{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "adc03ab0-e956-4067-b069-d1aa0bae7976",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a826ba78-ce94-406f-adc0-404c18b03f76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('Titanic-Dataset.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ca1354d3-6362-4c36-acf0-341b467470f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bbaa6544-c9e6-4c72-8c44-13edd6f804aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId      0\n",
       "Survived         0\n",
       "Pclass           0\n",
       "Name             0\n",
       "Sex              0\n",
       "Age            177\n",
       "SibSp            0\n",
       "Parch            0\n",
       "Ticket           0\n",
       "Fare             0\n",
       "Cabin          687\n",
       "Embarked         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "28c78cef-1a2c-4fe8-b077-97e4b9581996",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "891"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b3971b94-d2ec-46f4-82e2-279915c992da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId      int64\n",
       "Survived         int64\n",
       "Pclass           int64\n",
       "Name            object\n",
       "Sex             object\n",
       "Age            float64\n",
       "SibSp            int64\n",
       "Parch            int64\n",
       "Ticket          object\n",
       "Fare           float64\n",
       "Cabin           object\n",
       "Embarked        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a436916b-856c-414d-9b08-559a055c0fd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns with more than 30% missing values:\n",
      "Cabin    77.104377\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "missing_percentage = df.isnull().mean() * 100\n",
    "columns_with_missing_30 = missing_percentage[missing_percentage > 30]\n",
    "print(\"Columns with more than 30% missing values:\")\n",
    "print(columns_with_missing_30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ca5f200d-b6a8-4796-904f-920666313752",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns dropped: ['Cabin']\n",
      "Remaining columns: ['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp', 'Parch', 'Ticket', 'Fare', 'Embarked']\n"
     ]
    }
   ],
   "source": [
    "missing_percentage = df.isnull().mean() * 100  \n",
    "threshold = 30  \n",
    "\n",
    "columns_to_drop = missing_percentage[missing_percentage > threshold].index  \n",
    "\n",
    "df = df.drop(columns=columns_to_drop)  \n",
    "\n",
    "print(f\"Columns dropped: {list(columns_to_drop)}\")  \n",
    "print(f\"Remaining columns: {df.columns.tolist()}\")  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0b89f2a9-c936-4cd9-b86a-f826981f38f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>523</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>190</td>\n",
       "      <td>0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>596</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>353</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>669</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>472</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  Name  Sex   Age  SibSp  Parch  Ticket  \\\n",
       "0            1         0       3   108    1  22.0      1      0     523   \n",
       "1            2         1       1   190    0  38.0      1      0     596   \n",
       "2            3         1       3   353    0  26.0      0      0     669   \n",
       "3            4         1       1   272    0  35.0      1      0      49   \n",
       "4            5         0       3    15    1  35.0      0      0     472   \n",
       "\n",
       "      Fare  Embarked  \n",
       "0   7.2500         2  \n",
       "1  71.2833         0  \n",
       "2   7.9250         2  \n",
       "3  53.1000         2  \n",
       "4   8.0500         2  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder \n",
    "label_encoder = LabelEncoder()\n",
    "for column in df.select_dtypes(include=['object']).columns:     \n",
    "    df[column] = label_encoder.fit_transform(df[column]) \n",
    "    \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "671b5b4a-374e-4b77-8188-c78c2f430817",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "data = df.copy()\n",
    "\n",
    "def replace_outliers_with_nan(column):\n",
    "    Q1 = column.quantile(0.25)\n",
    "    Q3 = column.quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower_bound = Q1 - 1.5 * IQR\n",
    "    upper_bound = Q3 + 1.5 * IQR\n",
    "    \n",
    "    return column.where((column >= lower_bound) & (column <= upper_bound), np.nan)\n",
    "\n",
    "\n",
    "for col in data.columns:\n",
    "    data[col] = replace_outliers_with_nan(data[col])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fc6726bb-10d1-4ded-8f86-c8bd4dccaa80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum of null values in each column:\n",
      "PassengerId      0\n",
      "Survived         0\n",
      "Pclass           0\n",
      "Name             0\n",
      "Sex              0\n",
      "Age            188\n",
      "SibSp           46\n",
      "Parch          213\n",
      "Ticket           0\n",
      "Fare           116\n",
      "Embarked         0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "null_counts = data.isnull().sum()\n",
    "print(\"Sum of null values in each column:\")\n",
    "print(null_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "812d709d-8a38-45aa-a272-6c9d45dc4e15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId    0\n",
       "Survived       0\n",
       "Pclass         0\n",
       "Name           0\n",
       "Sex            0\n",
       "Age            0\n",
       "SibSp          0\n",
       "Parch          0\n",
       "Ticket         0\n",
       "Fare           0\n",
       "Embarked       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.impute import KNNImputer\n",
    "imputer = KNNImputer(n_neighbors=2)\n",
    "data_imputed_knn = pd.DataFrame(imputer.fit_transform(data), columns=data.columns) \n",
    "data_imputed_knn.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "35b6a7c0-c8f4-42fa-9a9f-df57b6bba257",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "df = pd.read_csv(\"Titanic-Dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "92de8e3c-c059-4a11-ab28-f6f1eed4aefb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "sns.histplot(titanic_df['Age'].dropna(), bins=30, kde=True, color='blue')\n",
    "plt.title('Age Distribution')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "f59ceb9d-5f75-462c-a54e-d68bb3a4f1c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\STCs\\AppData\\Local\\Temp\\ipykernel_11012\\901352970.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.countplot(x='Survived', data=titanic_df, palette='coolwarm')\n"
     ]
    },
    {
     "data": {
      "image/png": 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TV/TUtTC6devmQobmacSJWis6d+7shqZOnDjREhISQgFl6NChNmHCBBc4VNcxYsSISH0UAACQhZj0oE+iEBat6LobDRo08NanvGTjAdt/4JiXdQORlphQxJrX+U/wB1C4pOXwGMoN0gAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAADA6R0yevXqZffdd1/oeWpqql1//fVWv35969Kli23YsCFs+Xnz5lnr1q3d/JSUFPv+++8jsNUAACCqQ8Zbb71lixcvDj0/cOCACx2NGjWy2bNn20UXXWS9e/d202XdunU2ePBg69evn02fPt32799vgwYNiuAnAAAAURcy9u3bZ6NGjbJ69eqFps2fP9/i4+Nt4MCBVq1aNRcoSpQoYW+//babP2XKFGvXrp116tTJatas6V6vkLJ9+/YIfhIAABBVIWPkyJHWsWNHq169emja2rVrrWHDhhYTE+Oe6+fFF19sa9asCc1XK0egQoUKlpyc7KYDAIDoUDSSb75s2TJbuXKlzZ071x5++OHQ9D179oSFDklKSrLNmze733fv3m3lypU7bv7OnTtzvQ1paWnmQ2xsrJf1AtHG1z4EoODv9xELGYcPH7YhQ4bYQw89ZMWKFQubd/DgQYuLiwubpudHjhxxvx86dOik83Nj/fr1lt+KFy9utWvXzvf1AtFo06ZNbp8FgKgJGePHj7e6detaixYtjpuneozMgUHPgzByovk6uOeWakFodQDyrkaNGpHeBAARaMnIyUl60UiOKNm7d68bOSJBaHjnnXesQ4cObl5Geh50kZQvXz7L+WXLls31dihgEDKAvGP/ARB1IePll1+2o0ePhp6PGTPG/RwwYIB9/PHH9uyzz1p6eror+tTP1atXW58+fdwyujbGqlWrrHPnzu75d9995x6aDgAACnnIqFixYthzDVGVKlWquCLOv//97zZ8+HC78cYbbdq0aa7PV8NW5aabbrLu3btbgwYNXHeHlrv88sutcuXKEfksAAAgCoewZqVkyZL2zDPPhForNDR14sSJlpCQ4Oari2Xo0KE2YcIEFzhKlSplI0aMiPRmAwCADGLS1RdRSItWdN0NtYb46lNesvGA7T9wzMu6gUhLTChizev8J/gDKFzScngMjcqWDAAAUPARMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByABQ6KSnp0d6E4BC8f+8aKQ3AABOtZiYGPtpwzJLO7A/0psCeBGbkGhn1r3UIo2QAaBQUsBI++mHSG8GcFqjuwQAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAAUjJDx/fff5/cqAQBAYQkZtWrVyjJMfPvtt/aHP/whP7YLAAAUcDm+d8nrr79us2fPDt3ZLSUlxc4444ywZXbv3m1ly5bN/60EAACnb8i48sor7ZtvvnG/r1ixwho0aGAlSpQIWyYhIcEtBwAAkOOQoUDRr18/93vFihWtffv2Fh8f73PbAABAAZanW71fd9119tVXX9mGDRvs119/PW5+p06d8mPbAABAYQsZzz33nI0ZM8ZKlSp1XJdJTExMjkOGgsrQoUNt9erVbl233HKL3XbbbW7e9u3b7cEHH7Q1a9ZYcnKy3X///da8efPQa5cuXWqPPfaYW65+/fo2fPhwq1y5cl4+DgAAiJaQMWnSJLvnnnvsL3/5S57f+NixY9arVy+rV6+ezZkzxwWOu+++28qXL28dOnRwhaUXXHCBzZo1y9577z3XVTN//nwXOHbs2OHm9+/f31q0aGETJkywvn372ptvvulCDgAAKKAh4/Dhw3bVVVf9pjfeu3evGwr78MMPW8mSJa1q1ap26aWX2qpVq6xMmTKuhWLatGmumLRatWq2bNkyFzgULGbMmGF169a1nj17unWNGDHCmjVr5gpSmzRp8pu2CwAARDBkXHPNNfbKK6/YwIED89xyUK5cORs7dmxoSKy6TD7++GMbMmSIrV271mrXru0CRqBhw4au60Q0v1GjRqF5xYsXtzp16rj5uQ0ZaWlp5kNsbKyX9QLRxtc+5BP7JwqLNE/7Z07Xm6eQ8fPPP9vMmTNt3rx5VqlSpeOul/HSSy/lan1XXHGF6wJp1aqVtWnTxtVaKIRklJSUZDt37nS/79mz56Tzc2P9+vWW3xR6FJKAwmDTpk128OBBKyjYP1GYbIrw/pmnkKGujT59+uTbRjz55JOu+0RdJ+r60B8kLi4ubBk9P3LkiPs9u/m5oZoQzmqAvKtRo0akNwHAKd4/1ZKRk5P0PIWM4HoZ+UUH+qDWY8CAAdalS5fjkpcCRLFixdzvuj5H5kCh54mJibl+bwUMQgaQd+w/QPSKjfD+maeQMWjQoJPOV2tEdtRyoRqK1q1bh6ZVr17dXXdDlybftm3bccsHXSQagaLnWRWSAgCA0+gurEePHrUvvvjCDTEtXbp0jl6jS5SrRWTXrl2habq4l16vIs+NGzfaoUOHQvM06kTXwxD91POAWj1SU1ND8wEAQOTlqSXjRC0VukjX559/nuMuEo0I0UW21DKiO7iOHj3a1Xo0btzYKlSo4Kbr+heLFi2ydevWhd5X3SnPP/+8TZw40RWL6joZKkBl+CoAAKdZS0agbdu2tmDBghz3Ez311FOu0rtbt242ePBg6969u/Xo0SM0T6NIOnfu7C6ypSChC3GJAsW4cePcdTO6du1q+/btc/O5EBcAAAW8JSMrBw4csNdee83OPvvsHL9GtRXjx4/Pcl6VKlVsypQpJ3xty5Yt3QMAAJxGIaNmzZpZthpo1MewYcPyY7sAAEBhDBmZL7alwKELcml0iC4RDgAAkKeQocJM+fLLL23r1q3uZmfnnnsuAQMAAPy2kLF//3438mPhwoXuFu268tcvv/xil1xyiSvAPPPMM/OyWgAAUNhHl6juQvcJ0XUxli9fbitXrrS5c+e64s+cXIgLAACc/vIUMv71r3+5+4ycd955oWmqx3jooYdc6wYAAECeQoZGkRQpcvxLVQBaEG/7DAAAoiRk6NbsjzzyiH399dehaSoCVTcK164AAAB5Lvy85557LCUlxdq0aRO68+mPP/5ol112mT344IP8ZQEAQO5DxldffeUu7/3yyy/bpk2b3BBWdZ9UrVrVqlWr5mcrAQDA6dtdkp6e7rpD2rVrZ5988ombVqNGDWvfvr27h0iHDh3sb3/7m1sOAACgSG6u8qkhq7oORnAxroBuZqbpc+bMsVdffdXHdgIAgNM1ZOjmZ6q30K3VT1QMOmDAAEIGAADIXcj49ttv7cILLzzpMk2bNrXt27fndJUAAOA0luOQkZSU5ILGyegqoGeddVZ+bBcAACgsIePKK6+0cePG2a+//prl/KNHj9r48eOtefPm+bl9AADgdB/C2rdvX+vatat17tzZunfvbnXr1nU3QtP1MTZu3GhTpkxxN0kbNWqU3y0GAACnV8jQRbdU/DlmzBg3VPXgwYNuuoasKmxoKGv//v2tTJkyPrcXAACcjhfjUr2FrpWhG6GpwFO3fNe0c845x2JjY/1tJQAAKByXFY+Li+PqngAAIP9vkAYAAJAdQgYAAPCCkAEAALwgZAAAAC8IGQAAwAtCBgAA8IKQAQAAvCBkAAAALwgZAADAC0IGAADwgpABAAC8IGQAAAAvCBkAAMALQgYAAPCCkAEAALwgZAAAAC8IGQAAwAtCBgAA8IKQAQAAvCBkAAAALwgZAADg9AsZu3btsjvuuMMaN25sLVq0sBEjRtjhw4fdvO3bt9utt95qDRo0sPbt29uSJUvCXrt06VLr0KGD1a9f33r06OGWBwAA0SNiISM9Pd0FjIMHD9rUqVPtiSeesEWLFtnYsWPdvJSUFCtTpozNmjXLOnbsaP369bMdO3a41+qn5nfu3NlmzpxppUuXtr59+7rXAQCA6FA0Um+8bds2W7NmjX344YcuTIhCx8iRI+2yyy5zLRPTpk2zhIQEq1atmi1btswFjv79+9uMGTOsbt261rNnT/c6tYA0a9bMVqxYYU2aNInURwIAANHQklG2bFl77rnnQgEj8PPPP9vatWutdu3aLmAEGjZs6EKJaH6jRo1C84oXL2516tQJzQcAAIW4JSMxMdHVYQSOHTtmU6ZMsaZNm9qePXusXLlyYcsnJSXZzp073e/Zzc+NtLQ08yE2NtbLeoFo42sf8on9E4VFmqf9M6frjVjIyGz06NGWmprqaixefPFFi4uLC5uv50eOHHG/q47jZPNzY/369Zbf1LKilhigMNi0aZPbJwsK9k8UJpsivH8WjZaAMXnyZFf8ecEFF1h8fLzt27cvbBkFiGLFirnfNT9zoNBztY7kVr169TirAX6DGjVqRHoTAJzi/VMtGTk5SY94yHj00Uft1VdfdUGjTZs2blr58uVty5YtYcvt3bs31EWi+XqeeX6tWrVy/f4KGIQMIO/Yf4DoFRvh/TOi18kYP368G0Hy+OOP29VXXx2armtfbNy40Q4dOhSatmrVKjc9mK/nATUFqaslmA8AACIvYiFj69at9tRTT9ntt9/uRo6omDN46OJcFSpUsEGDBtnmzZtt4sSJtm7dOuvatat7bZcuXWz16tVuuuZruUqVKjF8FQCAKBKxkLFw4ULXp/P0009b8+bNwx5q3lEAUeDQBbfefPNNmzBhgiUnJ7vXKlCMGzfOXTdDwUP1G5ofExMTqY8DAAAyiUkvpJfJVMDRdTV02XJffVZLNh6w/QeOeVk3EGmJCUWseZ3/u5ZNQbNvxTuW9tMPkd4MwIvYM8+2sxr/p84xksdQbpAGAAC8IGQAAAAvCBkAAMALQgYAAPCCkAEAALwgZAAAAC8IGQAAwAtCBgAA8IKQAQAAvCBkAAAALwgZAADAC0IGAADwgpABAAC8IGQAAAAvCBkAAMALQgYAAPCCkAEAALwgZAAAAC8IGQAAwAtCBgAA8IKQAQAAvCBkAAAALwgZAADAC0IGAADwgpABAAC8IGQAAAAvCBkAAMALQgYAAPCCkAEAALwgZAAAAC8IGQAAwAtCBgAA8IKQAQAAvCBkAAAALwgZAADAC0IGAADwgpABAAC8IGQAAAAvCBkAAMALQgYAAPCCkAEAAE7fkHHkyBHr0KGDLV++PDRt+/btduutt1qDBg2sffv2tmTJkrDXLF261L2mfv361qNHD7c8AACIHhEPGYcPH7a7777bNm/eHJqWnp5uKSkpVqZMGZs1a5Z17NjR+vXrZzt27HDz9VPzO3fubDNnzrTSpUtb37593esAAEB0iGjI2LJli91www329ddfh03/6KOPXMvE0KFDrVq1ata7d2/XoqHAITNmzLC6detaz5497fzzz7cRI0bYt99+aytWrIjQJwEAAFEVMhQKmjRpYtOnTw+bvnbtWqtdu7YlJCSEpjVs2NDWrFkTmt+oUaPQvOLFi1udOnVC8wEAQOQVjeSb33zzzVlO37Nnj5UrVy5sWlJSku3cuTNH83MjLS3NfIiNjfWyXiDa+NqHfGL/RGGR5mn/zOl6IxoyTuTgwYMWFxcXNk3PVSCak/m5sX79estvallRSwxQGGzatMntkwUF+ycKk00R3j+jMmTEx8fbvn37wqYpQBQrViw0P3Og0PPExMRcv1e9evU4qwF+gxo1akR6EwCc4v1TLRk5OUmPypBRvnx5VxSa0d69e0NdJJqv55nn16pVK9fvpYBByADyjv0HiF6xEd4/Iz6ENSu69sXGjRvt0KFDoWmrVq1y04P5eh5QU1BqampoPgAAiLyoDBmNGze2ChUq2KBBg9z1MyZOnGjr1q2zrl27uvldunSx1atXu+mar+UqVarkRqoAAIDoUCRam3eeeuopN4pEF9x68803bcKECZacnOzmK1CMGzfOXTdDwUP1G5ofExMT6U0HAADRVpOhCtiMqlSpYlOmTDnh8i1btnQPAAAQnaKyJQMAABR8hAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgAAgBeEDAAA4EWBDhmHDx+2+++/3xo1amTNmze3SZMmRXqTAADA/1fUCrBRo0bZhg0bbPLkybZjxw679957LTk52dq2bRvpTQMAoNArsCHjwIEDNmPGDHv22WetTp067rF582abOnUqIQMAgChQYLtLPvvsMzt69KhddNFFoWkNGza0tWvX2rFjxyK6bQAAoAC3ZOzZs8fOPvtsi4uLC00rU6aMq9PYt2+flS5d+qSvT09Pdz+PHDlisbGx+b59WmeJ+HS9Ub6vG4gG+v+dlpbmHgWN2+eLJ1qMxUR6UwA/ip/pdf8M1hscS0+7kHHw4MGwgCHBcwWH7AStHampqeZTca9rByLn2GGzNWusAIszi02K9EYAfugweAp20Ox6DgpsyIiPjz8uTATPixUrlu3rixYtavXq1bMiRYpYTAxnMwAA5JRaMBQwdCw9LUNG+fLl7YcffnB1GcGHVBeKAkZiYmK2r1e4yNwSAgAA8k+BLfysVauWCxdrMjQHrVq1KtQ6AQAAIqvAHo2LFy9unTp1socfftjWrVtn7733nrsYV48ePSK9aQAAwMxi0rMrDY3y4k+FjHfffddKlixpf/nLX+zWW2+N9GYBAICCHjIAAED0KrDdJQAAILoRMgAAgBeEDAAA4AUhA7lSo0YN++tf/3rc9NmzZ9sVV1yR4/X885//tP/93/894XzdXVeFvLo3jR5//OMf7cMPPzSfn2v58uX5vt5x48ZZ9+7d8329QH769ddf3f/VP/zhD1a3bl27/PLLbcSIEfbzzz8XqH3C136MvCNkINfmzZtny5Yty/Prv/32W7vrrrvc6KCs7Ny50/70pz+5cDFz5kybNWuWNW3a1Hr16uVugOfDkiVLwm62BxQmY8aMcaP0hg0bZm+//bYLGAr1AwYMyPf36tmzpwsaKBwIGci1ihUr2tChQ3N0j5isZDegSV92lSpVsn79+lm1atXsvPPOs/79+9sll1ziAocPZcuW5QqwKLTmzJljd955p1166aVu39NPXR5g0aJFtnv37nx9rxIlSthZZ52Vr+tE9CJkINfUCrFr1y57/vnnT7iMWiP0pdW4cWNr0qSJO0MKQomaZIOf6mbJTFdsVWvHV199FTZ95MiRdscdd5ywe0ZNsMEZ0n333ece1157rfvCVEi55ZZbwpZ//PHHQ9dVCZpZX3311ePWO336dLvqqqvc7/oM+iz6THroTE93/Q1s2bLFbrrpJqtfv767MJwufQ9EO92/6aOPPgq72ZVa9t566y13t2vtExn3Ve0r2mfkm2++cb9PmDDBnQgMGjTIXXlZ6wuo20XTVq5cGeou0Xu1aNEi7MRBJyCXXXaZvfHGG+65lu/cubNdeOGFds0119g777wTtt3jx493+7f2xRkzZnj9GyFvCBnI031jdLD/xz/+Ydu3bz9uvg7E6u5Qd8jLL79sY8eOtffff99GjRrl5gdfBvrZvn37417frl07dw8azVPT6nPPPWeff/65e98yZcrkeDv1RaVA9Mwzz1jfvn3dZecz1oHoC+vqq68Oe02bNm1cgFJNSMaWFW1TEEw079lnn7WXXnrJfXkqTAWfW106lStXdl/IWpcCChDtFIi1rypMDBkyxO0bhw4dsurVq9sZZ5yRo3WsXr3aBYbevXu78LBgwYLQPO3/pUuXtoYNG4adTLRt2zZsOd0mQqFdJyC6F5XWpZAxd+5cu+2229yJg4KHaN/SPvjYY4/Ziy++6K2VE78NIQN5ojORKlWq2PDhw4+b98EHH7gD9ejRo90Zjs40HnroIddK8Msvv7gvG9HPrO6Ym5SU5GoxunTpYp9++qlbj85iFFxOViyamc6c9KWpsyDd66Zq1aru8vOyadMm11py5ZVXhr1G26T6DwUL+fHHH91ZmwKPQtOUKVPskUcecevUZ1NwWrFihVvf0qVL3RekmpnVzaNi1datW+f6bwucaikpKW4/+93vfmevvfaaO4nI3MqQHe2f55xzjtvPFN4VHoKuUYUWBfXMd7zWcqr9CApMtVzLli3dFZynTp1qv//9710LpL5rOnbsaN26dbPJkye7ZbWdes9WrVq5/VstjIg+hAzkSWxsrDuY6gwlOHAHtm7d6r5oSpUqFZp28cUXuzvmfv311zlav77sVPehLyAFjttvv92d5TzwwAO5qh3JSEEhCA/6qS+wrPqG9cUXLLdw4UL3BadAoVYbVeHfeOONoVEv+kJUs++XX37pukr0uRMSEsKCDlAQqGtx2rRpLiyrEPT888+3wYMHh7Xq5XR/04F///79rlBb4VwnHlm1WjZo0MDVQy1evNg9134XLLdt2zZXExLsa3oo5GtfC75nFC4CanXJuO8hOhTYW70j8hQc1Nqg1gw1ZQbi4+OPWzYtLS3s58lMnDjRHZzVAqImVf2uh77EVJchmc+IRCEmo8zboS8vdZ3oy09fZhoimxW1bqjJePPmzWFdJcG2v/LKK8d9man1RV/QmYtac9rUDETKZ599Zq+//rrrihDVYKjlUN19qkXKWFsRyGo/zri/af9Q0FDLhFo11c2p1r+saL/UcgrzqmHS8Nlgf9Z29OnTJ2x53X07kHl/yzgP0YGWDPwmKnw8cOBAWBHoueee6842MhZEqhVCXwBqTs0qIGTu21X/cGaJiYmhrhYdvNX1kvHLRgVoJ6MuDD0UBrR9J+rKOPPMM11Tsa7lobO6oG5DtRZqwdHn0heiHmrW1XA/dePozE/r/emnn0LrUncPEM0UGF544QVLTU0Nm67RVurO1D6XeX/LqhYrM+03aqFQS2dWrRgZl1OLpYKGujd1h+3ge0TF38G+podaFlWfIdrf1q9fH1qP9n+dQCC6EDLwm+isR0FD9Q2BZs2auQPywIEDXa2CzoQeffRR69ChgwsKwZeIzqAyfnEFVDz573//O9RUqy+a+fPnuz7jP//5z24ZXTBIB3uFEX3h6UCv+ons6Avt6aefdhXsCggnW05fvBo+qy870fLXX3+96yZSnYa6R/QZtX0a9qfulwoVKrjtVlOuij+13UA0q1Onjms9UHG0DuA6WOukQK15KmZWa4ZaEtVtqQJs/d+fNGlStuvVPqbhr9mFDHV5lCtXznWFBK2GcvPNN7v9/4knnnDhXdumwuvk5GQ3X7UaKvxUONF2ab9TyyeiC/8i+M26du0adiErne0/9dRT7vcbbrjB7r77blctrhoL0ZmR+n818iOrYWfqhlG1uIbBanSJwomCgYrTgisFqvbh3nvvddM7derkWjLUvJsdfdmp5SXzqJLM1NSrdWb+clSTsrpxVBinz6bWGXXv6DPrbE/dMQo71113nSt0VfEnEO00AkyFlRoSqgO9RnWoGFMHfoVr7as6QdBID3WPBiOqTkYtIWotVH1VzZo1T7qs9jPtQwomAXWPagSb6jn0HaBtDIali7ZX+6FOYBRIdHKjbUR04VbvAADAC1oyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAF4QMgDkmu5GO27cOHclV13iXZel1qXdg1t25ye9T3Cl1/ymu+vqMtkA/OCWdQByTbcC183jhg0b5u5To/vH6HLTuo+LLgWdn3RpeV8hA4BfhAwAuTZnzhx77LHH3H1cRDeI043jdK8W3RRLN7zKLyVKlMi3dQE4teguAZBrMTEx7u66x44dC03TTfLeeustd2de3bJbd6ENqEtCXROiu3zq9wkTJtgll1xigwYNcnf51PoC6nbRtJUrV4a6S/ReLVq0sFmzZoWW062XdFOtN954wz3X8rqJ14UXXmjXXHONu0NnRroBmIJRkyZNsrw5H4D8RUsGgFzr0aOHPfnkk+423i1btnS3uW/evLlVr149x+tYvXq1CwwKD7pz7YIFC6xp06Zu3vvvv+/u1tuwYUNbtmyZm6bbeLdt29Yt16VLFzdNtyTft2+fqw3Zs2ePu3vof//3f7swonm6a2dSUpI1atTIpk+f7m4NPnLkSHdn0EceecTTXwdAgJYMALmWkpJio0ePdgfr1157zd1yO3MrQ3b+9Kc/2TnnnGNVq1a1q6++2oWH4KbQaoHQLcfVYpKRlvvwww9DBaZaTiFHtyOfOnWqCzu33HKLValSxd0KvFu3bjZ58mS3rLZT79mqVSurVauWqycB4BchA0CeXHvttTZt2jRXAKpC0PPPP98GDx5sGzZsyNHrK1asGPpdB/79+/fb2rVr7eDBg/bBBx9Y+/btj3tNgwYNrGzZsrZ48WL3/N133w0tt23bNlu0aJHrtgkeU6ZMsS+//NLN37p1qwsXAbW6JCQk/Oa/A4ATo7sEQK589tln9vrrr7uuCFENhuof2rRpY1dddVVYbUUgLS3tuGnx8fGh33WwV9BQy8SuXbusTJkyrq4iKwoVWk6tFT/88IMbPitHjx5129GnT5+w5YsW/b+vuaClJKt5APIfLRkAckWB4YUXXrDU1NSw6XFxcVasWDFXS3HGGWfYL7/8EpqnIa7ZUVeIWihU55FVK0bmLhMFDRWYFi9e3E0/99xz3RBahY/gsXDhQps7d66br5aW9evXh9ajAlS1ngDwh5ABIFfq1KnjWg/69u3rDuA6WKvIcsiQIXbkyBHXmqGRITNnzrTPP//cjSyZNGlStuvVKBENf80uZKjLQ0Nk1RWiuo3AzTff7LpqnnjiCddFom17/PHHLTk52c1XrYYKPxVOtF3q2lExKQB/2MMA5NrYsWNdYaWGhOpAr1EdKsbUgV9FmHfddZclJia64aS6SNedd96Z7TrVEtK6dWtXTFqzZs2TLqsQEhsb64JJxhoPXQhM9RwdOnRw26guHdWOiLZXBaqPPvqoCyTNmjVz2wjAn5j0zJ2UAAAA+YCWDAAA4AUhAwAAeEHIAAAAXhAyAACAF4QMAADgBSEDAAB4QcgAAABeEDIAAIAXhAwAAOAFIQMAAHhByAAAAObD/wNvrI6eYPngVwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='Survived', data=titanic_df, palette='coolwarm')\n",
    "plt.xticks([0, 1], ['Not Survived', 'Survived'])\n",
    "plt.title('Distribution of Survival')\n",
    "plt.xlabel('Survived')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "bc355586-2339-4108-9831-fbb3a7a6af02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='Sex', hue='Survived', data=titanic_df, palette='coolwarm')\n",
    "plt.title('Survival Rate by Gender')\n",
    "plt.xlabel('Sex')\n",
    "plt.ylabel('Count')\n",
    "plt.legend(title='Survived', labels=['Not Survived', 'Survived'])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "dad2b917-d9fa-4702-ada1-e3f787eb3363",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='Pclass', hue='Survived', data=titanic_df, palette='coolwarm')\n",
    "plt.title('Survival Rate by Passenger Class')\n",
    "plt.xlabel('Passenger Class')\n",
    "plt.ylabel('Count')\n",
    "plt.legend(title='Survived', labels=['Not Survived', 'Survived'])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "ad72eae0-a365-4923-929e-340e1afa6e43",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\STCs\\AppData\\Local\\Temp\\ipykernel_11012\\2688886906.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(x='Pclass', y='Fare', data=titanic_df, palette='coolwarm')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "sns.boxplot(x='Pclass', y='Fare', data=titanic_df, palette='coolwarm')\n",
    "plt.title('Fare Distribution by Passenger Class')\n",
    "plt.xlabel('Passenger Class')\n",
    "plt.ylabel('Fare')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "2ebf78fe-00f1-4a10-9177-d7f8ea0f86a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_counts = titanic_df[\"Age\"].value_counts().sort_index()\n",
    "plt.figure(figsize=(8, 5))\n",
    "plt.plot(age_counts.index, age_counts.values, marker=\"o\", linestyle=\"-\", color=\"blue\")\n",
    "plt.title(\"Number of Passengers by Age\")\n",
    "plt.xlabel(\"Age\")\n",
    "plt.ylabel(\"Count of Passengers\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "10a1e173-0b81-4237-855d-89639739774b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0UOAP81A5pnx/vldVdHEb95Gik/ZRPB43Kmgp2t/61reacWfeKCc8tGRjpL4KX5fHh+khjGjW5vmGQRcGRr15DDkho+jmucQoJ88rjgl/CKO0f/RHf2Q8gPn3PF+47H+jHrUUxtXcV6YR8DuzGlVHA/4994tR7ipMW/jf//t/mygt94tRdJ4DXDUIS2OphecVx4nnmRAiQIJWCGGWm7mUTw9SCi4KP964KeYYFWWR2HL/zlpYfMOUAd64GbnkDZkihX6ry5f+l0PRRaHAyFmtsCEUbxQ9FJrcTkHJ7k9h+bosBqMwWV4QVYUCgNE/RnEpJikGmIbA16ZIo4CmGKZAquaXMlpMH1gWzNGuikvH/Dt64zLaGgXfiyKKYm95W9r/7//7/4zIrXYMY94rPxd9XauiuQqXzCmC+NkoSmlrRdHG/a1G0WuhEKeFGkXoH/zBH5iINNMieByqXrNR8PWYxsHx4Gswoshlez6Pdl5VOJnguLCjGX8o1Fiox4jq9Xjta19rxpCvR6HK6DyX3GsL8wjHgoI2zKd4Ofx89InlPnMZn+PEqCjHjZZdHK/q61M8c18pajlhYySc5xjTFm4UTsAoQqOKwcL+nn61/Ky1cILB1QseW35vONYUvxwjnoc8R2s7zNXClROOESdNQogAi1YHlf8XQog9A9MNGAGuLfhipJT+tRT3bHBwMzBCSE9f5nBG5dqKcOjL+sgjj9xQE429BlNxuNrA1ZPl/rdC7GUUoRVC7EnY5ICWYeyYxZQLLtGzmQBzdVm8dbMw/5TRYi4jL29qIMJhQRrzuVkcx4i4WAnTKHheScwKUY8ErRBiT8KlZy7ZUsQyf5H5jswVZTpBmAPBemCXKS6bs8p+tfxVEcDUln/+5382fsiMlIt6mIbAwkWmWAgh6lHKgRBCCCGEaGhk2yWEEEIIIRoaCVohhBBCCNHQSNAKIYQQQoiGZs8WhbETCzvU0HtxuQeiEEIIIYTYfljqRc3Ghj9h/tvY64KWYvZ6/bKFEEIIIcT2QyvE1ToH7llBW1X5HKAbbXu4VthvnaJ5M9+jUdHYhKNxiUZjE43GJhqNTTQam2g0NjtnXKrvuVp0dk8L2mqaAQ/IZh+UrXiPRkVjE47GJRqNTTQam2g0NtFobKLR2OyccbleeqiKwoQQQgghREMjQSuEEEIIIRoaCVohhBBCCNHQ7NkcWiGEEEKInWJNRfclFkDtZNzK/uXz+Q3LoeXr0JLrZi1UJWiFEEIIIbaJYrGIK1euIJvNohGEdywWw7lz5zbUwz+TyWBgYGBVW67rIUErhBBCCLENsGHAmTNnTJRycHDQCLqd3OzJ933kcjmk0+kN2U++HgX9+Pi4GYejR49e154rCglaIYQQQohtgGKOonbfvn0mStkoXbtSqdSGCW+K43g8bqK+HA++9npQUZgQQgghxDay3qjkbsHegM+/t0dQCCGEEEI0PBK0QgghhBCioZGgFUKINeDOTaF84WmUnvwcSqcfhjtzFV65bLZ5uQW44xdQOv2I+Rtvfgq+G2wTQoi1UiqV8N73vhf/7t/9O9x555140YtehHe+851YWFjY8Pd673vfi+/6ru/CZnDLLbfgX//1X7GZqChMCCFuEHd6FKUn/wUo5q89dv5JxI49AL+tC+7pR4BSwTzuU+COn4czeBR2zz5Yji63Qoi18au/+qv43Oc+h//23/6bKRy7cOECfvEXf9EUUP3Wb/3Whr7X61//+k0TtFuBIrRCCHEDePksyqcerhOzBhqin34E/uzEkpitxb18En5ufut2VAixa/jkJz+JH/qhH8JXfuVXYnh42Pz7jne8A//3//5fjI2Nbeh7NTU1ob29HY2KBK0QQtwAFKX+/GToNrrX+ItzgB3WOcc3qQdCCLFWaI31hS98wVhlVXnOc56DT3/60+jo6MCLX/xi/Omf/unSNi7rc3mfXLx40fz/+9//fjz3uc/F2972Nhw/fty8XhWmLvCxf/u3f1tKOeB7ffVXfzU+8YlP1Nl1fc3XfA0+9alPmd/596961atw11134Zu+6Zvw13/913X7/b73vc+I7wceeAAf+9jHsBVoDUwIIW4Eb5WWlMwvcIuAxRhByN+VS5u6a0KI3cnrXvc6vOc978Hf/d3f4YUvfCGe//zn46u+6qtw5MiRG36Nhx56yIhTCtXZ2Vn87d/+Lb7iK77CbPvHf/xHdHZ24r777sPnP//5JQutr//6rzd/9+pXv9o89vDDD2NmZsYI6ImJCbzxjW/Ej/zIjxjhy20/9VM/ha6uLtx///346Ec/iv/5P/8n3vWud6G/vx8/93M/h61AEVohhLgREikgHt6W0YcHZNoAN1y4Ws2Nu4wnhNg+3vzmN+Pd7363EYZ/8id/gh/8wR9cET29Ht/93d+N/fv348CBA/jGb/xGI1QZcSWMrH7DN3zDiiYJ/Lt/+Zd/WSo+499RUDc3N5v9YPT1O7/zOzEyMoJXvOIV+NZv/Vb84R/+oflbbud7fu3Xfi1uu+02k/+7FUjQCiHEDWA1tcMZvi18W2s37Ka28G3pFlgUu0IIsQ6++Zu/GR/5yEdMcRiLxNge9u1vfzsef/zxG3r+0NDQ0v9TZM7NzeGRRx4xLWz/+Z//GS972ctWPOeee+5BT08P/umf/sn8/jd/8zdLf8cWtYzsMvWh+vPhD38YZ8+eNdtPnTplhGwVRpO3oguaUg6EEOJGO9n0H4IVixtLLuQXACcBp/8gbDoZpDOAdzvcq2eAYs7k01rtvXD6DsJOprd794UQDcbTTz+NP/uzPzPL+YQ5s8xXfelLX4qv+7qvq8uFreK6K1Oeksnk0v9TWFLUMuJ69epVdHd3mzzYMChg+XeMwk5PTxvLsOp7cD+YdlBLLHZNUlYjwGHbdmWElmFvJizX/jCcTp588kl8y7d8C+6++26Tw7F8JvKXf/mXeMlLXmK2MyQ/NaWiCyHE5mKnMogN34LEXV+L+L0vRfzel8A5ci+c5jZYThxOzzDix+5H7JavQOyWBxDbfwfsdPN277YQogGhcPz93/99o4dqSSQSSKVSJvc1Ho9jcXFxaRttva4H0wkYeWVeblh0dnnaAUUtc2fT6WBiToFL2zD+W/35+7//e/zFX/yF2c4I8mOPPbb0OixOY1R4VwvakydPmpnCZz/72aUf5lpks1m84Q1vMMnFrN5jOPsHfuAHzOPk0UcfNeH2t7zlLSb5mAPF6j0hhNgK7KZWOG3dcJo7VvQgtxJps51C1trj/dmFEOvnjjvuMFHRN73pTUYsUhiyAOtnf/ZnUSwWTZSWDgUf//jH8eyzzxqHg9/7vd+77uvSrYCWX9cTtEwb6O3tNekEzLOtwmAjg4y/8Ru/YdIMuG+//uu/jsHBQbOdubUsCqMQ5n5Rry2/Tm4G23q1ZZ7FsWPHTJ5G9ae1tRWf+cxnTIj8J37iJ3D48GEzGPRH+6u/+ivzvOrgvvKVr8Stt96KX/mVXzGzjRuZmQghhBBCNAK/+Zu/aYquaINF3cPgHgu1qINYoPXDP/zDRje96lWvMg0X6Fl7PRjh5Qo3C82ooVaDgtdxHCOCq1C4fvCDHzT5ty9/+cvNPjItgrm+hPvL1fZf+IVfwGtf+1q84AUvMPu4q3NoKWhpQbEcJivTQqJadcd/7733XjMz4UHj9u///u9f+vuBgQEzwHycnTSEEEIIIRodLvPTHos/YbDZwh/90R/VPVaNunLbM888E/q8X/7lX17x2Fvf+tbQx8Iep3ajUI3ie77ne8xPFa6671pBy4RhVsoxzeC3f/u3Ta4Ifc+o6sfHx1d4rNHf7MSJE+b/GSpnGHz59tHR0TXvR1gC9UZRfe3NfI9GRWMTjsYlGo1NNBqbaDQ20Whstn9s+PrUQ9WfnY5f2ceN3tfq5+d4LB/zGz0G2yZoL1++bCwjGPpmuJq5IcyfzefzS4/Xwt+ZM0L4N6ttXwu1icubxVa8R6OisQlH4xKNxiYajU00GptoNDbbOzZ0AKDuqe0GttPJ5XIb+nqFQgGlUsk4O6yXbRO09EVjAnNbW5tJKWDyMQ/mf/7P/xnPe97zVohT/s6qPsL82rDt1Qq8tcCEauaHbAacVfDLsJnv0ahobMLRuESjsYlGYxONxiYajc32jw0DdHQMoH6papydjO/7Rsxyf5c3Y7gZWDRGxwauzi8fh+qx2NE5tO3t9d1zWABGlc7iMLZWq4W/V9MM+vr6QrfzeWuFJ+pmf5G34j0aFY1NOBqXaDQ20WhsotHYRKOx2b6x4WtTGFZ/GgVrg/e3+no3M97b5nLA6rgHHnigLmz91FNPGZHLgrAvf/nLdbka7EVMz1nCfx988MGl5125csX8VLcLIYQQQoi9w7YJWnrLMnXgv/yX/4LTp08b2y3ab33f932fKQ6jtywtKOhVy38pfKs+aN/+7d+OP//zP8fHPvYxk29Bey96tcnhQAghhBBi77Ftgpb+af/jf/wP0+GLncDoNfut3/qtRtByG50PGIWt2nR96EMfWuoFTDH88z//83j/+99vxC3zcN/5zndu10cRQgghhBDbyLbm0LI9Gtu6hcHewp/85Ccjn0uhyx8hhBBCCLG3UV9GIYQQQgjR0EjQCiGEEEKIm4IuVT/90z+N+++/H1/1VV+F3/u938OeSTkQQgghhBAbS7HsI1sASi4Qd4BMEkjENtcWjIX9jz/+OP7wD//QNM/6yZ/8SQwODppC/61AglYIIYQQYpewkPdxctTHQv7aY80p4Eg//90cUZvNZo3z1O/8zu/gjjvuMD8nTpzAH//xH2+ZoFXKgRBCCCHELonMnlwmZgl/5+PcvhnQQrVcLhsXqirsKUCXqq1q6StBK4QQQgixC8gWAvEaBh/n9s1gfHwcHR0dSCQSS491d3ebvNqZmRlsBRK0QgghhBC7gJJ7c9vXC5tf1YpZUv29WCxiK5CgFUIIIYTYBbAA7Ga2rxd2fl0uXKu/p1IpbAUStEIIIYQQu4BMMigAC4OPc/tm0NfXh+npaZNHW5uGQDHb2tqKrUCCVgghhBBiF5CIWTjSb60QtYHLgbVp1l233XYbYrEYHn744aXHHnzwQRw/fhy2vTVSU7ZdQgghhBC7hOaUhduHsaU+tOl0Gq985Svxjne8A7/0S7+EsbEx01jhne98J7YKCVohhBBCiF1EIsZo7Na+59ve9jYjaL/7u78bzc3NeOtb34qv+7qv27L3l6AVQgghhBA3HaV917veZX62A+XQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCbAjFYhEvf/nL8a//+q/YStT6VgghhBBiF+GXivBz8/DLRVixBKx0C6x4YtPft1Ao4Md+7Mdw4sQJbDUStEIIIYQQuwQvOwf33BNG0FaxMi1w9t8BO9O6ae978uRJI2Z938d2oJQDIYQQQohdEpl1l4lZ83h2Hu75J8z2zeKLX/wiHnjgAXz0ox/FdqAIrRBCCCHELsBnmsEyMbu0LRtss+Jdm/Ler33ta7GdKEIrhBBCCLEL8MvFm9reyEjQCiGEEELsAqxY4qa2NzIStEIIIYQQuwCLbgaZlvBtmRazfbciQSuEEEIIsQuw4gnjZrBc1FZdDrbCumu7UFGYEEIIIcQuwc60wjp837b40G4nErRCCCGEELsIK57YNDeDnYoErRBCCCGE2DCeeeYZbDXKoRVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQohtxPd97GX8Dfj8ErRCCCGEENtAPB43/2azWexlspXPXx2P9SDbLiGEEEKIbcBxHLS3t2NsbMz8nslkYFkWdnIktVAowLbtDdlPvh7FLD8/x4HjsV4kaIUQQgghton+/n7zb1XU7mR830epVDKR1I0U3hSz1XFYLxK0QgghhBDbBIXhwMAAent7jVjcybiui6effhpHjhy5qWhqLRTHG/FaErRCCCGEENsMRd1GicTNFLQklUrtuH1VUZgQQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0OwYQfuGN7wBP/VTP7X0+5NPPolv+ZZvwd13341Xv/rVePzxx+v+/i//8i/xkpe8xGx/85vfjKmpqW3YayGEEEIIsd3sCEH76U9/Gv/0T/+09Hs2mzUC9/7778ef/umf4jnPeQ5+4Ad+wDxOHn30Ubz97W/HW97yFnz0ox/F3Nwc3va2t23jJxBCCCGEEHtW0M7MzOBXfuVXcPz48aXHPvOZzyCZTOInfuIncPjwYSNem5qa8Fd/9Vdm+4c//GF8wzd8A175ylfi1ltvNc+nIL5w4cI2fhIhhBBCCLEnBe273vUuvOIVr8CRI0eWHnvkkUdw3333wbIs8zv/vffee/Hwww8vbWf0tsrAwAAGBwfN40IIIYQQYm8R2843//znP49/+7d/w1/8xV/gHe94x9Lj4+PjdQKXdHV14cSJE+b/x8bG0Nvbu2L76OjomvfBdd117/+NvvZmvkejorEJR+MSjcYmGo1NNBqbaDQ20Whsds643Oh7bZugLRQK+Nmf/Vn8zM/8DFKpVN22XC6HRCJR9xh/LxaL5v/z+fyq29fCY489tq7932nv0ahobMLRuESjsYlGYxONxiYajU00GpvGGZdtE7Tve9/7cOedd+Krv/qrV2xj/uxyccrfq8I3ans6nV7zfjB313EcbNasggd9M9+jUdHYhKNxiUZjE43GJhqNTTQam2g0NjtnXKrvuWMFLZ0NJiYmjIMBqQrUv/7rv8bLX/5ys60W/l5NM+jr6wvd3tPTs+b94AHZ7IOyFe/RqGhswtG4RKOxiUZjE43GJhqNTTQam8YZl20TtH/0R3+Ecrm89Puv/uqvmn9//Md/HF/60pfwO7/zO/B93xSE8d+HHnoIb3zjG83f0Hv2wQcfxKte9Srz+5UrV8wPHxdCCCGEEHuLbRO0Q0NDdb/TlouMjIyYAq9f+7Vfwy/+4i/i277t2/CRj3zE5NXSqot8+7d/O77ru74L99xzjwl78+9e9KIXYd++fdvyWYQQQgghxB627QqjubkZv/3bv70UhaUd14c+9CFkMhmznWkKP//zP4/3v//9Rty2tbXhne9853bvthBCCCGE2Gu2XbX88i//ct3vd911Fz75yU9G/j2FbjXlQAghhBBC7F12ZIRWCCGEEEKIG0WCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0GyroD137hy+93u/F895znPwohe9CL/7u7+7tO3ChQv4nu/5Htxzzz142ctehs9+9rN1z/3c5z6Hl7/85bj77rvxute9zvy9EEIIIYTYe2yboPU8D294wxvQ0dGBT37yk/i5n/s5fPCDH8Rf/MVfwPd9vPnNb0Z3dzc+8YlP4BWveAXe8pa34PLly+a5/JfbX/WqV+HjH/84Ojs78aY3vck8TwghhBBC7C1i2/XGExMTuO222/COd7wDzc3NOHDgAL7yK78SDz74oBGyjLh+5CMfQSaTweHDh/H5z3/eiNu3vvWt+NjHPoY777wTr3/9681rvfOd78QLXvACfPGLX8QDDzywXR9JCCGEEELspQhtb28vfvM3f9OIWUZWKWS/9KUv4XnPex4eeeQR3H777UbMVrnvvvvw8MMPm//n9vvvv39pWzqdxh133LG0XQghhBBC7B22LUJby4tf/GKTRvC1X/u1eOlLX4pf+qVfMoK3lq6uLoyOjpr/Hx8fX3X7WnBd9yb3/vqvvZnv0ahobMLRuESjsYlGYxONxiYajU00GpudMy43+l47QtC+5z3vMSkITD9g+kAul0Mikaj7G/5eLBbN/19v+1p47LHHbnLvd8Z7NCoam3A0LtFobKLR2ESjsYlGYxONxqZxxmVHCNrjx4+bfwuFAn78x38cr371q41orYViNZVKmf9PJpMrxCt/b21tXdd7O46DzZpV8KBv5ns0KhqbcDQu0WhsotHYRKOxiUZjE43GZueMS/U9d3RRGHNeX/KSlyw9duTIEZRKJfT09OD06dMr/r6aZtDX12d+DysyWys8IJt9ULbiPRoVjU04GpdoNDbRaGyi0dhEo7GJRmPTOOOybUVhFy9eNFZcV69eXXrs8ccfNxZcLAB74oknkM/nl7axaIyes4T/8vcqjOY++eSTS9uFEEIIIcTeYdsELcPVdCb46Z/+aZw8eRL/9E//hHe/+9144xvfaJwOBgYG8La3vQ0nTpzAhz70ITz66KN4zWteY57LlISHHnrIPM7t/Lvh4WFZdgkhhBBC7EG2TdAyVP2BD3zAWG5967d+K97+9rfju77ru0zXr+o2uhmwecKnPvUpvP/978fg4KB5LsXre9/7XuNLS5E7MzNjtluWtV0fRwghhBBC7MWiMObCvu997wvdNjIygg9/+MORz33hC19ofoQQQgghxN5m2yK0QgghhBBCbAQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIURDI0ErhBBCCCEaGglaIYQQQgjR0EjQCiGEEEKIhkaCVgghhBBCNDQStEIIIYQQoqGRoBVCCCGEEA2NBK0QQgghhGhoJGiFEEIIIcTeFLQPPvggfvAHfxCveMUrcOXKFXzoQx/Cpz/96Y3dOyGEEEIIITZD0P7N3/wN3vCGN2BoaAhnzpxBuVxGLBbDT/3UT+F//a//tfF7KUSD4ZeK8It5+J5X93ih5GNm0cfEvI/5nA/X82/8Nd1S8JpueQ3PKcNbmIE7cxXe3CT8UqF+2+JsZduEeW0hhNhofN9HtuBjat7H5Hzw/3xMiI0ktp4nve9978M73vEOfNM3fRM+8pGPmMde//rXo6enB+95z3vw2te+dkN3UohGwSvk4M9chTt5CfBcWE3tcHr2mX/ncsDJUR+5YvC3FoCeNmB/N5CK87dw/HLJiFFv/Dz8Yg5WMgO7Zz/sli5YseivsFfIwr30LPyZcb5K8J6pZjj7bwcSKbhXTsGfusy7TfCEZAax/beZ1xVCiI2Ak/