Customer_service_Requests_Analysis-gs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1b7d0dd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import the library\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "db8b014f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/macbookair/opt/anaconda3/lib/python3.8/site-packages/IPython/core/interactiveshell.py:3165: DtypeWarning: Columns (48,49) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n"
     ]
    }
   ],
   "source": [
    "#read file\n",
    "df_service = pd.read_csv ('~/Desktop/Pro/311_Service_Requests_from_2010_to_Present.csv', header=0,\n",
    "    sep=',', parse_dates=['Created Date', 'Closed Date', 'Resolution Action Updated Date'],index_col='Unique Key')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f51a569b",
   "metadata": {},
   "outputs": [
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       "      <th>Created Date</th>\n",
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       "      <th>Garage Lot Name</th>\n",
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       "      <th>Latitude</th>\n",
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       "      <td>Blocked Driveway</td>\n",
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       "      <td>11105.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>No Access</td>\n",
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       "      <td>10458.0</td>\n",
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       "      <td>Illegal Parking</td>\n",
       "      <td>Commercial Overnight Parking</td>\n",
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       "      <td>2016-01-01 03:24:00</td>\n",
       "      <td>NYPD</td>\n",
       "      <td>New York City Police Department</td>\n",
       "      <td>Illegal Parking</td>\n",
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       "      <td>11373.0</td>\n",
       "      <td>87-14 57 ROAD</td>\n",
       "      <td>57 ROAD</td>\n",
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      "text/plain": [
       "                  Created Date         Closed Date Agency  \\\n",
       "Unique Key                                                  \n",
       "32310363   2015-12-31 23:59:45 2016-01-01 00:55:00   NYPD   \n",
       "32309934   2015-12-31 23:59:44 2016-01-01 01:26:00   NYPD   \n",
       "32309159   2015-12-31 23:59:29 2016-01-01 04:51:00   NYPD   \n",
       "32305098   2015-12-31 23:57:46 2016-01-01 07:43:00   NYPD   \n",
       "32306529   2015-12-31 23:56:58 2016-01-01 03:24:00   NYPD   \n",
       "\n",
       "                                Agency Name           Complaint Type  \\\n",
       "Unique Key                                                             \n",
       "32310363    New York City Police Department  Noise - Street/Sidewalk   \n",
       "32309934    New York City Police Department         Blocked Driveway   \n",
       "32309159    New York City Police Department         Blocked Driveway   \n",
       "32305098    New York City Police Department          Illegal Parking   \n",
       "32306529    New York City Police Department          Illegal Parking   \n",
       "\n",
       "                              Descriptor    Location Type  Incident Zip  \\\n",
       "Unique Key                                                                \n",
       "32310363                Loud Music/Party  Street/Sidewalk       10034.0   \n",
       "32309934                       No Access  Street/Sidewalk       11105.0   \n",
       "32309159                       No Access  Street/Sidewalk       10458.0   \n",
       "32305098    Commercial Overnight Parking  Street/Sidewalk       10461.0   \n",
       "32306529                Blocked Sidewalk  Street/Sidewalk       11373.0   \n",
       "\n",
       "                 Incident Address       Street Name  ... Bridge Highway Name  \\\n",
       "Unique Key                                           ...                       \n",
       "32310363      71 VERMILYEA AVENUE  VERMILYEA AVENUE  ...                 NaN   \n",
       "32309934          27-07 23 AVENUE         23 AVENUE  ...                 NaN   \n",
       "32309159    2897 VALENTINE AVENUE  VALENTINE AVENUE  ...                 NaN   \n",
       "32305098      2940 BAISLEY AVENUE    BAISLEY AVENUE  ...                 NaN   \n",
       "32306529            87-14 57 ROAD           57 ROAD  ...                 NaN   \n",
       "\n",
       "           Bridge Highway Direction Road Ramp Bridge Highway Segment  \\\n",
       "Unique Key                                                             \n",
       "32310363                        NaN       NaN                    NaN   \n",
       "32309934                        NaN       NaN                    NaN   \n",
       "32309159                        NaN       NaN                    NaN   \n",
       "32305098                        NaN       NaN                    NaN   \n",
       "32306529                        NaN       NaN                    NaN   \n",
       "\n",
       "           Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  \\\n",
       "Unique Key                                                                  \n",
       "32310363               NaN             NaN                 NaN  40.865682   \n",
       "32309934               NaN             NaN                 NaN  40.775945   \n",
       "32309159               NaN             NaN                 NaN  40.870325   \n",
       "32305098               NaN             NaN                 NaN  40.835994   \n",
       "32306529               NaN             NaN                 NaN  40.733060   \n",
       "\n",
       "            Longitude                                  Location  \n",
       "Unique Key                                                       \n",
       "32310363   -73.923501   (40.86568153633767, -73.92350095571744)  \n",
       "32309934   -73.915094  (40.775945312321085, -73.91509393898605)  \n",
       "32309159   -73.888525  (40.870324522111424, -73.88852464418646)  \n",
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       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_service.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5b686ba2",
   "metadata": {},
   "outputs": [
    {
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    "df_service.shape"
   ]
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  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f1c56103",
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   "outputs": [
    {
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 300698 entries, 32310363 to 30281825\n",
      "Data columns (total 52 columns):\n",
      " #   Column                          Non-Null Count   Dtype         \n",
      "---  ------                          --------------   -----         \n",
      " 0   Created Date                    300698 non-null  datetime64[ns]\n",
      " 1   Closed Date                     298534 non-null  datetime64[ns]\n",
      " 2   Agency                          300698 non-null  object        \n",
      " 3   Agency Name                     300698 non-null  object        \n",
      " 4   Complaint Type                  300698 non-null  object        \n",
      " 5   Descriptor                      294784 non-null  object        \n",
      " 6   Location Type                   300567 non-null  object        \n",
      " 7   Incident Zip                    298083 non-null  float64       \n",
      " 8   Incident Address                256288 non-null  object        \n",
      " 9   Street Name                     256288 non-null  object        \n",
      " 10  Cross Street 1                  251419 non-null  object        \n",
      " 11  Cross Street 2                  250919 non-null  object        \n",
      " 12  Intersection Street 1           43858 non-null   object        \n",
      " 13  Intersection Street 2           43362 non-null   object        \n",
      " 14  Address Type                    297883 non-null  object        \n",
      " 15  City                            298084 non-null  object        \n",
      " 16  Landmark                        349 non-null     object        \n",
      " 17  Facility Type                   298527 non-null  object        \n",
      " 18  Status                          300698 non-null  object        \n",
      " 19  Due Date                        300695 non-null  object        \n",
      " 20  Resolution Description          300698 non-null  object        \n",
      " 21  Resolution Action Updated Date  298511 non-null  datetime64[ns]\n",
      " 22  Community Board                 300698 non-null  object        \n",
      " 23  Borough                         300698 non-null  object        \n",
      " 24  X Coordinate (State Plane)      297158 non-null  float64       \n",
      " 25  Y Coordinate (State Plane)      297158 non-null  float64       \n",
      " 26  Park Facility Name              300698 non-null  object        \n",
      " 27  Park Borough                    300698 non-null  object        \n",
      " 28  School Name                     300698 non-null  object        \n",
      " 29  School Number                   300698 non-null  object        \n",
      " 30  School Region                   300697 non-null  object        \n",
      " 31  School Code                     300697 non-null  object        \n",
      " 32  School Phone Number             300698 non-null  object        \n",
      " 33  School Address                  300698 non-null  object        \n",
      " 34  School City                     300698 non-null  object        \n",
      " 35  School State                    300698 non-null  object        \n",
      " 36  School Zip                      300697 non-null  object        \n",
      " 37  School Not Found                300698 non-null  object        \n",
      " 38  School or Citywide Complaint    0 non-null       float64       \n",
      " 39  Vehicle Type                    0 non-null       float64       \n",
      " 40  Taxi Company Borough            0 non-null       float64       \n",
      " 41  Taxi Pick Up Location           0 non-null       float64       \n",
      " 42  Bridge Highway Name             243 non-null     object        \n",
      " 43  Bridge Highway Direction        243 non-null     object        \n",
      " 44  Road Ramp                       213 non-null     object        \n",
      " 45  Bridge Highway Segment          213 non-null     object        \n",
      " 46  Garage Lot Name                 0 non-null       float64       \n",
      " 47  Ferry Direction                 1 non-null       object        \n",
      " 48  Ferry Terminal Name             2 non-null       object        \n",
      " 49  Latitude                        297158 non-null  float64       \n",
      " 50  Longitude                       297158 non-null  float64       \n",
      " 51  Location                        297158 non-null  object        \n",
      "dtypes: datetime64[ns](3), float64(10), object(39)\n",
      "memory usage: 121.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df_service.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f9724539",
   "metadata": {},
   "outputs": [
    {
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       "      <th>count</th>\n",
       "      <td>298083.000000</td>\n",
       "      <td>2.971580e+05</td>\n",
       "      <td>297158.000000</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>297158.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>10848.888645</td>\n",
       "      <td>1.004854e+06</td>\n",
       "      <td>203754.534416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.725885</td>\n",
       "      <td>-73.925630</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>583.182081</td>\n",
       "      <td>2.175338e+04</td>\n",
       "      <td>29880.183529</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.082012</td>\n",
       "      <td>0.078454</td>\n",
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       "      <th>min</th>\n",
       "      <td>83.000000</td>\n",
       "      <td>9.133570e+05</td>\n",
       "      <td>121219.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.499135</td>\n",
       "      <td>-74.254937</td>\n",
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       "      <th>25%</th>\n",
       "      <td>10310.000000</td>\n",
       "      <td>9.919752e+05</td>\n",
       "      <td>183343.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.669796</td>\n",
       "      <td>-73.972142</td>\n",
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       "      <th>50%</th>\n",
       "      <td>11208.000000</td>\n",
       "      <td>1.003158e+06</td>\n",
       "      <td>201110.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.718661</td>\n",
       "      <td>-73.931781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>11238.000000</td>\n",
       "      <td>1.018372e+06</td>\n",
       "      <td>224125.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.781840</td>\n",
       "      <td>-73.876805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11697.000000</td>\n",
       "      <td>1.067173e+06</td>\n",
       "      <td>271876.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.912869</td>\n",
       "      <td>-73.700760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Incident Zip  X Coordinate (State Plane)  Y Coordinate (State Plane)  \\\n",
