DSPD0103EN-Data Collection & Data Source.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas_profiling as pp\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load The Data from UCI Machine Learning Repository in CSV\n",
    "\n",
    "The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms.[UCI Machine Learning](https://archive.ics.uci.edu/ml/index.php)\n",
    "\n",
    "## Data Set Colletion For UCI\n",
    "\n",
    "* `Step-1`: Goto this [link](https://archive.ics.uci.edu/ml/datasets.php)\n",
    "* `Step-2`: Select the Data Sets![](https://lh3.googleusercontent.com/-Qprd_P1bNeE/XkkiUnProdI/AAAAAAAAm2E/YAecsJa4keUvUppwOqC0MXZYga1HJEsmgCK8BGAsYHg/s0/2020-02-16.png)\n",
    "\n",
    "* `Step-3`: Copy the Data Url ![](https://lh3.googleusercontent.com/-_eSgbi1-jOg/XkkirtydthI/AAAAAAAAm2M/NG5Xupis8nw6-HuynC6-gE6NYfMfZKwzACK8BGAsYHg/s0/2020-02-16.png)\n",
    "* `Step-4`: Copy the Attribute Information:![](https://lh3.googleusercontent.com/-w6v3O1d_Tww/XkkjJumf7sI/AAAAAAAAm2U/uZI6zSkuMo48TrMO2nbH8_f7wkIcgJFygCK8BGAsYHg/s0/2020-02-16.png)\n",
    "\n",
    "\n",
    "## Usage\n",
    "\n",
    "```Python\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "URL = \"https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data\"\n",
    "Col_Names  = ['age','workclass','fnlwgt','education','education-num','marital-status','occupation','relationship','race','sex','capital-loss','hours-per-week','native-country','Income']\n",
    "\n",
    "Data = pd.read_csv(URL,header=None)\n",
    "Data.columns = Names\n",
    "Data\n",
    "```\n",
    "\n",
    "## Contributing\n",
    "If any one Intrested work with Use Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\n",
    "\n",
    "Please make sure to update tests as appropriate.\n",
    "\n",
    "## License\n",
    "[MIT](https://choosealicense.com/licenses/mit/)[Copyright (c) 2020 REDDY PRASAD]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "URL = \"https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data\""
   ]
  },
  {
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   "execution_count": 6,
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       "      <td>Iris-setosa</td>\n",
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       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>Iris-virginica</td>\n",
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       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
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       "       0    1    2    3               4\n",
       "0    5.1  3.5  1.4  0.2     Iris-setosa\n",
       "1    4.9  3.0  1.4  0.2     Iris-setosa\n",
       "2    4.7  3.2  1.3  0.2     Iris-setosa\n",
       "3    4.6  3.1  1.5  0.2     Iris-setosa\n",
       "4    5.0  3.6  1.4  0.2     Iris-setosa\n",
       "..   ...  ...  ...  ...             ...\n",
       "145  6.7  3.0  5.2  2.3  Iris-virginica\n",
       "146  6.3  2.5  5.0  1.9  Iris-virginica\n",
       "147  6.5  3.0  5.2  2.0  Iris-virginica\n",
       "148  6.2  3.4  5.4  2.3  Iris-virginica\n",
       "149  5.9  3.0  5.1  1.8  Iris-virginica\n",
       "\n",
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   "source": [
    "Data = pd.read_csv(URL,header=None)\n",
    "Data"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Col = ['Sepal_Length','Sepal_Width','Petal_Length','Petal_Width','class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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   "source": [
    "Data.columns= Col"
   ]
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   "execution_count": 9,
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       "     Sepal_Length  Sepal_Width  Petal_Length  Petal_Width           class\n",
       "0             5.1          3.5           1.4          0.2     Iris-setosa\n",
       "1             4.9          3.0           1.4          0.2     Iris-setosa\n",
       "2             4.7          3.2           1.3          0.2     Iris-setosa\n",
       "3             4.6          3.1           1.5          0.2     Iris-setosa\n",
       "4             5.0          3.6           1.4          0.2     Iris-setosa\n",
       "..            ...          ...           ...          ...             ...\n",
       "145           6.7          3.0           5.2          2.3  Iris-virginica\n",
       "146           6.3          2.5           5.0          1.9  Iris-virginica\n",
       "147           6.5          3.0           5.2          2.0  Iris-virginica\n",
       "148           6.2          3.4           5.4          2.3  Iris-virginica\n",
       "149           5.9          3.0           5.1          1.8  Iris-virginica\n",
       "\n",
       "[150 rows x 5 columns]"
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     "execution_count": 9,
     "metadata": {},
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       "   Sepal_Length  Sepal_Width  Petal_Length  Petal_Width        class\n",
       "0           5.1          3.5           1.4          0.2  Iris-setosa\n",
       "1           4.9          3.0           1.4          0.2  Iris-setosa\n",
       "2           4.7          3.2           1.3          0.2  Iris-setosa\n",
       "3           4.6          3.1           1.5          0.2  Iris-setosa\n",
       "4           5.0          3.6           1.4          0.2  Iris-setosa"
      ]
     },
     "execution_count": 10,
     "metadata": {},
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   "source": [
    "Data.head() # first Five Rows"
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       "     Sepal_Length  Sepal_Width  Petal_Length  Petal_Width           class\n",
       "145           6.7          3.0           5.2          2.3  Iris-virginica\n",
       "146           6.3          2.5           5.0          1.9  Iris-virginica\n",
       "147           6.5          3.0           5.2          2.0  Iris-virginica\n",
       "148           6.2          3.4           5.4          2.3  Iris-virginica\n",
       "149           5.9          3.0           5.1          1.8  Iris-virginica"
      ]
     },
     "execution_count": 11,
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    }
   ],
   "source": [
    "Data.tail() # last Five rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 150 entries, 0 to 149\n",
      "Data columns (total 5 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Sepal_Length  150 non-null    float64\n",
      " 1   Sepal_Width   150 non-null    float64\n",
      " 2   Petal_Length  150 non-null    float64\n",
      " 3   Petal_Width   150 non-null    float64\n",
      " 4   class         150 non-null    object \n",
      "dtypes: float64(4), object(1)\n",
      "memory usage: 6.0+ KB\n"
     ]
    }
   ],
   "source": [
    "Data.info() # Complite Info About the Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sepal_Length</th>\n",
       "      <td>150.0</td>\n",
       "      <td>5.843333</td>\n",
       "      <td>0.828066</td>\n",
       "      <td>4.3</td>\n",
       "      <td>5.1</td>\n",
       "      <td>5.80</td>\n",
       "      <td>6.4</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sepal_Width</th>\n",
       "      <td>150.0</td>\n",
       "      <td>3.054000</td>\n",
       "      <td>0.433594</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.3</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petal_Length</th>\n",
       "      <td>150.0</td>\n",
       "      <td>3.758667</td>\n",
       "      <td>1.764420</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>4.35</td>\n",
       "      <td>5.1</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petal_Width</th>\n",
       "      <td>150.0</td>\n",
       "      <td>1.198667</td>\n",
       "      <td>0.763161</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count      mean       std  min  25%   50%  75%  max\n",
       "Sepal_Length  150.0  5.843333  0.828066  4.3  5.1  5.80  6.4  7.9\n",
       "Sepal_Width   150.0  3.054000  0.433594  2.0  2.8  3.00  3.3  4.4\n",
       "Petal_Length  150.0  3.758667  1.764420  1.0  1.6  4.35  5.1  6.9\n",
       "Petal_Width   150.0  1.198667  0.763161  0.1  0.3  1.30  1.8  2.5"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Sepal_Length', 'Sepal_Width', 'Petal_Length', 'Petal_Width', 'class'], dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [4.9, 3.0, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [4.7, 3.2, 1.3, 0.2, 'Iris-setosa'],\n",
       "       [4.6, 3.1, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.6, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [5.4, 3.9, 1.7, 0.4, 'Iris-setosa'],\n",
       "       [4.6, 3.4, 1.4, 0.3, 'Iris-setosa'],\n",
       "       [5.0, 3.4, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [4.4, 2.9, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [4.9, 3.1, 1.5, 0.1, 'Iris-setosa'],\n",
       "       [5.4, 3.7, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [4.8, 3.4, 1.6, 0.2, 'Iris-setosa'],\n",
       "       [4.8, 3.0, 1.4, 0.1, 'Iris-setosa'],\n",
       "       [4.3, 3.0, 1.1, 0.1, 'Iris-setosa'],\n",
       "       [5.8, 4.0, 1.2, 0.2, 'Iris-setosa'],\n",
       "       [5.7, 4.4, 1.5, 0.4, 'Iris-setosa'],\n",
       "       [5.4, 3.9, 1.3, 0.4, 'Iris-setosa'],\n",
       "       [5.1, 3.5, 1.4, 0.3, 'Iris-setosa'],\n",
       "       [5.7, 3.8, 1.7, 0.3, 'Iris-setosa'],\n",
       "       [5.1, 3.8, 1.5, 0.3, 'Iris-setosa'],\n",
       "       [5.4, 3.4, 1.7, 0.2, 'Iris-setosa'],\n",
       "       [5.1, 3.7, 1.5, 0.4, 'Iris-setosa'],\n",
       "       [4.6, 3.6, 1.0, 0.2, 'Iris-setosa'],\n",
       "       [5.1, 3.3, 1.7, 0.5, 'Iris-setosa'],\n",
       "       [4.8, 3.4, 1.9, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.0, 1.6, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.4, 1.6, 0.4, 'Iris-setosa'],\n",
       "       [5.2, 3.5, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [5.2, 3.4, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [4.7, 3.2, 1.6, 0.2, 'Iris-setosa'],\n",
       "       [4.8, 3.1, 1.6, 0.2, 'Iris-setosa'],\n",
       "       [5.4, 3.4, 1.5, 0.4, 'Iris-setosa'],\n",
       "       [5.2, 4.1, 1.5, 0.1, 'Iris-setosa'],\n",
       "       [5.5, 4.2, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [4.9, 3.1, 1.5, 0.1, 'Iris-setosa'],\n",
       "       [5.0, 3.2, 1.2, 0.2, 'Iris-setosa'],\n",
       "       [5.5, 3.5, 1.3, 0.2, 'Iris-setosa'],\n",
       "       [4.9, 3.1, 1.5, 0.1, 'Iris-setosa'],\n",
       "       [4.4, 3.0, 1.3, 0.2, 'Iris-setosa'],\n",
       "       [5.1, 3.4, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.5, 1.3, 0.3, 'Iris-setosa'],\n",
       "       [4.5, 2.3, 1.3, 0.3, 'Iris-setosa'],\n",
       "       [4.4, 3.2, 1.3, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.5, 1.6, 0.6, 'Iris-setosa'],\n",
       "       [5.1, 3.8, 1.9, 0.4, 'Iris-setosa'],\n",
       "       [4.8, 3.0, 1.4, 0.3, 'Iris-setosa'],\n",
       "       [5.1, 3.8, 1.6, 0.2, 'Iris-setosa'],\n",
       "       [4.6, 3.2, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [5.3, 3.7, 1.5, 0.2, 'Iris-setosa'],\n",
       "       [5.0, 3.3, 1.4, 0.2, 'Iris-setosa'],\n",
       "       [7.0, 3.2, 4.7, 1.4, 'Iris-versicolor'],\n",
       "       [6.4, 3.2, 4.5, 1.5, 'Iris-versicolor'],\n",
       "       [6.9, 3.1, 4.9, 1.5, 'Iris-versicolor'],\n",
       "       [5.5, 2.3, 4.0, 1.3, 'Iris-versicolor'],\n",
       "       [6.5, 2.8, 4.6, 1.5, 'Iris-versicolor'],\n",
       "       [5.7, 2.8, 4.5, 1.3, 'Iris-versicolor'],\n",
       "       [6.3, 3.3, 4.7, 1.6, 'Iris-versicolor'],\n",
       "       [4.9, 2.4, 3.3, 1.0, 'Iris-versicolor'],\n",
       "       [6.6, 2.9, 4.6, 1.3, 'Iris-versicolor'],\n",
       "       [5.2, 2.7, 3.9, 1.4, 'Iris-versicolor'],\n",
       "       [5.0, 2.0, 3.5, 1.0, 'Iris-versicolor'],\n",
       "       [5.9, 3.0, 4.2, 1.5, 'Iris-versicolor'],\n",
       "       [6.0, 2.2, 4.0, 1.0, 'Iris-versicolor'],\n",
       "       [6.1, 2.9, 4.7, 1.4, 'Iris-versicolor'],\n",
       "       [5.6, 2.9, 3.6, 1.3, 'Iris-versicolor'],\n",
       "       [6.7, 3.1, 4.4, 1.4, 'Iris-versicolor'],\n",
       "       [5.6, 3.0, 4.5, 1.5, 'Iris-versicolor'],\n",
       "       [5.8, 2.7, 4.1, 1.0, 'Iris-versicolor'],\n",
       "       [6.2, 2.2, 4.5, 1.5, 'Iris-versicolor'],\n",
       "       [5.6, 2.5, 3.9, 1.1, 'Iris-versicolor'],\n",
       "       [5.9, 3.2, 4.8, 1.8, 'Iris-versicolor'],\n",
       "       [6.1, 2.8, 4.0, 1.3, 'Iris-versicolor'],\n",
       "       [6.3, 2.5, 4.9, 1.5, 'Iris-versicolor'],\n",
       "       [6.1, 2.8, 4.7, 1.2, 'Iris-versicolor'],\n",
       "       [6.4, 2.9, 4.3, 1.3, 'Iris-versicolor'],\n",
       "       [6.6, 3.0, 4.4, 1.4, 'Iris-versicolor'],\n",
       "       [6.8, 2.8, 4.8, 1.4, 'Iris-versicolor'],\n",
       "       [6.7, 3.0, 5.0, 1.7, 'Iris-versicolor'],\n",
       "       [6.0, 2.9, 4.5, 1.5, 'Iris-versicolor'],\n",
       "       [5.7, 2.6, 3.5, 1.0, 'Iris-versicolor'],\n",
       "       [5.5, 2.4, 3.8, 1.1, 'Iris-versicolor'],\n",
       "       [5.5, 2.4, 3.7, 1.0, 'Iris-versicolor'],\n",
       "       [5.8, 2.7, 3.9, 1.2, 'Iris-versicolor'],\n",
       "       [6.0, 2.7, 5.1, 1.6, 'Iris-versicolor'],\n",
       "       [5.4, 3.0, 4.5, 1.5, 'Iris-versicolor'],\n",
       "       [6.0, 3.4, 4.5, 1.6, 'Iris-versicolor'],\n",
       "       [6.7, 3.1, 4.7, 1.5, 'Iris-versicolor'],\n",
       "       [6.3, 2.3, 4.4, 1.3, 'Iris-versicolor'],\n",
       "       [5.6, 3.0, 4.1, 1.3, 'Iris-versicolor'],\n",
       "       [5.5, 2.5, 4.0, 1.3, 'Iris-versicolor'],\n",
       "       [5.5, 2.6, 4.4, 1.2, 'Iris-versicolor'],\n",
       "       [6.1, 3.0, 4.6, 1.4, 'Iris-versicolor'],\n",
       "       [5.8, 2.6, 4.0, 1.2, 'Iris-versicolor'],\n",
       "       [5.0, 2.3, 3.3, 1.0, 'Iris-versicolor'],\n",
       "       [5.6, 2.7, 4.2, 1.3, 'Iris-versicolor'],\n",
       "       [5.7, 3.0, 4.2, 1.2, 'Iris-versicolor'],\n",
       "       [5.7, 2.9, 4.2, 1.3, 'Iris-versicolor'],\n",
       "       [6.2, 2.9, 4.3, 1.3, 'Iris-versicolor'],\n",
       "       [5.1, 2.5, 3.0, 1.1, 'Iris-versicolor'],\n",
       "       [5.7, 2.8, 4.1, 1.3, 'Iris-versicolor'],\n",
       "       [6.3, 3.3, 6.0, 2.5, 'Iris-virginica'],\n",
       "       [5.8, 2.7, 5.1, 1.9, 'Iris-virginica'],\n",
       "       [7.1, 3.0, 5.9, 2.1, 'Iris-virginica'],\n",
       "       [6.3, 2.9, 5.6, 1.8, 'Iris-virginica'],\n",
       "       [6.5, 3.0, 5.8, 2.2, 'Iris-virginica'],\n",
       "       [7.6, 3.0, 6.6, 2.1, 'Iris-virginica'],\n",
       "       [4.9, 2.5, 4.5, 1.7, 'Iris-virginica'],\n",
       "       [7.3, 2.9, 6.3, 1.8, 'Iris-virginica'],\n",
       "       [6.7, 2.5, 5.8, 1.8, 'Iris-virginica'],\n",
       "       [7.2, 3.6, 6.1, 2.5, 'Iris-virginica'],\n",
       "       [6.5, 3.2, 5.1, 2.0, 'Iris-virginica'],\n",
       "       [6.4, 2.7, 5.3, 1.9, 'Iris-virginica'],\n",
       "       [6.8, 3.0, 5.5, 2.1, 'Iris-virginica'],\n",
       "       [5.7, 2.5, 5.0, 2.0, 'Iris-virginica'],\n",
       "       [5.8, 2.8, 5.1, 2.4, 'Iris-virginica'],\n",
       "       [6.4, 3.2, 5.3, 2.3, 'Iris-virginica'],\n",
       "       [6.5, 3.0, 5.5, 1.8, 'Iris-virginica'],\n",
       "       [7.7, 3.8, 6.7, 2.2, 'Iris-virginica'],\n",
       "       [7.7, 2.6, 6.9, 2.3, 'Iris-virginica'],\n",
       "       [6.0, 2.2, 5.0, 1.5, 'Iris-virginica'],\n",
       "       [6.9, 3.2, 5.7, 2.3, 'Iris-virginica'],\n",
       "       [5.6, 2.8, 4.9, 2.0, 'Iris-virginica'],\n",
       "       [7.7, 2.8, 6.7, 2.0, 'Iris-virginica'],\n",
       "       [6.3, 2.7, 4.9, 1.8, 'Iris-virginica'],\n",
       "       [6.7, 3.3, 5.7, 2.1, 'Iris-virginica'],\n",
       "       [7.2, 3.2, 6.0, 1.8, 'Iris-virginica'],\n",
       "       [6.2, 2.8, 4.8, 1.8, 'Iris-virginica'],\n",
       "       [6.1, 3.0, 4.9, 1.8, 'Iris-virginica'],\n",
       "       [6.4, 2.8, 5.6, 2.1, 'Iris-virginica'],\n",
       "       [7.2, 3.0, 5.8, 1.6, 'Iris-virginica'],\n",
       "       [7.4, 2.8, 6.1, 1.9, 'Iris-virginica'],\n",
       "       [7.9, 3.8, 6.4, 2.0, 'Iris-virginica'],\n",
       "       [6.4, 2.8, 5.6, 2.2, 'Iris-virginica'],\n",
       "       [6.3, 2.8, 5.1, 1.5, 'Iris-virginica'],\n",
       "       [6.1, 2.6, 5.6, 1.4, 'Iris-virginica'],\n",
       "       [7.7, 3.0, 6.1, 2.3, 'Iris-virginica'],\n",
       "       [6.3, 3.4, 5.6, 2.4, 'Iris-virginica'],\n",
       "       [6.4, 3.1, 5.5, 1.8, 'Iris-virginica'],\n",
       "       [6.0, 3.0, 4.8, 1.8, 'Iris-virginica'],\n",
       "       [6.9, 3.1, 5.4, 2.1, 'Iris-virginica'],\n",
       "       [6.7, 3.1, 5.6, 2.4, 'Iris-virginica'],\n",
       "       [6.9, 3.1, 5.1, 2.3, 'Iris-virginica'],\n",
       "       [5.8, 2.7, 5.1, 1.9, 'Iris-virginica'],\n",
       "       [6.8, 3.2, 5.9, 2.3, 'Iris-virginica'],\n",
       "       [6.7, 3.3, 5.7, 2.5, 'Iris-virginica'],\n",
       "       [6.7, 3.0, 5.2, 2.3, 'Iris-virginica'],\n",
       "       [6.3, 2.5, 5.0, 1.9, 'Iris-virginica'],\n",
       "       [6.5, 3.0, 5.2, 2.0, 'Iris-virginica'],\n",
       "       [6.2, 3.4, 5.4, 2.3, 'Iris-virginica'],\n",
       "       [5.9, 3.0, 5.1, 1.8, 'Iris-virginica']], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exploratory Data Analysis refers to the critical process of performing ... and try to catch hold of as many insights from the data set using EDA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x21f3779c828>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(Data)  # check the relationship b/w Each Col with Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x21f3ab1ac18>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dU+O2CASCBcKdD77OQ/sny/kmdYOH9p/kHRlvbhvbm/uWEt7cAsFS4dZtXdz9RGHl1c2dDXnLe0difO7hg8CkY4itrwVrps/W3+buk/u52LrpgpS0YRIaTxJNWtrs4fEkX3nqbZ4/MpLdZn2mfLtSYtzWed201nvxuOR4yRMK5oxi/e+WratL9qf5DLgradd9u97ma788mvV+jyR0vr+3F7Cu9b9ePcX39/bm2Va+c30bf3Ldeu59pqeidtY62FaAo9kPivJ7QL2qql9XFOXTwBNYSZr3q6p6qsZtEQgEC4RHD/Q7Lj88MEZXa7Asb26BYKlQTH/qpKUNx6wZ5KmJhra+tpT+1nTQpebuW4x4Ks1QNIluGJimyeMHB/nqL48wkbSCErcs8ftXruHDl6/B43L2X/C6ZFrrvUK7vQAppX++44H9jvvMt567HJ152jAJTST5zq+OZwNtG9M0+dG+Ph4/OMip0cnvf2vbgnzq+g1ctq51Vu2saW9XVfXuKZ8fyPn9EeCRWp5fIBAsTKbe6GzSJhV5cwsESwUn/emXniycbUwVGUP2WCmpvy0SbBcbZ6ZpEp5IZSUig5EEX/pFN/t6w9ltNnc2cNcNCucsq3M8hiRJNAc8NAc9SFLlr+MFtaWY/nmh6rln2q5oQiM0kSJtmERyrCkBDNNEN0xScZ1I3FrX4Hfz0avW8cGLVuKahXzEZsbBtqIoW4BlQPasqqrunnULBALBoqFcbVyx7X1u2THgdknWTVFotgWCyfFzPKOjbQlOfhH1up1njm19ba7+NndMtQQ9dLUG816R5+47dcz+9qWr2LS8gaRuYJgmP3m1n3/fc5SEZmTb8bGr1/Hbl64uGpQEvS5a63xF2yxYOBS7Z9fCz7oaTJfno6UNRqZUMm3yuwnHNHTDZOrXTlmCD160kj+8ah1NgerZU84o2FYU5evA+4AjkG2bCbyrai0RCAQLmnK1caW2v+nClXmabZvNKxo5OjSR/Sw024Kzldzx0xL0cHosmc1naPB7siXVp2L7C9v622hCy8uD8LplTo8lssfJJVcbLkswEEnwT48f5o+uPofljX7ueULlYP9YdvuLVjfxV+/ZxOoW54DLLVuSkXqfkIwsBkrds0vpueeTLSsaefrQpPtN9pmxvJ7RWIpwTCuQTV20pplfvHVm6qFoq/Pyzx+6sOjbmdkw0xHw68AGVVVT024pEAiWJOV6sJba/t4PXwLAYwcGSOppfG4XN164goSWZiKpC8224Kwnd/zYQXE4pjEa17hgdXM2yCnmL2z//JuHDgBkx5J9rKDPRUeD31Eb7pbBMCEatwKVr+0+Sl8ohpa2gpag18Unr13PTReuQHaQhEiSRFPAQ3PAg1yFV/CCuWEm9+zZ+llXm0MDYyxv9OU9M5Y3ejnYP0ZoojBkffl4iF/1jBQsb/C5uGB107SB9jtWNiZLblCEmQbbJ4AAIIJtgeAspVzN3nTb33PLRdxzy0V5627esUdotgUCCsePPS5kWcoGPlDaCeLaTe20N/hoq/cVrEtoRt5xwNKGe10ycU1HT5sktTSD0WSe5Ovyc1r5y3efy/JGv+M5hWRk8TLdPXs2fta1oi8UmxwbkpWkO5HUOTY8UbDd//nlEfYeDWWXyRK01nmtL4WSxGCm0qkTDT43TUEvX7j5/COVtLNksK0oyrew5CJu4HVFUXYDWWW5qqofq+SkAoFgbqimL2q5mr2u1iAvHwsRiqXQDRO3LNEa9HL5+jaguM92qXPct6uHnXt7Ccc0WoIebrtyLbdv31jR9QgE88VM/K+ddNoAfo/MHQ/sn7Hf9tQxZeu3E3qazZ/9OaYJdT43nQ0+QrEU48k0jX4XCc0glHE8ASth7PbtG/mNLR2OCY5uWaat3kudkIwsWqbTP1crZ6eSY03X5riWJp5KY5jQFHCzqbMRgPGkzvde6OXHr55CNyblJEGv5f0eTegkNCO7z8vHQ/z84CCDo3FWNAf4rUtX857zlvPi0RA/fKWPRw8MvHT8izdeXm47pxsVz2Z+/tJhnTCiFwgWMNX2RS1Xs+f3uDgzPvnGTTdMzown8bnloj7bV29c5nisW7au5r5dPezI8TgNx7TsZxFwCxYLM/W/dtJpRxMa0YRGLGO1NxO/7dxxa+u3tbRB2jAtuwMTXHKaI8MTeF0yST3NQETPe8BfsKqR//mB82it8xZcjy0ZaREuI4ueovrnzoaq5uxA5T7vU3nHigZe6BlmQktnTXaGx1O8py3IowcGuH/PsayLDsCFGanI4wcHs8u0tMHweIrzXRLffO4YYMmsInGNr+8+yolQLHf7il7ZlAy2VVX9DoCiKH+rquo/5q5TFOV/V3JCgUAwN5SrsZ6OUh6sTjzfM4xHlkkbJgYmMhIuWeL5IyOEJpxlb/uOh/naH2x1PIetPZ3KzhdPiGBbsGiYqf+1k077zFiiwEVkOr/t3HH7XPcQXrdMKm2ABLIkEfC6iKV0DNMKrnKDbK9L5tbLVvOxq89xbHOd101LnVdIRpYITvpnO2fm0MCY4z6V5OxU6vM+lYmkzqt9o/i9LpJpEy1t4HHJ+D0yD75ykvHkpMXf8kYff3LdBq49dxn/32OHWFbvJRLXs/s0Bdy82humsymAxyWRSpukM6Nh54u9tNUVSrHKYToZyReBDuCDiqKcO2W/K4HPzOrsAoGgZtTCF7UczV44puGSpQI7sNFYqqjPdlJPFz1HOOeV9tTjCQSLhXL8r6fqtG/esadgv+n8tmFy3N68Yw+GCQf7I/gyAXJuQJJ79ka/m+9+7HIaHezPvC6ZljohGVlq5Oqfc6nEm72aPu9T0dMGoYkU40mdvpEYdV43dV43WtpgaDzJ8PjkM8HvlvnwFWu4detqfB5LOjI4Gs/uk93O4+JU2Dp/Kp3fvnBMm3WwPd3X0YewJCQTmZ/2vyeAG2d1ZoFAUFO6imip58oXtZg1WXPQm33QT8XndlV0PIFgsVBqXE43Zp3We92y48yy0zjvag0iS5bPsJY2s17ZubhliVVNfrauay0ItCVJoiXoZVVLQATaS5DZ9M1aHiuXSFzjZDie/ZLY2RzAMEyGx5McH4kxnpx88/PuLR1852OX8wdXrs0G2vY+Nj63iwa/B0kCn8flqI8u9uwph5LBtqqqL2ekJBeoqvqdnH87VVV9e9ZnFywKhHPT4sROnJpKLXxRd3cPcccD+7l5xx7ueGA/u7uHuO3KtaQNk5RukNDTpHRLJ3rbFWu46cKVjse58cIVRc9x25VrnZdfsaYq1yAQzAW3busimtA4EYrRc2acE6EY0YTG5s4GhqLJvGU2ud7ZU2kJOntuO43zD21dBYBLlizN9hR8bpl1rUHqfG7ee97yvHV1XjerWwK01HmFNnsJ4HTPLtY3b9m6uuznSantK3k2pXSDgdE4I+NJjMzMuGGaLG/wcSwUIxTTsoGy3y3zqes38Jn3b6G9oXBG+n3nd+JxS5kg2ySVNjDMUs8Y5+XlMNOvpm8qirISGM18bs78fhT4hKqqr826JYIFy8rmAB/55ov0heNl79vVEuC7H7+iBq0STEe5GutKKZYI897zO2kJegjFUhgGyLIVGFywqimrsZ7qsz3VCjAXe5+dL55gNJaiOejltivWCL22YNET19I8+EofDX5PVjN7eixJZ6OfT23fWOCdPXVMOy2bOs6jCY11bfXcfPFKvrb7aN46WYKORj/NAQ8rmgO897zlXLauFRCSkaVIqXt2Mcp9nsxk+5kcyzRNRjN5C7la77f6x9ixqyevBoNbljh3eT0feedarjinzbFdsiRxw3mddDb6+dH+U5wIxVibc/4LVjU5tste/sapSGHp1RkgFROq56IoyveBH6mq+pPM5/cBtwL/BuxQVfXqSk4+Syp2Q9l+z7MFHowz4Zxldey68/pKTzuv5670vADXnLuMk+H4vP3N5pFqT98sSQefOx7Y72jXNzKRdNS5rVtWV+DvK6ga1eyzS7K/zjdO48XWqk59jV6NsWIYJiPjScYSGr/sHuLfnu7JujPIEnxo62o+etU6/J58CZckSTQHPDTX3mVE9Nk5ZrHcsxNamuFo0krozTAUTfKN547yVI5risclceu2Ln7v8jUEvM5SREmSaPS7aQ56C/KIyqSinWf6VfV8VVV/3/6gqurPFUX5e1VVX1UUJVBsJ0VR/hb4IOAFvqqq6jdz1n0a+DgwlFn0x6qqFvqKCQSCBU2xRJhiSSWiQI3gbMZpvMwkybESElqaoWiSwUicf326hz09w9l169qC3HWDwpYVjQX7NfgslxG3S7iMLEUW+j3bMExCEynGcqRUSS3ND185yX+8dIJEzni5blM7f3ztejqbnIssSZJEg89Nc9Azr/15psH2qKIofwx8H0vnfRsQUhRlM0V034qiXA9cBVwNBIE7p2xyKfARVVX3VdBugUAwDzgVIihWiKYl6KEvFCOS0DBNkCRo8nu4ZhoZSzUL8QgECw2n8eJ1y+hpgxOhmGMxkWLYY+Wt/ggJzcDvcfGOlY3cuq2LC1Y1EZpI8sSbp7n3mbeJZ5IhJeDXt3Rw53uUbGKlXchjdCLFumV1/Nal81+GW1A7St2znbDfuFTz3lzsWNGERmgilc0pME2TX3YP8S+/eDvPOae1zstnb9zCRV3Fx8ihgTGefGuQ48Pz/yyZaZh/G/AbQD/QC2wHPpJZ9jdF9rkBeAP4MfAI8OiU9VuBv1UUZU9mBlwgECxgbJ1f70