Flight booking project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "656ce9db",
   "metadata": {},
   "source": [
    "# FLIGHT BOOKING PREDICTION"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1da7204",
   "metadata": {},
   "source": [
    "IMPORTING LIBRARIES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9fb6a019",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcb3a329",
   "metadata": {},
   "source": [
    "IMPORTING THE DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "db9b6cfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>airline</th>\n",
       "      <th>flight</th>\n",
       "      <th>source_city</th>\n",
       "      <th>departure_time</th>\n",
       "      <th>stops</th>\n",
       "      <th>arrival_time</th>\n",
       "      <th>destination_city</th>\n",
       "      <th>class</th>\n",
       "      <th>duration</th>\n",
       "      <th>days_left</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>SG-8709</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Evening</td>\n",
       "      <td>zero</td>\n",
       "      <td>Night</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "      <td>5953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>SG-8157</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>AirAsia</td>\n",
       "      <td>I5-764</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "      <td>5956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Vistara</td>\n",
       "      <td>UK-995</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Afternoon</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Vistara</td>\n",
       "      <td>UK-963</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0   airline   flight source_city departure_time stops  \\\n",
       "0           0  SpiceJet  SG-8709       Delhi        Evening  zero   \n",
       "1           1  SpiceJet  SG-8157       Delhi  Early_Morning  zero   \n",
       "2           2   AirAsia   I5-764       Delhi  Early_Morning  zero   \n",
       "3           3   Vistara   UK-995       Delhi        Morning  zero   \n",
       "4           4   Vistara   UK-963       Delhi        Morning  zero   \n",
       "\n",
       "    arrival_time destination_city    class  duration  days_left  price  \n",
       "0          Night           Mumbai  Economy      2.17          1   5953  \n",
       "1        Morning           Mumbai  Economy      2.33          1   5953  \n",
       "2  Early_Morning           Mumbai  Economy      2.17          1   5956  \n",
       "3      Afternoon           Mumbai  Economy      2.25          1   5955  \n",
       "4        Morning           Mumbai  Economy      2.33          1   5955  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"Flight_Booking.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0982bad",
   "metadata": {},
   "source": [
    "PERFORMING EDA PROCESS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5750bf6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>airline</th>\n",
       "      <th>flight</th>\n",
       "      <th>source_city</th>\n",
       "      <th>departure_time</th>\n",
       "      <th>stops</th>\n",
       "      <th>arrival_time</th>\n",
       "      <th>destination_city</th>\n",
       "      <th>class</th>\n",
       "      <th>duration</th>\n",
       "      <th>days_left</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>SG-8709</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Evening</td>\n",
       "      <td>zero</td>\n",
       "      <td>Night</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "      <td>5953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>SG-8157</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AirAsia</td>\n",
       "      <td>I5-764</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Early_Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "      <td>5956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vistara</td>\n",
       "      <td>UK-995</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Afternoon</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Vistara</td>\n",
       "      <td>UK-963</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Morning</td>\n",
       "      <td>zero</td>\n",
       "      <td>Morning</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Economy</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    airline   flight source_city departure_time stops   arrival_time  \\\n",
       "0  SpiceJet  SG-8709       Delhi        Evening  zero          Night   \n",
       "1  SpiceJet  SG-8157       Delhi  Early_Morning  zero        Morning   \n",
       "2   AirAsia   I5-764       Delhi  Early_Morning  zero  Early_Morning   \n",
       "3   Vistara   UK-995       Delhi        Morning  zero      Afternoon   \n",
       "4   Vistara   UK-963       Delhi        Morning  zero        Morning   \n",
       "\n",
       "  destination_city    class  duration  days_left  price  \n",
       "0           Mumbai  Economy      2.17          1   5953  \n",
       "1           Mumbai  Economy      2.33          1   5953  \n",
       "2           Mumbai  Economy      2.17          1   5956  \n",
       "3           Mumbai  Economy      2.25          1   5955  \n",
       "4           Mumbai  Economy      2.33          1   5955  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dropping column 'Unnamed'\n",
    "df = df.drop(columns = [\"Unnamed: 0\"])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "08572ed4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300153, 11)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "20dbbd27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 300153 entries, 0 to 300152\n",
      "Data columns (total 11 columns):\n",
      " #   Column            Non-Null Count   Dtype  \n",
      "---  ------            --------------   -----  \n",
      " 0   airline           300153 non-null  object \n",
      " 1   flight            300153 non-null  object \n",
      " 2   source_city       300153 non-null  object \n",
      " 3   departure_time    300153 non-null  object \n",
      " 4   stops             300153 non-null  object \n",
      " 5   arrival_time      300153 non-null  object \n",
      " 6   destination_city  300153 non-null  object \n",
      " 7   class             300153 non-null  object \n",
      " 8   duration          300153 non-null  float64\n",
      " 9   days_left         300153 non-null  int64  \n",
      " 10  price             300153 non-null  int64  \n",
      "dtypes: float64(1), int64(2), object(8)\n",
      "memory usage: 25.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fc5ae06f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\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>duration</th>\n",
       "      <th>days_left</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>300153.000000</td>\n",
       "      <td>300153.000000</td>\n",
       "      <td>300153.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12.221021</td>\n",
       "      <td>26.004751</td>\n",
       "      <td>20889.660523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.191997</td>\n",
       "      <td>13.561004</td>\n",
       "      <td>22697.767366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.830000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1105.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.830000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>4783.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11.250000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>7425.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>16.170000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>42521.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>49.830000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>123071.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            duration      days_left          price\n",
       "count  300153.000000  300153.000000  300153.000000\n",
       "mean       12.221021      26.004751   20889.660523\n",
       "std         7.191997      13.561004   22697.767366\n",
       "min         0.830000       1.000000    1105.000000\n",
       "25%         6.830000      15.000000    4783.000000\n",
       "50%        11.250000      26.000000    7425.000000\n",
       "75%        16.170000      38.000000   42521.000000\n",
       "max        49.830000      49.000000  123071.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0021ecf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "airline             0\n",
       "flight              0\n",
       "source_city         0\n",
       "departure_time      0\n",
       "stops               0\n",
       "arrival_time        0\n",
       "destination_city    0\n",
       "class               0\n",
       "duration            0\n",
       "days_left           0\n",
       "price               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking out missing values\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9012c5a",
   "metadata": {},
   "source": [
    "DATA VISUALIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ea465cf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,5))\n",
    "sns.lineplot(x = df[\"airline\"], y = df[\"price\"])\n",
    "plt.title(\"Airline vs Price\")\n",
    "plt.xlabel(\"Airline\")\n",
    "plt.ylabel(\"Price\");\n",
    "#this graph is showing that there is differnces in the flight ticket prices according to different airlines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b0177c0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='airline', ylabel='price'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,3))\n",
    "sns.barplot(x = \"airline\", y = \"price\", data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "84dea44a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5GsQtguFC0D4rHrFxrKBOXE9znMqEGbaIY/HKK7vZeWSYY8OFseOlqpYZUUoppS51GsQtgnQxmHGLuzYRJ3gLUjGXloRLoXL2bNwrruzGtYVv7joJgC1CQZMblFJKqUueBnGLYLRvaiJiE7HPvAVr25IUKmfPsjXFXV60pZN7nzlNulgloj1UlVJKKYUGcYtiuFABgiDOss603WpOuCQi9qSuDK+4spuK57Pz8BAR25pUV04ppZRSlx4N4hbBaJmQZNTBHtc7VURY356c1G5rbVsS1xaODhVwbItyzaemGapKKaXUJU2DuEUwfibOtuWs+1qTERxLzgrSbEtY3ZLgyFCQ3CBohqpSSil1qdMgbhGkC8FMXDxinzUTB+DYFmvbkqQnLJmuaU1wZDAI4gyaoaqUUkpd6jSIWwTpUhXHEqK2jW3JpPs7G6MI4I8r/rumLcFArkyhUsMSmZQAoZRSSqlLiwZxiyBTDPqmIkFnhomijk1Py9mtuNa2JgE4OlggYltky5rcoJRSSl3KNIhbBNlSGMTBWLHfiVY2x6l6Z1pxrWlLAHBkqEDEscgUtcyIUkopdSnTIG4R5MpVkhEbSzirxMh4iYhDZ2OUfDlYNu1MRYm5FkeHCri2Ranq4flmymuVUkopdfHTIG4R5MseDVEH1z73t39VS4JSWDPOEgmTG/LAaIaq7otTSimlLlUaxC0wzzfkyzUSMwjiGmMOqbhDMUxiWNN6psyIAcpVLTOilFJKXao0iFtgnm8oVD0SEfu8QZyIsL4tSaEa7H9b25pkpFAlXaxiIZP6rCqllFLq0qFB3ALzfJ98uUYyYuM6U++HG68lESHqWFRq/lhyw9GhAq72UFVKKaUuaRrELbBsqYZvIO46uNb5v/2WJaxrS5ItV1nbGgZxg3mijnVWCRKllFJKXVo0iFtgw2G3hpksp45qT0WxLaEp7pKM2hwZKuBYQqHi42uGqlJKKXVJ0iBugaXDvqlx1yYywyDOtS3WtCTIlmusbU1ydKiAiABGe6gqpZRSl6i6BXEislpE7hWR3SLylIi8Mzx+jYjcLyK7RGSniNw47pr3i8h+EdkjIi8bd/x6EXkivO9jEkQwiEhURO4Mjz8gIuvq9Xrmy3Ax7JsatXBmsCduVHMygjFmrIeqMSbIUNUyI0oppdQlqZ4zcTXgvcaYbcDNwDtEZDvwEeDPjDHXAH8cfk143+3A5cBtwCdExA4f6x+BO4BN4cdt4fG3AcPGmI3A3wIfruPrmRfpYjATl4w42FO03JpOzLUwwNq2BLlyjeFCFUtkrPyIUkoppS4tdQvijDG9xphHwttZYDfQQ1DirDE8rQk4Gd5+DfBFY0zZGHMI2A/cKCLdQKMx5j4T9KD6HPDacdd8Nrz9FeDFo7N0S9VI/syeOHuabg1TiTo2jiWsagnbbw3mcS2LbFkzVJVSSqlLkbMQTxIuc14LPAC8C/iuiPwVQRD57PC0HuD+cZcdD49Vw9sTj49ecwzAGFMTkTTQBgzU43XMh5HiaBDnzCqIA0jFXLobY0DQQ3X7ykay2kNVKaWUuiTVPbFBRBqArwLvMsZkgLcD7zbGrAbeDXx69NQpLjfnOH6uayaO4Y5w/93O/v7+2b6EeZUpzm0mDqAp7hKL2DTHXY4OFYjYFrlKlWCCUimllFKXkroGcSLiEgRwXzDGfC08/FZg9PaXgdHEhuPA6nGXryJYaj0e3p54/KxrRMQhWJ4dmjgOY8wnjTE7jDE7Ojo6LvRlXZB0sUrcDQI4a5Yrvw0xh5ofFP09OhhmqBrRDFWllFLqElTP7FQhmGXbbYz5m3F3nQReEN5+EbAvvH0XcHuYcbqeIIHhQWNML5AVkZvDx3wL8M1x17w1vP164IdmiU9LZUs1klEbA7OeiYu5QZ7HmtYER4cK4Qyc0R6qSiml1CWonnvingO8GXhCRHaFx/4Q+B/A34UzZyWCrFOMMU+JyJeApwkyW99hjBlNvXw78BkgDtwdfkAQJH5eRPYTzMDdXsfXMy+y5RoN0eDbPpvsVICYE8Tca1uTFKse/dkyji0UqzWacOd9rEoppZRauuoWxBljfsbUe9YArp/mmg8BH5ri+E7giimOl4A3XMAwF1yuXCMZDZIarFnOxDm2Rcy16Wk5k9ywdUWKbKnGiqZ6jFYppZRSS5V2bFhAvm8olGskI86MW25N1Bh36EqFQdxgAdfWMiNKKaXUpUiDuAXkGUO+4gV9U625fetTURfXtmhviHBkKE/EsciXapqhqpRSSl1iNIhbQJ5vKFRqJCIOjj23msTJqIOPYU3YQ9USwTfaQ1UppZS61GgQt4DKVY9S1ScRsYnMom/qeDHXAhNkqB4bKuD5wQycBnFKKaXUpUWDuAWULgWFfuMRe8574mKOjYiwtjVO1TOcSpcwBAGiUkoppS4dGsQtoOHRvqmuTWSOQZxlCcmozcrmOABHh4IeqpkwQFRKKaXUpUGDuAWUDltuxSI2EWfu3/rGuEtn6kyZkYhjkdMMVaWUUuqSokHcAkoXK8Bo39QLCOJiDpYFKxpjZ8qMzCFDtVLzxwJLpZRSSi0vGsQtoNHl1GTUnnXLrfHiblCjebT9lm0Jnm+oeLNLbjgymGfPqcycx6GUUkqpxaNB3AIaCWe9khFn1i23xou6YfuttgQnRopUw+BtNhmq+XKN48NFCmWPYkWTIpRSSqnlRoO4BTS6dBmP2NhzrBMHEHUsLEtY3ZrA8w0nR4oAlGaRoXpoIEfUsUAgEy7zKqWUUmr50CBuAWWKVSwJGtlfyEyciJCKOXQ3BckNR4cKOJZFrjSz5IaRQoXT2TKpmEvctTmd0yBOKaWUWm40iFtAmVKVhqiDiHABeQ0ANMZc2pJRLAl6qEbC5IbzMcawvy9HMhLsq4u7NkP5MrVZ7qdTSiml1OLSIG4BZUs1klEHAxc0EweQirlYFqxsjo/1UM3OoFZcf7ZMthy0/oJgVs8YtESJUkoptcxoELeAsqUaDdEgeLqQ7FQI228RZqgOBhmqNd9QOUdyQ83z2d+fozHmnnXcsSwGdUlVKaWUWlY0iFsgxhgKlWAGzLEs5AJn4mKuDcDa1gS96RLlWpDUMPp5Kr3pEpWaP6nQcCJiczpbmnWdOaWUUkotHg3iFojnG/Jlj2TUJnIBmamjXNsi6lisaoljgGNDQYbqdGVGyjWPQwM5muORKR+rXPUpaKkRpZRSatnQIG6B1PzRmTgb5wJabo3XGHNZ0TTaQ/XcGarHhooIMv0yrkC6oN0blFJKqeVCg7gF4vnBTFcy4uDa8xTExV1aki6OJRwdyuPaQnaKBIWgsG+Bxrg7xaMEEq7D6VxpXsallFJKqfrTIG6B5MseNd8Qj9hE5imIS0RsLBFWtcTHyoxkpuiFemggh2tZWOP24fnG8MWHjnJsuAAEiRIjhepY9wellFJKLW0axC2QkbArQty1cedhTxycSW5Y05oMllNti6rnnxWIpQtVTmfLk2bhfrj7NF944Chff/QEEJQaEZhRrTmllFJKLT4N4hbISOFMy635Wk4dy1BtS3A6W6ZQCQKw0eQGYwz7+rNjhX1H5cs1PnvfYQAeOjyEH2alurbFQK48L2NTSimlVH1pELdAxvqmuvakEh9zZVtCwrXpaT6T3GAMlMMeqgO5MtnSmcK+o7740DHSxSqvuXolI4Uq+/pyACQiDqczZS01opRSSi0DGsQtkOF8sJyajNoXXOh3vMa4y4qzeqgK+XINzzfsO52jMXr2Muqx4QL/+fhJXrK9izfdsBpL4IFDg0AQFNY8X7s3KKWUUsuABnELZCSciUtEnAtuuTVeU9ylOeEScawgucEJeqj2pouTCvsaY/jUTw8RcyzefPNaUjGXy1c28eChobFzLEvGZg2VUkoptXRpELdARmuwJaM21jzOxMUjNkLYfmuogGtbZEo1DvXnaZrQXuuhw8M8cnSY229cQ3MiKPp74/pWjgwVOJUJyovEXZu+tO6LU0oppZY6DeIWyNieuMj8LqcGyQ0y1kPVtS3y5SoGcMYlUFQ9n0/97CCrW+K86sruseM3rmsFGJuNi7k2mVL1nO27lFJKKbX4NIhbIJlSlahj4VoWzjwGcVHHwpJgJm6oUCFTrJKKuTRNKCnyzV0n6U2X+O/P23BWcLeyOc7qljgPhvviAESWVqkRYwz92TKZUhXP16QLpZRSCsA5/ylqPmSKNZJRB4Sziu5eKBEhGXNYOS654YqeprPOGcpX+NLOY9y0vpXr1rRMeowb17fxjV0nyJeDMUZtm/5smfaG6LyN80L0pUs8eTKDYwuC0JJ06WiIkoq7JNz5XZ5WSimllou6zcSJyGoRuVdEdovIUyLyznH3/Y6I7AmPf2Tc8feLyP7wvpeNO369iDwR3vcxkSAKEpGoiNwZHn9ARNbV6/VcqFy5RkPUwRjmdTkVoDHmsKLxTBA30Wd/cZiq5/O2566f8vqb1rfi+YZHjg4DwZLvQLaMP4dZr6rncypdnPV10ylVPfaeztKajNCWjNKccClWPPb0Zdl5aIifHxjg6d40pzMlCpWalkdRSil1yajnTFwNeK8x5hERSQEPi8g9QBfwGuAqY0xZRDoBRGQ7cDtwObAS+L6IbDbGeMA/AncA9wPfBm4D7gbeBgwbYzaKyO3Ah4E31fE1zVk+DOIsqUMQF3dJxR0SEZsjE4K4Z05l+OGe07zh+lV0N8WnvH5zV4rGmMMDh4Z43qYObEvwjCFbrk1alj0XYwz7T+c4OlTAEqEzDCznKni8LLZljRVItkRIRJyx2neeb0gXapzOBMkYrm2xbUWK1iUyi6iUUkrVS91m4owxvcaYR8LbWWA30AO8HfhLY0w5vO90eMlrgC8aY8rGmEPAfuBGEekGGo0x95lgmuVzwGvHXfPZ8PZXgBePztItJZ5vyFc8EhH7rP1o8yXm2ogIa1sTHBnMjx33jeGTPzlIazLCG65fPeW1xhhsS7hhXSs7jwxRC1t2WSKkC5VZjaMvXaI3XaSjIcrTvRnyF1hvrj9bpj9bpjE2fSBpW0JD1KEtGaUtGcVCOJUtXdDzKqWUUsvBgiQ2hMuc1wIPAJuB54XLnz8WkRvC03qAY+MuOx4e6wlvTzx+1jXGmBqQBtrq9DLmrOb75CvBfrNIPYI4Z7SHaiLs2hAsKf5w92n2nc7x3569jnjEnnRdulhlIBcEajetbyVf9ni6NwNAMuJwKj3zYChXrvFMX5aWeATXtog5NrtPZsaCwtkqVYMl06Z4ZFbXxVyLkbzWuVNKKXXxq3sQJyINwFeBdxljMgRLuC3AzcDvAV8KZ8+mmkEz5zjOee4bP4Y7RGSniOzs7++fw6u4ML4PxbGZuPmfKIw4wXLj6tYE2VKNkUJ1rD/qthUpXrC5Y9I1nm+o+T4RR/B8wzWrW3AsGSs1EnEsChWPUvX8pUZqns/uk2lizpmZxmTUIV+pcXAgN+vXY4zhYH8OgVn3mXVsi4rna4kUpZRSF726BnEi4hIEcF8wxnwtPHwc+JoJPAj4QHt4fPya3yrgZHh81RTHGX+NiDhAEzDEBMaYTxpjdhhjdnR0TA5o6q3q+WNBnGvV51veGHfpDjNUjwwVxvqj3vH8y5hqhTldrLC+LcmKphi5co14xObq1c08eHjoTHKAQGYG3RsODuQoVLwg+3aclkSE48NFTmdmt7w5kCtzKl2a9SzcKCEImpVSSqmLWT2zUwX4NLDbGPM34+76BvCi8JzNQAQYAO4Cbg8zTtcDm4AHjTG9QFZEbg4f8y3AN8PHugt4a3j79cAPzRJMT0wXguK7Cdc5qw3WfGqMOnSFiQS/ODAw1h91Y2fDpHOrno9tCytb4rQ3RKn5wZLnTetb6U2XODYcZJfGHJvT2XN3b+jPljg+XKIlMTngEhGa4xF292YoVGa2P65c89hzKjvWUWIuBFlSde6UUkqpeqjnTNxzgDcDLxKRXeHHK4B/ATaIyJPAF4G3hrNyTwFfAp4GvgO8I8xMhSAZ4lMEyQ4HCDJTIQgS20RkP/Ae4H11fD1zNto3NRaxZ708OFPJWJCd2hhzuPvJU2P9UaeSLlbZ3JnCtS1SMRfbEnxjuGFC94Z4xGYoX5m2wG6x4rG7N0Nz3J1ytg+C5dCIY/P0iZntjzvYn8cw+2XU8aKuNfY9V0oppS5WdSsxYoz5GVPvWQP4tWmu+RDwoSmO7wSumOJ4CXjDBQxzQQwXgtmshGvj1mFPHAQZqpYlrG1L8sSJ9Fn9UccrVGqkos5YIV/bEtoboozkq7Q3RLmsI8mDhwZ5/fWrsCQI7nKlGk2JszNEPd/wdG8a1zp/YNoQdRjKlzk4kGNzV+O05w1kg+zW9uTZ5UH2n84xmC9zZU/TWGmRc4k6NiOFCsaYaYNLpZRSarnTjg0LIF0YnYmz6jYTFwuXaXesbaHmm7P6o46Xr9S4bk3LWV0OOlNR+jIlGnC4aX0b//HgUUYKFZoTERzLYjBfnhTEHRnMkynWZtzVIdgfV6I5Hpmyflyl5vNMX5amWOSswGswV+aPvvEE+YqHbQlbV6S4dk0L161u5rLOhim7X9iW4PtQqvpTZuUqpZRSFwMN4hbAcBjEJaPOvBf6HeXYFjHX5peuXskvX7dqynMyxSpdqdikGbrGsKCvMYYb17fy7w8eZefhYW7d3kUiYtOXKbGh48zeuuF8hUMD+Vm15Qr2x7ns7s3QEHMmzagdHMhhfM7aM2iM4eP37qfqG/7gtq0cOJ3jkWPD/Nv9R/i3+4/QGHO4ZnUL161p5to1LbQmz7wug6FY9TSIU0opddHSIG4BjBSDWmzJiF23IA6gMe6QKdSmnO3zjaHi+azvSE66z7UtWpMRihWPDe1J2hsiPHh4iFu3d+HaFtlSlUKlRiLiUKp6PHUyTVPcnTQL5vmGT/70IJs7G3jxtq4pnyfi2Dx9MsO1a1rGvhdD+QonhoMiweP98JnT7DwyzH9/7nqeu7Gd525s562sY7hQYdexER45OsyuoyP8ZF9QNmZdW4Ida1t5447V2CJkitWzAjullFLqYqJB3AJIh5vsExGnrs3am2IuA5kKySkmyEYKFda2JabdU7aiMcbTvRkSEYcb1rXyw2dOU6n5RBwLQzCLF3Ns9pzKIiJEnckzXF986CjffqKX7wh0pKJctap50jkNUYfBfJlD/Tk2dqWo1Hx292ZompAcMZgr8//99CDbuxv5patXnvUYLYkIL9zSyQu3dOIbw6GBPI8cHebhI8N85ZHjrGqJ85yN7QwXKqxjctCqlFJKXQwWpGPDpS5TrCESdBOw67jRPhFxMJNrHQclRSxhVUti2msb4y6jxVluWt9Guebz+PERAOJusKR6YqTIUGHqNliPHh3mzoeO8fxNHfQ0x/nwd56Ztj5cayLCkaEC/dkShwdzeL45Kygcv4z6zhdvmnLf2yhLhMs6GnjD9av50GuvJO7a7OnLEnUssqUa/jSZtUoppdRyp0HcAsiWqiQjDpZYdV1OjblT7/9KF6tc1tFwzhp1MdemMe5SqnpctaqJuGvzwGipEddmuFBl3+ksLfHJ03yDuTJ/fc9eVrcm+J0XbeQDr9hOzTd86O7dU3ZOEBFaEhGeOpnh+HCR5vjZQeHoMupbbl7Lyub4jF+/bQmbuhrY2xfMFvom2BenlFJKXYw0iFsA2VLQN9Vg6hrERR0LEWF8veNSNegU0TVFRuhE3Y0x8pVgT90147o3iAiOJaSi7qTxe77ho9/bQ7nm8b7bthJzbXpa4rz3JVs41J/n4/fuZ6r6y65tkYw4NMcnZ6NOt4w6E1u6UhweLIwFjwXt3KCUUuoipUHcAsiVazREg1myei6nWpaQjDhUxhXVzZZrbO5KzWgvXnPyzIzYTetbGcpXONCfB6ApHplypu/f7j/CUyczvOOWjaxuPbNce+P6Vv7LTWv40Z5+7nrs5KTrIJj9G5+EMZtl1Ols7krh+YaD/XlcyyIdJpUopZRSFxsN4urM9w35cjATZwl1TWyAIEO1UguCuGypSntDhJYZZmgmIg5x16ZS89mxrhVL4IFDg9Oe/9DhIb7yyHFedvkKbtnSOen+N+5Yzc0bWvmXnx8a2193LnNdRh1vS1cKINgX51qMFLRzg1JKqYuTBnF1VvNN0By+ji23xmuMBTNxvjGUaz6XdUzunXou3U0xCpUaTXGXrSsaefDw0JTnnc6W+Nt79rKhPckdz9sw5TmWCO++dTMrz5PoABe+jDqqJRmhIxVlb1+WiG2RK9dm1O5LKaWUWm40iKsz3xjyFY9kxFmQIC4WcRCCZIbVLXGS0dlVkWlJRsZ6pd64vpWD/Xn6s+Wzzql6Ph/5zh5qYRHecyVMJCIOH3jFNmq+4c+nSXQ43zKq5xv6s2VGitP3cR1vc2fDWCkUQJMblFJKXZQ0iKuzYCauRnyBZuJiroVvgqa1q9umLykynYaog+tY1DyfG9e3AkyajfvsLw6zpy/L/3rxphkte65qSfDel2zhQH+ef5gi0eF8y6jDxTIbOpKsaomTK1cZzJcpVGrTPt/mrhSns2VGCsF+uEJ5+nOVUkqp5UqDuDorVGpUPUMi4uA69W/GHnVsYo7F+o7klAV5z0dEWNEYI1/xWNUcZ2VTjAfH7Yu778AA33zsJK+6spvnbmyf8ePeuL6V/3LjGu7d089/Pn4m0eF8y6i5co2mmMua1gTr2xt41mXtXNnTRMy1GMiVGS5UJi2XblkR7Ivb25clatukSxrEKaWUuvhoEFdn6cJotwabyALMxAFsW9lId9PcEgMA2hui1HwfEeHG9a08fjxNoVLjVLrE3/1gHxs7G/iN566f9eO+6YbV3LS+lU//7BBPHB+Z0TJqqeqxZUXjWEKIbQltDVGuXt3CzRvaWNeWIF/xGMiXyZVrGGO4rKMBS2BPX46oazGU1wxVpZRSF58ZRRUisllEfiAiT4ZfXyUif1TfoV0cRrMj4wsYxDUnIhdUj64h5uBYgucbblzfRs03PHhoiA9/5xkQ+IPbtk67NFyo1OjLlKZMJrBEeM9LgkSHv/zOM3zp4ePnXkYtVNjY2TDtvr54xGZNW5JnX9bG1auaaYjaDOaDfXPr2pLs7cvi2halqjeWsauUUkpdLGYaVfx/wPuBKoAx5nHg9noN6mIy2jc17i7Mnrj5YFtCRypKoVJje3cjDVGHf/jRfvb353jXizezYprCwVXPp1j12NTZwFChgj9Fkd/xiQ7/dv+RaZdR8+UajXGHnhnsubMsoTUZ4cpVzVyzuplyzWNzV4p9fVl8YxA0uUEppdTFZ6ZRRcIY8+CEY7rRaAaGw8318YiNbdd/T9x86UjFqIQ9V3esa6FU9XntNT3cvKFtyvONMYwUK2zvbmRte5LLOpIM5itTdmtY1ZLg9166hcs6ktMuoxYnLKPOVEPMwRDUi8tXPE6MFBER8rovTiml1EVmpvUnBkTkMgi6q4vI64Heuo3qIjK6HysRsXGs5TETB5CKOYgEJVJed00PzfEIb33W2mnPHypUWNOSoDOcpVvblqRU8zmVLtGWnNxvdce6Vnasa53ysUaKFS7rSNIwy/IoELTzSrg269uTAOw9leXmDW2MFCusbJn7PkGllFJqqZnpb8l3AJ8EtorICeAQ8Gt1G9VFJBMupyYjTl1bbs0317ZoS0bJlWps6GhgwzmKBmeKVZriLuvHnSMibOpMUa76jBQrNMdn1jUiX67REHVY1TL78iijWhsilKs+cddmT1+WW7Z0MqydG5RSSl1kZjQ1ZIw5aIy5FegAthpjnmuMOVzXkV0k0qUwOzVqs4wm4gDoaoyddy9ZqephMGzrbpyUTGFbwrbuRmKORW4Gy5mjy6hbu2e/jDpecyKCh2FTVwN7+7LYllD1fEq6L04ppdRFZKbZqX8uIs3GmLwxJisiLSLy/6v34C4GmWKNiC1EbOuCMkYXQ2PcAWHKfW0QBF3ZUpUrepqIuVPXpIs4Flf0NOPhU6ycO4gaLlTY0D63ZdTxEhEbIdgXd3iwQLnmBckN53l+pZRSajmZ6dzQy40xI6NfGGOGgVfUZUQXmWypOlYiY7kFcVHHpjnuUqpOXZ5jqFBhU1eK5sS5l0rjEZurVzVTqNaoTtPHtFCpkYo6rGqd+zLq2PO5NpYImzob8HzDgf48IkJOOzcopZS6iMw0iLNFZGx3uojEgcm71dUkuXKNZDTImFxOe+JGdTfFKFYnBz/DhQorGqOsmmGyQCrmcmVPEyOFyf1PPd9QqHhs6U7NS6ArIjQlXNaGbcf29mWJOlr0Vyml1MVlpkHcvwE/EJG3ichvAPcAn63fsC4Ovm/Ilz0aokGm53KbiQNoikeYuJpaqNSIOhabulJjTeZnoq0hytYVjQwVymfVkBspBsuoqZg7X8OmNRkh7jp0pKLs7csSc20ypeq0S8NKKaXUcjOjzUfGmI+IyBPAiwl6q/8fY8x36zqyi4BnDPlKjfZkFFtkVgHPUhGP2CSjNuWaR9Sxxwr63rCudU7Fi1e2xCnVPI4M5WlPxihUaiQj9rwso46Xirr4GDZ3pdhzKoslgu8bSlWfeGT2PWWVUkqppWbGO8iNMXcDd9dxLBed0WXCRKuNs0y6NUxlRVOcQwN5XNtiuFDhyp6maVthzcT69iTlms+pTBEMXL+udd5nKeMROyz628DP9w8wUqhgCGYRNYhTSil1MThnZCEiPws/Z0UkM+4jKyKZhRni8uX5hkI5mGlaqL6p9dCSjOAbw1C+wtq25FhB37kSETZ3pWhJRFnXnqRxHpdRR0WcoOjvhvagdt3eviyOZZHVzg1KKaUuEuecTjHGPDf8nFqY4Vxcqp5PoeqRiDi4zvIN4pIRm5hjE4uc6YRwoWxLuKqniXquMLcmI/S0xLAE9vTluGpVM0OFCuuYn9eglFJKLabzRhYiYonIkwsxmItNtlTFmGBpz12GSQ2jRISt3Sm2zVP26CjLqu8+weZEBATWtSXHMlRzpRq+r8kNSimllr/zBnHGGB94TETWzOaBRWS1iNwrIrtF5CkReeeE+39XRIyItI879n4R2S8ie0TkZeOOXy8iT4T3fUzC3/wiEhWRO8PjD4jIutmMsd5GwlZPCdfGsZdvEAdBQBR1ltdesqDob7B0u7cviyEoXHy+LhRKKaXUcjDTNb5u4CkR+YGI3DX6cZ5rasB7jTHbgJuBd4jIdggCPOAlwNHRk8P7bgcuB24DPiEio1HDPwJ3AJvCj9vC428Dho0xG4G/BT48w9ezINJh39T4Mt8Tt1zFXRtbhE1dDRQqHidGimFygwZxSimllr+Zphj+2Wwf2BjTC/SGt7MishvoAZ4mCLh+H/jmuEteA3zRGFMGDonIfuBGETkMNBpj7gMQkc8BryXIlH0N8Kfh9V8BPi4iYpZIMbChQlBcNu46RKdpS6Xqx7KExrjL+rZgD9zeU1luWNdKulihI6W1qpVSSi1v5wziRCQG/BawEXgC+LQxZtbpfeEy57XAAyLyauCEMeaxCfuheoD7x319PDxWDW9PPD56zTEAY0xNRNJAGzAw2zHWw0h+dCbOwlqGNeIuBq3JCMPJCImIzZ6+LM/b1DG2zK2UUkotZ+ebifssQRD1U+DlwHbgnee8YgIRaQC+CryLYIn1A8BLpzp1imPmHMfPdc3EMdxBsBzLmjWz2tp3QdKlIFhIRp1l2a3hYpCKBd0yNnU2sLcvS8SxGMyXqXn+sq7dp5RSSp3vt9h2Y8yvGWP+GXg98LzZPLiIuAQB3BeMMV8DLgPWEyRKHAZWAY+IyAqCGbbV4y5fBZwMj6+a4jjjrxERB2gChiaOwxjzSWPMDmPMjo6Ojtm8hAuSDmd8khFbg7hFkogEfWs3d6U4PFigXAv2wxU0uUEppdQyd74gbmzdabbLqGEG6aeB3caYvwkf4wljTKcxZp0xZh1BEHadMeYUcBdwe5hxup4ggeHBcG9dVkRuDh/zLZzZS3cX8Nbw9uuBHy6V/XAQzMQJQWKDBnGLI+JYxFybyzoa8HzDgf48AMWyFv1VSim1vJ1vOfXqcZ0ZBIiHXwtgjDGN57j2OcCbgSdEZFd47A+NMd+e6mRjzFMi8iWCxIca8A5jzOh0yduBzwBxgoSG0fZfnwY+HyZBDBFkty4Z2WLQ4skSwdY9cYumNRlhTWscCJIb1rQkGC5U6WqKL/LIlFJKqbk7X8eGOadUGmN+xtR71safs27C1x8CPjTFeTuBK6Y4XgLeMNcx1lu2VKUhGizn6Uzc4mlOuCSiDh2pKHv6srzyqm5NblBKKbXs6c7uOjHGkK/UaAgbxWsQt3iSEQeBsaK/rm1RqnlUav5iD00ppZSaMw3i6sTzDYWKRzIaBBAaxC2euGsjImzubOB0tsxwWL+vqEV/lVJKLWMaxNWJZwz5skcyYmspi0UWFP11WN8eFP3d15fFEiGvyQ1KKaWWMY0u6iSYiauRiDq4Ogu36NqSUbqbY1gCe/pyRB1rbEZOKaWUWo40iKsTzzfkKx6JiI3r6Ld5saViDhHbYl17kr19WaKOzbAmNyillFrGNLqok3LVp1LzSURsIrqcuujiERvfwObOILlBBCqez4nh4mIPTSmllJoTjS7qZHSpLuE6OhO3BEQdm7hrc1lnkkLF48RwkdZEhD19GQ4P5FhCNaKVUkqpGdHook5GisFSXSxi4+ieuCWhtSHCutYguWFPXxbbEtqSUQ4OFNh3OovvayCnlFJq+dAgrk6G82WAYDlVZ+KWhOaES3sqQiJis7cvC4AlQnsywonhErt7M9Q8rR2nlFJqedDook5GCkH5irhr6Z64JSIRcRCETZ0NY0EcgIjQ3hClP1fmiRPpBSkCbIzRgFEppdQF0eiiTtLFcE9cxMHS5dQlIeHaWJawuSvF4cEC5drZxX7bklHy5Rq7jg1TqtanEHCl5nMqXWTn4SF2Hh6eNAallFJqpjSIq5PR3pzJqI0tGsQtBeOL/nq+4UB/ftI5TfEIngcPHxkmN0/FgI0xpItVnjmV4b4DAzxzKouIUPV99vdpUoVSSqm5cRZ7ABerTCkI4hIRG9vWIG6paE1EWN0SB2DvqSzbuxsnndMQcyhUajxyZIirV7XQlHDn9FzlmsdgtsLR4QLFikfEtmhORLDCoD7q2PRly7SMlFgZjkkppZSaKQ3i6iRTquFYgmtbOhO3hKRiLqm4S0cqyp5x++ImSkQcLBEeOTrMlT2NtKdiM3p83zdkSlVOjhTpy5axgIaoS7Jh6n9qQZmTLI0Jl4ao/nNUSik1c/pbo06ypRrJqIMlFrbuiVsy4hEbgG0rGnno8BCPHR/h6lXNU54bc21sS3j8RIae5goiQs338fwgWPNGP8zobR/fBwPEHJu2RAQ5TwBvW0IiYvP0yTTXrWnRPrtKKaVmTH9j1EmuVKUh6mAwY8tnavHFXJuoY/Hmm9fQkYryp3c9xb17Tk97vmtbtCYiDOYqDGYrZAo1CuUalZqPbwy2JURti2TEoTkeoa0hSntDlIaYc94AblQi4lCsehwcyM3Xy1RKKXUJ0CCuDkb7po4uj2mx36WlJRGhIeby4V+5iu3djfzNPXu5c+exaRMMbEtIxVwaYg7JqEMi4oTBoI1rWzh2MNs606BtyjHFIxwbKtKfLc35MZRSSl1aNIirA883FCo1klEbS9ASI0tMS8KlXAuC7D999eXcsqWDf7v/CB+/d/+i1W4TEVoSEZ7pzdatvIlSSqmLiwZxdeD5hkLZIxlxcHWP05KTjJ3JNnVti/fcupk37ljN957u4//8v90UKvNTWmS23HBGb3dvRluAKaWUOi+NMOrAM4ZCxSMesTWIW4Liro0gY8unIsKbb17L/3zhRnYdG+b9X3uCwVy5rmM4lS5NWeg3FXNJF6scGyrU9fmVUkotf5qdWge1mk++UtOZuCXKtoRU3KFc84m59tjxl12+graGCB/+zjP83lcf509etZ21bcl5eU5jDAcH8vziwCC/ODDA8eEiV61q4oOvvmJS9nJzPMKB/hzNicica9QppZS6+GmEUQe5Sg3fBOUsXEf3wy1FbYnIlHvPdqxt5S9edxU1z+cPvvo4jx8fmfNz+MbwzKkM//LzQ9zx+Yd51527+MrDx2hNRHj5FSt4/Hia/3jw6KTrRhMpnupdmD6uSimlliediauD4cKZbg2upXHyUtQYd/GnyUbd2NnAX73+av70P5/iT+56ine+eBO3bOmc0eN6vuHp3gy/ODDAfQcGGcxXcCzh6tXNvP76Vdy8oY2meDC7VvMMd+48xtbuFDvWtp71ODHXplT02H86y7buxgvKfFVKKXVx0iCuDkbyFQDdE7eEjRb9nU5nY4yP/MrV/Pndu/nre/byzz85OJZpbItgWRJ8LYJtCZYEXw8XqqSLVSK2xXVrm3nrZe3csK51ym4Mv/mCDew7neVvvreX/3v7NXRO6ArRHI/QlynTkijR3axtuZRSSp1Ng7g6GCkGM3Fx1yaiQdySNFrnrRgmoEylIebwZ6++nG/sOsFQroJnDL4Jlkn9sFOD74dfhx/r25PcuL6N69e0nDdQjDo273/5Nt515y4+8p09/MUvXzkp6G+Ou0FbrrhLUttyKaWUGkd/K9RBrhSUqIhHbBzdE7dkbe9p5LFjI5iKIRGZ+p+Ca1u84frVdRvDyuY473zxJv7yO8/wmV8c5n88b8NZ9zu2hWNZ9KaLbOxM1W0cSimllh+dJqqDbPnMnjhb9zItWY0xl+vWtFDzDbny4tSGA3jOxnZeffVK7nrsJD/fPzDp/oaow8mR0qIVIlZKKbU0aRBXB6MzcQ0RZ1L5CLW0JKMO161pwRLIlKqLNo5ff/Y6tnSl+Lsf7OPEcPGs+2xL8I1hKNxrqZRSSoEGcXUxOqsTi9gaxC0D8YjN1aubiToWI8XFCZRc2+L3b9uCYwl/+Z3dkwoBJ1yH4yPFaa5WSil1KdIgrg6ypRox18KxRIO4ZSLm2ly1qplUzGUwX99uDdPpTMV470u3cGSwwD//+OBZ98UjNulCZdFagimllFp66hbEichqEblXRHaLyFMi8s7w+EdF5BkReVxEvi4izeOueb+I7BeRPSLysnHHrxeRJ8L7PiZh0SwRiYrIneHxB0RkXb1ez2xky0G3BghKUKjlIeJYXLGykbaGSF0DOS/cgze67D7e9WtbeOOO1dyzu4/vP9131n2OZXE6szgBplJKqaWnnjNxNeC9xphtwM3AO0RkO3APcIUx5ipgL/B+gPC+24HLgduAT4jIaI2GfwTuADaFH7eFx98GDBtjNgJ/C3y4jq9nxnKlGomIjQGdiVtmHNtie3cTXY0xBnLlsf6qF8I3hny5xmC+zGC+TLZcpSnh4DoyZULFr964hqtWNfGPPz7AoYH82PGGqMPx4QKef+FjUkoptfzVLYgzxvQaYx4Jb2eB3UCPMeZ7xpjR31z3A6vC268BvmiMKRtjDgH7gRtFpBtoNMbcZ4LfqJ8DXjvums+Gt78CvFiWQGn7bKlKIqzppdmpy49tCVu6UqxqiTOQr0zb2WE6vjEUKjWGwqAtU6ySijlsW5HihnWtPHdjO9u7m9i+spFKzaM6IevUtoTffekWGqIOf3n37rElVMe2qPmGdHHxEjCUUkotHQuyJy5c5rwWeGDCXb8B3B3e7gGOjbvveHisJ7w98fhZ14SBYRpom+L57xCRnSKys7+//4Jey0wEy6lBUoOlM3HLkmUJGzsbWNeWYDBXxvMNnm+o1HyKFY9cuUa6WGU4XxmbYRsKP0YKVeIRm02dKa5f28JzNrZzeU8TXU1xklFnrIVWIuKwrbuRdLEyacavJRHh9162hVOZEh/74f6x+2OOzYnhwoJ/P5RSSi09dS/2KyINwFeBdxljMuOOf4BgyfULo4emuNyc4/i5rjn7gDGfBD4JsGPHjrqvReVKNbobY9pya5kTETZ0NODaFgf7c7iORcS2iEWCzxHHIupYuE5QkNe2BMcSYu7Ms5I7G2MMFSr0pUu0JqNn3XdFTxO/dtNaPnf/EZ66spsreppIRGwGchVKVY+Ye+6OEEoppS5udQ3iRMQlCOC+YIz52rjjbwVeBbzYnJmCOA6ML42/CjgZHl81xfHx1xwXEQdoAobq8FJmJVeuBX1TLQ3iLgarWxOsbk3U7fEv62ggXahSqNQmdY74patX8uWHj3PP7j6u6GlCRBCBgVyZVS31G5NSSqmlr57ZqQJ8GthtjPmbccdvA/4AeLUxZvy60F3A7WHG6XqCBIYHjTG9QFZEbg4f8y3AN8dd89bw9uuBH5r52Il+AWqeT6HiEXcdHFuXUtX5ubbF9pWNFCrepKSFmGvz/E3t/Hz/wNjeuMaYy/Gh4rwkXSillFq+6jlV9BzgzcCLRGRX+PEK4ONACrgnPPZPAMaYp4AvAU8D3wHeYYwZrXj6duBTBMkOBzizj+7TQJuI7AfeA7yvjq9nRrJh2YiYaxHRvqlqhlIxly1dqSm7Mty6vYtyzednYUsu17Yo1TwyRa0Zp5RSl7K6LacaY37G1HvWvn2Oaz4EfGiK4zuBK6Y4XgLecAHDnHejmYNx19Y9cWpWuptjDBcqDBUqNMcjY8e3dKVY3RLn+0/38dLtKwBwLYveTJGmhLtYw1VKKbXINMqYZ6P9N2OuTUSDODULIsKmrhS2JZSq3lnHb93Wxe5TWY6FmakNMYe+dIlKzZ/u4ZRSSl3kNMqYZ2dm4oLsRaVmI+JYXN7dRLZUPWt/3Au3dGIJ/GB30MXBEsEAw4vUIkwppdTi0yhjno22Uoq6NrZmp6o5aEq4bOxsYLh4JkBrSUa4YV0rP3zm9Fhwl4w4HBsqLtYwlVJKLTKNMubZy6/s5t73voCelpi23FJztqolQWsiOrY8D3Drti6GC1UePjIMBEv2uUqNbEk7OCil1KVIg7g6cOyw+Ku23FJzZFnClhUpfGPG9r3tWNtCc9zl++GSKgRt3foyuqSqlFKXIg3i6sSyBFvrxKkLEHNttnc3ki4F/Vsd2+KWLZ08eHiIkUJQiiQVc+lNF6l5muCglFKXGg3i6sRCdCZOXbC2hihrWhJkwoSZW7d14vmGH+0JegDbluD5hpGiLqkqpdSlRoO4OrEtQfMa1HxY2RKn5gczbWvbkmzpSnHP7r6xjg1x1+b4UOFcD6GUUuoipGFGnVgWOhOn5kUi4tCUiFCsBLXjbt3WxdGhAvtO58buHwl7ryqllLp0aBBXJ5aIZqeqebOqOU6hGgRpz9vUTsSxzkpwsCxhIKsJDkopdSnRIK5OHMtCdCZOzZPWZARLgv1vyajDcy5r48d7+8c6O6SiDkeHivjjCgQrpZS6uGkQVycRzUxV88ixLbqbYuTKwWzcrdu6KFQ87j84OHZ/zffHOoYopZS6+GkQVyeOttxS86yrKUY1LCVyRU8TXY3Rs5ZUo47N8ZECxYqnM3JKKXUJcBZ7ABcr19YgTs2vVNQhEbEp1zyijs2t27r4wgNH6cuU6GqMkYzYDOUqPJgbRERoiDk0xhya4hFirkXctXH051IppS4aGsTVSUR/Wap5JiKsbkmw73SWqGPzoq2d/PsDR/nB7j7+y01rERFak1GAsU4Pfekyx4fP9FeNuzZNcZfmhEtTPEI8Yi/Wy1FKKXWBNNKoE1f3xKk6aEtF8AFjDJ2pGNesbub7z5zGN2cvn1oixFybxrhLWzI69uHaFsOFKntOZXnw0CB96dJYvTmllFLLiwZxdaLLqaoeoo5NZypKflzNuP5smcePp2d0vWtbNEQdWpNRUjGXp06meeZUdqw/q1JKqeVDI406iWhig6qTlU1xyrUgiLt5QxvJqH1WgsNMubZFe0OU/myZnUeGSBc0s1UppZYTjTTqIObaRDWIU3XSFHdxLIua5xNxLG7Z3MkvDgyQK82+Y4OI0JKI4FoWDx8Z4shAXjNblVJqmdBIow46UlGaE5HFHoa6SFmWsLolflbNuKpn+Mm+/jk/Zsy1aU1GOTSYZ9ex4bEWX0oppZYuDeKUWoY6GqPU/GAf22UdSda3J7lnDkuq49mW0JaMUqr6PHhokNOZ0nwMVSmlVJ1oEKfUMpSIODQnIhQqNUSEW7d1sf90jsMD+Qt+7FTMJRVzefJEmt29mbECw0oppZYWDeKUWqZ6muMUw96pL9jcgWMJ//STA9z9ZC8H+nPULiD4Gp/08PDhYfLl2e+3UxcuW6pe0PuolLq4abFfpZap1mQESwTPNzTFXf7LTWv4+qMn+MSPDgBBhvRlHQ1s7mxgc1eKzV0puhqjiMyshuFo0kOhUuORo8NcvbqZxphbz5ekxsmWqjx8ZJiGmMMVK5uIuVqYWSl1NrnUCn3u2LHD7Ny5c7GHodS82H86y6l0maZ4EFwZY+jLlNnblx37ONCfpxLO5qRiDpu7UmxdkeKVV3aTmmFQVqp6FKoeV69q0qSdBVCp+TxydBgBPN/gG8OVPc00JTSIVupSIyIPG2N2THWfzsQptYx1NsY4PnSmrZaIsKIpxoqmGM/f3AFAzfM5MlRgb1+WfX059vRleeTIMN99qo/3vmQzV/Q0nfd5Yq6NJcKjR0e4oqeRjlSsbq+pnjzfMFKocDpbRgiSOWxLcEY/2xYiQceL4CN47Qs5C2aMYV9flmrNHwuYS1WPh48OsbWrke7m2IxnU5VSFzediVNqGTPG8OChIWxLiDozDzT29mX5q+/toS9T4g3Xr+ZXb1yDbZ0/MKh6PiPFKttWpOhujl/I0BdUseLRny1xdKhI1fOJOTYiYEzQZ9YQfjZgMAgCYsCAD6xsirGqJUEyWv+/e48NFdh3OkdHQ/Ss455vGC6U6WmJc1lHakbv10SjQaxjWzTGHA0GlVoGzjUTp0GcUstc70iRPX1Z2pLR8588TqFS459/cpAfPnOarStSvPelW1jReP4ZNs83DObLbOpsYHVrYk6BQKnqEbEtrDkEIjPl+4Z0scrx4QKD+QqWCKmogzPLlni+MWRLNaqeT3tDhDWtSRrj9QmARgoVHjkyTGsyOmWQZoxhqFChMeawfRb75Mo1j/5smSODhbEWa3HXZlVrnPaGqO63WwCeb8iWqkQdm3hEv99q5jSIG0eDOHWxKdc87jswSGsiMqfA4sd7+/nEj/YD8Nu3bOQF4TLsuXi+YahQZm1bkg3tyRk97+gs0PHhAkP5KomIzYaOJG3J6LwGc6VqELAcGy5QrvnEHZtExJ6XoCtXrlGqeqSiDmvbE/M69lLVY+eRIaL2+ZdvM8UqRsJ9cvHp98nlyjV6R4qcHAmW3FMxd6yvc6Xmky1XMQbaGyL0tCRoirtzmuFTUxsN3E5ny/RlStR8gyPCVat0f6OauUUJ4kRkNfA5YAXBisQnjTF/JyKtwJ3AOuAw8EZjzHB4zfuBtwEe8L+MMd8Nj18PfAaIA98G3mmMMSISDZ/jemAQeJMx5vC5xqVBnLoYPX0yTbpQoyE2t+W+U5kSf/29PTxzKsuLtnbym8/fQCJy7sfyTTAj19McZ1NnatpgJl+ucTpb4sRwkZpviLs2iYhDqeqRK9fmJZjzfEOmWOVkusjpTBlLzg5Y5lup6pGv1Ig4Futak3Q0Ri/ouXzf8PiJNPlybcYZwKPfv20rUqwYt7Q9OgN5dLjAUK6Ca1ukYg7WNEGsMYZ8xaNc83AsYVVLgo5UdEGWji9Gvh/M3PZlS5wOAzfXskhGHWxLxt637d2NdDUtz72lamEtVhDXDXQbYx4RkRTwMPBa4NeBIWPMX4rI+4AWY8wfiMh24D+AG4GVwPeBzcYYT0QeBN4J3E8QxH3MGHO3iPw2cJUx5rdE5HbgdcaYN51rXBrEqYvRSKHCrmMjs15SHc/zDf/x0FG+vPMYXY0xfvelW9jclTrnNcYYBvMVOlNRtqxIjS1VVj2f4XyFY8NFMsUqji2kolPP8sw1mKt5PtlSECCezpbxfEPUtklG52fWbSaqnk+mVMUSYXVrnJ7mBJE59E0+2J/jyGCB9obZvX81z2e4UGFNa4LVbQmGchWODBUoVjwSEfu8gfhUj5cr1/CMIRVzWd0SpzHu6nLreYwGbv25EqfSJaqeIWKfCdwmqno+w8UKG9sbWNM2ty0J6tKxJJZTReSbwMfDj1uMMb1hoPcjY8yWcBYOY8xfhOd/F/hTgtm6e40xW8Pjvxpe/5uj5xhj7hMRBzgFdJhzvCgN4tTFyPcN9x0cJO7aFzz79OSJNH99z16GCxXefPNaXndtz7SzOKOGCmWa4hHWtyXpz5U4OVLCN4aE68x4/89Mgrma55Mp1ejLlOjPlvFN8MsyEZn6l+VC8XxDuhjsu1vfkaS7KT7j8fRnSzxxIh283jn8Mh8NpAFEIBV15xRITlSseBSqQZHnZMSmqzFGczJCQ8Sp617G2cqVa5xKF2mMubQmI7Pe8zidmudT8XxqvsHzDJ4xwbFacLwS3q55hmLVw/MNjmXRME3gNlGwJaHCyuYYmzrnlqiiLg2LXmJERNYB1wIPAF3GmF6AMJDrDE/rIZhpG3U8PFYNb088PnrNsfCxaiKSBtqAgfq8EqWWJssSVrfEOTxYoOUC67hd0dPE399+LX9/7z4+84vDPHZshD+4bes5l9daE1FGihUePTaMY1k0xma/t2q0lEep6vHkicxYMNcUj5Arnx24RW2bprg7p6CnHmxLaE1GqXk++/pyHB0qsLGjgY7UuYsrFyo1nj6ZoTkemfRafGMoVrzzLmuKyKxn8GYiHjmzAb9S8zk8WMAfyGOL0JaK0NEQIxVzFm2WLluqcmyoQF+mhGNZHDdFHEtY05qgszE2p3EZY8gUa5zKFDmVKcG46QADCEHZmdHSNJYEn6ebZT4X2xLakxFOpUuUqz7buhvnJfhWl5a6B3Ei0gB8FXiXMSZzjv+hTXWHOcfxc10zcQx3AHcArFmz5nxDVmpZ6kjFONCfJ1OsTruMM1MNMYf33baV7z7Vxz/95AC//9XH+ZNf2k7nOerDNcfnpwjwxGAu+FduiNnOkgrcpuKE7coqNZ8nT2ZojDps7GqYskByzfN5+kSGiDN59tQYw0e/u4cHDw/x9udfxq3buxbqJUwp4lhEnOA1eL4hXajRl04jAg1Rh85UdMFm6TKlKkcG8vTnKsQci7bkmUC55vkcGshzcCDPiqYYK5vjM9pjWKx4DOTKHB8uUK55uJY9ZWA930SEtmTwB9CuY8Nc2dO8rDJXjTHkyjXirj1vM6BqduoaxImISxDAfcEY87XwcJ+IdI9bTj0dHj8OrB53+SrgZHh81RTHx19zPFxObQKGJo7DGPNJ4JMQLKfOx2tTaqmJR2yuW9MSbqguU/N9LBEaos6cllhFhNuuWEF3U4y/uHs3v/vlx/jjV13Oxs6GOox+snoV2R3tgFCvpAcIgp6OhuhYy7L2higbOhpoCGfVjDHs78+Rr9ZoTUyeRfvGrhP8bP8AKxpj/N0P9/HEyTRvf8FlS2Jvmm0FP1Ojr6Vc8zgyWODg6CxdQ4T2VJTG2PzupUsXqhweyjOYKxN3nEl19CAIoluT0WCJOVuhd6RIYzzC2rYErYnIWQFmsJ+wyonhAsOF6lgyTEN04bNGm+MRcqUaDx8Z4qo6tLfzwmSXgVyZpphDczIyq7qSE9U8n6F8haODBTLlKsmIw+U9TWM/E2rh1DOxQYDPEiQxvGvc8Y8Cg+MSG1qNMb8vIpcD/86ZxIYfAJvCxIaHgN8hWI79NvD3xphvi8g7gCvHJTb8sjHmjecal+6JU5cC3zfkKjWGcxV6MyVKVQ+AZGRuy19HBvP82beeJlOs8vsv28qN61vne8h1lylWufvJXr71eC8jxSoRxxoLRsY+Ymd/3ZxwuX5ty6wTBCbKlqqUaz49LTHWtCYZzld45lTmrFmkUU+eSPOBbzzBTevb+IPbtnLnQ0f54kPHWNUS5w9u28ratuQFjaWePN9QqnqUah6Y4A+LzsYoLYkIDXOo0WdMEHwcGsgzXKgQd51ZBwqje/sijsWa1gSpqEtfNkhA8M2ZbOmlYHRf6Hx0RfF9Q6ZUpS9zJvHHtSyqflAnsCMVpbspPquyMqWqR1+6xLHhAlXP0BAN/n9SqNQoVDy2rUjR1bQwHUV8P9iLWPPMRV+uZbGyU58L/BR4gqDECMAfEgRiXwLWAEeBNxhjhsJrPgD8BlAjWH69Ozy+gzMlRu4GficsMRIDPk+w324IuN0Yc/Bc49IgTl2KCpUaI/kqvZkS2VJQG2z0f8AzNZyv8MFvPc3BgRx3PP8yXnlldx1HPH9OjhT55mMn+f7uPio1n+vWtLC9O0Wu7JEv18iFH9lSdexYMQx6ISiK+8Ktnbzyym7WtCbmPA5jDOlSFd83+D40J9xJQc1QvsI773yUZMThb9549Vhw8dixEf7qe3soVj3e/oLLePG2uS2vVj2fvkyJnub4gvyirXo+hYpHzfcRgZZEhI6GoJCxIfiejO+aYUxwzA9/LQ0VKqQL1Tll2k41lmypioFZJSDMJ2PMeb/v1TDjeHNXipZkBNcWIrY1o/fLGEOmVKM/W+ZUujhtluzEsjLdTXE6G6M0RCcXsR59zBPDRfoypXAP4OSAvOb5jBQrrGiKs7GzYV5nun3fUKp5FCoemWKVkWKVbLEGGDzfcOWqpmXbCnAmlkR26lKhQZy61JVrHplijf2ns1RqPi2zKBJcqnpje7Vee81K/ttz1s9639CxoQJDhQpX9jTVdc/RM70ZvvboCe4/OIhtCbds6eC11/TMaCar5vnkKx4nR4p856lT/HRfP1XPcFVPE6+8qpub1rfNOQCYbjm35vl84BtPcqA/x1+/4epJ4xzKV/ir7+3hiRNpXry1k9+a4fKqMYYD/Xm+v7uPH+/tJ1eu0d4Q4eYNbTx7QxvbVzYtSDBjTDBzUq75Y8GbiJzZ2CxnNjmP/jxGbGtZ7RGbiucbHj06zLef7OXx42nueP4GXrp9xXmvGSlWxr4WIej04AaFq5MRh6hr4ToWEdui6vkM5iqcTBcpV31ce3ZZsrlyjZrnE4vYrGoJung4ljCUr3BkME+27BELZ67P9f8KYwzDhQox176g5dVSNfhjKlOqMlyokivVxoJ717aIOsGHiFD1fHLlKjesa1v2PyvT0SBuHA3ilApUPZ8D/TlODBdpjkdmnBnn+YZP/ewg33q8l2dtaOM9L9l83mCiL1PiJ/v6+cnefg4PFgBY3Zrgjdev4nmbOuYtiPB8wwOHBvnGoyfYfSpLQ9Th5Ves4FVXraQ1OffEi3Sxyj1P9/HtJ3vpz5Zpb4hw2+UreOnlKy44G3jUp356kG8+dpL3vmQzt2zpnPIczzd88aGj3PnQMVa1JnjfbVunnR1MF6vcu+c0P9jdx+HBAq4tPCsM2nYdG+aRIyNUPJ/GmMNN69t41mVtXLO6ua57BS8l6WKV7+/u4+4ne+nLlGlJuHSkouzty/Er163iLc9aO+M/Yowx1HxDzTPU/KCsiR/m8AmCwWBbQjIyt/2vo0a7eABYIvjGzGkLxlyWV6uez0ihysmRoKOLSDBjOj5gm062VCUesbl6VfOSKn8zXzSIG0eDOKXONpAt8cypLABNs8gw/eauE3z6Z4fY3JXij165bVIG5nChws/2DfCTff1jj7+lK8XzN3eQijl85eHjHB0qsLIpxhuuX80tWzrmnOGWKVb56f4BvrnrBL3pEl2NUV5zdQ+3buua17/OPd+w88gQ33q8l13HRnAs4Tkb23nVld1sWZGa8xLlT/f185Hv7uFVV3bzmy+47LznP3p0mL++Zy+lqsdv33IZL9oaLK/WPJ+Hjw7z/d19PHR4GM83bOps4NZtXTx/U8dZHT1KVY+Hjwxz38FBHjo8RKHiEXdtbljXwrMua+f6NS0X7cxGvRhj2HMqy/97spef7Rug5huu7Gni5Ves4OYNbVgi/PNPDnD3k6d49mVtvPvW8/8BtFh8Yy5opnwmy6uj+/ZOZUr0ZUoYE2xfiLuzL9g9mC+zti3B+vaFSbxaSBrEjaNBnFKTlWse+/tynM6WaYrPvF3VfQcG+Kt79tKScPmTX7qclkSE+w4M8JN9Azx+fATfwLq2BM/f1MHzNnewovHMvhXfGO4/OMidO49xsD9PZyrK669fxa3bus77/MYYDg7k2XlkmJ2Hh9jbl8U3QZD4umt7uHnD3Jc7Z+r4cIFvP9HLD545TaHisXVFit98/mWzzt49NlTgPV/exbq2JH/+uitn/L0fzJX5q+/t4cmTGV60tZPGmMuP9pxmpFilOe5yy5ZObt3WOaPl46rn89jxEe47MMj9BwfJlGq4tnDt6haetaGNG9a3nrNH62LJFKt8+8leBnMVXndtDyvHtR9bSMWKx4/39vPtJ3s5NJAnEbF50ZZOXj7FPkpjDN987CT/8rNDbOpq4I9esZ2WC5glXsqmWl4dLUsykCuPteIb3bd3IUGjHxa9vm5N85QlfWajXPOwRJbMrLQGceNoEKfU1Iwx9KVL7OnLhv02Z/ZLe29flv/zracp13yqYYX7FY0xnr+5g+dvaj9vEGGMYeeRYe586Bh7+rK0JSP88nWreOn2rrNmKfLlGruOjfDwkWEePjLMUCHYM7Sps4Eda1u4YV0rGzsbFryFUbHi8cM9p/nig0dJF6u8/Mpu3nzT2hn1sS1Uarz3y4+RLdX4v2+6ZtZFez3f8B8PHuVLO49hWcIN61q4dVsX169pmfOspucbnu7NcN+BAe47OMRALuhFe/nKJm7e0MbNG1rPWS9wIfRlSnxj1wnuebqPcs0nYlv4xvCKK7t5047VNF5AwNmXKfG1R0+w8/DQ2JKeYwm2LTiWnPnaEhw7KPj7xIk0hYrHurYEr7xyJS/Y3HHeWcz7Dw7yV9/bQ2Pc5U9etX1JZx1fqNHl1TVtCQayZQqV2lhyyXzWlytVPSqez451LXMuoTKYK/PUyfTY/rvGuEsqzFyPOhaxeeiKM1saxI2jQZxS51aseDxzKsNIsUJLPDqjGa1TmRL/+vNDtDdEecHmDjbNIZgyxrDr2Ah37jzGUyczNMddXnNND5bAziPDPN2bwfMNyWhQD2/H2hauXdMyb3vSLlSuXOPfHzjC/3uil4aow3979npetK3znI3nP/LdPfziwAAffM0VXL2qec7PfSpdIuZaFzwDMdFoUsR9Bwe57+Agx4aC/YwbOxq4eUMrN29oY03rwvX+PNif42uPnuCn+/qxJEhWed21q2iIOvz7g0e55+lTxF2bN+5YzauuWjmrDghHBvN89ZHj/Hhv8Ng3rGsl6lp44/aieX6wN23isXVtSV5xZTdbZ7mkvv90jv/zracpVj3ed9tWrlvbMpdvy7JQ83yy5RrJiFPXzhTpYoXmhMvlK5tm/XPZO1Jkd2+G5kQE1w7e+3LNoxq+16OCP3IdGmMubQ2RGf/BO1caxI2jQZxS5+f7hhMjRfafzs1LeYfZevJEmjt3HmPXsREA1rcn2bG2hevXtrB1ReOS7jN5aCDHP/7oALtPZdm6IsXbX3AZGzomL7F+c9cJPvWzQ7z1Wet4/fWrpnikpefEcJH7Dw1y34FB9vQF+xxXNsW4eUMbV69qZmt3at5/VowxPH48zVcfOc6jx0aIuza3XbGC11y9krYJM5dHBvN85heH2XlkmM5UlDffvJbnb+445zLdnlNZvvzwMR44NETUsbjt8hW89tqeurQym8pArswHv/U0Rwbz/NYLLuPlVyyP0j1LWX+uzJauFD0tM1teN8ZweDDPoYE8rYnz/+Hq+YZKzSdXrtHdHGVbd9N8DHtaGsSNo0GcUjOXLVV5pjdDseovyozXsaEC8Yi9YL9Q54tvDPc+c5p//cVhsqUqr7iim/9689qxkgtPnUzzgW88yQ3rWvjDl2+bdsYgXQz2E11Idf16GcyVeeDQEPcdHOSJE2k832AJbOho4IqVTVzR08j27sY5z1J4vuEXBwb42iMn2N+foyXh8uqre7jtihXnLV3x2LER/uXnhzg4kGdjZwO/8Zz1XNlz5hetMYbHjqf58sPHePx4moaow6uu6uZVV61clL1/hUqNj353DzuPDPOaq4PSPfP5h8pwvsKP9/UzUqhw84Y2tnTNPQlnVM3zefx4mr5siRds7lgyBZMh+NkZLlTYsa7lvD9/nm/Y25elN12kLRmd1b68fLlGU8LRIG4haRCn1OxUPZ+9p7KczpZpTda/n+TFJFeq8W8PHOHuJ3tpjLn8+rPXce2aFt595y5irsXfvPGaaRvcp4sVklGHXKmGE9b9WqpGl+CfOpnhyZNp9vZlqXrB75Z1bQkuX9nE5SsbuWJlE80Jl3zZY6RYIV2sMlKoki4GH8OFytjt3nSJoXyFnuY4r7u2hxdu6ZzVMpxvDD/ac5rP33+EgVyFm9a38pZnreP4cIEvP3yc/adztCYivPbalbzs8hWLHoR4vuHTPzvIfz7ey03rW/ndl265oMzVUtXjgUND3LvnNI8eHcY3Qcs0L9yz+rxN7bxgc8es9uJ5vuHx4yP8bP8A9x0YJFuuAZCKObzh+lW84sruuv7BUfN8jg0XONgf9Mc92J9jU1eK33jO+knnFirB2K5b2zLtHraq5/P0yQzDhQqts6iXOUqDuEWgQZxSs+f7wXLD4cE8LfHIsm527fmGYiXoyCASfiCIBLWxJCw6KyJYwrzs99p/Osc//fgAe/qyxF0bzxj++vVXs6596l+ghUpQ3PTatS1BosGJDPlKjdbk8piRrNR89p3O8uSJNE+ezPDMqQylarCnyLGEmj/1751UzKE5EaE57tKScHnuxnZuCktzzFW55nHXrpN8+eHjY504upti/Mp1q3jR1s4lk4E46j8fO8mnfnaQRMRhc1eKzV0N4efUeWcJfWN46kSaH+45zc/3D1KserQ3RHnhlg5euLWT1kSE+w4O8pO9/Tx2nuzxUZ5vePJkmp/uG+C+AwNkSkHD+5vWt/LcTe00xVz+/cGjPHpshLZkhF+9cQ23buu64JnEYsXj0GAQqI0GbEcGC2M/O1HHor0hyomRIu++ddNYmZ3xhvJluppibF3ROOm+UtXjyeNpilVvzntJNYhbBBrEKTV3p0aKY0V0l2p9q+mM9qW0LaGrMehZ6o9uUvcNnjEYHzzfxzNmrLOC7wMy976zo3xj+MHuPr7y8HF+7ea1PG9Tx5TnVcMN4NevbRmbfat6Pvv6spzKlGa0Z2epqXk+BwfyPHkiTaZUoznu0pxwaQo/N8cjNM6ih+dcjBQqfOepU6xsivOcje1L+nv4xPERfrS3n719WY4OFcbakHWmomzuSrGlK8WmrgYu62gg5tocGy5w7zOn+dHefvqzZeKuzXM2tvGiLZ1cPk1nlJFChZ/vH+DHe/vZPa6O4ws2d/Dsy9o4OVLkp+GM20ixSsy1uHFdG8/d1M51a5onzbg9cXyEz953hD19WVY2xfi1m9fynI3tMw7Ac+Uajx8f4dGjIzxxIs3JkSKj0UljzGFDRwMb2pPB544kK5uC/W5/9I0n2N+f42/feA2rWiaXcxnIl7liZROd4wLUXLnGY8dGELigpAQN4haBBnFKXZh0ocrjJ0bGSgQsZb4x5Eo1Kp5PQ9RmbVsy7Ec589mXYsVjOB+0NMqXaxguPKA713gH8mWu6pncC9IYw9HBQrg/bHavYVShcqYvbMS2SEQWvn/opcg3hmypNpbh2JKY+baEYsXjQH+OvX1Z9p7Osa8v2NoAYAm0N0Q5nQ3KwFyzuoUXbe3kpvWts/r5PJ0p8ZOwMPehgfzY8ahjccO6Vp67sZ3r17ac9zGNMTx4eIjP33eEI0MFNrQnefPNa7l+bcukGe2a57P3dI5Hjw7z6NER9p0Oaj3GXZsre5rY1HUmaGtLTr/UOZgr8ztffJSOhigfff3Vk5bcR3vm3rg+aMs1Uqjw2LERYu6FJ2xpELcINIhT6sIVKx5PnBihXPVntRThG0Oh7FH2PGwRUrH6zL6Mb3a+oilGd1Ocxti5+z7ORKk6GtCVyJaqCJCYx4BuIF9ifVuSdeeoOj+QLfHUycyMfwmZMIAoe8Gy0bpwD1R/tkR/tkzNDyrz17v0w6Vo9OcQoLs5TndTjIFcmYP9eVoTc9+WMFyosK8vy96+HEeHCmzvbuT5mzsuqLXcqKNDBR44NEh3U5wdMwjcpuL5hp/u6+cLDxzlVKbE9u5G3vKstbQkIjx6bIRHjw7zeLiUaQls6kxx7ZpmrlndzJau1Ky/Lw8dHuKD33p62o4nuVKNiCv0NMXZfSpLKubMy949DeIWgQZxSs2PqufzzKkMg7lzbwr2fEOhUqNc87EtoSMVpSMVJV2ocjJdpOYF/RkvtMWTMYZCxaNY9Yi5FqtbE3SkonXbaD1VQNcUj8w5KB0uVGhLRti+svG8wWa+XOPJE2kqtemDaM83ZEtVar6huznGyuY4jROWjnzfkKvUGMlX6E2XKFY8RCA2x9ZHKjBa3DbqWqyZ4uewL13i6d7MstyWMBtVz+eep/u486FjY8W5IVgWvm5NC9euaeaqnuYZFcY+n9Hew3/4im08a0PbpPsH82U8Y2idxz29GsQtAg3ilJo/vh+0vzo2lKdl3F4tzzfkyzUqvo9jCZ2pKJ2pGKnY2RXaa57PUL7CseEimWIVx5r57JwxhnLNp1j1MMZggLZkhFUtCZri7oI2wi5VPfqzZQ7054ja9qx/KeXLNSwLrl0zfSbdRJWaz56+DAPZyllZw1XPJ1OqYomwujVOd1N8xoFCseKRKVY4lSkxXAhmkOLzsOx0KRhdMq16Pk0Jl7WtiWDZdJqfw3SxyhPHR7DFmpcgZikrVT1+8MxpAK5d3Ux3U2ze/0Coej6//5XHOZUp8Xe3XzNlVxFjzDmft1jx+MSP9vOLA4NnJTqN/zya7BT8ezP86o2ree9Lt87ra5lIg7hxNIhTav71jhTZfSqDa1l4xgSBW2OMzlR0xkFZrlyjL13iZLqI5xsS7tmzc74xlKoe5ZqPbwwiwabk9mSwKT6xBJYDC5Uae/tyDOcrNMfdGf3FX6n55CtVdqxrnXWw5PuGI0NBkdK461CqBrM/61qTdDRGLyjzsur5ZIpVjg8XGMpXsS2hIeosqWxOzzdky1VqYTmTxpg7Lz8DY8ugAhgBMUz6VWmCX+YC+OEW/O6mYMZzppvlixWPp06kKVS9JdN5ZDnrTRd55xd3sa4twV/88lWzmhU/lS7xoW8/zdGhAi/Z1kUi6uD7wR+HvjH4JggCfRN8bUxQ8PfF2zp567MnlziZTxrEjaNBnFL1MVKoMJir0N4QpSE29w3z42fnssVgX9voX8FNcZf2hggNMZdkxF6SpU6MMZxKl9jbl8WxrHP28fR8w1C+zDWrm2m9gILGpzMletNFeloStJ5j9meuihWP/myJ4yNFKjWfqGOTjCzecuv42cae5jhdTTGyxSqHB/OUa/6cE09Gl0FjrsXa1iSJqI0xYGBstjf4Ojg4mr1sW9CcjMxp6V7rMM6vn+zt56Pf28Mbrl/FW561bkbXPHp0mI98dw8Av/eyLVy3Zmbtz5bCcurFPYerlFowzYnIvPTudGwrmMVrjJEr1yhUaiQiDgnXXtAl0rkSEbqb4zQnIuzty9KfLdOccCfNYBljGMpX2NSVuqAADhj7ftVLPGKzpi3JqpYE6WKwl7E/zJBMRedn9msmihWPfKVG1LXY3JmiPRUde+6GqENXY4zBfJnDA3kGcqXg5+Y8s5ujiR8Vz6MpEeGqzoZzLoPON9e22NbdSDxycdRhXGzP39zBruMjfOXh41y1KkiWmI4xhq8/eoLP3neYNa0J/vAV2+humlmrrqVCZ+KUUqpOjDH0pUvsPZ3FtqyzEguGCmU6U7FZN01fKkpVj6FchaPDBYqVINvYdSwitoVry7y9JmMMuXKNUs2jMe6yvi153iDLGMNIocqhwTzpQoWY45CMnj1zOD7xo6sxxqrWyYkfC62edRhHy8s4ltAQvfCs8IllUxpjk/9QWSylqsd7vrSLbLnGx26/dsql6lLV4+9/uJ+f7OvnOZe18c4Xb551ctVSmInTIE4ppeqsVPXYfzqYlWuKRyhVPSKuxTWrmpf9rIsxhkypRrZUJVeqhbOnXriHLFiCdC2LiGPh2tak4MGM2280ulwZ7DkKui14xtCZmnuQlS5WOTaUpz9bxrVtYq41VvR5VcvsEj8WwlgdxnlIeBifbNGScFnVmiBdqHJiJNh3OpdgcXQpW4CVzXFWNMXIlWocGMhR8wxNsZntBb0QxgQFuquej+8z5ffpyGCe93zpMS5f2cifvvrys5ap+zIl/vzbuzk0kOfNN6/l9devmtMfHRrELQIN4pRSi8EYQ3+2zJ6+LCKwY+3sCrIuJ75vqHg+5apPqVojWw6Cu1ypdlbLrdEWZ5YItiXYItiWhVhgi9AYd1jRGL/g8jMQ/MI9PlxgpFBlTWuC9tSFJX7UU7Hi8XRvmmwp6P8Zc2ziEXvG++VqYaBlCJIteloSZxXmrno+Q7kyR4cK5MoeUSco3H2+zM1CtUbEmbpsSs3z6U2XODyQxzfmgsrtjH/MiudT9Qw13yd4tOC/cdciGXWohjOqzfHJs23fefIU//Cj/fz6s9fxK9etAuCx4yN8+DvP4PuG333ZFnasbZ3z+JZCEKd74pRSagGIBBm7TQkXzzcXbQAHYFlCzLKJuTZNuIzvaln1guW38eUaFkIy6rBlih6aS1E8YnP92lZKVY9sqUZ/tsRAroJvDLYIyWmyhEvVYM+gYwnr25N0Nsam/DlzbYuupjidjTEypRonR4qcypQQzl4WHb9fsDEe4crOpmmXsh07qM3Y1RjjxEiBI4OFMBB3ZxR8en6QfV6qeWPHoo41lsTUEHOI2jZRN1iyHx1DpebzyJEhihVvUrD/ssu72HV8hM/ff4TLVzay51SWf/n5IXqa4/zRK7ezsnl57X+bis7EKaWUUkuc5wd7A4fzFfoyQWFmJKjj5xsoVWs0RB3WtiVpa5h9f93RWofHhgtUav7Y8RVNUxeKnsnjHRsqcHy4iGtbkzqmVD2fUtWj4gUzbLYltCYjtCUjJGMucdee8WvIlKo8fHiYlsTk2b98ucb/+uKjjBSrVGo+N29o5d23bp6X2odLYSZOgzillFJqmSlVPTLF6lgf1VUtcZri7gXPbPq+YaRYpVCp0d4QveAZ40KlxtGhAr0jRWyxxmrqRR2LtoYoLYkIyeiFdwg5OVzkmb4M7cnopMfZ25flg996mlde2c2bblg9b2VcNIhbBBrEKaWUUgtrdBYxGXVIROx5305gjOGZU1lOZ0q0JieX7Dlft4a5WApBnO6JU0oppVRdNUSds5Ir5puIsLGzgUw4izhxuXS+A7jRDNnFpkGcUkoppZY917a4vKeJnYeHcG1rXrKPvbCUSaXmUx2fISuGZMShJXFhhbovlAZxSimllLooNEQdtq1o5Kne9JT7487H8w0jxcrY17YlpGIOLckoqahDzHUmZcguJg3ilFJKKXXR6GqKkS5V6B2Zen/cVIKi1VU837ChPRn2wrXm1A93IWkQp5RSSqmLyob2BjLFoMj0+fbi5ctBS7Lu5hjr2pLLqoZj3cpVi8i/iMhpEXly3LFrROR+EdklIjtF5MZx971fRPaLyB4Redm449eLyBPhfR+TcG5URKIicmd4/AERWVev16KUUkqp5cOxLbavbKTqeWMFpicq1zwGcmWirsX161rYuqJxWQVwUMcgDvgMcNuEYx8B/swYcw3wx+HXiMh24Hbg8vCaT4jI6HfyH4E7gE3hx+hjvg0YNsZsBP4W+HC9XohSSimllpdExGFbdyMjxaDbxSjPNwzmy1Q9nyt6GrlmdfOc+vIuBXUL4owxPwGGJh4GRvueNAEnw9uvAb5ojCkbYw4B+4EbRaQbaDTG3GeCgnafA1477prPhre/ArxY5juHWCmllFLLVkcqxprWJEP5CsYESQvpYoXLOhq4YV0rHanYgrV+q4eF3hP3LuC7IvJXBAHks8PjPcD94847Hh6rhrcnHh+95hiAMaYmImmgDRio1+CVUkoptbysb0+SLVXpz5VZ1RJn7TLb93YuCx3EvR14tzHmqyLyRuDTwK3AVGGwOcdxznPfWUTkDoIlWdasWTPbMSullFJqmbItCffHmboWHF4M9dwTN5W3Al8Lb38ZGE1sOA6sHnfeKoKl1uPh7YnHz7pGRByC5dmJy7cAGGM+aYzZYYzZ0dHRMQ8vQymllFLLRdSxL7oADhY+iDsJvCC8/SJgX3j7LuD2MON0PUECw4PGmF4gKyI3h/vd3gJ8c9w1bw1vvx74obnUGsEqpZRS6pJVt7BURP4DuAVoF5HjwJ8A/wP4u3DmrES4xGmMeUpEvgQ8DdSAdxhjvPCh3k6Q6RoH7g4/IFiK/byI7CeYgbu9Xq9FKaWUUmqpkUtt8mrHjh1m586diz0MpZRSSqnzEpGHjTE7prpvoZdTlVJKKaXUPNAgTimllFJqGdIgTimllFJqGdIgTimllFJqGdIgTimllFJqGdIgTimllFJqGdIgTimllFJqGbrk6sSJSD9wZI6XtwMD8zgcVR/6Pi19+h4tD/o+LQ/6Pi19F/IerTXGTNkz9JIL4i6EiOycruCeWjr0fVr69D1aHvR9Wh70fVr66vUe6XKqUkoppdQypEGcUkoppdQypEHc7HxysQegZkTfp6VP36PlQd+n5UHfp6WvLu+R7olTSimllFqGdCZOKaWUUmoZ0iBuBkTkNhHZIyL7ReR9iz0eFRCRfxGR0yLy5LhjrSJyj4jsCz+3LOYYFYjIahG5V0R2i8hTIvLO8Li+V0uEiMRE5EEReSx8j/4sPK7v0RIkIraIPCoi3wq/1vdpiRGRwyLyhIjsEpGd4bF5f580iDsPEbGBfwBeDmwHflVEti/uqFToM8BtE469D/iBMWYT8IPwa7W4asB7jTHbgJuBd4T/hvS9WjrKwIuMMVcD1wC3icjN6Hu0VL0T2D3ua32flqYXGmOuGVdaZN7fJw3izu9GYL8x5qAxpgJ8EXjNIo9JAcaYnwBDEw6/BvhsePuzwGsXckxqMmNMrzHmkfB2luCXTw/6Xi0ZJpALv3TDD4O+R0uOiKwCXgl8atxhfZ+Wh3l/nzSIO78e4Ni4r4+Hx9TS1GWM6YUgeAA6F3k8ahwRWQdcCzyAvldLSrhEtws4DdxjjNH3aGn6v8DvA/64Y/o+LT0G+J6IPCwid4TH5v19ci70AS4BMsUxTelVapZEpAH4KvAuY0xGZKp/WmqxGGM84BoRaQa+LiJXLPKQ1AQi8irgtDHmYRG5ZZGHo87tOcaYkyLSCdwjIs/U40l0Ju78jgOrx329Cji5SGNR59cnIt0A4efTizweBYiISxDAfcEY87XwsL5XS5AxZgT4EcF+U32PlpbnAK8WkcMEW3teJCL/hr5PS44x5mT4+TTwdYKtWfP+PmkQd34PAZtEZL2IRIDbgbsWeUxqencBbw1vvxX45iKORQESTLl9GthtjPmbcXfpe7VEiEhHOAOHiMSBW4Fn0PdoSTHGvN8Ys8oYs47gd9EPjTG/hr5PS4qIJEUkNXobeCnwJHV4n7TY7wyIyCsI9iHYwL8YYz60uCNSACLyH8AtQDvQB/wJ8A3gS8Aa4CjwBmPMxOQHtYBE5LnAT4EnOLOP5w8J9sXpe7UEiMhVBButbYI/7r9kjPmgiLSh79GSFC6n/q4x5lX6Pi0tIrKBYPYNgm1r/26M+VA93icN4pRSSimlliFdTlVKKaWUWoY0iFNKKaWUWoY0iFNKKaWUWoY0iFNKKaWUWoY0iFNKKaWUWoY0iFNKXXJExBORXSLylIg8JiLvEZG6/f9QRA6LSPt5znmDiOwWkXtF5BYReXa9xqOUujhoEKeUuhQVjTHXGGMuB14CvIKgzuBiehvw28aYFxLUP9QgTil1ThrEKaUuaWFbnDuA/ymBdSLyUxF5JPx4NoCIfF5EXjN6nYh8QUReLSKXi8iD4cze4yKy6VzPJyK/Nu78fw4bz/8x8Fzgn0Tky8BvAe8Oz3le/V69Umo502K/SqlLjojkjDENE44NA1uBLOAbY0phQPYfxpgdIvIC4N3GmNeKSBOwC9gE/C1wvzHmC2FrPtsYU5zw2IeBHUAH8BHgl40xVRH5RHjt50TkRwQV+HeKyJ8COWPMX9Xtm6CUWvacxR6AUkotERJ+doGPi8g1gAdsBjDG/FhE/kFEOoFfBr5qjKmJyH3AB0RkFfA1Y8y+czzHi4HrgYeClrLE0WblSqk50iBOKXXJC3sdegQB1Z8Q9OK9mmDLSWncqZ8H/itB8/HfADDG/LuIPAC8EviuiPx3Y8wPp3sq4LPGmPfX5YUopS4puidOKXVJE5EO4J+Aj5tgf0kT0GuM8YE3EzSFH/UZ4F0Axpinwus3AAeNMR8D7gKuOsfT/QB4fTibh4i0isjaKc7LAqkLeFlKqUuABnFKqUtRfLTECPB94HvAn4X3fQJ4q4jcT7CUmh+9yBjTB+wG/nXcY70JeFJEdhHsqfvcdE9qjHka+CPgeyLyOHAP0D3Fqf8JvE4TG5RS56KJDUopNUMikgCeAK4zxqQXezxKqUubzsQppdQMiMitwDPA32sAp5RaCnQmTimllFJqGdKZOKWUUkqpZUiDOKWUUkqpZUiDOKWUUkqpZUiDOKWUUkqpZUiDOKWUUkqpZUiDOKWUUkqpZej/D973QBiEi81VAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# graph to show the changes in the prices as the days of departure are decreasing\n",
    "plt.figure(figsize = (10,5))\n",
    "sns.lineplot(x = df[\"days_left\"], y = df[\"price\"])\n",
    "plt.title(\"departure Days vs Ticket Price\", fontsize = 10)\n",
    "plt.xlabel(\"Days left\")\n",
    "plt.ylabel(\"Price\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8fd7341e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Price')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now getting the difference btween the range of prices between different flights of different classes.\n",
    "plt.figure(figsize = (10,5))\n",
    "sns.barplot(x = \"class\", y = \"price\", data = df, hue = \"airline\")\n",
    "plt.xlabel(\"Classes\")\n",
    "plt.ylabel(\"Price\")\n",
    "\n",
    "# only two classes are there"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e3e60590",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='days_left', ylabel='price'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,2, figsize = (15,5))\n",
    "sns.lineplot(x =df[\"days_left\"], y = df[\"price\"], hue = df[\"source_city\"], ax = ax[0] )\n",
    "sns.lineplot(x =df[\"days_left\"], y = df[\"price\"], hue = df[\"destination_city\"], ax = ax[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e1d5069b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zUH55S9uxLQ+nr1Smqu4H7ga2GdWYJEuSLE2ydMWKFTOxfZKkDZSBvyRJ0syYB/wG8N6qejLwI9qw/kmMOlNfU6RPVWbVxKqTq2pRVS2aP3/+FM2QJPWdgb8kSdLMWA4sr6pL2+tz6Q4E3NaG79Oebx/Iv9NA+QXALS19wYj0lcokmQdsAdw541siSeoVA39JkqQZUFXfBb6T5PEtaX/gGuA84IiWdgTwibZ8HrC4zdS/C90kfpe1ywHuSbJPu37/8KEyE3UdClzU5gGQJGlS88bdAEmSpB55DfDBJA8Fvg38Pt2JlnOSHAncDLwYoKquTnIO3cGB+4GjquqBVs+rgNOAzYDPtAd0EweemWQZ3Zn+xXOxUZKkDZuBvyRJ0gypqiuARSNW7T9J/uOA40akLwX2GJF+L+3AgSRJ0zVrQ/2TnJrk9iRXDaSdkOS6JN9K8rEkWw6sOybJsiTXJzlwIH2vJFe2de+auGVNGxZ3dku/NMnCgTJHJLmhPSaGw0mSJEmStNGZzWv8TwMOGkq7ANijqn4d+A/gGIAku9ENVdu9lTkpySatzHuBJXTXve06UOeRwF1V9TjgROBtra6tgTcBTwH2Bt6UZKtZ2D5JkiRJktZ7sxb4V9WXGJpltqo+1+45C/BVHpyx9mDgrKq6r6puBJYBe7eZbzevqkvaxDVnAIcMlDm9LZ8L7N9GAxwIXFBVd1bVXXQHG4YPQEiSJEmStFEY56z+f8CDE9XsCHxnYN3ylrZjWx5OX6lMO5hwN7DNFHVJkiRJkrTRGUvgn+SNdLPXfnAiaUS2miJ9bcsMt2NJkqVJlq5YsWLqRkuSJEmStAGa88C/Tbb3POBlA/edXQ7sNJBtAXBLS18wIn2lMknmAVvQXVowWV2rqKqTq2pRVS2aP3/+umyWJEmSJEnrpTkN/JMcBPwv4AVV9eOBVecBi9tM/bvQTeJ3WVXdCtyTZJ92/f7hwCcGykzM2H8ocFE7kHA+cECSrdqkfge0NEmSJEmSNjrzZqviJB8G9gO2TbKcbqb9Y4BNgQvaXfm+WlV/XFVXJzkHuIbuEoCjquqBVtWr6O4QsBndnAAT8wKcApyZZBndmf7FAFV1Z5K3Al9r+d5SVStNMihJkiRJ0sZi1gL/qjpsRPIpU+Q/DjhuRPpSYI8R6fcCL56krlOBU6fdWEmSJEmSemqcs/pLkiRJkqRZZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPXYvHE3QJIkSdLc2ffd+467CTPmK6/5yribIG0QPOMvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkjSDktyU5MokVyRZ2tK2TnJBkhva81YD+Y9JsizJ9UkOHEjfq9WzLMm7kqSlb5rk7JZ+aZKFc76RkqQNioG/JEnSzHtGVe1ZVYva66OBC6tqV+DC9pokuwGLgd2Bg4CTkmzSyrwXWALs2h4HtfQjgbuq6nHAicDb5mB7JEkbMAN/SZKk2XcwcHpbPh04ZCD9rKq6r6puBJYBeyfZAdi8qi6pqgLOGCozUde5wP4TowEkSRrFwF+SJGlmFfC5JJcnWdLStq+qWwHa83YtfUfgOwNll7e0HdvycPpKZarqfuBuYJtZ2A5JUk/MG3cDJEmSembfqrolyXbABUmumyLvqDP1NUX6VGVWrrg76LAEYOedd566xZKkXvOMvyRJ0gyqqlva8+3Ax4C9gdva8H3a8+0t+3Jgp4HiC4BbWvqCEekrlUkyD9gCuHNEO06uqkVVtWj+/Pkzs3GSpA2Sgb8kSdIMSfKIJI+aWAYOAK4CzgOOaNmOAD7Rls8DFreZ+nehm8TvsnY5wD1J9mnX7x8+VGairkOBi9o8AJIkjeRQf0mSpJmzPfCxNtfePOBDVfXZJF8DzklyJHAz8GKAqro6yTnANcD9wFFV9UCr61XAacBmwGfaA+AU4Mwky+jO9C+eiw2TJG24Zi3wT3Iq8Dzg9qrao6VtDZwNLARuAl5SVXe1dcfQ3Z7mAeBPq+r8lr4XD+70Pg28tqoqyaZ0M9zuBXwPeGlV3dTKHAH879aU/1tVEzPfSpIkzZqq+jbwpBHp3wP2n6TMccBxI9KXAnuMSL+XduBAkqTpmM2h/qfx4P1mJ8z6PWzbwYU3AU+hu6buTUm2moXtkyRJkiRpvTdrgX9VfYlVJ5qZi3vYHghcUFV3ttEEF7DqAQhJkiRJkjYKcz2531zcw3ayuiRJkiRJ2uisL7P6z+Q9bKd1b1vo7m+bZGmSpStWrJhWQyVJkiRJ2pDMdeA/F/ewnayuVXh/W0mSJElS38114D8X97A9HzggyVZtUr8DWpokSZIkSRud2byd34eB/YBtkyynm2n/eGb5HrZVdWeStwJfa/neUlXDkwxKkiRJkrRRmLXAv6oOm2TVrN/DtqpOBU6ddmMlSZIkSeqp9WVyP0mSJEmSNAtm7Yy/JEmSJK1vvvi0p4+7CTPi6V/64riboA2IZ/wlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqsXnjboAkSVKfJNkEWAr8d1U9L8nWwNnAQuAm4CVVdVfLewxwJPAA8KdVdX5L3ws4DdgM+DTw2qqqJJsCZwB7Ad8DXlpVN83ZxknaoL3n9Z8cdxNmxKvf8fxxN2GD4xl/SZKkmfVa4NqB10cDF1bVrsCF7TVJdgMWA7sDBwEntYMGAO8FlgC7tsdBLf1I4K6qehxwIvC22d0USVIfGPhLkiTNkCQLgOcC7x9IPhg4vS2fDhwykH5WVd1XVTcCy4C9k+wAbF5Vl1RV0Z3hP2REXecC+yfJLG2OJKknDPwlSZJmzt8Dfwn8fCBt+6q6FaA9b9fSdwS+M5BveUvbsS0Pp69UpqruB+4GthnVkCRLkixNsnTFihXrsEmSpA2dgb8kSdIMSPI84Paquny6RUak1RTpU5VZNbHq5KpaVFWL5s+fP80mSZL6yMn9JEmSZsa+wAuSPAd4GLB5kn8GbkuyQ1Xd2obx397yLwd2Gii/ALilpS8YkT5YZnmSecAWwJ2ztUGSpH4Yyxn/JH+W5OokVyX5cJKHJdk6yQVJbmjPWw3kPybJsiTXJzlwIH2vJFe2de+auMYtyaZJzm7plyZZOIbNlCRJG5GqOqaqFlTVQrpJ+y6qqpcD5wFHtGxHAJ9oy+cBi1u/ZRe6Sfwua5cD3JNkn9a3OXyozERdh7b3GHnGX5KkCXMe+CfZEfhTYFFV7QFsQrdzdMZbSZLUR8cDz0pyA/Cs9pqquho4B7gG+CxwVFU90Mq8im6CwGXAfwKfaemnANskWQb8Oa2/JEnSVMY11H8esFmSnwEPpxu+dgywX1t/OnAx8L8YmPEWuLHt6PZOchNtxluAJBMz3n6mlTm21XUu8J4k8Yi4JE3tuJcfOu4mzJg3/vO5426CNmJVdTFdX4aq+h6w/yT5jgOOG5G+FNhjRPq9wItnsKmStFHY2Ps4c37Gv6r+G3g7cDNwK3B3VX2OMc14K0mSJElSn41jqP9WdGfkdwEeDTwiycunKjIibUZmvPU2N5IkSZKkvhvH5H6/C9xYVSuq6mfAR4Hfos14CzCDM94y1Yy33uZGkiRJktR34wj8bwb2SfLwNlPt/sC1OOOtJEmSJEkzbs4n96uqS5OcC3wduB/4BnAy8EjgnCRH0h0ceHHLf3WSiRlv72fVGW9PAzajm9RvcMbbM9tEgHfS3RVAkiRJkqSNzlhm9a+qNwFvGkq+D2e8lSRJkiRpRo1jqL8kSZIkSZojBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSj00r8E9y4XTSJEmS+sC+jySpT+ZNtTLJw4CHA9sm2QpIW7U58OhZbpskSdKcsu8jSeqjKQN/4I+A19Ht6C7nwZ3fD4B/mL1mSZIkjYV9H0lS70wZ+FfVO4F3JnlNVb17jtokSZI0FvZ9JEl9tLoz/gBU1buT/BawcLBMVZ0xS+2SJEkaG/s+kqQ+mVbgn+RM4LHAFcADLbkAd36SJKl37PtIkvpkWoE/sAjYrapqNhsjSZK0nrDvI0nqjWndzg+4Cvjl2WyIJEnSesS+jySpN6Z7xn9b4JoklwH3TSRW1QtmpVWSJEnjZd9HktQb0w38j53NRkiSJK1njh13AyRJminTndX/i7PdEEmSpPWFfR9JUp9Md1b/e+hmsgV4KPAQ4EdVtflsNUySJGlc7PtIkvpkumf8HzX4OskhwN6z0SBJkqRxs+8jSeqT6c7qv5Kq+jjwzJltiiRJ0vrJvo8kaUM23aH+Lxp4+Ut097b1vraSJKmX7PtIkvpkurP6P39g+X7gJuDgGW+NJEnS+sG+jySpN6Z7jf/vz3ZDJEmS1hf2fSRJfTKta/yTLEjysSS3J7ktyUeSLJjtxkmSJI3D2vR9kjwsyWVJvpnk6iRvbulbJ7kgyQ3teauBMsckWZbk+iQHDqTvleTKtu5dSdLSN01ydku/NMnCWfoIJEk9Mt3J/T4AnAc8GtgR+GRLkyRJ6qO16fvcBzyzqp4E7AkclGQf4GjgwqraFbiwvSbJbsBiYHfgIOCkJJu0ut4LLAF2bY+DWvqRwF1V9TjgROBt67ylkqTem27gP7+qPlBV97fHacD8WWyXJEnSOK1x36c6P2wvH9IeRTc3wOkt/XTgkLZ8MHBWVd1XVTcCy4C9k+wAbF5Vl1RVAWcMlZmo61xg/4nRAJIkTWa6gf8dSV6eZJP2eDnwvdlsmCRJ0hitVd+n5b0CuB24oKouBbavqlsB2vN2LfuOwHcGii9vaTu25eH0lcpU1f3A3cA2k7RlSZKlSZauWLFiOtssSeqp6Qb+fwC8BPgucCtwKLDWk94k2TLJuUmuS3Jtkqd6/ZskSVqPrFXfp6oeqKo9gQV0Z+/3mCL7qDP1NUX6VGVGteXkqlpUVYvmz3egpiRtzKYb+L8VOKKq5lfVdnQ7w2PX4X3fCXy2qp4APAm4Fq9/kyRJ64916vtU1feBi+n6Jre14fu059tbtuXATgPFFgC3tPQFI9JXKpNkHrAFcOf0N0uStDGabuD/61V118SLqroTePLavGGSzYGnAae0un7ado5e/yZJktYXa9z3STI/yZZteTPgd4Hr6CYJPKJlOwL4RFs+D1jcRiruQncS47J2OcA9SfZp/ZfDh8pM1HUocFHrB0mSNKl508z3S0m2mtgBJtl6DcoO+xVgBfCBJE8CLgdey9D1b0kGr3/76kD5ievcfsY0r39LMnH92x1r2WZJkrRxWZu+zw7A6W1k4i8B51TVp5JcApyT5EjgZuDFAFV1dZJzgGuA+4GjquqBVtergNOAzYDPtAd0J07OTLKM7kz/4hnZWklSr003eH8H8O9JzqW7juwlwHHr8J6/Abymqi5N8k7asP5JzNr1b0mW0F0qwM477zxVmyVJ0sZljfs+VfUtRowKqKrvAftPUua4UfVW1VJglfkBqupe2oEDSZKma1pD/avqDOD3gNvozta/qKrOXMv3XA4sb7PcQjcU/zcYw/VvTnojSZJGmeG+jyRJYzXt4fpVdQ3dULR1UlXfTfKdJI+vquvpjoBP1H0EcDyrXv/2oSR/BzyaB69/eyDJPUn2AS6lu/7t3QNljgAuwevfJEnSWpipvo8kSeO2ttfpr6vXAB9M8lDg23S3x/klvP5NkiRJkqQZNZbAv6quABaNWOX1b5IkSZIkzaDp3s5PkiRJkiRtgAz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZKkGZBkpyRfSHJtkquTvLalb53kgiQ3tOetBsock2RZkuuTHDiQvleSK9u6dyVJS980ydkt/dIkC+d8QyVJG5x5426AJK1v3vP6T467CTPi1e94/ribIG1s7gdeX1VfT/Io4PIkFwCvBC6squOTHA0cDfyvJLsBi4HdgUcDn0/yq1X1APBeYAnwVeDTwEHAZ4Ajgbuq6nFJFgNvA146p1spSdrgeMZfkiRpBlTVrVX19bZ8D3AtsCNwMHB6y3Y6cEhbPhg4q6ruq6obgWXA3kl2ADavqkuqqoAzhspM1HUusP/EaABJkiYztsA/ySZJvpHkU+21w+AkSVIvtL7Hk4FLge2r6lboDg4A27VsOwLfGSi2vKXt2JaH01cqU1X3A3cD20zShiVJliZZumLFihnYKknShmqcZ/xfS3ckfMLRdMPgdgUubK8ZGgZ3EHBSkk1amYlhcLu2x0Et/RfD4IAT6YbBSZIkzbokjwQ+Aryuqn4wVdYRaTVF+lRlVk2sOrmqFlXVovnz50/VZElSz40l8E+yAHgu8P6BZIfBSZKkDVqSh9AF/R+sqo+25Ntav4X2fHtLXw7sNFB8AXBLS18wIn2lMknmAVsAd878lkiS+mRcZ/z/HvhL4OcDaWMZBidJkjQT2kmGU4Brq+rvBladBxzRlo8APjGQvrhdorgL3ejFy1o/6J4k+7Q6Dx8qM1HXocBF7QSIJEmTmvNZ/ZM8D7i9qi5Pst90ioxIm5FhcEmW0F0qwM477zyNpkiSJE1qX+AVwJVJrmhpfwUcD5yT5EjgZuDFAFV1dZJzgGvo7ghwVJvRH+BVwGnAZnSz+X+mpZ8CnJlkGd2Z/sWzvE2SpB4Yx+389gVekOQ5wMOAzZP8M20YXFXdOoPD4JZPNQyuqk4GTgZYtGiRR8slSdJaq6ovM/rkA8D+k5Q5DjhuRPpSYI8R6ffSDhxIkjRdcz7Uv6qOqaoFVbWQ7ij1RVX1chwGJ0mSJEnSjBvHGf/JOAxOkiRJkqQZNtbAv6ouBi5uy9/DYXCSJEmSJM2occ3qL0mSJEmS5oCBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSj80bdwMkrX+++LSnj7sJM+bpX/riuJsgSZIkjZVn/CVJkmZIklOT3J7kqoG0rZNckOSG9rzVwLpjkixLcn2SAwfS90pyZVv3riRp6ZsmObulX5pk4ZxuoCRpgzTngX+SnZJ8Icm1Sa5O8tqW7k5RkiRt6E4DDhpKOxq4sKp2BS5sr0myG7AY2L2VOSnJJq3Me4ElwK7tMVHnkcBdVfU44ETgbbO2JZKk3hjHGf/7gddX1a8B+wBHtR2fO0VJkrRBq6ovAXcOJR8MnN6WTwcOGUg/q6ruq6obgWXA3kl2ADavqkuqqoAzhspM1HUusP/EiQ9JkiYz54F/Vd1aVV9vy/cA1wI74k5RkiT10/ZVdSt0/SBgu5a+I/CdgXzLW9qObXk4faUyVXU/cDewzag3TbIkydIkS1esWDFDmyJJ2hCN9Rr/NgT/ycCljGmnKEmSNCajTkrUFOlTlVk1serkqlpUVYvmz5+/lk2UJPXB2AL/JI8EPgK8rqp+MFXWEWkzslP0SLgkSZoDt7WRirTn21v6cmCngXwLgFta+oIR6SuVSTIP2IJVLy2QJGklYwn8kzyELuj/YFV9tCXP+U7RI+GSJGkOnAcc0ZaPAD4xkL64TUq8C918RZe1kY/3JNmnXap4+FCZiboOBS5qlzxKkjSpcczqH+AU4Nqq+ruBVe4UJUnSBi3Jh4FLgMcnWZ7kSOB44FlJbgCe1V5TVVcD5wDXAJ8FjqqqB1pVrwLeTze30X8Cn2nppwDbJFkG/DltMmRJkqYybwzvuS/wCuDKJFe0tL+i2wme03aQNwMvhm6nmGRip3g/q+4UTwM2o9shDu4Uz2w7xTvp7gogSZI0q6rqsElW7T9J/uOA40akLwX2GJF+L62PJEnSdM154F9VX2b0NfjgTlGSJEmSpBk11ln9JUmSJEnS7DLwlyRJkiSpx8Zxjb82IDe/5YnjbsKM2fmvrxx3EyRJkiRpznnGX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHps37gZsCPZ6wxnjbsKMuPyEw8fdBEmSJEnSHPOMvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9VivA/8kByW5PsmyJEePuz2SJEkzwT6OJGlN9DbwT7IJ8A/As4HdgMOS7DbeVkmSJK0b+ziSpDXV28Af2BtYVlXfrqqfAmcBB4+5TZIkSevKPo4kaY30OfDfEfjOwOvlLU2SJGlDZh9HkrRGUlXjbsOsSPJi4MCq+sP2+hXA3lX1moE8S4Al7eXjgevnvKEP2ha4Y4zvP04b87bDxr39bvvGadzb/piqmj/G95fWyXT6OC19fennjPtvfpw25m2HjXv73faN07i3fdI+zry5bskcWg7sNPB6AXDLYIaqOhk4eS4bNZkkS6tq0bjbMQ4b87bDxr39brvbLmmtrLaPA+tPP2dj/pvfmLcdNu7td9vd9vVNn4f6fw3YNckuSR4KLAbOG3ObJEmS1pV9HEnSGuntGf+quj/Jq4HzgU2AU6vq6jE3S5IkaZ3Yx5EkraneBv4AVfVp4NPjbsc0jX0o3hhtzNsOG/f2u+0bp41526UZYR9ng7Exbzts3Nvvtm+c1ttt7+3kfpIkSZIkqd/X+EuSJEmStNEz8F9HSd6Y5Ook30pyRZKnTJH3j5Mcvpbv88PVrN8yyZ+sTd0zIckLk1SSJ7TXj05y7mrK/FmSe5NsMY36/32m2jpTklyc5MChtNcl+XaSo6cot2eS58x+CzUXVve3OSL/fkk+1ZZfMNVvRZLWR0keaH2eq5N8M8mfJ5myT5lkYZKr2vIrk7xnknyfTrLlLDR7jbQ+zZkDr+clWTHx/3sG6j82yV+sYZkZ7QsNfI/fTPL1JL81k/Wv5r1/8XtYHw3u25M8J8kNSXZeXf7Bffw032e/Of7cfzj0etK/xUnKz+j3tqZ9qJkuP1DPLyc5K8l/Jrmm/R9aMlN/72vZpvcn2W0m6zTwXwdJngo8D/iNqvp14HeB70yWv6r+sarOmKXmbAmMLfAHDgO+TDezMFV1S1UdOpwpybyhMl8DXri6yqtqzv4proEP07Z3wGLgiKo6fopyewJrFPgPfW5zKsn2ST7UDmhcnuSSJC9s6347yWVJrmuPJaup69gk/906GlckOb6lX5xkUVu+KcmV7WDaF5M8ZqD8KgfaknysLS9LcvdA3evjb2YlVXXean4r6421Obg3VH6NOwuDHZKsw4FTSTPuJ1W1Z1XtDjyLbp/2ppmouKqeU1Xfn4m61tGPgD2SbNZePwv47zG2Zzb6QhPf45OAY4C/meH6Z8y4+kFJ9gfeDRxUVTfPwlvsB6z3/ZW1lWSTcbdhdZIE+BhwcVU9tqp2A/4K2H6c7aqqP6yqa2ayTgP/dbMDcEdV3QdQVXdU1S0tcHlbC4guS/I4WPnobpLHJfn8wFHWx7b0NyT5Wgts3jzqTSfJczzw2BbwnDDrW75yex4J7AscSQuEs+qR/X9J8kngcy3tscAjgf9NdwBgoq7d22d2Rdu+XVv6xJHURya5sH1mVyY5eA43ddi5wPOSbNrathB4NPC4gWDlxUmuat/zl9LdduktwEvbNr40yd5J/j3JN9rz41vZlT63cWx7+2f4ceBLVfUrVbUX3Xe8IMkvAx8C/riqngD8NvBHSZ67mmpPbB2NPatqsrPdz2gH0y6m+41MeqCtql5YVXsCfwj820DdczpKJN1R+4uTnNsOgnywfX4kOailfRl40UCZwcD2sUm+2v623zLwm0+SE9rv6MokL53L7RqwNgf3ZswsHziVtJaq6nZgCfDq9v9qk/Y/a6Kf8keTFH10ks+mO5P6txOJrQ+17Zw0fvU+A0zs0w6jO+APrHrGvv2PXtge16U7W3dV2xf8bpKvtG3de6D+JyW5qKX/z1bPpPv6zNDZzUlsDtw1VRvatl2b5H3pDsJ/Lu3ASJLfbN/3JRP7rIEy/9bqGjmqIMnDknygvdc3kjyjpQ/3gx6R5NT22/rGbPeDkvwO8D7guVX1ny3tz9v3elWS162m/G+2dv5KkucnubS9/ny6kyoLgT8G/ixdn/B3RuWbzW0caOujktyY5CHt9ebtb/EhSfZK14+9BDhqoMzIv/V0/aEvJPkQcGVL+3i6k0dXZ+gkUZJ3tN/GhUnmt7T/2er9ZpKPJHl4S9+l/ca+luStM7T5zwB+VlX/OJFQVVcA/wY8MqP7dXulOzl1eZLzk+zQ0i/OgzHgf7Tf0MRv+aMZ/T/vvUmWts/mzQPpvzgpNmOqysdaPugC1yuA/wBOAp7e0m8C3tiWDwc+1ZaPBf6iLV8KvLAtPwx4OHAA3UyQoTso8yngaS3PD9vzyDzAQuCqMX0OLwdOacv/DvzGYHuAVwLLga0Hyvxv4P+0bbgJ2K6lvxt4WVt+KLDZ0PbPAzZvy9sCy2iTVI5p2/8VOLgtHw2c0Lb3PS3tSmDHtrzlwOfxnoE6NgfmteXfBT4y6nMbx7YD+wNfnGTdW4G3jMj/b1PU94u/gaH0i4FFA38/27blg4BPt+UXAZ+cou79aH9rc/wb+OHA+98NLGi/60voDoY8jG4k0K7t7/YcHvyfMPhb+RRwWFv+44F6fw+4gO6WXdsDNwM7zPE2PpLuTNevAte1tIWs/Df+L8AngYsmqWM4/0eBzwI3AH87kO/36f6nfpGuwzXx+fzitwP8T7rRQt8EPgI8fK6/dx8+NubHxP+nobS72v+oJcD/bmmbAkuBXUb8D/g2sEX7H/lfwE5t3S/2AePeRuDX6Q7yP4yuv/eL/QxD+zPgqraNC4H7gSe2fcHlwKnt///BwMcHyn8T2Ixun/4dupMHk+7rR33u67iND7Ttuo5u/7VXSx/ZhoFt27OtOwd4+cD2/1ZbPn7gu3448LC2vCuwtC0P/h5eD3ygLT+Bbj/3MFbtB/2/gffbkm5f8YhZ+v5/BtwJ/PpA2l50/bpH0O0XrwaePPjdTPxG6M7iXw7s3NK3Gvge/xB4xyS/o5H5ZuE7n3jczIP72Q8Ah7TlJQNt/BYPxjgnDHxvk/2t70c3YmaXgfed+A43a7+Vbdrr4sF+/18PtGWbgbL/F3hNWz4POLwtH8UM/E0Af0p3Umo4fT9G9+seQhfvzG/5Xkp3S1Xo+rMTn9tzgM+35Vcy+f+8ic9mk1b+1wfqWjST379n/NdBVf2Q7p/AEmAFcHaSV7bVHx54fupguSSPogsGP9bqubeqfkwX1B8AfAP4Ot0/v12H3nY6eebaYcBZbfksBs7gD7igqu4ceL0YOKuqfk4XALy4pV8C/FWS/wU8pqp+MlRPgP+X5FvA54EdGe9QnMHh/osZOBvQfAU4Ld2R/MmGO20B/Es7On4isPvAusHPbRzbvjvd72yydZcPpS1l5faPMnFk+4oMzZEwwkF0Iw6gGy2yUzuCelKSp6+m7DhcVlXL2+/6CrqOzROAG6vqhur+k//zJGWfShc8QzeSYsJvAx+uqgeq6ja6gPg3Z6PxUzgE+GxV/QdwZ5LfGJHnqXSXuTxzmnXuSbezfCLdCJid2hHzN9ONIHoWMNm1bR+tqt+sbnjqtXSjjSSNV9rzAcDhSa6gO8mxDaP7KRdW1d1VdS9wDfCYOWnlGqiqb9H9Hz+MNbt14o1VdWXbF1xNt61FFzQuHMj3iar6SVXdAXwB2Ju53ddPDPV/At3+9ox2RnOqNtxY3dlQ6PoAC9PNyfCoenCk3eA+7CHA+5JcSbePG/V//beBMwGq6jq6oOhX27rBftABwNHtt3UxXQA16XX36+hndMHd4P7lt4GPVdWPWgzwUeB3RpT9NbqTdM+vBy8PWACc3z6HNzB5X2m6+dbWxHe+Z3WjJf96YN376Q6+054/kG4eri2r6ost/cyB/FP9rV9WVTcO5P3TJN8EvgrsNJDv58DZbfmf6T5j6C6z+bf2ObyMBz+HfXmwrz3Yltkyql/3eGAP4IK27f+b7nub8NH2fDkr/71P9j/vJUm+Thfb7c7kfZ91Nrbrhvuiqh6g++dzcftxHjGxajDbULEwWoC/qap/muItR+Zpw4XmXJJtgGfS/YEWXXBbdCMgBv1ooMyv0/3BX9BGzDyU7ijYP1TVh5JcSje07vwkf1hVFw3U8zJgPt1R6Z8luYnuH/+4fBz4uxYIbVZVX2/bB0BV/XG6CR+fC1yRZM8RdbwV+EJVvbB9jxcPrPvRwPLYtz3JP9D9U/4p3VH44d82k6QNOrGq3r6aPF9ow9tupw31r6ofJtmLbif7DLoDbUdX1WlrsAmz7b6B5Qd48H/s6j6TqUz2/2IuHQb8fVueOLj3D0N5hg/urc6FVXU3QJKJHeC2dNfYrWjpZ/Ng52/QHkn+L90Zn0cC56/B+0qaYUl+he5/3u10/7NeU1XnD+VZOFRssv+X65vzgLfTnf3bZiD9fla+ZHZwfzy4bT8feP1zVt7O4X1DMaZ9fVVdku4Si/l0Zyona8Pw97YZU++n/gy4DXgS3ed174g8U5Uf7AcF+L2qun6K/DPl58BLgM8n+auq+n9Mf398K93n9WTglpb2buDvquq8JPvRnekfZbr5ZlxVfSXdpRlPBzapqqvaQZ3J+jCT/a3vx8r9/v3oRrQ+tap+nORiJv9NT7zXaXSjD77ZTqruNyLPTLkaWOXSxWbU/6kAV1fVU0cX+UWZ4f9rq9SVZBfgL4DfrKq7kpzGLP69e8Z/HSR5fNo16M2edEcpoTuTNfF8yWC5qvoBsDzJIa2eTdu1K+cDf5DumnmS7Jhku6G3nSzPPcCjZmrb1sChwBlV9ZiqWlhVOwE3svKRr2GHAce2/Aur6tHAjkke0zoP366qd9HtbH99qOwWwO1tR/QMxnyGoB3xvZhuGN/w2X6SPLaqLq2qvwbuoDvKOfxdbcGDEwa9coq3G8e2X0136QYAVXUU3XD++W3d8LVHe9EdxVxXE9t3Nd2cCBPv/0BVXVxVbwJeTTcMfn13HbBL2jwejB4RA91R8IntGZw08kt0Z8Q3SXft29OAy2alpSMMHNx7f+v8vYHu/9pwB+hHrJl1OUhyGvDqqnoi3QiBcR78kzZq7f/SP9IN0S26fsqr8uC1wr+a5BHjbOM6OpXusrYrh9Jvou0f28H/Xdai7oPTXd++DV1g8zXG1M9JN3HrJsD31rQNVXUXcE+SfVrS4D5sC+DWdsb0FYwe/fglugMeJPlVurP4o4L784HXtFEJJHnyNDdvrbTRuM8DXpbkyNbOQ5I8vP2mX0h3Hfiw79Od8Pl/LeiFlft6RwzknapPOJhvrpxB15/9AEB1E23enWTiTPzLBvJO9299C+CuFvQ/AdhnYN0v8WDQ/T/o5hKC7jO5tdU9+J5f4cHf12D6urgI2LSNzgW6+RmAyUaWXg/MTzf3FOnmQVjbkRmb0/Wf7m4nvJ69lvVMi4H/unkkcHq62z58i25oxrFt3abtzPVr6Y52DnsF3bCXb9ENJfrlqvoc3fCoS9rogXOBR6WbLGtiAsGRearqe8BX0k02MpeT+x1GNxPmoI/QzYY5mcUjynyspb8UuKoNnXkC3T+gQR8EFiVZSvcHf93aNXtGfZjuSPZZI9adkG6ymqvodhjfpBvOt1va5H7A3wJ/k+QrTH45AIxn2y8CHpbkVQNpD2/P/wC8cmIUQ+u4vI1ue9ZZu8zjdXTDyLZezYG29VYb0rUE+Nd0k/tN1ubXAX+e5DK6iUPvbukfo7u+7pt038dfVtV3Z7XRK1ubg3tr61JgvyTbtJ39iyfJN1mHQNLc2Kztw66mGwr+ObqDcNANF74G+Hrb9/0T6+/Z/NVqw3zfOWLVR4CtW3/lVXTXm6+py+jmCvoq8NaquoW53ddPfI9X0A23PqKNZF2bNhwJnJxuArjw4D7sJOCIJF+lG8E16iDxScAmrV97NvDKahNnD3kr3aUD32q/rZma3G1SbSTbQXSjD3eiO/B8Gd3+6v1V9Y1Jyt0GPB/4hzby81i6yzr/je5E0IRPAi9s38PvTJFvrnyQbp6BwZNZv0+3HZcAg5fgTvdv/bN0Z7e/RfedfXVg3Y+A3ZNcTneSYeJkz/+h+4wvYOXf32uBo5JMHCRbZ+2A5QuBZ6W7nd/VdN/DLZPk/yld3+ht6S5fuIK1vDNDVX2Tboj/1XQHGb+yNvVM18TkEZpB7azYonbN1kzU9yTgfVW192ozSzMs3XXXJwJPoZvL4kfAP1bV2UmeBryDLhAL8PdV9d4p6jqWbiKWtw+lX0w3uc3S4b+fJO+mGz76abohcFvSDbFcBiwZyLdfq+N5M7Hdc62N+vlJVVWSxXQT/R28HrTrYuD4qvrsQNqf0h2V3qmq9mjD8BZV1aunqGch3aRYq+RPd5/ct1fVxUl+n+62UrfS7Uw3qapXD/522oGov6Q7iHIl3cHPV87ohkuSpi3JI9soSJIcTTcJ7WvH3CytoSSH0k1a/Ypxt0Uzz8B/Fsxk4J/kj+lmm3xdO9svqYfakf730B1A+T7wB1W1bKyNkiRpGtoIxmPozvj+F91Z+xXjbZXWRDvR8mzgOdVN5queMfCXJEmSJKnHNthrriStv5K8kVWvz/6XqjpuHO3R3EnyRFa9xc59VfWUcbRHkiRJnvGXJEmSJKnXnNVfkiRJkqQeM/CXJEmSJKnHDPylnkry6SRbTrLupiTbtuV/n9OGSZIkreeSvKDdmpAkhyTZbdxtktaF1/hLG5Ekobtd3LeZoVtOSpIkjUOSeVV1/xy8z2nAp6rq3Nl+L2m2eMZf6oEkH09yeZKrkyxpaTcl2TbJwiTXJjkJ+Dqw01DZH7bn/ZJcnOTcJNcl+WA7UECSvZJ8sb3H+Ul2mOttlCRJG7Ykj0jyr0m+meSqJC9Nsn+SbyS5MsmpSTZteQdHJy5KcnFbPjbJyUk+B5yRZPskH2t1fjPJb7V8L09yWZIrkvxTkk2maNdBSb7eyl/Y0l6Z5D2tvhcAJ7S6Hpvk6wNld01y+Wx9ZtJM8XZ+Uj/8QVXdmWQz4GtJPjK0/vHA71fVnwC0eH6UJwO7A7cAXwH2TXIp8G7g4KpakeSlwHHAH8zCdkiSpP46CLilqp4LkGQL4Cpg/6r6jyRnAK8C/n419ewF/HZV/STJ2cAXq+qFLbh/ZJJfA14K7FtVP2snP14GnDFcUZL5wPuAp1XVjUm2HlxfVf+e5DwGzvgnuTvJnlV1BfD7wGlr9WlIc8jAX+qHP03ywra8E7Dr0Pr/qqqvTqOey6pqOUCSK4CFwPeBPYAL2gGDTYBb173JkiRpI3Ml8PYkbwM+BfwAuLGq/qOtPx04itUH/udV1U/a8jOBwwGq6gHg7iSvoDs48LXWd9kMuH2SuvYBvlRVN7Y67pzGdrwf+P0kf053gGHvaZSRxsrAX9rAJdkP+F3gqVX14zYU7mFD2X40zeruG1h+gO5/RICrq+qp69ZSSZK0MWtn9fcCngP8DfC5KbLfz4OXJa9pvybA6VV1zDSaFWBNJz37CPAm4CLg8qr63hqWl+ac1/hLG74tgLta0P8EuiPXM+l6YH6SpwIkeUiS3Wf4PSRJUs8leTTw46r6Z+DtwG8BC5M8rmV5BfDFtnwT3Vl7gN+botoL6S4PIMkmSTZvaYcm2a6lb53kMZOUvwR4epJdJvKOyHMP8KiJF1V1L3A+8F7gA1O0TVpvGPhLG77PAvOSfAt4KzCdIf3TVlU/BQ4F3pbkm8AVdDtqSZKkNfFE4LJ2OeEbgf9Nd438vyS5Evg58I8t75uBdyb5N7pRiJN5LfCMVv5yYPequqbV/bnWP7oAGDkxcVWtAJYAH239nLNHZDsLeEObhPCxLe2DdCMFphq1IK03vJ2fJEmSJK2BJH8BbFFV/2fcbZGmw2v8JUmSJGmaknwMeCzdxILSBsEz/pIkSZJ6r92ieNOh5FdU1ZXjaI80lwz8JUmSJEnqMSf3kyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8NeOSHJukRjw+P+629VGSRyQ5K8n32uf8yknynTbwXdzf8n85ydFJtpjjZk9bkr9Mst+42wGQ5CWjPt8kFyc5dwxNkiRtxOxzza016HM9JMmfJ7kqyY+T3JHk0iRHD+T51fb9bTlX7dfGbd64G6Deuhs4aESaZt6rgOcDhwP/DfznFHmvA34fCLA1sA/wF8CSJM+sqptmt6lr5S+B9wAXj7kdAC8BtgVOG0r/E+Bnc94aSZLsc82l6fa53gO8DDgOuBTYkq7P9Xzg+JbnV4E30fUpvj9L7ZV+wcBfs+X+qvrqdDIm2ayqfjLbDeqxJwDXV9VHppH3R0Pfy78m+SfgMuADwDNmo4FrYzZ+F0kCbFpV985kvVV1zUzWJ0nSGrDPNXdW2+dK8nC6kyxvrKoTBlZ9tPVDpLFwqL/mVJKFbWjUy5KckeT7wCfbuq2T/FOS25Lcm+TfkzxlqPyWST6U5EdJbk3yxiRvT3LTQJ5jk9wx4r0ryauH0v4wydVJ7kvyX0n+cmj9aUmWJnlWkm+19/1ykt2H8m2S5Jgk/9HqWp7ktLbuqCT3JHnkUJlntDb9+hSf17ZJTm9Dyn7chpQvGlh/E3Ak8OSJ4X2T1TWZqloOvAXYL8kTBuqezvdRbSjbO5PcmeT7Sd6d5KEDeXZIcmqSbyf5SfuM/u9QnpG/i7Z92wBvGhi+uN9A/ucNtee0JEsHXh/bhtf9dpKvAfcCL27rfjvJF9vn+r0k70vyqMk+p/Z9/h7w9IG2HNvWrTTUf+B9n9J+Pz9pv5tdkmyX5ONJfpjk2iTPHPFeU/4uJUlancn2rW2dfa5V2zxTfa5HAA8Bvju8oqqq1bUf7bsAbmz13TTwXnsmubC1464kH0yy/cD6ie/2fyQ5s23z7UneNLRNC5Kc09b9JMl/JnnrZJ+B+s3AX7Mmybyhx+BRzrcD99AFYf8vyabA54FnAW8ADgFWAJ9P8ssD5T4APBt4HbAEOABYvJbtewPwXuDjwPPa8luHd1TAzsAJdMO1DgO2A84Z2p5/At4MnNPqej3dP36AD9KNrjl0qN5XAl+vqm9N0cyPAwfSDcd/Kd3f7BeSPK6tfyHwaboh/E9tj7VxQXveB2ANvg/otnUB3ZC2/0v3vRw3sH5b4E7gz+mGIp5AdyT83SPasdLvom3f3cApA9v39TXctocDpwPvb+9/WZJ9gQvpdsqH0v2enkP3+5rMW4EvAN8YaMv7V/O+JwMn0v1udgbOBD4MfBl4Ed0wwX9Jd3YAWKPfpSRJgH0u1qM+V1WtAL4DHJvkRRl9UuHr7X2g6w88tdVPkvl0lzc+HPgfwGuApwMXZOCkSXMC8OO2ve+jO1Fy1MD6M4Cd6L6/Z9N9rptO8Rmoz6rKh48ZfQDHAjXi8bvAwrb8saEyRwI/BXYdSJtHd+3UCe317q3sSwfyPJIuqLxp6P3vGNGuAl7dljcHfgi8aSjPW+iCwU3a69OA+4fadUir6wnt9RPa6z+d4jP5Z+CLQ+3+4UR7JilzUKv36QNpj6DbOf/TQNppwNJpfC+T5qPbCRTwv6b7fQx8ptcBvzSQ9ka6ndDWk7zXPLod2b3AQ1vayN9FW3cHcOxQ2kT+5021jQO/xYOH8v0b8IWhtGe2vHtM8RmeC1w8Iv1i4NwR7zv43f1JS/vrgbTdWtqz1+R36cOHDx8+fFTZ55rkM1kf+lzPBG5vdT4ALKUL9B86kOd5bf3CobLH013zv/lA2t4t72Ht9cR3+7mhsu+jO6nwS+31D4Hnj/t36mP9eHjGX7PlbuA3hx6XDqz/16H8vwtcTjfcaV6SifknvghMDLP6zfZ83kShqvohD56tXhNPpfuH/i+DR8iBi4Dt6c5gT7ipqm4YeD1xPfdEnonr4k+b4v1OAX4nya+01y+h28l+aIoyewMrquqLEwlV9SPgU8BvT1FubQxfczad72PCJ6rq5wOvPwpsBuwB3XX1SV6X5JokP6GbBO+DdAcbdh6qa/h3MRMK+MzEi3Z2/al0ZxAGv/svt7btNUPv+1O6AwwTlrXni0ak7die1+R3KUkS2OcaNvY+V1VdBDyWbtTCqXSXLZ4AXJRkdfHX3nQB/Q8G6rsMuGlEWz429PqjwKN58PO6AvibJK9MMtzn0kbGyf00W+6vqqXDiUm2aYu3Da3alm6Y+aiZ0SdmTP1l4J5adVKa29eifdu256snWb8T8F9t+ftD637anh/WnrehmzTvB0zuYuDbdEPN/ppuqPsnqurOKcrswKqfEy1t6ynKrY2JwHPi/abzfUwY/vwnXu/Qnl9HN8zweLpOxV10HYp/4MHPcMKo7V1Xd1XVTwdebwVsApzUHsN2mqH3vWfogMhEG74/kVBVP22jFyc+hzX5XUqSBPa5hl3MetDnqqp7gLOAs9qlCm8G/g/dzP6fWE1bRn1Wo9oyVR/sZrpLFo6ju+xwyyTfBF5fVReuwaaoJwz8NS7DE6LcSTcM6lUj8t7Xnr8LPCqrzki73VD+e4GVroFKstWI94NumNWof/TXT9LuUb4HPCLJ5pPtiKqqkpxKd9u8M+mO2D57NfXeyqrbBt3R8al2XmvjgPZ8SXuezvcxYbiNE69vbc8vBv6lqt44kSHJbpO0Y7qTE07Myj98rduonfNwnd9vacfSXas37JZptmE2zOTvUpIksM819j5Xa9MJdIH/E5g68J+qLZcPpU3ZB6uq/wZe2UYZ7E3X9zkvyc5V9b012ght8Bzqr/XFhcDjgJuraunQ48qW52vt+QUThdqsrc8aqms53c5qx4G0A4byXAL8BHj0iPdb2o7STtfE0O3DV5PvNLqhV6fSXX+1uuFylwLbJXnaREIbpv5cumHpMyLJArod0ReqamLnO53vY8LBQ8PWXkT32V7VXm/GqgcLXrYGTfwpq44MuJ3uTMWvDWzHI5nG5IZt6N5XgcdP8t1PFfiPastMmsnfpSRJo9jnWtWM9bmSPCTJliNW7dqeJw5+DI9mGGzLgYOTAib5Tbrr+ofb8sKh1y+iC/qXDyZW1c+ru+Xjm+kmDXzMajdEveMZf60vzgD+GLg4ydvphmhtQ3d08rtVdWJVXZ3kPOC9STan+8f2BrqJ5AZ9lm4Hc2qSdwC7tLp/oaq+n+5WbO9M8hjgS3QHwn4VeEZVDf8jnVRVXZ/kZOAdSbZrdW0JHFpViwfy3ZLks3Q7kb+pqgdWU+/5Sb4CnJ3kaLqj3H9BF0ifMFXZKTwiyT501/RvCfwW3WdzD91QuAmr/T4G8j6K7rq999FNBvTXwHsGhtRdAPxpkkvphhC+jK7DMV3XAc9tn90P6e6fe0+STwB/luS/6M7iv57ue5+OvwQuTPJzugn77qGbb+C5dPfd/Y8p2nJwkkPodqq3rOZAwRqZyd+lJEmTsM+1ar0z2efaAviPJKfT3Q3obuDxwDF0ByEmrsufONnyR0nOAn7cDrz8Hd1ojPOTvI1ucsLjgSuBjwy91+5J/qmlP41u4sbXVtXPk2wBnE/3ff8H3dxKr6cbzXHtGm6T+mBdZgb04WPUg0lmeG3rFjJiNva2bgvgnXS3QPkpXWD1UWDfgTxb0V0v9SO6I6Z/TXf9+E1DdT2b7vqoH9NNsPZrDMwwO5Dv5XTDpn5Cd+35pcCfD6w/jaHZW0dtA901439Ft/OcaPsHRmzjH7ayu476fEbkn0/3D/uu1sYvAr85lGeVNk5S12k8ONvvA3RD174CHA1ssZbfR9Hdpu89rY130127v+lAnkfS3RLozvZ4Pw/OZLvHNH4Xe9Gdof9Ry7NfS9+ebqjcD+iuDVwy/Fms5rf4FLoOyw9a3dfQ7WxX+SwGymxLt8O+s7Xl2JZ+MavO6n/HUNn9Brd56DNco9+lDx8+fPjwUWWfi/Wwz0V36cPRdAclbmt1LQP+EVgwlPf1rQ9zPyvfLeHJdKMbfkx3cuNDwPYjPpeX0d0m+B66OxC8GUjLsyndLP/Xt3ruoJus8Inj/t36GM9j4ochbbDa0epDq2rhuNuyOknOAXaoqt8Zd1tmQpICXlNV7xl3WyRJ0uyyz7V+SLIQuJHuVn2fGnNztIFwqL80B5I8ke4WOS8CFq8muyRJktaCfS5pNAN/aW58km6Y+ElVde64GyNJktRT9rmkERzqL0mSJElSj3k7P0mSJEmSesyh/s22225bCxcuHHczJEmz7PLLL7+jquaPux3SXLKfI0n9N1Ufx8C/WbhwIUuXLh13MyRJsyzJf427DdJcs58jSf03VR/Hof6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJayDJTkm+kOTaJFcneW1LPzbJfye5oj2eM1DmmCTLklyf5MCB9L2SXNnWvStJWvqmSc5u6ZcmWThQ5ogkN7THEXO46ZKkDdS8cTdAkiRpA3M/8Pqq+nqSRwGXJ7mgrTuxqt4+mDnJbsBiYHfg0cDnk/xqVT0AvBdYAnwV+DRwEPAZ4Ejgrqp6XJLFwNuAlybZGngTsAio9t7nVdVds7zNkqQNmIG/NIl9373vuJswY77ymq+MuwmS1BtVdStwa1u+J8m1wI5TFDkYOKuq7gNuTLIM2DvJTcDmVXUJQJIzgEPoAv+DgWNb+XOB97TRAAcCF1TVna3MBXQHCz48k9uojdfNb3niuJugITv/9ZXjboJ6YM6H+id5/MAQuCuS/CDJ65JsneSCNmztgiRbDZSZseFxkiRJM6X1MZ4MXNqSXp3kW0lOHejL7Ah8Z6DY8pa2Y1seTl+pTFXdD9wNbDNFXaPatiTJ0iRLV6xYsXYbKEnqhTkP/Kvq+qras6r2BPYCfgx8DDgauLCqdgUubK+Hh8cdBJyUZJNW3cTwuF3b46CW/ovhccCJdMPjJEmSZkySRwIfAV5XVT+g65c8FtiTbkTAOyayjiheU6SvbZmVE6tOrqpFVbVo/vz5k22GJGkjMO7J/fYH/rOq/otuSNvpLf10uqFuMDA8rqpuBCaGx+1AGx5XVQWcMVRmoq5zgf0nRgNIkiStqyQPoQv6P1hVHwWoqtuq6oGq+jnwPmDvln05sNNA8QXALS19wYj0lcokmQdsAdw5RV2SJE1q3IH/Yh68Jm37ds3cxLVz27X0mRwetxKHwEmSpDXVTiacAlxbVX83kL7DQLYXAle15fOAxe1SxF3oRile1vo79yTZp9V5OPCJgTITM/YfClzUTnScDxyQZKt2KcEBLU2SpEmNbXK/JA8FXgAcs7qsI9LWdnjcyglVJwMnAyxatGjkMDlJkqQh+wKvAK5MckVL+yvgsCR70vU5bgL+CKCqrk5yDnAN3R0Bjmoz+gO8CjgN2IxuUr/PtPRTgDPbRIB30p0soaruTPJW4Gst31smJvqTJGky45zV/9nA16vqtvb6tiQ7VNWt7Yj57S19XYbHLR8aHidJkrROqurLjD7J8OkpyhwHHDcifSmwx4j0e4EXT1LXqcCp022vJEnjHOp/GCvfemZwSNsRrDzUbaaGx0mSJEmStFEZyxn/JA8HnkUbAtccD5yT5EjgZtpR7pkcHidJkiRJ0sZmLIF/Vf2Yocn2qup7dLP8j8o/Y8PjJEmSJEnamIx7Vn9JkiRJkjSLDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqcfGMqu/Nhw3v+WJ427CjNn5r68cdxMkSZIkac55xl+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHnNW/2nY6w1njLsJM+LyEw4fdxMkSZIkSXPMM/6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPXYWAL/JFsmOTfJdUmuTfLUJFsnuSDJDe15q4H8xyRZluT6JAcOpO+V5Mq27l1J0tI3TXJ2S780ycIxbKYkSZIkSWM3rjP+7wQ+W1VPAJ4EXAscDVxYVbsCF7bXJNkNWAzsDhwEnJRkk1bPe4ElwK7tcVBLPxK4q6oeB5wIvG0uNkqSJEmSpPXNnAf+STYHngacAlBVP62q7wMHA6e3bKcDh7Tlg4Gzquq+qroRWAbsnWQHYPOquqSqCjhjqMxEXecC+0+MBpAkSZIkaWMyjjP+vwKsAD6Q5BtJ3p/kEcD2VXUrQHveruXfEfjOQPnlLW3HtjycvlKZqrofuBvYZrghSZYkWZpk6YoVK2Zq+yRJkiRJWm+MI/CfB/wG8N6qejLwI9qw/kmMOlNfU6RPVWblhKqTq2pRVS2aP3/+1K2WJEmSJGkDNI7AfzmwvKouba/PpTsQcFsbvk97vn0g/04D5RcAt7T0BSPSVyqTZB6wBXDnjG+JJEmSJEnruTkP/Kvqu8B3kjy+Je0PXAOcBxzR0o4APtGWzwMWt5n6d6GbxO+ydjnAPUn2adfvHz5UZqKuQ4GL2jwAkiRJkiRtVOaN6X1fA3wwyUOBbwO/T3cQ4pwkRwI3Ay8GqKqrk5xDd3DgfuCoqnqg1fMq4DRgM+Az7QHdxIFnJllGd6Z/8VxslCRJkiRJ65uxBP5VdQWwaMSq/SfJfxxw3Ij0pcAeI9LvpR04kCRJkiRpYzaOa/wlSZIkSdIcMfCXJEmSJKnHDPwlSZLWQJKdknwhybVJrk7y2pa+dZILktzQnrcaKHNMkmVJrk9y4ED6XkmubOve1SYspk1qfHZLvzTJwoEyR7T3uCHJEUiStBoG/pIkSWvmfuD1VfVrwD7AUUl2A44GLqyqXYEL22vausXA7sBBwElJNml1vRdYQnfXol3beoAjgbuq6nHAicDbWl1bA28CngLsDbxp8ACDJEmjGPhLkiStgaq6taq+3pbvAa4FdgQOBk5v2U4HDmnLBwNnVdV9VXUjsAzYO8kOwOZVdUm77fAZQ2Um6joX2L+NBjgQuKCq7qyqu4ALePBggSRJIxn4S5IkraU2BP/JwKXA9lV1K3QHB4DtWrYdge8MFFve0nZsy8PpK5WpqvuBu4FtpqhLkqRJGfhLkiSthSSPBD4CvK6qfjBV1hFpNUX62pYZbt+SJEuTLF2xYsUUzZMk9Z2BvyRJ0hpK8hC6oP+DVfXRlnxbG75Pe769pS8HdhoovgC4paUvGJG+Upkk84AtgDunqGsVVXVyVS2qqkXz589fm82UJPWEgb8kSdIaaNfanwJcW1V/N7DqPGBilv0jgE8MpC9uM/XvQjeJ32XtcoB7kuzT6jx8qMxEXYcCF7V5AM4HDkiyVZvU74CWJknSpOaNuwGSJEkbmH2BVwBXJrmipf0VcDxwTpIjgZuBFwNU1dVJzgGuobsjwFFV9UAr9yrgNGAz4DPtAd2BhTOTLKM707+41XVnkrcCX2v53lJVd87SdkqSesLAX5IkaQ1U1ZcZfa09wP6TlDkOOG5E+lJgjxHp99IOHIxYdypw6nTbK0mSQ/0lSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknpsLIF/kpuSXJnkiiRLW9rWSS5IckN73mog/zFJliW5PsmBA+l7tXqWJXlXkrT0TZOc3dIvTbJwzjdSkiRJkqT1wDjP+D+jqvasqkXt9dHAhVW1K3Bhe02S3YDFwO7AQcBJSTZpZd4LLAF2bY+DWvqRwF1V9TjgROBtc7A9kiRJkiStd9anof4HA6e35dOBQwbSz6qq+6rqRmAZsHeSHYDNq+qSqirgjKEyE3WdC+w/MRpAkiRJkqSNybgC/wI+l+TyJEta2vZVdStAe96upe8IfGeg7PKWtmNbHk5fqUxV3Q/cDWwzC9shSZIkSdJ6bd6Y3nffqrolyXbABUmumyLvqDP1NUX6VGVWrrg76LAEYOedd566xZIkSZIkbYDGcsa/qm5pz7cDHwP2Bm5rw/dpz7e37MuBnQaKLwBuaekLRqSvVCbJPGAL4M4R7Ti5qhZV1aL58+fPzMZJkiRJkrQemfPAP8kjkjxqYhk4ALgKOA84omU7AvhEWz4PWNxm6t+FbhK/y9rlAPck2addv3/4UJmJug4FLmrzAEiSJEmStFEZx1D/7YGPtbn25gEfqqrPJvkacE6SI4GbgRcDVNXVSc4BrgHuB46qqgdaXa8CTgM2Az7THgCnAGcmWUZ3pn/xXGyYJEmSJEnrmzkP/Kvq28CTRqR/D9h/kjLHAceNSF8K7DEi/V7agQNJkiRJkjZm69Pt/CRJkiRJ0gwb16z+krTees/rPznuJsyIV7/j+eNugiRJktYDBv6SVvHFpz193E2YMU//0hfH3QRJkiRprBzqL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJayDJqUluT3LVQNqxSf47yRXt8ZyBdcckWZbk+iQHDqTvleTKtu5dSdLSN01ydku/NMnCgTJHJLmhPY6Yo02WJG3gDPwlSZLWzGnAQSPST6yqPdvj0wBJdgMWA7u3Micl2aTlfy+wBNi1PSbqPBK4q6oeB5wIvK3VtTXwJuApwN7Am5JsNfObJ0nqGwN/SZKkNVBVXwLunGb2g4Gzquq+qroRWAbsnWQHYPOquqSqCjgDOGSgzOlt+Vxg/zYa4EDggqq6s6ruAi5g9AEISZJWYuAvSZI0M16d5FvtUoCJM/E7At8ZyLO8pe3YlofTVypTVfcDdwPbTFHXSEmWJFmaZOmKFSvWfqskSRs8A39JkqR1917gscCewK3AO1p6RuStKdLXtsyqK6pOrqpFVbVo/vz5k2WTJG0EDPwlSZLWUVXdVlUPVNXPgffRXYMP3Vn5nQayLgBuaekLRqSvVCbJPGALuksLJqtLkqQpGfhLkiSto3bN/oQXAhMz/p8HLG4z9e9CN4nfZVV1K3BPkn3a9fuHA58YKDMxY/+hwEVtHoDzgQOSbNUuJTigpUmSNKV5426AJEnShiTJh4H9gG2TLKebaX+/JHvSDb2/CfgjgKq6Osk5wDXA/cBRVfVAq+pVdHcI2Az4THsAnAKcmWQZ3Zn+xa2uO5O8Ffhay/eWqpruJIOSpI3Y2AL/diubpcB/V9Xz2i1qzgYW0u0wX9JmrCXJMXS3tnkA+NOqOr+l78WDO8xPA6+tqkqyKd3suHsB3wNeWlU3zdnGSZKk3qqqw0YknzJF/uOA40akLwX2GJF+L/DiSeo6FTh12o2VJInxDvV/LXDtwOujgQuralfgwvZ6Ru9/K0mSJEnSxmadAv8kF04nbUSeBcBzgfcPJA/es/Z0Vr6X7Uzd/1aSJOkX1rYvI0nShmSthvoneRjwcLpr27biwdvLbA48ehpV/D3wl8CjBtK2bxPdUFW3Jtmupe8IfHUg38Q9a3/GNO9/m2Ti/rd3TGf7JElSv81AX0aSpA3G2l7j/0fA6+h2jJfz4M7yB8A/TFUwyfOA26vq8iT7TeO9ZvL+t8NtWUJ3qQA777zzNJoiSZJ6Yq37MpIkbWjWKvCvqncC70zymqp69xoW3xd4QZLnAA8DNk/yz8BtSXZoZ/t3AG5v+dfl/rfLh+5/O7wdJwMnAyxatGiVAwOSJKmf1rEvI0nSBmWdZvWvqncn+S26mfjnDaSfMUWZY4BjANoZ/7+oqpcnOYHunrXHt+fBe9l+KMnf0R2Vn7j/7QNJ7kmyD3Ap3f1v3z1Q5gjgEla+/60kSdIvrE1fRpKkDc06Bf5JzgQeC1xBd6s96IbUr83O8njgnCRHAjfTbmMzk/e/lSRJGjTDfRlJktZL6xT4A4uA3db2bHpVXQxc3Ja/B+w/Sb4Zu/+tJEnSgHXqy0iStCFYp9v5AVcBvzwTDZEkSRoD+zKSpN5b1zP+2wLXJLkMuG8isapesI71SpIkzQX7MpKk3lvXwP/YmWiEJEnSmBw77gZIkjTb1nVW/y/OVEMkSZLmmn0ZSdLGYF1n9b+HbuZbgIcCDwF+VFWbr2vDJEmSZpt9GUnSxmBdz/g/avB1kkOAvdelTkmSpLliX0aStDFY11n9V1JVHweeOZN1SpIkzRX7MpKkPlrXof4vGnj5S3T3wvU+uJIkaYNgX0aStDFY11n9nz+wfD9wE3DwOtYpSZI0V+zLSJJ6b12v8f/9mWqIJEnSXLMvI