Raghav_Aggarwal.ipynb

{
 "cells": [
  {
   "cell_type": "raw",
   "metadata": {
    "id": "LqnlCXKGJ3_O"
   },
   "source": [
    "This notebook contains basic to hard exercies for each library that you encounter in your data analytics journey. The emphasis here is to get familiar with the inbuilt functions of these libraries and get used to reading the documentation. Places with \n",
    "```python \n",
    "# ...\n",
    "``` \n",
    "require you to write code to complete the objective."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "S_L5CesyVgMG"
   },
   "outputs": [],
   "source": [
    "#Importing libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E3qxT1l3Jmv_"
   },
   "source": [
    "## Numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pqyJ2FVqKHPX"
   },
   "source": [
    "1. Create a null vector of size 10\n",
    "\n",
    "Expected output: `[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]`\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "OuwkcLo0JmNQ"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n"
     ]
    }
   ],
   "source": [
    "Z = np.zeros(10)\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l1WtEdtuKhrI"
   },
   "source": [
    "2. Create a vector with values ranging from 10 to 39\n",
    "\n",
    "Expected output: `[10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "5DeUt45IKiCN"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33\n",
      " 34 35 36 37 38 39]\n"
     ]
    }
   ],
   "source": [
    "Z = np.arange(10,40)\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "krEsOrGHK3oy"
   },
   "source": [
    "3. Reverse the above vector (Hint: use slicing)\n",
    "\n",
    "Expected output: `[39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "LxQDHVUWK3u-"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16\n",
      " 15 14 13 12 11 10]\n"
     ]
    }
   ],
   "source": [
    "Z = Z[::-1]\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zwXDmB_uLWyv"
   },
   "source": [
    "4. Create a 3x3 matrix with values ranging from 0 to 8\n",
    "\n",
    "Expected output:\n",
    "```\n",
    "[[0 1 2]\n",
    " [3 4 5]\n",
    " [6 7 8]]\n",
    " ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "id": "MBtv_l0JLW6d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 1 2]\n",
      " [3 4 5]\n",
      " [6 7 8]]\n"
     ]
    }
   ],
   "source": [
    "Z = np.arange(0,9).reshape(3,3)\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aGs7AwbxLgbZ"
   },
   "source": [
    "5. Create a 10x10 array with random values and find the minimum and maximum values. Also find the mean value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "LC7v8dlwLxQr"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9923238511530161 0.006914808870345124 0.48887903870784327\n"
     ]
    }
   ],
   "source": [
    "Z = np.random.rand(10,10)\n",
    "Zmin = np.amax(Z)\n",
    "Zmax = np.amin(Z)\n",
    "Zmean = np.mean(Z)\n",
    "print(Zmin, Zmax, Zmean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_v_yoK7ALx39"
   },
   "source": [
    "6. Normalize a 5x5 random matrix ( Hint: (x -mean)/std )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "WJZaFlmmLvvH"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.24242499  1.89897651  0.10448787 -0.54473153  0.83062926]\n",
      " [ 0.69380273  0.66975076  0.40678296 -0.88217158 -0.81143323]\n",
      " [-0.69896261 -0.63696372 -1.0110981   1.88415498  0.16245083]\n",
      " [-0.2475249  -0.63130032 -1.03984496  1.04157838 -1.29795192]\n",
      " [ 2.02393201 -1.33319081 -0.2508438   0.68846946 -1.26142324]]\n"
     ]
    }
   ],
   "source": [
    "Z = np.random.rand(5,5)\n",
    "Z = (Z-np.mean(Z))/np.std(Z)\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WPpIZvO2Mfj_"
   },
   "source": [
    "7. Multiply a 5x3 matrix by a 3x2 matrix (all elements of both matrices are 1)\n",
    "\n",
    "Expected output:\n",
    "```\n",
    "[[3. 3.]\n",
    " [3. 3.]\n",
    " [3. 3.]\n",
    " [3. 3.]\n",
    " [3. 3.]]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "OvyZjMRWMftv"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3. 3.]\n",
      " [3. 3.]\n",
      " [3. 3.]\n",
      " [3. 3.]\n",
      " [3. 3.]]\n"
     ]
    }
   ],
   "source": [
    "Z = np.matmul(np.ones(15).reshape(5,3),np.ones(6).reshape(3,2))\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rMfmqe_4NcNf"
   },
   "source": [
    "8. How to find the most frequent value in an array? (Generate a random array and demonstrate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "FYRrJcDQNcUf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6\n"
     ]
    }
   ],
   "source": [
    "Z = np.random.randint(0,10,50)\n",
    "vals,count = np.unique(Z,return_counts = True)\n",
    "Zmode = np.argmax(count)\n",
    "print(Zmode)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TU9Rkz9qOEc3"
   },
   "source": [
    "9. Consider a large vector Z, compute Z to the power of 3 using 2 different methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "Vm6lEJMeOEiX"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.68140461 0.72312248 0.24089207 ... 0.10294054 0.76824275 0.99352717]\n",
      "[0.3163845  0.37812517 0.01397872 ... 0.00109084 0.45341451 0.98070693]\n",
      "[0.3163845  0.37812517 0.01397872 ... 0.00109084 0.45341451 0.98070693]\n"
     ]
    }
   ],
   "source": [
    "Z = np.random.rand(int(5e7))\n",
    "\n",
    "Z1 = np.power(Z,3)\n",
    "Z2 = Z**3\n",
    "print(Z1)\n",
    "print(Z2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_qqq2l0dOlAp"
   },
   "source": [
    "10. Given a 1D array, negate all elements which are between 3 and 8, in place\n",
    "\n",
    "Hint: Use `<` and `>` to create indices\n",
    "\n",
    "Expected output: `[ 0  1  2  3 -4 -5 -6 -7  8  9 10]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "RuiGERlNOlHu"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3 -4 -5 -6 -7  8  9 10]\n"
     ]
    }
   ],
   "source": [
    "Z = np.arange(11)\n",
    "idx = np.arange(4,8)\n",
    "Z[idx] *= -1\n",
    "print(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yA3SN8PZPEKM"
   },
   "source": [
    "## Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z8_XtdvvPQKs"
   },
   "source": [
    "1. Create a DataFrame df from this dictionary data which has the index labels\n",
    "\n",
    "```python\n",
    "data = {'animal': ['cat', 'cat', 'snake', 'dog', 'dog', 'cat', 'snake', 'cat', 'dog', 'dog'],\n",
    "        'age': [2.5, 3, 0.5, np.nan, 5, 2, 4.5, np.nan, 7, 3],\n",
    "        'visits': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'priority': ['yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'no', 'no']}\n",
    "\n",
    "labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 359
    },
    "id": "xREF9gRGPLs2",
    "outputId": "ccb355a2-cc7e-4487-a6c3-9a623e646efe"
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "      <th>priority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>cat</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>snake</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>dog</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>dog</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>snake</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>cat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>dog</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>dog</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  animal  age  visits priority\n",
       "a    cat  2.5       1      yes\n",
       "b    cat  3.0       3      yes\n",
       "c  snake  0.5       2       no\n",
       "d    dog  NaN       3      yes\n",
       "e    dog  5.0       2       no\n",
       "f    cat  2.0       3       no\n",
       "g  snake  4.5       1       no\n",
       "h    cat  NaN       1      yes\n",
       "i    dog  7.0       2       no\n",
       "j    dog  3.0       1       no"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {'animal': ['cat', 'cat', 'snake', 'dog', 'dog', 'cat', 'snake', 'cat', 'dog', 'dog'],\n",
    "        'age': [2.5, 3, 0.5, np.nan, 5, 2, 4.5, np.nan, 7, 3],\n",
    "        'visits': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'priority': ['yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'no', 'no']}\n",
    "\n",
    "labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "df.index = labels\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3s66ibyiPaHG"
   },
   "source": [
    "2. Display a summary of the basic information about this DataFrame using a single method (Hint: read about `describe` method)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "id": "ZSWpZp68PaNW",
    "outputId": "dad0f748-dcf3-449c-bf4d-495ed3cf4225"
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   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.437500</td>\n",
       "      <td>1.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.007797</td>\n",
       "      <td>0.875595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.375000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.625000</td>\n",
       "      <td>2.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            age     visits\n",
       "count  8.000000  10.000000\n",
       "mean   3.437500   1.900000\n",
       "std    2.007797   0.875595\n",
       "min    0.500000   1.000000\n",
       "25%    2.375000   1.000000\n",
       "50%    3.000000   2.000000\n",
       "75%    4.625000   2.750000\n",
       "max    7.000000   3.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_vF5KU14PiCV"
   },
   "source": [
    "3. Return the first 3 rows of the DataFrame `df` (Hint: use either `iloc` or `head`)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "GN1NneyePiHQ",
    "outputId": "dd17e000-082d-48b2-8754-8d931f8e3aa1"
   },
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "      <th>priority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>cat</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>snake</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>dog</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>dog</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  animal  age  visits priority\n",
       "a    cat  2.5       1      yes\n",
       "b    cat  3.0       3      yes\n",
       "c  snake  0.5       2       no\n",
       "d    dog  NaN       3      yes\n",
       "e    dog  5.0       2       no"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cLGPdfdtPpgl"
   },
   "source": [
    "4. Select just the 'animal' and 'age' columns from the DataFrame `df`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 359
    },
    "id": "_q2esBxrPpns",
    "outputId": "dc8e9c04-99d0-4f05-bcab-b1412687cd50"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>a</th>\n",
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       "      <td>3.0</td>\n",
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       "      <th>c</th>\n",
       "      <td>snake</td>\n",
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       "      <th>d</th>\n",
       "      <td>dog</td>\n",
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       "      <td>cat</td>\n",
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       "      <td>snake</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>cat</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>dog</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>dog</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  animal  age\n",
       "a    cat  2.5\n",
       "b    cat  3.0\n",
       "c  snake  0.5\n",
       "d    dog  NaN\n",
       "e    dog  5.0\n",
       "f    cat  2.0\n",
       "g  snake  4.5\n",
       "h    cat  NaN\n",
       "i    dog  7.0\n",
       "j    dog  3.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['animal','age']\n",
    "df[cols]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IkRygI9zP4rd"
   },
   "source": [
    "5. Select the data in rows [3, 4, 8] and in columns ['animal', 'age']."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 142
    },
    "id": "u9Ufl808P4wH",
    "outputId": "f68cd180-e941-4e26-8f6c-fdcadd42440a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>dog</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>dog</td>\n",
       "      <td>5.0</td>\n",
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       "      <th>i</th>\n",
       "      <td>dog</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  animal  age\n",
       "d    dog  NaN\n",
       "e    dog  5.0\n",
       "i    dog  7.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row_idx = ['d','e','i']\n",
    "cols = ['animal','age']\n",
    "df.loc[row_idx, cols]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YXhVq4LXQ6AN"
   },
   "source": [
    "6. Select only the rows where the number of visits is greater than 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 142
    },
    "id": "oqdD6FXXQ7sH",
    "outputId": "fc705b22-5f34-4195-b48e-ce35c06429c8"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "      <th>priority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>cat</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>dog</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  animal  age  visits priority\n",
       "b    cat  3.0       3      yes\n",
       "d    dog  NaN       3      yes\n",
       "f    cat  2.0       3       no"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idx = df.index[df.visits>2]\n",
    "df.loc[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Y6OF0QMKRBSd"
   },
   "source": [
    "7. Calculate the mean age for each different animal in `df`. (Hint: use `groupby`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 173
    },
    "id": "_Iwprc6aRLEj",
    "outputId": "ae26fbea-c6e9-41a9-e45a-1eea4e8aeb2d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>animal</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cat</th>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dog</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>snake</th>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        age  visits\n",
       "animal             \n",
       "cat     2.5     2.0\n",
       "dog     5.0     2.0\n",
       "snake   2.5     1.5"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['animal']).mean(['age'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "522H21ZqRRRE"
