randomForest_cars_price.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Used Cars Price Prediction - Random Forest\n",
    "Ahmad Sotoude <br>\n",
    "<a href=\"https://github.com/ahmadsotoude\">link to github</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "importing necessary libs and dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>Ad ID</th>\n",
       "      <th>Car Name</th>\n",
       "      <th>Make</th>\n",
       "      <th>Model</th>\n",
       "      <th>Year</th>\n",
       "      <th>KM's driven</th>\n",
       "      <th>Price</th>\n",
       "      <th>Fuel</th>\n",
       "      <th>Registration city</th>\n",
       "      <th>Car documents</th>\n",
       "      <th>Assembly</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Condition</th>\n",
       "      <th>Seller Location</th>\n",
       "      <th>Description</th>\n",
       "      <th>Car Features</th>\n",
       "      <th>Images URL's</th>\n",
       "      <th>Car Profile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1079071571</td>\n",
       "      <td>fresh import Passo 2021model</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>Passo</td>\n",
       "      <td>2021</td>\n",
       "      <td>54000</td>\n",
       "      <td>4190000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Unregistered</td>\n",
       "      <td>Original</td>\n",
       "      <td>Imported</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>Used</td>\n",
       "      <td>Airline Avenue, Islamabad</td>\n",
       "      <td>it's 2021 model fresh import, perfect engine s...</td>\n",
       "      <td>ABS, Air Bags, AM/FM Radio, CD Player, Cassett...</td>\n",
       "      <td>['https://images.olx.com.pk/thumbnails/4039460...</td>\n",
       "      <td>https://www.olx.com.pk/item/fresh-import-passo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080125520</td>\n",
       "      <td>Suzuki ravi</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>Ravi</td>\n",
       "      <td>2018</td>\n",
       "      <td>95000</td>\n",
       "      <td>1300000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Karachi</td>\n",
       "      <td>Original</td>\n",
       "      <td>Local</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Used</td>\n",
       "      <td>Kahuta, Rawalpindi</td>\n",
       "      <td>Suzuki ravi 2018 col</td>\n",
       "      <td>AM/FM Radio</td>\n",
       "      <td>['https://images.olx.com.pk/thumbnails/4102504...</td>\n",
       "      <td>https://www.olx.com.pk/item/suzuki-ravi-iid-10...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1080748789</td>\n",
       "      <td>Suzuki bolan 2015 contact 03112271054</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>Bolan</td>\n",
       "      <td>2015</td>\n",
       "      <td>50000</td>\n",
       "      <td>800000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Karachi</td>\n",
       "      <td>Original</td>\n",
       "      <td>Local</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Used</td>\n",
       "      <td>Lyari Expressway, Karachi</td>\n",
       "      <td>Suzuki bolan model 2015 reg 2022 ghadi me koi ...</td>\n",
       "      <td>Rear speakers</td>\n",
       "      <td>['https://images.olx.com.pk/thumbnails/4139520...</td>\n",
       "      <td>https://www.olx.com.pk/item/suzuki-bolan-2015-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076081635</td>\n",
       "      <td>Diahatsu Move 2013</td>\n",
       "      <td>Daihatsu</td>\n",
       "      <td>Move</td>\n",
       "      <td>2013</td>\n",
       "      <td>94000</td>\n",
       "      <td>2155000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Lahore</td>\n",
       "      <td>Original</td>\n",
       "      <td>Imported</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>Used</td>\n",
       "      <td>New Amir Town, Lahore</td>\n",
       "      <td>Move Push start \\nHome Used car. \\nModel 2013....</td>\n",
       "      <td>ABS, Air Bags, Air Conditioning, Alloy Rims, A...</td>\n",
       "      <td>['https://images.olx.com.pk/thumbnails/3865337...</td>\n",
       "      <td>https://www.olx.com.pk/item/diahatsu-move-2013...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1080812928</td>\n",
       "      <td>Suzuki Swift DLX 2011 miner tuchap</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>Swift</td>\n",
       "      <td>2011</td>\n",
       "      <td>126544</td>\n",
       "      <td>1440000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Karachi</td>\n",
       "      <td>Original</td>\n",
       "      <td>Local</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Used</td>\n",
       "      <td>Shadman 2, Karachi</td>\n",
       "      <td>Suzuki Swift DLX\\nAbS Break 100%\\nengine 100%\\...</td>\n",
       "      <td>ABS, Air Conditioning, Alloy Rims, AM/FM Radio...</td>\n",
       "      <td>['https://images.olx.com.pk/thumbnails/4143509...</td>\n",
       "      <td>https://www.olx.com.pk/item/suzuki-swift-dlx-2...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ad ID                               Car Name      Make  Model  Year  \\\n",
       "0  1079071571           fresh import Passo 2021model    Toyota  Passo  2021   \n",
       "1  1080125520                            Suzuki ravi    Suzuki   Ravi  2018   \n",
       "2  1080748789  Suzuki bolan 2015 contact 03112271054    Suzuki  Bolan  2015   \n",
       "3  1076081635                     Diahatsu Move 2013  Daihatsu   Move  2013   \n",
       "4  1080812928     Suzuki Swift DLX 2011 miner tuchap    Suzuki  Swift  2011   \n",
       "\n",
       "   KM's driven    Price    Fuel Registration city Car documents  Assembly  \\\n",
       "0        54000  4190000  Petrol      Unregistered      Original  Imported   \n",
       "1        95000  1300000  Petrol           Karachi      Original     Local   \n",
       "2        50000   800000  Petrol           Karachi      Original     Local   \n",
       "3        94000  2155000  Petrol            Lahore      Original  Imported   \n",
       "4       126544  1440000  Petrol           Karachi      Original     Local   \n",
       "\n",
       "  Transmission Condition            Seller Location  \\\n",
       "0    Automatic      Used  Airline Avenue, Islamabad   \n",
       "1       Manual      Used         Kahuta, Rawalpindi   \n",
       "2       Manual      Used  Lyari Expressway, Karachi   \n",
       "3    Automatic      Used      New Amir Town, Lahore   \n",
       "4       Manual      Used         Shadman 2, Karachi   \n",
       "\n",
       "                                         Description  \\\n",
       "0  it's 2021 model fresh import, perfect engine s...   \n",
       "1                              Suzuki ravi 2018 col    \n",
       "2  Suzuki bolan model 2015 reg 2022 ghadi me koi ...   \n",
       "3  Move Push start \\nHome Used car. \\nModel 2013....   \n",
       "4  Suzuki Swift DLX\\nAbS Break 100%\\nengine 100%\\...   \n",
       "\n",
       "                                        Car Features  \\\n",
       "0  ABS, Air Bags, AM/FM Radio, CD Player, Cassett...   \n",
       "1                                        AM/FM Radio   \n",
       "2                                      Rear speakers   \n",
       "3  ABS, Air Bags, Air Conditioning, Alloy Rims, A...   \n",
       "4  ABS, Air Conditioning, Alloy Rims, AM/FM Radio...   \n",
       "\n",
       "                                        Images URL's  \\\n",
       "0  ['https://images.olx.com.pk/thumbnails/4039460...   \n",
       "1  ['https://images.olx.com.pk/thumbnails/4102504...   \n",
       "2  ['https://images.olx.com.pk/thumbnails/4139520...   \n",
       "3  ['https://images.olx.com.pk/thumbnails/3865337...   \n",
       "4  ['https://images.olx.com.pk/thumbnails/4143509...   \n",
       "\n",
       "                                         Car Profile  \n",
       "0  https://www.olx.com.pk/item/fresh-import-passo...  \n",
       "1  https://www.olx.com.pk/item/suzuki-ravi-iid-10...  \n",
       "2  https://www.olx.com.pk/item/suzuki-bolan-2015-...  \n",
       "3  https://www.olx.com.pk/item/diahatsu-move-2013...  \n",
       "4  https://www.olx.com.pk/item/suzuki-swift-dlx-2...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('OLX_cars_dataset00.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "checking different values each column holds:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Condition\n",
      "Used    9179\n",
      "Name: count, dtype: int64\n",
      "--------------\n",
      "Fuel\n",
      "Petrol    8984\n",
      "CNG        193\n",
      "Hybrid       1\n",
      "Diesel       1\n",
      "Name: count, dtype: int64\n",
      "--------------\n",
      "Make\n",
      "Suzuki        3048\n",
      "Honda         1758\n",
      "Toyota        1606\n",
      "Daihatsu      1373\n",
      "Hyundai        460\n",
      "Mitsubishi     249\n",
      "KIA            234\n",
      "Changan        192\n",
      "FAW            137\n",
      "Chevrolet       77\n",
      "Mercedes        45\n",
      "Name: count, dtype: int64\n",
      "--------------\n",
      "Car documents\n",
      "Original     9111\n",
      "Duplicate      68\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df['Condition'].value_counts())\n",
    "print('--------------')\n",
    "print(df['Fuel'].value_counts())\n",
    "print('--------------')\n",
    "print(df['Make'].value_counts())\n",
    "print('--------------')\n",
    "print(df['Car documents'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Ad ID</th>\n",
       "      <th>Make</th>\n",
       "      <th>Year</th>\n",
       "      <th>KM's driven</th>\n",
       "      <th>Price</th>\n",
       "      <th>Fuel</th>\n",
       "      <th>Car documents</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Car Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1079071571</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>2021</td>\n",
       "      <td>54000</td>\n",
       "      <td>4190000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Original</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>ABS, Air Bags, AM/FM Radio, CD Player, Cassett...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080125520</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2018</td>\n",
       "      <td>95000</td>\n",
       "      <td>1300000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Original</td>\n",
       "      <td>Manual</td>\n",
       "      <td>AM/FM Radio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1080748789</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2015</td>\n",
       "      <td>50000</td>\n",
       "      <td>800000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Original</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Rear speakers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076081635</td>\n",
       "      <td>Daihatsu</td>\n",
       "      <td>2013</td>\n",
       "      <td>94000</td>\n",
       "      <td>2155000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Original</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>ABS, Air Bags, Air Conditioning, Alloy Rims, A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1080812928</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2011</td>\n",
       "      <td>126544</td>\n",
       "      <td>1440000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Original</td>\n",
       "      <td>Manual</td>\n",
       "      <td>ABS, Air Conditioning, Alloy Rims, AM/FM Radio...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ad ID      Make  Year  KM's driven    Price    Fuel Car documents  \\\n",
       "0  1079071571    Toyota  2021        54000  4190000  Petrol      Original   \n",
       "1  1080125520    Suzuki  2018        95000  1300000  Petrol      Original   \n",
       "2  1080748789    Suzuki  2015        50000   800000  Petrol      Original   \n",
       "3  1076081635  Daihatsu  2013        94000  2155000  Petrol      Original   \n",
       "4  1080812928    Suzuki  2011       126544  1440000  Petrol      Original   \n",
       "\n",
       "  Transmission                                       Car Features  \n",
       "0    Automatic  ABS, Air Bags, AM/FM Radio, CD Player, Cassett...  \n",
       "1       Manual                                        AM/FM Radio  \n",
       "2       Manual                                      Rear speakers  \n",
       "3    Automatic  ABS, Air Bags, Air Conditioning, Alloy Rims, A...  \n",
       "4       Manual  ABS, Air Conditioning, Alloy Rims, AM/FM Radio...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf = df.drop(['Car Name','Model','Registration city','Assembly','Condition','Seller Location','Description',\"Images URL's\",'Car Profile'],axis=1)\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "checking for NULL values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9179 entries, 0 to 9178\n",
      "Data columns (total 9 columns):\n",
      " #   Column         Non-Null Count  Dtype \n",
      "---  ------         --------------  ----- \n",
      " 0   Ad ID          9179 non-null   int64 \n",
      " 1   Make           9179 non-null   object\n",
      " 2   Year           9179 non-null   int64 \n",
      " 3   KM's driven    9179 non-null   int64 \n",
      " 4   Price          9179 non-null   int64 \n",
      " 5   Fuel           9179 non-null   object\n",
      " 6   Car documents  9179 non-null   object\n",
      " 7   Transmission   9179 non-null   object\n",
      " 8   Car Features   9179 non-null   object\n",
      "dtypes: int64(4), object(5)\n",
      "memory usage: 645.5+ KB\n",
      "None\n",
      "--------------\n",
      "Ad ID            0\n",
      "Make             0\n",
      "Year             0\n",
      "KM's driven      0\n",
      "Price            0\n",
      "Fuel             0\n",
      "Car documents    0\n",
      "Transmission     0\n",
      "Car Features     0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(ndf.info())\n",
    "print('--------------')\n",
    "print(ndf.isna().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some EDA and plotting to find relations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Car documents', ylabel='Price'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ndf.loc[ndf['Car documents'] == 'Original', 'Car documents'] = 1\n",
    "ndf.loc[ndf['Car documents'] == 'Duplicate', 'Car documents'] = 0\n",
    "sns.stripplot(x=ndf['Car documents'],y=ndf['Price'],jitter=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ndf.drop('Car documents', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(ndf['Make'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SAM-Tech\\AppData\\Local\\Temp\\ipykernel_8292\\2350975893.py:4: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxenplot(x = ndf['Make'], y= ndf['Price'], palette=custom_palette)\n",
      "C:\\Users\\SAM-Tech\\AppData\\Local\\Temp\\ipykernel_8292\\2350975893.py:5: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,5))\n",
    "custom_palette = sns.color_palette(\"husl\", n_colors=11)\n",
    "sns.set_palette(custom_palette)\n",
    "sns.boxenplot(x = ndf['Make'], y= ndf['Price'], palette=custom_palette)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EMEzV8c72wN62b5gT1tCAvYZ6eV+MYRi5lGNcxOI+Hw25TLT9NJXupFCKrvbEzY8bDZ4H9/QZaMsXDLXkQRdwT52B0/Uq4HnJxwSAfNY38+g6BntE5UXf3EpjvCNDT5TPQl+3DM6zXYEKk75uGZ3BUJzTKzvBjhlOmBiGqSpuoRhIlgC/bcDatg9iyyquNDFMWpGxyM0YMboTojlt+QzsPYdDK0z23i6INYuTj2la0LesCp3DpG9ZRWd7bRhwuo5VbrXc1Jp8TBl6IhnHORA38lh51uCY4YSJYZjq0lcInbECDPRa9xXIdEbcBsgw4xyhQf389dCW3ARlhIub8/wrgNCSj2la0BbNAxQl4DDm62uIkgjbgfvOu9Aum37ubwO6Jfedd2lmE+WzcJ57sboaMUCKnkidNgViYwvct94N2IqrV18BddqUxGOiXI6u4FHopgCgJmZ0Rg2PzhgrnDAxDFNdJPVacxsgw0wAShbEsvmwdxwIiubbWoASgWi+WAYUQJ3TCG3h3PPGDvT6CQyV/qNkRld7KI7VcaIX9A5BkgZI1di4x08EEmH16itogsVdU6IhyDw6gx5OmBiGqS4SWm64DZBhJgj5DOyn94ebEuw4ALHptuRj1ubg7H+pYjsTWdWlQlzSak8ppiWvRFRNk/He/6jbt9oOsxXffgBiU2vyVabafMw1bU423nnw6AxaOGFiGKa61Oahzp4V2panzp4F1BIME5TYBsgwzCegbMa0blFUXdzomBUG6Y4Z24mOS9GSV5OFc/DocN3UYIXp5eM0uinA1xNdexWUy6YHKlveex/Q6Ilk2IrbMS6PNoHL43nw6Aw6OGFiGKaqqPkc9M2tsCq1x1G87NlylWEmBjKe1Tg3Ogq3OkDOsToutFtvhHe2d9iflal1UK+cQZccujbE2qWwdxwIOgJubAFcgkRCxvnl35pJCydMDMNUHaWhHmLLqoABA1nrgAznLYZhPjkynlVZ7wcZcRUAug73tRPh5gAUw3IBwPVgt3eEt1ru7KCZ/5Sme4khR5X9BRiGSSdqPgd1+jSoM2f4/0vZRjDQBhj6PajaABmG+eQMWEGHQWYFPWArXjkmkSWzjGNVVTgdR0ITF6fjCKASLQtdb5jxwrCPTpwCXIL5T2m6lwZwC0W4H3wE9/QZ/38LRdJ4aYITJoZhJj2DbYAjk6bBNkA2fGCYcYJtQrQ1BxadvkteM2ATaJhcB6KtJTzmxhbAJXKOM01oTXND4/p25gTHasVobCwijY2MVjUZ59e2INYtDb+X1i0FbCJTDQw4wT65F+a3H4X51/8b5rcfhf3kXnhne8hipgluyWOYCvDMnslF1dsAz4PvJYa5QPpKMJ/6MfStqyFUDV6pDCWbgec6ML+3HcZdK4HfSDim7cLe/yLUprkQdyyCVzahZAy4PX2wn+2CuO3mhAMOUCj5Lp2bW8/FzRpwu/tgbdsHY+ua5GOWYxbscZ+Plow+ts9HQ6EE68m90JrmBQYDW0/uhfHltuRj9pdg/kOF+/eRXTDuvj35mBhwgt15EMrll0K/de4wUw1r50GIu1bwb84Y4YSJYULgmT2TExkOQnwvMcwnIJcBft0N6y+frPx50nge3NdPwH39RPjnLQuSjwkA+Sz0za1wuo7BHqEn0je3AnmCYaOyNDaGHu2OahAkTPkMYFpwDh5BaI0wT3Cs2Qz0dcvgPNsV0Ijp65YBWaKWvP4CtPk3hNrFa01zgX52gh0r3JLHMCNwC8WAgxtwbmYP9wQzFwrfSwzzCTFiNCAGwYIzzqqcaNgoDANO17FwPVHXMZpjzRjRek4qjY2qQVs2P7w9btl8QNWSj2nEaJgMGg1T5DWlOr+OFx3XIdCIpQxOmBhmJBcys4dhLgS+l5hJQFWF5K4VrWFyCVrG4haxVItcGXOCTBNizVKojbOG/VltnAWxZimNrgcAymVYj+z05z/duwH61jXQ790AZeYMWI/sJJqJNKCHCztWKj2cjDliAODGzBJzieziUwS35DHMSHiOApMUfC8xE5zqt5SqsPe9BO2OpoAGxN73Eo2eSGhQr54ZuuBUr54JCILqByBpTpAJ1BjQmudD3N40pNfyTBNQPaCfaEFfLEe3x1Ecq6rC6+mHOqcR2sK5Qxomr6cXXk8/lHoCd1RZ73wzZiMh7nMmFk6YGGYkPEeBSQq+l5gJjFsoBpIl4FxLqdiyKnkheX8J2ueuDdWA+FoMgiGy/SX/vw1ULyYg5/1Ql4e9/UDF5FBsbEk+JiDnWD3AOfBy5WPdsDz5mLLe+bKqpCmCW/IYZiQ8s4dJCr6XmImMjJbSrAHryb3hrVtP7qURzcuICciZ2WNa0a1bVJUIQ4/RExGYPsiwUBci+jgFUZ1CU6PjarzcHytcYWLGPdW2ZB6c2TNSrD/UhjIJnWZk2F6nwWo7jfcSM4kolgFDh9Y0D+rMGcOsip2uV2nai4SAeuVloa1b6uxZNAtORQkuNpWBmFfPBBQl+ZgAkMtAtLXAfftdKPW1Q+fX6+6DevUVNNWIYhm4aAr0rauhDLY85jLwHAfW48/QtYz1FiA2LIPXW4BiGEMW6l7ZhFKXB3oLwMVTk41ZtqKPlcJCvb8YXa2k0v/1FaEtmgcoyrABwWrjLD9uXxGYThM6LSie501Y64yenh5MmTIF3d3dqK9ne97JiHe2p/Jik9iSOQ0LekDOOZZ5XWWQlnuJmVy4H34E74OPA+5bg4s/ZfpUqJdMSzbm//sQUDXYOzoCMX3TBwfqb1ySbMwPPgQUAXvHgZCYLYBnQ52ebMyh2P/2sX+sIxa5oq0ZatIJBOScX2DwHEfE9ZzEz7GUmO9/CPOv//fwTYaB2U9O16swvvZFqJcSnN/3P4R3tgfe2V4o9XXD9FpKQx2UhnqSuOMRqtyAEyZm3OIWirCf3FtxbgNJ/3zKkHGO+boyzMTA/bgH9g+fq6wBuXMF1KnJ/va6H3wM+0cvQP38dVDra4cNc3V/8gbE7YugTk82kXA/Ogv76f2Vj3PTbVCnNSQa04/bDfvpfRFxW6FOmzLhY8qKKyempHtJwrM6XqHKDbgljxm/XEj/PC+sx4aMc8zXlWEmBqVStAakVAKQ8CLMsaF9/rrQYa5a01zAIdCdyLKClmErLiOmrLhSbNut6JY8Ko2YFaNNs9glb6xwwsSMX9iSmR4ptrZ8XRlmQlCIeRbjPh8Nngfn5eO+AUPTvOG6qZePQ9y+MPmYJROozUNsbg1Utext+/zPKZD1/q22Lm0w7lg+nygxCyXfQXJzK8Qdi4bdS9a2fTC2rkk+JsC/q1WAEyZm/MKWzPTIOMd8XRlmYiDjWVUUaDfPgdN1DNbBI0N/HtqhpzBgyGdgPLAZdntnoKplPLA5+XiDyDi/+Sz0LatCz6++ZRWQzyYfE0jPb00+C31za2iFVN/cOrnOb8pgn0Fm/MKWzPTIOMd8XRlmYpDLRlsV52gWfyNNJgC/rcjpOkYSD0KH3d4ZGtNu7wQEgeU1ABgxtuIGga24oUefXwp7b0DOscqwbZd1fvl3lRxOmJhxy6Al88iXwKCbGhsDjB0Z55ivK8OMDrdQhPvBR3BPn/H/l8qieBDbgli3NLDoVK+eCbFuKWAT6CI8L1qLQeFTZcZomEyiljx4EOuXh5/f9csBEByrLL2WjGO1Yu5fCl2PpHtp8HdVbLzt3Cyx+zb4/8y/q4nALXnMuEZpqIfYsipgyczza5JDxjnm68ownwzvbA/salvxF8owH901XI+RMeD29MH8zjYY965PPmacXohCTyRL/9FfhFcsQ2tZMOz8eqYJ7+MeKLlM8rOJZB1roQRkReixQnGBAsF17S/BfHxP5fuXQk8kQ/d3Hu7rJwLvCO3aK0ljpgVOmJhxj5rPsWsaMTLOMV9Xhrkw3EIxkCwBvquktW0fnRV/LgOYFrzT78MbMAjwBv4ZpkWji8jGtEnFfT4aZOk/dAFrICFVzmtJ80om7G37YHx1U/IxZR1rNgN7z/NQLps+ZDbhlS24p8/Ae+8DiDVLko+ZywB9BdiP7qr8edLEaZSINEzS3hEpghMmhmEYhhnPyLLir81Dv28DnI4jQYOA+zbQ6CIGtC6V5slQal0qxqTQugCApkK/ZzWcjiNBg4B7VgMagWqiJhd9rDVEi2rHhvvmO8Cb78AJ+/wOAvdDGfeSpkbHpLimAI/rqAKcMDEMwzDMeEaiZbBz8GiogB2q4rfVJk2xBLFuGezdnXBPnhr6s9o4C2LtUqBYSj6maUGsXwb357+CUl83ZLXtdfdC/fSn6GbnqBqcw6+GW6gffpWk6qJOqYPYdFtguOrQUNUpdYnHBAAUY1ru4j4fDf2F6Hupvwhc3JBwzBK0xTcBihKIqS2a57cmUsC24uRwwsQwDMMw4xlZbVR9hWGLvvMh27XO6vD+rRvqnEZoC+f6SYQQ8Hr6fF3PxVOSjQcApg3kM3CPnxy+yJ09C+pnrqAb5urY0BbcUNlCnWJI7wChWiJKZLRaZnRAAdQ5swP3EhQAGYIlcM6AkjdC7t9eKBfVkXhb+HHZVpwaTpgYhmEYZjwzYBkc1nJDahksY9da6HAOv1KxpUncuSL5mLW5QMUF8JNCe0cHxKbbko8JAF5lC3UAfhUkYdzu3tBjBQbO790raapMihLdqkYxX0vXo4+V4roKAXv7gcoxN7YkHxOQ945IEWwrzjAMwzDjGGlW/DJ2rUulaFvmEkFLkyyrbRkW6v3F6Jj9dFb1WtPcUItvrWkuTUAZ19W0YmzFado7eVwHPVxhYsY9bqEYsJ/mh58ZDXwvMRMVKVb8MnatC2WgNg+xuRVqfa3fMpY14Hb3wd62j8aWWZb+o2QCF02BvnU1FFWDVypDyWXgOQ6sx5+hs1D/1G9A37IaimXBKw7E1HVYTz5Dq4d7+fhwvZYQcE+fgfPycYg7mpIPWCxHn1+KY5WoJeJxHbRwwsSMa6TMHmEmJXwvMROdalvxq/kcxIbmQIuRevVMiA3NNJsNNVkYD2yG3d4ZcI4zHticfDxAnv6jJgPj/o2wd3QEzq9x/0bADfWTGxv1WRhbVsPeEbymxpbVAIh0U0KFdvOcynotQdDwVJut/vmVrCXicR10cEseM25xC0VYEXMFyKfcM5MGvpcY5pPjdvfCbu/0qwL3boC+dQ30ezdAmTkDdnsn3O7e5IPquv/fDtH12O2dgK4nH3PAfjoMMvtpABBGYDEPDBzrjg5AEMRVjUCydC7mAUAlOlZVnKswjbiXnJePAyrB/r3QY84vwb2UibmXqCzqGXK4wsSMX3iuAJMUfC8xzCenvwj3nXehXTb93N8GtPnuO+/6epekDQJk6E5cC6KtBfbOjqD9dFsz4BLZipfLcN//EOLe9eHthxTufOVyzPklahmzTIhVTbDbOwMVJrFuKWARXFdJGiZt8TyoN84OWNQrDXV0FvUMOZwwMeMXnivAJAXfSwzzySmZ0LesCm2j0resotPYjOXz0aBo8Hr7Q+2nvZ5+KHVEDmNlK7r9kGI2kax3oevB3v8y1Ka5w+zM3Z4+2M+9BHHbzcnHjLs/qe5fD3CPn4B78rxr2jjLbz3k35oJCydMzPiF5wowScH3EsN8cmpzcPa/VNn2esPy5GPKeFY9L/Q4gUG9FsFxAkBdPtSCerD9kMSCWta7UFGgzb8e3tleeFAA24ZnWkBPH7T519PYisuY/VTpmTl5CvA8unuJIYcTJmb8wnMFmKTge4lhPjmOG93S5LjJxzT06Hk9BoHuxLKjj9MiMkKQYUE9oLGpeH6pNDYKAF2H+9qJgAGD1rxgqNUzUYQWfaxCSz6m7URfU5vAaIKpCpwwMeOWwbkCI8X6Q85mxJoTGRbUbHtNw+C95Lz5Cyj1tef1lfdBu/ZKtl1lmDCKMTOP4j4fDb0FiHVLA8YPQ1qX3gJw8dRkY5ZjEpO4z0eLjPY4e0CvFeKSJ9paAJvoWFUVzvOvDLcV1wXcU2fgPP8KxJrFycfsLw3NeAokaU1zgX6C+1dy+7fb3etrC4tlIJ8F8lmaQcQphBMmZlwja66ADAtqtr2mx339ROD8atdeKe8LMcx4JpcBDB1a0zyoM2cMX+R2vUrTvpXRYX5nG8Tm1oDWxfzONhhf3ZR8zFxMVSXu81HHldF+CAA2tDVLIDz4s4myGXiK/3cQzMoFANhOtK04ReUlo8P63tPQmuYFZj9ZT+6F8ftfSD6mxPZv96OzsJ/eH0yEN90GdVoDWdy0wAkTM+6p9lwBt1AMJC7AOQtqsWVV4lUfGTHTBJ9fhhkFmQz0+zbA6TgSNH24bwOQoUiYDKiXXgL70V2Bj8haxnQjumVXJ0qYMpmY9jiC86vrgUX1+THFptuSjwkAigKn61hlPdzapcnHzGSgXnkZnINHMDIdU2fPort/JbQ8ut29odfVfes07Kf3Q9y9kitNY4TnMDHMSC7EgnoyxEwTfH4Z5pNjO3AOHg1dhDkHj9JUBSwLWtPcwCyboUqERdAyZlnQFs6F2jhreMzGWb5rHkVMwLfaXrc09FgnldU2AHhedFyPoLRlmRBrloZeV7GG6PyaMfcvla14fzH6/PbzrMGxwhUmhhmJjB5ktr2mhc8vw3xyLGvYXKLzcU+eokkkCmVYT+6t3Eb1lY0EMUuwfvic3wZ4e9OweUjWD5+DsXVN8jEBoL8E8/E9ldsPKeLKehfKsPjuL8F86sfQt66GWLX4XPuh68B8ZCeMu1YmH7NQir5/v9yWfEyAf+OqACdMDDMSGT3IbHtNC59fhvnkyDBDyOiAaYW2UQ19njT5rG8K03UsMA9J39zqi+cpyGWAvkJo++HQ5xQxx/L5aJFh8Z3PQl+3DM6zXQFdj75uGc11zWWi71+q88u/ceRwSx7DjGTAgjoMMgtqGTHTBJ9fhvnkyFiEDeh6wqDU9VTS1zhdxwCdIEkD5BzrgMamckwqvZaEuEbMdaWwqBci+jgFUZ2iJhcdt4Y1umOFK0wMMwIZduayLdQnO3x+GWYUaGq0gF0j2HMd0DABFaygSTRMMboeCq0LADgmRFsL3LdPQ6mvO2/cQa9/fh0ijc3ieVBvnB2IqTTU0WlsLAti/TK4P38vMNpB/fRlNNe1bMI9fQba8gXhLo8Uei3XgdiwFF5vEYphDLV3emUTSl0OcGnmMKlT6iA23VbZJY8NH8YMJ0wME4IsO3P1htnQbp071Pfs9fSRxksbfH4Z5hMgY46NDA2IrDlM/SaQU+AePzlMK6bOngX1yk8BRYIFfbEMeIB7/ATck+dd08ZZ/jUtEWldiiaQywzEPXUu7uxZUK+8jOZYSyb0LatCrcz1LatodFMKAE+Fc+BIMHFZvxxQCIY9D8aY1gBx98pzc5hyGb/yxMlSInDCxDAVqKadeSXbawBwZ89i2+sxwueXmQxUfbC1jDk2YboSJebzsRLXDkbVplaXh739QLBl7MQp2O2HIDa2JB+zNg9n/0vBmCdPAZ4HsaE5+ZiAf6w7OgImIu6JU7D3dNLErc2FH+uglfmG5cnH1HTY2yvYe+86CLGRyLZ9AHVKHcAJEgmcMDHMeOBCbK95QT96+PwyExwpg62FBnXmjPA5NlfPBIRGEFONnv0kCNoAZbQeAoBpRbcCUrTH2XZ0TNtOPibgH2slx8UTp4iO1Yk5VoL2ODOmvdMkau9kyOGEiWHGA2wJSgufX2YCI23wsoyWPNutOPsJigKxZknyMftLEOuWwm7vDLZRrVtKc5xAukZYxLX6UbTHFcuAoUNrmheuYZpM53eAqlehUwQnTAwzHmBLUFr4/DITGVkV0mxMS97XCFryPC969hPFgNOaLOw9h6HMnBE4TntvF8SaxcnHBNI1wiK27ZHILj5Kw0RlKz6Wz8eAlCp0iuCEiWHGAwO212GLIra9TgA+v8xERtautW5Et+TpBNoeGQYMtgP3zXeAN98Jn51z+8LkYwJDVtsVWwEptFMyYsqKG2EXD4BGT2TEHKdBc36lVaFTBM9hYphxwKDt9chZQYO7Q/yiGxt8fpkJjaxda9OE1jQ3MN9lqCWPQo9RE7PrH/f5aJCVkFoWxLqloedXrFtKZrUdeU0prLYBwLKj41oE2ikZeqIBW/zKx0nkuHghVWhmTIybCtO3v/1tPPzww/ja176Gv/qrv5L9dRgGbnfvOXvOfBbIZ0ntOWVZmacFPr/0cP88EbIqpCUz2uL7KxuTj5kxoDbOHGZ5PYjaSFSJkJWQuh7s/S9DbZoLcceioZk9bncf7Odegrjt5uRjlkxY+1+CvmU1hGXBK5ah5DLwdB3Wk8/AWLss+ZgAUCz7lY7NreeONWPA7emDtW0fjC+tTT5myYzWMBHppqr+zAzErbpeK2WMi4TplVdewfe+9z3ccMMNsr8KwwAA3I/O+nav58+LaJwFsbEF6rQGsrjVtDJPI3x+6eD+eTrUfA5iQ3PAglq9eibEhma6pFSGxbdpQmxogb0j5FjbWmiqAhkjOiGlalNTFGjzr4d3thceFMC24ZkW0NMHbf71gKLE/zc+KbUZGFtWh55fY8tqwCNyyctnoG9uhdN1DPaIuPrmViBPo9eK1DBRJMJZAzCt0DbWoc8pyMccK8X5TRnSE6a+vj584QtfwPe//338yZ/8ieyvwzBwu3sDyRLgC47tHQcg7lzBg+AY5jy4f54Wt7sX9t4XhlciBnbn7b0vQKxfRvNO0vVoi2+dQKivaLDbD4UbMLR3QqyjqIAo0JbNB1wv6Aa4bD6GZ4mJhgV0He5rJ4JxmxfQhNV02E9XmBO04wDEJqI5QXF6Ioq4hoSYGQPqtVdBuWx6oNLjvfcBXfJtGNHHevdKmrgpQnrC9OCDD+L222/H8uXLYxOmcrmMcvlcWbGnp4f66zFppFCKnhdRKPFgOIY5H55zRUuhBO3z14XuzmtNc+neSY4TbfG9nmDwp2lW34ChXIb1yM7wNqpHdtIM6AUAVYXTcaS6g1XLMboeKg2TjLgyNEy2BbF2CewdHYFNBtHWDNhEGiZZ1zVFSE2YfvjDH+Kf//mf8corr1zQv/+tb30L3/zmN4m/FZN6eGYPw3wy+JmhxfOid48pZhMBgBUxbPTkKRoBu6zZRFFtVGSmDzFDZCmMEGQ9q1Kua0ySEPf5aHA82Ls6KlTwOuieVX4HkyMtYfrlL3+Jr33ta+jo6EA2e2F90A8//DC+/vWvD/1zT08PLr/8cqqvyKSVuHkQFPMiGGYiw3OuyIlcWFMhw+I7l4kWr0+m2USyzu9YPp9IcWNnPxFZfMt4VvkdTI60hOnYsWP44IMP8LnPfW7ob47joKurC//zf/5PlMtlaJo27P8mk8kgk+GLzhAjaY4Cw0xYeM4VLTIW1oC0RW6kbmoyzSaSdH5TM4cpGxOTwoAhrvWN6lnldzA50hKmZcuW4ac//emwv/3O7/wOrrnmGvyH//AfAskSw1SNmqwvuMXwHaEhIS7FHBCGmcAMzrmyKrnksX5pbGR1oDYPsbkVan3tcPvpbfv8zykw9OhFmEEQ13XhHH51uOnDYIXp8KsQaxYnH9OxIdYtg72nM3D/ijVLAYfIOU5o0edXEKyDHAuirYIL4cYWwCFa0MuIa/ozkYCQ3/KmuYBJUcGLWR8QVXr4HUyPtISprq4O11133bC/1dTUYNq0aYG/M0w1UfM5eBc3wLvxGmjnCYC9nj6oFzfwi4dhQuA5V4RoKowH74K962DA9MF48C5A8Wjiuk60e5wbqvgZG5YN7eY5cLpeHV5hapxFN+C0bAOGgHpDI7Rb5573zu/1nerKRAlTbwHaopsAILDI1RbdBPQWgEsuSjhmCeaOA9C/tAbCcc/NYdJUmI/ugtHWAkxPNiQAoN+EZ/ZDW7MEwgO8UhlKNgNPAbyPuqFQJN+FUvRMpC+3JR9TaNFVLYokeAB+B9Mi3SWPYcYjSkM91DmNw148ypUz+MXDMBHwnCsiNFHZCnrXQToraNOOdo976O7kYyqKb3AxYnDtoPkEiWg+l/WtzC+bDqV+wG1QAbyPe2E/8wKRlTmArAHr77b75/e8RM09fQbWY7tp3PlyGeD/fQTrz/6+8ucU1GTh7HuxYiJB4giYy0SbeVAca18huqrVVwQunpp83ME4/A4mY1wlTIcPH5b9FRhmCH7xMAwzLpBmBW1FLzhJ9BhetDMfCKpplgXt1hvhne0d9mdlah3UK2fQuAECvq5n5ozQ80um65GlYbKd6HvYJqhWyhhInNFh/e3TlataXyOyqGfIGVcJE8MwDMMwI5BlGRwniqcQzcdZPZeIksOoAbJU9BYg2pph7+gI6nramv0Oh2kNycY0LWiL50G9cbZfTRvQiHndvVAa6mh0PYB/j0a5H1Lcw64b01LqJh9T16OTYIphz0xV4ISJYRiGYcYzsiyDVRVq46zQio/aOAtQ1eRjxiVhFFUBTcIAWQDI6PA+6obWsgDijkW+mUfGgGeavq5nSm3yMUsm4AHu8RPD2h6HNGJUCWk+C33LKjhdx4Luh1tWAXkCMyUrpqWUouXRtKAtmgcoyrDnZuj8UiWkDDmcMDEMwzDMeCaTiWmjohq34Z3TY4Qt/ija4xQl+lgVJfmYlg339BloyxeEVz8ojCYAwDDgPP+TyrqeTa3Jx6ygJXJPngI8jy45NPTo4csUOryyGdNSSpAcli1AAdQ5jdAWhhmIcMI0UeGEiWEYhmHGM5YJsW4p7PbOYOvWuqWARVQVUFU4L70G5YpLoS8cbkrgvPQajcU3EC2ap8C0o6sfJlHCVC7HaNMI2tRkaIkAOTo8GYNra3Ix5hbNycdkqgInTAxTAbdQDNhzqmwCwTBMtemPsIJ+bI9vBU1BX3HA4juYSAw5fiVtQa0ocI6+PnwO02CSdvR1iNubEg6IylUX6pa8Yhm48jLod90OxTTPXVfDgPXUj2h0PbL0cJLiqtdeBeWy6YHKoffeByTx4LrR1UoK3RRTFThhYpgQvLM9sCsNgGuol/fFGIZJHzVZGFtXw951KFB1Mbaupot7vu11mOMXhQZEUyBWL4H79nnJi+I71mmfvw7wCBacTkzVxSGqutRnYdy5Eu5bp4ABAwavbMLr7oVx50oABJWtfEz7Ztzno0WGDk8oEGuXwt5xIJDwi7YWwCM4v6YF/Z7VoXPE9HtWs4ZpAsMJE8OMwC0UA8kS4A8WtLbtg9iyiitNDMNUD92A/fS+8DlM7Z00WhfA105F2l4TLHJVAe/j7lBTAuWSi6BMnZJ8zDijAyojBNXwjzXEnY/sWI0YPZxBlDDJsPjWDNi7Dg6vVg5Ue+zdnRDraWY/OT/+x8pzxKiqlQw5nDAxzEj6CqEvdWBgGntfgeczMQxTPWRoXQDAMqP1RBTaKceG8/wrUK6YAX3h8EWu8/wrNLqpjBFteU01m2jwWEMW9GTHasZcU5MoOXSdGItvgiqeaUa3lFIcq+1EzxGj0ogx5HDCxDAjkdXjzTAME4asd1KhDOvJvZVb8r6yMfmYthO9yKVYcCoK9Ps2wOk4EjR9uG8DjTMfIOdYi6XqX1MAMGMsvh+6myRspDPf2qXJByyWYj7n9cNEhRMmhhmJrJknDMMwYch6J2X0aFvmDMEQTkWp/iJX0+AcPBoeU1FoWrcAOceaMap/TQHfTjsqLoW2x/OiK7MegS1+rDMfD66dqBBMnWOYCU5t3u+pDkGdPQuozVf16zAMk3JyWV9fEoJ69UwgRzD0EwB0ER1XJ9hzlbHIte2YNioiW3EZx6rrMdeUaEEvYyCxDG2ajGeGqQp85RhmBGo+B31zK6xKLnmsX2IYpoqoU+shNrbA3tERGCAr2pqhTiVy7lQAreVmQFGCg2ubF/iDOJMmbh4PxbweWS2PMhb0mgqt5WaoN86GMuDMB13A6+6FMn0aoNHto0eaTVAQl6TFfT4aPM9/NhCiEWteQJMEM1WBEyaGCUFpqIfYsiowh4mTJYZhZKHOmQ3tvAGyXk8fbUDXhVJfA3VO44i4vVDqa2iE+jKGjcpqeZSxoHctKPW1cDqOhCbfcIlsrxUF2qJ54cl301wanZhhxDgCEpxfVQEsC+qNs6Gdp9XyenoBy/I/ZyYknDAxTAXUfI7d8BiGkY77UTfs7QcqLvzEplao0wgsqBUN9u7noVw23a9GAIACeB/3wt79PMSaJcnHzMTYXlNYmWdiFtZULnky4qo67Kf3B3VTJ0/B3n4AYtNtyccE/Fa/jBGafCNj0LQCKr6Nt/vOLwPVNPWqy2kqpIYB58XXhj8z8J8Z9413IDYRDZlmyOGEiWEYhmHGM7JsxZ0YFzeKga6OCdHWAnvHgUBLk9jYAjgEbWqWBbFuKez2zmDMdUv9ygAFtgWxbhns3Z3Bas/apYBNELdsxtxLVLbibqCqNYjaOIvGWMO04J3thXv8ZOD8Kg31UBrqKv/fjjqmBCtzpipwwsQwDMMkglsoBtpYJ+uQZ/fjHt9CePBYc1k6LZEsjY3nRbu4UVSYekswf9wF/a7bIUwTXrEMJZeBZxgwn/oRjJVNwPSEY/aXYO44AP1LayAc91xMTYX52B4YbURVgYIJr2yGtlp6Z3uhUFSYZN1LlhVtrEGRlHoenMOvhFbT4Hk092+hDOvZF0LvJeuxPTDuXJF8TKYqcMLEMAzDjBnvbA/sSkYpDUSJhCTcf/s40CI3WAFRL56afECJow4iqxEU1GRhbGqB+9YpYKCNyiub8Lp7YWxqASg08zVZGFtXw951KHBNja2rCQKei+vsfymi6rIs+Ziy7qVyTEIU9/koqfr9m8/A+N11vkHLyHvpd9eB5gZmqgEnTAzDMMyYcAvFQLIEAO6JU7C27YPYsmrSVJrcj3tgt3dCmTnj3ABOXcA9dQZ2eyeNa50sjY0MxzrdgPdxN9zXTgQWnMolF0GZSqDV0g3YT+8LraTZ7Z0Qm1qTjwkAjhtddXHc5GPKupdkGFzE3r8ESZoqKt9LOzro7iWGHE6YmHFPmtp8GGZC0lcIJEuDuCdO+c/vZHlmS+VojUKJoKXJtaJ1PVTOZlkDuGgK9K2roagavNJAe5HjwHr8GZpFrmP7WpdKbYAbCLQusjRiMtrjXLfyvdTWArgESRoACAG1cVbFahoEwXJUxhBZWfcSQw4nTMy4RmabDydqDHOByNJFyECGrscG7Bd/Aq2tBcKyzukidB328z+BuPVzyccEAE2Bcf+m0MW1cf8mwCMY6GrZ0QtOiyCmrPs3bsFOsaDvKwK1GWhrlkB48JPgbAaeAgAO0FcGLkk+LPqL/oYCEG4r3l8kCCph9lOa3oUpgxMmZtwis80nTXoMhhkzEjU2Mqi6LgKAdt1n4L19OqDr0a77DFlMaBUsqN86DXsHkQV1XJuUSVBNk3X/Zgyo114F5bLpUGfOGNbe6b33AU17XE0W9o6DlS3qKSp4AJDVYf2gHWJzK8TtTfDKJpSsAbe7D9YPn4Px/21KPqainEvSRg6RpZr9lLJ3YZrghIkZv0hq80mTHoNhEqE2D3X2rNDnVZ09C6jNV/0rkVGSoOsRGqDrcI+fgHvyvIVf4yxoy+f7n1Mgw4I6rs2PIokw9JgBpwSVHgCwbYhVTbDbOwPtnWLdUj+BShrHjb6mFLopABAC+j2r4XQcgT0iedHvWU3TkqdpcF4+PlxvKATc02fgvHycaI6YJI0YQw4nTMz4RVZpO016DGbSUs2WUjWfg765Fc6bv4BSX3vegMg+aNdeCWUyPS8ZAzB0aE3zAlUBp+tVwCBYENkOnINHhyVLwLnWJpKFHyDtHVz1Nqr+oj8PqT3okifWLfPbxSjcD10P9p7nK5tNkNhel6Lv30Ip+ZjAuXs4rJVVUWiOtb8I7ZYbg3pDyjbAUswcsbgNF2bcwgkTM36RVdrmHmRmgiOrpdR9/UQgpnbtlWTxpGBo0O/bAKfjSKAqoN+3ATAIqj2eF+2m5hFZFct4B8toozJ0eGd7oLUsgLhjkd8uljHgmSa8sz1QphAMOB2g+rbXWehbVoWaluhbVgH5LE1cGfdw1gBKJahzGkfMueoFFNCYlhgavF93h2rEvI+6oVxEdy8xtHDCxIxfZLX5cA8yM4GR0VKarjZWpfJOuapArKdwcZPQBgjIaS+S0UalaXCeDw44BQZ1Pc3JxwTkXFdDjzYtodClAXKOVdPgHH61utfVMOB0/lPlmHevTD4mUxVU2V+AYSox2Oajzp41/O8DO+VkC7CBRC30O002PQYz+biQltLJEFMWll15p/zEKRoXt1h7ZCJdhOtAtLUEWuHO2Zk7NDFXNcE7fQbWozthPb4H1qM74Z0+A7GqiSamHePMR6ElAoBszOZb3OejQYYuDZBzD8u4rrLOL0MOV5iYT4Tb3ev3/RbLfuk+n4VK2K6gNNRDbFkV0GJQaiIGEzWrUkvTpNkpTx+psIqX0VIquY21qtc1ToNAoVFQFKjXN0L9/HVQ62uHOYy5P3mDpk0NADQBe/9L0NYvg3Dcc3bmmgr74BGIlluSj+kB9sGj0O5oghic/ZTNwHMd2B1HIZbPTz6mjGsKAJoaXcHTCPa0ZR2rokQfK8U9LONYi2WgNg+xuTXwrNrb9nFL/wSGEybmgnE/OhuwmFWvngmx6Tao0xrI4qr5XNVNFmQkagwtqbGKl9FSKrGNterXNU73QKGLUAFxRxPsHR0BhzHR1kxTdQGAsgnthkY4u4JmCFrTXJrdcgUQzfNht3eGGDAsTT4eIOeaAkApZiBxgWBxLetYPURr0yhkeDKONZ+B8cBm2O2dgWfVeGAzTRLMVAW+cswF4Xb3Vp7H8fR+v/I0yVDzOajTp0GdOcP/X06WJixuoRioGALnNDZugWZoohRktJRKamOVcl0HdD1h0Ol6dNg7OirMQ+oANCLba6Ci3sXpOkYTUDdg7+3yNUz3boC+dQ30+zZAmTkD9t4uQCc4v5lM9P2bIUr4a7Kwd3cOP9Z7B461vROoITBgGKj0hEFW6QGAjH5OmzbiWJ2Xj9MM6ZXxrKoikOwD55wPodLWKdxCEe4HH8E9fcb/38n02yYZrjAxF0Z/Mbovt78IELbmMcyYSJFVvIyWUmltrDKuq2lBWzwP6o2zoQwMkfUt1HuhNNTRDFY1Y3QRJlEbledFx6VwNrNMaLfeCO/s8E04ZWod1CtnABbBsbo2tGXzAdcLVj+WzQdcIg1T2YT75jvAm+8gtEZYXph8TAUQ65ZWt4IH+M/Nwt8CdAHFMIZa1dTZM4FPX0b03FjQFs0DFGWY7nDIVpwiZrkco2Gia8lLTReFJDhhYi4MttpmJjIpu39ltJRKaWOVpdfyED5Etmnu5NKIydK76Drc104Ek5fmBTTxTBvWIzuhNc0LOPNZj+yE8dDdNHFlXFdVhb3ncKgLob23C2LN4uRjAkDJhNJQX3nWFdVzo6CyrfgkelbdQhH2D/cFDGkmp1OpHDhhYi4MttpmJjIpvH9laP+qHlOG81ZtDs7+l4ItNwOzZMQGAltxWfdvLub8xX0+GlQVTseRyrbXFOe3bAGmBefgkQqVHoJKBCDnutpOdFXrdoKqFgDU5WFvP1ChVe2Qr9lKmgrPKjBoKz6JntWe/mj3zp7+SdNFIQvWMDEXRk0uuhe4hh9EZhzDVvGTE6FFv5cEwRBZx41uuXHc5GMaevRxGkQaJk1AbZwVHrdxFqAR7LlaMVbQFLbtsowQZGhsZM30Mq2YtlKCpNR2YmzFCcxSspnoa0phFQ8AhVL058WYz5lYuMLEXBDqlDqITbdVdslj/RIzjkmjVXwqLNQLpWjnrbhFxChjjunz0dBbgFi/DO7P34NSX3uebqoP6qcvA3oLwMVTk4/rONCWzw9omdSrZ/p/dwgWnGUTMHRoTfOgzpwxdKzuqTNwul6lqfYoCtTf/AyUGZcEYnpnPqQzQiia0S55RYrBtTFJWNzno0VW+2yVLb7Vi6ZAbGwJVNMGr6l60ZTEYwKIT66prmuK4ISJuWDUaQ3+lOrBOUy5jF954mSJmQCkySo+NeLfrAHrOz8M1548uRfG1+9JPqYU23bjPN3UqaE/q42zoF55GU1rHAB4XrS25/e/kHzMfBb6llVwuo7BOnhk6M/q1TOhb1kF5AnOrzJg295+KBBTrFsGGs9rAJoCr6cP2polEB78mVO5DDwAXncflDyBS57uVw3D2rfUxlmATrQslPHc1GSjLb6JUC+eCrG5FSiVz/3WZDN0yRIAZPToOVcULoQpgxMm5hOhTqljNzxmwiJD11Nt3EIxkCwB1RH/Vr2qlTGgzpwRqj0ha2kaaLmpuDChaLnRDdhP7wvVTdnthyA2tSYfE/CrPdXW9uh6RStzABCbbks+pqrB3lnBtr39EMSG5uRjAv6uf38Rzp7nww0uKKoCmhZdNdQI2liBofbDygt6gmPV9crjUNo7ae6lAUiTozB0MWSKEnovUSXCKYLPIMMwzGRCkoW6lKpWqRzdklcqJ7/B47qV26jaWgCXQMMky6o4VttDsGstw0LdjtFN2US24o4TY3BBkKiZ5eiq4dcIqoYA4MYM6XUpLL5j7iUqvZYMTBOwLKg3zoZ23nX1enoBy6IbPZAiOGFiGIaZTEjQCkiravWX/P/+5laIOxb5GoWMAbenD9a2fTB+Z23yMcsWzB+0Q9+6GkLV/DaqbAae68D83tMwfmdd8jFl2YprWnRVgKIaEXusBAu/kglcNAX61tVQBq9pLgPPcWA9/gzdwtqy4L7/IcS968M1NhZBElEIOb9KzOdJ4GmwX/gJtLYWCMuCVxw4x7oO+/mfQCy6KfmYEsdJVL3aXijDeuo5iM2tUOprht6FHjxYTz0H4971dLFTAidMDMMwkwkZWgFZg4GzGeibW+F0HQtoFPTNrUCG4FjLJvDrblh/+WT45xQ7ubKsiosmRFsz7B0dIdW0ZprFdaxVPEFVqyYD4/6Nocdp3L8RcAnMLQDAcqI1NiWChKkmRiNWQ6CbAgDXgVj4ufAK07qlNOdY0nMjpdqez0C/awW8s73woAC2Dc+0gJ4+6HetoNH+pQxOmBiGYSYTAxbqYQkMmYW6rJ3cjAS9Sz4b7eKWI1hwytB/AEBNFnZ7Z/iQ093P+wvdpNFF9LFSaDFEhNZlRwed1qU2D3t7hMZmI0Fc3Yh5Zoj0cKoKe+fBysdKMRMpE6M3JNhQcQtF2Hueh3rr5yBWNg2rGlp7nved8ig2jwwjeuAzu+SNGU6YGIZhJhFSLNRlVUBkzOypr4F+3wY4HUeCO/T3bQDqa5KPaVrRWi2KGTYDcd1fvg9x85xzbT5ZA8rMS+EcPU4TV9WgtdwMKErAEVBrXgCoBG2AsrQuMvRa5TLc02egLV9QwbadaHPDdqLjUsxEcmNs212C89tfgFh5CzzL9c0VFQVQVShT6yFW3gL0E1XbLTtaD0cxGDhlcMLEMAwzyai6hbqMqhbgmzqM5fNR4hw8Gr4wURX/vCdNsQzryb2V7dO/sjH5mABQtqJbxij0RH0FKPU1UOc0Qls4d5h4Xamv8e/pixuSjSmrQiojbtmKbsmjSr5LJvStq+Gd7R32Z2VqHfStq30dWdL0mUCNAq1lwTCNo2eafgtgvwlcknRQFQDgPNMZSPjJ3BYBoBwzGJjC0TJlcMI0gUnFYEqGYUZFNS3UpQ0GNmL0LHGfj4a+AtxT71XeKafQa2WNaHvvODe70VKXDwzgBM5vGSPYtc5nAlqiQdSrZ9K0bsmqkMbNWaKYw1SThbPvxQhnPoLzCwB1OcB1K7eM1RG8Iyrcv4NxSe5fVfFjjphz5Z48BXtXh++kSUHcwGd2yRsznDBNUFIzmJJhmAmBlMHAihKtUVCUkP+jMVIyo3foKXbKZRwn4LfkRbaMEexaO250TIfAtt2IGfpJkXgDgKbGuBCqyce0nRgLdSKDC0+RYKEu4f4tm6FDgYEBAxyq9s44Mw+K5DtlcMI0AZE5mJJhGKYSVR8M7HnR2h7PSz5mNgPnR13VXfjJOE5ATsuYjJi9BYh1S2G3d4Y7uPUWgIunJh+3vwRt8U1Qb7wGSn3tUFXA6+6D0lAH9JeSjxmX0FMk/IBvoR6pNyRIXmTcS7FtwkTnN5uJNvO4eyVN3BTBCdNERJaFL8MwzHhCaHBePh7q4ua8fBxizeLkYzoxRhMOgdGEjOME5LSqxQ7LJWg/zOgwv7MtdJ6X+Z1tML66KfmYAJAzoOQycF54Nah3WbsUvmtA0jEltR/GaWgoNDYyjlWGLT6QriG9kuCEaSIicRgbwzDMuMF1oS25KdSxTmteALgE7VtxRgcURggKoo+TqCMPGQPqtVdBuWx6QBfhvfcBjZ25iBmWKwhc8jIG1Esvgf3orvCYVLbtQg+3FT95Cnb7IRpbcVnthzKSFxFjUS8IlsB6zPnVic4vrwvJ4YRpIiJrh4hhGGY8oamAZUG9cTa08yovXk+v3+KjEVh8y6iAuJ6vYwo7TkXxP6fAtiDWLoG9oyOQqIm2ZsAmqAr0l6LbDyna1GwrekAvxXECcmzFZVnUT6mNdtKcUpt8TNeJbrWkGJarIsYWP/mQAHhdWAU4YZqIyLLwZZgEkeHyyM6Sk4yaPJwDR6A1zYWiavBKZSi5DFCfh9N1DGLdsuRjKkp01YXCgEFVAFWD0jgLStmEVxw4zn83Degp+J9T4HiwdwUd64YGuq5ZknxMQ8D6XoSF+kN3Jx+zUIb59H7oX1oD4bhD59fTVJh/3w6DanCtjKpAoRRtUf/ltuRjDqAtXwB4CE8kKHA92K/8H2ibboM477nxMgbsF/8F4qbPJh9T16HU10Jra4YwrXMxDR2KB5rBywCvC6sAJ0wTEGkWvgyTEDJcHtlZcvKh5nMQt90SsA4etAwmSYZVQKxqgt3eGay6rFtK0x5Xk4cCFfbT+0MqIC1ADZ0DVmQFhAJdQJ05I9RC3W9pIli25DLQ71gEZ9ehwPnV71hEtzsvoyqQy0Rb1FMda08/rO/v8BO18+ZruafPwPq7HTD+YEvy2mtdgbj5xsrPDQj0hgM4Ye8kKktx8LqwGnDCNEGRYuHLMAkgw+WRnSUnJ253b+U5QdsPQNy9EuqUumSDCgP20/sqzyba1JpsPAAomrB3VDjOHQf8mBT3b5xQnEJIrmlDFYfQeT0agYZJ16MdxqgqTJlMtN4lQ2GqERMzS5QwFUvRiVqRoNVSjXhWB5+bpLGdmGeV6F4Crwup4YRpAlN1C19m0lLVVjUZLo/sLDk56S/Cff9DiHvXQ62v9d3Nsgbc7j7Y2/YB/UUg6YSpXI5xoyJoo5IRE/DNDqKGYVKYIZhWtC6NanaODIcxy4RYtwx2e7CyJdYtAyyCuJYJ0dYM9+13odTXnWdl3gv1M1fQxAQuwD2O4F6S8qyyW91khRMmhkk5VW9VS8tsF4aesgXjgc2w2zthj1hwGg9spnGsS9P9qyjQ79sQ6s6n37eBRq9VKMF6/BloTfP8Bf0A3se9sPc8T6OxkTWbqGgCNQa0lgXD7Mw90wRUDygQxHUBr7cP7vETcE+e98w0zoJyyUVQaog2jiQNmR7T56NB4m8Nt53TwgkTw6QYKa1qsvr2qx2ToacuX7klr70TYiOBZiBN96+mwTl4NLxVTVEg1i9PPqYMjY0M50MAqKsJtRUHBnV4BO1bmgqn40iolTk8D2IDwTUFAFWJduejMC6RcV0lPavcdk4PlcEhwzATgQtpVUuaATefMMjcfGTEZOgxrRhbZoL2rYHZLmGQzXYxjOiYBtGC3raHOZqdj3vylN/OlTSZmGOlaN0aqH5UjElR/QDk2IpbMYOXLSIjhLoaOEdf94cv37sB+tY10O/dAGXmDDhHXwfqCEYAyLiuMu5fQM5vecrgChPDVCAVFtQS2gdkuPmwg1B1qPozI6P9pa8AbfFN4XNWFs0D+gsALko2Zm9/9DyZ3n7g4oZkYwJyzq9tQbS1wH37dFBjc/VMmplIHqKrH0RjrqSc33LM+SOaw6Tmc9A3LIf70VkohjGkN1Rnz4R68xyad7CM69pXhGhrgb2zI/B+EG3NQF8RmNaQfFxuOyeHEyaGCSE1vcCS2gdkuPmwgxAtUp4ZGfdvPgOlJgN1TiO08+yRvZ5eKBfV0SzCMjrM72yD2Nw6TOvi9vTB/M42GF/dRBAUcs6vqgKeC/f4yeELztmzoF51uf950hjauerHiNlEztHXIdYsTj4mIOn+jbGgz9FZ1Hu2A+fAkUDyomxsIXHjhyHgvHw8/Lq+fNzfbCCI6f26G+qc2SPeD33wPuqGUk9QSQO47bwKcMLEMCNIVS+wxGF3Mlwe2VmSBmnPTC4bLSSnWPzp4VbFgzFJrIozGaiXXgL70V2hMUnsp4Gh9qLKttcE7UWqFpibA/j3kr3zII0ts6JCWzQv1NxCa14AKETqBSPm/FK0WuYy0e98Ko3Nxz3RIwDuXAF1asIbK5oGbclNla8rhUW9ocPp/KeI9wOVRb2EZzVlcMLEMCNJkQU1t6oxiSDrmbGt6FY1ivYtGVbFrh3dWuQS6U6smPNrTRKL77IJ64lnhlfwBuzprSeeoavg9RWiz29fIflWS9P0Kx8egi2lC+fS6KYAoFiKvq7FEpB0wlQqR1vUlyaRrbhpRr8jqK5riuCEiWFGkrJeYKWhHuLOFf7MmmLZb9nIZ6EkPb+GmbzIemYKZZg7O6BvWQ1hWfCKZSi5DDxdh/nkMzA2NCcfU4ZVcaHsV+rCFvTb9sG4d33yMQGgvwTzqR9D37oaQtXglcpQshl4rgPzkV0w7lqZfEwZ57dkQt/cCqfrWMCeXt/cSmcrrmvRrZb3b0w+ZqEMa9dB/5quWjzsmlqPPwNjy6rkYwJy3hGFEqyd/rEqg/dvLgPU5/1jpbh/Jb4LrSf3QmuaF2g/tJ7cC+P/20wTN0VwwsQwI0lZL3Bq9FoMHbKemXwGxpZVsHccCOyq+gs/AkGRDKvifCZ6QZ+nOr9Z6OuWwXm2K3B+9XXL4vUwo0HG+a3Nwdn/Urh9OkBnta2L6FZLnWCJls/AuG8D7N2dgQqTcd8GQCNyBJTxjqjNwrhvfWgFz7hvPUiEU7LehTLs+FMG24ozzEhSZEHtFoqBdjzgnPbELRTlfDFmYiHrmVEF7B0d4bqIHR2ASrDglGFVrAk4XcdCj9PpOgZoRHufhh4d19CTjynj/DpudBuV4yYfEwAUQGteEDjec9opgphCDyRLgN+eZ+/pBATBNQWAbCb6umYJFvTCCCRLwLk5bRAEybcsW3Fdj46rE13XFCG1wvTd734X3/3ud3Hq1CkAwGc/+1n85//8n7FixQqZX4tJOanS9aRIryUTGRb1bndvoM1SJWqzHHxmnDd/AaW+9jwr6D5o115J98zI0BMB0BbPg3rj7IDttdJA1MZaijlOCi0G4OsxTp+BtnwB1Jkzho7VPXUGTterZHqMSC0GBbLaqBwXSl0uVGOj1OVoErVSufJsrROn6O4lJ0aH5xDo8MpluO9/CHHveqj1tcNaWe1t+2jeD5YFsW4Z7D2dgfWDWEOk+wOAUjn6vUR1XVOE1ITpU5/6FL797W/j6quvhud5ePzxx7FmzRr8y7/8Cz772c/K/GoMA/WG2dBuHW4LOulImV5LBjJaHt2PzgacxgYdmlSKGSCDcV8/EThO7doryeJJuX8VAIYB9/gJuCfPO7+Ns+iqArKe05IJfetqeGd7h/1ZmVoHfetqGm2P50VbQd++MPmYmZjd97jPR4sQsPe+APXz10GprxnSMHnwYP/4JYhVi5KPKVNjU20dnmnDeOBO2Ls7YY9sP3zgTpqEv2QBNVloy+dDrGw6d01NE9BUoL+UfEzAv24ewt9LTXP5tzwBpCZMq1YNFxf+6Z/+Kb773e/i6NGjnDAx0qhkkQwA7uxZk8tWPGV6rWojw27b7e4Nt2V+6zTsp/dD3L0y8UqTPFtxCfevEHA6jgxblAADjmMKICiMJuK0QhRaIgCoywFeBR2YYfifJ42qQKxaBLv9UMAKWqxbBhJdmi6iLZkptEQAYNsQK2+B+/P34EEBbBueaQE9fRArb/GTxaSRlRxmjWgdHpE2zd7RUbH9kORZrcvD+7jHf0eMrKQ1L4CStBPgIJV0eCdPAZ5Hp8NLEePG9MFxHGzfvh39/f1YsGBB6L9TLpdRPq+E2tPTU62vx6SJNLWpSZzDlApk3Ev9xej2rf4ikHRrnqxnRsbsEdOKbmkyCVpuNDX6OLVJJEcWAvbu50MrTPaPuiDWLEk+pqr61UGEtIs1L6AZljuA11sMrQool1wEpXaSPDOAv9FQQQ8