0naGKzTNf5JFiT5WJLbk9yW5CNJFsxU4yRJkmaTfRlJ0sZgXSf3+wBwHvBoYEfgky1NkiRpQ2BfRpLUe+sa+M+vqg9U1f3tcRowfwbaJUmSNBfsy0iSem9dA/87krw8ySbt8XLgezPRMEmSpDlgX0aS1HvrGvj/AfAS4LvArcChgJPkSJKkDYV9GUlS763r7fzeChxRVXcBJNkaeDvdTlSSJGl9Z19GktR763rG/9cndpQAVXUn8OR1rFOSJGmu2JeRJPXeugb+v5Rkq4kX7Sj5uo4ikCRJmiv2ZSRJvbeuO7Z3AP+e5Fyg6K6RO26dWyVJkjQ37MtIknpvnQL/qjojyVLgmUCAF1XVNTPSMkmSpFlmX0aStDFY56FsbefoDlKSJG2Q7MtIkvpuXa/xlyRJkiRJ6zEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqsTkP/JM8LMllSb6Z5Ookb27pWye5IMkN7XmrgTLHJFmW5PokBw6k75XkyrbuXUnS0jdNcnZLvzTJwrneTkmSJEmS1gfjOON/H/DMqnoSsCdwUJJ9gKOBC6tqV+DC9pokuwGLgd2Bg4CTkmzS6novsATYtT0OaulHAndV1eOAE4G3zcF2SZIkSZK03pnzwL86P2wvH9IeBRwMnN7STwcOacsHA2dV1X1VdSOwDNg7yQ7A5lV1SVUVcMZQmYm6zgX2nxgNIEmSJEnSxmQs1/gn2STJFcDtwAVVdSmwfVXdCtCet2vZdwS+M1B8eUvbsS0Pp69UpqruB+4GthnRjiVJliZZumLFihnaOkmSJEmS1h9jCfyr6oGq2hNYQHf2fo8pso86U19TpE9VZrgdJ1fVoqpaNH/+/NW0WpIkSZKkDc9YZ/Wvqu8DF9Ndm39bG75Pe769ZVsO7DRQbAFwS0tfMCJ9pTJJ5gFbAHfOxjZIkqSNS5JTk9ye5KqBtDmZpDjJEe09bkhyxBxtsiRpAzeOWf3nJ9myLW8G/C5wHXAeMLEDOwL4RFs+D1jcdoK70E3id1m7HOCeJPu0HeXhQ2Um6joUuKjNAyBJkrSuTuPBCYUnzPokxUm2Bt4EPAXYG3jT4AEGSZImM44z/jsAX0jyLeBrdNf4fwo4HnhWkhuAZ7XXVNXVwDnANcBngaOq6oFW16uA99NN+PefwGda+inANkmWAX9O2/lKkiStq6r6EquOJJyLSYoPpOs33VlVdwEXsOoBCEmSVjFvrt+wqr4FPHlE+veA/Scpcxxw3Ij0pcAq8wNU1b3Ai9e5sZIkSdOz0iTFSQYnKf7qQL6JyYh/xjQnKU4yMUnxZBMeS5I0pbFe4y9JktRzMzlJ8bQmL/7FG3v3IklSY+AvSZK07uZikuLJ6hrJuxdJkiYY+EuSJK27uZik+HzggCRbtUn9DmhpkiRNac6v8ZckSdqQJfkwsB+wbZLldDPtHw+ck+RI4GbaXENVdXWSiUmK72fVSYpPAzajm6B4cJLiM9skxXfS3RWAqrozyVvpJkcGeEtVebtiSdJqGfhLkiStgao6bJJVsz5JcVWdCpw67cZKkoRD/SVJkiRJ6jUDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnHDPwlSZIkSeoxA39JkiRJknrMwF+SJEmSpB4z8JckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6zMBfkiRJkqQeM/CXJEmSJKnH5jzwT7JTki8kuTbJ1Ule29K3TnJBkhva81YDZY5JsizJ9UkOHEjfK8mVbd27kqSlb5rk7JZ+aZKFc72dkiRJkiStD8Zxxv9+4PVV9WvAPsBRSXYDjgYurKpdgQvba9q6xcDuwEHASUk2aXW9F1gC7NoeB7X0I4G7qupxwInA2+ZiwyRJkiRJWt/MeeBfVbdW1dfb8j3AtcCOwMHA6S3b6cAhbflg4Kyquq+qbgSWAXsn2QHYvKouqaoCzhgqM1HXucD+E6MBJEmSJEnamIz1Gv82BP/JwKXA9lV1K3QHB4DtWrYdge8MFFve0nZsy8PpK5WpqvuBu4FtRrz/kiRLkyxdsWLFDG2VJEmSJEnrj7EF/kkeCXwEeF1V/WCqrCPSaor0qcqsnFB1clUtqqpF8+fPX12TJUmSJEna4Iwl8E/yELqg/4NV9dGWfFsbvk97vr2lLwd2Gii+ALilpS8Ykb5SmSTzgC2AO2d+SyRJkiRJWr+NY1b/AKcA11bV3w2sOg84oi0fAXxiIH1xm6l/F7pJ/C5rlwPck2SfVufhQ2Um6joUuKjNAyBJkiRJ0kZl3hjec1/gFcCVSa5oaX8FHA+ck+RI4GbgxQBVdXWSc4Br6O4IcFRVPdDKvQo4DdgM+Ex7QHdg4cwky+jO9C+e5W2SJEmSJGm9NOeBf1V9mdHX4APsP0mZ44DjRqQvBfYYkX4v7cCBJEmSJEkbs7HO6i9JkiRJkmaXgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiTNoCQ3JbkyyRVJlra0rZNckOSG9rzVQP5jkixLcn2SAwfS92r1LEvyriRp6ZsmObulX5pk4ZxvpCRpg2LgL0mSNPOeUVV7VtWi9vpo4MKq2hW4sL0myW7AYmB34CDgpCSbtDLvBZYAu7bHQS39SOCuqnoccCLwtjnYHknSBszAX5IkafYdDJzelk8HDhlIP6uq7quqG4FlwN5JdgA2r6pLqqqAM4bKTNR1LrD/xGgASZJGMfCXJEmaWQV8LsnlSZa0tO2r6laA9rxdS98R+M5A2eUtbce2PJy+Upmquh+4G9hmuBFJliRZmmTpihUrZmTDJEkbpnnjboAkSVLP7FtVtyTZDrggyXVT5B11pr6mSJ+qzMoJVScDJwMsWrRolfWSpI2HZ/wlSZJmUFXd0p5vBz4G7A3c1obv055vb9mXAzsNFF8A3NLSF4xIX6lMknnAFsCds7EtkqR+MPCXJEmaIUkekeRRE8vAAcBVwHnAES3bEcAn2vJ5wOI2U/8udJP4XdYuB7gnyT7t+v3Dh8pM1HUocFGbB0CSpJEc6i9JkjRztgc+1ubamwd8qKo+m+RrwDlJjgRuBl4MUFVXJzkHuAa4Hziqqh5odb0KOA3YDPhMewCcApyZZBndmf7Fc7FhkqQNl4G/JEnSDKmqbwNPGpH+PWD/ScocBxw3In0psMeI9HtpBw4kSZoOh/pLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GNjCfyTnJrk9iRXDaRtneSCJDe0560G1h2TZFmS65McOJC+V5Ir27p3tfvc0u6Fe3ZLvzTJwjndQEmSJEmS1hPjOuN/GnDQUNrRwIVVtStwYXtNkt3o7k+7eytzUpJNWpn3AkuAXdtjos4jgbuq6nHAicDbZm1LJEmSJElaj40l8K+qLwF3DiUfDJzelk8HDhlIP6uq7quqG4FlwN5JdgA2r6pLqqqAM4bKTNR1LrD/xGgASZIkSZI2JvPG3YAB21fVrQBVdWuS7Vr6jsBXB/Itb2k/a8vD6RNlvtPquj/J3cA2wB2Db5hkCd2IAXbeeecZ3RhJkqQN1V5vOGPcTdCQy084fNxNkLQB2xAm9xt1pr6mSJ+qzMoJVSdX1aKqWjR//vx1aKIkSZIkSeun9Snwv60N36c9397SlwM7DeRbANzS0heMSF+pTJJ5wBasemmBJEmSJEm9tz4F/ucBR7TlI4BPDKQvbjP170I3id9l7bKAe5Ls067fP3yozERdhwIXtXkAJEmSJEnaqIzlGv8kHwb2A7ZNshx4E3A8cE6SI4GbgRcDVNXVSc4BrgHuB46qqgdaVa+iu0PAZsBn2gPgFODMJMvozvQvnoPNkiRJkiRpvTOWwL+qDptk1f6T5D8OOG5E+lJgjxHp99IOHEiSJEmStDFbn4b6S5IkSZKkGWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT1mIG/JEmSJEk9ZuAvSZIkSVKPGfhLkiRJktRjBv6SJEmSJPWYgb8kSZIkST1m4C9JkiRJUo8Z+EuSJEmS1GMG/pIkSZIk9ZiBvyRJkiRJPWbgL0mSJElSjxn4S5IkSZLUYwb+kiRJkiT12LxxN0CSJEmSND77vnvfcTdBQ77ymq/MaH2e8ZckSZIkqccM/CVJkiRJ6jEDf0mSJEmSeszAX5IkSZKkHjPwlyRJkiSpxwz8JUmSJEnqMQN/SZIkSZJ6bN64GyBJWn8c9/JDx92EGfPGfz533E2QJElaL/T6jH+Sg5Jcn2RZkqPH3R5JkqSZYB9HkrQmehv4J9kE+Afg2cBuwGFJdhtvqyRJktaNfRxJ0prqbeAP7A0sq6pvV9VPgbOAg8fcJkmSpHVlH0eStEZSVeNuw6xIcihwUFX9YXv9CuApVfXqgTxLgCXt5eOB6+e8oQ/aFrhjjO8/ThvztsPGvf1u+8Zp3Nv+mKqaP8b3l9bJdPo4LX196ueM07j/52g8/N43Xhvzdz9pH6fPk/tlRNpKRzmq6mTg5LlpztSSLK2qReNuxzhszNsOG/f2u+1uu6S1sto+Dqxf/Zxx8n/OxsnvfePldz9an4f6Lwd2Gni9ALhlTG2RJEmaKfZxJElrpM+B/9eAXZPskuShwGLgvDG3SZIkaV3Zx5EkrZHeDvWvqvuTvBo4H9gEOLWqrh5zs6ayMQ/F25i3HTbu7XfbN04b87ZL62wD7OOMm/9zNk5+7xsvv/sReju5nyRJkiRJ6vdQf0mSJEmSNnoG/pIkSZKkGZFkyyR/Mu52aGUG/usgyQNJrhh4HD3D9b9gpuvUuktSSc4ceD0vyYokn5rB9/j3maprXSV5YdvmJ7TX85NcmuQbSX7Hf+yd9hm9Y+D1XyQ5ti3/cZLDV1P+lUneM8m6v5rRxkqSJM2eLYGx9A/TmdUYN8kGOU+egf+6+UlV7TnwOH4mK6+q82a6zkHreuAiybFJ/mIt3vfiJDcnyUDax5P8cE3rmuI93p9kt5mqb8iPgD2SbNZePwv47zWpYHX/MKrqt9aybbPhMODLdLNGA+wPXFdVTwa+wxr+Y5+Lf8hjch/woiTbDq+oqn+sqjPWoe45CfzX5G8wyX5J1up32g5y/DzJrw+kXZVkYVv+dJItV1PHxUlWuUdvkj2TPGdt2iVp45Bkk3G3Qeq544HHtvjiA0leAJDkY0lObctHJvm/bfnPWz/gqiSvm6riUXmTLExybZKTgK+z8u1OB8v+MMnbklye5PNJ9m79iW8PtPFhrc1XtpNcz2jpr0zyL0k+CXwuySOSnJrkay3fwTPxwc2mPna+xyrJs5OcM/B6v/YDIckBSS5J8vX2w3lkS78pyZtb+pUDZ1Z/cQYwyWlJ3pXk39uP89CW/ktJTkpydZJPtQ7zodNs7lofuJiBI13fB/ZtdW0J7LAmhVe3066qP6yqa9a2cdPwGeC5bfkw4MMDbdu6Hcj4VpKvTgQ37UDJyUk+B5zRXp868A/nTwfq+GF73q+tPzfJdUk+OHHAJMlzWtqX229jxkYcDLTjkXTf05HA4iR7An8LPCfJFcDbePAf+wmtzBvaP8FvJXlzSxv+h/w77fX72m/3c2kHUlrg9tVW/mNJtlpN+sXtn/hlSf4jye/M9OcwTffTzSL7Z8MrMnCQLMlvtm24JMkJSa4ayProJJ9NckOSv235jwc2a5/xB+diQ6ZpP2BdDlAtB944akVVPaeqvr+W9e4JGPj/f/buPFyyor7/+PsjKCDKPhBkyaBiDKBCGBHjhqKIK6gQhriAIY4a1BiXiPGXSDAYd1whEkXAKIsQFY2KCCIubAMimxBGQZyAMAgiLqDA9/fHqWZ6mr537szcZabn/Xqefm53napz6nT37VPfc6rqSKuBdL2pehcvrk3y7aW0tf4lyfeAfZPs39pclyd57wzvipZTBoLAvvbGsPbFI9ox9qIk3+21tzUlDgF+UlU70t19pNc22wLoXZh7MvDdJDsDrwSeAOwKvCrJTsNWupS8fwYcX1U7VdXPxqjXusDZVbUzcAfwb3QX8F4EHNbyHAxQVY+ha+Mfl2TttuyJwAFV9Qy6NsxZVfV44OnA+5OsO5E3Z6YY+K+YXmO899gPOAPYte+D3w84Kd1VwP8HPLOq/gKYD7ypb123tPSjgLGuom9O90/yfLozaQAvBmYDjwH+lu4LuULagfHC9iN6dF+geXaSdyf5DvD3ffkfkeTivtfbJrloKZs5kcVXkF8M/Hdf+fQConZQ3q+l79YO6p8HLltKUHzf1cB0Z/cOT/KjFjhu1lfv89q+HpZl63FwIl0gvDbwWOD8vmX/Cvywqh5Ld6W2/0rvzsBeVfXX7fWjgWcDuwDvTPLAIdvaCXgj3Q/lw4Ente1+EnhOVT0ZmLUMdV8WewPfqKr/BW6l+834F+Ck9mP+NtoPe1W9NckewLZtf3YEdk7y1Lau+36QgZ+1fJ+oqu3pTgS9pOU7Hnhbe/8uA965lHSANatqF7r3qT99un0CeGmS9cfJ8xngNVX1ROCegWU70v1mPAbYL8lWVXUIi0/SvXQqKj2eJC/I4qEd30qyWbor868B/qH99j0l3RCQU9v/04VJnrSUVX8V2D7Jnw3Z5nXtN5Mk/9z+v89IckKW7GW0b/pO+KS7n/lhdO9d7zdZ0ohqval2BB5PdzLxGMZva93Zjpnn0J24fgbd7+7jk+w9fTXXZBgWBAIbMnb74mjg9S3oewtw5HTXeTX1XboLPtsBVwI3JdmcLmb5AV1s88Wq+m1V/YYuJhjrIs54eX9WVectpS5/AL7Rnl8GfKeq/tiez+7bxmcBquoqujbro9qyM6rq1vZ8D+CQdBfCzgbWBrZeyvZnlIH/ihm8Yn5SVd1N94V6Qbqr4s8Dvkz3g7Qd8P32BTkA+NO+dfUC34tY/MUb9KWqurddyd6spT0Z+EJL/wXw7WWo/7ATFwAfr6rHV9UOwDp0Jxp6Nqiqp1XVfWOZq+onwO3prgZD9yN87FK2fSbw1HRX7ucCJ/UtezHdgfhxwDPpzqD1egTsAryjqnpnC+8XFA/Z1rrAeVX1OLqD/ata+keAj7QzdTcspb5LqKpL6T6n/YGvDSzu/8E4C9i4LxA8rap+35f3f6rqrqq6BbiZxZ9rvwuqamFV3Qtc0rb7aOCnVXVty3PCkHKTYX+6kxy0v/svJf8e7fFDuiv7j6Y7AMP9f5CvrapL2vOLgNntfdqgqr7T0o+j+54MTe9b10T+f6ZcVf2a7gTFG4YtT9e75aFV1ZvD4fMDWc6sqtur6k66g+OfMvO+B+zaTticCPxjVV0H/AdwRPvt+y7d/9MR7f/pJcCnlrLee+l6j4w5jKGdvHsJ3f/5i4HBrv1LnPCpqj/Qd2Kqqk5C0urgI8BZwG2M39bq/SY8nu6q36LWbvscSx5TtGoYKwgc1r54CF0vtS+078YnWcbeplo+VfV/dCdk9qRrh38X+CvgN1V1B5Bxig8aL+9vJ1D+j7X4Xvb30g3TpLWxe72ZJ7qNAC/piwO3rqofT6AOM2aVnJhgFXASXTeRW4ELq+qOdiX6jKoaK3C6q/29h7E/l7v6nmfg7/L4fTtTPujpSf4ReDCwEXAF8JW2bKyG9KeAVyZ5E90Vy12Wsu176AKK/YB1quq6LB7y/2TghKq6h+6s4HfoDtK/pguCr+1bzwVVtRCg/ZDPbuvt9we6q4vQHQCe1Z4/ke6KNnQB2AeWUudBp7UyuwEb96UP+0x6PzKDP0r9n+lYn/2wPCvyuU9Iko3probskKSANej2Y7wr6gH+vao+ObCu2Sx939dh+U3k/2e6fJjupMdnhixb2uc2ke/DdNuSrtfS5sCDgGvHyPdMYLu+/+P1kjy0HdTH8nngHUm2GWP5k4Ev906WpQ2b6rNSnPCRNHOSHEgX3L+O7mLLeG2t3nFoyo+hmhZjfY7D2hcPAH41RrtXk+8O4KF9r8+lO0n/DLo28yntAd3JgGPTDW0MXbf7l4+x3mXJu7zOAV4KnJXkUXRX8a8G/mIg3+nA65O8vqoqyU5V9cNJrsuk8or/1Dib7svxKhYHyufRddF+JECSB7cv04r6HvCSdGP9N6MLQpdb60J+JLBPG9vyn3RdV3rGOpt2KvAcut4BF1XVLyewuROBjwEnD6Qvy9m8iQRK/Wf3JjOYOgY4rKouG0jv/WCQZDe6YRy/nqRt9lwFPLwF1NCdQJls+9B1zf/TqppdVVvRBX1b9uUZ/GE/HfibLB5TuUWSTSe6waq6Hbgti8fpv5yuG9bQ9OXaqynWuoCdTDcvwuCy24A7kuzakuYO5hnDH8cYBjIdPkbXC+gxwKtZ8veg3wOAJ/ad+d5iKUE/7UrbB+mGjAwz0RMlK8tJEknTqHX1fgvwsnbFbqJtrfOBpyXZpPU83J+V9JiicZ0D7N0+53XpgsDvDsvY2mHXJtkX7htW+rjpq+rqpcUB3083bPf9dJ/LmlW1gO7iyEYtjaq6mK6n8AV0/5ufGiuAXpa8K+BIYI0kl9HFcQdW1V1D8r0LeCBwabr5mt41yfWYdDaUVsw67Spzzzeq6pCquifdRGsH0nUzo6oWtbPSJyRZq+X/f8D/rmAdTqWbZf3ytq7zgdtXYH29Rv0tLXjbh8Vn5MZUVXcmOZ1ujoL7BTxj+C7w79y/m/o5wKuTHEf3w/BU4K103cYn03l03YhPYuIB2H1aT4OPDFl0KPCZJJcCv6N9ByZTVf0+3W30vpHkFrofwMm2P4vnkug5lW5c5KdbPX6Z5PvtB+/r1Y3z/3Pg3Hbl9zfAy7j/WPbxHAD8R5IHAz+lGzoyXvrK6IN0V5+GOQj4zyS/pTtJOJH/16PpDiwX1/SP81+fxXet6P8u3wGs1/f6m3T73Jvkcce+rpbjORb4R5Y8gdTzPeCTSf6d7nj1PLqTkeMZPBklaXS9jq6d8O12zJlP1/Yat61VVTcmeTvd8MgAX6uqL09XpTU5quriJMeyuA30KbrhHmN5KXBUkv9HF7CdCPxoSiu5GqvF81n19NqOf6Qbhtuf90PAhya43vvlbUMQd5hA2Yf0PT902LI23PLAIWWPpW8oc+uN+OqJ1HllkcUXQrWqSvKQqvpN65p9AfCkNt5/aeXuoZvMoucbVXVIultrzAWuo7td28+q6tAkZwNvqar5rfyhdONzPtBe70oXGG7duumPtd0l1tOX/puqekgbFvE+uh4EBfxbVZ3Urp6/paqe3/IPvv44ML+qju3fRm+9Lc8+wPOr6sAk2wL/RXfQ/x9gXlVtsbT3bWXR97mHblK5a6rqiJmul8bX+9za80OAzavq75dSbFokuZcl57v4EPAT4Ai64P884PFVtVu7inYK3Ri51wM/pvse/jldkH5OVb1mjO0cCMypqte112+gO4m2TRv2c11bfkv7ndmfbnKdRXTjcv9z4H98E7r//dlJNqLrefJAumEnjvOXJEmrPQP/EdAawBvQjb99XzsjNRP1eAuwflX980xsf1m1K8e/b+Ny5gL7V9VKfw/OniT/QHcF9kF0k+m9qqp+N7O10tKkm0Tz7XTB8c/oupAtmtlarbz6TnA9mK430LzW1U+SJI2gdjHzzCGLdp/IcOIk5wNrDSS/fMjw3NWKgb8mRZIvAo8AnlHdDPUrvTZe/ON0V/x/BfxNG3skaSWR7vad29ENQzquqv59hqskSZK0yjHw15RpJwMGZ+t+W1WdPhP1kTS9krwSGBzG8P2qOngm6iNJkrS6MvCXJEmSJGmEeTs/SZIkSZJGmIG/JEmSpFVOkje2yV8lLYVd/SVJkiStcvpv/zrTdZFWdl7xl2ZAkkPb7Q+nav0bJPm7qVp/33aWONOe5GtJNpjq7UqSpNVLknWT/E+SHyW5PMk7gYcB307y7ZZn/ySXteXv7Sv7myQfTHJxkjOTzGrpb0hyZZJLk5w4M3smTQ8Df2nEJFkD2ABY5sC/lV0WbwTuC/yr6rlV9atl3a4kSdJS7AncUFWPq6odgA8DNwBPr6qnJ3kY8F7gGcCOwOOT7N3KrgtcXFV/AXwHeGdLPwTYqaoeC7xmunZEmgkG/tI0SfKOJFcn+RbwZy3tEUm+keSiJN9N8uiWfmyS/2hp/5vk+S19dku7uD3+sqXvluTb7Z7nlwHvAR6R5JIk72/Lv9pXl48nObA9vy7JvyT5HrBvkj2SnNvW/4UkDxljf97A/c+0X5dkk1bPq5J8qp11/1ySZyb5fpJrkuzS8q+b5JgkFyb5YZK9puK9lyRJq7zLgGcmeW+Sp1TV7QPLHw+cXVWLqupu4HPAU9uye4GT2vP/Ap7cnl8KfC7Jy4C7p7b60sxac6YrIK0OkuwMzAV2ovu/uxi4CDgaeE1VXZPkCcCRdGeqAWYDTwMeQRdcPxK4GXhWVd2ZZFvgBGBOy78LsENVXZtkdnu+Y9v+bkup4p1V9eQkmwD/DTyzqn6b5G3Am4DDBgtU1UeTvInuTPuwsXWPBPYF5gEXAn9Nd6B9IfBPwN7AO4Czqupv2hCBC5J8q6p+u5T6SpKk1UhV/W9rTz0X+Pck3xzIkmVZXfv7PLqTAy8E/jnJ9u2kgTRyDPyl6fEU4ItV9TuAJKcBawN/CXwhue9YtVZfmZOr6l7gmiQ/BR4NXAt8PMmOwD3Ao/ryX1BV1y5n/XpnwXcFtgO+3+r0IODc5VzntVV1GUCSK4Azq6qSXEZ3UgNgD+CFffMdrA1sDfx4ObcpSZJGUOvKf2tV/VeS3wAHAncADwVuAc4HPtIuYtwG7A98rBV/ALAPcCLdhYjvJXkAsFVVfbv1evxr4CHAr6Ztp6RpZOAvTZ/BW2g8APhV76r8BPIX8A/ATcDjWvk7+5aPd5X8bpYc2rP2wPJe2QBnVNX+46xrou7qe35v3+t7WfzbE+AlVXX1JGxPkiSNrscA709yL/BH4LXAE4GvJ7mxjfN/O/BtuvbF16rqy63sb4Htk1wE3A7sB6wB/FeS9Vv+I5ynSKPMMf7S9DgHeFGSdZI8FHgB8Dvg2iT7AqTzuL4y+yZ5QJJHAA8HrgbWB25sPQFeTnfQGqZ3BrznZ8B2SdZqB7jdxyh3HvCkNqyAJA9O8qgx8g7bzrI6HXh9WveCJDutwLokSdKIqqrTq+qxVbVjVT2+quZX1ceq6tFV9fSW5/NV9Ziq2qGq/nGg/D9X1c5V9Yw2D8Afq+rJffnfMzN7Jk0PA39pGlTVxXTd6S8BTgW+2xa9FDgoyY+AK4D+ye2uppt59ut08wDcSTcHwAFJzqPr5j/0Kn9V/ZKuu/7lSd5fVT8HTqZNYgP8cIxyi+i6zp2Q5FK6EwGPHmfXjqY70/7tcd+Asb0LeCBwaZLL22tJkiRJkyhVg72JJc20JMcCX62qU2a6LpIkSZJWbV7xlyRJkiRphHnFX9JSJfkisM1A8tuq6vSZqI8kSZKkiTPwlyRJkiRphNnVX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAXzMuyaFJasjjWzNdt1GUZN0kJyb5ZXufD5xA/t8m+V2Sh07C9ndr291hRdc1ZN3XJfnAUra7tMfs9vf5k10/SdKqx3bK9JpoOyXJsX2fxd0t//eSHJJk/Smo16btuzB7IH0q2zXTvs2l1GfHJCcl+UWSPyS5oX0O2/XlWaItluSvltbW1PRYc6YrIDW3A3sOSdPkey3wAuAVwP8BP1lK/r2AB/c9/68V3P7FwBMnsN3J1ttuz5OADwAvBm7sS7+x5btq+qomSVrJ2U6ZPsvSTrkKeCUQYCNgV+AtwLwkz6iq6yaxXpsC7wTOBvrXO5XtmpnY5lBJXgycCJwD/APdZ7Ml8NfA94ENW9YXAb/sK/pXwCbAsdNVVw1n4K+Vxd1Vdd5EMiZZp6p+P9UVGmGPBq6uqlMnmH9/4Nq+5+MG/kkCrFVVd46R/mtgQp/1ZBrcbpJN2tMfDmkYTHv9JEkrNdsp02dZ2im/Hfhc/ifJJ4ELgM8AT5+KCvabiXbNdG8zycOA44ATgAOrqvoWf76/l2RV/XC66qVlY1d/rdT6ul2/NMnxSX4FfKUt2yjJJ5PclOTOJD9I8oSB8hsk+Xzrqn5jknck+UCS6/ryHJrkliHbriSvG0j72yRXJLkryc+S/OPA8mOTzE/yrCSXtu1+L8n2A/nWSPL2JP/b1rUwybFt2cFJ7kjykIEyT291euw479cmSY5r3d1+l+TsJHP6ll8HHATs1OseN9a6Wv4NgWfTneE9EdgjycYDeQ5NckuSJye5ELgT2Hec9CW6pyX5TpKTh2z7A0mubycMSPKeJJcl+U17vz6X5E/Gq//yyJCu/r1ua6374I1Jbk/ywXSe274TdyT5UnvP+te31O+pJGnVZDtliTLT3k4ZpqoWAocBuyV5dN+6J/J5HNTev9+3Nsx3kmyfrqv9ZS3bt/vrNtiuaWmV5O+TvDvJoiQ3J/lEkrX68mye5JgkP23b+98k/5bkQW35sm7zwUk+mq4b/p1JLkyyx8D+nZ3klCR/nWRBkl8n+XqSLZfytv4t8CDgzQNBf+89/2rfNu7r6t++My8BnpbFwzIOXZHvkJafgb9WGknWHHikb/EHgDuAfYF3tx/ObwHPAt4K7A0sAr6VJYPBzwDPAd4IzAP2AOYuZ/3eChwFfAl4fnv+rsGDLrA18H7gcLor5JsCJw/szyeBfwVObut6M7BuW/Y5ut44+wys90Dg4qq6dJxqfokuUH8LsB/d//i3kzyyLX8R8DW6rnFPZMmu78PsAzyQLug/YYx6QTcU4DjgU3RdIS9YSnq/E4HnJ+ntf693wL7AyX0HmE2BdwPPo/s8Hw6clWSNpezDZJkL7ELXpfB9wJuADwHvAv4ZeA3wNODfewWW4XsqSVrJ2U5ZKdspYzmj/d0VJnY8TvJU4D/oejY+B/gb4AfA+nTDAF/a1nnwBOv2ZuBhwMvo3u9XA3/ft3wT4Fa69sSeLc8rgY+15cu6zf9s5Q+nex9/TtcD4skD+Z4AvK7Vbx7wF8DRS9mXpwHzq+p+J6CW4l3At4Ef9tX/U6zYd0jLq6p8+JjRB3AoUEMezwRmt+dfHChzEPAHYNu+tDXpxjq9v73evpXdry/PQ+h+ZK8b2P4tQ+pVwOva8/WA3wDvHMhzGPALYI32+ljg7oF67d3W9ej2+tHt9RvGeU/+C/jOQL1/06vPGGX2bOt9Wl/aunQHtk/2pR1L9+M9kc/mLODKvtdXAGeP8fntNcH03Vr6Du31rPaeze3L88SWZ84Y9VoD2KLleWpf+nXABya4b89v5WcPpPe+c88fWO+C3ufc0i5o9d6mL+19wE3L8j314cOHDx8r9wPbKcPekxlvp4yXD1irbetty/B5vAW4aJzt7dDWudtA+m70tWv6PptzBvJ9CThvnPWvSTde/k7gQcuyTeDPgXuBA/ryPAC4HDi9L+1surkpNuxLe2Nb1zrj1O0q4IQJ/r9cR19bDDiFgbbj8n6HfKzYwyv+WlncDjx+4HF+3/L/Gcj/TOAi4NremfeW/h2g12Xs8e3vab1CVfUbFp8FXhZPpDs4faH/bD9dYLwZ3eQmPddV1TV9r69sf3t5euPNjh1ne58GnpLk4e31X9EdED4/TpldgEVV9Z1eQlX9FvgqMHi2d6mSbE53hvfEvuQTgKcm2WIgewFfH7KasdIXZ6haRPc+7teXvB/wk6qa31ef57RuebfTNVoWtkWPmsDuTIazq+qevtcL6D7rawfSZvW66TGx76kkaeVnO2VJM95OWYoMvJ7I53EJ3RCDI5I8te9Yvry+OfD6Svo+h3TemOTKJL8H/kh3JXwtul4Zy+LxdPv8hV5CVd3bXg++txdW1W0D9YLugsp4lnnYxVIsz3dIK8DAXyuLu6tq/sDjjr7lNw3k34Su+9YfBx6vBLZqef4EuKPuP8HOzctRv95EcFcMbO/bLX2rvry/Gij7h/Z37fZ3Y7rJaH49zvbOBn5K1+UJuv36clXdOk6Zzbn/+0RL22iccmPpdcH7RroxiBvQBfFhySAd4Laq+gP3N1b6oBOB5yRZL8kD6LpKntRbmOTxdA2jhcDL6Ro4u7bFazM9fjXw+g9jpIVuHBxM7HsqSVr52U5Z0tnMfDtlPL0gtre9pX4eVfWt9vqpdPt3S5Ij+4ciLqNfDbz+A0u2Wd4IfBD4It1dk3ah69IPy9622Rz4TVX9biD9JuDB/XMLjFGvpW3z/1j2kxFLczbL/h3SCnBWf60qBs8y3grMp7vly6C72t9fAA/N/WfX3XQg/50sDtSA+ya1G9wedN3Dhx20rh6j3sP8Elg3yXpjHVSrqpIcQ3c7ms/Sna19zlLWeyP33zfozvQvz4/o/u3v+WMs+1Df67HOAk/07PAX6cYi7gX8jG5M3El9y19E1xVwv6quP1iSP53gumfSRL6nkqRVn+2U6W+njKc3qd257e+EjsdVdRxwXJJZdLf7PQL4NXDIJNcPuoscX6iqd/QSkmy3nOu6EXhIkgcPBP+bAb+rqhVtc5wNvCPJRpMVmC/nd0grwCv+WlWdCTwSuH7IGfjeDKgXtr8v7BVqs4c+a2BdC+kOvP1dnPYYyHMu8HvgYUO2N3jWf2nOan9fsZR8x9J1CTuG7kzr0rr+nQ9s2ianAboZXukmw/veMtSP1u1qF7oD3tMHHu8D5iTZdlnWOZ7W5eybdD0J9gN+XEtO7LIO8Mde0N+8lJXfRL6nkqTRYzvl/iatnTKeNkP9PwPfrqreCY9lOh5X1aKq+iTwXaAXjE/kyviyWIf7XwQYbNtMdJsX0p18um+yvDZZ4z5Mznv7aboeEh8YtjDJ88YpO9jTod+xLNt3SCvAK/5aVR1PN4v62e2WIT+l65q2C/CLqjqiqq5IchpwVJL16M6GvhUY7Ab1DbqD5TFJPghs09Z9n6r6VZJDgY+0K83n0J04exTw9Kp60UQrXlVXJzka+GCSTdu6NgD2qaq5ffluSPINugPivw+MLx+23tOTfB84KckhdGfs30J3YHn/ROvX7E83ScwHquqG/gVJrqSbgXYu3Wytk+Ukuh/+24GPDyw7A3hjkg/T3SbpL+lmyV3ZLfV7OpOVkyRNGdsp91/vZLZTetZNsivdMLsN6NoHr6G7w8Ir+/It9fNI8q90Qw7OBm4BdqKb66h3tf96us/hgDbf0B/75yJaDmcAb0hyPt0kgy+lOznRb0LbrKofJzkB+Hj7Li0AXkU3UeOwXg7LpH3WBwIntBMrvUB9C7oLNk9j7OEaVwF7Jdmb7iTWDb225bJ+h7RivOKvVVJV3Ul39fkMutvNfBP4CLAtS94y7sC27MN0ZyvPZMnJ6qju1iQvoTvj+CW6gPKvh2zzfXS3PXkO8GW6ie5eSnc2eFn9Xav3y+huW/Nhuh/2QV9qfz8zwfW+iO49+TDdhC4BnlFVC5axfvsDZw4G/QBVdXPbxv73K7Vivkw3ad8m3P8z+hrwNrrP6TS6A8zzJ3n7k24ZvqeSpBFiO2VMk9VO6Xk0XW+H79FNjPcMunHzO1XVz3qZJvh5XEh3df8/gNPpAuZDW77eOl4F7Ew3KWCvx8byOozuM/q39vcPwBv6MyzjNl9Fdwvlf6b7/P+U7g5Fk9KboqpOpbsV4K/o3pOz6IZ9/pZu8sSxHEn3fh9DV/95A8u/1P5O9Duk5ZQle85Ko6+d6d2nqmbPdF2WJsnJwOZV9ZSZroskSZp6tlO0OvE7NH3s6i+thJI8hu72Mi+m61IvSZK0UrCdohXld2j6GfhLK6ev0HV5P7KqTpnpykiSJPWxnaIV5XdomtnVX5IkSZKkEebkfpIkSZIkjTC7+jebbLJJzZ49e6arIUmaYhdddNEtVTVrpushTSfbOZI0+sZr4xj4N7Nnz2b+/BW5FackaVWQ5GdLzyWNFts5kjT6xmvj2NVfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRNkiQbJDklyVVJfpzkiUk2SnJGkmva3w378r89yYIkVyd5dl/6zkkua8s+miQtfa0kJ7X085PMnoHdlCStYgz8JUmSJs9HgG9U1aOBxwE/Bg4BzqyqbYEz22uSbAfMBbYH9gSOTLJGW89RwDxg2/bYs6UfBNxWVY8EjgDeOx07JUlatRn4S5IkTYIk6wFPBT4NUFV/qKpfAXsBx7VsxwF7t+d7ASdW1V1VdS2wANglyebAelV1blUVcPxAmd66TgF27/UGkCRpLAb+kiRJk+PhwCLgM0l+mORTSdYFNquqGwHa301b/i2An/eVX9jStmjPB9OXKFNVdwO3AxsPq0ySeUnmJ5m/aNGiydg/SdIqysBfkiRpcqwJ/AVwVFXtBPyW1q1/DMOu1Nc46eOVuX9i1dFVNaeq5syaNWucakiSRp2BvyRJ0uRYCCysqvPb61PoTgTc1Lrv0/7e3Jd/q77yWwI3tPQth6QvUSbJmsD6wK2TvieSpJFi4C9JkjQJquoXwM+T/FlL2h24EjgNOKClHQB8uT0/DZjbZurfhm4SvwvacIA7kuzaxu+/YqBMb137AGe1eQAkSRrTmjNdgVXBzm89fqarMCkuev8rZroKkiSNutcDn0vyIOCnwCvpLrScnOQg4HpgX4CquiLJyXQnB+4GDq6qe9p6XgscC6wDfL09oJs48LNJFtBd6Z+7IpUdlTYO2M6RpPEY+EuSJE2SqroEmDNk0e5j5D8cOHxI+nxghyHpd9JOHEiSNFF29ZckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiz+kuSJEmSRtrhL9tnpqswad7xX6cscxmv+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI2wGQn8k/xDkiuSXJ7khCRrJ9koyRlJrml/N+zL//YkC5JcneTZfek7J7msLftokrT0tZKc1NLPTzJ7BnZTkiRJkqQZN+2Bf5ItgDcAc6pqB2ANYC5wCHBmVW0LnNlek2S7tnx7YE/gyCRrtNUdBcwDtm2PPVv6QcBtVfVI4AjgvdOwa5IkSZIkrXRmqqv/msA6SdYEHgzcAOwFHNeWHwfs3Z7vBZxYVXdV1bXAAmCXJJsD61XVuVVVwPEDZXrrOgXYvdcbQJIkSZKk1cm0B/5V9X/AB4DrgRuB26vqm8BmVXVjy3MjsGkrsgXw875VLGxpW7Tng+lLlKmqu4HbgY2nYn8kSZIkSVqZzURX/w3prshvAzwMWDfJy8YrMiStxkkfr8xgXeYlmZ9k/qJFi8avuCRJkiRJq6CZ6Or/TODaqlpUVX8E/hv4S+Cm1n2f9vfmln8hsFVf+S3phgYsbM8H05co04YTrA/cOliRqjq6quZU1ZxZs2ZN0u5JkiRJkrTyWHMGtnk9sGuSBwO/B3YH5gO/BQ4A3tP+frnlPw34fJIP0fUQ2Ba4oKruSXJHkl2B84FXAB/rK3MAcC6wD3BWmwdAkiRJ4vrDHjPTVZg0W//LZTNdBUkruZkY438+3YR7FwOXtTocTRfwPyvJNcCz2muq6grgZOBK4BvAwVV1T1vda4FP0U349xPg6y3908DGSRYAb6LdIUCSJGmqJbmu3W74kiTzW5q3LZYkzZiZuOJPVb0TeOdA8l10V/+H5T8cOHxI+nxghyHpdwL7rnhNJa2OPv7mr8x0FSbF6z74gpmugrQ6e3pV3dL3unfb4vckOaS9ftvAbYsfBnwryaPaRY7ebYvPA75Gd9vir9N32+Ikc+luW7zfdO2YJGnVM1O385MkSVqdeNtiSdKMMfCXJEmaXAV8M8lFSea1tGm/bbF3L5Ik9cxIV39JkqQR9qSquiHJpsAZSa4aJ++U3ba4qo6mm0eJOXPmOMmxJK3GDPwlSZImUVXd0P7enOSLwC602xZX1Y2TeNvihePdtlgay5M+9qSZrsKk+f7rvz/TVZBWCXb1lyRJmiRJ1k3y0N5zYA/gchbfahjuf9viuW2m/m1YfNviG4E7kuzaxu+/YqBMb13etliStFRe8ZckSZo8mwFfbHPtrQl8vqq+keRC4OQkBwHX0+4+VFVXJOndtvhu7n/b4mOBdehm8++/bfFn222Lb6W7K4AkSWMy8JckSZokVfVT4HFD0n+Jty2WJM0Qu/pLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmErTnTFZAkSZKk6fKdpz5tpqswKZ52zndmugpahXjFX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEnSJEqyRpIfJvlqe71RkjOSXNP+btiX9+1JFiS5Osmz+9J3TnJZW/bRJGnpayU5qaWfn2T2tO+gJGmVY+AvSZI0uf4e+HHf60OAM6tqW+DM9pok2wFzge2BPYEjk6zRyhwFzAO2bY89W/pBwG1V9UjgCOC9U7srkqRRsOZMV0Art+sPe8xMV2HSbP0vl810FSRJIy7JlsDzgMOBN7XkvYDd2vPjgLOBt7X0E6vqLuDaJAuAXZJcB6xXVee2dR4P7A18vZU5tK3rFODjSVJVNZX7JWk0fPzNX5npKkyK133wBTNdhVWOV/wlSZImz4eBfwTu7UvbrKpuBGh/N23pWwA/78u3sKVt0Z4Ppi9RpqruBm4HNp7UPZAkjRwDf0mSpEmQ5PnAzVV10USLDEmrcdLHKzOsPvOSzE8yf9GiRROskiRpFM1I4J9kgySnJLkqyY+TPNGJbyRJ0iruScALW1f9E4FnJPkv4KYkmwO0vze3/AuBrfrKbwnc0NK3HJK+RJkkawLrA7cOq0xVHV1Vc6pqzqxZs1Z87yRJq6yZuuL/EeAbVfVo4HF0E+A48Y0kSVplVdXbq2rLqppN13Y5q6peBpwGHNCyHQB8uT0/DZjbLlhsQ9eWuaANB7gjya7tosYrBsr01rVP24bj+yVJ45r2wD/JesBTgU8DVNUfqupXdJPVHNeyHUc3iQ30TXxTVdcCvYlvNqdNfNMOeMcPlOmt6xRg915vAEmSpGn2HuBZSa4BntVeU1VXACcDVwLfAA6uqntamdcCn6Jr9/yEbmI/6NpPG7eJAN9Eu1AiSdJ4ZmJW/4cDi4DPJHkccBHdbW+WmPgmSf/EN+f1le9NcPNHJjjxTZLexDe3TMkeSZIk9amqs+lm76eqfgnsPka+w+nuADCYPh/YYUj6ncC+k1hVSdJqYCa6+q8J/AVwVFXtBPyW8c9WT9nEN056I0mSJEkadTMR+C8EFlbV+e31KXQnAqZ94hsnvZEkSZIkjbppD/yr6hfAz5P8WUvanW5smxPfSJIkSZI0yWZijD/A64HPJXkQ8FPglXQnIU5OchBwPW38WlVdkaQ38c3d3H/im2OBdegmvemf+OazbeKbW+lm1pUkSZIkabUzI4F/VV0CzBmyyIlvJEmSJEmaRDMxxl+SJEmSJE0TA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wlYo8E9y5kTSJEmSViW2cSRJo2TN5SmUZG3gwcAmSTYE0hatBzxskuomSZI0rWzjSJJG0XIF/sCrgTfSHQAvYvFB8dfAJ1a8WpIkSTPCNo4kaeQsV+BfVR8BPpLk9VX1sUmukyRJ0oywjSNJGkXLe8UfgKr6WJK/BGb3r6uqjl/BekmSJM0Y2ziSpFGyQoF/ks8CjwAuAe5pyQV4UJQkSass2ziSpFGyQoE/MAfYrqpqMiojSZK0krCNI0kaGSt0Oz/gcuBPJqMikiRJKxHbOJKkkbGiV/w3Aa5McgFwVy+xql64guuVJEmaSbZxJEkjY0UD/0MnoxKSJEkrmUNnugKSJE2WFZ3V/zuTVRFJkqSVhW0cSdIoWdFZ/e+gm+EW4EHAA4HfVtV6K1oxSZKkmWIbR5I0SlZocr+qemhVrdceawMvAT4+OVWTJEmaGcvTxkmydpILkvwoyRVJ/rWlb5TkjCTXtL8b9pV5e5IFSa5O8uy+9J2TXNaWfTRJWvpaSU5q6ecnmT0lb4AkaaSs6Kz+S6iqLwHPmMx1SpIkzbQJtnHuAp5RVY8DdgT2TLIrcAhwZlVtC5zZXpNkO2AusD2wJ3BkkjXauo4C5gHbtseeLf0g4LaqeiRwBPDeydg/SdJoW9Gu/i/ue/kAunveer9bSZK0SlueNk5VFfCb9vKB7VHAXsBuLf044GzgbS39xKq6C7g2yQJglyTXAetV1bmtLscDewNfb2UObes6Bfh4krRtS5I01IrO6v+Cvud3A9fRHZAkSZJWZcvVxmlX7C8CHgl8oqrOT7JZVd0IUFU3Jtm0Zd8COK+v+MKW9sf2fDC9V+bnbV13J7kd2Bi4ZZn2TpK0WlnRWf1fOVkVkSRJWlksbxunqu4BdkyyAfDFJDuMkz3DVjFO+nhl7r/yZB7dcAG23nrrcaohSRp1KzTGP8mWSb6Y5OYkNyU5NcmWk1U5SZKkmbCibZyq+hVdl/49gZuSbN7Wuzlwc8u2ENiqr9iWwA0tfcsh6UuUSbImsD5w6xh1OLqq5lTVnFmzZk206pKkEbSik/t9BjgNeBhd17OvtDRJkqRV2TK3cZLMalf6SbIO8EzgqraeA1q2A4Avt+enAXPbTP3b0E3id0EbFnBHkl3bbP6vGCjTW9c+wFmO75ckLc2KjvGfVVX9B8Fjk7xxBdcpSZI005anjbM5cFwb5/8A4OSq+mqSc4GTkxwEXA/sC1BVVyQ5GbiSbh6Bg9tQAYDXAscC69BN6vf1lv5p4LNtIsBb6e4KIEnSuFY08L8lycuAE9rr/YFfruA6JUmSZtoyt3Gq6lJgpyHpvwR2H6PM4cDhQ9LnA/ebH6Cq7qSdOJAkaaJWtKv/3wB/BfwCuJGuy5kT/kmSpFWdbRxJ0shY0Sv+7wIOqKrbAJJsBHyA7mApSZK0qrKNI0kaGSt6xf+xvQMiQFXdypAubpIkSasY2ziSpJGxooH/A5Js2HvRzoavaC8CSZKkmWYbR5I0Mlb0APZB4AdJTgGKbizc/SaokSRJWsXYxpEkjYwVCvyr6vgk84FnAAFeXFVXTkrNJEmSZohtHEnSKFnhLmvtIOiBUJIkjRTbOJKkUbGiY/wlSZIkSdJKzMBfkiRJkqQRNmOBf5I1kvwwyVfb642SnJHkmva3fybdtydZkOTqJM/uS985yWVt2UeTpKWvleSkln5+ktnTvoOSJEmSJK0EZvKK/98DP+57fQhwZlVtC5zZXpNkO2AusD2wJ3BkkjVamaOAecC27bFnSz8IuK2qHgkcAbx3andFkiRJkqSV04wE/km2BJ4HfKoveS/guPb8OGDvvvQTq+quqroWWADskmRzYL2qOreqCjh+oExvXacAu/d6A0iSJEmStDqZqSv+Hwb+Ebi3L22zqroRoP3dtKVvAfy8L9/ClrZFez6YvkSZqrobuB3YeLASSeYlmZ9k/qJFi1ZwlyRJkiRJWvlMe+Cf5PnAzVV10USLDEmrcdLHK7NkQtXRVTWnqubMmjVrgtWRJEmSJGnVseYMbPNJwAuTPBdYG1gvyX8BNyXZvKpubN34b275FwJb9ZXfErihpW85JL2/zMIkawLrA7dO1Q5JkiRJkrSymvYr/lX19qrasqpm003ad1ZVvQw4DTigZTsA+HJ7fhowt83Uvw3dJH4XtOEAdyTZtY3ff8VAmd669mnbuN8Vf0mSJEmSRt1MXPEfy3uAk5McBFwP7AtQVVckORm4ErgbOLiq7mllXgscC6wDfL09AD4NfDbJAror/XOnayckSZIkSVqZzGjgX1VnA2e3578Edh8j3+HA4UPS5wM7DEm/k3biQNKy+85TnzbTVZg0TzvnOzNdBUmSJGlGzdSs/pIkSZIkaRoY+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZI0CZJsleTbSX6c5Iokf9/SN0pyRpJr2t8N+8q8PcmCJFcneXZf+s5JLmvLPpokLX2tJCe19POTzJ72HZUkrXIM/CVJkibH3cCbq+rPgV2Bg5NsBxwCnFlV2wJntte0ZXOB7YE9gSOTrNHWdRQwD9i2PfZs6QcBt1XVI4EjgPdOx45JklZtBv6SJEmToKpurKqL2/M7gB8DWwB7Ace1bMcBe7fnewEnVtVdVXUtsADYJcnmwHpVdW5VFXD8QJneuk4Bdu/1BpAkaSwG/pIkSZOsdcHfCTgf2KyqboTu5ACwacu2BfDzvmILW9oW7flg+hJlqupu4HZg4zHqMC/J/CTzFy1aNAl7JUlaVRn4S5IkTaIkDwFOBd5YVb8eL+uQtBonfbwy90+sOrqq5lTVnFmzZo1XZUnSiDPwlyRJmiRJHkgX9H+uqv67Jd/Uuu/T/t7c0hcCW/UV3xK4oaVvOSR9iTJJ1gTWB26d/D2RJI0SA39JkqRJ0Mbafxr4cVV9qG/RacAB7fkBwJf70ue2mfq3oZvE74I2HOCOJLu2db5ioExvXfsAZ7V5ACRJGtOaM10BSZKkEfEk4OXAZUkuaWn/BLwHODnJQcD1wL4AVXVFkpOBK+nuCHBwVd3Tyr0WOBZYB/h6e0B3YuGzSRbQXemfO8X7JEkaAQb+kiRJk6CqvsfwMfgAu49R5nDg8CHp84EdhqTfSTtxIEnSRNnVX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMKmPfBPslWSbyf5cZIrkvx9S98oyRlJrml/N+wr8/YkC5JcneTZfek7J7msLftokrT0tZKc1NLPTzJ7uvdTkiRJkqSVwUxc8b8beHNV/TmwK3Bwku2AQ4Azq2pb4Mz2mrZsLrA9sCdwZJI12rqOAuYB27bHni39IOC2qnokcATw3unYMUmSJEmSVjbTHvhX1Y1VdXF7fgfwY2ALYC/guJbtOGDv9nwv4MSququqrgUWALsk2RxYr6rOraoCjh8o01vXKcDuvd4AkiRJkiStTmZ0jH/rgr8TcD6wWVXdCN3JAWDTlm0L4Od9xRa2tC3a88H0JcpU1d3A7cDGQ7Y/L8n8JPMXLVo0SXslSZIkSdLKY8YC/yQPAU4F3lhVvx4v65C0Gid9vDJLJlQdXVVzqmrOrFmzllZlSZIkSZJWOTMS+Cd5IF3Q/7mq+u+WfFPrvk/7e3NLXwhs1Vd8S+CGlr7lkPQlyiRZE1gfuHXy90SSJEmSpJXbTMzqH+DTwI+r6kN9i04DDmjPDwC+3Jc+t83Uvw3dJH4XtOEAdyTZta3zFQNleuvaBzirzQMgSZIkSdJqZc0Z2OaTgJcDlyW5pKX9E/Ae4OQkBwHXA/sCVNUVSU4GrqS7I8DBVXVPK/da4FhgHeDr7QHdiYXPJllAd6V/7hTvkyRJkiRJK6VpD/yr6nsMH4MPsPsYZQ4HDh+SPh/YYUj6nbQTB5IkSZIkrc5mdFZ/SZIkSZI0tQz8JUmSJEkaYQb+kiRJkiSNMAN/SZKkSZLkmCQ3J7m8L22jJGckuab93bBv2duTLEhydZJn96XvnOSytuyj7Q5GtLscndTSz08ye1p3UJK0SjLwlyRJmjzHAnsOpB0CnFlV2wJnttck2Y7uzkPbtzJHJlmjlTkKmEd3G+Nt+9Z5EHBbVT0SOAJ475TtiSRpZBj4S5IkTZKqOofuVsL99gKOa8+PA/buSz+xqu6qqmuBBcAuSTYH1quqc6uqgOMHyvTWdQqwe683gCRJY5n22/lJq4onfexJM12FSfP9139/pqsgSauzzarqRoCqujHJpi19C+C8vnwLW9of2/PB9F6Zn7d13Z3kdmBj4JbBjSaZR9drgK233nrSdkaStOrxir8kSdLMGHalvsZJH6/M/ROrjq6qOVU1Z9asWctZRUnSKDDwlyRJmlo3te77tL83t/SFwFZ9+bYEbmjpWw5JX6JMkjWB9bn/0AJJkpZg4C9JkjS1TgMOaM8PAL7clz63zdS/Dd0kfhe0YQF3JNm1jd9/xUCZ3rr2Ac5q8wBIkjQmx/hLku5z+Mv2mekqTJp3/NcpM10FrYaSnADsBmySZCHwTuA9wMlJDgKuB/YFqKorkpwMXAncDRxcVfe0Vb2W7g4B6wBfbw+ATwOfTbKA7kr/3GnYLUnSKs7AX5IkaZJU1f5jLNp9jPyHA4cPSZ8P7DAk/U7aiQNJkibKrv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEjHfgn2TPJ1UkWJDlkpusjSZI0GWzjSJKWxcgG/knWAD4BPAfYDtg/yXYzWytJkqQVYxtHkrSsRjbwB3YBFlTVT6vqD8CJwF4zXCdJkqQVZRtHkrRMUlUzXYcpkWQfYM+q+tv2+uXAE6rqdX155gHz2ss/A66e9ooutglwywxufyatzvsOq/f+u++rp5ne9z+tqlkzuH1phUykjdPSV5Z2zkz/z8+k1XnfYfXef/d99TTT+z5mG2fN6a7JNMqQtCXOclTV0cDR01Od8SWZX1VzZroeM2F13ndYvffffXffJS2XpbZxYOVp56zO//Or877D6r3/7rv7vrIZ5a7+C4Gt+l5vCdwwQ3WRJEmaLLZxJEnLZJQD/wuBbZNsk+RBwFzgtBmukyRJ0oqyjSNJWiYj29W/qu5O8jrgdGAN4JiqumKGqzWeGe+KN4NW532H1Xv/3ffV0+q879IKs42zSlmd9x1W7/1331dPK+2+j+zkfpIkSZIkabS7+kuSJEmStNoz8JckSZIkaYQZ+E+RJJXkg32v35Lk0Pb8NUlesZTyByb5+BjL/mlSK7sc2v59tu/1mkkWJfnqJG7jB5O1Li2/JC9qn/ej2+tZSc5P8sMkT0nydzNdx+mS5J4kl/Q9Dpnk9b9wstcpSctjqo/zSQ5N8pZlLDPp7YK+3/UfJbk4yV9O9jbG2fbsJJdP1/aWRZLf9D1/bpJrkmy9tPxJdluW70jLP23vedvmbwZej9nmHqP8pH5ug/WZ7vJ96/mTJCcm+UmSK5N8Lcm8yWzbL0edPpVku5nafqtD7zfiivY78aYk48bQ/d+RpcR0X0uywRRUeygD/6lzF/DiJJsMLqiq/6iq41dg3TMe+AO/BXZIsk57/Szg/5ZlBUnGnVyyqqbsQLCiAdzyNFhaubOTXJ8kfWlfmqwf7ba+yf6R3B/4Ht2s0QC7A1dV1U7Az4FlCvzTWVV/e35fVTv2Pd4zmSuvqtMme53LYlm+hyvSWGsHwXuTPLYv7fIks9vzpR4I2//S/e6Tm2THJM9dnnpJWsIKH+cn2xS1C3q/648D3g78+xRsY1Isrd00RdvcHfgYsGdVXT8Fm9gNmNbAf7olWWOm67A0rV36ReDsqnpEVW1HF29sNpP1qqq/raorZ7IOLP6N2J7ud/C5wDsnY8VV9dyq+tVkrGsiVtXG96rgbrpZHf9hcEF/0Jjk8UkuTXJukvcPnEF8WJJvtLOs72v53wOs04LVz03Hjozj68Dz2vP9gRN6C5Js1ALaS5Oc12vgt30/Osk3gePb62NaI/6nSd7Qt47+s8dnJzklyVVJPtcLnNtZ6KuSfC/JR5fhrORyB3CTcOD9FfCktq4NgM2XpfDSDiCT+SOZ5CF0dT0ImJtkR+B9wHOTXAK8F3hE+z6+v5V5a5IL22f/ry1tdpIfJzkSuBh4Snv9n+0M6jd7jcsWuJ3Xyn8xyYZLST87yXuTXJDkf5M8ZTL2fRneo+ckObnv9W5JvtKe79H+ty9O8oX2fpLkuiT/2tIvy+LeFPedFU5ybPtO/6D9b+zT0h+Q5Mj2vn21Bcn7TOc+N7uxYo21hcA7hi1YwQPhjnQHZUkrbrzj/BInwHsn79rjqnQnoS9vx+xnJvl+a8/s0rf+xyU5q6W/qq3nIUnO7Pt93KtvG5N2knwM6wG3jVePvuPZsOPX0DZdK/Pdtq6hvQqSrJ3kM21bP0zy9JZ+YDt+fAX4ZpJ107WbLmz59hpc12Rpx9P/BJ5XVT9paW9qn+vlSd64lPKPb3V8eJIXZHFvwW8l2Szdyd7XAP/Q2hFPGZZvqvZvSH0fmuTaJA9sr9drx+sHJtk53dXec4GD+8qs0T7rXrvn1S19tyTfTvJ54LKW9qUkF7XvzbyBbX+wfTfOTDKrpb2qrfdHSU5N8uCWvk37jl2Y5F2TtPtPB/5YVf/RS6iqS4DvAg/J8Db4zkm+0/bp9CSbt/Sh7bL2Xf7vDMQ2bdlRSea39+Zf+9KHnuSfKVV1MzAPeF06Qz//Ie4X08F97cH7XSSeMlXlYwoewG/oDiDXAesDbwEObcsOBd7Snl8O/GV7/h7g8vb8QOCnrezawM+ArXrrXkn277HAKa1+l9AFAl9tyz8GvLM9fwZwSd++XwSs0/f6B8BawCbAL4EH9u9nW+/twJZ0J6vOBZ7ctvtzYJuW74Te9idS/zHS/4Xu/siX05246d354mzg3cB3gDf3PkPgEcDFfeW3BS4aZ7tn051B/Xh7/TfA2/r2NcD72/YvA/brew++DXweuLK9Pru9/1cBnxuo65y+z+lw4EfAecBmLf0R7fWFwGHjvB8vAz7dnv8A+Iv23ezVfzbtO9te79F739pn9VXgqS3fvcCufeXuBnZsr08GXtaeXwo8rT0/DPjwUtLPBj7Ynj8X+NYUfu/vofuu9x770d0W9Xpg3ZbnqPa+bQKc05f+NuBf2vPrgNe3538HfKrv/7733h4LfKG9j9sBC1r6PsDXWvqf0DVS95ms/+shaS8Azgd+CHyL7uz/bOAXdFf/LgGeAswCTm3fqQuBJ42znQOBI+m+53/W0i4HZve9P5u05/9M9x0/g+5/vPfbeTbdiacLgP9tdXhQ+ywW9T6fqfou+PAx6g+Wfpw/tPf/2F5f3n4bZtP9vj+m/U5dBBxDd1zYC/hSX/kfAeu038ufAw9rv6nrtTybAAtYfHyb9PYPi3/Xr6Jra+zc0ofWg/GPX2O16R4MrN2ebwvMb89n9+V5M/CZ9vzR7bds7fZ7uRDYqC17d9/2Nmi/f+tOwfvyR+BW4LF9aTvTtU3WBR4CXAHs1P/Z9L4jdCeGLwK2bukb9n2Of8vi4/bg92hovin6zHuP61l87P0MsHd7Pq+vnv1tkPf3fW7zgP/Xnq8FzAe2ae/Db2lt1La89xmu074rG7fXBby0Pf+Xvrps3Ff231jcbjgNeEV7fjCT8H8BvAE4Ykj6bgxvgz+Qrl04q+Xbj+62ojBGu4zxY5vee7NGK//YvnXNmezvwDK+N8PaRrfRtYfG+vxnM7GY7jpae2c6Hl7xn0JV9WvgeLp/pvtJd7X3oVXVG7P2+YEsZ1bV7VV1J12w96dTVdflUVWX0n2x96cLRPo9Gfhsy3cWsHGS9duy06rq9315/6eq7qqqW4CbGd6t6IKqWlhV99L9SM+mOzD+tKqubXlOGFJuLL1eE73Hfi3941X1+Krage6H+fl9ZTaoqqdV1X1zN1R3Bvz2dFfCAV5JF7CN50zgqemu3M8FTupb9mK6K5aPA54JvL93BhXYBXhHdd2vAHYC3kgXFD6c1otgwLrAedV1YTwHeFVL/wjwkap6PHDDOHXdHzixPT+xvR7PHu3xQ7or+4+ma+QA/KyqzuvLe211Z5OhaxzMbt+RDarqOy39OLr3amh637r+u389S6njihjsKXJSVd0NfAN4QbreIM8DvgzsSvfZfD9d74gDWPJ/eCJ1/lJV3VtdD47e/8WTgS+09F/QnRCaSt+jO2GzE9134B+r6jrgP+gaCTtW1XfpvlNHtO/US4BPLWW999L1Hhlz6FI7y/8Suu/6i4HBs/5rVtUudP8H76yqP9A1mk7qfT7LtKeSlrCU4/x4rq2qy9ox+wq69kzRBY2z+/J9uap+347/36Y7zgV4d5JL6U42bsHUdjfu/a4/GtiTrjdillKPYcevDRi7TfdA4D+TXEZ3QnfYcLz+dtNVdMHBo9qyM6rq1vZ8D+CQdlw5my6QGHPs/Qr4I11gd9BAHb9YVb+tqt/QHceG9bL7c7qLAC+oxcMDtgROb+/BW4Htx9juRPOtiCWO5XTHjZ5P0bXlaH8/M6QN8tm+/HsAr2ifx/nAxixu91zQ10YFeEOS3oWYrfry3cvituB/0b3P0A21+W57L17K4vfiSSxu8/bXZaoMa4P/GbADcEbb9/9H99n1jNXGGSu2+askF9O1H7dn+P/IyqQ3ZHe8z7/fShHTTftYodXQh+kCoM8MWZYhaf3u6nt+Dyvn53Ua8AG6M4Ib96UP27dqf387kD6R/RyWZ2nv33h+337sBz09yT/SnZ3fiK7B8pW2bKwg4lPAK5O8ie6M5y5j5Ou5hy6Y2o+u58N1WTzk/8nACVV1D3BTku8Ajwd+zf0PIBdU1UKA9oMzu6233x/ozrxD9+P7rPb8icDe7fnn6T7DJSTZmK63xg5Jiu4sbDH+uKYA/15VnxxY12yW/rmvw/LrrWum/k9OojvrfitwYVXd0RqOZ1TVWCdLJlLn/vcoA3+ny5bASe0E1IOAa8fI90xgu77v8npJHlpVd4yz7s8D70iyzRjLn0wLDADShlD0ma4TPtLqbKzj/N0sOWR07b7n/b9d9/a9vpclf++KJRVdgDOL7sr7H5NcN7DuKVNV57Zut7PorlSOVY9hx6/xfpv/AbiJ7qT+A4A7h+QZr3z/8TPAS6rq6nHyT4Z7gb8CvpXkn6rq3Uz8+HMj3Xu1E4svLnwM+FBVnZZkN7or/cNMNN+UqKrvpxua8TRgjaq6vJ3UGfyu9oTuSvzpSyR2df/twOtnAk+sqt8lOZuxv9e9bR1L1/vgR0kOpPsfHMwzWa6g61E4zFht8Cuq6olLKTPYxrnfulob4C3A46vqtiTHMk3/88sjycPp6n4zY3/+sweKrRQxnVf8p1g7Q3syS54x7S27Dbgjya4tae5gnjH8MW380UrgGOCwqrpsIP0cuoN378fultYDYjJdBTy8759rv3HyLlWStem6H+9TVY+hG9fW/8MzGLj2nAo8h653wEVV9csJbO5EuoPbyQPpEz3ww8R+RP7YrrKMl2cs+wDHV9WfVtXsqtqKLujrP6N7B/DQvtenA3+TxWPZt0iy6UQ3WFW3A7dl8Tj9lwPfGSt9GfZlqp1NNwziVSw+QXQe8KQkjwRI8uAkjxpefJl8D3hJurH+m7FkQ2AqfIyuJ8xjgFcz9sH4AXQNmt5VlC2WEvTTekt8kG4YxDATPTm6sp4YlUbBWMf56+h+90jyF3TdW5fVXunGtm9M91t2IV132JtbsP10pvHKWLr5VtagG3a4TPVYSptufeDGdsX05W0bg/rbTY+iu4o/LLg/HXh9O7lMkp0muHvLrKp+R9e2eWmSg1od927Hs3WBF9GNAR/0K7reb+9ubUDo3oPe5JAH9OUdbEeMlW86HU93Rf0zANXNOXN7kt6V+Jf25T0deG0WzwvwqPbeDFofuK0F/Y+m6xXY8wAWB91/zeKLOA8Fbmzr7t/m91n8/epPXxFnAWulzbUB3RwNwNPGyH81MCvJE1veByZZ3t4Z69G1cW9v7ZrnLOd6ply6+Rf+g65dVEz8818pGPhPjw/SjQ8b5iDg6HSThYRuHM3SHA1cmpmf3I/W9ecjQxYdCsxpXeTewxT8eLergH8HfCPJ9+jOpk/k/RtLL6C5pQWuE5owrXXbOZ1ubPewnh3DfJdu5uDB4QnnAPulmyxkFl139gsmuM5lcR5dF2oY+4TT/nQzvPY7lb6u2e0kx/fTTfLz/qr6Jt1V3HNb17RTWPKAPhEH0A1xuJRu2MNhS0mfToNDRN4D0HpofJXuYPXVlraIblzXCa3O59ENfVhRp9KN97wc+CRd17IV+d4vzUQba98EXtd70Tf8ZWmOpbsKMmvIsu/RDaFYu/1PPm9InkGD9ZK0AsY5zp8KbNR6nL2Wbqz5sroA+B+638d3VdUNdHPWzEkyny6ouWq5Kj5x9/2u0524PaD9pi9PPcZq0x0JHJDkPLru+8MuJBwJrNGOnScBB1bVXUPyvYtu6MCl6SYPnKzJ3YZqF7D2pOvKvRXdb/YFdMeeT1XVD8codxPdHDGfSPIEunbhF5J8F7ilL+tXgBe1z+Ap4+SbTp+jm2ugv432Srp9ORfoH676Kbqu2xe3z+OTDD8R/Q26q9uX0n1m/UMffwtsn+Qiup6WvfbNP9O9z2ew5Pfv74GDk/ROlK2wFsS+CHhWutv5XUH3WQwdDtqG1u0DvDfd8IVLWM4Jf6vqR3Rd/K+gO9H4/eVZzxTq/UZcQTfs55tAbwLCiX7+K4Xe5BmaIUke0sZJke6WcptX1d/PcLVWGb33r535/gRwTVUdMYFy99BmWW2+UVWHJPk3ukD4OrqJhn5WVYe2Lllvqar5rfyhdJN9fKC93pWuEbR1azCMtd0l1tOX/puqekjbj/fRBZAF/FtVndTOmL+lqp7f8g++/jjdZEHH9m+jt96WZx/g+VV1YJJt6caRha7RNa+qtlja+6aVQ9/3fmO6BtiTqhvvv6LrvZclD/IfAn4CHEEX/J9H1xVvt3ZF6hS67qCvB35M9z/453QHvXOq6jVjbOdAusl6Xtdev4FujoBt2tCX69ryW9r/2v50410X0d1q6D8Hvueb0H3/ZyfZiO5E3APphp04zl/StLBNNxpae2mvqnr5TNdFmkwG/jMs3aRyb6drKP+M7gzvopmt1aojyT/QXYV8EN3Zwle1rmnTXY+3AOtX1T9P97aXR7pbwvy+qirJXGD/qtprpuuliWlB7wZ03/v3VdWxM1mfqdR3kuPBdD1i5lXVxTNdL0kaZJtu1ZfkY3QXX55bVcvTi0VaaRn4SysoyRfpbo/3jOpmJl7pte50H6e74v8r4G+qasGMVkoaIt09kLejG4pzXFX9+wxXSZIkaZVj4C9NgXYyYHCio7cNzvopjbIkr6Qbi9jv+1V18EzUR5IkaXVl4C9JkiRJ0ghzVn9JkiRJkkaYgb8kSZIkSSPMwF+SJEnSCktyaLvT0bKU2THJc/tev7DdDnF5tr9Bkr/re/2wJKcsz7qWcbv31TnJ3km2m+ptSsvKwF9axSX51PIeYJJc1+6BPmzZjBw8JUnSamVH4L7Av6pOq6r3LOe6NgDua7tU1Q1Vtc8K1W4CBuq8N93daKSVioG/tApJssbg66r626q6cgo2twEzcPCUJEmrjiTvSHJ1km8Bf9bSHpHkG0kuSvLdJI9u6fsmuTzJj5Kck+RBwGHAfkkuSbJfkgOTfLzlPzbJR5P8IMlPk+zT0h+S5MwkFye5LMlerTrvAR7R1vX+JLOTXN7KrJ3kMy3/D5M8vaUfmOS/W32vSfK+pezvnm27P0pyZt86Pp7kL4EXAu9vdXhEkov7ym6b5KJJe/OlZWDgL61EknypHSSvSDKvpf0myWFJzgeeOOT12UnmJHlt/8GqHYQ+NtZ6J2C8g+eBbZ1fSXJtktcleVM7kJ6XZKOWb+iBX5IkrfqS7AzMBXYCXgw8vi06Gnh9Ve0MvAU4sqX/C/Dsqnoc8MKq+kNLO6mqdqyqk4ZsZnPgycDz6domAHcCL6qqvwCeDnwwSYBDgJ+0db11YD0HA1TVY4D9geOSrN2W7QjsBzyG7iTEVmPs7yzgP4GXtH3Yt395Vf0AOA14a6vDT4Dbk+zYsrwSOHbYuqWpZuAvrVz+ph0k5wBvSLIxsC5weVU9oaq+N+R1zyl0B92e/YCTxlnv0ox38ATYAfhrYBfgcOB3VbUTcC7wipZnrAO/JEla9T0F+GJV/a6qfk0X9K4N/CXwhSSXAJ+kC94Bvg8cm+RVwBpD1jfMl6rq3ta7cbOWFuDdSS4FvgVs0bdsLE8GPgtQVVcBPwMe1ZadWVW3V9WdwJXAn46xjl2Bc6rq2raeWydQ/08Br2y9NvcDPj+BMtKkW3OmKyBpCW9I8qL2fCtgW+Ae4NS+PIOvAaiqRa0b3K7ANXTd7b4/znp/uYJ1/XZV3QHckeR24Cst/TLgsUkewuIDf6/MWiu4TUmStHKpgdcPAH5VVTveL2PVa5I8AXgecEnflfDx3NX3vNegeCkwC9i5qv6Y5Dq6Ew7jyTjL+rdxD2PHSOH++7s0pwLvBM4CLqqqFW1/ScvFK/7SSiLJbsAzgSe27mM/pDuI3VlV9/RlHXzd7yTgr4CX0J2Br3HWu6L6D5L39r2+l+6Aed+Bv+/x55OwXUmStHI4B3hRknWSPBR4AfA74Nok+wKk87j2/BFVdX5V/QtwC93FiDuAhy7jdtcHbm5B/9NZfIV+vHWdQ3fCgCSPArYGrl7G7Z4LPC3JNm09Gw3Js0QdWi+C04GjgM8s4/akSWPgL6081gduq6rftbHwuy7HOv6bbjbZ/VnczX9517s8B+L7tC5/Qw/8kiRp1VdVF9O1Ny6hu7L93bbopcBBSX4EXAH0Jt97f5tc73K6QPxHwLeB7dqcQvtNcNOfA+Ykmd+2dVWrzy+B76ebQPD9A2WOBNZIclmr84FVdRfLoKoWAfOA/277NmxOghOBt7Z5jx7RV98Cvrks25MmU6qWtbeKpKmQZC3gS3Tj1K6m68J2KPDVqnpIX77fDLw+G3hLVc1vr78KbFdVDx9vvVV1dusaN6eqbhmjTp8HHgt8HfhEq8sOSQ5s5V7X8t23nv5l7Yz4UXRj+x4InFhVh63QGyVJkrQKSfIWYP2q+ueZrotWXwb+kiRJkjQFknwReATwjLEutEjTwcBfkiRJkvq02yYPTkr88qq6bCbqI60oA39pNddu7XfmkEW7O/OsJEmStOoz8JckSZIkaYQ5q78kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA3+tFpIcmqSGPL4103UbRUnWTXJikl+29/nAcfI+IMnfJvlBkl8nuTPJ5UnemuQhLc9ubT07TNtOSJIkSSNizZmugDSNbgf2HJKmyfda4AXAK4D/A34yLFOSBwAntbyfAA4D/gDsBLwOeBjwD9NQX0mSJGlkGfhrdXJ3VZ03kYxJ1qmq3091hUbYo4Grq+rUpeQ7GHgJsEdV9fe+OCvJJ4AnTVUFJUmSpNWFXf212ksyu3Ujf2mS45P8CvhKW7ZRkk8mual1Qf9BkicMlN8gyeeT/DbJjUnekeQDSa7ry3NokluGbLuSvG4g7W+TXJHkriQ/S/KPA8uPTTI/ybOSXNq2+70k2w/kWyPJ25P8b1vXwiTHtmUHJ7mj15W+r8zTW50eO877tUmS41o3/t8lOTvJnL7l1wEHATv1hlSMtS66q/lfHAj6AaiqO6vqzHHq8eYkFya5vX0+X0nyyIE8T07y3TaE4NdJLkmyb9/yFya5qL2HtyU5P8nTxqmvJEmStMox8NdqJcmaA4/0Lf4AcAewL/DuJGsB3wKeBbwV2BtYBHwryZ/0lfsM8BzgjcA8YA9g7nLW763AUcCXgOe35+8aPDkAbA28Hzgc2B/YFDh5YH8+CfwrcHJb15uBdduyz9H1+NlnYL0HAhdX1aXjVPNLwLOBtwD70f2OfLsv6H4R8DXgKuCJ7TFsX7cCtgG+Mc62xrMl8HFgL+BVwBrA95Os39a/HvBV4Kd0vQr2AT4LbNCWPwI4BTiLbqjBS1v+jZazPpIkSdJKya7+Wp1sDPxxIO1ZwIL2/LyqOri3IMlBwA7A9lV1TUv7FnA1XRD91naVfW9gblWd1PJ8G7ge+PWyVK4Fqu8E/q2q/rUln5HkwcD/S3JUVd3T0jcCntRXrwcAXwT+DLgqyaPprrr/fVV9tG8zJwFU1a+SnAq8Eji2reMhdAHyIePUcU+67ve7VdV3WtpZwHV0J0deXVU/TLII2GwpQyu2aH+vH/+dGa6q7hv7n2QN4AzgZroTAccDjwLWB15XVXe0rN/sW8VOwB1V9da+tK8tT10kSZKklZlX/LU6uR14/MDj/L7l/zOQ/5nARcC1vR4CLf07QK9r++Pb39N6harqN3RB6LJ6It0V+S/090qguyK9Gd0V7p7rekF/c2X728vz9Pb32HG292ngKUke3l7/Fd3JwM+PU2YXYFEv6Aeoqt/SXSl/8jjlxjPeUIAxJdk1yRlJfgncDfwOeAhdwA/dhIK/AT6fZK8kGwys4jJg/TZsYY8k6yJJkiSNIAN/rU7urqr5A487+pbfNJB/E2BXul4C/Y9XAlu1PH9Cd9V4cCLAm5ejfpu0v1cMbO/bLX2rvry/Gij7h/Z37fZ3Y+C3VTVer4Oz6brBH9hevxL4clXdOk6Zzbn/+0RLW9Yu8v/X/m69jOVIsjXd1fsAr6brhfB4uvd9bYCquo1u2MUD6YY7LEryP70THVV1NV3vgIfTXem/pc3VMGtZ6yNJkiStzOzqLy02eOX5VmA+3a3pBt3V/v4CeGjufxeATQfy3wk8qD8hyYZDtgfdePxhwfXVY9R7mF8C6yZZb6zgv6oqyTHAvCSfpbti/5ylrPdG7r9v0PVIGO+EwbDt/zzJT+nmC/jUspSluy3jg4G9Wo8DWu+IJU4+VNW5wJ5J1qHrwfEhuh4Nu7bl/wP8T5sX4HnAh4GPsZxzNEiSJEkrI6/4S2M7E3gkcP2QngKXtTwXtr8v7BVqY+WfNbCuhXQnCLboS9tjIM+5wO+Bhw3Z3mDvhKU5q/19xVLyHUs3POAYuivwSxuicD6waZKn9hLaHATPA763DPXr+TDw4iRPH1yQZO0kzxij3DrAvXRd/Ht6QxXup6p+X1VfodvP7YYsv72qPk83T8L9lkuSJEmrMq/4S2M7HngNcHaSD9B1i9+Ybpz7L6rqiKq6IslpwFFtcr4b6Sa5+93Aur5BF9Qfk+SDdLPZv6Y/Q5tw71DgI0n+FDiH7uTco4CnV9WLJlrxqro6ydHAB5Ns2ta1AbBPVc3ty3dDkm/QBe7/3jd54FjrPT3J94GTkhxC17PgLXSB+PsnWr8+nwCeCnwtySfoTjz8AXgc8Dq62yqeNaTcWXSz+H8myaeB7Vs9ftXLkOR5wN/Q3YXgerrJBF/dW1+SV9PNq/AN4AZgW7o7Ohy/HPshSZIkrbQM/KUxVNWd7Ur0YXS3xduMbgz5BfRN5kc3Rv4ouqvXv6ELZi+k71Z5VXVLkpfQ3TLwS3STBv41iyfl6+V7X5Ib6O5v/2a6IQL/S5uNfxn9HfAz4G/pZuq/meFX9L9EF/h/ZoLrfRHwQbr9XZvu/XhGVS0Yr9AwVXVvkv3oAvS/pTsZsiZwDd2t9z48RrnLkryS7i4ILwJ+RBe0979PC+iGb7ybbnjCIrpJCP+pLb+UrqfGh+iGCNwI/CfwL8u6H5IkSdLKLFXLNaG2pHG0HgL7VNXsma7L0iQ5Gdi8qp4y03WRJEmSNPm84i+tppI8hu62hC/GyewkSZKkkWXgL62+vkJ3C8Ejq+qUma6MJEmSpKlhV39JkiRJkkaYt/OTJEmSJGmEGfhLkiRJkjTCHOPfbLLJJjV79uyZroYkaYpddNFFt1TVrJmuhyRJ0nQx8G9mz57N/PnzZ7oakqQpluRnM10HSZKk6WRXf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjbM2ZrsAo2vmtx890FTTCLnr/K2a6CpIkSZJWIV7xlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYVMW+CfZKsm3k/w4yRVJ/r6lb5TkjCTXtL8b9pV5e5IFSa5O8uy+9J2TXNaWfTRJWvpaSU5q6ecnmd1X5oC2jWuSHDBV+ylJkiRJ0spsKq/43w28uar+HNgVODjJdsAhwJlVtS1wZntNWzYX2B7YEzgyyRptXUcB84Bt22PPln4QcFtVPRI4AnhvW9dGwDuBJwC7AO/sP8EgSZIkSdLqYsoC/6q6saoubs/vAH4MbAHsBRzXsh0H7N2e7wWcWFV3VdW1wAJglySbA+tV1blVVcDxA2V66zoF2L31Bng2cEZV3