   },
   "source": [
    "8. Count the number of each type of animal in df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 164
    },
    "id": "2o31JmCTRBXe",
    "outputId": "20fd63a4-7836-423f-88db-cf0487a1d8e4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "animal\n",
       "cat      4\n",
       "dog      4\n",
       "snake    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['animal']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "A2p_1gV0RfGH"
   },
   "source": [
    "9. Given the random data `xs` and `ys`, make a scatter plot utilising the Pandas `plot` method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "nLE7KX4DRfKs"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='xs', ylabel='ys'>"
      ]
     },
     "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": [
    "xs = [1,5,2,8,1]\n",
    "ys = [4,2,1,9,6]\n",
    "\n",
    "df2 = pd.DataFrame({\"xs\": xs, \"ys\": ys})\n",
    "\n",
    "df2.plot.scatter(x='xs',y='ys',c='blue')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uvH0t9yRSiVk"
   },
   "source": [
    "10. Plot a bar graph representing the mean age of each animal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "id": "F4-Oo3dKSiek"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='animal'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = df.groupby(['animal']).mean(['age'])\n",
    "k.plot.bar(y='age')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d5N4bol2T2Xd"
   },
   "source": [
    "## Make a simple Linear Regression Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8AoIjszRjJ8D"
   },
   "source": [
    "### Linear Regression from scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1uQjO45HhNzB"
   },
   "source": [
    "We will start with the most familiar linear regression, a straight-line fit to data.\n",
    "A straight-line fit is a model of the form\n",
    "$$\n",
    "y = ax + b\n",
    "$$\n",
    "where $a$ is commonly known as the *slope*, and $b$ is commonly known as the *intercept*.\n",
    "\n",
    "Consider the following data, which is scattered about a line with a slope of 2 and an intercept of -5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "id": "tTWWnzsbT2ek"
   },
   "outputs": [
    {
     "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": [
    "rng = np.random.RandomState(1)\n",
    "x = 10 * rng.rand(50)\n",
    "y = 2 * x - 5 + rng.randn(50)\n",
    "plt.scatter(x, y);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.73907352e+01, 5.18867376e+01, 1.30815988e-06, 9.14049845e+00,\n",
       "       2.15372915e+00, 8.52641608e-01, 3.46928663e+00, 1.19412216e+01,\n",
       "       1.57424429e+01, 2.90323473e+01, 1.75724041e+01, 4.69525764e+01,\n",
       "       4.18007224e+00, 7.71090232e+01, 7.50080261e-02, 4.49526682e+01,\n",
       "       1.74143298e+01, 3.12134324e+01, 1.97084925e+00, 3.92442000e+00,\n",
       "       6.41191864e+01, 9.37530479e+01, 9.82347155e+00, 4.79310604e+01,\n",
       "       7.68057946e+01, 8.00321082e+01, 7.23251789e-01, 1.52527609e-01,\n",
       "       2.88423714e+00, 7.71134256e+01, 9.67209972e-01, 1.77331632e+01,\n",
       "       9.17552352e+01, 2.84265221e+01, 4.78693941e+01, 9.95501134e+00,\n",
       "       4.71283524e+01, 6.96600012e+01, 3.34461088e-02, 5.62716493e+01,\n",
       "       9.77846253e+01, 5.59751846e+01, 7.86488327e+00, 6.22961858e+01,\n",
       "       1.06556084e+00, 2.00608611e+01, 8.25545788e+01, 8.62092681e+00,\n",
       "       8.28146455e+00, 1.69074296e+00])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(x)\n",
    "def subb(a,b):\n",
    "    return ((a-b)**2)\n",
    "def div(a,b):\n",
    "    return a/b\n",
    "def mult(a,b):\n",
    "    return a*b\n",
    "def sub(a,b):\n",
    "    return a-b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WBS61IRcVzZn"
   },
   "source": [
    "We will now build a simple linear regression model to fit this set of points. Firstly, define the hypothesis function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "id": "eg_AnaNGXYtU"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11.34044009, 17.40648987,  3.0022875 ,  9.04665145,  5.93511782,\n",
       "        4.8467719 ,  6.72520423,  9.91121454, 10.93534948, 13.77633468,\n",
       "       11.38389029, 16.70439001,  7.08904499, 20.56234873,  3.54775186,\n",
       "       16.4093502 , 11.34609605, 14.17379657,  5.80773877,  6.96202978,\n",
       "       19.01489137, 22.36523151,  9.26848356, 16.84645231, 20.52778305,\n",
       "       20.89213327,  4.70088423,  3.78109566,  6.39660839, 20.56285007,\n",
       "        4.96693668, 11.4221525 , 22.1577906 , 13.6633057 , 16.83754228,\n",
       "        9.31031262, 16.73001855, 19.69251344,  3.36576555, 18.0028863 ,\n",
       "       22.77722178, 17.96331309,  8.60887984, 18.78558657,  5.06452013,\n",
       "       11.95787052, 21.17191006,  8.87228297,  8.75550677,  5.60057144])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def h(x, a, b):\n",
    "  return (a*x+b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "x_tGjm2waFG8"
   },
   "source": [
    "Next, we define the cost function which returns a single float value given the input X, parameters and ground truth Y. Remember that $$ J = \\frac{\\sum\\limits_{i=1}^m (h(x^i) - y^i)^2}{2m} $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "id": "xBPJsuuxakpU"
   },
   "outputs": [],
   "source": [
    "def cost_function(X, Y, a, b):\n",
    "  y_pred = h(X,a,b)\n",
    "  m = 50\n",
    "  k = (y_pred - Y)**2\n",
    "  J = sum(k)/(2*m)\n",
    "  return J"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "M1iwpSCZc4br"
   },
   "source": [
    "In order to perform gradient descent, you need to calculate the derivative of each parameter with respect to the cost function. Remember the formulae:\n",
    "\n",
    "$$\n",
    "\\frac{dJ}{da} = \\frac{\\sum\\limits_{i=1}^m (h(x^i) - y^i).x^i}{m}\n",
    "$$\n",
    " \n",
    "and\n",
    "\n",
    "$$\n",
    "\\frac{dJ}{db} = \\frac{\\sum\\limits_{i=1}^m (h(x^i) - y^i)}{m}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "id": "5qSraaMMbdyL"
   },
   "outputs": [],
   "source": [
    "def gradients(X, Y, a, b):\n",
    "  y_pred = h(X, a, b)\n",
    "  m = 50\n",
    "  grad_a = sum((y_pred-Y)*X)/m\n",
    "  grad_b = sum((y_pred-Y))/m\n",
    "  return grad_a, grad_b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "loht93wDfC5a"
   },
   "source": [
    "Finally, we define the gradient descent function which will carry out the optimisation. Remember the gradient descent step:\n",
    "\n",
    "$$\n",
    "a = a - \\alpha \\times \\frac{dJ}{da}\n",
    "$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\n",
    "b = b - \\alpha \\times \\frac{dJ}{db}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "id": "SaHmNA9tbG0D"
   },
   "outputs": [],
   "source": [
    "def gradient_descent(X, Y, a, b, learning_rate, iterations):\n",
    "    \n",
    "    for iteration in range(iterations):\n",
    " \n",
    "        loss = cost_function(X, Y, a, b)\n",
    "        grad_a, grad_b = gradients(X, Y, a, b)\n",
    "        \n",
    "        # Define the gradient descent step\n",
    "        a = a - learning_rate*grad_a\n",
    "        b = b - learning_rate*grad_b\n",
    "\n",
    "        if iteration%10 == 0:\n",
    "          print(f\"Iteration: {iteration} | Loss: {loss}\")\n",
    "        \n",
    "    return a, b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "p7L29PDVfyty"
   },
   "source": [
    "Now we will run the gradient descent algorithm. First you will need to define the intial values of $a$ and $b$ as well as the hyperparameters (learning rate and number of iterations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "2byfJ7_FfxOK"
   },
   "outputs": [],
   "source": [
    "a = 1\n",
    "b = 0\n",
    "learning_rate = 0.001\n",
    "num_iterations = 200000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "nwRyD8qqciSC"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'gradient_descent' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-27-201289adcd56>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgradient_descent\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlearning_rate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_iterations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'gradient_descent' is not defined"
     ]
    }
   ],
   "source": [
    "a, b = gradient_descent(x, y, a, b, learning_rate, num_iterations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CLH0jk_QgRVC"
   },
   "source": [
    "Now let's visualise the line that we got"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "id": "PcT2m1lfgUTF"
   },
   "outputs": [
    {
     "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": [
    "xfit = np.linspace(0, 10, 1000)\n",
    "yfit = xfit * a + b\n",
    "\n",
    "plt.scatter(x, y)\n",
    "plt.plot(xfit, yfit);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "id": "ChsMB8OqgdaU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model slope:     2.0272088103604498\n",
      "Model intercept: -4.998577085551615\n"
     ]
    }
   ],
   "source": [
    "print(\"Model slope:    \", a)\n",
    "print(\"Model intercept:\", b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yQlLWs7_jNnS"
   },
   "source": [
    "### Using sklearn library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1ChmcY-Hjf6w"
   },
   "source": [
    "Implementing all the machine learning algorithms from scratch becomes quite cumbersome as the complexity increases. There are optimised libraries which has all this stuff pre-implemented and are quite easy to use.\n",
    "\n",
    "We can directly use Scikit-Learn's ``LinearRegression`` estimator to fit the above data and construct the best-fit line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 264
    },
    "id": "tUAMSfVHjSXM",
    "outputId": "74d67077-623f-4645-c072-6d48f55e5874"
   },
   "outputs": [
    {
     "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": [
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression(fit_intercept=True)\n",
    "\n",
    "model.fit(x[:, np.newaxis], y)\n",
    "\n",
    "xfit = np.linspace(0, 10, 1000)\n",
    "yfit = model.predict(xfit[:, np.newaxis])\n",
    "\n",
    "plt.scatter(x, y)\n",
    "plt.plot(xfit, yfit);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gpTfztdEj6OK"
   },
   "source": [
    "The slope and intercept of the data are contained in the model's fit parameters, which in Scikit-Learn are always marked by a trailing underscore. Here the relevant parameters are *coef_* and *intercept_*:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1ynD2VJaj9uC",
    "outputId": "3834f45c-5dc4-44b2-8e3b-ac39eb0b04ea"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model slope:     2.027208810360695\n",
      "Model intercept: -4.998577085553202\n"
     ]
    }
   ],
   "source": [
    "print(\"Model slope:    \", model.coef_[0])\n",
    "print(\"Model intercept:\", model.intercept_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3TGYxLDkkH5S"
   },
   "source": [
    "These results should be close to the parameters obtained from the linear regression we implemented above"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PxeRI7mUkmGR"
   },
   "source": [
    "## Solving a Data Analytics Problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v25RyO2ikp9Z"
   },
   "source": [
    "For the purposes of this exercise, let's pretend we're working for a startup that just got funded to create a smartphone app that automatically identifies species of flowers from pictures taken on the smartphone. We're working with a moderately-sized team of data scientists and will be building part of the data analysis pipeline for this app.\n",
    "\n",
    "We've been tasked by our company's Head of Data Science to create a demo machine learning model that takes four measurements from the flowers (sepal length, sepal width, petal length, and petal width) and identifies the species based on those measurements alone. \n",
    "\n",
    "We've been given a [data set](https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects/raw/master/example-data-science-notebook/iris-data.csv) from our field researchers to develop the demo, which only includes measurements for three types of Iris flowers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5BHgrtPomYqY"
   },
   "source": [
    "### Step 1: Checking the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "564HJ1VHmdn6"
   },
   "source": [
    "The first step is to look at the data we're working with. Even curated data sets from the government can have errors in them, and it's vital that we spot these errors before investing too much time in our analysis.\n",
    "\n",
    "Let's start by reading the data into a pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "NYy05hlUmdch",
    "outputId": "f2d0ca1a-7f7b-48ab-cf84-803029d85f2a"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
       "0              5.1             3.5              1.4             0.2   \n",
       "1              4.9             3.0              1.4             0.2   \n",
       "2              4.7             3.2              1.3             0.2   \n",
       "3              4.6             3.1              1.5             0.2   \n",
       "4              5.0             3.6              1.4             0.2   \n",
       "\n",
       "         class  \n",
       "0  Iris-setosa  \n",
       "1  Iris-setosa  \n",
       "2  Iris-setosa  \n",
       "3  Iris-setosa  \n",
       "4  Iris-setosa  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "iris_data = pd.read_csv('https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects/raw/master/example-data-science-notebook/iris-data.csv')\n",
    "iris_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z0G6snvlmwYw"
   },
   "source": [
    "The first row in the data file defines the column headers, and the headers are descriptive enough for us to understand what each column represents. The headers even give us the units that the measurements were recorded in, just in case we needed to know at a later point in the project.\n",
    "\n",
    "Each row following the first row represents an entry for a flower: four measurements and one class, which tells us the species of the flower.\n",
    "\n",