       "count  298083.000000                2.971580e+05               297158.000000   \n",
       "mean    10848.888645                1.004854e+06               203754.534416   \n",
       "std       583.182081                2.175338e+04                29880.183529   \n",
       "min        83.000000                9.133570e+05               121219.000000   \n",
       "25%     10310.000000                9.919752e+05               183343.000000   \n",
       "50%     11208.000000                1.003158e+06               201110.500000   \n",
       "75%     11238.000000                1.018372e+06               224125.250000   \n",
       "max     11697.000000                1.067173e+06               271876.000000   \n",
       "\n",
       "       School or Citywide Complaint  Vehicle Type  Taxi Company Borough  \\\n",
       "count                           0.0           0.0                   0.0   \n",
       "mean                            NaN           NaN                   NaN   \n",
       "std                             NaN           NaN                   NaN   \n",
       "min                             NaN           NaN                   NaN   \n",
       "25%                             NaN           NaN                   NaN   \n",
       "50%                             NaN           NaN                   NaN   \n",
       "75%                             NaN           NaN                   NaN   \n",
       "max                             NaN           NaN                   NaN   \n",
       "\n",
       "       Taxi Pick Up Location  Garage Lot Name       Latitude      Longitude  \n",
       "count                    0.0              0.0  297158.000000  297158.000000  \n",
       "mean                     NaN              NaN      40.725885     -73.925630  \n",
       "std                      NaN              NaN       0.082012       0.078454  \n",
       "min                      NaN              NaN      40.499135     -74.254937  \n",
       "25%                      NaN              NaN      40.669796     -73.972142  \n",
       "50%                      NaN              NaN      40.718661     -73.931781  \n",
       "75%                      NaN              NaN      40.781840     -73.876805  \n",
       "max                      NaN              NaN      40.912869     -73.700760  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_service.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b92fff63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Complaint Type</th>\n",
       "      <th>City</th>\n",
       "      <th>counted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>ARVERNE</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>ASTORIA</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>BAYSIDE</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>BELLEROSE</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>BREEZY POINT</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>Vending</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>Vending</td>\n",
       "      <td>SUNNYSIDE</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>Vending</td>\n",
       "      <td>WHITESTONE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>Vending</td>\n",
       "      <td>WOODHAVEN</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>763</th>\n",
       "      <td>Vending</td>\n",
       "      <td>WOODSIDE</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>764 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Complaint Type           City  counted\n",
       "0     Animal Abuse        ARVERNE       38\n",
       "1     Animal Abuse        ASTORIA      125\n",
       "2     Animal Abuse        BAYSIDE       37\n",
       "3     Animal Abuse      BELLEROSE        7\n",
       "4     Animal Abuse   BREEZY POINT        2\n",
       "..             ...            ...      ...\n",
       "759        Vending  STATEN ISLAND       25\n",
       "760        Vending      SUNNYSIDE       15\n",
       "761        Vending     WHITESTONE        1\n",
       "762        Vending      WOODHAVEN        6\n",
       "763        Vending       WOODSIDE       15\n",
       "\n",
       "[764 rows x 3 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "complaintTypeAndcities = pd.DataFrame({'counted':\n",
    "                                  df_service.groupby(['Complaint Type','City']).size()}).reset_index()\n",
    "complaintTypeAndcities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e7ad4788",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Borough      Complaint Type         Descriptor               \n",
       "BRONX        Animal Abuse           Chained                      132\n",
       "                                    In Car                        36\n",
       "                                    Neglected                    673\n",
       "                                    No Shelter                    71\n",
       "                                    Other (complaint details)    311\n",
       "                                                                ... \n",
       "Unspecified  Noise - Vehicle        Engine Idling                 11\n",
       "             Posting Advertisement  Vehicle                        1\n",
       "             Traffic                Truck Route Violation          1\n",
       "             Vending                In Prohibited Area             2\n",
       "                                    Unlicensed                     5\n",
       "Length: 288, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_service.groupby(['Borough','Complaint Type','Descriptor']).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e33da329",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_service['Created Date'] = pd.to_datetime(df_service['Created Date'])\n",
    "df_service['Closed Date'] = pd.to_datetime(df_service['Closed Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cc37c1f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Histrogram\n",
    "df_service['Status'].value_counts().plot(kind='bar',alpha=0.6,figsize=(7,7))\n",
    "style.use('ggplot')\n",
    "plt.title('Complaint Status')\n",
    "plt.xlabel('Type Of Ticket')\n",
    "plt.ylabel('Number of Ticket')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "207836da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_service['Complaint Type'].value_counts().head(10).plot(kind='bar',figsize=(4,4));\n",
    "style.use('ggplot')\n",
    "plt.title('Complaint Type')\n",
    "plt.xlabel('Complaint')\n",
    "plt.ylabel('Number of Ticket')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "08aaabd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Borough      Complaint Type         Descriptor               \n",
       "BRONX        Animal Abuse           Chained                      132\n",
       "                                    In Car                        36\n",
       "                                    Neglected                    673\n",
       "                                    No Shelter                    71\n",
       "                                    Other (complaint details)    311\n",
       "                                                                ... \n",
       "Unspecified  Noise - Vehicle        Engine Idling                 11\n",
       "             Posting Advertisement  Vehicle                        1\n",
       "             Traffic                Truck Route Violation          1\n",
       "             Vending                In Prohibited Area             2\n",
       "                                    Unlicensed                     5\n",
       "Length: 288, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_service.groupby([\"Borough\",\"Complaint Type\",\"Descriptor\"]).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3056ab8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Complaint Type</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Blocked Driveway</td>\n",
       "      <td>77044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Illegal Parking</td>\n",
       "      <td>75361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Noise - Street/Sidewalk</td>\n",
       "      <td>48612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Noise - Commercial</td>\n",
       "      <td>35577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Derelict Vehicle</td>\n",
       "      <td>17718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Noise - Vehicle</td>\n",
       "      <td>17083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Animal Abuse</td>\n",
       "      <td>7778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Traffic</td>\n",
       "      <td>4498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Homeless Encampment</td>\n",
       "      <td>4416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Noise - Park</td>\n",
       "      <td>4042</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Complaint Type  count\n",
       "0         Blocked Driveway  77044\n",
       "1          Illegal Parking  75361\n",
       "2  Noise - Street/Sidewalk  48612\n",
       "3       Noise - Commercial  35577\n",
       "4         Derelict Vehicle  17718\n",
       "5          Noise - Vehicle  17083\n",
       "6             Animal Abuse   7778\n",
       "7                  Traffic   4498\n",
       "8      Homeless Encampment   4416\n",
       "9             Noise - Park   4042"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "majorcomplints=df_service.dropna(subset=[\"Complaint Type\"])\n",
    "majorcomplints=df_service.groupby(\"Complaint Type\")\n",
    "\n",
    "sortedComplaintType = majorcomplints.size().sort_values(ascending = False)\n",
    "sortedComplaintType = sortedComplaintType.to_frame('count').reset_index()\n",
    "\n",
    "sortedComplaintType\n",
    "sortedComplaintType.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2a380165",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sortedComplaintType = sortedComplaintType.head()\n",
    "plt.figure(figsize=(5,5))\n",
    "plt.pie(sortedComplaintType['count'],labels=sortedComplaintType[\"Complaint Type\"], autopct=\"%1.1f%%\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "af3fab3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "groupedby_complainttype = df_service.groupby('Complaint Type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3cb5f4ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(77044, 52)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grp_data = groupedby_complainttype.get_group('Blocked Driveway')\n",
    "grp_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb443e77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Created Date                           0\n",
       "Closed Date                         2164\n",
       "Agency                                 0\n",
       "Agency Name                            0\n",
       "Complaint Type                         0\n",
       "Descriptor                          5914\n",
       "Location Type                        131\n",
       "Incident Zip                        2615\n",
       "Incident Address                   44410\n",
       "Street Name                        44410\n",
       "Cross Street 1                     49279\n",
       "Cross Street 2                     49779\n",
       "Intersection Street 1             256840\n",
       "Intersection Street 2             257336\n",
       "Address Type                        2815\n",
       "City                                2614\n",
       "Landmark                          300349\n",
       "Facility Type                       2171\n",
       "Status                                 0\n",
       "Due Date                               3\n",
       "Resolution Description                 0\n",
       "Resolution Action Updated Date      2187\n",
       "Community Board                        0\n",
       "Borough                                0\n",
       "X Coordinate (State Plane)          3540\n",
       "Y Coordinate (State Plane)          3540\n",
       "Park Facility Name                     0\n",
       "Park Borough                           0\n",
       "School Name                            0\n",
       "School Number                          0\n",
       "School Region                          1\n",
       "School Code                            1\n",
       "School Phone Number                    0\n",
       "School Address                         0\n",
       "School City                            0\n",
       "School State                           0\n",
       "School Zip                             1\n",
       "School Not Found                       0\n",
       "School or Citywide Complaint      300698\n",
       "Vehicle Type                      300698\n",
       "Taxi Company Borough              300698\n",
       "Taxi Pick Up Location             300698\n",
       "Bridge Highway Name               300455\n",
       "Bridge Highway Direction          300455\n",
       "Road Ramp                         300485\n",
       "Bridge Highway Segment            300485\n",
       "Garage Lot Name                   300698\n",
       "Ferry Direction                   300697\n",
       "Ferry Terminal Name               300696\n",
       "Latitude                            3540\n",
       "Longitude                           3540\n",
