Presentation_Notebook.ipynb

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   "source": [
    "# Forecasting the Neighborhood Change and Detecting Gentrification with Yelp Data"
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    "**Data Source**\n",
    "<br>\n",
    "Rent data - median studio price by zipcode *downloaded from zillow \n",
    "<br>\n",
    "Yelp data - Yelp API"
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   "source": [
    "## Visualising the changes in NYC neighborhoods \n",
    "#### - from 2011/11 to 2018/08 - "
   ]
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    "# importing all the necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "import geopandas as gpd\n",
    "from pyproj import Proj, transform\n",
    "from sklearn.preprocessing import normalize\n",
    "from sklearn.model_selection import train_test_split\n",
    "import sklearn.linear_model as linreg\n",
    "from sklearn.metrics import accuracy_score\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "import ast\n",
    "import statsmodels.formula.api as smf\n",
    "from sklearn.linear_model import Lasso, Ridge\n",
    "from scipy import stats\n",
    "from bokeh.layouts import column, row, widgetbox\n",
    "from bokeh.models import CustomJS, Slider, Toggle\n",
    "from bokeh.models import ColumnDataSource, HoverTool, LogColorMapper, LogTicker, ColorBar\n",
    "from bokeh.plotting import figure, show, output_file, ColumnDataSource\n",
    "from bokeh.io import push_notebook, output_notebook\n",
    "from ipywidgets import *\n",
    "import ipywidgets as widgets\n",
    "from shapely.geometry import Point, Polygon,MultiPoint, MultiPolygon\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "# %matplotlib inline"
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    "# calculate statistics\n",
    "ny_rent_studio = pd.read_csv('csv/EDA/ny_rent_studio.csv', index_col = 0)  # import csv\n",
    "mean_rent = ny_rent_studio['%_increase'].mean() # find the mean % increase of rent in NYC area\n",
    "# print('''Average rent increase in Manhattan, Queens, Brooklyn, and Bronx from Nov. 2011 to Aug. 2018 is {:.2f}%'''.format(mean_rent))\n",
    "\n",
    "## find out how many % of NYC neighborhoods have experienced above mean rent increase\n",
    "# print(len(ny_rent_studio[ny_rent_studio['%_increase']>mean_rent])/len(ny_rent_studio[~ny_rent_studio['%_increase'].isnull()]))\n",
    "# len(ny_rent_studio[ny_rent_studio['%_increase']<mean_rent])/len(ny_rent_studio[~ny_rent_studio['%_increase'].isnull()])"
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   "source": [
    "- Median studio rent in Manhattan, Queens, Brooklyn, and Bronx has increased by **21.04%** in average since Nov. 2011 to Aug. 2018 \n",
    "<br>\n",
    "- Roughly **38.71%** of NYC neighborhood (zipcode level) have experienced above mean ( > 21.04%) rent increase"
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    "# import csv files for mapping\n",
    "ny_qn_bk_studio_df = pd.read_csv('csv/EDA/ny_qn_bk_studio_df_bokeh.csv', index_col = 0)\n",
    "shape_fiona = gpd.read_file('new.shp') # shape file\n",
    "# clean up the files\n",
    "shape_fiona_for_plot = shape_fiona[['ZIPCODE', 'geometry']]\n",
    "shape_fiona_for_plot.columns =  ['RegionName', 'geometry']\n",
    "shape_fiona_for_plot.RegionName = shape_fiona_for_plot.RegionName.astype('int')"
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    "# create list of lists for mapping (x = latitude, y = longitude)\n",
    "district_zipcode = shape_fiona_for_plot.RegionName\n",
    "district_x = [ [list(shape_fiona_for_plot.geometry[i].exterior.coords)[j][0]\n",
    "              for j in range(0,len(list(shape_fiona_for_plot.geometry[i].exterior.coords)))]\n",
    "              for i in range(0,len(shape_fiona_for_plot))]\n",
    "district_y = [ [list(shape_fiona_for_plot.geometry[i].exterior.coords)[j][1]\n",
    "                for j in range(0,len(list(shape_fiona_for_plot.geometry[i].exterior.coords)))]\n",
    "              for i in range(0,len(shape_fiona_for_plot))]\n",
    "\n",
    "# create rent dictionary for mapping (will be used to update the color of polygons)\n",
    "year = ny_qn_bk_studio_df.columns[7:89]\n",
    "rent_list = [ny_qn_bk_studio_df[year_] for year_ in year]\n",
    "rent_dict = dict(zip(year,rent_list))\n",
    "data = dict(x=district_x, y=district_y, name=district_zipcode,\n",
    "            rate=rent_list[0], **rent_dict)\n",
    "source = ColumnDataSource(data)"
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Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"3ea47b19-b8a2-41c4-8687-88f03487b09f\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"3ea47b19-b8a2-41c4-8687-88f03487b09f\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3ea47b19-b8a2-41c4-8687-88f03487b09f' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.16.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"3ea47b19-b8a2-41c4-8687-88f03487b09f\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d65e2ddf805446599f7e9f2531b429f7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='year_month', options=('2011-11', '2014-11', '2016-11', '2018-08'),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.update(year_month)>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_notebook()\n",
    "\n",
    "custom_colors = ['#f2f2f2', '#fee5d9', '#fcbba1', '#fc9272', '#fb6a4a', '#de2d26']\n",
    "color_mapper = LogColorMapper(palette=custom_colors)  \n",
    "\n",
    "TOOLS = \"pan,wheel_zoom,reset,hover,save\"\n",
    "p = figure(\n",
    "    title=\"Median Rental Prices - Studio Apartments\", tools=TOOLS,\n",
    "    x_axis_location=None, y_axis_location=None\n",
    ")\n",
    "p.grid.grid_line_color = None\n",
    "p.patches('x', 'y', source=source,\n",
    "          fill_color={'field': 'rate', 'transform': color_mapper},\n",
    "          fill_alpha=0.8, line_color=\"black\", line_width=0.3)\n",
    "\n",
    "color_bar = ColorBar(color_mapper=color_mapper, ticker=LogTicker(),\n",
    "                     label_standoff=12, border_line_color=None, location=(0,0))\n",
    "\n",
    "p.add_layout(color_bar, 'right')\n",
    "\n",
    "hover = p.select_one(HoverTool)\n",
    "hover.point_policy = \"follow_mouse\"\n",
    "hover.tooltips = [(\"zipcode\", \"@name\"),(\"rent ($)\", \"@rate\"),(\"(Long, Lat)\", \"($x, $y)\")]\n",
    "# show(p, notebook_handle = True)\n",
    "\n",
    "# w = widgets.SelectionSlider(options=year,value=year[0],disabled=False,continuous_update=False,\n",
    "#                                                orientation='horizontal',readout=True)\n",
    "def update(year_month):\n",
    "    source.data['rate'] = source.data[year_month]\n",
    "    show(p, notebook_handle=True)\n",
    "    push_notebook()\n",
    "    \n",
    "interact(update, year_month = ['2011-11','2014-11','2016-11', '2018-08'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 13,
        "hidden": true,
        "row": 131,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# list top 11 neighborhoods with the fastest rent increase\n",
    "sorted_rent_increase = ny_rent_studio.sort_values(['%_increase'], ascending = False)\n",
    "sorted_rent_increase_top_10 = sorted_rent_increase.loc[:10]\n",
    "region_name_top_10 = sorted_rent_increase_top_10.loc[:,'RegionName':'CountyName']\n",
    "increase_top_10 = sorted_rent_increase_top_10.loc[:,'2018-08':'%_increase']\n",
    "sorted_rent_top_10 = pd.concat([region_name_top_10, increase_top_10], axis = 1)\n",
    "sorted_rent_top_10 = sorted_rent_top_10.reset_index(drop = True)\n",
    "sorted_rent_top_10 = sorted_rent_top_10.loc[:10]\n",
    "sorted_rent_top_10['neighborhood'] = ['Flushing', 'Forest Hills', 'Bushwick', 'Rego Park', 'Elmhurst','Midtown East', 'Upper West Side', 'Meatpacking', 'Battery Park', 'City Hall', 'Williamsburg']\n",
    "sorted_rent_top_10 = sorted_rent_top_10.drop(['City', 'Metro', 'State'], axis = 1)\n",
    "sorted_rent_top_10.columns = ['zipcode', 'Borough','Rent 2018/08', '%_increase since 2011/11', 'neighborhood']\n",
    "sorted_rent_top_10[\"%_increase since 2011/11\"] = sorted_rent_top_10[\"%_increase since 2011/11\"].round(2)\n",
    "sorted_rent_top_10 = sorted_rent_top_10.replace('New York', \"Manhattan\")\n",
    "sorted_rent_top_10 = sorted_rent_top_10.replace('Kings', \"Brooklyn\")\n",
    "sorted_rent_top_10 = sorted_rent_top_10.drop(['zipcode'], axis = 1)\n",
    "\n",
    "# list bottom 11 neighborhoods with the fastest rent increase\n",
    "sorted_rent_increase_asc = ny_rent_studio.sort_values(['%_increase'], ascending = True)\n",
    "sorted_rent_increase_asc = sorted_rent_increase_asc.reset_index(drop = True)\n",
    "sorted_rent_increase_asc_top_10 = sorted_rent_increase_asc.loc[:10]\n",
    "region_name_bottom_10 = sorted_rent_increase_asc_top_10.loc[:,'RegionName':'CountyName']\n",
    "increase_bottom_10 = sorted_rent_increase_asc_top_10.loc[:,'2018-08':'%_increase']\n",
    "sorted_rent_bottom_10 = pd.concat([region_name_bottom_10, increase_bottom_10], axis = 1)\n",
    "sorted_rent_bottom_10['neighborhood'] = ['Midtown West', 'Upper East Side', 'East Harlem', 'East Village', 'Yorkville','Lenox Hill', 'Yorkville', 'Upper West Side', 'Murray Hill','Upper West Side','Yorkville'  ]\n",
    "sorted_rent_bottom_10 = sorted_rent_bottom_10.drop(['City', 'Metro', 'State'], axis = 1)\n",
    "sorted_rent_bottom_10.columns = ['zipcode', 'Borough','Rent 2018/08', '%_increase since 2011/11', 'neighborhood']\n",
    "sorted_rent_bottom_10[\"%_increase since 2011/11\"] = sorted_rent_bottom_10[\"%_increase since 2011/11\"].round(2)\n",
    "sorted_rent_bottom_10 = sorted_rent_bottom_10.replace('New York', \"Manhattan\")\n",
    "sorted_rent_bottom_10 = sorted_rent_bottom_10.drop(['zipcode'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 15,
        "hidden": false,
        "row": 10,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "526ec45789cf4b6db48fcd8310cfc9df",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='select', layout=Layout(width='450px'), options=('Neighborhoods wit…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def update_df(select = 'Neighborhoods with the Fastest Rent Increase'):\n",
    "    if select == 'Neighborhoods with the Fastest Rent Increase':\n",
    "        display(sorted_rent_top_10)\n",
    "    if select == 'Neighborhoods with the Slowest Rent Increase':\n",
    "        display(sorted_rent_bottom_10)\n",
    "        \n",
    "int_widget = interactive(update_df, select= ['Neighborhoods with the Fastest Rent Increase','Neighborhoods with the Slowest Rent Increase'])\n",
    "int_widget.children[0].layout = Layout(width='450px')\n",
    "display(int_widget)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_williamsburg_one_hot_cumsum = pd.read_csv('csv/EDA/yelp_williamsburg_one_hot_cumsum.csv', index_col = 0)\n",
    "yelp_bushwick_one_hot_cumsum = pd.read_csv('csv/EDA/yelp_bushwick_one_hot_cumsum.csv', index_col = 0)\n",
    "yelp_east_harlem_one_hot_cumsum = pd.read_csv('csv/EDA/yelp_east_harlem_one_hot_cumsum.csv', index_col = 0)\n",
    "yelp_chelsea_clinton_one_hot_cumsum = pd.read_csv('csv/EDA/yelp_chelsea_clinton_one_hot_cumsum.csv', index_col = 0)\n",
    "\n",
    "yelp_cumsum_rent_williamsburg_df = pd.read_csv('csv/yelp_cumsum_rent_williamsburg.csv', index_col = ['Unnamed: 0'])\n",
    "yelp_cumsum_rent_williamsburg_df.index = pd.to_datetime(yelp_cumsum_rent_williamsburg_df.index)\n",
    "yelp_cumsum_rent_east_harlem_df = pd.read_csv('csv/yelp_cumsum_rent_east_harlem.csv', index_col = ['Unnamed: 0'])\n",
    "yelp_cumsum_rent_east_harlem_df.index = pd.to_datetime(yelp_cumsum_rent_east_harlem_df.index)\n",
    "yelp_cumsum_rent_bushwick_df = pd.read_csv('csv/yelp_cumsum_rent_bushwick.csv', index_col = ['Unnamed: 0'])\n",
    "yelp_cumsum_rent_bushwick_df.index = pd.to_datetime(yelp_cumsum_rent_bushwick_df.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 31,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "## Business Changes in the Areas with Fastest and Slowest Rent Increase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_williamsburg_one_hot_cumsum_all_buss = yelp_williamsburg_one_hot_cumsum.sum(axis = 1)\n",
    "yelp_bushwick_one_hot_cumsum_all_buss = yelp_bushwick_one_hot_cumsum.sum(axis = 1)\n",
    "yelp_east_harlem_one_hot_cumsum_all_buss = yelp_east_harlem_one_hot_cumsum.sum(axis = 1)\n",
    "yelp_chelsea_clinton_one_hot_cumsum_all_buss = yelp_chelsea_clinton_one_hot_cumsum.sum(axis = 1)\n",
    "yelp_williamsburg_all_buss_perc_change = yelp_williamsburg_one_hot_cumsum_all_buss.apply(lambda x: 100*(x - yelp_williamsburg_one_hot_cumsum_all_buss.iloc[0])/yelp_williamsburg_one_hot_cumsum_all_buss.iloc[0])\n",
    "yelp_bushwick_all_buss_perc_change = yelp_bushwick_one_hot_cumsum_all_buss.apply(lambda x: 100*(x - yelp_bushwick_one_hot_cumsum_all_buss.iloc[0])/yelp_bushwick_one_hot_cumsum_all_buss.iloc[0])\n",
    "yelp_east_harlem_all_buss_perc_change = yelp_east_harlem_one_hot_cumsum_all_buss.apply(lambda x: 100*(x - yelp_east_harlem_one_hot_cumsum_all_buss.iloc[0])/yelp_east_harlem_one_hot_cumsum_all_buss.iloc[0])\n",
    "yelp_chelsea_clinton_all_buss_perc_change = yelp_chelsea_clinton_one_hot_cumsum_all_buss.apply(lambda x: 100*(x - yelp_chelsea_clinton_one_hot_cumsum_all_buss.iloc[0])/yelp_chelsea_clinton_one_hot_cumsum_all_buss.iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# cafe\n",
    "# williamsburg\n",
    "cafe_williamsburg = yelp_williamsburg_one_hot_cumsum['category_coffee']\n",
    "# bushwick\n",
    "cafe_bushwick = yelp_bushwick_one_hot_cumsum['category_coffee']\n",
    "#east harlem \n",
    "cafe_east_harlem = yelp_east_harlem_one_hot_cumsum['category_coffee']\n",
    "#chelsea clinton \n",
    "cafe_chelsea_clinton = yelp_chelsea_clinton_one_hot_cumsum['category_coffee']\n",
    "\n",
    "# bars\n",
    "# williamsburg\n",
    "bars_williamsburg = yelp_williamsburg_one_hot_cumsum['category_bars']\n",
    "# bushwick\n",
    "bars_bushwick = yelp_bushwick_one_hot_cumsum['category_bars']\n",
    "bars_bushwick = bars_bushwick[bars_bushwick.index >= '2012-05-01']\n",
    "#east harlem \n",
    "bars_east_harlem = yelp_east_harlem_one_hot_cumsum['category_bars']\n",
    "#chelsea clinton\n",
    "bars_chelsea_clinton = yelp_chelsea_clinton_one_hot_cumsum['category_bars']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "#cafes\n",
    "yelp_williamsburg_cafe_perc_change = cafe_williamsburg.apply(lambda x: 100*(x - cafe_williamsburg.iloc[0])/cafe_williamsburg.iloc[0])\n",
    "yelp_bushwick_cafe_perc_change = cafe_bushwick.apply(lambda x: 100*(x - cafe_bushwick.iloc[0])/cafe_bushwick.iloc[0])\n",
    "yelp_east_harlem_cafe_perc_change = cafe_east_harlem.apply(lambda x: 100*(x - cafe_east_harlem.iloc[0])/cafe_east_harlem.iloc[0])\n",
    "yelp_chelsea_clinton_cafe_perc_change = cafe_chelsea_clinton.apply(lambda x: 100*(x - cafe_chelsea_clinton.iloc[0])/cafe_chelsea_clinton.iloc[0])\n",
    "#bars\n",
    "yelp_williamsburg_bars_perc_change = bars_williamsburg.apply(lambda x: 100*(x - bars_williamsburg.iloc[0])/bars_williamsburg.iloc[0])\n",
    "yelp_bushwick_bars_perc_change = bars_bushwick.apply(lambda x: 100*(x - bars_bushwick.iloc[0])/bars_bushwick.iloc[0])\n",
    "yelp_east_harlem_bars_perc_change = bars_east_harlem.apply(lambda x: 100*(x - bars_east_harlem.iloc[0])/bars_east_harlem.iloc[0])\n",
    "yelp_chelsea_clinton_bars_perc_change = bars_chelsea_clinton.apply(lambda x: 100*(x - bars_chelsea_clinton.iloc[0])/bars_chelsea_clinton.iloc[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 5,
        "height": 2,
        "hidden": false,
        "row": 40,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "*oldest review on Yelp was used to define opening date of business; hence number of new businesses means number of businesses that have received first reviews during the month*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
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        "hidden": false,
        "row": 33,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "Figures on the right show the cumulative growth (= percentage increase) of new businesses by month in the neighborhoods with fast rent increase (Williamsburg and Bushwick) and slow rent increase (East Harlem and Chelsea/Clinton). <br>\n",
    "- businesses seem to grow faster in the areas where the rent has been growing rapidly - the rent has increased by **39.37%** (3rd in the NYC area) in Bushwick and **24.00%** (11th) in Williamsburg, while it was **5.48%** (3rd from the bottom) in East Harlem, and was **13.04%** in Chelsea/Clinton"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {
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        "row": 33,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize = (15,4))\n",
    "plt.subplot(131)\n",
    "yelp_williamsburg_all_buss_perc_change.plot()\n",
    "yelp_bushwick_all_buss_perc_change.plot()\n",
    "yelp_east_harlem_all_buss_perc_change.plot()\n",
    "yelp_chelsea_clinton_all_buss_perc_change.plot()\n",
    "plt.legend(['Williamsburg', 'Bushwick', \"East Harlem\", \"Chelsea & Clinton\"])\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Counts')\n",
    "plt.title('cumulative growth in businesses')\n",
    "\n",
    "plt.subplot(132)\n",
    "yelp_williamsburg_cafe_perc_change.plot()\n",
    "yelp_bushwick_cafe_perc_change.plot()\n",
    "yelp_east_harlem_cafe_perc_change.plot()\n",
    "yelp_chelsea_clinton_cafe_perc_change.plot()\n",
    "plt.legend(['Williamsburg', 'Bushwick', \"East Harlem\", \"Chelsea & Clinton \"])\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Counts')\n",
    "plt.title('cumulative growth in cafes')\n",
    "\n",
    "plt.subplot(133)\n",
    "yelp_williamsburg_bars_perc_change.plot()\n",
    "yelp_bushwick_bars_perc_change.plot()\n",
    "yelp_east_harlem_bars_perc_change.plot()\n",
    "yelp_chelsea_clinton_bars_perc_change.plot()\n",
    "plt.legend(['Williamsburg', 'Bushwick', \"East Harlem\", \"Chelsea % Clinton\"])\n",
    "plt.title('cumulative growth in bars')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Counts')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": true,
        "row": 210,
        "width": 12
       },
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_williamsburg_one_hot_cumsum_top10 = pd.read_csv('csv/linear_regression/yelp_williamsburg_one_hot_cumsum_top10.csv', index_col = 0)\n",
    "yelp_bushwick_one_hot_cumsum_top10 = pd.read_csv('csv/linear_regression/yelp_bushwick_one_hot_cumsum_top10.csv', index_col = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_williamsburg_one_hot_cumsum_top10.index = pd.to_datetime(yelp_williamsburg_one_hot_cumsum_top10.index)\n",
    "yelp_bushwick_one_hot_cumsum_top10.index = pd.to_datetime(yelp_bushwick_one_hot_cumsum_top10.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 45,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "## Cases of the Areas with the Fast Rent Growth - Williamsburg and Bushwick"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 3,
        "hidden": false,
        "row": 42,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "### Is there any correlation between business growth and rent increase??\n",
    "- we just saw that both rent and businesses have been growing in these areas - does increase in rent and business actually correlate to each other?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 8,
        "hidden": false,
        "row": 47,
        "width": 7
       },
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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++kMxVkFPON4+3H9/H3/0jAtl+2gMyCeX1lf5tkX8m1/rLwK8TzMPOk+AKJVQHXVI4ionxZH4Omw7yux9PebTBs6GAm4DVVCtF2hMRD3O43vASGFDUGYxvf1G98XgiG3Px7bcm3FyLCuvHk+YxwqOi4oCv0rsExmVkZ5TIRMxyGp8qpC/qxjIdQL4viL5zqObbi8EVoOSmWNNZYahko8Dk2DeC7m9QDP9Q9DI6BMbAdEtv45Ks2E0fE2r02KoDLoI2gGxPP8FOhOaH0oatYXVnZ0WRFNgHWWczr0OpTJNRCiu/qc5zkOZ/9zXM/xVBU0AToZag/FWTk82Sa2k+Oci6CJ0GyI/mZ+PPOLLveDB89HPGewvzke5HFxEJTMMh2vJcsnV/4VyIjtLk2R4e1hnNdi4qTDycooikmfKY+qsC6FWGZyPOB1Pdt5MBQ1jnkZRu0cDcT6LWFYqRdWEPoxDd1xtiw8R0JvQdwvuI1+AfFaltt9G8isCA7mVWEekSXDue8yzlmRMK2KgAiIgAi0cgIcEPEEQZ1WTxaDw3wqseTgjnnywpgnsgVQMWS2BRy/QFY2b+rwZGfrPKmtAPl2OFYYzpuTUbseHpb2qWgg1u8Lwy8Mw3gziYOvhaE/B7pcN3FQZlYCB/Mug2xgw/b8BlmZzGdfKBvzBxPGi0vL+/JIptdhnfWcFcYhN6s3l+zTbKwSiVhmCVSX8UKAFy1WR9blD299Mtxx9SgN49yA5XOhmwPhqtDN/HihthuUC7N8D6ojs3MRzrKnpojHiyrGIe+2KeJFgwrgYZyKooHhOgd+bDfjHRH6+QtrR6Hv6bn9Muj27SasWPlccru1gSHXP4V8S5VXKSIyDbfB0aF7PpZ2U5ZhXN8JirO+8GR5jEdxP5rprdMdN6DOtA39kc/PXr6sE49DVi6XdW0TiFJj3B4tbVz9aiLW4WB7LR/WyT+G0P9+yL8o74Z17tPGl/3m7+t0rweZ8QJhFGRlcMky/OPJrViPs63g6fcFy2R5zONDyPaRcrijxu2XN9ytXG7LftuY7w5Q1IrgwTQVEC+s6WZdeTzmMXUERPPjVfvU/h2OVR5HrPzZkXWeMwog33h++QqyNCyP5fqszsJ6Yxov9FifuHPYbWEYbyJsFLrHYBm1W+DBPHgRGTVyZhh5+laIFfpX+Z6huzQM4zJqjM90hZGAPqE/wyhuD7YNm9+V8IuzcngyzkjovdDN/rRtkWHjIR6DD4W4H7HPrC4M5362CxS1A+HBfrY68JwVrVevSCLLdzj8ze3vG8zrA6hHJB1XKyCGF3EliVmehZHwUqwz7Y3QC6GbbbXjWF+4za6Gg3EpsmAc244vgLsCYlgRJGs9BFZBU227OK2ezR4c5lWJ5emh27Y17m/FkNkWcGh8X01D4/vFx01uizwXZDO+L0Q6pq+Ccm3cduvK+4QwDuvfIVKBojCsIuLvr1oZ5b4n3NmMQ5LlxayrILZlf8iu0Xh95o+PJmJ9GSjOhsPTj8tzr7+eq7HU/yFf1tPEOrIsW+f5PhMbjchMOxXi2CAb43jCyueSdfLHHXQXQb4dgxWOw3luZhqee/0x+vNY960vVj6FrBweO/1xN93JrjHqc54fjHz9sQ7H59yWrR4T4C6AolYOD8Y5H/o4dDOdje/hDMziFZuHt+wEt4VbeZbe1s/x4pszm/GapW2oZQUyZp1LUxTwRhjnrpg4xqE4Jsy8rIwi8wiX2fCoQlrWd38ok+PBtWG6W7GM2svwsH67NBqI9U/C8L29sILQj+nojtqm8Pgesnx5zLG6m5+friiMW4Fl1A6DB/crjk9OjAZqXQREQAREQAT8Ad/a9cQxGOl5opoD8eRzE7QiROsI9Qlc1f+6txPdh/DbPPTnoHU/iDchmc9zkG99sUJ/DjS7QL59gBWGcYDHgVV0APxdGD4US98qscJ0g6FkVoIAxuHAlm07HrKLh9XhfgliONvUDsrEDkJkpqVugHpCtOWg6yELYz9FrQQeDC+DcmGVyIT5lUCpjP8C+wJi3M+g7SBaG2h3iIN/hnEQGO2H0jCsCksOoo+D7GJyANx2E53hK0H1NebDupBzKrsPgYw3JkWkrcM4jLdWinjRoAIvXVEkkJMdG0DPh3G4nZJv1KwdhdGAcN0vg26zDeFgfTkQ5AVGd4jGcrlv/hW6EfItWV6MUwoxP+4L3NeGQ9y3aetAb0EMnwxFjRdBEyGGj4V4k6w9ROOx4WbI8vb7Pps2PBrmxePClhDbS2MdCqEroR2hdO0qRGTdZkHRbTrdPBiP29fhENtr+XSF+2jIbhgeA3fUiuHB8sujAZH1C8J43I6OgLqF4Txe8aLgJ4j5nAD5xjpMhRhGZrwYobGOe0OsG/s8WR0eCMPIh+VYv64P95thGNOz3b4VYYV5Mh23UfYLj3007ge2HVi8iiCk9s8QrC6E5kElUG+I1g7aHmJ7WMaDkG/XYoX+bDe3BeuPpeHuD50HHQw1pv0NhbFOVRCPp77ZTRPutwxjnN8gqzecgdnFJ2+WRI38mH9RJKAw9GeeUSuFB9NwGTXGZ1hhJKAX1h+D9oHotv2PfXs6NBdiup2gqJXDg2HMewq0A8T03Kb+Cs2BGH4h9Ad0HdQTonF74biB4Tw3+cbt4UeIYdxeV4fMCuAYCpVBtv3BGRjrwTRcfgRtBtGY34EQ+4Dho6GoVcCDYUXRAG/d8i/0/OgshZh2JsT9YwRkx1pu49ynaXtDjEdxzGD155J5cN/gsbqueiCKrIUROBTtsW1j7Xq2bXCYF/e/BZDG94BQhx2EcON/A9x2nOK+yX3VwthPUSuBB8PLoFxYJTJhfiVQKuN59wuIcXkM3Q6iNfX4nsdH1ulP6C1oJsTjP+t6J2THZTgztmKkYN5VMSl5fbI/ZOMfHlOjVgQPpq+IBnjrxWGccs+PzmzGIcnyYn5VEOvC+r4ObQrROK7h+YrnEoafA0VtCDwaYyzF/YD9yHrw/M0xghnD9oTuNY80l3ZuvyXN+HHRWC7Tc9zYPYzAscea0L8h1pfne+6/UauAB8OLogHeeie4s7kGYhb1Oc9zXDQDYv04Ht8QonFMdRhk28TD9IxYOdaZjvvbdIjt49iH1q96EfxavGLPz5x3wsE8PoXYDhu7dIOb8WdDDN8VMst2vGbpG2pZgYxZ19KYAsjZjuu8T7VZTJxy+DE9253MrIwiL0K2PKqQB8vL9HjAspmOfeYbx6BzIRtTvuoHwr0CxHS8nuO+bFYAB/0pun3rjRXbfyfBvQtk2xi3ER6XeDyg28zqV2Ee4fJkLFk2+cedV8NoWoiACIiACLRmApei8Twh8aKWA7362GAkthMcJxSS2XkIYDyekHvFRNo5DGcc3pTy7Wus0H+Y59kDbp7weOPvMYjhNuiHM5isoN88iANQ3yqxwrDBUDIrQQDjUIdAUeOgh3kznAPndI28P4eY7v4kiciR4ZUQL0B9K8EKw8qgXFglMmF+JVAqOwWBjMeLz9VjIm4FP/YH4+wTCS8N/Rl2UiSMq12hqRDD427gwjsjq0Js5nVQHanGhfH+kyLeamEc5rddinjRoAIvHbd5XkSYbLvhBQC3gVWhOLN2FMYFws8vg26zY+FgfV83jzSWyfJi0lKI+VG7Q1HjBdFCiOF2kWVxzgj9X8DSBrcWZkvb3i8xDyyzacP3SMc6DPPyqY/zf2F+vHhsKOPFN+v8fkwBxWFYeUyYedlxiNvSeuYZWe6MdZbBfcw/3p8W+vPivq5jcrQOG4RpmS9vsEStAB7WH7w49K0IK0xHjfIDIm6LVxHx5+pHENMfwZUYY3t+gXhMWtsLnwA30x3n+TW1szCsE+u1sVcZu6j8zPMbE8b1z3W84LRjL7enqJEf8yZP36zcKt8zdJdiyTRcRo3xGVYYDahj/ZQwHc/XUSuHB/NkO+LyvSYMZ5xHoagtBw+7ueYfg9j3TLMA4k3edM3ayH2DF+pRK4IH86XWjwRWhP6Mk8ws/8JIhFKsW74HRML81Q/CeKN9T8/NGweWT6p6eEnkbCEENL6v3vYHp+jPEoTZ/qHxvXN2bM638T2Pj9ZPXHIsPdfz4/niIigbK0Yi5sk8bGzO5c+hH8O+gs6B2kJR43GVcSqiAd66lVHu+dGZzTgkWV7Mrwqy+nahR8QuxjrD34v4c7WxxlI7oyzWYRoLzYFx3MP8qBNykF+yLB4Jyzg1JkJFGFYUE2Ze2V4DMX19zvM2ZiLvAquMt+T4wvht4vnTWR6Gcd/Yih5JzOIVR8I5PrW+5jVKnB0LT8Z51QvMdrzmZdEgzgrkyrryOss/VswK/cmJ17iDoThLxsmPa2UUeZ7Z8qhCHqwvj1+ZHA/svhrT+teEg7FOv/ugKRDvYfj31fbDOsN5LPGtACv0p+j27d9YoT+vSzl+T8fIhmkqvMjnhn48LzBcJgKtjkD0RnGrA6AGi0CaBHiSo1VBPJnE2Uh4+id6c18XFzn0uypFGE+QtNsh5hW1Z+HxeugZvfHzcug/yEvEyQjezB0PxYVb3LcRzom+bO0bJORJP2ocVL4VekZvgEXj+uuFWFkr9PBv+PtxLgxXVsNyCz+gCd3Wf7yxNiWmHm/Ab2zoH+0/i/4LHBz0RG0mPOwmuZUTjdMQ63ZDNNX28YdXcNxA0gtO6ixAyIqelg5jdsRyWSjdwV+YrM7F72EM5tu+ztjpR/gIUZ+Kic4J3U9C/+i+MDz0Z//yJnSc2f61kxeYTRssTbILLi/7tJzWLzPSip1dpGeQbD7Em/bZbF8HIx23Jx4/J0JxxjDue32g/l6EfUL3f7FMdkx+34vvO20/Zd8/6AeEbp5bSkN3suMBg1OdM8LkSyw2hQ+3M7bpriVCqz3YnnEQzxE7VHsFv7neRryss3Z+iJTkRdu+ehH88hxHs/Mb3a/wB2Zh5mY7eRHu30xgWD7Zk2Fltk1RKZ5DKmLCn/f8Lvfc5uS2YOn8Y5D1d1uEr2CRM1iWIe73MfHL4WfHPNsXYqJl7fU1Uj6UJPWa8LdJviuTxEnmnyS6vFsQgR5hW3hMSSRp10j48xgZlcb31cA0vq+94byB1aYY389CuaXQ1hDH690hPknCdd5w5nnvPOhEKFtjHv74nOM++tFsfG5j9mrf+v/aeSlXY1Wr0Y1wkFnUeL6i+edGrjfmWMrazBvn5FpfYz+ZNeQYPZ1xi9UjbpntNVB9z/M2LuE2wXNB1PjnmUmhZ7IxOseb3PcztRFhggew5LE0zu6HJ89PW0F27WPbSLbjtbhycunHY49/rLB7CDxe8Ly7fC4LQ1715ZHp8YD7kV1H+tcig8J2jceS1yM8HvIYbGbhL5lHHct2CP9rGIf3wTh+z8auRqKLodnQHpAd5+CUiUDrIdCm9TRVLRWBBifQFSX4J3pzJxu4zkF8/lspzniytIH3uLgIod+L4XKTSBw7qdpJlsHmZlhd4ZHsMlp9B7ETSVJ8F/rzoixds7b9hAQ20IimnQwPy9viR+M09rrVI5v+s7q+Bgdv9seZ9eFqCOwRF6EB/JYK80zWv7kqcm9kxLJM3Ic2g3iDc1eIA0p/MInVehnz44CwH0TmR0CrQPW1t1NkYNurvy90Q/z1wjQ28R294cb1sjCOX8ds2vB0mM8oLK+FBkIdQr+mXHBscij0FPQtNBfiNkfNg9pDjNMLytS2CRPshGUcW/Oz47bPeOMwbapJE14Ax5kdD8bHBYZ+djznuaN3TLwf4Dclxr8uL2szty9OTlgbo0vuWzS/zbaNnAt/bpPk1hlqSvMnrvyLTnP7fWB9ZWGst7k/gvvXpmwIyua5njcjn4fYH39Ctq1bXy8Pv3ZQnLENcfaj55nsvMntieYfg1iH9wPf6uPsmXBzLGLH/jAo6WJ80pDF4w7bF1JEzTjoDaQgtziz/fYPBFrbovE+hMdvUU+ti0BIQOP7ahAa31dzsGPYuBR7yIthmMWNRn0NHrke33+BPE+DeDzk8Y62COL6ztAzEI03QTsGrsx/eJy0sTmXHIv1gTiBwBuzf4degHI5lmyocUiyMfp3qD+tPeSPdxpzLPUBymY9OBZl/50E9YPywThG5Tb0FsQx1ELIxi13wk2LG8NWhyT/rc810MZhttmc5zk5uGqYvj779OvJm5YyxLarIxFrehJ9HubQFktjy7g2pnkZ7jOhTMZriN6gdh1y948VPOb0hy6BBkCjob9BubL68sj0eMB6vxRWfpDXCHMzrK5wL1lSJ/u0Sxhqx8KkkWMCeIy+DTod4uTuThCvOWQi0CoJcIeQiYAI1E1gRhilAEuezOPsLHgyzHRvXCTPjxcKvDCJsx7wtP2TA+Bk9m0YwBtkvnEgRNscWiZw1Z4Aq4AfL2K2g6wc/4QdJslqMTNFKt7IprWvXqT1a21LxYEZJWORViE5jsQLPxuspKp3XXVOldYPM0Y5bsYS2c0KfWybWiICPPwwix8XLxO/3xH5XeggaAxEttdDuTJOChwJsb7cZ+6AvoGmQrdDW0HZWKb7Qi8UYseXnnDzIjNOvFij+ayzacMFyIM3KjpBp0GvQGTN48epkG3DcKZlPKbRePzK1niBNBa6G9oNWhlKQD9DvGFPcZ3m35io9qn7d6UwCtPGsTW/dmE8Y8x6WXnTwrC4Bfshzmwf9ffbaDw7HtDf4vtxfvJXMnBbm9sjjbUvbmlttSWLuAm6D+JF91HQsxDPHW9D50Jx9YR3UpuMEF6kRnVM0hTxAdxGaTyHmZmb27HZW3D8CTHM9q3tw8CXwmVTLbifsH5kvAPEPuENUfYzt/MfITPb9mzdlsm2xYVhBPYVbwjFmcXhduHbYViZAvGm5pXQRxBvcvHfovtDbaBklmr7trBMt5lkZfn+qfYNHktpZJpszMXwZCwZJmu5BDS+T79vMx3T1JWzHQvs2JAsvp0bLX6yeI3h31zH9zz2nR0C4rln2xzB4niM/fcINAzi+WZr6BgoV3YTMsrlOMTqlWx7nmsRsGzvuRtzLDUH5R4C8dzWH7oR+gziuIAsyDoTs/E509RnjL4Z0k+COP7bHOJ9kVkQ68VzbBVESzZmqQ6N/63PNVB9zvP+cSXVsaiu41CqcUh8i6t9bbviBGDc2Nz8bAy7jJdZfcZrXjaBcxf8Rsfmts661dfmIYPJ0HnQBWFml2O5QujOxaI+PDI9HrC+di0yKKz80lhuBZEb22rXGRbOfW99iGZpq9eS/7L/aTyG2zYYeKT5swHiHR3GPRzL19NMp2gi0CIJpLqIbZENVqNEIEsCHOzROkL9Alf9fxammUWHNOP50ThIngZx4L41tCxUCPFkzJMyT6KvQt0hnhj7QqtCC6AJUD5aNhyaqh02SGX5DVVvv4zGauf3YUG9UxToh3EbzLXdFWbIi7A1cpj5aOTVFzoJehTihRxvAPOm/+vQP6GGNv+cvBoKYx+nEi88fcu0DRzs7whxYH4t9A7UFtoOKoU+hTI53tlxcj2kYz7ZGCfidoJ44/44iNtTJ4gXqLw4pmZDNLLJ1IzxBUiYiq2FlYcFZFNWXN3qczxI95wRLdfaPC7NNhd7GbBM3oTZBLoM4nmD5wnufxdDPNdsA6VrdiEfXWZ6s+SlsEBuFwMgXpxvCPEY9RVkNhcObte8OcJ4XaGNIJrlUb3W+L+Xo0jWhXX+K8Q6kgNvBnA7Xxcyy9X2Z/mlWk5EYH/oAOgO6HOIY4i/QDzGjIey2Y4bsg2p9o2GLBcoZM2cgJ23NL5vuo7M5njSVLX1jycNVW+/jFy2831kNj/MMJfjZ6vjFDheDld4/siV5Xockm29Gnss9RIqyn46AroP+gbimIfjhbHQg1C6xj+R/RRG5rgjG+N2eTfEewcToKEQxywcH3BMx3GL3WjPZhs2vsjGrQYxj1Tyr4GyKY/lRK0++3SqcUi0HH/d2j0cnqnaa2EVXuJcjtd4DoyOzW3d6ugVXS9nWZh6GSz3qFdOtRPnkkftnOPXXgq9OV7nvrkFxGtW8/8S7u+grSBuW9tD7Efej/sBSscYvz7GOvA6iFYKrRy49CMCrZRArg9mrRSjmt0KCNiJjE3dvRHaOwNlLArL4SAwmfEGPc0GtdVr1b8vhyuDsBwIcX8fD5lZmxhO0d6DZgWu/Pmxtq1aR5VSsagjac6D5yJH45ht/7FS/mRStJIreR7GyPNqEOcnYa7rpcjdbtqSwVcp4mUb9I2XcA3PTSdvzNM4iI8zXqSlMv5DchS0L8QLuY2heyHa/0HcjxrSfvQyN46eV1rObNrAY8Xp0OYQ/502ApoOcZBMHunauDBiZyx3SDdRJN7+4fpZWP4bmhYJZ95dIn6ZrNoFR6Z856CQ2WFB/r4XLTtZmO2j6RwPmKfFj+afzbq1eUA2icM0vHE2EtoO4s0P7iOfQ7wBcReUrjE+L+ai4kVZJuafq3hBuS3UFnolJhNO2tFYd4vH9bi49G8ss239KBT4AMR91zfeeGgq+xMFPwSxbmtDq0DnQTzGkuMZUJylc86Kbtt1Hbc5dqnPPm/lkSfzSmY85staHwEbC7PluzdC8zW+XwzZ9k2N7xczocsfRxij2jHqv5aofxaxOXwT+q4RCa3rOM/odY3RczUOiVQt7dWmGEvxWrIMOgTi+JHnYxsvHRD6Y5GWjQ9j8TjXNq0UtSNtgNX+EMfDnLTgmP8PyLf6jFvqcw1k+0k253lLy3akM0b34/ttz9Zt21Wm1yVWXrbjNUtvy3I4omNzW6+ySDlass2sNy3Xx4pc8aiuXepftmMyRE4cGw+CaOOD3+ofjjE4+bUlZOH0S9d4PU7j+JVj8UyNx5CdoQqIrF+ENN4FBFnrJMAdSSYCIlA3gamIMiaMdiqW9bkZU3dp1YOCj8OIQ1IkGBqG8WZg1F4OPXiyjTvh1hXu57coXOEJvrHN2tYZBW+RpHBeEKwchln8JFEbzdvqkW3/saK8WdsuSY2tT79G+IwkcXLtPS7MkAOwdZJkzkEWbTxk2w3Xc2XWz8xvfiRTG6D3ifjbKid4MjEOFg+DJoWJts8kcRZx2Y8cSNP2qV7U+zfTNvyOEu+CisOSB2KZ7ljhWcStDNONxDLd44Ufz/qONzribIc4z9DPtjc/v2j010OPYVjymJKJWZ3IJJnxAijO7HjAtMn2aTue84Lq+7hMsvSzNvOCZ5ss8/CTzcHKoxD3DdpaUO/A1Xg/C1DUhLA47pe2b9p5za/JKzHxPoFfrm9i+GXW5V4GETiRSLPtqnpt8e+Oi51N7voWNbgEuj2siZ1/ohVL5s94Fmb7gqWt67jNpw+zuVln+RtfMuefGuKMN/YK4gLk1+IJaHxf3cWpzpsNtRHYsUDj+9qE7Vj5Nbxn1A6q1xqPf+3DHCrrlVPyxDZGTzY+t/C4HDIZozfFOCQfxlKfA9xp0NgQoG0rcTyjfv8OPfpgOTwamGTdPy4wHY3b5a+Ba8mfVOOWusbo3NazvQaqz3mefz76JmzKkCWbVONjY3Q7btUE1NNh29XeyMfnnW226Y7Xss0/F+l6IpOlw4ySHStse