HgGY+kYxn1XECyRJQBQMRWTq8FCE9YfrpT3+KBQsWoFQqoba2Fu3t7fjN3/zN0H/3W9/6Fr75zW9W+RsyqSNFbWqp0muhuroeAHLupbTEBIDeAkRbc8D4Qb16JkRbM9BbAJJuQSyZgKFDa5oXruuhaFPrK0JbNA9QlODsnKa5QF8RmJ58WACA58F97UR4IkGBacH92dvAz94Od/tacWvyMXsLUOpz0FoWDLP39kzT1xL1FoCLpyYfV1XDF9eUVQHLjta6WEQzvWTMJ4rT7VA8q5YdfZxU5zf2WCfPukUW0hOm2bNn47XXXkN3dzd27NiBrVu34oUXXghNmh5++GF8/etfH/rnnp4eXH755dX8ukwaSFmbmtJQD7FlVcCUYNIlSzJ0PTLupbTEBICsDsCBtmYJhIdzM2UUAHAGPk+YXAb6llVwuo4FWsb0Lavozm+5DHVOoz9c9PwBnArozq+H6u+Wy5jDlDXgfdQL54VXgwnponl0Zh4yFtclM1rrQjVzSsamSly1jKL9sBxTtYr7fLTEHitR5TBFSE+YDMPAZz7zGQDA3Llz8corr+Cv//qv8b3vfS/w72YyGWQyk2uxyoxDUtimpuZzk6fNMAQZuh4Acu6lmlx0y00NwXWW9czoeuh1Bc4lw4mjadGtRRS6CEOHc/jV6h4nIGdBL0NjY+hwDr9SudJDdX7jqioUi+uaHJx9L0ZUtQjuX0DOpoouoF57FZTLpgeqwd57H9Bo02RtHg3Y8Vd871PY8aeMcdf47LruMJ0Sw1SbwTa1kXNlBtvUJo3hQ5q4EF0PATLuJXVKnV81C5ntIjbdRpIYSntmZLT52DFJBIVQX8ZxAnJ2ywcMGMIgM2CQdX7jZg9RGCG4MVoXl0jrYsTMCSKZ6QWI1Yvhvfs+rEd3wnp8D6xHdsJ7932I1YuJ5lxp0TPphEYQ1Edrmhs+04vKjj9lSK0wPfzww1ixYgWuuOIK9Pb24h/+4R9w+PBh7N+/X+bXYhi/Te3OFQG9i0Kpd2HokKhLk9HyqE5rgLh75bn7N5fxK0+E92/gmRmISfrMyLiucS1LFItrWfevjN1yx402YKAQr8s6v9lMdGWWYphrbFWLKDn0XIgNy+G+88uAdkq96nLAI7iutufPQwpzydt9CGL10uRj9hagLbrJjzNyxMKim3w93CUXJR8XiLbjv6OJJGaakJowffDBB7jnnnvw/vvvY8qUKbjhhhuwf/9+NDcTlYQZ5gKRMTuHIUSyLk1Gy6M6pS55N7wIpDwzMq5r3K4/hVZA1v2ra9ELep1gt1xBtAEDRQFE1vl1bIj1zbB3dgS0U2JDM80wV5nvQkWFe/zk8GOdPQvqZ2aC5MJ6brRLHkWSNqg3vKFxxBzHXj8eWUseoN08J1RbqTXNpammpQypCdOjjz4qMzzDhCJtpgxDhwxdT4qQN4cpG31dcwTziRQFauOs0IWY2jgLUAg63TOZGCtoqkWYBm3ZfMD1gtWeZfMBhSBh0g14Z3vgffBrYKAS4ZkWvO4+AApN8p2JqfQQnl9772GoCz8Hcfu5IaduTx/svS9ArFqcfExZekNN+HrDkdWeE6dg7+qA2EigE5NhIGIYcF58Dcpl0/1KGgAogPdxL9w33oFYT2QrnslEV5jauBAxVqSbPjDMuCNNc5hSwqCup6JLHnElxi0UAy15kyrp7ivA/fBj6H+4BYqq+W51uQw8x4H1+DN0z4xtQbQ1w3373WCbz2euAGwCjY1QoS2f79ttj0wils8HBMFWrmUO6RACMZvmAhaVhqkM64lnIDa3nqv2ZA243X2wnngGxlc3JR/TtaOtzF2Cqotr+wmgh6BL3jKimABgmnBP/ALKb0yDN2BK4JkWvNPvwz3xC+C2mxMPqeZzEG0t4e/CthZavWFUtYeiFTCjR48AoDAQsczoSg/Vs2pbEGuXwn37vE0VBVCm1kH7/HU078KUwQkTw4wkRXOY0oQMXQ+QkvZO04Zx/8bQeUjG/RvprHRdD15fIdjm0zgLyvRpNIM/LQfWIzuhNc0L7ORaj+yE8ftfSD5moQzryb3hMZ/cC+MrG5OPCQBlE/rmVjhdx2CPuK765laa6yrDytxyAMsKt223TMAiqjCVzGiLeoIKiFsowt7dGT4YeHcnxF0raJImGb+rhoB+3wY4HUeC5/e+DYBBsAR2vWgXTYrBywAAFV5PX+V3YX0tUdz0wAkTw4wkZXOY0kS1dT2pae/MZSrbtu/ooLNlVhQ4B16u7uDPkgmYFpyDR8IHq1LslGeN6JgUbmrAgAX1S1VOXiRYmStKtG37WgJzAACozcHZX+Xz21eA+3/eBv5PhcHAVNXguHuU4h5WNDgHj4afX1WB2NCSfEwg+v6lwnOr/y5MGZwwMcxIUjiHiSEiLe2dsmyZZSyuZZg+CC1aw0RlVWw7MRbqoUvusSHDynxEe+X5uG+dBjwv+ZgA4LhwT5+BtnxBeMsYhSNgoTS2z0eLjHvYimkDpGiPk+GiCch5F6YMTpgSYNLrE1LG4EwZq1Ib1SS8tm53b8BCnbpVLRUUy9E99JOlvVPWcZat6LgmTStg5MKPgr4itMXzoN44O6DVUhrqgL4iMJ0grgzRfNYAavMQm1uh1tcO003Z2/bRVCLi7iOqltJSueotebHzjijmIQH+PRylw6O4hwsx7524z0dDnC6K6vzK2GhIGZwwjZFU6BNSiIzZObJwPzpb2QxhWoO8LzYZyGeiF0T5SdLemc/GHCeBWx0A1EiIqyjRCz+FwPQhlwFKZbjHT8A9eV7Mxll+TKo24VxMchL3+WjQBYwH74K962BAN2U8eBegUpxfI/o+ojhOQE7Lo6pCvfYqKJdNDySH3nsfACqByyMAZA1Yf7e9sg6PQvsX936leP8aenSHClXCxFICcjhhGgOp0SekFBmzc6qN291bWXvy9H6Iu1dypWksGEa0APjulTK+VfLEHeemVjlx71xBEFOPtu9dv4wm5gtBjc2QPoFKI6aLmDlMBEsIVYW9o8I7addBmmNVtej7aAORJbPjRrdRUbTkaQrEqkWw2w8FkkOxbhmgEQ3syRhQZ84I1eH51vgESalhRFeDDYKYqhptxU+VkOZjRixQbVqlCKIrlxIuRJ/AMOOZ/mL0D3Z/scpfaJIhS9sDf0PH/eAjuKfP+P9bILyWTkz/PMUATgAolqLjFgn0GJYFsXYJvNNnYD26E9bje2A9uhPe6TMQa5cAFkHrixlzH5lU95EKsXZZoNXQN0JYBpIlhIxnxo65f22q+zemJaxE4RxnwN7dGZ6Q7umkSSIAwHV92/Kwe6mtBXAJkkPTgtY0NzSm1jSXpmW3bMJ6ZKe/oXLvBuhb10C/dwOUmTNgPbKT7p1vmjHHSvdbkxbGtD1kmiZ+8Ytf4KqrroIQKSxWsf30pCYV2jSJGpvUnN+xfD5KvLM9cN/8hW8la9tAfxHeO7+Ccu2VNK3Cst6FxXK03oUirgfYh1+B1tYCYVnwigMzp3Qd9uGfQNz6ueRjFs3o46TQugCA68B+5nC4BfUzhyHWLE4+pgzdlIyYgF9ViXr/UiQvxTLcU+9VNpoolmmcRC0b5t+3Q9+6GmJwVls2A891YH7vaRi/uy75mMWy3+1z/hyxgcHA1rZ9ML60liRmpKMl1buwEHKsgzPTtu2Dce96mrgpYlRZTqFQwEMPPYTHH38cAHDy5El8+tOfxkMPPYTLLrsMf/zHf5zolxy3cM/opCU12jRJ2pPUnF8J7wi3UIT3b2fhvvavgZYQ5ZKpUAw9+cRU1ruwJgvjgc2w2zuDepcHNtPEVAGx+CbYOw6EDP5sBlwC57h8pvrHCfjOW2++A7z5Tvjib+WtyceUYT8tIyYAGHrMnCACvUsxzmiCaEFfMoFfd8P6yycrf540uQz0u1bAO9sLD8rQYGD09EG/awXNe0nWuzCfiZ6ZNln0shIZVcL08MMP4/jx4zh8+DBaW8/1pi9fvhzf+MY30pMw1eahfvYzUC69JCiefP9Dtp+eoKRKm5bNVF0DkqrzK8OivlCC8/wrw6sCgzvIz78CsW5p8tq8jBF9nBT6BADQ9coavPZOGr2LpsPeHjFzaiNBTF2H/cxhqE1zA7vH9nMvQaxenHxMIN5Zi6KlSVGiTQkoTDUyMVoXqvtXVaLnBLURzAmqycLZ92J1jSYAOYmE0ABdh/vaiaCeqHkBjZW5rHtJ6NXXc6aMUSVMu3fvxrZt2zB//nwo5728PvvZz+Kdd95J7MuNd9R8DmLtUthP7w+KJzfdNnkWfWkjLbNzAMCyYmY3ECyIUnR+pVjUmza0m+eE7iD7vewEegzTjhY6U8QE5OhdZOiJLAtixS2hFSaxbinNcwrImTmlAGJVE+z2zhBTAqIBsrYd7XxIpWEqx8wJorh/ZRhNAIAQ0YkwhazD8+B0HKlucmhaEOuWwm7vDFag1y0lG3WAUoyes1QCMIm6NyQwqjv0ww8/xPTpQcP8/v7+YQnUZMctFANtGcDgTuOBybVTnibSpE2TcawSz6+MeVNVt6hXEHRxG6wwvXwc4o6m5GOaJqwnngnvn3/iGRj3b0w+JiDv/q22bkpVYe88WLmSRlUVgISZU6oGe2dHxLESONbFaV0o9DUDccf0+WiIa7mjasnrL/rufLtHJMKNsyDWLgUKRQBTk40pY5hrsQzzH340XKuVy8BzHJiP7IJx9+3JxwR8neNYPmdiGVXCNG/ePPzoRz/CQw89BABDSdIjjzyCBQsWJPftxjsp2ilPFWnSpsk4VknnV+a8qWpb1Gu33Ain69XAwmRwFz1xTBv6nSvgdL0Ke8ScIP3OFXQVJhn3kgzdlO3EuLgR6KYAOTOnZDjWZQzod62Ed7ZnhNalH/pdK+naqGTcv3FGElQuefks7F0HAxU19+Qp2Hs6IdYRJP0yhrnmM9DXLYPzbFfgmdHXLaPTEsnS4aWIUSVM//W//lesWLECP/vZz2DbNv76r/8aP/vZz/Dyyy/jhRdeSPo7jl/SVIlIEzJ0J7KQcawSYqZr3pTi97KfHHGsAwsVsYagrak2B2f/S5VjUlVAZOgFZOimZP3WyJg5FdeGRtGmJoRfha2odSFyAc5mot+FWYLFtSyNjeNEtx86BEm/jIRUlzSTTlGir2uKur+oGNUQhVtvvRWvvfYabNvG9ddfjwMHDmD69Ok4cuQI5s4l2sEcj6SpEpEiBnUn6uxZw/8+oDuZbG2W2rL54bMbls0niSfl/KZp3pTnVl6YnDwFeAQaBduBe+YDiHvXw/jDe6A/cCeMr98Dce96uGc+oKuA9BUh2porzHZpBvoIrqsM3ZSs3xrXgli7NHzm1LqlgEuwQx+3YKdY0EdoXZyOI4DnJR8TAFwv+v3rEsS1LWiL5kFtnDU8ZuMsaIvmATaRxkZG0q+pFVtH1atnAhrFHLFyzPuBaHNDqNFzmASPXR0ro942ueqqq/D9738/ye8y8UhTJSJlVF13Iou+AqxHdkJrmhfYQbYe2Qnj6/eQtJJV/fymqRosY6ZM2YxuUysRLcJ0Dd6ve6CtWQLh4dxsFwXwft0DpY7gHSzjXhJa9O4xhdsXAFge7B91hs9hau+EuH1h8jGFiDlWgmqPDPMbwNf+Rb1/f/8LyccsmoACqHMaoS2cOxTT6+kFFNBpXTIxFulxn4+GvmJ0S2lfEQjK8ceGrN+amjycoy+EV4OPvg5xF7vkjZVRvXl+/OMfQ9M03Hbb8NaD/fv3w3VdrFiRjgsjxQGLqRrV1p1IQdaQPVT5/KapGixjYVKbh729ggFOeyfERgJ7ZMDXW2glOHueD2+lotBjyLiXXBdi3TLY7YdCnLeWAS6RsxkQPYeJImFynOhFLkXrVmwbIJWzmRn9/qXY3KjJhdqKAwP3E4WpBuC3H0a55FG0H2YNWH+3PTwhfXIvTUIq6bdGzeegb1gO581fnPujAihT6yFunsPr0QQYVcL0x3/8x/j2t78d+LvnefjjP/7j1CRMQIoqEczkJC2JRE0uete6ZhI9r3rMDr1OsENvxuzQU1npum6MbTDB4k9GBUTX4XX3QWtZMMzFzTNNeIUSlCm1yccE4hfsFO2HxTKsJ/dWXuR+hcBxMW6xTiWYlyHUl2GqAfjW+FF28RRVvIwBdeaM0ISUTK8l4/1wHu7rJwIb+Nq1V5LGTAujunJvvfUWfvM3fzPw92uuuQZvv/32mL/URENWJcItFAOJ2mTT18gkFec3JW2l6pQ6iE23VXbJIzZ8qOq95Lh+dQUhO/TNC2jmrBTLgKFDa5oX2D12ul6lq1RaFtzTZ6AtXxAel2IR5jjRc1YoKiCeC+fAy6HaNHX2LDpTjawRbaFOseDM6NFVF4oKqa5Hvwd1gpiAHKG+rGfV9WCPqAQD51Wh1yxJPqZpRVcrKTZy+ou+FkxRhj2vQy6lBRq9bKoGwktiVAnTlClT8POf/xyzZs0a9ve3334bNTU1SXwvJgbvbE/g4RhqBWzg4WRjJS3nN01tpeq0Boi7V56bw5TL+JUn4mSp6veSAsCyoN44G9p5O/ReT6+fQCgE1zSfhb5lVeiwXH3LKn/mFQWmFR2Xws5cU2H/6B+hNs0NzOyxn3uJRtdj2dEOYxTzZADAMGA8eBfsXQeD2rQH7wI0Au2UjAopXIj1zf78pxGLXLGhmcYoBQA0QLQ1w97REUy+25oBjyD5lvWsAtGVLQqkVCsNoFSqrBGjciHkMTfkjOrNs2bNGvzBH/wB2tvbcdVVVwHwk6V//+//PVavXp3oF2SC8E4CLWk7v2lqK1Wn1AFVtA+Xci8ZBpwXX4Ny2XQo9eeO1fu4F+4b79BUIwxJVro1eTj7XqpuS56qQlv4OTgdRwJJhNa8AFAJ3KhkGHkAgAJ/dk5YVWDXQRoLdTemQkqh19IE7J0HoVxxKfTzFrlD5hZUFTxNh73rULipxu7naWzbZT2rMto7c5noaiVFy7mmwTn8avU1YmkyNpLEqBKm//bf/htaW1txzTXX4FOf+hQA4Fe/+hUWLlyIP//zP0/0CzIh8E4CLSk8v6kwuJCBjHvJNKHdPCd0B9lvQ6FwyZNkpevE6DEcgsqLbUOpy4VW8JS6HNlg1TF9PlpkWKh7iK6QegTvqVI52tyiRFA1BPzzGxW3TBBX1rMap8eiuIcNPbpaaRC0WsrSiKVFjyyRUbfkvfzyy+jo6MDx48eRy+Vwww03oKmpKenvx4TBOwm0yOrxZiYfMp7VgoQ2FFnvpDgLZAqLZA+wO45CWzwPiqoNWZmjPg/7wFGI5QTzy2TZisu4rp4H581fQGuaB8U04RXLUHIZ4Demwel6FWL+DcnHlPXOlxFX1rMqyS4+Um9IoXGUUUkD5A0kThGjvkMVRUFLSwtaWojsYpnK8E4CLflMTI83n1/mApHxrGaMGNH8JLHaBuS4jCmAaF5Q2eIbBMNG+0vQFs+DeuNsv81yYGHtdfdCaagD+kvJxwTkXFddgVg4F/b2EIOWthYABDv0snQ9MuLG/X5R/b55DkRbC+wdB4LXdWMLTTXY9WD/6B/DWx73dtHoDWVU0gDANKOTQ4rOgpRxwQnT3/zN3+ArX/kKstks/uZv/iby3/393//9MX8xJoKUOJtJI67H++6VMr4VMxHRY1pCKNy3sjE7jRRJhKzdTUWB2jgr3D2ucRaNy5iq+eYAoW5fh2g0ClkDKJbgHj8B9+R5i6FB5y0q2+tMJua6EiyuVQP20/vCz++OAzQam0zMO38zka7H0GP0RAQaMS2m0qMR2V4LHXZ7hSHIe56HWLuUJGzV54jJshV3PNh7uyonh6sW0cRNERd85f7yL/8SX/jCF5DNZvGXf/mXFf89RVE4YSImTc5mUpDRty+ZVFioy6BUjraYLRG0v5gWtCWfh9ayAIphDFlBe2UTsBwaK13TgrZ8PtQbr4FSX3teBaQPysUNdHOYhAptoAUucH6XLwAEgQGDbUdbmVNoFHQdzgtBIbl78hTgeRAbCRbWAOCYvovbzoMh7nHLAYdIDxd1fik0NrLmiJXNmGMlOL/9RWhLPg+oSnBez6KbfBdRCsom3J+9Dfzs7fDkZcWtyccsmdEtjxTnV8bgZQBw3eonhynjghOmX/ziF6H/f0YOaXI2qzop04ilxUJdCsUyoKCyxSzFvWRaUKZNgfv2u8BA+5ZnWvC6e6F+5gqgQNC+ZbtQGurhHPqncFtmKhc32/UNAsLOr2UCNkFLU8mMbqOiOFYrZkFPocUAgH4TXtmEOmf2iPPbB++jbigUlUMZ5zfumSgStTzKONacAaU2B235fIiVTcOGICv1tXQLehlOj3Ht9RQtpaUYDen9BBpSwE/qo5JDqqQ/RXzi2qBlWbjmmmvw7LPP4tprr6X4TswFws5mREjUiFW70pM2C/WqU5uDsz9oew0MWswS2BXX5uGd7Q39yOvp9zUvSZPPBIYCA34FxG+jIqqAANEWvhRtPrX50GtKamUeV4mkqFQCQE0Wzr4Xq3z/5uAc+qfhrUWDC7+Xj0OsWZx8TFm6kwrvh3P3EsH51XV4H/fA6TgSatuuTCXaJJOhN9R1OC8fr3wvUdi2Z2M0pFTtszUxergauvlaaeETJ0y6rqNUItptYZjxgCSNmJRKTwot1KuK48bYXhPMlHEdwPPgvnaiwhwbgh1kWW2snhcd1yMwYJBhZS7LVlzK/etG2+JTzGGS5UJoOzEW1ATPquMEkqWheCBK0gA5Ft+mFTNigaDqosXcSxTDngFAxOjh7lxBEzdFjEp99uCDD+LP/uzP8Mgjj0BQCdgYRhIyNGLSKj0S2w/d7l6/X75Y9t2g8ll/sCwhVY8Z1+pD0R7nofoLIln3UVmCRqFoArV5iM2tUOtrhzRibncf7G37aKzMgehFGBUyrqvrRS/81ixJPmZ/KVp3QuVCKMNW3IpJ+C2iOUGmFX2OKZIXT8K9VPR1f57nQbGdIVt8T2hQFIXQor4UfV2LJYCqepgSRpXtvPLKKzh06BAOHDiA66+/HjU1NcM+37VrVyJfjmFkUXWNmKxKj6T2Q/ejs4EWLvXqmRCbboM6rWHSxJRyfmUsiKTZisdoFLIEcfMZGA9sht3eCXvEvWQ8sDn5eACgKNGLTQo3QADIxOz6x30+SiLvXwqyBqzvPV1Zd/K1L9LElWErXo5JTOI+Hy0l09/829wKcceiIe2U29MHa9s+GF9aSxK26vdSTdbftBrhpDlki09lUZ8y7bUMRpUwNTQ0YMOGDUl/F4YZV1RVIybrZSeh/dDt7g3Xu7x1GvbT+yHuXpl41UdGTABANsaWmWJBX44R/1IsiGTZimta9A4yhZ5I1yvfS+2dNHotI0SLMbCgJ9NiDMSNtG2naKOKqwpSVA01DepVVwz/20AOql51BV0bVdh1pdbYyNrcyGegb26F03UssNGgb26lmf8k415SlMAMMeB8W3wiPSfP5yTnEyVMruviv//3/46TJ0/CNE0sXboU3/jGN5DLscaBYcaEpJedFIv6/mL0rl9/EUg6eSnExCwQxAQAx44eJkihd8lJcIaS0W4D+BbfkRoQgvMrQ68lQ4sB+JWt5fMDWjH16pn+3ykqWzL0WsUyxNolsHd0BM6vaGum27CScV2FFr1JRqXXitPYUFjjy7iXZOk5ZenwUsQnSpj+9E//FN/4xjewfPly5HI5/M3f/A0+/PBD/P3f/z3V95sQyJphk5bZOak4TonDiKvefiijmhanKyHSnaBQhtlxBPqm2yDK5rl+9owBs/0QjOYFyceUUXUplILtNgO6HmvbPhhb1yQfE5BjVSzl/g05v1VoZ0LZhPXD56BvXQ2havBKA/ev48B6/BkYv0MQV1GiF34USVpNNjhUdaDSY+9+3t/cICLyWaVweewrQqxZCntPZ2CTTKxZCvQVgUuSD4tyOSaRIHhuZNxLsrpFZOnwUsQnSpieeOIJfOc738H9998PADh48CBuv/12PPLII1BVggGBEwBZM2zSMjsnLccpexhxVdsP41ovKFozZFjaAr7eZc3SUO2U0dYCgMDxS0bVJZ+Nabch6tvPxVy3uM9HFVNCNTibgX7nCjhdr8I+ed75bZwF/c4VdPev5cC4b31ohdS4bz1QoqlsRS78KLDs6EoPlRGCDJfH2iy8ngLUGxqh3Tp8dpnXX4RST7Q5J6NVWIm5lyikf7Ja4zJ6tA7v979AEzdFfKKE6d1338XKlSuH/nn58uVQFAVnzpzBpz71qcS/3HhHlrNZWmbnpOU4B0nNMOJsNkbXQ7C4lrHTCACqgP30voh+9tbkY8qouhgx7TZUfftGjHbKIEgkZOi1DMM/vydHnN+TpwAFEBtako8JALX5ynqM9k6aNipdh3P09XC91tHX/SoIAVWv9ABynlVPgXPg5YjZWgQVaCB+iCzFRpluxGj/CBxDZek5c1moM2eEzn9Sr54J5HgO01j5RAmTbdvIjljM6LoOi2rK+HhHlrNZWmbnpOU404ZtQVs0D1CUYWJytXGWv+tnT5Jda0BOG4qMapoZ07dvErU8ytBO2RZEWzPsHWEuWM00969lhRovAAPvQqrfYBnX1XOgLZoHp+NIsNrTvADwCGYTyaj0AHKeVcuCe/oMtOULwis9VPeSLmFTxTSh3Xrj8EHeCqBMrYN65Qya+9d1IdYvh73rYPD9sH45zRwxAOrUeoiNLbC3HwjG3dgClS3Fx8wnSpg8z8OXvvQlZDLndgJKpRK++tWvDrMWT42tuKxe1bTYR6blOAdIS/shiiagAOqcRmgLh7eEQAGNnkhRoncaVy1KPiYg5x429Gg9HIWzmTSNWAnWk3srt6F8uS35mH0lmE/9eLiuJ5uB5zowv7cdxl0rgd9IOGaafmtMG9YjO8Ov6SM7YTx0d/IxZVR6ADlCfdOOrvSYRO2HMswQimXAA9zjJ4ZVZ4c250juXwvm97aH6g3N//UUjPs3Jh9zAPXiqf6A2mLpXJdKLsvJUkJ8ooRp69atgb998YtE8wkmArJ6VdNiH5mW40TK2g/zWTg/6qrcErKRor3Ii9YogGgHWcY97HnQls0H3BBns2XzaXbLZWnEws6fEvN5EjF/3Q3rL5+88O80VjJ6tP6DaB4ScpnouBTHWjYB0wptLfI/J6iAyLp/PTfaRdMjqEbU5ODse7G6pjCAHIvv2hyc/S8Fj/XkKcDzaIZ4ly2grwD70QqFA6o5VwOoU+t5QC0Rnyhh+sEPfkD1PSYmspzNJDqqVZW0HCeQrvZD24kxJSBouVHV6ArTmsXJxwTkaGysmB16CvGvLEvbjAH9vg2h7Vv6fRto9AIyjtUQ0cdpjGqkYjwyzm/cbDKK5EWW7kRRYf/4H6E2zQ1UI+znXoK4fWHyMWWYwgByLL5l/NakaKM3bRC9ZdOBLGcz2Y5q1WLwOJ03fwGlvnZod9Pr7oN27ZXkx1lVO3PJ7Ydud68//6hY9h3N8lmaQa6AnJ3GvmJ0hamvCExPPiz6ChDrlsFuPxSyg7zMv78ubkg2ZrEcvUNPcS8VYixtC0SWtp4H5/Cr4YM/X3gVYs2S5GP2FaEtngf1xtlQ6uvOey/1Qmmoo7mXPAXOwaPhVQFVgVhHsFMOAI5b/bi6gDpnNtR5n4VaXzvMot599f8AOsGypbfg69J2HgzoKsWG5UBvAZjWkHzcviK0+TfAeeFV2CP1nIvm0dxLxXJ01ZDqt0bGRkPJjD5WilZLXUC9vhHq568L3r8/eYPm/mWqAl+5MSLL2Sw1jmoA3NdPBBJD7dorSWNWXU8kcVfK/ehsqO212HQbVIpFghRbZgPW322vvuVqRod3tgday4JhO8ieacI72wOFIimVcX4NHdbfSrC0tWxoC26orh10LuPrMY6fDJqWLJpHc35tO9r0gaoqIMVswoFY2QR7x4GARb1oawFAcKwZHd5H3VDnzB6hq+yD91E3lCm1yccEgHwGSk0mVM+pXFRH0ymcz8a41RG5qcmYEyTDmc+2Ie5ogr2jI+T+baZ7VhlyOGFKgKrOsBkHcatFqmzbJbUfut29gWQJGLANfno/xN0rk680yWh/yWaiLVfj2oBGi2HAef6VynotCltxGedXUaLPL5VtOyTYQRs6nBdeDSQSQxbfbQQaPBlVWSBeb0Ghx1CN6lvxGwac539S3ecUAHQ99P17Li6Bc5ysEQBZI3pO0NcI9PAi5lgpbPFVLeCgORjT3tFBpxFjyOGEiRm/pMi2XVqbZaEY3eNdKAJJJ0ymGWMFTbD4M81ocTWV7XW5HG3hS2ErLsNqG5Js22XYQZtmdNWF4l6Sof8A5JghyLDiN2NimkRtajKc42TEBHz3zqhNFQr3ThnHKksjNhijmlKClMEJEzN+SZOVLiS1WcbZPVP0eBfKsNoPDbdlzmXgOQ6sx5+BsWVV8jH7SzD3dELfshrCsuAVB2LqOswnn4FBNAwTJRP6PavhdL06vCWkcRb0e1YTnV8JVtuaJFMNGXbQkizUI6uGVCgK1MZZoQmi2jiLpnIo4/1bjNG6UNniy9ATyfpdNS1oS26C1rIAimEMaXu8sum3zlJs5MQlRBSbGxL1yKkZTSIJTpiY8UsKbdur3mYZt0NMsXOdz8C4b31otce4bz2gqcnHrM3C2LIK9o7gUD9jyyrAJXBLAoDaPJwDLw+bAQJgaAFKMmk+l4k2faC4f/tL0aYaFPoEQE4FJM7Cm8LiW1GiK3iELY/aonl+3DC9FgWSNI6RWhcqW3EZeiJZv29lE0pDfWUDHIrNDRm/b5LOb6pGk0iCYGXCMAkxoOsJg9RWXNcr7tqqV88EdKKZJ5KIPFYKhB5IloCBHu/2TkAQnF9hRPaVQxAtiByncvvWyVOAQ5CoDWiYwqDTiBmwntzrV5ju3QB96xro926AMnMGrCf30i04ZRxrJhMTk8ZUY6iCN+L8Oi8fp2lnAvx3XcaA1jwfxh/eA/2BO2H84T3Qmuf755biXSjjmkboepyuY3TnV0ZcGecXAGrzgWQJGHzvHwJqCRbzihJ9rBQbDbLO74VICZgxwRWmBOCeURqk6XpK5ejd3BKtxXdVURRoi28CFCV8B5mk5aYU3eNdLCU/eE+GlgiQ03IjQ8OkqVBnXwll5qVQ6muG2m2UmZdCnX0lTdUQAMrm0H0auH+b5tJoFKyY80vhHGda0G69Ed7Z3nN/UwBlah3UK2eQ6dKgAHBdOB1HgsfavGD4kOCksCzfin93Z9Die+1SmvNrWdHvJBI3QMjR2EjSOMKMOcdU2sqo9wMFrgexfrmfHI68f9ctA1yiIemSR5OkAU6Yxgj3jNKj3jAb2q3DrV5JkaEBkUU+C0VTw21tp02h2Q2T8WIvmdGtLxTtIICcVh8Z92+hHG2lS9WSV7YABaH3LxTQuLjJOL/FMgClspU51WLIcQLJEnCey9gGgpbSQhle2Qy5pn3wPu6BQvJOkqCFAyTptcrR9+/9G5OPORB3TJ+PBgV+xSfs/ZAxaBJ+2wZUJdSiHvDoTB94YC45nDCNAe4ZpaXS+QUAd/YsuvMrQwMiC9v1hzVW005Xxou9Ngdn/0vVXfgBvl1xtW1tZdy/tTnY2w9UbHkUGwmstgGgJgtn34uV71+K6yrl/ObhdP4EyhWXQh9chA1WKl96DWL14uRjAoAV4/hFMeeqwrMKEF5TGVoXIH4OEMWcoKwRff9SHauM976q+Ql/BdMSEg2ppsHeGWz/BgbvXyJbcUmjSdIEa5jGAveM0iLr/NbkonuQayZREizDwlfG+XXc6ON03ORjAoAV03Jj0VhQV72HXlK7DRwn5rpOEo2Y60BbcAO802dgPboT1uN7YD2yE97pM9AW3EBnWiJjDpOMZ1Vo0ddUaMnHBAA95l7SaZKXqutWAd9WPCouhV5LhoZUkq34oIRhpO57sOOJN+/HDleYxkIKe0arqteSdH7VKXUQm24LDBQcHCSY+CDX83C7e4H+on9s+SyQz5LGk3GOh87v9gPBHu+NLTTHW4hpCYv7fNRxY85f3Oejob8E0dYS6ggoNrb47XHTEo4pbQSABDtozx9O6759Gkp93VBMr7vXX/hRSBQ8r/oDegE5VYG4e4VCQ9pfita6UL0fzBgNHoXttSzHRceG2LAc7ju/DD43V10OOASJhIx7SeK6UMpokhTBCdNYSFnPaNX1WjLtvac1QNy98lzyksv4lRHKZOmjs5WTtGkNNEElnWNfNxXs8VaozAHSZFGf1WE/+wLUprkQdyzyDRgyBtyePth7X4C4fWHyMSWe30iNGEVcz4XXWwjqiWbPgvLvLoZC0friIXrXmmJALwDoWnSbj05QeYmzZSdyjkOpVFkLZxC1qZXN6mvwNC1mZtqS5GMCgKoCjhf63KhXforGGCYnYeyA5HVh1UeTpAhOmMZCinpGpei1JJ9fdUodQFndOQ+3uzeQLAEDGpCn90PcvZImWRuwSK44EJPAIlmKNk2I6OMURK/CgfatyueX4AfbceH+9CTcn54M/7z1luRjyjq/EbbMACA2EWjEPC9cD3filO+QRaGxiXNLo3BTAwCo0JbN9xO2kRWQZQtA0tUv45nJ6HBefA3KZdP96gcAKID3cS/cN96BWL8s+ZgAUJOHsy9Kr0Wgd3EdiFWLYLcfCmwy+C5uRO2dqoC9Y1/oc2O3H6LRyxox9xJFIizj/mWqAidMY0Ca7bUMLkRPlPDxpur89hejd5D7iyTJmzptCsTGloBgf7B9S502JfGYMu4l9BWi21D6CsD0i5KNCcix8JXREuI6EOuWhg4jFuuWEmpsJNgyyzBCiFtkUS3CTBPWIzt9R7XzKiDu6TOwHtkB4/e/kHxMy46xbSc4v6YVPXiZTIMXcy9RtKkJAa+nH1rLgmEVaM804RVKUOprko8JyNHLynj/uk50SzTVu5AhhxOmMZKanlFJfbl8fi/w8zGgXjzV390rl8+d40yGJlkC4i2mKSyoswasx3ZDbG4NtKlZ2/bB+Oqm5GMCciyoM3q0rieu5Wk0uB7sQ/8E7Y4mCFWDVypDyWbguQ7sjqMQy347+ZiAb/ccdawUdtBlKzom0eJavfYqKJdND8T03vuAJB4A/30Q5agmw/b6KwS2154H5/WT0NYvg3BceMUylFwGnqbC6fwJxKJ5yccE5GgcLdt3XJxxydC95JmWfy+9/yHESoKWXUDOb5yM969hwD7wMrS2FgjLOncv6Trs538C0XJz8jGZqsAJUwKkomdUpp6Izy993zNVchRG3IKdYkFv6NDvWQ2n40hgTpB+z2oaXQQgx4La0KHftwFOx5Ggrue+DTTHqioQzfMrV5iokKFhiouZpbBHViBWNcFu7wxpo6I9v2P6fDTE2V5T6E6EArF8QXhVoK0F8CbX7BxtwQ2Vq2lUyDhWGe9f04RYONe3Fg8bvExh5MFUBbYVZy6MAT1RGJNNryWFNFmZy7Bl9gDn4NFQrYtz6CiNsxkw1EMfBlkPvapGH6tK8NrXDdh7u3wh+b0boG9dA/2+DVBmzoC9t4vMHjlKw+R0HaNJDmXE1PVAMjoY027vBHSihH9A4xgGlcZRSkxNDyRLwOAcsQOARnV+JbwLgej7lwoZx5oxoF7fCHHvehh/eA/0B+6E8fV7IO5dD/X6RiINqQd7d2fAztw9eQr27k7AofqxYajhChNzQaRKTyQBmVbmAOD+utu3WB1syctmoF5EVHUyLWiL50G9cXbAXlZpqKNpabIsuKfeg7Z8QXgblUWkUbBijpUibtmsPHvkxCkaXY9pxmhAiHZVZWiYZMQ0Y2JSnV/ThLbkJmgtC6AYht/KmvX/F5ZNE1dGzLIJ9/SZyu8HKlMN24Joa4a9oyOkstUM2ATvB8+D+/6HftJQXzt0ft3uPtjb9tE5LkrRE1kQdyyCveNAoLNAtLUALtH5jZr9RHV+GXI4YWIumNToiSQhw8ocANx/+7iy6cPFU5MPWCz7rlvHT8A9eV7MwdkjFL3sJTO6jYpC6zIQN/JYKeJK0sNJmRMk41ilxIy5TwjvX6WhHnb7oZBWy2U0x1q2omNSJC+y3g8qACihBgy+3zhBTNOG8cBm2O2dgSTCeGAzUCLaPJKiTdNg76xcOSRxIZQ8n7OqszJTBidMzCciFXoiiVTTyhzwK0sjkyVg4Adl+wGIza3JV5pqc+G2zAO7byS2zJViDi7oKWICQE0Wzr4Xq3usMrQCnidnTpAsXUS1Y8bpdqhc8urysNs7h8/sGai82HtfoNFP1eYqv5PaD/lOYwQxpbwfVD10nARwrrsgcWrzsLdXGGHR3gmxkSAmIEebZse4ENqTyNESEmZlpgzWMDFMminFWL1STEK3nZgfMQLbVceNse91k48pK66hx+imCPQYcTvwVDv0MnQRQouOKQiGuSpKdExFST4m4Ft83zwH3ukzsB7dCevxPbAe2Qnv9BloN88hs/iObj8kqIDIej+kqb1Txj0so9qTiXn/Upgawa8sjZRMAOdmZbqFIkncNCG1wvStb30Lu3btwr/+678il8vh5ptvxp/92Z9h9uzZMr8WE0Gayr0yjtX9uAcols7FzGWhTiXcGZLV0lSb96tXYT30RPayY/p8IsXtLUCsXwr35+8FdFPqpy8DegtA0q2WcbvDFLvHANBfip550l8CpiUcs68YM9OrCExPOKbnRcekquB5XnSr5ZolyceUZD89ps9HS7EcbVE/WVpKB4i8hymQUQ3OZ6E1LwAQcpzNC4B8NvmYgJz5hilDasL0wgsv4MEHH8RNN90E27bxH//jf0RLSwt+9rOfoaaGaHgaM2rSVO6VcaxV1xIBcn5QarLRPfQUyLJtl9S+5f26F+7xkwFbW6Wh3jebSBpZ0+11FeaTz0Dfsjow88R84hkYd61IPmbWgPV32ytrMSiGuQoB58jrw1vjBmI6R16HWL04+ZgDRFYjKEhLmyUA5LPR2imKxbWsY9V1OC8fD7+HXz7u69OSRsJ7Sc3n4F3cAO/Ga6Cdd5xeTx/UixvoNN+StVNpQGrCtG/fvmH//Nhjj2H69Ok4duwYmpqaJH0rJgy3UAwkEMC5cq/YsmrSVJrcQhH2zoNQLr8U+q1zh+36WTsPQty1IvFjdT/uidYS3bmCptI0YOFb+QeF4MdTD+/bH+qhp+jbl7Wgz2SiB46SnF8B5/ArlXVTFBoQx4ZYvxz2roPBhH/9csAhmmNjGNBXL4ETUmHSVy+hsW3PGFBnzgjVYpDdS5oKbfG80NlaWvMCQCPqro9rCaNoGZPxrMp4DwKAYURX8Da1Jh9T1rvQtiDWLoG9oyM4S4zKEdC2INYtrTwfjiKmLCRqp9LCuDJ96O7uBgBcdNFFoZ+Xy2WUy+ey5J6enqp8LwbpKvf2F6DNjxjs109wrMVS9E5usQRQJEyuFd3SRGG7KqNv34r54SSzFTejB45aFBbJMRqQMsXCxIX5t09DbG4d5vbl9vTB/F9PwfjqpuRjAoDjVpw5BUXxk7WkkWGPbFqwHtkZXtV6ZCeMr30x+ZiAnEWYjGfVMmNiUtnix2hIywRVATPm/FLcvwCgafD6itDWLIHwAK9UhpLNwFMAr68IpZZg/dBfhvnY7vD30ne2wfjS2sRDVtpcBgB39iy6zeUBbWXFRJhCW5kyxk3C5Lou/uAP/gC33HILrrvuutB/51vf+ha++c1vVvmbxZMKXY/Ecm/Vz68T07dP0Tog6/zaHuxnO0PbJOz2Tog7CCq9Mo7V9WDvfxlq09zAD6f93EsQt92cfEwA8DzYu5+vXE2jsNuOE20TzbFBXwH2o7sqf06BjPlahVK0PfKX25KPWSxHO4xRvR8URC/CKIT6/SWYT/0Y+tbVEKp2bmHtOjAf2QXjrpU0MR/fU3lhvXVN8jEBaRrSaicRAABFhXPon6DMuGToWfXKpl9tf/9DiDUE78KMDpgWvNPvwxuMOfDPMC0aAwZZm8uFUvRGDpUOL0WMm4TpwQcfxBtvvIEXX3yx4r/z8MMP4+tf//rQP/f09ODyyy+vxterSGp0PZL6nqWcXzfGMcklcEyS1VfueXDffAd4853whdjtC5OPKeNYFQXa56+D03UsoJvSmubSuYx5MRoQCrG+jKqArHYQ047WgJgErYC5THTyQnH/xi3siJy3AKX6Qv18Fvq6ZXCe7Qq2Wa5bRqfriUr4yTRMMf/duM9HQ9aIPlYqgxbLgrYgonODYnPDENDv2xDayqrftwEwCJbAsjY/swas7/yw8kbO1++hiZsixkXC9Hu/93t49tln0dXVhU996lMV/71MJoMMVS/xKEiTrge1eaizZ4XunKizZwG1+cRDSju/cS0JFC0LuWz0Tm6OyFknLRoFICg4HqxEvHycppIGxNtpU5xfGa0ZstpBKs25opyfI+P+1UV0TJ3op1xocI5WMJs4SmQ2Yegxuh4ijWOk1pDKtCTmXtIJ4ioK1MZZwwxhhmI2zqLbPIKE4dZCr9yyqypkGrExfT5aavNQr7wsXFtJtEZLG1ITJs/z8NBDD6G9vR2HDx/GlVdeKfPrfHL6CnB/EdEOMol0PWo+B31za8Dnf6jaQ3GcskrbcTuYBDuc6tR6iI0tsHd0BJzNRFsznbW4NI3CMtjth0J66JeR6Ym0m+dU3t2kIifBbttxo6sCFDNl+mPaQfqJ2kFkzPSSobHRNGgtN0O9cXbAKl6ZPg3QiBJSx4G4vQn27hEavMZZ/gLXITi/MjSOjm9I4L79y2F/VqbWQ7vps4BDpOsxzRg9HE0r61DMEb81pO9CGcOtLSs0MQQG1hAUz6rQopNvos2jwTWa8+YvoNTXnveO6IN27ZV07nwpQmrC9OCDD+If/uEfsGfPHtTV1eH//t//CwCYMmUKcrkJcHFLZnQ7CNWwRkkoDfUQW1YF9ESTziZTUjXN6+6DOqcR2sK551mR9sLr7oObz9JU01Q1+lhVAvetkgXkdWgtC4b10HumCageUKBZnFR9dxPwKwNR55eiMlAsR2ts7t+YfMysAet7T1eOSWVKIOMd4QH2s13hur+9XTTVSteFUl8Lp+NI6IYKSZswAGgC9o+7oC78HMTtTcO1f/tfglg5STSOiua/Z1/710DiolwyFcqU2uRjAkDJjH5Wv0LwrAJwXnoNyhWXQj/vt8Y9fQbOS6/Jq7ZTrJfiNmooNnKK5WijH2J7b/f1E4FNbe3aCVaMGKdITZi++93vAgAWL1487O8/+MEP8KUvfan6X+iTks/C+VFX5UUYhX2vZNR8rnpVs4GErOKAU6K+cinVtEIJzoGXK7ZmiI0tNOddaH6F9IbG8J1rit2w2lyohTpw3rEmjYzdTQBQVGjLF/happG7ucsXAApBQpo1ojU2JC1jWnQ7iE5UAZGhh5Oh+1PVcCv+k6f8sQMUbWqAbxd/2y2wd3fCHpmorV1KYxcv6Zo6HUeq29oJyNHDKTHVdqqOPEkz6cb0+WjIZSqPCGnvJFsXpkoiIgnpLXkTGhntIGmiNg/jwbtg7zoYHHD64F2kPblVr6bJsIIGAMv2W2COn4B78rxzPNieYREsiMyYY6XQiMnQag38d63v7/B3kEfs5lrf30Ez5NTQo3URBoFBgAdozb7TYGB3s/lmgOpVb8RoQCjmMMnQpcloUwMAKLCfezG8wvTcixArbk0+pAw9nGVHn1+K9yAAaGr0sVLM11LV6AGyaxYnHxOQc6wyYspaF6Zp9IskxoXpw4SlFFNajfucicayA4MwgYGdml0HIe4msJc9j6pW08omYOjQmuaF6+GIetnheXBeeLXykNM1S5KPKaPlRpYQV4YddG8hWmPTWwAunppsTNsBymWoNzRCu3V4SynKZUKXRyd6YK5H0KqWNaKfVYp7SUY7EwBoCrSb5wB1NX7SqyiApvranpvnABqNrbi2aB6gKOEaG4o2qrIVfU2pNqz6itEapr4iMJ0gZlSFiSLmYFwZx1rtmHG/5VSbGxJHv6QFTpjGQtxOLcVObproL0bv1PQXgSl1Vf5SRNRko/VwFFa6A0SeYwpktGaIGJcxQfQqzGWifzyJLKjNR3ZVnmPzu+uSj+l5cA4HE29gIHmhSLwBwHKqPzBXVaB/uQ3eBx8N+7MytQ76l9sAlSCJkNFaBAA1eShQwwdbt7UANQTvpawBlEqhek4oIGujinz/UiX8WQPW322vrGGiqEDnYmJ+jSAmIOdYZcTMx9xLFFbxgLzRJCmCE6axoMaUeykE82lC8o5JVQfmZjPRpgRU1bS02Io7ToxzHFGbRMaIngNCNBNJv3NF+BybO1eQVdPc02cqO4ZSUSxHz5SheEcI4euYXjsRvJeaF9Ak37Js28tWIFkCBqr8Ow5A3Lki+Sq8pkUn3xuak40HAHqMlflGIo1YxoA6c0a49o/qXWhkomMaRAtrQ4+JS7DBbMScX4qWXVVEj7BYT6SHk2BWlTY4YRoLWsxQP4p2hTQhccek6gNzy2b0gpOqjC+jVc2NaaNyCZIXGc5xAOC60XNAKH48vZiYFAJ204oZIEvU0iTjHeG61TcIkGXbXixFV6CLJSDpkQd2jJ7IJtATWTG6SqJRB1Is6iVZmcNzq98+KyOmaUa3PBKdXylmVSmDE6axUJOHc/SFykP97loh+xsmTlWrLjW56F3VGpq4UtxmJFrUR86MoMBy4BVK0DbdBlE24RXLUHIZeBkD3sc9UCjaDzMhu5fn72dQtc+aMXNAKBIJ04Z75gOIe9eHu0uaBAvOfBbO869AbZp7rjVuIKbzkzcgKJzjADnVShkGARk92radorUIkKOdkhFTVjdDfwnm43vCW0q/sw3G1jXJxyyU/N+x82MOPKvWtn00MQGgrwSvXA4dJ+F93A0lkwEuSTqo5//WrFkC4cFvT85l4AHwCiUotQS/NZ4XXa2kak+GBLOqlMEJ0xhQ8znoG5bD2rZv+CJ3kmb01a66qFPqIDbdFrDTVa+eCbHpNqhU+iUZbjO5GIv6NiKLek2BWLsE9o6O4MyItmaaao+uQJlSF35d21oAECw4DT26NY4qYYoTi1OIyU0bxgObYbd3Bt0lH9jsz8FKGteFWHFLaEyxbindnCDTgrZ4XvhA14Y6IsdFCdfUENG27QbRT7kM7ZSMmGEbKp/k89GSy0S3lFJUSPNZf8Bp17HAs6pvbqXTy2bPJf2Dm3Ne2fI3mLtepdFO2S5QLMHZ/2K4CyyR9k9Ke/IAVTWrShmcMI2RtGT0sjz+1WkNvn6nv3ju/Nbk6JIlQM5uo4w2FAAQevh8l7dOw97RQTPfRY2KSTRTRlXhHH41vK/8hVfpBtfKaBmrMOeKdA6IqsHe2VE5JoXuBPCfRQ+VbfEpnlUZ11TRYuZ5EWmYFCW6gqcQtJ3LsIrPZGIqlUTt3zLiGkZ0BWRTa/IxASCfi076KdZMMlxgY9uTiX7LGXI4YUqAVGT0fQW470W0+RB6/KtT6qrrhidD11MsRw/ppWoJkTHfRUZM04K24IaIvnIijYKmQW2cFdqWpzbOAjSCha6MOVeyEv7aHJz9L1VeEFHoiTQ1uo2VYrZLuVz9eV4DROpdKLCs6JgUuh47JqZN835Qp02B2NgC963TgQqpevVMqNOmJB/UiXlWKYYRA4AuoC2bD7he8Bwvmw/oNMvRqrvA5rNwnnux+kOQGXI4YWIujLIV3eZDNadCBkKLdpuhcKTKZWA8cCfs9kMh5/dOgGrIs4xqmoyYsvrK+wvnFmKhM2WKycdMyzUFACdmSCSF+2F/CWJVE+z2zmAb67qlNAYMMuZ5AYAIcfw6f8gpRWU2zqDlKwQGLbJMYQB/3tTxk8PfD7Nn+RsqFMh6VvsKsB7ZGX6OH9kJ4+v3JL/pKmPItKzBtQw5nDAxF0YuC3t7hTaq9k4621UZeF70ThhF8mJEtKm1H6JpUwPktBdJcj+s+k4jABg6rO9tD68MPPEMjIfuTj5miq4pihIMAmqysHdWGKjd3kmzgxynK6HSnagKxOrFsHcdDCaH65fTzZyKSg5JNEwxMams+Lt7/fbZERVo98SpIdv2xNvPZc2PDEvElJjPx0rceydL8F6SNWSaIYcTJubCMGPaqKisSGVg2dE7YRTtLzLa1AB/NkakXoDgx1PGEFkZ86YAQBfRc0Ao2lBkaEBk3EdA/OKZZKaXG1PVIjC40GJm/lG0AQJA2az+YGAZzocKqq/VAoBCKdpFs1BKvh1d1r0kY6CrjGOVNWSaIYcnqzIXhsQhsm6hCPeDj+CePuP/b4Ggjel8ZOyESWuTKEKsW+b/eJyH3160jKZlzHWiY1I488nQpQGAokBrXhB6rFrzApqFWF/BP78jWnrUxlkD17RAEDPmPuojemYHTAnCIFvoynhW+4rQmuaG30dNc+nO70AroHf6fXg9/UB/EV5vP7zT7/taOIpjNS2Itpbwe2ljC40Gz0P0+ZXVEl2aRPeS0OH85A2oTXNh/OE90B+4E8bX74HaNBfOT94ABMGmioxjHRgyHQbpkGmGHK4wMReGpJabqg+QBXzb1a2r4Z3tHfZnZWod9K2radpfZLU0ZXV4Z3vCZ2Oc7fGtmZNG0+D1FYfPxshm4CnwZzLVEpiHDPyIVa5qEf2IOQ6gqlBvvAbaedVKr6cPUFUajU1Wh/dxD9Q5jdDOawP0evr8OVdTCa5pJuY+ojJt8WJMCSjWuTIsqLMGrL/bXv05TPlsTFWA4F2oC3g9/eH3Uk8/lPqa5GPGabWoNI4yKqSy7iWzHD16wCRIDmUca9yQ6QLRkGmGHE6YmAsjl412hsol/8PpFoqwf7gvtL+b0sochg7oOtzXTgRfeM0LaNqLZLU0CR3O869UjEuiTRtIFJw9L4afX5Wg8F2Q9COmKEC5jODK3fP/XkOw4DQMOIcjrulmAttgw4i+j6isijN69EJ3/bLkYxp6tPMhxbOayUCdfSWUmZdCqa8ZctFUZl4KdfaVdLbXMiyoXS/U+RAYuJcoLOpVBdqSm0LntPnvJKKWPBm27ZlMdJsw1b2kaLB3VXn0QMaIOVaihDRqyPTXvph8TKYqcMLEXBDq1HqIdUthbz8QFP9ubIE6laDa09Mf3d/d009jZe44cDqOVNcWtK/on9/2zuAw13VL/da4i6cmH7dcjtFOEez6yTi/hg7rbyN+xKh2VTUNzouvQblsum8bPID3cS/cN97xr23SSLGKl3AfAb5d/M1zqmsXryjQlvvmL4Hke/l8mkWua0LcsQj2jgPB3fmNLYBLpMGTcV2tGFt8Cltxz4MypQ7qjbNHVIJ7/eooVUueqkRv5BAkaoNW5iNntQ39llNYmQNyRg9YFsS6ZbDbD4X8ri6juZdk6FaZqsBXjrkg3EKx8mDKnR001Z64Xf8iUVXAsuF+dBb6H26Bomp+y1guA89xYD3+DGARvNh1Debjz0D/0hoIx/Vb03IZeJoK87E9ML54R/IxgXg7eAq7eCvmh5Pi/CpK9I8Ylai7WI62oJ4sejhZc8QKpWg76C+3JR+zbEabwlA4Hyp6ZZfS7QfoXEpl3EtlC7hoCvStq8Pfv0RJsN1xBNrSz0M57/2Li6fAPngEonlB8jEBoK4GzrNd4RXSo69D3LUi8ZBuoQh7/0vQ7miCGHF+7f0v+VpEio1IKe8lE165XLlVmKKaVihBWzTPt4sPGyXBLXkTFk6YmAujrxA6lwgYqPZQDK6NK5dTuH0BgO3AuH8j7B0dgV0p4/6NQIHgxW7oML60Fvaug8GYX1pL1xKSywCGDq1pXqDV0ul6lUY7JSNJUxBdwaMil4G99wWoTXPP/WAPJhLPvQSxalHyMWVobGqy0XPaqMhlou2gqe7fqJgU968sl1IZ2sqaTPT7l8IUxrEhls8PjSnamumGuQIQq5fAffvdc39QAGVqPbTPX0cTsL8AsWw+7N2dgQW9WLvUN4WhSJik3EtZOPuCQ2SBwfZOgm6GnAH0F0I0pL2+eVSOXfImKpwwMRdG3K4Ixa6JLF1Pbb7yTKQdHTQzkVQV9o4KMXcdpJvDpAvo922Ac3BE737jLOj3baBpH5BhuyoE7PbO0J1ce28XXdLkONA+fx2crmOBREJrmktj+qCLaI0NxTXVo+aIddLdvxkjWltJoVGQsfCT5aIpZexAxL1E9f7VRKBFbVjMjS3JxwSAYhlebz/C3Em8nn4oikKQvCiwdx8KaoNPnoK9p9Ofr0WBjHtJxhBZw4Bz+NXKSdrdK5OPyVQFTpiYC0PGsDvVt2QGQvq7KYW4ZRPu6TPQli8Ir7qQaEAkzWFyPThHX4d2exPEquHtGU7XMYjmm5OPKcOxzrTgvvkO8OY74VWB2xcmHxMAPARNCQbvpZeP01SYVC1aY6MSnF8ZzwzgaxRWLYK9uzOQ8Iu1S2k0CjJmu8ioBA8g2lpg7wjRu7QRJREy3oVmjG6Kog0Q8KtligJl5gwog46huQzQUOdXKimqaZYN99R7lZ9VipZoYGj0QEU9UR+BTlfGEFlZ70KGHE6YmAtDVaN3rSmczcoWYFmhQlxYFk3rCwCUzGgrXYqXbLEcvSCi2kH2HIjbbq7cikLxgy3DsS5ungnFvBMA8LxoUwIKMbllRWtsKFyaZDwzAOAB9p7O8N3y3Z00dtAy7l9di6kEE9niaxrsnQfDK7PPPE9TjZClwat2zAGU2nxEQkowBLkc86xS/a7KGD0goxos613IkMMJE3NhiJhda4qqQKkM66nnIDa3DrPS9eDBeuo5GL+zNvmYAFCbC7W1JXVxkzH7CQC0CDH5jg4aMXnGiHaso1jQ57IxO/RE5xcxFaY7mpIPODBstKLGhmLxJ+OZAfz3USUnzZOnaBJSQ4f19+0Qm1uHLfzcnj5Y2/bB+Oqm5GNCgXPwKNyTI87vyVO+Po+qjapUhvvuGYgFNwTszJ2jx2k2GmQscmXNwVO1iPbDAzTthzU5OPskPKtGzAgLklZLLXqjVyNYt+SzcH7UVfn8UrV3MuRwwjSBcbt7fbvpYtlfUOezUKkGRNpO9K71H2xJPmZNFvrm1lD9h765lS6JcNzo9gyHYNdPxuwnQI6YXFOjHesoWpqE6u/Qh8xZ0e/bAAiCmANEVpgokGH6IOOZAeS03CgK9HtWw+k4Enwv3bOaxnHRdqJHLFBoMQCgbEWbeZQIqhEZI7rlkUKXJiMmIKf9UIauB5Djjlo8rxoc5lhH4bQr6/wy5HDCNEFxPzob2Jka3KVRpzUkH7Dkt4yFDU6EodPsNGYz0UMTqcSTMtozZMwmAuQca38pZuYUxY+YC+fwq+GVnsOvQlBpmIDoe3gtgdmELqIXfxSmDzJMYQA/+YuqHFIkh5rmV3vCrqmiTJ42NQCozVU2Q2jvpNkt9/yKWZhjqFi/PMwfYezYFsSG5XDf+aU/L23gPvK6e6FedTlgE7WpybiuMjYZgKE1RMVnlahaaT25F/rW1RCrFgcs6o2v0IwdGNPnzLiFE6YJiNvdW7mM//R+iLtXJl9pyhrVtw2WZYQgY4dexu4bIM3q1d5zuLJj3ZrFyccEoC24obqVHiDQwno+7lunaVrGFESbpVB4pchqaTJEdOXQIPiJcyKqPSdP0TgfyngnAXLMEEwT5t8+HdryaP6vp2haHl3AO9sN9/jJQCVCaaiH0kDUuSHjuZHhUgoAGSNa20NRxavNw/hyW/i4ji+3AbX55GPKehcy5HDCNBHpL0b/iPUXgaQTJhGhdWnvpNG6xFUaKCoRgJwdehmziQA5rSi2I8WxruqVHuACdhsprqviD+oNM0tRFJBkTLJamhS1crVHVSA2NCcfM86ghWKnPJOJOb9EizBZBgymBe/0+/AGzq838M8wLbJqmnM4qK8Z1MGRvR/S1H6oadHvYIpntWQGkqXBmPaugxCbW5O3ba/NQ509K3RupTp7Fk2SJhm3UPRncRbLfkJYm6cZfiwZTpgmIjIc1WRoXWTtqqZph951KtsGb2yhccmT0RIio9IDxC8+KO5h1/HbZj/49YgPFCj1NURWxVZ0myWFvTfgV2ajtD0UldlcJnqnPEvwrNpWtDMfVcuYjPdSPht9fim0q7LeD7YF0dZc2aWU4rrKelbtmC4Km+BZLZWjYxJsbqj5HPTNrbC27RuWNKmzZ0Hf3AplkiUS3tke2JWOtaFe3hcjgBOmiYiMHxRJPfSRQykpidyhJ0AX0btSFFUtAFA02M/9I7Q7miDUgTlM2Qw814H93IsQKwiqPZKsXiMh7CuP3M2lQNP9a7p4HhT13Gwt1Odh73uJ5pq6Huwf/WPlNksqjVjce4ei2qOpMTvlBBqmQhnWk3srO0vevzH5mICcwcCGHn1+KdzUZOl6+kowdxyA/qU1EI4LrzigsdFUmH/fDqOtBfiNhGP2l2A+9WNf1zPinW8+sgvGXUTaYBnnWNJ1VRrqIbasClRdJluy5BaKgWQJ8DerrG37ILasmlSVJk6YJiJxZgh3rkg+pozBiaoCsaoJdntnIDEU64haJIYxMjkiamcCfCOE9cvDdxrXL/fbDy8miGuacP/lTbj/8mb458t+O/mYuh6THBJUXeLuT4qqAODfw1HDGikU7LYFbd5n4f3q/wEDAnavbMLr7oM277Nk1Qgpg4Hj9BZULaVRgykpXLCyRrRVPFUblWNBrF0Ce0dH8B3c1gw4BPeSDO2qLF1PPgt9zRJ/YW0YfiXLdYFiyf87xeZnPgt93TI4z3YF3kn6umV07rMyzrGs6wq/0pR4u994o68Q+jsODFT4+wqT6hxwwjQRsWKEuBQl9VwW+pfb4H3w0bA/K1ProH+5jWaOja5XNrdo76TZaQRwLikauZj1Bv4fQdKUM2Dvfj58h37382RGCHLa4xxoy+YDbshMr2XzAY9gwWno0ZUeKtv2TKby4M8fddE4qimKv4CvZFFPUSUtmUBtHmJzK9T62iEXTbe7D/a2fXQVPEWJnrOiENjFm1Z0hZ/CCCH2OIk2chzA3t0R/g7e0UGj7ZHhMmYY0Zs4BtHC2tChTJ1S2RGQYr6hjAoeIEeHpyjRMamem7QgceCzDDhhmojIsPB1Xb/Pu9IizKWZSC7FJc92KmuyTBOwCZJDSUYIUnbgTDt6ptdDdxPEjNGAUCxyAb+H/mdvAz97O/y6riS4rooaY1FPIK7OZ6rvogkAQo0ZqE2wIMpn4Tz3YnVb8mKPk2iOmAxtT6zujyJ58aI3cUi8zP3/bKQpAYWZkqzfVdeO1mu5BBomoUa/9wnn76WClDkCcsI0ETFiZo9Q7JY7Dpx//GeoTXPPWb0O7CA7//jPNBoFWX3lxTKsp56D2Nw6bOaUBw/WU8/B+NJakphj+ny0yNiBK1vR7UUUznGFkt9THWJVbG3bB2PrmuRjAnKuq4wKtKxqsOXA2tkRqgGxHtsDY8uq5GPKaMmzYgaH//4Xko8JSNP+VV33Z1qwnngm/P3wxDM0VuaAHDMlWb81hTLMHz5XWa9FISWoycM5+kJohd85+jrEXQQxJVNVx7qUOQJywjQR0dTo2SMawa6J40KsuCV0B1msWwo4BBUmWf3HuQz0za1wuo4FjlXf3EqzayJrp8ZD9A4cxcaqjOuaz0ZfU6q+fRlOjzKszGXtWlsOjN9dF7prbfzuOqBAsPgrx7TkUZzfsMTl/L0Mspl0Mc8iRauapkS7uFF0UZXM6PcD4ebcmD4fDbJ+a/IZ6HcsgrMrqOfU71gE5JOPq+Zz0Dcsh7Vt3/BnlR3rEiFtjoCcME1E4ibNtxG03Gga7J0VetnbO2nafIyYeRGEfeVV7/GW4UYFAIaA8/Lx8B24l4/TmGtkYvQCJM5bRsw1bU0+JuAbXERdVwqDizgDC4qEVNaudW2ucmVrRwfNs1qTg7MvqiWPpuVR37oa3tneYX9WptZB37qabpGbjXkHU9xLQoe961Blx8X1y5KPWZuDs/+l6rZZAnKSFxEzZ1AQLQvj3sF3E7nzAVBvmA3t1rnnOd72kcWShSzHurQ4AgKcME1MbAfuqfeq2xIiY4aCFaM7oZoXYZrRLTcUbRKWFe0ISDgbQ7t5TuhuuT/fheC6mha0hX716nwRu9o4y/87hZ6oHDOPo0zV8uhBrF4Mu/3Q8PPbOMt3yVNoNCBVT0hluGgCcipbjhMd0yF4/+o6oOuVNaQUiTcgR/tXNuG+8y60y6af+9tAVcl9512aa2rHXFOK31RAjtlEfxHaonmAogTfv01z/cH3FEh4VislEQDgzp41uWyvJTrWpcIREJwwTUxkuDTJ2EEulKJnj3y5LfmYAFCyondzSwTn1/Ng736+cgWPatJ83HyXrxDMdymWYT3xjB9z4dzhMZ94hizmmD4fLbYLe8/zAXcz9+Qp2LsPQaxeknxMy4JYsxT27s7AgkisIUq+dRHdJkw1R0zSe2lMn48Gx62+kQcgR/tXMqN/3yja46S9H6xoswmKEQAZHSiXoTXPh7i96ZxGt2z6g56pBsLLOMdpsr1OmWOdDDhhSoCqiuwAIJeF86Ouyj+ebS0EMSW0DgzsWiszLx1mvqDMvNQ3tqData7N+rvIlXZzaykmzSN6941q0nxGj5nvQtEyFjNThkjDNKbPR4vnhVpBAwM/2BTX1QPsH3VBueLSQEJqP0s0RFZVK7cJqwrNOwmQ+l6qajVNhpEHIEf7J6M9Tpaux/Wqb+Zh6IAQcA4cCf99oxqxEPffpYibpiQiZY51MuCEaYx4Z3vgvvkLKPW1/suuvwjvnV9BufZKEpEdADntcTL0RBkDxoN3wd51MGhV/OBdNDMqAMBDzG4uwQ+2JDcq6DH97BSVAaHF9NATXFdNjY5JYZQCSJpz5cVYmd+afMyyGZ0YEpoSRM92oXkvRVbTKGLKMPIA5Og5HTem5ZHAYEgX0XOuqCqkZTPGMZTguXE9OdVKGe/gNCURKXOskwEnTGPALRThfdzrV0A8wCv5NploqIP7cS8UQ6epNMnYNXEsiPXLKw/Yo5j4DsB+5vBw8e/ATq79zGEa8S8AWDEJqUWQkMZVVahMHxTF31VEiEaBashpoQRt8TyoN86GUl83dF297l4oDXU0LU19xWgtRl8RmF7p/3gMyHDJk5GkFcvRVReqnVzTgli/FO7P3wvcS+qnL6NpT3acaNMdiveSDCMPQI6esxRzr8R9PhpsJ3rOFZWGScbMKVnVShnv4BQlEWlzrJMBJ0xjoVCCUpuHveNAyCC2Fn/hR3GTyrBldjyYf/tUaC+7+b+eoplTYVrRhgRUw0bjdmspdnN1Ef1ip9rhdBwodTmoN86Gdl5LiNfTC6UuRyNgzxhAoQT3+Am4J897bgZFxxSLhKwB67HdlbUYVHNWDD1655qiDUVGkpbPRutOqFoeSya8Uhnu8ZMBvZbSUA8lLtEYDZZduZp28hTNhoqhx5gDELVRybBQl5FEeBJa4wao+swpGb9vQPg7eGCWI9U7OG1JRJoc62TACdNYUBTY2ytZ2h6gG9YoZdioCfQVYD+6q/LnBES2g1AZIchISFU1WvyrErWMeYC9twvKZdP9HfrBP3/cC/uZLog7mpKPaehwXng1eF1PngI8j8i2PQN96xp4H3wEDwpg2/BMC+jpg751DZAhas0QInrnmsLCVxcxVuYEMWW0bgG+xffBo8P1WoMVkBf/BWINgalG3IKSYiNHUaAtXxDuLLmcqBIMAPksnOeiLNRp7LbV6xuhfv46qPW1wxbW7k/eIIknpTUO8K9rVNWF4rrKmm9Yk4N+z2o4HUeCerh7VgM1NIv6tCURaXGskwEnTGNB1rBGGcNGJe36STFCkKGxKZtydjg9D+6b7wBvvhO+UKAwCJDy3Hj+sVYy8iB5aABYVvR1/fo9ycdUFN/KfNfBoEX9+uVkGypS3oWOE12FpqiQymifNU1Y398R7iz5/R0wvkb0fpBht60pEHc0wd7RERyS3tYMuERV77F8Plp0CXPwRIxei2oOky6ijWG2rKKJC04imGTghGksyOrbNwScf34T2h1NEKrma6eyGXiuA+fwqxArCETdQPSuNQUytBiAr7GJSkgpNDbFcvQOJ9W9VDKj72GKha4UDZ5TfSMPIPxeUWI+Hyu2C3tPZwWL+kO+tXjSyHKj8rzoyhZFhUlGhb8YUwEpEr0LZVxXoVd/GDEktMYBQF8BYtUi2Ls7g3Pa1i71dT0XT002puL51W1UqlYSbR71FaKNYSaTxTczKeGEaSzI6tvPZyFab62snaKIqyr+i33kAM6rZ/oDOCl26GW1Dhg6rL99uvJsIopqjyw3n6wRfQ9TDTkdy+ejQYaRB+A7qm1dA+eFVwMLIr8VkKIy60ZrbDwClzGJblSRpgRERG6oUCDrXSjjusqoVspojQOAjAHv4x6ocxr9od1DGtI+eB/3+CY4SeO4vm41ELMXSl2WxoUQSJfFNzMp4YRpLMjq2y+agWRpMK6vnWpNfqdG12FvrxBzTyfNnBUZrXGAb1U8c0bobi6lVXHV7ZGB+Ht4I8F1lXGsZSumkkYkdBaar9cKGVwLBX6LXNLIsKiXdf/KGOINRLdRUej+Mka06QPZ+0HCOAkZC2tNjb6maxYnHxPw378v/stwDakCeB/3wH3jbRrHRV2H/cxhqJ+/7tx8w4wBDx7sH78EsXpx8jEBeW2PDJMQnDCNBVl9++VyTFyCHxTThHvqveray7ouxLplsHd3BloHxNqlgEu0E2Za0buNJFbFFkRbS3jVcGMLmW07LCt6h57CYta0oC2+CeqN15ybX6YLeN19/o4qxfnNZ3zBcVdIpeee1UCeqAJiO9HPDYUGRIbGxvOixw5Q6Q3zuRhTApqZMpG6KQpcB2LtMti7DwXcvsTaZTS6HgDoL0K0NcPe0RHSzdAM9BeBixuSjSljMLDrQqxtgmd5w0aEqFNnQ7npGrqqi2lBu/VGeGd7h/1ZmVoH9coZNO9C24K4ownu2+8GDHDEHU2ATbd5JGUDlGESghOmsSCrxCwjbilmJ7dE8JLVNMDzoM6ZHWhXgKoACpFzXKEE68m9lVvyvtyWfEzHg73vBahNcwO21/beFyBab0k+JhB/XSkqLyUTytT6QOVlKBEm0UUIv5J2csTCerDSQzWssWTGPDc07UVV19iYFsy/fbq6YwcAwIlptXQIWi09L7oaQWGUAgCqCvWGRmi3Dm+j8h00iRb0OQP27udDj9Xe/TxN5UXGYGBNBaDC2VOhzV0jOr8KAF2vbEZD0QnYX4ZnWv9/e+ceJUV55v9vVVdVzzQzA4hgUJExJoxGEklAV6JyHy5B7ihLdpFE/Wmi+SXG3STHs3vi7tmTk816ctyc3bgxmg2a3Y2IgHiJKDAIESGJrCAYfqAuxE3EmIsCMz3TXZf390fNDMx0dVWk6+mXmfl+zvHk0NWZp6v7rar3uX2fUin+pkYYQwfDkJKo7yjGO99SPcmEpAQdpkrQVbevw+6gGvgbqywva5qRzb9A501WquSxNhvfYC3x/SogOHgYxjnDoDqjqqroQv3qKIKDh4FZn0zfJhDKMsf+rgKORH0uurzz0JFQlECiDLDoxjccS8300nHdGAk9NhKbsPZC/NgBseBRwiZLQgzBNGDNmwRvfUtEP6fQqAMzo+de6PnVV9EE4tXUJMq/jUz8iJDrhL5f06y+GE1dLfy1O0ptHjwCBEpOAKc2C2/dlvLOt9QgekJSgg5TJVhWQopZ6OvV0S+gQ15WV8mjph4bHb0Y8BIi9J5AhL6YMGle4lx1KS7quG5MDf0YGkVLKjp+OlgWvPUt0Ru/J7fLOE267oU6+uGKxYTghpDNuNJkCZuAHjEaP0jIygpl0wrFeOe7IJSZJSQl6DBVgu/DWjQN3vqWkkiutWiazAwQACi68XYlNpw6JNR1ybbr6GHSkekB9JR36vhdswllJknHTxcd329rOzJXfzxSmS8zeUIoVTwiZZuOHS9KIFXmYxjx4w6kZk7Fbfw+JTDWQVf5d9J1IfG76ghu6CidBZJLniVKonU9V6mSVxWCfHvJkF6Tcu2pQIepEiwL3lNl+k6e2QHr2skydtsLKK56PLpf4L7VcD6zMH2bOiTUczXxksxSsu3thfgepluvS9+mjkwPoCczoGMt2QnZYFvoVqjl+83CGJSNlg0+q15mRq/nI9P8SZgfayoV8jhnmEwmDQBMxJfHSZQf6tjk6hBCAMLrJs4hlbhudKip1dXC3/KznlnDru9XUiVPR4a0Ngt75fxIoQl75fz+1UowwFDvHYe3emOJMIy9bDaMIQ36Plg/gQ5TJQyqQWbyBKjf/qGX2kxbGMkdJLShr83G9wtI3HgcJ0FCfbaATTteklmilh1I7mGqEfh+tUWQswnlhxJrSYMcv2GETdSIyBo2TxSds1L18k7bgffoxph+F4Fr1VAwcjXw9x6MFvKQGoaZscqPO1jfItMPp2Pjl80mCCEIbTZVAGv+FHjrNpc6pItnyMz00iFaEgTxyodSiqyGAXNMY2QJojmmUeZcHTteaEIqGzyoNv53HcQsSCUE+fYSZwkIy1jd1RthrZjHTFOFCMmMDRyM+kEI9h6E+4O1cB/aAPfBtQj2HoRRP0jOaMYsO33c/PDoTsWflCkm1NCL1JVratTPZMIyogjMpsZQvS9tdEXfgiKspTNL1lO3nHkg9LtWu4fJ8wHXhTmuCfZNS2CvXAD7piUwxzWF0ulSGRDPQ2bS+MjvNzNpvEzmUMfYASMDb/2WyOCGt34LYAhJBuvo7dFx/w38skII/pZdcrLiXb9rpEMq97vGXjMSKJQN4vjbd8tkZTvJTBofOkenYI5plDtX3y8rNOFv2inWSmAOrod1/azoZ831s2AOFhjSO5BozUeWRAOd+6XWfFU/Tn+EGaZKaC9ED5A9dKRzgOys9AfIAmGPQlyPjUSPgq5el2rbBIC2PDKTJoTKdb2i5ZlJE8LZI2ljJZS+SAmInCig+PRzsJfPhVUsQrWH80eU46D446fhzJ0MDE/Zpqa15D70BDKTJpwcEAlAvXsC3oatMmWWAJAvhNG9iPJZd/VGOJ9dlL7N9gJQl4O1bDbMhrrQZo2D4FgrvNUbZb5fz0Pwh/dgf3kFDDPTPcdG+T7ch56QKylNcogkyuN03H91BY98v7zdQ0dkNtc6hsgqFe94S80Ry5jwd+yBccFI2KeUzwa/egv+jj0y56pDaKITc9gQWJ/+VPgM7eqxGVRLZykN2CMmDh2mStClXFTjwP3+mvI9Nl/8i/Rt6mia19WoX+PA/WFnj9jcST03uT/+CZzPC8yUMRSshdPgPfZcaenL0pmQm7OShXPdzBJJXfPDo+FcN1Mmsqrjd61x4ssspabM1ziwl82Gv303vF7fr71stkyPwqAaOLctg7e+pcSmc9uy9O0BQNGDc+t1kTNWnFuvA9o6ZOwmlcdKfL867r9Jjp+Uw6QluFGEtXAqvMc2RdwLm4G8xJxBDWqAQFjyuHAqgtffPPmaEfYTZS6/VCZzqKMH7xTMwfUAHaT0YY+YOHSYKkFb34kD88LzIjd/ZlOjUF+EhqZ5XY36jgP7hvnwN+0s3eTeMB9wBL5fwyzfi/HYczK9GADg2JHzXbp7QCT6iXT8rjp6iQA9/Vq2ht+0Plfe5mOb5OYEOU6COp/A7+o4MEefG33//fBoGZtJjp/U+tUy868W3vqYeT2LBOb1JJ2HRN8qAFg21LHW6CGy55wNY3Bd+ja5se6f1OXi74V1uap/pP4GHaZK6JRsLFv6ItZ3EoTzIj42Jiwv6lakOgFjxDCZBtVMJr5pXqKvxzTjbZpCLXhKxQ9OlJD41tHXA4RZ0rj5IyI9IBlYi2fAW7e5VBZ/8QyZteS6sBZPR/A/vylRcTM/eF7YxySBjiz0QLEJAL4Ha+H0kv6pUGxiOhBIlBcpWEtnhqqDjtN931eFYme5p0BaVocQAtDdr1XWrlS/bLWH5eo4TwAIAvjPvVja+3fwCKCEBtfmauI31lLqs0QUM1cLe9lsuOVU8ij4UDF0mCqhtgbO7cvhrdtcWvpy+3I5tRnXDzcoew8iOHSK3a5GUVfghtdRhDG4Hua4prCP51Sp4iH1MnMqTuRh1NdG26yvBU7kgbOHpm9XR7+ArmxlRzFeYlbidw0CeE9ui44gP7UN1vwp6dss+kBttvOaOdL9stnUCPNDF/Sv2SMDxSYA+AFUazsy86fAUjjZOwWEkuZ1ApsEhc6N7s5oh18okJOZMgHmuKbSINkQwfKmtoR+LYlSS12zy6rdlwaE/URxPWIC/UTm4HpYS5rhrd1UsrG2ljSzn6gPYwxpgLViXskcJjpL6UCHqRJMoyRKDnSWoazbHDY3SmAglNuOEJuACnthUidrw3vmBWSmTDjZ1F2TBRpy8J55AdYcgWGNWRvFB9bBXjm/RyM5GnIoPrAOzo0CDfOAnsGJuuas1NcCQVBeYrZe4EZbdBH88nXgl69HR5BnX5W+zUE1YcljRCTXW7dJVqK+kuO0GY9thY3zT2wtDR41T5Qp7zQQf9+XKp+17egg2YwrZewBgGOf7OeMEi2REEvRcS/U0ZcGaHnWBPl2eBu2whg1EvbVPYUmvA1bYS2fQ/npPoyZq5URGyN0mCqirT2+DKWtXaa5UYeij+cjePkAgpcPRB/vLJ1LFceB/edz4D+1vWQzb//5HJleAUDPMEHbip+zItWvpVBWYhYQKgnR0XRcKMZnDaVKxpyE3imJNayjX0tXj5hphuv3UETwSGpWm47y2UwmLBOOOk8gzGxJ4NgJ/ZwCVRR2JuFeKFCya1nxfWlSKqU6BHBa8whefR14tUzAqjXPDTchEdBhqgRdZSiJUroCm7+OQnzUr0PgXF0P/q5XkLl2EqxeUsX+9t2wpglFVq0EUQKJh6dXfs4KDAPWgqnp2wT0SMzqcEiT1qdE1hAAWvOwlkyDOtFe2u9SXwu05YGzh6RrM/BhLZ0BdbwtosdmkIzylu/BWjqzZMxCt8qjLycrXnVHWMd9X4e8NwDAiO/nXCzQz+kF1b8X5hNK8vICoyQAPQI4lJ8m5LSgw1QJuspQkqK1EtHcmk7luO0v9Yz6jWkMI40Sm1xTwZr1yUipYmtps9ywRt+P7xeQ2JwoFb8hkpoDoiPbY1swL/0QjJHDS2dOHf2dkEpewrUoJituA4EBf9OuCFGCaTIRZC8ADCO6x2bRdJm15CuoE8eQWTIDluefnOdlZaDePSY3yFvH5k/HfT/R4Rfa5LoJ/ZwSYilKITjym/JCNBLr17Hhfu/R6pfkGQhLRw2jdObfjImAhJYHVfIIOS3oMFWCjkwEoEcxyeqURy5X+rJEoPQlY5fMBwJOkSq+TkiquFAMh9aWE9UQyeBp6JsC9Dw8TRPWtZPhrdtcOmdFqmm+JqFkTMLhBwDLDrMuvXunDh2Bt6FF6LrJhA3dkbLiW2RUHg2E5XFrS5UPww1h+iYBJCt6SSh+1WQT1pJEj40m2Wsd1QwFF/aKefC37y4tyVsxTyaIYxjxJXlSKoRmBsbgQcg0X9lj5p8qFmE05ABToPxQV/ksIX0cIa3MAYKhYC2eEd5kTqF742cIZQUAZCaNj7TbVVaQOsWE0peiwIOzmCBVLGETAHI1oahGhHPob3tJaBOmoUwNAKxMKCUbgdnUCFgCD2zfj22aF8ngFd34a0ZKtl3HdeMllFl6AuVxXb1EEb+pv2mn3AgAHevXLcJaND36vr9oOuBKSPGbJfZOtSsme62jmmFQTdnZZf723cAgGdnrqj9TASAIoI61wX9uJ4r3Pgz3vkdQvPdh+M/thDrWJjMipFhMuBcKPVcJ6eNozTBt374d99xzD3bv3o2jR49i/fr1WLhwoc6P9P5wfRS/92ikglDxuz+G87nrZewqBf/FvZGyzP6Le2FJzKnQ0QOiq9ba8xM2nAIbeiuTkK0U2PgBAFRY+qEQXRIiMVNGR99UvgPu6o3l1b5WLkjfJjBwrhsdvykAQCEz/UogUKWZrelXQmT9thVQ/K+nYa+cf7K3siYLFfgoPrgWzqfnpm+ztR2ZyROiS7ckZa+B+PuSBDruv44D/+f7YU4af/L+0DlT0f/5fljzhXpIlaq+6E6+APdHT5YvP/z8svRtEtIP0OowtbW14bLLLsONN96IxYsX6/wop0dHEWjNw/vBuujjUspbhoHMJy+LLFnITBovUz6QGGkU6MXQJbXdUYwfSCyxydU1B8QLgEAhs3h6Se8JjrWFx9NGR99Urgb2pz/Vsz/KAIwaJ3xdaljjQLluCm78NSPxmwKA68N9+IloR/jhJ2SCVjUO7KXNYVbSMcKeGhUARTd8XSIbXJsFCgWYl41B5prxPWbSwYDcvdAw4u9LEs8aHQ5/4MGacxW89S0laoDWomlCA5ChJ9BQmwWKbmT5YfdxQkgJWh2mOXPmYM6cOTo/QmUk3Vik6sodOz7DtHh6+jZtO0HNR2Djl83Gy8smNfKfLoOycG5bFvnwdG5bJtOPoWsOSMaAMaS+vLqZEojm6uibcmwYQweXlAJ2l89KZfBsG+YlF8E4b0SpwMVv3hG6bpyE60aijErDNQOEg5eXzYa/fXep7PWy2TLBjaxT/bXk2PCfL5291233eqF+Th3PGh33B1/BW99Spu+vJSy1lEBH8KguB7OpscfQ2i7MpkagLpe+TUL6AX1K9KFQKKBQOBldOn78uMZPg+668rJOhFRdeRDAWjgN3tpNJYp11pJmmbpnQ4XN24iINDZPlOnXUipe0laiYR4IG/UfLSM2sb5FZnOSdeKbjqUacTNW+XN97DmZc9UhpauUnmGjBmDNnwJv/ZbSa3XRdBlHIkiQZZYo89FxzQBAXS38Z3dUt6RJx1rS1c/purDmTYK3vqVUoGXRNBmVPB2iBEEQ//1KPFMBbYp18WWshJAo+pTD9M1vfhN///d/r/tjnERXGVW+AORqYF7W1Ks8o/Xk8bRpK8AYXAdz3MXInBJpVMdbYQyuA9o6gOEp29TRMA+Es13iHp4SpZadogTdNjoRFyUYKOeqY9goAHgBvA0t0Sp5j2+BNX9a+jaLMVLQh47InKuOdQQAfsJG15domtewlnSpaLZ1oPjjn/Ts1+qchVd8cB2c5Z8SMRs700sCHWqAQPgcj8v2SJQKt+bhPrg2uprhwbVw7ryBg2sJiaBPOUx33XUX7rzzzu5/Hz9+HKNGjdL3gWocuKse71k/31m3767eKCf6UFcbGc0FBMsz6mo7o2y9M0kqrOGvE7jB6hJ90GG3PaER95br0rfZabei46dDRzH+XG8VOFddG07EzNc6eAQiogSJm79+tKHPd1R2/HTQcc3oUKsDwt6/RdPhP7W9xHmxF00X6/1TrXlkFkyFpXBSVMMIXzcaBGZ66fp+bStedEdqcG1cDxMH1xISSZ9ymLLZLLJSfSunQ7ZzmOumnaX18zfMl7vJFooIfvVW+cF+QtEwb21pGQrQ6aRJlKHoGrCnw25Uo7iRcDwNdJ1r3ANbaPByRcdPFx2b68SZPf3o+9WxfnXYNAyYH/kQjHMjhj2/9Tu5OUGOXVbiG4BMcK5QhHv/oz1ES1RH+Mzzt78k08+pY7YhEGZ7HngsDB6dUi0S/OotuA88JpPt4eBaQk6LPuUwnXG4XnyPzQKBchsgbHReOR/qvRM9XjaG1sNeOV8mmqujDEXXYOBEiW8Bu6YR36hvCj2wNX3HVZcq1rUhSlLBk1DJs6z4Mh+J31TX96tDjt9J6LFxBJxDy4Q1L