VpVtwFnsPhkgSRJkiRJq41pGePfuuDvBJwPbFZVN0J3cgDYtGXbAvh5X7GFLW2L9nwwfYkyVXU3cDuw8TjrkiRJkiRptTLlgX+ShwCnAm+sql+Pl3VIWo2Tvrxl+us2L8n8JPMXLVo0TtUkSZIkSVo1TWngn+SBdEH/56rqv1vyTa37Pu3vzS19IbBVX/EtgRta+pZD0pcok2RNYH3g1nHWtYSqOrqq5lTVnFmzZi3vbkqSJEmStNKayln9A3wa+HFVfahv0WlAb5b9A4Av96XPbTP1b0M3id8FbTjAHUl2bet8xUCZ3rr2Ac5q8wCcDuyRZMM2qd8eLU2SJEmSpNXKmlO47icBLwcuS3JJS/sn4D3AyUkOAq4H9gWoqiuSnAxcSXdHgIOr6p5W7rXAscA6wNfbA7oTC59NsoDuSv/ctq5bk7wLuLDlO6yqbp2i/ZQkSZIkaaU1ZYF/VX2P4WPtAXYfo8zhwOFD0ucDOwxJv5N24mDIsmOAYyZaX0mSJEmSRtG0zOovSZIkSZJmhoG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphE1Z4J/kmCQ3J7m8L+2kJJe0x3VJLmnps5P8vm/Zf/SV2TnJZUkWJPlokrT0tdr6FiQ5P8nsvjIHJLmmPQ6Yqn2UJEmSJGllt+YUrvtY4OPA8b2Eqtqv9zzJB4Hb+/L/pKp2HLKeo4B5wHnA14A9ga8DBwG3VdUjk8wF3gvsl2Qj4J3AHKCAi5KcVlW3Td6uSZIkSZK0apiyK/5VdQ5w67Bl7ar9XwEnjLeOJJsD61XVuVVVdCcR9m6L9wKOa89PAXZv6302cEZV3dqC/TPoThZIkiRJkrTamakx/k8Bbqqqa/rStknywyTfSfKUlrYFsLAvz8KW1lv2c4Cqupuu98DG/elDyiwhybwk85PMX7Ro0YrukyRJkiRJK52ZCvz3Z8mr/TcCW1fVTsCbgM8nWQ/IkLLV/o61bLwySyZWHV1Vc6pqzqxZsyZceUmSJEmSVhXTHvgnWRN4MXBSL62q7qqqX7bnFwE/AR5Fd7V+y77iWwI3tOcLga361rk+3dCC+9KHlJEkSZIkabUyE1f8nwlcVVX3deFPMivJGu35w4FtgZ9W1Y3AHUl2beP3XwF8uRU7DejN2L8PcFabB+B0YI8kGybZENijpUmSJEmStNqZsln9k5wA7AZskmQh8M6q+jQwl/tP6vdU4LAkdwP3AK+pqt7EgK+lu0PAOnSz+X+9pX8a+GySBXRX+ucCVNWtSd4FXNjyHda3LkmSJEmSVitTFvhX1f5jpB84JO1U4NQx8s8HdhiSfiew7xhljgGOWYbqSpIkSZI0kmZqcj9JkiRJkjQNDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJG2JQF/kmOSXJzksv70g5N8n9JLmmP5/Yte3uSBUmuTvLsvvSdk1zWln00SVr6WklOaunnJ5ndV+aAJNe0xwFTtY+SJEmSJK3spvKK/7HAnkPSj6iqHdvjawBJtgPmAtu3MkcmWaPlPwqYB2zbHr11HgTcVlWPBI4A3tvWtRHwTuAJwC7AO5NsOPm7J0mSJEnSym/KAv+qOge4dYLZ9wJOrKq7qupaYAGwS5LNgfWq6tyqKuB4YO++Mse156cAu7feAM8GzqiqW6vqNuAMhp+AkCRJkiRp5M3EGP/XJbm0DQXoXYnfAvh5X56FLW2L9nwwfYkyVXU3cDuw8Tjrup8k85LMTzJ/0aJFK7ZXkiRJkiSthKY78D8KeASwI3Aj8MGWniF5a5z05S2zZGLV0VU1p6rmzJo1a5xqS5IkSZK0aprWwL+qbqqqe6rqXuA/6cbgQ3dVfqu+rFsCN7T0LYekL1EmyZrA+nRDC8ZalyRJkiRJq51pDfzbmP2eFwG9Gf9PA+a2mfq3oZvE74KquhG4I8mubfz+K4Av95Xpzdi/D3BWmwfgdGCPJBu2oQR7tDRJkiRJklY7a07VipOcAOwGbJJkId1M+7sl2ZGu6/11wKsBquqKJCcDVwJ3AwdX1T1tVa+lu0PAOsDX2wPg08Bnkyygu9I/t63r1iTvAi5s+Q6rqolOMihJkiRJ0kiZssC/qvYfkvzpcfIfDhw+JH0+sMOQ9DuBfcdY1zHAMROurCRJkiRJI2omZvWXJEmSJEnTxMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphE1Z4J/kmCQ3J7m8L+39Sa5KcmmSLybZoKXPTvL7JJe0x3/0ldk5yWVJFiT5aJK09LWSnNTSz08yu6/MAUmuaY8DpmofJUmSJEla2U3lFf9jgT0H0s4AdqiqxwL/C7y9b9lPqmrH9nhNX/pRwDxg2/borfMg4LaqeiRwBPBegCQbAe8EngDsArwzyYaTuWOSJEmSJK0qpizwr6pzgFsH0r5ZVXe3l+cBW463jiSbA+tV1blVVcDxwN5t8V7Ace35KcDurTfAs4EzqurWqrqN7mTD4AkISZIkSZJWCzM5xv9vgK/3vd4myQ+TfCfJU1raFsDCvjwLW1pv2c8B2smE24GN+9OHlJEkSZIkabWy5kxsNMk7gLuBz7WkG4Gtq+qXSXYGvpRkeyBDildvNWMsG6/MYD3m0Q0jYOutt574DkiSJEmStIqY9iv+bbK95wMvbd33qaq7quqX7flFwE+AR9Fdre8fDrAlcEN7vhDYqq1zTWB9uqEF96UPKbOEqjq6quZU1ZxZs2ZNzg5KkiRJkrQSmdbAP8mewNuAF1bV7/rSZyVZoz1/ON0kfj+tqhuBO5Ls2sbvvwL4cit2GtCbsX8f4Kx2IuF0YI8kG7ZJ/fZoaZIkSZIkrXamrKt/khOA3YBNkiykm2n/7cBawBntrnzntRn8nwocluRu4B7gNVXVmxjwtXR3CFiHbk6A3rwAnwY+m2QB3ZX+uQBVdWuSdwEXtnyH9a1LkiRJkqTVypQF/lW1/5DkT4+R91Tg1DGWzQd2GJJ+J7DvGGWOAY6ZcGUlSZIkSRpRMzmrvyRJkiRJmmIG/pIkSZIkjTADf0mSJEmSRtiEAv8kZ04kTZIkSZIkrVzGndwvydrAg+lm5t8QSFu0HvCwKa6bJEmSJElaQUub1f/VwBvpgvyLWBz4/xr4xNRVS5IkSZIkTYZxA/+q+gjwkSSvr6qPTVOdJEmSJEnSJFnaFX8AqupjSf4SmN1fpqqOn6J6SZIkSZKkSTChwD/JZ4FHAJcA97TkAgz8JUmSJElaiU0o8AfmANtVVU1lZSRJkiRJ0uSa0O38gMuBP5nKikiSJEmSpMk30Sv+mwBXJrkAuKuXWFUvnJJaSZIkSZKkSTHRwP/QqayEJEmSJEmaGhOd1f87U10RSZIkSZI0+SY6q/8ddLP4AzwIeCDw26pab6oqJkmSJEmSVtxEr/g/tP91kr2BXaaiQpIkSZIkafJMdFb/JVTVl4BnTG5VJEmSJEnSZJtoV/8X9718ADCHxV3/JUmSJEnSSmqis/q/oO/53cB1wF6TXhtJkiRJkjSpJjrG/5VTXRFJkiRJkjT5JjTGP8mWSb6Y5OYkNyU5NcmWU105SZIkSZK0YiY6ud9ngNOAhwFbAF9paWNKckw7UXB5X9pGSc5Ick37u2HfsrcnWZDk6iTP7kvfOcllbdlHk6Slr5XkpJZ+fpLZfWUOaNu4JskBE9xHSZIkSZJGzkQD/1lV9Zmqurs9jgVmLaXMscCeA2mHAGdW1bbAme01SbYD5gLbtzJHJlmjlTkKmAds2x69dR4E3FZVjwSOAN7b1rUR8E7gCXS3HHxn/wkGSZIkSZJWJxMN/G9J8rIka7THy4Bfjlegqs4Bbh1I3gs4rj0/Dti7L/3Eqrqrqq4FFgC7JNkcWK+qzq2qAo4fKNNb1ynA7q03wLOBM6rq1qq6DTiD+5+AkCRJkiRptTDRwP9vgL8CfgHcCOwDLM+Ef5tV1Y0A7e+mLX0L4Od9+Ra2tC3a88H0JcpU1d3A7cDG46zrfpLMSzI/yfxFixYtx+5IkiRJkrRym2jg/y7ggKqaVVWb0p0IOHQS65EhaTVO+vKWWTKx6uiqmlNVc2bNWtrIBUmSJEmSVj0TDfwf27rNA1BVtwI7Lcf2bmrd92l/b27pC4Gt+vJtCdzQ0rcckr5EmSRrAuvTDS0Ya12SJEmSJK12Jhr4P2BgBv6NgDWXY3unAb1Z9g8AvtyXPrfN1L8N3SR+F7ThAHck2bWN33/FQJneuvYBzmrzAJwO7JFkw1bnPVqaJEmSJEmrnYkG7x8EfpDkFLpu838FHD5egSQnALsBmyRZSDfT/nuAk5McBFwP7AtQVVckORm4ErgbOLiq7mmrei3dHQLWAb7eHgCfBj6bZAHdlf65bV23JnkXcGHLd1jroSBJkiRJ0mpnQoF/VR2fZD7wDLox9C+uqiuXUmb/MRbtPkb+wxlyMqGq5gM7DEm/k3biYMiyY4BjxqufJEmSJEmrgwl312+B/rjBviRJkiRJWrlMdIy/JEmSJElaBS3PBH2SdD/XH/aYma6CRtjW/3LZTFdBkiRpleUVf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYQb+kiRJkiSNMAN/SZIkSZJGmIG/JEmSJEkjzMBfkiRJkqQRZuAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkbYtAf+Sf4sySV9j18neWOSQ5P8X1/6c/vKvD3JgiRXJ3l2X/rOSS5ryz6aJC19rSQntfTzk8ye7v2UJEmSJGllMO2Bf1VdXVU7VtWOwM7A74AvtsVH9JZV1dcAkmwHzAW2B/YEjkyyRst/FDAP2LY99mzpBwG3VdUjgSOA9079nkmSJEmStPKZ6a7+uwM/qaqfjZNnL+DEqrqrqq4FFgC7JNkcWK+qzq2qAo4H9u4rc1x7fgqwe683gCRJkiRJq5OZDvznAif0vX5dkkuTHJNkw5a2BfDzvjwLW9oW7flg+hJlqupu4HZg48mvviRJkiRJK7cZC/yTPAh4IfCFlnQU8AhgR+BG4IO9rEOK1zjp45UZrMO8JPOTzF+0aNHEKy9JkiRJ0ipiJq/4Pwe4uKpuAqiqm6rqnqq6F/hPYJeWbyGwVV+5LYEbWvqWQ9KXKJNkTWB94NbBClTV0VU1p6rmzJo1a9J2TJIkSZKklcVMBv7709fNv43Z73kRcHl7fhowt83Uvw3dJH4XVNWNwB1Jdm3j918BfLmvzAHt+T7AWW0eAEmSJEmSVitrzsRGkzwYeBbw6r7k9yXZka5L/nW9ZVV1RZKTgSuBu4GDq+qeVua1wLHAOsDX2wPg08Bnkyygu9I/dwp3R5IkSZKkldaMBP5V9TsGJturqpePk/9w4PAh6fOBHYak3wnsu+I1lSRJkiRp1TbTs/pLkiRJkqQpZOAvSZIkSdIIM/CXJEmSJGmEGfhLkiRJkjTCDPwlSZIkSRphBv6SJEmSJI0wA39JkiRJkkaYgb8kSZIkSSPMwF+SJEmSpBFm4C9JkiRJ0ggz8JckSZIkaYQZ+EuSJEmSNMIM/CVJkiRJGmEG/pIkSZIkjTADf0mSJEmSRpiBvyRJkiRJI8zAX5IkSZKkEWbgL0mSJEnSCDPwlyRJkiRphBn4S5IkSZI0wgz8JUmSJEkaYTMS+Ce5LsllSS5JMr+lbZTkjCTXtL8b9uV/e5IFSa5O8uy+9J3behYk+WiStPS1kpzU0s9PMnvad1KSJEmSpJXATF7xf3pV7VhVc9rrQ4Azq2pb4Mz2miTbAXOB7YE9gSOTrNHKHAXMA7Ztjz1b+kHAbVX1SOAI4L3TsD+SJEmSJK10Vqau/nsBx7XnxwF796WfWFV3VdW1wAJglySbA+tV1blVVcDxA2V66zoF2L3XG0CSJEmSpNXJTAX+BXwzyUVJ5rW0zarqRoD2d9OWvgXw876yC1vaFu35YPoSZarqbuB2YOPBSiSZ9//bu/tgu6r6jOPfpwkC8mYF2sGQIloYyptRQ4YOtVqwSv1DsAMaxjYwZUQZaKVTHYGWSjtmKpXWGbC2g7xEGBik8pbRCFgVsUghQQIhQGqGSoGkEF4KZAQk4dc/zrrlJF4uueHmnJt9v5+ZM3ef31nrnLXu7HNnnr3X3jfJkiRL1qxZMyETkyRJkiRpMpk+pM89rKpWJfk14LtJHhij7Whn6muM+lh9NixUXQBcADB79uxfel2SJEmSpK3dUM74V9Wq9vNx4FpgDvBYW75P+/l4a/4IMLOv+57Aqlbfc5T6Bn2STAd2AZ7aEnORJEmSJGkyG3jwT7JDkp1GtoEPAPcCC4HjW7Pjgevb9kJgbrtT/970buJ3R7sc4Lkkh7br9+dt1GfkvY4Bvt/uAyBJkiRJ0pQyjKX+vw5c2+61Nx24oqpuSLIYuCrJicB/A8cCVNXyJFcB9wHrgFOqan17r5OBBcD2wHfaA+Ai4LIkK+md6Z87iIlJkiRJkjTZDDz4V9WDwDtGqT8JHPEqfeYD80epLwEOHKX+Au3AgSRJkiRJU9lk+nd+kiRJkiRpghn8JUmSJEnqMIO/JEmSJEkdZvCXJEmSJKnDDP6SJEmSJHWYwV+SJEmSpA4z+EuSJEmS1GEGf0mSJEmSOszgL0mSJElShxn8JUmSJEnqMIO/JEmSJEkdZvCXJEmSJKnDDP6SJEmSJHWYwV+SJEmSpA4z+EuSJEmS1GEGf0mSJEmSOszgL0mSJElShxn8JUmSJEnqMIO/JEmSJEkdZvCXJEmSJKnDBh78k8xM8oMk9ydZnuTTrX52kkeTLG2PD/X1OSPJyiQrknywr/7uJMvaa+clSatvm+QbrX57krcOep6SJEmSJE0Gwzjjvw74i6r6LeBQ4JQk+7fXvlxVs9pjEUB7bS5wAHAk8NUk01r7fwZOAvZpjyNb/UTg6ar6TeDLwDkDmJckSZIkSZPOwIN/Va2uqp+07eeA+4EZY3Q5Criyql6sqv8CVgJzkuwB7FxVt1VVAZcCR/f1+Xrb/iZwxMhqAEmSJEmSppKhXuPfluC/E7i9lU5Nck+Si5P8aqvNAB7u6/ZIq81o2xvXN+hTVeuAZ4BdR/n8k5IsSbJkzZo1EzMpSZIkSZImkaEF/yQ7AlcDp1XVs/SW7b8dmAWsBv5hpOko3WuM+lh9NixUXVBVs6tq9u677z6+CUiSJEmStBUYSvBPsg290H95VV0DUFWPVdX6qnoZ+BowpzV/BJjZ131PYFWr7zlKfYM+SaYDuwBPbZnZSJIkSZI0eQ3jrv4BLgLur6p/7Kvv0dfsI8C9bXshMLfdqX9vejfxu6OqVgPPJTm0vec84Pq+Pse37WOA77f7AEiSJEmSNKVMH8JnHgb8MbAsydJWOxM4LsksekvyfwZ8EqCqlie5CriP3n8EOKWq1rd+JwMLgO2B77QH9A4sXJZkJb0z/XO36IwkSZIkSZqkBh78q+rfGf0a/EVj9JkPzB+lvgQ4cJT6C8Cxr2OYkiRJkiR1wlDv6i9JkiRJkrYsg78kSZIkSR1m8JckSZIkqcMM/pIkSZIkdZjBX5IkSZKkDjP4S5IkSZLUYQZ/SZIkSZI6zOAvSZIkSVKHGfwlSZIkSeowg78kSZIkSR1m8JckSZIkqcMM/pIkSZIkdZjBX5IkSZKkDjP4S5IkSZLUYQZ/SZIkSZI6zOAvSZIkSVKHGfwlSZIkSeowg78kSZIkSR1m8JckSZIkqcMM/pIkSZIkdVing3+SI5OsSLIyyenDHo8kSZIkSYPW2eCfZBrwT8AfAPsDxyXZf7ijkiRJkiRpsDob/IE5wMqqerCqfgFcCRw15DFJkiRJkjRQXQ7+M4CH+54/0mqSJEmSJE0Z04c9gC0oo9RqgwbJScBJ7enaJCu2+Kg0mt2AJ4Y9iK1Fzj1+2EPQxHC/H4/Pj/YnfbPtNZFvJkmSNNl1Ofg/Aszse74nsKq/QVVdAFwwyEHplyVZUlWzhz0OaZDc7yVJkjQoXV7qvxjYJ8neSd4AzAUWDnlMkiRJkiQNVGfP+FfVuiSnAjcC04CLq2r5kIclSZIkSdJAdTb4A1TVImDRsMeh1+TlFpqK3O8lSZI0EKmq124lSZIkSZK2Sl2+xl+SJEmSpCmv00v9NbGSrAeW9ZWurKovDms80qD07fsB1gOnVtWPN+N9PgX8vKouneAhSpIkSa/Kpf7aZEnWVtWOwx6HNGj9+36SDwJnVtV7hzwsSZIkaZO41F+vW5JDkvw4yd1J7kiyU5LtklySZFmSu5L8Xmt7QpJrktyQ5KdJ/r7vfY5r7e9Nck5ffW2Sc5LcmeTfksxJcnOSB5N8uLX5UZJZfX1uTXLwAH8Nmjp2Bp4GSPK+JN8aeSHJV5Kc0La/mOS+JPckObfVzk7ymbZ9c9uv70jyn0ne0+rTknwpyeLW95OtvkeSW5Isbd+R97S2C9rzZUn+fLC/CkmSJG0NXOqv8dg+ydK+538HXAt8A/hYVS1OsjPwPPBpgKo6KMl+wE1J9m39ZgHvBF4EViQ5n97y6XOAd9MLVTclObqqrgN2AG6uqs8luRb4AvD7wP7A14GFwIXACcBp7XO2rap7tshvQVPRyL6/HbAHcPhYjZO8GfgIsF9VVZI3vUrT6VU1J8mHgM8D7wdOBJ6pqkOSbAvcmuQm4A+BG6tqfpJpwBvpfZdmVNWB7XNf7XMkSZI0hRn8NR7PV9Ws/kKSg4DVVbUYoKqebfXfAc5vtQeSPASMBP/vVdUzrd19wF7ArvTC/ZpWvxz4XeA64BfADa3vMuDFqnopyTLgra3+r8BZST4L/AmwYCInrinv//f9JL8NXJrkwDHaPwu8AFyY5NvAt16l3TXt5528si9/ADg4yTHt+S7APsBi4OIk2wDXVdXSJA8Cb2sHz74N3LQ5k5MkSVK3udRfr1eA0W4UkTH6vNi3vZ7eAaix2r9Ur9yM4uWR/lX1cutLVf0c+C5wFPBR4IpNGbw0XlV1G7AbsDuwjg3/jm7X2qwD5gBXA0fzyoGrjY18F0a+B9D7LvxpVc1qj72r6qaquoXewbBHgcuSzKuqp4F3ADcDp9Bb+SJJkiRtwOCv1+sB4C1JDgFo1/dPB24BPt5q+wK/AawY431uB96bZLe2jPk44IfjHMuFwHnA4qp6apx9pU3SLl2ZBjwJPATsn2TbJLsAR7Q2OwK7VNUi4DR6S/I31Y3Aye3MPkn2TbJDkr2Ax6vqa8BFwLuS7Ab8SlVdDZwFvGsi5ihJkqRucam/xmPja/xvqKrTk3wMOD/J9vSu738/8FXgX9py/HXACVX1YjL6if2qWp3kDOAH9M54Lqqq68czuKq6M8mzwCXjnZj0Gvr3/QDHV9V64OEkVwH3AD8F7mptdgKuT7Jdaz+em+5dSG/Z/0/S+8Ksobdq4H3AZ5O8BKwF5gEzgEuSjBzEPWNzJidJkqRu89/5qTOSvIXekuf92mUAkiRJkjTludRfnZBkHr3LBf7S0C9JkiRJr/CMvyRJkiRJHeYZf0mSJEmSOszgL0mSJElShxn8JUmSJEnqMIO/1HFJzk7ymWGPQ5IkSdJwGPwlSZIkSeowg7/UMUnmJbknyd1JLtvotU8kWdxeuzrJG1v92CT3tvotrXZAkjuSLG3vt88w5iNJkiTp9fHf+UkdkuQA4BrgsKp6IsmbgT8D1lbVuUl2raonW9svAI9V1flJlgFHVtWjSd5UVf+b5HzgP6rq8iRvAKZV1fPDmpskSZKkzeMZf6lbDge+WVVPAFTVUxu9fmCSH7Wg/3HggFa/FViQ5BPAtFa7DTgzyeeAvQz9kiRJ0tbJ4C91S4CxlvEsAE6tqoOAvwG2A6iqTwF/BcwElraVAVcAHwaeB25McviWHLgkSZKkLcPgL3XL94CPJtkVoC3177cTsDrJNvTO+NPavb2qbq+qvwaeAGYmeRvwYFWdBywEDh7IDCRJkiRNqOnDHoCkiVNVy5PMB36YZD1wF/CzviZnAbcDDwHL6B0IAPhSu3lf6B08uBs4HfijJC8B/wP87UAmIUmSJGlCeXM/SZIkSZI6zKX+kiRJkiR1mMFfkiRJkqQOM/hLkiRJktRhBn9JkiRJkjrM4C9JkiRJUocZ/CVJkiRJ6jCDvyRJkiRJHWbwlyRJkiSpw/4P4ApcxMnmpY0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1224x1656 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(17,23))\n",
    "\n",
    "plt.subplot(4,2,1)\n",
    "sns.countplot(x = df[\"airline\"])\n",
    "plt.title(\"Frequency of Airlines\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,2)\n",
    "sns.countplot(x = df[\"source_city\"])\n",
    "plt.title(\"Frequency of Source city\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,3)\n",
    "sns.countplot(x = df[\"departure_time\"])\n",
    "plt.title(\"Frequency of Departure time\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,4)\n",
    "sns.countplot(x = df[\"stops\"])\n",
    "plt.title(\"Frequency of Stops\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,5)\n",
    "sns.countplot(x = df[\"arrival_time\"])\n",
    "plt.title(\"Frequency of Arrival Time\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,6)\n",
    "sns.countplot(x = df[\"destination_city\"])\n",
    "plt.title(\"Frequency of Destination City\", fontsize = 15)\n",
    "\n",
    "plt.subplot(4,2,7)\n",
    "sns.countplot(x = df[\"class\"])\n",
    "plt.title(\"Frequency of Class\", fontsize = 15)\n",
    "plt.subplots_adjust(hspace=0.3, wspace=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c389d6e",
   "metadata": {},
   "source": [
    "Insights of above plots\n",
    "- 'Vistara' airlines have the highest number of bookings.\n",
    "- Most of the airlines have atleast one stop in between.\n",
    "- Number of flights departing in morning are more than any other departure time whereas the arriving time is mostly at night and evening. \n",
    "- Econony class has the maximum number of flight bookings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ab2f532e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessinumberg import LabelEncoder\n",
    "label = LabelEncoder()\n",
    "\n",
    "df[\"airline\"] = label.fit_transform(df[\"airline\"])\n",
    "df[\"departure_time\"] = label.fit_transform(df[\"departure_time\"])\n",
    "df[\"arrival_time\"] = label.fit_transform(df[\"arrival_time\"])\n",
    "df[\"destination_city\"] = label.fit_transform(df[\"destination_city\"])\n",
    "df[\"source_city\"] = label.fit_transform(df[\"source_city\"])\n",
    "df[\"stops\"] = label.fit_transform(df[\"stops\"])\n",
    "df[\"class\"] = label.fit_transform(df[\"class\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5fb1f8e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 300153 entries, 0 to 300152\n",
      "Data columns (total 11 columns):\n",
      " #   Column            Non-Null Count   Dtype  \n",
      "---  ------            --------------   -----  \n",
      " 0   airline           300153 non-null  int32  \n",
      " 1   flight            300153 non-null  object \n",
      " 2   source_city       300153 non-null  int32  \n",
      " 3   departure_time    300153 non-null  int32  \n",
      " 4   stops             300153 non-null  int32  \n",
      " 5   arrival_time      300153 non-null  int32  \n",
      " 6   destination_city  300153 non-null  int32  \n",
      " 7   class             300153 non-null  int32  \n",
      " 8   duration          300153 non-null  float64\n",
      " 9   days_left         300153 non-null  int64  \n",
      " 10  price             300153 non-null  int64  \n",
      "dtypes: float64(1), int32(7), int64(2), object(1)\n",
      "memory usage: 17.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "741674e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,7))\n",
    "sns.heatmap(df.corr(), annot = True, cmap = \"bwr\" )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24d2e902",
   "metadata": {},
   "source": [
    "# FEATURE SELECTION\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0129d4da",
   "metadata": {},
   "outputs": [],
   "source": [
    "# USING VARIANCE INFLATION FACTOR (VIF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7ed90f9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "\n",
    "col_list = []\n",
    "for col in df.columns:\n",
    "    if((df[col].dtype != 'object')&(col != 'price')):\n",
    "        col_list.append(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d0a20a38",
   "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>airline</th>\n",
       "      <th>source_city</th>\n",
       "      <th>departure_time</th>\n",
       "      <th>stops</th>\n",
       "      <th>arrival_time</th>\n",
       "      <th>destination_city</th>\n",
       "      <th>class</th>\n",
       "      <th>duration</th>\n",
       "      <th>days_left</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300148</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300149</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.42</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300150</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>13.83</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300151</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300152</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300153 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        airline  source_city  departure_time  stops  arrival_time  \\\n",
       "0             4            2               2      2             5   \n",
       "1             4            2               1      2             4   \n",
       "2             0            2               1      2             1   \n",
       "3             5            2               4      2             0   \n",
       "4             5            2               4      2             4   \n",
       "...         ...          ...             ...    ...           ...   \n",
       "300148        5            1               4      0             2   \n",
       "300149        5            1               0      0             5   \n",
       "300150        5            1               1      0             5   \n",
       "300151        5            1               1      0             2   \n",
       "300152        5            1               4      0             2   \n",
       "\n",
       "        destination_city  class  duration  days_left  \n",
       "0                      5      1      2.17          1  \n",
       "1                      5      1      2.33          1  \n",
       "2                      5      1      2.17          1  \n",
       "3                      5      1      2.25          1  \n",
       "4                      5      1      2.33          1  \n",
       "...                  ...    ...       ...        ...  \n",
       "300148                 3      0     10.08         49  \n",
       "300149                 3      0     10.42         49  \n",
       "300150                 3      0     13.83         49  \n",
       "300151                 3      0     10.00         49  \n",
       "300152                 3      0     10.08         49  \n",
       "\n",
       "[300153 rows x 9 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = df[col_list]\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3da4aaf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "vif = pd.DataFrame()\n",
    "vif['feature'] = x.columns\n",
    "vif[\"VIF\"] = [variance_inflation_factor(x.values,i)\n",
    "              for i in range(len(x.columns))]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cf9e66b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            feature       VIF\n",
      "0           airline  3.393124\n",
      "1       source_city  2.927766\n",
      "2    departure_time  2.779427\n",
      "3             stops  1.426614\n",
      "4      arrival_time  3.684550\n",
      "5  destination_city  2.885337\n",
      "6             class  2.849370\n",
      "7          duration  4.113876\n",
      "8         days_left  3.976790\n"
     ]
    }