4uWtzw8Vot6plhvaB523cF90fbHl7z61BXuRY118n4gJ7Fou1UvMv7l/roTxLzWhl6AyFEmAq2OQJtW12I1WASyJ3Aukv4J8aR7D9QRakh7OMx8BJb+vwGtzJ3h2DpcGW2e3tJOvlvCjzd7aeZH97sQT6i8cTgYovnh1T7Vv7wpTmuKG0QVKPeLoHTnzgmX0UVJ6FGJ5Vuhu6kX1n/7oyJrxVRmK/hZv8T1H5P0hI6hI2KcgD0l9HsoEtaQq28g8ylhAf8XUxDbWRT63xsTngsv/uORthD6MHAt/vkodP5lsVeNizdQz6hZq+2wQXht3+q1BBZzw4AOcRFy7FcW5jccy83qyNvfH7NpQ6o0vLlAY5x0xwoLENf2UR5XroJSGfM9G9rdi/Rb6OYN6aiRf0nU01tP5zjF7ZIXW2R3sZc2ztk94vlYuM6JnxUjYVzdAeLN+jiz48GqCDw0JgLrUxz6JzsexCRLy+tNxOKED+0aKFW/d0U49xWzVHFtG2Hcxtg3rE62fDl0cFvbLnS/YoHe8jW4uR8zHkVLdq6rDm34Xx5TOJ6gxW3rPeAfd4wNEjTgT6r+ZrHW58n6+wjE6RVTvz3ht17ob/uCRUt13Gacsyxilssvkc7KSHYOODPLvJWsZRDQ+F7j+0y2ZDuG5dv4fqkUjeB469IwvApLnhdzbTz227k4OkkwEWGLIF6/cKwUtY3gsUvUM1xPdV6ycxKjJjsvJck2Y+/GHEulajMrbu3OpM3PI92zYatLsdw2dCdb8N6DjXsZx8bnfeHmWDFqvCexV9TTW09njF4Wxs/0Gqi+53nbp09A+RyPR43XngNCz1yP0e8M810by1NCd7KFf13SENtIsnJz7W/X8sw3eqyw8RqvDf3rEavDP+CIO9Y1FQ+7ntgR9doG+hGaBJlZOO9N8DhHs+uX6rXUv7y2vj+MMhLL5VJHTxr6M0J47P0UWhfi8YDXGjIREAEREAERSErgKIQshHgzjSeQIyEOEM14Ql4T4o2rnyDGK4N8G4wV+ldCqYyDnO8hxv0AspvhHAzsC82AGPYcFGesi9WB8T6LifQM/BhGsV3LQnF2LzwZh4O+ZBN/JWGcMiyTWRkCmE8JlIkdiMhWzxvgtpM/l9d7YYfAHbUSeDBtGZQLq0Qm6bShM+J9EcadjOVAiMaLUA7qpkPMh5NK7FPfeGHCMF6kzoWOgWxg1x9uDpws3N/+4J2WcXDf0xMvapgfy/H9rUx419hf4WJc6nxoGYi2McSb7PT/EIq2CV4pjXWyfItiYq4Mv1IvTllMHKvbfISdDHUK4/TD8knI9hmWw/LM2I4nIN7MWN48seT2dRlk9eLA1syvr58Xw62eXCazcgQw3+JIBPIkP4ZVQcdB/n7ZG+vDodchP202bfgOeZRA7Lt2EI3HDW6rn0Osw7NQpnYdEjAtxYH/bpBtJ3AGN8h57OQNEcYpgsxGwUG/H6FhEPcX2obQeGgmNA9inELIt82xQv/ZUNykgsU9L4zHuHdCa1sAlqznEOh2iDc7fOuGFTJjuvehTSAat3W2gRcXv0IML4eidj88GMY2HAa1h2jrQyyLYUzfB/KNeTOswveMcaeKxzYtgJjPBGg7yNiy/htBF0E8ZxRAZu/BcTW0NdTBPLEshHjsYn6ToaYwbqcsn+L5i/s3t984+wieFo/Lg+IihX7kzDjk6RvbTP8q3zN0l4ZhXEaN8ZmuMBLwdOjPc/OWEOtOsV08BnB7YjqqAPKtHCv0L/Y9PTfLYniV5xd1xuUxGJHY5ydCa0Bm7PtDIe5bzPccyDeWY+V9APemYSC3Ld7osPDRob+/4LbFtNQlkN1Y4zH/P9As6E+I4YWQb6VYoT+XqWxfBFoZ/4K7RxiZy2sgbj+/Q4xTBMlaH4Gj0GRuB9wGNL6v3f8lIZey2t611hhGdiVQJqbxfe7G928D/OkQrxPs/M7lFtAzkB0DT4U7UytGAqaviknIscw2EMu3MjjmiJrVgeNLXtPyfMex557Q9xDP4UxfDvmWzTjE6hvNi/myDSynkCsxVgA/awfdvrFdjTGWGo5yxkMjoD6QWRc42H9Wh4MtIM3l8ohn43teX14LbQixL2jcXnhNcAU0EyIrs45w/AKRzVPQqhBtaYj1YP/ZuKUC7qjdBA+m5diH7YgzjsE5/mE8ln0ctCxk1hsOsnkdKjbPcFmf8/xKyIP1Z7kc224A0bhtc+zDcQjDHoKiVg4PhkXrk0k8jnWYxyLoKmgVyKwbHLtBHD89Yp5YDobeg06E1oDM6hqvWbyGWlYgY7alNKYA9iXra+Mtbot2LWTRuV3Nh5jHndByEI3LyyBu+5a+CG6zwXBkw6MK6VhWIRRnBfBkOEV31Lh/WjiX7KeoTYeHxfkiGhiupypnZcT5KcyDk2vDILtu5/axM/QYRLdZERwss8I8wiW39c8ghr0D+fsXVmUiIAIiIAIiUJsAB+rTIDuRcTkH4omJg0nfn4O8dSDfBmOFcSqhuowXLTMgy5MnfJZl67zRtAKUzB5FgMX9d0ykc7zwd2PCzWuoF28e3FOhSugByKwEDpZVBiWzMgQwTgmUqV2CBNYW3qQgF7tZQf/LoTgrgWdd9YpLl8yvMsyvJFkEz58D6GmQ1ZsXE39465PhtgsIOGusFC6muQF6LnST+6+hm2Fc3w3KxjgYsjqlWnLwFGccnFs6fyBKv2+hNeMS1eFXgHDLk+3kYNFkN10t/BWEdYWixgu35yGLx7pVhevcd8jLwlieWQkc5s8l4/4W8bsS67759fXzYpxSiPlwmczKEcA4xTER+sDvvTCccbid/wLZBRj9qFMhsxI4zJ/LdNrgx+fFBi9c7aKDYezLtaBs7HQk8vuNF3XsV3/7ZxkcfPsXbithneVa3XhMZVu4/ie0L1QVrhdi6Rsv4CsgS8tjcmWodbE0Yzz2p8Xjkmyjx5T34Re1beHh9wPrZsdkxj8XYn4PQlFbFh6vQVYu92FrC/14fNgBiloRPBjOtqWyuuLtj8R+n7D8aJ+zHNbTrBIOq69th/55jvXfyiI38pI3XYw96/hkivJvRpi1g8veKeKSM+OQp2+FWKE/2xy1UngwjMuoMT7DCiMB62Pdtm2Gc9+w/qF/suMVgoIbhExTzJUYY1kMZ9nJrBwB0TwGh370p8iXxx7uv+Y3Hu6OkG8sh+HDIXPzGOr3z4dY7wHF2R3wtPztWMH1uvb50jAdl3XZvxDByoiOIUYijOMphu8KyVongT3RbH/Mxu2B27DG99X7RhlYJLMyBJBXCZSpXYIEyfZN+mt8nx5RO/aSGc/v3G79YzCPrZdC2VgxEjFf5mFjcy5/gDjW9vuP47844znPH1tzLGXjiVfhPgtiPuWQb5VY8fPnOcnS0Z/tjo5DrL7RvBC15hxVyJUYK4CflUd31BpjLDUChVoduOTY4NeI3wNYt4krONO25RDzKcjPn2N/cvX7ku7rId+GY4XbgKVlf/I8zfXJ0NGhuwLLqG0GD7tuZ5pvoUroaci3PljJ9BrI0tfnPD8EmXAc7rfN385eR1jc9lAepinGMpWlitcBCe+GrGwuybYK8nk/hnWzwXD48dMdr1n6hlpWhPXiNusfK6LbL/t/vSSVOD/Mw9rHtNx2yOJUyMoogttsMBwWn8t0eZAx4xdCcVYAT8uX7jj7Cp4W58SYCKO98P/EhNOrrnK2QBweb60cHuOjTP36FYVxK7CMGvcxq/MbcHeNRtC6CIiACIiACPgEOmHlGOhRqBLiSZ4nomnQeIgXGP4NV6zW2GC4ePKqhNKxXoh0LcSBJU/mHJy9DZ0BdYRSGQcJdqI8JCYib+Za+L9iwn0vnkjHQ1UQByBMNx4yK4GDfmVQMitDAOOUQNkYJ+LKIQ4AOHj+EXocirtpDO/ASvBbV72qY6b3WxnmV5Je9OAfS1cg7icQb3Dygo+DEd5w6wzFWSk8WWcu20NnQxMh9j9vWD8CbQhlayyf+delohQF7ImwZyDWh/X6DLoKSnaDE0EprQChyerDCzP2+VhoBNQWSmbcNy+CvoC4T3LwfR+0DuSXQbdZbzhOgB6GJkFVkF2ckfVOUNSS5cV4pZD1XzSdrZeHcYrNI7Jsh/UjITLmdk4G3Pc/hm6GuM37HLJpw87Ig302AeKFCNvMMt6FLoS6Q/WxFZGY2/lLEI+Nlj8Z3wmx/LiLd7blduh7iGm4fBDaFKJVQeRbyJWI8XjJtF9DTGvbVFxcXozfAX0Jcd/k9jIVegI6CloOirN+8LwX4jbJi+PPoUsh7s8lEMu8FYqz9vA8CXod4sUt07P8m6BVoTgrgifzrIgL9PzSibcy4l8Z5vU7ltyuuH2xj86C1oR82xor3J8YTqasL8933A6vgZhfU9o4FG59fGaKihzsxWN/pTJyZp7k6VshVuhf5XuG7tIwjMuoMT7TFUYDsN4f4rbN4yi3v28gbpNrQQWQtY1u38qxwrBi39NzF4bhVZ5f1BmXB7fhgyDuQxWQHXt+gXscdAzkH3ewGhjLsTb2g/tuiPst28Rjse0fcMYa8/w7xO2K2xh58Ny+BUTz86/2qf4txYLlcpmOsW0ToFkQ97+XoX0gWiXEvLjNy1ovgU5oOrdzje8XbwMlcHLfKIOSWRkCGKcEysaGIlE5xPMqz90a3wNChnYY4vPm6oeQceSYjtcPt0AbQ9laMRKyf+PE8dNnEMveBEpl6yKQY22eU3is53jwXGhpyMrgduBbNuOQZHkx3yqI7SjkSowVwM/aSXecNfRYqgcKHQHdA/G8SF4cr7Ffn4YOgOprA5HBKIjbB2+kM3+ee1+FOO5bA4qzXeA5HuK2xb5nH/Ic3xUqgsiuAoqzYfB8HpoBLYSSxW2HsCOhZyAbh7A8srgZ2gHiuCHO6nOe5zj8RuhLiNvn79Ab0ClQeyjOyuHJdhTHBXp+6cTbEfHvh76BOH5iHb6CRkNsVxfILNvxmqVvqCX73vYff8n+5nbG659zoAIolY1A4DsQt7Eq6AWI2w/NyiiqXg1+s+XBvFnPQi8v31kQhjMO3XF2JzytrevFRDjJCx8eE06vdMrhceFC6H2I+wOvx3hN8xC0L9QGMiuCg3WqMI/IcjWs87qOcV6ByE8mAiIgAiIgAiIgAo1OoBQlckDCpUwERKD5EHgSVeW+W9x8qqyaikCrJ9ATBBZB3HcLWj0NARABEWgoAhrfNxRZ5SsCqQnoPJ+aj0JFQAREoMUT8GeJW3xj1UAREAEREAEREAERaCACGyBf/jOW9lz1Qr8iIALNgMD/oY5LQfy3cVUzqK+qKAIiIAIiIAIikD4BnefTZ6WYIiACItAiCWgCrEV2qxolAiIgAiIgAiLQAAQOQZ4l0DoQX9FC4yuz+DqaZyH6jYX4ShmZCIhA/hDgq54Ohpb3qtQH7qsh3hij0S0TAREQAREQARFofgR0nm9+faYai4AIiIAIiIAIiIAItGICekVKK+58NT2vCZyB2vE1adQCiN9l4NL8PoV7ZUgmAiKQXwQ+RnVsP50NN78BZutc3gDJREAERKAhCWh835B0lXdrJ6DzfGvfAtR+ERABEUhBwP69nCKKgkRABERABERABERABEDgCYhPkAyBVoGWg2ZBk6HHoBvDdSxkIiACeUTgPNSFHwnfDFoR4ge/p0NvQv+GnoZkIiACIiACIiACzZOAzvPNs99UaxEQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQgbQJLJV2TEUUARHIlMAUJOgGVWaaUPFFQAREQAREQAREQASyJtAXKX+HVs86ByXMdwIaZ+d7D6l+IiACIiACIiACLZFAXzRK4+yW2LMtuE3tWnDb1DQRaGoC3Tp16tRjwIABPZq6IipfBERABERABERABFoLgUmTJrk5c+a0lua21nZqnN1ae17tFgEREAEREAERaDICGmc3GXoVXA8CmgCrBzwlFYE6CFRy8uvdd9+tI5qCRUAEREAEREAEREAEckVg0003de+9915lrvJTPnlJQOPsvOwWVUoEREAEREAERKAlE9A4uyX3bsttW5uW2zS1TAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREoDUS0ARYa+x1tVkEREAEREAEREAEREAEREAEREAEREAEREAEREAEREAEREAEWjABTYC14M5V00RABERABERABERABERABERABERABERABERABERABERABESgNRLQBFhr7HW1WQREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQARaMAFNgLXgzlXTREAEREAEREAEREAEREAEREAEREAEREAEREAEREAEREAERKA1EtAEWGvsdbVZBERABERABERABERABERABERABERABERABERABERABERABFowAU2AteDOVdNEQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREoDUSaNcaG602i0C+EVi0aJGbMWOGmzlzpps3b55LJBL5VkXVRwREQASWILDUUku5Dh06uK5du7oePXq4Nm30v5olIMlDBERABESgSQlonN2k+FW4CDQrAhrbNqvuUmVFQAREQAREIC0CmgBLC5MiiUDDEeBF+dSpU90ff/zRcIUoZxEQARFoAAKcrJ87d26g2bNnu1VWWUWTYA3AWVmKgAiIgAhkR0Dj7Oy4KZUItFYCGtu21p5Xu0VABERABFoyAU2AteTeVduaBQE++cXJr3bt2rlevXq5zp076wZys+g5VVIERIA3FjnxNX369OA4xuNZz549BUYEREAEREAE8oKAxtl50Q2qhAg0GwIa2zabrlJFRUAEREAERCBtAnpXUdqoFFEEGoYAX3tI4+QXXyOmV4g1DGflKgIikHsCPF7xuMXjF82OZ7kvSTmKgAiIgAiIQOYE7LykcXbm7JRCBFojAY1tW2Ovq80iIAIiIAItnYAmwFp6D6t9eU+A3/yi8ckvmQiIgAg0RwJ2/LLjWXNsg+osAiIgAiKQMYHDkIIfrqWOTpJ6D/iPh36DZkFvQsOhRjE7L9l5qlEKVSEiIALNnoAdM+wY0uwbpAaIgAiIgAiIQCsmoAmwVtz5anp+EOB7xml68is/+kO1EAERyJwAPxhOs+NZ5jkohQiIgAiIQDMjsArqe8fS+hwAAEAASURBVAPESa1kdjICnoTWh+6BboN6Q2XQ1VCDm52XNM5ucNQqQARaFAGNbVtUd6oxIiACIiACrZyAJsBa+Qag5ouACIiACIhAfQnYTYL65qP0IiACIiACzYIA//VwJ/QLdEuSGveFPye5ZkCbQSdBp0EbQl9Cp0NbQzIREAERyDsCGtvmXZeoQiIgAiIgAiKQNQFNgGWNTglFQAREQAREQAREQAREQAREoNUR+BtaPBQ6ApqdpPVHwr8DdCNUCZn9Csdl4crx5qmlCIiACIiACIiACIiACIiACDQEAU2ANQRV5SkCIiACIiACIiACIiACIrCYwMIFi91yNWcCA1D5K6DroJdTNIQTZLSx1Ytav2PCNYtTK1ArIiACIiACIiACIiACIiACIpArAu1ylZHyEQEREAERaP4EKisr3eqrr+6GDx/uysrKGqxBfK3IoEGD3Pjx4xusjFQZjxgxwt11111uypQprm/fvqmiKkwEREAERKA+BGb95Nxbtzr33t3OHTveuW4r1Sc3pW1aArx2REe6b6Bz6qjKOmH4ZzHxpsGPT471gZaB/oBkItAqCGis3Sq6WY0UAREQgVgCi2bPdr/85z9u/g8/xIbX13OlkhK3VPv29c1G6UWgxRHQBFiL61I1SAREIEpg8ODB7qWXXnL2IfRouNZFQAREQAREQARyTOAXfOZpwg3OVdzn3MJ51Zm/ic9F7XRhjgtSdo1I4HyUtTE0EJpTR7nLhuG/JYlH/84Q46WaAHs3Sfr+Sfzl3QQENNZuAugqUgREQAREoNkR+H7kuW7m2LiH43PTlF7nn+/4oVaZCIhAbQJtaq9qTQREQAREQARaPoHLL7/cTZo0ya288sotv7FqoQiIgAg0JoGpbzn3wCHO3bCpc+/euXjyi3X4apzDv1EaszYqK3cEtkBWfOrrGuj1HGRr92e0QeQAprIQgXwjoLF2vvWI6iMCItDUBGY+/3yDTn41dftUvgjkMwE9AZbPvaO6iYAIiIAINAiBlVZayVEyERABERCBHBH48kXnXvonXo4XMzfSexPntv2bcwP2cg6vwJU1OwL26kO+zvC8NGvPJ7x6QnzC65eYNN1Cv99jwnwvzKTGGp8Mw4YlEwERyEcCGmvnY6+oTiIgAk1FYOHvv7vpF15UU3yXoUNd16FDatZz5ViqbdtcZaV8RKBFEdATYC2qO9UYEWj+BN566y134IEHBk/mdOjQIZik2Hnnnd3o0aNrGsdvU+27775ujTXWcJ06dXLdunVz2267rbvnnntq4tDBd+zzW1N8/SGNbhNf1eLbt99+604++eQgT5a73HLLub322su9/fbbfrQa97Rp09wRRxzhVlhhhaAOhYWFwTel+E0rllFSUlIT1xyff/65O/zww4O2Lb300q53797BOv2jxvTMh/ndd999bsstt3RdunRxffv2dZ9++mkQNhSDpmS2wQYbuPZ49/P06dOTRanTn+UUFRW5Hj16uM6dO7uBAwe6Z599dol0v/32m7vqqqsc69OnTx/Hti2//PIBvzfeeGOJ+Kk8mE+bNm2C/pwxY0atqPfff78bMmSI6969u+vYsaMbMGCAu+SSS9y8eeGrtbzYZMc+ZvuPPvrogHlbDAa57dD4DTDG4TYStTfffNPtt99+rlevXkFbVlllFXfccce577//PhrVffXVV+7YY491a621VrAdkBXZH3/88e6XX+Lu9y2RhTxEQAREoPkTmPgYvgy195KTX/12dm74/5w7BpNj6yG8jS7Km2lnd0G914YGQHMhPrVlugBu2m0Q/Uq5AptcvQjShc6aBf+Bwtcffgulev1hTQI5ckdAY+1qlhprb+s01s7dfqWcREAERCAVgR9xn2PBT/guLqzt8j1d78svcwW455BrLdWuXapqKEwEWi0B7RmttuvVcBHIPwK33XabO+GEExwnKjj51K9fP/fjjz+6d955x40aNcodcMABQaUZZ91113Xbb799MEHGiYann37aHXbYYW7y5Mnu4osvDuIVFBS4Cy64IJj0+PrrrwO3tZoTSWbvvfee4yQbLwKHDRvm9tlnH/fzzz+78vLyYNLnsccec7vttptFD+q0zTbbBJMnrAPdnGg58cQTg3xqInoOTqTtuOOObubMmUHbWH9OMN17773u8ccfdy+88ILbbLPNvBTVzmuuucY999xzbs899wwmfzjZ1L9//8A9btw499lnn7m11+Y9qcU2YcIE9/HHHweThJzEycamTJnitt56a7f++usHkz+c8HvwwQfdrrvuGkzIcZLSjK8SHDlyZNAfu+++ezBB9c0337gnnnjCjRkzxj355JNul112seixy0WLFrni4mJ3ww03uL333jsog5NcZkcddZS74447ggk29g/7lpNr5513XsCOjNpFBnvsz6222iqYOGQaTqytuOKKlmXs8s4773THHHOM4yQot0FOfnGC8vbbbw/awTJXXXXVIC2ZbL755u53/JuL2wcnZefOnevI7u677w4mVDmRKhMBERCBFk3gt++ce/LUxU1sgw9vb4jz9TanOLcC50tkLYAA/2nynyTt4FNYG0OvQpz0skcAMevptoU4ADA/OAPbNVwyjqwRCWisrbG2xtqNuMOpKBEQAREAgdm4h1D10MM1LHrhHkbbZfmAvEwEREAEREAEmj+BdzfZZJNEXfbJJ58kqNZuEydOTGACI4GnexKYvFkCx9SpU2v8vvjiixq3OfAUUAJPIAV54Gku8w6WgwYNCv6lXMszXJk/f35izTXXTGDCI4GnrWpF+e677xJ4SiuBSaQEJjZqwo488sggvzPPPLPGj46KiooEnn4KwjDxVhOGyZ0EJq0CfzylVuNPxwMPPBD4r7POOomFCxfWhDE9doHEMsssk8AEXY2/OR566KEg/PTTTzevmuXw4cODMDytVeOXrgOTN0Faln3GGWfUSoZJvIAvJp8SmIirCauqqkr89NNPNevmYJ/h9SdB283Plsyf/UKbM2dOAhNUQbl4Cq8WB4ZjUioIw8RY4o8//qBXjRmn0tLSGj86mD+FSdEE+zhqxojtNcPkaQJPzQXbQ3QbwgRlAhNoCTwRZ9ET119/fVBGtGxGmDVr1hJ1rUnYQh06lrXQjlWzRCAVAZ63yvZIJC7oVq1r108kqmqfg1Mlb6gwjr9wDuAr8mQNT6AERZD30ZGiVsc6nxbj49B9IbPucHwBMc3W5pnFUuPsDHcgjbU11uZ+p7F2+juOxrbps1JMERCBeAILcf/i8x13SnyyTv9AU08+JT5iM/LVODuLUauSNDkBPQHW5F2gCohAagJ9z3oqdYQ8Cq28Yvesa3PzzTe7BQsWBE/0rLfeekvkw1frmWHCypw1S75276STTnIvvvhi8EQQXzWYjj311FPuyy+/dJjscZiQqZWEryjEJFfwZBKf0OJTPn/++afjq/iWxT92zj333FrxN9poo+CVhnxayDc+kcWnvfhE1SGHHOIHBa97vPHGG92rr74aiE+U+cbX6228Mf9YXdv4akLWj6/0u/TSS4MnlhgDk1HB6yLJiE+cZWts3/nnn18rOZ9QY/3vuusux6fiMIkUhDNunLHP+CpB/tOUT4TZk1N+XD6lxSetyOiKK65w//jHP/zgwH3dddcFT3fxCTC+8tI3PgFGfnyS7tRTvScQEInbxNVXX73Ek2F+et/NbRCTZY7lrbzyyn5Q8HpH1pNPs/Epvq5du9aER+vEAL4yUiYCIiACLZ7AG6Ocm/JydTOXauPcPrfii0+1j58tnoEamIzAFAT8H3Q99A70IPQntB/EQd01UPTJMHg1rrWWcTapaqytsbbG2o17fFFpIiACIvDT9Te4+VOnBiDa4NMdK55X+x6SCImACDQOAU2ANQ5nlSICIlAHAftWFF+xV5dxMuXKK68MJrroxhNEtZLgya1a66lWXn+9+t4LX5HIbwFEzb7Pxdf8cQKMr1hkeZwM8idBLB2/kxWdAOMrFmnJvtlFf06Avf/++8FrBC0vLrfYYgt/tcbN1/3x21YXXXSRe+SRR9zBBx8chPHVe6wfJ874jatsDf/qiW0fv6vFCTDW1SbAWMZrr70WTByRJ19byYlC39gn0QmwH374IfjWF7+jxXpHJweZHk98uQ8++MD17NnT4UkrP8saN19XyP6JGl9zyW+0pWu2LfCbcXHffmO78JRe8NrJTTfdNJi4O+ecc4KJ12eeeSZ4fSa/RcfXW9aHfbr1VTwREAERaFIC0z9y7oULF1dh4GnOrbbN4nW5RMC5GwChEjoD4j+TMEvqPoF49+cuSNaIBDTW1lhbY+1G3OFUlAiIQKsnMOejj9wM3DsxWxF/9m2fwf0JS6elCIhA/QloAqz+DJWDCIhADgjwySVa9MmbaNacLOGk0K+//uq222674JtbfAKJ3w2rrKwMJmfwOsRosqTr/H4YDa8UTBqHAXilXRDOb3DRkn1LKs7f0uB1gEHa6I/5GwM/PNU3vDjJddlll7lbb721ZgLs3//+d/Dk0xFHHOFnk7E7rh3MxOpjbaIfnwbjk178ZtdOO+3k+PQZn4DiN7fwWknHCaW4PuF30/j9LD4pxr6MM/Yz3gbg8IpFd+GF3o3WuMgRP6trxDvpqm0LV+EDtanMtoXVVlvN8UPynDgdO3ase/TRR4Nk/G4Ynyj829/+liobhYmACIhA8yUwH2+2e+QY5xaGf3bojSeVB5/dfNujmteHQAkSU8nsSQRQsiYmYONMjbVrd0Sq8aLG2rVZRddSsYvG5brG2nFU5CcCItASCSTwh+BpI/F/H3zrnNZ5m63dsvvs3RKbqjaJQLMgoAmwZtFNqmRrJlCf1wo2J274rlRQXT4phO9lJa36tddeG1w84btQbsSIEbXi8dWEfDopE7PX9z3++OPBEz11pe2Gx9ZpfHopzuL8rQxO+MTZtGnTAm+L58dJ9SQRb2DsueeewQQUn4DiZBG+nxa8VnH55Zf3s8nYHdcOZmJt8OvK1xDydYPvvPOOGzBgQK2yjjvuuGACrJZnuMJXRvIpNvYjX/3I11euscYataJaOXwNpD1JVytCipVU7OKSWVmc3LN+jovn+7G9Dz74YPD6Tj6p9vzzzwevfOTrGDkJeNRRR/nR5RYBERCBlkGAT379FD55264TXn14m3Nt27eMtqkVrYpAaxlns1M11sYbWmNe251qvKixdurDQSp2cSmNv8bacXTkJwIi0JII/IzPYsz77LOgSUvhMw698GfeTI+ZLYmH2iICTU2Ar6GQiYAIiECTE9hqq62COowZMyZlXb744osgfN99910iHp80ijM+HUbj6+uiZuW+8sor0aDYdU7O8ZtPH374YfAtqGgkvsowavYNLz4NFWfmz9cOZmonnnhikIRPflE0TjrV1zjZxG9dRc3qam1iOPuEr/2LTn4twr+d4nj4eR566KHugQcecN9//30wCfZZOEi0OF26dHH8Jhw+3O74vbCGtEy3Bb8ufCUlX4vIb5hxIpZWXl7uR5FbBERABFoGgS9fdI7f/jIbdqlzPfvZmpYiIAJ5SsDGORprZ9ZBGmtnxitVbNsG073u8vPSWNunIbcIiEA+E/gTn+n45eZbaqq4QvGpbmm8JUYmAiLQdAQ0AdZ07FWyCIiAR+CEE05wvLC5+OKL3Sef8PMQte3bb78NPPhdJ5pNxAQr+OE3mKLf3rKw5ZZbLnDye2FR+8tf/hK8su+mm25yTz/9dDQ4WOe3ofgtKhqfdDrwwAMd/7l4ySWXBH72wyeA/vvf/9pqzZLfhVpnnXWCyaCHH364xp8Orr/88stu7bXXdvx+WKa2ww47BGn55Nvo0aMD95AhQzLNZon4bB+/L+Ybn/C69957g3/P7r334sf32Sf8Vhonscz42kK+sjCuLy2OLfn6RH7H7Oeff3aDBg0KJrssjMu///3vwTfFjjzySGev7/HD+eRbpk+H+enNffLJJ7v27du70047LfjOl/nbkt818y/Y+frDuCflzG+ZZZaxpFqKgAiIQMsg8Af+iFBe/ceLoEH9hjm32ZEto21qhQi0cAIaa2usrbF2C9/J1TwREIG8IFCFT0Qk5s8P6tJxow1dd/zpVyYCItC0BPQKxKblr9JFQARCAnyCaNSoUe744493fLqIE1P9+vULXnfIiZeuXbu6cePGOf4Lk68/3H///R2fAuOrSfjaP36D6YADDgheRxeFykkifuNrn332cbvttlvwBBe/33TYYYcFEx78dtOwYcPc7rvv7rbZZhtXWFjoOHkxdepU9/bbbzt+d4yvKbQJjSuuuCJ4Xd8///lP9+abbwZpGM4JKObPJ3/4/SszPurOCSp+H4uTZ2wbnySbPHlyEJdt48SZn8bS1rVk3mTGSSJaLp7+Yj58JSEnFNk+TuCxfXzVH5/q4jfH/FcEcsLI+o19wkmk1157LZj84isan3yy7k9/MB5fQ8mJtcGDBwevEuQrEmmc+Hr33XeD7YPfF2NfrbrqqsETYVOmTAkmEPnNs1tuWfwvqyBhhj/skzvuuCMoj0+d7bLLLsGE4nwMXjl5yskvvlry008/DXK+7777HCdOOWm31lprue7du7svv/wyaG+HDh1ccXFxhjVQdBEQARHIYwILFzj3xCnOzax+ba9bpqdzf7nR4X0ueVxpVU0ERMAIaKytsbbG2rY3aCkCIiACDUOAfwSeOWZsTebL4ZMPS4VvJKrxlEMEREAEREAEWhCBd/FKO5z/UhuekElQsmoCEyZMSGCiKoGJhgQmUhIrrbRSAhMeCUxg1SDC5EoCTzkl8C2DBF6Rl8AETeKxxx5LYIIsge0nccEFF9TEpWPBggWJs88+O7H66qsn8JRZEAeTFrXi4KmdBF5fl8DERwKvOEzg+00JTGokMKGTuPvuu/EHnvm14uOJtMThhx+e6NmzZ6Jjx44JTNYkysrKgnqyDv/6179qxecKJk4SeOVfAh+MDurB5SGHHBL4RyOzDcyHbarL8GrABCbPEph0SeCfnXVFTxmOCaWg3OHDhwfb5V577RVwJhNMDiYw0RibHpOSAQNMEibwxF2iqKgogddEBn0R1w76RfuAGbO97FNMJiXwhFWtsjCRlsAkZc22seKKKyY233zzxMiRIxP4BlqtuMnyt0hsH+OwvVFjvRmOSbYEnvgL6sLtAh9CT7zwwgs10d94440EJv4SG264YRCH2wEm6BL4plnio48+qonXWhw6lrWWnlY7WyWBP+ckEvcfnEhc0G2xPh2Ttyg4/sIx/l1I1nIJaJyd5R6osXY1OI21NdauaxfS2LYuQgoXARGIEpiDez6frNM/0Kcbb5JYOAdj6BZmGme33MF1S26Z/rLZkntXbWtqArww34RPrqQy3LgPgqPfT0qVRmH5SwCTMe6yyy4Lnkjjk0qNYXwdJF97yO9pYbKuMYpUGSKwBAEdy5ZAIg8RaBkE5v7u3AMHO1fpfStzy+Od2/XKvG0fv8mIV+O+hwpumreVVMXqS0Dj7PoSbKbpNdZuph3XDKutsW0z7DRVWQSamMCPpaXul1tuDWrRDW8YWvmaq5u4RrkvXuPs3DNVjg1PYPE7uhq+LJUgAiIgAi2GgP+9K2sUnvpx119/vevRo0fwWjzzb+glX8VI4zesZCIgAiIgAiKQMwKzfnSubPfak19b41wz7PKcFaGMREAERCCOgMbacVTkJwIiIAIikK8E8KBXrdcfdtt1l3ytquolAq2OgL4B1uq6XA0WARHIBYHNNtss+O7T+uuv7/C6RPf555+7p556KvhGFr9Fhdfh5aKYpHlwsu1///tf8G2sMWPGuD322MNtueWWSeMrQAREQAREQAQyIvBrpXN37+3cjK8WJ9vxQucG6vuGi4HIJQIi0FAENNZuKLLKVwREQAREoCEIzMM33v/8+usg6zb4pnzngQMbohjlKQIikAUBTYBlAU1JREAEROC4445z5eXl7v7773czZ850+B6Z4ysPzzjjDDd48OAGB8RXa55zzjmuW7dubv/993ejRo2KLbOystLh22SxYVHP4uLioB1Rf62LgAiIgAi0MgI/TMTk1z7OzZpe3fCl8NKIPa93bpPDWhkINVcERKCpCGis3VTkVa4IiIAIiEA2BH4fM7YmWZehQ12bBv5TdE1hcoiACNRJQN8AqxORIohA1gT0bYKs0SlhrgjY98HSyW/KlCmub9++6URVHBFYgoC+k7AEEnmIQP4SmFPl3MTHnJv985J1XLTAuTdvdm7ub9VhbTs4t/+dzvXHqxCbienbBM2ko+pXTY2z68dPqXNEQGPtHIHMw2w0ts3DTlGVRCBPCfD1h1/usoub//U3QQ373HiD67rjjnla2/pVS+Ps+vFT6qYhoCfAmoa7ShUBERCBRiHAp9E4GJOJgAiIgAiIQEBgxpTqVxv+imVd1qGbc3+937m+eoVLXagULgIi0DoJaKzdOvtdrRYBERABn8C8Tz+tmfwKXn+43XZ+sNwiIAJNTEATYE3cASpeBERABERABERABERABBqFwPSPnbuHrzb8oe7iOq/g3KGPOLfShnXHVQwREAEREAEREAEREAERaKUEar3+cIcdXJsOeIOCTAREIG8IaAIsb7pCFREBERABERABERABERCBBiLw9QTn7jvIuXnhqw3bdXRu86Od4zJqnQqc2+AA57quGA3RugiIgAiIgAiIgAiIgAiIQEiAb9z5fezi739122WY2IiACOQZAU2A5VmHqDoiIAIiIAIiIAIiIAIikFMCk8c499AI5xbMrc42eLXhA3i14bY5LUaZiYAIiIAIiIAIiIAIiEBrIjBv0iQ3/5vqb3+16dzZdR6oV4e3pv5XW5sHgTbNo5qqZSsksB/afAP0CvQ7xI8Y3QPFWT94/gN6EZoK/Qnx3T6PQ0OgVDYcgW9BsyD+JXo8tAckEwEREAEREAEREIHmT+D9e5174JDFk198teERT2vyq/n3rFogAiIgAiIgAiIgAiLQxARqvf5w6FC9/rCJ+0PFi0AcAT0BFkdFfvlA4FxUYiOIE1PfQv2hZHYxAg6EPoFwR8fNgNaB9gp1KpbXQ1G7Gh6nQ8z/NmhpCO8Gck9Cp0A3QjIREAEREAEREAERyF8CeO2Km/2Tc4sWLFnHD0c79/wFi/2793XusHLneqy+2E8uERABERABERABERABERCBjAkErz985pmadN123aXGLYcIiED+ENAEWP70hWpSm8BpWOXE1BfQIGgclMz4st0rofcjEZjuOegq6CFoGmS2DRyc/PoS2hz6FaIx7rsQJ8f+B1VCMhEQAREQAREQARHILwIL5jn3EYY3E/B/nZ8m1V23FTdw7tBH9F2vukkphgiIgAiIgAiIgAiIgAjUSWDuJ58sfv1hly6u87Z6vXid0BRBBJqAgF6B2ATQVWRaBDjh9TmUSCN2GeJEJ7+Y7CVoPMQnuzjh5dvx4cqlWNrkF70qoZugDtARkEwEREAEREAEREAE8ofAXLyx+dVS567bCC97Pim9ya/VcDE+Av/r6bpi/rRDNREBERABERABERABERCBZkxg5lj+H7/augwdotcfGgwtRSDPCOgJsDzrEFUn5wTmhzlG3ws0NPRffLZaXPQYOM+DGOeCxd5yiYAIiIAIiIAIiEATEfjtO+feGIXn1O/C105n1q5Eu47Odepe249rbTDU77+7czuWONe+E31kIiACIiACIiACIiACIiAC9SQQvP5wrPf6w112rWeOSi4CItBQBDQB1lBklW8+EFgNldgB+gN62atQZ7hXhmZB/msRLQqfPKOtXb3QrwiIgAiIgAiIgAg0EYEfJuI1hzdUv+4w+p2vLniia6sTnNsUD613KmiiCqpYERABERABERABERABEWhdBOZOxOsPp04NGt2Grz8ciDcuyERABPKSQJu8rJUqJQL1J8BXGN4LcVkC+a85XBbrNLxDKNbMP907SfxmWJz6x+YuTxHIYwKVlZVuqaWWciNGjMjjWqpqIiACItDCCSTwBugp+O/OPfs6dzPe4vzB/c75k18913FuL3z7q/gj5waepsmvFr45qHkiIAIikCsCZWVlwVifS9/69u3rqHRN1wzpklI8ERCBlkpg5li+PKrauu4w1LVZml9fkYmACOQjAT0Blo+9ojrVl0BbZHA3xL9fPAhdDWVj6Xx/LJt8laaRCQwePNi99NJLjo+oy0RABERABEQgbwksxBubJz3u3GvX4xn1iiWruSomw7Y91bl+O+P1hvof25KA5CMCItAUBDTWbgrqKlMEREAERKChCfAe0uyXX3bzp01foqjfnnq6xq/rLrvUuOUQARHIPwKaAMu/PlGN6keAk1/3QPtDo6FDoeishz3hZU+CIUotM3+LVyswZmXTGD968amwTZKEyVsEREAEREAEREAEqgnMn+Pc+xi+8FWHVV9HqCzl3IA9qye++mwWCdOqCIiACIiACKRPYO+993ZbbbWVW2mlldJPpJgiIAIi0EoJ/HzTKPfzjXjrQgoLXn+4rV5/mAKRgkSgyQloAqzJu0AVyCEBbs/3QZz84vJwaCEUtdnwwJfkg++AceQ/LRKhX7j+WcRfqyIgAiIgAiIgAiKQOwJz8V+bt2937o2bnZv9U+1823V0rvBg57Y+2bnl1qwdpjUREAEREAERyILAsssu6yiZCIiACIhAagJzPp7ofr4ZY/Q6rNvuu+v1h3UwUrAINDUBvTulqXtA5eeKAF+2+zDEya//QodBcZNf8A7sxXAZ95zyrpE44aoWjUHgrbfecgceeKBbeeWVXYcOHYJ/J+68885u9Gg+0FdtfGf9vvvu69ZYYw3XqVMn161bN7ct/nFzzz18+G+x2bvp+fpDGr9tZeKrWnz79ttv3cknnxzkyXKXW245t9dee7m3337bj1bjnjZtmjviiCPcCiusENShsLDQ3XXXXW78+PFBGSUlJTVxzfH555+7ww8/PGjb0ng/dO/evYN1+keN6VlX5nffffe5Lbfc0nXBh1X5bv5PP/00CBs6dGg0Wc36Bhts4Nq3b++mT1/yUf2aSHU4WE5RUZHr0aOH69y5sxs4cKB79tlnl0j122+/uauuusqxPn369HFs2/LLLx/we+ONN5aITw+2jX3A+h199NEBk7Zt2zr7HsEPP/zgzjjjDLfOOusEZRcUFARufpvsq6++is1TniIgAiLQbAjMwmTX8xc696/1nXvhotqTX516ODfoH/i+18fO7fEvTX41m05VRUWgeRDQWLu6n5p6rJ1OP7CmHBunc91jWx/H1xxn//nnn+6iiy4Kxs+8trHv+zI/hnMZZxzX85qI12IdO3Z06667rrv++utTvko+3WsGK+/+++93Q4YMcd27dw/KGDBggLvkkkvcvHnzLErNsry83B166KFu7bXXDq4JeD206aabBnVatGhRTTxzsJ1sH68Db731VsdrIrZjxRVXdMcee6xj+2QiIAIiUBeBRTiGTjv7bNxVrL6t2KHfWq7ggAOWUM9TTnYrnHF6XdkpXAREoIkJ8IkZmQg0dwId0IBHod2g/0DHQkuOhuHp2S1wc5JsJFQO/QrR+kInQRx93wnJGpHAbbfd5k444QTHiRBOPvXr18/9+OOP7p133nGjRo1yB2DAQWMcXoxtv/32wQTZL7/84p5++ml32GGHucmTJ7uLL744iMdJkwsuuCC4wPv6668DdxCAn76YSDJ77733HCfZZsyY4YYNG+b22Wcf9/PPPztecHHS57HHHnO77cbNq9pYp2222Sa4sGId6OZEzoknnhjkY/H8JSfSdtxxRzdz5sygbaw/Lxbvvfde9/jjj7sXXnjBbbbZkq+2uuaaa9xzzz3n9txzz+BCkRdt/fv3D9zjxo1zn332WXBB6Jc1YcIE9/HHHwcXy7169fKD0nZPmTLFbb311m799dd3xx13nOOE34MPPuh23XXXYEKOk5RmkyZNciNHjgz6Y3f8+4kXs99884174okn3JgxY9yTTz7pdol5JzZ58xUsvJAl8zZt2gQXp3/88Ucwofnll1+6nXbaKWg7373NPiSr/fbbL5iotPK1FAEREIFmQ+DXSrzmEK9Ref9u5xbMrV3tbn2c2+YUvDwZw5OlO9cO05oIiIAI5ICAxtr5MdZOtx/Y5ele90Q3D06a8fqDY3f+oY1/2qvLOGnG65Wqqip30EEHBZNojzzyiDv11FODa6ybbrppiSwyuWZg4qOOOsrdcccdwZ/mOP7n9Rr/MHfeeecF10O87mnXbvFtqrPOOiu4RuCfATkpx2uhF198MagT23f33TifxtiZZ57pnnnmmeA6gtd5vG4i9y+++CJIH5NEXiIgAiJQQ4CvPpwX/lF5Kfzpug9eg7j0aqvVhMshAiIgAiIgArkgUIRMykKNxZLf8foyXC/D8mrIjBNVDMffqR3+Tu1KYjQYflG7Bh5MNxXCX6wdR/Q/Q/Q7GaqvvbvJJpvgvn1q++STTxJUa7eJEycmcLGTwORJApM3S+CYOnVqjR8uXGrc5sA/BhN4AinIA09zmXewHDRo0P+zdx7wVRTbHz8JECD03qv0IggIiEqxYaOL+kQEsSDq/4kKFtQnKmLXZ8P6FEEUsQAiYkFFEBAEFJAmndA7hJqQ7P/8JpmbvTc3yb1JbpKb/I6fYXdnZmdnvrPgzD17zsGceuXZi/j4eOess85y9MtIR62tbLY57tixw1ErLUeVSM6pU6c8ZUOGDDHt6cbKk4eTv/76y1HrJ1OmijdPmX6d6KjSyuSrlZonHyeTJ082+Wrp5CQkJHjKcD/6HB0d7aiCzpNvTz7//HNTfv/999ssz3HQoEGmTK21PHmBnugm1tyLZ6sFltdtusk0fHWj6ujm01Omm2Rn3759nmt7gjnT+AJm7DbPHtE+kiotHcyBW1RxZsqGDx/uzjbnmOejR4+mymdG7hPgv2W5PwfsQR4msEP/HZ8y2HFGl3Wcx0t7p9fbOc4y/X9D/Ok8PIDw6hrWX/r/GMRipeRfAlxnB/nXkmvtvLHWDmYeMMWZ3feo5ZPf9fmHH35o1tk4uqVOnTomX71qeO179ENDR71umDL1quG5JTN7BvtsjUPm6AdvnrZwYvc+//3vf73y/Y0feyb1qmH6pMozr/p2H1SrVi1HP57zlGG/ceGFF5p7Fi1a5MlP74Rr2/TosIwE8i+BEytWOqubNXdWN25i0oEJE/PvYDMxMq6z8+/iOj+PLOXTmvw8So4tHAm01k4P8ul4fb1GgmzVNMKcidRLPlbU43+Sz/0d5vhkwk55hSYou6zV2DI9f0HTN5ryhowOIx/tozPvUuIt9a185swZ8/Vf8+bNU7GHaz0rqrCyp54j3O7ddddd5os+WFPB1WAgMnPmTIGlEdztqaLM6xa4KMTXg6qIMV8kwgoMX0bCbQd85z/66KNe9Vu1amWe+/77Gs/FJbDIgrUXLKoGDBjgKhHj7vEN/Zrot99+MwkWZW6Bq45zzjnHnWXO8SUn+gf3JU8//bRxF4kCfLEJd5FghC84MysY33/+4/3XCRZq6D9cPcIqTjeYpvm04ghgzmCt9frrrxuLsNq1a3t1B3P24osven3l6a4A95a+gnuQKCRAAiSQ5wk4+jvbhtki818V2TIvdXer6VLnQl2KNLla9PP21OXMIQESCD2BArLOBkiutfPGWjuYecC8ZXbfA48YFStiexycPPPMM559Be6EK3RYZ8H1uyqwjMcHd4vB7BleffVVs+6HBZjvOh/PwJ4I3jFgcWbF3/jhNQJ1JkyYYKy8YB3mK9jHuPcesCrDGObNmydwP9m+fXvfW3hNAiRAAmJcH45KcX0Yfe65Um6AxuSlkAAJhDUBKsDCevrydedH6+iQApGugVRKo85Hmo9EyWUCNlYU3HRkJHCv99xzzxmlFM5PnjzpdYtabnldp3excOFCUwz3eqNHj05V1cbngps/KMDgYhHPgzKoVKlSqerDZaKvAgwuFiFpxexCPhRgf/75Z6pNZVqbM2ziEDsLvv3hmuSGG5IWZXADgv5BcQb/95kV/arH7/gQVwAKMPTVKsDwjPnz5ws2teAJF5FQFLoFc+LehKIMbij9uWOBIhIuTp599lkBO3BHjDfEWYN7TAoJkAAJ5GkCCfEiK79QV4evi+xdlbqr9buKnK8/7tXvhoCIqcuZQwIkQAIhIMC1dt5YawczD3gNMrvvSWsPkd6rhf0FXLv7Ctb/EKz/fSXQPQNcnC9fvtwo5dTKy7cZc41YZdhzuQWu7hFrGO7uEQf4+PHj7mJJa9/nz7W8WoWZew8dOuTVBi9IgARIwBLY/8ab6vpwg7mMiI6WamOflgh+qGbx8EgCYUuACrCwnTp2nATyFwFYLkGg+EhPsPHBhg4bF3VjYWJu4ctDKEYQ7BjKGX8BlNNqE5sqiLoUTKuKyT927Jg52sDJCKTsT/zl23vUHaC/W0wcMxRYBu5K6cXwgpJr7NixJsCzVYC9++67xkIKXzhmRfyNA+3Z/tgxIQ/WYLD0QoBpxOzCl5olSpQw/vrnzJkj6i7F75zYttCGW0qXLm1iAagrFBNHDP77IfiKFXHWYHlXpEgR9y08JwESIIHcJxB3Iim2FxRfR+Bd2SURqrxv0Tcpxle1Vq4CnpIACZBAzhCw60yutb15p7UeRa1QrLUDnQc8Pyv7nvTGhbb9Cdba/j42s2251//2/kD3DNi7qactUbfp8sQTT9jb0z2C1blqfYE4Y9j/wcMHLNKgqEMZPr5La9+H2GK+gvsg6kLRt4jXJEACJCAnV66UAy5vPpXvv0+ikhXnxEMCJBDeBKgAC+/5Y+8LAoEsuBUMJzx2k4Kv+DReVppdf/nllwVKK7jgGDx4sFc9uCaEAiwYse77pk+fLj179szwVihnIHv27PFb11++fcbu3bv93rNr1y6Tb+u5K6VnxYUfMHr06GEUUPhaEhtLjZ9m3CpWqlTJ3UzQ5/7GgUbsGNx9hcsSuCVcsmSJNG3a1OtZQ4cONQowr8zki/TGBveJ//vf/8xGWf3vG9eWCLwNizeNqSZw60IhARIggTxB4KR+wPGHur79/S2RE/u9u1QkWqSNuovtOEykXB3vMl6RAAnkPoECss4GaK61xbgw933p0luPhmKtHeg8oJ9Z2fekNy5fBvZ6//79RjnkqwTzt/639wS6Z7B7B7h2t94xbBtpHeFVA8ovfBQ32sdTB7xOQAFGIQESIIHsIJB4+rTsfFhdH+pvDZBoVbqX+9e/sqNptkECJJAHCDDgQB6YBHaBBEhAfxvs2NFgmDVrVro4NBCyKe/Xr1+qerA08id2E+fvaz/7XPiDD0SgnIPP+hUrVkhsbGyqW+DK0FdsDC9YQ/kTmw8XIsEKLKIgsPxCgkDplFXBxtTf+Gxf7ZjwHMxJs2bNUim/oKjyxyOYvmHzjphw//d//yc//vijuXXatGnBNMG6JEACJBAaAsf2isweLfLfliI/q1LerfyKriDS7VGRe9UF4hXPUvkVmhlgqyRAAkEQsGterrWDgKZVs3utHeg8oJeZ2fcENzrv2ojHjNjFvuJv/W/rBLpnKFmypFnTr1q1Sg4ePGhvT/eY0+NPtzMsJAESyNcE9msMwrgNG80Y6fowX081B1dACVABVkAnnsMmgbxGYNiwYcadBSx7YPHjK9u3bzdZiBsFsRsxc6F/wE2eb+wtW1ahgv4QqQIf+r7Sq1cv47IP1kXwLe9P8IUh/NZDYOl03XXXCVyAjBkzxqs6/NojGLOvIH5V48aNjTLoiy80LoxLcD137lxp1KiRIH5YsHLxxRebe2H5NmXKFHPerVu3YJtJVR/jg7WVW2DhhcDU+IKzT58+niLMCWKl7dy505MHFydwb+JvLj2V0jiBFRvcWfqK/cI0Wn1xU0iABEggVwmsny3ymn608NsrIqePpnSldE1VeD0vMvxvkS4j9fPR8illPCMBEiCBXCTAtXbeWGsHOg94VTKz78nqK/awWkC43QpCWWX3PP5crAezZ7jvvvtMnOAhQ4b4df0ObxZu67C0xo9YZM8880xWh8r7SYAE8hmBRI2Fvu3W22RN02aypknToNKB99730KgycoREqUcaCgmQQP4hUDj/DIUjIQESCGcCsCAaN26c3HHHHQLrIiimGjZsaNwdQvFSqlQp+eWXX8xXmHB/2L9/f4EVGFyTQGHy3XffybXXXiufffZZKgxQEiHGV9++feXKK680Flx16tSRgQMHmlhSX331lXTv3l2uuuoqE/i5devWAiVLTEyM/PHHH8b/PtwUWsXLs88+a1zyPf/887Jo0SJzD8qhgEL7sFCKdAVKhRUTFFSIjwXlGcYGS7J169aZuhgbFGfue1INIo0MtA1m2FBCssP6C+107tzZKBQxPijwMD6whVXXO++8I9YVJOree++9nnnDnCA+1/z5843yCy4aZ8yYgWoBy+zZs814EIQbnCpXrixQgMJNJRiNHKk/KlNIgARIILcIrNCYkdPuUBcpZ1J6ULGRyPnDRVr2FykclZLPMxIgARLIIwS41s4ba+1A5wGvDazPgt33ZOV1Q7xiKL9atGhhXMPHx8cLPtbDPgB9wf7AV4LZM0DxtXTpUrPnQ8xg7L9q165tLMLg6hAfBULJ9vbbb5vHIObXCy+8IMOHDzf7QOwN8dHdN998Y/Z1/vZ9vv3jNQmQQMEhsPeVV+S4H488wRCIVs9EZfU3GwoJkAAJkAAJkEBgBJaqSzs1hElf1ELGQaIkEVC3G44qqhyNYeWoIsXRjZijmyNHFVgeRKpccdTKyVEf+o6603BUQeNMnTrVUQWZo1PjqJ94T12cqDsPR79mdOrVq+do8GNTp0uXLl511LrIefDBBx11t+eoi0OnRIkSToMGDRxV6DgTJ050dAPoVV8VMo5uyhwNFu0UK1bMadWqlTN+/HjTT/ThlVde8aqPi7Vr1zo33nijo4GkTT9wHDBggMn3rYwxoB2MKSPRLzMdVQw5RYsWddR3f0bV0y3Xzad57qBBg8x7qXHRDGcwUYWUo4pGv/fr5twwUCWhoxZ3Tu/evR11E2nmwt84kOc7B7Zh/H1QpZrTtm1bw1et7hxVWJq5wNxT8iYB/luWN+eFvcpmAgvfcpzHS6ekl5s7zqrpjpOQkM0PYnNZIYD1l/5/ZqkmSv4lwHV2Jv+ScK2dBC631tp22gKZB9QNdt+D9bX+tbePSXXEmh3lOLoFa22kw4cPO6rscqpXr+5gDa4fozkaa8vRj+Dc1Z3M7hnQiH4c5+iHh579XpUqVZxzzz3XeeSRRxyNa+z1HHWZ6OgHdaYu9hn49/29997zer77BuxhMD70z1fS2iv61rPXXNtaEjySQN4ncHzxYmd14yZZSht79HTiduzI+4PN5R5ynZ1/F9f5eWQR+XlwHBsJ5DIBbMzb4Cu39EQX+aa4adOm6VVjWZgQ0I2bjB071lik4avGnBC4g4TbQ1WuiSrrcuKRfAYJpCLAf8tSIWFGfiLg6O9pvzwtMveFlFFV0v9vD/xKpHT1lDye5QkC+gEF3Ggt0860zRMdYidCQYDr7FBQDYM2udYOg0nKJ13k2jafTCSHke8JJGq4ik29eku8evCBlOh8odSCJal6ywlG4F2HkjEBrrMzZsQaeY8AY4DlvTlhj0iABMKAgDvele3uypUr5bXXXpPy5cuLfn1ps0N+hCtGyN133x3yZ/EBJEACJFDgCCQmiHxzr7fyq2Z7kZs1biSVXwXudeCASYAEcoYA19o5w5lPIQESIIFwJ7D35Vc8yq9IDS9RTePKR2joBCi0gknhzoH9JwESSJsAY4ClzYYlJEACJJAmgXbt2om6SDQ+8tVdovFHP3PmTBMjC37r1S1imvdmRwGUbfB/DwvDWbNmydVXXy0dOnTIjqbZBgmQAAmQgCVw5rTIl7eKrPna5og0uFTk2gkiUdEpeTwjgYJB4DkdZjtNGvROKmo6qWmrpmma3tB0QJOVunqy2V74OSJo6/V+8plFAoYA19p8EUiABEiABDIicHzRYjn08ceealUefliKVKniueYJCZAACYAAFWB8D0iABEggEwSGDh0q06ZNk08//VRiY2NF45GZQM4jRoyQrl27ZqLF4G6B4mvUqFFSunRp6d+/vwkm7a+FLVu2iMYm81eUKg8BpjEOCgmQAAkUGAJ7Vov8Pk5kzyr/Qz6hv+cfxu/7yXL2dSK93hQpVMTm8EgCBYmAmkIKXEv+qGmvphKaOmoaren25PMk/0N6kSzL9QgFma/87ZvBaxJwE+Ba202D5yRAAiRAAr4EEo8fl10agsJKSfXCU6ZPb3vJIwmQAAl4CNDBqQcFT0gg2wkwNkG2I2WDwRKw8cECuU+DRUvdunUDqco6JJCKAOMkpELCjLxMIGaxyLyXRf6ZFXgvO94pcpnGAVOXKpS8TYCxCUI2PzBvP+Wndf2LIaM0vaVJ/6IYqat/wgLsI02DNWW3cJ2d3UTZXqYIcK2dKWxhcRPXtmExTexkASaw+8mn5NAnnxgCkfphcP0ZM9T6q3IBJpIzQ+c6O2c48ynZS4AWYNnLk62RAAmQQJ4iAGs0x3HyVJ/YGRIgARLIFQL4t3Djz0mKr62/Bd6FSLX26vawyAX3BR1MO/CHsCYJhAUBf8ovdHyKJijAGuKCQgIFiQDX2gVptjlWEiCBvELg+O+LPMov9KnKKLg+pPIrr8wP+0ECeY0AFWB5bUbYHxIgARIgARIgARIggewjkJiQFMPrt1dEdsEbm480uVrk3FtEipbxKUi+LFdHHb0h3BGFBEggDQI9kvNX+CmvrnlDNVXQhBhhCzX5q6fZFBIgARIgARIgARJIn0Aq14f60W+ZXr3Sv4mlJEACBZoAFWAFevo5eBIgARIgARIgARLIpwTiToj8NUl/bn9D5NAW70FG6hK45bVq1TVcpFJj7zJekQAJZERghFYoqQla43aaLtAEpdazmnzlUs1AcsscvRikaZs7k+ckQAIkQAIkQAIFh0BcTIwcnjJFEo7GBjXouI0bJX7HDnMPXB9WfeIJiYhghJ+gILIyCRQwAlSAFbAJ53BJgARIgARIgARIIF8TOL5fZPF7mt4VOXnQe6iFNYRRm5tEOv2fSNna3mW8IgESCJQAFGBVXJW/0/PBmva58lQDLU9pmqZpU3L+2Xocrambpp80tdZ0XFN6sjSNwiZp5DObBEiABEiABEggDAjsHPmAnPzrryz1tOojo+j6MEsEeTMJFAwCVIAVjHnmKEmABEiABEiABEggfxM4uktk7gtJVl9nfEIVFSsr0v42TeqJrWSl/M2BoyOB0BOomvwIKME6aYLl15+a1J+oLNME2avpP+Ys5Y+5enqZpt80ddB0q6ZXNVFIgARIgARIgAQKEAEnLk5OrsiaR+RSl14ipXv2LEDUOFQSIIHMEqACLLPkeB8JkAAJkAAJkAAJkEDeIHBCLb3ev0Tk6Hbv/sDK67y7Rc65USSqhHcZr0iABLJKYI82MFUTlF7/aJqgqYWm9OSMFr6vCQqwzpoyUoC11Tr+BJZhbfwVMI8ESIAESIAESCBvE4jfpR+uJSaaThYqV04q3fPvoDocWaqUlLr0Uro+DIoaK5NAwSVABVjBnXuOnARIgARIgARIgATCn4DjiMy4x1v5Va2V2qXoRrpZb5FCXO6G/yRzBHmcwFbt32pNcGlYUZP6IU1XrKtEaqXTxcRCEiABEiABEsifBOJiUj5aK3rWWVLu+uvz50A5KhIggTxBgL8I5IlpYCdIgARIgARIgARIgAQyRWD5pyJrvk65tc87ImdfJ/pJaEoez0iABEJNoHryAxICeFDH5DqbAqjLKiRAAiRAAiRAAvmMQHzMNs+IitSq5TnnCQmQAAmEgkBkKBplmyRAAiRAAiRAAiRAAiQQcgIHN4t8OzLlMW0Hi7TSL0ip/EphwjMSyB4CTbQZG/vL3SL2k09rqqxpgaZDmiBwcRhlzrz/uEgv703O+ti7iFckQAIkQAIkQAIFgYDbAqxIrZoFYcgcIwmQQC4SoAVYLsLno0mABEiABEiABEiABDJJIEFDCU29QyTuWFID5c8S6T42k43xNhIggQwIXK7lL2iaq2mjpgOaqmjqoqm+pt2abtNk5Tk9aa5pjibr5+hsPYcCDPKYJijMKCRAAiRAAiRAAgWMQHxMjGfEUbU0Zi+FBEiABEJIIDKEbbNpEiABEiCBfExgy5YtJujs4MGDAx7l+PHjzT04UkiABEggSwTmvyIS83tSExGFRPq9p/YmDCmUJaa8mQTSJjBbi97VVEFTX00wveyn6aCmJzRB2YU4YFYm6skiTedqgmLsTk0NNU3R1FnTGE0UEiCBdAhwrZ0OHBaRAAmENYG47fbbGF2+0wIsrOeSnSeBcCBAC7BwmCX2kQRIIEsEunbtKr/++qs4jpOldngzCZAACZBAHiGwY6nalTyb0pmuD4vUaJtyzTMSIIHsJvC3NnhXEI3+T+siUQoAAa61C8Akc4gkQAIkkE0E8LuM2wKMMcCyCSybIQESSJMAFWBpomEBCZAACZBAdhPo06ePdOzYUapVq5bdTbM9EiCBgkIg7rjIl2pQkqguECG1NNTQBTakUFIW/yQBEiABEiCBgkiAa+2COOscMwmEF4GEw4cl8ViSC/OI6GgpVL58eA2AvSUBEgg7AlSAhd2UscMkQAIkEL4EypQpI0gUEiABEsg0ge8fUadrCEGkElVKnbGpV7ZCXNImAeGfJEACJEACBZkA19oFefY5dhIIDwJu66+oWrVMiITw6Dl7SQIkEK4EGAMsXGeO/SaBfEpg8eLFct1110mNGjWkaNGixlLosssukylTEDIiSRA/ql+/flK/fn0pXry4lC5dWs4//3z5+OOPbRVztH7z4f4QEhER4Ulw1eKW7eqD+u677zZt4rkVKlSQnj17yh9//OGu5jnftWuX3HzzzVK5cmXTh9atW8tHH30kc+bMMc8YPXq0p649Wb9+vdx0001mbFFRUVK9enVzjXxfwf3oL9r75JNPpEOHDlKyZEmpW7eurF271pRddNFFvrd5rlu2bClFihSR3bsRkz54CWQe3K2C9fXXXy8VK1aUYsWKSbt27eSbb75xVzHnacUAw7iQTpw4ISNHjpTatWub+W/QoIE899xzabqvXLRokVxzzTVStWpVAdNauoAeOnSo7Ny5M9WzN23aJLfffrugTbw35fVLM3C644475MCBA6nqf/rpp9KtWzcpV66cGVPTpk1lzJgxcvr06VR1mUECJJCNBLZpXK/3LhZ5XV0a+qbX2ogs/TDlYVc+L1Kubso1z0iABEiABNIlEMgaj2ttrrXtS8S1tiXBIwmQQHYRiIuJ8TRVhPG/PCx4QgIkEDoC/Fw2dGzZMgmQQJAE3nvvPRk2bJgUKlTIKJ8aNmwoe/fulSVLlsi4cePk2muvNS2iTrNmzaRz585GQQblxbfffisDBw6UdevWyVNPPWXqlS1bVh5//HHBJn7r1q3m3HYJyhYry5YtEyjZDh48KN27d5e+ffvK/v37Zdq0aXLBBRfI1KlT5corr7TVTZ86deokUPqgDziHounOO+807Xgquk6gSLvkkkskNjbWjA39hyJr0qRJMn36dPnpp5+M0sh1izl96aWX5Mcff5QePXoYZcyRI0ekSZMm5vyXX36Rf/75Rxo1auR124IFC+Tvv/82SkIohoKVQOfBtgu27du3N8pDzAE4fvbZZ9KrVy+ZPXu26autm94xPj7e8IPy6oorrpDChQubOXjooYfk1KlTXvOHdj788EO57bbbjKIMykoov6BMfP/992XGjBny+++/G0Ua6kJhee6558rRo0fNXEKBijY3b94sEydONMpPKD2t3HLLLfLBBx9IzZo1zfuILvR0AABAAElEQVSAdwntPfbYY2auMCfoH4UESCCbCWxdIPJxP5H4Exk33KyXSKt/ZVyPNUiABEiABAyBQNd4XGtzrY0Xhmtt/sNBAiQQCgLxMds9zUbVrOU55wkJkAAJkAAJkED4EVjapk0bje+ZvqxevdpBKuiyatUqRxUKjlrbOKq8SYUjJibGk