gMw5zU+TnNjAG0BL0ZnZ312TRhNK4RLmHVV+wcu7uHiu4jECwmnJLD/B4ZLW1mZ7jtYiKbOxuKHsceKwdPRRiIJAnHNAYiCdTBMe55QuU/Xz7B//PQG/zzE2o20Pa5Zda0BjgxEuP1k1YK1svHQ3z7+eOMxTQM0+TI0IQYc0ucYgmKxRIBb9m6uqr3ZqdjfeWpbn762imGoslsoP326Sh/8Z+v84VHD+UF2m5ZYjyhcbDf2fu73ufmxMgE//eXRzk6tDCeJTOa2VZV9RTwIYdV95bYbRmwFrgJOAf4qaIom1VVtTVVPwDuA8aAHyuKcpOqqlMDcoFAsEAoVqTg8GCUu25QCpJKPvm9V+wCdVkkrMI15Z6j0kI8AsFCwylxLOh1EfAkHIuJFMMeK7b/vCRBwOPizFgSn1vj7ie6SWe+6UpAW503r8rj42+e5rJ1rezuHiLgdqEZJrlyVDHmli6lkheLJQje8cB+x2NV0k9y7/MSJh6XzERK58ev9XP+qiZCEynu33OMnx8czHt+uCTLScfuw4+83p/nRhXwuGip8+L3uPjCo29Vrb3VYEbBtqIoNwB/D7SSMxpVVV1fYrcR4LCqqilAVRQlAbQDZxRFkYCvqKoayRz/MeASCme/BQLBAqFUkQKnQjRJ3apSNzWbJKkXT+auRSEegWChMXW83LxjT/FiIkWwx0pKN/C4JNyyxFhCQ0+beQFKwCOzvMFf4MUdnkiyoinAyXAcBxdAMeaWOMWKhxVbXs17s30sr1tC0yGasGatT4Vj/ODlPr6/tzevUqqcCbLlKYm6tqbb57Ycc4I5RWoW2rNkpprte4FPAweZebbvHuDPFUX5F2AFUIcVgAM0AgcVRdmCVTDnXcD9M220QCCoHcW0dF2tQV4+FiIUS6EbJm5ZojXo5fL1bY77+NyyY6VIu3BNMf13sXMIBIsZp/4O1ixf70gME0szmxtwlyryYetumwJuogmNiZRZ4J1d73PRXu8jlTYYjqTQ0gZu2bI/i6fS/PqXnqXB75lxURzB0qFc/XVXa5CDpyIFb1+myytwYm1bkMODUY6PJEjpBm5ZwueRiacMvp5jSxn0uvjw5V088lo/kYRecJz2eh8djX7294b54c8PFzxLSrV3rnODZhpsD5cr8VBV9VFFUa4FXsLSht8O/I6iKPWqqn5dUZTPALuAJPC0qqo/K+f4AoGg+hTzXwWrnO2Z8WR2nW6YnBlPEo6lHPfZtq6VX+W4H9jceOGKoudpCnocz1Gs4qRAsBhw6u+fe/ggYJVkbw56OD2W5PRYMrsMShf5uGXrar7y1NsYpkksZRTMgrkl0NJmdibP45bxuSSSaZOknsYtS4RjGsPjKVqCHjoa/QktfLEAACAASURBVAXHFyxNSt3niwWcW1Y08nSO3Z6dV3BLibwCJ8aTOiuaAzzx5mnAKkwT0wwmpsxkt9V5aQ54eK57mEvWtvCsOqm19rllPLLEhy9fw/7esOO1KJ0N2fE0tb2VXP9smWmw/VxmhvpxIGEvVFV1d6mdVFX96xLrvgd8b4bnFwgEc0ApzfS+4yE8skzaMDEwkZFwyRL7jofY2FF4w20JevntS1c7Fq4ppv8rdo7nj4w4bi8QLAacxpWttc6Vj4QzxTsuWN1csmDIeFJnVUuAtnovr/WNFuRFuCRwZWzOTBP8XpkGv4czY0lsZbaduOySJXTDZN2yupoWvxIsHCrJjTk0MJYtuDTTvIJctLRBaDzFREpHHYzSEvQwMp7K5ApM0hzw0FaX74WdSpv8/pVreeLgIHFNJ+Bx8+Er1vCp7RuLPkuePzJctL2HBpwTK2up555psH155meuq7mJJf8QCAQzwDTNBV/muJTOLRzTcMlSQUGAYhrsE6EYD99+tWNVyGLnSegGfrer4ByjJRxMBIKFzky8te2gW5alogVE0oZJaDzJS8dD3P2EyvEc+7Zf27iMl46N5N1jLC23i4SWZkO7nzPRZDaHIncuPK6lRaGps4hK9Mx9oVjZeQVgPfcicY1wzKoAqacN3uqPMDyeyssVCHpc6IZBh0N59eHxBF++9SL+7v1bkKc8G0p5hm9sr3dub5FijrXUc8/UjWR7zVogmBGzK3gkWAicDMfxuWX8XhdBj6sig/1ydWb37eph595ewjGNlqCH265cW7K8eSmd29BYguHxVMGss88tE01oZWn5ivm8+ovIRZqD3pLXI7y5BQuZqf09mtDQDQPDsB7wuVptv0fmjgf2F/TlHc+8zc4Xj3M6kiI3THfLEh0NPtwuiYDHRUI3kCUreEmlTeJaOhuguGUJLT0ZaCS0NC5ZKpCQgPC7X8pUor8uN2fn2k3tTCR1whOpbAXIl4+H+OqzRzgTzZ88kSXweyTcsoeJlE4krqOlDQJeFx0NPtYvq88+A5zaVa5nuGmajvusaQ0WvRZ7+aMHBl46/sUbL3c4dElm6kayFvh3YB1wDfAA8DFVVY+Xe0JBZaxsDvCRb75IXzhe9r6XrW2pQYsE5WIYJuNJPesX6nPLBLxuAh4Xfo887ax3uTqz+3b1sOOZnuzncEzLfi4WcJfS5fncMg/tPzl5PZgYhsm5yxs5OjThuE8xbt3WlXctNjdeuJLHDgwULL/tijVFr+fY8ARqzqvMudDfCQTlkNvfowmN02NJJCRc8uR4sYkmNGJJ621R70iMf3lS5eHXTvHT1/vzAmWw5CCyZNn+9YfjuF0SfmQkCWIZb22XLNFSZwUePrcLLT2ZaGZi5UWsb6/LO+58aFoFc0cl+utycna+8otuxuIa71hp1WDoC8X4P788wt6jIcdjGyaEYjobO+roC8VxyRL1XuvLYl8ozs0XryrarmLPktuuWMvjBwcLltu5CE77bO5scOz3b5yK5B6rogSimcpIvgbcDfwTcBr4D+C7wLWVnFRQGX3hOMeGJ6bfcAqrWwI1aI1gtiR1g6SeYhSrpGzQ48LvdRHwuBzdAcrV2e3c2+u4/c4XTxQNtkvp8kzTpKPBl63u5ZIlWuu8hCdSZWv5Svm8nrOsjp0vnmA0lqI56OW2K9Zw+/aNXPWPTzse69EDA5zbUT/jv4tAMNfk9vfnuoeyYwTIjptU2qSrJZBneeZ1ScRSaX786ilHez4T694Rieu0BL2sa6snltKJJHRS6cnxY3snHx4cy/O+l7CC8dwvyyD87pc6leivn+8ZnjZnR8LE7ZKJa2keevUUa9qCfO+FXn786il0Y9Lz3ZepmGqYYGBFry5Zoi8cZ01bkNGJFOPJNF63zPJ6b8XPkmKe4TZT1xXr9zv39tJWXyhvKYeZBtvLVFV9UlGUf8oUpfmGoii3z+rMAoEgi2maTKR0JlLWrJPXZclN6n1u/B7LKq9cnZ2dgDWVUvrnkro806SjwU9HQ/4r5yNnxtnQUUQbV4Jifq63b9/o+GWg2PWkSmjGBYKFgt3fb96xJy9wtseNLEskNKsvy5Il+TgdSTAYTToG2jYuWcLnsgKfVNrA63Hx/F8UzoNdu6mdLZ89jZNSa+o9YaF5FAuqSyX66+lydrwuiZQO4wkd0zQ51B/hI998idH45H37glVN3L59A3/+g9dwuWRcOcep87pIaFbOTmdT/gRhpc+SYsuLrfvSk4Wz3QCjMW3Ogu24oiiryXwhVhTl17As+wQCQZV5+XiInx8cZHA0TmdzgP920SquU6wZ32PDEwUP3mJ+uC1Bj2OAWkz7BsX1b7bOzUnn1xz0lK3ZroRi1+N1u+bk/ALBbLA1n3ZS49SZ7Zagh67WILphEEumOTYaZ8zBWziXoNeF1yWhm2TvC7n3g6n604BHzpZuz2XqPaHUfUCw+KlEs90S9Djm7NR5XbhlKVuYJpZKMzSezKux0NHg40+uW891m9qRJIkmv5twTCNtmPg8LlwSjCfTBcmPNrXod8XqPDj1++Yi+u9ymKn25C+xqjueqyjKa1ia7T+f9dkFAkEeLx8P8c3njtGfqerWH47z1Wd7ePKtQd65oQ3dMHDJlsuAxyUhS8X9cG+7cq3z8pzytlOxC21M5Zatq9myopHTY8msi4Kt81vfUe+4fHOZ/qvTUex6tq1rmZPzCwSVYmuge0esZMiUbtA/mqB/NJHttwGPTDiW4tjQBN1nxvMCba8rPwjxuWXqvC60tEFSN/OSwez7Qe45DdPSn3rcckHhGyi8J5S6DwgWP8Xu5aXumVdtXIZmGFkXG1My8bgk3rGyiYmkldDYH0lwcjSeDbT9bpk/umod3/mjy7he6cjmJV2ytgV35u1tQk8zoaXRDINt65zzy6rd75zGxt1PqGxZ0ei4fbFnTznM1I3kFUVRLgM2AS4my7ALBIIq8nOHhA6Ax988zWdv3JL9fWA0zormADddsIItnQ1EExpBrzvvFZ8txXDSPxejlP7th6/0Oer8jp4Zn5X/6kwpdj2z9X8VCGpNrhbUfnV/ajSOYUDA66Kz0ZddNp4sLO7REvQyMpFkPKnjka0EyHq/h7WtQUwJEppRoEl10p92NPhpCXoZS+gl7wml7gOCxU8l98yElqaj3kcolkKWJHxuCY9LxuuRWd0a4Fl1KO+t67u3dPCJa9bTPsXKz+uS8btlmgJuRiZS2byB1kw//+Q162ve74ppsw8PRrnrBqWk/vuNUxFn3eI0zFRGgqqqGvCm/VlRlDFVVZ2/BggEgooYHHV2mxnILL9sXSuXrWvNWxdN6kSTOpDE73Hh97iyDifF9M+lKKZzK6bzq1SzXQlO13Pzjj0V+b8KBHPFVA10g9+DW07icsGGZUH6RxOcGZ/UZrtkieaAm5agFzkzG9jVGkRGIg08fPvVZZ/TxldE0z2VUnpXweKmEs12XyhGZ5Of1a1BYikdXTeIJnRe6BnJJj+C5ehxx/aNWScSG48s01xnnfP4SIz2Bj/tU/J/ToRic9LvSuUkTKf/vvfDl1xRyTlnHGw7IJyfBYIq09kcoN/B3nFF88wcZRJamoSWznM4Cficfb3L9dHtag3y8vEQoYkcn9U6b0nNdrk+35Ug9KWChUCp8eTURxv9blK6weHT43kOJBIgSSahCY1IXKO9wc/KpgAjE0nCMQ0JuOOB/TMar07jIuB29vEWLD2K9clSmu07H3ydRw/0k9QNfG6Zmy5cyT23XMTatiDHh2NE4xpxLc1QNEkiR5fdVu/lE9es591bOrJfEMH+4uilMeDOykgq0YxXk/l4ZlTkF5ihRH60QCCohPed3+m4/L3nLS/7WLbDyXA0yYlQjJOhGENR61X0bvWMo2Ztd/dQ0eP5PS7ORJPZWQzdMDkTTdJS53XU/4VjKXY805NNarR9se/b1VP0HJUg9KWC+aaYBtQeT7l9VMLEI0MqnWY0rhUE2iagpy3vbJ/bxfB4kiPD49kx1hz0zGi8Oo2LaEJjcCxR1rgXLE5K9climu2jQ+M8tP9kVnOd1A1+/Oop7nrwNa7Z2E40oTEQSdAXjmcDbbcscdsVa/juH13Oe96xPBtoy5JEc9BLV0uQpqAnr45EJZrxajIfz4ySM9uKohTLpJIQM9sCQdWxJSK5uuz3nre8QDpSCam0QSptEE1ofOuF4xmtnGU5pqdNDLO0j24xn9WjQ+Msb/QXzFK8cjyE5HCbKOXzXQlCXyqYb6bzpbb74n/tP4k6GKU3FCcSn0yAdGUC64SexjQh4HFhYhJPpTM+2hqNfk9epcnc4zvhNC7OjCXygvuZHEewOCnVJ03TdNRsHxoYy9vW77b64cOv9VPv93ByNJ5XWOmCVY38zfs2syLHqk+SJBr9bpqD3gKbQJv5zrOZj2fGdDKSX5LxzXdYN1z95ixsRMl0wWx49EA/y5usV8LtDb6iNyInXXa1Gci4ndh4MskuA5E4etpwLCVfymfVSf/XG4rhd7uYSimf70oR+lLBfDITX+oLVjfx/JFhfnZwMDuj5/fIfOKa9Tx5cAATiWMjEwRcMvFM0I1kOY8k9bTjK+5y/Ydv3rFn2nYKlgYl+6RpOt6zDdN6o+KWJbwumVgqnZUwfOtXx7PbbWyv5/btG7ioK1/20ZAJsj0Oz4+pbZvvPJu5fmaUDLZVVT1nugMoivJJVVW/XmTd3wIfBLzAV1VV/WbOug8AnwN04H5VVb9RTsPng9mUTAdRNv1s5+4nu7O/u2WJziY/K5v8rGgKsLJ58ufut4d5/I0BIgmdJr+bD1y8qqRdXyVM1YZruommp1nV6uO/9p/kGfUMQ2MJulrr+K1LVnGt0lHU59rnlh01276MzdjUmfBlDbMrDuBEufpzgaCalNKgGobJi0dH+F+PvoWaM3O3dW0LG9rr+M+XTjAykaLe50JGIqblyEpM6xW7iRWITPXmDnpd/M7XXiChpWecdyHyGxYv5dznpquZ4LROliy5YNowmXB4A+L3yHhkiROhCf7xZ4eyz6aHX+3n4ddOcjqamlFuznxrtueD2SRI2vwJUBBsK4pyPXAVcDUQBO7MWecBvgxcBkwAv1IU5RFVVZ19zxYQlZZMB1E2XTCJbpicDMc5GY4DYcdtJGB4IsW3nz/O22eifOjS1axsDtAyRf9WCe87v5NvPnesYPn6ZXX8e87yt/rHePtMlHBc40PbVvP9F3qz7bdfJ25d18q+45PXYOvvNrTX81bOa0kDE8MwuWpD26zaPhVbm2hjaxMBEXAL5oQtKxp5+tCZ7Gd7DPxmex1//9hbfPeF3myuQ73PzZ9ev4GR8SQ7XzyB3yNT73MzltSt2Wys2UX7dxOT5oCHhGZ5c4OVdJY2TKIJnQMnIyxv9GHMoN/fuq0rb6zYiPyGhU+597np/q+nrvPIElef28Zz3SMF+0gSnL+yCXVwjJRpSUUiCZ0f7z/J0aFx9h4NZbe1c3OAogF3sfFyyxKujVCNYLvYU/8G4A3gx0AjcFfOui1Aj6qqYQBFUfYA1wAPVqE9AsGC5Mu3XkRfOM5AJJ4paBGnPxJnIuls22mSeeCaJru7h9ndbSm3/B6ZlU0BVjRbkpSVzX5WNgdY2RSgo9E37Ss8KK4Nd/L51nSTn7zWz2dv3MJEMs0jr/eTTOu0N3r5zYtXcWx4gjWtfobHU8RSk7MU4ViKjgYfoQmr6pjtpZpbWawaTKeXFQhqzVQNap3PRcAr8/XnjuaN76s3tPEX7z6Xtnofv/+NvdR7XcS1NCZSNh/CxMTndpHU09kx09HgJ5rQ8ry5tbSRDcjDMS37Sr5cHbfIb1gclHufm8n/9YP7TtIXmmBNax3vXN/KsZEYz/eE8goftdd7+dKtF3HnD1/PTvIEPC5kCeKawS+7h/A5yAVL5ebMt2Z7PqhGsF3MlWQZsBa4CTgH+KmiKJtVVTWxgu9IzrZRoKkKbREIFiyXrmkp0LiZpslYQs8G4P/488OYpolpFh9YCc3g6PAERx3esMiSVbjCDsBXNOX/rPdNDnknbfi39hTOdsOkz/dtV6wpkLR86vv7ME2JjgY/HpdVcEOSrNfe69rq6Gz05+nDq63Lm4le9izCBVRUdEFQObYGtdHvwSVJnAhP0BdKZNc3Bzz82bs2cr1ilatu8LkZT6Uzb4esAMbOh5AkeOsL7+XmHXvyxo3tzY1sSQF6zoxn16VyvsCWq+MWLA4quc+V+r++dlM729a1MBJN8mz3EDt2HeFUTp2Hta1BPrV9Q/YZEUno+NyWjCSuT37RcyhICpTOzVkImu25phrBdjFGmKw0qSqKkgDagTPAGJD7vqABGK1hWwSCBYkkSTQFPDQFPGzubOTrvzxCJKdMs2mamEDQ6+IPrlw3OSseiTMQSeQ9ZMG68Q2OJRgcS7D/ROGQavS784Jva0bc+r2t3luRz7e9j6XPnozz3LLEeELH45ZwZ6reSVh6vVhKxy3LeFzSrCUxi1mHmjZMDNPStVtfsMzsQwwmv3DZ/cCwNfCmiWFA2rSkOYZpohsmzxw+0/rfr1kvfNzmmK7WIKfCMaJJnd6RWJ5jw69v7uCO7RtpCnrwuGTa6r0EvW7qfW7HHIjmoDd7zKn92uuW8363x3/u8sXQ7wXlU837nJY2CI2nONgf4avPHmFf76QMsMHv5g/fuZYPXrQymyjvkiVWNfs5PZbM69tQ3DjC7se1vpbFQi2D7T3AnyuK8i/ACqAOKwAHOAScqyhKKzAOXAvcU8O2CASLgg9cvIrv7+3NfpYkyzzvQ1u7+K1LV+Vta5gmI+Op/AA887N/NEEkXvggH0vojA1GHV/XeVyWL2osqeNxWYGw9VPm1zcXnwkrpv/+wEWr+MmrJ4nENXQD3DI0BTz87uVrGIxMzvpJkoQsgUuScLsk9vWG+fnBAfrDcVa1BPngxSt554ZluCQpO2s+Oati8puXrGLHMz15ywFuvnCl9TfIBLH2DIwEeUUXAGQZ3LKMS5ayDw/DpMB9xTBMK8C13z7knM8+v2Fa25iZYDhtWBta+00eI11sSmgWaGmz+gcVTMt7z+vksw8fzAue3bLEdqUDzTD4ux8fYMPyej50aRddrR0A3Hbl2qy2NRf7zdGt27r4XOaY9qt2v0cm4LFe2bcEPfSPJrJJyHYCpdBfL02qobc3TZNIXKN3JMa3fnWMn77en70vyhJ84KKVfPSqdTQFrBlnezKoOeDht7d28a9PvV2Q8H7VxmV5OTs2pZL6b93WxV0Pvk4ollMgLejlrhuUGV/LYqMawbbjjLSqqo8qinIt8BJW8Zzbgd9RFKVeVdWvK4ryaeCJzLr7VVU9VYW2CASLGvsG9cjr/YwlLG/dD1y00vHGJUsS7Q0+2ht8XOhwv51I6gxEbG14goHRePb302OJgtd/WtpkKJrMfMpXIvy/P3mTZfXerDY8Vy++aXkDH/u1dTzx1pk8/Xf36XHG4jpGZvLdMGAsrtN9ejxPvmKaJmkT0pj86kgoL3BXB6Pc/bjKx69JFbVDPGdZHb97eVeB/nx9Rx0j40nHfcpFkiRMEccKpqCnDR57Y4B/eOxQXqC9osnPu7cs58WjI/g9LvxeN8eH49zzZDeSJHHtpvasnnXniycYjaVoDnq57Yo1JV0cAh4Xt2zr4vBglDf7I5kvxFLRV/mCpcNs9fbxVJrTY3Ee2n+Kbz9/nGjOG9Sta5r51PaNnLOsLrus0e+hOejJzm5fsKqJlqCHUCyFYVgTFC1BD5+8Zj1vrI+U1Y/fyDiR5D4bwjGNN05FlqzEabqiNp8rtV5V1S+oqvquEuv/usS6R4BHpm2hQHCW4aSLroQ6n5uNHfVs7KgvWKenDc5Ek9ngu380PhmYjyaIa4Wy3+HxFMPjKQ6cjBSsq/O6WJGRpCxv8HF6LMFDr/RZnq1TpCKPvN5f9PqcEjTBSuQs5T1ea29yEWgLpnIyFOPvH3uLx988nV22osnPX71nE5euaeEfHjtEQ8CNphvkDqfchLbbt28sGpT88JU+R13r4cEo9374Eu54YD913sJHuEgMXrpUorfX0wahiRTPqme479kjefKNVc0B/uS69Vy1oS17j673WV7ZudIksPpjR6OfjkZ/3vIH953k3g9fUlahsp17ex1rNlS74NlCYrqZbVHGRSBYgrhdclazPRX7VWP/aIJTo5Z7Sm4gPjJRmPgykUrTc2Y8L2lrylGzmu3QRIo9bw9nZ8cD3slM9sFRZw/7gSLLBYK5Rk8bPLTvJF98/HB2NlsCfuvSVXzs184h4HFR53UTiaVI5SRA2sw0CWy6hDiRGCyYjkhM48CpUb666wgvHJ209LNygNbym5esygbVAY+Lljovfk+hswhUt7855SpAbQqeLRSmK2rzeafliqJIWA4jAoFgkfLy8RA/PzjI4GiczuYA7zu/k8vWtfLXD73B/t5wtnTspWtbuPtDF2b3efTAACdDE9T5Paxrq8MtS9nZ8cFIIusnPBXbYcUwTT730zezy1uCnmxBn7hukEyls5pxy51BKpmguZAp9jdejIjCQXBseJzP//Qtnu2ezEHtaPCxqiXAi8dG2HtkmMaAl8aAh6PDE8S1SVsze4Z6pklg0yWRdbUG+VXPMKNxDTNT+a854OHXzj27/k+mYyn125leS1JP0zsc49MPvsbBU/kl2N9/QScfu/ocWuusBEavS6a5zpvnVOVENZMaixVIaw56uW9XDzv39hKOaTMqkFNtatVfZqTZVhTlk1gJjHU5i48BS3O+XyBY4rx8PF8b3R+O883njvGN547Sc2bSUtAE9vWGuetHB7h12+rsPh6Xi5Rm0D0Y5ePXnJMNINOGyfC4JU/58av9vHBkOOsXXkyIEY5Z1SdzC+DYSIDHJeN2yXz12Z48vXhnk39GnuLzRbG/MbDoAu6zvXCQpqfZ+eIJ/uUX3YxltK6yBNdtaqcvFGNoLEE8lSaVNhgazw8i7IIdYNn3zTShbbqEuNG4lhewmKY9lpbu7GC5LKV+O5NrMTL33x+83MdXn+0hoU26VUlYkr4VTQFa67zIkkRz0HLCmokjVDULIhVLDl7fXpe3fCYFcqpJLfvLTBMk/xa4CPh74O+A92NVhhQIBIuQYtro3EA7l1d7wzT4nW8XuXpqlyyxvNHP8kY/l6xpYeeLJ/KSPd9z3nKu3rBsSmEf6+dQNFkQkJtAKm3w1sBYQTAuS9De4MvOik8t8FNfpL1zRaX684XI2Vw4qPt0lM/95CB7j01WydvYXs9dN2ziP17uI+h1E03oxDKBje0y43XLyJIl2UrpBqm0yV03KDP+e02XEPfK8ZDjfk7OEGcrS6nfTnct0YTGM4fPcO/TPfQM5cv53BmXJUmS+NmBAT51/Qaag94CzXQpqlkQqVhy8M4cJ65c5krLXcv+MtOn0RlVVY8pivIGcIGqql9VFOVTszqzQCCYN4ppo4thlNinlJ66WLKn4lCW15oBnLQuzA3IByKJgsqThgmnx5KcHkvymsM9ssHvzgvAcwv8tDf4Cuz/qs1S0p+fjfrgeErn288f595neoilrAxHj0viD9+5jlu3rcbrdjGe1JEksrPdAEbOV0bDnHzNLstS2Q/sUglxSd3AqQsndVHTyGYp9dti1zIQibO/N8RXnn47W2XYxiVLuDJBtiRBncdFXNNpq/dV1IZqFkRySg52mu2GudNy17K/zDTYnlAUZTtwAPhviqK8DCxOEaVAME8sb/LnFS4pJquQpUkfaCPjzWy7Ydi+22CXczcny7rbCzNe1LIk8eLRER5+7RT9o3FWNQe5+eKVXLVxGUpnI4cGI0TiOppu4HbJNAc8WQ/fAkyT1a1B3jg5yshEKs83+8KulqLa5HI0y163TFdrkC4HDaBpmoxMpBjIDcIj8WzS5qiDp3g0oaMmoqinnT3FOxv9Uwr8+K1Z8iY/Poe/Q7n660oKBFWK3baXj4ef/NPrN1xa7eNPp9cspnNcjHpZ0zTZubeXe37RzWiOTOMdKxq564ZNrG2ro87rtopANfrpHYnlFZiRsWwiU7qBYZoc7I9gmuD3yNy3qycvwKjk72PvY7U1k36ZE3Q7lc4+WynVbxdbn+1qDXIwY5mX0g0CHpnWOi/RhMnvfH1vXrGZd2/p4NXeMGMJHT1t4vfKSCZEk2mWNViB9p0Pvs6jB/pJ6gY+t8xNF67knlsumq/LA0pruefi/6WWxXZmGmz/GfDfgb8CPg6owP+c9dkFgrOIYlnetWJ39xBfeert7OejwxN8+am3cbtkNnU28ORbk5ZlaAbRhE5Hg49eh2/x15y7jNY6L+GYjtsl43VLmCbEUgaGafCDl/oAE7/XRXgixfde6OXt0+Pszkkkm41mWZIkltX7WFbv44LVTQXrYymdgdEEpzKFfWz3lFOj8aKe4n3hOH0OwTBAW703W1lzZVOAuJbmVz3DeFwyLmlm11Ks2M97z1te1rVPR7423KyJiL2UXrOYzvGNUxEez5HSLAa9bCyl85n/eoOHX+vPfhmWgGX1Xv7gnWtY315PW70vm0xm/11agp6sLluSrBltw/4GnPmhp808/Wkl+tDcfZr8His5EpByTE9uvHBFVf4WS4Fi/XZzZ8Oi67NbVjTy9KEzAATcEjEtTWgoX/a3ubOB27dv4LyVTfzT44fZ3T2Mx02eletVG9q488HXeWj/yeyypG5kP89nwF1My33VhrY50d5XU5c+lRkF26qqvqkoyl3AxcDngVtUVTWm2U0gEMwjpfRnpmmyvNGXV52uJejhgtXNdLUFeaFnhLRp4pIk3rmxje99/Aqu+senAdB0EwMjW0HspaMhNnbky0JkSeIXbw7SlplFsWfzDQOeOnSm6prloNfNho56Njh4iqcN05Kn5HiJWz+t2XFbIpDLyHiKkfEUb5wqTNqUJbJuKTt2HeFDlyays+PLG/1ZHaR9hnX+ywAAIABJREFUjVOL7VT72otpw6tJKb3mHQ/sd9xn54u9tNUVvq5eqHrZfb0hPvuTN/NyAwIeF8sbfXhdMr/qGeHWbWvydK65fxe5P0JCM4hkXnnHUum8gN2OvW39aSX60Nx9ulqDEIoRSVhuJAG3ixsvXDHvs5MLiWL9ttjffufeXkeJxULos4cGxljd4md4PEU4puW9GW2r8/KJa87h3e9YjixJuGUZn1umOehmeDyFhCUpaa3zktQNfvGW8z3jsQMD89p/imm5Dzkkz0P1/1+qqUufykzdSH4D+A7QD7iAZkVRblVV9eVZt0AgENSEkvoz03QsmHEiFOPh251zn8MxzbEQQcJBI2oCQ+MpGoPegnUjEynWtAbRDRPdMEmnTXTDQE+baGmDVLq63+NdslTSU3wsrk9KUnL8xPsjcUbGC7WChmnNBCV1GE/G+HLO2wOXLNHR4MvKUlY2Bbhu0zJWZVxUgg5FSGZLufr7Simm1yzWz8IxzTHYXmh62Ymkzlee6ubbzx/PvoqXJWiv99Hod+PzuPC5XfSF444JZVP/Ljfv2INhwsH+SJ7Dtq3ltvWnlehDp+7T1RqkC0sPXmzcnu049dsvPVk4ewkwGtMcg+357rOmaXIiNMHpaJKx+GR+gAS01nn57scuJ+B1IWfKqzcFPPSOxFhW72dZfX4RmhOhWEH+i81C0Ps7ablv3rHHcdta/L9UU5eey0zv/F8G3qeq6usAiqJsA/4vsK3qLRIIBFVhqsYvd/baNM2ytYwtQQ/D4ynShomBmZ3Z9rtlogmt4DzNQQ9noglCEyl0w8SdmVm5/Jw23C6ZYtJSwzBJZYJuTTdI6QbJjP612kiSRFPQQ1PQw5YVjQXrE1qagUiCLz/VzelIAi3zhcD6Zxbo7tOGyUDEkrHsc0isbw54JrXhOc4pK5r9tNV5Z2TBNZVi2vC5opjOsSXocdi6OvrHavFCzwh/9/AbHM15Hd9W56XJ78bjkgn63IzFU/SF40jAHQ/sL9CKTh0vfo+L02MJICeXAiswShtmVjNbanw6sbt7iKFoknBMq9i7W2BRrM82L8A+G5pI8tVdRzh4aixPDlfvc9Fe72Ndez1v9kfY3T3EQCTOimbrnl1Kf6wOjuXZAtpMJ3WcLz17uWNlITLTYDtpB9oAqqq+kilsIxAIFii5Gj+Y9Pu9pbOBC1Y1laVlBLhq47I8nZ+BiWGYnLu8MS9Ysc+zvr0u75W8bpiciSbxuUvLimVZwi+7Cm78ST1tzShrBkktXfUZcCf8HhfnLKvjD65cW6C/Nk2TD21bTXuDv6Dc/UAknudQYTMa1xiNa7w1UJi06XPLrGjKD8RteUpno7+gfLJNMW34XFFM53jbFWvz9K821dA/zpZILMU9T3az88XebADTFPBwx/aNNPhdfH/vCXxumZGJVFaLvbzRV6AVddJdnxlLEI5pyEikc76OmYBmGFy1oQ0oPT6nYp/H7gOVencLLIr22SsXTp9NaDoP7TvFvz3zdvb/Gqz7RHu9l6DXjQRcuLKJH7zcl30rY/fR957f6Rhs37J1NQf6Rh1zczoairuUzKdneTljZaEy02B7t6Io/w58A9CB3wWOK4pyLYCqqrtr1D6BQFAhhwbGHHXZhwej2dd0M9Uy2jrvjgYfoQlrdtvWAIYnUo7nOTI0jkeWC2bCnz8y4niO6fC5rdf5ZN6KammDuJYmmUoT19JFK1dWg+n01xd3Fc6wjCf0rI1hNhjPyFWGosmCpM2kbnB8JMZxhwekhOUpbktTVmR9xQNs7mzg49ecw+NvnqY/kpjz98CldI4XrGqqif6xUgzDZJd6hv/10zfzkmO3K+382bs20hz00hSwKpr+aP8pjgxNFMwiw6RW1Gm8JHQDt0vCxCSd878hSdBR78u+wi81Pqdin8dug71Pud7dAouF3Gf1tMHeoyP88xMqB05GssubAx7etbmDUCzFYCTBOe113HppFw+9ejLPicTm8GCUu25QHK/ldDTheO4z0aTjcphfz/JyxspCZabB9sWZn1+csvzzWF/Y31W1FgkEgqrQF4oV1WVDeVpGW+fd0eCnoyFfA3jkzDgbOuoLztMbiuF3uwp0rtXyTLWSFGXInDepp4mn0tbMt1794Puyda1lJTfW+91s8jewaXnh7IuWtjzFc2fDbc34wGicxBRNpYn1IDwTTfJaX6TgePU+N6uaA9y+feMNZV9YFSimc6yV/rEShqIJvvjzw/zX/lPZ+ea2Oi9/8e5zuXrjMrwumWUNPvweF9cpHVyndGT111Oxx5CT7tq2AHTLMlNfRnQ0+vP2LTU+c8k9T+4+lXh3CywWWp81TZNjwxN86clufvbGQLaPumWJ37xkFX/wzrXU+9y4ZImWOi+NmT7wlae7HY93IhQrei2VeLTPp2d5OWNloTJTN5LtlRxcUZRXAfvJcExV1T/KWfdpLBtB2xvsj1VVdX7SCwQCoLhm7r5dPezc20s4ptES9HDblWun1bk5HauUzq+YzruYzrGYXKTZIWmyGmRnvjOkdIPd3UP85NWT9IXjtNZ5ee803thzhccls7olyOqWQi3oS8dGePj1AU6FYgR9bla3WImdtjzFyYd2PKk7+onXgtx+Y0t9Elp6QXkS56KnDR4/OMDfP3aYwbHJGb33n9/Jn1y3gXq/m+aAhxYHzXzueMjNSwh4XfzO117IvoVoCXqIp9KEYim0tIkkgdcl5xVOsiUgdl5EOfrrWvr/LnWc7o1zUY2wHELjSb7x3DG++8JxJnLcka5c38qfXreBrtYgkiShDo7xszcG6B3Jv2cXu88Xe1743HLZmu357INLof/P1I1kLfDvwDrgGuAB4GOqqh4vsY8fQFXV64tscinwEVVV9828uQLB2UsxzdxPX+/nsQMD2eXhmMaOZ3rYuq4lT+uXq3MrdqxSOj+gLJ3jTReuzGtXdnuHipK1YO/REf71acspRALG4hr/+XIf9T43F61unhPNd7m8fDzE/XuOA9aDzzBMTozE+Pg152S/JMRTafozfuK51TadnFOqTW6/iSY0uk9bZaGXN/owFpAnsc3JcIz//dghfpbTPzsb/fzVezaxdW1L3my2E7a2N5rQsmMpbZiMJ3QOnIzQ6HczltA5GY5bZdqljN11xrHGLUvW2xcmE0btvIhy9Ne19P9dyty3qyfPt9m+NwILIuCOJXUeOdDPvz3dw6kcV6G1rUE+tX1Ddsw3+N281T/GfbuOZLex79lKZ4PjfX6bWy6qsd7QXs+b/YV2euvb64q2dT774FLo/zOVkXwNuBv4J+A08B/Ad4FrS+xzEfz/7L17nBxndef9raq+z30kjW4zkmXLKhvbEr4hY7CxnIBJbMImxGaDAkkgCeza727Cms8GPhv2TfLuhk3MJruxN9xMCCCWoDiEIINtgmVsIyxsGSRfSx5b9+to7jPd07eq94/q6unuqerb9HXmfD8f2TNPV9XzdNWpU2eeOuf3ENF1/bFMP58yDOOZnM+vBT6p6/oa4GHDMP680sELwnLCK2duz6HTKCx8J/jc0XHWeOS5eemWFsvzc6gkz3HTyo4FmqmNesjlni8LSGTyGh956Ry3b11HKm0STaaZS9jpJ+k6qJ1Uipdm9iMvncs+eMMBjUtWdXLJqoWa4o++dG5BWy3JPae5M+zj0WR2ZrYVNImTaZNvP3+S//GIweis/UeIAvzq1ev5yE2biAR89IT99EX8RRVgnO/xR/90CLBnp1NpM5taMpcy7cLJsSgWoKGgafbx0qaFhUVfR4CQT+WK9T15dRGV5F/XU/93KbPrGRdJIOa1zptFImVy4NgY9z12mAPHxrPtXSEfv/XWjfzKtnX4NJWQX6O/I0DIr7H7wMuux9o3fME1n3nf6xc8de7HZxOomcWXHFQF17dmDs20waVg/+UG2ysNw3hM1/X/YRiGBXxR1/W7S+wTBe7DnhG/FPi+ruu6YRhOif43gQeAKeDbuq7fYRjGniq+gyAsC7xy5uIpk5CLjl4ilfbOc/MILIvl+UHleY5umqmNolSOoU9T6dbUbO6jHfCYmbzvxqidFOKlmX2mQVrapcg9p4mcvPLcn5udR3lkZJY/3fMSe4351UuH+sJ84jadK9f3lJzNLuTmLatY1RnMBi7D52eynyVSZvb+UhTyFGM0VUFRYN8f5Zc05dZFVJJ/3Ur57+2CV/BYq7qRSkmbFsdGZ/mbx4f5zs9PZYNdVYH3bFvHb994ET1hPz5Vpa8j33d7+bOJaNK1ZmZ4ZMZT5348msxLuZs/VvHz0kwbbHf7LzfYjum6Pkhm4Vld198OeJet2hwGhjPB+WFd10eBtcCJjGzgXxuGMZk53sPA1YAE24LggVfemldudMBDyLpY/nWtc+AapcvqlbNeyXcM+FQCPpXnj43zredOcHYixvq+MLdduZar1vWQNL2D7137j/Pdn59ici5FT8jHe968vqp0GS/N7LUuC/I0g8L8UJgPKl89O0XKtAj5VB7YO8zdOzY3NF82lkjxzWdP8Fc/OJyVXVQV+LfXD/Ght15EwKfSGwmUnM12I9eWAj41+92d4NqnKriZh1t9glceeF/Ez5OHR9o6oGg1+iJ+zk/HM28ZyK6kONAd8tzn3t0H2XPoNPGUSdCncsfWdYteVdGyLMZmE/z9vqP83b6jTOfIgl67oZd/v2Mzm1Z22Lr/YT+9YT+q6l0/kItXzUwxnfuRjDzlwmMVr6dpls72UqC44O08f4gdCF+q6/rPsXO2/0OJfT4MfBZA1/V1QDfgJHB2Ay/qut6ZCbxvBSR3WxCKcNd1Q67td2xd59G+1rX9zmsHPY9Vyxw4J7/32GgU05rPGXzy8EjpnSvAyct0Hh5OXqbXzGWx75g75nja4o0LUf72idc5MjrLYF+EFZ1BOoO+vMK3XfuP8/VnjjGZeYBOzqX4+jPH2LX/eMXf5ZeuXOPa/u4rVld8rHpw+dpuzk3FSaRMNFXBxF6AKJ4ys+ovaRPuf3yY33xwv+t1eWDvcLEuKiZtWrx4aoLf+cqz/Ml3X84G2pes6uBvd17D7950MZ1BH+t6w/RXuXBQ7v2SG8Q4P/dHAq6rS7r9weUcy8kDzw3c63F/LGcuHugkZc4vPmVh6/175Sbfu/sgDz1/MivPGE+ZPPT8Se7dfdB1+3KIJlL8889O8Wt/u4///fhwNtBe1xviz957BX/x61vZtLKDjoBdDN3fEVgQaIO3/995w0b39u3u7XdeO1hkH+8Jgkb586VKyZltXdfvAF4Grgf+CNgBPAw8X2LXB4Gv6Lr+NLaNfxi4S9f1TsMwvqDr+qeAvdgz5D80DON71X8NQVj6FMtb88qNfvLwSMX517WiUbqsXnmZ+14f5TO/dlVF37HUmAM+FcJ+LMtiLmkym0jx2EsLi0ABvnvwdMWz26X0vJtNod6tX9Oy6gmOjroTdO4bvuD6qrqW+bKTsQRf+8kx/vaJ17Pj8GsKH7xhI//2+iF8WvWz2bkU3ntrukNYCswlTTb0R/jEbTovnJosqz4hmwf+0HweeK4aSSvkvC8V3jg/g09VFsxs5y7ClcueQ6dd2x8+dKbi2e14Ks3BExP81Q9e4ydvzK8tEAlo/OYNG/m1q9cT8Kn4VJUVnQE6gsXDsWq0wb3anWNVUk/TTJ3tpUDRq6vr+r3A+4HfAi7HDrb/I7bu9l8Cf+C1r2EYCeADBc37cj7/GvC1qkYtCMuUSnOjq8m/rhWN0mUtlpdZ6Xcsd8yKohAOaIQDGqOzSSJ+Latb68zyTs15FxsVo1I970bipnf74mlb3bVwhUsvmfNa5MvGU2kOnZzkv3/vFX52fCLbfvnaLj5xm85FKzoqzs0uRSlbunnLqrL/iLh5yypWdQVZ0emeUyvUhvFoMqPHn9/uZYPxlHuqWDH96UJSaZOTYzH+z4+G+afnT2Xf+CjYb64+/PZN2Tcs5RTp5lJpzUwxm620nqaZOttLgVIz2x8E3moYRlTX9c8A/2IYxpcyqR/upbEN4kMP7s9bAaxcrt/YV4fRCIJQSKO0Ufsi/qryD90opU3uRm84v3+fqtARUOkOBwhoaktKDFaL2zX1qQrptEUiZeatFOryJhxYnM66ZVlcmEnwlX1HePCpI9nFf0I+lQ+/fRO/evV6fJpacRDTDJaCdnCr0xfxc2EmsWAV25Uey5IHfaprwO32hqaQtGkxOhPnW8+d4EtPHWEiNu8Trlrfw907LskucNUR8NHXEVjwB2orI/a6OEpdacswDOfs7gAeAcgUPTaVE+MxjlyYrfjfmSn3ZUoFQagtjcgLh2I5i5UXKObmJMO8Zu1laxauAunVf8q0iCVN7rxukMF+e+GaFR1BIgGtpYO/cnC7ph0BHxZgZjJjTSySpsnla7tdj1GtznoskebHwxf4rS//lAf2vp4NtN881MuXfus6fv3aQSIBjXW9oapzsxtJo+6P5cyNm1eSNM0FtnnjJStct/eqf7ndo/4F7D8AJ6NJ9hw8zQe+tJ/7HjucDbQHuoJ8+o7L+ev3b2PL6i4CmsqanhCre0JtFWiD2OtiKTWzndJ1vRfoxFYLeQyyi9ykiu0oCMLyplHaqM6r0FroeRfmJOdqk1fbv6Ny0oMf07SIJtPEEimiibS9EEob4XZNIwGNo6OzjM3aM4iaqtDfEeDiVZ388lVrF31d0qbF+ckYX/rxEb76k2MkM3rpHQGNj77jEm6/ag2KotQkN7uRLAXt4FZnLplmoCu4wDa90kWcvOyHD50hnkoT9GncvnWtZ7729FySV05Pcf8Twzx5+EK2PeRT+bdvGeL91w0R9GuoikJvxE9PuH3ssxCx18VRKtj+DPDzzHZfMgzjjK7rdwH/HfiTeg9OEIT2plHaqLXS83bLSYbSeYnl9q+qCp1BH52ZYqhYIs1MPEU0kWqbwLvwmr73/qcZ6Aox0JUvp3Z8LMrf/MbVi7ouU3NJ9r8+yv941MjTt77h4n7+8Be3sKorWPPc7EbS7trBrc6JsainbXpx353bShZDxhJpTo1H+cpPjvIPz57I/gEI8IuXD/B7N13MqkyqSlfQThnxae01k+2G2Gv1FA22DcP4R13X92EvanMo0zwD/K5hGE/Ue3CCIAiNpNF5iU6RpWUFiCXTzM6lmEmksVpgNctyqcc5S6RMTk9E+eJTR/i/Pz2eLbbsDvm459bN/MJlA9kCs3ZIGRGaQ61tM5EyGZ2J8y8HT/PFp97gwsx8oaW+pot7dlzCFet6AAhoKv2dASKBcpczEZYyJa3AMIzTwOmc30WiTxCWMO24cIHXmCv9LnddN8RfPmosaK9HXqLX2FZkUk2i8RSzLR54P3l4hJHpOK+cmbKXu7fAp9mv6j9xm17x8SzLYjya5MfDF/jLR428Gchbtqzi//mFzfRFAi01m92O98tS5b33P513De66bohP/ONBxmYTpEwLn1qdbaZNi4logmeOjHH/46/xypn5tLIVHQF+76ZN/OKbVqMqip3SFPbT20YpTbmIPdcH+ZNLEIQszsIFDs7CBUDLOlyvMb9wapJHXjy7oB28v0uj8hJLnWcn1cSyLGLJNNFEmrlEc5aQ98L5Duen5rLyZmAHJuOzSV44NVnReZuNpzg1HuNzP3qdb//sVHYhkv6OAH/wC5fy9ktXArTUbHY73i9LmdzFVgBeODXJ+Gwyu7qnaVKRbVqWxWQsyWvnZvjCU2/wg5fPZT/zawp3XTfEB96ygXDA/qMvEtDo7wi2XfGjg9hz/ZBgWxCELO24cIHXmHc9c8xVx7jUd2lEXmK551lRFCIBX/ZVdCJlEkukiSVTxJJmU2e9ne8wFk2QG/cqGXm1chevSaRMxmcTPPXaCJ/9wWHOTM4rRr37ijX8u1supivkx6eqrOoKZgObVqAd75flwu4DJzlwdCxvoSWHUrZpWRZTcynOT87xf589zjf2H8+q3wDcfOlKPvqOi1nbEwbAp9opI50lFqZpdcSe60d7W4YgCDWlHRcu8BrzRDTZsouGVHueC5VNcme9k2ZjZ72d75AqKOx0ZNZKLV7jpIycGo/ytz96ne+9MP8WYnV3kI+/c0t2cZ+ukI8VHUHXZaybSTveL8uF42PRogteeTETTzE+E+cHr5zn80++zrmpePazS1Z1cPeOzbx5yNbdd+oGesP+lrPNahB7rh8SbAvCEqbS/LtWX7jA7ft4LUTTG/FzfnpuQb7mWza5a+wW6+PmLau4d/dB9hw6TTxlEvSp3LF1XcVLODvU4jyrqkJH0Jdd5jmeSqOv7nRfh7oODPVHePboGG6T67FkGr+m8P7P/wSwJdiccwnw0IETHLkQxcTi+GiUqbl5Jdl/8+Z1/N5NFxMOaGUvZV2Meuagtvr9spzZ0B9hZGqOs1NzeauZqgqs6QnzwN5hdj1zjPFokr6Inw9s38CvXr2ev3jU4HuHzpDM2ak37OfDb7+IVV1B/uXgab7wo9e5eFUnd103yC2XrW7Ct8unVjYu9lw/JNgWhCVKNfl3jSwQrBSv76Ov6cqbfXIWorl4VQcvn5nKtqdMi/PTcYJF8im9+vjCU2/w4+F5Hd14yuSh508CVBVw1+M8B30at16+uvJldask5Nc4Px33/FxB4dBJeyn31d1BzNEof7bnJbAgbcHIdJzp+HyQPdgX5hPv0rlq0FZz6Ar66O8MLkgBqIR656C28v2y3Lnz2kHeGJnh9GT+QnamZS+pfv/jwwCE/SqxZJr//cPX+Mq+o3kKIwCaAu/Zto7V3SEefOoIAZ9KR9DPifEYn/3Ba6iq2tQUi1rauNhz/WjPLH5BEEpSLP/Oi5u3rOITt+lctLIDVVW4aGUHn7hNb4l8Pa/vs+/1C6zuni9KCvhUVncHeWNkBr+qomIHayoKflVl3+ujlfeRE2jn8vChM5V8hSytfJ7LZd/wBfyq9yMkt5hzKpbEryqcn4pzfDzGsdHZvEB7Q3+EL37wWq4a7EFVFFZ1BVnVHVpUoA3V3QOVsBSu41Ki8Bq8PjLjut356Tghn0rYrzITTzE1lyKRtvICbVWxiyB9msqjL53l0ZfO0hn0oalKnm3XypaqpZY2LvZcP+o6s63r+s+AycyvRwzD+J2cz94DfBp7JcovG4bxxXqORRCWG9Xm37XqwgVe32c8mmTzqs4FC9EcG4sS8mkLArZi+ZpefZgWuIlfxFPpEqP2plXPc7mMR5P2uS1xCiJ+lWRGOm06nsp7pR/wqazpspeyD/o1wn6NlV1B/DVaAKQROajtfh2XEt+5+215v8dT5oL7NqCp+FSFWDJFyrTVc3IzoRTApyp5Odgp02QqlsxLLXFodj5zrW1c7Lk+1C3Y1nU9BGAYxi0un/mBvwKuB2aBH+u6/l3DMM4WbisIS4VCDdhqqCQ3rxXy76rJJfTaxys3u88jNzvkU0mmzezDVAE0VWGgO+TZj9c5UxVw0/0I+lpHGaPeOOfr5dOTzCVNEmkTs8iql0GfiqrAWDRJwKdydCyaF2iv6AjQn9EiXt8XZkVHkJ6I3/N41VDOPeBmB4BoDS8Bgj6VuaQ9C+1TFYI+lUTaZDZhouB+T2uKHYAnTYuQT7X/+X2s6Ql72lKjtKkL88x33rCxJfy8UJp6ppFsAyK6rj+m6/rjuq7fkPPZ5cCwYRjjhmEkgKeBm+o4FkFoOrkasE8eHql4fyc379hotKxjOUFDIY3Kv6t0vKX2uXxtN+em4iQyElxObnZfJMD56XhWFcPJze4K+UnlzFpZmc8uXtXh2c/la7tdx3Xj5pWu7bdvXVv1+WknnPP14qlJzkzGGY8msSzLNVhRFegIaJiWZS/Kgz3D6ATafk1hY3+YFRmt7JBf4ze3b6h5oA2l7wE3O/j0d17k0995sSK7FVqTYObNVkfA/v9sIp1dWt3Ndtf1hEhZoKgKnUEfKdNiMp7ixktWeNrSZWu6KvZz1fDA3mHuf3w4q7AyHk1y/+PDngs7SZ51a1HPYDsK3AfcBnwM2KXrujOT3s18egnANNBTx7EIQktRTT5dpbl5zc6/qyaXsNg+r5yZqig3+8JMAp+q4LwMdl4PvzEy69nPq2enXc/Z1z+ynfddM0jIp6EAIZ/G+64ZrFqNpN1wzleulJqbCknIrxL0aXlBjYOqwO1XreFP33sFFw904dMULl/XzX961xZ21EnRodQ94GYH49Gkq2Rcs3NzhcqwLItU2sSXCbLjqYXSmI5v8KmwosNPKm0y1Bsm7FeYTaRQFBjoDBJPmZ629EpOEXYutbaXXc8cc23f9/qo5Fm3AfXM2T6MPXttAYd1XR8F1gIngCmgK2fbLmCijmMRhJaimny6anLzmpl/V814i+5jWXSF/GXnZifSJkGfRuHEz0Q0UbQfr3N2353blk1wXYhzvhI5AUtuKO3XFAKarerglVny97/zFtb32YuA3LR5VcOWWy92D7jZQcIlKIPm5+YK5TMTTzExm2A24V1QsK4nREdAy65E6vcpnJ2Yo68jQG9HIG9b59q72dJnH1uo3pG7T60ophkuedatTz2D7Q8DVwH/Xtf1ddiz2U7p/ivApbqu9wMzwM3Ys+DCEmMJ6PzXhWry6Yrl5nnlDDYql9BrvG451lcN2gtCuOlWF/uOlmW5fhbykPJTPZbz7o0EJM+xQpzzFfCp2WBUyfwn4tdImVbRwCagKdlAuzfsp69Fllt3s1FVAZ9LgWY9bKOZ9+dSRP8v3yfsV9l+8Qp2bt9QdFtntUcFiAR9WFgE/Zprekmxa98oX9IX8XNhJkHatDCxUDMrta7sWrhwV6sg9j1PPYPtB4Gv6Lr+NPYkyIeBu3Rd7zQM4wu6rn8ceBQ7leXLhmGcquNYhCaxrjfMhx7cz4nxyuV/h/rCfPUj2xfVfzP7LkY1+XReGqhOzqCDkzP4wqlJHnnx7IJ2qI3GcCkuX9vND185n/3dybG+c00X9+4+mNV2o41/AAAgAElEQVSphnnd6rd55EY758vt+9++dZ2rBN+Nm1dw4Oj4gvad2zdw1foe0ZOtAMf2+iL+rKZ5yK8CStEg22HHZQP4NXu59UbMZpeLm42mTYvO4MJgu9a2UW8N8OWIqihMxFI8+tI5Hnv5nOd2/R3227GQX8PvU0ik7BB75w0b83ymQ7Fr3yht6hs3r8zzmSYWpmlx4yXFF+lqFmLf+dQt2M4UPn6goHlfzuffBb5br/6F1uHEeIwjFxq2sF3L9F2Iqips6I9w57WDVTkbZ5/dB05yfCyaPZZX/vGu/cdY0bFw1mP3gZMNcXZOjnXhzParZ6f5wcvuwkMHjo7z+Q9eu+A75o7X7bNNKzvYtf84E9EEvZEAO7dv4O4dm+3qfZf2YscSFpJre/4zk6RMOD8VKyl9GPSp3KKv4v/7N1e25HLrXja6uifEQFeorrZRrD5B7LA6UmZOmlNmirpQdcSvKVyzoZ+7rhtkz6HTHBuLcdHKjuw1vmp9T0V+wcsv1/oaziXTDHQGGYvmqC5FAq656K2A2Hc+soKkIDSIQg3YaqgkZ3A8mnQNthuVe3piLOqaY318LOr5gIin0kXzD70+u3vH5rwgulR7sWMJ7ty8ZRXXbOxjdCZO2rT4nS//lDNTc7jrOthBzmN/eDMrO4OLWm69nnjZ6FzS5G9+4+q69+2G5IZXT2FR7rqeIB0BX17KUkfQx0Q0wbuuWMO7rliz4BjV+IVG+JITY1EGukNZ6VKHVrUXse98WtMDCoJQNl45g30eUmqNykse6o/w7JGxBTMxb7l4BcbZKeJJc8FiEsEqUwzc9Ge9gmyhcuKpNGMzCWLJNLFkmr/78RGOlUjPigQ0PvilZ3j/W/KvRSvlcTYzd1/qBupLQFPYsqabA0fHmY6nCPrsxWz8mspNTa5nqYZ2s5d2G2+9keXahZalxd44tyxe+q87t290bW9UXnLIr3F+pkD/eiZO0Kdy3UX9C+ZDLeDai/oq7sdLf/aBvcOL/AZC2rQYnYlzajxGLJnmZ8fH+d2/f45/POBdYhPQVDoCGrFkmpGZ/GtRjfZ6PWmmFn2zdfCXIr6ch8ZVg71Mz6WYTaToDPpIZ4p4J2JJ3hiZaSk7LId2s5d2G2+9kZltoWVZTHElwPUbKw/c2pFiOYOV5h/Wkn3DF/Cr6oLq+X2vj3LNhl56w34m55JYmaXQe0J++iKB0gcuwEt/dtf+4zK7vQjSpsXJ8Shp02ImnuLzP3qDh1+YL0RVlUw+rAVOUlBHQCOZtogl03mrazrXotXyOBuVb9tqfS9V/JpKykzTFfTRHfbzs2NjBHwqM/FUdhsFePXMNG9at3ABq1bOJ243e2m38dYbCbaFlmYxBY6DGamx5YBXzmAz85LHo0k0VVmgf+3oXA/1Ryic+6gmn6+Y/qxQPaZlkTYtnnljlP/5g8NcmJk/n+/dto7vv3gmmwvrU+2VIEdn7W3CBelAzrVoxTzOZt4jUjdQWy5b08VsPIXfpzAzl2Iqnsr+MZ9L2m1FJlo/n7jd7KXdxltPJNgWBKEu9EX8roFwKZ3rSvOvi/UjVM/YbIL//r1X+NccabzBvjC3X7UW49w0pmVhpi06gz4UBaKJdFb5IZEyXbWAJY9TqCeaotCR0cxe0xMioKnMJRcWY2seGu9ih0K9kJxtQRDqws4b3HPGd27f4JnPF/SpFedfF+tHqJ5f/l9PZQNtVYH3XzfIx95xMXtfPc/p8Rh9ET+RoI/ZZIpYJqBxFhJySl9NLJKmmdUCljxOoZ4kTZOUaZE2bZu6ZFWn63Zebz3FDoV6IcG2IAh14e4dm7nn1s2Z1QKhryPAPbfaUnw3b1nFJ27TuWhlB6qqcNHKDj5xm86+4Quux9q1/3hV/QjV46SEbFrZwf0fuJqPvuOSbPAd9GkM9XfQEdBQFYW0ZdHXEWDzQCeru4LZQjWfqjDQGcxKPXpdd3nVLNQEJd+mxmcTCwrtVQWSpiV2KDQUSSMRBKFuVKpzXW3+dbF+hOoY7AvzC5cN8IHtG/Bnli8/NxGjM2QrOyTTVlb3V1UVvnP323jv/U+X1AKWPE6hXhSuZTAeTeYV6jpMRBNih0JDkWBbEISm4KZz2xfxc2EmsUDBxMn5reRYpR6k7aaz22jWdAc5Nhbl5ycmuP6ifjRVYcuaLt64MB84n5+aYyxqX6/L/vj7WJYt+dgXyV8oRnJhhWbQF/FzdmoOM6ceUlVgTU9Y7n+hoUgaiSAIDcdLb/nigU6SpumZ81vJsYpp5raa3nMrYllwejzGg08d4aXTU6zvDfO+a+dzrs9Pzdk66mkLy4J4yiSRMpmNpzg3FWd6bv4theTCCs2gryOQF2gDmBb4VUXuf6GhSLAtCELD8dJbfmNkhoFMzq9CJue3K+i5vHuxY+0+cLKm+yxHNE2hK+znBy+fw6epeTnXY9EEKootq+bkxSq2GknApzIRS0ourNBUXh+ZcW0/Oe4u8Sf3v1AvJI1EEISG46W3PB5NsnlVJwNd3jm/5R6r1vssN9KWRdivkUiZHHPJub78j8+BCnOpdN5+pmWxoT+Cqir8zW9c3ehhC0KWeMpcoLENkHaX2Zb7X6gbdQ22dV0fAA4A7zQM49Wc9o8DHwGcdzYfNQzDqOdYBEFoHbz0lvsifpeti+f8VqPdLHrPpUmbkM6k87idF0ffXEXJpv3A/JLZci6FZhP0qa5vxTR3mW2xWaFu1C2NRNd1P/B5wG2t7WuADxmGcUvmnwTaglAGTx4e4Z5vPM9773+ae77xfNvmGHrpLe/c7q6ZXSzntxrtZtF7rozc8+LYoGlZJFxmDvsziwnJuRSazR1b17m2v3XzSqbnkhwfizJ8fobjY1Gm55Jis0LdqOfM9n3A54BPunx2LfBJXdfXAA8bhvHndRyHICwJnKI+B6eoB2i7nFhnvLsPnOT4WJQN/RHuvHaQm7es4qr1Pa7t1RyrlvssN1RVWXBecm1wVVcIy4KxaAIfCj5NpSfi4/qLVsi5FFqC++7cBsDDh84QT6UJ+jRu37qWX9m2jk9/58Umj05YTtQl2NZ1/beBEcMwHtV13S3Y/ibwADAFfFvX9TsMw9hTj7EIwlKhWFFfOwY2Xjq31ejfNmqf5UShZjEstEFHU/uilR2Sny20JPfduS0bdDvc843n6Qrly1NC+/pSofWpVxrJh4F36rr+BPBm4KuZWWx0XVeAvzYM44JhGAngYUC8tCCUQIr6hGYjNigsBcSOhUZTl5ltwzBudn7OBNwfMwzjbKapG3hR1/XLgVngVuDL9RiHICwlWrmoz2uBCFlsZmkx1B/h2SNjjEUTpEwLVVHwqQphv8Y933herpXQcty7+yB7Dp0mnjIJ+lTu2LqupX2psDRpmPSfrusfADoNw/iCruufAvYCceCHhmF8r1HjEIR25a7rhvJyth2aXdTjlUv+wqlJHnnx7IJ28M4xX0p56UuRkF/j/Ezc/sWy5QHTpi0RKNdKaDXu3X2Qh56f186Op0weev4kb9u80nX7ZvtSYelS92DbMIxbMj++mtP2NeBr9e5bEJYSrVrU55VLvmv/MVZ0LFxmvVhe5FLLS19q7Bu+gF9VSZtWVhZQAWYTqew2cq2EVmHPodOu7QeOjvP5D17bcr5UWLrIojaC0Ea0YlFfsQVq3IJtWWymfRmPJtFUBU1V8hazSeWsiS3XSmgVvFaejafSLelLhaWLBNuCICyKYgvUTM8lGY8mSaRMAj6VvoifqwZ7Kz6W5FI2h8L8+XBAI5awg+zcxWychWxArpXQPN57/9N5dR5ei9oEfVoTRicsZ+q2qI0gCMsDrwVibrxkJeem4iQyD7tEyuTcVJzL1nRVfCzJpWw8Tv78sdEopmXnz/tVhXRmFlvLCbCdhWxArpXQPBw7/ctHDZ48POK5qM3tW9c2eGTCckdmtgVBWBReueTfeu4Eq7uDC2a2Xz07XfGx5HVv43HLnx/oDtHbEWB6LsVENEFXKMDKriAhvybXSmgpdh84mdV+L1zUplB3WxDqjQTbgiAsGrf8x88+ZrguHFEqp1dyKVsDr/z5kF/j0T+42fUzQWgVHD/jtqiNIDQaSSMRBKEuDHnk7kpOb3sg109oZ8ROhVZCgm1BEOqC5F+3N3L9hHZG7FRoJSSNRBCEuiD51+2NXD+h3VBVRexUaEkk2BYEoW5I/nV7I9dPaCe+c/fbmj0EQXBF0kgEQRAEQRAEoU607cz2UF+4qv3WdodQSm9W832b2beMu3KqtS9BEARBEIRcFMuySm8lCIIgCIIgCELFSBqJIAiCIAiCINQJCbYFQRAEQRAEoU5IsC0IgiAIgiAIdUKCbUEQBEEQBEGoExJsC4IgCIIgCEKdkGBbEARBEARBEOpEXXW2dV0fAA4A7zQM49Wc9o8DHwFGMk0fNQzDqOdYBEEQBEEQBKHR1C3Y1nXdD3weiLl8fA3wIcMwDtSrf0EQBEEQBEFoNvWc2b4P+BzwSZfPrgU+qev6GuBhwzD+vIrjy2o8Qr1ZzAKWbojNCvWmljYr9io0ArFZoZ2oyl7rkrOt6/pvAyOGYTzqsck3gY8BtwJv13X9jnqMQxAEQRAEQRCaSV2Wa9d1/UnsvzAt4M3AYeBXDMM4q+u6AnQbhjGZ2fbfAysMw/izCruRv2CFeiMz20K7IbOEQrshNiu0E1XZa13SSAzDuNn5Wdf1J4CPGYZxNtPUDbyo6/rlwCz27PaX6zEOQRAEQRAEQWgmdVUjyUXX9Q8AnYZhfEHX9U8Be4E48EPDML7XqHEIgiAIgiAIQqOoSxpJg2jbgZfLk4dH+NZzJzgxFmWoP8Jd1w1x85ZVzR7WckLSSIR2oymv5MVXCYugpdJIxJaFElRlrxJstyhPHh7hLx9dKD3+idt0ufEbhwTbQrvR8MBFfJWwSFom2BZbFsqgddRIhMXzredOuLbvPnCywSMRBEHwRnyVsFQQWxbqRcNytoXKODEWdW0/7tEuCK3Ihx7cz4lxt3WtijPUF+arH9lehxEJtUZ8lbBUEFsW6oUE2y3KUH+EY6MLb/AN/ZEmjEYQquPEeIwjF2abPQyhjoivEpYKYstCvZA0khblruuGXNvvvHawwSMRBEHwRnyVsFQQWxbqhcxstyhOMcbuAyc5PhZlQ3+EO68dlCINQRBaCvFVwlJBbFmoF6JGIgjeiBrJItlx3xNVpZFsWtnB3ntvqf2Alj4to+wgCGUiNiu0E6JGIgiCIAiCIAithATbgiAIgiAIglAnJNgWBEEQBEEQhDohwbYgCIIgCIIg1AlRI2kiTx4e4VvPneDEWJSh/gh3XTckVc+CILQN4sOEVkdsVGgFJNhuEk8eHuEvHzWyvx8bjWZ/F0cgCEKrIz5MaHXERoVWQdJImsS3njvh2r77wMkGj0QQBKFyxIcJrY7YqNAqSLDdJE6MLVwSFuC4R7sgCEIrIT5MaHXERoVWQYLtJjHUH3Ft3+DRLgiC0EqIDxNaHbFRoVWQYLtJ3HXdkGv7ndcONngkgiAIlSM+TGh1xEaFVkEKJGtEpRXPzme7D5zk+FiUDf0R7rx2UIo2BEFoC3J92EunJplLpgn51WyerPgyodG89/6n856/8pwVWgUJtmtAtRXPuc5AEASh3XD819ELs3QE7ceJKD4IzcK0FtqfPGeFVkDSSGqAVDwLgrBcEf8ntCJif0IrIcF2DZCKZ0EQlivi/4RWROxPaCUk2K4BUvEsCMJyRfyf0IqI/QmthATbNUAqngVBWK6I/xNaEbE/oZWoa4GkrusDwAHgnYZhvJrT/h7g00AK+LJhGF+s5zjqjVQ8C4KwXBH/J7QKqqqI/QktiWJZVl0OrOu6H/gWcAXwK06wnWl/BbgemAV+DLzHMIyzFXZRn4G3OJVKDAqLQqnx8Zadze647wmOXJiteL9NKzvYe+8ttR/Q0qeWNptnr+J7hDpRN5sFsVuh5lRlr/Wc2b4P+BzwyYL2y4FhwzDGAXRdfxq4Cdhdx7EsCaqVGBQEQVgM4nuEdkTsVmgV6pKzrev6bwMjhmE86vJxNzCZ8/s00FOPcSw1RGJLEIRmIL5HaEfEboVWoV4Fkh8G3qnr+hPAm4Gv6rq+JvPZFNCVs20XMFGncSwpRGJLEIRmIL5HaEfEboVWoS5pJIZh3Oz8nAm4P5aTk/0KcKmu6/3ADHAzdsqJUIKh/gjHRhc6CZE4EgShnojvEdoRsVuhVWiY9J+u6x/Qdf33DcNIAh8HHgV+gq1GcqpR42hnRGJLEIRmIL5HaEfEboVWoa7SfwCGYdyS+fHVnLbvAt+td9+txgN7h9n1zDHGo0n6In523rCRu3dsLnt/kdgSlgtqrXVghEWR63teOj3JXDJNyKdlc2K9fJAoQQjNpJpn5mKf04LgRt2k/xpAWw38gb3D3P/48IL2e27dLDdy6yLSf4ukWum/my5diQKcGI9VvO9QX5ivfmR7xfstEeouo5ar7uDwidv0BQFMJdsKy5q62mwlyHNaKIOWk/4Tctj1zDH39v3H5SYWBBdOjMeqCtSF+lFM3aEwgK5kW0FoBeQ5LdQLWa69QYxHk67tE9FEg0ciCIJQHZWoO4gShNBuyHNaqBcSbDeIvojftb03EmjwSARBEKpjyEPFwU3doZJtBaEVkOe0UC8k2G4QO2/Y6N6+fUODRyIIglAdlag7iBKE0G7Ic1qoF5KzXSX37j7InkOniadMgj6VO7au4747t3lu7+R77dp/nIlogt5IgJ3bNxTNA5NK/tpTzjl1ttlz6MxPj37m9rc0aaiC0HJ4qTsA3PON5zkxFiXk1wCYS6ZJpk3OT88RS5q2ssP2jXnbil9bGhTzq81+jnn176U6cuTCLHsOnSGRShPwadyxda3ka7cA1dhRs20vF1EjqYJ7dx/koecXLvf6vmsGiwbclSCV/LWnnHOau80LpyYPHP3M7dfVcAhte7NVy2LUSE5WWSC5aWUHe++9peL9lggNV3bIvWem55Kcm4oD0B32MRVLAbC6O0hXyM/0nJ0T2xXKf10vfq19KeZXgXKeY3WzWa+x6Wu6ePjQmQXtt29di3F2ekG72GdzqSYeqmMMVZW9ShpJFew5dNq13e3mrZZilfxCdZRzTr22EQTBndx7JrfAbGw2saB9PJp0LUITv9a+FPOrzX6OefX/sMczfI/HM1zss7lUY0fNtr1CJI2kCuIp06M9XbM+pJK/9pRzTr22EQTBndx7JpHjG9OmhU/Nb094+E7xa+1LUb/q8ea8Udfba2xzKZOQT1vQnvB4hot9Npdq4qFWi6FkZrsKgj730xZ0uXmrRSr5a08559RrG0EQ3Mm9ZwI5vlHLWQbUaQ/41LxtHMSvtS/F/Gqzn2Ne/Yc8nuEBj2e42GdzqcaOmm17hUiwXQV3bF3n2n771rU160Mq+WtPOefUaxtBENzJvWdypdP6OwIL2vsifld5NfFr7Usxv9rs55hX/7d7PMPv8HiGi302l2rsqNm2V4ikkVTBfXdu4+zUHD8ZvkDaAk2Bt25emVcc6VYFC5RdGetV9S9FGtVTzjnN3eaFU5O1ywsShCXKzVtW8YWn3mDf8AVMCxQFVnYEWNMTZtMKFUuBuaSZp1wifm3pUI5fbdb1vnnLKv7l4Gn2HDpNImUSyFEO27Syw1UdzFEpmYgm6c2olIh9Npdq4qFWi6FEjaQKSlW5un0uVfhtSS2r5EHUSMpG1EiqpuFqJI1QZxKWNHWz2Qf2DnP/48MLNrrn1s2ucn6iAiaUgaiRNIpSVa5un0sVviAIS5FGqDMJQjXseuaYe/v+467traZgISwdJI2kCkpVubp9LlX4giAsRRqhziQI1eA2wQUwEU24treagoWwdJCZ7SooVeXq9rlU4QuCsBRphDqTIFSDWzEuQG8k4NreagoWwtJBgu0qKFXl6va5VOELgrAUaYQ6kyBUw84bNrq3b9/g2t5qChbC0qGsNBJd128H/iuwAjs5XAEswzAuruPYaoabMkilxQ6Fx3j3lWt49ey0a5WrVxWsW5sUXXhTi+smCEJ1vPf+p0ved08eHmEumaY37GcqlsS0IOTXuH3rWimOXEK0qy++e8dmfvLGaFYpR1Xgxs0rXYsjofUULITWwbkH9hw689Ojn7n9LZXuX27O9v8C/iPwEm2mqFBYXXxsNJr9vdwbyO0Yx0ajRSuUb96yyvUzuWnLoxbXTRCE6jGt4vdd7j062BeBPrtdlBuWFu3six/YO8yBo+N5KU0Hjo7zwN7hogF3q38vobEU3ANVZYSUu9OkYRgPG4Zx1DCMY86/ajpsNLWoLpYK5cYj51wQWge3+07u0eVBO1/nStVIBMENr3ugEorObOu6fnPmx5d0Xf/fwD8DKedzwzCeXPQI6kwtqoulQrnxyDkXhNbB7b6Te3R50M7XuVI1EkFww+seqIRSaSR/kvPzEHBVzu8WcOuiR1BnhvojHBtdeKIqqS6uxTGEypBzLgitg9t9J/fo8qCdr3NfxO8acHupkQiCG173QCUUTSMxDGOHYRg7gHucn3PaPrWonhtELaqLpUK58cg5F4TWwe2+k3t0edDO17lSNRJBcMPrHqiEUmkkbwM04Eu6rn+E+WUqfcDngC1F9tWALwI6kAZ+xzCM13M+/zjwEWAk0/RRwzAWrpO6SGpRXSwVyo1HzrkgNBdVVYred3KPLg/a+To7RZC79h9nIpqgNxJg5/YNnsWRguBG7j3wwqnJqlbrKpVG8k7gHcBa4E9z2lPA50vs+x4AwzDepuv6LcD/BN6b8/k1wIcMwzhQyYCroRbVxS+cmuTA0THGo0lGpuYYjyb4o4cOMR5N0hfxc+Pmlcwl0xVJI7WrnFKjkKpwQWge37n7ba7tD+wdZtczxxiPJvFpClgW8ZSFcXaKZ4+MsXGFnV4wl0yLX1sitLMvPnJhlrHZOPGUiTkb58iFWSDfjvsifnbesLHqIFye5Usf5x74m9+4ens1+xcNtg3D+H8BdF3/oGEYX6vkwIZh/LOu63syv24EzhVsci3wSV3X1wAPG4bx55Ucv5E8sHeY+x8fzv5+fjrO6ck5fKqCX1O5MJPgoedPMtAVZKArVJY0UjvLKQmCsDzJ9YXJtEksOa8Eq5hwdmqOCzNx/JrK6u4gpvg1oYncu/sgDz0/r5oST5k89PxJXjkzxRsjs9n28Wgya9eVBtzyLBfKoVQayZdzft5R+LlhGB8utr9hGCld1/8e+FXg1ws+/ibwADAFfFvX9TsMw9hTeIxWoFA+KG1a2f/7tfnfx2YTDHSFstvtPnDS82YrJqckN6ggCK1Iri90/F4hjl8cjybpCtmr5opfE5rBnkOnXdtfPj1FyK8taN+1/3jFwbY8y4VyKKWz/aPMvy5gHfA48Bj28gVlaXQbhvFb2LndX9R1vQNA13UF+GvDMC4YhpEAHgauruobNIDCamar4P8m88F3LsWkkdpZTkkQhOVJri/0Wt3MaU+kzGyb+DWhGcRzbDAXL9utRhJQnuVCOZRSI/l7wzD+HtgA/LJhGF83DOObwPuANxXbV9f1D+q6/snMr1HAxC6UBOgGXtR1vTMTeN8K1D13u1r6Iv6835WC/6uZnzRVyduumDTSkMdn7SCnJAjC8iTXFyoe2zjtAd/840X8mtAMgj73EMfLdquRBJRnuVAO5S7X3gP0Axcyv68GOkvs80/A3+m6/iTgB/4A+DVd1zsNw/iCruufAvYCceCHhmF8r+LRN4idN2zMy9nWVIWUaWWDa01VME2L/o78G7WYNNJd1w3l5XmVs48gNIMPPbifE+Oxive7fmNfHUYjNIq0aTERTRAJ+AgH7Ffuub7Q8YOFOH4xNzAXvyY0gzu2rsvL2XZ407ruvJxth2okAeVZLpRDucH2fwMO6br+Y+zZ8BuA/1BsB8MwZoG7inz+NaCiostqKVUpXKoq+e4dm/nJG6P8ZPgCaQs0BQa6gkzNpYin0gR8Gm9a3c14NMHwyIx9jO0bF+RrFfZz4+aVxFNmTeWUyqmKLtzm8rXdvHJmSiqpBVdOjMeyFfyVMNgXrsNohEZhWhaTsSSTsSSaqhAJ+Pidt10EWOzaf4KJaALVtEim7EQ6KxN3p0wL00pzbCyKX1UZ6Ary2ccMvvXciaxerSg32NRbxcLt+LB8zv99d27jey+cIZqYV2uLBDQe/g83ce/ugzx86DTxlEnQp3L71nXcvWNzxSol7SyNWCvaUY3Fa8z1+i6KZXllL+Wj6/pa4EbsdKenDcM4v+jeF0dZAy+sFHb4xG06N29ZtUBpxOGeWzdnb7DCbdKmRdI0s+oj03NJzk3FWd0dzBYE5fbhdgy3fhZLqe/qtk05Y1/GeL1trJbybrYWY8d9T1QVbN906UpOVhmoL2bfTSs72HvvLRXvt0Somc0m06bllo9qB94a//DsCT73xOtEk2ncaiWVnNEMdAYZ6LZ9JZDna2B5+pty/HWtj9+i57+WfjbPEt/xF3s55mLDA11BVneHFrTra7p4+NCZBe21fE4vNeptx/XAa8zvvnINj7x4dkF7wXepyl6L5mzruv77mf9/Gvg94ArgSuBjmbaWp1ilMCxUGnHYtf/4/M8eaiRjs3YxhVM0VFhI6fRRbj+LpdR3ddumnLELgiA4pE2L6bkUX913FEVVCPk1IgENX0HNSm7UMxad95Vuy2cvR39Tjr+u9fGX2/l3C7TBlu91w0u9pJbP6aVGve24HniN2StOq8V3KTeNpNYzfA2jVKWwm+OB/Krkwm0K1UecqvtEQeVzbjVyOf0slnKqogu3KWfsgiAIhUzOpYB5xYeAphIJ2PM3qbRFIj3vU1IFvrKQ5ehv6q1i4Xb8pX7+EymTZNok7NdQ1crDlnjKJORbKAlYy+f0UqMd1Vi8xjwRTbKiM7igvRbfpVSwvVbX9bcCf2YYhvtd2uIM9Uc4NrrwRDmVwn0Rv2oUDgYAACAASURBVGsgnFuVXLiNioLJfIFkwKeSSJl51fe5fZTbz2Ip9V3dtiln7IIgCIX0hHzZgBsgkTZxUmP9mp1qAvakhJlJVyz0Mw7L0d+U469rffylfv6TaZNzU3MA2TcuYAfhbsW8hXipl9TyOb3UqLcd1wOvMfcWKM851OK7lNLKDgJ/AZzWdf2fdF3/mK7rlyy61wbiFIQU4lQK77xho+vnuVXJhds4QbajPuJU3RdKBOZWI5fTz2Ip9V3dtiln7IIgLD/+63de4qHnTzJ8fiYbLOfynjevB9xfeybTFtFEmmgiTcq0WNMVwq8pDHQFFvgaWJ7+phx/Xevj90X8y+b8zyXT9Ib9RBNpVMX+48/5t9YlXxts9RI3avmcXmrU247rgdeYveK0WnyXUsu1fwpA1/UgsB24Cbg/Uyz5E8Mw/t2iR1BnSlUKO0UPu/YfZyKaoDcSYOf2DQvUSI5cmGXPoTMkctVHZhO8fn6G3oif27euLaosUk4/9f6ubttcNdjLYDTBgaNjHBuLEspUZVda2FBpBbcgCK3NN346n6faGfRx1foe3jzUw7ahXi5Z1cnO7Rs4OR5lrzGSl56gKeDTFBRFQVMUsOD8bJx4Os2vbFvP1sEe/vWV85yejLG2J7zslBscvPw1wD3feH7RagjFjr/7wEmePTLKRCyJZcEfPXRogc9uR4WJQr7+u9v59c/tY2w2mX3r0t/h55u/fwMvnJ7kBy+f49R4jLW983a4aWWH53N6KZyTWnPzllW8cGqSXc8cYyKapDfz/G/kean0uhSLla5a3+Pa7sQ4pyfnZo5+5vZS0tcLqESNZCuwAzvovgx4zTCM91faYQ1pmLLDUlbwqIVKSiOUVprEklAjqVYnG2yt7GePjYsaSftQM5vd/KnvWV6v3jsCGkP9ES5MxwkHNEI+FUWxu/7ITZu4/qJ+nj06xoNPHVmwr/M5ZPK8gz46ghpBl1zZ5UajlB1K+ewGK0zUzGZn4ynLSSMByrJBsNNHQn4tY8vu+d7tqLrRCJp9XhrRf+79Ekumo0c/c3tHpccoOrOt6/pvALdhB9lvAP8K/BXwnGEYbSljVg3FFDxyg+3dB0623U1XTCWl3EC5FscQ6ke1OtkgWtnLmef+yy/y6EtnOXRykoMnJnj17HQ273U2kebVs9P2hrOgKpkcWb/GPzx3kquHevm+i4QWwCMvncsGOom0SSKaYCI6H3hHAhoh//IMvIspO9Ty2VLKZzdqHPWmHBsEuzAynjKZjCVRFIVQTvAdzPwhuVTOSa1p9nlpRP9e90sllCqQ3AU8CrzPMIznFt1bDTFNq6pq42pYygoetVBJaYTSiiAIjaUj6OP6i/qzQclcMs3Lp6f4+ckJDp6Y5MVTk9lXNaZFNkf7wmyCX3ngx6iKQjgTgIf88zPfZybc37IUBt6hgEZHwJe371KnUcoOpXx2OypMAHz0awdY3R1ky+ouLl3dyZnxKG4T5142CGBZFrFkmlgyzXiUrB2fmYzh15RMwe/89q1+TupNs22lEf173S+VUCrYvgp7Zvu/6bp+EfAk8Bjwr4ZhjC+690VwbmqOZNpW0fBpKgGfSkCz/9U6CF/KCh61UElphNKKIAjNJeTXuGZjH9ds7APgv/7LSxwZmSGWNIkm0swl09ngey5pT0REE2lGscOdcGamcMOKiKv/zCWRNknETKZiSbRMcVs46CNSpaRbu9AoZYdSPrsdFSYAnh6+kPe7qtjP65BPy6SK2DHC2t7yv4dpWcwmUnSF/Jwej+H3Kfg1FVVRUBQY7Gvtc1Jvmm0rjejf636phKJqJIZhvGQYxv80DOM2YBvwj9g520/pur5/UT3XgJRpV7xPxZJcmI5zeiLG0dFZToxGOTsZY3QmzvRckngqTbm56W4sZQWPWqikNEJpRRCE1uKOrWuJBHys6Agw1BfmklUdDPaGedebVnPNhl782nxQbAHRZJrR2QQ/Oz7Be+5/mj/8h5/zlR8f5WfHx4kn0579pC2L6XiK81NzHBuLcm5yjum5ZHadg6VEo5QdSvnsdlSYAOgJ5z+TTcv+w28iluTcdJxjYzGGR2YZPj/NX//ra3zvhTO8dm6aZLq0svEvXbkGgGTKIhpPMzOXYjqW4uZLV3J+ao7JaNL+g3MRsUY70mxbaUT/XvdLJZS1qI2u65uBtwFvB94CzABPLLr3GvDs0TG+/+JZzk7EWNMb5peuXMP1F/WTTACks9s89vI5RqfjDPaFCQV8PH90jJGZBF0hX0nlDLdq21LqI41isdXRbiopF6/qYNczx7j/8WH6In5u3LySuWTasw+3Y9x4yQpeOTPFe+9/mqH+CJev7eaVM1N5xwCKjl0qvwWhdXB87YsnJ5iKp7AsCKgKKPar9e6Qj/e8eT1bVnfy/RfPcvGKCCkLZuMppudSzCVN0plAJJm2OHhykoMnJ+EZW5f7sjVdbBvqZdtgL29a103YJW/byswyziZSKEqCsF8l7PcRDmhFZ8pbFTcf9+4r12SfNSG/ykB3iM8+ZvCt506U5SOhuF+FeYWthw+dJp4yCWZUqJziyG89d4KR6TgTsQSmBSs7A+zc3liFiWr48X/ewaGTkxw+P81r52Z47dw0zx0bz0v7sIATYzFOjM2nkvg1hU0rO7h0oIstqzu5dHUnF6/szLMpJ53qkZfOcWbCVjB59xWruXpDHzPxFDNxW3NeVRRCfpWgz649aLc0qGLP3WKfFVNBc6NSBTOvvqvt/97dB9mTY/93bF3HfXduc902N8aJTcSq+muqqBqJruvfBt4KXAD2Aj8EnjAMY6KazmrJmYmY9eRrIyUrjQurkUdn44zOJvGrCgGfmnkdBL/9tov4vZsuwa8p+LR8p93salsv6jGuwir1tGmRNE0GOoMM5GiTFuujHPWW6Tn7lUxugWnucVvknC8JNZId9z1RdYFksxRFRI2kampms8m0aTn5kI4fdfxnISs6/KzoCDKbsAOOjkD+PM5HbtrE1UO9vHZ+hp+fmODgSTvnO5pwn9HWVAV9dVdWavDKdT2EA8WLJgOaSjig0RH0tUWBpZuPy/WLjt8E8nxnMR9Zyq8W6xvg3Veu4ZEXz+b1ndt/u6mR/P7XnmP4/EIfoqlKyTcjmqpw0YpINgDfsrqLS1Z1EKzQtpyCy2BmkZ2gr3WD72LPXaBmz+RKFcxqHQ/cu/sgDz2/cAn2910z6Blw51DVxSs1s70b+HeGYbiX9AK6rv++YRhfqKbzxVJOpXHhNpMx2xmlTYuUaZEybWf/9WeOZwXtFUXBryr4fSqaalchO69ETcvCeePU7CrkelThFlbdOg5pLJrIC7aL9VGOeovTVvhQcI7b7ApnQRDmcfyo4z8LmYwlWdERZDLmHmw7Pvnytd1cvrab33iL7VuGs8H3BC+cnGQ2E3ynTYuXz0zx8pkpvvHTE6gK6Gu62DbYy7ahHq5c10NHML8PJ897MpbEpyqEA7aySbVLd9cbNx+X6xdzc0RzfWcxH1nKrxbrG2DX/mOs6AguyE91+m83/+sWaINtX//4sbdy+FxmBvz8DIfPTXN+Op63zesjs7w+MssjL9ltqgIbV3Rw6UCnPQM+0MXmgc6ifwjmFlxORO34IpyZ+Q63WPBd7LnrNTFbjU1UqmBW63hgz6HTru0PHzpTTrBdFaUWtflGGcf4GNCUYPusR0VxbqVx4TaOgEhhhtbU3LxzsSyLRNoikYmqh89NZ19DaWqmOEKF05NRYok0gUxQ3mjqUYVb6GTNzGRsod5usT7KUW8pVHIpPG6zK5wFYbnj11TW9YZJpE2mYwkiQQ2/pgELl752JiC8cl/d1B80VUFf04W+pov3Xz+UCW5m7PSSExO8cGqS6cxy8KYFr5yZ5pUz03zzWTv4vnSgi21DPWwb7OWq9T10huYfZynTYnouyfRcMhvchP0+QgG1ZfS83Xycl4/M/bmYjyzlV4v1Dbb/X9ERXHAc5/el5H/7OwLccPEKbrh4RbZtIprIBt6vnZvh8LkZzubMlJsWHLkwy5ELszz28jnAnuYc6o/MB+Cr7QC8M+geXlnW/OqquWonIb9G0K829a1M0eeuR7BdjU1UqmBW63gg7nGfxFPetSOLpayc7RI07U+yNb1hTrss1rG2N+y5jU+1A+7C7L7u0MIlbN2OkTYt0pnZ8PX9Ec5M2u1+1VZE8fvUrEB+vQPwelThFlbdqiiYWPgKvkuxPspRb/HKr3SO2+wKZ0EQyOScaqztte/HlGlmlr6ev3/tZ7D98PJr7vd1rk/2QlMVtqzuYsvqLu68dhDTsjgyMsvBkxPZAHwqJ/g2zk1jnJvmW8+dRAEuGehk22APbx6yg+/uTLFcbnDDLJlZb41wwEe4AX7aCzcfV+gjnSA3t72YjyzlV4v1DfNF/7l95x53qfvf3kggT+4SYCqWZNgJwM/bs+Anc2IKCzvoOz4W5Yevns+2r+8NZ2a/O7NShIVvHGBe7cRJwXKCbyfwbuTMd7HnrmVZNXsmV6pgVut4IOhTXQPuev4hXotguyl5qN/5+Sk29IV5/fwMmqKgqQp2rY7Cu69Ynd3ul65ck5ez3RP2MzqbXOBg37NtnWdfhcdwyO0naZokEybk/GEW0OzAO+DTMvnhC/PBF8Nd1w255jEtpgp35w0b83KpNFXBNC36C26CYn0Ujqsv4ufcVDxPvaVQyaXwuPX4boIgVIdzP/ZHApyfiZM07SBbAVBgbXeQrpCP9UoIy4JIUMM0IZFKY1r5vrJcVEXhkoFOLhno5NeusYPvY6NRDp6YD74nMmktFjB8fobh8zM89PwpFGDTqo5s2sm29b30ZHyOPeudys6aO39QNHoxHTcfV+gjnbzp3PZiPrKUXy3WN8DO7Rt55MWzeX3nHrfd/O/mgQ7XVJLNA+UvANgd9udJXoJd9Dt8fobD5+0izMPnZjgxFs0Lhk5NxDg1EWOvMZJtW9sTygu+twx0Ze3SYT74tn/PTTupd8FlqedurZ7JhXFGtt1DwazW8cAdW9e55mzfvnVtVccrh7KXa/dC1/XnDcO4pkbjKZuL/ujhBQNXgK6Qj4GuED0RP71hPz0RP8dGoxw+O8Vc0qQzqLGuL8K5KVs+qicc4OoNvcRTZlbRZHouxQunJkikLAI+hR36ALdeNrCgCjn3r99y0VSFgGZrg/s1BVVV8GVSU7xmhYrx5OGRiqtwS2FX6Z4hkUoT8Glcd1EffZFA0T4KK3uvu6g/b583RmZ45cwUpmXnvd24eSW/f9PFRcdej+9WIVIgKQWS7UYtbTbPXp378dkjo0zGUpiWRUfQx0BXkJPjsawag4Kt7uDzqazqCHDX9UP85g0XkUiZJNMmydS8KsmiBmdZHB+LZgPvgycnGZv1Xkhr08oOtg72ZAPwPpdZNL9qazGHAhqRgK9us96OssLLp6eYS6UJ+TWuWNfDndcO2spX+22VhrBfY6AzSDCgEfapWNiLCzlqDLnb9kX87Ny+kavW92T9ZsivggUj03HmkmlCfpVVXXbtzch0fEHfTuHl7gMneenUJHMpk5Bfzfu8DtTsJF/2x9+3wn6Vmy8d4OPv3ELasvj1z+1jLKeot7/Dzz9+7MZadZkllkjz+og9A374nP3/42NRSilUDnQFs4H3pZlCzP4O7zUqFEUhmPMGvdZv0R/YO7zAppw86koUPEpRGGfcsXVt0WMViweqUS77zQf3s294FNOyUBWFGzev4Osf2V7Osao62Usq2K4Uv2a/TownTTRVQVMU5lJpkumFh/6Fy1bxqV++vK6vcxRFIaDZgbeWKdB0Zscb9RqpmqrfUpW9i6z8bSYSbEuw3W7ULdj24jcf3M/Tr11Y0N4R1Lh4ZSew0H+k0qZd0Jiyg+94yszWyFQ9WMvixHiMQ5kVLn9+coLRGe/ge0N/JJvzvW2whxWdwQXbOMFMuIYzitUoPjgqIbmUq+iUqyziFLxrquKqcNIkamazmz45Hxfcee0gm1Z28IUfvYFz2SwLFAV23rCB91+3gaRp1VUXey5pB+BOEeZr52Y4MjpbUgllRUdgQQC+sjPgaX8BTSXotxVP7EC8ujc0xWzzhVOTFSmIVNtPpXZYzbFKqfGUOFZd1EjKoSkygP/nA1dzfjrOeDTJZCxh/z+aZCKWZCKaYDKWZDKWLPpXZTJtkcxUz5fih6+O8ORrF+gNB7Kz5r2RzL9wgN6In56wn75IINse9msVOWfLsoinLNdcokAmAPepmdlwZ2Y8k0KjKUpNKu6rqfotVdnbjMpfQRAaw77hhYE2wGx8vtio0H/4Mm/3cieX06ZFImUST6Xt/ydNkmb5AbiiKGzoj7ChP8IdW9dhWRanJ+bycr5z1SacPNvvHjwDwGBfeD7tZLCXVV1B5pL2ypgTkFdouZhCtmoUH3Y9c2zBHwPlKjrl5sbmBttuCidLie8ePENfxM+cy/P0oedP85/edRmQkbdNm7ZCWdqWuk2lTVI5IgnV4rw1uGJdT7YtkTI5cmF2Pgf83AxvXJjJm+QbnU0w+sYYz7wxlm3ri/i5dHUXlw50ZgPw1V1BFEWx/3BNm9nUqFy5QWcWvJwU1mK2eeDomOtnXgoi1fZTqR1WcyxPNR6X+6zacRVSNNjWdf3TxT43DONPDcO4dVEjqJKrN/QRK7LqGNi5Tx/72gGSaStT2Jj5Z9n/tg328uyRMVI57cVIpi1GZuKMzMSLbufg15RsIG7/C9ipLWE/fRF/Jmi3P++LBIrOnCTSprNGjyeKouBTFFTVdqaaas+Ma1omSC/IbXejmqrfUpW9zaj8FQShMZSzkGM5qgFatnBxPohNm1Y2+M7+KzMAUhSF9X1h1veF+eWr1mJZFmen5jh4YpKDJyc4dHKSM5PzShMnx2OcHI/x8At28L2uN5QJvu2Z79XdoflCy8x4I37NTvHwa2WnAVaj+DARTS4IAspVdMrdzsx5WeGmcLKUiKdstQ83clUv7Gel+x9OpmkH3Mm0STJt2UG4aZHOBOXVEPCpWRUeh2Ta5OiF2Uwh5gyHz0/z+shs3jUajyb56ZExfnpkPujtDvmyAbiTB76ux04TcuQGs/1qtoiDL/O23C0AL2ablSqIFKOW6iLVHMtrH7f7rNpxFVJqZrs1xB+rRFUUBvsjrool6/sj/PHtl/One17Ofm5ZFq+NuL+2VhW46dJVTEQTmdnzJFOxZNH3rJUG5wGfOj9jHraD8/nAPJA/mx4JLFhhzbIskpaVo2voHcwqioKmgIKChZ2zpKoK63vDnM4orCjMB+VDfRFiiTSKQiZgV1AAVVWIBDR7mVryDSaUeZUV8tuVv84+znZhv4aZ86Q2LSt7Pp3XfQr5D3OnTVEUe/vMdpYFFlb2WWUV7FP4DHO2NS3LPn72ZwslM85v/+xU34ffvmnc8yQKgoCqlA64q1UN0FSFSMDnOgPuBEGptEkyVTr4URSFtT1h1vaEeXdm6e1zU3McPDnJoRMT/PzkBKcn5oPv0xNznJ44m9UYX9Mdmk87GephTXeIadNeSh4y+d6B+Txar+C7GsWHXpfCx3IVnXKVRdQcD+2mcLKUCPq0ilUvClFVhZDqXjhrWVbOeh1WNjUqnZ6fIS8Xv6baQfPqLn7pKrstbVocHZ3N0wF//fxM3kz91FyKA8fGOXBs/jHVEdS4dCA/AB/sC2dnv3Ox68fs1NWgX2PTig6OjM4uuJ839EcYmZpb1LnMpZbqItUcy2sft/us2nEVUkpn+0/c2nVdV4BNi+69AZRSEsn9XFEUuoK+rPPM5Z1vWs1/fvdleW1p02Jqzg68JzMBeG4wPhFL2J9Fk4xHE0zPpYoG54mUyfnpeN6rzmIEfWo2dSUvtSWcH5w7n+cG55ZlkbJgPi3TgjS8Q1/ler5u3LwiK3NYyC1bVvGvr5xf0L5DH+D46Cy/ePlqfvDyuWxw6zj8t1+6kqOj1eUSN4Lh8zMRQIJtQSjCjZtXeuZsO9RSxSI7A87CyYZEZgbSngW3Z8QLNcFzWd0d4l3/P3tvHidHfd75v6v67rlPXTOSAEkFSCAOYQE2WkNswMF3DOtd2U5+wXZ2A9lsYjvxJnHWzjqJ92d7k2zsvH5JfKwPES9OHBuMjfGBwy1AIHQAJYSukUajuXuOvrvq90d11XT3dPd093RPT88879dLL01X1feoqm8/9fS3nufzvdzPrZdbz4OR6RiHzk5yMD37nSnxNjQVZeholJ8ctfSVe1t8TsLlVf3trG/3k4jOvcq3ky29Ga/yFUWpSPFh7/Wb5sWSlqrolKkskplIl0/hZCVxx5XruKi7qSzVi3JQFAW3S6FQeHTueEyk38yU6oS7VIVLepq5pKeZ29PbUobJwEQ47YBbiZjHh2eyVmKdjaU4ODDJwYG5CN+Ax8WWtA647YD3dwSJY2AVTUEkwQ1bunhtZBq3qqIo1oQlWOPj0rUtVbuW1VQXqaSugmo8eb5nlfYrl5JitjVN+yjwBSBTL+ckUDBQR9M0F/CPgIY1xfr/6Lr+esb+dwB/CiSBr+m6/o9l974EbMWQQkoiuft3XdTJVCTBkXMhRxv6zVrPPEcbrC9DR9CbN6s9HynDdGLJJ8PxtEOedsYjcSfm3HbObU3ZQsQqcM4zY8zzOebtQQ/vuWYDT58YZ3gqWpLyysdu1UgaJr/UR7Ku2e/fuo2kYfJ7b9lGPGnwS32EZMpSeHmz1sPHb9VK6rcgCMuXb9+9mw98dT9PHx8jZZqoipXgtb4juKQqQpZKgwufG8h4E2zH5MYShhWDnUwVTFDrafHxK5et4Vcus5zvsZmYFe99dpJDAyFOZ7xOHp6O8bNXhp2Jhu5mrzPrfWVfO/0dAcuxis3F0frcKtvXt/Jf37KVBw8NcmrUUjzIvUb5VBcyVUbs7YWOBZz/v3vgLGqGskhPiw/FhEjSqJfKU81QsGa078hRtti3/wyT4TjtQS97d28sO8a4or4UGI92aEosQ52n1Jlwawn5JjZ3NfHW9A9EwzQZnIxw7IIlQ/haOhRlJmPSMJJIcfhciMPnQs42v1vlkt5sHfCr+9uBzfP8pf7OIFt6m4klUzxw8DzT0ThtAS/vu7aP367gWmaOzcWqjVVSV7Ey+b5n1fh+lJog+d+AncBngT8GfhV44wJl3gGg6/obNU17M/C/gHcBaJrmAf4KuA6YBZ7UNO3BYsvC5/Kfv32A9iYvl/Q08/rIjCPb97Yda+c5hrki9bkcuzDD0bOThKJJxmdiXL2pgxsu6XLqvOXSXp47Nc6PjwwVbWchXjgzMa+Omy/tdfbv23+GBw+eIxRN0uZ3s/vyXmZjKQYnwrQFvWxf30pXs8+ZPQ+FE+gXphmdjpFHQGUesaTBhalYln5qMfxulclwggOnx61Z+bRs35beZq7qb+eV81NMRRKsaw/Q7HPT5nc7fQf4sx++nHWu+X6wZJJ7jUu5twtRizoFYbWQTwYLcLaNz8a5MBUlYZj43CrvuXID79y53tlfS6WHUrFjcv0eF21Ys7nxpEE0mSKWSBFLFI4D72r2ccullvQrwEQ4zqGzIWuJ+YFJTmW8ih6difPzV4edhU28LhWwcoEUoCPg4Z1X97F390ZGZ2KEIglGpqOcHpvh8WPDBD0u2pu8eFwq/Z1BPvbWbYB1rb/4iO6EMkxHEhw4Nc7Rc5OOjN+FUBR9aIqfHBmiu9nL3ustubY923rYs63HknN75jTnJ6NE4ylnv429fyKcIOB10dPsw+9R897zUqXVKpFjWyx26MhF3XPzgidHZxmfjRFLGhizMUfhqB79g8KhKaZphaMk0mFR8ZRBylg4REpVFPo6gvR1BJ1xapom50NRfnxkiMdeG2F8Jk4snfRpE00aHB2c4ujglLPN61Zp83uYiSZIGCYXQhE2dQa5bnMn0UQKfWiawVCYeNIKnzp8bpJzE2EODkzy8JEhzocibOgI8GvX9DuKOIWu8T88foKnjo9imHD47CQT4XjR61+srgdeGuSnLw8RSxroQ1P43OqC7R8+F+LAqXEmwglGpqJcurbF+b7UYhyUJP2nadp+Xdd3a5r2SeCorusPapp2RNf1HQuUc+u6ntQ07deBN+q6/tH09iuB/1fX9dvTn/8KeErX9e+W2vF3/u0T5thsjNGZON3NXpq8c78b7r7popIdqH37z/DtZ047nw3DJGGYdDV56Gqyfo7aKztltlFuO8+dGs8bnmHXUUo/ctvMLZNKGSRNaAu4afG5mYwkmImlrNUyM6SPWgMeDNN0XndWGzsu2+dWHK1at6LwtivXsfuiTtoC1oy6L8PY5F6f2Xhy0fd2sXV+5fGTfX/x3ivOlXHqCyHSf0tQVqT/qsNjx0bM3FetmXJzAxNhJtMxnPbiNpjQFvTQ35Ed41hnabkFSaZnGmNlvu4PhRO8dG7SSbo8USDnx0ZVYNuaFiLxJNPRBOPhbBvsdamsafXR3ewlHE9hmCZ+j9uR78tUE7H/NtKxw/ad96iWcpUtyfblR48XlWzL3J8y5hy73mYfva3+BSUG81GmHFvVxuxln3rYsbH33rKFk6OzeWVn37ilm1Ce+OPlOk7tePBE0iSeTFnjdAHZwtznn+3M37S1m7OTEZ45MU4saSwoQwjWmyq/x8W5yfmhpNdu6mA6MnctFcDrdvHmS7t5/Ngoqqo4Nzhlwu+/dRv/8PiJvKFnb9razbfv3j1ve7Hx9MBLg2Xf40XKGNZU+m9W07SbgUPAuzVNew5YcP3dtKP9DeA9wPsydrUCoYzP00AbZRJKy/aFIsks5+nhoxdKdsgePJjtS9kDLxRJOE6u3U6us11OOz/OEweUWUcp/chtM7eM/Z2ZjSVZ0+JnaGou2SczWcfnVvnOR68nmTKYiiaZmM0TZx6xQlmeOj5WtodoH2/JGM4N9q8/eYqvP3nK+RzwuBzJxJHpGImU4cgbTkWTGIbJ+GzCkT1UFWVRezDTxgAAIABJREFU17wa40UQVgv55LEy5eZCGQ9YO+nZxLJZ/R3Z5Za7tJwtRZhhah0H3Jb/y6eq1Bb0sGdrD3u2Wuc2FUnwx98/wrmJiLO6ZSaGCa8OTRfsRzxlcD4UIeBxMRiKoiqwuctNOJEi4FGzYtAzne3M5PSUYeJSFUeSbV/GhEwm+fZnOl7j4Ti9rf4FJQbzUU1pt0rZt/8M47P53+I+fXyMy9e3ztu+XMepPT7xAum3M3ZMeDznR6Ktqpb7/FMUBY9LYWAyimlCX3vAccDtH5rj4XheQZyxIotFvXB6gr6OAD63iqoomFhKMP/32YF5yZMet8J3njvDi6cnCKZVhzIlFp8+Ppa3jWLj6acv5/etnj4+yuXr57uV1ZYxLJVSne3fAT4MfAy4G9CB/15KQV3Xf13TtD8E9muadrmu67PAFNCScVgLZep1e90qblXBnZbsCXhdziAZm4lZiSCOooXiiNoradk72zDFU2ZW4qCdEACWRqaigEe1ygd9rqyBOBmO0+x3Z81XZqptZJrmUDieJWnl1DEbJ+h1FemHmfW6aSxD2WQ6lsxS2rDbs58J9v+5j4ip9EyF26XS2eQtulrVLV/8t4L71rb6SBkmIxkLR9jnXwqRRIpIKJUlv5VLwkhxMv2qVlXg5Ngs99wXyRt33pGhdd4W8DCU8ys8kf5CJ3JeGZ/P82tdEFY7+eSxMqXICk2q5dveiNJycw649Zg00k5JJJEinkwRTRgYOSfbGvCQShn0tvjyOtulkDSsxVDiyRSKohBNpJwZuljSmpBo8bnIeFRZqiy28522wLYk20KSbZn7M6UB7foWkhjMRzWl3SplMhwvKDtbSOa3kcbpXEy4K8uZSqQd8OlInKDPhWFAPJlyJuPOT0acL6ntgHtcKs0+GJ+N43OrmGmVLhOcvwthAgPpRGJ7cR2/WyUUSdDq92St/5FImpwYmWU2I6HTrSrpNUmsz7OxJJ60TKFNsfFU+B7n72+1ZQxLpSRnW9f1o5qmfQK4CvgMcKeu60XfsWma9kGgT9f1vwTCWD6ffYVfAbZqmtYJzAB7sBIwSyaetMyCnZCXORgu6mpiU1dTwbKZBL2urAsfTxoYmLhVJT3Q0s6qCblhfRs7gvSmY+YWYkNHAXmariBr2wIL9sM5t+4mLu5pxjBMept9hKIJ7J8OHlXBANyq9cOgxeciaYAKeNxqWk/cmDdDUQyvWyGezD9qW9P1TITjWe0kkgYG4FJgU2fQatc0aQ14uVnryYo5n0jPog9NRRd8nWWYYKRMXjlfeGYoE1tT3JXWF0+lX7u5VJWpaMLZ3tcZJJEyStbJFYTVQD55rMwHYD5JTXt7LitBWk7NowM+F/ttJbvFkgZr2wMMTkRwq3MTHmDZR7fLkixt8eeXpLM5k3ZeXKrlAKmKQsowUAHTMIkkUiTSlRukV0NOT8qoWG8ym9K5MwvJ32XuV1Ech9uddpIWkhjMRzWl3SqlPejFSMdq5+IqsM7EShinHpeKx6Wyrn3uHgS8LlRVwTRhQ0eAVMrkzHiYRNLI8i88buu62NLAFgptAQ8T4RgLLG0yt7hO+vPx0Vk8LgW/2+U44Zt7mlGGpp12LelEq2IVS47T7oPXpeB1q2zsDDohLLbkr2Fa90sfmipwj/P3sdoyhqVSknehadpbgTPAPwDfAF7XNO26BYp9D7ha07THgJ8A/xV4r6ZpH9V1PQH8fnr701hqJGXFxprMSRflSiC9rwyZlr3Xb8r6bEsjdWZc9I6gJ6/MUjlyMHaSSaE6CvYjZ9b5fddYx6uqwl1v2EgsaRJNGkSTBvGUZYQDHjcpA4I+t7X8vDG3KqXXpfIbb9zE+vYAa1r9dLf4aA96afa7CXpdeF3ZC+vcrPWSjxbf3O+0toAnq8/2/+1BD26XpTvb5HXzGzdu4n3X9vHhmy7m47dq/I937+BL//FqvnX3G/iL9+xgS08TF3UF2dgRoKvJg1tVaPO76Qh6aPW7afK62NgZYH27n6Y8bwlysVQIrOszG0+lnX7LIAxNxTgXinJmIsJTr49x218/zju+9AQf/Oqz3Hvfi3zq+0cWrF8QVjL5bFamLbS/9zAXwqDkbLdZidJyYDmirX4PPS0+1rcH2NwV5Ndv2ESz3826VuvVuo1LVVAUhV+5bA09zT66mhae9EgZJqOzcWs2PZVeh0BJS6im1zxwKdaaDvaCO7GkQTiR4u1XruNCKMpd1/UR8Kj43Nbkg40t2Zb57MmUBuzMcMbLff4t9LxbCvbu3sjbr1yfd98NW7rybl9J4zTzHiQNiCet5+Gd1/bz/jdsxKUqNPvdtPjdNPldBH0ubtu+Nu+P5XfsXM8tl67J287W3ma6m7y0+Nx48ni4iZSVTDk6E+fsZJQnXhst+APu6k1z8WfWitqWlOabtnYzE00yE00SjVtqQqpiSTjfceU6Ah4XfrfL+YEIcMOW7rxt3Hlt3zx/y6YakpCFKDWM5K+At+m6/hKApmm7gP8P2FWoQDpc5K4i+x8EHiy9q9moqsIVfe3scqs8dXyU14dnaA962Hv9prJiruz4HFsaqLvFx42XdBFLGiVLLJXCQvI099xsJXM8dGiQWNLA51bZuqaViXCc4yMzdAQ97N2dfW75+n5xTxMnhmec63H5ulZOjMwQS6bwuVVuv3I9O9a38/HvvuRk6F62rpVXzk85n7evb+XVoSkGJyzpnz1buzlyLuS8wrxxSxcb2oM8ePAcU9EkrX43127qYGA8zFQ0QUeTl6s3thNPmXnlFvORK8F4yZoWLu5u4sTorFPHxd1NjpLItjUtvPWyXrb0tjARjs/pnKdlFe1Z83OTYUam48QyXqMVYjaWYjYWcX5Bl/p2RBBWIoVslr1NVRU8apix2TiGCS7ghq3dfPSmi2sinVUvylGtUBSFmy9dg0tV+e6Bszx9fBS3ksJU0jNtisIv9RH8HhddQa/liKTXX3ClneeUtUIXipJ+G5dRv/O2NWUpnDR5XTT7rEXFwvFUehLKyzt2rueuXf3MxpO8c+cGpqMpfvjSICYpgh43nc1eHn31Aq8NTfPea/u495YtznOkxe+lu8WH3+Mq+vwDuPe+F/Jel2pKu5WDojBP3m9oKsrTx0dJmdY1vmGLlYT32LGRFTVOc1noHnzq+0eypCw3dQb5/j3X8If/8hI/PTpELGnicyvceEmP44SOzsR54fSEEyp7zaYOPv++K3nu1Ljz7O5p8XH5ulZcqsLTJ8bQh6azdMAh/6rSLsVaIG/f/tNs7W1h25pmZ6Y51z/oafVz+/Y1XLaulcvWtTITTfJLfcT6se/3cMtlvfzp2y/n+dMTPHToPAMTYTa0B/i1a/qy1EaWUhKyVDWSA7quX7vQtiXGLDPjeVmTey529vmaVl9W2Ec5GeD56sjNLM89ppR2H9OH+ZtfvGYZ/XQWvGHAB2/YyLWbapNouJCaSynEk8ZcCEskHcKSsQhRptMeiiR491UbRI1E1EgajWqu+lt0vK4k+1uIxZxjZtnhqSjD6VyioNuF22U50n6PSlvA6ygl2Svq2nGuXU0eVEXh0nWtjM7EODo4RaJAMKqt4b2zr50r+9u4bG3rvBnEfHbU41b4rT2XcOOWbrzpxXdy33BW87rkoWZjdjWM0Uq4438/niX5Z7OpM0hrzpspVYHfe8tWkiZ8+RevYaTfDqfS47CUZ3AknuL1EUv/+7XhaZ49OV40jMqmp9nHtjXNbF3T7Djg+ZZTLwVFUfCo1kJELtUa4x634oTdlFNVJe2XOrP9mKZpX8FapCYJvB84pWnaHgBd1x+rpPHFshwynqtF7rnYA3EinMhyesvJAM9XR25mee4xpbR7/4Gz2XHc6T+fOD7Gu6/uy9AJTZFIWa+CFqu3u5CaSyl43Sq9rX56W0uLs/9KHudeEASLlWR/C7GYc8wsO55OvEoZJrPxlLOEejyVoq8jyGQ0QcDjYiaawDDnnO2paIr1bX5SJvyvu64injR4ZWiKQ2mpwaODc/GqsaTBC2cmeeGMpTXgdatcvq6FK9MrXF6+rjWvHU0kTf714CA7NswpN8zFy1qxtl6X9c/uV6Pc+0bp51KTz9EGOD0e5ooN2Qoehgn/8uJgWrnE2uZzq7i8Vgz4E6+N8qYt3QUTFcGKGd+xoc0ZY+//+6fxujLy4tJx2LlewshMjJGZGE++PqdS0tnktRzw9GI829a00N3sLfrjEGz1FnNuxcwMbEfc51ZxpZewd6cV0Nyq4oSALYZSne2r0v9/Lmf7Z7Cuzy2L6kWFLIeM52qRey52BnhuJng5GeD56sitL/eYUtotdN1PjYXnfiVmSBSBJaOVSEv8JNOZ85Z2aHGtUJtcZREbURIRhPqwkuxvIRZzjpllM5eMt1PSDEyiSUsRazotS+pyqXhVBX86od12YGw753Wr1iqVfe18kE0kUgb60DQvpZeYP5peKRIsG35wIMTBgRDffPo0nrQDEfBYSZ4Bj8tRvcq1o1a8rB0zO7fdm1aJOB8K403H5yaNObWK5XbvV8MYXQrOjIezsqFTxpxM5JmJCBs6gqQMk2giRSSRIhpPFVwoCiAUTc6pwingciaLTf7m/Vdz7MI0r12Y4djwDCdGZrLe5ozPxnnmxDjPnJiT72sPeNIz4C2OE76m1VeygzzniBfus0e1nPC/f+zExZ9+5/YTJVWcQalqJDeXW/FSsBwynqtF7rnYMx+5rwHLyQDPV0dufbnHlNJuJdfdktGCAPNXzYqnHfFkeunaWHL+im52hn8u69oXlHsXBKEGrCT7W4jFnGNmWbeqOA63mnYsVBTUtJm17W4yZZJMmc5qve0BD00+F+vb87fncanOjOHe3dakxrELMxwcmOTQ2UkOn5sikpaQSKSsBLlIwoD0G0y/RyXocdHfFSQST+WVp83EVpto8XsZnIigAG63gktRUVXo7wwwFbXWRnCriqUNXUdWwxhdCjZ2BjFNs+i1dKkKTT63I5VpO9+2Rn3mG257telc2gJeZ7baJpkyODUWdhzw14anOT4ymzUhOBlJ8OypCZ49NeFsa/W72dqb7YCva/dnyTuXQ8IwSBhw5FyotFfjOZTkbGuatgn4CrAZuAm4D/hNXddPVdJotbhrV3/eeKxGzCjOPZeOoIcLU7F5WeALZYAvVEdufbnHlNJuNa/7nFZo9nbDsJzwWNIgnkzx7qs28Pf/9vo8ecDbt+fPkBYEobasJPtbiMWcY2bZzqCX4fQaCZmqTbl2N1MNxDCt1+9JA/79df1s6mqy1iaIJ4mk1ZVycbtULl/fyuXrW/mPuzeSMkyOXZjmpbMhDp2d5MUzk1mv+6MJg2jCYDwc4p1ffhJtTTNX9rWzs7+NHevbHMcpl7ftWMtXHz+JiRWGkki/ln/Tlm5Gp+fWgnApCh636mg5e9Px4EvlhK+GMVoJ29e3FozZzod9vcq5lrnOt60uEk2k+Pdv6OfrT56et+bFO3bOV49xu1S29DazpbcZrrC2pQyT02OzHB+24sCPXZjm+MgM0cRcfVPRJAfOTHLgzNwSLk1elxP/vXVNM9t6W+jrDFTsgJdDqWEkfw98HvifwAXgn4BvYulj1416ZTzXgj3bejh8LsS+/aeZCCfoCHq4uMdS3zgzHsbrVh0Zo1IzwK/oa6cvHOf5U+OcHg/jS9dxUXdTVjvXbu7gxMiMo3pit2uX2bW5k/ufH+CLj+hOm5+4TSt63cvJ4M+Hqir4VVd6QR8P7756A51NHv71xUEGJsKsa/Nz6+VrSaVMPvvQywxORFjbHuBtO9YWjeF+7tQ4Pz4yxNBkaccLgpCflWR/C1HOOWbaPHshstlYkmgyRZPfjRb0MjITI5JIOeoHAPueOc1kOJFepE1JL2hjoKoKYzMxxmbj/Na3DhDwuuhp9uH3qGzsCvLeqzdw6GyIf3nhLCPTMVp8bt5x1YYs+TKXqjiKDe+/rp+UYfKpHxzhuVPj89aNSBkmL5+f5uXz03znuQFUBbauaWFnXxtBr4vjwzOMTsccu3n3TRc56hCFFKdSpskzr43Ms7nXX9RlOd5ulfHZuGfrmpbKVgBagNUwRotR6Dn80H+5iZ2feSRrFdi2gId/+4Ob+fKjx7P8g0wVtAdeGuSHhwadt99vv3J9yddSURT8HuuZ/rFbL2UoFOVnrww7db1pazd7d28s+Izet/8MDx48RyiapM0/N9Zv3W491390+DxnxsL4vS66m31MRRK8OjSd9eNyNp5yQqtsAh4XW3qtJMxta1qIJVMcOD3BcChaVR+hVDWS53Vd36Vp2ou6rl+d3nZQ1/WrFipbQ+qi7FArcrOmh6ejDE/H8KiqM9uRMkw6mjzzFtIplFn95UeP86VfHM/alltHrvpIbrspwyRhGPQ2+7ISC8tRRSmlTCXY7bhVa8VNA+v166/fsJmd/e3zji9X0eQrj58UNRJRI2k0lkyNRJgj0+bZNhXIUnXKtX/5ythv7lyqQiJlWJ/TC3PZqx7atng4vTCHS7WSGe3nxPuu7eP9b8ivF7xv/xm+nbE8u5le6v2ajR14XCqHzk4ylef1vo3PrRLwuAh6XXxkz8X8uwXseSk2d3Ay2vSmrd3VCqKWMZum2HP4gZcG+ZcXzs7b98Yt3c5qpbllDp8LzfMnAO69ZUvZknn5+qYqcOv2Nfz8lWEM03TCqgAu6mnil/rIvHo+cP0mtq1pzjvGbtrWw2P6cHqtjVR6Vt0A0qFURVCwxrrP48LvVnn/G/q544p1uF0qf/DPh7b/83++8eWyTpjSZ7Yjmqb1kR7Imqa9CYgVLyKUQ27W9PjsXPZ6prM9Phuf52wXyqzel2FUbXLryFUfyW3XNv7j4XiWs12OKkopZSrBbidpL/GZ5lF9hHdetYFYMpWlivLTly/kraccRRNBEIRcMm1epqRZpqpTrv3LVybT2bY1thV7e/pnlG2Lx8NxDMM6Np4ynfWpHz46xH95yzYisSSz8VTWkvIPHsyeO7CT1E6OzvKdj16PYZqcGp3lpbOW2smhgVDWsvN27O1kJMFnHnyZS3qarITN/nau7Gubt6BRNVSkhMoo9hz+6cv578tTx8fYvr41b5kDp8bzlLB+wJXrbOfrm2FadXU1WdJ+XpdKwGOtuLr/xBiqwry1Mh58aZDL8/TX2neO9oAXr1vJykFb3xHgIzddZMkQXpjmtXQoSuYsvwnOYoEh4G9+fpy/++XrXNzTnLWgXzmUWur3gB8Cl2iadhDoBO6sqEUhL7lZ03Y8XuZiqgYmZp4fZIUyq/PpWObWkas+ktuu/X9ufGA5qiillKmEQu2cHg9berZed5YqyvhsnGb/XPyYiaUPfiEkiiaCIFROpi0qpP6Ua//ylcm097mL2divLGxbnC9mG6yFR5p9bpp9brpNa1Xh2ViKcDyZNykNYCq9/oKqKFzc08zFPc285+oNmKbJh7/xPLMxS2UinEhl5c28PjLL6yOzfO9Fy4m/qLuJnX1tjvMtKlL1o9hzuJBMn1Eg0uHMeLigLvZkWtayGn2bCCccZztl4mh5h6JJWn1uZ+LRVuqZiiYKjrFQNEl7YP7y60OhKOvaAqxrCzhvZkzTZHg6xsfvf4lIOqEzmjSyxnoiZaIPTbMrY5XLcljQ2dY07e3Ay8B1wCeBm4GHgBcqalHIS27WtJ29rma8Fc7MXs+kUGZ1R9Az7wuSW0eu+khuuypWeEbmMqjF2sx3LqWUqYRy21nfHph3vAJoa1tY0+q3Zm0SKaJV0AUXBGH1kGmLbJtq/22Ta5fylcm09wpzDnem9bVtsVtVMPL4TPaqe2DNXAe9boJeN6bpZX2bn1Ak4ShA2bT68y8drygKm7qbGJyI0I4H07QUTcKJFCiWMzQ2O+dsnRyd5eToLN8/OAhA0OvC41IIeiypQTsxUlSkak+x56M+NJXX4S6UKLixM8hIOmwpl8zxtti+5Qoz2PjdatbbG1WBoMdFe9DLxb3NnBqddUJObNr8+d3bfGNPURTWtPrZurYlS/UsmbKcbq/HxbpWP68NT5d8jrkUTQnWNO3jwH8H/MBlWM72fUAbVsKkUCXu2tWf9bmzyRrAmdnpLlVxtmdSKBt47/Wb5m3LrSMzGz5fu/b/nTlfqIVUUfJR7QzwctvJd7wJvOfqPpp8bjqbvKxrD7C5K8j69gDbN7RWFugsCMKqItO2FFJ/yrVL+cq4VCXL9trWP/M5YNvizqA3a7tNZoJkJoqi8L5d/UQShrPUe5PXhc+t5lWBsHnbjrVZdXjdKu0BDx976zbu/63r+dZvvoGPvXUbb7msl96W7NX9wvEUoUiS81MxToyFOTk2y4WpKGtafIxMSyRqLSn2fLTFFnK5cUtXwTL5/AkoPN4q6dve3fnbuCOnv4ZphXm8b1cf779uI16XSovfTZPPSsBUFXjHzg156yqmYJY51sFSQmn2ufnP/+5i/vw9O7j/t24odlpFWWhm+4PADbquhzVN+xzwgK7rX9E0TcGa7RbSLFZ9w1EjSWemtwc9vHFLNydGZpkMx53s9R8dPs/hc3OZtNvXtxZVAbnjynU89fpYVh1XbGjLUizZ5VZ56vgorw/P0B70cPm6Vk6MzBBLpvC5Vd5wcTcdQW/J2dxLlQFebjulHm9nTe/dvWkyXz2CIAg2X370OPueOc3YbBwlrY29qTPIyEyM86EoF6aitAU8TpxqIfWota1+TAVGpmNEEwZ+t4rHrTI6bSmYuFQFTJiKJXHNxvjQjZv50eHzvDw45YSZXL6+lSs2tBVUrLJja/ftP+M8Ez6weyO/+aaLiMStUJPcGU87trqQ8siGjgAbOgLcceU6TNNkaCrKS+kVLg8OTDrJomC9ig+lknznuQG+89wAfR0BPvfeK2t2b1Ya5fgZ+RTObGWRPdt6GJqK8tTxMQzTRFUUbtzSxbfv3u2MZ9sP2Xv9XBnIHjt7d2/knpu3lO3/5PN39l6/iXtu3sLTJ8Z4+vgoKRNcCtywpZsv3LkzraI2v20b+3u0qTvIndds4JrNnVy7qYMHDw5yamyWtQUUczJZaKwvhqJqJJmKI5qm7Qf+Ttf1b6Q/v6Lr+mWL7kHlLJv3/NVQ3yiljg98dT9PvDY675g3be3m23fvrqgfuWVy1UkqOZcVRLXFN0WNZAnKihpJ1Vg2Nna5UlDxKegh4HVlOZq2Ta3Eluaz7QMTYUs5IvOOm9AW9NDfkR2yUk6biZRBOJYikkgSSSw+pG5oKsqhgUleOhvi4MAk50PRrP3fvnu3qJGUQLnP92LHQ37N7Nt3rOXhPEmt1VYfK1SmLejhyePzfZxfu6aPL9y5M29dpZBIGc7KlpF4ylH2qYRK1UgWUpZPaprWnlYiuRp4BJxFbgrrA60yimX9VrOOp/IMQoCnj49V3I/cMpnqJKXWIQiCsBopqPgUjs+zofbnSmxpPtseiiTmeZZmensu5bTpcam0BT2sbQuwqTNIb6ufFr87b8hKKaxt9XPr9rV84jaNfR/ezXc+sps/+tVLueOKdVyVR6JVyE+5z/dixxfal288F2ujkn4VK/N0AR/noUPnC9ZVCh6XSqvfQ2+rn03dTaxvD9AR9BLwuEpe0n2xLBRG8jngYPq4r+i6fl7TtLuAvwA+U+vONQrVUN8opY4CyefOr7RK+pFbJledpJQ6BEEQViOFFJ8MY74NtT9XYkvz2fZCk3P5tldqv1VVcZRNTNMkmjCYjSeJxFIk8mVnlkBvq5+3tPp5y2VW7OzgZHSBEgKU/3wvenyBwTMZTtDV7Ju3vdrqY4XKpEzI5/vGkqmCdVWCvbgOWKtVR5PWjHckniKeu9pTlSg6s63r+j8DNwK/quv6b6c3zwAf1nX9WzXpUQPSX0D9ohz1jVLqKDSx4EqPzkr6kVvGzp7PzKJfqA5BEITVSD71BBVrJchcG2p/rsSW5rPthSbk8m2vhv1WFIVAenW+/nQSeXvQi3eJll5f7ZT7fC92fKF97QXUQMrxIRZTxlVgTPvcroJ1LRY1LRPc1eyjrzPIRudtjqeqY3vBmnRdH9R1/VDG5x/puv7LqvVgBVAN9Y1S6rhxS3feY25IZxBX0o/cMrnqJKXUIQiCsBopqPgU9M6zofbnSmxpPtveFvDMC9BX0ttzqYX99ntcdDZ56esM0tcRpLPJ68wWCtWnGupb9vEF1UAKKI5UW32sUJkbCvg4d1y5rmBd1cZWIOlpsZzv/s4g3S0+Wnxu3KqC21VZ3Inr05/+dJW7umR8ut4dsNnU1URfR4DBUJSpaJJNXU185KaLy0qCKaWO917Tx/OnJzg3EcHEmtF+Yzo5stJ+5JbZtqaFX71iHS5VrfhcVhDVDpX6dJXrK4lvPHWKyQILEizEpq4gU9FkReXrVbYj6OU3btxcdrkVQjXH7KerWNeK5A0XdaIo8Nqwpd7U0eTlI3su5gPXb2J0Nk4kkcLjUukIetjR116xLc1n2z9+q4ZLVTg5MkvKMPG7Xbzr6g3817dsW9SzqBJcqqXg1OL30OJ343ZZiuEF1k7JYjqa/IuNXcHKDNR8Pl2lepYd5T7fix1faN+du/oX7UMspszvvXWblRifOaav2rCo5MjF4lIVfG4XTT43bUEv3c2+P97c3VR27FNRNZJlTsN23GYhuZx8+4GyJHYWK0m40ijzeogaiaiRNBqiRlIFKrGb5ZSpp11eyrYNw1oAJ9/S8c+dGufho0M8/frY86/+j7ddV6UmV/SYLffe2TJ+jvRfWl6vmm00Kos4z4psbGWLvAuLJlf65vRY2Pm8Z1tP3v1/+oMjAI4kX26ZcttYbcj1EARhISqxE+WUqacdWuq2MxMsM5eOf+zYCF99/KSdhyRB3yVQ7r3LlaWcCCecz4Uc7tXyjKzHeYqzXSeKyeXs2daTd7+d+d6Ss7SuXabcNlYbcj2EUvnQV/czkLFsb6n0dwT4ZjqsS2hMKrET5ZQAN5y/AAAgAElEQVSppx2qZ9uZS8f/27FhWgJuMAurqgjZlHvvCsn47dt/pqCzvVqekfU4T3G268RCcjn59udKSeWWKbeN1YZcD6FUBioMYREan2pKmeUrU087tFxs4OmxsCNlG0sWErUVMin33uWTpQSYDMer1kajUo/zlNc3dWIhuZx8+71udZ6cVGaZcttYbcj1EARhIaopZZavTD3t0HKxgYX6IRSm3HuXT5YSoD3orVobjUo9zrNmzramaR5N076ladrjmqY9q2naO3P2/76maUc1Tftl+p9Wq74sRxaSy8m3vyPoyfsFqkT6ZzUi10MQhIWoppRZvjL1tEPLxQYW6odQmHLvXSEZv727N1atjUalHudZyzCSDwBjuq5/UNO0LuBF4IGM/dcAH9J1/UAN+1ARpWSpLjZjd8+2Hg6fC7HvmdNMhhO0Bz3cuKWb+58f4IuP6PR3BtHWtvDU66NzmcS7N3HFhja+e+AsZ8bDbOwMcue1fQXbtbcvdHwlGcuVXLN6U+r1EARh5VCubSrXTtj1j0xHCUUSGCZ0NXnZe/2mvGUy6z86GCKaSOF3u5w40oXaef7UOJORBGZGO6Xa60LnBnDvfS8smf3O7Mfhc6HqLg+4Qik2Los9w/ftP8NkOE570Mve3Rud7cW+F4XGfrnfpWLHF9pX7vZqX8taUTPpP03TmgFF1/XptLP9nK7rF2fsfwU4CqwFHtJ1/S/LbKImHc/NUrX5xG1a1iBZ6Jhy25mOJrgwFWNNq48Wv2fe50raKIXcjGWbe2/ZUrIBr8b1WKaI9N8qlf6r9JotA9lBkf7LoNa2ya7fttc2tt0u1k45fbOPHZ6KMjwz145HVXGpSln2ejH9qBEyZhdBJc/wSu55uWWKHQ/k3Xf7jrU8fGSo5O118jEqGq81CyPRdX0m7Wi3AP8M/EnOId8B/hNwC/AmTdPeXqu+lEOxLNVyjim3HTuZodD/lbRRCsUylkulGtdDEASh2tTaNtn159pp+3Oxdsrpm33seE5yWyqdW1iOvV5MP4TlRyXP8Eruebllih1faN++/QXOpcA5NtIYrWmCpKZp/cCjwLd0Xb8vY7sC/LWu66O6rseBh4Cra9mXUiklS7Uamay5ddhKI4X+r6SNUqgkYzmX1ZLBLDQGarXfRwgNS61tk11/rp22P1dbwSRXuMNIT+SWY68X0w9h+bFUqiPllil2fKF9hc8l//ZGGqM1i9nWNG0N8Ahwr67rP8/Z3Qoc0TTtMmAWa3b7a7XqSzn0dwY5PTb/BmZmqZZyTLnteN0q8aThqI3kfq6kjVLoCHryDvBiGcu5VON6CEK1WN8eqFgnG+C6TR1V7pFQL2ptm+z6bXttY9vthRRMSu2bfaxbVbIcbjX9Rrsce72YfgjLj0qe4ZXc83LLFDveNM28+worqOTf3khjtJYz238EdACfylAc2atp2kd1XQ+l9z8KPA4c1XX9RzXsS8mUkqVajUzW3DrsQVbo/0raKIVKMpZzWS0ZzELjYOtkV/Lv/FS03t0XqkStbZNdf66dtj9XW8GkM8eBcqVf45RjrxfTD2H5sVSqI+WWKXZ8oX17dxc4lwLn2EhjtGYz27qu/y7wu0X2fwv4Vq3ar5R8KiG5WeXVyGTds62HB14a5KFDg0STBn63yrWbO+kIejkzHuaKvnbuXNvCq0PTNc2WXShjudRzAVH5EARheVGKbSpV5SDzOL/HBUA0kSLodRH0uVBVhWjCsuXbN7QtaAPLsZuZxz53aoxQOIlhmnQ1+8q214vph1BfCqmOnBydzfIl7rhyfdExUck9L7dMKcfn21dIca0cJbblSM3USJaAuqmRVINqqIAINUfUSBpQjWQxZRdbXtRIGotS7X3mcZnKI5lqUStAfaleyJgtgUI+wx1XrkMfmp63XcZjzVheaiSNylJlZldDBUQQBEGonFLtfeZxmfGxmX83kjKC0HgU8hkeOjSYd7uMx+WFONs5LFVmdjVUQARBEITKKdXeZx6XmQiZ+XcjKSMIjUchnyGao4RjI+NxeSHOdg79BbJba6ECko/FZJULgiAIpVOqvc88LlMhKvPvRlJGEBqPQj6D353fjZPxuLwQZzuHpcrMroYKiCAIglA5pdr7zOMynZ7MvxtJGUFoPAr5DHdcuT7vdhmPy4uaqZHUi1IzywtRKIMW4N77Xqi43lwyM4hjSQNfCRnEtWKx10wQhNXDSrIXjvrU/gyFh92b5p1P7nNhbasfU4FowqjoGbGSrmGj0mj3wPYZfnjoPPFkCq/bxduvXMcX7tzJY8dGylbqKKRsItSGFeVs52aWnx4LO5/LdbgLZaIvpt7cvupD02zpbXG26UPTPHZsZEm/8LU4N6H6VLpIiyzQIlSTlWYvHjs2wsNHhuhq8tHV5APg4SNDXLGhLa/DXcx5LvW6rLRr2Ig04j2wfYatvc3OtkyfoZx+5yqbTIQTzmdxuGvDigojqZWSSC3qXSrVk0bph1CcShdpkQVahGqy0uxFtc6nnHpW2jVsRBrxHlSzz6KGtvSsKGe7Vkoitah3qVRPGqUfgiAsf1aavajW+ZRTz0q7ho1II96DavZZ1NCWnhXlbNdKSaQW9S6V6kmj9EMQhOXPSrMX1TqfcupZadewEWnEe1DNPosa2tKzopztWimJ1KLepVI9aZR+CIKw/Flp9qJa51NOPSvtGjYijXgPqtlnUUNbelZUgmQhJZHFJjzUot5a9bWUDOPcLOzbd6zl1aHpqvZDEISVR63sVr2o1vmUqmqS2+bRcyGiiRR+j+rE5C7UdqOpaCxHGnEcO2PsmdNMhhO0p5/vlfTZ9gn27T/DZDhOe9DL3t0bF0yOFAWTyllRzjYUzxhfbvVWu85SMozzZWGfHgvzidu0ZW1oBEFYHtTKxtaLapxPOaomdpsAp0ZnafJZj+FSFDEaUUVjudJo49gZY80+upoXHmMLcc/NW8pylEXBZHGsqDCS1U4pGcaNmIUtCIKwnKnEri5VGWFlUO97Lwomi0Oc7RVEKRnGjZiFLQiCsJypxK4uVRlhZVDvey8KJotDnO0VRCkZxo2YhS0IgrCcqcSuLlUZYWVQ73svCiaLQ5ztFUQpGcaNmIUtCIKwnKnEri5VGWFlUO97Lwomi2PFJUiuZkrJMG7ELGxBEITlTCV2danKCCuDet/7ShVMBAvFNM1696FSGrbjQsOgVLOyD311vzkwESm73HWbOnju9AQnR2fLLnvT1m7Oppd6r4TFlG/Esostf1F3E49+/M0VtVslqjlmxcYKS4GMWaGRqGi8ysy2ICwRAxU6cH0dgRr0RhAEQRCEpUBitgVBEARBEAShRoizLQiCIAiCIAg1QpxtQRAEQRAEQagRNYvZ1jTNA3wN2Az4gM/quv5Axv53AH8KJIGv6br+j7XqiyAIgiAIgiDUg1omSH4AGNN1/YOapnUBLwIPgOOI/xVwHTALPKlp2oO6rg/VsD+L4rFjI9z//AAD42H6O4Pctatf5JYEQRBWIGLvheWIjMvGpZbO9neBf874nMz4+zLguK7rEwCapj0B3JQus+x47NgIn/+J7nw+PRZ2PstAFwTBRq2qWKRQD8TeC8sRGZeNTc2cbV3XZwA0TWvBcrr/JGN3KxDK+DwNtNWqL4vl/ucH8m7/7oGzMsgFQXBY3x7gQ1/dT6V66kNT0YrKAvR3BPjm3bsrKivMIfZeWI7IuGxsaqqzrWlaP/CvwN/pun5fxq4poCXjcwswWcu+LIaB8XDe7WcKbBcEYfWyGD31xSzGI1QHsffCckTGZWNTMzUSTdPWAI8Af6jr+tdydr8CbNU0rVPTNC+wB3i6Vn1ZLP2dwbzbNxbYLgiCIDQmYu+F5YiMy8amltJ/fwR0AJ/SNO2X6X97NU37qK7rCeD3gZ9gOdlf03X9XA37siju2tWfd/ud1/YtcU8EQRCEWiL2XliOyLhsbGoZs/27wO8W2f8g8GCt2q8mdjzUdw+c5cx4mI2dQe68tk/ipARBEFYYYu+F5YiMy8ampjHbK4k923pkUAuCIKwCxN4LyxEZl42LrCApCIIgCIIgCDVCZrYFYYno7whUVG5dq59K5ZsXU7aebcs5l0+l40sQBEGoLYppmvXugyAIgiAIgiCsSCSMRBAEQRAEQRBqhDjbgiAIgiAIglAjxNkWBEEQBEEQhBohzrYgCIIgCIIg1AhxtgVBEARBEAShRoizLQiCIAiCIAg1QpxtQRAEQRAEQagR4mwLgiAIgiAIQo1o5BUkZTUeodYsZkG/fMiYFWpNNcesjFdhKZAxKzQSFY1XmdkWBEEQBEEQhBpRt5ltTdM8wDeAzUAK+Iiu66/Wqz+CIAiCIAiCUG3qObP9q4Bb1/UbgT8D/ryOfREEQRAEQRCEqlNPZ/sY4NY0TQVagUQd+yIIgiAIgiAIVaeeCZIzWCEkrwLdwNvr2BdBEARBEARBqDr1nNn+PeAnuq5vA3YC39A0zV/H/giCIAiCIAhCVannzPYEc6Ej44AHcNWvO4IgCIIgCIJQXRTTrI8spaZpzcDXgHWAF/gbXdfvK6MK0dMUaoZhmPzg4Lm177mm70IVq5UxK9SaqmkWf+ir+82BiUhFZfs7Anzz7t3V6oqwshGdbaGRqGi81m1mW9f1GeCuerUvCIVIGSYXpqI8d2rC/Z5r+urdHUGoCwMTEU6Ozta7G4IgCA1PI68gKQhVJ2WYDIUixJJGvbsiCIIgCMIKQFaQFIQ04mgLgiAIglBtZGZbEIBkymAoFCWeMjBMk/0nxuvdJUEQBEEQVgAysy2sehIpg/NpRzuRMvjcj1/lj79/pN7dEgRBEARhBSAz28KqJpEyOD8ZJWkYhONJ/vsDL3Pg9ES9uyUIgiAIwgpBnG1h1RJPWqEjScNgfDbOJ793mOPDMwD0tvjq3DtBEARBEFYCEkYirEqiiRTnQxGShsHAeJjf+acXHUf74u4m/vY/XF3nHgqCIAiCsBKQmW1h1RGJp7gwFcUwTV45P8Uf/esRQhFrMdOdfW38j3ftoNkvXw1BEARBEBaPeBTCqmI2lmR4OoZpmjxzYow/e/Blommpv3+3rYf/9rZL8brlhY8gCIIgCNVBnG1h1TAdTTAyHQPgx0eG+OIjOkZ6cd/3Xr2B3775ElRlbiXWtW1+EdwWBEEQBGFRiLMtrApCkQRjM9aM9rf3n+HrT55y9n3kpot4/3X9KGlHW1EUupu9/Jdf2Xq+Tt0VBEEQBGGFIM62sOIJhROMzcZIGSZ/+4vjPPDSIAAuVeETt2ncevka51iXqrCm1Y/f46pXdwVBEARBWEHUzdnWNO03gN9If/QDVwFrdV2frFefhJXHZDjO+GycWCLFn//oVZ44PgqA36PymXdu57rNnc6xXpfKmjY/HpfEbAuCIAiCUB3q5mzruv5/gP8DoGnal4GviaMtVJOJ2TgT4TjT0QR/8v0jHD43BUBH0MNfvOcKtLUtzrFNXjc9LT5UVSlUnSAIgiAIQtnUPYxE07RdwHZd1++pd1+ElcP4bJzJcJwLU1E++b3DnB4LA7C+3c///LUr2dAecI5tC3joapZFbARBEARBqD51d7aBPwI+U+9OCCuHsZkYoUiCEyMzfPJ7hxmdiQOgrWnhrl19fPWJkwxNRljXEeA/XreRt25fW+ce14fHjo1w//MDDIyH6e8McteufvZs66l3twRBEAShpiz186+uzramae3ApbquP1rPfggrA9M0GZ2JMR1N8tLAJH/ygyPMxlIAvGFzB2/fuY5vP30GALdLYSqc4H//4jg+j2vVOZmPHRvh8z/Rnc+nx8LO59V2LQRBEITVQz2ef/XOBNsD/KzOfRBWAKZpMjxlOdr/dmyEP/iXQ46jfdv2NXz23Tv4xasjAHjdKn6Pi3jKEtn+7oGzdet3vbj/+YG821fjtRAEQRBWD/V4/tU7jEQDTtS5D0KDYxgmF6aiRBIp/vXFc3zpF8dJr1XD3t0b+c03bkZRFIYmI/g9LlQVEinTKX9mPFyfjteRgQLnvBqvhSAIgrB6WMzz78i5UGDHhrZIuW3W1dnWdf3z9WxfaHxShslQKEI0keIrT5zkn561frEqwO/csoV3X73BOXbLmmYOnJxgNBwnaZi4VYXOoJc3XNxVp97Xj/7OoJM0msnGzmDRcqs5zns1n7sgCEI9qcT+FipT6fMvEk/xf546teULd+48XG7/6z2zLQgVk0wZDIWihONJvvDIMR55+QIAHpfCH//qZVlfxI6gl4DHzdBMbK68YTI8E8Pnrnc01dJz167+rJg1mzuv7StYZjXHea/mcxcEQagnldjfYmUqef7ZUsKnRmdTlZyDONtCQ5JIGZyfjDIdTfCZB4/y7KkJAJp8Lj777h3s7GsH4MCpCZ44PsKpsTD6hWlcioJpgoGJioJLVXjq9bF6nkpdsA3Udw+c5cx4mI2dQe68tq+o41gszq2YwVsJs8GVnLsgCIKweBayv/meM8XK/O1/uNr5e6HnX8owGZmOEo6neH14puJzEGdbaDjiSWtGe2Qmyh997wj6hWkAupu9fO69V3BxTzMAB89M8E/PnXHis2NJAwCPquJV52azJ8PxJT6D5cGebT1lOYrlxrmtpNlgiXEXBEGoD8Xsb6HnzGwsSZNvvotr2+xSnn/RRIrhqRixZIr79p/hG0+f4pqNHRWdw+p7fy40NLFkivOhCKfHZ/mdf3rRcbQ3dQX50n+42nG0fW6VXx4byUqEdKdXh0wZZlad7UHvEvW+sekvEM9WKM5tJSmelHvugiAIQnUoZn8LPWeiyfzRHqXa7MlwnPOhKGcnw/z+/Qf5+lOnyHEdykKcbaFhiCZSnJ+M8vLgFL9z34sMTkYBuGJDK3/z76+it9UPQLPPzbq2wLwEiM60U22Q/Y3Zu3vjEvS+8blrV3/e7YXi3FbSbHC55y4IgiBUh2L2t9Bzxu9xFSxTjJRhciEUZXw2zs9fucBHvvk8h89NAdDqrzwYRJxtoSGIJlIMhaI8c2KM37v/IJORBAA3be3m8+/bSWvAA0B7wENvqx9VVeb9Gu5t9dPb7MPvdqEo0NHk5d5btnDPzVuyjnvs2Aj33vcCmz/50LNLc3aNwZ5tPXziNo3N3U2oqsLm7iY+cZtW8FXcSpoN3rOth9t3rGVsNsbxkRnGZmPcvmNtw4XDCIIgNBrF7G+h58z29W1lPa/A8jPOTUQYmYnyPx9+lc8+9IqzXsfVG9v5xw/tqvgcJGZbWPaE40kuTMX4yZHzfP6RY04YyLt2rufeW7bgSoeHdDX7aEs73ZA/47i31c/n7yz8hcuJ/5IfozmUE+ddScb3cuWxYyM8fGSIriYfXU0+AB4+MsQVG9rE4RYEQaghxexvsedMOc+rUDjBeDjOy4Mh/vxHrzhvzt2qwm++6SLu2tWHqigVn4M428KyZjaW5MJUlPv2n+ErT5x0tl/UHeSGSzpxqQqqotDb6iPozR7O1VTcEIpTTHWknOu/XBE1EkEQhOpRjlJVtZRF8pEyTEanY0xFE3znuTN8/cm52Oy+jgB/csdlbFvT4hy/s7+97AVtQJxtYRkzE0syFIrypV+8xvcPDjrb17T48KgqX3viFF6Xyh071+Nz54/PqpbihlCYhVRHVoIzupLizwVBEOpJuUpVC9nfSp8zttrI4GSYv/zxq7x0NuTsu+OKdfz2zZcQSMd+u1WVnhYfn3r75ScL1VcMeU0uLEumognOjof5sx8edRxtBdjQ5ndCRfweF4+9NlrQ0a6EQvFfQmFWkupIIVZS/LkgCEI9KfeZUQv7GwonOB+K8rNXLvDhbx5wHO0Wv5vPvHM7H7t1m+Not/jc9HUECHgr9zXE2RaWHZPhOKdGZvmDfznEY8dGAXAp1isdWzfT+t/kZJ4lVxdDoaxnoTCrYdZX1EgEQRCqQ7nPjGra35RhMjwVZWBils/9+BX+7IcvMxNLAnBVfztf+dAubtraDYBLVeht9dOTFl1YDBJGIiwrxmZiHB+e4ZPfO8zJ0VnAWn69xefGMK1Aqha/m0TKxEQh4FG5974XSl6hcKE4scw448PnQhUty7qSyXf9+juD82QWwZp1WM4rSJbTt5UUfy4IglBPKn1mLNb+RhMpRqZjHDo7yZ/+4Chjs9aCdgpw2441fOytmiO40OR109Xsxe2y5qTtfv3w0PlnT33ujjeUe86KaS5Cpbu+NGzHhfmYppWkcHgwxB/+82FGZmKAtTjNhjY/sZTB+GycTZ1BPOmwkemoJf/X4vdk1VVI3ic3Tmyh47G+g9Wkocdsoet3+461PHxkqOTtC8kvLQUVjIVGoWpj9uYv/NK0f/CWy0XdTTz68TdXqyurgg99dT8DExXlXtHfEeCbd++uco+WjGra2Ya2sauFcp8l1bDLoXCCkZkY33n2DF978qSTBOlxKaxr9eP3uLj7povYfVEXHU3eLGWzzP4ePhc6cOpzd5StAVjXmW1N0/4b8E7AC/ydrutfrWd/Viv1nn00TZPhqRjPnBjjT35whOmo9UrH51ZxqwrnQlECXhe9zT6mYil6vG42dgYZnooSjs+ffC6kEFFvRYlCy8c2CoWu36tD03ziNm3erEOl17vYeKzWWK33WBCEXAYmIlT640YQGok923o4fC7Evv2nmQgn6Ah62Lt7E6+cn8p7/GLssmGYjM7EODEyw+cefpWDA3NJkK1+N73NPidE5LFjo7z3mj48ruwI6/ufH2A6mmAinAC4rJJ+1O3Jr2nam4EbgTcCQeDj9erLaqbcrOBqY5omF6ai/OToBf78R68QTxoABL0qyZRJ0gCvWwXTZHgmzrp2Pz+4540AvOtLT+Sts1DcV71ji0enY8zGknQ1+5xXVY1EseuXLxv8i4/Mn7mwjy9EsfEIVG2s1nssCIIgrFYK6WYXmpCq1C7HkilGpmL87JULfPGnx5yJPFWBNS1+WtIrQqoqNPk8nJuMzHO0AV4enOLCVKyiPtjUc5rtNuAw8K9AK/CJOvZl1VKrGb5SZiANw2R4Osp3nhvgf//8Nee1TmfQw3QsAaZCwKtiGBBLWTujCcMpXyzuKx/lHl8LZmJJIokUPS3zdcGXO5Vc7yPnQkyEE8STBl63SkfQwxV97QXbyJxByCzz3QNnKRTyVslYXQ5jQRAEYTVSyO+IJlN5ne2F7HI+f+Oqje2cHQ/zpV8c50cZoSk7+9oIeF0MjIcZDEVxqwpet0I0YRR8NkUTi0/fqqcaSTewC7gT+E/APk3TGm+6r8GpxQyfPTt5eiyMYc7NQD52bMQ5xjBMhkIRvvTocf76Z3OOdk+zl+5mH5gKXrdKPGGQNOacLL97bsiWm6G8XBQlUobJUCjK6HSsoAO5HCn3+l22rpULUzHnbUU8aXBhKsala1vyHg/w8mAob5mjg6GqjtXlMhYEQRBWG4Vsud+TX1qvmF3O9TcGxsP81U+P8Y+Pvc5Hv3XAcbRdqsKH33QRX7hzJ9vXtzERTuBzqyRSBtPRVNFnk9+zeFe5nlNrY8Cruq7HAV3TtCjQAwzXsU+rjlJm+EqZpc48ZmQ6htetzktctGcgDcPk3GSYv/zRq84XQVFgbYvPKdPV4mVsJu442m5VoTPoZfuGNqe+cjOUl5uixFQ0QSyZoqfFb4XK1IBqxuOXe/1eOT+Fz60SiiYwTeset/k9vDo0XbCNzDcXudsvX1e92ejlNhYEQRAalXKfM8Xeet55bV/Fqz57XArxhMG5qQhf+sWkky3rcSlcsaGNrWuacakK5ybD9LX7uTAdxzBx2i/0bLp8fRuGafU3kkhVNENWT2f7CeB3NU37X8A6oAnLAReWkLt29efNCrZ/SZYS0517TDqJAMhWCjkzHiZlmJwaneWPv3+YZ06MA9DkddHZ5CHgcTuxU6FIwnG0/Wn1kaloct4vz3JXjlpuKxrGkgbnJiN05mQ/V4NaxOOXc/2ePzVOKK0Yo6TfWYWiCZ47Vfhrbs1sJOZvd6sLjtVyWW5jQRAEodGo5Dlz2bpWfv7K3Lyq/QbzzrUtFa/67HWrhCJxzk1EiWSEfdhJkDPRJF9/8iTtAQ9DkxF8HjcbO7Nd4GI636fHwrT4PRw+F3q15M5lULcwEl3Xfwi8CDwLPAjco+u66BovMXu29fCJ2zQ2dzehqgqbu5uyZHZKWenp/ucHGJ6K8urQFEcGQ0STKRIpI8vpno4mmJiJ8q6/fZx3/92TjqPd1eTlr99/FZf0tuBxKwS9buJJg2jSwKNaaiRgfZHWtPqKzoo2KqZpMjYT40IoSjKVf2a3Euq9suNkZL7TDBAKJwuWuXx9K60BN0nDIJZMkTQMWgNutm9oY8+2HrS1Lbw2PM2RwRCvDU+jpY2zIAiCsPRU8px55fwUa1p9zhvdxTzfN3YGiCZTHD0X4vjwrONoK8C6Vh9r0wvS+D0ugl43Pzw8RF9nE9PRBGfGwxwfnuHMeJjpaKLgW9I923q4fcdaxmZjAJeW3UnqLP2n6/of1LN9waLYL8lS4mSfPzXO8ExGpq4JSdNkNr0q03Q0wfhsnFa/G314BvstTE+Lj795/1WsbfXzrp3r+dbTp5198aSBS1VY0+qfNzu+UpmNJ4lOpuht8S9qWVibeituFApHN4rEqdszHm5VxY6smYpYbzS+/OhxHjp0HgXFedvx0KHzXNTdxD03b6l29wVBEIQFqOQ5MzBuzRLnhpqW+2yKJVOsafXz0OEhMlK7UID2gJsWvwcFaPa7SaQMEimrjVsvX1NwZj0fmeopg5PRima2G0sOQSibUmKpvvzocfY9M6d3eXFvMyeGZ5gIJzAxafN76G31Z5XJ/AU4GUmAOX81AdPE0q80TZp8Ls5PxUjZoSEeFW1tC2tb/QS9Lt551Qa6mn1OrFZHkweva37c90pXi0gZJudDEdoDHjqavChK5TnDC8XjVxLPnTtW9l6/iXtu3pK3rq4mLy7e5AcAACAASURBVKMzcVKGiYGJioJLVehq9hVs357xyI3le3VomgOnxvP2ad/+M1yxoW3ZrlQpCILQKFQSf11uLk0lSlW5hMIJnjk5xr5nB7IcbVWxHG23qpIwDMLxFGcmIlltFHvO5HvGFdL/LoeqOduapl2GpTDieAe6rj9WrfqF8ikllurLjx7nS7847hwzPB1z5HA8Lkt2z561znS4M+NkUykz77JdqgL/96PXc/tf/RtDUzFnprPJ62Jdm5/R6RgtfjfdzT4URcmaYS+0wtRqUYuYjCSIJFJ0t/jwuSub5S4W41xJnF3uWJkIJ/jSL45zcnQWPeP1n13XjVu6eejQ+Xma4nt3byzY/mwsUXDGIzMsKZOxmVhdteIFQRBWApU8FyrJpSkWs70QtmTw1544ydeePJWlVuZxKaiKQjhh0Bl0MTIVw05nzGzjkaNDeZ8zz50a42cvX3A+28+4toCHnhbfgn0rRlWcbU3T/gF4G/A6cxOcJnBLNeoXKqMUDe19z5zO2mfPPCcNk5SZQkVBAUZnYkzFks5KT5lfPJdLIWnMd7h9bpVf+eIvOTcZdba1+d30tvhQFQVtbQs9LX7yIWoRVvLk4GSUjqCH9qC37PLFruG9972Qt0wxzercsWLz0KFBtvTON5KxpMG1mzt46vgohmn9+LpxSzf33LyFe+97Ia+edjxp0JTHpm3sDDIyFc3rcBdaH0hWgxQEQSidStbdqORZXYlSFVh61y8PTvHZh17mhTOTznb7EZBImfhdCn63yng4ydoCs9eFZuMnw4m0x5OzPZJYHs428CvAJWkZP2GZUEosVa7zkuswG+acE72lpxmwVnq6Ip2wBtAe8HAhGZsboiYEPCqRRIqZybmc15a0o+1yKTR5PfzaNcVnqVeaWsRv3/cCH73pYq7oa1v44DSmaTI+GyccT9Hd7CtbIrDQNawkzq7QzHIsmT+p87lTY4TCyayZ+QOnJvjyo8fnrchlzzq0B/Mrstx5bR+Xrm3Jmlm3KaTispLj+wVBEKpNpXk+5T6rK1GqCoUTPPDSOT7/E52p9EqQTT4XKjAds/yMJq+LRMokFEviVpWCb0k/9tZteWfjbcd//vbFr4dRLWf7DBAAxNleRpQSS9UR9BR0omDO+c4dgJm/dHdt7uS5k+OMhy1d7IBHJZowyHTB2gNuvG4Xfp+LS7pbeO81G1aUI10KRwen+N3/e5A3buniIzddXFb8eTSRsiQCg17aCjik5VBJnF2hseIr8AOg0CzBvv1nCmZPKorCJ27T8s6SOG9j9v//7L13nBx3ff//nJmdrbfXm069jiVZcpEbLnIJxMYGG1wIxMQECAZifwN8vzgxJhC+QAL87CQQyhdIHEKxAReMHTsu2LhiW1iSZRXLI6tLdyddb1tnZ+b3x+zubZu9tifpdJ/nAyPd7M5nZ3XzmXnP+/N+v14HGYgmqQ16ufHcBezsHBJukIITgpvu3sCh/tiE9zt7Yd00HI1AMDGOlbPuRJSqLMvmUF+UO5/SeXRrZ3b7qW3V3HHVSj77y9cxLRtFkhgxnNV4VZadfrESLKgPumbjb39wa8l7XEOVL3tf2tY+OCnVvCkF25qm/QQnHvMAb2ia9gKQ/dfSdf1jUxlfMDXcaqlOaQ1z672bOdQXpTqg0jOSLKqrLUQpiLZzn3QzGpTN1X48isTWQwPZQFsC5tT4kSRIGBY+WSZlVU7ebibyh929vLKnl/esbeMj5y+kbpwlIrZt0xtJEEmmaAr7UJXJK3dOps7uxvMWlswsX7W2La9me/R4S2cJBqJJWqt9mJZd1DzpV+WyWZJbLl1WpDzywq5uvvzw9qLlwtlS3y84cTjUH2NfT2TC+82rC0zD0QgEE6PSXgZujFepKm6YvLy7h6/895vZmEOW4KZ3LOTGcxeiyBJ1QZVI0iRaYIhWGywd3uZ+F9u2wbazmWu3e9yN5y7I3pe++6Ezzh33F81hqpnt59J/Pl/itZnjQ32SUurp7ZTWME+kXRsBVEWmLqRimDZxw8SvKnhkiUTKdOq3JSfQDvnyT5XcJ93M5/x640Gefas725AgSzC3NoBl20QSJrIMCdOetQ1sP/jzM/jBc3vY3jGEZcMjb3TwuzeP8sFz5nPDunmuVrWFxA2T9v4YjWEfVb7JTeHJ1NllgtzCzHJGjWS8WYLaoJemsJ/D/fGi16ZaFycQCASCyXGseqXGUqoC6I8m+fHze/n3F/dmmyDn1Pi548pTWN1WgyRJ1Ie81IV87OstXk1a2BDilkuWlfwubo2gt12ucetly0re46bKlIJtXdd/CqBp2hd0Xf9G7muapv3TVMYWVIbCLGGpxrjmsJ9FjSG++6EzeGFXN7c98AaJlIkNyOnUZF1B6ULhk25brZ+3OoeJJp0VFo8sMa82gNcjM5QwMEyLpmB+IDXbGthWt9XwnQ+ezku7e/n3F/dyuD9GzDD5yR/288gbHXzs/EX86erWMVcZwMkAdA3Fifo8NFT5xrVPIW4Z5HLST6Uyy25jlcsSvLCrG0WWio5bsicuPXXfxkMla/Nm2/klEAgEU+VY9Epl7g2llKqe17v42Sv7eWVvXzaeAHjnymY+8yfLCfk8+FUlu7prg+u9xO273LfxUMkG/fs3Hea7HzpjWnwbplpG8k2gGbha07TlBeOeB9wxlfEFlWesBoht7YP0RwyylR42IDk22rIslXzSff1gP5/6xaZsw9vSphAfPHs+L+/tYyRu0D2coCnsm7KA/cmAJElctLyRdyyp59GtnfzslQMMxAx6R5Lc+dQuHtzczs3rl3D2orpxaWyPJFLEDJOGqslnuXOppMV7uUz4UzuOlNQ57RqeuIzf8TbvEQgEAsH4cbs3rJoT5ssP7+BQfzSrnS1L8IGz5nHz+qVIklSkzhU3zJL3kphL4z7g2qAvtw9Ozxdm6mUkDwKrcNRIcktJUsDXpji2YBoYqwHinlcPFD0lmpbN/t4oWktVUVfus2918ZlfvZ7tDg6mNbRrA16+88HTqfar3HrvZtHAVoBHkXnfGXN516oWfvXaIe7fdJhkymJvT4Tbf7ONdQtquXn9Epa3jK07alpOljvm99AQ8rk2hoyHyUg/jYltOzV6OefO/PogVm+06AGsdyRRVLI01ucfq6YegUAgEFSGwlXSI0NxrvvBH/Kkgv2qzJxqP0eHk2xrH+SZnUc50Ju/4ul2Lyl3/Y8bZsmeoXiZAH2qTLWM5DXgNU3THtJ1feoWO4JpZ6wGiMIaW9OyMSwLyQLLzs80dg8n+MJD20imT9Cwz0NrtY++SJJfvXaQlho/61c0HbOmi5lIyOfh4xcu5urT2vjJH/bz5I4j2MCmgwN88hebeefKZj5+4WJaqkvrkecyHE+RMCwaw75x138XUskssZsJDrifh361dNNnuc8X55dAIBDMTCzL5pU9Pdzx0Pa8QLsh5KU+qKIoEkcGY9z94l7stLpVbhwymeu/ZTtxTfZnbCzLxrJP0GA7hx2aprUBGZXx2vTf9wKf0HV9S4U+Z9bz+fvf4NGtHSRSFj6PzFmL6qkNqNn61pVzqtnZOeRa7+rWNHnfxkP881M6NjaWRTazbVqOD7stwe6uEbwemYagyp1P6uzoGMwu9dQFVBqrvPhUBVWRSZp2Nhu5fkUT29oHuWdDjgVqgTHObKcp7ONvr9C4ft1cfvzCXv64vx+Ap3d28fyubq47cx5/fs4Cqvzlp2zStOgYiFEb9FIXVCds9z6/PshLu3sYjOWYDQRULlo+6jhayq69FPe8eqBk9uCeDQd5+fbLSp4TOzuHJmzjKwyQBAKBYPpx66eZaJ9NZqwHNh7itQN9eQ7TsuSomPVGkiRSKeqDXlI2eBXZtcYaJnb9lyUJRZIw02Z8Ek7MI0vypL7LeKhUsP088ICu678F0DTt3cAHgH8Dvg9cUGonTdNeBzJFMvt0Xf9ohY7npOTz97/Bg5sPZ3+OGxYvvd1DXVBlXl2Q7e2DPLOzi5Zqpz7ard61nC16TcCpmwUZRZaypjaedNCWSpl0DJrEc5btm6q81AW96bpusp3DmWzkC7u6eWL7ERpCPhrS9oCFxjgChyVNVXzzurVsOtDPj57fy+7uEQzT5levHeJ/tnXyF+9YyNWntY0p+zcQTRJLpiZs9z4QMxjIWd2wbUcvuz+aLJupLhVw94wkS2YPekcSrueE1houWUs3lo3vyWaAJBAIBCcSbv0829oH8xTOxtNn88Kubu56UmdP9wiRnCbI+qCXvmgSSYIqn4eYYXJoIE7I68m6W0NxjfVEr/+WDabtqK1l0lGmbRNLpirWs1RIpYLtU3Vd/3DmB13XH9c07eu6rr+uaVpJAVFN0/zp915SoWM46Sh8wnpqx9GS7xuIGcyrc4If07JpH4jhkRN5T39uJ0qprtyagErCsJCk9FOmJKEqMopkkzSd/8BRHPm7KzT+sKeXjoEYh/qjxI3ibOS01AGfxLy2v4/Htx9BkWxOaQ3TORhnMGYwFE/x/Wf38NDr7fzVhUu4eEVj2cx1ImVx15M6z7x5lKPDCWoC5TPR4Dh7SeTrdko4zo97u0ZK7nPPhoMlx5RlwCweS5Yk13Pi5d09JZtdxrLxFQgEAsH04abgcc+rB/Ik+zLcv+lwdr/cLPGFyxr5t2d2saNjME8muDnsoz+aJKDKSJLESCKVzTjHkikUWa5YjbUsgVpqPKO0X00lYpVKBdsDmqZ9EvgFIAM3An2app2S/rkUpwFBTdOeSh/HHbquv1qh45nxlHqKTJqW8xRWEF9lll9ihpnNJHrknKe/DvcO2zc7BosyiQBzav38/v9cwmV3PUvnYAJFgnjKzmatJeCb167hzIV1xJIWG/b25Y2Rm40UahHj57X9fdz94r70TxK2ZdNU5eX8pQ28sKubSNKkYyDOVx99k5Vzwnxq/VJX+/d7NhzkF68eAJxa6FjSLJuJhrT1ulR0ipFImfS7/LoGoqWNYwOqQrzAaMBOH4vbOTEQNVjaXCWUawQCgeAEwk3Bw7LtksH2jvZB9ucYPB3ojfIvT+n86Pk9bDwwkN3u98i01vjxKjLD8RRJ0yJlWVlDNDPdYG9VsMbar8ol5QItyy75/krcfyoVbN8IfAf4/wAT+B1wE3A9cLvLPlHgLuA/gOXA45qmabquF/t1zhJyM9ndw05mOjfokKS0K1/BfpmTMqMUIue8w7RsOgbiXPO9l0rWH8UNC8O0imqXMkHSqrYaYJCDfbFsoC1LcObCOtYtqqexysuuruGy2cj59cEJ1+HOVh7PWY7LIEvOE/wvPn4uP3/1AA+/0YFp2ezsHOYzv97Chcsa+auLFhd1X//3lnasdM10ImWhSE4T6y//WDoTDY71esKwirLRPlWhLqiWNCJodDGiCagKQ1LKWa5Lo0gSAa/H9ZyodbGiF8oiAoFAcPyIG2bJWEFVSq+uxg0zT1kqZVno3ZFsQo/0GPGURddQnKZqHzHDdHVDdKuxngyr2mqw7OL7T9IlU16J+09Fgm1d19txAutCvltmt13Abl3XbWCXpmm9wByg9PrySU5hJjtXFSQTcNf4VQZiJRz5As7rTkmBndfcaFgWqiQXKYlkAu6YYWaDaHAyjynLqV0CuHh5I0+9eTT7HlVxzGo+ePZ8Wqp9BL0eDvVFS5qKZJ4GV86p5pmdXdnt463DPdmoDqhEEs6TuxtHBoqdsAA6B2LUBFVuvWwZ7z9jLv/x0j6e39UNwEu7e3h5T0+R/Xt/zMDI+d2aNgzEU6Rsm1jSJOAtruU+a1E9L73dk7fNBtYtqqO12p/XM5DJLpy/tKHkMVu2E5TnVrpYONkIt3PiqrVzSlq/C2URgUAgOH64xQpuClKZ7TI2PRGDjoFYNpD2qzLxdFIn5FUwTJuDfTEn2VMi4JWl0jXWudnuifCBs+ZzoIRc4BWntubVn2eoxP2nIsG2pmmXA18H6slJvOq6vqTMbh8D1gB/nVYyqQY6K3E8M5HCGlavRyaZsuiPGtkTYn59kHAkSU8kSSLlWKsvaQrRH0myp2sERQLVq5BMWdlaJkWSCBTIwP3g2d3ZDPpgieBdwsl4bznYzzef0LNPe35VZt3Cet5/RhvvWduWlZcrpXM8HHeeGK/53kt0Dyeo9nuIp6xZXYdbF/JSF/ISS5oMxQwiyeJFnNbaAB39xQH3nNrR1oe5dQH+4b2reLNjiB8+727/7lbObZg2nYMxagMqdSFvXt13bcDJLheqkdQFvcQNk6BXIZIYrWsL+ZSSF0co3/G9s3Oo5GpIImVxxamt3PPqAQaiBrVpxRNR2y8QCATTj5saR8ylntm04LbLtSI1kPs2HuJAb4Q9PVFGEqP3uuawD8uysCwneZdpkJTS/98cduSDTctJHNaHvAzFDEyLolVVWZ5cZrucgtWauTXTomxVqTKS7wL/G9gOrqsAhdwN/JemaS+l9/nYbC4hKaxhrQuqHB1KFC1r/OO1a4qURBqqfDRU+egaitM1kkCVZfwemXjKxLRt/J7RE3I4brC7a4RlzVUAWem+wlpwWbK58T82ZCfCeUvq+dJ7VlHtV2mp9uPNGbNQ53I4bnB0KEFLtQ/LHs3SZ1RSMszWOtyAVyHgVTBMi+F4iuG4ke20fveprTk126NcsbqlaNuqtuqy9u9eWSZJ8QUy7HcekgZiBtGkmafLfagvyvy6IPPr8vc52Bfl6GCMaNLMC+KjSZPX9vWW/J6WbbtmI9xWQ3Z0OHV+mXMahHKNQCAQHAvKOQhbFiUTOJZtl1QDeW2f0+ifubdJErRU+fjsu5bz9Ud3AuQpkdhA0jBpbq6iOZzvKyEBg7FUUY11bmwzUdwUTKZL2apSwXaPruuPTmQHXdeTwJ9X6PNnPIXZ4UwQkjRtV5v0wmx4PGWhyjKZPKJHlrBs6BpJ0DWSwCM7mUZfTqZbVSQM09mDdD243yMRSY4G+Vee2srn3rWCoFehpdqPp0B2rlBH27ZtanICqVJZeoCAR+bWezdXXM9ypqAqMvUhRw97JJFiKGZw9qJ6AJ7YcZTOgRhzagNcsbolu72QcvbvAIrkXMQs22marQmorJk3GkknTYvOwTjVfg91QW9ZN0b9yJCjuZ77+TgXwVLZEFmSSnZ8y7LsWrOdNC0syy6ppzpZPVeBQCCYjUz0ennfxkN0DcfpiyRJWTaedGb5/k2Haazy0jWcKFqpbKjy5X3OvLoAIwkzW+YIzqr46fNruX7dPP50dStfeGg7dom0rI17lrzU/WL13NLiACcilQq2X9Q07V+AJ4CsBZCu6y9UaPyTnlIuSGG/ym2Xa66TozAbnkxZ6Sc/iWXNVRzuj2azypLk1FcZto0/p1a3yufJe48qy8Rysuk3nbeQj5y/kJDPQ3PYX9IKvFAzeXfXCEPxFAGvE1yXytIPxw2G40b2ybaSepYzDUmSslneuGFyqdbsGly7UWj//sCmwyRSVlZaKagqNFY5WuiFWXLbthmMGUQSJteeMZd/ffrtovFvWDePJ7Z1Fi1b2TgBe6lsiGVTsuPb75Fda7b9qky/YRRtl9sHy2ZdZts5IxAIBOWYzPVy4/7+tM+GQ8qy6RpOsHF/Hxcsa3R6dgpWKpc0hbLjpkyLp3d2ZUsLZQn+/NwF3HTeQsJ+lcawz/GIKFP/4JZZLlVjPZN6eSoVbJ+T/vOMnG02cFmFxj/pmYwLXmEWMpNBzpR45NZJZVRMJCCSs93JeErZp9jc5r3PvXM57z2tjbc6h3h8eycH+2LZp2PAVTmlMJNdKkvfNRQnmiwucZjt2tt+VcGvKtSbFkPxFNExGioLcbN/jxomB/tjnLGg1rWzOmVZLGoM8amLl/DUm0fZ35t/HiqKlNdwmcW2S+qvyjJUBzxF9Xer59a41mwfHYpTrLfjrNoIvXaBQCAYH2NdL0tlvQdiyZIZ54GoQdwwqQ04Ig2Zfp7agMrerhHqQ14GYwaH+0ebIH0emW9dt4bT5tdRH/RSk6M05Us3SBbiV0sbsJ0MLsGVUiO5tBLjzHYmWitUmA3PZJDr0id1yhydNaPygPnbkykLryIR8CoMx50gXALaav2897Q23j46zA+f35udQAd6o3z54e3AaKlLoXJKqUx2YZb+mu+9VPI7zdY67kI86RKT+pDTmDiSSDEST2GVuhKWwM3+/fWDA9z0n38sa/++ck41p82rzavlhtK62eCcU6X0VzMd5x5ZJlNaNxRLcUprmKd2HClZs905GKfE4klZbW5xzggEAkE+5a6Xbllvw6XZPWVavNkxRNyw8Oc4EscNi4SRcsog46NJvLDPQ2uNn3MWN9BY5cvr8QJ4z9q2PGWrDFetneP6fWa6S3Cl1EgW4uhlLwIuAu7FaXjcX4nxjzXTVRc61riFr6+cU83OziHX9xc+7a2ZV8u8aJJN+/s40BfNBsi5TQ2S5CiU9I4kGIgaSFhYtkQ0PVFkCepDXizT5u8e3Ep7f6xI7zsTXE8kk134FFquNni243ae1Ae9DCdSjMQNVwWQQnojSYI+D/Nr/fTHnIvieOzfM7XcuRmJgKowKBnkJrczgbGZ1vPOrc2OGRZ+VS5SNnnryLDr778h5MW0bPqiOTWDQS+r22qwbdv1nBG13AKBQDBKuXusmxtkpha7sC/Ho8jEDZN4gQ62V5Gdni9jNND2eWRqAx5WtVWzu2uEf/qfnUXX5btuOA2Ax7Z2kkiZ+DwKV62dk91+MlKpMpIfAXcC3wKOAr8Efgasr9D4x4zpqgsda9zC17e3D/LMzq6sgofbceQ+7X3/2d1ph0AJv0fJSvVkAh3nB0CChiofdUGVt7tHshlopxlCJZo0aagNEDesknrfhQop48lkF1KqRh1mVg3WdDDWeVITUKkJOLXdI3EneHbLdue6UQa8HvyqwnBcIZay8uzff7O5nU9ctJiLVzTlyQDatk1vJEHcMGmo8mLZ6caYnIc3G5Bsss6lMKq/LVmO8yQ5+wzGDDbu7+Nb160t+fs/f1kjj23tzM+Gx51s+Jq5NSX3OaU1LGq5BQKBIIdy99ivPLKj5GqkJEnY2EWFfLVBle6RRF6grSr5ZadSeptflRlOpFAVuex1+a4bTjupg+tCJq+bkk+jrutPAei6buu6/u84utkzjnJ1TpUedzhucPtvtnLN917i9ge3MhwfDWwzQW5usDvWcdyTtubOoORERRJOMO31yIR8HgzTZFfXCMnUqP26LDu1vXUBFW96qSiz/JN7HF6PjCQ5y1G7u0bojxr4PDJgs6drhN6RBFec2lo20Fm/oonbLtdY1BhCliUWNYbKBuezhbHOvxd2dXPrvZv5sx+9wlf+ewcHeiM0hHx4leKpXOhGKUkS1QGV0+bX8omLFqd/Z07pxlcf3clf/tdrbDs8WDROJJnicH+MoFfBK0tZh1IZR22EtOpI4XbbxlEvyfkP26n/W7+iiStObaV3JJF3zsQNk5bq0WVHr0empdrHW0eGXc+ZnZ1DZf/NBAKBYLaRvcZGEuzuHqE3MnpfjhsmpmWnPTlMkinHGVJVZEJeT941O+T1cNaieox0+anHueRnfwao8ilU+RTCfhVZkqgNenl5T0/J45qt1+VKZbZjmqbNI736oGnahUCi/C4nJtNVF1o4bkaLGqAh5CvKIGeyxIVZ5HLHURiYK7LkZBiB1W2ORM7urhGq/Qpvd0Xy9C9VWUJrruZAX4SeiIGiyK71136PTCxpYtvOtljSxLAsmqt8NFc7+pjj0Uae6TVY08FE6+zuempX9iElU9sdSaQwLdvVjbJrKM5Va1qZVxugN5LMupIe6ovxmV9v4YJlDXzioiV5JT2WbZM0HSUbRXJKRDLYtl1SdaRE/6vjOmZaowo2BXrakYRRspY7c96XOmf++ani7E3uPgKBQDDbKFQJg9H7smXbJVcjfbJMpMBLIZJMZRMzqly6SX5xQxWqR8oLwHd3j2Q/N5fZel2uVGb7c8CjwHJN07bg1Gx/pkJjH1Pmu9QMT7WWuHDcTGCcm8Ert308x1EXzA9QFNnJMPo8SjYTuLghyOH++GigDShAbcCLIjvZT9OyaR+IZbPW1X4PdSFvdoxFjSHaakeNbWxsVFnOulZmmK1PsFOh3Pk3Vtbbryo0VvlY2BBiTk2Apc3OBbCQObUBHt9+BEV23LoW1Qep8o0+d/9hdy8f+6/X+PbTb9MXSWa3L2uuosrnIWnaBFWZkE+hpdpHU7XP6S5PmcQMk3jKxKfKKC4Olh5Fdv0upRowM9/fjemaswKBQDBTKXe/kCXJqc3OyWBLOMm9UquUL73dg+ISaFf5PMhyfqYbiuORDLP1ulyRYFvX9Y3A2cB5wE3AMl3XX63E2MeajKxdIVOtJS4cN5MpzpyQmT/dto/nOG48b2HRNkWWuPWyZTx8ywWcvaiOnUeGs3VXGcMTn6qgSGDajuqDYVmk0pMqmXIk6G48dwEP33IB3/3QGcQNk7BfZUF9kGXNVXhkGUWWJpSFF5Sm3Pk3kVWXgFfhz85egEeWqfJ78lRFrljdkpf19npk2mr8zK8LEEi/L2P//hd3/5Gfv3qAuGHy7lNbCXk9tNX4aajy0RR2MiZLm6oYjI1qtYNTm62my40K/6sJeFy/i5v0U7nzfrrmrEAgEMxUyt0vYoZJYdxs2WS9EbweGb9HweuRUWQ4OjyaoMugyhIhr0JDyFs0FsCN5xbHIzB7r8uVKiNB13UD2JH5WdO0IV3XZ1zd9nTpORaOWxdS8SqjKh9hv0osaTIYT7G7e4S6oMqSphB7ukc40BfF55F5z9q2ouMoVGG4au0cXt7Ty0A0SW3Qy43nLuCvL1nKnU/ofP+53dn9nBpfm7DXkXOLpgPluJHrQkm2S/mtI8PZfcfS984wW59gp0K58+++jYcmpOCSO9ahviir2qq59JRm1syt4fHtR+jozy8zCagK5y6pZ0FdgPs3tRMzzDz794+dARX4WwAAIABJREFUv4iPXriIp97sonMgRmuN4275/57dg9/jyPzlOotJQNCrEEmM1pOEfApnL25wVRZZPbeGG9bNm9D8Oxk0WAUCgaCSuLn0rplX67gBj4Ft29g2JHKaIDOO0yGvgmHaNFb5eP5vL+WFXd0lr79r5taI63KaigXbJXBZRD7xma5a4txxC+tvh+OOOkRrWn2kayjOm51DqLKc1bV8bGsnixtD3HLpspJjZIKXb167Jvs5pmVz2wNbeSCnpKM17KM6oBL2e+iNJPNqsjMulC3V/ry62dzs6Vj63hlm6xPsVHE7/yaj4FJqrLhhcsO6eXz3mbeLMhJLm6p4cVc382r9DMZS9EaSmLZN70iSO5/axeLGEDevX8w5i+qzyiV/P+jorge9CrGUiW07zmJWqli9JJo08Xlkrj6tzfW7TGb+ifp/gUAgGMXNpfeG1jD/s62z5D6j12obIy3nmuESrYmjgzGCXjVPheSFXd2u119xXR5lOoPt8blvzFIKs3FJ06I64FinHx1KEE8HLYZpYVhktYv/86V9We3tQufGDBmHqFgyxad/sZnndnUDTonIipYwyZRJyOc0YRZqYtcF1ZJj5mZPS+l739Aa5q0jw+IJdhqpVAbXrypctbaNoFfhgc3t7OkaYU6tk6V+fPsRIskUg7EUhunoZMsSRJLOsuO+nghf+M12gl6FlXPCfOCs+UgSJFM2hmlmy1DiKTPrTmpadl7G++U9vVnJJ5H1EAgEgvExET8BN5fet44MY7vIxUo2XLCsgWd2dmUDuKBX4WvXrOaZnV34VaXI0Vg4+I6PKQXbmqYtcHkp4wwuKEPuU99ldz1H52A8+1pmLmSCFAsby7TpjSSzGexSGtjgZKH7Iwk+8pPX2JqWcqsLqnzj2jWMJFL8csNBV03swmx5hsLsqXhiPT5U8t/90lNauPSUFuKGyXDMYCRp8t3f76ZnZLQpMlO731ztZ15tgI0HHCfKaNJk04EBdh0dwavIJNN62jHDRJYgqCqkLNu5MEujFwMnS56o+HcRCASCk5mJeoAc6ou6Kzu5pEIlCZ7OyYZftLyRz/+pxqKGED9/5QBmif1Eb9b4mGpm+3lG48FCSossFqBpWjOwCXiXrutvTfF4ZhTff3Y397x6gP6oQSJlIktSkZNfLpl/6IN9UZIpi5RlISFlnRvBKUdJpEze8Y3fZ9VBAqpCXUDlwU2H+dA5C/jMO1e4ZhRF/evxp1z2YqJOiRMZ64az5qHKEgF11BApg2XZVPk9NIe99I4YmOmnweG086hflTFSFqbtuEr6VZmhWIqg6tT25cpMyZJ4DhcIBIKJ4Ob66JZZLlezve3wQFHALUE2mPZ7ZG69bBnvO72N5uoAXo/MPOH6PCWmFGzrur54rPdomnazrus/dnlNxXGfLC0IfBIz6vbo4HQC24A1ZsCdyUpLSE4Qk05EDscNuocTxNMC9c57HPWHkE+ldyTJvz79NrddrvHdD53h+hki43j8KJe9ACaU2ZjoWHc9uYuYYZJIWYS8TjlI1HDKmbwemd1dIwzGUngUCdlyst6Z63XcsJAlaKryUhtQkSSnkWYonsKryATTAbyNcz4KBAKBYPy82TFU0vVRbi82IoPyNduPbh19nyw58UfmWr68uYovXrWStfNqqQuq2d4c4fo8NY7FXe9TQMlgG7gL+CHwhWNwHNPKRDOOpdweTdsmZdmYtiMqL0FerauZI8dnYTt13JJTyy3LEnEjlQ2OSO+jSGBZoChkNTJFjdWJSzltVLc6O7ffZ7lMiNtYsiTh88j0xwxs21kVqQl6WN4SZsfhgdH3yRKqNPqQmJGN6h5JMpxIce2Zc2nvj7G9fZDBmEEkCVU+mYaQj9MW1E3iX0YgEAhmL3GjhEsYEE9ZJeOPnZ1DVPs99EWTpCwbjyxRH/Sma7adfSUoapK/+aLFPLS5nX/93a68WEasek+NYxFsl1wz1jTtL4FuXdef1DRtRgfbE62lgmK3RykTWQN+j4JpOUvvzWEfzWHHlXFn5xApy0aSnDdaOI+jTUGVm96xkM/f90b26bTa73H0sH0eoskUuT0NosbqxKWslrZLgOz2+yyXCQn7S0/9mGEyGB/VzI6nTOLDJhdXeQkHPAymy0ac152HuZYqH1eumcO9Gw4SSZrEDYt7Nxxifn2AoOopchG7bEUzI4lUnpGOQCCYPLKozDrp8aulV7wt2yoZf3QPJxiKp/DIMhlV3qF4iu05SZPCO0qVz8MvNhzMBuCFsYxY9Z48x+Ju56ZK8jHA1jTtncDpwM80Tbta1/Ujx+CYKkq5bKTbiVkXVOkZSWJadjZohlHpnYBXoc6josgysiyxoD5Ie3+UkYSZ3SejUGKYVl6gXR9UaQh5GU6mGI6l8ChC/3qmUKhhnmFBfdBVm3pBfbBkZqNcJmSVy+fEDRNVlovOsZd297JuQQ2KLNM7kmQkkUJVZGoCHla0VvOhcxZw5alz+PmrB3j4jQ5My+ZQn1Md1ljlJexXWdQY4orVLaydX0PXUJxBj0xN0CuCboFgirTVBrjp7g0c6p94Reb8ugA/+/i503BUgkqyqq0Gyy6uwU6aVskVzIFYEqkg12nbNkeG4kVjq2kjm1gyVdKgRqyGT53jdpfTdX195u+apj0HfGomBtowRjbShfOXNfLg5lHt68z5XeNX8+ynZVni4VsuAOCyu54lZjg62M5OFrZEVj1CIl0zG/QS9nswLJtBOyX0r2cQY9XFlXrtlNZwycyG5ZIJ96uy6+eYVrr8qCBVNhBNcsNZC7jzSZ25tX5URcEwLeKGyRWrWwCoCarcetky3n/GXP7jpX08n5ac7BlJ0hdJsmZuDUubqrJjJlIWXUNxBhTH5TLsV4s+VyAQjI9D/TH29USO92EIpokPnDWfA73RInWR7uE4RyPFK5imaeNRRq+npmVjmFZR9jOoyqQspz+nNlDaYl2shk8dkVKqAOWykW7EDZMav8pg3MhWB8hS8TJA7hi5T7amaZJCIm449SGqIvHFK1cS8Cq8sreXfT1C/3omMp66uMLX3GqzZUkqqbO6uq3G9XNuf3BrUYkTQG3QW7TPosYQ7zu9jVPmVOdl0efWBfiH967izY4hfvTCHra1D2Xt33/35lE+ePZ8rj9rXlaTO2la9EWSjqqOz0N1QC1yIxUIBILZzPoVTWxrH+SeDY6CWV1Q5cZzFxb1f2VQFJmWah99kSTRpJmVcQVY1lzF3JoA29sH6I8Z+DwKV58+j7hhCsWRaeJYBNsDY71B1/VLjsFxTBuT6dJ9s2OQRMrKukNmarRjyfyl/9wxMk+21X4Pe3uixJNO/WxAlfnGtWs4bX4djVVe/uxsN/lzwUygXF1cqde+8sj2krXZNQFPSZ3VzDlVaqwbz1uYp5KT3X7ugrLHNpJIMRBJ5hkerGqr5tt/djp/2N3Lj1/cy+H+mGP//vJ+HtnawUfPX8Tlq1uz2WzbthmKGwzFDcJ+J+j2peeHQCAQzGZe2NXNE9uP0BDyZftgnth+xHUFszbgQVVkDNPKC7TXL2/k6+87lTm1gSLls/H6bAgmzlRNbb5c7nVd17+q6/plU/mMmcBkunQzGekMiixh2RKmZbGna4TaoMqN5y3MG2P9iiZ6RxL8wyM7GEk4gXZNQOVfPnAaS5uqaK72EfSKxYrZRuG5lEGWZW67XJvQeXnLpcsAuGfDQQaiSWqDXm48d0F2uxubD/Rz/6ZDHBmI0xD2cqnWzNlpS/cLlzdy3pJ6HtvWyU9fPsBAzKB3JMldT+3iwc3tRfbv4Oh3D8dTBL0KNQEvAa8IugUCwezFrTes1ApmbcBDTdDLW53D2QSI1yPzkfMWcutly6kJqmUV1ITiSOWZamQmCizTTLRL168qwOhyvWnZmLaNqsgsbXbqWp/YfoQ1c0eX/N/sGOTOJ3WG0ooQixqCfPPaNcypDdBS7U+PKZhtFJ5L2e0eeVLd47dcumzM4DqXwmxIR3+c+zYeRpElzkzL/HkUmWtOn8s7V7bw642HuH/jYRIpK2v/fuaCWj65fgnLW8J5Y0eTJtFkDL+qUB1QCXmVvKBcIBAIZgNuvWF+VSHk82RXMFOmRftAjAN9o82yFyxt4I4rT2F5SzVejzymgpoIrivPVE1t/m+p7ZqmScCYhjezmVVt1Vi2nX0atbFRZTlbx5oh0wX88u4e/vqezQzEnKBqzdwavv6+1dQFfbTW+EWN6yym8FzK1mbPrTkmn1+YcckYL734dg8XL29iODEqFxjyefjYBYt579o2/uvl/Tyx/Qg2sPngAJ/6xWbeuaqFj12wiJZqf96YccPMKqU4zZSeIpUdgUAgOFlx6w1bPbeGG9bN4/5Nh9nRMUjHQCy72unzyHz6kqX8xXkLqQ95s4mKySioCaZGRWoONE27GcegJpSzeR8w/vTYCc5ETWvGorCzeHfXCECecshw3OAPb3fzzn95jr3dkawkz/rljdxx5UqqfB5aa/wi6JghXPO9lypy7hTi1qU+Vp1dpc5pt4zL/t4oTdV+woZJ70iCRGq03KUp7OO2yzWuO3MuP35hL3/c348N/O7Nozynd3HdmfP483MWUFWgB25YFv3RJAMxgyqvQjigihUdgUBw0vOBs+Zz2wNv0BfJMakJebntco3zljTw8p5eHt3akRVcWNZUxVeuXsVZi+qLrpGTUVATTI1KFfh+ATgN+DrwReBK4IIKjX3cmYxpzVgU1kbVBR0FhkzANBw36BlOIMsSu7tG5ZzesaSeL71nFSGfh5Zqv5BKm0FYdmXOnUImU2dXyXN6LDUev6owty5INJmiP5LMC7qXNFXxzevWsnF/Hz9+YR+7u0cwTJtfvXaI/9nWyYfPW8g1p7cVNfLYts1wIsVwIiVKTAQCwUnPtvZB+iMGVvryaVnQHzF4flc3dz75Ftvah7LvvWHdPD73zhW01viRS8QIk1FQE0yNSgXbXbqu79M0bRuwRtf1H2ia9tcVGvu4M11LLrm1UYXBz1AsiWHZJHLUSRpCXnyqQrVfpSnsKzmJBDODSi/XTbTOrpLn9HjVeIJeD0Gvh5FEir6RJClrNOg+a1E9Zy6s4+mdXfznS/voSruf/eC5PTz0ejufuGgxF69oKhlM55aYhANCr1sgEJx83PPqgTwPBNt2+rz+86V9o4Z2IS93XHkK7z51DqEyZmGTUVATTI1KBdsRTdMuBbYC79M07TUgUKGxjzvHYsklNzvZMRAlkrTyMoAtYR81AZXheIrmap/I4M1wjvdyXSXP6Ylm1qt8HoKqwkC6HCSDLEn86aoWLlnRxG82H+aePx4kkjDpHIzz1Ud3snLOYT65fglr59WWHNewRvW6RYmJQCA4mcj1P7Btm6Rp5bk9vmNJA//w3lUsbwmPmWwQqiPHnkoF2/8L+Cvg/wAfB94CvlKhsY85hbWsflXh6FC8qAFtjctNf7KsX9HEmrnVfOZXW7KBtgS01fjT3cYe5tYGRKB9EjDZ5Tq3OuuJ1l9Xehlxopl1WZaor/IR9HmK6rm9HpkPnrOAd586h59vOMAjWzpIWTY7O4f57K/f4IKlDXxi/RLXY80tMfF5ZMIBlSqvR6wECQSCGUtdUKVrOJGnmZ3hs+9czl+ev4jaoHfc4wnVkWNLpYLtNl3XP5f++3UAmqZdW6Gxjymlalm70oF25mkxYxpyQ2vYbZhJcagvyi33bmbr4UEAFElibq2fgKpQFfCQTNlcL5Z5Tgoms1znVme9rX2QJ7YfKdoO7vXXJ8oyol9VaKsNMBRL0R9N5hk01ARVbr00bf/+4qj9+x/29PLK3l7es7aNj5y/kLoyN5hEyiIxnKBXSlLlUwj7RbZbIBDMPBY1hegYjBdtP31BDZ++ZKkwADvBmaqpzZ8BPuCrBQY3HuAO4DdTGf94UKqWNZ6yUBUJjyLnZbbfOjJcsc/d2THIX9/7Ovt6nGbIOTV+PnzeAjYdHGA4lqK1xi+WeWY4sixNabnOrc76nlcP0FDlK9perv76RFpGlCSJmqBKld9DXyTBcDyV9/rc2lH79x8+v4ftHQX27+fM54Z188oG0bZtZ41yfB6ZKr/TUCmUfAQCwYnOvp4Ir+3rK9pe7VPoGUqKQHsGMNXMdhhHdSQMXJqzPYWjSjLjKFXLmkwvcRcuW1ei7ta2bV7d28vf/HIL3SOO5fby5iq+ce0aGqp8/OX5i8s2OghmDg/fMjWBHrc664GoUTLYHuv8PNGWERVZoinsJ+w36YskiRtm3uur2qr5zgdP56Xdvfx7rv37H/bzyBvF9u9uJFIWiZEEvUDI69jCC4dKgUBwomHbNvdvPMxX/nsHhjm66hdQHU+OmGHRF00exyMUjJepmtr8B/Afmqb9ia7rz1TomI4rpWpZ3QxjpiqTkzItfvfmUW57YGvWfv2shXV85epVVPlUWqr9IggQZHGrs64NqiXePXNlnLKlJXGD/kgSM6dGUZIkLlreyDvK2L9/4qLFnLu4fly9DZFkikjSkQ8M+z1U+TyiJ0IgEBx3BqMGdzy0jce2dWa3yRLU+D2kLJtY2rhmInXaguNHpVKmezRN+x2wCLgIuBf4mK7r+9120DRNAf4d0AAT+Kiu63sqdDyTplQta51LMDOV+tZEyuT+1w7zfx8dfWJ916oWPv+nK/CrirBfFxThVmd943kL82q2M8x0Gadqv0rI66FvJJHnQgnl7d/veGg7Zyyo5VMl7N/dyMgH9kWSVPtV4VApEAiOG6/u7eV//3pLtkbb65E5e2EdOzsGiaXyGyRvPHfB8ThEwQSpVLD9Q+BO4FvAUeCXwM+A9WX2eS+ArusXaJp2CfAvwDUVOp5J41bLWrjtlNYw9208xD8/pU/YfS+aTPHj5/fynWfezupjfvDs+XziosV4PU6gLezXBYWUq7NeM7em5PZKO58eaxRZoqnaTyjpaHMnTSvvdTf799cPDvDJX2zmnSub+fiFi4vs390wLTvrUBnyKoR8HoLCLEcgEBwDDNPi20/v4gfP7ck6QS5uDPG1a1Zz3pIGfvTCXu7ZcJCBaJLaoJcbz13ALZcum/HX+dmAZNvFMjITRdO0jbqun6Vp2uu6rp+R3rZF1/XTx9jPo+t6StO0jwAX6Lp+8wQ+duoHPkkKVSEy3Ha5NuYJPhBNcueTOvdsOAg40n63XLqMa8+ci88j01It7NdPICodYR3Tc3Yq5+mJiGXZ9EWSDMUN1/fs7R7J2r9nUBXJ1f59PCiyRJXPQ8jnmQmrTRU7Zy+96zk707A9URY3hnj285dU6lBmDJfe9RyT+Te7aHkjh/tjk9p3qvufAL+rSl5nj1tcMFUO9Eb4m19t4Y1DA9lt1545l7+7QqOl2t225GS7zs8AJnW+Viqqi2maNo/0ia5p2oVAYqyd0oH2T4HvAg9U6FimnXLue+U4Mhjj9ge3ZQNtVZH40ntWce2Zc/GrCq01ARFoCyrGZM/TExVZlmgM+5hTE8DrMk8y9u93Xr+WZU1VAFn79w/fvYEHNh3GKMiOj4Vp2QzGDDoGYhzqjdIzkihq3hQIBILJ4DRBHuLK77yYDbTrgip3Xr+Wb1y7pmygDSffdf5kpVKR3eeAR4HlmqZtwanZ/pvx7Kjr+keAFcC/a5oWqtDxTCsTdd+zLJv93c5T6xM7nNrakE/hW9et5RKtiYCq0FrtFxbTgopyLJxPjwcBr9NAWe0v3UsBsG5hHT/8izO5/QqN5rCj1JKxf//Ln7zGc3oXk1nVMyyLoXTgfbgvykA0SWqCwftsQFzKBIKxGYwZ/K9fvs5tD2wlknQe4M9ZXM99N5/H9evmjUvS72S9zp9sTFVnuw24C1gNvIbjJDkIvKXrelk9Gk3T/gKYp+v6N4AoYOE0Sp7wTMR9L2VavHVkiM/fvzWry91Q5eVb165hSVMVQa9Cc9gv3O0EFafSLpEnEpksd9Cn0DOcJGUVB7yyJPGnq1u5eEUTD73eXmT/fkrrYT51sbv9+1gkTccevi+SJOT1EPJ7CIn6bgDaagPcdPcGDvXHJrzv/LoAP/v4udNwVALBicMf9/XxuV9voX3AmSOqIvHXlyzjk+uXEJyA3O/JfJ0/mZhqg+RPgG3APcD1OAokHx3nvr8BfqJp2guACnxW1/Vie6QTkPG678UNky0HB/j8A29wOH3TWVgf5JvXraGl2k/I66G52iduzoJp4URxiZxOgl4P8+oU+qNJhuKpktlqn6o49u9r5vDzV0ft3986Mj779/GQkRCUJYmQz0PYPyPqu6eVQ1OoQRYITlYM0+Lfnnmb7z+7m4yq6aKGIP/0/jWcu6Rhwivcs+E6fzIw1WB7rq7rlwNomvYUsGW8O+q6HgE+MMXPPy6Mx30vkkjx0u4ebn9wK/1Rp6FrdVs1//i+U6kOONJijVUi0BZMHyeSS+R0IssSDVU+wn6V/kiSSDJV8n01gbHt3296x0LqQ5PXrbVsm+G4wXDcwOeRCQdUwkK7WyAQ4DRBfuZXW9iS0wT5/jPmcseVp9AUHp9iUiGz5To/05lqsJ0tFdF13dA0bdZYGZVz3xuIJnlqxxH+4ZE3iaUbqS5Y1sDfX7kSn6pQ7VdpDBc7/gkEleZEc4mcTrwemZYaP1EXmcAMGfv3nZ2O/fu29mL79+vXzSMwxcx0ImWRGE7QH0kS8jmGObM92y0QzEZs2+ah19v50m+3Z2uzawMqf3/VSq45Yy7qFIURZtN1fqZSaR/wGSu7Uwls26ZnOMFDW9r51hN61vnuvWvn8Dd/shxFlqgNqNSXsNYWCASVIej14K9V6I0kGI6XznIDrJxTzbf/7HT+sLuXHxfav2/p4KMXjM/+fSxMy2YoZjAUM/AqMlVpp0qhPCQQnPwMxQ3+/qHtPPJGR3bb2Yvq+Ma1a1jWPD7TLcHMZ6rB9mpN0/bm/Dw3/bME2LquL5ni+DMG07I5Mhjjp68c4McvjP6TfPT8RXz4vAVIkkRt0DulJWqBQDA+ZFmiKezHrzpW7paL8ogkSVy4vJHzCu3fI479+wObDnPz+iXjtn8fi1JNlUFVEQ3SAsFJyMb9fXzmV/lNkJ++eCmfunjphJogBTOfqf62V1TkKGY4hmnRORDj28+8zW82twOO9NXn3rmCq9bOAaA+5KU2KAJtgeBYEvar+FWF7uHy2tgZ+/d3rWrhV6+N2r/v741m7d8/uX4JK8Zp/z4eMk2VkiRR5VUICrdKgeCkIGVa/Nvvd/O937+dbYJc2BDkG+8/lfOWNIqH61nIlIJtXdcPVOpAZiqxpMnh/ij/+NhOnks3XPk8Ml9+zyresbQBgMawr6wmsEAgmD5URWZOjZ/+qMFAtHxbSdA7av/+05f383iO/fun0vbvH7twMa3jtH8fD7ZtM5xIMZwQaiYCwUznUF+Uz/56C5sOjLrYvu/0Nr541cpJN0EKZj5iHWMKDEYNDvRF+PLD29lyaBCAar+Hf3r/Gla1VSNJEk1hH1ViuUggOK5IkkR9yEvQq9A7kiCRKm9E0xT28fnLNa49c26e/fvTO7t4flc3154xlxvPXTgp+/dy5KqZeBWZsF+lyu8RhleCaUOcWpXjodcP86Xf7mAk4fSK1ARUvnjlSt5/5tSbIAUzGxEFTgLbtukdSbK3Z4Tbf7ONvd2OlmxrtZ9vXreGBfVBZEmipdpPwCuyUwLBiYJfVZhbF2QwZtAXSY7pIpmxf990oJ8fvbCX3V0jGKbNrzce5vHtR/jweQu55vS2abmRJk2L3kiCvmiSKq9ClV8V1xNBxREGRFNnKG7wpd9u5+Eto02Q6xbW8Y33r2FFq2iCFIhge8JYlk3XcJy3Oof52we30jWcAGBZcxXfvHYN9SEviuwE2mIZWCA4MakJqARUhZ6R8rXcGdYtrOOHHz6Tp3d28Z8v7aNrOJG1f3/o9Xb+6sLFXKI1TUu9dW6ZSUbNJOxXRbZbUDGEAdHk2XTAaYLMGNepisTNFy3hlkuXiSZIQRZxJkwAw7Q4Ohhn88F+/v632xlKy4qtW1DLV65eTcjnwSPLtNT48HlEoC0QnMh4PeOv5Ya0/fuqFi5e3shvXm/n3hz79689tpP7N03N/n08ZNRM+qOGyHYLBMeRlGnxvWd382/PjDZBLqgP8k/vP5V3LG0UD8OCPESwPU7ihsnRoTgv7Orma4/tJJmu+bzslGb+7goNVZHxKo6phqjNEghmBplabr8q0z2cyGrjl8OnKnzonAVcuWYOv3j1AA9Pg/37WJTKdgvtboHg2FCqCfKa09q446qVtFSweVpw8iCC7XEQSaToGk7w32+08+2nR59ib1g3j09evARZkvAqMq01fnGzEwhmIEGvh7m1Mj0jCaLJsctKwClFueXSZbzvjLnc/eK+rBpRJe3fx0Oudvcf9/c1fPDsBb3T+oECwSzm4S3tfPGh7dkmyGq/hzuuXMm1Z87D6xH3f0FpRLA9BoMxg57hOD995QA/e2VU6fDTlyzlhnXzAEfqr7UmIJaNBIIZjEdx5vFgzKA/4m6EU8jc2gBffu8qbnCzfz97PtefNXX79/HQHzHERUggmAaG4wZffngHD73ent22bkEt//j+NWitYaGPLyiLCLbL0BdJ0juS4NtPv81j2zoB8MgSt7/7FC47pRmAgKrQUu0XIvUCwUlCTUAl5FXoHUkSSbrbvRfiav/+8n4e2drBR8+vjP27QCA4tmw60M9nf/V6VrHFI0vcvH4Jn754KeGA8NAQjM1xC7Y1TVOB/wQWAT7g67quP3K8jicX27bpGUnQPZzga4/u5JW9zqps0Kvw1atXc+bCOgBCXg/N1T7xRCsQnGR40v0Xg1GDvujYEoEZ8u3fj/CzV/bTH3Us46fD/l0gEEwfpmXz/Wd3851n3s72cyyoD/LVq1dz4fJGUTYqGDfHM7P9YaBX1/W/0DStAXgdOO7BtmnZdA/H6RyI88XfbuPNzmHAsVu9fFddAAAgAElEQVT/5rVrWNZcBUDY56ExLAJtgeBkpiao4lNleoYTJM3yRji5OPbvbbxrVfMxs38XCASV43C/0wS5cf9oE+R7187hC1eupK02cByPTDATOZ7B9v3AAzk/j3+9tsK8sKub+zYeonMgRmPYy+nz67h3w8HsktH8ugDfum4trTVOl3HY72Fn5zD3Pfomh/qizK8P8oGz5rN+RdPx+goCwawmM4enYz76VYW22gBP7TjCr9PXidbaAO8+tZWzF9WX3TfX/v2/Xt7PE8fA/l0gEIwy0WvDC7u6+dend7H10ABmekGr2u/hby8/hevPmif8MwST4rgF27qujwBomhbGCbr//ngcxwu7urnzSR2vIhEzTHZ2DPP0zu7sktGqOWH+8f1rqEnXZdUEVHZ0DHHnk3p2jAO90ezPIuAWCI4tmTmcYTrm40u7e/j+c3vwKhIeRaajP8bdL+4DGDPgBsf+/bbLNa47cy4/fnEff9zXB0y//btAMJuZ6LXhye1HuP3BrfTHjOy2oKrwt5efwofOXSD6LQST5rgWHGmaNh94Fvi5ruv3Ho9juG/jIbwemUgixVDM4PBALBton7eknrtuOC0baNcFvTRU+bhv46GSY92/6