PricePredictionModel-RandomForest.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ML Modeling for Housing Price Prediction using Random Forest Regressors\n",
    "\n",
    "#### Author: (EJ) Vivek Pandey\n",
    "\n",
    "Note: The data engineering and eda notebooks need to be run before running this, since it expects certain outputs generated by those notebooks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependency imports\n",
    "import re\n",
    "import csv\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "sns.set()\n",
    "\n",
    "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn import metrics\n",
    "\n",
    "# Notebook customizations\n",
    "from IPython.display import display\n",
    "pd.options.display.max_columns = None\n",
    "pd.options.display.max_colwidth = -1\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def heatMap(df, mirror):\n",
    "\n",
    "   # Create Correlation df\n",
    "   corr = df.corr()\n",
    "   # Plot figsize\n",
    "   fig, ax = plt.subplots(figsize=(15, 6))\n",
    "   # Generate Color Map\n",
    "   colormap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "   \n",
    "   if mirror == True:\n",
    "      #Generate Heat Map, allow annotations and place floats in map\n",
    "      sns.heatmap(corr, cmap=colormap, annot=True, fmt=\".2f\")\n",
    "      #Apply xticks\n",
    "      plt.xticks(range(len(corr.columns)), corr.columns);\n",
    "      #Apply yticks\n",
    "      plt.yticks(range(len(corr.columns)), corr.columns)\n",
    "      #show plot\n",
    "\n",
    "   else:\n",
    "      # Drop self-correlations\n",
    "      dropSelf = np.zeros_like(corr)\n",
    "      dropSelf[np.triu_indices_from(dropSelf)] = True\n",
    "      # Generate Color Map\n",
    "      colormap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "      # Generate Heat Map, allow annotations and place floats in map\n",
    "      sns.heatmap(corr, cmap=colormap, annot=True, fmt=\".2f\", mask=dropSelf)\n",
    "      # Apply xticks\n",
    "      plt.xticks(range(len(corr.columns)), corr.columns);\n",
    "      # Apply yticks\n",
    "      plt.yticks(range(len(corr.columns)), corr.columns)\n",
    "   # show plot\n",
    "   plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>document_type</th>\n",
       "      <th>price</th>\n",
       "      <th>property_url</th>\n",
       "      <th>transaction_type</th>\n",
       "      <th>recording_year</th>\n",
       "      <th>recording_month</th>\n",
       "      <th>recording_day</th>\n",
       "      <th>contract_year</th>\n",
       "      <th>contract_month</th>\n",
       "      <th>contract_day</th>\n",
       "      <th>address</th>\n",
       "      <th>area_sqft</th>\n",
       "      <th>built_year</th>\n",
       "      <th>city</th>\n",
       "      <th>lot_size</th>\n",
       "      <th>no_of_baths</th>\n",
       "      <th>no_of_bedrooms</th>\n",
       "      <th>property_type</th>\n",
       "      <th>state</th>\n",
       "      <th>tax_amount</th>\n",
       "      <th>tax_year</th>\n",
       "      <th>zip_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Deed</td>\n",
       "      <td>224000.0</td>\n",
       "      <td>https://www.trulia.com/p/ny/holmes/10-cliff-ct-holmes-ny-12531--2305202587</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>2001</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>10 Cliff Ct</td>\n",
       "      <td>1184.0</td>\n",
       "      <td>1997</td>\n",
       "      <td>Holmes</td>\n",
       "      <td>60984.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NY</td>\n",
       "      <td>8320.40</td>\n",
       "      <td>2017</td>\n",
       "      <td>12531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>REO Resale</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>https://www.trulia.com/p/ny/craryville/52-two-town-rd-craryville-ny-12521--2011547915</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>52 Two Town Rd</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>1992</td>\n",
       "      <td>Craryville</td>\n",
       "      <td>39639.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NY</td>\n",
       "      <td>3074.64</td>\n",
       "      <td>2017</td>\n",
       "      <td>12521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>REO Repossession</td>\n",
       "      <td>137337.0</td>\n",
       "      <td>https://www.trulia.com/p/ny/craryville/52-two-town-rd-craryville-ny-12521--2011547915</td>\n",
       "      <td>REO and Trustee Deed</td>\n",
       "      <td>2015</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>2015</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>52 Two Town Rd</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>1992</td>\n",
       "      <td>Craryville</td>\n",
       "      <td>39639.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NY</td>\n",
       "      <td>3074.64</td>\n",
       "      <td>2017</td>\n",
       "      <td>12521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deed</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>https://www.trulia.com/p/ny/craryville/48-van-de-carr-rd-craryville-ny-12521--2158446804</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>1996</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>1996</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>48 Van De Carr Rd</td>\n",
       "      <td>961.0</td>\n",
       "      <td>1951</td>\n",
       "      <td>Craryville</td>\n",
       "      <td>20908.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NY</td>\n",
       "      <td>2701.22</td>\n",
       "      <td>2017</td>\n",
       "      <td>12521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>REO Resale</td>\n",
       "      <td>99900.0</td>\n",
       "      <td>https://www.trulia.com/p/ny/craryville/20-van-de-carr-rd-craryville-ny-12521--2011547529</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>20 Van De Carr Rd</td>\n",
       "      <td>1236.0</td>\n",
       "      <td>1957</td>\n",
       "      <td>Craryville</td>\n",
       "      <td>14810.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NY</td>\n",
       "      <td>3879.47</td>\n",
       "      <td>2017</td>\n",
       "      <td>12521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      document_type     price  \\\n",
       "0  Deed              224000.0   \n",
       "1  REO Resale        55000.0    \n",
       "2  REO Repossession  137337.0   \n",
       "3  Deed              50000.0    \n",
       "4  REO Resale        99900.0    \n",
       "\n",
       "                                                                               property_url  \\\n",
       "0  https://www.trulia.com/p/ny/holmes/10-cliff-ct-holmes-ny-12531--2305202587                 \n",
       "1  https://www.trulia.com/p/ny/craryville/52-two-town-rd-craryville-ny-12521--2011547915      \n",
       "2  https://www.trulia.com/p/ny/craryville/52-two-town-rd-craryville-ny-12521--2011547915      \n",
       "3  https://www.trulia.com/p/ny/craryville/48-van-de-carr-rd-craryville-ny-12521--2158446804   \n",
       "4  https://www.trulia.com/p/ny/craryville/20-van-de-carr-rd-craryville-ny-12521--2011547529   \n",
       "\n",
       "                                       transaction_type  recording_year  \\\n",
       "0  Purchase/Resale Arm's Length Residential Transaction  2001             \n",
       "1  Purchase/Resale Arm's Length Residential Transaction  2017             \n",
       "2  REO and Trustee Deed                                  2015             \n",
       "3  Purchase/Resale Arm's Length Residential Transaction  1996             \n",
       "4  Purchase/Resale Arm's Length Residential Transaction  2010             \n",
       "\n",
       "   recording_month  recording_day  contract_year  contract_month  \\\n",
       "0  7                30             2001           6                \n",
       "1  5                24             2017           5                \n",
       "2  11               20             2015           10               \n",
       "3  7                30             1996           7                \n",
       "4  12               20             2010           12               \n",
       "\n",
       "   contract_day            address  area_sqft  built_year        city  \\\n",
       "0  25            10 Cliff Ct        1184.0     1997        Holmes       \n",
       "1  10            52 Two Town Rd     1350.0     1992        Craryville   \n",
       "2  6             52 Two Town Rd     1350.0     1992        Craryville   \n",
       "3  9             48 Van De Carr Rd  961.0      1951        Craryville   \n",
       "4  15            20 Van De Carr Rd  1236.0     1957        Craryville   \n",
       "\n",
       "   lot_size  no_of_baths  no_of_bedrooms       property_type state  \\\n",
       "0  60984.0   2.5          3.0             Single-Family Home  NY     \n",
       "1  39639.6   1.5          2.0             Single-Family Home  NY     \n",
       "2  39639.6   1.5          2.0             Single-Family Home  NY     \n",
       "3  20908.8   1.0          2.0             Single-Family Home  NY     \n",
       "4  14810.4   2.0          2.0             Single-Family Home  NY     \n",
       "\n",
       "   tax_amount  tax_year zip_code  \n",
       "0  8320.40     2017      12531    \n",
       "1  3074.64     2017      12521    \n",
       "2  3074.64     2017      12521    \n",
       "3  2701.22     2017      12521    \n",
       "4  3879.47     2017      12521    "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions_master_df = pd.read_csv('./output/post_eda_transactions_master.csv', sep='|', \\\n",
    "                                     dtype={'zip_code': str}, encoding='latin1')\n",
    "transactions_master_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 788150 entries, 0 to 788149\n",
      "Data columns (total 22 columns):\n",
      "document_type       788150 non-null object\n",
      "price               788150 non-null float64\n",
      "property_url        788150 non-null object\n",
      "transaction_type    788150 non-null object\n",
      "recording_year      788150 non-null int64\n",
      "recording_month     788150 non-null int64\n",
      "recording_day       788150 non-null int64\n",
      "contract_year       788150 non-null int64\n",
      "contract_month      788150 non-null int64\n",
      "contract_day        788150 non-null int64\n",
      "address             788150 non-null object\n",
      "area_sqft           788150 non-null float64\n",
      "built_year          788150 non-null int64\n",
      "city                788150 non-null object\n",
      "lot_size            788150 non-null float64\n",
      "no_of_baths         788150 non-null float64\n",
      "no_of_bedrooms      788150 non-null float64\n",
      "property_type       788150 non-null object\n",
      "state               788150 non-null object\n",
      "tax_amount          788150 non-null float64\n",
      "tax_year            788150 non-null int64\n",
      "zip_code            788150 non-null object\n",
      "dtypes: float64(6), int64(8), object(8)\n",
      "memory usage: 132.3+ MB\n"
     ]
    }
   ],
   "source": [
    "transactions_master_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a48c01358>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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Mf4SegT661aspTSXMysjEurstLovcyUhL58C6ih8oCsUj9mzlcfnyZTw8PDh06BCpqan89ttv3Lt3Dz8/P77//ntFubS0NL744gt8fX3Zv38/TZo04eeffyYoKAiAn3/+mV27dnH06FEuXrxYUdWp9LK3hMnzPZ6Vlf+6CDp6ukxf6YOZZX02zs/+Api4ZD5h2wJ5cOuOuqMqaGhoIJfnz5yZ61oOxSlTENcJEwgNCQHg4sWL/HHpEl1sVX98naSY+YpbLrfk5GTGj5/A5MmTCA0NwXmgM6dPnyZNDceCSDQkBXWfQvuP2ypfzBrUJ2Bedv9xXeJJ6LZAosux/+Smqr7UokULgoKD2bpli9LpalVNnX3/tYmurkx3c2Pcp5+q9fgbSaHrnqx8j904forlHw7g1w1bGLVhORKJhEu7DxLis5b0l6949fwFp7cG06x7+R0LK9HQQF5AfnkB+f85foqVHzpzYsMWhm/wAYkETS1NGnZsy54vFvPdMFf0jAz4aOon5REdKHs/ea1pi+ZsCvyJ4B+38fux46qK91YSiQYUkD93+zcf4og8M5Mbv4TlK1fRClu3Z2Xm7z8F2R8YzKpFS3j18iXJz58T+N0PdO3dS9UxC1bIZ5fc631NLfRad+b50T3EeIwm6VAQpu6rQUub2hPnkxQWSPqDilnv56WhUXBfKmhdFHHsJHNs7Tm4/lumbPw639TU/6zMzLLdKpgYbOXRrl07GjVqhEQioX///pw9e5ZatWpRr57ynOqbN29iampKs2bZW0VmzpzJqFGjOHPmDMeOHaN///4MHjyYuLg4bt68WRFVqRL+jY2jpomJ4r6xqQnJic9IfflKqVwtc1O8dnxHVlYWXmMmkvI8GWPTOrzX1gbZmBH47NnO4KkTadrWhjkb1XtMXUxMDKampor7ZmZmJCYm8vLlyxKVycvA0JBJeY+3kUjIyFDNfOMZbjMICTlISMhBhg0bWqx8pamHRCIh5UUKw4YNx85OxsIFC2nYsBFROdNVVOnfmDhq1qmtuF9Y/6ltbsaSn74nKzOTRWMmKPpP0/dtcBgzAr+fdzB06kSatbXhSzX3n9wexsRQJ1f7mhbQvm8r4+DoyI/bt7Pc15f1/v5qzauuvg8glUpZvWYN/fr1w9nJSW0nVHntWWw8BiZv+o5BHRNSniWRnqvvGNe3oIFNC8X9P34OpYa5KbqGBlg79MK0cSPFcxIJZKros1ocSbEJGJjUUtx/PUUwd/6a9S2olyv/nz8fwsjcFD1DA54/eszNoydJe5FCVkYG1w4coW6r8tu7GxcTQ23TN3u7TcxMeZaYyKu39JPcejnYs3brD/gvX8EP6zeoI2ahnsclUC1X+1evU5tXz5LIyNX+7/XvTZ3mTRgcuAHZOm80daQMDtygtFxFiX8YQ+1csw1qm5qSVIL27zOgH+80baK4L5FIyMwon5OrZPwbh2bNN78btIxNyEx+hjz1TdtnPn1E+sN7pN6+DmRPI5RoaKLzbnN037PBUDYCC5/t1Bw8Ed2mNpjOqbhj8Z/ExmGUa11Uo05tXjxLIi1XXzKpX5d3bKwV98/8fBBjCzOqGRqUa1ahdMRgKw9NTU3F/+VyOZqamujq6uYrp62trbRF4fnz58TFxZGZmcmsWbPYu3cve/fuJTAwkEGDBpVL9qoo4tRZ3m3VAjPL+gD0HDqQi8d+UyqjW60anls2cj78OGtmziU9Z2v3k/gEJn1oh7uzC+7OLgSv3cCNS5fxnaDeY+pOnjiBjY2N4uD9ES4uhB8+XOIyeb1ITmbU6NH0tcuee/6/5s1p1aoVv/36q0pyr/x6JTKZPTKZPU4DnGmdK5+LywjCD4fnW+bkiZPFKpebXC7n+x++o2XL7OMDHRzsSU1NVcuP5z9PnaVxq5aK/tN72CAu5O0/1aux8MeNnAs/xqqZc0nL1X8mdO3LLKcRzHIaQeDaDfx96TLL1Nx/cvs9Tz9xcXHhSJ5+UlSZ7j164LlwIWNGjmTf3r1qz6uuvg+wctUq9A0MGOjszMMHD1QdPZ87Zy5Sz7oZxg2yj3FrN9iRm8dPKZXRN6nFoOWeVKthCIC1fU8Sbkfy8lkSpu82pNvkj5FoaKClI6X9MCeuh5XfnpW7Zy5iYf0/aubkbzPYkX+On86X32n5PPRy8rew78GjnPw3wk/QrM9HaOlkn7imSffOxF4rvw2D507+Tgub1tS3sgTAecRwToQfLfbyXXp0Z+aC+Xw++mPC9u1XV8xCPThzCVPrZhjltH/zwQ5E/npGqcwel6kEDhxP8NCJhEzxIDM1jeChE0nJOf64Ip3//RTNbVpRL6f9B7gM4+SR4u8Vb/ReYz6d/jkaGhpIdXQYOMqFowdC1RVXycuIs+i+2wIts+z1vkHPgaRcVF7vv7xyGq06FkgbNgVAt6kNyOWk3fmL6El2xLi7EOPuwtPgDby6cZl434o7Fv/v0+exatUckwbZG/W7DHUi4thJpTKGJrX52G8R1WsYAdDOoTcxt+/+vzluS56ZUaZbRRPHbOVx6dIl4uPjMTEx4ZdffqFr167cuHEjX7mGDRvy+PFjbt++zbvvvss332TPne3YsSNBQUF069aNtLQ0RowYwaJFi+jQoUN5V6VKSHrylA0eXsxY5YuWtjbx0Q/wd19Ao+bNGL94Hu7OLvRxGYKJhTnten5Eu54fKZZd8skkkhOflXvmx48fM2vWLNYHBKAtlRIVFcXMGTNo2bIlPr6+2MtkhZYpSlZWFuM/+4yFXl5MnzGDzIwMpk6Zojg1tjrqEBCwPvuU6VFRuM3IPhNVy5Yt8fX1QSazL7JcUaZ9Ph0f32Voa2uTkJDA+HHj37pMaSQ9ecr6uYuYuXq5ov+sm+NJoxbNcF08n1lOI+jrMhQTC3M69OxGh57dFMsu+ti1QvpPbo8fP2b2rFn45/ST+7n60jJfXxxy+lJBZQDmenggkUhY5uureM1Lly6xYL56jl1RV9+3adMGmb09d+/cYdfuN8c8+fr4cOLECbXU5cWTRH6Zv5yhXy1CU1uLJ9Ex/OyxDIv/NaHfwllsGDKO+39c5eTmbYz9bhVZGZk8f/QvP02fB8CvG7Yg+3Iak3Z/i6aWFtfDf+PS7oNqyVqQlCeJHJi/nIFfLUBTW4un0bHs8/DB/H9NsF84k2+GTCD6j6uc2rydkd99jTwjk+ePHhM83ROAS4H70DMy4JOdG9DQ1CDu71uErCi/vUNPHz9h8Sx3fNavzT7dddR9Fs6cRbOWLfDwWcpI+/wny8ht2tw5SCQSPHyWKh7789Il/DwXqTs6AC+fJHLccwW9V8xHU1ubZw9iOOaxHJP/NeGjBW4EDy2/MyOWRuLjJyydPZcl/qvR0tbm4f1olsycw3stW+C+bDEfOzgVufx3q/1xWzSfLaH70NLW4nhIGPsDg8sle1bSUx5t8KLODF8kWtpkxD/gkf8CpI2aUXv8PGLcXch89piEFV9Q61N3NHT0kKenEf/1LOTpaeWSsSSSnySybd5SPlu5BC1tbR5FP+THLxfToHlTXBa5s2zQWO788Sdhm7cw/ft1ZGVm8izhXzZ9/mVFRxeKSSIvaNLu/1Pnzp1j4cKF1KlTh/j4eDp37syYMWMYO3as4jiIPXv2KE6Q8frf9PR0GjRowPLly5FKpfj6+nL27FkyMjJwdnZm/PgS/NC8Xj4HV6tF84EMa/Z+RacotZ1/X6ShpWVFxyiVe1HZU/SsLBtWcJLSiYy6B8Dgpm0rOEnpBN+4BECjKtp/7kZFVdm+D9n9f4F1t7cXrKQWRRzH2zr/meyqAo+I7L1R7Rs2ruAkpXP+3i0AAlqV0/FGKub6Z/ZMgy6NmlZwktL5/e4N7g2rur8bGu68yOQWnd9esJLyv3bq7YUqgcwzZTtbsGanij1NvtizlUft2rXZsmWL0mO5Dzh3dnbG2dkZgPbt27Nnz558rzFv3jz1hhQEQRAEQRCE/w8qwVTAshDHbAmCIAiCIAiCIKiB2LOVS4cOHcSxVYIgCIIgCIJQScizxJ4tQRAEQRAEQRAEIQ+xZ0sQBEEQBEEQhMqpElyYuCzEni1BEARBEARBEAQ1EHu2BEEQBEEQBEGolCrDhYnLQlxnSxAEQRAEQRCESin9yIoyLa/d8wsVJSkdsWerkqnqFwWu6hdltrJqVNEpSiUy8i4AVpZWFRuklCKjIrP/U1X7T/OBQNW+qLSVZdXs+wCRUXdF/goSGfV63VPF84t1f4WIjIrEyurdio5RapGRt6t8fkH9xGBLEARBEARBEITKqYpPIxQnyBAEQRAEQRAEQVADsWdLEARBEARBEIRKSZ4lTv0uCIIgCIIgCIIg5CEGW4IgCIIgCIIgCGogBlv/ATYfdsb3l5/4OmQ301f6oFe9er4yXRzt8P15Bz57tuO141saNW+Wr8zoL92YHbCyPCKXmFwuZ86aYL795WRFR1Ho1q0boaEhHD16BH//dejr65eonIGBAevX+xMWFkp4eBgTJ07It+zgwYP55pvNqsnbvRuhh0I5euwo/uv9C89bSDkNDQ08PT05evQov/72Ky4uLopljIyMWLV6FQdDDnL06FGcnJwUz7333nvs3LmTgyEH2bd/Hy1atFBJfUqisvWfsr4Xr5mbm3P23Blq1qypeCz7vVjJwZADHD16ROm9UG3+EI4eO4L/+iL6fiHldHR0WO7nS9jhUA6HH2K5ny86OjpKyxoaGnLi5K/YyeyqVH4dHR0WeS3kYMh+jh0/yvgJ46pU/jp16vDjjz8QGnqQQ2GhDHDqX2WyN23alF27gwgNPcjBkP189NGHKs0O6l3vW1tbs2tXECEhBzh0KJQBA1TT9upc979Wr349rvx5hZYtWyoeGzN2DEePHSUkJIQ1a9ZgZGRU9rp0+4jQ0AMcPXoYf/+1RbT/28tt2ODPokULFPffe68J16//SUjIPsWtUSPVnmG2quevKPLMjDLdKlqVHGzt2bMHd3d3AMaNG0d8fHwFJ6o4BjVrMNF7ASunzcZNNpCEBw8ZPnOKUhlzK0tcZk1j2fipuDu7sGfDd7it8VMq07FvT7o4qP5HjSrceZDAmAXfEnbmWkVHUTA2NsbPzxdX10n06NGT6Oho5syZXaJybm4ziIuLo08fO/r1G8DIkS60aWMDZP9g9vZewoIF85FIJCrK64frRFd6dO9B9P1o5rjPKVG5ES4jaNioIb1796afYz8++eQTWrVqBcCKr1YQFxuHvcweFxcXFi5aiJmZGbq6umzdtpUNGzdgL7Nn7Zq1rF69usz1KYnK1n+y23h5rja+zxz3wvpO4eWcnZ0JCg7EzMxMabk374UDLi4jWbhoQb4yZc/vi+vESfTo3jOnjxTR9wsoN2XqZDQ1NenbR0bfPjJ0dXSZNNlVafmvvl6BgYGBynKXV373L+dQo0YNHB3607/fAEaPGoWNTesqk3/27C+4fOUKdnb2jBk9liVLFmNiUrtKZF+56ms2bdyMnZ09M6bPZJ3/WrS1tVWSXSmXmtb7AQHrWblyNTKZA2PHfsy8eR5YWVmpILP61v2QPQBetWqVUlt36tSJiRMn4jLCBZlMxvHjx1nms0wFdfHF1XUyPXr0Jjr6PnPmzCpVuQkTxtGuXTulx9q2bcPevfuRyfopbnfv3itT5v9SfqH0quRgK7fNmzdjampa0TEqjHXnjty59hdxUdEAhP+0K9+gKSMtjU3zF5P46DEAd6/9RY3atdDUzj4/ikUjKxw/Hc3u9d+Ub/hi2h56lsE936fvBy3fXric2NraEhFxlcjISAC2bdtG//75t0IWVW7RIi+8vZcC2VuTpVIpSUnPAXBwsCc+Pp6lS8v25aTI0dWWiIiIt+ctolyfPn0IDgomMzOTpKQk9u/fzwCnARgZGWFra8uqVasAiIuLY0D/ASQmJtK1a1eioqL49fivAISHhzN58mSV1Km4Klv/UcV7UadOHXr36cXoUWOUlsl+L7qwalX2gDb7vXAiMTFRxfmL0feLKHf+3HnWrfVHLpeTlZXF9evXqVe3rmLZqZ9P4ebNm9y8cVNlucsrv7OzE19/tZKsrCyeP3/OsOEjuHPnTpXJr6GpiWHOIFdPT4/MzEyysuRVIruDvSNTV0aJAAAgAElEQVSHD4cDYGnZgKSkJDIzVXdgvTrX+zo6UlavXsOpU6eA7M/ukydPMDcv24YSda77X/Na7MWu4F08ffJU8ViLli049fsp4uLiADh06BA9evQo0+DX1rZLTsaonIw76N+/X4nLdezYgQ8/7Mr27TuUlmvbtg3vvvsOBw7s5ZdfdtOnT+9SZ/0v5q9QmRllu1UwlZyN8Ny5c/j5+ZGVlUXdunWpVq0at27dIjMzk3HjxuHg4EBqaiqLFi3i0qVLaGtrM2nSJGQyGVeuXMHb25vU1FRq1qyJl5cXlpaWjBo1CiMjI27dusWqVau4efMmAQEB6OvrK/4GQPfu3fnxxx85f/48J0+e5NmzZ0RHR9O5c2cWLlwIwFdffUVYWBg1a9bExMSE7t274+zsXGBdgoODOXv2LF999RUAa9euRUdHBxcXF7y8vPLVKzk5mblz5xIfH09CQgKdOnXC29ub8+fPK9qkcePG+Pr6qqKp86llZsrj2Dd79h7HJ1DNQB+96tV5+eIFAI9iYnkUE6soM2rODC4dP0FmegY61fSY7OtFwNxFvFPA1MLKwHNc9krm1J+V5+J7FhbmxMa+adPY2DgMDQ3Q19cnOTm52OUyMzNZufJrZDI7wsIOc/du9gUqX69EBw0aqJq85hbExuTOEYuhoWH+vEWUszC3UK5LXCxNmzXFysqKhIQEPhv3GR999BFSqZTNmzZz7949GjZsyKNHj/Bd7kuzZs1ISkpi2TLVDCCLq7L1Hwtz8zxtHFfIe1F4uYSEBCZOUN4TBOR5Lz5Uei/Um7+Avl9EuZMnf1c8XreuBZ98+jFfunsA0KVLFzp06MDoUWPYsWObynKXR/5atWpRvXp1unTpjK/vMgwNDQkO3sX33/9QJfIDLPf1I3hXIDJ7GcbGxngvWcrjx4+rRPbXA6vfThynXr16LFrkRVZWlkqyg3rX+1lZWQQFBSmWGT58GNWr6/PHH5fLllmN636AocOGoqWlxc6dO5ky5c2smiuXrzB27Fjq1q3Lw4cPGTxkMDo6OtSoWYNHCY9KVxcVtH+1atVYsGAeo0d/govLcKXXT0l5yb59B9ix4ycaNmxIYOAOYmJiuHpVNbMiqnp+ofRUtmcrMjKSLVu2YGlpSfPmzdmzZw/bt29nw4YNREdHs3XrVlJSUggNDeX777/H39+ftLQ03NzcmD9/Pvv27WPYsGG4ubkpXvO9994jLCwMY2NjVqxYwfbt2wkMDORFziAir8uXL7NmzRr27dvH8ePHuXnzJseOHePSpUscOHCATZs28ddffxVZD5lMxpkzZxQd/8CBA/Tv35+AgIAC6/Xrr7/SrFkzAgMDCQsL48KFC1y/fl2pTdQ10ILsudSQf6tjVgGnydTR02X6Sh/MLOuzcf5iACYumU/YtkAe3FLdltf/DyQSDeTy/O2edytqccrNmOGGjU1batQwYtq0z1UfFpBoSIqXt4hyeZ+TICEzMxMtbS0aNGhA8vNkBg0cxNQpU5nvOZ8WLVqgpa1Ft27d+GnHT/Rz7MeWH7bww/c/IJVKVV/JKkKiUcy+U8xyuSm/F4OZOuVzxXuhKqrM36JFC4KCg9iyZSvHjh3DwsKCefM9mDF9hkp/JJc0V3HL5c2vpaWFlpYWDSwbMHy4C6NHj8Vl5Ah69+5VJfIDrF69ko0bNtGhfSd69ezDRNcJtGplXSWyv/Zh1258+GE3XF0n0umDTirJDuW33nd1nciMGdP57LPPSE1NLVtmNa77m7dojouLCx5zPfItd+HCBVavXs3GTRvZt38fWVlZPH36lPS09NLXpYztL5HA2rWr8PLy5tGj/AO++fMXsG3bdrKysrhz5w4HDhykZ88epc77X8svlJ7KrrPVsGFDDAwMOH36NK9evWL37t0ApKSkcOvWLS5cuMCQIUPQ0NDAxMSEgwcP8s8//2BoaIi1dfaK3M7ODk9PT54/z55K9frxy5cvY2NjQ+3a2fPGHR0dOXv2bL4MNjY2ioMI69evz7Nnzzh9+jR2dnZIpVKkUik9e/Yssh7Vq1fnww8/JDw8nPr161O/fn1MTU0LrZeDgwMRERH88MMP3L17l8TERFJSUpTaRJ3+jY3jXes3P6SMTU1ITnxG6stXSuVqmZsye/1KHt6NxGvMRNJTUzE2rcN7bW0wt7JENmYE+kZGVDPQZ87G1fhOmKbW3FXRjBnT6dUru//o6+tz8+abKU5mZqYkJiby8uVLpWViYh5iY9OqwHJdu9py48ZNEhISSElJYd++/fTt21d1ed1m0Ktn9o88fQN9pSlZZmZmheSNwaa1TYHlYmJilKbsmpqaEhcbpzhmMjg4GICoqCguXLhA69atSYhP4Pbt21y5cgXInkbo4+tD/Qb1uXP7/88AP/u9yOk7JXovWr+1XG4FvxcXad26FdeulX7r5gy36UXkL6Lvty647wM4OjqweIkXnp4L2bd3HwAyezv09HTZsuUHACytLJk71x3jmjXzTZmpjPmfPHlCWloae3b/jFwu599//+Xo0WO0adNGMb2tMuevWbMm77d7nxEjRgLZGwx/P/k77Tu0588/Iyp1dm1tbfr27cOBAweRy+U8iH7Aqd9P0bz5/zhz+kypskP5rvelUikrVvjRuPG7ODsP5MGDh6XLXE7r/oHOA9HX12fPnj0A1DGtw6rVq1i2dBlnzpzh3NlzBAUGKZaZOXNmiac0z5gxjV69sgcM2e3/T66MhbV/TIHt37hxY+rXr8/8+XMBMDExQUNDEx0dHebOnYer6wR++OFHxQZ9iURCenrpB4f/hfyVhbjOVg5dXV0AsrKy8PPzY+/evezdu5egoCBsbW3R0tJSOtA/KiqqwC2XcrlcMcp//ZoSifJWFS2tgseIuc9m9XoZDQ2NEm8hHThwIAcOHGD//v2K6YaF1Wvr1q0sX74cY2NjRo4cyTvvvKPI+jq/OkWcOsu7rVpgZlkfgJ5DB3Lx2G9KZXSrVcNzy0bOhx9nzcy5pOdsKXsSn8CkD+1wd3bB3dmF4LUbuHHpshhoFWLlylXIZA7IZA44OQ2kdWsbxcHLLi4uhIcfybfMyZO/F1rO3t6e6dOzt2hKpVLs7e05c6b0Pwry5f16JTKZDJlMhtMAJ1rbtFbOUcCPv5MnThZaLjw8nMFDBqOpqYmhoSGO/Rw5fPgwD6IfcPXqVQbmTHmsXbs2bdu2JSIigl9//ZX69esr9qy0b99e8UPo/5Ps98IemcwepwHOtLbJ3SdGFPFevL1cbgW/F22IiLhaxvy5+v6AgXlyuRB+uIC+f+L3Qsv16NGdBQs9GTVyjOLHMsA3m7/lw67dFH/rasRVli71KdNAqzzzp6enc/ToMQYOyv7eqFatGrZduvBnROkGKuWd/+nTp8TGxiHLOQNkzZo1ad+hPVcu/1nps6enpzPzCzcc+zkC2cdDdezUiXNnz5c6O5Tven/lyq/R19fH2XlQqQdaUH7rfi8vL7p36674WwnxCUyfNp0jR45gamrKzsCdig3gU6ZOYd++ffn+7lvrsnK14mQPTk6DaN26NVZWljkZRxTS/icLLPfHH5f54ANbxett3/4TBw4cxN19LllZWfTq1YPhw4cB2VNU7ez6EBoaVuLM/6X8gmqobM/Wax07duSnn35iyZIlJCQkMGDAAHbu3Em7du0ICQmhW7duPHnyhJEjRxISEkJiYiIRERFYW1sTEhKChYUFNWrUUHrNtm3bsnjxYuLj4zExMSEkJARDQ8Ni5fnggw/YvHkzw4cPJy0tTTHtryjvv/8+cXFxPHz4EA8PjyLrderUKYYOHYqjoyNXr17lxo0bZGVl5UzvU7+kJ0/Z4OHFjFW+aGlrEx/9AH/3BTRq3ozxi+fh7uxCH5chmFiY067nR7Tr+ZFi2SWfTCI58Vm55Pyvefz4MbNmzSYgwB9tbW2iou7j5jYTgJYtW+LruwyZzKHIct7e3nh7LyEsLBSAsLDDfPfd92rMO4uAgAC0pdpERUXhNsMtV15fZDJZkeW2bd2GZQNLQg+Foq2tzY4dOzh37hwAE8ZPwGuxFyNHjkRDQ4M1q9cQkfMDc/y48SxZsgS9anqkpaUxccLEMk+NqcretPH6XG2cu+/4IJPZF1muKBPGT8x5L1zyvReqy5/Tp6U5fXrGW/p+nnJzPeYikUjw9X1z/N7FS5fwnL+gwL+pSurO7z7nSxYs9CT8SBgaGprs27uP0JDQKpN/3GfjWLhoIVM/n0JWlpz1/gFcuHChSmSfMN4Vr8WLmDhhPFnyLJYtXcbVq2Xb0FBofhWv99u0scHeXsadO3fZvTtY8Td9fHw5caL0l6xQ97q/MHfv3iUgIIBf9v6CRCLh4sWLeM73LHU9suvyhFmz5hAQsC5Xu87KqUsLfH2XIpP1K7JcUaZNm4m3txeDBjmjqamJl9cSlZ7cpqrnF0pPIi9oYmgJnTt3jnXr1rF161aSk5NZuHAhN27cIDMzk/Hjx+Pk5ERaWhpLlizh8uXsgz2nTp1K7969uXz5MkuXLuXly5cYGRnh5eXFO++8w6hRo5gyZQodOnQAss9ks3r1avT09Hj33XfR0NDAx8dH6QQZ58+fx8fHB0Bp+ZUrV3LkyBGMjIzQ0NBgxIgRyGSyIuu0atUqEhMTFSfZKKxeZ86cYeHChUilUvT19dHV1UUmk9GgQQNFm5TEsGbvl7D1K4+df1+E67srOkbpNR+IlVWjik5RKpGR2SfWsLK0qtggpRQZFZn9n6raf5pn70mysqya1zSJjLqHlWXV7PsAkVF3Rf4KEhn1et1TxfOLdX+FiIyKxMrq3YqOUWqRkberfP6q4NWu/JdYKAndQctVlKR0VLJnq0OHDopBkb6+PitWrMhXRiqV4uXlle9xGxsbxfEFueUdpPTt27fA41leHxhbr149pTMMvl7+8uXLWFlZcfDgQdLT0xk6dCiNGhW+UpXL5aSnp3PhwgXmzp2reLywenXq1ImwsIJ3075uE0EQBEEQBEEQSq4yXJi4LFQ+jbCyadiwIevWreP7779HLpczYMAArKysCrzOBMDYsWNZunQpgwcPpnnz5uWcVhAEQRAEQRCE/4r//GCrRo0afPvtt/ke37t3b6HLODk5qTOSIAiCIAiCIAjFUcX3bJXPWRwEQRAEQRAEQRD+nxGDLUEQBEEQBEEQBDX4z08jFARBEARBEAShahIXNRYEQRAEQRAEQRDyUcl1tgRBEARBEARBEFQtZdvkMi1fbaS/ipKUjphGWMk0tLSs6Aildi8qqspeGBJyLg4pLqpbISKj7gFVP/+TeR9WcJLSMV7yW5W9KCrkXBi1Cq87I6Oiquy6/15UFFB1v7te56+q/SdSkd+qYoOU0n/hs1vV81cJ4myEgiAIgiAIgiAIQl5iz5YgCIIgCIIgCJWSPFOcIEMQBEEQBEEQBEHIQwy2BEEQBEEQBEEQ1EBMIxQEQRAEQRAEoVKSixNkCBWhW/fuhB46xNFjx/Bfvx59ff0SlzE3N+fMuXPUrFlT8ViPHj24/OefHAwJUdyqV6+unjp060ZoaAhHjx7B339dgXUoqpyBgQHr1/sTFhZKeHgYEydOyLfs4MGD+eabzWrJXxJyuZw5a4L59peTFR0FgG7duxF6KJSjx47iv96/8LZ/Szlzc3POnjuj1IeMjIxYtXolB0MOcPToEZycnNRal+LkfFs5HR0dlvv5Enb4EIfDw1ju54uOjo7acwNoN+mI4ZTvMJq2Ff1hi0CnmtLz0tZ9MJz8jeJmNHMnNRcdRVI9u81rfLlX6Xlpq55qyVnWNtbQ0MDT05OjR4/y62+/4uLiAsC7jd8lJCREcTsUdojIqEj69O0DwGfjPuNw+GFCQ0PZtn0bDRo0UEFd3r7+LKqccl1+U9Qlt8FDhvDNt9+WS9aics739OTI0aMc/+03RuTK2bFTJ/YfPEjooUPs2LmTZs2aKZ5zmzmTw0eOcPjIEVZ89RW6urplrocq6vNaQd9dr9WrX5/Lf/5Jy5YtVZZZFdnLs8/kz6Sezy5kf36DdwUTEhLCwZCDdO3aVfHciBEjsj+7h0LZvHlzge/X27Orp82tra3ZtXt3zjonjAG5vqcGODkRGhpKSEgIu/fsKVNfKo91Tb369blSSJ/v3bs3165fL3V+QTUq3WBrz549uLu7AzBu3Dji4+MrONHbRURE4OfnByjnVxdjY2OW+/nhOnEiPbp35/79+8zO8zffVsbZ2ZnA4GDMzMyUlmvTti2bN23CXiZT3F68eKGWOvj5+eLqOokePXoSHR3NnDmzS1TOzW0GcXFx9OljR79+Axg50oU2bWyA7B/83t5LWLBgPhKJROX5S+LOgwTGLPiWsDPXKjTHa9ltuhzXia706N6D6Pv3meNeWNsXXs7Z2Zmg4MB8fWjFVyuIi43DXuaAi8tIFi5akK9MZavPlKlT0NTUom8fO/r2sUNXR5dJkyepLfNrkmpGVHd2J/mn+TxbPYrMJzFU66280SDtShhJ/p9l3wImIH/+hJQDq5C/eIpG7frIXz5/87z/Z6T9eUTlObPbzi9X20Uzx31OicqNcBlBw0YN6d27N/0c+/HJJ5/QqlUrbt+6jUwmU9xOnjzJ3r17CTsURufOnRk6dCjOTs7Y2dlx6NAh/Fb4qagu2evG7H6Qf51dVLkRLi40bNQopy6OirrA63WPNwsWLCjzuqes6/rXOfv07k3/XDkNDAzYsHEjy5Yuxa5vX+Z5eLDO3x+pVEqfvn3p2rUr9nZ29O7ZEz09PT7+5JMy1UNV9YHCv7sApDo6rFy1Cm1tbZXkzZvrbf2mMvSZwnOr/rMLsGTxEoKCgpDJZMyeNZt1/uvQ1NSkXv16fDHrC4YMHoJdXzsePHjADLcZpcyu+jYP2LCBlV9/jUwmY+yYMcybNw8rKysaNWrE3LlzGT1mDDKZjLVr17Jh48YSt3tx85elDpC9oXBVIX3eysqKuR4eFf4bSCWyMsp2q2CVbrCV2+bNmzE1Na3oGG91+/ZtHj9+XG5/z7ZrVyIiIoiMjARg27Zt9O/fv9hl6tSpQ68+fRgzalS+127bti2dPviAkNBQgoKDad++vXrqYGtLRMTVIuvwtnKLFnnh7b1UUSepVEpS0nMAHBzsiY+PZ+nSZWrJXxLbQ88yuOf79P1A9VtaS8O2q+1b+8/bytWpU4fefXoxetQYpWWMjIywte3CqlWrAYiLi2NAfycSExMrdX3OnzvPurXrkMvlZGVlcf36X9SrW1dtmV/TbtyOjIc3yHr8EIDU83uL3DOl23UEWS+eknphPwBaDVpAVhYGn63FcMp36HYbAxLVr9ZV0cZ9+vQhOCiYzMxMkpKS2L9/PwOcBigt365dO+zs7PCY6wHAo0ePmOcxj+TkZACuRlylbhnfl+KsP99WLrsuQXnqkr1l3MHBIXvd4+1dppzFzfq2nLsKyGllZcXzpCROnzoFwN07d3ienIxNmzaEHTrEoIEDSU9PR19fn1q1apH49GmZ66KK+hT13QXgtXgxu4ODefrkiUryqjJ7efWZ/LnV+9nV0NTAyMgIgOrVq5OamgqApoYmWlpa6OvrI5FI0NXTVTxX/OzqaXMdHR1Wr17NqZz+HxcXx5MnTzA3NyctLY05c+bwKCEBgKsREZiYmJRqAK/udQ1k9/ldBfR5XV1dVq1axZLFi0ucW1C9tx6zde7cOfz8/MjKyqJu3bpUq1aNW7dukZmZybhx43BwcCA1NZVFixZx6dIltLW1mTRpEjKZjCtXruDt7U1qaio1a9bEy8sLS0tLRo0ahZGREbdu3WLVqlXcvHmTgIAA9PX1FX8DoHv37vz444+cP3+ekydP8uzZM6Kjo+ncuTMLFy4E4KuvviIsLIyaNWtiYmJC9+7dcXZ2LrQ+nTt3pkePHkRERFC7dm0GDhzI1q1biYuLw8fHh/bt23Pv3j08PT1JTEykWrVqeHh4YG1tjbu7O/r6+ly/fp34+HgmT55Mr169WLNmDSkpKQQEBGBqakpUVBSjRo0iJiaGTp06sWTJEtW8WznMzc2JjYlR3I+LjcXQ0BB9fX3Fj5KiyiQkJOA6If+UO4CniYns27uX0JAQ3n//fTZ98w2yvn2Ji4tTaR0sLMyJjY1V3I+NjcPQ0ECpDsUpl5mZycqVXyOT2REWdpi7d+8CsH37DgAGDRqo0tyl4TmuHwCn/rxdwUmyWZibExuTt00N87d9EeUSEhKYOME132tbWVmRkJDAZ+M+46OPPkQqlbJ502bu3btXqetz8uSb6Z1169blk08/5kv3uWrL/JqGUR2yniUo7mclPUJDVz97KmFqilJZSTUjdDsPJWn9uDePaWiSfucSKYc3ItHUQn+UD/JXL0g9s0ulOS3MLfK0Xf51ztvKWZhbKH+W42Jp2qyp0t+ZO3cuK1asULzmP//8o3hOKpUyx30OISEhZayL8rqx8LoUXs7CPM96KS6OpjnT8LZv3w7AoEGDypQTyr6uNzc3JyZXzricnPfu3UOvWjVsbW05efIk1tbWNGnShDp16gCQkZHB6DFjmDlzJnHx8YSFhZW5LqqoT1HfXUOHDUNbS4udO3cyecoUleTNrTj9pjL0mfy51fvZ9ZzvyY6fdvDpp59Sq1Ytpk6dSmZmJlFRUWzatImjx46SlJTE8+fPcXYq/LdZwdnV0+apqakEBQYqHh8+fDjVq1fnjz/+IDU1lQcPHiiemzd/PkeOHCE9Pb1E2Yubv7R1gOw+r5XT56fk6fNLly1j+44d3Lhxo8S5BdUr1ibQyMhItmzZgqWlJc2bN2fPnj1s376dDRs2EB0dzdatW0lJSSE0NJTvv/8ef39/0tLScHNzY/78+ezbt49hw4bh5uameM333nuPsLAwjI2NWbFiBdu3bycwMLDQKWuXL19mzZo17Nu3j+PHj3Pz5k2OHTvGpUuXOHDgAJs2beKvv/56a13+/fdfunbtyi+//EJqaipHjhxhx44dTJ06lS1btgAwa9YsRo0axf79+/nyyy+ZNm0aaWlpQPaX1Y4dOwgICGD58uUYGhry+eef0717d1xds398xsbGsnbtWkJDQzlx4gS3bt0qTjMXm4aGBnK5PN/jmbmuQ1CcMgVxnTCB0JwfMxcvXuSPS5foYmtbxsT5SSTFy1eccjNmuGFj05YaNYyYNu1zlWf9r5EUs28Ut1xuWtpaNGjQgOTnyQwaOJipUz5nvud8WrRoUfbghVBlfVq0aEFQcCBbtvzIsWPHVB82L4kG5I8EWVn5HtJp50j637+T9fTNF2/qxQOkHFwN6a+Qv0rm1akgpP9Tw+dVQ1LMNi68XN7nJEiUlm/Ttg3GtYzZ+8vefMsbGxuzdetWXrx4gd/ysk0jVEV/yfucpIDlVaGs63oNDQ3IkzMrM5Pk5GQmjB/PpMmTCQkNxXngQE6fPq30g/LHLVtoZW3N4bAw1gcEVIr6FKZ5ixaMcHHBY676NpAUp99Uhj6Tlzo/uzo6OqzzX8cXM7+gU8dODB0ylKVLl2Jubo6trS12dnZ80OkD2rdrT3h4OCu+WlHC7Opvc1dXV2a4ufHZp58q7XnT09PDf/16rCwtcZ+Tf9qlqvKXtg7NW7TApZA+P3LUKDIzMggOCipV7spInplZpltFK9bZCBs2bIiBgQGnT5/m1atX7N69G4CUlBRu3brFhQsXGDJkCBoaGpiYmHDw4EH++ecfDA0Nsba2BsDOzg5PT0+eP8+e5vX68cuXL2NjY0Pt2rUBcHR05OzZs/ky2NjYKA4YrF+/Ps+ePeP06dPY2dkhlUqRSqX07Fm8A8NfH8BZt25d2rZtC4CFhQVJSUm8ePGC+/fv07t3bwBat26NkZGRYo9J586dkUgkNGnSpNCpUe+//z41atQAoEGDBjxV0RSM12JiYmjdurXivpmZGYmJibx8+bJEZfIyMDRk1KhRrPf3f/OgREJGhmrmu86YMZ1evbLfI319fW7evJkrn2mB+WJiHmJj06rAcl272nLjxk0SEhJISUlh37799O3bVyVZ/2tmuM2gV87nQ99An5s3crd9wX0jJiYGmxL2odfHWAYHBwMQFRXFhQsXad26Fdeuqe6YNXXUx9HRgcVLFuPpuYB9e/epLGtRshLj0ar35sQEGoa1yUpJgvRX+cpKW3Qj5eAa5cda9yYz9jaZ8dnrJyQSlc1Pz27jXkBJ29imwHIxMTFK08JNTU2Ji32zx9zRwZE9u/fk+9HRtGlTvvnmG8LCwvD29iargIHo2+vilqu/GHAz19be0vSXgusSi6qVdV3/MCaGOrly1jE1JTY2FolEQsqLFwwfNkzx3LHjx4mKjKRZs2ZINDT4K+eg+p07dzL2448rRX0K4+zsjIG+Prv37FHUc9Xq1SxbupQjR1RzDGNx1oeVoc9A+X12mzRpgq6urmLD1OXLl7n1zy1a27SmY8eOHAk/ojjEYuuPWwk7XLI9pOpsc6lUyooVK2jcuDHOTk5Ke7MsLCz49ttvuX37NsOGDSvR9MfyWtcMdHZGX1+fPQX0+UGDBqGnp0dISAjaUim6urqEhIQwduxYEhISqJLKccC0f/9+AgICyMjIYMyYMflOSnL9+nU8PT1JT0/H3NwcPz8/DA0Ni3zNYu3Zen0moqysLPz8/Ni7dy979+4lKCgIW1tbtLS0lA7Ai4qKKvALUS6XK0b0r19TIlHeYqKlVfD4L/eZwV4vo6GhUaovXqlUqvi/pqZmvoxF5X6do6gDDnPXIW/9VOHkiRPY2NhgZWUFZB9AGX74cInL5PUiOZlRo0fT184OgP81b06rVq347ddfVZJ75cpVyGQOyGQOODkNpHXrN/lcXFwID8//pXjy5O+FlrO3t2f69Ow9WVKpFHt7e86cOaOSrP81K79eiUxmj0xmj9MAZ1rb5G7TEYQfDs+3zMkTJ4tVLrcH0Q+4evUqA3Omb9auXZu2bS/rrB0AACAASURBVNsQEXG1UtenR48eLFi4gFEjR5fbQAsg/fYFtOr/D41a2cch6bTrR/qNU/nKSXT10axVl4z7ygNWzToN0evxSfYeMi0puh2dSLt6XCXZsts4+6QVTgOcaG3TWvlzWGgbF1wuPDycwUMGo6mpiaGhIY79HDmca53UoUMHxTEUr5mZmbHjpx2sXrOaxYsXl2p9n12Xr3PVZUCeflDwuvHkiROFlsuuy5BcdemnVBdVKeu6/kh4OENychrk5Aw/fBi5XM53P/ygOHuZfc7hAH///TdNmzbFz89P8R3t7OzMmdOnK0V9CrPYy4vu3bopTuqUEB/P9GnTVDbQep3rbf2mMvQZKL/PblRUFIYGhrRp2wbI3rj8buN3uX7tOteuXaNb926Kw0L62vXl8uXLJaqHOtt85apV6BsY4OzsrDTQql69OjsDAzl06BBTp04t8XFm5bWu8crp86//Vu4+P6B/f/r07o1MJuPjsWN59epVdpmqOtAqR/Hx8axcuZIdO3bwyy+/EBgYyO3byoeAeHt78/nnn7Nv3z4aNmzIt8U4g2iJrrPVsWNHfvrpJ5YsWUJCQgIDBgxg586dtGvXjpCQELp168aTJ08YOXIkISEhJCYmEhERgbW1NSEhIVhYWCj2+LzWtm1bFi9eTHx8PCYmJoSEhLx1hPjaBx98wObNmxk+fDhpaWn8+uuvSqevLQ19fX3q1avH4cOH6d27N1euXOHff/+lcePGhS6jqampsr0/xfH48WNmzZrF+oAAtKVSoqKimDljBi1btsTH1xd7mazQMkXJyspi/GefsdDLi+kzZpCZkcHUKVNUvmfuTR1mExDgj7a2NlFR93FzmwlAy5Yt8fVdhkzmUGQ5b29vvL2XEBYWCkBY2GG+++57lWf9r3ndNwIC1qMt1SYqKgq3Gbnb3geZzL7IckWZMH4iXou9GDnSBQ0NDdasXkNERESlrs9cj7lIJBJ8fX0Ur3vx0iU853uqLTeA/EUiL/b4oD/MC4mmNplPHvJi91I0Ld6jutMskvw/A0CjVj2ynj+GLOWtey+P/0B1h+kYTf0eNLRIu/4rqRcPqDznm7YLyNV22dPCs9vYF1mu9U5B5bZt3YZlA0tCD4X+H3tnHlZF+f7hG2RxQchUEE3BLa1QUXOrHxSgIAdRQMsFt1RQ3NHMNVQUBDUBBXH5lrmmoKYou5hpLrikuZQbAuIClIhLGijw++PAkcMmHM4RqPe+rnNdMPPMzOd555l35pl3GTQ1NdmxYwfx8fGyYxi3NJZ76AGYOnUqdevW5YvRX/DFaGnrSnZ2Ng4O8hNrKO6LVr5G99f4Im+3betWjFq0IDIqqkRflEVl6/ptW7fSokULIvJ1/lBI5/SpU1nm64umpibp6em4ukjHAv74448YGRsTdvAgOS9fcv36dWZ/VXx2z6rwpyopLR6qW8yUrVv51+748eNZuHAh2tra5OTkMG/uPG7fvs3t27d55513OHDwANnZ2dy9e5cvZ35ZCe3KK/MuXbpgZ2dHQkKCrKcWgI+PDyYmJjRr1gwbGxtsbGxk64YNG1bhiZ5qUl0jkHLixAl69uwpy1VsbGyIioqSGxOXm5srG/L0/Plz2QQxZaGW95pml/j4eAIDA9m6dStPnz5l0aJFXL16lZycHFxdXXF0dCQ7O5ulS5fK3lpMmTIFa2trzp8/j7e3t0yMp6cnrVu3ZsSIEUyePJkePXoAEBUVRUBAAHXq1KFNmzaoq6vj4+MjN0HG6dOn8fGRPggV3t7Pz49Dhw6hp6eHuro6w4YNQyKRlOpPu3btZN3X5syZQ/fu3XFycpLzMyEhgUWLFpGZmYmmpiYLFiygS5cucvaF95WYmIirqys2Nja0atWqVK3loaWRUbnsqiOJyckYG7eqahkKk5R0C67seb1hdeQDaUuSsVHLKhaiGEnJ0gk0arr+jAWfVLESxXh76c8YGxlXtQyFSUpOwrgG151Jyck1tu5PTE4Gau69q0B/TY2fJJl+46oVoiD/hmu3puuvCTz2r9jkKsUY8z2PHz8utlhXV1eugWf9+vU8e/YM9/xkNzQ0lIsXL7Kk0KyOFy5cYMyYMdStW5c6deoQEhLy2m/IvTbZqs6cP3+epKQkHB0defHiBYMHSwdntm/f/vUbV1Nq6g0LRLJVpYhkq0oRyVbV8m94YKupdb9ItqoWkWxVLSLZejNUNtnaXMuCwMDAYssnT57MlClTZP8HBweTlZXF9OnTAQgJCeHy5ct4enoC8M8//zBw4ECWLVtGx44d2bRpEydPnmTDhg1lHr9C3QirGy1btiQwMJBNmzaRl5eHg4MDxsbGJX7HAKRdUqysrN6wSoFAIBAIBAKBQKAQlZwgY9SYUTgW+j5ZAUWHLTVp0oSzZ8/K/v/zzz9ln8QA6edItLW1ZZP8DR48mICAgNcev0YnW2+99VaJA9P27y8+dbBAIBAIBAKBQCD4b1G0u2BpfPTRR6xZs4aMjAzq1KlDTEyMXBdCIyMjUlNTuXXrFq1atSIuLk420VBZ1OhkSyAQCAQCgUAgEAgqi4GBAe7u7owcOZIXL14waNAgOnbsiIuLC1OnTqVDhw4sW7aM6dOnk5eXR8OGDfH29n7tfkWyJRAIBAKBQCAQCKolb/LDxPb29tjb28st27hxo+zvTz75hE8+qdj47HJ9Z0sgEAgEAoFAIBAIBBVDtGwJBAKBQCAQCASCakle7ptr2VIFNXrqd4FAIBAIBAKBQPDvJdPHtlLbvzUnUklKFEN0IxQIBAKBQCAQCAQCFSC6EVYzaupHXUH6Ydea+mFFKPi4Ys0s/4KP6tb8jzLXzI9DJv0LPoxq926nqpahMOHXf/sX1D3GVS1DIZKSk4CaHftQsz8KDDW7/I2NWlW1DIVJSr5V4/XXCN7gBBmqQLRsCQQCgUAgEAgEAoEKEC1bAoFAIBAIBAKBoFryJqd+VwWiZUsgEAgEAoFAIBAIVIBItgQCgUAgEAgEAoFABYhuhAKBQCAQCAQCgaBakpeTW9USKoVo2arBWFhaEBkVSdzhOILWBqGjo6OQnaGhIafiT9KgQQPZsl69enIw/ACRUZH8sHMH7733XpXrVVdXx8PDg7i4OI78fARnZ2fZNnp6evgH+BMeEU5cXByOjo6yde3atWPnzp2ER4QTdiAMExOTSvuiDH8KKKn8pf74ER5xkLi4Q3L+VAV5eXnMXh3Kt/uOVZkGC0tLIqOiiDt8mKC1a8so75Lt5OPnZ7n4KeCd5s258NtvdOjQQbZs5KhRxMTGEh0Tw8aNG2nYsKFKtFdG92eff87/vv222HItLS22btuGrURSYc2K0O1TMwLDQlkftZ+5ASuoU69eMRuL/nasCQthzf5drNy5mTYm76tcV1XVPQV88803uLi6VDv9bdq2ISIiQvaLio4iKTkJm742cvsdM2YM0THRldCvumu3Y8eO7N6zJ19/NA6llr+rwvrlNSqz3j9V5L7bi7ADYURGRvLjjz/SqZNiM4SqsryNjY3ZFRJC7KFD7Nu/n9atWwPg5uYmF0un4uO5dPkyAG+//Tbr1q8nMiqK2EOHmDtvHmpqagr6ZkFkVARxhw8RtDbwNeVf3E5bW5vlK3yJjokkJjaK5St80dbWltvWzOz/iIg4qJC+qtRvZGTE1m1biIg4SOyhaMa5jFWJD1VCTm7lflXMvyLZ2rt3L3PmzAHAxcWFtLS0N3KsquTtt99mxYrluE1ww8rSipTbt5k956sK2zk5ORESuosmTZrIltWvX59169fh7b0M2762LJi/gMCgQLS0tCqpd0UhHSnMnjO7QnbDnIfRslVLrK2t6W/fnzFjxshuRiu/WUnq/VTsJHY4OzuzaPEimjRpQu3atdm6bSvr1q/DTmLHmtVrCAgIUNgPeZ2qKX95f/rh7DycRYsXFrN5UyTcSWfUwm+JPnm5So4PheNiAlaWlvnlWPw6LMtumLMzLVu1yo8fe7n4AelNzN/fH01NTdkyExMTXF1cGOjkhI21NYlJScycOVPp2hXVraenh5eXFwsXLiz28NKlSxf2/vgjH374YYX0KopugwZMX+aJ95SZjO87gNSUu3zx5TQ5m2YtjRjzlTseYycyZcBgdgZvZH7gKpXqqqq6B6B1m9bs+GEHthLFP8ipSv03b9xEIpHIfseOHWP//v1ER71KrLp+2JXxE8YrQb9qrt3gdevwW7UKiUTC6FGjWLBgAcbGxgC0btOGHT/8oLSXDco4F1BQ74fI1emampqsCVzD3DlzsbW1Zc2aNazyq/i1oery9g8IYPv27fTp3Rt/Pz/WBgcDEBwcLIujIUOG8OzZM6ZMngzA1x4e3LhxA9u+felnZ4epqSmDPvtMQd98cZswESvL3vnlWtp9t2S7yVMmUatWLfraSOhrI6G2dm0mTnIDpPeAmV/OIDBoDbU0alVYX1XrX/nNCg4ePIhE0g8nx0EMGzaMXh/1Urofgorzr0i2CrNx40YMDAyqWobKMTM34+LFiyQlJQGwbds2BgwYUCE7fX19rG36MHLEKLltjI2NefL4CSeOnwAgIeEWT58+oUuXzlWq18bGhtCQUHJycnj8+DEHDhzAwdEBPT09zMzM8Pf3ByA1NRWHAQ5kZmZibm5OcnIyR346AkBsbCyTJk1S2A9l+lNa+Uv9+T/8/QMK+eNIZmZmpXUrwvbIU3zW+0P6ftTh9cYqwszcvJzlXbqdNH5CisTPq7fgnkuWsDs0lIcZGbJlly9f5tNPP+XJkydoa2vTxMCAhw8fKl27orr79etHWloa3l5exY47evRofH18+O3ChQrpVZQu/9eLG5cucy/5NgDhP4TwaX/5h9wX2S9YvWAxD//8C4Abl36nQaNGaGiqrkd7VdU9ACNHjmTnzp1EhEdUS/2F6datG7a2tsyfN1+2rFGjRnh6euLt7V0J/aq7drW1tQkICOD48eOAtPwzMjIwNDQECpd/uML65TUqq963ZuSIkXLbvHjxgp49enLlyhUAWrRooVCdr8ryNjAwoHXr1hwICwPgyJEj1Ktblw+K9BaZN38+Px85wpEjRwCIjo5my+bNAGRlZXH9+nXeadZMAd/MuHjxUjnLv2S70/GnCVwTRF5eHrm5uVy5ckWm5ZNPzKlbpy4zZ3xZYW3VQX/IrhD275OemydPnpCcnKxQOQuUj0rucPHx8axYsYLc3FyaNWtG3bp1uXHjBjk5Obi4uNCvXz+ysrJYvHgx586dQ1NTk4kTJyKRSLhw4QJeXl5kZWXRoEEDPD09MTIyYsSIEejp6XHjxg38/f25du0awcHB6OjoyI4BYGlpyZYtWzh9+jTHjh3j0aNHpKSk8PHHH7No0SJA2qUgOjqaBg0a0LhxYywtLXFycirVn3379pV4rMjISDZt2sQ///xDdnY23t7eNGzYkFGjRnH48GHU1dWJj49n48aN/O9//1NqGTc1NOT+vfuy/+/fT0VXVxcdHR2ePn1aLrv09HQmjHcrtu/ExETq1K2DmZkZx44do2PHjrz77rvo6+tXQm/TIjrul6K3dLumhk25f7/QutT7tH+vPcbGxqSnpzPOZRyffvopWlpabNywkcTERFq2bMmff/6J73Jf3nvvPR4/fsyyZcsU9uOVTtWVv7w/n8j5UxV4uPQH4PhvN6vk+FBQjvdk/5ceP6XbNTU0LBI/qbTP7x47eMgQNDQ02LlzJ5Pz38YW8PLlS6ytrfHx9SU7O5tVqyr2trk82hXVvX37dgAGDRpU7LhTp04FUMrLhfLQ2LAJf95/1avgr9Q06tWvT5169Xj+998ApN+9R/rdV366zP2S+MNHePnipcp0VVXdA7DQYyEA5mbm1VJ/YebNm8fKlStl+1RXVydgdQDLvJfx8qXi50eV125WVhYhu3bJlg8dOpR69erx66+/ArDQwwMAczMzhfXL+1L5cyGt9yeUuP+XL1/SqFEjDoYfpEGDBkyZPEUBjaor76ZNm5KelkZeXp7cOsMmTbiS32WwTdu2WFtb84n5q5iPioyU/f3BBx8woH9/hgwZoqBvRe+n9ct535XaHTv2i2x5s2ZNGTP2C+bOkb5giImJJSYmlp49e1RYW3XQHxq6W7buk0/M6dqlC199VbzltSZS06d+V9nrxKSkJH766SfWr1+Pvr4+vr6+PH36lCFDhtCpUyeio6N59uwZkZGRPHjwgNGjR9O7d29mzJiBv78/HTt2JDIykhkzZrBnzx5AOvYmMDCQtLQ0Vq5cyb59+3jrrbcYP368LAEqzPnz5zl48KC0ybVvX4YOHcrdu3c5d+4cBw8e5Pnz5zg6OmJpaVmqH6UdKzc3l507d7Ju3Trefvttdu/ezYYNG1i3bh3vvPMO8fHx9OrVi3379pWZyCmKmrq6XIVXQE6RgCyvXWGePn2Kq+t4Zn35JfPmzSX+9GlOnDhB9osXldCrVk69pdsVXaeGGjk5OWhoatCiRQuePnnKoIGDMDIyInR3KImJiWhoamBhYcHQIUO5cOECffr04ftN3/Pxxx+TnZ1dCX9UV/7y/nyW708IiYlJXL5cdV35qhJllHfRdWr5yz8wMcHZ2ZnPy+jWEhMTQ0xMDEOGDGHL1q18Ym5e4nEU1a6I7upGaddubm7x/vLadeoww8eTRoZN8Bg7sUp0qbruUda1qkr9BXTp2oW3G77N/n37Zcu+mv0Vp+NP88svv9CzZ89K6FfdtVsYNzc3vhgzhlEjR5KVlaWw3rJQxrl4HX/99Rc9e/TkA5MP2LFjBzcG3KjQizZVlreaujpFt1BTUyOn0DU+ZswYtmzezJMnT4rt29zcHD9/fxYuXMjvv/9ebp/Ko7midiYmJqzfsI7Nm7dy+PDhCmtRhDel38nJkQVfz8fNbRJ/pv+pJPWCyqCyZKtly5bUr1+fEydO8M8//8gSpmfPnnHjxg3OnDnD559/jrq6Oo0bNyY8PJzr16+jq6tLx44dAbC1tcXDw0N20RYsP3/+PJ07d6ZRo0YA2Nvbc+rUqWIaOnfuLBtU2Lx5cx49esSJEyewtbVFS0sLLS0tevfuXaYfpR1LXV2doKAgDh8+TGJiIqdPn0ZdXdorc+DAgYSFhWFqasqpU6dkLWqVxX2GO33y9erU1+Ha1WuydU2aNCEzM5Pnz5/LbXPv3j06m5q+1q4wampqPPv7GUOGDJUtO/zTYZKTkhXQ20cBvZ1LtLt3755cF1EDAwNS76fKxuiFhoYCkJyczJkzZzA1NSU9LZ2bN29yIb8rVWxsLD6+PjRv0ZyEmwkK+KP68i/Zn7OYmnb6TyVb7jNmFCrv+ly7elW2TpHyLjl+7jPQyQkdHR327t0LgL6BAf4BASzz9ubGjRs0btyYs2fPAhASEoKXtzd6enrl7uJTnhhQRHd14897qbTr+KqraUMDfZ5kPiKryDlqbNgEj/WrSUlIZO6IcWSr4MG4OtQ9lblW35T+Auz72bN3z165BzwnJyce/PUAGxsb6tarS5MmTYiIiEBSjvFPb+raBekkMCtXrqRt27Y4OTpy586d1+qrCMo+F6VRv359PvroI6KjpePlrly+wh+//0G79u3KlWxFRETka1Rded+7exf9xo3l9lP4XKirq2Nra4t9v37F9I0dNw43NzemTpki6/ZZHtxnTC/jvmtQim936WzaqVQ7e/t+LFnqiYfHIsL2h5VbiyK8af3zF8zD1taW4c4j+P33P1Tl1hsnL6d8LzerKyobs1W7dm1A+lZzxYoV7N+/n/379xMSEoKZmRkaGhpyA7qTk5NLfAOal5cny+YL9qmmJv/WSEOj5Jyx8AwzBduoq6uXeJzSKO1Yf//9N4MGDeLOnTt069aNESNGyGz69u3L8ePHiY6OxtzcvNhMN4rit8oPicQOicQORwcnTDt3lg0EdnYeRmxMbLFtjh09Vi67wuTl5bHp++9kM7L162dHVlYWf/xRsQtXqlc6YNbRwRHTzqaFdDiXobdku9jYWD77/DNq1aqFrq4u9v3tiYmJ4U7KHS5dusTAQQMB6TiDrl27cvHiRY4cOULz5s1lMxB2796dvLw87qRU/Ib8psq/ZH+6cPHipQprrskUDHqXxo9DkXJ0JjYmptg2x44eLdVOGj+fF4qf/sTExODp6YmlhYXsWOlpaUyfNo1Dhw6hr6/PmsBA2YxhDg4OXL92rUJjKcrSVBnd1Y1ffzlJO9OONDVqAYBk6GecijsiZ1OnXl18tn3LiZg4lrvPVkmiBdWj7qkJ+gvo0aNHsQfg7t26Y2tri0QiYc7sOSQnJ5cr0ZLqfzPXLoCfvz869evj5OSk9ERL6otyz0Vp5OTksHzFcrp+2BWAtm3b0rp1ay6cL9+YyzdR3qmpqSQlJ2Nvbw9IW6pyc3O5mp/ctW/fnkePHhU7DyNGjmTkyJE4OjhUKNEC8Fvlj0TSD4mkH44OA0vQfKgE334p1c7KypKFizwYMXyUyhOtN61/7rw5dO/enf72A/5Vida/AZV/Z6tnz5788MMPLF26lPT0dBwcHNi5cyfdunUjIiICCwsLMjIyGD58OBEREWRmZnLx4kU6duxIREQETZs25a233pLbZ9euXVmyZAlpaWk0btyYiIgIdHV1y6Xno48+YuPGjQwdOpTs7GyOHDlS5rTmpR0rKSkJNTU1JkyYQF5eHl999ZUsKaxTpw7m5uasWrWKNWvWKF54ZfDgwQNmzZpFcPBaNLU0SU5OZoa7dJa0Dh064Ovrg0RiV6ZdWUybOh0f32VoamqSnp6Oq0vlps19pSO4kI4ZhfT6IpFIyrTbtnUbRi2MiIyKRFNTkx07dhAfHw/AeNfxeC7xZPjw4airq7M6YLXsgcfVxZWlS5dSp24dsrOzmTB+QqW7mai6/Me7Tsj3x7mYP/9F5ONCK78c3YGy4kfebtvWrRi1aEFkVFSx+CmNM2fOEBQYyM5du8h5+ZK09PQKTyFdmiZV6q4KHmVk4D/Xg7lrVqKpqcn923f45qv5tDF5n2leC5kyYDD9hg+hcVNDPupjyUd9XnXfnjfKlSeZj1SiqyrrnpqgH8C4pbFKEpXi+pV77Xbp0gU7OzsSEhJkvWcAfHx8OHr0qIp9UexclMazZ89wdXHFw8MDTQ1NsrOzmTptKqmpqWVuV7ZG5deVU6dMwcfHh8lTppCVlcXEiRNlL6SNjYvHkaamJrNnz+bp06esX79etjw8IoKgwEAFfPuK4OCg/HK9XeS+uwyJpF+ZdvPmS6ed9/V9NXb77LlzeHy9sEJaFEGV+tcGBTNu3Fju3bvHtm1bZOs2bfpebiyXoGpQyyvvwIMKEB8fT2BgIFu3buXp06csWrSIq1evkpOTg6urK46OjmRnZ7N06VLOnz8PwJQpU7C2tub8+fN4e3vz/Plz9PT08PT0pHXr1owYMYLJkyfTo4d04GJUVBQBAQHUqVOHNm3aoK6ujo+Pj9wEGadPn8bHxwdAbns/Pz8OHTqEnp4e6urqDBs2rMw3diUdy8vLi1mzZnHlyhXU1NT4v//7Pw4dOiSbfefkyZMsWbJE1rRfXoyNWipQ4tWDpOREjI2Mq1qGwiQlJ9XY8k9Kzu9mcmVP2YbVlQ+kLQPGRkZVLEQxkpKlXWxrsn67dxX7pk91IPz6b/+Cuse4qmUoRFJyElCzYx8Q5V9FJCUnY2zUqqplKExS8q0ar78m8OfMyk1h3/ibk0pSohgqSbaqM+fPnycpKQlHR0devHjB4MGD8fb2pn379q/fuJzk5OTg5+dHw4YN+eKLLyq0bU192AeRbFUlItmqWkSyVbWIZKvq+Dc87INItqoKkWxVLSLZejOovBthdaNly5YEBgayadMm8vLycHBwwNjYuMRvHYB0+mQrK6sKHWPgwIE0aNCA4PyP/QkEAoFAIBAIBIKKk5dT/rkWqiP/uWTrrbfe4ttvvy22fP/+/SVYK8a+ffuUti+BQCAQCAQCgUBQM1HZbIQCgUAgEAgEAoFA8F/mP9eyJRAIBAKBQCAQCGoGebk1e3oJ0bIlEAgEAoFAIBAIBCpAtGwJBAKBQCAQCASCakleTs1u2frPTf0uEAgEAoFAIBAIagapk7pVavsmQWeUpEQxRMtWNeOz9l2rWoLChF49V3O/8wTwwcAa/52tmvytFaDmxo/sO2E183sr/4ZvxQj9VUPBd3pqvH7jGqo/qaD8jatWiIIkJSfR0rhtVctQmMSkGzVev0D1iGRLIBAIBAKBQCAQVEvycqpaQeUQyZZAIBAIBAKBQCColtT0MVtiNkKBQCAQCAQCgUAgUAEi2RIIBAKBQCAQCAQCFSC6EQoEAoFAIBAIBIJqSW5uVSuoHKJl619Al0/+j5X7dxIQuYcZ/r7UqVevmI2ZvS0r9v3Aih93sPSH72hl8l4xm9FzZzJnnf+bkFxh8vLymL06lG/3HatqKSViYWlBZFQkcYfjCFobhI6OToXstLW1Wb7Cl+iYKGJio1m+whdtbW0la7QkMiqKuMOHCVq7tgyNJdupq6vj4eFBXFwcR37+GWdn52LbvtO8ORd++40OHTrIlo0cNYqY2FiiY2LYuHEjDRs2VKpf5aG6xY80DiKIO3yIoLWBr4mX4nav4iWSmNgouXhp164dV36/RETEQdmvVSvlzrIp9JesX1e3vpzuiIiDJNy6wdhxY2uEfgB9fX22bPmeyMhwoqIjcXAcUGO0t2/fnt17QoiMDCc84gCffvqJUrUDWFhYEBkZQVzcIYKCytBfil39+vVZuzaI6OhIYmOjmTBhvGybjh07snt3CBERB4mKisTBQTllX9n7k3zdf0Su7reysuLCbxeIiIiQ/eoVeQb55ptvcHF1UY4vFp8SGXmAuLhogoJWl1H+r7cLXhfE4sUeANTXrU94RJjc72bCVcaO/UIpuv8t+gWKUSOSrYsXL7JixQql7Gvu3LncvXtXKfuqDug2eIuJ3gtZOXUW84xaiAAAIABJREFU02wHkpZyB+eZU+RsmrY0YsSs6Xi5TGGW4zD2BH/LrNUr5Wx69e2Dmb3tm5RebhLupDNq4bdEn7xc1VJK5O2332bFiuW4TXDDytKKlNu3mT3nqwrZTZ4ymVq1NOhrY0tfG1tqa9dm4qSJSta4ArcJE7CytMw/9pwK2Q1zdqZlq1ZYW1vT396eMWPG0KlTJ9m22tra+Pv7o6mpKVtmYmKCq4sLA52csLG2JjEpiZkzZyrNr/JQ3eJHWsa+uE2YiJVlb1Jup5QRLyXbTZ4yiVq1atHXRkJfG0l+vLgB0LVrF/bvD0Mi6Sf73bqVKPS/Af2PHz+R070rJISzZ86y+fvNNUI/wFdffcn5CxewtbVj1MjRLF26hMaNG9UI7X7+q9iwfiO2tna4T59JYNAaufpIafrdJmJl1ZuUlBRmzy5Dfwl2M2a4k5qaio2NLf37OzB8uDNdunQGIDh4LX5+AUgk/Rg9+gsWLJiPsbGxEjSvKHTfSWH2nNkVshvmPIyWrVrm1/395er+rl27smHDBiQSiez3999/A9C6TWt2/LADW4lyni3efvttlq/wwc1tMlZWNtxOSeGr2V8qZDd+vAvdun0o+//J4yfYSfrLfiG7Qjl79hybN29VivZ/g/6qJC+ncr+qpkYkWzdv3uTBgwdK2Vd8fDz/pu84d/y4FwmXfic1OQWAmJ27iyVNL7KzWff1EjL//AuAhMu/81ajhmhoSnuRNmtlzIBxIwldu/HNii8n2yNP8VnvD+n7UYfXG1cBZuZmXLx4kaSkJAC2bdvGgAHF30iWZXc6/jSBawLJy8sjNzeXK1d+551mzZSo0bycGku3s7GxITQkhJycHB4/fsyBAwdwcHSUbeu5ZAm7Q0N5mJEhW3b58mU+/fRTnjx5gra2Nk0MDHj48KHS/CoP1S1+pHFwqZzxUrKdNF6CCsXLFVm8dO3ahTZt2nAwPIx9+3/Epq+N0P8G9RdgZGTE5MmTcXefycuXL2uMfvVatdCtXx+AOnXqkJOTQ26ucu6Zqtbez86emJhYAIyMWvD48WNycpT3pGVmVk79ZdgtXuyJl5c3IG1F1NLS4vHjJ2hraxEQsJrjx48DkJqaSkZGBoaGTSqnWQn3J2ndH1qk7ncApMnWRx99RGRkJCGhIXTv3l22z5EjR7Jz504iwiMq5YNMo9n/5Zdrcr7GHQwY0L/Cdj16dsf8EzN2bP+hxOMYGbVg8uSJzHD/UrnXbg3XL1AclSdbeXl5rFixAhsbGyQSCZs3byYxMZERI0Zgb2/P4MGDuXjxIgBz5sxh6dKlDB06FEtLS/bs2cPjx49ZvXo1hw8fJjg4mL1798q2XbVqFdevX2fEiBEMHDgQCwsLfvhBGnyZmZlMmjQJW1tbBgwYwMmTJ9mwYQPp6em4urqW+sCXnJzMp59+Sm5+B9H4+HjGjRsHwIYNG3B0dKR///4sX75clrT5+fnx+eefY2Njw4gRI/jrL2lS07NnT8aNG8eAAQN48eKFSsq3kaEBf6Wmyv5/kJpO3fo6cl0J/7x7n19//kX2/6g5Mzj708+8fPGS2nXrMGX5EoLmLuKfv5+pRGNl8XDpj725aVXLKJWmhobcv3df9v/9+6no6uoWa/Yvy+7YsWMkJkrf3jdr1owxY78gXEk3qFfHvlfo2PfL0FiyXVNDQ+7fL6Q/NRVDQ0MABg8ZgoaGBjt37ix27JcvX2Jtbc3JU6fo3qMHoaGhSvOrPFS3+Ck5DuqXM17q58fLL4XipWl+vEQC8Oz5c8LCDtDf3oGZM7/Ey2uJXLdOoV+1+guYNWsmmzdv5l6h66km6F/uu4LefXoTf/oksYei8Vvlr7SXnarWXpBY/Xz0J9atD2bduvWye7lS9DctUgeWpv81djk5Ofj5rSImJopTp+K5desWWVnZhISEyLYZOnQI9erp8Ouv5yun2bBpkbIsre4v3a6pYdMidf99Wd3/MPMh27dvx9bWluW+y1m/YT1NmkgTxIUeCwnbH1Yp/YUxbNpETkdqKeVflp2+vj4LFy5g+rSZ5OSWnIh/OWsGmzdv5V6h8hD6BZVB5clWVFQUv/76KwcOHCA0NJS9e/cyYcIERowYwYEDB5g7dy7Tpk0jOzsbkL7N2bFjB8HBwSxfvhxdXV2mTp2KpaUlbm7SrgJpaWn8+OOPzJgxg9DQUCZOnMiePXvYsmULy5cvByAgIIAWLVoQGRnJ8uXL8ff3x9XVFX19fTZs2ECDBg1K1GtkZMQ777xDfHw8APv27cPJyYmjR49y+fJldu/ezb59+0hLSyMsLIzk5GRu3brFzp07iY6OxtDQkLAwaeXy8OFDXFxc2L9/v1K7MhRGTV0NSnjpmFvCRahdpzYz/H1p0qI5wQuWAOC21IPIbbtIuZGgEn3/BdTU1UtsLS36RrU8diYmJoSE7mLz5i0cPny4Wmksuk4tf/kHJiY4Ozszf968Uo8fExNDl86d8ffzY8vWraipqSnuTA1H+fESwubNW2Xx8vUCD7Zt3UZubi4JNxM4eDCc3r2thP43pB/A0NAQc3NzNn33vdJ0V0RXee1K0h8Q4Mf6dRvo0b0XfXrbMMFtPJ06dawR2gv4xNyCTz6xwM1tAr0+6qUU7QBqauXUXw47d/cZdO7clbfe0mPatKlydm5uE3B3n864cePIysqqnGZ1tXKWeel2RdepoSbbfsL4CURGSJPds2fPcu7cOczMzCqluTTUy1n+pdmpqcHqNX4s8fTmzz//LPEYhoZNMDc3Y9Mm5XX9fZ2umqK/Kqnp3QhVPhvhmTNnsLW1RUtLCy0tLXbs2IGFhQXW1tYAmJqaoqenx61btwD4+OOPUVNT49133yUzM7PEfb7//vtoaEilz5kzh2PHjrF+/XquX7/Os2fPZMdduVI6Lqldu3bs2rWr3JoHDhxIWFgYpqamnDp1ikWLFuHv78/FixdxcnIC4J9//qFp06YMGDCA2bNnExoaSmJiIhcuXKBFixayfRUe06IK/rqXStuOJrL/3zZozNPMR2Q9/0fOrpFhE2YH+3E3IZHFo8aTnZXF2wb6tP+wM01bGtFv1DB09PSoW1+HuesDWDZ+mkp113TcZ7jTp3dvAHTq63Dt6jXZuiZNmpCZmcnz58/ltrl37x6dTU1LtbO378eSpUvwUNLbQPcZMwpprM+1q1crpfHevXsYGBjI1hkYGJB6/z4DnZzQ0dFh7969AOgbGOAfEMAyb29u3LhB48aNOXv2LAAhISF4eXujp6dX6vX9b8R9xvQy4sWglHNxl86mnUq1k8aLJx4ei2Txoq6ujtvECXy/abNs3ISamhovXlauZV3oL5/+AiQSW6KjY2Q+VJY3pb9BgwZ82O1Dhg0bDkBSUhK/HPuF7j2689tvF6u1dk1NTfr2teHgwXDy8vK4k3KH478c54MP3ufkiZMKaQdwd59Onz75+nV0uHatnPo7l6zf3NyMq1evkZ6ezrNnzwgLO0Dfvn0B0NLSYuXKFbRt2wYnp4HcuaPY+HLp/amPVHOF7k+dS7Qrue6X9swYPmI4a4PWytYp43qV88V9Gr37SF+2lL/872FaQvm3aduG5s2bs+Br6YvBxo0boa5eC21tbebMmQ+AraQv0dGxyrt2a7h+gXJQecuWhoaG3FvslJSUYhl7Xl6eLLMvmFWorDfftWvXlv09ffp0YmNjad26NdOnTy/1uAkJCeXuTtC3b1+OHz9OdHQ05ubmaGtrk5OTw6hRo9i/fz/79+8nNDSUCRMmcPnyZcaOHUtubi42Njb07t1bzr/CWlXBb8dP0bZTB5oYNQfAesggzhz+Wc6mdr26LNqynvjYw/jPnEd2/puyjLR0xpv3ZZbjMGY5DmPXmnX8ce68SLTKgd8qPyQSOyQSOxwdnDDt3Fk2kNnZeRix+eMGCnPs6LFS7aysrFi4aCEjho9UWrcLv1WrZAOWHR0cihzbmdiYmBI0Hi3VLjY2ls8+/5xatWqhq6uLff/+xMTE4OnpiaWFhexY6WlpTJ82jUOHDqGvr8+awEBZS7KDgwPXr137TyVaAH6r/GWTJjg6DCyhjA8V2+bY0V9KtbOysmThIg9GDB8lFy+5ubn06d2bocOGANJuVra2fYmMjBL634D+Anr06M7xE8crpbkq9D98+JD791OR5E9o0KBBA7r36M6F879Ve+0vXrxg5pczsO9vD0jHQ/Xs1Yv4U6cV1g7g51dIv+NATE2L6IotQf+xX0q1s7OzY/p0aUuWlpYWdnZ2nDx5Mv9Yq9DR0cHJaZDCiRYU3J8K6n5HTDubFinL0u5PJdtJ6/7PCtX99sTExPD06VNGjhxJX1tpsvjBBx/QqVMnfj7yc7H9K+yLX4Bs0gcnx0F0NjXF2NgIgGHOQ4mNjSvuy7FfSrQ7/+sFPv7IXLa/7dt/IPxguCxRAem1e+L4CaG/mpGbW7lfVaPylq1u3bqxZcsWhgwZwsuXL5k+fTpqamrExMRgbW3NhQsX+Ouvv2jbtm2p+6hVq1apg/yOHz9OZGQkBgYGbN++HZA2yX744YeEh4fTrl07EhIScHFxIS4ujlq1ar12wGydOnUwNzdn1apVrFmzBpCOv1q9ejWff/452traTJo0CUdHRx49ekT37t0ZOnQoDx8+5MiRI7JWuzfB44yHrJ23mJkBy9HQ1CQt5Q6Bsz1oZfIebku+ZpbjMPo6D6ZxU0N69LagR28L2baLv3DjaeajN6b138qDBw+YNWsWwcFr0dTSJDk5mRnu0hn3OnTogK+vDxKJXZl28+bPQ01NDV9fH9l+z547h8fXHkrWGIymllb+sd0LafRFIpGUabdt61aMWrQgMioKTU1NduzYIetuWxpnzpwhKDCQnbt2kfPyJWnp6bi4uirFp5qKtIy/Ijg4KD8ObheJl2VIJP3KtHsVL8tk+5XGy0KmTXPHy3spgwYNolYtdTwXLyHhpvK6CQv9ZesHMG5pzJ0U1cx6q2r9LuNcWLR4EVOmTiY3N4+1QcGcOXOmRmgf7+qG55LFTBjvSm5eLsu8l3Hp0iWlaC+mXzNf14zX6C9i5+XlhZfXUqKjpV3voqNj+O67TXTp0hk7OwkJCbfYs+fVuFYfH1+OHlX8kxXydXrBfWdGIc0l1f3ydtu2bsOohRGRUZHF6n6XcS4s9lyMu7s7OS9zmDJ5isomQXrwIINZs+awNngNmppaJCffZuaMWfm+mODj642dpH+Zdq/D2Ni4Uonuv1m/QHHU8t7A1Hx+fn4cPnyY3NxcnJ2d6dGjB4sWLSIzMxNNTU0WLFhAly5dmDNnDt27d5d11WvXrh3Xrl0jMTERV1dXbGxsaNWqFadPn8bHR/pQumnTJrZt24a2tjbt27fnwoULbNq0iQYNGrBgwQKSkpLQ0NBg3rx5fPjhh3h5eXH06FH+97//0bx581I1nzx5kiVLlhAR8WqSgrVr1xIeHk5OTg5mZmbMmzeP9PR0Jk+ezD//SLvtvffee+Tm5rJy5UqZ/orwWfuuFS3eakPo1XNwZU9Vy1CcDwZibKTc7/m8KZKSpQPGjY2MqliJYiQlS2ddqrHx88FAAIyNWlWxEMVISr5VY7WD0F+VJCVLhwDUeP3GNVR/UkH5G1etEAVJSk6ipXHpL9urO4lJN2q8/ppAkvOHrzcqA+PtZ5WkRDHeSLJV05DOFORHw4YN+eKLN/tBOJFsVSEi2aoyRLJVtdTkh30Q+qsSkWxVLSLZqlpEsvVmSBxSuWSr5c6qTbZU3o2wujJz5kxu3rxZbLmlpSU//fQTDRo0IDg4uAqUCQQCgUAgEAgEgn8D/9lk65tvvil13bRpYoIIgUAgEAgEAoGgqsnNrdmfi1H5bIQCgUAgEAgEAoFA8F9EJFsCgUAgEAgEAoFAoAL+s90IBQKBQCAQCAQCQfWmOnwrqzKIZEsgEAgEAoFAIBBUS/LK/jxutUdM/S4QCAQCgUAgEAiqJdcdu1Vq+3d/VM6H2RVFtGxVM1rV0O8kAdxKTq6x36kC6beqMhZ8UtUyFOLtpT8DNf87WzX9Wz01+TthNfU7QyD91lBNjX2Qxn/LGqo/Mf/aren6a2r8vKo7jatWiIIkJSfV2LIHafnXdP0C1SOSLYFAIBAIBAKBQFAtEVO/CwQCgUAgEAgEAkEN58CBA0gkEqytrdm+fXux9bdu3WLEiBH079+fsWPH8ujRo9fuUyRbAoFAIBAIBAKBoFqSm1O5X3lJS0vDz8+PHTt2sG/fPnbt2sXNmzdl6/Py8nBzc8PFxYWwsDDee+89NmzY8Nr9imRLIBAIBAKBQCAQ/Kc5ceIEPXv25K233qJu3brY2NgQFRUlW3/lyhXq1q2Lubk5ABMmTMDZ2fm1+xVjtgQCgUAgEAgEAsG/ksePH/P48eNiy3V1ddHV1ZX9n56eTuPGjWX/6+vrc/HiRdn/t2/fplGjRsybN48//viDVq1a8fXXX7/2+KJl61+AhaUlEVFRHDp8mMC1a9HR0Sm3jba2Nr4rVhAZE0NUbCy+K1agra39hnRbEBkVSdzhOILWBpWouzx2hoaGnIo/SYMGDWTL9PT08A/wIzziIHFxh3B0dFSZH5rv9kR38nfoTduKzpDFoF1Xbr2WqQ26k/4n++nN3EmDxXGo1ZPqfWvufrn1Wp16K12jhaUlkVFRxB0+TFAZMVKSjbq6Oh4eHsTFxXHk559LfIvz2eef879vvy22XEtLi63btmErkSjZHwsioyKIO3yIoLWBr4md4nba2tosX+FLdEwkMbFRLF/hK4v7du3aceX3S0REHJT9WrWq2lk28/LymL06lG/3HatSHQVYWFgQGRlBXNwhgoLKKP9S7OrXr8/atUFER0cSGxvNhAnji237zjvvcOHCr3To0EExjeWI+bLsyop7Y2NjdoWEEHvoEPv276d169YAuLm5ERERIfudio/n0uXLMn82b97Mobg49oeFYWdnpzQ/yvLhaw8PDsXF8dPPPzOskA89e/XiQHg4kVFR7Ni5k/fee6/Yfr8YM4aomJhy6SwvlfGnAENDQ07Gx8vV+QW807w553/7TeG4qaxGReKmMGPGjCG6SJkPHzGCg+HhHIqLw8/fHy0trQr6U7l7rbxPR+R86tWrFwfDDxIZFckPO38oFkfSe8BWbCW2FdL8SpNqzoX0GSGA8IgI4uLiSnxG+Oabb3BxdVVId0X0K+pDx44d2b1nDxEREURFR+NQyIeRo0YRExtLdEwMGzdupGHDhpXyo6rJzVWr1G/z5s1YWVkV+23evLnIcXJRU3s1GUdeXp7c/y9fvuT06dMMHTqUH3/8kebNm+Pj4/Na/SLZquG8/fbb+K5YwcQJE+htaUnK7dt8NWdOuW0mTZlCrVq1kNjYILGxoba2Nm6TJr0R3StWLMdtghtWllak3L7N7DlfVdjOycmJkNBdNGnSRG67ld+sJPV+KnaSfjg7D2fR4oXFbJSBWl096jnN4ekPX/MoYAQ5Gfeoay3/4Jh9IZrHQeOkv+Dx5D3J4NlBf/L+foh6o+bkPX/yan3QOLJ/O6RUjdIyXIHbhAlY5Z//2SXESGk2w5ydadmqFdbW1vS3t2fMmDF06tQJkN6wvLy8WLhwoVyFBNClSxf2/vgjH374oQr88cVtwkSsLHuTcjuljNgp2W7ylEnUqlWLvjYS+tpIqK1dm4mT3ADo2rUL+/eHIZH0k/1u3UpUqg8VIeFOOqMWfkv0yctVpqEwsnJ1m4iVVW9SUlKYPbuM8i/BbsYMd1JTU7GxsaV/fweGD3emS5fOsm21tbXw91+FpqZmJTSWHfOvsysr7v0DAti+fTt9evfG38+PtcHBAAQHByORSJBIJAwZMoRnz54xZfJkQPrgdv78eXpbWTFs6FDGT5hQYoJTVN/yQvpul1K/l2ZT4IONtTUDCvlQv3591q1fzzJvb2z79mXB/PkEBgXJPcR3/fBDxk+YoFD5q8ofkNb5u0JDS6zPtbS18fP3VzhuCo6vqvqytLgpoKQyt+nbl9GjR+M8bBh9evemdu3ajB07VgF/Cu6hKcyeM7tCdsOch9GyVct8n/oXiaN1eHt7Y9vXlgXzFxAYFCiLI+k9YK/C9wBVnouV33xD6v372EkkODs7s2jxYllMtW7Thh0//FDpl4SqroeC163Db9UqJBIJo0eNYsGCBRgbG2NiYoKriwsDnZywsbYmMSmJmTNnVsqXms6oUaOIi4sr9hs1apScXZMmTfjzzz9l///555/o6+vL/m/cuDFGRkaylzn9+vWTa/kqjSpNti5evMiKFSuUsq+5c+dy9+5dpeyrIjx58oRJ+cnJnTt3sLS0fKPHNzM359LFiyQlJQGwbds2BgwYUG6b0/HxBK1ZQ15eHrm5uVy5coVmzZq9Ad1mXHyN7tfZ6evrY23Th5Ej5C8WPT09zMz+D3//AABSU1NxGOBIZmam0v3QbNuNl3evkvtAGntZp/eX2TJV23wYuX8/JOvMAQA0WphAbi71x61Bd/J31LYYBWrKvSzNzM1fW9Zl2djY2BAaEkJOTg6PHz/mwIEDsjdo/fr1Iy0tDW8vr2LHHT16NL4+Pvx24YKS/THj4sVL5Yydku1Ox58mcE2QXNy/kx/3Xbt2oU2bNhwMD2Pf/h+x6WujVP0VZXvkKT7r/SF9P1L8Tb0yMTMrZ/mXYbd4sSdeXt6A9DrW0tLi8eMnsm09PT3ZvXsPDx8+VExjOWL+dXalxb2BgQGtW7fmQFgYAEeOHKFe3bp8YGIit+958+fz85EjHDlyBACTDh3YvXs3AH///TcnT57Exqbs2FLGtbu7BB+MjY158vgxJ44fB+BWQgJPnj6lc5cuADRq1IjFnp4s8/YuU19Fqaw/+vr69LGxYdSIESXu33PJEvaEhvIwI6PKNCoaN40aNcLT0xPvImU+0MmJjRs38ujRI/Ly8pg/bx579+6tgD+Vv9dKfQot4pNDfhw94cTxEwAkJCTw9OlTuuTHkfQe4MtvF34rt155Tao5F9JnBDP8/f2BgmeEAbJnhJEjR7Jz504iwsMV0l0R/Yr6oK2tTUBAAMfzr+HU1FQyMjIwNDTk8uXLfPrppzx58gRtbW2aGBgoXJdWF/Jy1Sr109XV5Z133in2K9yFEOCjjz7i5MmTZGRk8Pz5c2JiYmTjswA6d+5MRkYGV69eBeDw4cN88MEHr9VfpcnWzZs3efDggVL2FR8fT15enlL2VREePXrEH3/88caPW4ChoSH3792T/Z96/z71dXXlmqrLsvnl2DESE6Vv7Zs2a8YXY8cSWckKpjw0NTTk/r37sv/v309Ft4ju19mlp6czYbybTH8BxsbGpKenM85lHLv3hBJ2YD8mJh/wzz//KN0PdT19ch+ly/7Pffwn6rV1inUlBGkrWO2PB/MsIvDVMvVavEg4x5PNs3jyv6lotumGdk8npWpsWuT8379/v1hZl2XT1NCQ+/cLnYPUVAwNDQHYvn07q1evJjs7u9hxp06dyrFjyu/2VnJM1C9n7Ejtjh37RRY3zZo1ZczYLwgPjwTg2fPnhIUdoL+9AzNnfomX15JKdUmqLB4u/bE3N62y4xeladMi8VBa+b/GLicnBz+/VcTERHHqVDy3bkk/DD148OdoaGiwc+cuxTWWI+ZfZ1da3Ddt2pT0tDS5+8391FQMC7W0tGnbFmtra1atWiVbduHCBT777DNA+ibbwsJC7o1pSZRUdxf1oywbQ0ND7hXyITU1lSaGhiQmJlKnbl3MzMwAaXekd999F319fdTV1fFfvRofb29SU1PL1FdRKutPeno6buPHF6vzAQYPGYKmhgY7d+6slEZV1ZdlxY26ujoBq1ezzNubtCJl3rJVKxo2bMjmzZuJjIpiurt7iWNPSvenaZF6sLRroXS7poZNi/h0H0NZHNUpMY6g8vcAVZ2LV88ILuzes4ewAwcwMTGRPSMs9PAgbP9+hXVXRL+iPmRlZRGy61UdOXToUOrVq8evv/4KSLu7WVtbc/LUKbr36EFoaGil/fkvYGBggLu7OyNHjsTBwYF+/frRsWNHXFxcuHTpErVr1yYoKIgFCxZgZ2dHfHw8c0porSyKwhNk5OXlsXLlSg4dOkStWrUYPHgw5ubmeHh4kJmZSd26dZk/fz4dO3Zkzpw56OjocOXKFdLS0pg0aRJ9+vRh9erVPHv2jODgYAwMDPjxxx/JzMzEwsKCfv36sWTJEp49e0ZGRgaurq4MHTqUzMxM5s+fz61bt9DS0mLOnDlcunSJ9PR0XF1d2b59e4n9uAFGjBjB+++/z7lz58jKyuLLL79ky5YtJCQkMHr0aEaPHs3z589ZsGAB165dQ01NjbFjx+Lg4MDevXs5duwYjx49IiUlhY8//phFixaxdOlS0tPTmTRpEnPnzuWff/7B3d2dGzduoKurS1BQUKl6lIG6unqJSWZOTk6FbExMTFi3YQNbN2/m8OHDqhFbCLVyaKqIXWE0NDVo0aIFT588ZdDAzzAyMiJ0dwiJiUlcvqzkrlhq6lBSjp+bW2yRdjd7XvzxC7kPX1WcWWcPyv7OewH/HA+hdq+BZJ3crUSJry/DsmyKrlOj7PJXNcqMHRMTE9ZvWMfmzVtlcf/1Ag/Z+oSbCRw8GE7v3lZcunRJWS7UaNTUyln+5bBzd5/B/PkLWLduLdOmTSUmJhZnZ2c+/3xw5TQqIUZKi3s1dfVil7yamho5ha75MWPGsGXzZp48edVaN3PGDBZ8/TVR0dGkpKRwOC6O2nXqlOlHZet3dXV1KOJDbk4OT58+ZbyrK19++SVz583j9OnTnDhxghcvXvDV7Nmcjo/nl19+oUfPnmXqqyjKul8V5QMTE4Y5OzM4P5mtDKqqL8uKm8Jl3rNImWtoaGBmZobLuHFkZWXxzTffMGvWLDw9Pcvpj1o5r4XS7YquU0ONnPw4cnV1ZdaXs5g3bx7xp+M5ceIE2S8FCLryAAAgAElEQVSKv3xTBFWdCw1NzfxnhCcMGjgw/xlhN4mJiUp9RlBlPVQYNzc3vhgzhlEjR5KVlSVbHhMTQ0xMDEOGDGHL1q18Ym5eJY0SNQ17e3vs7e3llm3cuFH2d6dOnWS9FMqLwslWVFQUv/76KwcOHODFixcMGzaMHTt2MHPmTKytrblw4QLTpk0jOjoakL5R27FjB9evX2fkyJEMHDiQqVOncvr0adzc3Ni7dy9paWlERESgoaGBl5cXEydOpFevXqSkpNC/f3+GDh1KQEAALVq0ICgoiGvXruHh4cGuXbvYuXMnGzZseG1ik5eXx+7duwkMDGTp0qWEhYWRkZGBg4MDo0ePZs2aNTRo0ICDBw+SkZHBZ599Rvv27QE4f/48Bw8elI716NuXoUOHsmDBAkaOHElQUBB37twhIyODL774go4dOzJ16lQiIiLKNS2koty9d49Opq/eehs0aUJmZibPnz8vt00/e3s8ly5lkZLe5pSG+wx3+vSWdrHTqa/DtavXZOualKAb4N69e3QupL00u8KkpaUByN7kJCcnc+bMWUxNOyk92crNTEPjnVfjLtR1G5H77DG8KN6KpmViwbPw1fLLTK3JuX+TnDTpW33U1CD3pVI1lqcMy7K5d+8eBgYGsnUGBgakFnrT9iZwnzG9jNgxKCV27tLZtFOpdvb2/Viy1BMPj0WE7Zd27VFXV8dt4gS+37SZv//+G5A+EL14+UKl/lV33N2n06dPfvnr6HDtWjnLv3PJ5W9ubsbVq9dIT0/n2bNnhIUdoG/fvtSvL2352rtXeiPT19fH39+PZcuWcehQXNkaZ8woFCP1uZbfzUN67IrXL6XF/b27d9EvNFtV4XUgjSFbW1vs+/WTs6lduzazvvxSpsF72TJuXL9epk/37t3DtBzXbmk2d+/dQ7+QD/oGBty/fx81NTWe/f03Q4cMka07/NNPJCclsdjTkwd//YWNjQ1169WjSZMmhEdEYKeESW4q609pODk5UV9Hhz353ev0DQzwDwhgmbc3hw5VbAysqurLsuLGycmpWJlHREQgkUhIT0sjKiqKp0+fAvDjvn1Mmzq1TB+k99o+QEXvtZ1LtCvZp9T8OHrGELk4OkxyUnKZ+sqLqs5Fyc8IZzA1Na30M8KbqodAOvnIypUradu2LU6Ojty5cwcAIyMjGjduzNmzZwEICQnBy9sbPT09lQyneBOU8P66RqFwN8IzZ85ga2uLlpYW9erVY8eOHTx8+BBra2sATE1N0dPTk3UN+fjjj1FTU+Pdd98t9WS///77aGhI8785c+aQlZXF+vXr8ff359mzZ7LjFvRlbdeuHbt2VayrSUHfy6ZNm9KpUyfq1KlDs2bNZM3yp06dYtCgQYC0q4eVlRWnT58GpH01dXR0qFOnDs2bNy/xq9H6+vp07NgRgDZt2qi8n+wvR4/SuXNnjI2NAXB2duZQkZmMyrKxtLLCY9EiRg0frtJEC8BvlR8SiR0SiR2ODk6YymkaRmxMbLFtjh09Vi67wtxJucOlS5cYOGggIO0L37VrFy5eVH7LxIubZ9Bo/j7qDaXjfbS79efF1ePF7NRq61CrYTNe3pavyGvpt6SO1RhpC5mGFrV7OpJ96Selajx29GiRMnQmtkiMlGUTGxvLZ59/Tq1atdDV1cW+f39ilDxD2evwW+Uvm6zC0WFgCVqLP1AdO/pLqXZWVpYsXOTBiOGjZIkWSGci6tO7N0OHSR8emjVriq1tXyIjo4rt/7+En1+h8ncciKlpkXKNLaH8j/1Sqp2dnR3Tp0sfGLW0tLCzs+PkyZN4ei7B0tJKdqz09HSmT3d/baIFyAaKSyQSHB0cXhvzoFjcp6amkpScLHvzaW5uTm5urqwPf/v27Xn06JHswacA9xkzGJ4/1qhly5b06d1b7vstJXGsSN09rJRrtzSbQ7GxfJ7vQ/18H2JjYsjLy+O777+XdY+169ePrKws/vjjD3p064bE1hY7iYQ5s2eTnJyslERLGf6UxhJPTywtLLCTSLDLT1CmT5tW4USr4PiqqC/Lipvu3bpha2uLpFCZS/LLPCIyEjs7O9lsqdbW1vz2mgH50nttwbXgiGln0yJaS7vXlmwn9emzQj7ZE5MfR5u+3yQ3WUBBHCkDVZ2LOykp+c8I0mc96TNC13JNdPA63lQ9BODn749O/fo4OTnJ1Tf6+vqsCQyUNT44ODhw/dq1Gpto/RtQuGVLQ0NDbvaxlJSUYs2TeXl5subOgoqi6Ixlhaldu7bs7+nTp6Orq4uFhQUSiYSDBw+WeNyEhARatiz/tMyFZykqSOyKan6dDwV+lNQcW3ifpdkokwcPHvDVrFkEBQejqaXF7eRkZrq706FDB5b5+tJPIinVBqSDuNXU1Fjm6yvb57lz51hYju8GVFb3rFmzCA5ei6aWJsnJycxwl86W06FDB3x9fZBI7Mq0K4vxrhPwXOLJ8OHOqKurszpgtVIq0qLk/Z3J33t90BniiVotTXIy7vL3Hm9qNW1HPcdZPA4aB4B6w3fIffKg2KfMn//0PfX6TUdvyiZQ1yD7yhG5roXK4FUZSs+/tAzd88vZF0l+jJRkA7Bt61aMWrQgMioKTU1NduzYQXx8vFI1VtyfrwgODsqPidtFYmcZEkm/Mu3mzZ+Hmpoavr7LZPs9e+4cHl8vZNo0d7y8lzJo0CBq1VLHc/ESEm4mVImv1RG5ctXML9cZryn/InZeXl54eS0lOlo6Ti46OobvvtukZI0lx7My4n7qlCn4+PgwecoUsrKymDhxoqyuNzY2LpZoAXh7eeHn78/AgQPJyclh5syZcmMxyvJjbSF9BfW7j68vdoV8KGpT4EOLFi2IyPfhh0I+TJ86lWW+vmhqakq74bu4KKfwVejPm0CV9WVZcVMaW7ds4S09PQ6Gh6Ours6Vy5fxWrpUQX8K7qEzgLKuBXm7bVu3YdTCiMioyGI+TZs6DR9fn0JxVLmp0kvXrtxzMd7VFc8lSxg+fHj+M0KA0p8RVFkPdenSBTs7OxISEtizZ4/smD4+Phw9epSgwEB27tpFzsuXpKWnV3oKe0HlUMtTMBuIjY1ly5YtfPfdd7x8+RJHR0cyMjL+n70zj8spff/4+2nXZm+zZV8m2YWRIZGiVHZZBmNfy64mZE32fRnfGWMZCim0CmMZgxm7IQaltCASQuvvj/Jol3qe0vzu9+vV69V5znWf87nuc53lPvd17pvFixdL0wgnTpzIqVOncHV1pW3bttjbZ3z437BhQ0JDQ/Hx8eHs2bOsXLmSw4cPc+nSJel49S1btsTf3x9dXV327t2Lm5sb//zzD8uWLUNdXR0nJycePHjA6NGjCQkJoXv37vz000/UqlUrX81Dhw5l0qRJmJiY5NrfR03u7u4kJyfj4uLCixcv6Nu3Lxs2bCA0NDSb/cdt1apVi/79+3PmzBkiIyMZNmyY9NuPDRs2ADB58uRC12udAvR/7TwMD8ewVunOR1QcwsIf8cLlu9KWUSQqLf4dAMMyGj9h4RlpJ4a16pSykqIRFp6ZBnr7UMGGXyvf9MHQsGzWPUBY2MMyG/uQEf+1y6j+R5nnblnXX1bj59O107B0hRSRsPCwMlv3kFH/ZV1/WeCqeftilW9x4oKMlBSNIqcRduvWjZYtW2Jvb0/fvn0ZNmwYv/32G7t378ba2ho3Nzc2bNhQ4OR7xsbGXL9+nZUrV+ZaN3nyZAYPHoyVlRV///031apVIzIykilTphAWFoaNjQ0zZ85kxYoVSCQSOnfuzJgxY4iIiCiqSwBMnDiR+Ph4rK2tGTJkCOPGjStwWMfKlStjYGDA0HyGohUIBAKBQCAQCAT/Pylyz5ZAPoierdJD9GyVHqJnq5QRPVuliujZKj1Ez1bpInq2Spey0rP1t1mHYpVvdfIPGSkpGkX+ZutrZfr06fz777+5fjczM2Pq1KmloEggEAgEAoFAIBAUhdS0/Md7KAv85xpbq1atKm0JAoFAIBAIBAKBQFD0b7YEAoFAIBAIBAKBQJA//7meLYFAIBAIBAKBQPDfIK2MpxGKni2BQCAQCAQCgUAgkANiNEKBQCAQCAQCgUDwVfJnp47FKt/uzDkZKSkaIo1QIBAIBAKBQCAQfJWkpZftNELR2PrKKKtzlUDGfCVldZ4kyJgrqSzPVQLQs0Gz0hVSRI7fuw6U/Xm2yupcVWFhD8vuHGGQMU9YGb52/hfm2Sqr9R8m5gkrVcpy7ENG/dctw/oflJF5tso6orElEAgEAoFAIBAIvkrS0kpbQfEQA2QIBAKBQCAQCAQCgRwQjS2BQCAQCAQCgUAgkAMijVAgEAgEAoFAIBB8laSW8QEyRM+WQCAQCAQCgUAgEMgB0dgqo3QxM8M/IICQkyfZtHkzmpqaX2yjr6/PhYsXqVixovQ3Y2NjvA4d4rifH/6Bgdja2cnRhy74B/gRcvIEmzZvzNOHguxUVVVZ4eFOYJA/QcEBrPBwR1VVNVtZbW1tzpw9jaWVpYz0+hNyMoRNmzd9Rm9uOwUFBVxdXQkJCeH076dxcHAAoF79evj5+Un/AgIDCAsPw6KHBQA/jP6BoOAg/P392bN3DzVr1iy2L/nRprMpG3292Bbgw9x1HpTT0Mjtn01PNvh6ssHnACv376KeURO56ckPecZOw4YNuf3PTfz8jkn/6tSpLVv9Xbrg7+9HSMgJNm0qQH8+dlpaWmzevInAQH+CgwMZN25srrLVq1fn2rUrNG3aVKbai0J6ejqz13ux88jZUtl/ca6X2c/b36XnLUD79u3xPXoUf39/vL29adbs02iggwcPJig4GP+AAHbs2JHtOvs1+PWRvO4D8qQwmguyK+h4fKR6jRpcu35d5rEv7/ru178/P+3c+dVoLmrsA6ioqLB7zx4sray+Cl8+klf9t2vfHp+jR/Hz9+dwHr7Iis5mZhwPCCD45Ek25KM/PxtVVVWWe3jgHxSEf3Awyz08pPesRo0b43noEP5BQXgdPkz7Dh3kor80SUuTFOuvtClzja0bN27g4eEhk23NnTuXJ0+eFNo+MjISMzMzmey7OFSqVIkVHh6MHzeOrmZmPH78mFlz5nyRjb29PQe8vNDT08tWbvPWraxdvZqeVlaMGD4cZxcXDA0N5eKDh4c748dNoKuZORGPI5g9Z9YX2U2aPBFFRUV6WFjRw8IKNVU1Jkwcn638qtUr0dLSkpFeD8aPG09Xs66ZOmZ/kd1gh8HUrlOb7t27Y2Ntw8iRI2nWrBn/3v8XKysr6d/Zs2fx8fEhMCCQb7/9lgEDBmBvZ4+lpSUBAQF4rJRN/OdEu2JFpi1zY+nk6Yzt0ZuYiCeMmDE1m0212rUYOcsR11ETmNx7APu37MB542q56MkPecdOq1Yt8fHxxcqql/Tv4cNHstc/fgJdu5oTERHB7NkF6M/DzsnJkZiYGCwsLLGxsWXIEAdatmwhLauqqsLatatRVlaWme6i8iDyKcPn7yTwwq1S2f+nczLjWhjx+DGz87he5mcz2MGB2nXqZJ631tLzVllZmQ0bNzJ3zhwsLS3ZsGEDq9esATIe9mfMnEn/fv2w7NGDyMhIHJ2cZO6XvO4D8qIwx+Jzdvkdj4+oqqqydu1amce+POu7fPnyLF6yBNf580EiuwfD0oh9gJYtW3LY25vWrVvL1Bd51H9WX6wsLdmYwxdZ6584bhzdMut5Zj7687KZOHkySoqKWFlY0NPCAjVVVcZPnAjAth07OLB/P5bduzN+7FjcFi+mStWqMvdBUHTKXGPr33//JS4uTibbunjxIunp6TLZVkli2qkTN27cICwsDIA9e/bQu3fvQtvo6OjQzcKC4UOHZiujoqrK+nXrOH/+PAAxMTG8ePECPX19Ofhgyo0bNwv04XN2ly5eYuOGTaSnp5OWlsbt27epXq2atOzkKZMIDQ0l9G6ojPQWXOefs7OwsMDL04vU1FQSEhI4evQotna22cq3adMGS0tLnOc5A/Ds2TNcnF148+YNADdv3KRaFh9lScuO7bl/8xZR4Y8BOP6bJ51tsr+VTE5KZr3LQl4+ew7A/Zv/ULFKFZSUS+7zT3nHTqtWLalXrx7HjvtyxMdb2sMoM/2mhdRfgN3ChW4sWbIUyDifVVRUSEh4LS3r5ubGwYOHePnypUy1F4W9/n/Sz7w1PTqUTg9bca+XGeetZ47z1o7k5GTamZhw+/ZtAGrWrEl8fDwAigoKKCkpoampiUQiQa1cOT58+PBV+ZXffUCeFEbz5+zyOx4fcVu0iINeXrx88aLEtRe1vnv26kVsbCxLlyz5qjQXJfYBvv/+e9yXL+f6tWtfjS/51X9ycjLtTUz4J4svL7P4Iis65tC2Nw/9BdlcuniRjRs2SO9Z/9y+TbVq1ahYsSL6BgZ4H8qYJ/H5s2fcvXuX7777TuY+CIpOiQ6QkZ6ezsqVKzlx4gSKiooMGDCATp064erqSnx8POrq6jg7O2NsbMycOXPQ1NTk9u3bxMbGMnHiRLp168b69etJTExky5Yt6Orq4u3tTXx8PF26dKFXr14sWrSIxMREXrx4wZgxYxg0aBDx8fE4Ozvz8OFDVFRUmDNnDjdv3uTp06eMGTOGvXv35ptC8c8//+DsnPHg26hRI+nv9+7dy7WvAQMGYG5uzs6dO6lduzaJiYlYWloSFBSUK72tOOjr6xMdFSVdjomORltbG01NTelDeUE2T58+ZfzY3GlHSR8+4HnggHR50KBBaGhocPXKFZlp/4iBvj7RUdHS5ejoGLS1tbL58Dm7s2fPSX+vVs2AkaNGMHdOxrHq2LEjJiYmDBs6nH379shAr0EOHbnr/HN2BvoGREdnWRcTTaPGn2IKYN68eaxcuVK6zXv37knXqaioMHvObPz8/IrtT15U1dfjWXSsdPl5TCwaWlqU09Dg3du3ADx9EsXTJ5/iavTcGVw8eZqU5BS5aMoLecdO4rt3+PoeZd/efdSuU5sDB34j6kkUN2/elI1+A/3scZCf/s/YpaamsmbNaqysLAkMDOLhw4yJlQcM6I+SkhL79x9g0qSJMtFcHFxH2wBw/vq/pbJ/gxzXwrzO3YJsDPRzHIeYGBo1bgxASkoKVapU4djx41SsWJHJkyYBEB4ezvbt2wk5eZKEhARev36NvYxTsuV1H5AnhTkWn7Mr6HgMGDgwM/b3MynzWMgKedb3vr17AejTt69MNZdG7ANMmTIFgIkTZXf9kWf9f/TlaB6+yFO/ViH0f7Q5d/ZTCrZBtWp8P2oUznPm8PLlSyIjIrDv25eDnp7UqFGDNm3acPtW6WQSyAsxQMYXEBAQwJUrVzh69CheXl4cPnyYcePGMXToUI4ePcrcuXOZOnUqSUlJQEbPyr59+9iyZQsrVqxAW1ubKVOmYGZmxvjxGSk/sbGxeHt74+TkhJeXFxMmTODQoUP8+uuvrFixAoB169ZRs2ZN/P39WbFiBWvXrmXMmDHo6Oiwffv2AnPVZ8+ezYwZM/D29qZ69erS3/Pal4KCAra2tvj6+gIQFBRE586dZdrQgow86rx65FJTU7/IpiDGjR/PNCcnRo8aJfM3sgCSQuorjJ2RkRGeXp7s2rWbkydPYmBggMuPzjhOcyRNRjPhSRQkhdSbv13OdRIk2cq3bNWSSpUr4XPEJ1f5SpUqsXv3bt6+fYvHCvmkEeanPa86VC1XjrnrPNCvVYP1zgvloic/5Bk7AD+6uLJn9x7S0tJ48O8Djh07jrl5V9nplxRSfyHsHB2daNGiFRUqlGfq1Cl88803ODg44OzsIjO9ZZ3CxEFBNjnXSXKUff78Oe1MTLC3t8dj5Upq166NqakplpaWdGjfnrZt2hAcHMzKVatk6ldJ3AdkjSzO3fyOxzdGRhmxP2+ezHXDf7e+ZR378kLe9f/8+XPam5jQR06+yEq/kZERB7y82L1rF6cy71ljfvgBSysr/AIDmTZ9OqdOnSI5OVmm+gXFo0QbW5cvX8bS0hIVFRU0NDTYt28fL1++pHv37gA0b96c8uXLS9/Qfvvtt0gkEho0aJCtizorTZo0QUkpo4Nuzpw5fPjwgW3btrF27VoSExOl+/3YFduwYUMOZOm9KYgXL17w9OlTvv32WyAj3/cj+e3L3t6eY8eOAeDt7Z2tjKyIiopCV1dXuqynp0d8fDzv3r37Ipu8UFFRYd369djY2GBvZ8edO3dkptvRaZp0wIGBA/ujq6uTRZ9unvqiop4UaGdt3Ys9e3/F3X0FmzdtBsCqpyXlyqmxa9cv+Pkdo6lxU+bNm4ODw+Av1OsoHbRi4MCBharPguo95zpdXV1iomOky9a9rDl86HCui22jRo3w9fXl1q1bjB0zVm4X0WdRMVTW+ZTnXVlXh9fxr/iQw8eq+nqsPLCL1LQ05g79gbevX+fclMwpqdhRUFBg4qQJaGQZGEQikZCcUrw6d3SUrf5OnUzR0clYl5iYiK/vUb755hv69LFHU1OTw4cP4ud3DB0dHdauXSPTxmJZo7jXy7zP22i0tLSwsPiUYnr71i3u/PMPDRs1wrxbN04EBxMXF0d6ejq7f/2V9u3bf1V+lRSOTk4lcB2Npo/9x9g/jJ+fHzq6uqxdtw5zc3OZ+FFW6jsrpRH7X6sv+aGlpUX3EvAlKioKnax1mY/+gmx6WVuza+9eVri7s2XTJqmdgkTCmFGjsLKwYPq0aejr6xOemYr4XyEtXVKsv9KmRBtbSkpKSLJ8/BkREZHrwTI9PV3aiv/YIyQp4INRNTU16f/Tpk0jODiYunXrMm3atHz3++DBg0L1eEgk2d/0KyoqfnZf1atXx8DAgKCgIOLi4uQyqs3ZM2do0aKFdOCKwQ4OBAcFfbFNXqxZuxZNLS362NvzJDJSprrXrF4rHXDAzrYPzbPoc3BwIDjoRK4yZ8+cy9eua1cz5i9wZeiQ4fj6+ErL/LRjJ9916iLd180bN1m6dDl79+77Qr1rpINW2Nna0bxF8xw6gvPQezZfu+DgYPr174eioiLa2tpY21gTlOWYmJiYSL+X+4ienh77ftvHuvXrWLRokcx66vLiyrkLNGxujEGtjNEOrQb148+Q09lsymmos3zPTv4ICmGF42yS5NDrmRclFTtpaWl0Mzdn0OCBQEaKoaVlD/z9A4qnf00W/XZ9aN48h67gPPSfPZevXc+ePZk2LSNVR0VFhZ49e3LhwgXc3BZhZtZVuq+nT58ybZojJ06EFEt/WebsmTN5xEHu62V+Nhnnbf8s560NQUFBpKamssLDg1aZgwDUr1+funXrcu3qVW7dukUXMzPU1dUB6GFpydWrV2Xul7zuA7JkzerVWa6jtp89FlC04+Hm5oZZly7SfT2NjWXa1KmcOJH73CoKZaW+c+op6diXpy/yqP+S8uVcHtpO5NBWkI1Z1664LljA90OGcNQne/bLkuXL6ZbZYGzZqhX1GzTg/LlzCL4eSvSbrTZt2vDrr78ycOBAUlJSmDZtGhKJhKCgILp37861a9d4/vw59evXz3cbioqKpKTk/X3I+fPn8ff3R1dXl72ZOdCpqam0bt2a48eP07BhQx48eMDo0aMJCQlBUVGxwO7lihUrYmBgwOnTp+ncubO0x6qgfSkqKtKnTx8WL17MkCFDilJNnyUuLo6ZM2eyecsWlFVUCA8PZ7qjI02bNmW5uzs9razytSmIFi1bYtWzJw8fPOBg5seWAO7Ll3PmzBk5+DCLLVs2oayiTHj4Y5wcpwPQtGlT3N2XYWXVq0C7ec7zkEgkuLsvk273r7//xvXH+TLV+knvTLZs2ZKpIxwnR6cset2xylLvednt2b2HWjVr4R/gj7KyMvv27ePixYvSfRjWNiQyRwN3ypQpqKurM+L7EYz4fgQASUlJ2NpmH1hDFrx68YK1c12Zu2ElysrKRD+OZNUsZ+oZNWHqkvlM7j2AXkMGUtVAnw7dzOjQ7dPInPOGj+F1/CuZa8oLecfO1KmOLFm6mL59+6KoqIDbwkU8+PeBfPQrZ+py+oz+HHZLlixhyZLFBAb6AxAYGMT//vezzDT+l8h+TqpknpOOBZy3n2wA9uzeTa2aNfEPCMh13o4ZPRpXV1eUlZRISkpiytSpxMTE4OXpSfXq1Tl67BhJSUk8efKEGdOny8UvWd8H5ElB9SyL41ES2v8L9S3P2Je3L7Ku/8TERMaOHs2PWXyZKgdf4uLimD1zJhsztT0OD2dGpv6l7u5YZ+rPywZgrrMzSCQsdXeXbvPvv/9mwY8/4jxnDkvd3ZkydSpvExMZO2pUqfWmyouy/s2WJL2Eh+Nbs2YNJ0+eJC0tDQcHB0xMTFiwYAHx8fEoKyvj4uJCy5YtmTNnDm3btpWm4TVs2JDQ0FAePXrEmDFjsLCwoE6dOly6dInly5cD8PPPP7Nnzx5UVVVp1KgR165d4+eff6ZixYq4uLgQFhaGkpIS8+bNo3Xr1ixZsoQzZ87w008/UaNGjTz13r9/n7lz55KSkkLz5s05c+YMJ0+ezHdftWrV4v3795iYmBAUFJStS7sw1K5Vq3gVXIo8Cg/HsFad0pZRZMLCH2JYy7C0ZRSJsPAwAHo2kM/8IPLm+L3rAGU2fsLCM1KfDQ3LqP6wh3D70OcNv1a+6YNhGb52hoWHl9lr/6PwcIAyW/9hmfpF/ZcOZTn2IaP+65Zh/Q8y4+drx79N8aZdsrx8UkZKikaJN7b+66Snp3PmzBl+++03tm7d+sXly/pFp6w+LINobJUmorFVuojGVulSlh84/wsP+1B2773/hfovq3UPorFVUhxrXbzGVq+/SrexVaJphF8r06dP599/cw9LbGZmxtSpU/MokT9Lly7l1KlT7NixQ1byBAKBQCAQCAQCQRlENLaAVTIcktfZ2Vk6L5dAIBAIBAKBQCD4/4tobAkEAoFAIBAIBIKvkq9h+PbiUKJDvwsEAoFAIBAIBALB/xdEz5ZAINPPELoAACAASURBVBAIBAKBQCD4KhFDvwsEAoFAIBAIBAKBHPBuaV6s8nZXZDO5eVERaYQCgUAgEAgEAoFAIAdEGuFXxnzjLqUtocgsvHGqzM6TBB/n2Sqb82WESedaMSxdIUXk4zxhZTV+pPNsleH4KavaITP+y/g8YU3LaOzfzIz9sj7H3z27NqWspGg08L4MwJ+dOpaykqLR7sw59jXvVtoyiszga8F0qNOwtGUUmT8ehpa2hEKRWsZz8ETPlkAgEAgEAoFAIBDIAdGzJRAIBAKBQCAQCL5KUinbA2SIni2BQCAQCAQCgUAgkAOisSUQCAQCgUAgEAgEckCkEQoEAoFAIBAIBIKvkrI+QIZobP0HqG/aDvOpP6CkokzsvYf4zPfgw9vEbDZtB9rSpn9v0knnZUQUvgtX8vZFPACzfj9CQuwzqe35Xw5w00/+cxJ0MevCrFkzUVFR4e7du8yeNYc3b94U2k5VVZVFi91o1swYiUTCtWvX+dHFlQ8fPqCqqso857m0bt2KcuXU2b9/P9u37ZCxfjNmzZqVRdesfPTnbaegoICLiwvfffcdikpK7Ni+nb1792Yr269/fywsLPhh1CgZ6O2SQ8fsAuo7t112vYrs2L5Dqrd8+fIsdFtI/fr1UVNVY+PGjXh7e2fb7qpVq7gbepcd24t/HOQVO6qqKuzf/1u2bTRs1JClS5ez86edRdApvxgxNDTEfcUKKlWqxNu3b5nu5MSDBw8YP3481tbW0m1XqlwZDQ0NmhoZUb16dZYsWUK16tV5+/Yt27dt4/jx4zLxoyg+tG/fnrnz5qGspMT79+9ZsGAB169njA43ePBgvh8xgtTUVCIjIpg1axYvX7784mNQXNLT05mz4SANauoxyta0xPefE1OzLkybNRNlFRXu372L66w5vM1xLPKzUVBQYJ7bQlq3awvA2VOnWbVkGQDfdTVjyeqVRD+Jkm5neL8BJL59WyJ+telsynCnKSirqBAWeo+18xbwLse+u9j0xP6H4ZCezod379m62J1/b/1TIvryQqPVt1QZMhGJsgofwu8Tu3Exae+ya1apWRed0TNRUNeEtFRityzjw8O7IJFQZegkNFp1hPQ0kqIjeLplKakJ8SWivUK79tQYOxYFZRUSHzzgofsyUhOzPzfUnDiJyp27kJKQAMD7iMfcXzAfAKMdO1FQVSE9OQWA58FBROe4dsoTA9O2NJs8CkUVZeLvP+LPBatIyfHc85HqXTrQfvFsvL7tLf2tx75NKKqqkpaSoT/ML4Q7u7xKRDtAhy7fMW7mdJRVVHhwN5Slc+aR+Cbvc83FYzkPQu/x20//y7Vu6ZYNPI99yuoFi+QtWVAMRBqhjHnz5g329vb06tWLhw8fMm/ePLnuT71ieWwXzeKA03w22AznZWQ05tPGZLPRb9yADsMH8NOwSWy2H0nc40jMJo4EoLJhDd69SmBr/9HSv5JoaFWqVAkPD3fGj5tAVzNzIh5HMHvOrC+ymzR5IoqKivSwsKKHhRVqqmpMmDgegDlzZ1OhQgWse/Wmt40tw4YOpUWL5jLW78H4cePoamZGxOPHzJ4z54vsBjs4ULtOHbp3746NtTUjR46kWbOM4ZPLly/PkiVLmD9/PhJJ8T8M/aRjPF3NumbW4+wvshvsMJjadWpn6rXJpnflqpXERMfQ06onDg4OLFi4AD09PQDq1qvLvt/2YWllWWw/PmmUT+wkJLzGyqqX9O+Apyd/Xf6LXb/sKqJO+cXI2nXr2Lt3L93MzVm7Zg2bt2wBYMuWLVhZWWFlZcXAgQNJTExk8qRJQEaD9+rVq5h37crgQYMYO24cjRs3LrYfRfFBWVmZDRs3MnfOHCwtLdmwYQOr16wBoHqNGsyYOZP+/fph2aMHkZGRODo5ffExKC4PIp8yfP5OAi/cKvF950XFSpVY5OGO47gJ2JiZE/k4gmk5Yr8gG2t7Owzr1sa+uyV9e/SktYkJ3TPPy+atWvHL9p/oZ9VL+ldSDS3tihWZtsyNpZOnM7ZHb2IinjBixtRsNtVq12LkLEdcR01gcu8B7N+yA+eNq0tEX14oaldAd7IrUStmEzapL8kxT6gydFI2G4mKKtXnb+Sl9688nj6EOK+d6DtmPBRrd7VBrW5jHk8fQvi0QSRHR1D1+2klol2pfAXqzp3H/R9duD5kMB+io6gxdnwuO61vjLi/cD43R43g5qgR0oaWgpoaagYG3BzxvXRdSTa0VCuWp93CGZyb4cYx25G8iYym+dS8X0hq1axGC8cxkOU+qqimhmYNA/wGjMV/wDj8B4wr0YZWhUoVcXZfxrwJkxlk3oOoiAgmzJqRy65W3Tps2LOLLpYWeW7HYcwPNGvdWt5yvwpSi/lX2ojGloy5c+cOKioqHDt2jGfPnhERESHX/dVt34aoW6G8ePwEgMuePhhbdc1mE33nHuuth/DhzVuUVJTR1qlC4quMN1U1mn1DeloaI39Zx/iDP/Hd2GFIFOQfFqadTLlx4yZhYWEA7Nmzh969e3+R3aWLl9i4YRPp6emkpaVx+/ZtqlerBoC9vR2rV60hLS2N169fM3DQYB48eCBD/Z24ceNGIfTnb2dhYYGXpyepqakkJCRw9OhRbO3sAOjVqxexsbEsXbJERnpNC6k3f7sMvV459NpSvnx5TE1NWbt2LQAxMTHY9rYlPj7jDe2wYcPYv38/fsf9ZOiL/GLnI7Vq1WLSpEk4Ok4nJfPt55fplF+M6OrqUrduXY76+gJw+vRpNNTV+cbIKNu25zk78/vp05w+fRoAo6ZNOXjwIABv377lwoULWFjkfSP/Ej+K4kNycjLtTEy4ffs2ADVr1pTGjKKCAkpKSmhqaiKRSFArV44PHz4UqFMe7PX/k37mrenRoWmJ7zsvOnQy5faNmzzOrOcDe/bQM8exKMhGQVGRcuXUUVFRQVlFBWVlZWm9Nm/VEpMO7Tnof5xfvA7Qqm3JzTvVsmN77t+8RVT4YwCO/+ZJZxurbDbJScmsd1nIy2fPAbh/8x8qVqmCknLpJOioN2/H+/v/kBydcY+PDziEVqceuWySYyN5e+UPAN5eOkPUyrkAJEU85NmudaSnJAPw/t87KOnol4j28m3b8ObuHd5HRgIQe8SbKt2yz3UlUVZGo359DAYNxviXXdRftBgVHV0ANBs3JvXdOxqtXIXxL7uoNWkyEhWVEtEOoN++FXG37/E687nnvtdRDC275rJTVFOl/ZLZXFm1LdvvlY0akpL4ji6blmHltZ2WM8ahqFpy+tuaduTOzZtEhmXMj3l4z290722dy67PUAd8Pb046ReQa10Lk7a062TKkX375a5XUHzKZGMrJSUFFxcXBgwYQNeuXZkwYQIPHjygR48eDBo0iBGZqSfLli3Dzs4OGxsbfvnll3zLvn//Pt99JScnM3PmTGxtbbG1tcXT0xOAiIgIBg0ahI2NDW5ubrRv3564uDjmzZtHaGgo48aNY/Hixdy6dYuFCxfKrS7K61XlVcxT6XJC7DPUtDRR1VDPZpeWkkqjLt/iFOxFrZbGXD3iD4CikiIP//yb3eNn8/OIqdTr0AaTwXZy0/sRA319oqOipcvR0TFoa2uhqalZaLuzZ8/x6NEjAKpVM2DkqBEcP+5P5cy0qY4dv2X//n34+R2jm7k5CQmvZaz/U7pNdHQ02tra+ejP285AX5/o6Cy+xcSgr59xs927dy/r168nKSlJRnoNctRjfnrztzPQN8ihNxp9fX0MDQ15+vQpP4z+gYOHDuJ71BcjIyPpeTXfdT6+Pr4y8SNDo/xiJyszZ05n165dRGU5fl+uUz4xYmBgwNPYWNLT07Ovy+xNBKhXvz7du3dn9epPb/+vXbtGv379gIzeqC5duqCjo1NsP4oa5ykpKVSpUoU/L15k7rx5bNu6FYDw8HC2b99OyMmTXLp8GRMTEzZt3FigTnngOtoG606y6xEvLnr6+sRkienY6Bi0tLXQyHIsCrLx8TpIwqtXhFy6wKnLf/I4PJzfQ04CEB8fj+feffS17Mk6dw/Wbt+KbpZ4kidV9fV4Fh0rXX4eE4uGlhblNDSkvz19EsXl02ely6PnzuDiydOkJH/5ixBZoFRFl5S4T5pT4p6iqKGJQrlPmlUMapLyMg7diS7U9NhFtQWbkCgqAvA+9CYfMieUVdDQovKAH3hzXv5ZJQCqOrokPf303PDh2TOUNDVRVP/03KBSpQqvrl4h4qcd3Ph+OG9u36bh0oyUU0V1dRKuXuGe64/cHDMaFV1dao4dVyLaAdR1q5IY8+nTh8TYZ6hoaaCU47mnrcs0/j14nPj7D7P9rqyhTuzl65ybuYgAh4mo6+nQbErxU/ULi66+HrHRMdLlZzExaGppoa6pkc1u9YJFBPsey1W+io4O01ydWeA4g7S0r6HfRv6Inq1S4OrVqygrK3PgwAGCg4N5/fo1v//+O48ePcLDw4Off/5Z2ijy9vbm4MGDhISE8Ndff+VbtqB9vXr1iiNHjrBt2zb++usvANzc3Ojduze+vr40bdqUFy9eULlyZRYvXoyRkRFbt27FxcUFIyMj5s+fL7e6yOiFyv3lYFpaWq7f7p46z4rvbDm9dRdDt65AIpHw96Hj+C3fQPK797x//ZY/dnvR2Ez+3yVIFBSyPSh+JDU19YvtjIyM8PTyZNeu3Zw8eRIlJSWUlJSoWasmgwY5MGzY9zgMGUz37rKbpV4W+nOuk+RRXlZIFCSF1Ju/Xc51EiSkpqaipKxEzZo1efP6DX379GXypMn86PojRjl6WWSFPGPnI/r6+nTq1Imf//dLqerML0YkCgq5znqJREJqlvN+5MiR/LprF69ff3rJMN3Jibr16hEQGIj7ihWcDAkhKTm52H4UJ86fP39OOxMT7O3t8Vi5ktq1a2NqaoqlpSUd2renbZs2BAcHs3LVqgJ1/n8gv3pOK8SxSEtNZfy0Kbx88YLvWrXFvN23lK9QnmGjMx4yHceOJ9gv44XD1b/+4trfV2hv2lFOnmQnv+tOXvcx1XLlmLvOA/1aNVjvLL8XmZ9DIpFAHprTszz8SpSU0Gj1La+CvHk8czjxfgeo5rIOiZKy1EZZrxo1lmzn3Z1rxPuXUCpbvto/1feH6GhCZ83kXeZLqej9v6FarRqq+vq8PH+eB0sWk/r6NelJSUTt3k0l004lox1AQSFv/amf9Nfvb01aaioPfQJz2T35/QIXXNxJSnhNWlIyt3f+Ro0u38pVclbyP0dzx3tOFJWUWLhuFesXLyPu2bPP2gu+DsrkABlt2rShQoUK7N27l4cPHxIWFkZiYiKVK1emevXqAFy4cIE7d+7w559/ApCYmEhoaCgODg55ls2P+vXr8+jRI0aNGkWnTp2YNSsj9/3y5cusyfy+wNbWFldXVzl7nTevomOp3vTTNxdaOlVJfJVA8rtPvXWVahigWaUSj69mfHdwxdufXi6OqGlrUd/UhNjQB8RmvvmRSCC1CClThcHRaRrdzM0B0NTSJPRuqHSdnp4u8fHxvHv3LluZqKgntGjeLF87a+teLFrshqvrAmnvyYsXL0hKSuLwIW/S09N5/vw5ISEnadmyJUFBwcXQ75RFvxahd+9m0aWXj/4oWjRvnqddVFQUurq60nW6urrEZOkBKC6OTo50M++WqTdnfRekt8UX6I0hNjbj7a6XV8aDQnh4OJcvX6Z58+bcuiWbb11KKnY+YmVlSWBgEG+/8JuVkoqRqCdP0KlaNdt2ssaPgoIClpaWWPfqlc1GTU2NmTNmSDUsXbaM+/fuFehTQfqK44OWlhYdOnQgMDDjYej2rVvc+ecfGjZqRPv27TkRHExcXBwAu3/9lcCgoAJ1/n8gJuoJxlliWkdPl1c5jkVBNl17WLBs/kJSkpN5k5yM78HDdLOyxPuAJwOGDuWnTZul5SQSCSkpBTfEZcWzqBgaGn9K1aysq8Pr+Fd8yHGuVNXXw3XbeiIePGLu0B9IKoXU0o8kP49FrcGnF0pKlauS+voV6R8+3XtTXjwnKfIR7+9npMq+vXQGJrigrFeNpMgwyhm1Qn/GUl567+alz54S054UG4tmkybSZZUqVUhJSCAtS5aPep26qNerx/OgT40ViURCekoKFTp8S+rbN7zOHMwGCaTL6bkhLxKjn1LFqJF0uZxOFT68SiA1i/46Nt1RVFPF8sBWFJSUUFRVwfLAVk5PcqZS4/okvXnLsys3pX6llaD+2CfRfNPs0zlaVVeXhPh43ueI97xo3NQIgxo1mOyc8U1s5apVUFBQREVVleVzXeSmubQRkxqXAiEhIcyYMQM1NTXs7e1p06YNBgYGqKmpSW1SU1OZOXMmPj4++Pj4cODAAfr27Ztn2bzeMHykYsWKHD9+nCFDhvDo0SPs7OxISEhAVVVVWk4ikaCkVDrt1gcX/qK6cWMq1cz43qRNP2tCT53PZqNZtTJ9V7iiXkEbAOOe5jz9N4x3rxLQrVebLhNHIFFQQElVhbYD7bgdeEouWtesXisdeMDOtg/NW7TA0NAQAAcHB4KDcqdQnD1zLl+7rl3NmL/AlaFDhmd7WE5OTiYk5CR9+toDoK6ujmnHjly/caOY+ldLBx6ws7XNQ1fuh8GzZ87kaxccHEy//v1RVFREW1sbaxsbgmT4QLlm9Zoseu1o3qJ5Dh25G55nz5zN1y5Db78seq0JCgoiMiKSmzdv0qdvHwCqVKlCq1atuFHM+s7uS8nEzkdMTNpy/o/zuX7/vM6SiZGYmBjCwsOlow526tSJtLQ07mY27ho1asSrV6+IzPwm4yOOTk4MGToUgNq1a9PN3JyAgNzfAxRWX3F8SE1NZYWHB60yP/CuX78+devW5drVq9y6dYsuZmaoZ6Y19bC05OrVqwXq/P/AH2fOYdyiBTUz67m/gwOncsR+QTZ3bt3GomdPAJSUlOjczZwbV6/y9s1bBg4bgrllxjdHjb5pglEzY86dPlMifl05d4GGzY0xqFUTAKtB/fgz5HQ2m3Ia6izfs5M/gkJY4Ti7VBtaAInX/kStgRHK+jUAqGDRhzeXstfX2yt/oKxjgGqdjIZBuSYtgHSSY6NQrdMQgzkexKxbUKINLYD4y5fQbPINapkvp3V72/Li3NlsNunpaRhOnYZqZsqvrq0diQ/+JenZM1SrVqXWhIkZ32kpKKDffyBxWTID5E30hb+pbNwYrcznnvp9exF5+kI2m8Ahk/HrOwb/AeM4PdmZ1A9J+A8Yx7tncZTTrUJLpzEoqqogUVCg0dA+hAfln+Ekay6dO8c3LZpR3bAWALYOAzl7IqRQZW9dvYZdx85838uW73vZcmTffkKO+/2nG1r/Bcpkz9aFCxewtLSkT58+REREcPHiRdq3b5/Npl27dnh6etKlSxeSkpIYPHgwCxcuLFTZrISEhODr68vatWsxNTXlwoULREdH07FjR7y9vRk2bBgnTpzIs3dMUVGxSB/WfwlvX8Rz5McVDFi1EEVlJV5EROHtvAyDJg2wWTCTrf1H8/jKTc7u2MP3/1tLWkoqr58957dpGSfm6a27sJo7lQmHdqKopMTt4N/5+9Dnh4IuLnFxccycOYstWzahrKJMePhjnBynA9C0aVPc3ZdhZdWrQLt5zvOQSCS4uy+Tbvevv//G9cf5zJk9l/kLXAk+EYiCgiK+Pr74+/nnqaXo+meyZcsWlFVUCA8Px8nRMYt+d6ysrAq027N7N7Vq1sQ/IABlZWX27dvHxYsXZaYxf73KmTqcPqM3u92e3XuoVbMW/gH+ufSOHTMWt0VuDBkyBAUFBdavWy/TxlZuX+QXOwCGtQ2JjHgiA53yi5EpkyezfPlyJk2ezIcPH5gwYYL0BZChoWGuhhbA0iVLWLN2LX369CE1NZXp06dn+57qS/yQhQ9jRo/G1dUVZSUlkpKSmDJ1KjExMXh5elK9enWOHjtGUlIST548Ycb06cU6Hv8FXsTF8ePMWazOjOmI8MfMc5xOk6ZNWei+jH5WvfK1AVjhtph5bgvxDQkmNS2Vi+f/4H9bt5OWlsaUH8Yyz20+ExynkpqSysxJU4gvoaH2X714wdq5rszdsBJlZWWiH0eyapYz9YyaMHXJfCb3HkCvIQOpaqBPh25mdOhmJi07b/gYXse/KhGdWUl99ZLYDW4YzFwOysokx0QSs24BqnUbozvRhcdODqTGxxG1fCY6Y2ejoFaO9OQkotxnkZ6cRJUhE4GM4d/JHMUwJfYJUe65R1aVNSnx8TxcvpT6botRUFbi/ZMn/LtkMRoNG1Jn1hxujhrBu0ePCFu7hobL3JEoKvDh6TPuZ35/Huvrg6qBAcY7/weKiiRcuUrkrp/lrvsjH17Gc3H+Sjp6/IiCsjJvIqO44LKCSk0aYDLfCf8BBX8/9u/B42hW16fHb1tQUFIk9vI1bm0ruQbvy7gXLJk1lyWb1qOsrMyTx49xmz6bRk2NmLNsMd/3si0xLYKSQZJeULfOV0poaCgzZmQMk6msrEy1atVQVVXlypUr0u8ukpOTcXd3588//yQlJQV7e3vGjBmTZ9k6dergmPlgkJPk5GRcXFy4efMmqqqqmJubM3HiROLi4nB2diY6OpomTZpw+PBhQkNDuXjxIhs3bmT37t28fPmSoUOH0rhxYzw8PArl23zjLjKoodJh4Y1TGNaqU9oyikxY+EMMa9UqbRlFIiw8Y1Qjw1qGpSukiISFhwGU2fgJC89Iwy3L8VNWtUNm/N8+VNoyis43fWhaRmP/Zmbs92zQ7DOWXyfH72Wkwt2zK7nRF2VJA+/LAPzZqWS+r5M17c6cY19z2X1PXdIMvhZMhzoNS1tGkfnjYejnjb4CtjcrXoyMuV70T0hkQZns2WrYsCFHjx4t0EZZWRkXl9zdqoUpm3M77u7uuX6vXLkyWzNHzgI4fPgwACYmJpiYmAAZKYjHjuUeSUYgEAgEAoFAIBD89ymTjS1Z8/79ewYMGJDnuilTptC1a+75GwQCgUAgEAgEAoF8Kcnh248ePcqWLVtISUlh+PDhODg45Gl3+vRp3Nzcso1knB+isUXGCF0+Pj7F2kZoaNnoihUIBAKBQCAQCATZiY2NZc2aNRw+fBgVFRUGDhyIiYkJ9erVy2b3/PnzPLPe8qNMjkYoEAgEAoFAIBAIBLLijz/+oF27dlSoUAF1dXUsLCzyHLHXxcWFSZMmFXq7omdLIBAIBAKBQCAQfJUUN40wISGBhISEXL9ra2ujra0tXX769ClVs8xhqaOjk2tk5V9//ZUmTZrQrFnhBwUSjS2BQCAQCAQCgUDwn2TXrl1s3Lgx1++TJk1i8uTJ0uW0tDQkkk8TKKenp2dbvnfvHkFBQfzyyy/ExMQUev+isSUQCAQCgUAgEAi+SorbszVi+HDs7Oxy/Z61VwtAT0+Pv/76S7r87NkzdHR0pMsBAQE8e/aMPn36kJyczNOnTxk8eDD79u0rcP9lcp4tgUAgEAgEAoFA8N9nXTHn2ZpayHm2YmNjGTRoEAcPHqRcuXIMHDiQRYsWYWxsnMs2MjKSYcOGidEIyyJLjMvuMPPON0LK7KS0kDExbe0yOrHrIzGpcanycVLjshw/ZVU7ZOgvq5MCQ+bEwGV1UuZv+gBgWb9pKQspGv73bwIwq+l3paykaKy4+TsAtQ3rl7KSovEo7H6xJ6wtTcZcD8bYsOxee26EPSxtCV8Vurq6ODo6MmzYMJKTk+nbty/GxsaMHj2aKVOm0LRp0a5zorElEAgEAoFAIBAIvkpSKbkkPGtra6ytrbP9tmPHjlx21atXL1SvFoih3wUCgUAgEAgEAoFALoieLYFAIBAIBAKBQPBVUtwBMkob0bMlEAgEAoFAIBAIBHJA9GwJBAKBQCAQCASCr5LUMj5wuujZ+g9Qz9SEHw7uYJzvL9ivdEVFQz2XTeuBvRlzeCejD/9Ev3VuqFeqIF3XaoANow5sZeyR/2GzdC6KysoloruLWRf8A/wIOXmCTZs3oqmp+UV2qqqqrPBwJzDIn6DgAFZ4uKOqqgpkzPr966+/4O9/nIBAf2ztestArxn+AQGEnDzJps2b89Sbn42CggI/urpyIiSEU7//zmAHB2mZdu3bc/T4cfwDAti3fz+NGzeWrnOaPp2gEycIOnGClatWoaamVgz9XfAP8CfkZAibNm/6TH3ntlNQUMDV1ZWQkBBO/34ah0wf6tWvh5+fn/QvIDCAsPAwLHpYZNvuyJEjCQwKLLL+3BpF7BQUOx8ZMXIkAUFBxfZB1n59RF9fnwsXL1KxYkW5aMyJqVkXDgX44XvyBKs2b0QjD8352SgoKOCyeBFHTgRy5EQg053nSst819WMc9ev4OV3TPqnrqFRIj4VRHp6OrPXe7HzyNnSlpKLNp1N2Xz0EDsCfZm3fhXqmvnX13T3xfQZNVy6rFlemzlrPdgR6MuGIwewGTq4JCRno5FpOxwP/Y+ZvrsZsmohqnncezsMssPJ+xecDv/M8PVL0Mi89yqpqtDPbTZOh3/GyfsX+rnNRklVRe6au3TpjL//UUJCAtm0aX3+184C7P6+cpHjfr7Sv969bQBo1KghXgf34+fvy7HjPnzXuZPc/Khh2pY+Xtvo7/M/zD1+RDmPuv9IrS4d+P4Pn08/SCSYTPuBvod30Pfgdrqtno9axfJy0/oR0y5dOOjvh2/ICVZuyufak4+NdvnyrNi4Ht+QExw45sug4cOkZb4xNmbXQU88/Y5xKMCfnrbFv2cJZEuZamxdvHiRoUOHFtp+9OjRxMbGcvjwYebMmQPA+vXrs01YVtZRr1ieXotmcshpAVttvudlZDRm037IZqPXuD4mw/uza9gUdtj/wIvHT/hu4ggAGnbtSOtBtuwdPZNtdqNQVlOh7dA+ctddqVIlPDzcGT9uAl3NzIl4HMHsObO+yG7S5IkoKirSw8KKHhZWqKmqMWHieABmzZrB1WvXsLTsyfBhj2nw7AAAIABJREFU37N48SKqVq1SLL0rPDwYP24cXc3MePz4MbMyY6owNoMdHKhdpw4W3bvT29qakSNH0qxZM7S0tNi6bRvLli7FskcPXJyd2bhpEyoqKlj06EGnTp3oaWlJd3NzypUrx4iRI4us38PDg/HjxtPVrGtmPc7+IrvBDoOpXac23bt3x8baRurDv/f/xcrKSvp39uxZfHx8CAz41LBq1boVY8eNLZL2vDWK2Ckodj7SqnVrxo4bV2Tt8vQLwN7engNeXujp6clFY04qVqrEIg93HMdNwMbMnMjHEUzLETsF2Vjb22FYtzb23S3p26MnrU1M6G5lCUDzVq34ZftP9LPqJf1LfPu2RPzKjweRTxk+fyeBF26Vqo68KF+pIk7LF7F4kiOjLWyIiYhkxIxpuexq1K3Nsl9/omOP7MODj503i/eJiYy1tMWxnwOtO3WkbRf5PdznRKNiefovmsNuxx/xsBlKXGQUltOyX+OqNWlAp+ED2Dx0IqvtR/A8PBKLSaMA6DpmKAqKiqzpM5I1fUairKqK2Q9D5Ko543xczvjxk+ja1YLHERHMmj3ji+zq1KnNq/hX9LSykf75+PgCsGbNSrZv/wkrSxucHGewceM6lOXw8latYnk6u80geLobnr1HkvAkmrZTR+Vpq12zGu2cxiCRSKS/NbTtQZUmDTg8YAIH+44h4fET2k2Xzf0pPz5eV5zGT8CmqzmRERFMm533tScvm1muLiS+TcS2W3cc7PrQsXNnOpmZAbB6y2Y2r1lHf6teTPh+BDNdnKlpaChXf0qa1GL+lTZlqrH1pezYsQNdXd1sv12+fJnU1K+h6mVD7fatib4VysvHTwC44unLN1bZ5+qKuXOfLdbD+PDmLYoqymjpVOHdqwQAmlp35+KvB3mf8BrS0/FftJZbx07IXbdpJ1Nu3LhJWFgYAHv27KF379xvYwqyu3TxEhs3bCI9PZ20tDRu375N9WrVAFBQVERbSwuAcuXKkZqaSlpa0buhTTt14saNGwXqLcjGwsKCg56epKamkpCQwNGjR7G1s8PQ0JDXCQn8cf48AA8fPOD1mze0aNmSwIAA+mbOUq6pqUnlypWJf/myiPpNP6v/c3YWFhZ4eXrl8ME2W/k2bdpgaWmJ8zxn6W9VqlTBzc2NpUuXFkl73hpF7BQUO5BR7wvd3Fgmo3qXtV86Ojp0s7Bg+Be8QCsuHTqZcvvGTR5n6jmwZw89c2guyEZBUZFy5dRRUVFBWUUFZWVlPnz4AEDzVi0x6dCeg/7H+cXrAK3atikxv/Jjr/+f9DNvTY8OX98cWC07duDezdtEhT8G4Ni+A3Sx6ZnLrpfDIAK9DnM2IPukpPWMmhBy5ChpaWmkJKdw6fQZOvboXiLaARp0aEPE7bs8z7z3/nnAhxY9zbPZPPnnHit6OfD+zVuUVFQor1OVxPiMe+/Dv64Tsv1X0tPTSU9L48nd+1TQ1821H1liatox85qYMS/jnj37pL1ShbVr2aolqWlpeHruw9//KJOnTEJBIeNRslcvW4KDMp4fatWqSULCa7k8b1Vv34pnt+6RkFn3/3gepb5V7jlKFdVUMVs6mz9Xbsv2+8sHYfy5ejtpyckAPPvnHppyrvv2pqbcynJd8dyzB6sc156CbJoYGXHM2zsz3pM5c/IU3ax6oKKqwtZ167mYeR+IjYnhxYsX6OqXzAssQeEoc42tly9fMmrUKKytrXF2diYpKYmGDRtK12ftxTIzMyMyMlK67siRI9y6dQsXFxdCQ0Pz3P6bN28wMTHhzZs3QMYM0VZWVtLydnZ29O7dm3nz5klvsnv27KFfv3706tULOzs7Hj58KN3/tGnTsLCwIC4uTvaVAWjrVSUh5pl0OSH2GWpamrlSCdNSUmnQ5VumBB+gZktjrh8JAKBSreqoV6rAwC3L+OHgDkzHD+f96zdy0ZoVA319oqOipcvR0TFoa2vlSmkoyO7s2XM8evQIgGrVDBg5agTHj/sDsMLdA/Nu5ly8dIHgE4GsWb22WMdAX1+f6Kgo6XJMdDTa2trZ9BZko6+vT1T0Jz9iYmLQ09fn0aNHlFNXx9TUFABjY2MaNGiAjo4OACkpKQwbPpzzf/xBxUqVCAwsWhqegb5BjnrMrf9zdgb6BkRn8SE6Jhp9ff1s5efNm8fKlSul54+CggLr1q9j2dJlxMbEFkl7bl9E7HwudhQUFFi7fj3Lly4lJiamyNrl6dfTp08ZP3as9DiUBHr6+sRkiYnY6Bi0tLWypfMUZOPjdZCEV68IuXSBU5f/5HF4OL+HZMyzEh8fj+feffS17Mk6dw/Wbt+Kbgn12OWH62gbrDs1L1UN+VFFT49n0Z9i83lMLBpaWrlSCbe4LeX0Ub9c5UOv36SrrTWKSkqoqZfjWwtzKhWjB/pLKa+nw6uYp9LlV7HPKKelmSuVMC0llW/MOuJ8wovarYz560iGL/cv/MXz8Iznkwr6upgO6cvNoNNy1axvoJftGh6Tz7WzIDslRUXOnzvP8OGj6D9gMJ06dWT49xkpbR8bVqd/D2HL1k1s27qdtLQ0mfuhoVeVN7Gfnnvexj5DRUsjVyphpx+ncefgceLuZ5+49+mNO8Td/RcAFS1NWo4dwqPgMzLXmRU9A31ioj9z7SnA5sa16/Sys0NJSYly6up0s7Sgio4OSR+S8Pb0lJbpM2ggGhqa3LhyVa7+CL6MMtfYioyM5Mcff8TX15e3b9/y22+/Fbqsra0tRkZGLF68OFsDLSuampp07tyZgICMxsiRI0ewtbXl/v37eHp6sn//fnx8fKhcuTI7d+7kzZs3nDhxgt27d3Ps2DE6d+7M3r17pdvr1KkTgYGBVK5cuXiO54NEQYH0PCZ7S8/jAnfv1HnWfGfPma27GLR1OUgkKCopUrtdKw7PWMT/Bo6nXHktOk8uWqraF+vO44PHnG/BCmNnZGSEp5cnu3btlk4wt27dGrZt3Y5J2/Z0M7dg3PixNGtmXGS9CoXQUZCNgoICZFknAdJSU3nz5g1jx4xhwsSJ+Pn7Y9+nD3/88QfJmW/cAH7dtYtmxsYEBQayecuWIumXKEgKWd/52+VcJ0GSrXzLVi2pVLkSPkc+5cbPmj2LSxcvce7cuSLpzgsRO5+PnVmzZ3Pp4kWZ1ntOiutXaZBfTKRl0VOQzfhpU3j54gXftWqLebtvKV+hPMNGZ6QvOY4dT7BfRoP96l9/ce3vK7Q37SgnT8o+CgqSbHH9kdTUwj2c71i2kvT0dDb6eOK6eT1Xz18gJct1U95IJAp5yc+zcXH75DkWdupN8JZfGLVtZbaUtmpNGjB+1wbO/+bNnTMX5CkZBUnhzseC7Pbv92TBgkW8e/eO1wmv2fnTz1hYZE/x7PxdVzp/Z8648WNp376dbJ0go+7zqvyszz1N+luTlppK6JH8X1BqVdfH5ufVxFy9ze39PvnayQKFfDRnvfYUZLNqyRJIT8fz+FHWbd/GhXPnSUnKHu8jx49jguM0Jv/wg7Qz4L9CKunF+ittytxohK1bt8YwMxfV2tqaw4cPy3wfffr0YcOGDfTt25djx46xa9cugoODCQ8Pp3///gAkJyfTpEkTNDU1WbVqFcePHycsLIyzZ89m+0i9WbNmMteXlYTop1Rr2ki6/DFFMPnde+lvFWsYoFGlEpFXM/L2r3sHYOkyjXLaWrx+FkdoyFmS3iYCcOvYCTqOk09aj6PTNLqZZ6RZaGppEnr3U++inp4u8fHxvHv3LluZqKgntGjeLF87a+teLFrshqvrAnwz88YrVqxI6zatGTw4I/89LCyMc2fP0dakLdev3yiS9qioKJo3//SGWE9PL5fegmyeREWhkyWlVUdXl+joaCQSCYlv3zJo4EDpupOnThEeFkbjxo2RKCjwz+3bAOzfv5/vR4wotGZHJ0e6mWfcBHPXd279H31o0bxFnnZRUVHZ0nJ1dXWJyfJm2rqXNYcPHc52k7a3tyfueRwWFhaoa6ijp6eHn5+ftLe48L6I2PlIYWJnoZsbcc+fZ9a7Bnp6ehz386PnF9a7PP0qDWKinmCcJSZ09HR5lUNPQTZde1iwbP5CUpKTeZOcjO/Bw3SzssT7gCcDhg7lp02bpeUkEgkpKSX38F/WeBoVQ8MsLzGq6OrwOv4VHwoZG+qaGuxcsZo3mSnxA8b9QFR4hFy05kV8TCw1jT/d67V1qpCY495buUY1tKpUIuzqTQAue/th/6MT5bS1SHyVQLMeZti5OHJk6Tqu+cknfd/RcSrm3TJS7DQ1NbNl9eR/7YyieYu8r512dr25c+cudzOvwRKJhOTkZJSVlbH4P/buPK6m/I/j+KvlliVlmxKmwtjVWMY6hEK6bWQishvr2IosIbKWjFDWGWPLkmwVFdnGntlsjRlmaNNmUHbafn9UV7uk2+L3fT4ePR7uvZ9ze3+Pb+eec8/3fE/fPhw7Gkh6ejrR0dFcvHiJli1bcPnylRJt0/O4BDSz7fdU1azN66SnpGRb902s+qBcSRVrn00oSZRRUlXB2mcTwZPn8fLhI7Tbf0mvlfO4vm0/N3YeKNF8+YmNeYB+m8K3PYXV1KlRl9UrXHmalATAt5MmERmRMcxToqLC0lXuNGz8BcOsBxAT/UDu7RE+TIU7s6Ws/O74MD09XfY4awcvJSXlo39H+/btSUhI4MSJE9SvXx8tLS1SU1MxNTXFz88PPz8/fH19cXZ2JjY2lkGDBvHs2TMMDQ3p379/jp3NrBnO5OXe5V+pa9CCGjoZ15u0tbHgzplLOWrUPqtF/5XzqVxdHYBWZsY8/CecV0lP+SvkHM1NeshmQWpi9DWxt/IfYvmxPFavQSo1Ryo1p3+/AbRu00Z24GxnZycb653d+XMXCqwzNjZi4SJnhg0dIdtZhoyhprGxcUgzL1yvUaMGHTp24Nof14ud/fy5c7TJlmOInR0huWZ4K6zmZEgIAwcORElJiWrq6lhYWhJy4gTp6en8tH07+voZ11SYmZvz5s0bbt++TbNmzXB3d5fNQGhtbc3lSzn/bwvjsdpDNmlF/379ad2mda71GJJnmfPnzhdYFxISgs1AG5SUlFBXV8fC0oIT2dZBx44duZg5bjxLh/YdMDU1RSqVMmf2HCIiIj74QCujLaLvfEjf6di+PVJTU8ykUubMnk1ERESJHmiVRLvKwqVzFzBo00Z28fhAOzvO5Oo7hdXcvhWGiVnGdUXKysr06N2LG3/8wYvnL7AdPpRepn0BaNayBa2+NODCWfkOTarIfr9wiWatDairqwOAdPBALp86U+TlpYMHMmzaZACq16qFycABnA04Jpes+blz6Rd0DFpQO/Ozt9NAS8LO5Nz+VfusFkPcnalSPWOmuzZmvYn75z4vk57SvHsXrOZM5cdxM+V2oAXg4bFWNpGFdf9vaNO6NXp6ugAMsRtMSMipPMucP3+hwLomTZtg7zANRUVFVFVVGT5iKMeOBpKcnMyMGfZYWJgDGddkdu7UkdDQqyXepujLv6Fp0Bz1zHXf3MaciLM5zwoesZvCgQHjODRoAkGT55H65i2HBk3g5cNH1Gr2BX1WL+LMvJWlcqAFcPn8BQxav9uu2NjZcSbkZJFrBtoN4TsHewBq1q6Nte1AAjM/u1Z4rKaqmhrDrb/5ZA+0xJmtUvbbb78RExNDnTp1OHLkCN26dSM0NJS7d+/SuHFjTp8+TfXq1QtcXklJ6b1DWBQUFOjXrx9Lly6VXf/VsWNHfvrpJyZOnEjNmjVZtGgROjo6NG3aFF1dXUaOHMnr169Zt25dqc2sBfDycSJHF6xkwPcLUZIo8yQqFv95rmi3aILZohn8OHA8Ub/f5OIPuxn602rSU1J59vARvtOdAfjNx5/KGtUYvW8TikqKxN2+S+CqTXLP/ejRIxwdZ7Fx43okKhIiIiJxsJ8BgL6+Pm5uK5BKzQutc5rnhIKCAm5uK2Tv++tvv+G8YCFjvx3LIpdFTJk6mbS0dDas38gvv/zykXkd2bBxIxIVFSIiIphhb4++vj6ubm6YSaUF1gB479qFjo4OgcHBSCQS9u7ZQ2hoKADTp05lhZsbEomEhIQExo0dC8Dhw4fR1dPD/+hRUlNSuHPnDrNn5Z1170Pyb9y4MXM9RuBg75BtfbshzdaG/Oq8d3mjq6NLUHAQEomEPdnaAKDXQC/HNZLyIvrO+/tOafjYdpWFx48escBxFqsz+0RURCRO9jNooa+Pi9sKbKTmBdYArFy8FKfFLvifCiE1LZXQi5f4KfO6lKnfjsdp8UIm2U8jNSUVx8lTiz2hzf+DpMeP8ZizgHmeq1FWkRAbGcUqRycat2rBtOUuTLa0KXT5/Zt/ZKb7CjYeO4SCggK71qznzs2wUkoPLx4n4rvAlaGrF6MkkfA46gH7nJZTv0VTvnFxZI3Nt4T/foPTW7yZ8NMa0lJTefrwETumZUweZD5jIigo8I2Lo+w9w6/d4siyNXLL/OjRYxwd57BhoycSiQoREZHMcMj4/fr6rXB1W46Z1LLQurVrPHFZvJDg48dQVlYmMDCIffsyrhmaMH4SixcvYvyEsaSlpbFihRs3b5b8TJivHyfys/Mqeq9agKJEwtPoGM7OW0ntFk0wXOjAoUGFz8DaYdoYFBQU6DDtWzpMy5i9+VlMLCH2LiWeNUvWduX7jeuRSDK2K/McMrY9i9xWMDDbtid3DcCPGzay3ON7Dh0PAgUF1q/2IOzGDQzatqGPmZTwf++x46Cv7PetcXXj0rnyd7uH/1cK6fkNzC2nQkNDWbNmDaqqqjx8+JBOnTrh5OTEoUOH2LhxI7Vr16Zdu3Y8efIEV1dXjIyM2LlzJ1evXuXq1au4urqydetW9u3bh5ubG20zZ+3KT2RkJAMGDODixYuyqZR9fX3ZsWMHaWlpNG/enOXLl5OSksLkyZOJj48nPT2d9u3bc/fuXfbu3Sv7/fXr1y9yG5cZ5J1Rp6KYd+MUeroNyzpGsYVH3KOBrm5ZxyiW+5nDCfR09co2SDGFR4QDVNj+Ex6RcQF2Re4/FTU7ZOTXr6B9B+BmxD0IO1jWMYqnZcatQkwbl78ZD4si6G7GEL9Z+t3LOEnxrLz5MwAN9BqXcZLiuR9+ly1f9n5/YTk17noIBnoVd9tzI/ze+4vKgYUGPT9qeZcbRT9rLg8V6sxWx44d850Qw8bGBhubvN+CZV3wXr9+faytrQEYM2YMY8bkfz+GLGlpaZw/fx4rK6sc96zJ7/eoqqqybdu2fN8n6/cLgiAIgiAIgvDhKvoNmyrUwVZJcnNz41I+17+0atUq87qNWLZu3VoGyQRBEARBEARB+BT83x5szZ49u6wjCIIgCIIgCIJQiNSKc8VTvircbISCIAiCIAiCIAgVgTjYEgRBEARBEARBkIP/22GEgiAIgiAIgiCUb+XhXlkfQ5zZEgRBEARBEARBkIMKdZ8tQRAEQRAEQRD+f3zsffCy7kdXVsQwQkEQBEEQBEEQyqWKPoxQHGyVMx0aVMy7wANcvX8XPd2Keyf18Ih7NNDVLesYxXI/IgIAvQqaP1yWv2L2n/CIewAVuv9U1L4DGf3HrMmXZR2j2I7duY5pY/2yjlEsQXdvZvwj7GDZBimulgMAMGzUvIyDFM+5f28D0FK3QRknKZ6wiPv0+qJlWccotpP/hNGwQdOyjlFs9+7/XdYRiiStgg/CE9dsCYIgCIIgCIIgyIE4syUIgiAIgiAIQrlU0YcRijNbgiAIgiAIgiAIciAOtgRBEARBEARBEORADCMUBEEQBEEQBKFcEsMIhTL3dc8e7A4KwPfUcVasX0dVNbUCaxeucsNu7BjZY1VVVea7rWBv8DH2HQ9kvtsKVFVVSyM2PY16EhQcyKnTJ1m/wQu1AnIXVKeqqspKdzeOnwjiREgwK93dZNmbNWvGgYP7CQo6xrHAAHr0+Lh7NOTNZERQcDCnTp9m/YYN+WZ/X422tjaXQ0OpUaNGnmXrf/45f1y/jr5+yc1QVpTMhdUpKiri7OzMqVOnOPvzz9jZ2cmWMTAw4MDBgwQGBhJ8/Dj9+vfP877ff/89Y8eNK6G2iL5Tmn2nOG0orK6wvpS9Hdfk3I7c2vfohpe/L5uD/Zi71p3KVavmqelpaYan/348/XxYtW8HX7RqUWr5cmvfoxsbAg7yw3F/nNZ9TxW1vHmzzHBbyoAxI2SP1TTUmbPGnR+O++N5xAfLYUNKI/IHS09PZ/Y6X7YeOV/WUfLo1KM7244dwTskEBdPj0LXv5P7Cmy/HZXjOf9fLrE14JDsp7eluVzzGhr15FBwEEdPn2L1hvX57isUVOOxcQMHA4/Jfq7cvI7Xjz8A0KFzJ3wC/DgUFMiew4fQ/1L+M4N27GHIlqOH2HbiKAs8Vxe67metXI7NmJGyx4qKikxzWcDWYH+2Bvszbs5MuefN0rNndwKD/Dl5Khiv9WtRKyB3YXVDhw7BP+AQJ0ICWe3hjoqKBIBmzZqy33cvxwL9CDh6mO7dDUulTcL7fbIHW6GhoQwbNqzA18+cOcO2bduK9d5WVlbFjVXiqtesyYKVrsyZOBkbYxMeREbx3ay8Gw69Ro3YsHsnRqZ9czw/avIklJWVGGJqzhBTc1QrVWLEpAlyz12zZk3c3d2YOGESxka9iIqMYvacWR9UN3nKdygpKdHXREpfEymVVCsx6buJAHisWc2WzT9gamqG/fQZeK33RCKRlFj2le7uTJwwAWMjIyIjI5k1Z84H1VhbW+Pj60udOnXyvL+Kqioea9aUWN6sPO7Z8kRFRjI7V+b31Q2xs6NBw4b06dMHSwsLRo8ezZeZH6obN23CY/VqpFIpI0eMYP78+ejp6QHQ6Isv2LN3L6ZSaQm2RfSd0uo7+bVBnn0JMg6G18i5Hbmp16jB9BWLWT5lBuP7WhEX9YBRM6flqKnXQJfRs+xxHjOJKVaD2LfxB+Z5rS61jNlp1KyBg+sSlk62Z6yJJXFR0YyaOT1P3eeNGrBi54907ds7x/PjnWbx+uVLxpv2w97Gjq8Mu9KhZ/naOfs3OoERC7dy/PKtso6Sh0bNGsxduYwF301jaG8psVHRjHeckadOt1FD1nhvo3vfPjme/7yBHs+SkhhjYS37CfE/Kre8NWrWZKn7SqZPmIi5kTHRkZE45NpuFlZjP3ESA6RmDJCasXDOXJ49fcbSBc5IJBJWeXmycM5crE2lbPb0YoWHfP8mNGrWYKbbUly+m86oPubERkbzraNDnjqdRg1x3/UT3XL1/V79LKnfsAFjpf0YZ27Nlx3aY2jaJ8/yJa1mzRq4rVzBpIlT6GXcl6jIKGbls79WWJ2JSW+GjxjKsKGjMOljRiVVVUaPHgnAag93ftjyI2ZSK2Y4zMLTq3S3oULBPtmDrfe5desWz58/L9ayfn5+JZym+Dp268qfN24SFZ5xn6KD3nvoa2WZp+6b4Xb4+fhyKjA4x/N/XP2Fn7w2kJ6eTlpaGnf+/BPtenXlnrubYTdu3LhJeHg4AN7e3vkexBZWdzX0Kl6e62XZw8LCqF+vHgDmZhacOBECgK6uDk+fPiU1NbWEshty48aNQrMXVqOpqUlvExNGFPBlwOIlSzjo68uTx49LJG9RM7+vzsTEBN/9+0lNTeXp06cEBATQr39/VFVVWbt2LRcvXgQgLi6Ox48fo62tDcDw4cPZt28fgceOlVBbRN8pzb5TnDa8r66gvpS9HQfk3I7c2nbtzN2bt4iJiATg2N799LDM+QVB8ttk1s134cnD/wC4e/NPatSujbKk9Efkt+3ahTs3w2R5j+7xoaelWZ46c7vBHPc9xPngkBzPf9GqBaeOBJCWlkZKcgpXz56ja1/573B+iN1BV7Dp9RV9u5S/e5B16Po1f924RXTmZ++R3XvpbZX3zFT/oUM46nOAs0HHczzfqm0b0lJT8dy3i23HjjBi8iQUFeW3S9bFsBu3btwgMvPvcZ+3N2a5/m6LUiORSFi+ehWuixcTFxtLcnIyRh0781fYnwDU19EhMfGJ3NoB0K5rF+7cuMWDzL4fsGcfxvn0fcuhgwnaf5BzQSdyPK+opEilypWRqKggUVFBWSLh7Zu3cs0M0K1bV27euEl4Zp/x9t6LlZXFB9X1t+7Hjz/+RFJSEunp6cyfv5DDhzP2SS3M+xMScgoAnRL+7CprqenpH/VT1j75a7bu37+Ps7MziYmJVKlShXnz5lGlShX27dsHQN26dRkwYEC+y/711184OzuTkpKCqqoqK1asQE9Pj6ZNm/L3338za9Ys/v4744Zwjx8/RkNDg6NHj3Lu3DnWrVtHSkoK9evXZ8mSJfkO9ykJWtp1SIiNlT1OiItDTb0aVdXUeJHtYHLVwsVAxsFZdqHnL8j+XadeXWxHjWCF0wK5ZM2urrY2sTHvcsfGxqGuXg01NbUcB8GF1Z3Plr1evbqMHjOKuXPmAcg2MD+fO0P9+vVxcVlMWlpaiWTX1tYmNiZG9jguNhZ1dfUc2QurSUhIYOL48fm+9yBbWyTKyuzbt4/vJk8ukbyQtR7f5YnNJ/P76upqaxObra/FxsXRrHlz3rx5w34fH9nzgwcPpmrVqvz+++8ALHR2BsCwW7cSbIvoO7nJq+/kJs++lNUO5cx2TJZjO3L7TLsOD2PjZY//i4unarVqVK5alVcvXgCQ8CCGhAfv2jR27kxCT58lJTml1HJmqV2nDg9j4/LkraJWlZfPX8ie37h4OZBxcJbd39dvYtzPgj9/v4ZERcLXJr1ITSn9dhTGeWzGF4cXr/9Txkny0sz12fswLh61fNb/GpelALTv9nWO5ZWUlfn10mU2r1yNsrIybls38fL5c3y375RLXm1tbeKybQ/jY+Oopq6eY1+hKDXWgwaSEB/PqePvDmBSUlKoVbs2vscCqFGjBjMmT5FLG7JoamuTkK3vPyyg73u5LAMyDs6yO3HwCN1NTdh38TRKSsr8duFZ9ZyqAAAgAElEQVQSV06flWtmAG3tOsRmyx0XF0c19WqoqVXlebbchdU1aKBH7Vq12Lb9R7S0NPnll19xXeEOvPvsOnM2hPr167F48bIS++wSPs4nf2bL0dGRYcOGERAQwNy5c5k2bRo6OjrY2tpia2tb4IEWwI4dOxg1ahSHDh1i4MCBXLt2LcfrK1euxM/Pjx07dqCmpoaLiwuPHz/m+++/Z+vWrRw5coSuXbuyatUqubVPUVGR9HyO2j/024xmrVqyxWcvvju9uXD6TEnFK5BCEXMXpa5Vq1bs993Pjh27OH36dI667oY96d69JxMnTqBzl84lkr0o67w4/y8tW7ViiJ0d85ycSiRndiWxvnO/ppDP8hMnTsTewYFvx4zhzZs3JRM+F9F38pJn38lNnn2pZatW2JVSO3JTUFTIN29+OyuqlSszd6072rqfs26eS2nEy0NRUQHyXb9F27n6YcUq0tPT8fLbj/OGdfxx8TIpycklHfOTldGH8z6fVsT1f9THl7Uuy3j96hXPnz1j/9btdOvTq4RTvlPQ32Natr/botQMHzOGzZ5eeWoe/fcfRh07M8R6AEtXuaPboEEJJc9LoYC+X9R1P2zKJBIfP8amU3cGdzWiWnUNvsl2PaO8FLxtTytynURZma+7fs2UydOwshxAdQ0NZs60z1HXs0dvevbow4QJ4+jcuVPJNqKMpJL+UT9l7ZM+2Hrx4gWRkZH06ZMxNKJ169ZoaGhw7969Ii3fvXt3lixZgpOTE9WqVcPCIu/p3pSUFKZNm8bw4cNp164d169fJzY2luHDh2NlZcXu3buJiIgo0XZlFxcTQ20tTdnjz+pokZSYyOtXr4r8Hr3NzfDctZ31K1exfcMmecQEwN5hOoGBRwkMPIqt7UC0suWuU0eLxMREXuXKHRPzoNA6CwtzvHfvxM1tJRvWbwAyhjlYWJijoKAAQHRUNBcvXKRly5K5kD0mJgYtLa1smerkyV6Umtysra2ppqbGwUOHOBYYiKaWFmvWrqVXr+J9ANs7OBAYGEhgYCC2trZFylNY7tyvaWlpEZf5za6Kigrr1q3D0tIS6/79uX37drEyF9wW0XdKs+/kVlp9aYC1NWpqahw6dIhAObSjMA9j4qil+ZnscS0tTZ4lJvEmV7s+067DKp8dpKalMXfYt7x49kzu2fKTEBNHTc13/bt2AXkLUkWtKltXrmaimTVOI8eioKBATESUvOJ+cuJjYqmdrb/U1tLi6Qd89vbpZ0nDpk3ePaGgQIoczyzGxsSgme1vTrNOHZJy/d2+r6ZZyxYoKSvxy5VQWY1atWoYm7wbfnr7Vhh//3mbJs2ayq0tCTGx1NLK2fefJiYVed13NelF8IHDpCQn8+L5c04c8qN1xw5yyTrdfipHjx3h6LEjDBxkg2a23FoFfHY9iIktsC4+IYHjx0/w/PkLkpOTOXLEnzZtWyORSDA3l7777IqO5uLFS7Ro2Vwu7RI+zCd9sJXfNwPp6elFPuvTt29fDh8+jIGBAdu3b2fhwoV5apYvX87nn3/O4MGDgYxvZ9u2bYufnx9+fn4cOHCAdevWfVxDChF6/gKt2rTmcz1dAKyHDOZc5pjdouhqbMSMhQuYOnwUx/0D5BUTAI/Va5BKzZFKzenfbwCt27SRTaJgZ2dHyImTeZY5f+5CgXXGxkYsXOTMsKEj8Pfzly2TnJzMjJkOWFhmHBxramrSqXNnQq9cLZF2nD93jjbZMg2xsyPkxIkPrsltyeLFGPXsiZlUiplUSkJ8PNOnTePkybzrpSiyJqyQSqX079cvn/WYN8/5c+cKrAsJCcFm4ECUlJRQV1fHwtKSE5mveaxZg1q1alhbWxMdHV2svIW3RfSdwpR038mttPrS4sx2ZP2ukm5HYX6/cJmmrQ2oq6sDgHSwDVdOnc1RU7lqFVy9t3LpxClW2s/mrZzO3hbF7xcu0SxH3oFcPlX0UQnSwQMZNi1jmGb1WrUwGTiAswElc13l/4NfLlykRZsvqZ/52Ws1ZBAXTp5+z1LvNGzSmDH2U1BUVERFVRXrYXacPhYkr7hcOncegzZt0Mn8exxkN4TTJ0I+qKZ9x46EXrqcY5m01FSWuK+kzVftAGjUuDENGzXixh85RwKVpN/OX6J5awPqZfZ9iyGDuPQB6/6fsD/pYWoCZAzn7Gzcg9vXbsgl6xqPdZib9cPcrB8DrAfSps2X6GX2GbshtpzMZ3/twvkLBdYFBR3HzMxUNntu7z69uHHjJsnJyTjMmI6FRca1a5qamnTu3JGrob/IpV3Ch/mkr9lSU1Ojfv36nDhxgj59+nDt2jX+++8/GjduzM8///zeYU7Tp0/H3NwcW1tbGjVqxIoVK3K8vn//fv7880927nw3xvrLL79k/vz53L9/nwYNGrBhwwbi4+NxdXWVSxufPHrMEsc5uG7wRFmiwoOISBbNcKS5fivmuS5nqFneyTKym+Y0GwUFBea5Lpc9d/2333B3lu/QmEePHuHoOIuNG9cjUZEQERGJg33GTE76+vq4ua1AKjUvtM5pnhMKCgq4ub37f/n1t99wXrCQ8eMmsniJCxPGjyMtPY0Vy1dw8+bNEszuyIaNG5GoqBAREcEMe3v09fVxdXPDTCotsKasZOXZmC2PQ2aejPXthjRb7vzqvHftQldHh6DgYCQSCXv27CE0NJS2bdtiZmbGv//+y8GDB2W/09XVlXPnzsmpLaLvlBV59qWylPT4MWvmOjPXcxUSiYTYyGi+nzWPL1q1YNqyhUyxGoT5UFs+q6tNl95GdOltJFvWacQ4niUmlXpejzkLmOe5GmUVCbGRUaxydKJxqxZMW+7CZEubQpffv/lHZrqvYOOxQygoKLBrzXru3AwrpfQVX+Kjx7jOnsfizBnfHkRGsWzmHJrqt2TW8iWMsbAudPlt69YzfdF8tgf6oSyRcCYwmKM+vnLL+/jRI+Y7OrJm4waUVSRERUTgZD+Dlvr6LHZzZYDUrMCaLLoNGhCT68u0ly9fMnXseOY4L0BZWcLbt2+ZNW0a8XFxuSOUmMTHj3GfPR9nrzUoS5SJjYzCzdGJJq1a4rB8MRMsC748BGDjMjcmL5zPT8czJoj549IVfH74SW55szx69JhZjnNZv2EdEomEyIhIZsyYDYC+fitWuC7F3KxfoXXeu/ZQXUMD/4BDKCkpEXYrjOXLMvYvJ06YjMtiZ8aN/5a0tDRWrHDn5s3yN5NncaSVg0kuPoZCen6nfz4BoaGheHl5sWjRIhYtWkRiYiISiYT58+fTtm1bfvnlF2bPns2oUaMKnCL+r7/+Yt68eaSlpcmWNTAwkE2Q0apVKz7//HMqVaokG9fv4+PDpUuXWLt2LWlpaWhpaeHu7l7kCTI6NGhcYuugtF29fxc93YZlHaPYwiPu0UBXt6xjFMv9zKGqehU0f7gsf8XsP+ERGUOTK3L/qah9BzL6j1kT+d/bR16O3bmOaePyN+NeUQTdzfwiIuxg4YXlVcuMHXPDRhVzuNW5fzOGbLfUld81UvIUFnGfXl+0LOsYxXbynzAaNpDfkEl5u3f/77KOUCRjWnzctWdb/7xSQkmK55M9s9WxY0c6duwIwK5du/K83r59+zwXxOfWrFmzHN/UZ8magfDWrfy/MTAyMsLIyCjf1wRBEARBEARBKJryMMnFx/hkD7aKKjAwkM2bN+f7Wnm6n5YgCIIgCIIgCBXL//3BVtaF2IIgCIIgCIIgCCXp//5gSxAEQRAEQRCE8kkMIxQEQRAEQRAEQZCDij4b4Sd9ny1BEARBEARBEISy8slO/S4IgiAIgiAIQsVm17z9Ry2/+3bZ3txZDCMUBEEQBEEQBKFcEtdsCSVq45e9yzpCsU28HoKeXsW8KS1AePi9Cntj13c3BdYr2yDFFB4RDlBh+094eMZNjSty/6moN2SGjJsy3+n/cd98lqUmh39hln73so5RLCtv/gxU/JsCV/SbMntV0H2HyddDONCmV1nHKLZv/jjJhJZdyjpGsW0Ku1TWEf4viIMtQRAEQRAEQRDKpdQKfsWTmCBDEARBEARBEARBDsTBliAIgiAIgiAIghyIYYSCIAiCIAiCIJRLaRV8ggxxZksQBEEQBEEQBEEOxMHWJ0CnWwcG+m5msN9P9HFfgKRqlQJr9Xp2YcwlvzzPq1SrykDfzXzWook8o+bQs2dPgoICOXXqJOvXe6GmpvZBddWqVWPDhvUcPx5ESMhxJkwYL1vGwMCAAwf2Exh4lODgIPr1syrZ7EZGBAUHc+r0adZv2JBv9oJqFBUVcXZ25tSpU5z9+Wfs7OzyLGszcCA/bt1aopnz5utJUHAQp06fYv2G9QWv//fUaWtrcyX0CjVq1JA917lzZ/wD/AkKCuLw4cN8+eWXJZu9AvQdefURPT09fPbvJ+TkSY74+dGoUaM87zt69GiOnziR47mhw4Zx9NgxTp46hceaNaioqJR6u7Joa2tzOTQ0R5/JUhp9P0vVdl+j67EHPa8DaDuuQLFy1Tw1KjqNqL9kEzrfe6PjvgPVhs0yXlBQoPbwKeiu9UF3zV60Z69ESb16qeTO0qxbJ+wP/oSj/y6Gfu+Caj7b/i6D++NweDsOh7YxYt0yqtbMyKisqoLN4tk4HNqGw+Ht2CyejbJq8fpEcXXq0Z1tx47gHRKIi6cHVdTyrv8sTu4rsP12VI7n/H+5xNaAQ7Kf3pbm8o78wdLT05m9zpetR86XdZRC6XbrgK3vZuz8fqLve/YjGvTswrh89iNKU52uHenlswWTw9votHIByoXkrdujC1YX/HM8V8+4G8a7N9Db9we+XrcMFQ11eUfOoZVhF+Yf2smio3sZu3oplfLJ38HchPmHdjDv4HYcvTej0zJj26MskTBk4SwWB/rgdGA7FpO/RUFBoVTzl7bU9PSP+ilr4mCrgqtUQwOjxTM5PmMxe61G8/RBLJ2mjcm3VkOnHl0cxuX5o9Tp2oEB3p5U16tfGpEBqFmzJu7ubkycOAlj415ERUUxe/asD6pzcLAnLi4OExNTLC37MXSoHW3btgFg48YNeHisRSo1Z+TIUcyfPw89Pb0SzO7OxAkTMDYyIioyktlz5hS5ZoidHQ0aNqRPnz5YWlgwevRo2cGIhoYGy5YtY+HChXLdeL7LNxFjI2OiIqOYPWf2B9dZW1uz33c/derUkT0nkUjw9PJk7py5mJqa4unpyWqP1SWcvXz3HXn2kTVr17J792569+rFGg8PNmzcmON92331FeMnTMjxnEnfvowcORK7IUPo3asXlSpVYsyY/LcT72vXymyZIyMjmZVPuwqrsba2xsfXN0efgYy+v3TZMpwXLoRS2HFQUq+O1hRnYlbOJnzyNyTHPaD2sMk5ahRUVKm/0Isnh3cSOWMoj3y3om2/BAB1Y0sqNWpO5IyhREwfTHJsFJ+NnC733Fmq1tBg4JI57LJfgLvlMB5Fx2A6fXyOmnotmmA4YhAbhn3HautR/BcRjcnkjP9343HDUFRSwmPAaDwGjEaiqorRt0NLLb9GzRrMXbmMBd9NY2hvKbFR0Yx3nJGnTrdRQ9Z4b6N73z45nv+8gR7PkpIYY2Et+wnxP1pK6Yvm3+gERizcyvHLt8o6SqEq1dDAePFMgmYsZrfVaJIexNKlkP2Irx3GlcrfaEFUamjwlctMrji6cLz/KF5Ex6I/9dt8a9V06mFgPz7H52mNFk1oPXsyl2e6EGIzlucR0bScPCrf5eVBrUZ1hi+dx5bpTiwyH8x/0TH0d5iUo0ZLT4cBM79j3TgHlg0YSdDm7UxYuxyAvuOGU6tuHRb3G8byb0ai8Vltug+2LrX8wof7ZA+2wsLC6NGjR75nDbJ4enri6en5Qe87bNgw2b+bNm1a7Hwl5fPO7Ui4dYekyAcAhO0PoLHUOE+dciVVjJfP5tKqzXle0x/Sj5NOrrx4+FjuebN069aNGzduEh4eDoC3tzdWVnnPIBRW5+KymGXLMjY+mpqaqKio8PTpM1RVVVi7dh0XL14EIC4ujsePH6OtXSfP+xcru6EhN27cKDR7YTUmJib47t9PamoqT58+JSAggH79+wNgbm5OfHw8y5ctK5GsBbeh23vb8L46TU1N+pj0Yfiw4TmWSU5OplPHToSFhQGgo6NDYmJiyWWvAH1HXn1ES0uLRo0aEeCf8S3t2bNnqVqlCi1btQKgdu3aLF68mOXLl+f4XQOsrfnhhx9ISkoiPT2deU5OHDp06IPaVBLt0tTUpLeJCSOybUezmJVS389SpXUnXt/9k+TYKAASgw9SzbBvnprk+Ghe/J5xL5oXV88Rs2ouAG+j7vFwx1rSU5IBeP3PbZQ1tUslO0CTLu2JCvuL/zK3/Vd8/GhjlvN+RQ/+vMNKczteP3+BsooKGpqf8TLxKQD3fr3OqS07SU9PJz0tjQd/3aW6tlap5e/Q9Wv+unGL6PCMewQe2b2X3lZ5z0z1HzqEoz4HOBt0PMfzrdq2IS01Fc99u9h27AgjJk9CUbF87dLsDrqCTa+v6NtFv6yjFEon137Erf0BNClgP6L38tlcyGc/ojRpdWrHk7A7PM/M+69vADqmefMqVVKlw9I5XF+9KcfzOlJjwo8E8zI2HoCwzTu5s32//INnatGlAxG3bpMQGQ3AuX2H6GCW88uElLdv2eXsytP/HgEQEfYX6rVroSRRRqdFM34NOknK27cAXDt1jra9e5Za/k9dQEAAUqmUPn36sHv37jyvnzx5EisrKywtLZk0aRJJSUnvfc/ytWUqQWfOnMHS0jLfFfUxrl69WqLv97HU6nzG8/iHssfP4x+iWq1qniEAhgum8+eBYzy6ey/Pexyb5MTDsDtyz5pd3braxMbGyh7Hxsahrl4tz3Cj99Wlpqbi4bGaEyeCuXIllHv37vHmzVv273+34Rw82JaqVdX4/fc/Sia7tjaxMTHZMsWirq6eI3thNXW1c7UpLg5t7YydtN27d7Nu3TreZm5E5aWudl1iY7Kv17xteF9dQkICE8ZP4P79+3nePyUlhdq1a3Ml9ApzneayeVPJfThXhL4jrz5St25dEuLjSc82LCI2Lg7tOnVQVFRk7bp1rFi+nPi4uBx5GjRsSK1atdixYwdBwcFMt7fn6dOnH9QmyBj+lz1zXD7tKqwmISGBiePH59tn9uzejWcp9P0syrW1SHkUL3uc8igBpapqOYYSqtTVIeXJI7S+m4+O+w7qLVqPgpISAK//vsmbe38DoFi1GrUGfcvziydLJTuARh1NkuISZI+T4h9SuZpanqGEaSmptDTqyryTvjRoZ8CvRwIBuHv5V/6LyNjZq66tRbeh33DzxNlSy6+pXYeEbH38YVw8atWq5RlKuMZlKScDjuVZXklZmV8vXcZx1Dim2A6jg+HXDBheemfmisJ5rCUWhq3LOsZ7FXU/oseC6YQVsB9RmqrU0eRl/Lu+/yrhIZJqVfMMJWw7bzr3Dh4j6U7OvGq69VFQVqKLx2J6+WymzZwpJL98WSrZAWpoa/Ek7t2250nm3272oYSPYuK4de7dDYe/mTWVG2cukJqcQvjNMNr1NUa1SmWUJMp0MOuN+me1Si1/WUhLT/+on6KKj4/Hw8ODPXv2cOTIEXx8fPjnn39krz9//pxFixaxZcsW/P39adq0aZFO2pTZwVZoaCijR49m0qRJmJiYMHXqVN6+fcvBgwcxNzfHwsKCOXPm8OLFi0Lf59q1a9jY2GBpacmIESOIiIjg559/Zu/evRw8eBAvL69Cl79x4wY2NjaYmZmxY8cOIGNHcf78+QwaNAhjY2MmTZrE69evWbp0KQA2Njay5Z2dnbG0tMTS0pKIiIxv6Nzc3LC0tKRfv37v/f0fS0FBEfLpSOlpabJ/txxoQXpqKn8dOZ6nrqwoKCjm2GHMkpqa+sF19vYOtGnTjurVNZg2bWqOuokTJ2BvP51vv/2WN2/elEx2xfdnKqwm92sK5G23vCkoKhRt/RexLj///fcfnTp2wtraGvdV7jRo0KD4gbNnqgB9R159REFRMc+cTAoKCqSmpTFr9myuhoZy4cKFPO+prKxMt27d+O6777C0sKC6hgaOjo4f1CbIuJbsfe0qSk15oKCgUMC2M9v/kbIyVdt9TdKJw0Q6jiAx0Id689eioCyR1Ujq1OPzZVt4dfsaiUG+pZIdsvp33ufTsm37s4SdvoCLoRUhG7czZvOqHEOq6rVowsQdnlzce5jb5y7LM3IOGX087/NpqXnz5+eojy9rXZbx+tUrnj97xv6t2+nWp9f7FxTyKGhbmX0/olXmfsTtcrAfkfG3m/f59Gx9p6GNJempqYT7BeepU1RWRtuwE78t9eCk7QTePHpMuwUO8oycg4JC/p+r+f3tqlSuxNjVS/lMpx67nFcAcHyrN7H/3GfW7i1M/3Ed/167SWpyitxz/z+4dOkSnTp1onr16lSpUgUTExOCg9/1oeTkZBYuXIiWVsYogKZNm+b4YrQgZXpm648//sDZ2ZmgoCBiYmLw8fFh06ZN7Nq1i4CAACpXrlzowcrbt29xcHBgwYIF+Pv7Y2tri4ODA927d8fW1hZbW1smT55c4PIADx8+ZMeOHfj4+LB7925u377NH3/8gUQiwcfHh5CQEJ49e8bPP//M/PnzAfD1ffeB2qVLF/z9/fn666/Zt28fDx484Ny5c/j7+7N3717++eefEtvJz8+zuASqZPtGo6pmbV4nPSXl1WvZc02t+qDZsgk2PpuQei1DSVUFG59NOZYrDfb20wkMPEpg4FFsbQeipaUpe61OHS0SExN59epVjmViYh4UWGdo2A1NzYzXXr58ib9/AC1btgRARUWFdevWYmlpgbX1AG7f/qvE2hETEyP7Q8vIVCdP9sJqcr+mpaVFXBH+WD+WvYM9gYGBBAYGYmtr+942vK8dBalWrRomJiayx2G3wrj9522aNiv+sNuK1nfk1UdiHjxA87PPcvyurNesra3p27cvgYGBuLq5oaurS2BgxlmMhPh4goODef78OcnJyRw+coS2bduWervKk+T/4lGu+W5dKtf6jNRnSaS/ebftTHn8H2+j7/P6bsaQ2BdXz4GiIpI69QCo3Kodn7v+xNMzx0jY5Fqq+RPj4lHXfLcNV9eszcukpyRn2/bX+rweem3eDWH75XAgNbS1qKxeDYAv+xoxdsv3BK3ZwpkfvUsvPBAfE0ttzXfrv7aWFk8TE3ldxH7Sp58lDZtmm9BJQYGUFLHDWRzP4hKomm1/QC2f/YjmmfsRg3w2YeG1DGVVFQb5bMqxXGl5GZdA5Wy/t7Jmbd4mPSX19bu8epZ9qNGyKb32baKr13KUVFXotW8TlT6rxauHj4i/9AtvHj2B9HTC/Y5Ty6BFqeV/HBtP9Wx9v7rmZ7xIesrbbOsbMs6Azdq9mbTUNDxGTebVs+cAVNVQJ2T7Xpb0H8b3Iybx8ukzHmYOSfxUpZL+UT9Pnz4lOjo6z0/uER4JCQl8lu0zVlNTk/j4d2cha9SoQe/evQF4/fo1W7ZsoVev93/JU6YHW40bN6ZO5vCXRo0akZSURM+ePWUzVA0aNIgrV64UuHx4eDjq6uoYGBgAYGpqSmRkJM+ePStyBqlUSpUqVVBTU6Nnz55cvXqV9u3bM2TIEHbv3s2yZcsIDw/nZQGnmLNW8hdffEFiYiJaWlqoqqpia2vLzp07mTlzJqqqqkXO86GiL/+GlkFzNHQyPvxb2pgTfjbnt5OH7KbgM2AcvoMmEDh5Hqlv3uI7aAIvHz6SW678eHisQSo1Ryo1p3//AbRu3UY28YCdnR0hIXmH4Jw/f6HAOjMzM6ZPzzgboaKigpmZGZcvX878XatRU1PD2voboqMflGg7zp87R+s2uTLlmvmtsJqQkBBsBg5ESUkJdXV1LCwtOZFreXnwWO2BVCpFKpXSv19/WrdpnStfSJ5lzp87X6S67FJTU1npvpJ2X7UDMv7OGzVqxLU/rhU/ewXrO/LqI3FxcYRHRGBhYQGAoaEhaWlp/PXXX3Ro3x5TU1OkUilzZs8mIiICqVQKQGBQEGZmZrJtUZ8+fbh+40ax2tUmW+YhBbTrfTXlwctrV6jUpBUS7c8BqG4ygOdXz+WoefH7JSSadWUzEFZu0QZIJzk+BtWGTak7x524tYt44le6ByoAdy79go5BC2pnbvs7DbQk7MzFHDXVPqvFEHdnqlTXAKCNWW/i/rnPy6SnNO/eBas5U/lx3EyuBZbe8Mcsv1y4SIs2X1JfTxcAqyGDuHDydJGXb9ikMWPsp6CoqIiKqirWw+w4fSxIXnE/aVGXf6NOtv2IVjbm3M+1H+FrN4W9A8bhM2gCAZPnkfLmLT6DJvCilPcjAOIv/0ZN/eaoZeZt+I0FMWcv5ag5PWwyITZjOWk7gQuTnUh985aTthN4/fARD06eQ7tbJ9kMhPWMu/Ik7O9Sy3/70lUaGLREUydjUjLDQf24fjrnbJWqVargsM2LP0J+ZqujM8lv3g2vNujZDbtFszLrKmM83Jarx8rfNrY82bFjB8bGxnl+ska0ZUlLS8tx5j89PT3fycqePXvGuHHjaNasGf0zr7kvTJne1Dj7QYiCggLq6uo5jjLT09ML/aYqv1Ou6enpHzRcRVn53SpIS0tDWVmZU6dOsW7dOoYPH461tTVPnjzJ95Rv9uWzTgsrKyvj6+vL1atXOXfuHLa2tuzatavEhlDl9upxImecV9Fn1QKUJBKSomM4PW8ln7VoQo+FDvgOmvD+NykDjx49wtFxFhs3rkcikRAREYmDQ8ZMVPr6+ri5rUAqNS+0btmyZSxbtpTjxzM+YI8fP8FPP22jbds2mJlJ+fffexw8+O4spKurG+fOffz0uxmZHNm4cSMSFRUiIiJwsLfPzO2GVCotsAbAe9cudHV0CAoORiKRsGfPHkJDQz86V/HbIMnMlzGMouB25KwryMuXLxk3dhzOzsHogIIAACAASURBVM5IlCW8ffuWqdOmEpfrOqKPy16++448+8jUKVNwdXVl8pQpvHnzhkmTJhW4fcqya+dOqmtocPTYMRQVFQm7dYtlmcOiP0RW5g3ZMs/IbJermxtm2dqVu6a8SU16QrznYuo6uoJEQnJcNHFrF6HaqDla380n0sGO1MRHxLg6ojl+NoqVKpOe/JYYt1mkJ7+l9tDvAIWMGQwzZzFMiX9AjFvemTHl4cXjRHwXuDJ09WKUJBIeRz1gn9Ny6rdoyjcujqyx+Zbw329weos3E35aQ1pqKk8fPmLHtHkAmM+YCAoKfOPybjhp+LVbHFm2plTyJz56jOvseSz2WoNEIuFBZBTLZs6hqX5LZi1fwhiLwmdX27ZuPdMXzWd7oB/KEglnAoM56lN6wzg/Ja8eJ3LKeRWmqxagKJHwNDqGkHkr0WzRhJ4LHfApZ/sRb54k8usidzq5O6OorMyL6FiuLnCjRosmtHN24KRt4Xljz12hstZndP/xexQUFXkZG8+vLt+XUnp49vgJO+cvY9yaZSgpS3gY9YDtTovRadmMYYvnsGzASHoMGUCtunVo3cuQ1r0MZcuuGT2VS4eO0kC/Bc5+3igqKnHhgD+/nzhTavkrohEjRuR7UKSunnPK/zp16vDrr7/KHj98+FA2CiZLQkICY8aMoVOnTjg5ORXp9yukv+9TWk5CQ0Px8vJi165dAMyZM4cWLVqwc+dODhw4QPXq1XFxcUFJSUk2fC+3t2/f0qdPH9atW4eBgQGBgYFs2rQJf39/2QVrU6ZMKTCDp6cnFy5cYNeuXbx69YpvvvmGTZs2sXfvXmrXrs2ECROIiorC1taW6dOnY2NjQ4sWLbhx4wbKyso0bdqUv//O+Dbk0KFDXL16leHDh7NkyRJ27dqFsrIyI0aMYMSIERgZGRVpvWz8sveHrMZyZeL1EPT0GpZ1jGILD7+Hnq5uWccolvDM6wX1dPXKNkgxhUeEA1TY/hMennEBdkXuPw0qaHaA+xER3OnfvqxjFFuTw78wS797WccolpU3fwbAsFHzMk5SPOf+vZ3xj7CDZRukuFoOAMCrgu47TL4ewoE2Ffdau2/+OMmEll3KOkaxbQq79P6icsC08cfN6Bl092aR6uLj4xk8eDAHDhygcuXK2NrasmTJEtkIutTUVGxsbOjVqxeTJk16z7u9U6ZntnJTU1Nj/PjxDBs2jOTkZFq2bImLi0uB9SoqKnh4eLBkyRJevXqFhoYGHh4eH/Q769ati62tLW/evGH8+PE0atQIGxsbZs6cybFjx5BIJLRt25bo6IzxsMbGxlhZWRU4bXKLFi1o3bo15ubmVK5cmbZt22JoaJhvrSAIgiAIgiAIBUvLb0YUOdDS0sLe3p7hw4eTnJzMN998g4GBAWPHjmXq1IwROn/++SepqakcP54xWUyrVq1Y9p5blpTZmS0hf+LMVtkRZ7bKjjizVbbEma2yJc5slR1xZqtsiTNbZauinNkyadzqo5Y/frdsbyxers5sFWTYsGH53hPG1taWwYMHF7rs9u3bOXz4cJ7nNTU1+eGHH0osoyAIgiAIgiAIQnYV4mAr67qu4hg5ciQjR44suTCCIAiCIAiCIJSK1Ao+CK9Mp34XBEEQBEEQBEH4VFWIM1uCIAiCIAiCIPz/Ka0JMuRFnNkSBEEQBEEQBEGQAzEboSAIgiAIgiAI5ZLRFy0+avnT//xZQkmKRwwjLGe6NmxW1hGK7cK9vyrs1OOQMf14Rc0vmzq9gk7f/clMXV+B81fUvgMZ/eeKYdeyjlFsnc5doIFe47KOUSz3w+8C0FK3QRknKZ6wiPtAxZ46HajQU9fbNGtX1imKzfev32hYgbed9zI/e8u7tAp+XkgMIxQEQRAEQRAEQZADcWZLEARBEARBEIRyKa2sA3wkcWZLEARBEARBEARBDsTBliAIgiAIgiAIghyIYYSCIAiCIAiCIJRLYoIMocx17tmd7YF+7DkZxBKvNVRRq1pg7Tx3VwZ/OzrHc0d/vcy2o4dlP72tzOWWtadRT4KCgzh1+hTrN6xHTU3tg+oUFRVxdnbm1KlTnP35LHZ2dnmWrf95fa5dv4a+vr7suREjR3Dq9CkCAwNZt24dGhoa5Sr7F42/wPeAL4GBgRwLPIahoaHstSFDhnAi5ARBwUH88MMP1KhR4wMyGxEUHMyp06dZv2FDIZnzr8uZ+eccmfX09PDZv5+Qkyc54udHo0aNAJg4cSKBgYGynyuhody8dQuAmjVrsmnzZoKCgwk5eZK5Tk4oKCgUsS3yW//GxsZcu34tR+6qVXP+HX3//feMHTe2SFlLO3/nzp05euwoQcFB7N23l+bNm+d4TxUVFXZ578JUalrM7O/vR8XpQ507d8Y/IICgoCAOHz7Ml19+mU9ub0yl0mLlfp/qnTqjv207X3rvobHLEpSqVMlTo/PdZNr4HkR/6zb0t26j8SIX2WutftiKwc5dste0bQfLJWduPXv2ICgogFOnjrN+/bqC+1Ihdb/9HsqxQH/Zj5WVJQDNmjXF98A+AoP8OXrMj+49DPN97+IyNOrJoeAgjp4+xeoN66maT/aCajw2buBg4DHZz5Wb1/H68QcAOnTuhE+AH4eCAtlz+BD6ufqSvOl264Ct72bs/H6ir/sCJFXz9qUsDXp2Ydwlv1JMV3zp6enMXufL1iPnyzpKDm27d2WV3z7WBh3EYY0blavm3e/pZmGK+5G9uB/ew9K9P9GwVcZ2UVmizDgXJzyO+uJx1Jfhs+1RVJT/7nBPIyMCg4M5efo0XoVsR/OrUVVVxc3dnaATJwgOCcHN3R1VVVUAdHV12entzdHAQI6fPMmYscX/nBLkQxxsVXDVa9bAyW058ydNZUgvU2Kiopg4a0aeOt1GDVnrvZ0epn1yPP95gwY8S0pilHl/2U+I31G5ZK1Zsybu7u5MnDARYyNjoiKjmD1n9gfVDbEbQoOGDejTpw+WFpaMHj06xw6aqqoqa9asQSKRyJ7r3LkzEyZMwG6IHVKplDNnzrDCdUW5yr50yVL279+PVCplluMsvNZ7oaSkRP3P6zPTcSYDbQZi2teU6Oho7B3sPzDzBIyNjIiKjGT2nDkfVDfEzo4GDRtmZrbIkXnN2rXs3r2b3r16scbDgw0bNwKwceNGpFIpUqkUW1tbXr58yZTJkwFY4OzM3bt3Me3bF3MzM1q3bs03NjZlvv7btWvHli1bZLmlUikvXrwAoNEXjdizd0+xD1Tknb9atWps2ryJ5cuXY9rXlPnz5uO13gsVFRUA2rZty6HDh/jqq68+MnvB/ag4fUgikeDp5cXcOXMwNTXF09OT1R4esvfMyH242LnfR1mjOo3mOnF3wXyuDx3Cm9gYPh8/MU9dtZatuOuykJtjRnFzzCjuLloIgGKlSlSqW5ebo0bKXovdt1cuWbOrWbMmK91dmThxMsbGJkRGRTFr9swPqmvYsAFJiUmYSS1lP35+/gB4eKxiy5YfkZpa4mA/Ey+vtTm2px+jRs2aLHVfyfQJEzE3MiY6MhKHObOKXGM/cRIDpGYMkJqxcM5cnj19xtIFzkgkElZ5ebJwzlysTaVs9vRihcfqEslcFJVqaGC8eCZBMxaz22o0SQ9i6TJtTL61Gjr1+NphHBTxS6ay9G90AiMWbuX45VtlHSUH9RrVmbR8IaumOjLNdADxUdHYzZiSo6ZuA12GOU5n2dgpOPYfwsGNW3FctwqAvnaDUK9RAweLgcywsqVpGwM6m8p36v+aNWvi5u7OpAkT6JW5jZyVz3a0oJrvpkxBSUkJqYkJUhMTKqmqMvG77wBw//57jh49irlUyjf9+zNkyBA6d+ki1/aUtjTSP+qnrJX5wVZYWBg9evTI9wxFFk9PTzw9PYv9Oz52+fKsfbevuX3zJtHhGfdKOOy9j95WFnnqrIfZcXT/Ac4EHs/xvH67NqSmprLex5vtgX6MnDJJbt/wdDPsxo0bNwgPDwfA29sbKyurD6ozMTHBd78vqampPH36lICAAPr17ydbdvGSxRzwPcCTx09kz7XSb8XFCxeJi4sDIDg4GGNj4w/agZB3dkUlRdnZtqpVq/LmzRsAlBSVUFZWRk1NDQUFBSpVriR77f2ZDYuYueC6jMz7c2Xuj5aWFo0aNSLAP2MH7ezZs1StUoWWrVrleG+nefP4+exZzp49C8Dx48fZuWMHAG/evOHOnTvUr1evCG2R7/pv164dXbp0ISgoiP2+++nQoYPsPYcPH86+ffsIPBb43pxlkV9PT49nT59x6eIlAP7991+eP39O27ZtARg5ciRurm5cv3a9mNnf34+K04eSk5Pp1LEjYWFhAOjo6JCYmCh7z4zcrly/dq1Yud9Ho0N7nv91m9fR0QDEHzlM7d45d7gUJBKqNm5M3cFDMNi+g8ZLlqKiqQWAWvPmpL56RbNV32OwfQe6k6egkHmAK0/dunXlxo2bhGdu872998jOShW1rm27tqSmpbF//x6CggKYMnWybLtvbt6PkBMnAdDV1eHp02ekpqaWSPYuht24deMGkZn9ZJ+3N2a5+lJRaiQSCctXr8J18WLiYmNJTk7GqGNn/grLuHFpfR0dEhOfUFp0Orcj4dYdkiIfAHBrfwBNpMZ56pQrqdJ7+WwurNpcatk+xu6gK9j0+oq+XfTfX1yKDL7uzL83/yQuIgqAE/sO0M0i55dhyW/fsmnBEhIf/gfAv7f+pHrtWihLlDm6fTceDnNJT0+nWnUNqlSrxvOkp3LN3M3QkJtF2I4WVHM1NJT1np6kp6eTlpZGWFgY9TI/O/f7+OB/5AgAz549IyIiQvaaUD6U+cHWmTNnsLS0ZPfu3WUdpULS0tYmITZO9vhhXBxq1arlGUrosWgJIf55z1gpKSnx68XLzBg5lsmDhtKhW1cGjBgql6x1tesSGxMrexwbG4u6unqeU+mF1dXVrktsbLbX4mLR1tYGYJDtIJSVldm3b1+O97v2xzU6d+ks2/jYDLRBVVWV6jWql5vszgucmTRpEpevXMZ7tzfz588nNTWViIgItmzZwqnTp7j6y1U6duzIeq/1RcysTWxMTBEyF1xXV1s7V+Y4tLW1qVu3Lgnx8aRnG0cdGxeHdp06ssdfNG5Mnz59WL363TfMwUFBPHz4EICWLVtiZWnJ8eM5vwDIvy3yXf9PEp+we/duTE1NWem2ks1bNlMnsy0LnRfin/mtf3HJM//9+/epXKUy3bp1A8DAwIAmTZqgqakJwNSpUzl/vvhDgIrSj4rThwBSUlKoXbs2V0JDmevkxOZNm2R1H5v7fVQ1tXibkCB7/ObhQ5TV1HIMJVSpXZukP34n6scfuPE/9s48LKf0/+Ovp5VUtnZL2ZeyxNdOZClFqFAkMbYsDbI1UQhDMrJkncXYS9ZQKsvYl2GYCLOgSKtI1vbfH08ePW1SPcX8zuu6nutyzvncp/d9+5z73OvnjHHidWQkzb4Xz4rLq6iQevMP/vb04PbECShpa1N/krPM9H5AV09Hqjzj4+JRV1cr4EvF2SnIy3PxwkWcnMYx3G4kJibdcRozGkDSsfrt7Ck2bd7Als1byc4un8DLurq6xOfx74S4eNTU1aWWEpbExsZuOIkJCZwKDZOcy8zMpLaGBqevXma2uxu/bK64Do2qjiavE5Ikx68TklBWq1ZgKWEvjxlE7j9O8j8PK0xbWfCcMAgrk7aVLaMAGrraPIv/2O5Jjk9ERU1Vailh0tM4/jh7QXLs5ObK9TNnyczIBCArMxMHVxf8wo7wMjmZe9dvylSzbr46Mj4uDrV89WhxNhfOn+fRI/EHuPXq1GHsuHGEHD8OwP7AQN6/fw+ASc+etGvXjrNnz8o0PwKfxycDZFy9epUtW7ZQpUoVHjx4QLNmzVi1ahVHjx5l27ZtiEQiDA0N8fDwKLDHIS+3bt1i2bJlpKWlUbNmTby8vIiKimLvXvGyCyUlJablLjUqjIiICIYNG8bbt28ZPnw4Tk5OAGzdupWQkBCysrLo3r07c+bMQSQS8dNPP7Fv3z5q1qyJuro6rVu3BqBz584YGRmRlJTE/v37+fnnnwkKCkJeXp5u3boxZ84c5OXlOXDgQKH569atG3369CEiIgINDQ1sbW3ZuXMn8fHxrFixgo4dO7Jt2zYOHTqEnJwcrVu3xsvL67P+Uz4HkZycVIP3A9lZJXs5Hg0IlDoO+OVXhjo5ErhtR7noy4tITlSo1vyjpsXZ5b8mQkRWVhaGRoY4ODgwfNjwAul+//131q5dy5atW8jOzmbfvn28ePGCjPSML0K7srIyfhv8mD1rNqdPn8bY2Jiffv6JiD8jaNy4MRYWFnTt0pXnz5/j9p0bq35Yxfhx40uguXDfKKi5aLv810R5z+f/eyIRWXkaZd988w07tm/n1atXBe5tYmKC75o1LFy4kLt375YgL7IrfwDnPI3k69evc+PGDXr06EFgYGCBe5UGWep//fo1EydOZM7sObi7u3P12lUuXbpEekZ6OWn/tB+Vxoc+8OzZMzp36oShkRF79uzhn8GDJY0KmSISQSGac/L4cFpcHH/NnSM5jvPfSx2nMSjr6vLi4kVeXLwouRa7cydNly4jev06mcqWE5XsuS7Ozt9/38cT7+Dnn7YxZuxotv3yq+R0r559qFu3LvsC9/LPP/9y+fKVMmsv+n31aV/KazN63DgWffddAZvkZ8/o3akLLYwM+XnPbkYMtia6AnxJVERZ5/Ulo+FW5GRlce9wKGp62jLX9F9GJCeisJVh2dkFZ2CVq1Zh6vLF1NbRZtkE6Tbm7tXr8V+3CeclC5iw6Ds2uC2UlWTkSlCPlsTGyMiIzVu3snP7dk6fPi1lZ21jw3wPD6ZOnkxSnoGk/wL/LwJk3Lx5E09PT0JCQoiNjSUgIIDNmzezc+dOjh49StWqVfHz8ysyfXp6Oq6urnh4eBAUFIS9vT2urq707NkTe3t77O3ti+1oASQlJbF9+3YCAgLYvXs39+7d49y5c9y5c4f9+/dz+PBhEhISCAoK4vbt2xw4cIBDhw6xbds2yfIxgBcvXjBhwgSOHDnCpUuXOH36tMQ2Ojoaf39//vrrryLz9+zZM0xMTDh8+DBpaWmcPHmSPXv24OLiwvbt28nKymLLli0cOHCAgwcPkpGRQUJCQkmKuVQkPI1FI3cEG0BDW5vUlBTev3tXovTmQwbRqHlTybFIJCIrs+SdkE8x03WmJOCAvb092tofXzI6OjqkpKTwLp/W2NjYIu3yX9PW1iY+Lh5bG1tUVVU5ePAgwcHBaGlrsWbtGvr27Uu1atW4euUqAwcMZJDVIMLDwgGklixVpvamTZtSpUoVScV58+ZN/vn7H9oat6Vvv76cDD9JcnIyOTk57Nyxky5duhSj2bUCNMcR+/QpWpqaUvf5cA3ELw0LCwv2799fQOO48eNZ7evLty4uHDp0qJi8VEz5q6urM2XqFKn7iEQiMsr4HFSUfpFIxNs3b7G3t8fCwoJFCxfRoEEDonOXj5WV4jSVXnccampqmJubS85H3rnDvbt3ada8ebno/hTpCQkoamhIjpU0NMhMTSU7d4QYQKVhIzTMzKXSiUQicjIzqdG1G2p5gzCIICczUyZaZ86cLglkYWc/HG3tj3W+jo52Mb5UuJ219WCaN28mlaeMjAwUFRUZaDVAErQmJiaGixcvYWjYslzyERcbi1YeX9DS0eFlPu2fsmlu2BJ5BXl+v3JVYqOqpkYf84/7ke/dieSvu/domiePsuRVfCLVNGt/1KOlwfuXqWS+++hLLQaboWXYFLuAzVj5LUNBWQm7gM1S6QRKxrPYeGpqfXx2a2lr8jrlJWl5yhtAQ1eHpXu3kZ2VxWKnSbx99RqAZsZt0DWoD4hnuM4cOkrDlrKtd57m82vtQurRT9kMtLJix+7drPT2ZuMG6RUu7gsW4DprFo4ODlzMMwj0X+H/xZ6tJk2aoKOjg5ycHI0aNeLly5eYmppKoqLZ2dlx5UrRo15RUVFSs0sWFhY8fvy40BHvorC0tERFRQVVVVVMTU25du0aly9fJiIiAhsbG6ytrblz5w7//vsv165do2fPnlSrVg0VFRX69+8vda8Pm+KvXLnCgAEDqFq1KgoKCtja2nL58mV+//33YvP3IVJcnTp16Ny5MwB6enqkpqYiLy+PsbExQ4cOxc/Pj7Fjx0o1NMqbaxcuYmjchroG+gAMcbDn/MnTn0j1kYbNmjBuxrfIycmhpKyMraMDp46FlJs+39W+koAD1kOsaWvcFgMDAwAcHBwkHZ+8nD93vki78PBwhg0fhry8POrq6lgNsiIsLAwvLy96m/aW/K3EhERmTJ/ByZMn0dbWxj/AXzJdP81lGkFBn14WVlHao6OjUVdTp1178R6b+vXr07hJYyLvRHLnzh1Me5uikru0qb9Ff27eLHq5g+/q1Xk0D6GtsXE+LWEF0pw/d65IO7Hm4Xk0DyIsLIz4+HiioqOxshLvDzQxMSE7O5v79+8D0Lx5c16+fElM7n6YDziOHs3o0aOxHjLkky+Eiir/169fM3r0aPpbiOsJQ0ND2rRpw9nfyrYMo6L05+TksO3XbZLomwMHDiQtLY179+6VSf9HTUX7R0lsivKhrKwsVvr40D43AEaTJk1o1KgRt4rx7/Ik5fdrqLY0pErdugBoDx7C8wvSyxZzcrIxmD4D5dxlj9pDrHn74F/Sk5JQ1tREf8pU8T4tOTl0h9uTfLrkde/n4Ou7VhLIwsZ6KMZt22KQW+ePdBhBePipAmnOn79QpF3TZk2Z6TodOTk5lJWVGe00iuPHgsnIyGDWrJlYWYkj0mppadGlcyeuXr1WLvm4dO48rY2NqZ/rJ3YOIzmd7zn4lE2HTp24eumyVJrsrCyW+KzE+H/tAWjUpAkNGzUi4qZs9vvl58nlG+i0bkH1+uKl6kbDBvLoN2mNgQ4u7LWdSICdM0enzSczLZ0AO2feJCVXiMb/En9evEKTNq3Q0a8HgJn9UH4/LV1fV6mmwqIdW7gafpo1s9xJz7PX2ahzB8a4zUJOXh6RSESPgRbcufK7TDVfOHcO43x15Ml89WhxNr379MFz0SKcRo0i6Ih0JEs3d3c6duzIYCsr7pVgpYhAxVOi72x9CC8J4hEwdXV1UlM/bibMyckhs5gRvcLWe+fk5HzWplsFhY9Ss7OzUVBQICsrCycnJ8aOHQsg6ewEBARITcUqKCiQnv5xSU2VKlWK1JWZmVngfP78KeXZBC0vL1/gHhs3buTWrVucO3eO8ePHs2rVKqkN9+VJSvJzvp/rztINa1FQVOTp4ycsnTWPZq2McFu+hLEDrYtN/8vaDbgu9mB7SBAKigqcCQ4tsLSwvEhOTmbOnDls2rQJRSVFoqOjcZ3pCkCrVq3w9vbG0tKyWLtdO3ehX1+fkBMhKCoqsmfPHq5evVrcn+Xhw4ds2rSJw0cOIxKJuH79Op4enl+U9kmTJrFw4UKUlZXJysrC/Tt3Hj9+zOPHj6lbty5Hjx0lPT2dp0+fMntWwchjn9aslKtl5ic0S9vt2rkT/fr1CTlxooDmb11cWLFiBdNcXEhLS2PKlCmS587AwKBAR0tRUZF58+bx+vVrtmz5uJ/iePCnA0/IuvwnjJ/AYq/FzJw5k6zMLFymufDiRfltsJe1/unfTmeF9woUFRVJTExk4oSJMtL+0T/Kw4cmTpiAp6cnirl19LfTp0utRJAlmSkpPFzxPU28liKnqMD7p0/5d9lSqjVrRsO5btweN5Z3jx4RtcaXZsu9EcnLkZaYxD+LxaHfE4KOoKynR+uffwF5eVL/uEnM9m0y152c/Jw5c9zYuGk9iopKREc/ZpareKljq1ZGrPD+ngGWg4q1W7tmPYu9FnIi9DgKCgoEB4dIlhY6T5qCl9ciJjlPIDs7m+XLvbl9u3yi0T1PTmbBnDms2bQRBSVFnkRH4z5zFoatWuHlvQJbywFF2nxAv0EDYvPVLW/fvuXbCZNw8/RAQUGR9PR05k6fTkIF+dK75ymc8lyFxSoP5BQVSY2JJXz+SrRaNsV0oSsBdrLfy/f/idTnL9jovphZa1eioKhIwpMY/OZ50tCoBZOXeDDHeiT9HezQ1NOlU19TOvU1laRdPHYyR376lTHfzWbV4b3k5ORw/8Ytdq8uenVWeZCcnMzcOXPYkFtHPo6OZlZuPbrc25uBufVoYTYgDjYlEolY7u0tueeNGzfYtGED48aPJzY2lh27dkmu/bptG/vLaRm8QNkR5RS2QDQPV69exc/Pj507dwLg5uZGy5Yt2bFjB/v376dGjRosXrwYeXl5FixYUOg90tPTMTMzY926dbRu3Zrg4GA2b95MUFCQJEqgi4tLoWlBHE3wwoUL7Ny5k3fv3jF06FA2b95MdHQ069atY/fu3SgrKzN27Fisra1p0aIF06dP58CBAygpKeHg4EDPnj1xcXGhWbNm/PXXX4A4OMemTZvYsWMHCgoKuLi40KlTJzp37sy0adMKzV/e9G5ubnTs2BEbGxtJOa1duxYHBwf2799PtWrV+O6772jZsiWOjo4l+g/p3rBiltDIggsP72Ogb1DZMkpNVHTUV6s/KjoKAAN9/coVUkqiosVL3r7+8jeoVB2lRez7X6fvgNh/rph0r2wZpabzuQs0MGhS2TJKxaOofwAw1G9QyUpKR2S0eE+XXxvZhv6WFdP+zJ31izxQuUJKi6Etw5q3r2wVpSbw/g0afsV158Po8lluLmv+16BxmdJff/RvOSkpHSWa2cqPqqoqkyZNwtHRkYyMDAwNDVm8eHGR9kpKSvj6+rJkyRLevXtH9erV8c3zPZWSoKenh729PWlpaUyaNIlGjRrRqFEj7t+/z/Dhw8nKyqJHjx5YW1sjEolwcnJi6NChqKuro6enV+g9TU1NuXfvHra2tmRmZtK9e3dGjRqFgoLCZ+UvL7VqCeDX8QAAIABJREFU1cLOzo6hQ4dStWpVGjRogK2t7WflVUBAQEBAQEBAQEDg6+eTM1sCFYsws1V5CDNblYcws1W5CDNblYsws1V5CDNblYwws1WpfC0zW+0Myjaz9UfUVzizVRSOjo5Se7k+YG9vz4gRI4pN++uvvxYamUxLS4sff/yx3DQKCAgICAgICAgICAhUBOXa2fqwr6s0jBkzhjFjxpSfGAEBAQEBAQEBAQEBgUqkXDtbAgICAgICAgICAgIC5cWX8K2sslCi72wJCAgICAgICAgICAgIfB7CzJaAgICAgICAgICAwBfJ1z6zJUQjFBAQEBAQEBAQEBD4Imlt0LBM6SOiHpaTktIhzGx9YTyy/19lSyg1DfyvY1DG8JyVSVTUv19t+OuPodPLViFVFlHR4orwaw9//TX7T4OvVDvAo+ho9rT9OkN3A4y8Fc7WrzT0+MTc0ON9GxtWspLScfLfSAD2G/etZCWlY+jNkwBfbfj0wPs3vt6w9QCGtti3+Hrbbf73rle2hP8XCJ0tAQEBAQEBAQEBAYEvkq99DZ4QIENAQEBAQEBAQEBAQEAGCDNbAgICAgICAgICAgJfJF97gAxhZktAQEBAQEBAQEBAQEAGCJ0tAQEBAQEBAQEBAQEBGSB0tv4DVDXuRh3vvdRZfQCtGSsQVa1WwEaxXiN0PLegt3w3est2oNSgeQGbWqNd0Z7rWxGSATA17UVIyDFOnQpjw4b1qKqqltpu8+YNLF68UHLcrFlTIiP/JDg4SPJr2LBB6bX27k3IiROcOn2aDRs3FqqhKBs5OTk8PT05deoUv509i4ODgyRN69at2X/gAMHBwZwIDWWItbXk2hBra0JCQggODubAwYO0atWq1PoLajUl5EQwp06fZMNGv6LLvgg7ZWVlVvp4ExoWQlj4CVb6eKOsrCyVtkeP7gQHHys3zVK6THsREnKUU6dC2bBh3Sd8p3i7TZs3sHixJwBq6mocDw6S+v374D7jxo0tm14Z+U/16tVZs3Ytx4ODOXXqFNZ5/OcDP/zwAxMmTiyT/vLKywd0dXW5fPUqNWvWlJzr3KULR44eJTgkhIOHDtGmTZty01wUej06YrFvCwMP/0J3Hw8UqqkUaVvXtCvDLh6ROtd/zwYGHPgJi4DNWARspoXTMFlLlqJej47YBm5h+JFf6OvjgWIx+vVNuzLmUh79IhGdZoxn6MEfGbp/K/1WL6RKzeoVoPojnXqZsPXYQbaFHcNj/WpUVAu+uz4wd+X3DBs3RnIsJyfH9MUe/HwiiJ9PBDHRbbbsBedDp3sn+gZsxfzQNjqvLN5/9Hp1ZfCFIKlzdfr0oM/ujfQL/JFu65ahVF1d1pKlaNezO6uO+LM25ACua7ypWq1g+fewssDn8F58Du1h6d5faGjUAgAFRQUmLnbH91ggvscCGT1vJnJyX16TMicnh3nrAvn58PnKliKFcc9ueB/ey+rgA8zwXVFo2Xe3ssD70B5WHNyN156faWjYooDN6O9cmbup4tptlUVOGX+VzZf3ZAh8FnJqNdB0XkiC71yeutqSkfiUWiOmSdmIlJTRcd/Ay6AdxH7nQMrBn9GctlTKplrnvqh2t6gw3bVq1cLHx5vJk6fSp48ZT548Zt68OaWymzRpAh06dJA61759O44cOYql5SDJ7+HDR2XQ6sNkZ2f69O7Nk8ePmefmVmKbkQ4ONGjYEDMzMwZZWfHNN99IGpKbNm/Gd/VqLC0tGePkxIIFCzAwMKBhw4a4u7sz2skJS0tL1q9fz+YtW0qlv/D8eDPZeQp9evflyeMnzHOb+1l201ymIi8vT39zS/qbW1JFuQpTpk4GxB2xWbNd8duwHnkF+XLRnF/XSp8VTJ48jT59zHn85Alz5xVsaJXETuw7H8P2vkp9xQDLQZLfvoBArl+/wfbtO8ukV1b+s+qHH4iPi2OApSUODg4sWrwYHR0dABo1bsyevXuxsLQstfbC8rIyj87Hjx8zt5C8FGdjY2NDQGCgRCeAoqIi6/38+M7NDUsLC/zWr2e1r2wbEMo1q9N58WwuzPbi2JBveB0TR9vp4wq1VatfB+OZE0EkkpyTr1IF1Xp6BNtNIsTOmRA7Z+5tD5Sp5rxUqVmdXl6zCZ/lxb7B35D6NI6ORehXr1+Hzq4TEeXR32xIfzRaNuWg3RT2D51I6uOndJ41qaLkU71WTWZ7L2Xx1BmMNRtI3OMYxs9xLWBXv1FDfHb+Qo/+0qHx+w4ZRN2GDZhgOYSJA21o07EDJhZmFSUfpZrV+d/i2VyZs5hQ67G8iYmj1bfjC7VVrV+H1jMnSZV/zZZNaTtvGpdnLyZ82AReR8dgOK1sgzqfg3rNGkz5fiGrvp3DdAtbEp7E4DDLRcpGr4E+jnNmsGyCC3OsR3Jg08/MWbcKgP4OdqjXrImr1XBmDbanmXFrulh8WZ8veBCTiNPCnwm9fKeypUihVrMGzssW4jt9Lq6WtiTGPGXELOl2m66BPg5zprN8ogtuNg4c3PwLrut8pGw69+9L94EV126rTLLJKdOvsvkiOluvXr1i6tSplS2j3Dlz5gzbtm2T6d+o2rozaQ/ukhn/BIBX4fsLdJqqtu5MZkIM725dBODtjbMkrv3Y+FHUM6C61WhSDvwkU6156dGjOxEREURFib8PtWvXHgYPHvTZdp07d6JnTxN2794jla59+3Y0btyIY8eOcPjwAczNS/8S7mFikqshKlfDLgYPHlxiG3NzcwL37SMrK4vU1FSOHj3KEGtrlJWVWbt2LRcviv9f4uPjef78Obq6uqSnpzNv3jySEhMBuB0RgaamJoqKiqXOx0etPYiIuF1sfj5ld+3qNfzWbyAnJ4fs7GwiIyOpW6cOAD17mqBSVYVZrrIZaRb7xO0S+k7Rdp06d8SkZw/27N5b6N/R16/PtGlTcJ05m8zMzNLrlZH/VK9enR49erBmzRpA7D9DBg8mJSUFgNGjR+Pv70/w8eOl1l7eedHS0qKfuTlOjo5SaTIyMujSqRN3I8XfPKpfvz4vcvMhK3S7tCc58m9ePX4KwD+BRzGw6FPATr6KMl2WzeOPH6QHO2obNSPz7TtMNyzHMnAr7WY7I6+sJFPNeanbpT1Jd/4mNVf/3X1HaWJZuP7e38/jyipp/S8eRHFl9VayMzIASLr7N6q62rIXnkv77l35O+IOT6MfA3B0jz99Bg0oYDdo1AhC9h3gXEiY1Hk5eTmqVK2KopISikpKKCgqkp6WXiHaAbQ7t+dF5N+8zi3/B4FHqV+E/3Rc6safqzdLna9v2Yeowyd4G5cAQOSWHfz96z7ZC8+ldbcuPLh9l/hocdshzH8/Payk2w4Z6els9lhCStIzAB7cuUsNjdooKCpw7Nfd+Lp+R05ODmo1qqOipsbrl6kVpr8k7A65wrC+/6N/1/JbFVIetO7WmQd3PpZ9+N79BTpNmenpbPVYQkpSMgAPc8teXlEc106voQFW40ZzYGPFtdsESs8XEY3w5cuX3Lt3r7JllDt37sh+NEWhtjaZyQmS48zkRORUVBFVrUbOuzcAKOrqk/UyGY1JHijVb0L221c8370OAJFyVTSnepG0aTHKjQpOUcsKPT1d4uLiJMdxcfGoq6uhqqrK69evS2SnoqLCwoULGD36GxwcRkjd/+3bdwQFHWPPnr00aNCAgIA9xMbGcvv25/+f6OnqEhcbm0dDHOrq6lJai7PR082Xh/h4mrdoQVpaGvsCAiTnR4wYQbVq1fjjjz9IS0sjJiZGcm2BhwcnT54kI7dhVBbEWktQ9sXYnT9/QXK+Th09vhk3lu/c5gMQFhZOWFg4nTt3KrPWwtDV05Eqz/gi9Bdn98F3nEaPY6SDfaF/Z/YcV7Zv30lsnjIoDbLyHwMDAxITExk/YQK9evVCSUmJH7du5dEj8QzuQk/x0kiTHj3KpD8vuvl0xheSl+JsEhMTmTyp8NmTzMxMNDQ0OHr8ODVr1sRl2rRC7coLFW1N3sYnSY7fJiShpFYNhWoqZL55KznfccEM/t1/nJR/HkqlV6ymQsLvf3Jj5UYy37+n6/ff0ebbcfzhs0mmuj9QTUeT1wkf9b/J1a9YTYWMPPpNPGZwb/9xkvPpT4z4+M5VUlOl3aRR3Assv475p9DS1SUxLl5ynBSfQDU1NVRUq/H29RvJeb/FywBx5ywvYQcO09PCHP+Lp5GXV+DGhUtcOf1bhWgHUNHR4m1CouT4XWISioX4T7v5M3h44Dgv/5Yuf1X9urz85xFdfb1Q0dPm5T+P+POHivEdAA1dbZ7Ffyz/5PhEVNRUqVqtGu/eiMs/6WkcSU8/1j1Obq5cP3OWzAzx4FNWZiYOri70dxjOg8i73Lt+s8L0lwTPCeLBtYt//lvJSqSpraNNctzHdltyQiFlHxtHUp53j+O8mdw4c46sjEyUVaoy1duLTe6LaVTI0kKBL48vYmZr6dKlJCYmMnXqVHx9fRk+fDjm5uY4Ojry7NkzIiMj6datG8+fPyclJQVTU9NiO2evX7/m22+/xc7ODlNTU9zd3cnJyeHq1auMHTuWiRMnYmlpyapVq9i4cSM2NjbY2Njw7Jl49ObMmTMMHjwYKysrpkyZIjnfu3dvSQP46tWrOOaOzjo6OrJy5Urs7Ozo168fZ8+e5d9//8Xf3x9/f38OHJDh19Hl5Ch0RWp21sd/yytQtW03Xp06SOz80aSe2Ie221pQUETD2YPU0AAyYh7ITmMhiERy5BTylbqsrKwS2YlEsH79Gry8lpGUlFTguofHQnbt2k12djYPHjzg2LHj9O1bcNSxRFrlPq21OJv810QUzOfkyZOZ6erK+HHjSEtLk5yvWrUqGzZuxEBfH7d580qlPz8lyU9J7YyMjNgXuI/t23dy+vTpctH3KeRK6DtF2YlEsG69L0u8vi/UdwB0dXUwMenBtm3by6xXVv6joKhI/fr1ef3qFUNtbXGZNg0PT0+MjIzKrLko5EqQl5LYFMWzZ8/o0qkTtjY2+KxaRYMGpd9n+Unk5Ar9UmZOVrbk302GW5GdlcXDI6EF7J6evczlBd6kp74iOz2DyJ/3Us+0m+z05kMkKkJ/9kf9LXP1/3W4oP4PqNXVZdC21cTfjCTS/0iRduWNSE5UqP7sPOVfHI4uU0h5/pxhnXsyontv1GpUZ+g4p/KWWSQikajQV29e/2k4bBA5WVlEHTlRwE5OQQFdk87cWOrLSXtn0pKf096j4DJKWSEu/4Lns7MLPqfKVavgusYbnfr12LRgidS13avXM6aTKUlP45iw6DtZyf1PIVdEu62osp/huwId/Xps8RCXvfNSD0J3BRDzT8W22yoTYc9WObBgwQK0tLSYO3cuDx8+xN/fn9DQUHR1dQkKCsLQ0BA7OztWrlzJkiVLGDFiBC1aFN2b/+2332jRogUBAQGEhoby+++/E5m7POXPP/9k8eLFHDhwgN27d1OrVi0OHjxIs2bNOH78OMnJyXh6erJhwwaOHj1Ku3bt8PLy+mQeMjIyCAgI4LvvvmPt2rU0btwYe3t77O3tsbW1Lbeyyk/ms3jka2pKjhVqaZL1+iU5ae8l57JeJJHx9BFp/4rL4O2Ns4jk5FFubEiVZsaoW45Eb8Vuag5zpkpzY7TnrZWJ1pkzp0uCVdjbD0Nb++OSFR0dbVJSUnj37p1UmtjY2ELtmjRpQr169fDwcCc4OAgHhxEMHDiAFSu+R05OjqlTJ1Mtz4ZTkUhU6lmhghp0Cmgtzib/NW1tbeJzZyqUlJRYt24dgwYNwsbaWmoQQU9Pj4MHD5KdlYW9vT2pqaVfojHTdQbBwccIDj6Gvf1wtLW18mgtquyfFmtnZTWQXbt34O29ko0bNpZaW4n0z5wuCVhhV2L9sYXaNW7SmHr16rHAw53jub4zYOAAVqxYJrG1sOxPaGg4b968oazIyn8SEsQjo4GB4n1C0dHR/P7777Rt27bMmmWVl6JQU1PDzNxcchx55w737t6lWfOCgXzKi7dxiVTVrC05rqqlQdrLVLLef6w7Gw4yo7ZhUywCNtNr/TLklZWwCNhMVc3a1DHpjGa7j8uTRCIR2WVYbvq5vI5PRCWP/mpaGrx/mUrmu4/6mw42Q9OwKTYBm7HwE+u3CdgsSafboQ1Ddq7l76AwLiyVTb1fFImxcdTO83xqaGuRmvKS98X4SV66m/flxP5DZGZk8Ob1a8IOHqFtp46ykluAt/EF/Sc9n/8YDDKjpmEz+vpvprvf98grK9HXfzNVNGvzLimZhEu/k5b8AnJyiDoSSu3WLStM/7PYeGpqaUiOa2lr8jrlJWl5/AdAQ1eHpXu3kZ2VxWKnSbx9JZ7BbmbcBl2D+oB4huvMoaM0bCm75/W/xLO4eGpqfmy3FVX2tXW18drzC9nZ2Xg5OfP21WtqaWvRrL0xlk4jWXFwN8NcnGne3ph5Wyr2+RX4PL6IztYH9PX1mTdvHoGBgaxYsYJbt27x9q14On7y5MncvXuXJ0+eMH584ZtQPzBw4EC6devGr7/+ytKlS0lJSZHcp2nTpujq6lK1alVq1qxJly5dAHHDNjU1lYiICFq3bk3dunUBsLOz48qVK5/U3iN3qU6TJk0keyYqgncRV6jS2AgFnXoAqPW15e31s9I2ty6hoKUniUBYpbkx5OSQ/uAuT6ZYEOvmQKybAy8CN/P+/k0SvKfLRKuv71pJsApr66G0bdsWAwN9ABwcRhIefrJAmvPnzxdq98cfN+natYfkfrt37+XYseO4ubmTnZ1Nv359GDFCvDysTh09LCzMCQkpenS3OM6fO0dbY2MMDAxyNTgQHhZWYpvw8HCGDR+OvLw86urqWA0aRFjuNd81a1BVU8PGxkZq2WC1atXwDwjgxIkTuLi4SM12lQbf1WuwtByIpeVArIfYFqK1kLI/d6FIuz59erNwkSeOo5wIOhJUIG154+u7VhK0wsZ6KMZ5fGKkwwjCw08V1H/+QqF2N/+4RbeuJpL77d69l+PHjuOWuwwSoFOnjly6eKlctMvKf2KePOH27dvYDh0KgIaGBu3btyciIqJcdBeVF+M8OkcWkZdP2eQnKyuLlT4+tP+fOFhJkyZNaNSoEbduym5ZUtzlG9Ru3QK1+uK9hk2GDiTmt8tSNqGjXAgeOpEQO2d+c5lPVlo6IXbOvEtKpqq2Bu1cJyKvrIRITo7mjrZEh50t7E/JhJjLN9Bq3QL1XP0thg0kOp/+ww4u7LedyEE7Z0KmifUftHPmbVIytZs3xmz1Is7MX0nEjv0VpvsDN85fokXb1tTRFzfYrUbacelkyWfH/428Sy8LcQddXkGBLn16ce+W7Hw/PwmXb1CrVQtUc8u/4VArYn+TrjNOO04jfNgETto7c2GaO1lp6Zy0d+Z9UjJPT55Dt0dnSQTCOn268yLyrwrT/+fFKzRp0wodfXHbwcx+KL+flvbfKtVUWLRjC1fDT7Nmljvped5DRp07MMZtFnLy8ohEInoMtODOld8rTP/XTMTFKzRuYyQp+752tlzPX/YqKnhu38K18DOsm+VORm7ZP09IZEpPC9xsHHCzcSBw/Wbu37iJ9yTZtNu+FL72ma0vYs/WB+7cucOsWbMYM2YM5ubmUstRXr16xZs3b3jz5g0pKSnUqlWryPvs3LmT0NBQhg8fTteuXfn7778l98kfYEBeXjpaWna29BKGnJwcqc3xH+6Tf8P8h7DXeaMNVQTZqS9I2uyF1kxvRAqKZCbEkLRhIUoNW6AxcQGxbg5kvUwmcdVsao9zQ065KjkZ6SSsnkNORsVtJs5PcvJz5syZx6ZNfigqKhId/RhXV3GUwVatjPD2/h5Ly0HF2hXH9OmzWLbMi6FDbZCXl8fLaykPHpRuyj05OZk5c+awadMmFJWUiI6OxnXmTFq1aoW3tzeWlpZF2gDs2rkT/fr1CTlxAkVFRfbs2cPVq1dp164dAwYM4MGDB1JLTVesWIGRkRF16tTB3Nwc8zwj/iNHjixzZ16sdS6bNm1AUSm3TGfOAsjN03IsLQcWa+c+3x2RSIS393LJfa/fuIGnx8JC/2Z5IvYJNzZuWo+iohLR0Y+Zlcd3Vnh/zwCJ7xRu9ykMDAyIiXlaTnpl4z8AkyZOxGvJEkaNGoWcnBzr1q6VaWfrg86NeXTOys3LCm9vBuTJS36b4nj79i2TJkzAw9MTRQUF0tPTmT59OvF59pSUN2kvUri6cBXdfTyQU1TkdUwslxespFbLpnRa6EqInXOx6f/dfxzVurr037sJOQV5En6/xZ0tu2SmNz/vn6dw1nMV/VaJ9afGxPLb/JVotGyKyUJXDn5Cf8fp4xCJRHScPp6O08UDmK9i4wifubgi5JPy/Dk+8xbg6bcGBUUF4h4/wXuOO02NDHH93gvnQcWvCNm0zJtpCxfwS+hRsrOzuXnpCgE//lIh2kHsP9cX+dDZxxM5BQXexMRxzcObmi2b0t7TlZP2xZd/3LkrVNXWpOdPPyCSk+NtXALXF/9QQeoh9fkLNrovZtbalSgoKpLwJAa/eZ40NGrB5CUezLEeSX8HOzT1dOnU15ROfU0laRePncyRn35lzHezWXV4Lzk5Ody/cYvdq/0qTP/XTOrzF2ye78XMNd6Sst/gtpCGhi2YuGQBbjYOmDsMR1NPlw59e9Ghby9J2qXfTOF1ysvKEy9QKkQ5hS2ur2Di4+MZPnw4Y8eO5eHDhyxZsoQXL17g4OCAmZkZM2bMYPr06bRt25bs7GwiIiJYu7boKVNnZ2cGDBiAlZUVt2/fxtHRkU2bNiEnJ4efnx87d4rDOPfu3ZsdO3ZQt25d1q9fD4iDFAwZMgR/f3/q1q3Ljz/+yB9//MGmTZuwtbVl2rRpmJqa4uXlxT///MPOnTtxdHRk2rRpdOrUiZiYGEaPHs3p06fZuHEjaWlpzPxEQyMvj+z/92mjL5QG/tcxMGhc2TJKTVTUvxjo61e2jFIRFS2OuGeg37CSlZSOqGjx5vEGBk0qWUnpeBT1D8BX7T8NvlLtAI+io9nT9ssKO/05jLwVztY2X6f+iX+GA9C3sWElKykdJ3OX1+837lvJSkrH0Jvi1QbDmrevZCWlI/D+DYiU4b52WWNoi32Lr7fd5n/vemVLKBFN9Q3KlP7v6Khy0VFavoiZrdq1a6Onp8fp06d5//49VlZWgHjzfUxMDMHBwTx58oTVq1eTk5ODra0twcHBWBbx/RgnJycWLVrE1q1bUVVVxdjYmJiYGOrXr/9JLRoaGnh5eTFt2jQyMjLQ09Nj2TLxXo5vv/2WJUuW4OfnR/fu3T95rw4dOjBv3jw0NDQkwTQEBAQEBAQEBAQEBErGl/CtrLLwRXS2FBUV8ff3L9Ymb8fqyJHiIyZ16dKF0NDC9+d06vQxHHXe6GkuLh8/5te7d2969+5dIG3Pnj3p2bNngfMfZsoA6tatK7lvhw4dKixCm4CAgICAgICAgIDAl8UX0dkqDcHBwWzZsqXQa5/qjAkICAgICAgICAgIfPl83fNaX3Fny9LSsshlhAICAgICAgICAgICApXNFxX6XUBAQEBAQEBAQEBA4L/CVzuzJSAgICAgICAgICDw3+ZrX0YozGwJCAgICAgICAgICAjIgC/iO1sCAgICAgICAgICAgL5aVjG70A+zP0WaWUhzGwJCAgICAgICAgICHyR5JTx9zkcPXoUS0tLzMzM2L17d4Hr9+7dw8bGBnNzc+bPn09mZuYn7yns2frCmGrUrbIllJoNdy5iYNC4smWUmqiofzEo4+hJZRGVO2pjoN+wkpWUjqjohwA0MGhSyUpKx6OofwC+av9p9JVqB3gQHU3Xhs0qW0apufTwL1obfJ3PbkSU+Nlt2ODrLP+Hj/4CwNmwayUrKR2bIy8BZR/5ryweRkdj3+J/lS2j1Pjfuw6RBypbRukxtK1sBV8UCQkJ+Pr6cvDgQZSUlLC3t6dTp040bvyxbTtnzhyWLl1K27ZtcXd3Z9++fYwcObLY+wozWwICAgICAgICAgICXyQVNbN16dIlOnfuTI0aNVBRUcHc3JwTJ05Irj99+pT379/Ttm1bAGxsbKSuF4UwsyUgICAgICAgICAg8J8kNTWV1NTUAufV1dVRV1eXHCcmJqKpqSk51tLSIiIiosjrmpqaJCQkfPLvC50tAQEBAQEBAQEBAYH/JNu3b8fPz6/A+WnTpuHi4iI5zs7ORiQSSY5zcnKkjj91vSiEzpaAgICAgICAgICAwH8SJycnrK2tC5zPO6sFoKOjw/Xr1yXHSUlJaGlpSV1PSkqSHD979kzqelEIe7YEBAQEBAQEBAQEBL5QRGX6qaurU7du3QK//J2trl27cvnyZZ4/f867d+8ICwvDxMREcr1OnTooKytz48YNAI4cOSJ1vSiEztZ/EEOTLrgf3I7n0b2M+2EJVaqpFLDpOcKWBYd3Mf/QTiatW4FqrRoVrtPUtBchIcc4dSqMDRvWo6qqWmq7zZs3sHjxQslxs2ZNiYz8k+DgIMmvYcMGZdPbuzchJ05w6vRpNmzcWLTeIuzk5OTw9PTk1KlT/Hb2LA4ODgXS1q1Xj1t//kmrVq0KXDMzM+NOZGSZ8vBRoykhJ4I5dfokGzb6FZOXwu2UlZVZ6eNNaFgIYeEnWOnjjbKyMgD6+vrs3LWD4OBjhJ8MZfyEceWiWUqXaS9CQo5y6lQoGzas+4TvFG+3afMGFi/2BEBNXY3jwUFSv38f3GfcuLFl1yxD/2ndujX7DxwgODiYE6GhDMkzgjfayYmw8HBCw8L48ccfqV27dpny0at3b46fOEH46dOsLyIfRdkoKyuzwseHkLAwQsLDWeHjI/Gb5i1asO/AAULCwgg8eJAuXWUfHa6raU92BAex9+QJlvqtRUW1WpG2C3xWMGL8N4Ve+37TelwXechKphQ9TE3ZHxJM0KmTrNrgR7VCyr8oG/Xq1Vnpt46gUycJOBbECKeehZ8cAAAgAElEQVTRkjSGrVuzff8+9gUf48CJEAYMGSwT/aamPQkOCeLkqRP4bViLahFlXpzdqFEjCTp6kLDwYFb7+qCkpAhA8+bN2Be4l+PBRzh67BA9e366EVQWjEy6suDgDhYd28uE1UsLfdd2HGjOgoPbmX/gV+bs2kJ9w+YAKCgqMnLhXLyCA3Df/ytW08aXaDlSWTDt3ZvgEyc4efo0fkU8u0XZKCsr45377J4ID8c7z7Orr6/Pjl27OBYcTOjJk4ybMEGm+QAw7tkN78N7WR18gBm+K6haraAfdbeywPvQHlYc3I3Xnp9paNiigM3o71yZu8lX5npLQ05ODvPWBfLz4fOVLeX/Ddra2sycOZPRo0czZMgQBg4cSOvWrZkwYQK3b98GYNWqVSxfvpz+/fvz9u1bRo8e/Ym7/gc6W69evWLq1KmVLeOLQbVmDRyXzOfHGfPxshrBs5hYBs+cLGVTr2Uz+owZwapRk1hm7Uji4ydYTZN95ZiXWrVq4ePjzeTJU+nTx4wnTx4zb96cUtlNmjSBDh06SJ1r374dR44cxdJykOT38OGjMur1YbKzM3169+bJ48fMc3P7LLuRDg40aNgQMzMzBllZ8c0339CmTRtJWmVlZdasWYOiomKB+xoYGOA+f365vIwlZeo8hT69+/Lk8RPmuc39LLtpLlORl5env7kl/c0tqaJchSlTxX626gcfjh07hqXlQGyshzJy5Ei6dO1SZt15da30WcHkydPo08ecx0+eMHfe7FLZiX3nY9jhV6mvGGA5SPLbFxDI9es32L59Z5k1y9J/Nm3ejO/q1VhaWjLGyYkFCxZgYGCAkZEREydMwNbGBnMzMx5FRTFr1qwy5WOljw9TnZ3pl6tvTr58FGcz1cUFBXl5LM3NGWBuThVlZSbn1t9bfvyRAH9/LMzMmDxpEl5Ll6KRZyNyeVOjVk3mey/HfYoLI/r2J/bJE6bMLehH+o0asn7XdkwtzAu9j8PE8bT5X8WErq5ZqxZLfLxxnTyFQX36EvPkCTPmzS2xzVzPBbx985Yh/cxwsLale69emPTuDcDqTRvZ6LuW4ZYDmTJmLHMWzKe+gUG56q9VqybeK5czZbILffv058njJ8wtpMyLszM378dop1E4jhqLudkAqigr8803Y8R58PXhx60/McByMLNc57Ler/D6tDxQrVmD0Uvns3WGO4sGit+11q5TpGy0DepjO3sq6ya6ssx2DCFbfsV57fcA9J84mtp6OngNceT7oWOorqlBzxE2MtEK4ufS28eHKc7O9M19LucW8uwWZTPVxQX53GfXMt+z6/PDDxw7doyBlpYMtbbOrfNlN1iiVrMGzssW4jt9Lq6WtiTGPGXErGlSNroG+jjMmc7yiS642ThwcPMvuK7zkbLp3L8v3QdayExnWXgQk4jTwp8JvXynsqX8v8PKyopjx44RGhrKhNyBgx9//FEyCN68eXP279/PiRMn+OGHH1BSUvrkPb/6ztbLly+5d+9eZcv4YmjRtSPRkfdIehwDwPmAQ3QYYCZl8+TuXywaYMf7129QUFKihpYmb14WjNIiS3r06E5ERARRUeLvQ+3atYfBgwd9tl3nzp3o2dOE3bv3SKVr374djRs34tixIxw+fABzc+ky+Gy9Jia5OqJydexi8OCCI7/F2ZmbmxO4bx9ZWVmkpqZy9OhRqRkIryVL2B8YyIvnz6XuWaVKFdasWcPSJUvKlIePGnsQEXG7BHkp2u7a1Wv4rd9ATk4O2dnZREZGUrdOHQD2BezjyOEgQDwYEh0dLblWLvp7dM/VVRLfKdquU+eOmPTswZ7dewv9O/r69Zk2bQquM2eX6KOFxWqWof8oKyuzdu1aLl68CEB8fDzPnz9HV1eXO3fu0KtXL169eoWysjI62tq8ePGi1Pnonk/f7kLyUZzNtatX8Vu/XuI3dyMjqVOnDjVr1kRXT49DB8Tfq3mWlMT9+/fp2bNnqbV+io49unPv9m1icv3j4K69mA22KmBn6+hA0L5ATgcXDO9r3KkjnU16cHiPv8x05qVLjx7cibjN49yy3bdrF5b5yr84m5ZGRhw7dIjs7GwyMzI4d/oM/Sz7o6SsxOa167ia60MJuT6kratTrvp79OjObalnci+DCynz4uysbYbw00+/8PLlS3JycliwYCGHDh0BwGqgNeHhpwCor1+f1NRUsrKyyjUPH2jZtSPRd+6RmPuuPed/kI753rWZ6ens9FxB6rNkAKIj76OuURt5RQXqt2zO9ZCTZKanA3Dr1Dna9TOViVYQ1y23P1EHFWdz7epVNuR5diNzn12AfQEBBB0+DHys8+uUY52fn9bdOvPgzl3io58AEL53f4FOU2Z6Ols9lpCSJC77h3fuUiO37AH0GhpgNW40Bzb+JDOdZWF3yBWG9f0f/bsWXOXy/5OyLSOsbL76ztbSpUtJTExk6tSp+Pr6Mnz4cMzNzXF0dOTZs2dERkbSrVs3nj9/TkpKCqampsV2zkaOHClptOTk5GBmZkZCQgIRERGMGDECa2trvvnmG548ET/k165dk5zv06cPJ0+eBMDNzQ1nZ2csLCw4ffq07Asilxo6WryIT5QcpyQkUVVNtcDyhuzMLFr37sGyU4do3L4tlw8drzCNAHp6usTFxUmO4+LiUVdXK7CsoTg7LS0tFi5cwPTprmRnZ0ule/v2HUFBxxg0yJpZs+aybNkSWrUyKr1eXV3iYmPz6IhDXV29oN5i7PR08+UlPh5dXV0A7OztUVBQwN+/YKPt++XL2b1nD/fv3y+1/oIaS1D2xdidP3+BR4/EM4V16ujxzbixHD8eAkBg4H7ev38PQM+eJrRv147fzp4tF+0Auno6UuUYX4T+4uw++M6M6bPIyi68MTZ7jivbt+8kNk8ZlBZZ+k9aWhr7AgIk50eMGEG1atX4448/AMjMzMTMzIzLV67QsVMnAgMDS50P3Xz64uPiUMuXj+JsLpw/T1Su3+jVqcOYceMIPn6cFy9eEPPkCTZDhwJQr149OnTogGYJNh6XFm1dHRLi4iXHSfHxqKqpFVhKuHrREsKDjhVIr6GlxQzP+SyaOZvsInyovNHR0yU+jw8kxMWjpq4mtZSwOJuIW38y0NoaBQUFqqqo0M/CHA0tLdLT0jm0b58kje0Ie6pVUyXij5vlql9XV4e4PGUeHy/Wln8pYXF2DRoYoFG7Ntt+/YngkCCmz3AhNfUVgKRjdea3cDZtWs+WLT8WeDeUFzV1tXkR/zHk84tC3rXJsfHcOXdJcjx07rdEnLlAVkYmUbcjad+/D8oqVZFXVKDjgH6oa5ZtiW9xlMez+yjPszt23DhCjovbDfsDAyV1vknPnrRr146z5Vjn56e2jjbJcR/LPjkhERU1VamlhEmxcdw8e1Fy7DhvJjfOnCMrIxNllapM9fZik/ti3r95IzOdZcFzwiCsTNpWtgyBcuKr72wtWLAALS0t5s6dy8OHD/H39yc0NBRdXV2CgoIwNDTEzs6OlStXsmTJEkaMGEGLFgXX7X7A1taWI0fEo2TXr1+nfv361KxZkwULFvDDDz9w6NAhxo4di4eHeH3+rl27WLp0KYcOHWLp0qWsXbtWcq8aNWoQEhJC79xlGhWBnJwc5BT8hFthL5yI0+eZ12MAxzf+zLQtq2W+XjwvIpEcOYXozD8KWZSdSATr16/By2uZVGSYD3h4LGTXrt1kZ2fz4MEDjh07Tt++fUqvV66Eeouxy39NlHve0MgIBwcH5ru7F0g3ytGRrMxMAvM0hMpKeeTlA0ZGRuwL3Mf27TsLDCrY2Fjju2Y1kydPJSmx4P9RaZEroe8UZScSwbr1vizx+r5Q3wFxY8/EpAfbtm0vF82y9J+8TJ48mZmurowfN460tDTJ+bCwMNoZG7PG15cdO3eW+lmXK0E+SmJjZGREQGAgO7dv50yu30wcPx4LS0uCQ0OZMWsWZ86cISMjo1Q6S0JRZZ2d9enGubyCAovX/sC6pctJLsKHZIGcqIj6PW/5F2Pzw7JlkJPDvuNHWbt1C5cvXCQzXbqMv5nszJSZM3AZP17Kh8pFf5G+kV1iO0UFBbp174bLtOkMHmRLjerVmT17ppSdaa9+mPYyw9l5Il26dC7XPHxAJBIV7j+FvGuVqlZhwuqlaNavw07P5QCE/ryLuH8fMXf3Vmb8tI4Ht26TlVG2GfTiKM9nd1/us5u/zre2sWH1mjVMnTyZpMTE/LcpN+Tk5CjsU7WFDXooV63CDN8V6OjXY4uHeHWI81IPQncFEPPPA5lpFChvvu6Zrf9M6Hd9fX3mzZtHYGAgjx494tatW9SvXx8QN0BsbW2pUqUKPj4+xd7HwsICX19f3r59y6FDh7CxsSEqKoonT54wefLHvU+vX78GwMfHhzNnznDixAn+/PNP3uQZJWndurUMclo8z+PiMWjVUnJcQ0uDNy9TSX/3XnJOs14d1DVq8+Cm+ENtlw8dZ4TnHFTU1WS6nHDmzOn06yfu8KiqqvLXX39LrunoaJOSksK7d++k0sTGxmJs3KaAXZMmTahXrx4eHuIOiqamJnJy8igrK+PuvoDJkyfx6687JP8fIpHosxtuM11d6de3r1ivmhp/5ZlZ0tHRKVpv27aF2sXGxqKtrS25pq2tTXxcHLY2NqiqqnLw4EEAtLS1WbN2Lcu//56hQ4dStWpVgoODUVRSokqVKgQHBzNmzBgSP+NlNtN1Rp68qPLX/b/yaCyq7J9i3LZg2X+ws7IayJKlXnh6LiLoSJBU2vkL3LGwsGCUgyN375Z9me/MmdPpK+U7JdEfS9tCfKdxk8bUq1ePBRLf0ZD4jpvbfAAsLPsTGhou9Tx/tuYK8h8AJSUlVq1aRZMmTbCxtiYmRry0SV9fH01NTUko23379rHs+++pXr06KSkpn52n2NhY2uTRp11IPj5lM9DKisVLl7LI05OjuQNbAHIiERPHjZM07H7duZNT4eGfrbGkJDyNwzDPnklNbW1SU1J4n+//pDBatDJCr149XOaL97PUzvUhJWVlVny3QGaa42Kf0iqPT2vpaPMyX/kXZ6NTU4/Vy1eQ+vIlAOOnTOFxtHipnqKSEktX+dCwSWMcbWyJjXlaLppnzPyWvn3FA475633tIp7dp7FxtMlT9+S1S0hMJDQ0jNevxc/m4cNBuHw7FUVFRczN+3H8eAg5OTnExMRw8eIlWhq24PLlK+WSl7w8j0ugQWtDyfGH5fh537UgngGbumElcQ+i8R07jYw08bLBatXVCf91LwdWib/902FAP8nyf1nwtATP7qdsBlpZ4ZX77AbleXYB3BcswMLCAkcHB+7dvSuzfAA8i4unceuPK1VqaWvyOuUlafnKvrauNnM3+vL0YRReTs5kpKVRS1uLZu2N0TXQx9JpJKrVq6Oipsq8LWvxnjRdproF/v/y1c9sfeDOnTuMGzeO7OxszM3N6du3r2SE5tWrV7x584bk5ORPNjBUVFQwMTEhNDSUK1eu0KdPH7Kzs6lbty5HjhzhyJEjHDx4kD17xHuERo4cSUREBEZGRjg7O0vdq0qVKrLJbDHcu3QNgzaGaNavC0B3O2siTktHslHX1GCsz2Kq1agOQIeBZsT++1Dm+7Z8fddKglVYWw+lbdu2GBjoA+DgMJLw8JMF0pw/f75Quz/+uEnXrj0k99u9ey/Hjh3Hzc2d7Oxs+vXrw4gR9oB4mZuFhTkhIaGfpzc34IClpSXWQ4bQ1tgYg9wN4w4ODoSHhRXUe+5ckXbh4eEMGz4ceXl51NXVsRo0iLCwMLy8vOhtair5W4kJCcyYPp2TJ08yZPBgzM3MsLS0ZOyYMbx//15s85mjhr6r12BpORBLy4FYD7EtRGMhZX/uQpF2ffr0ZuEiTxxHORXoaH3n7kbHjh0ZZDW4XDpaIPadD0ErbKyHYpzHJ0Y6jJDs05DSf/5CoXY3/7hFt64mkvvt3r2X48eOSzpaAJ06deTSxUsF7vlZmivIfwB816xBVU0NGxsbSUcLQEtLi/V+ftSsWROAIUOG8Pdff5WqowVw4dw5jPPoG+ngwMl8+SjOpnefPnguWsSYUaOkOloAy1asoJ+5OAhFu/btadK0KRcvXCiVzpJw7cIFDI3bUDfXP4Y42HP+ZEE/Kow7N29h3b0XYwYOYczAIRze48+p48Ey7WgBXD5/gdZtjSWBK4Y5OHAmX71ZnM1wh5FMdRXPAtXS0MDGfjjBuc/vct/VVFNVZbTN0HLraAGs8V3HwAFDGDhgCLY2wzE2bvOxPh9pz8lCnt0L5y8UaRcSEsqAARaSSHj9zPoSEXGbjIwMXGfNwMpqACD2/S5dOnHt6u/llpe83Lt0jQatDdHKfdea2A3hz3zvWmUVFVy3+XEz/Cw/z/GUdLQAWpv2wGHR3Fy7qvQZbc+14wXrhPIi/3PpUIJn16GQZ9dp1KgCHS03d3c6duzIYCsrmXe0ACIuXqFxGyN09OsB0NfOluunpZctVvm/9u48rua0/x/469QJ0UxoMHZpwjDKuC0ZBqVvWpRSslXW7DWFkDUtaLgxFMPM/CxZCinLJJQwYwsjRsjcqGRrqI6lqM75/P4wfcYZ2ymT63Od3s/HYx6386l77pfuc07n/bmu9/WuWRPzNq5F6qEUrJw6CyV/rdLm3c/FxF52mDlgGGYOGIYdq77H1XPnqdAilYr7lS25XI7S0lKcOXMGXbp0wZAhQ5Cfn48jR47AxuZFs+qCBQvg4eEBlUqFBQsWqG31ex1XV1f4+/vD0tIS1atXR8uWLaFQKHD27Fl06tQJsbGx2Lt3L1atWoXMzExs3bpVvLNcWc24mnqSV4DNcxZizPJQyPX08Oet29gUGIJm7dpg2IKZWOQ2Atd/u4ADP2yE3/oIqJRKKHIfYJ1v4AfN+fBhHgICZmDNmgjo6ekhKysbU6a8OGWwffsvEB6+EPb2Tm/9vrf55pupCAsLhpvbAOjq6iI4OBTXr1d8y8DDhw8REBCANWvWQK9aNWRlZWGKv/9fedsjPDwc9vb2b/2+zVFRaN6sGfYnJkJPTw9bt27F6dOnK5zp/f4u07FmTST0qv31M/Wf+tLfZRHs7fu99ftmzZ4FmUyG8PBF4r/37LlzWB25BmPGjMadO3ewefMm8Wvr12/Ajh07/6X8eQgImInVa1ZBT68asrKyMfWl587i8IVwEJ87r/++d2nRogVy/sUPnJX5/OnYsSMcHBxw/fp1xP51wAQALF68GMeOHUNkRASiY2KgLC3F/dxceI8d+15/jxkBAYj4K192Vham+fujffv2WBgeDse//g6v+x4ACJw9G5DJsDA8XPx3njt3DkFz52L2zJlYGB4O32++wdPCQowbPfqVFY9/U/7DPIRND0RY5Ero6enhdnY2gqfOQJv2X2DmolCM6Odcaf/bFZX38CHmBkzHf9dEQk9PD7eysjF7ylS0bd8eQeGL4G7f743fAwA/rl6Dhcv/i10H9gMyGSKXLUf6xYsw6/glbBzskXn9BjbG/t3Tt2JxOE4c+/eOnX74MA/TAwIRufrFzzw7KxtTp84A8OK1u2hxKPo5OL/1+zZHbUVtQ0Ps2bsLurq6SL+UjoVhiwEAE8ZPxoLgeRg7bgxUKhUWLVqC33+vnNPcHuflY9OcMIxdEQZd+YvftRtmBaNZuzbwDJ6JMNcR6D3UFUaNPkUH657oYP33MfQrRvnixK59MG7fFvN2b4aOji5+3bkHvx1MqZSswIvX7vSAAES+9Lqc+tdrd1F4OPr99dp93fcAEE/DXfSP1+6ayEiMHjMGd+7cwabNm8WvbVi/Hjvfoz/0bR7l5eP72cHwXxEOuZ4e7t/KQeTM+WjZ7nOMDZmDmQOGoe8wd9Rr1BCdrXujs3Vv8b8bOmoinhQoKiUXqUTsdwK+F5nwug26HCkpKYGnpyf09PTw7NkzsUnz888/h0qlgpWVFX788Ufs2LEDgiDA1dUV48aNg729/Vv/vb169cKqVavErYDnz59HWFgYnj9/DgMDA4SHh6NZs2ZYtGgRkpOTIZfLYWFhgf379yMlJQXBwcHo0qULBgwo31Guk77oXrEfhAREXjqOFi0+Yx2jwjIz/4cWzZuzjlEhmX9tBWrRvCXjJBWTmXUDAGDcwpRxkoq5mfkHAHD9/DHhNDsAXM/KwlctW7OOUWEnbmTArAWfr92LmS9euy2N+fz537j5Ykvy+HaVP9etMnyf/mIFviWnr98bWVkY/PmHGZ1QGaKvnAXSY9/9jVLVzpV1Ao20eM/3x8y/3qdY4X5lS09P77UnuL3s5cJq9z+Wv/9JEARcu3YNderUUeu5+vLLL7Fz56t35gMDAxEY+PeqUFBQEIAXd5UJIYQQQggh74Pvrifui62KSEhIwNq1a1/7NRcXF/z444/v3GpICCGEEEIIIW9TJYutsqb1NxkxYsSHC0MIIYQQQgjRSlWy2CKEEEIIIYRIn4zzEzL43gRJCCGEEEIIIRJFK1uEEEIIIYQQaZLRyhYhhBBCCCGEkH/gfs4WIYQQQgghhEgRrWwRQgghhBBCSCWgYosQQgghhBBCKgEVW4QQQgghhBBSCajYIoQQQgghhJBKQMUWIYQQQgghhFQCKrYIIYQQQgghpBJQsUUIIYQQQgghlYCKLUIIIYQQQgipBFRsEUIIIYQQQkgloGKLEEIIIYQQQioBFVuEEK2kVCpZR6jSiouLWUeo0vLy8lhHIIRUwJEjR1hHIP8yKraqgHPnzmHbtm0oLi7GmTNnWMcpl8DAQNYR3tv169dx9uxZnDlzRvyHF97e3ti/fz+XH5zd3NxYR3hvCoUCW7duRWRkJCIiIsR/eGBjY4MFCxbg4sWLrKNUSEhIyCvXZsyYwSBJxQwbNox1hPemUCgwZ84ceHl5oaCgAIGBgVAoFKxjlUvZe2dWVhaOHDkClUrFOJHmcnNzAQBnz57Fli1b8OzZM8aJNBcXF/fKtS1btjBIUn5LlixhHYH8y+SsA5DKtXHjRiQlJSE3Nxe2traYN28e3NzcMHr0aNbRNHLt2jU8ffoUtWrVYh2lQubOnYtjx46hWbNm4jWZTIZNmzYxTKU5b29vxMfHY8mSJejVqxdcXFxgZmbGOpZGPvnkE5w9exZmZmaoVq0a6zgVMmnSJNStWxempqaQyWSs45TL/v37ceDAASxbtgwPHz6Es7MznJycUK9ePdbR3mr27Nm4desWLl26hD/++EO8rlQq8ejRI4bJyqdNmzaIj4+HmZkZatSoIV5v1KgRw1TlM3fuXHTv3h0XL15EzZo1Ub9+fQQEBGDdunWso2kkIiICN27cwLRp0zBs2DB89tln+PXXXzFnzhzW0d5p/vz5KCkpwahRozB16lR0794d58+fx9KlS1lHe6sNGzbgyZMniI6Oxu3bt8XrpaWl2LdvHxc3IZo2bYrAwECYm5urvXadnZ0ZpiLvg4otLRcXF4ft27fD3d0dderUwc6dOzFw4EBuii0dHR1YWlrC2NgY1atXF6/zUqycPHkShw4d4vbDfpcuXdClSxc8e/YMiYmJ8PX1hYGBAdzc3DB06FBJ/71+//13eHh4qF2TyWS4cuUKo0Tlp1AosHnzZtYxKkRfXx/Ozs5wdnbGoUOHEBoaioiICHTr1g0zZsxA8+bNWUd8rTFjxiA3NxdhYWGYPHmyeF1XVxcmJiYMk5XPhQsXcOHCBbVrMpkMycnJjBKVX05ODgYNGoRt27ahWrVq8Pf3h5OTE+tYGjt8+DC2bt2KTZs2wcnJCdOnT8eAAQNYx9LI77//jtjYWERERMDNzQ0+Pj5wdXVlHeudWrRogUuXLr1yvXr16li8eDGDROVXp04dAHjl9UvFFr+o2NJyOjo6ah+Iq1evDl1dXYaJyicgIIB1hPfSsGFDPH/+XNJFybucPn0au3fvxvHjx9GzZ0/Y29vjxIkTmDBhAn766SfW8d7o1KlTrCO8t1atWuHSpUv44osvWEcpt6ysLOzZswf79u1Do0aNMG3aNNjY2ODUqVPw9vbGwYMHWUd8LV9fX+zduxdNmjRBly5dWMepsMOHD7OO8N50dXXx+PFjcVU3MzMTOjr8dD+oVCrUqFEDKSkp8PPzg0qlQlFREetYGlEqlVCpVEhOTsaCBQtQVFTERfbevXujd+/esLOz4+rmyMsWLVr0yjWetnCSV1GxpeW6dOmC8PBwFBUVISkpCTExMbCwsGAdS2NdunTB5cuXUVhYCEEQoFQqkZOTI/kPQWW9ZkqlEv3790enTp3UitzXvZlKkaWlJZo0aQJXV1fMmzdP3NLQtWtXyd/lzMvLw549e/D06VMIggCVSoWcnBx8++23rKO9k5WVFWQyGZ49e4aEhAQ0aNAAurq6EASBm9WJkSNHYsCAAfh//+//oXHjxuL1Xr164fjx4wyTvZ2enh6GDBmCjIwMeHl5vfJ1XlbVMzMzsXnzZvG9s+z5z0vfCgD4+PjA09MTd+/excSJE5GWloaFCxeyjqWxbt26oV+/fqhRowY6d+4MDw8PWFpaso6lEWdnZ/To0QMdO3aEubk57O3tMWjQINaxNHbnzh1Mnz4dCoUCgiCI13l47zx8+DBWrFih9tp99uwZTp48yToaqSCZ8PKzkGgdlUqF7du348SJE1CpVOjWrRsGDRoEuZyPOnvOnDlITU2FQqFAy5YtcfXqVXTs2FHSKyrA65tzy8hkMm62A2RnZ6v1m/HEy8sLDRs2RFpaGqytrXHkyBG0b9+ei60kL/cavM7LxYtUlRWGLz/OyclB06ZNGaZ6tydPnuDKlSuYPXs2QkNDX/m61G/0lBkwYAB69+6NlJQUuLi44NChQzAxMUFQUBDraOWSl5eHixcvQqlUwtzcHB9//DFXOwXu3LmDTz/9FDo6Orhy5Qo+//xz1pE0plKpxJXEvLw81K1bl3EizfXt2xczZ858pd+Vh/fO//u///avI8sAACAASURBVENISAjWr1+P8ePHIykpCUVFRZg3bx7raKSC+PjETSqsqKgISqUSK1euxP379xEdHY2SkhJuiq0TJ07gwIEDCAkJgZeXF4qKirj4sOzi4gIAWLt2LcaNG6f2tWXLlrGIVCF5eXlYtGiR2h22O3fucLFFKTc3F5s2bUJ4eDhsbGwwZswYDB8+nHUsjZR9IPDx8cGqVavUvjZ8+HBs3LiRRaxy2b59u7iqXqZx48ZISkpimOrdDAwM0LlzZ0RHR3P14fKfSkpK4Ovri9LSUrRt2xbu7u6SX43+J0dHR4SEhKB3797iNRcXl7fezJKSW7duITo6Gvn5+WqrKzzsbDh79iw2btz4yumPvKzs1qlTh5tVxH/66KOPYGFhgd9++w2PHz9GQEAA7O3tWcci74GPT9ykwqZOnYrWrVsDAGrVqgWVSoXp06e/8gFOqurXrw89PT2YmJggIyMDDg4OePz4MetY77R06VI8fPgQhw8fRmZmpnhdqVTiwoULmDJlCrtw5TBr1iyMHj0acXFx8PT0xMGDB9G2bVvWsTRiaGgIADA2NsbVq1dhbm7OOJHmJk+ejCtXriA3Nxd9+vQRryuVSnz66acMk2lu7dq12L17N1asWAF/f38cPXoUv/32G+tYGuvXrx/y8/NRrVo16OrqikVj2Yqd1A9a0dfXR3FxMVq0aIH09HR06tSJdaRyUygUmD17NoYPHw53d3cAAE+bcXx8fNCtWzd06tSJu9NEZ86cicmTJ3N1euXL/vOf/2DRokX4+uuv1Q7X6ty5M8NUmqlRowZu3rwJExMTpKamwsLCAiUlJaxjkfdAxZaWu3PnDr7//nsAL+7Y+vv7o3///oxTaa5BgwZYu3YtunXrJs6e4GHmk42NDa5fv45Tp06pbTvS1dXFxIkTGSYrn2rVqsHV1RW3b9/Gxx9/jG+//RaOjo6sY2nEwsICvr6+mDFjBkaNGoX09HS1Y3SlbPHixSgoKEBYWJjaMdFyuRxGRkYMk2nOyMgITZs2RevWrXHt2jUMGzYM27ZtYx1LY3Z2dmjfvr245TcpKQnJyclcrEoAgJOTE8aPH4+lS5di0KBB+OWXX9CgQQPWscrFyMgIGzZswDfffINLly5h3rx5XB2QIQgCV7PZXtagQQNutru/Ttl8v8uXL4vXeBm74ufnhxUrVmDJkiVYt24dYmJitGJuZFVGxZaWk8lkyMjIEFe3rl+/zs0WQgAICwvD0aNHYWZmBhsbG+zbt4+LngMzMzOYmZnB2toaH330Ees4FVa9enUUFBTA2NgYFy5cQLdu3aBUKlnH0oi/vz+ys7PRuHFjLFu2DGfOnMGkSZNYx9KIgYEBDAwMsGbNGvzxxx9qTd7Z2dlc3J3V19fHqVOn0Lp1ayQlJaF9+/Zcnah17tw5zJ07V3xsbW2NyMhIhonKx8PDA87OzjAwMEBUVBR+//13dO/enXWschEEAYaGhvjpp5+wcOFCeHp64vnz56xjaezLL7/EoUOH0KdPH66KRADw9PTEtGnTYGFhofaZgZcCLCoqinWECisbuQIAsbGxUCgU4k4Nwid+PnWTCim7q192RzM/P5+L09jKGBgYwNzcHEeOHMGQIUPQu3dvyTfYvywpKQmLFy8Wh6HysgWpzIgRI+Dv749Vq1Zh4MCB2Lt3L1fHkF+4cAGxsbEYP348/vjjD+7u7AcHB+Pw4cNqz3le7s7OmTMHO3fuxMyZM7Fz507Y2trCx8eHdSyN1axZEzt27IC9vT0EQUBcXBxXz5/i4mJs3rwZN27cwLx585CRkYFevXqxjlUuZTcJdXV1MXfuXGzfvh3BwcGMU71bmzZtIJPJIAgCoqOjxS2EPL3/x8bG4vnz5zh37pzadV6KLU9Pz9du3eThvfP27duYM2cObt++jS1btmDq1KlYuHAhmjRpwjoaqSA6jbAKKC4uxrVr1yCXy9GyZUuuTnJKSEjAmjVrUFRUhJiYGHEwJC9bIa2trbF69Wq0atWKdZQKK/uAUFhYiMzMTHz++edc9B8sXboU9+7dQ3p6Onbs2IEJEyagXbt2mDlzJutoGrOxscGePXu42f6oTXJychAcHIwzZ86gRo0a6N69O2bNmsXNoRlz5sxB3bp1cfjwYezYsQPz58+HSqXC0qVLWUer0oqLi7n4HczTQSSvk5qaKv65tLQUycnJ+Pjjj/HNN98wTKWZ0aNHY+TIkVi6dCni4uKwY8cO7N69m6uxDUQdrWxpqVWrVsHHx0ec9/RPvPQd/PDDD9i2bRs8PDxgZGSEuLg4jBw5kptiq379+lwWWm963pTh4fnz66+/Ii4uDi4uLjAwMMD69evh5OTEVbHVtGlTrg4EAP6eEfYmPMy5AYAmTZpg3bp1AIDHjx/j3r173BRaAJCeno64uDgcO3YM+vr6CA8P56bfsuyDftkKEfD3wRi8rAwBwKBBgxATEyM+VqlUcHV1xd69exmm0oyZmRlSUlLQs2dPtRmRvPjniIavvvoKAwcO5KLYys/PR48ePbB06VLIZDK4u7tTocU5Kra0VLt27QDwMxPmTXR0dGBgYCA+rl+/Pld739u1awdfX190795d7UQkqW/FKHvepKSk4OnTp3BycoJcLkdCQgI3PWhlz5OyD2vFxcVcPXeAFycqOjg44Msvv1S7Gy7lYjcqKgqCICAyMhJNmzbFgAEDoKuri7179yInJ4d1PI3t2LED586dw/Tp0+Hs7IxatWqhf//+GD9+POtoGpHJZCguLhaf//n5+VysSAN/zym8evUq4yQV4+XlJa6stGnTRrwul8thZWXFKla5JCcnqxWKAF+F7p07d8Q/C4KA//3vfygoKGCYSHM1atTAvXv3xNfr2bNnuVgNJW9GxZaWKntD37dvn+QHAL+NqakpNm/ejNLSUly5cgVbt25V++UldU+ePEGtWrWQlpamdl3qxVbZnLCtW7ciJiZGLFLs7OzEI5ilztbWFn5+flAoFNiwYQP27NmDfv36sY5VLl9//TW+/vpr1jHKpWxGWEZGhlpROGrUKAwYMIBVrHLbtm0bvv/+e+zbtw99+vTB7Nmz4e7uzk2x5eXlhZEjR+LPP/9EWFgYkpKSuDkgpkx2djbS0tLg6OiI+fPnIz09HQsWLJB832hZX1BoaKjaaaI8+fXXX1lHeC8eHh7in2UyGerUqcPN/xeBgYEYN24csrOz0b9/fygUCnz33XesY5H3QMWWlnv27Bnu3r2Lhg0bso5SIfPmzcOaNWtQvXp1zJo1CxYWFlwdpbto0SKUlJTg5s2bUCqVMDU15eo0yMePH6OgoEDcPvXgwQMUFhYyTqWZsWPH4pdffkGjRo1w9+5d+Pj4cDfk0sXFBdeuXUNqaipKS0vRtWtXfP7556xjaezkyZPo1q0bAODo0aPcbUeqX78+jh49Ci8vL8jlcq5OwnN2dsYXX3yB06dPQ6lUYs2aNVzdqAJefOgcOHAgkpOTcfPmTQQGBiI0NBTR0dGso2kkICAAhw4dwtOnTwG8mJOXk5PDxVa2oqIiRERE4OTJk1AqlbCwsMA333yDmjVrso6mkcOHD7OOUGGffvopdu7ciczMTCiVSu567cmr+PnURyrk4cOHsLKygpGRkdo2Nl76JrZu3QovLy9MnTqVdZQKuXTpEnx9fVG7dm2oVCo8ePAAkZGR3AzYHT9+PJycnNCxY0cIgoC0tDS147ClbOzYsXBxcYG/vz+3v6ji4+MREREBa2trqFQqTJ48GRMmTOBi5kpoaChmzJiBP//8E4IgoHHjxlydhPrZZ59h3LhxyMnJQbdu3eDn5wczMzPWsTTm4OAAFxcX9O/fH/Xq1WMdp0KeP38OZ2dnzJ49G46OjujUqRMXcxbLTJ06FQqFAtnZ2ejUqRNOnz6Njh07so6lkeDgYOjr62PhwoUAgO3bt2P+/PnivEupy8vLQ3BwsFqxGBQUhE8++YR1tHfy8PBA8+bN4eLigj59+nD7+4u8RCBa7caNG8L69euFcePGCRMnThRiYmKE7Oxs1rE0tmrVKqFv376Ct7e3kJCQIBQXF7OOVC6DBg0S0tLSxMfnz58XXF1dGSYqv/v37wuJiYnCgQMHhAcPHojXDx8+zDDVu50+fVoIDAwULC0thaCgIOHChQusI5Wbk5OTkJeXJz5++PCh4ODgwDBR+eXl5Qn5+flq11auXMkojeZKSkqE1NRUMXtycrJQUlIiCIL0n/uCIAg5OTlCRESEYGtrK3h7ewv79+/n7v3T3d1dSExMFL766ivh/v37wqFDh7h6/7S2thZUKpUQEhIiXL58WcjOzhYGDBjAOpZGHB0dX7lmZ2fHIEnFTJo0Sfjxxx+Fx48fCwqFQli3bp0wduxY1rE0lpqaKsyaNUuwsrISFixYIFy8eJF1JPIe+OoWJ+X2/fffIy0tDe7u7nBxccEvv/zCxZyJMpMnT0ZiYiLGjh2L06dPo3///ggODuamSbewsFBtFatDhw5cbUUCXmyl6tu3L2xsbGBkZCReX7lyJcNU79alSxcsXLgQCQkJMDc3h4+PD/r164cNGzZwc3dcpVKhTp064uO6detyc8hBmTp16qB27dpq13jY4iOXy9G5c2cxu5WVlbgFWOrPfeBF79ykSZOwf/9+DBw4EIsWLUKPHj0QFhaG/Px81vE0EhwcjCNHjmDevHmoX78+fv75Z4SGhrKOpTEjIyPIZDIYGxsjIyMDTZs2RUlJCetYGhEEQZwPCQCPHj3iahvwrVu3MHr0aBgYGODjjz+Gt7e32qEZUte5c2fMnTsXPj4+SE5Oho+PDwYMGPBK/zfhA20j1HIXLlxAYmKi+NjKyoq7QwIKCwuRk5ODW7duQUdHB4aGhggLC8OXX34p+e2FhoaGSEpKgrW1NYAXQ47/+cGTVwIHR5KfPn0au3fvxvHjx9GzZ0/Y29vjxIkTmDBhAhcHx7Ru3RphYWHitsGdO3dy13fzOjw8d96Gh/xPnz7FgQMHsHv3bty/fx9DhgyBg4MDjh07htGjR2PXrl2sI75T69at1Q5ZWb58ufhnHuZAmZqaIiQkBEOGDMG0adOQm5vLxXMHeDHQ3s3NDVZWVhAEASkpKRg7dizrWBqTyWRq/ep37tzhpl/65MmTiI+Px4kTJ9CrVy8sX74cHTt2REZGBry9vXHs2DHWEUk58fHMIxXWpEkTZGVloXnz5gBeHHDQoEEDxqk0N23aNJw6dQo9e/bEhAkT0KlTJwAvjvHu0aOH5IutkJAQBAQEYPbs2QBezE3iqW/lbaS+wmJpaYkmTZrA1dUV8+bNEwcDd+3aFa6urozTaSY0NBQrV67ErFmzIAgCunbtivnz57OO9d6k/tx5Fx7y9+nTB5aWlpg8eTI6d+4sXh86dChOnDjBMNm/g4eiJSgoCOfPn8dnn30GX19fnDhxAv/9739Zx9KIq6sr2rdvjzNnzkAQBKxatQqtW7dmHUtj33zzDQYNGgRzc3MIgoALFy4gJCSEdSyNREREwM3NDUFBQdDX1xevt27dGqNGjWKYjFQUFVtarrS0FP3790enTp0gl8tx7tw51KtXD15eXgAg+S2FFhYWCA4OfuUEpGrVqmHWrFmMUmmuRYsW2LFjBwoLC6FSqdRmhpHKtXHjRjRr1uyV6zo6OtzMuqlRowamT5/OOgbhUFJS0mvfb2QyGVfDmd+Eh4JXV1cXBgYGiIqKglwux9ChQ9GyZUvWsTQiCALOnj2LU6dOQalUiqfp8jKr0NLSEubm5rh48SJUKhUWLFigtg1eyt42wHj37t0YMWLEhwtD/hVUbGm5iRMnqj3m7a7I205d27hxo+TnVZ09exYbN26EQqFQuy71IlcbvK7QKnP48GH4+Ph8wDQVs2HDBqxevRqPHz8G8OIDEE+DRQk7b7uxc+nSpQ+YpOratGkTtmzZAktLS6hUKmzYsAHjx48X5xhK2bfffousrCy4urpCEATs2rULt27d4mZWVV5eHn7++Wfxd+/ly5cBvOgD5xkPK7rkVVRsabkuXbqwjlBpeHjTmTlzJiZPnoxGjRqxjvKv4+Hn/ya8ZN+0aRPi4+O5fP4oFAoYGhqqXbt9+zYaN24MExMTRqn+Hbw8f96E9/y82LFjB2JjY8XCd9KkSfDw8OCi2Dp+/Dji4+PFlazevXvD0dGRcSrNeXt7o1WrVuKQdW3Bw4oueRUVW4RbPLzpNGjQQPKrb28THx//yrUaNWqgZcuWiImJYZDo38HDcwcAWrZsycVcmJfdvXsXgiBg7Nix+OGHH8QP9kqlEt7e3khMTMTSpUsZp3y34uJiHD169LUDaXl+7gP8PP/fhoeCUV9fH3p6emqPeZmZpFQqUVpaKuZVKpVcnUYIQO1wFUJYomKLkErk6emJadOmwcLCQu0kJF4KsOTkZFy+fFk8TfHIkSOoX78+CgsL4ejoSHvHK5mXlxccHR1hbm6u9kFHyh8iVq5cidOnTyM3NxfDhg0Tr8vlcvTu3ZtdsHKaMmXKGwfSvjwgnlSeuLi4V1aBtmzZgmHDhkn6ZLyIiAgAQO3atTFkyBDY29tDLpcjMTERLVq0YBtOQ46OjvDy8oKDgwMA4Oeff+bqJGNra2vs2LEDFhYWau+dPO4SIPyjYouQShQbG4vnz5/j3Llzatd5Kbb+/PNPxMXF4eOPPwYA+Pj4YPz48YiJicGAAQOo2Kpk//3vf+Ho6MjVVpiyQnDdunXiB+KyXjOeZGRk4ODBgwgLC4Orqyv8/Pzg5+fHOta/QuqrQhs2bMCTJ08QHR2N27dvi9dLS0uxb98+DBs2DPb29gwTasbMzAwA8OzZMwBAjx49WMYpF29vb7Rt2xYnT56EIAgYP348VzdLCgsLsXDhQrU5hTKZDMnJyQxTvT+pv3bJ61GxRbjFw5vOgwcPJD8L5m3y8/NRq1Yt8XH16tWhUCggl8sl/+FZG3qGqlWrxm1Dt5mZGQYPHozo6GjcvHkT3t7eWLJkibg6JHX/HEjr7OzMzUBaAPjjjz9gamqqdi0tLQ0dOnTAV199xSiVZlq0aPHaQzyqV6+OxYsXM0hUPpq8ZseNG4e1a9d+gDQV4+bmhri4OPTs2ZN1lApJSUnByZMnxZEfPLl69eor8xQTExNha2sr6RVd8mZUbBFJ471nyMzMDCkpKejZsyd3+90BwMbGBsOHD4ednR1UKhUOHjyIPn36ID4+HvXq1WMd77W0pWcIAP7zn/9g8eLF6Nmzp1rvx8tzk6QqPDwc4eHhAF70nq1btw7Tp09HbGws42Sa4XUg7blz56BSqTBnzhyEhYWJmUtLSxEUFIQDBw5IfpxA79690bt3b9jZ2aFZs2a4efOmePQ4L4Np3+X+/fusI7zVJ598grNnz8LMzIybPrOXNW7cGAqFgstia+LEiRg6dCjGjBmDgoICBAUFISsrC7a2tlys6JJXace7FtFavPcMJScnIyYmRlwF4u3o7qlTpyIlJQXHjx+Hrq4uxowZg169eiEtLU2ywzm1pWcIANLT09X+E3ixFYaH0QHPnz9Hq1atxMcmJiYoLS1lmKh8Xh5I6+Pjg5MnT0r2Of+yEydOIDU1Fbm5ufjuu+/E63K5HIMGDWKYrPwKCwvRt29f1K5dGyqVCg8ePEBkZCTMzc1ZR3tvUt8Z8Pvvv8PDw0PtGk+/u0pKSuDg4ABTU1O1G1U8vHfu2rULoaGhGDx4MB4+fIihQ4dy8d5D3oyKLSJpvPcM/frrr2/8WkpKCiwtLT9gmopp0qQJbG1txTvkZ86ckfTKirb0DAFAVFTUG7+2atUqSc8Ka9myJZYsWYL+/ftDJpNh37593BwOALwYSCuTybBt2za4urri448/ViseparsOREfH89Nb+ibhIWFYfny5WJxlZaWhpCQEOzcuZNxMu136tQp1hHey/jx41lHqDBBEKCnp4eioiLxdxcvw6TJ61GxRSSN556hd1m5cqXki60FCxYgJSUFTZs2Fa/xsrLCe8/Qu0h9MHNYWBhWrFiBqVOnQi6Xo1OnTggNDWUdS2MbN25EUlIScnNzYWtri3nz5sHNzQ2jR49mHe2tAgMDxT+fPn36la9L+STLfyosLFRbxerQoQOeP3/OMJH2KztJ8U146SHt0qULLl++jMLCQgiCII5u4GH2qKOjIwYPHoyQkBA8evQIwcHB2Lt3LzdbsMmrqNgiksZjz5CmeOj/OH78OBITE7nc9857z9C7SP35Y2hoiPnz54uPBUFATk4OPvroI4apNBcXF4ft27fD3d0dderUwc6dOzFw4EDJF1s8fJjUlKGhIZKSksRt5IcOHULt2rUZp/p3SP31e/HiRdy7dw+2traQy+U4dOgQV6eizpkzB6mpqVAoFGjZsiWuXr2Kjh07ws3NjXW0d1q3bh3atm0LAKhbty5WrFiB/fv3M05F3gcVW0TSeOwZ0hQPK3NNmzaV/IeCN+G9Z+hdpP78iY6OxrfffouioiLxWuPGjZGUlMQwleZ0dHTUDgaoXr06F4fc9OjRA/Xq1cOdO3dYR3lvISEhCAgIwOzZswG8eD9asmQJ41Tv5unpiaioKKxevRoTJ0587fdIdYtn2crV4MGDERMTA319fQDA8OHD4eXlxTJauZw4cQIHDhxASEgIvLy8UFRUxMVJlgDw6aefYsOGDXj69CkEQYBKpUJOTg7s7OxYRyMVRMUWkTzeeoa0iaGhIRwcHPDll1+qffDkYSsS7z1DvFu3bh12796NFStWwN/fH0ePHsVvv/3GOpbGunTpgvDwcBQVFSEpKQkxMTGwsLBgHeud5syZg7Vr18LDwwMymUztZgkvc4Y8PT3Fmwk1atRAkyZNIAgC9PX1MX/+fMlvY87JycHy5csRGxsLlUr1ytcnT54s+X7j/Px8tRs6JSUlKCgoYJiofOrXrw89PT2YmJggIyMDDg4OePz4MetYGvHz80PDhg2RlpYGa2trHDlyBO3bt2cdi7wHKraIpPHcM6QNvv76a3z99desY1QI7z1DvDMyMkLTpk3RunVrXLt2DcOGDcO2bdtYx9LY9OnTsX37drRu3Rrx8fHo1asXBg8ezDrWO5XNbjp8+DDjJBUn5V5ETURGRiIlJYV1jPcycOBAuLq6inO2Dh8+jOHDhzNOpbkGDRpg7dq16Natm7gaWlxczDiVZnJzc7Fp0yaEh4fDxsYGY8aM4epnT15FxRaRNJ57ht5Fytvz/vzzT9SrVw9du3ZlHaXCeO8ZAvgezKyvr49Tp06hdevWSEpKQvv27fHs2TPWsTTm7e2Nn376iYsC63VePijjZTysSvPed9a2bVu0bdsWX3zxBXr16oUnT55ApVKJp+ryYMyYMbCwsEBqaipkMhm+++67VwbtSllYWBiOHj0KMzMz2NjYYN++fQgKCmIdSyNl7/nGxsa4evUqzM3NJf15gbwbFVtE0njuGQL4HcqsDVuReO4Z0obBzHPnzsXOnTsxY8YM7Ny5E3Z2dtycZAYARUVFuHv3Lho2bMg6SoW8XLCUlpYiOTkZLVu2ZJio6jE2Noabmxtu3boFQRDQqFEjrFixgpvtzDdv3oRCocC4ceNw8OBBrootAwMDODg4AHixLdXT01P8mouLC+Li4lhFeycLCwv4+vpixowZGDVqFNLT01GzZk3Wsch7oGKLSBrPPUMAv0OZtWErEs89Q9owmHnfvn3i6sqqVasYpym/vLw8WFlZwcjICNWrVxev83CjAXjxgfJlbm5uGDJkCKM0VdP8+fMxZswY2NraAgASEhIwd+7ct87Pk4qlS5fi3r17SE9Ph7e3N2JjY3H16lXMnDmTdbT3JvUbuDdu3MD06dPRuHFjLFu2DGfOnEFWVhbrWOQ9ULFFJI3nniGA36HMb9qCVIaHYpfnniFtGMyckpICPz8/rjK/LDIyEseOHcPTp0/RuHFjKJXK186t4sX169eRm5vLOkaVkp+fLxZaAGBvb481a9YwTKS5X3/9FXFxcXBxcYGBgQHWr18PJycnrSi2pPqeNHnyZFy5cgW5ubm4fPmyeL20tBSNGjVimIy8Lyq2iCRpQ88QwO9Q5rItSCkpKXj69CmcnJwgl8uRkJDATc8T7z1DAN+DmWvXrg1bW1u0a9dObWWIh0IdAJYvXw6FQoHs7Gx06tQJp0+f5uLnXqZNmzZq7zF16tTBlClTGCaqeqpVq4b09HS0a9cOAHDp0iXxKHWp09HRAfB3YVJcXCxeI5Vj8eLFKCgoQFhYGObMmSNel8vlMDIyYpiMvC8qtogkaUPPEMDvUOayLUhbt25FTEyM+EvWzs4O7u7uLKNpjPeeIYDvwcz/3MYGSPeO8utkZGTg4MGDCAsLg6urK/z8/ODn58c6lsYuXryI6OhopKamQi6Xo3v37nB1dWUdq0qZNWsWfHx8ULt2bQiCAIVCgeXLl7OOpRFbW1v4+flBoVBgw4YN2LNnD/r168c6llYzMDCAgYEBN6ufRHNUbBFJ0oaeIYD/ocyPHz9GQUEB6tatCwB48OABCgsLGafSDO89QwDfg5lzc3Mxbtw4tWvLli1jlKb8jIyMIJPJYGxsjIyMDDg7O6OkpIR1LI2FhITg6dOnGDBgAFQqFXbv3o1r166JA4JJ5evQoQMOHDiAzMxMqFQqGBsbi73HMTExGDRoEOOEbzZ27Fj88ssvaNSoEe7duwcfHx9YWlqyjvWvkHrPFtE+VGwRSdKGnqEyPA9lHj9+PJycnNCxY0cIgoC0tDTMnTuXdSyN8N4zBPA5mHnp0qV4+PAhDh8+jMzMTPG6UqnEhQsXuNnKZmpqipCQEAwZMgTTpk1Dbm4uVx/S0tLSsHfvXvGxlZUV+vfvzzBR1aSnpwdTU9NXrkdHR0u62AKAevXqoWHDhtDT00Pz5s1ZxymXq1evvnJ6YmJiImxtbcU+WEI+FCq2iCRpQ88QwP9Q5jZt2mDXrl04f/48Odt9twAADO1JREFUZDIZgoKCuNk7znvPEMDnYGYbGxtcv34dp06dUjt+XFdXFxMnTmSYrHyCgoJw/vx5fPbZZ/Dx8cHJkye5WI0u06BBA9y6dUt878nNzZX01uWqRuqF+6ZNm7BlyxZYWVlBqVRiw4YNGD9+/Gu3B0vRxIkTMXToUIwZMwYFBQUICgpCVlYWbG1tYW9vzzoeqWJkgtRf8aRKGzhwoFrPkEqlgru7O3bu3Mk4mWZsbGywZ88ebocy29nZYf/+/axjVMjr5qjIZDI4OzszSPPvKBvM/HLxLlWPHz/m6saItvD09IRMJkN+fj5ycnLQuXNn6Orq4ty5czA1NcWWLVtYRySQ/qwnR0dHbNu2DQYGBgBeDFj38PBQWy2VsoKCAoSGhiInJwcPHz7E0KFD4eXlBV1dXdbRSBVEK1tE0njuGQL4H8r82WefISIiAubm5moFIw/bIHnvGQL4HsyclJSExYsX49GjRwD+Prr+ypUrjJNpNx8fn9deHzly5AdOQnimr68PPT09tccvz7qUOkEQoKenh6KiIvG9h05TJKxQsUUkjeeeIYD/ocwFBQU4ffq02nwhqW+D1JaeIYDvwcyRkZGIiopSO+CDVL6Xt24SUl4REREAXmzDHjJkCOzt7SGXy5GYmCj5ftGXOTo6YvDgwQgJCcGjR48QHByMvXv3cnGSK9E+VGwRSeO5ZwjgfyhzVFQUAODJkydQqVTicGYp05aeIYDvwcz169enQouQN5D6FlszMzMAEGcT9ujRg2Wcclu3bh3atm0LAKhbty5WrFjB7ZZ4wj/q2SKSxmvPUNlQ5jt37rz267xMg7916xb8/f1x69YtCIKARo0aYcWKFVzc4dSGniEvLy9MnDgRz58/R1JSEnx9fTFkyBAuthGGhYXh/v376N69u9oBJTz3zBFSHkVFRVi1ahVOnToFpVKJrl27ws/PDzVr1mQd7b2MGzdOHM8iVXl5edizZw+ePn0KQRCgUqmQk5ODb7/9lnU0UgXRyhaRNF57hrRlKPO8efMwZswY2NraAgASEhIwd+5cccVLyrShZ4jnwcxPnjxBrVq1kJaWpnadii1SVQQHB0NfXx8LFy4EAGzfvh3z58/HkiVLGCd7P/fv32cd4Z38/PzQsGFDpKWlwdraGkeOHEH79u1ZxyJVFK1sEUnz9PR85ZrUe4a0ibOzM+Lj49WuOTo6cnEilbW1NVavXs31Vrbly5fD39+fdYwKKykpwc2bN6FUKmFqagq5nO7vkarDyckJe/bsUbtmb2+PhIQERon+HVI/SREAbG1tkZiYiPDwcNja2qJZs2YYPnz4K/9/EPIh0G8+Imk89gwB2jOUuVq1akhPT0e7du0AAJcuXYK+vj7jVJrRhp4hngczX7p0Cb6+vqhduzZUKhUePHiAyMhImJubs45GyAchCAIePXok/t569OgRHT3+gRgaGgIAjI2NcfXqVZibm3N9MjDhGxVbRNJ47RnSlqHMs2bNgo+PD2rXrg1BEKBQKLB8+XLWsTTSrl07+Pr6ct0zxPNg5tDQUCxfvlwsrtLS0hASEsLNjDxC3teIESMwcOBAWFpaQhAEpKSkYOzYsaxjVQkWFhbw9fXFjBkzMGrUKKSnp3PfK0f4RcUWkTRee4ZcXFwAAFu3blUbymxnZwd3d3eW0cqlQ4cOOHDgADIzM6FSqdC4cWNxyKXUaUPPUNnz6GW8rHIVFhaqrWJ16NABz58/Z5iIkA/LyckJRUVFUCgUMDQ0hKenp1ZspeVhhejGjRuYPn06GjdujGXLluHMmTPIyspiHYtUUfy/6olWy8/PFwst4MV+9zVr1jBMVD68D2VOSEjAmjVrsHfvXmRnZ8PBwQFz586FtbU162jvtGjRIu57hngezGxoaIikpCTxuZKUlITatWszTkXIhzNt2jTcuXMHJiYmyMnJEa9L+YaPp6cnoqKisHr16jeOypBy/smTJ+PKlSvIzc3F5cuXxeulpaXcnAJMtA9fnzxIlcNzzxDA/1DmNWvWYP369QCAZs2aYdeuXRg1ahQXxRbPPUPaMJg5JCQE48aNw+zZs8Vr0dHRDBMR8mFlZGQgMTGRdYxyycnJwfLlyxEbGwuVSvXK1ydPnowRI0Z8+GAaWrx4MQoKChAWFoY5c+aI1+VyOVczOol2oWKLSBrPPUMA/0OZS0pK8Mknn4iPjYyMuNhCAvDdM6QNg5mPHTsGfX19xMXFITs7G/7+/khNTYWxsTHraIR8ECYmJsjNzUX9+vVZR9FYZGQkUlJSWMeoMAMDAxgYGHC1A4ZoPzr6nUheSUkJlz1DAL9DmcvMnj0bRUVFcHR0hEwmQ0JCAmrUqIHg4GDW0d7pdccu83JsfRmeBzP369cPO3bsEFeii4qK4O7uztXPn5D3MXr0aJw/fx6tWrVCtWrVxOs8jC45evQoevXqxd1JwIRIEa1sEUnjuWcI4Hcoc5n58+cjKioKMTExkMvl6NSpE4YOHco6lka0oWeI58HMJSUl0NPTEx+//GdCqoJ/9lvyxNjYGG5ubtydBEyIFNHKFpE0R0dHrF+/XtzK9vDhQ4waNQq7d+9mnEwz2jCUOScnB//73//Qo0cP3L17F02bNmUdSSOZmZkYN24cCgoKxGvR0dFcbWPjeTDzkiVLkJaWBjs7O8hkMhw4cAAdO3aEn58f62iEkHcYOXIkBg0apHYS8LZt2yR/EjAhUkQrW0TSeO4ZAvgdylymbGXx2bNniI6OxuDBgzF9+nT079+fdbR30oaeIZ4HMwcEBCAxMRFnzpyBXC6Hl5cXNyvShFR1vJ8ETIiUULFFJO0///kPpkyZotYz1KFDB9axNMbrUOYyP/zwA7Zt2wYPDw8YGRkhLi4OI0eO5KLY2r59u9gzVHZQibu7OwYNGsQ6msZ4H8xsa2ur9oGNEMIH3k8CJkRKqNgiksZzzxDA71DmMjo6OmoHktSvX18c0Cx12tAzpA2DmQkh/OH9JGBCpISKLSJp1apVQ9++fWFiYiL2DL18qpPU8b4Vw9TUFJs3b0ZpaSmuXLmCrVu3ok2bNqxjacTa2hrDhw9X6xnq06cP61jlog2DmQkh/OnQoQMOHDggngRsbGws/u6NiYnhaocAIazxcYuaVFkJCQmYMGECwsLCoFAoMHjwYG4OxwD+3opRhretGIWFhbh//z6qV6+OWbNmwcDAAPPnz2cdSyMBAQHw9PTEzZs3kZ2dDS8vL+4OZ7h06RL69u2LmTNnIjAwEL1798aFCxdYxyKEVAF6enowNTVF69at1W5y0nByQsqHTiMkkubi4oKoqCh4eHggPj4eubm5GDlyJH7++WfW0TSSlpaGKVOmvLIVo2zQrtS5urpi48aNXM020yaDBw9GYGCg2mDm0NBQLgYzE0K0k7OzM+Lj41nHIIQbtB+FSBrPPUPAq1sxeBvKrKOjAysrKxgbG6sd0MDT0fU8KywsVCvMO3TogOfPnzNMRAip6mQyGesIhHCFii0iaTz3DAH8D2UOCAhgHaFK04bBzIQQQkhVRtsIiaT5+vqiefPmOHHiBFQqFSwsLDBp0iRuVod4H8pM2NKGwcyEEO3i4uKCuLg41jEI4QatbBFJu337NhYuXIipU6eyjlIhvA9lJmxpw2BmQoh2+eijj1hHIIQrtLJFJG3gwIHIysritmdo9uzZKCoqUhvKXKNGDQQHB7OORjjQr18/cTAzABQVFcHd3R179+5lnIwQos2KioqwatUqnDp1CkqlEl27doWfnx9q1qzJOhoh3KFii0haamrqa6936dLlAyepmOLiYkRFReHMmTNqQ5l5mhVG2Onbty9+/vlncbZWaWkpXFxcqNgihFSqwMBA6Ovrw93dHQCwfft2PH78GEuWLGGcjBD+0DZCImm8FFVvwvtQZsKWNgxmJoTwJz09HXv27BEfz5s3D/b29gwTEcIvfs7QJoRDvA9lJmxpw2BmQgh/BEHAo0ePxMePHj2Crq4uw0SE8Iu2ERJSiXgfykwIIaTqiY2Nxbp162BpaQlBEJCSkoKxY8fCzc2NdTRCuEPbCAmpRLwPZSaEEFL1ODk5oaioCAqFAoaGhvD09BR7Rwkh5UOvHEIqEe9DmQkhhFQ906ZNw507d2BiYoKcnBzxurOzM8NUhPCJii1CKlFhYSHu37+P6tWrY9asWbCwsMCMGTNYxyKEEELeKCMjA4mJiaxjEKIVqNgipBLxPpSZEEJI1WNiYoLc3FzUr1+fdRRCuEfFFiGVSEdHB1ZWVtwOZSaEEFL1PHv2DLa2tmjVqpXauBL63UVI+dFphIRUIt6HMhNCCKl66HcXIf8eKrYIIYQQQgghpBLQGdSEEEIIIYQQUgmo2CKEEEIIIYSQSkDFFiGEEEIIIYRUAiq2CCGEEEIIIaQSULFFCCGEEEIIIZXg/wPc0UK9ZiJzpAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 6))\n",