7dhwwbPuT1RqxxHLaJMG2rNZbPNsUuXLo6+Pl559kKVLs5ZZ53lqNWXo9ZWNtscd+zY4aiVlqNKJEeVJZ6yIUOGmPYeeOABTx5O/vrrL0etkEyZKt48ZYmJiY4qrUy+Wql58nEyefJkk9+4cWMnISHBU4b70efo6GhHFXSefHvy+eefm/L777/fZnmOgwYNMmU//PCDJy/Qk2DmQZVH5jnop1qseT3iu+++M2WqyPLK1420ycfRLXXq1PHUVyswT9GePXscdeViUlxcnCdfFZ2OWriZufOdb1UmOpGRkU7v3r099V977TXT/n//+19Pnj05duyY436m7aPGUPDKR307L/7ase0V1CP/LSuoM5+N49660HHGVNO/aKUzTq+1dZzjB7Lx4WwqPxHA+kv/37RUEyX/EuA6O8i/tMGs8bjWdhyutbnW5to2yH9kWJ0EAiSwY9QoZ3XjJiYd8Pl9JMAmWC0XCXCdnX8X1/l5ZPx8PT/PLseWLwi0/Khl2Ixj5aCVme7rW2+9JWfOnDEWNs2bN0/VDixxrKjCyp56jnB/d9ddd8nPP/9sLHTgajAQmTlzpmzcuFFGjBghqijzugUuClXJJcOHDzdtwgpMlTAC13jwr//oo4961W/VqpVxaQgLJLfAIgvWXuedd54MGDDAXWTcPb7xxhvy22+/mQSLMrfAZd8555zjzjLnqtwxLhRh3fb0008bKygUHNaAsnAXCUawOAtWgpkH27Yqr1KxgCUd3BjCzU4woooq457Q3gMXk7AkmzBhgrHua9GihSlCP2Ex9uqrrxqXkrY+jnANCYswWIHB4q5UKY0RlCxwfegrJUqU8MpCm7DuggWYb31YgGG+YLl3zz33eN3HCxIggSwQiFF3sx9fo5Zfx5MaKVlFpP9HIiUqpm40Qj14l63DuF+pyTCHBEggSAIFZZ0NLMGs8bjWFuFam2vtIP85YXUSIIEACXhZgOlvBhQSIAESCDUBKsBCTZjtkwAJBEQA7uUgcH2XkWzbts3EhYLbQJyfPHnS6xa13PK6Tu9i4cKFphhu/NSKKVVVG59rzZo1xnUeXCzieYhx5Vas2BvhMtFXAQYXi5C0YnYhHwqwP//807hUtG3hCNeC/gQKmltvvVWefPJJ+fLLL+WGG24w1eDOD/2D4gwxxIKVYObBto34Z3Bb6StwSWj5+pb5u4ZSEfG5fAXtQA4dOuQpsu0ivpu/OG1wnakWdcZFZNu2bY1CbNSoUUZJ+v333xtXl4gbB1eUbk6IQbZ8+XITy0ytvDzPc58gRhzeBwoJkEA2Ediuhjof9xWJi01qsERlkUEzRCo1zqYHsBkSIAESIIFg1nhca4v5GIprbRGutflvBwmQQHYTiNvuigHm+tA5u5/D9kiABEjAEqACzJLgkQRIIFcJwHIJUqNGjXT7sWnTJqMUgjLkwgsvNDGjoDiBAgYxuT766CNRd4jptuEuRPwwiLo5cWenOlc3eSYPMbggVaqodYIf8Zdv76lWrZqfO8TEMUOBZeCulF4MLyi5xo4dK++8845HAfbuu+8KrOFuvvlmdzMBn9s+ZDQP7gYRH8ufQEmn7h/9FfnNS68d3ACFlhU7by+88ILN8nu08wYrNVijQcmp7hnlq6++MvWhXIP137///W9zjfdKvQnIvn375IknnvDbJjNJgASykcDOP0Um9hE5fTSp0Wi1+Br0NZVf2YiYTZEACZAACAS6xuNaO+V94VpbhGvtlPeBZyRAAlkn4KhHnTO7dic1pB/sFsng95+sP5EtkAAJkIB+2EQIJEACeZtAVtwK5u2ReffOKj9gvaXxsrwLXVcvv/yyQPmBoMyDBw92lYhxTQgFWDAC5Rlk+vTpxkooo3tLly5tqmhsKr9V/eXbZ+zenbzQ87lz165dJsfWcxe7rZPc+TiHkqpHjx4ydepUY5EE5Y3GTzNuFStVquRbPaDrQOchoMZCWMmygnLRzklGj2vatKl89tlnxtUmrLxmz54tr7/+unFlCDeIt9xyi3FtiXbgdtJa7mXULstJgAQySQBuDyep28PTSR8WSPHyScqvyk0z2SBvIwESIIHgCBSUdTaoBLrG41o75R3iWluEa+2U94FnJEACWScQB289+sEppHDVqhKpH+9SSIAESCDUBDSIAoUESIAEcp9Ax44dTSdmzZqVbmc0KLcp79evX6p6cNHhT6x7PrcFka1nnztv3jyble4RyjnEhVqxYoWJL+VbGa4MfcXG8JozZ45vkbm2+RpM1G95epl33nmnKYblFxJk6NCh5piZPyyPjOYhM21n5z22n4HOm/vZsEyDW8QHH3zQKE1RNm3aNFOlZMmSghh0GiheDh486L6N5yRAAtlBABveTfpv9cf6b/j/LhE5lWT9K8XLJSm/qjTPjqewDRIgARIgAR8Cdu2U0RqPa21vcFxrB7ZHclPjWttNg+ckQAJuAvHbt3suo5JDHXgyeEICJEACISJABViIwLJZEiCB4AgMGzbM+Np/6qmnZPXq1alu3p68UKpbt64ps0ojWxFxnXxjb9myChUqmFPEM/CVXr16CQJ9v/nmm/Ltt9/6FptrxJtCbCgI3Ated9115mvIMWPGmDz7B6yKJkyYYC89R8Saaty4sYnz9cUXX3jycYLruXPnSqNGjQTxw4KViy++2NwLy7cpU6aY827dugXbjKd+oPPguSGXTu6++24pUqSI3HvvvSbOl2834tS1gls5BveH/qzzbF50dLSnifvuu09w/5AhQzzugjyFegJLO1qHuYnwnAQCIJBwRuTvL0Xe7SIyoafIhtkpNxVTS9ybpotUbZmSxzMSIAESIIFsJRDoGo9rbW/sXGtzre39RvCKBEggKwTiYlzxv2rVzEpTvJcESIAEAiZQOOCarEgCJEACISTQrFkzGTdunNxxxx3G/RwUUw0bNjTuDpcsWSKlSpWSX375RfAVJtwf9u/fX2AFBtckcPuHuE7XXnutcXHn201sXBHjq2/fvnLllVcaCy7EhBo4cKBRoiAeVPfu3eWqq66STp06SevWrQUKkRhdnP3xxx+CWAhwU2iVJM8++6z8/PPP8vzzz8uiRYvMPSiHAgrtw5ooMjLl+wK4MYSC6tJLLzXKM4wNlmTr1q0zdTE2KM7c9/iOIa1rtA1mUNpAsmL9hfsDnQfUzU0Bvw8++MAoqWCxdfnllxvlX3x8vEDRCeUX3ECuXbvWdPOTTz4xSs4uXbpIgwYNpFy5crJx40aZMWOGFC1aVIYPH+4ZDhRfS5cuNe8jlKN4N2rXrm0swjZv3mwUloix9vbbb3vu4QkJFGgCiPW3Y4lacx31j+HAepHfx2kAGt+PECJEmvYQuegxjfnVyP+9zCUBEiABEsgWAoGu8bjW9sbNtfYQ4x2Ba23v94JXJEACmSMQH0MLsMyR410kQAJZIUAFWFbo8V4SIIFsJXDbbbdJixYt5MUXXxRYeEGRVLFiRTn77LPl1ltvNc/CORRhjz76qLHYOnPmjLRq1UqgxEJsA8R48hXcu3XrVpk8ebJRWuEeKEKgAIOgTVhvIebBN998YxRsUEZVq1bNKOOeeOIJ0w/bbpUqVWTBggUyatQo0wcowWDhBQUeYkmh375xqTp06GCUabAaQ+wpKF4wtn/961/y2GOPmftt+8EeEQttxIgRRpk3aNCgYG9PVT+QeUh1Uy5k3HjjjWbuX3rpJfNO/PDDD4Z/9erV5ZprrjHKRtstcD59+rSZN1hvnTx50ihPr7/+ern//vvNe2fr4giLwCuuuMIouTBfCBxfvnx5owgbOXKk4NkUEiABJXBCXYVO6p+kAAsUSOFiIq0HiJx3l0iFswK9i/VIgARIgASySCCQNR7X2qkhc63NtXbqt4I5JEACmSEQF5PyQVyRmrUy0wTvIQESIIGgCeintxQSIIEQEViqMZ3awJIkPVmzZo0pbtq0aXrVWBYmBB555BEZO3assUiD5VBOCJSFcHsIpczEiRNz4pF8BgmkIsB/y1Ihyf8ZsbvVnWFvkX1J/x/LcMDFy4u0v03T7SIlKmZYnRVIILMEEOdRP3ZYpve3zWwbvC/PE+A6O89PUWg6yLV2aLiy1dQEuLZNzYQ5JJBVApt69ZbT6gkHUnfKZ1JcP0amhBcBrrPDa77Y2yQCtADjm0ACJEACmSCwc+dOgaWRW1auXCmvvfaasRSChVlOCVwxQhAXi0ICJEACOUIA7gw/0lhehzYnP06/qarXWSTSz9KyUJTIWReJnKNWX1ElcqR7fAgJkAAJkEB4E+BaO7znj70nARIgAV8CjuNIvFcMMFqA+TLiNQmQQGgI+PmVIjQPYqskQAIkkJ8ItGvXzsSSgstGuD1cv369zJw5UxI1Fg5iQxUrpi6+QihQtsFdIywMZ82aJVdffbXAzSKFBEiABEJOYP8GtfxS5dfRHUmPiigk0ucd9SerrhApJEACJEACJJANBLjWzgaIbIIESIAE8hCBhEOHJPHECdOjSP0NpZCGsKCQAAmQQE4QoAIsJyjzGSRAAvmOwNChQ02sr08//VRiY2NN/DG4PEQsrq5du4Z8vFB8IQYZYo3179/fxB/z99AtW7bI+PHj/RWlyhs+fLgZR6oCZpAACZCAJbB7pcjEPiLH9yXlwLqr/3iRJlfZGjySAAmQAAmQQJYJcK2dZYRsgARIgATyFIH4ba74X7VqSUQEo/LkqQliZ0ggHxOgAiwfTy6HRgIkEDoCjz/+uCDlliAYN1JGAgXYE088kVE1U472yvIrrIBYsRIJFEgCMX+ITOoncupI0vCLRItc/4m6N+xWIHFw0CRAAiRAAqEjwLV26NiyZRIgARLIDQJxMds9j41SBRiFBEiABHKKABVgOUWazyEBEiCBXCAAazT42qaQAAmQQJYIbPpV5NN/icQfT2qmaBmRAZ+L1Kbr1Sxx5c0kQAIkQAJhTYBr7bCePnaeBEggBwnEb4/xPK0IFWAeFjwhARIIPQEqwELPmE8gARIgARIgARIggfAlsHq6yJe3iiTEJY0huoLIwKki1VqF75jYcxIgARIgARIgARIgARIggRwj4G0BVjPHnssHkQAJkAAVYHwHSIAESIAESIAESIAE/BNY8qHIN/dqWbIlaalqIjepQqxSY//1mUsCJEACJEACJEACJEACJEACPgS8YoDVpAtEHzy8JAESCCEBKsBCCJdNkwAJkAAJkAAJkEBYEoDr1Hkvivw8JqX7FRokWX6VrZ2SxzMSIAESIAESIAESIAESIAESyIBA3PbtnhpRtakA88DgCQmQQMgJUAEWcsR8AAmQAAmQAAmQAAmEEYHERJHvR4kseiul09XP0ZhfX4iUqJiSxzMSIAESIAESIAESIAESIAESyIBA4unTcmbPnqRakZFSpJp6laCQAAmQQA4RoAIsh0DzMSRAAiRAAiRAAiSQ5wkkxItMu1Nk5ZSUrtbrInL9JJGipVLyeEYCJEACJEACJEACJEACJEACARCI37FTPaonuVQvUrWqRERFBXAXq5AACZBA9hCgAix7OLIVEiABEiABEiABEghvAnEnRKbcJLLhx5RxNOsl0vc9kcJFU/J4RgIkQAIkQAIkQAIkQAIkQAIBEoiP2eapWaQW3R96YPCEBEggRwhE5shT+BASIAESIAESIAESIIG8TWDGPd7Kr7Y3i1zzIZVfeXvW2DsSIAESIAESIAESIAESyNME4mIY/ytPTxA7RwL5nAAVYPl8gsN4eNdo31/XNE/TUU2wlf5YU3rSSQu/1XRQk37GLis0DddUSFNacrUWzNF0RNMxTYs0DdJEIQESIAESIIGCQ2Clxvdyuz3s/IDI1a+IRKb3v9CCg4cjJQESIAESIAESIAESIAESyByB+JgYz41FatICzAODJyRAAjlCgC4QcwQzH5IJAo/qPa00QSmFT0WaaEpP1EeTfKnplKbPNEEJ1kOT/non52vqr8lX7tYMKNkOaIJyLU4TFG/jNbXUNEIThQRIgARIgATyN4HDuiH95r6UMba6QeSiR1KueUYCJEACJEACJEACJEACJEACmSQQtx0/6yVJVK2a9pRHEiABEsgRArQAyxHMfEgmCNyr9zTSVFrTsAzuRx0NUCIJmrpqukXTSE2tNS3UBKXW9ZrcUlcvXtQERVk7TXdpwjPP1rRR0/2aztNEIQESyCUCdevWFaTckoiICOnatavX40ePHi3InzNnjle+v7peFXhBAnmVQGKiyDT93+xpGEKrlK0jcsVzSef8kwRIgARIgARIIOwI/PDDD9KpUycpV66cWbf27t3bM4YlS5bIpZdeKhUrVjRlrVtjy0whARIggdASiN+2zfMAxgDzoOAJCZBADhGgAiyHQPMxQRP4Re9YrwmuDzMSKLgqaZqsaYmrMqzBYEkG8VWiDdG8opre0LRFk5VDejI2+eIOm8ljeBOAEgMKCkr+JQCFFOYYCioKCZBAEAQWqiH0lnlJN0TosrDvuyLF8F0JhQRIgARIgAQCI8C1dmCccqLWli1bpFevXrJ582a5+eab5fHHH5frr0/6FvTo0aNy1VVXyeLFi00eyu64g1venJgXPoMECjIBx3HE2wKMLhAL8vvAsZNAbhAonBsP5TNJIJsJXJTc3nd+2p2reYgHhvhgUHid1gRJ755ZSVU8dZIveSABEihIBNasWSPR0dEFacgca0EjsEtDZf70VMqoL1Tj59odU655RgIkQAIkQAIkEFYEZs+eLadOnZKXXnpJbrhBXRq7BIqvvXv3ytNPPy2jRo1ylfCUBEiABEJHIOHAAXFOnjQPiCxVSiLLlAndw9gyCZAACfghQAWYHyjMCjsCjZN7/I+fnp/RvM2ammuqr2mNJkh69+zS8uOa4JgYv35DgZaeLE2jMKO4ZWncxmwSIIG8QKBJE/4VzgvzwD6EiEC8bkK/uk0kMT7pAdXbiHR5MEQPY7MkQAIkQAIkQAI5QWDnzp3mMdWrV0/1uPTKUlVmBgmQAAlkE4G4GI03nCxFNP4XvfNYGjySAAnkFIHInHoQn0MCISRgPx9JDmCS6kk2v6yrJNB7bD3XrTwNJQF8mXjddddJjRo1pGjRolKtWjW57LLLZMqUKZ7Hjh8/Xvr16yf169eX4sWLS+nSpeX888+Xjz/+2FMHJ3ABgsXVr7/+avJxbhNctbhluwZlvfvuu02beG6FChWkZ8+e8scff7irec537dpl3IpUrlzZ9AH+8z/66CMTGwrP8OeKb/369XLTTTeZsUVFRQk2prhGvq/gfrQD136ffPKJdOjQQUqWLCl1NSbW2rVrTdlFF1lDRt+7RVq2bClFihSR3bt3py4MICeQebDNYG46d+4sZfRLLswHnv3MM8/I6dPW4NLWTDqC9b///W9p2LChFCtWTMqXLy/t27eXp55yWaJ43+J1BR6Yo6ZNm8rWrVtl8ODB0q1bN1PniSee8Myx5YeCI0eOyAsvvCBgVrNmTQH/SpUqmTn+/fffvdq3F7jf9z2xZWkd8cPCwIEDxb4Xbdu2NfPnWz8uLk7eeOMNufLKK6VOnTpmPOBwySWXyKxZs3yrm2vMPRLc19x3333mHHNs37XY2FjDsEWLFubvRCn9uu6ss84yf5+WLk1LT+/3UcwsCARmjxbZtzZppEX0W4++GkqzUJGCMHKOkQRIgAQKNIFA1nhca4ffWht7Bqxd4dYQgrUxrpEwnzgOGjTIlME1orvMZOofJ06cMGt47GtKlChh9h7nnXeefPrpp7ZKquP3339v1rOIKYb1OdaeI0eOlMOHD6eqywwSIIGCSSDepQCLqkn3hwXzLeCoSSB3CdACLHf58+k5QyAi+TGBxBOzPQrmnrb2Jp8jfnHWT+opgRJ47733ZNiwYVKoUCGjmICCBG46EKx53Lhxcu2115qmUKdZs2ZG6QIF2QE1qf/222+N4mHdunUeRUrZsmXNJhCbPihK7IYQjdRVRYKVZcuWGSXbwYMHpXv37tK3b1/Zv3+/TJs2TS644AKZOnWq2djZ+ugTAktvUQUbFD84h6LpzjvvNO3Yeu4jFGlQbkBJAcUa+g9F1qRJk2T69Ony008/Sbt27dy3mHO4L/nxxx+lR48eZiMLRQ4sk7Cp/eWXX+Sff/6RRo0aed23YMEC+fvvv42SsGrVql5lgVwEOg9oC+5ToOzCphduVqCkgwIH+dgQo+9Q0ljBXIIxWIMdWGOzvXr1aqPIeeyxx2xVv8fnn39eHnroIcP866+/NsozG9gbCsguXbp4Ka3sPMOd4SOPPGKeidgHCAq+TQPxog30d8aMGXL55Zf7fWagmYcOHTL9wnuHHxaw8YdycMCAAbJjxw7zY4BtC+O/5557TH0EIocyDkpV9ANKMczBrbfeaqt7jlCcQYmH+6EYhvK3Xr16Ar/q6D/mHj9U4N7ChQtLjG428IPIhRdeKFDGUUjAENgwW2TR2ykwuo8Vqdgg5ZpnJEACJEAC+ZJAoGs8rrXDb62NNS/2Olj34eM/KLvsOhgKLZT99ddfZt+BGGHIg9gj1q1YY/7555/Spk0bGTJkiCQmJpr1PNb4q1atkjFjxnj9vXjyySdNu/iI6+qrrzYfgK1YsUJefPFFszdbuHChWat63cQLEiCBAkfA1wKswAHggEmABEiABEggAAJdtQ6UVx+nURcmOihP69fdv5PLm7ru35ecV8GV5z49llyelQBAS3XzoL9Lpy/6w7+DVNBFN1WO/mDvqGLCUeVNKhz6Q74nb8OGDZ5ze6LWRo5u2kwbamFks81RlSJ4P7zy7EV8fLyjXyo6+sWioxtGm22OqrRw1ErLUSWSo770PWW6ITTtPfDAA548nOim0lHLIlOmm0xPmW4eHVVamXy1UvPk42Ty5Mkmv3Hjxk5CQoKnDPejzxqDylEFnSffnnz++eem/P7777dZnqNueE3ZDz/84MkL9CSYeVBli3lOrVq1HFXeeB4BproJNmUaY8CTjznSjbjJV8WfJ9+eqELKnpqjWkY5SBCwUQs9c68qzdSF+EmTb/9QZaApc3O3ZTjqpt7Zt2+fO8uc471SJaqZH99C8Me74xY7L3ieW5L/vXD69+/vNY+bNm0y77QqAZ2NGzd6bsH75H6nbQH62bx5c3OPKgZttjmCBZ5z8cUXO8eOHfMq0x8bTJkqA73ycQF2qjBLlZ/dGfy3LLuJhqi9Q/r37IVGjvN46aQ06TrH0X+jKCSQnwhg/aX/XtL0VSHkY+E6O8i/tMGs8bjWdpxwXGvjlUhrrYqyDz/80KwXcfQVu3947rnnvIqw5taP1xy1GHNUOeYp+/nnn01b+uGVox+BefJxYp8zfPhwr/xwu+DaNtxmjP3NqwR2PPiQs7pxE5MOfjo5r3aT/QqQANfZ+Xh1nY+HVjgfj41DKzgE1ulQYToDMxjfHzvwjtfThFhgmzRZwT0VNeGehTYz+VhNjyU0bdeUUfyv5FtCd1jTxK23C91zsqPlpmttiLXgW3vrrbfkzJkzAgsgVQCkagBu66zAtYavwKXdXXfdJboZM9ZUcC0YiMycOVNUMSEjRoww1kPue+CiUJVcops30yYsc2CBAzcgcPf36KOPuqtLq1atjEvD999/3ysfVjmw9oJlDqyB3AJ3j3CF99tvv5kEqyi33H777XLOOee4s8w5rJ7QP1i3IZA1XI5ArNURGMHiLFgJZh4++OAD0zw4uC3NYHkEyzVY5YGFDbIN6yZYzcECzjcoNxpSRZrf7iKQN+rDEg9uKl999VWJjAzOgy/my5/gvbrmmmvk9ddfNxZhtWvX9lctoDxYLuqPBl59g3UW3D3CNePEiRM9VoiYL/c7bR+AfuKLW1VsGvebvu8D6oEt3NL4E7ig9BWwgsUbhQRkr7o8nNhH5Fiya9QSlUR6vi7qB4lwSIAESKBAEigo62xMbjBrPK61RcJxrZ3Zv8TwpgFX8vBGgb2PW+CuHOtbeHaAG3JrMfbaa6+ZarAqhPcDt8A9Odbr8HTxyiuvuIt4TgIkUAAJxG2P8YwaMcAoJEACJJDTBKgAy2nifF4oCPysjUKrAP9ln/o8ANoEWHHN1eQOSIR7zteEe3wVYFdoHgR1KDlEwMZhuuIKiz/tB8N1HTZicBuIc/0y0asy3M0FKnDNAYGLxNGjR5tz9x82Phdc6EEBBheLeB42iIix5CtwmeirAIOLRQjcivgT5EMBBpcjvgoPxMbyJ1Aywc0dXI98+eWXHoUSlCzoHxRn8O0frAQzD+mNC24ZoeDZvHmzUcphYxxM27bfGItaPAnmCXPuuym39QI5zp8/32zG0RbcWEKZ6Ra8N1lRgOFeKLx8BXHEoADD/LoFrmQQl2zu3LnG/SEUfW7x9x7jR4izzz7bXc2cw6UmfpCAchbvMlzb4F3EewrlMIUEJOYPkUnXiJxKjslRSN+LPu+IlFQlGIUESIAESCDfEwhmHca1thhX0uG21s7sSwxX7eoxwOwd/O2H1LuDaRr7IStYT8PNuVrKmWTz7RHrbPW+YFzVI7YyhQRIoOASiN+WogCLSuOj14JLhyMnARLICQJUgOUEZT4j1AS+0Ac8p+l6TfopuyzRBCmmaYw5048ek4/28KGe4PO2uzXhfIsmCMwkRpkzEVeAlOQcHkJGAJZLkBo1aqT7DHUpJ1AKId4S4hohDhKsZmB9A+sixIFSV3vptuEuxBePEGze0hN1OWeKEYMLUqVKFXP0/cNfvr0H8cr8ic23DNx13JZV7nycQ8k1duxYeeeddzwKsHfffdcoPBCDKjNi+5DRPKDtQMaFH1BQDwqwYNq2fQd3KNoQ6wqxwzIrsB6DpRcUSIi5hS+bYUUF6yh1fWliJQTz3vjrh7+5Rz07h5YX8vAjFBSfsHqEgg9WcRgj+mPjM/jrT+XKlf0qNvH+w/oRCtEvvvhCHnzwQTzGKGkRAwJx2hCfjVJACayfLTJloEh8slFzlL4L108Sqd+1gALhsEmABDJBAGtt63EBXhROatqqaZqmNzQlLaj0xCWd9Bzm8h01YV2+QdMHmrBeT9BEyUECga7DuNZOmZRwW2un9Dy4M7sfgiIMKS2x+yGU4x6sY/GRV3qCe6gAS48Qy0ggfxNI1I88z+jHp0Z0z1okjd9E8jcFjo4ESCC3CVABltszwOenRaC3FiBBqiYd5Dw9jk8+36/HEcnnR/V4m6YvNM3RNFnTQU09NTXWhPzPNLlls16M1ATfDUs0oRzmINdogk32S5oWasp1yYpbwVzvfBAdsK4zYPWi8bLSvPPll182Gy71LS+D1b2GW2D9AgVYMGJd402fPt0oITK6F0oKyJ49e/xW9Zdvn7F7926/92j8LJNv67krpWfFBSVVjx49jGtAfJEJpaDGTxO4VaxUKXNWHYHOA/po+4tx+XOV4zsud9vuMaZ3jnH873//M3PTrVs30bhmxqopvXv8lcG1JiyhlixZIk2bNvWqMnToUKMA88rMxIW/uUczdt4tL+QhiDis2zSWmMBCzC1QVuF99CfpvQ9wcwg3M0gau8OMCcpRuNjEj16wDqQUQAIrVLk/7Q6RxDNJg4/Wr7AH6P8Wa7QpgDA4ZBIggSwQuFfvXabpR034JauEJii2Rmu6Pfk85RNvkV6a96WmU5qwzsbavIcm+EODF4b+mnJdCso6G6Dd6zCutVNevfTWVuG21k4ZVXBndo167733CvZagQju0TjHonFmA6nOOiRAAgWUQLzLOw+UXxFqOUohARIggZwmEJnTD+TzSCBAAq213qDkZM0+6rvyoKhyC74+7aJprqZ+mv5PE3w13Kfpek2OJl/B16c9Na3SdJMmbN6hoRisySrX9JSSEwQ6dsRvKCKzZs1K93H4YR/Srx+m2Vt+/fVX74zkK1jHQODaw1fsc+fNm+db5PcaPxggztKKFSskNjY2VR24MvQVG8MLlkb+xOZrMFF/xenm3XnnnaYcll9IECh0MiuWR0bzgPbTGxfmafv27cYloP3BJZi23f2HhdR3331nvjJFXDPrttJdJ705Rj30B24CfZVf2Lj7mzN324Gew9oNVoi+YufX8kI5+lO+fPlUyi+UpfUeoyxQadCggdxyyy2mLVh+paVQC7Q91gtTAr+/LfLVrSnKrzIaZ2/ID1R+hel0stskkMsESuvzsVgboukhTVhrn6tprKbqmh7WZAV139OEhVdXTbdoGqkJ6/uFmrCOv14TJQcJBLoO41rbe1LCaa3t3fPAr+BdA14IAt0PoWW8T/j4Di69KSRAAiSQFoG4mBhPEeN/eVDwhARIIIcJRObw8/g4EgiUwGitGJFOqqtlvjJfM67UBDeGxTW11ISvTFNrPTQzWWboEYqzUprwJSs28sGZEOkNlKwTGDZsmPG1/9RTT8nq1atTNQhlCqRu3brmaJUK5kL/QGBm39hbtsy63YCCwlcQKwnWS2+++aZ8++23vsXmGgqXEyeSXIfBiggWVnBnBysetyxfvlwmTJjgzjLn559/vjRu3NgoWuCezi24RgwoxMxCzKZgBcoh3AvLtylTpphzWEplVgKdB7Q/ZMgQ8xhwgI9/K1A0jhgxwnwVCiWMFVirYf6+/vprE6vK5tujv5hXtgzuLn/88Ufj/g9uL32VROnNMdrAcxHPbefOnbZJcRzHuG3x9755KgVxgnHD9SCUalYQAw1BwhGz7cYbb7TZpj/4YhaKVLfA2g3vcrCC5/j7AQI/TMCVIpS2lDAkgHfpH1VYzVKXlt+o8UUwaYp+1/FdkitMM/JKall7i7ZVsUEYgmCXSYAE8gCBU2n0YUpyfkNXORRclTRN1gRPC1bQxqPJF8NsJo85QyDQNR7WTBCutQ0G46o6XNbaST0O/k+42B4wYIDxlIC9GFwb+srGjRtNbF+bD2sxyG233ea1vrblx48f98T/tXk8kgAJFDwCXvG/aurHeBQSIAESyAUChXPhmXwkCZAACaQiAOuccePGyR133GEsi6CYatiwoXF3CLd1pUqVMu7i8BUm3B/279/fWIHBNQnc/sFC6Nprr5XPPoOXHW+Bkggxvvr27StXXnmlUQbUqVNHBg4caII3f/XVVya+1FVXXSWdOnWS1q1bS3R0tMTo10rwg49YCHDnhzzIs88+a+ItPf/887Jo0SJzD8qhgEL706ZNM19R2l7AtQoUVIg9BeUZxgZLsnXr1pm6GBsUZ/jyMlhB22B2330wdsya9RfuD3QeUBesHnjgAQGHFi1amBhbiKsF6zHMCRR6I0fig+8kgfIQ8wAF1g033GBil+Hr0VPqFxwuHH/66Se/G257f4cOHQx3cLSccQ6BghHvwuTJk42rw9q1axtlGeYYc41Nun23YD2IoN3z5883ylYo5mbMgC48a3L22Web96Ft27ZmjFCS4n2E+0EwcruJHD58uFF0gRHeW7iRwXsOazTEKvNVlGbUMyhf+/TpI3g25qJ69epGKQnLLwQutzHBMmqH5XmEwJnTIivVdeGC10X2rc16p2q2F7lB/22MLp/1ttgCCZAACXgT6JF86f6i46LkvO+8q5qrufonvirqpKmoJv0Hj5ITBAJd43Gt7T0b4bTW9u55cFdwmY2Pxf7zn/8Yt9lYoyK+LT4ewzodeyK4m69Xr55pGPsr7Ikefvhhs2fD2hxliPm1detW87Ea2sAejUICJFBwCcRtd1uAUQFWcN8EjpwESIAESCC/EliqLu3UyCR9UesTB4mSRGDBggWOKqocjf3kqJLCqVatmtO9e3dHFSceRKq4cNTKyVHXeo66d3PUwsqZOnWqo/GU4OrSefzxxz11caJfMTq6OXN0U+aoJY6p06VLF686Gr/JUSWB07x5c0etZRxV5DjqRs5RZYmjsZMcVSJ41VeLNOemm25yKlas6BQrVsxp1aqVM378eNNP9EHjMHnVx8XatWsdtQJyqlatavqBo35tafJ9K2MMaAdjykjUkshR5ZlTtGhRZ//+/RlVD6g8kHmwDelm2MwB5gJ90B9YHLUKczTGla3iddRNsaNfITv6hbGZY3UF6KjrFXOPu6IqrhwkX1m5cqWjG3LzrG+++cZTvHjxYueiiy5yNE6boz9WpOKnilMzT6rIdNRizOndu7ejFljmffHHGnm+70la82LrqhWbmVO8v2Chbg+dSZMmefroPlGlm6NKPfMOqwLMUWWeo5ZtDvqJ9nB0S1o8UEeVteYdV6WkYaPKRkcVgs7ll1/uqGWju5mQnfPfsmxAe/Kw48zTfztebOw4j5fOnjSxn+OcPpYNnWMTJBA+BLD+0n9Hl2qiZD8BuAkfrQleFuZpAuvlmmDxZeUPPUF+W5vhc/w7ubypT34wl1xnZ/KvZCBrPK61veGG01o7rbUqRpTWGtOOVr0GOK+//rpz3nnnmfU01pO1atUy62vsbfztM9RtoqMfJpo9G/Zu2BthX6QfnzmqNLNNh+WRa9uwnDZ2Oo8R2HbHMGd14yYmHZk1K4/1jt3JDAGus4NZrrJuXiEQkVc6wn6QQD4kgI15m6VL0//9BV/UQXxjE+VDHgViSI888oiMHTvWfO2oirscGTNc1MDtIVzsqbIuR57Jh5CALwH+W+ZLxOc6Ub3xbvxF5EjKV5BeNQ5s0J/rPxKJi/XKlqiSGnBvYOZcF5atK3JWN5HIQt5t8ooEMkng0O7jsmvjEXESodsIXirUKClV65cJ/sYg74A17DIVvS0tBUyQLbK6iwDi5VZxXcO8Y7CmPa68f/QcLhGR9B+3VDJfc2ABhoSYYOlJWgvpJrrMjuY6Oz10+bOMa+38Oa95cVRc2+bFWWGfwolAonp62dj9cjmzJ2mJUFfDPxRv0TychsC++iHAdbYfKMzK8wToAjHPTxE7SAIkkBcJwB0I3My5RS2TTLwntWgStRxyF4X0HO71IHfffXdIn8PGSYAEMkngtCq1Jg8Q2fxr4A2U1N+XO9wh0k5j7RUvG/h9rEkC2UxAvwyVXRsOy58/bJMtKw9kqfVWF9XKEQVYljrJmzMiUDW5ApRgUGA9q+lPTVdrgtIxELEfYWZOkxrIE1gn7AlwrR32U8gBkAAJFHAC+zXOulV+RZYuLUUbnFXAiXD4JEACuUWACrDcIs/nkgAJhDWBdu3aibpINPGWEPcKPvNnzpwpiYmJ8vbbb4u6RQzp+KBsU/d/gi+fEXPr6quvFsTIopAACeQxAsf3i0y6RmQnfh8OQCo20p+U/y1y9rUihREeh0ICuUMgUa28Nv+1T5ap4mvvlqO50wk+NS8TwOfcUzVB6fWPpgmaWmiCHEk6SFrmfqWTy2295Eu/h7Ss+GAZ1sbvHczMFwS41s4X08hBkAAJFFACJ1etkgMffOgZfeUR90tkiH8j8TyMJyRAAiTgQ4AKMB8gvCQBEiCBQAgMHTpUpk2bZoJBx8bGisYjE7g8HDFihHTt2jWQJrJUB4qvUaNGica7EvW7L+PGjfPb3pYtW0Rjk/kt880cPny4GYdvPq9JgAQySeDwNpGJfUUOrE9poFlvkWJ+fhMuFCXS4GJ1GKauUyMjU+rzjARCQABWXYd2nZD40+qa04/s23ZU/podI0f2nUxVWrt5BSlZLnPK2Sr1rd4jVbPMCF8CW7XrqzW11lRRk2r9ZZ2mdppUo58qFhv2n/U0ndG0SROFBPwS4FrbLxZmkgAJkECeJ6AB1GXXo4+JJCStM6P1Q92y+psFhQRIgARyi4B1P5Fbz+dzSSA/E2AMsPw8u2EyNhsfLJDubt68WerWrRtIVdYhgVQEGCfBB8neNUnKr9idSQURqtS66mX9Sfhmn4q8JIGcI5BwJlHW/7FH/vxxmxzceTzgB0cWjpAmHapK60trS7mqJQK+L7cqMjZBjpOHNVhlTeU1HdI0RNP/NE3QNEiTWy7Si580zdWUFX/RXGe7qfI81whwrZ1r6EP+YK5tQ46YD8inBPa/867se+UVM7qIokWl/tfTJapOnXw62oI3LK6zC96c54cR0wIsP8wix0ACJEACaRCANRq+9KeQAAnkIIGYxer2UL9yPHU46aGw7ur3vkizXjnYCT6KBFIInD55RlbN2yErft4uxw+fTinI4KxodGFp0bmGtOxWU0qUyZzVVwaPYHF4EGii3cQ/aLt9uhup109pgvJrgSYovyBfaHpO0/WaXte0RBME/qHHmDORt5KPPJBAWBPgWjusp4+dJwESyGYCpzdtEsT+slLp3/+m8svC4JEESCDXCFABlmvo+WASIAESIAESIIF8R2D9bJEpA0XiTyQNLaqk/gT8iUj9rBg65DtKHFAOETh26LQqvWKM8ivuVJIbGvvowkULSfmq0fbS61g4qpDUb11Jmp5fTaKKZX274Kjl2ck1B6V4iwoSEUEHFF6ww+Picu3mC5pgtbVR0wFNVTThH7b6mqAYu02TFQSNwzUUYXM0TdZ0UFNPTY01If8zTRQSIAESIAESIIF8QsDReOhwfejExZkRFWvRQsoPuimfjI7DIAESCGcCWd/RhvPo2XcSIAESIAESIAESyA4CseoBbMFrIoveFklEaBuVaA2Hc6P+zlv9nKRr/kkCOUQg9uApWTpri6xZsEsSE7ytgIuXjpJWF9WU5hfWkGIlioS0R4lqeXZs0S45Nn+nJMbGScVbW0ixBuVC+kw2HhICqtmXdzWdr6mVprKa4EPzH00TNek/fkbBpQePTNMzKMge0dRPE6y/Nmi6TxPqe7+YmkEhARIgARIgARIIXwKHPv1UTi5bljSAwoWl2tNjJEKPFBIgARLIbQL8lyi3Z4DPJwESIAESIAESCF8CR3aIzH9VZNlHImdOpYyjTG2RgVNFKjZIyeMZCYSYACy+ln63RVZD4XTGW79Qtkq0nKMxvBp1qCKFixQKaU/OHDktx37bIccX7xbndIrlWezcHVSAhZR8yBr/W1u+KxOtz9d7rszEfbyFBEiABEiABEggjAjE79wp+17SeMfJUuG2W6VYYxh9U0iABEgg9wlQAZb7c8AekAAJkAAJkAAJhBuBw9tEfntF5M+PRRKS3Hx4hlCjrch1ml+6uieLJyQQSgLHVeG07Lut6upwpySou0G3VK1fRtp0ry11W1aUiMjQuh+M331cYn/dLieW71NLSG8FXGSpKCl2VhkTl5JuEN0zxHMSIAESIAESIAESyPsEEg4flvi9e/12dO8LL0riiSQX8FH160vFYcP81mMmCZAACeQGASrAcoM6n0kCJEACJEACJBCeBBLUveGPj4ksVm9g1tWhHQlcHXZ+QCPcXCEa6Mjm8kgCWSLgOI6sUsup1fN3yZm4FGsqd6NHD5yShHhfxVdpad+jvtRsUi6kcbfQv7jNR1XxFSOn1h1yd8ucF65cXEp1rinRrSurG5zIVOXMIAESIAESIAESIAESyNsEjs2dKzF33a1xjuPT76jugaqNGSORUVHp12MpCZAACeQgASrAchA2H0UCJEACJEACJBDGBOJPinw+WKPefOc9iJrtNdKNKr4aXELFlzcZXmWRgKNWVPOmrJeVc7YH3FLluqWlQ496UqtZ+ZArvk6tPSix2re4rUdT9S+qXmmj+CrWWPsRYsuzVA9nBgmQAAmQAAmQAAmQQLYQSDhyRHY+oiE9M1J+6dPK3XijRLdh/ONsAc9GSIAEso0AFWDZhpINkQAJkAAJkAAJ5FsCJw+LfHq9yLaFKUOs3Umk64Mi9bpQ8ZVChWfZRACuDH8av1rWL/Hvasb3MZVql1KLr3pSp0WF0Cq+Ehw5uXKfKr5iJH53kqsbT1/U8LF48wpSUi2+itYu7cnmCQmQAAmQAAmQAAmQQHgS2PP885Kwb7/pfGR0tBSp4d/Ne7HmLaTyvcPDc5DsNQmQQL4mQAVYvp5eDo4ESIAESIAESCDLBGJ3i3zcT2TP3ylNXXCvyMWPU/GVQoRn2Ugg7tQZ+e7dvyVm9UFPqw3aVZZ2V9aVCP3PVwpHRUqpCsVCq/iKT5DjS/dK7NztknDwlHcXCkVIiTZVpGSXmlKkYnHvMl6RAAmQAAmQAAmQAAmEJYHjCxfKkS+/8vS9+vPPSalL1OsFhQRIgATCiAAVYGE0WewqCZAACZAACZBADhM4uElkYh+RQ1tSHnzZ0yKd1Ac+hQRCQODUsXj55s3lskfjallp0aWGXHhdI4nMBVeCCcfj5fjvu+TYgp2SqOduiSgSKSU6VJOSF9aQwmWKuot4TgIkQAIkQAIkQAIkEMYEEk+ckF2P/cczglLdu1P55aHBExIggXAiwEjU4TRb7CsJkAAJ5AMCP/zwg3Tq1EnKlStnrBV69+7tGdWSJUvk0ksvlYoVK5qy1q1be8p4QgI5TmDXCpH/dU9RfkUUEun9NpVfOT4RBeeBsWpZ9dWLS72UX+deXU86X5/zyq8z2pdD0zfI7mcXy9Eft3opvyKKF5ZSF9eWqg+1l7JX16fyq+C8ohwpCZBALhAYP368WRfjSCEBEiCBnCKw79XXJH77dvO4yDJlpOqjGgeMQgIkQAJhSIAWYGE4aewyCZBAcAS6du0qv/76qziOE9yNrJ3tBLZs2SK9evWSsmXLys033yylS5eWJk2amOccPXpUrrrqKjl16pQMHDjQKMGqVq2a7X1ggwWMwNFdIutmisQdD27gZ+JEFrwmcjrZCqdwMZH+40UaXxFcO6xNAgES2L/9mMxUy69jh04n3aGeDjur1VfLrjUDbCF7qsXtOCaxv8ZonC+N9eDzv81CauVV8oIaUqJ9FYksym1E9hBnKyQQ/gS41g7/OeQISIAESMBN4OTy5XJwwgRPVpWHHpLClSp5rnlCAiRAAuFEgDvXcJot9pUESIAEwpzA7NmzjYLrpZdekhtuuMFrNIsXL5a9e/fK008/LaNGjfIq4wUJBE1g7xpVYL0usmKKSKK327ag2ypaRuSGz0TqnBf0rbyBBDIisHfrUVn23VbZ+Nc+j8IpUmNqXXJzM2nYrkpGt2dLOT4Qidt8RI7+EiOn1x9O1WaRqiWklMb3Kn62WucWogOJVICYQQIkQAIhJNCnTx/p2LGjVKtWLYRPYdMkQAIkkETAiYuTXY8+quvSpC+hSpx/vpTp3Yt4SIAESCBsCVABFrZTx46TAAmQQPgR2Llzp+l09erVU3U+vbJUlZlBAv4IYJO2db7IfLXcWv+9vxrB55VUK8QbvxSp2iL4e3kHCaRBAAqnHf8cVsXXFolZc8irVuGiheSKoS2kdrMKXvmhuEA/Tq05KLFzYiRuW2yqRxRtUFZKda4pRRuWNe63UlVgBgmQAAmQQMgJlFHXY0gUEiABEsgJAvvffU8/iNpgHhURHS1Vn3iC68CcAM9nkAAJhIwAP+EMGVo2TAIkkBkCsAK67rrrpEaNGlK0aFHzpeNll10mU6aoFUeywP99v379pH79+lK8eHHjRu98/Srp448/tlXMEe72IiIijPtDZODcJrhqcct29W199913mzbx3AoVKkjPnj3ljz/+cFfznO/atcu48KtcubLpA2JVffTRRzJnzhzzjNGjR3vq2pP169fLTTfdZMYWFRUlUALhGvm+gvvRV7T3ySefSIcOHaRkyZJSt25dWbt2rSm76KKLfG/zXLds2VKKFCkiu3fv9uQFcxLIPNj2MDedO3c2G3PMB579zDPPyOnTyW68tCLGgfE8/vjj5rZu3bqZa+RhPnEcNGiQKYNrRFzbMvucExqEF+2CdYkSJQyP8847Tz799FNbJdXx+++/lyuvvNK4U8S8nnXWWTJy5Eg5fDi1hUOqm5kRPgQSE0RWTRN5T/9OjL8qtfKrVkeN2/V/wadLRosMnUvlV/i8CXm+p06iI5uX75Mvn18q01/5M5Xyq07LCtJvZNuglF+Jp8/IqY2H5dT6Q0Gl40t2y95Xl8mBCau9lV/qehGWXpX/7xypdGtLKdYoKV5jnofLDpIACQREIJA1HtfaoVtr2/3J4MGDzZoesXDLly9v1rYXXHCBIFaur9i1Mo5WcL9dL/s71tU9A8Q+z18dm+du95dffpHbb79dmjVrZvZYWNu3aNFCntAfwOGmnEICJJC/CZz65x/Z/847nkFWHj5comrW8FzzhARIgATCkQAtwMJx1thnEsinBN577z0ZNmyYFCpUyCifGjZsaFziLVmyRMaNGyfXXnutGTnqYFMGpQtcgRw4cEC+/fZbEzdq3bp18tRTT5l6iDMFhQs2dVu3bvUoX1BoN4U4X7ZsmUDJdvDgQenevbv07dtX9u/fL9OmTRNsRKdOnWqUKKgLgZu+Tp06mQ0l+oBzKJruvPNO005SLe8/oUi75JJLJDY21owN/Ycia9KkSTJ9+nT56aefpF27dt436RVcBf7444/So0cPgdLoyJEjJmYWzrFB/UcXqI0aNfK6b8GCBfL3338bJWFmYmgFOg94KFwVQilVsWJF49IQSrpZs2aZfCif0Hco4sAbcwFFGOKxQdll5wAKLZT99ddfhgVihCEPYo9QWEHh9+eff0qbNm1kyJAhkpiYKHgGXCmuWrVKxowZY+6xfzz55JOmXfyocPXVVwuUlStWrJAXX3zRvC8LFy40G3tbn8cwJHBGlazLJ6vF16siBzf6DEB/xW+iyrDz7xGp1d6njJckkLMEEuITZd3i3fLXj9vk0O4TXg+P0Fe1gbo6bNO9jlSsWdKrLL2LM0dOy7H5O+T4ot3inFYlcFZF3S6WaFvFWHwVrlg8q63xfhIggTxIINA1HtfaTcy6O1RrbbwamzdvFnzIBeXS0KFDBR/XffbZZ3LFFVeYj9/wQWB6AsWZXUu7661cuVK++uoriVarDYjdD7nr2PM33njD7KNsXeQ/99xzZo+C/Y2NzTt//nzBx3lYx8OdOfZqFBIggfxHwElIkF2PPSYSn+Q+vnirVlJugHfYgvw3ao6IBEiABEiABEggKwSW6g/16l0ofVm9erWDVNBFFRhO4cKFnXLlyjmqvEmFIyYmxpO3YcMGz7k9UWsjRxUkpg215rLZ5tilSxf1i6YerP1IfHy8o1ZBjloHObqp86qxY8cOR620HFUiOfrFo6dMlS+mvQceeMCThxNV4Dhq2WXKVKHjKVNFjdOkSROTr1ZqnnycTJ482eQ3btxY15sJnjLcjz7rhtRRBZ0n3558/vnnpvz++++3WZ6jKpdMmX5B6skL9CSYeVBFm3lOrVq1HN20ex4BpqpwMmUaz8uTjxM7Lv1BwSsfFx9++KG5B0dfsWPSTblX0cmTJx1VWjr6BaujyjFP2c8//2za0h8WnEOHDnnycWKfM3z4cK98XmSNQI7+W3Yq1nHmv+44LzbRl6q0d3qykuN8/W/H2bc+awPi3SSQDQROHY9zln63xfnggXnOG0N/8krj7vrZ+fnjNc6hPceDelLcrmPOgc/WOjGj5jkxD87Nctr+2G/OoW82OmcOp/x/LqgO5cHKWH/p/0OXZmURx3vzPAGus4P8uxfMGo9rbccJ1VpbFV9mjap/w5wRI0Z4zaJ+MGf2Mqq0cvSjN0+ZXbv6WyN7KukJ9kvqRcMpVqyYox96uYtSnf/nP/8x/dAP/7z2IBs3bnSwd/GVRx991NTH3qWgSI6ubQsKVI4zTxPY//7/nNWNm5i0pkVL59R67qfy9ITlUue4zs7za2R20A8BWoD5gcIsEshLBN684+e81J10+3LX22m75Ev3Ri1866235MyZM/KYfnHUvHnzVNVr1qzpyYMbO1+BS8G77rpLVPFhrKngWjAQmTlzpuhGT3QDKqoo87oFLgpVJDgWuAAAQABJREFUySWqKDFtwpVenAaEhcs9+OHXjaBX/Vb6hRSe+/7773vlwyIL1l74ynPAgAFeZfi6E19f/vbbbybBoswtcEFyzjnnuLPMOb76RP9g3aZKJuMuEgWwlIJLQjCCxVmwEsw8fPDBB6Z5cHBbmqki01iuwSoPLGAllhWBhR/cW8JCDvPhFt3gmy9VYQkGV5HWYuy11zQGlAq+dMaXr26By5hXX33VWN+98sor7iKe53UCJw6KLFKXHIs1nfSOmyTFNDbGubeJdBgqUrJyXh8J+xcmBOCy8NTxpK9gg+ny6RNn5O95O2T1vJ0S72OdVaRYIWl+YQ1pfXEtKVG2aEDN6v5WTm86IsfmbpdT63zefW2hcIViUqhcsYDa8lSKjJCidUpLiY7VpFCJIp5snpBAQSJQUNbZmNNg1nhca4uEaq1t/35hL6FKKHtpjljrYq8At+rwQGHdg3tVSuMCXibg8QAxdbEX6NhR3T+nIRMmTBB4Smjfvr1ZY0dGRnpqwsW8P8F+CN4WsObOyDrN3/3MIwESyNsETm/aJPt0j2ylwrA7pGiDBvaSRxIgARIIawJUgIX19LHzJJB/CPz+++9mMHD7kZFs27bNKD3gNhDnagXkdYtabnldp3cBN3gQuEiEaw9fsfG51qxZY9wgwsUinocNaqlSpXyrG5eJvgowuFiEpBWzC/lQgMG9n68CDBtTfwIl06233mo2r19++aVxA4h6EydONP2D4gx+/YOVYOYhvXHBLSOUlnDvAqWcrxIqmH7BfaRax5nx+JsjtTgzzWGOrGBe4XpRv941yebbIxSZ+/btM25fEO+NkscJHNoq8vs49Vc6UV1yHPfubMkqIufdJdL2ZpFipb3LeEUCmSRw8licrJyzQ/7+dbucjA1eAebvsSXKRMnZF9WS5p01xmXxwJbgToIjJ1ftl1hVfMVvP5aq2ai6pY3LwmJNykuEKrQoJEACJJAWgWDWeFxr64cFIVpr2/mBS29/ewnEKYYCDPuCQBVgWCfDVfzy5cvl+eefl2uuucY+JtURbh2xh6hXr57MmDHDxDJ2Vzp+/Lj5UAwKOLhah2INH2FYCWafZe/hkQRIIG8TgOvDnQ8/LI7ukSFFmzWVirfph4UUEiABEsgnBALbfeeTwXIYJEACeZcAlCQQdduRbic36ZdJUAqpWzu58MILTcwtfEEJX/QI8owNo7pDTLcNdyGsiyBQlKQnx44l/fCIGFyQKlX0R3c/4i/f3oN4Zf7E5lsG7jpuyyp3Ps6h5Bo7dqy8o0FqEQcL8u677wqs4W6+WZUBmRDbh4zmAU0HMi78gIJ6WVGA2TmCIgwpLbFzhHLcA4tCBOxOT3APFWDpEcrlsl3LNb6XWvOtmqqOgnxiHJWtkxTfq/UAkSJBWr7k8rD4+LxL4Mi+k7J89jZZs2CXnNG4Xdkh5auXkNaX1JZG7atIocIpX9mn13ZiXIKcWLJHYn/bIQkHT3lXVT1X8WYVpGSXmlK0NpW+3nB4RQIkkBaBQNd4XGunEAzFWtu27m/PgDK79rfrbFs/vSO8YHz33XcmltjIkSPTrIqPxRDruESJEgIvGIiP6xZ8VIYP8xYvXmxik8HSq1KlSuajMtTDujqYfZa7bZ6TAAnkXQIHP/xQTi1fkdRB/Yi0usb4jtAjhQRIgATyCwEqwPLLTHIc+ZZAVtwKhhMUqyDBV4UaLyvNrr/88stGuaE+8AWu7NwC14RQgAUjUJ5Bpk+fLj179szw1tKlk35s3LNnj9+6/vLtM3bv3u33HgS9hth67krpWXFBSdWjRw/jIgUbWigFNX6acUuCzWpmJNB5QNu2vxiXP1c56Y0rmL7Z59x7772C+Q9EcI/GL5CDBw8GUp118hIBfGW88WdVfKkLjs2/pu5ZZXWResG9Is37iGoTUpczhwQyQWDPlqPy5w/bZNOfe/VLd+8GihQtJIWKBKa4snfCALdCjZLSSt0c1mleIWDrrAS1PDu2cJccX7hTEtWNopcUjpASbatIyQtrSpGKxb2KeEECJJA5AgVlnQ06ga7xuNZOeZdCsda2rfvbM6DM7hfs+tfWT+sIiy98DHf55ZfLm2++mVY12bt3r1x11VUCCy+4MWzatGmqutgPQfkFy7Px48d7lWNdn9GHZV438IIESCAsCJzWcBD7Xnvd09dKdw6TYo0be655QgIkQAL5gQB/OcoPs8gxkEA+IAA/9UuWLJFZs2alqwDToNxmtP369Us16l9/9fNjudaCdRgE7kHsucnQP6x//Hnz5gWkAINyrnjx4rJixQrjEsTXdQlcGfqKjeE1Z84c3yJzbfPhCiVYufPOO40CDJZfUIBBhg4dGmwznvqBzgNuwLjgBhH991WAYZ62b99u3KvYH1w8DwnyBBZ/iE2AOQpUMA582aoB3/3GlAu0HdYLAQHE8fpKXWrsWeW/8QR1vXEiyTLTq0K9ziKd7hFpcLGoP0yvIl4UDAKnjsXL3+oK8J/FeyTupI9yKAsIoPA6cTTJ5Yu7mYq1Sso5l9WWBm0qS2Sh4BRg7nYCOYd7qdg52+XoT9tEznhbnkVGFzZxukp2qi6FSkYF0hzrkAAJkEAqAoGu8bjW9kaX3Wtt2zrW0HAv6LuXsPsCu3+w9f0dv/jiC3nooYcEcYgR98t3n2Pvgft2fDQH1+T4WLBbt262yOuYmbn3aoAXJEACYUXAUY8pOx8e5XF9WKxZM6mgLlIpJEACJJDfCIR2N5/faHE8JEACISMwbNgw42v/qaeektWrV6d6DpQpkLp165qj3RyaC/0DXzL6xt6yZdbFHdzx+UqvXr2M8gZfTH777be+xeYa8aROnDhhzuFeEO5A4JYEgaDdAr/7CCrtK+eff7401q+ooBzDRtUtuJ47d64gZtYFF1zgLgro/OKLLzb3YjOLjS/aSWtTG0iDgc4D2hoyZIhpEhwQT8sKFI0jRowwFli33HKLzc70Ee5ZEBAcClK8H3Bt6Csb9cs1bOqtwFoMcpv6LkcwcF/B1682FoZvGa9DTOCnJ0U2zBaJVctHf8mt/IqIFGmhyu7b54gMmiHS8BIqv0I8PXmx+aP7T8rcz/6Rj0bNl0Vfb5ZDu0/I8SNx2ZZ8lV+1mpWXnve0lmtHnSuNzq0aeuVXoiNHZmySo99v8VJ+FSpXVMr2qC9VH2ovZS6rS+VXXnw52ScSCCMCga7xuNb2ntTsXmvb1rGXePJJXRO5BGvdSZMmGS8Lffr8P3vnAR9FtTXwk7Kpmx4IaSQQeu9VIKCIioCACBYQbGDnWR8qIgqIPp8+EbF+iIKKBUUFVJCqIB2kdxJSgJCQkN529zvnbma2Jtkku5st5/x+h71z584t/1k2M3PmnIOe7jUIXcdOnjwZYmJiYM2aNSaGNOlQiohwzz33CM+uOXPmwJQpU6RdJp/VnXsKi/n888+btOcKJsAEnJtAzlIMfYgv9grBkIfRHPrQuU8oz54JMIFqCXhXu4d3MAEmwATsSKADvm20ZMkSmDFjhvAsIsNU69atRbhDuhmktyMpaTO9hUnhDydMmADkBUahSSjsH8W9p+TP33zzjcms6caVcnxRzPtbbrlFeHAlJCSIm0YFXuj98MMPMGLECBEWZMCAAdCtWzcICAiAtLQ0kXOKbvoo7AfVkSxcuBA2bdokkkzv2rUL6BjaTwYo6n/16tXCY0maCIUxJAPV8OHDhfGM1kaeZCdPnhRtaW1kOCMvp7oK9U3MnnrqKXFoQ7y/qANLzwO1pXU/99xzgkOnTp1Ewm3KKUBefHROyKBXUx4C6sNSWbx4MZw+fRpefvllWL58ueibcieQcYvCP1JuMAqBSQm9Seic03mahcl86XtE54X2Uc6v1NRUIG9Bmh99b1jsSCDnLMD+L2ofUIH/17pPBuj/CEBYYu3tuYVLEshKxbCEGy7A2X2mYQmtvWBPTw9o1bspdB/eHCLjgqzdfbX9adD4lbvqNBTv04XVVUQHQlByPPh3igQPL/Z2rBYe72ACTKBOBCy9xuNrbUOs1r7WlnofPHiweHmP7iXoZTm6l6D7GDJYUUhDKey61N74k15EKy0thb59+5p9CZAiMMycOVO8fEf3OtILga+88opxV3DbbbeJ+x/yEmvVqpUIOX748GFxT0YvEJKBjcInmnuZ0KQzrmACTMApCJThvXX2e3qhDx99BEMftnGKufMkmQATYAJMgAkwAcchsA9D2mFUo5oFvZ00pCxaAjt27NCgoUqDOaw0aJzSREdHa9A4pUEDloxo+/btGvRy0uCNnUapVGrwplHz448/atBARplbNPh2o9yWCugxpEFDiAYNIBpvb2/RZsiQIQZtMA6/Bt9s1HTs2FGDIQ41aMjR4A2gBo1sGjS4aDAptEF79EjT4BuUmsjISI2fn58GQ49oMFa+mCfN4Z133jFoTxsnTpzQ4BuYGkxuLeZBn+jZJOqNG9MaqB9aU22Cea40aDzT+Pr6arKzs2trbtF+S86D1BEansQ5oHNBc8AHLBr0CtNguBWpifxZ07rQsCnWTJ/mBJNua9577z1N//79NfhQQIPeeJr4+HgNJusWvM2tHcMmatBYKr5H9H2i80XnCj3ENGg0MzcM19WTgEW/Zd9N02jmBGt16S0azbUM81pRWs9Z8GHOQqCirFJzeGu6Zu2SfzS/vHfQRL9buEezePpGE/361V2aEzsvagqulqCWWk3LSyvtjk5dodJkrzimSXt+m6y0TfUsDSNA11/4N3QfKovrEuDr7Hr+N7HkGo+vtQ3hWvNaGyMWiOtdzLMl7gExB7G4p6H7D3y5TIMvZxkOjlvmrpHxZT7RD/4XN/tJ+0mkY6trR/XURhI0cmnuuusuDXqWiXscuq5/4403xL0QtTW+h5KOc8VPi65tXXHhvCaXJ6DGZxvnxt+uOda2ndBz48bj9afh8w6Xh8ALrDcBvs7Gv4YsTkeAXyt1ulPGE3YiAnRj3mPfvpqfv5D3Com5RMROtFaeahWBF198ERYsWCA8i8irzB5C4SAp7CGFNyHvKBYm0BgEav0tu4jhNT4apJva/RgGMb63bptLbkGgpLAcjmzNgEOb04Fyelkqce3CRD6u+PbhmALO+S9fNRUqyFlxHEpPanM3EoeAnlEQNr41eKA3GkvDCPTs2ZNyVO7HXno2rCc+2oEJ8HW2A58cW07N2a+1U1JSRFQCNIABvjxnS1TcdwMJ1Hpt28D++XAmYGsCJZiioRx/c4yl+OBByPt6paj2wIg4LX5YBb4YNYXFcQngy3qQduwqVJarapxk6z4Yvt3G9xJ8nV3jKeCdDkqAQyA66InhaTEBJuDYBCj0HsXc1xcKFbJo0SIIDw8HfDtSf5dNy2+++abo/7HHHrPpONw5E2gQgU2v6Q5vO5KNXzoablG6dqUE/vnjAhzfcREqK9QWrZkMQa16asMSNmluv7CEFk2uAY3UZZWQ8/kxKDt3Te5FOSAGQm5tycYvmQgXmAATcHcCfK3t7t8AXj8TYAINIZCPof4zZmrzYtfUTyQ+Q2DjV02EGn+fWqWGXxb9A5f07h2qm1US3jt5enpVt5vrmYDbEmADmNueel44E2ACDSHQq1cvESOfcl9R3ivKT7V27VoRt//DDz8EDIvYkO5rPZaMbRSPnzwMKefWrbfeKnIA1HogN2ACjUEg9W+A0+urRkbvlmEvNcYseMxGIJCfUwJ//3jWbB4vZbgvdB0WD6FR2vyKxtOLjFOCMsy2v6XGY9p6uzKvDK5+eRzK0wrkoYKGxkPwjQku4dkmL4oLTIAJMIEGEuBr7QYC5MOZABNwawK5K76sdf1+nTtDxP331dqOGzQugX82pltk/GrcWfLoTMCxCbABzLHPD8+OCTABByUwffp0WL16NWD+KygoKABKNE0hD5955hlITk62+azJ8PXCCy+IBNmY4wqWLFlidkwKs2JpeBVKlE3rYGECViWgwdQUf7yi67LLRICoDrptLrksAQrRsfrtA1CQU2qwxsh4JXQf3hzoDUUvL0+Dfa66UXGpCAq2pkPxP1cA1JSuRSshNydC0JB4aZM/mQATYAJMoIqAq15r8wlmAkyACdiaQEVWFhRLqTg8PSF4JEbfMIqw7RUSCpEPPQge3vxY2NbnoyH952UVw65fzsldUFj4gBAfedu44Aqh4o3XxNtMwBoE+JfOGhS5DybABNyOwJw5c4C0sWTq1KlAWpuQAWzu3Lm1NRP7qT82gFmEihvVhQB5fqXt1B7hqQAYOqsuR3NbJybwz6Y0A+NXfHvM4zU8AeLw0x1uzjCztAhzSIavslO6XF/SKQ29LQmU/QxD6Ur7+JMJMAEm4O4EXPVaOzExEejvAwsTYAJMwFYECtZvAPyhEd0HYOSa2P9oUybYajzu1zYE6G/FlhUnQFUVPp5eIrz18a5u8wKhbahyr+5KgA1g7nrmed1MgAm4BQHyRuObbLc41Y65SDXmetr4mm5uvaYBhCXqtrnksgRKCsth/2+p8voGTWwDXYbGyduuUCi/WASV2cVml6IpUUHhrotQkVFost8nMRiCb2gOfq3CTPZxBRNgAkyACTgXAb7Wdq7zxbNlAu5AoADzf0kSfPNNUpE/nYzAsb8yIeNUnpg15UYeNrk9G7+c7BzydB2HABvAHOdc8EyYABNgAkyACbgWgaM/AFw+rF2TAvM8DX7WtdbHq6mWwN51KVBeqhL7KcdXp8Gu4emkwfCFpSeuQsG2dChPya92/SY7PAD8O0aAcnAc+DYPNtnNFUyACTABJsAEmAATYAJMoKEEKi4bhj8MGj68oV3y8Y1AoDC3DHasOiOP3H14PDRpHiRvc4EJMIG6EWADWN14cWsmwASYABNgAkzAEgKqCoBN83Qt+z0MoGyq2+aSyxK4dqUEjmzNkNfXf2wSeDp5ri9NpRqKD2QJw1clrs9i8faEQMx1phwUB4pIf4sP44ZMgAkwASbABJgAE2ACTKCuBArWY/h5Kfxh797gHRlZ1y64fSMToAg+W78+Kb9MGNLUH3qPbNHIs+LhmYBzE2ADmHOfP549E2ACTIAJMAHHJHBgOUDuee3c/EIBBjzhmPPkWVmdwK6fzoJapc07EJ0UAi26Nv6NN3luqfLKAPCzLkI3oCVHc6BwewaoC9Coqy8YisSvdSh4KDz1a7VlDw9QNAuEwL7NwEtZfaJq0wO5hgkwASbABJgAE2hsAhxCvrHPAI9fXwL5v3P4w/qyc5TjzuzLgpRD2fJ0hk1uB94+XvI2F5gAE6g7ATaA1Z0ZH8EEmAATYAJMgAlUR6AE45Tv+wzgr3d0La6bifHf0AjG4vIELmNYwNN7s+R1DhjfCjzQGNRYoi5XQfG+y1DwVwaockqtMg0PXy9h2FIOjAXvEF+r9MmdMAEmYBsC9PtDD7LVmJPS09OMsdo2w3KvTIAJODkByQDWmNcwTo6Qp98IBCj8Ycm+/dqR8W8ehz9shJPQwCFLCyvgz29Oyb10HBwLMa05b7AMhAtMoJ4E2ABWT3B8GBNgAkyACTABJqBHgEJt5GcCvINx5ssLdDuUzQD6TNdtc8llCdDDIv1Y9Undm0