27Yc/omAegptYwKIhgJxytFqfgyYSU0U1FHtoeiD4ScFloH17a2tmLPnj3Ys2cPAODw4cPYs2cP3nzzTZ0f608nCOLLbaQaRetrAdtGsOcg3B+shfvQBrgPrkWw52CoulUvUB6no+Qm8GEtmlZmQOQ0IBBQcAMAFcBaOhPmmMaedsc0hpk0CeU4yy7rfPtbdgGWwMYa0PMdd0oVlx2cKLG5NhIGU0qpuHUKXEQhJnAR+LAWTItevwvkrhtdgz/j16/APdh34236AsEjhfhhz1Iz0tsLoUT9jImwb1oCe+UC2DcvCcvFHFtmQ5+rgf2ZhTCGNvR42RjaAPszC2XKAK3MSTXArvO8aQmM0efCf3GvnIqmhmyPmauFvWx2ycBns6kxfJ39S4REojXD9NJLL2Hq1JMD4br6k1auXIlVq1Zp+lTvA12NospIGHbXnL5NHWl8MwPv6e09hwl2zljxntkBa+6k9G0CgGVDvXciYuZJK9SxVhhD6tO3qUvgQgHe5l3IXDupZAint2kXrBkCqkk6pIotK97mIqFscBDEq0tKbOhtG97GF5CZew2seVN6/qZbdsGafXX6Ng0D/q5Xor/fXa/IXau2De+pbdH3iGdfhHXt5PRtBoD31PbIc/We3A7rWoFz1TUYOFcDe8W8yJl/9op5Ms6LYwNWBsGe/xd9zTgCwSPbRmbq5ZEZ/kzzRBn5f0BbtscY0gBrxTygNR86vbVZoC4Hg84SIWXR6jBNmTIFSirVXQ10NYrqeHjqkFD3fWSuGBs5YyUzaTzgC2WYfB/+cy+W79eSkCrWJXABwGq+smQGSXe0XOLyLCZIFQup5MUOe5ZSyQMA14U5rqmXuuSJTklmgQ2KAqwZE8vPCZL4TW0LmckTYjacQo8apZC56uORfaSZ5okypVRKITjwBnDgjegyqrnXpG9Tx7weALCt+B4mid5VP6h+QNBzO1VgS69TY3Ad4MndH3RJfJu5WqrhEfI+YA9ThVS9FwNIzjZIZCNa25GZMgHmuCYYDfXdTcfq2Ikw4yIhoZ6kHCehpgbom75eyfHTxdEwP6e9gGJvdcnOrEDxvtVwPrswfZtJynxSKoSWBf+FPTDOGxFeN52od08g2P+GTGYr8OPnBEk4/IUi3Eee6Sk/3ZnVch96As6Ni9K3CQBFF+7DT0QrlT78hIxSaaEI1OVgLZsNs6Guh01v9UaZygJd9wcdPUxuQr+sxOwnX8F75qcwrxgLo2FQ9z1JQcF7ajusOQJZWYAS34T0IegwVYJhxDsRYo3kGjJbtVmgo4Bg70EEh06JhI1pDCP0ImpUCWpqUspbOqK5ugQudAzErHGA1jy8H6yLPi6lkqdjLRW9hMyWgPOtw+EvuHBuXhyZqXRuXgy0C5WUdhRhL5sdmYW2l82W6a2szcK5bRm89S0lNp3blqVvDwAyGZhjGiPLds0xjUBGqMdGx71Qhyw+VHw1g1STGCW+Cekz0GGqBNsCHAfB3kOlMxQky1C0KEPZ8Le9VBq1PnQEUEomE5GxYH50DMwrxpZEcoOf7wcyQt+vDonktoQhyPn29G0CesQ8DAPmJRfBOG9EqUTyb94REn3QJMtc0JAl1bHJrc/BW9/Ss6+n8/v1ntwu1yNWVwv/2R0x5VsC2TTLhrcmJit7ncC9sDWPzOQJoZ3ez5rJE8JelBFnpW9Xi2x7Ql+UhE2F+NLDhULrV1dZPyHkfUOHqRJcP6y17hX1Cw4dAQzAmi90k/WD+M21xHR7HbOflA/r2kkIXn8TCkY4j6PoAsdbw8ZqKZW8bIJssMRDLGvD/eH6yDI10SHIWSe+vEjogR3bwyQRzDUA69pJ8NZvibA5HWIR5KymmVOO3WOOTY9rVcLhdxMyaVKiBH4Qn02TuBfqyMrWZoFCIUKI5gQAJVeSpyOzZSXYlAgIKhX/m0r1WluZ+OCRlDofIeR9Q4epElSCrLgSkhXX0dtTcOPVkiSi1mYG6lgrgj0HSxxDY/hZYTOuBEU3jNoaRmk0V0ogwDRgr1wA9c4fSpxDe+UCuTlMpgHn9uXw1m0uLS+6fbnMGrYteGuei4nQCzSSZzKRg5eD134Fb0NLKIYgRNX7HHXM9FIqPkK/YGrU/6ty8h3xx9sTjp8OOgRaHBv+86UZfqDT6ZfI8AOh8M6MK0scCvPDo8PXJYR3ToTZNPOyJhgNdaeUuncqlJ7IA8NTzqbpUrxtL8QHj1iSR8gZAx2mStBRzgQk92NIRK0H1cDf+EJ1S1+USlBLEtrkthcAA9HRXAMyD7GkSK1Uj0JcedG6zTLlRa4Xn62UyEZ4XnxwwxPKgHTOnALKZIMlSgHNTPmB2oYh5hzGRuilSJK1TirvOh10lKnpGBwOAErFixJ88S/St9ndL/v/qtcvq6s0rjZb/eARIeS0oMNUCdmE2QxJx08Xx06YNC9g1/PjH9ieQKRR1+yRMn0RgKCsOBBGcSOyaV1zfETQUV7UUUzIVgrYTBIdkApuODb8n+/vOSeos+TR//l+WPOnpG/Tj3EODx0BfIHrJun7k4rQ6ygZ03H/1TV2oKMYH5yT+F119MtCk+KtjucqIeS0oMNUCXaCspmU6ENrO6ylzfAe21Q6Z2VpcyjxffbQdG3qyKYV3PheDKnZIzoeYjqzaZUcPx0G1cB//hflnQiJOTZJfTtSEeS2DljXToa3dhO8XuWd1pJmoK0DGJayzSTnUEKxLik4JOFEAECQUDIm0efoe7AWzyg/50rCIdUhRPOn/F2J60ZHNk1HJhgAOhLur0nHCSFVgw5TJRjojv5HZgWE7rHIZeE9vjV60vzjW2EtmJK+TR1lKLlswpR5oUZnHc6hrmyajt81CGDNuSpSltlaNA0IBPqmjIQIstSGqMaBt2ErjAtGwu4q7+xSj9uwVSbDpGNzrSt4FGgoGQMAI0Bm5sQeAi2qWASMQEY/RIcyKqBHAEdHECdXA/+p7ZHPVP/FvbCuFyqNSwokSAUaCCHvGzpMleAHgGnCHHdxr+ngrYBpyig0ddqNnTR/7aT0bepQLrLt+EZyqUZnHRtOHVLQAOA48SpNjsC5mhl4T2+PzDB5z+yANVdg/SIhgiyF7yMz8WPl1eMkmuYNo/rOoa7gUVTwwkg4XilW9LBnQFCAId8RP/MvSfzidCkU468biZI8DaXu5uB6WIunw3v02VLxhetnwRxcH/P/rsSwGX+tmqaMXULI+4YOUyUYgFGfg/rt73sdUDDqc3Ky1zoicG0dsBZOg/d4S4lynLVwWlhaNDxlmzqmzANhtLypMRQD6IXZ1CgTLddVcuO58SpNnoCjFvgJGSaB68a24e96JTqCvOsVWAuERgBAw3wXAwnlRembRGsH4LowxzX1Ch6dAFxX5v4AALUJWWiJDKmO+1LWAfId5QeHS5WUdhThrt7Yc9xBZ3DDXb0RzmcWpm9TU7bSHDYE1qc/BbS1h8/Q2iwwqFbOWQKATEIgJyMVaSCEvF/oMFVCJlphDOjc/EkojAFhhC12do5AGj+Xhbfh+Z6lRV1lgE9ukykD1NXo7PmwFkyDt6Glh9NkNjWGG2uJHibDiM/gSZWMKYROcDmVJokNvWmGa6nckFOJteS5sOZNLp3D1NQIa9EMGccQ0DPfxbLgv7i3fHmRxBBZx4Z7/6PITJoQZkA6Ue+egLdhK5z/K1Qa52jIQuu4L2VM+Dv2wLjgXNjX9Lxm/B17ZK4ZICyLXjYb/vbdJcENe9lsmbJow0jIVso5EebgekDSQerNoBz8XdvKB3KWz6neZyGExEKHqRJ0KIwBgGPFz86RyOJ7fnwZoESjftLDWKqHycoASsH82Bhkru4lK24agCFTJtEdaYya/SSFjg29H8QPOZUoZTUQOqVRv6mB6paMnYpENqLoxn+/Ek3zWRvm6HMj1dTCXhehXoyOhHuwREmejr4/HdcMEDrfcQ6phOy178Ooz0VmK436nEwZqybMXC3sJTPgrt5YEsixl82GkavV+OkIIadCh6kSdGVAzAy8x2Jm50hEVXUM9ssklGZkhJavaVa/RyGT6Ywgl2bwwgiy0OBPHb+rjiGnurLBtRpKLTuK8YOtbxEYbO168aVFUqIlSUEpiaCVkyCEINH3Bw2lnQBQSFCsk+itNAyotg4YI86C4TjdohqoscPXBwnM1tKIMaQB1op5QGv+ZClgXY7OEiFnGHSYKkFHpBHQU0PvOMBZg2GvnA/DzEB1FGDUZqF8H+5DT8hsEtra4zdhbe3p2wT0fL+BH5aMPd6rl6irR0yqH07TwMaqDzktFhEc/R2smxZHl7FKZYNhxPfDSaS2ahMGWyc5cadDe6H6ThqgZ/225WEtmgZvfUvJfclaNA1oywNnD0nXpo5MMJB8r5O4bjIZ+M+9WLY82VranL5NzZi5WoAOEiFnNHSYKkGX1Gt7IX4+kURmK+vAufV6eGs3lZSMObdeL1NX7lhw74/ZhP3fT6dvE9CWOVRt7TAvG4PMNT1LxlRbu1xUVUe0XEeZWsGFc9uySKEJ57ZlMrOJAMAErMXNkdeNtaRZZmaPlSBaYgmJlsQ5aVKiJdAwcNS2ULxvdU8hhKyD4HgrivethvO569O3qWPUAaBnDpPnxw9e5jBXQogG6DBVggpgLZpeXjlOCdWV52pg3zAf/vaXSrIR9g3zgZzA5tpAOCi314MsOHQE3rpNsJYK1LJnnYS+CKFNmI7MoWnCb/k5jPNGnGyaN8Km+WD/G3JN3a6bUEolUHKjYxNWn4O35rny4hYSvRhAKEG9bku0WMr6FliLp6dv0/eRmX4loCL64aZPlOkBsayEsQNCjxrDiJfblgjkmCbMkcPh/WBd6SEpKeikrKBE1hDQI1Gvo0yYEEISoMNUCWYG6kQ+IivQCpXvCBtUJehShjrUa/N36AhgQMZ5KRbLR/0OHpEpzfAS+iI8ob4Ix07Iugg0sHt+fFO3VFQ13xFfSvV/lqZv00roTZPYXBcTejEkhBCAsLwzTiylICCWohBKfEdkK+EWASUQUMmfUj4bJVqSFyqftS3AtqPltmdcKSNBrUMKOlcbf80IlnNVfX6ZrlJ3jQT59pIeJpMleoScUdBhqpCytdZNjbAWz5AxWnQTnBeBzZ+OkpC2jvgZICsXpG8TAFrz8ZnD1nbg7KHp2jQMPU3dtdmEfheBzUngw1raHGYse/eALG2WyYDoEmjRZNd/YU/5bKXEYOusDfd7oax470ya+/ATcL4kJCvu+fA37yofPJKYr6VBCtocXA/rupklWf6unh7JWUGxEvUSa6kuF19SWicUiNSEeu84vNUbS0ZY2MtmwxjSoO+DEUJ6QIepElwv3nGRUobSsQnT0Vydq0mYASLV12NDvXs8OnP47nEYg+vSt6kUgl+9hcyMidF9aVJN3TqyPZYF78ltMCeNL+kB8Z7aDmve5PRt6opaa7Ibm60UMZiJL5/NCPVzBkH8PThIvyzazNWGQ7wffbZ02PP1s0QyA8GxE1DHWqN7HI+1IrAtGafJSFhLEhWPuVrYy2bDLedE9KPMS5BvL3GWgHDtuqs3wloxj5kmQs4Q6DBVgq6oddJME6GZJ1VvrtYxlBIAHAf+Cy9HROiPI9j/OqxFAn0nRRf2inmRGxN7xTy5kjEdSoSui2DfIQT7DkUfn/3J9G1mE8QtpPrhdJR3QoMEdVtHwjrqSN8moCXzHeTb4T3Vy+HvUlx8ahus62amv8ktFMNqhnKy+EuEqhmy2fgMk5Bi3YCR2m7NR2bSgE6HvzVP9TxCzhDoMFWCrqi1bcG85CIY540oyUao37wjU7dvJNTtSzT/6hoM7CUM/vQEnJdcDfxnXii/yZXaEOlQIkxSpJMo7yy68VLQUg6p7yWUHwpkoXVIUNc4cO9/tPw6+tJfpm8T0BM8assjM+HSyMx36BwKbHJdL/43lapm8H1Y86fAW7e5NJu2eIboENkBIbWtK+hKCHnf0GGqBF1RawPxDzEB3wWZTHykUWLYaEcRqMvBWjY7enaOlJSu0hCh9/z4DZGU6INtxZdSSTjfOlTy2gsornq8vBT0ZxambxMIVfJ+8lNkrp0Eq2t+WU0WKvDhbdwB61MCog86ZNttC+ZFF/R8rfM+ZF50gcw6AvTcg/2EwcsSGeikAbESA2Q7/27x/kejr5vv/jgcKUFOnwEocEFIX4UOUyUUEySZpaLWXgBvw9YyEslbZJyXrsGq67eUOmmLpssMVq3Nxs/OkUJHhF7XnBXTRKZ5IoCINdw8UUYiWYdUcW0WaM1HSkF3H5fAdWE1TywvICIh256UVZEoA8x3RA9ebmoMhRfyQiV5boKSpkTmJQji7w8CfVM6h6THXjdiA58HCANM4IKQvgwdpkpoL8SruElFrZWKH+wnsaFXgLfxhehG/WdegDX7qvRtWja8Nc/GzM4R6mHSEaHXtSFqa4dRn4M5rgmZUzKH6viJUBa/TUARUKn4Ta7E+s0kDJmWEiXIF6AKxfICIhIZEB1Zl9osvLWbS+e0HTwCb0OLnGJoeyFeFv+W69K3mRQIkwiUDa6L31hLCNEAycI6tULCOwOEgSRwQUhfhw5TJeSyCSpuglG/So6fJpkrxpav25dAVw9TknNSI/C7ZjLxGyKpDX02VAQ0RpwFw3G6HWHUdL4+REB5y0oq75ySvk0d4hYAUFcL/9kd1W3W1zG/zPPj1eqkSkprnHhZ/KTyz9MhyYkQUO/UtrFuGATz0g/BGDm8tF/26O+AhkEydgcQA0bggpA+Dh2mSrASVNykMiA6JL519DDpaojNmAnZCIEytcBHZvqVgIoY/Dl9okzJIxCu4a2/KL+hl1jDhoHM1Mvhb9pZKqrRPFGmJC9rx4sSfFFoTpCfUL7lC5Rv5ROyLrcKZF10XauGAXNMY/QsvDGNMmtJUxmVjo21Dgn1gciAELggpI9Dh6kSCoX4zVBBcJNQ7R4Q349XjpNQS9JVppYvxCuq5QV+10DBfXBt9ODPBx+T29AXCgiO/g7WTYujhTUk1rBpAqYJc9zFvcoAW7uPpY6VMCfIEsrg6cgG52oShhELlFFpGnUA4GQ2rXegQSrzDYTBjUCVZvCmXylmE6j+xjrIt8N77LnosujHnuOcIELIgIEOUyXoUi4C4ktuJIjq1+rsYRLr19IxVBUAcll4G56PzKZ5T26XKRnrKMZvcqVEH1wvXlijQ2ANu26nI9a7V0mFr7sCjnA+YU6QlChBksCChABDw6D4DIhEGZWdcK1KqeTVZOH/bB/Maz4Ba+6kHg6//7N9MoqWrfmTwY3eGbwH18K584b+ky3gnCBCCAFAh6kyahzAsZGZNKGkvtvf/pJM/XwnseVx105K32CNA3v5HKj3TkDBADwPqugCx1thL58jc67Kj8/0KKEyNc9HcOAN4MAb0c7LXAEp6KTvT2ot1eXgrSkTQV7fAuu6menbzBfgPvQEMpMmnBwMDEC9ewLehq0yjfqODfd7GkryzITyToFsmpmrhbV0JrxHny29bpYKDFUFADOToLYok8EzhzaE6nxrnitx+K3rZsIc2pC+0fZCfHCjP83O4ZwgQggBQIepMmwL9s1LInsx7JuXyEVVTcBaOBXeY5tK68qXNsv0uzgOYNsI9hyM3hA5En1TNrwnny+jzLcD1rwp6dsE9JRR6ZrpVXQThDWEZK/jNpwS5Vu6SvIyCQOfM+mXzwb5dniPt0RnSB9vgbV8TvpOk+fCqK8to7ZYKzPsGZ3nunZTtMO/dpNMydhAmp0zkM6VEEJioMNUCaYJf/OuaNEH04C1VCA6D4SOxPotZTZEW2UGJwYB/E07ywtcLGlO36brxivzScywAZJV8CRU8oIgzAr06hfoygqIzHYB9ESQdTiHbQkleW1CJXmDcvB3bYvOBu96BdbyOenbbM0jePV14NXXox1SiTKqjiKK/74e1rLZMBoGdQc3FBSK310N58ZF6drrQkfJ2ECanTOQzpX0W4J8e4lYCnvvyPuFDlMlFIrxUrpC8t4oFqtfMuYmZCIknBcdM1YAPSp5SsF7ent0Nu2pbbAkflNATwRZx7BRTSp5Zq4W9pIZcFdvLBnoKiYHrcMJztXEDzgVkNoGoOVcB9LsnIF0rqR/ot47Dq/c+h0iULJL+i10mCqhI+FhLNWon/R3JezqELjQUboF/AkzewSyEa6HYN8hBPsORR+fOTF9m0BYqhYrrCFQqqbDEc468SV5UiWP0CAHrcMJ1pWJ0FQyNpBm5wykcyX9iyDfXuIsAWFA2129kSqP5H1Bh6kSEuchCW3odQgE6LCpS3kr68C9f011sxG6FBeDIF5YQ6IUUMew0dZ2WEub4T22KaLksTkcXDtsSPp2u+xUUw5ag/OiLROhsWRsIM3OGUjnSvoRVHkkKUKHqRJsO2FDL+Qw6ZjDpGNAZCZBeSsj1KifdWBeeF50NqKpUSYboau52rbhPREjrDF/Svo2nYQeJgkBESuD4v1rYK+cD8vMQHUUYNRkoQIfxfvXwPmsUI+NBnQ5L7oGq7JkjBASCVUeSYrQYaqErB2/oZfKMBkJc5gEfBcAyEyeENrsPSCy8/XUCXwYg+ujlbcG18uoAQKA78Ja3Byqb/U6V2tJM+ALZHtyNTAv/RCMkcNLJOrV0d/J9YDoENbIZWEtngFv3ebSbM/iGUBOwDnM2jCHDYF7749KDoUleXKDVXVgDGmA9edzwsxZeyFcP7ma8LoRREcmgiVjhJBIqPJIUoQOUyW4XjhnZdzFvTb0reF8FYnmdSBU54ubwyQxWNWyAMeGedkYZK4Z38N5gWPLDJFVgLehBcZ5I0rn9TzeInOeAOAD3vM7kVk0DZYfQLUXYNRmoTImvE07YU25PH2btgXr2snw1m0ulYpfPEOu/DBf/X4iM1cLVXSRmTmxR1ZLFYswsrbMRjdXEx/ckHJINTHQGp1ZMkYIKYEqjyRF6DBVQtEDCgUAqtcBFb5eFIpetLUjc9U4+Nt399xcj2mUEyVwrFBWPKokr6kxjGanjevFqwF+6ur0bQKAAjIfGwN/3ZboDF7vnzsN8h0lGRegc57Mus3hAFmJDaGOfiKEWQHDsYHWPIwgALI2jGGDxbICZq4W6uwhUBHBDfPsIf0qG8FGZ0IIYckuSRc6TJVgAP7zL5XtxbAWTpOxW5MFOgrR2R4DMpvcfEe8hHq+A0i73EeXEIJjxWfwFgn8roUE2Xapc9Whktf196ucFTCGNMC8bEyP0i3jwnP730OTjc6EEAKAJbskPegwVYJS8ZtcJZGKAJB14h21ZbPTt6mjeVKHMh8Qlm9NvRz+pp0l5XFi5VtJM7uKQhL1+UJ8P1y+fzXFDojSLTY6E0JINwPivk/EocNUCUmbXKnBtZ4X76h5MoM/Kzp+OthWvDKfUF+PlvKtpObTGqHyzlwW7vdWl+9huvMGGbtEDjY6E0IIIalCh6kSEucwCWVA8gk9SknHTwctM5EMZGZcCSBCmW/GRIjJAUJD+ZYm5xB1uXgJdTbF9j3Y6EwIIYSkCh2mStAxDwnQk+3JOgkS6gLOYXsH4LrRvVpuMTwuSFXT+G3tJ0vjejuHk8aH8tBnD03dLJti+x/8TQkhhJB0ocNUCUohM2UCzHFNoex15+wcdewEjCH1cj1MVsLAXCt9h8kcXI/A86NnIg1tgCkx36XGgXvfI8hMmlAqK75ha/8qF7MtuA8/EZbGneIcBr96C+7DT8D54l+ImWZTbP+DvykhhBCSHnSYKsGxAdtGsPcggkOnZF3GNIalZI7QMEzPi2/Ul+hhAmAOGwJ85KKTwzBrszDOHyHjLAEDq1zMNGGOPjf6XD88OpzrJWmeTbH9Dv6mhBBCSDrQYaoE24K/eVcPZwnoLKkyIDObCAAKxfhho5+7XsYuwkxT6vLh5WwNpNKijBHvBGfk+rUIIYQQQkh56DBVQqEYP5tISiUvVxM/bFRC9loTA6a0aFAO/q5t0bOfdr0Ca7mQ800IIYQQQmKhw1QJuuadDDAVrIFQWmTmamEvmQF39caes5/6YzaNEEIIIaQPQYepEjTNOxlQpWoDiAGTTSOEEEII6UPQYaoEjZkebq77JwMhm0YIIYQQ0peQld7q53Rlesymxp6vd2Z6TOGNr5mrhTliGMzR54b/y402IYQQQgghqcIMU4Uw00MIIYQQQkj/hQ5TCrCMihBCCCGEkP4JS/IIIYQQQgghpAx0mAghhBBCCCGkDHSYCCGEEEIIIaQMdJgIIYQQQgghpAx0mAghhBBCCCGkDHSYCCGEEEIIIaQMdJgIIYQQQgghpAx0mAghhBBCCCGkDHSYCCGEEEIIIaQMdJgIIYQQQgghpAx0mAghhBBCCCGkDJbuD1AJSikAwPHjxzV/EkIIIYQQQohOunyCLh8hLfq0w3TixAkAwKhRozR/EkIIIYQQQsiZwIkTJzB48ODU/p6h0nbBqkgQBHjrrbdQX18PwzC0fpbjx49j1KhR+N///V80NDRo/Sykb8O1RNKCa4mkBdcSSQuuJZIG5daRUgonTpzAueeeC9NMr/OoT2eYTNPE+eefr/tj9KChoYE3AJIKXEskLbiWSFpwLZG04FoiaRC1jtLMLHVB0QdCCCGEEEIIKQMdJkIIIYQQQggpAx2mlMhms7j77ruRzWZ1fxTSx+FaImnBtUTSgmuJpAXXEkmDaq+jPi36QAghhBBCCCGSMMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw3QK3/zmN3H55Zejvr4eI0aMwMKFC3Hw4MEe7+no6MDtt9+OYcOGoa6uDkuWLMFvf/vbHu958803MXfuXORyOYwYMQJf+cpX4Hlej/c8//zz+MQnPoFsNosPfehDWLVqlfTpkSpSrbX0/PPPwzCMkv/efvvtqpwnkSWtdfTFL34R48ePRzabxbhx4yJtvfLKK7jmmmtQU1ODUaNG4Z/+6Z+kTotooFpr6ciRI5H3pF27dkmeHqkiaaylvXv3Yvny5Rg1ahRqa2txySWX4Dvf+U6JLe6V+jfVWktp7JXoMJ3Ctm3bcPvtt2PXrl3YtGkTXNfFzJkz0dbW1v2eL3/5y3jyySexZs0abNu2DW+99RYWL17cfdz3fcydOxfFYhEvvvgiHnroIaxatQpf//rXu99z+PBhzJ07F1OnTsWePXtwxx134Oabb8azzz5b1fMlclRrLXVx8OBBHD16tPu/ESNGVOU8iSxprKMubrzxRixbtizSzvHjxzFz5kyMHj0au3fvxj333IO/+7u/w/e//32xcyPVpVprqYvNmzf3uCeNHz8+9XMiekhjLe3evRsjRozAf/zHf+DVV1/F3/zN3+Cuu+7Cv/7rv3a/h3ul/k+11lIXFe2VFCnLO++8owCobdu2KaWUeu+995Rt22rNmjXd7zlw4IACoHbu3KmUUuonP/mJMk1Tvf32293v+bd/+zfV0NCgCoWCUkqpr371q+rSSy/tYWvZsmVq1qxZ0qdENCG1lrZu3aoAqHfffbd6J0O0cTrr6FTuvvtuddlll5W8ft9996mhQ4d2ryullPra176mmpqa0j8JckYgtZYOHz6sAKiXX35Z6qOTM4xK11IXt912m5o6dWr3v7lXGnhIraU09krMMMVw7NgxAMBZZ50FIPRiXdfFjBkzut9z8cUX44ILLsDOnTsBADt37sRHP/pRnHPOOd3vmTVrFo4fP45XX321+z2n/o2u93T9DdL/kFpLXYwbNw4jR45Ec3MzduzYIX06RBOns47+FHbu3IlJkybBcZzu12bNmoWDBw/i3XffTenTkzMJqbXUxfz58zFixAhcffXVeOKJJ9L50OSMJK21dOzYse6/AXCvNBCRWktdVLJXosNUhiAIcMcdd+Cqq67C2LFjAQBvv/02HMfBkCFDerz3nHPO6a6DfPvtt3tscLuOdx2Le8/x48fR3t4ucTpEI5JraeTIkfje976HtWvXYu3atRg1ahSmTJmC//7v/xY+K1JtTncd/Sn8KWuN9B8k11JdXR2+/e1vY82aNXj66adx9dVXY+HChXSa+ilpraUXX3wRq1evxi233NL9GvdKAwvJtZTGXsl6/6c0MLj99tuxf/9+vPDCC7o/CunjSK6lpqYmNDU1df/7k5/8JN544w3ce++9+NGPfpS6PaIP3pNIWkiupbPPPht33nln978vv/xyvPXWW7jnnnswf/781O0RvaSxlvbv348FCxbg7rvvxsyZM1P8dKQvIbmW0tgrMcMUwRe+8AU89dRT2Lp1K84///zu1z/wgQ+gWCzivffe6/H+3/72t/jABz7Q/Z7eqkJd/056T0NDA2pra9M+HaIR6bUUxRVXXIHXX389pTMgZwKVrKM/hdNda6TvIb2WovizP/sz3pP6IWmspV/+8peYPn06brnlFvzt3/5tj2PcKw0cpNdSFO93r0SH6RSUUvjCF76A9evXo6WlBRdeeGGP4+PHj4dt29iyZUv3awcPHsSbb76JiRMnAgAmTpyIffv24Z133ul+z6ZNm9DQ0ICPfOQj3e859W90vafrb5C+T7XWUhR79uzByJEjUz4jooM01tGfwsSJE7F9+3a4rtv92qZNm9DU1IShQ4dWfiJEO9VaS1HwntS/SGstvfrqq5g6dSpWrlyJb3zjGyV2uFfq/1RrLUXxvu9Lpy0X0Q/5/Oc/rwYPHqyef/55dfTo0e7/8vl893s+97nPqQsuuEC1tLSol156SU2cOFFNnDix+7jneWrs2LFq5syZas+ePWrjxo1q+PDh6q677up+z//8z/+oXC6nvvKVr6gDBw6o7373uyqTyaiNGzdW9XyJHNVaS/fee696/PHH1Wuvvab27dunvvSlLynTNNXmzZurer5EhjTWkVJKvfbaa+rll19Wt956qxozZox6+eWX1csvv9ytivfee++pc845R61YsULt379fPfLIIyqXy6n777+/qudL5KjWWlq1apX6r//6L3XgwAF14MAB9Y1vfEOZpqn+/d//varnS+RIYy3t27dPDR8+XP3lX/5lj7/xzjvvdL+He6X+T7XWUhp7JTpMpwAg8r8f/vCH3e9pb29Xt912mxo6dKjK5XJq0aJF6ujRoz3+zpEjR9ScOXNUbW2tOvvss9Vf/dVfKdd1e7xn69ataty4ccpxHPXBD36whw3S96nWWvrWt76lLrroIlVTU6POOussNWXKFNXS0lKt0yTCpLWOJk+eHPl3Dh8+3P2evXv3qquvvlpls1l13nnnqX/8x3+s0lmSalCttbRq1Sp1ySWXqFwupxoaGtQVV1zRQxKY9H3SWEt333135N8YPXp0D1vcK/VvqrWW0tgrGZ0fmBBCCCGEEEJIL9jDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIeSMQSmFGTNmYNasWSXH7rvvPgwZMgS//vWvNXwyQgghAxU6TIQQQs4YDMPAD3/4Q/zsZz/D/fff3/364cOH8dWvfhX/8i//gvPPPz9Vm67rpvr3CCGE9C/oMBFCCDmjGDVqFL7zne/gr//6r3H48GEopXDTTTdh5syZ+PjHP445c+agrq4O55xzDlasWIHf//733f/fjRs34uqrr8aQIUMwbNgwXHvttXjjjTe6jx85cgSGYWD16tWYPHkyampq8J//+Z86TpMQQkgfwVBKKd0fghBCCOnNwoULcezYMSxevBj/8A//gFdffRWXXnopbr75Ztxwww1ob2/H1772NXieh5aWFgDA2rVrYRgGPvaxj6G1tRVf//rXceTIEezZswemaeLIkSO48MIL0djYiG9/+9v4+Mc/jpqaGowcOVLz2RJCCDlTocNECCHkjOSdd97BpZdeij/+8Y9Yu3Yt9u/fj5/+9Kd49tlnu9/z61//GqNGjcLBgwcxZsyYkr/x+9//HsOHD8e+ffswduzYbofpn//5n/GlL32pmqdDCCGkj8KSPEIIIWckI0aMwK233opLLrkECxcuxN69e7F161bU1dV1/3fxxRcDQHfZ3WuvvYbly5fjgx/8IBoaGtDY2AgAePPNN3v87QkTJlT1XAghhPRdLN0fgBBCCCmHZVmwrPBR1drainnz5uFb3/pWyfu6SurmzZuH0aNH44EHHsC5556LIAgwduxYFIvFHu8fNGiQ/IcnhBDSL6DDRAghpE/wiU98AmvXrkVjY2O3E3Uqf/jDH3Dw4EE88MADuOaaawAAL7zwQrU/JiGEkH4GS/IIIYT0CW6//Xb88Y9/xPLly/GLX/wCb7zxBp599ll89rOfhe/7GDp0KIYNG4bvf//7eP3119HS0oI777xT98cmhBDSx6HDRAghpE9w7rnnYseOHfB9HzNnzsRHP/pR3HHHHRgyZAhM04RpmnjkkUewe/dujB07Fl/+8pdxzz336P7YhBBC+jhUySOEEEIIIYSQMjDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZaDDRAghhBBCCCFloMNECCGEEEIIIWWgw0QIIYQQQgghZfj/vgrHwTbMZt8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,5))\n",
    "after2000 = pd.DataFrame()\n",
    "after2000 = ndf.loc[ndf['Year']>=2000]\n",
    "sns.scatterplot(x = 'Year', y = 'Price',data=after2000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AYVUVUB66F/zkGbGBzmQNrLNdoSVqStNMGOt3+H8Rz3X4ypNp8pQMxTRIdTXBvWpq4+DdPeBnhaGAWz/EwUUmJqQvDmIxMYfuXkh1NWCjhwdrjw61AZyDxaudewD8DUSBzC//jEF9/GFYf2z1ZGikuhqgohTqN5fBfPW3vuuw4UNhrAvWMAGAdFe9uL+de4SWqcD1k0qKfYYCViLpO19umASeSkF5YB5YRZmTCbOzW1K8Glb7x84c3M8zyhbaeHG704PIHQz7znFlE9XZkwFuAYblyVTphnHeLnHhjodHw9+TPOVr9pjy5PGR1+ZnukRGrsDeVARBEMRVzLnscQhiALnsfYKuKVJp6Ks3OCVi0ohhYOVlYPMbgK1vw3r/iHOoVBuHNPImGOu2iw/skq+aakCWwEqLga5eWH0JUUIWlGmyN8nuTWI6LRzPgMAMCassg7Fpt/jM7TDW1w9l8Syf6YFwlZsFWIaYw29aoCydC/SnwEcMgzx9kq+sze6jo+/c49TyRmma5Nlf8DQelWrjkKdNgP6z56AuX5i9D/caFWlgd9aCm5YokfvwOMy9ByBPHi/K82IqpFE3gcWHg8kylEWzYWx6Lf/65c4vYwmuLG4UjniZ80WDUh3WgYO+dVYfbQZ0HfozL0FdvhCmff9BfX+CSgrLS2G27PMEw4E102kd5s49MHfugbqqWWT33HO/EJe4kBpts2WfyEBJLHQtQ21OM2PK0yb6xvVg68LIIpsgCOKaJ7SapoB/owniQqAgaCDpT4faU8v3N0Ce+lkRKGSyRPxslzggwtZabpgIc+8bUBbNgnTXONH81DAARQHv7vXPIZGC/uxLkGd+Huq8LwKm6WhlrPeOQBo5DGzEMKh33+V1K0ulkf75WijL7oEyfzp4Kg0W02B19yL987XQVi0Biw+Bcu80GC9s82/8cy2tbT1PAbW8TFWg/d2q7KY5pgHpNLRvLssaKeRZI/7JaWiPLYOxcZf/++mTwM92QbqzLv/6uXDKwT48DnXlQu/5lWUwN+8OzkQxBjZmhFgLt4tbbt+fiJJCez2dQCDfOoa5xZ1vLXXYeZkMlPa3ywGJeQIdVlIcaXOK/rQoMSwvicw6enRhVAtOEARxzePoXnN+QKMAiLiYUBA0kJQUwfxNS/DG+DctTpmTjZTpFxRlaw0ALF4N44Vt4v+vfdV7TG7JUHFMZAi2vQVz21u+KUqrmkX2ADn9ihQF6E3AWL0h+N6KY6Kcad22SEG7c3+2e1lxDLB48Jg2RTFH05SLrXGKXCPGIM+fDt6TAItXA+0dnqwUGIM0vi6bdXOfH1Jy5S4HkxunwHx9n+fa2rdXRLrwqdMmwnSvg70Wrv8fek+ZkkJnPe1/EKIIc4s731rqqPPSGWOGnGcWVeanr90KpXmOuKetb2ezlbl6pvsboP/cVSZLteAEQRDXBUHl6ARxMbmiLLKvegwz2jI5x/KZd/dCqq+JtrXOnBdmGe2zj4zqPZPzK7vbFrqg3kV5msLa83P66NjnKXJkzx0ocuB37vvJZ/2Nrl7ov1jrs1m2v2cV5cHnhtlvuu416NqF9Dtyr3dQ359CnjuAbElZgc/V+fxCaqkL7WHkJp/NqWFCqh0N6/0j0NdsAYtXQ13VLPoErWoWAWxfMqsLo1pwgiAIgiAuEpQJGkhsy+QAnYfV1gFYpnOoNL4+sxEeDl5oqVNYyVNf1rbYrq013/9QCPZNAygvAzQFLG2AmyYgi9hXGj0cuHUMlIUzwA0TbHwdrKMfw9i827MRdbQep87mnWe2hO9dKA/ME0YAn3aG//I/fRJgmiLjk0wBJTFA08RaJvqBmAaleY4wnAgis9asohTqyiZh+d3VA3nm572ZsKjmokHr7/4s6Nyw7JY9nyFVojeQboA9MA/yuDFZvUxfAsri2eCFrOftY0V5YG8Cytwvgs/6AqzWo44GS6qvgbJ0LoxNu7zvHTjYkMro8SM4rxrtfO9xKg1mZ6xsPVPudVc25b8OQRAEQRDEBUJB0EBSHIvUrrDP3S60FMUawCRROtTa7i1LC8LeOIaUPHHdyAQoFlBaAgbAevegz45abpgIfe1WqCsWwty5F7orSLC/t977ANqTK8B7k2DFMaCyLLsRzVOaxIYOgnzfNCBtQJ47BcaW16E2zQRUJetk1jDJ0eRYx04ADMKM4VCbZ+08wVJdDZSFM/wXdB2fzllrZfFsmLt/l9UoRTUXDbov92e552qqsNXO1bWEzae+BvK4MV69jKZC/caD4XMCgJJiKItmwXj+VV8goj25QvTgLRWmA8rD9wJ9/TDW7/BbiS+ZLXo05RoV5OGca7QHwOaU3TBI6MOoFpwgCIIgiIsIBUEDSUyD0jQzVLtibNgpNpW6AePXrzjH2KVoUULx0JKn2jisw0fB2zsgNUwEuo/5HMvs6wOAsuwemDv2ROuP1u+EdFc9OADptluyB0XZWNbGYb5z0NEESbVxoYF6/0Px54weyv3Lf67WJkojY5fX5dpUh671pl2Opkaqqwk1QQgtuXLda+7zCdO1hM4no4mR7qz3WFxb738QaTfNbqiC8UKIlfbG13xaJmNDjt26pkKefKdoTOoOKnP7UEVwTjXaBdqcRh4zqJwssQmCIAiCuOiQJmggSachjbwpXOdh60/6kp5jzJZ9kBsm+nQzjvPZx6egPDgP/ONTgd+bLSKQkCrKwCrKIhtRShVlBemPWEW50NH0ZbUvdolUrlbEPY/csVhFGYzNu4Lvb+xo7+Y8QiNjbN4NpWmW6B9UwPHWoTZhU56Zm3TziMD1tUv2cnHfa+7zkeLVgboW+Y7ayGfPKso8n4U+d9tNzdCjNTZuLVOAHidfUGbl0zWdI6HvR+Z+pJLigo4hCIIgCIK42FAmaCBJpMC7om2Xkej32D47Gg7LhDx/OmTTBLM4UKSJYxiDsnQOpMpyKPdOBZ88PltO5mqMCQA8lfbqVwK0SdwuDwsjV3/k0nlYiSSg61CaZgGWBfSnwftTsNo6oK/d6u93U1oMdPd6G3u6yuHAreBrB5HWwbt7Id/fAGV+g7iPPKZziKmiaeuzL0H9+lKxvoYJ9PQCslg/mOHX5Joq7jXRDxRpUB6cJ9Y6mYL67RXioIyVOAfAk/2hYwXen2tdtIUzxffFMWHfnUyJ60bRlxSNXEuKA/U4nj5QOYT14Ant8VMghZTQXc9WqBe6vgRBEARBDAwUBA0kJTEwKTq5xnUDrChaO6Q0z0H6R8/4zAkgMV9DTDesSANPZYKckPHVby6LvgdFEZqXwZVgAKAbwrRAVWBseA3Wnw9n51pfA3nqBJh7DwgzhoB+N8qiWWK8ACG8TwsVpdsBgJgGJkvgiX6xYTZzZfVeWEzLNnHtT0P/2XOewFAaMQxIm9lAwkVgvxvbyIExmNvf9vVKUhbPdu41kKD7y6yLPOk2SCOGwfr0bMFaMZ5IwVyzRbwbQXqbqKAS8AVOUT1+Cimdc84poITuerRCHaj1JQiCIAjiwqFyuIFE02AdOxFpB221HoXV3ZtXOyQ3TMp+lilfgqZFjs05d/Qr4XqZo9HzO3YC6qPNMH/TgvSPn0X6f/4a6e+vhvH8VsiT7/RaTx9sg9myX+iMQrQ8xuZdUL/e7DnPhnf3eMrbIm2662rAO04i/YOnof/8efBTZ2C+d8Rzfu7x1rETIuCx9VSZwJC3d0BfvR76M5uR/uHTMNZsAe/szs4jkfS5oom1a4fZsh+8sztQc2Vs2gWlaWbwfOrz65Kss90w1m33acUCz8nck/NuxDS/pXW+oNIVOIXe80UqnbveoPUlCIIgiCsLygQNJKk0jM27RZ8a5NhB19VAnjZBlK9pKrS/ejCweSeQabbZMNGTNbEOtgGpNOT5DZCTaSDZ71hv809OQ278AhhjkEYOAxtfBw5Ad2l0bMyWfWJ+EstuyDQVStNMSCNvAu9PAZyDjR4OtB3PNh1t74DUfSvUxx8GEkmw0mJw0wIS/WCVZTAitDDK/dOhPbkC6f/9ItCbEIHJ2NGAxKAsmA7ePxlI6YBhgN1ZC+ujT2C8+ibkyeNFeR0D2KAKQJKg/uevglkcPJWGFNOAcTcDnPust5VFs5D+yRqoq5YAdXHoT60PDwyPn4R1uhMs0e+UKYVqcQ61QZ42MfQ75f4Gn/DfyeRBNGcNs5y2Ont8WrHAd8l2+luzxVljpNNQlsyB8aI/iAozXoAkieCwOCb++8PjwfcVUjoHXNryrqu6lCxfD6WQ9SUIgiAI4uJAQdBAkkyF61/KiqH/Yq0IKtI6+Ked0WNpqre0SlMBSYL5cot3Q3zbWCgLZ8BYv8PvALZ8gUczBMCZn/rNZWIzr8hgVRUwNuz0BGVSbTx7PpC1rl63zXOM3DARvLMn8lb46U6Yb78D7a8eBDiHsX6nKJsLs8S+fSy0Jx7JHmd/XlcDuXEy0k+tz5YK3jYWytK54H0JoT+SFfDuHpgHDjrHsEEVkMaMCNbIlJVAe2yZsOnOzEHN9KoJJaLMjJ/tEjoiiQXqXSK1MLm6ntx3qUgD+tM+LRgAIJECGBNGDfZ7p6nAZ8YCv2nxvRvy7MlI/+Bpb8ll0PtiE6A5upTlXVd9KVm+Hkr5vicIgiAIYkChIGggscuLwvQv7s2lLEePZXHH4hkQTl/Gxtd8v+qz6qG+AAjI/LqcM4ZDWgd6k9BXr4fcOAW8vSPUMtsuywsr3QMA+Z6p0feiKKJcbP0OYROdKSULy8yw4UNhvBhwT4faAO69J+u9wzB0HdJd9WAVZTDffgfy3eNFw1cArLwU0pAqEXycOO2f2rJ7PAGQPd989xOKrAASgzRsSODXkVqYIF2P613SvvMVpH/2XOS5vgakGQ2U2jAJrCQGFBfB+vA4dFcgCeR5XwLmZiWSvqDEHkdfu9Vn330hXMprXTQGoIcSQRAEQRADB2mCBpJMn5QgfPqXYydCj7V7/0jx6uxnY0cHWl9H2kRnbKoDx8/0HCrk/HzHQJHzalcAv0102Ljnek+2pbf55h8g3T3eyWZI9TVARakYs6QYKHNtlDUVcuMUSFUVkO++C+qjzZAbpwCaml+bFKbtqY2L74L6DhVCcVG05osFn+b04Al6/+wg6rf7gRuHABKDsW5bYLYn9H0J6qVUSHnXQHEpr3WxiPjfhtBeVQRBEARBXDQoEzSA2D1QcgXQUl0NpJtHQqoZAWPzbieYUZpm+rIQUn0NlMWNwgJalqB+fanYWCsh8Wo+B7AcH2mPnkRTw8cteHwAnd2icahbZ5R7raDxwsbOd82g7w0jq9fJBEDKkkYg0Q8LdhCUaeZ5/KQwa0imwT89m9VWHT8pSsLWbs1qeAK0OGDMr/upjUOeMwXSDVUFWz1biaSwwU7pQCoNlBRBeXCecOE7clRop2qqAVUBKy0GGIP62EOwDrU7rnduTRGA4PfPrTv6tFMEfy4rc6utI+uil/u+5IzvcCnLu66BUrLQ/20IW1+CIAiCIC4qFAQNMJ4eKH1JUQp27ATSP14DQJSAqbO+IIwFDAvy/OlQZAn8bDcABqu9A+kfPQMpXg15zhQx5g2Dsr2FcslXulVSLErxDANsSBXMdw95dD5geYKgfOMDgCRDX/MS1G99GYppgZ/uDOxj5BsvbOzzKUezP4upUFc1i3X8YXYd+Q1VkKoqoC67B7wvCeOl1wMDHPPtA5Anj/f07+Gfns3ez7MvAQDUv/kS5PssMN0AYhoQU4GSorybWSuRBPpE5oJ39cHcsccfBDfPBbjl10S5mudqT64AGIDSc+zBU1wk3PFyxrX1QGxIFbS/W5W/f8+lLO+6RkrJruf+SARBEARxpUFB0EXA1n1YXT0wfv2K1/Fr5x6YLfug/e2XYW7aDTa6GvxoB6xDwXob6a5bAQD8bHeg01ekA1htHNb7H2R1RRn9D9I65MYpMFv2g8Wrox3EyooBSRKW00HleJlyNyleDevdQ5Buuxnm2+8Ej1dXA96dNVGw2jsCx817T5nyusDPUrqnl5I9Br/rVkjj6wBNhfH81lB9E8uU/5lpXWil4sNhPLPZNw+c7YG+ej20v1sVqv/JxRb3s1HDwQaVw3rnIKz2Dl9mhnd1w9y5N9CG256jsfG1UC1MmO7ISiRhbAjQWmX+rDTNAipKC9PX2Fm1gDK1AS/vupTXushcj/2RCIIgCOJKhDRBF5NUOnAjLzdMgrFpN6xDQoORGwDZCK1LmRD8t+yD3DDRpxnhH5+C8uA8n97AyWy4bLKdMepqHN1N2Lh2OZm5Yy/0nz0HedoE/zGuzISypBH86Ano/7oe8v0Nvv499rGsqtwZx2zZJ6y5c+/p+Ekoi2f5r1dXA3nOFM89ue8zKEByryN6E0JfEhDM2cfZwYhUG4eypBHG2q2+45zA7xw24O4+MVK8GqyiHFZ7h69vkf7UesDk4RqYzBzPSwsTpa1pbYdUU12wwYBd3uV77zLlXQNpVHApr0UQBEEQxPUBZYIuElYiCZiWU4rm1l54rJrd+paMk5cUrwYsE6iqAJMk8P4UtL/5EjgAeeEMyBYHOrsBSQYbXAGYOpSFMwHOgf40EFNhHjiULUXLGVdZPAvo6xfXDLP0rixD+pfroH5tMRTzbvBkv1O6h7QuSsBkCejrh3LvVECWxLipNJA2hB7HNEXZj6qAA7DeOwLzrf+APHl89locXlvnTNlZ+udrIU8eD61pJngqDRbTRPkXGLQnV4iSOwtOyZ00ZgTkqRO8+iM3iiT0N2FlhTaGATZ0EJRH7gPjHNKIYYE6J3Pvu6FajqB+NuhLwPrwOOTGKWAVpeCpNNRvPAh+4pQ/cEv2552jOO4ctTD5jk/0wzp5OrD/ju+eYhqg6yJ7ZFninSgpumjlXVRKRhAEQRDEQEJB0EWAd3aDf9rpK2mytRcwXYGPrWVx9czRM00yzZffCNat7HkX8t3joT/7EtSvLQF0PeuINu4WKPdPy9ocu8d16UDUby7LziHA0lv79gqx4Tzbg/Tq9VlTgGGDwEqKoD+/1XdvjjHAiArwzm7oa3f6Agh12T3Q12yBmdEJqd9e4dOoOOv48Sng85+B+dLr/mvd3wD0JSGNGAb58YfBJQb9p78O7nEDCO1TUQz8TFfw9zYlRQBjQDoNrmkiuEymhOZHVTIaKgvKw/cGbsDD+tkoS2ZDXbEQ5hv7kA7R4zhzL1QTda5amDzH8/409J895+u/E3hPbtOLAIOGiwGVkhEEQRAEMVBQEDTAWIkkrPc/hPXOXwrqq2PrYtjo4U7PHFuvE6VbMVv2Q2maCevwUfD2Dqe/CxsxzKOpCevFY7UejdbdHDshxj92IqtZAQc48wVA7rnxu26FdNvN3k2zOxMFDvUbD8J6/wPw4ydhvXdEBFeuMYBM4LBoNowXQvQ7v2kR67BzD9SVTbCOnwy33M5YjvOjH0PKlPWFHYciDelfrIW67B5/E9c8DnBR/Wysw8dgHYh4J9y9jwrQRJ2XFiZKW5NjZW733wEQfE85876qevYQBEEQBHHdQ5qgAcRKJIHOHkgjb4zuq6MpQjOjqaKMbNEsSLWjs2YI+frk1FSDjR4OaXQ1pJHDIE+fBOmOWkBTIcWrYWze7eh8wsZy64Pc2L/wG5t3Qxo1HNKom7KaldUbwE+djdTUsIoyoC/pCYA8upfVG6D/9N/B2zugLGiA+dZ/iHK2u26F9t2vQHviEWj/+atQmucA/f2F9QtSlOz9RGijrENtkCrLoSye7b/v+hrI9zcITdPk8aFBqLljD8z3PxTPOpcIzQ2rKIvUfrn78+R7NkKDNSdwrChCtTUB+jFHc5RPR+Sa91XTs4cgCIIgiOseygQNEO6SIfUrTdEHp3QozXPAu3pg7tiD9O7fQf3qouz3+frkaCp4e4e3rKquRpTacdOj80FMDR4jc4z6zWWit45Lj2OXOHHThPnGPm8wUEgPH5f2JDwT1Q5j825o31wG3puA1XoU6c27RGmVXXpnmrmj+67lZDAy96P9zZfAp/YE3g8A8NOd0J97BUrTTCj3Nwi9UXERzAMHof/8eXF9t2YrBzu7ht6EvzQrSnNzLr2P0jrMtw9AmjZBmEkUxYAiDdw0gd4k2PChSP/waUhjRnjK1grBo63pSYD3p4OtzPPdT9h9XQU9ewiCIAiCICgIGgB8ZVDlZZHHs7JiWB98BOs/3s8GB4ZLsJ9PE2Jxf1BxqA3gHPKiWeKDjM7H/Uu9j7QO9CY9ltKeeUqSPxNTiF7FpT2JDCgOtoH3JqD/Yq3384CywUCKi7zNWDOb+LD7ceaX1mGs2y6CrSWzwU93ZTVUwDkHetn5RGhuzqH3kVQbF5qvTGCiffcrMLa8Hlhmdz4laI6FOwD9Z8+FH6gqub1TI+cN4Krp2UMQBEEQxPUNlcMNBLklQ4rss3e2kWrjgG6ClZV6yqNsHUjuf/vOr6uBdfho4HdWazuYxT3nRo5V7+3bkztPHlDyFTlebRy8uxcoLc6WXOULKBLBTmhWa3v0OtbVgLsMIez78Vw7YH5uJzartR3MtMDKS70HnmOg55DR3ATBu3vD51VfA1SVQV3ZBHVVM1i8Oms4UBsHNC28JO1CStAi5ivVxmG+cxDmgYORz9u9nldbzx6CIAiCIK5fKBM0EORmBTq7IU+fBDAGq+24xxSAVZaBp1JehzgIHYiaEaK7/9sjzK8TvXvS//PXoVPhyX6P0UDoWLVxyPc1AADUxx4CALCSInAIJ2quqWCpNNSVTR57b7NlH9QVC8W9uR3b6mqE/XNlKaTKcuECt3arMEXIaQZqj4W07g84NBXyzM8LswjDgNI8B8bGnX63tUWzYL5z0POZuuwecFWBsnCmcIFjzGNLLk+fBOujEx7bcq7I4EdPeIwIIo0J6mrAexNgY4IzbMqSObAOHxXaKKf5aS/kcWMgjxvj9Apy7vPWm8FMEwADv6EK1p8OO2sj1cahPDA3v2W26/2zEkmgu08ElzEt62qXSnuspaWSYkcjpOc6v9XViAzbsy+J9yPsebuOuRTucFcrVlcP0JcU619SBJQUQaosv9zTIgiCIIjrGgqCBoLcrICiAOCQPnsrlEWzYGza5bWnfuwhsEGV3nNy+vWw0mIoD8wDP9sF9KeAqgrAMME/PQvtPy2F+ecjMHf/zqfjYCVFSD+1Xowz43NgMQ3ctCA1TBSBmW4AxUVASQzoScB8/ffBNtxvHxAlWc+94mzI1eULRGDDAGl8nUdLxLt7M/ojUT/laE8S/eCv/95z//ZY5t53vT1yNFXYSLfsh77tLeczZdFsKAtmgJ/tBsBEH6Efr4FUMwLat74M3tkD3t0Hblow1mzxmDIoTbOETqgnAVZaBFZRCn3NS57skdwwEfKMzzkb/cjAsXEy2KAKX/kZ7+yGsX4n5CnjhQucK8sn1ddAHjcmuyZ9CYAzGBt2Zu/THn/OFMifvVX0MyqKQRpUIXr3RJF5/3hnN4xc6/K6GsiNk0UTVtc9u7VE0p31kKe6n2VPpieT/VIFP282dDC0xx4CijTq2ROCdboTxgvbfO+R8uA8SEOqLt/ECIIgCOI6h3HO81X9X7F0d3ejsrISXV1dqKgoXBw+0FiJpGfzraxaAqtlP1i8Gry9w5dRUFYtAbp7Yb1zMDTbIC+cAXPzbljtHU6fn9yskDxtgrcczH1exmqbHz8JNmKYyMQoEsAkUU4nS+AfHAu1YbbnbttQ259LDRNhBRgd2NdXmucA3HLKojxBSc41lAfvgbHpNVh/PgwAYr5HO3wuanLjlMB1dM8VgPcYV38kXyCTyQhJI28Sm/qSIqA4Bn7spCiNs0zghsFglgmeTIlAEplmr7t/B2nMCI8Ox37+bNTw8HnW1zjn5L4vufcj3XUrpPF1vvEDj8+Mm2+t3c/ROe+he2E8/6r/HE2F0jQT7KahgMRgvvrbQEdA9z0RfqyuHhi/fiX0vVUeuY8yQgRBEAQxgJxLbECaoAEg13qYMebYBwdtgBhjHhtrz1i1cSiLZoFZVnSfn0NtMFv2C6cy13n6/9kIZemcrD32+0dg7twj7Kl/tQnQdfD2Dkgjb8prP+2zQG5th1RVEX7eoTbwU2eQ/v5qGGu2AF29kfbKMA2ozY3Ouknx6kAb6byW4fFq3zFRrnRmy36REVq9Hvozm6H/Yi3M37SAlZdAX/sqIEkwN+9C+ofPQP/580j/+FmYL78BaeSNYoxcHU5GExY5T/c5eWynWUWZZ/xQa+tMRkcqKT4nK2tnPm4rc5tM8Gi9cxD6T/8d6E2GW6KTJXY0fcloq/y+AJt1giAIgiAuCVQON0DkWg8DCDcF0A1f+Zvb0pmfOiNK1pDHXa21Hdr86ZDvrIP57iFxXloH5xaU5kZAN4TeR5ZF0LT7d/mts23suefcA+9PQf36UlhHPxbzs7MpGa2PbWttHWwTupwokimwYUP86xY0F3fDVdMQDnyKDHR2g1WUgluW6LtkZ8Wi1u1Qmyjtcn92sA2wONSvN8P8zZuhzWCdpqZuHZj931EmEJoqXP1OfJp/82sYYgPd3iF0PYoMJPqhNM1y/ttXgpbPmjpobgHn+ILHfMYWZIkdTr61obUjCIIgiMsGBUEDiNt6GEC4y5j9ecbGOrcbjrSqGSymiT/k2YTyM11ggyuFHfZ/egDa48vAuxMwduzxlc+pKxZCf/YlcWxNhHW2e46599Cfhr7mJaiPNsPcudenaWETxrmCEYZIMloW37rl4ipty9UWyQ0Tkf7Zc5BqRgjNkl0eeC59eTJYre1QmBTZDFZtmCSel1sHZv932PPOaJ2MTbtgHWoTxgxRKAp4IuVYfdv3qa/ZEt4bKJ81ddDcAs7xBY/5nPLIEjucfGtDa0cQBEEQlw0qh7sYZKyHw+yk81pgt3fA6u4Vx+TdhBbB6u4V/11aBOuD4zBzAiDAXz6HmJrX+thngZz5s9wwSVwjIFtibN4F9ZvLoD7aDA4ebQuda6ccYtnMLSuytE1umOS/v3Poy+O5Vn/+jIrvueR53k52JbNeVnsHpLqawOGFzXiPz8rbuc9MbyAr1748j921x4ACEXbiOcFhPot1ssSOoLQ42iq/lLRUBEEQBHG5oCDoImBrOPjHp7y6H9suujYOZd4XoX5zGeTGKSJzgqztsNmyD8barVCWNIJ390RupNiQSiCREv1lJBmsojxSsyOPr4f6+ENgRbFQTZLcMNGZu9myz/O5bTcdrX1JCuvk3gSUJY2BWhblgXlAX0IEfCdPw0okQ7UvTFPzaoKc/64dLf47Tz+j3KDAuZadgQsj06AVqbQTiIQ+b+d6oz0Bo9myTxyXEwjZ7nCsqtxZd/d9ynfUQn20GWzUcOEw5z43TDdUVwN5zhTPeI6WKGNl7jknJzh05pp7T249EhGIVFkuXOCCdH8PziNTBIIgCIK4jJA73EXESiTFZtXkAOeALMHY8JrXwri+Bsqi2YBlwfzzYZg79zqW1PLMz4FlbHSNDQG9cprngvcmYG59E9ahdqH/6UtCf2Zz6JzUlU0w334HyrwvIv2/1wmdTU01IEtgJcVCW5PoB6rKgc6eTI8ZHVZ7trePurIp+hpfWwQwSWQ/Mpkjp0/S4EqgSBPrkHGFs+/HLvOyEkmgq1doJmIqkNIjeyO556P9zZeE21t/GigugrFhh2/d5Nley2jnuwLc76RpE2Cs2QL14ftg7j3gKU3zPG/LEuOXFAGJfqT/5d+9g7n7IXEL0DRAlUWD0gDrc/d9SrVxKM2NkIYN8R3j9AlK9osxI/oEec7pTYjvS4thrPeumaPHqh0NpirinnLGIMLx9AkqjokMEQVABEEQBDHgnEtsQJqgi4itdQFcNse5JWQH22Bs2ClskevHQBo62DFI0J/eDO3JFZBs8wB7cxvTxC/2ug5YJpT5M2B19YAVxcBT/s2zB0WB1doOft+0UE0SAGjf+QrS//oi1FXNjjbFPUYkQwbB3LTLCSTc15DqayDdWe8JgOx10NduzVouuzfp+frkuOdTUuQJDhzTBVcAwNI6pDEjfP2EpJE3gnd1Q1k829Hv2PgsyRXFN+fceUfOP63D3PYWzG1vCY1QMi3WyqWx8lFRBmSyYsbG1wLtqcPmEEXuOb4Gqmkd/KOPId093q9FIvIiVZYDFPQQBEEQxBUFBUGXijwWxnLDJKC7z5NhcWsuWFqH1ZuAufv3kO8eH9j/Rlo6B7ynT5R7hfQmccrAJCnyOMQ0SONuyWqDXMcFfeY+l1k8slxOnjox9Dv0JvybeFtzE9IDx74ne96e74OCgpLibHBkZ4zW74Cxbpv4PtMnR7m/QTSrLSoC13UnAHJfM3TO5zB/3t0DfrYnez8h68pPnHLMHwq67nnicTp0B4+U+SEIgiAI4hqBNEGXir7+6O9NwyNKd2surEQS5vsfwtyxB2zEsFCTAGPDTki1oyHPvduvN6mvgbJ4NiBLQoPU2Q35/oZQTZCxaRfke+4GP37SpwkxW/ZBnjPFf426GiiLZonSqyiinNtCbIOVJXP8ehe3Tinz30iLa1tdPbA6TsI68hGsj0+JPyeSQn/U3iE2+GUlQGWZKP9yZ+jSOox122H8pkWI101D9D2yyxRdWqmoOTvzDNPr2BqgYUNg7j0AaAqU5vD7NDbv9po/JPK8UwXgXhNbm2XPWRo2RPRgGjbkii59C7sHgiAIghgI6N+ZaxPKBF0CrNOd4FIeu+jyMjBFhrpqidABVZRmf3nvTYBVlDkWzaH9bw62gZ/tBqsshzS+XvTCyfQfEtmGLvCjJ6AuXwBIEtCXBItX+/oU2RkP5Z67Ic+dAibLkBfMgMIYeG8fWFkpzD+1go0ZAbVhYrYHzuGjSP/zv0FdvjD6XqPK6XJsg3lnN4y1W2F9eFz0VJo6EWAAqywX+qXObqjLFzrz1r65DNbpThgvbMsGiprqWHr79FhNs2C1HQ9ez0NtkGd/AWzIIKhfuh+QZM/6hM05CCe7kqvXKRH9oLQnvgTe1SOa6N7XILJlAc/EbdPNdQO8s/u8S9Sctc3RTAVacF+hXAv3QBAEQVy50L8z1y4UBF1krK4eGC9sgzx/enT5mabAPHAI5s490P5ulZMBcpqI2s1N8/W/URUYL24PL1WLV4tsQtNM4Gx3qCYIAPjpLk95nq0PUlYtAf/gmLhG4xTw9o7Cy+XqasC7ewKvl2u5bCWSnv/h8WiL7HvJDQg11RsAAVlL79zs2cE2kfGyG6AGkeiHsev/Qp4/HdaBQ445RNicowjVDCWSsA4fhfXOX0Rp5Oc/E2k8Ydt0W61HYe76v4HaoHzkrq3zea426wrmQu/BYwgRYBhBEARBXN9cC/9WEuFQOdzFpi8pNt+d3ZGW1OhPZ0uskinxy8OaLUh/fzXS//pi1ro5jykBk6S8dtJWazsYAFZRFj1317XcOhhj7VYoi2cJt7QAu+xQW+WMBTirKg8s1/NZLufRUdnW2O45Qvbff6Sl96E23zgeMgYI6OwFb+8QWTTb0nygbKJdmT77mpFkbLrNln1ZbdB5XDN0bc93zEvNBdyD5+/XP/8b0t9fDWPNFvDO7oszV4IgCOLq41r4t5IIhTJBA4SVSAqNRkoXmpiSIqCiVAjvAUCSoa95SZR0BZSfaX/9MNSH7xMb7NISWKc6IU8eD3naRHDOYZ34FMoDc4HKMigPzBMBjGEAqgKrrcPp38Pz1akaBqCp4ABgmlBXLQEYc8awsxxSfQ1QUQq5cYrQBd09XpRkAUBvAumfr4W6sgmMsayFcrw6O6ePToDdPBLa/OnCXKCiHKy0WGh2UmkoTTOdkjwUaWJOnb3gaQMwzbw6G7Hopui7ZNtvV5YDkgztyZXg/SmwIg1WV68YL5Jgl3iPkYRhiCBFYtC+9WVxiqaCJ1Pgpz8SzzumAYYpXPtSuvMOhNpRZ7IP4Dyb6UMBmTRddzRKAALXKirLIb7L8570JGABF5QdueiZlnzvSMj39MseQRAEURDn+e8McXVAQdAAwDu7wT/t9JVcSfU1UJY0Clvj9g5ImfKt3C25VBuH+W4rzJZ9UJcvgLHOW84l3TYWyvwGGC+3QK4sh3XgoFfbUhuH+miz2HybVvRkVQXq8gUwX3rdP0bGeUyKV0NpmoX0T9ZAGjMCSvMcGFve8JaBDR8KVlUO6LoYr2W/R6vkNF3tS4o+NYbhK9OzNTnmgYPgR09AWdAAY/NuWO8fATQV2uMPh9+HpoLdeAP4W+8EXtft5KY0zYxcElZR5gs6PJbYgJOdsQ62gXf2iL5OboOKCN2RXTccVlcsz54M6NkyR/s9AOBzAPTYdNuE6agC6pcBkckLc+hzxuhPQ//Zc+dd93xJaqjzabHCvi/klz0KggiCIIjz/XeGuCqgIOgCsRJJWO9/6Og5PN9legApTTNhbN4dvLF1bbblhkmBzm+seiiMja8JDcwb+wKd4cAY2JgRgGlF2yxzHtgM1B5Dffxh8GMnYB44KIT4B9tgrNsOqWEi5M/fAVgmUFUBmCb4mS6wQRWhbnUAIM9vAD/2Cax3DoZqcqTxdZDuHg9jSwvYiGHA+0cgN0yCdexE6L0oTbNEI9RDIdfN6Hys1nYRgEZYVJvvHfEaRBSHW2IDAEqKYL7yZsG6I33tVigP3RuafYDFIWXKB63WdiCtO++D2jAJAAfKSmH9+bAvAMqno3Jfx3z/Q1jvHoR1sA1s1PCCrNTPJztyyTItUdbjUVot+mWPIAiCKITz/XeGuCogTdCFkqvnyME62AapZgSkeDX0NVvEZntVM9RVS6D956+AjRmR3WzXBGtXbE1L2PdARtsy6ibwjlNQls4JtK+Wp08C07TIMZBMgVWUwdz9u+znre1gYNDXvAQoMvixE8LyO9EPpHXI8xugfXsF1McegvbkCiirlgBlJc55rKI8et4jbwI0FdLd4yGNGSHmO2YEeHcflMWz/fdSG4cUH+4LgJwx2zsg3VEr1nllk3Bma54L6faxvjVRFs6ANHo4pBHDAAZRTpjHEjtIdxX5bA62CW1YhL6JMebVUdmNbH+7H+ymGyBVloJ/9LE3ALp9LJQH54nMRsa2E4l+WB8Gu92xirKsyUSYbivgfq2DbcDZnkhbUI/9eFcv2KjhjnbKtxYDVEMdaj2eT6tFv+wRBEEQBXDe/84QVwWUCbpQkqn8jm1pHcoj9wn9S7/QR1htHaKkattb2ePkkJjUHj/se5siDax6KNI//TWUe6dmm33KCnh3L9iQSlHKFQW3/OVWmTnIMz8PqGo2q1NWAu2xZTA3t/jKtrTHHkL658+Dp/W868PPCBc6qa5GlK6VlYBVlYO//nukd/9OZESmTQTARYD23hHwZEiPHE0V5Xm/afHbYc+fDtw7DfzTM2BDqsAtDuPV38J670j2uLoaKEtmQ125ELDgs8SWauN+3ZWmBm74PeTLLugG9Ode8WjG2A1V4leoynIA8DYwLYkBsiKc8HJLzjJljUHP0CE322QYYIMrYf6xNfBc/ulZ8YwCStoCS99c5ZW+eQxgpuW8GrvSL3sEQRBEgVAD8WsXCoIulOJYfpF5cUxsZCvLRanQs1tgtR2H+o0HPYexsM1XRo+S7y8cU1XH6tlYt91nIy3VxiHfMzV6robl37Rm5iDddgvMl99wAh5l2T0wNu4Kbty68TUoD90LVhQD78/TPNXW2xxqg7F5tygd27zbGTfIGptpWuBQYSWF1sE2GBxQFs+GdewkpCFVnntxjjvUBmP9TihL5/o1TLaTX47uSm6YBFjB5goO+YIkRclmf+xT/p+vOQEQ4LXYthJJGGu2hJbXBdp+57rO5VxPXdUcbhXu0kS5S9pCS99yyhI9DHCmJcx6POp4ddk90MM0S/QPG0EQBOHiXP+dIa4OqBzuQikrAe/u9ZUV2fh+We5NiABo+QLwE6c853HGAsex3cK4ZYVfJ/O957wcG2mrtR1Q5MgxPNqXnM8Z4A0KosoAW9shVZbD6uwG7+4p+JrWoTZxniuL4xt37GhYIWuezw4bpinOSxuRc+d9iWzp4mMPQX3iS5Duqoe+Zgustg7PtaV4NazDRyPfgbD5Bq2B/RkUOfB4AOdsHw5AvKc5KX33HHl3b0Hz85S0nauN+RWSabF/2dP+bhW0b30Z2t+tgrJ8ATW+IwiCIIjrBMoEXSBSSTHYuDFgQwcByAkSgn5ZThtQv70cTDeBmAalaSZ4sh/6My+BWVxkGnLG4cdPQlk8C7w3Gfi9k6FIBJSI5ZaidfdAWTgDxstv+H4FV5Y0gvf0CV1OWs+UeSlgpcXgPQmPgxkA8FSeDE9/CkwC2M0jwYYODp2348BmjxtW6uacyGCs3Qp1xUJAYjmb8OiMDD/bDTa4Avx0V9ZeO8dqHGldWF3LEqxjJyDfdgv42S5Io24SJhev/lY4rSmKMHKIqZGObsrCmUj/Yq3nHOe6JUVglWVI/2pTjt13mZhDGPlKypjrvzUVStMsSGOqIY0dCevwMY/FOu/qhTxujJh7TpmYVFcDZZFw8IOm+m25883D9f4VmmmxunpE6WgyJWzGS4o8GbGBIuqXvTB774G2/b4aGrZeDXMkCIIgiHOFgqABgFVVgGmq6OOT0kUvnGLRI8a94bO6eoCYBjOgzEp74ksATJhvH/A6lWV6CRmvvgW58QswX98X+L359gGxIc/FXQKlqWDDhsDY/DrYqOFQp0503NBQrCH9019DGj5UBCbPveIxBtDXbIG6fKH3vmPBJWkORTGgP4X0z56Hcn8DlCWzAd0E0jp4MuXT2xQ6LiuOQXv8YXDdgHxPRvuU0sGKYwBjkecCDLA42LAh4G/+Qdhr232Oxo6GVBcXwV5MA//oE8gzJiH9s+c8/ZO0Jx4B0gaUxbNgvLgDiFcHamzsZ8M7e4DeBPSNr0H7Tw/A2LDTZ+utfW0JjM27vZ9HWUrnKSljgyqg/f0qICneRWPDDhibd0FdsRDWgb94TCWk+hrI48Zk6567esHPdAFgsNo7hFV6vNqr8bGvn28eQweJvkoF1lBbpzuFzik3kHxwHqQhVZHnDhSBGqfbx0JZNEuUSOZ+vmS2eGfOMUi4JDbiF8jVMEeCIAiCOB8Y5zyPmOHKpbu7G5WVlejq6kJFxZX9D7J1uhO8sxvmdr+NMpDJiiydC3T3wtz+dnDGZO1WqMvu8WlecnvjuD93a4KUB+Y5FslB17ePDdISsUxZE2/vyGqCVi0JtNt25rRkNswNr3nHvXkkpPH1MDftCix5k+prIE2dED5ufQ3kBTNgujRD7jWwPj4FfuSjyHuU7qrP9kmyjRRy1zRjXW4Hl2ZOcKI0z3X6OcmNUzzrErau+dbLveaeazXNAiTma3gapAmyx5LuuhXS+DoAcI6LnGd9jQiAXMeHzZF/9LFXExR2fGbMgq21u3pg/PqV0PVRHrnvomSEPHMIuZ/AtQt7dwoIEgZy3S4WV8McCYIgCMLNucQGpAm6BFhdPTBe2BZtT93aDpZKC6vou27NalFWNYNl7LXRm/DabD/2ENRvPgTlwXkw977rC4DcVsdSbVzYOBeg3wjSEknxap+tsrF2K5TFswJtlpUljbD+2Oofd+RNwNluyNMm+K2v62ugLJkjmnmG2DcrSxph/uZN3zpare0wW/YDpiVKvyKsnxmHE4CFGikcaoPZsj9buub+7mAbkEpnjRsKtJvOq6EK0PFYB9vAT3ch/f3VMNZsAe/sFmOVFENZMif0msbmXaKEyaXZidRL2TqffBqf2tEeW9ABtQ/tS0auD/ryGJAMBCH3H7R2USYc+tqtoXbiUdexzx8oG/EL4mqYI0EQBEGcJ1QOdxHw1dBDmBvk09Dw/hTAAem2m4HeJHi/KBmT4tWQHr7Po1sx0zrUlU3CtjhTqsNtXZCqgHMOSBLUh+8TupOqCiBE+O7g1g/laokMw1PypS2YAW4KzYrc3AhFN8H7+8E0DTydBj/bBXPnXu9YmgpUlAgHuv5+yE0zIfengZ5eQFbAhlQCpUWQRgwLLC0Twn0O68jRYD3P3gNQF80COIc8vwEKWKbvjwWrTZTeSfFqz3OQ4tWeEjTPc2xth3rPVKC3L/hZ2QTZTd9QBevoCU92Lq+GKsxKvEiD9uQKWF290DfvhvLAXBFcJPsDSyOda2ZcC9WvLxW9g8w8Vu4FWFczVfFlOLimQmmeE1kKWhD5XAQvRRPTsGsEPJvId8cOEkJ0RFfEveaDmsoSBEEQ1zAUBA0woTX0yxfk17rENMAwhTtaOg0mF4O3d/j0I442w7Yt/vNhYO7d0H+xNnRsdVVz/sm79UO5dsr2n9O6yHxMGAdzy+u+EjJl0SxY7x0RzVbtzJSquPr3vOnt3+OU8r0E7ckVHvtijzV2JrPAO3udEiTPuoy7Bdpjy2Bs2h04vtmyD1K8GnLDRO9zyNfjKZEUpg5uUwAArChHC5Nrb/3dr0CqHQ3tb5cDqbTY/EYZHQD+NbfpTyP9s+dEJmzxLKBPbK5RpHmumQtPpqCvXg8gU8p2R2309YtjAEO0YURJkfcaEZqRc7ET5Z3dTlAdOb+LTdg1gp5NvnenPx26PsqSOb53qqB5XEqoqSxBEARxDUPlcAOIlUj6eo8A4ldhs2U/OHi0TXJ3L1Ca2WRqGoxNwT14zJb9UJpmemyLC8ky2FbbodfPjJdriZz7Z6VpJoxNrwX32Nn4muijYxsJ1NWAc54tHcrocOTGKVBXNUO++y4RIH292bFOjrQvLi0OLEFiI4aJnkU5OiOrtR3mm3+A+vjDTlkh567nEBZ4ZEeGsWmX6AVkr0ddDbhlRq/l2W6k/99/hbF5F1hlGaRhQ4DS4vO2J7fvxdi4C85f20zTz0LGs1rbYR074StBdI63ratlRQTeq9dDf2Yz9KfWg7d3QF2+ANLtYz321lHve95yMPfx9jitETbjtXGg9BLoT0LWNPDvTr53p6QodH2MDTuE1iuAK8VGPPL9ulLmSBAEQRDnCWWCBpK+hNd1zfUrutXaDrmvH0rzHBjrd/jdrxbPgrHtbUj3N4jNq6ZkA4aGSb5f5qVRw5HevNsZw5PdyD1HU4HBFZA0FaiLQ26cDKv1qPPrvttYIde22s7u8FNnID3aDN7VA2nUTTDWbQ9cAqu1HeqMzwGNUyCNHQ2myICmgo8vh96yzyMmD3JCg0tr4nQ9ypTdWLoBmMH9fSJLkw61Qbm/IftBTx+UJY0wNux0NrdhYnyrvQPWoTZo86dDvrMWPJUGKy9B+leboX1tMfjZHiDZ7zwXfvwklAUNSD+1wcmoWMdPgvWngYpSKA/OC3Y/e2AuDNfztNdevm8a9KfWe59pTx8sbgFlJcFNP0Osx43Nu6H97XIYG70BrJNlAxyzB8/62UYYD8wDTpyGVRwTGaFU2q8Zcc/zxGlYZcX53dJs7cmHx4NtxutroCyde9FNEYDwRqr841Pi2bnc4SLfnfoawDAjNTXKwpmih9QV2rCVmsoSBEEQ1zIUBA0kHNHla6aJ9P9eB/XrzRkNTQospsHq7oWx7W3IX/ws0j94GsjofUIDhto48NlbPX+2m3FamV/tg86RGyaKDXVah1RXA+3bK4S2JaaBJVPCdlpTgGQa6iP3gw2qgHXsBNI/WZPN7Nw+FtKNN4SvgaaCDa4Ef2OfP8hZvgDWsU8ixeS241RgGVFtHMqiWcFlRHlKk/iZLpHReLQZKIqBp3VI0ydBqiwDJt4mMlsRgQQ/3Sn0V7VxKEvnQm0S9ti+zXrTTKSfeQnq4tmhgZ7yyH3ZPjjFMfBkP9KrN0B95D7I0yaKoMq2Pt/2NtSH7wU4YLrX1O79U1MNZd4XgQUzwHUDTJZhvnso0HocaR1I9Asrd8PMlullrKv5ydORpgj85Gnx/tjP4p4veg/KE+CGuqXZ2pIQm3E2uOKS2WMD2UxkUG8cz+clMWDynSJwDAgSeFceDV5aD7zOlRRchK3FlTRHgiAIgjgfKAgaIKxEEsaGgBKxzJ/lhklASTHUxY3AyTPgVRVgJUWAbogNXl2NE6AAABQl3H2qtR3G5t2QGyaBH/1YbNaff1W4cfXeBvPN4HPseZg794jStU2vgY0aDnPnHmhPrkT6R8+IgzUVyvIFMH/T4isvY8OHgkdoW+SGSSLTkFuWdrANsDjk+dOhb3vLuU5ulguJfliALwDKve9cK+m8pUmKItZAYpCmTQTjgLF6vbA+7jgF+b4GyHYGL9dgAAAbXAn10WZYbR2wPjgG6z/eDwzkjI27oMyfnj/Qqx7msSCWG6fAfLklOKvwmVtgHTiY/c4VbBjrtmWPq41DWTw7q98JoqwY0g2Dgr/LJ3R3Ncu1WtvBZ0/2fJ3PLc1tqewxC8iUR9rzztU5aX+3KnpeF4GwRqpBn4cFCTzsGdgUxyIbtl4pXA1zJAiCIIhzhTRBA0VvIrDvDZCxFh47Gtb7Hwitxa82Qf/xs4AiiwBAYmIz69o0We0d4pwwy+BDbZDvqBW9YBjEr+hrt0IadaOnEaZvHm7r64NiDPXRZnBuQRp3i7PBZqoa3McnXg3rcJR2Y3TkOjitTDPXydWfGOt3AF294RmJQ22Qxo72f16g3sk62Casqh3902hY7x2G9cdWmC37xDxWrxdBlp39qo3D/GMr9GdfAhtUDmnkjdHPOsoK220tXKB9Naso9zzTyOB40y4oTTOD1+H2sUBMg3XytCjzO3naq9vJJ3TPCTStw0c9mpGCLLiRMVNYswXp769G+p//Den/71eO7gia6p3zVaA9kUqKIQ0bIlwchw3Jlv6RpoYgCIIgrlgoEzRQ5PsVXWKALAmXNsMQmgpbxxNwrrn3AKS76sXxlglUVYgSpp5ekalo6wDv6gY/2wM2ZBDUry4CSorBO3ui55FTNsbPdHnKvKwjH8Fs2S8MCwDxK/3MzwtBvWmCFceAYxLkGcIoIFfbwmQ58vL2r+O+jbwrK8T7kk7WJTCroUg+LQY/flLoqjbu8s0pVx/DU2nhFldfA5bZ2Jst+4L1KO5GtZnsS95SID1TzpjrrGZjP2/3c48q58v5LlT/pKlgo4dDGl0NddUSgDHn+nYpofH8q8H6jqoKZ9Me1ig117jBbNkH7dsrsqWE+dzSkimR/QrJ8gHwZPmudu0JaWoIgiAI4sqFgqCBIs+v6CymgX9wLFsKBrcZQM65mgp12T0wX3odVpsQi5svv+EPOCbdDr7nj86GWP36UrDy0uh5hlhfW63tMNbvgLJgBowXtoryPU2FumKh0Hi4510bB0bdBHbzSF+PGmh5XilNhVRf493IR2ifHD2V255aUwP746R/vhby5PHQmmaCnzobWNYGAKw4Bu3JFeKXeDsrk6NHYcUaeDLtnO8O2txOcUHwZBr6M5vD78F+V9zvTFQ5X+53QcGGaw3TOXoc7TtfATTFFwAB/lK1czFaQFoHLCtbDqYXYHGdpxmr1jQT8u23XDPaE9LUEARBEMSVCQVBA0XUr+h1NbCOfRKulXjoXs+5ng1345Tw0qcNO8FGDwfePyI+LCkSNsh53M7C/mwdagNP9ov/bu+A0jRTONsd8l8bgLCczvShccaLD4++/ntHIE+dAIA7n0eVdznf29mB2ji4aYX2xzF37oH82Vthvv2Ofw6aKkrFGMtmYVQV0u1jRa8llx5F/cYD3ntzBW2FOMqF3YOnDMr1zkSNybt7ve9WQMAUpccxNuyA0jwn0qnMbuzp27RrKqy244FGC1JtHCgpcjQjViIZ/nfAvu9TZwPn4KAbnpLNawHS1BAEQRDElQdpggYI+1f0XA2AU4a0eVfgedbBNiCVFueOr4eyagnk8fXOZjZSZ3GozbNhZJKUMQ6Y6NPHuJuGAhn7ZdefnTEyJXpmyz5II28qWF9kj2+s3Rp9/d2/Extq16Yw8h5d17HHQKI/8FgHRYLy4DzvHDRVlNgdOIT0//croUX5/moYL2yFMn+60EN5JpzzV8OVfTFb9hW0xrn3YJcc2poR9zsTOmZ9DeRxYzzvVpD+Ka8eJ5VHpO8qzfNoXIYPhVRX4wtMpNq4WGOXbXXo34FMxlMqKaYGnARBEARBXBEwzjnPf9jF5/vf/z7+/u//Ht/61rfwk5/8pKBzuru7UVlZia6uLlRUhNjvXmKsRBLo7gM/3QmAwfrkU0h3jAXr18HTOlhZMXjaAM52A4oMq60D8q1jgLJiQJZhbNwF+XO3i3IqTYX6zWVAb9LXd8j+VV5d2eSUXqnfeAD6L9cFuq5xziFVlYN/2ikyCWXF0FdvgDx5vNedbUglzJfegPX+EahfWQT96U2h96o+/jBYkQZucVjvHYG5+3diXq7rs2JNWFJrGlhaB0/2gxXFwBXJuS9WXgquG8IZ7sPjMPce8MyL3VAl5mZZIoGkyLA+OA5WUQqUFIFJEngiCVgcvLMH0tiRomGrJAO6LgKAshLRFyjI7KE2DqlhIhiYU17HwWG9fQBsxDAxj5iw5XbWX1OhLLsHUkWZ6B1UUgTrrLD1dkrs3Gv12EOwDrWLfjMP3+vpm+M4paV0p/+OUzpVWuwEGs5x/WmguAjGhh1O1sX9HgShPfEI0j/9dfj3f7dKNHQNwerq8dh6u+flO9bt/JYp/wIgPrM4jM27QrNFSvMc8azdaxDQZyjoGlG9iCLnVOAYxIVzrs+NIAiCIM6Fc4kNrohyuN///vf45S9/iTvvvPNyT+WCsUtfeJEG/TctUObeLfrJZNyvjO1v+7Q9mDAO6R89CyleLTIdkpTVeLz6W8/G3acxcZdGmZn2ogE2wwCgPtqcDZi+vlTojnJ1OHU1UBbNhKHIYIPyBJb9aaR/9hykcbdAvuduSKNuEjbKdrC29wDke6aK3jXr/A1CHZ2Jq2Er/+Q0tMeWwdi4y9/naPokWB0nId96M1hFCdigCiHKd2WrpPoaSGNGwNjSAssuEwSgfnNZpKOb3DDJU/6GG4dA+9piGOt3+nVKKxc6fXuMnHtSl90T3KPHMAFZgjz3buBsN6wTp0XAU1GafWc6u8NF9FUVvrIq5cF5IqhN9IMNrox+VsVFkaYHUKP/p0CqLAcKbFaaO0/PfWXea1jc/z5Mmwh+6gzM1/cFNnO1+wwF9pCK6EXkOz6TFTR37vX+3crXz4i4IM71uREEQRDExeSyZ4J6e3sxYcIE/PznP8c//uM/4q677rqqM0FurDNd4h/9jLaHt3cE60jqasBGi349Um0c8vwG8GOfwHrnYKjuhMWrwY+fhHT3+GwGo6IM/MQpGJt3B+o3WLxaXKOuBvKcyTC37wntdi83zwVvbYf1zl+i55xxVcvVo0i1cShLGsElBjOnqWjQnOw/Sw0TYQVoW+xrSuPrYKzbHr2eOeMC+TMlnu/LSqA98YivGaqN8sBc0bcnoFQw6NpSbRzy0rlAV0+mR5N/g8811ekZ5BuzvsbTYweAp8cQgOj1yJyP/rTzPnrm1jAR5t53fRmqQon6dT93ngCymcLajNV52hA6KlkC/+BY9D0AF7ROQGFrRdmJgSXwPchAa04QBEEMFOcSG1x2TdDjjz+O+++/H42NjXmPTaVS6O7u9vzfFU1/6py1PVZrOxiThB4nSidTF4eyaCaslv3ZPjs//XdY7x6C+mizp9+KW6vi6GpkOVJDwvpTMDbvCtW+KItmZXQsET1rNuwE47wgvY/z56geO4fawCpENqJQHZFDAc1Unf9cdg/42Z6C+/ZEXdteb8atTOYh2BwDif78xgVuclzWojRFjh7HNISr3qpmqCuboK5qFuYWa7YIY4iAMr58+Hr+fH81jDVbwDu7RXDU2eO/r0ymUv/FWiBtOH2ZIt95ew2i3OUKWCeg8H5GxAByrs+NIAiCIC4yl7Uc7vnnn8cf/vAH/P73vy/o+H/6p3/C9773vYs8qwGk0D4wABBToT7xJUCRRS+d3r7Iw1lpcWCmwjrYBnCh18HZLqC8DFBkoLNb9ByqKgczjLzmArw/5bONdttR81NnRBlbvBp6yz7IjVM82iJHO6Pnue/cvkWpdGHH51vPnO8jHd3qa8C7s/2VpIoy8DNdBY/tI6aKPkEui27tiUfCy/Ey5hiR5D6v3N5SuRbfRRpQXuK1Y06kQl31Asd0zzFEUxPY8ycT2El31oOVFEXfl3st861rn9B9RZJ7D0HveQH9jIgBJt+a0poTBEEQl5jLFgR99NFH+Na3voUdO3agqCjPRinD3//93+PJJ590/tzd3Y1Ro0ZdrCleOIX2gQGAlA599fMiy7J4dv5gICrDcqhN6G2e9pd/qauakV69HupfLYsc3naJC9MXSauaMxczI3v8IJ1nw5mzLs51w7C1K+eQ2QFczVAl5tUk1NVAWdII8w/vO41sea7WKs/YPlK6v/QunztbSg8PJDNmEx6CXNRczyrQ6OA8ndnCtBzKwpmRv+7LUydGXw/wrmWedeWJAjbKrnvgnd3CcCPqmnnGIAYIcgUkCIIgrjAuWznc/v37cfLkSUyYMAGKokBRFLzxxhv4l3/5FyiKAtP0/14di8VQUVHh+b8rmuIipzwpyNbYxt1bxmpth7FpF1BZFnl83k21pvo3zoDzK7h1+Gj0fLp7C5ovqipCy+HMlv3gRVph4xR4XVvCVuh6OqR1mHvehdw42VMOJo2vAzgX1t2ZskKmqZHj8+5eSHU1BV9bqo0DRXmCu2INvL0jW9r41Hrw4yehPv6QcAjsT8M6eVpkZACnx1DgHNy9iNycxzlWIukzawBEkBOZLQMAw4h+TvU14N292TELeKb5xrPvwZl3q/89L3QMYgA5n/eVIAiCIC4ily0TNHv2bPzxj3/0fPbVr34Vt956K/7Lf/kvkGX5Ms1s4JAGVUB5YC6MdduzmQggUJiur9nifGYdaoPCIbQ7IcejKCDAccM55Jmfh7ntrexnmgoMrhQZD8sEmzDOZ1fsdmFTFs/2f19XA7lxMvSnMk5qhhmpzZFT6cj7sO/b0S3t+zOU5jkw1u8Ivu9M/56o9VQWz4KxpcUzF6m+BvKMSdD/db3fNOL2sVC/vRwsbYAnkuAMYIMrIY2p9o9fXwPp5hGQxo6Csd5rue1bG3s+D8wDT6fDy/HqamC1fez9TlMh3z0e5sstgU5pUlWFcKILc9sKEJnbfXzM9z8EqyjL2qd39UIeNybwnCgtB8BCPs+gKOHPKTNPALAyrnWF/h1RVywEGAt2drPvwZ73h8d9Y5ot+4RuLjcrGLF2xIVhv3vn8r4SBEEQxMXksrvDuZkxY8Y15Q5nY53tBpL9or9LWbGwsk70g/enYbV7+/7YqI89BP2p9d5+PxmNidmyD9q3vgzjpd2hlscsXg35jlqkf/acU04lbIFd7mSaCqVpFqRRN4Gf6QRkBdaxE5BG3yRsits7stcHB6sog3nwQ8C0II28ScyptBj6z58PvXf1K03Qf/2K5z7Y0EHgigxmWeCJfjBNAzdNp08Q/+Q05MYvAD0JoSly3be6fAH01Ru8848PB0/2A/26OC6nzxBUBWzYYPBTZ8VaqAqsj06ItRo9HKyqHMbm3b5NtTx7MqwjHwnrb00Vts6HjzrNUJWmmZBG3gR+tstZOwCQRt4kNDmufjrW2S7w010wd+wJCNpmI/2TNZ53oFAHszBntrDP89lw52Id/Rjmnw4HlunJDZPAP/o48h00d+7x9a1iQwcBVeUeBzlnriUxQNOyfYIUBeaBg56yQHXlQvDOHmGSYfd16s4Ecpl7sNo7kP7nf3Pek9y+WWzYYFhHjoGVlYSOQQw81CeIIAiCuJhcdX2CrnWkQRVATs8d6+Rp6D97LvQcFtNC9TgAwHUTyqLZogFoyK/mUnw45JmfF0HL+DqYW97wuZPxs93gN1QBxUWAboCNvBHmb9/J/mruur57Y2t/ptraoDBkxXcf6sommHsOQFkyW9h0BxkG9Kd8VtMAwKoqHO2OHRylN++CurJJlDnFqyGNGObpVaQuu0eYSARkbawjH4G//vtQgwllyWzwZMrXrwkAjHXbAy2xgzQ50qBKWBaHdFc9ZJfJBO/uAe9L+rNT8WqPxso3t94EUFLs68kDRGh4HpwH44VtoUYGgTbFxUWiTC9A76Wv3QrtiS95mrba15JnuzJirudvOwu6rxN0D87cTp72rK3cMMnXR8g51m217NaY5Lx/cuMU8Jb9ge+dRXbNF5WoZ00QBEEQl5IrKgh6/fXXL/cULh2ZGvmwX9FtbUyom9nxE0BVhbA8znFuc5p1Mgb5s+NgbNgJxKu9mz67GWuuoUF9DeSpE2AdOerbmFut7VAbJnmCMt7dI8q5AjaUgdocQMzzUBt4Z29kA9Pca0m1cVid3f4+QpoKlBYHb9YfbYa57W3fdaxDbaJk8J6p0N0lgznH8JQOpPRznmdg81HLBD/b49h8AxB/DmpCep4OZlYiGerYxj/tzG9TnNtjZ0OAA2Hmz8q904DSItG/x/3rPpPAPz3js6LOljTmKaNzk/P3pNDgMPrv1+jCxiAIgiAI4prligqCriekkmKhuVkfkslZuzVY+1CX/ZVdbpjk2/g7x9XXgN1QBd7VA3n6JKCkCCgryZaJKRIgSWDxaqC9wwl4rINtgMXFL+5BG0XX5lyqqwGrKhcb2xy3uiCtk/25Exglo226c6+lNM0ET/QLndX6bPZBbpgE8zctwZv1V98EGzUceP+Ib3irtR3ynCmB5VKOM1uyHyyfm5h7nhlNEhIpWGc+EuteUgSpsjzconreF/2BZL5rqiLgRUwTFuiJfmG+IEmwPjwefE4eW3RfYBXV26W13ZvRyQmezJcOBAbodlPWQnG0JOt3gg0fClZRKuzHc93zcu4hSoOS93mSXTNBEARBXPNQEHQ5sazsRtE0vD19lt0LFMXAxoyAOm2is5FERakoo0vr4ULyTKCU/tGzjo5CWdwI7a8fgbFhZ3Bpk509QnB2w4YNroS6agnYoApAlpH+8bMA4O0lpCpAeQnMbXs8G1RfYJRnM8qGDoL2xJfADQNW61Gh8UjrkG4fC+XBeUIvlEwBqoJ0xC/76tSJob1xWFEs2uJbkkTPpKh5Dq4UG/PiIrDBlTC2vA7rj4c8YykPzhN6lxDkxsmeQDKyr1FtHOY7B50g1VnXnz8PacwI3/N0CMpOucm1Kc4XDOSOb8+vpBhqcyP0tVt9WcbzEcGzqgrxg8EL2zzPOejddd8Dq6rwZ6nKSvI35iS7ZoIgCIK45qEg6DJhJZKwPuwIz+TU1YCNHu7LHKirlmQ3fAHNTNkNg2Ad7RB6DFtIvnwBeHevz3ENyAZPvsxPQDmWVBuH+cdWmDv3QKqNQ2qYCKlmBKxDbb55SuNugTzrc1DumwquG2CSBJ5IZrNMLcJ4IaqUDoosAorc0q4/H4ZhGFCa54gP+gtssBoAV+VQi28AkBomgrd/HB2QZNbE/jOLVwN/9I5lvLANykP3BpZoSSNvcjJ7TiCpqcBnxgI5Ga5AN8HcZ8ghbLX7kp5sCec88j6Q26PpAnq7hAUg5+MCZiWSMNZt85c05tx3kNVykAbFAsJL5ciumSAIgiCuCy5bn6Drnt4EjM27IDdM9PUskWrjUJobwT8+5f28vgZscKV3nIzo2+4vA8uCsW67EyiJgGM/WEV5pJW1cIBzUextYOtYWGec0azWdkiDK6AsafT1/5Bq45Bnfg7QDXDDhPnKm0j/+Fnov1wH/V9fBG/vEIHZJ6ch3zfN13PH0Y6YVqSGhX9yBul//jfwfBmL4uBmvFJtHEimIteFMZZxQgt+Tu41cdYldy0znyPZL+ytff1SuO856v/6IvSfPw8Wr4b27RVQVy2B9t2vgMWrA7M87utah9qA3qToNZRZa2gqWEyLvA+kc4LJC+ztIpUUQxo2RJhVDBty/mYDecrypHh11jq8gGvYpXK+9/YcxiAIgiAI4uqGMkGXGMciticBdcVCWB0nIc34HJSFM4FUCohp4JIEWJbQTuSW8qT0SEMFbjfTtD/LCMnlu+/KfhiggUFpscg+pMX4rLwE2ne/Aq4bjnW1b/Od0iHVDIPy0L1Cb5KZJ1dVsFQKnBXBfOn14CyLxCAvmAH0pyEvngXFMMH702DFMXBFAW/vyGYNQjQ7sETuKW9GqazYt2a2OxxczToDKdKg/fXD4P1poUliTNxrWheZDVmC+vWlYt6yBOuPrc68fCRTYNXDRIakLwFYHGAMMFzH2/daUw3IElhpMbgkgd1QCXDm1cDkWk9XlEJunCKOsZvi2iYGTbPAZBnpnMyh20xD+6sHgaGZZ5RIAn0JUYa28bXz6u1inekC+lPZ97coBik3iA86L9dG2eLOuxkEK4lBWb7AN58oO+aBzFQRBEEQBHH1QUHQJcDeUIIDxobXspt1p3fPXhhu84PaOOQ5U8AkJvpRDh0kvuhLwtj8OuSpE0TPmlwd0LQJogeRGzNTCmbrb8Jc4epqxOdvH4B89/is/sad7cjZfENRYH14DNy0YB1qh/mH96A9ugTmum1CV7SqOdhVTVPBRg0HMy1wywK6+2C2HnWuYd8/irXw+dbGwSaMAzRVaKNWLBRrHbCO6O6FfP90yPO+CFhc9PBhTJhDhGSJHAwL6f/5rGdMZekckXHb8Jq/58+SRoCFbNoz5WNSSTF4Wof1aSfMHXvA4tWOYUTYvcoNE2HufTergQHyapmctY5XQ4oPB4I6grmM2rhugHd2i9u2DQUyz1qd9QVhKFBaVFCwYH16Fsa67f71eWAupBsGhZ4XZu8dqnMCRC+mAJtwy90Uti8JfuQYmKsPENk1EwRBEMT1yxXVLPVcuRqapdrNKdmo4b7ml3LjFPCjHb7ePYDYMEp31YOf7QH/6GMo86fDeOW3sN4/4s+MlBQBpcUwf/Mm2IhhnuuoT3wJ+k//3Wm+yeLVkU045fumQf/Z8z5DA3fjS3vz7W/6OQvGlhZnjuo3lwG9Sa/jWqZvj3O+fS9jRwvrZN0QDVOPn4Q863PgJ8/CeucvwfN16aagqZBnfh7yZ2rBk/1gMQ0cgPXeEfCjJ8BG3wRp5I0w39zvWW/lgbmwDhwKzSIF9SqS6msg3Vknyg4DzpHnToF1sN1znlQbh/LIfaJxaiIprmnfl0u3Zb1zMFSzYz87lil7C32OGb2WsWaL51nJ874I6ZZRgQ1b5TlTYB35CKyiDNa7B0P1MoX00LHOdIlAJmRuyrJ7AjNCViIJY82W/M1X88zJSiTBO06F3ierHkolbwRBEARxDULNUq8Q3D1b1KkTfQYIkT1PWtshN0wCqyiHvnMPDA6w0RmrZ00Fiw8HqygFT6VFZkNVIc/+Asw39kG+vwF45U2xsVdkId63neQ0NbJHinJfQ3B/oOnCLc7WGAWVuBmbd0O+rwHy5DvAhg6GsWmXLzOjfr0Z5ta3hSve9EkiY8I5rNxMUMNEIG1AqqmGsW5b8HwPtUFbOAPy+HpRSlgUA1dk6L96FfKE24RWZOSNYLffAqsnAfOt/wAbXQ11WtbFzvroBJQFM2C8/Lq/4efUCSL7EFQ+WF4amO2xWtuhzJ8OKV7taTKrPDjPCYDQ2SOCDXsNMwYX6jcehNXqD6ycZ9AwCfrOPVAbJwNpI/rduXcq1G88CCSSkKdPEoGTLMHcuTe4PJExsDEjxLzOoZdQIP3ROiuEue3l0f6ojZO9gWVYWV4yJQw47r4L8vRJjjmEUxr4wFzKABEEQRDEdQ4FQRcT96YuyKEsX0NM1/fWoTao0ybCLCuB9tgyGBt3wcjNxCydC2XBdBibdoONHi6stdO6CChaIDbaX18aeUmeCnZaY0UxqF9dBFZVEWlHLU+dCOujT8B/+x+Bm225X4d89/jQMi59zZas69d90/LaNPOzonzLLpWS6mugfeNBGL9p8YyvPvYQ5Ck519VUKItnA5oC6c56yFPdVuQlIiOGkLKzuvASLZ4S2ibt8YdFCVxpsQiAznaBf9qZ0QHlPPu0nl+flDmHqQogy9HH9iWhr96QnW9tHMr86Ui/8mbg4dahNqgNE4XteBSF9NDJd0zY93nOY6oC7e9WRWp4eGe3KMPLDb7d71YqWFtEEARBEMT1AwVBFxP3pi6oJ06+po253xsGlGX3wNi4KzgT8+J2UYr13mHgvcMwAairmj022qwo2vaY5dokZ+CGCeujTyBZeaonDSMywwVNgblzT3A2Alm7Y6u1HYoyEzyVDBrFPeOMe1vmvINtMNbvgDRtAqx3D2YPUxVveZTHOnynrxxOXdUsAsjGKcGZr0NtAA9uKstiGhBTIQ0bkj3eVSKmrmq+sPehJI+OSczCO9/WdvB8QZYsAfwcewmdzzFh3+c7r6TIs6a5OJnXPFbaPhc8giAIgiCuO8gi+2Li2tTZzS/d2K5mQUi1cfDuHljtHa7xiiC5y6hysFrbwTRvEGO1d4jSrIz9stXZ7ZuH+5pWwEZZqo3DOnxUlIMVslGPyHAxSSrcqjuVFteNmm9GFyPVZM+z2o5DuqEK6qpmqCubhHubqnj1WG7r8AA9kP28pHj1OVmLS7Vx8HTaYx9tJZIwXtjmaYTKu3uC34c89+pYU0fZV2eO9cMCPnN9W1IM3t17QbbYAIQLXMR9ICwQv0BL7kKstAHkN8MgCIIgCOKah4Kgi4lrUxfUa8Zs2Qd5zpTgPjtzpoBVlTs9aKS6GqCsGNCjS3lyy9lyr2us3Qpl8azg3kQPzIX1+z/75zJ9krBrrih17KaDkOpqYB074Q+UNBVy4xSoq5rBU2mojzZDbpwiNDW5uAOoIg3SyGFQFkyH8sA8z/FSXQ3k+xtg7j0gPpCzbmjq8gUwNu7K9tx5ZjO4ZUH99grRc+exhyCPrxc6GTM4YLPXLdhSLXi+tjscqygD+hIiQDvxqdictx33jM2qysWzL/R9aJgI/vEpp49NaK+buhpf7yKbvEE3OORxYy64h440uFK4wNXVeJ69umoJlEWzgKLgbOMF9+/JV4ZnGGLsitK89xCGlUjCOnlaPNuTp4XGiygYWj+CIAjiSoHc4S4y1unObBbA5YTGVBkoisE6egK8LwG5fgx4f0q4mjHA+tNhmLt/5zEK0Ndsgbp8IfTV60Ovp317BdI/ftb1gXBNk+pqwDgHYsJ2GhID+tMuJzUOJFJASQxMksF7+0Sz0o9OQBp9E8zX92WdzFYsFC5rbiMB245a18U9fXDM43wW5CZn35NbU6Ouaoa+er3PDUyqr4HSNAv81BlAkkU25fhJyHePFz1uHn8Y6R8/67jgecreVi4EVDXQLUxZMB3pH7nWy7OYKrS/+RLSP3g6fL2/+xXwZAqsKAauSIBhwnz1LVGSaF8nY1/uuVf7udx2CxhjQFoHV2RAksCPfSICTlkS2RlwoQOqKPMEAryzG6bbBlpVgMGV0H+yJthKWlOh/e1y0fcn4FmwG6og3XgDgOgeO4XAO7thHmyHFB/uN8iwDQ2qgv/Onu+1rZOnkf7+6tDv1W8ugzR0UOh182E7PQb2TDrPMa8naP0IgiCIi825xAYUBF1ErEQSxnOvgg0fmnUWyzSn5B+fgnTbLTDWbfNu3N1OZIoEMAnW4axzmm+T78K2Z7YF/ZF21g/MFdqiI0eDj8ls3K2PT4GVFoNVlDsbbc6QcTgrz97TsRPivDEjAW6BlRbD+ugEeHdfNiAKmK8n0HHZQAcFSEE2ybaVOKseBv2f/80Jomzkxilgg8pDrafVxx+Cud2vUXLWc34DzJdbCpp/vmcTZPEMiM05GzEM0A0Yz73qLc+zg6VbbwYzTRHExlRAVWC8uAPWnw97xoqcQ30N5AUzwM92i8BL976PysP3Doh1tG11HWQL755LIXbb53PdUHvvh+6FVFl+ccbO3MuFBo/XKoWuH0EQBEFcCGSRfaXQmxCb1D8fduyS3ciTxwPIscpO6zB37smaGqxe5znHsboG/IHNg/PAZAlSfY1waouys16/A2zUcMgjhkUK/5Wlc2Fs2gU2YpgIzHQD0pAqpP/VlY1yNzTd9lZ2TnU1UBbOQNr1We481AZhvS3V1UBpmgmYFkwg0HXNfbz7M2X+dPDeROYTb0xv60DCdD1IG5myN/96yg0Tgb5+0f8ox4zCLn1L/+w512ejI22rc+duj8NuqBIb6JOnfQGQumKhf10zWTf57vFiTq51ct4PxgKzLwCgb/HbgQdaTZ8vGW1OkC28TcF22+eAXU4Xmm04zwAIQLTeKHMvPK0HN3qlTEdB60e25QRBEMSlhIKgi4T4RThPvbutJwkzEgj6PNNTRm6YBG3hDKA/LX5xLi4CDB28LwmleY74ld+yIu2s1WkTRb+beDXku+/KNjTNZJ2s1nbwrh6fpbW6sskzVmiwdajNsbAOpUiD+jdfAmQZ/NOz+TeLAWvCexPADYOgfecrQCoF9dHm7H3Yxwf0+rHaOgDDgP7vv3Hc89zZOn3NFqhfXQRjS4voa5TzvbHlDWiPPwTekxCue1F6LU0FBpVD+85KYaGtquASAysqAmIarJOngd6kKK8DwDgHtyyY294OdTuT7qqHPPPzgGl576vjJJQljeLPdkaitNgJApTlC3zZigELgICsNiefBXzmuIHMnrCqCigP3Qv0JbPjaSp4Zy94fxqoKD2/sfPpjRL90De+5tvoWwfboK/dSpmO87VNx8C+HwRBEARhQ0HQRYB3dsNYu1X0nYnCNhAIc1wL+zyTLZLi1TD3HoCyaJboP5NIis02A8yd/xfytAnR19dUmL9pCe2pgrTut5YOmFekJXY+R7LiGIzNu31ZFl8PnkwQwwZXiiDMDtj2HgC7oQrGi9sDx4AkDBMCe/3UxsEmjAMAJ/vmm19JMaz3jwDvHwn8nk8Z75TfqX+1LPgm7UzZS69713rcLVAWzoDx7DbfM5AbJsLc+y7kKeNhHT4amBWTGyZBGnkTjJff8PQ+Uh9thrFhZ6gORyopvri/utuuiPmcBItjzt+VgcqeBI5n68/+11pIY0ac39j57Ls1lTIdUZynbfpAvx8EQRAEYUNB0ADj9Co52AY2ariwKw7RRNh9W2xrZF8mJeRzIGODfOwE5Ml3euyX7e/k+Q1Avp4+qpK3p0qQpbVvXhG/+Nu2zoFagLoax+I6ag7ucrt0ThCjfeMBGJtfDx1DapgIVqQF6n6s1nYYm3ZBWdwIfrrTlyXix0+CW1boveXeu23nnXudsEwZGzFMBCshc2fxapgt+wN7EdnX5t29fuvv3KAVlzgjEdOylt4R7z9iGvTnXx2w7In7757n85z36bzWIeP0GKZpsYPtUAppMnstk2/9AuzPQ58nZdcIgiCIAYCCoAHESiSBrl7IsydDua8BXJLAJt0OY+POwF8yAcCqrwnV+fDjJ4WBwfodgb9sW8c+CdX8yElRJhcVRIVt3Gz9Cq+vAQ+wsPXNN+IXf7NlH7TvrBQi/lxNzaJZSP9kTeQcTGQ2r28f8JakZQIVY+tbYNVDgfcOB46hNM0EJAarvQNy4xRfoGO27BPZmD+858sSKUvnAOk8JV2ue3fWRWKwPjyeLb8r0oCa6kxQs8/J6khjRngzaDkle2xIpdBLjRkRmIUKsiKX7qgFxt0sLNZjGjgA670jMHf/TrxDfQlYQGh50YCUHqXTIpP19oFgvVXm/efp9MBmT/L0CbLfp/MZO5/eiOexri+oyew1TF69Vs6zsBJJoLMH8uTxkKdN9JTpApRdIwiCIC4cCoIGCN7ZDeP5rb4SJLlxCljNCKhTJ4rNd3ER2JBKp5TD0WckUpAXz4ZiWlnb6nQaTJHFMWd7wD8969WrLF/oEcx7SPYDqVS06L8zSq/DoSxpBO/0N0/16JLmTwe3LJHVCWg6KsWrwQ0zUFPDT50JtnK2KdKgrmwCG1IFHh8eWM4mN0wEJCk4SACEE9qQSmEw8MY+3/nq8gXgXT3BWaIXd0DK9FgKzca5m5Jm1kX964ehKAqMTbsCr6ev2QJoKljM1S/HbS6RW7L32VtFmWOOUx7v7s1qrmwThYDyRnnOFEijb4L+3KsAh8+lyx2UD0jpUSLlvB+QJMj3TYMiTRcBtWmBDRbvPw9s6JpdD1hcaKUKDcgK6BNU8LEBsKqKUD0VTyTPOdNxvRG1fm7CShp9JbLXe3aNIAiCuCAoCBoAnLINe/Pp/kW/PyUChPc/cH7JlGrjUB65D1JluXAFA0Tvlgj7WKgy9Gc2e7+MEp5nsgT6mpfCRf/LFwafq6nA4EpxvCxB/eYyWK1HPb/EIq2DH/0YJlwZEM6D+8+YVqDmRlrVHD5/AOhPQ39mM9RvfTk04wUA8n3TIgZhsD7sgHXgL+Hnz58eeKbV2g55+qTgQDLTlFR/9iXvSWldBBo5vXg812uYBBYfDm5kVyTSye+l3V4DBHCwqnIgpiH9L//uOn8frEMhZYF31UNZdg+MDa/5SyAz5UXSnfUDU3pUHPO4HOai/d2q7HFB2A1vz7G/UN5siztzdp6ZmTA91blmOq5X8unRCi1pBHDdZ9cIgiCIC4OCoIHAXYYT8Yu+/Uum1dou3Ktsy95C7GNjmv+X5ogyNKu9A2xQhTBPCApA6rKaJA8ZYb25eXekYYKnnM2VGVJnTxb9jZLpbLD1+MOBmaK8mqdMpiBIl+SM0doORZ4R+J2jS4lX+4ID9/myEZZHAqAb0J97JRtIxlQgpYN39wR6Pkh1NYBpRs5XbZgEVlEK84+tzv1HmUtYHx6HtqQRxvqd3neqrgbqioXQn1offX7GRIFVlsEIyNYB4j2TpwUbeZxz6VGh+o+Q40IDwnwBWdR1Xe/TxcrMFJrpICIosKSRsmsEQRDEhUJB0EDgKsuI+kXf+X7nHm8pR76yjv40IElQljQKIX1mkxAVRPDjJyHdUQt56CDP9YFMmV7DJPHfOcGJ0jQT5s69wYYJjEH95jKgLwnOOWCYUB++z2MkgPhwQOewjp2ENO5mSPU1YBKDsmQ2rA87YGzc6WST+HFh5Wxs8mbB7Eat+pot4rgAXZIHXffdh+MItmYLpIfviz6/JyAYdBZE8fZuWtnkZOTENbK/TEu1cciNk4GooAoQhgaptEdbFZrV01QoyxeAd/ZAnjJeaMEy+gjrUBvAAO3bK8B7E15r8NwyQ8MQn4VYhZst+wA5Qtx/DqVHdlbEfP9DsIqybJPdrl7I48Y4QUFo9iSq31JEQBY+nutdOM/MTKFaqaBMB1k8nwMFlDRSdo0gCIIYCCgIGghcZRn5fpF3GmaWuEo5oso6NBUoLhLGAm1CbK9OnQhRElUBfP4zMNZt9wU5yuJZomRNU6EsmQ3ohuiTosjgiX4AACvSoCyeDRim0CEVxwAwGOu2B8//UJsoDeMcVst+GLnlYfdNg/7sS9AebQZ/8z8CG3xq31kp+icpMqApMP94COyWUVDnfhEwTaGTialI/+jZ7EbezOPQpiqQF82CfLrLV/KHtJ7fqrmoKPBjn+YH8IxltbZDmz8d0ohh2Ws+tR7aE1+KvBwbUilMKVwZNDa40n+gnVV88w+hWTnrYBv4p52OTXegdsKed3EsMkvJyst82iP3XM4V692DvtIwedwY71oEZU8y72coERtlz3h9/SJzp8hAXz+0b30ZqCw7583zhdg0k8XzOZKnxI0NHQRl+QIKgAiCIIgLhoKggaCsBNLtY8GGDwWrKPX2scn9Vd4whDObe+PtLuPJ/aV+UAWsw0dhtR336Syk2jikCeMgNzdCSemiCWdMg9XdC/7Jp7DaT4AHWFADImhho4dnsxj1NVCaZoF/cjr6Xos0mNvfDmyMCs6hPnyvT8sBuLUpt0K67WbxYV8S5itvAoBzT3LjFLBB5aKELXOO1RZRNldXA6vjU0hjqmG07AvOinX3hhs31MZFA82c8d3ZA/dnuUERP9Pl02pxy4ws8zPfbYU0YZxzjDuT5LO7LiSr6GoIy+LVgKpC/eoiwLSyVt/dvWBDB0WPt2R2oB23VBsXjWUrywrKYITqOj48DvP9DyGNGQGk0t6siGtc62SedzDPRnkg+yBdiE0zWTyfB/lKKavKac0IgiCIAYGCoAFAKimGsmgWjBe2+frY+H6VLy4S2RRD95yvLrsH+vqdkCffGakncgdUjtYjpSP942c9c1JXNYdab+faUzs2v5oK9PRF3itT1Uh9jbJwZmCw4Z4vEv1C7H9fg7+MLV4Nfc1LnnlH3YfcMBGoKIWx+fVQJzzplpFglWWhxg3o7Mm61zGAVZbDOtrhWe+goAhAcJapNxlqDS3Pniw0PDePhLJ4FoyNu0LvseCsoqJEatGUJY1gMRU82R+trdINSGNHe4Ig931rt4wsLLgI0nW45mes2+ZZE19W5Dx6ylw0CtHrha3JhZx7nUIGEwRBEMSlgoKgAcBKJGG8uD2wFw3vTUL964fBOESmpqQI3IwBhiWyCvav4VUVUJbOgfHcq/l/+XcTU8FlCerXl4pf2vcegDx5PFBaDPXxh8AYgzxnCpQFM8BNE+AAVBk82Q/tiUeAmAaUFIGVFIMBsAZVRmZdeJRuBADvz1/TzxP9YDUjwCQJyty7wWd/AdYHx5z78Rgt2K52kgSpYSKU+dPBU2lAlkWZU7IfTJLAqodCX7sV8uTxfivungT0ZwNc8o6dgHXsE8i33SJK2mIqUFkOfroTbHAltL9+GFyWgb4krEPtviA0KDMk3VEHlBWDIbPuTTPBJQno6gW7oQrQDWj/6QGgSIP10SeQZkxy7okVxSDPb4Cc0sEkCeJhRa+lPQdPL6XpkwBZAistBjct8J4+oGhQ/p5HaQOoKoP2na84Nu1Wdy/0tVvFfReqC0qm/BnNijLwE6fEeuV8Z506C8YYpIxRyJWwEXZ0PD15tFZRa5Jvva4Qi+crTbNEBhMEQRDEpYCCoIGgNwHrw+PBv8TX10AePBnpp9Z7sgrK4llIr94A9CZEKdqSOYBuRGZRnF/+3aR0mDv3Qp42AfyT09AeWwZjSwuQ6avjs3VunAz9f63NzsXuEWNvMPpTUJrn+Bu81sYhT5sAdEWYCABg+bQjiiJ6IH14HGm3ZiiTJXFbcAe52mnf+QpYRZloIJuT1VGX3QN9zRaYORtV+Y5a/3iuzER621vZP78YoK9a0ihMH9wBkL2WT63PfnZnPZT7p/kbw467BcqimUK7ldtHavZkpH/2XPZ5ZMZN/+914RbmNpmsor5miyjBjOilZLy4A8rCmeGaHwA8mYK57S0oi2cJ6+/ehGddC7YkLonQHq1cCHD4ezblZIQu9kbYSiSB7j6hP8ro0FBSBKmkuPA+NUD0muRbryvA4vlK1SwNZEkjQRAEQQTBOOd5fm6+cunu7kZlZSW6urpQUXH5/sG22jtg/vlIuP6mNg6Wsap2fyY1TISxeoPzZ/m+adD/+d9Cr+N2Jssd1x7PatkPFq8+t7lkehFJJcWwPj0L68hHgGVBGnUTeF8SYBKsw6JPkNwwKXJsqWEirN/+IdSmWLqrHuyWUcCpTp87mRSvdu4hcvw39weW5AXdGwCo3/0KePvHXqcyzmG9fQDW+0ccBzamqqLJbI6eS6qNQ26aCaR0oLsXKC4CNwxROicr4hxFAYYN9gVRgNA5ha5ZfQ2U5jnCMl1TYbUdh7F5N5DW854nN06G/q8iuFa/9WWYr7wZ+cz5Rx9DurMu0Pgi6F1yv5vSXbdCGl9XmCaoqwfGr18JnIvywFxYBw4GPz/Xe3gx4Z3d0HMbG2eMO9iQShgvbAt9f93vV775WomkrzGtM9YlutcorvT5EQRBEMS5ci6xAWWCBoLiWOH6DddniqtJp9XeAaVIg7qq2W9dbP/y7NKf5GpU7PGMzLXOaS4H20SGp6QY4IBUPQz8TJdwMCsphu7KVOTT5+hrt0J9tDk7rl36NHa0KNEqKYL14XEYG1/zZD+0v10O88BBMFmGPH0SwJin+azSNAvSyBvBU2mhgxpd7StPCro3adwtYJoK88BB76Y30+yUjamG/Jlaf2POnL5OCkQ5I1dkMMMQLna6AVSUin5B/SkwXQ8OQqLejYNtIuCMV8P69CxYRXnWdvyjE6JJqnst4A2c1CceAdIGmKLk7U2k79wD5b6GvCYQvneztR3KolmFb4hT6dC5sIpyWG3+slHnXS9QJ3O+JVy+xsb253bJ6cIZBfepyVeadyWU9UVCmiWCIAjiOoaCoIGgrAQ4dTb6mIA+MDyVFv+RKcUyNoZvxKWaEWA3VIqyp1wL6NzxwnrORMwF/WlRGrN+hy9Y8JQB5ep1Ms1D3fPRn1oP9etLId/bABZTYWx8LdLowTrUBmPjayJLVFkG3tUDaXydaN5pmWBDB8PYtMsrqA8rT3Ldm1RXA6VphihPy930Zv4sz5kMY+NreXVYPNEvmqDaWSq7fG7ja7DaO6AuX+BYjxe03m76+sXa58xTGncL2IRx2bXIaJl4dw9gCltzc/fvxfW/vjT6Gpk58LNdYPFqaAtmgJ/uzP8u2YSU0AUSpXWxzEibbvSnw8+153YhJVx5mnEqVnRinBVp0P5uVcGleVe0vuUq0SwRBEEQxMWAgqABQCophhXU58VNgIsYi2kA8lshK00zwSrKwM90++yYg8bL1xeHDa6E3DjFm0kpLRK/WAcFC5x7TRnczUNXNTs9ahx6E9B/9hzU73zFF1S578s9pu0cZ7y0W5Rsbd4tMkh3+LM0YWPY96auWgJWVQHzwEHwTzvDdVaH2qDc35A3g2ICYMUxGDv2eK+beWZy4xSYbx+Act/UwHHyPQ8uSYHZCTZimE9fZCPVxiHPneJcP28vJXsOsgJz5x7Id9QW9i7ZnIt+JerYqgqYL78R/q4/MDdy6Au2nc6zsfcFf7mUl0AaNiT6mByuWH3LVaBZIgiCIIiLRbTVF1E4lWXCvjeAQBex2jisbmEy4O6Jk4vV2g5WfaMoy/rwuOhrE3aN7l7nWlHHmX9sBc9kL6Cp4ljDjPyFXIpX+8eqqxFZiaDrxKvBMlmegsc0DFgH28CqKkRmpb0D6O4reAz73vTVG8AzgRr06CxM3k1vxoGNK7K3hMz1zKQxIyDfPR68PxW47vmeByQWrMvI915oWva4D49BqqsJvkZdDaxjJyDV14Bn3jn7XQmbk/1uAudhS52xuA6eOI+8Jxg+6w8vhZRwRZFvYy/L4X+PL7U998Um4jldc/dKEARBEDlQJmiAiKr/t3vDOJ/Z7nA/X5v5JE8JjmVCGjMiq8dRFLARw7KaipIi0cT0jf1QHpibyaIE9Kmpq4GyaJbQx7R3AC2Asng22KibCihD8s5Rqq8RPX/AvRoTt34nn112TPU0loXtLFdSBHP7HrB4dXDzWSBrsRxToT7aDN7VA1ZVDv2Zl8QYPZlNfL6sWG7GI5fiIiiLZ4Gfzil3dJe4lRQJU4KPTwl3vkzvHxt+/CSUpXOFjXrA8+Cci3K2kiIwSQJPJAGLi+ca5eaWU/4oN04O7oXUOBn8dBfk5tsAJkH95jIgmYLSNBNWe4djxCCe3UxINSPAORdW2akUWHFR0OUdgvQ5zt+FD49nnxU4mCL7s5Bu8gWlF1rCFdWDqDYOfvIMlAfmwVi37crU8eThXLRSl0KzdKXZbxMEQRCEDQVBAwirqoCyuBH81NlsL5qPT4LrOrTHHxa9YIqLwC0TMDnU5jlik14SvcnkyRTYqOFQp04EZCYas67f4bMYVprnwNi5F2z4UECSIN83DYo6Uzi86Qastg6kf7IGUrxa6GnWboUyphHGhteE5iTq3gZXQntyJZDWwRUZYAzmtrdhHW7P6oMkgA0ZBGPDDhjrtgmThyhSulOSJdXGgc+MBTRVmCNMvQu8swe8O9u8lQ0qh/qVJsDifovljNGBgywaiHJwX0NW5xx39izEgQ3FGtJPbYC2ssn7pR1caSpYkQa5YRJkwwA/2wN5fgMUJoH3p0SQVRQDuJFtyGoaYIMqYR0/CX62C+ZbByBPudPn7ubTY+U+kyINcuMUUd44uBLpnz3n74XU3iE0Wo89BHAO48VtPpMF7Tsrgd4kUFYMY/PrYBVlfnv1EM1NoD7n9rHCSOGucVCaZsHYtKug5r8ALrxEK8/3oRv/jDucdEPVla3jieB8tFIX816vVPttgiAIggDIIntAsRJJWAcOwXrnL6Gbalvvon59KayDbeIX8rJimK/+NnSj7rbljbRNzrE2lhungB/9OHRcYTf9B1iH2vIfe1c9hA0aFxbLubbSigIO7rG3zjfXQNvwu24Fiw8HEv0wXRoc+3u5aSbMl3ZHWmTz9g6wm0dCGnkjzLcPQL57fHjPpGdfgrrsnsBNvzx7CvSnXhRudIPKYb1z0Htvx0+KsTNr6Jmn7baW1qE+9hD46S5Y77wP62Cbsy7s5pHgHx4DG31ulub250pzI4z1O4V2Kcc+PRf1Gw/A3PW7cJvuh+6F8fyrYKOGR9t5uzQ3ViIJ47lXwYYP9TYI5vyCrdrDGChbZ6dPULIf0Lx9gq5GrjS76yttPgRBEMT1wbnEBqQJGkh6EzA274LcMNGnt5Bq46L0qbsP6l8/AlZaDN7eAX31eui/WAt52oTAc+SGiU4JGJBfJyJVlHmPjdLTVJQ535st+8Sv9yFzMDbvhhQfLkqnACCtw1izBdB1mG+/A331ejAwz9xEX6Hgtci9L2dO8eFgiuwLgOzv0ZsMDICc88eOdjJCZst+WO8fgb5mi8jCrGqGurIJ6jeXQV48C4hpkIYP9X6/agm0b6+ANP5WsMoySLeMhhSvdkoM7XsxW/ZBvuducY0A0wazZX+mXBAA52DlJVCWzBGBcLwaVnsH5NtugXWoPf8zHTvat37K0jkwXnIZDOQr+yspDr/GwTagL+kE5ZHHuTU3fQnIk+/MvsfPbIb+1HowVXX0WpH35dZzZTIE+TbGdiYnV8tS6PnucaSbboA0ZiSkEcMg3TDo6t6UX6hWaqC50uZDEARBEDlQOdxAkkwJi+i1W6EsuwfK/OmiBK5Ig9XVC/SnIX/2VgCAsWGnZ4NoHfsE8r1TIc+7G6woBjAGntJhHfzQe408dss8nc7qSOxj7V49OX1ZuG54+rXwvmS2ZMtdTpXJaNgW0J4eL5IEqWEi5Bmf8+trcu20i1SwohjMA4dCS7x4ol+sV8jmGckQG2obVQYrK4ZcFANuvwVWVy+MtVsdNzsb7dsrwHsTkOc3QO5PA5l7s9o/hrn3AOTJ48EHV0Ke+Tmw4hjkhknQN74GZfFsKAumg6d0MFmO3ORr86dDqouLLAMA9PRBaZol3PZmft4xKchroc2tbP+ozDOBbsJ673D2ehnzhbCsC2dM/KGsBMrD90IaXAnoJpBOg2sqwJh4b/LNpScBy7RECSfnga6GzjPKMxYriUH71pd9JVj5dCSXs1ztitW4XGl211fafAiCIAgiBwqCBpLimOgfkymvMnJKuaSlc2Bsfh3KvLuz2Qy730zLfujb3vIcLzdMBD96wqufyCv0j2WPVxTv+DmlZ+xznwE/ftL5XF3V7AsWPGMXacFjjbsFyoIG8J6AX3fddtp/tQy8s9dX2uW5RnEReFSgk+f+oZtI//Tp7Nxq49AeWyZMKFy/PvMzXdCf2SzK4qZNgP7cK445QNg9ao8ugbFxl/Nc1VydUA78bBcg+7NaUn0NlKZZoiFtIfdkWD4b8txMSL4mtgwAykqgPb4MvCcJY8Nrvjnlux8A4P1p6D97LpONmgvr41P+g+z7yXdfpcU+u+lCdSSXw3b6ita4XGl211fafAiCIAgiByqHG0jKSqA0zQrt+WOs3wlWPdRjyxzVI8hs2Q82YpintCqf3bLV1QPzd3+C+vhDYDdURs/nxe1gI4ZlP8szNg/55Z+NGJZxRDsaPbfDR/NfgwGIcGyz2juircgPH/Ue39oOY+MuKMvu8R5cUQZ1VTPkKeMdfZOdMYu+R9fn+Tb55X6DAUCUAxmbdoFzXpClea69OhDgapfJujllfY89BHVVM1i8GvqaLeCmCXXlQlgfHA8uNTzYBrNlH7hlhc+lrsaZi/3++NYVmWc07hbHlCJwrAALZiuR9BkW2HPT124VWZjLxJU8NwBXnt31lTYfgiAIgsiBMkEDiFRSDNRUw1i3LfB761AbtPkNAMvGntKYEbCAbAmaywrabtap79zjNO3kHaeC7Zbra6Asmg3e1Qvl/gbRpLS9A9rjD4fPxy7ZqqkW19x7AGpmU+uzcl4wHeCAfPddkGd8DhwcrKxUZBh0HXzczbCOHIU8Y5L//PoayPc1wDr4IaQRN4J99lYYm3dntTS2NfPIm0Q5XEmRsCnevMtXMsc/PgX53mkAh8/lTGkS9t+5ttJWazuU+dM9x0JTYL3f4Vg1S3U1UFcuBMpKgXg15Lvv8jwLKV7tyQwB+UvQoESUyx1qgzx9ktBGvX0A8oxJkO6qB6sozxoM5Np+u56H1dUDadwtXqt0TQXKisEkGTzZD1ZZKkwmNBXQDbCSIqCiPFLzI8+aHGqvLjdMhP5sdi6562pj7j0A7bGHYGx5A/K0CX7bbpcFs6e8TFPBRg0HPjzue+7WwTZhZHCO2Z8BK18rROOSez+XsFzuUthdX83zIQiCIIhcKAgaaEJ6utjw/jT4p51iI9t2HKyqXAjLwyyEbV1FTIW6qhlWewfSv3wB6teboegGkDbATRNW61Gkf/wslOULYK7f4Ww6+dmu6PnYZWG1cWfTIk8eDy2jZ4JuAGUlMF79Laz3jogeMP9pKSRFgbFplzcQqasBRtwIdvNIj64I5SVCU3T4I+ivvOlkXNRZXwBkCay8NGOrvT07Vn0N1EebRX+lzJpKdTVQ7puG9C/WQn10CZT7GzK6GibWxW3/naM5srNvUm0c8tQJ0H/6a8+xVttxyI2TYf6mxef0pi5fAFj+IsF8JWjo7I5ce1iW0EzN/DzYoEqYb+z3BXZy4xTPKVJtHErTTKRXb3DK83LfHbcznVQbF/bsEgfvSuTX/EgMKC2B3DQTCgeQSoNnmrnqz77kD0oD+vrIX/ys825YR456bbtLisCGDQarLA8uL4uwz+anO8GLtIJLzwa0fK0AjcvlLpe70qy9r7T5EARBEIQbCoIGECuRBNQ8S2px8K4eyI2TIZ06IzIiQS5oEKVyTslVSvfqQj7tgtne4bMglirKPFokyHnmkxnfuebk8TB37oEUrxYZkIaJsF7OuJBpmcakH52A6bKLduad2cCz0cM9c9X+y9dgvNKS1UHZOqGde6A8MFeUZx3yl2eBA9qTK4DeBHgyDau9A7yzR2yqVFVstCPWzq09YsVF0J5cAaurF/rarUBa964zEO5IB0AOyHi4jR+0hTOBVMqZp75mC9TlCyOXnlWUiSyOacHY+FpgiZqzBn1J8ETKWQN5wm3+8ryA+7da22Fs2All6VygpAg8FR2kM01F+sfPOn9WVzVDX/OSCGSWL/RlK1lJka/5qHTrzVl9m0sTZqP956/CUhVfwBA0/+xJKlBRBuvUWbDOHmHMEJFlsRLJ4PEz5WthFs1OJifRL8oyGQNkFlmiCQCIaZHlcpfKEvpyaKWiuNLmQxAEQRA2FAQNEPavwGzU8PASqboaWIePitKqp9ZD/caDsFzZDzdWazvU2ZPF8S4thvN9eweksaN9JVq5v8znK9lyj2uX3/HM53a5k+HemL7yJuRpEyPLvNRpE51Nr1RXIzbvIbbWrKI83Mb7UBt4Vy+Q6M/2wGmcIkwdLB4+h8x9OHOojcPq7IaxekM247Vmi7h+vBryHbVi3WqqRe+aTImcezzZMIPXMa2Dt3c413IHpfnW3nzviHP9dIhZhHWoDbA4cOMQ8AOHRNBUUgSp1v/sw+7fam0HdB3I2LJHNYe1bMc6+9xjJ6A+2gxzxx5/tvLRZvD+NJQH54mMof1rf28efUwyBchSeHlZzvzt4Nv8zRue9ygyy1Jg+ZqbsMyU3DARvDfpC/bc84Ain/P1CIIgCIK4fFAQNABYiaQwPRg1HFJNNVAXh9w4GVbrUcduWRo7GkyRxWa7pEicmLPh9CEx8OMnoSyahfRP1ni+Mlv2CfvlHHIF8+beA1C/3gw5mRbWxbY9dqbRpx0MZOHZcip4gypbFyNPGR8970zJlVQbh7KkMbokL195VqLfY0Bgl6BFOsjlzmHxLOEOB1emYebnRTPVlv2eACS0HCvZD2XxLF/2xVN+BkBdsRBgDNahtsLWPq1DcplTBK9BUgQNBw6KoCgTFBRy/9n5pyBVDwPqasCGDvasBZDRVC1phPFyi+c0VlkOc+fe4IyTxMBuGQXe/jGUpXOc66AoX9ZEzV9e5pq/0jRTzCEgWxiaZclojIKs4c2Wfb7rh2aOMvfNbh4JefZk57o2Un0NlMWNQFrYzecG0J75EARxRXHFWt4TBHFJoCBoIMg0jfTZKtfXQHviERibX/d+XlcjtCR275YQWJEG6TNjhdg/d2OV1gM3W1Z3b/aXftuu++UWv8j9vmkevY1DSTH0X77gfM6Ki7Lf2RvTfDbdgysd/RL/5FMgFmGHm89hLdMXx7mnTAma9sQj0XO4oQrat1fA6u712WNbre1Q50+H+fIbecvJHIqLkP75WsiTx0NtmARWHANPpjx9lKCpAAOk8XWQp08Cqyr3GkAgZO3zrAFnEswXszqvsGefu24eYhp4ZzekIVWwFBlKc6PI3qR08Y+/qiD9v16APOE2qJ/P9iRCSVF4pu6gyPph+FAYz73qHCdnsnWhhhGqkrdslA2uFJbd9hzCMqZhWZaSWKg1vLp8AVCS805GZY5sg5Kn1kP77lcAywL6+sENQ2jxfvSMo78K0zORJTRBXFlcbg0fQRCXH7LIHgjMYOto62AbjBd3gFUP9X5+qA1my37HIjkIqTYO66MTYCOGgR89EXgM7+rxWRAba7dCWTwrk6EIsd8+1AbzNy2QJ3szOlJtHNb7H2SNCDJlZM4cbf1QlKVzXQ3MP7ZCX71eBBGSLEr6Qo7n3f578MynXfxyLzdMzI6R1mF19kRbbRsm0j9+FsbqDYHd6RkQWU4nxatFJqFxCtS/Wgak01AfuhcAoK95CdyysveYWS+5YRLM1/fBWLcd1ofHfcYRQPDa8+7eSNvvIJc5q61wW23bOt22cpYqyyENGwJpxI2Qbh4JafhQsbE/0wVz5x7oq9dDf2az0HXly1bKknjHXPfpe16uechzpgh9TZSFcm1cvEOFziEoy6Jpkdbz0HKyVYVkptI60JcURiHb34L+i7We52+PbWvMnPshS2iCuKK44i3vCYK4JFAQNBBYVv4NdcDnLBaDfH+DLwiQ6mtEeZEkQX9qPeS7xwduKFlVuX+z2ZuAsfVtKA/Mg3xXfcHzssu6zJZ9nj8ba7c617CDn9BNbn2NbwxPEJN7n3U1wfeQO1ZuD5yVTZAGVUBZOid4o90wUZTRRRDkaubBNETZXXsH9P+1Fvov10F/aj14ewfU5QsCHa6keLWz3u7/zsW99uI5lkGeFhI0hLjMRQYaOc9AWTwr+4tnQEAIIDwoyZf1KykO1EnZz0v79gqoK5ugrmoWFuCDKkQQlrFQzr1m7vwLmUNgliWVjlx/5D7/fJkaew7FsbxZI8/fq8wvy1RiQxBXEIVoBgmCuOahcriBIF9pklufYesUaqrBJAae1iFNmwB5+iQxTkkRWFUF0v9nA+S7boX69aVgjAnLYjCRwuBclDEVaYCqQnlgrjg3U9fMZQnp1euh3js1el4xVZQcqQo452CV5UJrktI9ZV76xtegrlwIJivAxNtgbHrNcUVTGyYB4GCDKmD+5UPHRjnXqllfswXq4w9BWTAD/PRZQFbAwWHu/SNY9VDI86dDQSY4kWUAAD95RmhsZAmstBjctIBEP3giCd6lgDEJ8uLZUEwLvD8F9Ged2eSGSZEGFZ4yvwDYDYNgvPR6pFucTyhvmZDnT4dcPwboT0F9tDmrQcl9R2Iq1K8vBbcsgGfOXTQLCufgyRSYpsLqFk526rJ7/e9PvBqQOOSlc6Ho2WePmAb0p6E+2gwW0/zlgCEZj7C+Lry7F9LtY8GGD/Vpa/jxk2L+UUgMrKwEKI6BVQ+FNChbZsI1FUrTrKwTm6bC+uCYsGl3a3kqSoU5SEBZnlRfA0iSyHC5A40CLK09ZILAQOMD+weA28eKefYmnb83Qc+XlcSgfevLZAlNEFcq5/q/DwRBXJNQEDQQlERvqJ1fkTU1VKcgN0yE/twrTgChLJgBxnlWt+I619eIdPZkbz+d2ji0ry32/9qdS0rPuq5B2CED8Fpxl5U4/Wis1nbRJ8gt9gdgtX8MvvddKAtmQBo6SJTAubUyAJDWwZgE3t0L/dfiPlFWAu2xZaLXjW2pnJm/snQuzNf+L6z3DvvWyXrvA8jTJ3nuWf2rZZ55R/bwmTYB5vtHwjfWdTUiLgnTwrS2Q7YsIZS3Xeo0FWzoYPC33kH65Tc81wvUiaR10UQ093lm7jH9ry+KPkbL7oF17ISzEXfen70HxNrlNs3NZH70Z18K/jUzIuMR1tdFqovDeGGb751VFs8C7wsqRcu+q+kcjZxdbx9Wj68snQt1ZRPM7W9nr2cbQTD4ndumTkD6B09DGjPCW8ufL7OT831oc087M7Xvz1AWzYLx/Kv5+xqVFkMaNiT6+gRBXD7O8X8fCIK4NmGcc365J3G+dHd3o7KyEl1dXaiouHxCRiuRhLFmS+ivyCxeDXPnHsiNU3x9fYKOAwDtu18RmQiX2LzQc+3P5KaZMAP6EAGZbMjo4ZmyqkmQxo4GuAVoGviJUzA27wbSOpRHm8VGvZB51NVAuutW8DNd/qxBxymwUTeCf3DsvNYj93Pe3uH5PnAsO2tSO1pklzJNZc2WfcId7pZRvt5Ajm5FlqD/9Ne+edmoTzwC/ZfrshmLyjIRsAYFVTn3ItXXQJo6wRcABR0v1cbBbh4JaeSN4N29sDL9mZRVSyLPlxomCj2U+/P6mnPuVxP5btfXQHlgnghmXPOIfK71NVAeutcXTLi/l+6sh7Fum/cLTYXSNBNs5E0ZjRBzSi2d4N91f1ZXD4xfvxK6Psoj90GqLA+8X6dPkKYCkiT6BGla+Jzdz+s81pggiEtL3v9do7/DBHHVci6xAWmCBoBQfUOd0PbwjlPizwXqRAAAyVR2Q62pkMbdHH3uuJvFps31GbN4qG5EWTRLWDjbupf/swHWkWNAoh+sogza33wJ6pMrIVV5+/hE3sOhNkijbxLj2eL6jI5GWTgDUrwa8t13Qb6zVjiI1ZzDeuR8nvu9ufeAYwjhhg0qBystBvqSYKXFkMbXQf3S/ZBvuwX6U+s9OiN1VTNYpodTrtV4LiymiUDqjlqwilKwtA65YSLkxime55B7L7ZtOJMkf8DWOAXqqmaxRnfVi0Dn41OQRt4kNDbVw2C1d4i1q6qIXrucDb6wwJ4DfNoJ6+Rpn/DXSiTF5+0d3u/z1c6nUr53LPIdOdgG9CUjx2QVZf4v0jqMddvBJAn66g1eU4rM2slTJwInTsP6+BSQ7I/UTKGvP3AdpBKRxZFqRkCqHgbpphsgDR0iNEZ5dECk/yGIq4PQf7Pp7zBBXFdQOdwA4ZQSdfWCn+mC/Ut1+qe/hnLvVCjz7s4vxndrh+x0fKa0CPn64iSSvrIc3p/yancytsdWewd4XxLaNx+Esfl1b5mVnRkCAypKwM/2hc8xAH62O1BHY6zf4cuGsFvHFL4eQZ+7vpcnj4expUUENQ2TAMsEGzoYxqbXYLjslZ3ml53dQFqHuXNPtilnDpE2zxITmaQcm+3Q8reYCu07K2EeOAR+tlu4sdlElElqjy0DT6SgLl8IpNLOcTxPbyGeSovyRgawQRWw2jqQ/uHTnqxJvtI0ddk9+WvjEwHvWEyNPIXnMa2Iesd8/aFC1k5dtST03dfXbIH68H3Qn9lcuCVunnVgJTEoIYYZBEFceYSV/9LfYYK4fqAgaIAxXtrt+8XYWLddbL7nT48+OaMdkmrjQoANODbX8j15TA7AnNI2O9BgMS10oy+NuxngInsjmjzu9wZDO/dkNEI5vYzyOXXlHp/B7rViz8M62AY+6wvRQ4Vdy/7c9b3dyBXvH4GJTEnWb/8j0tggEg6RMXCdA7iCKIv7Suk84+f2GUrpQHGRKJmqqfZkO0KtzFvbYWzcBXnJbOj/89dQv70C5msi6Mq1Yc6FFcWQ/tlzYh3e2Bdo366v3SpK0yKsYpWmWdHrVBzzvWPqE1+KnluhTmxB5+Zk6MLWDmDRQa5t9x7VcNVNvjmXFtOvxwRxlSGVFPt7jBEEcd1A5XADSR7rXKYpeXu7SHU1wu2tOCb0EXZpkSLnPTe37IqngzNPUm0c0JRsViBzDd+G0jB8PYHy9Qhy96fxkfMLv9V6NG+PoLDPfd/njJ2v9BCGGb2end0w974bWC5n7vszYBZuiy7VxsG7e8At0+n/xAHn3vPNlRmZbbxhOsdFPofauFOSd6Glaf8/e28eZlV1pou/a0/n1FyAEimQKoSqEo1CqNIAQhVVFJMCBRSKxoB2o51EYwbT9z7J/eM+3X/07eHXuemkO9q5wU7QmyhRQHBiEhAVuIakRaM2FEgVMgUEah72sNbvj7X3Pnvep7AQkP0+j4/U2dNaa69Ttb71fe/7QhLD/Xwqy/ji33s8Zq6yqOMVZWAdnaHHLDNg+7OQ/sWNj3PuZCWJG+VrlPgAJUiQIEGCBFcckiBoMBFTMsO6eiHWVgf7Ai1pgPiVGyHeVQP0qRBycyAtngmunwygrSPYa8frq6LrnHdy92yQwrxQHxaiGQ5VOwpp5RKIEyohzpoC5fEVkFYuARTZ50cT5REkLWlw+7t44dzhV2RAFCAtnAF55RLIDzXZfBpLHY6dPBPYdnbiDMRZU2Ds3c95NA81gQwrdj8rpmwPhsE9mkI4I/qaTZDm17r5TU+tBTt+GtKdNfEGnubzhfFjITbWQSgrAbp6IC2qh1B1E6Dq/N+VZfElhta86sw8M8onSFpcD9bZHTwO+bmQVi7h/j2P3MszXgE8Jhs9fdG180UFkO6e4z5uzdUwPs6n58O9oWqrQUZdFzjPpcY6l29VYP+845ONDxEQ+91NOAQJEiRIkCDBFwtJOdxgIqZkhuSkwFQVwoQKiNOrbJ4C6+gEO9cGbfVGCKUlkJbONi9AJlUviNCe2Qj50ftc13qlqMm1QyDOngL1Z78BVI1zIuq+Cgi8PIi28POVx1fw3e0JlSDDh8F4YSt0r9Ry0ywIY0f7uRWCAHH2FIjzpgHtXYAsAcUFoEeOh+7Mu3bfnRLKTmnsijIoP3gAEEToL+0EGXEt5CkTuE9QQR6YpnPhhuu/BPrJSSjf/hr0ddugbdsDcc4dbsnruLK9fg3Gjt9DnF8DiRCws+2+8WRtnfy4IIL19fP3p8jQX9jK30HUu76mGMpfPwjIMvS1W93iEpYM9uoXIU6eAHLNkOh75aR4FqrYIRhgei853wu5ZghoWwfUJ9ZAeXipfxwckuTedx3IYwK4FxUA4dZKLjxgz1kekLG2DujrXwe5fgRk8zgZUgT1334bzsdZsRDa0xsh1lRDaawDNJ1/dwQB7Mw5GJveBhk9ArI1z3PSQI4C1t4FdPW4+u0aEyfM8VEeX8F/7u4F6+n3S7dbyEISN+EQJEiQIEGCBF8cJEHQYCLGcJEZBoydfn6GddzikejrtvLFlqKAnfokUwJWWgL6fnOkrDTr7YP28+fsz4xtezJSyw4ZX+Tn8mzTghk+iWPA5KOs2wapaRb0tVtd3Aqhooz7Gj3NfXmk5QtAN+4EbTke7M1TUQZx+iS++EQEB+ZgC/R12yDcWgn63gHefvOY/P3lMF59075GWrmEBxcuaebJ3HunuTVTMhcRkNGPDvPMWU0VdIdfkn3O4U9sXo+8sgnqz5+F/Nj9oAdbQEaPiLy/sf8gAAS+K7sPy+aCgID19kH+1jJbvtu5QOeleZ2gb/0R0r3z3PPLwXlxvV+zbAyAaxykZXMzfk8B7fHymITKMiClQAuRhqamnDX94BDwwSH7XUkrl0Aw2+LjopWXgjHGg8xPTgIzqu0sCj3fkfl+mNwu53Xi/BpXv1llGaR75oa/h9ISIKVAKCoA7emF4ZTEdZrOgnG/J6/hagASDkGCBAkSJEjwxUBSDjeIiJLKFmuqgK7erHgkNkdBVUGKCyDOmsJLwKxSsKhSIzW4PChUxrevP1Lymp05B2FCBZTHH4D8jbshr2yCMKGCZ6nMjA6RZZ7pMHffvTwaaUkDjN37fRykwGeGSCRrqzdCWjrL7rdQmG/LRcsrmyCMvR7QeEAjP7wUwvVfgrR4Zmz5IOdqyZHnAMiUXRl8aR5ajma+a2PXvniujyzzUrsnnoP25BowU5jC5vOYpW103wd26Vng/HK015Lg1tdsAgCwk2cg3cPL1YTC/Ox5TJY6nBohDR3yroggRM5RIgjBZWR9fdHjRTKiG/b1Qwp5/4LKAu+ZY0uFu76b5ry1Sx2fWgf1n/4D+jMvcdXABAkSJEiQIMEXHkkmaJBhl8x0dHNZa0UBBAL1p/8X8n13Rl/s5Dd09QK5aWjPvgbxjq9AvJOXnmX+Px2SUAvW08tJ+i0Z6V/XLrfDsJTkpf0yvnESyJrO1e0qykDGjIRhlq8J5aWQls3lynVTJ2bOD1DkUr79NZDR10GeewcIAVi/pxQpahwA3p9JN4GdbYc49w5IjXUAIZBXLITxxj63rHRFGaRF9WBnzoGd74AwfRKku2q4bLm3fNAcJ5KbhvLtrwGyBAaAfng4k7VqmAKhtAQkJwXlv/2Fq59BEswozIP282f5/eN4SR65Z9rcCggE8nfu5xp7igKAQZpzB1h7F1ifCkgipAUzwKZ18oBsSCFISga6e6F8+2tgsggQBuXBRbxcK50CdI2rvHX3BjQiA5KTgvLdr7vKvFiU0AUQ3EdVg/bsq6HlcMo374F07zywfpXf33weemLmYr8G5QcPcgnu3LQ9j4VhxZC+difvn1Wmlpfj80qyv5s9fdBf2OrPiDmU4gD4yt4ulPdjG7AOwr0SJEiQIEGCBIODJAi6CPCWzNDTZ/miOI6n4jjOevthbN0NedlcaM+8ZBpmboTynfuh/vKF8HvIUqjnDG77smvxxdo6bCnuuDbRgy2Qp1dlJK6bWyHNr4WehVwzUjKEUV+yPXW49HYECvP5ObrOsyJ5OTBe2eXqj3T3HND9B4JL6ta/nikNKy+FML8WmqfczcVL8oyTWFMFQ5Ehm0Ge+7mzM9wjT8AnVJSBjB6RKWcbwPu223+gBeK0TqhPreVCATMnQ1u1NpNFKy+FNL+W88Me4N5ButeryCpX/D/Pc4PamioefDx6X3R7clIQRlzr+2ygfYAkhctTKzKQlwvdU2InVJZBWlgX/SxFhvrjX2eyVI65LBQVAJ6gJwhCbg5oV4+Lo+UEPXIc6O6Dvm5roG9SrJ+QB1EeTAO9V4IECRIkSJBg8JCUw30esLhCWcr2cs5ODsTpVWAdXRDrbgdtPQGpsS76HpVlQEoO95xZt5XvSoPvTmtrNvkkh8PaBMC362+Zv8a3SXG1Ke58duqMrchGjxyH8couX39IYX74QtZZWtjcCnrslK8sLsqbx9j1BzvL5T2ub9gBsWGyv8yuogzS4plgx09n7jUAmWb3Q/g40wMtMLbucQWZVn+kxnqwts5gr6KDLTxDV1Nt90esqebvOkqSvOWEPT9sxEhDswCVvKh+S431vgDD6ittORHdPovnZGZsfG3NFhHZT7GmmnPNQnyTBvJM+zs2CPdKkCBBggQJEgwuLmkm6Mknn8STTz6JlpYWAMDNN9+M//k//yfmzZt3KZt1wQgre7H4CNrabZy3Qwhoy3GIdbdDuGksL33SNDBBALlmCIQxI8E+PQ+IAoTrRwCiANbeBTKkAOrPn+O74PCID5hcEPRrwbwKRQa5fgTQ1gl65jz/uWwkiChwDsm6bYGmoFZZGADfrr9lXGns2hcsiGDueLO+fpu/I5SWANQAmTQe+ovb3appzsyH9ZllgupFXKmZ47i+YQeU7y2Hvv51u32h9zX7IDXWuRTUbKgatFVrfSp9KM4HQCFOmwjhy2NBCgui+zltkntsHSBDiyA/0GiXMYoTb4Q48UYwMBAArE8FSStgAMTiQp718ggqODN3tLkVyvxasO5eSE0NvlIw57tWxo4CBVzzWLpnDvR1r3MBBEcf7HnoEQNhJ89AWjo7E+xY5Znlo0FEEWR6Fcj1I3xt1jdsh/KDB/ztqyyDtLgB6v95PtM/izd3IWVlEdmtyHkx0GdG+YZ9hvYPRnldUqJ3aXGlj/+V3v4ECRIkAC5xEDRq1Cj8wz/8A8rLy8EYw+rVq9HY2Ij//M//xM0333wpmzZgxJW9kOJCSPfNA9q6IDbWQRIJmE6Brl6w3j57wctOngEZWsjLtxwlUGJNFfSXd/Fgas0miJMncL4FNQCrrKazG0gpEBumuBeYYaVfFWXA2Ouh/vIFSItnQlpYZxLDiU9K2Ju5ECrLgNy0rVbm4sdQAxhaBCLw4A2yDPmRe90lbYoMqbGO83X6VaBfA7mmCOpPnnHLF4cFOwMpNVM1HgAsmcl5Ne2dnFcSAdbbH8qtMnbtA861u0rs5G8tAxMELjS2/wDowVZHP+u559C5NkCUwMBcQhFOCOWlMN5vtlXahPJSYNJ4sPPtPmVB2zfp+OlgiWvH2DGzvfIj93LhigCuDlQN6O7lwaK3VO3uOcDCWs7b8UhDS8sXAO1dnHdlzh31X38Dad50zt8SBOjrXveVZ/rarGpAnwrpnrl8rHr67PbpG3ZAXjzTfX4cny0MESqOti9XGAbyzLg5dAHtH4zyuqRE79LiSh//K739CRIkSGDhkgZBCxYscP38d3/3d3jyySexd+/eKyoIoj29vj8KVuaFnjkP0tbJjUnzcwFFAqEGoBkwNu4MXNQaO37vkiumza0AIRCmT4Kx5z3IDy8Ffb8Z2prXIN87j5eLeXxo5OUL7GBJuKU8sKSMHmwBGIM46SboT61zBEvBi20rc2EtioWhRXZQRg+0cA6IIkN+qAnGS2/YbRIbpvilolWNCy6Ul0KcXwvtiee4eac3MAgJdrKRwHZ/yBfi1vnyQ9G8JJJWoHz7PtBPTkFb8xofx9ISCKUjIH77PjAGzm+xF/A6UJwPY8vugH5udklYW+MMXY/NvtHmVugbtkO8s4YbiVpZHwCktASQZYg1kwBBgLR8AXRnkOAcO/PfJKUEc3VMMN0ILN/Sn98MqWlW6HjpG3f45j873wE2+joYL+7wlS6GyXIjJwX9hc3BAYquu8/PwtsnEP0qxJmTuSy2Z/zJkJhFXByHzoncVCg/T16+AMgdWPsDf8/ALegQtxs/GPdIcOG40sf/Sm9/ggQJEjhx2QgjGIaB559/Ht3d3ZgyZUrgOf39/ejvz+yednRcJnK23rIXR+bFmfmQH2qCsW0vxLtqgoMS82dSWsJ9VpzHDrZArP8qxCm3Al09XE754SYzAAq+j/xwE4yXdwGlJZH8Gbmmmj/Lo3hG0gpQkMvNMc+1c+U5a2d+/euQmxr8BpJ5OX5z0JjSM1E3eMZDFP3HQ4IdY9c+HsgIxL0jGRBICBVlgCJl7qHIQEFurM+PsW0PhPFjbYNRrwqdlckQykbydubeECnxHDTOysI6sN4+kHQKxnsHA4086YEWSHfWQH2am+nKDywEGAKV8bxtsvpj/ZtRGt7vyjLQ5qPB7T/QAvbnc9CeWmufa+/8eud/fi7kh5uAXhXo7eey2KP95W+uMTHviYAgLOh8y+tqoKA9vWCftkF7al2geh0zIsanvBSQ/HM0FIoSyjsDwBXtBoLBKK+7SCV6CbLElT7+V3r7EyRIkMCBSx4Evf/++5gyZQr6+vqQn5+P9evX46abbgo89+///u/xt3/7t59zC7OAp6wliHQv1lTbJHbprprYoCSwDKy3D8budyEunglx7jQQQfAFQM77iL0q/79TwjoIzmc5VL2Uv34QkGWwzh4AnKvCAEAUQJtbXTt/FAAEAdB0kOtHQJ5WZZf/IC/HnTUJ6Je0eCaYqmaU10yE8o3KRvLMQGM9JE0H61dBctJgfX3QVm/MlPFVlkGcOQXoU+1rxZpqGJt2c36W976eIIqMHM4NRp2cJrNfrL0T0uIGCKUjwM6csz2EQpGSXVwfY9c+CJVlIPk5YN197oyIB6yjy86CCBMrQ5XxwBikxnqQonxoz73GM3ajvgR2vh3CQ02AKEKsrfb3u6IM0qI6GO8ezCjzOUu3PJLf9s7vvfMAzcj065NTEMbfAOPlXb5xjSrZs3g/6OqJHkNdzwRgF7LY6urhZXZeWBZEHZ2R8yLw2jD0q5FBMfrVwGOhiCufy6a8bjDukeDCcaWP/5Xe/gQJEiRw4JIHQZWVlXj33XfR3t6OF154AQ888ADeeOONwEDoRz/6ER5//HH7546ODlx//fWfZ3OD4SnLCcp8CGWZz1jc4sci23sh8WyG2NkN7ck1fOEZBcuH5gKkmoXyUhjvHgBrPZEJClSNLwZnTYEw+joebHT3gKka2KdtMHb8HtL8Gm5CGZKhCAyE8nKh/sszAMADHuYoU1I1GHvfg7R0NtDfz8vOUjKYQYGuHhhe0YGKMiiP3MuDEkEEuaYIxvvNEG8ckznHfD/08NFMNiAlc1EJLxeqtASaGYgFlTVJTbOg/ttvga6eeOnvfs3mEdklUaoGpmogsVkNYmcHSWFBZPDLuV3tUB65F/qL26E/v9k1PuKsKRBqq02eEvdPQlE+wAjYx8egmV5QznZqz7zkmyf0QAvY6XPQnlxjfybdPRvGq2+GZj+85W/kmmLI31oG2nwU6v9eDXn5wuhRuHaI3+tqIDB5OmHvk0waD/WJ5zKcO6/H0eMrBvasz3Lci7jyv2zKAwfjHgkuHFf6+F/p7U+QIEECBy55EKQoCsaNGwcAqKqqwu9//3v89Kc/xS9+8QvfualUCqnUZfhL1ku0DsriiA418oCyLxdy0qCH3GVJLp5Lz8CCG1dJmZeonZsGBOLK1LiyIeZn1uLVVlebWMmlmw0G49AR0Hf/C6S0BPqGHeHcIy//w+rXB4fs59jleA2TAVEAkWUwSYTxxw9h7HgHUmMdyDVDgHQKxhv7Ap9l+QSx1hMQJlYCqg7jvebMGFjvx5H1kh9o9HsJARkeSqjs+DaIkyfwsRkAT8kex5oqkPxcLuMddm1FGb/3yOF2m6LAPj0Pevw02K4/Br8LAojza8Hauuw+y9/9OvSXd4YGL1JjfbCkd0+fa06Rwjzoz28JbFdQ+Rs9esoVpEWOYWUZUFzw2TgHOSmwrh7QsPf54nZI86ZDf36zjzc14BK8wV4wRgg6ZN22wbhHggvHlT7+V3r7EyRIkMCBy84niFLq4v1cCbAksG0/lYDgxLlzTQ+2RPqhID/HJr9bn4k1VZnPFBliwxSgMC/8PubCGeAlZWJNFYTxYyEvX8AzNaYPj/bkGhhb90L53nLIj94H5fsrQEpLXAGQ03fH+pkUFphy15R79pjnRHr3jBvtbmNlmbtfgB2YaE+uAXpVqD95Gtr/9yuwj49BXr4ApKiA81YojSw1EsaN5op6G3bwDIo1BpVl4QafQZAk3q+wZx1sscfGfobHI8f3/hztJISACAL3Hwq5VlpUz6+12phF8CuMGx3e5gMtIIDLzyeutFIoHeFrPwA7q2LNKa4QFwFn+duSWdA3bHcdDh1DswTuM5Ou83NBFCX6fZaV+LyRLuj5MR5LA10w+n7PXEDbBuMeCS4cV/r4X+ntT5AgQQInLmkm6Ec/+hHmzZuH0aNHo7OzE7/97W+xc+dObN68Of7iywwugQDKfLtlTkK6seMdyCt42Y/PP+bOGtAPD/OyoIASLWH8WCAvhy86Lb4M86tciXdOh7HVzLqYRHxp+QIYbwZnB/T1r0OoqeIlZqaCmZMDQwrz3NLbus5J4k6uSEyGgsgiFzPQdaAgHyQ3BXb6HOQVC93cE4BnpvJzXPwU1t4Fct0wzqWpKI2WH2aUq+PVVIMU5nFRh3SKl9WpKuSVS0y/Jn5+WAaCtp6AUDoi+uWnuOgFbTlhK/IpZqkZGcrL8QJLARWZv0tV84lSuMj6Z87xQMwSN+joCt+NrSgDCvPi+Saq5uJbsRjjTtan8jFUZDBKQQgBGAMKcsE+OZXJEsUEaGRoEZT//pe8jZ+2+cfEIxoBXfdJcn8WCLk5oHHiBqrGuU7dvRkflLwckKIC+5RsfFJsf7AwOeEL6I9PiOQCxmYw7pHgwnGlj/+V3v4ECRIksHBJg6DTp09jxYoVOHnyJIqKinDrrbdi8+bNmDUrXIr3coaQm2Mr4/gWPz19LsK19vRGvuCt/yovR1M1sPZOoKsbxra9MFQN8jeX2WpcgMnnmDvVRTp3LZzBgNwc0I8+hrZqLeeEqKZ5qqqBgERmasTaar6IjeBMOPkhZGghL/Przq48j8kSYDCQa4aAtXeCnerK+CM5vW7AuUHGa2/5pL9tmWbdiJYfpgzysrkZbySzT/rvdvsCRktOXF6xkAdGjmeyE2dAvlIZ2S+SUjivZ0gB5PvmQVvNVdy01Rsgr2wKFjywFNT6VIAQO4gydu2D4QkMhG8us8sThfJSkOJ8btQaIPEs1lQBXd2AGPPVzklDGDOSixssmwuSnxd9fr8K7dlXIS9f4Cslc86LuJJA5OdAGFIEAKDpEBEEMxsoVt+UKQEcTOSlo48rMvTnXgv1QRmIT8rFWDA6f89cynskuHBc6eN/pbc/QYIECQCAMMZi3AEvX3R0dKCoqAjt7e0oLLz8TNpoTy/Q0Q12tg0ozIexeTdIybUQxt8A9PTCMpZ0ZkAsPxl29CSE6ZNAQABDBxlWzIOI9m5oTz4X/EBFhvzofUBHNwDGswzdvSCCwO+fnwvt58+Gtld+9D6wvn6wY38G+/hY6EJWmFgJgECYUMH7uf+gzQny+QFZ11WWQZw/A0QWoa/dFuyPtHs/iLnojbqPMPFGkLISGA7fH28bxfk1rmAx0KvIOr+iDOJdPAMHAMKo6wBJAIjAuVmKBHbok8AA0un/Y4lGsLNtYGfb+UI+6LlKxjw2VJnOqW63ZBbw6TmAIjNfwHlawrjRAOHllvToCbCObrCPj8W+C2n5AhBVA/20DcbWPdHnm+NJP/w4cl5YHkZWcOpTn1tQCwwp5NkY53fDkZFz9vtieY7Q9k7ov301dC4IEypdPCX7WGUZpHvn+QIk1/HEJyVBggQJEiS4ZBhIbHDJhRG+yLB2y1hagbZ2G8Q7JoC1dYJIIphucPloD2hzK+SGySC33QzoBi85MrMFRBTBxBAal5W9CTBOFWuqYPz+A0h3TotucJ8KuusPkBbPhLrjncBTaHMrpAUzQPJz7N1sMn4MyJeGgZ05D3HSeOhexbbKMogzJ4P+qRnsyHFfQOA0/SQFeYAoQA3in8D0zFlUD9bRE8kJkkQR5IZRQOsJXkYY5VV0sAXi9CoYpiqaAUBe2QTtqeftNsoPLIQwoQKksMAlkU2KC7hKHhwiAk0NYIX5QMMUGHv3+zJMYk11VgpqQnkpxHnTQTQdSKXADAMQBYh1t/NADQykIBcQRbDObgjXXwdmUK7u1noiWFrcUYpFARiv7+XHT56B8u2vcY8nT2AmLa6H/trbEGfc5lKO87ZdrqmG4S3rS8lcCEQSeXmgKID2qdCf3+zzd7IyctK86RDKSoAz50FzerhBqaoCPeGlZ9mUp9lQ1WAZ7IoySE0NMP74ES9VNN+Fs9wS/SrokePBY3AV+qQMaNwTJEiQIEGCywhJEPQ5gBQXQppfAxABxht/cKlnBfqnEAJ25rxP/YyTyRsCPXeiFMwgEAjTJsF4vzmyVImamQB9w/ZAJTcbuu4q+yHFhSC6AWPLbujrt/EF8PQqAAxkaBHosT9DW7UW8vKF7kV0WNldnKS2bgC9MRyW8x0Qxl6fkfKO4Sv5jnt/ZuDePAfdi2ZrMW2B+79o0H75gi3XTT85BfGuGkh31QCaDigyL9ELAG1uhTK/FuIt5WBgMDbtBv3ocOaZZkCprVrrU/NTf/mCHfiEcYzI0MLMu3MYH4qTJ0DfuBOktMTHSdJf2sUzdHE+SB7VPVZRBvGu6Vll5CzlQuU790Nfu9Ut6+3JkHlLzwZSngYA6OnnY1N3O+dudXTBysqqP17NDWlXLAQIYOz0GNJWxszNq8gnZcDjniBBggQJElxGSIKgzwuiCP2Frb6SqkD/lJRiG6u6zj3QAn3dNkiN9b5ynchMx4EWiNOqoO94Jzg74DEIpQdaIE+r8kkE28h1cypoeyf057fY97Rkp+17z6+F/I17AErdQxIWuEVIagOcpI+C/LDWmSAwtu7JSHnHKarlpEN/FmuqQ+W4g9pp+UA55brpvg8gNs2C8fIbsea17Fw7L5/c9FbgHAB1P9M5hzKun3BJgFtQ/vrBzO59Z4aTY8+fDw8Fvnd56kSQdIyks2OMeQZpJvSNbtntqHlKRlyb1XfENmo157J3IQ7AdY4vM2FKU5NRX4LuyZzazyO83DOb8Q+69xcdtKd34OOeIEGCBAkSXEa47CSyv7DQjWj5aFNmWSgv5edGyBsLpSN8EsJADLVL1+3sACktgfL9FZAfaIS8sskniR11P6GyjBPyT5/li2kA6O6NLE1DXz+0f/0NL+tz3itKetojy+16vigCualImXErq2VJedNjpyLlxJGbhvL4Csjf/Trkh5eCaZo9xgNup8MHypYOb24F0XV+n2wCMkkc0DPt5zhkr339HD8WkGXoz7wE9R+e4sGkhWwyZYoUfu+KMpBrilxzinX1uLJYcc+JlVh3yrRbpWeObJbvGuscL/JzIT/UBCLL4c872MJLH7Noi93+q8kn5ULGPUGCBAkSJLiMkGSCBhGR9fHOMpkAaWfk5UC4aRzEKbcCnV3RD+pTIS6YAQkMrE8FSSuAEBPPShKQnwtp2VwIhflczWxYEWh7F4y9+13S1GJNNUhxoVtG+o8fQr5vHkhOGqyrByQ3DdbRDfrnc5y3FDkwFFBkv3JY3MLbE4gJ5aWQGuvAVB3GS7sgTp/Ebx/AgbKyWtB1vqs/+jpg7PXBcuLTJ0H7t9/yUivzen3NJsjL5gKEDKiUTqgscy+snVLfvf2QH7ufB3BhEtflpUCOArR1xD/TM49IYR5IWQnEWyu40qBDcEAoGwlpUT3n/Jjtc72PuMAsNw0Q8Hts2OEf8+mTwE6fyxjODi2CePstUH7wIFhfP0iOyWnqiSgXG2jJYk8ffz9AqFy6N/C2YGzbC3HKhIE9zwXP3IyRvf7CcWfiyv6uorLABAkSJEhwZSIJggYJYfXxUtMsHmAo5lCH8WAqyyAtboD6b7+FvGxe9LN6+/miHZlFPz3252i+z8nTUB5ZBn39duieIEB5ZBnUJ9YAqma3TfVwdJRv3MMFD5z8FEuSmRBEgggZGeplcwEgu4V3nhk85KQAwwBtPgqmGbaqGj3UCvnR+7hctIPD4spqSRLI0ALom/eAjLgG4txpEGdNAUmnwAhA/3TIZwwLcI6M9sxLkL+3HMSgYS20n2GNk9RYD/VfnuGfW+/aK/V98zhuFLpuq3++LG4AO3MWZFhx9DMjZMyJhz+jPP4A6JFjYN09mXYoMiAKkCxOjGm8G6aAh7wcsE/boD37GsTJE1zS7rSFj7m8nHtfYWgRny/Pb/aLLCydDeEr40H/8yN/n3JjpKs984VpOkh+buRY4LYv++/T1WOLYQzkeU6QYcVQfrgyK9nrLyR3Jq7s7yopC0yQIEGCBFcukiBoEEB7eqE/t8nPLTjQAv35LVz9DE4Z4QAejMX3mTc91mvFNqZEZtFOykdzFa/12wPVvej5Tt8x63p9/XZIy+aCtZ4M5ejoL5j9cARB1nlCTVV0e48c44alf7EY6OqGOL8WIgAiieEZkfFjuQeRLPFMk2buyhs08xxVA32/OVLamXV0gnX1QKy/HcYru1zCDLZynuc62noC8vxaLj/d3glWXBAeIFSU2Zke1tEJY/8BM+iVM+a03nnxwSHolEGYNonzePJzQAQRrItLRrOObqCoIHJMGaU+vx4gmD+jr90KUlqSCawcQYNqjYfCDV9B4F6sV5RBvHM6tH//HYQR10KcPIHzjEz1Oqc8uDUv5b9cDP2FLcFz7YUtEJfO5oGIR/SDXFMcmSFzzns+NkdBhhRCaqwPFQXR123181PMLEXk96yyzBRMcMDKNpWPBvr6edB27ZDIjM7F4M5cFlml/Nzwd3U1lQUmSJAgQYIrFkkQNBjo6I7kMsg11dCe2chFCWQ5UqpZuqsG+geHgyV8vaVezmfMncZVvELUvaQ7p7syQN7rpYV1QGF+pGqZXFPtDxiaWyHOuC28vbXVtsoWbXar4kkLZkCcNgk+08/xYyEtqIH+or/sinzlRpc6nuVLE/jsWVMATQM9egr0Pz+KDRgABEuNWwECgkvv6H8dgXDDKJDhw/jO/pw7ePmdKIXPi48OQ5z2FYBSl3oaYAYeQ4ogLamHvm67L1gQZ07mAWDE+5RrqmE4S8RSMkhuGmLDFEAU/EGDqkFbtRZSYz3E2XcAHV2ZzNoTz9nPc84B62dmSkujtx9i9U3RnLbmVkiqBuneuTyw9SzkfSbD8M9778/Kd78e6OsDOPgpziDBzFKEzh0zSwMA1FroR2RwIzM62XBnBhDAXC5ZpdB3FVMWmCBBggQJElwu+ExBkKqqOHLkCMaOHQsprrTpi4yevujjksBLhajBTTgjwPpViHOmgogCpEX1AGNgZ86DDC2C8X5zuDSvYfBStY8OB6u6zbw9+rm9fUC3R3bauYg2dJDiAsjfX8H5KqLoMrjUnn0VYk01lxw+124voOknpwINNmlzK1h7Z0bGubYaEAWQ3BwwWfJ5DVnX6Bt3cEPYc+0270NbswniHV+BPL8WRCBAvwqkU6BtndCfew3ysnnQdrwDsWGKjzNi7NqXWdiHZW/sAKEO4pw7OGerIB+QJZCUDEGWgN4+/llhPoSJlSAGBevt56Vo7Z3Q12zyk8Vz036/IEUGGT0CEAWwzl6IC2ohyRJYVy9IToqLJggEONse+T6RkqE8dj9Ybx9IWgFt74L29EYII66FNL82kwFyQtWgP78ZyvdXcMaLt8rRyW8yx5AMKYR03zwIRVxEgJ5vB+uMIcX39UMYOTwjrGFlZvo1QO3nAbnlj5WjALIC9ul5yPfdGVzyGPf98/JTHFkMn4x4bhpk+FAQsz/S8gX8vVHG52RABjcyozOI3JnLTZGNFBdmxieLssDLBZdFJi1BggQJElxyXFDk0tPTg8ceewyrV68GABw8eBA33HADHnvsMYwcORI//OEPB7WRlz1SSvRxItjGm/LKpuhzRRHaT54GAAg3jYN013RAksD6VW4giWo78HA9Iq4NSvRxklLA+h33jOBZiDVVfEFdWsJ30gXBlmMWSksy5Hizv2EGmwDnlBi79kEoXQBj+zs8u7CyKTyDYsp9W88Qyksh3zuPZ5tefsOXDZKXzQUYDe2LvHwBwAy7vwhTDFM16M9v4f359QZ+/iP3ckln65n5uVAevQ/6um2+dti8K0cgRATBFwBFjTkKcyEM4bv9tCvaJwmUQf3xrwPb4Cvz8oCda3ePr4PP5eM3ObMmPb1gn7bFL4JzUsEZDa8fkFWuuPc9iJNvhfbsq8EbAAPkp3izGJaMuJ3FKCpwnYvcHK6GGDEnQzM6pulqtm2LxCBnlQYD1vhcKbhcMmkJEiRIkODS44KCoB/96EfYv38/du7ciblz59qfNzQ04G/+5m+uwiBIjubEHDpq/xzH94FkyisrMsQptwYqcXnNGoXy0jiBbDBRiOaYgLnI8ZHmq3CXkAlmKZxQWQYU50N+oDGjzmWEK2zR1hMQbhoHYcqtgCxDnDqRl8+JMUp3DtWuSE8X82epqQH62m3hfVlUb/c3zsPHerZYU+3L4kjL5voCIOs5Fu9Kf2odAHPMe9yBTOCYKzLnYsky0NULqp/hXJSUnOEpeZXRctNgJi/JKfhgtcGf4vHAkdW1x3DZ3FAum+3Z09UD9PSBpZXoOZ5K+cqonM+y+UwW3620BMbu/ZCWLwABcWXy2MkzYL19kdyeIH7KgLMYcdmmgOO0vRO05fiA2xaKRJHtM+FyyqQl2agECRIkuPS4oCDoxRdfxJo1azB58mQQhzLYzTffjMOHD0dc+QVFbprzT+DnFojTJrk4PJEclpoqWxo52yDEegb98HB0IPbBoXDhhKWzob/8BuiBI2ZmhEWbrzq4IbS5FWJttc1V0f71t67gjNxS7r7YuWBnBshtN/MAxRHoyd9cFvhcG57SyyilL9rcGs9RYQziLeVQt+3hQgVZPFso84+PUJgfzbuaX8vPqyjj8t4e1TnfmEdkhqS7Z/M5J4oQp04IzXJ5le+k+bUw3m/OWoDAvm7BjPC+WVmI3n5AkqCt3gjlG3e7s2SOdkNTwzMaQbyjGbcBpSN8ZYrW3FV/8TvIi2fa57uOL5kVurgcUBYjFZPRCTre3Qt9w47Q77u0pAFE1bJvQ6LI9tlwmWTSkmxUggQJElweuKAg6MyZMxg+fLjv8+7ubldQdLVAyM0Bu6YYmD2FSw6rGkhKBhMFaD/9ja+Ehx77M8T5tZAIAevr5/yagy0umeG4IESZXwtxYiWYKAJdPRBvHgd8ZTz09dv8ssuLZoL1q4DBIDY18Jeu6UC/BqQV0JbjoAeO2GaqYt3tQDqmvM6RjSHpFIRbK6GtWuvqK21u5dLdIeRysWEK2Jv/6Q/0Dh3NWh0vqD1esJgdctbTB5hZmchMXUUZUJgHeeUSkLR/wcn61VC/GmPXPjBVg/ytZYAogDYfhXDTWLfqnKcPUYGwvnYrxAUzIDbWwQjJPtn3cMwjpmpcGnvBDLBpHW4vodKSQOENu29RMHe06QeHIQwrhmrOZUnTwHr7uSQ5NaD+++8gNzWE8rOgav53GcSdssZh3VaIk27yc3tM7hB6YzI42ULyZHud7xkMAMlwnKyA0KCZ71RA21hHN/Rte7LPQAxAkS3JNATgMsikXU7ZqAQJEiS42nFBQVB1dTVeeeUVPPbYYwBgBz6rVq3ClClTBq91VxiMrXv9GQ01hGcTINXMxpUChXlcwSuijAzgHinG5ndAPzyUuc/4sZAWzwQ72w4IhIsMEACCwBeRLcchL18A3bOwdmUNAAijvuTLUvjgzMaklIw6lzcIUGTuibNhB0jJta5FfVigZ2fLBBKpEhbaHg+CAhbX8ZRi87pCM3Vm9kb7+bOAqkH5b3/hW8iT3HQk94gHApT//8hxaDvesTNvQb5JkYHwgRaI0zr5v2OUCW2hDEUGKcgD+/iYSxhBqCyD8oMHYPzxo1DhjXjOmQzk54KdPAOx7nZIQwq5MWvLcVewoDzYCKRSYG+9G5658owDEQTQ1hPhwhbTqmCYnDSvKIhYfVNokwcUKOh6RgGx9USoUpw4c7K9GWDz/8Ladku5KwMR155sFdmSTEMILodM2mWSjUqQIEGCBBcYBP2v//W/MG/ePHz44YfQdR0//elP8eGHH2L37t144403BruNlz3s3T2vmpknoxFb4ja/BtrPn4VQWgJya0X0Qw3DFQABXHZZ13WI82u47HLrCciP3mt7togNU2JL7ADA2PUHkNKSrLIxQnkpmMXhCSvfqiiDtKAWAHFLcIdlb8zdc/lbyyBOM41QC/PBTp0JXKQLFQGeLo62MoLIvjAwMIfZbJBiGNIKtF+ama78XEASwVpPuPop//WD0eO7ZCbou81gR47bc8X1rELPTn9Ediur455zpMa6YM6S6VEl3FqRGVtPpoOJQnQJXctxCDeNhdzUANrTx58TFixY0uKHj/pMaqXGOp8fEOvtixa2CKGQRXFuBhwo9KuZdzW/1jbs9Y4jKMtwmuL8vqw529ufdXviuEz0fAfYp+chTpnApc4l0VZzND46AmFCxdWbabgcvI0ug2xUggQJEiTgiGGgB2PatGl49913oes6brnlFmzZsgXDhw/Hnj17UFUV48L+RUTI7p6xax/Emir+BxZ8Zz+Km4LOHtuPhR4/bV/nhVBRBtqcEVuAIkNsmAJ5ZRPEqRNBBAGktISXtfWqrsxL1POF8TdAvKUc4tSJEMaMhHhXDSeyO59tKXbt2mcbsaKNZyRCg7yDLdA37gTr9/yBj5JVVzWgqxfaU2uhrd4A7Re/AynMNxfl/vYQ09DUd2zWFBCZQFo6K7Av0tJZIKII1tHNuU3lpfbOvfbUWhi73zV//n+QH26C/FAT5L+6O1BoAe1d0e/3XAeEG0b55LetZ2k/fw5SY32mnXGy85KU3TlmX4WykZEKZ8Ko6/izzWCWtZ7g7XpqHbSf/l+IMycHj3FNFfQNO4DuXrCePhCzv1FBv7HrDz7+FW1uhTDqOl4WBzN4XjwTKMyPvA8ZNsT3XbECiKAFP+3pDRZmMEuSqEewAgAPhM13hc5oXzBrjhq79vE55R0zs1/6mk38g5SSVXtoTy/o6bPAmfP8hGuHQBg+zO4jPdsGfc0maE+ugfbrDdD+9TcwXn4DEARoT28Effe//DL4VxGsTNpA5sqg43LIRiVIkCBBAgCfwSdo7Nix+OUvfzmYbblyEbZ7Z2U0vnM/L12KI1dr5q69IoMU5nJTTK+RaEUZpMY6qD/9v/a5oeT5xTPBzpzL3D8uc9DTC9VULwN4eZ04vxaiYQC6AZJWeNkTpVAe+xpoWyfUJ9ZAnDyBL7JjeExSY537s7idcif3x8GtUObXco5Kv8Y9Y57eCAAQ626HPOcOwDC4p44kgp5rh/avGyEvmwOhpgpSYx3nqKQU0PZOqP/6W6Crhy/+R18Hobaaj3tvX8aTxpKHNk1NQyW8g+SbXR2mIGJEWZmqgZ05xw1va6uB4oKsBAwi1ceGFED5/go+92Jktdn5Dv7soEyH1yvJaaZqZudYTx+0J56D/Mi9/PlZimu4oOlmOSIBbT0B9V+egfyte6ODS0oHpvR2ISVJVhbhyPF42Wvn94wAwoQKLtxh8oFYRxfY+Q4uA15ZxudpVHu6e8BULTJTRNs7of9ucyw3TF+7zeXrdLXhknsbXQ7ZqAQJEiRIAOACg6BXX30Voihizpw5rs83b94MSinmzZs3KI27YhC1e6dqIJRCfWptvEeQuWsv1lTD2LmP8yA8hGrW0QlmEq7tc8PI8xu2c8NVz/3D4Ra1oIePQuy/jZf2HPQo2d1VA91c/GZ4NNFC3Uxwy3TH8m+83B+HFxEAaE+tdR02Nr8Nw+S6yCubPMcF6E+thfy9r8PYuidYWlqSQArzoP3kGVdA4ysjDAsmY8aXFBUAAjHv5/d64s0UebahYQrY8dMQp03yB8IeblSo+lhjne1NJK9s4tmMKBTk2eMb65Xk8IKy+5fD72/zhy6gnI/pBjRHIA4AaO+Ivk+/CiH3muy5FBdQkmRlEYyPjnAj1yh4v8chQb7UWA9x/Biwju7o+xkM2rpoMj26eyMDRVvN8WALDwL71atWLOFSehtly+tKkCBBggQXHxcUBP3whz/EP/zDP/g+Z4zhhz/84dUXBMnRPkFMluyd+6x4No4d9CBCtfzY/fZuYhx5nvX0288cUOYF5iJu657g3eVX38woj5lZGuWxr4UOEQAQ3ciQy5tb7eukxjquqmdmdxgYjN37A4OErDIgnr44OUOECHYAFEZuV763HMb+AzB2vMN3671jHBLs0GOn3GpvzjZVlMH44BCMzW8Hylf7+mY+kx4+ygPhudN40MA418x5LR/DekgL68B6+7jxrSJB/flzdpaLtp6AcEt5tH+PYvbrAoIXobwUTOBBNO3oMj2vsivVs+9RWeby1LIhxtxnoCVEF1iSRIoLIYwZCeOPHw34e+wFbW6FtKgepLiQK/ZFgdL4zFVcYOd4Z+zTNmirNyRiCZcIlzwblSBBggQJAFxgENTc3IybbvKrLt144404dOhQwBVfcPT1uxf3Jmy+ik4h3TMH+ovbI8+zMx9xi9DePkiLZkJf/3r8uZ1d9jNjMy9rNrkUuMiwIh6AtZ7wy3wfbIEyvwbC2OuB4nwQg4H19UP+1jLQ5qO+TIdQUQbW3RMqF6xu2AH5vjt5hsEMUEAN927pzeMgzpvGOUi6DnJrOegnpzgfxfImqiiDtKgexv4DQH4upHnTIIy6DqxfhfytZWCE2BmgMPNPff3rECbeaAdDXqW+qGBSnDUFwoQKkMICW8WMtXeCDB9mL/BpcysgEMjfuZ+X9B1sATv2Z+4jpBsQbh4L6GboaymL7doH+YGFgCyDed6HUDYSpCgf6r9m5Njlb9wNedk8AAykKB/GB4eB9o7I+Yc+NbvgJcedUbKvP8u5KvqaTVAeuRf0SIRRqDdQNaXc1Z887Ts3MnivLLOV/bJGfi6ECZUQqm+GUJgP1q+CpBXQ9i7QfR9ElyT1q9HfowZTHQ7Iovy0L9OeqBKpuCDJWkhHwflOzX9/kWWZL3eJ8EuZjUqQIEGCBBwXFAQVFRXh448/RllZmevzQ4cOIS8vbzDadWWhpy90ca898xKUh5dCGDkc0n3zgO4eXqKmG2CaBpJOuXgVAHyLTB9y0lyyd940ECFG20KUoD2zMdM2akBa0gAYBtin5/kue2EetF++APneeTB27fMpuynfW865RaLo8nNhZ9v5jrIziFM1X6aDLw6ngKTlULlgAJmFmpVZ+v4KsLNtnCulyCCF+dA37nQbZpryzuzT8wCFzSMRxpVCeexr0Ndug/78Ftf58vIFACGRu/RiTbUZDFWCDCniB6zyuTEjQb5yI/SNO9xB2g3XA/0q6P4D7vLBijIukDF6RMYE1JS41p5ay6WV502H+vNn7cyNtHgm555Yc0LVoK3eCLHudu4xJRDuf2R5TD290b1YFgRoTz2f+bG8FOTmsVD/7dnQeSo/0AhSWgIU5oVntMpLwTRT/tk7zx+9D/JDTaCfnAJr6wQEAmlJA/T1r/tMTsW7aoB+DcLYUYBOuW9OZ3fggj9SMn3aJOgvbIXc1JB1RkPIzYF0Vw3057e4DGAtM9fIxXJOKtz759gpIJ2C8p37+ZyVs8tgxZVIxWaKclJASslazdEZfH4RZZkTifAECRIkSJANLigIamxsxPe+9z2sX78eY8eOBcADoB/84AdYuHDhoDbwioC5MApd3DsWO5YfiP7MSyDXjwAZxhfY8vKFtq8OcpRIQjw7dQasMB9ElmFkYyzqaZv8yL18IfdrzusQG6ZAurOGZ0YOejIjB3lmhJSWcL5IgJ+Ll3xNm1sBQrgxaFcvWEcnoKmgn56PXFy7MgOlJaAffwJ2vhOGZazaeiI4c/PCVrt9FkjJtdBf2BouYzwrxs9K1+1giB47BeGmcRCn3Jopn1NkyI/el5HwliQgJ5Xpv2cMwRjEO6f7nmG3iQHi5An29fqL27mktSOAg6rB2Pw2WMtxSHfPgbFxZ/h7b3aXldHmVrB+FYI5Tt55apXDGdv2wNi7H/JDTZm2W+d4fHC81xvvN/M5UlEGjBsN1tYJdq4d4sIZkCgD6+4BDMoD6c27IU6dEFwS6O2TqsHY+x6ke+byYLenzy3KAHD55zEjgX41dueftndCf35LMI/u+S2QvnZnuHCAI2vjHUehvJR/L00ZatreGV1+mJdpX1SJFOvpjSXTC7k5PNvsEUdwblCE+mz1DJKh7GWAxIw0QYIECRJkiwsKgv7pn/4Jc+fOxY033ohRo0YBAI4dO4bp06fjn//5nwe1gVcE8nKyXuwAjp3ftdsgjCkBZJlzbyxflU27wwnxs6YCaZnLaUsChIpS4MvjAI+aV6SxKAPIkMwiz9i1D8pj90P/3abA7rmI1bafSz0YmJ2t8Kp90YMtEKdX2eIEQnkpyA2jIC2q55mBiLY6f5aXL4SBgSuNxfIxFswIPGZDyvBj9A07oPzgQdtvCQDv8/vNrsBM+f6KSHK6JNQGPwN8vOTpVa7xk0yJctdYVZZBWjob+tbdkJbO8gV6QmUZxGkBohIAoDoMP4PKNvNyeMnh5FthbN4NMnoEZEvVLDcNck0xwABhzMhIE1vachwiY2BHjrlNgU1lQ3FIIQzAFwCFZnwqyyA3NYBpGrQn17j75OB22Ya9iNn5jxERQHcvEBIEhWZtTDl24Zpim9shFBUEByYVZZCaGnyZorASqWzJ9MKwYkhfu5O33wqkJBHo7oO8fKE/4+wYwy8MEjPSBAkSJEiQJS64HG737t3YunUr9u/fj5ycHNx6662oqakZ7PZdEQhd7JSXQrpnDne3P32WL0xSCl+Y9PRBuqsGEAQwVYO0dDbAKPR1vHTIJsQ7DTuL8kEYhb5+h3uHfvxYiPNrIHb28DKc4kKwE6eDjUUry4C0Atre7dpdZn3ZE6tpcyuk+bXQN73tJvh7ORCea5T5tWDdvVx2mzIQagCKDNrWCQgC5PvuzOzwr38d0vIFIMUFkB+5F0RwK9f5kKNAeXwFWB/nd7A+1a/+Jks8C7F3P5gkQv7mMi6FbX1ulvnZWSlFBoYW8SxdZxfEGbdBqKkCIcQu0cMt44BNu0E/OgwW5C/jgPN4kBCFd/zY+XaQ0hI+bm0dIF8aBhiUZ1e+eivo4WMgN4xylWQhP4cHCkElVKoG7dlXw8s2v3kPD6yefY3Pr48OuwPLyjIuwLBkFr+2tx+st9+3uA4V1DjYwnlxjXWurJ2rfc+8BOV7ywGB+DMi3vFChDpi1M7/BajDuTgmuSlI987j/+7tAxSFS5Dnpn3kdjsw6ekDO9cOW/r7x6shjBmZdYlW1mR6WeK/XyQRMEtlWUqGsemt8E2auJLai4CLxtlJzEgTJEiQIEGWuGCfIEIIZs+ejdmzZw9me65YBO7C5uWAMAbtmZdCd86FMSN52dOL2yFOnZgJbgLK6+TH7ocesJihHx0GqAFxwQygqxe0uQVCRZnPHFMoL+V+JaoG+tZ/8myTIEKcOgEkbjfYQ5Zn59v5c3U9oxLnJdR7rznXbksrCxVlEGurQVIp6F5J5PxcKI8sg75+u83ZiJUX1ynUf8uQ6uVv3Rus/jZ+LL/3i9t9YyMvXwBjz3sQp9zKvYEeaoLxyhu8RNDMOFDPgtvit0jzpnkVxv0waOaaoCydd/xEXp4mjBkJCIIdIDv7Is6dyrOCAH9+1IJWkqLLNhWZc5oiDFXZuXaAMW52Ou0roJ/8GUJpCYT77rSDSWHMyOgsXHgLeSAlEAjDh/mPBZD/AzN+zuD31FnQ/Bz3InuA6nCRHJPrrom+FwDIko8/Bgy8RCuOTB/WTumu2mhBDDFu4g4uLipnJzEjTZAgQYIEWSLrIOhnP/sZ/uqv/grpdBo/+9nPIs/9zne+85kbdiVCKCpwldHQnl5fAAT4OTT6+u2ckB6jJkUYDS/jOdACsa4X2n+s44t5bzlTThrIUfhCtvkol8w+1ArJWvjfNX1A8tmWbLFVisa8nJ6gazzlXwAgLpzhe660bC709dtdn8XKe3uklZmq+gIWACAjh/vubfUDhEBcVA/tX56B1FgHY9temyMV5ceEV3ZBnF8LeHyQXG2sLAOK8iF/c5lP4hrgQWHQ+AnlpWCU+vuiyBCnTrANXJ33kR9qCuTtsI6uSE4WBCF+p1wUYGx/B7T1BDfjfes/fSa95Cs3ukUdPGD9avQ4hamzBamoeb8zEdLn9iI7Jx1dvuoQJhkUjsnnUKIV1U56awXoBx9zI1xPBtDY8x6ku2d9pmcPVjsHhbOTmJEmSJAgQYIskXUQ9JOf/AT3338/0uk0fvKTn4SeRwi5aoMgX4kHZeGLHw/PRq6pjn+A7MnWWDveZSWAKIDk50D+zv08ITB1AvQ1m1xlR0J5KcT5tdC27eVS2GNGggwtgjB3KhjLiAXEcYv8AQ6DWFvNFcrCrqkoc3GIAJP3YlBITbOgr9tmL86FwnyXahcUGRAFSItn+jM4IcaqhJDgRW4UV8hsj7x8IZCXBnWqypWWQNu1zyUh7iyjE3UD2uoNUL5xD/S1W32CAtLiBoAArLffL3FdWcb5U9b4VZRBvHM6jNf/H8S624DiQog11RCnTrSfiRwFrKPL97mxax/w+l7Ij68A0Qywvn7uG9TfD1JUADJyODeFLbk204/cNJBWeEYgJiNI8nN5WSCl0F9+gxv6zrmDLzANCpJWAIFA/v5yQNNBALtEkbZ3QV+zCSSlBGcmLDU0IFM+6imVkhrrwDQdBASspxfEw7fLpjwOugZpcb0vGOaqfPWA7gjeBiWAIVzpsN89DugyM3ghgSdt78xklnPTQG46XLAhop36hh1Qvrcc+vrXfcqPYm01oOmh4z3oaO+6qAFhYkaaIEGCBAmyRdZB0JEjRwL/nYAjqMRDXrkk+iLnLraugx4/HW266vwgbMfbDEDo7v1QHlkG9Yk19mLLKkWSH1gI1tENMqQwI1+syJAfWAhhYiXEmmrA0EGGFIEe+7MraxFYypWfB5KbgvxXd4PkKKAtJ/3XTJ8EY/d+n0koO98O7bevmmafM8B6+twZBEc/1R3vcD7L9CoADKQwH4xRaE8EcGC0kKxaTLaNBwv5/vtRI3S85eULgO7uzGcTKnnZobnjzjo6wc6eh/bsa5DuquWkeE0H+jUgrYBJEoimQ/6LRRn1tK17IC2cwZu8dpuvDE5aVOcXRXAo94ltXVD/fY3rmHT3bBhv/yfE2VNgvPqmrx/SPXOiDV/LS2HsP2grwIm1VRDv+AqMN/a5BRBMkQAQAvWXL7jmgfLoffydmRLTSmMdHwtz8Q1Vg+4tH7XEIF5+A2L1za4gxwrArPPjzIOtTQr1mZcgP7AQkiDyQDEnBWYYUFetg2J6AAH4zBwT+ul5HhR73pPruxlQokXPtgVzDO+eDeGaIf4HdUcovKkaD5jn10ICz8RBFEEPHwUY4/PIE7RfDDlperbN5EVFYBA4O4kZaYIECRIkyAYD5gRpmoYbb7wRL7/8MsaPH38x2nTFIazEI5Yk4igPI0OLIChypNIb/fCwHSRFlmcBIKUl0Ndv56VlTs6NbvCMEqVulTbLh6amGmTYEEAWAYW3T/7GPUBPLyxStzfAoR8cAms9AVJaAnbmHMQ7a6B8+2t8cWnufGvWzreTQwQABTzg0J/fzEupSksg3lKeyXLdUg7DMR5OPotQUcZ37oPKrsIMP+OMQA0K472DEMaNdnNLchSe6SgtcZnH2ovx+bWQH1joVpBzQCgvhTh5AvQ1r/EAYt40oK8frLcvsGwPAOhNY03PoRbX52TkcB4Yhbx7saaaE/Y9x/Tnt0CcX5vhOXmPv7AF4qJ6SCOuAWufBBBiZ5eE0hK3AtzBFggTKkD3H/S1z2qHFVBb75o2t0Jftw3S3XP4wvzkGeCOiVzWurcfoAzG8dMQ76yBNH+GKzjRX30TgicAsiDOnJxRUow1GubCBvLimf5SwvJSyItnArmOoOQzcEzo+Y5wKW7zu0nf+qOvRIu2d/oCIPu657dAWjYXwtCizOc9vWBx/dYMaP/uNqIVG6bAeGPfwEQlLhBWn8S4jPcgcXYSM9IECRIkSBCHAQdBsiyjr++L4ysxKAgpRYnksVSUAYV53P/m+OmMx4pT6Y0x7iv00cf24tNyqo+VjJ47DSgtAclRuIGlVSqVl4axdhvEmupgP5Zte2Bs2wP5+ys4Eb85IwpgvPkHv9CCwyRVnnEbUDoChrccrLyUl6g885KrDFAoL+UqVs5211SDdnVzUYKte4DSknCi/sEWsJ7+wDEOG/tYblHzUe5RdOSY3YagzI8zEKTNrRB1AyQlR0ov2+WPDvlw+ZvLQq8hhfnBGZks5MLDjkmi4AuA7OMHWiC2d7szSJXcLNfYf8DHYyKFBeHvxgzUSWGBS4SBNrcCqgrh5nFcLv251zLfHUU2xSh2+eaPtHQWoBnuMkkAwqjroK1aayvekcIYs+acFKAokRsI0tfuzHz4WTgmvX3RkukLZkAMKtGKk/Du6QNNK5kApauHz9sInhXr6PJ/nk3WbLACCbNPpLTkwvhgCRIkSJAgwSDjgtThHn30UfzjP/4jVq1aBSluZ/1qQEgJh7Frn1lidiNIYb7NI2HtXRBuGAnj3QNgx09DWlDDS2MAW3FNmDQewg3Xg505B+H6L0F49D7AMABVg9RYxx8QQT4Ho4BAYPxXi72TLz/UBOiU8zjyc7jimofbYt2PwMHXMKWL5W8tc5V5+XxHctMwXn0zMkNhbNvD+2cqmxEA8gONGa4LNYAeFcYf+CJVnPaVUB4OVA3QNIgz+KKftp7IZG4EgFTf7OIaAeDjHcQHcfjrCPfxRbCxbW98X+w50MeD1iDk50JaNjcj922WwCE/15excSFsdz9u1x8MtPVk8KGguerMeAnEFTTTAxmzXN9ci2uHJIDk5rjer7FrH9Dbz6W4nQEQIqS1m1uhv7AV4t0BSpS67lK8ExumRC+yKYsPMvr6QWXJLqeSGutAj5yA/tqbECdP4OMEZhsd29d6OYF9avT49Ksgo77k/zymJIz19YM4A5Te/ozHEuCe1+WlkBY3gCgSqC+YC5mvWbZjQOjtj+b2JZydBA4MiA+XIEGCBBeIC4pgfv/73+P111/Hli1bcMsttyAvz737um7dupArv6CIKuFg8JU0CRVlIEX5YEdPQZw6AfpLuyBOnpApG2o9AWlJA/S1W0BbTAPVl9/wq4B5MhIu6BSgFOz46cx52/ZCWlTH7/faW4ES0db9WL9nAadqQFevbX4aBCJJWWVCyDVDuCx4AFeC3HYziG5Af/ZVQJFBrh0aqEBmt5UQgAgg5aOhmIsr+1xFhtRYB+muGt4fxkCGFIF1dnNejm6A9faB5KTBDAPaz5/j/ZQknmFw8FzC+mL3vSift8WLALlvqw/KI8vA2vw79DYusKSPDC2EEWSWCgBpz1yN4JZZYxzUXwA+s09/QwSoP8mUYNn8qdw0l+L2ZFdiDW6zKHuMCgbEaZOg/ssz3I8qDIoMgATykpTH7oe+YUeg6hwAPyfwW8vCnwOE/96IKQkjKcUdoOSk7I2KIA8oEBbMk6ExQdBgyknnpiO5fUgpg85BSnBlIpQPd88cCMOKL13DEiRI8IXDBQVBxcXFaGqK8W25miDLgbvPYk11cM39wRa+IC8tgbHrD7xEpLTEXmSKNdWmYEErr9sPKt0x7+HLSCAjGW3xdIxdf8icR4TIUiCxppqrl4kivIgrJWNd3b7PXdB1fn1bRyAPxuKMiPNrM+Pw4uuhbZUa60Cbj4IdPQlh+iQ3xwkwuUZbIJSXQqipgv7UOpt3xFpPQLxzOtjp8zD2H7D9k+x+lo6I7Yuz78b+gyBDCn2lU0Fy33ZfN+yAuHQ2hFsrQd874HtEmKR1bJmlV0XQcYz19bmujeOWObN3PqSC5z3gkC03s2BCYT5XR8tJ8UCjJyADFida0eeX1vYJOTiDgYbJfB4bBmizQ5Y8IojMfPda3ONxoAX6C1t4RuzDQ67PtTWb+Dv0SeEfhTB+LMjI4b5MJjt+2iXF7UJKiR7Xji4I1zrEERwle14PKKGyDDAzpV6eDG3vjJYKTynB7bsQpFOueebi9pWXcvPZBFc9Ivlwv9sM6Wt3JhmhBAkSDBoGZBVOKcU//uM/4uDBg/jTn/6E4cOH44knnsCvfvUr139XHfr6IdZU8YWDA8K40ZGZEaG0xP6/a1Ht4MFY54Teo3y0+5kmT8fYtc//DADQtOj7jRsNsaYK7PQ5voBywNi1L7iflumiaQYaipw0xJqqUPlqgC8qiSkowcchoq2jruP9PNgCoTA/sl8kj5f/iVMnQpxQAaGmCkSSQK4dwvsLZvfL2LWP705HwVxIO8db37Ad4szJrnGLbNeBFuBcO6S7aiBMqHQdE8pLQYoLIC2q9403O3EGUtOs4PcwfRL0DTsyJZOOY9KielP8IvMOY+eXNW88C3ahvBQklQqeDxVlfEz++CGUR5aB7voD1J88De2J56D+eDX0323mGSkv/yMuw5VWAp8nNkx2f6ZqPJAnBKQgB9qTa3gg5wxyPfew2z5udCTPyR4P5+cHWgLni/HHDyEtqgNrPQHtqbXQVm+AtmotWOsJSIvrIQwJyXzkpCAtDX6/0uJ60H0fuMbOkoX2fl+tLFWouIGqRn+f1ZhyvoEg5vcOtJCy3gRXF+JKVbt7P+cGJUiQ4IuMAWWC/u7v/g5/8zd/g4aGBuTk5OBnP/sZzpw5g//4j/+4WO27MtDTF1iKAhYTFFiBDzWAoUWco2PoIMX5ZgZoXzzvQhAy3J4gno51vfl/FsdTEAUgnQcyrAhSWQnPxFg73KoGY/d+LtzQp3FvIlkC7eDqb+LkCZEZCqZx+ePIciRkzDRjMwPn2zNS297yPcDNdTE4R4qe+hSCIoHu+gN0B4eIEMIzS60noG/YAePDw+FS0ZVlgMmp8o63tmotlMdXAP1mSWEYZ8tCTx/0bXshNtZBapgC9un5zHtcvYGX9C2bC2lhHVhfH0g6Dcgi2Ln2QPNLqy3SndOh/Pe/ANMpCGNgPb2ApkO84yugJ89AnDcN4uypgRV8LpjZO6ZpfJ6Bl1bRtg6wc+3QfvuKf97n88BDWr4gPAv2whbIDyzkJYjW560nwjMnfz7L/Y2KCyDNuQNYVM/LDxmD+uQaPkbza11ePNrTG6F8425fl6JK5iDG7AsZeiBHDdRXLMi5Lx4Zc7v/z28J3dUWcnPAVA1iUwMkVbe9nmhHF/TNuyE31rm4M7Snl7/zOXcAC+v4uIgEyIuRhe7pDy2h0555CUpcOd9AYHKC7O+jl983mPyjBFcuPqMkfYIECRIMBAMKgp5++mk88cQT+MY3vgEA2LZtG+666y6sWrUKgjCgpNIXC2ZNvrcUhS8aIyBJNu9Ff/F1V9bD5k/ErFKJIkP9+bPRzwAAWeKL95gSF5JSuAmm6R0k1lRDrvsqIBCu5CaKQFc3SEEejA8Ow9jxDhddMA0KLX6Ej49hGZrGlCPxPkncxDGOcyI6JMadmQpFhlh3O8QJlW6OEMxysbHXg548E8yFqSyD8vgDYN29IJNu8kle84zKTM51CQpwVA3szHlopiy58v0V0X0weVSSmUXTVm/w3U9/ah2U76+AsYWLBohz7oAw6ku++eYE6+3n72i9p/0VZRAbJkP7999xRb+HYuZobtpWALRkstV//Q2E0hJIC2rD572q+U1vHaDNrZAa61yBprF3P5RH74O+bpvfw2jpLOgbdoI6StG4Ce1MyPfdCeON30M/6O6nfO88sP7gd2T7FM2v5d41kgTW0QWSG1KiZoIMKQJ7+11f+8ik8T6hkrj+o7sXCCntIcWFID29QE8fCCFcUW9YMYS7Z7sCmyB/sqxFBkJ+b7mODxZyU9E+W7mD+KwEVy4+gyR9ggQJEgwUAwqCjh49ijvvzOziNzQ0gBCCEydOYNSoUYPeuCsGeTkD526Ul3IBhMY6UykpmJMhmOUqkfyAmGfw+n4Z0qKZoC0RbaosA/3klItfYWzbw3fOH2qCsentcDGFXYA4eQK0Z16CtHwB925hFCAC6KGjbknpuHHp6Obkb7BI407aesJut811aeVCEqyjy88RQoZLJS2bG8yFOdACfe1WCDVVMLbtDcy2sI7umAxPJnDN5v0AsIUbgiBUlIEeO5XhU+x4B+Jj90c8H0Bu2ic84ey/xfVhjEXzQooLgU/PQf7GPRmpdpWXNlkZuzAZ8sDsnAOspw9k9AjI9V/lWcWCPK7mF6IOF8TH0de/zvk43u+POWfExvrg/qka2Ccngdu/DFJcAOSkQMbwUrdQSWzPe3C178XtPn5eXP/jdrXjvG7C/Mmy9vmJ4R45N0x8ynf5uQPzEBqILHmCqxd5OdFzMi9RD0yQIMHgYUBBkK7rSKfdO6WyLEO7yuu5haICSHfP5lkDx4KEHT/NVd6cJWVw8Ej2vMezFc9vCbwvbW6FOOM2Xp+PgOxKTRWMd/4Eaels6Ou2Bj9j935+fSoFfeNO0MNHg0uBKssgNdZD/ZdnMg3wGpaGmGJaiz+5thrGNg0EBNq/r+HKY4/cC3b8tLsMJi+Hy1cHqMOJNVWgJ06DHvoEtOV4pq1ef6K7aoDuXggrl4AMLYLxwSGe/ZFFGFv3QpxeFe3RMr82Oksxvxb6R4eBjw4H7pJnE5wBXDFMeWQZ9A073O+nogxSYx1YWyfQMIULBsgyz0I5TGbpHz+CNHca2JlzLqlpRilvQ8txX4kRa+8EMWgkt8VW6hOEyPmF7l5oqzdCXr7QJ8ABzeClkb0ql/p2lK5Ji+u5QmEESE4awsjhgK6Dne0EyU1l1WbX5we451KYjLqo68H9u3kcpCUzAc1dcmnxa7SA7Iq0pAHqj1cHt+9gC+T6r7rGiIQJH1j4rLvaIf5kgMk3a+sE1fRwIrnJCQJC3r3JCYrMNmWr6NavRnM94gLGi4DPHNhd4vt/ESEUFUC6Z064OlwiipAgQYJBxICCIMYYHnzwQaRSmT/efX19+OY3v+mSyb7qJLIBCMOKucJRTx//o5eSAUUB8tIZadqePkCRwTSdl7mUXAt29nz0jWUJ6O2DOL8WkiCAdfeA5OeCASCMQbxrOvRX3oA4dxpXOBO5NwujlD9j5HDu8fNQE/cgAgJ5AOSaIt4+K8PhkE6ONCx1Lk5tPoWZ0VA1oKcP4pypMF59010GY5rCSoSAnW3ngcz7zbytyxdCe/VNu622P5GhA4X5IHm5PKhwlkaVl4JMuBGsrZObkU6ZEDmssVmKiOPGrn1Qvr/CpyImVJRlyv4sdPVAfWIN5IebINZPNg2YGOiho1B/+n952Vh5KXDblwP7JC2dDf2VXS71OKG8FKgsg1hbBbFhst/QtaIMwpeuieyfzbdSNWjPvhrKC5GXL+CBqJfzosggRfk8i+ktt7tzOtRV6yB/457oLFhbB3Sz/E8oL82+zV4oMhcfCCqzCpKOVmSQa4r5QitgYQ8Awq2VEKdV2UEVigvAPm2LzgAyyssLFRmgDEyWone1lWAVv6wR5yd05jyMDTvCpYWz4AR95mxTlm39vLkegxLYXcL7f5EhDCvmmUHLJygnxTNESQCUIEGCQcaAgqAHHnjA99nXv/71QWvMlQ6hqCC0xh+5OaA9vWDHT0N7ck3mmjjeUL8G7VcvAoBNxGetJ/jCSpGhfPs+0PcOQrz9FmirIjx8rNKWEHKyQA1AyMhiO6WTxakTo9toLk5JQR7ng+Q5dsBzUjyL5C2DMU1hxTunQ1u9AfLKpswuunOx6/EnEhumZPrvvJ9Jthfrb+cfxPGOvNwo57hQA6QwD/Jj9wOdXXxh6DRoVTUuTDB6BJSFdWCaBiIIYJoG9Gvm2GWMZ9HVA+3nz0H567+A/nyI/GuQ/LL5uVBTBfpfH7veG0kpoP0q6LYAc9GDLWAzvxrZf3t8JCmSF0IK88H6+oHCPBfnRayp5kFbWLndpJuAs22QmmYFZvykxfW2QbDVV9YwObs2e0FZeJnVkpm8f7v2Adb45aahr90WKINtyV3rz2+2P7fmnFhTHd0+04jYmp/yysXBxrxm/9HVC1wzJOKGMYjLJJl8s1Bp4Ww4QXHZJqdp62dp6+fI9Ri0wO4S3f9qQOTf0gQJEiQYJAwoCLoq5a8HE1093DvEsTucDW/I+W+XoaSqgZmSoaHcDtMwFKIA+cFGkKFFoJ+cgvbMRntBaxG7jf0H7Hu4nhMTUEDiO94gBMbe/RBnT7XvQwQhuixNqPWPg+d5zmOxhprzA+7nHdeKMjDVwWdxGoaaymH62m2+havFfxLGjAQ9cpyXW026Ecarb4aea4/xmJGAFl0SFFju1dwKaUFtIKlc/uayCAnxo+HcFse8ipt/xvvNMLbt4bvYjj7FvQd55mTQQ0chgPPabOW2nDRoWwcPgLp6/G3OsszQ/ryyjPsRhbQDBvUZwsorm8IzmwdaeAbI+Qyzr6S0JJJPxzq6POMiQH3Co1xnqrypT6z57OprDn8gX3uc7zhMhCHq+soyLsN9JiZTHZHBcZWD5eXEP+vzwmAFdpfq/gkSJEiQYFBwQWapCYIRVAMOIPOZJAGiANE0L6TNrdEO95YqV2UZl0hu7wKKCyA/vJQvrmUJxHyGze1IpyDc/uWMOWVuGqy3D+q//85edHoX6Raxm4wZad8DRfkZ6e3CvODFqSJDaqwHGVIAcfZUngForIOx6W2ba8B6on0dWE8vzzCIApcU3rDdtzB3jpFVziTW3Q7hprEgMEvXRJFnQMxgMHRcTQ8beuS4/Txy/YhM1ivMnLa5FSAE0uIGCGUlUH/yNMSGydBfDMiGNLcCAoHy+Aqwzh6QdApMFsG6YjwuQsq9mKrDePOP/sV3b4DhqAlj1z4o3/16YLmatKAWrKMbwgONfOwnVgKvvQX6gbsUz5p/gLl4o05z3mARBxuSACgSSF4OcK4drLObZxxHDYf+6w2Blxi79kH53tf9/KnKMkiLZkLfuDNzshncC6UlYJ+eh/BQkztbZ41dnwr5G/cAPb0Qa6t5ts2IkZ33vgfzZ2Pvfl7u9uqb7jJIRxkdPX7a/py2noBw/Qiw1pNgZgaPqRpY60k7I/VZEMpf8rw7AEBvf+DvpzD+k6UuR3PcgaoPIRkcXzmYIttKhPRASybzWj4aRJJ44GD26aLjYpfmxV3fpyZ8oQQJEiS4DJAEQYOEsD/6xra9PlI/rr8O5IZRmTp8QeD8GEEE6+3jMr2SCNbZA/kvl/j4I2JNFbRnX+USx99fwWWfVQ3aSzuh/NXd0NdudZH+hfJSKI8ss3ffvYIGgEnsnl4Fbf02fo91jnIh5wLG85mxba+rdMgudVq9EdL8WpD8DFcsCCQvhy/WN+yAuuMdvjAaMxJk0o2ZxbDJ65Aa60CuHQr5gYWALMN4+Q3fAp9MqORB5s59br4DGEhhPowPD0N7eiM/f+RwCLdWQhj1JajmOERmOA62QFo4w84uiDeNhWpyl3znHmgBO9Nml/FZZqWRCMm4kbQSnLmIytCpGlhbZ0bdLiWD5KUBSfZzjyrLIDXNAu6cDtbTxxdpXr8p8OBOWTAD4i3lYHqYOLcJg0EoG8nl250Zx1vKw69RZECUINxakeHjSBJYRycgCJAW1QF3TgNUHchJQX/xdZeoSFAGjigS1P/9tOucyDYA/nE1pezlZXNhbN7NFe2mm+3LSYMMLbJ5HsThw2Xs3c9FMdZv90t+3z17UDgOpLiQcw7bOsHOnEegVxjAx+uZlwKDHZuz6FiQE7N8F5RBXrkEIMQXZIZlcALLwVQN2tMbIT+wENKCGUCfCmYYoM1H7Xt+bpyZi12aF3W9IgM56dB3kfCFEiRIkODzQxIEDQKC/uiLNdUwtgbwNcyfSWmJvUAGzMVZaYkdlEh3zwbdfyBYOpsQiHW3w9j8Nv93w2SAMp7ZCJJFbm6Fvn47pGVzoZuBgVBaAqRkCGUlmcWNrgffQ9WgrVoLqbEO4pw7gJ5e4JpiGOu3ByrG6eu3Q36wEca618GiSogqysD6Vdv/BkCGn5CfyxdM82u5501uGkwU+KK4rRP03QOBfBQro+WStlYkoDAP6k+eyXBaGqbA2LmPl2490Ji5SaxBawdwTTHkR+/lRPkoOO5Fm1tBW45nVb7k/Ryy7POgAbIopTxy3B5PeeUSsOICGM9v8Y/bgRboL2yFMKESJDft9ypy9r+/n3tFpeTovjS32jwaO9BubgU9diq05E1+YKHPl8l5T/HuOTA27uQcqU1vhX63rGcK5aU+1fG4NvCytk73NaaUvZ0h9CgGCpVlGZ5HYZ49LuLkCeFmsWu3Dho3RMjNAdV0GAEcLYCPHevti+aoDB/mOhZI7PeUhIZ6EQWVgyky5PvmgZ0+BxQW2HxEMqSAm+au3vj5cWayKQO8SPeXGut9Sp5AwhdKkCBBgkuBq9jhdBAR8EdfKC2J5H8IpSWZcy0561377M9IYUE43+NgC8SbxvKFMWPQVq0F0zQIRQXRzyzM5x46rSegPbUW2hPP8WtNbx0oMoTC/OB7qBrfddd1kOKCWAlmohl2uZ9oeh25xqeyDNKCGSCpVCCPSV42F8aWPVB/vBraE89B/edfw1j3OtCv8rEJ6+fBFgijroOxbQ+0p9bC2P0uSFEBJ6E7jSzHjc7cw7nzH8d/AgHRdBCdwukHFAjPvfQNOyAtafCPhZkZYI5SKutzsaYK+oYdgaR8e2wrywKvs+eTIoNcOwTELH0MAj3YAlKYH9//Pg3az34D45U3eWlgRfizvfPcHoNF9YHzgeSkI+cvUTmnihAS+90SykshzpoC+uFh3zlRbZCaZoEUF7iOGbv2Qbh+RPgzLZ4HMiVqQmVZ9O8AxzWDAUtaOGxuaas3Zt0O2tPrK5EDzPLdt/4I5a8fhLR8QXjWIqAcTKy7HZBl0HcP8N89qzdAW7UW9N0DgMzLW8PaM9hwviPX52Y25rMGIVH3F8pK4vlCCRIkSJDgc0GSCRoM9Pb7VddS0fK3JDcF5dH7wPpU0JOnwQjhP6saSH4OoBkuXxgf16Gjiy+M+1UeoDzzEucKRYCpGl8Ql5YArScy5qVmdkmoqYr36xBFQNW5BHfUs/rMhZAigxECaWEd0N/PDRhlCcZ7B6G/9hakmV91e7woMpCfA/SqEKdOhDjjNjBKQQSBt5cxzjeJGtucFB+73DRQkAf1/zwP+f67IP/oYRBN4+8rnTL5P/tcmYG47AoDAwHhfbmmaGCZHVUD6+yBuKgekkF5f9IKDzz6NZCRwyFPneiTKoaqQa6p8vv0qBr3mlpUD0nTwfo1QBBAD7ZkyqEUGfLDS6Gvez1WNhy6Dnr8dHTmDgxQZNCPDoNNmwhx3rSMfHlBPiCJQFsH5BULQVtOAGnFHmdLWQ99/bz8rl9187niJJ+t41oMpyclQ5hYCaQUGDve8R9XNbAz53i2sGEyiCzxuZKfC3zaBm31Rnhlo1l3zOK0qwdUEADdAFSN96+jO/qaLLkntKeX36unj39/UjKQm/Yt1l3Swn39QE6az62Obsj3zvP/HjF/Z0Ez+Fy1eIzWpk6IkiQYjQ4UAsrBhJvG+spXAUf2bn4tz2wPYFw+C+wywoAywIty/9wUt0w42x594ecsFZ4gQYIEVzOSIGgwkJvyqXfJcdLXpvO1tnoDlEeXgX58HIwQkOICXkLj4RF5uQ4AgVBakpF6VjWQGN8RoshQf/J04P1svgshoYsfY9c+EFmC+pOnoXx/RfSzUgqQn2tzIrwcJWlxPdS97wE5qYzHi6Xi9cqbvv67eFDfjFHVSiumOeNROxtC8nN9pVZCeSnkFQsBgQBjrwcYc/E4fLLGS2dBf3kX9PcP8g8trhRDcHudxHTnO/j/fpUZ43GjubcTIeFSxQAgEF9wIlSWQZxRDc1R5mdnYsxzpMUNvCzzIDcVjYQkxQpKsM5uHqyfbwcpyAcIgfrMRv7ePCVqluogO3EGyveWg505B4gimCxB+9+rfW0m6WguBrEW11nIn9PznTxTEebrI4hgn5yEMHWCK6NB0z2BstEWJy4UigzdU2oof2959DVemfYAsLYO6M9t8s+vWVPArin2ZWMsaWHW1hEomGB/7wH7d5bq5CtVlkGafYdPUc95D1TfFN3ogHIwAkRm71xv9HOSyxZycy6qSpvz/qytA9pzr/mUB334HKXCEyRIkOBqRxIEDQYUxacoFplRqCzjCyBNh/xgI1hnL+i7B0BKS0I9cAA314G2noAwcjgYMhwM2tEVzRHp6Aq8nwV2vgP40jAueOA14Cwv5YarXXx3O5tnScvmhnMi1m/nHJAXX3e3J0yZzdFeeuhoZLaCtp7k3IzSEgj33QlcU+yTvLbvKxDuC7NhO9/9n18L/eU33ZwiMyujv7gDZORw4H3zBg6ulLRwBlh3L0huGvToST8x3RqX9k7fAlNsmMKDoSiomrtNxQVgJ85wbyiPeAEIgfytZQBlIIoEfc1r/FicbLjJhaHH/szNeWEq78kSIAhAVzfoHz+CvmaTfZ1092xIjfWh701/cTvI6BHQ179uc96EijKfOiEAiEtmRpuLplJ8cZ2trPfKJYFDKVSWgXxpKC/p8i6CQ/gcoRL05jNZf4D8eU46uj8xwZzNNQzg3QEAm3gjhAkVvqxMqE+N43sEIPidHWgBq/9q5HdRX/96JHclSLUuW3Piz0su+/NUZ3O+D3L9iJg5Hh8YJ0iQIEGCwUESBA0GAhZAoTvqlWWQlsyC/vxW0EOtUB5fYS/Q5ZrqaO+Vmmowp3T28oVgp85CnDUFAKCv2RSexVhcD3XVOlfpGRlWZLeVL6QJSL8Gfec+94LbygS9sQ/khpEQG6aACAKkJQ08iPHsNktNs6C/sgtSw2RXBsjbH0kQXbynWO8Z00fHHltC3DvkZrZCe3oj5L9cAu3fuRlnVr4w5u6/UFrCldM+PBSYlZGnTsx8bmZzSGEBL9XSDTAGCDdc7+OD8HcwE+oTz/EF5u79LuU2iCKku2dD37DDHzxVlgEFXGVPe2YjhNISSPNroTlU+Vx9OtgCsbaaLyYZMmWVn5xyybO7xq22GkgpmQDYKk0CINw0DtKierC+fl6iWFttZwb1DTugfPtrLoVAb1vk6VXcn8d8f7ahqkc0QTIopKWzAzN20tJZAKNcKr6tA2TSeC6nHiENTYYU+gIai/fBFJmXfZ05nylV6leB3n5IjXWgR05A37A9ozKXUmDJvgdJ2UPVM9m9MSOB3DSIpsVcE1N62tUDeuR45jvrKTkkQwp5iZx38R7lU9PcCrm2GmCws6/erC9TQycFZAABAABJREFUNQjlo8O/i1l43fjKweSYPzWi6JLmBi5eoBIo+nAx1dkc7yPOEiF2TiRIkCBBgkFDEgQNBoLquE1ZZ7GmGsrCOs5DMH1C9Be3g35kErZVPfPHMM6/JMX5PNozL0EoG8mzHUP4AlyYWAmxphrsbBvEJTMh6ZTzAhSZmzOuWgd58czA8hZ5+QIYu/fzHfacMRCn3Bp4njijGmRIEfT1r7sWUHL9V0FEEVAk0PYuzsFZPDN+97evP+NFJHMPpUhYamvm2MrfuR+SQV28Eu1p0wTW6aETo/jmOp7tuWHlQhXc00lc0gBJN8D6+nmZV1qBumot0NXDF8mlIwKvlR9qcmV3hPJSiNMmQfv5sxDKRkL53nIY+w/wrF0YFJmXVW7YESvPToYWgR47xblYigzj5Z3ugF6RIU65Ffrzm/2lhGY2h51rC2yDU4VQfqiJl4CaKnfOoNYCO3Me2ks7uSqgIPL5m06BSQKgGWDn2zNSzc++BvmBhRDrv8oDAQ+HSqgog/HhYUiN9bzc0endZXLoLN6L9R69mxXKDx7k8yitAD19UFc5JNc9vC35a3fa3yOUjoDx6puQ5tzhlmn3XKP81d3h7xAA+tTQkjSxpgrqvz2bUWlzLt5jeCW8rJCEz+HxYyHN/Gp027rDPars+zjKwejJM5GKfCQv7crMXaxAJTRLdjHV2Zzvw/F3wfkdNN5v5nPisxroJkiQIEGCrJEEQYOBsDpuM7sgThoPfcvboAdaeFbiI4dilXPnryA/+jmiaJfDidMngX54GOzjY6CmFDEpLAB0CnzaDpaWAcqg/YR7pESagAIQ59dA+/lzEKvGQ9/8duB5wsRKGG847mFxJ8w2OSW+tWdegvLY/ZHdISmF+8iYiOX6OMuHVA043wnVITMeem6c4tkFnCvW3W6LU4hTJ7p4U/qG7a6xAMxsxvxa6E+tA3LTMF59M1DiGwDk734dONcOgLgW9vRgi11WZmWGgiDWVPsCICDzri15duc7s9T6vIqE2ZQoQvSMWUSA6OKieQNO2TTNfP8QD54IX7Czj49Bc2TIhPJSXm61eiPkFQth7Nnv58xMn8QXm18ud8k/e5XPQvt3oAX6uoyMNT19NpArZKMwH8Zrb/HxtO63qD76mjj+R24axiu7YstDfYv3mPsy3QAZUhje948Og824LeYeOmhP74ACBjsr5s3eTq8CjIzYwkUNVKKyZFlkuC4I3vfhmRPyyqbM74qEE5QgQYIEnxsSiezBgMkjCIJQWQZIYuYPr3fhl3L80ZNEn8StfZ/yUpDcFOSVTZls0Kjr+ALG/KNqS88+tRbo00Cbj9r3i5PsRmePWRJDQ8/jst0tofdwyX6XloDJ0f2h7R4/lkNHo893qK1xDktXVudaHJLAcx1cmNhzrfsqMsQJlT65X0tqnLae8ElD0+ZW2xyTCEK0VLVuQHtqHZf43rbHx/kRSkui58q40bHvySujTQ8Eq7NlI/VOW0+4pLJDF9cHW2Ds+oPNSXEGnEJ5KVCYB3nFwoyE+6q1UP/516DvHrAl3K3nGrv+AHHyBGir1kJcUAt5ZRPkBxrd3w9znFzwLIJjZazbOnlZVkqJnBfITWfGw+LsmGIWodeIYuAxG7qRlcy+T1o56vdReSlo81FANyCUj46+f9w9BiLnrMgw3n6XG80639XoETDefjfzbnt6+ZhfLBnpOPW1i6HOFvc+zN9VnxcfKkGCBAkScCSZoEFAEBEYcPAPnFK5nkwDYyzDW2jriOQQsNPnoP3qxczFUaVbuu6qP48t82KMPyNqgRFzD5KjQH7kXpC0AtreBe1XL0L5y8XQX9jq64+0uB7qE2tc19vtFUgk10MoL+UclfMdwYpp0yZBW7Mpw6WgBueQvOhX3RNrqgCSEZeIUkeTmhrA2rt4tixE8AEwsyMp2S9x3q9yEn1Pb+Q4xpURIsVLyqTFM/19Gj82VkLcWVbpDLBIOoCUnUV5IDt+GuKd0wHG7MV5Ntw2e/Fnze9jp0Hf/Sh4XAmB/Oh9PENmjqkwZiSMbXs4j+3NPwS/2x5P2ZZ3kRtnjnvmPIyXdnKj4IjvJtEM//0+bYvmBPX1R/Ne4uaB81mOfgm5Oabp8Tb/HF5Uz1X6DAriDRAdMHbtg/L9FdDXbQtsu/bMSxBvHhvdPidyUpAWzoC+bpuvtE9a0sBVIs0SOHFyjJT7ZwlU4jItFyETE/r3wcnv9PChEiRIkCDBxUcSBA0SonwnmHMn31K2skrYAEiNdZwQL4jQnvF7lNi8g+UL3Q+NKt2SJFf9uSWCENr+IYVQf/YbyN+8J/qeEWC9Ks9CgS+4lAcawc6eh3TPHKC3n/NjUgqYLEF94jn/jq6T63MXBevpAynI5aR1VYPy8FIgJwV6voNfr2p8rGqr+U4yZWCaBuOdP3GzVWc5liJzFbfGOjBnqdnT3ERSrKmGPHMyl6vOTUNsaoD4aRuv2R/CeTPqj7mss/xQhNCCRTzv16Ct3sDHwuTPIJ0CKS0ByYte6JCcdORx9Gt8nK0+3VXD+TKyDDKkAKwzZqe8X/N7DgE8u+TlbcSVB+amIU41MzKTJ2TeRSQYpMUzwc6cg7CyyTW/Iw2Cp1e5xpR85UbuQ9XXzzMM9V/l/B9VA20xeTePe6TcvYvcLMof6YEWsLPt2fF7nPfLzYH2i98FX7NmE5THvpbhJplw8V7iFuTOZ3nPJcgIbxiOOfwvGTl1OYp/omoApYEqiXbwPICAQTB/D4qzp0CaXwvWr/LfBaoKkpLBADtIuKgy0iHqf8DFzcT4/j6kFJ6l7Onjc3QQPYoSJEiQIEF2SIKgzwOOP7zGrn2c0C3LMLbu4R4dlmlhcb69u+3lEAiV/vKvKKlg1tGVeea2PSCl0dKszKA8a5KTirhnZ9bmoE7+ivHrjZAa6yCMug7sfAcPyMIyTibXR9+1D0JNFYwXd7ikw8WGKWCtJ+zrjW17APMz2tzK+SiP3gvjZQ+XQtWgP78Fwk3jIM6ewjk5jsU+O3oSKCsBDAJGABiUL+wbpoC9/a77XnECDrLEy4WssXBIQFvBRyhJvLwUtM2f4QocZ6tPJrcHANjOEyBmuVvs9d7Pz7X7eBuxUu9Di2Csex3o6rHnbaxHVm6OazFuYwACFrS5FfqGHVzJreVEIDdNuHkckFI4n8famEgpEG4eB/rBofj+ucaKRPN7ctN++W5JhGC2xXuNdPdsnqnx8rYcvJfIBXtcGVVeLtgnJ20Jdt8cBuxy2dB3m5u27xF4fIABAykuBCEE6O7l/5dEkMIhIEUFYKfP2v2MnXOfIVCJy9pfzEDkYvsSJUiQIEGCgSEJggYJUWpGQnGh6w8vPXoK7Mgxv8DArn3B5pvmfQCAOhZF9vleqejKMojjx0AYN9qWGyaCEF2a09Vjl/WEnUeKCyAtboC+1l/eFmQOaiuAWYv18WMhzpkKevRk7MKTNrdyIYHmVsDk2th99pSrucqvVA3o7AnnOnx4CNK8aRAmVHBCtrnDzTo6+YL50FFe5pPmHi9BpV1xCyWSm2NzbZxjIWm63Qfle8uhr389eBzXbMq87wGMM2DKHjvGyyfP3jQL+vrtruuF8lJId8+B/soboB99DLHudshz7gAMAyQ/B5hQAX3jTr+s9vQqLgNddxugZ1QO4/yI6EcfB5uYDkTAAvw7It1VA3XDDt9YsJu5rLf+3Gu+76S0dDZ0APSDQ7GSxdZY09YT0RmEwjz+HV+7zf7+RJW3CqOug/78lsBuWrwXYfiwCy6jci72hTEjQQG/5P3e/XyeectPrXsWFQxqwBD1OxJ9mdK/KHuBwQhUorL2CRIkSJDg6gFhjLFL3YgLRUdHB4qKitDe3o7Cwovg75AlaE+vr6zFglBZllGYsur/NQPqj38dfDNFhvL95WB9KqDpXFq7vcs2RaTtnUB3r2tnG4YOGCxTZpGSgdw08GkbjD8dsmWKtVVr4fIEMctbjF37IP/FIs4TSCtQ/88L4ec9vBT0QEvGa2hoEWhnN0hhPghjLrlqY8c7PEgzy5MgCmBHjoO2HA+VJZaWNIB+eh76s69BXrEw02bLe0US+djk54DoBlhvP0hOCsb+gzD27oc4eQLEW8p5yZuTj+NYdMsrl0B7ap1rzMWaagjl3LCU5OeAEcK9Xzq73eeCq7cFqbsBnJMjLqgFzra7F5y79kF+uAnaz58z27AYDARCYT4vDUorYIxx6eF+FWRYMWh7J98x1zIyuq6+5OdCWjaX30PVQHLSoOfb+TWGARQXAroBdHYBogQytJBvexCZqxJacygnzedMdx/ooaMghfkZ2fLiAtADRyDcNBZEp6bkN+d86c/xd4S0AqLIfL72m2VSlEF/aacvOJeWNPCAyszEON+B/HATQBnn8XjenVd90H4XDy6C9usX3bd67GvA0CLoL2wFGXGtywOHtpwAO3mG+w6ZvkBIydzoVlH4vHHMd3usFRnKDx6Evm5rpGwz7ekFunsACICmQf3Zb9zfJUUGo5S/s4g5qnz36xnhAydvyFFGhbQS6J3jO18U3bL8cAfcyiP3+mTEnfcM4i0BGJCHT+zvyKZZUP/XL13zwTlu5NohQHHBRTM0TXBp8Hma1iZIkODqwEBigyQTNBjIUnbVKocIKkeyoWpgp87C2LMflvEnVA3KuFHcYyhgJ1VaOhv6S9tdC0uhkvvVuEqUvOU8ls/P8oV8l91QwWQ5uuxHEDLHzICNKDKMl/yZAnnFQkDToa1aa0tEq6YJp/bMSxDrbocyv9Ys8+McHfXHqyGUlvCFmUigPHofP84Y6AeH+e71ioUw1vsFASyjWDXAB8ktAkAy/QmTc67kxqsI4u/09AXv8I8fC2lBTaAAg+zwQIEigwwbAmP96y4zWXth+uyrkJcv5HLaJlwyugCQn2v3V7fKAJcvAPUGlnbWYCPklUv4uw0IPsWGKTxY3f9fbgPbm8dBums69HX+rJW8bC5IXg7vr+OY/N//AkSRg7Nt4PLilleQ/Q4eaoKxdW/guBm793PekScDBnAum+U9ZCMvB1BViJND/K5MU0qvdDZ6+mDs3R+8UB8zEjC9bKIyCBb3RVuzCeT6Ee5yOMc78r533xx18F4GUkYVmG0x+0wPH7Xvb5doTp4ACMQ1Fr6+e57P2jrCs0NhHj5xvyN1w51pc/wOcm4kJfji4HM3rU2QIEECD5IgaDAwUNnVLAjP9GCLqdjGvUBgMGjrgr0z9N9t5pwQRxBED7RwBS1zYeErUQpZ/Et3z4Zw87jQHXT26fmM6lp+DujHx0Hf/a9Qzxtxcb3pUbTPzWlSNcCg0F9+I1ANTN+wHcKtldCf32x/LpSXQn64yc/3AUBGDo9VbDO27eHlWI4gNMonBpRBqKnylXbRI8fBjp/2kcYZWHQb7pljZzT0F18PPU9qrMu00eKL5aZ5EGOahZIxJfxZrSf4+xh/A9DTC7G22vSq2ecKNKTGejBN9wVJdl8ZIEyo8AkTkBHXRvfp7tn+jJhmBF4DmKVgZhvtsRtaxP1wgnyNBAKxYTK0X671ldAJ5aWgx05lviNwcEY6uiP9jaQlMwN3obMq/4rLeFjXHzkO+YGFECZWcg+v/BwYr70VP0cvkPcS6q/jub/zc3nmZJ4t+qzPiPPw8ar0edHbf8m4Ogk+f1wS09oECRIk8CAJggYDOSlf+YarzMUb9MQQnhkYz9zoekbVjdHwnVSLe+P5XN+w3S7h8dbZhy3+9dfegvLofcFStktnA1QH1Q2eWVi+EKQwP9LzRjzXwf1zHlgI5OfZ/YIsAQV50P74IaSVS1xlYbS9i0vlelSiaHMrxF41eHE9ZmS0LHMtl2WWFtVzUr51nZfz4y3DGVIIoWkW9NfeBLl2KP/c0EEmVoL19vHyL4CrcRUVhGb5aHMrpH4V4vwaEFF0Zat8582v5TyXsCxVeSnE6puhnzwTetyZWaDNrZAa63iJWtC7UmSQ0SMgjLrOJ+vtGh9Fhlh3Oy+NA5fyJprO5bEBCGNHcx6RKIDcMAriDaMgXH8dV9zLywEzKNDTBzK0EOrTG2FYKmUrI9T2DrRAWjAD0uIGkPxce+6wzh6QkmuBzm7+XspKuHz5+DEguTmgbZ3h87L1BCAIocpsYdmerEp3vBkPIoDuPwh6sCW6nxaXybHoH3CpUFS2JeR3BFfTi5HizvYZUWajMYqBTNe5UmbC1bk6cClMaz8HJOV9CRJcWUiCoMFAfq5ZzrPHvxh9qImXcp0+a/9CjPKNkBbXQ39pl69+H+PHRLchSFlL1YDevszCok+FdPdszhMxaOBCXJw8wecNApjZmRe22Ept8vIFADU4hyMKsgR68gxXw/Ps9gs3jYPyjbuhv7DVVx6kPLIM7Gyb/359ATvKisw5LVFIKzxDsv+A2yDTOW5hQcf4sVzG3AoMHef5iNu+0jsHevthbNkNcerEyKay8+1c/rthSmg2Q1+/DZIpAx6XWQAA1tMX7Dvj6EtQGSGokTnvgYWALMNwZu+sUrZte6G9+qb/M7P80bqnWFMF/eVd7nGK8+oxFQW1VWY2yLq/dz6ZgiAAIj12xLrbY5XZvOVhWZfuOLK+4uypMHb+PvOcOJ+t3BQks2zygkqF4jLSYb8jegbgu3OhZqNEiFa6az4KY/v/Cxz7BF9AXArT2ouMpLwvQYIrDzFavwmyhbFzHy/xsdzQH+LO9cbOfTDePQD1H56C/sxLYG0dADIKRcoPV0L5/grIj9wLcUEtaMtJXrvvAG1uBdMDGToZhClrpRUeeA0fBmH0CAjXDIFw3TWAFrBIB9wBggeWESY3Ff0DJ97HKXpRxhfrW/f4Fp2k5Fqfkar1HH39duCaIf77FeT7PhJrqkGU6JIeIsucY7DjHYhmiRsAV/vDsmNk5HCuiGeV+EWU0Bm7/sDL14KQkzKlk2PGzPQJinwXB1ogRGXhzHdl9yGlwMWFMhHaF+c7Ns9jbZ38PTrOFWuqfe826DPnPcmIa93jFDceIDC27rHPD72/GcTQ9k4wnYbeLUye3LoHnObG4Lu73g0L1/Oc5rdW1leRId44ZmCeS3k5toBK1s9zYiC+QjCDj5YTA/PduVCzUVmEOHMyhIoyXxvEmioYu/ZlMgAJvvi4BKa1FxMX/J1NkCDBJUUSBA0GunsgTrkVrPUEtKfWQlu9AdqqtWCtJyBOuRXC6BEA/L8QiapBX/c61J88De2J56D976dB//MjvgPvKR+hzUc5VyAAQkUZ6LFT/s+juAVh5SlZerXQ5lZAN7h3kBVQBLXr0NHQxXpcwEWCAj9J9D1PKC0BM4zwdpglhgBsQ1YrYEVhrj2uYe3xfp5NoBjYBjNQs/hZYW1FoVk2GJPdYhHZDgD2uxLKS0E7uvhzvYvQmL5AN2ypcFJY4Ds36PpsA2lb/SxmPCzJdOv8uOAQ3b38/JB7goYHSACAXk+2Ma50p93BdTNLXcWaaqDPvZsd2U/ndzWbUqEg5OeG/47w+ENZwQc7eWZg/KOoZ0T9vlE1rvQ4b1pmo2gl3yhyZU6vwAxAggvAhc6jyxUX+p1NkCDBJcUlLYf7+7//e6xbtw7/9V//hZycHEydOhX/+I//iMrKykvZrIHDYNFlSSZnAsj8QqQAT50fbPHziUzDT+2XazOmoLv2QXn8Aejrt/mVnxomA4TA2PGOvZiIJRQTEuzlMhCvls5uCDeMBLl2qKu/1vPFmmpoqzdAqAhZjAYFXI6xYH0q5O/cD+SkQDSDyzNLIsS7aoBXHOIIus4V22qr/Z5JFVzljQhiphzHVJ5iFWWQFtdx2ea128IDQO/ncYEi3CWCQgWXAGafngUQ4YNSUcbnCmUghXkA8WdunCC56ehmSJL57Aaov3ge6Orx+xN5ygG9vDakFUhLZ/GxB/FxhgLHIlvTU/P/7MQZrnDolZ/2+iJ5rgtFvwrhphuACv7doM1H3VLb6RghAHODwK7v7+yB/FBToJQ1ALBz7aBFZoayuwfS4plg7V2AorjH1NBBbi0H/eQU9A07wr+rF1gqJOTmcL+n5zf7FSSbZoO1dUAYOTwjAb73PchNDQPi3ESZjUpLZgGftoGme/xcCKvNgmPfLWh6S5KrdDjBFxOX0rT2ouALWN6XIMHVgEsaBL3xxht49NFHcdttt0HXdfyP//E/MHv2bHz44YfIy8u7lE0bGCiN3PmWhFr3h+YvRHqgJVKiWXlkGdQn1vCFmKpxKdtbK7lggMO/R1u1FsKYkVD++kHuIZQloThI5pl1dGXlUg8AKMiD/urbkObXQlw4AxLN+ASxP5+FFQyQMPUpb8AVJQRgLYZVDcJN4yDOr4VEANbeBVKYD+PDwxDGjQ41QWWMQZhwIz+myAADmKqCne0AdAPSgtrwoMPbzrhAMT83IwAhSVwVjxoAM+9vZqPEmmpbIY1cOwTGh4cBTeceRC3HIT96b7jpaGUZmKK435VzwQ0GMqQA4qzJYJ09EG/7MljLcTAA4uKZkAzT88dRvhU2D6XGehib94B+6JBgtzhDQkAyOctAmlxTDOW//QVoywmo//obKI/eC/Zpu3tuO7ME1n1j7s80A9q/r8m0taIMyne/DtbWCXrkOCBLkWa9kKVQqelgzhcB2rugb9yR+U7/xSJAkYK5ghVlUL63HKyrByQvByjKd39X40qBQrK4rK0D+vrXQa4fAdn6HZGbBrmmGMKQItDclE3aFqtvumDRAZ/ZqCLzd/jjX/sDO4sLkZfm8+uVN9wS7I4xFUzOnqWQl3Apvtj4QpnWfsHK+xIkuFpwSYOgTZs2uX7+9a9/jeHDh+MPf/gDampqLlGrLgBBJHgHmLceOKXYgVAUv0Rfvx3SvfOgr1oL4eZxgKa7JKO954NSl8EiPX02XKWGEBi79/tknunJ0zwz4uHqeHflhfJSQBJBvjQM+totPmll6xypsQ5MVQN5GF7Z7ih+in18W2YxLtZVAyBglIIUFwbyRAAzK7WwHvrvNkFsmAJ2/DTEqRN8ctHS3bOzaqdPbtzTZ/rBYZ+pp1BRBnHW5MwHTh+U8lKIs6dyrsyW3VwFr2EKjE27AwNVy3OJGRrf4T/fDvT2cePaT05Be2ZjZjFaXgpx1hQIk24EqboJoJR7/lj8poYpGSPS0Hn4OpdgdwRB1nmBEuJx49PKpduRm5PJhgJgqgZj97sgI4dDKC2BMHI4hBULuTz78dN2AB57/0MeTt3BFugbdkC8qwZkSAGYQSHOmhI4ruKsKQAhwfX91jxsmMwl5C1Fw5w0mEBAj5+23y10CsYYjG17A+Xj9Q3bIUyvgvH6Xr4QhCPz1NMH+VvLXBksV/9aTgBF+fb3mfb0Ah3dYGfbIE6ZANpywj0HnD47g7TAtD3PQkxQfVLHshItWd5YD1KYZ/9+SaSSrw4M5py8pIhSfL0Sy/sSJLhKcFmpw7W3twMAhg4dGni8v78f/f2ZtHJHR8fn0q5YxJUlGRkOghU8QOA7Qz6JZgdocyukhXXcsHLJTLATZ6KfYwZWWanUiATi1AmBWReMHwuhpopnR1QdzDBAm49mMjEVZZAW1YP19MW3v7EOtKOLL+YZc2edTpyBtHSWHXDF3cuW+FVkiFNuzZhrKjKX9V7zWvC1B1ogmSpnQmkJKBAsD75hB1fzA1yBEDt+mqv2md43oeVslWUQp00KNPWkB1sgNc7wLd6F8lJISxp4qVJxoa2SZ40FPXzUlTGyMiSsswekuICXPjUH76w7fYLEhTMAEOhbd4OMHgHZypYpMvDlcUCfmt3Yez4Xa6vtwMEaM2PXPj6O3tJEiwS/9z1IS2eDnW1zB5w9/W4VPs8YqT9/1n1/gbjneEUZxOnh4y9OrwLdfxBS6UgwTYMwsZJzd5xZQ00DdCO8vv/kGSjmnA1SNLQyt7T1BMTi/Gjp77tqoJvlsYFGyJ536dyIUMaOAsJU5Lxz4GJKDmcrddzfH50tb6yD+rPfuAK+K1kqOcHVhS9ceV+CBFcJLpsgiFKK733ve7jjjjvw5S9/OfCcv//7v8ff/u3ffs4tywIxvj+0he9gW8EDOrqBwjy+QxQnD9zbB2npLFPyN5ojwrkax8E0HeT6EcCR4xmHeMfOKgDAYIBAIM6vhagbQGcXIEqgx07xzAoI2Nl2oCgfYATCmJGcTyBLYIxx2eL8XLBOU0krxCeJ9fZD//UGAHCXfw0tAqMU6i+eh7R4Js9sODNqQfyUvBz7c1cQo2pg52MCYktEQNfDgy2TvC0/ep9dUkeuHcKL+hi4T1K/ysc0rUBcVM9LAPv6QRQZTJagPfFceGawpx/i7Cm8r/0qSDoFxigfy+J8Pt4WrHnhyBg5IXz369BfjDeHtT6TKIP+6hsQ75wO4+VdPglwcebt0eMnCTxg8vSNpFMwPv4EZMxIKHfVgJ1r54HaJych3lUDacEMu+yOKTJwth3SglroL26HWH1z5kaKDDKkkKvwBaoFvg7l2/cBnT1AOgWmSBBm3Abpzhqwtk6QoUWALIJ19UL5zv1ghgFt9UbgnHtM6cEWMEOHsfd9CLd/GaQwz/anYmAw9r4PqbY6eD5/cgrCTWODFQ1bT4AeOQ754aXA+XagMD8+Q6ya77inD9r610GPHM8YEVt+SO1dkB+5F+jkgZW2ZhMP3DQD9NSnfA4EmczCY456sTgJ2XIhYs5jvf2hsvIJElwJ+EKV9yVIcJXgsgmCHn30UfzpT3/CW2+9FXrOj370Izz++OP2zx0dHbj++us/j+ZFQsjNgdQ0C/rzW/y7/Etng505C/H7K0CPneJGnYoM5dvLIC2ayfkiESAphS+8e/ujy4AqymC8e8Be9ATxFywlK5u74GinWFMFbc1rkFcs9PuvWMfXboW8bK5dRiY2TIEwbnQkl4dMGs9/8JR/kdISvtg71w79qXUAuGkmgPD7VZTZPBSvwSkZEsMdSKXMLJwUHXiqGnCuHdpqHrhZPk+6M+hy+OB4RRjkZXPDfYJyUtD++de+PlreSy5p7RjeCxGEWONNZ+DE+lXQAy0Q677qX8B/dJiLSkQ/MJgPk1JgmP5AwvXX8XHLz4XyyDI7c2bB8sFCdx/oB4cgTp5gHxNrqsHaIwxOD7Zwf6uCXKj/8JT9ufyNe0CuGxZYvql8424uCGEFQtaYdvdBmncH9PXbfdkcaXE9QOCff+Y7J4T42+j0jXp+S+bjxx+IHlJLoEGReQAV8h2SxoyE+sxG3l+Hp1M25qv2HLhYnIS4++amuC1AOvo8EnY84VIkuILwhSnvS5DgKsFlEQR9+9vfxssvv4xdu3Zh1KhRoeelUimkUpffH0Xa3gn9tbcgzq+BJIh85zudAqMG9E1vQZxRDd1hMCktXwB6+Djonw5DXFgbnUXq6IKQnwvkpMLLsMpLIS2q5wGW1SZrN7judsCgmd1lw/BniZpbAYFA+e7Xob+wJXRn2WvOaezaB+GWcZAa68JNPV/c7tqRdpb0kMZ6FwfHCvJC+SkHWwDGXGp7AF9A02OnIgNERimXBO7oBBkW4D/khDMAyUnD2PRWsDdOUPtEkRtegrgzYsdPgzkEIpzZLLmmGtqufRDAIH9zGZdoLswL9bMRykvdWbMgeAM9UeT/98o/W20/dDR8HlaUATkpsLPnIdbdDsM0QHVJjwNcfKK8FEJNlS8AAqyMznZu2As3t0coLQF6gttmQ9WA4gJ3O4vzw72mXtgK+eEm4NN2AAzITXNOGKUwwtr34g5enmhKitvDZ75zi0vkRBiXzZJtD+MuMZh8AUGI5MNZ3yHAU8aZpQrfReUkxHEhFAXac69BXFQfPRaSX2Aj4VIkSJAgQYKLiUsaBDHG8Nhjj2H9+vXYuXMnxowZcymbc+Ho7YM0a3L4zjdzBC2KDOGaYqDQVIRq7+ZZpLV+eWBpcT3UJ9ZAeeRevtgYM9KnKmZxGYz9BwDAV05DhhVB3/iGb3dZXr6Al9ZMnpA538wWBIE2t/IypuZWd6nQ+U4IpSXQHTvgrusOtkBZOANC6QgAxFb8EsaMhFBZBmHcaNBDrSBFBYAogEys5OpeUTwjcYbrM6G0BNozG3mAKEk2sd5WxxpSxPknx/4M4ZZyEEWJJe5b/0ZaCfTBCWyfInOe1Zt/9GXSpKWzAUMLvgc1MpkET7bJGkPnvcRZU8J3zi04AjlXMBWSYTJ27ePy2Ru2+7OE0ydB+/mzEEpLIC2eCWPHOxBKSyDWVIEQAuUHD4C2dYJIEv+sqMCVYXGCNrfawbczqAc1gKFFvM+iAJKXA2ZQoKcP9MhxLhCQ5upm0uypYDMn8zI2I0aZ0aAwWjPS1kJ5KcRbysPbd7AF7Mx50P0HuYLbmXM8gCzIg7ZrH6QApcPQ+dDTFypsIdZUccnxZXM5P8l7D085Hrl2CCAKUHfty5yThQqfk5NgCy+EiaVcAOK4EHYGsq3Lxf9zjoW0dBZYp9tHJeFSXB24GHMyQYIECbLFJQ2CHn30Ufz2t7/Fhg0bUFBQgFOnuOFnUVERcnKuoF+EggB97bbwne+mWdxfRZGBvBweLJmEfnn5Aujrt/tkbVGQB3XVWggjruVcgfFj7MWGkyNikfH1194KLSETp08CPXzUnfmRTPneVzL8EPmBxuh+qjqXfzYzQllf16eCjPoSoKoQ83O4PK8sQd+4E+Ltt4DuP+ha6Msrl0TejvX1u4MYXed8njWbeJ9efdM3BtLimWBHT0Hb/DbwpWFQ/nIJz3qFKOBZ/jro17LzxkG0up3+whaIi+oy7Xbeo7gQhiNTCMDmJ0mN9ZAWzgDr6eO8FUJA/3QIwo1jsg7kpEX1UJ94ju/YB5jqWs9j5zsgzp0GcfYdQE8vnEGrJbKgb9gO+dH7QN9v5uqCI4dzSWMz0FN/8TvI990Z8fY4/8Nqu/bMSxDrbgf50jXcJ+ig/32w46e5T0/rSZf4hVBeChKQmXE968x5sNYTdikfbW6NLUG1uEOWKp6xbY9dikk7u/3jHjIf6JHjYMdP+xUYW0/A2L0f0uKZIMWFpnrk+cyFMeWg9vuIKY9FYR6EW7nnWlZiKReIKC4Es7Jpff1Q/2M95AcbuTx7r8kTEwWo/7EeyrK5UH64MuFSfEERFOyQIDGQRBo9QYIEnyMuaRD05JNPAgBmzJjh+vxXv/oVHnzwwc+/QRcK3YjcjYamQ1u9gZfitJ4IloT+6LCLwyFUlEFqmAJSkMsXb++NhLR8gX+xAQL1f68OX4BbJWROkjTAF6+vvuk+P85/xTB8JXFZXUcIjOde43/cSofZsrrk+hEwdv4+YOxiBCBUje+wW+pg5vPFyRM4nylIkvhF7p+Cjw5DnHgj9A3bM4tTQwcK8rlqX1c35G/eA1KQx6WkPzps38f2xgnxE4pVyqMZbybXmIXNH1WD/vxmyI/dD+2J5yCMHwtpUR1IYR43jQ3KMljKfd29XAmv9QT0l96ANG8ayLVD3eILzrZXloEePckXzz190Eyelq8fB1ogTqsyOUwZyXQr0JMWz4zNUpGclLvtBvUFQM5+kdISGK/vBSkb6TsuzpyMSEhSgFBAzPwy342TV2N9j0j5aJdSoPN8L6xMl/HWHwPV7sBMxcLcHNChRfbxbL/LUeWxVvYOqgbcPQf0vQPxMtafAaFcCKcP1fxaGOte97VVnl8L5KUhXDvsM7UhweWJoABcunsO6P4D/tLrRBo9QYIEnyMueTncFwKmYWCQOpqxax9YH+c6eBfJkYvmgy2QFsyA+ovfuWRuheHD7MUG7ekF3X+Qe6pkKy8d8WzLvyWUn9R8FOKtFb5SojjfFkiiW53OlNWVp1cFtjnWB8YcV/nRe7n6mKbz0rqoMTjQAnlaFQxFhnjTWKib3wY+POxTXQMA5YcruchFCDcqyBsHQFZKf1Y5I7mmKFOm1hmTmaAUyl8/COP9ZrCz7aD7DwJFBaB73wvMMugv7wK5/ks2dwfg3jbaL34H5bH7A2W6xTtreDbo1BmQwvzo9qRkkNISn0gCL5mcAabI0fwPRXaVdZLCPKgxc1fbtoe/P+/xI8ciuUxW5os2t0KZz02L6bFT2RsCO96p1Rb1iTWQls2FNL8W0DQwWQ7mb6kajL3vQVwwA9KdlJfvpRRu0nu+HURRgGvNc4vy7TZl/V12mu42TAYoBXTqM5klhfnZyVhniQGVMJmcIUapz5fL6g8ASF+Lzh4muDJBe3p9ARBgzskI+fhEGj1BggSfBy4LYYQrHrnpUGUnefkCkFSKl8I5yb/5uUBRPldE8wRN1uKF9fVDvOMrmcWsVy62q4eXJy1fACAmoPQu0L0/KzIgCpAWzYS+bpt/kWzu+ouVZb5b+3akrYCwfDSIKHLi95w7YOx4J7N4AgDRT4Z23S/EZ8aSCSaiBAYGIgqcsB4XU+s6xJrq+HIoVY9U3RJn3ObzxgEA5KQjg2FIoq2SJ1z/JYjTJwGMAWLM15AysDPnAYPC2PEOb8P8Woi1nKzvK/1bVA/W0QXhoabMszu6eJBzto0HTg2T+btRJND2Ll4mdrAV9MRpKN+8J7o9/ZrPDNYC61dBBAHS4pk++WZbIl7XuQAE4Sp3zJIvD4M1V8PKEGdOBijzz9mGyaCHP8m07Vw7z2DNqAaZND7WEBhAQJaH8e+drWi4BNr/eYHPV+Zvg3TXdDDdAASBZxBFLjWuPfsalL9cnDnXwa2JFTxQpIxcuaqBtZ4A+cqNUH/6f4NVCePuFyND7Qp6UjLokRPQN2x3mbGGlTBZ/aJn2qKz5XFzIKpNVyCX5Epvf9YI85H6jHMyQYIECQYDSRA0GFDkSDd0cX6tuag3F/2WhPCLO3yLfJcMsUEh3DQ2EwR55WJNbw3tmZcgfyNm4epdzOU4DF4dHAQ2ekRgdsFuU1Cpk2NHWmmsBwRAf3GHn8+wYiHQp9r9CK35t/pk+fWkZKBfs31S5GVzYezeD1Y6wjXutsR2CMjQIojDisAYAj1vMs+PWZDJEtjZdoh31XCCe1oB61XBDINzkryBSXkpJ/ynFM5taTkBSBIvkaypjlWCQ1oGSSsQhxbZGRPCGNRVazMiGYYOMqQI9MRpGPsPQBh1HfdEKh8N4ZZxQDfPRpJhRRDSKdDmoy6xAGnhDKgvvwGxYQro0VPh7aksc2dKvGOcVrg6Yl4awoRK22+JC3h0AQRg3f1Ab19GHS/mvdlzN6DsTBh1HTTnODjn7Kq1kJcvzGSPHKVxwozbuCHwwjou4ezhP1lj7+trXk5m40KSOH/PmZFxtuHYKUAUfUp0QnkplIeXgvWpYG0ddvBAigshNc3KagGofG85WHcv0Kdy89y2zvD5HCegECFDna0Za1QJEykuBGnrjG7DABa9F5Pf9HngSm//gBD2Xj/DnEyQIEGCwUISBA0GTNJ4ELiamcCTFDkpCBVlEKZPCpUQBiGQH70P7Ngp0CPHIN40FkCIXKz1h0LVQD/6OCuiPMDNMVGU55Bjzgc7dQa09QTIkeNgrScCy3GE8lIwWQx+jqqBHT0JVlkKY0uIfDTAjV9z07xEhpDwxXZpCej7zWCfnIRwayX05zcD4Op3lreON/CMK6Mz3m/OkNwfaoK2aq1v4ShUlsV6mqBfg77mtYzf0S3lMLbsgVBTxb2DQt4rGTMSxua3eWDz5XEQxo52czuCMgmL66G//Cboh4dcAhTMNG21RDLEhilg/+9PEKdOAP3jR1wAwnmfplkQbhoHevSUPZbO9jFzkSqMGQl69CSkRfX+TI7JZdFf3BE4LFzqWARkmWcTQ4IosWkWjM1v232NLX+0jgcGXyzUUBZARibacT1tboVYW815T4rMvbF2/cGXtRJrqqA9vdHdlg8/dmXBxIYpdtu9bZDunhMumLJuG8QlM/3BQ24atPlo9Hg0HwVrPcGlyC3ulqMdvhHq6IyWsQ6RoQ4rZfJzrLIoYcpNB39uIctFb2ibrhAuyZXe/gEj5L1GfucTafQECRJ8TkiCoMFAnBu6RTS3DBfTqUiJXnF6Fej+g1wZy9qpXzLL/8fR4dERSpKuKOO+Ot29EBwKdYEEZVM2W142138fS5pZlGyvlEBC/rn28IDQNLy0SmRYdx9fbK/3t0WsqeIKWo31YLph776TYTwbYvFEnIgkijtJ/FZA1ljnkvYWKsogzpwM4/3mrAJKi59BPzxslnkZ0MPK6A5yDpRhte3VN7k0umGAHmzJZBJmTgYEwoNKxqC/tCsjzuDcPbV8f6x2lZaAAuHqdOu3QVoyC+qPfx1YsmeV8pHiArCdv4e64x3enulVABhIYT6MDw+DdfZAWlQHVlvNA2iHD5K0oAbsfEdsvb/k2TSIe29cSa0e+ku7fO8ilr8kScFlbobBA5iyEj4ed06HeFcN0NYBCCJYR6dLP8EOSF9503V7dvy0XyjBPF8oG+ELOO1xMOW7vcGDkJsDVJZxSeywclAzA+M0uI0aQ1JcAGnJLC4+ESRjDYCePusvzWrvipTM9/IMI38PxvkJZbvoDSuvwhXCJbnS2z9QhLx3Y9c+nh23xG1MJNLoCRIk+DyRBEGDgbQSyQUhOemMf09vH1iIupgNU6IXjEFqaoAw8UYgz7+TKuTm8N3m5zfznUQHSZpIEpBSwAQCnO8ABAIyrAhMkmC8HKCgZu3uTp7gK+0hQ4tAj50CGVIIYVgRqKpCnF8LCSYHJCcF40+HeLmTpkfzYszaf6bIQE8fWE8fxCUzIemUl1HlpHg2QTMgzr0DrLsXJCXbXi/yXy6G2DAFpDDPL13tLMubX8uzJVYZnZfEf7AF4pw7MqVNZjZMW7UWAOKDKUXm0s7XFkMcUmAafWbPy6IHW4D+fgi1VZCWzARUHUwgIIyBdfXwzNGwIojTvgLx9i/zEjzG7MwZPdjizqLpeqwwBPr5IlV+kI8bURT+/tIKmCBAapoNfcMOu88uKXYz60XSCs9uOBfnlWWQGuuhrlrL30mfYzEcFHAR4i5HdJaTzbgNSCm8TQAIIRCmToC6ah3ESTdBnjrRvg9jjPtuORdZzueBgQwpgGDyyADYgQ9JpyCUj+ZlgXv3c7+scaN5MKjpYOc7QT/8GPJ37gehFLS9C+qqdVD+ainY5Amusjv1iTUQJ0/g3xdH6SbridkcsYIGR/BAe3r5ezIMLo1uUDsw881jzcGrMMdQaqyDOHca54BZZYGrN0J55N5AGWvWr4IdP83nryyBfnAY7OQZSEtmgp0LVhK04eV1xGRzQrlbpsJfVjyZuLK5AZTVXRJeziC2//NC3DhFHQ/1kRozEsI1xSAh0uoJEiRI8HkgCYIGA7IYzQVRRFeJmfKDB93Xe40RhxWZZV/7AE2HOH5M4B8G1tbBvUw8HkPkmmIIQ4pAz5yHsXarf8G6sA7sjokZE0qHf5BcUw3DU16k/PWDEG4aC6GowHwwg/aTpzPN//4KXua1sinc48SSl85NZWrijxzn5zpKowAzI9Mw2VWuJpSXQn5gIfdVaT3hUhPzchSMbXvssdRWbwh/bx1d9nH5m8tcWaGgQNB4v9nOJsgPNoIU5HMZbXN8Y7ktsvvrxs61g+TmQN/4BsQpt/qyOFZ2zdh/gBuUjh0NqakB+gtbYex4h3OsYAZUkhRPNlZ1iA2TQYYUBYpfSEtnQ38puNSNNrdCbpgM2noyUNZWf3E7pIYpYMdOgYwewQ+EzYVKt98Nb5sGY9c+CKUjYGzZ7efKLZ4J7ZmXYHjKF+W/upuX6L2wFdT0Awqce/fOAwhg7NznPjZ+LOfnrd/uu0asqQLau6D+8gW7Dejug/bUWt/4WN8X5dtfA3JTECdUxipxEytoMP8fxr/hgfdGP+cnx70xIpSWgBTmQzMVJV1IKz4Za3qunT8vINDnUurZSYkD/myOb2FMWSR3S/nu16Fv3BHPk4krm8uyrO6S8XIGqf2fF+LGKZtxjPKRIsAXK/OV4AuBq0a4JEESBA0KDBbJBRHvqnEdY9TIlFvFBA2sTwVEAayn17f7Zv/x+eCQW/66sgzSvfNM75UWd5vMBSspLXGZSNqLJs9CWqgsA4oL3L8A8nJc5WK0oyvD3QjjBFlSuPfOs3cFLX5PNt5GtLkVwsRKGG9ECFCY5wsVnLzPswHhIEOLeOZCkgBG3QfNRTnM4JT1q7x0CtVcnasw35U1AcCllyMEBVCQ51IDxJBCGC/v4p5NIeOgr38dwsRK+z3pG3ZCqKmCmDsN6Ovj4gxz7rBL6CKRkiHePA704098/Brb52fZ3AzPxDteoghtw/bAY7ak+7/+BsrjKyCMHwth6gRAliFOnQixttrO2NEDLQD1e1dFmc3axz3fEcgi9A07uZjH/NpgnyjzeyhMqPAdIyOHh/PzAF5K6vhZWjo7sP828nO4jD0AerYtWio8pdjBw0D4NwCfT2RIIZS/ftAWLKFHjvsynta53nIz2tML/XebI/tND7ZmZ8jrKWEKWhjLK5dEcrfYufbseDKDUFZ3SXk5KSXaTiClXJznXgBix+neeVmPY6iPVIIElxmuKuGSBEkQNCigNJwDcbAF0l01rs+01RuhfONu6Gu3gYweEassp/7TrzL1+4rMdyi6enn2aNokEEHgCx9naVh3b2w9vxV0uRZYnt1d6e45vgWBUFQA6Z459iJKX7OJ76a/tAvk1vJoKdzePrtdcX4oyvxaCCOH2/0iRQWR0tVyTTWYVZr1L8/wACaCfMtUFdqzrwKq5s/ihAWnFWWQmmaBtXUE3ldsmBwscLBoJvSX3gD98JCrDVIj5xJF+eTw4GCf/Z7Emipov/gdb9/Lb2SC6UfvixaG2H+QB4leFULHsyTTSycQqQhFPXAfJKgaQABp4QzO9QpRP6TNrZBnTvYENaPj50NZCecg/fksxDlTQRgg3nYzDyp1I/J7KE6v8o9LnMGtXAfl+yvAenoByssdhZvHgX5wyH2yIvN3aVAuy20KAYgzqiFMrAQpLMiU8bV3ghQXgKgapCWzgE/bbC+tsHY4+Tdhf5BJWgF9b2R2HIuunsjvkiTURvIMpaYGoLcfYvVNrhKmsIUzQKLLZEOyTkGcqcDyqoFwSS4lL0dVOZfLy/cyhThilSkDcNF2rePGKepvzBeR35TgC4+rTrgkQRIEDQpiduBZv+r2AzpxGmAUwoRKCKOvi14A63zpQ48cB/20Dcbre4PLZczFvF12FldbbmZ8nAssoaIMsLg2OWkwTYP+0k5IC2dw/oHzj+ywYm5w2N3LPzcYxIW1/Oeosejp87Uh9Nxz7Xa5mlBeClSURvcprUBqmg0wA0LZyGixiGmTYOzYx6WGz5wDivNdO8yhWYmDLWDnO7gogAdhcs0MDPrGnRmBA+teB3imx8o2hELX3QthUYAwZqS7ZE/gi2Bp4QwebIUR6h1j4c0uAAj17LFMb6NAzF1splMYG3b4s5De54oClB88CNbfDxgUoNR7S3fbzPkg3DwO0sI66Gu3gB7MvB955ZLI6wPnW9wcPN/BRU1MCJVlvGwQyARCpuCJsW2vSwhBfngpwAC6/4CrndaCl/X0gR46CmPz2y7lv0CkZMgrl4AMLQKK8gMX+1FlRz7Eibn0qzxADJD+Zh2dnIt17VD/hSELZ3rydGTJsNPPKa6tA+pnFvcb8PHPgl4VIIAwocIjH28KcfQOLAi6qLvWn3WcLkN+U4IEkbjahEsSJEHQoCCdit7lZMzFIxAqysDKRnKj0zin9E5u7CnWcGPMuFIhu2xnUX30fZ1KY7rOF8rTJ0H7+bMQSksg1lRBN5Xi9Oc8vIHKMr6D3dvHRSGK8qH+86+DMyoeEGe5R5xXhOM4bW61CdSh91ZkME2D8cqbthGpaxHnUDmzsiC6pnG57d+8wvlb4L/sojIE6O0LbruuB5b8yCubfAGQs1+SEJF9ATLPMhfsJJ2CuHgWxE/P2eR4RhkMkxdjq7o5/ZUCsj4+dS8AJCftK+mzeSKaEV3eZd2DsdiMnQEAfSqYJMLYvHtAfkFkxLXQX9gS0I7sOSyRn0Xckx5o4WWD984DFtTyhV5uDvS1/tJTFBfAeDGg1M4pejLqOj4WMe0guWmg5NrYXUgf76e9k2+69Pbz7FRumnP7YrgnJJ3imYldfoGMyIxFyMKXlAwPLxkWCEjZ/8/ev4dZVZ154vhnrX05da8CRKVAzkGpKtFECJQGEKooKG4KlFAiEoOkG+10tHMx6e/8ev6cf74zzzPdk87kG3t61Oko3VGioEC8gqAYwbFJR0yigQKp4lIgCNS96uzLWr8/1t777PuuguJ+3ufJE6lzzt5rr732Oe+73s9lbPRgrLGGdjws6OGQ4nLycooKQiGbgNUxXpkAt3TFRd+1vtB5usL4TfnIR2LkC/vrLvJF0HCEHC+M4N/ldHNeIA2uEEiC7bgTWtbSJqSBo7DzPs8VckMF5OZG8C/PQFmzzEmaI7shViJI0pUCXlWT891hbe2xxp+sqyencDYIfxjPeQ8eib6m6gzMzw5B+tpEsM8Ogh1syxU/TjFwwiME4Zk7TRfmmk+uhjTLKiCiwiJ0B8YelcgmdRv6+gc3D5bcs7lvP/jRE5DmTRc+Nlbx6Vd1U9Y2xQtD+PlfVWmwzm6xS73wXtGZkWXw9i/Femi4J1we3ZJPZ59Zhd5Awm62VXSztnZIX8/BJwe7HqKehdjPV2fEbvtQPhPhTcT2twL9WdCbbxD/bj8Vut6JTwnNc4yWNsAwcx3ZJN8Ui5c3FOgTO9MR4P3QqjTkhxbGc2uq0oBEww1gre8G9XurQs8ZlfjS0uJo+fj9rVDmfjOUK2TzfIa14zFcct3nE4aZvCYGGxd71zppnooLL9885iMfFyPyhf11F/kiaDiCI9Ek0x+Ox0xCEsa5tb+epPzlf71/QPBQQlTA3NAomysi1WSg/8tr3vO7k80wqePS4hzRXZah/NWDgKqC1N4J49Xt4bC9DW9BfeJhGK++O2hfHzvMXXuhPvVo+DXNngpzz6fgGUsMwdWRSSwGTCMnYZ4VcJU46BdrawdvPy12xF1jj7yXSd0GkwWO5Z8HWpMBRpRCbmoA6+iG+dE+4N2PIDfNFRAsbuauwXV/PFLU/vDzvx6YB36uC+xct0gsdR3k5huAG0eBThgrFOrG3ww6pUYU8C4oDykpFK9XZ+ILSAAoKoB0fx30ZzeCTrwlN25mgkydFGrS6lkPEc+Cs54i/HVAEEjaePtpyA/OD8p+V2dEZ9S3Bp3PdfeCF6hiniJ2B6OghZ7XrXsQ+SzUZCAvbwR6+8AGNEcO3/O6uytrFUWssztS+MD49duQv3VfJLdGXrkQMMO7mk6oEfc4InFOmgsiS4HPuX2M/OMEzr/jMSy8ovONhHlIfN0dF3nXOnGeyksv3zzmIx8XIy7nBkk+Lkvki6DhCF2PJWTbJpmBMIzEQgCUij8MAToGAFAV8O5eoZpVXyuSFsbBDh5xoFG0RnBj9PVbIX29KnhM03COFSUSYBusSjMnA4zD3PpeDpI1y2u0qa/fCpquhLlvvxhXXS3ATEGyNpkw2iwtzklR+5N3TQcMA9KSekgDWeFtYu1Om3s+FWMwQ3glSVCjEeXgH37iuTZ55YLIL0PefhrSghkw396duw7DAIoKRQG4cZtXDbCrO74rZ8EmnV33AlWYpTIGEAJlzVKQ8hKYf2gRhUa6EuoTD0N7+iVIi2ZB/fFaIKWAf/D74P2xOnRhimHkhnKof/MtcNMEazkC7acvOLwy8o3bHZ4OKS8BvatGdMgME2TczSCUAFkhxoGyYoASKGubwA4fBxQ5viOj6WDv7YXy8GKQ8hKPfDxKiqCsXQZ56RzhG5VSwDp7hM+PfQ1R99PyylGfWiM8erp7AMnqXrywBQCg/PDbkHr6PGtH+/mvhM/P3G8CEgWymjDl/en6WL4f+6oDRFUidwfJICBn5ueHPWOX6mqhPtAADOjghiHuy/94HlJdLXhb++C6sqsWAf3Z6I5DWzuQ1cAJhJgDY+I6iwpyRVRff+KaRXlJUDQlInEmBQk7qAVqJM+Hnzoz7B2PC+YVnW8M507zJdi1TpqnyzaP+cjHRYjLukGSj8sS+SJoOGKQIgSBkGWvUaTFW0FRIdjnX0BfvxXKt+6D1DgjQNx3hx+2Q2syQm3qQFsuwXR1cujq+0TCU1EGZDWoT64G13UoP1oD9vkXMHd+DEAUB0C8SAAAKI83gx/7EuyT/eFGmzUZSPfVgZQVg1SUQn9eQLhM6zX5oUUwNr4peD+NM8Db2kOTT1qVBuvoBtu9D2TsjaCTbgX6+kHTlWAA9JfehLxqUQCOx46dhLxygUehyy48aGYs2LGTgWszNu8UHCGOYFdhwQyY7/5fMQa782Kbra7fkjPOtDslPX2Q7qtDqFGk3eGwdt15dQbSirkgKIa5aXukuprx6ruCl9LZDV5cmFOJC7k/clOD8ECy18DE8SCyBN6fBf/yKxibdwYggsaWnaCzpop/u++9VRAbIZ5G0uypYk7v/lo0bM7urmg6YJpe2WpVgfLwYsF98wkJKA8vdqB/sd3TzFiwL455PJ/c52efHgCddCvM3/4e9J6vQfp6FWh12jHp5UdPAboOpBSxrqI6tJoOtut3gsPhk4x3QqLxcsgStZTRrNB08KMngHunCCEN94/wIOGwTndk6ZzQ9zr3b5NPuc/3I0+LCiGvmB/gXrnXrHrbuNDig1SUibVpi6YUFQCqCjrptlBuHK1KAwUF0TLKF6njcVlkm0uKQO+cCDJmdIA/yk+cHtpO8yXatU6ap6TX854r+bia4koo7PPPzKWLfBE0HJG04xayc01rXBwFOwG2EwyX2SG5YQT47n3Q7Y5RXCINF4SkqzfQZbILE1qVhryiEby7N2hUWpOB8ugysKMnhe9NVTo+ATvQKmSVy0qjd573t0KaNQ3s0wOQm+ZCeeR+QJLAO3sgTZoA3j+QK57iOmP314nzLboXvKsHGMgKSN7ru3JGmbv3OaIItnQ0veVmUcT5C4rHmkFKi8SOvz/cHKG6ad5O2rMboaxa5O2MWQphdOyNQSL5/BlAbx/IreOg1NWKDoEigx076el40ZoMpHnTwX6/H/yLY4kiGPKyOQDj4P3ZeIn2pXOgPLEapLQIxqvvhvpRBYQT9gtJaVJaDMM1jtiC2Oa59Q2AlBVBWjBDGPP2D4CkVLAub0fHL1stNdxj3afwYk5quAfm2x8KCNvyeUKCO6x7ShAoPtzPifnJn6H+5QoYr7zjuTbbMBamAX6uOxaiCErF37M66A0jPJLxAMR66emPP0ZPv2fOnWc3qwUT2yHAYdn+VmBp+NvieH4BaFn/gLfT6eIEQdOjYYAR/B15RaNQ1XMVQrQqDXn5XMCIUdi8hnD6tKgQ8gNzYfz67cBzKD8UtCNIOtaVvmud91zJx9UYl9PXKv/MXNog3CGdXH3R1dWF8vJydHZ2oqzs8i2OMOd1O2h1BnRytWdnmlZnIN1fB1JYAGgaeGc3UFIsXsxqICkVHAJ2BXAYG94Sr7l5OeBAcSF4bz8IpQKWU1qUg7OcOgPtvz0X5PJYiYw0pQa8p19wCdxKdpruSBDzr86BVJQKaeIIA00AUJ54WPj/HP0yXB1P0x1eDq1KB6A7/Fw3zM+/yH1WVcAZc/yPyMhymH9ogXRXNYyt73kTyjsnCkgP5zmFLvc1lxTCfPO3kQam0tI50P/+l+EXpipQfvgICOPgAxpISSG4ZgAd3SCjKgQUbCAr+A4pFShQwI+dEnAxXQfvz4oOg8lgvvfvIKMqwI+cgHT/bBBFBmRFyHNrOlBeAn7iK6EYuGaZR00wMN/rmqGv3wLlh98WnDPDBD/TEZhz5/3faQI7dioUTmWvRzJhLMy3P/Re+w8eAQHAvzon1k1ru5DmfuaVyLGpTz0qeGz9WfCznSBlJQF/HLsTCHj5Wsr3H4H+839zzu/noJEbKgDNEEVVcSG4yUAkCt6XK7IMq8iS6mpBJ4wFKS8RhWJvnyhiDx8HrcnAfGd3rEIX7+2H/twmSNMnh69LVQFJKQKuqkhAcZEQhBjIiv8vLQI0A9rP/y30+TN37YX6g0cE98y328fa2qH97F+D93wQa8I+FylQwRkDazniWQ9Jx1H/bl3O7NX+DnGtCfe1kBtHBiBxrK8fxvqt4d2JSbdBWlYPYjABdSxKgVMKnD4nus4jSkOLgNhj1mSuKu+Oi3EtV+qu8bV03/KRj0sR+WdmeGIotUG+EzQcYWjCOyQEOiI3N8L8Y0vOJ0i2OBSEwHhtB0hmDKS7agTZ3w+7mj9DSCDb5HYfUVlZ1wzDKk7Un3zHOyYXVMJPbqY1GbARZR5PE6cjsOEtSNPv8hQUyncfir18YhGy+W9/H91lsLphAejOxu2i4HLzQpDbLddffAPKmmWiaEqPCe5g/+kgDMOA3DQ3N39uUYR1zdFdkv2tkO+3OET+pFtVRAH1+m+FwakbSlZcCDCRyOm/eFHcG1WB+sNvg4y7KXwdPDgfvLsPSI+B/ouXAAg+Bh13E3hnF4iqQLfvR9Kuv2lAWbsM6O0PyKaHdnYkOb6b13oc6vK5oLfcnFtvJYUw3/it19zV5grFiC3ws52iYBxVDvbJn0NV5OyOjpgE11eQaTr3IpSDZnPYLOl2f0eDVqXFzvj6rQKWlx4jYGU+2BeZUpNg6JuF+eZvc8ey7q+yZqkXGojcOjU/eh9Sfa3jE8Xb2iEtqRccuBBxAVqVBlIq6KiK4CBCOhuJKnbHTobPWWA9JOx5ubs7briVqkB5dBnMXXsD98SzQxmlWKYqkGZOhvlquOiF9vN/A50wNnS382roeAw6LoKi2+XctY6NvOdKPvIxtMg/M5c88kXQsAQVBU0IdMR4bSfozMnO7qvdCZHuqoY04y7wrp4AkR7IwWdsJS6/qSUAJ1m2ZZPd3RVaURaZOEjzpguyvP98sgzl8WagX4M0YzKkumlgre1gB1oTFexC/VBsz6KmBq/UsCvJJ2NGx16/3NQAduwkpMYZIGUlwlTS1/Fg+1sF0T0skuSpdUPsUM+cHJpASnXTwI60B+FvCAoPcEWG+XLQv4a1tMF4ZRuklQug/++XAcBJWI2X3xbqaITmPpAkglEq+EduDpZ/3uw1Q6sz4OAgpj8Nt8LmiEQkp+xgWw6+1tIGY/PO6PVojZ1UlodzlOyxLamH+faHAdlq20MqDrIFxiGHFED+awcQeQzemGwUyg60ApIEec1SEBBApgClIOlKwMVZs49P0pUwt+1xCml9+x6Qg23RmyMPLoiuR0K4HrHGv/fNBjvQGj0nlIiuEwCQBC8lVwHmLj5IZmw4VNEPo4uAyEXeU996jVJ7uxJw+kONsA7NdeVDcj1daz7yMRyRf2YueeSLoOEIwxQ4988P5XZ8rc6BNHMKSKEK5bFmDxxI+sbtMHf9DlJdbeyutFRXC1JWGq4uJ8uO+7ytfuV0V5rmAroOecG9wPJ5wn9iQAMKUzA/PRA8lr1T+/oHwWR4Ti1wy83OmDyv1U0DegdizTHlJfXQNu/0jNuZn69XQQtLqFUFJF0Jmq4UsLICFayjG8bGbUBPH2h1BuqP1gg4mSQJRTX/9dTVgowsDy2c7CAFKqRF93qTdh/sUPneKpibI0wvkRMeIJoeey9l67zymqWAokCaOQVSfa2Qsu7uzb03YdcfqgJy82iwliD53z6XUlcrOGazp8LcvQ/yontD3zvY5NR9zcrcb4YWQWHeP6HzYL1Xum82CKVQ1q0ACAGXpWQOmrWejJjjK3W1gCpHHiNJqYyk1Nzz8MF/5Na2qkBuaoD6N6sFDNWC5KFvACgpgv7RPihL6kEgYH5kVDnMA62QVi6ErGk5eKSqQnvxdajN80PPH9r50HSYH30K+aGF4Ge7gL7+HLTu7d2Ql9ZD2/5R+JzsbwWWS6A3jopXfQsh0zvFR2cPNDdc0n/8rl6xQxnlEzQEYYeo3c6hdDwuN0Qskhe1rCH+g1cRvykxkq6lKHXZ71M+8nFFxTXEf7xaIl8EDUf4q/MYSWmpbhrobeMd4r40c0r8sSM6GbQ6A5QVg06u9praq4qAs73yDljrcTGOt36bCJlKSobJreNA0pVQl9QLDoymg7UKkrTyFw/EXgI/15kj//ugO3zsjcEPuOZP83Vm1CdWQXt6A9iBVhivvuvwi+SVC73QnYjPu69bSP2eABlzQ0D9zH3vBKQuIuk+0App4b1Q1jWDJ+zS8P4s1B+tCfrgVGcg3T/bKXxiPWNWNAKcg3d0xZ4LBSqkRbOEKe2hI2DHJoYmv4NKTv1ckOJCyCsXwti8w3NfHU+j6nT82HRDdEg27/TA7eTV9wsI6GD8deIipQB+qqPrGnhWg/K9VQG+jH0drKsn+Dy41oWH32fD4d79v1CfWAXjtZ2eokl5rBnmK+8ENhbUhxcDfdHrJbTzkVJhvLIN7E8HvYX62BvBu3shr1kKI0xaHnC+o84HWkaLCsFOnokcqzi+1YmNUiwbis/ZBe52Xm5iMevrD5wfEAUea22/fnxI4tTr7pwISHKA/5AngOfjuo68T9Elj3wRNBzhq84TFbSW1OUS5sH4/yje9zhQpc8OgY67GWAcyncfAvv8C0t293eO3PRgd/kHkwzrz20UHax39opEzApSnPBgSrJ33Me+zI3Rgi553h5TkBmbd0L5q5WCuyJLopjJVIIdFZA5ACC3jEm8bt7WDun+OqFkxnIJc+i5kxK4rh7oL76RgxxFBClM5RTNSoqEnHdZCXhWA5EkyM3zHWigI5s+bzpAiVN0si+Og/3+c4+qWmgMaNCf2+jheqnf/5ZIoj3zksARYWYkP0f98VqRpBeo4IQAZ85BeXSZEPyIi8JUACIGAPxsB8jIssQv+sTjZ/XAxsBg+DK2Upn29AYoqxZ73pu0SUDrpglIoV9Jz8fZsj9jvLIN8kMLYy/D3/lgp844BVCsb1dYIeT6jgoUWCkVkCXwrl5wTQ/fjU/5Oq3+UFVnzGFFFooS7pn7ezDpXDERV4Ccj7HqeUUMrt948wOo338kEiJ5LXVB4gpuuUko5PkRBJf0Pl1Bke+I5QO4xviPV0nki6DhCFXxwJeSCgqpuw+kVKjBJUGfeFeP2Dn+2++An7ZUuo6dBAjAvzgG3QVRodUZyMvmOLCVwUJQAAxqp5bWZIDyEsirF3u/sE0e8OZxxlSTAcqKoT71qCMJraxZ5ow77Ppjx23JbdsJvtN9SFcCt9wMaekcEJOFQ+ys61aX1IN/fSLMt3YLr5+J4+PPnWS2ekMFlO9/S8AT42BssuwUQOoTq2C8usMr0TzpNiGg8FWHSGIVGZCIMIwEIE2uEYpfG94EGT8mnihvcbCcwm/6ZPCePodj5oh0JCWnFWXh/J79rTA2bQedPRXG/34ZNF3pwDLl5vnxu1myFD7ucTdDf+YVkQBFraeqNFhHV/S112RAbqgAp9QZQ2wBQ4lQwTMZWFcPtKc3iLXtex7OB6KX9JmkjlcgrI2TwciUm76C1V9Y2gUW7+iK/sF178anlPi1nVKcf4d2sWi8Z5K9XmlVGuzwcZAC9fy6AVcCsTimkyVNnwxj884I/ugOyKsXX1PJr2ct9A44BsD81JlYwZrriQB+uTuX+biy4mrkP17NkS+ChinkFY1C4a2lLbmg0A1wzoWBZ3kpUJ2G1DjdA8+h1RlLDKAI9IYK4c9hSQlLjTNgvrc3mAS1Hgfv7Rf/UBVB5o4dNM0pfSUlw4UFAor1VYfg35QU5aR0vzoHqXF6zpvHClqVhjRvOkhBSvzwV46GsmaZJ2EKhX4NEjoT1tGS7psN3tEd/IwbDqXpggu0YAaIqoBTkku6Q84dW6jWZABKQEDA+wZEd+nND7w/aBYM0r438qpFga4BALDPD8FgJqT7ZkP/hZATlxbPAj/XJdaMXRhFzRusOa+vBTt6MqdIqMhAaTEIIUBZCcxdubUjNc6IT24NM5rfc6AV0txv5roPu6wu29lO0ZXzG81aa5obESINhgFoOoz1W8W1ha2nummOOlzotc+aCu2nL4BOTEN+YJ4o1BKKavk+BsNf6PmfhySBjbCCJmkdW8ky6+z2GosWFYCWlwbfb3VzhrK5Qe+cCHnFPFEcnDoruiyEABIBVBXGxu2D65ooMuSlc4ScPyE5s+F0pYAwKjLYqTPenWzr+wEA2JdfRRvo2hsZrv9mn451zj+kXfIrgVgcg9t37t1nB8N5ntdg8k+LCsEA0QW31hpd2xT/oeuEAH5FdC7zccXFFav4eA1GvggajlBk8K5OYQ65pD5ZgUlVQApSMPcdCCSJ6g+/Dd7RLRL5lAIwS8LZrdoUlgRZEBlw13+ThCKIUuHrcrYToCR69746A67rwMmvoP/La+Jv7p0qw3SkgQPGis9uhPLXD4HccpPgMZkmiDvB1PQc9Mv6LLlhRPy4XZ0ZD6m6pQ0yrQf3d25i4FBS3TSYH/8R8gMNMF7dEdr1iS04Zk2F9jPhbaM+tQa8px/0rmpIs6Y588C7eoSfjyXeQMtKoon9+0Vhof5kLQBYUuVtOSGJu6rD5y2lAFk9vku4otGSQJ+cu0+qAnxtIvD6roDqmNzcCHT3xd+L/gGYuz9xClGlrtaC72mgk6sFbM+Zh25A07z33x323LuuTV1SL9anz6jTeX3pHPD+AUAzPK+zzw7C4By0bpqn6A4LntUgLamHZJhAd49Yf8WF3uchqRsYBuFKgroWpsDOdHhNVoGccaZfPtvCiycVV6QoBfWH3waKUoJ38eu3vUW5I+v9KaTpd4lz++Bz7t340J1qS5iEtZ0AGVGW4yrZr/t3sikBKS3MdSJNAygtAVQZRDOgrG0CO3w8d//2twK9feCaPrRd8iuBWByD6x+SRPm1FP4O3SCejesiroTOZT7ycR1HvggajtA0IJsVhUtZKVBSGAvnQUlhwBcIELvmttS2LXctr2gUL6bU3I59SBJkQ2RIuhJyU4Pz37EQlJYj4EdOgIwfI8wbf7Qmx1lxvU+aPdWBsbk7Kuz4KZCB3A54mB8KAKCrB+bbHzreMOp/+ktvkuDy9aFVaUhL6gYFnXHCNR+8rz/QuUkUfUhXwti6SyTMZcXBe2cl3XJTA6RFs8T9JhTs4BEnaZMaZ4B9cSxUthqwuiAr5gmIYxIMihBwTYe59X2nALKLOHuO7MTV7YekP7cxukt4QMDX5MWzYLz8jvc+qQrkprni2rp6cvCcze9BXhyuKueEBfFzug+GAVSUwnzjg8j7Jz8wN/T+eu6bdW107I1OB9QTrtchy6EGoOzzQ0J4JBvuaeREVof+9Eu56fibbwGGCXnFfBibtglCe5JPjwVbdb8+GJU/fwEEWJyhX78N+Vv3eTpCNl6cnT4Xfz3FhY4SXJjxnkfW21KoDJU8789G71QfaIWxeQfkhxaJ7zJXAQSE7GSrKoxN74Le8zWQsmLBg1MksI5umB//EeSmUcExmBz6piHukl8BxOI4XD8ZWR7/4Ws1+fcVd4nd9euFAH4ldC7zkY/rOPJF0HBEX1bIXlty1ujqgfzA3KAKmLUDSwiNlZT2yMXaCb6mQZpTCzrl9lDZZ6c71NYO9cnVQsGqrT3aW8QqbKDpUGZPg6npMPftB51yu4czYu+u03RltCFjTQwhG3CEEXL/JuFJgktyW6qbFhy3Cy7jCY/hJoP50T6Hc8Na2gYn+rB9D6SZU6D/4sXcnLnvXboSpKwE+j//WnCannvZcxwhp43QH3X7WLJhivufINGMrC66Otb5PUVcxD3lXT2gNZn4az3QCvn+YIFJ05WgE8ZC+8f1wfu3dJAFqb1OZRlEorES2YK3Ery//MRpyMvneZ+bwQiHxHVGDAPs+Kl4jpGvqOb9WVFUWcWhvKwBvG8AZOqkyGfa/PiPkB+c7xGeMHfthfJYM0BJYJ0LlT8WP0+9/YAPFkcqykBITNfWnUDG7TK71r2HG+iOwlTyTnX/QKAA8rxu72RrGqR7vibU9UKeaVAaHANjQ94lv1KIxVG4fnss1536k6+4i1PAvK4I4FdC5zIf+biOI18EDUcUpgTELVMJUl4CPqABjEFqng+prx+EMYHFp1SoVvX0xx/PzdXpt7oG/RpsySvelfOUISNKoaxdJtTSAGHaea7T+W8PZIqZQEUZCKXglpIXa20HClRRVKkKyKhywRPwJypzasF5tAElGM8ZS1o8FNbaDn78lCfJpDUZwOTg0CE/tAj8TAdQVABiMvC+foBxoDAF/blNOdiWTAOdF/fYPKTq1nZBPt66K0c+ToBDOUm0xUnR12+F8uTDkJfNETweDu+5w5JuwxC3xycn7S5U+YAmjv2DRxILC+qSDvcUNmHwwZHlYD19goczkCDTfa5TzItPdY6fPgvA4gi5xs4BweUgJDT5dwpSWxSirT1ZIjurgRQVCsNQ0xQCAYUpwGTQnn7Juu/TAImCVJRFJ432+SaMhbxuRU5pr0AF6+yBseEtQJbju5y+otpTFGk6jJffFsXlrKkwd3wMMn4MlPpaQJFBCgvACUC4MIA13vqth/BObhgBLhFIy+ZAZgAfyIIUpMAJRFHl97ayw1pD4Bys9biXx1NcBFpeOrhEP2kX2b3u/XNrJ+RJXafB7mSbPF6x8b7ZwfOHbagM4twXSiw+X6Wu0M+5eFF2XAlF2iUPf4fO/T3WOB1EsURarjcC+BXQubQjr1CXj+sx8kXQcERJEdS/WQ126KiwJzEM8KwG3tkNetstIkEcWe4oMclL5sQfj9BcZ6VAFYRj0xQwko4u6Ou3eP1Z5s8A3LLB7s6LDZmyIVW/eV8YWlqJOk2PASlMwTx4BObOjwWh/MH5AtrXNwAyshzmZ4cADhBZju1gSfOmQ/9fG5y/uSWHnbHOmuokutLkGiCrwdz+UYAbpaxeDHbkpPhDVgMZWQ4ywrsr7idVyysXwHjrQ0jfmCSKhkNHAMuQNTbsboOLkwIGmPsPASYTqmxHTuSSsrDuhCwDxYWxUsykMAVlzTKwzw6JjsfmHaGdMH39VtA1y3LH9iepLhgcYBlzyjL05zdDefzB2EslIytAJRnsoNcjhz7+IJRHl8HctTfQ5ZNXNEKaPwPS3G8KPxgfP0eoGHY7Y3d4S1Ehy9B++oJzfJvfwU6dyc0xhzD31Q1ITXOBre8LQ2LfXJl7/wRy950wX9kW6DCoT64Gs+4bP302V6CYBsiIcketMMzryB1sfyuk2dOEeWoYr+z+Opi/2Q1y06hcASnL4KYJIinCD8m3vuUH5iKUHxLjcSV4PO9DaW4cXKKftItsr2MfR8udkLPCBE7YYHeyE7pestyQE/IoKgC5oSK3sXMe5z5fYvH5KnVFmqOuXCj4T32uxPI6VH+KMgDmR0+Azpx83aqgXSmdy7xCXT6u1yCc+10Fr57o6upCeXk5Ojs7UVZ2+R5U1tkNfvpcwBPEKVAoARlVAeOlN8H2t0J56tFQ2WH7MyRdCd7WDjrldgCA8fLb3mPaiZoreZMfXGCR6FuFAldbu9ezxP6bBafy78q6IXI0XenwkqTGGSAjysA++bOAi4XxM6xQ1jYFXrdd0nlPn1C/+2gflFWLBBfhvtnh3BHbZHL7Ho9JqZ088r4BsTMuS0BHF0AlsDbRdZKW1QM9/dCfecW5Tns+k+bb4WJZf6PpSgcW5XR3ZApSUSqgdq7EVmqcAVp7B0xfF819HnnlAmj/7zPiDyVFUJ58GOjsFR2ZrA7W1u4UJu57aPN9Iud9XTPATYBQ8K6eaF5SVVooz/3sXwN/p/W1YLt+FylzLs2fAVJSHOCy0eoM5OXzwHUDxPJu4hKFuXnnoMdAazKQH1oEZMXOvsdw1J675vngnT1AX79ThPHjpwTsNMRzyPncQwsBa71o/+P53It+A9gbKmDuO+A1T3W/p0AVSRtjIJSKe2Z1J91r2j0O5e/Wxa+HhxbBeMUrWhD27LrnmkwYC956fFCqUVGcIPv8JF0JfvQE5IcXi25cyA5w6DHseakaDyLLjuxxwHi2JpNTeDt8HNrP/y1yrMq6FdCf2+T97EMLA6IOYcceroidr5jzDWaeHT+26zyxzHcbwuNyzsv5rvt85ONKjaHUBvlO0HBEVos0RQQgJGp7+8WXjKoAhAhJ7dfejewEQNMhL50D7f/7Vegx3WRm1tIG6LrFp3g3FG9tQ6oiDVR9HiM2T8DctRfqDx6B8fLbCDM29URIh4TtF8fV/0l0g9znl2l9aLIXaTJpCUdITXOh//f/Ez6ExbOcJC2JR2NLV5sffoIwmV5qfcbTeVEVqD94BNLsqR4JZ3PXXkiTq+M5Hm5BhJ4+4EynUM9b1wx9veCUKWuW5VTbvj4ReGt3Mim/rR30G7fDfG2HU+QGrrUmA7mpAbxnIPB5eflccM2I9e2QZk2D2XIkoPjG2tqFJPUEIWmMzh6gozuW04W+gcDx+elzYAePhBYArKUNxsZtoHXTQCwOEJ04XsxPNps459pPXwhKgfvFOBbN8hLzExQFAQr9mVzX04H21NeKe8c5SJy8eEsbkM1CmjcdYDzwnIZ+5kAr1PvroO38WMxzQmISucvsUodTVi0SMv0x4RaIGLTxrH8nOwmS6nG3heVD9S7klQthvPz2pdklP1+lrkFwr+yu7fUufZyX/g2PyzoveYW6fFzHkS+ChiN0Iz7ZMUwB7YGV4P/mfbD2U1D+aqVHStkNMQIAfrYjFBfPWtqgzLkbcPM3OIDSohzMoi8rJI5d5wYSkqyWNihL6mF+tM8lyKCDdwsO0mCS8dBwYfdpJnd+3hfOjUok9zMTymPNYEcFXI6Ou9kpHLgqg+gmpK9X5eBEUTyaY18CI8sgLZ4FcAb1qTWAYYITAvX73wKyOpQnHgY70Jbzb8qMBQeBuefTgOEhH0hQffOrlFlwH3bspOh8bdsTSCzlZXMAiQLfuB3Glp1B/6HG6UKefHKNc1/81wpZBkaWwXj9A0gPzIX647XgA1mriDsC7ekNghMGRHKawEyYH/4eyuPNgp9mc6AA0NvGQ15aJ56DIycFof2PB0MNIc09n0JaOBPSwns9944UpkAn3RpvSLp0Dng2C1JUCk4oSP+A4JDFRX8W6t9+RzwDd98pOlkhBQE70OpVFGy4B7yrB1JdrVCYc3G78Fsi7os7fIWy8oNHBsWXCUjL+4sF//0ggLxmKXhHF1h5SWIi7YHN9Q2IAo1SQCKQVy+OLSQciMzh42KMs6YBZUUwXw92b23jWfVHa0SXzA/vGqRZqueYfzoILKsfFHRsKDvpke89X6WuwXKv7PPvbwW6esHyHZF8XAmRV6jLx3Uc+SJoOGIQErwoCDE67OyJhTkFVNXsUBWQilLwtvagStuqRSAhZFx26oz4jyQDx64eqE+sAu/oyf3NFF5FcYo+0qypQdU2O2zsvqqI/zmDikhgk4wpv+qA/vxmTxEAQOxQW/AjxW/GF8KjMV5+G8r3HgYMHVAUGG/tdngf/o6R+qNvAwaD+ecvgK5uSHNqA0WL8qM1seNGoY8I7+qcmds/Cu+A/OZ9SPfXgYAI2NnpDqeIM/cfFt4r6UrhlRNxrQCgfKcJ7E8HIdVNA9d0x3CUHz0B9PSBWPcmdJe/OgMy7Q6o310JduQEjM07c1DMmgykxbPBO3pAGIfx6naoP1kLMnpEaFEn1U0TUMVHl8Hc/lHOy0hVoKxbETt9/GwHzN37IC2bA3Pzu2AH2kSBExcpFdrf/9I5h9w0VxRTp895Nx6A3Npua4c0uSZUSMHpdhjMex4/vI5x4dMTF4Wp4Lpc1+w5ZtT9kB+YC/QGd2gjE/whJth+aWy3FHtcxxCUhIoBQBLrN2xO3bzBQPRlQUePih3/UPgMce8d1P0ayt/tCOmQ8zMdAfjf9QyTy8dljLxCXT6u48gXQcMRSV8SBSogy5BXLRIkWSuEklYmnIdRnYnsrEgN9wgVtJBd6iT/jFjJYVUBykrAu/oE7OupR8EB8J5eZxc30GUoLADKi2FueT+0a0Wr0uCq4mDj3YUPZyx8d3gwssjwQvgAn3LdII9BZAr2VTfYJ/sd35RQGN6rO0Cn1ACaAf2Xm6H8zbcgLakXD5BudaEUOXa3m6veIoh39YBWZ0DH3ewxNvWce38rpAX3WhArUYg6RZ5mwNgiVPBIYYQBqR12Qd1nmZtOnwzzo09zfBDA8ZeK8hiyuVNu2JOtDEjrpoH0Zy3ejAkUFwpVNBDwji4AxCk4AnBHt9FvXJSWCM5bT7/DFeOqEit/zRUp9wdL7U1euRBs3/7AZ4QX1FxItrx9lJJZXS14X3/uXkcUK8qTD8f7BIUYrLq/EyL9rSxYqBBXyMWFkps9BZSqgNwyBjh83PtcJ22iRO0aqyqMl7eFdgeNrbvEegzrAiZ8t0b6GIXAzhLf+/DicKUuq3gG4+I72d+5iVP4iuyQB+F/1zNM7nqPy8qVuoIU6vKRj0sd+SJoOEKSYosZyJLgNEy5HWRkhfOauWsvlCce9nBLgBx5nJ84nVNMsgudj/aF71JbDu789FmgoxtMNwJGi3LzArCW1vDEzBYjeP19rxiBJe4gNzeKc+5vzXEpLDEFnOuGNHOy8GQJ4YAQzYB0fx2Q1cC+OObMFaE0lDvCu7oHnVTYmHsAngR00NA9RQEpK/X4poQFa2kTnJqJCsz/+Azo7BYy3haRndw6DtJd1bFcGKLrUJ56FIQQAUcrUCGlxwCd3aHnzJ2cwdy3H5CoI1cNWc51FT8/BPr1iYO7XlUBSVcKZb6ajIBIFRUAigx6yxjhLxVx/e758XPSpPpaRyoeVAZ6enIJrCx5il8/3NFt9BtbNMiSOH5KEc+FKcQYpGVzgNc/8KrHWXwvYnKLh5Yj7Rubd0D98dqgyENmLOjEWwQ/KazbYc/d16sEB6+pAbx/AOzw8dBiBZoRz42yuDPude6W806ChYLlulGDSfCjxA+AiALKx/MBkLy5UJgKTejQnwX77CDw2cFQTyJl5pTA3+0ELCpBZH39gn82fTKk2dNycEVrrAE+QxL3IasFOVSOSMtHXoEaV3GZxL3yd8gj4X95/sV1GZdbme1KUajLRz4uR+SLoOGInr5csuNTzpLqpoH39ItEsa4W7OjJXOKj6dBf2AL1uyvBz3Xn5IePnRT8it//OaCSpfz1Q+G71AdaYbz6ruhm/MtrAjLT3Cjc460vMSJT0KoM6IRxAXlmuanBkqoO3/2mU+8QMKJZ3TkODLiAJ93zNegvvuHtEKkKOGMAIQKqxTlQVACaHgPcdov4t6YHPmdLcgufFASuP9Qs1d6dLimCvGpRzi9mSg14/wD057eI5MJ3DFqVBjfNWL8Ud/DT52Du/gTqdx8SHT1VAf16FWCpxoExsGNfgtw6LrDbra/fCvW7K2G+9WGgeJWbG3O+UCFBUqoofu/9BkiBCmneN0FKCsENM/e53gHIy+eGKqu5rxcjy8Df+/eA/LL80MJkSWJrfvxkbwCiq6EZIoHfvBPSvZPBT50BykqdIj7gaWWf32X0G2fui65u0XF587fBa7y/DtKsb4i5kGXwrm7xrOlGrnu14S1I0yeDZirFM3vfbFGcWwqDvKtbzGmYYGaMdLX84Hxo2z8KfkbXof/K91y41oPy+INC1fGVd7yywZaXU6KYgHu9JCT4/NRZR5wE8CZZkQVUmAhL3OZCTQZQ5IDSFK3JQJ4/M/5avI2RHETNgm56jnfnxJwqYFLR5u5MDYL7QG4c5eUgFRc6qpvu8HduQiXLFRnGpncDinmx0OE8/+K6iqF0Mi9mXKi31nBFXj0wH5c68kXQcESBCv1/vyySHZ9ylv7CFqjff0S8LyW4PPKKRsdZXpp6B4zXdoKMvdHhE9A7bgt0ZABrx723P9arx05O2YFWGK9sA516B1A9HsjqwphUkoCRpR5+CWRhVMdiugDSolniH76ulLJqEZBSveTtlApSUQLTn5DbCmUdPQI+VV4ayokw3/4QpsWxUBbeK3a8B7SAcIQTsgxIFOoTq2C8uiPoF/P9R8DPnANM7hyDZsYKg0bOgz5BUSHLgqfzyjuQHloI9UePCoW/0KJjS2CcPEQtzIaayU0NoV0YWpUGBxwJZs0Fm6M1mVzSl9WgPb0B8sOLhcnrOS8EjWbGWoVEnweGZt83fvIrkBEJu47u+fEXjAMazLZ2pysGRfFKdasK5KYGkNISBHBvLhGOUFGH8hLo//tlKI8/GCotz1ragNd3eaSIgRy/hrW0AbJsdTp3hfOUrPtFJ90GeUld4NIjoWktbTA2bvcUCk6UloTys+wghSnwc11CHlzXcz/8jMN8ZqN4nuLC8vcRiUOCAXOIIp+dZA1F3czctRfKY80AJaGeOMamd0MTOiR4o5GKUqj/6S9zxrklReBAqHQvGTNaSGeHrQNCIK9ZCsP+nnDD6QbJfXBzqNipM4NWzgrjXsmrF3uTOkoFRy3KCDbPv7i+4gpSZrvcyn2XuyOWj+sz8kXQcISqgloJWADSUZUGl6n4R1aH/txG0DsnQlpSB6m7D6SsWOwsf37IUwj4CyAnfMlMIFzJKWtpg7ykHsZLbwXJyCsXOvwSAEEhgcB5+z0+H7QqLVror74L9a9W5kQaVAXKkw8LHx1/krJfcGtIuhL8yAnQFY2gd0wUMBn7Pa6dZnP7HtB0pfCEifFOYW3toF+fGH5OV9GCM52gY28EXbNMKJW9+38hL50D1n46JzU9CEgZa2mDbJgwXg16wITtnjvjbDkSOrVsfyvk++sD53Z8pjgPT8AtPo5UVyuKhZ4+GM96fY3s60VZMfRfvAhl9X3iwyE8loCMdMT1A/AURM7cWR0dZUm9t1hxnct4+Z3gedzFVZiow1+vgvLoMhBKYlUYA90pcLC2EwAAMvbGUE8q//1inx8CmhoCMLUkaJoye1qw0JGlRHif/vRLAUET1tcvzp/UdSkpchIHada00LHlxiKHKv+hb8CjHhkaru8UOmEs6A0VICG7xujtE4puoeePV4eDRAFCPIVfVAGSdC+kud8U6+2jT718hvPhPlygcpY/sWR9/aATxub5F/kQkVdmA3DldMTycf1FvggajihKie7Opu3BYmNFI8w/HMglkaoCMma0SDwszyC/XHAsDGaQhH87eFdPeGHw2g7IzfMF1MPaKY8PH5HX9kBaPk8co61dJLeTbgVBcrKqb98DY+M2SEvqBZfI6qY4O82EiL8ZRrQqXVUa8gMN0P7xXyF9vSr2nHJ/FubBI7lu24SxwNcmCt+heydDmj8D5s5/j+VweCAsRrwsujsht9W8tH9cH/p+AMIgdcEMwa3RDQfSBV0HKSyIPZe6THBT1J+sBevohrHhLVFI2EnvxPFAX78odEeWifmVKECpgF21tYviI26el88FDAZanRYdDFUFbhoFesMIASk71yWSaoiV4qwHGyroOpf/PInF58Ej4EdPQJr7zej5s+6JO0hZieCIYBDS8K77xb/8SmweuPx7EgUBwlQdOrpi1xPvHXAECNjpcyAd3aK7U1IkNhg2bg9+3iLp00wlcOosmG6Izx87GT+Hx04GxRtcx1K+0yQ6nT5eDQCQ0SOg/vDbHogMAYLKdKfPRc9OT3/8XPT0g8iS90OWQIOncFMVYEQZlMcfFGNUQsbcL8Q/5IcXeRKn8+I+JHVmFDlcLCEiLgf/Ig8xuoIjr8wm4grqiOXj+op8ETQMIUi6A5AWzIC8pF7wUVIquKYBhIEf/VIk0RveCk1EbOKtrRDmkcn1RayiXCjhlgTeBwDss4Pg904BrZsmxizRISscsZY2yMsaYFicC/u6ErtKLm6JTEjAgJOf6YB0f52AJXFEwqRYWzvAAOXRZeBR8BIreFbzSIrbggaspQ3sYBukhnsgLboXhBBITQ2QAeGPZDKw1hAYXpIsekoR82AXM+DREBgAvD8L84PfQV7RCN7dC6Iq4ODQX3wTyqPL4q/tq3PQn98MwIL/PbEK2rOboCyfl1trdjdmU4zss2ue1WVzBISSMZDyEsE1cgsPVKWh/uUKANyBdtrrlmt6oqGm+36SogJg6qQATy1gHnxfEKbmCXd3qjoD87NDuTlPKmJcqo2gErR/eQ3qdx8SsML+AZAbRsR+nIwsCxYhBSkhnhHBCVJ/8Ej4PFkJsbx6MdDbB3n5PAEJ1Q2gqBDGpm1ekn5VWhTP428G4CsyLA4KO/alt5vo6c55j+U3PUVF6eCS5piEjagKtGdeiZ6LJ1cHN3+KUrGGtfqLb4gx+rlAFmw1jOM2ZO5DgvKb+cl+p+M7WOjOpeRf5CFGV3jkldlE5Dti+bhMkS+ChiFYXz+MzTtBxox2dix5VhcwrvbToDPuykkD24mIvcM56VagfwDSwntzJO2y4shChx8/5XBZkroVcTLbYuAMhu1V4ZIpDog7zI4m8vL+AShPPuw1UBxCt4rrOnhXL0hZKUAJUFYskuLuXvCyYgDcgcz5YVK0Kg02ohT8XLdQO4sJklK98xXWGTBMcNMESamALMHc8XE0fKcgKG/siazuFCYAIK9ckFhksgOtMDZuc7gtNuQwUf7aNZ+spQ3Gqzug/vUqQRx3w70iOC3O69v3OHA0mh4jyPs/+Y7nOJ7zvPIOpOZG5zW7o4OiApjv7E48l30/1SdXQ/vH9VC+tyrePDhKUh3eQp1WpYNrtihhDktLxGerM2DHTlpcvR0OV49L8XAuDoBOqRHQRJvLVFEGett475tdBrNcliJhjg4EZHTOc4f19YdyZOzPk1vHeSSoyQ0jAFUR3c6ZUzwy7INZD/zoiaF1J2ISOg6hvhcKGa7OgAMg/oRPVQe1Zj1jbmvPfedFJE5D4T4MRfntSoPu5CFGV37kldmsyHfE8nGZIl8EDUf0WFj4P4XLv0ozJosdSzvxjjJB9JlJAiEFScPd0F/YAnn5vFzXqagArO2EJ2EUULF4CBYZ4dq9troAyo8fhdTR4yjV2VySSOWy4gLwbq9Yw6DlqQEQVQUpK4a+fouYEx/x3VZPMzgPdCLsJERZswycmfHn9MtQ250BVRHGnbt+50kSlScejofvmINLyJ3Tbd4J9Sdrna5J2HXY53LELezk7sEFQzoXa2kTcuTutTMEOJgIAmg6iK7HwwyN3KccmJs+eKggAEtZTgd6+uPNg/sGwu9JTQZy01zwr85CeupRsGMnvc9CTQZkRHkiP4dWpSE1Tgc7dNQjP24CQEmRI7wRgAo+OB/a/3kV6tplntfVn3wH8tI6GK/uCDzn8vK5ossYNU9hEJBBCBjoz2105lb9u3UAmJCv98H1ktaD2tQAzKkdUhIWl9CRAhVS4/TwzZvG6SAFajAhz2qDXkespQ3KvOmAVbwDGLbEKdC5UWSYn+wPFWkZDHTnknVn8hCjqyKuFGW2yxr5jlg+LlPki6DhiKRWrU+CObAL68a9g0P5i+VgB1pBv3E75GVzxA9tQUr4pIBA/auVMN74ALj7TiEH3Z8FvW0c1B9+W8B3uChEzH37hbBABLGanTgDaUkdZCqBD2RBrKRB+z+bnB93m9cReYzW9sCXdRy3xJ3w06o0OAFIWWn0zvSBVhgbt4POniqMYcO6BIYB/fktUL/7ENjBNtFVsojfvLMbdGIa2v/ZBPmxZtDyEvABDaQwBXndCvATp4VAhF+J70Ab+PFToeaO5p5PQW65afD8IUBIH3f3Cfjh0jlCqS+k2+FZL9ax5awmzuVX5Io6FyB8iNyRBAdzk9+rM+DgQuY8YW17XrcL6ccfDCXhO9yNlICAstZ28OOnwDq7BydMcfg4zF17A5AqMrJUFPua7pxXWbMs9/qoctFtDbtf1UKxEFwYvuovvQllbRMILLEQ17i1pzdAXrUI8pJ665lUwTp7wDu6IU25Haz1BKRFsyDNnyHgsJTAjBLreHUHpKYG8QdVgdRwD+gdt4FAQDcheb2VAAz+ewZW4mB9nvf0g9w0MvK9oaEb59UliEro0NEN/dmN4XC4ZzdC/cEjwYMN4XoBAJx5YXwRidP5cGQ8inFt7eHGroMY9yXtzuQhRldNXG5ltksZUc9fviOWj8sR+SJoOMIyiYxM+mw4kwVboplKLycooitE66YJxaTMWABiB5HrJozXd0FefG+oHLT84HxwSwUNqgJMuhV4fVc40Z0h1HTVja+PJcuvaIT2D8+LhNMdbm7J0nrwAQ1gHOzgkVySYhuIcgj43x23xis+1U2D/mxEl0CRQceMBkwTbN+BgCw3nXAL1O80wdj0bnC+msM9XuzrNn/7HyG7+POg/eN6mIAnqSOjR0TuEAMAKVBhvv0hSF2tByoXeN/IcqdIMD/aB04JQCmkpXMgLwF4Ty9IaXHCuXy74IOEKNpQMnP3PihrljqFceRYQ14nhQWxnCDoBvRnN+bW61dnhcDGb3ZFFipS43Rx/231OJfoA+/LQnl0mfO8+SFX6t+tA1JKjodUXyueDWtNaj/7V2dNqo+tgPGbDzyKhW7OiQ0fVb7/CPR/eF4c/8drQw2M1R+vje+icYjnf+0yQFGCXVB/d2AQJH17vNKsqU5hSGsykJbOiVbkC4sL6KKEJXTs5JlYuXBkQxTqksbgvwaDOdcblTgNSxfmQqA7F6k7E2pQW5SHGF0tcb2IVyQ9f9d9RywflzzyRdBwREmR8DDZttub9FVnoDz+YM4DA9YOrUSd9yRh8+UH5gooV98AeE8fSGEB6D1fi5GD3gZaNw2GnWRb/ixyU4PHO4YzwPQlbYAFv+PcwxHxiBKkFEGY7+oG7+4DND18B99KeMiIMrDPDjl8Kbr6vlxHZfc+IV28fQ+UdSvi51gJX6q0Kg3cMAJS01wYL4d4h+xvhbH5XdC7qsPna1OEx4vd1fibbwlVsr6B3LhdHTaPx9H/7y/BLaW1sHHylCoU0mI4X7QqDfMPLYKXM+k2AcHy+y1VZyCvXBB/Lh88MLbLUp0ByoqgfP8RsM+/8HTYpIcWgk66zeNjZRf4/PgpcNVLZpfqaoWJbsyapq5Cx9i4HdLiWeDnuiA11IIUpIQwhcnA+/oFZOzoSUDXcx3JmI0Dv1mmuyNAJwhOClyiGP7x2RLucMu227DEhnsAk4FWjQc0LdfNUiWYm4LPI9cSpKc1TcD4Orq9nkr2ef3dAUWJ7ZSRG0ZA+d4qsJYjnjlg+1sB+beQVy4QSo77Wwclv30hEUjqEguHEM5WgiiBGwZKazIgo8pFwRuROLG+fmEXkGB8mhgXAt25CN2ZqMRSXrkQ9M6JobLleYjRlRPXi3jFoLug+aInH5cw8kXQMIW5bU8IpKoVIBAP96gKAML0kruMDZOw+eAcxq/ecJIVZW0T6MhyT0fD34UiI8qgPLUG6B0AOAcZVZEzMS0qAL1hEkiIcaf7vB7ehlXQ8Kq08PhpaxddHFUsn8huUU0G5KZRkCeOh/HKO96EddJtkBbNBHr6Qb+7EqS0GFLjDEfS2N9VI+UlUP5mNfRfbhZy0rb0MyUghgHOePB63POSUqB8/xEBKezoAiTJ6RyEerzYwTlISaFQn7NI7ea//xHKXy6H1NsviiOrKEBfVnQ0XtsRLFoemAvoulCos+crTtxCVUBnTobxmw9Axo/JmfBa52JHTkJ+cEFAtMDNUVGW1Dv3JPIeVWfEOX/xEpQ1yzzFIGtpg6zrCbwWw5NM03SlKIxj1pZUX5v794FWSLOnCf8s2xeJMWj/69eezznmuXW1wIhSmFveSyTMi27lfDEuC25hfn4YdNxN4GNvhFRfG5BXZi1tUOr9/ChRRKrL58F49d3APJC77wRrPR64VpJKSPxTKmimEvxsVzw3qKsXrKcPMFksBBOmCf2fNuQ+7O9OGwbkhxeLrsuABtz9NRibtl0w/MRT8BSlACqDn+3IPRt/OgQyqiK+cCgrDv59kKIEg04Yu3qjjaateR5MAnZB0J1hJoDHJZbGy29DfmghDMPIQ4yu0LiuxCvyHLV8XIGRL4KGI4b448oJcomjGY/N5wM+crAsC86AHTG74vLyeeDnunJeQK7XpPkzEi7KR6SuyUB+YB742U4wAPr6reIL2rqOgIR1YQEwogwEDFw3IDU3QtYMQNPAszpQXAjzN0GYnrJ2GcAB8/29ga6a1Dgd6ve/BZgmjNd2el4PdJKSxCde2AKarhSFAUUwbOny13cFChr1uw8JOefPXEINNRmQqbeD9/YHJb+7usF7+0GKc34/nvkqUIEBDezYSbBjXwpRDFUBKSwAWTAD5uu7gtdQeyeM37wfylkyXtsJ6evV3nOAg4wqh7RgJqTFswDDdHgr4IL/E8YT4YzD3LwzsmsiNzVA/tZ9IrHuGwA3GWBElpQi/NLFLsl0AJBXzAt+xgWlUp96NPp5a2mDuqQ+Z7L71TmYm/ZCWbVIvP7p/lhJaACeTq0dUl2tKG6H0E3kBNEdv+oMQIjTcYsLfqYD+nOboDzxcKRUvL5+K9THH8x9KGr9+4xZLxR+4tnFVhUoTzwM8/WgXxqdMNbyFAvxUntwQWSiFwqRSamApkH93qqhjTnJaLo/4fWkcQ1mHMNNAE9KLHUjDzG6kuN6KgzyHLV8XIGRL4KGIwb542rv+kgLZ0GaUws6pQZk1IjYjxKfFDNra4d0V7Xz7zg4nfHaDtDJ4TAwad70+PNWlAnfF1eixc92Qn/mFec9xoa3PIpZdpLqcD00HezYl2C//wystV3sSlcLgnsUHIlOqQHbFwINsmF6C2bA3PZRSGJJPP8atCQ0ALm5MZCYyE0NMLcHz8MOtMLYtA101lSwg0e8kCNKQ6WhYc9Jc2PuD66kXlnbBP3FN3JJq6VSJ8XCtraD3DImkmOhzJwC09XBk+6vg/HWbkh33xmYF1qVFgaqvf3eg6gKiCxBqqsVohQ+Y0rnGIosiiBKhbw4DzEOdYefy+GT+IbBYhNF3tcf+Ls7+NnOnG/S2iaw/a0wPz8M9un+3DH9YiTffQjs8y9g7tobmiDGdmz3t0KZFewmEpnGKqJBpoCUAnrir8de28RS0Yvk1bi6CJHr37fDfCHwE/8utlRXC/OND8KfOUJAp9weUbTvgLx6cWQhNGwQmVSCrL2a8Lovzndc0rzpgo/mXxMJ38mhMYjEkt446tpJpK+1uEYLgzxHLR9XS+SLoOGIJM8Y+8fX2vWR7q8HFEXARG4dB+WvV4lCyZdk2tK97jB37QW9+2tOByY2ObOgRqGvHTwSb7ra2Q3juY3eZFGWHM6BuWsv0NOXU8xaOkfIdasKWFcPtJ//CrTyRshL6mBsED/2wn+mMnbMpKw0ACt0xtzSBnlJfeiY/RyHwUpCs5Y2QDchLWuAzDl4fxZEVQCJwnj5nfDP72+F1PDNYAchQRo6zLwRACDLoUnr+STedpBC1TFrZW3tQG8/yI0jowvDNz8AnTU190erE2ZsetfbCfN3TrIa+PFTDvSJA6A3jBi0pHdA4ltVwCkg31cHPmsqQIjzTNAJYyEtnh1OoneHu8iy/puUlXgKoEhO0WPN4KFFXEJhF/I6zxrximg//DZQXgJ+6FgsX8ueH9bVEy/zXVjgFI9Ja2dYdph9u9iD+S4yfv1W+Jq9FDveqXhOVcCs9WJET1/8mvjxo0Obh7y/ytUd1+D9y3PU8nE1Rb4IGo4guWTOz2Xhnd0AtboU9q4OM2G+txfSjMlCQjckyTR37xP+Hv1ZR6ba4YR8dtDhgwxF+tgd5q69UH/47QDEh1alBeneMKD+7XcASkL5IE4i3NMH9sF/gMyfIQqrcTeDGCaUhxcL0viA5iukaLwyVRI0KCIBdjgvhIj5HMK88P4BoDAF3jcgIF2qkrxr3D8Ac/cnXhhUNsRLyX3tAzkyvYeH0tYOWjU+xLz1/O4tAHBCPQp0dN2KxMRYqqvNrTVVFnyo8WOA1uMezgyQ66Rxg3l4KLQqDdrcCGnO3bl7Yb9m849e2OK81yPxbRcnm98LKPypP1oDgEN7egOUx5sHbZrqFFiuuYrtEhICaemcwDFJWUnovNlBRpYHu1fdvfGdm/4s6JjRIJMmgIwekRuD67ql2dZ8qQr4idOQH5wf6jUlP7QQdESZw1VJXDshO8xDVqga0LzfTUlFRNyYLsWOd1GBAwMOhQdHiK8Ma/RnE9fEkOIq91e5XlTRIuMqv3/+yHPU8nG1Rb4IGpYgkObUQlIUmNv2BLgsdOJ48I4upx1MCAWpHB2biNHZU6FveAvq978FfqQ9UITw8WMgP7RwaLvi7tB08I5uB55CClUglQJnJvhXHYBpAjdURKrQgRIoP3gEhDEgpYCf7gD/4pjHcJRWpUFq74SydhnM93IcH2Vd89DHa4UfHui+Hn39VihProY0expICNE66jykqADGFivxthLxRF6LLAcFJPy7doNUMePHTwE1mdgxhkZRiKIWxI+Kv/ggZSXgZzujj6UqICPLwf1crBDOjH3dvCYDqLKnsGMtbTC2vg9pwcwQblSPUPD67kpw3QQKVejPbMx5UsVAuIzNOyAvbxQ76c9sFPC9Nz4IbCDYRVWgwHLNZVLHQibIdWetXXp24qv4ZKVABb2rBtKs3PWiOCGBsYoGUlEGoiqQVy4QhbSmCU6dLEH7+18CgLOOtF2/c7yKbKNkFBeClpc6x5LXLAU6uqPOKsK1VllfP9DZI9aHu/NWlRb8rKwuOn0pVYy5qEAkqoUFQuhjMM81EL+eL8GONy0qBL+hAnzK7ZBcXRje1Q3oOoxXtkFpbry4ilyJdgpDm4er2V/lUqqiXanF1tV8/0Ijz1HLx1UW+SJoOEKSwLv6BPclyuxzcg3oHbc6nIbBQEfkxbOEqIFfdc4qQmSr8xEndcu7wpMhx3zS4ozQKTUg427yiBUo65pjBR+kWd3QntsI5SdrYb6/N5K74penjpPn5V3dsbK4UBXQOyZ6fFyc1zNjwY99CePltyEtvDce7md3C6ozYG0nnPfZiThJVw4O0uXe3VZkz9gHw0vibe2QFs4M8nEQP0+0OgMyojzwuu19hKwOetstQgXvQCvMzw6BThgXOI4dUl2t8Lnxc6BCOFQiOKRZU0UXyIJu2sUSGTM6ICjhHp+0pA76z38l/nv6ZOe4od0wexz7W4VMtnVP9adfEpCi2dOEuEh5qYClnu2EsmZZwISWd3Xn1kNSt/GrDrBjXzpJKk1XgtNoLoe8pF7ABn0wD2nhvdFruToDqEowORtR6iRnrK8fdMJYwf1yrSPbqwiwYCaW6p/9GfT0AZQOaoc5NBGtSgtxDkJgbHg7WGjOnwE2shzGlp2Dfq6TvovszuvFTlZJRRnoHbeCnzrrrAPe1Qve1Qtp+mSw46dABjQhY38xErOSIiG44t8ss3l557HzfzX6q1xKVbQrXYL6arx/kZHnqOXjKot8ETQcwUzQW26CseHN8Jdtbk5Wg7JqEdjpDsBI6OCAg467OZaXgs4eGO/shrx8bqBjY5uZ8q/OhSbKnh3z+TOAlArzrQ+9Ccwg4VgkTJ7aNU5plpeXFCfXTG8dB3rb+HBFu7pposuwtA7Q9dDXUVYidqRLi4DbbomVobbFCjTL9BJwdQna2r3wupDPA8iZjNZkHOlucHHPk3hJ6pJ60UXq7Qc7fDxQtMUa1TbPh7H1vUh1OHrnrZ61Q++YCDJ1UnSSOjGmAPF3vACgqBD6P/86FCaXdN2SJQTAWtqgNjVAuvM28cOfIBDA+7NCUABift1CHFLdNKGgtmpRqPADGXcz5AnjYLy2I7nDJkkBuJKyrjmSy8G7ekNx7kAMCb5xOkApjPVbI5Mze5eYnT43KH5PQKltzdLguV07zJGJqN2NnlwdWRTTKbeDjBkNuK47TipfXtEIfqYD8soFIGWlHrgwqSgVqpGXKlnNajkIp7tb6+5iX4Tzsr5+oRSa1SDV14KkK70iI/bG1nnEVeevcolU0a4WCeqr7v5FxTXIccrHtR35Img4gkrgZ8/FvyelAIYJTgByQwX4V/FEazKiTEDo3OGHUZgmyOiR0J7dBHn5vBxEpiAl4DTZLGCYkJbUQzJMwVEoKxa7rn0DUP/mW4AiwfxkP+j4MWCfH/Kez58s+v2IRpULBbMkadmQYood+xLSknrIlIBndZBCFaz1BLSfroeytik0ubd39uVF94LWTXNdrwrW2QP9pTeFbO6IUoBzaO6k1TSA0hLHJ0j9wSPgEhUGsm7DUXusFrxOXrNUmKW6oFH2OGhNBhhRKsjMqiKgWs9vznUoEjgSXNdBJ90KmKbY8Z96u7eY1XSYez4VnR1NBx8QfALW2i5EGP5wAPgDcsm6dX+kGZOBAhXqjx8VktV9A4KAf7ZLFMx+89WqdI63Noh7SKvSYJ9/ETBqtYulxOLZ/TndAEaPEElPwnyRwgJwxiAvrQeyM4BUCpAlmJ/82bknfglpckMFoCgC7niwTRSpcWa1NRmgokSISrhhSoYRyeWga5tCIU4oLID+L69awiH1Yp0XpITwQk8feFYDO+z1F/InZ6SiDCQJ2tafFcneRqEYqNiQPEpB66ZBapwBokgCPuneYY5LRONEVVrEPJKyEu9cuOZfXdZgSeVbylBnOkVBtm+/p7Nt88TQOwD9rZBO5MVIVl271YNV0bvQiOy4uaCmV4ok8iWBjl0qVbTrSYL6SohrjOOUj2s/8kXQcIRpit3MuMjqMLZ/BGn2VJif/BnyolnBXXk7kZo4XvjKjCiHdN9smNs/AoBwfkl1BsqKRkGe1vTczuZv3g/vYPyv3O69jeE33/5QJHK+8MBbYvgtZOokUQRoIcIAgLeYCtl5lRbeC374eG68ccRhVRHFyAe/g+FLppS1TWBHTsDY8JZIYmOOo6xtgv785iCPwT1WTYexfqslVPFJ0GR03nTo//PfnOtW//Y7XunrJI6EwaD/rxdzx5x0m5AW7+gWhYvd2dm8E/LSeujPuvgzfg5Rgi8SOnugP/OKMKm9f7b4m26AjCyH+YeW6HvnmxdanYE0e2quExa4JiOSq+Q/lj1uuxsi3Tc7XhqbQKzrEPEAv7Gv/W/lqUdhurqK5vY9uY6Fv0tYY93Tn//KmQ87UY0Vygibe1WB8uRqqI8/CN7dCwDgp85A37wzd+yaDJRHl+WeXSsCyVnSfBamgN4+SNPvir7/FSNAR4/yfi4p0YwrZqNes+Zfqr0DdOyNzp9Z30Dg3gFwpO/lFfPivdaGM1l17UZfChW92I4bfFDTyyyJfMm6cZeqY3CNSlBfqXHNcZzycc1HvggajlBkcMYSOST2Dz6trxWwrvvrgDc/8MBXQs0N1ywFO/Zl+I6lzWVpuAfm2x8Oiodibt8TUNEKgwi54S0CuhHhR7RZmGaGQfdodQa8q8f5d6gUdHXGA0WJgyvluCsh80AActst4g8JSk9OF6un19MVCPAa3N2FedMBzgBVBf/yDNiho1DWLMvt/KdUTxIfy5GoSgufIfc1fH4IhmFAWjADqCgFdAN04ngwAOa+/cIA1D6WL0lIuu+0bppzDhgGSLoSvK1d3Nfte4DGGbH8I5QUQvneKqCkCPrP/jW6aCoqEFCuwai31WTAWtud+SJjbwTNjI3m3bzx29Ade/AwzpK1rg0zOA53x6KpQXSjUirY4eOeQtOZP0ogP7QoskCDKsN8Z0/uPPaz7DfaDdv5jxi7JzkbzO5qV2/s/ZeXhxjQJiWacbBBWY58xkJ3fMPug3uMBosfy3Amq+75PA8VvSFHXDciSVzlEsYlhY5dqo5BHp51yeOa4jjl45qPfBE0HCFJQEe32HFFkL/h5pCwljbIyxpgfLof7M9fCMjS6Q6gpBDmmxFJHuOQltR7CwX3ew60QllSJ8QNTAZenYa8tB6sswfGhrfElxFyP7jc3vF+diMA0WHiXd3BxNWGhDXNBU2PgRazYyovnROAGNnXTkZX5LgAKQXIVHrw8DC9vZr44iGePK8suBcmAM55bCJuftoiRAmm3SHkj62ugIfX4JY8BwcpSsH80yHQdCVIaRHY7z/38ggm1wjuQ1cPiKqCazpI7Z0wXt3u3RWL6aawljbIS+th/ukQpK9VCU5XphLs6ElIc2qd93DTW3TTdCX0XXu9ksWqAs4YCKWA4lVxU+ZNB9JjnDGYu/YKYjYlAciONDsngKA89ai3GHPPa00GoERwd5bUQerXPP5X/PgpSDMnCz5WTQbyivnQ/uGXuc+XFEP7xYvRvJsQMQzAWv/zpnsKCacD0p0rwD2QNTc80jABxmC8/HbwfXaBa5qRO5ykqNAzH0Mx6mUHWqHMDvF7cncrwnZXVUU8l5lK4PQ5QJFB0pVAW3soTBEspMiIS0R9mxee16rS4F3dIONuCvINo3Z8B7KxqmiJkNphTFbd85nIDxuO8w6y43bZ4UKXEDp2yToGeXjWZYlrhuN0meJKVTO8FiNfBA1HDAwAvf3QX3xD7C4vqRdysz4OiR3OD76mg3f3QX9uY7wSW0sb5ATOBtEMGFvfDxRg6hOroD29wSmESKEKqVEIIahPrha+O6oCetMNoBPGwdi8w/ujNGEsyE2jHEhPVPCvzoGMHyO4MOAgI8rAOrqhb9oO9bsrg1wAt5qYD2oUJwhAJCleYtYqqAilyUWppsN47V3QKZO8HKSUCnnlQoAzGBu3B+F/37gdxub3gknuoaMA50J5yiJ/c02H1DhdmMn2Z4EBDSgpdIqK0Lkc0MC/OAbNJzeOW24W5rp1tQAB5BWNMDZtt5JcMxYOZ3c4HHgXJZ51SSeMBSkvgdQ0F7JueLlWG97KjbWjK3Je5aa50J5+CerffCsobFGTgby8EfxsB9QfPCI6XV91eJ+LrBbPu4kJIktQ//M6oC8LyDLMffuFZPqaZeINSXBBu0iI68iuWgT54cVCya8/K2BqRQVAp7dYGKxRrxO+bkRYcubZXR0QEtrGpm25wg3BTpMnQtZaXCIqr2gEH9DCNzbmzwB0HfozGyFNn+wpWMmo8nDYVIEaKxcPRY5VlhvuZNWZz76Bi58kD6LjdkXAhS4xdOxSdAzy8Kx8XG1xpasZXmuRL4KGI/q9hqA8q3kTc18CQlw/iqRA+EagpFBwSPxJvf3ZBD8gHgI3YS1tMF7bKWBMp84K2J6igH12CHTczeD2TvuBNtAJY3Ok/lkWqV+SwL88IwQWpISl4t5RZUx0YspLoHzrPuFHNL4SaM3tUntkooF4CJpMAZMBpcWAEZ3sK2uWivkERJL//NbEotTuYvGSolzn4dBR0Kl3wPSZUjpz+uq7ILeMAXxCEvLqxaJj8cn+UDNGUlEK7RfPiPscx8Fxw8HcBR/nIin9/AvQCWOhbdwGZe0yyFQCFAnGxu2J3Qfn3yvmQX1ytRhHYQooLgQ0A+ZrIea9qxY5c0YqysCzGuRVi8R89faD92VFt+b0WUjTJ+cKM/c49rfC2LRdQEA1HbSoEEzxFg/+Ytg7ufHrjxsGSHER6OhRYKfO5DotVlcxDs4JANKS+tw8hb3v8HGwrzpgvvtRaMHg4cQN1eTW7WFUlRbO6iHJmb27yvr6A6pynmsJg9dF8IqiElH09kH/xYuQGu6BsvBewXtMqQL698l+mDs/Di1Y1b9bF37NspI4/6HF9UVMVu35vOhJckI3gtw0EvKapZc/Ib8M0LFL0THIw7PycbXE1aJmeC1FvggajigUKlVu40AgfGeWVqXBZclJ+jlnwjfizd/G8geQSsXulPr5JXawA62QznZBf36zeK8DxdriGRMDnKSGW0kjTVeCn+0E+/3nib45KC0S1291ccwt7wUKgSjTTfbZoaCTu6aDt7UD1WmwliNCvKEqDWnlAphbY5KpFYL7QIoKneuhY290rj80sppnPqTGGSBZLVb2W5kVhDDRkeXCLyaKl9HcKP6d4P/j3Ms4MYppt0NZ0ej4OinffySWc+HuPrCWNkgDGrSf/avzHnnlQqtb1xo6dqmuFvzICZh/aIG5fQ+U760CHT0CvKQIppWQ03XNyUak99cJ/k1fP1irdx5YV8/5+UdVZ8BajkAqLxEJlSvpdLqKqhIv222YoFXpyPFLdbUwt+2JLO48nLgkiJW76KnJAGXFUNatEAXO518IqF5cDIVjguSORlgiyiC6g+bbH8J0dSSlxhniuQzrLMWdR4t5nlraIBNAcyv7gYOMqgDKii96snqxk+TEbsSVsrt7DUPH8vCsfFwVkVczvOSRL4KGIyQK87Vd0Yl5XS3MXXshNzWIDkx3n+DsHD0Jdugo+OeH45PPtnZwxoKFAkQCKD8wD9pPX4gen2vn2RZncAQS7pgIuakBGMiCVgszUhAilMTG3hj0zfGfvyoN6f46mO/tFbLVFQL25eckRe5SGwbMnR+DThwPGuHkbu782Dmv7PMH8s+ZbIj0zyNUkZSUKgrkNUth2NLXE8aKbl5chO326wnkb92AvHIhSHkJUC28YljLEafj53g7nekQ8K+R5TBfD1HUamkD+6IdbN+fc691h/M3IserGx4ZaFJeEgvHVBqnA5lKoWSmKsLo8/Q5EEWG/EADeE+/4MYZoZp+TvCuHpDRI4XH1eYdnjVlbHgL6hOrQj2v6K1jQW+9JdBlsiWW9Re2CL8huJLOjduFlw0hAKXx89PdY3UiwqXrk1TE5PvqQCfdBjL2RqCoQBQ1hAQ6un5hCHlZA4zf7BJcKct3yb6OSFx4FCzJ6hqSsmIof/EAUFEGMA5imkBnD5hugJYnqFja1xuRuPMTpyE/tBDGK+8MrXPiHnMInJVb98fcvgf8MhQHQ02Sh4rZD4MzwjDAz3QKmGxRwaDvzfnEYMabh47lIx+XOfJqhpc88kXQcESC8pG6pB7S1EkwXtvhNbCszkBumgNt887IzyqNgsCO3n6AM9ApNZ5CARUlQt0qDl7lKwKcMU2uARRJeOXYBPYDbeDtp6E8vFgkj/ZxwzxYbHnl/izk+dNhvLoDRgwnKWyXmoyqgPLkagG3uWkUSIEKrhtA3wD4uW4YLklhAMlfAlldSFUznoPXJKi0mZ8eAD96AuqP1oCfOQcyshy8uxfSwnuFMpoFBeIA2GeHRFEWBi/Sda8wgR/WmNUD3RZak4H6ozWCy6SqMDbvdAQABE8sfF2JosX1WmKh53s9q+e6g1VpoDod/3lKAEIgNdwDOv7mXOfS1a1iLW3JsuAgIvmz/Jk8ayqlgHf2QloxD7LBwAeyIIUpcNOE9swmKA8vFt5SgAM5BaXQn3klB+uzz1JRBnn5PBi/fhv69j3J45Jk6Ou3QPnuQ+GvW0ITkcT+zi5IC2fCfOODyG4wnTBWFLmdPZDuqgJUVayt8Td7eTxFqVhceCgsyXUfNLsb65cTr0pDfmgh6KiKhHvkmsOQDgktKhx658QecwznSv3JWmGYW5gCVxXEsyDj42ISi88Xs+/AGc90wPj12xd0by7WeK9H6FiehJ6PKybyaoaXPPJF0HBEEl9H14MeGaoCMn4MeF98Uk9kGZwQpzsjdnpzO4a8oxsoUAclSewZU18/SElRgEdCq9KQ6mvBu/tAKkd7ExEfB0BqnAF+5AQwdZKQrQ7lz+yAvGoRjOc2iT+6TTcn3QakFJgbt4eqyoXxqWL9WgBAlcHaTojz//GggPFNGGuJGQRNQr0iCTsgPTBXyJcvmAF++LhX/c3i9tCJ48XOrXvOVQUoKYqHRBaooWaQxqvvQlowA+bW97yFTRy3RPJ2NpLU8Djnnn+71wRraYM0b3r0uQBgQIf+3EZRFN52C8iEsUIEQ6YApY4yGWtrjzYitc4rFU0A7JXl9lV6/EGAc5g+CXTbCwu6Af3plwLHlKZPBj96AqAUrK9f8I36+mG8/Ha09HnIuKDp4Ce/Ch+/qkBZu0w8b64gI0qhrF0GlJXC3LIzvBtMCJQnV4P9oQXGaztBxt4olAlXLgA/dFzw3VzeQVBV6C+9GY0Lf3hxALbk5jJJjTOi5ex//Tbkb903pI5QWIdkyPCiwoJ4btb+VhivbHMk2y8EKnYxicUXitlnnd2BAgg4v3tzscZ7PUHH8iT0fFxRkYrP5RLzn3wMORIwIvkYVCQsTFKQChRAypqlAls/kAC7SinQn90oxBSshFF/biP05zdDf26jgHDpBuQVjeIhcYWnmPCPqaQ4oCYHwJKJ/h3ATOg/fQHmH1oCx7WDnzgNubkRxGSxnTBaVpL7g226WZWGtGimKMJCoIDmrt+Jjpf7emoyjopUWNCqNKDIMDbvAL11LKSGu0VR8swr0H72ryDjx0D98Vooa5ugrGsGSVd6OUoHWkF0A6RyNMw3doWPa9se8FNnwf4kCixlXTOUJx6G8uTqSGECc9fvIDfNBWfhUCvW0gZSUBDs+sR0d/w7s7YaXtQaIBbciNZkQtcEO3hEFDgh4S6a2IFWmNs/AikrFuvwn1+G/k8bwC24pPnRPsgPzI1fiynVKUrcwTkXCXKIB5T5we88hZzzWksb6MTxkGZNhfb3v4Sxfit4R1cAW23u2hs7P+auvQ7sLux9SCmAooB9sj/3/D27EeyT/YCigFAS/QwcaBU+Ptv3gH1+yJEYJ5oOY/NOS4Ld1enJavG4cE2Dskr4FjnX4ZItj5Iwt+cLvf2hr13MoCPKIK9cIHyv4r4rrLmwk3TWN7Sxsr7+AJzrQo4XiMFg9uOit//S3psLHe81HBd9reQjH0MNTYv9nYKWkC/mY8hxWTtBu3btwn//7/8dv/vd73DixAm8+uqreOCBBy7nkM4vXEIH/hBGpJLnb+5d20TBAQuCxNpOhL9P02H+9hNIy+oCMCLWdiJULpdWZwSno/V4OMTn6EmQW8YICJFpgNxVBXb0pAeaJnbg74L2818JbklM2Pwax3RzXbNIqrv74nkoLuicI9vbn4W0YKbwRLJkqKHI4J3dIDeOAs/qYkf/1Fmw9tMCPkUJuG6AFBUI6CCAKKwNz2qJEsdSXS3ouJtg/qFFQKhW3yegbnES50vrwc91Rk9SmI9KWXEkUZnD1/nRdEei3e+xo6/fCuWxZih/vQooK4b+j+sDa8LctRfqj74tumV+nyCXzxUgknpp9rTANYIQKOtWgBsm6NQ7IC2pB7HmFJIEdqAVdKIw5g2TQSdFBdFzuL8V0sJ7w+eOM7BjXzrGtez0ORB/AWlD7xrugbJoFghnDreJmwzK2iaww8dhfrIf/NiXQop80aycKlpKiVffa2oIH5sd7q6e9d+8u08o7hWoQlXNgh3xkM6tJ/qyIOlRkB9eLOTY+wZEkRZ2rrC4AFw56+wOSIQndS4cuJFmgChS7Hs9/MXzIQJfbGLxhWL2LzXmP88xiI48CT0fV1r0ZQO0A/fvuPq9VZd7hNdcXNYiqLe3F5MnT8Zf/uVfYsWKFZdzKBcWvQOQ5tSGJ+YVpUCv1wjQnWTHeeJIddOEiMHkGmhPvyR2iUPeJy+pAz/TJbgRdpQUQX1iVWBX2Da/NLbsFDAeDpjv7/VCuCzIk0dBrlpwV3hvP8CYkEo+9RWU1fflZKkjglgtXrfpJoBE7xcUqKLAsr4EjM3vQb5vFqAqMPcd8ELbqjOQH5gLrumieEspoLfcLJTnpk4C+rOh0D9lzVLor74Lefk80bHSdKAwoeVsGOBnO0X3Y+0yoKQ4GRI5oMXzdgpTQa6EqggDU44AjI/IMjySwrIc6bEj3sQBXQc6ugUEpqzE4wVkbHhLeA89uADQNPDeAVHYhfhc2XNgj9FduBGJwvzzF5AmV4N39QreCwCiSKATbwH5Rg3ATdDbxoOdOA3pgbmQTSZ2uMI6ZR6DUybMhU0G9GfBTROEEBBFBr11nEdkQvnew6HTTMfdBPMtrykxrclAbpoLHDkB3n4aclMDuKYLfkr/gDC9JcXxghyhr7jCfe/t/7Y7W6VFoDeOyr0+CFw46+sX3mT/tAEAvJyni2QAej5cFgdudPg4lLXLQEpLQt/nhH/sQ03S++NNWS846b9QzP6lxvwP8/muKf5MvkDMx5UWLsRP6O94nhM07HFZi6DFixdj8eLFl3MIwxOFKtA/EDQEtZSrAjhP905tjOCAuXufkN7dtB3S9MmROwT8XGcAaiVNnwxj6y7QummC79E/EPDJoXfcKsbs3932KcjZfzNefRfSfbOh/+xFcW1L6kEkCt7XH89HSSkB6JmYt3DvEicGtIC0NV9WLzhEIWM2Xn0XUlMD9Oc2eu4B/3pVuLxxSxtQkIL6VythbNzmiDoo65rjEylZBojgmUiKAvP1XYHOiD9IQQo8wvCWVqXBTQbe1QOprhbSzCnO+fQXtkBePEt0Qbp6nHvIznWBffxHoci3pB5corES0lzXwfb+CfJ9s2G+si0oYPHkaoASsANtYJ/8GVJdrWceAyHL0ST3u2qAybfDfGdPMGFe0QgODnlZHXh3v/Alcs+7O2IkwuXlc2Fu3QXm8mpyitoNbwEFSmBNRnoAWbwsOqUG0jduBwiBudnL71GeXB09F0Cosah7XI4inPXftCoNFBeESw8nSRUrMoz1WyFNn5y7BhfnKYn/hOKhJ63nw2Vx81GkxhngHd3gHd1D4y/aBd9gE++ikM0E5NYGii4wibhQGenCgvh7k/SdONQYRtnra44/kyeh5+NKi2tYpv5KjatKGCGbzSKbze3OdHV1XcbRuEJRYL6/N7yYACAtnwtpwUxHEjmg1OWr/JV1zYI4PX+GSLYPtEKZPQ1mxA6B9NSj3k6EqoDeORH69j2QZk6B/r82eD+gKkLFbNzNIEWFkOpqA1K+YUpurKUNMq13rk1W5gpBhPbTkdLG8soF4Fk94C1Cq9JAUQryygWe7pk9Dpqu9CZEtvyvYYriI0KFTeawiOHiWtiBVkg90Th8es/XYGz0mqKyYyeFd9O2PcFE6rFm8DMdQGkx5DVLYW7/SHCJxo+JT+6OngC97ZbAFxytERLn4AwcCPg32Ualyppl3oJwZDnU7z4E45V3REFjFQweo1X7HjzQAOOt3ZCX1AuxgFABi3dBJ9eAlJUMCqbJ2tojiwp6951CQjnsPJu2Q165QCTrPlNZf/IeWbRYghskXekxrGUtbQAlUP76IcAwhQHqWx+KQklVQL9eBaQrPUWms04smCM7dCx0YyBRYpsSSLOninH4xTfurwN6+0HXrRCqfsdOgU6oBKFSqPRwnFSxvHKh8KLa3wppVq7wdneUI7vL1Rmn08fa2oe2k5/VAgW6e+7Q2w/4YXEuuBFNV4oi+8gJodoXYsrrh126C75BJ96qGmvKKn/rvuRrjYkLlpE2dMjL54Z/Vy6fCxgxKp+XY7xWXJMmjvmEMx9XWNjPq/n5YZCyEheqqAfSpAnXtErj5Yqrqgj6r//1v+K//Jf/crmHEYw4Y80DrZC+6nR21Wl1BuTur8Xu2qOsGHTK7cJzxSGuRviXVGdgfnYI9NZxUP+fvxCcl8IC8FNnxBv8/AC3lG6CsWuYaSN3k0U1w+l8aU9vgLxqkehKZDUhKa3KMLa+DzrpVkhL6iD19AvugsHADh8DevrB/LA2q9AgpYXQfrEhMGZek4nd6eUDWYek71xLvxeO6Jm/shJPV8QOc/tH4YkUJZDuqwMhBLxvwBl7EqxRX78V6ve/JbhWs6cJPgrjYAePCI8nyyfIPW53MeC/j9LUO7zFm7ujOG86wJmY57Z2GK9/AKlpbrxhpc3zsc4TeT01GUjzpkN/dqMozEK4U1Fz6hxL00HKSgNj8Z8ziZvlL9IBizs0q9tRspPumw1p9lSQ8pJQdUDPOjGMSL8kdqA1utNjG7Pu/BjKk6vFPJoGUFYCUlzkkT0HXB3irCZ8hUIiSqoYvX1gfxLH8hSN7vtfXwsUpCAtmwNJM4SHlCSDd/WAd3bnJMUxuJ18drZTFF5xcxcGHfL8jYGMHAn+3r9D2/mxGOds4ctERpSBHTnpNZX2FXye8cQl3nHfxS1tibDVwcQFyUj3ZaE9tynwXcm6eqA9vQHquuGHhQ+L7PU1yJ/J+yLl40oN9un+wJqUJk24fAO6huOqKoL+83/+z/jxj3/s/Lurqwu33HLLZRyRFUnYYZ9ZqbF5J6TFs4Ncj+qM4CN0dAPgIpG1lOdIWUlgZ55WpQU87emXQMfdDGPLTsgPL4bx0pu5XWIfxj5ud9153U48w/D7jDtdGO6GtvX05WSwrVDWNoH94QCke74O8zcCmsfe/RjSzMkgZcUw3/s4qARmEezplNshTZ8Mc/sez5jlFfNgvLM7eqd3xbzgtVjQrTB4W5gpKh13s0ca23Oe/aJY4Jx7jUFjYI1OcpcVnTw0zgBvax/UPWAtbYLIL0sec1NanQ4WCHancPseqE89Ct7d6xxDOtcpzEzjwvaeirgeyDJQVgz09ObmMSQSjWb7s0Ja2x+uc6pWgpg43pi/288WnT3VA7uzIzDfZSUAY6GHNHd+DOXRZaIz6+/OrGgU0tqPLgP6+p0NDynqPltwU7m5MfbywqSK2elzuTH5C1Xr/pOVC8F2/S4SmudZXzEFBevsBrK6MKiNMXM2t+8Jhw65/3bDSI+MvrujTavSoHXToP7gEWsTJ1jw+SMy8b5EPI/zlpEuTIV+V3pevwhxwbLX1yh/5nr0RcrHlRvXZMf1Co+rqghKpVJIpa5AnG7SD5ffrPSzg5DunQIyfgyU++sE1wMErK0d2s/+1QOHklcuFJwOANIDcyENaKKzUVgA9vkXAmZjQcfY/lYhwbq/FeSWMR7+gVs+dzC762GqdrQqDZQUOl44sQaUqgKMLHdECqT6WpBR5TAOHQE7dATKdx8CcxnHesZhdSVIabEYi2vMXDNid3q5ZgSuJQ7eRibXBA+UpK6lWwXBIGCNpnuurXUy5A5HXz80V9JEq9Igt8fvCvGzndCf35zjQgxkwRMELGy+kbu74E9Whc/LXgFNvGFE6GFIkpdBYQroCS827HPaUslJ4439u+XFRSvKYjtTSl0teHUG/ORpjweXf1z6C1tEp2eW6PSQkRVgR09C+4fnnWdW+eucek/SfYYZMQdx4f6u8ReqTBgOwzBhvPx27PV6YK4hBQU70wHj5XcgzZ6WqODILZ5RgLuTUkHvnCjk5E0z9jhS43SgotTzA+8u+EIjLPG+hDwP1tcPdPVa6nxCQRBFBfFJSkkR6J0TQcaMDm7InDh95UKwrmH+zPXki5SPKzyuwY7rlR5XVRF0xUaCRHaYWamT7GUqob/6LpS1yyBNrgGtyYAUpsBNE/rzWwBdEwlCTy/057eApisFvOqffy0gVOtWQKqvBTt6UhQcVmJg7xKbu/fBoyKWlOAbRk6ZriPHubKhReZbuS5MgIBtd1smjAUZUQrjNR/8yIKy6eu3WoVf/DicIsw95nMJPDD369bnSEVZJLyND2SD9y5JXauoAKzlCEg6gQfkuu+0JiPkzhfeGwoz9ETgHnkFFVhLG3hjgrmpdQ3Ojv2SerA/tEQnYO2nwbt6Yvkk0uypTlfL3L4H9M7bQq+fdffGYu25ooAd3D+ouRvqc+X83Q2hjICc5YJDahQQP6muNvqct40H7+oBAQFSKnj/ALhvPbKDR3KfT7rPSR5h9jHdxUVKFTCxzTtE4WUXqqoC5fEHwQ4dAxkdXpw6EfYd4Coo3CII0ozJwfd6gkN+aCEI59BDuDvyA/PA59wtlrCqBFUGrSDWhgI7dSZXRBUXej/j7+aqimOO68Ql4nnwji4YL70V5DXNnwF+Q0UkvJAWFUJ+YC6MX78dFPt4aOGVu8t7HvN6TSnJ5SMflyKu0Y7rlRyXtQjq6enBwYM5uMPhw4fxySefYOTIkRg/fvxlHNkQw5IW9pPBbbKr9vSG4GdsFSDCoX53JYxXtgU+q353JdCXBQpSQP8AlDXLApLFpKJMYP0PH4P+9oe57oxrlxiUQlo6x7rZ4dwi51JGljtKbuqTqx2Jat7VI7yHDh3xFjvfuB3Glp1CAtdKOhkA/l4IDGh/q4DT1dUmFhpkZDm4rkP92+8ABCLBO3w80J0KhBvyJcug1RnQW26CseHN0Lezw8cgr2gUkJ+o4s4VtCoNMqJcFAtrm7wFpus9bpK3MCitBUwGUlYMMqI8/hpccxOV7LOWI0GOin1fJo4HOIPyWLNDYJcME+ZH+6B+/xEYr7wTTMAeXAAQq3vh7i6Ag5SVwPzsUFDdr28g9PrROyAUCUNEGqR500XibhdbhMQS5KN4VvLyuTC27vLMifuzbgil33TXH2REGbT/+W/ecfnPOek2yEvrQgntbm6M83lKBLwuLgqS3b8jFbkea4b+7EbnfsjLGwHOHWW/2Ah79tw7+W5Dz0E8pyhMBQogQDzvxqbtIOlK8KMngpxDO1QFKC4MF0CwrxMI5wL6OE2XgufhQFYiIIJ8yu2gk6tDE37W1w/jNSHq4cBMrY0I47UdkFcvviILhaHO6zWnJJePfFyKuIY7rldqEB5mw36J4r333kNDQ0Pg72vXrsUvf/nLxM93dXWhvLwcnZ2dKCu7PF+svKML7EwHzB3/DjL2xtwupS1fffwUyNgbPbAoWpWGtKQe/NhJ0KpMqGKX/T75oYUwtrwHctMozw4oZ0zAjigFSSnghgn0DYAzBrZ7n0c6GBDQLP25jZAW3gt++HgkX4CkK8Uuf3UGZPwY77irMyATxgqvFZtXpCpQvv8tEFkSCeKBVudcUWGbpfIjJxLH4cxX3TTR1Vo0E+ZvdoXPlzU+8+0PRefi/jrxQlaD/vRLkWPRN7wJedUil3dOCpBpMOGtyUBeMgdcVWC+8o5Q3rMMSt2dFc45CKUCjqUq4AUpmO9+BGnmZKC7H7yrOyAI4S9gYDLwzh6QihLREQxJHNWnvg32RbtQkWEmyOiRkapb4AzsyJexcy5ZfDSiyALiI8vg4KHrCQDklQvBPjskOkuTbgX6+gEQYcj6ixe982I9D+auvVD++iHo//PfxNr54bdBKAF0E1wTc8+OnITx2rvimlUFclMD6PgxgGbkTEEpAVQVvKdPkN256MI4PkGuNRjFzXHu6dI54B3dOcUzwDN2MqoCrLNb8GyiCmPXeoWqQPneKpDCVKjBqv0ZubkRRFWcpDAMTma8si2UF0NrMpCb5wtVtsIUQKizCRN7vf6xhh2ruw/aL14c3NxZfArtvz0XeN0O+16EnRuAUAv0Pw+uc9C7asDPdSWOwwOlu4hdCHbqTOL1ktEVXu8n+7Onz4CfOhfgZdrPKblxBOjo4OeulBjMvLK+/kBBa0fYvcrH9RPnY7Z8PUX+2RmeGEptcFk7QXPmzMFlrMEuOOwdQfm+OpEkfn4o1OBKmTklx6uoyQj1qJ4+sH37QcdXhv6wAzk1I3lJHYxXtokdUAvm40/I7B9Rtnuf2LEGfIkrFzLB428GbhNiElE78EJWeS60f1zvHc+BVij318H8zfseVTJ09oC7j5cEuQMXyfCjy2LH4ZkHQCRQb+0Wxc0bHwQ/1zgd0A2QVYtAK28UwgCFBSBFMd4bhhFOVLaKEnVJPfjZTqsb1g3OGdDRLQoLRYk1NlPWNUP7hfBUkpvngxsGYHTD2LwT6o/W5IjiUX449loJi5IigMqWN5Xlw/Lb30eT/5fUg05MxXJUZJOBlBYLtTrXPChrlgKGEVhvdEIl6MRbYGzcDt2GX+7aC2nuPfGGby7BA0KIUADzQe/UH60BP30WoJKY96wOMqpcfNZOwBgTKnWrFwOK4pVhd63BWOW+WVOdLpDHZ8gdlAjp8DBYK0J4NrbRKke8HHJfVhj1rlkKoumhO+fSrKkOP8tzzv2tAGMOd4odP5UTHRiEsp//b9rf/9I5h/rjtYOaO3mlgG8lcndsoYqWNijzpgc2hOgtY2BE8QP3twoj2/QYj5plYC58WPmLyvMYjBBO1HtMHi/hvXzecIzwosWg5jXPa8hHSJyP2fL1FnnFwksfeU7QhYT1Zc/nxfMzSGEKyhMPi2ScEJifHgD/4pjohgzE/6Dy/qyQkraSZXnNUkBRIM2cIrhA1u61u1AwNu+EtKQe8uJ7AUoBRQJMy/z0vb1gbe2Q1yyFNPebwMCAUIGTJaCjC8qaZeBd3TD37Q/F7xMg6NNTWOAtfJIgNOUlUP9mNbgkCbEH3RCyyQUpmPv2h0Jm7ERT374HctMc0Mk1OUln2wT22Y2gE8ZCapwO3tVrjWkAnJmR8saR5oRWEi9NqQGKC0EKC8DBge4+ATV88Q2xKzMIg0x2oBXGK+9AXrkQGD0CUsM9wEAW0op5kPqzIClVyCjHwAf9u+fKXy73wC+TSPgyJclQQt0AV2QvD8NPvk8pQFYXa7e7HygvEgIfs6cBzBSKZ0Zo6eOE/UUuN80VnasQ9TTjtR2QFs8CevrBu3pBykthvPhmkGP2+IOiSMnqkJc1AIoEbjIQzr0cEiZ8gyTDBDQNoBSs5YhnrdnjUB5/EObr7wdhV1FwLsCz/mlNBuSmkQBjMDa/54U+WWvV2LoLctMccY/7BqBv3BYKJ4u6/wBEtw7W7jw4lO805Z7lru7c9Xb3gIyqAEaIHTH1x4+KJL3A7qTpUFbf58CyWHev17+LUmG6XF8LcA6UloCUFIrC2OJfub25AuH+PiCWKa41F7yrJ/E7cFCy1r6iY7g7QZ7j+QVR/CHL0bAVxuI3vSLUCa+qyPMa8uGL8zFbvl4jr1h4aSNfBF1IWF/msZ0GAChQQVIq6KgKsFNnQG+5GfrOj6GsWQqSgPEkhSnw0+dy3YIP/iPSr8NTKNxXJ7oQE8ZCWbUIvFgBrcrJKhvrt4rjffhJKAHe2LwzfECGGdq1UJ54OFcYyRTK91aBtRwJJEa0Kg3z0xYHcic1TgcIASkpBO/uC0/2nHMLKGCs+tX+VkgN3/TA8eik24RB46tBrxMUqtGE36o0OKWiOOg9B1JcCBQXgBhMJI2UQrp/NiBJnq5bZDdL06D9/S+FF9TkGug/XQ9oOtSfrI1X4ArZPSeA9wclqfuW1QdVcJvbdgeTfVdXxwNtuvtr4F+dcU0YdQogOuk2LzzUFmA4fgqcMdEBGHdT9H20FAL15zaKBDvMjNgqEgLQyfkzwFOqKGbe2R3kPy2dA+1/PB9+3pY2SAPZoHR7UkFiJfpu3gM7cSq2Q4wls8X/Z/XonfMIPyQAQEoJ517Y6+8XLzpCKpClXBFg/T87fQ7mO3sC3Cdp6iQY7+8NJf2T8hJAkgSE13fOsCIxwGmTZQFrtIKf6xLHjIvB4OBd7xluPor/eFLjjFjOIO/qAZkQoW4YIQwx6NevhsjzGvLhj95ow3LW0hZutnwdR16x8NJFvgi6kLC/zBPU4SBLohOwZqmAMXX2OMRtacW8+B/UlArIsofo7Y6AX4eVDPOuHudvtr48cXuzRPjasK4emLv3hf4Y06o0UFwA863fesehKoKnZElnO++vyUB54mEBv+npCxQHdpIlLa0X0tZ6QiJvzYNfkSsQPnNU9vkhGACk5XMhfdXp7R49s9ERCwhApebUgre2C9lhXQcpUMFaT0C3lbmQgzbxOXcDFMCAHhCvsMP2vXE6Hdb94UkqYZwJ3x9dFwaoB4+IDqFvbmKjQAX78+FEtTW2vxWgklgvIIEChrW1C3jfUgETJCMqwN/zFsTqf/oLR0QgUIAsnwtw0bHk5zrjx2yt5aFIijudsSm3e/7tfj/v7I4/b1+4uS5raYNSHyxIaHUGZGQZ1L9b592xS7qv9uvn4YckvleUAGzCHifg9ZuSv3Wf9z19/V6zXSvI2Bs9fj6eY1Li+JAN5pwBgZA7JoL39Yt1BTiihzxBTRCKAuj6oNTJhttnI+x45kf7oD6xKhzmuKIRJKVE79ombZglvX41xCVS6MvHVRT57mA+rtDIF0EXEtaXPe/pt3ZbZe/ud1GBgJz0DQhls65e0JtvACsudBI76Vw3pDm1oFNqcvATRQbv7AapKAXRdJht7fGJYFs7lCX14rwpBcpjzUBpMeiEscInx8Jh8wSYEiQKUlYC+YEGsK9NFIR733hgmoEESaqrhfl6UKzA3j1Xv/8I+FfnwA4fDxQHrPU4JMaBgSxIRWk0vKw6Aw4OWp0Gsgm7pSEFAfv8EORF90LzCTbQqjRgGqB103IO7gUqWFcvAAL2+89j1cBYSxuM13aCjB8D6etV0H4RLsAAeP1z2IFWKLOnCY8VKcQ41B0mE/A+iQLFBaATx4P4lMXYiVMJiaTsVfNz75JXZ0Sy+sIWAW2aOTm04yg/uAD8TAcYAO3nv4Lc1ABz58eB+86pBDMkwWYtbTBe3QFpxTzRCYzzmYJQHlMea06eH1+R4CjCUeKFbVrFHGjC8eIKygLVo7pH05Wim6kqQVx7kl9SSnQhHbGHqPBBNp1i0jQG1UGyuYWe6OkLf87ivmdcPmRR51SXzhHPKONgB3NwQzrpNshNDeGbDVMngd56C4xN2wLdG7l5PtiBVpDSYkjzpkOa+01PhzmAlU/io/T2gVnvGxRULuR40vTJMLbuCoc5/uZ9yKsX+0TtXXGJC4TLIVOd5zXkIxD57mA+rtDIF0EXEPaXPe/PQvvla8KQ840PQuSH5wvugsnAznVaSZYlCKHrAk61b78HgmMnpujPgh8/BUR5ndgwudd3eZPW6gzkpoYcvyOrC1lluxMQRca/cyLkJfVg+/7sHU9NxuIQhXSIEnbqeUcX2OHjQRiRf+w2CZ+HSCvPngpz9z7I874pisKh+jIB4L7OjH1vwDjYrt95DDVtqJ7/WM6Od8M9gMlyCmKjRwCyBHnVIhivvhvoAtGqdIg4OYe8cgFASHwnsSAF1tIGOulWRxnPD8khY28CnTBOqKT51oHUOAMcgP78Zihrl4HeVS0MPx1eRrezKx/XcTQ2bQO5JacYSMpKRRHrKzSIHm9oK9uGtgn30fyDgE26DUhDI6xoYSbIDaPA3/v3wPOIr00EvWMi2GfhqmtR6wcAiKJA+/9eBK3JQP3xWvCeXrFZELGTGdvlBYTwwdEvY7llXNc9PBqHU+T3ivL56JCy4hxXxz++qJ3XJFhlwo4tH8iCFKTAKRG+Z9VpASdlLLTzJArjdyEvnxfEwSsK+NlOsP/wbURUZ6D+6NviH2Ul3qQ6bnyqAnCES3FHQeVCjud830XBHGOI/5eyQLicMtV5XkM+PFFcGP8bV5xfF/m4PJEvgi4wSEUZuHYG8uJZ4d2QljYYm7aDzpoK/ZlXQCeMhdzUADKyHFLjDJCRFeCd3ZAWzoJ0f70wKJUksdP84SeQm+YIaWUlfLc4Mmk90Apjy06xS60ZItEedyPIXVVgR0+Cd/WGfo6MGe3xzHGOZ+Phl9QHB5GUOPUNgKYrAwlDYOxuiN686UIq2mAeeBmfUxuvfjVrqoeL47m2ogKoP/lOLlFjJtjZTrCd/x46f+DhHBDW1g7V4hj5E2xp/gwojz8I/ZlXPJA5qW6aIOu7x1NRBnboKMioCsT5DZGiFCBRz/py1PUsnx1aXgre2QU6udojGMG7ugFNAzEK4AhjRPwQ2Ql0XCdAmTUtdx9ZBD9s3YrQz9thwwLjjFnlB+aCnz4L+lgzuC46CWEy3ZFFb0VZNKzr9V3C18swghsHKxphvBbOh6NVaXCLuM72t8LYuA10yu2CE5gK+SolJP6+EgLN9kN6THTF/MIPznoO44rcPzv331GbGlbnEkW+ndaondckWGXSjm1WhxYiR6+sa47lvdmCALastN3BMLftCf9ue3UH5ObGYFcjZnxSXa1QIvT7+8RB5cKOd4GFIgDQu2p8GxEJ5tFDjOGGBZ5P5HkN+bCDlpcKu48odbg8HygflynyRdBwRO8A6LibY2VepYZvOvK7XKIgnIAfOeGRfXUw9C9syRGaGYO+fqv40QqBUcQmrYePQ31gHoxN273nsZI9befHgc8kJcHSgnuDOzpJiZO785V0LpuEv31PqN8QazkCmhkb4DOhrARgDObOfw/nM905UYygtx/oHwDPamCt7ZDuqoIRJ0oQQkqX6mrDVc1cfBTlydWAJa3N2tph7t4HOnNybjw1GbCOLpCSYqCvH/qv3vBej81ZWr8VyuMPQpp0G7Q3PvAOhCBX9BAeW+DID8wV8/3RPsjrVrg8kVSwzh4YG97KnTsu3K9XlHnl0t0Diwvb0NZf9MoSiCKDHTsp5Nl9vCuDEo9nTpgAhf13MBafdGt6SMEoElF5SR0M0wz3W3LxhWzYnbF5J+SHFwdPpCowd+8LhU2Zu/dBWj7PuUb92Y1QnlztGQ9GlAo/pSiyPKXOd0ISZ9DPCYqCZcV252oyYkc3Bs4VnczHWyHw0+dgbn0PyqpFAABjw1uQZk2Lv4dhHMI4uFnV+HioX1gHJ+x4F1AoRhUnAMCG0wckL1Odjyss6KgK8T1k+wQVpsT3Sb4AysdljHwRNByRUsC/SvDK6B+A+fEfoTzWDH7wGMxP/pwscgBAbmqA+uRqcIlCXjFfSCl7YDzRyYVUVxu+G35AOLmHKl0lJcHdPYHdbdbWHquwxtraIX29KiS5SvCIChmLuWsv1B9+G8ZrOzw+NHTSbZAfaIA0RySbngT2zomQlzUIOI5fHe72CUMeQxL8T6qrBbGvjgBkRCmkabdD+8UG8fkaUYSa+/aD3DhSyBrH+OqQghS4T+xBqquF+dtPQMbeKLhkHEHpcosDY+7aK6SNwRxCt+HbjVOfWAV+piOZmF1WIqCdRQUgEg1NlpMSaX7qbO4Pmi78fdJjgAIFRkhR5XCJls+DNH2y4NBwDhSkYL6zO6BGJs2fAZjx/Dfe0RW6aUGr0iC3jhOy33O/CVAiuF+tonAhfliqYfFy+rNgbg+jkiKgp0/w6w4eyb3fXg933wn+lXcecLYT+vObnT+pTz2auzYf1A2KDMiSA61KWpPo6wdTZCfBjoJl8ROnxY7tK++Ew6jKSyPhXPLKheDnugL3nlalBZ8wLmQZbH8rzM8Pg326XxR20ydHv19VAErBTp0J8F2ixkeSipcw6FvI8RILxThez6UqTnrDxT0G/Xo+8jGIGCrnjJaX5lXg8nFFRb4IGo4gBChISB4t0QTzjQ8g1U2L5UzYClSspQ0wGbSfvuAkd9LCmZBmfQMoTIFY8s1uorYnIYxLjCxifiBVTEoUJBn6+i2ergW5cSRw953C3d7f6l4+F8abH8KUaGBHPDHhDhuLpoP39oeTkt/eDWnO3YI0rgs/GK4o4D19gQIIsPhKfl7FoOYjoXiT/cR7AoBA/Yvl4JSCFBWAn/oKNF0JUlYMrhkJ6oLUI6oAAHTCWCA9xoE/Kd9/JB4OpenADSPDoY5WkSE/uADcNKPHUp0BP3UGpKRIrOOZU0Iv34G5URIiwFALjCoLcFz09VuhPrk6nkukG0LYoqRIFHNbdwkvnLnfBEwTJKU6hWciJImEiyaYu/YKmfnnNgrxhqq0ULJraw/tOtnrg5/pgO4y3KU1gpPHz3SC7TsQgLmREeVASXHosQBR1HNwwYcaGBDKjUdPQl+/JdchswoTec1S4OQZxAU/dQ7mlvc8fJAo3gYtKozlc0R9Dr190J95JbSjaX7+RfRGSXUG7NhJceyyktx7or6LLOifsXln0DfKur7Q8fX0xc5RVAcncLyiFDD9rqBM+GB4PZdKJStJbCPp9XzkIyEuJ+csH/kYrsgXQcMRBEBRymsw6EqqaLpS7B7ainANd8cfz6WGxfv6AbigVlMngYwZHeAfhfp0JKCSwl6P3eWszlgcE6trYe9Oj70J5qvvRppCSvfPdmA97qJLXrlgUGaj/jGgqCAox12VhrTwXtEh0AwH6sU7e0AojYHVHAG9YyJI5eigp0376QC8RySwCV/whEL76QuesZHRI0BGlIEfaIW+eWcuka3OQFowM5Y7wjt7gMIC730pKoD5xge5fxeoMLd/5L0H9hrcvQ9y0xwQI6jsl5sHARGzi/SwschL62H+8aBDVJfqasOv34K5qT9+VPgTZTWQlArW1QP9xTfEOvXBHAEk+xhZzwJ6+qA9vQHyqkUgEoXxzoceDxfe1g6SroxdxygtEpLfEJsF0A3QqvGgX58IuO65rXhmAk4B5BRP4EBRAaTGGQHFOba/FZDlUPU8WzVRXrlA/EFVhIhJUQGUtU3CnLesJCAkEFAmdPE7UJLQPbA6LX4+SBRvI4nPEfY6O30usqMpLbxXzBOHENOwu1rgIBWlYJ09lgdYrvMa9V0UCf3zX59/fMB5K7OFHe+8iP+XUCUrdmMlH/m4gLgSOGf5yMdwRL4IGo6QJKBvILjjW5UWhGddh/78FtDVApef9EPped3MOYizljZIS+ojBRiAHJSOVqVBEtrOZERZ4IeSHz8lujchHhhSfS3IyFLxmROnoTzeDPRrIAPZWFNIecls0MzYwK4tnTgedMJYsaPr6xjID8yF8fouz3Hsv2vPbhRqUm5J654+kKKCAPzP9u5wVPJ8YX60z/EJCqr6LQDAc10LRQbnHJCk+OLNDX+Ci5fR3BiAYLEDrZDmfTPIcXJzgtatAPvskKc4IdQHRdN0IW0d0gmS6qaBawaIluRbI+4jO3QkdCy8qxd03M3Q3/5QjCOuYM6MBTt0zGOGSqvSYpewpAjyygXCkNdVDCYZB7ufBfT0wXhuk/AkaporOFoHWnPdz7b2SPEMeUUj2OF2SLOmwHxvb/C+N8/3rBc+kAU/cgIAIrtt+NpE7xpTFSCrxRedWU10NR5rhrn9IzBrbdiF3GDgsg6EKpYLk9tQuKh8kJj7R8ePAXQd0oIZkEuKYWza7p3DauEpRigVhaAigx09CaleFNreZ/o8uD0YfmW28yL+XyqJ7ARRDpCkHbJ8XM64HNLmQ4o85ywf10jki6BhCvOdPaFwKxACMmGsSI4svw/OWLx0rkRFInT8lPA1cQUBwrsaqgKSroQ0uQbS7RlwVQGXafxuYAhEjbW1Q3t2kygyljUIJTVVcXbxAUBevRjyDSMc+Juytil2bnhfFnRyTY70rchARSk4mBCVCJFs5n0DkJY1QF4wE9wSGODg4B1dUJbPg+mTtFaefDhSDcx47d1w/hMsz48o6d5N2yA1L/B0zHjbCZhnzkFeOgfGb94Lwr1mh6vTRRK5YXWjJowN3UGnVWmgrBj0lpsBw4C0aBakJfXguuHjiZjOGkBbu5OMO4nzfbOTfWvsJDZiN5/67nOcupvUOF2Y5PrnAACtmwa274CQmO7uFR07xmAmmbn6ngVakwEkGcZrOwSHZ/a0HMzHFl1ouAfqknqro0fE+v6H50EzYyMl0I1XvXw5UqAKH6mQzQHnul7f5fmMVFeb7GeV1aH++FGxbt0bBEMwhwUA9GdBbxwVnuCHiUdcLGPCmAQfpUXAgAb+5RmYb++OVGMk6UqP2SrG3wxy6zjxHQUOMqoCSOgYoj8bmURebunmSyaRXVQA8zfhXkbm7n2QH1owPOfJx7CEs14HNKCwINQz64qCmeXNT/NxjUS+CBqO8BHx3cEOtEKpmwZeLWBUtDoD9A3E79J19oC3tUN+cD60f37Zczwe5i7vksf1qMDdOTG6q1M3DbynP5jsuo7lJ88rqxZBX78V/HA7jPddcJQEHhEpTEF3dQSc8zz1qJDADeuo1GQg3V8P3p/NkcVVBepTa4TMrV/aW1Wjd933t0KZ+83QIihpV1k62+lJ5m1vIeP1D0AyY6EsuNfho0CWoP3sX6PVvCKSYnPXXqhPPRrg69hdC+O1nR55aFvtLY4D5IZFspY2yLQenCYUxWoCT8B/n93qbjY/bGQ5oMrQfro+dB5YSxukhnuEOMfGbU7SS6vSkBruBvlaldPVccZWnYG8fB60X7zom5v5gK57upCK24BV0wGThYstxEmgu6TAaVUa5qeWX9H3Ho5VK3MXJzRdCRQkFZ0qwHiwaBiKQh/gFK9Ogt/RDX76nKeb6LkXQ4BcDWVH2k7wzc8P+4yWe0BUBcbW9yHV1cbzIV1zaL+PpCth/vZ3ThLITsXzn6AqsV5Al1u6+VIUYrS8FPKKeTB+/Xaw05mXJL6iws2tiewCX2kws7z5aT6ukcgXQcMRAwkwo4IUyPgx0H7+b8JctaMb7I8HI3fpyNgbxY70K9tEEmwl4bQqHeoXFImR/9NBGIyD1k0TO9N+IvoPHhn8sVxQHP9OdZLpJZf8QgEQSVnfQHRSub8V0qJZQKGaO7amg/dnQ88TWhy6gkhSuGqVLdccFT5VNvu+kHQlzLc/hGlBw6TGGaB33hZdAAHRPwyaLro8S+shEQLCuLieAhXsi+Ngh4LwOt7Xn3if3Mk9H8iCtbVDfnAB2ME2D3eNd3aDThwPdjiJD9Yj1L/cUEBX18gWEaA1mfh5kCVnrHbSy1raQKdOAhQl1OuI9/RB/f5qoKdfmMe2tkP7h19C8Uk/+9fikLsqdhiGp4tCazLJHDt3cWIY4FJS0amGk/UHJTlvHccHoaJFhWC6AXPzzujzJnUErYgjPnNViSyObHU392fo+JtFARwhpuGEr8BjLW1QmxqAObW5IiEBUsZa2y8ZV+F8YUuXohDLSxJf+eHn1iRZVFwxMLNLBevMRz4ucuSLoOGIhKSCWDvCyqrFADNBJ44TXJjXdgT5G/W1YEdPOjwUUlEKed0KEFUFKAEpTAW+fGK/OD8/BGnmlAARXaiOhRQGSUljfa1HuAGIgUVZ6nC8szeoxHX0pJD4fepRISed1YRJ7IFWmDs/Fkm0bgC6IVTxGqeDtRwBunrD5zgpsUupkB6YC5lz8P4sSEoRZOykz4UkpGHJM01XAkmdFomGSh1zexwd3QFzyFDBCwDI6oPeUQdEN87c9TtIk2tC1croxPEwtu50fFoC9/GBuYBEYWx5T/C1QrhXdsEgTamJmEx7LC5VwJQCqXEGzF17QSpvjPAdsiB2zfMBQoGznSDlJaKwLyvxzikzQaZOynWThtpVscd4wwhhDNzRBWXNMmBEGUiC7LZnrRQWgBim4LRYhraea6mbJjhBSsj6SthUsCF8bgiVJxlXFUhL6oC3duc6iJb4Ah13M3CmU8h5xyTsnuTMPb+mAd43IOTUs9Yz2tsPfugYcHtGmCGGFCC8cUZwjpLm0A5NFxyE0+ecQiNSpnvFfGj/8MvwaxrmJPJqUMe6GJLEVzxf5WqKnj6ww8dzv48pJVLtFcBFhZmdT9f3osM685GPixz5IugCg53pAEeCEo+ieNTMlO+uhP4vr0Gqq4V6f53DeWHHTgIE4F8cc8jn9jHcuH7lsWahsmQnVkmJnk/S2YHDnT4XhOUlHIsUpMD9yaAfFpVSRJLe1g7jzQ8h3z87qOZWnQGZcjuMLe95oV7VGSiPLoP+whaAcejPvOL7THiCzbp748UKOrpgPLfJuXbtmVdA05WgKxcOKuEMhH+eDAPoT4A59g4IEvy2Pd65qMkI2JWvAHIfJwDbiuAXhY2P1mTAuvsg318PY+P2IHdtfyuMjdshTZ8cKdDAz3WCHTkJMmY0uGGCTrk9tLtI05XgIcW1ey64u6OSFT5Bypqlgu8WVdgdaIXU0eWsNWi66DzVTgrOqZXwy0vqE7s3ZGR5johvqzlOGAuUFIL0DYBTClAiXm87Hu8PU1YM5TtNwvepKAXeN+A1tHV1tkAA3tMHdvBo4JixmworFwD9WUi1dzgQqtBkvCoN6f46IadvGCCjR8J47V2PMEdswm4Tn13wWH37Hs+//WOjE8aCHT4ePtEW1HKwBZ47uG5A/2/PBcYdKoP9VUd8F3KYkshEdazm+UBRwTVXHFwNhd9VFQPaoGHNAC4azOx87uvl5tflIx/DEfki6AKCdXbD+PXbkJvmRie/99cJ9TP3j35KdWBENF3pcF6kxhkw39ubmAjrz26E3NQAafEsQJVBGAKJnOeLs6gw3JflB4+AGwbkZQ2WUpUMv9SvP7hpCiK/O5FRFUgN9wi+E2PCryWlCuGFytGhHB7bsJWkKwFXEWQn6HJTQ1Bl7UAreP9AMIlSFRBCIDVOBzgP8mqa5kJ7+qXQuTRef19wfDZtD/wASLPCRQ4ACNNQl2ocSotBAGj/58XQIsKeb3PLh6F4b36uc0idnbAOgiesHXValYY0ayrMDz+BfN8sGBveDD+H7RsVJXH81KNOh878aJ8oPN78IFTVD4zFFoPE9W/mwr9LC2fGX1PfAMzdnzj3jrW0gWcNoazmU8ozXn5HdFwemBurmmb+ocVDxFceawa9oQJckWFs2eng9Kkswdi8M7o4WdEI4ze7IN3zNZhv/RasrV2IHrwVvN/OZ5obwwseTYe5ex+kJXWQuvtEwWtLzm/eCXn14hz0LCoZt8QaSLoSAMB/+/uh8QysYsEPj42Dyxqv7QjlWHnmO6rAi3jexLPu+x5wj/vGUd7XCs7PC2jIkaCOxb886+ExBd5zFXZT8rLIFyGKCgal9gpcPJjZhdzXy82vy0c+LjTyRdCFRG+/SMQkIrg8IRwfZHWwzw56P1eYchJ5duyk08EYNH9B02Fs3gn1x2tF8u6X5XbtINGqNNjnXwQSE1qTAVKpAHdAXrkwuqNSkwEKUqC33JSDHLUeh/LoMrGT5e9ezZ8BUqBCc/098prcfz/QCvn+OmibdwY/pJuQV8wF++J4jtdSVgJ+8jSMN38Lafpkzz3gXT0w/9ji4V54uCj79oN/8y5I99UJ082+AVFA3FAOc8v7obvKtCYjzufeVa/OQFo2B9Qi+oeqvPlgUZ7oS3Bw93eeUkqCa70ofN3EeD7jrvhzRJjA0uoMzM8OiblQFUF+f3s3yC1joMyaBpgGUF4qVN5OnwW5eXTk82Du3gdpWX2gu8la2kQxHheyHFgzkWqJAFjrcciUCJXDs51i/l3eXX7VNNbSJiCn1u6mG6ePvoFQIQjnOe/th9zUIOBgTlc1wZfJMD3HVJsaRMGjyDA/2Q/9Fy+FdzXckK64ZNyaKwBD5xlYxYL/O+m8DJgBoKNLFMa74J1DcCGiIEswfrPLa/ZswWm1pzcMftyXiquQ1FEyjMgk8qrtpuRlkYc/Er4j7O+6iwozy9/XfFzHkS+CLiSsH0Le0S14EiFeM+T2CYGPEd10dsoBOB2MofAXpLraQAEEeHeQbIU5Y8t7nveIXegFMF4LdmiMzTugPP4gQBDsjMybDv0XLzrJsNzUkFOfixpH4/RBX5M7eFRRUFQA3hPhyWSp15m+xFFZ1xxMzNznzWrQf/maKOb27BPJ3F8/BGnmZJHM+Hes54XIPx9ohZSk+hcHzRoKGb4qDVJcGH6uamtH/Z82hCTQ8dgwUlYS5Ij5dug9nYDPD8G04VEu41blseWQl9bBeDXIeZOXzxXeUunKANSDUwzK68Z97xwDVX9Y4zI2vRvg46g/WQvzPz4PQk1grflz3QAlOV5eWXEOAholH54Rhqvuc/GERNl53TqmdOdtjrFyVDcFgDcBH0QyDiCUi+Z0ja1jeLoTKRXyyoUAM8OPF31V4X8uSEF/bpO3gATA2k6I7tC6ZpCxN0KZOSVotjx9cvh8hFz7JeMqJHWUrOfVn0Re1d2UvCzy8EeSoE+BCvXv1l1cmFn+vubjOo58EXQhYUvTFhXC2LwzdOebuw0ereADWWc3VPpaFbSf/xukulohLxwX7kQ4oWukLqmHCQiIzpI6SDMme2A1vKML7E8HQz8PTQO9qybn3WN1WvRnN+aSRgtypPz1qljZYHlJ/aCvyROUejHRVhJHClIw3vggtvgLJExhiZv7vLIsduRf2CKStNnTQIqLoP3zryGvWpQzZU2p4KoMPUr++dBR8JNfCU8Zt5FrZw/MvX+CfH9d5DSwtvb4DtzIMgF5tDsPfdlQHhZKCiMKIOsccdCwzw7l1jA4yIgycEqh/2Puev3rLhQeVVgE7ekNgbljXT3Qnt4A9bsPhSe1nb3C+HTzjnivG/e9C3m+IscFC4a5cTvI+DGR3BHePyAgdq57Ia9cGNth4ACIr3AnBfGJcuB1O7EeivxswnvJ6BEASCzvAEWpyO6E3DTXawKbJIc/sjwo3FKTARlRHt0lrc6AtbSFvgYAyswp4d2liGu/JFyFQZrTAvAmkVfzrnteFnn4I2nOSosCkM9LPob8fc3HNRz5IuhCorhQ7MoDAvL22cHQH+tAcitJOU7QbeOc/wbiBRa8pOGIHVf71bOdOePGb37d27lQFXHekJDqagO8JGVdswf65Yn+eBgXZyxesCCECE2r0kCBAvO9f7eS2b1OEofJNYP2anHCl7h5FLYs6WcAnl1+5UdrRGdo2x6vKetjzdHEa4lCXjQLxqbtAY8leUVj7txhEt/HT0F+oEF4Avk6XPKyBvCO7pxfEiAU2Fzjtf0lpLrayPHF+hEtqQfv6hVcI87BWo7AXL9V7EynKyOFM0KLcVkCHTMaxnObAmOgVWlw6utIWV1FpFTws+cgNy8Ashp4/4BTROob3hKHXrkAKCpwOHBIKaB31YDcONLT5UBhwfnBtgCA8cAaMzbvCAqSWNcjzZsOFKSAzh7PZ3iBGvs8c5cvkweqNRRIV9J7K0oB3YC5OcLkFYD88OJA5wQQSbmxeYcoTC2fr1hhg5oMQIgonGRJQAgLVDHe/izk5Y0wNr8byiPT/nF94HhOhGxiJEHbLjZXIbLjZCn/6S9syb3ZnUTa6n0JXbnhimHlHuVlkYc/roQ5vRLGkA9PXI2cwas18kXQBQQtL4X80ELwju7oH7aP9kH93irBn7ESB3agNfel49rJjlOFcu+E06o0yIgE7Lg78XcriVkwIZBwAYTQpDYOApME4+obCJdUdhmBes5vXav51m6QsTeK+XTv6mcHCf9xHc9daHm8X2yi/ugRwUJNljwQLydiak9aMyFQYAAWaXzTdsjNjZDmz3D+5nyuOiPgY29+CDJ+DBRbSaywwDHU9F8Xp9Tzw2V+tA/qE6vADscomGXGwvzDAdHtaZwOoshAUYHzI0cUGdBNj8QwodQLu/Pf77C1YfM//NdpwwI7unPvVYUkrLn9IzBLeMB4+e3A55SHFwMpVSjo+bhYcrNYR+51q6xbERyXJ6L5T35BDgCiU/jsRihPrvYovbG2dujPboT65GqYvgKBaHrsPBBr7vxQraFAuuLeK69cCPT2AVoCN6l/ILY7IS9rcNZa7HfUrKmimNF0D8eFd3RBf+UdIQVcVyt4ZBYXiB0/FZDcD0RRgeefV5IMr6dj7lL+c173J5FFqcSu3HDFcHOP8rLIwx9XwpxeCWPIRy6uWs7gVRr5IugCg46qANP16B+2VYuEY7obKqcqIN+YJBLmVlfi5CdeuyBJxGQisZNlQJZEEjzYrpErcbVhQiRdGf75JOiYL5IgVryjC+zICZB0JdSlc8A7uwEQoKwYXDNCeQA2BE6ZOQWkMAXp61XQXPLHseHjzsjL5gAcoONuAkqLAVkCMQyoT64G6+qB/tKbUP9iOeQHF4Cf63SEEaII93E74bESzy1tlu+RDjqlBm55aYwohbF1l5AK/wO8/kNVaUgLZgCuLz9alQY/1wV5RSPYwaMWsZyC9/SDjLsZ8sTx4Wp3dbVgR07kiP43jvTuMBUVBjtzmg79xTdya7Kk0Fswhq0NKkHf8KYXDufq6KjfWwXle6vEGEaWw3z9fbADbZZfUIQBLCWgdwW7gOxAq2Ne61YZPC/+U3UGclMDtJ/9a/iHNB042+npyNnBs1quQKBEzH3fQKSQgr5+K9THH4zE+w8F0hX6XkUWfKg/HRRds7hI6j5ouvf4RSlhwpnVgN4BcMMAazni4Vg5HJeHF3t+0N2QN9tc19j3Z0+3yR20JgNy40gxTzHzcKl3TqO4PYBd5NaCHz0RTCJlJdbkWH548UUd34Vyj/KyyMMfV8KcXgljyMdVzhm8SiNfBA1HKGrsDxutmxbAuyt/+QDo7KmgI8qBaXcIkYL9rQ7EidtGox09AKXAiDLoP/+3HNSppAjqE6uEKEFC18jTCbE7PZY3i3ucAAK7rgA8Cnb+4O2nIa+YD2PTtiCPY/4MQBdKdtB0SFNqoFsQKalxBmhNJpIHAAAwDHBTBrpzBqmcx0AGqzMgN5R7uDPaz38Fmq4EsfgIgJAT15/f7BSpKFDBWlqF2hwg8ueBcMJqINF1XW+id09Wh/684B3Z5yJlxeCa7vFKcgdraROGm1QS57GECkCpgGbt+zPYAd/9r68FyYz17LgjpYCf6Qh6UPl3mPz4b4sv5dwnu5NoSZGHcZnYsZOhUEJalYby6DIBlxs9AvqGtyDNmuaMP8ktXZo1Lfy1EBhkkh+Nh/9kF6NlxeBZPd5nJmpDwIa4fvSpSGSzmqP+FrnG7bk+fQ6ssC+QuA8F0uV+L+vrh7F+a259JnVrB8EJCBsL7+gShe0/BdXbAIvj0tufqF6nb9/j6TY512SvzQSzz8uyc5qgyqc2NQBzaoNJ5MBA/EbJwACAYRjzReQe5WWRhz+uhDm9EsZw3cfVzBm8SiNfBA1HaFrsD5tUXxv4OxlZIfg0nIOf64K0vBGyYYD3Z4UhKTNhbPsIdOJ4kAljwU995U3Oevpy5POl9YBugBumZ0eW1mQgN88XRYgddqcnQu4X5SWhBY/jwWPxTmi6EgAHqSgF5wzS/fVi139AA1EVcADss0OOtwytSguegBXmrr2QJlfHz2tRIVhLm3Uuaz4/OxQOKatKC16MJf4AwxCKXbA4RXPuBsJcuT/+I+Sl9WCf7PccT/3J2vAxWfOmfP9bkBbeC2Q1YVjJWHKXqjAVSIoTd+kBUVypplArKy8RReGIUksdMLzwFuprouCiE8eDWPNC0pVAW3twx97eYfLhwwPFhHvdNE4HURXgnq/BePkdr+Gn37vHHhslkJc35nYeT57JvWEI6ohJr8UVq84mgaZ7uhLSkjrwE6eGbObpSNzXZKA0NzpJO/uqI95EWVWg/b/P5P42XIm774c0kcdTXBjPCWAc7NQZT5Fm71hK0yfHj2Ww6nX+btMgd6Iv285p0nXpRvh5+xI+l/T6YCOv+JWPfFx9kX9uL3nki6DhiIHkH0R30DsnCi+QzXvArI6MuXFbqAEjKIH281+JhC6Cd6Tt2gv1J4+CFBdBKi+BdOdtHkiIvHpxLrlwm2yG7FKrP16b4zFYhRAddzP0ZzdCargH6vJ5MF7zSR/XZCAtng325RnQW24W/Cc/efz+OqDXJaKg6eCyFJskkpFlgixcV+u8z9z5Mej4mwOQMt7dC1JaAOPVoLCA8ugykBGl4O+1B+CK0v11QozANwbz8y+iE8N0Jdi+A6Jz8VxOcEL9z4/FJ5OuItCJwoLkDpIsiy7ScxuhrGuG/txGqH/7nXiBiPpa0PTgnMjdO0w2Ptz8/LDoIJkGyF1VYEdPOh09aDr40ROgMyc7Cbv88CLwrzqAvgGQG0ZEe0Ptb3USX1pUCFbihgoNXiY88TWrWFP/9jsAYwGYmMePpiYjJONffRfs0JFwzotF4Dd+s8tzGlqTgby8ESAcmD3Vm7RzBvnBBTBeeSf4bD+4AFzz3vdhS9x9P5RxBqV2pyXACbDEKui4m8FPnRHP2KFjIJMmiHtuFVpR3TknBiklHdVtSozLtXN6vopal0qJK6/4lY98XH2Rf24veeSLoOGIlBr/up+nYuHfWUs8D8J49V1ITQ2gY28ESooEgXzbnmBS+/iDgKp6d1FTKtDbB3b6XK4gunEUWF9/PIeHc49UNAxDyC9rOmCygMABAOdY5JYx0DZu837WZSaJilLvufu1eAK9lXD7kzgHUjZqRG5spUUwNkUoYBECOrkm/LU3PhByyT5DW3P7R1B/9G2wwy5TVkUG7+wGqSiF/vwWUGtMThimIM37FcSqMxaZ3guKolVpQCIg5UFZYc896eoGP9ft6UTwCLieExKFuePjQTmRAwgkzuzT/QF4kfqT74jupaX45SHojygHS1lrsLsPseE+l6vzlNSxcFT8/K9FdWgmjAWKCgIFhWdTwHo20NvnQBJDO6RlxdCefkmY8dZP84hKRBYshgnj7d1eyXRLKtx4fRekuXcHPjIsibv/h9LX9SVFKaC40HMPA5yAlArjtXe9hsBVaZDRI0T3z/YWupAuk3XfaFU6+Ts0Ki7Xzun5KmpZiqKR3cHiYSrY8opf+cjH1Rf55/aSR74IGo4gCTyV0RVQvtMESFZB4ILPJTmwy5xDbp4P85M/gx88GksadxOLPVKtLrUmWlEWrgRjFR7ss0MBPw9lXXPyWA8fh3JfXa5LRQB2/JTo5Gg66LoVYEdOQl65UBSA+1uBrm7ov3ojkHDaxHHlL5Y782onceqSevCzneJ9B484x1fWNUdDEg+0iiIk4rVouWQCtm+/l3NjzSsAkFEVUP+fvxDjAQH6s8EC0r6eF7ZA/e7K3HEsDxZz336YH/7+/9/enUdHUaX9A/9Wb1kInYQtJJCE8LKKEgU0ZBQQCCYaHUQdeZmMojDOMOL2E/ctbjN4GJ05jkcYj7wSnYNExaCOQoQBAiMiDkhYhDeyw4sigoQkZOnt/v6odKWru7q60+mkk/T3c07OIV033be7LtX3qXvvc+XsZxrBk+mGSRC1F+Dae0g+n++Vw5iXCylWv9MoNU8l1HzPWqnEmzvOetOLHGXr/I5S+CxM1+Nx3DMzUaARCwBwaawbMd00DY5PvLIM6mQ2co84KHX+6RxgMjXfkNiuOUJqnj0dqKv3GQHTJYQcTO6u0jxsmpqj/Xdt7bhrfZG61xoOH+T3HCqfy5lzPtMbAY/F+7+6RjmHIY0yoeV64/xyV/MNjwBBvT8RunMaakYtd0ZRx/u+GRBNt+bDEGD9U3vXj4gih/9vOx6DoHAQ0B7RGDYIxusmAE6XvAbIbofxkqHqTk6gdRBNNsBshiG9P+yr/61ZRGtairszbZx8BZyfb1FPtUmywjRjKsRP1b5Z2YDmFNqS8hzK3drmzHY+U/JOnIIhoz+cn232nYrWPPVKsibI05MW3N5yx9nu0F847pWe2T1yIY59H1xWu2CPaxwzThwnJ6vwXnPz3VFACHkvFGsPeUpXYoL8fpwu/fcTGwPLvUVAj1j5TvvKdcqGtfbSNTDfdQuMU3OUDHWuY9/DUb4FpsKJkDL6w/5euTxVbfMOOKETeA/NlNcoBfl5GIYNapkmGcL0Iu+F6ZbH7wq4FsZV36B0xFWjEI02uZPtcMpt32NtiKiu0UhJXAfJbNQc3dH7wtBcTK8xVdBN6pMc9M7tSnAVYLRO1DdoH2hjx73NX6RNdv3F+012ILllVNdn5Cw+FlK/XsraKCnJCtP0KfLNAqOhZQ1dfSOkAf3k68IfZob2ZiN45zTUjFqG3klydr0LDS1/1yMubAFQW+tHRJHD/7cdi0FQOJiMcH65yyfblOvY93B+/iVM06+W1w0ZjbD99R15nUJCPEzNi6DNd/+3kkLY8V653PibCbMZ4uAxGDJSlQ0ilY31PDtqJgPM9xYBTiekGIuSmMAwPAvO5vUZqk5sjAXOzds1OzvOrbthLJwAU+FEeQpPXAxw+cUQ1bXaqcCHDQL+Kx2uoydVz6PcOZ4+Bc59h+T61jfB0Le3ciderwMj9UmEo2y9+nNNToSUPQyOTyrUdY/zzWqnPkc6TV0jI57uqNeBY/J6CY99Xdx30HU7ZGYTDKl9lcfMN+fB7nDIQez4bDg/3aR5Phw2O6TMNLmMe+qkn+x+ylTCev1NbN2fh5xQYjzEzzXydLZWTi/SGjkSFxr8r4X51TUQdQ1wfrhOlQQg0HoQvZTELvfoRpA7q/sd7fKcKrh5uyoBCIyGoNIuewZXlgdv16+I0zdQDVfHvU1fpE0BRmVsNp9Ayx34+83oZpDUGzZ7CzHwi/Sd01AzahkSewJhDno0X4cZv8KGG1hSR+H/247DICgcJAnGyZdrrtcxTssFJEme895og/m3N0NYLLDMnwVH2b98Ughb7p4J2+L3gLp6GEb+F6QYM5yVVT5z833uWBsMcgptr9eW4mPkrGXucs2dWN1pGTdOllNve6RtNoweDuP1k+D02sgSaBkd8VlngpaAQZyvA/JyVZsBBuzAJFm17/Db7DBcOkKVGAFGyX8AMmyQvImhBsPQTHlExycjns6uqID2XX5JgnHqeDmblndgMnW83A48i3t2VO3Olr2QvCgpdwVaynhn93M6IPVNhqhvBGzy3Xh/ac0NwwYBCXFyWxRCHpFzuYDzdfKaBM/24s27s3qhHlJ6qpyOu3lkEAnxcPyzQvOmgGPVBhinT259EoBwLoAPkN7Yb1KJANnbvIMr4XTpTpMV59VrnMLdcQ/5i1TjpoBK8w2HVgVa7Thiwzun1N64gSVR98QgKBycTnnxvVfHXNTIe/y4Dp+E4701SnHzk7+T0xtrJkPYANPMArg274Cx4BdwfKhdDmhZ3C53tI5rlnHXSQlOPNdjaE3LiIuV6+a1b41rdxWMV13WunUmzcSZc7CXyPvyYPxo1bFAHRjNjlx8HAzZw3z+Rm/tgda6LTlhwRigrgFSRqpqHY/UK8AXm9eaHFd9gxyYLP1Qe43T0g9huf83Pk+jjCJpLOxX0cog551ue86NEJIBBmsChM0O0815vpumDs2EccIY2P+nDObmduazluO3N8t37b0CIc3OqpCnJ/pkC7xqDOz/+CecGsGU6bqr5M+sNcFLOBfABygrxcXA8fmX6rZuMUNKT4Xrp3OQqmu1kyJ4B1f1jbqJP4LZBDScgr6Tbe2hH7BYe7T8HmSg1d4jNrxzSu2FG1gSdV8MgsLBheaFvRqjB0LAsepfqoekJv19hUzTJ0NkpgG19fppkCeOg/DocGqVkTfmTFCmqnh3Yr2nZbhOn1XWqfhw+t3WVOZv3Y3RpNTH8cHnPl8aoXRg/AVHqoDKbIKzskpODgFoZvyyv74Clt//CuLED6qOvPnhO/VHUrxGdZTX1FsTpNf5DscCb8kIh2fK7gdnw3DVGBinjIdkMgIWE5y7vlNGkDSzEjZ/0bszGLppdVZd9Q1wlPnJFujSHhkEAOH5OQQbvIRzAXygsjEW9Xlv3iA24MiQ91TBIychTp7Wnia7dRdMs67tsM5Ta+5kt2fAorWmi6hT4waWRN0Wg6BwMJvg/KIS0oB+cjrlZtLAFNjfXOmTSEAE6PiJhiZ5hGfuTfqvG2OGseAqecd2f9OX3HuyBNuB0ambFGjKisa6G+/0xa6qo0B1LVxAu3QAPYMj17HvVZ1wzYxfNjsQa/EdjRIueV8Y7z2PmveLgeQV8DY0yem69egdD3K6kG664f87BaN7Q1iHAxACqKmDNGwQDL2T4Dp1Rvk8dNc8VR2FafqUwKMUdYGDdK1gUPJcvxVs8BLO6VQxFv3EDV4Brl7AqLoT7PVe3JnT/AZPHdRxCuVOdrinmAW1posdSeqMuIElUbfFICgcJGiuCTLfdYuSzcvzcctDd+g/XVyMvCdHcoApWU12wCX8B0CAPLUruSdMt90QXAdGp1MqJEl/jYPXXV33tB/vUSpR3whx7IeWjRfbSxAbNRqGZiqbhHrezXOdqYZj1XqfaXKuY9/D8c9NMN00VfO1dDvXZv//3YK9++53yt/V4wABODdt952aNnKw/IvnNKcgshLKSQF0BPry13gNw9BMCIOk1C3Y4CWsoxO2APtTeb92gIBRuRPsHajZ7HKQMbMAphuulhMOxMfK2dM6YFG8IsQ72WGdYsa76dRVdYINLJmUgah9MAgKh/pGwG6H4dLhLWuCLGZIvRM11/QIs1m/sxxjgWHSODj3HfI/JWu4vP8QzOYAG23WQcpKC/6CqXPHXXIJ/c6jNUHeUyjGLKfZdafd9g7SmuxwVf6vsvFiu13M9UYPmjch1dqbQ1TXAI2N8rqo/Ye0p7Y1TfB5LVFTJyfCgMbnMy0XMBh1qxvM3XdVmfpGCLsDrgPH4Tp+CuLw/wUcrXAHErrZ8oDgvtgDdg7UC+yVdnK2OqTgJWyjE/VNmhuiutur5YHb1O0mUMDoTjbiHahZzMpNEIf3uquOXFDd0KSd2t6dZbIj7mTzbjp1VRHewJJJGYjaD4OgcIi1wL64tHn9TXOHOiEeoqFJM9Cx/+MTWG77JRwfrvOdanXLNNje/Qw4chKwmGFZMFtzcbvp5mkw9EkGoDM6MC0Xhj5Jreok6t1xh8XsPxX41l0wXDQYjg/WwpiXq72XD1qmx6k2XmynIEjvvZhuygMsZp8AyD1txzh1vO5zi3M1EPGxqhTPrpo6CO9g2GSSM9PZ7YBDZ8TOo86BPg/PMqK6Bs4N22C8aizszanQ3enXDdYEOcV5bHPq6/i4lkCivrHtX+yBgky7vImtT5Bx/2+CH5nUee8hi4vRX7tllNTtphUBoypQcwl5OmWgaXTtLT5Ge1pec5ZJz4yN7aYT3E0nCkUk07AzKQNR+2IQFA4J8TCMHAwpMxWStYfc8TQa/G+GePpniHPnYcgeDuMEr0XCTifMebnKomoYDDDdWgA0NKoyuBk8psopHa+aC3I5i0UejYmPDekC7e+OO6A97c8wNBPGa34BxJhh+X+3Q9jskMaNkoM3r81TPafHKRsvtiN/78XvF0fztB3jNVcGembfL6H6Jtjf/kQdDAMQ52rh+HgjLL/7VXjelGct3O/v1Fn5gYR4WO6eCceqDT7p10235sPQO0kJJNr6xa7XOTBOHa+dYa55WmBEv7gD3dntIY8ueQYzrQkYlYx/p8/6XzPVkVPALBbtNU3uGxG/vq796xDhu+lEbRGxNOycRkrUrhgEhYEhPg6mwolwfLBW1fE0z9PeBd04cRyc67f5HSmRMtMgjn0P04wpgM0ub7AZYH1QuFPE+ns+0ScJQisVuM0G+5srWzq9zdNvzBPG6k+PswXYmLEd34um5mk5ru+O+p+K6B7N8v4SijHrjzAESpwQIkN8HFwJch1MMwvkPZ600q+//zlMv75OGf0Kxxe75nO4hBzkZ6aFtpGru87tNA8+2Du7nu0mpICxs0wBC5CN0t/mqOH8/CO9qSlRW0UkDXtnuYYQdVMMgsLAdb4Wjg/W+nY8Dx7XXPuju9C6OauW/V9b5T2DbpzSbvUOhZRk9dmjR+qbBNtf3vEKblqCAfPcm2H3SN2sEhdgY8aO1jwtx7nxa5hv/yUgwXeaoWeyB88vIbMp5MQIbdZ8p91gTVAF4p5cB47Je0J5TAEMxxe7T1KJ02eVETHNNTcP3h7wOdt7HnxrA8CQAsbOMgUshI5Ue3z+3NSUqJU6yzWESEdXTtzBICgcLjRodnzdKXIhSV4jChr7CXlqXojtOnAMEAKu+oZO1aB8Or3na2HIGuB3qou/vUC8N17sFDym7djf+QTm+bNU+5r4jGZ5fgk5XfqJEZyusFdXufg02mC6aRrE+Vr9P+iIO4cJ8TBkDdAcEQtm6lNHzYNvbQDY6oCxs0wBa2VHqj0/f25qStQKneUaQuRHV0/cwSAoHPx1LG122P/xT5j/MLNl7U98bKv22xE/nYPznxWdu0GZTXIiAZfw7fzn5UJKtvpcyDvrNBjvaTuuPQf8J3nQ+hLSS4yA8L5Xn4uPxQzLvUX6f9QBdw7bPPWpm8yD7zRTwFrbkeomnz9RV9dpriFEGrpD4g4GQeGg17G02SGZTUBCXEuCgQuNutOmPDcXhcnU+RtUXT3sSz/Unv705kpYFtzepabBqKbtNNqAyy+Go2xd4C+h+Fg4y7fAcMXFLQkyYi0QEHB+tcd3b6E20Lz42OxwVdfoT8nr0TGfeZumPnWjefCdYQpYqztS3ejzJ+rqOsM1hEhTN7hhxiAoHHrEBex4eqZidp2p1t1vx73exDMg6tQNqqFJPyFAfRMMfXt3zrr74T1tJ6gvIbMJpusnwbFyrW9mtluuCe+aID8XH8d75Up2OO+2pbUnUnsKeepTN5sH3xmmgLWqI9XNPn+irq4zXEOIfHSDG2YMgsLAkNgTplvz4Xj/8+A6nh77CpknjQMsZnkq2cHjynoTnwX4QOdtUN240+Sz4K9vsv/RuPpGOFZqJMg4cAyOlWvDuyeSv7ZQVw/b4vfkaXF2e0u9vQLxTo3z4NtF0B0pfv5ERBRIN+j7MQgKE0PvJHm/jQsNgTue3gvHPXZzN9x2g7zHyP7DvumkO2uD6qadplYv+GuyB0hFHMY9kfTaQl09IFwwpPUL3+t1IM6Djyx+/kREFFA36PsxCAojQ2JPVfphv+W8OxnNU8mEe5PJN9733WSyEzeo7thpCmnBn5/9VhTh3BOpG1x89HAefGTx8yciIj3doe/HIChC/HYybHafdNNdoUF1u05TKAv+4gPseRTGPZG6w8UnEM6Djyx+/kREpKer9/0YBEWQZicjPq7LNqhu1WkKZcGftYf+6EyY90Tq6hcfIiIi6tq6ct+PQVAn1JUbVLcRwoK/SIzOsK0QERERtR6DICItIa654egMERERUedniHQFiDoj96iOYfgg9ePNozp6m9Ya4uNg6NdbzvbXr3fn3OCWiIiIKIpxJIjID47qEBEREXVPDIKIdHDNDREREVH3w+lwREREREQUVRgEERERERFRVGEQREREREREUYVBEBERERERRRUGQUREREREFFUYBBERERERUVRhEERERERERFGFQRAREREREUUVBkFERERERBRVGAQREREREVFUYRBERERERERRxRTpCrSFEAIAUFNTE+GaEBERERFRJLljAneMoKdLB0G1tbUAgPT09AjXhIiIiIiIOoPa2lokJibqlpFEMKFSJ+VyufD999+jZ8+ekCQponWpqalBeno6Tpw4AavVGtG6UOSxPZAntgfyxjZBntgeyBPbQ+iEEKitrUVaWhoMBv1VP116JMhgMGDgwIGRroaK1WplgyUF2wN5Ynsgb2wT5IntgTyxPYQm0AiQGxMjEBERERFRVGEQREREREREUYVBUJjExMSguLgYMTExka4KdQJsD+SJ7YG8sU2QJ7YH8sT20DG6dGIEIiIiIiKi1uJIEBERERERRRUGQUREREREFFUYBBERERERUVRhEERERERERFGFQVCYvP766xg0aBBiY2ORk5ODr7/+OtJVogA2b96MG264AWlpaZAkCR999JHquBACzzzzDFJTUxEXF4e8vDwcOHBAVebnn39GUVERrFYrkpKSMHfuXNTV1anK7N69GxMmTEBsbCzS09OxaNEin7p88MEHGDFiBGJjY3HJJZdg9erVra4LhW7hwoW4/PLL0bNnT/Tr1w833ngjqqqqVGUaGxsxf/589O7dGwkJCbj55pvx448/qsocP34chYWFiI+PR79+/fDwww/D4XCoylRUVGDMmDGIiYnBkCFDUFJS4lOfQNeTYOpCoVuyZAlGjx6tbFSYm5uLNWvWKMfZFqLbSy+9BEmS8MADDyiPsU1Ej2effRaSJKl+RowYoRxnW+hCBLVZaWmpsFgs4q233hLffvutuOuuu0RSUpL48ccfI1010rF69Wrx5JNPirKyMgFArFq1SnX8pZdeEomJieKjjz4Su3btEr/85S9FVlaWaGhoUMoUFBSI7Oxs8dVXX4l///vfYsiQIWLWrFnK8fPnz4uUlBRRVFQk9u7dK1asWCHi4uLEG2+8oZTZsmWLMBqNYtGiRWLfvn3iqaeeEmazWezZs6dVdaHQ5efni2XLlom9e/eKyspKcd1114mMjAxRV1enlJk3b55IT08X69evF9u3bxfjx48Xv/jFL5TjDodDXHzxxSIvL0/s3LlTrF69WvTp00c8/vjjSpnDhw+L+Ph48eCDD4p9+/aJ1157TRiNRlFeXq6UCeZ6Eqgu1DaffPKJ+Oyzz8R3330nqqqqxBNPPCHMZrPYu3evEIJtIZp9/fXXYtCgQWL06NHi/vvvVx5nm4gexcXFYtSoUeKHH35Qfn766SflONtC18EgKAyuuOIKMX/+fOV3p9Mp0tLSxMKFCyNYK2oN7yDI5XKJ/v37iz//+c/KY9XV1SImJkasWLFCCCHEvn37BADxn//8RymzZs0aIUmSOHnypBBCiMWLF4vk5GTR1NSklHn00UfF8OHDld9vvfVWUVhYqKpPTk6O+P3vfx90XSi8Tp8+LQCITZs2CSHkz9tsNosPPvhAKbN//34BQGzdulUIIQfVBoNBnDp1SimzZMkSYbValfP/yCOPiFGjRqlea+bMmSI/P1/5PdD1JJi6UPglJyeLpUuXsi1EsdraWjF06FCxbt06MWnSJCUIYpuILsXFxSI7O1vzGNtC18LpcG1ks9mwY8cO5OXlKY8ZDAbk5eVh69atEawZtcWRI0dw6tQp1XlNTExETk6Ocl63bt2KpKQkjBs3TimTl5cHg8GAbdu2KWUmTpwIi8WilMnPz0dVVRXOnTunlPF8HXcZ9+sEUxcKr/PnzwMAevXqBQDYsWMH7Ha76hyMGDECGRkZqvZwySWXICUlRSmTn5+PmpoafPvtt0oZvXMdzPUkmLpQ+DidTpSWluLChQvIzc1lW4hi8+fPR2Fhoc95Y5uIPgcOHEBaWhoGDx6MoqIiHD9+HADbQlfDIKiNzpw5A6fTqWrMAJCSkoJTp05FqFbUVu5zp3deT506hX79+qmOm0wm9OrVS1VG6zk8X8NfGc/jgepC4eNyufDAAw/gyiuvxMUXXwxAPgcWiwVJSUmqst7nKdRzXVNTg4aGhqCuJ8HUhdpuz549SEhIQExMDObNm4dVq1bhoosuYluIUqWlpfjmm2+wcOFCn2NsE9ElJycHJSUlKC8vx5IlS3DkyBFMmDABtbW1bAtdjCnSFSAi6kzmz5+PvXv34osvvoh0VSiChg8fjsrKSpw/fx4rV67E7NmzsWnTpkhXiyLgxIkTuP/++7Fu3TrExsZGujoUYddee63y79GjRyMnJweZmZl4//33ERcXF8GaUWtxJKiN+vTpA6PR6JNt48cff0T//v0jVCtqK/e50zuv/fv3x+nTp1XHHQ4Hfv75Z1UZrefwfA1/ZTyPB6oLhcc999yDTz/9FBs3bsTAgQOVx/v37w+bzYbq6mpVee/zFOq5tlqtiIuLC+p6EkxdqO0sFguGDBmCsWPHYuHChcjOzsarr77KthCFduzYgdOnT2PMmDEwmUwwmUzYtGkT/va3v8FkMiElJYVtIoolJSVh2LBhOHjwIK8PXQyDoDayWCwYO3Ys1q9frzzmcrmwfv165ObmRrBm1BZZWVno37+/6rzW1NRg27ZtynnNzc1FdXU1duzYoZTZsGEDXC4XcnJylDKbN2+G3W5Xyqxbtw7Dhw9HcnKyUsbzddxl3K8TTF2obYQQuOeee7Bq1Sps2LABWVlZquNjx46F2WxWnYOqqiocP35c1R727NmjCozXrVsHq9WKiy66SCmjd66DuZ4EUxcKP5fLhaamJraFKDR16lTs2bMHlZWVys+4ceNQVFSk/JttInrV1dXh0KFDSE1N5fWhq4l0ZobuoLS0VMTExIiSkhKxb98+8bvf/U4kJSWpMn9Q51NbWyt27twpdu7cKQCIv/zlL2Lnzp3i2LFjQgg5LXVSUpL4+OOPxe7du8X06dM1U2RfdtllYtu2beKLL74QQ4cOVaXIrq6uFikpKeK2224Te/fuFaWlpSI+Pt4nRbbJZBIvv/yy2L9/vyguLtZMkR2oLhS6P/zhDyIxMVFUVFSo0p7W19crZebNmycyMjLEhg0bxPbt20Vubq7Izc1VjrvTnl5zzTWisrJSlJeXi759+2qmPX344YfF/v37xeuvv66Z9jTQ9SRQXahtHnvsMbFp0yZx5MgRsXv3bvHYY48JSZLE2rVrhRBsCyRU2eGEYJuIJgsWLBAVFRXiyJEjYsuWLSIvL0/06dNHnD59WgjBttCVMAgKk9dee01kZGQIi8UirrjiCvHVV19FukoUwMaNGwUAn5/Zs2cLIeTU1E8//bRISUkRMTExYurUqaKqqkr1HGfPnhWzZs0SCQkJwmq1ijvvvFPU1taqyuzatUtcddVVIiYmRgwYMEC89NJLPnV5//33xbBhw4TFYhGjRo0Sn332mep4MHWh0Gm1AwBi2bJlSpmGhgZx9913i+TkZBEfHy9mzJghfvjhB9XzHD16VFx77bUiLi5O9OnTRyxYsEDY7XZVmY0bN4pLL71UWCwWMXjwYNVruAW6ngRTFwrdnDlzRGZmprBYLKJv375i6tSpSgAkBNsC+QZBbBPRY+bMmSI1NVVYLBYxYMAAMXPmTHHw4EHlONtC1yEJIURkxqCIiIiIiIg6HtcEERERERFRVGEQREREREREUYVBEBERERERRRUGQUREREREFFUYBBERERERUVRhEERERERERFGFQRAREREREUUVBkFERNRtlJSUICkpKWC5q6++Gg888EC714eIiDonBkFERBSUO+64AzfeeKPqsZUrVyI2NhavvPKKUkaSJMybN8/n7+fPnw9JknDHHXeonvPZZ59tx1prKysrwwsvvNDhr0tERJ0DgyAiIgrJ0qVLUVRUhCVLlmDBggXK4+np6SgtLUVDQ4PyWGNjI959911kZGREoqoKm80GAOjVqxd69uwZ0boQEVHkMAgiIqJWW7RoEe69916UlpbizjvvVB0bM2YM0tPTUVZWpjxWVlaGjIwMXHbZZbrPu3jxYgwdOhSxsbFISUnBLbfcolu+pKQEGRkZiI+Px4wZM3D27FnV8WeffRaXXnopli5diqysLMTGxgJQT4d74oknkJOT4/Pc2dnZeP7555Xfly5dipEjRyI2NhYjRozA4sWLlWNHjx6FJEkoKyvD5MmTER8fj+zsbGzdulW3/kREFBkMgoiIqFUeffRRvPDCC/j0008xY8YMzTJz5szBsmXLlN/feustn2DJ2/bt23Hffffh+eefR1VVFcrLyzFx4kS/5bdt24a5c+finnvuQWVlJSZPnowXX3zRp9zBgwfx4YcfoqysDJWVlT7Hi4qK8PXXX+PQoUPKY99++y12796NX//61wCA5cuX45lnnsEf//hH7N+/H3/605/w9NNP4+2331Y915NPPomHHnoIlZWVGDZsGGbNmgWHw6H7vomIqOOZIl0BIiLqOtasWYOPP/4Y69evx5QpU/yW+81vfoPHH38cx44dAwBs2bIFpaWlqKioUJUrKSlR/n38+HH06NED119/PXr27InMzEzdkaNXX30VBQUFeOSRRwAAw4YNw5dffony8nJVOZvNhnfeeQd9+/bVfJ5Ro0YhOzsb7777Lp5++mkActCTk5ODIUOGAACKi4vxyiuv4KabbgIAZGVlYd++fXjjjTcwe/Zs5bkeeughFBYWAgCee+45jBo1CgcPHsSIESP8vg8iIup4HAkiIqKgjR49GoMGDUJxcTHq6ur8luvbty8KCwtRUlKCZcuWobCwEH369NF97mnTpiEzMxODBw/GbbfdhuXLl6O+vt5v+f379/tMY8vNzfUpl5mZ6TcAcisqKsK7774LABBCYMWKFSgqKgIAXLhwAYcOHcLcuXORkJCg/Lz44ouq0SNA/nzcUlNTAQCnT5/WfW0iIup4DIKIiChoAwYMQEVFBU6ePImCggLU1tb6LTtnzhyUlJTg7bffxpw5cwI+d8+ePfHNN99gxYoVSE1NxTPPPIPs7GxUV1e3qc49evQIWGbWrFmoqqrCN998gy+//BInTpzAzJkzAUAJ9t58801UVlYqP3v37sVXX32leh6z2az8W5IkAIDL5WpT/YmIKPwYBBERUatkZmZi06ZNOHXqlG4gVFBQAJvNBrvdjvz8/KCe22QyIS8vD4sWLcLu3btx9OhRbNiwQbPsyJEjsW3bNtVj3kFJsAYOHIhJkyZh+fLlWL58OaZNm4Z+/foBAFJSUtH2UsgAAAGpSURBVJCWlobDhw9jyJAhqp+srKyQXo+IiCKLa4KIiKjV0tPTUVFRgcmTJyM/Px/l5eWwWq2qMkajEfv371f+Hcinn36Kw4cPY+LEiUhOTsbq1avhcrkwfPhwzfL33XcfrrzySrz88suYPn06Pv/8c5/1QK1RVFSE4uJi2Gw2/PWvf1Ude+6553DfffchMTERBQUFaGpqwvbt23Hu3Dk8+OCDIb8mERFFBkeCiIgoJAMHDkRFRQXOnDmD/Px81NTU+JSxWq0+wZE/SUlJKCsrw5QpUzBy5Ej8/e9/x4oVKzBq1CjN8uPHj8ebb76JV199FdnZ2Vi7di2eeuqpkN/PLbfcgrNnz6K+vt5nU9jf/va3WLp0KZYtW4ZLLrkEkyZNQklJCUeCiIi6KEkIISJdCSIiIiIioo7CkSAiIiIiIooqDIKIiIiIiCiqMAgiIiIiIqKowiCIiIiIiIiiCoMgIiIiIiKKKgyCiIiIiIgoqjAIIiIiIiKiqMIgiIiIiIiIogqDICIiIiIiiioMgoiIiIiIKKowCCIiIiIioqjCIIiIiIiIiKLK/wf9xgKp1Vdx8AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,5))\n",
    "after2000 = pd.DataFrame()\n",
    "after2000 = ndf.loc[ndf['Year']>=2000]\n",