    "One of the first things we should look for is missing data. Thankfully, the field researchers already told us that they put a 'NA' into the spreadsheet when they were missing a measurement.\n",
    "\n",
    "We can tell pandas to automatically identify missing values if it knows our missing value marker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "id": "ldsB0qXtkoea"
   },
   "outputs": [],
   "source": [
    "iris_data = pd.read_csv('https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects/raw/master/example-data-science-notebook/iris-data.csv', \n",
    "                        na_values=['NA'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "q6Fm66Zkomv8"
   },
   "source": [
    "Next, it's always a good idea to look at the distribution of our data — especially the outliers.\n",
    "\n",
    "Let's start by printing out some summary statistics about the data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "id": "EUGEvwpBonhI",
    "outputId": "d3bc9bb6-6ed0-410d-ed5e-45e353d7ac9e"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>145.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.644627</td>\n",
       "      <td>3.054667</td>\n",
       "      <td>3.758667</td>\n",
       "      <td>1.236552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.312781</td>\n",
       "      <td>0.433123</td>\n",
       "      <td>1.764420</td>\n",
       "      <td>0.755058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.055000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.100000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.700000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.400000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm\n",
       "count       150.000000      150.000000       150.000000      145.000000\n",
       "mean          5.644627        3.054667         3.758667        1.236552\n",
       "std           1.312781        0.433123         1.764420        0.755058\n",
       "min           0.055000        2.000000         1.000000        0.100000\n",
       "25%           5.100000        2.800000         1.600000        0.400000\n",
       "50%           5.700000        3.000000         4.350000        1.300000\n",
       "75%           6.400000        3.300000         5.100000        1.800000\n",
       "max           7.900000        4.400000         6.900000        2.500000"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BEA8e8aRoss7"
   },
   "source": [
    "We can see several useful values from this table. For example, we see that five `petal_width_cm` entries are missing.\n",
    "\n",
    "However, tables like this are rarely useful unless we know that our data should fall in a particular range. It's usually better to visualize the data in some way. Visualization makes outliers and errors immediately stand out, whereas they might go unnoticed in a large table of numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 908
    },
    "id": "ab2I-2roo1uw",
    "outputId": "cc0e446b-69db-4a7a-e011-8e4693efd187"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/raghavaggarwal/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/raghavaggarwal/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/raghavaggarwal/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/raghavaggarwal/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f936e6bb910>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 823.25x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris_data.dropna(), hue='class')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F2EWDQb3pFjw"
   },
   "source": [
    "From the scatterplot matrix, we can already see some issues with the data set:\n",
    "\n",
    "1. There are five classes when there should only be three, meaning there were some coding errors.\n",
    "\n",
    "2. There are some clear outliers in the measurements that may be erroneous: one `sepal_width_cm` entry for `Iris-setosa` falls well outside its normal range, and several `sepal_length_cm` entries for `Iris-versicolor` are near-zero for some reason.\n",
    "\n",
    "3. We had to drop those rows with missing values.\n",
    "\n",
    "In all of these cases, we need to figure out what to do with the erroneous data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0uIblWAypg4o"
   },
   "source": [
    "### Step 2: Cleaning the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U4bisVfkpkpI"
   },
   "source": [
    "Now that we've identified several errors in the data set, we need to fix them before we proceed with the analysis. Let's walk through the issues one-by-one."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z4_LBsg2pwuY"
   },
   "source": [
    "#### Fixing Class names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rLVkk82spoVH"
   },
   "source": [
    "After talking with the field researchers, it sounds like one of them forgot to add `Iris-` before their `Iris-versicolor` entries. The other extraneous class, `Iris-setossa`, was simply a typo that they forgot to fix.\n",
    "\n",
    "Let's use the DataFrame to fix these errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jnyEvWh1pfiI",
    "outputId": "fa8b5773-4452-4df5-893e-16a860941810"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'], dtype=object)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_data.loc[iris_data['class'] == 'versicolor', 'class'] = 'Iris-versicolor'\n",
    "iris_data.loc[iris_data['class'] == 'Iris-setossa', 'class'] = 'Iris-setosa'\n",
    "\n",
    "iris_data['class'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "x_wkEA5Ipurx"
   },
   "source": [
    "#### Fixing outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MzoCyTFhp5c4"
   },
   "source": [
    "Fixing outliers can be tricky business. It's rarely clear whether the outlier was caused by measurement error, recording the data in improper units, or if the outlier is a real anomaly. For that reason, we should be judicious when working with outliers: if we decide to exclude any data, we need to make sure to document what data we excluded and provide solid reasoning for excluding that data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nMUcOed6p78_"
   },
   "source": [
    "In the case of the one anomalous entry for `Iris-setosa`, let's say our field researchers know that it's impossible for `Iris-setosa` to have a sepal width below 2.5 cm. Clearly this entry was made in error, and we're better off just scrapping the entry than spending hours finding out what happened."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 283
    },
    "id": "74VX_jTup11w",
    "outputId": "c313eeed-137c-489a-8795-03cf991064db"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 96,
     "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": [
    "# This line drops any 'Iris-setosa' rows with a separal width less than 2.5 cm\n",
    "iris_data = iris_data.loc[(iris_data['class'] != 'Iris-setosa') | (iris_data['sepal_width_cm'] >= 2.5)]\n",
    "iris_data.loc[iris_data['class'] == 'Iris-setosa', 'sepal_width_cm'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_xpPptbjqHjF"
   },
   "source": [
    "The next data issue to address is the several near-zero sepal lengths for the `Iris-versicolor` rows. Let's take a look at those rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "hUAKocYVqBxL",
    "outputId": "14f44d41-158b-4168-fd80-479665ebeebf"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.067</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.060</td>\n",
       "      <td>2.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.057</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.055</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.1</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>0.055</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
       "77            0.067             3.0              5.0             1.7   \n",
       "78            0.060             2.9              4.5             1.5   \n",
       "79            0.057             2.6              3.5             1.0   \n",
       "80            0.055             2.4              3.8             1.1   \n",
       "81            0.055             2.4              3.7             1.0   \n",
       "\n",
       "              class  \n",
       "77  Iris-versicolor  \n",
       "78  Iris-versicolor  \n",
       "79  Iris-versicolor  \n",
       "80  Iris-versicolor  \n",
       "81  Iris-versicolor  "
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_data.loc[(iris_data['class'] == 'Iris-versicolor') &\n",
    "              (iris_data['sepal_length_cm'] < 1.0)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PEnQTOTNqN1y"
   },
   "source": [
    "All of these near-zero `sepal_length_cm` entries seem to be off by two orders of magnitude, as if they had been recorded in meters instead of centimeters.\n",
    "\n",
    "After some brief correspondence with the field researchers, we find that one of them forgot to convert those measurements to centimeters. Let's do that for them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 283
    },
    "id": "uOWTZXZXqS-Z",
    "outputId": "b05d15d5-c4ec-4149-f15b-d565859d1465"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 98,
     "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": [
    "iris_data.loc[(iris_data['class'] == 'Iris-versicolor') &\n",
    "              (iris_data['sepal_length_cm'] < 1.0),\n",
    "              'sepal_length_cm'] *= 100.0\n",
    "\n",
    "iris_data.loc[iris_data['class'] == 'Iris-versicolor', 'sepal_length_cm'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e1ACMz_TqXRq"
   },
   "source": [
    "#### Handling Missing Values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Rr1SkpHVqenj"
   },
   "source": [
    "Let's take a look at the rows with missing values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "ZR5jad4JqZxC",
    "outputId": "1c4fadec-7af5-4d3e-85aa-9cad2a47ecd7"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
       "7               5.0             3.4              1.5             NaN   \n",
       "8               4.4             2.9              1.4             NaN   \n",
       "9               4.9             3.1              1.5             NaN   \n",
       "10              5.4             3.7              1.5             NaN   \n",
       "11              4.8             3.4              1.6             NaN   \n",
       "\n",
       "          class  \n",
       "7   Iris-setosa  \n",
       "8   Iris-setosa  \n",
       "9   Iris-setosa  \n",
       "10  Iris-setosa  \n",
       "11  Iris-setosa  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_data.loc[(iris_data['sepal_length_cm'].isnull()) |\n",
    "              (iris_data['sepal_width_cm'].isnull()) |\n",
    "              (iris_data['petal_length_cm'].isnull()) |\n",
    "              (iris_data['petal_width_cm'].isnull())]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eER2CdgcqgD4"
   },
   "source": [
    "It's not ideal that we had to drop those rows, especially considering they're all `Iris-setosa` entries. Since it seems like the missing data is systematic — all of the missing values are in the same column for the same Iris type — this error could potentially bias our analysis.\n",
    "\n",
    "One way to deal with missing data is mean imputation: If we know that the values for a measurement fall in a certain range, we can fill in empty values with the average of that measurement."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "s3TWd262qqwq"
   },
   "source": [
    "Let's see if we can do that here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "id": "jKdupXg0qfVK",
    "outputId": "25471099-814f-4e6d-a1bb-7bc0f4d9e08f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 100,
     "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": [
    "iris_data.loc[iris_data['class'] == 'Iris-setosa', 'petal_width_cm'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "O4pGDsgBqvKF"
   },
   "source": [
    "Most of the petal widths for `Iris-setosa` fall within the 0.2-0.3 range, so let's fill in these entries with the average measured petal width."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "MJNI1m7aqwMJ",
    "outputId": "b7047b94-6a1d-4098-e5d7-0e4c0526a653"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.25</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.25</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.25</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.25</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.25</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
       "7               5.0             3.4              1.5            0.25   \n",
       "8               4.4             2.9              1.4            0.25   \n",
       "9               4.9             3.1              1.5            0.25   \n",
       "10              5.4             3.7              1.5            0.25   \n",
       "11              4.8             3.4              1.6            0.25   \n",
       "\n",
       "          class  \n",
       "7   Iris-setosa  \n",
       "8   Iris-setosa  \n",
       "9   Iris-setosa  \n",
       "10  Iris-setosa  \n",
       "11  Iris-setosa  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "average_petal_width = iris_data.loc[iris_data['class'] == 'Iris-setosa', 'petal_width_cm'].mean()\n",
    "\n",
    "iris_data.loc[(iris_data['class'] == 'Iris-setosa') &\n",
    "              (iris_data['petal_width_cm'].isnull()),\n",
    "              'petal_width_cm'] = average_petal_width\n",
    "\n",
    "iris_data.loc[(iris_data['class'] == 'Iris-setosa') &\n",
    "              (iris_data['petal_width_cm'] == average_petal_width)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 49
    },
    "id": "j9bmsiZVq0Ko",
    "outputId": "0183d63b-7c9a-4a1f-8523-b11df3fc4ca6"
   },
   "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>sepal_length_cm</th>\n",
       "      <th>sepal_width_cm</th>\n",
       "      <th>petal_length_cm</th>\n",
       "      <th>petal_width_cm</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [sepal_length_cm, sepal_width_cm, petal_length_cm, petal_width_cm, class]\n",
       "Index: []"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking again for any missing values\n",
    "iris_data.loc[(iris_data['sepal_length_cm'].isnull()) |\n",