CzliGNsl5VYTkU/n0RinZmgrqo0ipz8Az2gSA0epFXl6cfX0JbBSp3wgRsTMDX1xdKS0uhqKgIgoI4d4aNcXP3TMBlCNBvBgn9hrAwAWchYBD+sE8f8I6IcJap8zyrCPz13WkoqYo6oQzzhQEYSp6FCTCBhhPgu/eGM+QemAATYAJMgAm4L4EKzIdUiB4/lfhZhJ/Gxq8JywB8AtyXjxutPPVIDmSeRg9AFA8MD9jvNvvfsFXmlEDBnxnC60tToTagT55bnkqFQZ0lGxTCMLB3Mwjo1gQ8MKcXCxNgAs5DgIxeZAC7dOmSmHRgYKDwSmWvDuc5hzxTJmAvAvQiDykZv6TfDDac24s+j2MNAvm/6YU/vOkma3TJfVRDoLy0En7/5Ij23qduEdar6VFbXal3/zLkrrbg48+P7WsExjuZgIUE+H+ShaC4GRNgAkyACTABJqBHgDy+rqUBFOfoVVYVI9sCDMScX50nAHjzm7OmgFyvRo25tf7+8ay8sI6DYiA0yn6Gz/KMQijYmgYlhzFevtFNqFeoLygHoedWL/TcQiMYCxNgAu5DIDw8XDzMLi4uhvT0dPdZOK+UCTCBBhMICAgA+g1hYQLOQKDi8mUMf7hPO1UR/vAGZ5i2085xz5rzcOHoVZvNv3XvKEjs3Ph5lG22QO6YCdiZABvA7Aych2MCTIAJMAEm4BIEyNvL2PjlowS48xuA1jcCJltxiWXyIiwjcALDDV7N1IYLUqCRqffIFpYd2IBW9JZ2+fl8yN+SBmWnck16UsQEQtDgOPDvjJ5bXo2Xh8xkYlzBBJiA3QhQ3q/4+Hi4evUqFBQUQFlZmfDwsNsEeCAmwAScigB5h1LYQ/L8IuMX5w50qtPn1pMt+H29vP6Avhz+UIZhg0IOvnj3zybbvVQTGa+EQRNb22Dm3CUTcF8CbABz33PPK2cCTIAJMAEmUD8CFcWY7+ui7ljfYPT0KgWIxAv1tu119VxyCwIV5SrY/fM5ea3db2wOAZgvy1ZChq/SE/gwe0s6lKfmmwzj2zoUgobEgW9SqAh1ZtKAK5gAE3ArAvQAOzIyUqhbLZwXywSYABNgAm5DwCD84QgOf2irE0/3IdtWngINRr8giW0TCiMf7Yrx3603osKHI1ZYjyb3xAS0BNgAxt8EJsAEmAATsJhAYmKiaJuSkmLxMeYa0tuVQ4YMgS1btsi7X3nlFZg7dy5s3rwZkpOT5XouOBgBNeZVyk3FSVXFmVNgmLvwFgBZJx1sojyduhCgm7kLx67Csb8yoSS/3OJDPfG4sIJy6FKpAi8l5tjy8oSmqdcg64N/LO6jrg3VRRVQmY055/QFbzr9MUxI0JB48IlFT0QWJsAEmAATYAJMgAkwASbgBgRE+MP9+7UrxZc+gm4c7garbpwlntp1Sc557Ik5jwdPagsU/YKFCTABxybABjDHPj88OybABKxAgIwpW7du5ZA3VmDJXTABKMgEqERvLxIPDHMYmqD91Nbwv05GgHJ3nTtwBfb9lgLZaYUWz94bDU4tfDwhydcTfPHmDxS6kJcVFwos7qfBDTG0YWCPKFCix5ci0r/B3XEHTIAJmCUQgbVjUUeidkaNRSVL+WHUz6oU346QJRFL5+Ut0wLGyoVJptVcwwSYABNgAkyACdSVQMHvv8uHBPbrC96cu07mYc1CWXEFbF91Ru6y6/XxEI4h11mYABNwfAJsAHP8c8QzrBsBujF/ErUDKt2sU4wuygT6NurfqMYyACteQu2H6odKf82Wor6HqkJlYQJMwE4EHnvsMZg0aRI0b97cTiPyMHUmUIrh5oqu6A4LxmegCvrpZHE2AqpKNZzENxgPrL8AeZcxpKWF4ou2rpZo9GqBqkBPzsYSDzS+BfaJhqBBseAV4ttY0+BxmYC7EJiAC/0Ala6rN6NeQI1CHYf6KerNqNRGg6ov5Aq6Wr+iqnzETB1XMQEmwASYABNgAvUgkP/rb/JRQRz+UGZh7cKuX85DSUGF6DYw1Bd6jUy09hDcHxNgAjYiwAYwG4HlbhuFwBs46nOoOah0s52N2gp1DOp41CmoK1AlofpVqOTKQG+iXkUdhfoO6kBUupFnYQJMwE4EOD+HnUDXdxhVJUAePfOsEsr7FUDvGbA4GoGKMhWc2n0JcjKKzE6NYtanHM6Gwtwyg/0+6MXVt1UIhIdi/i5zxi3M9QXnr+HrIUbPuJUK8OzaBMLaR4AnuYbZWnBuiqgA8PTjy1hbo+b+mUAVgVP4ORp1Laq+p9cLuL0bla6zyRhG19X6chA3XtGv4DITYAJMgAkwASZgPQIVly5ByYED2g69vCBo+A3W65x7kglcwQgXRzD/sCTXTWgNPnwvIuHgTybg8AR08Wocfqo8QSZQI4FmuPcZ1Muo5P31AOq/UW9HHYFKT+ReRZUEn9zCJ6jk5ZWMej/qs6jdUMlTjI6bhMpiZwK7d++GiRMnQmxsLPj6+kJ0dDTceOON8O2338ozWbZsGYwfPx5atmwJ/v7+EBwcDAMHDoQVK1bIbaiQkpKCz3A9RPhD2qaypMY5ptLT04E8kKhPGjciIgJGjx4Ne/bsoUNN5OLFizBt2jRo2rSpmEO3bt3g888/FzmtaAzKZ2Usp0+fhilTpoi1+fj4QExMjNimemOh46kfypH11VdfQd++fUGpVEJiYiKcOHFC7Bs2bJjxYfJ2586dQaFQwCW8IK6rUC6gxYsXQ8eOHcHPz0/Ml9hcu4YPvmuQr7/+GoYOHQphYWHiuPbt28O8efOgrMzwIXt1XeivWb/Nn3/+CaNGjYK4uDhxbpo1awb9+vUT+cL023HZhgTwOwHXLuBjT+0bb2jlwNCH6KmH31EWxyFQjLm7dv18Dj5/YTts+fIkHMabNHN6ZFuGgfHLx98bet7UHMb0jITwi4UAx/F9kGP4LomxnskzMH55N/GHsAltIHZWH4gZlQT+rULBNzHE9poQzMYvx/na8Uzcg8AmXOYvqPrGL1o5XWR8SAWUZPEv/8MEmAATYAJMgAnYjYBB+EN8ZsDhD62Pnl4e3LbyJKbU0PYd1y4Mkno0sf5A3CMTYAI2I4BPsFiYgEsQSMBVeKLuQs0yWtFm3C5A1f8LRQYu2v4CdS+qJKVYoJCIG1EfRl2JymInAp988gk8/PDD4IVvLpHxqXXr1pCVlQV79+6FJUuWwB133CFmQm06dOgAgwcPFgaynJwcWLduHUyePBlOnjwJr732mmgXGhoKc+bMATKYpaamirK0FDIkSbIfE8aSke3q1aswYsQIGDduHGRnZ8Pq1avhuuuugx9//BFuueUWqbmY04ABA4SBjeZAZTI0PfLII6IfuaFegQxpN9xwAxQUFIi10fzJkPXll1/CTz/9BBs3boRevXrpHaEt/ve//4UNGzYIAxAZl8gI1a5dO2Fo2rx5M5w6dQratGljcNyOHTvgyJEjwkhIxqK6ysyZM2HRokWC7UMPPSQMaTTHXbt2QXl5OZDxzljuv/9+WLp0qTBSET9iv3PnTpg9e7ZYG63B27vuf3J+++03GDlypDBy0neCDKN0no4fPy6+E3R+WexAoAQNIqV6BlAyfnkp7DAwD2EJgbysYjj4Rxqc+PsiqCqMn09X34N/sA90w9j1nQbHQsXRHMjdSdHNahdFnBKCk+PBr0MEpoFjI2jtxLgFE3BpAlVvRgC6CZtIDNZMRyV3YbSqi5fMDuEnCxNgAkyACTABJmAFAgbhD28aYYUeuQtjAsfxHuvSOUwFgOKJ+YcHT2ojXkg2bsfbTIAJOC6Buj+NdNy18MzcmwC50JSj9kGNRKXwh5IMxkIQKoVFlGRYVeE3qULvcxuWKSHKAFRfVMvcV7AhS/0JHDt2TBiQyJuLPH7I+0hfyENLEjLuJCUlSZvikwwzN998MyxcuBBmzJghDCVkhCGvIvKiIgMYlY2lsrJSGNYKCwuBDEpDhgyRm2RmZkLv3r2BjDvkTUaeYSSzZs0S28899xy88cYbcnsyHPXpQ19BQyGPKvL8ys/PF15qd999t9zgm2++EXmv7rnnHiAGnp5kx9XJpk2b4O+//4bu3bvrKrFExjaa78cffwxvvfWWwT6qI5k+fbpBvSUbZDwj4xfxJW+88KoEuvPnzxdGN/J8S0gge7NOyMBIxq+xY8cKgx555UlCzOfOnQvvv/8+PPnkk1K1xZ9kFFWr1eIcdu3a1eA4MlKyWImAGp1hycClMWc80QDkZ+oGCsCfWL8Q3TaXbEqgvKQSUo/kQAWFHzQWPDUX0HB19iDmZcOyvgRF+EGHgdFA3l3mxD/IB1p0iQRvHy+ozCmBvJ/Pys3IsOWXZP4cK6KV4NMimG/6ZFpcYAJuTYB+YKZUETB3TT0c95HqyxbcuBf1gn4ll5kAE2ACTIAJMIG6EajAe/OSgxRtGEWEPzT+k6vdxf/Wn0BpUQX8/aPuPqnb8OYQ1iyw/h3ykUyACTQKAfNPRRplKjwoE2gQAXRPgOdR30Y9hkrGLnrTlKwko1E3oOpbA9riNskp7YfBv/QG63lUssC0RD2OWpPsq2Znu2rq61T934m31ql9YzZ++ps19R7+gw8+ADJGkceQsfGLOqXwd5IYG7+onrySHn30USCDEXlTkcHJElm7di2cPXsWnnnmGQPjFx1LIQrJyEWGLeqTvMDI0Eah/kJCQuCll8hZUCdkoKFxP/30U10llsioRN5e/fv3B33jFzWicI8UbvCvv/4SSh5l+kIeWMbGL9p/2223ifmR8YmMU5JxLi8vT4SLJEbkcVZX+eyzz8QhL774omz8ogoKhfj6668LI5hxn++++67w7iIjmL7xi9rR+aT1kadbfQxg0ljG/VI95QxjsQIBNf7k5eBFfQXZ/WsRLzQCB8fU0oh3W4tAdnoh/PLeQSi+Vm5xl02aB0H3G5tDUvcm+IaioUHdXCcazOd19dtToKkysHlH+kP4pLbgiYYxFibABJhALQQW4v5OqOtQf9drS39QyB2frsfPVdV3wc9XUIeibkTthlqEWpvY9Dq7tsF5PxNgAkyACTABRyWQ+9XX8tQCKfwhpiJgsS6B7avOQGmh1tldGe4LvW5OtO4A3BsTYAJ2IcAGMLtg5kHsROB/OE4K6lLUB1ElOYOFZaj6oRGlV9v1YnpJzcWnVB9qUMsbNiNA4fJIyIurNrlw4YLwvCKjFJVLSkoMDsnIyDDYrmmDvKtIqvMQk/JzUcg9MoBRiEUaj8IVBgWRY6GhUMhEYwMYhVgkqS5nF9WTAewAJq81NoCZ8yijviic4AMPPACvvvoqrFq1Cu666y6qhuXLl4v5keGMcojVVaS56nvCSX0MGjTIJIxhcXEx/PPPP8IY9b//0X9BUyHjHPGrj5DB8IcffhA50MhYSGEgKd+bvkG0Pv3yMVUEyPPLUuMXpVIMS6C4D4zPDgQyMd/W2vcPAXmAWSLNO4ZDd3wjMbZtWJ3+7xdsSYPyVG1ID8BwhuET2fhlCW9uwwSYADyBDJ5GPYE62YgHXXO/bFS3DbdvRP0LtS/qA6jvorIwASbABJgAE2ACdSRQcvgI5OALqJKEjKH3vlmsSSDlcDac2HFR7nLQHW1A4cv3wjIQLjABJyLABjAnOlk81VoJPIctFqAuQl2Megm1HerrqF+i0pum1MYSkSwHGgsa96ymDb2x2qOafVxtRIA8l0gox1NNcu7cORFmMDc3F8ggQ7m7yBuL8oalpKTA559/DmVllketpPxhJN99911NwwKFSCShHFwkUVFR4tP4H3P10jHR0dHGzcW2VC8x0G9UUw4vMnItWLAAPvroI9kARuEPyRtu2rRp+t1YXJbmam4dxDgigtJ46ITOA4V4vHLligh1qNtjnRLlE1uzZg1QLjTyMKO1kvTs2VN4pA0fPtw6A7ljL+aMX35o8zcKw6lFgz+JtM+Hwz3Y46ty/lA2/P7JETmfl4+fF7Ts0ZRMkCbiG6iAtn2bQSTm5aqrlKcVQP7GVPmw4Buag0+8qWFfbsAFJsAEmICWwKP4QcarY6jXo15FtUTIov8pKhnABqNaYgDj62wExcIEmAATYAJMQCKgxqg0F1+YBaDClxlRAjBtQ/CoUdJu/rQCgbLiCtiygt7x0Uqrnk2hZbcm0iZ/MgEm4GQE2ADmZCeMp1stgWTcQ8mYfkR9ClUScr0Zi0qhDukt1Q9Rz6FqrRgAkicYVhlIcNWW1M5gpz03GhJW0J7zbOhYlK+LhLy32rUju6V5efvtt4GMVhSqb+rUqQaNKDQhGcDqImQ8I/npp59g9Oja35qiHGUkly9fFp/G/5irl8a4dIlssqZCebVIpHb6LWry4iJj4Si80P3xxx+FhxUZoyg/GnlKNWlSv4szaQ60jpYtKQKoTlR4gU3s9Y2UUnsK0yh5j+mOsE5p5MiRQFpUVAS7du0SBjEKmXnrrbcKr7kOHTpYZyB36oWMX1fPYthDvehTIXEAgfX73rgTOluv9cTfF2HT8hOYjk37/oV/sA+MerwrNLGyYUpdpoKrK/GmTq1dkU9CMAQlx9t6edw/E2ACzk9gJi7hHdQjqGT80o+wgJu1ypWqFvxGRa2ouAETYAJMgAkwAVMC2Yvfh7LTZ8QOD8y/Hb1gPniYfYnR9FiusYzAX9+dhqKqMPT+QQoYPKmNZQdyKybABBySQO3JIRxy2jwpJmBCQEqUtdlkDwDlIdiNSt/37lX7T1Z9mvsrRobhFqj0lioZy1jsQKBfv35ilF9//bXG0c6c0V7ojR8/3qTd1q1bTeqogjyXSMiAYyzSuH/++afxLrPbZJyjfFSHDh2CgoICkzYUytBYpBxeW7ZsMd4ltqX6Hj3q7jD4yCOPiD7I84uUZPr06eKzPv9IczDHkhhRnjZ9USqVImfb0aNH4erVq/q7rF4ODAwUYSTJCPrCCy+IfGy1fV+sPglX6FAYv/CnrVzP+BUcx8YvBzi3BzZcgI2fH5eNX8GRfjD+2R5WN37RUq+tPQeVOaVi1R4YyoNCH3pgCEQWJsAEmEANBJ7HfWT8Oog6FLWuxi88BLQXfHyNTSxYmAATYAJMgAnUiUDJ4cOQo5dzvOnTT2MEB36JrU4Qa2ksQh/+rXt5ecidbcE/yKeWo3g3E2ACjkyADWCOfHZ4bnUh4FvVuDr3Bam+vKrdpqrPm8wMMhjrAlB3oJaZ2c9VNiDw8MMPi/xSr732Ghw7RhF1DCU9PV1UJCYmik/JaCS1+v33301yb0n7pLB9lC/MWMaMGQNJSUnw/vvvw7p164x3i23KE0a5rkgovCB5WFGowHnz5ok66R/KhfXFF19Im/In5axq27atyPP1/fffy/VUoO1t27ZBmzZtgPKH1VWuv/56cSx5vn377beiTHmy6iuSV938+fMNDFqlpaUwaxaGWTAjTz31lDBG3XfffWAujCN5ptXXO4zyvBnneKMpSJ52AQH0X5XFYgKy8Usb0lMcF4xhR5XST6TFPXFDKxKgMKI7fjgDOzDJsiQRsUoY92xPCGli/e94ydEcKNqtu6kLHZ0E3uF+0tD8yQSYABMwR2A2Vi5EpRDf5PmVjVqdUIhDc0+KhmH9v6oOWlHdwVzPBJgAE2ACTIAJmBJQY6qHTLonV6vFzoA+fSDsrjtNG3JNvQmUFlXAZv3Qh72aQhKGomdhAkzAuQl4O/f0efZMQCZA7juPoT6E+hFqBqokN2NhICq96k5GLRKyQlDIxEmo76HuRSWhJ4CSVeMDUcP/2IUAhbFbsmQJzJgxA8hjigxTrVu3FiH39u7dC0FBQbB582YgjycKfzhhwgQgLzAKx0dh/3777Te444474JtvvjGZLxmJKMcX5ZO65ZZbhAdXQkICTJ48GRQKBfzwww8wYsQIEWZvwIAB0K1bNyDDSlpaGuzZswco7xiFKZSMLQsXLoRNmzbBm2++KULy0TG0nwxQ1P/q1asxjZLu/QIKY0gGKspXRcYzWht5kp08eVK0pbWR4Uz/GJNFVFNBfRMzMkKRNMT7i44nY93jjz8O7733HnTq1Aluv/12wYhCRIaFhYGUr4zaSkKGr3379onzR8ZEYtm8eXNhQDt//rww8FFOsg8//FA6xOLPp/GNNsrtlpycDGT8JAMkjUX86RxOmkT/hVlqJYAGFijFiK6FaPSoKNE1D45B4xdf0OuA2L+kxlCHW748Ace3a0Oh0gyiW4XAyEe6gG+AwqoTUperoHjfZcjfkCr36985EgL4pk7mwQUmwATMErgXa19FJVd6uuZ+AtVYUrBiWVUlXWN3RN2Cmo5K0gWVDGAkZEyTrslFBf/DBJgAE2ACTIAJ1Ewge/FiKD9zVjTywOcVHPqwZl712UuhD4s59GF90PExTMChCbABzKFPD0+uDgTIoPUH6g2ox1F/RMUnvdAe9VZUD9R/o+agkuSjPohKx21BXYlK8dtGo7ZFpXpTSwpWstiOwIMPPiiMLm+99RZs2bJFGIciIyOhS5cu8MADD4iBqUyGsJdeekl4bFFIvq5duwojFuURM2cAo2NTU1Nh5cqVwmhFxwwZMkQYwKhT6pO8tyi03po1a4SBjYxRZOwhY9zcuXOB5iFJVFQU7NixQ4ThI68xyktFHl5kwKMwfWQAk3KFScf07dtXGNPIa+yPP/6AX375RfR55513wuzZs8XxUtu6fpLX1jPPPCMMVffeS8+oGibvvvuu8CQjr7iPPvoIyINu7NixsGDBAsHaXO/U9uabbxZGLlofeYKFh4cLQ9izzz4L99xzj7nDaq2jUIeU44yMoNQvnRcyrlH9zJkzhVGu1k7cuQG9HViCP22FGKVKVWZIIigajV9RhnW8ZVcCqko1/PHZMTizD89PlSR2iYQRD3QEbx8vqarBn6rCcijE3GJFf2eCurhS7s8L84uFjW0FNeUalBtzgQkwAXcm0KJq8fTDRDnAzMlWrFxWtWM5fo5F7Y16MypZ8y+jfou6GPVPVBYmwASYABNgAkzAQgIl+Lwi5/+Wyq2bPoOhD+Pi5G0uNJzA+UPZcHInPUbUSvJdmP5C6SNt8icTYAJOTICMAixMwFUI0M31o6jkEtIBNQCVjFq7URehrkc1FvIMexG1P6of6hlUuqqg9vSWa0NkH+ZT6kHeKjXJ8eNkr0NLXXuy1bE4O4EXX3xRGIrII408oewhZCyksIdkZFq+nJ45sbg9ATUaOYqyUa9giAydwUPLBf/0B1vf+MW/ZXX71lWiN9ZvnxyB1MPSexkA7fo1g6GT24Gnl86DtG69GrauzC6Bgr8yoGgvPndGY5u+eAZ6Q8SUjuCbEKxfzWUm4BIEevbsSaF39+NierrEgngR5ghYdJ1t7kCuYwJMgAkwASbgTAQo9OH5seOgHCPTkATgy7XNP1uK+Xutc8/gTCxsNVcKffj1q7tk76/WvaPgxvvJmZ3FmABfZxsT4W1nIMAeYM5wlniOlhKowIb/q1JLj9mODW+xtDG3YwISgczMTIiJwfBxenIYE9IuWrRIeD6Rh5m9hEIxkjz22GP2GpLHaUwCKvypK8rCkIYFOAsMbWhOVJjuUGNo8AAPfHE/IEKb78uL32Qzh81edeWllbDug0OQcTJPHrLz0DgYNKE13sg2/N0kdZkK8lafgeKD+D0x+op4hflC0HWxENC7GXha0ctMXggXmAATYAJMgAkwASbABJgAE7AagSv4jEEyfnlS6EPM1+1Mxq/LRZehuFKbU91qUKrpSK3SQPFVegHU6CaomvZS9Zk/8mTjl4/SCxJu9oXz185Lu53mMyE4ATw92DDqNCeMJ2o3AmwAsxtqHogJMAFXItCrVy9o1aqVCNlIYQ9Pnz4Na9euxXy0ahEG0M+PHAptJ2Rso3CN5GH466+/wq233goUZpHFhQlUYghDCmVYTB5Ddbig90TnWGUTNH5hGE9PNIKxNCoBertwzeJ/4PJ5isSrlZ43JUDfMS2tEopQhf1nLzsKFWlkINWJIlYJQYNjwb9TE7SFNtzIpuuZS0yACTABJsAEmAATYAJMgAnYggCFPrz62TK566bPPYuhD2PlbUcvvLXnLfj82Od2maZfRSCMPfIvCCnFe98GyM+xH8KiDUca0EPjHbr3nr3g6+XbeBPgkZmAgxJgA5iDnhieFhNgAo5NYPr06SLX19dffw0FBQVA+cco5CHl4kpOTrb55MnwRXmwKNfYhAkTRP4xc4OmpKTAsmXLzO0yqaOcWrQOFgcjUFGChi8MYVeSW7eJeaMRVtkUwD8MsyDyW2B1g2eb1sX55fDzuwchJ6NQHqD/2CToMSJB3m5IoTKvDLL/7zBUXsHvTJX4tglDw1cc+CaFWMXAJvXLn0yACTABJsAEmAATYAJMgAnYjoC6vBwyMcUCvmUrBgno3w9CJ0603YBW7nnnxZ12M37R1Aedn9Bg49epyL2QEu6cxi8rnz7ujgm4FAE2gLnU6bTbYrrjSJQz60vUa1WjBuLnEtQxqOTb/Abqu6gsTMAlCcyZMwdIG0umTp0KpLUJGcDmzp1bWzOxn/pjA5hFqOzTqBLDGF5LByiTfmb1hlUEaI1bZOQyJx7o4UNvftEni0MQyErNhw1Lj0HeZV34j8GT2kDn5DirzK8iqxiNX0dAdQ09BUnw1IeOSQJlP8NQrdqd/C8TYAIuRoCvzV3shPJymAATYAJMgAnkfPQxlJ85K0B4UOjD1+Y5zQttxRXFMHeH7jlEuF84BPvYLvdws0ttICmHLoe0UhRAL4/WIWoKti4IyoYLHXdDoiJR24kT/utBN4EsTIAJmBBgA5gJEq6wgMDz2GYQKhm8JHkdC5NR6bV2TDIDb6MeR12PysIEmEAjESBvNI2mbhd+jTRVHlafgFoFcBVvdipL9WsBfJQAQc20n2zcMmTjgFv0f+/C0atwYEOqQb4vOnXD7m0P7fpFW2XW5RjuMPuzI6Aupnj3KBjiMHxiWwjo0rDwH9rO+F8mwAScgABfmzvBSeIpMgEmwASYABOwlEDpyVOQ/fHHcvOmGK3FmUIfvn/wfUgvxJc5UcjwtWr0Koj0j5TXY80CRdn4+tVdUAqYKxulw8BoGDp5WD2HmFHP4/gwJsAEHJkAG8Ac+ew47tx64dS26E0PE8zAvai7UZNRw1EPoD6BygYwhMDCBJgAE6gTgfwMQ+OXXwh6fEWh4YucbVkcnYCqUg2n916GgxsuYLjDIoPpeqJx6sYHOkJS96YG9fXdKD2dCznLj4GmXBsaxcPHEyImdwC/1mH17ZKPYwJMwPkI8LW5850znjETYAJMgAkwAbMENCoVXJw9G6BCa9Dx79YNwu6+y2xbR6w8dOUQrDi+Qp7as72ftZnxi1443Pb1SSgt1LJShvnCwNtby2NzgQkwASZABNgAxt+D+hCgp3ZpegfSTXcQ6keo5K6QifoT6k2oLEyACTABJlAXApTrqzhHd0RIPECgbd6W0w3CJWsQIMPX4S3pcPCPNCjCfFz6ovD0gK6tQiChTSgEFpZDwZ/aNyL129S1rC6phIKt2I9K6+XpGeANkdM6gU88/UlmYQJMwI0I8LW5G51sXioTYAJMgAm4NoGry5dD6aFDYpEeCgVEz3sNPLy8nGLRFaoKmLNjDqg12pfz+kf3hzFJY2w29zN7s+DsgSty/0MntwMff37ULQPhAhNgAoIA/yrwF6E+BOhJm/535zrcprqtep3RXyCOvaQHhItMgAkwgVoJVKLRJE/v/QK/UIAAiirL4ugEKstVsO7Dw5B27KrBVJV+XtCruRJCcvH9kKwiqES9ZtDCOhteIb4QeX8nUDTF/HAsTIAJuBsBvjZ3tzPO62UCTIAJMAGXJFCelgZX/veuvLaIh2eAb6tW8rajFz498imcyTsjpunv7Q9zBsyxWd4yCn24beUpGUmH62KgeQe+d5aBcIEJMAGZgL4RQ67kAhOohcAF3N9Prw29zpGOek6vLgbL6MbAwgSYABNgAhYRoFxtuan4OgHm/yLx8gEIRe8vzvWl5eHA/1aUqWDtkkOY50v3Z69JsAK6NwsA/+wSNHwV23T23k39IfK+zuAd6mvTcbhzJsAEHJYAX5s77KnhiTEBJsAEmAATsIwAhfO7OPtl0JRSYCUA3zZtIPKBByw72AFanck9Ax8f+lieyZM9noRYZay8bc0Csdr6FYY+LKoKfRiOoQ/HO4+h0JosuC8mwARqJ8AGsNoZcQtTAt9i1VzU71HpL3N/1P+h6ksn3DirX8FlJsAEmAATqIFAwSWM866XLyosEcCT/0zXQKzRdqmLK6D8Ip4rtFmS59fOn85BWUYhRHp7gMIDoEtMIPhdQ28+I8OXN3pn+bVGrz4rGjW90OgV2DMKPDnUR6N9H3jg2glcyd4IRYUnITHxkdobc4v6EOBr8/pQ42OYABNgAkyACTgQgWurVkHxzp3aGXl6QvT8eeDhgy9FOoGo1CoR+rBSXSlm26VJF5jUdpLNZk75ls8d1IU+HDa5PYc+tBlt7pgJOD8BfrLm/OewMVbwDg5K+b3GVQ1+ED9frSrTRwfUnqgLaIOFCTABJsAEaiFQVgBQiAYwSYKiAXwCpS3+dBAClTklUPBXBhTjDZemQhvXnqbWjv5R6l1SkfFLT3xahEDQkDjwaxMGHpgLjIUJuBOBzIvfw4kTL4AGvVu9vYMhLu4ed1q+vdbK1+b2Is3jMAEmwASYABOwAYGKy1lw+Y035Z7D770X/Dt3lrcdvfDVia/gULY2b5nCUwGvDngVvDxtk7esCO+19EMfdhwUA/Htwx0dEc+PCTCBRiSg97SmEWfBQzsbgUKc8EBU8vIiOYaqexIIQLGexqLuRWVhAkyACTCBmgio8C05Cn0oiY8SjSlR0hZ/OgCB8rQCKNiWDiVHsrUZLy2ZE9q5/DtFQtDgOPCJD7LkCG7DBFyOQGrqx3Dm7Bvyui6kLYXo6Ang5cXhOmUo1inwtbl1OHIvTIAJMAEm4EYErpVdg7f2vgUZhRmNu2oM5zdm6SloU4AvRaLkRfjCOx2OQuXv9zXuvOow+uErh+XWD3V5CJJCk+Tt6goUPv7AhgsiokZ1bczVF+SWQVmR1tMsKNwPBnDoQ3OYuI4JMAE9AmwA04PBRYsJNMeWeahHqjkiBetzUMOq2c/VTIAJMAEmQAQo71cepm5Ra2OXi5CHYQlWDZHHoOtHgOLKl+JNWSEavsrOXTPppBg9uYow95ckoRjeUBmmfaiviA4E5YAY8I7wl3bzJxNwKwL0/4cMXxcufCKvW6lsD926fsbGL5mIVQt8bW5VnNwZE2ACTIAJuDoBulaZvX02bE7b3OhL7X9MDW0O6d4pf3dEBRy9ur/R51WfCbQOaw33d7q/1kMLrpbCug8OQXmp7n6q1oPMNBg6pR34+PGjbTNouIoJMAE9AvwroQeDixYTOI8t56Lqhz00PviJqv228Xk2Ho23mQATYALORqCiBIDyfuGbh7KE4jNML+eI8y7P2cUKmko1FGM8+YI/06HyMjk0G4pPUigcwPxfZzJ1+wZPagMtkuMMG/IWE3BTAmrM/XDi5ItwEUMfShIa0hu6dPkYFIpgqYo/rUuAr82ty5N7YwJMgAkwARcnsPb8WocwfoUUaeD+9Trj18auHnA0wdMp6ft7+8NrA14DhZeixvmT8XHLihMNNn51vSEe4ttx6MMaYfNOJsAEBAE2gPEXoT4EOIFJfajxMUyACVidwJYtW2Do0KEwZ84ceOWVV6zev006LC9Cw9dlQ8MXDRTYBMAvxCZDcqe1E1CXVkLRrktQuD0DVPnlhgfgPWhA16agHBQLOzan64xf+Ncw+a620BHrWZgAEwBQqUrhyNEnITv7DxlHZOQN0Knju+j55SfXccHqBPja3OpIuUMmwASYABNwVQJXiq/A67tel5c3quUouK3VbfK23QpoCPKb8x4oSvaJIdVNw6HP/AXQJ9A5o0i0DG0Jkf6RteI7vuMiXDh2VdsOr2Cun9IelBjKsC7i6+8NkfGYOoCFCTABJmABATaAWQCJm9SLACWwwae8LEyg8QkkJyfD1q1bMdqcpvEnwzNwTwL03SvDmO6FaPgqp1QtRkKGr+AYo0retAeBSkyiTEYvMn5p9EIa0tgePl4Q2KcZKK/DcIahfnB2fxYc/TNTntbgiW3Y+CXT4IK7E6ioyIdDhx6CvGt7ZBTR0bdDu7bzwdOTbzlkKI1X4GvzxmPPIzMBJsAEmICDEKBnAq/+/Srkl+eLGcUqY+HFfi9CoCLQ7jO8tmYtZP6pNX7R4AkL3gRlq4F2n4c9B6TQh9u/Oy0P2XVYPLTrHy1vc4EJMAEmYAsCfDdqC6qu2ecUo2V1w23jOmpCIQ8xhrKBlOIAAEAASURBVBdMRtVlwcQNFibABJiAtQn06dMHjh8/DpGRtb9pZu2xLeqPDF+lmDKRDF8U8tBYyPClxGeSPva/4TKeijNvl5y4CvkbL4Da2HPLgkWpCtDbS21oHPcMUoByYCwo0fjlGaAN4UE3a5sxVIckrXo2hU5D2PNL4sGfzkUgK+s3SEn9AMrLKWWrdUSlKoLKSu3DJOqxefMHoVXS8+Dhwc5J1iFs0ovxdThfm5sg4gomwASYABNgAoYE1pxbA1vSt8iVrw54tVGMX5VXrsDl116T5xF6xx340p1rG7/I+Lh5+XE59GFIU3/oO6alzIALTIAJMAFbEWADmK3Iul6/y3BJ0hNC+hxTpfhhINJTDkqOMtdgD28wASbABKxMICAgANq1a2flXq3QnRqT+RZjWIeiLIwJZhROj7r3x1jlyqYACucMb2EFQlbromjfZcj9/pTuL1QDevZu4g9Bg+MgoHtT8PDGuIdVolapYcP/HYWy4kpRE4QhOpLvbssP9iVA/OlUBC6kfQanT8+z6ZzJ8JWQ8JBNx+DOYRky4Gtz/iIwASbABJgAE7CQQFZxFry+Wxf6cGLbidAnuo+FR1uvGRmCLs6dC6pr2lzQ3jHR0PS5Z603gIP2dOyvTEg7nqudXVXoQwVG3GBhAkyACdiagO7pjq1H4v6dncA0XMB9qPejkpHrp6ptqtNXeht1JGoc6npUFiZQJwK7d++GiRMnQmxsLPj6+kJ0dDTceOON8O2338r9LFu2DMaPHw8tW7YEf39/CA4OhoEDB8KKFSvkNlRISUkRD6gp/CEJvYUuKYVF1Jf09HR47LHHRJ80bkREBIwePRr27NGFctJvf/HiRZg2bRo0bdpUzKFbt27w+eefA+WkojHM5aM6ffo0TJkyRazNx8cHYmJixDbVGwsdT/1Qf1999RX07dsXlEolJCYmwokTJ8S+YcOGGR8mb3fu3BkUCgVcunRJrrOkIDGbOnUqnD17Fm6//XbBIigoSJyHI0eOiG6u4BtrDz30kDg/fn5+0Lt3b9i8ebPZISorK2HJkiXQr18/ca7IaNW9e3dYvHgxqNVqg2Nuu+02sbb33nvPoJ42Zs+eLfY98MAD8r6aeF+9ehVefPFF6NSpE9CYISEh0LVrV/j3v/8NRUW6CK379u2DJ598UuwLDw8HWk/r1q3h6aefhtzcqgt0eUQA+v7RuaFPWjN9l4gPfQ9H3nILHN+zDeDyUYD8dCPjF/50BqCnWtMOAGEJbPzSY1rfYuHfmZD7XcONXz6JwRAxpQNE/asnBPZuZmD8orntWZcCF89qb1A9PD1g+P0dwbfKM6y+c+fjmIC9CdDDlrNn/2tT45e3dzC0b/8GG7/sc3Kn4TD3ofK1uX148yhMgAkwASbgxASk0IcF5RiWHoVCHz7V86lGWVE+hj4s/GOjPHbMvHnghff6riz5OSWwfdUZeYldr4+H6Fah8jYXmAATYAK2JOBty865b5ci8Lneau7F8mrUL/TquMgEGkzgk08+gYcffhi8vLyE8YmMEFlZWbB3715hQLkDwwKQUJsOHTrA4MGDhQEmJycH1q1bB5MnT4aTJ0/Ca1WhBEJDQ2HOnDnCUJGamirK0iTJkCTJ/v37hXGHDCYjRoyAcePGQXZ2NqxevRquu+46+PHHH+EWNGxIQnMaMGCAMLDRHKhMhqZHHnlE9CO10/8kQ9oNN9wABQUFYm00fzJkffnll/DTTz/Bxo0boVevXvqHiPJ///tf2LBhA4waNQqGDh0K1/AtMfJ4ojIZX06dOgVt2rQxOG7Hjh1AhioyEjZr1sxgn6UbZAgjo1v79u2BjGG0TRzI2PP333/DTTfdJAw+ZKwkbitXroSbb75ZzKd5c4qCqpWKigox999//x3atm0Ld911lzAw0dwff/xx2LVrFyxfvlxqDkuXLhXGsWeffVawJ0MZCfFZsGCBOO+LFi2S21dXOH/+vGBE571nz57iO0PGNuL1zjvvwIwZMyAwUBt2kL53tLYhQ4aIc6RSqYC+E2+//Tb8+uuvYo5k4DKWNWvWiHNH657x0ANw7PAhWIft9+zeCce2fA+R4WHaQzy8AAKboKLxy0th3A1v15NA/uY0yP89RT5aER0I4Xe2w7xdnnKdJQUPhRd4BVZ/XjJO5cI+NIBJ0ufWFhCdhKErWZiAExHQaFRw4uTLkJm5Up51SEgP6ND+TczP5SvXNbSgUETg33Dr9dfQ+bj48Xxt7uInmJfHBJgAE2AC1iPw89mfYWv6VrnD1wa+BgGKAHnbXoUKfJZwCQ1ekoTi/XQgPk9wZdGGPjwBFaUYJQUlNCoA+o1u6cpL5rUxASbABJgAE3AbAvt69OiBf+trlmPHjmlI3V2OHj2q8fb21oSFhWnQeGOCIy0tTa47c+aMXJYKZWVlGvSIEn2gN5dULT7RsEEhggzqpA000GiSkpI06PWlQW8iqVp8ZmRkaNBLS4NGJE1paam877777hP9Pffcc3IdFQ4ePKhBzy6xDw1v8j40vGjQaCXq0UtNrqcCGo5EPRqHNGh4kffR8TRn9FzSoDFGrpcK3333ndiPXkpSlfx57733in3r16+X6ywtoOFIHEtjz5s3z+CwV199VeyjczR9+nSD+X7xxRdi38yZMw2OkdaB3nUa9AST91FZ4oiGRrmeCtu3bxfnEQ2gGjQYai5fvizOAXr7mXw30JAmxtXnTX2gUVLUo9GMNg0Evdc0JSUlch0a9wzmJu349NNPRR8LFy6UqsTnZ599JurRUKv549dfNJqcsxpNBp4j1H8/Nk3se+PFJzSaS/g9LsjC5866dRt05GIb9voto/9Peb+e06Q9v03Wy+8f0KiKyq1OtKSgXLPs339pFk/fKPTH/+7D773a6uNwh0zAlgQqK0s1/xx6WPPHxpayHjh4P/7uFdty2Ebtm66/8O+YLqs8brC4HAGLrrMb9YvIgzMBJsAEmIBDELhUeEnT/8v+mk7LOgmdv3N+o8yL7mMuPPyI5ljbdkJPDx2mqSwobJS52HPQw1vT5fup92ds1Fw8m2fP4XksKxPg62yXu6Z2iwWxB5hbnGZepDMTSP/3n04z/biFg+o91w8++AAoVB6FuevYsaNJP3FxFFVTK2iwkoryJ4UUfPTRR2HTpk3CW4hCDVoia9euFaH+nnnmGeEBpH8MhShEIxegUUf0SV5g5eXl8PXXX4twei+99JJ+cxFCj8ZFw4lBPXlkkbdX//794e677zbYRx5UFArwr7/+EkoeZfpCYQYlLyj9egoVSPOjMHzz588X4SJpf15enggXSYzI46y+Qh5yFCpQX9CwBi+//DKgsRH+85//oNeAztOGPLvQoAVoBJQPIY8rWht5oZHXFXn2SUJl8m5DY5LwghszhtIKaoU86siLb9asWYCGNqBwi+RhR55a5r4b0nHSJ4U0JOYUlvL555+XquXPyEj0xNKThIQEvS1dkdbz1FNPAXmvGfSjoeeqAJPGjoTru8QClGpD41HdQ3ePg4WLP4PdR89rQx1iqEQW6xHQqDWQ98tZKPr7otypL3pjRUzpCJ6+uu+XvLMBBbxPgE2YpLkwt0z04odeYjdMw3EwBCILE3AWApWVBXDo0AzIzdspT7lZs9ugfbuF+F2u3vNRbswFJsAEmAATYAJMgAnUQODctXNw8urJGlo0/q5Vp1dBQYU29GGcMg5m9pjZoEmp8ZlAEd5vqvXC6lvSYfnZc1CIzyskiV4wH0MfaqOSSHWu9pmfXQI79EMf3tAcmrXkaBqudp55PUzA0QmwAczRz5Djzm8ITo2ydFLGUIrzpXsSjhtVQk+J+Tsm0eDPGgns3Kl9OEfh5GqTCxcuwBtvvCGMUlRGbx6DQ9Bzy2C7pg0K50dCofKqy9tF+48fPy7CIFKIRRqPwhWaC4tHIRONDWAUTo+kupxdVE8GsAMHDoiwjqJx1T99+phPyoveckC5sNArC1atWiVCC9IhFE6Q5keGM8pTVV8h45G+wYr6IYMbCYVcNF47tY2KigLKpSYJhRuk8JQUyhK9yaRqg0/K4UZsjYUMTpTfi/Kfkdx5551ivcbtzG1L3yUKZ6lvpDPXluooTONHH30kwjiiF5MIM0nGO0ky0lIxn5dkcMGftQJtuVen1lIT7advEMR3HijKufmYY6wB/A075i0ioC6rhLyfzkLx/iwZiF/7cIi4qz14KMz9CZKb1blAxq9/NqbB+X+y5WOH3dselGG+8jYXmICjEygtzYRDh2dg6F3MSVgl8fH3QetWs/Dnybr/Z6T++bNRCfC1eaPi58GZABNgAu5HYO+lvfDghgehUl3pNItvaOhDuk/IeOJJKMR71YZI6J2TIBBzZLuyEKvNKzD0YZk29GFYswDoO6qFKy+Z18YEmICDEmDjhIOeGAef1kicH+UAo9ftL6DS6z7Oc8WDk2VxPALkuUQSG4seNTXIuXPngIxCubm5MGjQIJFzKyQkRBhrKE/V559/LjyUaujCYBcZaEgwpKBBvfFGYWGhqKIcXCRk7DEn5uqlY6Kjo80dIvKY0Q6JgX6jmnJ4kZGL8mKR8YY8sEg+/vhjIG+4adOm6XdT5zIxNRYyupGY20f1tJ+MSZJIbE+fPg1z586Vqk0+Jbb6O8h4N3bsWOF9RfXkhWepSBxr+y5J/ZEXHuUAa9kiEcaMSIZmkaHg66P1jPjfp19BWSkaWAsvSc0BVNo1hgZTXjAPAH98B0DZFEDhL1v8KY8Yi3UIqPLLoXB7BhTuugiaqrjx1LN/l0gIn9gWPLys9yBfrVLDGTSwHVh/AbLTtP/naazOQ+OgBY7HwgScgUBZWRakpH4AGRkrMfZvuTzlpJbPQkLC9Aa9HCF3xgVHI8DX5o52Rng+TIAJMAEXJ1BcUQyzt892KuPX3e3vhl7NejXozOThc4OGGr8U+MwjCiPQuLoc33ER0k/kimXSu6H0QqG3j3Wjdrg6Q14fE2AC1iHABjDrcHS3Xl7BBdMTYLrZXo/KYkMCDQkraMNpWb3r0NBQ0Sd5b2G+rGr7f/vtt4VXEYXOmzp1qkE7Ck1IBrC6iGTM+emnn2D06NG1HhocHCzaYF4qs23N1UtjUBg/c3LxotajSGqn36YmLy4y8IwaNUoYb8iLioyCmD8NyKDTpEkT/W4apSythwxZP/zwQ53mQEYzCkuJ+caERxZ5u+3evRv8/Pxq7Uf/u1Rb4727dwl+NwzuB+u+eBcUCq3hi44jL7A3l3xRfRe++F1o2gEtfz7Vt+E99SZQkVUMBdvSofgAenypyKFYJwG9oiBsXGvwsFI4wvLSSji+/aLw+iq4WqobCEsRcUoYMC7JoI43mIAjEigrz0Zv5o/Q8PUl/n5pQ3dq5+mJf1fnQWzMREecNs/JOgRewW742tw6LLkXJsAEmAATsIDA//b/D9IL00VLpUIJ18VeZ8FRjdekRUgLeLDzgw2aQEVmJmS98abchz9GTVHEmH/JVW5kVPAMVEI4vqzqGRhotMe1NovyymD792fkRXW9Ph6atTB9yVZuwAUmwASYgA0JsAHMhnBduOtOuLaVqGz8cuGTbO+l9UP3/71798Kvv/5aowHszBntRdT48eNNprh161aTOqqQQvmRV45UlhrSuCR//vmnRQYwMs5R2L5Dhw5hWKkCk1CAFMrQWKQcXhTSz5xI9ZhM1NzuGuseeeQRYcAhzy8ygJFQ3ixHEGJFxigKSUieYfrGpZrmRznGyIhXhDHVf/vtN9i2bZvIc0ZeYB9++GFNh4p90jml3F3kIWc2DCJ5cRVdgTP7tohjRg8frDc/fD0tIBx27zsEJaVoDPHEt9SCmunGxX1CAtDzi41fOi5WKFGYjPKUfGH4Kj1+1aRH70h/CBoSB2QAq8k4bHJgNRUlheXC6HVkawaUFRs6MntjWMX2A6Khz6iW4K3gNxWrQcjVViRA+bry8vaCWs9ry9Lur107gCFol6PhC3+z9CQ4uBu0SnoOXyboq1fLRRckwNfmLnhSeUlMgAkwAUclsOfSHvj6xNfy9Gb1nQWjk0bL265YoPuUiy/NlvN++SQmQvPPloInPhtgMSWwbeUpKC/R3l8FR/pBn9EtTRtxDRNgAkzATgTYAGYn0C42DMWFMn0y6WKL5OXYl8DDDz8sjBuvvfYaUO6mDh3Qs0ZPKLdUXFwcJOKFJgkZjcj7SRIydhjn3pL2RUREiCLlC2vRooVULT7HjBkDSUlJ8P7778PQoUNFni+DBrhBecK6du0KAQEBIrwgGWeWLVsm8lpRLjJJ/vnnH/jiC1OPoYEDB0Lbtm1Fnq/vv/8ebr/9dukQoG0y8FBeLcofVle5/vrrxbHk+VaKxhrqh9bhCEIhER9//HGgc/rEE08Aee+R8VBfyPuNDHf655s8vygfGuUBu/HGG4HWSOebQj1SvrQ77rhDvwuTcs+ePWHAgAGwAxMT0/mZNWuWrk1lGeSknYRATQl6k/lAYpzWsLXl773w+P13AwSi51xgJGTl5MKjz83RHudBBjC9N/sw1xeLdQlo1BooPZYDBVvToTxNm6BafwSf5kEQNDgO/DpEWM3rKyejEH5edBCKr+lCxNGYfkoFdE6OQ40FfyV79+mfBy7bhgB5bqVdWArp6LmlUtElVsMlKKgztGw5EyLCh1jFWNzwGXEPNibA1+Y2BszdMwEmwASYgJaAFPpQ4jEkbgiMaqm7L5fqXe0z79vvoAjvL4VgPL9oetHS6N7W1dZc3/WcxZDy5w5ekQ8fOrk9KDj0ocyDC0yACdifABvA7M/cFUbciIvo7woL4TU4DgEygCxZsgRmzJgB5DFFhqnWrVuLcIfkGRYUFASbN28G8nii8IcTJkwA8gKjMIAU9o88hcgw8s0335gsigwolONr3LhxwsBFRpiEhASYPHmy8Pqh8HxkdBs5cqQwnHTDUAZk7EpLS4M9e/YA5R0jQw3VkSxcuBA2bdoEb775JuzatUscQ/u//fZb0f/q1asNvI7IU4UMVMOHDxeeTbQ28o46efIkUFtaGxnOzHoqmazGsIL6JmZPPfWU2OEo3l/SLGfPng1kGCTPrV9++UUYsOicZWVlAYU53L59u/DukgxgxGPx4sXQt29fYWCkfshrj8Jb0nl58MEHoVevXvhgt+Y3yFasWAHJycnwwgsvwKpVqyB58HWgKSvCMU/B+m074cTWHyAxPgZ6d+sIA/t0hx/WbYIB46ejEXIQUBhL8kQko2VMTIy0FP60AQFNhQqK9mVB4Z/pUJlj6LlCw/m1DxceX76J1g2XkZWaL4xfZUU6r6/gJv7Q/YZ4aNs/mm/QbHCuuUtTAiUlaZB64RP8+/Idem4ZGmJNW1tWo1R2EIavyIhhbPiyDJmrtOJrc1c5k7wOJsAEmICDE3h739uQUZghZhnkEwQv93/Z5a85ytMzMPSh7sXX8KlTIaBHdwc/U40zvdKiCtiK3l+SdLguBuLaYuQUFibABJhAIxJgA1gjwnfioZ/Hue9GfQl1PqphchasYGEC9SFAxo1OnTrBW2+9JTx+yBgSGRkJXbp0AcoBRUJlMoS99NJLsG7dOqisrBTeWWTEonB75gxgdGxqaiqsXLlSGK3omCFDhggDmNQnGWnIQ2nNmjXCwEbGqOjoaGGMmzt3rpiHmAD+ExUVJbyLyLhCcyAjGBlLyIAXiLG8ad5SrjDpGDLokDFt3rx58McffwhjEK3tzjvvBDIS0fH1FcqFRl5TFGLw3nvvrW83NjmO5kQ8yCBFXnPEt7CwUOQoI2888g67+270vEIhD7377rsPKHcYGbzIg0yS+Ph4WLp0Kdx2220wadIk4U3n41O9dw71vX//fnjz9fli/MVLPgA/X/L4ioGnH7oHmkbiRbjCH7zCouDndRvgJTwHdC4XLVokjKr0naHvmGSYk+bhyp8albphv+YYFkSDuboqjXJomWNGY5UcyobCHZkYRoTS1uiJlwcEdG8qPL4UTbVGZ729DS5mns6DNe//AxWlKtGXws8Lht7dDpJ6NkUjtEeD++cOmEBtBAoLT4lcXZezfgGNRvs9lI4JCGgBgQGtpE2LPz29/KFp05ugSeSNLv8QymIo7tWQr83d63zzapkAE2ACjUJg18Vd8M1J3Quns/rMgqYBTRtlLvYaVIQ+nP0SqIuLxZA+eJ/Z5Mkn7DW8042z/fvTUJKvfbErMMSHcyk73RnkCTMB1yTAT3pc87zaelVLcYBE1CGoqagHUfNQjYUMY/cbV7rR9j7M6dRj3759NS75+PHjYn/79u1rbMc7nYPAiy++KPJOkUcaeZXZQyg8IIU9vOeee2D58uX2GNI5xii4CFBwyXSuPkoAZRQAhTJEDzp3F3WZClT5ZeghZ/ggvq5czuSkQkVWMURsLKvroaK9h583KPtFg3JADHgFV2/crFfnVQelHs2B3z48DJUVaOxD8Q30hlGPd4OoxOCqFvzBBGxDgB6e5OXtQUP/J5Cds8lkkOCgLpCQOAMNWMPxZ8nTZD9X1I0AhcLFlyD241E963ak07Z2x2tzi66znfaM8sSZABNgAg5GgEIfjvt5nOz9lRyXDIuGLXL5F29y8SXaS6/M1Z4NfEk28asvwR8jk7CYEriAIe1/WfSPvOPmGRiSuxumGGBxKQJueJ3tUufPXReje73eXQnwuutDYKreQYlYJjUn7m4AM8eE61yEQGZmpkl4vMOHDwsPovDwcOFhZq+lUihGkscee8xeQzr+OKX5psYvXwyjF4SGL59Ax5+/HWaoLifDVzloSnVhAO0wrMkQXqG+oLwuFgJ7R4Gnr+0uSygW/fr/Owpq9FIjCUAj2+gnu0FELBpEWZiAjQiQh1fWlfXC8JWfr3sgIA0XFtYfEhMehrCwAS7/AElaM3/ahMBUvV4TsUxqTvja3BwVrmMCTIAJMIFaCeiHPgz2CXaf0Idv/kdmEz5tKhu/ZBqGhXK8p9zy5Um5shVG12Djl4yDC0yACTQyAds9aWrkhfHwNiXQwqa9c+dMwAkIUB6qVq1aiZCNFPaQ8lmtXbsW87ioRb4rPz8/m66CjG0UTpA8DClf1a233iryZtl0UGfpXIUh9fJSdbMlg1dIvAh5qKt031KNhi+vBnieoDedh7cnhpX0tQiuVwgavvpGg3+XSPBoyLgWjHZi50XY9PlxDDenbawM94UxM7tDqA1CLFowHW7iBgRUqlLM7bUKLqR9CiUlF4xW7IGeXjegx9fDEBLc1WgfbzKBehHga/N6YeODmAATYAJMwBICJqEP+86CJgGu7dmjwfv6ixgSXw59iDmomzzBoQ+r+77s+vkcFFTldKYoG4MmtqmuKdczASbABOxOgA1gdkfuEgPqPVl2ifXwIphAnQlMnz5d5JaiXFUFBQUi/xiFPKRcXMnJyXXur64HkOGLcpBRrrEJEyaI/GPm+khJSRG5t8ztM66bOXOmWIdxvVNtk4WDjF/qKq8mT/wzF4bPBb0UTrUMa0+Wwq9pyOOroMKsx5dngAI8g1AVXvUe2iPPExTNAiH6efuHcz295zLsXnMeiq+ZD79YXpXvixYXGhUgPL+Cwm1rpK43SD7QbgQ0GjVcubIBjVRLMTfhCauOq9GU4wsR2vwHUseenj7QrNlYaB7/AOaLbClV8ycTsAYBvja3BkXugwkwASbgxgQW7V8E35/6HirURvl5kUlpZalMZmj8UBjZYqS87cyFcrxXTv/XU1CRlma6DDSAScYvTBQMMa8vwGgVlr3oZ9qZ89fkXiqC3z85ikauErOL0b/fGjShtYi2YbYhVzIBJsAEGoEAG8AaAToPyQSYgPMTmDNnDpA2lkydOhVIaxMygM2dO7e2ZmI/9RcaGmpRW4dtVJQFUFagm15Yolsbv4ThC8NRCMMXGsCMxdPfGzwxFGBDDF/Gfdp7+9DmNPjzm9MWDUvhDinsIYU/ZHFfAmp8sHPp8k+QmvoxFBeftTkIb+8QiIu9G+Li7wVfn0ibj8cDMAEmwASYABNgAkygLgTWp6yHTw5/UushIRhS/uX+L7tE2GZNRQVkPP0MlFXlZK9p8RH33wf+Xd3Xa1+tUsOGpccgJ6OwJkxiX/MO4dCmb7Na23EDJsAEmIA9CbABzJ60XWes5nVYinHcnzocyk2ZABNoKAHyRiMjiFtIeRFA/kXdUpWY78s3SLftRiWNWoNvLFaAuhA9virVJit3BcMXLWrvrymw66dzJuszV5HYOQKun9oB/ALd2xvQHBt3qVOpSiAz81vMx/UplJZl2nzZfn5xEB8/FWKi7wBvb849aHPg7j0AX5u79/nn1TMBJsAE6k0gpyQH5u2cV+vx/t7+MG/gPIj0d42XeXI+xevBo0drXXdAv34Q6ea5tg/+kQZXLui9ZFoNtZAm/pB8TzuXMJBWs0SuZgJMwEkJsAHMSU9cI087Bce35Ik6teHvWCOfLB6eCbgFATV6N+Wm4FKrfpoUAQBB7vfmmQbfzlMXVYAKDV+ARjAD8QAQoQ6VDQt1aNBnI22QUXfn6nOw/3dd1K9mLYPhpoc6g7evl8msPD09QGGm3qQhV7gkgYqKPEhPXwFp6Z9DRcVVgzV6eSkhLu4e4aHl7W1dgzn17YG58ViYgB0IpOAYRj/6Zkfla3OzWLiSCTABJuC+BObvmg+5ZbkCQFRAFHx5y5cQQPdSRuLn7QcKT9d4kaz05Em4suQDeYVN/vUvCLvrTnlbLnhgfmOle7/ElHe5WISal5j0Hd0SOg+NkzYNPn38vPja14AIbzABJuAoBNg44Shnwrnm8QVO19xNNsVO64aagLoFVfdkEjdYmAATYAI2I3AtDUBVlW/HAw0gFPoQb1jcRcjLS1WIOYeKMPeZsccfGn880evJCw1fHl7Oz4S827Z9cwqObM2QT29cuzC4eUZn8PHjyxoZChegpCRd5Pciry+12jBfgUIRjrm4pkFs7D2gUAQzLSbg7AT42tzZzyDPnwkwASbQCAR+S/kNNqRukEeeO2AuRAViFA0XFgp9mDlrFuBbUWKVFNow4oH78T7J9CU6F8Zg0dLovmvzihOgqtBGFGnSPAh6jGgOni5wT2kRAG7EBJiAyxDgJ0UucyrtupCpNYxGT1dno85AvbeGdryLCTABJmAdAsU5ACXatxZFhyH4Rpq3eyQoVmNeL3UBGr5K0PBlLHhjQkYvMn55oBHMFYTiz29afgJO7rwkLyexSySMeLAjeCv4plWG4uaF/IIjcCH1E8i68ivagw1z3/n5xkDzhAcxLOEE8PLyd3NSvHwXIjC1hrVY49o8AvsfizoStTNqLCq9dXIY9bMq1T4dww09GYDll1D7ofqhnkFdivoequF/TqxgYQJMgAkwAfsRoNCHC3YukAcc13ocDIwdKG+7aiH7k0+g7NhxsTwPHx+Ifn0BG7+qOdlH/8qEzNN5WlZ4Pzl0cjs2flXDiquZABNwbAJsAHPs8+OMs6Ob37moN6EuRL0blYUJMAEmYBsCFejVcS1d17d/OEAAqgsLhf/TlKlAhYYv+jQWD4UneAb5AOX5cqXwayr0clv/f0fh3IEr8pJb946C66e2R0MGPd9lcXcCBQXH4PSZ1yE3d4cJCmVgW2je/EGIiroVPF0kfI/JIrmCCZgnYI1r8wnY9QeolGhzM+oFVHIRGIf6KerNqNRGgyrJGCysQi1F/QaV4o+OQn0HlZ6wUnsWJsAEmAATaAQCdD+hH/qwWWAzeKbXM40wE/sOWXriBGTrhz6cORN8W7a07yScZLTC3FLY8QO9t6KV7jc2hybxQdImfzIBJsAEnIoAG8Cc6nQ51WTp6dMUp5oxT5YJMAHnIVBZBlCAXkAlevl8vNDri7y/XFToRpU8vdQFFaCpMGP4whxXXmj48sBPVzJ8Sadz368pBsavDtfFwJC72qIxwzW826R18mf9CFC4w3377wSVqtCgg7Cw/pDQ/CEIDx/kkv8vDBbLG0ygZgINuTY/hV2PRl2LSgY1SV7Awm7U8ahkDCODFwnFFf0Elf5YJaPuRSWZjboJ9XbUSagrUVmYABNgAkzAzgR+T/ndMPRh/7kQ5OPaxg1t6EP8s1VZKWj7d+8O4ffyIytzXz2679zy1UmoKNXec4ZGBUDvkYnmmnIdE2ACTMApCLABzClOk1NOklww3DtbqFOeNp40E3BwAmT4KrwMQGEPDQSNIJT3y9P1wuAJw1cxGb7Q4wu9oIyFPL2Ex5eP661dWmvRtTI4sIEcDrTSdVg8DJzQig0aEhA3/6Qwh0ePPa1n/PKEqKa3iFCHwUGd3JwOL58JyAQacm1ORitzgm+iwIeo81GTUSUDGBm4mqB+gSoZv7AovMFews+NqA+jsgEMIbAwASbABOxJILskW3h/SWOObz0eBsRSxFrXluyPPoay41WhD319IXrBfA59WM0pP733MqQe1t1vU+hDDjdfDSyuZgJMwCkIsAHMKU6T003yBpzxRNQjTjdznjATYAKOSUBVrvX4KiaPL/0IS7hJbysGx+BngGPOvZ6zEoavwgpQFeLaVUZr9vDA3F7emOMLPb68Pes5gvMctmfNeags1xr/ImKVMOB2Nn45z9mz/UxTUz+Ca9e0z9g9PLygR/evIDS0l+0H5hGYgPMQsOW1eUUVBu0r9dqNYVV1v5lBtA3rilHpaSsl7MQ3W1iYABNgAkzAHgTo/mLeznmQV6bN6xQdGO0eoQ/R8JX9Ib2voZUmFPqwRQtpkz/1CJTgveef35yWazoNiYWYVqHyNheYABNgAs5IgA1gznjWGn/O1b0FSt+neNTmVVN8tfGnyjNgAkzA6QmU43Oyq2cx6JL+szVclY8SICgaH5/hp4uJRq2ByuwS0JRrw07Iy8Nwf56BCjR8KfCNRdc3fNG6r14sgmPbKe2MVgaMS+KwhxIM/oT8/ENw7vy7MonExMfZ+CXT4IIbEWisa3O69p9SxVnf2NW2qu6UmXNAf8zPo3ZEbYmqfR0fCyxMgAkwASagI1BSWQI/nP4BLhdj9AsrSV5pHmy8QE64Wpk7YC4o6Z7KSaR4/wEo3LIF7wuN7pFqmX/Bps260Ic9ekD4lMm1HOHauzNO5sKFY1eBDKLGcvl8PpTiS5gkyjBf6H9bknET3m4IAYpos3cpvtyru79tSHcmxw6bDeClMKnmCibg7gTYAObu34D6rT+5msPor2cu6u+ob6FWdzOOu1iYABNgAhYQKCtAC8g5dPpS6xr7YHRVYfhCzy8XFI1KrTV+VeitGQ1flN+LjF8ebpbzaufqs3j6tTdnce3CIL4DRfFiYQLoGKkqxtCHT+HNu9Y4HhLcHRITKKoaCxNwOwLJ1azY1tfmC3HcTqjrUOn6X5KQqsI1qcLoU6q35JXyfUbHSpvtpAJ/MgEmwARckcB7B96D5ceW22xpE9pMgP4x/W3Wv7U7rsjMhAvTpoGmDA0I9RQPPz+IcfPQh7mXiuDndw+Cuur+qiaUlG/ZB8Pts1iRwNqnAQ7Y7v81JL/ABjArni7uynUI8C+Z65xLe67EPdwO7EmUx2ICTMCUQAmG5shNwfqqN9MwtJnI8+WLhi8MAehqkpiYKJZ0audRfENRZ/zyCkbDF4U6dDPDF8HIPJMH5//JFlzonwHjOPShDIMLcPrM61BcfF6Q8PIKhA4d/ovegXxpy18NtyTQGNfmTyBpfIoDJ1Dr+iq99Ee86g+8W54zXjQTYAJMoFoClRj5Ys3ZNdXub+iOWGUsPN2LfsKdR/LXr2+Q8YtW2vSpp8Cn6p7LeVZu3Zme2ZdlkfGrbb9mkNg50rqDu3tvZzfb1vjl7nx5/UygBgL8lKAGOLyLCTAB1yCQnJwMW7duNevi7xordMFVFKHR41qabmGe6MYfkQSg8NfVuWKJcn3pG7/C/MALvb7cUSgkx45VZ+Slt+kTBU2au6bXn7xILlhMIDt7E2RkfCW3b9P6ZQgISJC3ucAEmIBNCTyKvVPs0WOo16NSgk59kTy8JE8w/X1UDq6qkNoZ79ff7qm/oVcmz7AeettcZAJMgAm4DIH9l/dDbhkF1wEI9wuHKR2mWG1tvl6+MDxhOAQqMKqGE0nhHxvl2QaPHgW+rVvL25YU/p+96wCPqtq6K5OZ9IQ0SiCQ0DsCUpReRURAQcQuIDaev/p8lmdFxF7R50OfKAKKVJVepBdBBem9hRBIICSk9yn/3mfmTk8ySSYhyZz9fWfu6WXdOzP33nX23r7NmiFo0CBXqtbqOucPWTYXtu0VhdD6jn60/cjcfuueDWo1DlW+uMIcYOUzlmFj+wIt+BbKzSI3A7oZUNldbUFAEmC15Uxe33XwQyw/4PJDbOb1nYocXSIgEajRCLAd8myyc29tE5se0gT5paZjLRV9gRZr568gZTdaPwtpuKnD/aDyYJMT5/ZfBdugZ1GpvdBzVDMRlx8SgYLCFBw7/pIZiLp1hyEqaqw5LSMSAYmAIJgq6978WcL3MwpHKPCbm2QK9nKSMrpRaEXB3oQhP382pcC2S89RkCIRkAhIBCQCdghsvLDRnMNk1SMdHzGnPTGivXYNufv2GZdOz0n1X3wR6kipnVTWayEnvQDJ8VmimYqsi/S+qwV8Azxzs2VZsatw/c3vAOnxxm78yAL02O/IrUP9CncrO5AISARcQ+B6mMtwbWayVnVHwJsm+G8KvD0/jcJ505HTnC/JVQJBikRAIlAGBJj8ybxkS35paEdaJO3uq83kV16R8PnVPKYpmscSyUMPI+pIzya/dOQHbfevZ80XT6cB0QiJrOXaf+bVykhJCLBm4InjL6OoyKhw4uNTD23bvEOcsWJRraTWskwiUKsRqIp7c2aemfw6QGEgBWfkF2Wb/QDfygk76Udp3m6+i0L5HbnYdSqTEgGJgESgtiCgJ9/Hm+It2k5MgHm6ZG/ZArLbJ2Dw79pVkl/lvCDOH7Zof0W1DJXkVzlxLHOzhD3AHzMtzYa9K8kvCxoyJhGoEgQkAVYlMNe6QXxoRRso0BYGxFJIoPCX6chpzuctS1xPikSgTAj89ddfGD9+PBo1agRfX1/a1R+FW265BYsXLzb3M2fOHIwdOxbNyIyBv78/QkJC0Lt3b/z444/mOhw5f/68eCnK5g9Z+AWpEtgsorVcvHgRTz31lOiTx42IiMCoUaOwZw/drDiRpKQkTJw4EfXq1RNz6Ny5M+bOnYutW7eKMd58802HVqdPn8ZDDz0k1ubj44OGDRuKNOfbC7fnuXJ/P/30E3r27ImgoCDExsbixIkTomxQCSYcOnbsCI1Gg8uXL9t3XWJawWzChAkCv3vuuQeRtLvOjxwGd+vWDatWrSq2/YIFCzBw4ECEhYVSfV+0bdkUb7/4DxTE/UnOnPabQ8MGdREdRbudrPI4HtO4IbxCG2P6Z7OMY/gEkeZXC6xZv0Gs94033jCPferUKfz73/8Wc6pbt664VmJiYvDYY4+Bz6W9WJ+XvXv34tZbb0WdOnVormHiWkpI4J8x2op+7hx4zdwnX1u8noMHD9p3J9K5ubl47733wOc+MDBQnJ+bb74ZjIO9WI/P1/iIESMQHh4u1nXmAG2UJ+6v1c0dRFDX9YfKV23TxaJFizB48GDRhs8FXwf33nsveC2KZGRk4KOPPgJfF9HR0eBrjNfB1/Eff/yhVLM58jXG34WUlBSBHX/f+Ppv3749vv/+e5u6VZk4tiMRGVfzxJC+AWrcODy2KoeXY5UBgaysYzh85P+wZWs7bNrcvNLD5i0tkJK62TzDdu0+ot+6MHNaRiQCHopAVdybv07Yvk+BNboGU7C8RaOEnSylNJffQ4E1wRTxo8jbpsRXSqY8SgQkAhIBiYAFgUNXDyE5z7i/INQ3FDfWL84SrKVNbY9lWZk/DKZnIinlQ8Da/GHTTlKDrnwolrGVthBY8X/UiB74WZoNBDrfZ4zLT4mARKDKELB9w1Zlw8qBajgCz9H8B1DgN+H/omD99r45pT+hMJIC1+MH5aqWvjQgm2fpRSGcAm8TP0xhBoU1FKyF67xG4SYK/FDOGmyzKfyHgo6ClCpEYNasWXjyySfh7e0tXtq3JLveycnJ4iX/zJkzcffdd4vZcJ127dqhX79+giBLTU3FmjVr8OCDD+LkyZOYPn26qBcaGoqpU6eCCbP4+HgRV5bDBIIi+8icApNs18i0wrBhwzBmzBhBCCxbtgx9+vTBr7/+ittuu02pLubUq1cvQRDxHDjORNOUKVNEP+aKVhEm0oYMGYKsrCyxNp4/E1nz58/H8uXLsWnTJkHmWDUR0U8++QQbNmzAyJEjBRnDJEebNm1EfAvthGMiqFWrVjbNdu3ahSNHjghip0GDBjZlriYYrx49eghCkHFlbJiEGT16NDZu3CjGt+7rkUcewezZsxHdqCHG3DoAoSHB+GPfYbz+0Uxs2vkXNiycCbXa+JczqHd3zP9lLU6ciUObFk1FN2fiLuDCpcsivun3v/D6yy8AYTHEWqqwebPxZTcTQIr88ssv+Prrr8U8GH8me44ePYpvv/0WK1euFNcMk6j2wufhgw8+QP/+/fHoo4/i8OHD4L74uGLFCnG+GV8mKhkDLhs6dKggxpiAVCQ9PV0QTfv370dX2oU4adIk2pSox/r163HfffeJubz9tvKOT2kF7N69W5BmvXv2wsPjHkDqtVT4aPi9pUm8vaDSeCsp4beOiVYmV5mI5GuTSS0m+fj8t27d2nzdHD9+HK+++qr4XjDBxuTehQsXxLrWrl0rcGHiz154LUwgM4Z33XUX8vPzsXTpUrEmlUqFhx9+2L5JpaYL87XYszrOPEbXW2Pg56F+0MwgVMNIWvoexJ+fSdfw9us2u8aNJyIivM91G18OLBGoRghU9r05/xG8RYHvjXdQeJqCvZynjDmmzEw6PkqBibCtFBZS4PvxURRaU+D8RRSkSAQkAhIBiYAdAhvjeS+xUQY2Hgi1h/v00efkIOf33xVIEDx4kDkuI64jUFSoQ8IJNt5klNhOEUpUHisTgZ2fAlePG0dgv3sjP+ed2ZU5ouxbIiARkAhIBNyEwCHqh4OqmP44n8uZdKpqYTLLQOEqhe8pvEvhGwqsxvMhBWsZTQkthWwK31H4iMIJCtx+CYWKyt/0YpysNZUsx44dM3DwdCHywkAEiYFe2huIvHGAgzR0zHlnzpwxx5VIQUGBgTRfRB9EDijZ4khkB59TmzwlUVRUZGjevLmBtF4MpKWjZIvjpUuXDKSlZSASyUCkgLmMyA7R34svvmjO48iBAwcMRCKIMiLezGVEjBiIVBH5pKVmzufIwoULRT4RGQadTmcu4/Y854CAAAMRdOZ8JbJkyRJR/q9//UvJMh+JsBBlv/32mznP1UhcXJxoy2OTFppNs3Xr1omy4cOH2+STppDIv/P2Ww25Z3YZDJdovqYw9bnHRNmMac+b87775A2R9+U7L5nzvn7/FZE3tN9NAsOc7GzzGKRhZSBtLAOfY0X4HFufEyWfCCgDkTaGJ554QskSRyKLRP+8LvtzoJxPvvaItLJp99ZbbxnnP2OGTb6CMZFpNvl5eXkGIlENpFllIHLMXGY9/pfvzTAUJGTahMIrOQbSYBPB3Igi//vf/8T43bt3NxBRZV1k0Gq1hsTERHMel1+9etWcViL83SHNLnENKnnKkfHgQASm6E/J5+8jEdGGtm3bKlmlHt31W/bH8rOGLx/fJMKcl3caigq1pY4tK1QNAvxbdvXqZsOeveMMGzc1u46huWH/gUl0zVp+l6sGATlKTUGA77/ot401lTxFKvve/E0CUvxflHDcSmX20psyePMZv3FjtV5+NvgnBctOD0qUU1y6z64p16ycp0RAIiARYAT4XmvY0mGGDnM6iLAtYZvHA5NBz3fHWrcR4eztIz0ej/ICcO5AsvkZa/6bf5S3G9muLAhcPmowTIswGKaGGMPumWVpXW3reuB9djlvVWWz6oSA1ACrTmej5sylBU2VNaT0xUyZ89dSYD3fqpRxNNh0CrxlagyFLArWorFKhFCc7azxTtYBFPZSYHmdAqub3EWBzbbwjtXrKmwKr6ZIReb61VdfgV7o4/XXXxfm1+zXzCbdFCHCSomaj6y98o9//ENoC7E2FWvwuCKrV6/G2bNn8fzzzwutIOs2bKKQSC48++yzQkOLtcAKCwuFiTs2n/faa8y3WuSGG24Q47IWkrWwRhZre7F5vPvvv9+6SJh7/PLLL7Fz504RWKPMWtikX5cuXayzRPyOO+4QJhRZu+2dd94RZuu4gLV52FwkY8QaZ+UVImMc1sfacU2aNAGb8LOWzz//XGh3zf7wZTIb6GcsYvOF4U3x+ocz8eXcnzF/1TY88wZzzGQ3aWw46Y6+hU17T+EfrxjXtunv94Q5yadfeBUbSNttJ+3yY6081u5jE4S8Fj7HijjT7uIybsPm+1gTy5mwRp/9OWANJ9Ze43PKZhWtha8jNr1I5KY5m+fE5jbZJCRfHywG8lmlyyyEN+2se/vFN8X4P8yai/ZvtBTl2mv83g+4oX0nPPrAJBHnDy9fb3gH+4ijOdMq8p//8E8tQESYmJ9VkdCUZJOFivD8nQl/d1izi/tijTA+h9ZCJCs+/fRT0Z+SzxqKrBW2fft2obUYHBysFFXake7wkXD8Gg5svGAe46ZRzaC20ogzF8hIlSKg1xfhSvJqun5mITub94lYixd9d4cjNuYJBAe3ty6QcQ9CIPHUCexbuwLXEi+WuOq2fQag+0i+RZPiZgQq+978TZovh7IKb9m3qNCXtbWsLxGQCEgEPAyB49eO41L2JbHqIE0Qboq6ycMQcFxuNj3bKxI0ZLASlccyImBr/jCijK1l9TIjoKdXjSueoremRcam0d2BHo+VuRvZQCIgEXAPAmr3dCN78TAECmm99Ha7RAmkUtMvfYn13FXIWmcfUMilcB8Fe/KLsmzmwwRXXQrzKCjkF0WRT4FZDb7LepLCdSfAaA4eIYqPItIuKnW9/BKfzdgx0cVx0rqxaUOaWzbpkhJsko6Fzd05I/AU/1xsXo4JMDaxyOMx+eGMFGCCxZ4AYxOLLMX57OJ8JsDYnJ49AcZmCJ0JmxOcPHkySEMJP//8szC7x/V++OEHMT8mzti/U3mF/VqxKUp7ady4sTDjp+TnZmcLgioyPBQzvp1vzPYmEsw/1Kzazz6lGD9FmFxj/21swo/NBiq+zpjkYtOEvDY+t0xmcR0mRuyx4zw2H8kEIBNkaWlpIA06ZQgbssycSRE+b/bCRCeLszUrRJu1XzE2o8hj8bz5mjHoDdDn0s8dHVmKirTieIJeCBuK9CJu0BnLunW+UaS9/NREfGkcfH2JQtNHDpn7YFOW9evXd0qCWtdV4r8TcciEJF/XbD6UCVtr4e+GPQHGpkbZj5698LlmYVLV2bVuX7+8aR2Rh2f2JmP/hgtIvcgKuUaJiA5Cqx4NlKQ8XgcEtNpsJCYuxoWE2SgoSLKZgZeXBlEN7kRMzGMICDCaMrWpIBO1HgH+HY4/tB9/LVuChGOHXVpv43YdXaonK5UZgep4b17mRcgGEgGJgETA0xGwNn/Yv3F/+HhbNgCWBZsrmfkoMD2HlKVddatr0BYhd/NW87RyuvXBhVR+5SOlLAjw8+rZgynmJv4xwR6Jo1dRLlS5V804VGYk8NSvCL1kNEZgUPkgqf9H0KYVVOaQou/oMPInrir/e6BKn6AcQCJwnRCQBNh1Ar6GD3uI5s8E0psUnP17RJrKD9KxqqQXDcRv4JZSYDMrIyh0oMCEFqurGFkOiphkkOm4TsmwOm6nON9VcZ++FCr/X4oG8XThl+wsCuFQHB7nzp0TvqmY8Ojbt68gSVjzhcma8+fPC19JZCqvuOYO+azNw0ImBR3KrDOyiehhYR9cLExKOBNn+Uoba20d67ZKvoKBdVlJPryY5Hr33XeFdhD7nWL55ptvBPnDfqMqIuw/zZkwOcWklRC9Fmlx+wVBdTU1DdM+/cZZE6d57M+Lfb4xOajRaECm+8B5TLSQuT9BgHFDJsJYrP1/cfq5557DjBkzhA841kzj64bMJHKRIMWY0HQmzrSkeE0sJZWRqUxzd8o1w0QYh+KECSx7iYpqAHW9AKh8HMlF+7rK9VDad0Jpx77qWNPLz89P+C1jLcDAwEC6AVaBzHti27ZtRGI4fjdKOtfctzWxqIzljiP7+jq2MxEHNycg+5rtvNQ+KvS/tzW5gJM37+7Auqx9FBRcRcLFubh0aT5p5mbaNFep/On7dg+aNH6ErrUomzKZ8AwEyD4TTu/ZLYivK+fOeMaiq/8qq+O9efVHTc5QIiARkAhUMwQ2XthontHQJkPNcVcjvDnlucUH8et+1zeEutr39ah3w9XTeD/LeC961b8OHlpBG7JWXr4eU6nRYzbQeuHBbKOlllwvA+5ctBcGD3vMutHrJOb5vI9AL9vnzqo4sZ8VjMIX3yXSUBwqV05MvxV+qtLfNVTuLGTvEoHqh4AkwKrfOakJM/qSJsmaUUwsvU1hCwW6EwFv1R9AgTWoWLvqaQpVJaRPLOQKfbK6jf0WYya1mLRTCLvWFGc5ZTzYfLL6RhyF9hSaUbCorlCiqoU1TDxBlJfwrKFC/rKKXTKbamMCgvxOYcKECTb1FixYIAgwm8xSEgrpsXz5cowaNaqU2jBryly5wpeaozjLV8a4fNn5zXpSEn99nBMwJWlxMTEykswFMvHBGlZMCrLG0Pjx41G3Ln8FK1GKSOsuLR51/FRikC4d2mDfTnpgC2lo1vwqaXTW6GICbOPGjWZtLUXLi4/vvfcerl27Jggwxo/sTJu7Y82mL774Ah06dACbl7TXTuLroDJFOZ/PPv0MPniJfgJNml+ghwjvUD94aYyYWM/BO9RXJL0DfVwiv7iy9XfCuq/i4mw+lM1E7t27F+S7y6ba448/Lggwm8zrlCDXBvh77Xkc3JSAglz+ubUIE19tezVE5yGNERJpJDQtpTJW2Qjk5saRNuw3SLq8jIjtQpvhNJpwREc/hOhG99N1Fm5TJhOegYCWNgKc2LkVe1b87GDq0IuI9ra9+6Pj4GHQ+BX/3Q0IcW6q1TMQrNRVVsd780pdsOxcIiARkAjUNgTOpp9FXAa/hiBjGmp/9GrUq8xLXH4gsdaQX7z4m5OOmjHY3YD2N1fAwom5Iw+MNC+yECLn1DqPI7/8aE/7p5qvrgv5dULfGF/pSn/P5IGXpVyyRKBKEZAEWJXCXWsGW0wr6Uzh3xS+cbIq3kvyIQWuV1VSzzTQE3Tku8YhFP6kEEPhEwrDKLCKzwAKLMobGKM6jzHP+lPJd64GY12zeCfrxbM4tu1lihC46aabxIv7tWvXlkiAnTlzRuA1duxYB9xYw8WZKKb8WJNFiSv1eFyWHTt2uESAMTnHmkaHDh1y6huJTRnai+LDi7VwnImSb03yOKvnLG/KlCmCAGPNLybAWJjsqDQxmMwMXj0hhggKDED71s1x9NQ5XNP5I9zFhxImuZjcYw0vNpHIJhGbNm0q+mRtL/ZrxuYc2QTl6NGjbc4bawGyFhqbSLQnv9hUIZdXprBZStaq2rFtB/CCwTgUrUUd4QcVmTZ0Jqpy+LFi7S0m+ZjUZPOYynXkrH/O4+8G+z+zJ78YK2fXZXH9VHb+nyvOYd+6eJth/MkcZMcB0ejYPxp+QRqbMpmofASyso7ifPzXZDZzLQ1muqZNw/r7x5DZzMlk7nAMfQ/9Kn8ycoRqh0B+TjYObVwnfHzlpF2zmZ9a44MOg4ai2+1jUKeec81omwYyUVkIVMd788paq+xXIiARkAjUSgQ2xG8wr6tPoz6CBDNnuBBJzS7AtJUWwigyyBf+tLmsxgpps/W9YlnP6dY3onF48Ztsauw6q2DibS9aBkkPU6NxkPNnVkut2hWbUrgIMdpksagCaJDqVTWb+VIELF1sAABAAElEQVS9wvCB3xQ0CAquMkBdfB1TZfORA0kEqgsCnvWrV11Qrx3zeIWWsYLCIxS6UGBCiUmj/RRmU9hNoSpF2dLC5Btreh00Dc53THdSOEWhP4WbKbgyN+6HxfZNoDFPflYCAk8++SS+/vprTJ8+HWzSrl27djajMLERHR2N2NhYkc+kEWs/KbJ+/XoH31tKWUREhIiyvzCFZFHKmFxhU3H//e9/MXDgQOHnSylTjuxP6YYbbiA/NwFCw4Y1rNj31Ntvvy18kSn12BfVvHnzlKT52Lt3b7Ru3VqQEEuXLhVm6pRCTm/fvh2tWrUC+w8rqzBZxG3nzp2L/Px8Eed1uFXo4QMFWUD2FXJwRZpfdvLcM0/jkSnPYNKkSQIXRXNJqcbEXFxcnI0WV7169QRZwz6r2AThPffco1RHr169hBk/Nu/IomiGKRWUa4BJHWtSk81UPvroo2SyzVarSGnnrmNEUBjuvfNuzP95Id6d8QFefPp5+DUIttHsOnv2rCDJ7K+3ss7h6aefBpu6ZFJzw4YNNmYamdhijUPFhCbjwoRhYmIiFL9mbAZl2rRpOHbsWFmHrpT6iafTsW99vLnvOnX90XloE7S5iUxDumAW0txQRiqMAF8b6el7iPiaSdqWRObaSUhIZ8Q0eYy0SYcQWa38xdpVkslajUBWagr+XrMchzetQ6Gdr00f/wB0HjYCXYePQmBoWK3GoQYtrrrdm9cg6ORUJQISAYnA9UfA2v/XkCZDyjyhaSuPIY39EpM0CvXHb//sh0DfmvvKL+8obdD63rjBU0UWQWZ9NJksbciNcmW9MDJT8/DDq8ZXYCq1F+a+0hc+xWzaLGvfNaI+++H6dqV5qr6jPkPDrg+a05UZaUid/1iZA8i+JQISAZcRqLn/hi4vUVasRAT+oL45VAcx3hkBrPqhkF/KvPiN/XoKTNb1oMD//hkUWJi4cyYhpkylnrM6St6NSsTuSP+0sNhtsyuUSVsEmPCaOXMmnnjiCaHpwsRUy5YthblDNunGmj5btmwBazyx+cNx48aBtcDYDCBryKxbtw533303Fi1aZNsxpZgkYh9fY8aMEQQXa3DFxMTgwQcfFP6nfvnlF0G6jRgxQpAvnTt3FmRXQkKC8PHEGkVsppAJMJb3338fmzdvxocffog///xTtOHyxYsXi/6XLVsmyA9RmT5Y04kJqqFDhwrzhLw21iQ7efIkuC6vjYkz1ioqq3DfjBn7xGJxu/ZXPn0Fsi4T8cVu8ezEl74+wQ0w6cku+PvISXH+mExkArNJkybChCETX0zwsU8yJjithc8LnzsWjivCGmFMGhbn/4v9ojFhtnDhQvC5Yk0w9rPGBBH7v+K8AwcOKN259ajLLoQuvQAzpn+MM3FnMe2Td/DT8sXo07eP8AvH5BObo2TfYGyKsaIE2OTJkwVxytcHfx/42mHzljwOX4NMOipmUv/5z3+avz/83WDfakwwMvnFZPHKlZYbf7eC4mJnBXlabPyeiDjTtoJGrcMw6pnOdN17udiDrOYOBAwGPf2ubiXi6yv63uxz6DIioj8RX0+QCc7u4rfLoYLMqPUIpFw4L8wcnti1HXrSnLaWwLBwQXrdMHQ4fAMCzUV6uq52J+42m24yF9hFWoe3RvcG3e1yZdKNCFSne3M3Lkt2JRGQCEgEajcCCZkJOJl2UixSo9KgX3S/Mi1447ErWHHQ4l/onTs71GjyixefbfIFzfHgAf0l+cVAlEPiD6eaW0W3CvMs8ktbCCz/P3r+1BsxaEp74rs8YMZDRiQCEgHPQUASYJ5zriu6Ul/qgLeIkxoIbqVg3FpEETvxoTTbUOK3In0pFFePitwqxrtFIL2YXhWCTNGZ5/rdKLSiwESVtfD3oikFViNhQk1KFSHA2jts8u3jjz8Ga3gxORQZGYlOnTqBiQAWjjMR9tprr2HNmjVC24e1s5jEYs0jZwQYt42PjxeECZNWrCHUv39/QYApfbL2FvsXW7VqlSDYmIxizRo2O8caNDwPRerXry98T73yyitiDkyCsYYXE3hsto7nHRKicKjGVj179hSkCGuNsd8rJiO4z3vvvRfsu4nbl1fYF9rzzz8vCI+HH364vN04tsslU1fpFm0dmwp12wAa5esEoUE3fPhwQXLx+tLT0xEeHi6IsBdeeAEPPOB4o8mk1+effy5esttrrXEZE2CMNZv1s5fvvvtOmE3k883ae0wKsQ+3t956SxCj9vXdkdbRjkomv1hCgkOw6df1mP3rj1iwaAF+/vlnoYHH82Wi6rPPPhOEZ0XHVchTJvnYzCWTrAUFBeLa7Nu3r43ZTiY/mTycMWOGIFyZ6OU6TBjz/K43AbZ94UlkXcsXkPgGqDFkQltJflX0AilDe72+AJcvr0D8hW+Rm3vGrqUK9eoNR2zME0TI22rf2lWUyVqMQOKp4/hz2RKc+/svh1WGN2qM7iPHoE2fAVBb7b4u0hdhbdxazD48G2czzjq0s894oO0DkgCzB6X86ep+b17+lcmWEgGJgETAwxDYcMFi/rBXw14I8glyGYHM/CK8tsy4qZAbjenSCANa13O5fXWtmLVho3lqQVabJc2ZMuISAnGHUsz1YjtZ3mmYM2tz5PcZQLLJjKaGNjOP/Jx3J9fmFcu1SQQkAsUgIL/5xQAjsx0QmEQ5syiMpLDGodQ2gwkyrsNt5lCoCuF/8iQKORT4bo+2etgIk3I8r3spLKTAc/uOwjwK9ozBIMrbRGE7BdoiUm75m3w6df37b3t+zbY/1hZhsffbY1tLpmoKAq+++irYdB9rpLEmVFUIk4VMIDHJxH6z3CJaIiquEk+s7JYC/V0ERABB9PVS8zs3zxKDVo+i5FxAbxAL9yJzfezzy8tb5VlAlLDakn7LTu+5gt++Mz18UB/DHu2AFjfyT7WUykagqCgTlxIXICFhDgoLk22G8/LSkG+vO0kj9jHScG1qUyYTnoEAm8KMP7gPfy5fgovHLC/PlNVHt+2AbkR8NevSDV5WWsr59B/xy+lfMPfoXCTmJCrVSz0yAfZSj5dKrVfRCjfeeCP2kVA/xWnpV3SI6tB+Ek2iOt+bVzZGLt1nV/YkZP8SAYmARMAdCNy3+j4cTjksupreezruaHGHy92+8uth/PTnBVE/ItAHG5/rjzA61mQppM2rZ4fx6xviK2iDX6vdu6AyWWOpyeuq6rkX5mvx3fM7oNcan2EfercXgsP9qnoa12e85BPA133o+d20J3/Ye+QQZcr1mUstG9VD7rNr2VmTy5EaYPIacBWBMVSRtaHWuNBgHdU5TWEchTkUqkJ4WwvbvrufwhsUXqOgyFCKMBPB5gx5bixLKXxA4R4K/6GwlwIL3w28LWLAV6ajPEgEHBCw9rOkFB4+fBhffPGF0HxiDbOqEtZqY3nqqafcMySTXmnnLeSXNxFekS0Bb417+q9hvfALYm1avpn8ApFe6kh/ehks95C4cipZ62vbAla6NUpr8vclyS8FjdKPOl0+srOPQa88vJXeRNQwgEwdpmwh8msR+crLtmnl7R2ERg3Ho3GTSfDzbWBTJhM1D4FcMlHLZpO0eq3LkzeQD8GUQyeQsGEnsi8mObSL6NQGjQf3RkhsNEgXGNeSLZt5Dl49iB+O/YBr+VxikUBNIG6JuQUBvMO2GOlWv1sxJTK7HAhU93vzcixJNpEISAQkAp6HwOWcy2byS+2lxsDGA10G4Y9zqWbyixtNG92+xpNfvI6sTZv5ICSQ/ENL8ktBo2zHhGPXzORXRHSQ55Bfeh2wgt6NKM9Pjej+s+fjZQNP1pYISARqFQKSAKtVp7NSF9OFeneF/FImwdpTtymJKjqyE6SeFF6l0I/CXxRiKNxJgf4B8SgFxURipinNRNhWCgsp8JucURRaU+B8JtSkSAScItCtWze0aNFCmGxks4enT5/G6tWr6SW1XpgBZF9UlSlMtrG5RtYwXLt2LW6//XawmUW3SCa9DC3KM3VFJE9YrMeSXwyCPrsIhgL+CTGKOtxXkl8KGKUcDaQxt2nuMRTkGl/MB5PWXL/xrUppJYsZgcLCa7h4aT4uXpyHoiJboqG8CPn41EOTxhPQsOG9ZDI1pLzdyHbVBIGUvBT8dPwnLDq5CJmFfFtTunjrvNDiYiDax4UgJNd2U4Pey4BzDXNwuHkGMoLigZPrKZTeZ5hvGB5o9wDuaXMPQnzkdVU6Ym6rURPuzd22WNmRREAiIBGorQhsusDGZ4zCfjLrsJ9lFyS/SId//3zIXHNI2/oY0THKnK7JkSxr/19DLL6ia/Karsfcrc0fNvUk84d/zQIu7jFCTj71MIr2vKu8r8cpkGNKBCQC1QQBSYBVkxNRA6YRSXO8UoZ5ct2IMtR3R9Vk6oQZANb+YtLrJgpZFFZTeI/CHxSsZRklWE2HCbOxFJixOEOBibQvKBj1xCkiRSJgjwD7W2JfXwsWLEBWVpbwP8YmD9kX14ABA+yruz3NxBf7IGNfY+PGjRP+x5wNcv78ecyZM8dZkUPes88+i1A/FRkS5a+SSUIaAj4BSsrjjvpCHXSZBeZ1q4J9oPKVf51mQEqJHNiYgEsnjfsO2Nz6kInt4OMv8SsJtry8C7hwYTYSk5YQoU6ah26QwMCWRHxNRoMGI8nvmq8bepRdXE8E4jLihOnBlWdXolBvb/HZ+cx8C1VoHR+MthT8C21fAGhVepxqnI2jzTKR428h+533ZMltENgAE9pPwJiWY+Cv9rcUyFhVIVAT7s2rCgs5jkRAIiARqLEIbIjfYJ77kJgh5nhpkc82nsL5VDLRThJMzydv39FB+FYurV11L9empiJPWDGmmZL55SAy9S+l7AjoaSNi/JFUc0OP8f+VRpu4Nk0zrxv9ngfqt7OkZUwiIBHwSATkWyiPPO3lWjSrgwSVoSXXdc+buzIMSlV5mzwTWBxckd+p0m2uVJR1JALWCEydOhUcrpdMmDABHEoTJsCmTbO6ASyhwYQH70dooNXX1pd28gfWLaFF7S5i7SUdmz40UeFeGm94h9Rse/pVecZSLmbhj+VnzUN2vTUGDVuEmtMyYotAZuYhxF+YheTkdVRAZkitxJfMFPr7N7HKcS2q0YShYdQ4RET0pxciRG5LKTMCbAI1uyi7zO30Wi20ha6RU652fjb9LOaTxtfOSzvoZ8n4w6Rh/4wkUYFRqB9Y36ErdZ4BEcfzEH46Hyo7C4k6Hy+ktvFDSjt/6PzroY1Da+cZTHYNix2GEU1HQOOhpnGdI1PluTXl3rzKgZEDSgQkAhKBykIgNS8Vn/39Ga7klmVvcPGzodsM/H1ln7GCwQs/7wjFih1/Ft/AVML3AbvPWsiNV0a0RYM6vJ+3+og2JQXJH30M7VWrzZUuTE+bTpvnGBiSgK5doQ4Pd6GVh1YpoHvUjW8CqacdALiSGYX87LtFfoAmB/W2PWj0cu9Qs5ZlpJ0nazZGYhj1iPjq4+qrwVqGg1yOREAiYIOAJMBs4JCJEhBIoLLuJZTbF3WjjAv2mTItEZAIVC0CrI3GL3BLFa5zjciKAtMbUhX9PYTSC3dW2/FQYc0vQ5GJiCAcvNn0oQfj4eploCPMTv51GXtWx0GvM1579WKC0f32pq524TH1+LuZlrYL5+O/ouNuh3UHBbVDTJNHUa/ecNoAa2uuzqGyzHArAmxScPHJxVhwfAGS81x/cROco0aHcyFofikQar37SUemQe9D42LWynuASpfgyLq48bY70HHQUNLIDCi9gaxRXRGQ9+bV9czIeUkEJAK1EgG+b3tpx0v4M6l0gqo8AGjzYvBnfBE1TSlT85uaheOe7sXdG5SpK7dVZqwu/et55P5ZMayCpPnDks/JGtJuOrjAoQ4/2h9If9GcH6veBa+4rea0Z0ToPQabPlTLDayecb7lKiUCJSMgCbCS8ZGlFgS2UnQKBSa29lIoSW6kwl4U6N9GikRAIlAjEGCzhwVZlqmGxXq23698rfD9pQDiXYdMH5IGmJTiEeAH3bzMIsx7bRdyMyyaL2ofFYZOag9vb/eTAcXPpnqXGAx6XL26QRBfWVmHHSYbHtYHTWIeRXhYb0m6OqBTuRlJ2Un44fgP+PnUz8jVmnaPujBkWKYGHc/WQWxSAFQmrSwXmlVplboxTdF95Bi0urkvvNXyEaBKwa+cwbZSt/LevHKwlb1KBCQCEgEHBJacWlJp5BcPVnStj8OYpWWEBmjw/phO1e5+MX3p0gqTX96hoahDfq6lFIPAybVOyS+ufSa/N84V3Gxu2Np/iznuMZG+pPkVza8vpUgEJAISAeLCJQgSARcR+JLqPUlhCYXbKByn4EzYgg7X0VGY6ayCzJMISASqGQKFOUBmkmVSQWRGyzfYkvawmEGnh5ZNH5rEy08NVaDUvlHwsD/qtHrkZhaCNb+y0/NtyC+NnzeGPNwOofUD7Jt5ZFqvL8LlK8sRH/8NcnNJ49JKvLy8Ub/e7WjSZDKCg9tZlchoVSBw8tpJzDk6B+vi1kFrsLUV6OvtC00xGngRqWq0Oe2PqCuOu0uLvGn7rZdRC9I9a/CCmhx4a1REyLto0tJL5YWoFq1x4+13IqZj52r3gsw9uHhsL/Le3GNPvVy4REAiUNUIXMy6iI/3fmwedlyrcSiLvy5zQ1OkiO6fX112BEkZxmeOG+o3xT/v5j3ErosXbbhpGxWMiCBf1xtVQc2iK1eQ/MGH5pFC774bwcNuMaddibDVDb8OHcj8PJnkl+KIQC5p/a98xpLfdhRtVZ8o0rn0aL/9e0tRu05Aw2HvWjI8IeYfRvbBO3vCSuUaJQISARcRkASYi0DJajhJGLxF4U0K+ykspbCZwkUK/HYnmsJgCmMp8B3YGxS4jRSJgESgOiOgoxe9bCfb5E8GGiIqghtU5xlX6txYi0mbVkAUvumlNb08VodJ04fOQGesctILBPnF5dav+QNIY+6GQY3Rvl8j+PrLWw2tNgeJSYuRcGE28gsSbeBUEZkRFXU3mTqcTH6+XDdfcyD5AOYdm4fjqccJe2v0bbqXCRcQ4Gs5Mcf2vHCzNn7NMTSuKbwuZhJx5NiRTqdDdmqKQ0FMpy7oeefdiG5bO5zROyxQZlQXBOS9eXU5E3IeEgGJQK1GQE+a+1N3TUWell0vAs3rNMdLPV4Cb5Apr7y75jguJhrv+wJ9vPHFuH6IDqv5G8b4nurytLfIkka2gEYT0wT1X3kZKr/q5Z+svOet2rRb928g+4pxOrx5deTn5DAtXLg+2Pa/I8jPuyrKgug5tvfEnoB8Hqs2p05ORCIgEbg+CMi3UtcH95o6KhNgvC16KoX7KNxLwVr49RAbrX6VwnvWBTIuEZAIVEMEtGSmLvUMkT0mc3WkgQI2feiiZkE1XFGFpmTQE/l1LR8GMn+oiDrMD17SdJ8Ch80xP7vITH4pBWoyEznooTZo1b0BvDXS5GFBYQouJszFxUvzodVmKDCJo7d3EKIb3Y/GjSfC17euTVlxCX6psDtxN2YdnoW9V/YWV03mVxCB7g26496oO5EwexXSkhydijvtnhiyVj16occd41C/WQunVWSmRKASEJD35pUAquxSIiARkAhYI8A+Qf+6/JfIYg3s6b2nV4j8+js+DbN2nDMP8cqItrWC/OIFZa1bh+zNvE/aKFHTp0vySwHDXccTq4FDiyy93T5DkF+ccXrvFZw7YCS/OD3owbbk71W+9mUspEgEJAKejYD8JfTs81+e1bPu9HwKkyj0phBFgYkv3jq9k8L3FOIpSJEISASqMwJFtIMxlUywkUk2s4TSLkR1+XcymvupgRFBfqXmwVCgM89eFaSBSj4wmPGwjmiLSPOFNeVMoqadq95qFcKjAtG2XUMl22OPOTnncCHhW1y+/Cv0ehPBbEJDowlHEyK9GjV6ABqNa2ZddHodNl3YhG8Pf4vj1457LK6VuXB+oTWkyRBM7DARDfKC8fM7r9M1TuZlShGVtzfa9h2IHqPvQnjD6FJqy2KJQKUgIO/NKwVW2alEQCIgEQASshLw6d+fmqGY2H4iOtbtaE6XNZJP99AvLDlImjrGln1aROK+Hk3K2k21rK9NS8Plt98xzy10/HgE9uhhTsuIGxAQpg+ftXTUaTyZLLhNpHMyCrB94SlzWbu+DdG4Xbg5LSMSAYmARMCTEZAEmCef/fKvnQku1gKTIhGQCNREBNjnF5NfBoXsIQ47LIZMI5CtbA8U4fMrhcgv8mGliCrIB95kxk+KIwKshZSZQppypid31vRiH19X0nkvRMWEiaNLiQuQn3+xYh250Fqn1yOJzN6l5ae51YSgmhSlI5EidoZYTyMHATiL5rhYFA1dHD2cxr1hXVxi/Gz6WZzPPG9Tx5s0Nkc0G4F729yLOr51bMpkouwIMIYhPiFIPHUci95/Cfk5RtM93mo1hj3xDKJatXXaaQD5pvDxr/kmi5wuTmbWJATkvXlNOltyrhIBiUCNQIBNH77x+xs2pg+ndJ5Sobl/8ttJnEuhZzGSIF813h/bsdb450x+/wPoUlPF2tT166Pe8/8ScfnhRgTWvgjkJBs7ZNOHt74v4vxctu2nkyjIMVoyCQ73Q++xLdw4sOxKIiARkAjUbAQkAVazz5+cvURAIiARKBsC+Znk8yuOyC8T2cPmDsOaAn6uaaKUbbDqX9tADqi1TH7RURHvOr7wDpbkl4KH/TEnoxDaQoU8BUIi/KEiX2kVkfSMv3EhfhaupmykbkxbYivSoYttWd+xsj3exReosDlLjUN57KmLiGcRXJygk2rsb2JMyzGY0H4CGgZJbTsnEJU7K+7A31jx6bvQFhi1GzV+/rjjhdfQpMMN5e5TNpQISAQkAhIBiYBEoGYisPDEQrPJad549Haft+HjXf5nhL/jr+HbnfQcZpJXa5Hpw+wdO5CxfLmyNDSYOpWep4LNaRlxAwLHVwKHl1g6Mvn94ozTe64g7qDFL+1AMknv4ydf91rAkjGJgETA0xGQv4iefgXI9UsEJAKegwCbTEi/QOs1EQwq+gsIbwb4BHoOBlYr1ZMJEia/oLMQLt7k88s7UGNVS0atESgq0CKXzGsoEhjqC40v+Y4rhxiIhE0hwiv+wixkZOwrRw/Vu8mRPCa+NDhHBJjRUnDF5hukCcI9be7B/W3vR6R/ZMU6k60dEDi+cyvWzfwMep2R3PUPqYOxL0+T/rwckJIZEgGJgERAIiARqP0IJGQmYMY+8q1kkkkdJqFDZAclWeZjHm0ee37JIbPpw74tI3FP98Zl7qc6NtBl5yCJCC9FQm67DcGDBipJeXQHAjmkWbfqn5aebrgXaD1cpO1NH7bv1wiN20jThxawZEwiIBGQCJC3FwmCREAiIBGQCNRyBNhUXQ45w828ZFko714Mbw5o/Cx5HhTTE5GjTc0nH2gm8osUmNThpMnkoT6/9HotiorS6AqwaMLZXw58GeVlFUJtumRUai94+2lgUpYhX1dFoo9zcazFVbIYDEVITl6L3NxzDhUjIgaiQf1RpFVm64+uQFeAA8kHkF7A8yybpBdkiB28Wmufd9RFqG8Y+kX3Q4Sfmx8SfRqhvU99tC/bNIutzbuNu9TrgmAfz9hJm5uZgZO7tiM/22iGsFhg3FSQm5mOA+vJobhJQurWw9hXppNPr0ZKljxKBCQCEgGJgERAIlDJCORr87Hn8h7k6+ge/TrLD8d+MJs+bBHaAk/c8ISYEZuaO3IpExfTcss0w43HkxFnMn0YTKYPPxjbqdaYPrw6Ywa0iUkCD+/QUNR/9ZUyYSMrGxFgIuvKuUyzmXkbXHb/l1wY0LM7mVOHH7ktiHoJ2Gc0hXhsZyIKck2mDyP80GsM15MiEZAISAQkAtYISALMGg0ZlwhIBCQCtQkBNnPIWl/ZdHNM5IFZmMFg8ktdfhMe5r4oMmfOHEycOBHff/89JkyYYF1ULeP6fBP5xYwOi5cX1JF+UNHDqCcKE1dMROn1haUun6zv2Uih1WVlMGiJDCPzG3GW3bI2lUtIeHlp0KDBaDRpMhlBgS1taqbkpeCn4z9h0clFyCwkE54VEuM5jg2JxSMdH8GIpiOg8ZYafxWC1I2N87IysXflL9i/bhWKCq7Py6+I6CYY++pbCA6XWnZuPLWyK4mAREAiIBGQCJSIAPvbemrTU/jz8p8l1qvqQnvTh0v/vogXlh6q0DReu70tGob6V6iP6tI4/9QppM2fb54Ok1/qiAhzWkZcQyDrWj4Wv0vkb3ZRMQ36Uz4Hk8yJU2I2x0EPtZWmD20QkQmJgERAImBEwDPf9smzLxGQCHgUAgMGDMC2bduc76aqjUjoyYRXLtkAzyatLzuNF2gCjOSXt2f+/OvziqClBwzFCiTId5U6kjS/fLxr45VQ6prKQn6V2lk5Knh7ByG60f1o3Phh+PqSI2crOZ9xHnOPzcWKMytQ6AI5Z9W02Gi7iHaY3HEyBjUeBG+VZ57zYsG5jgWs6fX36l/x95oVKMons6TXSRq2aos7XnoD/kGeoWl3nWCWw0oEJAISAYmARMABAfa3Vd3IL54kmz5sH2HR6Z+z67zD3MuS0b9VXdzdrXaYPuR15+zaRc9Vxk2Fgb16IeT228sCh6xLCLBW4ZYfjpdAfrkGU4f+jRDdmrTDpEgEJAISAYmAAwKe+QbUAQaZIRGQCEgEaggCZKoOhWRyQ9Fesp92EZWxuUOD0Y+NuZgcNyOwLhBUD3Dzi/8777wTN910E6KioszDVceILqcIujQrrRJvFTREfnlp2EeT54mR/Iqz0vzygo8P7dj0ssXDQGYi83g3oslcpNpHBZ8AR60pL68rRGLVQ2Tdp1wC08+3AerXvx1qtS3ZwGYOvz/yPbYkbCGe0vhArXTYOLgxbom5BWr2X1cG4d27Xep3Qc8GPWuNuZkyLN8tVQ16PRJPnyQzmBXVwrOdTnLcGSK/lqMwj367rCSySSxadOspNDStsistGlo/Cq1v7kuKse7RjK20iVZBx2k5hTiQkA6tYiLWjWM2CQ9A6wa233k3di+7kghIBCQCEoEaiEBidiI+3/e5eead63auFv5OW4e3FhunlImdJxOGRxON90E+9BwxqA09V5VB6of44p9DW9Wqe9GCM2fMCAQN6F+r1mZeWCVH2IRhwnGTiXcyy9+0UyQ9jlGEJfGAyYc3xdVkiqP5QIBdGdhJaP0AdB8Ra5crkxIBiYBEQCKgIFC2N0hKK3mUCEgEJAISgapFQEcERA6ZMswhzS42beiqqIioCCLiK4DMebmZ+FKmUKdOHXCozqLLLoQu3WKvz0utEppffPREYZ9fublMflkw8fdvDI3G9jzqdXqkJ+dBS467WVT0sB8UGSCO9ripVNeEFlfzZlYOmu0rFZNmszdbE7ZiztE52J+836FWh4gOmNhhIgY3GSw1txzQqdwMbWEhju3Ygr2rfkVa4sXKHYx6ZxOEvcbdh5Y9etHDv2d+Pysd5GIGuJSeh1nbz2HhngvILyrD/0wx/TnLntS7Kd4Y2c5ZkcyTCEgEJAISAQ9EgLVf3vrjLeRqjRthmtVphu+GfQf2f1rdZPVho58rnlf/1nXx9YM3VrcpVvl8Ck9bCDDfFi2qfPyaPiCbPvz9ZwuGNwxujD53tTQu69xWYB5tLFSUusb/CLSV11xNP+dy/hIBicD1QUC+Wbg+uMtRJQISgWIQ+OuvvzB+/Hg0atSIXqb7Cq2iW265BYsXLza3YJ9TY8eORbNmzeDv74+QkBD07t0bP/5IN4VWcv78ebELjc0fsniRryclsFlEa7l48SKeeuop0SePG0G2y0eNGoU9e/ZYVzPHk5KShN+revXqiTl07twZc+fOxdatW8UYb775prmuEjl9+jQeeughsTYf0jJo2LChSHO+vXB7nuvWTb/hp1n/Qc/uXREU1RKxPYbjxJk4eDXqikHjHrNvZk53HDwempgeuKwPJwKMTMu5SH4pmLEvrxMnTuCOO+5AeHg4AgMD0adPH/z222/mMZQInw+eKx8V4fYK1s6OsbGxoqoynrM6Sp51v1u2bMFjjz2Gdu3aifPO579Dhw6YNm0a8vOttLuUidBRl2VHfpHGl7ouaX5J8suMkjPyS6fVI+1Krpn84soh7CuNSDB3SQH5plt6ailGLxuNZ7Y840B+9Yvuh9nDZuOnET/hlthbJPnlLuBd6IfNEv7562LMemoSNnzzn0onv8IaRmPE0y/goY/+g1Y39ZHklwvnyF1VziRn4/klB9H/wy1g006VRX65a76yH4mAREAiIBGoPQisOrcKv1/6XSyIntQwrde0akl+8QRXH7IQYCM6Vm/LF1VxhTB5WXD2rHkoH0mAmbFwJcL4bZ53nMx/GzcashbXTaOaGZsW5gArnrZ00240kV8jLWkZkwhIBCQCEoEyIaAuU21ZWSIgEZAIVCICs2bNwpNPPglvb29BPrVs2RLJycnYu3cvZs6cibvvvluMznWYAOnXr58gyFJTU7FmzRo8+OCDOHnyJKZPny7qhYaGYurUqYKYiY+PF3Fl+goBw+l9+/aBSbZr165h2LBhGDNmDFJSUrBs2TJB+vz666+47bbblKZiTr3IxjmTNzwHjl++fBlTpkwR/ZgrWkWYSBsyZAiysrLE2nj+TDDNJ6fBy5cvx6ZNm9CtWzdLC9b4Ivnk/bexYcefGDmkHwb26oaMzGy0ad0GA/vchC07/8CphFS0atHU0o7M1+06cBJHTpwWJGEDItnKI3Fxcbj55psFufT444+DCb9FixZh+PDh+OmnnwRJWVK/TJxZY6zUPXz4MH755RcEBASILOUccYIfAqwt3v135n/B59bf1w8GImNYPnj/fZygc9yL5nbb8NsE6bWLbM8zYbh1y1ZsWP+buH5EZfpgs4d6IsAU8SJfX+oIP3i5kcRR+q6MI2tqke1Bt3XNGOflXyDNLwtZaCS/Qm3G0BbpkH4lD6wBpkhQuJ/bnCpnFGRg8cnFmH98PlLzU5UhxJHNG45oOgIT2k9Ai7AWNmUy4R4EdFotctKvOe2sMC8Phzf/hsOb1qOowHKdcGUf/wBEtyU/GF5eTtuWJ1Ot8UFzMnXYpnc/qFwk6sszjqe2ySC/h9kF/DviKJczWOMrDuuPXXawqtu6fjAah/s7NqpgTqv6QRXsQTaXCEgEJAISgdqCQEpeCj7Y84F5Ofe3vR+d63U2p6tTJI7MHx5LMpk/pE10g9uWzfxhdVqLu+aipedfPW2YYlGRNRB1XbI6IsVlBI7uSMTFE2miPt9aD364LZniJrcFLJvfIdOH8ca4Hz2nDf/IGJefEgGJgERAIlAuBCQBVi7YZCOJgETA3QgcO3ZMEEiszbVjxw60b08vWa2ENbQUOXLkCJo3b64kxbGQzHQxOfM+ESRPPPGE0LJickUQI6SVxQQYx+1FSy+CmVjLppt31i7q37+/uUpiYiK6d++ORx55RJBdrBnG8vLLL4v0iy++iA8+sDy0Pfvss+jRo4e5vRJh0oE1vzIzM4WW2v33368UCVLpnnvuwQMPPIBjR49CxeY/spOBXDJ1SLL59z3YvWIOunRoA2iINGJtLr86mPLMv4gAG4dvlqzDxx9/bO6PI9/MmybSTFyVV7Zv347nn38eH31kudlmDTkmxRhfxprPVXHCBBgHa+FzyL7C/Pz8MHv2bFGkEGD6XC09QBXCYDK79dYn7wjy647hozC693AUXaZdcCQz3vgITck3EGuHWcubH03He198hEXfzce4UWOti8xxL18mv0jzS7Gpbi6pXhG+XnS6HBQWpkCrzarUyfn5R5PZQ1vyq6iAyK/kXLK0SYSkSULIV5pfoEZJlvuYnJuMeUfnYfGpxcjT5tn0E6QJwrjW43B/m/tRP5CucyluRyAnPQ371q7AwQ1rUJBj/E65MkhQeAS63jYanQbfCl8Tee1KO1nn+iFwNDEDMzaexoZjV8o0iR5NwzFlQHP0b1XX4Xe2TB3JyhIBiYBEQCIgESgFgff/eh+8KYqlYWBD/F+X/yulxfUrXmNl/nAA/UcG+1X8vvj6rcY9IxecsWh/+dKzuf3zmXtGqZ29ZKbkYZe16cMhTdCgmckU/cW9wB8zLQsf9i4QLJ+NLIDImERAIiARKDsCkgArO2ayhUSgShHYtNmW6KnSwcs42OBBlpvgMjbFV199RS/7tXj99dcdyC/uKzo62tylPfnFBWxS8B//+Ac2b94stKmYcHJFVq9ejbNkuoHJHmvyi9uyiUImuZjYYg0t1gJjom3BggXC59Vrr71mM8QNN9wgiK5vv/3WJp81lFjbi8kja/KLK7G5xy+//BI7d+7EztUL0K+bLfH32P1j0KVrd+NNrw/tnDcRP0wu8fzYPOA777wjzEVyf+np6cJcJGPEGmflFfbp9cYbb9g0Zw01nj+bemStuIcfftimvKQEa77dfvvtYFKRzVkyEcYEi540tNg/F3QWsuXHpT/hnRkfoHvnGzHn81mkFWIxudcspqnTYf5v8hRBgG3YtskpAeblp4aaNJiqM/nFxJdWmyGIL53OlhxyuugKZvr5RcNHoxiVN3ZWmKdFxtU8ozYeZfGDbAiZi/T1r9jtQkJmAmYfnY3lZ5ajSG/UblSmXz+gPh5s9yDGthyLIL7GpbgdgdRLCfibfHgd274ZrP3lqkQ2jkG3kWOEdpa3Wr7ocRW361nv5OUsIr5OYe2Ry2WaxqA29QTx1S2WzOZKkQhIBCQCEgGJQCUjsPnCZqw/v948ytSbpyKAN/tVU1llbf6wkzR/yKep4MwZ89mS/r/MUJQa4WfgzT+cIEsLFtOHPUeannG19Fy8/Cnqw/Rs3Gwg0Pm+UvuUFSQCEgGJgESgZAQq9kar5L5lqURAIiARcBmBP/74Q9RlzaLS5MKFC0LzikkpjueRyS5ruXTpknWyxPju3btFeXEaYop/ruPHjwsCjE0s8nhMBgUHBzv0zX6y7AkwNrHIMmjQINv6ejIvl5eKQT06CAJs/4GDDgRYj35EYkW2sG1HKbVajcmTJ+Ott97Czz//jPvuM94Y//DDD2J+7CerIrvwunbt6nR97DuNCbD9+/e7TIDpdDqhZXfw4EF8+OGHGHvnGGgzCkjji4gQIn2sZeuuHXjixf9DbJNY/DJvCfyDAq2LkZObgy+/nYnla1fi9LkzyMrOMpM1XPHSlSSQoyhLG1IUUxF54x3iUyE8LB26P2Yw6FFUlCaIL72eHnrsxEvlXuKB/Sv4+tZ30PzKJzIyM5W+S6ZTwmRhaD1/aHzLf6tw8tpJfHf4O6yPXw89rdNaWoS2wKQOk3Br7K3QeLt3jdbjeHL80olj2LPyZ5zd+6cDDH7BIdD4GLVa7QsjGjdB11tHIpZI6Ir8jtj3K9OVh8CZZCa+TmM17VC3+1lFVB0i/50MraLveHcivB7r1wxto4rX6HXSVGZJBCQCEgGJgESg3AhkFmbinT/eMbcf3Xw0ejXqZU5Xt8i5q9k4bmP+UGrj8DkqOHPafKokAWaGotTI0R2XcOlkMaYPd34KXD1u7ENDz8EjPzdvgC21Y1lBIiARkAhIBIpFoPxvtYrtUhZIBCQCEoGyI8CaSyyNGjUqsfG5c+eEmcG0tDT07dtX+NxibSX2G3b+/HlBzhQUFJTYh3Uh+5hiWbJkiXW2Q5xNJLJkZBjNdNSv7/zBx1m+0iYqyrRbUE+7vXJSKJCpQ/LxFFXXuOM+PZPN3dFrygBKBxhtqDeIjuVhnQqTXO+++y7+97//mQmwb775RmjDTZw40WkbVzN5Hbpc8p9FJJXif4vbRmiMphnSklJQmGjERJtm9BPERyXPepx/vPQM1q1bh8kPTMIz9z+JoiQnptfoReypS2cx/vH7ERgYiDXr1pCvoabW3RBJVIRb+wzCX3/9JXyTjb9nPOqSrXmNxkieTJs2DUXQwifKljSz6aScCaN2VqaJpHL9+nJlONKDcyACiXWgdYWRhlYkXdvOSQpX+rauk1uUi4zUHHgVamA8c8bvnFJHZbAQh3ovHbL8UpGaQ9pCTk6X0sb6mK/Nx/nM83h04aMimzHjFxz2ckPdGzC542T0iyafT+SzTop7ETAQsX5m7x9EfP2CpFMnHDqPatEa3clMaPPuPaXPLQd0al7G4YsZ+N/2s06Jr1vbN8CzQ1uiTQNJbtW8MytnLBGQCEgEai8Cn+79FMl59BxEEuEXgRe6v1CtF2tv/jCoApvDqvVCyzg5Gw2wlo4bNsvYnUdUZ9OHv/9isZrT2dr04ZVjwPaPLTgMJmssYTGWtIxJBCQCEgGJQLkRkARYuaGTDSUCVYNARcwKVs0M3TMK+4JiYe2tNm3I31Ux8umnnwrfUN9//z0mTJhgU4tNE7J2UlmEyTOW5cuXY9SoUaU2VfxeXbni3K+Ks3xljMtJieTfi9qxjy8ivhRJSr4qonUiiSCr3540mIjQ8Tb+PJekfcFk4ciRI4U5QtZQY1KQ/aOxWUUmhsojit+nywmJ0F0zElvW/SjrCyHtEVLpMRaZDkJzSMkzNfr4qxn49sfZuGXAEHzx9ieWNqZyL3IirQrWICUrDaPG34kc8ku0fv16tG3b1npYEedzxOQXm15k04/WkpSUBCbA3C1G7ax0Ir6uwpl2lrvH8/LyJq2cCCK+womcMBJ7FRmDSaiswiyk5qfCkKtCUKGtyUNnfWu9ipDhT+slEoy5OVfFQBeAzqAz+3Kwb9erYS9BfHWr301qFdmD44a0lsyzsonDvWTqMC3pkkOPzW7sge5kzrBRm/YSfwd0alYGf6+3nbqK/207h93njJs4rFcwpG19PDukJTo0MvmSsC6UcYmAREAiIBGQCLgBgezCbLy842UcuHqgzL2lF1g2Yb3S8xXU8a3e/1fS/KHjKeZ7kUJrH2AtaigBdu0csPQRIO284yJLyDmd3R2708aSaXe/Emo5FmkNPtAajJsbwzSJ6HHqceAD03uBIrLEoZiKj+4O9HjUsQOZIxGQCEgEJALlQkASYOWCTTaSCEgE3I0A+4Tau3cv1q5dWyIBdsZka3zs2LEOU9i2bZtDHmewdhgLm+JT4iKDPnhclh07drhEgDE55+/vj0OHDoH9WtmbQWRfXvbShXyDsWzdsBaYcpdtsbcPtv51ROR17TXQSH7Z1igxNWXKFEGAseYXE2Asjz9ON9JlFINOT764ilB0NVe03H/4oDAvGBxka+Zx++4dorxz+06ljvDL6mV47b2p6NSuI376aq4N9l4+3vAm4ot9c+Xn52PU6FGIi4sTBObAgYSDEynPuXfSjUtZBiJyCk1mCQ3Kg4hLLctXSaXyIc29CKH1xSRYRYXNDbJT8ZQ80tTTFUKt1yC00LnWovVYhd75yPQlssyrDMyXdQd2cdbwGtxkMB7p+AjaRxC5K8XtCOSRGdCDv63B/nUrkZtheaHEA6mISG/XbyC63X4nIqKbuH1s2WHVIlCo1WPlwUTM2nEOJ8jXl70MbF0X/xzaCp2ijRtK7MtlWiIgEZAISAQkAu5C4OO9H2Prxa0V6o7vEYfGDK1QH5Xd+CyZP1T+c31p495g2mQiBdBevky+nHMEFCq2xhIZWfNg0RHxxORX4r4yzT1d2xCbUiZCh/Jb6fCi1oOCZ0BdYNSEtJkAvR/AqC/5Rt4mWyYkAhIBiYBEoPwISAKs/NjJlhIBiYAbEXjyySfx9ddfY/r06Rg2bBjatWtn0/vFixcRHR2N2NhYkb9161ah/aRUYq0he99bSllERISIXoiPR9NGpBmVQzvmTaTG6N7t0Dy2Cf773y8xsGsr3DZ0gNLMfNy9Zz9uaN8GAQH+oNtRjB89HHMW/oK3X/0XPnjjBXO9g0eOY968ucZ0Lo2RYrSL3rtlGFo3j8XOv/Zj6aqNuOv2IUR0UU9B9bF0zWZs/303WrVqBfYfVlYZPHiwaMuab0wkcT/2BBKbMNRlF8JQVDypYSgkbR/W5DJpcGVkZuCdzz/ARx98CFUAaSJ5QRCUC5YtBmu03TXhHmhCjKYGvUMZFVoSHTUm84Ps023is4+hYcOGWLVmFcKjG4g64oPM+7F/KRY9mWt74IEHhGbX1KlT8dBDD4l86w89mYwsKrqGqKgAkb1hw3IMGmwhU+LiLuDFF/8lynT6fPITds66ebniel0++dEhTKzEi8gcjYa0s3zYZKV7Tfcx6VWStp/VNEqMakmzMC0/Ddfyr4HjLOzzKyQ/Qhw5rdJQui75BDKeAs4yCZ+XADSA0SSnkuvq8VTyKbQJa4Md440kKbfzVfvCX+3vaheynh0ChXm5OLx5A84f2kdKo+Qzz05o8y0unzlFTrRttTV9AwLRaehw4ccrKNz4+2fXVCavAwJ6+n3dcPwKlu2/hIw8x/NZ2pTOXc3B5Uzbc+1Nv6UjO0XhUfLj1b5h9d5BX9r6ZLlEQCIgEZAI1AwEfr/0O34+/XOFJhsbEotXe77qlvvfCk2klMZrDiWZawygjSbS/KERDhvzh6T95Y7nGDPQVRXZ9UWZyS89mYzflPFUhcmvm4J/RAMf47sCm+XyRshh7wL1ireIY1NfJiQCEgGJgETAJQQkAeYSTLKSREAiUNkIMOE1c+ZMPPHEE+jSpQtGjx6Nli1bCnOHrBnGmlZbtmwBazyx+cNx48aBtcDYDCCb/WMfU3fffTcWLVrkMNXBgwYJH19jRt+O2wbeDH8/P8QQIfPgXbeDqB38MutDDLv/KYy47zH06nYDOrdvhQB/PyQkXsGeg8dwLv4ikvb/hgC1cWfb+/9+Ept37MKH/5mFP/fuQ68bOyEpOQWLV27AbYP6YNm6LVAZiHwg0yAszDPMnTENQ++dgvFP/hujV92KNqRBdfLUKSxbtkysbd68eWTyruykCj9sMGbPPfecGMta+0tfpIM+qxD6XCMRIiq4+NG3d198v3Ae9h7dj969e4NNDDK2TFixz7E6YRYNAy/TvPno5W1cwyOPThaEXM+ePfHd97MdRmWTl88++yyWLl2KX375BQpJ+eabb5rrMgGl0+Vi+PBe6NixFfl764lmzZrgP//5js75MXTq1AYXLyaRycTtVNYPCWS2EdxGa9yNaO6oghEvLzWRXpGC+HKHdlYFp+O0OWt5sZnD9Px04jBtic7ggnB4G/hKp2uRrpfQugFQa9y/o5D79qaHtlA/y7XhdLIys1QEstOuYf/aFThIWqMFua5fz0ERkbjxttHoOGgYfAOMhHGpg8kKlY5APv0W/0qkF2tuMYnlDgkgLdp7ujfBpD6xiA6T59odmMo+JAISAYmARKB0BNi09tRdU80VWYPr9ZteN6ddjYT6htYI0mT1YQsBNqJTQ1eXV+vrFZw+Y16jb000f8j+tra+Z14DBrwCdJ9sSRcTO7TtKi6voGdOEn4EvmNKC3q28i2mtvNstQ9tqvTpSoWfOlbQ0MZBH3lf5wiMzJEISAQkAhVDQBJgFcNPtpYISATciMCjjz6KDh064OOPyaTG1q2CHIokcwqdOnXC5MnGG1KOMxH22muvYc2aNdBqtbiBTAwyicKkig0BxuoReWmYPLoP4o9OxMIVv+HDr+aJNv1vvlEQYDz9Tu1a0Yvmhfj0mx+xauMOfL9oJd3QeiGqXiS6tG+Naf96HJHhlpf69etGYNfyOXjl/S+xZvNO/Ln/CFo3i8HMd19GIGmJMQEWEmTUjlLg6dmtK/Zs34C3P/0vNm7chJVrfwOv7d5778Xrr7+O1q1bK1XLfGRfaM8//zxpJ2mEfyx9AZFARHwZ8stGfLFZQnWY8Qa+WYtm+N+s/+Hf//630MwrKChA165d8cYbbwgNvdImmZtrNKXI54WDvcTExAgCTKmXmpparA+vRo3CBAEWGBiAlSu/xZtvzsDOnXuxe/c+xMZG44UXHsNTTz1E46yzH6ZCafbB5eNT12SWsOzkZIUGd7FxvjZfmDlkc4f2olapEe5VFwat5a8+KNy3Usgv+7FlunwIpF5MIB9ev+D4ji1E5Lr+/Y1sEiv8e7Xu1Y/cB1rOd/lmIVu5C4GM3CL8+Gc8vv/9PFKyC9zSbWSQLyb2jsUDPWNQh7VzpUgEJAISAYmARKAKEfhoz0e4kntFjBjmGya0uML8SvcxW4VTdNtQZ5LtzB+2qee2vmt6R/YaYDVqPWz6cPkU8o9QaJx2QyKj+pI1EZMP7uLWknY5B3+svWwuvvG2pojq0MSclhGJgERAIiARqL4IyLck1ffcyJlJBDwSgZtvvhk//1yySY1evXph8+bNTvFhh7ykpkRmDq8C2cnixpZ1Xd59+f9EEPpYAeEAa6mQxooi9chK2Puf9MD7SkYpx0YRLTD3x14OtV594y2R1/bG3gDVMQqNowlA6wYq/PDDzQ5t7DNYc+v1517Ga8++LIq06SW/ON33+x6hmTV29BiE6P2hNfnxsu7Xy5d8bgWxKUPLmq3LSXUHXmTXXpVreaHatm1bLF++3KaaswQTcBys5fz589bJYuNKWz5vOl0OCguvEkFp1JyzbqRS+QotrFatmuKnn5xjWFSUZd2kgnEV+SxjM4HVj/hirHKKcgTxxUd7YbODkX6RCPIORloSE5H0nSDxC9SIIBLyo8oRYHOG+9evRh6ZF3UmaUmXcG7fHoeisKiG6Dp8NMIaNnIo4ww/8tNXL7ZZjdhF7XQBNTQzu0CL5QcuIa4Yja7M/CKsIrNJuWxe1kqCfdW476Ym6NuibrE/x1bVbaLse6RDozrwqwQNTpuBypHg36UTJ07gwoULJbbmzQ/sS1NKjUTgLpp1fwqdKbBz02AK8yk8QMFeYikjzj7TKs3q+vdYpWVUIiARqAEI7Li4A7+e+dU801dvehUR/rXX1PIaK+2vga3rIZD+w6UYEbAhwFoqz7w1BJ3fZ5Dpw/3GybJbgju+KpX8YjPWm+cdh87kUiCycRBuHB5TQxYspykRkAhIBCQC8h9cXgMSAYlA7UGAd3PlEvGVk0IkmJ32BBMZAZHkd6uu0f9WBVedmJgo/FtZd3P48GF8MfNrhIeHo/+Q4eQAyc+6uNS40NxiX115dnMvpeVHn34sajz5wGQYSPvLWrz81fAO9oGKtLuqo/BLU602QxBfOvK7ZS/e3oGC+FKrgz3+BT9jxWZnUvJSkKfNs4cKgZpA8RIiSBMkytIu55IfMyP55U0vzoPCmdArhgB16E1muBuBdV/NwOk/d7ncbVSrNkKrq3m3nqSRWj2/vy4vphZVTCYfXN/vOo/5f8QjswxatlF1/DCpd1Pc06Mxgv0sGw1qAzRsGnfVqlXYt690J/L8myQJsBp71l+jmTPxxbtULlJwhck8SPWWUbCXI/YZMi0RkAhUbwQyCzPx5u43zZMcFjsMHGqzrLby/3Ub+duUYkSA/8sLz5wxw1GjTCBeOUqmD622vA4k04cu+Ns6uDEBl89lijWzpZjBD7elzZLVb6Ok+aTIiERAIiARkAjYICAJMBs4ZEIiIBGokQhoSUOKtb1yr9H0bf0fkVMqI+kVwMSX+37yunXrhhZk75xNNgYGBuL06dNYvXq10MT6+uuv4Ud+xlwRfoAw5JtMFtppCpTU/sjxo1izaR32HT6A9VvI99iQW9GjS3dzExWZxlIFU6iGmgI8SfbvVVSURsRXCmFWZJ63ElGr68DHNxJqb2kDnX16ZRZkCuKrQOeoDRjiGyI0vvzZZrxJstPyobW6nkIi/YVZT6VcHqsWgUsnjrlMfjHh1X0k+Tds065qJylHKxEBNoM0a/s54curUGf3P1NCyzYNgvFYv2a4nfyG+BARXdtEpyP/Zr/+Knxx1ra1yfU4IPBPymHii996sibYFgqlyQGq8GZplWS5REAiUP0RYNOHybn0vEUS7heOV3oScVCL5UxyFk5eMVqXYA3swdL8oflsa8k3tN5k7t67Th14R9QQLUAdPXMue5JeF5ieLxjMcwAAQABJREFUPRt1A27+P/O6iouw6cM/V5wzF3cbEYvIaFaCliIRkAhIBCQCNQUB970NrikrlvOUCEgEag8ChTlG4is/3XFNbM4gkEivALohd4P2hEJUGcj8AcujEydjxaoVWLBgAbKyshBaJxS3DLkFzz39Twzo1x+6HEdSx2GS1Jee6hm0ji9TvfzUUJHZwuLkwNkjeP2DaQgJCcFdd47Fl59+Ae865L+LFHxU1JbNGbKwKcI5c+aIeGkfzz77rE0VXrNOl0cElSPpYlOxjAnur6jomiDBbJqSdpJGEwYfTSTtqKO1eLjo9DqkZWYiuyAbWgNrBXrDF0ZCkAxWCo2vIJ8gqJnkpVOUX2C0Y88mOnIzjXGGMDDUF5oSriUPh7nSl8/fo23zZ5vHady+E5p1oQduO1GpNYjp1BkRjRrblcikNQJ5ROzuPJOCLDIxWBWio+/T+qNXsPH4FYfhYiMCMKZrNPydbDRgZcu2USHo1Tyi1mpeFhUVYcmSJTh16pQZGzad27hx8ddwVFSUua6M1DgEXCG8atyi5IQlAhKB0hHYfnE7lp2xKHO+dtNrggQrvWXNrbH60GXz5AcR+SXNH5rhgLX5Qx8yf1hjLEzsnAEksWIyCT9rumj6cNNcMn1oel6v2yQYXW+NMfYhPyUCEgGJgESgxiAgCbAac6rkRCUCEgGBAL1MBmnDCI2vQrbCYydq0oIJIgfF/mHF+7uya1JakgkqbUqeDVH16pMvgIMz0ZH2TbmEySt/1zS3Jj0xGRxKEybApk2bVlo1Uc7+uGJjY4UWG5slzM09KwgwlxpXoJIXETg+PhFEfkWQlpL8W9KS+c5r+ddQkK6Hb1EAUV51nKNLpFcumAQongjwITI0IITIYCnXDYEze3Yj6dQJMb6KtFCHPfE06tRrcN3mU1MHvpZTiHm7z1OIB8evp3RpEorHSatraLsG8CYzOJ4oBQUFWLhwIeLi4szL7969O4YPH06/47VP0828SBkpKwINqcHjFFg9IJXCbgqHKEiRCEgEaggCGQUZmLbL8ixxa+ytGBoztIbMvvzTtPb/dVtHuXnDGsmC0zXQ/OFlsry77QPLMga9CtRtZUkXEzuw8QKuxJlMH5LPbGn6sBigZLZEQCIgEajmCMg3jdX8BMnpSQQkAiYEyAwc8tKMxJfWCcHkS2YIAon44iNvvXeTMPlVROQXnGhpuWkIMV9VkAbegRqz5pa7+h4wYIDZD1RpfRoI48LCVJNZwsp/waxS+Qj/Xqz15cU+2jxc2Lxhal4q0gvS4a1TI6yoYiQJ26cPjpB+v67nZaXTarHjp7nmKXS5dYQkv8xouBaJT83BtzvisOTvBOSbHI+71tL9tYa0rYfH+zdHtxj+zXLf/4z7Z1q5Pebl5WH+/Pm4ePGieaA+ffpg8ODBHo2LGQwZsUaA35LbvynfSnkPU7hAQYpEoEIIJFzLxb+WHMQIIiiGd2iAeiGlmyA/ezUbv+67VOq4A1rXRbfY8FLrcYUpKz+j+7cMl+rWtEopRaeQXGg0feinqoM6uXfj4/Una9oyyjTf/CKd2fyhn0YF1gDzdIk/moqkM0arK9mHDchveruAJEjTBfHLz7oXHjZVmER7JZz4PC73QCmnaefgOGPzENqbcXUEUMq8+fXDwU0J5iG7k+nDiEZGX8vmTBmRCEgEJAISgRqBgCTAasRpkpOUCHgwAqQNg1zaNJx91WKv2xoO1vRi4svHaBrOuqiicT09/LDmF3SkdWYSlT/9bLrxxacXPVSpmPiqZC0CJrf0+uJILQO02kxBfrFvLhuhtaq9g91MUFGf6mAKIbXqZSmbLCxSbMrbgFhyQkeYs8YX+/lSJLAwVIkCagN8fegaKct1R+/m/YN9yO2dJBYtQFZ97PDm35CWZHzJ5hsQiJ53jq/6SZRxxIy8IiRl0O/edZY0Mg/74x/xWHuE/ExYfoLFrBqF+qN7bNWRUJFBPhjfvTFa1KMNFh4u2dnZ+OGHH3DlisUkJBNfffv29XBk5PLtEMil9HQKbDPtnKmsEx3fpDCQwiYKnSmQLetS5e9iarQpJl9mexACqw8n4a+4ayJsO3UVsyd0L3X1vLHiyy0WDZbiGoSSP11XCbDfk5dDr6bnlVouaRdG/j975wEfV3Xs/5+2qfduq9qWe5d7L7hgYxuwAYdiwLSXR+AFXgghhDTI+4d0QkISig2YjgGDezfu3ZZ7lSVZ3ep9tUX/ObvS3V1pJe1KK23RDJ/Dnnvuqd+7Wt9758wM3j0vlGFGhZiHL9ewvJkD2P3hjTNF2PQWKaQkSQYSKQkR+qGbmYasY/8X4djuEG/qT/zLk2ffHgzh+nDUvERTH5xjAkyACTABtyLACjC3ulw8WSbQgwiInV/VpPSqLgJaKGXopb6I7SUUX4quce+mpzgzBuVX05tXoQgK8yEXhe73s6nV1qC2NpMswUQcKdtEuCVUqsIoHpdwS6i0rVEPraXWqlFUVwThIkbEe+qsqHQ+EKlJwqIozpeVGENN5/nTNQnU19bg0NpPpMmNu/MeUkoGSceumHl3Xzr+SLu61V1p8dqJhQ/pFYQnyfWg2OmvkLNytxMoO9RUSxaNH374IQoLTS8+hcvD8ePHd6g/buTRBMSX5JfNVriXjudS2k9JfGkep/QGJRYm0GEC5m7qxL8NLF1HQFM+EtrKoV03gIv2LDbA9GRR12oplq3RlXdP5SA2FLLrw5569XndTIAJeAoB93uT6ynkeR1MgAlYJ0DKBEN8L2H1hWbKBBEfyj+SEu0I68JYUXq1lpRf5GaxSZkhlF/kSk5G8ZTcTbTaqkblF/lwsEGEskuliqB4XMK6Qm5Di55ZRSi6akixKFwWVtZXOgxCgDIA/upQNF0tX7I8cQfllyMUfw6D6CIdHd/wDWrKja5iAsIjMOr2RS4ys5bTENfvrzuu4u87yT2MC8q0/pGGmFuT+obbZwnpgmtx5ykdPXpUUn4Ji9QlS5Zg5EhhxMPCBGwmIHbivEtJKMCmUbJFAZZK9ayJsAwbbe0El/UMAlnFNTiTbXQ7qKTYPLcNjrZp4ckRAfjfOe3H/kkld7e2yozYZRaW/La2c5d6vuT6sH/vmZAP6Vmb4obFBWMGWYD1ZDn49TVUlxu9iPgGKjEkNRjFq1cbkMh8fBD+5JN0b+YgQmqK733k3+T6kJ7DhYSnAEG9jXlH/N+fNtBGDiJvLrZ3Jry0JAwOZ9eHtiPjmkyACTABlyTgfm9zXRIjT4oJdJyAeIkkXj7q9fqeHTheU2tUfIk4X80VX3JvIIAePvzC6Ia1a3f96+tI+VVspvyim15FuC9k3u6nDNJoKlBblyUp8kScLS8v6w+uXqRQVCnDyC1hML9gbuPPWfytCoVXUW0Raq34pVfKlZB14Dvqq/BFuE84GupkqGx86BO/DX7BXWPh2MYSO3SqSQFml5vGDo3kHo2qy0pxfP030mSn3PcQWVTS75gLirh2r264iFUHbkizi6EYKsG+1n8rpEpdnBEvU4b2DsbKyckYTJZfLM4lIOJ+7d0rDHiMMmfOHFZ+NcHgT3sJkHm/Qfztbcj1mYA5AeH+sEmmpUTa/O9WcoQ/nplNL9YdKG8s+JEDe+OumIBrEMi5XIoL+3KlyUxbPgAxVRfJ4+EWQ5nfmDFIXJgsne9Uhu5H8cl9gM9WYzchicAPaY+EN8fc6hRXbswEmAATYAIGAqwA4y8CE3AyAW9vb9TV1aG6uhqBgYFOnk0XDS9uaCvpIdWaO8O2hlT6kuIrhm6Egx0ad8vakA06PXRVGuiraIcbTdcgQvkVQcovlWsrv8QL7GpNNYrrig2f4thP1oAwih3VtMFNhDG7RV4lNQ30P6siynMak9UKXNgGgUBVICJ8I+Cn9GujVtunGsjdZnGZKRyKX5D7xPASv19CxO8ZCwyuDzVq4+7VyIQkDJo6wyWx6Og79/I3Z/HZMRHAwSjTydrq3w+mwtfFf/ea5suf3UNg//79hnsVMVpoaCjGjRvXPQPzKJ5IYELjotI9cXG8pu4jYOH+cDi7P+w+8jxSTyCgoXAAuz+6JC01eUQE+o6ORMmq9VKZKqWflO90Ju1T4Gqj8kt0tuSfrPzqNFTugAkwASbABJoIsAKsiQR/MgEnERBKL6EAy8/PN8zA39/fYIHjMZYUQvlVRlZItSW2E1bRTq8AcmPiTQpBh/lUsD68XqODvpIUX7WkAKKpSkLxZRQR5PbQhWMvCUVXRX2FwRqprslVBC3Av1H51bQWLa2rUOsFoQRjcRwB8Tca7B2MCJ8IeCs6r/ipqayHnhSxQmSkfPUlBZgri/j+GZSvpPxq+v3yWCW+HReiOOcmzuw0PcBPfeBRup6up0TX0Hft+S/SsD7NtLP39qEx+NvykfR9dr352nEJuKqDCZSVleHw4cNSr7NnzyZrYX6EkIBwxhqB8VR4ipLRb5apxizKPtd4+JGpmHNMwD4CmcXVOJtjdH+oont2W90f2jcK12YCPZfAsfU3UH6LPLSQqCgG9vQfDDC8o1BfvSZB8e7nIAVYBd2Lbv6Z1C/GPQUkTzUdc44JMAEmwASYQCcJ8NNrJwFycybQWQJhYWEG66+amhpkZ2d3tjsXa08aF62wqNLZNi8Rc4pcyMGLQkTcEtZIXSfC2gZNqfkwpNjwUpDtVFmT/VTzCs49FkoHHTHV6rWks7PUaonX1lU0bfKgbhBxVijALGs1nuSPDhGgbwfkpNBQeClQ4VUB8V9nxXBNNXrpOsnpZc4tcSHdSPz8/CB+z3q67P/0AzSQS1shCUNHIGmE64WoqSPF/48+OYkdFwuly7V0dBxeXzoMCvrusTABcwK7d++GTmf8d7xXr14YPHiw+WnO9xwCd9JSRRISY/zARPp8vzFfRJ8/acy/Tp9DKO2h1HRzO5zyQgEm5BVKBw05/h8T6AABC/eH/SMQ5EPPDyxMgAk4hEBhZgVO76ANrI0yeWk/+IcYN/upr5krwFKaqnT8U2yW/e5ZQG1UaCM0GbjtVx3vj1syASbABJgAE7BCgBVgVqBwERPoTgIymQzx8fEoKSlBZWUl1Gq1waqiO+fQJWM10Avgkht0M2umHPCjwLPB8a0PZ4e1VwO9wBUuCxtIaWC3CMsVK+28yOWXPFAFmQ+pkbpQ9yCUVhXEpUxdBp3eRuWg2SLr9fUGBZhZESi6FyIpxpCqoUYqlst94eubBG8XtD6RJumGma6wzqwuU6OmwrhRXq6UISzWPUKjCBbC7aGw/BLKL/F71lNFKL0u7NuNa8dMljLTyPpLMBLWVhvO5OKrEzkoF9amTpbSmnpklxp39YqprJiYiF8vGmKwPHTy1Hh4FyMgrDvT0tKkWYnYXz3571wC0TMzI2nZDzdbeh86FklIJqUmBdgayt9FaSyl2ykJ7UQBpS8o/YPSPkosTKDDBMzdHy4Yxu4POwySGzKBZgR0dM+668NL9D7CeKL3gBAMmmz8GxP3uur0dKmFd7++Ur7DmdMfA9e2m5oL14cq93gOMk2ac0yACTABJuDqBFgB5upXiOfXIwiIl0kRERGG5BELrqMdXJ8sB7LMNvdOpODQE17rlEtDYSWjvlaGyr3ZUF8tcxgqn0FhCJweB1VikOFltcM6btaRnpSCu7J24Z+n/4lrZabdc82q2XUY4h2C5QPuwxTvHBTlfyH5GgoOTsXIEe+RmyoPjStnFyXXrlxRVIuP/3GY3B8anzTnPzUUfQdHufakeXYSAT0psa8cPoAjX3+Oopvi/a9RBk2ZAf/eSXh3XzpW7b+B3PK6plMu9fnDGX3x03lGtzYuNTGejEsQ2L7d9FIqJSUFycm0M5ulpxL4NS1cJFvkPaokEgsTcDiBjKJqnMsxbrBj94cOx8sd9nACp7ZmoTjH6EtEQZvyZj44UHo+1uTmoYG81giRUzxQRThtbu2MlOcAW14y9TD+h0DSZNMx55gAE2ACTIAJOIgAK8AcBJK7YQJMoJFADcX6WkObfvNOm5DMoBvb6S92WPnVQIqB2rO3DIovTW61qd/O5ORe8BsVhcBpcVBG+XWmp3bbCsXdnpt78FbaW7hUcqnd+rZU6B3QGysGr8DiPguRce1XKMg3BSQOC52M4cP/Dbm8a9dlyzy5TvsEDn+bLim/YvoEoc/IyPYbcQ2nE9CTS7hLB77H4W++QGlutsV8fINDcSZmMl78fztRWUcuXV1QlPQb+Nyc/vjvGf1ccHY8JVcgcP36dYgkRFgy3nbbba4wLZ4DE2ACHSBQr6tHSZ0d8Xg7MEbzJnJybR7pZ9s9TVV9Fao0xpfuzftpfvz5qQxyVW7cCDc+JQI1umLU0ONBgDIAASKOcDsi4uYKLwztSaAqEP5KtkRpjxOf9xwCJXnVOLaJPLg0yvglfRAc2fg8SRu+1GkmLwfeyfFAueX9b1M7mz/X/4/JW0wYGRPP/qXNTbkiE2ACTIAJMAF7CCjsqcx1mQATYAJtEqjMBz68k+J3XTRVm/s7YBJZf3VA9PU6VB/LR9W+HOjIRZyFkItC36ER8B8fQy4L7f8pU4T5QOantOgyvTwd31771qaHYouG7RxcLL6IiyVmTKi+r8IXDwx6ALPiZ0HmZZ/bOCXFSesT3AdeDfU4c/a/yX2myZNQVNQCDBn8J3JRZfTT3s7U+LQdBOqqNbh4MA+l+Q5SwtLYQrl79ZjwCmWUSXf3k3ZZNpXxp+sRuHxoP0Ssr7KCPIvJKbx9UJ40Dh+o+6LihOWLxogAFR6emIRp/SPpGls0c8pB7xBfhAfw74RT4LvBoHpyc2Ru/TVy5EhER0e7wcx5ikyACTQnIO5DV25dabOCqXn7jh4nBSVh/V2mDVpt9fPllS/xlxN/aauKxbmAFOOh2G43Z60x/1zqc1g5dKVFPWsHR/OP4umdT1s7ZVH2wpgXsGLICosyPmACnkpAT7Gxd6+5BL0IHk0SlRSE4bNIySWkgu53V89H/cEiOggyFHlXHAL+OsSQ7/z/6MZ4yVvk+pA3b3aeJffABJgAE2AC1gjY/9bYWi9cxgSYABMopl3iwvKrLLORBd3I3vFXYMyjdrPR12hQdSgPVQdzoK+2tJ7wIlcMfmOiETilN7ld8LW77+YNhHXWqcJTWH1uNfZk72l+2uHHQvG1fOByPDLkEYT5hHW4f42mFKfSHkdFhXj0N0rv3vdjQP9f08t1eVMRfzqAQHW5Gmk7buLc3hxo1DoH9Gi9i+QREYjtF2L9JJe6BAHxe3H4689w8IuPLeaj8PVDccI4fFmXjNp6HzKXMZ3uE+GPx6f2wd2je8NHyX+bJjKcc2UC586dg4j/JUShUGDmzJmuPF2eGxNgAm0QeO/ce92u/GpjOnyKCTABFyRwZtdN5KdTGAMSGXkJmPXQQGNsWLr3xcbngdIMqMtNzymqYAfGtJ1Arg8TJ7ogFZ4SE2ACTIAJeAoBVoB5ypXkdTABZxLISwM+WgpU3zLOQihg7voPMPweu2alq6hH5f4cVB8h/+LNFA0yfwUCJvaCPyW5v6Xlll2DNFbWkRuH3Td3Y/X51Thz60xHurCrjbfcG/dRrK5Hhz6KCN8Iu9o2r1xXl4dTpx9BTY0pjlhy0rMUm+VZth5qDqsTx+W3anFqWyYuHcqHTqvvRE/tN1V4yzHxrr7tV+QaTiMgAn/v/uAdnNpi2s2u9PNHQfx4rK1LgrqerKnMjDlHJ4Tgqel9MWdQtPEFgtNmzgMzAfsIaLVa7Ny5U2o0ceJEBAUZd3xLhZxhAkzALQjUamuxN3uvNNcovyjao2G2S0M64/hMuG+4zZ0KV4PRfu1bmVaptZJrYR/aFBfqp5LG8FfY5q5QJVfZNJafkq1RJLic8WgCwruFcMneJKm3JyG8d6M70fPfAJc3GU6pK0yvD71jSRkWFNrUpOOfCaT4mvVKx9tzSybABJgAE2ACNhAw/QtmQ2WuwgSYgGcR0NDNrjqDdnp15t2+sPw68T6gHW+EI6OflVEPAVWDgYO5NgErrStFQWY2oq76Qqa3fCiv89fi5tBKFPSrhl5BPsmzbOqy9UoNtFut5gzOFxwyxEIQr/SmNN7fi0YpISnoF0pu6Bz4ckDhpUBycDL8Vf6oLd6Em63Prv0zDXpkZb2HOnUTWy/07/9LxMexi5b24ZlqiAe9nCtlUuwt0xljTuyAvHa8AGLTo7mExvpjyJReUJLCymFCX/leZPkVEs0vWhzG1MaOrhVW4nB6CXTk9qUtadBpUbVtDdRXTkjVqiP64CP/GahvpvgSLg6fmdUPY5M6buEpDcIZJmADgaKiIty4cQPCbaEjRFh+lZcbd4H7+flh8mQOSO8IrtwHE3AGgX3Z+yCUYEL6BvfFujvXOWMa7Y5574B7IVJ7suCNfcjPqzBU+919I3HnqN7tNWlxfkLsBOy4Z0eLci5gAj2RgHB9uOvDi9BpjPcQEfEBSL090YhCxPbe9IIhL56J1JXC+4rOcOz98wNAGN/rGkHx/5kAE2ACTMDVCbACzNWvEM+PCTiYgHDhpb5Whsq92VBfLXNQ749Y9nNEHJJizEYRKq8YWL78z1Tl4ouIbfg+6Dh0FXRDftLGzlqp5u3VgMkBWkwP1CCYdBfR4v5dpBZygdw4UnKw5JQ6uEPqzstLicGD/4iY6EWO79xDeyzIqMDJLZlIP91orWjjOqOTgzB6XiKSh0fAS2appLWxC67mQgROZZXirT3Xsf1CQbuzUug1WFC4FYm1JtX1Vf++2BYwG3ozd6OzB0bhmdkpGBlvcg/TbudcgQl0kID4tzwrKwsHDhzAlStXOthL+82mTZsGHx+f9ityDSbABFySwNaMrdK85ibNlfLumEm/VYULjcovlUKG2YOi3HEZPGcm4FIE0nYK14dGpbKMnnFmPzwIcnmjS4MtL9HGURH3C9CgFxo0RuWXnBRfClZ+udR15MkwASbABJhA2wRYAdY2Hz7LBDyGQIOuAbVnbxkUX5rcapdd1yWfG/g8YiuOBJxFAymtOiv+sgZMD9BgSqAWfmbuyTrbr7Pby2S+GD7sXwgPn+rsqbj8+OJFcfblUoPiK/uSfZrI+EGhGD0/Cb37h7B7SZe/0m1PUHwP9l8rwlu7r+NQenHblRvP+ujqsKhgI2LUhVL9M4FDsDd8Cv0+GX9Q5g2JJouvFAztHSzV4QwT6CoCwsrr0qVLOHjwILKzs7tqGEO/YfRya8yYMV06BnfOBJhA1xGo0dRYuD+cm+jeCrBNZ/MkWNPJ2jrQp/Mu0aUOOcMEeiAB4RHjyHfp0srHLExCRFyg8fgqWUme+Uw6p055jPLvGY69+/WTyjnDBJgAE2ACTMAdCLACzB2uEs+RCbRDoD6nStqRZa1qfXYVqii2lq5MbXmaDFl8BoZBHkKxa2wVoZPKOw1kHzO18CZHggMXAKpAVNSXQ62rN50zy1XWV+JyyWWU1be0PIsMiERFgg75EWVI8hqMJAw2a2l/VqWvQqz2HKK0lyFvdNXQ1Ivayw9636FICu4Dpcz9Hp7ligDExtwFf7JCYWmdQAO59LhxpggnyOKrkCy/mkvCkHAER1i3bBAxufqOjkJ0knCSydIRApV1GlwpqEQ73gU70rXVNrVFBaivbPnbIioXV9djfVourt8yKv9jzXoQsbqiAq18D/Ra+B7fCLmZ8qtu6GwkDrsND3l5wd9bgSUje2FgDH9HzHBythMEROytgoICiE9rUlhYiEOHyH1vSUmL0ykpKQgJcZz1oUqlQmpqKhQKflRoAZsLmICbENiXsw91tJFDSL+QfgYX324ydavT3Hg2Xyq/Y7j5v+RSMWeYABOwkYBwfbjzA0vXh6PnN7o+VFcCG35s6mnoUqhLTRu9WAFmQsM5JsAEmAATcA8C/FTrHteJZ8kE2iRQ8vllaAtr2qxjftKLgkb7pUYjcGpvKMKt+gE0r27KkwUFdvwaKPgb0KQ3ihkO7f1fYEdxGlaf/z0ulLfjPtDMVbiIjTU/eT4eGfIIBoQNMI3TiVxl1SVkZb6DgsINFL/J8iWir28SkhKfQkzMEshkdij9OjEfbtr9BLTknuPKkQKc2p6FsgLLvwvhvjBlTJTBnaEU3Ln7p+jRI+aU1eK9fTfw2bEs1NQbXaV05YJlDTrMvrUHA6vbdgM3iiYhUgsxbShvcUoqIIXXrEeexKj57G5UYsIZhxFQq9U4ceKEQblVWUkvnWwUuVyO4cOHY9KkSYiMjLSxFVdjAkygpxCwcH/o5tZfwv3hRQv3h9E95TLyOplAlxA4vSMLBTcaXR/KhevDwSbXhzt/C5Q3uv72pYf3+a+j/tU/S/PwTmELMAkGZ5gAE2ACTMAtCLACzC0uE0+ygwQeonYfNrZ9gj7ftdLPHVT2E0rivaic0nlKb1H6gJLHicxfgYCJveBPSe7fpMGycZlC+bX1ZeDwP6UGNUmTsS51GT7c/ihyqnKk8vYyfgo/LOu/DA8Nfggx/jHtVW/3vHBtVlp6EJlZ79DO+H0t6gcEkEVZ4n8hKmo+ubETl5nFEwnUVWtwbm8OzuzORm2FpRWinGJFDJoUi5FzEhAcaYfS1xNBddGaLuRW4O2917H+TB503WT2JScrrdsLtyG5NrOLVgXI5Arc/vRzGDh5epeNwR33TAI1NTU4cuSIIdXVGa00bCEhYnIJ14Tjx49HYGCjqyJbGnIdJsAEegwB4f5wX7bpntjd43+Zuz+cQe4PA8gKm4UJMIGOESjJq8bR725IjccaXB8GGI+zDgNH35HO4fbXAfLUor52TSpjCzAJBWeYABNgAkzATQjwnaObXCiept0E4qnFm5SqKDXezbXo40eNdYrp8yNK4o35MkrvUxpGSSjG3EJUvfwh8239z7nBW0OuDkPgOyoKMqUcDbRUrdaoIFCTaxS9UG61JeL8rleBk6RPpB1ilTIZ1iUOx1pFGcpP/cXQUkXuFIWoZCoMDBtoNV6SUqbAuNjxuDvlbgQqjS/ttFqjSzJja3v/r0dR8R6DxVdlldBdWkpIyHiDxVdY2DSr87GszUeuTkBYdukpll1zqa3U4Cwpvc4fyIVWbWlxpPKRY8i03hgxOx7+wWz115xdZ4+b4mq9vTcd+64WteguMdwPkQFdw11Gv2EDz32JYDPlV3VANHRW3JqSAZfhZVlUkA+UTYG9W8y2ZYFvYBDGLLwTcYOHtjzJJTYT0Gg0ELGrWIwEmhRfwupLsDEXf39/iNhb1kS4I+zfvz9Gjx4Nb++u+buyNq4jyvSk4KvcsRNBCxfwv8eOAMp9MIF2COzN2Wvh/rBvSN92Wrj26Q20uaZJFrL7wyYU/MkE7Cag1+mNrg+1xvuyyIRAjJqXaOxHQ5txvnuG8o3PWykUN3DYPWigezh1uilWmIpjgNnNnRswASbABJiAcwm0/sbcufPi0ZlAZwgIVcxqSkKx9TUla4qsJCr/EyURSGMMpQxKQsjeHyK41f9S+orSIUouL2HLB7aYY0MDKYeKdiIz8z8orzgFiM3lnVmNMJqZHC6NMwA3QfZgVqSWyo5YKW8sKtqPk0V/bv18p8/IDJZeiQlPIChoeKd74w6cT0BDSq09H1/C1eOF9ADWUgFmbYb+FNduxKx4DJnaC6o2lMPW2nJZ+wSEhdeWc/l4a881nCfLr+YyoU8YnprWFzMGRHbJy+66qip8/ftfIa/MZPk17s57MGX5ii4Zr/n6+Lh9AkI5ev36dRw8eBDpZi9N2m/ZM2uEhoZi8uTJGDFiBJRKOy20XRiZtrQUpZ9+itKPPoaOYpfJQ0MQQOtkYQJMoGsJbMvYJg3QFdZfaTfL8B+y+m7L1XEMbTr5/VLb7sWFhdcXx29KczbPiHuOS/lG97AqsuifPYjdH5rz4TwTsIfA6R03pdjIMoPrw0GS68PKN/8HZRtv0fMWbcSRyYFMegHw/VMUa1yDhlrxjE97YcPDoaB7FhYmwASYABNgAu5EgBVg7nS1eK62EniWKs6iNKPxkz5ayEoq8aZENv2S8ktUKqX0f5Teo/RflDqjMqLm3S96vQYFBRvIHeB/UF19tfsn4KQRRUyv2Nh7kBC/En5+jbvYnDQXHtZxBIRbw43/TEN+eksli7VRwsgachS5OUwZGw3h9pDFsQTqabfoulM5+Pf315FeZGm9SeHVcPvQWDw5rQ9GxIc4dmCz3mrKy7D2d6/gVuYNqVQovsbfda90zBnnEdDpdDh//jwOHDhA/xYVOG8ibjJyVFQUpk6disGDRewNetnkIVKfnYOS999H2VdfSS/NxNJK3lvFCjAPuca8DNcl0Nz94bzEeQ6dbFGVGo++fwwl1ZbuppsP0ifCv3lRq8c3S2qw5/KtVs83nZhJG2vY/WETDf5kAvYRKMmtxpH1JkuusQuT0RQTuXbPN8h+53sy/iKlV5PkiH3BlsLuDy158BETYAJMgAm4BwFWgLnHdeJZ2k5gEFX9PaU3KO2lNIuSNWkq32Ll5ObGsqY6Vqq4XpGOXBnm5a01xMGqq8tuNkEZ9BTiTEPxciSXBs1q2Hso85JBQS4N5V4Ksriwt7Xj6isVIaT4Woa4uAehUpks1Bw3AvfkLAJVpWqsf/M0xMNakyhUMjT/wonvX3RSkMHNYeLQcLYAaoLlwM+aei0+PXoT7+5LR165Zawib1I03jsmHo9PTUZiuO0vuzoyvcriInz52i9Qmmv6jZu18r/IdcsdHemO2ziQgFqtxsmTJ3H48GGUl5e36NmTrJpaLM7OAi/60YqNjcWkSZMMLg3FsadILSk/hZKrYutWgJSh5qKIiYE/KfuEdaAnrdl8jZxnAq5AYG+2pfvDPiF9HDqtX357rl3ll0MHbOxM/FQ+Mim5K7rmPpmAxxMwuj68AL3W6E1DuD4cPS/BsO6G2mrkvfwKvSZo/34keBHfc3v8l4UXyASYABPwQAKsAPPAi9qDlyS+z2soZVH6eTscBjSev2KlXh6ViTfucZT8KNVQclnRaquQnfMxbt5chfr6Iot5yuX+KFQMxFsZV1GsFcovk1ulEIrBdb88HMtv5SLUWmwW4QO8MtfU38gHgMVvGt0hmEo5xwS6hEBZQQ2+feMUqkrUUv9T70vB8Jnx0jFnWhLQk5ugt0lJ9c3JHKi1li+fW9a2vaSYdnlX1onfEJME+iiwYmIiHp2cjAgb43yJF98Zp0/g5Jb1KMs3+30xddtmrraiAuoao0LUi5Tw8374PxgyfXabbfhk5wmIOFVpaWk4ffo0RPwqa1JFbinr6y2tAYTSa9SoUZg4cSKEiz8WzyQg/q5rSPFZ/M47qD7Y0nDem+KWhT/+GIJuvx1eHuTe0TOvJq/KEwhszSAFdKPMS3Ks9deGM7nYdDa/qXv8dskQxIeKx6WW4quy3apVWJD3jw5s2YlZSd/IACRQbFEWJsAE7CdwansWCjONrkRlCi/MfmQQeTmkjYUkt37+CNTFxucGL3kDev3qZ5BFt1Q2K3v1gndKiv2DcwsmwASYABNgAk4mwAowJ18AHt6hBH5JvY2iNIWS0Ul1690HN55quU3deEKUC1MGUc/62z5jPfH/E6asRa5lYC6L04450OlqcePG36DXm148KpWh6N17BT7KzcHaa5ssBorzicDD9QosuXoMvvTSyiYZvQK44w1Sfhlvkm1qw5WYQAcJFGZWkOVXGuqqNIYeZORbb/ajg9B/bEwHe+wZzTQU1PrFtWfwNbko7EoRyq7HpiTjgQkJCPIxKdXbGlOv1+HK4QM4+u1a3MowuV5pq01b52RyBRY++xP0nyB+7lm6ioBQdh07dgxHjx4ll7omS8z2xvPz88P48eMxduxYcknLLyvb4+Wu5xto80zlzp0ofvsd1J0922IZfhMnIHzlY/CfMpktvlrQ4QIm0DUEDO4Pc/ZJnTsy/tetSjVeWXdO6nv52HjaCJMkHXcmIxRbrNzqDEFuywRaJ1CcU4WjG0yuw8fdQa4PewUYGtTu+QrFW8S/4Ubrr6jlMxB07yOtd8ZnmAATYAJMgAm4IQFWgLnhReMpWyUwjkp/TunPlFpuP7bapM3CJvt/GzVEbfbVpSe9vSMNsa9yyArM2zsGCQmPIyr6brx88LfYlrlNGnuwXy+sLK/CbTdOkjNEG4VcHGI8hUKb8yorv2xExtU6R+DmpRJs/tdZaNTGXYjC5eH8p4YhcUh45zr28Na19To8/clJ7LpU2GUrjQv1xVMU3+secnfoo7TtV0RLlkMX9u7Ese++IosvYVzbefENCsbt//0ckkeN6Xxn3INVAqWlpTh06BBOnToFYf1lq4SFhRnc+o0YMQLs8tBWau5Xr4G+E+UbNqL43XdRf/265QIojlnQvHkIe2wlfIcMsTzHR0yACXQ5ge+zv4daZ7SeTwlNQZ/gPg4ZU1h6CuVXaY3x34RewT54eaHwPM/CBJiAKxMQrg93fXhRcn0YlRhoiJcs5qyvqUTez2kPcaPrQ794H4S+9A9XXg7PjQkwASbABJhAhwiwAqxD2LiRixEQ3+M1lK5QesXGuQkLrwhKwsKr2EqboMayCivnmhelNi9oPBaWYaNbOefQ4sSEJxEUOAwxMUtQTzuyn9/zPPaZ7f68q94Lv7pxuKXia8BCYAIpuIJ6W5+Pbyg5gQyzfo5LezSB6jI10nbeREVxe8aWtmMSBokZZ4ukBzRvfwXueHoEYvo0GWza3ldPqllOL6NWfnAMJzJLpWX/YFwCniRlVWdFWHjknT2BvLSjUEEHr0NHsN3GLQYNaEDelUuoKi2xmIbC2xvDZ83D0JlzoFCpLM7ZchAUGQW5wjbLM1v662l1dBSX6cSJE8jIyLC6dBHLKz093RCnybxCUFAQJkyY0GrMKhlZCAcHB5OhMFsKm3PzpLyeLALLvvoaxatXQZtrqdD2or/l4KV3I/yxx6CKi/OkZfNamIBbEdiWYdr8Ni9xnsPmvv5MHracN7k+fH3ZcATaaAXusElwR0yACdhN4OS2Zq4PHx4suT4seolcH5boDX0K14exf/4HvBT8itBuyNyACTABJsAEXJ4A/+vm8peIJ2gDAWG/37+xHgWusirvUKlI5McPP6Z0mZJQgIl2zV/nxlKZcH+YTak994dUxfni6xsHX997UK2pxo92/gjHC45Lk3qwogovFJdAeiUppxfOI5YDE58BIpuwSdU5wwTaJWAtPle7jeysEBDqjUXPjERYL/GnyNIagfzyOjy86iguF1RKVZ6Z1Q/Pz+nfKZdjWorldGHfLhzfsA6lueKnsPPi7e+PUfMXGZIfWXGxdD8BYc315Zdf4soVsV/ENomOjjZYdQ0dOhRysu5h6XkEtMXFKP34Y0qfQFcu9g+ZREZ/16H3/wBhK1ZAERlpOsE5JsAEup2AeA4w3wDnKPeHhZV1+OW356T1iE02U1P4710Cwhkm4KIEhOvDY2auD8cv6iM9W9XuWovibedp5o2uD38wE6rhk110JTwtJsAEmAATYAKdI8AKsM7x49auQUD4+XivlakIC6xRlPZTEkqvJmXXLsqLO7z5ZmWUNcjtjZ+ijttIubocP9zxQ5wtEj68jfJUnReeJuWX4bbWh144j3mMXBo+BQRyLKUmRvxpHwHxIPXtG6dRW1FvX0M7aofG+GHRsyMRGOZjR6ueVzX9VhUeeu8ocspMVni/WjQYj05O7jCMuqoqpG3fhJObv0NNeVmH+zFv6B8ahtSFd2LEbfOh8uV4UOZsujNfW1uLTz/9FFlZWTYNm5ycjMmTJ6Nv376dUqbaNBhXckkC9RkZZO31PsrXrUMDWQaaizw0FGEPP2xQfsnJOpCFCTAB5xP4/qbJ/WH/0P5IDu74/UDTaoTrw198cw5lja4Pe4f44ucLBjad5k8mwARclICOXB/u/IBcH+qMER2ikoIw8rZ4w2wNrg9/8StL14c/e9NFV8LTYgJMgAkwASbQeQKsAOs8Q+7B+QTE29/HW5nGr6lcKMA+oPQupSZZTZmfUvoRJZHPoCQklNLPDTng342fLv9RVFuEJ7c/iaulV6W5Pu/bB4/e2GM89qaXU0/to9UlSuc5wwTsJVCQUYH1b56GulpraKpQyjBpaT/4BpJVoYNE6SNH3IBQcnEn2Sw6qGfP6uZEZgme/PAEiquNikiFzAt/umcE7hzVu0MLra2swOGvP8fZnVsp/pqlIa1QWo2Yczui+6TY3bfK1xfxg4d1yNWh3YNxg1YJVFZW4qOPPkJBQYFUZ/z48RQzMkE6Ns9EkiVPVFSUeRHnexCB2rQ0Q3yvyh076eVYg8XKlfHxCHvkYYTcfTdk9PfNwgSYgOsQMI/9Oy9pnkMm9l1aLrZdMP3b8fpSdn3oELDcCRPoYgKntmbiVpbRQ4R4rpr98CCT68OfPWxyfagg14d/+Se7Puzi68HdMwEmwASYgHMJsALMufx5dOcRuEFDv0Dp75SEv8DPKYk3ycsoieAVf6Z0iJLLS15VHp7Y/gQyKzINc/Uie69fJC3GvbvNdnEt+BMrv1z+Srr2BHOvlmLDP89AU6czTFRFiqqFFJ+rV0qIa0/cg2YndmEfuVGCt/Zcx94rt6SV+ZAi8l8PpmLmgI4pLESMri9+8xJK83KkPkUmICwcqQuWYNjs+fD2Y8stCzhudFBM7uvWrFmDsjKTRd/cuXMNbg3daBk81S4mIH5fqg8eRPHb76DmyJEWo/mQC8zwx1YicM4cfknWgg4XMAHrBNZdOIwbpXnWTzq4VA89vr+5V+rVX5uK7WaKK+mEHRktWZD86jvhIs0o949PwJQU4UGehQkwAWsEROzcwpMnUVNQZO10t5XVVetwbLc3jWfcUDiidxaU249CqMN0RYUo3n6Bcl6G+UTdPxuqYZMMef4fE2ACTIAJMAFPJcAKME+9srwuWwgIDVEGpZ9QWkFJ3CGKu8FfUBIWY24hSrlSmqfcS45XU3+CRRtekcow5G5g+L2mY84xATsJZJ4vxuZ/n4VOoze09PFXkovCEYhKZLdXdqLsUHXxYnrnxUJSfF3DySyTEkN0FuyrxKpHxiI1URiv2i/VZaX48rc/t1B+RcQnYsyiuzFw8jSyxDP9vtjfO7dwNoG8vDyD5Vd1dbVhKl5eXliyZAlGjhzp7Knx+C5CQLysq9y+gxRfb6PuvOlFd9P0/KdPQ/jKx+A3biy7wmyCwp9MwEYCbxx/G0UNx2ys7bhqurpYvPxFPnUokmPE6PpwkGM6416YgIcSOLn6Gxw+Ju7JHecdo7OogsrTEfzBXyi4ublFt1H55Zfgg9CfvtHZIbg9E2ACTIAJMAGXJ8AKMJe/RDzBThL4NbUXqTVZTydEcluJ8I3AO3PewePbHsfzqc9h9t63gNoS43qCyB3aHX+hDV7Gm1y3XSRPvNMEKoprUZJrfAluT2cVRXU4sPaq5D/eL0iFxT8eifBeAfZ00+PrXiusRFZJjd0cblWqsfpABi7liz2bJiGPh1gwLBY/mTsASRH+phN25ESMry9ffZm+F9mGVl4yGeb91/9g8LRZ/KLbDo7OrFpeXm7h1tB8LjU1Ndi8eTPUjbGbFAoF7rnnHgwYMMC8Guc9gICOvge1Z86iQWd0T2vrkrT5BSj54APU3xBG8WYilyP4joUIe+wx+PTvb3aCs0yACbgDAU254zc5/HHZcAR486sDd7j+PEfnELiVVYGjx1xrc6BMr8Ggyx+RrZe58svIx0u4Pvzrv9iq2zlfFx6VCTABJsAEupkA38V2M3Aejgl0BYHYgFisW7IOyuOrgOsUs8Mg9Ib8Lgpj5tsxy5CumCf32f0EhO/3E1sycP0Uucxr+exj14QCw3wMyq+QKHaHZws4Ybm15/It/GfvdRxOb1RK29KwjTpKuReWpcbhqWl9O6z4Et3XVJTjy9d+geLsLMNoXl4yLHz2BQyYOLWN0fmUqxAQsbz279+Pc+fOUYim9v+wfXx88IMf/ACJiYmusgSehwMI1GfnGBRYZV99hQZSeHZWvLy9EbL0boSRxZcqrmPxBDs7B27PBDyJQL/gQdCWabp1Sb7ohbjoOyGLdsxjvow20S0cHotJ/dj1YbdeSB7MrQjotHrsfO80OSKVG+YdJC9AWLBlTN3uWJBeo0NNBm14pHtDL70WyZoTiI4T4dItFXNeSgVCVzwK1ZAJ3TEtHoMJMAEmwASYgNMJOObO2OnL4AkwASagLL4GbP+lCcSkHwHJ00zHnOsxBMQL8dwrZThBwY9vXnCM4iUk2g9LyPIrINSnx3Ds6ELr6SH429M5eGdfOq4UVHW0G4t2fio57h+XgMen9kFMcOeuQW1VJdaS8qsoK8MwhlB+3f7M/7Lyy4K4ax5kZWUZFF9XrlyxeYIBAQF46KGHEB0dbXMbrujaBOouXEDxe6tQsWULBfMwxmXszIxl9B0JJQVp2MMroIjgl9ydYcltmYA5gXeWvGB+yHkmwAQ8lMDxTRkoLjBaYcuhxqJxhxDysAg13n0iXBpnrliB2rMnDIP6DB6MpG8+Zwuv7rsEPBITYAJMgAm4MAFWgLnwxeGpMQGbCWjVwNdPANrGnWbRw4BZZnHAbO6IK7ozgQZ9AzLOFePE5gwU3KhosZTYvsFQ+dr/sx8W64+RcxIg3B+aSx3tMiyr6d6dzebju1peQ8HiN53NM7gszK+w3PUpJ5+F45PD4K0wBqO2de5i5/WohBA8MD4Rof6W/G3tw7xeXVWVQfl1K/OGsZj6n//0cxg0ebp5Nc47gUBtbS00Gut/T00WX5mZmS1m1rt3b/j5WbfKDA0NxaRJkxASEtKiHRe4JgHhzlBfZ/n70TRTNSk+i1etQs2hw01F0qeqb18o7bTa8pLJ4Zc6GiH33Qd5YKDUF2eYABNgAkyACTAB2wgYvW2Y7s8mBH6MkLHdH3+77PPPUXvcqPwCuTKO/d1rrPyy7RJyLSbABJgAE+gBBOx/E9oDoPASmYDbEdj1GsW5PmucttwbWPoOoKBPlh5DQE2KqM3/OYecy6UWaxbh3/qlRmH0/ERExDnuBeeaQxn4w5bLqFTbF3PGYnI94MCfLLeWk+XWyinJEAHknSXa+npc2LsLx777CmUFecZpCOXXD3+MwVNnOmtaPC4REEqv9evX4+xZiuFkgzvDJmiDBg3ClClTIBRgLO5PQCi98n7xCio2bjS4LrJ1RX4TJiCcYnX5T5nMsftshcb1mAATYAJMgAk4gIDB9eEHFyA2IQqJVV7A8ODdQAo9i3ejaPLyUPjHP0kjhj/+OHzoPpGFCTABJsAEmAATMBJgBRh/E5iAuxPISwMOvmlaxZzfAlF8w2sC4vm56nI11v89DcU5Jnd7MoUXBk6Ixai5CXBkzC7xgv6tPdfxx62XPR9sJ1YYEeCNRycn4UGy3Ar2U3aip841Fe4O07Ztwqkt61FTXmbR2dynnsGQ6bMtyvigewnUk2Lys88+Q3p6uk0Dy2QyDBs2zKD4ioyMtKkNV3J9ArqqamQ//TRqjhyxbbL0PQiaP88Qq8t36BDb2nAtJsAEmAATYAJMwKEEDK4PcyjmFomCXB/OCn4TsoHzAGX3bXoTz2b5v/4N9I2xQFXJyYj47x86dJ3cGRNgAkyACTABdyfACjB3v4I8fyYQMxxYSDu+tv4CSJwIjHuSmfQgAuW3avDdG6dRUWRymTVsZhxGz02keF2OtQIUD1ivk9XXv7+/LhEO8lHAl6ycWIwEooN8DLG67hzVGz5K53EpLyzAiU3rcG7XdmjUpu+GmKXK1w+zHn2KlV9O/tIKl4effPIJbt68Kc1ExOvyEmabzUROrmz69+/P7gybcfGEQ11ZGbKeegp1aWek5cgjI+h70NJdqpe3NwKmTUPYo49AFRcn1ecME2ACTIAJMAEm0L0ECjMrcGKLuevDjxCiyAeG3NWtE6nYsBFV338vjRn72quQ0f0CCxNgAkyACTABJmAiwAowEwvOMQH3JCBelo59HEiaBniTizvaGc7SMwjculmJ9W+mobai3rBgL4ozNeuhgRg4MdbhAPTk2uOX353DR4ezpL4n9wvHOyvGwE/F/5RIUJpldFoNLh3Ya7DCKiukh+JukrrKSnKnp7cYLSA8AqkLlmDYrHnwbiVmlEUDPugyAtXV1VizZg3y803fiVmzZmEaKTdYeg4BbVERsh57HOrLJovayP99HhFPUExPFibABJgAE2ACTMAlCeg0euz84KKZ68PzGO5HLoxVAeR7/rZum7O2pAQFv/udNF7o/fdTbM9U6ZgzTIAJMAEmwASYgJEAv7XkbwIT8BQCkf09ZSW8DhsI5Fwpxaa3zqC+TmeoLVfKMO+JoUgeHmFDa/uqaHV6/HTtGXx9KkdqeNugaPzj/lFOtXKSJuOCGTW5ITmzcwtObvoWVSXFTp1hREISxi66GwMmTYNcwf/sO/Vi0OAVFRX48MMPUUTKjyaZP38+JlAsJ5aeQ0CTm4uslY+hPiNDWnT0L19BGL28YmECTIAJMAEmwARcl8CxjTdQktvo+lCuI9eH/yDLbYoD1n9+t7o/LPjd/0FYkgtRxMYi8vnnXRcaz4wJMAEmwASYgBMJ8JswJ8LnoZkAE2ACHSGQfvoWtr17HiLwshCVrwIL/3s4eqWEdKS7NtuotTo8++kpbD1fINVbMrIX/nTPCCjlbG0oQWnMVJYUkdLrO5zZsQX1tTXNT3frccLQ4aT4WorEEaOtutXr1snwYAYCJbRTVyi/yhpfVgh3h4sXL8aoUaOYUA8iUJ+ZicxHH4U2N8+4arLcjv2/3yHkzjt7EAVeKhNgAkyACTAB5xHQ1uuw88OLyL1KCiTSXdkjNZVG7xuizcTI7xCCRov+Vtwf6inma+5PX0TNieP2DNN2XZqzzmwzVexvfg15gH/bbfgsE2ACTIAJMIEeSoAVYD30wvOymQATcB4BEUsr+1IpLhzIhbpaY9dEqClyLpeSeztjM78gFRY9OxIRceRyowNyo6gaHx7KwLXCKqut88vrcNXs3A/GJeC1O4dCTu4We5qU5ufi1Jb1KMnJtrp0vVZL1+Yi9DqtxXm/4BCMvn0xBk2dAYVSZXGuqw7kNA67Oewquq33W1paigMHDkAouqxJQUEBhPtDITJSeixduhRDhgyxVpXLPJBAg16Pqj3fI+9Xv4TuVqMFoFKJ3n/+E4LmzvXAFfOSmAATYAJMgAm4JoHD36Xj2vHCTk2uV6ISw+rWAOKxyOD+cLbV/sq//gaVW7ZYPeeIwqDFiwwxQh3RF/fBBJgAE2ACTMATCbACzBOvKq+JCTABlyUglFdH1qcj71p5p+cYFOmLxaT8CqZPe+VEZine3nsd2y4USMq09vp4Ymoyfr5gUI+zJirMSMfRdV/iyuEDLeJqtcUstFccxtxxFwZPnQmFqnsUX23Nh891LQHh0vCDDz5AJcVfa08U5Iry3nvvRf/+7Lq2PVaecF7s/K5Yvx7Fq1aj/vp1aUlePj6Ie/NNBEydIpVxhgkwASbABJgAE+haAnnXypC282anBgkI9cbsIfvhdbJxV+KA21t1f1i5a2enxmqrsapfX0S/9FJbVfgcE2ACTIAJMIEeT4AVYD3+K8AAmAAT6A4Cwr3G0Q3pZCFk9NPe2TEjEwJxx49GQFiA2Sp6fQN2XirEf76/juOkALNVyEsbfjy7P56d3a9HKb+yL54zKL5unD5hKypDvV4DBhtibvVNHQcvsvJh8XwChYWFBteGVVXWLSnNCXh7e2P58uVITk42L+a8BxLQUby30s8+R+maNdDeumWxQllAAOL/9Rb8xo61KOcDJsAEmAATYAJMoOsIaBpdHza5PYwfHIbZDw+ye0DfACVk/3zG1K4194dk+V9z6LBUL2ntWiiiIqXjzmSEK215RESPej7rDC9uywSYABNgAj2XACvAeu6155UzASbgIAL56eXIPFcMncYYk6t5t7duVhpcHjmcnXQAAEAASURBVJqXy+ReGDQpFskjI+mhxfxM+3mVjwLRSUGkXLFseLWgEuvP5EGt0bXoRE8+E3eR8uv6LaP7NfMKMwdE4r6x8fBTWf8noW9UAHqH2G9lZj6Gq+WLbmbi8qF90JJlhjXJu3oJOZcutDiVRPG0hs+eDyVZbliTgLBwRMQnWjvFZR5KQLg1FJZfNTXGmG9Kcmm3cOFCBJCCo7mIFxVxcXEQSjAW9yagp+tdvnEj6jMyrC5EX1GJCjov6pmLzN8fIWT9F/bIw1BGR5uf4jwTYAJMgAkwASbQxQSOfJuO8sJawygqHzlmPjgQ/sEduC/LOwOUNFp1qwKBvtbdH1YdPIgGjdHlvTdZ/vsOZdfXXXyJuXsmwASYABNgAi0IWH/b2aIaFzABJsAEmIA5gQaypso4W4RT27PscmcolFaDJsYg9fYkBEU4Tqm05Vwenv30NOp11pVw5nMXeSUp4JaM7I0np/VB/2h6aOtBcvXoQWx84w/QUcwum4SUFv3HT8a4JcsQ3aefTU24Us8gkJeXZ7D8qq1tfJFCri4feOABJCayEtRTvwFacnVZ8vHHKP3kU+jLbXdlq4iKQtiKhxBy332QB/as31xP/S7wupgAE2ACTMC9CAiPHGm7TK4PJ9+TgsAw65va2l3Z+W9MVQzuD633U7V7j1QvYOZMKc8ZJsAEmAATYAJMoPsIsAKs+1jzSEyACXgAAS1ZV105UoDTO7JQmm+5s7+t5QkrrwETYjBmQRLF7PJrq6rd5z49moWXvzkL0sm1K4HeCtw/PgGPTk5GTLD1B7V2O3HjChf27sKWf/0NDfr2FYUyuQKDp83E2MVLEUbxvFiYgDmB3Nxcg/Krrq7OUCysuh588EHEx8ebV+O8hxBQ37iBktXvo3zdOjS0YjlqbakiNkf4oysRtOgOyDgWoDVEXOY+BJbRVKdTGklpBCWhyf2Y0oOUWpNJdOIXlCZQEjcd1yitovQmpZbm6lTIwgSYABPoCgLC9eGuDy+iyfVhwpAwgzeODo1FnjVwYZ2paSvuDxt0OlTt2SPVC5w5Q8pzhgkwASbABJgAE+g+AqwA6z7WPBITcCsCFUW1KLhRgQZxg89iICCYnN2Tg5oKS7d5wp1hythohMX6WyUlV8iQODQcIdGOVXyJa/PWnuv449bL0rh9Ivxxz5h4q24Vw/xUmD8sBkE+Sql+T8qc3rYJO997S1pyaGwvDJ05Vzo2zwgXh31Tx5OVnmN89Jv3zXn3IFBWVobs7GzorShL60kBsn37dqjVasNifOj7IpRfwr0hi/sRUKeno+78BesT1+tQuWMHpZ300szy30MlKTuDFy+GzNfKZgLa9eA9gNwqTZrIsQCtk+VS9yMgFFlC8SWCHWZTGkipLVlCJ7+iJHYJfE6phNIiSn+lNJnSPZRYmAATYALdQuDwuusov9Vose+rMLg+FK6pOyT5wv1hurGpwf3hLKvd1J45A12J+OkD5OHh8Bk+3Go9LmQCTIAJMAEmwAS6lgArwLqWL/fOBNyOQP6NcpzeloXrp29JO+TcbhHdNGHhN37I1N4YPiseAaEd8B3fiXnqydzr1Y0XsPpAhtTLsN7BeP/RsQgP6N65SBNw4czRb9di3yfvSzOMSEjCspdfhX9IqFTGGSYgCAjLrgMHDuDChQs2bQDw9fXFQw89hF69ejFANyRQc+IEsh55VIrPYcsSfIYNQ/hjKxE4Zw685HJbmnAdJuAJBJ6jRQjFl7Dimk5pN6XWJIhOvENJWHnNoHSckpBXKO2iJKzJllP6jBILE2ACTKBLCeReLcWZXeLnyyhT7ulHz25WNq80VWjv87yZ9dfABeRb3npfFu4PZ0znDTHtceXzTIAJMAEmwAS6iAArwLoILHfLBNyJgIhnlXmu2BDPSvhGZ2mbgH+wCsNnxxuUX960g7C7RUNxvl74Mg3rTudKQ0/qG463V4xBALk4ZDEREFZyBz7/CEe+EZvPjRLTrz/ufuk38A3gODxNTHr6p/ieXLt2zaD4ysjIsBmHn58fVqxYgZiYGJvbcEXXIaCrrETuCz+1WfkVMH06wkjx5Td2LFnZdnDXuOssn2fCBOwl0JbCq3lfQsElTKg/pNSk/BJ1hDWYsCQjk0r8kBIrwAgCCxNgAl1HQKPWYecH5PqwUYRXjoETY5sO7f8U1uDm8b8G39lqH1W7hb7fKIEc/6sJBX8yASbABJgAE+h2AvymtNuR84BMwHUI6DR6XDmWj1Nk8WUtnlXv/iHwC2ZroqYrJlwdxg0MRcqYaAi3hp2Vwso6lNdo7OpGxPn6f5svYs9lstBrlAXk1vCv942Et8J1LBGqSkugrhZekpwraTs249Tm9dIk4gcPw50/fQUqX8e6o5QG4IxbEdBRbIZz584ZFF+FhYUt5p6QkICgIGHI0FICAgIwbtw4hIWFtTzJJW5BoOC116Ahiz8hMrrOAVOnWp23IoJc2C5bBu+UFKvnuZAJMIEWBGY1lmxpcQbYS2UiiKqIDyZuMo2+ZCnDwgSYgImA8Mpx80JJc++7pgrumiPXwshPA+qru2UFt0r8UVFk9PigUmoxo88OeH2/ueNjqyuB0hvG9t50j9i36efOsst6cqOtvioMZgEvigHqP0n85LEwASbABJgAE2ACziDACjBnUOcxmYCTCahJ6XJ+Xy7Sdt1ETXmzeFYyYzyrkXMSEBEX4OSZeubw53LK8dftV7DzUssX7vau+P7xCXh1yVDI6bo5W4QVTeaZUzi2/mtknT3t7Om0GD951Bgsev4lKFWs1G0Bp4cViBheJ0+exMGDB1FRUWGxemHZM2TIEEyePBmxsZ3YIWzRKx+4GoGKTZtQ/u130rRif/sbBM2fLx1zhgkwgU4RGNDY+oqVXrRUJt4eD6HUh5LJNIMOrMgJK2WiaGAr5VzMBNyewK2sSnzzp5PQ62jnm0eKUEgZlVLdubwpvm8h4Ohuxw05oA33h7tM4/hNnAAZeQ1gYQJMgAkwASbABJxDgBVgzuHOozIBpxCoKq1D2s6bOL8/F5o62n1nJkpvOQZP7YURFM8qMMy6H3Oz6pztAIHzueX4246r2H6hoAOtWzZ5ZlY/PD+nv9Ndcem0Wlw5tM+g+LqVKd5puZ70nzAFC575X7LcU7re5HhG3UagtrYWx44dw+HDh1FTIwwQTKJUKjF69GhMmDABoaHd/1LGNBPOdTUBTX4+8n79G2mY4CVLWPkl0eAME3AIgeDGXspb6a2pPKSV81zMBHosAR25Ot+15qIHK7+cc2mTvI9hoK9JKeWQWYx6sNVuKtn9Yats+AQTYAJMgAkwge4mwAqw7ibO4zEBJxAozqkyxPe6erQAeuFDz0z8giie1aw4DJ3WG95+rBwwQ+Ow7OX8SlJ8XcHmc/kWfYoQMskR/pDZGUtGxPl6cEIilqXGWfTX3Qf1dbU4u3MbTmxah8oik0tGMQ8vLxlCY3uJTHdPy2I8uVwOofwad9c9kMlcx0WkxST5oMsJVFKsJ6H0EsovYf1lLiKO1/jx4zGW4jqJPItnE2jQ65H7s5egb7T8U/bujehXfuHZi+bVMQHXI9B0c2B5U2p9nqnWiyEsw0a3co6LmYDbEji9PQtFN41uxOVKGUbeFg8vF/D00Gmgmlrg2CpyfdjoIj0kAQiJ73S3tnTgo9JicJ8GeCletKW6bXXixtGDnHXXySLGaM0xU/jDgBkzbOuTazEBJsAEmAATYAJdQoAVYF2ClTtlAt1L4LPXjlIMr9b9qOu1Ld8vhMb4Qbg5HDAuBuLhisXxBE5lleI/36dj64X8Fv77Fw6Lxf/cloL+0YGOH9gBPWrq1bjw/S6c3roBpXk5VnvU0w7Vhga9xTmFtzeGzZyL1IVLEBwVY3GOD5iAMwgIxdf27dsh4n2ZS3BwMCZRPIZRo0ZBRbEZWHoGgZIPPkQNfScMIpOh1x9eh5ziubEwASbgUAJNFl5NlmDNO28KrthUr/l5PmYCPZKAeJ47tiFDWvu4O5Ixel6idOzWma+fpKh/nxsj//lHAU8fAfw8M45q9f79AHnIEOIzeDCUMfxM5NbfXZ48E2ACTIAJuD0BVoC5/SXkBTABGFxkWFNyWWMT2y8Yo+cmInFouGfsJrS2SCeWCQu7XRTb6+296TiaUdJiJvOGROPHt/XHoNimdz8tqji1oLayAqe3bcSpLRtQW2H7eynfoGCMmn8HRs5dCN9A11ybU8Hy4N1OQMSk27FjBw4cOGAxdkREBKZMmYJhw4ZBWAiy9BwCdZcu4dZf/iItOPzJJ+CX2ppxiVSNM0yACdhP4DI1GUOpP6XmMbzE82cyJfF2OJ0SCxNgAkSggZ4hdn90CTqtcXNZZEKgwfrLI+Bc2gScIeVXkyz6m8cqv8QSK83ifwXMnNm0av5kAkyACTABJsAEnESAFWBOAs/DMoHuJCCTeyFpeARGzU1ATHJrm3G7c0aeN5Zaq8O3p3Lx9r50XCtsdO1htszbBkUZFF9De7sm//LCApzYuA5nd2+DVq02m3nb2bBecRi9YAkGT58Fpcq77cp8lgl0EwFh7bVhwwacOnVKGjE6OhozyAXNgAEDyB0mW71KYHpIRk+/a7kvvIAGjcawYp+hQxH59NM9ZPW8TCbQ7QR20YgPUJpP6dNmo0+jY+Fvdi8l2284mnXCh0zA0wic35eDvGvGzWcycnk4a8VAyOQecL9SQxsCN/zYdLmG3QsMXGg69rBcA1l+Ve0VP29GCZjFCrAmFvzJBJgAE2ACTMBZBFgB5izyPC4TcCCB+14eS9sGW++QwjF5xgNU60t02pnyWg0+OZKF1QduoLDS8j2Ogh5eF4/shSen9cHAGOdZRRXdzMTJTd/iVlaGVU4iJk5hRjrtPDXuOG2qFBgeScqtxRg6Yw6Ea0NrolBy3DhrXLjMeQQ0pOBYu3YtLl8WBghGEUqvZcuWQcnf1yYkPepTW1SEgtf/APXVa4Z1e/n4kOvDP8CLvw896nvAi+1WAmtptNcpLaf0JqWmYDg+lH+NkpB/GT/4/0yACVSW1OHg19clEGLTYkSca7pJlyZpa2Yzxd2qKjDWDogGbhc/DZ4rtbT5Sl9uVGQqaPOVcIHIwgSYABNgAkyACTiXACvAnMufR2cCDiEgV3jA7kCHkOi+TnLLarFq/w18ejQL1fWWsYUCvBX4wbh4PDo5Gb1CfLtvUs1Gyrt6GUfWfYnrxxvj3TQ739phZEISxixeigETp0Ku4H8mWuPE5a5HoK6uDp9++ikyMzOlyY0cORKLFi1id4cSkZ6TUaffQMnq1Sj/9ls01NdLC4/+2Yvw7iM8sLEwASZgB4E7qa5IQpoC2kyk/PuigKSI0k8MOaCCPp+gJBRheyh9RonMQLCY0gBKovxzSixMoMcTEC6b93x8GRq18XkiJNoPYxYmeQaXixuAs1+Y1nKHZ7s+FAu1cH84Ywa8vLxM6+ccE2ACTIAJMAEm4BQC/GbTKdh5UCbABNyVwMW8CkN8r/VpudCSr35ziQ7yNii97h+fgCAf51hGiYfozLOncZQUXzfPnzGfXrv5hKEjMJYUX4nDR/HDWru0uIKrEaisrMRHH32EgoLGXcY0wUmTJmHOnDn8fXa1i9XF86k5eQrFq95D1U7ywka/ieYStOB2hNx3n3kR55kAE7CNwEiq9nCzqn3oWCQhYudBkwJMHK+jNJ3Sy5SWUhLWX8IM83lKf6dk+cdJBSxMoCcSuHK0AFnni41LJ13JrIcGQqH0gBilBteHz5ku6XAyCB24wHTsobmq3bullQWy+0OJBWeYABNgAkyACTiTACvAnEmfx2YCTKDDBOrranHh+124lXmjw33Y2rCB3tEUVKghlF955XWGZlPNGgf7KgwuDpPC/SG/fAlHTJ7XzGp1T7bgxnUUpF9tMVjfMRMwcu4CePv5tzgnCvyCQxAcRW5JWJiAjQREnK0LFy4YrK2E4tXZcv36dZSVlUnTEIqvyZMnS8ec8QwCdfSdK9+4EfrKlrEWxQrVV66g9vTpFov1GT4c4StXInAuK0RbwOECJmAbgV9TNZHskQNU2fPfeNtDhOs6nYBWo4O6RtvuPFQ+Cii9bVNE1VbWQ99sY1y7A1AFTZ0O+78w3bcPm9Ybsf1CbGnq+DpacuVea7qP6vQAW18CqguN3QSQ0ejtv+90l67SgYgrqq8Qhq6WosnNRX1GhqHQy9cXfhMmWFbgIybABJgAE2ACTMApBFgB5hTsPCgTYAIdJVBdVoqTm79D2vZNUFdXd7SbDrULp1YitZBK4/Pd+RYnnFvgJZNh0OTpGLtkGSLiE507GR7dYwiIGFunKL7BwYMHLRROrrJA4Wpm8eLFGDVqlKtMiefRSQJCwVp94CBKyKqr+uAhu3oLIPdD4Y+thO+YMWwJaBc5rswEmAAT8EwC2ZdKsfGf7XtJmLysH0belmAThLWvH0dFkXGTnE0NrFQKCPXGhLv6WjnTDUXXyWrpswdII9dFz1aL3gB8Q7thIV0/RNW+/ch+5hk0kNvttsR/8iTIWomh3FY7PscEmAATYAJMgAk4ngArwBzPlHtkAkygCwgU59zEiQ3f4MLeXdBp29+12QVTcJsuFUoVhsycg7GL7marLre5aq4/URFf6/jx4zh06BCqu1n5bCsdBcWsW7ZsGQYOHGhrE67nwgQaSNlasXkzuTNcDfWlS7bPVKlEMMV9C1/5KLz79bO9HddkAkyACTABJuAkAjMeGAhhddbtIlwVfvNU1ym/RtxPkf/md/uyumJAbWkpcn/2s3aVX2LswJmzumIK3CcTYAJMgAkwASbQAQJOuMPqwCy5CRNgAj2WQP61Kzj8zee4fvxICwYhMbEYNmteq279WjRop0Cj0+NkZin2Xi1CaU29RW2FzAujE0MxtV8EwgO8Lc650oFCpULSiNHwD/GMXZauxLa751JbW4urV69CTW5WnC3CtaBQfjWfiy+5dxlDljXBwcHOniJkZPHYj5QdQUFBTp8LT8BEQJOXR1ZbB9FQb/mbaqphPaej71zpF19CS+0thK5z0Px58Bs3jopbBpb3ot3W/hT7TRkdZdGMD5gAE2ACTIAJCAJyhQy+Qap2YShUtrk/FB35BKigqde326e1CnK5F4ZM7Y3EoVb9TFhr4tiyLT8Dqhrjp8qJi48DXTD2Hu1Rrg8LXn0NumJjvDYveuaStXLP6T9uLG3EucOx14l7YwJMgAkwASbABDpMgBVgHUbHDZkAE+hqAhf27caWt/6KBr3lA2VsvwEYu3gp+o4dTy+9bX84bW2+JdX1WHMoEx8cy0BJNSmOFJQa36H708PvgxMS8diUZEQFifjtLEygawmUl5fj8OHDOHHiBOrtVBp07cxMvQcGBmISKRlSU1OhohcALEygOYE6stgqXrUKFZs2Aw6w2hWxNEKWLkXYIw9DFRfXfDg+ZgJMgAkwASZgE4H4QWFY+YcpNtW1tdI9Pxtja1XXqndpI3Dmc9Oc7nkfGLjQdMw5iUDF1m10T7NJOo578+8ImD5dOuYME2ACTIAJMAEm4LoEWAHmuteGZ8YEejQBEeNrx3v/Aij2S5P0SR1ncOvXe+AQh8RyySquwbv70/HF8Zuo01gq2UL9lFg5ORkrJiYhmPIsTKCrCRQUFODAgQM4d+4cBVK3/D529di29h8eHo7Jkydj+PDhEO4GWZiAOQERq6uGXGQWv7eKYnYdMD/V4bw8LAxhDz2IkOXLaW8CW7Z2GCQ3ZAJMgAkwASZgTkC4Plz/Y1PJsHtZ+WWiYZHTlpQg/ze/kcqC77qLlV8SDc4wASbABJgAE3B9Avz2yvWvEc+QCfQ4Ase++wp7P14trTsiPhF3/PhFhMclSGXtZYRV140i64Gca+q1+OzYTWw+mwe9Sb9m6LJ3iK/B2mv5uHj4qfgnsj3OfN42AhUVFRCWXdakpqYGx44dw7Vr11qcjoiIQGJiokMUvi06t6NAuBdMSkoyxNYSeZaeSaA+IwMi/oU10dy8ieL334f6wsUWp/3ITaaqX98W5W0WeHnBd8gQBN1xB2Q+bH3bJis+yQSYABNgAkzAXgKbfwpUFxpbBUSTq8LX7e2hx9TPf/VV6EgJJkQRHY3ol8htJAsTYAJMgAkwASbgNgT47a7bXCqeKBPwfALCeuDglx/j8FefSYuN6ZuCu3/+W/gGBEplbWUu51fi7b3p+C4tBxpdM+1WGw0Hxwbhqel9sGBYLJRyfsHfBio+ZQeBm6QUOEjxjy5ebKkUaKubhIQEg6VVSkqKIbZVW3X5HBPoSgLCBW3V7t0Gq67akydtH4oUpYFz5yL8sZXwHTbM9nZckwkwASbABJgAE+haAhc3AGe/NI1xx98AvzDTMeckAhVbtqBy8xbpOPbV30LeSuwvqRJnmAATYAJMgAkwAZciwAowl7ocPBkm0HMJCOXXng/fxclN30oQ4gYNxZ0//SW8/fykMmsZ0fZwegkpvq5j9+Vb1qq0WjY1JQJPTuuDKf0inG5l0+ok+YRbERDuC69evWpwZ5iVlWXX3AcNGmRQfMVxjCO7uHFlxxPQq9Uo/+47lKxajfobN2wewIustULuvotidT0CFSlyWZgAE2ACTIAJMAEXIiBcH254zjSh4cvJ9eEC0zHnJALa4mJyffhb6Tj47rsRMG2adMwZJsAEmAATYAJMwD0IsALMPa4Tz5IJdBkBnVaDhuZ+ALtsNOsdNzTosWPVf3Bhz3apQsKIVMx/9kU0KL0pPpdOKjfPkN6LFF6F+M/315GW3dK9XP/oAPh7W/+ZS4kKwMOTkjCkV7B5l5xnAu0S0Gg0VusIxdf58+cNFl9FRUUt6sTExLQaN6tXr14YP348RIwtFibgTAI6ctVZ+tnnKFmzBrrm32OlEj6kpPUi94QtRKmA/4SJCL3/B1BQ3C4WJsAEmAATYAJMwAUJbHrBzPVhDLk+/L0LTtI1ppT/W3J92Oj6WUH38dE/e9E1JsazYAJMgAkwASbABOwiYP3NsF1dcGUmwATcjYBer8PVI4dwYsM3yLt22eWmf9WvD/5ZnooXXttt99zEe9m5g6PJqqsvUhND7W7PDZhAawQKCwuxbt065ObmtlalRbmIlzWM3L9NmjQJ0RQzgIUJuCoBTUEhSiiGV9nnn0NPcenMRRYQgNDl9yH0oYeg5O+xORrOMwEmwASYABNwHwIXvgPOrTXNd9EbgC8/L5mAmHIVmzejcutWqSCW4oCx60MJB2eYABNgAkyACbgVAVaAudXl4skygc4R0KjrcG7PDpzYuA7lBfmd66yLWl8IGIBdETPQ4GVfHC6VQoalo+PwxNRk9IkM6KLZcbc9lYBQeq0hi5ja2lqbEKhUKowZM8Zg1RUczFaGNkHjSk4hUJ+ZieJ330M5KXcbmlk3ikDvYStWIOS+eyEnJRgLE2ACTIAJ9BwCxTlVOLk1E/V11j0xtEfCP8QbM+4f0F41w/n0U7dw8VCeTXVbqzRwYgz6jopq7bT7lZ/6CLi8GeSqw3Fzzzpk6mvE/cCA+abjHpYTLvRLPvgANceOE+OWcaNrjlN5owQvW4qAqVOaDvmTCTABJsAEmAATcDMCrABzswvG02UCHSFQU1GO01s34NTWjairrLDsgkym5Iru+ynQkbtFkZo/Zmi8lDgfMgwnwsZCac29luWspaNQPyXuHROPFROTEBnoLZVzhgk4ikAmKQg++eQTqCkmUpPI5fKmrMVnEAXFTk1NNSi/fCgWEgsTcFUCdZcuofjtdyCCu4Pcd5qLd0o/hD32GIIXLIAXKXNZmAATYAJMoGcRUNdosP7NNFSXme597CUQEt12DF/z/spu1SDjTJF5kd352L4etOFIKL6+fdpuBjY3CIwF5v8/m6t7YsWyzz5D4e9fb3dpBteHL77Ybj2uwASYABNgAkyACbguge576+26DHhmTMBjCZQXFuD4hq9xbtd2aDX1Fuv08Q/AyHkLKd0B/5DOu74QcbrWnsjG1yezUVZrPUZSYYUaVWqtxTx8lXLcNzYej01JRnyY7Q/KFp3wARPoIgLXr1/Hp59+Cq3W+L0VSq0HH3wQcXFxXTQid8sEOk+g5uRJlHy4BurLl6121kBucDWZWS3O+Y4cifAnn0TAjOnwIvedLEyACTABJtAzCexfe61Tyq+eSc1Bq64rBzY876DOrHTjRZu4Fv+DXB+GWDnZM4rqs7NR8Mc/tb9Y2iTa6/9+B3lgYPt1uQYTYAJMgAkwASbgsgRYAeayl4YnxgQ6TqDoZiaOfbsWFw98T14zLHf2B0VGIXXhnRg6cw5UPr4dH6SxZWl1PdYczsQHBzNQTHlbJdxfhUcmJeHBCYkIpTwLE3A1AhcvXsTatWuh0xld//j7++MhioEUQ0GwWZiAqxEQv/WVO3ei5L1VqD192q7p+U+ZQoqvJ+A3diy87LDAtWsQrswEmAATYAJuQSDjbBEuHTS5I5x4V1/YY83VtEilj3Vr+abz5p99RkQiJKpzG+HCYv3Nu3Tf/PZfAZWN8Wb9I4GFfwFktrNsd+ER/YGIlHareWoFcb+U9/Iv0NAY71TVty+inn/O6nK96ZwqKcnqOS5kAkyACTABJsAE3IcAK8Dc51rxTJlAuwTyrl7GkXVf4vrxwy3qRiX1xdjFd6P/hCn0DNX5h6ibJTV4d186vjiejVqy/rJVkiP88TjF6RLxunzI+ouFCbgigbS0NKwTMZEaYwII14YrKBZSRESEK06X59SDCejJNWf5um9Rsno16jMybCdBiq7AuXMR/sQT8B06xPZ2XJMJMAEmwAQ8loBwfbjno0vS+vqlRmH0vETpuKsyQsHWESVbV83Haf1m/P/27gO+jfJ84PjjFcd24p3hJFBnEUooK4EMAg2rdEGBAE0hECghdEHLn1JWoS4pq7tQWlpGTIBCB2GVvUIhCSNh7xVnbzuOE8fx/D+PNSzJki3ZknWSfu/n80R379299973JOeV3rv3XhJZPr9j91//jcg+x3fMM9VrgRod+rD+lVdc5ejd7sOuu1Zy9tuv1+VSAAIIIIAAAgg4V4AOMOeeG2qGQFgC9gP99bc9JC1vPis5W1Z02mZX6UjZNvYwWTFotLyyMk1k5Vud1ok0o66hWV78ZLPoo7z80rCC/vJdHcpw+ji9WlF0XwGpX0a6jCjKkfT0zssCVmUWgbgINDY2yiv6pfhZvZPGk4qLi9s7vwoLU3eoGI8Fr9EXaNM7DOueflp2PL9I2gKGqu1ub/b3v/7V16Rl61a/VdOysiT/+OOk6NRTJT3EsD0ZRUWSqUFCAAEEEEDAI/DSvz+RnbWuER1yBmbJ4TP1biFS3wg07RJ5+PyOfY37hnZ+ndAxz1SvBRpXr5ZNPkMflujzTun86jUrBSCAAAIIIOB4ATrAHH+KqCACXQts27he+j1zW6eVPs8tl2UFB8rG/jpc2wZdvMH+iU36Ylm+nHf4KPnGfmWSpZ1cJAQSTWDnzp3y2muvyauvvir17iFR7BgGDx7cPuzhwBCdCIl2nNTXOQKt2tla+5DeuXXb7dK4cmVUKmadXUUzZ0rRGbMkS9+7JAQQQAABBMIVaB/6cGnH94Uvf2ec5AxkmPJw/Xq93qLrRKo/dxWTXaBDH/5OryfkosFeu7oLaB/68PIrpG2XdjRq6jdmtJSe/yP3Ul4QQAABBBBAIJkF6ABL5rPLsaWEQNHQYbKhaKwMrflEWvWuq4/zxsrywgOkul9JzI//sLGlMlc7vqaNKeW5MTHXZgexEKiurpalS5fKG2+8Ic3NzX67GDZsmMyaNUtyc3v3TAq/QplJeYFW7Wyt+de/pbqyUpo3boyKR6Y+l6549mwpPOUUyRiQF5UyKQQBBBBAIHUEGnY2yfM+Qx+OnThYRh/EhRR99g5Y94bIkps6dveVeSL5ZR3zTPVaoOYf90q9XuzWnvRxAMOuu07S+9HB22tYCkAAAQQQQCABBOgAS4CTRBUR6E7gy6fMlA3LXpSiyV+RcYWlclx3G0Rh+ReHDpSxQwZGoSSKQKDvBdatWycvvfSSfPDBB97nfHlqUVBQIFOmTJEJEyZIlg4lR0IgGgKtesXx1jvukJoFd0lLba1fken6jLmi73xHsveK/KH0GQWFkjfpELFhD0kIIIAAAgj0RMCGPqz3GfrwMIY+7Aljz7ZpaRJ5SIc+bGt1bV9+mMhBZ/asLLYKKtC4apVs+p3eUedOJXPmSM6XvuSZ5RUBBBBAAAEEklyADrAkP8EcXmoIfPOoSSIWJAQQCClgz0uqqqqSF198UT7/3D3EjM/aQ/UumkMPPVT22WcfydArQ0kIREuguaZGVp/3PWl4+22/IjNKS6Xk7LOk8Nvf1ju3BvgtYwYBBBBAAIG+EFjx9hb56OWOoQ+nn7a35Azgzpi+sG/fx+I/iWx8x7W7zByR43SeoQ+jxh849GH22LFS+sMfRK18CkIAAQQQQAAB5wvQAeb8c0QNwxOw8f5O1NCnBYtdzjVcw57gbN8m5rvDfVmdznWkqTr5c43JGv01PtW4Q8PGoGjRICGAQIILtLa2yscff9ze8bV27dpORzN69GiZOnWqjBo1iqE8O+mQ0VuBpvXrZdU5c6TRp9M1a8QIKZlzjhSceKKkZ2f3dhdsjwACCCCAQI8EbOjDRfd86N127MFDZNSBg7zzTERBoFm/kq7Rofea6jsXtnu7yAs3dOQfeYVIyeiOeaa8Aq27d8uuN9+Stt0N3rxwJuqXLZf6Zctcq+oFbmUMfRgOG+sggAACCCCQVAJ0gCXV6UzpgzlFj/6vGus1ntdYpTFE4ySN2zS+pmHrtGl40rd04n4Na0X/U6Na4ziNP2gcqmHrkxBwlIB15qxevVoaG61/l9SdQF1dXfszvjZv3uy3appeWTt+/Pj2O77KynjGgh8OM1ET2K2dXtb51aydYO1J33eDf/YzKT5jlqRl0gSLGjQFIYAAAgj0SMBv6MP8fnL4t/fqUTlsFEJARx+Qf50h8vETIVbwyR52oMik7/tkMOkRaGtpkdVzzu14hpdnQYSvJefq0If7jo9wK1ZHAAEEEEAAgUQX4NeXRD+D1N8j8LFOHK/xqIbvnV6X6/yrGjM0rDPMOrws5WvcqmF3eU3XcF8WJlfq9HMaJ2vM1LhPg4SAIwRq9blBd999twR25jiicglSCRva8IADDmjv+CouLk6QWlPNRBTYpcMdrp57nrRs2+aqvj6ja/gN10v+17+eiIdDnRFAAAEEkkxg5XtbA4Y+HCf9B/A8yaie5uU6EEk4nV/p+rPM8X8WyeDnmWD+1fPn97rzq33owx8w9GEwX/IQQAABBBBIdgFaWMl+hlPn+KzTKliyAe1v0bhGY7qGpwPMOrgGaSzQ8HR+6WT73WA2JOKzGnYJHh1gikCKv0B1dbXceeedYp1gpMgF+vXrJxMnTpTJkydLfr71f5MQiJ3AjsWLZc35F0hbvWu4o7TcXBlx040yQJ8xR0IAAQQQQCDeAo0Nzf5DH04cLKMOsK9GpKgJ1KwUecqurXSnofuJDBjsmet4zdDnrR04S2Tovh15THkFdn/2mWy+0Z5O4Er999tPMgoKPLNhvWYUFsqgH18g6fp9gIQAAggggAACqSdAB1jqnfNUPOIm90E3+xz8ke7pYONR/E+X2a+WUzXs4Sy7NUgIxE1g06ZNsmDBAtmxY0d7HdLT02XkyJFxq08i7dis9thjDzn44IMlJycnkapOXftAoE2HJmq/Q0uH1olW2rl0qay7/Ap91ofrvx770WWPv/9NcvQHGxICCCCAAAJOEHj5wc9lR7XrK07/vCw5jKEPo3tadMhyefhH+kRqV9tdSnVoyXOeEsmiLRoJdFtzs6y77HJpcw/93l+HLy+/525J07vqSQgggAACCCCAQLgCdICFK8V6iSpg7/Ez3ZX37ewa586zoRMDk3WUrdCwAcJHaXyg0VVaHmLh3iHyyUYgbIG1a9e2D3u4a9eu9m0y9blBM2fOlDFjxoRdBisigIC/gP2gsv3xx2XrrbfJ7o+D/Tfgv35P5zL1+XJ73narZI/mgfY9NWQ7BBBAAIHoCqz/dJu888Iab6HTTh0rOQO5M8YLEo2J5Xfot0m7plJTWrrICfqoajq/XB4R/Lv1jvnSoENKW7JOr7LrrqXzKwI/VkUAAQQQQAABlwAdYLwTkl3gej1AG0/iMY0nfQ7WM25CqPHkPPmFPtswiUCfCqxcuVLuueceaXRf9WjD+J122mlSXl7ep/VgZwgki0Dr7t1Su3ChbL39Dmla0/HjXyyOr592elnnV5Z2gpEQQAABBBBwgkBzU4s8f/eHIm2u2nxh3xLZ65AhTqha8tShpkqHPryq43imni8yYmLHPFNhCez+5BPZclPH0IelP/yh9N9L76QjIYAAAggggAACEQrQARYhGKsnlMAFWtuLNPRbnpwRYc3T3Ou7vx52ufWEEEvtzrCDQiwjG4EuBT799FO57777pFnvVLFkw/fNmjVLhg8f3uV2LEQAgc4CLTp8aM2990r1nQukZcsWvxXStGM5feBAv7xezaSlSd6UKTLk8ssks6ioV0WxMQIIIIAAAtEUWPZYldRscD2fMis7Q7582jhJ0/+3SFESsKEPH9KhD5t2ugos1UFHpl8epcJTpxjv0Ifu4aT777uvlMw5J3UAOFIEEEAAAQQQiKoAHWBR5aQwBwn8UOvyJ433NY7SqNbwTZ47vDx3gvkus+l8d4ZnvcDlzCPQY4Em/TK3bNkyef3118UztGFgYTt37hR7PpGlvLw8OfPMM2XIEK7QDXRiPrEE2vRZW3VPPy3Vd90tjatW9lnlW+t2SFtDg9/+7AHqRWeeIcWnny72nC4SAggggAACySyweXWdvPHkKu8hTj1ptAws7u+dZyIKAstuF6l60VWQd+hDjCOV3Xrb7dLw7rvtm9nQh8Ns6EMdBp6EAAIIIIAAAgj0RIBWRE/U2MbpAj/RCv5Bw1rN1vm1SSMwfaQZNhaFjaMQ+Awv+1yM1LBbbz7XICEQFQHr+LJOrxdffFF26B0p4aQC/ZHeOr9KSkrCWZ11EHCkgD28vPbhh8V+0GisqoprHTO1I7n47LOk6JRTJF07l0kIIIAAAggku0BrS6s8f9eH0trquriqbEyBjD+MUQWiet6rV4g87TP04aE/1qEPQw0UEtU9J1VhDfps1s033+w9ptLzz5fssWO980wggAACCCCAAAKRCtABFqkY6ztd4BKtoD33602NYzT8x7rSDHd6Tl9P1/iqxr3uPM/L4TqRq2FPLt7tyeQVgZ4K2DCGno6vurq6sIsZMWKEnKI/0lsnGAmBRBRora+Xmn/9S6rnV0rzxo1xPYR+5eXtw+fkH3+8pOuwhyQEEEAAAQRSReDNZ1fL5lWuNmhGZrocMWtvSUtn6MOonX/v0Ieu4SVl0N469OFlUSs+VQpq04sF11+mQ0Z6hj7cbz8p+e7ZqXL4HCcCCCCAAAIIxEiADrAYwVJsXASu1L1erWF3dH1FI3DYQ83ypv/o1A0aMzVu0limYcnGqPhV+5TIX92vvCSYQE1Njbz66quyefNmR9R806ZNsn37dr+6DNRnDh122GGy9976A0SQZy9Y3oABA/y2YQYBJwm06Hu65p//lF3Llkub/fATmHQITxu+pmXbNr8l9rytotNPk8IZMyQtO9tvWaxm0jIyJKO4OOhnLVb7pFwEEEAAAQSiKWB3b/3vvo9l1btbvcNkh1t+fW2jd9WDv1kuRUMT6A7oug0iD5ynlzV+6j2GoBOHXShy8Jygi/wyP18k8qCNlt9N+vLPRCbM7mYl9+LXbhVZ+ZJrJi1D5IS/iGT2TRvHt4JNerHRuksulcaVK32zE2baOsA8z2q1Z7QOu/Yahj5MmLNHRRFAAAEEEHCuAB1gzj031CwyAft2Yp1fLRo28PoFGoGpSjMq3ZnWG3GuhnWELdK4T8M6zI7XGKdh+f/UICWQwNq1a2XJkiXy/vvvR/zDQF8dpnVqTZs2TSZMmCBZOqY9CYFEE2jeskWq71wgNffeK61hDuVpx5hRWiolZ82WwpkzJYPO3UQ77dQXAQQQQCDOAm8+vUre+9/aXtWidI8BcsAxe/aqjD7d2J6H++D3dVD6Rd3vdnd4w4tLsw7wsX1N9+U1hlle9eciz1R0lDdNR+Mf3vdDH9qzg9dfdpnUv/xyR10SeGrQBTr04ZgxCXwEVB0BBBBAAAEEnCJAB5hTzgT16K3ASHcBesmd2DPAgqUXNLPSZ8GDOv1ljSs0ZmjY3V92aeH/adyood+4SE4XsC97n376qSxevFiqqqocW908fdbQoYceKhMnTpR+DL/m2PNExUILNK5ZK9V33C7b7l8obbvDHx02S4fyLDnnu1Jw0kmS3kd3fIU+CpYggAACCCCQeALV63bKK49oR0svUv+8LDlq9j6SkZHei1L6eNPX7xT57Lk+3mmEu8vOFxmrg4+8r18tB++j3y5tRP6+T7UPPCg7lyzt+x3HYI95hx+mz2s9OwYlUyQCCCCAAAIIpKIAHWCpeNaT85gr9LAsIk2LdYOvR7oR60dXoLq6Wt555x0d7r0pooKt8+uTTz4RG2IwMI0aNUoOOuggyXbAD+6ZmZkyfPhwOr4CTxLzCSHQtHGTbP7976T2v4/qPbZ2k21H6qefs+LZsyWrbGhHps9Uunb85uy/P8PX+JgwiQACCCCAQCQCrS2t8uyd70trs+vavEF7DpSvnrdvxMP65ub3E3v+V8KkbatFnvx5R3UnfU9kyo865gOn+of5zNyRh+vlku8Gbt15Ptzy8kpFTtWOuvceECkqj8vQh8067PvG66/3HkPR6ae3X3zkzUikCf3elDloUMTv70Q6ROqKAAIIIIAAAn0rQAdY33qzNwQQCBD47LPP5L777ou48yugmPZZe27WvvvuK1OnTpWysrJgq5CHAAIRCLTu3CmrtIOrMeDuyv76OSuZe64MPPpoSUtPoB/TIjh2VkUAAQQQQMAJAm/o0IebVta1VyU9M02OOuuLkl+S44Sqxa4ONvThw9rZ1eg6bikZK3J0hUhWFI7byijcI/p1H39i9MsMs8QN834lre7nDdud94Mv+j9Jz80Nc2tWQwABBBBAAAEEkluADrDkPr8cHQKOFnj33Xdl4cKF0tra2qt62rO07JlakydPlsLCwl6VxcYIINAhsOFX1/h1fuXqZ6xUO75yp0zhytwOJqYQQAABBBCIicDWtTvk1f+u8JZ9yDdHSsmwAd75pJ1YPr/juV9peqHNCX+JTudXEoJtf+opqdPwpLJ5V9P55cHgFQEEEEAAAQQQUAE6wHgbIIBAXAReffVVeeyxx7z7zs/Pb38+lt3FFUnKycmR8ePHi72SEEAgegK1j/xXah/Q4Xzcqeyaa6RwxkmeWV4RQAABBBDoTqBKV/hCiJU2an7w8XNDbJBq2Tb04XMLPvAOfTj4CwPlwGP2TH6GmpUiT13ZcZxTfiiyxyEd80x5BVpqa2XDvHne+YKTZ0ieXqREQgABBBBAAAEEEOgQoAOsw4IpBBDoAwF7bteiRYvkhRde8O6ttLRUzjjjDCkoCHPsfu+WTCCAQCwEGletkg0VFd6iC751PJ1fXg0mEEAAAQQiEKjVdf8YZP0dQfLI8hF4/amAoQ9n7yPpGUk+7LCNCtE+9KH77VG6l8gRV/ioMOkrsPHXv5aWzVvaszIGlcqQiy/2Xcw0AggggAACCCCAgArQAcbbAAEE+kzAhjp8/PHH5bXXXvPuc/jw4XK6Pqg5l3HqvSZMIBBPgbbGRll70U/Fnv9lKesLe8qQK6+KZ5XYNwIIIIBA4gps06pXJG7141NzG/rwNZ+hDycdN0qKh+XFpzJ9udfld4is+J9rj+1DH/6VoQ9D+O9cskRq71/oXTr0qqskg4sJvR5MIIAAAggggAACHgE6wDwSvCKAQEwFmpub5QEdTu29997z7mf06NFy6qmnSnZ2tjePCQQQiK/A5ptukoZ33nFVQp+vN/x3v5eMASnwo1t82dk7AggggAAC7QItOvThs3fq0Ictbe3zg8vz5YCj90h+nZoqHfrQ54KbqeeLjJiY/MfdgyNsra+X9T4XJw089ljJP+aYHpTEJggggAACCCCAQPIL0AGW/OeYI0QgrgItLS3tnV4vvviibN682VsXe27XiSeeKJmZ/BnyojCBQJwFdixeLFtvvc1bi8EXXig5+473zjOBAAIIIIBAhAJ2ldMsjT017NbitzXsFp8WjaROnz38qNSsqY74GKtrc2TzquL27TLSW+Wo8UslffHzEZcT9w1yikQOnhNeNWzow4d+JNLkuvtcSseJTL88vG1TcK3Nf7pRmtaubT/ydL3ra+jPGSYyBd8GHDICCCCAAAIIhCnAL89hQrEaAghEJtDU1CRvvvmmLNHhOWpqavw2Pvjgg+VrX/uapKcn+XMM/I6aGQScLdC8dausu+RSbyXzpk2T4rNme+eZQAABBBBAoAcCQ3WbuwK2W6HzZ2t0PBA2YAWf2eU+076Te/vOOHH6k2Ub5bNN5b2q2iG5d0nx8gd7VUbcNi4ZE34H2LLbRapedFXVO/Rh/7hV3ck7rn/jDalesMBbxSGXXCKZgwZ555lAAAEEEEAAAQQQ8BegA8zfgzkEEOilwO7du2XZsmWydOlS2bHD//nmWTqc2vTp02Xq1KmSlpbWyz2xOQIIREugTa+8XnfpZdKyxf0g9ZISGXb9dZJGJ3W0iCkHAQQQSEWB+XrQ1qth41/XaYzS0Nt8ZK7G4xpTNN7SIAURGJL1kRyQ93CQJUmW1dYm8oHPcR76Yx36cEKSHWR0Dqe1oUHWX6Z3xpmZpjz9TlVw4gnRKZxSEEAAAQQQQACBJBWgAyxJTyyHlVoCf/vb3/yGF4zn0duQh23uL2WeeuTk5MikSZPkkEMOkdzcXE82rwggEEUB+9ztWr5cts6vlPqXX5Y2/SyGnXTbNu289qRhN9wgmaWlnlleEUAAAQQQ6InALwM2elfnv6dhV0hdpFGhcaJGVylUT4jdGXZQVxvGe9mo/UulcPXqHlWjX1az7DOqRtL7Xdij7R2xUW5JeNWwi+JmPSCy9CbtKtXX6ZeFt10KrmVDHzZWVbUfeXpenpTNu5qLClPwfcAhI4AAAggggEBkAnSARebF2gg4UqC5uVksnJYGDhzYfrfXQQcdJNnZ9ggIEgIIRFvAOrrqnn1Wtt5+uzS89Xaviy8+57syYNqhvS6HAhBAAAEEEAghcIvmWwfY4SGWJ0X2XjOOT4rj6JODyNCfJaZpZ9/UC0TSM/pkl4m2k/rXX5fqykpvtQf/7GeSNXy4d54JBBBAAAEEEEAAgeACdIAFdyEXAQR6IVCqd45MmTJF9t9/f8nM5M9MLyjZFIGQAjYMTu2DD+odX/OlaeWqkOtFsmCADlE6+Mc69BAJAQQQQACB2AlschedF7tdUHJCCtD5FfS0te7a1Wnow8JTTwm6LpkIIIAAAggggAAC/gL8Mu3vwRwCCSkwd+7cTsMOxutA7Nle9qwvEgIIxEagpbZWav7xD6m+625pqa7220mafvYKTviWFM+eHflVwfq8r3Tu1PTzZAYBBBBAICYC9uwvS5+7XvgXAQS6Etj8xz9J48qV7au0D334q3kMfdgVGMsQQAABBBBAAAEfATrAfDCYRCBRBehwStQzR70RCF+gadMmqb7zTtl2733SWl/vt2F6fr4UzZwpRbNOl6zBg/2WMYMAAggggEAcBMbrPtdr+F+pIfIFzfuzuz53u195QQCBEAL1+nzX6gULvEsHX3qJZA0b5p1nAgEEEEAAAQQQQKBrATrAuvZhKQIIIIAAAnEVaFy9WrbedrvUPvCAtDU2+tUlc1iZlOjdXgUzTpaMAYwk5YfDDAIIIIBAPAVsfLZLNZ7XWKFRpzFa4xsa/TUe0/itBgkBBEII2NCH6y6/XHSoj/Y18qZNk8KTTw6xNtkIIIAAAggggAACwQToAAumQh4CCCCAQEoKtDU3S90zz0j9a8ukrbUl7gYtW7ZI3bPPibS2+tWl35jRUnruuZL/9a+LDXtIQgABBBBAwGEC1vE1TuNADRvy0K7S2KbxksZd7nD9qq8zJAQQ6Cyw6Q9/8D7nNX3AACmbdzVDH3ZmIgcBBBBAAAEEEOhSgA6wLnlYiAACCCCQCgI2pOC2+xdKdWWlNK1d69hD7r/fflJ63lwZcMQRkqbP7CIhgAACCCDgUIEXtF4WJIcLtDY0iN1pFO1k7ZSMgoKwio1GHdJzciS9v91c2HWyu+lbdu7seiVdGm55VpA9n7Ut4GKlbnfQzQoN770vNfq8V08actmlklVW5pnlFQEEEEAAAQQQQCBMATrAwoRiNQQQQACB5BNo3rpVau65R+Mf7T9eOPUI86ZOkZK5cyV30iSu/HXqSaJeCCCAAAIIJJhAtbaBNl57nfbgRP+u937l5TL6icfDErG22Kbf9G5EzME/vUhK5szpdn87liyRNd/7frfr2bO2Ss46q9v1bIUVJ58iTTpkdaxS3uGHScFJJ8WqeMpFAAEEEEAAAQSSWoAOsKQ+vRwcAgggkBwCLdu2yY4XXpDWht1RO6CG99+X2gcflLbd/mVmFBZK4SmnSGbZ0Kjtq6cF2dXTOXrXV/999ulpEWyHAAIIIIAAAgh0Etj9ySey8fobYtL51WlnZPRYIH3gQCm7mqEPewzIhggggAACCCCQ8gJ0gKX8WwAABBBAwNkCu956S1bPPS/md2hljRghxXqlb+FJJ0p6bq6zUagdAggggAACCCDQQ4E2veNr3c9/LtLU1F5CWnZ2WMMHRrK79Pz8sFdP65cd9nCJoQq1MsJJaZlZYe0rXU3CTRnaSdUa5nCP4ZZp65nhkCsul6yh8b8oK5J6sy4CCCCAAAIIIOAkATrAnHQ2qAsCCCCAgJ/AjpcWy5oLLpA2fUZXrFL/8eN1yJxzZOAxx0haJv8txsqZchFAAAEEEEDAGQI1d98tDW+93V6ZtKwsGXn/fyR7zJi4Va74jFli0RdpwLRDZa9XXo7qrkYuvD+q5VEYAggggAACCCCAQPQE+KUvepaUhAACCCAQRYHaRx+VdZde5r062YYmHHjM0bqHtKjsJU0flD7wqCN5rlZUNCkEAQQQQAABBBJBoHHNGtn0xz95q1ryvfPi2vnlrQgTCCCAAAIIIIAAAgjEQIAOsBigUiQCCCCAQO8E2h/K/qtrRNra2gvKLCuTPW+/TbJHjepdwWyNAAIIIIAAAgikqECbtqs2XHWVtO3a1S6QPXaslJ57bopqcNgIIIAAAggggAACqSBAB1gqnGWOEQEEEEgQAfthZsufb5YtN9/srXG/0aPbO794/oGXhAkEEEAAAQQQQCBigdqFD8jOJUtd26WnS9k1v5K0fv0iLocNEEAAAQQQQAABBBBIFAE6wBLlTFFPBBBAIMkF7IHsG6+5Rmr+ca/3SHP2319G3PJXySwq8uYxgQACCCCAAAIIIBCZQNOmTbLxhhu8GxWfeabk7Lefd54JBBBAAAEEEEAAAQSSUYAOsGQ8qxwTAgggkEACdtfXziVLZOstf5P6117z1jxv2jQZceOfJD0315vHBAIIIIAAAggggEDkAhvn/Upat29v3zBrjz1k0AXnR14IWyCAAAIIIIAAAgggkGACdIAl2AmjuggggECyCLQ1Ncn2J56QrXfMl90ffOB3WPnf+IYMu+5ahuXxU2EGAQQQQAABBBCIXGD7k09J3dNPezcsm3c1Fxh5NZhAAAEEEEAAAQQQSGYBOsCS+exybAgggIADBVp27JRt//m3VC9YIM3r1vvXUJ9HUXzWWTL4pxdJmk6TEEAAAQQQQAABBHou0FJbKxvmzfMWUHjKyZI3ebJ3ngkEEEDyhRMaAAAidElEQVQAAQQQQAABBJJZgA6wZD67HBsCCCDQQwEblrD+5Zel+p57pLGqqoelBN+secNGad2xw29hWv/+UjhjhnZ+zZZ+OiwPCQEEEEAAAQQQQKD3AhuvvU5atmxpLyhz0CAZfPHFvS+UEhBAAAEEEEAAAQQQSBABOsAS5ERRTQQQQKAvBNqam2X7k09K9e13SMP778d8lxnFxVI063Qp+s53JLOoKOb7YwcIIIAAAggggECqCNQ997zUPvSQ93CH/uIqycjP984zgQACCCCAAAIIIIBAsgvQAZbsZ5jjQwABBMIQaK2v12EJ75fqO++UprVrw9iid6tkfWFPKTn7bCk44QRJ17u/SAgggAACCCCAAALRE2gf+vAXv/AWaM9XHXj00d55JhBAAAEEEEAAAQQQSAUBOsBS4SxzjAggEDOBtpYWqXvmWdnxwgvS1tgYs/3EtODWFtm5eInYDyW+KS07WwpOOlEKTzopqp1UaVlZkrXnnjzjyxebaQQQQAABBBBAIIoCG6+9Vpo3b24vMaO0VIb8/Ioolk5RCCCAAAIIIIAAAggkhgAdYIlxnqglAgg4TKC1oUFqH3hAtlZWStPKVQ6rXe+qk1FYKEWn67CEp58mmTpEIQkBBBBAAAEEEEAgcQTqnntOhz582Fvhsl9WMNS0V4MJBBBAAAEEEEAAgVQSoAMslc42x4oAAr0WaK6pkZp//ENq7r5HWnQ6mVLWHntI8VmzXXd85eQk06FxLAgggAACCCCAQEoItGzbJut9hz487jgZeNRRKXHsHCQCCCCAAAIIIIAAAoECdIAFijCPAAIIBBFoXLNGqu+YL9sWLpQ2vfvLN6Xrw8SLZs6U7LFjfLMTajqzpERyJ02StIyMhKo3lUUAAQQQQAABBBDoENhwzbXSsnlLe0bGoFIZesXlHQuZQgABBBBAAAEEEEAgxQToAEuxE87hIoBAZAINH38sW2+9TbY/9piIPu/LN2UOK5OSs86SwhkzJD0vz3cR0wgggAACCCCAAAII9KlA3TPPyPZHHvHus+yXV4sNbU1CAAEEEEAAAQQQQCBVBegAS9Uzz3EjgECXArvefFO2/P1W2aHPUAhM2V/8opR897uS/9VjJS0rK3Ax8wgggAACCCCAAAII9KmADdO9vuKX3n0WfOt4GXjkEd55JhBAAAEEEEAAAQQQSEUBOsBS8axzzEknUP/GG9K2a1fSHVc8Dqhle53U3Huv1L/ySqfd506ZLKXnniu5U6ZIWlpap+VkIIAAAggggAACCCBgAg0ffSQtW7f2GUbNvfdJyxbX0IeZgwbJkMsZ+rDP8NkRAggggAACCCCAgGMF6ABz7KmhYgiEL7D+yiul8dPPwt+ANSMSGHD0UVI6d67k7LdfRNuxMgIIIIAAAggggEBqCmz56y1S98QTcTn4ofN06MOCgrjsm50igAACCCCAAAIIIOAkATrAnHQ2qAsCCDhHICNDCr75TSk5d45kjxnjnHpREwQQQAABBBBAAAEEQggUnHCCDJw+PcRSshFAAAEEEEAAAQQQSC0BOsBS63xztEkqkLP//mJDnZCiI9B/3N5SNGuW9BsxPDoFUgoCCCCAAAIIIIBASglk7zVWWmq39ekxZ48cKYMvuqhP98nOEEAAAQQQQAABBBBwsgAdYE4+O9QNgTAFhl1zTZhrshoCCCCAAAIIIIAAAgjEWmDQD34Q611QPgIIIIAAAggggAACCHQjkN7NchYjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkFACdIAl1OmisggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAt0J0AHWnRDLEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEkqADrCEOl1UFgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoDsBOsC6E2I5AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAQgnQAZZQp4vKIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIdCdAB1h3QixHAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIKAE6wBLqdFHZGAiM0DLv0FinsVujSuOPGkUaJAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEhAgcwErDNVRiBaAqO1oCUagzUe0vhQ4xCNH2t8VeNQja0aJAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEggAe4AS6CTRVWjLvAXLdE6vy7QOEHjUo0jNf6gMU7jGg0SAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIJJgAHWAJdsKobtQERmlJX9Go0rhZwzf9Qmd2apyhkee7gGkEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBwvgAdYM4/R9QwNgJ2p5elpzRa26c6/qnTycUauRqTO7KZQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgUQQ4BlgiXCWqGMsBGyIQ0sfu146/fuJ5tgdYntpPNtpqX/Gcv9Z79ze3ikmEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoM8EuAOsz6jZkcMECtz1qQ1RL09+YYjlZCOAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBDBbgDzKEnhmrFXSDNXYO2MGoyIcQ6dmfYQSGWkY0AAggggAACCCCAAAIIIIAAAggggAACCCCAAAIxEuAOsBjBUqzjBTx3eHnuBAuscL47w7Ne4HLmEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwKEC3AHm0BNDtWIu8JF7D/aMr2BprDsz1DPCgm0TmFf+wQcfyIQJoW4QC1ydeQQQQAABBBBAAIHeClj7S1N5b8the0cL0M529OmhcggggAACCCCQjAK0s5PxrCb/MXmGeUv+I+UIEfAXGK2zn2pUadh0q4YnDdSJ9Rp2h+QgjZ0aPUkrdCO7k6yqJxv30TZ7u/fzYR/tL5l3g2Xvzy6GvTe0EnDEMToC0SuF92TvLTGMzLBcV9+uMTKyzVg7gQQSoZ1tnHx2o/OmwhHH6AhEpxTejzhGRyA6pfB+xDE6AuGXUq6r0s4O34s1EUAAgbgKPKl7t2d8nR9Qi9+7828JyE/GWXtOmQWp9wJYYth7geiUwHsRx+gIRK8U3pO9t8Sw94aUgEA8BPjsRkcdRxyjIxCdUng/4hgdgeiUwvsRx+gIUAoCSSzAEIhJfHI5tG4FfqBrLNG4UeMoDRsvZ5LGERo29OEVGiQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIMAEb4o2EQKoKfKYHPlGjUsM6vi7SsOEQrUNsisZWDRICCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggkmAB3gCXYCaO6URdYrSWeHfVSKRABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiJsAdYHGjZ8cIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAKxEKADLBaqlIkAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnERKNG9ztF4QONTjV0atRovaZyjka4RLE3VzMc0qjXqNd7W+IlGhkZgKtSMizXu0Xhfo1mjTeNojWApTTO/qnGTxpsaNRoNGh9p/FFjiIbTkhMdzegEjX9qfKhhjnZ+P9G4V2OihtOSUx0DnUo1Y4OGvY/ts+K05FTHCoUys1Bhn3snJac6eozsffgbDft822d7m8YbGjdoOCk51THU+9A3/wwHQTrV0YhGatyiYe9FaxNs1FiqMVejnwYJgVQWcOJnl7Z2dL6z2PuatnbnT3ehZkXy3a9zCSK0tUV64lihmL7tmMBp2trd/xbh+36krd2h0ZP3Y+D7L9g8bW3XZzbUb2OeM0Bb2yPBKwIIIIAAAj0Q+J5uYw2RdRrWQXWdxh0a2zQs/z8a9iXZN31LZ6wTa4fG7RqeH2Bt/X9rBKYDNMPT2Fmt056Og1D/yfd3r79bX5/W+K3GHzTe0rBybPuxGk5KTnQ0n/kan2tYJ5gZ2g/j92s0aLRqzNFwUnKqY6CRGdZp2PvRiR1gTnWscJtV6qtNB8YYzXNScqqjGR2osUmjReNxjes1/qjxsMYKDSclpzpWKFKwsP9z7LPdpDFUwynJqY4HK5C1B+y9+KiG/T/zV401Gub4pEZgO0KzSAikjIATP7v9Vd8+n7S1/d+GkX5nsa3na9DW7r2jfwmu7yu0tV2fU/ushvMd2gwrNGz9So2KIDFG85yUnPj30eNDW9sj4Xrtyd/HCt00WNDWdn1Ow/1c09Z2vQf5FwEEEEAAgR4LHKlbHqcReKeX/ei3SsMa0DM0PClfJ+xHV/vCPNGTqa/2RXqJhq0/U8M3FenMURrF7sxKfbX1jnbPB75kacYVGradb7I63qJh2z7iu8AB0050NBY7L8HSlzSzQWObhpOuzneqo6/hmTpj78Hvu19f8l3okGmnOla4zaY7xKm7ajjV0f42rtGwz+/kIAdhf0OdlJzqGMroPF1gn/GFoVaIU75THa3Ty7xmB7jk6fx77mWHByxjFoFUEnDiZ5e2tuvvVm+/s9j7mLZ277/7Bf49oK3tEon0O7RtVaFh/ydP10iE5MS/j+ZGWzv6n2vf9yNt7fB/GzM32tq+7x6mEUAAAQQQiLLA5VqeNaBv8in3u+68O33yPJPWgLX1X/BkhHit1HxbL1QHWIjN2rOHube1KwITJTnR0exsqDQ7D8NtJgGSExz3VCfrdLhNo1zD/JzYAabVCpni6VihtTKz6RqJnuLpeLXimeMPEx1R6x9Px1B8y3WB+R4bagUH5sfT8QO3V+BFK8Z0o3uZ74U0lk9CAAGXQDw/u6HOwTBdYH8DaWu77qIxi558ZzFf2tqmEJkjbW2XWbB/KzWzu/djhXud6fqa6Cmefx9pa8f2Nx3a2h2fzkqd7O5zTVu7w4spBBwpkOnIWlEpBBAIV8CGf7Jkwx16knVyWXrC9eL37/90zp79MVUjW8PuEot2anQX6FunaO8j2uU50XEvPchxGls01kf7gGNUXrwdbQivSo1ajf/T8NzRqJMJleLtaFjTNCZoWDuhSuNZDXsvJlKKp+NpCmXDzd2lsY+G3WGbq/GZhv1ttuHoEiXF0zGY0UGaaVGl8bRGoqR4OtpdXntrfEPjbh8we09am2GnxlKffCYRQKBDIJ6f3Y5a+E/R1vb36Okcbe3I5WhrR+87NG3t3v0WQVs7dr/p0NaO/G8jbe3IzdgCgT4VoAOsT7nZGQJRFbDPrw0/Ycm3s2ucK0s+dr/6vlin1AqN8RqjNOxKlWinc9wF+tYp2vuIZnlOcTxaD8q+CNlwhyM1bNhLS3M0WtunnP2PExx/okTTNb6isV2jWCPRkhMczWxeAJx1lv9G4yoNuwLO6SmejnaXzWgN+xtcoWHvS/vByJO26oT97X7Mk+Hg13g6hmI5z73gVn1NhL+NVt14O/5c6zBVo1LjVI33NWy45G9qWN1O0VinQUIAAX+BeH92/WvTMUdbu8MikqmjdWXa2pGIdV6Xtnb0vkPT1u75bxG0tWP7mw5t7c5/+7rLoa3dnRDLEUAAAQQQ6KGA58GkjwZsbz+62g/UYwLyPbOL3cuneDKCvFa617EvipGkg3Vlu8PMOh/sB+BESE5xvF6x7Lx5Yr1OH5sIgO46xtvR7rLZpfEXH7NynTbPl3zynD4Zb8cTFehsDeuEtWdm7KkxR2ODhlleq5EIKZ6O4xTIrJo17M6BizWGaAzV+KmG5dl79YsaTk/xdAxmM0Az7f8XMzTPRElOcByuWHYXuOf/GHtt1Pi1hv2QREIAgc4CTvjsBtaKtra/SKXO2t+zcL6z0Nb2t/Odq9SZ7hxpa7uMevsdmrZ27x1pa4vE6jcd2tq+fxld0+H8fbQ1aWu7vPgXAQQQQACBqAlcoCXZlxS7gyvwLpfuOsCWuLedrK+hUqUu6O5LUOC2e2mG/UhuP0weH7jQofNOdMxTqwM17tGwuxuu0HB6irdjlgLZOOWfa1ij3ZPKdcLex4nSARZvR49bsNeDNNN+LLcoDbaCg/Li7Wg/ENn7zsJ+PA1Mv9MMW/a3wAUOm4+3YzCOczXT7O4PttCheU5wtP9TVmq8pmF3P9jfyREal2pYR621Gwo0SAgg0CHghM9uR21cU7S1A0Uie3aVZ2va2h6JjtdKnbT/X0N1JNLWFonVd2jPWaCt7ZHo/nNNWzt270fa2h3vQ89UpU509ffR1qOtbQokBBwskO7gulE1BBAILvBDzf6Thg1hdIRGtYZvqnXPhPoxK9+93LOe77Y9nR6rGz6vYZ1xMzUe1nB6cqKjme3UsAdyn67xpIYNj2FX+zo1OcHxMsWxRqfduZRIz1byPadOcPStT+D065rxqob9ANLVla+B2/X1vBMca3wO+gGfac+kJ+8QT4YDX53gGIxlrjvz78EWOjDPCY6Z6vIvjUEax2nYBQH2d3KNht0NcZOG/R9+oQYJAQRcAk747AaeC9ragSI9n6etHbkdbW3X0MEmF83v0L5ngra2r0bX07S1Y/d+pK3d9Xsv2FLa2sFUyEPAYQJ0gDnshFAdBLoRsHHX/6zxroZ1ftkdV4HpI3eGXSUamOw/55EadsW33S0TjWTDeL2gUapxikYiXJnvREel65Se0Jw0jS93WuKMDKc42hWT5rRIw67O8sQKnbZ0qIblbbMZByanOHZHs9m9Ql53K8ZpuVMcbfjS7W6DYO85z5f2nDg5dbdbpzgG1vMAzZioYZ/rpwIXOnDeKY57q80YDbtjPFib4Xm33QT3Ky8IpLqAUz67vueBtravRnSnaWuH50lbO/rfoYPJ09YOptI5j7Z2bN6PtLU7v9fCyaGtHY4S6yAQZwE6wOJ8Atg9AhEIXKLr/kHjTY0jNDZpBEvPuTO/GmTh4ZqXq7FEY3eQ5ZFmfUk3WKRRrDFD4yENpycnOoYyG+5eYB2WTktOcnxacW4PEv90o210L1vgnnfSi5Mcu3KxO7/sxw9L0eo8d5UWnX+d5uj5O7xvkMPz5FUFWRbvLKc5+nqc5565TV+tQ9vJyUmO2W4ou0glWLI7wyzZ8KYkBFJdwEmfXc+5oK0dne8sHs/AV9ragSLB52lrR/c7dDBl2trBVELn0daO3m86HmXa2h6JyF5pa0fmxdoIIIAAAgiEFLhSl9gPfss0rLOpq2RDHNrVY9bBZVfLe1J/nbCOLyvHhinsKlXqQlvv6C5WsiuEtmjUaxzbxXpOWuQ0R2ssTQ0BdLDmb9do0bCripyUnOYYyqZcF9j7+KVQK8Q532mOA9XDPteBqZ9m3Kxhlh9oOO3iGac5KlH7307zekej0DLcyabf1bBlZ2k4KTnR0eNjdx3akENNGkM9mQ59dZqj/T9jdx3ae25OgJm9H+0zbct+ELCMWQRSTcBpn13zt/+TaWt3/U6s1MX2NyzUdxba2i6faHz3C3Ymyt3+tLVdOpVuj1DvR9ra0Xs/mrF99mlrK0KIVKn5Xf199N2Mtravhv90pc525Uhb29+LOQQcKWBDRpEQQMDZArO1epUaLRo3aQQbd7xK8ys1POkEnfiPRoPGfRrVGsdrjNOw/FM17D9x3/RbnfFcIT5Np0dr2DBT6zUsPegOmy7S+FTDOuOe1Qj1peePumybhhOSEx0LFcZ+mPxQw8Z9X6Nhd+jZUDdHali6WON37VPO+MeJjqFkynXBCo3FGvaedlJyomO5ApnXmxpva9hn3+4OsTtOR2rYj3DHaNhypyQnOnpsbtSJ8zXWajzizvymvo7QeFBjhkarhhOSkx3N5xyN2zQWapibU5NTHa1e8zWs3W//Z7+hYf+PW7vAPuMva0zXiMad4VoMCYGEE3DiZ5e2dnS+s9DWjo5jqA91uS5YoUFb2yVk3ze6+g5drsvNi7Z2736LUML2RFs7Oo6GSVvb9Z7y/BvJb2O2jbUj5mvQ1jYNEgIIIIAAAj0QqNBt2rqJRbo8MB2qGY9pWAfLLo13NC7UyNAIlqo0s6v9VPhsVN7Nup5ybD2npAqtiKdeoV4XBalsLB2zdH92xfEzGtb5ZR2Wdq4+1bDh+iZpOC1VaIVC+XnyFwWpdCwdg+yuPatc/7U6heqgbV8pTv9U6H49XqFeFwWpWywd83V/9kXSfgzfoGFDou3QeEvjeo3BGk5LFVqhUH6e/EVBKh1LR9/dnakz5mmO9tm2jgfrFAv1d1gXxSVV6F49XqFeFwWpWV85vuKu37FB6uCkrAp3PUMZWv4ijcDUF46H606tA9E6tps07D25XONSjf4aJARSWaBCD76rz208PrvlYdTJ6mXrOSVVaEWc5khbO3Sbo6qb82Xns7tUrivYOaetHfq9X6E+nkRbO/rvR9ranneX67VKX7r6O1zhWq3Tv7S1/UmqdDZSR9ra/obMIYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgfIGFWsU2jQu7qOrBuqxJY4VGfhfrsQgBBBBAAAEEEEAAAQRcArSzeScggAACCCCAAAIIIIAAAgggEEeBEt33Oo0GjS8FqUeu5n2k0aIxLchyshBAAAEEEEAAAQQQQKCzAO3szibkIIAAAggggAACCCCAAAIIINCnAsfq3lo13tbIDtjzX3Xe7hC7JiCfWQQQQAABBBBAAAEEEOhagHZ21z4sRQABBBBAAAEEEEAAAQQQQCDmAjfqHqyj6/c+e/q6O2+Zvmb55NvkFzRu0bBhEXdrbNF4QONAjcC0h2b8UmOpxgaNRo21Gndr7KURmPbWDKuLlf9Fjf9obNawTrrJGiQEEEAAAQQQQAABBBJFgHZ2opwp6okAAggggAACCCCAAAIIIJCUAv31qN7TsE6mozRKNayzaqfGOA3fNElnajRsWMRHNX6jcafGdg0bStG2901n6YyV84jGnzV+rfGghj1XrFbDOrl8k6cDbJFmWplLNKxj7u8a+2qQEEAAAQQQQAABBBBIFAHa2YlypqgnAggggAACCCCAAAIIIIBA0gocoEdmd3Ot0XhMw+7C+r6Gb7IhEldq1GtM8V2g03tqbNRYpeF7x9gQnc/TCEwTNWOXht055ps8HWC2/1/4LmAaAQQQQAABBBBAAIEEFKCdnYAnjSojgAACCCCAAAIIIIAAAggkl8DP9HCs48niv0EO7dvuZfOCLLOsS9zLjwyxPDD7Kc3YoZHus8DTAWYdaZk++UwigAACCCCAAAIIIJCoArSzE/XMUW8EEEAAgZQU4AeplDztHDQCCCCAQJIL/FaP70KNoRoXBzlWz11fo3VZRZDlnuEM7fU5n+Un6PRcjYM0SjQC2xEFmmfDKvqmN3Sm2TeDaQQQQAABBBBAAAEEElSAdnaCnjiqjQACCCCQmgKBP1ylpgJHjQACCCCAQHIJ2DPAbBhESzY8YWCyzitL33G9hPx3gM8Suyvseo2tGs9o2J1dVrbdZXayxngNG1oxMG0IzGAeAQQQQAABBBBAAIEEFaCdnaAnjmojgAACCKSmAB1gqXneOWoEEEAAgdQWqHUf/rH6asMXdpesY+tKjdUaEzQ2a/imI3xnAqatg4yEAAIIIIAAAggggEAqCNDOToWzzDEigAACCCSMgO+zOhKm0lQUAQQQQAABBHol8LJ768PCLKVM18vTeFEjsPPLhj3cX4OEAAIIIIAAAggggECqC9DOTvV3AMePAAIIIIAAAggggAACCCAQc4Eq3YPdfVWuEZj6a4YNYVincUzgQp1P05im0c+9LEtfGzU+0ch159mLLb9bw/ZjYc8c86S9dcLybvFk8IoAAggggAACCCCAQBIIVOkx0M5OghPJISCAAAIIJL8AQyAm/znmCBFAAAEEEAgUaNCMEzUe17AhEF/SeEvD8vfQOESjXKNIwzq+mjRu1viJxtsaj2hYJ9pRGvacMLszLNy7yXRVEgIIIIAAAggggAACSSlAOzspTysHhQACCCCAAAIIIIAAAggg4CSBKq1MqCtTPfUcqhO/0XhfY5fGDg27y+ufGqdp+A6VbHeBXaLxoYZ9sV+vUakxXOM+De4AUwQSAggggAACCCCAQNILVOkR0s5O+tPMASKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQP4H/B2dGtKF/4hiSAAAAAElFTkSuQmCC\" width=\"864\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.figure(figsize = (12,4))\n",
    "plt.subplot(121)\n",
    "plt.plot(yelp_williamsburg_one_hot_cumsum_top10)\n",
    "plt.title('Growth of Top 10 Business Categories - Williamsburg')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Counts')\n",
    "plt.legend(yelp_williamsburg_one_hot_cumsum_top10.columns)\n",
    "plt.show()\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(yelp_bushwick_one_hot_cumsum_top10)\n",
    "plt.title('Growth of Top 5 Business Categories - Bushwick')\n",
    "plt.xticks()\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Counts')\n",
    "plt.legend(yelp_bushwick_one_hot_cumsum_top10.columns)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 6,
        "hidden": false,
        "row": 49,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "Figures on the left show top 10 and 5 growing businesses in Williamsburg and Bushwick (cumulative sum over time). Bars in Williamsburg and Cafes in Bushwick seem to lead the others.\n",
    "<br>\n",
    "**Can we use this to predict the rent...?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# Williamsburg\n",
    "yelp_williamsburg_cumsum_perc_inc_df = pd.read_csv('csv/yelp_cumsum_percent_inc_rent_williamsburg.csv', index_col = ['Unnamed: 0'])\n",
    "yelp_williamsburg_cumsum_perc_inc_df.index = pd.to_datetime(yelp_williamsburg_cumsum_perc_inc_df.index)\n",
    "# Bushwick\n",
    "yelp_bushwick_cumsum_perc_inc_df = pd.read_csv('csv/yelp_cumsum_percent_inc_rent_bushwick.csv', index_col = ['Unnamed: 0'])\n",
    "yelp_bushwick_cumsum_perc_inc_df.index = pd.to_datetime(yelp_bushwick_cumsum_perc_inc_df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_williamsburg_cumsum_perc_inc_df[\"%increase_rent_month_later\"] = yelp_williamsburg_cumsum_perc_inc_df['%increase_rent'].shift(1)\n",
    "yelp_williamsburg_cumsum_perc_inc_df[\"%increase_rent_2_month_later\"] = yelp_williamsburg_cumsum_perc_inc_df['%increase_rent'].shift(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# yelp_bushwick_cumsum_perc_inc_df=yelp_bushwick_cumsum_perc_inc_df.rename(columns = {'rent':'%increase_rent'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "yelp_bushwick_cumsum_perc_inc_df[\"%increase_rent_month_later\"] = yelp_bushwick_cumsum_perc_inc_df['%increase_rent'].shift(1)\n",
    "yelp_bushwick_cumsum_perc_inc_df[\"%increase_rent_2_month_later\"] = yelp_bushwick_cumsum_perc_inc_df['%increase_rent'].shift(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# pearson's corr for percent increase in each business vs. percent increase in rent\n",
    "pearsons_corr_perc_inc  = yelp_williamsburg_cumsum_perc_inc_df.corr()\n",
    "corr_to_rent_perc_inc = pearsons_corr_perc_inc['%increase_rent']\n",
    "corr_to_rent_perc_inc = corr_to_rent_perc_inc.dropna()\n",
    "corr_to_rent_perc_inc = corr_to_rent_perc_inc.to_frame().transpose()\n",
    "corr_to_rent_perc_inc = corr_to_rent_perc_inc.loc[:, :'category_wine_bars']\n",
    "\n",
    "# pearson's corr for percent increase in each business vs. percent increase in rent a month later\n",
    "corr_to_rent_perc_inc_month = pearsons_corr_perc_inc[\"%increase_rent_month_later\"]\n",
    "corr_to_rent_perc_inc_month = corr_to_rent_perc_inc_month.dropna()\n",
    "corr_to_rent_perc_inc_month = corr_to_rent_perc_inc_month.to_frame().transpose()\n",
    "corr_to_rent_perc_inc_month = corr_to_rent_perc_inc_month.loc[:, :'category_wine_bars']\n",
    "\n",
    "# pearson's corr for percent increase in each business vs. percent increase in rent a month later\n",
    "corr_to_rent_perc_inc_2_month = pearsons_corr_perc_inc[\"%increase_rent_2_month_later\"]\n",
    "corr_to_rent_perc_inc_2_month = corr_to_rent_perc_inc_2_month.dropna()\n",
    "corr_to_rent_perc_inc_2_month = corr_to_rent_perc_inc_2_month.to_frame().transpose()\n",
    "corr_to_rent_perc_inc_2_month = corr_to_rent_perc_inc_2_month.loc[:, :'category_wine_bars']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# pearson's corr for percent increase in each business vs. percent increase in rent\n",
    "pearsons_corr_perc_inc_bushwick  = yelp_bushwick_cumsum_perc_inc_df.corr()\n",
    "corr_to_rent_perc_inc_bushwick = pearsons_corr_perc_inc_bushwick['%increase_rent']\n",
    "corr_to_rent_perc_inc_bushwick = corr_to_rent_perc_inc_bushwick.dropna()\n",
    "corr_to_rent_perc_inc_bushwick = corr_to_rent_perc_inc_bushwick.to_frame().transpose()\n",
    "corr_to_rent_perc_inc_bushwick = corr_to_rent_perc_inc_bushwick.loc[:, :'category_wine_bars']\n",
    "\n",
    "# pearson's corr for percent increase in each business vs. percent increase in rent a month later\n",