    "sns.scatterplot(x = \"KM's driven\", y = 'Price',data=after2000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3+K1YX7Hu18a4XC4dP378jHOaPHmyQkJC7FdkZGRVnCoAAABqAY8H8OWXX66cnBxt3bpVDzzwgAYPHqzPP//co3NKSUlRUVGR/Tpw4IBH5wMAAICq4+PpCfj6+qp58+aSpA4dOmj79u2aOXOm+vfvr7KyMh05csTtKnBBQYHCw8MlSeHh4dq2bZvb/iqeEnH6mJ8/OaKgoEBOp1MBAQFnnJOfn5/8/Pyq5PwAAABQu3j8CvDPlZeXq7S0VB06dFCdOnWUmZlpr8vNzVVeXp5iY2MlSbGxsdq5c6cKCwvtMRkZGXI6nYqOjrbHnL6PijEV+wAAAIBZPHoFOCUlRT169FCTJk109OhRLV68WBs3btS6desUEhKiYcOGKTk5WfXq1ZPT6dRDDz2k2NhYde7cWZLUrVs3RUdH6+6771ZaWpry8/P1xBNPKCkpyb6CO2LECL3wwgsaN26c7rnnHm3YsEHLli3T6tWrPXnqAAAA8BCPBnBhYaEGDRqkQ4cOKSQkRO3atdO6det0yy23SJKmT58uLy8vJSYmqrS0VPHx8ZozZ469vbe3t1atWqUHHnhAsbGxCgwM1ODBgzVx4kR7TFRUlFavXq3Ro0dr5syZaty4sV555RXFx8fX+PkCAADA82rdc4BrI54DXD14DjAAwHT8W191/pDPAQYAAABqAgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjeDSAJ0+erKuuukrBwcFq2LCh+vTpo9zcXLcxJSUlSkpKUv369RUUFKTExEQVFBS4jcnLy1NCQoLq1q2rhg0bauzYsTp58qTbmI0bNyomJkZ+fn5q3ry50tPTq/v0AAAAUAt5NIA3bdqkpKQkffjhh8rIyNCJEyfUrVs3HTt2zB4zevRovfPOO3rzzTe1adMmHTx4UH379rXXnzp1SgkJCSorK9MHH3ygRYsWKT09XampqfaYffv2KSEhQV27dlVOTo5GjRqle++9V+vWravR8wUAAIDnOSzLsjw9iQrfffedGjZsqE2bNun6669XUVGRGjRooMWLF6tfv36SpD179qhVq1bKyspS586dtWbNGvXs2VMHDx5UWFiYJGnevHl67LHH9N1338nX11ePPfaYVq9erc8++8w+1oABA3TkyBGtXbv2N+flcrkUEhKioqIiOZ3O6jn5MyhJTquxY3mC/7Rxnp4CAAAexb/1Vedceq1W3QNcVFQkSapXr54kKTs7WydOnFBcXJw9pmXLlmrSpImysrIkSVlZWWrbtq0dv5IUHx8vl8ulXbt22WNO30fFmIp9/FxpaalcLpfbCwAAABeGWhPA5eXlGjVqlLp06aI2bdpIkvLz8+Xr66vQ0FC3sWFhYcrPz7fHnB6/Fesr1v3aGJfLpePHj1eay+TJkxUSEmK/IiMjq+QcAQAA4Hm1JoCTkpL02WefacmSJZ6eilJSUlRUVGS/Dhw44OkpAQAAoIr4eHoCkjRy5EitWrVKmzdvVuPGje3l4eHhKisr05EjR9yuAhcUFCg8PNwes23bNrf9VTwl4vQxP39yREFBgZxOpwICAirNx8/PT35+flVybgAAAKhdPHoF2LIsjRw5UitWrNCGDRsUFRXltr5Dhw6qU6eOMjMz7WW5ubnKy8tTbGysJCk2NlY7d+5UYWGhPSYjI0NOp1PR0dH2mNP3UTGmYh8AAAAwh0evACclJWnx4sV66623FBwcbN+zGxISooCAAIWEhGjYsGFKTk5WvXr15HQ69dBDDyk2NladO3eWJHXr1k3R0dG6++67lZaWpvz8fD3xxBNKSkqyr+KOGDFCL7zwgsaNG6d77rlHGzZs0LJly7R69WqPnTsAAAA8w6NXgOfOnauioiLdeOONatSokf1aunSpPWb69Onq2bOnEhMTdf311ys8PFzLly+313t7e2vVqlXy9vZWbGys7rrrLg0aNEgTJ060x0RFRWn16tXKyMhQ+/btNXXqVL3yyiuKj4+v0fMFAACA59Wq5wDXVjwHuHrwHGAAgOn4t77q/GGfAwwAAABUNwIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABG8WgAb968Wb169VJERIQcDodWrlzptt6yLKWmpqpRo0YKCAhQXFyc9u7d6zbm8OHDGjhwoJxOp0JDQzVs2DAVFxe7jfn000913XXXyd/fX5GRkUpLS6vuUwMAAEAt5dEAPnbsmNq3b6/Zs2efcX1aWppmzZqlefPmaevWrQoMDFR8fLxKSkrsMQMHDtSuXbuUkZGhVatWafPmzRo+fLi93uVyqVu3bmratKmys7P1/PPPa/z48XrppZeq/fwAAABQ+/h48uA9evRQjx49zrjOsizNmDFDTzzxhHr37i1JevXVVxUWFqaVK1dqwIAB2r17t9auXavt27erY8eOkqS///3vuvXWW/W3v/1NERERev3111VWVqYFCxbI19dXrVu3Vk5OjqZNm+YWygAAADBDrb0HeN++fcrPz1dcXJy9LCQkRJ06dVJWVpYkKSsrS6GhoXb8SlJcXJy8vLy0detWe8z1118vX19fe0x8fLxyc3P1ww8/1NDZAAAAoLbw6BXgX5Ofny9JCgsLc1seFhZmr8vPz1fDhg3d1vv4+KhevXpuY6Kioirto2LdRRddVOnYpaWlKi0ttd+7XK7feTYAAACoLWrtFWBPmjx5skJCQuxXZGSkp6cEAACAKlJrAzg8PFySVFBQ4La8oKDAXhceHq7CwkK39SdPntThw4fdxpxpH6cf4+dSUlJUVFRkvw4cOPD7TwgAAAC1Qq0N4KioKIWHhyszM9Ne5nK5tHXrVsXGxkqSYmNjdeTIEWVnZ9tjNmzYoPLycnXq1Mkes3nzZp04ccIek5GRocsvv/yMtz9Ikp+fn5xOp9sLAAAAFwaPBnBxcbFycnKUk5Mj6acPvuXk5CgvL08Oh0OjRo3S008/rbfffls7d+7UoEGDFBERoT59+kiSWrVqpe7du+u+++7Ttm3btGXLFo0cOVIDBgxQRESEJOnOO++Ur6+vhg0bpl27dmnp0qWaOXOmkpOTPXTWAAAA8CSPfgjuo48+UteuXe33FVE6ePBgpaena9y4cTp27JiGDx+uI0eO6Nprr9XatWvl7+9vb/P6669r5MiRuvnmm+Xl5aXExETNmjXLXh8SEqL169crKSlJHTp00MUXX6zU1FQegQYAAGAoh2VZlqcnUdu5XC6FhISoqKioRm+HKEm+sH9jnf+0cZ6eAgAAHsW/9VXnXHqt1t4DDAAAAFQHAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUowJ49uzZatasmfz9/dWpUydt27bN01MCAABADTMmgJcuXark5GQ99dRT2rFjh9q3b6/4+HgVFhZ6emoAAACoQcYE8LRp03Tfffdp6NChio6O1rx581S3bl0tWLDA01MDAABADfLx9ARqQllZmbKzs5WSkmIv8/LyUlxcnLKysiqNLy0tVWlpqf2+qKhIkuRyuap/sqcpKS2p0ePVtLIa/noCAFDb8G991anoNMuyfnOsEQH8v//9T6dOnVJYWJjb8rCwMO3Zs6fS+MmTJ2vChAmVlkdGRlbbHI005ylPzwAAAFQnD/xbf/ToUYWEhPzqGCMC+FylpKQoOTnZfl9eXq7Dhw+rfv36cjgcNTIHl8ulyMhIHThwQE6ns0aOCQAAUFVqumUsy9LRo0cVERHxm2ONCOCLL75Y3t7eKigocFteUFCg8PDwSuP9/Pzk5+fntiw0NLQ6p/iLnE4nAQwAAP6warJlfuvKbwUjPgTn6+urDh06KDMz015WXl6uzMxMxcbGenBmAAAAqGlGXAGWpOTkZA0ePFgdO3bU1VdfrRkzZujYsWMaOnSop6cGAACAGmRMAPfv31/fffedUlNTlZ+fryuuuEJr166t9MG42sLPz09PPfVUpVsxAAAA/ghqc8s4rLN5VgQAAABwgTDiHmAAAACgAgEMAAAAoxDAAAAAMAoBbLBmzZppxowZnp4GAADAOXE4HFq5cuV5b08A/4KsrCx5e3srISHhnLcdP368rrjiiqqf1HlKT08/4y/y2L59u4YPH17zEwIAALXCkCFD5HA4NGLEiErrkpKS5HA4NGTIkJqfWDUjgH/B/Pnz9dBDD2nz5s06ePCgp6dTLRo0aKC6det6ehoAAMCDIiMjtWTJEh0/ftxeVlJSosWLF6tJkyYenFn1IYDPoLi4WEuXLtUDDzyghIQEpaen2+vOdDV15cqVcjgc9voJEybok08+kcPhkMPhsLfPy8tT7969FRQUJKfTqdtvv93t1zNXXDlesGCBmjRpoqCgID344IM6deqU0tLSFB4eroYNG+qZZ55xO/60adPUtm1bBQYGKjIyUg8++KCKi4slSRs3btTQoUNVVFRkz2f8+PGSKt8CceTIEd1///0KCwuTv7+/2rRpo1WrVlXNFxUAANRKMTExioyM1PLly+1ly5cvV5MmTXTllVfay9auXatrr71WoaGhql+/vnr27KmvvvrKXr9//345HA4tX75cXbt2Vd26ddW+fXtlZWXZY870U/IZM2aoWbNm9vvt27frlltu0cUXX6yQkBDdcMMN2rFjR5WeMwF8BsuWLVPLli11+eWX66677tKCBQt0to9L7t+/vx599FG1bt1ahw4d0qFDh9S/f3+Vl5erd+/eOnz4sDZt2qSMjAx9/fXX6t+/v9v2X331ldasWaO1a9fqjTfe0Pz585WQkKBvv/1WmzZt0nPPPacnnnhCW7dutbfx8vLSrFmztGvXLi1atEgbNmzQuHHjJEnXXHONZsyYIafTac9nzJgxleZdXl6uHj16aMuWLXrttdf0+eefa8qUKfL29v4dX0kAAPBHcM8992jhwoX2+wULFlT6bbnHjh1TcnKyPvroI2VmZsrLy0u33XabysvL3cb93//9n8aMGaOcnBy1aNFCd9xxh06ePHnWczl69KgGDx6s999/Xx9++KEuu+wy3XrrrTp69OjvO8nTGPOb4M7F/Pnzddddd0mSunfvrqKiIm3atEk33njjb24bEBCgoKAg+fj4KDw83F6ekZGhnTt3at++fYqMjJQkvfrqq2rdurW2b9+uq666StJPIbpgwQIFBwcrOjpaXbt2VW5urv7973/Ly8tLl19+uZ577jm9++676tSpkyRp1KhR9nGaNWump59+WiNGjNCcOXPk6+urkJAQORwOt/n83H/+8x9t27ZNu3fvVosWLSRJl1566Tl93QAAwB/TXXfdpZSUFH3zzTeSpC1btmjJkiXauHGjPSYxMdFtmwULFqhBgwb6/PPP1aZNG3v5mDFj7M9QTZgwQa1bt9aXX36pli1bntVcbrrpJrf3L730kkJDQ7Vp0yb17NnzfE6vEq4A/0xubq62bdumO+64Q5Lk4+Oj/v37a/78+b9rv7t371ZkZKQdv5IUHR2t0NBQ7d69217WrFkzBQcH2+/DwsIUHR0tLy8vt2WFhYX2+//85z+6+eabdckllyg4OFh33323vv/+e/34449nPb+cnBw1btzYjl8AAGCOBg0a2Ld9Lly4UAkJCbr44ovdxuzdu1d33HGHLr30UjmdTvu2hby8PLdx7dq1s//cqFEjSXLrlt9SUFCg++67T5dddplCQkLkdDpVXFxc6Ti/B1eAf2b+/Pk6efKkIiIi7GWWZcnPz08vvPCCvLy8Kt0OceLEiSo7fp06ddzeOxyOMy6r+HHD/v371bNnTz3wwAN65plnVK9ePb3//vsaNmyYysrKzvpDbgEBAVVzAgAA4A/pnnvu0ciRIyVJs2fPrrS+V69eatq0qV5++WVFRESovLxcbdq0UVlZmdu407ul4jNSFd1yNh01ePBgff/995o5c6aaNm0qPz8/xcbGVjrO70EAn+bkyZN69dVXNXXqVHXr1s1tXZ8+ffTGG2+oadOmOnr0qI4dO6bAwEBJP109PZ2vr69OnTrltqxVq1Y6cOCADhw4YF8F/vzzz3XkyBFFR0ef95yzs7NVXl6uqVOn2leJly1b9pvz+bl27drp22+/1RdffMFVYAAADNS9e3eVlZXJ4XAoPj7ebd3333+v3Nxcvfzyy7ruuuskSe+///45H6NBgwbKz8+XZVl2HP+8o7Zs2aI5c+bo1ltvlSQdOHBA//vf/87jjH4ZAXyaVatW6YcfftCwYcMUEhLiti4xMVHz58/XunXrVLduXf31r3/Vww8/rK1bt7o9JUL66TaGffv22bcVBAcHKy4uTm3bttXAgQM1Y8YMnTx5Ug8++KBuuOEGdezY8bzn3Lx5c504cUJ///vf1atXL23ZskXz5s2rNJ/i4mJlZmaqffv2qlu3bqUrwzfccIOuv/56JSYmatq0aWrevLn27Nkjh8Oh7t27n/f8AADAH4O3t7d9W+bPPwR/0UUXqX79+nrppZfUqFEj5eXl6fHHHz/nY9x444367rvvlJaWpn79+mnt2rVas2aNnE6nPeayyy7TP/7xD3Xs2FEul0tjx46t8p9Ucw/waebPn6+4uLhK8Sv9FMAfffSRvv32W7322mv697//rbZt2+qNN96wHyt2+tju3bura9euatCggd544w05HA699dZbuuiii3T99dcrLi5Ol156qZYuXfq75ty+fXtNmzZNzz33nNq0aaPXX39dkydPdhtzzTXXaMSIEerfv78aNGigtLS0M+7rX//6l6666irdcccdio6O1rhx437zyjEAALhwOJ1Otxit4OXlpSVLlig7O1tt2rTR6NGj9fzzz5/z/lu1aqU5c+Zo9uzZat++vbZt21bp6VTz58/XDz/8oJiYGN199916+OGH1bBhw/M+pzNxWGf7fC8AAADgAsAVYAAAABiFAAYAAIBRCGAAAAAYhQAGAACAUQhgAAAAGIUABgAAgFEIYAAAABiFAAaAP7Dx48friiuu+N37SU9PV2ho6O/eT23SrFkzzZgxw9PTAFALEcAAjONwOH719fPf7libjRkzRpmZmb97P/3799cXX3xRBTMCgNrPx9MTAICadujQIfvPS5cuVWpqqnJzc+1lQUFB9p8ty9KpU6fk41M7/7oMCgpym+/5CggIUEBAQBXMCABqP64AAzBOeHi4/QoJCZHD4bDf79mzR8HBwVqzZo06dOggPz8/vf/++/rqq6/Uu3dvhYWFKSgoSFdddZX+85//uO23WbNmevbZZ3XPPfcoODhYTZo00UsvvWSvLysr08iRI9WoUSP5+/uradOmmjx5sr3e4XDoxRdfVM+ePVW3bl21atVKWVlZ+vLLL3XjjTcqMDBQ11xzjb766it7m5/fArFx40ZdffXVCgwMVGhoqLp06aJvvvlGkvTJJ5+oa9euCg4OltPpVIcOHfTRRx9JOvMtEHPnztWf/vQn+fr66vLLL9c//vEPt/UOh0OvvPKKbrvtNtWtW1eXXXaZ3n777V/92jdr1kxPP/20Bg0apKCgIDVt2lRvv/22vvvuO/Xu3VtBQUFq166dPa8K//rXv9S6dWv5+fmpWbNmmjp1qtv6wsJC9erVSwEBAYqKitLrr79e6dhHjhzRvffeqwYNGsjpdOqmm27SJ5988qvzBXBhIoAB4Awef/xxTZkyRbt371a7du1UXFysW2+9VZmZmfr444/VvXt39erVS3l5eW7bTZ06VR07dtTHH3+sBx98UA888IB9dXnWrFl6++23tWzZMuXm5ur1119Xs2bN3LafNGmSBg0apJycHLVs2VJ33nmn7r//fqWkpOijjz6SZVkaOXLkGed88uRJ9enTRzfccIM+/fRTZWVlafjw4XI4HJKkgQMHqnHjxtq+fbuys7P1+OOPq06dOmfc14oVK/TII4/o0Ucf1Weffab7779fQ4cO1bvvvus2bsKECbr99tv16aef6tZbb9XAgQN1+PDhX/3aTp8+XV26dNHHH3+shIQE3X333Ro0aJDuuusu7dixQ3/60580aNAgWZYlScrOztbtt9+uAQMGaOfOnRo/fryefPJJpaen2/scMmSIDhw4oHfffVf//Oc/NWfOHBUWFrod9y9/+YsKCwu1Zs0aZWdnKyYmRjfffPNvzhfABcgCAIMtXLjQCgkJsd+/++67liRr5cqVv7lt69atrb///e/2+6ZNm1p33XWX/b68vNxq2LChNXfuXMuyLOuhhx6ybrrpJqu8vPyM+5NkPfHEE/b7rKwsS5I1f/58e9kbb7xh+fv72++feuopq3379pZlWdb3339vSbI2btx4xv0HBwdb6enpZ1z386/DNddcY913331uY/7yl79Yt9566y/Ot7i42JJkrVmz5ozHsKzKX6NDhw5Zkqwnn3yy0nkfOnTIsizLuvPOO61bbrnFbT9jx461oqOjLcuyrNzcXEuStW3bNnv97t27LUnW9OnTLcuyrPfee89yOp1WSUmJ237+9Kc/WS+++OIvzhfAhYkrwABwBh07dnR7X1xcrDFjxqhVq1YKDQ1VUFCQdu/eXekKcLt27ew/V9xaUXElcsiQIcrJydHll1+uhx9+WOvXr6903NO3DwsLkyS1bdvWbVlJSYlcLlelbevVq6chQ4YoPj5evXr10syZM93ud05OTta9996ruLg4TZkyxe1Wip/bvXu3unTp4rasS5cu2r179y/ONzAwUE6ns9KV1/M5R0n2fn5pLnv37tWpU6e0e/du+fj4qEOHDvb6li1but3S8cknn6i4uFj169e375sOCgrSvn37fvXrAODCRAADwBkEBga6vR8zZoxWrFihZ599Vu+9955ycnLUtm1blZWVuY37+S0FDodD5eXlkqSYmBjt27dPkyZN0vHjx3X77berX79+v7h9xa0LZ1pWsc+fW7hwobKysnTNNddo6dKlatGihT788ENJP90vvGvXLiUkJGjDhg2Kjo7WihUrzvprcia/dr5ns835nOP5KC4uVqNGjZSTk+P2ys3N1dixY6vsOAD+GAhgADgLW7Zs0ZAhQ3Tbbbepbdu2Cg8P1/79+895P06nU/3799fLL7+spUuX6l//+leV34N65ZVXKiUlRR988IHatGmjxYsX2+tatGih0aNHa/369erbt68WLlx4xn20atVKW7ZscVu2ZcsWRUdHV+lcz8YvzaVFixby9vZWy5YtdfLkSWVnZ9vrc3NzdeTIEft9TEyM8vPz5ePjo+bNm7u9Lr744po6FQC1RO18rg8A1DKXXXaZli9frl69esnhcOjJJ5885yuU06ZNU6NGjXTllVfKy8tLb775psLDw6vsF1Ds27dPL730kv785z8rIiJCubm52rt3rwYNGqTjx49r7Nix6tevn6KiovTtt99q+/btSkxMPOO+xo4dq9tvv11XXnml4uLi9M4772j58uWVnnxREx599FFdddVVmjRpkvr376+srCy98MILmjNnjiTp8ssvV/fu3XX//fdr7ty58vHx0ahRo9we6xYXF6fY2Fj16dNHaWlpatGihQ4ePKjVq1frtttuq3TLC4ALG1eAAeAsTJs2TRdddJGuueYa9erVS/Hx8YqJiTmnfQQHBystLU0dO3bUVVddpf379+vf//63vLyq5q/iunXras+ePUpMTFSLFi00fPhwJSUl6f7775e3t7e+//57DRo0SC1atNDtt9+uHj16aMKECWfcV58+fTRz5kz97W9/U+vWrfXiiy9q4cKFuvHGG6tkruciJiZGy5Yt05IlS9SmTRulpqZq4sSJGjJkiD1m4cKFioiI0A033KC+fftq+PDhatiwob3e4XDo3//+t66//noNHTpULVq00IABA/TNN9/Y9xwDMIfDsv6/58wAAAAABuAKMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKD6ensAfQXl5uQ4ePKjg4GA5HA5PTwcAAAA/Y1mWjh49qoiICHl5/fo1XgL4LBw8eFCRkZGengYAAAB+w4EDB9S4ceNfHUMAn4Xg4GBJP31BnU6nh2cDAACAn3O5XIqMjLS77dcQwGeh4rYHp9NJAAMAANRiZ3O7Kh+CAwAAgFEIYAAAABiFAAYAAIBRCGAAAAAYhQAGAACAUQhgAAAAGIUABgAAgFEIYAAAABiFAAYAAIBRCGAAAAAYhQAGAACAUQhgAAAAGIUABgAAgFF8PD0B/LKS5DRPT6Fa+U8b5+kpAAAAA3EFGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUjwbwqVOn9OSTTyoqKkoBAQH605/+pEmTJsmyLHuMZVlKTU1Vo0aNFBAQoLi4OO3du9dtP4cPH9bAgQPldDoVGhqqYcOGqbi42G3Mp59+quuuu07+/v6KjIxUWlpajZwjAAAAahePBvBzzz2nuXPn6oUXXtDu3bv13HPPKS0tTX//+9/tMWlpaZo1a5bmzZunrVu3KjAwUPHx8SopKbHHDBw4ULt27VJGRoZWrVqlzZs3a/jw4fZ6l8ulbt26qWnTpsrOztbzzz+v8ePH66WXXqrR8wUAAIDnOazTL7fWsJ49eyosLEzz58+3lyUmJiogIECvvfaaLMtSRESEHn30UY0ZM0aSVFRUpLCwMKWnp2vAgAHavXu3oqOjtX37dnXs2FGStHbtWt1666369ttvFRERoblz5+r//u//lJ+fL19fX0nS448/rpUrV2rPnj2/OU+Xy6WQkBAVFRXJ6XRWw1fizEqSL+yr1P7Txnl6CgAA4AJxLr3m0SvA11xzjTIzM/XFF19Ikj755BO9//776tGjhyRp3759ys/PV1xcnL1NSEiIOnXqpKysLElSVlaWQkND7fiVpLi4OHl5eWnr1q32mOuvv96OX0mKj49Xbm6ufvjhh0rzKi0tlcvlcnsBAADgwuDjyYM//vjjcrlcatmypby9vXXq1Ck988wzGjhwoCQpPz9fkhQWFua2XVhYmL0uPz9fDRs2dFvv4+OjevXquY2JioqqtI+KdRdddJHbusmTJ2vChAlVdJYAAACoTTx6BXjZsmV6/fXXtXjxYu3YsUOLFi3S3/72Ny1atMiT01JKSoqKiors14EDBzw6HwAAAFQdj14BHjt2rB5//HENGDBAktS2bVt98803mjx5sgYPHqzw8HBJUkFBgRo1amRvV1BQoCuuuEKSFB4ersLCQrf9njx5UocPH7a3Dw8PV0FBgduYivcVY07n5+cnPz+/qjlJAAAA1CoevQL8448/ysvLfQre3t4qLy+XJEVFRSk8PFyZmZn2epfLpa1btyo2NlaSFBsbqyNHjig7O9ses2HDBpWXl6tTp072mM2bN+vEiRP2mIyMDF1++eWVbn8AAADAhc2jAdyrVy8988wzWr16tfbv368VK1Zo2rRpuu222yRJDodDo0aN0tNPP623335bO3fu1KBBgxQREaE+ffpIklq1aqXu3bvrvvvu07Zt27RlyxaNHDlSAwYMUEREhCTpzjvvlK+vr4YNG6Zdu3Zp6dKlmjlzppKTkz116gAAAPAQj94C8fe//11PPvmkHnzwQRUWFioiIkL333+/UlNT7THjxo3TsWPHNHz4cB05ckTXXnut1q5dK39/f3vM66+/rpEjR+rmm2+Wl5eXEhMTNWvWLHt9SEiI1q9fr6SkJHXo0EEXX3yxUlNT3Z4VDAAAADN49DnAfxQ8B7h68BxgAABQVf4wzwEGAAAAahoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADCKxwP4v//9r+666y7Vr19fAQEBatu2rT766CN7vWVZSk1NVaNGjRQQEKC4uDjt3bvXbR+HDx/WwIED5XQ6FRoaqmHDhqm4uNhtzKeffqrrrrtO/v7+ioyMVFpaWo2cHwAAAGoXjwbwDz/8oC5duqhOnTpas2aNPv/8c02dOlUXXXSRPSYtLU2zZs3SvHnztHXrVgUGBio+Pl4lJSX2mIEDB2rXrl3KyMjQqlWrtHnzZg0fPtxe73K51K1bNzVt2lTZ2dl6/vnnNX78eL300ks1er4AAADwPIdlWZanDv74449ry5Yteu+998643rIsRURE6NFHH9WYMWMkSUVFRQoLC1N6eroGDBig3bt3Kzo6Wtu3b1fHjh0lSWvXrtWtt96qb7/9VhEREZo7d67+7//+T/n5+fL19bWPvXLlSu3Zs+c35+lyuRQSEqKioiI5nc4qOvvfVpJ8YV+l9p82ztNTAAAAF4hz6TWPXgF+++231bFjR/3lL39Rw4YNdeWVV+rll1+21+/bt0/5+fmKi4uzl4WEhKhTp07KysqSJGVlZSk0NNSOX0mKi4uTl5eXtm7dao+5/vrr7fiVpPj4eOXm5uqHH36oNK/S0lK5XC63FwAAAC4MHg3gr7/+WnPnztVll12mdevW6YEHHtDDDz+sRYsWSZLy8/MlSWFhYW7bhYWF2evy8/PVsGFDt/U+Pj6qV6+e25gz7eP0Y5xu8uTJCgkJsV+RkZFVcLYAAACoDTwawOXl5YqJidGzzz6rK6+8UsOHD9d9992nefPmeXJaSklJUVFRkf06cOCAR+cDAACAquPRAG7UqJGio6PdlrVq1Up5eXmSpPDwcElSQUGB25iCggJ7XXh4uAoLC93Wnzx5UocPH3Ybc6Z9nH6M0/n5+cnpdLq9AAAAcGHwaAB36dJFubm5bsu++OILNW3aVJIUFRWl8PBwZWZm2utdLpe2bt2q2NhYSVJsbKyOHDmi7Oxse8yGDRtUXl6uTp062WM2b96sEydO2GMyMjJ0+eWXuz1xAgAAABc+jwbw6NGj9eGHH+rZZ5/Vl19+qcWLF+ull15SUlKSJMnhcGjUqFF6+umn9fbbb2vnzp0aNGiQIiIi1KdPH0k/XTHu3r277rvvPm3btk1btmzRyJEjNWDAAEVEREiS7rzzTvn6+mrYsGHatWuXli5dqpkzZyo5OdlTpw4AAAAP8fHkwa+66iqtWLFCKSkpmjhxoqKiojRjxgwNHDjQHjNu3DgdO3ZMw4cP15EjR3Tttddq7dq18vf3t8e8/vrrGjlypG6++WZ5eXkpMTFRs2bNsteHhIRo/fr1SkpKUocOHXTxxRcrNTXV7VnBAAAAMINHnwP8R8FzgKsHzwEGAABV5Q/zHGAAAACgphHAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjEMAAAAAwCgEMAAAAoxDAAAAAMAoBDAAAAKMQwAAAADAKAQwAAACjnFcAf/3111U9DwAAAKBGnFcAN2/eXF27dtVrr72mkpKSqp4TAAAAUG3OK4B37Nihdu3aKTk5WeHh4br//vu1bdu2qp4bAAAAUOXOK4CvuOIKzZw5UwcPHtSCBQt06NAhXXvttWrTpo2mTZum7777rqrnCQAAAFSJ3/UhOB8fH/Xt21dvvvmmnnvuOX355ZcaM2aMIiMjNWjQIB06dKiq5gkAAABUid8VwB999JEefPBBNWrUSNOmTdOYMWP01VdfKSMjQwcPHlTv3r2rap4AAABAlfA5n42mTZumhQsXKjc3V7feeqteffVV3XrrrfLy+qmno6KilJ6ermbNmlXlXAEAAIDf7bwCeO7cubrnnns0ZMgQNWrU6IxjGjZsqPnz5/+uyQEAAABV7bwCOCMjQ02aNLGv+FawLEsHDhxQkyZN5Ovrq8GDB1fJJAEAAICqcl73AP/pT3/S//73v0rLDx8+rKioqN89KQAAAKC6nFcAW5Z1xuXFxcXy9/f/XRMCAAAAqtM53QKRnJwsSXI4HEpNTVXdunXtdadOndLWrVt1xRVXVOkEAQAAgKp0TgH88ccfS/rpCvDOnTvl6+trr/P19VX79u01ZsyYqp0hAAAAUIXOKYDfffddSdLQoUM1c+ZMOZ3OapkUAAAAUF3O6ykQCxcurOp5AAAAADXirAO4b9++Sk9Pl9PpVN++fX917PLly3/3xAAAAIDqcNYBHBISIofDYf8ZAAAA+CM66wA+/bYHboEAAADAH9V5PQf4+PHj+vHHH+3333zzjWbMmKH169dX2cQAAACA6nBeAdy7d2+9+uqrkqQjR47o6quv1tSpU9W7d2/NnTu3SicIAAAAVKXzCuAdO3bouuuukyT985//VHh4uL755hu9+uqrmjVrVpVOEAAAAKhK5xXAP/74o4KDgyVJ69evV9++feXl5aXOnTvrm2++qdIJAgAAAFXpvAK4efPmWrlypQ4cOKB169apW7dukqTCwkJ+OQYAAABqtfMK4NTUVI0ZM0bNmjVTp06dFBsbK+mnq8FXXnlllU4QAAAAqErn9Zvg+vXrp2uvvVaHDh1S+/bt7eU333yzbrvttiqbHAAAAFDVziuAJSk8PFzh4eFuy66++urfPSEAAACgOp1XAB87dkxTpkxRZmamCgsLVV5e7rb+66+/rpLJAQAAAFXtvAL43nvv1aZNm3T33XerUaNG9q9IBgAAAGq78wrgNWvWaPXq1erSpUtVzwcAAACoVuf1FIiLLrpI9erVq+q5AAAAANXuvAJ40qRJSk1N1Y8//ljV8wEAAACq1XndAjF16lR99dVXCgsLU7NmzVSnTh239Tt27KiSyQEAAABV7bwCuE+fPlU8DQAAAKBmnFcAP/XUU1U9DwAAAKBGnNc9wJJ05MgRvfLKK0pJSdHhw4cl/XTrw3//+98qmxwAAABQ1c7rCvCnn36quLg4hYSEaP/+/brvvvtUr149LV++XHl5eXr11Verep4AAABAlTivK8DJyckaMmSI9u7dK39/f3v5rbfeqs2bN1fZ5AAAAICqdl4BvH37dt1///2Vll9yySXKz8//3ZMCAAAAqst5BbCfn59cLlel5V988YUaNGjwuycFAAAAVJfzCuA///nPmjhxok6cOCFJcjgcysvL02OPPabExMQqnSAAAABQlc4rgKdOnari4mI1aNBAx48f1w033KDmzZsrODhYzzzzTFXPEQAAAKgy5/UUiJCQEGVkZGjLli365JNPVFxcrJiYGMXFxVX1/AAAAIAqdc4BXF5ervT0dC1fvlz79++Xw+FQVFSUwsPDZVmWHA5HdcwTAAAAqBLndAuEZVn685//rHvvvVf//e9/1bZtW7Vu3VrffPONhgwZottuu6265gkAAABUiXO6Apyenq7NmzcrMzNTXbt2dVu3YcMG9enTR6+++qoGDRpUpZMEAAAAqso5XQF+44039Ne//rVS/ErSTTfdpMcff1yvv/56lU0OAAAAqGrnFMCffvqpunfv/ovre/TooU8++eS8JjJlyhQ5HA6NGjXKXlZSUqKkpCTVr19fQUFBSkxMVEFBgdt2eXl5SkhIUN26ddWwYUONHTtWJ0+edBuzceNGxcTEyM/PT82bN1d6evp5zREAAAB/fOcUwIcPH1ZYWNgvrg8LC9MPP/xwzpPYvn27XnzxRbVr185t+ejRo/XOO+/ozTff1KZNm3Tw4EH17dvXXn/q1CklJCSorKxMH3zwgRYtWqT09HSlpqbaY/bt26eEhAR17dpVOTk5GjVqlO69916tW7funOcJAACAP75zCuBTp07Jx+eXbxv29vaudPX1txQXF2vgwIF6+eWXddFFF9nLi4qKNH/+fE2bNk033XSTOnTooIULF+qDDz7Qhx9+KElav369Pv/8c7322mu64oor1KNHD02aNEmzZ89WWVmZJGnevHmKiorS1KlT1apVK40cOVL9+vXT9OnTz2meAAAAuDCc04fgLMvSkCFD5Ofnd8b1paWl5zyBpKQkJSQkKC4uTk8//bS9PDs7WydOnHB7tnDLli3VpEkTZWVlqXPnzsrKylLbtm3drkrHx8frgQce0K5du3TllVcqKyur0vOJ4+Pj3W61ONN5nH4uZ/q1zwAAAPhjOqcAHjx48G+OOZcnQCxZskQ7duzQ9u3bK63Lz8+Xr6+vQkND3ZaHhYUpPz/fHvPzWzIq3v/WGJfLpePHjysgIKDSsSdPnqwJEyac9XkAAADgj+OcAnjhwoVVduADBw7okUceUUZGhvz9/atsv1UhJSVFycnJ9nuXy6XIyEgPzggAAABV5ZzuAa5K2dnZKiwsVExMjHx8fOTj46NNmzZp1qxZ8vHxUVhYmMrKynTkyBG37QoKChQeHi5JCg8Pr/RUiIr3vzXG6XSe8eqvJPn5+cnpdLq9AAAAcGHwWADffPPN2rlzp3JycuxXx44dNXDgQPvPderUUWZmpr1Nbm6u8vLyFBsbK0mKjY3Vzp07VVhYaI/JyMiQ0+lUdHS0Peb0fVSMqdgHAAAAzHJOt0BUpeDgYLVp08ZtWWBgoOrXr28vHzZsmJKTk1WvXj05nU499NBDio2NVefOnSVJ3bp1U3R0tO6++26lpaUpPz9fTzzxhJKSkuwP6o0YMUIvvPCCxo0bp3vuuUcbNmzQsmXLtHr16po9YQAAANQKHgvgszF9+nR5eXkpMTFRpaWlio+P15w5c+z13t7eWrVqlR544AHFxsYqMDBQgwcP1sSJE+0xUVFRWr16tUaPHq2ZM2eqcePGeuWVVxQfH++JUwIAAICHOSzLsjw9idrO5XIpJCRERUVFNXo/cElyWo0dyxP8p43z9BQAAMAF4lx6zWP3AAMAAACeQAADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjEIAAwAAwCgEMAAAAIxCAAMAAMAoBDAAAACMQgADAADAKAQwAAAAjOLRAJ48ebKuuuoqBQcHq2HDhurTp49yc3PdxpSUlCgpKUn169dXUFCQEhMTVVBQ4DYmLy9PCQkJqlu3rho2bKixY8fq5MmTbmM2btyomJgY+fn5qXnz5kpPT6/u0wMAAEAt5NEA3rRpk5KSkvThhx8qIyNDJ06cULdu3XTs2DF7zOjRo/XOO+/ozTff1KZNm3Tw4EH17dvXXn/q1CklJCSorKxMH3zwgRYtWqT09HSlpqbaY/bt26eEhAR17dpVOTk5GjVqlO69916tW7euRs8XAAAAnuewLMvy9CQqfPfdd2rYsKE2bdqk66+/XkVFRWrQoIEWL16sfv36SZL27NmjVq1aKSsrS507d9aaNWvUs2dPHTx4UGFhYZKkefPm6bHHHtN3330nX19fPfbYY1q9erU+++wz+1gDBgzQkSNHtHbt2t+cl8vlUkhIiIqKiuR0Oqvn5M+gJDmtxo7lCf7Txnl6CgAA4AJxLr1Wq+4BLioqkiTVq1dPkpSdna0TJ04oLi7OHtOyZUs1adJEWVlZkqSsrCy1bdvWjl9Jio+Pl8vl0q5du+wxp++jYkzFPgAAAGAOH09PoEJ5eblGjRqlLl26qE2bNpKk/Px8+fr6KjQ01G1sWFiY8vPz7TGnx2/F+op1vzbG5XLp+PHjCggIcFtXWlqq0tJS+73L5fr9JwgAAIBaodZcAU5KStJnn32mJUuWeHoqmjx5skJCQuxXZGSkp6cEAACAKlIrAnjkyJFatWqV3n33XTVu3NheHh4errKyMh05csRtfEFBgcLDw+0xP38qRMX73xrjdDorXf2VpJSUFBUVFdmvAwcO/O5zBAAAQO3g0QC2LEsjR47UihUrtGHDBkVFRbmt79Chg+rUqaPMzEx7WW5urvLy8hQbGytJio2N1c6dO1VYWGiPycjIkNPpVHR0tD3m9H1UjKnYx8/5+fnJ6XS6vQAAAHBh8Og9wElJSVq8eLHeeustBQcH2/fshoSEKCAgQCEhIRo2bJiSk5NVr149OZ1OPfTQQ4qNjVXnzp0lSd26dVN0dLTuvvtupaWlKT8/X0888YSSkpLk5+cnSRoxYoReeOEFjRs3Tvfcc482bNigZcuWafXq1R47dwAAAHiGR68Az507V0VFRbrxxhvVqFEj+7V06VJ7zPTp09WzZ08lJibq+uuvV3h4uJYvX26v9/b21qpVq+Tt7a3Y2FjdddddGjRokCZOnGiPiYqK0urVq5WRkaH27dtr6tSpeuWVVxQfH1+j5wsAAADPq1XPAa6teA5w9eA5wAAAoKr8YZ8DDAAAAFQ3AhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAAAARiGAAQAAYBQCGAAAAEYhgAEAAGAUH09PAMAfV0lymqenUK38p43z9BQAANWAK8AAAAAwCgEMAAAAoxgVwLNnz1azZs3k7++vTp06adu2bZ6eEgAAAGqYMQG8dOlSJScn66mnntKOHTvUvn17xcfHq7Cw0NNTAwAAQA0yJoCnTZum++67T0OHDlV0dLTmzZununXrasGCBZ6eGgAAAGqQEU+BKCsrU3Z2tlJSUuxlXl5eiouLU1ZWVqXxpaWlKi0ttd8XFRVJklwuV/VP9jQlpSU1eryaVlbDX09UPb5HAQC1RUWnWZb1m2ONCOD//e9/OnXqlMLCwtyWh4WFac+ePZXGT548WRMmTKi0PDIystrmaKQ5T3l6BsCv43sUAP5wjh49qpCQkF8dY0QAn6uUlBQlJyfb78vLy3X48GHVr19fDoejRubgcrkUGRmpAwcOyOl01sgxAU/gex0m4fsdJqnp73fLsnT06FFFRET85lgjAvjiiy+Wt7e3CgoK3JYXFBQoPDy80ng/Pz/5+fm5LQsNDa3OKf4ip9PJX5IwAt/rMAnf7zBJTX6//9aV3wpGfAjO19dXHTp0UGZmpr2svLxcmZmZio2N9eDMAAAAUNOMuAIsScnJyRo8eLA6duyoq6++WjNmzNCxY8c0dOhQT08NAAAANciYAO7fv7++++47paamKj8/X1dccYXWrl1b6YNxtYWfn5+eeuqpSrdiABcavtdhEr7fYZLa/P3usM7mWREAAADABcKIe4ABAACACgQwAAAAjEIAAwAAwCgE8AWsWbNmmjFjhqenAQBG279/vxwOh3Jycs552/Hjx+uKK6741TFDhgxRnz59zmtuwPlyOBxauXLlH/Z4BHAVGzJkiBwOhxwOh3x9fdW8eXNNnDhRJ0+e/M1t09PTPfYLN4CqlJ+fr4ceekiXXnqp/Pz8FBkZqV69etnP4m7WrJkcDoc+/PBDt+1GjRqlG2+80W2Zy+XSk08+qdatWysgIED169fXVVddpbS0NP3www81dUow1C/F5caNG+VwOHTkyJFqPf6YMWPcnmEPVLfTO6ZOnToKCwvTLbfcogULFqi8vNwed+jQIfXo0cODM/19COBq0L17dx06dEh79+7Vo48+qvHjx+v555+vsv2XlZVV2b6AqrZ//3516NBBGzZs0PPPP6+dO3dq7dq16tq1q5KSkuxx/v7+euyxx351X4cPH1bnzp21cOFCjRkzRlu3btWOHTv0zDPP6OOPP9bixYur+3QAj7AsSydPnlRQUJDq16/v6enAMBUds3//fq1Zs0Zdu3bVI488op49e9oX9MLDw2vl483OFgFcDfz8/BQeHq6mTZvqgQceUFxcnN5++22VlpZqzJgxuuSSSxQYGKhOnTpp48aNkn66mjB06FAVFRXZ/+c1fvx4ST9dLZs0aZIGDRokp9Op4cOHS5L+9a9/qXXr1vLz81OzZs00depUD50x8P978MEH5XA4tG3bNiUmJqpFixZq3bq1kpOT3a74Dh8+XB9++KH+/e9//+K+/vrXvyovL0/btm3T0KFD1a5dOzVt2lTdunXTG2+8oQcffLAmTgn4RceOHZPT6dQ///lPt+UrV65UYGCgjh49ai/bs2ePrrnmGvn7+6tNmzbatGmTva7iivKaNWvUoUMH+fn56f333690C8SpU6eUnJys0NBQ1a9fX+PGjRNPM0VVq+iYSy65RDExMfrrX/+qt956S2vWrFF6erqkyrckHDhwQLfffrtCQ0NVr1499e7dW/v377fXb9y4UVdffbUCAwMVGhqqLl266JtvvrHXv/XWW4qJiZG/v78uvfRSTZgw4ax+en6+COAaEBAQoLKyMo0cOVJZWVlasmSJPv30U/3lL39R9+7dtXfvXl1zzTWaMWOGnE6nDh06pEOHDmnMmDH2Pv72t7+pffv2+vjjj/Xkk08qOztbt99+uwYMGKCdO3dq/PjxevLJJ+1vTMATDh8+rLVr1yopKUmBgYGV1p9+i09UVJRGjBihlJQUtx+rVSgvL9fSpUt11113KSIi4ozHczgcVTZ34HwEBgZqwIABWrhwodvyhQsXql+/fgoODraXjR07Vo8++qg+/vhjxcbGqlevXvr+++/dtnv88cc1ZcoU7d69W+3atat0vKlTpyo9PV0LFizQ+++/r8OHD2vFihXVc3LAaW666Sa1b99ey5cvr7TuxIkTio+PV3BwsN577z1t2bJFQUFB6t69u8rKynTy5En16dNHN9xwgz799FNlZWVp+PDh9t/h7733ngYNGqRHHnlEn3/+uV588UWlp6frmWeeqb4TslClBg8ebPXu3duyLMsqLy+3MjIyLD8/P2vIkCGWt7e39d///tdt/M0332ylpKRYlmVZCxcutEJCQirts2nTplafPn3clt15553WLbfc4rZs7NixVnR0tNt206dP//0nBZylrVu3WpKs5cuX/+q4iu/NwsJCKzg42Hr11Vcty7KsRx55xLrhhhssy7Ks/Px8S5I1bdo0t21jYmKswMBAKzAw0BowYEC1nAdQYfDgwZa3t7f9PVfx8vf3tyRZP/zwg7V161bL29vbOnjwoGVZllVQUGD5+PhYGzdutCzLsvbt22dJsqZMmWLv98SJE1bjxo2t5557zrIsy3r33XctSdbKlSvdjv/UU09Z7du3t983atTISktLq7Sfin93gN/r9I75uf79+1utWrWyLMuyJFkrVqywLMuy/vGPf1iXX365VV5ebo8tLS21AgICrHXr1lnff/+9Jcn+b+Lnbr75ZuvZZ591W/aPf/zDatSokf3+9ONVBa4AV4NVq1YpKChI/v7+6tGjh/r3769+/frp1KlTatGihYKCguzXpk2b9NVXX/3mPjt27Oj2fvfu3erSpYvbsi5dumjv3r06depUlZ4PcLasc/xRbIMGDTRmzBilpqae9b3tK1asUE5OjuLj43X8+PHzmSZwTrp27aqcnBy31yuvvGKvv/rqq9W6dWstWrRIkvTaa6+padOmuv766932Exsba//Zx8dHHTt21O7du93G/Pzv+tMVFRXp0KFD6tSpU6X9ADXBsqwz/uTtk08+0Zdffqng4GC7b+rVq6eSkhJ99dVXqlevnoYMGaL4+Hj16tVLM2fO1KFDh9y2nzhxolsf3XfffTp06JB+/PHHajkXn2rZq+G6du2quXPnytfXVxEREfLx8dHSpUvl7e2t7OxseXt7u40PCgr6zX2e6cfJQG1z2WWXyeFwaM+ePWe9TXJysubMmaM5c+a4LW/QoIFCQ0OVm5vrtrxJkyaSpODg4Gr/BD4g/fT3b/Pmzd2Wffvtt27v7733Xs2ePVuPP/64Fi5cqKFDh57XLTr8XY/abPfu3YqKiqq0vLi4WB06dNDrr79eaV2DBg0k/XRb0MMPP6y1a9dq6dKleuKJJ5SRkaHOnTuruLhYEyZMUN++fStt7+/vX/UnIu4BrhYVf1k2adJEPj4//T/GlVdeqVOnTqmwsFDNmzd3e4WHh0uSfH19z/rqbatWrbRlyxa3ZVu2bFGLFi0qBTZQU+rVq6f4+HjNnj1bx44dq7T+TMEaFBSkJ598Us8884zbB4a8vLx0++2367XXXtPBgwerc9rA73bXXXfpm2++0axZs/T5559r8ODBlcac/iHQkydPKjs7W61atTrrY4SEhKhRo0baunVrpf0A1W3Dhg3auXOnEhMTK62LiYnR3r171bBhw0qNExISYo+78sorlZKSog8++EBt2rSxn+QTExOj3NzcSts2b95cXl7Vk6oEcA1p0aKFBg4cqEGDBmn58uXat2+ftm3bpsmTJ2v16tWSfnraQ3FxsTIzM/W///3vVy/7P/roo8rMzNSkSZP0xRdfaNGiRXrhhRfcPjgHeMLs2bN16tQpXX311frXv/6lvXv3avfu3Zo1a5bbj4BPN3z4cIWEhFR6rNmzzz6rSy65RFdffbUWLFigTz/9VF999ZVWrFihrKws/mcPtcZFF12kvn37auzYserWrZsaN25caczs2bO1YsUK7dmzR0lJSfrhhx90zz33nNNxHnnkEU2ZMkUrV67Unj179OCDD/KTEFS50tJS5efn67///a927NihZ599Vr1791bPnj01aNCgSuMHDhyoiy++WL1799Z7772nffv2aePGjXr44Yf17bffat++fUpJSVFWVpa++eYbrV+/Xnv37rX/BzA1NVWvvvqqJkyYoF27dmn37t1asmSJnnjiiWo7RwK4Bi1cuFCDBg3So48+qssvv1x9+vTR9u3b7R/pXnPNNRoxYoT69++vBg0aKC0t7Rf3FRMTo2XLlmnJkiVq06aNUlNTNXHiRA0ZMqSGzgY4s0svvVQ7duxQ165d9eijj6pNmza65ZZblJmZqblz555xmzp16mjSpEkqKSlxW16/fn1t27ZNgwYN0vPPP6+rr75abdu21fjx49W/f3+9/PLLNXFKwFkZNmyYysrKfjFqp0yZoilTpqh9+/Z6//339fbbb+viiy8+p2M8+uijuvvuuzV48GDFxsYqODhYt912W1VMH7CtXbtWjRo1UrNmzdS9e3e9++67mjVrlt56660zXnioW7euNm/erCZNmqhv375q1aqVhg0bppKSEjmdTtWtW1d79uyxH405fPhwJSUl6f7775ckxcfHa9WqVVq/fr2uuuoqde7cWdOnT1fTpk2r7Rwd1rl+agUAAFTyj3/8Q6NHj9bBgwfl6+vr6ekA+BV8CA4AgN/hxx9/1KFDhzRlyhTdf//9xC/wB8AtEAAA/A5paWlq2bKlwsPDlZKS4unpADgL3AIBAAAAo3AFGAAAAEYhgAEAAGAUAhgAAABGIYABAABgFAIYAPCbNm7cKIfDwW8dA3BBIIAB4AIxZMgQORyOSq8vv/zS01MDgFqFX4QBABeQ7t27a+HChW7LGjRo4KHZAEDtxBVgALiA+Pn5KTw83O01bNgw9enTx23cqFGjdOONN9rvy8vLNXnyZEVFRSkgIEDt27fXP//5z5qdPADUEK4AAwA0efJkvfbaa5o3b54uu+wybd68WXfddZcaNGigG264wdPTA4AqRQADwAVk1apVCgoKst/36NFDgYGBv7pNaWmpnn32Wf3nP/9RbGysJOnSSy/V+++/rxdffJEABnDBIYAB4ALStWtXzZ07134fGBiolJSUX93myy+/1I8//qhbbrnFbXlZWZmuvPLKapknAHgSAQwAF5DAwEA1b97cbZmXl5csy3JbduLECfvPxcXFkqTVq1frkksucRvn5+dXTTMFAM8hgAHgAtegQQN99tlnbstycnJUp04dSVJ0dLT8/PyUl5fH7Q4AjEAAA8AF7qabbtLzzz+vV199VbGxsXrttdf02Wef2bc3BAcHa8yYMRo9erTKy8t17bXXqqioSFu2bJHT6dTgwYM9fAYAULUIYAC4wMXHx+vJJ5/UuHHjVFJSonvuuUeDBg3Szp077TGTJk1SgwYNNHnyZH399dcKDQ1VTEyM/vrXv3pw5gBQPRzWz28MAwAAAC5g/CIMAAAAGIUABgAAgFEIYAAAABiFAAYAAIBRCGAAAAAYhQAGAACAUQhgAAAAGIUABgAAgFEIYAAAABiFAAYAAIBRCGAAAAAYhQAGAACAUf4fNdolm4UMtjAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 10))\n",
    "ax1 = fig.add_subplot(2, 1, 1)\n",
    "ax2 = fig.add_subplot(2, 1, 2)\n",
    "ax1.hist(ndf['Transmission'])\n",
    "ax2.hist(ndf['Fuel'])\n",
    "ax1.set_xlabel('Transmission mode')\n",
    "ax2.set_ylabel('Density')\n",
    "\n",
    "ax2.set_xlabel('Fuel')\n",
    "ax2.set_ylabel('Density')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Binerizing values in Transmission column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Ad ID</th>\n",
       "      <th>Make</th>\n",
       "      <th>Year</th>\n",
       "      <th>KM's driven</th>\n",
       "      <th>Price</th>\n",
       "      <th>Fuel</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Car Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1079071571</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>2021</td>\n",
       "      <td>54000</td>\n",
       "      <td>4190000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>1</td>\n",
       "      <td>ABS, Air Bags, AM/FM Radio, CD Player, Cassett...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080125520</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2018</td>\n",
       "      <td>95000</td>\n",
       "      <td>1300000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>0</td>\n",
       "      <td>AM/FM Radio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1080748789</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2015</td>\n",
       "      <td>50000</td>\n",
       "      <td>800000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>0</td>\n",
       "      <td>Rear speakers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076081635</td>\n",
       "      <td>Daihatsu</td>\n",
       "      <td>2013</td>\n",
       "      <td>94000</td>\n",
       "      <td>2155000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>1</td>\n",
       "      <td>ABS, Air Bags, Air Conditioning, Alloy Rims, A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1080812928</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2011</td>\n",
       "      <td>126544</td>\n",
       "      <td>1440000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>0</td>\n",
       "      <td>ABS, Air Conditioning, Alloy Rims, AM/FM Radio...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ad ID      Make  Year  KM's driven    Price    Fuel Transmission  \\\n",
       "0  1079071571    Toyota  2021        54000  4190000  Petrol            1   \n",
       "1  1080125520    Suzuki  2018        95000  1300000  Petrol            0   \n",
       "2  1080748789    Suzuki  2015        50000   800000  Petrol            0   \n",
       "3  1076081635  Daihatsu  2013        94000  2155000  Petrol            1   \n",
       "4  1080812928    Suzuki  2011       126544  1440000  Petrol            0   \n",
       "\n",
       "                                        Car Features  \n",
       "0  ABS, Air Bags, AM/FM Radio, CD Player, Cassett...  \n",
       "1                                        AM/FM Radio  \n",
       "2                                      Rear speakers  \n",
       "3  ABS, Air Bags, Air Conditioning, Alloy Rims, A...  \n",
       "4  ABS, Air Conditioning, Alloy Rims, AM/FM Radio...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf.loc[ndf['Transmission']=='Automatic','Transmission'] = 1\n",
    "ndf.loc[ndf['Transmission']=='Manual','Transmission'] = 0\n",
    "\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we use one hot encoding method to create columns based on categorized data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Ad ID</th>\n",
       "      <th>Make</th>\n",
       "      <th>Year</th>\n",
       "      <th>KM's driven</th>\n",
       "      <th>Price</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>ABS</th>\n",
       "      <th>AM/FM Radio</th>\n",
       "      <th>Air Bags</th>\n",
       "      <th>Air Conditioning</th>\n",
       "      <th>...</th>\n",
       "      <th>Rear Camera</th>\n",
       "      <th>Rear Seat Entertainment</th>\n",
       "      <th>Rear speakers</th>\n",
       "      <th>Steering Switches</th>\n",
       "      <th>Sun Roof</th>\n",
       "      <th>USB and Auxillary Cable</th>\n",
       "      <th>CNG</th>\n",
       "      <th>Diesel</th>\n",
       "      <th>Hybrid</th>\n",
       "      <th>Petrol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1079071571</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>2021</td>\n",
       "      <td>54000</td>\n",
       "      <td>4190000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080125520</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2018</td>\n",
       "      <td>95000</td>\n",
       "      <td>1300000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1080748789</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2015</td>\n",
       "      <td>50000</td>\n",
       "      <td>800000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076081635</td>\n",
       "      <td>Daihatsu</td>\n",
       "      <td>2013</td>\n",
       "      <td>94000</td>\n",
       "      <td>2155000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1080812928</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>2011</td>\n",
       "      <td>126544</td>\n",
       "      <td>1440000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ad ID      Make  Year  KM's driven    Price Transmission  ABS  \\\n",
       "0  1079071571    Toyota  2021        54000  4190000            1    1   \n",
       "1  1080125520    Suzuki  2018        95000  1300000            0    0   \n",
       "2  1080748789    Suzuki  2015        50000   800000            0    0   \n",
       "3  1076081635  Daihatsu  2013        94000  2155000            1    1   \n",
       "4  1080812928    Suzuki  2011       126544  1440000            0    1   \n",
       "\n",
       "   AM/FM Radio  Air Bags  Air Conditioning  ...  Rear Camera  \\\n",
       "0            1         1                 0  ...            1   \n",
       "1            1         0                 0  ...            0   \n",
       "2            0         0                 0  ...            0   \n",
       "3            1         1                 1  ...            0   \n",
       "4            1         0                 1  ...            0   \n",
       "\n",
       "   Rear Seat Entertainment  Rear speakers  Steering Switches  Sun Roof  \\\n",
       "0                        0              1                  0         0   \n",
       "1                        0              0                  0         0   \n",
       "2                        0              1                  0         0   \n",
       "3                        0              0                  0         0   \n",
       "4                        0              0                  0         0   \n",
       "\n",
       "   USB and Auxillary Cable  CNG  Diesel  Hybrid  Petrol  \n",
       "0                        0    0       0       0       1  \n",
       "1                        0    0       0       0       1  \n",
       "2                        0    0       0       0       1  \n",
       "3                        0    0       0       0       1  \n",
       "4                        0    0       0       0       1  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_features = ndf['Car Features'].str.get_dummies(', ')\n",
    "fuel_types = ndf['Fuel'].str.get_dummies()\n",
    "car_make = ndf['Make'].str.get_dummies(', ')\n",
    "\n",
    "ndf = pd.concat([ndf, car_features], axis=1)\n",
    "ndf = pd.concat([ndf, fuel_types], axis=1)\n",
    "ndf = pd.concat([ndf, car_make], axis=1)\n",
    "\n",
    "ndf.drop('Car Features',axis=1, inplace=True)\n",
    "ndf.drop('Fuel',axis=1, inplace=True)\n",
    "ndf.drop('Make',axis=1, inplace=True)\n",
    "\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normalizing values in Year and KM's driven columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ad ID</th>\n",
       "      <th>Year</th>\n",
       "      <th>KM's driven</th>\n",
       "      <th>Price</th>\n",
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       "      <th>Air Conditioning</th>\n",
       "      <th>Alloy Rims</th>\n",
       "      <th>...</th>\n",
       "      <th>Chevrolet</th>\n",
       "      <th>Daihatsu</th>\n",
       "      <th>FAW</th>\n",
       "      <th>Honda</th>\n",
       "      <th>Hyundai</th>\n",
       "      <th>KIA</th>\n",
       "      <th>Mercedes</th>\n",
       "      <th>Mitsubishi</th>\n",
       "      <th>Suzuki</th>\n",
       "      <th>Toyota</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1079071571</td>\n",
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       "      <td>4190000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080125520</td>\n",
       "      <td>0.828571</td>\n",
       "      <td>0.178058</td>\n",
       "      <td>1300000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1080748789</td>\n",
       "      <td>0.742857</td>\n",
       "      <td>0.093714</td>\n",
       "      <td>800000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076081635</td>\n",
       "      <td>0.685714</td>\n",
       "      <td>0.176184</td>\n",
       "      <td>2155000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1080812928</td>\n",
       "      <td>0.628571</td>\n",
       "      <td>0.237182</td>\n",
       "      <td>1440000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ad ID      Year  KM's driven    Price Transmission  ABS  AM/FM Radio  \\\n",
       "0  1079071571  0.914286     0.101211  4190000            1    1            1   \n",
       "1  1080125520  0.828571     0.178058  1300000            0    0            1   \n",
       "2  1080748789  0.742857     0.093714   800000            0    0            0   \n",
       "3  1076081635  0.685714     0.176184  2155000            1    1            1   \n",
       "4  1080812928  0.628571     0.237182  1440000            0    1            1   \n",
       "\n",
       "   Air Bags  Air Conditioning  Alloy Rims  ...  Chevrolet  Daihatsu  FAW  \\\n",
       "0         1                 0           0  ...          0         0    0   \n",
       "1         0                 0           0  ...          0         0    0   \n",
       "2         0                 0           0  ...          0         0    0   \n",
       "3         1                 1           1  ...          0         1    0   \n",
       "4         0                 1           1  ...          0         0    0   \n",
       "\n",
       "   Honda  Hyundai  KIA  Mercedes  Mitsubishi  Suzuki  Toyota  \n",
       "0      0        0    0         0           0       0       1  \n",
       "1      0        0    0         0           0       1       0  \n",
       "2      0        0    0         0           0       1       0  \n",
       "3      0        0    0         0           0       0       0  \n",
       "4      0        0    0         0           0       1       0  \n",
       "\n",
       "[5 rows x 48 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf['Year'] = ndf['Year']-ndf['Year'].min()\n",
    "ndf['Year'] = ndf['Year']/ndf['Year'].max()\n",
    "\n",
    "ndf[\"KM's driven\"] = ndf[\"KM's driven\"]-ndf[\"KM's driven\"].min()\n",
    "ndf[\"KM's driven\"] = ndf[\"KM's driven\"]/ndf[\"KM's driven\"].max()\n",
    "\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Picking X and Y from dataset for cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x:  [0.9142857142857143 0.10121137262031725 1 1 1 1 0 0 1 1 1 0 0 1 1 1 0 1 1\n",
      " 1 1 1 1 1 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1]\n",
      "target val (y):  4190000\n"
     ]
    }
   ],
   "source": [
    "X = ndf.drop(['Ad ID','Price'],axis=1).values\n",
    "Y = ndf['Price'].values\n",
    "print('x: ',X[0])\n",
    "print('target val (y): ',Y[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using cross validation we split data in 5 groups and each would be used for training and the other 4 for training. Using this function we can find the best value for n_estimators as we are using Random Forest method for prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "def get_score(n_estimators):\n",
    "    my_pipeline = Pipeline(steps=[\n",
    "        ('model', RandomForestRegressor(n_estimators=n_estimators, random_state=0))\n",
    "    ])\n",
    "    scores = -1 * cross_val_score(my_pipeline, X, Y,\n",
    "                              cv=5,\n",
    "                              scoring='neg_mean_absolute_error')\n",
    "    return scores.mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = {}\n",
    "\n",
    "for i in [300,400,500,600,700,800,900]:\n",
    "    results[i] = get_score(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's find the optimal n_estimators value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(list(results.keys()), list(results.values()))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we should split the X and Y into train and test datasets and train the model using the train data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.2,random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor(n_estimators=500, random_state=0)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestRegressor(n_estimators=500, random_state=0)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestRegressor(n_estimators=500, random_state=0)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = RandomForestRegressor(n_estimators=500, random_state=0)\n",
    "model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking the error (MAE) on the test data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error on Test Set: 223699\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_error\n",
    "predictions = model.predict(X_test)\n",
    "mae = mean_absolute_error(y_test, predictions)\n",
    "print(\"Mean Absolute Error on Test Set:\", int(mae))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we do predictions on some random values from test data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 )----------------------\n",
      "actual price:     1000000\n",
      "predicted price:  918031\n",
      "error:            81968\n",
      "2 )----------------------\n",
      "actual price:     3280000\n",
      "predicted price:  3236340\n",
      "error:            43660\n",
      "3 )----------------------\n",
      "actual price:     400000\n",
      "predicted price:  460060\n",
      "error:            60060\n",
      "4 )----------------------\n",
      "actual price:     1480000\n",
      "predicted price:  1864036\n",
      "error:            384036\n",
      "5 )----------------------\n",
      "actual price:     3499000\n",
      "predicted price:  3542060\n",
      "error:            43060\n"
     ]
    }
   ],
   "source": [
    "random_indices = np.random.choice(len(X_test), size=5, replace=False)\n",
    "random_X_samples = X_test[random_indices]\n",
    "random_y_samples = y_test[random_indices]\n",
    "for i in range(5):\n",
    "    pred = model.predict(random_X_samples[i].reshape(1,-1))\n",
    "    print(i + 1,')----------------------')\n",
    "    print('actual price:    ', random_y_samples[i])\n",
    "    print('predicted price: ', int(pred[0]))\n",
    "    print('error:           ',(np.abs(pred - random_y_samples[i]))[0].astype(int))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE / y_test * 100: 10.99 percent\n"
     ]
    }
   ],
   "source": [
    "error_percentage = mae/y_test.mean()\n",
    "print(\"MAE / y_test * 100: %.2f percent\" % (error_percentage*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "though the MAE on the whole test data is a sensible number (almost 11 percent inaccurate), there is still room for improvement on this model. Using XGBoost probably is a good idea..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "pygments_lexer": "ipython3",
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