1J3JIpHQDLImo79OKaQ7cvj6y8C7TU53xWw91v9uRTngMmbWKkoH+JgOb/gTh0d2Fmel/IZMfFwMsohtnx+MfCgy+CBkSTetkLail2kxGOn3UkGidQUE95+qV1Rg8DBYguYXOKXXSd4U2BlbOudTCzsGCnIjoJM8tYuIiEsRrqhYHh/se5LYDrfyxT8umjys/qQbMH7i2u5Nkpyyl7tSwNCm34dRVZmMjIyMjI2QANlBuhv9qkkNLhxqOcjzUOSrhstTRXbcvMSRaTb77dJ4seIHeejxMgmU/2UH2q+aQJyo5WJ19V0MwemE9WChBiR5/JOtcWtvLFjtcM32PBdxNiXv2zFN+zQMFlaPyODDUdygxe/jDG9+qRzioIc8/Kp06+nHQEPfZt4dSDnLN4Rkq4da/sSC8lrYOX66vKa0wJtgS45s6U8B0wf5rbu2CHNWYJ4lHTYZrmFlI9DNVBc6IP/1CysZS+UTETG5/lxELd5u13ej6b9WoeUOmxkBEI54/KYKkyTq2JuhpSbBrd4fdxYpM4mVf503IGqbJrcPLz+SQm8P8nM/akXZWRkZHxF4ZiEn+Yomc1l1NgLgD+lD0y9aT6TdCj5mhUJkjbd2CHli8SBgVenYvsDvrFphw8GHh2KogBB2p8JgGcVqZOJ2KER0rOSEpEQEC2V+IV4ZKSsBNs/pjda3ZfOQLIzUR1kXEIxAdobd7iEBXDxz8kE68GN207E7wNRlfQ6yo2+KLksZiokk21Y8Lmr/6Xa5uvixvxYeY7XN4UoKIOXwsiYAsgwSUQmCVamXVPYJFd67MZJW/Y2qz/ThySFuWLlaEgodBCknfbt5BqGV27LW0nMwAo75vZqHT1AEYEItXaqKZHS99rQk6UzmICszGRkZGR8RcEPDJl3xLEy03D0wPDx9DP1N8AY5dOzfsoXAkSRCURY8A00aBS/EAXrkOY0AUw+tL1X26SpQQpdi6KGGCn3dHOkyc2hYQXIX5DSk6T4dku+ySelQ0oqtmTVpdzm9bsjUU6kfTgEXv/2b/WBdgAwfTswvsw35NUXNi+h2wZmbwau/AVuwfZr9o24qahAJZOHahvc+lyKZ0aW0VZryDk6DfUT86sV5cRaLiu5EVCcZ3I3vgJ0tRBFUTqM5eC5KOnHhag0RjrGqi1wCQ9Igzz5RESd8qy4lNvcYl1uA8UOj2voBiZuff+oYqcZMOU5/l2NwGnkhJX3IvGxF2PMmyN07RG8q7BFvicqSiiBXuE5btG6z5CVmYyMjIyXgmaqvFxEz+bY+uZLLHiHMpNf9UqIQstFKRwvSKbLHMl4mwy4kl1iR/xp3Ldc+tGBhZDgNKqZeKyv8c07es6VaedAfbsvp8QVlzCs62+OppAyCQHtmokEgGRgjh3vR30XREjjAaoLrD7YEd9kQytx/wQsn9wkMgBQP8dKRncbOPy/5UELXPhzwPZXA7O3STidlKdikNEKECJSicoylRECXqZyj8V7IqZdzWZxg5lFrpDrNkWagWQBzN7KpKWQNmo/mFNlpfunEJ9OK11jwYO7o+ikwlHt8jkokRld5JET1fneNK3lRy0fGTECJ1OwdEFNHwUmD2EzdFHeW0a8M+U5tNI1t+rW4sHSEhT1ZEavx3C/9yHu3yPLyMjIuF+grcFhWBK5C8jzp/BuyT4WNfGeWO6YMqOG0GafyZCdcrlBP/VT6G9oYQVoPgi0HCRlKC9jAtyU14lzMQFLmYeCrGOZqMWaSYWRkgwF8FBFAoxuL/SeEGP7kkn0THrWz8p8JDlONaWWE6CRJFs9flOyAZU8D500U26PJg/U105ep1gDCMDBH/QKVHlBCN66v6GbQpQNICUVE4lCEVndqCT7pdhistDNeeSAqkkaPGdnPE7BlOCQOfGuEAAzZjLkSqS29HIioXiS16LX37eA6VjxGu0C7Tn2x5AYePW4y3N8TYoJExmA3zcU+/TdU98vkG2F3iwNABtBd+jJky0G5ymt3TB9K7cG66nBXAP/xg9tbu8+w/17ZBkZGRn3G+429HFjOUlvDWtg+Sz6hNcTC8r3gTJDHhzhL1kw7YE8Z7jr6OjznAnTzrkMEZv+5gkZE6CloGKrb7uFHpMYXDvpdkKQ/UW+GQK8X+1+6Y5k8vV+78moLop/pJJtLtjgSlqqkqRgWFGAIMe14se6OZdh6n3pZNqTdWM/kqA8x4qLYv93B34ZC0zfzN+1PKTdSZorE6RsYkpuRdbrGzpWroqJKFktE4Bqh89HfUPUSZlqxNdIy4XWyrLSYeVGkvJbsIrjxvJYJX6dKPOewkA9Q18eLLeZVOk65U7/vjAFl9f0/Mopl8tSUJ628ct7yBTH1BN7+s+ThxFHPDCUjOs7srUlnNTrBPHToFeu7lNkMpORkfHgITT9J8fXGqfNP3rJdQJ/0l0+w4m57W0uHdU3jh33sTKTmm4pyA0qDoyYhlNl/ZJD0+obUrqoRZkQZabZZ7VFTaImshcleODoSWD5RQm0m4sBtxO1QXJtNNcl1tL5pInAkruC0Htm4JEGYcYaaXJ1lNTedl+ya8SrY2J/k4weiAsmO6FmBWPv9/pLU50Hpm89/fpWl6ULh/grtnxdvLwvyEq2y1RKPhIe58q+hBflPGJk4hIayVOpxEdTCHmbAXaLVRI35vMjyE3eSQlGzLNuxMuMLvQt0zqiQTueqi0mbM0Nvt6mEqWr4NyX6gJ6I3hEMgcby2qUHfO1MdK2r/kykG0oCU2pw+h/r3ahwydDItBsyI4k3VhD5dG4+7q0NMSDcZQZGRkZiijzagBg+sirs039xHzaH+6NkQEvl8wQsH4Rqe15SL66Q77ZbWx7qMyIqVfLRyRtwsYA9QETim4BHgkg24jEpaDugBUX8ryd7og/6UdRidoDUXT2JA5/W8jPin9OwwwJQOBuGnODS1rdEa/nl5zlouoHed4/SXkC6NUOL11RJvLzQXNvxKPR6QwkcOidtpMDwOhRLtOUF1i5GaLcZRUkatAbSSqwXAtLQLPofS8Wop7o2ALwRHHqejKEsveHGDUDV72CgwhA1i9mck6invlayI1h5URfMzeWVGUrxES6kiCvT+iA0aCcU0zEOK46Q0TyOFFkFYfEi2Qu8X6KEZKh2I56n4wSpARpwy5mAICQZkkxmQkUYI3t/THAA0NkgKzMZGRkPGhQQ+mrifqGKB2nlYMGBOZE6u4dECTankjyWRaD5+oBiTnFA9EtZRn0qhAFVlf0BhTq/jljAXgmMu1hPx8pSK4Mdfx8c51v4NqdREFIipR6ogdnnsjhRJl3FGTwoj9CGhHgJTMliJcGgQlMt+QyjObKpFbywU2RPNDe4muiZmJXsPFXYUomfHYCPP7/OHl9q3PgAZQjJnlRSkd6OSN6BcaMehLhRqwaaYcSwGSIwOdTbgk5IPEQyRynYotThaePSneRtEun8QaSKDy+JITJcCnKTYDpY3wupbRdk5SdYtg8juRXQd9GXV0ScmJAFFGHNag815MygM+t2ublqvMDImR5+8VEFJtq4xIGzSsyBnF0AcHIZGw3WE7J7QOAB4d2ZWRkZADYJBendIXc8+aovynFlm+gd9zfy/DMrG9wOac94O11gaP/hybgUMsnfvlk39wEzEN8U9QRAcVOT3piAx4IqPsXNcPItprDPm+kvi6Jt5UYQg0TkOaQt7d8BmnwYmxFPZGuIwO+OcbAhCR0fDM/Tp7CSnJlJMQNFmmiti14ezHyPjoxHrsJL3vr4zxCYfdrmEAWM95+N+hgOv8NMlRS/CeXvhm49Zv8nJsBo4f45GONFHIXa1Gr5LbmxnKO4OMpZqIgSQnNConBwENT7KD3K4mnRX0kbirdXI4JUDFhZSl2cu21lV1fI/XhjIFwKKRCMn60LbyY9R1WOl0bQD9jacGzo4zFvN5HHWpMiyl23MAz4xe8bHlekoIH/iCACc4piMP3tS2xF4GH3QQmBedhs0x1nyMrMxkZGQ8Y7pFcvOTmXsJ7k9SRKCMFXqLUtHqOb/RhhTSt+oSapMdNPHogBjHzStnGr7k9WdcLTe9NAfiGGYVghIaXJclz0XbtKIQHDvAyiDCsmEgECbFTZSWs+HntdCLP65kIjM7x76HDRraNBu8ZyE3ai7pT9WUq6pBakm3Jx7n6Eqs8t38LWP4xMP8kcPs3+3ObvIWvD7W8vnXAxa8Hxo+y8fjKtzIxNIWoLgXf/EON1FpsSVJ0x6yiqGk51qx6+DUTESuMkFper5hukmOd+q3JwfresyNgdEl+J3D7lOkJTyobGvbuVBdEpetEQdsTT4thX1IphGPYLZRINktltYQirvxqQIwj0nTycipE0p7c1ikIp6iM/Njw/DOZycjIyHhtsPFH+FUgM6cZcjd3yN+6A/abDBWEE9sK/HxYY4Ow+FU/LgAYkLBjBmDyvJ5fAV3D+2v3uSSTJiwbNs6i7D0p5Pt9+9XAFCo3w1DLWALLu+wORNHZ60kRQm/GRSG/NwA0/K7tDcPRS66K1KSc5LU4HYYI3pcRY6yWbJqXyt0BUF7qy1Ohle6gKYfinf+zfOM3FZMUa6XbSMhTCgd0ssyY1ZFCfDBWtqXhfVHNueiVDfWaUBSDbcs+p+qclG2mwOyqpPySKE6Wy1Ma0AfTK1Y6lRoaKqhEkNBn4AzKjCk40fdkZoOYWFZxyp3+34KTOUzHydhdEE/5ILBsl8fIXCYzGRkZGa8Nhn+E9Y95uz+I87/X7Q3IzGlKjyoxQZQIvzq5jKKb83LNnCdN6zGR546m48dNEamtFuDl02RmEhWlYfKxelZ8Jl1fOglCKKIHt157pMGTAJOd9dMyjVuSff0BNubukLQyRz0e25tOQeBgvboP53Ou97uQtF3bSW8cDbUYaAP6ELbAwyG7wTU4DdvvQYrWT+3dUoojw0TBiB9ldIXLQkoIki+k4uWddgFJngrJtlLaL6R9eswBftUWf5WXWO0hec3dhNfvllyyUfKieTTGyfmP+VoWOz2R0W6lGDg12I7YaN0e8vkahw3DbZpqjn6auTlGZnQZJVyjHS5bbb+jz6cBepJ2BwTxh02LadrnsltiPRxA+gBRhOyZycjIeLCwQWYiZ6+snucbzdZb7t1DM5xBc6rSQy/x/CnbIikxhZV4XwblGWMH6pKYZNNQxgZpUKTmwzS3uGSipl3fgc2dI75B26pf1ouhVw01Ycn+m3pf1BRJ/CVpS+4OeVkNwGtucQnIqFdHumiMTOIG2HcC4mwZzUzRVm1TsGpkHfj2Yvh4108xwVCYktuQuwWXt2Z/gmcG2REPrjRSMqnOi89Fz1nGHkyu8sTuciKzkYjPa3xR/DyRyy4AUv5LjKwU6WtkJVXXjURVqZDatynyOsWYCU5suFQUNX/HMNFRf8noPD+vk64BeR+6Xq2y6rvR9F5RbcptbLTfp9C9wftuQyGRMDzNmjEjVmS0i2l8hd97QyPvaW9V+Xc0KSeIBChFb32DSamZOv1+99Z7KG2J7dH2Xbd7VnhwaFdGRkYGsElm2gMufQB9CeSet/dSysyQPBHu6pnRDJX6Fm/XiulVSUkiO9LtEzXRV/4Up4C72JecYge0i76s49fcfdTekpvp4JO7Zs/oNhKxW3E5aThYMjQyiFK8NWEh+Sc3eZvdQnw7hzIO4YgJDQVWf7oVsNHe65Bawq2Et4U1sPrcJpEBuFy089XA7O3A1ruB6ePA+BEpv0h5TG/YhbRHOxmFYIiJg7ZCOxknQB5peKMJTBKM4dTdQn7WbJliS8pXEykNTfmx8qIoNhPOlim2uPQ0eUgmYUc+piD+I30rlNu8n3JrcxaXk9lQmp6srzHA5zR7y2aui5aohjimzJCqPsfTffV3nQj+ElDPjDUW29W5/hBO+SzQhha1r3HUHiVFRx8/rVx1FshkJiMj4wHDsT+eQ//Jy22dVvjly/PMDFuk0zTk0w6t7Q2jgHyyP98fc1j021FFKdYD0kH9siQR+p0oImGJ1IaNUpJ3OykbNYCdcTnKi7rjxnLzloyTKOUkjfkPYvK1I95XjJI5s5CJ2weinMg19Ss2KZOUsmILxBUTh6DhcDrHaAS4LWDxR3y9hhg/zsqKjkKwMhIAhtfhCznw4UyFeGib8ZjVrtF5KSPp8MRWSmxSJjMOQMXtzdopZApukx5dYo9MNWM1Z3SOE4dH53kdA1Z9qovA5DFg991IapeR1vNhBotT5SwOUpQlcVnN1AQJ0huoMKPzxxSYYyQF4GPdUGYMTqqP93YrVwISy3OwxRZctYOtiq99PCWMkgbH2Ip3q/Y1bq1u4fbqJUqHrxMymcnIyHhwcJoysuH9uMdPie0xM++pJEXKKhTZMFvfvDNp0puXlY4eOxmUkNaibEjX0eJLXFLZ8PqociLmVETxeIBv1pqnEla9KTd4ma8keTZKjpLxVDwrVpQOUtWnE3VBboxWFIJYc4fR/n8Dnvt/SWdUx4/HIyFBojYE4tZhDYDT5GEQcPgHA4+MBbb/FDB7H0+4tpUQFTW7ht73Yor+d1RMMtyUvSdpercoQQBQynRoK+UmLUUZJ96aC/KYrFedlzwV6YSyYz4+HU1gjCQBO6AcyQwmmXGlM6l0RpVifHnw/hHS5WXWU2j5vMptoLiARJg1Xfc4eTnRhWQ3yYy2iwPwtmSFxd69pHQcSmZsMYUZnQeMQSHkLJ7y3qYBydd1Vx0XprovRw19DZDJTEZGxoODU8tAof8+zMh4KYSWTZZaGgJOLyGlFlnfH8NpoxSIABLC4SruhNGpydHL1O3I6kYngxNVzeg3MlCBJLTOzrjE0i1kTtJK2p0XcnOXYwodez80e8eAr0dzwN9twQqCMTJraYk0hdtO+LshzqHxB3KNVsCt30IqfXQte1ys+EwMAH8dOPjvfI7GcTnqxn/eDMGbvk3SZ60kDQ/SeGPXm3E1dZfEH1POkDqCCiEUxVT4mR6/jB0ohLwZ8doUY2B8gX83Osk69jf+cipzkBw/Z2VydjERYlX2JSItZQHyWBSyM5PBkBfkGpFsY1CeKqYy/XqXCWV6Dwsp0ZJXyoM5hdxskJkCJIm9t7oWt73fNP6+DGipyA6Ik/4c1Tg8UJ6Gygydql6ePTKZycjIeIAwaGWWWPY+pAxCGF4mls9wqWf9Qr+tU/9Qiwk2eRlo0/sSGiRz7tBcaytRaMAkwa96f4yfox88SIMbh5CZFOrW8bZCYNWj2RcVpBVVyfdDJ/2C/TSu6LebOp0kzM2K3wQVYHyfRuxGTGhiC9TPbZ5+c5OJU+ykrCQdOL7lwY9+DjTPA3u/zfuf/8GmR8YUwM47hQzINZlcleMomAASMXGyUsaptkUFGbFpF5aVGR3wOBz1oMRSRw+U57g0U13qPUum7K9HIYRu8ggva6XEZUfsddJBkUYyW6IXMlT16g2fGG9j8igTnEISgasL/LR1PRHRUQVA/91JS7kx/SwnACfaofW9bkrAVCA3ARnD5R5jEN0ILY6t8xJQdcUN9qVkxrtZn8tzbPnjPyv86zUn7S7IZCYjI+PBQUqhdX0GSHuLW7N5gZe/rU7aY9ujgbR/B2Vm6GUZkpn1DZ5ivfxiP8Ea2FQdwoq/4JC6mTSsTglNmoIcJVMmsHKC2H+lgY+iAAGsxtQvyODJ66IySSw+RT7Hbr8vMWm3jrW8HaNqxRaADlh+/vRr0M0BBB5j4KXUFFa9Bwjg12HxR8Dij/vHinPApb8gakbL+yqmwNZ7BiZVhzTDClHyY2T4Iggpb6WYIHlWnJSjNKCOZFhmuQ2Mz/Xr2zFS95NxrGAUMzbeji6yemMcK0FOxhDo4Mhiq39dtPQ0uoCUcKyDHJ0qOjtMwsYPyTquP16AyVW1y2bnSkYbaGlviOPGXgBN6HDdRyyFnEUAXegJY3ePJtyh+VeRlBnIdRx0Mg3VGFVphqRm0Q7eB2eE3JqdkZHxAGEo0UOi8n2vRLxUOu8QxvbLp6CyO3hmhtuO0s0DsOdFSw4AUju2LTj0rpvzDT1Kmi3Ew+KXfLOIQmisjAxQ0kSeSUN31MfdRy9lNAtu+dXOppbXrW/wzTtGoJAxBt1hn4uTuoFK3odmuKAAaM7bPvxsOmtfXUXRvijX+Tabc8MaWF0D7DaX6I6nJ+890f+89Q5g93183YotviaaaePEfwKd2I3+WFAhGIsWFSoQXNdI2W4LCJcAt80k0o75OlTbQC1jFOyIr5eG35Wy3/FF4Nz72B9U7EhnEsl1lHlMTjJs3ITX9+J16Q8Q6X1HQrKMlXRf6VjToL7xpZ6M6XvDjeV9ccidW9PHNwhD/74c3pZ5v7dXtxEoYN7MMSknIKKNBN977ShKyow9qcwQCEQEMzAZD8tMuu5QjQmnzjR7fZHJTEZGxoOD4XwgUoVE/9BK2eGl5jVR5InWKRvFsMLBT55cXg23inZfPBw7m0oREXcBRQCQnBn1gxQ7QPMcE5JuzuWo4Qwg9XFEJRdSXlo9zx4TihKoVwsB8twJYx2XsAis6IxKDrVzU74eaj71MlbBgH0iQyNwIfu+8Z/7c3RbaCZvBahF0e2xPwVCGP2KFZrV03e+xnYC7LyXz8dV3BlkJTHXasmnYIVHM210Cvf4IuquhXczdDFiJ66RwvJgAbQADBOrcku8M9LJpMZnN5Z9lrwf66RTyXJ5DeBlrXYPRfD4Bos0sFJNxhqOp+toyF19iz0xMKwatbIYYaC0HXsvuhHQiqqj1/3EtRuE3SlxOEYalXAovlwyYwZt4EOVJlLcKEEdNwAT0UuWnl5v5DJTRkbG2aNbMMF4qRTfjUnRJAZO8KfzGJg81C9yyedOSCZh7VIatkOfQmbqm5xn0+xLIu9a/DFSptKf/Rp9G7Id+FYgN6jIya+6vE7SpnZAZlqw0Vh8HHp8mvxLMu/IWj58WwoBikjTuXUoYrfibcUWfTu56f051vXlsOUXBydsQNO3gIxBN3m8f7jbl2PqgPUtYP1sWp7nKQ2w9XYuJxUVh7jZkaTr7ojBdgag4esEIyWeyOqIncCbAtFWiFb8JiQERs3Uek2plWRm8TWZUiZHOyFKer5yPTfGRmDgqZmIYiWlI0gujBOvzPBmXWz3r2t5nktH5S5Sd5V6gCj2nVXVLh97SlbGSW9MuvwniTgde18SUXqnka3umUzo9oYEBug9NMe3N/ydQCc8MpnMZGRkZABMMLT1+a44psy4ERsV7Zh9I80tvtmlJN27QJN2ATHuarcSnVyOIpdxNPclSju0ej0oAt2e5KYA6U9raluV46WWy0Bx3Yf92YLVmvIcr6+ZKFZKMqrwhFbOC7Ifx+3YhmSQZCfHIqF1Q4Nxsc3ERQPv9DlXMgk6/Ex/vuNHQWYEQxFhdAWkn979oeyjA5Z/1F+76hKw+9XA5E2sSBQ7wNZXybWDlFcqPobiHF9DQ2KsBVKbsxsxEbElLAiILQjSuhw7UTu0PCXvgSDBgjpbylbA7FHZt6h0gyC6YBy6IKU9foSvYzmVMQRW2sBLJl52JEm6g1vl6MKAcFBvHlfFxq+59FRu8WPTx/m7mr/T+/Llm3aPdxARCKE8x2bgcvfeyYxszxwjTsk3c2x7x1Wg1Np9h+XPApnMZGRk3Ad4mX8Mo2eVpFvwOkEyVYbD+3Qg47DlWhGafjp1lLlCYcHdQKrmdAsmVfrp2q9EhTF8U232uQvq6HOSuOvFzCotxASwEuL5K6g3BUjDILujfr6RX7MqFVsujRB4XySdMKrG6Cd+HWqo+SKh5kRgPX9ISSZI3cMW0mFjeX/tvnQlyfHc/p3+5j56GBg/jmgqgDxisYU4EXIQ13IMAVgPOp6qi9wRtPMu4PK3Apf+POe4mLInZjBMDkrNeyFRyEhIConX5aL4TkYARZDTwYnSLaZKDqTk5LRkRQBk7lExZd+K7jN1lXncbhbYb4/Q6fyh2PFybszlOZ2+XZ5jAjK6jKSQKUxPjjYyjtxY3ouelbNiCxsheBT79ypwul/mDjhOFhrfIBoLKncB416VMhNwZ3KyocwMSkyaTXO87HUWyJ6ZjIyM+wCDG8bdPC/dXG7eayEbOmdHMkqAgcJyiimxvgWsnhPFQCYp+wZ9CQDciuzG7JMxJROPsOJ9tXsyPXuPiUGxxe252l7brZBatEMA6BDAlXRu62aBGhV2YwcbpPPJL5nMFBOkWUiI4GA6L0ZbAN1ayh4lE500ZHKgNFDgkpsSKhguhaS4/8D7aqQ7af4ppM4oADj3tUB7C2QqEBlQMYXfeQ+ckhe/Yu+Ln8t1H4kXZsJErJjy6zK+IqSx68taXtQOArC+yceTpkaXPOzRsFJiUICKGaKbgmBhohiiU2lG3iN2CtgVUD3EmS+TS0KiZvLaPIwWBkfzz2EWa5AZw8Cg8zXKaheYPMzXu9jh44zin0nDLM/JgM3AP8dOJnAf736jY8RFfTlC5DBYfKNUegcYs6EQ0rGfNbCu3+y9EYk7lZn093Ds385xf8ywtdsai0gRPnqUmn58BsjKTEZGxv2Fu33K1LKNDmvUjBlruZ0UGJCZU7ZDmpq76ksd/AR/4g5Nvw+ivtVaBwtqx1F3yPtZXwOOnpIJ2R1SsF6MgJHSUDfnzhgAdXsLPgY0fsXqSAyS7BvET9Py8RnxWljJImnmMiepATASFcb3qkSM6I2noVcK3ESuzUyUA4nVDzXn66TzA5OJogLcGNFZwFqQGcFvvaNfJs1uErgdMUPPuCW5PM/+EVsB6kmyEyZfrmKSUc4Avw9oaJwbSzvzoN3ZVjC2gLEOZAsph3VcKtORALGTkpoE+FXSxaTlHsMlqkXwCBRx0DXSAWVgtDRVbAGzN8lwRlHiEjEw/etAkdedPIKUV6Pvm433mpAtfV8Zi425SWq85jftyfdnQk+ATlNJNHV3Itk096qK3GuZ6bhnZhi6p+rMWWfNZDKTkZFxH2D4x/geyEzq8rBc6hhdwEag3ca6ErCmAW3L57nEY2zvVYkyCbmds/qzvt6v38on9G4heStLKU15oLkh84qGnVWRu48osHl2I9k3sHITZVAkiVk1dHIsFZddiqmUug44x8UYwPj+mI2UvtxISi5iHtZWZwPZTsXPGw1yA5/DEDvv5WMqRohRjMd2hG76J3pFJB7Llim25dqDFSNXiTnZ8rG7kZT0WiYDRSX+phUTNzfmbThJ0rUGKKaIksZryPONujwnr7uRFGMLVp6ELJRbwOghJrSkWT/8PqFiC2THCG6CKESHYtu/zyYPc+t2mjI96FxKJSU1/G7LdT1eIlKjt5qAVdkQspDIDHGg3/jy3ZUZzeAx9kTn0NCAW8kxD5WZEAMaPyCpp+CVlJmAzZyaTGYyMjIyAJzIh7mbMpNuEg79dGgIuZFP9cVUljm+ndiXWpoD6fwBqxSrZwANX+vmrFocfZ5TgnXicWzZLxMbpInTSloISFOu07Rq6Y5xMyBGkK2A0MH6pagklktcsWVVRn+GJAg7HTFQyD7FBGtkWjSJ50evn5d8G20zDx0AIRUYkpG1lKmUlDjg/J8T862Ut7Rd2RhWPSaPyfXvgCAlJhhWNhA5eBBRlKAxG2rh2PDrxAekSpNfM5EykrtSTKWdfJbKf9HJHCZYkFGTrXQXFTtsqgXQuAJBfTFK1JJnyg/Uug4xBgTpGls0h6g16C3NNbLchWU1zM8wOUmt5PoejH1JKb0f9fljZCYRFvkeNA9HW83vgHJXJnFfSq3QafdE8IGJg5Z1hs/fWN7A7fXtNBDyNNyxm8me7GYiohNlLCUuxhiUtkRpyxPber2RyUxGRsYZ45TuoVMXi5s3CQ2uM9pyeyfpf7B+CP3N3xi5sR4B9W320kTPCkx9Ezh8km8+WvoISgQcG1yTbycwsalvSnlBlAmIp2NyGai2EAGYuADpwEgrhGz1JS5btbfFUCxkJkjrcvLESFlNSUHo2MybgvpGvYhQ3wYQucQzvMza6dXt99ey3JFLV4EJGAHkYagEFRO+mpNHTr4edhD7H2vpWJohBc25Gas01vBXyqg5YE+RDmJ0QmiM5XOiCDKlEBuHGEO/vWIbAJ9vW0yw8gFHvuU033KHO7PKLTk+Nh/HUAMwIDjxVvNtb76+JcsJmaHAxuE050jaunXWkyb7qpEXBpTUNlVmbL8t3QbQKzYpFoCX60KHg/rgZOicMZLCWzCZGfwb8dEjUICB2TDg9i8z/1yryfkYIkUctUfw0cPIWIRn5s/gqb2nTk33Hf6srdtKZpxxmFUzXJ5dxqya4SyRyUxGRsbZ4gR5uUP9P/pBN07TT7zWZFnlMlrqafbY8KvkhQKSp0UD4AAhCEJWurmQg1ZKUi3SbB0QqxlGbmYxsJISZXl/xCF3FPmmZgx/UDcVEFqEbgWKBFe/IPsBk4CwFkVogTSyQDunSELlVIUyho/XGf7rnXJn5NN+lHOMK5m3VEjGibCc+haPG1g/1V/X8oIoDSQ340oMz61UqwiYvvnk61Fe4O6jYotLRG7GyknyFImvBZYJgc5dsoUQlUpM2BO+vnq+FEWpKUAoQZBMHUP9dbEWIbK6EYsZMH1MTNstH0+1m7qJSDregingYwOAfTiGIqJeo+F7sRQfULmFnowUPSFBRIiEW/U+biyvCxHZ9MyE2KEO9aC8dHrn0q3VLay6FQ7qg1OfB7DRKWSNRRc6EAjOuo0yERFtkKI7dTjdXt3Gol1gXs9hjcWqXeHW6hbmzTyNJRiu28UOB+sDRIpJfWnEvF4Mr90Z4/45koyMjK9QvFxlJrDiYCsu9+gnam3t1c1Y26slxUxIioTV6egDdsHKCkJwuhUThe4IrK4E3s90JoZTKacEzwpBWCB1UEH2Rx2XizRdFwCkhZziEqZrQMUMVF3gEQFB9hWjEKiayYzbAmgFBDkOneUEA5TS/m1HQtyEWGnujZPkWy9DJNt94PlfBuprJ69pcY69Jimgj0srZEcwsQNF+Zy//e5+GcX0TayqpNyVKIqRzo/SvBsjJMny9SKT/D4+AoWrOCfHGsBOQOUFnjdlxyA3ApUTJpBawtNDKKdAw/Omgqvg/Jr9QUQbpSMSZSYYi1UzR4g1tkc7iOUOYrkNImDZLlBah4kqZluPD7w5x96jFHDULhAAEEWsuhW2nSzn+JZ6a3ULBMK5YgfjUnxFm29m+T9/v1tJyEe/keuiSk1hi82RA9gccXCnEQOHDXuldN3hXKU2tHDWbaz7uVufw83VTUSKeHTnUTShQRc6VK66r8hMVmYyMjLOFic6MQZlonbeG3rbA0naPepLTunGRf16GmznFxKkt89G3dUNsA8EvE4MYvaVbcaal2v2hJhEVkraPSZE7T6vG9f8uypA0SOVgELbh+qFmm/cBIACom9h/BKuvcWeELsl3ViFlItE3WnnfJwate8mrLRoAF5oxW9SAbQeXC/P56DqRVgBy6eAz/+r04mMmwFb7wTg+1IaecBUIPGqGFoDzU3s2Sna7a9mMmLHwPb7pJVa83W2WAkpd7kEN7rIx2UKoBAlxlTyswdciXU0WMeIdfRM6ohHP1AhQyKNQZi+CVRMef1iymRFynCRiImhm8GnwLtRT4YlTI6Is2SCcTAUUbgRSsMKUogBB80hVt0C82aO9fI5eU+NxRCseTIDgk1BuomY3K39un8Pu9mGx6RR/9JxZSaRLX3Hn65GtqHFsl2m562xCBRAoKSSqDpzXJk53l6dHpdltGS09uuN/enxqBq09ms2FYcmEZ1AAdbYE91QZ4n7h1ZlZGR8heIOZMYv+y/jgPXzgAamtQd809TOEi0zaXttWLHSYkpRVaSjqJiJqXUis44kSK67JYbcui/zWEnUtRMmN1Z8MN1K1BuI+uF5O0ZD7jrwn1b18ngADqAGxh/AwMKungMmVwBMuVTV3QLiVfbwpFlQkqYbgnhJpOyFyCTBr6X01vGNN9q+lONrwN8G9n7n9Es+ehiYvVUUoJavCwUmDNVFoLkBCgEm1LDdISis0FYXUW2/T+Y++f6Gb0usKaIwJUrqmNSEmstmyZiryg2n4kazRGsCjJuiQYVJoSqIRzQOlPwqBEIF0CG/Dq5iggop7BgDKrcRJleRCKCOESgmOFhJG7kpQUZu7nacvC2RItqYMo6xbJeYTAak2MqxE/G1tgWaboVABCPvOx89QvRcYDIOTUp9Rm/yPX7TL3dPf10GiBRxa8W+HgJxpgssmtigdL3h1hiTCNRLzUs6rvIAm2RGlynEq2NhE6lxxqGwhZxvuK9UGSArMxkZGWeOO5SZhsP1KAwSY8W/oiMQtMyks3so9CUlDdhL26XB8mICJg+EyObUsBBvhCggfiXKTAu4bcCM+nk9OuQy1H3UvxpAJeOE91VJy/caCAGGpP0axMfWzqW8dcglmrCWsQ6RSVRskIZq6kwm8kxcQg1ujZ6AW7YJqavq8I+OXWfDy07fAYwfFr8KmMBECCnizJio3d2x4+MlvRlbIVVS7hpdwro6j9qMcNQtemWoOwIg6pAZyfqUDLXr9gAGxMJVKfk3YGMzyXJkuEQVi+2eKLpJ6lAKqldYhwjxDEHMxrbCXrPAM/MvwgePw65GJypJUYxhBzOIKLVgi8qRSIASESklSqL0qj1knmpLWCEpUVQQAnDQHKUrnpSZ4a1W2s5fCsfLREpgAgVEiifaqk8b/ng8f6YL3UZ6b+3rjZbqSDHtV8PxInry44xjpYbuPzJzfx1NRkbGGx9aRqnOn/68X7HqcrzmHzUkT1tw173JVRWbZPQ1vZlXJxTrPCINjiPwtqSDBnbKN8tim5dZPcdlHzsFsAaKEqxIFIOEYCs3OWLSYcSMDMc3LFdKW3UNIMAqMfBLVnjaBZeYyi1uF7fSrURtf+zauh08gD6an4dMDhKQYwugEGLVAPXz/bV75H/kbbYrUTaE1LkxXxfrmCi5Mchx2Y5MKTd5yzFztkJKFXYTJimjc6BuAWMN85UoCsawY0w9PNLGHhERZHYUVbsgO5KU4gYoz4PSBOsKMOpokrEORnw3xqKzW5j7PQBTXFa1St4D62IbdQQMBdRdjYFWgsIWsKLgEDE5jtV52OYm37hTx5yQBSfXVq51CDz0cnt0DkvJc4nyXg3ELfhG2uI9LNrQotpQZvqy0BBEtFG2OU5MnHFw1iHGCLKnlJmOKTMATqTyEiiREwCou77jqXJV8szoskFHfgicdWhDCwNuyb6fkJWZjIw3MkI9aAe9C2LovR6vJShK6Wjdk5XT0kuDpLturCuKg5WI+FjzNqxOO1aDqtxQ/ZwJh8ro0SfjKXTYIUx/jcKSyVJshSiJryEcyafzqr9hugmXCoi4pKPBd1E6k6yUiGzVe2rCEibU3CIcG1GP1kxU1tel3CShd1YIl06Mpsh/rb10O4WWM3D8oZhtQ59LEyNw9EWku9DVvwRMH2FzbimJwlaIihlLt5PkvJhC1uIyjzUlyJZA9DBROqco8LUpt/pwNwJMLSQVQV5bMRQXJe8bAGIDb4BY7IKKKWJ5jq9Ttc3ktpyARldBdgoqeNu+PeC29VizAdsQYEc4sjM00zdh7SZ8E9f3AQi1KCKGAjw8tscXcHEqLdcGMHLDDiRt8MYBpuDfh0GMAGBKePKIoQbFAB+ZzIyKKRMKIiFgEB/PFmy5i3J8BTBGDLaDW21Sc+4eTKe/ExFm5QzWWDYAI250Fun348oM0HcdKYg2O6M89eF7pS2TuXe4Pd1moIDrR9y9RSCMHL+mB/UB9tZ7Zz6bKZOZjIw3KmLgckU772/od4I/ZDJT35B8k9cIG6ZE/cOr5slx/1RoTpKcIGUd7TAJNZJ/xADQEgFRP5FaSzck3Usk/hUjxlwlFaps+IUEmzl+Lnbi+5AMFxArBpCsGWPl2sq5dKK4hFoIQymlFy4PmdiCKILI8A2ePP8VjrUoSdoJpdfK8DZjLTxhASyeBG58jP0wR5/hdUa7kktimcCtnuyv28VvFO9HAfjQk8RiC6w0jYDpBY70d2OQsewrIYK1BrHcBVkDg7Yvd6nx2o75HK2FgQfVt+T9o3H+QhxtJUGDNQIc4vQhhPHDQHUecXwFHlE8KTPEYgKqtmDdBCY2MO1cXtsgXiKDaAxiOUMsd1hZiVG8PPweSCUWCuiCh7MjGBjsjHb4HSfvrRCYzDAhEB9NSplm0hHgcGt1CzcX1xBTWJyDtU6UFNooM8EYmHKHVUNw3kvcKKX2SsoQx4PulER0scOknMAai8pViUyoIjNM7VXTr5aAjpeqhh1P2uYN8FgENQRfW1zDUXOUlh2OPiBDaZRCG9o0J6r29UZX1Fkgk5mMjPsZfi037S8H8Q4/n4IhgXk5Ss6XiyGZOZ6eaox8ugag84XCUm5gkDJK5Gj70KKfCl2JJ2OgzHDvMhO6INk0oEHpxvO8o3aPzcSr5/uuJwo8c6hbMFmxMgbAzZhQ2UK6ZqR8ZKLc0CeizrTcdl3fZLWhucmlnW4FE45gQououSpuJkTJCpFRVUD8PwATGUP8/OEneThkc6O/dovPsBqjStLq2f4aF9JdpN1PADg9Wbatc4fMhPdnJxwyZx3fsI0FSRBehANZ15f1RpeA0Tme3kwW1h9KQJ14loyU2oiYZPkjPt7RZT4uAIAFEdD5FoDndutyC7G6AKOvK3Wcnqw5NDAIUV5fuaEHCoNyI+skMYZEG4wrsF1tY1yM+2sAIKC/sSe1Jg5fA6AVUkmIiKHBollgJR8ODE4hM+Ab/6TsAwvbsKkytqHF0cBbA3BJaF7P0+9KZrScMypGXGbSUQRmk8wECom8KJk5rtQc98wctXwMzrqNdZbdMvln0v6IjcaqyHjyGx1TZ93ZlMlMRsb9Cop8E272Ti/FvOT6w2yMlyAzw1bROwR8vSo4TmZCPfDGmF51idJmHBq+Q4Ra2qVFrYCUVtT3oh1ANCAyEF9NfZ0nRde3WX0y4qeprwGLp2VGkeHtt3P+3RoZOSDjA7QbJ6578y6mfHP1K6A5BLo9OZ+2J4fkeaZSbIG4BqEUZUQUEiVLsJy1En0/j8lYKcmt+Bz9HMAp74PYAHtPMHl64X8HVp/vn9t5D5dxYseva7Xdq1iG+JycdCVV24AbsSGWiAnb5K2gcpv3X86YVNgZH2/BSgiR4VJYbBBIFJKUz+JEabKSCFyC3BSxnMEYByq2EEfnhQRyCZHMCHAVnKv4lTYW0W2JH8mDYHHYLNBR4I4icKnD63uIIkK7gJGuJ2MsyFgOmZMbLpVbgHFoHZuJnXFw5jgBGNycxQRcd0dY+zXWHastWmY6ag7RxjYpMAYG03KaiEYnBMmTRxO5S+mgPjiRL6PkIFJMCb66jcPmEHvrvRMvvz6/aBc4qA+w7taJAB1Xf5Ytf1DRbiVVU7arbVyaXeJroZ4ZomQ25utocNgcJvPxsAQFAFvV1oljez2RyUxGxv2KoX/lpcjIqaA7/HwKNj5VfTn7epkYnkc7Z6ImNx2oiRcA3+wj0k2zk8yYbol+fIF84o+eyUkn5laSrhnyrLxo3gwFYH0DWN/kJNz6FhOAdsn7SYnAkiFCXjqmZIp1t0Ca/wMxA4eaPTP1C+xd8StpC1efjvhHiDtmjAGbgCEZOqouUZAuHPG0hDWTr9hIiamWgD3B+Q8Al7+j/335BeDF/2PzWtsKePP3SPeV43Z0I2UyW8i+Iptvq20O0LPsmSFjQOUORuNdGFNxeJ2pmGgUFc9rGng/DBmQcfB+ycQtdetwuzXshNcZXUIstkB2hjB9DCgqJhvUB+JxNI+BsQXfoOyIDby2AmKNRagx75aY13MUUppsY4uF59ET5GuYcAiSLjZjHBrf4qA+6H0oxQxxdBleyJA1Fva4mjE4P5Kf205UQmMRYpQbP8EQcFQfpbeQkqZZOeu3Ucxwsz7Ec6uD1EodYkDlKlyYXJB/Abze3novlXO09dpHj8Y3JwiQko/nD5/Hslti3szvqMxoG/a0mHKLdeCupGk5TYqLob4MFmJIJbna11i2S+zX+zBmk8xUrsJZI5OZjIz7FaeWZO5l/Xj6z6cuew8qzr0eQ/BMGpq9zfPQrJawZqIASNmDpMtnjx8PtXhf2l5h0LZqOwIgptR2nwlCdwDUe5KI23IZya+4RBSWwOJLXFJqpf05KT2tGHIXErq35mPzLZeS7LgvCVn0fhB4Vlm09Ts0TEyA/lgtQMaBjOM/upFA0fcKhoG0gkuuTrdm8lK/KCWxwfTu7fcA576aRwmUl06/7uUF4NH/ERidF47Ibc8wY54/VG2zIkRyHm5bOpoqRL+CgYVxDtYvcQEtTFjDmBJkubsJhQyJVJ+OdDwFU3BmTYy8TLnFJM96Lg8WlWxDWuyjZ94IKf3ZSuPh+KJIq/cSQFuM4WHRhRaRgI46wBjsrfewalZotaNI9JH+Ru5w0MxBICwafZ9t+laMMYnMhKFSqNtJ6si+LG/hJThOy5rGmPSR4bg5N1BAkORnJmtsxF20C6y79Qny0fgGq26FEAOccSnzZdhuTWC/imbHaLIvH/nJjimi3u8yKkbJY6PGYiVF3BBG6XlViza8OoSNNu6zHjIJ5NbsjIz7F8dzVu59A3f4+SWWfblkhqL4PkZ3XqYRUqED+9xoUAqSfRLxcqNzXPLo9rnDp74u05I1DE1KTKaUMox0r0TJgwGYzFRbfPPXtFz1zkAICgUmNFFMutYyWYnE3+FlOWn9phaIBrABcDaVHFghsr2Xg7yoMFK+AfimHjogWhAcDCyCncLYArEYw8WaSYbOaIpKiGoAY4BqUZcOZJ8FMH0L78MEoLrMgXtDbL+HH9cxAJEQjYExE5hyBrRj9NOdI+/XQDrDxqxuwMDYCUAdDAUxZxv2zxjp1CpkphIFkDVcqTMFn7sBAH29V0AMIJQwcIjEgXuzcgQKNRYwiE5TfrekXdrAwKBwI3TRI8LgkCysb4BqikgdgArz5ohNqH6FQAZUbMP7Q8COQdI2fejXGLvRxg2XRH1g4zDf/M0JNWPYdSRt0GoABiszlXPcrQ6CMXajzAT0qkmI7Gc5bA5xe3kbV7evovY1DptDlLbEYzuP8XGBEGPE9SWT18pVmJZTJh3W4mh9lFqrD+tDePJofYsmNImYnRufSz8PlZlArLIYGJSOO5dC7JN8h63eSrZ88CAilK5MjxmY1FE1TCY+a5z9EWRkZJyODePvKywzfTnKjM71uZMhuNljw+zdOqViO/B9yO/tbVYcKPCNdP0CG1rX1/nmGFqk7JbukI8hSHszItchtFvJ6qd76WTSrpjUcSMeFRORAvbCmgkKyZBIVzGJKKdIXhtETt4tdplQOQt0DT8ms5aSIVkHUmpJiFpZDuCunghYwyMMjIExXHqi6FkRKSZAV4vqJK3hccUqkT/gkQSK8SNMOlpJJHYToLyCFCi38zVAdYlLMl0D1PsIYYnDdolDkmvqJmKalps0db1Hxo0AN0MYnRcvDwGm5NIDtSB/NCAzuxj6nAglYEZYa6u6dVIiizhsDnDQLbmL3EqZyxjxvBCiLfi4hQ6QrWBgMS2mgDEIxQwgA3ITxEjwdgyeT1SmyiQJQYzFLmBM8oW0ETDiIUmeGV1noMw4WSaZWs1JZWZYgoogFClXiG/yx8tM2iGkysmXDr6Eg4ZbmXVMgS6rBGje9Cbg7Wo7ra8KTRTzdi1/H47aI1w7upZUknExTuc19MyosuKsSzOeImJSZgDg0uSSnAeXwZKS40YYFaOeJMW4oRIdD/A7C5wpmfnwhz+Mr/3ar8X29jauXLmC7/7u78bnPve5jWWuX7+O7/u+78MjjzyC6XSKv/yX/zKefPLJO2wxI+MNhNOUmei5BPJy1JMNgnIPygxIVA3JaGnnp68iiaip2+hO+09dKOgj+Knrtx0aMfrGvtwUm355v+KWcU38DdIVo2WmWAPLZ4H1NelcOuTrpepA6jQS5aVbSJeUHJet+jJMMQUbimUgpU551jJIDADJTVrPj2ouC2kYoAGAwNOXg7R3gxDdmAPiYLijSdUV9bQAsrxco7Bij8/qabmgBhg9ClCDVB6zDpg8Clz6FuDKd/LQx046ikThaf0aMAUiDF8PW3InknHA5JIEANZ8HcpzzE80mFD9R+U20q3RaWllUCajyCF7Fqi7NdZBn7OAIQTfgGDQuArRbYFnC5UwUqbpokywRuTLWkyB8RXY0UWE0SVEstBut1DsIBYzIQMGu6Nd7vKB2SiLOFuiIStGbs4mGmayAD1xMTAoy20AJrUcK0saEoI+o6VAkKyXacnvLRosaY2Fjz61PgdiVcbAYN2tQUR4YfECbixvYH+9jza0sMbi2tE1PHn7ybSN0pVJUXGG5yK1ocVOtZOI1apboQ0t1n59orw0VGY0VE+TfNXzMiQzGrAXwSWklXiE1IxM6TxpQ5k5604m4IzJzG/8xm/gB37gB/DEE0/g13/91+G9x3d8x3dgueRPgkSE7/7u78YXvvAF/Mqv/Ao++clP4s1vfjP+4l/8i2mZjIw3JDRBNf2uOSaSB9PcOn29zY0Mfn4p8nNsX+tr3AGUCMmxML2XQ5QoDlQeIHUvpedaSfDVcDppQycSQiL7pMBqjl8KSTE8mdqWfKNdXWPCox1NfsHPq2pAMvF6dEU6j+b9sTkplZRbQLXDKoxVr4aT0o9HHQNiXAEQ/wzA2ycHhCgelxUrMiQnbCcyRZlAsDBUAq6CMQUAj+hKViPcRMoxYjgOragqN4D57/XX021L+7WVDizItZPraix3Elk5NoANv0LMTKz5OVdxy/j4Cm8TQZKOKx5RAMNZM6ZI52msQxxdBU0e5tlNpuTrAylJUcDIOSZ7oUUTa1Zu3JRHDRhi4zAsSAifsSWbc9sa83aBw/YokQLAwpgCtuCW8oio2geIWtkOEGFY/WAbx4aPgyYPoXFTGBkxQZI1A/Q3+RgjjpojzJs5qmIEa7mc4slj7Wvsr/c5cZcils0SCyHb1jju3AIw0sRk6smMgcGN5Q0cNAdpXECkCGt5HEEXOrShTYTgoD5AoIBbq1tYdAvcXt1OAXd1VyNQgDEGB/UBbte3uWVefC0GBj5yuWm/3sf+en/zn+GA2Axbt9VrY+Q/AKnji4hQ+xqNb1D7GvN6jmW3TOfWeiZ8qhLdDzhTz8zHPvaxjd9/5md+BleuXMHv//7v45u/+Zvx5JNP4oknnsAf/uEf4k/+yT8JAPjX//pf48qVK/j5n/95/P2///fP4rAzMl4HHCMISZkRxeJlJfXegzJzagpvzTc0UwqxGPy5ODX8TtDu87rF1uAYIq+jgW2J6KgXRjw0YYVUTpJWXfbmePBYAUiHUAeEkn/u5gAMG07r20wMwpLLMN0RE4T4BWD0p6UUtGIFJKXrFkizgYotpMnQ1ADmPNZ+gTVK+HofW1F8O6ET82vBxxtWbDQmybUJLft2nv8t4PAPQZPHgMnbQHYEGwmIAXb+GfHtnGNiJmZYVrxaYP3c4KIaoLws16mQ0lmFmgwoRky0xIYSaaSDMXLNmdCRcex5iJ6vlTHoh2rKuAE3YeJlCphSroUxsACCq0Cjt3BOTFjweRsgugrWE1BdkJb0DgRgFQjVdAYij2g5BTjCClkpYI0DlVtYt4eAm8KHBpECIkm32ugcDDU8mBL7iAQ4AhAbUCE3c7AZ18Kio4hox4i0QiSDFw5fQBMajNwIFycXQdSmcLwudqn1uPENnHHw0cMax9mEFLBfzwFj0PiGrU8U0PoWl2aXQK5gZQ0D/Wbwb6gbDJvUx3VAY4gBdagRY4SxXA7bX++nTqP99T6bdX2H7dF2UmQKWyTfysqvMHIjMR0TmtDgqDnCxenFk6m/QgO1zGRhE5nR6dvDzBotMzW+wVHLreiTYoJ1u8Z2tc1en/YQ5yfnU5bOV3yZ6Tjmc5azL1zgNrWm4RdlPO6TQZ1zqKoKv/Vbv3XqNpqmweHh4cZXRsYDh+PkIsnF9/BPdmMb96DMDB9T0nTH48GAaIn51a/l+3KgzIT+S7eXWqCF2JB0AukfxtAizU3SOT9WlBYjLdl+wapCDFw+ii2famw47l+zX7pDSTcOQmCkFZoAOFFmZo8iTdSOjcwtahFRwvhDkF8iIkhJKDBhogD2xXTixRFD7eJJ4HM/Adz+HaA7hD38LKZ7v43R8kkYtBgf/j6qg98Dnv0F4PD3pYQlx05C/PygvDd5C9auQm0qvgaBlY4o6cYtdaxmaemHIpfNCAA6kJ0AxiLqbCNbiboSwSRVXrfgETUYT2dQyaWnlEUkJTwrfhE3Q5w8BDe+CCovADBo2xVaf4DDZtmH19kKvrqE4MagYoYuehw2SzRujGgLmBhwa30bc8k+McUWMH4Izo1B5OA1gwUGVTFCJ8qQsxrzbxHcFqKb4aaPuLZgH8nFyUVufXYT2PEl0OjSRoZK6g4iQqGG3RCSZ6YJDcg4LMlgXI5BRLBp7EP/L5JLL1K+Oj5XDByUp2WtxjesDhGrIbWv03Es2gWrNoi4sbiBeTPv26Cli2hRL3DYHKILHfbWewgxpGnaADYGUaoioyUvZx2a0ODm4ibqrk6+HkCM0IYNviu/QqSIwhTSum6x9EscNocIIXCruygzX/FlpiGICD/yIz+Cb/qmb8J73/teAMC73vUuvPnNb8aHPvQh7O/vo21bfOQjH8GLL76Ia9eunbqdD3/4w9jd3U1fjz/++Ot5GhkZrxLuoMwM/2jcyTdDkVWC4Se0e/LMDNZJvp3j+xqYhImYdGg4naJdSKJu3FxOz4cC0nwkbY8Gpc4Z+KXcmLX12aNXcgwrMLFlstLu9aWmYsSlHzKs7iTFY83bNxW4nRqsyJgRYCbgUdElUoeS3AyMHLeJHiF4UW0Ck4diJpdD9gPiYzj89InLWXR7KNdfwnjv/4tiSFT2f08ufxTlyvRpuQBodBWNrYAIdKEGuZGYlgPIcaszDwSMrMIYUWfcFAChbdcw1ILMSDqFSBS3QkpLU16nmADOILgZqJgCKAHjgdEOTHkeaV6UEiBTJA8QzBilHcO6CWe46GtqHCIFkOUwPg+eXYRihFXo0AGwUsrjdvYCjRABIz6XcTEGGaAV71EhJK1zU3hREpxxCGTQkYcvJph3S9jB7a10JXz0uFEf4qhdpZwUjevX3514Rw6ag8E/A8K8meOgnqfcFWuLQedSb7bVf0XHw+oAJkU+8L+nLnTJiKtQf4oSISP+nWW73BhjYGFRRx4fsL/aT91HpS3RdE3ahm573a1xfXk9nVNhC8zrOQIxIdH9Akh+GhDQ+S4ZhDWEbyy5PuqZ0c6qrMwM8IM/+IP4gz/4A/z8z/98eqwsS/zH//gf8cd//Me4cOECptMpPv7xj+M7v/M74dzpKaUf+tCHMJ/P09ezzz576nIZGfc3UluE/DogBGmRO5CZ7ki8Icd8NXczDZ9GdjQ35bTnSTp6mht9jguANMWZiBN2Q9MbhL3MfvKLXn1o9lkFMbZXdoxlI6pf9ypCiq4XMmMcUsdRfYvVEG3Tbm6zIpPanjtO1/UyiiDKKAT99GzlfGKjv3C2jMbYhxWrOQjc7usqUXsO5BqNmCCEWspLN46V4V4Gbn6MXy+KwPJJYP2F9FRTnEf0ami2aIX/RRgQHKIZCxFxQg71tZOOlbgGSTZMJM/Xzo3Qd26V6Ic0GlCxAyp3+sdCDROWMBT7jBgAgAO5AlRtA8bAVOdwbvdtTEZtkY4PsYOxJQgWXdTyooFx3NVkYwMXViA4DucTFcIY7nhicy8lKxIbi8XHYyxsuQtTTBGkVJS8JIOOosIWaXyAdgGpJ2VoBlYy0/j+g0Ak9tWQsclkW7iKrxXRgMwMSMzgn4t6TxrfJGWm9jVqX6MLHZ6dP5uUmBADIiJ2xjuwlgdBqklX26eNYc/KQXOA5xfPwxg2Phe24OwdOWY9/4P6YOOcnHFpneH1AJD2ESmiCawezcpZ2taknGBWzZJClLqZ7gNl5r7ImflH/+gf4Vd/9Vfxm7/5m3jsscc2nvszf+bP4FOf+hTm8znatsXly5fxdV/3dfjABz5w6rZGoxFGo7vkXmRkPAhILaCuV0dig42/kndUZvRGeux5Ipz6AeqOqg0N9nF8GWICQ3ITJ/3jLySlmwPdHhaB0JHBua0ZTLMnJEiGO3ZLNsmmsLi5JMvKnCBVKsigV1KkHBJrVg1Wz8mYgn02+IYVB/R1B0yCnAF7cFr28hQTViSKLQmJk9+NkTKRXLv2ZlKCIgWY7hAmrBBpxebiWPM1CLW8RlKSix5oB+rUpb8A2BJx77/C+s1ZPCew+Byw/S4ef6BX083QjS+hkNwRmJLnABVjRGsBW4JgpCOqZB9Pd8TvFWpZbKLAnUam4KRd2ys73K2l3VsBQAEyBcg4Mc4W4lHygC1AjgdQcmu1A6EAmQqWIu+/mAFuxv4cNwJcCepWQMHbDSDYqDfnAtYQrCiIZApQMQH5FoEA44r03ich8pNijIWccymhf7baBUVWCXzwSeRL2SmGFYfjREMHKXahS8pMUUyARkcjMAIFNKGBNQ6GDHbHu2iEUNHg3wh3aPf/Tub1HGu/TuWhLnJJqA0ttqotLLslQgi4OL2IeT3HtJxi0S0wK2bp3BrfoHIVjDHYrrZhjcWsnKENLVbNKpWVKlMh2p5cdLFD7Ws469J5D6dlq/cGQEr81ecKV6BtWtxa3cLIjlAVVTIgp9A8w6MZfPQwxmRlhojwgz/4g/ilX/ol/Jf/8l/w1re+9Y7L7u7u4vLly3jyySfxiU98At/1Xd/1Oh5pRsbrjeMVeUiC7ileleNIas7xJ+6kzJxCZmwhisZCWquPEyM1nAokOj4pLqEFKGJd78NTi0anU0P9NTX62UwtE4puIaUaVV+0I8cC0cpNyjHBiR2rNs2LQDhkgtTt8/E2t5lodQspN4niE46k9Tty62+5zftV8kXE7dQUWF3xS8B4UPQwfgHX3sTo6A+BZ/49dy8ZywqHKYUgjFgRUkzeJJkuY7QXPojF+T/PM4YAdOUFrM9/A7Dz1UivMXUnylP15W+DMSPACcHQTio7QTQOsdwS70pkEuimiYyAPEKIoCg+H1vJROySTbxWPEg63HOgxJEZwRrDXU8UYVzJ5SPtcDIFMLoAKrdBbgxSMlXMYGwBKncQbQkyJbwx4GS6gs21sYU1JcgUgLEw2llkKyZIRNARkTC9H0bbgj0M1rHFSILwtFzDhuCY/DAGrOpoN5HecI0xqVx0c3kTe+u9lJviqgugYhttsZ1eA/WaRNj0njQ6x0n0J3kwEYdIMRl6tU277liJiTFi3a15arUoKV3sULgCKymBAVx2WrQLRIqobAUYDtHTYZld7BIp2RnvpOONFLG33sNRe4R5Pe89QVoWG6gvcmE28mKssbixvIHD5hCLbsFZOkAyIhtj0jmsu3Xa5lnjTJWZH/iBH8DP/dzP4Vd+5Vewvb2NF1/kTzS7u7uYTNgl/Yu/+Iu4fPky3vSmN+HTn/40/vE//sf47u/+bnzHd3zH3TadkfFgo0/f2nzsZc1Q6i2JfUlmsM27YXQRafhjs4c0w6faPXZ8sSdT3RF/gp4+xvsMK76RxqCfXWHaQ+6AocjqSux4uei5zbjc6ZUNIgCBVRNYUWukPGFkqKQB31C1s0lPLUiQnV8g2gJkLsJZyRlpD4GKfRgwIymHSGeSFWOwGQPrW9JCTr2ZmAjV+jm+cYUFcO1XgPFDTGR23g24i1xGa3XsgAGqK+C5RDPAr0CWUF/+Njg3RltfR0EEzN4CTB4Grv+nEy9Fc+EbUZsxqrgn3hTxFBkHVLuI5UXEqoOLa54PZQCyJZYoYOwIMzdh9aacgGdJOd6OG3PnUXPAKlMxleBDfr9EW4LKbRgb+XVp5/I+siCUABp+X4wuy6tLPNdpdEHIUYUIg6ZrMLIWXo3DruLwuHofl2YVKuPgKaLtVvzpvzonRT5CJxOkz5WTpAjAAF3wmIcVDo1FgxI7Zid14ChBUS+MKgbH02kNDK4vrqMNbSI6nrg85YS0hWa10YUEOa7a7aKtzsNT5LIbkTSJy6sj6wznJ2nrtLZC++gxKkYobZkyZ4gIu6NdbFVbKXNGu5K0zBSI5zjx2zKmkhqAPvwOFiEGLNoFZtUMta8xo1k6foWzLqk6ug8nU9ItLA7WB1j5FbbKLexUO3DOcVt5DFh2S27/NsDN5U28uXrzfaHMnCmZ+emf/mkAwLd8y7dsPP4zP/Mz+L7v+z4AwLVr1/AjP/IjuH79Oh5++GH8nb/zd/DP/tk/e52PNCPj9Yb+4THcaaOKAgZesTt6YIaloWFZ6g5KzpA4aQrsSksl1CstG+uI2kEybJEGRMTXwOpFdO0SIIIJHuQaVk3MiG+i9YusshQDTw5Jym9zXcLjaiBwe2xSDYxl0uGXrETUNyWsznI5SpOD/RI1SnRjYKs8BxcWvI6VzBMrLeehZkUEE77WXrJuYg1YCwqePTPtIWwchgNG9gQBnIHz8F8B6meRWs/L86JuAbAEMgQTCLAj2GoHaPZBWsxwM2D6J4BV75NBeQFdscU3zRAxMlLWMZUYd8egcgaUI6AGIgjRWJAbwVc7cP4IPkYutZEFVVPAEEgVL1cB228HxueZ0Jj99LqSEGBbjsVz1EpDdYFopAOsmAHGIIYAQwGmGHP+jF8C1Xl0dgvWBpTlBaBbwQEoTYUVcVmm8R1KV2LezLEGgYLHpNhlMkPAQX2I8bTG7bDGJWdB1iGaAuu4ZgJqLJeHbO8jUTNvlIGVALA12sK58bmNt24bWtxe394oPekU6GGgXBc79qGELpGG280+Xlhc5336Ja6MJhtlJvWqeCmPHTaHICKsuzWTD0PoqMPWaAvrbo1ZOWOCQx57q72NjiNrbdq3Zr9UtkJAQOyiZO+wCoUIzKoZjGXiBANsgVXAcId/91vVFvbXbCBetAsUlruWal/z+YcOt8Nt/PtP/3u0ocX//Of+Z8yqGTrfMXEGJR/OV7wyQy/jk+IP/dAP4Yd+6Ideh6PJyLiPkCRgwzc7TcY9voy2TtthBgzx8s2BZKGMhMjcxWNDHZOL7nAzH0aPI9ab6ySj72AbiD2p8QtQd8BKhw7gCzWnx9a3JNQOHCpn2UzJHznZD5JMwlFanaMYcvU6NPusCIUVKyVum/dNETCcJhyLEWAKtKbgHJZQA3HCx1xNZDs3eOL11jt4VICTaxUjjwIYLWGbPdhwl4iHsASOngSO/qh/bPQQACd5LhKIF9nEa4ttkC1AvgPcFj+39W4u0yyf4jydrXeDzJinV6tTwZqejElZZUhuvbGwbibLgMs7kuVCxQ5AQEsFSuIpSXAF1h2vPyl4lAP5mq+hLWDcNjC+AKyf5xxBN4ZBBAJvl8kRlwWNBg8WU2zDYm//c9zRZEt4IjhrUI13QYFgADhbpNC56KaobQlf7KAEk1EvLb+RCAYWhgzmwaAkgOBQ2BLRr2FhN0YG6HTpSBGFK7BdbYPA5aR5M8e4GKcMmBDCRguzEhvNc/HRwxmHNrZpe0SENrQobIFSfDZG7mOHzQJNYAJlyCTTL8Almja0MDCYlTPMyhkPmHT877bxDY9UMA6ePAyZpLLoeRERqqJC7etkDNb5ScYZFK5AZSusWla6VJHqQpfyYACkHBkC4driGv7XT/6v+La3fhv+7vv/LibFBPv1PkIM8MHjj/f+GL/97G8DAH7yiZ/E//QN/1M/EoIoeXO+4pWZjIyMO2HgmUmR8UF+lz8cOmEZ4PKQDnwkLrMgLLnTaLYj+Sp3UGbqF9lEq7H+QW5oMbDPxE2AsL25jo4ykHRVznqJTIQa8Y1ED9jA/g3ujWaCFWsuLdkRQDMhM65fBwQU2wD2eB2dlk3gFuzRNq/TybiFrgWsECE4IK4570OnUle7WNfXAb/E2E5hRlvcttwdcg4Mgsw/IuDi18tH7Ja5VXcEE9Yo2pv9uc/+BD8/DLWbf6r/2W0Bk8f4/MpdMTjzCALTHcK2ezCGeHoyRTbaVjMgPMTn7XaB8XkQShhfizIFcDu0lTEIFhES9EcOsA7BclquiTVATCAjRW4ltw6BHApq4DFDKTfChW9hQoeqmEmeC3d8kUbctwes0hTnEYuSzclxzdevvIDobyCWO/37wViePi3H3EUjZRiLabmDzhiQnaPxDWgwL2labWN79hC65TPp3W+MgQ5Rur66if3lLcwqAxS7sLaQvJd+2rPG7KuvY5hs28UOjecAvcpx2SuAA+zUE6IeEiVH626NVbdC3dWYN3NcmV1B69tkei0A1F0NKnifS79CtBUO6gMYmI3gPAOD26vbqYxEIFiyCIa7lzTEz1rLFVZr4YPn9un1QUoKtsZiVIwwr+e98GqQSJExBs8fPY/t0TYuTXmi+tqvsYMdtL5NZmg1S//kEz+JF45ewP/19P+Fn/idn8Cv/z9/HUftEepQY7/ex1P7T6Vz+I0v/QbW3Rrf877vSVO+29jioD7Am3bfhLPGfdOanZGRMcSg9JMMvYQ7qyvD/gvu/EA751ZoDMnQ8fWoLzMFIUZRyj3tbfaZtPv9zUrXaW7LL4PpyyTdVt2CvRdxJV1HTtQf2QepxyX2JKXaEp/ObTmXyPH37bIvHZHn7XUyR8iIakMe0I4eVwKBTbtpHwbw1AEUUMcjpGGRt38byZAMAHtPyHU4SgoT1ddRrp/BaNX/UcfO1wAP/w/Am/4OE73jmLyJXzNrhBjKVGririAT1jAhcHAc1UwMjE03boCA0IEMl/i8qQA3gqlmICNTx02JloCaALIFGirQuRlICYAxABFCbFllgYFFB3JTVqy6JSI8qLqAMLrMgxxtgWikbdpqRyhfV1tO+RO9m4LKc+ylsQ5UXQBsCWulo0tKPQCw9jWOuiWIAox1MAbYqaYIxDkutyT35NzoHOz4CqbVDJNCE2XFsGssFu0Ctxa30cQaq26No27JEf+iHqTQN0LyzMTI5Z7j5Q8NgeN3rksEaOg/0ePfr/fRdE0iJwDn1Wj2C2Cwt97DzeVNrNt1UsussThqjzYqD4fNYSoDFa7gDBz9ZwlCFzpuDRdi5oPHXr2H/XqfS1J+nba9O9rFpemlvlOJ+FqN3RgH9UFKGtYgvta3OGqOsFfvYdEuYC0f55N7T+KFoxc2jvE/fPo/wMFh3a4RKODZw81ok//2wn/DL372F1PujOba3A/IykxGxv2I9Idw0NGDoW/klO4iXSdqyUeWTzOOTiFCEkTGGHy2CbEfZ+DX0k4tBmTpVAIgLcFammmAToy0oUZsj+DMCn765r4EpNOsIWoDRQCdzCSq+86cIAM129tA3GXVxwCsvCx5n4AoKJ6JjduS60SIsQUMIY7OI9ip3FiIVZxiAdA59uYM0R0Ae78r5SAHdC9gtLyxsUgotuFKKWmNLrGRdv18v0B1FSh3QQhY+TVsPMSk2ALMBOREZStmaF0DMhZFlOwbH1nlitJhRB6mWwEUYIxDWYwQjONuJBA6W+CoXSG6bTgzAkyDjghl6ACwx4SIuNOIApdlUMLASkdSh0ganEcIIQKm4BwYgNUVGfyofUDGAOQqRFfCjS5wKQ8RbWgQujW2EGApIhKh8S0aIrjYIpoK1vAEbhMbnvFDwIo8HnOAsQbBjTZu/kQBe+s9WBgY02Ada8RujXUJGB8RHS+7HEx0Vw9JlP+Om3/Vd5JeqqLCBBN0oUMTmjRMMS0PkxQIYwy60GG72sZSyNTUXkZBrHas2zVctQMffOpCmpQTbFfb/dBGv0JhCpSu5CBAIoQQYAruDupix0qTc2kMg5qAffSIMaYOrtKWKGyBndEOjzywg04jUXFCDGkW1LJb9t6d4LH26w0io/g/n/o/8U2PfRMCAm4sb5wgMwDwzOEzOD85D08ebeSS2/1QZsrKTEbGfQklHgMyozf/FCs/AEWguclKDHm++QObysupwXhq5I29DyY2QP08P+YqvoulHBL0IXhpqrJ8940QKQKo46C1bgF0B4h2wo/Hhr+shN7FCETpbur2+HeS39sll4LgeR9G8lDaA2m5JlE8pCxUzoTkSDKpHcPYKULsuP2XwOoRAdj7b/01KPq2Vrz4a5xkTB5oN4kMALSzd6AjQmuIu4K239k/aUfA+fcDBd8gKYpCZAruyHITwFZYkwMZhzYCRDLQsdiSgZPn2CNlWEsJbgobapltWcBSQKwuYWWniBYgW8EX5+Adz1HyiDCSqkyGhxQeLK9j1TUwdoxoIV1lQIwesdwG7ASLbo1bzQLLwO+bAIObnceyWydl0IoKEN0kjXxouyX21wdoKOCoOQRAiG4CMgZdcQ4hGrzYzLFo14BxcNJOvE8GsZigQwUU59FGSl4NAFjFjktD4lcJsIgxYr8+RACBLJInRgcrLrslt1jHk9OgOdzObHhk/v/s/XfcbWlZ34+/7/tebZennjozZxpTGIahOBSpASlKsWMgimgwys9o1JcNFX/xGxONMeabKDZiTCRRQZGoWLBAAKkylKEMwwDDzJwpZ0596t57tbt8/7jutfZ+zpkBBoHReK7zOq9znl3WWnvttZ/7s6/rU4Bevg2wXW/PPxbxs9J3SqICKU9yyrbEe8+p6Wnu2rmLzWqTSTPBBQmMrF3dg4bEJKwX6yQm6R1zl/NlBumA1KQCwLwEW+42u2ilWcvX2D/cL2qjMCcn22AZZaN+HOWDJ0/zngBttGHWzHqeTQeYFtVYBpGqn5qeuk8w88kzn+SGYzdQ2pKbT918zv0AW+UWh0eHewAGfz8IwOfBzPk6X38f6xxpduSc4OW24sDexzcbc8DhW3owtAfA3A+YIcgCV58RvsssOvcqBHT0gYWL5n1IRyFZYi79bqWbMr0T6m2CrVHtBDO7E5+MZfc+muCpLmE5jmBUCsQ8IOL4yO3EhPCNhW5OB87qmP0UlU5djpMZQfAEDN4M8TrDuwnKN5FM3AjnY3JrfA0ZrD9F0qu72vkw7N7U/+jNkGbpOqbrT6cqLmbqppRtRYuG8UNgdKWQh4+8QM5H6DguPipcAqgsnicBYEobvEmolYqdoCTye4Yiu1ZaCLYq4JIRKi3QJifojJAMCa4Fb8UBV2fRcTfg21mUCENtK2bNLrO2xKvQy4m9F/BXBx/9Z3JqPcapor/UKl3gshUmpATkuFWX/qykwxRcy+bOXezUu0yaGVvlppjXKUWb7ccnI05WG8yCZsM5GtI5uMCA0lTFQUK+ymZTsl1tsxEMVg9owlw23DpLAHZ1TqUHqAgwVotVAQSR/9ORbFvXCv9F0Y+t5KMUlT563mnZrDbRQY6pcU2fBt0pgLrRznK+zBXrV2CiDw5Kxmha6X5Rn9myV1J1dv+pTsWEzjakJkWjOTg6yMHhQVKV8ps3/ia/eeNvYr2lbMt+ZGZUHCEp+m5LB9BWB6topWlsQ93WVK4i1Snei1zbOtsnXIPIzrXSrBVrOByNb3BeOi9dfcsjvqX//29/9Lc5sXuCjXLumfTTT/tpLl6WaKCteos2SOq3dbYHig92nR8zna/z9fehfCTomq7rctbop+uCBCFTolPxOalP0rvw6pze/6UPdFzg0pw9Zmp2YXan3D6N39Imn5afO9VQT96NKiXDnD+TLMkiXZ+Rv+lqJB5HMGVL4S14S+gk5t6K7T5a5Mt2W4i8uhDjOnXZ3BG4Oi33q0zAmyV2iaJhXv/aWoJv8b7CpENQOSHJCOkSXmeYeovOERfloTw2P7/jh8q21p4Ap/56LzcoVjm6Bj24iJke0QTNKAhB2gKp97D22LkRXXVauhfKiFmdSghJhne2N1ezKJQeoFxDG0wEeNE4UM15J0EPpKOkNSRLKK1km2iC1ui2xqXL6ETjnChwnK0wOqGqd3CpltRppfAqwUQCeSAwbSZUeUYwI/DboDQu1BgERGiVCtAxBY3y5MGKH42rRJ6NEYkwnsY3bNQlG9tHWc4KinwdpzNcW6KCRekcNbqYSZT3pyqdA2BdENIVbNjkdHmaUTIimAGlO8WJyQkZn4SaznU2NwVL+TLJ6CCtFqBSpAW7zS6JTvpxUQduVooVGtcIVyTKubvU6J12h8Y32GBJdUrrWwEBat7JcTgOjg9yaHSIRCccHB3k5Owk1lk8865H4xpsM2NpfJiqrXoycW5yZs2MSTshMxkrxQrDbMj6cJ1/+cZ/yUYlgKEwBd95/XeS6AQX3NzoLxKpu+0ppXjL7W/hpW94KQDfff13M8pGPPaix3J4eJgup8lo04M8ye0i8nzok7vff+/7ZZsoXvqol/KOo+/grp27ODk9yW/f9Nv99T9IBjxk7SE8/MDD+7HTW29/K5evXb73OB/kOg9mztf5+vtQ7ZZ0Q9JlWfTP7sz0nJkFNZM2Qh4tj80l2oR5t6Xjw/jIfTm7M9Pts5Nd2915eGO7KdssDtArmzrw0MURJAMBMdWGkI3rk9JRsdM4ioqE5eDwOp+7CmsjAKXr8PhaXoOdQnmXZBS100gk7jg1Mzk3rowLYQR5XvKTqraiaXYYFgdJEVWTRcZjoRuLhRZIwG7Nz8HyNQKmCHDZdwiP5vibpFMF2HQ/IV0nSXKcymUyRoVRQlHtj0EnEtioL4DmjHROjCQrN+TMvCWxLSaV23RoCDqnVVAqxYAONAaRtaucgMKj0CoTYFOsEKotfLGOCwFvclAF3oyATUoStHYUVsZYXmm0qyXKAIMhKsuck9DGACiROTcxxymLl1AHNoIpcIj8WqsQZfIyOus6GC54rGvJQ6AMKRmaJhlhq21WkgKvwKmEiR4xcBPybImkafsU6X4hDAIKOmLrZrnJUr5ERcMgHeAC5MaSmoLVYpUdryjbks1yk1SlWBVddn1Ll/6c6IRhOuzziCpbEQgkSsI5O0+WIiloG5EZZybrOzM+eFbyFVxw7NQ7JDohMxneexwK6yyVrdiqtwgehsMD0iWJ4GOQDnqH4UDgp976U9xwzw09ybirtx59K9/xZd8RJd9p71PT2Kbnv7ztjrfxw2/64T3Pe9UHXwVIJ+errvgqzpRneM4Vz2H/aH/fHep4RB3/ppNkd2Omaw9cyzgb87UP/Vp+9X2/ytl1cHQQow1fdeVX8Zef/ksAXnnDK/nhJ/6wdHvuIyH8wajzY6bzdb4g9uU37tvP5UtRXcJ1n99zFmeGOE4JEdDAXP3T7IhKyFcxLyl2VuxEfm46j5T4C7SdxA6CFeDSbM85NjETRrxiZvPOjHfRoG5XOCXNpjzHRrWOt7D7SRlR1afBTlG+jsTdXHJ6vIvuwB5UF1sQR2NuIvfN7o2KJ0cfmtjHG0TL/I4742o6BZVTCuUbap1Ll4dA09ZUzQbKVZGjE89BBCpk+4TAu9i9Wn00XPoSKC7CJ0s0g8tRoSGJUQzBaFTXVlcJVXBRdWSlo5StQ7GK7RizKCoczgwIxG148RSR0MaEpp3ikiUBh/H99mhJrlYDkTBrhTIjQnGQoAcCVELAp6uQjglBs1ltMbGBaVBUzsp4yXuU0ohbC+y6ll03w7oWTM7+0WGGqXBcGrewKHVBvsrQmBGoBJXtQxHwWro2rRO5M0FFPxxPHQJtsirRC3gyk6OUYuYsp8tNdvWQk60QUnfrXabNdK/Pi6J38gWieZslNzmJUdjg+q5JohNmdia2+lbiAUpXivFcJOXOmphEHeMNWidcHBssO9UOzok0e9oIQbYjAXfcmg4EbZfbzNoZMztjtVhlfbBOluaUrmTaCFcHVN8B6kBOalIJbPSetx59K++9573nABn5dMux7Rvs44LxBQQfuH3zdl7/8ddz86mbuX3rdl7+5pef87yuXHC88dY38t573svvfPR36B2RIxCy3u7Z1x3bd/Q/X7V+FWdmZ/iaq7+GYTo8Z9tX77sarTSXr17OZSuXAaL0euUNr5QuzwMNVf0i1fnOzPk6XxATj+PfdPzgHcc5ZN2zOjOdpT9E4BNBjm/EwyXUoMfRUK4V4MF1822GIKTaEOTxzbb87CvExySSfftxUExi9nVMvJ7JttHz5Ghbz4nH6VIEHUq4KckSwWRiLObK+M1+JNtvY+5Tshq5LNFN2E5FQaW7/afxmGKqdbDRvj8Sl1VMrfaOgBBqnYegA95bgmtQzRYEK9b/XRUXyXO9BdNxcpwotC74KsrJPeAmaDzKTjEmp01ygncoO6VsZhjbEFzDoCNom4IQpCtiUPhgCRhctgLVMXHwDRZlBgSV4tSAELZpg8XoQeTPOAE6WoMSgmXQGSYZENQAl68RZpLMnbYbKGUo02WstdQolIv2974VN19g5iqWVEprclo9wqBJ9JA0Bm/6EOTcAUEbLIksDkrR6CFTDTpmLXkzoiXl1OxuNstNXHB4rwjes11tMBwexjPnaozTMSecIwmO1lvqqICx3u75Zi9hkuIJY73tM43aYMV/JUheURNVP4RocBdHSpN2QtsKX6ZqKjKdsV1vszpYZdLImMcjzrazdtZ3LhKdiNOvbXtCa+Maalvj8YyyUU8E7qITjDaM0yXutTVV6MZa8lmdNBNx/iXwpk+/ie/4k+/gwPDAHv7OOR97Am+89Y3cO72Xr3vo13GqPMV/eNd/oHY1R7eP8uLrXvw5g4ZPb36a0pa0vmW32pVzaOdE3eVsmVtOzw0eD40OgYILxhfwG8//DW4+fTPvvPOdvP3Ot3N4dJjnXvncfkT3sse8jFe85RUAnJye5JbTt/C4ix73OR3XF7seMJi56667UEr16dY33HADr3nNa7j22mt52cte9gU/wPN1vr40dT/+LQ9adWOmrnkaOTPR/RUQANNZ/btWPs22EhBS3iUAIymgPC6met12fUyQrk/QjzZCS4minG2wpFrSEECJCRvexxTsaNTlJjC8RI7FTmX/HbBSSoziVI5yDZiA8p4QapEdh+gS3CuoqojXutFZHJP5ZoEYGz1sQhuVODYGQsbzo3RU+1is3aGhYVB+ivHsY9T5YQiOvDlFQKMW3+fikDzf1ZE4HGMbdIrTI5zO0FYM6WrvUbpGhRx8jSJDNydQoca5Zq4w05oQE6FbJ7LxgMZrIwnS3tPahiwf4fUAnyRQniT4TDpKSkZeXmV4leINoBQhX0clywTt8PkBQkzRVkGugaALag2DMCPJhlhfymLtvXCpVMLp6QnKtgFanErJkwy0QZkMVIpNxvh8HZ8OSbJ9BBoaDDvTuzmQL4EaogaHcaagTlewWYnlDmrXEJSkY6vyDGZ6MjrWIh0lnaGCwTrLmdkZvBcAcXB8EGMMS5kYMno8QYl82AXHar5KILCkM7adjIcI0PgWpRPapu4dc33wTKoJgdB7qiit+lBJ68WAbiVfwXmHwcxJtVqTJRmzVpRArWvZmG2wU+9waHRIxlSRg2IwKBSZybjpxEf51Xf9B9aKNb7p2m9i3/AQgUAZuWI3n76Zn3/XzwNwarZgurhQDz/wcD526mMAvP7jr+f1H389ucm55fQt/Vjo5PQk/+ND/6N/zg98+Q/wlQ/5Sk5MT/C2O97Ga256zZ7OC8CnNj7FNQeukfEXgTwaaiY6ofENHz05DzS9dOVSfPBslpss58v8k0v/CZevXc4LHvYC9g/2U3khOjeu4aH7HsqPPPFH+E/v+U8AHJscO2ffD1Y94DHTt3zLt/DWt74VgOPHj/PsZz+bG264gVe84hX823/7b7/gB3i+zteXpBZVP/ebefQFLO+ivf59/CLo5M3AvDOzMGbqHYGJz4+eMEAv0fZ2PrKy23OeTQjSWfFOxk8hSqODp2wrvGuYVFtx4x1wUiIbLo/FcVYr27Ndmnb8G1r5m6wSUAJmOhO12PrvfGAwRTznAULsOnXA6exvoL4bh+1IjIEto2V/Eg3ySsE1dkZoG5jciQlCNs3r4+TRvXcPkMn2Q35YQFJHrib6y3hPY2dR9lzgfUPranTwKOfABWwQdY7SGdp7WlcS7K5wWHSO00OstzQkBGNiyrKi9SXOlbSuJsv2xciCBKsSAaGmwOsRDQo/uAib7iMYSchWWsigAYXzYhSYJsPoHQPKW4ydkISSQCpgxsVullK0cWxYW4vHsxTTl5VS2GwVm64wXLqE1eFhBvmIkC6xUe/K5QE0riSYASEZCi5VmonKmagBrcqEA+MadiqRSvvoJaRVAsgIqHbS7chM1nu4pCZlrViT1xZziDo/ltzkJDplnI2F4KuHWFUQzLDv3nRp2dN2yonJCWpfSxcj4vQ/+cSf8KhXPYqvec3XsF1t934s3cipi0To8p22qi3KtqRxDSdnJzk+OY4PnjOzM2zVW/jgObp1lO//qx9gp97l6PadfPDeDzJtSjbKDZFUK3jjp974GX8FPOXip/CEi55wzu3/9QP/lXff/e49ty3Kxr/1Ed/aq8JedN2L+O1v+G1+7Ek/xoHhXOH415/+a1rfUtqS2tbsNvK7INMC2rrOzIHhAZbzZcpWAFjXuepGbEVS9AGU3dhq0e33zOwMJydCiH6w6wGDmZtuuonHP/7xALzuda/juuuu493vfjevec1rePWrX/2FPr7zdb6+RPUlBjNNlEFXJ4WHsudQ3LkE4LB4ezTNq09G7ooD2qiKcTGEMRJUu5yhDhR15ODewC6GKrbbgEaFltA57iriY6ws8koJMTcEyJaB7nFRMu1KASbZqihodCp7DS2hk5R3pnhaCUfEVcLt6aTnto3AJxrMdXJvV0cTP+K+2ti5CXgSkvoESyf/gpVjryWt7vjs539wRDozZiXyhFwEihml97h2BiGIx0v/JCVjHwU1mkppnNJYBZVvmblSxkzZCo3S2BCBghLgFoImxGurVRn54CB5toQzY6wZRs+XDEuL8g0+qKiAMrFDZdAKQrC0iXBRsmwsQAXQoRa45hXGaLSzBDw6tOBq4fYoAT7Oe3LEq6dTwIQYAbDb7HImerd0t/vgUbaMt6l5XpCCGs/MV0JH8g7rGyG8xvyfoATudq6ygcA4k1FuF/aYmKTvfjjveu6GjIIcq8Uq42SMUwabyGvuvFUCMmbSWjOxE8q6pNAC1FxwfOPrvpGdeodTs1O89Y639jEGrWuZNlNx5FVaxlDBc3p2mkBABUVucib1pOe5JFqIw//rI/9rz+V008mbqGyNRrbzjjvfsaf7sVhXrF3B//O0/4fve/z39XLnxfrUxqfu1+PlyNIRxvlYwGi6JO9XtctTLnkKv/MNv9M/7sbjN3LTiZtoXdtLsX3wDLMht5y+pecGXbl2pYyhnPj/dKTu3OSsFCss5Uss5Uv9e6mU4sKlC/v9bNfb1L5mK7o5P5j1gMFM27bkubSs3vzmN/O1X/u1AFxzzTXce++9X9ijO1/n60tViwDm8wEzIQiwsOVnfyzs7ch0apt+W4udiU4x02UhydhDiL4dvyYu7O2OAIo6+kd0TsHnuAMjAMXXvTLJeSv8F+9QiEII187BULMdeS3R8C50wCZuOzBX9Qz2E3wNSAKzUFuiG7Fr5RxZK10ekws3xE5iV6YVJZWbxdGNlv21U3k9Po6cFEg3xxBUSl5+CgDTbnxujhfDS+VYTSYJ0CgaVzL1LY2vaew2+IrgxNhP4fG6AFJIhjgzlHNka3wQ1Zh1DkyCz9bYaS3Ot9gAQQ9wOsUlhXSQvCWYATpdIjWZqI1UgtdZJMBavBmg/DRKs8ULJqjOY6YRgrAypGbALGia1qKUFqoSARNAYbHexyTqhtZ5vMpxusDhZVRHoHY1W+UWLnhqW9O4htLO5cXdMtE52QYlyqcuAsBZH8dZKnbhhKTrYtSF0Skz59ltdvHBs1qsUqRFn07d7adIin5B7bKGiqRgJV+Ol7OK/8rxdJb6iRYglJmMaT3FYgkEPr3xaf7sE3+2523/8IkP45xj0k6EY+OEV9K6lkxnvRuwDVacetNCXHRjPMBvfOA3+NE3/yh/9em/2rPd0pb4AMN0yB99/I/4vZt+734vve953Pfwo0/6UfYP93NwfPBzuVr7evmTX06IrbL14TprxRorxQqJTjgwPMAzL38mICDwXXe9i+16G+stta2ZtTO2qi3+5ujf9Nu7fO1yJo2ci+V8mS7aYbVY7U0HO4CT6IR9g308dP/cKPLk7CQzK/lVD3Y9YDDz8Ic/nFe96lW84x3v4E1vehPPec5zADh27Bj79u37LM8+X+fr72v5+/n/51guhh42m3/3Q+mTqmPWkdwY/zVn3acEFLQT6WBUZyKg0vQdnD1ArRW1UbMjXRcnCdM7diqOvc1GlGtHWbebSUckW4qgS4MaSlBkaOfHQFjoJiUih+6VV57gyrkKyu4IcApWeDkKAUrttgCZDiQRYxJcK50sFWJnR8fgRulSBbeLug9y5ObKE9lcexrbgyuZDK/BYwgoquXrxTMFZEE3CaUylB526g2CytB2grMtwaTS0QBaPxWVjpL9yj4V2rs4wnJsVRt4nUk3Q2landGmY5xewbk2clwcyiSEbEXs8LNlOUddNwpAp3gzxicZigSPYtPOKF3owadSBudbkmRATYCkkFOpU3yS0uohVid4laJcQxykUQbFJAgoI3i2qi2a0LLlhWB7qhXJdC+5jQ6zneLGo9ipd2TR95atehutdd8laeyMtj6D1po2GaHyQ9Sh7WMMDg5lAe8M6Dowk+mMXOfStYmXUmYyQszP6iTcPl5nf3DzH/C9b/xebt24lf3D/X3KdOMaPnziw7ziLa/g+//q+/dcEx86/iFKW/buuKNsxNROOTM7w8zORAUUX7vW0Zcmuu3+wrt/gd+88Tf5wL0fOOdamzRT3vCpN/DJM5/kv9343/bc9/RLn86Lrn0R1+y7hhc/4sV83UO/Dhek+5SZbM946L5qkAx4ySNewi9+1S/y3KueSxm/MKVmDua0lvDI73nc9/TPu3XjVnKT09qY+4Rhp9rhf9w459887sLHSeBoI8DOetunji/ny/3/DwwPcNnKZSzlS4zTcd9ROj45znvvei/HJ8cl/PJBrAdMAP75n/95vuEbvoFf+IVf4Nu//dt51KMeBcCf/Mmf9OOn83W+/sHVHs7MudLJB7ytz2QidU6u0lkLcbAig/aNGNMVC+603WZ9x1eJQMJXELoQwuiu25GGm01oS0gLGW25NqZc1+AbgmtRtiKQoP0OweQEN0WxBNN7ZLF1iYAcLQRSbDUfz3QeNr6SxzSbBDtlLnkOqNkxKE9I50hrAV9agVmW41Q6gppuuwZxyYuEYDxdw0hI0AAOZkdJdz92zim2ZkhVXEhBS+Va+fbuoiTcDOUcpUPBWirFBUWrB3hXEvQY7SStOiQDPB4dLKqdotUgjqN8L6KORBZZCNsd6uBxyQjvCqwZY3TGtN5B2ZI8eJQPTD3slhuMnSVBgw8EV+FtG3kjhuC9uO5qqLxI2RsvY7iahEKnsSmmqJMValtxyOQM8iXqAFY7aCcsFasxEDDgTUbjU7ad+LEkvvN5UVgMGyrHx65I4xoUSrgrOsd7T+MaZk3FTijZqrZwzvWeKCo66U5nx1kKNaDwKiWYVAIQrWWUjuZc7zhi6jORFIzzsXRY7LRXDbVtgyaa7QEKzbSZ8jPv+Bmst9xwzw287zvfJ+MQFWjahj+4+Q/u86O3XW/zXX/6XRRJwcMOPIynX/b03nW3cQ2jbETrWxmTaTm2lWSF3/jgb/Cuu961Z1uFKbh05SBHtyXp+113veucxwA89eKncsnqJTzl0qdw8fLFTNspaZX2nKBnPeRZvPam157zvC87/GX84BN+kPViHaUUW/UWGzMJn+xGa0APNJ13XL56ea8UOz45zigdcXp2muViGa01Hzz+wd4d+Msv+nIuXLqQm8ub+5Fb42REuJKvoLVGI92Z0pbkiUxkXHA88cgTuetmMdB729G38Z2P+c4HXaL9gMHM05/+dE6fPs3Ozg5ra2v97S972csYDs/VqJ+v8/UPo8L9/P9zrQXw4tsFJ9/72tV9gJlObg1RaXSKPnOoe3wnHR9eTB8i2XVG2l3ARF5JzD0yyRwo2U1gJF0P2VivFgrpUMzU4rEoXxO0kQgARgu8Gx3l09FkzjYRPCVRdj2RDkpoCYhLbHeMuro3KpRqCIUAkqAEXARLn54ddM+FkU0M5945oZKOksmlu3Tvn8l+u9OIYvfgV5Ls3sosPYjCoFSDVwarR5CPoxFfK0GWahA7PBqfjnHJMi5YVCM+ND54lMlJjME3WwSUyLxVlDGbhFBLrIBSWvxg8DTNFJss4+0WQafYAJPyNKl3+Eh49s7hfUXpa1JvGZkUpzNKAi7a1rsgii6lJFJAKY3Rit12gjMZPgTaYJnZmt12SuIdLsnkijAjUmoSHUh1gcsSnG+weozXFWVTcWz3GJl1PQ0p9PyneIV4SXFWKo3h7UrCBV1F7ZHcn2ClUxIkuFGh5X3W8vZqpdmtpwQ/51yAGLHtVDtUruq9YAC89wzTIcuZjJYKU1C1KUWoe8IwKG45fUuvovHB87zXPI9nXf4sDowOsJwtf0YOx7GJmMXdtnUbR5aOcMXaFX13qHPH7RK5syTj/cfez2s++po92/gXX/YvuHrtasrJp/mvH/iN+93XK57yCr7sgi9jo9rAOSeZTd6yVW6hlKJICr7isq9gtVjlmvVruHz9cmbtjFSnjNIRJ2cne88bhWJay+fXeosxhuDmUQIuOIZmyJHlI9yxdQf3TvbSPpRSfOrMp/qfv/IhX0mRFCgi8TfmYRkMRhsSnVCYgu1GRlXTZkqe5FhneckjX8Lrbn6dnMfN2/pjfjDr8zLNM8bsATIAl112GQcPPrD53/k6X39v6rNlGH32DSz897N8Q+nASU/uPfvxYW93p7u/jUTh6uR8GzqmWttZJOD6eZfDDGLjxsuibWfgdmXbLoIIPN4sEQZHIAR0syFNFmmTgOqIu2kEaDEqofO2MYXc7prImxH+TnCNAKTgRLYb/VcgUNqKsi1BF5Q+CF/H2di16TpNToCMGQg4m90Fd/0OnPwrOPMeuOd/7wEyAH5wEUEV2Gw/IQTS9hQqaJzOCSYT0BUcwVkhSUeg5ZXCJ2NCMsCZESrEkUx3HrVBJ2OCSnCRB+TNkBBVOh4IWszpCI7GVgSlMGbI1FmOz7Z7CbpVOdYUBJOjgiRczwLsqIyJ1wRT0AYx5AvBkRqDTjOJR1BCVPXO4oG8WMd7CyaLBE2N12MaFKRLUeWjIM0ZDQ7QJivMXE3lGnbaGRvlBid2j9HYRtRJhD1urtNWuiOJyWBwWC5BZ9kst9koN+Tx0QE40QnLxWpMpvZYZzEqYZBIlpJSisQk/VhJK937rnQSZKOMeNYEATSDdCAjp2TEhzfu4N+949/x2o/9Hp7AJ858Ys97f2J6gt+96Xe58fiN3L51+577lvNlvuv677rPj+KHT3xYgCNiqrddbQuo07BVbXFs5xi/8O5f6B//bY/6Nk7/6Gn+/TP+PcvFMpesXsKPP+nHztluohN+7Xm/xiMOPqInNwOsFCtyrXZxB0nOIBlwZPkIR5aP9O7D4qfT9AaCnRlfGa/5YTIk1WkPELv8JoXistXLAAE8O/UO+4b7+q7Wx09/vD/Ghx14mIzxlIBR62x/XIlKGKQDjDF9d6YDnhvVBkv5Us/PccFx1/Zd//A6MwCvf/3red3rXsedd95J0+zNMvngBz/4BTmw83W+vrT1dxwzhQcCZjouQiJdgi5Pqe/OdB2XebdE5NAxysB1ScYxcRnm6iU3AZ9JSrPtTPCcGNh5I6ABL+Ogdgba4nsP+7aXhQdtmEung3BcqtNCyjVLMmZCQRqNwPRCVlK7LR2MoIQH4isUyzI58uBxODejtUNcUtDYwAodkdjKiMmV1CbDB8Vg5yNQ3T0/f82CZ4fO8SrBpiv4levRwSLWeRqFRvsazBCXjKHpOD1aZNB2G0xKjRdJtLckrpRTBnLswaCSBIuhdSnKT/BKE9JllG+iykXROoNrJiR2igszAgVpOqBuFbpYp53cyqypGSSKhEBQCcpZUJpJW6KTMROlWMHgFXjfspSvUzUt1itCtopKRtDs4nyD1ymDwUF2Z6dw6ZBKDyi0AWNxyYDalTS+oQASFORrLDUzqnKH1k9wkXzrbMm28313pXVtL1uetBOGyZALli6ASAZtXYNTAp6897ExKF0DOeeqJ4ymWpEnOcNin4yLXIvDoeN36EE6YLPepHENAz0g1SnTdrpHsp2alN+96Xd55XtfyZJM4/jzT/15b6t/dv3N0b/hMRc8pv/55U96Od/yiG+htjVXrV3Fy//PXhfd99/7fk7NTrGSr6AShVaaOqqSdttdfvYdP9sv8M+47Bn8zFf8DCB5UKN0BHabtcEa//xR3857zhzlsRc+lvXBOk+++MnMWln4Nbrn5yzlc08dED7McXuclWyF/aP9PR+m68RopcnSjFPlKcbZmGkzZblYZmWwEi9l1Z9zHzxGGS5fvZy38TYAbt+6nSdd8iQaKyGan9qQzsxqscq+wb4eZAFUvmI5XaZICkor18+B0QGUUr1Z4LSdspQtoZTq3YABvu2Pv40b/3838ujDj77P9+VLUQ+4M/PKV76Sl770pRw8eJAbb7yRxz/+8ezbt4/bbruN5z73uV+MYzxf5+tLUF/CzgwLXRUTeS5dThEsEGmhJ/D6Rki4KDHBa6cCfpJMbutSl80g8mc6w7k0jme25K+bxTyl43LMKo5Oms04cumYIIk44QYnwKfelH9tDGy0u6KaanfmGU/dWKzdkbOhtYx6nIzKvHO9MZryjXwjV0mfEF26itZ3M44pdnIH6Yk/FwPA+yqVwMUvZHLoa6hWvxydjsU8L8rIdTf6Mwabr0snpftriuh1YwEjxyffc0EZOfVKg8kxOsXrnJDkGKTzMMxWGOSreDw+GTNzNdNmG2ctLhg0QToSpsDiaNtdmi7HKDgh1eKwQeOVBEK6oLFi4CLeLq6lbCaUrqYOAZ+u0ASRdRtlMMmIVqd4ZfAofHAU6QiHYVpN2S53mNkKozSZzjFmwPpwH8EHPGK5P6m3Y1dHFsStaovNcpOZnYkDbvCy4AVQSuOCo3JypqbtNC6+UWWkFINsQMCjlYjKc5OTJHK8VVvRtPLl9823vZnv+JPv4J1H3ylZSkr1hGDrxfF3u9rmE2c+wSvf+0oAdj1MA/zie39xj4Pt2eONRYLuMy5/BlppEpPw3Kuey//6+v/FD3z5D/CIg48ApHvxM2//mZ4fBNKh2Kq2+Ll3/lwPZLTS/Orzf7UnOVtv0Wi8SnHBcWTtMp56yVN51KFH9SZ0a8Uaa8WacE+iT0thin6/ACvZSt8NWx+sx4+96j1fjDY0tumf03nAjJMxK/kKwUtnJhBoXMNus8vlq5f3r/9VH3gVJyYnsMFydPsokzhCvWLtin6MtH+4nzzNMcowzIYYY/puD8Bqttoff3ebQnFk+cie8/64//Y4PnLiI/f9Wf0S1AMGM7/2a7/Gb/zGb/Arv/IrZFnGy1/+ct70pjfx/d///WxvP7hs5vN1vj7v+lKOmXpZdky/drO9o6NeSt0Z5UVHXMRrpJdlK2IOkccHzcyW2Pzw/HjSXMCMnQkPJzgZVYVm7tyrtPA4tHR9QvSB8ckSBE3V1kzbXXz3eJqFLKhaxkvR6bZ30G0ngCOoAqU1SbAoN8P5WvYVia3BOXwyRgXHtJ3hXU0VnHBx6g2GG+8kaRfUYdl+QvQPAWD9cRKXkI5B5xLVqA3KtQQVM4m0wutCspF0KgBNRxPAfB0w0XnXiILFTmWMlAxokhWCTtCxQ+V1QUKLslN567TBmyUaH2hcTfCOygxxGLz3GJWSJzmztiYxhoDBqQRLSu1bJtUWW/UuznvaehfrPaVJYqeDGJgo19WZepuNesaptmbqahJc/Dbu8N6JzNlbTLYMZoRTimlIKINh0k7RScHK0sVoLREBlY3GcrgYRijxA0qJu+3p6WkyI1LxrlPi8wPsqiGNtzjv2Kl2CCGw20x4/cdfz9/c+Q4MhnE2jpLqNYwxfODYjfybv/k3/MWn/4LTs9O87ubX8e1//O38xa1/wb/5m38jShtl6OAkwH//4H/naa9+Gs/+7Wd/xo/SD375D/I/v/5/8pC1h5xz38HRQS5avmjPSOeZD3km33n9d/ITT/mJ3uvm6PZRPnT8Q/I4JVygD5/48B5n2xde+0KWo0TcB5GiK62wyZialFoJcbkzs0u1GOd1ry1RCeN83JN2nXdkJiNLMi5cvpAjq0dYL/aCmRBCT5LWSkcQ6lFKkae5hG/G8Zj3vvfouf6C66VrhIzw3n33u6nbmt//2O/3r+fRhx+Nx7N/tJ/9w/1cNL6oj3UYpSPyJO9B4iAbCKk4WPIk74/vmn3X7Dnfz7nyOT1IfDDqAYOZO++8kyc96UkADAYDdndljv+Sl7yE1772XEb2+Tpf/zDqC6BgOntbPi7ui9VlD4F0Upqt6OHS0qdX7+HUePqsJBXl1p2CBh3l1Q0Tb5nmB9kJgd61VxdiYAexAxHDENtSOkJJAekq+JkADxQEK94mKoDyVOUpmmabWbMT1UaR29LEfKceaMUOjm/AlQTEvh+VovwMVZ/Ah4BHpNYik3agx/hkTOsa2hBQAZwvCeXRfiEH8HoA60+kXnsc9fAKZvueQn3wWTizLNwcBdo1sSMgvjDaNwSVo5RBY/BmKIBNJZAsi2leMiboPD5/BsrjvaX1kcAa4vsUPBqHsSUhWLQVvlAwY1pfE9DUyTLbrmHbR5EUmsTkjLQmqARvMmq9hNUJjbdo31B7R2krZu0E7x2bXlORooyBYKldRWh2mbU1W21J6y3OiiRa2SkqiBQZk6EDYiiXrTH1itKJiZ4ipWwbZrt34NuS0tdstyUb1QYDk+G8I08KfPAsZUuMcwEj42yMRgt/wzWgNDaOkKbNtB8d/eEtf8h77v5b/t+//UU+ufHJ/n0zMTfpe//yX3F0+yh/fdtfc+vmrfzhx/+wf183q01e/aFXywjLt/0C/vsf+/0e2HT1pCNP2vPzt1z3LTznKllA3/7P3y4uwgt1zb5rxAsnbqczygOx8H/po1/aP/bH/s+P8V/+9r/wiVOfwHq7p/MD8ENP/KH5pzt2j4RPlLMyvpgkybl85XKWsiVWi9X+tbggEu/MZCJtD7L/1rU9gBulI5ayJVYGKyxlS6Qm7bOnVvPV/px0sQ1aaYbRWqC7r0vHToxwXV7+5Pk47aMnPsovv++XueHYDYCA02df/uw+1ypLMrTWrBQr7BvuYzlfZrVY7UdQmclYG6yxksvxdSOnfcN9PPzAwwHhJf368399noD+INQDBjOHDx/mzJkzAFx66aX87d/+LQC33357n3R6vs7XP6jq7PK7+ryu4/vg3FQnRHUTw+sA+nRsiF2WUroc3bgDFjo7UVq96MLbGci5GeCjA3CNtxO0q7A6h3wtdl3i6EmFaDYX5tlGoRX+i06gmUm3RhkSPAQbUwosym2j7QTb7rLbzGh9Ex2Dd+ZS7GCj2ikCKW2igZrF+Brd7KDsLngrZm9mKJwB7/FJEb1jAhUJtc5p0OJFE6vNL6RcezIQCPkqzcp1tIMjeKXxvka5UhQ3tBBqFJIHpbUAP5dIKnTUdUuHJlvBBsdWM2PHVTjbCs/ZA76SdGZUNHYLKAI6KLSbxRyoIHJqk0i3iUDQGa0ZMk2XUFpjdUEbux9aGZwuaEyB71LAXYPReQyD8Fg8rVmi9g4C1G2J847SVTTRPM+plLKdMrVOSLvBYUOLNyNsMqIyy9RKRddeh1UKYxJ2221scBidkuiUJsCsmbFTbuG8Y7VYZ5SOZGGLbrgg3IpJM+FMeQaF6hdUkBHSB+79APdOJCfKBnj/sffjI3dKK4NzjuOT4/17+a/f9q/7LKKufvsjvy0Gbcii7JzjTHlmz2P2D/fzLdd9Sz8KeuolT+VfPe5f9UocAj0htaur9l0l3ba4zBlteuM+GyxPPvJk9g/ntgev//jr+aG//iHu2rmrJxEXScHHv+fjXLR8Ud91gdhxMeI6HFSgSArWR+s9F6b1rcjRI+jpzqcKc+VRJ6lGwSiVMMsjK0fYPxAC+1KxxCiT96TrBq3kK4yzMetD6eJIKvrckTlRCalOeei+h7JarALwsVMf23POH3nwkawOVnvC9VqxJnEOsePSxN+Fq8UqCtWDxO71K6W6jxL//NH/nG99xLfy+9/0+/2Y7MGqBwxmnvGMZ/Cnf/qnAPyLf/Ev+MEf/EGe/exn86IXvYhv+IZv+IIf4Pk6X1/U8k5GPPWZeUfk7zpmOtt0bxEodY9LBgImmi0BJ3Yqo57F5ytklFMejx4vog6S5OodIeHWGwJMou9MSAagR3F0ksTukBPw007kdXaZTUHIxE27gfKW3AzQZgB4greERgCFcjU6NAQ7pWm2Y1fGiWuvqwQM0QpoQkUwFlVJWJRv0NWpmB+VSMMpWHlItgzO0liLbrclX8lbeY2A1wX16CpskuNNhiclqCEhGVOSUnon3STvQGXQTvFKVFMaiUOQNryVEZpK8GZAGF3CbjDMXIMFGi+eNkonoFOsit2aJIvKLhXzngJeeZQvUToQOkWJPBijMhwi027aXab1Do2tUUHR6kIykLL9VLYlKEXrLZrA0GS0wdCkK3gzwHpH60M8i4n4nmBozZDaDADDRrkt77l3nJidZqPZpbQCSk2xnzaOtJIYcKnwmCQjTwraKPOdtTN2mh1MfB0g38Q70NIFFHaqGedcP36ZtlM+ufHJ/sp3wJvvuoFa5QQ0jbN871987+f06Zk2036c0uUfLdajDz2aq/dfzY886Ud42fUv49ee92tRNi7jmJOzkzz14qfuec6TjjyJPMlZLpZJohKscQ3WWayzDLMhP/yEH97znEk74a8+/Vd9FtJ1B65juViWmIPpaY5PjlNFd+RUpxhkPNn6ltzkrBarTNuppGhrwygRkDLM5vEM3ehIoVgdrDIwA9aKNUIIHB4fZpAOWM6XxRtJiZpIZPMCyEbpqAcWHt8DPACtIwmbwJVrV97nuf76a75eHrswEhun4347XcL2Sr7CofGhPdESHbeoIx2v5Cs878rncdnKZdS2PndnX8J6wGDmJ3/yJ/mJn/gJAL77u7+bV7/61TzsYQ/jp3/6p/nxH//xL/gBnq/z9UUtX8VxSWAOQuKv5+DFvK4bC32mOtt0ry1j98KyN0wyPk5n7PGK8XPy7XxbCqZ3iyx5drcAnyBOs3RZRwBBxU15CFo6M8kwes6oqEQ6Ll2idhpjChAfGgzBteA9iZ9GF94dvJvi283oJePACUcguCnMjkEVOyehFvm2a+X0KUMf2NgFSCoj30g1EHkRAQ2hJgmB1FaMZh/nYHkz6zt/y3Dnfajo+uqTJZRW6OAlSRpwiMdNXZ6kxmP1EGU32W134/jKRLKvh6YmaTbRWJE9mzEhGRGyZWzw1E48cbzSaJ2II7BOsXoItiIhiHpJGenS6CwSQEVh5k1Ga8Y0eoBLRrR4BukSmU7I0wFDBdrV4pBrMnS2TJuuSsxBCGyToJIhHk2RLaNNEceEDunVOYLWBCBLh/Fy8ZIvRCAEz4dPfJSfeefP8svv/SU+uXkrqJQiGTAs9jGIC58KIp1XgEqESN4Bhp1qh924AIMsbiEEqraiigGmnXqp8U2/2DW+4fjkOAtXKzdv3clvfuR3sGbI625+HW8/9qHP/tkBbjl9Cz5KvM/uyjz3yufyooe/CBUUj7nwMfzAl/8Ao3TUdzaqKPXfN9zHNz3sm1Aonnbp07h639U9qfjQ+BCDqLxrfCNgQxmuO3gdv/iVv8jB0dxW5J13vbP///UXXA8gCqf4ZWO33u2DFY2RjkbwoZebpzol0QmXLl/KgdEB9g32MU7H/XkcJkNyncdzplgpVkiNgMnMZCxlSxhtSLXEKXSvM8QcrcQk/TinC+YcpAPZhpc32QfPtQeuPec8//JzfpmnX/Z02bdSpDqVf82cRN11l7oxU2pShumwP9cd4XgRmFW2YiVf+Zze6y9WPWAwc+WVV7K1tdX//MIXvpBXvvKVvPjFL+aaa665/yeer/P197F6QNH9nzmYsDPpeDTbn8Po6SzOTH1Cnj87eha59+wOjpqTfUHAR++cqyJR180Ju51hXQgCFpodKI+jQxlN7ubyaJoN6erYkj4l21XQbsi+VSQgx1GWd1OadkLZ1jLCcRZjN6NxXwMuoGMnBLcDOo/3uXn3SRl5Wd6hfCvdHxzKTaUr1E4lzNI1KNeQ+SmD6ccZNcfu86za7EAcy4QoJ4bGTamabbxSwuFpZ7SuIShNE89bSJYBhQoWE2pMOxOeUDrC5xf0uUGJUujgRG7sBfAEldPiwJVkyQDSVVxxCJ0to1UyB0uA94HGDCnTdUw2YpecRo9waMCAyRkkOcvFCkUyRpkBtUohgiKHwiUjGl0ISDM5WidYJJnb6gGoBIWH2C0SQKiinDrwhk/8mTCpfMsffeJP0ColKAE/mUmFbB3kuvRqSQBb5KhsVVucKk+x20x7wqdSCust2/U202bKbi2jGRccW+WWdE7wqKA4MT2xB8wAvOvOd/FXd7yNX//YG5jcz8fmZ7/iZ/m5Z/5c//Mnznyi95c5PT3d3/6y61/Gtz3q2xhnY5QWFY8XcX+/oG+UG7266JkPeSa/8txf4cef/ON7coWMlgRooA9VNEoAw/pgnVc971U9wXexHneR2P2HEHoidOMbGt/MAUY8DqMM+0f7uWDpAg6MDlD7upc1D9IBq8Uqy8Uy64N1BtmAaTvtu0vdsXbnH0CjOTw+3J/c7nEd/wbolVCJThgmQwnrjJL5Z1+xlzz9A4//AZ50yZPmYzdl+m0ZbQgqegDF+7t9pFqcilFy7hKd9CPB7rGTZtLLyh+sesBg5v54MZPJhKIo7vO+83W+/t7WIpg5uzOzSGYLi92V+9tO/4Ms8J0/jLcLPJiFX/22EnVRl1LtPWT7BGAsbte3sduzK90V56STY7egPoWvT8rIRwG+kpZ0syWPraMnizbynJ5krGQ8VZ9BAFCNdy4SZCE0O/hQC69FGUDhTZRREwENeq5kojPqy+S1aEMwSZw0Veh6M5KVK5RzYEuM2yU58z6Se99w36dUJdh0HW0GhGQZj8N78GTyC9+L8V+I1vkqBNAJzmQEE7k4Wqi4xs8IOiGky2BSAUIoTJTEF1rhdIb2NaVrCLahbGtmJLQqZVcVzFxNUEqARLpMMAOcktfr0wF6eAltfpgqWKYeKpVQmREeyJIcZVJCuk6VDPurwOqEaT1lp96htBVGFyKDdQ6rc5TSqOBJtMEpCN5hQsARsFFlddvu3ZLEpeDWzdtwOqpbzIhgcmqd9ZyNXRy/9v5f5w2f+BNa34pzKyl5MuyjBBSK2tV84NgHOF2eprIVu/Uu02YqpnZ4vPNsV9vUriYAl6xc3H9cFPCam17Loqbvex77PfyTS/4JAJcsX8KLrntRTx4FuPnUzQIwtOlN9AD2DfbJeCt+fhb5I51tvw/iXouS0UnX5ej+OO/kdp1inWXWzihtyepgFa21EGEJe44H4PLVy7n+gusZZ2NG2agft4BEH2Qmk0td6T4fKdUpFy1fxCgb9UBjmArIMFpGRovy5o5M23U4YA5mULA2WOvl3EYbsiRjtViVtGpb912UTkGGmndWlrIlfvm5v4xCcenKpTzxyBPZmG2glOpJvt3+cpP3fjjdqKo7jizJSHSCQhyLOxA0TIYMsyFaaZbypX84pnk/9EPC5lZK8VM/9VN7ogucc7z3ve/l0Y9+9Bf8AM/X+fqcyrey2KfLsoh97k+cd0vO+XcBoHi7F2ScU2eNmTqlj7NQ3SvckOFFe0dI9RkBMs2m5C8FUaVgBpEUHO3/m00BDOlIwIPdhToFMvAtwVUoO0NVpzDpOsEkqI6k6+o4crLgJ/ORV5FDWxNQccSVEPwsfvFXuGaLADjX4J1Da4X2CqUygtbiduuqGGPQ0Bv6qYF0glRKCI7GTsnaHfpYBiMeMCqUeBfI7vydPWdwe/BQlHdkRlOpAdo7TPCERDxhgkqhCx6sNgkm4HROolOCSghaY0KC1ykJlhYjRnquJJAIUTg4vMohTGj1EM8MpRLSVL6ZN2ZAowu8q6l9y065TRgeJlEKcdlNSOL76FQC3qONJqgMawa9N8vEVTg9IqgEQ4qnEZULilE2ILga5S01mmAbtmenuXT1