       "Location                            3540\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_service.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7ad1b6cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_service['City'].dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d354e496",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/macbookair/opt/anaconda3/lib/python3.8/site-packages/pandas/core/series.py:4463: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    }
   ],
   "source": [
    "grp_data['City'].fillna('Unknown City', inplace =True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a218c269",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HcnKyARirV6822zz55JPGs88+axiGYZw7d84oUaKE8b///c+mn7lz5xqlS5c2jwMCAoyYmBjDMAzjhRdeMN555x2jVKlS5t/RlSpVMqZPn17otcXFxRkuLi7GpUuXDMMwjPXr1xuAsWPHDsMwLv/DQuXKlY3x48cX2oeIyL1KU3RFRORvZ/ny5Xh4eFCiRAlq1apFYGBgvik6eZKSkihfvjw1atQwy1xdXWnUqBFJSUk3NO4jjzxCYGAgVatWpXPnznz66adkZmbatLFYLNStW9c8rlSpEnB5KmJePI0bN8bFxcVsU7duXUqXLm3G07p1azZs2MCpU6dYunQpDz/8MK1atWLp0qUALF26lNatWxcZa1hYGK6urjZx5MUAsG3bNho3bmxzzkMPPXTd96Iwb775Jh988AGNGjViyJAh+aZbXo/Tp09z8OBBWrRoYVMeHh7O3r17zanK12P9+vXUqFHDZlrY7bBu3Tq+++47cw1CDw8PypcvT1ZWFjt37gRuz73Ic63X8/z58wwdOpSaNWtSrlw5PDw8+PHHH22mDN+I++67Dz8/P5uyo0eP0qdPH0JDQylTpgweHh4kJSUVOkbZsmXp1asXjz32GG3atGHs2LGkpKSY9evWrSM9Pd3sK+/PihUrzHu4bds2GjZsaDM9ulmzZteMP2/6dEFu5P115WfZwcGBChUqUKdOHZsyb29vc4p9nqs/S02bNmXbtm2Fxrtx40aefvppqlatSqlSpcx7f63Xr169ejbHV78vrsft/LwVpn379pQuXdr8Of3FF1/g4eHBU089ZdOuqPu2bt06cnJyqFSpks375YsvvjDfL4VxdHRk48aNbNy4kU2bNjFv3jw+//zzIjcgSUpKKvCeZGVlsXv3bpKSksjKyir0fZbn008/5V//+hdLly7lkUceMcuv53q2bdtGWFgYZcuWNc+rVavWLa+7ahgGFovFpqxhw4ZFnhMaGkqDBg34/PPPAcjMzOSnn36iW7duwOX7deHCBTp27GhzPa+++iqnTp0ylxS48u+yZcuW8dhjj9G8eXOWLl1KSkoKhw4dsvn7LS4ujhYtWuDr64uHhwddunQhJyeH9PR0AB544AHq16/PZ599BsD//vc/jhw5YsYlImJPlOATEZG/nUaNGrFx40aSk5O5cOECv/zyC4GBgYW2v/oXGSj4F5xr8fDw4I8//uC7774jODiYTz75hGrVqtmssefg4GCzGUHeGFartch4rixv3Lgxrq6uLF++3EzmtWrVio0bN7J//37++OOPayb4rkwg5vVt/P81ja4Vx6146aWX2LdvH7179+bw4cO0adPGZn2lG3F1fFfHf7P93A5Wq5XIyEgzaZD3Z8eOHeYadLfzXlzr9YyKiuKLL77gnXfeYdmyZWzcuJEnnniCnJycmxqvZMmS+cq6d+/OihUrGD9+PCtWrGDjxo3Uq1evyDFmzJjB+vXreeSRR/jtt9+oVasW06dPBy7fw7CwsHz3MDk5mRkzZgAFf06v9/W8VrvreX85OzvnO6egsis/3wUp6r17/vx5Hn30USwWC7NmzWLt2rWsW7cOi8VyzdevoPfFtWIpzO36vBXEycmJnj17mq/rZ599Rvfu3fPFf7UrY7BarZQuXTrf+2Xbtm3873//u2YM1apVo1q1atSoUYPnn3+eAQMG8MEHH5CdnV3oOYXdkyvLr/U+e+ihh/D09GTmzJk3fD038/fUtWRkZJCRkUFQUJBNeUGf+at169aNb775hpycHL766ivKli3L448/bl4PwH/+8x+b69myZQs7d+40N+Bp3bo1y5YtIykpiTNnztCwYUNat27Nr7/+ytKlS6lSpYq5ruuaNWv4xz/+QYsWLfjuu+/YsGGDud7flZ+N3r17M2fOHC5evMhnn31Ghw4d8Pb2vvWbJSJylynBJyIifzslSpSgWrVqBAQE2DzVVJCaNWuSmZlp8/RMdnY2a9eupWbNmsD//ZJ86dKla47t6OhIixYtePfdd1m/fj0VK1Ys9OnBwuJZtWqVzS8nmzZt4tSpUzbxNG3a1PyFpnXr1nh5eVGzZk3effddHB0db3knyxo1arBq1SqbstWrV99Sn3kqVqzISy+9xOeff87MmTP58ssvOX36NHD52q51nz09PalcuTK//fabTfnvv/9O1apVcXd3v+5YHnzwQZKSkq5745DrfS/Ur1+fzZs3ExQUZCYO8v5c+bRNUffiZscuyO+//06XLl147rnnqFu3LoGBgfk2abiee3+tMfr06UP79u2pXbs2FStWNDdIKEqtWrX45z//yf/+9z969uzJp59+Cly+h6mpqXh6eua7h76+vsDlz8uaNWts4s7bEKUoDz74oM1mHle6ne+vwlz9WVq1ahVhYWEFtk1OTubo0aOMHj2aVq1aERYWxokTJ25Lgu1uf96Keg+//PLLbNq0iU8++YRNmzbZbMaSp6j7Vr9+fU6ePElWVla+98vVT5teDycnJ3JzcwtN8NWsWbPAe5K3YU6NGjVwc3Mr9H2Wp3bt2ixbtoy4uDheeeUV83W9nuupWbMm27Zt4+TJk2Z/SUlJ5iYTN2PcuHE4Ozvz9NNP3/C5zz//PGfOnGHx4sXExsbywgsvmE/X1qxZEzc3N1JTU/NdT7Vq1cx/+Hr44Yc5fvw4kyZNokWLFjg5OdG6dWt+++034uPjbf7xKiEhAS8vL95//30aNWpEcHBwgT/LO3fuTFZWFtOnT2fx4sW8/PLLN3l3RESKlxJ8IiIiRWjdujUNGzbkhRdeIDExka1bt/Liiy+SlZXFa6+9BoC/vz8ODg78+OOPZGRkFPrL04IFC5g0aRLr169n//79fP/99xw4cMBm+u+19OvXj9OnT9O9e3e2bt1KQkICkZGRNGvWzNxFNS/uL7/8ktDQUPNJhNatWzN37lxzR8VbMXDgQL7++ms+/vhjdu3axeeff25OvbqVJ0b69evHjz/+aE5hi4uLo0qVKpQqVQq4vENsYmIi+/fvJzMzs9Cnjd566y0+/vhjZsyYwc6dO5k+fTrTpk1j2LBhNxTP888/j7+/P+3btyc+Pp49e/bw66+/8s033xTY3svLCw8PD5YsWUJ6ejonTpwosN2wYcNITk6ma9eurF27lj179rBs2TLeeOMNM+l1rXtxtet9HxYkJCSEBQsWsHbtWrZt28Yrr7xCWlqaTZuqVauyfv16du/eTWZmJhcvXrzu/vPG+PLLL9myZQsbN27k+eefLzJ5tGvXLoYMGUJCQgL79u1j1apVrFixwvy8dOnShapVq9K2bVuWLFnC3r17WbNmDWPGjOH7778H4LXXXuPo0aO88sorJCcn8+uvv/L2229fM9bhw4fzv//9jzfffJPNmzeTkpLCnDlzzCnCt+v9VZgffviBKVOmsHPnTj7++GO++eYbBgwYUGBbf39/XF1d+fjjj9m9eze//vorb7zxxm15cutuf96K+vz4+fnx+OOP88Ybb9CyZUuCg4PznV/UfWvdujURERE888wzfPfdd6SmprJ+/Xoz7mtJT08nPT2d/fv3s2jRIj788EMefvhhPD09C70n3377LWPHjmXHjh3Mnz+fkSNHMnDgQFxcXPDw8GDgwIGMHDmSmJgYduzYwaZNmxgzZky+vvKShT/++CMvvfQSVqv1uq7nhRdeoFSpUnTt2pVNmzaxevVqevToQYkSJa7r9Th69Cjp6ens2bOHJUuW8Pzzz/Phhx8yadIkqlatel19XKlcuXK0bduWd999l3Xr1vHiiy+adR4eHgwbNoxhw4YxZcoUUlJSSEpK4uuvv2bIkCFmu4oVKxISEsLcuXPNZF69evVwcHBg4cKFNgm+kJAQjh49ysyZM0lNTeXzzz9n6tSp+eIqWbIkXbt2ZeDAgfj5+dnsKi8iYleKYd0/ERGRYlPQLrpX46rF6NPS0oznnnvOKF26tOHm5ma0aNHCWLdunc0548aNM3x9fQ0HBwcjPDy8wH5/++03o1WrVoaXl5fh6upqVKtWzRgzZoy5U9/VGzEYRsGLzq9atcpo3ry54ebmZpQuXdp4/vnnjSNHjtict3btWgMw+vfvb5YtXLiwwMXVC9pk4+p7FBsba1z9teHf//634evra7i5uRmPPvqoMX36dAMwMjMzC7z+gvq+emH6Pn36GNWrVzfc3NyMcuXKGU888YSxdetWs37dunXGAw88YLi5uRW5sYnVajXGjx9vBAQEGE5OTkbVqlWNSZMm2bS5nkX/DePyzsWRkZFG+fLlDVdXVyMkJMSYPXu2YRj5N9kwjMuLwueN6+/vbxhGwa/t5s2bjfbt2xtlypQx3NzcjKCgIOPll182d7+91r0oSEHvw+t5Pffv3288+uijhru7u+Hj42O88847Ro8ePWzey7t37zaaN29ulCxZssjNLwq7r5s3bzYeeughw83NzfD39zdiYmLybdxx5SYbaWlpxtNPP21UqlTJcHFxMSpWrGj06tXLZlOBzMxMo3fv3oavr6/h7Oxs+Pr6Gh06dDA2bNhgtomPjzdq1apluLi4GDVr1jR+/fXXa26yYRiG8dNPPxmNGzc23NzcDE9PT6Nly5bG7t27DcO4vvdXQRthFLRpRUhIiPH222+bx4AxadIk46mnnjJKlChh+Pj45Fvw/+q+//Of/xjVqlUzXF1djXr16hnLly83HB0dzfdpXr9Xb7Jx9T24+vUojs9bQZ+fPN9//70BFLib9PXct/PnzxtDhgwxAgICDGdnZ+O+++4zHnvsMePXX38tNJ68TTby/jg5ORkBAQFG3759bX7WFXR9c+bMMUJDQ8335rBhw2w2fLFarcaHH35oBAcHG87Ozoa3t7e56YRh5H+dd+7caVSpUsV44YUXjNzc3Ou6ng0bNhiNGzc2XFxcjMDAQOOrr7665iYteRtk5P1xd3c3qlevbnTv3t1Ys2ZNgW2v3pCjsPK817BWrVoFjv3ZZ58ZdevWNVxdXY0yZcoYDRs2NKZOnWrTpk+fPgZg8zl/5plnChzvX//6l+Ht7W24u7sbbdq0MebNm1fgezlvs6oPPvig0PsiInKvsxjGbVwgQ0RERP623n33XT766COOHTtW3KGI2C2LxUJsbOxNr7f4VzZ16lTeeecdDh06lG95Bd03uRU//vgjHTp0YP/+/fj4+BR3OCIiN8Xp2k1EREREbF28eJGJEyfyxBNPULJkSZYtW0Z0dDR9+/Yt7tBE5C/m7Nmz7Nq1iwkTJtCvX79rrp0qcr3Onz/P/v37effdd3nhhReU3BMRu6Y1+EREROSGWSwWli9fzsMPP0zNmjWZOHEiw4YN4/333y/u0ETkL6Zfv340bNiQsLAwm/XYRG7V+PHjqVWrFg4ODowfP764wxERuSWaoisiIiIiIiIiImLH9ASfiIiIiIiIiIiIHVOCT0RERERERERExI5pkw25I9LS0oo7BBEREZFr8vLyIjMzs7jDEBEREbkmX1/fQuv0BJ+IiIiIiIiIiIgdU4JPRERERERERETEjinBJyIiIiIiIiIiYseU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JgSfCIiIiIiIiIiInZMCT4RERERERERERE7pgSfiIiIiIiIiIiIHVOCT0RERERERERExI4pwSciIiIiIiIiImLHlOATERERERERERGxY0rwiYiIiIiIiIiI2DEl+EREREREREREROyYEnwiIiIiIiIiIiJ2TAk+ERERERERERERO6YEn4iIiIiIiIiIiB1Tgk9ERERERERERMSOKcEnIiIiIiIiIiJix5TgExERERERERERsWNK8ImIiIiIiIiIiNgxJfhERERERERERETsmBJ8IiIiIiIiIiIidkwJPhERERERERERETumBJ+IiIiIiIiIiIgdU4JPRERERERERETEjinBJyIiIiIiIiIiYseU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JgSfCIiIiIiIiIiInZMCT4RERERERERERE75lTcAdzLIiMjiY2NNY+XL1/O7t276dmz512PZeTIkURGRhIUFJSv/MSJE7i4uJCbm0vbtm2JiIi4beMmJSWxaNEihg4detv6FBERESlu1qPpsOBLjp87g7VkKXiqCw4VfIo7LBEREZGbogTfPejSpUs4Ojped/v+/fsTFBTE2bNnef3112nZsiVOTnppRURERApiPZqOMekdOJrOxbzC1BSsA95Vkk9ERETskrJAN+no0aNMmzaN06dP4+npSZ8+fShXrhz9+/fn448/5vz58/To0YMRI0ZQo0YN3nnnHfr06cPZs2eZM2cOOTk5uLi40KdPH3x9fVm+fDkbNmwgJyeH7Oxs3nrrLaZOncrBgwepVKkSOTk514wpKysLV1dXHBwuz7zetGkT8+fPJzc3l/vuu48+ffrg5ubGf//7X9avX09OTg7BwcG88sorWCwW0tPTmTFjBqdPn8bBwYEBAwaY/U6cOJEDBw4QGBjI66+/jsViuaP3V0REROSOWfAlHE23Lfv/T/TRa2DxxCQiIiJyC5TgK0JOTg5RUVHm8dmzZ6lfvz4AM2fOpEWLFrRs2ZKlS5cya9YsBg8eTMWKFTl48CAZGRkEBgayfft2qlevzrFjx/Dx8eH8+fOMGjUKR0dHNm/ezLx58xg0aBAAO3bsYMKECXh4ePDDDz/g4uLChAkT2LdvH0OGDCk0zsmTJ+Ps7Mzhw4fp3r07Dg4OnD59mri4OIYPH46bmxvff/89P/zwA88++yyPP/44zz77LAAff/wx69evp379+kyePJkOHTrQsGFDcnJyMAyDY8eOsWfPHv79739TtmxZhg8fTkpKCqGhoTYxxMfHEx8fD8DYsWPx8vK6ra+FiIiIyO1y/NyZ/3ty7wpO585QTt9hRERExA4pwVcEFxcXoqOjzeO8NfgAdu7caSbmWrRowZdffglAWFgYycnJZGRk0KFDB3799Vdq1Khhrp13/vx5YmJiSE+//K/Gly5dMvuvU6cOHh4eAGzbto0nnngCAH9/f/z9/QuNM2+K7unTp/nXv/5FvXr12L9/PwcPHmT48OEA5ObmEhwcDMDWrVtZuHAh2dnZnD17lipVqlCzZk2OHz9Ow4YNzWvPU61aNcqXLw9AQEAAGRkZ+RJ8ERERNmv/ZWZmXscdFhEREbn7rCVLFVieW7KUvsOIiIjIPcvX17fQOiX4brPQ0FB++eUXTpw4QadOnVi4cCFJSUnUqFEDgG+++YaaNWsSFRVFRkYGo0aNMs91dXW9pbE9PT2pWrUqO3fuxMXFhdq1a/Pmm2/atMnJyWHmzJmMGTMGLy8v5s+fbz6tVxhnZ2fz/x0cHLBarbcUp4iIiEixeqoLpKbYTtOt4HO5XERERMQOORR3APYqODiYlStXApCQkGA+0Va9enV27NiBxWLBxcWFgIAA4uPjzfrz589Trlw54PITgYWpUaMGCQkJAOzfv599+/ZdM6bs7Gz27t2Lj48PwcHBpKSkmE8KZmdnk5aWxsWLlyekeHp6kpWVxZo1awBwd3enfPnyrF27FoCLFy+SnZ19o7dFRERE5J7nUMEHy4B3sTQKx7nWA1gahWPRBhsiIiJix/QE30166aWXmDZtGgsXLjQ32YDLT7uVL1+e6tWrA5en7CYmJuLn5wfAU089RUxMDIsXL6ZmzZqF9v/oo48ydepUBg0aREBAANWqVSu07eTJk3FxcSE3N5fw8HACAwMB6Nu3Lx999JGZ1OvcuTO+vr48/PDDDBw4EG9vb3PqMEC/fv349NNPmT9/Po6Ojvzzn/+8tZskIiIico9yqOADvQZSzstL03JFRETE7lmMouZmityktLS04g5BRERE5Jq8lOATERERO1HUGnyaoisiIiIiIiIiImLHlOATERERERERERGxY0rwiYiIiIiIiIiI2DEl+EREREREREREROyYEnwiIiIiIiIiIiJ2TAk+ERERERERERERO+ZU3AFI4Y4dO8bMmTM5ePAgVquV+++/nxdffJHExER2795Nz549zbYjR44kMjKSoKAg+vbti5ubGw4Ol/O3YWFh9OjRg5iYGLZt24a7uzsArq6uvP/++yxfvpxp06Yxfvx4/P39ARg4cCBDhgzB29ubpUuXsnjxYiwWC4Zh0LlzZxo0aHD3b4iIiIjIbXJp+xaY8xFHLpyHEu7Q/Q0cQ2sXd1giIiIiN0UJvnuUYRhMmDCBRx99lMGDB2O1Wpk+fTpffPEFVatWveb5I0aMwNPTM195ZGQkjRs3zlderlw54uLiGDBggE35sWPH+O677xg3bhzu7u5kZWVx+vTpm78wERERkWJ2afsWmPQOWC9dLjh/Fia9w6UB7yrJJyIiInZJU3TvUVu3bsXFxYVWrVoB4ODgQLdu3fj999/Jysq67eM9+OCDHDx4kLS0NJvyU6dO4ebmhpubGwBubm54e3vf9vFFRERE7po5H/1fci+P9dLlchERERE7pCf47lEHDhzI96Seu7s7FSpU4NKlS4Wc9X9GjRplTtENDw+nXbt2AMTGxvLtt98CUKVKFfr37w+AxWKhffv2xMXF0a9fP7OfgIAAypQpQ9++falduzYNGzakfv36+caLj48nPj4egLFjx+Ll5XUTVy0iIiJy5x25cL7gigvn9R1GRERE7JISfPcwi8WSr8wwDM6fL/hL6ZXtb3SKLkCzZs2Ii4sjIyPDLHNwcGDYsGHs3r2bLVu2MHfuXFJTU+nUqZPNuREREURERJjHmZmZRV+ciIiISHEp4X55Wm4B5foOIyIiIvcqX1/fQus0RfceVblyZVJTU23Kzp8/z6lTp6hatSrnzp2zqTt79iylSpW6pTEdHR158skn+f77723KLRYL1apV4+mnn+bNN99kzZo1tzSOiIiISLHq/gY4ONqWOTheLhcRERGxQ0rw3aNq165NdnY2v/32GwBWq5XPP/+cxx9/nGrVqpGSksLJkycB2L17NxcvXqR8+fK3PG7Lli3ZsmWLuZHG8ePHbRKNe/fupUKFCrc8joiIiEhxcQytDQPehfLe4O5x+b/aYENERETsmKbo3qMsFguDBg1i5syZfPvtt5w+fZomTZrwzDPPANC9e3fGjBmD1WrFzc2NN954w1xzD2zX4PP39zfX1btyDT6AMWPG2Izr5OREmzZtmDNnDgCXLl0iNjaWEydO4OzsjKenJy+//PKdvHQRERGRO84xtDaM/QwvLy9NyxURERG7ZzEMwyjuIOTaUlJS+Oijjxg0aBCBgYHFHc41Xb0br4iIiMi9SAk+ERERsRdFrcGnBJ/cEUrwiYiIiD1Qgk9ERETshTbZEBERERERERER+YtSgk9ERERERERERMSOKcEnIiIiIiIiIiJix5TgExERERERERERsWN/+wRfZGTkXRtr5MiR7N69u9D6mJgYVq9efUfHys3N5csvv6R///4MHDiQt956iz///BOAMWPGcO7cOc6dO8fPP/98W+IQEREREREREZE7y6m4A5C765tvvuHEiRNMnDgRZ2dnTp48ybZt2wB46623AMjIyGDJkiU89thjxRmqiIiIyB1z6eX2ABy5osxxxsLiCUZERETkFinBV4C9e/cyY8YMsrOzue+++3jttdfw8PBg5MiRVKtWjaSkJM6fP0/v3r0JCwsjOzubmJgY0tLSqFSpEkePHqVnz54EBQUV2L/VamXatGmkpqYC0KpVK9q1a2fT5r///S/r168nJyeH4OBgXnnlFSwWS6Ex5OTkMHXqVA4ePEilSpXIycnJN252dja//vorU6ZMwdnZGYAyZcrQpEkTAPr27cuYMWOYN28e6enpREVFUadOHU6ePEnjxo1p0KABAJMnT6ZJkybUr1//tt1zERERkbslL7lXULmSfCIiImKP/vZTdAsyZcoUunTpwoQJE/Dz8+O///2vWWe1WhkzZgzdunUzy3/++Wc8PDyYMGECHTt2NBN3hdm7dy/Hjx9n4sSJTJw4kVatWuVr8/jjjzNmzBgmTpxITk4O69evLzKGJUuW4OLiwoQJE3jmmWcKjCE9PR0vLy/c3d2LjO+FF17Ax8eH6OhoIiMjefjhh1m2bBkA58+fJyUlhfvvv7/IPkRERERERERE5O7QE3xXOX/+POfOnaNGjRoAhIeHM2nSJLO+YcOGAAQGBpKRkQHA9u3beeKJJwDw8/PD39+/yDG8vb3JyMhg1qxZPPDAA9SpUydfm61bt7Jw4UKys7M5e/YsVapUMZ+YKyiGbdu2mTH4+/tfM4YbUaNGDWbOnMmpU6dYs2YNjRo1wtHR0aZNfHw88fHxAIwdOxYvL6/bNr6IiIjI7XSkiDp9hxERERF7pATfDcqb2urg4IDVar2pPjw8PIiOjmbjxo389NNPrFy5kj59+pj1OTk5zJw5kzFjxuDl5cX8+fNtptzebAw+Pj5kZmZy4cIFSpQocUMxN2/enBUrVrBy5Upee+21fPURERFERESYx5mZmTfUv4iIiMi9QN9hRERE5F7l6+tbaJ2m6F7F3d0dDw8PkpOTAfj9998JCwsr8pzQ0FBWrVoFwMGDB9m/f3+R7U+fPo3VaqVx48Z07tyZPXv22NRfvHgRAE9PT7KyslizZs01465RowYJCQkA7N+/n3379uVr4+rqSuvWrZk9eza5ubkAnDhxgt9//92mXYkSJbhw4YJNWcuWLfnxxx8BqFKlyjXjERERERERERGRu+Nv/wRfTk4OvXv3No/btWtH3759zU02vL29bZ6uK8ijjz5KTEwMgwYNIiAgAD8/vyLXuTt+/DjTpk0zn7574YUXbOpLlizJww8/zMCBA/H29i50s46rY5g6daoZQ7Vq1Qps17lzZ77++msGDBiAi4sLrq6udOrUyaZNqVKlCAkJYeDAgdSrV4/IyEjKlClDpUqVzI02REREROyV44yFBW60oQ02RERExF5ZDMMwijsIe2e1WsnNzcXFxYX09HTee+89PvroI5yc/jr50+zsbAYNGsS4ceOuuUkHQFpa2l2ISkREROTWeHl5aVquiIiI2IWipuj+dTJQxSg7O5tRo0Zx6dIlDMOgV69ef6nk3ubNm5k2bRrt2rW7ruSeiIiIiIiIiIjcPXqCT+4IPcEnIiIi9kBP8ImIiIi90CYbIiIiIiIiIiIif1FK8ImIiIiIiIiIiNgxJfhERERERERERETsmBJ8IiIiIiIiIiIidkwJvmI0Z84cFi9ebB6PHj2aTz75xDz+/PPP+eGHH266/6SkJMaOHVto/fHjx5k4cWKBdSNHjmT37t03PbaIiIjIvezSqDe59HJ7jjzdhEsvt+fSqDeLOyQRERGRm6YEXzEKCQkhJSUFAKvVyunTpzlw4IBZn5KSQkhIyB0bv1y5cgwcOPCO9S8iIiJyL7o06k04mGpbeDBVST4RERGxW07FHcDfWUhICHPnzgXg4MGDVKlShZMnT3L27FlcXV05dOgQ586dY/DgwVy6dImgoCBefvllnJ2d2bJlC7GxsfnKN27cyJw5cyhVqhRVq1Y1x9q2bRuzZ88GwGKxMGrUKM6cOcO4ceOYOHEiOTk5TJ06lYMHD1KpUiVycnLMczdt2sT8+fPJzc3lvvvuo0+fPri5ud3dmyUiIiJyu1yd3LtWuYiIiMg9Tgm+YlSuXDkcHR3JzMwkJSWF4OBgjh8/zo4dO3B3d6dixYpMnz6d4cOH4+vry5QpU1iyZAmPPPIIU6dOLbB8+vTpvPPOO/j4+DBp0iRzrIULF9KzZ09CQ0PJysrC2dnZJpYlS5bg4uLChAkT2LdvH0OGDAHg9OnTxMXFMXz4cNzc3Pj+++/54YcfePbZZ23Oj4+PJz4+HoCxY8fi5eV1h++eiIiIyM05UkSdvsOIiIiIPVKCr5jlTdNNSUmhXbt2Ngm+cuXK4eLigq+vLwDh4eH8/PPP1KxZE29v70LLK1asCECLFi3MpFtoaCiff/45zZo1o1GjRpQvX94mjm3btvHEE08A4O/vj7+/PwA7d+7k4MGDDB8+HIDc3FyCg4PzXUdERAQRERHmcWZm5u28TSIiIiJ3hb7DiIiIyL0qLw9UECX4illwcDApKSkcOHAAPz8/vLy8+OGHHyhRogRVq1Zly5Ytt2WcDh068MADD7Bhwwbefvtthg8fnu8pvoIYhkHt2rV58803b0scIiIiIsWucmDB03ErB979WERERERuA22yUcxCQ0PZsGEDHh4eODg44OHhwblz59ixYwetWrUiIyOD9PR0AH7//Xdq1KiBr6/vdZUnJCSY46Snp+Pn50eHDh0IDAzk0KFDNnHUqFHDbL9//3727dsH/F8CMq/P7Oxs0tLS7uxNEREREbmDHEd8mD+ZVznwcrmIiIiIHdITfMXMz8+PM2fO0KxZM5uyrKwsypcvT58+ffj3v/9tbqbxyCOP4OzsXGj5q6++ytixYylVqhShoaHmrrw//vgjSUlJODg4UKlSJe6//35OnDhhjvnoo48ydepUBg0aREBAANWqVQPA09OTvn378tFHH3Hx4kUAOnfuXORjoSIiIiL3urxknpeXl6blioiIiN2zGIZhFHcQ8tejp/xERETEHijBJyIiIvaiqIetNEVXRERERERERETEjinBJyIiIiIiIiIiYseU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JgSfHZo7dq1dOrUiUOHDhXZLi4u7qb6HzNmDOfOnbupc0VERERERERE5O6yGIZhFHcQcmP+/e9/c/LkSWrVqkWnTp0KbRcZGUlsbOx192sYBoZh4OBw63nftLS0W+5DRERE5E659HL7fGWOMxYWQyQiIiIi18fX17fQOqe7GIfcBllZWaSkpDBixAjGjx9Pp06dOHHiBB9++CHnz5/HarXSq1cvNmzYQE5ODlFRUVSpUoX+/fvzww8/sGzZMgBat25N27ZtycjIYMyYMdSsWZMdO3YQFRXFyJEjGTNmDJ6enowfP55jx45x8eJFnnjiCSIiIor5DoiIiIjcmoKSe3nlSvKJiIiIPVKCz86sXbuWevXq4evri4eHB6mpqSQlJVG3bl2eeeYZrFYr2dnZhIWF8dNPPxEdHQ1Aamoqy5YtY/To0QAMGzaMGjVqULJkSdLS0njttdfo1atXvvH69OmDh4cHOTk5vPXWWzRq1IhSpUrd1WsWEREREREREZHCKcFnZxITE2nbti0ATZo0ITExkQcffJBp06aRm5tLw4YNCQgIyHfe9u3badiwIW5ubgA0bNiQ5ORk6tevj5eXF8HBwQWO9+OPP7Ju3ToAMjMzOXz4cIEJvvj4eOLj4wEYO3YsXl5et+NyRURERG67I0XU6TuMiIiI2CMl+OzImTNn2Lp1KwcOHMBisWC1WgHo2rUro0aNYsOGDXz88ce0b9+e8PBwm3OLWmoxL+l3taSkJLZs2cL777+Pq6srI0eO5OLFiwW2jYiIsJm+m5mZeaOXJyIiIlLs9B1GRERE7lVFrcGnXXTtyOrVqwkPD2fq1KnExMQwbdo0vL29SU5OpnTp0kRERNC6dWv27NkDgJOTE7m5uQCEhYWxbt06srOzycrKYt26dYSFhRU53vnz5ylZsiSurq4cOnSInTt33vFrFBERERERERGRG6Mn+OxIYmIiHTp0sClr1KgRMTExuLm54ejoiJubG/369QPg4YcfJioqiqpVq9K/f39atmzJsGHDgMubbFStWpWMjIxCx6tXrx6//PILgwYNwtfXl+rVq9+xaxMRERG5WxxnLNQuuiIiIvKXYjGKmrspcpPS0tKKOwQRERGRa/Ly8tK0XBEREbELmqIrIiIiIiIiIiLyF6UEn4iIiIiIiIiIiB1Tgk9ERERERERERMSOKcEnIiIiIiIiIiJix5TgExERERERERERsWNK8ImIiIiIiIiIiNgxp+IO4F723HPP4efnB4CDgwM9evQgJCSEjIwMBgwYgK+vL7m5uQQFBdG7d2+cnJxISkpi/PjxeHt7m/1ERkZSp04dm/4AmjZtSrNmzRg3bpzNuBkZGTzyyCMcO3aMsLAwHn30UQB27tzJ9OnTGTduHI6Ojmb7kSNHcuLECVxcXHBzc+O1114zY/viiy9Yv349FouFypUr07NnT8qXL2/GFRsbS0ZGBv369eOll16iTZs2AMycOZOgoCB27dpFSkoKubm5ZGRkmFsyd+zYkcaNG9+Buy4iIiJy511a8xt8PoUjuRfByRle7Idjo/DiDktERETkpijBVwQXFxeio6MB2LhxI/PmzWPUqFEA+Pj4EB0djdVq5b333mPVqlU0b94cgLCwMIYOHVpkf1e6smz//v2MGTOGtm3bYrFY+Ne//kXjxo3x8PBg1qxZ9OrVyya5l6d///4EBQURHx9PbGwsQ4YMYd68eVy4cIGPPvoIBwcHli1bxoQJE/jggw+wWCw255cuXZoff/yRRx55BCen/3tb9OrVC7icdBw3blyB8YuIiIjYk0trfoPPJv5fQU42fDaRS6Akn4iIiNglTdG9ThcuXKBkyZL5yh0cHKhWrRrHjx+/5TFycnKYPHkyPXv2pGzZspQpU4Ynn3ySL774gl9++QU/Pz9CQ0OL7CMsLIz09HSys7NZvnw53bp1w8Hh8svcqlUrnJ2d2bp1a77zPD09qV27NsuXL7/l6xARERG5p30+5cbKRURERO5xeoKvCDk5OURFRXHx4kVOnDjBiBEjCmyza9cuunfvbpYlJycTFRVlHg8cOBAfHx+zvzxPP/00TZo0MY+/+OILQkJCqF+/vln2yCOP8Ntvv5GUlMTYsWOvGfP69evx8/MjPT0dLy8v3N3dbeoDAwM5cOAAtWvXznduhw4d+OCDD2jduvU1x7lafHw88fHxAIwdOxYvL68b7kNERETkbjiSe7HgityL+g4jIiIidkkJviJcOaV2x44dTJkyhYkTL0/nSE9PJyoqivT0dBo1aoS/v7953o1O0QX4888/2bJlS74knoODAxEREaSmplKqVKlCY508eTIuLi5UqFCBHj16cPbs2XzTcPMUVu7t7U21atVISEgodJzCREREEBERYR5nZmbecB8iIiIid4WT8+VpuQWU6zuMiIiI3Kvy9kUoiKboXqfg4GDOnDnD6dOngf9bg2/y5Mns3LmTP/7446b7Pn36NJ9++in9+/fH1dU1X72Dg0OhSbk8/fv3Jzo6msGDB+Pl5YWPjw9Hjx7lwoULNu327NlD5cqVC+3n6aefZsGCBRiGcXMXIyIiInKve7HfjZWLiIiI3OOU4LtOhw4dwmq15nuKrmzZsnTp0oXvvvvupvueOnUqbdq0oWrVqrcapsnNzY3w8HDmzp2L1WoF4LfffiM7O5tatWoVel6lSpWoVKkS69evv22xiIiIiNxLHBuFQ6+B4OIKDg6X/9troDbYEBEREbulKbpFuHrNvL59+5obVlypQYMG/Oc//yE5ORnIvwZfx44dady4cb7+6tWrR4MGDdiwYQPHjh1jxYoVZl2dOnWIjIy8pfhfeOEFYmNjeeONN7BYLPj6+jJo0KBrPg34zDPPMGTIkFsaW0RERORe5tgoHBqF4+XlpWm5IiIiYvcshuZiyh2QlpZW3CGIiIiIXJMSfCIiImIvtAafiIiIiIiIiIjIX5QSfCIiIiIiIiIiInZMCT4RERERERERERE7pgSfiIiIiIiIiIiIHVOCT0RERERERERExI45FXcAd1unTp1o164dL774IgALFy4kKyuLTp06MX/+fH799Vc8PT3N9iNHjmTUqFH06dOHgIAALl26RPfu3Xn55Zdp0aIFAEOGDOHVV18lMDDQPC8pKYlFixYxdOhQsywmJoYHH3yQ1NRUrFYrXbt2BeDo0aOMGjWKcePGER0dzYkTJ3B2diY3N5fatWvTuXNnSpYsCcBzzz2Hn5+f2WfTpk3p0KGDzTXGxMSwbds23N3dcXBwoGfPngQHBwMwe/ZsVq9ezbRp03BwuJzfXb58ObGxsZQrV46LFy8SERFBu3btAJg/fz5ubm60b9+enJwcxo0bR2hoKP/4xz9uy+shIiIiIiIiIiK35m+X4HN2dmbNmjV06NDBJpGXp23btrRv396mLDg4mJSUFAICAti3bx++vr7s2LGDFi1akJWVRUZGBgEBAdcdw7PPPsvgwYNp2bIllStXZvbs2Tz33HNmEq9///4EBQWRm5vLvHnzGD9+PKNGjQLAxcWF6Ojoa44RGRlJ48aN2bRpE59++ikTJkzAarWydu1avLy8SE5OpmbNmmb7Jk2a0LNnT86cOcObb75J48aN8fLyMutzc3OZOHEigYGBSu6JiIiI3bv08uXve0euKHOcsbB4ghERERG5RX+7KboODg5ERESwePHi6z4nNDSUlJQUAFJSUnjkkUfYu3cvALt27aJq1arm03DXw8XFhRdffJGZM2fy559/kpWVRfPmzfO1c3JyomvXrmRmZprj3aiwsDDS09OBy08V+vn58cgjj5CYmFhg+1KlSuHj48PJkyfNMqvVyocffkjFihXp0qXLTcUhIiIicq/IS+5db7mIiIjIve5v9wQfwGOPPUZUVBRPPfVUvrrFixezYsUKADw8PBgxYgTBwcF8/fXXwOUE3z/+8Q8SExO5cOECO3bsICQkpMBxkpOTiYqKMo8zMzN58MEHAXjggQdYunQpU6ZM4b333is0VgcHB/z9/UlLSyMgIICcnBybPp9++mmaNGlS6Pnr1683p/QmJibStGlT6tevz1dffUVubi5OTrZvgczMTHJycmymAS9YsIDatWvTvXv3QscREREREREREZHi8bdM8Lm7u9OiRQt+/PFHXFxcbOoKmqLr7e1Nbm4uJ0+eJC0tDV9fX4KCgti5cycpKSm0adOmwHHCwsLyrcF3pccff5yLFy/i6+t73bFf7xTd2NhYvv32Wzw9Penduze5ubn8+eefdOvWjRIlSlC9enU2b97MAw88AMDKlStJSkoiLS2NV1991ea+hIaGsnPnTvPaCxIfH098fDwAY8eOtZneKyIiInIvOVJEnb7DiIiIiD36Wyb44HIib8iQIbRs2fK62gcHB7N69WrKli2LxWKhevXqpKSksGvXLqpXr35TMVgsFiwWS5FtrFYr+/fvp1KlSjfUd94afHn++OMPzp8/z6BBgwDIzs7GxcXFTPDlrcG3Y8cOxowZw/3330+ZMmWAy4nK8PBwxowZw6hRoyhXrly+8SIiIoiIiDCPMzMzbyheERERkXuBvsOIiIjIvaqoB8T+dmvw5fHw8OChhx5i6dKl19U+JCSExYsXm8m84OBgfv/9d8qUKWNujnG75W2yUb58efz9/W+pr4SEBF599VViYmKIiYlhypQpbN68mezsbJt2wcHB5tONV2rcuDFPPvkkH3zwAefOnbulWERERERERERE5Pb52z7BB9CuXTt++uknm7Ir1+ADiIqKwtvbm5CQEObOnUtwcDAAZcuWxWq1Frr+3q2YPHkyzs7OXLx4kdq1azN48GCz7uo1+OrVq3fNjS+ys7PZtGkTr7zyilnm5uZGaGgo69evz9f+qaeeYsiQITz99NM25Y8++ignT55k/PjxvP322/mmN4uIiIjYA8cZCwvcUEO76IqIiIi9shiGYRR3EPLXk5aWVtwhiIiIiFyTl5eXpuWKiIiIXdAUXRERERERERERkb8oJfhERERERERERETsmBJ8IiIiIiIiIiIidkwJPhERERERERERETumBJ+IiIiIiIiIiIgdU4JPRERERERERETEjjkVdwD26LnnnsPPz888joqK4ujRoyxatIihQ4fatD1w4ACzZs3i+PHjGIZBixYt6NixIxaLheXLlxMbG0u5cuW4ePEiERERtGvXzjx3z549DBkyhGHDhlGvXj2zPDIyktjY2ELju7Lf3Nxc2rZtS0REBABr165lwoQJTJo0iUqVKgGQkZHBgAED8PX1JTc3l6CgIHr37o2TkxNJSUk21/X111+ze/duBg8ejLOz8y3fSxEREZHicOmVp8G4xJG8Aosjjp9+V5whiYiIiNw0JfhugouLC9HR0TZlR48ezdcuJyeH8ePH06tXL+rWrUt2djYTJ07k559/5vHHHwegSZMm9OzZkzNnzvDmm2/SuHFjvLy8AEhMTCQ0NJTExESbBN/1yOv31KlT/POf/6R+/fqUKVOGhIQEs89OnTqZ7X18fIiOjsZqtfLee++xatUqmjdvbtNnXFwcKSkpvPXWW0ruiYiIiN3KS+7ZMC5x6ZWnleQTERERu6QpundQQkICISEh1K1bFwBXV1d69OjBggUL8rUtVaoUPj4+nDx5EgDDMFi9ejV9+vRh8+bN5OTk3FQMpUuXxsfHh8zMTLKyskhJSaF3796sXLmywPYODg5Uq1aN48eP25QvWrSIP//8kyFDhuDi4nJTsYiIiIjcE65O7l2rXEREROQepyf4bkJOTg5RUVEAeHt7m/9/tQMHDhAYGGhT5uPjQ1ZWFufPn7cpz8zMJCcnx5z6m5KSgre3Nz4+PtSoUYM///yTRo0a3XCsR44c4ciRI/j4+LB27Vrq1auHr68vHh4epKam5osvJyeHXbt20b17d7MsJSWFtLQ0xo4di5ubW4HjxMfHEx8fD8DYsWPNpxBFRERE7jVHiqjTdxgRERGxR0rw3YSCpugWxDCMQussFgsAK1euJCkpibS0NF599VXz6biEhASaNGkCQNOmTfn9999vKMG3cuVKtm/fjrOzM6+88goeHh4kJibStm1b4PIU3sTERDPBl56eTlRUFOnp6TRq1Ah/f3+zLx8fH86ePcvmzZtp3LhxgeNFRESY6/zB5YSliIiIiL3RdxgRERG5V/n6+hZapwTfHVSlShWSk5Ntyo4cOYKbmxslSpQA/m+tvB07djBmzBjuv/9+PD09WbNmDevXr+e7777DMAzOnDnDhQsXzPOuJa/fPGfOnGHr1q0cOHAAi8WC1WoFoGvXrsD/rcF34sQJRo4cyR9//EH9+vWBy9N8X3/9dd577z08PDyoVavWLd8bERERkWJjcSx4Oq7F8e7HIiIiInIbaA2+O6h58+Zs376dzZs3A5env86ePZv27dvnaxscHEyLFi348ccf2bx5MwEBAUybNo2YmBimTp1Ko0aNWLdu3U3Hsnr1asLDw5k6dSoxMTFMmzYNb29vtm/fbtOubNmydOnShe++s11g2tfXl4EDB/Lxxx+zd+/em45DREREpLg5fvpd/mSedtEVERERO6Yn+G6jLVu20Lt3b/P4n//8J4MHD2bWrFnMnDkTq9VKixYtzB10r/bUU08xZMgQ0tLSaNCggU1d48aNWbJkCS1atCAnJ8dmnHbt2tGuXbsiY0tMTKRDhw42ZY0aNSIhIYGnnnrKprxBgwb85z//yff0YbVq1ejTpw/jxo1jxIgR+Pj4FDmmiIiIyL0qL5nn5eWlabkiIiJi9yxGUQvFidyktLS04g5BRERE5JqU4BMRERF7UdQafJqiKyIiIiIiIiIiYseU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JgSfCIiIiIiIiIiInZMCT4RERERERERERE75lTcAchla9euZcKECUyaNIlKlSqRkZHBgAED8PX1JTc3l6CgIHr37k1cXBy5ubm88MIL5rl79+7lo48+YtKkSfTt2xc3NzccHC7nbsPCwujRowcxMTFs27YNd3d3AF588UVq164NwMiRI8nKymLs2LEA7N69m9jYWEaOHElSUhLjx4/H29vbHC8yMpI6dercrVsjIiIicttderk9AEeuKHOcsbB4ghERERG5RUrw3SMSEhIIDQ0lMTGRTp06AeDj40N0dDRWq5X33nuPVatW0axZMz744AObBF9iYiJNmzY1j0eMGIGnp2e+MSIjI2ncuDFbt27l008/ZfLkyWbdqVOn+PPPP7n//vvznRcWFsbQoUNv5+WKiIiIFJu85F5B5UryiYiIiD3SFN17QFZWFikpKfTu3ZuVK1fmq3dwcKBatWocP34cX19fSpYsyc6dO836VatW2ST4riU4OJjjx4/blLVv3564uLibvwgRERERERERESkWeoLvHrB27Vrq1auHr68vHh4epKam4uHhYdbn5OSwa9cuunfvDkDTpk1JTEykevXq7Nixg1KlSlGxYkWz/ahRo8wpuuHh4bRr185mvI0bN9KgQQObsuDgYNauXcvWrVspUaKETV1ycjJRUVHm8cCBA/Hx8bFpEx8fT3x8PABjx47Fy8vrJu+GiIiIyJ11pIg6fYcRERERe6QE3z0gMTGRtm3bAtCkSRMSExN57LHHSE9PJyoqivT0dBo1aoS/v7/ZZvjw4bz44ousXLky39N7hU3RjY2N5YsvvuDUqVOMHj06X33Hjh2Ji4ujS5cuNuXXM0U3IiKCiIgI8zgzM/P6Ll5ERETkHqLvMCIiInKv8vX1LbROU3SL2ZkzZ9i6dSuffPIJffv2ZdGiReY03bw1+CZPnszOnTv5448/gMv/slyhQgW2bdvGmjVreOihh65rrMjISCZPnkznzp2JiYnJV1+rVi0uXrxoM/1XRERERERERETubUrwFbPVq1cTHh7O1KlTiYmJYdq0aXh7e3Ps2DGzTdmyZenSpQvfffedWda0aVPmzp3LfffdR/ny5a97PAcHB5544gkMw2Djxo356p9++mkWLFhwS9ckIiIici8rbCMNbbAhIiIi9kpTdItZYmIiHTp0sClr1KiRTTIPoEGDBvznP/8hOTmZsLAwHnroIebMmcNLL72Ur88r1+Dz9/enX79+NvUWi4VnnnmGhQsXUq9ePZu6Bx54IN/03qvX4OvYsSONGze+0UsVERERuWfkJfO8vLw0LVdERETsnsUwDKO4g5C/nrS0tOIOQUREROSalOATERERe6E1+ERERERERERERP6ilOATERERERERERGxY0rwiYiIiIiIiIiI2DEl+EREREREREREROyYEnwiIiIiIiIiIiJ2zKm4A/irOnnyJHPnzmXnzp2ULFkSJycnnnrqKRo2bEhSUhKLFi1i6NChNueMHDmSEydO4OLiAoCPjw8DBw5k/vz5LFy4kJiYGEqXLg1AZGQksbGx+cY9f/48s2bNIiUlBYCQkBB69OiBu7u72Wb27NmsXr2aadOm4eBwOce7fPlydu/eTc+ePbFarUydOhUHBwdee+01li1bxuLFi7FYLBiGQefOnWnQoMEduW8iIiIid8Oll9sDcOSKMscZC4snGBEREZFbpATfHWAYBtHR0YSHh/PGG28AcPToUf74449rntu/f3+CgoLylZcqVYpFixbRtWvXIs+fNm0aVapUoV+/fgDMnz+fTz75hH/+858AWK1W1q5di5eXF8nJydSsWTNf7DNmzODSpUv06dOH48eP89133zFu3Djc3d3Jysri9OnT13UfRERERO5Fecm9gsqV5BMRERF7pCm6d8DWrVtxcnLi0UcfNcsqVKhAmzZtbrrPVq1asWrVKs6ePVtom/T0dFJTU3n22WfNsmeffZbdu3eTnp4OQFJSEn5+fjzyyCMkJibm62P27NmcOXOGfv364eDgwKlTp3Bzc8PNzQ0ANzc3vL29b/o6RERERERERETk9tITfHfAgQMHqFq16k2dO3nyZHOKbp06dYiMjAQuJ9ZatWrFjz/+SKdOnQo89+DBgwQEBJjTbgEcHBwICAjg4MGD+Pj4kJiYSNOmTalfvz5fffUVubm5ODldfhskJCRQuXJlRowYgaOjIwABAQGUKVOGvn37Urt2bRo2bEj9+vXzjR0fH098fDwAY8eOxcvL66auX0REROROO1JEnb7DiIiIiD1Sgu8u+Oyzz0hJScHJyYkxY8YU2bawKboAbdq0YfDgwbRr167AesMwsFgsBZYD5Obm8ueff9KtWzdKlChB9erV2bx5Mw888AAAgYGBHDp0iF27dhEaGgpcThAOGzaM3bt3s2XLFubOnUtqamq+JGNERAQRERHmcWZmZpHXKSIiInIv0ncYERERuVf5+voWWqcE3x1QpUoV1qxZYx736tWL06dP89Zbb91SvyVLlqRp06YsWbKk0HH37NmD1Wo1n+KzWq3s27ePypUrs3HjRs6fP8+gQYMAyM7OxsXFxUzw+fr60qlTJyZNmsTbb79NlSpVALBYLFSrVo1q1apRp04dpk6dWuhThCIiIiIiIiIicndpDb47oFatWly8eNEmEZeTk3Nb+m7Xrh2//PILVqs1X52Pjw9Vq1YlLi7OLIuLi6Nq1ar4+PiQkJDAq6++SkxMDDExMUyZMoXNmzeTnZ1ttg8JCeHll19m7NixZGZmcvz4cVJTU836vXv3UqFChdtyLSIiIiLFobCNNLTBhoiIiNgrPcF3B1gsFqKiopg7dy4LFizA09MTNzc3unTpYrbZsmULvXv3No/zdrm9cg0+T09Phg8fbtO3p6cnDRs2ZPHixQWO3bt3b2bNmsXrr78OQPXq1XnttdfIzs5m06ZNvPLKK2ZbNzc3QkNDWb9+vU0fDz74IKdPn2b06NEMGzaM2NhYTpw4gbOzM56enrz88su3cHdEREREil9eMs/Ly0vTckVERMTuWYy8BdpEbqO0tLTiDkFERETkmpTgExEREXtR1Bp8mqIrIiIiIiIiIiJix5TgExERERERERERsWNK8ImIiIiIiIiIiNgxJfhERERERERERETsmBJ8IiIiIiIiIiIidkwJPhERERERERERETvmVNwB3C4nT55kzpw57N69GycnJ7y9venWrZu5hfAPP/zAV199xYwZM3B3dwcgKSmJUaNG0bt3b1q3bg3Anj17GDJkCF27dqV9+/bExMSwbds23N3duXjxIk2bNuUf//gHACNHjuTEiRO4uLjg5OTEq6++SkBAAAB9+/ZlzJgxeHp6ArB27VomTJjApEmTqFSpUoHXEBkZSWxsrHm8fPlydu/eTc+ePZk/fz6//vqr2V/e+Hv37mXRokUMHToUgI0bN/LNN99w4cIFnJ2d8fX1JTIyEi8vL2JiYnjwwQdp3LixzZijR4/m448/BiAzMxN3d3fc3d3x9PTk7bffZs6cOSQlJQHg4uLCgAED8Pb2vrUXTERERKQYXXq5PQBHrihznLGweIIRERERuUV/iQSfYRhER0cTHh7Om2++CcDevXs5deqUmeBLTEwkKCiItWvX0rJlS/NcPz8/Vq5caSb4EhMT8ff3t+k/MjKSxo0bk5OTwz//+U/Cw8PNBFf//v0JCgpi2bJlxMbGMnz48AJjTEhIIDQ0lMTERDp16nRT19m2bVvat29faP3+/fuZNWsWgwcPpnLlygD88ccfZGRk4OXlVeh5fn5+REdHA+RLAiYkJHDixAmio6NxcHDg2LFjuLq63lT8IiIiIveCvOReQeVK8omIiIg9+ktM0U1KSsLJyYlHH33ULAsICCAsLAyA9PR0srKy6Ny5M4mJiTbnenl5cfHiRU6ePIlhGGzatIn777+/wHEuXrwIUGCCKzg4mOPHjxd4XlZWFikpKfTu3ZuVK1fe1DVejwULFvD000+byT2A+vXrU6NGjZvu8+TJk5QtWxYHh8tvlfLly+Ph4XHLsYqIiIiIiIiIyO3xl3iCb//+/VStWrXQ+sTERJo2bUpoaChpaWmcOnWK0qVLm/WNGjVi9erVBAQEULVqVZycbG9LbGws3377Lenp6bRp08bm3DwbN26kQYMGBY6/du1a6tWrh6+vLx4eHqSmphIYGJivXU5ODlFRUebx2bNnqV+/vnm8ePFiVqxYAYCHhwcjRoywOf/gwYM8+eSThd6HK6/lej300EO88847JCcnU7t2bZo3b17gvY6Pjyc+Ph6AsWPHFvnEoIiIiEhxOlJEnb7DiIiIiD36SyT4rmXlypUMGjQIBwcHGjZsyKpVq3j88cfN+iZNmjBp0iQOHTpE06ZNSUlJsTk/b4puVlYW7777LikpKYSEhAAwefJksrOzsVqtjBs3rsDxExMTadu2rTlWYmJigQk+FxcXc6os/N8afHmuNUX3SmfOnOHdd98lJyeHhx9+2Dwv71quvLailC9fng8//JCtW7eydetW3n33Xf75z39Su3Ztm3YRERFERESYx5mZmdcVp4iIiMi9RN9hRERE5F6VtwxdQf4SCb4qVaqwZs2aAuv27dvH4cOHef/99wHIzc3F29vbJsFXpkwZnJyc2Lx5My+99FK+BF8eNzc3atSowfbt280EX//+/fH392fevHnMnDmTQYMG2Zxz5swZtm7dyoEDB7BYLFitVgC6du2KxWK55Wu/UuXKldmzZw8BAQGUKlWK6OhoFi5cSFZW1i316+zszP3338/9999P6dKlWbduXb4En4iIiIiIiIiIFI+/xBp8tWrV4uLFi+YUUYBdu3axbds2EhMT+cc//kFMTAwxMTFMnz6d48ePc/ToUZs+OnXqRJcuXcy15gpy6dIldu3axX333WdT7uTkROfOndm5cycHDx60qVu9ejXh4eFMnTqVmJgYpk2bhre3N9u3b78NV27rqaeeIi4uziaGnJycW+ozNTXVXFvQarWyf/9+TV0RERERu1bYRhraYENERETs1V/iCT6LxcKgQYOYM2cOCxYswNnZmQoVKtC9e3cSExMZNmyYTfuGDRuSmJhI9erVzbK8J/IKkrduXW5uLrVr16ZRo0b52ri4uNCuXTsWLVrEa6+9ZpYnJibSoUMHm7aNGjUiISHB3ATkel25Bh9gs14fXN4N96WXXiImJoYLFy5QqlQpypcvf9O79gKcPn2a6dOnk5ubC0BQUJDN048iIiIi9igvmefl5aVpuSIiImL3LIZhGMUdhPz1pKWlFXcIIiIiItekBJ+IiIjYi6LW4PtLTNEVERERERERERH5u1KCT0RERERERERExI4pwSciIiIiIiIiImLHlOATERERERERERGxY0rwiYiIiIiIiIiI2DGn4g7AHs2ZM4cKFSrQtm1bAEaPHk358uXp3bs3AJ9//jnlypVj2bJlTJw40Txv/vz5uLm50b59e2JiYnjwwQdZsWIFGRkZZGVlcfr0aby9vQHo1asXX331FSdOnMDFxQUAHx8fBg4cSFpaGp9++innzp0jNzeX0NBQGjVqxJdffglAeno65cqVw8XFBX9/f/r168f27duZO3cuFy5cAKBdu3ZERESYcS1cuJCYmBhKly4NQGRkJLGxsQA899xz+Pn5mdfRtGlTOnTocKdur4iIiMgdd+nl9gAcuaLMccbC4glGRERE5BYpwXcTQkJCWLVqFW3btsVqtXL69GnOnz9v1qekpNC9e3eWLVt2zb6ioqIASEpKYtGiRQwdOtSmvn///gQFBdmUzZ49m7Zt29KgQQMA9u/fj5+fH/Xq1QNg5MiRREZGmuedPHmSjz76iKioKAIDAzl9+jSjR4+mXLlyPPDAAwCUKlWKRYsW0bVr13wxuri4EB0dfZ13R0REROTelpfcK6hcST4RERGxR5qiexNCQkLYsWMHAAcPHqRKlSqUKFGCs2fPcvHiRQ4dOkTJkiXv2PgnTpygfPny5vGVT9cV5KeffqJly5YEBgYC4OnpSdeuXfn+++/NNq1atWLVqlWcPXv2jsQsIiIiIiIiIiJ3hp7guwnlypXD0dGRzMxMUlJSCA4O5vjx4+zYsQN3d3f8/f1xcnIiPT3dfEIPLj9J9+STT97QWJMnTzan6NapU4fIyEjatm3LqFGjCAkJoU6dOrRq1arIhOLBgwcJDw+3KQsKCuLAgQPmsZubG61ateLHH3+kU6dONm1zcnJsruPpp5+mSZMmNm3i4+OJj48HYOzYsXh5ed3QdYqIiIjcLUeKqNN3GBEREbFHSvDdpJCQEFJSUkhJSaFdu3Y2Cb7g4GDg8pp5V05tnT9//g2PU9AU3VatWlG3bl02btzIH3/8QXx8PNHR0Tg7OxfYh2EYWCyWfOVXl7Vp04bBgwfTrl07m/LrmaIbERFhrukHkJmZWWR7ERERkXuRvsOIiIjIvcrX17fQOk3RvUnBwcGkpKRw4MAB/Pz8CA4OZseOHaSkpBASEnLHxy9XrhytW7dm8ODBODo62jyNd7UqVaqwe/dum7LU1FQqV65sU1ayZEmaNm3KkiVL7kjMIiIiIiIiIiJy+ynBd5NCQ0PZsGEDHh4eODg44OHhwblz59ixY4f5BN+dsnHjRnJzc4HL037PnDlDuXLlCm3/2GOPsXz5cvbu3QvAmTNn+PLLL2nfPv8C0+3ateOXX37BarXekdhFREREilthG2logw0RERGxV5qie5P8/Pw4c+YMzZo1synLysrC09OTrKys2zLOlWvweXp6Mnz4cDZt2sTs2bPN8q5du1KmTJlC+yhbtiyvv/4606dP58KFCxiGQdu2balfv36+tp6enjRs2JDFixebZVevwVevXj26dOlyW65PREREpDjkJfO8vLw0LVdERETsnsUwDKO4g5C/nrS0tOIOQUREROSalOATERERe6E1+ERERERERERERP6ilOATERERERERERGxY0rwiYiIiIiIiIiI2DEl+EREREREREREROyYEnwiIiIiIiIiIiJ2TAk+ERERERERERERO+ZU3AH8VT333HP4+fkB4ODgQI8ePQgJCSEjI4MBAwbYbG3crl07wsPD6du3L2PGjMHT09OsW758Obt376Znz542/fft2xc3NzccHC7naMPCwujRowcxMTFs27YNd3d3AF588UVq164NQG5uLl988QXr16/HYrFQuXJlevbsSfny5QGIi4sjISEBBwcHLBYLr7zyCtWrV2fkyJGcOHECFxcXAHx8fBg4cOAdunMiIiIid96ll9sDcOSKMscZC4snGBEREZFbpATfHeLi4kJ0dDQAGzduZN68eYwaNQq4nCDLq7sVI0aMsEkG5omMjKRx48Zs3bqVTz/9lMmTJwMwb948Lly4wEcffYSDgwPLli1jwoQJfPDBB+zcuZP169czbtw4nJ2dOX36NLm5uWaf/fv3Jygo6JZjFhERESluecm9gsqV5BMRERF7pCm6d8GFCxcoWbLkXR83ODiY48ePA5Cdnc3y5cvp1q2b+dRfq1atcHZ2ZuvWrZw4cYJSpUrh7OwMgKenJ+XKlbvrMYuIiIiIiIiIyI3RE3x3SE5ODlFRUVy8eJETJ04wYsQIsy49PZ2oqCjzuEePHoSFhd3wGKNGjTKTdeHh4bRr186mfuPGjTRo0MAc08vLy5y6mycwMJADBw7QunVr/vvf//LGG29Qu3ZtmjRpQo0aNcx2kydPNqfo1qlTh8jISJt+4uPjiY+PB2Ds2LF4eXnd8PWIiIiI3A1HiqjTdxgRERGxR0rw3SFXTtHdsWMHU6ZMYeLEicCdn6IbGxvLF198walTpxg9ejQAhmFgsVgK7MdiseDm5sa4ceNITk4mKSmJSZMm0aVLF1q2bAlce4puREQEERER5nFmZuYtXJmIiIhI8dB3GBEREblXXbmfw9U0RfcuCA4O5syZM5w+ffqujBcZGcnkyZPp3LkzMTExwOWk4tGjR7lw4YJN2z179lC5cmXg8mYgNWvWpFOnTvTs2ZPVq1fflXhFREREREREROTmKcF3Fxw6dAir1UqpUqXu2pgODg488cQTGIbBxo0bcXNzIzw8nLlz52K1WgH47bffyM7OplatWqSlpXH48GHz/L1791KhQoW7Fq+IiIjI3VLYRhraYENERETslabo3iF5a/Dl6du3r7le3tVr8LVq1YonnngCgKioKHMq7UMPPYS/vz/Lly9n3bp1Zvu8abdXrsHn7+9Pv379bGKwWCw888wzLFy4kHr16vHCCy8QGxvLG2+8gcViwdfXl0GDBmGxWMjKymLWrFmcO3cOR0dHfHx8eOWVV8y+rlyDz9PTk+HDh9+2eyUiIiJyt+Ul87y8vDQtV0REROyexTAMo7iDkL+etLS04g5BRERE5JqU4BMRERF7oTX4RERERERERERE/qKU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JgSfCIiIiIiIiIiInbMqbgD+Lt47rnn8PPzw2q1UqFCBV5//XVKliwJwIEDB5g1axbHjx/HMAxatGhBx44dsVgsnDx5kk8++YRjx46Rm5uLt7c3b731FhkZGQwYMMBmB5V27doRHh5O3759cXNzA8BqtdKoUSM6duyIs7Oz2Xb27NmsXr2aadOm4eBwOc+7fPlydu/eTc+ePW1iz+svr11YWBg9evS4o/dLRERE5E669HJ7AI5cUeY4Y2HxBCMiIiJyi5Tgu0tcXFyIjo4GYMqUKfz8888888wz5OTkMH78eHr16kXdunXJzs5m4sSJ/Pzzzzz++OPMnz+fOnXq8MQTTwCwb98+s08fHx+zz6uNGDECT09PsrKymD59OtOnT6dfv37A5aTf2rVr8fLyIjk5mZo1a14z/rz+REREROxdXnKvoHIl+URERMQeaYpuMQgODub48eMAJCQkEBISQt26dQFwdXWlR48eLFiwAIATJ05Qrlw581x/f/8bGsvNzY2XX36ZdevWcfbsWQCSkpLw8/PjkUceITEx8XZckoiIiIiIiIiIFBM9wXeXWa1Wtm7dSuvWrYHL03MDAwNt2vj4+JCVlcX58+d57LHH+PDDD/n555+pXbs2LVu2NBN+6enpREVFmef16NGDsLCwfGO6u7vj7e3N4cOHqV69OomJiTRt2pT69evz1VdfkZubi5NT0W+FUaNGmVN0w8PDadeunU19fHw88fHxAIwdOxYvL68bvDMiIiIid8eRIur0HUZERETskRJ8d0lOTg5RUVEcPXqUwMBA6tSpA4BhGIWeY7FYqFevHlOmTGHjxo38+eefDBkyhIkTJwJFT9EtTG5uLn/++SfdunWjRIkSVK9enc2bN/PAAw8Ued61puhGREQQERFhHmdmZt5QXCIiIiL3An2HERERkXvVlfswXE1TdO+SvDX4pk6dSm5uLj/99BMAVapUITU11abtkSNHcHNzo0SJEgB4eHjQrFkzXn/9dYKCgti2bdsNjX3hwgUyMjKoWLEiGzdu5Pz58wwaNIi+ffuyfft2EhISbs9FioiIiIiIiIjIXacE313m7u7OSy+9xKJFi8jNzaV58+Zs376dzZs3A5ef9Js9ezbt219e/Hnr1q1kZ2cDlxN1R44cuaGpI1lZWXz22Wc0aNAADw8PEhISePXVV4mJiSEmJoYpU6awefNmcwwRERGRv7rCNtLQBhsiIiJirzRFtxhUrVoVf39/Vq5cSYsWLRg8eDCzZs1i5syZWK1WWrRoweOPPw5AamoqM2fOxNHREcMwaN26NdWqVSMjIyPfGnytWrUyd9sdNWoUcHnNv4YNG9KxY0eys7PZtGkTr7zyinmOm5sboaGhrF+/HoDly5ezbt06s3706NFmf3lr8Pn7+5s78oqIiIjYo7xknpeXl6blioiIiN2zGEUtAidyk9LS0oo7BBEREZFrUoJPRERE7IXW4BMREREREREREfmLUoJPRERERERERETEjinBJyIiIiIiIiIiYseU4BMREREREREREbFjSvCJiIiIiIiIiIjYMSX4RERERERERERE7JhTcQfwVxUXF0dCQgIODg5YLBZeeeUVPvzwQ8aMGYOnpycASUlJLFq0iKFDh7J8+XKmTZvG+PHj8ff3B2DgwIEMGTIEb29v+vbtS9WqVRk0aBAAq1evZv369bRv354JEyYQHR2Ni4sLAGPGjKFFixbUrFmTTz75hGPHjpGbm4u3tzdvvfUWGRkZjBs3jokTJ5KUlMT48eO57777yM7OpkyZMrRv354HH3wQgPnz5/Prr7+aMQOMHDmSkiVL3s3bKSIiInJbXXq5PQBHrihznLGweIIRERERuUVK8N0BO3bsYP369YwbNw5nZ2dOnz5Nbm7uNc8rV64ccXFxDBgwoMD61NRUDhw4QJUqVcyyKlWq0LBhQ+Li4ujcuTNr167l0qVLNG3alE8//ZQ6derwxBNPALBv374C+w0LC2Po0KEA7N2710wW1q5dG4C2bdvSvn37G7oHIiIiIveqvOReQeVK8omIiIg90hTdO+DEiROUKlUKZ2dnADw9PSlXrtw1z3vwwQc5ePAgaWlpBdY/+eSTfPfdd/nKn332WVatWsXevXuZN28ePXv2NOO4cty8JwOLEhAQQMeOHfnpp5+u2VZERERERERERIqfnuC7A+rWrct///tf3njjDWrXrk2TJk2oUaPGNc+zWCy0b9+euLg4+vXrl6/+oYceYsmSJaSnp9uUu7q6EhkZyYgRI2jbti0VK1YE4LHHHuPDDz/k559/pnbt2rRs2fK6Eo2BgYEsWrTIPF68eDErVqwAwMPDgxEjRuQ7Jz4+nvj4eADGjh2Ll5fXNccRERERKQ5HiqjTdxgRERGxR0rw3QFubm6MGzeO5ORkkpKSmDRpEl26dLmuc5s1a0ZcXBwZGRn56hwcHMyn+O6//36buvr16+Pu7s5jjz1mltWrV48pU6awceNG/vzzT4YMGcLEiROvGYNhGDbH1zNFNyIigoiICPM4MzPzmuOIiIiI3Gv0HUZERETuVb6+voXWaYruHeLg4EDNmjXp1KkTPXv2ZPXq1ZQqVYpz586Zbc6ePWuzeQWAo6MjTz75JN9//32B/bZo0YLk5OQCv3zmbehxJQ8PD5o1a8brr79OUFAQ27Ztu2bse/bsoVKlStdxlSIiIiIiIiIiUtyU4LsD0tLSOHz4sHm8d+9eKlSoQI0aNfj9998BsFqtrFixgpo1a+Y7v2XLlmzZsoXTp0/nq3NycqJt27YsXrz4mnFs3bqV7OxsAC5cuMCRI0euOe1k3759fPvttzZPAoqIiIj8lRS2kYY22BARERF7pSm6d0BWVhazZs3i3LlzODo64uPjwyuvvIKTkxMzZswgKioKwzCoV68ezZs3z3e+k5MTbdq0Yc6cOQX237p1a+Li4q4ZR2pqKjNnzsTR0RHDMGjdujXVqlXLN/03OTmZwYMHk52dTenSpXnppZfMHXTBdg0+gKioKLy9va/zboiIiIjce/KSeV5eXpqWKyIiInbPYly94JrIbVDYTsAiIiIi9xIl+ERERMReaA0+ERERERERERGRvygl+EREREREREREROyYEnwiIiIiIiIiIiJ2TAk+ERERERERERERO6YEn4iIiIiIiIiIiB1zKu4A/goiIyOJjY21KZs/fz5ubm5kZGSQkpJCbm4uGRkZ5o4n+/btw9/fn6ysLE6fPo23tzcAvXr14quvviIyMpKgoCCzv6SkJMaPH2+2yxu3Tp06NuP27duXqlWrMmjQIABWr17N+vXr6du3L8uXLyc2NpZy5cqZ7d944w0qV65MWloac+fOJS0tDScnJ6pUqUKPHj04dOgQixYtYujQoQB8/fXX7N69m8GDB+Ps7Hwb76KIiIjI3XPp5fYAHLmizHHGwuIJRkREROQWKcF3h/Xq1QuAjIwMxo0bR3R0tE19UlKSTQKtKGFhYdfVLjU1lQMHDlClSpV8dU2aNKFnz542ZTk5OYwdO5YXX3yR+vXrA7B161ZOnz5t0y4uLo6UlBTeeustJfdERETEbuUl9woqV5JPRERE7JGm6P4FPfnkk3z33XfX3T4hIYHg4GAzuQdQq1Yt/Pz8zONFixbx559/MmTIEFxcXG5rvCIiIiIiIiIicvP0BJ8dSU5OJioqyjweOHAgPj4++do99NBDLFmyhPT09Hx1K1euZPv27ebx6NGjOXDgAIGBgYWOm5KSQlpaGmPHjsXNza3ANvHx8cTHxwMwduxYvLy8rvu6RERERO6mI0XU6TuMiIiI2CMl+OzI9U7RdXBwMJ/iu//++23qCpqiey0+Pj6cPXuWzZs307hx4wLbREREEBERYR5nZmbe0BgiIiIi9wJ9hxEREZF7Vd6+DgXRFN2/qBYtWpCcnHxdX1KrVKlCampqofWlS5fmrbfeYu7cuWzduvV2hikiIiIiIiIiIrdICb6/KCcnJ9q2bcvixYuv2bZZs2akpKSwYcMGs2zjxo3s37/fPPb19WXgwIF8/PHH7N27906ELCIiInJXFLaRhjbYEBEREXulKbq3QU5ODr179zaP27Vrd8t9jh07FkdHRwCCg4N57LHH8q3B17Fjx0KnzAK0bt2auLg4m7Kr1+Dr1asXISEhDB06lDlz5jBnzhwcHR3x9/ene/funDlzxmxbrVo1+vTpw7hx4xgxYkSB6/+JiIiI2IO8ZJ6Xl5em5YqIiIjdsxiGYRR3EPLXk5aWVtwhiIiIiFyTEnwiIiJiL7QGn4iIiIiIiIiIyF+UEnwiIiIiIiIiIiJ2TAk+ERERERERERERO6YEn4iIiIiIiIiIiB1Tgk9ERERERERERMSOKcEnIiIiIiIiIiJix5yKO4DidvLkSebMmcPu3btxcnLC29ubbt264evry4EDB5g1axbHjx/HMAxatGhBx44dsVgsLF++nN27d9OzZ0+b/vr27cuYMWPw9PQ0y5YvX05sbCzlypUzy9544w0qV67M4cOHmTt3LocOHcLd3R13d3f+8Y9/UKNGjSLPu9Jzzz2Hn58fVquVSpUq0bdvX1xdXTl27BgzZ87k4MGDGIbBAw88QGRkJE5OTiQlJbFo0SKGDh3K8uXLmTZtGuPHj8ff3x+AgQMHMmTIED788EMuXrzI2bNnycnJMWOJiorC29v7tr8eIiIiInfDpZfbA3DkijLHGQuLJxgRERGRW/S3TvAZhkF0dDTh4eG8+eabAOzdu5dTp07h5eXF+PHj6dWrF3Xr1iU7O5uJEyfy888/8/jjj9/wWE2aNMmXDMzJyWHs2LFERkZSv359APbv309qaio1atQo9Lyrubi4EB0dDcDkyZP55ZdfaNu2LRMmTODRRx9l8ODBWK1Wpk+fzldffUVkZGS+PsqVK0dcXBwDBgywKf/ggw8ACk1oioiIiNibvOReQeVK8omIiIg9+ltP0U1KSsLJyYlHH33ULAsICCAsLIyEhARCQkKoW7cuAK6urvTo0YMFCxbctvETEhKoXr26mdwD8PPzo2XLljfdZ2hoKOnp6WzduhUXFxdatWoFgIODA926dWPZsmVkZ2fnO+/BBx/k4MGDpKWl3fTYIiIiIiIiIiJy9/2tn+Dbv38/VatWLbDuwIEDBAYG2pT5+PiQlZXF+fPnb3islStXsn37dvN49OjRBY5xPee5uLgU2PbSpUts3LiRevXqceDAgXzX5u7ujpeXF+np6fnOtVgstG/fnri4OPr163cjlwZAfHw88fHxAIwdOxYvL68b7kNERETkbjhSRJ2+w4iIiIg9+lsn+IpiGEahdRaL5Yb7u56pttHR0aSnp1OxYkUGDRp03efl5OQQFRUFQFhYGK1bt2bJkiUFxmkYRqHxN2vWjLi4ODIyMq7nkmxEREQQERFhHmdmZt5wHyIiIiLFTd9hRERE5F7l6+tbaN3fOsFXpUoV1qxZU2hdcnKyTdmRI0dwc3OjRIkSt238bdu2mcdRUVHs3r2b2NjYG+rnyjX48lSuXDnftZ0/f55jx45x3333cebMmXz9ODo68uSTT/L999/f0PgiIiIiIiIiIlJ8/tZr8NWqVYuLFy+aU0sBdu3axbZt22jevDnbt29n8+bNwOWn5GbPnk379gUvynwzmjVrRkpKCn/88YdZVtD6eDejdu3aZGdn89tvvwFgtVr5/PPPadmyJa6uroWe17JlS7Zs2cLp06dvSxwiIiIi95rCNtLQBhsiIiJir/7WT/BZLBYGDRrEnDlzWLBgAc7OzlSoUIHu3bvj4uLC4MGDmTVrFjNnzsRqtdKiRQubHXSXL1/OunXrzOPRo0cDl5/Ey5sG+9BDD+Hv759vLb1evXoREhLC0KFD+fzzz5kzZw6lS5emRIkSPPPMM2a7ws673mv77LPP+PbbbzEMg/vvv5/nn3++yPOcnJxo06YNc+bMueYYIiIiIvYqL5nn5eWlabkiIiJi9yxGUYvNidwk7cYrIiIi9kAJPhEREbEXRa3B97eeoisiIiIiIiIiImLvlOATERERERERERGxY0rwiYiIiIiIiIiI2DEl+EREREREREREROyYEnwiIiIiIiIiIiJ2zKm4A7jXREZGEhsbC8CGDRuYM2cO77zzDkuXLuXXX3/F09PTbDty5EhGjRpFnz59CAgI4NKlS3Tv3p2XX36ZFi1aADBkyBBeffVVAgMDbcbZtWsXX3zxBcePH6dEiRKUKVOGLl264OfnZ7aJioqiUqVKvPnmm2ZZTEwM27Ztw93dHYAXX3yR2rVrm/GcOHECZ2dncnNzqV27Np07d6ZkyZIAPPfcczb9N23alA4dOjBy5EiysrIYO3YsALt37yY2NpaRI0eSnZ3N9OnT2bdvHwDu7u68/fbbuLm53Zb7LSIiIiIiIiIit0YJvkJs2bKF2bNn8/bbb+Pl5QVA27Ztad++vU274OBgUlJSCAgIYN++ffj6+rJjxw5atGhBVlYWGRkZBAQE2Jxz8uRJJk2aRP/+/QkJCQFg+/btpKenmwm4gwcPYrVaSU5OJisryyahFhkZSePGjdm6dSuffvopkydPNuv69+9PUFAQubm5zJs3j/HjxzNq1CgAXFxciI6OLvB6T506xZ9//sn9999vU/7jjz9SunRpJk6cCEBaWhqOjo43ejtFRERE7imXXr78ne7IFWWOMxYWTzAiIiIit0hTdAuQnJzM9OnTGTp0KD4+PkW2DQ0NJSUlBYCUlBQeeeQR9u7dC1x+Sq9q1ao4ONje5p9++onw8HAzuZfXT8OGDc3jhIQEWrRoQd26dfnjjz8KHDs4OJjjx48XWOfk5ETXrl3JzMw04ylK+/btiYuLy1d+4sQJypUrZx77+vri7Ox8zf5ERERE7lV5yb3rLRcRERG51ynBd5Xc3FzGjx9vTo+90uLFi4mKiiIqKsp8Ki44OJgdO3YAlxN8YWFhODs7c+HCBXbs2GGTxMtz8OBBqlatWmQcq1atokmTJjRt2pTExMQC22zcuJEGDRoU2oeDgwP+/v6kpaUBkJOTY8YfFRXFypUrzbbBwcE4OTmxdetWmz5at27NggULePvtt/n66685fPhwkXGLiIiIiIiIiMjdpSm6V3F0dCQkJISlS5fy0ksv2dQVNEXX29ub3NxcTp48SVpaGr6+vgQFBbFz505SUlJo06bNNcccNmwYFy5coE6dOrz00kvs2rULT09PKlSoQPny5Zk2bRpnz57Fw8MDgNjYWL744gtOnTrF6NGjr/vaipqiC9CxY0fi4uLo0qWLWRYQEMCUKVPYtGkTW7Zs4a233uL999+ncuXKNufGx8cTHx8PwNixY81pzSIiIiL3miNF1Ok7jIiIiNgjJfiuYrFYGDBgAO+99x5xcXE888wz1zwnODiY1atXU7ZsWSwWC9WrVyclJYVdu3ZRvXr1fO0rV67Mnj17zKfvPvjgA1avXs369esBSExM5NChQ/Tt2xeACxcusGbNGh5++GHg8hp8DRs25H//+x8xMTGMGzeuwLisViv79+/P9yRiYWrVqsU333zDzp07bcrd3Nxo1KgRjRo1wmKx8Oeff+ZL8EVERBAREWEeZ2ZmXteYIiIiIvcSfYcRERGRe5Wvr2+hdZqiWwBXV1eGDh1KQkICS5cuvWb7kJAQFi9ebCbzgoOD+f333ylTpoy5g+2VHn/8cZYvX26u3QeQnZ0NXE7KrV69mgkTJhATE0NMTAxRUVH5puk6ODjwxBNPYBgGGzduzDdG3iYb5cuXx9/f/7qv/emnn2bBggXm8fbt2zl79qzZ58GDB6lQocJ19yciIiIiIiIiIneWnuArhIeHB8OGDWPEiBGUKlUKuLwG34oVK8w2UVFReHt7ExISwty5cwkODgagbNmyWK3WAtffAyhTpgxvvvkmX375JcePH6d06dKUKlWKZ599luTkZMqVK2ezsUWNGjWYPHkyJ06csOnHYrHwzDPPsHDhQurVqwfA5MmTcXZ25uLFi9SuXZvBgweb7fPW4MtTr149m+m4AA888ACenp7m8ZEjR/jss88wDAPDMHjggQdo1KjRjdxKERERkXuK44yFBW6ooV10RURExF5ZDMMwijsI+evJ29hDRERE5F7m5eWlabkiIiJiFzRFV0RERERERERE5C9KCT4RERERERERERE7pgSfiIiIiIiIiIiIHVOCT0RERERERERExI4pwSciIiIiIiIiImLHlOATERERERERERGxY07FHcC94rnnnsPPz888joqKwtvbmx9++IGvvvqKGTNm4O7uDkBSUhLjx4/nvvvuIycnhwceeIAXX3wxX5/Xard27Vrmz59Pbm4ujo6OPPfcczRs2NCsX7hwIUuXLsXR0REHBwfatWtHeHg4I0eOJDIykqCgIDIyMnj//ffp0aMH9erVA2D8+PGcOnWK0aNHAzBnzhwqVKhA27ZtARg9ejTly5end+/eAHz++eeUK1eOdu3acenSJV555RUefvhhXnjhBTZt2sT8+fN5//33sVgsWK1WhgwZQq9evQgJCbm9L4KIiIjIXXLp5fYAHLmizHHGwuIJRkREROQWKcH3/7m4uBAdHZ2vPDExkaCgINauXUvLli3N8rCwMIYOHUpOTg6DBw+mYcOGhIaG5ju/sHZ79+4lNjaW4cOH4+3tTUZGBu+99x733Xcf/v7+LFmyhC1btvDBBx/g7u7O+fPnWbt2rU3fx44dY/To0bz44otmcu/cuXPs2bMHNzc3MjIy8Pb2JiQkhFWrVtG2bVusViunT5/m/PnzZj8pKSl0794dgE2bNuHr68uqVat4/vnnqVu3LsuWLWPp0qU8/PDD/O9//yMoKEjJPREREbFbecm9gsqV5BMRERF7pCm6RUhPTycrK4vOnTuTmJhYYBsXFxcCAgI4fvx4kX1d3W7RokU8/fTTeHt7A+Dt7c3TTz/NwoWXv1R+99139OzZ03xq0N3d3SbBePLkSd5//306d+5M/fr1zfI1a9bw4IMP0qRJEzPmkJAQduzYAcDBgwepUqUKJUqU4OzZs1y8eJFDhw5RtWpV4HJCs02bNnh5ebFz504AunXrxvfff8+BAwf46aef6Nq16w3dRxERERERERERuXP0BN//l5OTQ1RUFHA52RYVFUViYiJNmzYlNDSUtLQ0Tp06RenSpW3OO3v2LIcPH6ZGjRpF9n91u4MHD/L/2PvzuKrr/P//v53D4gEVFRFRERFkMddcCMFcimyRSNLUScnSNOejaU2ijjWj1pgi2U6NY9pCU5O/1NL0YhMWlQe1slxTdERyQSSURURA5Pz+8Mvr7YlFTA1O3a+Xy1zevJ7r4/WyP87l8X4ud999t12bgIAAPv30U86dO0dJSQk+Pj41jvfqq68yevRo+vXrZ1dutVoZMWIEzZo14/nnnyc2NhZPT0+cnJzIzc0lPT2d4OBgTp8+zYEDB3B3d6dDhw44OztTVlbGnj17mDRpEsXFxWzevJng4GBatGjBXXfdxVNPPcVDDz1EkyZNqsSTkpJCSkoKAIsWLcLLy6vW7yEiIiJSX07WUqffMCIiIuKIlOD7/1S3RTctLY0ZM2ZgNpsJCwtjy5Yt3HHHHQDs27ePGTNmkJWVxbBhw2jevHm149bUzmazYTKZqu1js9kuG2+3bt346quvGDRoEI0aNQIururLzs4mNDQUk8mEk5MTR44cwc/Pj5CQENLT00lPTyc6OtouwRccHAzA9u3b6dKlC40aNeKmm25i1apVPPjgg5jNZm6//Xbee+89u1WEl4qKiiIqKsp4zs3Nvew7iIiIiDQ0+g0jIiIiDVXbtm1rrFOCrwY//fQTJ06c4B//+AcA5eXleHt7Gwm+yrP1srKy+Pvf/05YWBj+/v5Vxqmpna+vL4cOHaJDhw5G24yMDHx9fXF3d8disXDy5Elat25dbXz33HMPX3/9Nc8//zwzZ87EycmJtLQ0ioqKmDp1KgDFxcWkpaXh5+dHcHAw6enpHD16FD8/P7y8vPjkk09wc3Nj8ODBwMXVf+np6UyZMgWAM2fOsGfPHrp3747ZrN3cIiIiIiIiIiINkbI2NbBardx3330kJSWRlJTE0qVLOX36ND///LNdu7Zt2zJs2DA++uijWsf7ZbuYmBg++ugjcnJyAMjJyWHNmjXGtt1hw4axfPly4zKM4uJiYwtspXHjxuHm5sbrr7+OzWbDarXy5JNPGjEnJCQY5/CFhoby/fff06RJE8xmM02aNOHs2bMcOHCA4OBgiouL2b9/P6+99prRf8KECTWePSgiIiLiqGq6SEMXbIiIiIij0gq+GlitVubMmWNXFhYWhtVqJSgoyK58yJAhrFu3zri1tiaXtvP392fMmDEkJCRw4cIFnJycGDt2rLEKcMiQIZSUlPDXv/4VZ2dnnJyciI6OthvPZDIxdepUFi1axAsvvEBubq5dbN7e3ri7u3Pw4EECAwM5c+YM/fv3N+r9/PwoKSnBw8OD1NRUunbtiouLi1Hft29f3n33Xc6fP29XLiIiIuLoKpN5Xl5e2pYrIiIiDs9kq8uBbyJXKCsrq75DEBEREbksJfhERETEUdR2Bp+26IqIiIiIiIiIiDgwJfhEREREREREREQcmBJ8IiIiIiIiIiIiDkwJPhEREREREREREQemBJ+IiIiIiIiIiIgDc67vAK6VuLg4kpOT7cqKi4tZsWIF6enpAISEhDB+/Hjc3d3Jyclh6tSpPPTQQ9x5550ALF++nMDAQAYNGgTAJ598QkpKCk5OTpjNZrp27cqYMWNwdrb/bPPmzSMuLo7AwEA+//xz1q9fj8lkwmazMXr0aPr27UtSUhK9e/cmPDy8SuyHDx9m1qxZzJkzh549exrlI0eOJDo6mgceeACAtWvXUlJSwsiRI1m5ciWbNm3Cw8OD0tJS/Pz8GD16NL6+vtV+n7Vr1/L5558b7xIdHc3AgQON2JcvX8758+cpKiqirKwMT09PAHx9fencuTNDhgwB4ODBgyxdupSEhAScnJyu8F9JRERERERERESutd9Ngq86r7/+Ou3bt2fq1KkArFy5kn/+85/85S9/AaBZs2Zs2LCB2267rUrS7r///S87d+5kwYIFNG7cmPLycj755BPKysqqtK106tQp1qxZQ0JCAu7u7pSUlFBYWHjZOK1WK6GhoVitVrsEn4uLC9u2bWPYsGF4eHhU6Td06FBiYmIASEtLY/78+SxZsqRK2//+97/s3r2bZ599Fnd3d4qLi/nmm2/s2jz77LMApKamcujQISZMmABAfn4+Tz31FOHh4TRp0oQVK1bw8MMPK7knIiIiDu3CxIu/oU5eUua0bG39BCMiIiJylX63W3Szs7PJyMhgxIgRRtmIESM4dOgQ2dnZAHh4eNCtWzdSU1Or9F+zZg0TJ06kcePGADg7OzNs2DDc3d1rnLOgoACLxYLFYgHAYrHg7e1da5w2m42tW7fy//7f/2PXrl2UlZUZdWazmaioKNavX3/Z942IiKBHjx5s3ry52neZMGGCEbu7u7uxSvFymjdvzt133827777LZ599hp+fH6GhoXXqKyIiItIQVSb36louIiIi0tD9bhN8x44dw9/fH7P5/17RbDbj7+/PsWPHjLJhw4bxySefUFFRYZSdO3eOkpKSyybnfsnf35/mzZszZcoUXnvtNb777rvL9klPT8fb2xsfHx9uuOEGfvjhB7v622+/nc2bN1NcXHzZsTp27Mjx48ftyirfxcfH54re5VK33XYbx44dY+3atYwdO/ZXjyMiIiIiIiIiItfe73aLrs1mw2QyVVt+KW9vbzp16mS38u2XbXbs2MG///1viouLmTZtGiEhIdXOaTabmTNnDocOHWL37t28/fbbZGRkMHLkyBrj3Lx5MxEREQBERkby1VdfcdNNNxn17u7uDBgwgA0bNuDq6nrZd65L2ZWqXEmYkZFB06ZNq22TkpJCSkoKAIsWLcLLy+uq5xURERG5Hk7WUqffMCIiIuKIfrcJvvbt23P48GEqKiqMVXwVFRX89NNPVS6iiI2N5fnnn6dz587AxaSaxWIhJycHb29vevbsSc+ePVm0aBHl5eW1zmsymejUqROdOnWie/fuvPbaazUm+CoqKti2bRvbt29nzZo12Gw2zpw5w7lz53BzczPaDR06lFmzZl12W21mZiYBAQF2ZZXvcvLkSVq3bl1r/9qYzeZqE6aVoqKiiIqKMp5zc3N/9VwiIiIi9UW/YURERKShatu2bY11v9stuj4+PnTs2JHVq1cbZatXr6Zjx45Vtqu2a9eOdu3asX37dqNs2LBhLFu2jLNnzwIXV8KdP3++1jlPnz5NRkaG8ZyZmUmrVq1qbL9r1y78/f15/fXXSUpK4rXXXuOmm27i22+/tWvXpEkT+vXrx+eff17jWFu3bmXnzp3079+/St2wYcNYvny5sc23uLjYWG0nIiIiIiIiIiKO7Xezgq+srIzJkycbz9HR0UyePJkVK1bw6KOPAhAUFMSf//znavvfe++9zJo1y3geMmQIpaWlzJkzBxcXFywWCyEhIXTs2LHGGC5cuEBycjJ5eXm4uLjg4eHBxIkTjfp//etfvPXWWwC0bNmStm3b0rdvX7sxwsPD+e9//8uAAQPsyqOjo9m4caNd2fr16/n6668pLS2lffv2zJ07t9rbdocMGUJJSQl//etfcXZ2xsnJiejo6BrfQ0REROT3zGnZ2mov1NAtuiIiIuKoTLZrcUibyC9kZWXVdwgiIiIil+Xl5aVtuSIiIuIQ/pBbdEVERERERERERP4IlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOTAk+ERERERERERERB+Zc3wFIVaNGjcLPzw8As9nM+PHjCQkJMeo/+eQT3n//fZYtW4abmxt///vfuffee7nxxhsBSEtL44svvuDJJ59k9erVbN68GbPZjMlkYtKkSQQFBTFv3jzi4uIIDAxkypQpWCwWACoqKrjpppsYPnw4Li4u5OTk8Pjjj9tdxRwdHc3AgQN/wy8iIiIicm1dmBgDwMlLypyWra2fYERERESukhJ8DZCrqyuJiYkA7Nixg/fee4/58+cb9VarlcDAQL755hsGDRrExIkTeeGFF+jSpQsVFRX85z//Yc6cORw4cIDt27eTkJCAi4sLhYWFlJeXVzvn3Llz8fDwoKSkhKVLl7J06VKmTp0KgI+PjxGPiIiIiKOrTO5VV64kn4iIiDgibdFt4M6dO0fjxo2N5+zsbEpKShg9ejRWqxUAPz8/evfuzccff8yHH37IgAED8PHxIS8vj6ZNm+Li4gKAh4cHnp6etc5nsViYOHEi3377LUVFRdfvxURERERERERE5JrQCr4GqKysjPj4eM6fP09eXh5z58416qxWK5GRkYSGhpKVlUVBQQHNmjVjxIgRzJo1C2dnZxYtWgRAjx49+PDDD5k+fTrdunUjIiKCG2644bLzu7u74+3tzYkTJ2jWrBnZ2dnEx8cb9ePHj6dz5852fVJSUkhJSQFg0aJFeHl5XYtPISIiInLNnaylTr9hRERExBEpwdcAXbpF98CBA7z66qssWbIEk8lEWloaM2bMwGw2ExYWxpYtW7jjjjuwWCxERERgsViMFXsWi4WEhAT27dvH3r17eeGFFxgzZgyDBg26onjqskU3KiqKqKgo4zk3N/fKXlpERESkAdBvGBEREWmoLr0f4ZeU4GvggoODOXPmDIWFheTn53PixAn+8Y9/AFBeXo63tzd33HEHACaTCZPJZNffbDbTpUsXunTpgp+fH6mpqZdN8J07d46cnBzatGlDcXHxdXkvERERERERERG5NpTga+COHz9ORUUFTZs2Zf369dx3333ExsYa9VOmTOHnn3+mVatWVfpmZWVhMplo06YNAJmZmdW2u1RJSQlvvPEGffv2pUmTJkrwiYiIyO+O07K11V60oQs2RERExFEpwdcAVZ7BV2nKlCmYzWasVitz5syxaxsWFobVamXYsGFVxikpKWHFihWcPXsWJycnfHx8mDRpUrVzVt7SW1FRQVhYGMOHDzfqfnkG3+DBg7nrrruu5hVFRERE6lVlMs/Ly0vbckVERMThmWw2m62+g5Dfn6ysrPoOQUREROSylOATERERR1HbGXzm3zAOERERERERERERucaU4BMREREREREREXFgSvCJiIiIiIiIiIg4MCX4REREREREREREHJgSfCIiIiIiIiIiIg7Mub4D+K2NHDmSm2++mUcffRSACxcuMGnSJIKCgpg9ezapqakcOnSICRMmsHLlSjZt2oSHhwelpaX4+fkxevRofH19AZg3bx55eXm4uLhQXl5Ot27dGD16NI0bNwYgLi6O5ORku/kvHbPSvHnzjD4AU6ZM4cknn7S7HeWtt96iRYsWdOrUiXXr1lWJ9VJTpkxh4cKFdnNU+uSTT3j//fdZtmwZ7u7uRvmOHTv44IMPOHfuHC4uLrRt25a4uDi8vLxISkrixx9/NNo3atSIf/zjH7/q+4uIiIiIiIiIyLX1h0vwNWrUiKNHj1JWVoarqyu7du3C09OzxvZDhw4lJiYGgLS0NObPn8+SJUuM5Nm0adMIDAykvLyc9957j8WLFzN//vxaY7h0zOpERkZitVq57777AKioqGDr1q0888wz5OTkXOkr27FarQQGBvLNN98waNAgAI4cOcKKFSuYOXOmkbz87rvvyMnJwcvLC7iYrAwPD7+quUVEREQaigsTL/4WO3lJmdOytfUTjIiIiMhV+kNu0e3Zsyfff/89cDHhFRkZWad+ERER9OjRg82bN1epc3Z2ZuzYseTm5pKZmXlV8UVGRpKWlmY879u3j1atWtGqVaurGjc7O5uSkhJGjx6N1Wo1yj/++GNiY2ON5B5Anz59uOGGG65qPhEREZGGqDK5V9dyERERkYbuD7eCDy4m0D788EN69erFTz/9xODBg9m/f3+d+nbs2JHjx49XW2c2m+nQoQNZWVn4+/vXOMb69ev5+uuvAWjSpAlz5861q+/QoQMmk4nMzEz8/f2vKAlZm8pxQkNDycrKoqCggGbNmnHs2DHuvvvuWvsmJyezatUqANq3b8+0adOuOh4REREREREREbl6f8gEX4cOHfj555+xWq3ceOONV9TXZrNd9fyX26IL/7eKr3379nz33XeMGjXqqudNS0tjxowZmM1mwsLC2LJlC3fccYddmzNnzvD0009TVlbGrbfeasR5uS26KSkppKSkALBo0SJja6+IiIhIQ3Oyljr9hhERERFH9IdM8MHFLajJycnMmzePM2fO1LlfZmYmAQEB1dZVVFRw5MgR2rVrd9XxRUZGsmDBAm644QY6dOhAs2bNrmq8n376iRMnThiXY5SXl+Pt7c0dd9yBr68vhw8fxt/fn6ZNm5KYmMjatWspKSmp8/hRUVFERUUZz7m5uVcVr4iIiEh90G8YERERaaguvYz1l/6wCb7Bgwfj7u6On58fe/furVOfrVu3snPnTh544IEqdeXl5fznP/+hZcuWdOjQ4arj8/HxoUmTJvz73/9m6NChVz1e5aUdsbGxRtmUKVP4+eefueeee0hMTCQoKMg4h6+srOyq5xQRERERERERkevvD5vga9myJXfddddl21Wel1daWkr79u2ZO3eucYMuwMsvv4yLiwvnz5+nW7duzJw506grKytj8uTJxnN0dLTdmJXi4+Px9vauMndkZCTvv/8+YWFhNcaXmprKt99+azwvWLDAGNNkMgHQr18/vvnmG+bMmWPXNywsDKvVyrBhw3jooYdISkri3LlzNG3alJYtWzJy5Eij7aVn8AEsXLgQZ+c/7H8+IiIi4sCclq2t9kIN3aIrIiIijspkuxaHyon8QlZWVn2HICIiInJZXl5e2pYrIiIiDqG2Lbrm3zAOERERERERERERucaU4BMREREREREREXFgSvCJiIiIiIiIiIg4MCX4REREREREREREHJgSfCIiIiIiIiIiIg5MCT4REREREREREREH5lzfATiCnJwcEhISWLJkiVG2cuVKLBYLMTExNfZLTU3l0KFDTJgw4bcIs06+/PJL1q5di81mw2azMXjwYGJiYvjggw/o3Lkz3bt3Z/369URFRdGoUaP6DldERETkurgw8eJvuJOXlDktW1s/wYiIiIhcJSX4/kB++OEHNmzYwJNPPomnpydlZWV89dVXAIwaNcpot2HDBm6++WYl+EREROR3qTK5V125knwiIiLiiJTguwbmzZtHp06d2Lt3L8XFxUyePJnOnTvbtfn+++9ZtWoVs2bNIjk5GTc3NzIyMsjPz2fs2LGEh4djs9l499132bFjBwDDhw8nIiKCN954g549e9KnTx8SExNp3Lgx/+///T8+//xzcnJyuOWWW1i4cCEhISEcOHAAT09PZs6ciaurq10MH330EXFxcXh6egLg6upKVFQUAElJSfTu3ZvTp09z+vRp5s+fj4eHBzfffDNHjhzhwQcfBCAlJYXjx48zbty46/tRRURERERERESkTpTgu0YqKipYuHAh33//PR9++CF/+9vfjLpvvvmGTz75hL/+9a80adIEgPz8fJ5++mmysrJISEggPDycbdu2kZmZSWJiIoWFhfz1r3+lc+fOdO7cmX379tGnTx9Onz5Nfn4+APv37yciIgKAEydOMH36dCZPnszzzz/P1q1bGTBggF2MR44cISAgoNb3uOuuu1i/fj1z587Fw8ODkpIS1qxZw9ixY3F2diY1NZVJkyZV6ZeSkkJKSgoAixYtwsvL61d/SxEREZHr6WQtdfoNIyIiIo5ICb46MJlMly0PCwsDICAggJycHKN87969ZGRk8OSTT+Lu7m6U9+3bF7PZjK+vLwUFBcDFhF1kZCRms5nmzZtzww03cOjQITp37syGDRs4duwYvr6+nD17lry8PA4cOMBDDz3EmTNn8Pb2xt/f34jh559/vibvbrFY6NKlC99//z3t2rXjwoUL+Pn5VWkXFRVlrAYEyM3NvSbzi4iIiPyW9BtGREREGqq2bdvWWKdbdOugadOmFBUV2ZUVFRXRtGlT49nFxQUAs9lMRUWFUe7t7c25c+c4ceKEXf/K9gA2m63W+T09PSkqKmLHjh107tyZ0NBQtmzZgsViwc3Nrcp4ZrOZCxcuVBmnffv2ZGRkXO51q7j11ltJTU3liy++YNCgQVfcX0RERERERERErh8l+OrAYrHQokULdu/eDVxM7u3cuZPQ0NDL9m3VqhUzZszg1Vdf5ejRo7W27dy5M1u2bKGiooLCwkL27dtHp06dAAgODmb9+vXccMMNdO7cmXXr1tVp/ksNGzaMd99919jie/78eTZs2FDt+5aUlBjPQUFBnDp1CqvVSmRk5BXNKSIiItLQ1HSRhi7YEBEREUelLbp1NHXqVJYvX84777wDwIgRI/Dx8alT37Zt2zJt2jSef/55Zs2aVWO7sLAwDhw4QHx8PABjx46lefPmwMXk365du/Dx8cHLy4uioqIqF3lcTq9evSgoKOCZZ57BZrNhMpkYPHhwlXZRUVE8++yztGjRgrlz5wLQr18/MjMzjTMERURERBxZZTLPy8tL23JFRETE4Zlsl9sfKsLFizOGDh1Kt27d6tQ+KyvrOkckIiIicvWU4BMRERFHoTP45Fc7e/Ys06dPx9XVtc7JPRERERERERER+e1oBZ9cF1rBJyIiIo5AK/hERETEUWgFn4iIiIiIiIiIyO+UEnwiIiIiIiIiIiIOTAk+ERERERERERERB6YEn4iIiIiIiIiIiANzru8AHMlbb71Fq1atGDp0KAALFiygZcuWTJ48GYB33nkHT09PevTowYoVKzh9+jQ2m40BAwYwfPhwTCYTAN988w0rV66kvLwcJycnRo0aRVhYGABJSUn8+OOPuLu7U1ZWRlBQEPfffz+enp4ATJkyhYULF+Lh4QHA3r17WbduHbNnzzbiXLx4MQUFBSxYsMDo8+STT9odxvjWW2/RokULOnXqxOLFi/H29jbq4uLi6N69OyNHjiQ6OpoHHngAgLVr11JSUsLIkSOvy/cVERER+a1cmBgDwMlLypyWra2fYERERESuklbwXYGQkBDS09MBqKiooLCwkKNHjxr16enpBAQEsHjxYoYNG8ZLL71EYmIiBw4c4NNPPwUgMzOT5ORkZs6cyYsvvsisWbNITk7mp59+MsaJi4sjMTGRF198EX9/f+bPn095eXmdYjx79iyHDx+muLiYnJwcACIjI7FarUabiooKtm7dSkREBACdO3cmMTHR+F/37t0BcHFxYdu2bRQWFl7FVxMRERFpWCqTe3UtFxEREWnolOC7AiEhIRw4cACAY8eO0b59e9zc3CgqKuL8+fMcP36c48ePExISQo8ePQBo1KgR48eP5+OPPwZg3bp1xMbGGivmvL29iY2NZe3aqv8fY5PJRHR0NM2bN+eHH36oU4zbtm2jd+/eREREGEm9yMhI0tLSjDb79u2jVatWtGrVqtaxzGYzUVFRrF+/vk5zi4iIiIiIiIjIb09bdK+Ap6cnTk5O5Obmkp6eTnBwMKdPn+bAgQO4u7vToUMHsrKyCAgIsOvn4+NDSUkJxcXFHDt2jLvvvtuuPiAgwFjhV52OHTty/Phx+vbtC8D8+fMxmy/mZktKSmjXrp3R1mq1MmLECJo1a8bzzz9PbGwsHTp0wGQykZmZib+/P1arlcjISKPPvn37iI+PN56feOIJfHx8ALj99tuJj4/nnnvuqfXbpKSkkJKSAsCiRYvw8vKqtb2IiIhIfTlZS51+w4iIiIgjUoLvClVu001PTyc6OtouwRccHMz58+dr7GsymbDZbMZZfHVls9nsnufOnVvlDD6A/Px8srOzCQ0NxWQy4eTkxJEjR/Dz8zNW8bVv357vvvuOUaNGGeN17tzZ7gy/S7m7uzNgwAA2bNiAq6trjTFGRUURFRVlPOfm5l7RO4qIiIg0BPoNIyIiIg3VpXcr/JK26F6h4OBg0tPTOXr0KH5+fgQHB3PgwAHS09MJCQmhffv2ZGRk2PU5efIkFosFNzc3fH19OXTokF19RkYGvr6+Nc6ZmZlZa32ltLQ0ioqKmDp1KlOmTCEnJ8fYmhsZGcmWLVvYvXs3HTp0oFmzZnV+56FDh/LFF19QWlpa5z4iIiIiIiIiIvLbUILvCoWGhvL999/TpEkTzGYzTZo04ezZsxw4cIDg4GBuvvlm9u/fz65duwAoKyvjzTffJCbm4qHNMTExfPTRR8YFGDk5OaxZs6bKtl24uHJvw4YN5OXl0bNnz8vGZrVaefLJJ0lKSiIpKYmEhATjHD4fHx+aNGnCv//9b7vtuXXRpEkT+vXrx+eff35F/UREREQaoppuy9UtuiIiIuKotEX3Cvn5+XHmzBn69+9vV1ZSUmJsm505cyYrVqxg+fLlVFRUMGDAAO644w4A/P39GTNmDAkJCVy4cAEnJyfGjh2Lv7+/MV5ycjKrVq2itLSUoKAg5s6di7Nz7f9UOTk55ObmEhQUZJR5e3vj7u7OwYMHCQoKIjIykvfff5+wsDC7vr88g2/48OGEh4fbtYmOjmbjxo1X9rFEREREGqjKZJ6Xl5e25YqIiIjDM9l+ecCbyDWQlZVV3yGIiIiIXJYSfCIiIuIodAafiIiIiIiIiIjI75QSfCIiIiIiIiIiIg5MCT4REREREREREREHpgSfiIiIiIiIiIiIA1OCT0RERERERERExIE5/1YTrV69ms2bN2M2mzGZTEyaNImgoCDmzZtHXl4erq6uWCwW/vznP9O2bVu7cmdnZx555BH8/f0BmDJlCgsXLsTDw4ORI0cSHR3NAw88AMDatWspKSlh5MiRAHz11VesXbuWiooKnJycCAwMJC4ujsaNG9vNATB8+HDCw8OJi4sjOTmZnJwcHn/8cbtbSqKjoxk4cKBdDJVSU1NJTk6mZcuWlJSU0Lp1a0aMGEFISEi136S22AAKCwt55JFHGD9+PLfddpvRb8qUKVgsFkwmE40bN2bq1Km0atUKgFGjRuHn58eFCxdwcnJi4MCB3HXXXZjNZvbu3cvixYvx9vY2xoqLi6N79+61fsesrCz+9a9/cfbsWcrLywkNDeWRRx65qv8eREREROrThYkxAJy8pMxp2dr6CUZERETkKv0mCb4DBw6wfft2EhIScHFxobCwkPLycqN+2rRpBAYGkpKSQnJyMrNmzbIr/+KLL0hOTuZvf/tblbFdXFzYtm0bw4YNs0u2AezYsYP169czZ84cPD09qaioIDU1lYKCAiOJVjlHTXx8fEhMTKzzu0ZERDBhwgQA9uzZw3PPPcfcuXPx9fW94ti2bNlCUFAQVqvVLsEHMHfuXDw8PFi5ciWrVq1i8uTJALi6uhrxFhQU8PLLL1NcXGwkPDt37szs2bOv6Du++eabDB06lL59+wJw5MiROn8PERERkYamMrlXXbmSfCIiIuKIfpMtunl5eTRt2hQXFxcAPDw88PT0rNKuc+fOZGdnVykPDg7m9OnT1Y5tNpuJiopi/fr1VepWr15NXFycMZfZbOaWW26xW5F3PXXt2pWoqChSUlJ+VWxWq5UHHniAU6dO1fj+wcHB5OXlVVvXrFkzJk2axMaNG7HZbLXGWtt3zMvLo2XLlsazn59frWOJiIiIiIiIiMhv5zdZwdejRw8+/PBDpk+fTrdu3YiIiOCGG26o0m779u3VJo927NhhrB6rzu233058fDz33HOPXfnRo0cJCAioNbaXX37Z2KL797//naZNm9rVZ2dnEx8fbzyPHz+ezp071zrmpTp27Fhtgu9yseXm5pKfn0+nTp3o168faWlpREdHV2l3uW/TunVrbDYbBQUFAOzbt8/ufZ544gl8fHyAmr/j0KFDmT9/PiEhIXTv3p3BgwcbqwwrpaSkGO+5aNEivLy8aoxJREREpD6drKVOv2FERETEEf0mCT6LxUJCQgL79u1j7969vPDCC4wZM4ZBgwYB/5dka9WqFePHjzf6vfzyy5SWllJRUUFCQkKN47u7uzNgwAA2bNhgJOt+6ciRI7zyyiuUlJTwpz/9iYiICODab9H9NaqLLS0tjX79+gEQGRnJP//5T7sE3/z58ykoKKBZs2aMHj261vEvXb1X0xZdqPk7Dh48mB49erBjxw6+++47UlJSSExMNFZkAkRFRREVFWU85+bmXtlHEBEREWkA9BtGREREGqradqT+Zrfoms1munTpwsiRI5kwYQJbt2416qZNm0ZiYiIzZ860+/+aTps2jVdffZX+/fuzfPnyWscfOnQoX3zxBaWlpUZZ+/btycjIAC5uK01MTKRnz56UlZVd47er2eHDh2nXrl2V8svFZrVaSU1NZcqUKSxevJjMzExOnDhh9J87dy6vvfYavr6+fPDBBzXOf/LkScxmM82aNatTvNV9RwBPT09uueUWZs6ciZOTE0ePHq3TeCIiIiIiIiIicn39Jgm+rKwsu+RUZmamcevr5Tg7OzN69GgOHjzIsWPHamzXpEkT+vXrx+eff26UDRs2jOTkZE6dOmWU/ZbJvR9//JGUlBRuvfXWKnW1xZaVlUVJSQlLly4lKSmJpKQkYmNjsVqtdmO4urry4IMP8tVXX1FUVFRljsLCQpYtW8Ydd9yByWSqU8zVfccdO3YYl6Lk5+dz5syZas9QFBEREXEENV2koQs2RERExFH9Jlt0S0pKWLFiBWfPnsXJyQkfHx8mTZpU5/6urq5ER0ezbt06/vznP9fYLjo6mo0bNxrPvXr1orCwkGeffZaKigoaN25M+/bt6dGjR53n/uUZfIMHD+auu+4CID4+3kic9evXjw4dOpCWlsb+/fspKyvD29ubJ554osoNupeL7bPPPiMsLMyu/U033cSLL77IiBEj7MpbtGhBZGQkGzduZMSIEZSVlREfH8+FCxdwcnLi5ptvttva+8sz+IYPH054eHit33Hnzp28+eabxrbdsWPH0rx58zp/QxEREZGGpjKZ5+XlpW25IiIi4vBMtstdryryK2RlZdV3CCIiIiKXpQSfiIiIOIoGcQafiIiIiIiIiIiIXHtK8ImIiIiIiIiIiDgwJfhEREREREREREQcmBJ8IiIiIiIiIiIiDkwJPhEREREREREREQemBJ+IiIiIiIiIiIgDc67vAP7oRo4cyc0338yjjz4KwIULF5g0aRJBQUHMnj3baLd48WIKCgpYsGCBUZaVlcW//vUvzp49S3l5OaGhoTzyyCPs3buXxYsX07p1a86fP09ERAT33XefUe7t7W2MERsby5o1awDIz8/HbDbj4eEBwMKFC3nooYdITk422qempnLo0CEmTJhwXb+LiIiIyPV0YWIMACcvKXNatrZ+ghERERG5SnVO8J05c4amTZtez1j+kBo1asTRo0cpKyvD1dWVXbt24enpadfm7NmzHD58GIvFQk5OjpGge/PNNxk6dCh9+/YF4MiRI0afzp07M3v2bEpKSpg5cya9e/e2K79UREQEACtXrsRisRATE3Pd3ldERESkvlUm96orV5JPREREHFGdt+j++c9/ZvHixWzdupXy8vLrGdMfTs+ePfn+++8BsFqtREZG2tVv27aN3r17ExERgdVqNcrz8vJo2bKl8ezn51dlbIvFQkBAANnZ2dcpehERERERERERqU91XsH32muvsXnzZj7++GOWLl1KeHg4AwcOJDQ09HrG94cQGRnJhx9+SK9evfjpp58YPHgw+/fvN+qtVisjRoygWbNmPP/888TGxgIwdOhQ5s+fT0hICN27d2fw4ME0btzYbuwzZ85w8OBBhg8fTmFhIfv27SM+Pt6of+KJJ/Dx8akxtrKyMrv2RUVF9OnTp0q7lJQUUlJSAFi0aBFeXl6/7mOIiIiIXGcna6nTbxgRERFxRHVO8Hl4eHDXXXdx1113kZWVxVdffcUrr7yCyWTi5ptv5pZbbqFVq1bXM9bfrQ4dOvDzzz9jtVq58cYb7ery8/PJzs4mNDQUk8mEk5MTR44cwc/Pj8GDB9OjRw927NjBd999R0pKComJiQDs27ePmTNnYjKZuOeee2jfvj179+6tdotubVxdXY0x4f/O4PulqKgooqKijOfc3Nwr/QwiIiIi9U6/YURERKShatu2bY11v+qSjfz8fPLz8zl37hwdO3bk9OnTzJw5k3vuuYdhw4b92jj/0Pr06UNycjLz5s3jzJkzRnlaWhpFRUVMnToVgOLiYtLS0oztuJ6entxyyy3ccsstPPHEExw9ehSo/qw9ERERERERERH5/alzgu/o0aN8/fXXfP3111gsFgYOHMhzzz1nXAgxfPhw4uPjleD7lQYPHoy7uzt+fn7s3bvXKLdarTz55JMEBwcDkJOTwzPPPMPo0aPZsWMHXbt2xdnZmfz8fM6cOYOnpyfHjx+vr9cQERERafCclq2t9qINXbAhIiIijqrOCb65c+cSGRnJE088QadOnarUe3t7c9ddd13T4P5IWrZsWeX75eTkkJubS1BQkFHm7e2Nu7s7Bw8eZOfOnbz55pu4uroCMHbsWJo3b15rgu+XZ/ANHz6c8PDwa/w2IiIiIg1bZTLPy8tL23JFRETE4ZlsNputLg1//PFHbrjhhirl//vf/6pN+MkfW1ZWVn2HICIiInJZSvCJiIiIo6jtDD5zXQdJSEiotnzBggVXHpGIiIiIiIiIiIhcE5fdoltRUQGAzWYz/lfp5MmTODk5Xb/oREREREREREREpFaXTfD96U9/Mv4ePXq0XZ3ZbCY2NvbaRyUiIiIiIiIiIiJ1ctkE36uvvorNZmPevHnMnz/fKDeZTHh4eBgXPIiIiIiIiIiIiMhvr86XbIhcCV2yISIiIo5Al2yIiIiIo6jtko1aV/AtXbqURx55BLi4kq8mU6dO/ZWh/TZOnTrF8uXLOXbsGBUVFdx444088MADuLi4kJqayqFDh5gwYYLRft68ecTFxREYGMiUKVOwWCyYzRfvI+ncuTPjx48nKSmJH3/8EXd3dwAaNWrEP/7xD1JTU3n99ddZvHgxHTp0AOCJJ55g1qxZeHt78/nnn7N+/XpMJhM2m43Ro0fTt29fY+69e/fy3nvv2V1ecuHCBSZPnszixYt577336N27N+Hh4XZxXtp/3bp1zJ49u9pvER8fT7t27Xjsscfsxv/ggw/YunUrjRo1AqBfv37ce++9AIwaNQo/Pz+jfWRkJMOGDfs1/xQiIiIiDcKFiTEAnLykzGnZ2voJRkREROQq1Zrg8/b2Nv5u3br1dQ/merDZbDz33HMMGTKEmTNnUlFRwdKlS3n33Xd56KGH6jTG3Llz8fDwqFIeFxdHeHh4lXJPT09Wr17N448/bld+6tQp1qxZQ0JCAu7u7pSUlFBYWGjXpnPnzpw+fZqcnBzj++/evZv27dvTokWLur52tSoTnPv27aOkpASLxQLAf/7zH/Lz83nuuedwdXXl3LlzrFu3zujn6upKYmLiVc0tIiIi0lBUJveqK1eST0RERBxRrQm+2NhY9u/fz3fffcfYsWOr1L/77ruEhYVdt+CuhT179uDq6srgwYOBixeDjBs3jilTpthdIHIt9e7dm3379pGVlWW3fLKgoACLxWIk1i79u5LZbCY8PJy0tDRjlZzVaiUyMvKq49q8eTMDBgzg+PHjfPfdd/Tv35/S0lI2bdpEUlKScZ6im5sbI0eOvOr5RERERERERETk+rvsJRtr1qzh9ttvr7aua9eurF69usbtoA3B0aNH6dixo12Zu7s7rVq1Ijs7u05jzJ8/39iiO3DgQKKjowFITk5m1apVALRv355p06YBFy8giYmJYfXq1Xbbl/39/WnevDlTpkyhW7duhIWF0adPnyrzRUZG8q9//Ythw4Zx/vx5fvjhB8aNG3flL/8LW7Zs4amnniIrK4uNGzfSv39/srOz8fLyws3NrcZ+ZWVlxMfHG8+xsbFERETYtUlJSSElJQWARYsW4eXlddXxioiIiFwPJ2up028YERERcUSXTfBlZmbSs2fPauu6devG66+/fq1juuZMJlOVssvdLXJpnyvdogvQv39/Vq9eTU5OjlFmNpuZM2cOhw4dYvfu3bz99ttkZGRUWS3XqVMnSkpKyMrK4tixYwQFBdGkSZNa472c//3vf3h4eNCqVStatmzJ66+/TlFRUZV2X3zxBRs2bKCoqIhnnnkGLy+vOm3RjYqKIioqynjWYdUiIiLiiPQbRkRERBqq2i7ZMF+u87lz5ygvL6+27sKFC5w7d+7XR/Yb8PX1JSMjw66suLiYgoIC2rZtS9OmTTl79qxdfVFREU2bNr2qeZ2cnLj77rv56KOP7MpNJhOdOnUiNjaWxx57jG3btlXbPyIiAqvVSlpa2jXZnmu1Wjl+/DhTpkzh0Ucf5dy5c2zbtg0fHx9yc3ONf8fBgweTmJiIu7s7FRUVVz2viIiIiIiIiIhcX5dN8LVr146dO3dWW7dz507atWt3zYO6lrp160ZpaSlffvklABUVFbzzzjvccccduLq6EhgYSHp6Ovn5+QAcOnSI8+fP07Jly6uee9CgQezevdu4SOP06dN2ycbMzExatWpVbd/+/fvz9ddfs2fPnmq38V6JiooKtm7dynPPPUdSUhJJSUnEx8djtVpp1KgRt9xyC8uXL6esrMxoX1NSV0RERMTR1XSRhi7YEBEREUd12S26Q4cO5V//+hcVFRX07dsXs9lMRUUF3377LcuXL+eBBx74LeL81UwmEzNmzGD58uWsWrWKwsJCIiIiuPfeewFo3rw5Dz74IAsXLqSiogKLxcL06dONM/fA/gy+Dh06GOfqXXoGH8DChQvt5nZ2dubOO+/krbfeAi6ueExOTiYvLw8XFxc8PDyYOHFitXH7+vrSqFEjAgICqlzEcalFixbh5OQEQHBwMLfffju7d+9m8uTJRpvbb78dT09PPD09jbIbbriBl19+mby8PEaPHs0HH3zAE088gZubG66urgwcONBo/8sz+Hr27MmYMWNqjElERESkoatM5nl5eWlbroiIiDg8k+1yh9EBn3zyCStXruT8+fN4eHhQWFiIq6sr9913n3HhhKNIT0/npZdeYsaMGQQEBNR3OL9bWVlZ9R2CiIiIyGUpwSciIiKOorYz+OqU4IOL59YdOHCAoqIimjRpQnBwMO7u7tcsSPl9UYJPREREHIESfCIiIuIoakvwXXaLbiV3d/cab9MVERERERERERGR+nHZSzZERERERERERESk4VKCT0RERERERERExIEpwSciIiIiIiIiIuLAlOATERERERERERFxYHW+ZOP3YNSoUfj5+VFRUUGrVq149NFHady4MQBHjx5lxYoVnD59GpvNxoABAxg+fDgmkwmAH374gQ8++IDS0lJsNhu9evXigQceYOXKlVgsFmJiYigrKyMhIYHQ0FDuu+8+AD755BPef/99li1bhru7O99++y1ffPEFM2fOBGDNmjV8/vnnvPLKKwB89913bNq0iVmzZgGwePFiCgoKWLBgAQUFBcyZM4cFCxbQvHlzAN544w28vLwYNmyY8Z45OTk8/vjjtG3blvLycjp37szDDz+M2WymsLCQRx55hPHjx3PbbbcZfaZMmYLFYsFkMtG4cWOmTp1Kq1atAIiLiyM5ORmA77//nrfeeou///3veHl5Xad/KREREZHr68LEGABOXlLmtGxt/QQjIiIicpX+UCv4XF1dSUxMZMmSJTRp0oRPP/0UgLKyMhYvXsywYcN46aWXSExM5MCBA0b9kSNHWLFiBY8++igvvPACS5YsoXXr1nZjl5eXs2TJEgICAozkHoDVaiUwMJBvvvkGgJCQEA4ePGjUHzhwAHd3dwoKCoznkJAQAM6ePcvhw4cpLi4mJyeHZs2acc899/DOO+8AkJGRwf79+4mOjq7yrj4+PiQmJvLcc89x/Phxvv32WwC2bNlCUFAQVqu1Sp+5c+fy3HPP0aVLF1atWlWlfvfu3bz55pvMmTNHyT0RERFxWJXJvbqWi4iIiDR0f6gE36WCg4M5ffo0AJs3byYkJIQePXoA0KhRI8aPH8/HH38MwNq1a4mNjaVdu3YAODk5cfvttxtjVVRU8OKLL9KmTRvGjBljlGdnZ1NSUsLo0aONhJqHhwfu7u5kZ2cDcPr0aW666SbS09MBSE9PNxJ827Zto3fv3kRERBj9o6KiOHnyJHv27GHFihWMHz8eZ+eaF2I6OTkRHBxszGe1WnnggQc4deqU8f7VfZu8vDy7sn379rF06VJmz56Nj4/PZb+viIiIiIiIiIj8Nv5QW3QrVVRUsGfPHm655Rbg4vbcgIAAuzY+Pj6UlJRQXFzM0aNHq10lV+njjz+mW7duPPjgg3blVquVyMhIQkNDycrKoqCggGbNmhEcHEx6ejoVFRW0adOGoKAgdu7cSe/evTly5AiBgYFG/xEjRtCsWTOef/55YmNjMZvNTJw4kfnz59OnTx9uuOGGWt+1tLSUPXv2MHLkSHJzc8nPz6dTp07069ePtLS0at9rx44d9O3b13guLy9n8eLFzJs3z0hy/lJKSgopKSkALFq0SCv8REREpME6WUudfsOIiIiII/pDJfjKysqIj4/n559/JiAggO7duwNgs9lq7FN5Bl9tQkNDOXjwIFlZWbRt29YoT0tLY8aMGZjNZsLCwtiyZQt33HEHISEhRoIvODiYTp068eGHH3L48GHatm2Lq6sr+fn5ZGdnExoaislkwsnJiSNHjuDn54e/vz9+fn52qwh/KTs7m/j4eEwmE3369OHGG29k7dq19OvXD4DIyEj++c9/2iX45s+fbyQhR48ebZQ7OTkREhLC559/zkMPPVTtfFFRUURFRRnPubm5l/1uIiIiIg2NfsOIiIhIQ3VpzumX/lAJvsoz+IqLi1m0aBEbN27krrvuon379uzbt8+u7cmTJ7FYLLi5ueHr60tGRgb+/v7Vjtu5c2cGDhzIwoULmT9/Pp6envz000+cOHGCf/zjH8DFVXDe3t5Ggm/jxo1UVFQQFRWFm5sb58+f58cffzS256alpVFUVMTUqVMBKC4uJi0tDT8/P+Bi4rG25GPlGXyXslqt5Ofns3nzZuDi9uATJ07Qpk0b4OIZfBaLhaSkJD744APGjRtnzPX444/zzDPPsHr1au69994r+ewiIiIiIiIiInId/SHP4HN3d+ehhx5i3bp1lJeXc/PNN7N//3527doFXFzp9+abbxITc/Gg5ZiYGNasWUNWVhZwcYvvJ598YjdmeHg4d999N88++yxnz57FarVy3333kZSURFJSEkuXLuX06dP8/PPP+Pr6kpeXx/79+42kob+/P5999hnBwcHAxWTck08+afRPSEio9mKMusrKyqKkpISlS5caY8bGxlYZ09XVlQcffJCvvvqKoqIio7xRo0bMnj2bzZs38/nnn//qOERERETqW0235eoWXREREXFUf8gEH0DHjh3p0KEDaWlpuLq6MnPmTFavXs306dN54oknCAwM5I477gCgQ4cOPPjgg7z00ks8/vjjPPHEE1UuoQAYMmQIYWFhLF68GKvVSlhYmF19WFgYVqsVk8lEp06daNq0qXFBRnBwMCdPniQkJIScnBxyc3MJCgoy+np7e+Pu7m53A++V2Lx5c5V4brrppmqThi1atCAyMpKNGzfalTdp0oQ5c+awatUq41ZeEREREUfktGwtTsvW0npNmvG3iIiIiKMy2Wo7gE7kV6pc7SgiIiLSkHl5eencPREREXEItZ3B94ddwSciIiIiIiIiIvJ7oASfiIiIiIiIiIiIA1OCT0RERERERERExIEpwSciIiIiIiIiIuLAlOATERERERERERFxYM71HUB9GDVqFH5+fsZzZGQkw4YNA6CwsJBHHnmE8ePHc9tttxltPv/8c9avX4/JZMJmszF69Gh27txJeno65eXl5OTkGLeZDB8+nPDwcKPvypUr2bRpEx4eHkbZvHnzyMzMZN26dcyePdsuvnnz5nHy5Elee+01TCYTAIsXL2b37t0kJyeTk5NDQkICS5YssZvDYrEQExPDvHnziIuLIzAwEMCu/d69e1m8eDGtW7emrKyMXr168cADDwCQn5/PP//5T06dOkV5eTne3t6MGTOGV155BYDc3Fzc3d1xd3fHw8ODv/3tb1f9byEiIiJSHy5MjAHg5CVlTsvW1k8wIiIiIlfpD5ngc3V1JTExsdq6LVu2EBQUhNVqNRJ8p06dYs2aNSQkJODu7k5JSQmFhYX07dsX+L8EWk1jAgwdOpSYmJg6x9i4cWPS09MJDQ3l7Nmz5Ofn1/0FL6Nz587Mnj2bsrIyZs6cSVhYGKGhoaxcuZLu3btz1113AfDTTz/h5+dnvFdSUhK9e/e2S16KiIiIOJrK5F515UryiYiIiCPSFt1fsFqtPPDAA5w6dYrTp08DUFBQgMViwWKxAGCxWPD29r6ucURERGC1WgHYtm0bYWFh13wOV1dX/P39jffMy8vD09PTqO/QocM1n1NERERERERERK6tP+QKvrKyMuLj443n2NhYIiIiyM3NJT8/n06dOtGvXz/S0tKIjo7G39+f5s2bM2XKFLp160ZYWBh9+vS5ojnXr1/P119/DUCTJk2YO3dure27devG0qVLqaioIC0tjUmTJrFq1SqjPjs72+4d8vPzufvuu68opqKiIk6cOMENN9wAwO23386LL77Ip59+Srdu3Rg0aJBdwq82KSkppKSkALBo0SK8vLyuKBYRERGR38rJWur0G0ZEREQc0R8ywVfTFt20tDT69esHXDyX75///CfR0dGYzWbmzJnDoUOH2L17N2+//TYZGRmMHDmyznNe6RZds9lMaGgoaWlplJWVVVkx6OPjY/cOK1euNP6uPLevJvv27WPGjBlkZWUxbNgwmjdvDkDPnj159dVX2bFjBz/88AOzZs1iyZIldmcH1iQqKoqoqCjjOTc3ty6vKSIiItKg6DeMiIiINFSVdz9U5w+Z4KuJ1WolPz+fzZs3A3D69GlOnDhBmzZtMJlMdOrUiU6dOtG9e3dee+21K0rw/RoRERE899xz3HfffVfUr0mTJpw9e9Z4LioqskvSVZ7Bl5WVxd///nfCwsLw9/c3+vbv35/+/fuzaNEifvzxR525JyIiIiIiIiLSgOkMvv9PVlYWJSUlLF26lKSkJJKSkoiNjcVqtXL69GkyMjKMtpmZmbRq1eq6x9S5c2eGDRtGZGTkFfXr0qULX331FTabDYAvv/ySLl26VGnXtm1bhg0bxkcffQTAnj17KC0tBeDcuXOcPHlS21RERETkd6emizR0wYaIiIg4qj/kCr5fnsHXs2dPXFxcqlxkcdNNN/Hiiy8ycOBAkpOTycvLw8XFBQ8PDyZOnHhFc156Bh9gzL97924mT55slP/lL38x/jaZTFe0rbdSVFQUx48fJz4+HpPJREBAAPfff3+1bYcMGcK6devIyckhIyOD5cuX4+TkhM1m45ZbbqFTp05XPL+IiIhIQ1eZzPPy8tK2XBEREXF4JlvlMi+RaygrK6u+QxARERG5LCX4RERExFHUdgaftuiKiIiIiIiIiIg4MCX4REREREREREREHJgSfCIiIiIiIiIiIg5MCT4REREREREREREHpgSfiIiIiIiIiIiIA1OCT0RERERERERExIE513cA18uoUaPw8/MznuPj4/n5559ZvHgxrVu3pqysjF69evHAAw8AkJqaSnJyMp6enkaf6dOn07ZtW9566y327t0LgKurK48//jje3t5MmTKFhQsX4uHhAcDevXtZt24ds2fPtotl7969zJ8/n8mTJ3PLLbcAcPjwYWbNmsXYsWOJiYkhKSmJH3/8EXd3dwAaNWrEP/7xD2OMxYsXU1BQwIIFC4yylStXsmnTJjw8PCgtLcXPz4/Ro0fj6+sLQHl5Oe+++y7bt2/HZDLh6+vLhAkTaNmyJW+99RatWrVi6NChACxYsICWLVsyefJkAN555x08PT256667anx/EREREUd1YWIMACcvKXNatrZ+ghERERG5Sr/bBJ+rqyuJiYl2ZT///DOdO3dm9uzZlJWVMXPmTMLCwggNDQUgIiKCCRMm2PXZvHkzeXl5JCYmYjabOXXqFI0aNbriePz8/EhLSzMSfFarlQ4dOti1iYuLIzw8vErfs2fPcvjwYSwWCzk5OXbJtaFDhxITc/EHalpaGvPnz2fJkiV4eHjw3nvvce7cOV566SXMZjNffPEFzz33HM8++ywhISFs2bKFoUOHUlFRQWFhIcXFxca46enpPPjgg6SlpV2T9xcRERFpKCqTe9WVK8knIiIijugPu0XX1dUVf39/Tp8+XWu7/Px8WrRogdl88VO1bNmSJk2aXPF8Xl5enD9/nvz8fGw2Gzt37uTGG2+sU99t27bRu3dvIiIisFqtNbaLiIigR48ebN68mdLSUlJTUxk3bpwR++DBg3FxcWHPnj2EhIRw4MABAI4dO0b79u1xc3OjqKiI8+fPc/z4cTp27HjN3l9ERERERERERK6P3+0KvrKyMuLj4wHw9vY2/q5UVFTEiRMnuOGGG4yytLQ09u/fbzwvWLCAfv368fe//519+/bRrVs3br75Zjp27Gi0mT9/vpH8KikpoV27djXGdNNNN7F161b8/f3p2LEjzs72nz85OZlVq1YB0L59e6ZNmwZcXO03YsQImjVrxvPPP09sbGyNc3Ts2JHjx4+TnZ2Nl5eXseW3UkBAAEePHqVbt244OTmRm5tLeno6wcHBnD59mgMHDuDu7k6HDh1wdna+7PtXSklJISUlBYBFixbh5eVVY4wiIiIi9elkLXX6DSMiIiKO6Heb4Ktuiy7Avn37mDFjBllZWQwbNozmzZsbddVt0W3ZsiUvvvgie/bsYc+ePTz99NP85S9/oVu3bgDMnTu3yhl8NYmIiOCFF17g+PHjREZGkp6ebldf3Rbd/Px8srOzCQ0NxWQy4eTkxJEjR+zOF7yUzWYz/q/JZKq2TWV5SEgI6enppKenEx0dbZfgCw4OrtP7V4qKiiIqKsp4zs3NrfE7iIiIiDRU+g0jIiIiDVXbtm1rrPvdJvhqUnkGX1ZWFn//+98JCwvD39+/1j4uLi7ceOON3HjjjTRr1oxvv/22SoKrLpo3b46zszO7du3ioYceqpLgq05aWhpFRUVMnToVgOLiYtLS0mpM8GVmZhIQEICPjw8///wz586dw83Nzag/fPgwvXv3BiA4OJj09HSOHj2Kn58fXl5efPLJJ7i5uTF48OBr/v4iIiIiIiIiInLt/WHP4Gvbti3Dhg3jo48+qrVdRkaGcU5fRUUFR44cuaqtGyNHjmTMmDHGtt7LsVqtPPnkkyQlJZGUlERCQkKN5/Bt3bqVnTt30r9/fywWCwMHDuTtt9+moqICgC+//JLS0lK6du0KQGhoKN9//z1NmjTBbDbTpEkTzp49y4EDB4wVfNf6/UVERETqW00XaeiCDREREXFUf7gVfJcaMmQI69atIycnB6h6Bt/DDz/MuXPnWLp0KeXl5QAEBgZyxx13/Oo5Q0JCaqy79Aw+gMcff5zc3FyCgoKMMm9vb9zd3Tl48CAA69ev5+uvv6a0tJT27dvbbRm+//77SU5OZvr06ZhMJtq2bcuMGTOMLbp+fn6cOXOG/v37G+P7+flRUlJijFFYWHhN319ERESkIahM5nl5eWlbroiIiDg8k63y0DaRaygrK6u+QxARERG5LCX4RERExFHUdgbfH3aLroiIiIiIiIiIyO+BEnwiIiIiIiIiIiIOTAk+ERERERERERERB6YEn4iIiIiIiIiIiANTgk9ERERERERERMSBOdd3AL9nb731Fq1atWLo0KEALFiwgJYtWzJ58mQA3nnnHTw9PenRowcrVqzg9OnT2Gw2BgwYwPDhwzGZTAB88803rFy5kvLycpycnBg1ahRhYWEAJCUl8eOPP+Lu7k5ZWRlBQUHcf//9eHp6AvD555+zfv16TCYTNpuN0aNH07dvX5KSkujduzfh4eHMmzePvLw8XFxcKC8vp1u3bowePZrGjRsDMGrUKPz8/Iz3ioyMZNiwYb/VZxQRERERERERkVoowXcdhYSEsGXLFoYOHUpFRQWFhYUUFxcb9enp6YwZM4bFixfz8MMP06NHD0pLS1myZAmffvopd9xxB5mZmSQnJ/O3v/0Nb29vcnJyeOaZZ2jdujUdOnQAIC4ujvDwcGw2G+vXr2f+/PksWbKEgoIC1qxZQ0JCAu7u7pSUlFBYWFhtrNOmTSMwMJDy8nLee+89Fi9ezPz58wFwdXUlMTHx+n8wERERkd/IhYkxAJy8pMxp2dr6CUZERETkKmmL7nUUEhLCgQMHADh27Bjt27fHzc2NoqIizp8/z/Hjxzl+/DghISH06NEDgEaNGjF+/Hg+/vhjANatW0dsbCze3t4AeHt7Exsby9q1VX+AmkwmoqOjad68OT/88AMFBQVYLBYsFgsAFovFGKcmzs7OjB07ltzcXDIzM6/VpxARERFpMCqTe3UtFxEREWnotILvOvL09MTJyYnc3FzS09MJDg7m9OnTHDhwAHd3dzp06EBWVhYBAQF2/Xx8fCgpKaG4uJhjx45x991329UHBATw6aef1jhvx44dOX78OL1796Z58+ZMmTKFbt26ERYWRp8+fS4bt9lsNmLz9/enrKyM+Ph4oz42NpaIiIgr/BoiIiIiIiIiInI9KMF3nYWEhJCenk56ejrR0dF2Cb7g4GDOnz9fY9/Kc/Mqz+KrK5vNBlxM1M2ZM4dDhw6xe/du3n77bTIyMhg5cuQVjVeXLbopKSmkpKQAsGjRIry8vK5oDhEREZHfysla6vQbRkRERByREnzXWXBwMOnp6Rw9ehQ/Pz+8vLz45JNPcHNzY/DgwRQUFLBv3z67PidPnsRiseDm5oavry+HDh0yztsDyMjIwNfXt8Y5MzMz6datG3AxSdipUyc6depE9+7dee211y6b4KuoqODIkSO0a9euzu8ZFRVFVFSU8Zybm1vnviIiIiINhX7DiIiISEPVtm3bGut0Bt91Fhoayvfff0+TJk0wm800adKEs2fPcuDAAYKDg7n55pvZv38/u3btAqCsrIw333yTmJiLZ8DExMTw0UcfkZOTA0BOTg5r1qypsm0XLq7c27BhA3l5efTs2ZPTp0+TkZFh1GdmZtKqVata4628ZKNly5Z2SUUREREREREREWmYtILvOvPz8+PMmTP079/frqykpAQPDw8AZs6cyYoVK1i+fDkVFRUMGDCAO+64AwB/f3/GjBlDQkICFy5cwMnJibFjx+Lv72+Ml5yczKpVqygtLSUoKIi5c+fi7OzMhQsXSE5OJi8vDxcXFzw8PJg4cWK1cb788su4uLhw/vx5unXrxsyZM426X57B17NnT8aMGXMtP5OIiIjIb8Zp2dpqL9TQLboiIiLiqEy2ygPbRK6hrKys+g5BRERE5LK8vLy0LVdEREQcgrboioiIiIiIiIiI/E4pwSciIiIiIiIiIuLAlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOzLm+A2goVq9ezebNmzGbzZhMJiZNmsRHH31ETk4OJSUlFBYW4u3tDcDDDz9MSEgI8fHxtGvXjscee4wvvviCDRs2AHDs2DHatm2L2WymZ8+etGvXjuTkZDw9PY35pk+fjqurK1OnTuWhhx7izjvvBGD58uUEBgYyaNAgu/hWrlyJxWIhJiaGAwcO8NZbb3H+/HnKy8vp168fI0eOJDU1lUOHDjFhwoQq73fhwgUmTZrErbfeyv3332+Uz5s3j5KSEhYtWgTAoUOHSE5OZt68eezdu5fFixfTunVrSktLad68OTExMfTu3fuafnsRERGR39qFiTEAnLykzGnZ2voJRkREROQqKcEHHDhwgO3bt5OQkICLiwuFhYWUl5cTHx8PwN69e1m3bh2zZ882+hw7doyKigr27dtHSUkJgwcPZvDgwQBMmTKFuXPn4uHhAUBqaioRERFVEm85OTk0a9aMDRs2cNttt+HsXLd/jqSkJB5//HH8/f2pqKggKyvrsn127txJ27Zt2bJlC3/6058wmUxGXUFBAT/88AM33nhjlX6dO3c23jszM5PExERcXV3p1q1bnWIVERERaWgqk3vVlSvJJyIiIo5IW3SBvLw8mjZtiouLCwAeHh52q+2qs3nzZgYMGECPHj347rvvfvXcHh4edOvWjdTU1Dr3KSwspEWLFgCYzWZ8fX0v28dqtXLnnXfi5eXFwYMH7epiYmJYvXr1Zcfw9/dn+PDhbNy4sc6xioiIiIiIiIjI9aUVfECPHj348MMPmT59Ot26dSMiIoIbbrih1j5btmzhqaeeIisri40bN9K/f/9a26elpbF//37jecGCBcbfw4YN49lnn+WWW26pU7xDhw7lscce44YbbqBnz54MHDgQV1fXGtuXlZWxZ88eJk2aRHFxMZs3byY4ONioDw4O5ptvvmHPnj24ubnVOndAQADr1q2rUp6SkkJKSgoAixYtwsvLq07vIiIiIvJbO1lLnX7DiIiIiCNSgg+wWCwkJCSwb98+9u7dywsvvMCYMWOqnINX6X//+x8eHh60atWKli1b8vrrr1NUVESTJk1qnKO6LbqVvL296dSpE5s3b65TvCNGjKB///7s2rWLzZs3Y7VamTdvXo3tt2/fTpcuXWjUqBE33XQTq1at4sEHH8Rs/r8FnMOHD2f16tWMGTOm1rltNlu15VFRUURFRRnPubm5dXoXERERkYZEv2FERESkoWrbtm2NdUrw/X/MZjNdunShS5cu+Pn5kZqaWmOCz2q1cvz4caZMmQLAuXPn2LZtG7feeuuvnj82Npbnn3+ezp0716m9j48PPj4+3HrrrTz88MOcOXOmxrZWq5X09HQj3jNnzrBnzx66d+9utOnatSsffPBBle27v3T48GHatWtXpxhFREREREREROT6U4IPyMrKwmQy0aZNG+DiZRKtWrWqtm1FRQVbt27lueeeM87p27NnD6tXr76qBF+7du1o164d27dvp1OnTrW2/f7777nxxhsxmUycOHECs9lM48aNq21bXFzM/v37ef31140zBr/44gusVqtdgg8uJhmXLVtG69atqx3rp59+YtWqVUyePPlXvKGIiIhIw+C0bG21F23ogg0RERFxVErwASUlJaxYsYKzZ8/i5OSEj48PkyZNqrbtvn378PT0tLuE44YbbuDll18mLy/PuPzil355Bt/DDz9cpe29997LrFmzLhvvV199xdtvv42rqytOTk48+uijxnbb1NRUvv32W6PtbbfdRteuXY3kHkDfvn159913OX/+vN24vXr1Mm7+vfR9Z86cSWlpKc2aNeOhhx7SDboiIiLi8CqTeV5eXtqWKyIiIg7PZKvpUDWRq5CVlVXfIYiIiIhclhJ8IiIi4ihqO4PPXGONiIiIiIiIiIiINHhK8ImIiIiIiIiIiDgwJfhEREREREREREQcmBJ8IiIiIiIiIiIiDkwJPhEREREREREREQfmXN8B1MXq1avZvHkzZrMZk8nEpEmTCAoKory8nHfffZft27djMpnw9fVlwoQJtGzZkpycHBISEliyZIkxzsqVK7FYLOTk5JCenk55eTk5OTnGLSTDhw9n+/bt9O7dm/DwcKNfXFwcycnJVeI6deoUy5cv59ixY9hsNnr16kVcXBzOzs68//77fP/990bbsrIysrOzefvtt7FYLHzzzTesXLmS8vJynJycGDVqFGFhYQAkJSWxa9cuXn31VVxcXCgsLOSvf/0rSUlJ5OTk8Pjjj9vdnBIdHc3AgQPtYps3bx55eXm4urpisVj485//bPRZvHgxBQUFLFiwwO7bbNq0CQ8PD8rLyxk+fDj9+/c34qn8JkVFRTz99NPceeedDB48+Ff/m4qIiIiIiIiIyLXR4BN8Bw4cYPv27SQkJBjJrvLycgDee+89zp07x0svvYTZbOaLL77gueee49lnn611zIcffhjASAImJiYaddu3b69TXDabjeeee44hQ4Ywc+ZMKioqWLp0Ke+//z5xcXH86U9/4k9/+pPR/uWXX6Zfv35YLBYyMzNJTk7mb3/7G97e3uTk5PDMM8/QunVrOnToAGC8z5AhQ6rM7ePjYxdzTaZNm0ZgYCApKSkkJycza9Yszp49y+HDh41Ep7e3t9F+6NChxMTEcOLECWbPnk14eDjOzv/3n0hxcTELFiwgKipKyT0RERFxaBcmxgBw8pIyp2Vr6ycYERERkavU4Lfo5uXl0bRpU1xcXADw8PDA09OT0tJSUlNTGTduHGbzxdcYPHgwLi4u7Nmz57rHtWfPHlxdXY1El9lsZty4cXzxxReUlpbatf3qq6/Izs7mvvvuA2DdunXExsYayTVvb29iY2NZu/b/flQOHTqU9evXc+HChauOtXPnzmRnZwOwbds2evfuTUREBFartdr2bdq0wdXVlbNnzxplJSUlPPvss0RGRlabdBQRERFxFJXJvbqWi4iIiDR0DT7B16NHD06dOsX06dN54403+PHHHwHIzs7Gy8sLd3d3u/YBAQEcPXr0quZMTk4mPj7e+F91jh49SseOHe3K3N3d8fLyMpJpcHGV4Hvvvce0adNwcnIC4NixYwQEBFSJ+9ixY8azl5cXISEhfPXVV1Xmzs7Ototv3759tb7P9u3b8fPzA8BqtRIZGUlkZGSNCb6MjAzatGlDs2bNjLK3336b0NBQoqOja51LRERERERERER+Ww1+i67FYiEhIYF9+/axd+9eXnjhBcaMGYO/vz8mk6naPiaTqda6y4mLi6tyBl9dx7LZbEZ5RUUFr7zyCqNGjcLHx6faNrW59957SUhIoFevXnbldd2i+/LLL+Pq6kqrVq0YP348+fn5ZGdnExoaislkwsnJiSNHjhjJv/Xr17Np0yZycnKYM2eO3Vhdu3bl22+/5e6777ZL/FVKSUkhJSUFgEWLFuHl5XXZ+ERERETqw8la6vQbRkRERBxRg0/wwcXtr126dKFLly74+fmRmppKeHg4P//8M+fOncPNzc1oe/jwYXr37k3Tpk0pKiqyG6eoqMjuzLmr4evry7Zt2+zKiouLOXXqFK1btwZg1apVtGjRosp5db6+vhw6dMg4bw8urprz9fW1a+fj44O/vz9btmz5VTFWnsFXacOGDRQVFTF16lQj3rS0NCPBV3kG37Zt23j11Vd55ZVXcHV1BSAyMpLQ0FAWLlzI3Llz7b45QFRUFFFRUcZzbm7ur4pZREREpD7pN4yIiIg0VJdeuPpLDX6LblZWFidOnDCeMzMzadWqFRaLhYEDB/L2229TUVEBwJdffklpaSldu3bFYrHQokULdu/eDVxM7u3cuZPQ0NBrEle3bt0oLS3lyy+/BC6u1nvnnXcYNGgQjRo14sCBA6SmpjJp0qQqfWNiYvjoo4/IyckBLm7jXbNmDXfffXeVtvfeey/r1q27JjFbrVaefPJJkpKSSEpKIiEhodptujfddBOBgYHGu1UaOnQoXbt25bnnnjMuOhERERERERERkfrV4FfwlZSUsGLFCs6ePYuTkxM+Pj5G0uz+++8nOTmZ6dOnYzKZaNu2LTNmzDC2v06dOpXly5fzzjvvADBixAi7rbJXw2QyMWPGDN544w1WrVqFzWbjxhtvNG7O/f/9//5/lJWVMX/+fLt+TzzxBP7+/owZM4aEhAQuXLiAk5MTY8eOxd/fv8o87du3p2PHjhw+fNgoqzyDr9LgwYO56667ao03JyeH3NxcgoKCjDJvb2/c3d05ePBglfYjRozgpZde4tZbb7UrHzt2LK+99hqvvPIK06dPNy44EREREXEUTsvWVnuhhm7RFREREUdlstlstvoOQn5/srKy6jsEERERkcvy8vLStlwRERFxCA69RVdERERERERERERqpgSfiIiIiIiIiIiIA1OCT0RERERERERExIEpwSciIiIiIiIiIuLAlOATERERERERERFxYErwiYiIiIiIiIiIODDn+g5ArkxcXBzJycnGc2pqKocOHWLChAkApKSk8MknnwDg5ubGuHHjCA0NBWDevHnExcURGBho9N+7dy/r1q1j9uzZdvNc2vbzzz9n/fr1mEwmbDYbo0ePpm/fvtf7VUVERESumwsTYwA4eUmZ07K19ROMiIiIyFVSgu93ZPv27Xz22Wc8/fTTeHh4kJGRQWJiIgsXLqR58+a/asxTp06xZs0aEhIScHd3p6SkhMLCwmsbuIiIiMhvqDK5V125knwiIiLiiLRF93fk448/Ji4uDg8PDwACAgIYOHAgGzdu/NVjFhQUYLFYsFgsAFgsFry9va9JvCIiIiIiIiIicvW0gs/BlJWVER8fbzwXFRXRp08fAI4ePUpAQIBd+8DAQL788stfPZ+/vz/NmzdnypQpdOvWjbCwMGO+S6WkpJCSkgLAokWL8PLy+tVzioiIiFxPJ2up028YERERcURK8DkYV1dXEhMTjefKM/hqYrPZrmo+s9nMnDlzOHToELt37+btt98mIyODkSNH2rWLiooiKirKeM7Nzb2qeUVERETqg37DiIiISEPVtm3bGuu0Rfd3xNfXl4yMDLuyw4cP4+vre1XjmkwmOnXqRGxsLI899hjbtm27qvFEREREREREROTaUYLvd+See+7h3//+N2fOnAEgMzOT1NRUbr/99l895unTp+2ShpmZmbRq1eqqYxURERGpLzVdpKELNkRERMRRaYvu70ifPn04ffo0Tz31FCaTCTc3Nx599FFatGhhtFm0aBFOTk4ABAcHc/vtt7N7924mT55stPnLX/5i/H3hwgWSk5PJy8vDxcUFDw8PJk6c+Nu9lIiIiMh1UJnM8/Ly0rZcERERcXgm29Ue0iZSjaysrPoOQUREROSylOATERERR6Ez+ERERERERERERH6nlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOzLm+A6irU6dOsXz5co4dO4bNZqNXr17ExcXh7Px/r7B48WIKCgpYsGCBUbZy5UosFgsxMTGUlZWRkJBAaGgo9913H3FxcSQnJ1c735tvvsnWrVt5/fXXMZsv5kFTU1N5/fXXWbx4MR06dADgiSeeYNasWXh7ezNlyhQsFgsAFRUV3HTTTQwfPhwXF5cq4+fn5/P2229z8OBBGjdujLOzM/fccw9hYWGXjSE5ORlPT0/Onz9PVFQU0dHRxrtu2rQJDw8PSktL8fPzY/To0fj6+gIwb9488vLycHV1BcDHx4cnnniClStXsnbtWpKSkmjWrBmA3bdZvXo1mzdvxmw2YzKZmDRpEkFBQVf6TygiIiIiIiIiIteBQyT4bDYbzz33HEOGDGHmzJlUVFSwdOlS3n//feLi4gA4e/Yshw8fxmKxkJOTg7e3t90Y5eXlLFmyhICAAO67775a56uoqOCbb77By8uLffv20aVLF6PO09OT1atX8/jjj1fbd+7cuXh4eFBSUsLSpUtZunQpU6dOrfI+iYmJDBw4kOnTpwPw888/891339UphoiICCZMmMCZM2d47LHHCA8Px8vLC4ChQ4cSExMDQFpaGvPnz2fJkiV4eHgAMG3aNAIDA6vE3bRpU9atW8fYsWPtyg8cOMD27dtJSEjAxcWFwsJCysvLa/1+IiIiIg3dhYkXfy+dvKTMadna+glGRERE5Co5xBbdPXv24OrqyuDBgwEwm82MGzeOL774gtLSUgC2bdtG7969iYiIwGq12vWvqKjgxRdfpE2bNowZM+ay8+3duxc/Pz9uu+22KmP17t2bY8eOkZWVVesYFouFiRMn8u2331JUVFTlfZydnRkyZIhR1qpVK+688846xVCpadOm+Pj4kJ+fX219REQEPXr0YPPmzbXGCjB48GC2bNlSJda8vDyaNm1qrEL08PDA09PzsuOJiIiINFSVyb26louIiIg0dA6R4Dt69CgdO3a0K3N3d8fLy4vs7GwArFYrkZGRREZGVkmIffzxx5jNZh588ME6zVc5VlhYGNu3b7dbsWYymYiJiWH16tWXHcfd3R1vb29OnDhx2fe5khgq5ebmUlZWhp+fX43jdOzYkePHjxvPL7/8MvHx8cTHx9ttT7ZYLAwePJgNGzbY9e/RowenTp1i+vTpvPHGG/z444+1xi0iIiIiIiIiIr8th9iiCxcTa79ks9kwmUzk5+eTnZ1NaGgoJpMJJycnjhw5YiS+QkNDOXjwIFlZWbRt27bWecrLy/nhhx8YN24cbm5uBAUFsWvXLnr16mW06d+/P6tXryYnJ+eavNsbb7xBeno6zs7OLFy48LIxpKWlsXfvXrKysnjkkUeMM/WqY7PZ7J5r2qILcOeddzJz5kzjTD+4mPhLSEhg37597N27lxdeeIExY8YwaNAgu74pKSmkpKQAsGjRImPLsIiIiEhDc7KWOv2GEREREUfkEAk+X19ftm3bZldWXFzMqVOnaN26NZs2baKoqMg46664uJi0tDQjwde5c2cGDhzIwoULmT9/fq1bTHfs2EFxcTEzZswAoLS0FFdXV7sEn5OTE3fffTcfffRRrXGfO3eOnJwc2rRpY1fevn17u/d5+OGHKSws5K9//WudYqg8g+/AgQMsXLiQG2+8kebNm1cbQ2ZmJgEBAbXGWalx48ZERkby3//+167cbDbTpUsXunTpgp+fH6mpqVUSfFFRUURFRRnPubm5dZpTREREpCHRbxgRERFpqGpbtOYQW3S7detGaWkpX375JXDxTL133nmHQYMG0ahRI6xWK08++SRJSUkkJSWRkJBQZZtueHg4d999N88++yxnz56tca7NmzfzyCOPGGO9+uqr7Nq1yzjrr9KgQYPYvXs3hYWF1Y5TUlLCG2+8Qd++fWnSpIldXdeuXTl//rxdIq2srOyKYwgODmbAgAFVttVW2rp1Kzt37qR///41vu8vRUdH89lnn1FRUQFAVlaW3RbjzMxMWrVqVefxRERERERERETk+nKIFXwmk4kZM2bwxhtvsGrVKmw2GzfeeCN/+tOfyMnJITc3l6CgIKO9t7c37u7uHDx40G6cIUOGkJ+fz+LFi3nyyScpKytj8uTJdvU7d+5k0qRJRpnFYiE0NJTt27fbjeXs7Mydd97JW2+9ZVc+f/584GISMiwsjOHDh1f7PvHx8bz99tt8/PHHeHh4YLFYGDNmDKWlpXWOAeCee+5h1qxZxMbGArB+/Xq+/vprSktLad++vXGrb6WXX37Z2NLr4eHB3/72N7vxPDw8CAsLY/369cDFROWKFSs4e/YsTk5O+Pj42MUmIiIi4miclq2t9kIN3aIrIiIijspk++UhbSLXwOVuGRYRERFpCLy8vLQtV0RERByCw2/RFRERERERERERkeopwSciIiIiIiIiIuLAlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOzLm+A/itxcXFkZycbDynpqZy6NAhJkyYAEBKSgqffPIJAG5ubowbN47Q0FC+/fZbvvjiC2bOnAnAmjVr+Pzzz3nllVcA+O6779i0aROzZs0CYPHixRQUFLBgwQJjrpUrV7Jp0yY8PDwoLy9n+PDh9O/fH4CkpCR+/PFH3N3dKSsrIygoiPvvvx9PT88q7zBv3jzy8vJwdXWlvLycoUOHEhUVBcCUKVOwWCyYzRdzt507d2b8+PEAXLhwgUmTJnHrrbdy//33G+OVlJTwzjvvsHv3blxcXGjatCljx44lKCjost9LRERExBFdmBgDwMlLypyWra2fYERERESu0h8uwVeb7du389lnn/H000/j4eFBRkYGiYmJLFy4kJCQEP71r38ZbQ8cOIC7uzsFBQU0a9aMAwcOEBISAsDZs2c5fPgwFouFnJwcvL29jX5Dhw4lJiaGEydOMHv2bMLDw3F2vvjPEBcXR3h4ODabjfXr1zN//nyWLFli1F9q2rRpBAYGUlRUxKOPPsqgQYOMdnPnzsXDw6NKn507d9K2bVu2bNnCn/70J0wmEwD//Oc/8fb25qWXXsJsNnPy5EmOHz9+7T6siIiISANSmdyrrlxJPhEREXFE2qJ7iY8//pi4uDgjORYQEMDAgQPZuHEjHh4euLu7k52dDcDp06e56aabSE9PByA9Pd1I8G3bto3evXsTERGB1Wqtdq42bdrg6urK2bNnq9SZTCaio6Np3rw5P/zwQ60xl5SU0KhRI2PFXm2sVit33nknXl5eHDx4EIDs7GwOHjzI6NGjjTFat25Nr169LjueiIiIiIiIiIjUvz/cCr6ysjLi4+ON56KiIvr06QPA0aNHCQgIsGsfGBjIl19+CUBwcDDp6elUVFTQpk0bgoKC2LlzJ7179+bIkSMEBgYCFxNpI0aMoFmzZjz//PPExsZWiSMjI4M2bdrQrFmzGmPt2LEjx48fp2/fvlXqXn75ZVxcXDhx4gQPPvigXYJv/vz5xvPAgQOJjo6mrKyMPXv2MGnSJIqLi9m8eTPBwcEcO3YMf3//GhOEtX2vS6WkpJCSkgLAokWL8PLyqvG9REREROrTyVrq9BtGREREHNEfLsHn6upKYmKi8Vx5plxNbDab8XdISIiR4AsODqZTp058+OGHHD58mLZt2+Lq6kp+fj7Z2dmEhoZiMplwcnLiyJEj+Pn5AbB+/Xo2bdpETk4Oc+bMqTXWS+f+pcotuoWFhTz11FP07NmTVq1aAdVv0d2+fTtdunShUaNG3HTTTaxatYoHH3yw1vmh7t8rKirKOAcQIDc397Jji4iIiDQ0+g0jIiIiDVXbtm1rrPvDJfhq4+vrS0ZGBl27djXKDh8+jK+vL3Axwbdx40YqKiqIiorCzc2N8+fP8+OPPxrbc9PS0igqKmLq1KkAFBcXk5aWZiT4Ks/g27ZtG6+++iqvvPIKrq6u1caTmZlJt27dao3Zw8ODjh07cvDgQSPBVx2r1Up6ejpTpkwB4MyZM+zZswdfX19++uknKioq6rTNV0REREREREREGhZldC5xzz338O9//5szZ84AFxNsqamp3H777cDFBGBeXh779+/H398fAH9/fz777DOCg4OBi4m0J598kqSkJJKSkkhISKj2HL6bbrrJbvvvpWw2Gxs2bCAvL4+ePXvWGnNpaSmZmZn4+PjU2Ka4uJj9+/fz2muvGXFNmDABq9WKj48PAQEBrFy50lgxeOLECb799tvLfi8RERERR1TTRRq6YENEREQclVbwXaJPnz6cPn2ap556CpPJhJubG48++igtWrQALl5+0alTJ4qLi40ba4ODg0lJSSEkJIScnBxyc3MJCgoyxvT29sbd3d241OJSI0aM4KWXXuLWW28FIDk5mVWrVlFaWkpQUBBz586t9gZduHgGn6urK+Xl5QwcONDu7MBLz+Dr0KEDXbt2pWvXrri4uBht+vbty7vvvsv58+eZPHky77zzDtOmTcPV1ZWmTZsyduzYq/yaIiIiIg1XZTLPy8tL23JFRETE4ZlstR30JvIrZWVl1XcIIiIiIpelBJ+IiIg4itrO4NMWXREREREREREREQemBJ+IiIiIiIiIiIgDU4JPRERERERERETEgSnBJyIiIiIiIiIi4sCU4BMREREREREREXFgSvCJiIiIiIiIiIg4MOf6DkDs5efn89Zbb3Ho0CGcnZ3x9vZm3LhxXLhwgRUrVnD69GlsNhsDBgxg+PDhmEwmUlNTSU5OxtPTk/PnzxMVFUV0dLQxZkpKCp988gkAbm5ujBs3jtDQUADmzZtHSUkJixYtAuDQoUMkJyczb948o/+bb77J1q1bef311zGblRMWERERx3dhYgwAJy8pc1q2tn6CEREREblKSvA1IDabjcTERAYOHMhjjz0GQGZmJgUFBbz22ms8/PDD9OjRg9LSUpYsWcKnn37KHXfcAUBERAQTJkzgzJkzPPbYY4SHh+Pl5cX27dv57LPPePrpp/Hw8CAjI4PExEQWLlxI8+bNASgoKOCHH37gxhtvrBJTRUUF33zzDV5eXuzbt48uXbr8Vp9DRERE5LqoTO5VV64kn4iIiDgiLcdqQPbu3YuzszNDhgwxyvz9/Tlx4gQhISH06NEDgEaNGjF+/Hg+/vjjKmM0bdoUHx8f8vPzAfj444+Ji4vDw8MDgICAAAYOHMjGjRuNPjExMaxevbrGmPz8/LjtttuwWq3X6lVFREREREREROQa0Qq+BuTIkSN07NixSvnRo0cJCAiwK/Px8aGkpITi4mK78tzcXMrKyvDz86uxb2BgIF9++aXxHBwczDfffMOePXtwc3Oza2u1WomMjKRPnz68//77lJeX4+xc9T+blJQUUlJSAFi0aBFeXl5X8OYiIiIiv52TtdTpN4yIiIg4IiX4HIDNZquxzmQyAZCWlsbevXvJysrikUcewdXV9YrGGz58OKtXr2bMmDFGWXl5OT/88APjxo3Dzc2NoKAgdu3aRa9evar0j4qKIioqynjOzc2t07uJiIiINCT6DSMiIiINVdu2bWusU4KvAWnfvj3btm2rtnzfvn12ZSdPnsRisRgr7irP4Dtw4AALFy7kxhtvpHnz5vj6+pKRkUHXrl2NvocPH8bX19duvK5du/LBBx9w8OBBo2zHjh0UFxczY8YMAEpLS3F1da02wSciIiIiIiIiIvVDZ/A1IF27duX8+fPGVleA//3vf7Rp04b9+/eza9cuAMrKynjzzTeJial6QHRwcDADBgxgw4YNANxzzz38+9//5syZM8DFSztSU1O5/fbbq/SNjY21O9dv8+bNPPLIIyQlJZGUlMSrr77Krl27KC0tvabvLSIiIvJbqukiDV2wISIiIo5KK/gaEJPJxIwZM3jrrbf4+OOPcXFxoVWrVjz44IPMnDmTFStWsHz5cioqKhgwYIBxg+4v3XPPPcyaNYvY2Fj69OnD6dOneeqppzCZTLi5ufHoo4/SokWLKv169eplXMZRWlrKzp07mTRpklFvsVgIDQ1l+/btREREXJ+PICIiIvIbqEzmeXl5aVuuiIiIODyTrbYD3kR+paysrPoOQUREROSylOATERERR1HbGXzaoisiIiIiIiIiIuLAlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOzLm+A/gjGjVqFH5+fsZzfHw8P//8M+vWrWP27NlGeWpqKocOHWLChAlG2bx584iLiyMwMJDPP/+c9evXYzKZsNlsjB49mr59+5KUlETv3r0JDw83+sXFxZGcnExOTg4JCQksWbKEvXv3Mn/+fGbOnEmfPn0AWLRoEXfffTddunThwoULfPDBB2zdupVGjRoB0K9fP+69997r/YlERERErqsLE2MAOHlJmdOytfUTjIiIiMhVUoKvHri6upKYmGhX9vPPP1/RGKdOnWLNmjUkJCTg7u5OSUkJhYWFVxxLy5YtWbNmjZHgu9R//vMf8vPzee6553B1deXcuXOsW7fuiucQERERaUgqk3vVlSvJJyIiIo5IW3QdVEFBARaLBYvFAoDFYsHb2/uKx+nQoQPu7u7s2rXLrry0tJRNmzYxfvx4XF1dAXBzc2PkyJFXH7yIiIiIiIiIiFwzWsFXD8rKyoiPjwfA29vb+PtK+Pv707x5c6ZMmUK3bt0ICwuzW4WXnJzMqlWr6jTWvffey3/+8x+6d+9ulGVnZ+Pl5YWbm1udxkhJSSElJQW4uM3Xy8vrCt5GRERE5LdzspY6/YYRERERR6QEXz2obovulTCZTJjNZubMmcOhQ4fYvXs3b7/9NhkZGcYKu7i4uCpn8NWkc+fOAOzbt6/GNl988QUbNmygqKiIZ555psqP36ioKKKioozn3NzcX/VuIiIiIvVJv2FERESkoWrbtm2Nddqi24A1bdqUs2fP2pUVFRXRtGlT4GKir1OnTsTGxvLYY4+xbdu2Xz3Xvffey+rVq41nHx8fcnNzOXfuHACDBw8mMTERd3d3KioqfvU8IiIiIiIiIiJybSnB14AFBgaSnp5Ofn4+AIcOHeL8+fO0bNmS06dPk5GRYbTNzMykVatWv3quHj16cPbsWX766ScAGjVqxC233MLy5cspKysDoKKigvLy8l//QiIiIiINQE0XaeiCDREREXFU2qLbgOzevZvJkycbz3/5y1948MEHWbhwIRUVFVgsFqZPn47ZbObChQskJyeTl5eHi4sLHh4eTJw48armv/fee1m8eLHxPHr0aD744AOeeOIJ3NzccHV1ZeDAgXh6el7VPCIiIiL1rTKZ5+XlpW25IiIi4vBMNpvNVt9ByO9PVlZWfYcgIiIicllK8ImIiIij0Bl8IiIiIiIiIiIiv1NK8ImIiIiIiIiIiDgwJfhEREREREREREQcmBJ8IiIiIiIiIiIiDkwJPhEREREREREREQemBJ+IiIiIiIiIiIgDc67vABzFqFGj8PPzM57j4+Px9vZm//79vP3225w7dw6A6OhooqKiAFi5ciWbNm3Cw8OD8vJyhg8fTv/+/QFISkrixx9/xN3dHYBGjRrxj3/8g/z8fP75z39y6tQpysvL8fb2ZsyYMbzyyisA5Obm4u7ujru7Ox4eHvztb3+zizMuLo7k5GTjOTU1lUOHDjFhwgRWrlyJxWIhJiaGpKQkevfuTXh4uNE2JyeHhIQElixZYjfmgQMHeOuttzh//jzl5eX069ePkSNHXqtPKyIiIvKbuzAxBoCTl5Q5LVtbP8GIiIiIXCUl+OrI1dWVxMREu7L8/Hxeeukl4uPjCQgIoLCwkAULFuDp6UmvXr0AGDp0KDExMZw4cYLZs2cTHh6Os/PFzx4XF2eXYIOLScHu3btz1113AfDTTz/h5+dnzF1dYu56S0pK4vHHH8ff35+KigqysrJ+s7lFRERErrXK5F515UryiYiIiCPSFt2rsHHjRgYNGkRAQAAAHh4ejB07lo8++qhK2zZt2uDq6srZs2drHTMvLw9PT0/juUOHDtc05l+jsLCQFi1aAGA2m/H19a3niEREREREREREpJJW8NVRWVkZ8fHxAHh7exMfH8+xY8cYOHCgXbvAwECOHj1apX9GRgZt2rShWbNmRllycjKrVq0CoH379kybNo3bb7+dF198kU8//ZRu3boxaNAgu4TflcQJUFRURJ8+fa7oXX9p6NChPPbYY9xwww307NmTgQMH4urqatcmJSWFlJQUABYtWoSXl9dVzSkiIiJyvZyspU6/YURERMQRKcFXR9Vt0bXZbJhMpiptLy1bv349mzZtIicnhzlz5ti1q26Lbs+ePXn11VfZsWMHP/zwA7NmzWLJkiV4eHj8qjgrz+C7GiNGjKB///7s2rWLzZs3Y7VamTdvnl2bqKgo4+xBuHhWoIiIiIij0W8YERERaajatm1bY5226F6F9u3bV0meZWRk2G1hHTp0KC+99BKPPfYYr776KmVlZZcdt0mTJvTv359HH32UwMBAfvzxx2se+5Xy8fFhyJAh/P3vf+enn37izJkz9R2SiIiIiIiIiIigBN9Vuf3220lNTSUzMxOAM2fO8O9//5uYmKoHN990000EBgby5Zdf1jrmnj17KC0tBeDcuXOcPHmy3reKfP/999hsNgBOnDiB2WymcePG9RqTiIiIyK9V00UaumBDREREHJW26F6FFi1a8Oijj7J06VLOnTuHzWZj6NChNZ55N2LECF566SVuvfVWwP4MPoCFCxeSkZHB8uXLcXJywmazccstt9CpU6frEv+//vUv3nrrLQBatmzJ9OnTycrKYvLkyUabcePGsW3bNt5++21cXV1xcnLi0UcfxWxWblhEREQcV2Uyz8vLS9tyRURExOGZbJVLs0SuoaysrPoOQUREROSylOATERERR6Ez+ERERERERERERH6nlOATERERERERERFxYErwiYiIiIiIiIiIODAl+ERERERERERERByYEnwiIiIiIiIiIiIOzLm+A6hPo0aNws/Pj4qKClq1asWjjz5K48aNycnJISEhgSVLlgDwv//9j+TkZPLz8zGZTISGhvLQQw+xZcsWDh06xIQJE4wx582bR1xcHIGBgUyZMoWWLVvy9NNPG/Xx8fFUVFQYY+/fv5+3336bc+fOARAdHU1UVBQAK1euZO3atSQlJdGsWTMA4uLiSE5Otov/woULODk5MXDgQO666y7MZvu87S/fp3Jsi8VCTEwMSUlJ9O7dm/DwcLv4K+3du5d169Yxe/bsa/btRUREROrThYkxAJy8pMxp2dr6CUZERETkKv2hE3yurq4kJiYC8Oqrr/Lpp59y77332rXJz8/n+eef57HHHiM4OBibzca2bduMhNzlnDt3jtzcXLy8vDh27FiVsV966SXi4+MJCAigsLCQBQsW4OnpSa9evQBo2rQp69atY+zYsbXGX1BQwMsvv0xxcTEjR4684m8hIiIi8kdRmdyrrlxJPhEREXFE2qL7/wkODub06dNVyj/99FMGDhxIcHAwACaTifDwcJo3b16ncfv160daWhoAVquVyMhIo27jxo0MGjSIgIAAADw8PBg7diwfffSR0Wbw4MFs2bKFoqKiWudp1qwZkyZNYuPGjdhstjrFJiIiIiIiIiIiju8PvYKvUkVFBXv27OGWW26pUnf06FEGDhxYY9+0tDT2799vPGdnZ9vVh4eH89prrxETE8P27duZNm0aX3/9NQDHjh2rMnZgYCBHjx41ni0WC4MHD2bDhg2XXZnXunVrbDYbBQUFVRKQ2dnZxMfHG8/5+fncfffdtY53JVJSUkhJSQFg0aJFeHl5XbOxRURERK6lk7XU6TeMiIiIOKI/dIKvrKyM+Ph4fv75ZwICAujevfsVjxEREVHlDL5LNWnShMaNG2O1WmnXrh2urq5Gnc1mw2QyVRnzl2V33nknM2fOJDo6+rLx1LR6z8fHx9jOCxfP4LuWoqKijLMDAXJzc6/p+CIiIiK/Bf2GERERkYaqbdu2Ndb9obfoVp5h99prr1FeXs7GjRurtPH19SUjI+Oq5omIiGD58uV223MB2rdvz6FDh+zKMjIy8PX1tStr3LgxkZGR/Pe//611npMnT2I2m40LOURERERERERE5PfvD53gq+Tu7s5DDz3EunXrKC8vt6u74447+PLLLzl48KBR9tVXX5Gfn1/n8cPCwoiJieH/396dx0VZ7///f86wiIjgMhIhIIsilpSZue9haqKpmVZKLpVZiqWJ9mk52WIuZKWJ5te0PNjys5OZplnS0YzBpTgpae64EyIqogIizPz+8MZ1nEA0N5jO4367fW4f5329r/f1uobzx9yevZcmTZo4tHft2lVr167V/v37JUmnT5/WJ598ol69Sm/8HB0drdWrV8tms5X5jNzcXM2bN0/dunUrc1YgAAAALrjUQRocsAEAAJzV//QS3YuFhISoXr16SklJUUREhNFeo0YNPffcc0pMTNSpU6dkNpvVqFEjtWjR4orHrlq1qnr37l2qvWbNmoqNjdXcuXOVn58vu92uHj16qFmzZqX6ent7q3nz5lqxYoXRVrLEuLi4WC4uLmrXrt0VLeO9nClTpsjFxUXShcNHunbtqt9++00jRoww+owdO9Y4eAQAAMDZlIR5FouFZbkAAMDpmewcuYobICMjo6JLAAAAuCwCPgAA4CzYgw8AAAAAAAD4myLgAwAAAAAAAJwYAR8AAAAAAADgxAj4AAAAAAAAACdGwAcAAAAAAAA4MQI+AAAAAAAAwIm5VnQB/yv69++v6OhoPfbYY5KkZcuWqaCgQP3799fixYv1ww8/yNvb2+g/ceJEvfbaa3rmmWcUHBys4uJiDRkyRE8++aTat28vSZowYYKeeuophYaGSpJOnTqlF198UZMmTVKNGjUkSR9++KEsFouio6O1aNEipaamymQyKSAgQI8//rhq164tSRowYICCgoJks9lUp04dxcbGqlq1asrKytLUqVM1ffp0SVJSUpJWr16tV155RV5eXjfr6wMAALiuip/sJUk6elGby7xlFVMMAADANWIG303i5uamjRs3Kjc3t8zrPXr0UHx8vPF/1apVU3h4uHbu3ClJOnDggPz9/bVr1y5JUkFBgbKyshQcHGyM4ePjowceeED//Oc/JUnp6enasWOHoqOj9emnnyo/P18zZszQzJkzdc899+jtt9+W3W6XJLm7uys+Pl7Tp0+Xl5eXvvvuu1I1rlu3TqtWrdJLL71EuAcAAJxWSbh3pe0AAACVHQHfTWI2mxUVFaUVK1Zc8T0RERFGwLdz50516dJF+/fvlyTt2bNHISEhMpsd/4RRUVE6evSotm7dqgULFmjYsGEqLi7W2rVrNXjwYKN/p06d5Obmpq1bt5Z6bnh4uE6cOOHQlpKSoqVLl+rll192mGkIAAAAAACAisUS3Zuoa9euiouL0wMPPFDq2ooVK/TTTz9Jkry8vPTqq68qPDxcn3/+uaQLAd9DDz0kq9Wq/Px87dq1Sw0bNiw1jtls1pNPPqnXXntNzZo102233aYDBw7IYrHI09PToW9oaKgOHTqkyMhIo81ms2nr1q3q3Lmz0Xbs2DEtWLBA06ZNM5b+/llSUpKSkpIkSVOmTJHFYvlrXw4AAMBNcrSca/yGAQAAzoiA7yby9PRU+/bttXLlSrm7uztc69Gjh3r1clwW4uvrq6KiIuXk5CgjI0P+/v4KCwvT7t27tXPnTnXv3r3M5wQHBysoKEhdu3aVJNntdplMpjL7lrQXFhYqLi5Ox44dU2hoqO644w6jj7e3t7y8vJSSkqLo6Ogyx4mKilJUVJTxOTs7+zLfBgAAQOXDbxgAAFBZ+fv7X/IaS3Rvsh49emj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      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 15))\n",
    "plt.scatter(grp_data['Complaint Type'],grp_data['City'])\n",
    "plt.title('Plot showing list of cities that raised complaint of type Blocked Driveway')\n",
    "plt.xlabel('Complaint')\n",
    "plt.ylabel('City')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4026a5ec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}