bxOR9nx4GyGzzm2MBIN9DbBsSc6GufEJsuaM+dO4d77rlnxeN33XUXrl69up6XFKLhYYTTPf8k/PnJmsdGUZ4dh3Xgbjw70YlCTXCVMnJslhd3H4d6ActaeWH3PRfu2Hl4o6euPVYqwF2YBoaOwe4diX4eBevMWP3j+QWUL5+AnWqGT9FdSyGL8ulHETv2XNjp5pscDSGEAOaynMjXP+Z6wOkxIBkHulq2a8/EbmNdKQdHjhzBP//zP694/JOf/KTZJsRehMv3tWL22gYXhUun0JwITxWgqM1eywSow88vwrt6JnSbe+W0Eaihz8stwp8On1zayQzcsbPhb8i0BoplIYS4STzPx+Xp6NQCbnNdpR6IbYzQvu1tb8Mb3/hGfOELX0CpVMJv/dZvmajt448/jg9+8IMbtGtCNBbebH00tJby3CzaOvKYxMrIJ6MV5fpU2zpBCz9io1eGX8gC6ZAQh1uMfh6THZhLm8yEv2cuXCQLIcRa4HWtmmIVBreVPMBxtnKvxG5lXRHa+++/H3/1V3+Fw4cP48UvfjFmZmZMCsJnPvMZfOVXfuXG76UQDUF0Lpi9yjfNtoKcsg19Tye+yv74le0RrxghdIUQYi3wupZKRG9nykFM5qFiOyO0b3rTm/BjP/Zj+KEf+qGN2g8hGh67vRcui6xCSLZ14LKbCt3GHLJMxEXfSjUBtmPSFlbgxCLFJ4u/rNYu+HMToYVrds8++NOjIR/CgdXSEb4zQgixBhzbwkA7jLNLGAPtlorCxIaxrrnRQw89ZGy6hBDXsJvaYLX2hGxwEB86hN6OOOLLltbaM8D+Lgs2w7QhGFeC/kOh25yBI4HgDXue48AZOmbcFeqIJxHrPwhn4DCslu76bbE4nJE7YYWlMAghxDpo4zWuh0Wv1x7j/w93AR2qPRUbyLpUKW25fuRHfgTf9m3fhsHBQSSTybrtz33uczdq/4RoGKx4Es7+W+HPdsObuATfK8Nu7oTdPQi7qR2dAI7vB7LFwL6GS3FNCSAei45QWLYNu3sfkGqCN3YBfimw7TJWYM0doQ4HVehUYB26B35u3th9UbBaqRbYqSCqax04Dj8/H+ThOnFY6WbYEQJZCCHWAyOwwx1ARxOQKwTuLlyRyiSDCK4Q2ypoP/CBD5h/f+ZnfmbFNt5gn3rqqZvfMyEaEDuRBnr2we7sZ4kvEEvUic5M0jIX8rVAr1mnvTfwh/XKQaoB0xBu5LnxBKx4uK+sFY/DincCLZTaQgixOXAFqiUF8yPEjhK0Tz/99MbviRC7CItFVxtcucs0gs0oB/Z8H/YqkV4hGhl2pGrKqNBRiN3OuhNh2e52cnISrusuXTSKxaKJzr7sZS/byH0UQmwCC/mgDeXMItMefPS1WWjNAHEVaYhdgEcv5rlxeNNX0ZfPw59ph9/SASuhMKEQu5F1Cdq/+7u/w3/9r//V2HUth+1vJWiF2NnMZn08ddGv87+dWvAx1Ans61I7StHYeNl5lE8/DBRzJthSnp2D6+Xht/chtu9WiVohdiHrcjn4tV/7Nfz7f//v8elPfxqtra34yEc+YporDA0N4Yd/+Ic3fi+FEBtG2WVf9XoxW+XSFLAY0bVMiEbA9z244+eMmF2xbXYM3sLKQIwQYo8K2gsXLuD7vu/7cOjQIdx5550YHx/HC1/4Qvzsz/4sfv/3f3/j91IIsWGwO8/8ynv9EtMRnpFCNAJ+IQd/Jrprnzd5yURthRC7i3UJWkZlc7ngjnjw4MGlIjEK3IsXL27sHgohNpTr3crZileIxsVnmDZ6M91HhBC7jnUJWkZjf+7nfg4nT57EAw88gD//8z/HE088gY9+9KPo7e3d+L0UQmwYyRiQiu58i/aM8mdF42LFUysbitRgd/Su6t8shNhDgvbtb387RkZG8Pjjj+MlL3kJ7r77brzmNa/BH//xH+Mnf/InN34vhRAbRjJuYX93+A2dLgfNqpcRDYzlxOD0HQhaRi8nkTEtoYUQe1jQfsd3fAfm5ubM/zc3N+Od73wnvv7rv97MdH/1V38VX/rSl/CFL3wBL37xizdzf4UQG0BXC3DbUGB2zmY9iVjQivJov2UErxCNjNXSidihe2CxGYntmAYjdtcwYofvhp1Sv1Uh9rRt14MPPohSqVT32POf/3yTbrBv3z4jcoUQjQFbTlLUMiJbKgeiNpWQkBW7AwZaGIll6oFXyKJwdQzW8Ajs2Lqt14UQuzHloIoqRYVobNhEge14JWbFbsR010tmMDo1o7xZIXY5NyVohRBCCCGE2G4kaIUQQgghREOzpoSi//N//k9drqznefjbv/1bdHZ21v3dK1/5yo3bQyGEEEIIITZC0A4ODuL3fu/36h7r6urChz/84brHmKckQSv2Mr7nwS9k+T+w4knzI8T18EtF+KU8r6Kwkpkg/3Mz389zK+epr/NUCLF3BO0//MM/bO6eCLEL8LLzcEdPw58dN4IWySY4A4dgt/UYf0whwiZA3twEvCun4OfmGRWA1doNp/8Q7Ka2TXlPLzsHd/TMtfM01Qyn/6DOUyFEw6IcWiE2CC+/iPLpR+DPXA1EAikswj37GDwKByFC8Ocn4Z55JBCz5gHfCM3yqS+bCdKWnKf5BZ2nQoiGRoJWiA3CX5gBitnQbe6V0/CLXE4W4hq+W4I7etaI2BWUi5siMP35KaCYC93mMWpbKm74ewohxGYjQSvEBsFl40gKixIKYgV+sQg/Nxe9fW7cpCRsJN78ZPT75RcqebxCCNFYSNAKsUFYscQqG23A1tdNLIMt2uxVir+chMmp3UgsJ77KRjv4EUKIBkNXLiE2CLu9N3KbxWKbZHpL90fsfKxEGnZHf+R2u2twwztcrfZ+VnuvcVgQQohGQ4JWiA3CamqF3X9w5YZE2lSQW6tF4sSehGLV7t4HK92yclvXEOzm9s05T3sPrNyQyMDp43mq24IQovGQP4sQG7iU6/QdgN3cCW9mDH65CLu1C1ZzB+xU03bvntih2Okm4NA98BemgyIwx4Hd3gc70wYrvkoay82cpwMHzbnpzVyFXy7pPBVCNDwStEJssFiwWruMQBDiRrGZjpJMw+ka3JL303kqhNhtaG1JCCGEEEI0NIrQij2N77rw6clpBQU6ynO9eYplH4VS8P+pBBB3bqyoKWgZTH9UH1YiuXo1vthUfDZ34LFg++ZYYlNSH4QQYiORoBV7Fm9+Gu7VM4HRPNuNtnSaopjNKMTZKyJoehE4O+4jWwgea04BIz1AeyYogFq1FevVc0utWK2mdjj9B2C1dG14lb9YHS+fhTdxAd7UZcAtw0o1m2JHu7VbbXGFEDsWpRyIPYm3MIPy6S/DZzMEtv/03GvtRhdnt3v3GpLZLPDUpWtilizkgacv+Zhfxavfyy0ErVinrwBe2RwPf2EK5VMPB5MNsWWwm5179nF4Y+eAcilow5ubh3vmUXjTV7d794QQIhIJWrHn4NK2O3HRRJ9W4JbgTV0x0UZx43iejyszfmgHV9cDrppt4WNqJhVhrVh9D+7Vs/DDjpPYFDiZ87Mzodvc0dPwIlrmCiHEdiNBK/Ye5eKqkT/TwpbRKXHDlMrA/CpaZy4HlN2Vj1Pk0joqCn9xBn6pJuQrNhVah0VCMVvUsRBC7EwkaMXegzmZq5jHm8IwtiQVNwyH01nlahJbbUjt67RiZcWe2BqulyOrfGYhxA5FglbsOax4EnZntN+n3TWkCvs1Eo9Z6F+llq6/zYIT4nYQdMpa5Vi096ll8Baymi8tC/WslNriCiF2JhK0Yk9id/TByrSteJzdkqy2nm3Zp0anq8VCZ/PKx3tagY6Qx6vYHPP2/pUbkk2we/fJ5WALsVIt4e2bY3E4Q0c10RNC7Fi2VdBevXoVP/iDP4jnPe95+Oqv/mq8853vRKEQ5GhduHAB3/M934N77rkHL3vZy/DZz3627rmf+9zn8PKXvxx33303Xve615m/F+JGYYtP5+BxOCN3BNZQLd1wRu6Ec+DOoGuTWDOpuIUj/RZuH7Yw0A4MdAB3DFs41GshEbNWjZjH9t0C5+DdZjJh7NP23YbY4Xtgp1u29DPsdaxYzLRvdg7fC6tjIGiHO3AEsSP3mYmHEELsVLbNVJDFIBSzra2t+OM//mPMzs7ip3/6p2HbNn7iJ34Cb37zm3Hs2DF84hOfwN/93d/hLW95Cz7zmc9gcHAQly9fNtvf+ta3GiH8/ve/H29605vwqU99StEcccPYyQyQzMDpGtruXdk1ULgyStvZvLbvIUWt09FnfsT2wiis09ZtfoQQolHYNkF7+vRpPPzww/iXf/kXdHcHF04K3He96134mq/5GhNx/chHPoJMJoPDhw/j85//vBG3FLEf+9jHcOedd+L1r3+9eR4juy94wQvwxS9+EQ888MB2fSQhhBBCCLGXUg56enrwu7/7u0titsrCwgIeeeQR3H777UbMVrnvvvuMACbcfv/99y9tS6fTuOOOO5a2CyGEEEKIvcO2RWiZasB0gSqe5+HDH/4wvuIrvgLj4+Po7e2t+/uuri6Mjo6a/7/e9rXguiHmmBtE9bU38z0aFY1NOBqXaDQ20WhsotHYRKOxiUZjs3PG5Ubfa8c05n73u9+NJ598Eh//+MfxB3/wB0gkEnXb+XuxWDT/n8vlVt2+Fh577LGb3POd8R6NisYmHI1LNBqbaDQ20WhsotHYRKOxaZxxie0UMfuHf/iH+I3f+A1TCJZMJjEzU99+kWI1lUqZ/+f25eKVvzPqu1aOHz8Ox3GwWbMKHvTNfI9GRWMTjsYlGo1NNBqbaDQ20WhsotHY7Jxxqb7njhe0v/ALv4D//b//txG1L33pS81jfX19OHnyZN3fTUxMLKUZcDt/X779tttuW/P784Bs9kHZivdoVDQ24WhcotHYRKOxiUZjE43GJhqNTeOMy7b60L7vfe8zTga//uu/jm/8xm9cepzesk888QTy+fzSYw8++KB5vLqdv1dhCgLTFarbhRBCCCHE3mHbBO2pU6fwgQ98AN///d9vHAxY6FX9YaOFgYEBvO1tb8OJEyfwoQ99CI8++ihe85rXmOe++tWvxkMPPWQe53b+3fDwsCy7hBBCCCH2INsmaP/+7//e5EV88IMfxFd91VfV/TCMTbFLcfuqV73KNExg8wQ2VSAUr+9973uNLy1FLvNtuV1NFYQQQggh9h7blkP7hje8wfxEMTIyYmy8onjhC19ofoQQQgghxN5mW3NohRBCCCGEuFkkaIUQQgghREMjQSuEEEIIIRoaCVohhBBCCNHQSNAKIYQQQoiGRoJWCCGEEEI0NBK0QgghhBCioZGgFUIIIYQQDY0ErRBCCCGEaGgkaIUQQgghREMjQSuEEEIIIRoaCVohhBBCCNHQxLZ7B4QQ4mbwS0X4+QX4ngsrloSVboZla66+HfjlEvz8Iny3BCsWh5VqhuXoNiOE2Hx0pRFCNCzewjTc80/Dz88HD1g27K4hOP0HYSVS2717ewovNw/3wjPwF6Yqj1iw2rrhDB2DnWra5r0TQux2FMYQQjQkXn4B5dOPXBOzxPfgTVyAO3Yevu9v5+7tKfxSAe65J2vErHkU/uw43IvPmoitEEJsJhK0QoiGxF+YBcrF0G3e5EWz9C22Bj+3AD87G75tbgJ+TsdCCLG5SNAKIRoSP1cTmV2OWwbKigpuFX4xv9pWE8EVQojNRIJWCNGQWIn0KhttQMVIW0csvupmFogJIcRmIkErhGhIrOYOwHbCt7X1wkpltnyf9ip0lkBEEZ6VbjFuB0IIsZlI0AohGhIr0wJn5M4VkVirqQPOwGFYEWJ3t+I42/d57WQGMR6LeLJ+Q7IJzv7bYcUT27VrQog9gtbkhBANiWVZsNsZiW2Cn50DWEmfaoLNiOByYbXDKbk+sgVgIe/DtoDmlIWmJGDzl1Xw3XJQkLU4i5EmB8jOws+0wHK2fonfbulE7Ohzg9zmUh5IpE101k6ukhoibgovn4Wfm4NfyJkUHE7yZJEm9ioStFsM7Wv8fBbwPCCeWHHxKZR85Eu8WQPpOBCPrX5DE8L3vaCiv1xmmM4IvI2ITuaKPorl4FzMJICYY+1IUWuWu/nToPA7f2bMx0RNjZsFHyM9QH979Lj75SLcq+fgXT1rzoHy7BzKc5fhdO+DM3hkW6KiNtM8lOqxJXgLMyiffRSoLciLJxE7cNxMLoTYa0jQbiHe4izcSyfgL0ybyl/EEnD6RowRvGfHzQ3t/ISPQqU4uykFHOgBOpp2npAQOwOvkDOCxpu6DHiuKYay2vvgDBxad6Sm7PoYm/NxcRJG0JKWNHCwB2jN6FzcaMZm68UsoYPu2fHgGtARcRi9+Wl4V8+sfHzyIqymVjjdw5u0x2InuEqUzz9ZL2ZJqYDyucdNpFyRcbHXUA7tFuHlF1E+/XDFeLxi+M4Iy6UT8KauYC4LnLhyTcySxTzw9CUf8zkZxIvw5Wb3yknTSMCIWfOgB3/6CtwLT5mWsOthct7H6avXxCyZzwFPXfKxmNe5uJEUij5Gw+1bDVdnw8fbd1144xcin8dtfkm2ZbsVsyKTXwjfWMybVtBC7DUkaLcIE5WN8GIsj55FbjEbus31gIl5iQgRflPzp0fDt81PreumxuXvC5Ph20ouMJPVubiRuD5Qqpk4LKdQBLywjmeeC78c7e3KdATfW+WFRUOzovPa8lNEHsxiDyJBu4X5TpHbigXYq7SGnM1S2EpIiHp8Ft6s0t7VL4RPklaDopU53Kudi2LjiDtAapVUV6Z62ExiXo4TMwVXUVjJJnm/7mJM0aPPiUsJfnYB3uIMvOy8+Z2PWxEWakLsZiRot4jVLjAWTeDt6EORiPGmtkk7JhoWy75OCvw6Kt15njmrXBV4LoqNg0Wfw51W5LHobg3fZtk2nO6hoGJv5VaTm2+pscSuxRRCZlrhL87AL+UCh49S3vwO5s7K6UDsQSRotwi7tcvcaMJwOnqAZHRlcF+bZaq5hajFmNVHnTexRHDTWyPpBNDTGr29J0JgifXT2Qwc7KWbwbXHUnHglkELLasE2ozfrvF+rfkjFpruvw2Wqtx3NcyPt5vbYXcNBl3xiLGx6zdWdqzPEGKvoSn8FmFlWuEM3wL30jN1y8RcNqQJfLvjoKPZx/SytMehTlaWb/3+ip2PlUgitv92lM88Wn8Ds2OIjdyxLpcDTpwGO4HFAosR67fRcaNZK5kbDm25BjsCN4NC1bIvASTjq08eTJS2cwBWU7vJp7anpxHrG4DTwBZm4sbwC4vwxs8DTe2IHbo7uKdYNrz8Aryx87Ca2oBVUlKE2I1I0G4R9AW1u4fMhcYU7JSL5kZEoUt7FeqEo33AQjswl/VNBkJbJjBX34n+n2JnYMzsj90Pf2HWFIFZyYw5r+zM+m9mmYSFWwdp8g/M5XwTOWxLW8ZCylHuy6bAiUQmCfOzVnj9cGMJnD15DvfsO7QZuyd2GtWaCubOMs1gxXZvy3dJiO1GgnaLRa2ZOfMnhETcQmecS5ASDeLGsZl6wJ8NhNHBZBzoatG5KMROw2KeLFMN/BDhymYjyqEVexDl0AohhBANlj9v946EbrO790nQij2JIrRCNDjs7JUtBJZbTA/gsnVcaSqbBpsaML3DLxWMkwDFRbXNrE9/2Fxlm11pQ7xFFkqxmC7newWTP907AiuRhjt2NvA4jyfg9IzA7uiTw4XYk+isF6KByRZ8nBnzMb1Y7116uI8FXBK1G41XyAbtq2fGltzsTWHn/tuBeBLulVPw2Ya4WviZbEJs/20m13mzDPaNgJ6fwr6UZ3Iq/Uyr8aBlJzk/Nx94YHueSXdibrXxMN0jcILBzlm9Ha3wV/FsbkQ4iXJ6hmG395jzgDZ+8p8VexkJWiEaODK7XMwSuhOcGPVxxzB9YyVqN1IcGcE6c7X+8dw8ypdOwk5l4E9eqn9SYdG4UMSO3g97g90HaN3kjp421e4Ua+7sHMoLY7A7B+EMHIE3dRne6Om6NlJeazecfbeZQrLdDMfDX5iBO3YO3sIUMgtZIO7C6x7e8OOw3XCCspcmKUJEoRxaIRoUphksF7NVFvPBj9g4/Fx0q2E7mQqWfsNgG9pVOgWuF29+MrBuWgb30Z+fgDd6akVPVH9uwgjdvdBqvHzqIfizY6YNrFfIGXFbPv0IvHzEl0YI0dBI0ArRoBTd1bcXylu1J3sEt7hKq2EryGOMgDm3G53H601cDN+TTAu80bOR1k18HgXeboVj417l5w/5ghQWTXqGEGL3IUErRIMSv863N17TeUpsAKbQJiKFw1q91TCLdzYUFp9FdIPyLQdeMQd/WXR2Cbe8q31KfbaAXZiO3O5Nje66fFohhAStEA0L3QyiOnfRQ5aNEMTGYdwMTAvrlTDiaXcPhz+RbgctHRu7M7EYrHREj+JywbTatqotUZdhpTKwYoErw65ltVbh7FojhNh16JstRIMSj1k40mchnVwpZo8NWEhdp3WqWBu0QnKGjsHKLGuMEk8i1jcCZ/AorOVuBk4czsidxglhQ/fFsuF0DwXm+ssx4npfZMTY7jsIKx4dTW50GA23Wnsit9tsF7ya4BVCNCRyORCigWlOW7hzGFgsAIWSb1wN2C45ldANezNghbx1+B54uXkjHOn9SbFqJzNmu3XgrsCjloVHsTisdHPQyW0TsJo74Bw8bmzEUC10SqTgDB2F3dYF69BdcC8+ey1/N56E038Idms3dr1Ha98IygtTK/KaGWHfLAs1IcT2IkErRINTbVMbmd8pNhRaJDkRNkn0BrXincAWiCZGGZ32PtiZNnj5LKzpKcT6BuGkKuK6tRvW0Vb4hcWgmC2RWhLeux0704rY4XvhzY7Bm74KB3E4+48FQl9erULsSiRohRCigTECzYnj3Ikz6Bg+GCKwd3m+bARsIsEft3sfJk+fRlvnAGxHlZJC7FYkaMWOwat0PPKyc+YmzaVRi12PbqKIw1R7L87Cm500r2O395pimt2cQyi2D3dhxni98scs/3cOAk3tsPeoqNwR2A7mFuQ9K8RuR4JW7Ag8GqGffsSY0BOa6nhXzwRdjToH1yVqaaDunn0Cfnbm2mtOXIDdNQxn8MiejVyJzcGbnUDpyc8B+fmlx9zzT5qlbwwchh3TJEoIITYLuRyIbce08Lz4zJKYvbbBh3vh6XWb0nuTl5bEbP3jF42AFmKj8EoFlM49XidmDb4fdKzS+SaEEJuKBK3YdvxCFn52LmKjZ1IG1gp9Qb2pK9HbJy7JXF1sGH52Hn5US1nfhzczttW7JIQQewqlHIjtJ6xFZQ1RHZFWf5IHuO512ph6NBfFbscvFeCXS8ZQfjdWuXNiwkkRjycbBtCFYFvO4dUmSKu0xRXiZqBdX9kFWO8m72mxl5GgFdsPBQjbirIlZwgsDFsrpro70wqfXpRh21lwZu9uMUsRy8ig6WtPwReLw+4aNB2tdouwpV2VN34+iMa7ZVipJtj9B2G39ZhGCFvqNJBsAmiRFbZ9l3u/iq2nWPYxPufj8jRFLZCIAQMdPvraLONHLcReQykHYtsxIqR3JHxbph32OrosWezQ1DcS3gLTiRu3g5uJCNJY350ehTt5Gd7iDPwIMb5dmH2cvAT3/BMVkeWbHGXv6tkgL3kXRAz9Yh7u2ceNoIVbMp+R+dbu2ceM9+hWYje1Ibb/tsgGCHbz+lvf+p4LLzsLd/IK3KkrxgXE97yb2NvdQ9n1MZf1MTbrY2LeR7bg74lUIs/zcXHKx5mxQMySYhk4N84fRmx3/xgIsRxFaMW2Ywziu/eZiKk7di5YnrUdWB19cNimc51G6FZLF5wDd8G7cqpSWGYF3ZUGDxvj9fVAIcFooHvhGfjlQBRyv+2eYTgDh81yN2+ouWLFyz4WtKjdargE746eCd9GW6ncwvYszW8gRtiFFP0Rd/SUaUNrJ9Nbtj92737ELBvlC08B7CRmx+D07INNp46mdZ5v5SLcsfNmImJSZMwbOeZcY6R9K6PQO3Gp/ew4o5TXHos5wOE+C90t/q5ub7tYBK5E1BmOzQJ97UDr1p36QuwI9u7VUOwomCLg9B2Axcipyfd0YCUzN+VBa1pgdvSZ6JhfzJlorXnNmxAB/uIMymcfDVqblpjb68N34kZ48LWL7SMmcjIxD7ge0JQC9nUBHU2AY2/hDbaYr0Qto8Wg3dqFRsafn17985fywFYK2kQaNtvOdvTD53vzHGZb3Juw6/LmJuGNnl72oAv30rNAMgPnJlYaGhlOGq9M14tZwlzSE1d8k0vasosFXaEyYQ6DD+eLErRi7yFBK3YUJrdzgwOHG9ktyaU7wsIs4NcUnLkl+NlZlEbPYtzrw9XZax9gMQ88fcnHrYMWutcXpFsf1uoTgUbLH2auLKPsB7uaTfTTTzcHVTA7MKOK3amAtafJhOZAXz0Xud2buGgmJY12LDeCfAkYjTA/8XxgatFHUzKIZOYLFjr6DiNfstC0S4bqOl9v1n8KseeQoBViLdX09BOtFbNLWChlc7A85tKuVOTnJ320ZpiCsDVRWiuVAVLNQJiHLyPVTW1oBEwu8OxYkPfLnNnZOZSn2oLmGJ39K6OXFaym9mAMGhjmZVfTWkK3c9WBTh57UNBy9YPR2Cg4kbwy45ucUtfzMTfnYyzr41CfbyaWdoOnI2QSQNwBSiFj4NhAWj1jxB5E8zgh1kBk3inzf50U8m64uMgWgqKNrdzP2PAtgXvEMpzBo7AY4WwA6E/Mwq862ytOLNgcY34K9tCxlU+KxeEMHYXV4J25rFgMViJ63ZgpLmHHdy9A0UZBFwVz1y9NBdHaKhR/J0Z9zOfQ8KQTFg71WViexcRf+TgFrxB7jb15NRRiHbDIhO4I7tXTLDNettU3rgqTuXARxYDQVseEuBwdO3K/iXD6CzMmn5RRTSvT1jDL1GwnG+VTzCX32NH7YKfvg8umBqUCrOZO2G3d6y7620nQqYOFZu6ZsMI3yxSc3UyOeaMLOlpUnZ8I/67F7PAJJPNOaXXVlmnsCC3pbgGScQuT8z4W8kAmCfS0WGhOB9cqIfYaO+JqWCwW8fKXvxz/+q//uvTYhQsX8D3f8z2455578LKXvQyf/exn657zuc99zjzn7rvvxute9zrz90JsNn6qGbEDx4F4jfMCXQ76DgAtXSj74UKxsxlIbUPUhNX1scEjiB+7H/GRO2C3dDVUZby/vJVsLWy44flGuMcPHEf86P2IDRzaFWK2Cj8bI+p1aQVODM6+W41jx16mv91Cf3u9Mx8js0f7KVqjn7dYCFJZGh2K1ta0hYO9No7vt3G4z0ZrhlFbiVmxN9l2QVsoFPCjP/qjOHHixNJjvNi8+c1vRnd3Nz7xiU/gFa94Bd7ylrfg8uWgtST/5fZXvepV+PjHP47Ozk686U1v2hUXKbGzcZpa4dOOafgYYofuQezg3YgdvAuIJZFMJzDYufI5vMnu67K21uVgl2AxDzgKphQ0kDhfd5S27wBitzwPzsF74PCcO/a8wLKrQaLsmwXz0Q/2Wrh7v2WKLm8ftnDXfiuIvq7yVeNyvCKYQuw+tvVucPLkSfzYj/3YCiH6hS98wURcP/KRjyCTyeDw4cP4/Oc/b8TtW9/6VnzsYx/DnXfeide//vXm79/5znfiBS94Ab74xS/igQce2KZPI/YCJje1/yC8xdlKdyrXpCHEejtgp9LYl/DRngmWNUvlIDLb3mQhk9QNdD2w41edB2vtNnY8a/DCrxuB4ov2X1hHg5HdDieJXGLnTy2DHUHTgeXwW9jbpu+iELuRbY3QVgXoRz/60brHH3nkEdx+++1GzFa577778PDDDy9tv//++5e2pdNp3HHHHUvbhdhsUUv/z/ihuxE/ei+cHgqrJrMt7ljobLZwy6CNO/fbGOy0JWZvArYvdg7cGURjrz0Kq3MAdve+bdwzsZPpaWWObX2glnm1R/qBlvX1aRFC7HC2NUL72te+NvTx8fFx9PbWG4Z3dXVhdHT0hravBZe2N5tE9bU38z0aFY1NOBqXEFp74BxpNj608blZOJ09xqXBp7OExsmg86YexwL2dwVFUuzat9BsobfLN3ZWXBHUMAXovIlGY7NzxuVG32tHJqDlcjkkEvUVNPydxWM3sn0tPPbYYze5tzvjPRoVjU04GpdrpFIp9LakESssAm4Zc9OTmB+fxMTMKpU/exSdN9HMhKQghNHalEFnUxJ2bi7oxpVuxVSuhNmFEE/nXYLOm2g0No0zLjtS0CaTSczM1FvVUKzyxlbdvly88vfW1rVXNx8/fhzOdTsOrX9WwYO+me/RqOzpsWHzBc8zLXOXF6fspHHxfQ+WWw7aEm1T8ZVPe7Spy3AvPWP+f35uHi2tLWhu6cTw7bcDq/i07iV20nnT0GNjurOdgTd2rUgZC1fR0jUI+8DtQGx3GbzqvIlGY7NzxqX6ng0paPv6+kzBWC0TExNLaQbczt+Xb7/tttvW/F48IJt9ULbiPRqVvTQ27HTlzU3AG78I3y2Z/FCbXqLNHSuE7XaPi7cwA880L5g21fR29xCstl7Yya0VkF5uDuVLzwa5kJUxMmO1OAN/7Dyc/betu2LddH7LB1Ff5uiyUcGNvpbH55VLpv2ulWzaED9Ynh9+sRB0ckuljcPBWtmK88bzfeQKgOsHzQ3oCdsI3MjYuPRsnriw4jzwWQDa3AGnexi7ke2+3uxkNDaNMy47UtDSW/ZDH/oQ8vn8UlT2wQcfNIVh1e38vQpTEJ588klj7SXETsQvlVC+fBI+GwBUHyvmUJ4dh3PwLlNktlNgB67yqS8vNTTgqqt78RlYsxOwRu6Aldi6qhrPrBOH2/F501dg9+1f3dor6nULWXhXz8Hj8eDndGKmna7duw/2KlFfv1SAN3EJ7vj5wAfXdmC198LpOwQ7HRQGrhXfc83ndK+cBphWwaI3iqfBw7B3mNdstuDjwqSPyfmgCxcF7UCnj/42a8vaOq+YJObmTUc5+iublsfplnVNMHzXNc06ovDGL8Bu64MVb+wOdELsVrbdhzaM5z3veRgYGMDb3vY2409Lcfvoo4/iNa95jdn+6le/Gg899JB5nNv5d8PDw7LsEhuOieJtgL+xz3y8GjF7bYMHl0K3trXrNuK75UBYhXTn8ucn4S3ObO3+FOv7lDqxmogA99H11v6a5ZIR6B4jcYw4N3UA8SS8sbPms3MMQp/HYqKx83CvnAzEbGUfGL1zzz9hxNV68Ocmg/a+RsyaR+AvcFLxMLzszskTLpZ90zqWTQuqLWXZTvb8OHB5emO+J2uBUfLymcfgnvoyvCunzDEtP/slI0o5SVj7C7qrfg/9chG+v4X9q4UQjS9oGcb+wAc+YNwM2DzhU5/6FN7//vdjcHDQbKd4fe9732t8aSlymW/L7TLLFhuFV8jBnbyE8skHUX723+COXzBRvXW/3vxU9Mb8AvzCzmgwz/3wF6Yjt3vTV7d0f2yKTeYblwomCpcs5wHuI0UnI8XriJb5jOgVcibdg1E5ikfzXj37zWc3aQhhz8svwGNkNmzb4oyJFK5LXNNnNywK7ZYqEeqdAdurzkecplemGb3dun2heGaE3V+cXjlBvPgM/MV1TAQY4V2lyxydNSxnd+XQCrGb2DEpB88880zd7yMjI/jwhz8c+fcvfOELzY8QmyJmzz1eJ+xc3jjZ9vbg3eteWl4ddbkLw2puN6KPEW4OkV8uB4KzmDPtX1dLD4jCKxVhpZqCtIpKVNE3uc3nTVtjvxThlsLo3SqRPz+3ALT1rGlf/HLBCOzI7fOT8L1DG5Kje7MsFqLPUQbKi2VgM74ZYfiFRZNyErEV3uw47Ja1pWtwjJkjW+YkYkUjDwtOzwisHZYzKITYgYJWiJ0CxU1olJIRuqnLsIeOrvk17ZZOUz0dSqrZFCRtNRRuJlqZXwDouJBpMVFP5m9Wo5bLsTv6bvp93cp69Y20AmbxnDN0FO7oGfjVKDcbW/QfDISuWza5k2sVLuWLTy+J2SU8D+WLzyDe3h/+xEqrWRMd5vJzuRS0n40ng/zNuuYPN7wzwetGCeVYwiyfMzodCF/LHCcTLdzi1rfx62hq2/YxlwWmFn0TrW1KAZ1NFppTm9Bqlgp6tcnFslSVtUygnAPH4V5+1qwEGBIpOINHYLWE9LXewPQJPzsPlAtAMgM73Qorkdy09xNiNyJBuwsIIljz8OYnTXIbL7w2b3pxXRDXVRgyGZLrWoFRIZ/OBGssjLJ4g+ocXJlHa9nBzXKLjxVvoO75J+uFuxODs/92IxbLp5koWZ8vaLV0wW5qX/d75os+phd9XOVqsA90t/joaraQXqWTmjc9Cn/6aiCk+0bgF4twYrFgvxem4HcNBm1h1wLdCWgHFrktPE+Sbga0CWMV/FJkl/+heMq0mWO8VqxEGnbnoMnfDYPd0JgfyoKkpSi+ZcHuOwSHBXHrcEJYL81pC7blL+XP1m1LBfm0z1xmLm3w2NQCcGnSx61D7J63wTvDyQO/gxF5y+s9Ty1+Hzv6YDe1wa+mGPEYbaK7B6PJ5XNPXMvL5mPskDdyJ+z0Rg+cELsXCdoGh1E2lzc83mSrjJ2F19YDZ/jWLbdZani41OivUlDCfE7fr2upufIlvOBmyL+LJ4xYZWV0bPAIvOb2Otsux9h2rV8krgfunzt6eknMUoCYz8OCsHNPIHbL8xA7ci/cyYvw62y7etbtcJAr+nj2il+Xg8mczKuzFDxAU5SoZYcYRigZNfd9LMzOobWt9VrEbz2FSLTFYqcxRsRqUz0qj9c3TK3Fh9M5AG92rF5IcamaYnsdUUh+Drt72ByLYELqBW9vO3D6DxuxbPJ2WZxoIpKWiTB7o6dgZZrhtN98xPxGaUoCh/stnBy9JloJnQ72d1s4caX+cULxy7+/awRIxYPx8Twf9g1E51eD1zWn9wBcRtqXE0vcdDTVc5LIc5JpAcnY5hWbeLkFlFkQ6JbqHmdEnt7L1sG717wCsSZ8r67F/HX/3Pfg5xaDCLhtm0me7jFipyBB2+Cw2KhOzFbwZ8fh0/Kn78C27FejwmVjq7UnyIcM297StWo0lYVBLPLxmYfnucZSyh44BLu124hB5ujZFCEUJ7zxriE3cmmJPRa7qcgcc1AZ9Sy7Qd4j/6UWS8aBmEPxOAmn7wCsptYgYgm7zqqomqrgLc6a/Q+sklgwE305mV6oF7NV2JZ0fM5HU0+4wLHbeuDOhBeiGXum+NoFtvGbjaWAZif4fEwh4L7z2HPyEXGD9vNZY9cVG751aVWEx5TH2OOYNc2gEG82Qp35phR6LWnLCMHVltx5PClqOYYeJxmcQLR0wmrtgnvx2aC6Pp8D3CCC5/O8SWbgjV0MzqstSj3gZ+hp9ZFJWCbSXigDzUmgLWOZFANGaMPgOcbofKEEjM36WCwAmaSP3lYLrWmsW9zaHQPme2SK6iqC0EwSh24xK1TXw7gyVFwNaidqs1kfc/MlxNzghC3ZKbS2JNCWuX7qhCkypFuFmcwmrzsB9LOzK8Ts0ra5KfNdtZrasNHwu+vNXIU3N4X+Qgn+XBf8lo5V02ZoPcjz36wmVNM9mP7DwEl7rxmbqDEVYiuQoG1gjH/lKr6J7sRF2J0DSj1YI1ze9iYv1S0BBhtiQUQ1QoTSBaF8+tEa+6WgMt498yhw4LiJ7pHgpnHjgpSCpjwzgdLVC3ALeTipFOL9BxBr7TJiaM14LkplDwu5+lI0CpJUHHDyOTiV5VfesOo/Yy6oImeUcgkLDkU7i2aYDuCW4BeCCCbFoQcHV2ejd4c2UAPtPpKVCF4tpulEumVl4RQjmwOHTQT8epibrOctFfRQONo9Q8F3Z5kIt3tX8bVl5N4tB+eGEcAJE4kPIt0WsrFWnLzkY7E2eGv5JqrZ2+pHiiFvZtzYfpl8WooAvsfYOVh0dsjPVyr2a44UBS7HmPvJCPYW5tLaloWWdCDUa5nPRUfKEzEKfODs+LUILkU/xe3hPqC//QaEIptOVH1/Kw0wOMmyOfFq6QoihpYdNCu5gdxTb3HOHEdvbtwcO37nmfqRRRNKM5NIj55CeSE4adNNLXAHjmDB6kJLZpX0mMVZFC+dMs/nORdLZ5AYPASnozdysmcaaUR/6mCytcFw8lU+84h5be5neXYOrpsF+pnGcjDymmIE8Oip+gdLBbhnH4N19H74lh00Y5mbqBtTpU2IrUKCtpHh8mQlahMKL1iMEm7lPu0C7ExrsOROWyDe8Bhtaek0UUt7lfQALs/XitlaWNRkom5rnFzw+BVHz2P2zOlruYsLBdhTj6Dt0FEkBg6sueDGs2PIuzH4WHmzzJeAdCo6uuVNXVkmZs1emrQXP9NmBI/xcq341Zp87v6DcJxVxo2fK0IPmeXMA3eZVQiX3ZooaJo6EBs4aITMatARwVucDgRoMQ+L+8cJXlMbHIrhZNO1BgmMNPUeCCJNUVFzRoMpTCgyqj/V98q04+Jcuk7M1i65M6pJIRiaMjR2rvKLB9RYw/kUqkashgxOJZ2Ff7MTvt+pVeYVHU0Us+HZIXycUVoWkIXBSLgR/FfZdCIbRK87BmD3jsBKpkz+qcfzjYWNHIu2XqD/AOxV8qopZsunHqrPWb161ljSxYZug3vmERNpreIuzsM9/QjitzwHXqozNKLs5haQe/ZhLM4Xrh2tQhaJhcfRcuw44t3BZHY5VmqV5X5OcNZTaLgK5ny79Gxw7vL+4XlIJoL3YNGq3dZtJpErnlfMw43I8+Z5ayYHXNVixLluTMcQO3yPRK3YEiRoG5lKZ5zI5XEuye6y3uNbKWrZFctEfphjmggq2a8X+ajCmzd/zL3PqnjNFgtrFrTlxQXMnj1rhFHMDlID+LplD5g/dxrtbd2INa2tKKpgZYCuYeDKWcSa20ykz3JLcOemjJjLxdsQtpce8zkno1cEkJtHmU0ZanKQaTvlZmdxcPhePJJtjRQ8lXtqKLRJs4ZvgdW9D+Wro3CGhmFfZxzN6sX4ebhXz8Br6oAXb4GTnTeC3Dlwp+nMxrxXRpF8j04JQbrBatDqy+RtsrHCMgodBzA1HS6Eeby4jL08qmm2cUIaUZFvcTLa3gd3anRlWi+jkUw3oCjZAVZSTKvoaQ2i7WFil+evFWFWkC1GC1oWBboXnqp5gEWbF42Nm91/KFj9qNnmT19BOTtrJqR2iHOI8a9lZH756osplMwBU5crqwzuSgeMsYsotbUhyZDzMsqzU1iYL4SmW+QunobT2gE7ZAne+N4mMkBxpce1xcnXOrrgrYZfzAaOGYz+c4LgurCZJgEP4GrK3FRodzrj7BHVOISB5JnxcHHO95sdByRoxRYgQdvAmIISVkgzcrXCwsaCwyjGZhYU7HJMfmjqxp01mUpg/DhdmHxBChnmUQa5qbRnWnsszc1lYcMDVwH5mnx9vhRTA8qua7avVdAyZj/ftB9Nt/TjylTJLBfHHAv9+/ajKZPEdDmN0Hgq39zk1IaQboU/cSlwCFgeMXbLSCxcQVu6BbO5+m1s/NXfbl03ymy2J1K4PDmD3n3XzwvnJK+YXcBc9124MmObLldNKQv9PS6amXvKCQvzX/lz3Ve7tg90HWDUzORtUoiyZS7dKzId8CMELWG+aehr2kHqQqiopXgrLMIZuSMQ0dUuVok0YoNHA0Fyk8VVGwXPnwM9PC99jM4E6SvUfYMdwWRl1SLKiOg8U3hYvBj6nIWZwMatOsOrhWkgXC0JE7RslWvSDFZigZHGy4hnelAorBSnXHWwTb7rymtqcfraZHY5uflFpIvFUEFL0R07eNyIdgrNYEcsWB39cPo3wX/Y84P0DUa0q3D8ijkzsYvK5zUrBTxPSytFre+7Qe0BVwTD3nJ6FHbP8JY6coi9idROg8Pl09ihu+FeOnEtzzCZ2XTfRBFCWy8WL1yoK46hkGGUprW/C/F1eM1WbxC1BVVVE3taJa2nHQOrtv1YEg9eiiNmubBsOjsA01MxdBRtHImwYWW0n/mLYY0AzPLv5JVI43lrcQpHDpZxaTaOycrT25soeLgUv/GirJzP4zKGcOkSlWRg0ZUvAFNzwLHB/egpZtdVtMK8TZNH3dYdiPtKTme8SFHnmwI740ZgjPnpSOAYgdKcCv+MplCwZ19Q/MUomIluW4GAyM4bCyl2C4vtuzU42KbwxjPFoHRB2EkTVuZAj/RY6G3zzTnKyQqdDRbyfqTdF0clHbWIRAEf0YqWTh2m+x6j6iGRQ+ZxOt1D4W8YIa/NpMkxjYdDtycSMcS4TBKCt1oHMcuBt4pPAi3CrMP3BsWaXC3g92yzfIb5/YyaPNJ5JSJVw7hK8Dy9fCJkq2WKN6Os56p/0ygwis9Vg1LZQmfP8LqMVMT2sHOuhmJdmOIILj2ycMYsj/vG21IVplvPot0C9IwAo5WcyBqxl20/hLhvr/kL5yebkCvzxrayhJx5sGkuV64R3s9YkFPyLMRi9Ba1QCMy17UxMQ9TqBP6PBbh9B+sX+Zd2lErcAcIWcoN3tNBKuHgcJ+Foc7g9sbIHd97M8haTbg0sTKfmTcnFie1tCVxM60sTIeymi5l6YSPgTYf56/kK5Ztgf0WHQmSTU1oTUdHp4wdGnNBLzGVoeKP68TNpJT5ov7C7ApvZPOdb1s9h3i7SCfqj2kmCXPML4QEMfs7gu2ROaRR8LoXi8PPR5xvEalWdMVgnnRoC2PLQqxnP3BldMUm6thk/1BkWkqssw8YvRS6Ld7VW3euhO8X7f22ID3M80zhV/nsYytys6323oo1XDjMPzcNIGq9tG3HTLa8qJUb87zBHTXxWo18ycelKR9js1wB87G4kEA5Dgx3+SvOa7HzaIyzTFyXwOtUbgbbydWFGMrJg+g53Alr7iosWju1dCGX6MTFmQyOtwZOUWthwc8gMXQI+fPLIiOWBWfoCBa8zJqFGQu/imUPbXG2XV0whTe2ZaOZ1eOpDGazMXRFZDHYLd3AvttMEdiSeE01m+iNz2rwyyfDn0cf28pNLTIit4EsunyT8AI9pm4U/MRNCdqwiWVfbApei43LJd+YD1AvtCQ8HGqbQdJnDmH4O3LpnFHB2JF7gjxrRuYcx/jdskjHOXjcLHezyjyoHu8PonoNMmnlpGWwkxFcH5emgWIpSMXhY90tVmTHOJ6LpkagUmBYt42R8dbu8I5+fM/23lXSRoZMMdnyNA8GBehE0lwsoDh51ayC8Bhy4hVv70ZslS55dqYNicGDKF4+syL/O9F/AMnE9uc5GywLXn4BsUP3mIJIn9Z7TgJO/36AjUOiUg4qqwmxfbfA7x4yXrTGh5Z1Gsxxzy2iPHEZKK0cU7Oa0QC4ro9z435dHjhXGphCU/Z8HO0PUmvEzkWCVogNZCoXwxS6kEl2wU4H4rEcUUtxIxRdG1f8IQwfaQJoiVPIwmZeb9cwzuY6MOIH3o/G+7JMP1UugTddP/eOdkELU0sLgRaXumkRxSKlThaFhD+fBTNmyZ3pLFzqZXEShUc8CS+ZgjU7sUKABNHE69/UGBGhL61fSYsIs/G6YSotacOWrE3xygZHjLx8FvbFJzDkJNDdN4iSlTTL7KncKOwr4/ATd4TndNL2iC4HhSy8hRkznmbJu7LOyTSO2MjtpmCnavvWiMSZo93OjmFBWgbTERKx6+RNM0o9dAzl0w+viPxzMofWLoAFXsuEqd1b8VCOgA4IrLynq4Hxi7YqUcS2HvPdiu+/FU73IFKzEybSbh6v5FxHkc7EUeo/AL+5Ez6f5xZhNXfBam5DomXr21pHYSzPbMd0PGSaALqHUMpm4XEitTgH59j9qz+fxZMsGltWOMZ2zGZMZ8LHtBFYNJ7Y4duYJsV8cHoRi52LBK0QG0Rns2WW8glzsGqhNRELudZTPT62EMNkrhtdLZ1ItrvIuw4mJwPBeVc8D/fSxcB9gDmYjFyZgpKDoVXeJOkXkEYWpq6agrRaWFMxRW9LMkqz+s6am9SyG5V5P0YTF6rRRDvworyBaCJdABgdmatoE47V/m6YSHFUBG81mtM27FQzfCdeScXxlvJdk6kEVskAWB/lQiC6ykUkx59d4RLBSBhCBCn9ZOtEt8m9rfk1N2/yRTe8OGiboIgNMQmIhDZ5MXqcZudNMZPJ0abXbKWRh3XkXhPh9igimRLTXoleX6cAiaKWPz5ThKyqN3QAJ2cOxR5/1kBrcxyFZCcKrZ0mX5hR6HRy89Jq1gM/pzN0FOXTjxgHEk6G87NzSLSxIcXRtbeRroHNLPgTNqaNAFdubma72H4kaIXYIChaWeg0s2ylm3psX7e1ruWqlhRwbAB46hJwZZai5pqwue+gh/jEaXi1OW20Lpq8BLdUgDVy3OS9stiIpvRmmTaeRKw0j5GOEp7O2oE9UbX3reWguyOBTI5i9OD6c0s71xZNZNHQU5eCyF0VRrbZKvc224pMf7jeRGCgy8aV6bT5zIx6mkYRloWRXgupjc6Hs0wrimhD3aicTrocMJJc4z9bB5dzd4mYXQ/0EjZtYOkqwcp8ukowr5gNMPj/lYkVVw3WQ20HvI2Aqwp0NdnJ0JYrduS+wFJvbhKxVDti+46YtImNyHXd6DHdKugeczPbxfYjQSvEBkaf6BAwNR9YF7l+IHIH2sNN9W8EVlXv7/aMT+e5MSBbCsTaSDfQHVswvpth+HMTxqvTX3Thjp0PbHoYneGNP55Cy9ijuKP/VowuJjCfpS2Yjf5WD+2lC4iVtjYXe3KhXszWcnHSR2smWLJeC5w87O8KnCBGp21jpZZJBK4Km7FsSHs3tqrluK/caJmmGtEuB/vhXnw6bCuczkHsZbg0XudDyy5qExdMxNY6dFfD5BHvNExrYP5078Plp59GK9tXb6OfsYkUV6wOOSFYz6rMzcLiRKY6hVnsMdoeWbwodgwStEJsILQpGuy00NMWtPlkruDNLjkm47bJ3+pu9owlGC+uibgNd6YAdxVPGY+FRPTxrP5NuQj3wtOwD94Ny/eQOfGPONTWg3K6A7ZbhH2BRR0F2Pd+HbbyRjYT3hfEwJappXLwmddKPGahrw3oYofYio3UZt0oKQboSlDOZ+tN8lm8x6YQFA8RmOYOzKGduHDtWLHN8vAxUxS1WyiUfHM8+S8nf5yYrRYpX9WHNjsDLzsLZ52Clr7EbL87s0hLMa6sWGbSuNaJ024gn7+JJP8NYDHv4/K0j8mF4PRnEGCoC2hLX78l8kZfu48MAM9wtcirj8weHbDkctAASNAKsQlsxo2RIra2o9ZqPpUmlaDECqsQwbswZdr4llkhPjuGWE0rW3voqClU2ip4w0rEokX5OvtRrIjWUsxuScvko/cGpv/MmY0nYLd0GTG72rEyOZu06OocMF6kpnqcEV92cNtB+Zc3A9NKnrkcFP0F+CYSd8sA0Jqx1uxDa16BRXTt0c4DUVBQn7rqY6pmInVxykd/e5C3fb1itdVY6sDFDm5s2sEirF1yDDeDbMHHk5f8uvzU6UVgLufj9uHNWU1ZjY4mC8dHgpx+trHuSVsY6tscr2yx8UjQChGBV8hVchvp3ZPecdW6pi0mC7HC8i+pBJcVGC3h+3DHLsA5/ByABVwL04GZOwVV1UN1C+lts0zaQfi2+ihefIfn55nCOP50rS1VwBQ4NbUB/Nnh0ObNNAGgEX8sGdg2rSLYGQ09MVorZgMoYp654uP4/iA6tiYfWrLOfM+JuXoxW4VpQkxv6Y02SFgVNnpwLz5zrfEIXRr6DgSWdWpBHsrUQr2YrcIVFaYbMWVoq9MPmpJcPaAvt4vHHjuLzL7jW/r+Yv1I0AqxDNOJaWbMdG9aavUYS8AZOGyiaBSEvGl5c5OmCMtq6QgKKrY4ny/whbwNZTY6qPWPpNn58C2BV2yExRStq3xaHrEJR1tvUEzGfFzfN1Ha60GD9cC2iw0VmmAlkjccHatac9HJgMt4FBH0JL08Vf+3XHqk1RPN3o1f7vwUhhPlID+44pxABwAWDXnzkyYiTVFoNbcvOTx4pTz8xbnAAYJezZk22Owj3ID4pdK2V497i3Mm33fJmo0uGZ0Dpk0ru0mFkS1wWTn89ShmuD3MAcRENyN8aAnzkk0r2+wc/OzskqVUbZctprRw+biltX1JXI/ORn++0RnfpKisVURxH+gcUPc9dEtBZy0nsLoT9Xiebxq5REHHE3oBb4VvdRQUtaJxaMwruxCbCJcyXXbSqV2uN/mnTxkBSDN372qNgfr4eXhN7XBG7oRNj9MtxG7tgnPsuQBv6qV80Fwj1Wr8YjFab/K+xOKs6R9fPv9k4OFZ4+NpDxwOus6VChWhMGcq8SkSKRToR+RNXYLL1656g7IfPfNE6TcbsbxKYUEvxzPj1yIytG8a6fbR3coCLssIiekF3xTTtWUs4/CQsF14E5fgXnrWiFd3dg7u4jj8pg7YI3eY9AlTUFU9VsxDTWQQO3SXiSSWzzwCf4qdn/wgL7X/oGkMYYpiGgQvtwBvevSav2fHgOnqtNUrBlyxMB2m6HlcxfcCVw0K0H23hToyRBX8ValtFR1lMbXCh3bgiLFkc08/avJp6xuOHIPdPYzFoo3xueC8y+V70DTLJezoAkSzr2VzirMD7prwObmNaEpAhwZ6vqqArR7TaXiVIDznFFroF2tBglaIZdFZd+JSeO4prEDMslBlmXAznZwmLsKil+N1cuYYJar6VN7schoLZ7yrZ+FPj1barQatkJ3Bo+bGHgjz+hQCm5ZHLZ2IHb3P3Ii9uSk2qodDoZRpg18qwj3/RH0XpkpxE+y4WVato5A1UWJaAVH4mkYPJnobtBrleDDawuXl2mFl9OXEKIu3Ag9f5stRyNZ9voX5IFK+zA6LIoa2Q57Zl2XHqpiFO30V3ugZ+HPjNS9WvtaL/vC9JlJrls/dspkAXM+7tO79jRVaqWKFllhTVIqfm7rvRnI1vdw8yqcerpt0uLkTwPQVxA7evaWilpObOjFbu23qCnw23MisXK/n8V0NVpbfiMUUz1OuBLBTGiv03Usn6sWs2RHfnC/lRAueGG83Ypnn3FzWxemrdMxgg4fwNryEqwVsc7tWTFOMKIq5wDZPgrYOXheYUsR81TBo17fTLdDEzkKCVohauMRUzYFbBiOUHm/c7B5kfEfroR+s3TNslkqjltsnKpZejBIxP6zafcZeh7Bl4Ze5qZsmBtUHffiz43DLZTgH7zJiwJ26BHDZPZ40+2c3dwY5mzRRZ7vPvgM1T/fhXT63sqUoH2cXMLa8DMNzTatW01pz4hK8ipC02/tgdw3h6mxT+BwBML3TWdHshBTSsZtTqLdrLAF/dswIS6ZYMOeOf8VhNJMEporQqiwERpft/kNwywV4tDSjZ28yY4Q+I96rCVu+H8WLWQZnRI4+shxDRrBXESwc12w2j/L8HNz5WbMMHW/rQKK5BckIRWeOxeTlFZ2wDEzBYPvWdQpapnG4i/Nw2XaX50pzG2LNq6fNmG500S+4IopahW4GYf7MhN8B2iExhaW8MAsvuwCbVmYt7SaKblrVZlrg2Q6c5s4gxSGZNs0yzCQubFd8H4XJcTh2IGhrmc8FQomitbaSnfC0YT73jRRxmfPO95fSP8w+BV8TUw9mzsVqQSNzfVfJMd7LtGdYiBUUgtWSTAR2hyqoE2tBglaIWngX4rJ9iBjybQd+OQsraiGMNznezUIolX2cHguWP6vwIk7boGODFnrWUYjis1Utl6ENXIt2jLDk7dRfnAYKC0GVfXN7pYuYvWrxjnlNRnwjvG1Ztc+820jRY8dQPvlQ3dKrN34e5ZkxtPXegzE0hz6NOZQUHmE2mEyjCH8vHosiXN9GIdGJcnMfPNhwyjkkc+NI5dkdbJXPybzbKyev/c7XOjMDDB6F3Xcg8kbqzU3AGztnvH2NgLPYDa0fGDgEp2swUgznF7LInngc7sK1BM7iJQve/qNA/3C4qGXaR+1kJWwCxYKjNUSWzWd1yyhevYj5MydMu2FC4ZXpaEP60J1wMuEi2aSzrAbFfYTLxKFe4MyYXydcmCN9uM+CnZvF/LOPIr+YXzpkiYSD5qN3INbSEaQ0jJ8DyjyvuALRBbt3JGIVJUgZKOXzcCKyf6YXgFuGgNNXsVSoRsuuA91Bmsv10i44kTATDbAtbm/QDa+9D8XRC8iXggg84XI68z+T3YORk9y9DhtR0Lt7NgtcnQ1WrrpbAreBTFJiVqwNCVohaqDgs3v2wWWR0XKKeTid/fAmL4U/l8UosfCbPj0va8VsFd6S2fKVN3de3NeCsdeiSGV+HgUeI42MXHIbo5d0aWipeDmGFBIFebLzwTIyC2rYtpIigeI3KnodJYiTTUEeIUXHso9hFfNILY4hGW8OrWjmknRULp3d1AF3SbTXwM/eeRjZzD5cnM9garRs9E0i3oahrg70pxZhsx1wCIyqmZSIsI84ejoYT+YLL9+Wz8K9eq5OCDMySWHJiCFbqTKVY8Wull0ULp+tE7PBc33kzj2LRGsrkAxrvMB2xKG7ubR51e0RlBfmMHPq2To9SCGxMDULO30W6UO3hwp6pqOYaGPI+WEx6p+OjhZTnNwyeG3yQhs1RmZtr4TFZ59BblnVWLHoYuHEk2g9fEv9eHOyNjeBcm7BiHl//ELEG7aHGuQHr8DIoGXcFWjmT9gKmb7F1xOz7rnH61YvWKzI64E1cjcKvcdQPH8tPYarBrlEJ6z2fYgr0hgJr3tMPeCkPlhlsXa2l3IeyNV4KUt47xwkaIUIydvz+w+ZHMxaxWC3dsPuGjAOCGEFIHbfwci2j1F5YoQ3Vf6sNV+MxVpczjcFU7VpEok0YvtvNxHVKLjE6557MojkLn0AmvnfAj/TDmt5bmIlT5hFVcwVXrEvqSbj+hB2L+Jj8cUxtLTtQ6EUXxJS1b8daI8WE4zG4Wpi5XK2ZSHf1I8TZ3LIsn1ahWLJw5lRD7GDPejlEjXTLcJeM6rVLB0VKPBDBC2Fvzd2NvRpJrc6Nx/aEczL51CYCF8eJ6XJMaQ7QgRtPGWKiUzDhRCsjr51OR4UJ8ci0z8Wr44i3j+CeNPKz2+nmxE7cBzls4/Xn//p5qB5xHUixYzUMke1bl8WFpGbCbcdcLwCvPnpwL5rWR64VSmA9EO22TzvmztRjsiT7a1M8liUyJ8bhS4bK1JxSKmA4tgFXE3eivbDbYgVZk2+tp9qxbTXgguTCdyZCQSQiIbHxNrhXspsx81JWYBv6iCODQYRZbH9SNBuMbmCj5ls4IPIKEVPa9AWdbd0qGGEj3lq9BVlVyDmyLHgh0t518uH4gWDvoR8PsUdx+ZmfQhzRd8sZ/F1+TKsqG9l9fwq0VCKBK/7ANxMN0rzs+bmH29pRSzTjFgyjtihe0xx0ZKdUCIdWHpRKEW95nU+wrqCEomUiRjWiVlSzKF88Rkk7npR6NOMW8CV0/Vitlo0dfFpYwXmngspcvE8I6CZc+nP1Ag05jm29wRFQxEl60wnYDemS7PXomIUE/u6mdMY/eGNiDp0tyn0WRpvWqgNHcN0MYmsxaKsRVPIFjzBhpVI49RkHB0j9yE+P1Fnzm81dQTFcucej3zPyNpqRp+joteEVmZhr0YngNXsfyLSKkz+aPdQkHawXNAnMmaZez2UmY4RgVt2UfYtLC76xiGAy+fM8e5oDrw5KbBjx55bOdb022oykX07sb7ezh7PpYhtNjwTSTfOCQx3LqdUhDN8K1xGcCvjQ5uv2NBRxO1mONP+iqcxota2DvFhrPxMmkE4hckJpIaKODnXCsduNdeaUs3XkuO4FvEsdhZMzWFR4TUxG8DL3bOXAy9lRWq3H33FthAKtqcu+yjU3Jt402DV7UhP44taitnxOVauX6tmZyHI5SkfxwYsdK+SJ8pc0qeXtRykJ+TB3iCCt56iKXahefpy/UWIRVncD+b0RUVMTCehMRtTC8HNibhZGFF+bMBHuqUD1uHnVJoQ+Can9HoVzLyJXpgMv3Vz6TXMh/O6UFB45ZURLBbOOEEKQhjGFD8qN5M5uKUCnKFb4F49XclbZDpFi4nC2fR53Xcb/J5heIuzQZU/H0s3m9el40IYVscAFooxHOgF8pUGZumkhWLJN61tV7vZM2JuHbnX2FdZU5OI9fbDSTdj8aKHxVIMsVgrEnGXHhQmj7bgOfDyQMlpQubuFxsh7BfygfAyrWT9ypiFiEymXkQVWtEcfylPOeQzRuRJOok4kpk0CtlwIcnisFW7j/GzLxXaWUHOZseAEfvrwW7pACZq3B9qSHT14+piChenr52rzHtl4d5tw8x7tYL3Xed7L4dRVpMuEzKmPvNlaYOXnY7usMYiTH6eavoNPZFjcfBbe8e+4BrCnNlM0sb+bgu9retsYWqGI7rhiG329lqqQe2n4aVri3sDiA2G9xA6tYRBUcvgDa/jYnuRoN0iPN83N4VaMVuFVe+dzcFPI8MCC85ily9nMj+PrSZZeBF2MylWCqaWVx2Ts2NB8Qij2GsV17yZLZ9Rk4k5GM/TqEIs3sCrnYRqIzzzeWBs3sdI0jI3TSt2412dmpNsEhAc61p4ozvQw+XP9bgcsFNTHGDRlzHQZI6rHYgyhkQjqs7N363SDYxRsdj+22C1dQPFqlDILNlTMa3CineuWF63OwfhTY8Z26xaKIZzqR6MVjQ082X5ablSQVIJHweSq0fwzefMtOLcs6fRMXzQPJbh7liMnlgoL7uUUSDTitdJdwLL9pMRakbUmaqx7F2M72mUMGXzDEaoPZO3WX+SW+lWY+ofhpNMI7PvAIrPPLUiGplMJxBvC8ufrX3fVlj7WuCUgs99s/ZPsfYusyzvVaPaNfj9h3Fx3Aq9aTPX+7ahIHVgo7DTTUj2DSJ/ZWVahZduDyYRYTFcLk9XjquxLguZhFB8cxLKCdTFizMY7myGs5rx6SowSsxJhMuWxiEkOzsxWw4/LnRVSKlRWEMTdm9afg+Ta+72I0G7RfCiGlYUVBup5dL8db0vK8UsXFY1omUHkS1Gf/F5Q+T2sK4vHJsw4Ul4mZjP+Wvupc3iI0aLo6DYZTXtchHleuwkFJ3vOjbLiPHa8+EoAka6g+XbKzO+0Z+mzWbb9SurowgK0NipKwOrq8PkMFLk+rzpFnPmHAnfmXhkcY95Xdp5cSxiGRStjLlMp2LXv1yb9IDD95gc4yAlwQo6q7X04PTVa/uyfBmYEwzal601h5gTQE4UFnju1Bwyaha+XlNEJM6Ik+5hE4l1xy8GAjzVDIeP0X4rQlhTyDOHtFQumuYbJo+UKQ/pJpOGEubBWiXR3Y92z0P+0hkU88VgTDvakNp3DLGm6zd5MPu0QT6miaZmNB272xSk0SqL2IkEksNHMBUhyghTdzhpXevkcjXicQfJwQMmsl4auxTYYVkW4u3dSOw/gljcR3n2ar3/LT2R2cShcp6uRpAr62FuZgLA8E3tq8m9pnBenlrixJDoH0FzzsbcsuwRCtnhTmtHFzqJ68NcWR7BqDtDaOtmseVI0G4RfiVSWft77VegtnsNzdeNC1PNRdD0CadR/MLUUlWxM3DILMdu6n7TC5Odc25gzSzCseraa0Vsrx2XMCrOQuseb16MKKQZOaaoNkuC9IrkMC/7WFUfyaowogDln3C5iaKc2663v1Gw8IlRYQoxvga9MG/GZ9G4KtBDNrcQtLllCgQ9PLv3BwVDEcvCxnO1Z1+l6G0ZjIg1t5vUDKZIsKKX48B9Hu6kvZF1XVHLH783aPVJkc38M2+VcnyzZR1j2pyycOugb5ozVI8N89KZd32o1wr1ta1ifHjpZtDSVYlsO6FdrlZ8vuZ2xG/9iiCNITsfpJu0sMI/8EytRmuYRsFfed6ZYhcnjuTACOId3fCKBVi0+0oHy+ObjWl0wUZple8wv8upDnZ+uxcu/Ww9H3YyiXg6A29q9QOxzlN/VdJNaWD/USR6BuGVuOrgwEk3IZ10zNjFjjzHTNJM17pY4tp438Dx2kgYCWYzC7pasHObSTfidbh3n0ll2Z/x0ZEJ6gd4PrJQiNePdaU4iB0F0wm6WoPJd9g2XnPE9iNBu0VwCZQnPavdPRaIUFGxk5LjwHYcswTOnE+2/mR/a16raWVC4+l4YRblU1+uy91j55xydtYY5zOv0ctng5xO5nIxestijZsQSxQhVW/AoDCEEU0WsEW/JqMRUbNY7kpUnqhZHuYKeUTdTPM6ku0TThABTTpAvhykEJiisJZg/1gcEpaXy0hqR5OP3kwZLdY8SrNT5sY10NqBfKwVM4W4ee2bgYJiQ2LrzJX1yiiPnrpW+FTMm1abTuxIcBKFPY0Rru79xobLWJBVzisr1QJn/62YLjeZfOYqPFUZ7WYO+O3DN3aDrq1455h2t/g4HxGFp1hOrEPX8fgxjaM5HeRgU0Q2py2TonKjIsKIojUKo6Ul7q6V35nJBeDilI9cIZgIcALDaHG1YITP3ejuXvzuM2p4gHfcQhY+JzqWZXLBZ7JcVQiKo3gMuArEfeE5mMkwjaN+QswGF1dq8mdroVXuZhU2pZM2yrHmwI94eRc1Xi+LBVP4x+Ism6k2nL1ssaBdmrANHYPfs99MFIIcYPvataM5KKDb6TBoslikPZqFzr6DKLmcAG73Xu1c+H3hChvvHpNz1+5xLRUv5bVaLorNQYJ2i2DB12CHh9nJLFoTRbRmXLi+hamsAzvWhFQijicu1efYUvxS0B5K5hALK0Rxy3DZvYkWTMwHrOZMOrGg6r5zyLT0XCu8MTM6dykIBi/5qHKZnjl0rFYnxrOUXbMq3qRNiUCEXw1JM6PwiEqaZxRrXxeN11du4+dn7u1aYXSOqQEPnalPZ6CwpcgYWiVtsa+5hNz5U5i7XGtPdRbJ7l7sP3QMtp3Z0IjZul8nTw/My8b/1Gd6QSXkzOgjzd/Z1cs0VQiBLURNz/uuwcC/lhHKVDPKVhznLoYLGi43c5ITljZyPTgZujq3Moec0fO+G+zOFAbHkAKWkyVqHNNOeJuKKxnVPllj/kARyZxpTgT4vdnomx5zgRkpNLZt9BSenUN5pguxwSMotw3i1DgLG+u/w0x34b4wuh0Gb9CcePNvl0NHis1YWuX1hsL7UmUiQF9ifnfpfhEvzKB8+uGl4kTiMoeZ17feEXOubwcmMo/GhBOd8xM+xuYCYTs3Z2Gq6ONIv7+i9bS4BifJR/uBoY6KlzIbZyQbv5h7NyFBu0XwwpHOj+O5+4Dc6EWURqdgOzEM9A6YZciL020oFFcejpkFD7N2Al0R1dW0BHLPPla/dk6hyx738RScjrVb+7Bis1bMLr2sB5wZ93Fn3IWTn4E7wbacWWO4zlxJRopZSZyMB+1dq1Y1jFAxVzRKwFHM9NGz3fZxcTKwdWLEluJ4sH2dBVN+YI3GaE81+mv8UB0Yw/VcMRBCocxPmU5K/Ptaz9Ty9Bi8aYYEr7WK3eyo96qfkS1ReU5QxIY1TmCuX4SgJYwsLc/7LOR9ZCOacxHan/W3r31/GRW8fSiIFk7MemZcO1ttI2bX+/mX2gnPMe95WTvhpq01aGeHqPNM0wyB4rBqRbeR0BPVPfdE/ZqIWzLWa56VxMxiT2huOSOw7M4UNomg6KavJp1JGJXnd5437X2d1g0XrfI8Z1A1doOTC9YPnKox3eC8/DQnt14J3ROcqK/0fGaKjUk92OSUq63EL5fge2VYTmLT6iN4XeTEYXnQgZP+Z2g/tS9wHxHRkdqNzCEXG4sE7RZRyuURy8+ZaEPStpHkkiwTKS9OwJ/vQbLrOazLXflECxhbcNCZboO1uExlMjIX1kWpAlt02q2da26NuVoTAMtzjbG+P3qivo3o1GU4B+5Esr3PRFs7Mj5Y+MlZLKNB14vAcbmOQonL/Swso/Zl1G29kTveuFmERwEbS13Le+XqIF+RwoqR2uWihz6chYqYpRiujgT/io9xW6JnAIlUclOi3qvdiKr5vyYyYCr8r3PTW8eSbNViKCpPmOO5XtLeIoa9cfQlXWNylPAsOD7X8dbR97eSq0r3jNoo5M22E14vxVIwgYtiLke7uI0TCsZL2DS4CDlQPlAYPY+21g5M51Ze4pkWMVyKjrRnEhYO9wUTA79yzG9kUllyA4ssCmZOGtl9a6AzWGWJckagTzQnAtwa+HEHOfOcAFjFrPGBjqeSKLUOouRkYMNFcuGqafzhzU1teg3BVhBE18eNewZbMHOlxGH0mfaA12lVvVa4yhK2gkZ4/rKojRMYEX0dX2rVbQerjmqYsXOQoN0iLL8ceHRyFm4eqVkHX5xBU8es8Txd4R9u2fDsij/R8k1sc5qdjXTlZ04tZ/2rCVoTFWAFsVmvTZr8vtWKu/pTWZQvn0R8uVbyXGN+7yVacX4+adwA+Fn4pe9r980yzY0sufJvNuJ6WlsUZsTpsrc24xzitEI/TI4Jn8txWLIgqwhcGsFT1G9k1PvsuI87UtFLV/mij0vT/tKYUtD2tgP7mplgnaxrHLCEHYssClsNTiIYiWMedxirNUFYDXrIls88hnKqDYVEEDW2ivPwzzxmnAPsprWrT04IasVsXTvhCS6f3tzNxnijsuqeY3mdiNn15l0bHnCj40k+5MNX8HJZpNrLoZd4kyl0neouTiTX4qtJdxBG/rjCUiuQZi8FXtIUx2GTUzqcUMTyvOIkk98TrupwxSbpeHCbezGdGcbFSd90gbOsGLraDmFfXxZpL7pBRKNAVxL38il4NW2aKXDL81NwRu6A0zW4oe9HIRbWo6LKYt5Hgda/hWDVgdc8LrVH1RzstaZItJfkpLlKJgUc7eNkbG+PzU5BgnaLcPwyihWHghWUS4gvjiPdvM9EJpZHE7s7ErDn40BLF6xksN5hCsBMcQnDGVOmXWkxw2iXhURuClZ2KqgItmOmS1FdE4CKn6i3MAN37AIKThq+5SDuZhHPNKOraQAXp1aeGryeJUpzcCJqnf1CDtn5RSzkkiZKy/sXRSEjQpzZMupzPbcEUyHO2S8jtDdRHcybIgVNmOAhLA4Lu0A78TjirW1YnFn2RD+oTck0t8BOrj2JtOq5GiXMzI09ZCmL48Y0j1rLN0awL5tatRRGhm+Fx65XtSLb2BrdaiI9a4VjMtxFz13fRLlroShZ73KbOzeFubYjODthIZsP9jWV7MJIdyc6Z8dN04PrRuM9Fx2tzUHu9vXaCReD1JX1FDEZezx+N8bPm++NFU/D7h02vrtRk0NGO3m+MaUkjPYbyE2kkPHp+2tVrNhqVHDJ9YzIsCr+u47DDmmpIK3EPNlHrJovz+9pOoGSH66imWqz0ekP2YgJG2EEtqMpPIee1zjmyD910V+6qlRztdtG0pjP7Me50WsnIg/9xEwZ2XwKtx9sb/gbmJ9jHvzKVtK84LAbIXPg7Qhf5PVgPKBrUqmWw+/L2JxvGuLwGDBtpKvZNyk83c17V9RywnZ2ol7MEqZnPXPFx537ZN21E2j060HDwBzHWCqN0mKIwnLLSCQcI2TpqVmt9mfkor0J6GyxYcf7TQSU1l3G0qtzALHeEfitXVhoGsTl+QSmxpibyItPK4b7htGSDFpHuqOn4M9NBII21Qx74LC5YS7OLmDUG8DEtGeEU3OmBcMJH235SXS39hmLEkYDedOhyDROBTHv2kq2Ted6JqiWTHEYhVbM8o3bweMXghsTb2IHewIfU970ogQR33+qWiFeidr0tfkmx3I9wpbCmYVfFD1lDqhXcZWwHSST9qqev2wQ4FwZhbusjatlW4j377/+Un8I1ah3W8pDVyIL23dRQAJj+bQRjlFL/IxYRfkXj04DfSM9yBy93yxZ+otzxhPVbu81ec3rTddgisidw8D0govpBc8sF/e02WjJ2EtRZAovk8NbFV+VHF4jBrPzQWtUbmOObiKNRWTw9GW3LvqfL7h49jJw+742dJTycJ0UcjyV/KCivhrR5znszU2aYqD22Rn4SQ9e1yBidssNRYa5L6bwjasPyRZk/dSSCF0ewTU2dVNX4F546tpjhSzchUlg4AjsvgOhdlHGZ7gnEGbLu//y8aqtD2+MjFxSFyx9PhZ3zY3DYztitjE2TQO6Alu+psBCjQWTc9lA0FJcHOy10dazD2WmHNEXt5hHgubGBcCPp5DYtx/ZhZWqle871BW4HGwk/M5GiSRGBKvXguUwb/78ZLgzylQ+ibkFblmZQ5stOVj00tg4qXcNcw6b82Y2aCrHxhaccN1EAVo1ZWjB2P/5Jqec54S9MGPGjWNUtZ7jJdUUN3LlpcDk69U/JV+Pk22KVVoDrgYnQ10RKzCBuwTw5bNBylYVrgwN0YLX8dG6jrbBuwHeu6bmoyfPDEqsq9tjg+EzcJJfwP7uduN1vlEdAzcKCdotgpFRp3sIfvkM3EKhcgEPCqWcTDOszn50uIHVDm9cvHPxwsMuM4nCTFD45bnXlmbzi2YJt3DkBXhquozCwqLpRsYXnporY66Uxh2HUsic/nzdkjSXKd3zT6I8fBzPTqawmLt2951fdPHUInDrvgQOt+fRnkmZnDjmwzGiyQhUEi0oT6ZQ6DyIeTeFQtlCJuGj2ZuDNX0JC17aiFlerCnGmVv42AWY6tCWdP0afyp1zb6Ay42mEKQCb/oXJinofPPc612ow2hJuLitp4hLYwXMZEuBbVd7AgM9KWSS4dYJFOXnFlqx/5a7ULhwArm5YAKSas4gte8wzuU6cKhy81gLrB5OufNITJxCiSbvvo90IoFDfSOYbhlEqhI1Xw6jjFFwNPMlLg0ngoYAjNgzghi7ZiW0HvxyGYn5q+geP4ce0yLWB3IJOINHjCUUGycs+d7yiDa1m22mUcGVUybH+hoWrMFjuJrrhOetDF/ypS/PxhBvTeDsFX+pvSRvDvu7ga50Ad6Fp+HPjgXuEIVFeIycTl9B78g9OG+1hwopRv2S5XmUTz9oCqX4NzynirEmlAaP49Rss8kVZAtk4zVcEf/GMeTytfzwWtzR07Bau2FFpEewM9Wd+4McXka3KA5Y9GeEixU8zmV53vwCWz7ftGJN5ibhnnn0miLk55ybQDk7h+yB5+PseCzIQ2fmsRUU2J0c9XF7fyuSHX1moms2WJYRtnQ3cZpacEuLZVwNOCHihImRWYpZWnNtFSZ1x+f3KhD6y9NqjF2UFXyu5ceR37Gsl0Ai0xqsMJmmC7Zx6OAkab5gY2XZ2zV4vlBI5yvWVMWyhfR15qJMN6LtXdDC+doO2d37zASDNl3ragk+D5waDezTKo+aqPXRWHBecuK6RMXDmA1XYqtMSqtBgMvTfrAaEQ8q8JkyFJW+xPsNv1dFt3KfqcBI7KG+IJq+fGWGXJoE+tsstG6s41zDwHN3tSwd3rd3e6cwr+J3zus/ZmZQnukGekdgdw+t63uxGUjQbhFcjqcpu5VIIB6LGz/FwGIpDqtrEBNuOxaLQfcqXpD49eA1ib3u8zMXkQzL24zFMTFdxIJHpRmr5Hb6cO0YipaDKxNFHGJFVG4BMG0uWaXFXvXNmM/bWGQ4LIQLEz4yzWxjG3xFefO9nA8Kbm4faMZC3z149kIebk0yVjLRiltG+nBqLI3bhixTBMObCUUtl7CZW8eLLR9npTwvpl5iH+bzFhJxz4jXMHjB5sW+fT1Lx/OTyJx5FEeaOlDqYfGIh8TiOHAqD+9o4N+7HAqPsm/hsZkuDAy2oG1/DpbvG6F+cj4ZRKzXcd1qcXKwrjxmJh5VvGIR3oUTGDrEaF3Q1nQ51xPOll9C+eRD9Z2U4skgL3VZy9cwKIDo77nU3ta24c2OwT3P6nmeMdyB4DiXz2SNcHXPPl53s2eTARY7OvtuXyZmg1dgN6qFcncl0ZTJyFQVViBQfA/zfhpXZi2TmmJuHBXxyaW853bPwpoZMxONUtmCZ6WNMIn7Zdhjp3Gw6y6cnoitGLORThfW2YeDbl6VxiVGNBQWEbv6NHq770aznYc7NoUCsog3NRuTfEZylzqoMWWDEw1GPhk59b0gb7WpNUh7MA4Tdt3koRp57Wn164rsuIT71KWgSYnB5fcscDE5msghFqLKvVgac9kg9YM5wbVjuq+Tr2mhq6kH3u1DKGWDlCI/0wS7nIc9NYrMUIvxyGRDDD6bArs2MkvnFQqhtRR+mUkFI95Mcyrmg8hlcwcyPHcsHiNOJnwzIaGTCJ0SeDz4fWexGKPVLBKrXT3gfvFXHnMeJw4nI/QUWYAd3Cw5UateMyuFUrT3Wk3sseCS1x1GMGlNNZH3caiPXrw1ExiGNk19ZfCa3vwkvKsrG454ExdMpJZBibXCCczJKzXHvgKvp4udbdVT1Fxb+LWoRmzzSCPBdJeI48DJyrnxpQdMC+gTV3xzvClao9IDOCG6dTDwPed3Kt8ZQ0ebZb57V5a15q5lct7HUGeleUjJM8d1va2Ew+D5aO57OzCtITgXo9nthWF+MWeu+36OJryVE7lchHvlpNEytAm9Gd/7jUKCdivwAhstLifGho7BY7vJ+cnAL7ZzAG7PISzMJzE171WKjnhD5c3bQVuzg6KdRsJc5bgmFWxjZyO/pcXkk1H05kpc77i25pFwfEzPFFBqaUZs8eS1fWFL1EwrpnOVyFvISbiQ85Atx3C4ZQ5ObiqI8GZasei0YyKbxsXpNDx+gV3eRGlJEEPRyeDEVBKDnRYeOlN/8eb16Y7hoMEBRQq38a3n5lwslH0c6GVryOjhYz7n9VwAlmMKuypRFrpDJJY5RNC/M0zQ8mJKz1w6EpStBMZLCXORjVVusqycX8/Fy87PIeUtIpUswaoIOY6b78RgT56D190barjPJUKKjeXL2CQZ85BeuFIvZgmLSs4+jtix+yPz71iM4k2NosxoJCc83A+mWvQfNBEqv/sA/HQLvEIBlmMbizkrNwP30glzM612W6sW3Nle0eQC+vE03HxuKRLF+x2N8GMMO6WazWf3SxVfMJrS0zPXipnl2PnstSq8gkWTegu58THEqhEsnzdgH67vGzuoZkyjZyAPpzeFK5NllEoeWpsd9HXE0VyahlfKVwq7XBN6b47ZKPkxlOZnMDw4jdLMOGK8U/kssFqEl52Dzc5htKFraoNLm7b5GSP0Y93D8Nitynbgzk7CZYrH/BSsVCawrGvuQNaNw85No21hwqQQcFUGHYOYKXbg8lzCpDgwSspjWc2P53d+PpZGR4gtXznTiYUihX6wRF0L2zN3NDm4VGrDuUs52MgE3dh8oK25Cbd0W2hmmkUiZVKAlpPLFWEtzsCaHYPFG1NrN7JNnUg2N5n9YuqTaVbhMlIYWBUZr9+Zq1goJ5B1BlBKWEhZPppmp5FqdnGwO2PO64mZErLzPjIpG/fsi6PgOWZiyqj51HxgC8foOAuN6IRAQcvX5nvwXPIrIpDnBCf4jl9AT2zBCHVe9xasZozlm9CWsYP0gPxiJf3FDlKqUhkzOZqZL+Ng8yKcUhbllAc34eDcWBPiMRvN1gL82Ymg4xdXyroGzYTGYyvkCLgyYNJ5Irq7eZ6H+TwLqwKnBn53g2Y60SlFZ+ebcXRwP0pXz5vVLNNB0GGAwDIpLjkvhZaIJXBOiOiKYPKueV+gl3QihUtT8WBlICISz++vcYFZAGYXfRQLPlLpysRilW5wpmNi1jMWeVdngv0c6vTMSmJTyr6uWOXxrHqCc2yYgkLRzeIzTvhoZ+hVG4C0sBBt+wVSFe4vU31ml11qa5sm7WY8ppFRzEZ9Lzr611WEvNFI0G4F7OJVKQijNQtzongCcGbjzU6g3HEIbtkzgtfkblWr820LC14biv39wMRTZludkVRTh7kghF0svYroNTfzZbCNpNNSiZKFwIhIzC+heOpLKNdEjjLpDPIjD5iLoU2Ry8hJpfKLEeh5K2VuWsv3h7/nKxfQavTB8y3EEynzaZhqwIIjeteGsZ4Ju7nQr1IFTg9Pip0wW5zWtG+ExzOXr1UEcx8O9AbR8/XAIiO7lKu8b/CiJl5J0cMIKKOkYYI2aRnP0Gev1C5XBkLxcLeH2LnT4W9IMcfzJULQuhOXUD7xIDzYpiDQ4rL85ZNBi9Hh25C/chHZE89ce794Au23HYd35RQKSJroexV+juakj9jcFErJDizkcnXb0v4M+ofKmLvqo9XJobOLpl0slHMxXUyiuyuFM1fLJtWh9nZaLsVRtnnCVDxNLXoSB+E8RvKKZQ8OxfwzX8JwM42M4/DHFlG+6sI9cru5yfsLs0GOajUvPRZHMt0Ex83BHT8DNzsPzyxDsJ10e5Cu0d6H/BOfXzpOwDRK45eRPHKXWQXJP/Yv8JjbWOXsU0jd+lwkWjrhnfoSck09KCd7TZ504uyjaOnZh762o3j2qoMz45XCnEpU9HCfjbl8HJ3JTJA/W0syg8lpy+Tn8mtcDQTzPOCS8sQC0FXJw60u7fM8nV10MdHajKhTtZAvwLp6GqWTX65b57fbe+De8jxMuq1mdaa65QqCvPhbe8vIeu145BKLYbg1+Ivu1k7cmXLhlco4eWbWiBdef/jtm5ywcPRgG3pb48ZrloKPE8NMiik3wC0DgUXYlemgsQqjtByf3lZggH7CziJyZ55BYWI0SKliOkk6jeNHjiOJZpQvnoU/dfna54glYA/fhlK5DQO5UyhduIyy56HENJpkEiP7boGVb0P58mN1E0E3Owsr3Qq0dAARxbvmmkKf2JrAQa2YvTwd1A5U7dt4ZBgp7V7FwGMyG8Pw0EGUrTZYkxeCqFe6BaXOYZSSbWiLUJe0O3ML+fpzxkwWC/DSzcgW06ZrXhhsYsFOgNX23wws0HtnsMPCgZ6KB/AyeJnvbAEePB0cwyqMwDMAcMc+D03JcFHruj4uz/hGgNc6zzCS3NPm49RofTElJ6+csK3WAGSr4XeQ6UmMgNc2HeG5fHTQ2vXtjX3WRETBAA31gATtHqG6plSFdlqV/MPqjHl2Ng8vWy/A2GPdW5zBeLYbHYmmYNnz2lZg8iL6j92FSxcsNCfKiFvBXdv1HWTLDro7k3DGq2tSNc/MLaAz7WI03RRYdtVeNJ0YOjvScC89viKpjUvk5Rz/nqqV0eJ6sWwEusf+68um+ZWGBkyeZ+SCgpifuVymmGI0InrorEpu4prh3Z+RlGKExZYR4+EX4GwxyD1kBKF6c+L+B13Grm9nFLQhXjBCv9qG2OQ3ztOawEw1rlHMmajfavlZFNHH91smYsYsEUYLWDWfKszCXX5u1VLtHLdi/xZRvvgMihSmjAp5zGG0EI+l0BJLoDQzhezVy3XPcUtF5CeumiXQYs5bmctbttGcTqGwbLy5ja4GzVjE3YNJFK9cQOlC0E64v7Ud+wYOYsEuwaVp8bJRyBVc+L09cBZGkS8Ai+VgSTJmUwxZSDa3YOHKFbNsXGaL4hryl84g1TYAzE/XjTcj95xYmEhxtl5AMnWCgt0evrVGzFZz4xg6S6B0+pF6MWsG1EP5xL8hfudXY7T9OC5NeCiWXPM96Gg9jv0oYiHrYmzWMV8pU/hTKbR89oqF5+xvAgorzwDLLZqUD7Mcz0BzzdK0CSyb71K4B9PVxQT6/QTCgnT24jTyJ768Yry9mXH4l5/FdNO9lVSTmvEsApM5GycvM8Ja/54Tcx7OpBOw8/OAW4RjJom22b9yycOZ8/M4ONKG+XwweeQucxtfk6kUPJ+ZY2r2rVKFT9E0u+CiI/csUvMXEUvGUPaClZw4crBPfQE4/Bz4bN1cS7mI0tnH0TV0K2bH67fxPPGunkPc7TA1CCss+7JzJoWCxznsu8PoL5sehMH0gacuAwfbsmixs2biU3TSuJRtQjLhmAh0WD48BdGV+TguTPehq6UbCdvDYsnB9FXbRP2eezgiN9N3rzlcLN+UX4TlcT9XXt+4wkGbwDDrLqYbHBuwTKSU0dSlOUKlyQ0jyLVitgoDEQxIMOIeJaCXUiOq++gHNRL8HtDZZzm8RzBlhJOdnbCUTRgxZutvRuBZV8J7Aj/zzbjxNAoWvxOrscF+yetFgnYr4MlgimsqVxHmsSaC5TlGEbmk6+YWQgsj+FUpFwpA/0H4to1Sy4D5o/j8FVNM0RovYKTDwjTvCCYdgTcFB4NtzWhvSsAudMGfHa1/zUwrmrCAgZ4+XJlOLLkUMMKVSDoYbisgX2soWYHLeykUYPvByV3bdMC8r+8i7tgsA1pxDTYerpWb2NLr8cJVDjI0qzlzVYeHKsy5W4sfZhU7kYbdNWQESuj2rqHQCyXFHS+kJvexUm1cCwswooouTIW8yT996toNkTl/nVzOXKVjFxOWq+dG2HYrKCxaHq3wyowURS8SUkyHwclUMV8yBXfX9j3I1y61DyN75unQ5+Wnp5Ds7YaVC2vmYcHvPYhSJapb22GNxJJJeGcehc8ky8qYsq1p7MKX0XnoOUjGOT4OYlRrFiOSrpnQOS3tyE20o5SdruQTs22whXzZQUv3MEonwwu4cpOTSN52J3DxySUP4aVoe3sPvMpkjJMNh00ymAbBiSbdQPh4axfQ3AU3HuSkOvNjxu6Oy9QUCjw/WKQV+B1bJsLt5RZxcSJtUh+qYzA1W0LW6kBHu7/Upc5EUitHjv+fLbM8PR2kftTgpJrRVLRMi9LaI8x8Yt5UhzosOKWQSZllo2wnIv2kGZ2POmdKV85i4M6jmFqsT8fhccwWLJS9aznVtUzO+djfkTTLMCbP1hynymvymPsc7+DAm/q1yvP4vb84VWmAUhHp1SYmTVhEafIqYsVFJGhHSLVbabfNLogejxWdVirXvbqJwMwo7EQSHpfja0g0N8OfOB+eFMnrL9NI2LCGKWHLNjq9+yP9iKcXfBxvHYd74Wm4xeC7z6Yth3qHMFc+iLZMEvmQhgZ97YEFH8/NsXm+9rXXr6b1hJG2imZit/x6SXhpStvch5WRZE5gee5EkS36uPeQhTNjvhGaHCZ6AjP14wvhXzUDo9OslVgOXT0YHAiDj9LhgqkmYXZ3LGZkFDcsZWa7YLpZYvsDkVuOxftXrYap3dZUKUjeAUjQbgF+qglWR5+JjNpdw+bGSWsgkxXQvR8Ju2yWuKd47Q2Z7HWlSig39eFMpgdzs/TlAdra9mG4rYSm3AQOuXnM93ZiPBsLcpCaymjxziFdbDWixjlyHzx2oGEkLpE0USpMX8LIwX50tMQwNhszURNW3dLOKj52FkVrZREDyRQm0JJqMrPu2u0UDAPtQDbnmtw+zrCNjRdzT+NBbmrURJv3Oy6tM8+W+YK84PIGx2ioyau7gZwD47VLUWKqoFNGBDIn1CyhV0RKFbvvYGSHIbciuvnReDOp3jD4OfgZGaXgY2Edsxjxc888brqN8bMHBQ4+nIlLcHhDPHhXpZr92kXBdAXqGAxvjnAdaNHFqnt/bmUU3lgNRSwBuXCQKwVCOJZphpNOm/SL0uysUfEuP2SIUHYLRXipVsTbiihOztT5Jcf69uNiqRvt+y0UL540f2vGLZVEauRWI4a9XBGFYnmpWKVUCCLDbVOXcHSoC4+et7BQDIRQ3ImZm9l82Ua5+za0tYyagjOvXILT2gWrdwTzC9OIWS5KHE+mvdCWzoT4KhdeNkQw4zMRdD9jLjC/fxwX10Xp8PMxXWKU2kZTu4eOWB7Jyw+bLmbTfffh0jSQn/eQjNsY6NmPIQQRsZhdCTHy/fgdtm3zHAoZx2laErS1Ef92inW7rp3KUv4di9yc/bfCn+8zIo1pMEx7KCfbjfPJWaZdVM4nc2wrjRq4cpGzU7CSvjl/lr7f8TSa0jHE44yOe8HStOfBTqaQSjqB3U4UJt955U2L5z4dTcKonimcaBh8WvvZ5rsU/G7VTdQpYqvXAmPK5VYeW9aggnnXTMUylf7VIrzqe3LFgxMAswqzTNDyP7l52PGVgtZMYrlEygEM+Tgce7tnP1ymK1W/kzE6fBw1rXajaLPmUTjzRJCzXYU531cvoi2eRLzzoFlKry5X83zsr0Q1mW6RrHyMallDYCm39GlWkPSyONBr4+SVlYp2pNdGyjiKrBQZ12uowe0dTRaa9wfXZWPVGA+KeaPygEnQiCY47rWY4rbwhSIDt7FIMGpfrrO7YouweJ/adxvcC0/Wn0TxJJzhY5F55VuNBO0WYFnBjdQUqcyOm5zaYMZjwZ24ALtcxEhvP2bmLDOjrYX+tBSaV6ZK6EnmMeAEU9lSrIyJ+QRSxRk4V8+g2aVHYDt8XuinZuG4rKgYgDV4BGDe5syYualZLe2w0y2w+g/CScbQlQy69BgxULmbuM0taE4G3pHVYiRu4YUtsXgFh4b6caYUw9R82ZzbLNDp73Aw4ExgzO7G/NQMYvRsrBa6ZMuI9XSiv902uXnLYQ4W8+M4+21NWSbyQJsuXuSjWmbWpjn489NBIRN9I3lD6hgwViIssrJG7ggS2hemjfIy5vipFlhVE/plBJ1xgnxf461ZPYamixlMoUVU+1cWAnHJnYUPS7liledlrp4Jiq4O3W2WO02Ly3SLGZ/ypWcR79mHtUKHDF5M3EuoRA4rZnDNnXCYKxhhpcIWovHOfqT4YRam4C1MmAtSenjY5G07qbRJLzErCDwv+KSKaCsUPUx33ImmtllYprDRgdfUgzGrBZO5OM4XBjE42IFmO2f2ZtrNwC85GJg7AbcSMmQU/Nrx81Gan4PTWsCRvpRxveBNkJZFXIFYyLm4eqWIuNOOro5243M8V7Axf87F8cG0+d1M0KqvV6lU42dgWoFNm62e/eazcFJRXpiDOzeNucH78cxp+ozyBHfBhIVLdgK37H8+Uo6Dpy9eEwqlsosTOaDnlozJJQ6Wepfl1HAVJtOO/OVqAmWluomj5rtYpGhOB7HNwL4qOC/4LydtXFFAV7q+M1TBM8u/rEhn/mHV2oljw8Yl3NaadpCzmozHted68Cy6nVjY122hMD+P4tWLprjNVCIzP3ToIJJt3SiNngs9N+zmNmQrKzC1cFiZGhAmMPylVIGaiRqTFqwgv9+J8TuNJWeC2mYXVReIMFwrHni/hizV87zhdcxfnF6xzUxmm5oRm11kKWLNBub+LyLW2WfSS8Kw2nvhtPfASj838IDlp0tkTKHZaiRz48hHdBD0Jy4gM9iPO4YzZimfXwOOAVeeZnPBpJf/z+trNcHAeMpWzpEw7EQKXdmnkBoewehCDDmmMCaBvmYXTfNnYHcfC30e34OvGWbNVbUXJFyBqr3OpeO+Kf6KapvLa/hyMUuqbbrD0i2CdLIg8BG6L03BREdsPxbvnZ0DJkjCSXcsOQGnbwh2S0doMfN2odNlK8jNw52fgnfxafimqrZCMo3YoXvMDSedacVtgw4uzsYxt1AyUayOFgeDLUXEnAQ6chdRGj1bd23vPXIHyvN507mLnchAYVK5IprVuUIOVjGPMn0qKXBNnuA0/OZOxJe1VKxdfmd0L5ZpQrO9uFQ4wNcz2rLngDG4H3bLGOzvA2WC7RdhTV9BzGnFYMpFsrcJV2Y8I+5YrTvUbaPJyWLRy+Bov20iX7wA8+LKGy8vsLypPXkxaH0Z4JuL4dGB1dut+nNTxjJqKerpluGNnQ2WDA/dAzuZhtOWBNrYRe368CbM4ocTFc/I2iIGvwT0tESL7PLivInALLXNrdywvRLAImDbsuGeesgU+/BG7U2y6qwMZ+ROM9FYD0a0H7gLfn6+0uY4FuT6rTJj9pwE0v2DKD/x/0y6CaNSnFD402NIHLkHzcP7MXv6lDm2VQHDICG7U8U7unHmZBG2Z6O9ZQie62PmQglOpoSj++N48AzwbJ6pDtfSHYbayojHY8b7cjkxJyhKK5QsnBotI8HAmQVMzrKYxkJ72ocDOhgES7PG6N5yzQ2fxvrdmTTyuWJdi2LarDUNH4C1QCeCybrlY96ji0N3G09Q0yDDCNrKuMDGSTp19HHfVwqek9Np3L7/dpSf/eKyLb652E95zbDshWutmCohR8srmXQRFtDw3GBUrhql5OfojHDw4HlmWUExDYukquKGE62z48FSMKN8nASMz9mmSK6/Ezjca6HJymLhxCPGcaJKeXoci3NTSN1+HE4mA5dWXzVwf+L7b8PVYnhkL2glbKNQrCz9V+QXb3bdLbZpurIU16dnNifyjo39A2ksMEXErLbUC1i+J31xKfSWM1FqQnfvEHyuS68YnDjsth64IasTZlvnIFJzj5tMDte1UHbYmc6CU87CGbnbuICsqG1g6+/2PvO/xh1kDR264sX5yA5cSauIhO3CjlloW3bHbUr6pmiMTWyWO2Ax3Sqq2MikyrR1ofnKIziSboWXTplUC+vqLOzekcjVGVrKjXQHRabLYSpVVLV+Im4byzOuoC1Pc2jNRBfL8j7G/NrpxfBYK4vmmFK/HI4Fi9T2ameynYhFa8emNvipZlyazOE2urtseE/vm0OCdpNh8wC2mDVm8DQkrl3KLeRQPv0YnAN3oDAzjZbmZhzGKNweJiP5iC+OwUkcRK5YRnnsgon0Vtt+UoCWxq8gw+mv7Rhrm6V7urnP2LCZt0grIvpmVv0WK35B7th5WCOtoQb8vJjHuDx+5SSsSocxs+zWO4LZ1CBydgmp6dPwLj0TLPXGYnB6huG1dsC+8DgGB0bQvr8bruUgBhep/DhKi2XkCwfgWrbp4BWzLSxmXeRLMRPhZR5dnbl4JVeQF9674rSFscJN0EdPh+b1GMcIVisn1+Ybyeghi69Y0cqK9OpqpvE27Q4KGFhYEdbooRRrQdkbC5qSxWLBsmupZKp8F/wMOjv74Y11mbxpRtJNJHH4FhNlte2YKTbifh/qyACLM6aJAaOsPOYUylMsCisE9kdcFqQw4nnAvD7mMUXB92dREScI3O+MXcLCpdOwU61GYPHzmGKbmIXs5fNoPv4A0oP7MH+Jod+KI0MqiabDt5qCw1v22ZgrpoyFje1Y2L/fR3OsaGzJjvU34dTYNdHCU6e9JQY3NQRMTVeKCbk0aSGRjJniI7d9EDkriVuGPEzOBRXcMatsRHRnogTee/ly3P/qOW7ysQsukiO3oWSfQW5izDwYS6aQGRox4iLWPYSCnUTWaYULGwmUkUYWuWQn3BjzGmh8WqOkYkkU7CZTUGmzw1kpayS9a6oa07iyEMfIgQNoOubDvfBM4KLhJOD0H4Ddsw+Ti2k0dzpoyQSRSU6OikUXs6WYqThnYQ07NFV9V/kvfWJ5PMPgisVwZ3DsOQmszUtmtJTfo/Y0cOdACfkerrJYSMXLyKRjmL80Xidmq/A6sDA+hpbbn4/yuSdQnho142ZnmhHbf5uJEI8wdcAPrJSqHrXsFEUrpbsPWHjsQsx8R1D5jBQeB/uAhB+Dc6gVl6/mTWpJKhnH8EAKHa0xlOwYcqWg4UQViid2AmR+JqvueY5W5wG8LHHVJ548BJeOFIwoM1eW53tzO2KHnmOs1bzFAfj8DNUzg9epfbeZ70Ns4CDssfOI2WUUclk4Ld2IsSV0azdiR+4118DqZId2XHb3MGwWha2DeHMzWjMTphPYUt5r5Til+B9OGnkfYGEoV2ea2sxPPJkxnRRbUr5JPaBYZKSVfq9cmYuC122nZ79JKfPGzsFmq/N4Cvb+22C39Ya6t1TheHOyVG3ykUnaGOnh+UkXkWgByRa4zzti4dyYb85jIzo7gzzX1nS0bRcFL4u7WBhWjcbyuRSzTHHj+T9a0wCEKQg8p1pvoF202B4KrOvZgUjQbjKdrc1AKQcszga5fWZZrvLl582dLgNcdi77GIsdQO9QB5Il9ri0kO8YRMHOIHbuoWtG7hX4a2l+FlbvEWCK3ol+0GfeVJEFXrVceqfXqLkJLFtiZ+oDvRujkrl5YbcOHA/cGPi+tMNJNaE44+PMXBytTbejq/2AiZ4VkcDFfBoHCmNID9+OC3PA6IV5k0vIlImBzmb0tvo43ObjmfEg2Z+fZ26ugPa2pIk+0SIrDN4cWFkbdtM3TQEilg7N8M6Mw+mqF7Q0E2c3qmLZR2uijCZ/wfirms/c3AE30YzJecdc6Clgq1ET3i7pvcgb7UhP4DZg8srM8nhQtFVMd8FumkC8ZxiLbgKuZyET9xDLTsJzYsgme4DjX2+qt/n+zWkbLU0xxFMxc6Mrn3vcRNXLs3MoT7ea/