    "sns.heatmap(data=transactions_master_df.corr(), linewidths=0.5, center=0, annot=True, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "heatMap(transactions_master_df, False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dropping highly correlated fields and other useless fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 788150 entries, 0 to 788149\n",
      "Data columns (total 17 columns):\n",
      "document_type       788150 non-null object\n",
      "price               788150 non-null float64\n",
      "transaction_type    788150 non-null object\n",
      "recording_year      788150 non-null int64\n",
      "recording_month     788150 non-null int64\n",
      "recording_day       788150 non-null int64\n",
      "contract_day        788150 non-null int64\n",
      "area_sqft           788150 non-null float64\n",
      "built_year          788150 non-null int64\n",
      "city                788150 non-null object\n",
      "lot_size            788150 non-null float64\n",
      "no_of_baths         788150 non-null float64\n",
      "no_of_bedrooms      788150 non-null float64\n",
      "property_type       788150 non-null object\n",
      "state               788150 non-null object\n",
      "tax_amount          788150 non-null float64\n",
      "zip_code            788150 non-null object\n",
      "dtypes: float64(6), int64(5), object(6)\n",
      "memory usage: 102.2+ MB\n"
     ]
    }
   ],
   "source": [
    "transactions_master_df = transactions_master_df.drop(columns=['contract_year', 'contract_month', 'tax_year'], axis=1)\n",
    "transactions_master_df = transactions_master_df.drop(columns=['property_url', 'address'], axis=1)\n",
    "transactions_master_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "8\n",
      "45\n",
      "3\n",
      "1359\n",
      "1196\n"
     ]
    }
   ],
   "source": [
    "print(transactions_master_df['transaction_type'].nunique())\n",
    "print(transactions_master_df['property_type'].nunique())\n",
    "print(transactions_master_df['document_type'].nunique())\n",
    "print(transactions_master_df['state'].nunique())\n",
    "print(transactions_master_df['city'].nunique())\n",
    "print(transactions_master_df['zip_code'].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deed                                                                                                                                                                                                                    547645\n",
      "Bargain and Sale Deed                                                                                                                                                                                                   95164 \n",
      "Warranty Deed                                                                                                                                                                                                           55735 \n",
      "REO Resale                                                                                                                                                                                                              22949 \n",
      "Other                                                                                                                                                                                                                   19198 \n",
      "Land Contract                                                                                                                                                                                                           16690 \n",
      "Executor's Deed                                                                                                                                                                                                         13017 \n",
      "REO Repossession                                                                                                                                                                                                        8815  \n",
      "Foreclosure                                                                                                                                                                                                             3087  \n",
      "Administrator's Deed                                                                                                                                                                                                    2595  \n",
      "Condominium Deed                                                                                                                                                                                                        777   \n",
      "Corporation Deed                                                                                                                                                                                                        656   \n",
      "Deed in Lieu of Foreclosure                                                                                                                                                                                             445   \n",
      "Sheriff's Deed - Common in New Jersey. The default code for transfers where borrower is in default, in other states document may be called something other than Sheriff's Deed, i.e. \"Masters in Equity Deed\" in SC.    416   \n",
      "Special Warranty Deed                                                                                                                                                                                                   211   \n",
      "Fiduciary Deed                                                                                                                                                                                                          152   \n",
      "Redemption Deed                                                                                                                                                                                                         99    \n",
      "Joint Tenancy Deed                                                                                                                                                                                                      89    \n",
      "Agreement of Sale                                                                                                                                                                                                       72    \n",
      "Public Action - Common in Florida (Clerks Tax Deed or Tax Deeds). Also when property sold for taxes.                                                                                                                    46    \n",
      "Declaration                                                                                                                                                                                                             42    \n",
      "Exchange                                                                                                                                                                                                                33    \n",
      "Contract of Sale                                                                                                                                                                                                        26    \n",
      "Lease (Hawaii)                                                                                                                                                                                                          24    \n",
      "Vendor's Lien                                                                                                                                                                                                           23    \n",
      "Beneficiary Deed (Buyer ID = \"BE\")                                                                                                                                                                                      22    \n",
      "Commissioner's Deed - In North Carolina used in probate-related transfers.   In Hawaii used in foreclosure-related transfers.                                                                                           19    \n",
      "Personal Representatives Deed                                                                                                                                                                                           19    \n",
      "Satisfaction of Land Contract (Wisconsin)                                                                                                                                                                               13    \n",
      "Deed of Guardian                                                                                                                                                                                                        12    \n",
      "Legal Action/Court Order                                                                                                                                                                                                8     \n",
      "Conservator's Deed                                                                                                                                                                                                      8     \n",
      "Receiver's Deed                                                                                                                                                                                                         7     \n",
      "Grant Deed                                                                                                                                                                                                              6     \n",
      "Individual Deed                                                                                                                                                                                                         5     \n",
      "Assignment Deed (or Assignment of Condo Deed if Land Use = \"CND\".)                                                                                                                                                      5     \n",
      "Limited Warranty Deed                                                                                                                                                                                                   4     \n",
      "Affidavit                                                                                                                                                                                                               4     \n",
      "ExecutorÃÂ¢ÃÂÃÂs Deed                                                                                                                                                                                              3     \n",
      "Sub Agreement of Sale (Hawaii)                                                                                                                                                                                          2     \n",
      "Cancellation of Agreement of Sale (Hawaii)                                                                                                                                                                              2     \n",
      "AdministratorÃÂ¢ÃÂÃÂs Deed                                                                                                                                                                                         2     \n",
      "Certificate of Transfer                                                                                                                                                                                                 1     \n",
      "Assignment of Commercial Lease (Hawaii)                                                                                                                                                                                 1     \n",
      "Assignment of Sub Lease (Hawaii)                                                                                                                                                                                        1     \n",
      "Name: document_type, dtype: int64\n",
      "Purchase/Resale Arm's Length Residential Transaction    665430\n",
      "Insured Non-Residential Grant Deed                      54433 \n",
      "Non-Arm's Length Transaction                            51282 \n",
      "REO and Trustee Deed                                    11380 \n",
      "New Residential Construction Transaction                5625  \n",
      "Name: transaction_type, dtype: int64\n",
      "Single-Family Home     671788\n",
      "Multi-Family           56434 \n",
      "Townhouse              29946 \n",
      "Condo                  17089 \n",
      "Unknown                9338  \n",
      "Income/Investment      2294  \n",
      "Mobile/Manufactured    923   \n",
      "Farm/Ranch             338   \n",
      "Name: property_type, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(transactions_master_df['document_type'].value_counts())\n",
    "print(transactions_master_df['transaction_type'].value_counts())\n",
    "print(transactions_master_df['property_type'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ML Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Performing one hot encoding, and normalizing the data if necessary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['document_type', 'price', 'transaction_type', 'recording_year',\n",
       "       'recording_month', 'recording_day', 'contract_day', 'area_sqft',\n",
       "       'built_year', 'city', 'lot_size', 'no_of_baths', 'no_of_bedrooms',\n",
       "       'property_type', 'state', 'tax_amount', 'zip_code'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions_master_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Defining features and target using the dataframe we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>document_type</th>\n",
       "      <th>transaction_type</th>\n",
       "      <th>recording_year</th>\n",
       "      <th>recording_month</th>\n",
       "      <th>recording_day</th>\n",
       "      <th>contract_day</th>\n",
       "      <th>area_sqft</th>\n",
       "      <th>built_year</th>\n",
       "      <th>lot_size</th>\n",
       "      <th>no_of_baths</th>\n",
       "      <th>no_of_bedrooms</th>\n",
       "      <th>property_type</th>\n",
       "      <th>tax_amount</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Deed</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>25</td>\n",
       "      <td>1184.0</td>\n",
       "      <td>1997</td>\n",
       "      <td>60984.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>8320.40</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>REO Resale</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>10</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>1992</td>\n",
       "      <td>39639.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>3074.64</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>REO Repossession</td>\n",
       "      <td>REO and Trustee Deed</td>\n",
       "      <td>2015</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>1992</td>\n",
       "      <td>39639.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>3074.64</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deed</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>1996</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>9</td>\n",
       "      <td>961.0</td>\n",
       "      <td>1951</td>\n",
       "      <td>20908.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2701.22</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>REO Resale</td>\n",
       "      <td>Purchase/Resale Arm's Length Residential Transaction</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>1236.0</td>\n",
       "      <td>1957</td>\n",
       "      <td>14810.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>3879.47</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      document_type                                      transaction_type  \\\n",
       "0  Deed              Purchase/Resale Arm's Length Residential Transaction   \n",
       "1  REO Resale        Purchase/Resale Arm's Length Residential Transaction   \n",
       "2  REO Repossession  REO and Trustee Deed                                   \n",
       "3  Deed              Purchase/Resale Arm's Length Residential Transaction   \n",
       "4  REO Resale        Purchase/Resale Arm's Length Residential Transaction   \n",
       "\n",
       "   recording_year  recording_month  recording_day  contract_day  area_sqft  \\\n",
       "0  2001            7                30             25            1184.0      \n",
       "1  2017            5                24             10            1350.0      \n",
       "2  2015            11               20             6             1350.0      \n",
       "3  1996            7                30             9             961.0       \n",
       "4  2010            12               20             15            1236.0      \n",
       "\n",
       "   built_year  lot_size  no_of_baths  no_of_bedrooms       property_type  \\\n",
       "0  1997        60984.0   2.5          3.0             Single-Family Home   \n",
       "1  1992        39639.6   1.5          2.0             Single-Family Home   \n",
       "2  1992        39639.6   1.5          2.0             Single-Family Home   \n",
       "3  1951        20908.8   1.0          2.0             Single-Family Home   \n",
       "4  1957        14810.4   2.0          2.0             Single-Family Home   \n",
       "\n",
       "   tax_amount state  \n",
       "0  8320.40     NY    \n",
       "1  3074.64     NY    \n",
       "2  3074.64     NY    \n",
       "3  2701.22     NY    \n",
       "4  3879.47     NY    "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = transactions_master_df['price'].values\n",
    "features = transactions_master_df[['document_type', 'transaction_type', 'recording_year',\n",
    "       'recording_month', 'recording_day', 'contract_day', 'area_sqft',\n",
    "       'built_year', 'lot_size', 'no_of_baths', 'no_of_bedrooms',\n",
    "       'property_type', 'tax_amount', 'state']]\n",
    "# ADD CITY AND ZIP_CODE AS WELL, RIGHT NOW THEY ARE REMOVED\n",
    "features.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Splitting the data to train and test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(features, target, random_state=21)\n",
    "X_train.reset_index(drop=True, inplace=True)\n",
    "X_test.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below we will create a ML pipeline where a series of steps will be taken in order to train the model. This pipeline will also be used in any subsequent predictions. \n",
    "\n",
    "The pipeline performs the following order of operations\n",
    "* ColumnTransformer takes in the categorical columns and performs one hot encoding on them, using a mask for selecting the column subsets based on the dtypes\n",
    "* Any standard scalers or imputers, if necessary\n",
    "* Linear Regression Model for training and predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_features = (features.dtypes == 'object')\n",
    "numerical_features = ~categorical_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['document_type', 'transaction_type', 'property_type', 'state']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features[categorical_features == True].index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "document_type       False\n",
       "transaction_type    False\n",
       "recording_year      True \n",
       "recording_month     True \n",
       "recording_day       True \n",
       "contract_day        True \n",
       "area_sqft           True \n",
       "built_year          True \n",
       "lot_size            True \n",
       "no_of_baths         True \n",
       "no_of_bedrooms      True \n",
       "property_type       False\n",
       "tax_amount          True \n",
       "state               False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom Transformer\n",
    "\n",
    "Out-of-the-box sklearn one hot encoders do not support dropping one of the columns after hot encoding, and it also creates a problem while trying to retrieve the new column set post hot encoding when there are other transformations happening. Hence this option"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "import pandas as pd\n",
    "\n",
    "class CustomOneHotEncoder(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, categorical_features=None, reindex_columns=None):\n",
    "        self.categorical_features = categorical_features\n",
    "        self.reindex_columns = reindex_columns\n",
    "        self.updated_feature_names = None\n",
