{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Päivitetty 2024-05-17 / Aki Taanila\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "print(f'Päivitetty {datetime.now().date()} / Aki Taanila')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.03334,
     "end_time": "2020-12-21T20:34:25.103544",
     "exception": false,
     "start_time": "2020-12-21T20:34:25.070204",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Auton hinnan ennustaminen\n",
    "\n",
    "Olen lainannut ideoita lähteestä https://www.kaggle.com/mohaiminul101/car-price-prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "papermill": {
     "duration": 1.209696,
     "end_time": "2020-12-21T20:34:26.344354",
     "exception": false,
     "start_time": "2020-12-21T20:34:25.134658",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# train_test_split osaa jakaa datan opetusdataan ja testidataan\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# Käytettävät mallit\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Funktio mallin sovittamiseen ja tarkasteluun\n",
    "\n",
    "Jos samaa koodia käytetään toistuvasti, niin siitä kannattaa tehdä funktio. Seuraavan solun mallinna-funktiolle annetaan parametrina sovitettava malli. Funktio sovittaa mallin, laskee selityskertoimet opetusdatalle ja testidatalle sekä piirtää mallin hyvyyden arviontiin sopivat grafiikat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "papermill": {
     "duration": 0.066241,
     "end_time": "2020-12-21T20:34:31.187643",
     "exception": false,
     "start_time": "2020-12-21T20:34:31.121402",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def mallinna(malli):\n",
    "    \n",
    "    # Mallin sovitus opetusdataan\n",
    "    malli.fit(X_train, y_train)\n",
    "            \n",
    "    # Selityskertoimet opetusdatalle ja testidatalle\n",
    "    R2_train_malli = malli.score(X_train, y_train)\n",
    "    R2_test_malli = malli.score(X_test, y_test)\n",
    "        \n",
    "    # Selityskertoimien tulostus\n",
    "    print(f'Opetusdatan selityskerroin {R2_train_malli:.3f}')\n",
    "    print(f'Testidatan selityskerroin {R2_test_malli:.3f}')\n",
    "       \n",
    "    # Opetusdatan virhetermit kaaviona\n",
    "    y_pred_train = malli.predict(X_train)\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "    ax[0].set_title('Ennustevirheiden jakauma opetusdatassa')\n",
    "    sns.histplot((y_train-y_pred_train), kde=True, ax=ax[0])\n",
    "    ax[0].set_xlabel('y_train - y_pred_train')\n",
    "    \n",
    "    # Toteutuneet ja ennustetut hajontakaaviona testidatalle\n",
    "    y_pred_test = malli.predict(X_test)\n",
    "    ax[1].set_title('Toteutuneet ja ennustetut testidatassa')\n",
    "    ax[1].scatter(x=y_test, y=y_pred_test)\n",
    "    ax[1].set_xlabel('toteutunut')\n",
    "    ax[1].set_ylabel('ennuste')\n",
    "\n",
    "    # Palautetaan funktion tuloksena malli\n",
    "    return(malli)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Datan tarkastelua"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a",
    "papermill": {
     "duration": 0.05608,
     "end_time": "2020-12-21T20:34:26.432107",
     "exception": false,
     "start_time": "2020-12-21T20:34:26.376027",
     "status": "completed"
    },
    "tags": []
   },
   "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>Car_Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Selling_Price</th>\n",
       "      <th>Present_Price</th>\n",
       "      <th>Kms_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Seller_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ritz</td>\n",
       "      <td>2014</td>\n",
       "      <td>3.35</td>\n",
       "      <td>5.59</td>\n",
       "      <td>27000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sx4</td>\n",
       "      <td>2013</td>\n",
       "      <td>4.75</td>\n",
       "      <td>9.54</td>\n",
       "      <td>43000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ciaz</td>\n",
       "      <td>2017</td>\n",
       "      <td>7.25</td>\n",
       "      <td>9.85</td>\n",
       "      <td>6900</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>wagon r</td>\n",
       "      <td>2011</td>\n",
       "      <td>2.85</td>\n",
       "      <td>4.15</td>\n",
       "      <td>5200</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>swift</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.60</td>\n",
       "      <td>6.87</td>\n",
       "      <td>42450</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Car_Name  Year  Selling_Price  Present_Price  Kms_Driven Fuel_Type  \\\n",
       "0     ritz  2014           3.35           5.59       27000    Petrol   \n",
       "1      sx4  2013           4.75           9.54       43000    Diesel   \n",
       "2     ciaz  2017           7.25           9.85        6900    Petrol   \n",
       "3  wagon r  2011           2.85           4.15        5200    Petrol   \n",
       "4    swift  2014           4.60           6.87       42450    Diesel   \n",
       "\n",
       "  Seller_Type Transmission  Owner  \n",
       "0      Dealer       Manual      0  \n",
       "1      Dealer       Manual      0  \n",
       "2      Dealer       Manual      0  \n",
       "3      Dealer       Manual      0  \n",
       "4      Dealer       Manual      0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://taanila.fi/car_data.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "papermill": {
     "duration": 0.05177,
     "end_time": "2020-12-21T20:34:26.692119",
     "exception": false,
     "start_time": "2020-12-21T20:34:26.640349",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 301 entries, 0 to 300\n",
      "Data columns (total 9 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Car_Name       301 non-null    object \n",
      " 1   Year           301 non-null    int64  \n",
      " 2   Selling_Price  301 non-null    float64\n",
      " 3   Present_Price  301 non-null    float64\n",
      " 4   Kms_Driven     301 non-null    int64  \n",
      " 5   Fuel_Type      301 non-null    object \n",
      " 6   Seller_Type    301 non-null    object \n",
      " 7   Transmission   301 non-null    object \n",
      " 8   Owner          301 non-null    int64  \n",
      "dtypes: float64(2), int64(3), object(4)\n",
      "memory usage: 21.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "papermill": {
     "duration": 0.066165,
     "end_time": "2020-12-21T20:34:26.798311",
     "exception": false,
     "start_time": "2020-12-21T20:34:26.732146",
     "status": "completed"
    },
    "tags": []
   },
   "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>Year</th>\n",
       "      <th>Selling_Price</th>\n",
       "      <th>Present_Price</th>\n",
       "      <th>Kms_Driven</th>\n",
       "      <th>Owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>301.000000</td>\n",
       "      <td>301.000000</td>\n",
       "      <td>301.000000</td>\n",
       "      <td>301.000000</td>\n",
       "      <td>301.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2013.627907</td>\n",
       "      <td>4.661296</td>\n",
       "      <td>7.628472</td>\n",
       "      <td>36947.205980</td>\n",
       "      <td>0.043189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.891554</td>\n",
       "      <td>5.082812</td>\n",
       "      <td>8.644115</td>\n",
       "      <td>38886.883882</td>\n",
       "      <td>0.247915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2003.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>15000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2014.000000</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>32000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>48767.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>92.600000</td>\n",
       "      <td>500000.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year  Selling_Price  Present_Price     Kms_Driven       Owner\n",
       "count   301.000000     301.000000     301.000000     301.000000  301.000000\n",
       "mean   2013.627907       4.661296       7.628472   36947.205980    0.043189\n",
       "std       2.891554       5.082812       8.644115   38886.883882    0.247915\n",
       "min    2003.000000       0.100000       0.320000     500.000000    0.000000\n",