    "              (iris_data['sepal_width_cm'].isnull()) |\n",
    "              (iris_data['petal_length_cm'].isnull()) |\n",
    "              (iris_data['petal_width_cm'].isnull())]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gFfvEcJlq9XP"
   },
   "source": [
    "After all this work, let's save this DataFrame into a new variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "id": "mvPYz9pAq3-X"
   },
   "outputs": [],
   "source": [
    "iris_data_clean = iris_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tmkXnCLQrF1t"
   },
   "source": [
    "Now, let's take a look at the scatterplot matrix now that we've tidied the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 633
    },
    "id": "ALk9GqJKrGAY",
    "outputId": "c83e7cd1-3b7f-4e4b-b8df-92769a4296b3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f936f982eb0>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 823.25x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris_data_clean, hue='class')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bvZABBh2rWcf"
   },
   "source": [
    "### Step 3: Exploratory Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "87DV4RSIrdOZ"
   },
   "source": [
    "Now after spending entirely too much time tidying our data, we can start analyzing it. Exploratory analysis is the step where we start delving deeper into the data set beyond the outliers and errors, we analyze things like correlations between various features of the data, confounding factors that explain these correlations, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vpmhKrHWrsUc"
   },
   "source": [
    "Let's return to that scatterplot matrix that we used earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 633
    },
    "id": "EKlZlAdBrZKv",
    "outputId": "8857a057-fd50-414c-9419-d33da84e33b5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f936fd05460>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ez8KZEQi8jFFrZHLYZCaHTSavLo+blt7k9r7NbmNv7V7hzAgOSbmtnPf3vO/WZnfaya7N5ozEM5gaNnWILBMI+ocIMztC7A4nFQ2tBPgeOmcGlFCz0joRdiM4+lBJKoIMQR7tQYYg7E47LfbD54u12FtwOB39ssHWbuv3GALBcEOWZZrbm5HlzhBlW7sNp+zE1m5Dr9Fj1Bg9zvPRiEWzYx2749D3Xp1Kh0Vnwaw1c1zkcaQHpgNgUBsG00QXTtlJc7soXyHoP2Jn5ggpa2jFz6BFqz68P2g1aoUIgOCoRKPScFnaZSwtWIrdaQcgxhzDhJAJ3LHsDkoaS7gw9ULmRM7BaugUDihtKmVx7mK+2vcVaQFpXJh6oetHtbeUNJawOG8xX+/7mvSAdC5KvYjUwFSvfj6BYCjYX7efL3O+ZHnRco6POp4FMQtYVriMJflLyAjKIMmaRF59Ho8e9yi3/Xob7c52ANID0kmxpgyx9YKhwuF0sKV8C2/ufJOqliouSbuE2RGz8fPpDIUPNATywIwH2FC2gdXFqwnxDeGcUecwOmj0oNubXZPNJ1mfsLFsIyfGnsip8acSbYkedDsERwfCmTlCimp6DjED8DfqKKkVzozg6GRcyDjeOeUdtpRvQavWkuCXwDWLr3E9YN2/8n7umXoPF6ddDEC7o53Xd7zuCnXYU72HJflL+N9p/yPWEtura7Y72nl1+6t8lPVR5xgFS3jv1Pd6PYZAMByptlVz17K72F29G1CKGa4oXMEo6ygyazLJrMkkyhTFcVHH8fCah3lt4WtsKN1AhCmC8cHjCfUNHeJPIBgqdlXt4qqfrsIuKwtLdy+/m4dnPsxZSWe5+siyzM6qnby24zXlnOpdrC1ZO+jFV0ubSrnpl5soaiwCILMmk51VO/nncf/EV+s7qLYIjg5EmNkRUlxrO6ySWQcBvjqKRZiZ4ChFJakYEzSGS9Mv5YKUC8ity3U5Mh28vuN1qm3VAJQ0lfBx5sdu79e31fep8GZRYxGfZn/q1lbXWudRK0EgGGnk1ee5HJkO9tTsIcoc5ToubCzET+9HWXMZTW1NXD32ak5LOI1Ic+RgmysYRmwo2+ByZDp4fcfr1LfVu47Lm8t5Y+cbbn1sdhtZ1VmDYmMH++r2uRyZDpYWLKWwoXBQ7RAcPQhn5ggpqrVhNWp77BfgqxNhZoJjhu7qFejUOlQq5VajklTd9umu7VCoVep+jyEQDEfUKnW37RJSt8dizgs60Kk983d9ND6opc45pZJU3dYrGux5pJE8r6eSVG62CgR9QTgzR0hhzeFrzHQQYNRRKpwZwTHC2OCxWHQWt7Ybx9+Iv94fgEhTJNeMu8bt/RhzDMnW5F5fI9IUydUZV7u1xVviSbImHZnRAsEwIc4Sx7yoeW5tx0cez47KHa7jMUFjKGgoID0gnVH+owbbRMEwZXLoZI8QrevGXefWFmwM5qYJ7ip4gT6BpAWk9eoaOyt38ti6x7h16a38kv8LDW1HVig50T+RccHj3NouSLmAaLPImREcGWJZ5wgprLExLT6wx35WXx0Vja3IsowkST32FwhGMk7ZyRVjrqCsuYy61jqSrcno1Z1OvyRJnJd8HvF+8awoXEGiNZHZEbOJMEX0+hoqScX5KeeT6J/IyqKVjLKOYlbELMJ9wwfiIwkEg4ZFb+GeafcwL2Yea4rXEGmOJNgYTJWtCj+9H6kBqZi0JuxOO9ePu54go6eaoODYJCUghTdOfoNlBcuobqnmhJgTGBs01qPfwriFhBhD+LXgV6LMSv5VrF/PuYaZ1Zn86cc/uYoiL8lfwj9m/4MzEs/os62BhkAePe5RVhWvYmflTqZHTGdy6GT0mp4XiAWC7hDOzBFSUttCkOnwsswAPlo1OrWK2uZ2rD3IOAsEI53tldt5atNTWPVWTDoT3+3/jgjfCCaGTsTqoyia+ev9mR8zn/kx84/4OlYfKwtiF7AgdoG3TBcIhgXhpnBSrCm8vuN1fin4hRZHCzqVjghTBBemXMi4kHE9DyI4JkkLSOtxl8WkM3Fc1HEcF3Vcn8beXrnd5ch08MKWFzg+6njXzntfiDJHcX7K+SAE+AReQDgzR0hJfe8EAAACTUrejHBmBEc7TtkJQE1rDTWtNQDIyIc7RSAQHIQTJ7n1ua7jNmcbufW5OGRRU0kwNHR3H5eR3WohCQRDhVdzZiRJOl2SpM2SJFVLklQvSVKDJEn1vTgvRZKkLV1e9ZIk3epN27xJfUs7sgxGXe+S1QJ8dZTVi7wZwdFPRlAGBo17AbZrxl7j2pUBoLkG9nwP390J616FqpxBtlIg8ALFm+G3f8HPD0L+GnC093xOL4m1xDI7YrZb29jgscT5xXntGoIRRH0xbPsYvv0zbH0fagsG3YRu7+3jDrq3CwRDhLd3Zp4CzgG2y31w12VZzgTGA0iSpAaKgM+9bJvXKK61EWzS9zoHxmrUUSqcGcExQEpACq8vfJ0vcr6gqLGIc0adw7TwaZ0dZBk2vwOL7+9sC0yCyz4Hf5H8KRghFG2GN0+B9gNhNyufgj98BfF9C905FGadmfum38fSgqX8WvArMyNmsiB2AQE+AV4ZXzCCaGuEnx+CbUptLta/CsmnwtkvgMF/0MxIDUh1v7cnncO0sGk9nygQDALedmYKgB19cWS6YT6wV5blPC/Z5HWKa20E9aJgZgf+Ri0ltaLWjODYYEzQGMYEjen+zdp8+PWf7m1V2VC2QzgzgpHDnm87HRkA2Qmr/wsxM0DtnZ/VKHMUl6VfxmXpl3llPMEIpTKn05HpIOs7qMyG6CmDasph7+0CwRDibWfmTuA7SZJ+A1o7GmVZfqIPY1wIvH9woyRJi4BFADExMf00s38U1bYQ4NtzjZkOAow6ioQzc1QynObliMBpB8eBW4POBHYbOB1eDdERKIi5OYB0J0lrq1OcGsFhEfOyjzjt3bc72gbXDoFgGONtZ+YfQCPgA/Q5212SJB1wBnDPwe/Jsvwy8DLA5MmThzTjrLC6mQBj73dmrL46dpf0mDokGIEMp3k5XNlflcm26p0UNBSR6BfP6D9+RUn5Fna31xOqMTKusY6IkPShNvOoQ8zNASTtd7D2xc5jjQ/MuRO2fwStDRA5mXxLMFsrt1PTUsOYoDGMDhyNXqOnpLGEbZXbKGksITUglTFBYzDpTFQ0V7C9cjt59Xkk+ieSEZRxVOYjiHnZRwISIHIKFK3vbAtOA2MQ7PgM6gohbCxETQK9eUBNya3LZWvFVurb6skIymB04Gi0aveF3ab2JjaVbWJn1U4sOgvjQsYxOnD0gNolEHjbmQmQZfmkfpx/CrBJluUybxk0EBTW2IgNNPa6f6CvjrL61p47CgRHGWV1+Ty++Rl+K1rmarsk9WKqWqr5IfcHAMYGjuFJg4WQoTJSIOgrkVPg0s9gxVPQ3gTz7oMvroHGcgAKjr+d62rWkt/Ymaj91NynGBc8jruX382m8k2u9nun3svvEn/H4xse59v937raLx99OTeOv1HU3jjWMQbA2S8quYZZP0DiCTD+EvjqJihc29nv1P/A1KsPPU4/yavL4+qfrqa0uRQACYnn5j/nIfH8W8Fv3L38bpf6WbhvOE/Pe5q0wN4V5hQIjgSvqpkBP0uS1B9n5iK6CTEbbhTV2gjspSwzKGpmQgBAcCySWbfXzZEB+CDzQ7caM9uqdpBZkznYpgkER45WD6Pmw6WfwOXfKupSBxwZgN3mADdHBuDxjY9T0FDg5sgAPLXpKfbW7nVzZADe3vU2efXDNnVUMJgEjYIFD8BVP8NJ/4DGMndHBmDJg1AzcPNla+VWlyMDiizz05uepqG1M+SytLGUF7e+6CbjXNJUws6qnQNml0AA3ndmbgB+kCTJ1hdpZgBJkozAicBnXrbJ65TU2QjuRcHMDkx6DW0OJ02th4h9FQiOUg4usgbgkB3YD4oD766fQDDs0ehBawBbdWebJNHUTT2YmpYa2p2euWE2u422bvIfnLKTFodYBBMcQJKUMDKVCtqaPN9va+zMRxwAGtsaPdqqWqpoc3bO3RZHi6u+mNu57Z7nCgTexKthZrIsH3HApizLzUCgF80ZEOwOJ1WNbX0qgClJEsEmZXcmMdg0gNYJBANMeyuUblNqwxisED4OLOFuXYobi9lTvYem9ibiLbEE+gRS1VLlev/E2BPRqDQsGrsIrUpLaWMpCf4Jg/1JBALvUL0fzOFKzoxKA+teJhk1akntVuTyotSLCDWGYtAY3Jz3edHzMGlNhBhDKG/u3N05O/FsGtsa+SL7C0J9Q0kPSMfPx29QP5pgmGCrh9Ityg6gXyQEjgKdr7tTk3YmWAZOEXJ04GhUkspVGBng4tSLCTR0PrbFmGO4JO0SVJKKdkc7KklFXWsdKdaUAbNLIAAvOzOSJJ0N/CLLct2BY39grizLX3jzOkNJaX0L/kYtGlXfNrUCfPWU1ApnRjDCyfoOPr688zhxvhLPbVIyXgobCrn5l5vJrs0GIMgniMeOf4w3d7zJrupdnBA9j3Eh47lj2R2uIWZFzMKqP/oSnQXHAJXZ8M45UJevHGsNcOLfSVWpefGE//LM1ucpbSrl98m/5+ykswnzDeOVE1/h2c3PklObw4yIGYT7hnPZD5fxxNwn+Dz7czaVb+KcpHPQSBqu+fka16X+kP4Hbhh/A0Zt7/M1BUcB9jZY+wL8+khn28yb4I/fws9/g/JdkPF7JV9GZzj0OP0k0BDIPVPv4ZOsT6hprWFBzAImhU5y66NSqUgPTOeWX27BLiu778n+yVycdvGA2SUQgPcFAP4my7Kr2KUsy7WSJP0N+MLL1xkyimtbCDb79Pm8AF8dJXUilEYwgqkvge/ucG/buwRKtyv5A8D2yu0uRwagsqWSpzY+xX/nPUNjay0atQ8Xfu/+w7ayeCWZ1ZnMjJw54B9BIPAq+37rdGRAqT2z7xfU573JdI2OMSHjaXW0uq1ejwsZxy0Tb+Gz7M/YVL6Jb/Z9A8Adv93BJ2d8gkFtoKqligu+ucDtUm/veptT409ldJBQhjqmqMqGZY+5t616FsacBxe9D62N4BsEKvWAmrGtYhv/Wv8vjo86nvTAdJbkL2FH5Q5eOvElTDplkba+tZ5nNz3rcmQAsmqz2FO9hxiLkOEWDBzedma6267w9jWGlKLaZoL6kC/TgdWopbROxD8LRjDtzdBU4dneUuv635oWz3jposYinBLEBiSRW5dLbWutR5+G7up2CATDndpcz7aqvWBvBY0Ok86ECc/d+EpbJZ9kf+LW1mxvxtZuI9ocTUFjgVuIWgci9+AYpLVBqcV1MC31SqiZzndQzKhuqabd2c6S/CWuNrvTjs1hc83xFkcLxU3FHud297sgEHgTbzsaGyRJegJ4DpCBm4CNXr7GkFJc20KAse/OTICvjsIasTMjGF4UNBSQU5ODSlKRbE0m3BR+6M7mCEg9HfZ809mm0kBQsuswNSCVs0adRaQpEofTARKEGkIoqNjB5qYyYqyjOC7yOJYXLXedY9KZCDWG8lXOV6hValICUhjlP2ogPq5A0Heq90P5bmXlOyQd/A/kJdQVKjljc+5Sir6ufVFx+OfdC4XroK0ZgpOoNoeQVZ1FQ1sDcX5xjPIfRawlFh+1Dy2OFqaFTWNq+FTCjGGUNJWwo3IHob6hHBdxHMuLO78nAT4BRJsHLidCMEyxxoFfNNR1UcfzDVJyZ/Yvh+YqpRZNSDqou3mkO2j+yn5R5NTmkFuXi1lnJsma5LZzeCjSAtI4a9RZRPhGKHkzEmgkDUE+Qa4+gT6BXJx6MUiADCpJRWFjIUnWJHZW7qSosYhAQyBJ1iRUqMisyaTSVkmkKZJkazI6dd+frQQC8L4zcxNwP/DhgeOfgP/z8jWGlPyqZgKPYGcm0FdPdnlVzx0FgkEiqzqLRYsXuZLzo83RPHfCc8T7x3d/gs4ACx5UFJx2fq78gJ7yL+VH9AAhGl/y6nL5IucLAAwaAw/PfIg//XarK3H0hXnPYtQaWZy3mFhzLPdMu4eblt7k2rGJNkfzr+P/xZigMQP22QWCXlG6A945q3NH0poAl3wESPD+hUoIEIAxUHFifINh9QtQsBqAykl/4CGDk6UH5Mk1Kg0vzH+B6RHTeWHBC3yW/RlqlZqlBUsZHTiaDzM/dF36jsl3YNAYWJy/mIygDO6eejcRpohB/PCCYYExSKkhs/w/ULQBwsfD/L/C8idgy7tKH0kFF7wLqae5n3vw/A1KZf1Z/+Hapbe4lPWOizyOB2c+SLAx+LBmhPiGsL9uv9u9/bn5zyFJkquPWqVmcuhkbvzlRpcS36TQSbQ52rj8h8tdks13TL6DClsFb+5803Xu32f9nTMSz3AbTyDoLV6VZpZluUmW5btlWZ584HWvLMsuuQ1Jkp715vWGgsKa5j7VmOkg0KSjuFbszAiGD59lf+amMlbQUMCvhb8e/qSgUXDWC3DzVrjiJyVXpkus9u7KHWyu2OI6ttltvLP7XWZFzHK13bbsDm5Ou5zvzv6Ot05+i6/3fu0WelbQUMDq4tX9/XgCQf+QZdj0tntoZc0+2LsUcn7udGRAWR2vzFEePAs65+7u0CSXIwNKWM4j6x6htqWWyWGT+X3K7/ki5wvmRM3ho8yP3C7/9Kan+V3i77g642oenPkgGcEZA/ZRBcOYqhz4+A9K8czZt4MlAgo3djoyALITvrkV6ruEeHUzf+siMnhs4xNuEuHLi5azu2p3j2bsrtrN1oqtrmOb3caLW1+kub3Z1dbY1sizW551kxTfWLaR7ZXb3WrP2Ow2N0cG4JG1j1DQ4F6bSSDoLd6uM9MTs3ruMrwpqrURfATOTJBJT4nImREME+wOO9srt3u076ne0/PJGj1YY8DXMzShzOaZU5Nbn+u2otziaKG2uZxIcyRqldpNMKCDvbV7e7ZDIBhIHO3KSvjB1BVA2Q7P9pLN0OKe+1Ute9YWy63LdeW+dOSKtTvb3R72ANqcbdS21fLy9pe7zTMTHCPYapQcrKwfYfnjsOdb6K7+UGO5kkfTQTfzt8kaw776XI9Tuy5qHYrSplKPtuyabJraO+Whm9qb2Fe7z9O09kY0UmcgUNfaNB0025upb+tVWUKBwIOjKjl/oJFlmdL6FoKOwJkx6pTV6zpbO34GrbdNEwj6hEat4fSE09lWuc2tfV70vL4PVl8MFZmg0pDsl+jx9qyIWWwq66x6Hu4bTrg5CgCL3sL86PkeTtSMiBl9t0Mg8CYaHYy7CCImKGFkkqTkyYSNA2c7bH7Hvf/YC8Ec6tYUK3ne6+fHzCfIoOQZRJmi0Kv1OGUnRo2RZnvnKneIMQRk8Nf7i/CyY42qHCXXxeCvzKmoqcouuKNdmZc+ViW0rEvNF6KmKrs2HWh0ypws6kxbDty/khPj5/F9/mK3y8X5xfVoUkqAZ62YU+JPIcAnwHUcYAjgpLiT+DT7U7d+QYYgN4UzjaRBr9bT2qXIZ7Q5mnDfw+RsCgSHYbB3ZkY01U1t6NQqDLq+SyBKkkSwWU+REAEQDBPmxczjopSLUEtqdCodi8YuYkrYlL4NUr4H3jhFict+63RGN9bzfxNuwVerKOzMj5jN+Yln09CurECPssTz+PQHCA7sFA2YHzuf0xNOd9lx+ejLPeoXCARDQtRkyFkCvz0Gvz6q5CDIdsj8DqZcpexSqtQw6QpIPwPCM+DUx5VK7UBadQmPzHwIi84CwPSw6dw04SZ8NIq8f7xfPM+e8CzLCpZx44QbifBVHkbjLfHcN+0+Psn6hGfmPSOcmWOJvFXw0hx47zx4dQFs/wQmXArL/qXkzfz6qFLP6Py3lBwtgKgp8LunwMfiPlbqqTDlamWOavTo447nurGLXGG/Fp2Fv8/6O2kBaT2aNSZoDP837f9c9/YFMQu4JO0S1F3CjLUqLX8a/SfXophJa+Kv0//KlNAppFpTAcVJnxgykafnPU2oUXH+k63J/Pv4f/dKiEAg6A5JluWee3nrYpK0WZblCf0dZ/LkyfKGDd1s/w8wWwtquf2jLfz9rCOLXX78p0yumZPIiemhPXcWDBd6nY04VPOyP9gddgobC5EkiShTlNsPU4/IMiy+X6l5AMrK9dx7IfsnimZeR6taS3juWgwN5VTM/TP1rXUE+obi7x/nMVRTexP7a/ejVqlJ9EtEpxGqNj3QpyzZkTg3hwU//RVWPe3eNvMmJRfBFAKpv4OwsUriddc5W5OnhAb5RYHOSHFjMTa7jTDfMNfDYFcqmitcIWf1bfX46/2RZRk/vR8BhgCP/sMYMS/7Q3M1vHEqVHTJYTnuL7D6v2DvElqm0sC1q0BvgtZ6RWnS4Nf9mPZ2qM1T7s/WOFCpaWpvorSpFIPG0GdHuaihiFZHKxGmCJdTfjC2dhslTSXo1XoizZEA1LXWUWmrxKw1E+KrFFmuaK6gvq2eQJ9A/H38+2THESCUBY5iBjvM7OmeuwxfimptBJv7HmLWQaBJR1FNc88dBYJBQqPW9CrEoFvsrZC7ostgPtBSB4XrifxofWe7wUrwwocJDko95FC+Wl/GBAv1MsEwwt4Gecs926v2giVSqby+4gmIngbpZ7r3sca6Hfb0wBhsDO5RTUpwDNBS5+7IdGA/KEfGaYfGEgiZC0QefkyNVhFu6YKv1pdEf8+Q4N7Q4ZwcDoPWQIJ/glubn94PP727wyXmvcBbeNWZkSQpGbgDiO06tizLJxz475vevN5gU1jTTKBvP5wZXz0FIsxMMNKpLVBW+nyDlZXp4s1Ke7sNDFYqT3qI7KhxNNltxKl8GLXjGzhodbmksYSixiL89H7EWeLQqkUemWCYodFB2plQtMm9PSQd9i3tPE4/C1SeEdst9hb21+2nzdmGhESbs41oUzShvsrOfLuznby6PGpbawnzDSPqQB6ZU3aSX59Pha2CYEMwsZZYIVd7rOAbBLGzIa/LIpGjFQxWRQigA61R2Y0p26m0+8cor15S1lRGQWMBJq2JOEtctzssNruNPdV7qLZVE2mOJDWg+8WoutY6cutykSSJOEscFr2l234CwUDi7Z2Zj4EXgVeAbkrWjmyOtMZMB8FmPTuL6/p2kr0VqveBfyzojEd8bYHAKxSshw8uUuQ+JRWc9wYknwJZ34MkkRM3g7fyf+CLpTcBSoLz32c9zKQuIThbyrdwy9JbqG6pRi2puXnizVyYciFGrZjfgmHG6LOgcL1SKFaSYNwlSlJ2x0p50kKIO87jtNrWWl7b/hqZNZlE+kbyafanyMiEGEN4Zt4zJPon8mXOlzy6/lHsTjsWnYUn5z7J5LDJ/Jz3M/etuI8WRwsGjYFHZj/C/Jj5wqE5FtCb4ZRH4ZMroDJL2e0OTILzXofProamSsWxOesFyF0O398BToci23zh+xAzvcdL7Kraxc2/3ExZcxkSEleMuYI/jfmT265JQ2sDH2V9xH83/xe7rMzPR2Y/wpzoOW5jFdQX8MDqB1hXug6AGeEz+OuMv7occ4FgsPC2AIBdluUXZFleJ8vyxo6Xl68xZOTX9C/MLNisp6C6DzszeavhqQx47/fwRCpseOOIry0Q9Jvmavj6ls66BbITPv4jzLkTrlkO165kT3sNX+z9wnVKYWMhr+14nVpbLQC1LbX8bdXfqG6pBsAhO3hy45Nk1mQO8ocRCHqBNQ7OfgmuWQHXroTE+ZD5PRx/J8y5CxxtkLPY47RdVbt4c+ebTA6dzCfZn7hkl8uby3ls3WPk1ufy97V/x+5UFJ7q2+q5d8W95NTkcO+Ke111Omx2G/euuJe8+rxB+8iCISYsA/70PVy9FK5dARMug8QTYNFvcPUvsGgZmELh29sVRwaUe/OXN0CjpzR+V5ram3h8w+OUNZcBICPz2o7X2F3tHtq2s2onT216yqVAVt9Wz8NrHia3Ltet38/5P7scGYDVJat7rlUmEAwAXtmZkSSpI4bka0mSrgc+B1yae7IsV3vjOkNNUU0zp44JO+LzQ8x6imptyLLc8ypbTS58cDHMugUiJym1DX79p1Kc7fi/HLENAsER01wF5Ts926v3QsbvAcgv+c3j7a0VW6loqcDf4E91SzX76jzrEHRXw0AgGBboTYpKGcDSRyBvpfLqoL0ZZt3qFmpW1FAEKKFmB7O5YrMr2b8rZc1lVLZUusnVguLQVNoqjzy3TTDy8A1SXl3xi1Je0H39o6oc5R5tOnQOSl1rHRvLPNeXSxpL3I67ux+XNZd5zMNlhcs8+q0qWsWlaZce0gaBYCDwVpjZRkCmUy3iji7vyUCCxxkjDFmWKa5t6dfOjEmvQZZl6mzt+Bt7CFf79i+QdobiyAD4RcOJf4fv74TgFEj73RHbIRD0haKGImpaawjWmgmNm0Ph2LMp8PXHIqlJWfE8GmsilG4HSU2M2TNue3zIeHQqHTsqd2DRWRgXPI4EvwSCjcE4nA6+3/89Yb5HvkggEAwILQ1Qsx/UGghIVFbBY2cpIWddST7ZI2emI0m6u1yEccHj8FH7EGIM4bT40/DX+5MSkEJ9az1WnZUI3wiKmzorufuofVx1aQTHCE2VSm6ijxmsCZ45WX7dhHEFJCr1kA6Dn96PqaFTCTQGEmmKxCk7WZy3mHDfcMqayqiwVWDVW7sVrAg1hhJkCGJf7T5aHC1EmaOYEzUHlaRiYuhEADaUbmBW5CzqWusoaizCoDEQbY5GoxIlDQUDi1dmmCzL8QCSJPnIsuy2FCVJUvfafSOMqqY2tGoJo+7I/2SSJBHm50NeVfPhnZmijVC6DaZf795uDIDj71BCfSInuRfIEgi8jFN2sqxwGfetuI/6tnrCfMP4x8K/89Cah8mrz8OgMXDj1Bs4M28Zfov/BpJE2h+/4IzEM/hq71cARJoiuST1Ei7+7mLq2+oJNgTzwIy/8ezm//J5zufKGONuIMFXxFgLhhHV++D7uyH7RyU3bMpV4BcDDUUQO1OpBQIQPV0RADiI9MB0/pD+BzaWbeTcpHP5LPszZGSCDEGcHHcyn2d/zqKMRTy56Uma2psI9w3nD+l/4L9b/st90+7jH2v/QXFTMT5qHx6Z/QixlliPawiOUkq3w6dXQcUeJWfmpL/D+ItB10XSOzBJkcFf9pjiZBuscOp/DrsrA4qK2XUTruPh1Q/zzb5v0Kl0XJFxBb4aXy769iIqbBVYdBYeO+4xbpt4G89ufha7bMesNXP/9Pv5Of9nntvyHHannXHB47hzyp1sLt/Mi1tfREJiQewCxgaN5dqfr2VH5Q40Kg3Xj7ueC1IvcNVaEggGAm+7y6uAib1oG3EUVDcTaum/XxZq8SGvuplx0f6H7rT6OWXnpTuFp+AUZSXwq5vhko+VpFSBYADIq8vjz7/+mTZnGwDnJ5/P4xuecMXv2+w2/r3xPyTOepRZALJM4ptncstVP3Na/Gk025sJM4Zx5U9XuiqbV9gq+Ouqv7EwbiF7ava4xpjgN4oMXyHRKRgmbP1AcWRAyQ1b97KSI7P+VUXwYu7dEJQCCXOVRaaD8Nf7c9OEm1xqZifGnsjmciW87JnNz3DFmCt4ZN0jOA9UcC9pKuG9Pe8xOXQyD655kOdOeE5x/o1CzeyYorVBcaIr9ijH9hb47i9KLaOYaZ39anJh95dKDRrZAe0tSmHXiAlgtB5yeJvdxmvbXyO7NhuANmcbL259EaPGSIVNybepb6vn5qU38/HvPmZCyASqWqqINkdT21rL05s6q2vsr9vPiqIV/FLwC6Dk3yzOW0yKNYX9dfsV8512ntn8DBlBGUyP6FmcQCA4UryVMxOGInZukCRpAp3hZhbgqJAoKuhn8n8HwWY9eVVNh+5gq4Wsn5Sk00Mx5jz49jbY/bVSdVogGACKmopcjgxAtDmaXdW7PPu1uqfEhax7lZBzlPm7onCFy5HpoKqlCpPO5NZW2FjIkZWiFQi8TGsD7P7Ks70qByxRynu7v4JRJ8GYcw45jI/Gh7RApbL6h3s+5KVtnff0dme7y5HpoLChkFPjT6W8uZzq1mpmRsz0zucRjBwaK9xlmTuo2X+QM7NfkWUuOyiHsbHssM5MTUsNK4tWerQfnMPV7mynpLGE2VGzXW1v7XzLrc8o/1GsL13PwWws20iCXwLbK7e72vbX7xfOjGBA8dbOzELgciAKeKJLewNwr5euMaQUVDcT1A9Z5g5CzT7srWg8dIc930L4WPA5zJasWgtTF8EPd0HSiaA19NsuwVFKY7midOMbDL6e8dTtbTaKa3NQSSoirEmou0goBxuC8dX6sjBuIUGGILQqLTHmGBL8E0ixptDQ1sB3+78jSG8l94S7UTsdROz4AnXUFNcYgYZAJCSXmhOAUWOk3dHuZkegbxh55TtQSSoiA5JRqTUUNSjOVLhv+CErTQsEXkdrhJiZUH5A4Sl8PIxaoNSXqcju7Jd6ClTvB6cT/KORVRqKqjORAVlrwIGMTq2j1d5KnCXO7RI6ledvSYBPACGGEKx6KwF6992e2pZaqlqq8NP5EWQU+TNHLQZ/CEqFgFhlN6