YWiV4F2JM4FcpwxMzkBnhKAp6zOgFC54nA8UZsDERfUQcGq2wa2bd3L5cIWNekKjMm64+/0UxTpXrF/G7930+3zwxIdpA/zPD/9PvurKr+K6g9exb3SAPB0yTsdslpv85/f8Zz5w7we46KMX8evP/3Vxn23L3g/G4Tg2lW6aD/DQfQ/l6Zc9k5//4Kv7Dk13pb/uBa9jo9rg2v3X8sJrX8iXX/zlGG32pC/fGfONAoHT5bwzszZYwznHbrXLRcsXkZBgnSUYGXEYbWhcQ21rjDYsZ8uUbSkdGe/6jlKXrN39u5Qs9QCnA0svvPaFvOfu9/T7fvmTXo5R847OtJ2Pm7v9HRwd5GR5Ulx2dSp8oy5NPC7u3XF2r68DLVqJTH7aThln475R0BNtEfPCUT7qScFdd6hsSzarTfneRCDVaT8G60CUVppve+S3MUpG7DQ7pEnaE4+X8iUuXbmUe3bvocvfalzT76M7hsyIR1AHbAbpgJViRQBt8AzqAUVSMEgG99nZ+lLW5/xb/8YbbwSkM/PRj36ULJtnz2RZxqMe9Sh+5Ed+5At/hOfrfH0u1RF4g4XiAcRqdKZ0ob6P7kmQhTm0ApK66jg0yWhhO2GeNp2OZawTnPBVWFlIgo6lYmek3ZF9lKeiOy9Rzh2XBNcFQkaZd7NNXZ/BVacY7Hssyu4QbAxvRMY9vt5E2yp2hWrEEZj5uKitoa0gzwjeiyontDjv45ioRTVb+OBoCVQqZUzAYdEhkGtFQhLByQDqOIbTGdAAObgJzjZoZfChERO5egPtJuTlneTKkPi9bekzw2uYDa9hqbqDxjtcHMOZAOic4AJBB7QtCdoQjLS6LTlBZ9JRQmHyZQbJmLQ6SqUNLmTgG6rQMEhHQMBFHxCLprIVW23FwWTE8uAATbuD1RlBp8xsRRUs3nvWfIVXmiZZxSQFSmlawNoJBiVS8NTgvMUYLZM8ADPAKsOO20X5AO0WpljGRyVYILDtHAPvcSQEHT1XQoAkJ9EZQRsmzRTjHZnJ8cHhTMGpZgMdr9iOcv36T76BqwcrBGW4beOT3HzyJhyiNjoTTXstcPPOvdzzoVfzjIc8h0de9hwUis1qkw+d+FBvPHfP7j18/PTH+bLDX8bMznrVkfNzlVIAjqwc4fpDjwFePadyAa/+uleTmERcZSnJdEZta3bqHfYP9zNMh8zaGSemoohy3nF6NgczPaFWh75b4ILDe9+DkWmY9tLkQTrYAwY6snJHph1nY6GiNfIZ1lqzlC0xtVMODA/wkke+hNfe9Fq+8Zpv5OEHH94rhTp+UUeu7Rb+UTFi0A5Yypc4MDpAnuS41smIrp1KV0aZ/phccP34xmhD2ZZkJmOn3umjDjovFx88u80uiZKuCNEDpxttdbc5L8oqg+lDMkEUVUYZjiwf4fjkOCv5CsNkKMqrwTpZkvVdq07N5IOX7pxS7Bvs68Mll/NllvKlfhRY2nIPd+ZsGf2DUZ8zmHnrW98KwEtf+lJ+6Zd+ieXlBxeFna/ztac6oOA/yzjonOcFASf1jnzFHI8X+C1euCcgj0nH8vgm3qYLGd/Ig6WDAtGXpI1y5W5bEbh0H3rvYXI0dk9mQCNy5OqUSLqjgkak3I4mtMx278LXZzDVSVAa1ewwcA3ezUS5hEL5UsZCvon5S2HuzhtacfD1kTeTjuIi2KLaSgiiKo3HLyZ2KgR8soSjpqnOQAgMVUqSDOS1K0PppuCnDJKxuOpuvJeiPoExS5TFVagQyOuj6DCXqOuzfvedyS5lN72QEFq8yXF2R9KYzYhEGUKyjAsK5SVbKmBwZoRVKa7dRrmakdb4ZAT5AVAS0mhUKoGQOofQ0AZII5gJ6ZhAwAe5bmb1JquDgwSdE5TG6hTrHK1K0CqAWcJm67RqRG6GYBK27YTgLam37FctWuVY31L5ioEPOAVJvkab5ARO4b0m14ambanbGYoA7QSHZqoGBAJKD2gjpyaoAT4RsNa4mjzJSBVsekMLnKwmGBWFZAhI+avb3sbNccLngQzYcOcMUSkDlA5e+6m/4juf+HIuXLoQrTTvvuvde96bj574KI8+9GhOTk/KWEQLx+L4roAZDxxZOsLlq5dx0dKFNLNjZCblz1/0x2xHefkwGXJgeIDdZrcHIwAHhgc4un2UU9NT0Yk4cHJyst/3ar7KdrON9pqtaqsfZ3gEzCRKvFJKW4q6KLrYhiCeK108Q2/8t/CFQitNYQpKU5KHnLqtecHDXsCLH/FiDo4OSicqAqJu9NV1U2wEoZnJODA8QJEWPWACej5N16Xr9m+9pbY1g0QUTB6PqlWvgALphuwf7meUjfrnd6Oo1rcSCxFDQPvREJo8yanqqu8gdW7FWssIa6veYpgOe2Clo6NzF3iJEh5N69s93SQQMNMFeHbgRSHE4xBCr3p7MOsBZzP91m/91hfjOM7X+fr86+/ibxScLPL9/xdUQgQZpYQulJG93ZV2O7rInnV71yHCLtBxGiEEdyMwuwuTT0N5Ij4gFQ6Nb2OAYuj5JnhLbSu8Vmg7lW3pRLoszQ7BlWgMzoOuN/CGuVlfaMGbCJoq2a+WTgUqxYeW4DzK7YJJ8CqRBbYqhZ4aaormXpJkmdKW6HYHzwByMfELQdPWO6TO0epAunUjlEdRQOYrbLqPweyTQmC9n2rTdazOMNrgfEsbEpq2ITFgCSSkoBMqPCq06NCiVMbEljjV0FSb5MrTBoNXBSody0hNxVU+gNIZ3qvYPVI4PQK/iydI/ye0OFdj3QySEV4ltGpArTNq5ylUglINQee06TIuGVMnQ6zZQAWF1kqUWdqRqgTvJSyQZJnEpNTjK1EhYeQrdraO84vv/89kKqCL/WhfM8j38cyHXY6LI7RpU2ETQzAZTg/F2M6kFEmBjURLrzRvuev9GGI+J9J96c60QvC5LFLxUgx7BqLxKg+888538k3XfhMfOfERXnnDK/fc//5j7+dFD38RVSt8q0xnjLJRn/MTEBM6Yww/+dRXcPu9N/D0S55Kbgraeqdf7EbpiEk76Uc/IP4xR7ePUrmKnXqHg8lBTs7mYGa5kOuuDjXOOyb1hMIUvfS5SAs8nspVZCYjT3Mh+Eb1lYonJlFJPxrpFv/O7RjowyZzk7OcLzPOxj0Q2ql3+vGaUorT09O44AjISGY5X2aYDVkr1kiMfL577xdC3/noznW3vWE2ZNJM9nY4IgDqjPOcd31HqiP/npmdofa1OA5rzXKyzJHlI2xWm9JZSTLKtpTXHH8vTdoJo2zEZrXJKBvNCcQRzBhtWElWaF0bnadVf8xddaOmrruklKIwBXma95lTD2Z9XqnZ5+t8/f2qs349+wdCRFvonhCVRB3nxVvh4dhyQZ69sChH2arcHAGRTuUxMT26B0Zdx6g7Ntd5w0QlkLdndZeiZDvuw0VCsXITlK9FuVSfATeLhD8tIwszFnlmO5ERk/Pz7RPoM6B8CThCsLLge4vyHlSG8S2KVgz2MCS2RNkdUj9FYeW5TkBW43ZQCAnYlJ+G2R17zu5wdst9AplWFewUV1KvPIYqvwjQJH5G6huc1tgoRwbwymHrDbyd4X0r4xwU3llcO6Optqldi9IFmJRZt4IrjUej0gGYHJeOUcoQzACbLqOCp3EtztvoqZzgvSVLxvjiAAwvotZjqiQ6yypF5Vq225bttorkXgXpSBxZdUJanZJvzApab/EojE5YGq6zUW4SgBuOfYCJs2xax6npCTbKLW7e+DTvO/Y+WlvjQqANnt16B7RB6Yxa5ygVJB8pjt9u3TrK73/8D6gDDIzmMRdcTxP2XKHyuhQ85/KnczCamj38wHU85eKncM3+ufr0Yyc/xla5xb97+78757265cwt3LZ1G5WtKJKCVKcc3TzKnTvCc1kfrHPp6mVoNAOdc/X6VdKJ0PPQSaNNDxw6n5YQwh7TulOzU7S+5e4dCRUtkoJRMiI3ed8hCSpgg+1jAjKTodH9IlxoIah2o62uK+OCjFM6QKOUYjlbnoOPuLh3QKLz1ek6FSAk20kzwQUnaqZ4f7evzum3216IyLEjCHcAxwXx6lns4gDM2lk/YjMxCLSLWJDLTzHKRpJyDb2iaFGV1B1nYhLyJO8J0h1468BRp57qkrZ1DBLtFEnDdHiOm28/Klv4/aqUBIx2OV4PZn1eqdnn63z9vaqzOzPB0bvpfqbyLoKWLsW6M3wDARILIytb7XXvBVEQ2SqGRcbn6YTeUThmH3U8FKoToFLp5vgyPibILysbjec6x18VjwGHkHNbGQH5FuVEZRSaTRl1eQiJJHAHraHeAj+FoIVLE2AeNxBfb7MLzbZY87czXLsDYYDK94OdoDpQBwLw6jPo4HGAc9J1sjqlKk+hnSVrTqBDxWeqVhXM9Bo+GRCCuOL6/ACuOi1GdPIo2qBxSqPxKO+wTuISGm8xocW7El9tY8wy1jfkfkawKS63OJUhfNiWCoNFkQwvoA0JodlFaUkNdz6g2ymlrajbisIkOJ1SB3HPTZIBjVc45bDpCI+jUQm1Hsr4KTgMijooUjWMwZVDsC2VHmDNCPQ2rYe7tu/k297wvYxDw6PWLmFrdi9TB7MAl0ZOuQtw+/YdeFcJHwgtPJ+24S3H3s3K6rVcObyAEJOpfQj8jw8LeXoW4Gsu/Qoed/gx/M6dHyQNcw6NBwqd8S+/7J/zQ6OLOFOXnAlCmj1dnua7/vS7ALht6zb+09/+Jz568qP3+d797kd+l++6/rt6ifN77pkTZb/6qq8mTwZU7RTvK0IcjXSApSPGjvMxelfT2AbnHS44DgwP9Ns5PTvNodEhju0KsfjQ6BBnqjMUaUHpSgEYQUDNItcDRDI8a2cM0gEzO5N4gGKFzWpTErCbXQlmjKOs5WKZcT7GlfK5TXUqhNvIOZm1s54s7LwTlX0cF/XdHaX7xRzoj+nQ6BAnpyelQ5SGvqvSH6tvyUzWj54WQUMHnPIkl2OJQKRIi3kEQgQN3bit66x02xulI/YP9zPOxmxWmyQqITHJnucqpTg9O93zbxaJ0Ap1n2Te7vitt/NRFQKATs1OMc7HDyoJ+Hxn5nz9X1Bng5nPkTfjIgG1B0OLiiQPoRJ+ibeAE7lz9xhXRkfdUzLC6cFMGkdFkQysjJCAbRn5K9F9t53RZxoh2T8iuY5AqDoduS7iD6NciQqWzKQkvkbZbXyzA158ZxQKnQxQdiJgxtXz2UMSYwu8i6+n7I8xlPcQ6jPRS6clVcwdgztHT53jXYUKHu0aWlfThoS2Og7eYprTmAUgE9J1mvzCPafao5noNYJOscoACc4MIcyl39o2eFdRek2NpEGjxNCu8opdUqq27i12jA740KKDR2OxgFcJQRkcmt12wlbbUPtAmo6pQo21Et5ofR3J2QmOwCk1oNRjJskKrS5ww4tQRkeTPk1rlrEqxyUjAhodwPmG0Jyh0kO8GeKTEdo7gmv4q0+/ibcdfQdvvf2t/PTb/x2lbZgFuG37To43LXdaASFdQKINcHT7TpR3aJ3jkHTs37jpdbzqw7/HL7znF7C2IkkycpNz+/Yd3HBcEorXB6s87tJnkg8P8IQjTyIAjzh4Hf/maf8Pj7/kyXzHl30HWhsq2zAqVvpv4fsG+3q58fuOvW9PZtLB0UF+5Tm/0lvU33Dshn7xs85y4/Eb+8d+9VVfTZIuobVm1UiHom5rTk/PUNqSPMnZP9xPohLxKvHi8zJtphwaHeq388N//cO866539Qt6Z2SnlWYtX+vBg3XzjKKu26JQrOQrPWG164LM2pkkfVvhkuwZM6HmXQ6tWc6We3Jvx1UxyvQk4q7D0nVWOvBSpKJ26roaRs+f00UMKDWPBeg6Ll0X575qmArvp3UtFy5dyKHRIZbz5f51gSiLFIrlYhmtdM9bUUqxlApZd6vaovFN3wHrntt1srrOzCKXJjPZHr5MV1mS9c/tCL9dvlP3fjyYdR7MnK//C+psMPNZ2p22FK5KT9iNt3svgMXFxb7eERVSuy2ut3Y256J0Y6XgBczUm3GkZMRtNzgBDcrIbR3Y8V4AS70hz9OpHICPMQVBEqOxU+n6QMwVAm9yCiV+LqojFLsWHyCgMa5BtbvyGrospmjhD0kcO0UQZTJwU0KA2pe44LGupdCJBESGgPLRNFB5vBUwIyZ4HutbAWTBUVRH5+d2cITq4LOY5BfveXd2tNjre6WEvKtSvHfUrai1dGjRtDhd4CNXwGMIWksyNYE6WY2z/IDROalJossxOBK8ymQ8pjStt1g9oHSWe6tdNuoS5yy1lW/4zkXVhzY4JTEB23pI0AnWDMQULwiQCWicFhJxqwqcypiQsjk7gfeOJh1jin1YlaGU5wP3/C3vuPvdfOzULbz5zr/pz8G2h+MW6tg2+Y/P/A886yHP4aLxhVhgt5my3WySpQUe2G13+cDJW6gD7NS7/Md3/hwfOfExXHB89ORNdHTqr7/qaxmYnFzn/KvH/wC/8w2/w7/9ip/hIWsP4Yee8KM8/IInsFvvMLMzmsgDybR0Bi5c2gs6AR534eP4pef8EgfHB3nelc/rb//F9/4is2ZGZrI+u+iy1cs4tHSIJB2SqIQsSUh1QksLqJ5n05NwA1gnQKBxDQdG885MZSt+8i0/2f+8b7CP2tUsut52fiynZqckeTrJGJgB42zcE4C76hyFt6otgB7YdFyXxW4JQGKSHgBsVVsUSUGRFH04Zaee6kBGl7s0SMRZuJNk92844kczaSaAdFt6bxfmPi73Fc6YGfHT6RyY1wZrjLKRTIoXsrE6kLhI2C2bknun91LbmlkjsSCdvHxRtt11qQKhdxqGeZfq7OqA76SdSPAo9J2qDhQ9mHUezJyvf/h1DgE4cl5cdd/k4GYz8mGiJX8iVuO028Jlabalg+HklxDpQB7vyoVuziIhOMQui4ok20rASb0ljzGFdErcdO4Ts3trnAWYCFy2AEsfKokSwBEimFEJ6AEKL+ZwXpRJvt0V/oxWGDdBNZuEBdUQmNgtqubjtG6/aBmD+YCJxnNt0NQ+4AIoX1M0J8jKY+TNBkV7EkMrxnmhBgLK7qCjxDpg4OJ/Rp0t45XhnvHjmA2uYju7mDpdxaoMa4YEpUmVJbgSG4LgQTUmmAxvhjiV0oSMJliCygjJkNqMJRHaFKgAA7uDthXalbQhUJLh0czIaXSO9w6LotQFDQlOeZS3+BCw1tK2W7SRP6SCREXaZCTfzFWGS1ZwegAmIyiFDQrrHVYl3FVNeOex9zGtxahwmC2R5AdxwVO3Fe+/590ooFps9MV/4zvLv3/av+ah+6/BKcPB0QFRHgW4a/MOvM7xSnP39t04pIMD8NETH+Kn3/ULfPj0p/nY7gkh9wIP238VDocxCVlS8MjDj2KQDmVxRmEJ7NS7bNe7wi2K4ECjObJ0ZM9HIzc5//1r/jsgvirf/uhv77/xn5ie4KMnP8rL/vxl/YL6xCNPZP9wP1oLwTbt+CHSK+zlxBotkQ4x3PDU7BQbs41zkq4Xa32wjnV2j3QYZDGfNlMqW5FF4rhRplfvdOWDFy5LXOY6sm6q054TspwLb6YLVewW99a1fdeo6xRpJYqhzpSuI+kuRgHcO7mXsi33KIa6NX7Rv6XrEHV8FWCPIe0gGfSvZbveFmCmkj2vr7JzoNjtSyvNpBU33uPT42zUG4CowoAehAB7tjVIBv35TU163wBLZ/2xl6185jul1Ea5IYT3B7HOc2bO1/8FdR+dmWZTgEUygmxl730wVzB1nJZ2R0DEIHrU2NkcCKlCuizBzzssffcndiu6kEW7FZ1wjdznLSSFAKM6iPxaGaiifb9K5rwdV8W/MVTSZJCMhOwaYhq1LdHtLg5QdoJL1gjBipBbpejmXlS7E7frIF2JnJxaRlL96xcVl3dWPGkAhaFCFF3WeQb2FNp6qO/uT98Aw05+RLaXBpLq3v4+mx8m9W1UzARQirK4mKY+jVUKby1oQ+JbQnAoF6idHLvPRrgo9W51gddC3nXpKs6M8DrBRSNCFUTVlNgtkY4rNU8rNgMmzrOqhzhSnNLSEQrg1YDKbTKpd6l272XsHEpr6khWVckIhXRjSAbiwOvF3djFscFWO+NXP/jfmDhHc81X87j9VzJIMnwyYpiv8P57/4RTO3eyYmDqofTgk5z/99n/niv3Xc0bP/GHPPnQw3j6ZU/n1OQUoNk/PNDRvfnUmVv4ysPX4lTB7bvHaIMAoG65DMCvf/h3OeWFID1IC3KT472nSIa00dlYK4OJi+TU1pTtDHQJ6YxSGZZTGVlctnoZLDTWLlm5hM1qk1kzwyjD1etX83PP/Dl+6K/FNPW/vPe/7PmovfDaF0auhmaUjFjKhmzM5P1Q0Um2bEtccJyZnek7IWVbspwts3+4n/3D/Xu8ZbrqujadH8oiIbfjimgdbfX1ud/Lu8esDlbl2nAtw1QURJ3LbWpSLl+9nFk7YzlfZqfZgSALeqITKlvJSMaJXDlVaQ/kUiWL/lK21I9tQMZNw2xI3uSsD9Z7sLJHuq2iHDuqneS9DT2gyBNRVZ2encZ6y0a50QOOLoqhe2yRFOzWu+zUO31mVKITqrYiNzmJThjnY05ORSXWgajudXRA8MDoAK2XuIL0PgxCO96NC67v8HTnpwuffDDrfGfmfP3Dr3PGSnMV0DkhkT0YcfI4lUhXpVMthfiBnN27oFZSsbvR7B0vQRzhBHle5+mChnRVOj5KCYApT0g2UrsDs3voIwF8kNGSQrZfnojE4mkc8aQEcrwZyfaj8ZxyFUGBx4HO0D5+C+wjEiL4UgIQBHAl89dnS/AW50MP7JSbsHT0tzhy+k85VH8cfR8qJI1jtT6KdTNcs0O6AGacGsZOjyIgac6NayVZOqTS4bAej6FVmciufYUNjqANpEt4nWOTAW1SUKscpTMUDk8ipzdAEChHYjJSpUhQghtR1N5jTY7TuYyGlCIAs7ZkqgKtGRBUStls41RCpXJKVaBUgk5HlPkFqOIAKjhRuqiMNnIvAG48/hEmzqGAP/7kn6GiIVpQsGMDf/jx1zOKX8afeulTecljvofffsHr+eqHfg2pSXnOlc/jkYceKd+itUaphH3D9e6q5dYzn2S72WUXza27x8WU7yysfrra4HR5mgCsF+skOhFZclQaiYJJkagUQstuU1LZGhskb6mxDW2QcdP1F1y/ZxG6et/V7NQ7Is9VisY1POniJ/WjlMV6/lXP5+EHHy7f2CN3RSvdjzSMNgyyAZWtsM7uAR9An8z9rY/81j2qpq4ODA+Qm5yVfKU/xs7nZXHxzJMcrbS46MYvNouGed3C7LzrAyaB3k+lSAoOjg6SJzmDZMBStsRyLvyZ0orTbmey142igJ7Ea7SREVCsylaEEFjOl/twy+58dF0kjWan3ulfE+ztzCyOwLoOkg++5wQt8lO0EoJzZStxBWbeRQkEVoqVnq/U3QbzcVV3fhKdcHh8+JzjXtzPIjDrzkG3zQebM3O+M3O+/i+oB8CZ6cBMsy2eI8owT8w2Mo4xS3KbnQkYKdaEkOtbAQFpMt9HtiKBjnZHCMHtloyV0NKR8bFL1JyWbaOFX+MbGWnpKgIhhCuTrNB73bgWQo3XmcQIBAjeyjeQYPHG4BGnWkWLdg2mPinjLBXi6wuioDKDeFvkxOgMkiHBtzgFhoxBdQfqfvJVRFMxP69L2zec9Q4YQrYK7QwbM5la72SapQyKQOs9A9WiKPDe4pV8m6pURkYqezBD8mSF2iTgNQaFUwYLTNuSZSU+MYkuaHXWH5GmpXYNjXPseMcEWdRrleGUwhGYtTMKrQCNbSe4NMEmI6wZgFdULrDtGtbSgAnSjh/kS9x94mbefftfM/YVN27diwNSJV2Xm07dzJOOPJE33vqX/OYtb6SwLZmGRxx8BE+46ImYlWtITSqhkIDW8wVqYAY4lTAwA9aG+9ienOHu7aMENFtNhfWONsBTLnkqL7r6uXzkxIf5vY/9fn+1B2D/aD8Kxb7hPtBC5PQE6MYubUkbHAFRsihvZdySLbNdbXPh0oW8+BEv5j13v4frDl7HCx72gp6g2317HyZDnnjkibzljrf073emM77v8d+3Z8zScUsSk+D8nFhqlGQKdQteF1S4UW6gleb6w9fzhIuewHqxzive8gref+/7edShR3HZymWsDdbYP9zPVr3V80y6xbgDJ6N0xEq+IkqaeHIWXXu7BbfrOnQjlPvkeaj5+AigsXIdpCbtFUyr+Sq7zS7rw/U+CHKYDslM1nc/un10i/7ibUVSnANcuuMxmD4RfNHJuEgLlnN5z0rKPREDiyCiOzdpkkINhSlYy9d67xiAqq0obdmfn/UIprtz9ZmIyYuxBtrpPefvPJg5X+fr71z3wZm5v9oT+hg7F8EKoNAq3q+kW1GdEABTlPIcWwqJ1k4in6VTIgVopgJY6jOQrYr0OTSg4zecLo4gNFCdke0HDcWqSLv9TLbdTiL/ppBk6mYXp3K2giLxDUOdMFBxhBVS2R7SeTExIRkfl6KQxM5MAvkK1APQEyATwKU0zlkhzvodUrt1n6esHF0LdoYJDdn9pVsnKwRTUCqo25LUN8JFMcNIbi5pMRShIVFeZvdaY4OiMiOCzsmSIQWGSknidKsUtStlQVGBXCe0XozIlALvlQRGKo0DKtvgzIBd6yntFj4kOJWg1ABFTfCegMYHR2h3ac0IkIW1RUjVZQvjdIy2JUYlaJ3xptvfzL2btzPW8ziAQoFTcHJ6L7du3sb/vOkPOOngMiNfgJ92yVdA5KaA6n1OlDKMU+FoFWnBoFihApaXLuPE9hn2m8AbPv0mxtlYRlTAFetXcXh8IVvxW/cix/Tw8LBsJ5WOU1A6hrALYDlWbQNQqQFrJsXkawyzJQbpgNSkpHXKN1/3zXz7I7+d2tVYLG0bTdO0jBRqV/OEI0/YA2ZecO0LAFnkU51G7xfpLlRtRaLFEl8MBcVptpP/5omMxeq27kcana/Lrz3/1zg5PRlNE8W/JdEJOsx9ULarbfFbIfTdlyIphADb2TotjFC0FrJr123qOh5L2dzorXPsnbUz8QyCfmQDe91yl4tlRtmIcTbes/Avkon7yIKF21IloM9oc5+BzYHQG/Z1+1z8d/H1dmTfRSJxf1Eg3Kf1wTrDbMggG6DsvJM1szPyJGe33mW1WL3Prtv91YHhAe7ZvYcQApnO+ut6MT38warzY6bz9Q+/em5LvJz3AJazH7twXwjSseg6IUrPPV6aCCqChfKYEH/rkxJBUJ+R55tiroQKTUy0bqA8KZLt8ji0UWLdue+6Rro3bQySDEo6JQC2geaMdGjQohZqd/H1KRxdFlBCGTs5qp2IcimEnu8hQxUt2UNa/i+ut0HOixnKp957cCWqOcl6dSvL9Z3nnKqGlO3sMjkvwVElK1TZBeeeUjQ23U9QKVPrKZttvKtIQovSikCKTZfxSmE7WavSGDwuBILSeDNABNstzjdoLdyI1lsSo8l9jQkejcNFQrTVCY0aUCdDah9oQ4sFmrZkFgxO51R6gDYalywT8FihUIPdobWWTOcU2ZhRvkxC6LNviIF7dXCcmJygCjDxcK+TGICoW2Oz3uV/3/pmtj1MnOBhpWDfaL9M9pRBK0Vt68h1SHuJq1IKkyzRZstcse9hOOCMg9/95F/yR59+K5MgYOaC5SNs1Fu9VHkxlmC1WO1ltanOhHCrDEEnVL4i19Kp2TVjdHGYUbHG2mCtHxnkRkY02shnZyVb6flHWs35KNesX9Mv/lppnn/V83teSdeZsUrhkG6JXKKhV8bY2BFKIlG4Uyd57xlkAwjCNZk0ExIlxw7Cl+m6OSCLd+OansPSufR2HJiO7LuoFNJKRjqTZrJHQjzOxv3jOnCwW+/2JNkusqA7Dx1PpEgKhulQOCwLC7hSqgcii47B3b46DxajzDljnNzkEty4ACzOSdGG3jm52/ZiN6RICvIkp0gKxtlYFFDpiIOjg/Ja4y+rTm6/+J58rtWNuTrw2XncdJ2rB7POd2bO1xemXCOLf/zW+aWtjr9iokppS7gjWRzZhMDcibedj4h0x3c5ywHYx4BIV8uqpeI3PtvSO/mm69GQLhJ/fWcyF7s9/XFpATHBgRe4QRPJxlnkCQRkFGS3QHkZE/km3hHwQaGUg5CitMy+lQtgolFe9GnB12g/w7QnCMygOBy5OHbeSUrGoIc9YFvevAFzduDj2j+h3L0H46YUyggBOZ7jaX4hpRrgXIXK11kOFUoZvFnCZctUQVxaK29IaQmAMQUQqOqclBlDwJsC5UtMUgAGkwwBUVQZoqFeP9hKaYJFKYvBgSpwg8NM20BFiUZJorUPBGXQNFjgHXffwN2t5fnXfCOHly/h1DYCaEKgtjNsvcNSvh+lDeiMRKdMmglFUpAlQ1TbsO0N282EBAExdRBnoB0PyxredeYupq6hCvJulR5GGoxO4vsfTd7iIjTOl+Q1KkPjG7wWgs2jDj6CYTrA+xIf4GR5hhUtHKELly/Bul1GOmffYJ07Z6JQMcpwxfoV/SJuTPT8IODyA2g3oxikDKYnyHUCOmFtIOqhbtyS2KRX76RJSppIZELng9KZtqHhWx/xrfyf2/8PL37ki7l639V7FlLvPQ6FczEzKJrmychpLgdWSEjp4kKfCIycW/hH47YiLXo5cKrlPh/HV93C2fNiIhm3AyVdZ6bbZ+cBswhI+rDGWGmMi3DekZmsHzF1PJ/ebwbN+mj9Pnk+ucmZMGFRpdQBzhBC7xLcjaO6WhussZqv7vF3CSGwb7CvP8ZOSt0d0+I+QEDPFetXcGp6irVijY1KSMNGGVaLVdIkZZnl/jmd0d4DGQ8phPDsg+fA6ACnZ6f7IM0H2wH4fGfmfMlibqfzDsfnU/XpmAD9IMjzuuN20T+m3aUPhGx3ZSzUP9btBS8EGR+BdCCSsXRHZndFAnCQMVB03yXUAoy6b1Cultc8u1f2FW3+UYay3mV7doLKxeTt4ETVZDuJdxBQg4tclgJmx2XUVG3Sqae8Cmg7w9hduU2nQEsgwcyOMtx6L7q8Hcq7yGa3krgd0uoe2LwBMJCN5Ng7zxkdJdm7Hz8HyNjsABUGlHQoKmdpgseTEmIHwKGw0V3XFkdQpiCYFGeGOJUQfIIm2gHqFJMtSfKzCmgFFoNSCVblKCAxGZmR/CWFwSvDsdkOd23fK9b3ylAmS5hQy3hJKbwZsKmHTM0IhyE1CYURsJj7mtu2jvLuU5/i05u388sf/C1C8IRgRNWEp25n+OD52Omb+Q/v+o+8/C3/mjfe+kZKWzK1FU1Q1GaFl/31j/dDy8tWLmVcrHBofAHDYp2TDs60DbsLl9MswKXLR/Ah4FWO1obaSwci1SmjbMTyYL+ACgVBZzEkMOMVT/4JuaSYD0pXi1XWhvsoXcvUTXnG5c8goFgtVvnBJ/wg+4b7ZRE3BqU0NlhRmKCgOITWBpOMyRPJRqI/VPFHSUzSd06CF3JsohNWihVyk1O7ug90fMShR/Czz/hZvvrqr2aYDklNSm1rtqotdpvdXiqepzk+CF/jwPCAdGN8DExUqgctGj33Rwn0tvzdon1gdKD3ZcnTXJQ0CNDp/E064NN1hxbjBBbdbrtywe1ZwPu8Ie9YzpcZpTI+Wi1W+3DJzjnXBdePU84OYuxqcbtnc1qUEg5RohP2Dfad89yzk6c7gNcBUAlFXQBp6qwRU7x933Bffz6MErl6ZjJW8hWRXUdAsl6s7zm+z6W00owycRhezpf7zk5u8vs8H1/KOt+ZOV9QnZRFMg1/986Kbz/7Y77gFbsvrpH/11vSlVFxnu1qSCOpcA3cwgAAyHJJREFUt5NXewuJnrv4umr+2nUiz6lPQViT55g0dm3k23bf6alPC/ixO/I3WMj3AZ6m2SSYgql3oFoKkwqICVa+RgRR5RCbO+LQO5PRk9sEO6LSOW29TepApwXBGIIaoMIWg8lHSWtRE5lNIeTu+dVWn4Tjfw5H/lm3AwFe6TLYKSEGQi6WHV1BRgdgAgZRcrl0jDJr4HYRrZLGROfPBsBbZs2EEkuiYuxAZ/duBmhX4kMgBE+RpFQhYava4aOnPkUzvoRnrVwB3uJDS2U9f33X33KJAc/HuG7tkbLC2xpFwHmLVTkNM4ISb5Vh8Oh0lbudw+mcO7ZvY+LghAPsBu84cTMPL9ap7QTtIQRHEhr+6JY/ovEeC/zBza/nltO3MCrW+ds7386h0UFOVNscNpBqeM5Vz+P569dzZvNT/OUn/5gz5Ya4Dof527hvsMKzLn8mtW9oTYbN9uN1Qo7vF5alpUuhPkPQKV7n/WJyYLifb77un/Ham34PF7tAl++/jmk9xfsEr1qefcWzecJDnsPVBx/NJ858AlWe7LscuSmw0SStshVZvoJPZvhkzDAu4l11sQSdGsc6Oze1i2ohrTVb5RYrxUr/nG7BSnTCKBnRupZRNqJsS0K0wy90QR0aBukg5lTpPSOTDghkSdaTaruxRefo290+zsYMkgFb5RYm8o1m6awPmPROsosSJaCsV+ZEkNapejpJs0YLefUsPooLrvdX0VpAVjdu6rpFzrs+16l7LWfXImm366jcl2Q5T3KWsiV2m93+tkUwsziy6Xg3zrtzTO/ua9uLwZRdrESnAosPYClf6hV6DxTMdP92JoKDdMD6YP1BD5s835n5x17dAg9xtPF3rS9SqzEEAV0d8Npzn5jOg5LF2jdzQzyY/7/jyriZKIzaidzXGdXpNJrjWelUtbsCWnwlwMjN5u7Ai2OlYGLnxQvhN1ujtSW4huBK2mYiLevQyvgreLwPVDqlNANKZWRFdCUR5Qh/pp1QuVYmV6ElwRCik29R3dYDmc9Ys7vg7tcJmbhLALcNtBsoO/9F6nUBxYU0a48FFFopHKoPCwxmREhHYokTQJYfTx0cBIVTBcq3NHZKGlqSJEH7FrBonaCAjECrhqh0DfL9fHDrLk63cPPpOzlTbeODpnU1m+VxdiI35ej0NJuTe3Fa+DauLWl84HQzY6va5RObt3HH5ifxPmCSnJAuYbTixO5pNj1YBZse/viWP0YpQ5qNRUbsHLNmyr27x3BhLn/+0MmbeNvRtwNwYnoSD0yDjJWuOPxEjDFYpXoLexvmXZSffupP8Z+e9QtccfBRkb+Vozspb6DnXwSAYj8+W6c7kwbIVeAJFz2BUTZmy8PtFq45/HgZc+gUj2GQjlkZHBQQ6RpQujfAK9JBz8voFnWVDCF2RFrf9ovkwdHBuQtuzB/Kkow8yeepyHGh7Bx0uxgBiN/Q01EvSRaQI87NeZqTJYN5CGLkCHXW/lrrPuJgrVjbK00O546IuvFRnuYEQp/67LzrgVe3D611r6BSSu1JsR6lo95zZhF0gPje7Na7PT+nC8jsXkP3c6fyuj8A0N2+aKR3f49dypc4MDzQd8wWAcwisFkEkJnJep7T2ZyZs/fXnbtFMjTMicj31bn6bNW7DNuSylYcGB3g8tXLOTQ69KCrmc6DmX/stdhJeQBEsPutLxYJLEQDOtfA9K6946wOkNmJyKTb3Tm3BaJzbzUHM76JIKWek4VVJMq2W0LgbbchkmnJ90tHpt2V7ourYk6Tk4eYLinbQr4K6RqzJjrzhkAINUHnOBLhuQAVmjoEzpQ7nLY1pWujN0yIhNsQR1JTcfQNHuMrFB7TnLxfCTVAkx6gTQ/Ob5gdjSqpGDY5u41wZh4UeCa9mHrtKXD4q0APMFEtpLFYM8ImS1g9EBO0YGXME2yMB2gJOkOlQwKul8vKZeDR1pIERxkUzoi5nE1X2FE5W05YMjbAxzdu5ZYzt/KbH/kD/vgTf04DNEHUQ6//9FvxOifEkME6BM7Um/zOx/6Atx/7ADec/ATvPX4jLigx0XMVx6b30tInX1GVp3j73e+U7gGOgOO27aO0Abb8HJBMvRB9QUBMB5tf+ph/SUgyTByDXb56OSCGdt1jLlk5gtYKb3JaM8Ylw3580jnLLnYpZGzQeYpA7is0mn/1uO/j8n3X8sJHfBsXLF9AQoJODMX4YigOUXvbu7/KFRpHHjH/Z32wLoGLzYytaquPBAhB1DD7h/tZKVZksVeJ8Cq0ITc5y9ly/w1eKcUwGwqhNBUPF+/nQKM7BogKnbjIiytv2mcm5SYnhMBWJd0Vo4yALRW5HwsE3pViBULktMTFuBvtdNlLnXndtJ0yaSZ9VELnb9ONP2CvNLrLleqOv3uN3XvR+rbnf3QgoOtqdP/vfr4/g7hFSXanTFoENmfXotvuIuekAzaLwMkFx9pgjZWYr3U2qOpef9ch6YBZt91ROqJICw6MD/SvefFcfC61eD43y00yk7E2WLtPX5ovdZ0fM/1jr0Xr+y8EgeuLRQLruyol4AVMRAmlLCdeOif9twzPPLVa0YU+ivyyoXCNkE/biYyK8PKY+rQojXzspIQgICc00b8lESde3yDSaCt+MF4JF6adwtJYyI9+QmU92paQr+GTZUx9BnxMtw7QKoMKBu+baLgnjrN0YKCdIF64CpMvgw8kZ3VktkfXSdu/OUGrU+r0AkywaJNiqnvk9G19CJUdJmzfiPJl/6u4VRkuxG5QskYwGVoZIOBQpMFjk1Uyk6NxNDrHqgFaNXgvZGlnEpTS4EtU0ATEtVgpUKGR16oSajIy1eKU5u1nbmbTR9aSgnfe+R5WNCRqTrSdxoneHZMzfOzUJ3nkaABKEQJ85PTHmHlP5eGIgXtmmzTakCQpd28dlaBGBChFZhQfOf4RnnXJUyR52TXcPjlFi4CW73jki/mtj/wuIT7veMSpWTxR1x26Dq8yEuUIynDl+pV888P/Gb/20d8jU/AN13w9a4NVQrsh59YUeIp+oV1MWg4xKd17T2Au4c2TnOADjz/yBI4cegyzdsZd23ehtGKYDPcsXrv1buScdK6ySkjHeu4Mu9PsMGtn4g4cfUpG6ahXJXXy60PjQ4yzcU+27YiqnXHbIBuwEUnH9zdi8cGzUqzhYhiiNvJZK614othgo7ng3GvG+rlaaDVfZd9Qgi/XB+tUruoX7K4bYrTh4OggjW0o0qLn1nTnZZgOpculjfw6CI5BMiAzGa1r+/DIUTY6pzPTVW8MF+Yp2N3r68dMn6Ezs1iDhU7ZZ6puW5WtyNpMZPZnjeUWqwPHiyZ2ACv5Sq9U6rxslFLs1rviH5NkLIUl8XNa+D39QJx794DDszg+D3ad78z8Y689HJfP8+Lc0435Yl3gi4qjsyIF+q5NLeMgHYMdq1MLzwnQ7jJtdpiWp9ie3An1NkyPCuel2YTdT0m3pst0UkbURb5FDPU6vk0DoSa0JeXGh7GzOyIXZgZuRmhnhHZH1E+uBiXf6GZ2l9DuEGIWsw2KkAyEmeJLISy7RvaphAOkfIXTGdpVJKogtGcwfv6N+OTy42iy/djiIBz4J7jlhxOSESFJaMbXEGJLWU1vg/J22U9/Rg2b6UUoJGaAwTq+i1DwGtC0QRFGF6PzfYAm6EyiBpS46yolXbEQz40Piso1OKVRIaCDAyQuoPUNIXjee+KDvO/eT7DhYMuJHHmR9NoE2HDyt4ojnjff8z48mlQX2AAfuvcWfAQ9p5yEON5e1tyzdSe3bd4qU7sAP/6kH+PC8WECsNvW3HjmDqwTD5y7phv9Pq+/8DH83j/9Pb7ncd/HMy9/Jq/5xtdy8fLFNAH2L13MtYceR5auyMgnSpqfc9VzuOE7P8jvveB1/NNr/ymNrQhxsfM6ZXnpCJ082QffczZ6B1Y8S8UKIQiHolvIZ20pi1KgX9j2Dfahlaa2dW+Fr5Qi9ItdwJis7yh03+w1mrXBmtju50tkSbYHkHTyaKNEXmudFQJsvipW/AhfpO1copUiMxnDdNiDH5CFP00HDIo1ghmgTI7zrlfMyMRyTlrt1ESoucy4Vzgpej5I15npFu1hOuTg6CCFKfpuV9d1GqZDVotVLhhfMFfsKLPH0bYj9Z7j4RLPl9HizouajwU7o74+T+l+xjtn1+cqVe7AhAuOzWqz7252953dCepl6mcdxyIBt3uPQMwCd+vd+baU2rP9B+oP0wGmrmpbs1vvUtv6AW3nC13nOzP/2MstXIBfkBHRF3HM1JXvOD42AosIOFwjAMQMBBgkQ/ogyHYblKEtT6DdFOWmiEw6qoZc3A7RkA4vEmaMKJycnUu/Z/fSesekmRLq0zQmZyU0dHKO1teUzQSrDMq10p0IgeActatIQkDbKSHU6PoMOnhoSyH/mmXh7mgtYEbJd/c0SdA0DLY/0p+GzeJKWrNMhoOgCe0OBYY6GUqHSGU04yvJdz8uT6jO6ugMr8Q5i8HEMVtBCC1KZ2glsQNohU+Xwe7I2ExlWJWhdUoSz4fTWujFusAjhneoNLKRFUqnOAytSrGh4fYN6ZxUCFjpeCchSINLIf0pZxJ2vSVX8IntY0ycwc5O8qETN3HGR04wAn4mHn7pw7/LUQsXRMW9MQmPvfCxXL18iB9/0w/hgVu27+Kho33UKI5NJaxxOV+iGF7C0vAQX3ftC3latcU4H/Oq57+KN3ziDTzzIc9E5asMnEOX0llx+T5Ctg9Mwv7RAXZ372ar2mB5sMIwSRmmB1AmozBF763SqXe6haTzWCmWLiIEy0q+EiXEuleypCrdo5xpvaR9tzEDS2F6XkjXpbHe9qOiPM1pfMNSttTftxgNoFWXUO77EZjRZi6FVrKAN7bpF/LCFOwf7u/t+IGeX0K2jldTlNvuwYDRhgIxtRun414h1fNyurU0ghjxqZmbsPWeJnExTkwiqqA2YdpMeyO+Ti20SNIFell2vBqBOX/k7IW8A3Udd0cpJZ+P+Bo78PSZAECXX9SNfT5bnQ2M7MKIfFER1cn7z5Zj3+9xLICbWTvrAWMg3Oe2PtfqgkdB3q/KVkzbKeNs3PvQPBh1vjPzj70WuRef94joS9Bu7I8tkm5Bjr0j93Yy6mQgah1lYkclRP7JLD5FJNIhuNhliRLpOIai3ZaRUgjzkZbSkC+JRJuAC56d2Qm8naKCxTVTMbqLydlNeQwVWsRv1qGCIigNMWHWR66ObidoN5PjCB0wc/LLXUu4ZYjW8gYDdkJmN+XldoGPoUWHGh0qfCtjtqRYj2DCUK08QXKdFk8lirvGX06th9igUDpB65zQucjqHE+CQ9GQ4swSJh0DssgYkxPi/VonNDhJoyZHhUAwKUrngCYxkSirUlQ64FS1wyyKz8b5Eo+5+KnMIqBpgcPjg+Rx3PT4C5/Mw/ZfLbyQAKfqHf7i2E2cdvM+3aXLRzjp4Q4r3JdZkLHRJMDDDjycw+NDXLXvCnwQ4LPT7NKalNPlNrVzOOCKtSvYcS0+kTGF845ZM+OxFz6Wn3vWz/HoQ48m1SKR1TqqbZRh5i2ta1nKV4VvQUCnA5JiP2ls83t8L01GddyS0N8HMMqXWMlXuHD5wgh8mIf3KdUv+sN0yEq+wjAd9llHK4NVEiP8DLNgw98tVt3inZq07y70nZmO/BoX+0Qn2JgG33cl4mOsj9lKzImni6OKTmmTmQyFWgBYupeAg4CrYSYS/65bA/Tb7pOvw5wA3HcR4n6F7FyQmYylfKknM3fVZR91tVVt7el+dNtaPAfdPhIlUuM9BFw1967pzt9nAgH7h/tZLVZ7A73PVmdLmrvx2+LxLb6+jnzdkYG7287Z7oL78CIIm7WzPtjz8wEziwDqbLn4g1nnwcw/5rqvgMbPazsLz/uiGSd1ACYsjJkWgFjXYTKFgBKtIapFqDdizpGMd4KKfiu+iSBICZjQCRBjB1wpt3sxcoPozRIsToHyLbo8AUDSbEtEQQRPIVi0EzKvUpqQ5CjXoOw0qlqchC8SCCQYO8V2HaYggEj4PaD8DO1qdGhR09v7l1vpJRwqCqocqq0ldDJYQn4RPlmC4iBhcIjZoa/acyZbs0LQKQ1JPKuGpp2y21SgNEonBJ1jlcGh8CbFxDa9ClbM7ExKpcc0ZoTXOaiASgeyvaAJ2nCqPsE7jv4fPnLPu9jVA7QuuKMpaYJ0VZ595ddw1YFH8tCD1/KQCx7Hdz/+e3n65c9g/3AfX7Z+Kc+9+rlcunwRATiYwJ998g00AdogPBsUPOvyryAgPBvkXcLF7X/11V+HMgnjdInEJFQedqptQvBszk6SKHnsFfse2i8oRhlmrRBnt6otQgiM8zGHxodYypYYGHGrNdowrafYYCnSEUv5EvuKFXHQDR4VU41H6YjEJL0BXaeU6QANgIqdEKMNg2RACNK6r1yXZi6L0CgbceHShXjv8Xh26h3S2CXJkxyj0l6K23U4iqRgJV/h4PAg1lsa1/QkXqUUO/UOu/VuzwXpoha6BXvxODufGGBPhwnopcupSfsOjNGGtcHaOUCjS5JWqN4XZt9gH4fGh+aE3+5PHPEsgg8TeUFnB0ee3XGCOa/jbJLtIojqDATXB+usD9clbqFT+rDXiK87ts+0cBttGKbDz3l8k5lsD/Dp/GwWj/tsMLNSrLA/egwtvp7FOpt4/Jmk5A+0unO9mIG1CJ4ejDoPZv4x1xcKzOx53hdrzNQBl9hpWQQ1EEEH0pVJl2KwYip5Sc22EIbbLYIeSPdARRKvt7JNkxIH5RIj4JxwV0CATgQaAVkAVSdzDpZATZ+RhCa4rtPSoqwAHK1Vn6gdomIp6AIVWkx7Bt9OAAuu87HRhGQIQdN6oUHqZrN/uVbnGF+Rq4AioGjiLxUTk8I1+IbgG9rhpZTrTyHoATY7zHZ6sWwDjfUy2vEETk9PsV3tgClwxuCCJkTApHVMxA6OVClaNaRKlmmTgqAyPIE0XcEpQ1CKxtVsTifMrOPdxz7CrDxD6xxHN+4gDv44vHIJSsFjDl/PV1z2DEKyzCAZ8s3XfTM/+vh/yaX7H8HjL3kqlZczWwaJDLjLwnqxxvMe+k85GM3HWnq/ZQBe/IgX8/iLn4xC3Jv3Dw8wCXCm3sFiuKvc6IaJXL56Zf+LuGxLNsoNps1UyLMLn5Ha1fKNOxXvk0CIMQVzHozIhaUL0wGCi8YXCWGVMFc2hbm6SUVCMMjC5pGxQKbmsQedHX2nfum2YdUCUIjAoFtgOrO0cT5mnI/78cVWvSWXdRDn38WOzX0FI/bdCLSopaLZ2tkE0MY3ZCYT4z2TsD5Y771s1oo1AVWjg+Qm30Pa7fbVmed1HauuK9VxZjpw04GPbuxz9vEugq6zF9rFOIOuDgwPcGB4YA+oWBzDLPJqPpfOzOdTy/lyTxZ2fv66OtCwOL65ryDIxdHP4uPO7g6dncP0eYOZbgQY/m4jqy9knefM/GOu+/Rr+bw2tPDfCDQeIKlsT7U7oPMYwGijq+4C6deL6DZ4O6fF6Vw6KjoTzkm6JIfV7AgRWEm3Q7kpAScLSKcgCog/DDoa5jWQDiMBuBB33+CYlaexrkFnJYQGraBqS1RbUfqWJJE8F0+DApStUUlKGlq0EoCCbwh4vDJgxLjMVx7abSqTUGgrxxICHkejUqY6Jw2BYbvRn6LajNHKoENDp/cIkbRs3AyrNE1oUUG4FfXKI2F4Mc32LQQrdNsqWSG404xMkCgAX+OSISFdxmvhIHglhNegFcqkBO9AZxgjv2htHBl5PcAOD0K1g9aanWqLEASAtMD/vuUNlAFGCpIARZqTDg8yaCpCKvEKlQ847wnKYYIjTXIOr13Ns656Dm/59F+y44Twq4F/dt1LmMzOoBVce+DhfODkx8gULGU5P/O0/z8HxheTaIMyCcEFVkeH8Dv3stvMOF5bjs028YiN/FK+xjARu/k2EuJ9/NMtKpNmIvk+7YRBOhDlUXx85Rpa59BoaleTJIP77Cp0I5puUeyiAkQOLAtDalI8AjLEryXr/WDWCulydB43SinSpMCnq7L9hQW7+7cj1XbHAvN0625h7uIMTk5O9mCmA13d4zplT6ITtpttal9jve2N02A+ikpM0hvOAb0xX3fM/d94jtbyNdIkJTc5s2j6F9T8d0rH81nsUuxR4ES52n12Zjoi9GdYaDvScbdt5+YqpsVtLXYhHogC6HOtxf2c3ZkpkqLP5loEnAeGByhtuSc0c7FG6YhJM+m3fzan5fMFIN2Y8e/TmOk8mPnHUN4KZ8QMz/KSib8wlI6dh88TzJxDHA7w+X7Y7Uzk0mFXPFvqTVj8kLQ70GxRodimYDkfMTDF3FdGZ9HkLnq1tNP4vF1Az7k1gLclOrQCjsxQ/ipi+KRGkrOPCQHYpLTNDtpOqMwyJh3iXEuJopjeBe0uLZpGpbh2irYVAT8/DbpY2LcCneFVSqJz2njswTlIETAW5GfvG1K3LXyUZmt+mrJ1EvX/sffnsdZl6V0/9nnWWns6wx3fsbq6enTb3W7aE21j3DKGEBNiBCaJfgkihExG/LAdxShEgj8ioQSZRIDysyJZ/IRiiSCGTMZO9IsTCGAHY4PddNu42z3a3fXW8M53OsPeew1P/lh7n3vurbeGrqruqu6+T6n03nvPOfvss885e33383wHA8nnBCMp8gJgLLgaOkNUwWhChvymdVgjKRI0sAqB1ilqJ0QJJCMEO8H5Jb0pSINzqiIkVYyr8UnwKdAnEFtjYiBhB26QQc2EWB4iruBxOKYfSboDwXdULLXA09c/QpIaLad4FbqUsNqTzdbzeM7anJn0P/jIfx8jBb/4uf8HrcLEwE61y2J1j6ieP/ttP0o0BY11/LH3/2l2yh0Wfs3u0LVQ2/Ch6x/m3zz/SfYt/P1P/pfUw/vy1M7TGOd4z8F7qGzFw+XDzTEebewh80pGs7K9eo+maGh9y1l/hjOOnhwoCZDclMIUG7fWkVy7Tb4UzWMSEUGLHay2G3Azep7U1NSu3vBODieHm3HT1E1p+zYrpczFMMZxZNSFDlOZDV9lt9rlpDvZjB9GtZEgmwVvVBmNJFhgw6PZTmpOmlj1K2bVbPO8G8M4U1wAM8XgOTPeZ0y4npdzFKVwBfMq/zySgEnn6qeR0zN2H0pbvqQrBBfJstcm1y5wgEYuz8gduVwbzoxxG1+ecZsXQAavXc30ldbl59n+27hvl6uwxSv62Lza419vBMETx0xvcZzB1Zjpm6HCcsj7uRhutgEvW63q1wdoth6jmlOlR5XQS/ZllfOTks/dlhQv3j5KxcNJvt/ii1xwJh5kyWeru6h6TroTFuv75/swLMIbf5lxLBX7TY6SaHb41dgOKqaQx0zFHtg5VAdZCRWH8VJck6IHY0ka8O1jsCVJHMX6LmYMhtRAqm5lWTYRwdPHiJgGxYFG0nCSV1ORTIHRjsoYNmGWzkJ9c9i+QAyYGJHoMeEEyOTfaOb0YiDFfHo2DmxFqzJ0UhwRQANGexRHGyOaEiElejTLeo0jIUQFq4lfu/Mr/F8+9U9ofZ+VTAjWGNROWUuZgxy1x9gKTEGIXR6uCVnJ5CqMtTx3esxCs9KoKWuULbdchT/y7v86QQQVi9PEcTSs1AxKFoOaZuhkOKZuwvsP3w/kLs+3XP8D1AO3ow8de/U+/8sf+Ov85x/9Cd65+zSqSpcC68EgLboJH37mj9OzEZzR5fWSb7/27fQpMC2mGHN+Opy4yQXuybgQHjQH7De5k7NT71CZ3KEJtiG5KZ2dI7ahGRxwVXUTjugGN+DT7pQXzl7YLFhFMUXrG/R2Bq5G7JSYIp3vqO15F2YzkkE4nBwyq2bsNXvZuKze3ywmYwIzXOS2jLePv4/jgcIUhBQumMKNRNyQAms/EITFbcZB20TisTMzLpw3Z9kNdhxxjO68474747g9u70BMOP+jMfqgiR66GKNpnjj48dtbb+e7Rq7Z2O9WqDiNnjY7sZsg8RxX1+rz8xXWk/szLzBDtA2T+ZJ+7yd1/V6thu3zt9vdWfmCsx8M9S2l8wFsu7w98E9NP/tdYCZ7cdonwFLGFx3L1d/nLku3VHODmrvne9T7GH9fCbsLp+D9mG2/98GYQOPwGjagJxVd3zOnzFF3p6phvnHAIT8Mal7QOeXSGjzuCm2eft+lV+DK/KqHBfDqjvOUNYEPCo1EYcXJYYVZTjGxtUQ1ph5MLgJ3jb5FJQUsEjyIJ5kZwgRsCQ1qJ1jIBvOKaiUUN7M3SeNJHHYtGZn/QWqLiukALyp0XKCpwQp8rEQg6YcL7COfvg982kcYxtdiaYmpoAkT9SESu6FRA08e3aHf/vsr/HFo2f59OPPZjec5Klcw1oVcRNEI0FKMA2CktKaPqxRMXg7pXM7nPmeU9+TgL1mj//OB//b1NUujyLc2nkHf+67/6fM6x0SOZCyygeB0lYsQ0unSpLEUXvEwq9Y+QUfvvZh/sT7fpjvuvkd/OUf+t9iixnq5qykyd1GsURGw7Ns+BeGq/wHqwd8x+3vvhC00SrslHP2631iUpZ+uZH5wvkCHzVuZK1jS91ITj6ellNKl4m9meM0IxnHXp3Tj0dOx7g4F1JcWLiBTUhfaUs6Fbyd57FV8kTipkMyRgxAHldVtuKgOcAZR2EK1mG98VCZFnm/RhLqCGK2F0u4uBCNQGJ8fYUp8jhK2ZjoFbagcc1Gzr0NOuB84R25MSOY2eZpjF2E7e7G6I0TNXcNk6aNI/AIuJxx3J7f3gCl8XEjyNx+/ss/j4/fftzl2h7rjJwcYOMIPB63EcR9pd4sr6W2eT2XictvpEaO0uVR1Kycve7tj8dkkyT+FgMZuBozfXPU9gdW43knZvRfsM0Q0hhfHsykkN1x3eylYZTbRFy/yHwVyB2P8XnCMj92s732fD80ZLJudz8/vj9hNLkD8u+Tp4d9deDJoxX1oAWqCe0eZ1LuOMrxSwhnw2vKr+ukP2XdZfvz0p+SCIP/DAMXRzO4STF3ZcbtyH2imMxN6O5TxDVl9wj6x5iQ1UZofqx2R1n2DaQxSNK6vI+2Qu0s+86IQQaZadLAmLSNDIqmuALt2V1+Oo/CtnBhZxpIBkTpgWK8QkUQcagYoiSSkPfL1mjyJLF4jVhrcApqHIUrc5cqJT7+wm8gkjsWj1anPHKO37z/+3zm4WP+1g/9TUCIpsy0KLH0cQkx4Ems1bAu9ggh8MUHnyAkWBt4R3NIXTT8j/7gT/Jbp/d4jxOsa7AY1uJIKTIVkHJK64+yGims0ehRDVS24mx9REiJP/ttP0ptSt5/+AHupZYvPPocGIvaofNjKkzqSZJBqDM1XeiIKVHYkr/wB/4C/+9P/Z/yx1Th5mCuZm3BWX+26cKYYcQ1ckX62DMtpxf4F4UbwM44qhm+Y3v13oagufFMGfxZtq3l135N61ucdZsFvteeznd0sbtANrU2L3K1q2ljy069g3a6ed5xDDPui09+0z2oXZ2B2eDAC3mBXPSLl4yPmqLZRBA44zjtTln2SxRl4ibZf2YcUem5kihpYr/OxnyHzeFLFsjRsG67U7LhwOj52Kr1bVYPyTn4GpVXY2DluP/b23hSxtDl0cs4rgOeaO62DYiccRdCJrf5NyKy8eB5s2tbgTUCzTeDm3PQHGy6bAufx4k3pzff0FhofI/GsMq3WskEV52Zb4660DkZYwFGTxOTuxjjl1Nj7p60D4cuytA18ad5O9sBjpe3qZq7QONjRh5Lf5Q7JOvnzh/TnStzNvcLQ+bR2Elq725lJAFuStbkDq8pDTwfjcT2LqxfgP4s5zOlwX03tIOHjGTCsEZW/Qlr37Juj8lLd8jAauP5krKBXQygLYQF2p1COR3GFAHRniQOSS2VdpRkia1JayT1+NTioyemHokdSQraZNChC4EoSbI5npFsWicpoGrzvqQWu/xSBjJbFXB00qDGkUyFx+TOmrGARbEYsfjoMMQhSiBzDLxt8KakEMFax6RowAjqKgKGTz34LCJ5HBQF7i8fcxbhc4+/xK/d+08kN0VNQavwjz//X/Grz/477hx9lgC4YkowJfNql998/tc3AY071QRVw6SYcnN6G58CQiYiHvVrln5NSj0ptqCwTEXuCJkSNGKNI2EJGsE2zHfenUcgqjTFBIPkEEwUbEXlsnQ6mZLSNcOVY+6a/c0/9r+mGBU/wPc+/f2ICE1xDlSSpky8HaTUcQuoj2MGZxylyYZ4SRM++o28eQQgI2fmwiJpzzktR+0RZ/0ZonJhoU5b/aNycPStXHVhARXJku9JMbmw2I2kzKiROKRkGzEcTA42t4/7MhreCTnPaXQJhtyVKgbPmpDCRp5emOLCaGeMB0iaqFzFYXP4sqZp20nV42sY/x0ByTqsN4AparxAWt5+7PZx2F6QLx+La5Nrm5/n1fyCY/Hl2gaq2wvzZS7SSKj+aoCZ0dQO2BDR34zOzLi/pS05aA64Prn+hvktm+iLJ7w/b1W99XtwVV/9ehKYGU+a4vLialwGIet7uSOyfHbobizHB76G7W8b220/11DbbsMXeDZh4NAMQGhcwDUOQMdCeZg7PqMkMKXMfdGAtPeJKdCL5fH6AUfLF/MilPzA3zkeOkuPMWFB32dTvBjWuXuigwNuXA370uVukhnMTFJCU5fHQBpBFQ0tmAKb+kHqndUkGrNjb0x5AZXYMToMe/rN8dIk2LiifPRrVKe/g9CjAioVaqssvV6/8JJD/cgcABZjm0zSFUhSDLEFgroabIMaQ6BAzCx3cNTh7U5uQqkSSRQk1E4IpuA0BjrNEugILIdsotMEqwRfXjxATIFPnk89+Az31ws6hdN2zcP2IdY0AwfC8GD5gCBQ2ZK96oCQ2Tt4EsZWiC2Yl9PseSKOXocWvhhaU3KkDjFl7lQZIUpOzPZ2ghZzxNS0boraCmMs2GzCpmIw1XXq5jq4OYWtN2AkisWZkv/s2/8znt55iv/et/853rHzDDvVDvv1wYanULuaeTnfkFaX/fLiOGbkudgiZ92U882C3Md+ALARY7Y8WuR8oRq7PZtFwJgLah8jhnk5zyZ4g1dNZasc1sgWt0QThS0udjvkPByxj/2GZ3OZ+LlNlC1sdmp2xm2O1bjNkQx80BxsnHHHrtOYUzS63Y7be631JBA2SuGduAs8pcv335BzebKUfKzSllybXOPG9AZGDLdnt9mtdp9ImN0e62wv9NbYzWv2yb+EU/Nm1/jcm7DPN1k1Vbv6FQnDr7Uuf6beDmDmasz0TVHbo6MRaIxgZviy2AbWD/JoZuClZDDyWjg0I9C5DGZeKv3O6bmPSeuH7FXX8pWIhgyiwuKctLu9b3GZ85Piiix3CDmYkUipgRROSSngVQnru5hwxtIU7MST3GGqb6KmgNhhQotLLSJ5QUmSMKJ57JVkGPdIBlRSDK6/BVEKRDtEAyIWjSuEaQYryZNIFMbSh1NMXA9tfotJXeYWaA8xkVKPHaSge/f/X5TtneGl1rSzD5FEaPs15uyLTPzDC4dvUT1DCgnrKpoipwZHU6FDdwITSO46WEswJcYvSbZg2S9YJvBxSS3QayDGDiuO0/aMT9/79zyKYCVf3YwRAUGhH96Gu0e/z+/qKV/80v8vgw/JmUj7Br58/AJP3V7go+dXn/u1geMBttwl2IrSzSB1pCQ001vcmF5jRY3oCc7UlFZZSkFTHmBDwKqntBUqDisFakqCJkZfVtvcoCtucFY+xW6xYndykLtxGM7Ckl4KjHVYV9GvwmDXn1OdP3LzO3nv/Cm6gd9SGKir2QZ0TMvpRqGEZvfYnWpnQ6Td9hlRlMpVVK6icc2Gs5LN7PKCkTSR0nnS8tg5GTsBYwr0OF4RkY3apzAFhpxCXbmKo/aIEMO52mkYIV3+KiZNhBSG9OpzBZKi7NV7F9RHG5fdrYuVseNz2BwSNV6ILbg5u5nl2W2OK7DG0vZ5Bnq5S/IkxdHm9i3g0RRNBoLJs+7PowdGJ+BxX8fa7sy85PVfqm1PltLlEMftjKXNc20Rbsft79f77NV7TNyEO9zZ3PdJqqA3qy4rwb4a3Jw3oy67QL/VSia46sx849fo+7L5/RLgGE8Sku3y84hlncdCm67MpUqXQcrLgJdLQCilQBuWdGFF1EQ/zq5TzItRfzR0ZzLnoYuBk/6UEM4yyOhPM3DojkA94tdU/gzTPybELnugkECEmFaQIlGUViMpriCuMXGNTSsk9qhUxDAa1WUSLtUhGeOn3J2REgbQQ7/OHQONxBiI3Qka1sTkyYJrxfolSQqurT/LrdUnqdMJjoTEFqOKJE9ISuhPqNqtE6S2SGxZxxWsvsjk6Nc2t53ZQ57f/6OsbHaXVVNiQo/TloQjlXtosUssdqEoEbG0fpFBQPJgp0QMIXZEhT45gpmhGvj4vU/QxhwfkAMI4HtufxRxhtF+Y8fAx5/7Ff7Pn/55Vpr5Jqs0mAcO+/j/+b1/xTKs+b9/5p/nzhRQNHOibUhuD5JHrUGkIJo5a/UcljV1PWG/OWRuC5yxJFtRuCrzUQBjsltzHOTGozdsIIJxxGI2yGUzCRjNadGYzEm6GxL3IkRNBFXKoqF2FaWriMU+VIdYcsekthlEPLP3DLfnt/MIKXlG07oxifhac+1cGUQeO82rzBMbR0Zd6HLXTBNn/RlW7GYkMxJta1fTDJ402wTVpmyYltk5eAQ3Izg67U/PQRXykvyfLnYXVUlyvp9wkQNyeaQyVmWrTYfCiMFHv3nMyNPZdLxS3JCTt43b9uo9gJf1P9mWPo/bT5pYx3Um/w5dpicRYbc7C9tg5dW6GNuvPV7qGm/zbkaAVLmKvXovuxqPx3HLcfirUfNq/opE5rdTXXYlfqvrqjPzDV+Xr45G4JH/7aPneHmfXePIp6JBJdQvcmem2s+uuts8mPbFLIF2O2DzYn+BT+MX+X7FHAZfk3uLe8TlC5TTm5s9iSM3JnUZVKVBCi0GyAoTNLFYPWavvc/oQBtdk30oCNj+FLN6MY9W6usYf5o9XGIE9Sy7BUkrNCmdPyFGpQhng2W/ySDH7G64N5mULBlgaQCpiHqG6c8QGxDjsO0DIHMiHDHnJ4mjp6AgMtElVTgGYLf7Mq0kQnkNkzzJn1L2D7keHr3knZquPo2uP5fHZ1v1qLxNosYNxFDFErKWKDsZG4uWM0gtIkLbnRJiRwd0vmWnqDLXJXiaFDFGqMspXz55nofdmtkgABtPBh+89QfYPXiK55//FaQ7ytM24FShT7Amd29u7txC13dZK3zp9EV2Hn2RT50+4IPTzJe5Xj1FogKxmQsiFi12iKRMiMZQxB7jJsS0wpFJvFUKJI0s+jVqHOvU0/ZrKNtzClf0IGCKXaIpiZOnCaHD9ieEGLCj07JxkBjUQQ2CpXIVrtplWl1nHf1Gki0i3JreYtkvN50Q1dwdGAHL6MKrqjxuH18wqLusiBmjC5Z+mUGLCDFGJGUezDjGsSZb/I8dkBHgFCaPkW7Mbmw4FLWtL/ApJsWE/WafmCIPVg82EmvgieOQy79Pislme5A7A6NCS0TYq/foQiYl17bedDQum8dtK4Agd1tKW77sFfs2f+e4Pd7wW8bbRu+byzJsyKOSvXqP4QpiU6+li7HhFaV4YTHeHmdZY7k2uXahA7RT7XDUHjEtp1/VhXvktoxdvrdrZwZ4CVH6ra4rMPONXMlnmfR2bbo0+WR00p0RbMPj/pjbmrJyyJYQTs/dcLclznEF0oDvM3gpdnKOkR/kzMmDhLx94yBFjtZHPF4+wIUlVYp5AQbCSOYdn0MHo3s7GfZQsP4M1a3ASFMQs6AZiyCxRdIaLQ/OYZsAYUlEYRghdcHQJfBxxdQvAU8fepA2E4tNCaHL46U4kIZjD/1jEgG1DkEx4QQbF2D3GdVfTjskearjX6PEIly86qvbO9Qv3GHi9inC0YXb1GQljhn8cy4DmefK9/GgfIbraTlwagSfBKuRaGdgOpKp87EJHmrDsc/RBskvqMseNQ1taOmT0qdAZacYU/ArL36CswipyGOjAcaxX1+jSmuu7z3DtVhjjnPa9kozoPEK33P7u/iRd36UT3zhF3i0vEer8F994f9Jr3CU4Luvvx9X74Ax2LikMxWCwRRzPEpKmXwu4obJYlZ+qalojeDdDCVhpaSwFT52xH6JDl2BjWTXFaRiF3ETND3eyNwN7sIowUdPJEctJAylrcBNqV0e7wQNtKEdCMFDDtUwFtqMlYYIgm0C6LbHybbbr5WcT9THnlrrjUoqaSIQNiqdsTty2QfFisUYw06dbe4frTP4nVfzzc/b/A0ZEKc1djOq2SYWT4spS7/k+uQ6R+35Z7Cy1YWU5mk5Za/eY1pMube8R+1qKlfRxY5pNd0obUIKF2TLT1rMXmn0MAKE0+6UqHGTpJ00UUiObNhWHV1e1CfFBB99vuAZ6rUsqNuKoe267BR8OTLgcHK4IUV/tRfuC0Tpt3Fn5jJR+q2ut34PruqrV+2DYXSz7fcyjH5Gv4vxz0rukKieS5P9WebQ+JPzh485RXErbbo7Gp6nG26PQHanDXGd5XvDIp3CavP1jMRhNJDOJdXbX2RNQETSAC6G59OwzPwV0yDJIymSEJKCkl1vTepo+2NImgFC6jLvJUWIS8QvKMMjfOgGdZFs5NC5SzSQkcMxGlf5tcUOUcFoBknBFKipCWpwg6HdZSCzXZeBTMLib/wxwuzbXnJfb2ccV+/nxB6QMCj5BPzC6oR/9fwn+MTdj6NS4k1DGjkp5R5SHeBtg1UgeKwGVr4jJiUhhJRIGB6vj2h9JMkQzKj5EHzrzW8jISgQMbx3710ZGyosgZMIf/gDf4YffOcfoTc1O80+S82xBb9y59/jJHdlqum7OTW7RFeBQC8OMZa6mBKlpiOTq+tiAlJhho+ktQXRNixDz6JfIGIpbI0dfEfa0HJvcW/D13DkROpsSW9IxZzONVjrNs67AG1oCRpZF/t4N5jdCUzKCaUtaUO7AUijiki3/hs5MiMxdduAbpu8OwYklraksEV2oR1SkDdgJoVNN2gcP42PH6t0OVPpsDm8sLBum+Bt8ztE8nNednwdQcBOtcPN6U2aormwQI5xCZBHQtcm1zL5eAi93HwXh1FYTJGH68zlupDA/To6CKMrL5C7aWNgpJEL/jXjcb5clxfQ17LwbzvXbter+bq8GnB7M2t7H97unZmx3g7S7KvOzDdqXeCxpJf+nbE9Pv6uaIr5qx59duDdGODl7o5PnhhW1LZhE4EAuZvRPco+MmEF06c3Y6P1kGkzdhyWoWXuBllfGsYApCzD7o6y+65qBkRmDPAT1t0xTTmD9T10+Rwm9RgEaR9Baln0S0IKTKprNPVNVt0RfXsfqwFsTUqRpDGrj1KPJo8kyYpmsXm/JWWOjBmStFMLWNRN8/KuhhTDAIi63Gkgp2TbJ4CYIBWtNMzS8YW/e6n5vZ3vw02f4enpPiH0bF8HLpv30BeHhNBiU4cVn8cVfcsL7ZKVwmcefR5T7XNr/4PEak4yjljdxpUHKM9jCIgxOE14zeoIkyIR4XF7xG88/GLmUit86Pq3cXvnnfyh5t1gHMnl97fD8fTsJhZ4FGHfwf/ke/9ndGLxUlGYwH61s0nBTmTuDWLY2/8gZ+oRCaBKEEuycyjmBAxtVKYuUsZ8/BBIKM6WLNXRKpTFnFDsEtozquY62ArlYkqvM47T/pSmaLg2ucbD1UPUNBuibWEKOjpa33LSnRDFQrXP2s4QYFbNNunLbWg3240SNx4xMUUerR7xaPVoI5F2xnHYHNKGltrVPFo/2oyHBGFSTjjtTzcn/HVYo6rsVrsbXgtc5K3MqzlH7RGNa7g+uc6smvGOnXdsODsZ3F0k1m4vrHv13gWy7mWjuG3/lm33322fme1Faa/eow41fewxYtipdjZ5TMMZ4w3l8oygcSwRYbfa5aw72xzHV6qXgJnXOGaCi2BmGyi93HNud5m+lp2ZtwNIeLmqXc2snG2Ubm91XYGZr8Na9kuSpg3p8Im1mYNfGizreWemix26uW1ooZsyd2JUMwG2vQtiicUOj7pTTHdEMSgvGK2w0yBntofZs2aTlZToBkOvfK1vsrfK2BWSzKOgP6Fb3CEpNMUUtEdTGHbdAoJvH9PEBSyeRdYPMGmVgUk4g9TTasDRoKmn8kesNRBjj9Fs9x+wOaMopU3GsagSVdGYzrs/xWTwbRGyO1+Jmprc82kRCYMkfI3IhITBXSY6uxmdu04bE17grPwAE+mR7gEpJR7bGyyKm+yamkRBR4GVKbXmlnnbvAtCR9KWgAMxaFRe6BccKzxMmaz72ePneOf1P0gorqFFjRRzEg41BUnBiSFgsG5Kke4SUk+fIv/p0RdxsIFft3eeQWPLTjHlNHaA0NmG1lRMTMGPftuf5u9/5l/w3/rgn6Ap5hRiiGIIfUtZTOnEkoiUArXCtx9+K87V9EEQEl3s6F2RJdTVAeJPicWcZKDohliL4Qg3dkqrCW8nzKt9WmBld8A8ZqfaoTQOn3LSsxOHGGHt1xtjO3QACMaSUvY/WfQLjtoj9uo9KlvRI7iiIWqkshXWWR6uHm64I844+tRnk7oB4Ixqm1GGbRgccYuG/Xo/g5mi4eb05gU1yiYWIAYWacGBO2BSTLKrMHJBCrxf77Pyq+xjM8iKx9ossnpxJHK5E+O2oklezg9lG8yUtqQwBU/Nn2JSTC54sYwjt3fvvTuHbPaLC07Eu9UuZ/3ZZpuvp0aQtu3hgrx0QZ+WL7Xdf5LC6dXqSePBbWDzcoBom9z8tRypvB3GNy9X46jw7VJXYObrsE66PNJ4Rc+AbSM7YZAb52FF/ns2+xr5KySf7f3dLAOIOPBHlneg3M2W9XYHoif6Bbbc3er+hLwgicuP0ZQ5N2KJMtiXa87cSWIQ/xjpjtHicFAynbBevYgai3MTimJC6h4io4RSE9I9AibQ3wfN/jcyjB4QS596LFCEM0wAaR8i4RQ0ogIhz9GwdNn+n8wDUluy1sCEAugGArAbQiczAVlNSXKTITbAIpoIpiFJzmqacD63X+59L3b6NIvFfdz6Trb/tyWrybtRmWDXzzHYuJHEcdyvcRo5KW/T64p2/m30k/dSLr+E+iUMV6h9bHm0OmKp2ai4A87aY2IxRU2Vrfw15y1Z41ApEV0TbMOeLXEknAhfOvk9LDB4I/M9tz5C4Ro6jYgRCndA0khASWIRY/hDT/8AP/DtP8YNPeXB8efz+4KAKYnNO7g+e5ovPPoyRmAi8KMf/LM88oGIY4WhcTOidXTFLlYcEUPSiJEKayeE1FOIwysURc2hmzKzdvBu8dlLZghEVFOx9mvWfk1T5k7IOAqC8wV+JMoaydb8o+PtzdlNCik46U9Y+xweuVvvcufszkatVNgCApQmA4rt71iIW665iQ0XZhz/XAYQ1tjNWClp4vH68UbpM95vXCitsec5QE8Yq+Qv0vlIZNt5eKydaoeH64fUtn7ZLsPl/bs+vf7k57rwtOfjGZGsXBq5RfD6OwjbaqvRlG8EeeNruzG98USQ8XKGea/4OobtnPVnm4vBJ3nZPOlx+/U+fexf1hjwzaoLnaK38Zjp7VZvKez76Z/+aT760Y8yn8+5ceMGP/qjP8pnP/vZC/dZLBb8xE/8BE8//TRN0/DBD36Qn/3Zn32L9vjNqTiQYrev4F5rbX/QL8sLL94xnv+rynmY5PlYKWrEx2zXLrHNC5RIJvUOLA3SGhSCJjIqUnRb3l0dDs+lIAV5ZPQg/98dEUILA69Ah5PoPJzh1newZ5+G5ZfxZ59F/An0p6g/gZSIaTDESx5tH7Js7xL9GYQ12p3knKLUI6YmUULoEU1URIgeE1skrBASJIi+Q4LHxg6jPZIiRvO4KKaUicIkSJFF+5hl7FAG0GMAqVBTISkiYonJ0oeOef/swGgZAUpWOaWw4rRf8OLpc/z+yZchJSr1aApE9USxrOMa0UjvW1Qsi/I2nT3MZOSh+5FEMAj3Vs/TbcuhBY7aLHFXY4cIBcXZBoOALUgqhNgj/piZdVgjPOhWJGCh8IHr38Yfeu8P506OCAmLFUNj63xMTJNfqwZ0WDiS1PnKWQPJlGh1yHtv/kG+9eD9vHf3Gf7qR/9z5uWM5OZYN2Va7eUQTBXqYoodxjSaPBaldA4Vx7zaYa/ZY1rucHv+1OaKrzAle/Ue89l78cUOyZQs+wweyyEtepvLOXItjDFcn1zfjGs2gYXimJSTDQF3JLge1Ac0rtk450Luxii6SbtmOO7j8wDnScqcL77jIjtmJwGbTKPxMUbMK7qxvpzR3UhKhicDiN16l716j9169zV5f3ylV/4vN1Z6JXfdV6pxH5OmjRQdyCGjyEtUUtv1SoZ5L1fb58+R+PxaR2VN0bBb776m53kj9Ur+PFf18vWWgplf/uVf5sd//Mf59V//df7Fv/gXhBD44R/+YZbL8yvdn/qpn+KXfumX+Ef/6B/xu7/7u/zUT/0UP/mTP8kv/MIvvIV7/sbq/vI+67C+MN9+rbXdEr1MYrtQ22CGkZsC2z4zMUUet0c8Xj8mxD5/hQZZNENaLyHHHgTs5kSehm1r7GmXz6H9WfaeEc3/tveH0dM6d3H8I+bWcGgNB66mHBx+M4A5IixfQMIC4x/lgU1qSX6JDqqlzp8RwoqT9Sln3Sl97BBVJCVkcAy2aT10iDJxWXSFiSuSCia2BH+CTSvcQEA2ZZ1Jp6YgGUvbPuA0RtZhgcYFKbaEFLNCKGQysAmLfPVmKwIJ7Y+p0rlaTLEIjujXhNhyf/GIZYTfeXSH+8sXCaEjxUBQoTNFDnzUDqMdSgYkwQ7jGANRDJ2ZkkLPs0cvEMlg5vb8IP8M3Fs+YOFbSuPYrXZYhpbT6AlSkFIihGXuJpmaR/2a9UD2/Y5b38V/97t/ElPfGo4zkFaU6qmLBmNKymqHZKas7A5peP/VFkM3xJCMw7kpTTnhO299mP/hd/xFvuPGB+lDj3UzyuYWtpzS2wYQZtUca7Nk2cQ8srHVNTAGV+3z1PwpDqfXYOh0TNyESTmltjV7kwOSFBt3W8h8jw1Fd9MlPF+Ugoas6BkGi33siRo568+oi5rSlnnRl/OOSExx02kZgya3M5XGq/exWzM+94Vxz3DhUNqSW9NbzIpZDvUbHhtTZF7OaYrmJZ3V0X348qK57Xq7ScF+ApgREW7NbmGN3XSALtdlb5rXUpfBwvZ+vxLgeLW63JnZlmy/mine9jF/xXPhVm2DrvExl5VMb3WNAZ2vFyB+s9ZbOmb6pV/6pQu//9zP/Rw3btzg4x//OD/4gz8IwK/92q/xF//iX+SHfuiHAPhLf+kv8ff//t/nN3/zN/kzf+bPfK13+U2pEXn3sSek8BU5Sm6j9m2b9fM76GDhfzRkGeUcGJWaA+sYhu7Q3id2R+jgLtOFJWrJIGYII8OUWbWkkTiOqTRtANFi+SLLYp/J+i47qRtUTcdsvGJUob+L7U8o4xnY6XlKNArdEdqdDMnZgeDXpH5BbSxKQIVM4AVikmyHH1doewzWQFMiLg+QXMjqKtUO/Brbn+YcJV0PHJKIYplLwmJIdoqJa4JfkmLC9MdosU/X38dq7tDQvQDrZymXB/Q3/+S5UksKvMKs+9KFQ39SXIeUfVO+sLzLZDhkNfD5oy9yfb6HJ5FCm7smKKv+hEoUi7KOgXV/RrIdOyERKUCEs/YBTqBTuHHwTg7cnOfOHhMEPn/6ZW4cfBvL6JnbhgUFago6LBbowyp/Yoo5j9ozeoUFcHvnnbQhom5CJJvR2RRQEbAOsTlSwNfXodhHiSQVrDjW9W18AvqHzJoZJ8vn0aT40FIQWYYV0lzPHZPqFqk/JhU7FMYhkrkmg5iHqrmOb09w8YzCljTlnJ1il1pbFn6BDuOG0mV1UNK0CUi8Ns2EX2BjIoc5HzWFGDYL7eiaOy7CjWuYFtONIdrGTG0LzGwDlW0PmdGsblQnbbg0g9XApJxsniNqZBZnm8eiuaM6c7MnLp7zav7KXLitMdPLTUUuc18u17ScbsDDa63LI5htpdMbAQHbHBYR4bA+pPXtBf7SK9WoFtvmtLxSjZEMfezz+dNeNMx7O5Qzjtuz22+b/fl6qbcHFB3q5CRzQQ4ODjZ/+9jHPsYv/uIv8vzzz6Oq/Ot//a/53Oc+x5/4E3/iidvouo7T09ML/7+datvTAeDB8sHLz8efUK/amYlb7r0aCamjDx1tDPkEoZpl0GFF8GcDPVhI0Z93ZuIg5RYLKaIhkPwppn2QGQpDZ6btT3Iu0uru8OQmxw4wSKxjh7SPMKnFaJfVQv0RElrEHyPhDF2/CLFDY0uMLaF7QAyrvImNbHUAYCmi0QPLTPwNp2xO7alHwhrtjiHm8RRkwi8oQXuSGOLACbKmQIYr/aL9faqj36RYfBbFQfTUi09TrJ8FwPrHlCefoPUrJK5QDZw9+FVubEVZH8sea7uTDfSS53F7SkxQCcwMvHh6l+UAEntT0UuBqNBFn4MVxdInZdUtOW3vchZ9NkAzBY/9AgUWCa417+TG5DqRDG4+8+CzBKmIxYw0eYYoJkvT3ZxIouvOWK6P6YEXV9kvZhHhqXoXL5ZTCgJCQkBjBnoKIYGYEjeMBwUliWCtASkJ1T6+PMC6BrETDImSSDEQOdVWqCmh3Gft5qRyd7gKH8YIkrtumIL95oCdcp7fSTEUrtoakciG97Jb7VK5ipgis2rGfr3PzdnNzXdhBBeSV/wL+TYppewrNPy+7Reznb9z2p9u1DujWmf8eXzs+LhxofXRXxgzFaZgp9qhsMWFyIHtMdNXGlY4bnv7O2/ewOl7Vs6+Iu7H5YV1u7vzRrxQtp2UBWFaTtlv9i84Dr9SHTaH7Fa7XxERdewGbTozW3yrt0tdAZmvvN42BGBV5a/+1b/Kxz72MT784Q9v/v4zP/Mz/NiP/RhPP/00zjmMMfyDf/AP+NjHPvbE7fz0T/80f/Nv/s2v1W5/xXUZzChZErpNpnvZUuV0fe4c+8TZamzZJD+j+NiTkYHjrDvloDmA5bOE5R0eLx5xNqk5aA5RDXnhbx/kaAGR3J3wJ8T2HridPNqJS9TsAyCxw8YVprsP5RQIGxUTsYPuIdKvMHGJ0wlBCkAR7fM4KnZoOAP1JDVE02BTIoolSpl5PmIwJIx2WfQSWiRmCq2kHiShYrB0OH+MBqV1eRSSpEKKgqA+u++aKk/iU89k9Xlcf58ZMOY/lu0davkPOX/p0rFtzj5Nc/ZpervDo9TwnuL89s+0UDcNkqAQw9qvOe0D1wYcZgR2Ddw7e46nJtdo7ZRQ7LJqF9S+pU9QaAY0IpEwELPFWHZsw+fXJyw1m9Zdn91mQsuknOFXC+6c3uVxu+Sg2SMZS4xddpoVh8NAWNH1jwkpcG95jx0FtcKNgw/weTH0KdCliNVM0jZi8ao5/sDUqJvQhyW3OSAmpXLNEGWgSHWdVE1xp89juiU7As4IqrmrNKtn+OYpllogbpJBjsim2yEC1pbU5YwUF9lIb9iH85P5uR+LouzX+9kATyM3ZzdpjzOgHPlj22Bj+7uWNHHanzItp5S23PjFjAvx9sjmqD3KZGDOPWY2wGhrkRkdUH3yFxb0ywvwtck1jtvjra/xqxNOL9c2AfegOWDRLdhr9l7z499oXV7oa1dvXGpfkbv3KnUhJmA4btuuv69GLLbmyUqnV6rLkQaXR4hX9fVZbxso+hM/8RP89m//Nv/kn/yTC3//mZ/5GX7913+dX/zFX+TjH/84f/fv/l3+yl/5K/zLf/kvn7idv/7X/zonJyeb/+/cufPE+71V9aRuyms+GXSPCOsXN52TJ3Z0Un/Oi0mBlMJAALb0Y+7R+h5ddwT+jNg+HnxXQh75LJ+H7vHgiJt5KLE/QlKH7V5E2oe5I6Ie8ceY9YsDT2WRx0wpc2xGV2DpHmCTx2x8O/KIKQ82Em2fu3HJVKgtSCkQROjFAmmQUgckrelX97P3i4a8GKUugyIMxi/p+jM0LvHB02FQBB8DbfD4ZEjRYFJi0r+I6+8/8RAb9S8BMttVxlPeqffYGc6xj0MGM8fakqTGiPA4BOLAG/bkJGoU2gArOrxU1M0NXLnDyi9IkGXjgEE5U5ePkBhmpuWFxQOOI7QKB/UORhx78+tMJMcKfPHoiyzXD4nJ04c1bVjnY0PEoMTYsQ4tJz5xprA7vUFhJ0QcBiWI0g1t/ZACXix9UaNuOgBAw6yqacoJdbWfuzcoxliqchdf7NCaEiM5rFLFYG3JrJihtkSKOdaWw9Vz7p7sVrvUtmZe7mHEghQEjahtMMaeL3JjRpDJGUHbuUTb6p+UhhwfPedwpEEyP7rjjryZ8Wc4BycjMBjHJ0fro43PzLZq6AJoGfZxHE09CRiNz9EU5wTg/Wb/wnO/ltruzJS25Nr02ktcar+adRnMOONe9vV+JbVRb3GeebQdjvnV6JZclme/3TgzV/X66m3RmfnJn/xJfvEXf5Ff+ZVf4emnn978fb1e8zf+xt/g53/+5/mRH/kRAD7ykY/wyU9+kr/zd/4Of/yP//GXbKuqKqrqqyudeyP1JADymsdMQ6SAxDVqys245/z2845M3nAYWvfkTgtCTD12dCGNa5x20B/lbcXTnJ7tz6DMJ9w2tqz6E4zbhRQx/jHaVbB+gAlnG8AzaHkGp9w2K5vCMnNRql2Mmw77t4ZyBzUFkjr6GKnFoBpRDGoMj3xgaopBNdNT+DWdmaOiJO1xKSKSMLGHlCXfecy0YuX2MBi6pBQpEJMlqZIwVKIUaYnTNa9WXio6O0eKfabrz7/s/T43mCa/cHrE3q33gcKiPUbJQOagnCCNoz07pQUerztCDZ89usOv/NZ/yXeU8LH5Lh/Yf4YkE9ZuN3dJsJgU+cRz/57KwnGEppxjxRBNxUF1Ha+/jxV4/vR50u0PsV4/4mh5H+PX9JqoNCGSu3On/oRTBZvg6eY6ppgi3oL2eJnh9JiAsqTC47JCTAJmUFaREq6Y4xPUZpcUIvtFSVXURIb3AKWyFaVtcK5hUkwuZPzs1/usfU5bblzDXr03jPuEVO5mEOwajKkwpsr+PqZim9nRhvbCWGBc0KNmi/2RNJpG64GhAwNsOC3bNS5g83LOYXN4PjoawN04ZhpHOtsAZPsK3xq74fI8aTRSmPOwwm2S61dab1UX4fJCP0q6z7qzV+b4vMbtbpOokyYa1zyRIP1m1GXjvLcbZ+aqXl+9pWBGVfnJn/xJfv7nf55/82/+De95z3su3O69x/vzILixrLUbaeXXWz2pM5M0DeMZhVcg5V1QbHQPIZRQ72Ubfjs5N8rb3C8yOO/nEslhfKQsvU0eO0i303BfYFA+DSRl3yJFj5Iy5yV5tDuiL+bg10hcDGZz87zv/Sm4Buwg704tNk2RodPS9SesXYNIOXSMUo4hiAmT+qzkaR/mtobeQlYv4lKPxIBqwoQ1SQOoQfDQP0Qp8m3J0/olXRiM7ZKCzUnKQh5fuHi2OZ59+Q5WNLTGcq37Ek6zieAL8+/B+DMCBa6+DqKY1OHtjJ3l7154Tx5RE6XlNMFxCDSF42FaEMidFFvW3HIHPFycogpnoSf6Jf+7//B/4LvL7Jp7Z3nC0zuBqm5YGYdTIVISo+Nxe4LPDQf2dt+B17yU70+usQROI/y753+VP/rMd3PNr4gahsxvR49jRcClxGn3gFJyrtJOcQB2ioTchQrFPp07Q+wURBEyAJyUMzBV5r9oJKoh1TdRKdjpF9Ta4qSkMCVRLIVx+Njhiimlq2mKhoerh1SuYuIm1EXN2p9tyJ4iAmN+kAg5oRyMsZjmJhrzd6U0xQZcjOOe0d22sBkMqer5bfY8QuBofbQxqLs8lr08GtpeOEeJ93ifTRjly4yTJsWExjXcmN64/LXd3Pfm7CaLfnHhOV5rXQYvX+uF9yVgZhgFjl2mN1qKsugXTIoJMcWNxPyrUeOxGz8Pr8Vn5qre/vWWgpkf//Ef5x//43/ML/zCLzCfz7l7NxNJd3d3aZqGnZ0d/sgf+SP8tb/212iahne961388i//Mv/wH/5D/t7f+3tv5a7Tx54udBuS32ut7atKIYfmKVldBEBze+iivLTGtjmkLGter8A6KIYYAVMM0QOSAc5AYNTNiciQ1OdE5diSgEr7gXynJDOojIbujo65SSkgqcWGHGC4bu8R+hNS/whn7EAq7oYRU5cfYyzr1EFcYUJWfkQiPq5Z+jWzoqGN5fBqwPaPMrlWUo5YKBvEH2FIJEmUGug0EWKPSVnBJNGDX6B2H8VQqEdEWYaOQMIRkOhy2jVKYTRLuMejaCfZ/C54zoqnEDyPy9sku08T1iQVPIbH1/4oJq5o2iMeUrKz+C1KgXsBZHqD9uhZAnDUn3C9rri/OMVrziuyJsuR584QYmIZ4TN3P8GuwJnmBOr7Ce71J7xz/i5WZfbtkdDTxi6PqhJE2/D0te+nKCqi9uzUB6ywPIiRPdb8F7/+v+d/9V97CpLHOEfoPd6UWfXlLKuzY1AoDJjmFsuYb++LirI6wPr7hKQUkv2H1Fie3nknfXHA49jlOAhRMJYQzgGFcwXXpjdYtCfsTQ5pk0eLfKU+dk3G7kxTNJzZglazM29ePM7HM2Mu12UzOGcclau4L/c3oOagOdjcZsXmYM3hAqcwxWZ0a43NBNxhcyu/YlpMQXgJeBnVRyMB+ElBeiNw2v7b+Pfa1a+ovqlsxUpWFx7zWuvyfb/WI5HXEx3wWkpEOGwOc3ClsRy3x+chol+ByvMrqcudmW2l2lV9/dZbOiT82Z/9WU5OTvihH/ohbt++vfn/n/2zf7a5zz/9p/+Uj370o/z5P//n+dCHPsTf/tt/m7/1t/4Wf/kv/+W3cM8zmDnrzzZ259v1SmOj8bZpMd34CaRtUvB2qOPFB553dZLH9I/Bn3C8uss6rDOAaB/kJOv+Afgl9I/Px0wACCerx3z5+PcGS3gwUgy8E9CBWMtgSJdsQY4WaCFF3JDZo+EM0z8kdY+GUVbKQKY/y8nTKYE4un6FpICNS0zKkAlVNHWZmNqe4lMiqUNHh9cYUDxd7City/dXodBlxkymAk3Z+C52A1/nIW2KhNRSxI4inWEFUggYAm1YUVrBqt+kUwN0tiGLoiEZy8rOWboDUvIYhECiHztmaulSz3Hw/Ksz+NcL+B1fsVvfpCMri47jmi5GHqzP8ArJgrgJCWFqagryW6HkDKPx3NkrfPn4Bf79i5/E2BJEUNuw7jOYWSeY7r2LqrmWJ4aZTcC33/gIAThLUGrPb7/4SXxYD8BROOrOWKeWKJaz9mTzvIfTG7zYPgbJILyu8mhONOQwykE8VrkGGUBH1IBPAbDnVvhuMK2rb3Jt9g5cMUeLXdQ2m5DFSTHBGZcBBHB9cpOD5uA80Xkr2XnsBo4gYlQBTctpDmQUu7EjGIGSM47depd5Nacu8usxYgZhev65dvUFtZGVHKJ4WQGz3+xzbXKN65PrG76GXtqn7UX9srT51RbDy+On10MAfj2PfTuXIJtYCLjIH/xq5RJdDpu86sx8Y9RbPmZ6tbp16xY/93M/9zXYm6+sXi599aw7Y9EvOJwcPpGgt+02uZkXp3g+CworKHaf0J25CGZkCKsLYUHbndDYekiyBrbyWfK2LbZ/jIYzNPXE5CEGkualPI9tlBSWmTfjFzC1pBCR5DFhSfKPMM3NvN74ZR7fJJ9HOJrAH2+oOsQ1KazQgTisscBqj/YLiD2mu0+rERMXdL6iFCUZC6ZGjcugJUWckFU9WFwMCAFJAcSQtMgAykLfBxyBjib7TUTFxg4hItpjUoEVg8YOO/BloqkRcZngLGYg3zKkcVuScRADIQXq2GHiKUKk9yvWCe4GuDmbc2N6G6/QJThZL1hNA48TXDdg3QQvGSzdmF/ns4++jJDN7kTgAwfvYeof0XenoHDn9C7XlvdoJjd5YXkXiS2B3OGZ2kOSrXDh3hANUfLD7/2T/PM7n8jbVHi0uMvh7DZqhPvrY37n2X9HIfDRp76DO4vHeOCUgv3JdaKd4KxlaqZIXJAQnAYUQxzUXFkinZVhMQbWMWE00fqWwhUU9U1EEqE8ZFLep7IFURPLlDspY6bOdjK0mPPP/Wa8VMzBL0hudp7PAxxODokpUtjsqrxT7XDSnbBb7l7olEyL6YXvoxW7uUwTJI+AttSCzmYA9HLdjXF0NUq9IQOXWZGN78bxh4hsfE7G+7xSvZFR0UuA0DdIF+GVXsdrcTB+PfVyBOBvlGP6zVpvCwLw12M9KX0V2ASvPXf6HNcn119CjttWUZwrFAL4R8Pl8LUMEi4DIU0bbo3tH24pllL2kwkrXH+aH2eqvC1V8EdQHOJU8bElxTYvhpqGBTyPdXIIYw/0pNQjalBRUMlOu6HFaXb5TWpQtTnpqD+hMhaNPaIn0D0AY7OOJrTYuMaUO3SxZ90dEdf3kWoHrXYzKEkKYY2khA75Qf3AfzH+hKgeRbAasWlJSit6FJMi3kRM9ITYgm9xtiHYGc5GfFRIC5IWqIIxgSaebpaTZHcycIoeS84aSgomrPFiiZQZ6KSEiYrDorGjTy2t5tFYW+4xrQ5oXEnnex72C45jPq4YwGY1UC+Wupgx2+24+/hufpsFfvSDf4765FP8y8/9QgY4wD//zP+NkwiNwIcLmNg8fambfUxqsZowxhGlpCwn/Nh3/Y/5J7/1f0QVHrT3KU9+n39x51/x7Nl9vrPM2/z487/FmcJpgvfOb5KKHTAlIsozu+/i0VHLCkjR04WeYBUj4GyJmDKTW2OHWoMPaxIpj5iKGWIcKg+xtqApJ7S+JUhDKTaHPPrFRt481mXCpSl3STEM/j8XRzvGngOfwhab8MVtEu0YKrl5nDE5kX24X+UqdqqdTAhGN92dVxrV3Jrdog89feqpbJWTq6sZO9XOBWBUmGIDZl5NInz5+b6SUdEbeexVXayXjJmuOjPfEHX1jXid9XJgBjJJ8bg95qw/e4mvzKYzozFn6ACafB6XhJPshhufoLbxJ5nx7xc43drm4Mgbu0dZRRTXGcD4Y7K6SMljEuXR+ohl+yiTYxFKV2cPl7RG+hWhO6LzKxZ+yUl3RsKgxiH0zEyBpICY7EqrYknGEDWBX6LEzM/oj/NVdhiM7cj5OilGbArYcEbyy7wtKRF8Ts9OIY/PCKgxENaY4FHtEUlgDUU4ycZ5gww3kf0/XOxQ7Yh+lUMcix2whqhKTIkyLXCpZervnb9H5T4iBUImJicMxpYIQu/zgq0kAkplB1CH4mkx+chS1zcRLLvVHgJ0EV70SxYJjEJZNiQp8jGs9nnHje+nKGt2Cvjf/MBf410H72cyvcmPfOBP0QGNySBn10At542uoLA3fRqbQlaJGUcwNV4dB80+MuzPlx7/Hj//u/9X7i7u4zV3j8YveJvy9m7Nrw3jE4OoDIChxtkJMflBvTSOsixicoclqCcqdCG76E6KSbboFyGhWFvlCIJygivn3Jje2IxxRkXQS74D26qeJ4xxtuvyVfP21fR2dtJIDB5HFCOX5aA5uKB8gle+8i9tyU69w43pDQ4nhy+bh3QZfL1SvYR38hUunpeTpL8Ra3yNX8005m0C8Ci/3/77VX191lVn5nXWk8DM+KXoQneeD7MVV6Cq+OghtjgfwOQZf4pt5qn4NUiVfVzK3fMn02wwt1kEkt9QgYXcmUmpHboxeayEm0P0gEJY0boVqNL5JXXyLENLU05zmz+sWC+fZR1XFNIP+9QRrEXF4TRluatkbKRiUQ35VJwUJZBCiyn2B4V2T9I+byN5GluQjNJqT6UdPq1wKCatMAqEJSqCEZAYEVlhwxmknewr4qaYYo62Zxsglg+1kMICQotLPZq6rOAxNVGXmRCcOozAJKyp2+fy4QSi2wdTITZfqTsriDFZDqwCJoEUGFNgTI2XFieJsPa0mmXX+5PrNNWUneYa5fI+SeFTD76YG2KAoaGtDrAaCdUBlWn42Dv/CMFWtINz7bTcRdKSqijp+56zlMdQ04FTI4Czwq3pLVw8Qd0UIxU+lvRqsMUh66xP46Q7JiRQC8cJbuZg58wHJ2PND+5/YPjgGEQ05xaZClPU1AaW5UGOD7AFiMHaJnc+oh+MDPPneuxWjFlB3tTMmwNaqXhveXDBIfflatOZ2VqkXxbMvMyIZuTCbEi5xmDGruKwvVk5Y1pMc9p8PAcCrwQIXsKreBkvklk5o4/9BXv/V3u9L/f7q9X2uearRY59q+vW7NZX/Tm238PtxPWrzszXd31jfiO+BvUkMDP+HFLYfDEeL+9xo97BlXsD6VZxqcNJTUo9YFB/ivb3EI2gOwMI2aotP4ScV+RzirWYc+VRWA1XtwLlAYQXQEpUloh6XGzJJnQ9nV/hVZlKQaEtffSE5DFhjUgA60imIqrPLrvlHhiHNE8R+wUmLpGUFS8iCfUDuNIEpOw90x2j3SOkaGhTxIQVogZJCWJ2GxYMJkU0dJmDIwY05ERsDZlvgyHZBspZVlyh9MlQGiGJwQeFtMYQSao8ePwp7j/6T9yJlo9dezdlipQizPtzr5ggFckUYAuCas5/0m4gROe0ajGWWFgwU4wdgwaFta4ZPI6ZTW5hrWNvfpvF/U+z0jwespmly+7+e/FmRkEgmQm+2se1LyCppY0dopHSNiAle5NDTrsXL5CEx0/Wfn1AKYGdckrtyN4rweJNjYRTOgy9RqwMinbYcG0ieX/+wnf/GL1UzMo684fEYgeJtHXN8KxCUc4pEHZd3o44i9qGTiOrfsVMFTuMfDYfTxRfHjLZeQ+zcp8XF/cYs3+eJIl+SWfmCd4tl+vywj9euYsIla02HdDNzyY/z9ipMcZsAiCfBKIu1+VO0st5kRgxm9HXa6nt4/GVjooa12Sy/+t47JtRIz/oG2HRH9+HpOmqM/MNUldg5nXW5ZPdtuX5Rm4NmP4RHX0+EQwKC2ebzTY6v6JsHxIJRH9KVd8458MMFaPPwxDNswKH0IcztNgD9UjKnRHGcDnN3RqNHX0ILOjZMxUSVkhY4P0ZVgRhl1ocnpSVLALqJiCC8Q+JMeI09xiwFSIK7QmSQlY4uX2IKzR1mVQcVue5UEkxyaPRkfolah9R9KeYwaxPwjIvlniUDk11JjaLyWZ4IiRxYAqMX9FqNkJLQNCIixCdQ+mR6LFEyrTkD4ffQ3YAIl9sv8Rx+S1MbJfNAYc6K5+iiSuCKUkacxpzXvYzIRpIyRPtjFDsEFIP4vAUnIWEE+hVcMUUtVP2JzdZa/ZwyR4v8L7DD3EwezdHEYp4xKTaJYhQFRNW64fE/ohmdhvrKlqNzKpbrPVFusFTphQIQ2dmf3aTedHg4gpjayj3Ma7GxJzq/NT8HfTLL9EARqBxNRpavMLh7Cn+1Pv+GOvZu3noW6Iobui6CBEBmmrOXbdLgcGaihv1BPVKtjE0qK3pzAwFutix43ZespiqcZjqMP88KoAGpdJlh+voJuBPMcXeS75LL7dQXnbe3ba8H+W9e/Uej4a4j2W/xFl3rprS85HQ2JF5pWyiTddpHEW8TgByubaB3Ve6rf1mH9cNwYpfQa7Sm1UHzQGn3Snz8vWb5L1davxcbr+33wgg7Zu5rsDM66xtFK+a5c/jSTumeEGplYm7npgC4s+ww+zeJ89pe0K1fIFJWqECvj9lVl/fPLaPPQ+Xd5mkNTqGLgpMipo1CWcq1rEfYgvSoDAaMkfEsFjfIxZ7dOkBk7TCr56j609YTd+DTYm9yXW6vqU9+dyGFFzZirUKMawoUj9IuxP02SBPtM37MQZXEtlEGKhmMGNtJgtHz6JfUfGIlDwuLYGExjWiKXdhYoc4hxhFNGKTRzWQ4holK406dahkpZNBweQk4yIec0vvYxlIIVvno/cVkcfxCxxscYy+mBpMFBpNubMUOzyRXiYYA9HuoOGYNnjWbgIIK7/CGKXTHMC4VNCipijmaHnAtLrHt1z/AL/+8IscTg743uvfzbfvvQOdvIMyJgpv6aTM0QIpYY2lsobGFCRbkkjsTK7zjmvfTkzK91z/MKY/5Te+/EucJfju698JJIxGnDHMq332Zc7pyfMkEt9167v4+Be+BAKNLfmf/6H/BT//7L9nvfgy3/f0R3DlIeoq1K8Ho7pi6EJZTP8IZ/ZyAOcQFNkYw3owIlRNyADOVRwrv+La5Nq5ImRcnHXrsz7UmEY9LhpjRTsByTEHcG6Nr+jLOr5uf9+e9LOSYwdUlaZoNtlK434g56MZY3I35dVGNeO+X+jMvMUL3htx232j5Yzb+Pu8mbWtGvta1ZhgvugXV52Zb5C6AjNvoDZXbsNJc1RJxCHoceIqWkawI6TuARKXOUG6yO1wI4IJK5b+EZNiRru+z2yaIx2SJtZ+DSTa2GJlkgEAUJd7NGpZ4+nae6gMw4nBaRdNRIEQe87iY6wr2C1n9NoR/Akmeep6h4l69myBMcokRXbr/RxOGVtSzD4xktoMErqHSFqjCMYYmnJK1+WTkE89rjsm+BZbTICQg661J4OXJaY/RZInpYBf38sS2NhD7EkUOFGwBdGWuNASwxqPwZKVLi6uOYj3ASWlAusdZTrjlerAnAOZVYLfOV1T2t/j2vwPY8oD1C/xvsOy4DeP7nBS7nOjnBGMUgC91AQjFCaxDmv6YXRzy01x2pLKHVQs/433/Tf5kx864OHx72GaW6TuAUkMqT5gbQsod6n6B6TQDmomgwunpGICUuCxvH//A3xo9z1MjOPs7Et831Pfz82qZjbZ5VFscbGjSw0hekxZEVPisD7k+97xfTxTOFL3gPccfoBZs8+f/eCP8vzDT6PiSW5CMhWiGe0ZKRggIQahEU/jakI44aCsEGMoBsCtQ5cPMjjeq/eGz+3QVRgwyuVUZxk+I5f/3oXcITO2vNCZuDm7SR/7lzWg3AYRT+pobGS2ww6VttwY7I0Ll4hw0Bxwe3b7NeUajY/b7iy90c6MFfuSTtU3e+1Wuxy1R0zGzvLXoMYu+ji2g7ceqF7VG6srMPMG6vJVZ0iBlc8On84f47rHkOJ5Bshwch1HHjFFSusQEj50UEwQvwC/Imni7uIuXeioGbk4CUvMljRissFef4yEBMZAUYHbgRjAH+GTssKw9gtstOy5JmcnaaRIa+b1IbiG4uzLuHCKxpQ9XUQQ44aYAY+ENvN4YjbEUzMhkSj8Ajte3fYn9DEgQiY5p4iqR5JkAJY8JvX5dBFaYhGwafCOiWsiFnUFKqDiCAlOuiXWmDzCmkZurD+NZYxsCOdyn0v1H1bwXQ0Ul85N/3YJzybYS/CgXXNzPsmdH/Xcae/xaH3C75+e8DngtoV33ih4+tpBbkVHOBuSjwvgoJniUhyASO50FCTKsiGIxZuK0pZUWHpboqYguSmpmJL6ANEzFVgodNVNwvIBImBEaOrrnJ09S11M2almRKBMLUXhhra4cNYviCJYa5nKlJ3pTT5y64MUpkSlzB6KYvDlAX15E2MnCIoomdxLwmBxxiLGMTeWanqLuSEPl1yZpesoorlj0qt5Kd9kOMYjCfcyH2biJvjoN2ORMeixdvVLuDKv5KR9oRvDS3/eWNMP38V5Nee0O90YU25GTMa+5oDGTfZSOgcfb/Tqfafa4ag9ek2E4W+WGjOY3mqF1pXc/eu7rt69N1CXMz5Ou1NOu1PQiGWICPCLAf2fKy7GE3BIIefOhJY+tkBEwhnaPdw4C/d+iVndQQaCbyp2MKrQnQJ5BGDCEVmG7YEIqaMNa46XD2nVYjSb50V/jKRA1IRRwYrmZOvUY+I629UDxs6w/gSJS0gLiIsMnMIpkvJrQQySfDaeA0iRaFzuVanH+zM0eZREIZZOYYVBFZwB7xec+hV96PAaSKFDwpLOL/F+SRfbnNQdTjEaqI5+G6uXiNEvU7/bZUCzXf/fU/hygHXIfJQvr+4gpkDJbrl3zk5pB3DkgR741Rc/CUQS2aTuqDvKJFuBw2oXa0qcAR23E3rUlIRqn2QKSjenmd5ATInxpyQguikqDiEwdSVFfwSmIBlLQHFiEFuwqG+DMVkybgpKI0xsDZI5LN7NM+gQw7yaY2yNwWCMkGwFAioFsTqktyXJ7QxdvURhHEWxT+kqalsjxmBdiTUGM3wGnJ2gxU7uzOS9oCrqTWdhAyK2PtMjvwTOF4aDycGFvKLLYOf11OUYge39GL+LhSm4Mb2xudrfqXaobMV+vf+azdi2gyTf6D6P1RQN1yfXv2q5Q1+vNSadf63q8rhszOK6qq/fuurMvIG6fEIfQ+RkyBkR4LQ9BlX2/HqrBZ/v72NLrYaFXyIaSQmsRJJ6YsxtUAlnmaeSPDp5JyIWsQXEHijyHsRuSNBO2clXPUuFTj2dD8xiS4GHrs9BkRrADDnAGjH9EQgYDbnjkS3vcOEMjV0GSf0ZDDyXaMtMSJYKIwVJHEkN1iiIoj7iY0dICtZgjBJkTowJDSeoESo6VnYXqx0oGDx9dBgLkZDBm8mhAsTEbH0e8HjXw62BWqHAC8kR+8COg3+3hrsRztY5YuCagfshhz6uEzQ25yG9cPyQk36Jx5Kk5Cj2rFP2eUmDtLpTeLC6z+H8BsZZ7q7OqMhgaLecZekyAlIRdT3IxsHakqLcIYmhtg5XH5DaB3RxBaZCxeBUB0DYUVc7LFASgiZFbY3aCin2KcoZSQxWR32ToOUeGiuSGJwRnHXUbgpi8THQVLvUMTKr9jNh2DqiP8G7moJMAJ7N3sHMFUi5A/0pKpYQYw4gBUx9nagBS1bMRY00Lrv5hhToQneBvyEimxESnC/84yJx2aDsjQCDbTCy3ZnZ5uVcXpiccZtQxNfaAdi+6Nj+/Y3WVyMJ+qq+sqpdfUEd9lZ3ha7qjddVZ+YN1OXOzLkJ2HDiTpGonqSJk9W98ys8hJgCqT/GhBNKJ5i4IsaWMcE6DeRa0x4h67uQ2rzAa8IMoAVTZB8VfzKMp04hrjIB2U5ICn2/pkhrXFygaT1caQtiLMYUWQJNyInVYQ3LO9Ddx8Y2RyHEnnyZP8iuBWLss51cMccxtODVQ8qSbpFxpKQ4AuUgWXa2AU1oVEQFSR4bA0ksRntm/h5N9yxV9wjUY1OHCWvm69+lGNKuVwl+ZwX/cQXHxU3u26d42AbuR/jVJXyph++49j6syR2a53wGJUvNDrhBwZJN6Z4//gJWA237iHVQHidoxVICJSAKv/HCbxNSZBUD933PMkFTTjHGgS0zcdY6VCTLzcUycxNkGL9ZgXrIAcpJzo5oGrSoMxJzNc6UYOrsxJw6bGwxbk4od9HmGlEMLkMd1FUU5Q471U4+bmIwGJJIDugkgyEpdqE6QIxFpKKwjpQiZhizqDGIa0CEupjibLX5XADYIo9nnLWoxjxWdNXmM37SnZAGkDPmGHXbXkjbkQWcd2TejM7MdmzANmjZJpFeBh7b5pVfcWfmNTgGX9XXX10wIfwqRSdc1deurr6db6Aud2Y2J9MBtDxaPxyiA/JVddueArkDkoZuC9FjNXu4BhFyEKMnpg6Ja8Q/hv4Y45dIXCFhifhl5ioYi0kDp6W/C90RrO9l74SU85IK/5AiniKpp+8XxNgOHiOD7b4GTIpI7JGwoiNmNZIUmJjHVkIETJZe+zO6pGgSEIe1U4REEsGnDp96Quqx2pNSQrEUeIwRMCVe6gHsZX5Nb0uMem6E55imY2b9fW6tfpt3dp9l0j7L7urTGyATEH57lV/6sx7ulu/hOHqSQkw5n+gj197PO6a3c+SP5HHRwe5T2L33cGv3aZ6+9n5QWCncWR0TEJ5rF6yGi/qP3P4e/ty3/xkqa5la+N2zuzyQmufPniOQt3dtMhsWfQvqMapEVRKeqrpGlIKmuUYiYRFc0QAJJ5bW1PhiTipvkuprTIsZlSkpy53sbyiOZEuMySGYYmuSqTJoLGak4hDVRBc7opQ52dxWRCmJJIzYPPIas78GB2JnCypXM3VTrDGQoyXz51Ysztb5NzFgisF7BkBpbIWqMit3Nl0FESGkgI+enWoHZ1wG0aPMdSvUEc5HNW8EzBw0B8zL+YU4ge3v4AhYnjSyGKMGRg7Na6lxgdt0Zq7GEN9Qtf0Z/EY1Ifxmqqt38A3UZaXGeAUnmghDaB8oSRX1S+juIkYx2hJGFUhcZ7IslkQmZqbUk2JWAUHMzieiSH+ECWeE/hFrDHVlsLFFJOTtpxa052h5j0V/guuPKeMpxjbMiHl8knKopEuetHwRwhkmniEpstZEGTN4MaUDstxbUg/+DLqHqEzwdodQz4nNU5TdA9KQZK3aE0Ki0JAjGgZhddTAZx5+ngf9MR+tpzhjMBQEWxNUeTo8GLQ1W8cWmIZHF/72G0vlXoAJsAJWSdB+CUPn5VsO3kc9vYaKoZSCAk9tYbfax9VP8/76gOOTO3xJvkCr8On7n+F26bi3fowhJ0q/c/4MpXXcnN/mucfPMTNwf/UYf3qXqHCSYGp3EBwYaNuHGXxicSrYcg+p9jFdn3OnUIw4YrmD9tmDR6JDyn364KnFMisnpGKftl/TD8GghUSSdQMwqaAwYHdR4zgJkZQyb6kv5uxNbuDtcyTxxGIOKgSXSZU701sclBWn6/tUtmZSNhnEiMGMn18EI5aU0QwqJW7ofogq06Jhv95nWs0RcazDGkGIKdLHPo9UVS6Q4UeQMYKfERCMBODXM7KpXf0SkvB2d3QbzFyu0pbcmt16XXlIb5bHzFW9veqVEtCv6uuvrsDM66w2tDxcPcSKzS3/2GcjOXGIJmbFLKt/hrgBuiNiipjuIVLNc6o0SqG5+5HEoVKAdGhKG+UTQwCktkfYsMakjuX6CBXh1OxyEM4gtGAqSIEQfQZPYU2Ma8qwwhQVagsi5eB6KXmM1N2D/j4S1mAEidnJP6ri0ppkJMuwU8ycGQziF6TJU4BFYp9TlSUnUpuwJgwci6RKZvFY7hz/Pr/+8Hn2Bb7cWT609zSiDtXEbnuHSttXPd6/vYZP9XBo8tgoKaz6YzR6SnJXZl6WRA0YsXz4xrdxfPJl3rt7g14TOjjkTqvzxTAq/NoLv4NIHoPN6n0m1QyMp3FTDHAgoH7Bl86+TKcwE9gtGkpjQA2iSiALnXWQIquAuhkzKQClIrGkwJmCXhyFWKwGkmbJe6eKKSaIK1ARrCk4qPdYhBOiKVAxGE3MJtdI9U18eQ27PrugLHrn3nvo1s+yV06YTG7QxcS0mFKXDbacEf2aJPdZhzW36z1itUNlhk5gtsYDW+d9nzyFjFlJDC6pgBGXDf1siYhw1B4B5wvBy3VmhMyZebQ6B6dvFjDYBkWbzKWX4T98pc95eTtX0t1vrLoAZq54TF/3dQVmXmf5mLkwbWizJLW9i+mP0PKAd8xvserP8N5jwhIBkjEkAlbyYnq0uMMyBK5VM0QTKiaHOKZ1HgWlDqTIidLdEc4u0N4iZoK0L2ZH3uoma7+i7c+oXQY8wc7A7KL+lJgiNq0wqYby2iBDTkCB1T4nbsfRbC8HK6YUQCCoQEoYTbjuEagDEwmhHeTRFfNqhkRDqwaJnkp7UiowKbCrDxCUzyyO+eQqsIxwvYAuRLwKVep4z9l/yFECDERe9wzU1/Eyo+m+xG54QJ1W3PPwyXXmn7Qpd2Y6hefO7nAzelQzsdeqR8ISqoa9co9m7rEihGTQlChCC5pdb9PwpB1Zal0buDa/SWMrjMKkmFID0cD9x7/DyfqYpNBUeUzjXI3YcgAxFTFGEpEY1tnrp9zDGkv0SwqBwpYYa1GxGBEsgTjwkRJKVU6wzU0wJbWb0tGSiimtneUuV1xR2YJQzhFjKWyx8XExYnCuZGd6C+NKJtN3oH5Bt7yTP6yS5drRVPh4Rutb9sudzLECkrFoMUdDS6yfpix3kZH/pencS2kYg8rw31i1q+lix3Yi9Xj7GPS4Dmu6mAnCzdA1ejPqSZyZN2scdJVU/Y1dtauZFlNKW16Nmb4B6urb+TprWk43WSVtaAmD+silQGVylk9IHpt8Bgr+FJLmLoYmUncCqc1OuKnPrh+2Bk2E2KLdYyScYbsjvD8Fv0Jim+W1sUX6x0h3D2/y1XwapNUal+BP8X6BCQtcXFP4UyQFQlJMCjD4yDD0TgSDaiRET9ueEEIOpRQNCEqbOnpds45dduFFacoZrphgELokiAYm3YscdF9k1z+HQRHg0ASCZgXQjsnTknVMTOKjDZABuGdv4E1FQojW0VHxvB7yb8/gi+ucKO0TRAFn8we3bReElHOIrM1dA0RyQKNAFMl52NbgkselllIS15sD2mE0tR6Mgy2wV+zmcZ44JvU+65jHXcfLe2gWanFz/g5kGB015T6QstzaOCQlNObkpsJOSFi02EFsTV00NLYh4qhcjUsBjYEkBmKPNTU7zXX2p4dZzm4rRGwm+RIQN0VMRXK7qFh2611qV7NX7W24HVpeY+X2MjkZObfkN46cdO4ItsCn7gJZtk8JcRO0uobWh0yKCWbTlRjuJ2Zj/d4UzQXAMDr4wnl3ZPv2y74uu/Xu6/7ePakuh0J+tVRHV5yZb6wSEXbr3QscrKv6+q0rMPM6a2PypZHjo98dnHrBkGXZabD5z4Zxa5JfoSlgjEFJ2QhOFVLIAZPkq30QQuzQ9nFWEo18nLjMZN/UZmIwQGyR2GNSjwkrUlhCivl5Uw8xUqeAi+usDPILTOpzfpDaHLZoSgSLElj5BWt/Ru9XeWSmfSaYKvQxkGxNMgU2tThjoD/LhGQr7K+/SBOPqHRx4Thdc3mcc+jAKFgF9Jgqnmzuc694hrtcQxAKY6ltRcAQdU0tUNsMhq5VBe/be4bdnWt5ZGQAgV6hKGpUs67ahTVGIImjpyKKoTZKU81JpuI9h+/nj77rB3nX/rs2oZFNUTOvphQiVK5iVu+xM8lhhiObxwi8Y/4MopI7acVOJniLJUkBcYFHkBQoigYVR+bM5A5KUc64OX8n+5MbWCNE7Ul+iaQWJ46Jm+U0iORxtsCZmt7l5HCtrsP0XajJxGtnHPv1PpWrNuMQsRVnoeP+6j6KYE2ZOyymZOIaEENhpqDKvdM7G2fqdggPrIpJ/hwat+nMJE0DOBj4I6rZDNCeZwOZkWwML+nMwEs5LF+tDseb3ZmB80BLuOrMXNVVvZ3rqrf2BsqJw8SONq65v7qf/5YCIsJZv6KOPTatUQ0Yf5Rzh+QmqiGf9CVA6jEaUKlBCpz2xCjEuEbX9wmxxZG9a9AeCR3eLxDZzaTbUbKrgeBXRLcmFRNMXGN1MYxCEoSOIrUEMSSxiJVNlpOEM0zs89TJQJ8Cvj0lRsWlbHKnQLJziEumqUfCAsKS2N6h0Y76ZWIFjMD3NNDtfw/37n0cD9yOp4wX/i+Uz7Cwe2gfSSIYYBVWdDhaPFGhMvC+3VvsX/+DtH5Bt7rPQ3eUfVHIYGS/vA5YrPYYrbBhiSV7ubgUsc5SSpU5LQj7s+v8qYPv5BPP/Qpny7t86+5tCnHslTMsUCJc33mK5x7kUUwJTOoZdTFBokXE4YoGjTM0HueUcdsQbUWyDa7YQ2MP0WOMwSaLVtcxpqTWE3xMqBqSQFLBGUHKGbRrksYMflyJL2b03MZZB8YNAMQiqlS2whqbCbjDuGkMPFWrVNN3UtV77FQTbFyxU+9T6QpQUE8bWyp3QCJnNhUDP2cbfIwjJr0EEApTEOPAUdkKlHxSZ2a7w/HVMIu77D78ZnJbtnkzV5yZq7qqt29dgZnXW5qwGnLatCb6kAMZJ4ZMqhQzOAFHoAB/gkGQpMR4hsoIJDwGiMWUiGJFILR0/pS+XxH9isJVoD1oxPePUY3EsCJqYIIgUhDV0vkVUe4BDhfXmBixYrEGJB7RR0FkWJx0yN2JLRhHUEPAENThk6L9kiaeUugZRb9CUMpHn2En5Q7UWv40LP4Tdvn73Lp0aIIUdMEzHdaB75tAH7/I5yYlZerZseP9Kk6Kpwj+eMiRSqTowVY4U7JcexqTuTJTWxBS9u4pjePW/CmePb7DSRpur3aI2mVmMAljwOKzr4s4jBi0mCHrR3gp6amhnPG9z/wAbRC6k09RlVNMkSW81jhmZrYZL1UGPvaOj+W33k1QN8W5OZIe5LGhqQl2h+hmaLGHsSU6iJ9FDKbcRWOWvffRs+7X9LEnlA1rFWxRUNiaDiFpxKlhvzngvjgwJdacd0cQQ20Lrk2ucdKdYMlgYgQVecQZMMay1+wzLWccL+9BuYd0g5pIA6fdKVEtmJJichsnBuumGYiI2bj6ZpAwjLJGh11b0MZM3HbGvaRrcTlL6eb05gZwvdm1GXF9Ffxgtv1HrjozV3VVb9+6AjOvt8IC0x9RhVPa0BJNgysqGpPN01RsDpQWy9SWdJowKaD+aJCwCkaEFNvB2MzlK/LUozEQuyVFvUdKfXZ6I0J/isSObJtXZpIuLoMn7ZBUgV8QeYzRkP1sXEkSsDE77UYsxuRWi2oCU4BY1JjMqzCKpo6b3eepw/koyLUXx0fNvV984mF5XL2XtZY8Xn2G20UeMwGU4ZgPX4rEWVbvxBqXs420QyRx5Fv+wwv/CYmeWy6DCAMUtmaRAiF21BiuTW5yt13yqbPH/OD1d+dFPGVjPxGLjeO4IyGmJGgkotnpmEQnFdY0JBvBDiMWV5Mmt3HrByTjuDY/RO5nZtF3X38Xh80ufVhgbI3YYsg1MpvFP4gBW2Nck1tSMnq5CMZNIJ4Chi729LElGUdkIPiIzVwXyWowBErbMDHZmLAwEYzN/kFycbRTunIzytqtdlEUHz1Bw5CSbakmt0n9itKX7Na7HGEy4Db5TZlUexc9WAbgETVmldKlzsxlWeurkWW/mqZkYyDkZSXVm1Hbkt2vdbLzVV3VVb32ugIzr7ekIGjACNj2Lup2sOY6xmXJsRqHEctevT94a2QNTfSLAUCAEcX3SwwGa8rcmSl2sMvPYNwuxAmlKBo7VEDUY8KaRCAVJZBQY1FjibhBzROI7gBQrM0hiugE0YBKmTkdACPPo5hDjBBaboUXud0/fN2HpKekoyZET4jwfMpGd9fLEpu6C/d95OFZegpZgy0HErTy3OkLOZhQcqTAkAGOoaRTgzEVGbAI3/u+H+FbQ2LaPQ/hlJhyh8DYAoIHM6Ww2SCuT4EUlvSpp9e80O4UFaUk2hApjMtghIrodvFul2kV+fCt7+cGp3zr9Q/zWCV3zqTCkHOonCkQTM67SkpBxA2qMPFn59nUYjJHylaoqYBlJuTKBDSgbgcZOhxt8MxQKjdh4mZY2qw+w6Kcdx9GgFDaksPmkIPmgNPulC52+ORzKvnQtZiWU3aaa+w4KKoD6M6yFQDZSO5JZnIGQyTmGaPYDViArARZ9Iv8HE/ouHwtybKXxz9v5jhIRDZE/zEs86qu6qrefnUFZl5vDVejoor3S8RMmJGTnI/7M7KaJGHa03zlbSdDB2WwgNeYXXj9EQWCtQVRKopiF3EVRf8IVUtgdBhWJPYMKwtDRjNqLbG6TuqXoB2ooejvYVyDTTUxeqIpKVOX83cMGJUMuGwDBpRTol9yKx2/rkOxqp+ho2TpAwFlHZeDmgh+P0ww17+fKjxk9+yT+f4J/uMaXjh7Fute5AM3vpNPPfwshwYWMTeiSqCN2XF3Yi3BGtQ6rBZUNhKkYq2CcQ3Sg7EFwU6Q1FMhiK0p7ZSSQEwJa1yOi8AQbIPYGdPqkKZKhH6JP81eK2JAXI2aErVT3rFzg1suS6aTb7FiMNaBnUJY4mwBYvApkqFQHi6l/iQHcZrzdtS0mLBMPVoe5JFTCnhXE7BUboIU++DuEftTVBOFLZiVc0xaUks1dGbOJc9j10BRJsUEayzOOJqi4eHyIQfNwQVTuaZoEHYwbortVwN4ezlXXNl0PBBQzoNSIXdabs5uXvj90qNf12fp9dRl4PRmA6lrk2skTVfy3au6qrdxXX07X28Zx25zyOnxFzAhA5ZJNSV0a3BTBKXqj8Ef49sjRBShyaOd0GNii40d4k+gmFKox3b3UemppSC5Ci+RE1NikieahEqNUY/GzOnw1mZejgzuqyki0uP8qOooUDy/9+hzHK/usJaSqqh45uA7MNrTa6InoZoo04KCc6l0Esvx7DvotWDm7xLL6zyyh7i05LB/jsbfR+Kax4c/yEP3NM3iM0i4R8KypsuEYYWmnlC4irTzfSz2v5MXf++f8cJ6zXLISeqD59df+A1Sgr0id2J6YCLZA0Yc7E8O6ExBbxtc6ilQjCnoNbE2DaXdpTCCJOFMHU47ELAEKjzJTpCUCcbCIOUWgeoQ0hoT+jzm0YjEzLNJAMlTpjWRCcFmMGNMiRYTKBqIa0qb84qiCEHGPoyicU0q95G4yt0vhHk5Y9kvN+67iYRXBWOzFL6YonaKckxKKSdi19dA13n8VMxJZgKhZcxDAi6ADGey0mlaTulj/5L7iMm/X2uucRQ9tpg+mQsydCT61A/gYCup+glA5bLB3NeSX/LV7MzAxZHeVV3VVb096wrMvIEqJ+9gbg1nOgAC/wAtr2PDGZJqirSmTz0pLBA3Q8UTk8fFQUKdekKKaIyIGhLZoCwah9Ueb0pEHPlC00BxDelPcraSlJgYc8p08oSwACJi8qlcNIEtebR6wBcefw4AzxrWENxn2dl9Hz5GitRS90sOw93N6zqefICz5lsoxRNDh3pQY4i2xuiazuyg+x8AW9HZ3YF0O+wjhr7vsIMh3XVbUduCutpl0Z0Rm3cj/jP4qBTD+rAYqAiB/Jhe4VsOv5XaOW7EY5wxnCWlt3N2tMVh6VXoTIOXhJoSSQVJO5JUpNRh3JwZHqcRpz1rKUCVQpQkNSIG6xqiOtLqcR65oaxjoCxqln4BcYXXSBsjRVJwDQmDlnsDUTjlDCUpMrfENiRVbFgQi10Qjynn4OaMfi1G8leuMgUh9SQpNzLvebXLGkcwExJKLyWVJEx1bfjA7UKX1VUiciFOY/x5HIUoik+boeKWJb/dPP6guQbFy2cVjZEGViwMcQUvt6i/lQZzlzsxV8Djqq7qm6+uvvVvpESwYYVJPVEcKXRIWoMmCiOU2pNiHj3JIBNWDElzf0BDh+8XpNgSk8f6UxTJ8YQpYNOawj8mDeGQYkqSLbN3DZEdTqjiGaE7QlKL90tiaLNCRQxrKXnh5A6J7JybyGnRpyfPk0XQiSQOll/EDV2Z3kxY188QbYEZOBXJFAQVzrCZQKwB70/xYpHUYkKbTffEEYzhLHpaBa8wKaeYgVeBsew6x/t3383Hbn+YErjpNoeSKtvE8KFr72e/noE4gp3S2xlJCmaupjKAm+Kra3R2iseBFJiNbBmCmzBtdplX8+yYbBze7SEoVrL8GFuTqkOCnYI19OUBXXmDLkVWfkEZWyrJIaGLfoXXnuR2s8ldsYvFQcpqsVDu4t2MIG4gzko+roA1RX5xw1fN2jp3ZoylsVMQSHaKuJppuYNzDgSWajn1Sx4thwiAyx2WoTOzU+1gxDAdVFhGDIfN4dZHVC49bquD8irjmHF0ZCRbIL6Sj8tl1c9bypm5Mre7qqv6pqsrMPNGKnRoWFKop1NL158MTr0LJqbI8QBEstQiIdqT3IQoOdVX0xqjfb7iFyWmHtWA2pyzZMIC48+IoUXCihiOhuDHgEkt0q+he4yNPSYGZDDmawdyr0p2By7JipzjmDmoGiPPntxBNNFpxKzvbF7SmTskFDsENyGZTDJOOHwMmHKOMxbVHLfQhS6/NlFEE8k4vG1YRc9a8xipsBNEffbIycxjBENRVDR1RZfgfsjGeij80Lt/gA9d/zaiKUADyTZEWxNtBaoY1azGwrKMkaWdk6pdjK1RU+UE6PKAqauxtsS5EjEVRTHHmym+mCMiJFPgo0fLfaI7QIxDiznRlsTB5t8MnQlnHL0aFkmzEZ6AKWcQFri4pLYTBOilxLkJUh0QN52Y4Ss2jHecK8EYrEbE2CEVyVDavN150TDRwCStASWoH0DESx12BWFSTLg+vX4BTIy+KzpED8B5Z4YLrrav/PUvB2M8a2wG7mNX51XGTF9rP5ZXkoVf1VVd1TdHXYGZN1IaSCSExLo7ou1OSMlj+mPK1Z1MAB3kwDH16Pohq8Xz9LGFpGhqEXK6Y1JFpWTdL0GzR43pH1GGM2r/aHD+DYQYkOjpYsKHJYgbxko6bCsRFYxGrEaWoacHFgprBS95Wfz9089jUkT7Ba67l18OENw+IBRuL3NuhjXQ4BE7xWjuNKGRmBTUQvJEFUQFHyJdSFmBZIeRV+xBJSd7j4cOx0ef+hj7Tba2T8DB/IBCTFb7aMKmgGIJCBEhxoRImbPITbXxyylshVR72OY2rtqnqnYwCBWG0lr260NSUdGXc4KbYcsdQrGfw0DFItZSuppSW2xc5hGUkaycEkMylo4SX+wSxSKYPD4yFkkde9PrzMsZO9NbpGIX4xrSGNRoxq9YXmCtcaRiFy3mSDFlp5rRuIr9ag+6h7iwYFJOqayDwX150S9Yx55Fv6AN2dtlWw49pkWzeSbZmN29pDNjthQ5r9LBEDHZGFKy1fIrdTzeym7IW6mkuqqruqq3R11xZl5vhRWsX0T6x7jYM48voK4iacCmjrp/FtPezz4iKSEs6fslZVgi2uc04hhzp8FOkBxLzDJEavUUaQ1hjdEOGzqkP0U14mNHoR6vEUHwqSOEM1QUTwYxAcUOk41F8CjQCXzo+rdy/OizGIFuvQBNlO0L2MEIryWHFzbFhNNiioTHxLimSwpGsLFDsVnZEnrEpdxlQhHtOe2P+cTRZ6mBLsGsqFAsfWzp+2NEsv+OHbxgZtWM77z1XaR5z3F3l6dnNyjqA3oNmOQpjZBMibcFrd3JrsFSorbClgewPibZAicGZAKacGGVlUYUoJ46GTpXk2iAEqVF7YSd+pDT/pSq2kPVUNqSXoekcrGIrZEUUE0EU+HtDK2u516bbbBSQVGDm1NJonbZS4hh/DM6kpx3CfK/zk1QU0Ixp9FIiGt2yiq/3yjGWGIxR0yBmgZQViF33FTPux+Vq1iH/L4t+gWHzSGP14/ZqXZy52mIIbjcmRFbQxxe56tey2xFMWz5rWxLtJ9UX2vOyvbzXXVlruqqvjnrqjPzeksTxCXGLyEFynCWr+rDAhRMXCJhjYRTiv4RRTijSCucP4a4wsQ1qmuQLCM2/jRv01hMWGJTwrUPKNoTXDjLPIoYiX6BNxYXO0QjoTvFxBaPIZFNzlxoMamj6xe0g0PufPo0tye3s/QYaP0pCaVZfmHzkk6ZkjBDwGTmxmjqiCjLGCjjKW5cFEmoBKIRNEW8X/Clk3vjUI0WqJq9HLQsjuRPIQWwjmRKoq3BFIjA+3Zu8tEb305VzQl2Fy81EUsyDspdXP0UmR5tcKZA3S62vkZvJ1T0Gy8XK47GNexMb2dia/KAYmyRs5qArjgkmSIHZqoSNHOZRBzTYoYAKgV1dRtjCpI4ztwetpwhEjHNIZDVSPmNtoOHDCiGUOxjbE20Exi7GhveDJnbU+6jxQ7TcgqDqZ7EIdF7MLJTU2fX5w0sOv+qjpEAl/ORbs1uMS2nuTOjL9OZEQPVNSh24FIA5JNqXs0BeHr3necffX0ymGlcc+ExX6u6AGauujJXdVXflHUFZl5viYUUUBIGnyXS/gy7ehbxC4rkIfY4v0bUowxpzuoRf4qEZebcYHCpI6Y1KeX8ZqEHDUhcY3QJ6unUsCY/Z1SLxWRwEFtcWhI0pyInBQkLWoXF6pgkmfxr6zkGS23KfO0aTvnii7+BWX4RyFya3zo55t/c+Y+8sHhIwRoTV9iU05+IyvHyRR6sHuZuTOox6ul9S4o9zy6e3+QkiWRF0sTMiKoEUxHEEVPCFTtYm31cGFQ4ZjT+T55gLHH0VMHR2SmxnDNxVVZeGQvG4orZMGKzkJQ+eFQEYx1F0WTptKvBVhgzRUxJ7+ZodW0gFFuSJvygxEq2ZOJqymKHyfQ2VDuAUBZTajdlXu1SFHsYsTlkUzR35xgJrxm0YStMfYMkjlQeYNwcyj3GzkxhHK6+QWWnOEZlUTEohhSpr58DH7/In5Px8zbUyE9pimYDaHzym4U8509lzsxGmr3tjmvLV1QxbVdhCm5MbrDf7G/+9nKdl716jxvTGzmA9WtY2/tzpWS6qqv65qyrb/7rrQHM5JBHk8dFcQX+NAc30iHJY+ISp55SCgo3zUZ4ZkJMCVVBsPhwSpci3v//27vzGMvO8sD/3+ddznKXurX16m4vGDCL2cNAMoQlGhF+IkIIkBhkBWVmlExGYKJk0Gj4Y+Qh85uBKJqF+ScjJcRhRkmcyQQECgk/MRNMkp+B8DMmGCcYDDbGeGm7t9rucs55398f77m3q6qr2+2i3d3VPB+p5K5bp+5SdXzPU8/7vM9zmjpW6S/fZog0Y0yoAMOkGdPU69TNmLpex9gIxhFinZaoIoikcQijCOtVxWpbo1IBc3aAMzDfXcII5BGefOxOOqQlh5UGRjFtj/7q8W/TuPm0vRuY4Bg1Y776g7/mvie+wenRiXRxDGMkThjXq6xOAmsBqgaOBTjRwNzcYWoxVBhGITBCUjM68QSxmAjdrIe4jEYEjE9DOdtsROUKYucIdb6folhmoVxMxbDGghFMZz/g6BRdGpd2CVnxIB5oRwMYj8lKynyBUBzFF8uM/FzKzsRILZJ66poMZz37evuYK+bIigUa10OyeQblAnWo0o4ysZRZPw3+RFI2BTvrqoyYM5kLMZh8oc3MpP/VBFjuH2G+f6jdHr3IUm9/Ot5mbYfjzdkFmd3X1E4X782t9qePH9kUzGzaBXXhptu5t75NZOfI6Ey75V5qusyklNKamd0SQwxpN0/VdgImjKDxUG/g4pCqXiOECd54aueQ2hDanSYWII7AFFTiME2GGz2MybpgBR+GVGFE2ofUQFMRnGUUIaPGEqhMhxihoOa5zfcBCAin6DIS4dtrTzIJaSPNXDGPoWLOz7PGY/QNvL5z5uUcq9NlcyPCD1ePY8W2AxQtNYZj4yfoSFqyOrn2JAuL1zEan+Tupx5mzgtjUgBzKoAX+Il9L8ZmfZpxQxBDtDmhXsXanMaVxFAR83liU7c7tADXYdK2zYs2AykQV2BdB9tkCJKyRBjq8SmWy0PkWZduPMGpJiBhRJ71U/BgM9IyUJqU3fE9utmAUVMxdr00QJFULB3EUOX7iNZTdo5ANk9oGiar3yfzfXA5Q9shYih8iTUZYizEOu2wcmU7okCQNuND+mzTssf0v23QYdKSjBGTgqB8HsRiw4ktWZjpv6PJEWTW5Xdqp8Z5syxMu9w0zdTAM1yG2bactFguslFtMCgGF34fl4AuMymlNJjZNUOYrKQgRoRaLHW1wVg8tt7AGaGqVpAwprI9TITgCiSkgtpeWEsX1JguZp4x4yjkBExd42JDFScQ00QeCRV108VF8AAxtffvjx+mO3l807OKHAon+EG9n++tHGPBpq66c3mXOPohZZYimNd34Gj7B3aIaYxAO86Sjckao9FTdEKTgi3T4fTw2xSSApU6QtU0/P2p7/BkBSsCXYEnG7jp4Ku4eX4/S77ENGs0IRBMjqHdcWVygilpbMmw2iA2Q5qsh4QKbIfGlKmPjmQ0tsQB0Q9Y9pFhhNCcTr1kiAwnp1gs56E6SY2h8n3IF6HcD1UaKYHrABllNk+/d4RmeBwZrdLYDrUtCUQMNgUS+dysvqVwGQd6+zleTVIDvAiQAolofGo+1w6Y9H4uzYNqanJXzoKZLRmN6b9jhFE7/6o8kAKiTctQ1jqCn081VJu+r18s7FiLsnlcwcx0B5qYVDeDnLPO5ZkoXHHJl5AuhC4tKaU0mNmtZkxs1miiMKoqYqwQaWhiTRwfJ+RdrExrSARplyPGtJ1/m9HsAmRDhQtjQr2OcRbLBmDTN8dAI7AGNM0aeTNBXMRUJ9l38q/JqhNnPbVF1jBr/x8fWIL7x/BYfg0Hq8dYrB5hxR3kgIUbNu3QPSV95ruBh0+tsxrSOIHvHX+QgYfK9fnbU99lNFxnybaBDHD/qUdYC6keZyXCqoHVCJ3uYZzrpD4xVGDW0rJSiGA71CEgNgUMIo5IYC1Y5khLQrVxSCjT3CibY2kIvgv5MjJ6kuBOEk2H2pTQtBOdo9CIpGGf+X7wC+C6YIq05OQKfLmELxbw9RqdrEfjOimgaSqyfAGpT2Fs3mZCDMZmgKSuvrZDiB4TJojxGFekQaARcCVCYKFcQiYb9LJ+O1iUbUsubcagGUFIX6fYD+JSFqmtv0lNbPyZf8t0S/fOU6dnu5V2ysy0WUBka7bmgvkeVGspQLyCbc7GaGCj1I8nDWZ2qzpNMDkbzZgqjHGTIUSBGOgQmUxWsJI2A4dmhRgLhBEyXsPEBl+tslZt8I1T36QsF7l+/kZcs0rNIO2oCROCROooTKKFaJDYEMOYfHyM+fEDZz2lCYasXcaYb699BxwcNxssrd0FwDCc5NCm5aWVIOS9a+mPn+K6+SXue+phQoRvrzzAi+eX2agjf/v4g7w4T1mZKqZMTgTqAMdD2oadRxjanIXOMkEqqrxPM6mpZR0XI9ZmNGGC8R0msUZiA8am2hljUh+aCLUpiD6DSQ9rIJiMKA7Tfw5Ua2m3lbi05b1doqlDQxUiQXJsuQ/yQboQ5/uAGkyOLw9h6hUMBm8zlstlqlCli7wpCH4AfpAu3CZLM5jampvG94lkmMkJkDQXKhXQpl1UhAneegpfEoVZMLOltmR6wW2b3p25PfVw2fx5P5tjI1R4akZA8AtnzT46c7dnRhpMhRhm84RCDFjspt1MzySYmUvb3M8RSF2JtGZGqR9PGszslu3QREMMFZNqg7UwYWAzkAwbx1CtI9UIiUOMWNJM5YiJddptNDrF3594gEcraDZOsT48wUv2vSDV3dg8XUhDRIBacsYEbJhwOB6jz2j2NAKGdb/Ml1c2eHS0xnvmIdv2fr4UTs7+XYZ1yk2/9W+b/Ty/vSh3s7n2r3j45uN/z9zptHT0aJ0yOdNt1yFCLalYeBJS994GeOuNb8W4DjCi7BxhjIOmplfMY2wXqVeYYNioHJ6AGEtjuljjCY0liKExjiAFzh1nIh2MX2gnVZfE3nNxoyeYNBVYT2V71H6e4cb3QCIxm0OyBehclzId69+Heg1cDzft8yKu3Yp9pj1/FDA2R/JFyBZhcgJjO0Q3B/UYxNLJFliZnKT0vTMBgc0Bk4q1xYMEYoyz+92amZkuM20LZmBb8zpDN+vQzXqsjlcJtpsKm88RUGzfrTT9d2YzYowM6yHe+t1lZmBPBTJw7gyWUurqpsHMbtWnGI6PEauTmFAzCTDO5+gaiNUGxAm2WSVSI+TEmFrw0wyJoWKlfowccBG6BubqU8j4SSiW24xFuxuHSG0MWay4rnpgSyBzuoFH3FEMBavjY1QR/nIV5hy8IIe5p3lfv39ieO6B5xEnJ4giiC+4YelGHnnsu/RMWkLaaFJR8DjAoYUjbMQRp1eeYtLAsQYyA9cPjvLi5RdS5z0Wuwc42p3HuDlOjI5jbYYRKIxlbAwShEYMvglpjEOo21lGUNsuNj9KFQMuH6YJACbtELLWYVwGtqS0Qm1LyiYSm3UmpD4vVgxiXGrZ7/pnsh42zUyyxmGNJXcFVVPNlmGElMWQGGCcZiFJsUzTOUo/Rp5qGpZ6B8ibVRxjZDpd3Ng2+xOQ0BBtKrSdjhzYWjNzjiBCUp+ZM5+f+Z68mGe1Tvd1zszMDstMIYbUBLCezLoD7yozs4cM8gHDekgvu7At50qpq4sGM7vVVIThKagniAiZjIECixBjA8243bodII4wcUTAEJohplqnGm5gJBXz/nQXbswhVt/lkY05KG6iqtaJpNkDLla8aPxtHGf+qn+8gk+vgpfvsyCQG/ABHq/T0s9fDlMA8qv7SzpxyKod8LC/lueP78fHCRM7x437X0rlS8YTS4iGgHDzgdfwlSe+Sy6wQZpiPSRNWFieu5ZHV55gPTzFBDhVw1Dgtdf8A4iwbrv0ekegXGRt+ASTGClNGppZuJxxbVInYSmJpFEMtetijEmdgU3B0PcwcUzOfkaTp2Y9bAWLKQ/R+DmoTuGlIYsVVXQ0bTGuRdp5SgZMDrT1KO0AyIUiLdecahrqWGPFpuLY6e7nbRd6yXqIW6AX6lT46rtQ18g0y2IymGZfwhAwWzIzW7ME5woitgUzm74nswXzzm/bFbXtu3dYZqpDPVtmakI6Z3admdkjulm3bUKolPpxpNVyuzV+EjN6JPVEieCaCU09YlKNifUa1KtpSWH2UeOqlTScMG5gY8QDA5cCGUiXtMXxd1nZOEHVNMTYYEPF9eNvbQlknqjgvo1UszJql3gy0kTsmhSAEOHxBh5YfDMPDf4hX59/Cxsyx2PFSziWv4BhdgDnTOpVI45ocwSLd11+5qa307iCjSbdt0R47sILMOJY6l9DZT0PVWne0/MXb8BFiCJgDSYbsFaPWMPT0CDGg2SIceSui4gDY8hMRjefJ/ouBkODoc77LPSO0O9fT172AcE0EwyCuLwdJpkKcx1pzlGMMGoqwOLEpNlDYlI2pnMN+Pl2R5PgxDEoBmknEunCPt0a7eTsuF4QMJbSlyx3ljGdg20jvPYXtqnFv7QZlipU59/NdNaDnCnyTTZvyzZ0fIfSl+c8DbePK6hDzUa1gRU7q5nZnLW5WjMzSqkfb5qZ2S3bp8bTYLCxTruZwgbO9WiaSVsbIWnrbQhI+xe7RaAaQkzBxyv6BWxaOuo2K1Tjxwg4RDI69eNIe6EaBfjyeur1sjTo0z+5ykbarEKMUAIL3XmOb5zCChzqLSOu5LQcAFPQp8KGSbtZV4hNTcgH1PY0jVmnsTnO97hucZFr5m5gPHwEg+f/8sssjr9PzgZBOlx34LX88MR3OUzkddf8FCEMIQYMFhFhJB1q5zCAQVINke1gcoH1p6hDjfguWT6PDZYmnsZgqaXESKRwHZoN22ampB3W6LBiaFwfMzmBIJSuZNhU7XTwBudLxLr0c8ekDsBhHiSfBRMGM5tgPZ08HWPEdY+ctRIk0yLjVj+fZ9SM6TRtFkS2No+LAnFThmTrzppz/d2wrQDYuDTWAs4dAG3+7m1N84bVcHa7iNDEZks9je72UUpdjTSY2a1sQG0yVqsh337y6yw5w7LZh3U9hmuPY3xGYcs0cgCDcV2kPg3AiCb9QQ5cY6uz7ro7epBhfoRu/Sg2pp0xKw187ARc6+BVCwP2lwcpc8f/8+h96SJKuvbdtO/FlD7jvlNPIv3n4gQmIVDIBlbAS2rCl2b3CCF9hpDqTYLrp/EJbsCEJ/FiyfM+PTNPGbtE04HJkFcd/occ6Q4obMHqxjgtJeVz7bKNhTDGiQfjUlDQbGCZPqYQjMW6PmKGCJHadsCYNMLBlURjiSZDpO0DYzwmxlRn4wcE36M0OaPhiGg9plgkLxZnBb4IKSsTxmmbNmda/RvxszzXtBDY2xwjm34XxiFua0akn/fpWwunV2bHTKWalh2Ke6fOl5nZEsxkafs2bG2edw7bg5lp5sWImWVtpktNV+sSk1JKaTCzW9UKbuNh7v7BXzGuVjHAd4ZPUbhvsxAbVg1cO7ihHYIYwXjyrItMPGPGGKBnIG8vgKttd/y+Bd+s4Te+teXh/mKjnbFEW5kTGkqTce3cAR5beYKegzLLGNou+/Ilbljqc6IOUK9T0mCjwVlHxKUGdQSi7xBsSWxb/wuO2g+ojaeuRtTiEFOQGYfP+pSuYNQ0jF0PS6rHMDaQ2Rwrhtxm5C5nVKd6lMx3CJMxSIBYYUKgDbto3BzROKIt0gs3Lo1kCDW2WSe4uZRBiu1SkLG4dihktD3A0HE91u0G3uQcGdyALabzg9oAweUQFmfLTFNicohpW7bF0sQmZWnkzLIRxX5K22M8OrW1+HYaLMWQioxjBTG0x5zJygzybV1yz5kR2bbMZHzaIh7GYJ++Qd3mTMvmupnNu7W2BzpKKXW10ZzzLoXqKTYmq4wnqzQNVG1n3FA3BNp6lnq9vYilLdyESFWtcGJ1jRhh36ZQ8lQDD47TNuftTjXwjRHkkgpxve2n7cQCR+euT5kZgflyGWdzpNxPZnzqJtxMcECR9bHGt0tM6VocyahMSW0KwGB8gRHBxlSvk15HhRhHk+3Hd/YTskUmpqQWT6rUiAQ/R2M7GGfIbc5iscBiuYRzvTZYapd4jCUaT+NLoikZiSUYT+3nmPhB29fFYKnSVGqR9HzaPjRWDM7kYDNivoDp38Bc0aebp+3ds9a3swu8zHZDYdIQSLIFpF1mKmxBIOBtCmJkW/DQ8R0Wy0WWO8tnbhQL+RK4HmSDM8tXYmZBiSBnF6OeN5jZFERJGqSZArCnlzJNZ7IzmwOaabfezeMVlFLqaqSZmV0Kbp5Tk3UaUtFtFVPn3L5JQc04wDAEOgARQhhxYnicH5x4iF67CrLQ/vQjwkpI7fq/OYKXlmfyCCHC/7sO1/cOcMPS81hqVnBsIFgkpoLd19/wjzAr3yYYl6IdDEVMO1om0ZIBeayIroDaEKIAgfVmxLFqhDOGvnis69I067hmgq8rTgXImODEYqxDikOY8CSZTS37uz5v61XS9uqIxYplImnEA8bR2A6VKRi5AUWYEG0EE6izJTYCRFsSJYOsSzQeCQGDIboO3jii7SAmSw3c6tMYcTQCYCizPhu2h7VlymJsbtkf6hQk2DItM/m51ENm05wibz2DYjDbSi1+LhVu2zPLS2e17zc23Zfvt8tMZwKEru8xCg2L5TPomCttwOV7aXnpArIx200LfTcX+xauYCKTLQGOZmaUUlcrDWZ2KdguD42GjAIsmrSbaNqsbhRgHEHYwDcjIoamGfOD9UfSIkuEeZ8KeQEmUgIbhAiPT2Dfvn9A0Zzk5PA0954+xkM1PGdunjKbI6+G2MYhvgfRMLRd5uMQS2AolsoVjMM6NENsNFQhEr3DxQmhnfwcoiDUTOoxIVqiOBrrwRYUo0eRaIi2T90M6Rdz2DjB2i5gsVgQj3GezHcYNRV5GBGsJ7NdvHFshAYBut3DSHkURg+xESMhm6exi4zNKqXLiKSLeF2tkbsOWTZHJ+/TxIp+9zAbqw8RRajdXNqdVEWcy6gmAkScGJbnrsX4rK0viSnQmJw4M6m6c03buyc/q9fLtLncsB5ixWKtB3sBgUi2aQlpU8ZlUMwzON/U6GweQpWCoMnp9sb2+/1c+tgFK5aamjrUs8AltzlVk2qAdtxdpZRSVxENZnapDjXHxydnXUKeu3AtR/IOVoQHnvp7fqKARTZmNaH++J1cXzskg9MVHNk0G2lsejRMGMcaI1Cbkqre4PH1Y7Ot0fPlQtuDJCOaMdYvYEKN+JIwfAorEWMMa8ExCQHXTDBNjQ0RZ/tYGkQCGEsMQhQhiNDYDEtJMB1srJFoMdFiYyBKRjAdEEFsB6xHaIjWEiM0naPI2kOIsRQ2o8h7hDRQCkHI8kXGJifEdQgThngq6zGyBqEm5PMEKanqBssE2ztK084t6mQ9jO/TxIArl2YzjXq+R/AD8mIeTJZqVWzZzjuKZ2YfiYV8GcpDqYneJtMamBjjrKnc7idByzn+vYPp0lFzZvfaOZvpPQOZzRg3Y8b1eEvgIpIqw3WZSSl1tdNgZpfWo+OJp/6e57o0s6iblbhmyHw8xeu6O1+jbnB1+olvCmQCllpyqjxH6poADJuKOlQQ0xBH4+BA9xAb4zVEasR0MNbhjcFJhoghRjBYjElFvjFboB6ewDXrxOCxjSNGQ4PFUJEmfedUoaJvHbHJMOJSgSsGiTFlc2IK18SXUOynXj9JHibpwul7OFdQxQZnGhCDsx5pRoiA9yXUgpCyJhGgXsNOZxoZTywPMrLzyORJMimwUuPF4o1hUC4yjIa5Yh+M00BNEcNg7jrIFtLoB0hBy+REChamQxwh/eB2yJTMF/NM1icslAvnGAr5DGz+RV9o5mNzTxuTnfu4CzSdATWsh5uelsyCl9kymi4zKaWuUhrM7NJv3/V/0wGOenh+AZNmjX3N41iap/0DfbO13ouoJ0MwGV7WU63N6DSV1IzbWs7DC9fhrSeThqwekucDMl8QTElRR+poUv8UMYhpgw+bE2OFEbBhjFAQjYPgU22FpKCpmazRSEPmOgTXJ1oL9ZhAQMKIus09edsDW5D1ryU79SAjWzEMDcv5As44YrVCYfO2sjhijJCZEsyE6DKk7X8SQ42JIW3fFkfH95i3PdaZpKyOGEy7nduIpcy6OMOmjUKbdv804/TfbLD5gDP83I5RZe5y9nX3kducUZ0Col0vwYRN27EvNFgwLgVgYi88ADqPzGZpS/y2fjLbuwPrMpNS6mql72678MOVH/Lb3/h9bsrhJ7uwZOFQ88MUyGw/loxR5zkc8wfP+lqV7Sf4eWoxZHSJMdXa3P/UfYT6NKVJdThdtw8BCglIDCmzYQokG5B3DuJd2U56tu3SkCFkA0KwiJm1yMO6btoCRYCY6lrKyUlcrBHr8Xa6GyeyXq0DpAnXYsh9ngppjadceCG9/rXEGKjFQRTECOK6hKYiGpN2F+VLDIplGr9AcHOAYNpt0BCJYulmXZxxNJK3/VAMzmQYMZRZj9L36GxeJpr2ZZl2VoZ2dMEO3M7t7acZi9XJ6lm3PWO7DRBsdtGGOIrIbEfW1ObAZdpnRoMZpdTVSt/ddmF/dz/v+8kP8oZzjII5VTyXz6zCp07CI2sTHqssX67m+NhTsN4mEMZ2gVHvxbOOsWXWJZB2RQXgwdNPzRrrLZaLOBocqc9KwLQXc8tc7wa8LfC+j7UF/WI+ZT38gGAs0gSsNIjNsb3ribZHI5YYBQkTyuYURuKZZmsRCldiEbwYPIEsm8Pk85At0LgOznhylxEQRnhqmzPJDhJEqJsJYFLzOptjOtcQfb9dWolIbLDtAEhnczKbpw3eYlL9SjsQEqCfzzHIF1LR7BZtZ2VotzLvcBr7/jkzJTvNM9r1EoyfSzuQin27+/6LxJuzg5lpgKY1M0qpq50GM7vgref9L3wLnR1+emM7x0bnWnr9axiT+r/83VPf4e4nv81KgD9dgVW3n7Fboo5QtbtwStcldxlD0jU4kHrOSIR9mcUYKE1Mje9cmbrjGsH7DkVWEn2OsRlOArXtM5Qc8nmCcdgYcOLbgY4pizJpAwIBrAjRdjA4jFh8NqCbdchMRscXVG4e0znKuBlTmwxXLjNfzFO4kjE1pyXnJJbV0UlGzQZMdwYBxjgwOdGkYZDSBjrz5RKL5RJGbNpOLKat7TApaAOmAyJny0npRpgGc3AmM7I5GPG9FMycw0W9qBsH+eKWOU2Xw7RuZmrzcMrp8pNmZpRSVyt9d9sl99Dvz/69ahdZlTlGdsBa+Twm0qVTXDPLtFSk4iRjoMxzKimIRGoBcDQRjMu4dukFWEm/FEsKZkoDTb2eSlFsjyAOTMa4WoOmxoUKn83hrUeMxzYTEMOoadot130a28X6LnkzQcQSBKJYxqagMRmCpbF9vC9ns4pwi4jv48QwNB4jno1qI71g26dfzFHHhqoaMQkTolhMvYZU64CcCWbaJnDRDYhkbWO6gLcZIhbZdIGNJieK4KZblHcMENqamWlPmVl33s2FuD9+pWC527rUtrkAeEqDGaXU1Urf3XZj9bvY7/0OkDYhn3SHOOkPsuEPYGzOKDQM+kdZi7AR2q6+kgKbTt5FgBAbQhQqKRiZnAqLzQe8cP9LmERwkr5vX38BMExiBS6ncR0QSx1C6iUjAU9Mu5pcu7RSrTIxBVkc0nGOwhdgOu1MwxQqRSxRDNFmGIToPMbmiEs9W3zWw9osjWMIDaZeaS+GgrEOg6FnfDttyRAlTxO4fR+M4NohjNam3VExGxCL+TR/afpzbLvmTjMHaebSIjKtddkpKDHbp0Fu6vY7u+38tSjbl5T2dS7vEtHFYMSwWC6S2YyFdqzD9tepwYxS6mql72670b+R9Zf+Jo3JOekOMLYlpS1wPrXuDRhwHV5x6NVUEUYxJRIcUJg5GjEEcQwl43RsmNgekxgxtuTw0gt503P+EZl1iLMs5gfa5RkBcWSmZERO7XJwJbmxmGwR60twA6IpmNgOE2ORCEUMWECMxRqLBGjaYZCCwUpKBYkp20LSgkB6wgUBGytsvYJl2klWmG8vlmkbeEyZJXGp34vNsOIx1s8CjdiOJpDYFiIjxFlQIrOutYik7dXTi7DdlG0wPi0d5Qe2/i6mgcsz2CK9OWMhnF08u1cVrmC5s0zpUwfj7UtP9iIVHCul1JXmxy8ff5GMei9iffA6Js0GngLbnCKajGAKqhCYVBOuXbwRxj/k8ROPcqyC5U6HfeUSdX2CYDyVZBBHRNshcxFjCyo3oHRDnrPwHEIUonhsaAimTFkM46hcSfALmCwNiYydw1Sjp8CUQKSODUEcwRRkNi03CZGsqTHOI2JpYqAWC7ZDnS0Ss3kgIFmHPDZ0/D7Cxg+oabDiQSwxTkAEbzMm2QCpR9TiGdsumcSU4bEdMuPbrEoKGgo/x3j8FDHWGJMBw7RKZDI2BzOCsNDZD1SpTsaWZ4p/jUvBzJb6GXZeZnqaGH3zRf1qvsBvHsVgxOy+l45SSl3h9N1tlxpjCM4jwSFikBCJxhBwQMARWK9GPHfheoZ+mQXp8sL9LyY7/XfQWGrjaWLanmyzEpEIrked7yMPQxocEyAzBowQTUb0HmKqiYm2wBVHqbFISLc516M2hkpyagzGWCQaEItIARaMS3+1V2IZZUtkxSKjznV0+jfC+DEINdbP4d0A7zLqeoz3OQFmmRlvMyYmI+bL1OaHBLGYdihkQPDGnCneBRZ6hwnW8NTwiTRnyXSo3Hw7ckAofMFatcah3qE2q1CCZ2unXHZYToJNWZi4w2072zwFu+vPsSXtKrB5WUmXmJRSVzMNZnZpX+8gY99nFWFSN0TXQbBsGIuEiKEi0mBNyeuufRmrknNytIrE0M5nClRxgrd9Ml9ijIXOEsHNw+RR8B02arASyWMkYImmkxIUMWCaVSROkHqVGiEiWJtRiWESSAGP6+LDhBgFbyqQgsJ12UiVMDTiWB7cSKdzkH5nkfXxY2AMQSxQ0c3msXaIEUdA2lEFDtd2rTU2a1vVmdlYh4jgskEbyLQXUOMwvsti9zAbzXpq3mcLQgwYhK7vYrqGzG3vhrt56aj99/aL8jQw2Txk8mm2WW++sG9firla6bZspdTVTP9c2yXTjMG4NL1aLEShjoY6BEQkTYCuGyIVEUuo1xmNnkphhETqCMMmIs7jfQexaQtzLy/AdlNliQiVLRHbwRKoisNINsBZTy/rzJ5LVdep/4t1RITSdTFi6WQ9imxAr1xEjIMYyVyO910i0LFC4QoWynlcmCDWp23UCIQJ1lispCLfiGkzMxHfBgDSFgRHcbOhmd5mZNPljc0ToE2Oy/vMlfvwLs17aGJDE8JsPpI9q3B3h6WjszIM08936AB8DpuXln5cll6u5uU0pZT68XgnfzZYl7q4YlLWIwgVIW0vpsSHmiiBIBmNGEb1BBMrGuPIaahsRuVKoimIYokYoi0xriDvHMTajLxZp5d1Mfkc+B6uXKb2Xezad7HYNsiAETXGdMhthxFjamPoZ32oB5hgwBXtjKLUR8YVy2QIJltMoYDttz1nLBBoMOlz4xDTpJ43pCWm4PuzpnaB2DatS43rSl/S7R468zPavLXaZCCpiNc0DdBQh5qTG8dmx511wZUdMjPnWmbanJl5GtOdP5t7sVytBvmAtckac/nuJnIrpdReoMHMrqXi2cZukNUTRFK9TGM75M0QEyakwQCOJqadQA2eYLtEfNrxhCGaIgUDoSGSJjlju3ibU/hAZgswGUXnGtzc83nixN8zLx4xKTCpbNYGQjl5MWC+qRhXqbldzOaQRsCVqf5E0tKQ+B519JAv4LpHwHloQrtjytAQIdRph5JJ2ZhJNIR8f6oPajMoIQQQh7S9YUw+3wZN08BiU6BgXBv4+NkW71E9SoFU66wsyeat2TvtWtrp8wu0uTj2atbNunSzq7cuSCmlQJeZds8PaExJjBETKoSKIA6JNS5MyJp1hEhjDU1IAxQxBktFFIcLNZnY1JkfS+PKFAJEA5KWXJyxNCYD47HlEhu2JNqSYHOszcHP0Ygjiif4OWxxCGtzgsnSbSaHbA78IAUTEUxocDYH54kmw/l+6kHTDqqMSFqwCU3aedQGFKv1KG2vljODHkMMiHF0XId+0cfYNvjYvNV6s7ZTrjUpmGlCs+WYs4pURaA4ANn81iUrpZRSahMNZnZLUg2JrU+k8ltxTNwcleuAZKnpfhxTS0EVa+oIvpngYsTanNxYSmfplwuItTSmQ2MLgkQIgUBsr/NpsrKIJzQNQk20JXm5H+N7gG0zKh7J5rH9G2ncAIkRiSEt7WRzgElZEWOxrsd8Nk/pSoqsn9r/C+BKoljq6IAGYx0NhsYUDMPmycuCaV9/AymQIZKJZ1oG3P6Qtv3M0kgDK6lhXz2dr3Q+xqbeM08nX2pHCyxdwC9PKaXU1USXmXbLdpBYIbFt7+sXqFyfGCPRFVSNRULNKFgCnsaAiRU2hrYpXapBEVOk75ecGA3SVNSxohGLEYsxBohY64gxZX86WQeTLSEYApHKD7CuwNiMDENhLKNmRBkbqFZSsBJJ3XObccr8ZD2yfD6FGyZlPcT3CaZDXdeE+jTGd8mKa1iXjJVqhJghgyLtVLJYQgyEAAaDxLCp/uQ8wQwGMQai33LMM6rpMBmEybbfRw52/4Xfh1JKqauGZmZ2q1knNMPUw8UY8H2CZFSmpM7mGOcHGGaLNCanjoFxPWYcKtqN2VhjKF2ZRgiYPAUaoQIiwybOti8LNYQGL2mnkmlGSGzAFpT9G6nzgzR+HmtLxHcRsewrF5nLuszZVJdDGLeFsgbq4WzJK2YLBD+XgoxIW/cjBAkEN0D8gLn+DdhiGYCV8cpsKaj0JcN6SL9YwBvPIJ9vfzBy7mUmMZAvItniWWMIelnvwn/22UIKXvLFZ/57U0opddXRzMxuVSsE8cS2qBXJaHA4Y4jGY4lQCcPQcHzjJOMY6dsegzhEzBAkw2BwJmNkO6notlmniQ1DIsGWOIkEk6fdQ8V+guth44Qm1IxiRZEPWHJdmpWHmBNSBqZep2egLBex1eMQpn1UGggRiHRch1W/D2xBNDmENEBymukZSoeM1IivcDlFFCbNBBGhbJvuiQj9rE/WPciBchGpTs2yPmf61+1QnGs7GFsA6+0hwmL5DIMSY3U5SSml1IwGM7tlPFV2gCiPpsyM69HEDG8LGuPwTUWDYRwqTKyRZgIuRwwEakKMaRaSK4EuoVknhFViqKnrMWIyokCwJU15GKxH6rWUmRHL2ngDHwWMo3QdjDSkIt6068fSpMJe26QlLbEQR2ALvPHEzjWEYpkggo0RbI4TR6irlFGxOWDpdQ8QJkNWJiuEGMjbeUl1aMhcRlkeQKTeeVfROW6TTdusu777Y7OzSCml1LPjsi4zfeQjH+HVr341/X6f/fv38/a3v537779/yzHSXvy2f/zmb/7mZXrWyammoekcps4XiLZP7bsYGozNwBRE1ycaw7gJECapf67kRFsittd26C3Jsz5i0/KOYKjCBDHgjCX4ObzvkdkCP3yUfP17aRu27xLyJRoRmmZMlHbQYzsRO2nAtMGNmBSc+AG4HhT7EN9t+9vEVDPj+/j+czF5WlKK2YCmTFPAe3kPIwYrltPj0wBU2QLBL+B8F1yXWRZmVi5zri3TBrNpNIG22VdKKfWjuqxXki9+8Yu8733v48tf/jKf//znqeuaN7/5zayvr8+Oeeyxx7Z8/O7v/i4iwjvf+c7L+Myh7BwmFAexxQFCNse4mWDqEZkI1jrEOCaxnauUeupirceYjGgd3nr6xTze5WlAoxGKrJM6CIeItSXR9bH5Es441qsNnLEpZLAlTXmQE6OTrFfrgOB9h3b4Ugok6jE0wzaokFRnYgooD0KxnIY2SiriRQTKQ1DunwUhBpPmKJH6v+zr7GOps8SwHnJyeJJRU6VszvTxzlpSOkcwI3br1OqrvGmdUkqpZ99lXWb63Oc+t+Xz22+/nf3793P33Xfz+te/HoCDBw9uOebTn/40b3rTm3jOc55zyZ7nTnKXs9jdz3B9H8PVNQRDY3OiycD1kep0mmEUh0ykIBpLJ59LSz31OG2lRlJH3nYLdiWG3GRMTNX2hikIJmME2NAgRshdQbCdVKcz3dpsMvJsMQUV00xMbHf7iEm3uw7Epi3C3ZcGUG6aWI1Jy0emXaYyGGRT07rFcpGTo5MADOvh7HZvPdSTHQY+niNIMXZTABN0ZpBSSqkf2RVVM3P6dFrCWFzcuSD0iSee4LOf/Syf+MQnznkf4/GY8Xg8+3xlZeXiPsmp2ECsiDajdt00KTpmhHyRUByA0aMY47HGs45QGEe0Paw4qnoNIUtdfE2GlxEYw6QRrM2RUBHzfYTONaxvPILfNLOol89hOwdZI6bnAPT712FmwYtNH2E6q8hs2l3kZv81pOZ3s2Cm7eWS+/RfESFri33hzO6lUX1mkrVsWSaaLjM1Z57HBdBlJqWUUj+qK+ZKEmPk137t13jd617HzTffvOMxn/jEJ+j3+7zjHe845/185CMfYTAYzD6OHj367DzhJgVMTRQavwS2j4hpa0sMoS3+tc4wigUTydoGcAMwNjW2Kw+DGBwREyIhNph8nl73CIsLN6XdSYAxLmV8SEGGc520PZvUKbibDdonFdNykeu0fWxoRwgUqZOuuFkdjYgQXZ8gbssWZyOeftanzErmiq1B5fYJ01sCkWcyZkAsc9kcpSspfXnu45RSSqkLcMUEM+9///v5xje+wR/+4R+e85jf/d3f5ZZbbqEozr375UMf+hCnT5+effzgBz94Np4u2Izo5mgkI7pu2/wOwGER1gMELN5lRGtSWW4EVy5R+wGhWEZ8F4xvgyBoEEKo8S6nzDoE8Wc9bIxgbDnLgJS+u2nYYoDJiVQrAymgMB4616Rgpn8D9J+Xpn27bqqZyRe3jAqI1BS+YKFYwNqtj3/2VOupHWpmzjd+wPfo+A6DcvncxyillFIX6IpYZrr11lv5zGc+w1/+5V9y5MiRHY/5q7/6K+6//37+6I/+6Lz3lec5eZ4/G09zixGWlXrC2BSAJfqcUI1oQsXq8DjOFWRZBxMj+8MqAJXJMPlBquwUNtb4Yn8q2DUWC1ShIYsBExuk7fS7QVsk206WjhGsy6FJy0reFtumS5vZ1xCfMjXFMmSDlLERB5OTsx1VYZrBaQXJgfV03LbsyvYloVnti+uCLcFP62882POMIGgDKXYI1pRSSqln6rIGMzFGbr31Vj71qU9x5513csMNN5zz2I9//OO86lWv4mUve9klfIbnVseAhBGNgBWHuIy5YpGKGounyJdw1EgcY+p1Yl2zERrGcULZPwII3XJ/yqTEiDEWxBGrVUzWI81SckRxCEJwc0jYIGRLWFtiZQNByFw7DmFK7JnaGONh89KQ66YxAMUSYudgfPpMzUwr2JLo5jDF2aMBtgczs89FoNgPo2Pt4/TOv8wEOjhSKaXURXNZg5n3ve99/MEf/AGf/vSn6ff7PP744wAMBgPK8kwtxcrKCn/8x3/Mf/yP//FyPdWzTJdc6hAwNmfO97D1CmM83vUYNWPqpoerKgqbs1EPsS5NtHZ+Hi/T+UyGGBusGKIYYttpFxEK12elOETmc3q9aziNY7FzEAkbLLdLNGLsDvUq7XJQNkgBzHTUgOtDrNKYhDZ7c1ZmBoiuk+53m+3BzHwxf/ZjwtMHMkoppdRFdFmDmd/6rd8C4I1vfOOW22+//XZ+4Rd+Yfb5HXfcQYyR97znPZfw2Z2fhAkn1h9HEBo/wJiICYHcW4J1DENFFMswREqTEYwjywZYm9OUB8njRlv3ImkGJJHG9QlhLdWzmAzxJQtzR+jnA0rfpSwOpKOHG5u2N2/Kjsy2WdtU6GtKKA6mpSxob2uLikPa1h3ZmpmZfr7TLqPNtx3qHdraI2a6FBbrNAhSKaWUukQu+zLThfilX/olfumXfulZfjbPzMboJMSGIBbrOlhTMR2yaIwjiqe2XUbhKUqJOOPIYkMUg7E5eWxIXXozEIMRQYxh4pcw2QJkA8K2oloRge0/MjOtOzHp/iAt4XSuTcMr831QnZzew5lvawOTJjRb7m76O9mp/4uIsNxZPvNctsuXSRMrr5i6cqWUUj8G9KqzS73eYbBdghuQ+y5G7JnVFVPQ+DkiQuP74OepbRdjPYNigX3dQ2mZKqbBj/1iMQ2TBGJocNaRlp/awGJ7BmQzW559e/+FqYalc+3WmplNQcZ0mayJZ4KZGOMsM3OuzryZzc7aor3luWkgo5RS6hK7InYz7UWZ8Qz6h6EepUBmOmoAwJV0jKXsDPFEzHhMx3dSt1/jkdmW5wgEvCvZ3zvIZLiCWE8dItZ6YhOJJktZEt8/8+CuA6FO/WE2DW088/Uceten27YEF2eOsSaNFYhEmtBgjd2y5KTN7JRSSu0VGszsWmSpXOLk8KnUhC6kfjGCYGyBEXAho3EdYtNjznfJy/mUEbEl+C5MTqVlpjiBpqaX9Zk0OXU2IM+XietPEv08Uiy0wxxb2fwOz2fb9uzNwUhxoL19a7bFGksdaupQY42dFQPriAGllFJ7iQYzuxUjuc0pfR/buQZO35duBsR4DAGxBZmvCRyAzJNZD9liKsj1CxAawEATgArTxhDBlmmqdlt/Yuwz7ZuzLRjZYWcSgDeeOtSsTdbIXT5b1tKsjFJKqb1Er1q7li78g2KeXt6HfPHMLqRqBW/SjCRrPBhLNAVSLINr+6sY2wYZoW0el4qAg58jpH7B5y3GPdfzSd9wYZkV3y53jZsxIYanrZdRSimlrkQazOzatunQ+RLiOu3yTiAzaXr1LBARgxN3ZvlHTKp7iSHtSDJprhNiCO0xzyi42EUTuo4/06W3Cc1smUkzM0oppfYSvWrt1mwS9TSYWcDN30yTLxNtgQMihtwVYEucyXA2Zxb8iG0nb7d9WcQiYgBDiFu3rV9QZsb10mDKTUMjn44Rg2+3docYnmEmSCmllLoyaM3Mrm3LzIihnL+JxmbYGBjXYxCDtZ7F/lEW8l7bE6b9vigpMwPt7Q4jKTMS2l1GUxeUmREBP/eMX8Ws30xstGZGKaXUnqRXrV3bFsy0evk8pStnS0YgeJthXL/Nxky/rx0jIKZdZrJtEGHSSIFLlCWZBi4hBqpQAeCMxrhKKaX2Dg1mdmv7MtNUOwl6Gpggpp21NP1Rt9/XBg6zoZDlQUy+H0QIcMnqV2y706kJTcomcaYwWCmllNoL9E/wXds5MzMdL5AyMwJR2uxK3Pp99Xp7fPsrsB1MjCAZkUjdLkHZc2yrvlimWZj1Kj0fQc7d4VcppZS6Amkws2vnysy49uYztTTTKdjp29pp2dMp067dUWQsUh4gNmnEwXTJx8qzG8xsD1xyl2vNjFJKqT1Fr1q7Fc+VmUnBhxFDdD0QScGB2dT4LlRp2ckWZ5aZ2kzONJComjaYuQSZmc11ORrIKKWU2mv0yrVbIim7stPF388htiDaLiHfh82X0rbpaXam2Uj/3TyiYEutDbPMzKUILkpfnnkaui1bKaXUHqPLTLvluluDkc18D2MLWD8GWOxsSKQBGqiH7ad56ghssi0ZHeCSzkmaL+bZqFKAtXlLuFJKKbUXaDDzLNlc6zJbKhLZMnUAV0I22PJ92zMxuuyjlFJKnZ8GM88SEeFA98C2W7cFJq531vdtD14u1ZykuXyO9ck6/az/9AcrpZRSVxANZp5FZxXvbs+y7BCoXK7MTC/r0cvODq6UUkqpK52uYVxKZwUmZwcz2zMxWpCrlFJKnZ8GM5fSBWRmCldsO0SDGaWUUup8NJi5pDYFJucIUpxxLHeWZ59rAbBSSil1fnqlvJS2BCbnzrh44zcdpZkZpZRS6ny0APiSurBgRkTY19lHJOoyk1JKKfU0NJi5lDZnZp4mSNHJ1UoppdSF0WWmS0rO8W+llFJK7ZYGM5fSlsyM/uiVUkqpi0GvqJfSBRYAK6WUUurCaTBzKT2DmhmllFJKXRgNZpRSSim1p2kwo5RSSqk9TYOZy0Z/9EoppdTFoFfUS83PgXHgdEK1UkopdTFo07xLzffSh1JKKaUuCs3MKKWUUmpP02BGKaWUUnuaBjNKKaWU2tM0mFFKKaXUnqbBjFJKKaX2NA1mlFJKKbWnaTCjlFJKqT1NgxmllFJK7WkazCillFJqT9NgRimllFJ7mgYzSimllNrTNJhRSiml1J6mwYxSSiml9jQNZpRSSim1p7nL/QSebTFGAFZWVi7zM1FKKaXUhZpet6fX8fO56oOZ1dVVAI4ePXqZn4lSSimlnqnV1VUGg8F5j5F4ISHPHhZC4NFHH6Xf7yMil/vpXFFWVlY4evQoP/jBD5ibm7vcT0ddZno+qO30nFCbXerzIcbI6uoqhw8fxpjzV8Vc9ZkZYwxHjhy53E/jijY3N6dvVGpGzwe1nZ4TarNLeT48XUZmSguAlVJKKbWnaTCjlFJKqT1Ng5kfY3mec9ttt5Hn+eV+KuoKoOeD2k7PCbXZlXw+XPUFwEoppZS6umlmRimllFJ7mgYzSimllNrTNJhRSiml1J6mwYxSSiml9jQNZvawj3zkI7z61a+m3++zf/9+3v72t3P//fdvOSbGyL/9t/+Ww4cPU5Ylb3zjG7nvvvtmXz9x4gS33norN910E51Oh2uvvZYPfOADnD59esv9XH/99YjIlo9//a//9SV5nerCXIzzAeCNb3zjWb/rf/yP//GWY06ePMnP//zPMxgMGAwG/PzP/zynTp16tl+ieoYuxjnx0EMPnXU+TD/++I//eHacvkfsDRdyTnzyk5/kZ3/2Z1leXkZE+PrXv37W/YzHY2699VaWl5fpdru87W1v45FHHtlyzCV9n4hqz/rZn/3ZePvtt8dvfvOb8etf/3p861vfGq+99tq4trY2O+ajH/1o7Pf78U/+5E/ivffeG9/97nfHQ4cOxZWVlRhjjPfee298xzveET/zmc/EBx54IP6f//N/4vOe97z4zne+c8tjXXfddfHXf/3X42OPPTb7WF1dvaSvV53fxTgfYozxDW94Q/zFX/zFLb/rU6dObXmst7zlLfHmm2+Od911V7zrrrvizTffHH/u537ukr1WdWEuxjlR1/WWc+Gxxx6LH/7wh2O3293yHqDvEXvDhZwT//2///f44Q9/OP72b/92BOI999xz1v388i//crzmmmvi5z//+fi1r30tvulNb4ove9nLYl3Xs2Mu5fuEBjNXkWPHjkUgfvGLX4wxxhhCiAcPHowf/ehHZ8eMRqM4GAzif/tv/+2c9/M//+f/jFmWxaqqZrddd9118T//5//8rD13dfHt9nx4wxveEH/lV37lnPf7d3/3dxGIX/7yl2e3felLX4pA/Na3vnXxX4i6aC7We8TLX/7y+E//6T/dcpu+R+xN28+JzR588MEdg5lTp05F73284447Zrf98Ic/jMaY+LnPfS7GeOnfJ3SZ6SoyXRpaXFwE4MEHH+Txxx/nzW9+8+yYPM95wxvewF133XXe+5mbm8O5raO7fuM3foOlpSVe/vKX8+///b9nMpk8C69CXSw/yvnw+7//+ywvL/PiF7+YD37wg7Pp8wBf+tKXGAwGvOY1r5nd9trXvpbBYHDe80pdfhfjPeLuu+/m61//Ov/sn/2zs76m7xF7z/Zz4kLcfffdVFW15bw5fPgwN9988+y8udTvE1f9oMkfFzFGfu3Xfo3Xve513HzzzQA8/vjjABw4cGDLsQcOHOD73//+jvdz/Phx/t2/+3f883/+z7fc/iu/8iu88pWvZGFhgb/5m7/hQx/6EA8++CC/8zu/8yy8GvWj+lHOh1tuuYUbbriBgwcP8s1vfpMPfehD/O3f/i2f//znZ/ezf//+sx5z//79s8dQV56L9R7x8Y9/nBe+8IX81E/91Jbb9T1i79npnLgQjz/+OFmWsbCwsOX2AwcOzM6pS/0+ocHMVeL9738/3/jGN/jrv/7rs74mIls+jzGedRuk8e5vfetbedGLXsRtt9225Wu/+qu/Ovv3S1/6UhYWFnjXu941+0tMXVl+lPPhF3/xF2f/vvnmm3ne857HT/zET/C1r32NV77ylTvex073o64sF+M9Yjgc8gd/8Af8m3/zb876mr5H7D3nOyd2Y/t5cynfJ3SZ6Spw66238pnPfIYvfOELHDlyZHb7wYMHAc6Kgo8dO3bWX2Krq6u85S1vodfr8alPfQrv/Xkf87WvfS0ADzzwwMV4Ceoiuhjnw2avfOUr8d7zne98Z3Y/TzzxxFnHPfnkk+e9H3X5XKxz4n/9r//FxsYG733ve5/2MfU94sp2rnPiQhw8eJDJZMLJkye33L75vLnU7xMazOxhMUbe//7388lPfpK/+Iu/4IYbbtjy9elSwXR5AGAymfDFL35xS4p4ZWWFN7/5zWRZxmc+8xmKonjax77nnnsAOHTo0EV6NepHdbHOh+3uu+8+qqqa/a5/8id/ktOnT/M3f/M3s2O+8pWvcPr06fPej7r0LvY58fGPf5y3ve1t7Nu372kfW98jrkxPd05ciFe96lV477ecN4899hjf/OY3Z+fNJX+fuOglxeqS+Rf/4l/EwWAQ77zzzi3bITc2NmbHfPSjH42DwSB+8pOfjPfee298z3ves2Xb5crKSnzNa14TX/KSl8QHHnhgy/1Mt9jddddd8T/9p/8U77nnnvi9730v/tEf/VE8fPhwfNvb3nZZXrfa2cU4Hx544IH44Q9/OH71q1+NDz74YPzsZz8bX/CCF8RXvOIVZ225fOlLXxq/9KUvxS996UvxJS95iW7NvgJdjHNi6jvf+U4Ukfjnf/7nZz2OvkfsHRdyThw/fjzec8898bOf/WwE4h133BHvueee+Nhjj82O+eVf/uV45MiR+L//9/+OX/va1+LP/MzP7Lg1+1K9T2gws4cBO37cfvvts2NCCPG2226LBw8ejHmex9e//vXx3nvvnX39C1/4wjnv58EHH4wxxnj33XfH17zmNXEwGMSiKOJNN90Ub7vttri+vn6JX7E6n4txPjz88MPx9a9/fVxcXIxZlsUbb7wxfuADH4jHjx/f8ljHjx+Pt9xyS+z3+7Hf78dbbrklnjx58hK9UnWhLsY5MfWhD30oHjlyJDZNc9bX9D1i77iQc+L222/f8ZjbbrttdsxwOIzvf//74+LiYizLMv7cz/1cfPjhh7c81qV8n5D2xSmllFJK7UlaM6OUUkqpPU2DGaWUUkrtaRrMKKWUUmpP02BGKaWUUnuaBjNKKaWU2tM0mFFKKaXUnqbBjFJKKaX2NA1mlFJXpDvvvBMR4dSpU5f7qSilrnDaNE8pdUV44xvfyMtf/nL+y3/5L0CaEXTixAkOHDig07iVUuflLvcTUEqpnWRZNpvqrJRS56PLTEqpy+4XfuEX+OIXv8jHPvYxRAQR4fd+7/e2LDP93u/9HvPz8/zpn/4pN910E51Oh3e9612sr6/ziU98guuvv56FhQVuvfVWmqaZ3fdkMuFf/at/xTXXXEO32+U1r3kNd9555+V5oUqpZ4VmZpRSl93HPvYxvv3tb3PzzTfz67/+6wDcd999Zx23sbHBf/2v/5U77riD1dVV3vGOd/COd7yD+fl5/uzP/ozvfe97vPOd7+R1r3sd7373uwH4J//kn/DQQw9xxx13cPjwYT71qU/xlre8hXvvvZfnPe95l/R1KqWeHRrMKKUuu8FgQJZldDqd2dLSt771rbOOq6qK3/qt3+LGG28E4F3vehf/43/8D5544gl6vR4vetGLeNOb3sQXvvAF3v3ud/Pd736XP/zDP+SRRx7h8OHDAHzwgx/kc5/7HLfffjv/4T/8h0v3IpVSzxoNZpRSe0an05kFMgAHDhzg+uuvp9frbbnt2LFjAHzta18jxsjzn//8LfczHo9ZWlq6NE9aKfWs02BGKbVneO+3fC4iO94WQgAghIC1lrvvvhtr7ZbjNgdASqm9TYMZpdQVIcuyLYW7F8MrXvEKmqbh2LFj/PRP//RFvW+l1JVDdzMppa4I119/PV/5yld46KGHeOqpp2bZlR/F85//fG655Rbe+9738slPfpIHH3yQr371q/zGb/wGf/Znf3YRnrVS6kqgwYxS6orwwQ9+EGstL3rRi9i3bx8PP/zwRbnf22+/nfe+9738y3/5L7npppt429vexle+8hWOHj16Ue5fKXX5aQdgpZRSSu1pmplRSiml1J6mwYxSSiml9jQNZpRSSim1p2kwo5RSSqk9TYMZpZRSSu1pGswopZRSak/TYEYppZRSe5oGM0oppZTa0zSYUUoppdSepsGMUkoppfY0DWaUUkoptadpMKOUUkqpPe3/B4A6Yu4IgJZNAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "color_dict = {'ssp245':'green', 'ssp585':'orange'}\n",
    "\n",
    "for country in ['Fiji', 'Solomon Islands']:\n",
    "    plt.figure()\n",
    "    for k,ds in timeseries.items():\n",
    "        ds_country = ds.sel(country=country).rolling(time=12).mean() # take a rolling average to remove the seasonal cycle\n",
    "        temp = ds_country.tas -273.15 # convert to celcius\n",
    "        temp.plot(hue='member_id', color=color_dict[ds.attrs['experiment_id']], add_legend=False, alpha=0.1)\n",
    "        temp.mean('member_id').plot(lw=2, color=color_dict[ds.attrs['experiment_id']], add_legend=False)\n",
    "    plt.title(country)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2042c3f-ace5-4034-b84d-4e3c2ec5d3b4",
   "metadata": {},
   "source": [
    "**NOTE**: This is only a single model showing the range of predicted values due to internal variability (chaotic behavior of the climate system). For a thorough assesment you want to look at multiple models!"
   ]
  }
 ],
 "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}