    "    \n",
    "    def transform(self, X, **transformparams):\n",
    "        #print (transformparams.get('arg1'))\n",
    "        self.updated_feature_names = []\n",
    "        hot_encoded_df = pd.get_dummies(data=X, columns=self.categorical_features, \\\n",
    "                                        drop_first=False).copy()\n",
    "        # Lets reindex this thing, which will add any missing columns in the passed data\n",
    "        print(hot_encoded_df.shape)\n",
    "        hot_encoded_df = hot_encoded_df.reindex(columns=self.reindex_columns, fill_value=0)\n",
    "        print(hot_encoded_df.shape)\n",
    "        # Now we have reformed the encoded dataframe by filling any missing columns\n",
    "        self.updated_feature_names = hot_encoded_df.columns\n",
    "        return hot_encoded_df\n",
    "    \n",
    "    def fit(self, X, y=None, **fitparams):\n",
    "        return self\n",
    "    \n",
    "    def get_feature_names(self):\n",
    "        return self.updated_feature_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparing inputs for the encoder\n",
    "\n",
    "The encoder needs to be provided with\n",
    "* Columns to be encoded\n",
    "* Exhaustive list of columns that should be generated from one hot encoding\n",
    "\n",
    "Normally, encoders generate the second input on their own. That's actually one of the tasks of one hot encoders. The reason we are tweaking this behavior here (predetermining production needs) is because we need to merge the train and test data, find all unique values in categorical columns and provide these column names to the encoder. If we don't do this, the one hot encoder will only generate hot encoded columns off of train data. This will create issues if your test/validation data has different set of unique values in one of the categorical columns. This will cause the preprocessor to generate a higher/lower number of columns than what the pipeline has been fitted on, hence resulting in errors. Comprende?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['REO Resale',\n",
       " 'REO Repossession',\n",
       " 'Land Contract',\n",
       " 'Warranty Deed',\n",
       " \"Executor's Deed\",\n",
       " \"Administrator's Deed\",\n",
       " 'Foreclosure',\n",
       " 'Other',\n",
       " 'Bargain and Sale Deed',\n",
       " 'Special Warranty Deed',\n",
       " 'Deed in Lieu of Foreclosure',\n",
       " 'Beneficiary Deed (Buyer ID = \"BE\")',\n",
       " 'Fiduciary Deed',\n",
       " 'Affidavit',\n",
       " 'Sheriff\\'s Deed - Common in New Jersey. The default code for transfers where borrower is in default, in other states document may be called something other than Sheriff\\'s Deed, i.e. \"Masters in Equity Deed\" in SC.',\n",
       " 'Exchange',\n",
       " 'Condominium Deed',\n",
       " 'Agreement of Sale',\n",
       " 'Contract of Sale',\n",
       " \"Vendor's Lien\",\n",
       " 'Corporation Deed',\n",
       " 'Redemption Deed',\n",
       " 'Declaration',\n",
       " \"Commissioner's Deed - In North Carolina used in probate-related transfers.   In Hawaii used in foreclosure-related transfers.\",\n",
       " 'Deed of Guardian',\n",
       " 'Legal Action/Court Order',\n",
       " 'Joint Tenancy Deed',\n",
       " \"Receiver's Deed\",\n",
       " 'ExecutorÃ\\x83Â¢Ã\\x82Â\\x80Ã\\x82Â\\x99s Deed',\n",
       " 'Grant Deed',\n",
       " 'Lease (Hawaii)',\n",
       " 'AdministratorÃ\\x83Â¢Ã\\x82Â\\x80Ã\\x82Â\\x99s Deed',\n",
       " 'Limited Warranty Deed',\n",
       " 'Satisfaction of Land Contract (Wisconsin)',\n",
       " 'Assignment Deed (or Assignment of Condo Deed if Land Use = \"CND\".)',\n",
       " 'Individual Deed',\n",
       " 'Public Action - Common in Florida (Clerks Tax Deed or Tax Deeds). Also when property sold for taxes.',\n",
       " 'Personal Representatives Deed',\n",
       " \"Conservator's Deed\",\n",
       " 'Sub Agreement of Sale (Hawaii)',\n",
       " 'Assignment of Sub Lease (Hawaii)',\n",
       " 'Certificate of Transfer',\n",
       " 'Cancellation of Agreement of Sale (Hawaii)',\n",
       " 'Assignment of Commercial Lease (Hawaii)',\n",
       " 'REO and Trustee Deed',\n",
       " \"Non-Arm's Length Transaction\",\n",
       " 'Insured Non-Residential Grant Deed',\n",
       " 'New Residential Construction Transaction',\n",
       " 'recording_year',\n",
       " 'recording_month',\n",
       " 'recording_day',\n",
       " 'contract_day',\n",
       " 'area_sqft',\n",
       " 'built_year',\n",
       " 'lot_size',\n",
       " 'no_of_baths',\n",
       " 'no_of_bedrooms',\n",
       " 'Multi-Family',\n",
       " 'Mobile/Manufactured',\n",
       " 'Townhouse',\n",
       " 'Unknown',\n",
       " 'Income/Investment',\n",
       " 'Farm/Ranch',\n",
       " 'Condo',\n",
       " 'tax_amount',\n",
       " 'CT',\n",
       " 'NJ']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns_to_encode = categorical_features[categorical_features == True].index.tolist()\n",
    "\n",
    "reindex_hot_encoding = []\n",
    "# Iterating through all the columns in feature set\n",
    "for column in features.columns:\n",
    "    # If the column name is in the columns_to_encode list, append all the unique values of that column\n",
    "    if column in columns_to_encode:\n",
    "        # Ignore the first unique value, we drop it in reindex list instead of using drop=True in get_dummies later\n",
    "        for count, item in enumerate(features[column].unique()):\n",
    "            if count is not 0:\n",
    "                reindex_hot_encoding.append(item)\n",
    "    # If the column name is not in the columns_to_encode list, append the column name itself\n",
    "    else:\n",
    "        reindex_hot_encoding.append(column)\n",
    "reindex_hot_encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipeline = Pipeline([\n",
    "    # Preprocessor to perform necessary scaling on the data before running regression\n",
    "    ('preprocess', ColumnTransformer(transformers=\n",
    "        [\n",
    "            ('hot_encoder', CustomOneHotEncoder(categorical_features=columns_to_encode, \\\n",
    "                                                reindex_columns=reindex_hot_encoding), features.columns)\n",
    "        ]\n",
    "    )),\n",
    "    # Using linear regression modeling\n",
    "    ('random_forest_reg', RandomForestRegressor(n_estimators=100, n_jobs=-1))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(591112, 70)\n",
      "(591112, 67)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Pipeline(memory=None,\n",
       "     steps=[('preprocess', ColumnTransformer(n_jobs=None, remainder='drop', sparse_threshold=0.3,\n",
       "         transformer_weights=None,\n",
       "         transformers=[('hot_encoder', CustomOneHotEncoder(categorical_features=['document_type', 'transaction_type', 'property_type', 'state'],\n",
       "          reindex_columns=[...mators=100, n_jobs=-1,\n",
       "           oob_score=False, random_state=None, verbose=0, warm_start=False))])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['hot_encoder__REO Resale',\n",
       " 'hot_encoder__REO Repossession',\n",
       " 'hot_encoder__Land Contract',\n",
       " 'hot_encoder__Warranty Deed',\n",
       " \"hot_encoder__Executor's Deed\",\n",
       " \"hot_encoder__Administrator's Deed\",\n",
       " 'hot_encoder__Foreclosure',\n",
       " 'hot_encoder__Other',\n",
       " 'hot_encoder__Bargain and Sale Deed',\n",
       " 'hot_encoder__Special Warranty Deed',\n",
       " 'hot_encoder__Deed in Lieu of Foreclosure',\n",
       " 'hot_encoder__Beneficiary Deed (Buyer ID = \"BE\")',\n",
       " 'hot_encoder__Fiduciary Deed',\n",
       " 'hot_encoder__Affidavit',\n",
       " 'hot_encoder__Sheriff\\'s Deed - Common in New Jersey. The default code for transfers where borrower is in default, in other states document may be called something other than Sheriff\\'s Deed, i.e. \"Masters in Equity Deed\" in SC.',\n",
       " 'hot_encoder__Exchange',\n",
       " 'hot_encoder__Condominium Deed',\n",
       " 'hot_encoder__Agreement of Sale',\n",
       " 'hot_encoder__Contract of Sale',\n",
       " \"hot_encoder__Vendor's Lien\",\n",
       " 'hot_encoder__Corporation Deed',\n",
       " 'hot_encoder__Redemption Deed',\n",
       " 'hot_encoder__Declaration',\n",
       " \"hot_encoder__Commissioner's Deed - In North Carolina used in probate-related transfers.   In Hawaii used in foreclosure-related transfers.\",\n",
       " 'hot_encoder__Deed of Guardian',\n",
       " 'hot_encoder__Legal Action/Court Order',\n",
       " 'hot_encoder__Joint Tenancy Deed',\n",
       " \"hot_encoder__Receiver's Deed\",\n",
       " 'hot_encoder__ExecutorÃ\\x83Â¢Ã\\x82Â\\x80Ã\\x82Â\\x99s Deed',\n",
       " 'hot_encoder__Grant Deed',\n",
       " 'hot_encoder__Lease (Hawaii)',\n",
       " 'hot_encoder__AdministratorÃ\\x83Â¢Ã\\x82Â\\x80Ã\\x82Â\\x99s Deed',\n",
       " 'hot_encoder__Limited Warranty Deed',\n",
       " 'hot_encoder__Satisfaction of Land Contract (Wisconsin)',\n",
       " 'hot_encoder__Assignment Deed (or Assignment of Condo Deed if Land Use = \"CND\".)',\n",
       " 'hot_encoder__Individual Deed',\n",
       " 'hot_encoder__Public Action - Common in Florida (Clerks Tax Deed or Tax Deeds). Also when property sold for taxes.',\n",
       " 'hot_encoder__Personal Representatives Deed',\n",
       " \"hot_encoder__Conservator's Deed\",\n",
       " 'hot_encoder__Sub Agreement of Sale (Hawaii)',\n",
       " 'hot_encoder__Assignment of Sub Lease (Hawaii)',\n",
       " 'hot_encoder__Certificate of Transfer',\n",
       " 'hot_encoder__Cancellation of Agreement of Sale (Hawaii)',\n",
       " 'hot_encoder__Assignment of Commercial Lease (Hawaii)',\n",
       " 'hot_encoder__REO and Trustee Deed',\n",
       " \"hot_encoder__Non-Arm's Length Transaction\",\n",
       " 'hot_encoder__Insured Non-Residential Grant Deed',\n",
       " 'hot_encoder__New Residential Construction Transaction',\n",
       " 'hot_encoder__recording_year',\n",
       " 'hot_encoder__recording_month',\n",
       " 'hot_encoder__recording_day',\n",
       " 'hot_encoder__contract_day',\n",
       " 'hot_encoder__area_sqft',\n",
       " 'hot_encoder__built_year',\n",
       " 'hot_encoder__lot_size',\n",
       " 'hot_encoder__no_of_baths',\n",
       " 'hot_encoder__no_of_bedrooms',\n",
       " 'hot_encoder__Multi-Family',\n",
       " 'hot_encoder__Mobile/Manufactured',\n",
       " 'hot_encoder__Townhouse',\n",
       " 'hot_encoder__Unknown',\n",
       " 'hot_encoder__Income/Investment',\n",
       " 'hot_encoder__Farm/Ranch',\n",
       " 'hot_encoder__Condo',\n",
       " 'hot_encoder__tax_amount',\n",
       " 'hot_encoder__CT',\n",
       " 'hot_encoder__NJ']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_post_fit = pipeline.named_steps['preprocess'].get_feature_names()\n",
    "features_post_fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(197038, 64)\n",
      "(197038, 67)\n"
     ]
    }
   ],
   "source": [
    "predictions = pipeline.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1a25dd4b70>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x=y_test, y=predictions, kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a236ff6a0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot((y_test-predictions), bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73832.18804814348"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(metrics.mean_squared_error(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      1999                                                \n",
      "recording_month     2                                                   \n",
      "recording_day       25                                                  \n",
      "contract_day        3                                                   \n",
      "area_sqft           2384                                                \n",
      "built_year          1992                                                \n",
      "lot_size            14810.4                                             \n",
      "no_of_baths         2.5                                                 \n",
      "no_of_bedrooms      4                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          7784.56                                             \n",
      "state               NY                                                  \n",
      "Name: 0, dtype: object\n",
      "167467.0\n",
      "181546.25\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2005                                                \n",
      "recording_month     5                                                   \n",
      "recording_day       13                                                  \n",
      "contract_day        5                                                   \n",
      "area_sqft           1428                                                \n",
      "built_year          1952                                                \n",
      "lot_size            5950                                                \n",
      "no_of_baths         2                                                   \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          3740.19                                             \n",
      "state               NY                                                  \n",
      "Name: 1, dtype: object\n",
      "89900.0\n",
      "96342.87\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2016                                                \n",
      "recording_month     10                                                  \n",
      "recording_day       19                                                  \n",
      "contract_day        13                                                  \n",
      "area_sqft           1632                                                \n",
      "built_year          1871                                                \n",
      "lot_size            38332.8                                             \n",
      "no_of_baths         1                                                   \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          7268.87                                             \n",
      "state               NY                                                  \n",
      "Name: 2, dtype: object\n",
      "190000.0\n",
      "226604.7\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2010                                                \n",
      "recording_month     9                                                   \n",
      "recording_day       21                                                  \n",
      "contract_day        31                                                  \n",
      "area_sqft           2694                                                \n",
      "built_year          1957                                                \n",
      "lot_size            40075.2                                             \n",
      "no_of_baths         2.5                                                 \n",
      "no_of_bedrooms      4                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          10554.4                                             \n",
      "state               NY                                                  \n",
      "Name: 3, dtype: object\n",
      "225000.0\n",
      "349323.7\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2015                                                \n",
      "recording_month     7                                                   \n",
      "recording_day       8                                                   \n",
      "contract_day        24                                                  \n",
      "area_sqft           1186                                                \n",
      "built_year          1988                                                \n",
      "lot_size            6098                                                \n",
      "no_of_baths         1.5                                                 \n",
      "no_of_bedrooms      2                                                   \n",
      "property_type       Townhouse                                           \n",
      "tax_amount          4029.07                                             \n",
      "state               NY                                                  \n",
      "Name: 4, dtype: object\n",
      "191752.0\n",
      "189491.7\n",
      "document_type       Bargain and Sale Deed                               \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      1999                                                \n",
      "recording_month     10                                                  \n",
      "recording_day       7                                                   \n",
      "contract_day        4                                                   \n",
      "area_sqft           1364                                                \n",
      "built_year          2008                                                \n",
      "lot_size            19166.4                                             \n",
      "no_of_baths         2                                                   \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          7290.87                                             \n",
      "state               NY                                                  \n",
      "Name: 5, dtype: object\n",
      "68381.0\n",
      "66482.4\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2010                                                \n",
      "recording_month     12                                                  \n",
      "recording_day       17                                                  \n",
      "contract_day        14                                                  \n",
      "area_sqft           3100                                                \n",
      "built_year          2002                                                \n",
      "lot_size            22651.2                                             \n",
      "no_of_baths         2.5                                                 \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          6783.16                                             \n",
      "state               NY                                                  \n",
      "Name: 6, dtype: object\n",
      "200000.0\n",
      "353215.39\n",
      "document_type       Bargain and Sale Deed                               \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2002                                                \n",
      "recording_month     7                                                   \n",
      "recording_day       8                                                   \n",
      "contract_day        19                                                  \n",
      "area_sqft           2133                                                \n",
      "built_year          1976                                                \n",
      "lot_size            9583                                                \n",
      "no_of_baths         2                                                   \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Unknown                                             \n",
      "tax_amount          9667.96                                             \n",
      "state               NY                                                  \n",
      "Name: 7, dtype: object\n",
      "160000.0\n",
      "265324.25\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      2001                                                \n",
      "recording_month     8                                                   \n",
      "recording_day       3                                                   \n",
      "contract_day        25                                                  \n",
      "area_sqft           2027                                                \n",
      "built_year          1989                                                \n",
      "lot_size            16988.4                                             \n",
      "no_of_baths         3                                                   \n",
      "no_of_bedrooms      4                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          8748.85                                             \n",
      "state               NJ                                                  \n",
      "Name: 8, dtype: object\n",
      "325000.0\n",
      "283609.9\n",
      "document_type       Deed                                                \n",
      "transaction_type    Purchase/Resale Arm's Length Residential Transaction\n",
      "recording_year      1995                                                \n",
      "recording_month     11                                                  \n",
      "recording_day       20                                                  \n",
      "contract_day        17                                                  \n",
      "area_sqft           1718                                                \n",
      "built_year          1900                                                \n",
      "lot_size            21344.4                                             \n",
      "no_of_baths         2                                                   \n",
      "no_of_bedrooms      3                                                   \n",
      "property_type       Single-Family Home                                  \n",
      "tax_amount          1709.63                                             \n",
      "state               NY                                                  \n",
      "Name: 9, dtype: object\n",
      "29900.0\n",
      "54889.78\n"
     ]
    }
   ],
   "source": [
    "for index, row in X_test[:10].iterrows():\n",
    "    print(row)\n",
    "    print(y_test[index])\n",
    "    print(predictions[index])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trying out predictions on external data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['document_type', 'transaction_type', 'recording_year',\n",
       "       'recording_month', 'recording_day', 'contract_day', 'area_sqft',\n",
       "       'built_year', 'lot_size', 'no_of_baths', 'no_of_bedrooms',\n",
       "       'property_type', 'tax_amount', 'state'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test property: https://www.trulia.com/p/ny/binghamton/32-decatur-st-binghamton-ny-13903--2012602134"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_input = ['Deed', 'Insured Non-Residential Grant Deed', 2018, 7, 2, 23, 1503, 1960, 3000, 2, 3, 'Single-Family Home', 1225, 'NY']\n",
    "\n",
    "input_df = pd.DataFrame(data=[new_input], columns=X_test.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 14)\n",
      "(1, 67)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([100652.35])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "outcome = pipeline.predict(input_df)\n",
    "outcome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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