fAxO26BQOBwLOZj5jOSpo1HlgilneGe2HF0QuMsaXKcZu+6fm22JC1j//7huzfwwKbDGBMoVxEIBO5M5Nrw+sF+PnfflrxAuyns5ZQ5Yf64v08E2oIpcTwbJFuAp4BbdV1/5ngcg23bdA7GGI6lGIobHBlKZF+rCah87ZpTsxOsPuSlNujo5R7qi5Yc76DLdoFAMH0ci/mY+xmmDdg2Yb9Kz0h8UuOdmbZ/f2ZnF3eXsH//xEWLuXjF9Ni/C8pz090bsiWEE+HsdOO84MRhPNcG07L5f8/t5l9/9zZmuhFaVSQW1oWoDnowTJsD4t4umCLHc83yDqAO+JKmaV9Kb3u3rusTv8pNgkwjZNivcrA3SvfIqF1zfVBl7fzabKDdUOXLZrcB5tcH2d4+SH/UIJmy8Hpk6oIqa8awaf7+s7u559UD9EcN6oIqN563kFsuXeb6/umsQxUIZiKl5sRk5+NEcPuM0+fXUuXz8KzexePbj3BkAvXcsiTxrlUtXLyiiQc3H86zf//qozs5pXX67d8FxRzqj7GvJzLh/ebViaa5E41y14YXdnXz05f3s2FfLyOJUSOroFehyq9wZChGdyT/WiLuyYLJcjxrtj8DfOZ4fHYyZdE1FCeeMp2gOyfQbg77qA2ovPvUVsCptQz783U0V86p5pmdXXnjHR1KcEOru7LA95/dzfd+vzv7c3/UyP5cKuA+FnWoAsFMwm1OaK1hjuasSo1nPk4Utzm/vCXMW0eGue+1w8SMFJbNhOu5vR7ZsX8/dQ6/2FBs/37+0gZuvmgJCxqmz/5dIDgZcZu3Z3lkvvjQNjoG4tlstizB6fNrOdATYTjmBN9mzrVE3JMFU2HWdeNEkyn+Z1snj7zRwZaDAwzF80VQBmJJzlhQyzmLG2gK+6hK12Z+/v43eHRrB4mUhQSoioxl26Qsp4azPujlrSPDrp97z6sHSm/fcLBksF2u1kxMbMFMoVwmyO01t+1uc+Ll3T34PDKDcQPbBkmCGr/KW0eGK5aJ2tk5RLXfQ180WTTnd3YOkTQtfB4Zrwei6SzZEzuOjivYzlATLG3//vKeXl7d28tVa+fwkXcsmnb7d4HgZGFn5xAp08KwRnXyPRI8vq2TSHI0mx1QFRY2BOkbSeBRZFKJVMl5XopM/bfIeAvKMauC7cGYwZPbO/nR83vpHIwTNUYnmyKRFah/8e0e1szt4NbLlgNOoP3g5tGGCsuGRMpCkST8HkcGaCieYkfHoOtn90eNktsHosmS20VduGCmUy4TBJR8bVv7IE9sP1JyH7c50T2cIJXOTmVKnAfjBi+93c3+nHKAqWSi3uwYZCiewiPLeNJt5Zk5H04/kKcskICwXyVqpOgcmFxFnJv9+3+/0cnTb3YdU/t3gWAm8/TOo3mBNjg9F7mBdmPIy4L6ACnLZt9gAlmWys7zQnZ0DFbsOiM4eZkV9ke2bdM7kqB3JMFDW9o5PBDLC7Sd9zh/emQJnyJz7x9Hs2iPbu0oOa5Z4CoXN9xVBOqCpS1dM02XhcyvL71kvMBlu0BwolFudcbtNbcVoPs3HXadE5aLu+NQrLR0/2RUStzmdtyw8o7LBpKmRcCjsLgpNOHPySVj//7Vq1czP10PnLF/v+nuP/LY1s6scpJAICgmd95mxEQyM0ZVJBY3BFnYEMKwwEZCcomICud5/mtmye1CnUyQy0mf2bYsm8e2dfLg5sMc6ImwvzeanWxej0wy5UxGC2fyqbKzHN0fM1j8hcfweWTihlM6Uuq2FktPNEmCo0NxVn7pCeqCKucvayRumNllpfOXNfLb19sxLRsbJwOmyBI3nrug5HF/4Kz5fPnh7UWNHTesm1fhfyGBYHoouzpj2+ztGSGS05gU8inYltOQXGqf//OuFXnZ8AyyJJUMOi1shuNG0Rwaa3Uot2TM55F5z9o2/KqCaSUxLRsLGxkJRZbwe2Q+cNb8ouMyLJsPnjWf2oDKQKz0qtZr+/vGbKp0tX+PJPnn3+3iwc2O/bssOWUrr+3vf+rTlyw9s+wXFAhOUhbd/hiyBOcva+QXHz83u12WnBXpXObX+RmKpzgylMheG2oDXrqG43nvlSVc5zmQXd0uRKxCC3I5qYNtw7R49I0O/t9ze4gZJu0DsbxAe35tgAN9EVIW+BUZRZIYjBt5Ey2RDsbHyh/ZdjrTrUDPSJIHNx+mOeyjOeznQG80PYFFFkowe5hfH+RAb/ENZ0F9kFf39OQF2gCRhIlXKS11t6A+mF2SvX/TYQ72RVlQH+SGdfP45M83Fi0VQ+YBuLhxspxbY2HJWCJl8eDmwzS41Ek3h32ux5XZ7lMVekYSeQ8Er+3vyzZRwthNlWPZvwdUhaYqL2DPitVKgcANy4aX3u7hw3dvyCbJCi8PTi+WhGHmv5CyrKL3WrYTS7jN8/s2HnK9zgkEGWZ8sO3WABU3TI4OxXn4jQ5HSzvnxi4BquxkpmoCKiMJExsYLGiWnExsHE+Z2ci8L5KkOezP/l1CwqeO3gtNy+a7v9/NUzuOFDVV3LfxEGG/WqSEIhokBScipebhB86az9/86nUGYzmNiwGV2y7XeMylNMswS2ejc1d0bNsG23b+TO9TisxNsnA1yZbcj9mtZKwvksTnUYqMLTJjrV/R5DovQz4PXo9M93Aiu+T8eE5dei4Zkxy3jHfG/v3q09r4rz/s54kdR7BsZ4XtYH+MkE/UcQsEAK/s7ilKkqmyhOqRGUmk8CgSQ+mm6njKRJKcvq5SZB7a3eZ5qYy3WIUW5DKjg223BqykabG0qQrbttm4r4+RZEF9NpC0LGRZojnsJxKPkKiga1tmgqdygoBUYZOGZWNYFpLlBAWFTRWiQVIwU3CbhzVBlcGokZ0Ptg2DUYNH3ugoyh5lKPd86/Y5hXMrl9zX7PTPB3ujrmMljHSXYwGWDS3VvqKHgHJ9GrmoisycGj/9kSQDMYMjLs2Tbx8dpj1njrtlvBurfHz+co3r1s3jb375el7Dl0Aw25GktPlUDgFVxrQgmp4rAzmiBbY9+nNhyaiEk/F2Y6yVLYEAZniwfd/GQ3QNxbNyXKoi0RDy8sXfbKU2oJIw7aJAO4OZsvF7ZHZ3D2MB/nRnf8yl2WFS5Ny0PbJTV5pMWVjYpP8HEuzuGsnevDOZ63JL8ILZy4loqlBOkq8Uj23tLFlDCc6UiRkm0aQjvZWyLPyqzP2bDmcz2VNlIGq4HrMklQ74FYmSK02Z+Tie34skSdRX+fCpCvPqgxwsMb+TKZNgCZURNxnBxY0hzl5cz+6jwwzGUs61RSCYpSiShGnbeavSEs7qUiSZmtRqNYDPpS47Q7mVLYEAZrgaycb9fXSNJEhZNrIk4VUUOgcTdA8nOTKcYH+Jm1kGv1fBBiJJC8OypqWrX8mxWq7yebBssjfDzKf9/+y9e5xcdX3//zznzH139p7NJpvNhQROQkiQa7gIEqyichMUrAXsr6XVVmntt9V+BRUrVWkrbe1PrK2W/lohaAVBkCAqCEVuARIk9wMBcs9ukr3vzn3O+f1xZs7OdXdnMrO7s/t+Ph48yJzZ85nPnPl8PvOez3m/3i819TfpfNJ0+cDrz+4q2Kbcmpq7pHdj9/WGsu6GPJuqxzxdFLsLY1r5gauFrd6/YEVbwXPcmsrR4aizI50wLY4OR3l1b1/R1ymVWCJZtK1Mp9hMzi/S3+vOWlTy51LndXHTeUvwe/K/wD1FvtTHKyP4wdM6CHhcLGgsnosuCHOBzAphmgIeTcHv0RiJTj7QLrRmnbW0uWJ9FOYmNR1sp1X+LlXBo9l5WGBXFhnMKfuV+UbrPBrJlBDClcrBTAfbmQEyjNXtLQW3ptDkd9Pe4ENVFZa21XHK/CDzg17n9RxyZnb6tvTFp8zj85fpLG2rc9r4/GU6ALfcv4Wr736OW+7fMu2BljB1jFdKbzopVhKrGKqicN/N63j3yW3OfNNSVTdUFfuuT8Z/pG7xFnsdv1sld1rlPs5GKdrWu0+ex0fOXITPpaFgVxr4yJmLuO/mdQXn43hmOw9sPsizbxwrOF/fo7fzV+/XWbWwAZem0NkS4OaLlrGivb5gWwuailuBn7O0hZsvWkZnSwAFRfJJhClj/Hk2fXg0hQ+sWQAoTtrIZGnyu53vfUWxHzcXKdErCJOlptNILAs8KSOaQukfmqpQ79EYjCRwpyrUu1SFcDzJvFR5sZaAh6MjUWfHWVMVTNOivd5Le6pqwY7Dg0VzTP1uzcm/TlcfSZP+Mga4+u7naG/wOW0a3cPETTPvtq/PNfazIPfWlNjFzm1mah5/sZJY9V6NkWj+vGz028tOZmmuNCff9njBnaVE0iz6OpevXcjGrUfyjkcTyYLzVlWL9zmda3nXdafnPVfsVnGxz2XHofHNLtL/RRNJjg9HncpHmVVK0nxg9fyCr5HmnKUtnLO0hV/s6Lls3D8UhAqysMnPJ+7ZxIH+8gycupr9/KDAOlAu7UEvQa9GU52Hj53dVXBdmLBPLQFy7ytP9xor1D41G2xfffdz+NwKsbjlfEll4tYUOpv8eDSV1jqLkVgC07IIxRLMywik0/8fiiRQFGgLerlgeSvRhOmIHQ4NhBkKx7OqGigKKChFz8kVSOTmYPs9GsTASoUW6Zzt1Z2NRd+zWLjPbWZqHv94JbGeMY5mBdz1Xo0LTy4+VjVNKVjGz6Wp4wqRlrXVsWHTfgZCMZoCHm5Yt5gNL+3j6HA0rxrJvKCvoqKmYp9LJJ6kroDrXO589bo0Fjb56R+NOXnZT+zo4chAmAVNfj6wen5Jtu+CMJUc6A/zTsaPyukkaZqYqFy6cv6EczlXN6Iq4HUVvtk/3WusUPtMe7Ct6/o64O8Nw7iklPNsQwmNwXAMV86k0VSFruaAk7LxqUtO4n2r5tNS783bHQY74P7mdXrRyXnpXU8TjiXJ1S0taPLx67+aXLdzd9KaA25iCZP5Db4s0dV4OdkzdWdTmBrG242dbgrt+m47NMhTu45m2YonTVjZESzaTpPfTU8imnc8vRtebHf5M+tX8Jn1K/KO3/3rPXnzNm0kVSlRU1GzC3fhL+5C8zUtngx4XVy4vE2Ca0Eog4VNdlD8xPZu1nQ2omKnlRaikOjx8rULMLqH847PhDVWqG2mNdjWdf2vgZuAkn8WJ5IWjX4P4XiSocjYzllbvYdTFzZydCji7Ao1+d3c/ugOp1LAB07rYHf38KR3tE5d2IhpDeaV/Vq9sPgudC65O2lrFjVxXUewpH7M1J1NYWqotRJTu44MFSyXt7vAl1mas5e28Mo7fU6FIZeq0BLwcM6y1pJfPx185+54p49XqrJLJc0ufG6Nzma/UyJQEITyeGDzQToafRwejOQ9t7DJb9/9KrA2PPvGsZpZY4XaYbp3tt8CrgXuLefk4UiC4YxA+7LV8/mr952CSxvbUdpzdIRv/3qP83hfb4h9vaGsfOqJuP7sLvb1hvLKfpX6a/dEd9Jm8s6mMDXUUompA32hguXyxrsTk55r7Tkuj+WO8WI73pXWP1TS7CK9y+33uDg2HB23xq8gCIXZ3xfighVtWY6waS5Y3lp0bailNVaoHaY12DYM4ye6ri8t59zjI1GODI39Yr1h3WL+8MKlKBnlQ1rrvfzTr94oeH4pec4zZUdxpvRDECZDOXdipmqMT4X+4UTfi99j73L3jkSdSkuCIEyOxS0BIvEk7fXevDtlhXReglBNpntnu2wybw19+F0Lufndy7Kebwt6afC5K5bnPFN+7c6UfgjCRJR7J2YqxvhU6R9O9L1oqkJ7gw9/JE7vSAyzQsY+gjDbue6sRfzjL42sKmBpROckTDU1XWdbVeCm8xbz5+89Oev4vFSgDcVrAEuesyBUl2K14mfCj8VaWxeCPjedzX7H6VYQhHxy15lam+fC7KVmd7aDXhdf+/BprFk0JlJUFIV5QS/1GeW2JM9ZEKaPmXonphbXBbemsqDRx0AoTn8oNt3dEYQZxyOfuTDrcS3Oc2F2Mu3BtmEYe4HzSj3vJ396fpYQUlEU5jd4CXiy35LkOQuCkEutrguKotBc58Hv0Tg+HCWWlNzTXE7EZOWcJWLLPZuo1XkuzD6mPdgul6DP7bhGqorC/AafbRRTgJm6uyYIwvRRy+uCz20b4fSNxhiKSInATE7EZGVRs7/CvRGmm1qe58LsoaZztsEOtDsaiwfagiAIsxFVVWgLeulo9OFSa34pFwRBmLXU9AqtqXagLaIhQRDmKgGPi85mP0GvC7eWUftUEARBmBHUbBqJS1VoqfcVtFwVBEGYS2iqwrwGH+tOau2f7r4IgiAI2dRssN1a70VVZRNHEAQhzZrORnG/EQRBmGHUbBqJBNqCIAiCIAjCTKdmg21BEARBEARBmOlIsC0IgiAIgiAIVUKCbUEQBEEQBEGoEhJsC4IgCIIgCEKVqNlqJIIgCEL16DoBN8UFDT7KlbCfyOue6Pkn0u/pOnc6X/tE+32in7Ug1AqKZVnT3QdBEARBEARBmJVIGokgCIIgCIIgVAkJtgVBEARBEAShSkiwLQiCIAiCIAhVQoJtQRAEQRAEQagSEmwLgiAIgiAIQpWQYFsQBEEQBEEQqoQE24IgCIIgCIJQJSTYFgRBEARBEIQqUcsOkuLGI1SbEzFHK4SMWaHaVHLMyngVpgIZs0ItUdZ4rVqwreu6Bnwf0IEk8AeGYbyV8fyVwO1AAvhPwzC+X62+CIIgCIIgCMJ0UM00kisBDMO4EDuo/qf0E7quu4F/Bt4PvAf4pK7rHVXsiyAIgiAIgiBMOVULtg3D+CnwydTDJUBPxtOrgD2GYfQbhhEDngMuqlZfBEEQBEEQBGE6qGrOtmEYCV3X/xu4BvhoxlMNwGDG42GgsZp9EQRBEARBEISppurVSAzD+H3gFOD7uq7XpQ4PAcGMPwsCA9XuiyAIgiAIgiBMJdUUSN4ELDIM404gBJjYQkmAXcDJuq63ACPAxcBd1eqLIAiCIAiCIEwHimVVp1JOahf7/wM6ADfwd0AdUG8YxvcyqpGo2NVIvlPiS0iJH6HaSOk/odaQMmpCrSFjVqglyhqvVQu2p4Ca7bgw80maFg9uPrjgY+d0dVewWRmzQrWRwEWoNSo2Zj9xzybrQH+4rHO7mv384OZ1leqKMHuZWXW2BaFWSZoW3YNhXj8woH3snK7p7o4gCIIwCQ70h3nn+Oh0d0MQ8pBgWxAySCRNugcjxJLmdHdFEARBEIRZQNWrkQhCrSCBtiAIgiAIlUZ2tgUBiCdNjgxESJgSaAuCIAiCUDkk2BbmPLGEvaMtgbYgCIIgCJVGgm1hThNNJOkejJA0pfCCIAiCIAiVR4JtYc4SiSfpGcoPtE3LYtPbfdPUK0EQBEEQZhMikBTmJJF44R3tWMLk6xt38cWfbp+mngmCIAiCMJuQnW1hzhGKJegZipJr6DQUjvPlR7az7dDQNPVMEARBEITZhgTbwpxiNJrg6HB+oH14IMwXHtrGwZT72IJG33R0TxAEQRCEWYakkQhzhuFInJ6hSF6gvfPwELfc/5oTaK/sCPLtj58xHV0UBEEQBGGWITvbwpxgKBLn+HA07/hv3jzO1x/fRSxhl/27cEUrX/zQKnxubaq7KAiCIAjCLESCbWHWMxiK0zuaH2g/uPkg333mLdL73Nee0cmfXrIcTVWmtoOCIAiCIMxaJNgWZjX9ozH6Q7GsY0nT4rvPvMVDrx0CQAE+vX45Hzlz0TT0UBAEQRCE2YwE28KspW80xkBOoB2JJ/n6xl08/1YvAF6Xyhc/tIp3n9w2HV0UBEEQBGGWI8G2MCvpHYkyGI5nHesbjfHFn27H6B4GoMnv5uvXnMaqBQ3T0UVBEARBEOYAUo1EmHUcH84PtPf1jnLL/a85gXZXs5+7f++McQPtrhZ/sqodFQRBmMOMRBNsPzTon+5+CEK1qdrOtq7rbuA/gaWAF/iaYRiPZjz/l8DNwLHUoU8ZhmFUqz9CcZ594xg/fvUAB/pCdLUEuP7sLi4+Zd6Ut3GibVqWxfHhKMPRRNbx1w8M8OVHdjCSOr6ms5G/vXo1DX53wXZURaG9wcufXrKi+4TegFBxvvP0Hja8tI/+UJzmgJsbzlvCZ9avKKutaoxZQagVJhr/mc+nqzNF4smKzZW0nmYgFBdFujDrqWYayY1Ar2EYN+m63gq8Bjya8fyZwCcMw9hcxT4IE/DsG8f45i/GfuPs6w05jye7mFaijRNt07Isjg1HnYA6zZO7eviHJwwSKVv29fo8/u8HVuJxFb6p43WptDf4cGty02em8Z2n93D3r/c4j/tDcedxqQF3NcasINQKE43/zOeHI3He6BkBYH6DF/ME54ppWhwfiWL0DPOMcZT1+vwTfTuCMOOpZkTxAPDljMeJnOfPAm7Vdf05XddvrWI/hHH48asHCh5/YPPBKW3jRNo0TYueoUhWoG1ZFve9tI9vPL7bCbQ/fm4XX7x8VdFAO+hzsbDJL4H2DGXDS/sKH9+0v+S2qjFmBaFWmGj8Zz7fH4oX/Hc5cyWeNDkyGOaJ7d186t7N3PPc3pLbEIRapGo724ZhjADouh4EHgS+lPMnPwK+AwwBD+u6foVhGI9Vqz9CYQ70hQoe31/keLXaKLfNZCrQjsTH0qsTSZNvPfkmj2+3s0BUBf7id07mirULC7apKAqt9R4afIXTSoSZQeYXfSa5FWcmQzXGrCDUChON/8zn04Zfuf8uda6EY0mODIb5j9+8zf0vFw72BWG2UtUtPF3Xu4CngXsNw7g/47gCfMswjOOGYcSAjYD4Y08DXS2BgscXFzlerTbKaTORNOkeDGcF2qPRBLc9vN0JtP1ujW9cs6ZooO1SVRY0+iTQrgGaA4U/o6aAp+S2qjFmBaFWmGj8Zz6feScw89+lzJWhSByjZ5i/fnCrE2irCnzyomUl9VsQapVqCiTnA78EbjEM46mcpxuA7bqurwJGgUuxxZTCBFRa1HX92V3c/sh2+kNxYgkTj0ulOeDmurMmb/BSiTYKtZmZU5gm3aYdaEeIJcd2Wo4NR7n14W28fWwUgNZ6D3des4YV7fUFX8Pn1mgPenFJ2sikqeT4K7WtG85bkpWz7Rxft7jktiYaX4JQC5QzH7/z9B5e2HOc/nAcl6rQUuehPegDxsZ/5vxoDrjpGYo6/04zmbliWRZ9ozFe2dvHVx7d4bTT4HNx+xWncuaSZg4PREp/44JQY1RTIHkb0Ax8Wdf1dO7294E6wzC+p+v6bdi73lHgKcMwHq9iX2YFc0nUlX4/D2w+yP6+EItbAlx31iIuPmUe8VSgHc8ItN86OsKtD2/j+IidUnBSWx3fuOY02ht8Bdtv8LlprfegKCKEnyyVHH/ltJUWQW7YtJ+BUIymgIcb1i1mTWdjyW2NN74EoRYoZw5liozdqkrStDg6HKU54OG2D61yzsudH/MbfSgWhBPmpOdK0rQ4Nhzh4dcO8c9PvumkoJwyv56/uWo1HUXWZkGYjVQzZ/uzwGfHef5e4N5qvf5sZDxRS7lBwo9fPUDQ5yaYk0ZRSpuVaKMQF58yL+/8eNLkyECEhDkWaL+yt4+v/mwnoZidTnLWkma+cuWp1Hvzh7fkZ5dPJcdfuW19Zv2KvMojt9y/pay2Co0vQagVyplDmSJjTVXQVHuzYSiSyDvnROZHLGFyqD/Et558k0deP+wc/+BpHXz2vSc76ShBrwuXpkTLehFBqCHEQbKGmE4hYrXbmAyxhL2jnRloP77tCP/0qzdIFRzhg6d18H9+5+SCqSEuVaW9wevUjBVKo5Kf80xtSxBqhXLGfSVFxsUIx5LsODzI7Y/sYOeRIQDcmsIt61dwxdoFKIqStekxr8En5mHCrEeSVWuI6RIiTkUbE5EbaFuWxT3PvcNdvxwLtP/gwqV87v2nFAy0fW6NhU0+CbRPgEp+zjO1LUGoFcoZ95UUGRdiMBzniR1H+OMfvOoE2m31Hr71sXdx5ekLURQFj6aysElE6cLcQna2a4hKibpyncGGI/GsFJDhSJyjQxGuvvu5SYvNcgWSPpdKwKM5bfjcmi3KKcP5L5pI0j0YIZmKqmMJk2/+wuCp3UcBcKkKn79M532nFjZHyMzPrqQDYa0zFaLCYtd7PFHt5x54nce2HiaaMPG6VK5Yu5C7rjt93H5VWqArCDOdzHEfjiWxsFBQiCdNPvbvLxKJJ/OcHy9Y0cbGrUcAO6c6aVqYWAS9Lp5945hjaJO7LgDjrhVp997/enEv//a/bztr9bu6GvnyFafSnArm670u2uq9qKrivM5jW4+8vPfvLj93Ci+dIEw5EmzXEJUQdeWKasx5S+4AACAASURBVNJ5zgGvRiRu4nepDEfizvFyRHCJpEl/LIl/KELQ5+aVvX0cHY7iVlU0VSnJ+S8ST9IzNBZoD0fi3P7IDl4/OAhAnVfjjqtWc8bi5rxzc/OzK+lAWOuUI64qdfyNd73XdDYWPOd7v3mb5/ccdx5HEyY/2WKbZ4wXcAvCXCWeNImbJioKimLx9rFRNFWhwediKGIbfaWdHwEuX7uAp3cfpS8Uw6UqtAW8eFwq3/yFwbZDgzyRKpsK9rpw+yPbAZwNmdy1Imla7Ds+ytcf3+VsgID9I/yTF5+EptppIy0BD42pnfWc9UfusAuzHgm2a4wTFXUVEtUEfW7agz6+/fEzuOX+LYzG8lPoxhPd5Aok9/eFMC2T/pC9Y943aucDJk3LEeSAXVVivCA3Erd3tE3LDrSPDIa59aHtTk7i/AYvd167hqWtdXnnaqrC/IbstJHxHAjnWrBdrkCxlPE33vU+c3FTQVHtixmBdiYbtx4pGmxXS6ArCDOZ9LjvD8VJLZHEEiZJy15n7WDajmPTazHYP2DPX97Kvt783O4Nm/bRWufNOpbO8y40v85d1sJr+wb44k+38fZxu+Sqz63y+ffrrF/ZDhTWyhRbfwRhtiLB9hyjFOewQs9Pps10iaf0/9N26SZW1t+NJ8oJx5J0D0WwUt8iu44M8aWfbncWfn1+kK9fcxotdfm5hl6XSnuDL892fSrEQbXCVIgKx7vexV4/aUGhaozRRHENlQgkhblIetxnujpmrrEJ0yLtQZPn/Ghlr8Vp+kPxvGA789xMugcjPLTlEN94fBcjUXsHfVGzn69etZplbfYGSJ3HRVvQm7XJktl3Yfr5xD2bONAfLvm8rmY/P7h5XRV6NDuRYHuO0dUSKLijkekcNt7zk2nT41Kd3Fmwc6oTpoVK9oJbTJQzGk1wdDjqBNrP7znO1zbuIppa9C9Y3soXL1+Fv4DYMTMnMJfmgLtgAFgpcVAtUc7nXCrjXe9ir68pUOir3esqLmydivciCDON9LhPr7dA1hrrylgDc50fLcsqOGcKCSgzzwVQAJcKx0ei3PbwNuf4Bctb+cIHVzolV1vqPEXX1mJzVph6DvSHeSd1V0KoHpIrNcdIi11yyXQOG47E2d8XYs/REfb3hTg6FHEEk7fcv4Vn3zg2bpvpBTv9//Tuc+7uxg3rFuf1YyQn0H5oy0Fuf2SHE2hfc0YnX71qdcFAuyngob3BVzDQBtuBMGlaxBImkUTSvuVqWgX7MduZaBwU49k3jnHL/VuKjoVMxrvexV7//BVtBY9fvnZB0dcp972USinvXRCqTXrcZwbImbWzWzIC3cy/WdkR5Nhw1FnfhyNxZ803Tcs5lnlu+nxNAQsLo2fECdAU7EpQd1y9mnqvC5eqsqDR7wTaheZNsTkrCLMV2dmeY5QqcssVOxYS0uW2uWZRE9d1BNndPcz+vhDnLmvF61J54a3eLOe/3Dzp4UicY8O2v0HStPi3/32Ln2w5BNgL+p9cspyPntmZ5/qoKArzgt6CJjaZrOlspDngpi8UwzRBVe0vkmJivdlMOWLbUkWV413v8V7/cw+8zsatR4gmknhdGpevXTCuOHIq3CDnknurUBtkjnv18CCRuInPpdIe9GIpEImbLHWrWc6PKzuCjgByfoOX/lCcw4MRXKpCe9BL0OdmOBKnPxRHVRRWdzY6P1of2nKQnUeGONAXJhy307qCPhe3fWgl65a1AhDwaLTVe53yq8Xmzecv0/n8ZToPbD7ItkODUmdbmPUoVpHcrRqgZjs+k7nl/i1Zt/f294WclJDM2/JL2+r49sfPqNjrDkXiHE8F2pF4km88vpvnUmI5j0vltg+uLBjUuDVbfDNemkGa3PeWZpz3Umkv95oes6VevzKu94ylht5LJcdsTY9XIZ9C4zitbchNu8oc26FYgh++vJ9vPmEQSd1lXD6vjq9etZqFTX7AvrOYq6GZ5Lyp2Jhdf9czVrkpEcva6nj6c5dUqis1w/q7nikrjWSuXi/KHK+ysy1kMZHYMU0lxWcDoZhTsaQ/FONLP93OriPDADT63Xztw6tZvTB/99nv1mhv8OWlpxRDhHQnRqnXbzZd79n0XoS5S6FxXEwAmR7bx4ej3PnzXc5dRoDfWdXOX77vFHxuDU217ywGPPnhhMwbQbCRnG0hi1xXsrQ4JlckUynxWd9I1Am09/eFuOX+15xAe1Gzn7t/74yCgXaDz01H4+QDbRCnwROl1Os3m673bHovwtyl0Dj2uNS89R1gSYuf3UcG+cP/fsUJtDXVtl2/9YMr8bk1/G6NziZ/wUC72OuBzBth7iE720IWuW58qmLnT+eq1HPFZ7muY6sWNLDryFDRx9edtYhTFzYwnDJd2HZwkFsf3uaY6TT4XfzhhUvpTN2iTJNrVDMRE7llFnovQmFKdWq8/uwu/vyHrzEYsesAKwo0+tx8/jIdKN3BstxzKkGl3FsFYSpJz5edh4eIxJOYluWsuXHTwrIsLMsOuNNr43Akzkg0wUAowlXf6XF2vlvqPHzlilNZs8je/Gjyu2mu8+RpaDJfOy3ETK8V6bVX5o0w15BgWxgXl6ZS71WZ3+gjEjcLis9yRTDbDw3y1K6jzG+wBTe5j/f3jvKtJ9/kd8/t4pylLfx691Hu/PluxyWy3uuivd7Lj14+QJ3XxTlLW+y+FDBHGI9ibpl1Hs0RDFVaSCeM8ejrhxkMx53EX8uCwXCcR18/DFCy4HA6RYpTIcIUhEqSni/DkTg9Q2PCc9Oy/7MsUBW7eknQ66I/FLcD8tTfHOgf8x9Y2hrgmx9dS2u9FzUlSK8bR5CeOVfTQsyeoSgdDT4+vX6FzBthziHBtpBFMTe+tMNksXMySddWTruWZT5u9LuxLIXRaIKfb+/mzZ4R/uO5d5xzmwNu2jJ2S57Y0cM5S1vwuzXmBcdU7pN9L7kEfW7mNRR/L9Uk10Gz1ijVqfGxrYdByVeTbNx6hEi8cAGCiZxKSz2nkpyoe6sgTCXp+ZJZ6z69oaGgoChj6YGR1ObDcCRGfyjOYDjhnNPkd7OkrY7WenujY17Qm2cYVuy1gaw1Y16DT+aQMCeRYFvIohoOkun/m6aJZdnVRizL4rf7B3jGGKtV3B700uTPDuSODIRp9LtpGed2ZSXfSzU5MhCmIeCedArMTKPU6xktIryKJpIVGWeTOUcQ5ioTOUxmkkiaKaObsPMXCjA/6KXB76ZnMFLSOixzVRCyqZpAUtd1t67r9+q6/htd11/Wdf2qnOev1HX9FV3XX9R1/Y+r1Q+hNMoRtEwkqvS4VFyqgs+tObcpDw1GGAjbOy4+t8qazoa8QFvTFFZ2BGmt95YcaJf7XqpJ0rQ4PhylezBMPFk4EJ3JlHo9vQVEV/ZxrSLjbDLnCMJcJT1fMsWPKkrWf2C7QbpdKjuPDDmBtktV6Gr20+B34ypjHZa5KgjZVHNn+0ag1zCMm3RdbwVeAx4FOxAH/hk4BxgFntd1/WeGYXRXsT8znolEhlMhBiskBDs6FOHQQJhVX36C5oCbG85bkmVIk3tOc8BNz1DUEVW213voGY7icanEkyaHByPOrmdrnYevX3Mag+E49/xmLJ0krZC/9szyhTSF3stwJO64YRa7punP4bGtR17e+3eXn1t2B4oQiiWJ9IdprvPQ6K/uLnclBYXXn93F5x98nb7RGAnTwqUqtNR5HMFjLlesXciDmw/mHb987QKuOn1hUcFhsT5Pt0hxusSZggD5YkefW2Ve0AfAseGIbWrj1jh1YQPXn93lzJf0egz5Lr4eDSIJi2h0LNUk4NFYkCqp6nNruFRlwnW40HdXur522iQnljAJeDSefeOYzBthzlHNYPsB4MGMx4mMf68C9hiG0Q+g6/pzwEWpc+YkE4kMp0oMlisEi8aS9IfiziLdH4pz96/3ADgB93gOkocHQixsqudivZ2tBwd5bX8/iVTe4NLWAHdeu4b5DT7n9Z/Y0UP/aIylrQGuPfPEBGi5/fK5bcV9WihZ6JrmfA5Vu/NjWha9I1FC0QSt9d6CpbdOlEoLCrcdGqR/NI6Z2pQ3TegfjbPt0GDB9q46fSFP7ephIDxWjaTJ7+aq0xcWFRzCxMLJ6RApioOkMJ0UEzse7I84f2Ov0XFMy2JfbyjLpVE9NEgkYaYCdC+KBX2jMfb1hbLSvW48bzGrFzbwy51HGYrE6Wz08dGzxv9RWWhu7OsN8YHTOnj2zWNONZL5DV5CsaTMG2FOUrVg2zCMEQBd14PYQfeXMp5uAAYzHg8Dc88zO4OJRIZppkIMlikEu+DOpwqK+jZs2p+1u11IPBZNJOkZjJIwTTbv6+dHL+93Au0zFzfxN1etzrJYP2dpC5eubKetzLSRid7LLfdvIRTNF+ZlXtNiIrxqEY4nOTQQpjngptHvrtj7hsoLCje8tA9NVfLGQ+5YyHz9Rc0BFjUXfv1CY+aW+7eM2+fpEilOtzhTmNuMJ3ZMk7khEvS5eWDzQb798TMKjs8t+/r4i/953Qm06zwaX/jgSi5c0YaqKFx5emfW2jyZvuWyu3uYefVeVrTX5z0n80aYa1RVIKnrehfwMPCvhmHcn/HUEBDMeBwEBqrZl5nOdDg3TobMxT2TgVCs4PE0kXiSnqEISdPi59u7+adfveF8OVy2ej5/+b5T8hTtrXVeGgPVS6uYjGin2N9UE8uy6BuNMZra5Z5sacOJqLRIqdSxMJtEkDO1X8LcoBSxY/pvCo1Ny7L48SsH+Juf7SScqgi0tDXAV69aTVdLAK9Lpb3BN2G1kUJ9y2V/X8iu91nsOUGYQ0w62NZ1/XLgK0ArtlBZASzDME4q8vfzgV8CtxiG8VTO07uAk3VdbwFGgIuBu0rv/uyhqyXg5LiBnbOcNg7JZKoFJs0Bd8EgqyngKXpOJJ6kezBC0jT5rxf2cu9L+53nfv/8JXzi/CVZO7iaqtAe9OH3VCbILEbuNU6TeU2L/c1UEE2YHB4IT2gWMVkm835LodSxUM7rV7rPlWKm9kuYG6THX/p7AXAEjrmkvzNyx2YkluBrG3dx36ax9fg9p8zjry/T8Xu0sqs+jTc3rFRKS6HnBGEuUcrO9r8AnwV2QJGf1NncBjQDX9Z1/cupY98H6gzD+J6u638J/AI7L/Y/DcM4VEJfZh0TiQzTeF0qF9z5FP2heEGxYjmMJ8wM+twcH4nlpQ7csG5xwbbCsSTdQxFiiSR3/fINfrWzB7AD6s+//xTev7oj6+99bo32Eutnj9f38URrkxHYFfubqWQgbOeVt9Z7T+gHSKmOj2k+98DrPLb1MNGEidelcsXahdx13enccN4S/uXJN21jDCxU7JSSYmOhHEHjdIsgizFT+yXMDTLFjocHIo45TeYXcSSeRFMVGvwu9veFGI3GueX+LVx/dhcnt9dzyw9fY/O+fgBUBf74opO4/uxFaKpKW9A7btrIeOvsRHND5o0glBZsDxqGsXGyf2wYxmexg/Niz/8M+FkJrz+rGU9kmBaDeV0qG7cecc4pJFYslYmEmekALWFahONJmgIebli3uODrjUQTHBuOMhSO8ZVHd/LbA3ZmUJ1X46tXrebMxdnJuw0+N6315e/glipam4zALvNvth0aLOy8MgXEkiZHBsM0+OzdJnWKzHA+98Dr/GTLWAWRaMJ0Hl91+kKa69z0jcawTFBVaK5zs6azsNyiHEHjTHVqnKn9EuYG6XH2nWf2cHgwgqoClpKXt50wLQZCcRY0+qjz2sL6bzy+i+6hCAOpu1KNfje3X7GKMxY343XZFU3GE2hPtM5OZm7IvBHmOopVJKcqja7rF6f++UfYedU/JaOyiGEYz1atd+Mzmd31WUV6RzuX5joPL3zh0rLavOX+LVm3+fb3hZxd0MxbfUvb6sZ1XRyOxDk2HKV7MMKtD29z2mwPernz2jUsa6vL+vvWeu8Jl73L7ftk+1oCFY1w9x0ftZITzLdCuFS7gkCpu9zlXJ+VX/55QTMan0vjvavaq329hROnkmN2zq2xM53MOb27e8gRnKsoToqJqsLKjgYULAbCcQ70jRnV6B1BvnrlqbQ3+Ca92VFL6+z6u56x3jk+Wta5y9rqePpzl1SqKzXD+rueoZxrNlevF2WO18nsbH81499dwJqMxxZQXpQnlEy5YsXxqIQwczAcp3ckitE9zG0Pb3P6eXJ7Pd+45jRa673O31YyP7vWRGv3PPcO15zRWbIINGGWt8tdzvWptOujIAiVI3MOJjJ2tdNiSRML0wRFsTjYF6Ev47vh8jUL+LNLV+BzaxOmjRR7zUxk3gvC5JlwthmGsR5A1/XVhmHsyHxO1/XzqtUxIZ9CArV4ymY3bThzwYo2IvHkuMY4gJN/d2w4SjieZCSayNolUVWc+qg+l4qmKQWNYAZCMfpGY/z3C3u596V9pNf/lR1B/vG607OC6lKV7hOZ/PjcmlMzO5OZKr75wUv7+PGrB7jy9IVcf/airB8hk2EoVSO8Legh4Jn4i7KrJcD2Q4N5OdtrFjUVPcfrUonGs+scKIDXrY3b3nee3sOGl/blaQluvGcTL+w5jmnZeaIXrGjjvpvXAcXzQIu1JQhzjUz9hKYoWJaFie3wqACZWSSxhIligc+j8GbPqFNtRAFa6z288k4vH/veMfxujUa/B59bLfidkHtsX28IC/v7J7MMrd+lcsv9W8TkSRAmwWTSSC4ENOA/gJsZ20J3Af9mGMYpVe1hcebcLc7vPL3HydEGO9BOO/m5NZWkaRE3TdrrvbQ3+BwDhHT+NdjpHoDz+EB/iIFQ3P5QlbFKTapi22rntpnm85fprOlspD8U41+eepNHfnvYea7R76K93ssfXXwS5yxtsV/P66ItOPn62bl5gpN5L5l9q9CiX9E0kqVf2OiMWbem8MHTFvC753bRkXFdJ0u910VLnWdcYWnueElzy6UrigavN96ziefePJ53/N0nt3H+Sa0F2ztraTOb9/bnHW8PetlXYPfr3Se38cmLTioonNI7glm6hMn0WchC0khmCZn6idyvaUXJPpZev72aSjRhZtmuBzwq4ZhJg99NKJogkrTvXmV+T0D2Opp5LNNIJ73+VnjtlTSSaUTSSEqmrPE6mS3G92GnkiwA7kj9+6vArcC/l/OiQnl8Zv0Kbrl0RaosnF0zNR1ow5jJQfrWYaYxTpr+UDzr8Wg009hzbBRZzv8t3KpKJCO9QAEe3HyA3tEo333mraxAu63eQ3vKlOaJHXYlktY6L/MafCUJIccz+UkT9LmZ3+hjaVsdqqqwtK2ukoF2xfnL3znZCazjSYtHXz/MTfe8zD88YZRc33skmuBgf5jBcOHUIoBdR4aY3zDmTpl2cdvdPVz0nCa/m6aAm/RHpSjQFHDTHPAUbW/z3r6CbRUKtAFe3NNb1Ahj49bDBY9vyChXJghzgceKzAXILvunqQqKYt+VimQE2gGPxrqTWnFrGg0+F6FYklhyLELP/J7IvWOaeSzoczvzfiAcZ2lbHfMbfHmBNthCSEEQ8plMGsnfAOi6fpNhGPdWvUfCuHxm/dgO36ovP5H1XHqZTaeDFMq/zs3FTpiWE1j5XBqRRNIpor6ivZ49R0eyzlOw0FSV3d3D3PGznTyb2gVVgI4GH0Hf2JA6NhxhQaO/rPzsyeaSR+JmzYjzrn5XJx84rYNf7z7Khk37OdAfJmlaPLGjm1/u7OY9p8zjhnWLOWlevuNaIdKW7+GYbYaTm56TLt2Y+6U4kalMV3OArhzXx7RBRaH29vWF8Lkm/xknLavoj4tIwizY1onoEgShFimmnwD7h256rV7VEeTgQNipNgLwsbMX8UcXnYTfrXHFt39DNDGW050m93sik9xj6Xmvqgrf/vgZXH33cwX7JXncglCYCYNtXdf/M+Pf63OfNwzjDyvdKWFy5OZwqyiY2LvdUNgYJ7fEk0tVSJiWs1OSbkMr0IaqgGUpDIbjHB+N8kaPHYi7NIUFDT78Gc6HPrfGSe11ZQshZ6rJz4ni0lTev7qD966az2/ePM59m/bx9rFRTAueNo7xtHGMC5e3csN5i1nZ0TCpNkOxJOH+MI1+N82BMcv3SpvKFDOo8I1TNqwQmqIUfZ1ibY1noiQIsxGvSx034FZRcLtsbU36zqOiwKkLGvjUe5YT9LporfcS8LiIJuLOOemAO/N7IpdipQDTa4eYPAlCaUzmW/J/U/8FgYXAr7GdIZsneX7N8ewbx7jl/i1cffdz3HL/Fp5949h0d6kgN5y3JOtxOkBuSQUmaUOcTGOc5oA763FLnSfrXKeNuuw22urcWBYMheMc6A8xFLbTTzqb/Pyf956MaVkcHoywry/EYCTOaDTOtWeUb1yQFuhk9jv3vUDtmiNoqsIl+jy+f9NZfO3Dq1m1IOg89/xbvXx6w2v89YNb2XpwYFLtWZbFQCjGof6wkxp0/dldDEfi7O8LsefoCPv7QgxH4hOayhTiurMWFX3u8rULCx5fUuSL9/wVrSW3Vcw4RxBqmfG+a64oMhdUxd551lSFSNxyAm23prC42c//c/5S2oJ26p6qKlnfE5nmZJnfE7nraqFjMLbejrdOCIKQz2TSSP4bQNf1TwPnG4Zhph7/GHiput2beko1SplO0ukkGzbtZyAUoy3o5YLlrUQTZlFjnPRimDYZOHdZK16Xygtv9RZvY36Q7YcH2XF4kCODEeKpvL9TFzTwtQ+v5s1Uqomi2MK9aNzM2uUuh8mY/MwGcwRFUbhguS0+3LJ/gPte2sfrBwcBeHVfP6/u62ftokZuWLeYs5c0T5j3Hkua9AxFCHg0Esniu2LFKNegYllbnTMO08ZHazob+dP7NjOaUTGmzqPxyYtOGvd1CrUl4khhtjHRd81d150OwMatR4gmkqiKgqYoRJMmXld2monPrXLO0hauPaOTD61dgDcjFSv3eyLo89AW9OJzawW/E8Y7lp63YvIkCKUxYTWSNLqu7wbebRjG8dTjBcBThmGcWsX+jUdVlPJTUMC/pogl7ODtVzu7ufPnu51A++JT2rj1AyvxujXueGynHeC5XcQyArxZcM2mxdRm28FBNry8n5ffyRYe6h1Bbly3mPOXt6JOQmz6t4/tTOVxWmTejZ6qz0Xm0rQg1UhqhHLmx6fufZUX3+plKDImbG+t87BmUSPf/MhaWuu9U+Y2W0GkGsk0ItVISqZqpjZpvg5s1XX9eez0kfOAPy/nRWcyUsB/jEg8SfdgmPs37ed7v3nHOX792Yv45MUnOQFf70gUv1vLCrRhbl6zSrBmUSN/t2gNRvcwGzbt57k9tgjV6B7my4/s4KS2Om5Yt5iLT5mXdVs4lyMDYUwLNE0h4NGIJ0wslCn7XGQuCUJxSp0fOw4N8rRxzBEvqgosaPAR9LsYjSaZV0YJUUEQpoZJ51ynKpGcBfwI2ACcYRjGT6rVsemiq0ie6VwTfoRjSQ72h/jHX73hBNqqAp997wr+5D3LnUA74NE4qa3O2fHOZK5ds0qjdwS54+rV3PP7Z3PpynbScfXbx0f52427+IP/eoWfb+8umi7S0eQHIJm0GA4nAMXO65yiz0XmkiAUp5T58eDmA1z73RecQNvrUlnSEqClzhZAdjRKoC0IM5nJVCP5pGEY39N1/facp07TdR3DMO6oUt+mhevP7ipotlErwo9y3Pdynfw+fEYnCxt9fPVnO9mUSmXwuVS+dMUqLlje5pzX6Lftwz9yVnWuWTGHwbnGsrY6vnT5Kv7ggqX88OX9/HJnDwnT4mB/mG/+wuAHL+7ld89ZzAdP68iqIvDB0zq4J+OORCSeRInDh07rwDStorebK3Xdrz+7i9sf2Z7nOHki46JY32SsCLVGsfmxsiPoODN2NvuJJUye3HXUOS/oczE/aJvLDIVjHO+PMxCKc8v9W8oe9zJ/BKG6lJJGUnOJYOVQy8KPXMfA/lDceVws4M4V6RwZjHDnYzsJJ00OD0QAW5n+jWvWoHfYFTMURaGt3uPUW67GNasloepU0dns53OX6dx0/hJ+9MoBHt92hHjSomcoyr889Sb3vbSP689exBWnL8Tv1hz3zid29HBkIMyCJj8fWD0fvSPIwf4wLfUe6r3ZS8BMvu7F+rbt0CBPbO/OOw7T32dBKIVwLMkDrx4g6HMTT5o8+8ZxRlLVhTRV4TOXLGdRk5/n3+5l+6FBjo/amyp1XlfZ434mz3lBmC1MJtheoOv6+cDfpiuRzHYuPmVeTS4yG17aV/j4pv1Fg+20k5+CXTrq+HCEQwMRx/BgSWuAO69d4zgfulSV9gZbyZ5Jpa9ZMYfBBzYfrMnPBqA16CUUTTAaSzJZYXIh5jf4+Ox7T+bGdYt5YPNBHn39MJG4Se9ojO/+79ts2LSf685exNXv6uScpS1O0J1JwjQ5OhRh2K3RUu9xqhdU8rr/OBU05JrglPsZFuvbhk37aK3z5h2v5bEizH4KzY/9fSEiCRNNgf39YSc9z+NSueuja3lXVzPtDV6uP3dxUYFlqeN+Nq61gjDTmEyw7QX+AThZ1/UXsGts/8owjLeq2jOhZHItd9OM5753oC/kuEL2DEU4PBghFWfzrq4m7rhqNfUpV0i/W6O9wTeuKK9SzEZxXb3XRb3XRdK0GIkmGInExzWtmIjWei9/8p7lfPzcxTy05SAPvXaI0WiSoUiCe57by49eOcCH39XJR89cRGOBmrkA4XiSQ/1hgj4XzQFPRa97pT/DYu31h+IFg+1aHivC7KfQeI7Gk1jA28fjTikYv1uls8nPuctamBccW38rNb9m41orCDONCQWShmHcZhjGRcAS4FtAK3C3ruu/1XX9u9XuoDB5CpkQwPjue4tb/KiqwuGBMAcHxgLt+Q0+/v4ja5xAu9HvpqNxagJtmN3iOk1VaPS76WwO0Nnsp8HvPqHr2uh38wcXLuOHf3wef/TuZTT67XEwGk2yYdN+hSlStAAAIABJREFUPv4fL/HdZ96idyRatI3hSIKD/WGWtAYo1JVyrnulP8Ni7RUb97NhrAizl9zxbKbudkUTY6bqTX43i5v9rO5spKPRn7VOVGp+zea1VhBmCpPO2TYMI6rr+gAwAvQD84H8+9MZ6Lq+Dvh7wzAuyTn+l8DNQNou61OGYeQr7GYZE4lQyhGpZJ4T9LnpHopgWXaBXAU7sMt130ufc7g/hKYp7Dw8nFW2z6MptAc9fPaHr7Gw2c+ZXc3s7hket1+Vfm+1LlSdLF6Xhrdeo7XOQyiWZDSa4D9+8zY/fe0Qg5EEjT4XV76rc1IOivVeF7+3bjHXnNnJY1uP8ONXD9A7EiMSN3lg80Ee3HKQ85a18GfvPdlJC8rEtCwuXNHG3uP7cWtKVoWZ9HUvJsAt9Plef3YXn/3RawyE41iWbXrU5Hfz+cv0ktu6+JR5RcfEDeuWZOVs5/ZZEKaL8da968/u4pP3vkokPlbKz8zILtMUe86gKHzkzEXOfDk+EkNV7TuN6TtjlkXZAuS5stYKwnQymWokHwcuA9YDbwNPAv8MvGoYRtHEU13X/xq4CShULf1M4BOGYWwup9O1yEQilHJEKrnnDIRiWYv1eOe4VYVowmLPkSFiOWX7YkmLwwNhFjT6Odgf4sW3+pjfYKvfC/WrGu+tloWq5aAoCnVeF//1wl5++PIB3JpCnUdjNJbkvlQu/mQty/1ujevOWkRnk4//96k99I3GSJgWlgUvvt3Hpnc2cdnqDj5+bheLmrN3r9L53b/Y0cNgOE5Xs59rz7SvezEB7jvHRzG6h53j6c+3MeDOSm2yLPucR18/zLZDgyW1BeOPiTWdjXNmrAi1wUTr3t8/sdsJtCE70FYAj0vDsiyiCZNHXz/Mxq1HSJoWcdMEEyJx27KdVC39cplra60gTAeT2dneAPwC+IhhGK+W0PZbwLXAvQWeOwu4Vdf1DmCjYRh3ltBuTTKRCKUckUruOX2hGIoCKkpWCbhMgeSPX7UDuVAswb7eMNHE2ArvVhWSpoWJ7Rzp0hQO9Nv53v2heJaQJ7Nf1XhvULtC1RNhw0v7SJiWI1B1qQp1HpWndh3lxvOWlCSsfHLXUZr8bhp9LoYiCfpCMeJJC9OCn2/v5hc7urlEb+eGdYtZ1lbnnJcrqgz6XCSSZlEB7sath1nRHsw7/uKe4xQyuty49UjR1I9ibaXHSrExMRfHijCzmWjd23F4KG83O01LnYdwLIGFStDnZuPWw4C9PmdimhY+t4bHpTppH+UIG2X+CFPNJ+7ZxIH+cFnndjX7+cHN6yrco+oymWB7DfbO9td1XV8KPIstknzSMIz+YicZhvGT1N8X4kfAd4Ah4GFd168wDOOxUjpea0wkQilHpJJ7TjpAM3NcljMFkj1DYYYjcfb1hvMcH1VVIW5a1HtdhOJJkiaOiUIsUdwdshrvba6SK3JNB96RRIQlLQFGYwlGownCcXPCwLt7wF7IFMXOEW/wuRiJJugL2cJM04Jf7z7Kr3cf5cLlrdxw3mJWdjTktTMcSTASTRKNJ3GpijPO0kSKiDyTqdSRXKKJJP1FPvpiglEZK0KtMd66NxyJFwy0XaqdWhaKJQHFWXcjCROfS8tb29OPMtdnmStCLXCgP1yWTXytMhmB5A7DMP7JMIzLgNOBB4F1wG90Xd9U6gvquq4A3zIM47hhGDFgI3BGqe3UGhOJUMoRqeSe40qJZ9SckuhpgeRoql7r28dD+YE2ds5gg9fFaCzhiOTSO+SZO+W5/arGe5urjCdyVVWFoM9NR6OfJS0B2ht81HlcKIUiWsYcJNMoin3++ctb+dqHV7OyY2wH+fm3evn0htf4vz/ZytaDA3ltWZaFpipYWATcqjPWwDY8KkSxO9tel1b0fXqLtCVjRag1xhP0Xvnt5/ICbb9bQ1NVRmNJ51h63U3Psdy1Xcn5O5C5IggzkUkLJHVdXwFcCLwbOBdbKPlMGa/ZAGzXdX0Vdj73pcB/ltHOjGIiAeBEIpRyRCq557QEPBwdiWYp1qOJJEeHIpz2lV8QTSRImmO7KQGPhs+l0BdK4HOr+NwaI9Gk0xbYXww9Q9G84CjT5czn1jg6HCESNx0nNJ9bJeDRuPru5/C5NYYj8bx6y5ltiGuZzQ3nLcnKZXaO5+Rrq6rilBI0TYtQPJlXwzvXQTLNB0/r4JylLbhUhftfPsCbPcOEU7mjr+zt55W9/fZOuFfjpPZ6PrRmAecsbeHKd3Xygxf2EoomcWkqXs3e5b789IW8urcvzwnv/BVtPPfm8bzXv3ztApa11fEvT76ZSluyUFHQVIWr3lW4LRFrCTOVUgS9g+E4b/QM593Bqfe6CMeTTppIOG6vw9FEkjd7hvF7NIbCCftOUaaIMrXWZ67PE80VcYsUhKlnMgLJh4HzgePA09g70Z83DCN/+2v8dn4PqE9Zv9+WaisKPGUYxuMl93wGMRkB4EQilHJEKrnnnHtSK16Xygtv9TIQimFZdn5unUdjOLWrnWZhk4+g18XC5gBBr8bWg4McHY7SFvRywfJWogmT/X0h1ixq4rqOILu7h51+rewIZlV/6BmK0D8ax53aykwkTfpjSfzuCEGfO3VLFAJejUjcLNiGuJbZpHPrN2zaz0AoRlPAww3rFhc1JYLswDuRNBmO2KkmxRwkz1nawit7+/jP5/YC0NUcIBxL0huKOZ/VYDjOYDjO0ZEYb/aM8OfvXcEp8+tp8LsYDMeJJe00lPagj6WtATbv7cvrV0eqJntmnqmmKixrq2NNZyPNATd9oRimCapqBwzL2up4tUBbgjATmcza/8Dmg+zrHWU0mshK8VAV+z+vS3NcInNiaUzLTiFpDLhpC3roG43hQsGlqTQF3CxuDaBYEE6Yk/rOELdIQZgelInyPlNB8q8Nw8ivrTX2N580DON7le7cBJRvwVdhijl5LW2r49sfn74MmVW3/xwVJeu2JNgBzy//4iK7AobHxbygF7WEOs+573d/X8jZhVzcEsh7nCbzeszUa5ZDpYuKT+mYjcSTDEfijEaTTg3fNHc8tpPDBcQpx4YjxE3LucORps7rYkmLn3jCzEtbGQjF6Gj049aUrMo2bx4dRilwCZvrPJy5uKng5987EqW1Pt+gZoaNi5lMJcfsjFljZyqTWcd6R6Lccv9rvPh2r/O8lhI+K9hzJpYwUVOZIGlNRHrKKoqdIpjWU5zIXJih627Fxuz6u56xys0DXtZWx9Ofu6RSXakZ1t/1TFm50yd6vcp93Uq89glS1nidcGfbMIz7J9HOnwBTHWzPGGaiANCyrIKBNtgKdkVRaAp4aKkrbnhTjNz3myuirISoUjhxfG4Nn1ujrd5yanin00zS4slcwqk7D9FEkr7RuHNHZDSaYOeRYdyaQkvAQ4NvLFd8KJKgKZAkErdf062pJEyTaErUlctAKFb08x8IxQsG2zIuhJnIROvY6wcG+JP7NnNkMALYd29GIgka/G4i8bEfwSYWlln8103m3aETmQuy7grC9DChQHKSTI2t4AxlpgkATdPC6B5yUgJy8Xts2/VyAm3If7+5IspKiCqFypGu4d3e4KOr2U9zwENXa+Hr3JByDPW6NBY0+ljaErAD69Tz8aRFz3CUd3pDDITjmJblnANju+lJ06LZ78JTQCXZFPAU/fybxA1SqCHGW8f+55X9fPTfXnAC7VULgvz7TWfR1eInFEtmCSTTmgVXkTuMmTqcE5kLsu4KwvQwaYHkBMzp243lOnDlOug113l469gI0YSJ16UyP+ijZzjiPL5i7ULuuu70cdtMJE027+vnrx54veCH4tFU1i1r4Qs/2eoIZFYtaGDXkaGijwuJPW9/ZLsjYlMVe+clLdIpJqrMvB7iWlYexVwXi1FMDHXjuiX8y1NvYloWkYwv/ivf1ckT248wGE4QT5q4NZVGv4tPX7Kc/33jGC++bedTJ0yLo8NRjg1HOXdZC5v39ZF5I8OtKVy6sp1ndh/Fo6kkLPtOR9rRdE1nY2E3yPPEDVKYWUzkApkexwf6QgxGbLfU7YcG+dnrh502FOxSnJ++b7M9t0wra4fKYqzSSKHMzsyNkROZC7LuCsL0UKlge05Tjrgx142veyjC4dQOiKLY7mD7Urf2FMWuP/yTLQcBigbcsYTJkzt7uPXhbQyG7XrNmbVcfW4Vn0vlneOjTmWQ7YcGeWrXUcchMvfxZAQ0Lk2l3qvS0eAjnDALiipzr4e4lpVOMQdHoGDAPZ4Y6j16O4qi8MDmgxwZCLOwyc+lejvRZJIntue/dnOdhwZ//q6zBWx6J1/QGE9abDs4SL3PFlQmLWjwajT5PazpbBQ3SKEmmEhQmB6XX3xoGwOpNTdX5Ah25aeRWJJ40kJLpV+l/0YBNEXBsuxAW1MVTMt2fA16XXQ2+/G6tYrMBVl3BWF6kGC7QpTqwJXrxjeRzXqajVuPFAy2w7EkP371AF9/fJeTK91W76HJ70ZNpRGYlsXe3lCWG2TaRCV9LPdxmlzHyKDPnVfKb16DrySRjbiWlUYxB8dMh9BMJnKwK3T9P/ujLcwLeqn3uLIChid29PD8nmMl9ffwYIRT2utprcvOwf7hy/s5vauJi05uEzdIYUYzGffbi0+Zx7HRqPNc5rxRsMXFo7GEs2OdtCwUxQ6sFWydQyxhYll26l2msLwawkWZX4Iw9VQq2C6pDKCQ7xQ4WaKJ/Dzs4Uicf33mLf7tmbechf4jZ3ay/eAAFoptt23aZQBzRYsibqwdio2ZTIfQTMr5nPYeD9nlIn0uLAvCsQSmBUcGwsQSpWeLJZImLi07d/+d46P0jkQZCMVo8Llp8LuzclIFYaYwmTlkWRaReL7zqUdT0FTVKetXiPSMynSGFDdIQZh9TKbO9u3jPW8Yxh2GYVxauS7NDZoD7rICbm9OdYfekSh3PLaTR35r5wcqwGfWL+faMxfxtY07GQwnshbvXNGix6U6ZfoKPU6TK24sVD5KRDbVpdiYSTuE5lLO55Q+J54q4ef3aCiKwoJGP+/0jhCNlxZwv9MbosHvpiXgxp0KuheknC2TpkV/KMZAOE7Q66LB784bd4IwnUw0h0ajCf76wa15z/vdKklzzJymGOmfmJnOkOIGKQizj8nsbMuWUxW44bwlWQ564+HUWwVOmlfHBXc+xWA4zrx6D0kLDqTqJXtdKl/80CrefXIbLlXlxnVLuOOxnVlufD6Xit8zFrDnihlF3Dhzmay7ZJqJPqdCYstc8WvawfEvfucU6r0aj209QiRhZpUiq/e6iu7eWYwZ5LhUhdY6NzevXpb9N5bFUCTOUCROwKNR73NTlwryBWE6GW8OvX1shE/du5k3j444x9NpI6HUHaFCaIrilPyzsHeyFQXU1Hj3uVTHqyDg0Xj2jWOS9iEINc5k6mx/tdBxXdcVYFmh54SJWdPZSHOdm77RGJYJLs0u/WSakDDtKhAWFgnTFsooih1Mv9kzgtel4NYU9vWFnTC9OeDmax8+jVULGvC5NdqDXvb25heM93s0rju7yxEv5ooZRdw4cynVXXK8z6mY2PLytQuKvv7laxfyi509JEwLn0slkgoGvnT5Kr7/m7fZc3RsvC2fF+DMxS08/Nohx6QjYVr0DMf44cv7aav3sqytLu81QrEkoVjSNv3wugj6XHl3cwRhqig2h6IJk6vuft75kelSFVTFFosXc4NMZ0qpKmDZZf4s7B+bimI7qyoW7OsL4XGpzG/wEoolxeFREGYBk87Z1nX9k8BdQOY35DtA8bpjQlF+/OoB2oM+2oO+rONpQUwhp6/d3UO4FAXTguHw2E6ipirc/XtnsKDRT73XdoRUFKWokHF39/AJi25EZDM9fGb9inFL/eVS7HMqJrbcuPUwK9qDeWPmgc0HsSyLruax29ruVPTw1K6jfO+ms/PauuOxnSxrDTASTdA7alu8A/z2wCA3//erXLiilRvXLUHvCOadmzQthsJxhsJxfG6Nep+Leo+rJKdTQagEmXMoaVp868k3+HbGD9V6r4bPpRFLmsSTFn63Nm4qyHguqZZl4S6QSpUpyBQEofYoRSB5K3A68DXgi8CHgAur0am5wETCm0LPu1SVWDJJMuOOvQK4VFjQ6M9zhBQho1CMYnqBaCJf6AWpMZNTADie2rE+PhKltc7LUDhO3Bw7v3sgjKIoBH1u6r0uRmNJ+kZjRFKv8fyeXp7f08s5S5u5cd0S1ixqLPjakXiSSDxJnxIj6HNRL7vdwjQwEIrx2R/9lv99w67KoyrQWuehq9nP7u5hMitn5wrMs9sZxyW1UJFtZM0WhFqnFDXSUcMw3gG2AWsMw/hX7OBbKIOJnLzyXBo1lXgySTJjDVcV2zykOeChLejNc4QUtzChGLk5+Wm8RQSKi1sCRcdTZ3OAxoCbrtYA8xt8+N12INyREkKC7WJZ73XR1ezn9K4m1mYE1q/s7eez//Nb/s///JZX9/ZhFQk4TMtiMBznUH+Yg30hBkIxEsniQY0gVIodhwe58tvPOYF2g8/FP3x0LResaCVugjvnx1+6hF8hwe94LqmyZgvC7KSUne1RXdfXA1uBD+u6/grgn+CcWct4rmKToZAQzedWCXg0rr77OXxujeGIXevarSns6x3NcujTFDt9xONSuen8JTT48hdwETLOHYqNx2KOk8XElpevXYjRPZx3PD1mJhpPdV4XdV4XkXiS685axLd//SYZm90oisLvndvFOUtb2HpwgA2b9vPK3n4AXj84yOsHt7GyI8gN6xZzwfLWoiLJWNKkbzRG32gMfzrNxOsSUaWQx4mu1Q9tOcitD21z7vqc3F7PDesW8+wbx9h+aJCeoSgJ0yKWNB3b9WI/ZmFil1RZswVh9lFKsP1nwB8BfwXcDOwG/qYKfZrxTOQqVg6JpEl/LInfHSHocxOKJVGAoFdjx5EhBsNjopt6r4u4adJW5+Xj67r4zPqTC7YpQsa5QbHx+Ojrh9m49YhzvJDjZCGx5bNvHBt3zExmPPncGpevXUi918WDWw7y1tER5jf6+cDq+ZyztAWAtYuaWLuoCaN7mPs27eP5Pb2ArSn48iM7OGleHTeuW8xFJ88btw53OJ4kHE/SOxKjzqtR73VnVdwR5i4nslbHEiZf37iT/35xTN9w2er5XH7aAv7jubexsPUz8aRF0rSdIRUFUKCjwcenU3OsHJdUWbMFYXahFLtlm4uu6+8zDONXOceuNQzjoar0bGJKd9ioEIXEi1Ca21duG+lST2n3MDXlMHagP+Tk1wY8Gl+58lTOWdqC16Uyv8GXZxgiVJRKb5NWZcwWG49vHh1GKfAWmus8vPCFqS2Nn0iaDITs8n7FeOf4KBs27ecZ42hW2bRFzX5uWLeY965sn/R4d6kKAa+92+1zz6nAu5JjdtrW2EpR7lp9dCjCpzds4dV99l0Xl6rwZ5eu4OZ3L+MLD21z2kyv20DVnR9nMRUbs+vvesZ653h+Fa7JsKytjqc/d0mlulIzrL/rGcq5Zid6vcp93Uq89glS1nidjKnNxwAvcEeOwY0LuA2YrmB72qiE8DC3jUznRpcK4ZjJ28dHnQoObfUe7rxmDcvb6wl4NNqDPqnMIADFx2MsYRYUEhZznKwmLk2lLeilwe9mMPT/t3fncVJVZ8LHf7f2qt6bBpqGZhHlgIKgIuC+xASNC2rcosaYmGTijJNkMjEZs71ONseJGZNJzJs3xiQuoHGJxiVRo8EFFRBQFoWjgNA0zdL7Vl37ff+4VUV1d1X1Qld3V/N8Px8+dN1bdc+5VfeeOnXvec4Toj3NvNwzKgr47oVzuPHUaTy8dg8vvn+AaMyktrmLO5/X3P/mbq5ZVM35x1X2mfwmkjKbictuw+d24HPZj7SO9xFvMG31ul1N3Lx8A/XtVgr2cYUufrxsLufOmYjLYeu2zdRASMn8KITIpD+XiYqAc1L+T/w7BWtWkoyUUouVUq+kWX6xUuptpdRbSqkvDrjWI2woglh6BUDGOw9FHjttgQgf1nckO9pHjS/gnmtPZOaEQoo9TiYWS0dbHJLpeMzUIc2UcXI4uBw2xhd7qCr14ssw1GNKmY9blyoevGkRy+ZX4bRbx/r+tgA/f+lDrrtvDY+vr+0zO19CKBqjxR+irsUKrGzuDBGWwMojwkDaatM0uf/NXVzz29XJjvbxU0p46KZFfCLlB17qNlPPMcn8KITIpD9JbX4H/E4p9TGt9cv93bBS6pvAZ4DOHsudwN3AyfF1byilntFa944YGSHpAmo2721NBpp5nTacDluvObIHEsTSM0DSMMBtNzBN2NnQmZwBqtDtwA785rUdXHvyVNxOe9Zgn8MNBhK5s+xXq/r1mWT7DNOtu2phNbc+tpEmf4hIzMRhMyj3ubjo+KpuY7YTEhknM5UzHMeQx2mnssSLPxShqSOU/GGZqrLYw1fPO4brl0zl0XW1PLOpjkA4RmNHiF+/soPla2q48qQpLFtQRYG7f+EnoWiMkD9Esz+Ex2mnwOWgwG2X4VhjVH+CxO9ZuZ0H39pFfXuIaMqwygKnndomPzf9cR3XLZnGvMklPLpuD+/XtdHYGaLM50xm3IXumR9DkRhX/7+3CISj0g4LIQYUILlDKfV3YDpwBrAC+LzWelem5wOXAw/2WD4H2K61bgZQSq2Kb++xAdQlZ9IF1Nz62Eaa/eFkkFZXOEZHMEqZz4XbaT/sIBbDgGKvg46uCC0dh27x+1x2JhW7cThstPsj/PivWwGSCUd6BvvkInBTDJ2Y2fdnku0zBNKuU5VFNPvDyVk/YjErGHJGRQG3nHt0xiDIdNvavLe120wJuT6GfC4H3jI7bV0RWrpC3dLAJ4wrdHPz2TO5dtFUnninlic37KUzFKW1K8zvVn3EI2/v4bITqrj8xCmUeDPPAtFTYv7uxk6SM5oUSOKcMaWvIPF7Vm7nf1/+kFA01m2Ka6fdmumpKxyjKxzjFy99SFmBkwlFHgrcDmKmSbM/zLhCF/OnlNDiDyczPxZ7HNQ0+alpgonFbmLSDgtxxBtIZ/s3wE+BO4EDwMPAA8CZ6Z6stX5CKTU9zapioDXlcTuQPpvFCHh03Z5ey5r8IWIxus2IYLcZtAUivPm1tLvfr3KKPE5KvE4MrBS9HaFDt8VnVBTgMMDltOF22AlGY8lAyXTZ/c6cNT5t3VPXi9Ej02eS7TPMFMz83KY67Daj14wdy9fU8OZ/nJs242Smcpav3p024UYujyHDMCjxOSn0OGiNj7OOpdnXEp+Tz582g6sWVvPUO3t5fH0tbYEIHcEID66u4bH1tVwyv4qrFlb3mnO+L8kZTQxrRpMCtwOfayDNoxitsmW7ve/1nb0SOXkcNqKmmUy+BFbmyKbOUPJuZiIzb2rG30Tmx9Tx2s3+cLK9lnZYiCPXQO6dVmitXwTQWpta63uxOs4D1YY1/juhCGgZxHZyIl1ATSRmEksTmH84gWZ7mvw4bFYjvqO+M9mRNoDvfHI2bruB22nHbbcTjlplJ25P9pQt62TqejF6ZPpMsn2GmdYFMmSry3Z8ZtpWS4bMksNxDNltBuUFLqrLfZQXuLBlmDO70O3g+iXTePhLS7j5rKMYF+9YB8IxHl1Xy6fvXc0vXv6QA22BAdchZpq0ByLsbw2wu7GTho4gXaFoxh86Ij/FYia/fPlDmlKOd5thJXsKxtOud3s+Ztq7LunaXgmaFEL0NJDOdpdSagrx6aCUUqcDwUGUuRU4RilVrpRyYV0Zf2sQ28mJdAE1DpuBLc1sL4cTaDZ9XAFd4Rg76juSMzPYDFgwtZSPzZnIjPGFOOxGMiU2kDEjWaaskz3Xi9Ej02eS7TPMtM4ziEDITNvKlt1uuNhtBqU+q9Nd5Ml8ddnrtHPlwmqWf2ExX/3YMUwstq7Ih6Mmf3m3juvvW8tdL2j2NncNqh7R+Iwm+1q72N3o52BbgLZAWLJW5rm2QJgvPbien/39g+Qyl91GicdBIBwDs/fcXolkNT2la3slaFII0dNAOtv/BjyL1VF+F2vM9lf6+2Kl1LVKqS9prcPA14EXsDrZv9da7x1APXLqqoXVvZaV+1xpG9pEoNlAtQfCzKksYkd9B11h64vbYTOYWubjmpOrKXA5+PTJ1fT8Tk8E5PSUCPZJV/fU9WL0yPSZZPsMM6278PiqtMuzHZ+ZtnXdkmkZyx9udpvB+CIPU8qyd7pdDhvLFlTx4OcX8c2liillVmLbaMzkr1v289k/rOXHz20d9JyuYF3x7ghGaGgPUtPkp66lixZ/KO2dJjF6fXCgnWW/eoOXth4ArE52gcuOx2kjELEubKQbkpW469JTurY3tY1O/VvaYSGOXP2ZZ7sKuAs4DngbK5NkK7BNa511HEU8eHJJ/O8VKcufAZ4ZdK1zKF1Aza1LlTUbSZpAs4Fq6gjy1s5GfvPazuStSo/TxknTyrlk/iQ+NnsiFUVuJpZ4wDB6Bfb0rFtqsI9kjBzdbDajz8+kP59hunUzKgoGdHxmK6ev7HbDzeWwMb7IQ7E3SlNHKOOUfw67jfPnVvLxYyfy6gf1rFhTw86GTmImvLztIC9vO8hpR4/j+sXTUJVFabfRX4ngyqbOEG6HLTnGu6/5v8XIeXZTHd98fBP+eGzMURUF/M9V83ljRwPL1+zpdu5A7+yq2c6LnufTxBIPhgldkdioOIeEECOrzwySSqkXgM3ASuAKAK3153JftT7l1SDKWMykvj3IC+/t58d/3ZoMyjlt5ji+c+EcPE475QWuEZ0DWfSSFxkkjzQdwQgtnemnC0wVM03e2tHIQ2tq0Pvbu61bNL2M65dMY+7koY3Ndjts+FwOCtwj1vGWDJI9RKIx7nx+G/e+/lFy2bmzJ3DH5XOZWOwdwZqJOMkgOYIkg+SA5SaDJDBZa70UQCn1IvDuYAo6koWjMQ60Blixtob/+8qO5DfY5SdM5uazZ1rZ9QplPHxxAAAgAElEQVRdvWYZEUL0Vuh2UOCy09oVpsWffuYSAJthcNrRFZw6cxzrdzfz0JoaNtVaEyGt3dXM2l3NzJ9SwnWLp3LStDKMDAGZAxGMxAhGrHm8JXPlyGvoCHLLig2s3tkEWHExt5xzNP98zkw8TpltRggxPPrT2iSHimitw0qp4c/1nMcC4Sh1LV386h/b+fM71tB0A7j57JlccdIUbIbBhGK3TDMmxAAYhhVEWeh20NyZPv176nMXTi9n4fRyNtW2sHxNDW/vagZgY20rG2s3M2dSEdcvnsaSo8qHpNMNhxLotPjBabPhcdnxuex4nXaZy3sYvFPTzD8v38C+VmtWmjKfkzsun8cnjq2U918IMawG08MbE7cWh0NbIMze5i5+9Oz7vLGjEbDGn37nk3M445gK7DaDicUeueolxCA57Fb698JQlMaOYJ9DS46fUsrxU0rZtr+N5atrkufl1n3tfOepLcwcX8B1i6dyxjHj0wZFD1Y4FiMciNEeCGMYBj6nHY/LToFLslcONdM0eXjtHm5/+r3k8XDspCJ+fvUJzDrMsfpCCDEY/elsH6eU2pnyeHL8sQGYWuujclO1/GWaVgKEjxo6+c5TW5LjRUu9Tn506VyOrSrGZbcxscSDU75ohThsXpedyWVeWvxhWrrCfc6LPbuymB9eOped9R0sX1PDqx/UEzNhR30nP3h2K9Vlu7h28VQ+NnvCkHeGTdOkMxShMxShESt1vc9lJdKR9uDwBMJR/s9f3uNPKUmbli2o4geXzKUkw7SWQogjyw33rWHPIKaErS7z8sBNiwdVZn8627MGteUjVDRmUt8eYOu+Nm778xb2xxNrVJd5uePyeVSVenE7bFSWeIf0ypkQRzrDMCgrcFHgdtDYEcw4a0mqo8YX8r2LjuXGJj8r1tbw0taDRGMme5q7uPN5zf1v7ubTi6pZelxlzgIeU2c28Trt+NwOCt0OaR8GaG9LFzc/tD45Lt9pN/jW0tnceNp0uXsghEja09x1WFPBDkafnW2t9e7hqMhYEAhHOdgWZP3uJr73l/foiI8jnTe5hB8uO45irxOfy86EIo+MGRQiR1wOG5NKvbQFwjR1hDIGUKaqLvfxrfNn89lTp/PI2j38bcs+wlGT/W0B7n7pQx5YvZurF1Zz0fGTcjrsK5E2vqkzhM9px+e2U+BySHvRhze2N/CvD79DU6cVUjSx2M3PrpzPaUdXDNkYfCGEGCyJyhsiHcEI9e1BXnp/P//9gk7OoX2OGs+3zp+Ny2GjyO2gosgtjb8Qw6DY46TA5aCpM0h7IHMAZarKYg9fO+8Yrl8ylcfW1fLMxjoCkRiNHSF+/coOVqyp4YqTprBsQRUF7tw1n6lDTRqMEIUue3JmE2k/DjFNk9++tpM7n99GItnuwmll3H31fKrLC0a2ckIIESed7SHQ1BmiuTPIirU13LdqV3L5tYuq+fzpM7AZBqVeJ+WF7pGrpBBHoEQWyiJPlIb2vgMoEyoK3dx89kyuXTSVxzfU8tQ7e+kMRWnpCvO7VR/xyNt7uPyEyVx24mRKvLkdC2yaJu3BCO3BCDbDsGY0cdnxuY7soSYdwQjffHwjf928P7nsM0umctsn58jsTkKIUUVapMMQi5k0dARp8Yf4+csfJht9mwFfO+8YLoqn0R5X4JbgHCFGkMdpBVA2d4Zo6Qr3+3UlPic3nT6DqxdW89S7e3l8fS1tgQgdwQgPrN7No+v3sGx+FVcurE6bznuoJdLGW0PUgsngSq/Ljttx5MxqtKO+g396cD3bD3YA4HXauf2SY7nypGoZciOEGHWksz1IoUiMg20Bmv0hfvDs+8l5e71OO9+/eA6LZ4wDYHyRW5LVCDEKGIZBeaEbXzyAMpHFtT8KPQ6uXzKNT504hWc31fGndbU0dYYIhGP8aV0tT75bxyfnVnLNydVMKPbkcC+6SwRX0mnN5f3a9vrS6xZPaxm2CoyAF97bz78/ujEZEzO13McvrlnACVPLRrhmQgiRnnS2B6ErFOVAW4ADbQFue3IzO+utqNZxhS5+culcjplYhGEYjC9yU5jDcZ1CiIHzOO1UlXpp7QrT7O97msBUXpedKxdWs2zBZP62ZR8Pr93DwfYgoUiMp96t49lN+/jEsRP59KKpTC4b3lTg4ViMtq7ImG1wojGTn72o+fUrO5LLzppVwV1Xzmd80fD9wBFCiIEasw3zUHvtg3oeXbeHA20BCj0Ojp9cwvI1NTR0WNHvMyoKuOOyuUwo9mAYBhMlK6QQIy5x3u5p8lNd7uOqhdWcOWt8MgNlYppAf6jvaQJTuRw2li2YzIXzJvHS1oOsWFtDbXMXkZjJX7fs5/n39nOOmsC1i6cyo+LICtTL9J4fjubOEF955B1e/7ABsIbqffmso/jaebNwHUHDZ4QQ+Ul6g/3w2gf13PXCNhx2Gx2BCHXNXbyq65PR7ydNLeX/XHIchW4HNsPKCul1yReAECPptQ/q+ekLOvl4d6M/+TjR+XParTnv2wNhGvs5TWAqh93G+XMr+fixE3n1g3qWr6nho4ZOYia8vO0gL287yOlHV3D9kqnMmjj2sxf25z0fqC17W/nyQ+upjSehKPE6+cmlc7lg3iQZny2EyAvS2e6Hx9fvAQw6AhFau8IcaA8m151/XCVf//gxOOw2bIZBZYmkXxdiNHg0JYtgqsfW1/bq+BV5nHiddpo6Q8mxwANhtxmcO3sCZ6vxvLWjkYdW16APWJljV21vYNX2BhZNL+P6JdOYO7lk4DuTJwbynvfHE+tr+faTm5Pj62dNLOQX1yxgzqSx+x4KIcYe6Wz3wR+KsLO+g2A4RmNniCb/oZkMKgpd3Lp0FoZhYLdZHe0jaUYAIUazPU3+tMtrMix32G1MKPbgC0Zo6ggRifU/gDLBZhicdnQFp84cx7rdzTy0ejeb97YBsHZXM2t3NbOguoTrF0/jhKmlY27O7IG+55mEIjF++Oz7PLj6UE61T86t5MeXzaWsQKZQFULkF+lsZ9HcGaLZH6K8wM07NS20p1zxqix2M6eqBMMwcNhsVJZ4cpbOWQgxcNXlPnY39u7kTS33ZX1doduBL36Vuy3Q/2kCUxmGwcnTyzl5ejkba1tYvrqGdbutGYve3dPKu3s2MWdSEdctnsopR40bM53uwb7nqQ60Bbj5ofVsqLEmVXHYDL523jF88YyjcMtdQyFEHspZZ1spZQN+DcwHgsAXtNbbU9Z/HbgJqI8v+iette61oREQjZk0tAfpDEVoD4Spbe5KdrRtBlSVeDCBxo4gX3vkXaZX+LjipMMPAhJCZDeQ4LurFlZ3Gz+ccOVJU/osx2YzqChyU+R10NQRois8sADKVPOnlDL/ilK27W9j+eoa3tjRCMDWfe1896n3mDm+gOsWT+OMYyryPklNz/e8PWDN+NIZDHPLig19Bkuu/aiJf16+gYYOa6heRaGL//7U8ZytJsj4bCFE3srlle1LAY/W+hSl1BLgZ8CylPUnAjdordfnsA4DFoxEOdgWJByNsa+1i9v+vCV5C9TjsDGp1EOxx2l9GZhgs8FHDYcfBCSEyG6gwXeJZY+tr6Wmyc/Uch9XnjRlQOeo22FnUqmXtkCYpkEEUKaaXVnMDy+dy876DpavqeEVXY8J7Kjv5AfPvs/Uch/XLqrm3NkTcNjz8y5Z6nv+3t5Wmv1hynxOCtzOrJ+XaZr88c1d/Pi5rUTikefzp5Rw91ULOGpC4fDuhBBCDLFcdrZPB54H0FqvVkot7LH+JOA2pVQl8JzW+o4c1qVf2gNhGjpCmKbJtv1tfOfJLTTHx2jPmljITy6bR3mBix88+z6maV3lTs3+PNggICFE3wYTfHfmrPFDck4We5z4nHaaO0PdhpMNxlHjC/neRcdy46l+Hl67h79vPUA0ZlLT5Oe/ntfc/9Zurjm5mqXHVebl0LTEe37Lig1ph5T0/Ly6QlFu+/Mmnnq3LrnsqoVT+O6Fx1LslYRgQoj8l8uWvBhoTXkcVUqldu4fAb4MnAucrpS6KId1yco0rWEj9e1BTNPkje0N/NufNiY72qccNY67r16QTMfc1hXCMCDa4yLXQIOAhBD9N1TBd4PlsNsYX+yhssSDw3b4TWd1uY9vnq948KZFLJtfhdNuDZPY1xrg7pc+5Pr71vDEhlorQ2Qe6s/ntbuxk8t+/Uayo+1x2PjPi4/lx5fNk462EGLMyGVnuw1InVjWprWOACilDODnWusGrXUIeA44IYd1ySgSjbGvNZAMhPrzhlq+/5f3klNNXbqgih8sOw5vPDCn0O1gcqk3Ocd2qoEEAQkhBqY6w/k13Oedz+VgSpmX0iHqDFYWe/jqecew/AuLufKkKXjiV7MbOkLcs3IH1967hhVraug8zCvqw62vz2ulPsjFv1zFtv3WFIlVpR7+cOPJ3HDqdJx5OoxGCCHSyeUwkjeAi4FH42O2N6esKwa2KKXmAJ1YV7d/n8O6pBUIW2nXozGTaMzkN6/u4IkNewEwsDKUXXHSFAzD4O1dTbz+YT17m7twOezsafLTGYoQiZk4bAblPhe3LlVZy/vGYxt5dlMdwUgMt8PGRcdXcdeV8zM+PxeZ2ITIV9kCHu9ZuZ3lq3cnxwhft2Qa/3LO0YMqJ9N5l275ohnlNHYE+f0bu3jm3b20BiKUeBxcvGAy1y2eOqByKwrd3Hz2TK5dNJXHN9Ty1Dt76QxFaekK87tVH/HI23u47IQqLj9xCiU9Ovpv72rib1v28/au5hdvPnvmiYPa8X5K9z48vbEu2bY5bVZiL6fdxv62AACmaWXdLPM5URML+cTdr/LBgY7kNpccVc5Pr5ifsYMuhBAJ+RgrncvO9pPAx5VSb2L1XT+nlLoWKNRa/1Yp9W1gJdZMJS9rrf+aw7r00toVpqnTGp8dCEf5yV+3sWq7lQrY5bDx7QtmJzu2b+9q4tG39xCOmphAXUMnrV1hErN1xWLQ7A+zeW9rxs7wNx7byBMbapOPg5FY8nG6DncuMrEJkc8yBTxu3tvKr/6RnOiIZn84+XigHe5M593mva08v2V/r+W3LlVsrm3hqQ21BOMBHK2BCA/F54ceaIcboMTn5KbTZ3D1wmqefHcvT6yvpS0QoSMY4cHVNTy+fi+XzJ/ElQurKS9w8fauJu57/aP4q82cXhJO9/585eF3aO0KW628CaGoyZ7mLgrddiJR60JGYpaVzmCEe1bu6Da7y/hCF184fYZ0tIUQ/VJV6uWG+9awJ55VdiBOnlaWgxr1LWedba11DGtMdqptKesfBB7MVfmZxGImjR3BZJBTsz/Ed5/awtZ91q3MEq+TH116HMdVHcpQ9ub2RkIpA7Sb/CEwwMDAnRLAtHxNTcYv92c31aVd/tymfWk720OdiU2IsSBdwON/PLEp7XOznY+ZZDrvlq/Zzbg0yVQeW1/L+l1N+MMxnHaDQpeNznAU04RnNtYNqrOdUOhx8Jkl07jixCk8s6mOR9fV0tRpTUP4p3W1PPluHZ+cW5m8ejwc0r0/rYEwJsm+dlJHMIrXacduM3A5bEwocrOjviM5BM9mWENKyn0u/rJxH+cdWzkcuyCEGAP2NHfxUUPngF83pcybg9r07YhKahOKxDjYFiAUvwJV0+Tntj9vZl+r9WU1pczLHZfNY3LKh1Fe4GJXY/cPNDE1VYzuA7db/KGMZSfGgPdenj74aaSDwYTIF83+9Ilnsp2PmWQ675r94bSd7Zomf7L8cNQkHDXxOe1ETXPQCXF68rrsXLWwmksXTOZvW/bx8No9HGwPEorEkoGFxR4H5T7XkJSXTbr3pz+zIfpDEXbUh5MdbbfDxszxBTjtNsLxmViEEGKsOmKiUDqDEepaupId7U21LXzl4XeSHe25VcX88poTunW0xxW6KfW5et3edMRvidroPnCoNMuXnTvDFF6Z0ruPlmAwIUa7Ml/6QMVs52Mmmc67TGVMLff1WtcVjhGOxKgq8WIbwsyQLoeNZQsm8+BNi7h1qep2haYtEGHXMHRY070/2XbRNE1C0RjhqJnsaDtsBsdOKsJhsyWXSbsmRlo+jgMW+WPMXdlOF7zjD0b407o97GvporLUS1WJh8fW1xKODw2ZN7mEUp+T2/68icpSLxfOncT58yop8lhfolctrOb7f7Hm3A5FYtgMA9M0iWLSFY5iAHabkfWW8UXHV3Ubs51w4fGT0j6/Z5mJ4KL+ZL8TY1e+Bc0OR32vWzKNX7z0IdGYSQwTG0byfBxo4GSmIMzrFk/jgbd20dQZOhQUXWAFRc+uLOo2ZhzAxOBTJ01hSpmXxo4QnaGhm0nEabdxwdxKPnHsRF79oJ57X9/JgbbgkG0/m6sWVnPrYxtp8lvvA+ahoSM9r3D7XDa6Qt3v/xW5HUwqddPzRp+0a2KkHc444OoyLw/ctDgHterbYOsMIzd++Ug0pjrbPYN3apv9/PCZ9/CHoxS4HJimyZbaVl7R9cnnnDWrgrrmLg7EA3b2t3bxp7f3MLHEk7FTMJgfwIlx2c9t2kcwEsXtsHPh8ZOyzkYiRKp8C5odrvrOm1xCmc9Jkz9ELGZldS3zOfmooZPnNu1LPq8/gZPZgjCbO8PE4p3EWAyaO62g6MS2lq+pocUfotTn4rrFU5PLJ5Z46AhGaOwIEk03Z+gg2W0G586ewNlqPA+8uYvn3zuAPxTN6aTcm+NZIWOx7MNH7AYEwt072iUeBxOK3SxbMIVt+9sHndVTiFwZ7DjgkXQ4dR6p8ctHojHV2U4N3nHaDUKRGPviV3x8TjsH24O0Bg5dYfrqx45hY20LRvw+qN1u4HXaCUZj3QIRH123hyKPM3mle9v+NgzDGkbi6meAJFgd7v52rnuWmSABkkeufAuaHa76PrpuDxOKPUwo9nRb/uymOow0P437Ok8zBWHabUZyVo2e20r8y6TQ7cDrtNPUGaQ9MLTzZdsMgxtPm8GNp83ghfcOLB3SjfewfPXu5PvQlSXZTizlirfHYWPmhAKcNhtRE7btb+eXnx6RtApCCDEixtSY7UTwjsthwx+KEIrECEdjhCJR9rYGkh1tw4AppV6WLahif4t1+8UR72gnhpakBuz0DAoaTIDkYPelJwkkOnLl2zExXPXNVE6moOTBnKdDEYRptxmMLxq6DJQjIdP70FOiZSzxOpkTH5+dmNBptB6vQgiRK2PqynZ1uZd9LQHauw59IdhtBoFwjMTdVbvNYHKJh5kTreSWlaVeDrYF8KR0tKF7wE51uY/djYe+IBw2g0jMHFCA5MD3pXuZ6eoljiz5dkwMV30zlZMpKHkw52mZz5m2ozmYbVkZKO00+0PW/NR5JNP70JOBNUPK0eMLk0HpCaP1eBVipOTbnNFi4PK+s53IyhiLgddpEMNgUvx2cjASJRiOdkutHo2Z7Gu3rnJf8IvXKXLbCcditAWsuXENAwpcDnwuO8t+tYrqch9zJhXz0tYDBMLdvzQSAZIJjkCYOd97njKfk1OPriAQjnYLDNu8t7VbsNZREwrZebAjbfBWpkCt2ZVF3LJiQ94EyImhky2D4khLFwh51cJqvvrIO7R0hZPnVqnXmcy0mil48cL/fZ336tqS2z6uqpjnvnJG1nJu+uPbhFNOdKfNYNkJk3lyw16iKYOL7cahQOZM5adbni0Ic6Dvy5mzxmOzGYwrdFPgdtDQHuzWIU1kg9wfD+i+YG4lJ08vP/wPaYAS7V+izves3E57IJx1+EiCw24QjMZYX9OMDXA77ckgb2nDhOgu3+aMFgOX153tRFZGt8OGYUBrwPoSKHCFcdpt1LUGiKYJ4glHTNoiYQo9DtqD0W63m00TOoIR9P725BWzv79/IOMt6VSdwQhuh52GjhBPbKhlQpGbCUUedjf6ufXxjTR3hpNjPg+2B6lrDeCwGTjttl7BW+kCtWZXFqXNYgejM0BODK1MwXsj/dlnCoQs6XEV1DStYQhPb6zLmPXx/jd3cbC9+8wa79W1ceH/vs63zp+dtpwDbYFuHW2AcMzkr5v3detoA0RNk48aOrln5fa05b+1s5H1u5p7Lb/w+EmUFTitrLOJIMwCJ/Mml5BJfwJEPU47k8u8NPvDtPhDPbJBQl1zV/LxcHe4Y+ahOj+9sY7nNu0j0I+OttdpIxojeXEiBnSFo7gcNrpCUR6Lx6OAtGFC5CuZKnFg8rqz/eymOnxOO8FILDmOGqChI4QJWSP/3U4bmN3HdRrGoQj71kCY6vjybB3t1NckikuU29QZYkKRJ/l3LEays514TjRm4kyZajs1eKtnoNYtKzakrcNoDZATQy9d8N5IyxQI+eb2hrRzMD+3aV/Geat7drQT3q9ry1hOptf4Q9EBl//W9gZcaea+f25THUdPKEqezwnZzr3+BogahjWNoM9lZ6U+mPY1z793YESubickgk37mkulwGWnq8fdxISp5T5qmvwEIjEJ/BYiz+VjyvSRlNedbYfNRkewd2R/pI/ptTxOG9GYmfWroz9Z0TJJBE6mdvZ71sns8X9CtoCrfAuQE0eGTMdlzEyf8CQYidI8wEPWzFLOQGUrP92dMIBAhh/c2c69gZ6vHqedA60BirwO/KEo0ZTK7GsZ3Dy6QyUUiWVMwAXWVS6fy5G2Pe65nXSkDRMi/8jwl/7Lz5B4oL49QLYpZe02g2+dr3A5un/be512ojGzWzBkOoeT+C0ROJk6TZjDZnQLqDR6/J+QLeBKskqK0SjTcZnpNqPbYc94ZTkTI0s5A5WtfHuGOnsyBFtmO/cGc75OLvMRiph4HXZ87kOd20mlI/vl5Mqw/2CNj3c77H12tBPbSbctacOEEGNZ3na2v3j/Osq86TumDpvBnZ+ax9LjKjlHTUgu97nshOOpgxMdgdQOQerVbNO0EjhsqWsd0JsUiEQxTWuS2fKCQ/UrL3B163wn/u45b2+2gKurFlanXT4aAuTEkSvTcXnq0RWYJr3+XXj8JK5bMo1gJEpX+NC/YCTKhCJ32m0dW1WcsZxMr/G50l+JTZSfzilHV2R4TVXa5dnOvb7O19c+qOeWFRtY9qtV3LJiA699UJ98TThmEotBkceJy2Hj/OMmZiwnl9oDYWqa/HgctrTjtT0OG4aRfc5tODQzTJnPmfaHjrRhQoixLG+HkcRMaw7XjmCEztChht7jtHHPtScyo6IAgG+dPxuAdR810RqI4LTbUJUFyYCkMp+Ljvic3OmGjiSWlXidtHWFMYlPa+V1EorECEaiOO02bDZr2Eg0ZmK3GxS4HcwYV0BXJMbUch+3LlXWbCTxLHMTij0cNb6AnfWdabPOpTNaA+TEkS1b1sU3tzd0G79rM2BGRQEfNXT2GtcbM61tbd3Xxvt1bclz7diU2UjSlXPmrPGc9d8r2Z0yFGFauY9Xv3kO33hsY9asremyPt6zcnva5a99UD+gcy/b+ZopePLWpYpbl6rka6rKvFxx4mTmTSmltSts/ZAfJp3BCM3+MMUeB83+cK8hbwUuO4FIrM+smCVuB9MnFCb3H6QNE0IcWYzhbLyH0iW/XGW2+EPsbQ0kG/tjJhTyk8vmMq6w+5WuIreDiiJ3MlNkqltWbOg2R++WutZkBzv16R6Hna0/PD9tXXpuI2F6RYFkSstvQx1vnZ8n2yCdesfLaedkLitw0dQZTBt4nO08G0sG02aEIjGaO0N0hjIP13jhvQPjbz57ZsMQ1dHctq+dmqZOQvFhd3YD5lWXcv/nFvGdJzezu9HP5r2taV9vNwx23PHJoaiKGNuGrJ09565XzMGmLj/jmApqBzkGeUZFASu/cfagygU4565XBlXu4dT5cF8/Uq8dybLjn/Ogjte8vbLd1hVmT3NXsvey5KhyvnfhsXh73Dou9jipyHCbGXoHMWX67RGMZL5NKoGLQvSWLetiphl+sp1nY8lg2gyXw8bEEg8dwQhNHSEisb6nIz0cG/e0UJvSxrodNqaWe3EYBiVeZ58Bqz2nXRRCiCNVzjrbSikb8GtgPhAEvqC13p6y/mLg+0AE+L3W+t6BbH9XSkNfVerlh8vm9hr/XOJ19rrK3VPP7HOpU/mlyhaJn2+Z/YQYDtmyLsYyXNnOdp6NJYfTZhS6Hficdlq6wjkdWpI6pVexx8HUch9Ou5EM1sy0Dwn2w4kyF0KIMSSXAZKXAh6t9SnAfwA/S6xQSjmBu4FPAGcBX1JKVQ6mkIoCF185d2avjnapz9VnRxt6BzGVxOd/7fk1ceHxk/q9jQQJ+hFHskxBiNctnspFGQIOs51nY8nhthk2mzU39+RSL15n7n6gGFgBqDPHF2K3GURih+qY2IeCDIGopxw9Lmf1EkKIfJLLYSSnA88DaK1XK6UWpqybA2zXWjcDKKVWAWcAj/V344nAqRtOmdYr2UN5gSvrFHqpegYxnTFrPM3+EOt3NWcMquprGxL0IwTJYN90wYYJ2YIXx7KhajNcDhuTSr20+sM0Z5mjfzCuPrmaCUUuapq62NXoZ+q4gm51TN2HldsO0BmMYmJd0T7l6HE8dNPiIa2PEELkq1x2touB1MiZqFLKobWOpFnXDmTOe5zGY18+pdvUegnjCt2UeAc2h+9QZOUbjZn9hBhp/3LO0Rln2LnryvlHTOc6naFsM0p8Tgrcdo6ZWBgYkg0CP7lsHsFIFJ8r89eEtHtCCNG3XA4jaQOKUsuKd7TTrSsCWgay8ck9kjwYhsH4ooF3tIUQYixw2G2cN2dix1Btz24zsna0hRBC9E8uO9tvAJ8EUEotATanrNsKHKOUKldKuYAzgbcGW5BhGEwoclPkkY62EEIIIYQYPXJ52eJJ4ONKqTexhlh/Til1LVCotf6tUurrwAtYHf7fa633DqYQm2EwsdjTa8o/IYQQQgghRlrOOtta6xjw5R6Lt6WsfwZ45nDKsBkGlSUePDmMxhdCCCGEEGKw8nZAnsNmUF7qOWLm5RVCCCGEEPknbzvb4xMpJlUAAAytSURBVArd2GySNEEIIYQQQoxeuQyQzCnpaAshhBBCiNEubzvbQgghhBAjTa79ib7k7TASIYQQQoiRVlXq5Yb71rCnuWvArz15WlkOaiRGG+lsCyGEEEIchj3NXXzU0Dng100p8/b9JJH3ZBiJEEIIIYQQOSJXtoUQQgiR96oP4yrxpGIPgx16nY+vHcmy87Xeh3N8GaZpDvrFQgghhBBCiMxkGIkQQgghhBA5Ip1tIYQQQgghckQ620IIIYQQQuSIdLaFEEIIIYTIEelsCyGEEEIIkSPS2RZCCCGEECJHpLMthBBCCCFEjkhnWwghhBBCiByRzrYQQgghhBA5Ip1tIYQQQgghcsQx0hXIF0qpd4DW+MOPtNafG8n6ZKOUug24BHABv9Za3zfCVepFKXUjcGP8oQdYAFRqrVtGqk5DQSnlBH4PTAfcwI+01k+nrL8Y+D4QAX6vtb53mMv/OnATUB9f9E9aaz2E5duBewEFRIHPaa13pKzP9f73VX5O9z9exgRgPfBxrfW2lOU53fd809exmq8yff75KB++S3JFKWUDfg3MB4LAF7TW21PW57wtiZezGLhTa312j+XD0p5kKT/X3yVj6rtUOtv9oJTyAPQ82EYjpdTZwKnAaYAP+MaIVigDrfUfgT8CKKXuwTpZ8rqjHXc90Ki1/oxSahzwDvA0JE/eu4GTgU7gDaXUM1rr/cNRftyJwA1a6/VDWGaqiwG01qfFj8X/AZbBsO1/xvLjcrr/8X38f0BXmuW53vd809exmncyff75KF++S3LoUsCjtT5FKbUE+BnD2JYAKKW+CXwGq81IXT4s7Umm8uNyvf9j6rtUhpH0z3zAp5R6USn1j/iJN1otBTYDTwLPAM+ObHWyU0otBI7TWv92pOsyRB4DvpfyOJLy9xxgu9a6WWsdAlYBZwxj+QAnAbcppVbFr1oNKa31U8CX4g+nAQdSVud8//soH3K8/8BdwG+Auh7Lh+Ozzzd9Hav5KNPnn4/y6rskB04HngfQWq8GFvZYn+u2BGAHcHma5cPVnmQqH3K//2Pqu1Q62/3jx2pElwJfBpYrpUbrXYEKrEbhSg7V1RjZKmX1beA/R7oSQ0Vr3aG1bldKFQGPA99NWV3MoaFIAO1AyTCWD/AI1nFxLnC6UuqioSw/XoeIUup+4JfxOiTkfP/7KB9yuP/xoVH1WusX0qweln3PJ/04VvNKH59/Psq375Kh1vOcjfb43h+OtvQJINyPuuWqLc1UPuR4/8fad6l0tvvnA+AhrbWptf4AaAQmjXCdMmkEXtBah+LjhwLA+BGuU1pKqVJgttZ65UjXZSgppaqBlcCDWusVKavagKKUx0XAkA+dyVR+/Ivy51rrhvjVgOeAE4a6fACt9WeBWcC9SqmC+OJh2f9M5Q/D/n8e+LhS6hWsGIQHlFKV8XXDtu/5JMu5ko+yff75KG++S3Kk5zlr01pHYHjb0n7WbVjbk+Ha/7H0XTpar86ONp8H5gH/rJSqwvpVtW9kq5TRKuCrSqn/wfpBUIDVaI5GZwIvjXQlhpJSaiLwInCL1vrlHqu3AscopcqBDqz9v2sYyy8Gtiil5mCNczsXKwBkKMv/DDBFa30H1h2hGFagIgzP/mcrP6f7r7U+M6UerwBfThlDmPN9zzd9HKt5p4/PPx/l03dJLryBFQPyaHzo6OaUdTlvS/sw0u3JcHyXjKnvUuls9899wB+VUqsAE/h84hfuaKO1flYpdSawFuvOxb9oraN9vGykKGDnSFdiiH0bKAO+p5RKjPe6FyjQWv82HsH8AtZn83ut9d5hLv/bWL/Ug8DLWuu/DnH5fwb+oJR6DXACXwMuV0oVDtP+91V+rve/G6XUtcBw7Xu+SXesXqC1zvvgwrEgz75LcuFJrDsVbwIG8Lke5/OwtiUw8u3JMO//mPouNUzTHOL6CSGEEEIIIUDGbAshhBBCCJEz0tkWQgghhBAiR6SzLYQQQgghRI5IZ1sIIYQQQogckc62EEIIIYQQOSJT/w0TpdQVwG1Y77kNeEBr/dMh3P7tAFrr27M8ZxdwttZ611CV22P7i4BPaa2/Fc+mdrbW+sZclCWGz0gfu0qp64ArtdaXxh/PxZrz9nqt9fL4sjuwpmDaH9/Wb3ps40bix6NS6j+Bl7TWr8fnQ75da/3KUO2PGDlKqelYScjex5qm1YWVOv1zWuvaDK/5ItChtX44y3ZvB2lfhRCDI53tYaCUmgz8DDhRa92olCoEXlVKaa310yNcvaF0LDBxpCshhs4oOXb/Adyd8ngpVrKBpcDy+LIzgG9prd/ox/bOwpofVYxNdVrrBYkHSqmfAT8FPp3h+acBrwxDvQ6XtK9j3Ej9WJQLGrknne3hUYGVYMMHNGqtO5RSnwUCSqmTsToSPqAB+Cet9UfxA/RdrMxIHuBrWusX4yfBL4FCYAJwR8+DfqD6qMNarI7MeOBftdZ/U0pNwerklGGdkGcBc4EfAIVKqe8Ae4Gj49uYijXp+xcPp55iRIz4sau13qeUalBKzdJaf4DVyf4u8Hg8ba4bKzX7mtQvlXg2ye9ipfbdDXQopW4AFgK/U0pdFi/ipniWvFLgq1rrZw7rHROjzUrgjnTHKzATuAQ4Vym1D6vdkvZVjKSR+LEoFzRyTMZsDwOt9UbgL8BOpdRapdSdgB2oAX4HXKu1PhHrCuK9KS8tji+/FrhfKeUCvgD8SGt9MnAO1kk4aPFtZquDS2t9CvBvwI/iy34B/ElrfTzwODBZa90CfB94Wmv94/jzpgKXA3OAC5RSxx1OXcXwG0XH7j+A05RSXmCG1not8BEwH1gMvJma1VUpVQX8N1aH/xSgKL4/DwDrgC9orRPpl1vjdf0K1jEsxgillBO4AnibNMer1vol4Gng+1rrF5D2VYw+K4G5SqmTlVKrlFIblFIvKqVmKKXOw/qx+AOl1FKl1Fyl1Eql1NtKqd1KqS/3pwCt9T6gQSk1K75oKfA94GyllKGU8pByQSNxUUMp9RmllFZKvQ1cFF+WekFjXnx7N8XrvVMpdfHQvC35RTrbw0RrfTMwHfi/wDRgNfAfWFdWnlZKvQvcCRyV8rJ74699F9gHHA/8O+BRSt2G1TgXHmbVZvVRh+fj/28ByuN/fxx4MF63J4GWDNt+TWvdpLUOAjuwrpKKPDNKjt2Xsa7gnAW8Fl/2d+BsrCsuL/Z4/qlYHfAD8U74Q1m2/VT8//eQY3QsqFJKvRs/Ljdhpdr+I9mP1wRpX8WoMcw/FuWCRg7JMJJhoJS6ECjUWv8J+APwh/g4q2uBnYlbRkopO93H5EVS/rbFHz8KNAPPAI+Q+dZSf9n7qEMg/r+J9aUFEKV/P9RS65/6epEnRtGx+wrwn1hDQhId6xexrgiWA7f0eH7P4y1CZol1coyODd1uwwMopeaT/XhNkPZVjLSq+A8zsIbIrcX6sXgV1o+2xPOK07z234Hz4z8W5zHwCxoXYl0c6XlBo5AsFzQAlFIPAR/LsO0j/oKGXNkeHn6sMYPTAeLjTBdgXSEsV0qdEX/e54EVKa+7Jv78hRwav/dxrF+xfwEuiK+3H0bdtvVRh3RewupsoZS6AGusK1iNv/yAG1tGxbGrtW4GuoDzsY4/sK6ezAYmaa0/7PGSVcApSqnJSikbcHXKOjlOjzzZ2rnU40HaVzHS6rTWC+L/5mitPwu0Ev/RFv/hdhJweprXPgpchhVg+Z0BlvsKsAj4BN0vaCzGunv49x7PlwsaAyCd7WGgtV6JdVXuWaWUxmqAo8DtwJXAz5RSm4DPAjelvPQopdQG4LfA1VrrxGtWKaXexzoBdgEzBlCd95RSHYl/8VuQ2eqQzleBTyml3sHqxCRuc64Fliil/msA9RGj2Cg7dl8BOrXWjfG6xYDtWB3/nvU+APwrVsdlLdYV8YTngd8opU4dQNkij/XRzr0EfFtZU1zejrSvYvTJ+Y9FuaCRW4ZpmiNdB5GGGsXT5SilvoI1rc/7SqkTscaOnTTS9RKjw2g+doUY7aR9PXLF7yC+orWenmbdKVjBsx6siwef1VrvUEpdA/wE+CZW0OwtWMOTNgJLsDrg10P2eeLjZdwJnBsf851Y9hjQrLX+Uvzx7YltxX+g/hDoxLqaHotP/fcN4MvADfG63a61fiXb/o110tkepQbbYVFKrcS6bd/Tbw53CquUMi4A/guIYZ3U/6K13jAU2xb5bzQfu0IcDmlfhRCDIZ1tIYQQQogxTi5ojBzpbAshhBBCCJEjEiAphBBCCCFEjkhnWwghhBBCiByRzrYQQgghhBA5Ip1tIYQQQgghckQ620IIIYQQQuTI/wdwIqafGPA/3AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(Data, kind='reg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. **0** -- No Relationship\n",