       "25%    2012.000000       0.900000       1.200000   15000.000000    0.000000\n",
       "50%    2014.000000       3.600000       6.400000   32000.000000    0.000000\n",
       "75%    2016.000000       6.000000       9.900000   48767.000000    0.000000\n",
       "max    2018.000000      35.000000      92.600000  500000.000000    3.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "papermill": {
     "duration": 0.066311,
     "end_time": "2020-12-21T20:34:27.046773",
     "exception": false,
     "start_time": "2020-12-21T20:34:26.980462",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Muunnetaan 'Year' auton iäksi olettaen, että data vuodelta 2020\n",
    "df['Age'] = 2020 - df['Year']\n",
    "df = df.drop('Year', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "papermill": {
     "duration": 0.054384,
     "end_time": "2020-12-21T20:34:29.911743",
     "exception": false,
     "start_time": "2020-12-21T20:34:29.857359",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Pudotetaan 'Car_Name' pois, koska sitä ei tarvita\n",
    "df = df.drop('Car_Name', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "papermill": {
     "duration": 0.535539,
     "end_time": "2020-12-21T20:34:27.912245",
     "exception": false,
     "start_time": "2020-12-21T20:34:27.376706",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Kategoristen muuttujien jakaumat\n",
    "\n",
    "cat_cols = ['Fuel_Type', 'Seller_Type', 'Transmission', 'Owner']\n",
    "\n",
    "for i in range(0, 3, 2):\n",
    "    fig = plt.figure(figsize=(10, 4))\n",
    "    plt.subplot(1, 2, 1)\n",
    "    sns.countplot(x=cat_cols[i], data=df)\n",
    "    plt.subplot(1, 2, 2)\n",
    "    sns.countplot(x=cat_cols[i + 1], data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "papermill": {
     "duration": 0.491483,
     "end_time": "2020-12-21T20:34:28.441768",
     "exception": false,
     "start_time": "2020-12-21T20:34:27.950285",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Määrällisten muuttujien jakaumat\n",
    "\n",
    "num_cols = ['Selling_Price', 'Present_Price', 'Kms_Driven', 'Age']\n",
    "\n",
    "for i in range(0, 3, 2):\n",
    "    fig = plt.figure(figsize=(13, 3))\n",
    "    plt.subplot(1, 2, 1)\n",
    "    sns.boxplot(x=num_cols[i], data=df)\n",
    "    plt.subplot(1, 2, 2)\n",
    "    sns.boxplot(x=num_cols[i + 1], data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "papermill": {
     "duration": 0.420676,
     "end_time": "2020-12-21T20:34:29.291858",
     "exception": false,
     "start_time": "2020-12-21T20:34:28.871182",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pjrlOs5CZ8fEPqdUTV2LcMhdsu7kD2VnZePYgFH5HL6FCrQrffiIq0LFHW8xdNl32fGz/KQDyuCZKrqGiPjnX/WNb+66O6NyzHWaMnofQ4OeoWqsypi2YiLiYeBzbfwIA4DysD6xtamL8gKmIjIhCfbt6mPXbFMTFJOCG383vOFPV+Pnn7tjwxxLZ8y5dBwJQfD0VfX0pMmXyaPR16orWbXrLfn6XKmWFlb8vQIdO/XL9TC/0ftApQqEIsp1Ez5490alTJ/j5+eHatWs4deoUli5diq1btyIuLg6vX7+GqampXJ+3b98iNDT0m9/T2tpa9t8ikQiWlpaIjY0FAAQHB8Pa2ho6OjqymIYNG371ezRp0gQaGhpIT09HiRIlsGPHDtSu/XHY3dZW+TBzYGAgevfurfC1R48e4d27d2jTpo1c+/v371GvXr08j+nh4YH58+Xvepk91QVzp0343OmQmhjr60FTQ5RrdCsx7Q1MDYsp7LPt+GXUrVQGgzvmrJGrUhrQFWvjl8XbMa5nK5gb6eOPvy6ic5M66OFQHwBQuXRxvM14j4U7/sbwn+yhoVEgblr+KmlJqcjOyoaxubFcu6GpIVI+GQX7ICkuOddomKGpIbIys5CWlCbX3nVEN/Qc2wvuznMR9viF3Gsx4dGY4zQTYl0x9PT1kBSbhMnrpiL2Zcz3nla+8jl9GffvfFyUXUSsDSBnBCs+NkHWbmJmjIT4vNfdxscmwNRC/ue0iZmJXB/XueOwbd1unDp6DgDw9HEoSpSyxNDxA3Fs/wmIdcRwcRuFiUNmwO9czp3MT4NCUa1mZQwe3a9QFF5//30G/v4fp67F4iIAAEtLc0RHx8raLSzMEBMbn6v/p1wnjcSM6ePRrn1f3L8fJGu3samN4sXN4X/9pKxNS0sL9vaNMXbMYOgVKw9JYZ1qK6x5q4hg+3jp6OigTZs2aNOmDebOnYthw4Zh3rx5GDNmDEqUKAEfH59cfYyMjL75/bS1teWei0Qi2RepVCpVMLrwZX+Z/Ju3tzdq1KgBIyOjXIUjABQtmvcdLQCgq6ub52sfcv3nn39QsmRJudeUjV65ubnB1dVVrk0j7ZXSPEi9tLW0UL2cFa4/DEXr+h8XGF9/GIoW9RSvW3r3PhOamvKFk+b/C6kPX8vvMjIh0hDlipFKPzuwUWBlZWYh9H4I6tjXxY3TH9cE1bGvC/8z/gr7PLnzGLaODeTa6tjXQ+j9EGRnfbwdvevI7ug1rg8WDnRH6P2QPHPIeJuBjLcZKGpQFHWb18Muj53feVb5K/1NOtLfyG8zEhcTDzuHBnj84AmAnLVz9e3qYdWv6xUdAgBw9/YD2Dk0wJ7N+2RtTVo0xN2b92XPdXR1IP3kl6okWyL7OtTS0oR2Ee1cMdn/iinoXr9+g9ev38i1RUXFwLF1cwQGPgSQ8/unuX1juM1crPRYk11HYabbBHTs5Izbd+SnWi9cuIw69VrJtW3dsgLBwaFYtvyPwlt00Wfl2waqNWrUwJEjR2BjY4Po6GhoaWmhXLly+fV2cj5MN2b8awru1i3Fd48pU7p0aVSsWPHzgXmwtrbG+fPnc41QATnXRywWIzw8/KvWc4nF4lyFWeb7z//VpWrp6W8RHvFxbcyryBg8fhIKQwN9lLC0UGNm6jGgnR1mbT6MGuWsUKdSaRzyuY2ohBT0bpkzarr6wDnEJqVi0YgeAACHulWwYMff2H/hJprUqoi4lNdYtvcUalUoCQtjA1nM7tPXUK2MJWpXLIWXMYn44/AFONSrKivSCqO/tx6Fy8pJCLkXguA7j9H253YwszLHGa+ckQHnaQNhammCNa6rAACnvU6hw6BOGDxnCM7+eQZVbaqhtZMjVroslx2z28ge+HmyM1ZOWI7YiBjZCNm7N+/wLv0dAKBu83oQiUR49ewVSpQtgYEzB+PVs1e4cOCcSs9fCHu2eGOoyyCEPYtA+POXGOYyCO/evsOJw2dkMYvWzkVMVBzWLN4AAPDash/bj6zHL+P64+IpP7Rsb49G9g0wuMtIWR/fs5cxfMJgRL2KQWjwM1SrVRUDRvXFkT+PAwDevE7Hzat34Dp3HN69y0BURDTq29XDT707YLn7atVeBAGtWbsVM6aPx9OQ5wgJeY4Z08cjPf0t/tz3lyxmu+dqREZGYdbs3wDkTC/Od5+K/gPH4UXYSxQvnnOzwevXb/DmTTpev36Dhw+D5d4n/U06EhKScrUXOiwalfruwishIQG9e/fGkCFDYG1tDX19fdy6dQtLly5F165d4ejoCDs7O3Tr1g1LlixB1apVERkZiRMnTqBbt26fna77Fv369cOsWbMwYsQIzJgxA+Hh4Vi+POeHsCq3enBzc0Pt2rUxZswYjBo1CkWKFMHFixfRu3dvmJmZYcqUKZg0aRIkEgmaNWuG1NRUXL16FcWKFcOgQYNUlmd+ePD4KYaM/7juZOnanLtOu3ZwxKLZk9WVltq0b1QLKa/TsfmoL+JSXqNSSQv84eoMKzMjAEB8chqiEz4uEO9qXw9v3r3Hn+f88fu+09DX00GD6uUxsc/HqenhXZpDJBLhj8MXEJuUBmN9PTjUrYpxPVt9+vaFypXjl6FvrI8+Lk4wtjBB+JMwLBq8AHGv4gAAxhbGMLMyl8XHvozBr4PnY8jcYegwoBMSYxOxzX0Lrp/8eKdd+wEdoC3WxrSNbnLv5b3yT3iv+hMAoKevh/7TB8LU0gyvU9Jw7eQ17F22W27UrLDYvm4PdHTEmPXbFBgY6uN+wCOM6jtRbmTMsmRxuVGVu7fuY/qouRg3fSTGTRuBly9eYdrI2bgf8HEa02PmCoybPgKzfpsCE1MTxMXE4eCuI9i4wlMWM23kHEyYNRoef8yHoZEBoiKisfa3jdi/82ORUtgsW74euro6WLdmMYyNDeHvH4AOnfrJjYyVKW0ldz1HjRwEsViMA95b5I61YOHvWLBwhcpyVweptPB9z6iSSPotc3D/kpGRAXd3d5w5cwahoaHIzMxE6dKl0bt3b8ycORO6urpIS0vDrFmzcOjQIcTFxcHS0hLNmzeHh4cHSpcuDXd3dxw5ckS21cPgwYORnJyMI0eOAMjZTqJu3bpYtWoVgJztJCZOnCh3p2LdunXRrVs3uLu7A8jZTmL06NF4/PgxateujcmTJ6Nfv354/PgxqlatqvScXrx4gfLlyyMgIEBuR/1/E4lE+Ouvv+R22Pfx8UHLli2RlJQkm0b19fXFzJkzcfv2bejq6qJRo0bYt28fjIyMIJVKsXbtWqxfvx7Pnj2DkZERbGxsMHPmTDRv3vyL/w0y4599cSzJy356Q90pFGr9+v6p7hQKrZCMOHWnUGg9SgxXdwqFWtb7/F2e8tbH8/NBX0i3xZDPBxUy3114FRZeXl745ZdfkJKSonTtVWHEwuvbsfD6Piy8vh0Lr2/Hwuv7sPBSrx/2Q7J37dqFChUqoGTJkrh79y6mT5+OPn36/HBFFxERUYHC7SSUKrwrcD8jOjoa/fv3R/Xq1TFp0iT07t1btrv9qFGjZBu/fvoYNWqUmjMnIiIqxLhzvVL/manGf4uNjUVqaqrC1wwMDGBhUbjuuuNU47fjVOP34VTjt+NU47fjVOP3yfepxvObPx/0hXRbf9sm6wXZDzvVqIyFhUWhK66IiIgKBU41KvWfLLyIiIgon/ygU4RC+WHXeBEREREVNBzxIiIiIuFwqlEpFl5EREQkHE41KsWpRiIiIiIV4YgXERERCYcjXkqx8CIiIiLhcI2XUiy8iIiISDgc8VKKa7yIiIiIVISFFxEREQlHKhHu8Q3Wr1+P8uXLQ0dHB/Xr14efn5/SeC8vL9SpUwd6enooUaIEfvnlFyQkJHzTe38JFl5EREQkHDV+SLa3tzcmTpyIWbNmISAgAPb29ujQoQPCwxV/vufly5cxcOBADB06FA8fPsSBAwdw8+ZNDBs27HuvQp5YeBEREVGBlJGRgdTUVLlHRkZGnvErVqzA0KFDMWzYMFSvXh2rVq1C6dKlsWHDBoXx169fR7ly5eDi4oLy5cujWbNmGDlyJG7dupVfp8TCi4iIiAQk4FSjh4cHDA0N5R4eHh4K3/b9+/e4ffs22rZtK9fetm1bXL16VWGfJk2aICIiAidOnIBUKkVMTAwOHjyITp06CX5ZPuBdjURERCQcAe9qdHNzg6urq1ybWCxWGBsfH4/s7GwUL15crr148eKIjo5W2KdJkybw8vKCk5MT3r17h6ysLHTp0gVr164V5gQU4IgXERERFUhisRgGBgZyj7wKrw9EIpHcc6lUmqvtg0ePHsHFxQVz587F7du3cerUKTx//hyjRo0S7Bw+xREvIiIiEo6a9vEyMzODpqZmrtGt2NjYXKNgH3h4eKBp06aYOnUqAMDa2hpFixaFvb09fv31V5QoUULwPDniRURERMKRSoV7fIUiRYqgfv36OHv2rFz72bNn0aRJE4V90tPToaEhXwppamr+/zS+7v2/FAsvIiIi+iG4urpi69at8PT0RFBQECZNmoTw8HDZ1KGbmxsGDhwoi//pp59w+PBhbNiwAc+ePcOVK1fg4uKChg0bwsrKKl9y5FQjERERCUeNHxnk5OSEhIQELFiwAFFRUahVqxZOnDiBsmXLAgCioqLk9vQaPHgw0tLSsG7dOkyePBlGRkZo1aoVlixZkm85iqT5NZZGKpMZ/0zdKRRa2U9vqDuFQq1f3z/VnUKhFZIRp+4UCq1HiYo3w6Qvk/X+Vb4e/63XHMGOpeu8ULBjFRQc8SIiIiLhfONH/fxXcI0XERERkYpwxIuIiIiEo8Y1XoUBCy8iIiISDpeOK8WpRiIiIiIV4YgXERERCYdTjUqx8PoBcEuEb6dZuZG6UyjU7KX/qDuFQut9kWx1p1Bo1Syh+ONfqIBg4aUUpxqJiIiIVIQjXkRERCQc7uOlFAsvIiIiEoxUwrsaleFUIxEREZGKcMSLiIiIhMPF9Uqx8CIiIiLhcI2XUiy8iIiISDhc46UU13gRERERqQhHvIiIiEg4XOOlFAsvIiIiEg4LL6U41UhERESkIhzxIiIiIuFIubheGRZeREREJBxONSrFqUYiIiIiFeGIFxEREQmH+3gpxcKLiIiIhMOd65XiVCMRERGRinDEi4iIiITDqUalWHgRERGRYKS8q1EpFl5EREQkHI54KcU1XkREREQqwhEvIiIiEg7valSKhRcREREJh1ONSnGqkYiIiEhFOOJFREREwuFdjUqx8CIiIiLhcKpRKU41EhEREakIR7yIiIhIOLyrUSkWXkRERCQcTjUqxalGIiIiIhXhiJeABg8ejOTkZBw5ckTdqRAREakFP6tRua8qvAYPHoydO3fmdNTSQunSpdGjRw/Mnz8fRYsWzZcEv9eLFy9Qvnx5BAQEoG7dul/Ux93dHfPnzwcAaGhowMrKCu3atYOHhwfMzc3z7Ld69WpIpT/2EKv3eX/sOHkV8clpqFjSAtP6tYdN1bJ5xv9z9R52nLyC8JgEFNPVQZPalTC5b1sYFdOTxew5fQ37L95CdEIKjPT10Ma2Blx6tYa4iLYqTqnAuRV4H9v3HsSjxyGIS0jEao85aN28ibrTKnCsBzjCdmRHFLUwQsLTV/Cdvwev/IMVxlZqbwvrAa1hXqMsNItoI+FJBK6vPIywS/dVnLXwOg7ohB4je8DEwgThT8OxZf5mPPR/mGd8rUa1MGzucJSpXAaJsYk4tPEgTu45KRfTpEMT9J8yACXKlEBUeBR2L92Fa6evyV7X0NRAv0nOaNGtBYwtjJEUm4RzB87Be80+2c9Au/ZN0MG5PSrWrgRDE0OMbz8ezx89y5+LIKA2Azqg88huMDI3RsTTl9g1fxuCbz7KM756o5roP2cISlUujaTYRBzf+BfOeZ1WGGv3UzO4rJuCm6dvYMUID1m7hqYGek3qi6bdHGBkboSk2CRcOnABf609UDh/p3CqUamvnmps3749oqKi8OzZM/z6669Yv349pkyZkisuMzNTkATVpWbNmoiKikJ4eDg2bNiAv//+GwMHDlQYm52dDYlEAkNDQxgZGak2URU6deMBlu49heE/2cN7wSjYVCmDMSv2ICohWWH8nSdhmL3lL3RrXg+HFo3FsrG98fD5K7h7HpPF/HP1HlYfOIdRXR3w1+KxcB/SBaf9H2DNwfMqOquC5+3bd6haqQJmuo5RdyoFVpWfGqHFvP7wX3cMXh1n45V/MLrtnAp9K1OF8SUbVUO43wMcGbQcezvNRsS1IHT1nAzzmnn/0VAY2P9kj+HzhmP/Om+4dHTBQ/8HcN85H+ZWiv9ALF66ONx3zsdD/wdw6eiC/eu8McJ9JJp0+FjYV7Ophul/zMDFwxcwvv04XDx8AdPXz0CVulVlMb1G90aH/h2wce5GjG41CtsXe6LHyB746ZefZDE6emI8uhWEnb/tyLfzF1rjzk0xcO4QHFl3AG6dXBHs/wgzds6BqZWZwnjz0haYtmMOgv0fwa2TK47+cRCD3IehYQe7XLFmJc3hPGswgm7kLoq7jO4BR+f22DF3Mya3Ho+9HjvReWR3tBvcSfBzVAmJVLjHD+irCy+xWAxLS0uULl0a/fr1g7OzM44cOQJ3d3fUrVsXnp6eqFChAsRiMaRSKVJSUjBixAhYWFjAwMAArVq1wt27d2XHu3v3Llq2bAl9fX0YGBigfv36uHXrluz1q1evonnz5tDV1UXp0qXh4uKCN2/eyF4vV64cFi9ejCFDhkBfXx9lypTB5s2bZa+XL18eAFCvXj2IRCK0aNHii85TS0sLlpaWKFmyJDp37gwXFxecOXMGb9++xY4dO2BkZITjx4+jRo0aEIvFCAsLw+DBg9GtWzfZMSQSCZYsWYJKlSpBLBajTJkyWLRokez1V69ewcnJCcbGxjA1NUXXrl3x4sWLr/wXUZ3dp6+he3Mb9HCojwpW5pjm3AGWJobYf+GWwvj7oRGwMjOCc5vGKGVuDJsqZdGrhS0evYiUxdwNfYm6lcugo501Spobo0mtSmjfqDYe/ivmv8bergFcRgxCmxZN1Z1KgWUzrAMeePvgwT4fJIZEwnf+HqRFJsB6QGuF8b7z9+DWxn8Qc+8Zkl/E4MrS/Uh+EY0KjvVUnLmwug3rjrPeZ3Bm3xlEhLzElvlbEB8Zj44DOiqM79C/I+JexWHL/C2ICHmJM/vO4Nz+s+gxoocspsvQrgjwC8CBPw4gIjQCB/44gLtX7qLr0K6ymGr1q+HGmRu4deEmYiNiceXEFQRcCkAl68qymIuHL2Lf6j8ReDkw385faJ2GdcVF73O4uO8cIkMisGvBNiRExaNN//YK4x2d2yMhMg67FmxDZEgELu47B5/959FpRFe5OJGGBsaunoSDK/chNjwm13Eq21TFrbP+CLhwG/ERsfA/cQ33/AJRwbpSvpwnqdd3L67X1dWVjW6FhIRg//79OHToEAIDAwEAnTp1QnR0NE6cOIHbt2/DxsYGrVu3RmJiIgDA2dkZpUqVws2bN3H79m3MmDED2to5U0z3799Hu3bt0KNHD9y7dw/e3t64fPkyxo0bJ5fD77//DltbWwQEBGDMmDEYPXo0Hj9+DADw9/cHAJw7dw5RUVE4fPjwN5+nRCJBVlYWACA9PR0eHh7YunUrHj58CAsLi1x93NzcsGTJEsyZMwePHj3C3r17Ubx4cVn/li1bolixYrh06RIuX76MYsWKoX379nj//v035ZifMrOyEPQiEna1Ksq129WqiLshLxX2qVOpNGKSUuF39wmkUikSUl7j3K1HsP/XD+d6lcsg6EUk7j+LAABExCbi8r2ncjFE/6ahrYnitcsj7NIDufZwvwewqv+FXzciEbSL6uBd8pvPxxZQWtpaqFS7EgIuBci1B/jdQbX61RX2qWZTDQF+d+Ta7vjeQSXrytDU0vwY88kx7/jeQfV/HfPRzUeo07QOrMpbAQDKVy+PGg1q4FYef4QVBpraWihfuyLu+QXKtd+7FIgq9asp7FPZpiruXZKPv3spABVqV5JdTwDoOaEP0hJS4eN9TuFxgm8GoVYTa1j+/3qWqV4O1WyrI/Di7W8/IXWSSoR7/IC+a3G9v78/9u7di9atc/7KfP/+PXbv3i1bB3XhwgXcv38fsbGxEIvFAIDly5fjyJEjOHjwIEaMGIHw8HBMnToV1arlfGFXrvzxB+eyZcvQr18/TJw4UfbamjVr4ODggA0bNkBHRwcA0LFjR4wZkzMtM336dKxcuRI+Pj6oVq2aLBdTU1NYWlp+03k+fvwYGzZsQMOGDaGvrw8gZyp1/fr1qFOnjsI+aWlpWL16NdatW4dBgwYBACpWrIhmzZoBAPbt2wcNDQ1s3boVIpEIALB9+3YYGRnBx8cHbdu2VXjcjIwMZGRkyLVJ32fm+3qopLR0ZEukMDWQX8tnalAU8SmvFfapW7kMPEb2wLQNB/E+MwtZ2RK0qFcVM/p//Gu8Q+PaSEpLx+BFngCArGwJ+rSyxdDO9vl3MlSo6ZroQ0NLE+nxKXLtb+JSUNbc6IuOUX9ER2jrifHk+I18yFA1DEwMoKmliaT4ZLn2pLhk2JgbK+xjbG6MpLhP4uOToaWtBQMTAyTFJsHY3BjJ8UlyMcnxOe0fHFx/AEX19bDx4iZIsiXQ0NTA7mW7cOmYryDnpg4GxvrQ1NJEyifXMyU+BYZ5XE8jcyOkfPJ1mPL/66lvYoDk2CRUsa2GFk6OcOswKc/3PrbhMPT09fD7hXWy67l/mReuHvP77vNSix90ilAoX114HT9+HMWKFUNWVhYyMzPRtWtXrF27FuvXr0fZsmXlFp/fvn0br1+/hqmp/LqLt2/fIjQ0FADg6uqKYcOGYffu3XB0dETv3r1RsWJFWf+QkBB4eXnJ+kqlUkgkEjx//hzVq+f8BWZtbS17XSQSwdLSErGxsV97anLu37+PYsWKITs7GxkZGWjRooXcFGaRIkXk3vdTQUFByMjIkBWln/pwbh8KuQ/evXsnuzaKeHh4yBb+fzBrSA/MHtbrS07ru30oEj+QSgFRHrGhr2KxxOskRnZxQJPaFRGX/Borvc/g153HMf//0xY3g55j69+XMGtgJ9SuUArhsYlY6nUSZoa+GNnVIZ/Phgq1TxYdi0S52xSp2sUOdpO649iwlXibkJpPyalQrusg+syCbAXX7ZPDfNr902M2/6k5WnRvieXjlyHsSRgq1KyA4fNGICEmERcK+/rMXOcO5ddTwfXPaZZCp6gOxq6ahC0z1iMtKS3PQ9j91AzNurfAOpcViHjyEmVrlMfAeUOQFJOIS4cufuuZUAH11YVXy5YtsWHDBmhra8PKyko2LQgg152NEokEJUqUgI+PT67jfFiE7u7ujn79+uGff/7ByZMnMW/ePOzbtw/du3eHRCLByJEj4eLikqt/mTJlZP/97xyAnC98yXfezlq1alUcO3YMmpqasLKyko3YfaCrq5urCPn0dWUkEgnq168vV1R+oOzOSTc3N7i6usq1SQOOKH0vIRjr60FTQ5RrdCsx7Q1MDYsp7LPt+GXUrVQGgzvmrFWqUhrQFWvjl8XbMa5nK5gb6eOPvy6ic5M66OFQHwBQuXRxvM14j4U7/sbwn+yhocGt5kje28Q0SLKyoffJ6JaemWGuUbBPVfmpEdosG4Z/Rq9F+OW87/wrDFITU5GdlS03EgUARmaGSP5k1OaDpLik3PGmRsjKzEJaUmqeMYamRnLH/GXWEBxcfwCX/r4EAAgLDoNFSQv0HtO70BZeqUlpyM7KhuEnX1cGpoZIzeN6JsclK4zPyszC66Q0lKpSBhali2Pqtlmy10UaOb839oQegmvLsYgNj4bzzME4uuEQrv19GQDwMjgM5qXM0WVMz0JZeEk54qXUVxdeRYsWRaVKX7bgz8bGBtHR0dDS0kK5cuXyjKtSpQqqVKmCSZMm4eeff8b27dvRvXt32NjY4OHDh1/8fooUKVIEQM6dh1/b73vet3LlytDV1cX58+cxbNiwXK/b2NjA29tbdtPBlxKLxbmKwHcq2HZBW0sL1ctZ4frDULT+11qP6w9D0aKe4vUP795nQlNTvnDS/H8h9eEvyHcZmbIfRP+OkUpz/eFJBACQZGYj5v5zlLWvhdDTH9cUlbGvhdAzea+JqdrFDm2XD8eJcX/g+YVAFWSav7IysxByPwR17evJbfVQ174ebpy5rrDP4zuP0dCxoVxbveb1EHLvKbKzsmUx9ezr4ui2I3IxQbeDZM/FumJIPvnlKpFICvUfStmZWXh+PxTW9nVx6/THKeja9nVx+4ziKemnd4Jh49hArs3avi6e3Q9BdlY2IkMjMLWN/MBBnynO0C2mi53uW5EQFQ8AKKJbJFexIsmWQEMj7z/uCzQWXkrl63eJo6Mj7Ozs0K1bN5w+fRovXrzA1atXMXv2bNy6dQtv377FuHHj4OPjg7CwMFy5cgU3b96UTSFOnz4d165dw9ixYxEYGIinT5/i2LFjGD9+/BfnYGFhAV1dXZw6dQoxMTFISVH+F7FQdHR0MH36dEybNg27du1CaGgorl+/jm3btgHIuanAzMwMXbt2hZ+fH54/fw5fX19MmDABERERKsnxaw1oZ4fDvnfw16U7eBYZh2V7TyEqIQW9W9oCAFYfOIdZmz/evOBQtwou3A7C/gs3ERGbiICn4VjidRK1KpSEhbGBLObAhZs4ef0+IuKScO1BKP44fAEO9arKirT/mvT0t3j8JBSPn+RMOb+KjMHjJ6GIiv6+6fMfyZ2tJ1GrbwvU7NMcJpWs4DDXGfpWpri3J2e0pen0Pmi3cqQsvmoXO7RbORK+C/ciKiAEeuaG0DM3RBF95SPTBd2RrX+hbd+2aNOnDUpVKo1hc4fD3MocJ/acAAAMmj4Iris/jpCf3HMCFiUtMGzOMJSqVBpt+rRBG6e2OPyv79tjnsdQr7kNeo7uhVIVS6Hn6F6o26wujm47KovxP+cPp/FOsG3VABalLGDXzg7dhnWXKwCLGRZD+RoVUKZyzuxEqYolUb5GBRjlsV6qIPhn61G0dHJEiz6tYVWpFAbMGQIzKzPZvlx9p/XH6BUTZPHnvE7BrKQ5+s/5BVaVSqFFn9Zo6eSIfzbnXKvMjExEPAmXe6SnvsHb128R8SQc2Zk5N2vdOXcL3cb1Qr1W9WFWygK27Rqh47AuuHm68K5BpLzl6871IpEIJ06cwKxZszBkyBDExcXB0tISzZs3R/HixaGpqYmEhAQMHDgQMTExMDMzk23ICuSs3fL19cWsWbNgb28PqVSKihUrwsnJ6Ytz0NLSwpo1a7BgwQLMnTsX9vb2Cqc+88OcOXOgpaWFuXPnIjIyEiVKlMCoUaMAAHp6erh06RKmT5+OHj16IC0tDSVLlkTr1q2/agRMldo3qoWU1+nYfNQXcSmvUamkBf5wdYaVmREAID45DdEJHwvbrvb18Obde/x5zh+/7zsNfT0dNKheHhP7tJHFDO/SHCKRCH8cvoDYpDQY6+vBoW5VjOvZStWnV2A8ePwUQ8ZPlz1fujZnbWHXDo5YNHuyutIqUJ78fQM6RvpoNKF7zgaqTyJwZNAypL1KAAAUtTCC/r/2Xqrt3Aqa2lpovWgwWi8aLGt/eOASzkze/OnhCw2/v/2gb2SAvhN+homFCcKehMF90DzEvYoDABhbmMjt6RXzMgbug+Zh2Nzh6DSwMxJiErDZfROunrwqi3l8OwhLxy1B/ykD0H9yf0SHRWPJ2CV4Evhxc9pNczei/5T+GPPrGBiaGSIxJhEnvU5i3+o/ZTGN2jTGpBUfF5RP/2MGAGDvSi/sXbk3367J97h+/Ar0jQ3Qw8UJRhbGePkkHEsGL0T8/6+nkYUJzP51PeNexmLp4IUYMHcI2g7oiKTYROx03wr/k9fyeguFdszbjD6TnfHLwpEwNDNEUkwSzu89jUOr9wt6firDneuVEkkL5ba49G/vrv35+SBSSLNyI3WnUKits5mr7hQKrfNI+nwQKaQv+m9+qoVQ/gw7kq/HTxvTQbBj6a8/+fmgQua/OZdDRERE+UPNO9evX78e5cuXh46ODurXrw8/P+XbcmRkZGDWrFkoW7YsxGIxKlasCE9Pz2967y/xn/yQ7GLFFN+FBwAnT56EvT33kCIiIipsvL29MXHiRKxfvx5NmzbFpk2b0KFDBzx69EhuN4R/69OnD2JiYrBt2zZUqlQJsbGxss3S88N/svD6sKu+IiVLllRdIkRERD8YIVcwKdo0XNHd/R+sWLECQ4cOle0msGrVKpw+fRobNmyAh4dHrvhTp07B19cXz549g4mJCQAo3YVBCP/JqcZKlSrl+fjc/ltERESkhIBTjR4eHjA0NJR7KCqggJxPz7l9+3auT35p27Ytrl69qrDPsWPHYGtri6VLl6JkyZKoUqUKpkyZgrdv3wp+WT74T454ERERUcGnaNPwvEa74uPjkZ2dLftM5A+KFy+O6OhohX2ePXuGy5cvQ0dHB3/99Rfi4+MxZswYJCYm5ts6LxZeREREJBwBN1BVNq2Yl9wfbSfN85NmJBIJRCIRvLy8YGhoCCBnurJXr174448/8mUW7D851UhERET5QyqRCvb4GmZmZtDU1Mw1uhUbG5trFOyDEiVKoGTJkrKiCwCqV68OqVSab5uZs/AiIiKiQq9IkSKoX78+zp49K9d+9uxZNGnSRGGfpk2bIjIyEq9ff/wc4idPnkBDQwOlSpXKlzxZeBEREZFw1LiPl6urK7Zu3QpPT08EBQVh0qRJCA8Pl31qjJubGwYOHCiL79evH0xNTfHLL7/g0aNHuHTpEqZOnYohQ4bk2812XONFREREwlHjJwY5OTkhISEBCxYsQFRUFGrVqoUTJ06gbNmyAICoqCiEh4fL4osVK4azZ89i/PjxsLW1hampKfr06YNff/0133LkRwb9APiRQd+OHxn0ffiRQd+OHxn07fiRQd8nvz8yKGVAa8GOZbj7vGDHKig44kVERESC+dpF8f81LLyIiIhIOCy8lGLhRURERMJR4xqvwoB3NRIRERGpCEe8iIiISDBc46UcCy8iIiISDqcaleJUIxEREZGKcMSLiIiIBMOpRuVYeBEREZFwONWoFKcaiYiIiFSEI15EREQkGClHvJRi4UVERETCYeGlFKcaiYiIiFSEI15EREQkGE41KsfCi4iIiITDwkspFl5EREQkGI54Kcc1XkREREQqwhEvIiIiEgxHvJRj4UVERESCYeGlHKcaiYiIiFSEI14/gH59/1R3CoWWvfQfdadQqI27s0DdKRRaj22nqzuFQmtR1Vh1p0DKSEXqzqBAY+FFREREguFUo3KcaiQiIiJSEY54ERERkWCkEk41KsPCi4iIiATDqUblONVIREREpCIc8SIiIiLBSHlXo1IsvIiIiEgwnGpUjoUXERERCYaL65XjGi8iIiIiFeGIFxEREQlGKlV3BgUbCy8iIiISDKcaleNUIxEREZGKcMSLiIiIBMMRL+VYeBEREZFguMZLOU41EhEREakIR7yIiIhIMJxqVI6FFxEREQmGHxmkHKcaiYiIiFSEI15EREQkGH5Wo3IsvIiIiEgwEk41KsXCi4iIiATDNV7KcY0XERERkYpwxIuIiIgEw+0klGPhRURERILhzvXKcaqRiIiISEU44kVERESC4VSjciy8iIiISDDcTkI5TjUSERHRD2P9+vUoX748dHR0UL9+ffj5+X1RvytXrkBLSwt169bN1/xYeBEREZFgpFKRYI+v5e3tjYkTJ2LWrFkICAiAvb09OnTogPDwcKX9UlJSMHDgQLRu3fpbT/uLsfAiIiIiwUilwj2+1ooVKzB06FAMGzYM1atXx6pVq1C6dGls2LBBab+RI0eiX79+sLOz+8az/nIsvL6Qu7t7vg8/EhER0UcZGRlITU2Ve2RkZCiMff/+PW7fvo22bdvKtbdt2xZXr17N8z22b9+O0NBQzJs3T9Dc85Jvi+sHDx6M5ORkHDlyRNZ28OBB9O/fHwsWLMC0adPy660VKleuHMLCwgAAOjo6KF68OBo2bIhRo0ahVatWn+0/ZcoUjB8/Pr/TLFDaD+iAriN7wNjcGC+fhsNz/lYE3XyUZ3yNRjXxy5yhKF25DBJjE3Fk42Gc8Tole92xb1u06NkSZaqWBQCE3g+B19LdCLn7VBajU1QX/SY7o1G7xjAwM8Tzh8/g6b4FIfdC8u9E1ch6gCNsR3ZEUQsjJDx9Bd/5e/DKP1hhbKX2trAe0BrmNcpCs4g2Ep5E4PrKwwi7dF/FWRdctwLvY/veg3j0OARxCYlY7TEHrZs3UXdaKufQvy3ajuwKQwsjRD6JwP4F2xFy83Ge8ZUb1UDv2YNgVaUUkmOScGbTUVzyOisX03pIRzR3bgeTkmZ4nZiKOyev46+le5GVkQkAEBfVQdfJfVG3bUPomxni5cPn8J6/HWH3QvP1XPObTudu0O3dFxomJsgOe4HXG9ch68E9hbHa1nVhuGx1rvakYQOQ/TJnqkvcoTN0HNtBs2x5AEBWSDDSt29BVnDe/z6FjZCL6z08PDB//ny5tnnz5sHd3T1XbHx8PLKzs1G8eHG59uLFiyM6Olrh8Z8+fYoZM2bAz88PWlqqud9QZSNeW7duhbOzM9atW6fyouuDBQsWICoqCsHBwdi1axeMjIzg6OiIRYsW5dlHKpUiKysLxYoVg6mpqQqzVa+mnZvhl7nDcGjdfkzuNBFB/o8we+c8mFmZKYy3KF0cs3fMQ5D/I0zuNBGH/ziAoe7D0bjDx2HbWna1cPnYJcztOwtu3aciPjIe83bPh0lxE1nM2CXjYG1fF6snrcSkti64eykQ87wWysX8KKr81Agt5vWH/7pj8Oo4G6/8g9Ft51ToWyn+OivZqBrC/R7gyKDl2NtpNiKuBaGr52SY1yyr4swLrrdv36FqpQqY6TpG3amojW3nJugz9xecWHcIv3achpCbQRi/YxaM8/jeNS1lgfHb3RByMwi/dpyGk38chtO8IajXvpEspmHXZug+3RnHVx+Au+NE7Jq+Abadm6D7tH6ymIFLRqN6M2tsd12LBe0m45HfXUzaMxdGhfh7t4hDSxQdNQ7pf+5G8pjhyHxwD4a/LoGGuYXSfolDnJHQt7vskf0qQvaatnVdZFw8j5RpE5EyaQwksbEwWLwcGqaK/30KIyHXeLm5uSElJUXu4ebmpvT9RSL5wk8qleZqA4Ds7Gz069cP8+fPR5UqVQS9BsqopPBaunQpxo0bh71792LYsGEAckbEunXrhsWLF6N48eIwMjLC/PnzkZWVhalTp8LExASlSpWCp6en7Djv37/HuHHjUKJECejo6KBcuXLw8PD44jz09fVhaWmJMmXKoHnz5ti8eTPmzJmDuXPnIjg4Z5TBx8cHIpEIp0+fhq2tLcRiMfz8/OSmGk+fPg0dHR0kJyfLHd/FxQUODg6y51evXkXz5s2hq6uL0qVLw8XFBW/evJG9Xq5cOSxevBhDhgyBvr4+ypQpg82bN3/t5c0XPw3rivPe53Bu31m8ComA54KtSIiKR7v+HRXGt3Nuj/jIOHgu2IpXIRE4t+8sLuw/h64justiVk1YgVO7T+LFo+d4FfoKG6avg0hDA9ZN6wAAioiLoHGHJtjtsQOP/B8iOiwK3qv+ROzLGLQb0EEl561KNsM64IG3Dx7s80FiSCR85+9BWmQCrAcoXtzpO38Pbm38BzH3niH5RQyuLN2P5BfRqOBYT8WZF1z2dg3gMmIQ2rRoqu5U1MZxWGdc2X8BV7wvIDr0FfYv2IGkqHg49G+rMN6hfxskRsZj/4IdiA59hSveF3DlwAW0HdFFFlPBpipCbwXj5rHLSIiIQ5DfPdw8dgVla1cEAGiLi6Be+0Y45LEHT/2DEBcWjeOrDiA+IjbP9y0MdHv0wbvTJ5Bx6h9kvwzDm43rkB0XB53OXZX2kyYnQ5qUKHtAIpG99nrJr3h3/Aiyn4Ug+2U4Xq9aBog0oF2vfn6fjsoIucZLLBbDwMBA7iEWixW+r5mZGTQ1NXONbsXGxuYaBQOAtLQ03Lp1C+PGjYOWlha0tLSwYMEC3L17F1paWrhw4UK+XJ98L7xmzJiBhQsX4vjx4+jZs6fcaxcuXEBkZCQuXbqEFStWwN3dHZ07d4axsTFu3LiBUaNGYdSoUXj58iUAYM2aNTh27Bj279+P4OBg7NmzB+XKlfuu/CZMmACpVIqjR4/KtU+bNg0eHh4ICgqCtbW13GuOjo4wMjLCoUOHZG3Z2dnYv38/nJ2dAQD3799Hu3bt0KNHD9y7dw/e3t64fPkyxo0bJ3es33//Hba2tggICMCYMWMwevRoPH6s3iFnLW0tVKxdCXf9AuTaAy8FoFr9agr7VLGphsBLueMr1q4ETS1NhX2K6Iqhqa2JtOQ0AICGliY0tTTxPuO9XNz7jPeoblvjW0+nQNLQ1kTx2uURdumBXHu43wNY1a/8ZQcRiaBdVAfvkt98Ppb+EzS1tVCmVgU88rsr1/7I7x4q1q+qsE+FelXwyE9+6uzRpbsoW7sCNP7/vRtyKwhlaldAuTqVAABmpS1Qq2U93L94BwCgoaUBTS1NZH3yvZv57j0qNlD8M6PA09KCVuUqyLx9U6458/ZNaNeopbSr0fqtMNl7GAa/rYB2HeV/GInEYoi0tCBJS/3ulP/rihQpgvr16+PsWflp8rNnz6JJk9xLDgwMDHD//n0EBgbKHqNGjULVqlURGBiIRo0a5eojhHyd0Dx58iSOHj2K8+fPK1xHZWJigjVr1kBDQwNVq1bF0qVLkZ6ejpkzZwIA3Nzc8Ntvv+HKlSvo27cvwsPDUblyZTRr1gwikQhly37/FIuJiQksLCzw4sULufYFCxagTZs2CvtoamrCyckJe/fuxdChQwEA58+fR1JSEnr37g0AWLZsGfr164eJEycCACpXrow1a9bAwcEBGzZsgI6ODgCgY8eOGDMmZ1pk+vTpWLlyJXx8fFCtmuIfVhkZGbkWFmZLs6EpUlzcfAt9YwNoamkiOT5Zrj0lPgVG5kYK+xibGyEwPkWuLTk+GVraWjAwMUBSbFKuPgNmDERidCLuXcn5JfHuzVs8vh2E3uOdEPE0AinxyWjWtTkq162CqOeRgpxbQaFrog8NLU2kf3LN3sSloGwe1/hT9Ud0hLaeGE+O38iHDKkwKmasD00tTaTGJcu1p8Ulw8DMSGEfA3MjpH0SnxqXDE1tLRQz1kdqXDJu/X0V+iYGmHpgIUSinALPZ/dpnN5wBACQ8eYdQm8Ho6NLL0SFvEJqfAoadmmKcnUrIfa54rU1BZ2GgSFEmlqQJCfKtUuSkyAyVjx9KklMQNqqZch6GgyRdhGIW7eFwW8rkDJ1Qp7rwvSGjIQkIQ6Zd24Lfg7qos4NVF1dXTFgwADY2trCzs4OmzdvRnh4OEaNGgUgp6549eoVdu3aBQ0NDdSqJV9EW1hYQEdHJ1e7kPK18LK2tkZ8fDzmzp2LBg0aQF9fX+71mjVrQkPj46Bb8eLF5U5WU1MTpqamiI2NBZAzPdmmTRtUrVoV7du3R+fOnXPdvfAtFM3/2traKu3j7OwMOzs7REZGwsrKCl5eXujYsSOMjY0BALdv30ZISAi8vLzk3kcikeD58+eoXr06AMiNpolEIlhaWsrOVxFFCw2rGVRBdSPFf81+D+mn9/KKlN/e+2n8h2ua6zgAuo3sgWZdmmOu0yxk/n9xLgCsnrgS45a5YNvNHcjOysazB6HwO3oJFWpV+PYTKchyXbPcbYpU7WIHu0ndcWzYSrxN4F/K9Bk5X1h5viyF4u/dD6o0roEO43pi75wteB4YAotylnCa+wtSYpNwYm3OyL/npLUYtGwMlvpvRnZWNsIfPMfNo5dRurB/73562USKGnNkR7xEdsRL2fOsoIfQNLeAbq++SFNQeOn2/hnilq2RMnUCkPk+1+uF1bfsvyUUJycnJCQkyNZ016pVCydOnJAN1ERFRX12T6/8lq+FV8mSJXHo0CG0bNkS7du3x6lTp+SKL21tbbl4kUiksE3y//lxGxsbPH/+HCdPnsS5c+fQp08fODo64uDBg9+cY0JCAuLi4lC+fHm59qJFiyrt17BhQ1SsWBH79u3D6NGj8ddff2H79u2y1yUSCUaOHAkXF5dcfcuUKSP7b2Xnq4ibmxtcXV3l2gbU+llprl8rLSkV2VnZMDY3lms3NDVEyiejYB8kxSXnGg0zNDVEVmYW0pLS5Nq7juiGnmN7wd15LsIev5B7LSY8GnOcZkKsK4aevh6SYpMwed1UxL6M+d7TKlDeJqZBkpUNvU+umZ6ZYa5RsE9V+akR2iwbhn9Gr0X45Yf5mCUVNq+T0pCdlQ2DT76u9M0MkZrH11VqXDIMPvle1zczRHZmFl7//3u3i2tf3Dh8CVe8c9a8RAaHQ6wrRn+PkTi57jCkUiniw2Pwu9M8FNEVQ6eYLlLjkjF83SQkvMz7D8mCTJKaAml2FjQ+Gd3SMDSGNCn3CH5eMh8/hLhV7gEC3V5O0O3rjNQZk5H9/Nl350sfjRkzRjaT9KkdO3Yo7evu7q7wjkkh5fsarzJlysDX1xexsbFo27YtUlO/769zAwMDODk5YcuWLfD29sahQ4eQmJj4+Y55WL16NTQ0NNCtW7ev7tuvXz94eXnh77//hoaGBjp16iR7zcbGBg8fPkSlSpVyPYoUKfLN+SpaaCjkNCMAZGVmIfR+COrY15Vrr2NfF49vK15/9uTOYwXx9RB6PwTZWdmytq4ju6PXeCcsHDQfoffz3iIi420GkmKTUNSgKOo2rwf/M/7ffD4FkSQzGzH3n6Osvfxwdhn7Woi8/TSPXjkjXe1+H4mT49fj+YXAfM6SCpvszCyEP3iG6s3k16VWb2aN0NuKtyl5FvAkV3wN+zoIu/8Mkv9/7xbRFUMqlf+DUCKR5IykfTI69v5tBlLjkqFnUBQ1mtfB3bPya6QKjawsZD19Am0b+dkPbRtbZD56kEen3LQqVoYkMUGuTbdXX+j2G4jUWdOQ9VTxv0thJpGKBHv8iFRyV2OpUqXg4+ODhIQEtG3bFikpyv+iz8vKlSuxb98+PH78GE+ePMGBAwdgaWkJIyOjL+qflpaG6OhovHz5EpcuXcKIESPw66+/YtGiRahUqdJX5+Ps7Iw7d+5g0aJF6NWrl2zdFpCzXuvatWsYO3YsAgMD8fTpUxw7dqzQ7AX299ajaO3UBq36OKJkpVL4Zc5QmFmZ44zXSQCA87SBcFkxURZ/2usUzEtaYPCcIShZqRRa9XFEaydHHN38lyym28ge6De5P/6YtgaxETEwMjeCkbkRdPQ+Xre6zeuhnoMNLEoXR51mdbFg3yK8evYKFw6cU9m5q8qdrSdRq28L1OzTHCaVrOAw1xn6Vqa4t+c8AKDp9D5ot3KkLL5qFzu0WzkSvgv3IiogBHrmhtAzN0QRfV11nUKBk57+Fo+fhOLxk5y9o15FxuDxk1BERRfOUZdvcW7rcTRzao0mvVvCsmJJ9J4zCCZWZrjkdQYA0G1aPwz+/eNNPr57zsK0pBl6zx4Ey4ol0aR3SzTt0wpnNh+Txdw7fwvNndvC9qcmMC1lgerNrNHFtS/unbsF6f9H6Gs0r4OaDnVlr7vuc0fMs0hcOXBRtRdAQG8P74dO+04Qt+0IzdJlUXTkWGhaWODdPznXRu+X4Sg2daYsXqd7LxSxawYNq5LQLFsOer8Mh9i+Bd4dOyyL0e39M/QGDcXrFUuQHRMNkbFJzpoxnR/n+1gq4ONHpJrdwpAz7ejr64uWLVuiTZs2sLKy+upjFCtWDEuWLMHTp0+hqamJBg0a4MSJE3LrxJSZO3cu5s6diyJFisDS0hKNGzfG+fPn0bJly6/OBchZMN+gQQPcvHkTq1atknvN2toavr6+mDVrFuzt7SGVSlGxYkU4OTl903up2pXjl6FvrI8+Lk4wtjBB+JMwLBq8AHGv4gAAxhbGMLMyl8XHvozBr4PnY8jcYegwoBMSYxOxzX0Lrp+8JotpP6ADtMXamLZRfg8W75V/wnvVnwAAPX099J8+EKaWZnidkoZrJ69h77LdcqNmP4onf9+AjpE+Gk3onrOB6pMIHBm0DGmvcv46LmphBP1/7b1U27kVNLW10HrRYLReNFjW/vDAJZyZXDC2IVG3B4+fYsj46bLnS9fmXJeuHRyxaPZkdaWlUreOX0VRo2LoNKEXDM2NEfnkJdb9shiJr+IBAIYWxjAp+fHrKiEiFmt/8UCfOYPgMKAdUmKT4D3fEwGnPt60cWLtIUAqRdfJP8PI0gSvE1Jx7/wtHFn+pyxGV18P3af1g5GlKdJTXuPOyRs4svxP2ahZYfTe9yLe6BtCz3kgNExMkR32HCmzp0MSm7P0QcPEFJr/2tNLpKWNoiNGQ8PUHNL3GcgOe4GU2dOQefPjtdTp3BWiIkVgMGeh3Hul796O9D07VHJepF4iqaKVz1So9Cjb5fNBpJC91EDdKRRq4+4sUHcKhdY42+mfDyKFFlX974xg5gez0775evyrJXp+PugLNYk69PmgQkZlI15ERET041PnXY2FwQ/xIdleXl4oVqyYwkfNmjXVnR4RERERgB9kxKtLly557jD76XYNRERElH/y3hCJgB+k8NLX18+1OSsRERGpnhScalTmhyi8iIiIqGCQ8JY9pX6INV5EREREhQFHvIiIiEgwEk41KsXCi4iIiATDNV7KcaqRiIiISEU44kVERESC4XYSyrHwIiIiIsFwqlE5TjUSERERqQhHvIiIiEgwnGpUjoUXERERCYaFl3KcaiQiIiJSEY54ERERkWC4uF45Fl5EREQkGAnrLqVYeBEREZFg+JFBynGNFxEREZGKcMSLiIiIBCNVdwIFHAsvIiIiEgy3k1COU41EREREKsIRLyIiIhKMRMTF9cqw8CIiIiLBcI2XcpxqJCIiIlIRjngRERGRYLi4XjkWXkRERCQY7lyvHKcaiYiIiFSEI15EREQkGH5kkHIsvIiIiEgwvKtRORZeREREJBiu8VKOhdcPICQjTt0pFFrvi2SrO4VC7bHtdHWnUGitu7VE3SkUWsvrz1V3CoWam7oT+I9j4UVERESC4XYSyrHwIiIiIsFwjZdy3E6CiIiISEU44kVERESC4eJ65Vh4ERERkWC4xks5TjUSERERqQhHvIiIiEgwHPFSjoUXERERCUbKNV5KcaqRiIiISEU44kVERESC4VSjciy8iIiISDAsvJRj4UVERESC4c71ynGNFxEREZGKsPAiIiIiwUhEwj2+xfr161G+fHno6Oigfv368PPzyzP28OHDaNOmDczNzWFgYAA7OzucPn36G8/8y7DwIiIiIsFIBHx8LW9vb0ycOBGzZs1CQEAA7O3t0aFDB4SHhyuMv3TpEtq0aYMTJ07g9u3baNmyJX766ScEBAR8w7t/GRZeRERE9ENYsWIFhg4dimHDhqF69epYtWoVSpcujQ0bNiiMX7VqFaZNm4YGDRqgcuXKWLx4MSpXroy///4733Lk4noiIiISjJB3NWZkZCAjI0OuTSwWQywW54p9//49bt++jRkzZsi1t23bFlevXv2i95NIJEhLS4OJicm3J/0ZHPEiIiIiwUgFfHh4eMDQ0FDu4eHhofB94+PjkZ2djeLFi8u1Fy9eHNHR0V+U+++//443b96gT58+X3fSX4EjXkRERFQgubm5wdXVVa5N0WjXv4lE8qvypVJprjZF/vzzT7i7u+Po0aOwsLD4+mS/EAsvIiIiEsy33o2oSF7TioqYmZlBU1Mz1+hWbGxsrlGwT3l7e2Po0KE4cOAAHB0dvznfL8GpRiIiIhKMuu5qLFKkCOrXr4+zZ8/KtZ89exZNmjTJs9+ff/6JwYMHY+/evejUqdNXvuvX44gXERER/RBcXV0xYMAA2Nraws7ODps3b0Z4eDhGjRoFIGfq8tWrV9i1axeAnKJr4MCBWL16NRo3biwbLdPV1YWhoWG+5MjCi4iIiASjzo8McnJyQkJCAhYsWICoqCjUqlULJ06cQNmyZQEAUVFRcnt6bdq0CVlZWRg7dizGjh0rax80aBB27NiRLzmy8CIiIiLBSNT8aY1jxozBmDFjFL72aTHl4+OT/wl9goUXERERCUbIfbx+RFxcT0RERKQiHPEiIiIiwah3orHgY+FFREREguFUo3KcaiQiIiJSEY54ERERkWCE3Ln+R8TCi4iIiASj7u0kCrr/ZOH18uVLuLu74+TJk4iPj0eJEiXQrVs3zJ07F6ampupOr8AZPWUoevbvCgNDA9wPeIjFbssRGvxcaR/HTi0wdvoIlC5bEi/DXmGtxyZcOOkre11TUxOjpwxFp57tYGpuivjYeBz1PoHNK7dDKs35ptXV08XE2WPQqn1zGBobIvJlFPZu24/9O//K1/P9Fh0HdEKPkT1gYmGC8Kfh2DJ/Mx76P8wzvlajWhg2dzjKVC6DxNhEHNp4ECf3nJSLadKhCfpPGYASZUogKjwKu5fuwrXT12Sva2hqoN8kZ7To1gLGFsZIik3CuQPn4L1mn+wa2rVvgg7O7VGxdiUYmhhifPvxeP7oWf5cBAE59G+LtiO7wtDCCJFPIrB/wXaE3HycZ3zlRjXQe/YgWFUpheSYJJzZdBSXvOQ/NqT1kI5o7twOJiXN8DoxFXdOXsdfS/ciKyMTACAuqoOuk/uibtuG0DczxMuHz+E9fzvC7oXm67kWJLcC72P73oN49DgEcQmJWO0xB62b5/1RK/8FNgMc0WhkRxQzN0Lc01c4N38PIm4GK4wtamGE1rP7wbJWeZiUL45b28/g3II9ueIaDGmHev0dYVDSFG8T0/D4hD98lu5H9v+/FunH9p9b4/Xs2TPY2triyZMn+PPPPxESEoKNGzfi/PnzsLOzQ2JiorpTBJDzaepZWVnqTgO/jOuPASN/hsfM39GvwxDExyZgk/dq6BXVy7OPdf1aWLppIY4fOIVerQfi+IFTWLb5V9SuV0MWM2Rcf/Qe2B2LZ/6Obs37YuXCPzB4TD/0G9pbFjNtwQQ0bdkYbuPc0a15X+zevA8zFrmiRTv7fD3nr2X/kz2GzxuO/eu84dLRBQ/9H8B953yYW5krjC9eujjcd87HQ/8HcOnogv3rvDHCfSSadPj4C66aTTVM/2MGLh6+gPHtx+Hi4QuYvn4GqtStKovpNbo3OvTvgI1zN2J0q1HYvtgTPUb2wE+//CSL0dET49GtIOz8bUe+nb/QbDs3QZ+5v+DEukP4teM0hNwMwvgds2BsZaYw3rSUBcZvd0PIzSD82nEaTv5xGE7zhqBe+0aymIZdm6H7dGccX30A7o4TsWv6Bth2boLu0/rJYgYuGY3qzayx3XUtFrSbjEd+dzFpz1wYFTfJ93MuKN6+fYeqlSpgpqvizSf/a6p3bgTHuf1xdd0xeHaajQj/YDjtnAoDK8V/oGsV0UJ6QhqurjuKmKBwhTE1uzVBi+lOuLz6MLa0noYT07ag+k+N0WJan/w8FZWSCvj4Ef3nCq+xY8eiSJEiOHPmDBwcHFCmTBl06NAB586dw6tXrzBr1iysXbsWtWvXlvU5cuQIRCIR/vjjD1lbu3bt4ObmBgBwd3dH3bp1sXv3bpQrVw6Ghobo27cv0tLSZPFSqRRLly5FhQoVoKurizp16uDgwYOy1318fCASiXD69GnY2tpCLBbDz89PBVdEuf7DnbBl9Q6cP+GLkMfPMNtlIXR0ddCxR9u8+4xwwvVLN7Ft7S68CAnDtrW74O93C/1HOMlirG1r4+JpP/idu4rIl9E4e/wirvn4o0adarKYOra1cGz/Cdy6GoDIl9E4tOconjwMQc061fP1nL9Wt2Hdcdb7DM7sO4OIkJfYMn8L4iPj0XFAR4XxHfp3RNyrOGyZvwURIS9xZt8ZnNt/Fj1G9JDFdBnaFQF+ATjwxwFEhEbgwB8HcPfKXXQd2lUWU61+Ndw4cwO3LtxEbEQsrpy4goBLAahkXVkWc/HwRexb/ScCLwfm2/kLzXFYZ1zZfwFXvC8gOvQV9i/YgaSoeDj0V/w159C/DRIj47F/wQ5Eh77CFe8LuHLgAtqO6CKLqWBTFaG3gnHz2GUkRMQhyO8ebh67grK1KwIAtMVFUK99Ixzy2IOn/kGIC4vG8VUHEB8Rm+f7/ojs7RrAZcQgtGnRVN2pFAgNh3XAXW8f3N3ng4SQSJxbsAepUQmo17+1wviUiHicm78bDw5fRkbqW4UxJW0qIeL2Uzw6eg0pEfF47vcAj45dQwnrCvl5Kiqlrg/JLiz+U4VXYmIiTp8+jTFjxkBXV1fuNUtLSzg7O8Pb2xstWrTAw4cPER8fDwDw9fWFmZkZfH1zpsqysrJw9epVODg4yPqHhobiyJEjOH78OI4fPw5fX1/89ttvstdnz56N7du3Y8OGDXj48CEmTZqE/v37y475wbRp0+Dh4YGgoCBYW1vn16X4IiXLWMG8uBmu+fjL2jLfZ+L2tQDUbVA7z3516tfC1X/1AYArPjdQ5199Am7cRSN7W5StUBoAUKVGJdRrVAeXz3+cSrtz4x5atGsGC8uckaMGTW1QtmJpXPW5Lsj5CUFLWwuValdCwKUAufYAvzuoVl9xgVjNphoC/O7Itd3xvYNK1pWhqaX5MeaTY97xvYPq/zrmo5uPUKdpHViVtwIAlK9eHjUa1MCtC7e++7zURVNbC2VqVcAjv7ty7Y/87qFi/aoK+1SoVwWP/O7Jx1+6i7K1K0Dj/9cz5FYQytSugHJ1KgEAzEpboFbLerh/MeffQUNLA5pamsjKeC93nMx371GxQTXQf4+GtiYsa5fHc78Hcu3PLz1AqfqV8+j1eS9vPoFlrXIoUSen0DIqbY6KLesg5ELg96RLhch/ao3X06dPIZVKUb264l+I1atXR1JSEiwsLGBqagpfX1/07NkTPj4+mDx5MlauXAkAuHnzJt69e4dmzZrJ+kokEuzYsQP6+voAgAEDBuD8+fNYtGgR3rx5gxUrVuDChQuws7MDAFSoUAGXL1/Gpk2b5Aq4BQsWoE2bNnmeQ0ZGBjIyMuTaJFIJNETC19BmFjnD6Qlx8tOvCXGJKFHKUmm/xE/6JMYlwsz84/C857rdKGZQDEcv70N2tgSamhpY67EJJ498XJfz2+wVcP/dDecCjyEzMwtSiQTukz0Q4C//S1adDEwMoKmliaT4ZLn2pLhk2JgbK+xjbG6MpLhP4uOToaWtBQMTAyTFJsHY3BjJ8UlyMcnxOe0fHFx/AEX19bDx4iZIsiXQ0NTA7mW7cOmYfDFfmBQz1oemliZSP7k+aXHJMDAzUtjHwNwIaZ/Ep8YlQ1NbC8WM9ZEal4xbf1+FvokBph5YCJEop8Dz2X0apzccAQBkvHmH0NvB6OjSC1Ehr5Aan4KGXZqiXN1KiH0eLfyJUoGnZ6wPDS1NvIlPkWt/E5+CouZG33zcoL+vQ89UHwMOzgX+/7V4Z/c5XN/w93dmXHBwcb1y/6nC63M+LEjW0NBA8+bN4ePjg9atW+Phw4cYNWoUli9fjqCgIPj4+MDGxgbFihWT9S1Xrpys6AKAEiVKIDY2FgDw6NEjvHv3LldB9f79e9SrV0+uzdbWVmmOHh4emD9/vlybRdGSKF6s9Nef8Cc69miLucumy56P7T8FwMfr8oFIJPrs5PunfSCSb2vf1RGde7bDjNHzEBr8HFVrVca0BRMRFxOPY/tPAACch/WBtU1NjB8wFZERUahvVw+zfpuCuJgE3PC7+R1nmg8UXKNc10C+wyfxuQ+T6xJ+cszmPzVHi+4tsXz8MoQ9CUOFmhUwfN4IJMQk4sLB899yFgWXSARlX3TSXNdT/n72Ko1roMO4ntg7ZwueB4bAopwlnOb+gpTYJJxYewgA4DlpLQYtG4Ol/puRnZWN8AfPcfPoZZSu9eNMAdE3yPW9nbvta5RpXB1NxnbF6Tk7EBkQAuNylnCc1x9NXbrhypoj35drAcGyS7n/VOFVqVIliEQiPHr0CN26dcv1+uPHj2FsbAwzMzO0aNECmzdvhp+fH+rUqQMjIyM0b94cvr6+8PHxQYsWLeT6amtryz0XiUSQSHJmqD/8/z///IOSJUvKxYnFYrnnRYsWVXoObm5ucHV1lWtrUjnvEbKv4XP6Mu7feSR7XkScc05mFqaIj02QtZuYGSMhPu+bEOJjE2BqIb/41MTMRK6P69xx2LZuN04dPQcAePo4FCVKWWLo+IE4tv8ExDpiuLiNwsQhM+B37mpOTFAoqtWsjMGj+xWYwis1MRXZWdlyI1EAYGRmiORPRsE+SIpLyh1vaoSszCykJaXmGWNoaiR3zF9mDcHB9Qdw6e9LAICw4DBYlLRA7zG9C23h9TopDdlZ2TD4ZERB38wQqZ+MPHyQGpcMg0+ulb6ZIbIzs/A6KWedZRfXvrhx+BKueF8AAEQGh0OsK0Z/j5E4ue4wpFIp4sNj8LvTPBTRFUOnmC5S45IxfN0kJLyMFf5EqcBLT0qDJCs71+iWnqlhrlGwr9F8ci88+OsK7u7zAQDEBUdAW0+MDh5DcGXt0e8q6gqKH3VtllD+U2u8TE1N0aZNG6xfvx5v38ovfIyOjoaXlxecnJwgEolk67wOHjwoK7IcHBxw7ty5XOu7PqdGjRoQi8UIDw9HpUqV5B6lS3/dSJVYLIaBgYHcQ6hpxvQ36Xj5IkL2CA1+jriYeNg5NJDFaGlrob5dPQTevJ/nce7efiDXBwCatGiIu//qo6OrA6lE/ttTki2BSCNnpEJLSxPaRbRzxWT/K6YgyMrMQsj9ENS1lx+5rGtfD49vByns8/jO41zx9ZrXQ8i9p8jOypbF1LOvmysm6F/HFOuKIZHI/5CWSCTQ0Ci839bZmVkIf/AM1ZvJr2+s3swaobcV38L/LOBJrvga9nUQdv8ZJP+/nkV0xZBKP/l6k0hyhi8+GR17/zYDqXHJ0DMoihrN6+Du2YJR5JNqSTKzEX3/Ocrb15JrL29fCxG3n37zcbV0i+T6uSbNzvlaFBWcH22Uj/5TI14AsG7dOjRp0gTt2rXDr7/+ivLly+Phw4eYOnUqSpYsiUWLFgEAatWqBVNTU3h5eeHo0aMAgBYtWmDy5MkAILe+63P09fUxZcoUTJo0CRKJBM2aNUNqaiquXr2KYsWKYdCgQcKfqED2bPHGUJdBCHsWgfDnLzHMZRDevX2HE4fPyGIWrZ2LmKg4rFm8AQDgtWU/th9Zj1/G9cfFU35o2d4ejewbYHCXkbI+vmcvY/iEwYh6FYPQ4GeoVqsqBozqiyN/HgcAvHmdjptX78B17ji8e5eBqIho1Lerh596d8By99WqvQifcWTrX3BdORkh954i6M5jtO/XHuZW5jixJ2fKdND0QTC1NMWKSSsAACf3nEDnQZ0xbM4wnPrzNKrbVEMbp7ZYNn6p7JjHPI9hyYEl6Dm6F26cuY5GbRujbrO6mNZzmizG/5w/nMY7IS4yDuFPwlCxZsWcOyz3f1wnV8ywGMxLWsD0/1silKqYM+KaFJeE5Dj5NWQFxbmtx/HLivEIuxeKZ3eewL6fI0yszHDJK+drrtu0fjAqboIdk9cBAHz3nEWLge3Re/Yg+P15DhVsqqBpn1bY6rJKdsx752/BcWhnhD98jucBOVONXVz74t65W7JfgjWa14FIJEJ0aCQsylmi58wBiHkWiSsHLqr8GqhLevpbhEdEyp6/iozB4yehMDTQRwlLCzVmph7+W0/ip5WjEXXvGV7dCUHdn1vCwMoUAV45I8oO0/pA39IYx103yfpY1CgDAChSVAw9U31Y1CiD7MwsJDzNua4h5wLQcFgHxDwMQ2RgKIzLFkfzyb3w9OwdSCWFf7QL4Bqvz/nPFV6VK1fGrVu34O7uDicnJyQkJMDS0hLdunXDvHnzYGKS8wtKJBLBwcEBR44cgb19zr5R1tbWMDQ0RIUKFWBgYPBV77tw4UJYWFjAw8MDz549g5GREWxsbDBz5kzBz1FI29ftgY6OGLN+mwIDQ33cD3iEUX0nIv1NuizGsmRx2XQqANy9dR/TR83FuOkjMW7aCLx88QrTRs7G/YCP05geM1dg3PQRmPXbFJiYmiAuJg4Hdx3BxhWesphpI+dgwqzR8PhjPgyNDBAVEY21v20scBuo+v3tB30jA/Sd8DNMLEwQ9iQM7oPmIe5VHADA2MJEbk+vmJcxcB80D8PmDkengZ2REJOAze6bcPXkVVnM49tBWDpuCfpPGYD+k/sjOiwaS8YuwZPAj6M+m+ZuRP8p/THm1zEwNDNEYkwiTnqdxL7Vf8piGrVpjEkrJsmeT/9jBgBg70ov7F25N9+uyfe4dfwqihoVQ6cJvWBobozIJy+x7pfFSHyVc5exoYUxTEp+3NMrISIWa3/xQJ85g+AwoB1SYpPgPd8TAaduyGJOrD0ESKXoOvlnGFma4HVCKu6dv4Ujyz9eK119PXSf1g9GlqZIT3mNOydv4MjyP2WjZv8FDx4/xZDxH9d5Ll27GQDQtYMjFs2erK601Cbo+A3oGuujqUt3FLMwQtyTCOwfvAypr3KWXhSzMILBJ/vLDT25WPbfJawroGa3pkh+GYcNzXK+D6+sPQJIpXCY0hvFLI2RnpCKkPMB8F12QGXnld9YdiknkipfAUyFgLWlnbpTKLTKFPnvbI6ZH0pq5L2RLim37tYSdadQaC2vP1fdKRRqbmG5d9MX0qRyfQU71soX+wQ7VkHxnxvxIiIiovzDxfXKsfAiIiIiwXy6vQvJK7y3PxEREREVMhzxIiIiIsFwqlE5Fl5EREQkGG4noRynGomIiIhUhCNeREREJBiOdynHwouIiIgEw6lG5Vh4ERERkWC4uF45rvEiIiIiUhGOeBEREZFguIGqciy8iIiISDCcalSOU41EREREKsIRLyIiIhIMpxqVY+FFREREguFUo3KcaiQiIiJSEY54ERERkWAkUk41KsPCi4iIiATDsks5TjUSERERqQhHvIiIiEgw/KxG5Vh4ERERkWC4nYRyLLyIiIhIMNxOQjmu8SIiIiJSEY54ERERkWC4xks5Fl5EREQkGK7xUo5TjUREREQqwhEvIiIiEgwX1yvHwouIiIgEI+VHBinFqUYiIiIiFeGIFxEREQmGdzUqx8KLiIiIBMM1Xsqx8PoBPEoMV3cKhVbNEsXVnUKhtqhqrLpTKLSW15+r7hQKrSm3F6g7BSrA1q9fj2XLliEqKgo1a9bEqlWrYG9vn2e8r68vXF1d8fDhQ1hZWWHatGkYNWpUvuXHNV5EREQkGKmA//ta3t7emDhxImbNmoWAgADY29ujQ4cOCA9XPEDx/PlzdOzYEfb29ggICMDMmTPh4uKCQ4cOfe9lyBMLLyIiIhKMBFLBHl9rxYoVGDp0KIYNG4bq1atj1apVKF26NDZs2KAwfuPGjShTpgxWrVqF6tWrY9iwYRgyZAiWL1/+vZchTyy8iIiISDBSqVSwR0ZGBlJTU+UeGRkZCt/3/fv3uH37Ntq2bSvX3rZtW1y9elVhn2vXruWKb9euHW7duoXMzExhLsgnWHgRERFRgeTh4QFDQ0O5h4eHh8LY+Ph4ZGdno3hx+bW7xYsXR3R0tMI+0dHRCuOzsrIQHx8vzEl8govriYiISDBC3tXo5uYGV1dXuTaxWKy0j0gkknsulUpztX0uXlG7UFh4ERERkWCE/JBssVj82ULrAzMzM2hqauYa3YqNjc01qvWBpaWlwngtLS2Ympp+W9KfwalGIiIiKvSKFCmC+vXr4+zZs3LtZ8+eRZMmTRT2sbOzyxV/5swZ2NraQltbO1/yZOFFREREglHnXY2urq7YunUrPD09ERQUhEmTJiE8PFy2L5ebmxsGDhwoix81ahTCwsLg6uqKoKAgeHp6Ytu2bZgyZYpg1+NTnGokIiIiwajzQ7KdnJyQkJCABQsWICoqCrVq1cKJEydQtmxZAEBUVJTcnl7ly5fHiRMnMGnSJPzxxx+wsrLCmjVr0LNnz3zLUSTlx4gXelpFSqo7hUKrd4kG6k6hUFtbLUndKRRaWx6XVncKhRZ3rv8+2mYV8vX4rUu1/XzQFzofcUawYxUUHPEiIiIiwfBDspVj4UVERESCEfKuxh8RF9cTERERqQhHvIiIiEgwEi4dV4qFFxEREQmGZZdyLLyIiIhIMFxcrxzXeBERERGpCEe8iIiISDAc8VKOhRcREREJhvuyK8epRiIiIiIV4YgXERERCYZTjcqx8CIiIiLBcOd65TjVSERERKQiHPEiIiIiwXBxvXIsvIiIiEgwXOOlHKcaiYiIiFSEI15EREQkGE41KsfCi4iIiATDqUblWHgRERGRYLidhHJc40VERESkIhzxIiIiIsFIuMZLKY54fYerV69CU1MT7du3V3cqKjV3jivCX9xGWkoIzp89gBo1qiiNHzqkH3wuHEZczEPExTzE6ZP70MC2bp7x06eNQ9b7V/h9+XyBM1etNgM6YPXlTdgZvB+Ljv+Oqg1qKI2v3qgmFh3/HTuD92OV30Y4OrfLM9bup2b4M+wIXDe7ybVraGqgz5R+/39fb6zy24geLn0gEokEOSd10uncDcY798H07zMwWrcZWrWs84zVtq4Ls9O+uR6apcvIYsQdOsPw97UwOXgcJgePw+C336FVtZoqTkXlbAY4YvTlFZga7InBxxeiVIOqecYWtTBClzVjMOLCMsx4vguOc/srjGswpB1GXFiGKcGeGHttNVrPcYamWDu/TqHAuxV4H2OnzUPLLs6o1bQDzl+6qu6U1EYq4P9+RCy8voOnpyfGjx+Py5cvIzw8XN3pqMTUKWMwccIIuEycjcZNOiE6Jg6nTvyJYsWK5tnHwcEO+7yPwrFtHzRr3gXhL1/h5Im9sLKyzBVrW78Ohg11xt17j/LzNPJd485NMXDuEBxZdwBunVwR7P8IM3bOgamVmcJ489IWmLZjDoL9H8GtkyuO/nEQg9yHoWEHu1yxZiXN4TxrMIJuPMz1WpfRPeDo3B475m7G5NbjsddjJzqP7I52gzsJfo6qVMShJYqOGof0P3cjecxwZD64B8Nfl0DD3EJpv8Qhzkjo2132yH4VIXtN27ouMi6eR8q0iUiZNAaS2FgYLF4ODVPF/0aFVfXOjeA4tz+urjsGz06zEeEfDKedU2FgZaowXquIFtIT0nB13VHEBCn+uVazWxO0mO6Ey6sPY0vraTgxbQuq/9QYLab1yc9TKdDevn2HqpUqYKbrGHWnQgUcC69v9ObNG+zfvx+jR49G586dsWPHDrnXjx07hsqVK0NXVxctW7bEzp07IRKJkJycLIu5evUqmjdvDl1dXZQuXRouLi548+aNak/kK7mMHwaP39bgyJGTePgwGL8MmQg9PV383Ld7nn0GDhqPjZt24u7dhwgODsXIUVOhoaGBVq2aycUVLaqHXbvWYdToaUhOSs7nM8lfnYZ1xUXvc7i47xwiQyKwa8E2JETFo01/xaOjjs7tkRAZh10LtiEyJAIX952Dz/7z6DSiq1ycSEMDY1dPwsGV+xAbHpPrOJVtquLWWX8EXLiN+IhY+J+4hnt+gahgXSlfzlNVdHv0wbvTJ5Bx6h9kvwzDm43rkB0XB53OXZX2kyYnQ5qUKHtAIpG99nrJr3h3/Aiyn4Ug+2U4Xq9aBog0oF2vfn6fjko1HNYBd719cHefDxJCInFuwR6kRiWgXv/WCuNTIuJxbv5uPDh8GRmpbxXGlLSphIjbT/Ho6DWkRMTjud8DPDp2DSWsK+TnqRRo9nYN4DJiENq0aKruVNROIpUK9vgRsfD6Rt7e3qhatSqqVq2K/v37Y/v27bK9S168eIFevXqhW7duCAwMxMiRIzFr1iy5/vfv30e7du3Qo0cP3Lt3D97e3rh8+TLGjRunjtP5IuXLl0GJEsVx9pyvrO39+/e45Hcddna2X3wcPT1daGtrISkxWa597ZrFOHniPM5f8BMqZbXQ1NZC+doVcc8vUK793qVAVKmveCqrsk1V3LskH3/3UgAq1K4ETS1NWVvPCX2QlpAKH+9zCo8TfDMItZpYw7K8FQCgTPVyqGZbHYEXb3/7Camblha0KldB5u2bcs2Zt29Cu0YtpV2N1m+Fyd7DMPhtBbTr1FMaKxKLIdLSgiQt9btTLig0tDVhWbs8nvs9kGt/fukBStWv/M3HfXnzCSxrlUOJOjmFllFpc1RsWQchFwK/J136QXCqUTkurv9G27ZtQ//+OWsf2rdvj9evX+P8+fNwdHTExo0bUbVqVSxbtgwAULVqVTx48ACLFi2S9V+2bBn69euHiRMnAgAqV66MNWvWwMHBARs2bICOjo7C983IyEBGRoZcm1QqVckaHsviOdM6MTHxcu0xMXEoW6bUFx9n8aKZePUqGufOfyyw+vTpgnr1aqGxXeGeEgMAA2N9aGppIiU+Wa49JT4FhubGCvsYmRshJT7lk/hkaGlrQd/EAMmxSahiWw0tnBzh1mFSnu99bMNh6Onr4fcL6yDJlkBDUwP7l3nh6rHCW8xqGBhCpKkFSXKiXLskOQkiYxOFfSSJCUhbtQxZT4Mh0i4Cceu2MPhtBVKmTkDWg3sK++gNGQlJQhwy7xTiIvUTesb60NDSxJtPvrbexKegqLnRNx836O/r0DPVx4CDcwFRzh8bd3afw/UNf39nxkQ/PhZe3yA4OBj+/v44fPgwAEBLSwtOTk7w9PSEo6MjgoOD0aBBA7k+DRs2lHt++/ZthISEwMvLS9YmlUohkUjw/PlzVK9eXeF7e3h4YP58+UXnIo1iEGkaCHFqcn7+uTs2/LFE9rxL14GyPOXeXyT64p2Kp0wejb5OXdG6TW9ZAVmqlBVW/r4AHTr1y1VUFmqfXBKR6DM7Oiu4rjnNUugU1cHYVZOwZcZ6pCWl5XkIu5+aoVn3FljnsgIRT16ibI3yGDhvCJJiEnHp0MVvPZOC4dNLJ1LUmCM74iWyI17KnmcFPYSmuQV0e/VFmoLCS7f3zxC3bI2UqROAzPfC5VxQ5Prayt32Nco0ro4mY7vi9JwdiAwIgXE5SzjO64+mLt1wZc2R78uVCr0fdYpQKCy8vsG2bduQlZWFkiVLytqkUim0tbWRlJSkcATq01+4EokEI0eOhIuLS67jlylTJlfbB25ubnB1dZVrMzbNnzux/v77DPz9A2TPxeIiAABLS3NER8fK2i0szBATG5+r/6dcJ43EjOnj0a59X9y/HyRrt7GpjeLFzeF//aSsTUtLC/b2jTF2zGDoFSsPyb/W5hR0qUlpyM7KhuEnIwoGpoZI/WQU7IPkuGSF8VmZWXidlIZSVcrAonRxTN32ccpapJHzNbYn9BBcW45FbHg0nGcOxtENh3Dt78sAgJfBYTAvZY4uY3oW2sJLkpoCaXYWND4Z3dIwNIY0KemLj5P5+CHErdrmatft5QTdvs5InTEZ2c+ffXe+BUl6UhokWdm5Rrf0TA1zjYJ9jeaTe+HBX1dwd58PACAuOALaemJ08BiCK2uPfldRR4XfjzpFKBQWXl8pKysLu3btwu+//462beV/iPfs2RNeXl6oVq0aTpw4IffarVu35J7b2Njg4cOHqFTp6xY9i8ViiMViubb8mmZ8/foNXr+WX+wfFRUDx9bNERiYc0edtrY2mts3htvMxUqPNdl1FGa6TUDHTs64fUd+xOHChcuoU6+VXNvWLSsQHByKZcv/KFRFFwBkZ2bh+f1QWNvXxa3TN2Ttte3r4vaZGwr7PL0TDBtH+VFSa/u6eHY/BNlZ2YgMjcDUNvJFep8pztAtpoud7luREJVT+BbRLQKp5JMiP1sCDY1CvJ1EVhaynj6Bto0t3l/9OGWqbWOL99cuf/FhtCpWhiQxQa5Nt1df6PYbgNSZU5H1NFiwlAsKSWY2ou8/R3n7Wnhy+uPPoPL2tfDkzLdPqWrpFoH0k+9LabYEEIn+P7L7zYcm+uGx8PpKx48fR1JSEoYOHQpDQ0O513r16oVt27bh8OHDWLFiBaZPn46hQ4ciMDBQdtfjhyJp+vTpaNy4McaOHYvhw4ejaNGiCAoKwtmzZ7F27VpVn9YXW7N2K2ZMH4+nIc8REvIcM6aPR3r6W/y57y9ZzHbP1YiMjMKs2b8ByJlenO8+Ff0HjsOLsJcoXtwcQE5h9+ZNOl6/foOHD+V/6aW/SUdCQlKu9sLin61HMXblRDy7F4Ind4LR+ue2MLMywzmv0wCAvtP6w9jSFBtcVwMAznmdQttBHdF/zi+48OdZVLGpipZOjljrsgIAkJmRiYgn8rf2p6fmFMX/br9z7ha6jeuFhMg4vHzyEuVqlkfHYV3gs/+8Kk4737w9vB/6U2ch60kwsoIeQqdjZ2haWODdP8cAAHq/DIeGmTleL8v5A0Cney9IoqORFfYcIm1tiFu1gdi+BVIXzJYdU7f3z9AbOARpSxYiOyZatl5M+vYt8E7x3XyFkf/Wk/hp5WhE3XuGV3dCUPfnljCwMkWAV87XhMO0PtC3NMZx102yPhY1ckbdixQVQ89UHxY1yiA7MwsJTyMBACHnAtBwWAfEPAxDZGAojMsWR/PJvfD07J1chf9/RXr6W4RHRMqev4qMweMnoTA00EcJS+XbnvxoONWoHAuvr7Rt2zY4OjrmKrqAnBGvxYsXIykpCQcPHsTkyZOxevVq2NnZYdasWRg9erRstMra2hq+vr6YNWsW7O3tIZVKUbFiRTg5Oan6lL7KsuXroaurg3VrFsPY2BD+/gHo0Kmf3MhYmdJWcqNUo0YOglgsxgHvLXLHWrDwdyxYuEJluavS9eNXoG9sgB4uTjCyMMbLJ+FYMngh4l/FAQCMLExgZmUui497GYulgxdiwNwhaDugI5JiE7HTfSv8T177qvfdMW8z+kx2xi8LR8LQzBBJMUk4v/c0Dq3eL+j5qdp734t4o28IPeeB0DAxRXbYc6TMng5JbM6WGhomptD8155eIi1tFB0xGhqm5pC+z0B22AukzJ6GzJsfRxx1OneFqEgRGMxZKPde6bu3I33PDpWclyoEHb8BXWN9NHXpjmIWRoh7EoH9g5ch9VXO6F8xCyMYfLK/3NCTH0ewS1hXQM1uTZH8Mg4bmuXc2HFl7RFAKoXDlN4oZmmM9IRUhJwPgO+yAyo7r4LmweOnGDJ+uuz50rWbAQBdOzhi0ezJ6kpLLTjVqJxI+qWroum7LFq0CBs3bsTLly8/H/yVtIqU/HwQKdS7RIPPB1Ge1lb78jVWJG/L49LqTqHQmnJ7gbpTKNS0zfJ3v7XypnUEO9bzhLuCHaug4IhXPlm/fj0aNGgAU1NTXLlyBcuWLSvQe3QRERFR/mPhlU+ePn2KX3/9FYmJiShTpgwmT54MNze3z3ckIiIqxCScalSKhVc+WblyJVauXKnuNIiIiFSKK5iU40cGEREREakIR7yIiIhIMJxqVI6FFxEREQmGU43KcaqRiIiISEU44kVERESC4c71yrHwIiIiIsFw53rlWHgRERGRYLjGSzmu8SIiIiJSEY54ERERkWC4nYRyLLyIiIhIMJxqVI5TjUREREQqwhEvIiIiEgy3k1COhRcREREJhlONynGqkYiIiEhFWHgRERGRYCSQCvbIL0lJSRgwYAAMDQ1haGiIAQMGIDk5Oc/4zMxMTJ8+HbVr10bRokVhZWWFgQMHIjIy8qvfm4UXERERCUYqlQr2yC/9+vVDYGAgTp06hVOnTiEwMBADBgzIMz49PR137tzBnDlzcOfOHRw+fBhPnjxBly5dvvq9ucaLiIiICqSMjAxkZGTItYnFYojF4m8+ZlBQEE6dOoXr16+jUaNGAIAtW7bAzs4OwcHBqFq1aq4+hoaGOHv2rFzb2rVr0bBhQ4SHh6NMmTJf/P4c8SIiIiLBSKRSwR4eHh6y6cAPDw8Pj+/K79q1azA0NJQVXQDQuHFjGBoa4urVq198nJSUFIhEIhgZGX3V+3PEi4iIiAQj5Idku7m5wdXVVa7te0a7ACA6OhoWFha52i0sLBAdHf1Fx3j37h1mzJiBfv36wcDA4KvenyNeREREJBghR7zEYjEMDAzkHnkVXu7u7hCJREoft27dAgCIRKJc/aVSqcL2T2VmZqJv376QSCRYv379V18fjngRERFRoTdu3Dj07dtXaUy5cuVw7949xMTE5HotLi4OxYsXV9o/MzMTffr0wfPnz3HhwoWvHu0CWHgRERGRgNS1gaqZmRnMzMw+G2dnZ4eUlBT4+/ujYcOGAIAbN24gJSUFTZo0ybPfh6Lr6dOnuHjxIkxNTb8pT041EhERkWCkAv4vP1SvXh3t27fH8OHDcf36dVy/fh3Dhw9H586d5e5orFatGv766y8AQFZWFnr16oVbt27By8sL2dnZiI6ORnR0NN6/f/9V78/Ci4iIiP5TvLy8ULt2bbRt2xZt27aFtbU1du/eLRcTHByMlJQUAEBERASOHTuGiIgI1K1bFyVKlJA9vuZOSIBTjURERCSgwvBZjSYmJtizZ4/SmH+fR7ly5QQ7LxZeREREJJjCUHipE6caiYiIiFSEI15EREQkGI53KSeSckyQ8lFGRgY8PDzg5ub23bsN/9fw2n07Xrvvw+v37Xjt6HNYeFG+Sk1NhaGhIVJSUr5po7n/Ml67b8dr9314/b4drx19Dtd4EREREakICy8iIiIiFWHhRURERKQiLLwoX4nFYsybN4+LTL8Br92347X7Prx+347Xjj6Hi+uJiIiIVIQjXkREREQqwsKLiIiISEVYeBERERGpCAsvIiIiIhVh4UVERESkIiy8iIj+w7Kzs+Hr64ukpCR1p0L0n8DCiwTn5+eH/v37w87ODq9evQIA7N69G5cvX1ZzZkT0KU1NTbRr1w7JycnqTqVQe//+PYKDg5GVlaXuVKiA01J3AvRjOXToEAYMGABnZ2cEBAQgIyMDAJCWlobFixfjxIkTas6w4MvKyoKPjw9CQ0PRr18/6OvrIzIyEgYGBihWrJi60yvwnjx5Ah8fH8TGxkIikci9NnfuXDVlVbDVrl0bz549Q/ny5dWdSqGTnp6O8ePHY+fOnQByvv4qVKgAFxcXWFlZYcaMGWrOkAoabqBKgqpXrx4mTZqEgQMHQl9fH3fv3kWFChUQGBiI9u3bIzo6Wt0pFmhhYWFo3749wsPDkZGRIfshPnHiRLx79w4bN25Ud4oF2pYtWzB69GiYmZnB0tISIpFI9ppIJMKdO3fUmF3BdebMGUyfPh0LFy5E/fr1UbRoUbnXDQwM1JRZwTdhwgRcuXIFq1atQvv27XHv3j1UqFABx44dw7x58xAQEKDuFKmA4YgXCSo4OBjNmzfP1W5gYMCpjC8wYcIE2Nra4u7duzA1NZW1d+/eHcOGDVNjZoXDr7/+ikWLFmH69OnqTqVQad++PQCgS5cucsWqVCqFSCRCdna2ulIr8I4cOQJvb280btxY7trVqFEDoaGhasyMCioWXiSoEiVKICQkBOXKlZNrv3z5MipUqKCepAqRy5cv48qVKyhSpIhce9myZWXr5ShvSUlJ6N27t7rTKHQuXryo7hQKrbi4OFhYWORqf/PmjVwhRvQBCy8S1MiRIzFhwgR4enpCJBIhMjIS165dw5QpU7i+5gtIJBKFowsRERHQ19dXQ0aFS+/evXHmzBmMGjVK3akUKg4ODupOodBq0KAB/vnnH4wfPx4AZMXWli1bYGdnp87UqIBi4UWCmjZtGlJSUtCyZUu8e/cOzZs3h1gsxpQpUzBu3Dh1p1fgtWnTBqtWrcLmzZsB5PwQf/36NebNm4eOHTuqObuCr1KlSpgzZw6uX7+O2rVrQ1tbW+51FxcXNWVW8Pn5+WHTpk149uwZDhw4gJIlS2L37t0oX748mjVrpu70CiwPDw+0b98ejx49QlZWFlavXo2HDx/i2rVr8PX1VXd6VABxcT3li/T0dDx69AgSiQQ1atTg3XhfKDIyEi1btoSmpiaePn0KW1tbPH36FGZmZrh06ZLCKQ36SNldeSKRCM+ePVNhNoXHv+9G3r17Nx49eoQKFSpg/fr1OH78OO9G/oz79+9j+fLluH37NiQSCWxsbDB9+nTUrl1b3alRAcTCiwSVkpKC7OxsmJiYyLUnJiZCS0uLd0d9gbdv32Lfvn1yP8SdnZ2hq6ur7tToB8W7kYlUh4UXCapDhw746aefMGbMGLn2jRs34tixY/zLmVTi/fv3eP78OSpWrAgtLa6o+Bw9PT08evQI5cqVkyu8nj17hho1auDdu3fqTrHASk1NVdguEokgFotz3ShDxJ3rSVA3btxAy5Ytc7W3aNECN27cUENGhYuHhwc8PT1ztXt6emLJkiVqyKhwSU9Px9ChQ6Gnp4eaNWsiPDwcQM7art9++03N2RVcH+5G/hTvRv48IyMjGBsb53oYGRlBV1cXZcuWxbx583Jt5kv/XSy8SFAZGRkKPzIjMzMTb9++VUNGhcumTZtQrVq1XO01a9bk5qlfwM3NDXfv3oWPjw90dHRk7Y6OjvD29lZjZgXbh7uRb9y4Ibsb2cvLC1OmTMk1ek3yduzYASsrK8ycORNHjhzBX3/9hZkzZ6JkyZLYsGEDRowYgTVr1rDwp4+kRAJycHCQjhs3Llf7mDFjpM2aNVNDRoWLWCyWPnv2LFd7aGioVCwWqyGjwqVMmTLSa9euSaVSqbRYsWLS0NBQqVQqlT59+lSqr6+vztQKvJkzZ0p1dXWlIpFIKhKJpDo6OtLZs2erO60Cr1WrVlJvb+9c7d7e3tJWrVpJpVKpdNeuXdKqVauqOjUqoLj4gQS1aNEiODo64u7du2jdujUA4Pz587h58ybOnDmj5uwKvtKlS+PKlSu57s67cuUKrKys1JRV4cHNLL/dokWLMGvWLN6N/JWuXbumcDS6Xr16uHbtGgCgWbNmsmlvIk41kqCaNm2Ka9euoXTp0ti/fz/+/vtvVKpUCffu3YO9vb260yvwhg0bhokTJ2L79u0ICwtDWFgYPD09MWnSJAwfPlzd6RV4Hzaz/ICbWX4dPT092NraomHDhiy6vlCpUqWwbdu2XO3btm1D6dKlAQAJCQkwNjZWdWpUQHHEiwRXt25deHl5qTuNQmnatGlITEzEmDFj8P79ewCAjo4Opk+fDjc3NzVnV/BxM8tv8+bNG/z22284f/48YmNjcy0E5/5neVu+fDl69+6NkydPokGDBhCJRLh58yaCgoJw6NAhAMDNmzfh5OSk5kypoOB2EvTdUlNTZftz5XVr9Qfcx+vLvH79GkFBQdDV1UXlypUhFovVnVKhwc0sv97PP/8MX19fDBgwACVKlMg1LTthwgQ1ZVY4hIWFYcOGDXjy5AmkUimqVauGkSNHIjk5GXXr1lV3elTAsPCi76apqYmoqChYWFhAQ0ND4VoaqVQKkUik8HMIiUi9jIyM8M8//6Bp06bqTqXQS05OhpeXFzw9PREYGMifeZQLpxrpu124cEG2U/3FixfVnE3h06NHD+zYsQMGBgbo0aOH0tjDhw+rKKvCqWXLlujfvz969eoFQ0NDdadTaBgbG+f6tAn6OhcuXICnpycOHz6MsmXLomfPnti6dau606ICiIUXfTcHBwcAQFZWFnx8fDBkyBDZolL6PENDQ9koIYuF71O7dm3Mnj0b48aNQ8eOHTFgwAB07NiRu4d/xsKFCzF37lzs3LkTenp66k6n0IiIiMCOHTvg6emJN2/eoE+fPsjMzMShQ4dQo0YNdadHBRSnGklQ+vr6uH//PsqVK6fuVAodqVSK8PBwmJub85ffd5BIJDh37hz27t2Lv/76C5qamujVqxecnZ1lfySQvHr16iE0NBRSqRTlypWDtra23Ot37txRU2YFV8eOHXH58mV07twZzs7OaN++PTQ1NaGtrY27d++y8KI8sfAiQXXr1g3dunXD4MGD1Z1KoSORSKCjo4OHDx+icuXK6k7nh/Du3Tv8/fffWLRoEe7fv8/1NnmYP3++0tfnzZunokwKDy0tLbi4uGD06NFy368svOhzONVIgurQoQPc3Nzw4MED1K9fH0WLFpV7vUuXLmrKrODT0NBA5cqVkZCQwMJLANHR0di3bx/27NmDe/fuoUGDBupOqcBiYfX1/Pz84OnpCVtbW1SrVg0DBgzglhH0RTjiRYLS0Mh7T17e1fh5//zzD3777Tds2LABtWrVUnc6hU5qaioOHTqEvXv3wsfHBxUqVEC/fv3g7OyMSpUqqTu9AmvWrFlo0aIFmjZtymnur5Seno59+/bB09MT/v7+yM7OxooVKzBkyBDo6+urOz0qgFh4ERUgxsbGSE9PR1ZWFooUKQJdXV251xMTE9WUWeGgq6sLY2Nj9OnTB87Ozhzl+kLt27fH1atXkZGRARsbG7Ro0QIODg5o1qwZd7D/CsHBwdi2bRt2796N5ORktGnTBseOHVN3WlTAsPAiwYSFheHMmTPIysqCg4MD1zh8gx07dij9TMFBgwapMJvC58yZM3B0dFQ68kqKZWdnw9/fH76+vvDx8cG1a9fw9u1b2NjY4Pr16+pOr1DJzs7G33//DU9PTxZelAsLLxLEpUuX0LFjR6SnpwPIWXi6c+dO/Pzzz2rOrHDJyMhAVlZWrrVxRKoSHBwMHx8fnDt3DkeOHIGRkRHi4uLUnRbRD4OFFwnCwcEBBgYG2LRpE3R1deHm5oZ//vkHL1++VHdqhUJ8fDwGDRqEM2fOQCKRoFGjRtizZw8qVKig7tQKPBsbG5w/fx7Gxsb4X3v3HhRl+b4B/Nrl4IJ4AkREEQScUAGPWNgoJGigThKVMh5GHTOJUhuUgEHUL+IxUgtTyUbHcphBzWAsxkODLGoZFOqSmJiAIgMJgqICCsv+/nDa5LcLmbzus4vXZ8YZed794xoG9fZ+n+d+Ro0a1WHHkGMR9Nu1axeUSiWUSiXUajUmTJgAf39/BAQEwMfHR3Q8oi6FhRdJwtbWFrm5udoN4Q8ePEDPnj1RU1ODPn36CE5n/BYvXoyjR49i2bJlUCgU2L17N1xcXHDy5EnR0Yze//73P0RHR8Pa2ppjEZ6RXC5H3759sWLFCkRERPBOVaLniIUXSUIul6OqqgoODg7atR49ekClUmHw4MECk5mGQYMGYffu3Zg6dSoA4I8//oCXlxcaGxt1hlmSfmq1GmfOnIGPjw+L/f8oIyMDubm5yMnJQVFREUaMGIGAgAAEBARgwoQJ3GBPJCEWXiQJuVze5s5GABg/fjwOHjyIgQMHatf42kI/c3NzlJeXo3///to1a2trXL58GS4uLgKTmRaFQoHLly+z2O+Eu3fv4vTp0zh8+DDS0tIgk8nw8OFD0bGIugwOUCXJBAYG4v/X8dOnT4dMJoNGo+Ecrw5oNBqYm7f942hubo7W1lZBiUyTt7c3SkpKWHg9g9raWu2JxpycHPz++++ws7PjNUtEEmPHiyRx/fr1p/ocuzf6yeVyeHl5tSm+VCoVPD0921zwzM3hHTtx4gRiYmKwbt06vTcncO+Sfj4+Prh06RLs7OwwceJE7WtGDvElkh4LLxIiMjISiYmJsLe3Fx3FKPzbpvC/cXN4x56c3/Xk6UZ2XDu2Y8cOvPbaa3BwcIBcLoednZ3oSERdFgsvEqJnz564cOECxyU8o7Nnz2Ls2LHo1q2b6ChGRalUdvicr8103blzB/Hx8UhPT0ddXR2AxzcohIeHIykpCb179xYbkKiLYeFFQvTo0QMXL15k4fWMWLiSFGpra+Hn54eKigrMmTMHQ4cOhUajweXLl5GWlgZnZ2f89NNPPCVKJCFuricyQfz/kn5Xr15FZmYmysrKIJPJ4ObmhhkzZrBAbUdiYiIsLS1x7do19OvXT+fZlClTkJiYiG3btglKSNT1sONFQrDj1Tn8/unauHEjVq9ejdbWVjg4OECj0aC6uhpmZmbYsGEDVq5cKTqi0XF1dUVqaipef/11vc+PHTuGiIgIlJWVGTYYURfGm2SJyOSdOnUKq1atQnx8PGpqalBZWYmqqipUV1cjNjYWsbGxyM3NFR3T6FRWVmL48OHtPvfy8kJVVZUBExF1fXzVSEQmb/fu3Xj33Xexdu3aNuu2trZITExEVVUVdu3ahYkTJ4oJaKTs7e1RVlbWZsjxk0pLS3nCkUhi7HiREHPnzuVMpU7o6CLoF1FeXh7mzZvX7vN58+bh3LlzBkxkGoKDgxEfH49Hjx7pPHv48CESEhIQHBwsIBlR18U9XiQplUqld10mk0GhUGDQoEEcgSAB7vFqy9raGsXFxe12bm7evIkhQ4agsbHRwMmM282bN7VjST744AN4enoCAIqKirBz5048fPgQv/76K5ydnQUnJeo6WHiRpORyeYfdGAsLC8yaNQupqalQKBQGTGYaJk2ahCNHjujMTqqvr0doaCiys7PFBDNy+i5pf9Jff/0FJycnDlDVo7S0FJGRkThx4oT2tKxMJsPkyZOxY8cOeHh4CE5I1LWw8CJJZWZmIiYmBtHR0Rg3bhw0Gg3y8/Px6aefYs2aNWhpaUFsbCxmzZqF5ORk0XGNTnsFxK1btzBgwAA0NzcLSmbc5HI5kpKSYGNjo/f5vXv3sHr1ahZeHairq8PVq1cBAB4eHm0uvCci6bDwIkmNGzcO69at0zmefvz4cSQkJCAvLw8ZGRlYsWIFrl27Jiil8fn7Fe3IkSORnZ3d5h89tVqNY8eOITU1lcf62+Hq6vpU+95KS0sNkIaIqH081UiSKiws1HsRtouLCwoLCwE8Li4qKysNHc2ojRw5EjKZDDKZDJMmTdJ5bmVlhZSUFAHJTAMLUiIyFSy8SFKenp7YtGkTvvzyS1haWgIAmpubsWnTJu3G3YqKCp0p2S+60tJSaDQauLm5IS8vD3379tU+s7S0hIODA8zMzAQm7Fq8vb2RlZXFTeNEZHAsvEhSX3zxBd544w0MHDgQPj4+kMlkUKlUUKvV+P777wEAJSUliIyMFJzUuPzdJWxtbRWc5MVQVlbG/XJEJAT3eJHk7t+/jwMHDqC4uBgajQaenp6YPXs2evToITqaSSguLkZOTg5u3bqlU4itXr1aUKquheM4iEgUFl5ERmTPnj14//33YW9vD0dHxzYbxmUyGQoKCgSm6zpYeBGRKCy8SHLs2Dw7FxcXREZGIiYmRnSULo2FFxGJwj1eJKl/69iw8OpYXV0d3nnnHdExiIjoOWHHiyTFjk3nLFq0CL6+voiIiBAdpUtjx4uIRGHHiyTFjk3neHh4ICEhAefOnYO3tzcsLCzaPF+2bJmgZKbrzp07OlcwpaamcqQJEQnBjhdJih2bzhk8eHC7z2QyGUpKSgyYxvRs3rwZrq6umDVrFgBg5syZ+Pbbb+Ho6IisrCyMGDFCcEIietGx8CJJbdy4EVu3bsW0adPYsSGDc3Nzw4EDBzB+/HicPHkSM2fORHp6Og4ePIgbN27gxIkToiMS0QuOhRdJih0baTx69AilpaVwd3eHuTl3BDwtKysrFBcXw9nZGcuXL0dTUxNSU1NRXFyMl19+GXV1daIjEtELjn+jk6R4CXHnNDQ0YOnSpdi/fz+Ax6M53NzcsGzZMjg5OSE2NlZwQuPWp08flJeXw9nZGceOHUNSUhIAQKPRQK1WC05HRATIRQcgon/ExcXh4sWLyMnJgUKh0K4HBQUhPT1dYDLTEBYWhtmzZ2Py5Mm4ffs2QkJCAAAXLlyAh4eH4HREROx4kQSioqKwbt06dO/eHVFRUR1+duvWrQZKZZoyMjKQnp6OV155pc0MtGHDhuHatWsCk5mGbdu2wdXVFeXl5diyZQtsbGwAAJWVlbwflIiMAgsv6rTz589rLxw+f/58u597spAg/aqrq+Hg4KCz/uDBA37/noKFhQVWrlyps/7RRx8ZPgwRkR4svKjTTp06pff39N/5+vrihx9+wNKlSwH8U6zu2bMHfn5+IqOZjIqKCpw9e1bvlVU8VUtEorHwIjIiGzduRHBwMIqKitDS0oLPPvsMly5dws8//wylUik6ntHbt28fIiIiYGlpCTs7O50rq1h4EZFoHCdBnRYWFvbUnz1y5MhzTNI1FBYWIjk5Gb/99htaW1sxevRoxMTEwNvbW3Q0o+fs7IyIiAjExcVBLufZISIyPux4Uaf16tVLdIQuxdvbWztOgv6bhoYGhIeHs+giIqPFjheRESkoKICFhYW2u5WZmYl9+/Zh2LBhWLt2LSwtLQUnNG4ff/wxbG1tOe+MiIwWCy8iI+Lr64vY2Fi89dZbKCkpwbBhwxAWFob8/HxMmzYN27dvFx3RqKnVakyfPh2NjY16r6ziOBMiEo2vGqnTRo0a9dSjDgoKCp5zGtNWXFyMkSNHAgAOHToEf39/pKWl4ezZswgPD2fh9S82bNiA48eP46WXXgIAnc31RESisfCiTgsNDRUdocvQaDTaEQg//vgjpk+fDuDxpvGamhqR0UzC1q1bsXfvXixYsEB0FCIivfiqkciITJo0Cc7OzggKCsKiRYtQVFQEDw8PKJVKzJ8/H2VlZaIjGjVHR0ecPn0aQ4YMER2FiEgvHv0hyd25cwdfffUV4uLiUFtbC+DxK8aKigrByYzf9u3bUVBQgA8//BDx8fHa+wUPHz6M8ePHC05n/JYvX46UlBTRMYiI2sWOF0lKpVIhKCgIvXr1QllZGa5cuQI3NzckJCTg+vXr+Prrr0VHNElNTU0wMzPT2SxObb355pvIzs6GnZ0dhg8frvP94hw5IhKNHS+SVFRUFBYsWICrV69CoVBo10NCQpCbmyswmenQ1zEsKirCrVu3BCczfr1790ZYWBj8/f1hb2+PXr16aX8RERkDbq4nSeXn5yM1NVVnfcCAAaiqqhKQyLSoVCoEBgaid+/eKCsrw+LFi2Fra4vvvvuOHcMOJCcnY+XKldi3b5/e5/X19ZgyZYqBUxER6WLHiySlUChQX1+vs37lyhX07dtXQCLTEhUVhYULF7Jj+B8lJCS0W3Tdv38fwcHBen8uiYgMjYUXSWrGjBlITExEc3MzgMezk27cuKEdCkody8/Px5IlS3TW2THs2DfffIPIyEhkZGS0Wb9//z6mTJmC27dvIzs7W0w4IqInsPAiSSUnJ6O6uhoODg5obGyEv78/3N3dYWNjg/Xr14uOZ/TYMXw2b7/9NlJSUjB79mycOnUKwD+drpqaGuTk5MDR0VFwSiIinmqk5yQ7OxsFBQVobW3FmDFjEBgYKDqSSXjvvfdQXV2NgwcPwtbWFiqVCmZmZggNDcXEiRM5uf5fbNmyBevXr0dmZiYSEhJQWVkJpVKJAQMGiI5GRASAhRdJ5JdffkFtbS1CQkK0a/v378eaNWvQ0NCA0NBQpKSkoFu3bgJTGr/6+npMnToVly5dwr179+Dk5ISqqir4+fkhKysL3bt3Fx3R6MXFxWHLli1wdXWFUqnEwIEDRUciItJi4UWSCAkJQUBAAGJiYgAAhYWFGDNmDObPn4+hQ4fik08+wZIlS7B27VqxQU3Ekx3D0aNHIygoSHQkoxYWFtbm66ysLIwYMUKn08U5XkQkGgsvkkT//v1x9OhRjB07FgAQHx8PpVKJM2fOAHh84fOaNWtQVFQkMqZRa2lpgUKhwIULF+Dl5SU6jklZuHDhU32uvZOPRESGwjleJIm6ujr069dP+7VSqURwcLD2a19fX5SXl4uIZjLMzc3h4uICtVotOorJYUFFRKaCpxpJEv369UNpaSkA4NGjRygoKICfn5/2+b1793jdzVNYtWpVm4n1RETUtbDjRZIIDg5GbGwsNm/ejIyMDFhbW2PChAna5yqVCu7u7gITmobPP/8cf/75J5ycnODi4qKzmb6goEBQMiIikgILL5JEUlKS9o48Gxsb7N+/H5aWltrne/fu5ZUtTyE0NBQymQzceklE1DVxcz1J6u7du7CxsYGZmVmb9draWtjY2LQpxugfDQ0NiI6ORkZGBpqbmxEYGIiUlBTY29uLjkZERBJi4UVkBKKjo7Fz507MmTMHVlZWSEtLQ0BAAA4dOiQ6GhERSYiFF5ERcHd3x/r16xEeHg4AyMvLw6uvvoqmpiad7iEREZkuFl5ERsDS0hKlpaVtBn5aWVmhuLgYzs7OApMREZGUOE6CyAio1Wqd/W/m5uZoaWkRlIiIiJ4HnmokMgIajQYLFixoc5dlU1MTIiIi2oyU4JU3RESmjYUXkRGYP3++ztrcuXMFJCEioueJe7yIiIiIDIR7vIiIiIgMhIUXERERkYGw8CIiIiIyEBZeRERERAbCwouIiIjIQFh4ERERERkICy8iIiIiA/k/knLJbAWB79IAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Korrelaatiot\n",
    "sns.heatmap(df.corr(numeric_only=True), annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "papermill": {
     "duration": 0.061072,
     "end_time": "2020-12-21T20:34:30.017883",
     "exception": false,
     "start_time": "2020-12-21T20:34:29.956811",
     "status": "completed"
    },
    "tags": []
   },
   "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>Selling_Price</th>\n",
       "      <th>Present_Price</th>\n",
       "      <th>Kms_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Seller_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.35</td>\n",
       "      <td>5.59</td>\n",
       "      <td>27000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.75</td>\n",
       "      <td>9.54</td>\n",
       "      <td>43000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.25</td>\n",
       "      <td>9.85</td>\n",
       "      <td>6900</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.85</td>\n",
       "      <td>4.15</td>\n",
       "      <td>5200</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.60</td>\n",
       "      <td>6.87</td>\n",
       "      <td>42450</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Manual</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Selling_Price  Present_Price  Kms_Driven Fuel_Type Seller_Type  \\\n",