a1AXZ8AuaDcgrNYWCNp2zeXTTqjIRU5mDe8A4YAqEmT1HZ84sGrft906w1kxqYyo7KHe6X1bg/Q0hIBBrcfy8OllsubCzkpNiT2FDmLkaQbE2mqLGImWNnYrPb+DH3RyJ8I6hvrXeFsXUUyqywVVDfWk+QIcijoKZA0Be8lTPzFvCWJEnnyrL8qTfGHG7kVjYRZOr/A1WYnw/r9h9G3G3nZ73SiidsrJLwt+pZRRpXIDiY3BXwxQ1QmwvBaXDmfyFqsuvtsuocXt/1Nh/t+xqVpOKKlAu4KPlCAg4UX4v3i+fBGQ/yxMYnKG4qZkLwBO6ffj//3fJfXtr2EgE+Adww/npklYazcj9Eo9Jw5aRzuDBxDh1rgwl+Cdwx+Q7+veHfyMhoJA33Tr2bl7a94rLj0pSL2FmTyaKtz6NRabhrwq3YJYmntzxLc3szJ8aeyC0TbyHG0vuicALBEaNSw5QrIfsnRRLXboOVTynt4y+FwARFGrehFJ6fDs52Gs58ni/kWpaXbyI9MJ0PMj+gub2ZWZGzSAtII7Mmk3/M/gf3rbgPgHWl67hqzFW8uuNVALQqLZePvpxv933L32f/ndTAzgKFOyp38LdVfyOrJotw33AemvkQ08KnidCzoxFjAPzuSVjyICz794E82bshZLRbN3twKstO+RsPbX6aqpYqJgSO4f/Of5nknZ/CLw8pCntjfg8n3KfIix/ArDdz84Sbuf3X22lsVxZVT4k/hYygDDSSBrtsR0LiL5P/QoKfu25TRlAG82PmsyR/CQBtjjYWxi1kdfFq9tbtBRRHZkHsAp7f+jwvbXsJk9bElWOuJMAngKt/uppd1bsINYbywMwH0Kv03LPiHsqay0i1pvLgzAdJD0ofwD+u4GhGkmW55169HUySbu+muQ7YKMvyFm9dZ/LkyfKGDd1IEw4g57+0mvmpIYyN8u/XOLXNbdz92Xa2/u0kzzfbmuE/o+Dc1+CgMJxuqS9RimbduKHHxD/BEdPrJ4ahmJeHpHofvHS8srLXgTlMqV1wQDji/a2v8MiWZ9xO+/e0+zk59XxAyZk5/5vzXWFix0UeR3N7MxvLO6U9JSRunHAjz25+1tX2+JzHOSmuc3632FvYV7ePSlsl4b7hxJljKazeTWFdPn6GQPKairh3zUOu/rdMvMUtNhvg0rRL+cvkv6BWqfv5hzlq6NOT7LCamyOF+mLY/gksvt+9/cznlALGH//J1bTyoje4ds3fup27pyeczu7q3YwOHM05o86htLmUOEscCf4JbCnfwsayjagkFZ/nfE5pUylR5iheXvAy0ZZoKmwVXPrtpW7qZgaNgY9O/2i4SjWLedkf2pqUgplZP7i3X/ULRE1yHe4pXscFP1/tFqo4PmA0z/tPxrzk4c7zjvsznHC/K7e2sbWRf6z7B6HGULQqLWqVmm0V27g49WJCfUMpaSohyBBEgl9Ct7vhda117K3dS7O9mThLHFHmKMqbytlXvw8JiQS/BF7Y+gIfZ33sdt6dU+7kX+v/5TrWqrQsGruI57Y852qLNkfzzinveOwIeRHh/R/FeFsAYPKB19cHjk8D1gPXSpL0sSzL/zrkmcOcgupmQsz935nxM2ixO5zUNLVh9T0o1CBvpaJS0htHBsASDvFzlMS/0/7TY/fM6kxWFa/CX+/PibEneuQtCI4iavLcHRlQVpJrC8ASgb29hW+6KW62tHiVy5kpbCx0y3dJC0zj5W0vu/WXkT3qYiwvXO7mzPhofEgPdF9xiw8ZR3zIOFpa6nh485OudoPG4Cqo2ZXv93/PlWOuFCE2gsHDGAS7vvBs378M/OM6jwMT2Vabg4/ah5qWGo/uK4tWsiB2Ad/s+4abJtzEpLDOh9Kqliq3XBpQcmcKGwuJtkRT2ljq5siAksRd2FA4XJ0ZQX9oLPd0ZEDJ1+rizOTV53nkXG2p3kl50kWYuzZu+wim3+AKMS5pLuGH3B9cxVo7mBkxk9lRs0myJh3WPD+9n0uGuYMQ3xBCfEMAKGsq44f9nvZX2ipdOz+g5OS0O91DjQsaCihtKh1IZ0ZwFONtZyYQmCjLciOAJEl/Az4BjkepRTMinZk2u5PKxlaCzP3PmZEkiSirkX2VjUzyPUgFJ3uxki/TFzJ+D1/dALNuBv/uw3BkWeaJjU/w1d6vmBQ6idqWWp7Z/AxPzn2S8SHjj+yDCIYnTRWKso3BqqzGdd15VeuUmGxAo/VhjF8C2yq3uZ2e2iW0wOrjnkha01JDqDHUVT26g4Pj/3v6QeyKVmNktCWRPdWKek+roxWz1oxFZ+Gk2JMw68wsL1pOoE8gRu1RoSUiGCmo1DDlaoicCDu/UL5boOTOmMM7+9nbGBs6iQvUKvx1/h7DxFhiKG0qJd4Sj1GjzOHallqa7c1E+kZ69DdoDPjplPwBi86Cj9qHFod78U1/H8/rCI4CdCbFUfYNhPjjlQWoXV96FNA8+N4MEOgTiKnNXWyF0DFuks5mrZkYcww+ah9mRMygqqWKn3J/wqo/tGhAX/DV+hLvF0+Lo4XZkbOpba3lp9yf8NX6uhwZ10c96HfDoDFg1rm5YgJBr1H13KVPxABtXY7bgVhZlm1Aa/enDH8Ka5oJNOnRHFy46ggJ8/Mhp7wbEYB9v0LYuL4NZvBXpJp/ffSQXZ7Z9AwrilbwwIwHuCj1Iq4bfx2Xpl3Kjb/c6HqIFIxw7G2Kut3L8+DZiZD9Mxx/UC7VwkcgcJTr8JzEMwnw6XSoo30jmRN1vOs4wS+Ba8de6zr+fv/3SqiX1BnqdWLsidS21LqOY0xRHB/ee9UatUbLhcnn4a/3B5TaNhadhUVjF7G8aDnv7X6P0YGjuXHCjcKZEQwe9aVKzsJ3f4adn8Oky5WHS/9YcLRDUzlM/CONcbP4YvbV3Lf2YT7K/Ah/H38ygjp1+QwaAyfHncz60vXcMeUOzDoza0vWcvmPl3PqZ6fy7u53+ddx/0LqEgFzy8RbSA1QcmaiLdHcPfVuN9OuzrjaI59BcJRgCoaznlOc5VXPQsFaOPmfilPSheSANM6MOdF1rJJU3D/xNkJ3ftvZSW+G4//iJgIQZgrjvmn3EW2O5q1db7G+dD23TrrVa7kqJp2Jv0z+C0n+Sbyz6x1WFa/ihvE3MC5wnNscvzTtUkxa98iQDrsEgiPB2zkz9wNnA18eaPod8BXwOPCyLMuXeOM6gx1nuzSznKd/zuauk1N77twLvtxShK9ew/2nd7mBNFXC0+PggveUFcG+0NoAX1wL1yxzS/YDWFOyhruX3c390+/HondXSFtbspZv9n3DZ2d8Jh4UD83IyJkpWAuvL3TfiTnx7xA9Rcmt8o+G0NEeyncFFbvIqc1ChYqkgFQiApPd3m9sayS7Jpuy5jLiLHF8mPkhYb5htDvb0aq0ZFVncWnkXGpqclAjkVxfSXjMbEg5uU/m51fsJKcmC41Kg9bHyqIl17m9vyhjETdOuFEkPXcichMGkrUvK/mIXTnzOSjbBeteAqcdznmFlSYL1y537/ev4x7DR62j1WnH6mPFZrcRZYoi0T+RnNocLvjmArcQm5nhM7kq4yryGvKIMkcxOmA0Zn3nCnWLvYWc2hwKGwsJMYSQbE0eziHCYl72B3srfHEd7Oiio6RSKzkzEeM728p2Upv5HVmhiVS3NxKnDyRx3xq00xYpNWrabRCSBkHuu+TtjnYeWfsIn2R/4mqTkHjv1PfICO6/OL7D6eCJjU/w9q633drfOvkt9Go9BY0FBBuCSbYqvzNZNVlU2CqIMkWR5J+EXtP/8heHQfx4HMV4NcxMluWHJUn6HpiFMnGulWW5407lFUdmKMivaibECzVmOoi0Gli776C8gPzVysPmkSQ4683K7szyx+GMzkTsNkcbD6x6gMvSL/NwZACmhU9jZ9VOntn0DHdPu9vjfcEIonyPuyMDsOxfcP2aw6rjRQenEx186FU5k87EhNAJgBKn/Wn2p24yywALjFGc8v0DnQ1NNX12ZmKCRxMTrCj2vLPrHY/3P8v5jItSLxI5M4KBp7URNr3l2b7/NyhYpzgyAPt+Y02U5w7JS9tf5t1T3u3W4city/XIFVhVsoo7p97JlPApHv1ByTkbEzSGMUFjun1fcBRRX6zsBHbF6YDKLHdnpioH/1/+ztSDz594qVKu4RBU2ir5aq97DSUZmb11e73izFS1VPFFzhce7Tm1OZyfcj6jg9xV2SaFTvLoKxAcCd4OMwPYDHwMfAaUS5I04vVU91c2eaVgZgfRVqNnmFnuCgjux85P2hlKXHddkavpgz0fEGwIZmzwofNwzks+j6/3fc3e2r1Hfm3B0HMgF8YNvyi3eOne0tTWRLXNMwnfR+3jFpbWgeXg20hQCk3NVVTX5ff52tB9PHiEKQKDqKckGCgaKzoFM9R6t3BMF77BSlFjvRkyzoPEeUQYQ11v69V6FsQs4KxRZ6FTd59f2V1OgEVnQafSUdlc6eHoCI4RmqqgpU6pcWQK9Xzfx4/2lnoqq7JotdVCN4uTGKzK+YfBR+NDqG8okaZIzh51NnOi5qCRNFh0h6lr1wd81D6E+4Z7tIsaMoKBxqvOjCRJNwFlwGLgG+DbA/8d0eyrbCLU4r2ifcFmPbW2Nhpauvxw5a9WtoWPFB8/SJwPq/8LKIo3r+14jbOTzj7saRadhZPjTuapTU8d+bUFQ0/ERKX2UAcqNZz09+6dnENgd9pZXbyaq3+6mvO/OZ9Xtr1CaVOp6/1Q31DunnSb2zkzwqaSXJnrOm6PnMzqqHSu+vk6zv/pCl7d8BTl1X1zlMcFjSPB0rnirVFpuGXCLfhq++6YCQSHpb4Ylj0OLx8Pb58Je5cqwhkzbnR/MDRHKA+LoaNh5s1QvAWW/oPpWithxlBG+Y/ixgk3kt+Qz3u73+ODPR9Q2VzpcbkkaxJzoua4td0+6XZe2vYS5319Ho+seYT9dfsH+EMLhg1NlbD+NXhlHry2EIo3w8J/uKSUAYg9jhxzEH9b9TfO+3kR9628n0yDL6Sf6T7Wwn8q4cSHwepj5YEZDzArchYri1dS1VLFfdPvY3TA6MOe11ssegt/nvxnt7zKZGsyYwLFrqJgYPF2zkwOME2W5SqvDdoNgx1nO+ffS7lh7iiiA7yXV/LXL3fw6LkZTIoNUOJbH4tT8mX6EzPaVAFf3wK3buP93B/4Ke8nrh9/fY+ntTnauGfFPbx84suuxFOBi5GRMwOK7HLJVmWFOSRVcW76ELa4vWI7l31/GQ7Z4Wq7ftz1XDvuWiVXpbWRtl8fZbc1lFzs+Esa0mpKCEmYr+TsSBLb4qdx2W+3ucmG3jT6Tyya3F0JqkNT1FjE7qrdNNubSfJPIiUgBZU0EBvJIxaRm9BfZFkRTvmti3iKSg1XLobISUp+TNkORQUwfCw47Mr367OrOvurtRSc/ybZGolbV9zjFoJ595S7uSTdM7q6ormCPdV7qLJVEW4K5+WtL7OubJ3r/QnBE/jv/P92Gxo8AhDzsi9sfg++POg3+tw3oXaf8lyg1lIdMZ4rdzxHTn2nkxthDOPtOU8SWluk/O4HJilztIfda4fTwVObnuLNnW+62jQqDf879X+kBfZjMfWga2RWZ5JTl4Ov1pe0gDQiTBFeGbufiJyZoxhvSzMXoBTJPGqwO5yU1LZ4dWcGIDrAyO6SBsWZKdkK1tj+OTKghEFET8O5/lXeqljCH9L/0KvTdGodJ8aeyMvbXuaJuU/0zwbB0OEf3ePK3OHYU73HzZEBeH/P+5ybfC4hxhCoykG35jnGyU7cNPf8YpVaR3oLO/2sHvUP/rf3K85JOoegPtTFiDRFEmnylK0VCLxGY5mSzN8VpwNKtinOTGi68urKb4+5Hzvaid74Dj8mTPTIJXtvz3uclnCah4xysDGYYKNS5Hhl0Uo3RwZgc8VmChsLSdeLauhHNW1NsPZFz/acH5Wac7VKmG7+Ba+7OTIAxc2l5DUUEJp8Sp8uWW4r54M9H7i12Z12smuzvebMqFVq0oPSvaaQJhD0Bm8vde4DfpUk6R5Jkm7veHn5GoNKSV0LfkYtOo13/1RRVgO7iuuVg8INEJR8+BN6S9oZ2Fc/h6+kZZR/N3Hfh2BO1BzWFK+hqLGo586CYYu9rYVmm2fhvt7QXRiXv94fveqAk63RK7HavkGQciqEj1fatUYYNR+ipmDSGJCQGB88njlRczBpTVh1fujUR7AYYG+Dg+smCATeQq0HYzcF+vSHqXVh9swHQG8h3i+O4yKPw6fLPA/wCUCHWnloPQTdVVnXSBq3cQQjGIddEZToDpWm+/nk4+9W8NhHrXWTNe7AoDFgb2+l6eD8xtZmJberG3QqHX56Pyw6C3Oj5zI2SAlNNqhFPqJgZONtZyYfJV9GB5i7vA6LJEn+kiR9IknSHkmSdkuSNMPLdh0x+yubCPfz/g9LbICRncUHNrEK13WfcHokBMRTpJa4ShXQJxlbg8bArMhZ/G/3/7xjh2BQkZ1OthSu5I5lt/PHnxfx8fY3qKrN7dMYo4NGu4UDSEjcNvk2/HwOJG+GpMHvnoGM86E2D/wi4ZxXlB9lWy3YbYy3pnLvtHsxao2UN5dzUepF3D35L1hMYb03xOmEvFXw0R/hjZNh8ztKbLlA4E2MVljwgHubfyxETPDs21QN2z+GwEQ3UY32kHTWjjuLj/IXU91SzZUZVzIzYiYqScXvEn7Hj7vfp/rXR2DD69BQ5jFsol8ic6PnurVdlXEV0RZRb2PEU7RZkVl+/SRY/bybOA+gLA7NukW5f3ZgsELiPOiyIBVXvJOLE93zY86IORGtjz8PrryPPyy+mjc2PUtJZSZk/QgfXqTkf617BWoK3M4LNATy4MwHOS/5PEoaS/DT+3H/9PuFUp5gxONtaeYHASRJ8pVl+dDLUZ48Dfwgy/J5kiTpgGFT9GR/ZRNhXg4xA4gJ9CW7vBGnU0ZVtFGRVvYC1S3V/KDXcFn+VnZPk90TCXvghJgTeHjNw9ww/gZRd2aEkVm6gSuX3kybU6lZ+1D1Hhrbm/jTxBt7PUasJZaXF7zM1oqt1LTWMDZ4LKMDuySGOtohfyWsPRCaU7ZTUeGbdg0UbQSgoWQT/9rzikuVaXf1bgKm3Mk0juv9hynZCm+foVwP4Msb4dTHYepVhz9PIOgrzTWw4EGlCGbHPa+7nZT9v8GnVykPm7Nvh7ZGMFjZETmGRctud4VW7qzayd1T72ZmxEze3vU2+Q353JvyBy5a+gi01MPsW92G9ffx5/+m/R9nJp5JXn0eKQEpZARmoFVpB/iDCwaUikzlHtZ6IPrix3sUZ+bEB0Hd5bErZoaSo1W4HjQ+ED0V/GPgj99A8SYwh+MTPY1FzjZmhE4mp24/CeZYIv0TuGLpDdS1KguiT9Rkkd9cxj2Za9EVHAhbLNkCJ9themfNLlmW2Vaxjdd3vA5AZk0m60vXMz54POF0s0skEIwQvOrMHNhReQ0wATGSJI0DrpFl+ZBZ6JIkWYDjgcsBZFluA9q8aVd/2FfRSIjZ+86MSa/B4qMht7CIBFstWLyTH7CyeBXtEePR7t+CqXQnjeG9X3EJMgSR5J/ED7k/cE7SOV6xRzA47KnJcjkyHbyR9RGnJZxGiH98r8eJ9Ysl1i+2+zfrCpUV5q601OHKq1Tr2OFs8pCXfWPnm5wSfyqBhm5CerqjaEOnI9PByqdg9FlKiJtA4A0ayuCXh5QEap2vUrDQaVceJsMPkrPfemDH2lYDvzysrKqPu5hVRo1HjtgXOV8Q5htGfoOS8/BawY8sTD2FgJVPwdgLwOL+0BjqG0qobzdyvIKRS9muTkemg/UvKQsyAV3uxyoVRE5UXl2JP055HSAAmBOYRIcO3pLMz1yOTAef7/uGPyZdSFxBlxys9a9C+lmuOVfWXMZbu9xrKLU4WsiqySI5wEuh7gLBEODtMLOngIVAFYAsy1tRHJXDkQBUAG9IkrRZkqRXJUnyCN6XJGmRJEkbJEnaUFFR4WWzD01OeSPh/gMTvxwX5MuO3TuVKr1eUGqSkVlRtIIxQWOojZtJ6LZPez7pII6POp7397zfb1uOFYZqXh5Mdyu5PhofNJIX1ytUaiXP4GA65q7sQHfg/2MtsYwNGotGpcT/d5Xq7JHuhDC0RvdwDEGPDJe5OWxRa9x3YzqKYXY3xw8ugGlvBUmFQeOZa+Cj9qHV0QpAtDmaCUHjUDvtB+bwERRFPso4Jualpps6Qxofr93DtGrP+71WpUV98CKQ1ui2E6SW1PiofdCpdIwLHkeUOeqQ4wkEIwmva53KslxwUJOj246daICJwAuyLE8AmgCPcvSyLL8sy/JkWZYnBwcHe8fYXrC/qnlAcmYAYgKMbM8thQDPKtJHwr66/TicDsJNEdRFTcZStAltY99yDcYEjaHKVsWuql1eseloZ6jm5cGkB6Z5FLS8efSVBPh5MfbeLxrm3uPeZo3rTFZ1OhiPD3dNuYuMoAxMOhPXjbuOu6fc6a7o1FAGW/4H75wNSx5SVjG7EjVFCefpygn/16eaOYLhMzeHLcZAmP9XzzZzGLx/MXx1sxL+I8sw/hL3B1G1FlJPZ0bEdDeHRkLipLiT2F25m9sm3cb44PE02BtZEzmGut89CaaQQfpww5djYl6GZYB/nHvbvHv7pTbZleSAVBLM7jvoi9L/SGTWYveOM29WVE4PEGwM5q/T/o+rMq7CqDEyMWQid025i7QA7yiZCQRDhdelmSVJmgnIB3JfbgZ293BOIVAoy/LaA8ef0I0zMxS0tDuobGgdkDAzgPggX37Z7YAk7zgzq4pWkhaQhgQ4tT7UR04gZNdXFE29otdjqCQVsyJm8UnWJ/x1xl97PkEwLIgPGctrc55iZfFKSprLOT5yFuNDJ3v3IpKkPNQFjoKcnxUFvoQ5SuiNWgsaA60RE3jmt1uw2W0ArCpexQNTunydnQ5FjnTFAQnwvb8otRau+KEz/CIkTYkZ37tEcXySFyoOjkDgbZJPgcu+UBKn/SIhJB3evxDaD6jobX0frvgR4o+Hiz+GnMWABEknQtxxpJXt4K3ky1neVkGDvZU55nj8/ZIJn/k37l95P43tipLVyuJV3Df1Hi4csg8qGFT8Y+DST5T7W2U2jFoAMdO9NnyYpOOZMdeyprmQnIZ8ZgSNY6LGH9XJj0LOErBVwaiFEOuppVRYt5/ntz7vOv614FdmBmaAJcZr9gkEg423nZlrUZL5I1GclJ+AGw53gizLpZIkFUiSlCLLciYwHxgW2wK5VU2E+ulRqwam1lJ8kIndzX44A4z93iJzyA7Wl27gorSLXG21sTOIXvMyxZMuRVZ3s+19CGZHzubBNQ9yx5Q7ug2jEAxPRoVNYFRYN0pM3sRohZSTlVdXDvxQb9/+psuR6eClXW9xQtQcrJYopXbC6v+6n9tYCuW73GPJw8YoL4FgINH7KupRifOUHcbXT+l0ZAAcbZC7XMlpGHWC8upK9k+kLf0Hab5BoDFAXQFETmb3vFtcjkwHL257mfmxJ7pqzAiOcoKSlNdAULaT2A8uIdYcriwq/foKIMP1a2D+/Yc+rWYvL+16062tvq2ePTV7SAgd1/1JAsEIwKthZrIsV8qyfIksy6GyLIfIsnypLMtVvTj1JuA9SZK2AeOBR7xp15Gyr6KJCL+Be5j3k5ox0kKus//Jn7uqdmPRW7Dq/V1tbeZQWi3hBOxd1qexAgwBJPglsCR/Sb/tEhxbdFcPQWkTxZcFwx0JLBHd15453DmgSIfXFbi3Haa7QOAVGkoUpT1Hh/jLkU4wMTEFIxuv7MxIkvQsHFT+uAuyLN98uPNlWd4CeDkmpv/klDcSNkD5MgBU5ZCor2N7ZTgJ1p67H441JWtIDUj1aK+NnUHotk+pSl7Qp/FmRszkk6xPOD3h9P4ZJhhZlO2C7J8UGdGUk8k0B7G2YjN7ajIZFzSWiUEZFNoqWFG0ggS/BGZFziLOL851+pig0Rg0BrfdmWvTLsXaodbnHwMzboIVj3de0xQGIV0koAeJ6qZW1u2vZll2JSmhZo5PCiI+2NTziccIdc3trMut5rfMcuKDTcxNDiYx5Cj5+7TUQ/4aZb5bwqBgnZIrM+ZcCBqlODQrnlQeEuMOo2GTeAIse8xdfe+420gLSsGkNbntziwau4hgg9iV8Sa2Njub8mtZvKuMYLOeE1JDSAu3DLVZCpVZSshXRRYknaTsXhsP+qFvbYK85UqYo85X6Rffk2YSEDoazBHQUNzZNu06pU7S4U6zJnJd2h94bGvn7rhFZyHamsRHmR+xpXwLqQGpTA2bSmqg5/PEkVLZXMnG8o2sLVlLWkAa08Oni1pKAq/irTCzDV4aZ1iRVdZAlHUAw6yq9xJncrC53M6ZSUeuJtLutLOlfAuXj77c473G0DRCdn2Nb9lumkJ7n+Q3PmQ87+1+j8KGQpfiieAopyIT3joNmpWK0sVBcTySvY5N5ZsA+HrfN5wWfxplzWVsKFO+8tF7onnlpFeINCnOSkr4ZN6Y9wxf7/uOYlsFZ8YuZEpEl1hxlVqpSxOUBDs+UQoUjj4XAuIG9aM6nDLvrMnjycXZrrbkUBNvXTGV8AHcjR1JfLqpkIe+6Yz4fcNq4P2rpxMdcBTUoNr1Jfx0H8y4ET6/prPdGAhTroSVz8Cp/1GKZEaMP/Q4ERPg8u+UvC9bNUz8A8TOpLluL9eNu47MmkwqbZVMCJlAoL4vOz6C3vBbVgXXvrvJdfzSsr18fM1MUsJ6rNU9sNTkwbvnKcWFATa+DgsfgRkHRd3v+wU+ukwRmQBFSvnij91kmbvFGguXfQY7Plek7DPOg8T57jVsDsHpCacT7BPAVwU/k+AbycKE0/h071d8kv0JAF/v+5pxweN47LjHiDT3v2REu6OdN3a+wdu73na1ZQRl8My8ZwgyCql9gXfwijMjy/JbPfdSdnBkWb7JG9ccDHLKG5kWH9BzxyOlIptEaxJfl/Uk+HZ4dlRuJ8QYjPlg+VAASeXandl34v/1ekytSsu0sGl8kfMFN07ofeFFwQimeLPLkQHItkayac8mty7f7v+Wa8dd63JmChoKyKrOcjkzAKMjpjM64jDJruZQGH+R8hoiCmqaeX7pXre2rLJGMksahDMDFNfaeGJxlltbYY2NXSX1I9+ZaSiDJQ9C6mmw+R3395qrAAla66C9pWfhCZVKKXQYPdWteXf1bv694d9EmaOw6q28tO0lAn0CSQpIIsHfO4Ivxzp1tjYeP2iO1tvsbMqvGXpnpmxHpyPTwa//hLQzOhXNWhthzQudjgxAu00RV+nJmQFFKOWEvquQ+VsiWWj5PQtTfw/AptJNfJrtXsZha8VWsmuyveLM5Dfk897u99zatlduZ2/dXuHMCLyG16WZe2DWIF/viHE6ZXKrmojwH8idmRziwwLIrHbS7jhklF6PrClZS5L10AWvamOm4pe/Dm1T32SaZ0XO4oucLzyKwgmOUuzuRTfbe/nvbu+ozzGCcDhk2h2en6/dKeY6gN3hpM3u+bewd/M3G3E47WBvUep+tLuLVaA/8BBsDod+zAW7Q/lOFDYUsr1yO3annRZHCw65fwtXgk4cThlbm+ffs7WbeTvodNxLVRrw8TvQ1gpd//2d9s75p/NV5iNAe9Pg2Qm0y+3I3WQJHFz8+EhxOB3dzntvjS8QgPfVzI4aimptmPQajLoB+hO1NUBLPUZLEKG+reypdpIR3PeCam2ONrZXbuPKMVceso9Ta6A+aiIh27+gaPpVvR47xhKDQWNgbclaZkR4SjwKRjayLLOrahdbKragUWmYEJFGsikEGssBGNXaQrQ5moKGztJRk0ImkVOT4zo2a80k6QNhzYuKPHPMdBrsGshfjWSrQY6agk/sJLT6wd/t2FveyIa8aupb2pkYbSUjyh+dRlm/iQow8PvJUXy4vtDV32rUkhzatxXdels7Wwtq2VZUR0yAgYkxAUQOZGjqINDY0k5ZfSsXTo3m7dWdq8tmvYaUMDNtdgfbCuvYnF+Dn0HH5DgrDS12NubVoNeqmBIbQPJQr4w31yjhNyXbIDBB2WHxOxAua4lQ6m9seA3Gng+rn1MUocZfArZaJdTspEeU5OrC9Z27MyVboWAtIEH0NAgf2+2lc+tyifOLQ6/Wu4pnAlyQcgFJ1gFStzpG2FVcz4a8amQZpsYHcO2cRP7vix2u97VqiUkx/izLqmBHUR3RAUYmxljRqGFzfi17K5pIDTMzIcafAN9uiqN6i9DRMOs20GiVOWUOB7UOLF1Ctg3+SthZXYEiIKHWgtYAcXNh11dQsgVMoRA5GaImDZipif6JTA6d7NptB4gyRRFtjubH3B/Jr88nPTCdjKAMLPq+5yNFmaNYELOAn/N/drWFGkNJ9Ev0iv0CAQhn5pDkVDQSZR3AcIrqfcqPqkpFor+KLeWOI3JmtlduJ8wYhq/W97D9auJnE7vyOUomXYJT2/uHrRkRM/gs+zPhzByFbK3YyhU/XuFaITNqjLx5zvOkrXoRmiqIq8rj0RkP8fn+b9hWuZ1pYVM5JfoEtuT+TIE1hVTfCC4Knkrc9s9g1bPKoHozprn3Iv14oLimJNF0zrtoMwZXSGJveSMXvrKGiobWDjN48/KpzElRErD1GjU3n5BEQpCJL7YUMTbKjz/MiCM28PDfo644nTIfri/gH991ltKaGhfAc5dMJNg8gA9KA8xnm4v465c7uWBKNFcdF8+qnCqSQ01cMTueUSFmfs0s509vrkeWQSXBA2eM5qGvd2F3Kqu7fgYtHy6aTupQJWI77LD+FVj6j862USfC2S+Bb6AyGSb+UXFaqvbBggeVlfHv7+gM+TGFKvkv/7sALvoAJBW8eZqyowNKZfXLv1Ukm7uQV5/HVT9dhVlr5tHjHuXLnC8pay7jlPhTOC6yF6FDgkOyrbCWC19eQ/OB3Ri9RsWH10zn8d+P463VuYSa9Vw/L5E1+6r4x3d7XOdNibOycHQYf/+283t69XEJ/GVhMnpN339ze4XOqNQkKut0tDj9Kc+cFt9gJWerY3c7cir4+MP3d3b2CUqGc16FiIGRTg4yBHHnlDv5Zt83rClZQ0ZQBmeNOosnNjzB6tLVrn63TryVP435EyqpbwE9Rq2RP0/+M2mBafyY+yMTgidwfur5hJvCvf1RBMcwg+3MjBj9v5yyRsIHUsmsMkdZrQES/NVsKLVz2eje14LpYE3JWpIDDh1i1kG7bxDNAfEE7fmB8oyzez3+jPAZ3LPiHurb6rHoholKjKDfOGUn7+95322rv9nezM9Fy0hT6xRlpzXPMXbHp6RfsZhGuQ3/tlZ4+TgyVGrOi56Grngz6uVvKZWtO2htQKrKVs5vKAVZxmfZ32mOnY7RMnjx0Rvzq12ODCjPqP/5KZOJsf6YfRSxjUirkWvmJHLZjFj0GnWf60kV1DTz+OJMt7Z1udVkltYTbB6ZqlWFNc386wflM324vgCrUcvEWCsXT4thbJQ/DbZ2/vVjpuuZf2p8AN/vKHU5MgB1tnaWZVcMnTNTvQ+W/cu9LWcxlO+G+NnKsTlUSfRvb1ZCgt46wz13obFMOW5tgNwVyk5PhyMDynnbPvRwZrZWbKWsuYwyyrjt19s4M/FMZkTM4PTE08X9s598vbXY5ciAEk723tp8/n3eOE4bG45akiiutXnk0azPrWF2kvv38bUV+zh3YuTAzdHS7e6ODCh5Wkkndu4Q2luVXcGuYbpT/qQIU3SlMksZa4CcGYC0wDTSAtOobanFpDOxsWyjmyMD8MLWF1gQs4BYv8MrpnVHlDmKRWMXcWnapfhofPrsEAkEPTHYM+rpQb7eEbOntH5g82WqssGiODNJVhWbj0AEoNXRyo7K7YfNl+lKdeIcwrZ8hOTofY6DSWdiTNAYvtv3XZ/tEwxfnLKTsuYyj/by9gblYTDrR+VBzlaNxtmKvykUWqqhtR6aqzBkfoe6dNuBwQ6aT7Za6CJGobZVIbe3MpjU2Tzjsaub2rrNAzHqNEdUGLfN7qSl3XO85m7i+EcKbXYnTW2d/541ze0s2V1OVaOSA9DmcFLV2PlvafbRUtvc5jFOR/8hwdHqLpXcgb3Zs01rVOZvczf5hHabEhpkq1Hm/cHUF3s0NbW55zt8ufdLXt3+Km32Ifx7HCWU1rd4tJXUtiDLMj5aNVqNijZH999Jx0H5T04ZWuwD+D1t72autdZ3qQcDOB1KKGNXNAZFNtxjPJtn2wDg7+OPRqXxKHwMyvNGm7N/89ioNQpHRjAgeKvOzNccvs7MGQf++6Y3rjcYZJU1cs7E/it5HJLKHIhQVvWizBKVNplqm5MAQ++/6NsqthNhisRX07twuBZrLHaDPwF7l1KVfGKvrzMrYhYfZ33MhakX9vocwfBGo9JwQcoFbCzb6Na+0C8VKt/sbDjxYSjbqSjsBCXTcOLDbAuJJ6+1ErPayOgWGwm1Bz3URYyHXZ+7Dm0Tr8I3cAC/S90wMcaKJLkvtl8+K45Ak/fCvyKtBk5KD+WnXZ1OoVmvYVToyK3FEulv4HdjI/hqa+e/qVGnJunAZwo06fnTrHge/V4J41mzt4o/zopjd0mD2zhzU4ZwZ8o/VqkNk9ulWLAxQHlQbChTdmUc7Uo+TUUmmIJh6tXw8wOd/SWVEgLU1gixswGncp50wOmVnRDprnRWUF+ASWfi2rHXolVr+TDzQ8qby7kk7ZIhUW1yyk4yqzPJrs3GoDaQFpg2omX2z54Qxddb3R/+L5kegyR1LkREWg2cmBbK4t3u38mOXLkOMiItxPUhpLTPBKcpCf1dd/PGXwqoYOfnym5gWAZMuxa+vL6zz56vIeP3sPX9zjaNHoJTPK9RX6rk1TRXKhLi4eOVnBsvEO8Xz12T78KoNdLQ3kCgTyBlTWVuqpUCwXDCW2Fm//HSOMMCWZbZO5A5M22NSk0C3xAAVJJEcoCKzeUO5sf23plZW7qW5D4mlFaNmkfEhneoGnWCUvOjF6QHpvPOrnfYVbWL9MD0Pl1PMHyZ6RPBQ+lX8UrBj2glDdcnnMlESxJETFaKsc27Dwo3KDUSAAKT+Gnh3Tyw8m7XGBNCJvBw2hXEWuNBo4OZtyKrdUhh45Qf2dTT0ccdRqZ5gMiI9OfNy6fwn5+yqG5q4/JZcZw5LsKr1zDqNNx7ahrRAUa+3lpMeoSFWxcoeTgjFb1WzZ9PSibMz4cvNheREmrmtpOSGRXSmdB/zoRIJAneWplLsFnPcaOCCLXoeem3fZj1Gm47MZkJMf2sAtwffCxw+pOw9kXY/RWEpCvhPe9fCPFz4MxnlXn9/oWKU6LSwO/fUmrO7PpScXzGXwx7f4OzX1QEBFrrlfFa6pRrGKxw6amuS+bV5XHdkutcYhlalZa7ptxFs72Z0xJOG4q/AhvLNrJo8SKX2mCsOZbnFzxPjCVmSOzpL1PjAnj2ogk8tSQLh0PmphNGMSvRvXaPUafhvtPSiA4w8M22Etd30kejZldxPetzazghJYSrj0vA39j3sO5eE5oOf/hSyduqzIZxF0H6mfDmqVBfpPTR+Ch5V6c9CaueBq0vjD5HmVt6izJ3/WMUsQpTmPv4TRXw1U2Q81Nn21kvek3uXifpWF2ymmVFnQsCf570Z3zUAxh6LxD0A0mWj1wSeKiYPHmyvGHDwNXpLKxp5sznVvLfiyb23PlIKN0G616GqYtcTZ9kthFsVHH3tN7dLFocrdz+621cnXE1Bk0fVmNkmZhVL1Ay4UKqk07o9Wlf7/0alaTigZkP9P5aRwe9jj8a6HnpVWRZ+THc/TV1qScj2duxZP0As/+sFLW0tyiF317tnCP7z3uFy3c+R3VLtdtQ/57xECfv+A4cDoibDT/cqSRcG6ywd4nitF/yKZhDBvtT0tjSTqvd6dUdmYNxOGVqmtrw1Wsw6AYoodiTPsXF9XVuOp0yNc1tGHWH/kxVja3otSpMeiUHqaapDY1Kwmw48gLAXqW2AFY+peTK5K3sbL9yCXx2FdTsV46TFyoPh37REDIGmsogOBVaapXimSc9DFV7YdUz7uPPvg0WPADA59mf89dVf3V7e2rYVJ6b/xw+msF/AGxub+a6n69zFbzt4O+z/86ZiWcO5KUHdF6CUl8GGfwO44x0951stTtosNnxM2rRqgcp1KmtCdqawTcI1r2iiEx0JeV0+P0bygKnpFbCzt45E6wJkHEu1BbC6mfhzOdh3AWd5+1dCu+c5T6WwQrXLO+sY9MPfsn/hVuW3uLWZtQYefPkN0kL7Httm2HCiMnZFvQdrwoASJKUBPwTSAdcd3BZlkdUlbCssgZiBlLJrDIbzO6rxMlWNT/m9j6XZVvFViJ8I/rmyABIEpVJ84lc/ybViXN6vTszO3I2f1v1N+6YckePymmCEYDTriSWttTit+WDzvbKLNCblFfpdrdTmnVGalpqPIZqtDfDto+U1cSQFCWEJ7NLjpWjXZEiZ/CdGZOPloHeJ1GrJIJGsHpZd6hUUo8O4MHvW30HcKX7SGhrUCqqH4zd1rk6DoqzXbINrPGw7X0lZ6wrdUVQV4gH5Z3iDxW2Co+3ixqLaLG3DIkz02JvoaixyKO9qrlq0G3xNn6GnudZd99JvUaN3jxoiw0KOl/lBVCX7/l+dY6S42U8UJy7eq8ijd9QCvmrOvu11rmf110Ol62m+1ydI6ChrcGjrdneTHN3eWcCwTDA22pmbwB/A54E5gF/YgR6w5mljQNbK6Jij7vePDDKquKpjQ7aHDI6dc9/sjUla0m2dhNH2wuag5Nx7F1KUNZiKlNP7tU5Vh8rqQGpfLvvW85POf+IrisYZFobFBWc+hJltS4oRXFQqnKUGgcn3A97f1HqG0iS0j/pZMhZolSntsYqP7LNyk5M9P6VzI6czfKi5a5LaCQN8foDP8St9RA4ytOOMecpD4r9oN7Wzu6SeioaW4nyN5IabsZHO/APJqV1Lewpqael3cGoUJNbuNWxgtMpk1nWwL6KRrRqFT5aFbIskRZuJsQyjMNO/KKVncLcFRCQoIT6gPJgeNaLyoNkXbESRhY6WiloaI2D5Y+7jxM1WfkuBCcr35G1LymLAV1WyicET/C4/HnJ5+Hv4z9wn+8wBBgCOC/5PJ7b8pxb+9jg7mvjjGQ25dWQXd6IQatidISFxOHyHW2qVO6/thrlvjhqoaJgZgxUwhtlB/jFKXlc+35TZJuDUiD1dCXErAOVGgIPEvkJTFLEKboKCozqopTWTxL8EvBR+9Di6Mz5GRs0lhjzyAxRFBz9eNuZMciyvESSJEmW5TzgAUmSlqM4OCOGXcV1RA6kklllNkS75xEYtRIRJhXbKxxMCjv8P4vN0cLuql0cH3WEdQskicqUk4lc/wZVo05A1vRuRfX4qOP5357/8fvk37slXQqGIe02Rfbz138qx+ZwOOkf8PnViooOwBn/hc1vKz+6ALNuVfp3rAj6BsO5r8PSf0LxBizlmdx40l/x0fiwtGAp0aZobpl4C+OqSpTK6WqdkoB61gtKrHhTJYy7ECZdDqojD+toarXz/K85vPhb54r5Y+dkcP6U6AGdhwXVTVz/3ma2Fymror46Ne9eNW1o80GGgFX7qvjTG+todyghydPiA4iyGnjxNxtPnD+e8IG8V/YHvRlOe0IJNQtOVRL85QOqVskLFUGApBPh2z93JmrPuVtJyt70tpJ7M+//YN1LioMPSg7D3LsVtb74412XygjO4NHjHuWJjU9Q31rPJWmXcHrC4NZWOpgzE8+kqb2JD/Z8gJ/ej79M/gtjgsYMqU3eZnl2BYve3oitXbmnpYdbeOL8cUMnC95BYwV89xfY9YVyrFLD79+Ggg1QciD0z8cPLngPXlugODyg1JQ5/Snl/7O+VxzyWbfAwXLIIWlw6afw3V1QlaXk48y9u3MXqJ9kBGfwxNwneGrTU+yr3ceMiBlcN+46go0jU3JecPTjbWemRZIkFZAtSdKNQBFDEVvST/aUNjA9IbDnjkdCS50SH+vrOX6yVcW6EnuPzsyW8s3EWGL6lYxnC4ijxRJB6PbPKZ1wQc8noAgBfLDnAzaVb2JS6MBVJBZ4gYos+O3RzuM5d8HPf+10ZIKSYP9vnY4MKIXeuoY2NFUozs2F7x5YUQwgXefLwwFJFDcWY9KalMJnMTKMmqfEfJsPJKrGzFTCeQJGKVWw+0F2eYObIwPwt693MjUhgPgBTLbfkFvjcmQAmtocPL0kmxcvnTQou0LDgdrmNh74aofLkQFYu7+aWaOS+XRTEduL6oavMwOKCtTce+HV+Z2ODCjS42e9BGtfcFec+u1RuOBdmHmTsmO56r+djgxAbT6otDD9OrfL+Gh8OC3hNKaFTcMu2wkxhgy5BG24KZxbJ97KJWmXoFVpCTQM0G/aEFHb1MZ/f8l2OTIAu0rq2ZRfM/TOTOn2TkcGlPvuD3dB4vxOZ8Yap4RB2rqE7lZmKcqRzVUw/QYlh+aHu+HMFyCoy+62JCnO9J++U54nTCGK6pkXOS7qOFICUqhrrSPcGI5JP3KFTQRHP952Zm4FjMDNwMPACcAfvXyNAaXd4SSvunnglMwqM5WQn25+6FICVKwudnCdZ8SCG6uL1xxxiJmbKSmnELP6BSrSTsbh49djf5WkYm70XN7d9a5wZoY7tmp3XWIff/e4f0tUZwI0KA9ubd3EQ1fsUUJquiSV+mp9SeqqoidJYDlIsjMgrl/md6WmybNmSEu7k3pb73PMjoTCGs9aC5mlDTS12o8ZZ6ax1c7+Ss950eZQHIPKLjVnhi3tNqUI5sGoNZ75MaAk+6f9TpHP7Soc0EH5rkNeaigkmA+HWqUmzDes544jkFpbO/u6mZuldZ71aAad7nKT6goVGfAO/KIU58WjX76S07Wyy9zrrg4SgNGqvAaIEGMIIcYRtx4tOAbx6tKRLMvrZVluBOqBm2VZPkeW5TXevMZAs6+iiRCz3kOX3muU7/F88DtAWqCajWUOt2raB9PY3kR2TRaj/LvJTegjbeYQGsIziNjwTq/PmRU5i7Ulaylu9CwYJxhG+McqCfkdFG92C4uheDPEzuo8drQrYTUHM/pcJdysLzRXQ94qyF4M1ft77t8NRTVN/LyrlK+2FOFn0OKjdf8+xgQYPEJBi2ttLMuqYPXeSiobPB+ya5taWZlTwWebClmfW01r2+GdoXHR/h5tZ02IJGC4JboPIMFmPaeO8XwYNhxw5gJNeopqmsgqbeDrrcX8uLOU/Komj/5DiiVcyZ3piqRS8l9GLfDsH3wgP0Gj68yz6Ur88UqND8GQEuWv1Hk6mJQwM7mV7nOwqrGVZVkVfLKhgNU5lTS2DHAR08DEzppEHSTOg6LNnceF65X8mIOJmKTsAHYgSd3nIrY2KBLjmT8oi04jUJlWIPAWXn1ilyRpsiRJ24FtwHZJkrZKkjSilvD3lNYTEzCASmblu8Gv+yQ6i14iyCCxo9KzgnEHG8s2EO8Xj17tnQeqyuQTCcr6GX2dp/JNdxg0BmZFzuKdXb13gARDQGACXPRBZ+J99hKYe58S/gXKqnTMTCU/QKVRQhT0fkq8to+f8gOadgbMvFHZtekt9SWK5PMbp8B758Er86BoU8/ndSGnrIG7Pt3BVW9v5OYPtnDHx1t49sIJRB0Q5UgPt/DcxRPd1Ir2lNRz3our+MPr67jolbVc8+4GCqo7V21rm1p5dcV+Lnl1Hbd/tJWLXl7DN9tLPK7dlQnR/jxwRjq+OjUqCc6eEMFFA5ynM9zQa9T8cWYcMw7U8/A3arn9xGR+zSzj5vmjeOHXvdz3+U4+WJ/PTe9v5pp3NnLzB5vZXVzXw8iDiN4Mp/77QPFLlJCc+X+DTe/AhEsh+YAIio8fnPwoRHXJZ0w9FaZ2fEd8YMpVkP2TIotbmTPoH0XQiUaj4tyJUZyUHookgUmv4c6FKTS22PndsyvYmKeEb9U2tfK/tfn88Y11/OWTbVz6+jq+2FKCw+Ho4Qr9IHQMnPemIskMSn2jBQ9DwlzQGpUcmuRTIP0smHSFcqw1KFLf0dM779PGQPjdsxA11X18Wz389pgSPvn+BfDS8YqYi0BwjOLtMLPXgetlWV4OIEnSbBSFsxEjobKruN710OR1ZEdnst4hSA9Us7qonfEh3YexrC5e7dXClQ69meqE44la/TJ7T36wV+csiFnAg2se5Npx1+Kn7zk8TTBExM2CKxcfKNAapPwwnv821OYpuzbByTBqvlLvSFIpuzkqlbJabW9RQtF0ffwuFG2EPd90Httq4Je/wwXv9Do5dUtBLStyOsMq9lY289HGAj64ehq2difBZr1bwTunU+a9tXkU13aGl2zMq2VlTiUXTlUWDnaWNPDfpXtd79udMg9+s4v0cAtpEd3PYbNBy+Uz41mQFkqb3Umk1YBec2yEl3VQZ2vjwa924u+r46YTRhEXaMThlBkbZeWDdQWUH9gBmxBrRSWBU4YtBXWs3ld9yL/rkBCSDhd/APXFilPibFcqrftFQuRkRRJXY4DQg2poWCJh4d8hdiaUbFbmdmW28t6er5VaM4IhoaXdwfO/5hDuZ+CZCydgdzp5c2UuJ6SG0NRm5+/f7OLtK6ays6SeJ3/Ocm1cOJwyj3y3m/RwCxNjByhES6OD0WdB9FQlp8UcrjjVYWMg/QylJpd/tNLvlMdg5g0gaRTVPEmC89+CmlzQmRW5+4Mp3wGrnu08trcqi0hX/9KZtygQHEN425lp6HBkAGRZXiFJkqdg+TBmZ3E90xICBmbwmlxl9Vt36J2f9CAVywq7z5upba0lvyGf0xN+512z4mcT/+u/8S3bRVNoz45SgCGAccHjeH/P+1w77lqv2iLwMqZg9zjtg4/VWiUkoiv9KbrWNTyig+JNSkhEL52ZghrPOPhNebW0O2SSQj1lV23tDtbt96x/s72ojgsP/H95vWccfb3NTlVTz+EmA5Y/NwJoaLGzs6QepwzLsyu5aGo0P+0s8/i71Ta3YdCqaWpTVrv3lHZTB2Oo0ZsVQYCDMfhB5GEKJKu1sP4VyF3u3p67SjgzQ0hDSztbC+r4eXc576zJc7VPiLHiq9Owo7iO+pZ2yhtaOThyu7nNQdVg5HtZ3OvJIUlK4n9XNDrPMDLfoM5dne7oLgesvghstcKZERyTeNuZWSdJ0kvA+4AMXAD8KknSRABZlvsWbzIEZJY2cP7k/lfQ7ZayXcrKy2FID1Tz/OY2WuwyPhr3cJa1JetI8k9G08tCl71F1uioSl5A9OqX2XPmk56xvt1wStwp/HvDv7ks/TJRRFPQSXCqZ1vyKdAHJaXuHJbjkoMI8+9evc9Xr+G0jDDGRvkR4W9AJSmOzMzEzmvGBBjRqCS3fLRwP5+BlWA/Cgj01TM3OZhfMpWikFsL6pg1KhCLj5YAkw61SsWafVUE+updjgzA5LgBWhAaKtLP9HRm0k4bGlsEAPgbdZw8JgxZlpW5KEms2V9NkElPQ6udk9JDCfDVE201oteoaLV3hm8HmXREDGQtuYHGP86zLSwDTJ45RALBsYC3s9zHA8kodWUeANKAmcDjwH+8fC2vU93URnO7nSDTACX4lmxTQnkOg1ErEWtRsaHUM553dclqUgP6r2LWHXVRk9E2VWIp3NCr/uGmcFICUvjf7v8NiD2CEUrkRKUYZ0eeTdRUZfW6D/LMk2KsXDsnAe2B4rETov3508x4DNpDr73MTQ1hW2EtTy/J5smfs7E7ZFK6OEUZUf48dm4GFoMyRrifD4+dO5b4YCE3ejgMOjV3nZJK2gGp270VjZw/OZpfsyp4ZkkOTy7OItSsJ9BX+fdVqyQunhrN1LijrBZP8skw9oCEvSTBuIu7Fw8QDBpatYqzJ0R2zsWfswk26XA6nYyJsPCXk1Iw6NSMjfDjsXPH4m9U5miIWc+j52QwejiFQfaVkHSlnpfuwP0rIAHOeHZAlc0EguGMV3dmZFme583xBptdxfUkBPkOUIKvDOU7lTyGHhgTpOK3gnZmR3X+85Q2l1FlqyLWcnhn6IhRqalKPpGota+zK2pyr3Znzkg4g3+t/xcXpF6ARTfEuv6C4YHBXym+mXaGUmfGP04J4+kD4f4GblmQxMLRYbS0O0gI8iXU79CrqLIs8/XWYjLLGl1tv2ZVcMb4CEYdcGh0GhXnToomLdxCdVMbkf4G4cj0kpQwC/+7ehpF1TZMejX/WZzlJlv9xZZiTh4TxgeLpqNVS6SFWTDqvb3pP8T4R8PpTysFDEF5eNSO4JX9o4BWu4M3V+e6zcWvtpbw7EUTePeqOFdenU6n5qwJkSQE+1LV2EqYnw9p4SPYkQHQ6hWlvejpSu06vyj38GGB4BjD22pmoZIkvSZJ0vcHjtMlSbrSm9cYSHaX1A9cfHxtgaKIY+w5/GJsiJpfC9x3ZtYUryE1IHVAC7E1hGegbmvCL39dr/qHm8IZFzyO17a/NmA2CUYgao0iLhA+rs+OTAcGrYYJMVZmJAYd1pEBJf79t6wKj/YONaOupEf4MTspWDgyfcRq1DEmyg+jXsOqvZ41NPKqmpmeEMik2ICjz5HpQGeA0NHKSzgyQ06drZ1VOZ71VwprbG4CIR2MjfJnXmroyHdkOpAkRbUycoJwZATHPN5+Mn4T+BHoyHrLQimkOSLYXlQ3cLLMJVuV1bxekOivoqzJSWmTEuMrI7OqeBVpAWk9nNlPJBVVo+YRsfGdXmvWnzHqDD7O+piSxsPL3ApGMDW5Sj2DrkU3B5h2u5Pssga2F9ZS16wkm+dXNbElv4aSOvdilkadmnkpnoXdJh+BUlFDSzs7iurILK2n1T6A0q0jFLUKZiR45j8lhoxA57CpSpENr8gCx8AWYBV4B1ubg90ldewqrsNHo2b2KM8k+aSROBd7Q22Bch+uyeu5r0BwjOHtJbQgWZY/kiTpHgBZlu2SJI2YJ4KdxXVM7+aH2isUbYSAxJ77ASpJYmywml/z7VyYpmN/3X6cspNwU/jA2NaFhohxBGUtxlS6g8bwjB77B/gEcEL0Cfx7w795Yu4TA26fYBBxOiHre/jiOiWUwTcYzn0dEo7v+dx+UNvcxusr9vP8r3uxO2XGR/vxl4UpXPfOJhpa7QSb9fz3oglMO/BdlSSJ8ydHs2ZfFVsLlfomp48N7/N3Obeyifu/2MHynEpUElw2PZYbTxhFsLl74YFjjayyBm77cAu3zE9iZ3EduVWK6tx5k6KICxxhim9lO+GTq6BiF6h1Sp7XpMu7LxwrGBYU19r4z0+ZfLZJqYl26pgw/jQrni0Fta65eO7ESOKCRthc7A17l8KnV0JzFRiscNaLkLywV+HgAsGxgLd3ZpokSQpEUTJDkqTpwDCqnnZoWtodFNTYBqbGjKMdynZAUDdVfA/B2GA1P+cpq4Uri5RdmUG5bUkqauJnE775/V6fcnL8yWyt2Mqq4lUDaJhg0KnKhk/+pDgyAE0V8MnlygrhALKloJZnfslxKY9tKajj3TX5xB54SKloaOXG9zdT2mWHJjHExBt/msKn183gqxtn8eg5GYT3QalMlmU+2VjI8gNhK04Z3lqd163k87FIa7uDp37OAuDLrcVMTwjk5vmjuHVBEvnVzewuGYZSzIeirRl+fkBxZAAcbbD4fkWgRTBsWZ5d4XJkAL7bUcry7HLmpYS45mJBjW1kzcXeUJMHH1+uODKg1O765HKo2nu4swSCYwpv78zcDnwFJEqStBIIBs7z8jUGhMzSBiL9DWjVA5CTUr4TfEN6XWcDlLyZt3e20WxvZ13pOi5Ou9j7dh2CuugpBGUtRl9bSKt/VI/99Wo9F6VexEOrH+LzMz/HoBHx5EcFdYVKMbauNFdBQ0n/atH0QFaZZ2mq9furOWl0KDuKlAeVioZWSutbCOuSTxPgqyfAV39E12xstfPDzlLP6+ZWcdrYgd8RHe5UN7Xxa2YFZ46P6LbOzPT4ESTF3FwFe5d4ttfuB2YPujmC3rFkd7lH26q91WjUEmv2VbvapsYF8Ltxg2nZAFNfBC217m3tNqgv7NMCqUBwNONtZyYROAWIBs4Fpg3ANQaEncX1xA5UqETBWiUhug/46SUiTCo+zdyP1ccfq95/YGzrBlmtpTZmGqE7viB/9o29Omdc8DjWl67nyY1Pcu+0ewfYQoHXsLdBbR5IKkU2XN3l62oKVdrlzvoM6Exg9H4oZqvdQVGNDZUkERvoS5TVwGkZ4eg0Kjbl1yAhsb+yydXf4qMhwKj3GKOw2oZaLRFtNYLsZEdxPa12mcRgI4GmQ4eLGXUapsUHkFPe6NY+ouVbvYjFoGVctB/7K5tIDTcjyzAp1kqQSUdzm4PUMAt5lY2ARHSAEYdTpqCmGUmSiLJ6eZGooVRZnTaF9kpQxQMfPwifAEUHydCbhdM6nJkaH8BPu9yLRWZE+mExqLlkWgwOJ7y7Jpe4QCOltTaKam34GbWMClEUDfdXNFLV1EaYn54oq7KwWFjTjK3NQYSfAV+fQXhUcTqVHESnXak5p+nF4otvsCI40d4lV1ClURZIBQIB4H1H435Zlj+WJMkKLECpL/MCilMzrNleVDtAyf8y5K+BsRf23PUgxgar+SKnmvNS0gfArsNTGzONuOVPUTjtSpy9VO65MOVCHlz9IHOj5jIzcuYAWyjoN3VFsPwJ2PQGSGqYeTNMuwZMB34kg5LhlH/B93cqDo1Ko9Qy6KWQRW8pqrHx7C/ZfLShAK1axbMXTeC8SVG8vGwfzW0O5iQFsWhOIpe+thYArVriwTNGE9Nl8aGoppmnl2TzycZCtGoVT54/jr0VTbzw216a2xyckBrCTSeMYkJM96IAapXEH2bE8ltWhUvqdUZiIDMSByiHboThq9dw8wlJXPfeJv597ljeXZtPq93JsuxKftlTjo9GzcXTYsitbOSMcRFsLqjj3TV5SBJcMSueK4+LJ6S/uUdOJ+z7Bb68UdkdDBkNZz6nqDn1BR8LnPwovHde54r3hD9A+Pj+2ScYUBakhfLllmK2Fylhr0khJk4bG85zS3N4eslejDo1181JJDnUlyve2sCuknqCTXoePTcDh1Pmga92UlzXQkKQLw+fNYaKhlb++tUO6m12Zo0K5MEzxjBqIMUDmqth4xvw27+U0MaxF8Lce8Aac/jzAhIVWfAvrwOnQ1lgOvVxCEoaOFsFghGGt52ZjmT/04AXZVn+UpKkB7x8jQFhR1E9Z0+I9P7A1XuVB0FzWJ9PTQ+y8/3+IFIDjix0pj/YjVaaAxMIyP6FyvTeVbo26UxcMeYK7llxDx+d/hGhvqIa8bBmzzew4dUDBw5Y/h+lGFvGuUqTRqc85EVPhYYy8I+CwGSvJ51+t6OYD9YreTitdifZ5Y089XO26/3fsisJNut58IzRlDe0opYk3l2bx4QYf+KClIePr7aW8NGGQtcYtnYHjy/Oco3xy55yQi16RodZ0OnU3dqREmbho2tmsK+iEa1axagQE4Gmwf/uDUdsrXY+21jIX09PY2lmOfsqGwnz83GF/tjaHby2Yj93LkxhT2kjb67KdZ370rJ9pISZOWdizyGrh6UyCz64uDP0sXynktN15U+dDnhviZ4Ci5ZC1T7FuQlOFcn/w5y4IF9ev3wKOeWNOGWZpGBfnvg5m6WZiix7c5vynY8KGMeuA3kzFY2tNLc5uOvTbTS3KY8n+yqbuP2jLZyUHka97UBeak4V//kpk6cuGIfPYYrz9ov8NbDkoc7jrf9TFobm3HH481QqGHMOhI2BumKwhEFQSmdhYoFA4HUBgCJJkl4Czge+kyRJPwDX8Dp2h5Ps8oaBCTPbtwxCxxzRA2CrIxu700JD29BITdbFTCNk51d9OictMI25UXO5demttDpaez5BMDQ42mH7R57tWd+5H2v1Sr2Y5JMUR0ft3R96W7uDLzYXu46NOjXVB+VjgFIEc3dJPf/9JYenl2SzMa+W/GplB6Wp1c6XWzoTgyP9fTzCxUCJuc+raT6sPRH+BmYnBTMtIVA4Ml0orLXx3Y5S/Aw6ftpVxqSYAFZ2U+OjtL6FvRWef/vvtntBur0m1zOHq2a/klNwJAQkQNICxVkXjsyIINisZ0ZiILNGBVFrs7Nkj2ceTXZZI6GWzu9uQ0u7y5HpoKy+FT+juzPw085SKho87z1eI3eFZ9v2j6ClF4IFaq1S3yj5RAjLUBaaBAKBC287Guej1Jk5WZblWiAA6GHZYejZV9lEgK8Oo87LKzKyE/b9BmFjj+j0HZXbifdrZkPp0DxUNQUno7XVYKzM7rlzF05NOBWD1sD9K+5H7mW9GkEvsLcqyjaNngUiD4mtTjmn5aCkerUWIid79g/zTuZsRUMLhTXNtDuc3b7f2u6goLqZ5lY7k2KtxAUaWXR8AhdMiSbM4jnf08LMTIkL4LmLJ3LdnAR89WqsRi0F1c202Z2MjerMbalobCPUzzOkKTHYF6tRrGb2hVa78u/ko1Hxl4UpGDQqbpmfRFKIL6MjPB2AAF9dt07guCj//hvj61lTBJ0JfA6M3dqgODy2A+p7bU3K3G8WinRHI/5GLQlBvqSGmbluTiKXTo/F36glzM+H5BATN8wbxVnjIzH7aD3WEvUalUcptYRgX8w+GkrrWiiqteF0euG3qyZPkQFvbeg+bzZ8AmiPQilpgWCQ8aozI8tysyzLn8mynH3guESW5Z96c64kSbmSJG2XJGmLJEkbej7De+woqiMhqPdKY72mdBtofcDS98TSutZaqloqyQjWsK5kiFaIJRV1UZMJ2v19n05TSSquHHMlObU5/GfDf4RD4w2q9iq5As+Mh1cXQNaPPRf6K9wA75wFT4+F9y/0lJ6deJl7eI41AVJO7peZLe0OvtlWzGnPrGDef37loa93UlDtvhuyt6KR2z7awpx/L+XcF1exMD2UOcnBvLM6j882FeFwwh9mdMaRp4SauGJ2PC8v28cN/9vEpvxaXrlsMp9sKOT4fy/l3BdWcua4CJej0mZ3YjVqyYjsfNj21am5bu4ogkTNmF6zv7KROz7exofrC3jk+z2U1rXw/voCHvx6F++syWdBWiiTYjqdyDERFkaFmEgJNbk5pFFWA6dk9D3M1oPgFJh1a+exJMFpj0NAvFKU+H8XwNPj4N1zYP8K+OwaeGYcvHka5AnZ+KONEIsPt52YRHq4hddW7OfHHaVcNyeRjEg/ZCSe/zWH7UW1GHUqrp/rXuPtnlNSqW/u3IXRqVX885yxfLW1mIVPLWPB47/xzC/ZlNe3HJlx9jbY+QW8fQa8OBs+v1bZ2Q4d09nHYIUZ13t9t1sgOBaRhsuDpiRJucBkWZY9YxcOYvLkyfKGDd7zdx74aiet7Q7OGO/lnJlf/6ncsGL7ngy/omglFbYKkv0n8cQGKx+fUcpAqEb3hKa5mrgVz7LlDx8iq/u2td3Y1si/N/yb0+JP44YJNwyQhQNOr+MDvT0vXbS3KIUrd37WxSoVXP0LRBwi+bkmD16ZqySdduAfp+QXmLvkMlXnQsVuZbzQ0eDXv7yGdfurOf+l1W5t1xyfwF0np6JSSTS32bnxvU38ciDO3WLQcPHUGF78bZ/bOQ+fOZqa5nbsTieTYwO4/r1NNLZ2Om+Jwb5cNj2WB75WaoVYfDS8feVUKupb0WpUpISaqbO1k1nagK3dwagQE5PjRpB8cM/0KW61r3Ozpd3O7R9tpbDGRqS/gb0VjYyO8OPzze4hXU9dMI59lU2oVSrK6lqYNSqISbH+tDtkssoakCRICbUQ6a36XS31Sq5MQxlY45QHxOYqeG2BIiXegW8QjL0AVj+nHOt8YdFvIml64BnQedkVu93OP7/P5LWVuW7tD54xmr99tdN1rNeoePDM0VQ0tNLS7sSgVbMxv5oHfzeawhobdS3tJASZyK9u4uq3N7qN9Y+zx3DJtNi+G5e7QnFknF3C25IWwimPKQtTjlYlTyuwd4W0BV5BVBg9ihFLAsD2ojpOSvdysrqtGoo3wey/9PlUGZntFduZETEds07GqneSVaMlLbDduzb2ArsxgBZLBP65q6lJnNOnc006E7dPup3HNzyOU3Zy44QbkUTF4r7TUAq7Pndvk51QmX0YZ2a/uyMDUJuryDB3dWYC4pSXl9jVTcG6jzcWutSsSutaXI4MwMQYKyu6yb1Yt7+aHcX17K9s4pGzx7g5MgB7K5qwGDpDxupb7BTX2jg1I8LVFu5vIDVc5EIcCWX1rXy/o5Rrj0/kleX7uHR6LJ9uLPTol1XWyIu/7aUjIseoU7vq8kQPhDqkjwViZri31ea5OzIATZXu4TttTVC9TzgzRxE5lc18vc0zFyuvqgmTXuO6Z7TanQcUE3Pc+t18QhszR3WGLr6+0n1BBeDD9QWcNzEKvbZ70ZBDUpHl7sgA5PwELfcpeVoCgcCrDKfkfBn4SZKkjZIkLTr4TUmSFkmStEGSpA0VFX3IGegBp1Nmd0k98d4OM9vznZIro+v7imRhfSFqlYoAH2UlOdG/nc1lQ5eMXB85gaA9fQs168BP78dfJv+FH/N+5J/r/olT7j6HYqQyUPPSDZ0BTN2E6fgcpgaKvpuHeJVGyTFoKIPWziTtmpYaag8uynaEBPp67t5FBxiQnTJZpfVoVRIBXfpUNLQS4ef5HQk266k5EAZi7EZ9TK9RoVa5O8YWH5EP05X+zE2DTk2wSU9FYyvh/j5UNCj/PRi9Vk3X1IKQbvKdBhy9+f/ZO+8wuaryj3/u9F62916STe+Q0HsvgjQRVCyIIhZEkZ8FEAWpYqFaEEQEFFBAeg2QQHpv23vfnZ2dPnN/f9zN7E5mk2xvOZ/nmSeZc9s7s2fOve857/t9lZXFA1EdMFc3Bkn+Xb4uuvxdoz7Pkcxox8z6Ti91nb3Y9BoyHfFjh9WoxReMdSQ0B4Q1aNUSFn1s/8hPihfaKU6xjKxG0mB9bZiFs8eSsRzjBYKpyFRyZlbJsrwYpejmtyRJOm7gRlmWH5Vleaksy0uTk5PH7KKV7b3YDBqsY/kgFPLB7lfiZxCHyJa2LeTZ8qLvCxwB1k+iM9OTPg9r0w40I0yktelt/HDpD9nYspGb3r+JQHgcFWMmmPHqlzFYUuGse2IV8fKOg/RDCEsklcDRB4T2HX8T7H0LHl4FT11EV/06nt/zHJe9fBlfePULvFrxKr3B3sHPN0TmZ9kpTbNG36da9dx0+ixufH4Llz22ljtf2839ly5gvx+yvcHFqWWpmAc4LKlWPRkOI10eZSVyZ6OL8xdmxFznWycW8ty62uj7U2anMFuswsQwmr6ZYjVw6/lz+N+2Rr54VB5v72rm0mXZaAY4kGXpNlze/t9ydoKRJbmD1/EZVxKK4LgDVsCXfQ3K3+5/v/ALkDzyel0uv4sX973I5a9czuWvXM5/yv+DOxCv2iY4PCPtl60uH39fU80Vj6/hskfX8vr2Zq4/qQjdAGejIMnMnHQroQEe9pnz0nAaY+/vPzitlLwDJjBPmpUS44xb9BquOjoPlWoE0QTpCyFnQHi5JMEpv4CkouGfaxR0+bt4bsAY/7/K/416jBcIpiJTJmdmIH21adyyLN8z2PaxzE14cWM9z66r5fqTxjD8YMdLUPOxcgMdJoFwgD9u+iNn5Z+FQaPMhPpDEnescfLs+U3oh7naPVakbXoWV9YSmhdcNOJzBMIBHt/6OJIk8eCJD2LRTY7k9DCZ/JwZUBJKm7dB224wOBW55MMJS3g6oWkzuBrAnq3UOXj3l8o2rZFXT/8/frT9kZhD/njyHzk269gRm7mhppP/bmrAYdYRjkQ4piiJ6/6+gTZ3/0NvWYaNOy6YQ0WrhwSzjrkZNjq9QXY1utCoVZSl2/AHw2xrcOEJhClJtZDhMLC1vpsWV4DsBCNzM200dPmoaO0lwaJjboadZOsRJaU87rkJgVCYHQ0uGrp8GHVqOnr92I1aGrt9dHiCePwhzHoNoUiEnAQzJSkW5mc7hnWNMcHdAm/8THlQDHlB01ctPf84RbbZkqY4/oOpoQ2RN6vf5PvvfT+m7cETH+TEnBNHa/1MY9z65Uub6rnhmU0xbb+9ZAEJVj0Vrb3otSrSbAZ+++ZuTpmTjk6tojjVwtwMO2q1xPb6bhpdPnKcJuZk2LEY4qPsq9p72dHgIhSOMCvdRkmqNW6fIdG8XRGd0OgVJTNrOnTVwVHfUNomiFcqXuHHH/44pu2hkx/imKxjJsyGKYSIcZ/BTImcGUmSzIBKluWevv+fBtx2mMPGhM11XeSMZWx3OABbnxuRIwOwq2MXKaaUqCMDoNfIZFjC7GjTsSh1clY1XJkLSdrz+qicGZ1ax7ULruXvO//Ol177Eo+c+giJRlFhfUhodJC5WHkNFZMTCk5Q/t9RCe//OroplLWMZ1vWxh3yRtUbo3JmttV385cBBRPzEs0xjgzAjgYXXZ4QFy3pFxtIthniHhxKD1hpyU6InUlNtRlZlDMJKwFHCDqNmoU5ThbmQLPLy2n3b+Lez8/n9+/uo9kVW+/le6cUc/GS0YlHjJjOStjyj/j2whNh4RVjcol/7f1XXNtL5S8JZ2YCeXWQ/Jhn1tVRlGLGadbx4Nv9OTEb61wYtWre/sHxJPVNchxTfPhVoLxEM3mJYxAK1roLXj1gtVClhrJzlPpGE0AoHOLZ3fG1xN6ofuNIdWYEM5ipEmaWCqyWJGkz8CnwiizLr03EhTfVdlGYPIYrBLtfBVsG2EemjLapdRP59vy49nx7kM0tkzfz7EkqQuvpwNBRParzqCQVV86+khJnCVe/djUtnviiZ4JxQK2LybFR+bpJ0znidks1j04Iw6rXoFLB1Ufl8v1Ti7Hq4+dL1Cpp0DyYA3H7g3T0isKrUwG9Rk2iRUcoEuHMuWksy3PGRD3ajPFhut5gGN8BxQrHBa1p8KLE2jFSUAMyzBlDahOMH4PlY6XY9ATDERZnO/jSylxW5Ds5fU4qpakWzl+YgU49SZPx2kEcIoMd1BN3D1epVKSZ43MtU01jLHYkEEwBpoQzI8tyhSzLC/pec2RZvmMirhsKR9jV2DN2yf9Br7IqU3jyiA5v9bbi8rsGvUkWOIJsmkRnBkmlCAHsGVLZoEOfSpK4sPhClqUuEw7NRGHPhNP6f1aqxs1cnroSnao/Gd+itXByzsj67n4W5zn44xWLqWhz879tTdR2evn+qbHF4q46Opey9IOHb4RCEd7Z1cK1T67nC4+v5fEPK6hpF3Hek4nDpOPOC+dR0ephTUUHBq2an55dRopVT5rNQJbDyFs7mvEHQvT6Q7y+vYkrHlvDlX9ay9s7m/EGDlMTaTQkFsGKb8a2Lfqikjc2Rnyu+HMYNf3OkVFj5OyCs8fs/ILDc9a89JjcOoNWxUWLMylItnLX67vZ2+zmy6vyOa44iRNKU1hf3cmdr+1me0P3xBubNk/JmxnIaXeMeJJzJKgkFVfMuiJujD8p96QJs0EgmCimRJjZZLGv1U2CWYd5kNnjEbH9RXDmj6hIJsCmZmVVZjD54lxbkCe7rfhCEgbN5OQ5uTIXkfnZE9StuGZw9aBhclbBWcjIXPP6NTx11lPY9YdQ5xKMnrLzwZ6j5NFY05ifuZynMhaytW0rGpWGeUnzKHaOLnesrsPH9f/YSDCs9NHbXt7BD04r4b5L5lPZ5iEnwYQvEEI+RPjy2qoOvv63ddEk3l++shN/KMK3TpzY5FlBLKv3tfFgn7ztrqYePq3s4LeXLSIQCvPdf27GGwzxly8tJxSJ8I0n++t1XPPEOv72leUcVzJOAhlaIxz7AyWsrHW34txkLlFUzsaIuUlzefLMJ9nSugVJkpiXNI/ShNIxO7/g8KhVEvd8fgHV7b3IQEGyhfpOL796dWd0n4gsk2jW8fLWJgD2trh5Z1cLL1y3ktyxCB8bKvZMuPRJpXBxTyOkLYDMg8jojyPzk+fz1FlPjekYLxBMRY5oZ2ZLbTeFyWM0wPm6lVogB84QDpFgOMiOjh2clnfaoNt1asi0hNjZrp20vBm/LYOw1oi1YQs9mQvH5JxnF5yNJ+jhureu40+n/ykmV0gwxujMkH+M8kLJhpwNzE6cPWaX2FbfHXVk9vPkJ9WcPDuF17c109Ent7wwx8m8LMeg59hc2xWjRgTw9zXVnL8gg6zxqF0iOCyVrW6eWlsT0+YPRdje0M0f3t0XlWdeV91BZVv8Ktrz62vHz5kBJbm/+DTlNU6UJpQKB2YS+centbywsR6TToWEih+eXsLjqytj9lmal8Dv342tJ9PRG2Bvi3tinRkAR47ymkQkSWJ24uwxHeMFgqnIlAgzmyzW13SOXYjZ5n8oClPmkSW07+rYSZIxCbPm4Pbk2UOTmjcD0JO5iKTdr4/pOS8quQij1sj/rf4/pqK6nmDo6DXxQ4pZr8ETCEcdGUnikLUb9Nr4bSa9JkYWWDCxaNWqQfOc1Copps6MUaeOq98BSpiaQDAa7H3lEzyBCL2BEL5gGOMBxSzDERmtKn780I2kVoxAIJg2HNG/8I01nRSljEHyv7sJyt/pV44aNjLrm9dT6Dh0GE2+Pcjm1sl1ZrozF+Go+ghV0Dtm51RJKr4858vs7drLn7f9eczOK5h4FmQ7YopiAlx5VA5v7miOvr98eQ67m1xc9ugn/PSlbayv6ojZf1G2E6cpNqH8uuMLSRukQJ5g/Gnv9bO9oZtrjy+MaU+y6GJW0Kx6DcvzErh4SVaM46lTq7hg4cTlCghmJucvyohxSh5fXcF1B4SeflzexlePjRXQmZNui6l9JRAIZh5HbJhZrz9ETYdnbJaeNzypFMgcYYx2vbsBb8hH+iDKIwPJtQd5codtUvNmwgYbXmcezsqPaC85ZczOq1PruG7Bddyx9g7mJ89nWdqyMTu3YOJYlOPksauWsHpvG61uP8cVJ1OcasFh1LG1vouluQl0egLc8M/NAKyp6OC1rU389SvLmJOh5EwtznXy2FVL+WhfG21uP8eVJLM8X0gwTxb/Wl/Pr17dyaVLs7n/koV8WtVOut3Awmwne5p7+PzSLCx6DckWPQaNitkZdp679mje292KWiVxfEky87NEPpxgdCzMdvD8tUfz3p5WQpEIp8xKpaLNzY/PnEV5ixurQUOiRc+cDBvFqRY213ZTmmZlZWEiqTYRviwQzGSOWGdmc10XeYnmQ4a7DInOKqjfAMd8b8Sn+LTpM4qcxUiHqemk78ub2dWhZWHK5OTNALiyFpO089UxdWYAEowJfHnul7npg5v413n/IsGQMKbnF0wMS3ITWJIb+7fLT7Jw0ZIsdtR3c8EfN8dsa3X72dXYE3VmQIl9X5on/v6TTWOXl9+9vReAf66r5Z/ralmUbef8hZn84j/b2dXUQ5rNgC8UpssTRKOWmJvlYFGOU9QAEowpkiQxP9sRLcza0OXhO8/spardQ7rdgCcQptsb5OYzZ/GN4wu5cNEk1T0SCAQTzhEbZra+eoxCzDY8AfnHgnZkMz/d/m5quqspsA+tkFbeJNebAXCnzsXUXoHOFV/EbLTMTZrL8rTl3LL6FpE/MwORJSVnRqOSKEw2YzMesfMp0wJJkmKEC1UqsBi0qFX9pV2aXD66PMG+/SfBSMERy37lT71GJfJiBIIjmCP2SeLTyg6W5o5y5rd1N7TthVnnjNyOxrUUOArQqob2pyiwB/mo3sjVc3tGfM3RIqs1uLIWkbzrf9Qv/8qYn/+Cogv49ae/5rk9z3FJ6SVjfn7BxFLb4eHDva1squ3ilFkp/N85s+nsDbKrycUJ9hQSzFpmp9tijtnR0M3bO1todvk4bU4aS3KdMRLqHb1+1lZ08N7uFkrTbJxQmkzBWBa/PQJpc/tZU9HOB3taKcuwc3xJEvlJFr57cgm3vbyDLx6Vw4JsBx/ta+fdXa3ceFop3356I96gUhhTr1FxVMHIBFAEguGS4TBx46kl1HZ62dHowmbUkuU0sjTHyStbGvhgTyuz020cX5JMvhgbBIIZzRHpzIQjMptqu/jCitzRnWjDE0rSvzq++vVQ6A32sr19B2fmnznkY/LsQZ7aYcUbkjBOUt4MQFf2crI+/TP1S68G1eGruQ8HjUrDNXOv4e7P7ubo9KPJtmWP6fkFE0e7288Pnt3Mp31J/msrOzh3fkaMfGpOgpHzBySI727q4bLH1uDyKoUWn1pbwx+uWMTZ85VispGIzFNrarjvzT3RY55cY+apry4n0yGkm0dCMBzhT6sreOi9ir6WOmalWXjiyyv43OJM8pOMVHd4ufG5LdFjnCYtf/jCIv6+toZMh5HPLc5iXqZjUuwXHJl4Q2HufG1X9L3NoOH3ly/iW09vjLaVplp44ivLSbMLARGBYKZyRK7L7mx04TBpsRtH5oQA0LQVuuuV4mwjZG3jWnLteTGVpQ+HTg3Z1hDb2yZX6jRgSydoSsBR/cm4nD/DksGZ+Wfy49U/JhwJj8s1BOPPvhZ31JEBOHNuGo+vrojZp6bDy66m/pXGjbWdUUdmP/e9tYfuPmnn2k4PfziglkRlWy+7myZvtXK6U9vh4fEPY2t27Gpys7u5B4dJR1GKlUffj/27dXqCVLd7aHH5WJ6XwMK+XAaBYCKo7egd4HwruHwhtje6sBr652l3N7vZ3eSeaPMEAsEEckQ6M2sq2pmdZjv8jgdFhvV/VSpOj3BVoifQw9a2rZQlDL+YVYEjyLqmyc2bAejOWUHq1hfG7fyn5J5CIBzgbzv+Nm7XEIwv4QOKX6okiVA4fkUxFI5E/x8MReK2+4ORqAxwOCLHFdVUziFyrEbKwb9T5W8Risj4B/m7hCIy2xtdtPdOniCJ4MgkFJEJhOMnuoLh+FozoUh83xUIBDOHI9KZ+XBvG7NG48zUrQNfF6QvHPEpPqj7gAJ7wbBWZfZT7JwazowrYz7GjiqMHZWH33kEqCQVX5rzJR7f+jjlXeXjcg3B+FKQbI4pTPv+nlYuWBRbc8Rh0lI64Pe4MMcRl8x77fGFJFqUPp/lNHL5stjQQ6dJS0mqqCUxUnISTFx4QC2YZKue4r7vND/JwtVHx4bl6jUqMhwGNJKKxTmOiTJVIACUPvnFA0LFtWqJsnRrtEAvKPWQisXYIBDMaI64nJlAKMK66g6uWJ4zshPIkb5VmVMUaZ8R0ORupKKrgjMLzhrR8VnWEF0+Na0eFcmmSZxxUmnozFtJ2qZnqTzpR+NyiRRTChcUXcCPP/wxT5/9NFrVKEIDBRNOmt3Io19cwj/X1fJJeTtnzEnj1LJU5mTYeH59HfMy7Xzx6NwYh2duhp2nv7aCP6+upKHby1VH53FiaUp0u06j5roTi8hPtvDvDXUsyHJw5VE55CWNQc2oIxS9Vs0PTithVrqVlzY1sDjHyRUrcshO6M9BOn9RJhaDhhc3NZBmM/D5pVmsKW/n6a+tYG6mqCMjmHhOmZ2KXqfmhQ31JJh1XHlUDrNTrdxy1mxe3FTP4hwHV6zIJSdB5NIJBDMZaTrK3y5dulRet27diI5dU9HO/724jdvPnzuyi5e/C9ueh+VfH5EOaUSO8LftT5BvLyDfnn/4Aw7CP3dZWJXp4+xCz4jPMRaoAr0UvPsbtl3yJ4KWpHG5hizLPLjxQZanLec7i78zLtc4BEP+I4+mX850ZFkJUzJo+8MyfcEwOrUKlWrwrzgUjhCOyOi1Bw/lPNw5ZjDD+sDD6ZuH+07dviBatQRIqFUSGiGJK+hn3PrloXB5A2hVEkZ9/2TXETw2CAZHdIQZzBF3F3p7ZwsLRlqNOuxXVmWKTxtxQYVPGj5BrdKMypEBmJUQ4KP6ya9qHNGZ6c5eRvrGf4zbNSRJ4uo5V/PcnufY0Lxh3K4jGD8kSYpxZAAMWvUhHzQ0atUhHZmhnEMwfA73nVoMWvRaDXqtWjgygimBzaiLcWRAjA0CwZHEERVmJssyb2xv4mvHDa1AZRxb/w22DEgYmSNS46phffMGTs87bWTXH0BpQpB/77XQG5Qwayd3da2j8Hjy37uXpkWXErCkHP6AEeDQO7iq7Cpu+uAmnj/3eRwGx7hcRzB8djW62NnoQq1SMSfDhk6jYmt9N73+EKWpVuZk2lEPeKjwBkNsr3dR3uomwaxjXpaDNNvkO+aCwen1B1lf3UV5qxuLXkOW00iXJ8jcLDvZThG+I5g8AqEI66o62NviRq9VkZ9opq7TQ2GyhTmZdrTC2RYIjgiOKGdmT7MbTzBMwUhi691NsONFOOqbI7p2h7eD/5S/xFHpK0aU9H8gBo1MkSPIx/UGTs3zjvp8oyGst9KVexSZa/9E5ck3j9t1FqYsZE/nHn704Y946JSHUEniRjXZbKrt4vJH10QLJ15/UhGvbm2kvLUXALVK4okvL+OY4uToMa9tbeJ7z26Ovl9VmMgDly0i2Tr5ohaCeN7a2cJ3/7mJ/RHJZelWrl6Zx9ee+IzHrloWk1cjEEwkH+xp4dqnNkSV+LITjNx4aimfe+hjHrtqKSfPTp1kCwUCwURwRD0NvrixnqPyE5CGHSImwyd/gNxVYEoY9nXbvO38Y/czzE2aR5o5bdjHH4z5yX7erJoaDxIdRSdgr1uPuWnHuF7nc8Wfo8PXwW83/HZcryM4POGIzBMfV0UdGZWkSC/vd2T273Pn/3bR4w0C0Njl5daXY/vIR+Xt7Gx0TZzhgiFT29HL3a/vZmBq5Y7GHsIRpQ7N1vruyTNOcETT7vbzu3f2xUiK13Z4aev1o1OruO3lHXT0+ifRQoFAMFEcMc5MKBzhXxvqYmaIh8zeN8HdDHnHDPvQXR27eHrn08xNmkuBfYThbQehLClARZeWRvfIat2MJRGNgZbZZ5P/3j1I4fGrOaFRabh2wbW8XPEy/97z73G7juDwhCMRKtv6HRetWoUvGF/3oaHbhzektHuDYbo8wbh9XL74NsHk4wmEaXb54tq9QaWoabdX1JcRTA5uf4imQfpmlyeI1aChqduHNyjqywgERwJHjDPz1s5mEsy64Us0dtfAuj/D3ItBPdSoPJlaVy3/3PUM79e+z7GZx5BvyxuuyYdFq4IlaT5e2js1JGl7MhYSNDrIWvP4uF7HprNxw+IbeGDDA7xR9ca4XktwcHQaNZcv76/34g9FcJjipbMvX55Ncl+NmHS7kdPKYkM/dGoVRSmW8TVWMCJynCbOXZAR06aSIM1mQJKgNHU0xYcFgpGT7TRywQG1kQCKUyy0ugNcuiybVBG6KhAcERwROTOyLPP7d/Zxxtxhhnj5XfDWrVByGlgPfmxEjtDl66LJ00RdTx3lXRWoJIliZzEr0o8a19yOlRk+Htzg4LLZbhyGSZ6FkiSa5l9E3ocP0ps6m46iE8ftUunmdG5YfAO3r7kdX8jHeUXnjdu1BAfn5Fmp/PjMIH98bx96tZosp5GHvrCYO17dSUdvgC+syOWK5TnR0E6jTs3NZ83CatDw8pZGCpLN/PScMkpFUbspiVGv4avH5CMh8crWBtLtRr5zcjFv7Wji0S8uZW6mcGYEk4NKpeJzi7PwhcI8v64Oh0nHt08q4t1dzVx1dC5fPbZAqO0JBEcIR0SdmZe3NHDvG3v45QVzUQ01XybghtdvAVsmlJ4RbY7IEdq8bTS4G2jsbaTZ00yHtx2DxkiCIQGnIYE0cxpOvWOYn2rk/LfcjEUb4btLp0b8ut7VQNaax6k8+cd05ywf12vVu+t5cMODnFt4Ltcvuh6Nasz9c1FnZgg0dftQSZDSp0rW4fbjD0dIsRpilMz2EwiFaXMHMOvU2E26iTZ3JjCh9Ty8wRB1HV6MWjVqlYReqyLBLGa9BXFMeJ2ZUChCVUcvBo0as16DNxgmxaoXjozgQIRO9wxmxq/MtPT4+MV/tvOtE4uG7si46uHt28GZByWn0eFtp9JVRWVXJXXuOowaI4mGRJxGJ/OT5mPXO9CO/UP0kDkl18Nv1ztY1+RjadrkJzz6bRnUL72K/LfvpH75V2gtO3vEdXkOR6Ylk1tW3MKftv2JK1+9kltX3kppQum4XEtwcNLssdLKCZZDP+jqNGoyHKNX9RNMDEathmKxeiaYgmg0KopS+vumcxJtEQgEk8OMdmY6egN86c+fcdKsFGalDSEcIuyHnS8jb/knzRnz2KSXqNz8CGE5TJo5jTRLGvOTF2DQTK0ZSaNG5tLSHu5a6+TnqzqYmzT5Sbm+hDxqj76WjI1/x1H1MbUrv4HPmTsu17LplRyaD+o+4KtvfJUV6Su4uuxq5ibNHYFynUAgEAgEAoFgujAjnZkeX5BXtzZy7xt7WFWUNGiSIIA/7KOzuxpP42bUDRtIbdpFo1bH+xYDWtlNipTCMZmrsE9gyNhIyXeEuKS0h1s/SuCUXA/nFPaSYQmP14LIkAhYU6hedT2OytXMfvG7eBIL6Cg4Dnf6PHyOHOQhCyocHpWk4oTsE1iRvoL3at/je+99D41Kw3FZx7E4ZTElzhKyrFno1CKkSSAQCAQCgWCmMC1zZiRJagWqB9uWdvUDpfq0IgtAJNAV1jobo7rFErDU58d4kM/sliT8siQjA0y/7wXALVupoDDGhblR/ZvwPNW2Sf1AWgkWSyGN4SDO1d6IKnJG0N4TOVRYaxgdaoa07CQhoU3WGnSJusMuo7W81FLX8kJL80E2t8myfMZBtsVe8xD9coxJAtom4DqjZbrYCdPH1v12DrlfwoT2zYMxHb5fYePoMciyPHeoOw+xX071z3w4hP2Ty4jGTMH0Ylo6M0NBkqR1siwvnWw7xpsj5XPCkfVZD8V0+R6mi50wfWydLnYeyHSwW9g4esbDvqn+mQ+HsH9yme72C4aGkPsQCAQCgUAgEAgE0xLhzAgEAoFAIBAIBIJpyUx2Zh6dbAMmiCPlc8KR9VkPxXT5HqaLnTB9bJ0udh7IdLBb2Dh6xsO+qf6ZD4ewf3KZ7vYLhsCMzZkRCAQCgUAgEAgEM5uZvDIjEAgEAoFAIBAIZjDCmREIBAKBQCAQCATTEuHMCAQCgUAgEAgEgmmJcGYEAoFAIBAIBALBtGRCnBlJktSSJG2UJOnlQbadIElStyRJm/peP5sImwQCgUAgEAgEAsH0RjNB17kB2AnYDrL9Q1mWz5kgWwQCgUAgEAgEAsEMYNxXZiRJygLOBh4fq3OeccYZMiBe4jURryEj+qV4TeBrWIi+KV4T9BoWol+K1wS+BDOYiViZeQC4CbAeYp+jJUnaDDQAN8qyvP3AHSRJ+jrwdYCcnJxxMFMgGD6iXwqmKqJvCqYiol8KBIKxZlxXZiRJOgdokWV5/SF22wDkyrK8APgd8OJgO8my/Kgsy0tlWV6anJw89sYKBCNA9EvBVEX0TcFURPRLgUAw1ox3mNkq4DxJkqqAZ4CTJEl6auAOsiy7ZFl29/3/VUArSVLSONs1Lejo9eMNhCfbDIFAIIij0xOg1x+abDMEgiERCIVpd/sJhSOTbYpAIBhjxjXMTJblm4GbQVEtQwkhu3LgPpIkpQHNsizLkiQtR3Gw2sfTrqlOfaeHf22o59l1teQlmvjuKSUszUuYbLMEAoGAlh4fL29p5K8fVZFi1fHdU0o5qiABjVoo/QumJjsbXTz8fjmfVXZw0uwUvrQyn6IUy2SbJRAIxoiJUjOLQZKkawFkWX4YuBj4piRJIcALXCbL8hGbrBUKR3jsw0r++nEVAHWdXj6rWsuL31rF7PSDicEJBALBxPDixnp+9eouAGo6PFz157X865srWZTjnGTLBIJ4Gru8XPPEZzR0+QB4ak0NW+tcPPGVZThMukm2TiAQjAUTNpUmy/J7++WXZVl+uM+RQZbl38uyPEeW5QWyLB8ly/LHE2XTVKTR5ePva6tj2vyhCHuaeybJIoFAIFBod/v58+qqmLaIDJtquybFHoHgcFS09UYdmf1sruuiqt0zSRYJBIKxRsQFTDF0agmrQRvXbtCqJ8EagWD4lHeVc+2b1/J/q/8Pd8A92eYIxhCtWoXDFL+gb9FPyiK/QHBYDNr4xxyVBAaNePwRCGYK4tc8xUi1Gbn5zFkxbYXJZuZkiBAzwRRm53/h1R/S1byNr73xNXJtuXT4OvjJ6p9MtmWCMcRm1PLD02PHp2SLnsUixEwwRSlMsXDGnLSYti+tzCM/2TxJFgkEgrFGTKdNQc6al06mw8j66k7SHUaW5TnJcpom2yyBYHD2vQUvfx+yVxD627ksWnwOp+SeQjAS5Gcf/Yz1zetZkrpksq0UjBHHFCXx3DeO5rOqDpwmLcvyEygUydSCKYrDqOMX55Vx3oIMdjf3MDfTzuIcB3qNiHYQCGYKwpmZgpj1GlYWJbGySChUC6Y4kQi8djMc9U1cKbNoqnqLr0bMuAGtSsupuafy1I6nhDMzg9Br1SzLT2BZvlBYFEwP0uxGzppv5CzSJ9sUgUAwDogwM4FAMHKqPoRIGDKXsrp+NXtTZ5Gz643o5qPSj+Ljho9xBVyTaKRAIBAIBIKZinBmBALByNn0NBSeCJLER/WrseQfi87dit7VAIBJa6I0oZTVdasn2VCBQCAQCAQzEeHMCASCkREOwZ7XIHcV9e4GeoO9ZFqz6U2djb16bXS3eUnzeK/2vUkzUyAQCAQCwcxFODMCgWBk1K8DczKYk1nfvJ5iZwkqJHqTirDXfhbdbU7iHNY0ruEIroUrEAgEAoFgnBDOzCQjyzKNXV5aenyH31kgmErsfQsyFgKwqWUjhfYCADxJRViatoMcASDZlIxWraWiu2KyLBWMEaFwhIYuLx1u/2SbIhAAEI7INHR5aRd9UiA4YhFqZpNIS4+PZz+r5ZH3KzBo1fzw9FLOmpeGZZCimQLBlKPyfZh1Du6Am4beRrJs2QCE9VbCOjPGzmq8CfkAlDhL2NiykUJH4WRaLBgFtR0e/rS6kmc+qyHZqudn58zh+JIkdELiVjBJNHR5eeLjKv72STVOk5b/O6eMk2aliCLTAsERhliZmUTe3N7MPW/soccfotXt56Z/bWFddedkmyUQHJ6gD5q2QspsdnTsIMeWg0bqf4DwOnMwN++Kvi+wF7C+ef1kWCoYA8IRmb99Us1fP67CF4xQ2+Hl60+uY1u9UKkTTA6yLPPsuloe+aACbzBMQ7eP6/6+gS21XZNtmkAgmGCEMzNJeAIhnv60Jq79nZ0tk2CNQDBMGjaCMxe0Rra3bSfbkh2z2W/LxNzS78zk2/PZ2rZ1oq0UjBGtPX7++VnseCXLsLtZODOCyaHdHeAfg9xDN9d1TbwxAoFgUhHOzCShU6vITTTFtecM0iYQTDlq10JSKQA7O3aSa8+N2eyzZ2Fu3R19n2nJpKm3id5g74SaKRgbjFoVaXZDXLvdqJsEawQCMOrUZDqMce2JFv0kWCMQCCYT4cxMEhq1iq8dW4BB2/8nSLbqOa4keRKtEgiGSM0aSCqh099Fb9BDkjEpZrPfno6hs1YpqAloVBpybbnsbN85GdYKRondpOOWs8tQSf1ts9OszMuyT55RgiMas17DD08vRTOgU+YnmVmc65xEqwQCwWQgBADGmWaXD18wTLrdEJcouyjHyYvXrWJnkwuNSsXcTDv5SeZJslQgGAYNG2DuRezt3EO2NRsVUszmiMZAyGDD0F2Pz5kDQJYli10du1iatnQyLBaMklWFibxw3Sr2Nvdg1mvISzKjU0uHP1AgGCNkWVEuk4EMu5EV+Ym88K1V7GnqwahTMzfTTk6CiG4QCI40hDMzTviCYd7Y3sRtL++g0xPkwkWZXH9SEbmJsc7KrHQbs9Jtk2SlQDACepoUAQBLKrtr3yTDkj7obn5bOsaOyn5nxprF9vbtE2mpYAzRqFUsyHaQYNbxx/fK+fY/NmI3arnlrNmcOS8Nk07cTgTjR0evn2c/q+PBd/YSkWWuPb6QL6zIYV6mnXmZYoVQIDiSEWFm48S2+m6+88wm2twBwhGZ59fX8ZfVVYTCkck2TSAYHQ2bILkEJIk9nXvJtGQOulvAkoKxoyr6Ptuaze6O3YPuK5geRCIyT6+t4R+f1hCOyHT0BvjBc5vZXNc92aYJZjgf72vnztd24QmE8QUjPPDWXt7f0zrZZgkEgimAcGbGiV1NPXFt/95YR6so7CWY7jRsBGcevrCfFk8zqea0QXcLWFIwtfcXysy0ZFLTU0MoEpooSwVjTHuvn+fX18W1bxMKUoJx5pWtjXFtz62rIxKRJ8EagUAwlRDOzDiRaIlX+clNNGEWoRiC6U7DBkgopLK7klRzakx9mYH4rakYumqj7w0aA06Dk5qeeDlVwfTApNOQmxSfk5Bii1c6EwjGkpJUa1xbWYYNlUrkbQkERzrCmRkn5mfaWTBA6Uerlrj5rNnYjNpJtEogGAOatkJCAeVd+0g3DZ4vAxAwJ6PvaYwqmoEiAlDeVT4RVgrGAbNew02nl6LX9N86ytJtLM4RClKC8eWseekkD5Bddpi0XLwkaxItEggEUwWxTDBOZDpNPPzFJexocOH2hyhOsTArbWSJ/t3eIC0uHzajllQxAyqYTDwd4O8Baxr79u0j15Z30F1ljY6Q3oa+pxm/PQOAVFMq+zr3cWruqRNksGA0uH1Bmlw+TDoNGX01PZblJfDidavY29KDSaehLMMW3SYQjBelaVaeu/Zodja5iERkZqfbKEi24AuGaOjyodOoyHIKJTOB4EhkQpwZSZLUwDqgXpblcw7YJgG/Bc4CPMCXZFneMBF2jTfpdiPp9tHd5Hc0dHPzC1vZXNtNqk3Prz83j+NLUlCLpXXBZNC0FRIKkSWJyu5Kjs44+pC7BywpGLrros5MhiWDPZ17JsJSwSjZ29zDz/6zjU/KO0gw67jt/DmcVpaKTqNmdoaN2RlChVEwseQlmckbUL6gur2X37y2i1e3NWHSqvnRmbP43KIsLAYxTysQHElMVJjZDcDBquWdCRT3vb4OPDRBNk15ujwBfvj8FjbXKkpBzS4/X//beva1xIsLCAQTQtNWcObS6eskIkew6Q4tiRowJWLo6k8Yz7BkUN4twsymOp5AiDte3ckn5R0AdPQGuP4fG9nZKMYewdQgEpF5ak01r2xtQpahNxDmZy9tZ3Nt12SbJhAIJphxd2YkScoCzgYeP8gu5wN/kxXWAA5Jkg4eiH8E0djtY3uDK6YtFJGpavNMkkWCI57GzeDIpdJVRbolg8OtDwbNCTEiAGmmNOp76gkPyKMRTD1aXH7e2x0reyvLUNnWO0kWCQSxtPf6eXFTQ1z7tgYhEy4QHGlMxMrMA8BNwMEKrGQCtQPe1/W1xSBJ0tclSVonSdK61tYjQ1veatBgH0QwIMEsRASmCkdcv2zeCgn5VHVXkWxMPuzuAXMy+u7+n7deo8eut9Pgjn8IEYwto+mbFr2GLGd8iGyCOV6lUSAYDmM1Zpr1GkpSLXHtIn9LIDjyGFdnRpKkc4AWWZbXH2q3QdrihONlWX5UluWlsiwvTU4+/EPUTCDLaeKXF8xFGvANXbkih