   ],
   "source": [
    "print(vif)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7cc10bbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>4</td>\n",
       "      <td>5</td>\n",
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       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
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       "    <tr>\n",
       "      <th>300149</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.42</td>\n",
       "      <td>49</td>\n",
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       "    <tr>\n",
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       "      <td>49</td>\n",
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       "    <tr>\n",
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       "      <td>5</td>\n",
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       "      <td>5</td>\n",
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       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300153 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        airline  source_city  departure_time  stops  arrival_time  \\\n",
       "0             4            2               2      2             5   \n",
       "1             4            2               1      2             4   \n",
       "2             0            2               1      2             1   \n",
       "3             5            2               4      2             0   \n",
       "4             5            2               4      2             4   \n",
       "...         ...          ...             ...    ...           ...   \n",
       "300148        5            1               4      0             2   \n",
       "300149        5            1               0      0             5   \n",
       "300150        5            1               1      0             5   \n",
       "300151        5            1               1      0             2   \n",
       "300152        5            1               4      0             2   \n",
       "\n",
       "        destination_city  class  duration  days_left  \n",
       "0                      5      1      2.17          1  \n",
       "1                      5      1      2.33          1  \n",
       "2                      5      1      2.17          1  \n",
       "3                      5      1      2.25          1  \n",
       "4                      5      1      2.33          1  \n",
       "...                  ...    ...       ...        ...  \n",
       "300148                 3      0     10.08         49  \n",
       "300149                 3      0     10.42         49  \n",
       "300150                 3      0     13.83         49  \n",
       "300151                 3      0     10.00         49  \n",
       "300152                 3      0     10.08         49  \n",
       "\n",
       "[300153 rows x 9 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ea0dc2d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>airline</th>\n",
       "      <th>flight</th>\n",
       "      <th>source_city</th>\n",
       "      <th>departure_time</th>\n",
       "      <th>stops</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>2</td>\n",
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       "      <td>5</td>\n",
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       "      <td>2.25</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>UK-963</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>300148</th>\n",
       "      <td>5</td>\n",
       "      <td>UK-822</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300149</th>\n",
       "      <td>5</td>\n",
       "      <td>UK-826</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.42</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300150</th>\n",
       "      <td>5</td>\n",
       "      <td>UK-832</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>13.83</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300151</th>\n",
       "      <td>5</td>\n",
       "      <td>UK-828</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300152</th>\n",
       "      <td>5</td>\n",
       "      <td>UK-822</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300153 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        airline   flight  source_city  departure_time  stops  arrival_time  \\\n",
       "0             4  SG-8709            2               2      2             5   \n",
       "1             4  SG-8157            2               1      2             4   \n",
       "2             0   I5-764            2               1      2             1   \n",
       "3             5   UK-995            2               4      2             0   \n",
       "4             5   UK-963            2               4      2             4   \n",
       "...         ...      ...          ...             ...    ...           ...   \n",
       "300148        5   UK-822            1               4      0             2   \n",
       "300149        5   UK-826            1               0      0             5   \n",
       "300150        5   UK-832            1               1      0             5   \n",
       "300151        5   UK-828            1               1      0             2   \n",
       "300152        5   UK-822            1               4      0             2   \n",
       "\n",
       "        destination_city  class  duration  days_left  \n",
       "0                      5      1      2.17          1  \n",
       "1                      5      1      2.33          1  \n",
       "2                      5      1      2.17          1  \n",
       "3                      5      1      2.25          1  \n",
       "4                      5      1      2.33          1  \n",
       "...                  ...    ...       ...        ...  \n",
       "300148                 3      0     10.08         49  \n",
       "300149                 3      0     10.42         49  \n",
       "300150                 3      0     13.83         49  \n",
       "300151                 3      0     10.00         49  \n",
       "300152                 3      0     10.08         49  \n",
       "\n",
       "[300153 rows x 10 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = df.drop(columns = ['price'])\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65f9ffcf",
   "metadata": {},
   "source": [
    "# SPLITTING THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8cc990f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#a = df.drop(columns = ['price'])\n",
    "a = x\n",
    "b = df[\"price\"]\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(a, b , test_size  = 0.2, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ef4051dd",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>airline</th>\n",
       "      <th>source_city</th>\n",
       "      <th>departure_time</th>\n",
       "      <th>stops</th>\n",
       "      <th>arrival_time</th>\n",
       "      <th>destination_city</th>\n",
       "      <th>class</th>\n",
       "      <th>duration</th>\n",
       "      <th>days_left</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300148</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300149</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.42</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300150</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>13.83</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300151</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300152</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10.08</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300153 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        airline  source_city  departure_time  stops  arrival_time  \\\n",
       "0             4            2               2      2             5   \n",
       "1             4            2               1      2             4   \n",
       "2             0            2               1      2             1   \n",
       "3             5            2               4      2             0   \n",
       "4             5            2               4      2             4   \n",
       "...         ...          ...             ...    ...           ...   \n",
       "300148        5            1               4      0             2   \n",
       "300149        5            1               0      0             5   \n",
       "300150        5            1               1      0             5   \n",
       "300151        5            1               1      0             2   \n",
       "300152        5            1               4      0             2   \n",
       "\n",
       "        destination_city  class  duration  days_left  \n",
       "0                      5      1      2.17          1  \n",
       "1                      5      1      2.33          1  \n",
       "2                      5      1      2.17          1  \n",
       "3                      5      1      2.25          1  \n",
       "4                      5      1      2.33          1  \n",
       "...                  ...    ...       ...        ...  \n",
       "300148                 3      0     10.08         49  \n",
       "300149                 3      0     10.42         49  \n",
       "300150                 3      0     13.83         49  \n",
       "300151                 3      0     10.00         49  \n",
       "300152                 3      0     10.08         49  \n",
       "\n",
       "[300153 rows x 9 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbb77afe",
   "metadata": {},
   "source": [
    "STANDARDIZING "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2fc743b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(x_train)\n",
    "X_test = sc.transform(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "293613f6",
   "metadata": {},
   "source": [
    "APPLYING LINEAR REGRESSION MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2cecf78f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b0a4b1bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c0895bc2",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred1 = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bc812756",
   "metadata": {},
   "outputs": [],
   "source": [
    "error_pred = pd.DataFrame(columns ={'Actual data','Predicted data' })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "449ed037",
   "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>actual data</th>\n",
       "      <th>Predicted data</th>\n",
       "      <th>Actual data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27131</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4585.880510</td>\n",
       "      <td>7366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266857</th>\n",
       "      <td>NaN</td>\n",
       "      <td>52842.077073</td>\n",
       "      <td>64831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141228</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7877.980184</td>\n",
       "      <td>6195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288329</th>\n",
       "      <td>NaN</td>\n",
       "      <td>56120.138579</td>\n",
       "      <td>60160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97334</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6663.204177</td>\n",
       "      <td>6578</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       actual data  Predicted data  Actual data\n",
       "27131          NaN     4585.880510         7366\n",
       "266857         NaN    52842.077073        64831\n",
       "141228         NaN     7877.980184         6195\n",
       "288329         NaN    56120.138579        60160\n",
       "97334          NaN     6663.204177         6578"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error_pred['Actual data']= y_test\n",
    "error_pred['Predicted data']= y_pred1\n",
    "error_pred.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8b1a12b",
   "metadata": {},
   "source": [
    "CHECKING HOW ACCURATE THE MODEL IS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5303c731",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import r2_score,mean_absolute_error,mean_squared_error\n",
    "from sklearn.metrics import mean_absolute_percentage_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "57a5773a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.904554350718816"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#R2 indicates the proportion of data points which lie within the line created by the regression \n",
    "#equation. A higher value of R2 is desirable as it indicates better results.\n",
    "r2_score(y_test,y_pred1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e071f893",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4624.9948680168745\n",
      "0.4353581089683267\n",
      "49200540.293722\n",
      "RMSE: 7014.309680483319\n"
     ]
    }
   ],
   "source": [
    "mae1 = mean_absolute_error(y_test, y_pred1)\n",
    "print(mae1)\n",
    "MAPE1 = mean_absolute_percentage_error(y_test,y_pred1)\n",
    "print(MAPE1)\n",
    "from sklearn import metrics\n",
    "mse1 = metrics.mean_squared_error(y_test, y_pred1)\n",
    "print(mse1)\n",
    "root_mean_square_error1 = np.sqrt(mean_squared_error(y_test, y_pred1))\n",
    "print(\"RMSE1:\", root_mean_square_error1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0e26c01a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\shiva\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shiva\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1c15983db20>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(y_test, label = \"Actual\")\n",
    "sns.distplot(y_pred1, label = \"Prediction\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed8c0d7e",
   "metadata": {},
   "source": [
    "APPLYING DECISION TREE MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b569164b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "eca25861",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = DecisionTreeRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0f0dadcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor()"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e2133385",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.15009744 -0.33003243  0.90291402 ...  0.67246146  1.04760002\n",
      "   1.03096515]\n",
      " [ 1.03227296  0.81160707  0.90291402 ... -1.48707407 -0.33126787\n",
      "   1.17836796]\n",
      " [ 1.03227296  0.81160707  0.90291402 ...  0.67246146 -0.23813869\n",
      "   1.10466656]\n",
      " ...\n",
      " [-1.15009744  0.24078732 -0.80832578 ...  0.67246146  0.18997755\n",
      "   0.14654831]\n",
      " [-0.05891224  0.24078732 -0.23791252 ...  0.67246146 -1.41962831\n",
      "   1.03096515]\n",
      " [ 1.03227296 -0.90085218  1.47332728 ... -1.48707407  1.83572309\n",
      "  -1.69598679]]\n",
      "[ 7366. 72783.  6195. ...  6314.  5082. 70049.]\n"
     ]
    }
   ],
   "source": [
    "y_pred2 = clf.predict(X_test)\n",
    "print(X_test)\n",
    "print(y_pred2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f525e3e5",
   "metadata": {},
   "source": [
    "SCORES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3dda29ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9755799924842121\n"
     ]
    }
   ],
   "source": [
    "r22 = r2_score(y_test, y_pred2)\n",
    "print(r22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a43ee7bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE2 Score: 1172.5982631196107\n",
      "MAPE2 Score: 0.07367950167186328\n"
     ]
    }
   ],
   "source": [
    "mae2 = mean_absolute_error(y_test, y_pred2)\n",
    "print(\"MAE2 Score:\", mae2)\n",
    "mape2 = mean_absolute_percentage_error(y_test, y_pred2)\n",
    "print(\"MAPE2 Score:\" ,mape2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3e625f9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE2: 12588080.994807314\n",
      "RMSE2: 3547.968572973458\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "print(\"MSE2:\", mean_squared_error(y_test, y_pred2))\n",
    "root_mean_square_error2 = np.sqrt(mean_squared_error(y_test, y_pred2))\n",
    "print(\"RMSE2:\", root_mean_square_error2 )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26a0ecf4",
   "metadata": {},
   "source": [
    "APPLYING RANDOM FOREST MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "47cfa12d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor()"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "rf = RandomForestRegressor()\n",
    "rf.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6647b59c",
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_pred = rf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bd8e3cee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2 Score3: 0.98497022521525\n",
      "MAE Score3: 1088.9661864286124\n",
      "MAPE Score3: 0.07039882328342371\n",
      "MSE3: 7747582.477271032\n",
      "RMSE3: 2783.447947648928\n"
     ]
    }
   ],
   "source": [
    "r23 = r2_score(y_test, rf_pred)\n",
    "print(\"R2 Score3:\" ,r23)\n",
    "mae3 = mean_absolute_error(y_test, rf_pred)\n",
    "print(\"MAE Score3:\", mae3)\n",
    "mape3 = mean_absolute_percentage_error(y_test, rf_pred)\n",
    "print(\"MAPE Score3:\" ,mape3)\n",
    "print(\"MSE3:\", mean_squared_error(y_test, rf_pred))\n",
    "root_mean_square_error3 = np.sqrt(mean_squared_error(y_test, rf_pred))\n",
    "print(\"RMSE3:\", root_mean_square_error3 )\n",
    "# lower the rmse and mape the better the model."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45b2ad88",
   "metadata": {},
   "source": [
    "so the best model for this dataset is Rndom forest as we can see that random forest model have the \n",
    "lowest \"Mape\" and \"rmse\" score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "599b1dfa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
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