    "corr_to_rent_perc_inc_month_bushwick = pearsons_corr_perc_inc_bushwick[\"%increase_rent_month_later\"]\n",
    "corr_to_rent_perc_inc_month_bushwick = corr_to_rent_perc_inc_month_bushwick.dropna()\n",
    "corr_to_rent_perc_inc_month_bushwick = corr_to_rent_perc_inc_month_bushwick.to_frame().transpose()\n",
    "corr_to_rent_perc_inc_month_bushwick = corr_to_rent_perc_inc_month_bushwick.loc[:, :'category_wine_bars']\n",
    "\n",
    "# pearson's corr for percent increase in each business vs. percent increase in rent a month later\n",
    "corr_to_rent_perc_inc_2_month_bushwick = pearsons_corr_perc_inc_bushwick[\"%increase_rent_2_month_later\"]\n",
    "corr_to_rent_perc_inc_2_month_bushwick = corr_to_rent_perc_inc_2_month_bushwick.dropna()\n",
    "corr_to_rent_perc_inc_2_month_bushwick = corr_to_rent_perc_inc_2_month_bushwick.to_frame().transpose()\n",
    "corr_to_rent_perc_inc_2_month_bushwick = corr_to_rent_perc_inc_2_month_bushwick.loc[:, :'category_wine_bars']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "corr_to_rent_perc_inc = corr_to_rent_perc_inc[list(yelp_williamsburg_one_hot_cumsum_top10.columns)]\n",
    "corr_to_rent_perc_inc_month = corr_to_rent_perc_inc_month[list(yelp_williamsburg_one_hot_cumsum_top10.columns)]\n",
    "corr_to_rent_perc_inc_2_month = corr_to_rent_perc_inc_2_month[list(yelp_williamsburg_one_hot_cumsum_top10.columns)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "corr_to_rent_perc_inc_bushwick = corr_to_rent_perc_inc_bushwick[list(yelp_bushwick_one_hot_cumsum_top10.columns)]\n",
    "corr_to_rent_perc_inc_month_bushwick = corr_to_rent_perc_inc_month_bushwick[list(yelp_bushwick_one_hot_cumsum_top10.columns)]\n",
    "corr_to_rent_perc_inc_2_month_bushwick = corr_to_rent_perc_inc_2_month_bushwick[list(yelp_bushwick_one_hot_cumsum_top10.columns)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 55,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "### Williamsburg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 12,
        "hidden": false,
        "row": 57,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "f, ax = plt.subplots(figsize=(10, 2))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "sns.heatmap(corr_to_rent_perc_inc,cmap=cmap,vmax=.3, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc.shape[1])[:10], corr_to_rent_perc_inc.columns, rotation = 30, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(10, 2))\n",
    "labels = [''.join(wrap(corr_to_rent_perc_inc_2_month.index[0], 5))]\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "sns.heatmap(corr_to_rent_perc_inc_month,cmap=cmap,vmax=.3, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent a month later')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc.shape[1])[:10], corr_to_rent_perc_inc_month.columns, rotation = 40, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(10, 2))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "sns.heatmap(corr_to_rent_perc_inc_2_month,cmap=cmap,vmax=.3, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent two month later')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc.shape[1])[:10], corr_to_rent_perc_inc_2_month.columns, rotation = 40, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 25,
        "hidden": true,
        "row": 158,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# yelp_cumsum_rent_williamsburg_df[yelp_cumsum_rent_williamsburg_df.rent>2800]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 5,
        "height": 12,
        "hidden": false,
        "row": 57,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1058.4x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# log-transform\n",
    "log_yelp_cumsum_rent_williamsburg_df = np.log(yelp_cumsum_rent_williamsburg_df)\n",
    "sns.pairplot(log_yelp_cumsum_rent_williamsburg_df, x_vars=['category_bars','category_chinese','category_bakeries'], y_vars='rent', size=7, aspect=0.7, kind='reg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 4,
        "hidden": false,
        "row": 69,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "|          |rent vs. bars |rent vs. chinese rest.|rent vs. bakeries | \n",
    "|----------|:-------------|:---------------------|:----------------:|\n",
    "|p-value   |1.33e-15      |1.46e-16              |2.95e-15          |\n",
    "|r-squared |55.20%        |57.59%                | 54.31%           |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "lm1_multivariable = smf.ols(formula='rent ~ category_bars + category_chinese + category_bakeries', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# print the coefficients\n",
    "# lm1_multivariable.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 5,
        "hidden": false,
        "row": 69,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "p-values are all far less than 0.05.\n",
    "- we can reject the null hypothesis that there is no relationship between these parameters and rent\n",
    "- we can conclude that there is some correlation between the # of bars/chinese restaurants/bakeries and studio rent <br>\n",
    "\n",
    "Looking at r-squares, the chinese restaurant model performs the best"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 74,
        "width": 6
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "**Would they perform better together?**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 1,
        "height": 6,
        "hidden": false,
        "row": 76,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "|                    |rent vs. bars + Chinese rest. + bakeries | \n",
    "|--------------------|:----------------------------------------|\n",
    "|p-value - bars      |0.658                                    |\n",
    "|p-value - Chinese   |0.041                                    |\n",
    "|p-value - bakeries  |0.645                                    |\n",
    "|r-squared           |57.70%                                   |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": true,
        "row": 212,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# print('Would they perform better together?')\n",
    "# lm1_multivariable.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 6,
        "height": 2,
        "hidden": false,
        "row": 74,
        "width": 6
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "**Or could we predict the future?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "lm1_multivariable_two_month = smf.ols(formula='two_month_pred ~ category_coffee + category_newamerican', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# print the coefficients\n",
    "# lm1_multivariable.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 6,
        "hidden": false,
        "row": 76,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "|                    |rent vs. cafes and New American (opened 2 month ago) | \n",
    "|--------------------|:----------------------------------------|\n",
    "|p-value - cafes      |0.023                                    |\n",
    "|p-value - New American   |0.657                                   |\n",
    "|r-squared           |51.20%                                   |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 2,
        "hidden": false,
        "row": 47,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# lm1_multivariable_two_month.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 18,
        "hidden": true,
        "row": 192,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# log_yelp_cumsum_rent_williamsburg_df = np.log(yelp_cumsum_rent_williamsburg_df)\n",
    "# sns.pairplot(log_yelp_cumsum_rent_williamsburg_df, x_vars=['category_coffee'], y_vars='two_month_pred', size=7, aspect=0.7, kind='reg')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 5,
        "height": 11,
        "hidden": true,
        "row": 192,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# # ### STATSMODELS FOR CAFE COUNTS###\n",
    "# lm1_cafe_2_month = smf.ols(formula='two_month_pred ~ category_coffee', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# # print the coefficients\n",
    "# print('< number of cafes vs. rent >')\n",
    "# print(lm1_cafe_2_month.params)\n",
    "# print('Result - rent vs. number of cafes')\n",
    "# display(lm1_cafe_2_month.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_cafe_2_month.pvalues)\n",
    "# print('r-squared: {:.2f}%'.format(100*lm1_cafe_2_month.rsquared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 9,
        "hidden": true,
        "row": 183,
        "width": 3
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# ### STATSMODELS for BAR COUNTS### \n",
    "# # create a fitted model\n",
    "# lm1 = smf.ols(formula='rent ~ category_bars', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# # # print the coefficients\n",
    "# # print('< number of bars vs. rent >')\n",
    "# # print(lm1.params)\n",
    "# display(lm1.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1.pvalues)\n",
    "# print('r-squared: {:.2f}%'.format(100*lm1.rsquared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 3,
        "height": 9,
        "hidden": true,
        "row": 183,
        "width": 3
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# # ### STATSMODELS FOR CAFE COUNTS###\n",
    "# lm1_chinese = smf.ols(formula='rent ~ category_chinese', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# # print the coefficients\n",
    "# print('< number of cafes vs. rent >')\n",
    "# print(lm1_chinese.params)\n",
    "# print('Result - rent vs. number of cafes')\n",
    "# display(lm1_chinese.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_chinese.pvalues)\n",
    "# print('r-squared: {:.2f}%'.format(100*lm1_chinese.rsquared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 7,
        "height": 9,
        "hidden": true,
        "row": 183,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# ### STATSMODELS FOR MEXICAN COUNTS###\n",
    "# # create a fitted model\n",
    "# lm1_bakeries = smf.ols(formula='rent ~ category_bakeries', data=log_yelp_cumsum_rent_williamsburg_df).fit()\n",
    "# # # print the coefficients\n",
    "# # print('< number of mexican spots vs. rent >')\n",
    "# # print(lm1_mexican.params)\n",
    "# # print('Result - rent vs. number of mexican restaurants')\n",
    "# display(lm1_bakeries.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_bakeries.pvalues)\n",
    "# print('r-squared: {:.2f}%'.format(100*lm1_bakeries.rsquared))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 82,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "### Bushwick"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 14,
        "hidden": false,
        "row": 84,
        "width": 5
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "f, ax = plt.subplots(figsize=(4, 3))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "cbar_ax = f.add_axes([.905, .4, .05, .2])\n",
    "sns.heatmap(corr_to_rent_perc_inc_bushwick,cbar_ax = cbar_ax, cmap=cmap,vmax=.3, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc_bushwick.shape[1])[:10], corr_to_rent_perc_inc_bushwick.columns, rotation = 30, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(4, 3))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "cbar_ax = f.add_axes([.905, .4, .05, .2])\n",
    "sns.heatmap(corr_to_rent_perc_inc_month_bushwick,cmap=cmap,vmax=.3, cbar_ax = cbar_ax, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent a month later')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc_month_bushwick.shape[1])[:10], corr_to_rent_perc_inc_month_bushwick.columns, rotation = 30, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(4, 3))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "ax = plt.axes()\n",
    "cbar_ax = f.add_axes([.905, .4, .05, .2])\n",
    "sns.heatmap(corr_to_rent_perc_inc_2_month_bushwick,cmap=cmap,vmax=.3, cbar_ax = cbar_ax, center=0,square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, ax = ax)\n",
    "ax.set_title('correlation bet. % increase in business and % increase in rent two month later')\n",
    "plt.xticks(np.arange(corr_to_rent_perc_inc_2_month_bushwick.shape[1])[:10], corr_to_rent_perc_inc_2_month_bushwick.columns, rotation = 30, ha = 'center')\n",
    "plt.yticks(rotation = 0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 412,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "log_yelp_cumsum_rent_bushwick_df = np.log(yelp_cumsum_rent_bushwick_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 5,
        "height": 11,
        "hidden": false,
        "row": 84,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1058.4x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(log_yelp_cumsum_rent_bushwick_df, x_vars=['category_bakeries','category_chinese','category_coffee'], y_vars='rent', size=7, aspect=0.7, kind='reg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 5,
        "height": 3,
        "hidden": false,
        "row": 95,
        "width": 7
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "|          |rent vs. bakeries |rent vs. chinese rest.|rent vs. cafes    | \n",
    "|----------|:-----------------|:---------------------|:----------------:|\n",
    "|p-value   |6.59e-15          |2.55e-11              |2.37e-08          |\n",
    "|r-squared |55.24%            |44.51%                | 33.81%           |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 417,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# ### STATSMODELS for BAR COUNTS### \n",
    "# # create a fitted model\n",
    "# lm1_bushwick_coffee = smf.ols(formula='rent ~ category_coffee', data=log_yelp_cumsum_rent_bushwick_df).fit()\n",
    "# # print the coefficients\n",
    "# print('< number of cafes vs. rent >')\n",
    "# print(lm1_bushwick_coffee.params)\n",
    "# display(lm1_bushwick_coffee.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_bushwick_coffee.pvalues)\n",
    "# print('r-squared: '+ str(lm1_bushwick_coffee.rsquared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 419,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# ### STATSMODELS for BAR COUNTS### \n",
    "# # create a fitted model\n",
    "# lm1_bushwick_chinese = smf.ols(formula='rent ~ category_chinese', data=log_yelp_cumsum_rent_bushwick_df).fit()\n",
    "# # print the coefficients\n",
    "# print('< number of chinese vs. rent >')\n",
    "# print(lm1_bushwick_chinese.params)\n",
    "# display(lm1_bushwick_chinese.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_bushwick_chinese.pvalues)\n",
    "# print('r-squared: '+ str(lm1_bushwick_chinese.rsquared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 421,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# ### STATSMODELS for BAR COUNTS### \n",
    "# # create a fitted model\n",
    "# lm1_bushwick_bakeries = smf.ols(formula='rent ~ category_bakeries', data=log_yelp_cumsum_rent_bushwick_df).fit()\n",
    "# # print the coefficients\n",
    "# print('< number of bakeries vs. rent >')\n",
    "# print(lm1_bushwick_bakeries.params)\n",
    "# display(lm1_bushwick_bakeries.conf_int())\n",
    "# # null hypothesis - there is no relationship bet. # of bars and rent\n",
    "# print('p-values: ')\n",
    "# print(lm1_bushwick_bakeries.pvalues)\n",
    "# print('r-squared: '+ str(lm1_bushwick_bakeries.rsquared))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 6,
        "hidden": false,
        "row": 98,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "## Predict the Future Rent with Time Series Analysis\n",
    "#### Now that we saw that there are some correlations between business growth and rent increase, can we use time series analysis to predict the future rent?\n",
    "- as the rent varies area-by-area, I am goint to focus only on Williamsburg\n",
    "- use number of bars as exogenous parameter of time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "from statsmodels.tsa.statespace.sarimax import SARIMAX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# yelp_williamsburg_cumsum_perc_inc_df_arimax = yelp_williamsburg_cumsum_perc_inc_df.loc[:,:'%increase_rent']\n",
    "# rent_williamsburg = yelp_cumsum_rent_williamsburg_df['rent']\n",
    "yelp_williamsburg_cumsum_df_arimax = pd.concat([yelp_williamsburg_cumsum_perc_inc_df_arimax, rent_williamsburg], axis =1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 10,
        "hidden": false,
        "row": 104,
        "width": 6
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rent_williamsburg.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 6,
        "height": 10,
        "hidden": false,
        "row": 104,
        "width": 6
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "decomposition_williamsburg = seasonal_decompose(rent_williamsburg)\n",
    "\n",
    "# Gather the trend, seasonality and noise of decomposed object\n",
    "trend_williamsburg = decomposition_williamsburg.trend\n",
    "seasonal_williamsburg = decomposition_williamsburg.seasonal\n",
    "residual_williamsburg = decomposition_williamsburg.resid\n",
    "\n",
    "# Plot gathered statistics\n",
    "# rcParams['figure.figsize'] = 15, 15\n",
    "plt.subplot(411)\n",
    "plt.plot(rent_williamsburg, label='Original')\n",
    "plt.legend(loc='best')\n",
    "plt.subplot(412)\n",
    "plt.plot(trend_williamsburg, label='Trend')\n",
    "plt.legend(loc='best')\n",
    "plt.subplot(413)\n",
    "plt.plot(seasonal_williamsburg,label='Seasonality')\n",
    "plt.legend(loc='best')\n",
    "plt.subplot(414)\n",
    "plt.plot(residual_williamsburg, label='Residuals')\n",
    "plt.legend(loc='best')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "log_yelp_williamsburg_cumsum_df_arimax = np.log(yelp_williamsburg_cumsum_df_arimax['rent'])\n",
    "log_diff_yelp_williamsburg_cumsum_df_arimax = yelp_williamsburg_cumsum_df_arimax['rent'] - log_yelp_williamsburg_cumsum_df_arimax\n",
    "rolmean_log = log_yelp_williamsburg_cumsum_df_arimax.rolling(window=12).mean()\n",
    "rolstd_log = log_yelp_williamsburg_cumsum_df_arimax.rolling(window=12).std()\n",
    "rent_studio_williamsburg_log_moving_avg_diff = log_yelp_williamsburg_cumsum_df_arimax - rolmean_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# rent_studio_williamsburg_log_moving_avg_diff = rent_studio_williamsburg_log_moving_avg_diff.dropna()\n",
    "exog_log = yelp_williamsburg_cumsum_perc_inc_df_arimax['category_bars'][yelp_williamsburg_cumsum_perc_inc_df_arimax['category_bars'].index>='2012-10-01']\n",
    "model_log = SARIMAX(endog = rent_studio_williamsburg_log_moving_avg_diff, exog = exog_log, order = (1,1,1))\n",
    "fitted_log = model_log.fit()\n",
    "pred_in_log = fitted_log.predict()\n",
    "pred_in_log.name = 'pred_in_log'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "pred = fitted_log.get_prediction(start=pd.to_datetime('2017-01'), dynamic=False)\n",
    "pred_conf = pred.conf_int()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 13,
        "hidden": false,
        "row": 114,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pylab import rcParams\n",
    "rcParams['figure.figsize'] = 18, 6\n",
    "#Plot observed values\n",
    "ax = (np.exp((rent_studio_williamsburg_log_moving_avg_diff+rolmean_log)).plot(label='observed'))\n",
    "\n",
    "#Plot predicted values\n",
    "(np.exp((pred.predicted_mean)+rolmean_log)).plot(ax=ax, label='One-step ahead Forecast', alpha=.9)\n",
    "\n",
    "#Plot the range for confidence intervals\n",
    "ax.fill_between(rolmean_log.index,\n",
    "                np.exp(pred_conf.iloc[:,0]+rolmean_log),\n",
    "                np.exp(pred_conf.iloc[:,1]+rolmean_log), color='g', alpha=.5)\n",
    "\n",
    "#Set axes labels\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Housing Price')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 127,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "## Detecting Gentrification using Machine Learning Algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 8,
        "hidden": false,
        "row": 129,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "#### We've only looked at Williamsburg, and Bushwick, but can we generalize it to the whole NYC area?\n",
    "- use machine learning algorithm to detect if the area is:<br>\n",
    "    - **Gentrifying**: the area that was low-income in 1990 and experienced rent growth above the median SBA rent growth between 1990 and 2010-2014<br>\n",
    "    - **Non-gentrifying**: the areas that started off as low-income in 1990 but experienced more modest growth<br>\n",
    "    - **Higher-income**: the areas that had higher incomes in 1990.\n",
    "\n",
    "- for this, some of yelp data are combined with demographic data from 2016 Census\n",
    "\n",
    "*Source: http://furmancenter.org/files/sotc/Part_1_Gentrification_SOCin2015_9JUNE2016.pdf*\n",
    "  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from textwrap import wrap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "zipcode_neighborhood_df_test_exc_income = pd.read_csv('zipcode_neighborhood_df_test_exc_income.csv', index_col = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "X = zipcode_neighborhood_df_test_exc_income.loc[:,'avg_rating':]\n",
    "target = zipcode_neighborhood_df_test_exc_income['gentrification_label']\n",
    "X = X.replace('-', 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "# # correct the class imbalance\n",
    "# print(target.value_counts())\n",
    "# X_resampled, y_resampled = SMOTE().fit_sample(X, target) \n",
    "# print(pd.Series(y_resampled).value_counts()) #Preview synthetic sample class distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 2,
        "hidden": false,
        "row": 140,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "#### Random Forest Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 19,
        "hidden": false,
        "row": 142,
        "width": 8
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Top 10 Features:\n",
      "(\"% bachelor's degree or higher\", 0.1207)\n",
      "('% High school graduate (includes equivalency)', 0.082)\n",
      "('%, 9th to 12th grade, no diploma', 0.0815)\n",
      "('% Some other race', 0.0762)\n",
      "(\"% A Associate's degree\", 0.0749)\n",
      "(\"% Bachelor's degree\", 0.0729)\n",
      "('%, Less than 9th grade', 0.062)\n",
      "('% high school graduate or higher', 0.0608)\n",
      "('% White', 0.0478)\n",
      "('cafe_count', 0.0456)\n",
      "Accuracy: 90.71 (+/- 12.46)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data_train, data_test, target_train, target_test = train_test_split(X_resampled, y_resampled)\n",
    "forest= RandomForestClassifier(n_estimators= 40, max_depth= 5)\n",
    "forest.fit(data_train, target_train)\n",
    "feature_importances = forest.feature_importances_\n",
    "feature_importance_list = [round(value, 4) for value in feature_importances]\n",
    "\n",
    "def plot_feature_importances(model, data):\n",
    "    n_features = data.shape[1]\n",
    "    plt.figure(figsize=(15,4))\n",
    "#     labels = [ '\\n'.join(wrap(l, 35)) for l in data.columns] \n",
    "    plt.bar(range(n_features)[:60], model.feature_importances_[:60], align='center') \n",
    "    plt.xticks(np.arange(n_features)[:60], data.columns, rotation = 30, ha = 'right') \n",
    "    plt.xlabel(\"Feature importance\")\n",
    "    plt.ylabel(\"Feature\")\n",
    "\n",
    "plot_feature_importances(forest, X)\n",
    "\n",
    "# print('Train Set Score: {:0.2f}%'.format(forest.score(data_train,target_train) * 100))\n",
    "# print('test set score: {:0.2f}%'.format(forest.score(data_test, target_test)*100))\n",
    "\n",
    "\n",
    "feature_importance = dict(zip(X.columns, feature_importance_list))\n",
    "print('\\n', 'Top 10 Features:')\n",
    "sorted_dict = sorted(feature_importance.items(), key=lambda x: x[1], reverse=True)\n",
    "for item in sorted_dict[:10]:\n",
    "    print(item)\n",
    "kfold_scores_forest = cross_val_score(forest, X_resampled, y_resampled, cv=5)\n",
    "print(\"Accuracy: %0.2f (+/- %0.2f)\" % (kfold_scores_forest.mean()*100, kfold_scores_forest.std() * 2*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 3,
        "hidden": false,
        "row": 137,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "|                       | Random Forest      | Gradient Boosting |  AdaBoost         |\n",
    "|-----------------------|:-------------------|:------------------|:-----------------:|\n",
    "|Accuracy Score (k-fold)|90.71 (+/- 12.46)   |82.66% (+/- 9.31%) |78.85% (+/- 16.16%)|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import label_binarize\n",
    "from itertools import cycle\n",
    "from sklearn import svm, datasets\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from scipy import interp\n",
    "\n",
    "# # Import some data to play with\n",
    "# iris = datasets.load_iris()\n",
    "# X = iris.data\n",
    "# y = iris.target\n",
    "\n",
    "# Binarize the output\n",
    "y = label_binarize(y_resampled, classes=[0, 1, 2])\n",
    "n_classes = y.shape[1]\n",
    "\n",
    "# Add noisy features to make the problem harder\n",
    "# random_state = np.random.RandomState(0)\n",
    "# n_samples, n_features = X.shape\n",
    "# X = np.c_[X, random_state.randn(n_samples, 200 * n_features)]\n",
    "\n",
    "# shuffle and split training and test sets\n",
    "X_train_roc, X_test_roc, y_train_roc, y_test_roc = train_test_split(X_resampled, y, test_size=.5,\n",
    "                                                    random_state=0)\n",
    "\n",
    "# Learn to predict each class against the other\n",
    "classifier = OneVsRestClassifier(RandomForestClassifier(n_estimators= 40, max_depth= 5))\n",
    "y_score = classifier.fit(X_train_roc, y_train_roc).predict_proba(X_test_roc)\n",
    "\n",
    "# Compute ROC curve and ROC area for each class\n",
    "fpr = dict()\n",
    "tpr = dict()\n",
    "roc_auc = dict()\n",
    "for i in range(n_classes):\n",
    "    fpr[i], tpr[i], _ = roc_curve(list(y_test_roc[:, i]), y_score[:, i])\n",
    "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
    "\n",
    "# Compute micro-average ROC curve and ROC area\n",
    "fpr[\"micro\"], tpr[\"micro\"], _ = roc_curve(y_test_roc.ravel(), y_score.ravel())\n",
    "roc_auc[\"micro\"] = auc(fpr[\"micro\"], tpr[\"micro\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 8,
        "height": 9,
        "hidden": false,
        "row": 142,
        "width": 4
       },
       "report_default": {}
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute macro-average ROC curve and ROC area\n",
    "lw = 2\n",
    "# First aggregate all false positive rates\n",
    "all_fpr = np.unique(np.concatenate([fpr[i] for i in range(n_classes)]))\n",
    "\n",
    "# Then interpolate all ROC curves at this points\n",
    "mean_tpr = np.zeros_like(all_fpr)\n",
    "for i in range(n_classes):\n",
    "    mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n",
    "\n",
    "# Finally average it and compute AUC\n",
    "mean_tpr /= n_classes\n",
    "\n",
    "fpr[\"macro\"] = all_fpr\n",
    "tpr[\"macro\"] = mean_tpr\n",
    "roc_auc[\"macro\"] = auc(fpr[\"macro\"], tpr[\"macro\"])\n",
    "\n",
    "# Plot all ROC curves\n",
    "plt.figure()\n",
    "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
    "         label='micro-average ROC curve (area = {0:0.2f})'\n",
    "               ''.format(roc_auc[\"micro\"]),\n",
    "         color='deeppink', linestyle=':', linewidth=4)\n",
    "\n",
    "plt.plot(fpr[\"macro\"], tpr[\"macro\"],\n",
    "         label='macro-average ROC curve (area = {0:0.2f})'\n",
    "               ''.format(roc_auc[\"macro\"]),\n",
    "         color='navy', linestyle=':', linewidth=4)\n",
    "\n",
    "colors = cycle(['aqua', 'darkorange', 'cornflowerblue'])\n",
    "for i, color in zip(range(n_classes), colors):\n",
    "    plt.plot(fpr[i], tpr[i], color=color, lw=lw,\n",
    "             label='ROC curve of class {0} (area = {1:0.2f})'\n",
    "             ''.format(i, roc_auc[i]))\n",
    "\n",
    "plt.plot([0, 1], [0, 1], 'k--', lw=lw)\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver operating characteristic to multi-class')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 4,
        "hidden": false,
        "row": 161,
        "width": 12
       },
       "report_default": {}
      }
     }
    }
   },
   "source": [
    "### Next Step..... \n",
    "- Could we generalize the regression model as well?\n",
    "- Use these parameters above and machine learning models (Decision Tree Regression) to predict the housing prices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
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   "source": [
    "Random Forest classifier performs the best overall \n",
    "It's performing questionably good - possibly there is data leakage:\n",
    "   - gentrification is classified based on \"income\" and \"rent\"\n",
    "   - demographic parameters like education level could highly be correlated to these\n",
    "   - if number of cafes, bars etc.. actually correlates to the rent, it also could cause data leakage "
   ]
  }
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