    "2. **1** -- Strong Correlated\n",
    "3. **-1** -- Negative Correlated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21f3c5c30b8>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,15))\n",
    "sns.heatmap(Data.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x21f3c8b71d0>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c8b7550>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x21f3c8b7940>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c8b7cf8>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x21f3c8a9e48>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x21f3c8c10f0>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x21f3c8c1470>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(Data.Sepal_Length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x21f3c916860>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c916c18>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x21f3c916fd0>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c9223c8>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x21f3c916518>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x21f3c922780>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x21f3c922b38>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(Data.Sepal_Width)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x21f3c973668>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c973a20>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x21f3c973dd8>,\n",
       "  <matplotlib.lines.Line2D at 0x21f3c97f1d0>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x21f3c973320>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x21f3c97f588>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x21f3c97f940>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(Data.Petal_Length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x1080 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=2,figsize=(30,15)) # create 2x2 array of subplots\n",
    "\n",
    "Data.boxplot(column='Petal_Length', ax=axes[0,0]) # add boxplot to 1st subplot\n",
    "Data.boxplot(column='Petal_Width', by='class', ax=axes[0,1]) # add boxplot to 2nd subplot\n",
    "Data.boxplot(column='Sepal_Width', by='class', ax=axes[1,0])\n",
    "Data.boxplot(column='Sepal_Length', by='class', ax=axes[1,1])\n",
    "\n",
    "# etc.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load The Data From Github"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. **Step-1:** Go to any Github Url and [Data Set](https://github.com/reddyprasade/Machine-Learning-Problems-DataSets)\n",
    "2. **Step-2:** Select the Data [Data Selection](https://github.com/reddyprasade/Machine-Learning-Problems-DataSets/blob/master/Regression/Automobile%20price%20data%20_Raw_.csv)\n",
    "3. **Step-2:** Click On Raw Data \n",
    "![](https://lh3.googleusercontent.com/-UR_u5QzIvV8/XrDN1pRwYzI/AAAAAAAAn9s/BQ8qac0D3q0HT1MC8RG3iIMiwuMFHyuYwCK8BGAsYHg/s0/2020-05-04.png)"
   ]
  },
  {
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   "metadata": {
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   "outputs": [
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       "      <th></th>\n",
       "      <th>symboling</th>\n",
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       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
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       "      <td>mpfi</td>\n",
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       "      <td>8.7</td>\n",
       "      <td>160</td>\n",
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       "      <td>volvo</td>\n",
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       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
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       "      <td>173</td>\n",
       "      <td>mpfi</td>\n",
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       "      <td>145</td>\n",
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       "      <td>106</td>\n",
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      "text/plain": [
       "     symboling normalized-losses         make fuel-type aspiration  \\\n",
       "0            3                 ?  alfa-romero       gas        std   \n",
       "1            3                 ?  alfa-romero       gas        std   \n",
       "2            1                 ?  alfa-romero       gas        std   \n",
       "3            2               164         audi       gas        std   \n",
       "4            2               164         audi       gas        std   \n",
       "..         ...               ...          ...       ...        ...   \n",
       "200         -1                95        volvo       gas        std   \n",
       "201         -1                95        volvo       gas      turbo   \n",
       "202         -1                95        volvo       gas        std   \n",
       "203         -1                95        volvo    diesel      turbo   \n",
       "204         -1                95        volvo       gas      turbo   \n",
       "\n",
       "    num-of-doors   body-style drive-wheels engine-location  wheel-base  ...  \\\n",
       "0            two  convertible          rwd           front        88.6  ...   \n",
       "1            two  convertible          rwd           front        88.6  ...   \n",
       "2            two    hatchback          rwd           front        94.5  ...   \n",
       "3           four        sedan          fwd           front        99.8  ...   \n",
       "4           four        sedan          4wd           front        99.4  ...   \n",
       "..           ...          ...          ...             ...         ...  ...   \n",
       "200         four        sedan          rwd           front       109.1  ...   \n",
       "201         four        sedan          rwd           front       109.1  ...   \n",
       "202         four        sedan          rwd           front       109.1  ...   \n",
       "203         four        sedan          rwd           front       109.1  ...   \n",
       "204         four        sedan          rwd           front       109.1  ...   \n",
       "\n",
       "     engine-size  fuel-system  bore  stroke compression-ratio horsepower  \\\n",
       "0            130         mpfi  3.47    2.68               9.0        111   \n",
       "1            130         mpfi  3.47    2.68               9.0        111   \n",
       "2            152         mpfi  2.68    3.47               9.0        154   \n",
       "3            109         mpfi  3.19    3.40              10.0        102   \n",
       "4            136         mpfi  3.19    3.40               8.0        115   \n",
       "..           ...          ...   ...     ...               ...        ...   \n",
       "200          141         mpfi  3.78    3.15               9.5        114   \n",
       "201          141         mpfi  3.78    3.15               8.7        160   \n",
       "202          173         mpfi  3.58    2.87               8.8        134   \n",
       "203          145          idi  3.01    3.40              23.0        106   \n",
       "204          141         mpfi  3.78    3.15               9.5        114   \n",
       "\n",
       "     peak-rpm city-mpg highway-mpg  price  \n",
       "0        5000       21          27  13495  \n",
       "1        5000       21          27  16500  \n",
       "2        5000       19          26  16500  \n",
       "3        5500       24          30  13950  \n",
       "4        5500       18          22  17450  \n",
       "..        ...      ...         ...    ...  \n",
       "200      5400       23          28  16845  \n",
       "201      5300       19          25  19045  \n",
       "202      5500       18          23  21485  \n",
       "203      4800       26          27  22470  \n",
       "204      5400       19          25  22625  \n",
       "\n",
       "[205 rows x 26 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Automobile = pd.read_csv('https://raw.githubusercontent.com/reddyprasade/Machine-Learning-Problems-DataSets/master/Regression/Automobile%20price%20data%20_Raw_.csv')\n",
    "Automobile"
   ]
  },
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       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>4wd</td>\n",
       "      <td>front</td>\n",
       "      <td>99.4</td>\n",
       "      <td>...</td>\n",
       "      <td>136</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>8.0</td>\n",
       "      <td>115</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>17450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   symboling normalized-losses         make fuel-type aspiration num-of-doors  \\\n",
       "0          3                 ?  alfa-romero       gas        std          two   \n",
       "1          3                 ?  alfa-romero       gas        std          two   \n",
       "2          1                 ?  alfa-romero       gas        std          two   \n",
       "3          2               164         audi       gas        std         four   \n",
       "4          2               164         audi       gas        std         four   \n",
       "\n",
       "    body-style drive-wheels engine-location  wheel-base  ...  engine-size  \\\n",
       "0  convertible          rwd           front        88.6  ...          130   \n",
       "1  convertible          rwd           front        88.6  ...          130   \n",
       "2    hatchback          rwd           front        94.5  ...          152   \n",
       "3        sedan          fwd           front        99.8  ...          109   \n",
       "4        sedan          4wd           front        99.4  ...          136   \n",
       "\n",
       "   fuel-system  bore  stroke compression-ratio horsepower  peak-rpm city-mpg  \\\n",
       "0         mpfi  3.47    2.68               9.0        111      5000       21   \n",
       "1         mpfi  3.47    2.68               9.0        111      5000       21   \n",
       "2         mpfi  2.68    3.47               9.0        154      5000       19   \n",
       "3         mpfi  3.19    3.40              10.0        102      5500       24   \n",
       "4         mpfi  3.19    3.40               8.0        115      5500       18   \n",
       "\n",
       "  highway-mpg  price  \n",
       "0          27  13495  \n",
       "1          27  16500  \n",
       "2          26  16500  \n",
       "3          30  13950  \n",
       "4          22  17450  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Automobile.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symboling</th>\n",
       "      <th>normalized-losses</th>\n",
       "      <th>make</th>\n",
       "      <th>fuel-type</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>num-of-doors</th>\n",
       "      <th>body-style</th>\n",
       "      <th>drive-wheels</th>\n",
       "      <th>engine-location</th>\n",
       "      <th>wheel-base</th>\n",
       "      <th>...</th>\n",
       "      <th>engine-size</th>\n",
       "      <th>fuel-system</th>\n",
       "      <th>bore</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compression-ratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peak-rpm</th>\n",
       "      <th>city-mpg</th>\n",
       "      <th>highway-mpg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>-1</td>\n",
       "      <td>95</td>\n",
       "      <td>volvo</td>\n",
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       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
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       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>23</td>\n",
       "      <td>28</td>\n",
       "      <td>16845</td>\n",
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       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>-1</td>\n",
       "      <td>95</td>\n",
       "      <td>volvo</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
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       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>8.7</td>\n",
       "      <td>160</td>\n",
       "      <td>5300</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>19045</td>\n",
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       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>-1</td>\n",
       "      <td>95</td>\n",
       "      <td>volvo</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>173</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.87</td>\n",
       "      <td>8.8</td>\n",
       "      <td>134</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>23</td>\n",
       "      <td>21485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>-1</td>\n",
       "      <td>95</td>\n",
       "      <td>volvo</td>\n",
       "      <td>diesel</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>145</td>\n",
       "      <td>idi</td>\n",
       "      <td>3.01</td>\n",
       "      <td>3.40</td>\n",
       "      <td>23.0</td>\n",
       "      <td>106</td>\n",
       "      <td>4800</td>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>22470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>-1</td>\n",
       "      <td>95</td>\n",
       "      <td>volvo</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>22625</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     symboling normalized-losses   make fuel-type aspiration num-of-doors  \\\n",
       "200         -1                95  volvo       gas        std         four   \n",
       "201         -1                95  volvo       gas      turbo         four   \n",
       "202         -1                95  volvo       gas        std         four   \n",
       "203         -1                95  volvo    diesel      turbo         four   \n",
       "204         -1                95  volvo       gas      turbo         four   \n",
       "\n",
       "    body-style drive-wheels engine-location  wheel-base  ...  engine-size  \\\n",
       "200      sedan          rwd           front       109.1  ...          141   \n",
       "201      sedan          rwd           front       109.1  ...          141   \n",
       "202      sedan          rwd           front       109.1  ...          173   \n",
       "203      sedan          rwd           front       109.1  ...          145   \n",
       "204      sedan          rwd           front       109.1  ...          141   \n",
       "\n",
       "     fuel-system  bore  stroke compression-ratio horsepower  peak-rpm  \\\n",
       "200         mpfi  3.78    3.15               9.5        114      5400   \n",
       "201         mpfi  3.78    3.15               8.7        160      5300   \n",
       "202         mpfi  3.58    2.87               8.8        134      5500   \n",
       "203          idi  3.01    3.40              23.0        106      4800   \n",
       "204         mpfi  3.78    3.15               9.5        114      5400   \n",
       "\n",
       "    city-mpg highway-mpg  price  \n",
       "200       23          28  16845  \n",
       "201       19          25  19045  \n",
       "202       18          23  21485  \n",
       "203       26          27  22470  \n",
       "204       19          25  22625  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Automobile.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Government Website:\n",
    "1. Go to This URL[USA Data Gov](https://www.data.gov/)\n",
    "![](https://lh3.googleusercontent.com/-XSy-ylBkcxU/XsvLLVBnMgI/AAAAAAAAoPU/Y6xynaRbM8IDbDgEwi4Lcnj63gkCwy1HQCK8BGAsYHg/s0/2020-05-25.png)\n",
    "2. Click On Data Menu Bar [Link](https://catalog.data.gov/dataset)\n",
    "![](https://lh3.googleusercontent.com/-EyhhxuIxLQ0/XsvK-RCkOMI/AAAAAAAAoPQ/sGT3vpskZ0IwqOkKgAbkY1nX-Xt0GUUhQCK8BGAsYHg/s0/2020-05-25.png)\n",
    "3. Select Which Data Set you want to load [Link](https://catalog.data.gov/dataset/u-s-hourly-precipitation-data)\n",
    "![](https://lh3.googleusercontent.com/-7wkUiTZ-wRU/XsvKmxqRMtI/AAAAAAAAoPE/CqqRIDKo9ysIhmt9PJf5ccRXuPzcdxCoACK8BGAsYHg/s0/2020-05-25.png)\n",
    "4. Select the File Format From the Web Link[URL](: https://www1.ncdc.noaa.gov/pub/data/cdo/samples/PRECIP_HLY_sample_csv.csv)\n",
    "\n",
    "![](https://lh3.googleusercontent.com/-bFioJlVgJZs/XsvKVe6UbZI/AAAAAAAAoPA/JuTTHH6TYP4JoJGwPJuPnOKnA6EySR6xQCK8BGAsYHg/s0/2020-05-25.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** It is not same to all the data set in this wesite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>STATION</th>\n",
       "      <th>STATION_NAME</th>\n",
       "      <th>ELEVATION</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>DATE</th>\n",
       "      <th>HPCP</th>\n",
       "      <th>Measurement Flag</th>\n",
       "      <th>Quality Flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COOP:310301</td>\n",
       "      <td>ASHEVILLE NC US</td>\n",
       "      <td>682.1</td>\n",
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       "      <td>-82.5568</td>\n",
       "      <td>20100101 00:00</td>\n",
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       "      <td>]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>COOP:310301</td>\n",
       "      <td>ASHEVILLE NC US</td>\n",
       "      <td>682.1</td>\n",
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       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>COOP:310301</td>\n",
       "      <td>ASHEVILLE NC US</td>\n",
       "      <td>682.1</td>\n",
       "      <td>35.5954</td>\n",
       "      <td>-82.5568</td>\n",
       "      <td>20100102 06:00</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       STATION     STATION_NAME  ELEVATION  LATITUDE  LONGITUDE  \\\n",
       "0  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "1  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "2  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "\n",
       "             DATE   HPCP Measurement Flag Quality Flag  \n",
       "0  20100101 00:00  99999                ]               \n",
       "1  20100101 01:00      0                g               \n",
       "2  20100102 06:00      1                                "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "USA_Data = pd.read_csv('https://www1.ncdc.noaa.gov/pub/data/cdo/samples/PRECIP_HLY_sample_csv.csv')\n",
    "USA_Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>COOP:310301</td>\n",
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       "      <td>COOP:310301</td>\n",
       "      <td>ASHEVILLE NC US</td>\n",
       "      <td>682.1</td>\n",
       "      <td>35.5954</td>\n",
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      "text/plain": [
       "       STATION     STATION_NAME  ELEVATION  LATITUDE  LONGITUDE  \\\n",
       "0  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "1  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "2  COOP:310301  ASHEVILLE NC US      682.1   35.5954   -82.5568   \n",
       "\n",
       "             DATE   HPCP Measurement Flag Quality Flag  \n",
       "0  20100101 00:00  99999                ]               \n",
       "1  20100101 01:00      0                g               \n",
       "2  20100102 06:00      1                                "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "USA_Data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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