fn/2zsPIMmu6vx/L3QOMz057Mzu7K42ahUJkhEYyzLGJKuMbBc4ICegLOGEZQHmD6gAUwhjuzAg2RgwtikHmeBSUUXZlHFCAhuhtELanGZnJ+eZzu/96zu330xPT/cqsMvObJ9fVe/sdE93v3ffffeee+4537EH92OmGBfDPvAWczIZnvKxu886r4wYw1d4rtnFLKKujyINl3AMGSzAzc9jTvQyLUme8Utl+IUSklFHdhFm03vQmumThCgupLJOHE/PhLEtU5TKawsl6vOyP/tYXCyjO1lCb3QBqVQcNwyVYJfMgFd2Y5hadlCKt4vRwHjWkGN0ZLk4cJItWHR7cPQcvac+ruimpTqPXNEWHVw3O4Zt3S04eo5ySaYwA7fPWYa3L7aA/HRejM/W/QzZ4PXwkR8fEbmu4oGbcLicwfwc38uQGhsdrS56xNqm9pwLS9yeJnCRSWiML+a91Z4JIRbJrCw/8wUfIzQACi5iY6fhbN1vkjt9D+WJYZTPHsLA1lac8KI4NE6tXGMUtsRcCRlIO0tI9ySwo8cUiOAhcC36bBnS9FL3LhsDYiVm2apIWsV8TEzncWJ4WcINSuUyXDeEvdsT8KbGjLHd0YdSJG0MUy8HTJ1FYWIM5f4huHteCjdnCjIw4U2KJNiOyH3t6TeeYPZvhgnQU0gvPhdH2zst2N1MEDPGLhd9TIyLxGNos8NoTYaMvBU9peEIwmEuJsxnMhyHIRdcnHBBxkUUrxml6XiOLMDAdqHeM73zdjgBa8e1sHt2mNhf7kDE0yv6yu7AXvgdA0aHlrHH0cTKFqjVs0M8rl4hB3dhAW5HN5yK51IMyq37VzSRRY2kJsif96hEHFSk0c4HjcioGM/eyq4Wxw6Rm+vcIuMUKzSurEroWI4kxHEQiafEgGUxDiPJ9uyhVnLMbkgWIAyrYcKuLGxrwow4BvAz2WeCz+RikuMGt/sZenBuZA79meSzFkngAl0qRsZMQQ5+mtGSPf/7Am1vevgDuT9eYz7Y5lKlrMss0KS9Ga2mnlnlBaAG7UWGN7tlh1fq3q9JW2WGLrc8iznE2roxOW8jF0mjxQ2LY2w6F0NLuIC4l0WxTnwWBzF6YMPbrhRvi0jRcMDkNnv/rkoOti914a1ITAYLTjQSTyri/r4I7PsyqTGDK7ImVky2r+mpqiIo4zmfo37mWmsq0p7A6dEcxqdWV2/0UJ0aLaPgRTHUV8SBgYgYgjQY22M2tnQbjc3zIRNL3QwO44luqBBQI8vFCmWHR3yZiLsTBZQmjmJmckTOiYMqP8XqGEBPajsOLoRkW7cWliKmJ/n4mI+WiDGUJuaMBy4RSaE0cDUOnZpnWQxTdawEtGS2oK8jKvFyx8ddFEruyoTHbdirepZgsbRxTWIYJ8Hs/AKOzkVNJj0nJdt4OdiNWP70qsHGRtH8QgE+wxzsCEaXWb3JQpry+x5DPjyEerbDj7VhKW8j5PpI2HkURo8gKuESNsYKKSzmUjLBivEVKmN0wcXCchZeeTUjn5fvXA7o2dOBhLeAQq6E2WWz/ZyKF9AdCcGLpOBu241orksMZm4xh3t6MG+14fQ8g0sLUjDh6CiwszuBsyOLWGIs9vYE2udG0Lp7UDyGpZKHdMJB3F+EOzuJIsJww2FgdlQ8XzRmQtyZSA/hqbOOaLXCd1aM1oVxk8iVcE1cq+jw8rpTk7hUQDhSRlvKRanMLXxjgDHLmmEvLQlb5Mf87BzKxyl7tYq9/RpMzRQkDj7quqboREV67+RwDgcGbSTT9nn7OJMhWUSE/YYJX1zE8Zpt6/Kl3zFkQco3M1ky6iObLWJsfAnbMiXYTKGnyka0BfPzDlpjMSy3bseRCRrjnuk7ThxbOvYgUzgr8a5eLgd/fkriuVlQwrJdSRIMjJDa7We2xdGx+kUCFnM+tmaKKM5Nw+duFJPUIjGTYNXahkTclbhMGjW1MAv+sROVCmEh7kSY3REauTt7KAXoYsFqwxLVXejx8y0kKjH/MkaJgsj6HYqiZ2HJS2G+mMRSKQLbiyNJ5YyKsZRnqfFSTC5UrLwa27uU8zCftWS84Km2JYw2NRegjZCt2IH9yB59BkVJqjQ64smeXtjpLnhHvrM+HiG/ZHbBth2Q82jkHeXinwYk+xTv/9r7XRYjNaWzuUjgeMNFmNxrrknapdc32F2SkBZ4mJuZALY+950sFqY4X5W2evBa0fhtpFjD1xmCpig/CGrQXmRE2odeTg7w0QT85aq4LW6h0asaScAOhbA7PY3y6AnRnqUxtiXVgVj/AKx4DIWlJdkaroYDUyiRgpdblJW+UAl4LS/OwmECFLPWx06txhFGElKTXLKDyyWUjj1jDFwO3cxY7N4m8WeNYjA5IA11QUTSq6FxVkII49M14vAVRqeK6O5KIs2t8qiRZTp48CQSA1dKlrndQFWB0Du0WhEoJ4lIbEsp1ZqmLFkdy5NGRluPJMLxfdmShcNnXRR9ByHXQVt5QsTyCQ1UScxhvOvEGXT1tyLkdBvDgmU6pVqZ8S70tFpyPXe4EwA9gZ6H9pYOlNAL203h6IiD/i1t4oWid4STz1LOl8psNFjogaIxwomJXWFi3kI2No9YIV9XBWK56MgipLslJO1DjwonfYkzXTCxhzS4vMATI2oMFnIFkyD0vZPBNm8l2cO18corksDQtTg24WBxiuYoTXlf5N529l6JUtLG+KyR1Ang91014GB2waw+YlFHtrbZ3xjzzU8POx6GR4sYm5SyXitv7KP3pWsJ+fFhzEyNIbLzWowvWJiZLiBXLsKJhREJObJNLeoQlms8mFEHboQPF7lHv4aOcMTE++aXRelAKqHNjqFw/MlKKA0XjGWRu3L2vgzTx8yib+VYKgbF8GQI+wfCmDpdRK5sm8Qli1qhYezvYSIc8MQpX7z5ATQsrx0KkpssgEUUIilY9GDPT6AQ78HoyRJQmJMyti63fCuis3nXwXwhVSfn3JAr+Dg+zpLQ1c/6siXLbd7D54y0FRcVPJVjY0afszsJ9OIcikdPmStYOdxYVz/Kg3tx+On51fUzNWHLPk6OlZC+YjswPYLcM4+sWQy67d3AFS+C2yCee+E8me6pSBnF8TMonq2SyWPIw9w0rG174PZuEbWIWmg8PnPWqItwYVtdEY+LG8asn57itVh9nmPFzh7j0WykUVrdplQeyBdcTNHo7qRh52NmyRIN3CA5im3LogIR1xej/XRVqeHjLDrQxiIQHlINjFoe36GFbnQMpBDzqQPrye7EiUIC7UsFtHOcr6Ntyx0Ljie1joOV8ygyFMEsdoLdgpaEL6Ea5wsPoIojiwAE8Dx5/Xgeg+3PzQN8PiQRs7Kg+GHAnQH2VKPqd/G9txxPORYlEhsn4Ul5dtSgvci4pYKUzGR8FpOAOHCJtzYYEJhRy7itYgGhkafhFTzx6lkoI7Q4BuvkFEJbrkCCZUpdevfMfMrkGTdkSSymGK3HHjNFEiTeLyK1lWUSY0JYdcUsegVYFnX/TbLFTQmxFYp5KdFLY9ppkHXPmDkmo9CwnZj3RXYlFQfaExaW+PUMEmfppWqPMgsHMPGnRvanJKER5rMYX1ivUhiNtWSoJIUAfEqdBbN2OAZ3cB+cnu0oMZyjZrKwKqX4ZIEwfhJLHVehME+3mY2Wzjh8VuWp1ntkJaZKbKM1PYzrh7owOmdhnI6vStwZt0Ej1OE9c1CKDzBujtt8xbGTcBensLzlxehqdTAy46E3kUPU9jC7GEbOCyEepZePJXyNdA+vY1+SE4uPQjaPsOXCaxvEcqwL5S0OFlBEfHFYrm9Xi4sjo568Rwqz+aZdmGDHBCgathIPlw9iK31J0Hl6xMLscpBtb+BnTOfDWCi1YSlHbddggjZKF8cnHOxpaRFZtmrY7DQwdvc5yMRiWCw4kiDChUxnVwydKQ9ziwWMT+ZkEWeuk5mCz41l0ZIMIRRJYLljH05NhkXTtC0dRrtTwvh8HrFwBBHXli3/cNjC/u1xxPKTsMsJLJ4+jhAlyoo50Xtlhje9YNbkMJBdgh9NIc9NbUq2lQuI2D680RPIRPeIh9bEZVaOSQrbMYbXxWAn7zJecGN8UgIsGnbxyAlP9DhrDYsnTpVxw64Uile+RhZoS9kyQpT0usJBOJpCscRSSKvJiSttVypjqWBiGhkfLJX2Ktnf9FqOzxvDSxYFXCNUrhP7HidVCtCTaqPuKKuuRV2EJ86tu2cYbjExx+36CLzcamw9YWIfw0jyx1g4xayA6Kej0VeaGoOdOApr57Xyd7U0ykYnrc4yls+eqCPlD5Fxi2baGGi67jUuJqvVG9ivGUfK/se+xTCE2ox89n/uTnChy4VoPagAMTXLsrC82XIVRVYPp8bYz3g/1RTxYJGHCeMJP71W5U9gQiI9tclofSOaSU+8PqfzdEGvdUNnlzy0pHrgzpxe/8FBpY06cAFCY5bjE0OH6KXlWMnzZswpY1frbc2zj/Fc6sHz6GC4wXPPd1sDdwRZLlhUVZin0dEvMclMvpXXqQxR2Y0Uh0MDpZXnSr7IxYepHMYpheMnx+HUCym28xwIwrTYvizRXPJ7ZQxtTax69pWNixq0F5lwOCTSFpbbI3FaZRplrDbDmK1Um4QGeCNH5LnlrLcyaXA4EtkorwiHepsDu2CdeRohK5goKdl0lUgTlahtWjWB0khlvJabSJsBhfJL3M6W5C4WdYjBGz1ujOtqg7ZCeezEmkGqFg6i3DoMJF4CsrmKXDy9U8F2v/xJJXargVeARjJFuWlQBZnghJPV9i4LoekTRhGgmkJWztulR+mK6+HNTMhWsEhztXSJPBfLCnujx2T7nJ4fMbF8D6HSEjyWmq00NLVSLXq/pFa8Ba+lR7w7zB4PxjCpDb8MXNdXghdPS9tPZh2ZbFoHPYSxBJpyLFhxfeQMwBhGr4zueAr51iGMldrREnPEEGG8HA0aJnidnfLQ0d+FbLodh6djWJoX0wuWFUVbYg+GUh5OnjQxpxHbSFqFJVPcx+iMkTp76gxF+02jsaLW6KyFXb22GGVtcWBXH6uAmXYdrnieWJ0onMyYRDRZQVmwmcDoRrCQtzHQxvb3EQtxU5KyccAwdVlFmD0kyhVbukzjLCx7CLtFnJmi5VGlV1ZVZevcgotoqF2yY62YjbzHREAPYcfFtk4fZ+dtiUuuhC3ixLSDra3tSM4NyyTjhiJmW1fi0C347UNYDiXhtIcQKS/DYRUobjLYPgoLc1JBqr8ri7aWtMTbBkbtxJy3snXPeEz4tim6UKbkgIVCmRXZPAlBYduK3qnvS0gADa2lvIXh2RSScSCdNouh08tAK4uctCYxNzmLWNRFJOqiXPawuMiwDweRiINzM56EsQSJhkx+Gew0oQSMaeQilTsB7BsMcWDcM72zpiVXRTmDwgTDUx729G1FcW4Gdkef6L2ysIebTMmkLDGarikaIdE5lGZLRuDPHgKYtBhqgcfFprSNB6uYR2HkpCyGy8lW6Z+89ibkxEIyYq5lX8aXUsdMQpOdgkULdmFJ7q1KnEWgf2CuVakEi+NMqn7AtyzC2i3MLa1uj9MDzYUf71teH8Z78nleY8Zesx/OLft1DRsuPkanClIkwayrzDWkMcY2mJzLiNyZqfJkkmiXCuY8g8VDPZiNT+9uTNphLdLeDch5DkqhxNrJllXn0r0ohtNwkECs7K/zmnKHgJ7Z6lK0bBM6Enb1mvmhXm4B26ZGmnddeMgLSbiiY6Z07NE1zoPymXmRCcTWfSZOeOSoLCAE7pT07RQ1imfzqso9xqqFFZ1izjG857gbUb1zwf7BBeC+fhrlF9bA5DGMz/E7g99ZFthDYdgX731H2heVCM5XFxqOcYHDwiigqPH8QlCD9mKSX4Y9cUq0ZgljWZ2+HaYSDROaZsYkFIA1xAuzU1LasZZcyUJ0cU6UCpgRH3R0kyTmmWo59Vb4jiveSREDX5oVI9avJMbwrmESktvSWV+4mgMSPcgNDNpGxGWLOGIqm9XckOFYBPFo4+7GLV1OYozzCiYxZvs6hSWU6ImrB+N/F2dgMas3FmdJNZM0Eo5KKACzfykOni16cCwmzRhDZqlgozUaRyydQigWNR500aDskCSRWb9FxPDzpdUtSdGNDFuYK7jIJ6/AqXMm9pfarCPzQCYews72LNyRg5ifXRTvikR/LM8jPv8EBrcfQN7tlkXA02d9qRhFg2Z7j42iFcGxaRqG/D7GuPpi/HueLZ7E1qSRaTKGvjEV6C2gh4axvJwGWFqV72P/YLW3kxMO9m/hpAA8c87H/JKZvJnNbOLYLEzlQmJQujROZCK0YZeAnrKP7lYLc8u2xBFyoqeU2UAnKyLR+DIeY04snINpjLQlQpLYaAK1qy8SG8HBEtUsQhYKroNCzhcjj95h3/GxVDIJR2yzjpSHpfkscks+zrox7PHyiLZ3IpsexEwuhFAsDCuSwOlJT1QyWJAjGW1Be6KM4bPzSEQdbGnvQHp7C5KhFBbmbBw8Y64jZXcH2x30tRsDZrloSXIdDQAaN1vaLCR9/p2FUtlaKf8puxKtFgbajXoBM7NPjDGOHGCX5jYuDdvO9ihSqS7ML5v4RUbt9Gyl0oEniUUsjUpvZEUqVwwSxswyIebkpAlHWU388nHVVpa8Ndv83AJlGxklMCNnxHOyerZiObENU1LzwUZbTx8SUR/+OI1DG+FQBGUuBioasFJPgJaqGxbjnQsgniPluMJhF47EMls4M276bxD2z8UN4y/39tEo93HwZFmOiSE1Q92ubNUvc4RhciENW8bny+4RxxvKwplqWozLrVYIiYWMUc9+zL/hd5l2YSU04xVdDnEHwhhz7IusrtUdb2y0sRhDcXmZJrqEMpioCmOIcOFTzBextdeRBSo9wIEeKuXDjrFoYoNyBhxLGoVcnE8v1QmF1kiVefEMZhJDEtZQsOOw5h20xE04RHWZb/bLenH8vC4nxhmO4ddVf1lpB8+MpUEokiSbnT9/a/UYPd8UVrDNwo4efGp91w2bWJwWBZ/yueNrq7blFlE++SSsndfBalDIhrBi4disSXwM5OEo9cVjXxuGY+A4fmbKxx5qVV9Ar2kgh1dNOBKTueDgGe5O8Zi4oLtwHmIpe1+Jdeb9z+tED7TZBVWj9vmiBu1FggMAvaD52UnEGLBfzMOfHUOZySscWAf3m3rcywuwurcjR+FNSa9ZT8GKIt7WC+/MMytZuQhH4QzsQ5nGnniaOIkE4qd04dmSMU+lAxmDZWtxFUq8rKlqUw09rM+SudrIoN25LYlDJ6jZaiqaicM2HMGOwaTERJ4PTtI0Oqrx6Hmu9j7XwuIUxx+Dn51ffQ+LGHQPoWSFZBLkYbhLU0gnuzC/WMbUfBm7rtgG7/RB5IefrmTPG2Ms3L8TXtyWBCSJP7RWJ5di0UfBD4vxMbscGG5mhuOa4orYHOZnqe6wOutRp3UxZ6Eln8WpJQ/HJ1avAkMFuG3/kh0Wsvkysjkm6pnX+N3LJQsTVkg8uivGrHEzi4ICn6PUUbZKxJMTQi5L/d+oVKB65JgxVgm3RJ8e9hEZsmQCXrJM9ad84EEXh5olAurUBOY2X+Bh5QJjX7957b+e8czxMKQFRo6H4ZGx1hbka7RNBTeMaIRJhL6oBZgvK6PkO5LxPx+ykIn7aAl7SISKODti3F3LfhHF/h5MZ8M4eoYyUEB7PIGnj9ODaiEdc7GULWFm0cPUgoWtnQkxamfmgat2p3F22sYRGvyVr2R4N42q64Ys8VLRKIi4Rv6M58NtaIYAULWCpTxRMQKv6LEwueDj1KTZNeD5inayzQWn8aBxAtrZ7eDkiCdJdkHHmVz0sasvhLklTybMIKZVSg0z6awACRWhh49G3Eq3liRGY2gtZk0p2aC3SWnZMtCSdDC5ZOHgKePaYWnsE5MmvnJXn4OJJW6Fm8UhH+zDPM9drW3Izk6u0X6l8cDjy7S1YrEclrhriujTeKARygx0epAPn/UxPltaE6v6zHARndsTsmBaWqrIA64cZxmxRAgFO4anhn2ZrBmDH8R/UnyFoRU09KuNRb7Kkr/UaH2alXorcCHIkAAa1/u21BsQANfLSchNbdgMP9+vGOfn5tjHqwqnWMA1g6tJn/XgArRR4hIT9RqVeO3OOIilMvCyHVK5cC45hCMjvtmSDxsXK9ub9+aVg1xcmbYx6hH1v4+v8d6vB4+R58M+VZ2HlmMyZKSx1iwR9RkaWDOm9C37TXeLj+5odl3Fxao3ibHLyoU8vzXQEGaoHcuj1vE6ZvO+LPCrq4nRsGUIBxeQjeD4zPc0krx7IVTfn4QLOzo/bOoHsihL2eym8NhY1fJCGLW87hxrV66zZxZv/I69/Y11iJX6PH+rRXlOMBHJmx1HqVQWoXsaoGv2DEOreokFqTvb0/Czyq39sNOdcHe9GO7O6+Hu5Db7i2VbHaw2RbeLZAO5Zoao1Dxn1Z9q4fhqnO6t6wefCuLxfB6i4ivvsyx0tji4elcaAwMZtHdnMDjYhqt2pdHR8gIFmOXcGrw3mhRprmpjNqB87pjoVAbjRGnyLIZSy2hPu4hHbZSyy/CWFyt6jRU1CMYiz08jWZ5ddTAH+vE+kEqYZAsJC6mZaOjBzU9Pib5uPRYZjJCtbMkGVKok0ePVnlj/mbJNWtHlXFkdyIEZI9O81mDA8xvXbGe1NuqKrsj5VAweTn59rb7EnY6ya1QZ7PRGn5hgGEbVJBscikia+ehsdepWVGIGdkfKEs/lCqxa57EMLiWugO60h8LSgqgbBBTLNrKRDpycMLNMG1U0KrGBps69JSWbg+1ZD0bTmH+xWAxhaoFlU40xLg92JYvxhSYphkYVt6fpIWKsHncJzs1S/7Sypw9TpIDbnmJcJYHTE8b4E/3OqsRyTnQlz0bIyyMR8hBzy4iHyki6RZybKsGm8kEd48SqLGxqo3H4pzSiBzvWLkQD+Pe9GXqfPRPdUymOwT/mtinbh0YozztYfJA0h6FUO/L+estMNInbtmFsOSqTaiCgz3OlrB4NHRqUFQnllQd5eiKC6JbtsiUbHK+pkmch1jcI6kkE7VTtdaMRwUk9KLggGrSVghMSS8vqtnVmKXq1Ghl7tldCb0v9FxkbnIy7EmNa/RdsukdPcYfIyEjVa2/ubjSStqKRSEO99loxVrWv1YJDnd+hq+HvvAFnc2lRZhDlmSojj/2KC66V86jkOdY9x0qfrnuOtslJWD+emNCW8zk1aSgyhIl9kkZz4LXkwqhBqK+p1sik3QbXQyQrGzglqK1drzQu+y8X1Iyrrvud/OcC23q1x08PdW3lTsJ+ycVLoAn/gyS6nZmun2hJ54NoPSvPC/XQXizo/QwyiOkdFcPTKAuIN4VxrrzRC1m4cWpY7YazMIcy65NX4Wa6gETGBP9zAKwJAxDDlNVyGMIgcaGmCAJDDJgwRS9srQoAt3+kmkw0gfLZI2tGPh6n0zNUt+DCczVqqWSQTqwvn/mCPo9qBvQyT60PO7CTraIBWm/QpxwTE4aceALlZSNnVjpzCP0tbYgNDCF38izK5RAiUcawmZm75Nuw4cKeGUZXqgsjs2tnNnohOQjVMyJF9qvsrBomVQaxE4mKzNnqSVX91zITR6hBtSh+H42CauMyQEoDi/eg3vmb7/GrjiP4bhp/9ERe0W0yvWmgc7JiWMH2HgsPHao6zsBJKyGm9FSardlqgXz5eB+YnStg19YETo5FkOe2Ntcc8QiGumzkilm4ThQFu2oiqBhENAaWlvJYXl476cXjIbkGDMmxs4sIhV0xPoOQC/FQMaGrUuB0Qcp/ulKhjlv5klpZseakilNlPRF4tpg8s9JevgkxkLWmY0rLsnAEPbA04kxcn9lyDC6gXDfHGCLs9/w8x7WllK+IgTFcIRyCFUlLPDY9Z9WJXQiMt0qiX1XJFfk/Y1bHZ8u4druFwyMmPIG0xCzs3WJhdKYsSYk+j6lyfjyB1qS5rjyn3b2rn83YT4Z1PDOZRN/Q1bDPHZZjleMIhaQQwYl8Fxi9Uwvb5eQ4PayWhK/UwkpXy31bkNjmIzY7Dq+Qlxh8q6UTs2NTiEeonGCKFtAYCMT9aRwEC6tKbt5KjDB/sm8yeY5e7KDb8F5j2Aw9iPT41lIKxRDLn8POvnacnvCMw4DtGXcx1BvCyDRzFdbfb3yGyZXXDQHHRk3MPL+SXvIreqg4gYawPzJcin9LWUKeE6vDsW8H3mheq5IbxXKJi+f6n8P7ivkEcrxR44HkgqL61g+qqwWe3FokZGOZHmyTcMiFbThkdhFopDEOvHYnjLBvMwyinoE1lo0gyXloab2XluOhnemR+O26sCx0nfmEYQ1c4DSCnvKelrU7FwEMS7jQZXGlRlHlXjQ7KFWLi0r1zWrDnyE/3JV4oXBc4XVqBMda6k0rTWLQslrFPffcg3/913+Vily/+qu/Ko8NAY3XKkkTSS5hHXjGIBULcMJReNSNtWypLe4mkpjrvxrxwgyshTEZ3f2WHiw6rehqJN7HGy2VMYll507AipQqCUUOrI5+GWT4ORTo9+anxMgWYzaeNnGmnHASrfAo6cXEDXoNRLT8+cXOXkwY88tKTOVSfq1hzuS2dAesifrxtSKdX/YQ6uhD+czRlVKdrNZDLx1DN7xSCVmxhVatvqjjwy6XkAxzElxr0HKSMrGlawu+8f+cdJyubpSpnlD9WsWDEYrw2leVuqr8jYnRZEJI421OZlbT48LB3/y98cDQa8pM/Zk6jnZu1zHOtDKVrjGi6cnjVv9s1se2LuORokHLMAp+PgfaNQ250jpAoWhiamuhgVAoFNG6eApXdrQjb5m4zYg/D2fkGCJduxAORbFcdCuKA2Zm5mTfkfSxOLfe/WNbTC7yJW7ZcZkQZpLpaL/VcxbRSM9KrKmJe631wAXnEExa9Vw8Qcy0U8hib38Mw9NUEzD6t57PuF9TUIDQkKWRyp9cXEjbWXGE0iYRU8Jh4CBXstFmCvTVJZO0xFNDLz+3hPk5nMTZ3xZZ3CC3hH29YTiV4iilQhFevozpJaNPDDtUnXspXmqGF9BYpKeN52uKGPjys+ABT0xlkElfh+4uLvY8LPoRnFlIiJG+o8HmTL58frknVmObOnEakZYW0QMuFkrIHzspJxSv2mVhvw2MJvYlGibi+a0Ya9Vwy5XHTQlfMcwrCwD52eCesewQvFQn4qeexN5MryRksTc4S2Owcy1YKPRX7XxUvc8yBiVDGV60gwsccz/QcJRF5bNApwNDUs63FS25iOzDDbydgRYu4fcOdZpQF+MtNO9lGMz27oqMWx14L3NxxgUWjWIaf3wvPeP8mWGgeIO+X894JPNZB8X2bXBZhKY6TjYoUpFuFym4uu3SuaV+5bIaI3FdW1T6xrrPs8z49oNKj9XCaXagw4QU1UIJvdrEvwvx7dLfG+006P55cxm09957Lw4ePIgvfOELGBkZwd13342+vj68+tWvvtSHZmptd2wBplcLVfOmloQw6qi2dEkpRhqQlJdqoRfXimN0JoZCS5/cLXRydrUyiec8A6QTMtqxLYzPMhaPfGacklJmW1GM2DpB+XI8yVbxdG5kWBXI2nqlKWcbVAuK8vxYUjVhqq3VvodNlmrHWa8fHTsycEpm8cDSplMlJu+0olQn3pOFIOIdLUjEHRnEgkQFbtUxbo9bYNUexmpvglRa6hgEzp1a54VtaY3iFKWZKlv7q++30Bpn1nhZPDqM7QzgNn1vuozFLGto0du2aqQx9paeoM5EWTwxVDbgBMxtc3o1OpNlnJmsspqx9ngof3Nk1GRMm+81h8PYMFbenanjOeC2/GC72YKvHc2ZYNTTHkH5qadhlfKIhcxeIa9X2Qkj2r0NfW22JBFJm1Zqx/O7OEHG3fVbkq5flmx/hmQUfXqbjCHPEqEiMu9Ya+KV01EP02PG/ZqM2yjPrZ8txFPJkPbSebw0NjBXcGBNLKHkRZDlNbEco1ccNclgNBrEaxMYi44xNGjYMwGORi/nowiz6GE8iTSWquMzeR2YCESFCmZR8zO4lW7CCUzMKxPVCsu2eHbnZugK5iLHguOZ/sECALy8qxG21CA27w/igMVxa69673gsNHRPz4ZwuqogAY0l9h3xCNYgAim2EeKvR1uLg3BxHjnq7s7OGDWqwGiNx5C1VvU8afQFCzgaiqy8F6g5VMMKgvTiBcdWaxKxHWi0sV25PcvPZJswKW45lEFk8ADsqdOwJ7jItGSRX0x2Iea5mOC9WGdYzaRMZTAuiJ6LEft8Caqg1ZMoJDz+gCDxk4YWY1oLFY8gY+q50G2UCS+VtiqLtnoGKpNbny+8ClNeK7axZPDEGVNWnLJdbb3yEH3o1h74zBGpgoU17GTF5VwD25jXeE0oUhX04jMBkPcj46x5PvSA97Is7kXwubA96WXnIpXtzTGXKi9MemXbV++u8BrS6/2DwO/JJM3uRj260ho/2zQG7fLyMh544AF85jOfwf79++Vx5MgRfPGLX9wYBi0H0M5BuPPzQJ5ipt7Kapb1xOsZmMxwTdKDUplsjYD+s3dqqZaTaAX4uEyh3I4oNtTA8Igy9XRrCYURybQjN+7gSJb7kqt7kzSkOvu2Ijc1biSr1nyRg3BXPyZGObF76OIEYxkFgvEis/9dEXWnR43bToSxlIMd9DbaWO7chlC8HdbsOaBcgJ/qgJ9oRzjkoD9jS7B/kJlrssuZ3WyhuJhFX8qG2xGuCP0bfdo0J9dowgilj5mtTMYU0kPBmD27WMDk6DzSsZCpcFUqY2osj+50GvsHEvjfI55kylfbdaxaRc3VXsa82quGKk+U8lwsz/q9E1UxipWfYYeauMDZGSpHrG02Gv/JiAdrYB+8c8dk8SEk2kzoSzSFsTFLDDpOVEHSCo2v67faKC1NIrEljdlcRQot6iFankEolpbzml7wJUnpwKAlW+9MtONnRMMO8nlTaGB6ZkFCZdxYXLxk9GIdPL3WG8Z7iqoC3MIOPNMB/J1tyvbN+xFM5MNyXkyuYtvQ0KNHXJI4+N2BV7YI7NpqDFtGWkjFK1NzQs6PsazcOmb5Tz7YBvwuGjc8HiolUC7q1PzqsdJ453Ey2ejp2TDGJ2ioVyTXZhgDHcb2XkqfBRMtC2OY93P8oGE6XJGg4vcE8Za8plyYUT2AcdLBNRYVBJYg7TbnV0uQfZ1JWGJwV8cDM5Rh3xYHVtarhECU5e8ZdcWQi8SOvTg6b3aZ2PVZnCSQPuKx0YtIGaaRWXMuNMjYTnyNRivvmVoNXIaE8B45OMxKaKvPUz+Ur/FYj45m4CVbkGrJoVAsY9FPotO3pLAAjf0gRri6b3ABcTFkmQI4njNLngvX2oUDvYO1urpUhGCoAMcserbZb57NM0kDuIcLmlVfypqY3kaJVOzP9ObWhhMFUKGFzg+Re2ShIM5xlaQ2wnnN7+iHx0I93E1hYZ/YqmOlHlxY1/tOqWyWscRDz3uwp9WUGb/YZXHZtqaf08vt4/RoUUqhy05IBS5Su1qMpN8Pgl1ZsNCgr1XsCEoTK01i0D7zzDMizH/ttdeuPHf99dfj/vvvrwinbwB/vRvGKBLYtWuXyJ2IR5SexZoyhbWd/AeJy2k2qDkLqj2MHa/oH1rikXb6d8JOpLA35MtWOr2CnAc4EHEAde0MWvdfh6VTh1GcN8ZXON2CxLYrEEq34kCohOklW4TNOenT0GFSUDJhpLCYTMQEEmLi5bjzS0XJMpadDPLxNtna57ZZImLkrZixfeMuZtAbGSnKP3EVzvdHoiH0uQVMzi3Ka7Eo0N3uYiIXQQdj+HrNwG48k8ZgitieGMcHrkhibqGEpVwJ6aSN7b0phCOWGIUv221hbM4YBZwc6N2hR/T0lCPxkJSLYZwovYQ8Fm79pqNlHBh0cHKchquRiqIhQz3bVmsO1w+lJUmE4vU0lPoyphRrIhJGMUG3ytDKfjB1kp1kCm5LK/aHTVwqjYmgTTlxHB9zsKNzCzA7ha7iSEVsvgWhti6Jo7160CSm0EtDZQJqE3Py5STIkIVMIoSZRe77p9CfsaS4RSZpIx4qIR21jQFe8GVCFg9MmElswJUD1Jz1xWtJI4BxiTQyaLRfu83EGvK60XvK8+VhMVGL2ce8RmwrGr9UFeA1ZjLd9TuMFBg93DRUr8hU4ux8M3kFYR0cntoSjLH0pSKbiOaHa5PCjAenCBvJOL1ExjPOilusMsdjpYF/ZtIXnWRCQ5YxmAxP4Wvsv6JvWTFY2YdaExau2uajcwY4M2niVBkfuq2T94aPnd3AcSa/VbLsxfjmQqDbQiLk40f2MeHORy5PPVNbrmE66WAp3I70gRejOD8NL7uMRCIJP5HB8fmELIDYxvyO6omaRgHbm0mFXOg49MpST9g14T30JjLznzsScr0dcw+z3ZjcWG3MBnBxwGtNmaWFnIPZpTiKxQW5h7gbQTvkuiFTZjkwKnntr+g1hsTFhjtu7EOMAZ7LmqqBvCZcEDUyVhlOUy/Upx5sU/Y1x2ZhBmO4m5LJ7BuNK4zxu2lULw6bhXM1VH8IErS4aJSEttrvlRK87bAZfvAc4Y4S23120ccoNxjZF1NGh7k6Rvh8VdEuBmyLRNhD3J5DpjMmDgUeG9uwPXn+XdPnA/vj/gHumJhEPA6bHE/ogb8YOwSXO5vWoJ2YmEAmk0GYddwrdHR0SFzt7Ows2trWe/PqwRKsFwt+9nI2i3IoJuU4V5KNL+J3bhaCdv+B25+zU1uvlPmlNJr8Ho5LWAc/m4ZfdxroqngFVzZnOWlmOpCiEgKr21S8DU44JCEFlBjrjzJD2YjE2xUDjYslluPkYMs4NXoNaIjQoBHNTisEFoJNhgtGtshxpZQrDSJunXPBQhkoGgn08FI6iNtq04sxkXcbzOREMzdXdnBoJibeL351zGX1L/N9TJ6JUE9UTihKnSJ0uYwZ4CKOe98ROK4jm8P0gLRGqQ3KRJRKTGfRxTaJqfSQiXsolk0BiYjrwfXyKJ94HMlkBzqHdiBPLVx6I/0lRIYfh5doRXpgrxglg+0V+Xwq08vWtiUV8Zx0m2lTvhqJw2chD24XRk08qhTRqGixUjZsew8NvBhivVtQ6uyVi8N4UWqbcoubgzs9eNs7Gb/qi9RWPMIFRSA1RkPERtmzxQAV76DnIRy20RE2EyQleILYS7ZFX5slWro0jDlRc9Knwby7z0IqQiPDhHcwiYpeO3pZqclrtj0txJhFXiEaYhU3szhgPDSNUHohTdyiUUggW9q4aDBb6QYubCyp6sV+yklUrm8llIFXl59JGbFFWGu2OHlsLAnLcBW2D0MMyqUyip4jWsE8r+C7aCyzv8siKGRGoXiICg7UejXyb2xrGkCE3lF6uCcWjDFMLym/IyZx5cZYrC2qwnuN31lKJoBI0uwy2MYY3k5DqCIYH3K8ddnyvC70WuaKJklMqqiFeD/5MlTSmN6SAfpbV+/hbMFIqTVKNGcoDT3cDGlJR8o4NHEa8dBuphNK4/W1mgWFZNhbFW+564uW8w9jdKYRy4UAH4ZVNZELAduUbdaRrN+mjcbhVIRhRya8h4s9jj3sy60xXk/vokxdTLalV5T3Ka+n2U1Ye5yXArbJzOQ5HOjtQFfauWjHxnGdmsscz0wc+YXtCxt27n4B33nZGrTZbHaNMUuC3wuFOsv2Bjz55JMX/NguxXdsVi7XtmGSIiWCcrmc/PRig1J1hvzfbCVJsDIbZ5eBq4biODScw9nxYLb30J4qIxXN4TCt3h8SA50ZWKNM7uDjiZW4xXzl4bb5GM0elpCfzUw4HMFAWx/mcg6yOeNh7UwWMXLyHE5VqsiFmPnvupgrlWQ3KBaLSXuMTubEYK6mrXsr5udNa83WSdKbCdmYHz29bmzKdPZjdi5SN0nIZRKpH4JXzGN+Ye2epOuGEAqFkUUB47M18R+V2FQnv4C5mQaZ58+1D9s2pqYLGKsNzbnEtHcPYm7uPIVaLBuHZs7KPHG5jzUXgtq2iUSiSEdj8AseRk8sYKSRZlcToP1m87TLpjVoI5HIuskh+J0D8XPlwIEDdeuWX6hVBS/6xfyOzUqztc30ooX5qgSmahgXRqmzG/aGRJZqZnYB7ZmUbEE6dhIDfR0/vAMtFVFeOAc/t1jf89O3Fen2flwufWadNv8L1Mmhp3k8uz4WLqCvk0Up9q17nobsgte4dCpjaOeXHSmzWwu3qfNFvhaTxdHCwgJSqZQslrh9v60nBWtrHy5HuKswWfAlZrkeW7oZzrO7Kcea54O2TWO0bTZOuwTfedkatN3d3ZiZmRHPCb0oQRgCjdl0vdG/AbwgF/ui/DC+Y7PSLG2TppIB9VbrTMBMYklETcx3yCnj5OFjGOq75tK0C7+zd7uUrFxHOCbxcUH4xaViI/aZuMSneit14Ne8FjF15+uJ8vM0Bjp8qRJVu9xhzCRjYmcWTdznmvfZJtns0Mja12jMMq6aIRXuDznu8IcJ240hL4fPrV8kMmmHxn5te2/EfrNR0LZpjLbN5mmXDZA59cLYu3evGLKPPfbYynOPPPKIrBo2REKYotRsATM+kwkwQZIus6p39pgkl42E3dIJZ9sBqcQmWLbIzLnbrxbFBaU+TLLj9eR1JbzOjA3kdWfySyMY57ynn3JT5neThGeE8WmY7e03+qYBTGrka4wb5k/+HsC/4983Q4Y0Yy539TIT3vxOw57P7e0z2fGKojQXm9ZDy3i2W2+9FR/4wAfwR3/0RxgfH8fnPvc5fOQjH7nUh6YodWFmLA0eZiBLJrezMTNZKQPnUF8y1Qa/QB0qy9Sdb1SCWBGY1MUEmkzCl2ILkkwn1YfOf435Og0xGqFBaVkmWAXybkwyY2WnoOgDXwuy4ZmcxYx5KjVMTZXQ270x+9TFgO3DBSIXBIGSg9ERbo7zVxTlMjFoybvf/W4xaN/ylrcgmUziHe94B171qldd6sNSlPMaL+cp/LahsEIReSjPDxqUgZf2+UDNUcpVPV/ZJhq38bCHw2OnMdD73NRdLico6VRdYUtRlOZkUw8D9NJ+9KMflYeiKIqiKIrSnGiwqaIoiqIoirKpUYNWURRFURRF2dSoQasoiqIoiqJsatSgVRRFURRFUTY1atAqiqIoiqIomxo1aBVFURRFUZRNjRq0iqIoiqIoyqZGDVpFURRFURRlU6MGraIoiqIoirKpUYNWURRFURRF2dRs6tK3Pwi+78vPcrl80b4j+OyL+R2bFW2b+mi7NEbbpjHaNo3RtmmMtk1jtG02TrsE3xXYbY2w/Gf7i8uUQqGAJ5988lIfhqIoiqIoivIsHDhwAOFwuOHrTWvQep6HUqkE27ZhWdalPhxFURRFURSlBpqptNlc1xWbrRFNa9AqiqIoiqIolweaFKYoiqIoiqJsatSgVRRFURRFUTY1atAqiqIoiqIomxo1aBVFURRFUZRNjRq0iqIoiqIoyqZGDVpFURRFURRlU6MGraIoiqIoirKpUYP2IpDP5/Ge97wHL3rRi3DTTTfhc5/7HJodVmZ73eteh+985zsrz505cwa33347rrnmGrzmNa/B//zP/6CZGBsbw2/91m/hJS95CV7+8pfjIx/5iPQd0uxtc+rUKfzar/0arr32Wrzyla/EX/3VX6281uxtE/DWt74V73rXu1Z+//73v4+f/dmfxdVXX403vvGNOHjwIJqNf/u3f8Pu3bvXPHiPkWZvH47B99xzD1784hfjR37kR/Anf/InK6VEm7VtvvzlL6/rL3zs2bOnqdsl4Ny5c3jb296G6667DjfffDP++q//euW1jdg2atBeBO699165uF/4whfw/ve/H5/85Cfx9a9/Hc0KjbTf+73fw5EjR1ae40B6xx13oKOjA1/60pfw0z/907jzzjsxMjKCZoDnz4k2m83ii1/8Iv70T/8U3/zmN/Fnf/ZnTd82rAhDYy2TyeArX/mKTML33XcfHnzwwaZvm4Cvfe1r+M///M+V35eXl6XNuIjmJM2FACciPt9MHD16FD/2Yz8mi5zg8aEPfUjbB5B2eOihh/DZz34WH//4x/FP//RP+Md//MembptgQRw8/uM//gNbt27FL//yLzd1uwT8zu/8DuLxuJw/nXScn7ho3LBtw0phyoVjaWnJP3DggP/tb3975blPfepT/i/+4i/6zciRI0f8N7zhDf7rX/96f9euXSvt8tBDD/nXXHONtFfAW97yFv8Tn/iE3wwcPXpU2mNiYmLluQcffNC/6aabmr5txsbG/N/+7d/2FxYWVp674447/Pe///1N3zZkZmbGf8UrXuG/8Y1v9O+++2557oEHHvBvvvlm3/M8+Z0/f+InfsL/0pe+5DcT73znO/2Pf/zj655v9vZhn9m3b5//ne98Z+W5v/iLv/Df9a53NX3bVHP//ff7t9xyi5/P55u+XWZnZ2WOOnTo0Mpzd955p3/PPfds2LZRD+0F5plnnkGpVJIVS8D111+Pxx9/XDxPzcb//u//4qUvfal4Aqphe+zbt09Wf9Xt9Nhjj6EZ6OzslG10ehqrWVxcbPq26erqEk9AMpkUj+wjjzyC//u//5PQjGZvG/LRj35UPNM7d+5ceY7twnawLEt+509uEzZTu5Bjx45h27Zt655v9vbhPcT7ifdQAD1sDHNq9rYJmJ2dxWc+8xm8853vRDgcbvp2iUajiMVi4oEtFos4fvw4vve972Hv3r0btm3UoL3ATExMyFYpb4gAGi3cducN02y8+c1vlq0K3hi17UTDpZr29naMjo6iGUin0xI3G8DFzt/93d/hhhtuaPq2qYZxW+xDXCD+5E/+ZNO3zcMPP4zvfve7+M3f/M01zzd7uxAufk6cOCFbx+wrt9xyC/74j/9YYkebvX0Yd97f34+vfvWrePWrX40f//Efx6c+9SkZd5q9bQL+/u//XtqB7UOavV0ikQje9773iTOKcbI/9VM/hVe84hUSN7tR28a9pN9+GcKYyGpjlgS/c2BVzt9OzdpGH/vYxyTI/p//+Z8l8F7bxvCJT3wCk5OT+MAHPiDepGbuN1wUMyafkwy9J9U0c7sEMI46aAd6+IeHhyVuNJfLNX37MLaRiZb/8A//IPcRDRL2Izoamr1tgsXQAw88gF//9V9feU7bBbLjwZj0X/mVX5EcmA9+8IO48cYbN2zbqEF7EVY1tRc1+L12Emr2dqr1WLOdmrGNaMwygZCJYbt27dK2qeLAgQMrxtzv//7vSzYtB9NmbBsml1555ZVrPPvPNu40Q7sE0ANJFZWWlhbZAuXWKD2Qd911l2y1N3P7uK4r4UxMBmM7BQsAeiWZBNXMbUOefPJJUZ157Wtfu/Jcs99TDz/8sDhYmHzKc+ZYzDZigu7AwMCGbBsNObjAdHd3Y2ZmRuJoA7ga5oXmNrOy2k70vFXD32u3MS53uOL9/Oc/L0Ytt0lJs7cNz/Ub3/jGmucYL8o4LsYeN2vbUNmA7cLwCz6o+sAH/9/sfSagtbV1Ja6P7NixQxZDzdxvCM+fBlpgzJKhoSGRZdK+A/z3f/+3ZOxzMRTQ7O1y8OBBWexUG6nMX+BCaKO2jRq0Fxh6Bbgarg6OZkA+Vze2rc0dwJicp556SrYDq9uJzzcL9LhxC5B6kNWegWZvG24VU4qL3oDqwbWtrU0SEZq1bf72b/9WDFjGQfLB+GI++H+e/6OPPrqiK8qfTOBohnapNkqYgFrtwX/66afFyGW/aeb24XnSsGeMcQCTfGjgat8BnnjiCUlqqqbZ26Wrq0vCVKo9sewzW7Zs2bBtoxbWBYYxSbfeeqvE/PEmoUeFhRWoa6eswi3A3t5evPvd75bYnL/8y7+U9rrtttvQLLFJn/70p/Ebv/EbMtnSix88mr1tuPjbv3+/JBNSV5RbXvRgv/3tb2/qtqHxQY9J8EgkEvLg/5nIMj8/jw9/+MPSZvxJw46JHM0CPdX0Qr73ve+ViZf9hprgjIts9vbZvn27FCjhfUMlHhr/vHfe9KY3NX3bEI4l1aohpNnb5eabb0YoFJL7iQuhf//3f8f999+PX/qlX9q4bXNJRcMuU5aXl/0/+IM/EL1M6op+/vOfv9SHtCGo1qElJ0+e9H/hF37Bv/LKK/3Xvva1/re+9S2/WaAGJNuj3qPZ24aMjo6K9ux1113nv+xlL/Pvu+++Fc3DZm+bAGrQBjq05PHHH/dvvfVW0cG+7bbb/KeeespvNg4fPuzffvvtMvay3/z5n//5Sr9p9vaZn5/377rrLmmbG2+8UdumCp73f/3Xf617vtnb5ciRI3I/cRymPi9tmY3cZyz+c2lNakVRFEVRFEV54WjIgaIoiqIoirKpUYNWURRFURRF2dSoQasoiqIoiqJsatSgVRRFURRFUTY1atAqiqIoiqIomxo1aBVFURRFUZRNjRq0iqIoiqIoyqZGDVpFURRFURRlU6MGraIoyibhy1/+Mnbv3o0HHnjgUh+KoijKhkINWkVRlE3C1772NQwODuJf/uVfLvWhKIqibCjUoFUURdkETE1N4eGHH8Ydd9yB7373uzhz5sylPiRFUZQNgxq0iqIom4Cvf/3rSKVSeMMb3oCurq41XtpcLoc//MM/xPXXX4+Xv/zlEpKwb98+DA8Py+vnzp3D29/+dlx99dW4+eab8clPfhLlcvkSno2iKMqFxb3An6coiqJcpHCDV77ylbBtW4zSr371q+KttSwLH/rQh/Doo4/is5/9LEqlkhi3gcHq+z7uvPNO7NmzB1/5ylcwMTGB973vffI+vl9RFOVyQD20iqIoGxx6WL/3ve/hlltukd9f9apXScjBI488gqWlJTFu/9//+3+45ppr8KIXvQjvfe97V9777W9/GyMjI/jgBz+I7du346UvfSnuvvtu/M3f/M0lPCNFUZQLi3poFUVRNoF3NhKJ4KabbpLfX/KSl6ClpUU8rny+WCziwIEDK39/7bXXrvz/2LFjmJ2dlXCEAM/zJExhZmYGmUzmh3w2iqIoFx41aBVFUTaBQUsDtNooZUgB42pvu+22dX/PMIMAhiDQM/vpT3963d8xJldRFOVyQA1aRVGUDcyJEyfw/e9/X8IIGC4QcPToUfzu7/4uTp06hVAohIMHD+KGG26Q1/j/gKGhIQk5aGtrWzFgv/Wtb4mm7b333nsJzkhRFOXCozG0iqIoG9w729raip//+Z/Hrl27Vh6vec1rsHPnTjz44IP4mZ/5GXz4wx/G448/jscee0z+T5j4xTCF/v5+3HXXXTh06JBIfjHeNhaLwXGcS316iqIoFwQ1aBVFUTa4Qfv6178e4XB43WtvetOb8NBDD+Ftb3ubVBC7/fbb8Y53vAOve93r5HV6bmm03nfffRI3+3M/93Py+o/+6I+uSRxTFEXZ7Fh+dbCVoiiKsun4xje+gRtvvBGJREJ+f+KJJ/DmN79ZpLxo1CqKolzuaAytoijKJoeFEr75zW/irW99q8h4fexjHxOtWjVmFUVpFtRDqyiKsslhghh1ZumZZWgCjdn3vOc9qmKgKErToAatoiiKoiiKsqnRpDBFURRFURRlU6MGraIoiqIoirKpUYNWURRFURRF2dSoQasoiqIoiqJsatSgVRRFURRFUTY1atAqiqIoiqIomxo1aBVFURRFUZRNjRq0iqIoiqIoCjYz/x8mkT+GYzpQaAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "sns.scatterplot(x=\"Age\", y=\"Fare\", hue=\"Survived\", data=titanic_df, palette=\"coolwarm\", alpha=0.7)\n",
    "plt.title(\"Fare vs Age (Colored by Survival)\")\n",
    "plt.xlabel(\"Age\")\n",
    "plt.ylabel(\"Fare\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "887c24b7-3459-49fa-897b-544cb6f3e344",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wO378+E2PK0PEcpOwlPbdaKg4KCgITZo0UWuZZYjZOW8sc70yAiCPS3rHcsufPz/GjBmjhskrVKigjnvp0qX0Y8lwOhGR0TGENQkODlZBLPOrTo0aNVKB9eKLL6q50vXr1+PNN99Ehw4dVJAGBASo++3ZsydTkDpJcdPvv/+OkSNHqiIoqZJevHixmht+/PHH1X2qVaumwlDCWoaJJQhl/vZWJFA/++wzNG3aVAXoze43efJktTxKTiqE3L9Hjx5qGF7miWX4WR6jtE+WVMnwdvHixVW7ZUheirOk3URERscQ1qh79+6ZNrqQ3uKnn36q3n/wwQcxbNgwtRxJ5niF9GZl6ZBULjsrpbMOc0+ZMkUtc5LqaAlvCc6nn346ffcpmXsdPny4+njnzp1VT1iqkW9FhqSl5561KjqrFi1aqGNmrd6WZU8yTC7V4fLYpHcvw+fymKV3LsPdcjLQpUsXVYgmxVlEREbnlXarHSCIiIjIJViYRaSLnP9KUZzzPNhqddyux24HUlIc98143ux8P+PH5a0Utl1nGVs6KZaTY8p9pdbA29vxlojyFEOYyFUk4CQ4LRZHyDklJQGyWcvBg8DJk4AU4t3qJkVrOR20ku9ZoAAgS95udpOivVKlgDJlgPBwqbD79xgS1HKicLMTBCK6bRyOJrpTziVezqC9fBmQdd0SsocPA0eOALKVqLyVW2ws3JoU3pUsCZQuDZQrJ2X7jltUlOP/zsK8rI+biHKMIUyUE7KPtwz1ytCtDOlKyG7aBMhVqpw36d0amfSaa9QA7rrL8bZ2ban4c/SUnb1/53NERDfFECa6EenpyVCy3GRJ2PbtwJYt/4at7JN9g8tKmo4sn6ta1RHKcqtZE7j7bsfQtgxpy409ZqJrMISJrhe6cXGy9yawYgWwapXsHpLzOVmzk+exWjWgWTOgeXNZvyYL5BnKRBkwhMm8MoauzNMuX+4I3ZUrZUcU3a0zpsqV/w1lufRlWJjj5EaG9hnKZEIMYTIX53xlfDywZMm/obt3r+6WmVP58o5QlqtydegA5Mv378+IyAQYwmRsGXtZUjA1Zw6wYAHw++//VveSe/D1dfSQO3UCunWTC3D/uzyKRV5kUAxhMh7nJhTy4i09XNniU4JXiqrIM0jo1qrlCOTu3YFKlRwnU/JxmT4gMgiGMBkveDdudATvwoXA/v26W0a5QdYnOwO5YUP2kMkwGMLk2Zzzh9LjlctCTp8OxMTobhW5kmwi0rcvINfilvc5h0wejCFMnkd6QTLHK9s5yvWTv/mGQ81mJL3gJk0AuUxnz56OvbJlRITba5IHYQiT5y0pkvW7X37pGG6WXhCRbKUpQ9X9+wONG/97okbk5hjC5N6kGEd6NqdPO4J30iTH/stEN5s/luHqJ54AihX793eIyA0xhMk9Oef5ZJj5nXeA+fMdL6ZE2SW/Pz16AMOHO7bSZO+Y3BBDmNwzfBctAt59F1izRneLyAhk/fELLwDt2rGQi9wKQ5jcg/RSpKhmyhRg/HjuYEWuIZdjHDbMMVwtvWIOU5NmDGHSR0JXyBaSH34IfPIJcOaM7laRGRQuDDz1FPDss46LSsjLIDcBIQ0YwpT35FdObrKed/RoR++XlwQkHfz8gMceA15/3XExCVn2xA1AKA8xhClvSXHVxYvAa685qp2Tk3W3iMixxnjQIOCVV4ACBThMTXmGIUx5N+eblOSodJ4wAUhM1N0iomsFBTmGqKWiWnrJrKYmF2MIk+vDV3q///sfMHYsEBenu0VEtxYS4gjioUMdvWKGMbkIQ5hcQ5aBSKGL7Ocs823cz5k8UfHijiFq2fhDXiq5tIlyGUOYcpdzQ4Tvv3e8eB04oLtFRHeubFlgzBjHHtXc9INyEUOYcnfJ0Z49jl7D2rW6W0OU+1q0AL74AoiM5JImyhX8LaLcGXq+fBl4/nngrrsYwGRcK1YAVasCL73kWFbHC4jQHWJPmG6fc2P82bMdFaWc9yUzKVnSUenfrRsvEkG3jSFMtz/0LFczGjgQ+PVX3a0h0qdNG+CzzxzzxhyiphzibwzljAy/Xb0KvPoqULkyA5hI/gaqVAFGjnSshecQNeUAe8KUPfJrItv5LV3q6P0ePqy7RUTup3RpYPJkoGXLf/9miG6CPWG6NTmzlzN8Cd+2bRnARDdy9CjQqhXw5JPsFVO2sCdMt5773bIFePhhrvklyomICOCbb4CmTXW3hNwYe8J08+0m5UILDRowgIlySgoXmzcHhgxxXKiEvWK6DvaE6VoSvjLk/NBDwObNultD5PmkcEt2kZO3rKCmDPjbQJnDV8hyixo1GMBEuWXXLqBWLWDcOMcUj/NvjUyPPWFykKGy8+eBRx91VEATkWs0awbMmgUEB/OCEMQQpn+Kr37/HejRA4iN1d0aIuMrWhSYMwdo2JDD0ybHn77Zw1e89x7QujUDmCivnD7tuBjEBx9k/lsk02FP2MzDz3Lr0weYO1d3a4jMS0agZCmTDE3zEommwxA26/Kj6GigY0dg927drSEi2QL2hx8ca4sZxKbC4Wgz+ukn4J57GMBE7kL+FmvWBBYt0t0SymMMYbOQJREy7zRiBNClC3Dpku4WEVFG8jfZtSvwwgtcxmQiHI42A5n7vXzZMffEqx4RuT+5AMT8+UBgIIenDY4hbIYAPnXKUf28b5/u1hBRdsnuWnLSHBbG9cQGxuFooxdgyVxTnToMYCJP3GXL+bcrf8tkSAxho5L5pJUrgUaNHGsSicjzxMQ4LqCyejXniA2KIWxU330HtGsHJCTobgkR3WnBllzHe8YM3S0hF2AIG9Ho0Y5NOHjpNCJjkL9l2ddd/rbJUFiYZRTObe8GDwY+/VR3a4jIVQYOBD75xPE+9532eAxhI5C5Irn17AksWKC7NUTkarLb3ezZjuVLVqvu1tAdYAh7Ognf5GTgvvscV0IiIvOsJV68mEHs4TiWYYQAlqINBjCRuSxf7ii+lPliVk57LIawEXrAsnyBiMwZxO3bM4g9GEPYE8kfm/zR3X8/e8BEZscesUdjCHtqAMsf3apVultDRO5gxQoGsYdiCHsS+eOS7etk+En+6IiInBjEHokh7IkBLMNPRETXC2KZpmIQewyGsKdsxCEB3KEDsGyZ7tYQkTuTPeMliOU1w7mJD7kthrC7k2XccuvSBfjtN92tISJPCeJevXS3grKBIezuvLyA/v2BJUt0t4SIPInsnifb2JJbYwi7uxEjgG++0d0KIvJEso/8mDG6W0E3wW0r3ZXM5cgfEM9kiehOTZsGPPQQt7d0QwxhdyRVjT/8AHTvzsIKIrpzPj7Azz8DTZs69pomt8EQdjdS0bhtm+OP5coV3a0hIqMICgLWrQOiohyhTG6BIexuAXzyJFC7NnDmjO7WEJHRFC8ObNoEFC3KHrGbYGGWOw1BX74M3HsvA5iIXENO8lu3BhITuZmHm2AIu5POnYE9e3S3goiMTF5jpN5Elj+Sdgxhd/HCC9wPmojyhmz8M3Kk7lYQ54TdZB544ULHmSkRUV5v6CH70XN+WBuGsO4APnwYqFkTSEjQ3RoiMmPF9J9/AqVLs2JaEw5H6yLrf+VKJw88wAAmIj0uXQI6duTFHjRiCOtisQB9+7IQi4j02r0b6NPH8ZpEeY7Pug5yxjl+PDB7tu6WEBEBc+YA773H3rAGnBPOazIELYvlmzVzDAEREbkD2Vd6+XKgQQPOD+ch9oTzkiyOv3AB6NaNAZwHkr288HqRIqgTGYmG5cphfGgosp5xbvb3R6uIiFsea3rBgmhetixqRkZiSPHiuJBh6E6OWzsyEl1Ll8bhDC9e56xWtImIQBLXY5KnvD7JKo24OG7kkYcYwnlJXox79ABOndLdElN4KywM6wID8fWJE3j/5EnMKlgQ3xcsmP75vb6+GBoejrRbhOTi/PnxblgYRpw9i5nHjuGktzfeKFJEfW6Pry+mFyqEqceP466kJLxfuHD6130dHIzeFy7An4NN5CnOngV69+bVlvIQQzivyJmlzAOvWqW7JaYgPdW5BQvizdOnUSMpCQ2uXEG/8+fxl7+/+vzMggXRq3RphGbjjH9iSAgGxMWhbUICKiYn48XYWOzz84N85SFfX1RITkaVq1fRMiFB/V/EWSz4LX9+9Lp40eWPlShXLVsGfPQRe8N5hCGcF2To+cAB4JVXdLfENLYEBCC/3Y66Ga5E9cT58xhz+rR6//d8+TD21Ck8dv78TY+TYLFgl78/2mRYRlbnyhX8GB0N6SsUt9lwzMcHlywW7PT3V/8Xk0JC8DB7weSphg937GHAaTOXYwjnlYcfBq5e1d0K05BgLJGSggVBQbgvIkLN+34SEgJn7eenMTG4Nxvrs+U4Is5qRa9SpdC4XDkML1oU8f/MCd+TlIS6ly+jbmQkphQqhKGxsThvsWApe8HkyeTk9aGHuL90HmAIu5qU/L/xBrB1q+6WmMpliwXRPj6YWagQxpw6heGxsZhWqBCmBAfn6DiJ/7wIyRywDEn/LyYG+/388GKxYun3+eDUKaw9eBBrDh1CjatXMTk4WPWCT3l7o0epUqo4S04GiDzK5s2O1y4uW3IphrCrlyPJlnBjxuhuiel4p6UhwWpVBVnSW5Ve78C4uEyFWdk6Toah7FaJiaiVlIS3T5/Givz5cTpD8UqI3a7uK3PRvwQFqV7wW0WKoP2lS5h2/DhGFymS6f5EHmH0aMdrmLyWkUswhF1JziCl0pDzKnkuLDUVfnY7SmR47ssmJ6vK5hwd55+vL5ecnOk44tR11lJKL7jXP3PBW/390eTyZRSz2VAmORl//1MURuQx5PdfptKkSIv1DS7BEHalF18E9u7V3QpTuuvKFVy1WDKt25XKZZknzolwmw1FbDbs8fNL/9hBX1/Z5QbhWY510WLBz0FBeOifuWD543IO5KVybo081b59wPPPc37YRRjCriAvzrIUScr8SYtyKSlonpCAEcWKqbW8qwMD8WVISHpA3oxsrnH2n6FjedmRCuoPQ0OxNjBQHWtUkSJonZCgetsZyXxzz4sX0yuiqyclYV6BAtgUEKCCuyoL88hTffqp4xrEHJbOdQxhVw3hyIboHL7R6r1Tp1A6JQUPlS6N4cWKqY0zHpUdy25hcVAQGkdGpv9f1hfL10oxlhxLjulc6uQk1dLydQ9lOL5s7rE6Xz4MLl5cve9cvkTkceS1bMAAFmm5APeOzm3yS/rSS8C4cbpbQkSUu2Svg9df5xWXchFDODdJT0cWuFetymEbIjIeqY3YtQsoU4ZbW+YSns7kJqm8HTiQAUxExiR1DfIaxwDONQzh3OwFz5rluBQYEZFR/forMHcuOxu5hMPRubnNW4UKwIkTultCRORaJUoA+/cDAQG6W+Lx2BPOrWKsUaMYwERkDvJa9+qrrJbOBewJ3ylZKyrFWFWqcHiGiMxVA7NjByDL+XK4Ex39iz3hOyUFCizGIiIz1sE8+SQD+A4xhO/0l3DOHMdFsImIzEZ2Bpw5k52QO8Dh6Dshv3hSjBUdrbslRER6lC3r2CP/Ohc0oVtjT/hOesFffMEAJiJzk5oY2Vua27LeFvaEb1dSkuMM8NQp3S0hItIrLAw4cgQIDNTdEo/DnvDtVkT/738MYCIicfYs8M47jtdGyhH2hG9HQoJj79S4ON0tISJyD/nyAUePAsHBvPZwDrAnnFNypvfuuwxgIqKMEhOBt97iJVxziD3hnJCnSq4XK73gS5d0t4aIyL34+zuKVWWOmL3hbGFPOKchLGd6DGAiousXrMr1htm3yzb2hLNL9kiV4oOICMcvGhERXcvX17FsqVgxwMJ+3q3wGcouGVqRizQwgImIbiw5GXjjDd2t8BjsCWdXbKzj8l3yC0ZERDcmlziUKy1JpTTdFHvC2a2InjCBAUxElN3rq3/4IXfRygb2hLNDhqBLlgTOndPdEiIizyAV0sePO+aI6YbYE87ORRomT2YAExHlhBSyfvMNr7B0C+wJZ0dUFLBvn+5WEBF53mvnnj26W+HW2BO+GZnP+OknBjAR0e2QSxwuXsze8E0whG/G2xt47z3drSAi8lyyzS+vNXxDHI6+WUX0rl1AjRq6W0JE5Nm2bQOqVQOsVt0tcTvsCd+I/LLIGRwREd2ZsWMZwDfAnvCNnD4NlCrFuQwiotyY2jt2zLGVJWXCnvCNCrI++4wBTESUW6+pkyZx847rYE/4RsqWBY4c0d0KIiJjKF8e2L9fdyvcDnvC1yvI+v13BjARUW46cABYt87xGkvpGMJZyaW3vv5adyuIiIznq694ecMsOBx9vY3HZc/TxETdLSEiMpb8+YEzZxxXWSKFpyQZSSHWzJkMYCIiV0hIAL7/nkWvGTCEM5JdXaZM0d0KIiLjkgvicAetdByOdpKnQdaxRUQ43iciIteQwtfSpQEvL5gde8JOUrEnBVkMYCIi15o4EbDbdbfCLbAnnBHXBhMRuV7JkkB0NCul2RPO0Ateu5YBTESUF44fBzZsYG+YIZzB7Nm6W0BEZB5z53L6j8PRGXAomogo73AbS4U9YTkHkesGM4CJiPJ2G8u9e03fG2YIy3zwvHm6W0FEZD5z5ph+L2mGsFzncuFC3a0gIjKfBQscr8Emxjnh06eB4sVNPyRCRJTnvLyAmBigWDGYlbl7wrJ/qQxFM4CJiPJeWprjNdjEe0mbO4Rl/1IORRMR6R2S9jHvXtLmHo6WqyWFhADJybpbQkRkTj4+QFyc4zKHJmTenrDNBixezAAmItIpJQX46SfTDkmbN4StVkcIExGRXsuXO16TTchi6qo8+cETEZFeq1aZ9mIO5p0TlmsHy/UsiYhIv7NngcKFYTbmPPWQuYdff9XdCiIicpKRSanVMRmLaavxVqzQ3QoiInJaudKUQ9Lme8QZf+BEROQeVplzXticc8InTgAlS+puBRERZSTrhYODYSYWU84HcyiaiMj9LDffvLD5QljWoq1dq7sVRER0vWlCWT5qIuYLYZlzWLNGdyuIiOh688Im27TDfHPCly4BBQvyyklERO7GywuIjzfVPtLm6glL8G7ZwgAmInJHaWnA9u2meo22mK4o688/dbeCiIhuZOtWU13MwWK6TTrkLIuIiNzTX3+Z6vrCFtPNNzCEiYjcO4S9zFMhba7CrNRUx4R/UpLulhAR0fUEBDgKaE1SJW2unvDhwwxgIiJ3duUKcOQIzMJiql6wVEYTEZF727zZNDtnmSeE7XbOBxMRecq8sEmYJ4RZGU1E5Dkh7O0NMzBPCAuGMBGR+/vLPD1h81RHJyQAQUG6W0FERNlx6ZIptq80T0/44EHdLSAiouw6dgxmYDFNUdaBA7pbQUREOek42e0wOnOEsJS6Hz2quxVERJRdR46YYpmSxTTXEGYIExF5juhox2u3wRn/EQopdWcIExF5Vgh7G3+ZkjlCWDCEiYg8K4RNgCFMRETu54g59o82xzrh5GTA3x8wwUMlIjKMpCTAzw9GZo6ecEwMA5iIyNOcOAGjM0cIm2RYg4jIUA4dMnwHyvghnJLiuI4wERF53q5ZNmOvFTZ+CMtZ1OnTultBREQ5deECe8Iez8sLuHhRdyuIiOh2QtjgjB/CVisQH6+7FUREdDshbLXCyIwfwrLtGXvCRESe5+JFhrAhsCdMROR5LnA42hgYwkREnucCQ9gYOBxNROR5Lhr/tdscIcyeMBGR57nAnrAxmOBsiojIcC4a/7XbHBdw8PV17JxFRESew2rljlke7+pVBjARkSdKTQWuXIGRWUxxGUMiIvLcIDYw44cwERF5rjRjz5gyhImIyH2lsifs+RdwICIiz2S3w8i8YXQMYTKyRYuA2rV1t4LIdQoVgpExhIk8ka8v0rZuhVfVqlh6cCmSbEm6W0TkEveF3Qdf+MKoGMJEniYkBPYdfyOtaFEMWNgPk7dN1t0iIpeJezEOvgEMYSJyB5GRsG3dgpQAX3Sf+QAW71+su0VELmW18FKGno09YTKKBg1g27Ed8T6paDalGQOYTMHiZeyYMvajEwxhMoLu3ZHy+0rEXI1F/a/qY1PMJt0tIsoTVi/2hD0bQ5g83bPPwjZzBnaf24O6E+tif9x+3S0iyjNWgw9He5tiA3AiT/XBB0gdMhgrj6xAl++7ICE5QXeLiPKUxeDD0eYI4fz5gQS+eJGHmTcP6NIFM7Z/i34L+yHFzguRkLn4Wn3hbTF2TBn7FMMki73JYCwWYMMGFcBj145Fn/l9GMBkSqEBoTA6Y59iOAUHA8eP624F0a0FBsK+YwcQUQbPLhmCjzZ+pLtFRNoUDiwMozNHCLMnTJ4gPByp2/+CvVBB9J7TC7N3zdbdIiKtQgPZEzZOT5jInVWrBtv6P5DkA3SY1garolfpbhGRdqEmGI7mnDCRbm3aIGXLJpxLS0TDrxsygIkyDEfb04x9FSWLKa5FyZ4wuavHH4dtyU84fOko6kysg7/P/K27RURuNRydauf1hD0/hNkTJnc0ahRSv5qITTGb1S5Yx+KP6W4Rkdv1hNOQBiPjnDCRDlOmwN7nUfy4dxF6ze3FSxES3WBO2AvG3vXQ2xTbVrInTO5k2TKgZUt8sekzPLPkGcPPeRHdSU/Y2+CbdRj70QlvbyAsTHcriABfX6T9+Se8qlTByOUjMXr1aN0tInJrRfMVhZfB9/83fgjLDzAyUncryOxCQmDf8TfSihbFgIX9MHnbZN0tInJ7YfmM34EyfgiL0qV1t4DMLDIStq1bkBLgi+4zH+B1gImyKdjf+PU8xq+OFgEBQKjxF32TG2rQALYd2xHvk4pmU5oxgIlycB3hIL8gGJ05QlhEROhuAZlN9+5I+X0lYq7Got5X9bApZpPuFhF5jDKFysAMGMJErvDss7DNnIGdsbvUJhwH4g7obhGRR4kKjYIZmCOEbTaGMOWdDz5A6vvvYWX0SjSZ3ARnEs/obhGRx4kqHGX43bLMU5hltzOEKW/Mnw907owZ279Fv4X9eB1gojvoCaempcIKK4zMHCHs4wOUK6e7FWRkFguwfj1Qpw7Grh2LEb+NMPx2e0SuVCWsCnwsPjA6c4SwrBUuX153K8ioAgNh37EDiCiDZ5cMwUcbP9LdIiKPV7lwZcNv1GGeEBalSuluARlReDhSt/8Fe6GC6D2nF2bvmq27RUQeL8g3yBQbdZinMMu5VrhoUd2tICOpVg22/XtxOb8f2kxrwwAmysWiLLMwTwiLGjV0t4CMok0bpGzZhHP2RDSc1BCrolfpbhGRYUSZZHmSuUJYlindfbfuVpAR9OsH25KfcPjSUbUGeMeZHbpbRGS4nnByajLMwDwhLBjCdKdGjULqxC+xKWYz6n9VH8fij+luEZEhe8JWL2MvTTJfYZZc0rBOHd2tIE82ZQrsfR7Fj3sXodfcXkiyJeluEZEhVStSDVYLQ9h4ZK2wFGhduaK7JeRpli0DWrbEF5s+wzNLnoE9za67RUSG5AUvlAs2z74O5hqOtlpVRStRtvn6Im3nThXAI5ePxKDFgxjARC6+cIO/tz/MwlwhLNtXcl6YsiskBPYjh2GvFIXHFz6O0atH624RkeHVL1kfZmKu4WhWSFN2RUbCtnULUgJ80W1GRyw5sER3i4hMoWGphqoy2tfqCzMwV0/Y1xeoXVt3K8jdNWiAlB3bEe+TimZTmjGAifJQszLNTBPA5gthUb26Y7N9ouvp3h0pv6/EyauxqPdVPWyK2aS7RUSmkd83P6qGVYWZmC+NpDq6YkXdrSB3NGwYbDNnYGfsLrUJx4G4A7pbRGQq9UrUM83SJPOGcFoa0Lix7laQu5kwAfZx47DiyAo0mdwEZxLP6G4Rkek0Kt0INrsNZmK+EJbirKZNdbeC3Mn8+cDQoZj+93S0/649EpITdLeIyJSalG4Ci5e5Yslc1dHCx0et+SRStQHr16ud1N5Z8w5GLBuhu0VEpmXxsqBByQYMYVMoUcJxfeFj3PfXtAIDYd+xA4gog6FLBuPjjR/rbhGRqVUvUh35fPPBbMx1ypFRkya6W0C6hIcj9Wg0UkuXRM85PRnARG4yH2w34W505gzhlBSgRQvdrSAdqlWDbf9eXM7vhzbT2mDOrjm6W0REABqVYgiba174/vt1t4LyWtu2SNmyCefsiWg4qSFWRa/S3SIi+kfziObwtphvhtScIeycF5arKpE59OsH20+LcCg+Wq0B3nFmh+4WEdE/SgSVQHhQOMzIvCEs64VbtdLdCsoLo0YhdeKX2BizCQ2+boBj8SzII3Inrcu1Rpq8JpuQeUM4NRVo3Vp3K8jVpkyB/dX/w6J9i9BqaiucTzqvu0VElEXXyl2RmpYKM/JKM+vph7h4EQgNdQQyGc+yZWpN+KebPsXgJYNNWfRB5O4CvAMQNzzOVNcQzsi8PWFRsCCXKhmRry/Sdu5UATxy+Ug8vfhpBjCRm2oT2ca0ASzMHcKyVKlLF92toNwUEgL7kcOwV4rC4wsfx+jVo3W3iIhuonNUZ6SkpsCszD0cLWJiHJXS5PkiI2HbugUpAb7oNqsbrwNM5OasXlbEvhiLQv6FYFbm7gmL8HCgVi3draA71bAhUnZsR7xPKppNacYAJvIADUs1NHUAC4awXFWJQ9KerXt3pKxagZiks6g7sS42xWzS3SIiyoZOlTqZeihaMIStVqBHD92toNs1bBhsM2dgZ+wu1P2qLg6eP6i7RUSUTT2q9ICP1QdmxhD28gIqVnTcyLNMmAD7uHFYcWQFmkxugjOJZ3S3iIiyqWpYVZQuWBpmxxAWsk6YQ9KeZf58YOhQTP97Otp/1x4JyQm6W0REOdC5UmfY7DaYHUPY2RvmkLRnsFiAjRuBzp3xzpp30GdBH6TYzT2nROSJulXuBosXI4hLlDIqWRI4cUJ3K+hGAgNh37EDiCiDoT8P5XWAiTxUyQIlcew57uEueBqScUj64Yd1t4JuJDwcqUejkVq6JHrO6ckAJvJg3at05y52/2BP2EmehoMHgQoVdLeEsqpRA7Y/1uKKNQ0dZnTA79G/624REd2Bvc/sRfmQ8hyOZk84y7xw+fJq0wdyI23bImXTBsTaE9BwUkMGMJEBNuioGFqRAfwPPgtZ95Lu3193K8ipXz/YflyEQ/HRqDOxDnac2aG7RUR0hwbUHGD6DToy4nB0VleuAEWKAAlc8qLVqFFI/b9XsOHEBnT4rgOvA0xkAAX9CuLU86dMfdWkrNgTzsrfn8uVdJsyBfZX/w+L9i1Cq6mtGMBEBtG7Rm/4Wn11N8OtMISzstuBAQN0t8K8li0D+vbF55s/V1dCSrIl6W4REeWSp2o/pbsJbochfL29pBs0AKKidLfEXHx9kbZzJ9CyJV5e9jKeXvw0lzAQGUjt8NqoVqQaC7Ky4LNxoysrPf647laYR0gI7EcOw14pCo8teAxj1ozR3SIiymUsyLo+FmbdSGwsULy4I5DJdSIjYdu6GSkBfug6qyt+PvCz7hYRUS7L75sfZ54/gwCfAN1NcTvsCd9I4cJAp066W2FsjRohZcd2xPvY0XRKUwYwkUH1qtYLft5+upvhlhjCN9vGcvhw3a0wru7dkbJyOWKSzqLuxLrYHLNZd4uIyIUFWRx0vT6G8M0KtOrUUb01ymXDhsE2cwZ2xu5C3a/q4uD5g7pbREQuclfRu1CzeE1YLVbdTXFLDOFb7aD14ou6W2EsEybAPm4cVhxZgSaTm+BM4hndLSIiFxpabygLsm6ChVnZWTdcuTKwb5/ulni++fPVdYCn/TUN/X/oz+sAExlcmYJlcGDIAXhbvHU3xW2xJ5ydueHnn9fdCs9msQAbN6oAluVHfRb0YQATmcCLjTiSeCvsCWdHcjJQqhRwhkOnORYYCPvOHUCZMhiyZAg+2fSJ7hYRUR4onr84op+Nho/VR3dT3Bp7wtkt0nrmGd2t8Dzh4Ug9Go3UUiXx4OwHGcBEJvJCoxfgJZeIpZtiTzi7LlwASpQALl/W3RLPUKMGbH+sxRVrGjrM6MDrABOZSFhgGI4+d5RXS8oG9oSzq0ABbmWZXW3bImXTBsTaE9BwUkMGMJHJPNfgORZjZRN7wjmpkj5xQm2zqJYu0fX16wfbF5/j4IVDaD2tNY7HH9fdIiLKQ8H+wTg+7DgCfQJ1N8UjsCeckwpfGY7mZQ5vbNQopE78EhtiNqL+1/UZwEQmNLjeYPhZuUVldrEnnBPyVJ07B0REAImJulvjXqZMgb3Po1i4ZyEemvsQrqZe1d0iIspjQb5BqhdcwK+A7qZ4DPaEc0Iq/YKDgaFDdbfEvSxbBvTti883f47us7szgIlMalCdQcjnk093MzwKe8K3IyFBrXtFXBxMzdcXadu2watyZby87GVeB5jIxGQO+Nhzx9ScMJcmZR97wrfD3x946SWYWkgIUo8chj2qIh5b8BgDmMjkBtYeiEL+hRjAOcSe8J3solWunKNi2mwiI2HbuhkpAX7oOqsrrwNMZHKFAwvj0JBDyO+bnyGcQ+wJ30m19KhRMJ1GjZCyYzvifexoOqUpA5iI8HbLtxHgE8AAvg3sCd/p2uEqVYC9e2EK3bsjZcZ0xCScRKuprXgdYCLC3cXuxpYntsDixT7d7eCzdqdXWHr7bZjCsGGwzZyBnbG7UPerugxgIlI+afcJUu2pupvhsRjCd8LHB+jWDWjYEIY2YQLs48ZhxZEVaDypMc4k8mpSRAT0rNoTDUs15JWS7gCHo++UzQbs26cuWKB6xkYzf766DvDUv6ai/w/9YbPbdLeIiNxkSdKBwQdQNH9RDkXfAT5zd8rbG6hUCRgyBIYrPNu0SQWwLD/qu6AvA5iI0g1vNBxF8hVhAN8h9oRzi1zisGJFYyxZCgyEfecOtSHJkCVDeB1gIsqkTMEy2PvMXvh5c4/oO8VTmNycH54wAR4vPBypR6NhK1UCD85+kAFMRNcY33Y8e8C5hD3h3Na2LbB0KTxSjRqw/bEWV6xpaP9de6w+ulp3i4jIzTSPaI4VfVfoboZhMIRzkxRmHTvmmCO+6mEXMWjbFik/LMC55AtoPbU1dp7dqbtFpJnPJR8U2VQEAbEBSPVNxYWKF3C+ynn1uYAzAQjbEgbfeF8kByUjtmYsLhe7fMtjBu8KRqH9hXC40+H0j4VuC1UfS8mfgpONTiKlgON63dYkK0otLYXodtFI8+bLlDuwelnx91N/o0JoBXhbvHU3xxA4npCbrFagdGlg+HB4lH79YPtxEQ7FR6POxDoMYALSgBIrSyDVPxXR90XjTJ0zCNkZgqAjQSocw1eF41KZS4huH42EMgnq/96Xb/6i7JPgg9C/QzN9zPe8rwrg462OI6lwEgpvK5z+ueDdwSr4GcDutT90pcKVGMC5iCHsiqrikSPV/soe4fXXkTrxS2yI2Yj6X9fH8fjjultEbkCC9mrwVZyuc1r1TBNLJOJy0csIOBugbvLKIb1i6b3GVY1DmjUN/rH+Nz1mkY1FcDUk8wiR6kkXTFYfTyiRoP4vLEkW5D+WHxfLX3Tp46TsiygUgXFtxuluhuEwhF1B9k/97DO4vSlTYP+/V/DD3h/UNpQXki7obhG5idSAVJxsfBJpPmmqV+x/1h+BZwNxuchlpPqlwnrVqkJSPpfvWD5YbBZcLXTjKZigQ0GwpFpwsVzmULUF2lQP2ZJsgf95f9jyOZbBhewJYS/YjXjBC1M6TVE9YO4Pnbs4puCqSuk2bYABA4CJE+GWli8HWrTA55s+xeAlg2FPs+tuEbmpsgvLwueyDxLCE5BQKkFekXGhwgUUX11cve+V5oVT9U+lz+Ver1cdti0Mx1seh39c5t5yUliSCvbIuZFq3vlE8xOwXLUg/9H8ai6Y3MNTdZ5Cs4hmupthSCzMchV5WpOSHDtpHTgAt+Hri7Rt2+BVuTJGLBuBd9a8o7tF5Ob8zvnBO8lbFWkllExA7F2xCF8TjiuFr6hhaukRF9pbCEfbHkVKwWuDuNi6YqrHG3t3LAocKqDmhTMWZjmHn+2+djU2J4VaMhedGJ6IYn8UU73uc9XP4VLZS3n4qMmpbKGy2DloJ/y9/dkLdgEOR7uK/LLKblrffeco2HIHISFIPXIY9qiKagcsBjBlx9XQqypsz9Y8i4IHCiJ0p6O4Kq56nJrLPXfXOVVUFbw3+JqvDYwJVHPF56qdu+n3sPs7Alh6wUHHgtRccJEtRVTx1/HWx9X71stu8ndksmHoqV2mchjahRjCrh6WrlULePll3S1RhWK2wweRXDhYrQGWvaCJbsR6xarmejOSAiqL3QK/836qaCsj+b9P4rWb+AcdDVJD2ZHzIlF+VnlVnOWd6K3el2VOWQXvCcaF8o65YJmHvlz8supFyzKorEPZ5HqD6w1G49KNeYEGF2II50W19GuvAbVr62tDo0ZI2bEd8T52NJ3SFL8c/EVfW8gjSKCGr8687Mgvzg82P5sKRd+LjipmJ6lqlkrprGQI+kj7I4i+P1rdztU4B1uATb2fFJKU6b5SnCWhfbHCP8Vb0vH6Z7LMy+6V/j7ljaphVVkNnQcYwnk1PzxzptqTOc91746UlcsQk3QWdSfWxeaYzXnfBvI4EpAy1Fx0fVEVuPlO5EPYn2FqOdLFyIvIF5MPhfYUUpXN8jbfyXyqWEt42bxUT1rI3G5KUEr6Tf4vrzryftbKZ+kFyzC08+NJoUlqDll6zBLyWZc3kev4Wf0wq8csWBgRLsdnOC/I3HBEBDAuj88qhw2DbeYM7Izdjbpf1cXB8wfz9vuT57IAJ5qegN3brnatKrqxKC5EXVA3mf+NaRKjArLM4jIocLiAqmpOLpSsvlR6s5Hzc7ZOXvWCo4PSg1zIHLSEu1Rhy/vO5UvkeqNbjUZUaBS8rVxA42qsjs5r998P/Pyz67/PhAmwDx6M3w7/hq7fd0ViSqLrvycRebzW5Vrj10d/1d0M02AI5/Xe0nFxQJUqQGys677PggVAp06q+Kr/D/15HWAiypaQgBDsGrQLhQMLw2phNXpe4HB0XpKlSsHBjvlhKdjKbXLMTZtUAI9ePVotQ2IAE1F2yKUJv+36LUIDQxnAeYghrGN+uEUL4O23c/e4gYGwHzwAe62aeGbxMxi5fGTuHp+IDO2NFm+gbWRbXpwhj3E4Wqdu3YB58+78OOHhSN3+F1ILFcDDcx/G3N1zc6N1RGQS3at0x+wes3U3w5QYwrrY7Y5tLWX98O7dt3+cGjVg+2MtrljT1CYcq4+uzs1WEpHBVS9SHRv+swF+3n5qSJryFp9xXWT+VnbUWrQIKFDg9o7Rti1SNm1ArD0BDb5uwAAmohwXYv348I9qRywGsB581nWSEC5TBpg2zbHXdE707w/bT4twKD4adSbWwc6zO13VSiIyIKuXFXN6zEF4UDjngTViCLtDodYDD+Rsf+nXX0fql19gw4mNqP91fRyPP+7KFhKRAY1tM1ZdnpABrBfnhN1pjrh9+1tv5DFlCux9HsWCPQtUEdbVVG7lR0Q580iNRzCtyzTdzSCGsJtt5JGY6Ljq0o2uP7x8uVre9MnGTzDk5yGwp9nzupVE5OFqFa+Fdf3Xwcfiw8sTugGGsDtJSQFOnADq1Mm8o5avL9K2bYNX5coYsWwErwNMRLelSL4i2PbkNoTlC+MwtJvgnLC7FWqVKAEsXgwE/HOt1ZAQpB45DHtURbUDFgOYiG6H9HznPThPbUnJAHYfDGF3DOKaNYEZM4CKFWE7fBDJhYPVGmDZC5qIKKdk+dHULlNRv2R9tRyJ3AeHo92V3Y4Uuw2XUi6h7bf38TrARHTbvuzwJfrX7M+1wG6IYxLuymKBj8UXkzdNYQAT0W17t827GFBrgO5m0A3wtMjN/bfBfzGgJv+AiCjnXm7yMl5o+ILuZtBNcDjazcmPR/71mN0D83bnwsUeiMgUnq7zND5u97HuZtAtMIQ9gKwHTrWnou23bbHiyArdzSEiN/dojUdVIRa5P4awh5AQlt2xmk5uii0nt+huDhG5qc6VOmPug3PhJf+4GYfb45ywh7BarPC1+mJ53+WoE15Hd3OIyA21Ltcas7rPUu8zgD0DQ9iDyAL7QJ9ArOi7Ao1LN9bdHCJyI7IG+IdeP6hlSFyK5Dn4k/LAIPb39sfSR5aiVdlWuptDRG6gRtEa+OWRX9RomYyakedgCHvw0PTi3ovRrkI73c0hIo1kempl35VqlIwB7HkYwh5K/tikV7yw10J0q9xNd3OISNMc8KrHViHIL4j7QXsohrAHc879zOoxC72r99bdHCLKQz2q9MDihxerUTEGsOdiCHs4CWFZiiBrArmzFpE5PFX7KczsPlONiHEI2rMxhA1AliLIvy87fokh9Ybobg4RudBrzV7Dp+0/ZRW0QXCzDgMasWwErztMZDByov3R/R/h6bpP624K5SKGsEGNWTMGI5eNVPtOE5Fn87H4YFrXaWoemL1fY2EIG5T8WBfsWYBH5j+CyymXdTeHiG5TPp98WNBrAVpEtOD8rwExhA3MZrdhT+wetP+uPY5ePKq7OUSUQ6EBofj5kZ9xd7G7WQFtUAxhg0tJTcGl5EvoOKMj1h1bp7s5RJRNFUIqqA15IgpFMIANjJMLBudj9UFBv4JqR53H735cd3OIKBseiHoAW5/cijIFyzCADY4hbKLdtSZ1moT3730fVi/OKxG5Iym6erPFm2onPNmGUk6iydg4HG0y9jQ7fjv0Gx6c/SAuXr2ouzlE9I+QgBDM7DYTrcq1YgW0iTCETVqwdeTCEbSb3g774/brbg6R6UnhlVyGsHhQcQ4/mwxPt0xI/sgjCkZg8xOb0aZcG93NITK1Pnf1wfr+6xnAJsUQNilvq7dafyjLH4Y3Gs7hLyING3B80u4TfNP5G16EwcQ4HE1qY481R9eg97zeOBZ/THdziAwvPCgc8x6ch9rhtbkBh8kxhCl9PXGSLQlP/PgEZu6Yqbs5RIbVpHQTzOs5Ty0dZPUzMYQpU+W0DEtP3z4dgxYPQvzVeN1NIjIMP6sfRjUfhRcbvahGn9gDJsEQputWT59OOI2H5j6E1UdX624OkceTYedvu3yL8iHlGb6UCatx6BpSIFI0f1GsfGwl3m75tiogIaKck4Krt1q+paqfI0MiGcB0DfaE6ZZD1NtPb0fPOT2x79w+3c0h8hj3FLsH07tOR1ThKK4+oBvibwbdlLx4VA2rir8G/oUnaz2puzlEbk9GjmTud9OATagQWoEBTDfFnjBli/yaeHl54ecDP2PQT4Nw+MJh3U0icjs1itZQvd8qYVUYvpQtDGHK8VKmNKRh9OrRGLt2rFrWRGR2UkfxUuOX8Fqz19L/T5QdDGG67bni4/HH8fTip/Hjvh91N4dI677PUzpNQfWi1dn7pRxjCNNtS7WnqmrPxfsXY/CSwTh0/pDuJhHlmWL5i2F0y9Hoe3df2O12tRUsUU4xhCnXhqjfWfOOul2xXdHdJCKX8ff2x7AGw/BKk1fUjlcceqY7wRCmXO0Zx1yKwTNLnsEPe3/Q3RyiXNerWi+81+Y9dcUjDj1TbmAIk0uGqKWK+pnFz+Dg+YO6m0R0x+qVqIcP7/8QdUvUTd/elSg3MITJZUPU4v0/3se4deMQdyVOd5OIcqxkgZIY23osHq7+MGypNs77Uq5jCJPLe8ZXU6/ig/UfYPwf4xnG5BHkWttyoQXntbZ5tSNyFYYw5VkYy5piZxifTzqvu0lE173SkVQ7v9niTYQGhHKvZ3I5hjDlKYYxuaP8vvkxsPZAvNjwRRQOLKyq/TnvS3mBIUxaw3j8+vH44I8PGMakhQTukHpDMLTeUBXEXvLPy0t3s8hEGMKkFcOYdChVoBSeb/g8nqj1hFrny7W+pAtDmNwmjGWTDxmm/nTTpziVcEp3k8iAKheurPZ4lmpnwfAl3RjC5HZhLPNx8/fMV2G88shK3U0iA6gTXgcjm4xEp0qd1PI5VjuTu2AIk1tyvlDuP7cfH2/6GN9s+wYXr17U3SzyINLL7Vixo5rzbR7RnOFLbokhTG5NdicSyanJ+O7v71TveMvJLbqbRW6sXHA5/KfmfzCg5gBVeGWz2zjsTG6LIUwew9mT+fPkn/ho40eYuWMmLxZBiq/VF50rdcbAWgPRomwLBi95DIYweeS8sazhvJR8CZP+nIQvtnyBPbF7dDeLNM319rmrDx6p8QgK+Rdi+JLHYQiTR3O+6O46uwvf7/wec3fNxc6zO3U3i1y8vEhCt989/VA+pDznesmjMYTJEOTXODUtVQXywbiDjkDePRdbT27V3TTKBaULlkaHih3wYJUH0aRME/XzltEQbqxBno4hTIbuIR+7eAyzds1SPeT1x9er5U/k/iRg5fKBHaM6onNUZ1QOq6yK9OTlivs5k5EwhMnwnMOVpxNOY/au2aqHvDp6teo5k/so4FcAbSPbqh7vA1EPqDle+dnJyRR7vGRUDGEyZSCfv3IeSw4swYojK7D88HIcOn9Id9NMSeZ0JXQ7RXVC49KNVeByjpfMhCFMpiUXaZehTellxVyKwdKDS1UgSzAfjz+uu3mGFBkcifol66NeyXpoV74dIkMiVbW74DAzmRFDmOgfGXtgEsqrjqzC2mNr1e3v039z+DqHCvoVRN0SdVXoNijZAA1KNVBDzM7NV2RtL5HZMYSJblLcJQVCcrucchkbjm9QgbzjzA7sjt2NvbF7cTX1qu5mugWrlxXVi1ZXxVQSujK0LEPN6c+j/LPw+rxEWTGEibJJqnNl6NTZW5b3j8Ufw/bT29XaZFmrLDfZOERC24gCfQLVkLIErAwly9tqYdVQs3hNBPgEXPMcEdHNMYSJ7pDdboctzZZpePVE/IlM4SyFX6cTT+NM4hlVFObOS6VkyNgZtCpsgyMRVTgKFUMrqr2YnaSHKy8frF4mun0MYSIXkV6hBJWPxSdTSMnHJIglkE8mnMTJSydx5vIZ9X9ZRiVv1fuJp5GYnKjmoqV3mfGt88IWNyMnBRKocgv2D/73/YDgaz4eEhCCsMAwRBSKQEH/gpnmyYURerYpKSn4/PPPsWDBApw+fRqFCxdG27ZtMXjwYOTPnz9Xv9dHH32EjRs3Ytq0achtUVFRmDp1KurVq5frx6a8xxAm0kxCWULVC145Cjv5GudNwjn9/bRUBHgHwM/b74Zfp67bLH/6Xo75XDNUJo8ZMwbr1q3Dyy+/jFKlSuHYsWN4++23UbJkSRXOuSkxMVGFfqFCjkK03MQQNhbudE6k2e1ecMBZNKZYc/h1VvMVSc2fPx+jR49GgwYN1P8lfEeNGoXevXvjzJkzKFKkSK59r3z58uXascjYzPeXSESmJFMC69evV3P4Tvfccw9++uknBAcHo2XLlpg3b1765zZs2KB6neL48ePq/U8++QR16tTBiBEjUL16dXU8p4SEBPWxzZs3q+HoRx99VH2vJk2aYO7cuen3kxGIpk2bYuHCher/cv+uXbuiRo0a6NixI3755ZdM7f7444/ViYP0fGfPnu3S54jyHnvCRGQKffr0wYcffojffvsNzZo1Q8OGDdG4cWOUL+9YSpUdW7duVYEq4Xrx4kX8+uuvqF+/vvrcypUrERISglq1auGPP/5QH5NlWffdd5+6X7du3dTHtm3bhgsXLqBVq1Y4e/YsnnzySTz33HMqrOVzL730EkJDQ1G7dm18//33auh57NixKFasGF5//XUXPTukC3vCRGQKTz/9NMaNG6fCbNasWRgyZMg1vdRb6du3L0qXLo2IiAi0b99ehauzrEZ6sPfff/81leJyv7Vr16qesvN+chIgxWDTp09XJwOPPPIIypQpg06dOqFnz5745ptv1H2lnfI9W7RogcqVK+Ott97K1eeE9GMIE5FpPPDAA5g5c6Yq0HrvvfdQoUIFjBw5Ejt27MjW15coUSL9fQnG+Ph4/PXXX7hy5QpWr16Ndu3aXfM1d999N8LCwrBq1Sr1/6VLl6bf79ChQ1ixYoUaFnfevv32Wxw5ckR9/uDBgyp8naTXHhgYeMfPA7kPDkcTkeHt2bNHLU2SoV4hc8Ay/ypLlO69995Mc7tOqanXblPq5/dvxbmEoQSx9GydS55kXvd6JHTlftLbPX/+PJo3b64+brPZVDsGDhyY6f7e3v++NGddwJLxc+T52BMmIsOTQJ08eTJ27dqV6eO+vr7w9/dXc7k+Pj5qaZGTLGG6FRlqlh6uzDNfrxecdUhaglgKwAICAtTHy5Yti+joaBXOztuyZcuwaNEi9Xnpqf/999/px5ECMel9k3EwhInI8KpWrap6n4MGDVIBJ2EmRVCvvfYakpOTVW9YKpvnzJmDffv2qcroSZMm3fK4UuUsy5tuFcIypCxLoGSoWeaNnR5++GE1FP7BBx+oIWhp2/jx4xEeHq4+L3PFUpgl4S3tkqFz7sFtLPxpEpEpTJgwQRU+yZIfCUKpSpZiKQlGKZJ69tlnUaBAAbVcSDbxGDp06C2PKT3p1q1bq2KvSpUq3fS+EtJWq1UFd8Y5ZtkoROaTO3TooNooQ+Yydy2kvVJA9uabb6rAbtSokWojGQd3zCIiItKEPWEiIiJNGMJERESaMISJiIg0YQgTERFpwhAmIiLShCFMRESkCUOYiIhIE4YwERGRJgxhIiIiTRjCREREmjCEiYiINGEIExERacIQJiIi0oQhTEREpAlDmIiISBOGMBERkSYMYSIiIk0YwkRERJowhImIiDRhCBMREWnCECYiItKEIUxERKQJQ5iIiEgThjAREZEmDGEiIiJNGMJERESaMISJiIg0YQgTERFpwhAmIiLShCFMRESkCUOYiIhIE4YwERGRJgxhIiIiTRjCREREmjCEiYiINGEIExERacIQJiIi0oQhTEREpAlDmIiISBOGMBERkSYMYSIiIk0YwkRERJowhImIiDRhCBMREWnCECYiItKEIUxERAQ9/h8w8Ecr8TK94QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "survived_counts = titanic_df[\"Survived\"].value_counts()\n",
    "plt.figure(figsize=(6, 6))\n",
    "plt.pie(survived_counts, labels=[\"Not Survived\", \"Survived\"], autopct=\"%1.1f%%\", colors=[\"red\", \"green\"])\n",
    "plt.title(\"Survival Distribution\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "b7c3e709-bae7-4bd2-98cc-368dbbd528a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\STCs\\AppData\\Local\\Temp\\ipykernel_11012\\2345624986.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=titanic_df[\"Sex\"], y=titanic_df[\"Survived\"], palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 4))\n",
    "sns.barplot(x=titanic_df[\"Sex\"], y=titanic_df[\"Survived\"], palette=\"coolwarm\")\n",
    "plt.title(\"Survival Rate by Gender\")\n",
    "plt.xlabel(\"Sex\")\n",
    "plt.ylabel(\"Survival Rate\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e92f45a-584f-443e-983f-5aa5c33b3007",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}