       "0           3.35           5.59       27000    Petrol      Dealer   \n",
       "1           4.75           9.54       43000    Diesel      Dealer   \n",
       "2           7.25           9.85        6900    Petrol      Dealer   \n",
       "3           2.85           4.15        5200    Petrol      Dealer   \n",
       "4           4.60           6.87       42450    Diesel      Dealer   \n",
       "\n",
       "  Transmission  Owner  Age  \n",
       "0       Manual      0    6  \n",
       "1       Manual      0    7  \n",
       "2       Manual      0    3  \n",
       "3       Manual      0    9  \n",
       "4       Manual      0    6  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Useimmissa koneoppimisen malleissa ei saa olla selittävinä muuttujina kategorisia muuttujia. Kategoriset muuttujat voidaan kuitenkin muuntaa dikotomisiksi muuttujiksi, jotka kelpaavat selittäviksi muuttujiksi. Pandas-kirjaston **get_dummies**-funktio muuntaa kategoriset muuttujat dikotomisiksi.\n",
    "\n",
    "Esimerkiksi **Fuel_Type**-muuttuja voidaan muuntaa kolmeksi dikotomiseksi muuttujaksi:\n",
    "\n",
    "* **Fuel_Type_CNG**, joka saa arvon 1 (True), jos polttoaine on CNG ja muutoin arvon 0 (False)\n",
    "* **Fuel_Type_Diesel**, joka saa arvon 1 (True), jos polttoaine on Diesel ja muutoin arvon 0 (False)\n",
    "* **Fuel_Type_Petrol**, joka saa arvon 1 (True), jos polttoaine on Petrol ja muutoin arvon 0 (False)\n",
    "  \n",
    "Käytännössä yksi dikotomisista muuttujista voidaan jättää pois menettämättä informaatiota: vaikka Fuel_Type_CNG-muuttuja jätetään pois, niin Fuel_Type_Diesel = 0 ja Fuel_Type_Petrol = 0 tarkoittaa CNG:tä.  Yhden dikotomisen muuttujan poisjättäminen hoituu parametrilla **drop_first=True**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "papermill": {
     "duration": 0.060741,
     "end_time": "2020-12-21T20:34:30.122703",
     "exception": false,
     "start_time": "2020-12-21T20:34:30.061962",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Kategoriset muuttujat dummy-muuttujiksi\n",
    "df = pd.get_dummies(data=df, drop_first=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "papermill": {
     "duration": 0.061437,
     "end_time": "2020-12-21T20:34:30.229101",
     "exception": false,
     "start_time": "2020-12-21T20:34:30.167664",
     "status": "completed"
    },
    "tags": []
   },
   "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>Selling_Price</th>\n",
       "      <th>Present_Price</th>\n",
       "      <th>Kms_Driven</th>\n",
       "      <th>Owner</th>\n",
       "      <th>Age</th>\n",
       "      <th>Fuel_Type_Diesel</th>\n",
       "      <th>Fuel_Type_Petrol</th>\n",
       "      <th>Seller_Type_Individual</th>\n",
       "      <th>Transmission_Manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.35</td>\n",
       "      <td>5.59</td>\n",
       "      <td>27000</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.75</td>\n",
       "      <td>9.54</td>\n",
       "      <td>43000</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.25</td>\n",
       "      <td>9.85</td>\n",
       "      <td>6900</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.85</td>\n",
       "      <td>4.15</td>\n",
       "      <td>5200</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.60</td>\n",
       "      <td>6.87</td>\n",
       "      <td>42450</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Selling_Price  Present_Price  Kms_Driven  Owner  Age  Fuel_Type_Diesel  \\\n",
       "0           3.35           5.59       27000      0    6             False   \n",
       "1           4.75           9.54       43000      0    7              True   \n",
       "2           7.25           9.85        6900      0    3             False   \n",
       "3           2.85           4.15        5200      0    9             False   \n",
       "4           4.60           6.87       42450      0    6              True   \n",
       "\n",
       "   Fuel_Type_Petrol  Seller_Type_Individual  Transmission_Manual  \n",
       "0              True                   False                 True  \n",
       "1             False                   False                 True  \n",
       "2              True                   False                 True  \n",
       "3              True                   False                 True  \n",
       "4             False                   False                 True  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.04556,
     "end_time": "2020-12-21T20:34:30.319499",
     "exception": false,
     "start_time": "2020-12-21T20:34:30.273939",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Mallien sovittaminen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "papermill": {
     "duration": 0.05552,
     "end_time": "2020-12-21T20:34:30.422442",
     "exception": false,
     "start_time": "2020-12-21T20:34:30.366922",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Selittävät muuttujat\n",
    "X = df.drop('Selling_Price', axis=1)\n",
    "\n",
    "# Selitettävä/ennustettava muuttuja\n",
    "y = df['Selling_Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "papermill": {
     "duration": 0.07607,
     "end_time": "2020-12-21T20:34:30.786978",
     "exception": false,
     "start_time": "2020-12-21T20:34:30.710908",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Jako opetus- ja testidataan\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.045748,
     "end_time": "2020-12-21T20:34:31.280392",
     "exception": false,
     "start_time": "2020-12-21T20:34:31.234644",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Lineaarinen regressio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "papermill": {
     "duration": 0.535588,
     "end_time": "2020-12-21T20:34:31.862166",
     "exception": false,
     "start_time": "2020-12-21T20:34:31.326578",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opetusdatan selityskerroin 0.888\n",
      "Testidatan selityskerroin 0.842\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "malli = LinearRegression()\n",
    "\n",
    "# Tässä hyödynnän aiemmin määriteltyä mallinna-funktiota\n",
    "lr = mallinna(malli)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.050885,
     "end_time": "2020-12-21T20:34:36.773959",
     "exception": false,
     "start_time": "2020-12-21T20:34:36.723074",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Satunnaismetsä"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opetusdatan selityskerroin 0.985\n",
      "Testidatan selityskerroin 0.954\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "malli = RandomForestRegressor()\n",
    "rfr = mallinna(malli)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.053049,
     "end_time": "2020-12-21T20:41:00.804511",
     "exception": false,
     "start_time": "2020-12-21T20:41:00.751462",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Gradient Boosting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opetusdatan selityskerroin 0.997\n",
      "Testidatan selityskerroin 0.956\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "malli = GradientBoostingRegressor()\n",
    "gbr = mallinna(malli)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ennusteiden laskeminen\n",
    "\n",
    "Kokeillaan kahden auton hintojen ennustamista. Lasken ennusteet gradienttitehostusta käyttäen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gradienttitehostusregression hintaennusteet:  [4.93561603 5.24532615]\n"
     ]
    }
   ],
   "source": [
    "# Uuden datan muodostaminen\n",
    "df_new = pd.DataFrame([[6, 40000, 0, 4, 0, 1, 0, 0], [6, 80000, 0, 4, 1, 1, 0, 0]],\n",
    "                     columns=['Present_Price', 'Kms_Driven', 'Owner', 'Age', 'Fuel_Type_Diesel',\n",
    "                     'Fuel_Type_Petrol', 'Seller_Type_Individual', 'Transmission_Manual'])\n",
    "\n",
    "print('Gradienttitehostusregression hintaennusteet: ', gbr.predict(df_new))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  },
  "papermill": {
   "duration": 496.115101,
   "end_time": "2020-12-21T20:42:36.266794",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2020-12-21T20:34:20.151693",
   "version": "2.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}