9IRCgkIxp4jql+Gg9BeAY4cKrorSDtIfZmBBM2JGFyx9SHSLelUuirHy0pBH6Ppm0lWPb+8YC6aAbl5Z81Lo0zkyQhGyViNmSadhh+cWopJ1y8NvyjHweIcxxhYKRAIphPjnSW3CjhPkqSzAANgkyTpKVmWrxywTx2QPeB9FjCjp23dviB7W9zIMpSkWbDoD77ScvqcVP777WOoau8lyaJnVppVyDsLJoe2vWBNQ9boqXFVc0LWCYc9JGhMQNvbjhQOIauV4SbVmEpldyXHZR036DGyLPPn1ZU89mElKgl+eHopFy4WEqwTzbHFyfzn28dQ2e4m3WpErZbo9YdINOuQpNg5KG8gTG2nB41KIjvBhFYtVP8F48/iXCcvfWsV5S1ujDo1s9JtB1X83NfcQ1tvgDSbIUZEQCAQTH/G1ZmRZflm4GYASZJOAG48wJEB+A/wbUmSngFWAN2yLMeX+p0h7Gvp4eH3K/j3BiUp+rwFGVx3QiElB1lt0WnUzM20Mzfz0InWAsG407wtmvwPEhZdfIjHgchqDSGjA527JapolmJOoaKrYvD9ZZlb/7ud1fva+e4pxQTDMr/63y6MOjVnzBWpdBOJWiVRlmFDq5b40b+2sKGmC5NOzS1nz+bCRZmY+goA13Z4+PX/dvLq1ia0aolvHFfAl1flkzigJohAMF4Up1opHqSg5n4ikQivbW/m5y9tp9XtJ8tp5FcXzuW4kpQJtFIgEIwnkzJ9JknStZIkXdv39lWgAtgHPAZcNxk2TRQf7mnj+fV1RGSIyPDipgbe3X0E5FoIpj9NW8GRS5WrmjRz6mGT//cTMCWiHxBqlmZOO2iY2T8+reHdXa3cfOYschPNFKVYuP7EIm55YRsuX3AMPoRgOHgDYe5+fTcbaroA8ATC3PLCNnYMECb594Y6Xt3aBEAwLPP7d8tZV905GeYKBHFsq3fx/Wc30er2A1DX6eUHz20RqqACwQxiwpwZWZbf219jRpblh2VZfrjv/7Isy9+SZblQluV5siyvmyibJoP39rTEtb2zK75NIJhyNG4GZx7VruohJf/vJ2hKQN8zwJkxpVHjqonbr6LVzV2v7eY7JxdHZ/1BmXmdk2nniY+qRmW+YPi09/p5a2dzXPt+VTO3L8h/t8QvpH9c3jbutgkEQ6G6w4MvGKs/1Nrjp7bDO0kWCQSCsUYENk8wczLiw8VECJlgWtCyA5yKklmKKXXIhwWNDvTd/WlwToMTd9CNJ9gvMR6JyPzw+S1csChjUDWic+al88QnVQTDBxNFFIwHVr2GWYOEwCZblRAyg1bNkkESrsvShVCAYGqQbNVxQIoXBq2KRKHMJxDMGIQzM8GcPieVnART9H2W08g580UugGCK09sGQS+Yk6lz15JqGnq8edCUgKG7v3CmSlKRakqlpqd/dea59bX0+IKcNntwhbTsBBMpVgPvilXMCcVu0vHz88owaPtvFefMT2du36SMRq3i6pV5JFn6HwznZ9k5qiBxwm0VCAajLN3O9ScWRd9LEtx85mzhcAsEM4jxVjM74ggEwmxt6MblC5HjNFJ4QGLigmwnf/rSUnY19iADs9KslAySvNjh9lPX6cVi0JCbaEatGmqGwvSi299NvbsevVpPjjUHrVpRamv1tNLU24Rdbyfbmh2nniSYYJq3QUIh7pCH3qAHu8Ex5EODpgT01Z/EtKWaUqlyVTErYRbdniB3vbabG08rRXWIfr6yKJF/bajjtDmHl4QWjB0r8hN5+fpjqGzzYDVomJVmRQK21ndh0KgJRWQeu2opgVCYUESmMNmC1ahlR0M3kiSRl2jGOEA+VzD2dHg7aOhtwKw1k2PNQa1Svm9XwEVdTx06tY5ca250fJ1JdHsC1HR6MGjU5CWa0WpUVLa6qe304jTpmJNh5Sur8lhVmES7J0CqVc/sdCsajZjLPRSyLFPbU0u3v5s0cxrJpsFDiz1BD7U9Si2xHFsORo2o8yOYeIQzM4a0urz8e2M99725F38oQm6iiTs/N4+jC5Ni9itOsVKccnD1lZ2NLr799AbKW3vRa1TcfOYsPr80G7N+Zv25yrvK+b+P/o9tbdvQSBq+Nv9rfGH2F6jqruIH7/+AZk8zJo2Jnx39M07LPW1G3oinDU2Kklltj7Iqoxpy+r/izOh6YvMukoxJ0byZe9/czZJcJ/mHkUtdnpfAPz6twRsIi4fjCaYoxUpR35i1r6WHHz63heNKkvlgTysba7tQqyQ+tygTtz/EiaUpvLenJSoKcOGiDH54+ixRzHCc2N2xmx9+8EMquyvRqXR8f+n3ubDoQpo9zfz0o5+yuXUzaknNl+d+mavLrsYxjImIqU55Sw8/fF5R2lOrJL55fAHHlSTz3Wc20dDtw6RTc+t5ZdgMOn74/GZcvhBJFh2/u3xR3H1Z0E8wHOT1qte5bc1teENeUk2p3HvCvSxIXhCzX4O7gfvW38frVa8DcHb+2dyw+AbSLSLaRDCxiKmJMWRrQw+//t9u/CElrr+63cOvXt1JXWfvkM/R6wtx28vbKW9VjvGHIvzivzti1INmAsFwkD9v/TPb2rYBEJJDPLT5Icq7yvnxhz+m2aM8/HpCHn6y+ieUd5VPprmCxs3gyKXGVXPQGbqDEdZZUIWDqP3uaFuKKYWq7ir2Nvfw0qYGLl5y+DoyVoOWwmQLH+wV6n+TRTAU4bEPKnH5QtR0eNhY2wVAOCLz3Po65mba2NvSE3VkAF7Y2MD7e8TfbDzoDfbym09/Q2W3og4YiAS489M72dWxiyd3PMnm1s0AhOUwj299nC1tWybT3DElGI7w2IeVUaW9cERR0ttU20VDtw9Q1PdqO71855mNuHwhANrcAb719EbqO4UAwMEo7y7nlo9uwRtSvqNmTzM3f3gz7d72mP3er30/6sgAvFL5CqsbVk+orQIBDMOZkSTJIUnSdyRJuk+SpAf3v8bTuOlGXYcnrm1rvYsWV2DI52jv9fNJeUdce21n/LmnM13+Lt6vfz+uvc3bRp27LqYtIkdo6J3RdVSnPs1bISGf6p5qkozDnNGUJALmpJjVmVSzEmZ2+8s7OW9BBjbD0FbdFmQ5eGtHvLqWYGLo9AZ4a2cz87PsfFYVP041dfuoao8fq94eRBFNMHo6fZ182vxpXHuNq4b3at+La9/VsWv8jZogujwB3t4Zn0NX3+XDOiCKIRwhOsG4n47eAM0u37jbOF1pcDcQkWO/s9qeWlq9sZMSb1a/GXfsuzXvjqttAsFgDGdl5lUgD9gKrB/wEvSxX+FnIHmJJhymoYdH2Y1aZqXFh6AdrKrxdMWqszI/aX5cu0PvIMGQENc+HClgwRgTCkB7BThyqXXVkmIcupLZfoKmBPTuAc6MKZV9DSr2tvRwWtnQz7co28H7e1qRZXnYNghGj82gZVGOg4pW96DjVLLVQMYgY9XyfCEIMB5YtVZKHCVx7SmmlLiQIIB8W/5EmDUh7O+LB5Ji1dMbCEXf6zQqDkzFM+vUJAg1s4My2IRVoiERh94R07YifUXcfsvSlo2XWQLBQRmOM2OQZfn7siz/RZblJ/a/xs2yaUhZuo3LlmVH35t0av7v7DIKkg9fKX0/dpOOX14wF8uAmaUrj8qZccorBo2Bby/8Nk69M9p2Wu5p5NvzuX3l7ehU/Teaby/8NoWOwskwUwDQugtsGYTVGlo8zSQPd2UGRZ554MqMTWejvf44zluYikY99GEozW5AkmBfi/vwOwvGHINWzXdPKaGu08vy/ERSBkzgrMhPoNnlozDVQlFK/5g3J93GqcNwWAVDx26wc8tRt2DW9uebXVp6KWVJZXx9/tdJNPQ7kSdkn8D85PgJpOmKXqvmOycXxyjpnVaWyrwsG9oBY4peLfHTc8qi8swalcSdF80nN9F04CkFfRQ5ivj2wm9H3+tUOm5bdRtp5ljxldPzTqfI0a8UV+os5cTsEyfMToFgP9JQZzglSfoe4AZeBvz722VZjo81GGeWLl0qr1s3NWtr1nd52N3YQ6cnQG6imaV5yiqDJxCisq2XQChCut1AS48fWYb8JDM2Y/zKTVVbL1XtvdiMWkpSLFiGGIYz3ajrqaPaVY1RY6TIUYRNbyMiR6jqrqLOXUeiIZFCRyEGzaStTA05030q98tRsfEp2PZv6hdeyv3r7+er864Z9ikSyt8jotJSe8y3AFhf6efe16q5/YLZ5Npyh3WuP62u4JiiJL60aubMMo+AYcn7jXXf3NXYTU2HB4teC5JMJKI8XIYjMsUpFsIRmb0tblQSFKVYSLbOrJXlqUZ1dzU1PTXYdDYKHYVYdIoz2eBuoKq7Cr1GT5GjCLt+3GuaTXi/rGh1U9Hai0GrIsWqxxcKEwzL1HZ4SbbqKEu3YdSp2VLXTVO3n+wEI/My7cOaRDkS8YV8lHeV0+5rJ8uSRZ49D5UU/521elqp6K4AoNBeSJJpygorCEnUGcxw5LECwN3ALcB+D0gGCsbaqOlKrz/Eq1uauOu1XYQiMqk2PY9+cSlpdgP3vrGHZ9cp8oVzMmycVpbK/W/t5bjiJH554byY2jMAeUlm8g6j7jQTyLJmkWWNTf5WSSoKHAUUOETXmhI0bAJnLnXuWlKGmfy/n6DRialtH6BIfj6/ppeM1AbavEnDdmZmpdn4YG/bke7MTBrrqjr40b+2Ut7qRpLgkqXZfO3Y/Kja2X5SZlho7FQm155Lrj3+d5RhySDDkjEJFk0Me5t7+NbTG9jTrPTF8xdk4g+F2d7QzcNXLqEsw04oHOF/25q46fkteINhbAYNv7t8EceXDr1W1pGIQWNgTtKcw+6XbEoetiiMQDDWDGdq4vtAkSzLebIs5/e9xNPmAHY2urjj1Z2EIoqv1+zy87OXtrG2oj3qyABsb3BR3eGhIMnMB3vbeGN708FOKRBMPg0bIaGQ2p66mLCV4RA0OaM5M7sbg3T2RshJ9dPsGX4RzDkZNtZVdRCJiLyZiabHG+Tx1RWUtyphfrIM//yslq113ZNsmeBIIxAK8/D75exp7u+LL26qpyzDRm2nlztf20VvIERFWy/ff3YT3mAYAJcvxHee2UTdDBPVEQiOZIbjzGwHxK//ENR3xUs9tvb42dgnHTmQjTVdzO7Lg3lLKP0IpiqRMLTsgMTCEcky7ydodKLrURyXVzZ6WVaoJ8HgoLl3+I68w6TDZtSyq6lnRLYIRk5jl5dPKzvj2vc7NwLBRNHlDQ4q+d3mDmDRafikvJ2u3gCN3V6C4diJj25vkBaXP+5YgUAwPRmOMxMGNkmS9IiQZh6cdHt8WIXTrGVeVnyc8rxMO3tblIex40vEcrdgitK2F4wJoLNQ764bsaqcUmsmQE+Xm83VARbm6nDoHSNamQGYlWZlbWX74XcUjCkpdj0Lsx1x7UdCSKxgamE3ajmqIH6lONGswx0IsTjHid2oJdVmQHOAnJlVryHRItTMBIKZwnCcmReBO4CPEdLMgzI7zcZ3TiqKqqbYjVpuPW8uRxckxsjP5iWaKE2zsqfZzYJsB2fOTTvIGQWCSaZhIyQV4Q15cQd6sY+0ergkETAlsHprF6XpWgxaCYfBGVe3YKgUp1hZWzHh2iNHPA6Tnm8cVxAzcXPWvDTmZY57YrlAEINeo+ZbJxaR6ejvi6eWpVLR2kuiWcctZ8/GYtBSkGThjgvnRR0avUbFPZcsIDdROOACwUxhOAIAzwM+WZbDAJIkqYH4wiozhIYuLzUdHsw6DYXJZkz6g39VgVCEyrZe2nv9XLgoi9PmpNHtDZKdYIom9t/9+QVc2+ImEFbUzFp7/Dx37dEUJJlJtEzvr9EX8lHZXUlPoIcsa9aMTjg94qhfBwkF1LvrSTYmoRqFIEzI6OS9vTLHLFCU+Ww6Gz0BF6FIEI1qeGp9s9KsPLuuFlmWkSQhUjNWVLf3Ut/lJcGsoyDJjE6jjtne2O1FpYZHvriEmnYPJr2a0lQrmU4hczsRVLuqaeptIsGQQJ4tD616ZqpcDpXZ6Tb+dPUyylvdmHRqkq16ur0hfnh6KZlOI6DUmfnc4kwWZttp7fGTbjeSL1YSJ51gJEhVdxUdvg7SzGnkWHPEWC4YMcNxZt4GTkGRZwYwAm8AK8faqMlmW3031zzxGc19MbVfWpnLd04uJsEc73T4g2GeXV/Lrf/ZQSgiY9apefjKJRxbEhuOYzdqWZzbX1NlpswKuQNuntj+BI9seQQZGYfewe9P+j0LUuILtgmmIXWfwfzLqe2pG7SQ2nAoV+fS7lWRl6wMO2pJhU1np83bRpo5fVjn2l+gtrbDS46oFzEmfFzexjf+tp4efwi1SuKWs2Zz+fJsjDrl77W9oZtr/rqOpr7K6Vcdnct3Txl8XBSMPZ80fMJ33/0unpAHtaTmR8t+xIXFF06mbP2ks66qg+/+cxN1nUq+6rkL0vn+KSVRR2Y/WrWK0jQbpSIIYkoQCAd4ad9L/GrtrwjJIYwaI/edcB/HZB4z2aYJpinDLZoZzfLs+/+Me4roDYT4zWu7oo4MwF8/rmZb/eBqPXtb3Pzspe1RBbPeQJjvPbuJhkHEAGYiuzp28fCWh5H71Lq7/F3cvuZ2uv1C3WjaE/JD6x5ILKKup5bEUTozb3rnsMDShmrA7JtT76BlBHkzkiRRmmblsyoRajYWtLh8fP+fm+nxK5XTwxGZ217eEVWK8gRC3P367qgjA/C3T6rZIlTMJoTm3mZu/vBmPCFFgycsh/n1p7+moqtiki2bPHr9QR79oCLqyAD8d3MjG2u7Js8owZCo6Krgl2t/SUhWxhtvyMtPPvwJje7GSbZMMF0ZjjPTK0nS4v1vJElaAsy4J/ZuT5BPB3lAGjhgDqSx28uBdUfb3AHaewPjYd6Uo8kTr0a1u3O3cGZmAo1bwJ4FWgN17jqSjCOTZd7Pu+58FmirY9rsejstI8ybKUqxCGdmjGjvDcQ4Kvtp7FbGvW5PkE8rhz4uCsaWdl877b5YwQsZmWbPkauE2dLjZ0NNvLJeRWvvJFgjGA7NnmYiciSmrdPfGdfHBYKhMhxn5rvAc5IkfShJ0ofAP4Fvj4tVk4jTpGPlIAop2QmDL0JlOowcGOaZYtWTfIQopWSY4/NjyhLLcIw0UVwwdahdC8mzkJGVnJlRFEbrCUhUeO3MlffGtNv1dlp6R/ZAVpJqZV1V/MOMYPgkWXRkOoxx7fvbHCYdKwvjx8UDi/0KxockYxIppljVSwmJNPORGzeVajWwLC8hrr0oxTIJ1giGQ5o5DZUU+/iZaEgcdSiz4MhlyM6MLMufAbOAbwLXAbNlWY6qmUmSdOrYmzfxGHVqbjxjFtkJyk1ckuAbxxccVK2nKMXCnZ+bj16jfJV2o5YHLl1Imj3+wWAmUuIs4YbFN6CWlEThZGMyPz3qp9h0tkm2TDBqqj+CpBJcAReyDGbtyB8SNrfoybf5MPliZ/ftIwwzA8hNNFHf5aXbGxyxXQKFZKuB+y9dgNOkJJRr1RK3XzCH4lQroIyLPzitlJyB4+JxBYPKzgvGnhRTCr8+5tfRcVWr0vLzo39OoaNwki2bPEx6DV87toCCAcn8n1+SxaJBpMMFU4sCewG3rbwNnUqZ9LXpbNx57J1HtHMuGB3DEQBAluUgsO0gm+8C3hzYIEmSAfgARfVMAzwvy/LPD9jnBOAloLKv6d+yLN82HLvGmrJ0G/+6diXVfWpmBclmDFr1oPvqNGpOL0sl06EolGU5jagkif9sqqcoxYI3GKHXHyI/yTzo6k6Ty0t5Sy9atURhioXEaZZMa9FZuLrsao7POh5XwEWWJYtUc+rhDxRMbWQZatbA3IujqzKj0ZlZ36Qn3xlBXd8LkRColKHHaXCMOMxMo1JRlGJhY00nJ5SKWk2jZXl+Iv+9/hhFzcykIz/JjEatTNJsr++moq2XW8+bi1GntHkDYarbetns7cKs11CcYsFhOjJWpCeD5enLefacZ2nqbcJhcJBny0OtGvy+dKSwONfJA5cupKKtF5NOTVGKmewEI5tru6hu7yXJqqcszYpjiPfVdreffS1uwhGZwhQLqbYjV1xhPNGqtZxTcA7zkubR6esk1ZxKljVrss0STGOG5cwchsGedfzASbIsuyVJ0gKrJUn6nyzLaw7Y70NZls8ZQ1tGTYrNQMoQBrJur5+/fFzNg+/sRZYVDfs7LpzLzgYX/93cwJs7lVnnBLOOv355GfOzHNFj9zT18LW/fUZ1hxJ3flRBAndfvOCgIW1TFa1aS7GzeLLNEIwlbXtBrQNLCvXVm0k0xodzDIfNrXouLukh3GpG4+smZFJClhw6B+3edmQiSMOKelUoSjazrko4M2NFltNE1gEyy6v3tnLd0xtweZVk3QsXZVCaakWSJP7yUVU01+bk2Sncfv5cMgYJVxOMDZnWTDKtmZNtxpThk/I2vvPMJlp7FMGes+alcf6CTG7450Z8QSUn49rjCvjacQWHLYFQ29HLD57dEs2ZLUgy88gXl0RXJwVji1qlpsBRMNlmCGYIw396ODhyXIPCfgU0bd8rbr/pzLb6Hn779t6oCIA/FOGOV3ZyQmlK1JEB6OgNcPdru+kNKA8EkYjMPz6tiToyAGsqOvi4XCTACaYAVR9A2jwARZbZMPJ8mU6fii6finRLmJDeitbbFd2mU+vQq/V0+boOevyhKE4VimbjSbPLy53/2xV1ZABe2NhAfrKZddWdMaIBb+9sYX21+FsIJobOXj+PfFARdWQAEsx6fvrStqgjA/DwBxUHVSMdyAd72mLEfyraeqO1rAQCwdRmLJ2ZQZEkSS1J0iagBXhTluW1g+x2tCRJmyVJ+p8kSXMOcp6vS5K0TpKkda2tIwtLGQ+auuPVfDo9QTzBcFz7xtouXH3x/d5gmE8q4h2XzUJWcloxVfvlqKl4D1KVn2Jdz+iUzLa36cizB1FJENJb0Hpik/adBgetIww1K061srW+m1A4cvidjzDGom92eYLsaHTFtYfDsHOQ9j1N7rg2gWAgYzVmtrkDbK+P7YMOk5aWAc7NfpoHUeo7kMEknT8ub8cfEmOLQDDVGUtnpmqwRlmWw7IsLwSygOWSJM09YJcNQK4sywuA3wEvHuQ8j8qyvFSW5aXJySOfJR5rshNMqFWxEXbpdgNmfXws8/ElySSYlZhys17D6XPic0tWFIwunEcwsUzVfjkqImGo/ADSFyIj09jbMCqVme1tOrJtffVLdGY03lhnRhEBGNlDjUWvIdmqZ2djz4jtm6mMRd9MtupZnh8/JmnUEksGFAHejxAEEByOsRoz02wGjj5AYa+520f+AUV0JengaqQDWTWIWt8Zc9IOmi8rEAimDsNyZiRJWilJ0hWSJF21/7V/myzLnzvUsbIsdwHvAWcc0O7aH4omy/KrgFaSpGmjzzcv084vz5+LWden5mXV8/Nzy3j201quPjoXTZ+jMzvdyg2nFKPX9A+MFy7O4pgi5aNKElyxPIejBpGFFggmlMZNYHSCOYlOXydalQ6jZuR5EDvbdeRY9zszFnSe2BVJu85G6wgVzQBKRL2ZcSPBrOfG00qjilFatcS3Tyxid1MP+UlmFvQ5LyoJvnpMPotz4h0cgWA8sBq1XH10LnMyFIU3tUrCZtBw+wVzSevLdzVq1fz83DLmZRzeyV5ZmMilS7OipRaOL0nmvIXxpQcEAsHUY8gCAJIkPQkUApuA/TFUMvC3QxyTDARlWe6SJMkInIKiejZwnzSgWZZlWZKk5SgO1qQnjlS0uqls68Wi11CSasVp1uENhNha301Nh4dUq4E5GTYSLHrOnJNCYYqZzt4AaXYDnkCYE2elkJ9k5rSyVDo8QUpSrZT0JRLua+lhd1MPsgw/O3c2gVAEtUpFfpIJg3aIf5KAB1p3QU8TOLIhqRQ0Orr93ezr3EdPsId0czq9gV7cITf59nyyrdnj+I0JZgx73oAMpT5uXU/dqOrLhCJQ2a3hstl9zozBiqGlIWYfh8FJ0whrzYASavZpZQdfOSZ/xOcQHJyleQn89SvLqGrzoNeokCMRVGoVtR1ebjpjFuGIEoZj0WvY3dyDDATDEfa1uJEkKE61kGabAaIA3fXKmCtJkDwLbCN70HUH3JR3ldPh6yDblk2GOYOK7gpaPa1kWjLJd+SjVWnH2PiZyZK8BO64YG5UzSzHaaSi3cOjX1xMc48fh1HH7HQLoXCEj/a10dTtJctpYm6mHbM+9l6bajfyi/Pm8KVV+YQjEfISzVgM0+zv0NsKLTsh6IPkEnDmTYoZ1d3VVLmqMGvNFDoKseqsVHRVUO+uJ8mYRKGjEJN2egkdCaY2w1EzWwqUycPLhksHnpAkSY3ipDwry/LLkiRdCyDL8sPAxcA3JUkKAV7gsmFeY8zZUN3JVX/+FLdfeQA7c24ad1wwhzd3tvCTF7YRjijmXXt8AV88Kpe/flzFYx9WcsrsFPQaNa9sbQQUZbObzijlntf3oFFJ/O2a5agkie/+cxOVbUqV4uwEIw9etoi5mcOoyxL0wmePwZs/U95LKrjgYdqLT+budffwSuUrABg1Rr6z6Dvcu/5ezFozj576KGWJZWP0LQlmLLtfhfmXANDgbiDRMPLQx2qXBqchglGj/GZCOktcmJlT72Bb29YRX6M01co/P1MSdaUDK9gKxoScBDM17R6+/uQ67vn8Am58bmO0vs9R+QmcMz+d5zfUMz/Lzr4WN39ZXUlVhweAomQLj161hILkaVzMsHU3/ONy6ChX3ieVwGVPQ9LwVBx7Aj08tOkhntz5JKDUi/nFyl9w59o76Qn2oJbU3HnsnZyRf8ZhziQARWnvW0/398UV+U6+c1IRlz+2lnsvWcAX/7SW286fQ0OXjwfeVgr2qiS49bw5fGFFDipVbHCKUadhdvo0rZHWVQsvfQsq31femxLgyhcgY+GEmrGldQvfePMbuINK/tyJ2SdyWellXPf2dYRlZR78mwu+yZfmfEk4NIIxYzhhZtuAYVU0kmV5iyzLi2RZni/L8tz99WNkWX64z5FBluXfy7I8R5blBbIsHyXL8sfDucZY4/YF+dWrO6OODMD/tjVR3trLL1/eGXVkAB5+v4I9zW4e+1ApkTM/yxF1ZEBRNvvLR1WcsyCdHn+Ih94r5+1dzVFHBqC2w8srW/qPGRJte+CtAeV65Ai88j12tm6OOjIA3pCXF/a9wMnZJ9Pt7+aRzY/gD8UnRwoEUVwN0FkFqUpqW427lsRRJP/v7dSRaen/LYX0VrS+bgaKGtr1Dtq8I1+MTbbqkSSobveM+ByCQ9Pe4+PeN/Zw8ZIs/vJRVUyh0jWVHcgSbKvvItGsY29zT9SRAdjX6ub17SNfeZsSbPt3vyMDyhi84z/DPs3uzt1RRwYgGAny2w2/5cyCMwEIy2Fu/eRWal21ozZ5ptPi8vLI+xUxfXFtZSc1nV7CkTC/e2cf3z65CJNOw2/f2RvdJyLDr17dxbaGeAGLaU3Nmn5HBsDTAR/eBxN4z+8N9vLA+geijgzAu7Xvsr19e9SRAXho80OUd5UPdgqBYEQc1pmRJOm/kiT9B0gCdkiS9LokSf/Z/xp/EycWly/E9kEGuU5PkJ4BDs5+Wnr6VVICgygq1XV6o4W3XN4gW+viJSK3DkE2MgZ3Kxy4eBXopc3TFrfrvq590WJU29q30RvsjdtHIIiy82XIXhEtark/LGCk7O3Qkj7AmZHVWiIqLepA/83OrDURDAfxhkbmjEiSxKw0W4ysqmBs6fAE2dPcQ2Gyhd1N8WILTd0+nCYdbW4/zYOoSU17yebqj+Lbag4sl3Z4Orzx30OLpwWH3hF97w666Q4M855wBNLeG2TXIH2xrsNLaaqNPc095DhNdPuCcbdLbzBMuzswQZZOEO374tsa1oN/4hQG3QE3Ozt2xrcH3Wik2ECgdt+kZxMIZhBDWZm5B7gX+AVwAfCrvvf7XzOKRIuOU2bHF+BLtenJPKAYnFYtkZNgiib5GzTxqicLsx3Rm39ukonjSuLzD06cNcyCf45s0BxQ0NOSSrYtJ27XFWkr2NoXwnNq7qnY9UJtSHAItj4HOUcBEEGmyd1E4iicmT2d2piVGYCw3hYjzywh4TQ4aR2hohlASaqFNaJG07iRYTdwTHESH+5t5dji+P6Qn2im1R0g3W4kv08sYCCnlQ1rUX/qMeeC+LbZw6/znGnJRDqgvnSJs4QaV030faoplVRTvNKlIJZsh4HjSuL7Ykmalc31Lo4pSuKzqk7sRi0GbeyjTrJFT5ZzBuRxDSRjUXzb7PMVMZcJIsGQwInZJw7aHpL77wMaSUOmRRR/FYwdh3VmZFl+X5bl94Gz9v9/YNv4mzix6DVqbjilmKV9sqMGrYqfnjObwmQrd140LzoAOk1a7r54PvMybPzm4vk4TFpe3drID04rwdKXWFiaZuG8BRm8vbOZpXlOvnZsIccUJfG5xZmoJCWP9Nz56ZxYOswE68RiuORvYO4byO1ZcMkTzE5ZwC0rbokqT5UllrEyYyWfNn3KyoyVXF56OWqVkJkUHITuOmjbHU3+b/O2YtQaMKgPXTn7YERkqHVpSLfE1lwK6S1oPF0xbQ69g2bPyEORZqfbWFM5zWf/pzBmg5brTiiiqdvP6XPSWJ6njI96jYpvHl9IRaubK1fksKm2k9JUCxcvzkSSlPyEK1bkDPrQOa0oOQMWfVEZtCUVLPkyFJ867NMUO4u589g7sWoVMZgCewE3Lr2Rdc3rAMiyZHHP8feMSnTjSMFi1HHF8hxW5Ct9UadW8c3jC9BIEvMz7VyxIoeXNtdj1qq45/MLSOwri5BhN3D35+dT3CfIM2PIXg4n3AzqPtGColNh2TWgGssKHIdGq9by1flfZXGKcg/Rq/X8YMkPWJKyhCyLEiFi19u5+/i7ybcLwRbB2CENNddekqQNsiwvPqBtiyzL88fFskOwdOlSed26deN6jW5vkPouD0aNmtxEM6q+1Zeqtl4aur0kmvWUpimDocsbZGNNJy09fnITTWhVEp2eINlOE2q1hC8UJtthwmpUBhm3P8ieJkX1pyTFGm0fNl214O0ASypYlZlPWZap7anFE/JgU+mpc9cTiATJMqWRlzT7oKeKRCJsadtCRXcFVp2VWc5ZZNuE+hkw5IzyieiX48oH90L9OjjqOgA2tmzk1cpXuaj4ohGdrr5HzU3vJXHTigMS/qs+xuvMobPwhGjbu7XvkW3L5uz8s0d0LVmWue7vG3jlhmPjVlBnKMNSOhirvrm1vou9zW6seg0Osw4VyoSPPxShyxMgEIZ5mTaSLHqqOzxIQE6iKUaSftoS9EGnkh9JQgH0tkHzdoiEIGU2JAz94ayup46eQA9p5jScBieN7kY6fB10+bto7m0mw5LBnMQ5WPVW/CE/+7r2Ue+uJ9mUTLGjGItuyoopTHi/3FrXxZ5mN0adiqJkCx29QTIcBly+EHajNlpjZk+zi7aeAOl2A/nJFtrdfnY39dDtC1KQZKEk1TL9BURcTUo+V9gPznxIKhrT07d52tjTuQdvyEu+PZ8CR8Gg+/UEeqh312NQG8ix5aCSVLR722nxtGDX28mwZNDqaWVn+05ava1kW7OZkzQHszZ+VXcMmeZ/XMGhOKyamSRJ3wSuAwokSdoyYJMVGCSQeGZgN2qxG+NDsvKSzOQNCKNw+0L8/p19PPphBaBM3H3vlBL+vraadneAx69eygmlsWFkFr2WxbljUBzTka28BiBJEjm2HOrbdnHT6h+xuVOJXzVrzTx2/P3Myzx60FOtrl/N99//Pv6wEu++LHUZPz36p2L25EhBlmHjk1FHBqCht4EEw8iT/yu7Y/Nl9hPSWdB6YldRHHo7LaOQZ5YkibIMG5+Ut3PxkqwRn0dwcD6r7OCLf16LL6jkBh5blMTdn19Am9vPV55YR5dHScSelWbhkSuXRqXoZwxag+K0ALTtg2cuVx4cAUyJcNVLkDZvSKfan8e4H7PWzDO7n+HP2/4cbbtxyY1cVnoZr1a9ys8+/lm0/Rvzv8E1864ZVe2nmcLGmk6ufHwtvQFl9XdJrpMHL1tIpjNeJask1UZJX/ReS4+PW17Yxps7lDFHp1bx168sY2XhNF5B7KyG578M9euV93obXPUiZC4Zk9M3uhu5efXNrG9Wzm/UGHn01EdZmLIwbl+rzsqshFkxbYnGxKiYTKe3k8e2PsY/dv0DUEKNf7LiJ1xSckmcwpxAMBSG0mueBs4F/tP37/7XElmWrxxH26YFe5p7oo4MKM+Ej31QwfkLMwlFZH7y7620DhAJmCg2tW6KOjKgqIw8tO3P+Pzx4gYtvS38duNvo44MwGfNn7GtbduE2CqYAlR/BMhK/Yw+al11JI1CyayyS0uqKRzXHtIP5sw4RxVmBjArzcbqvSPPuxEcnB5fkDte3RF1ZAA+3NfG5rou/rS6IurIAOxqcvNRebwYyYxi31v9jgyApx3W/Rki8SIwQ2FXxy7+su0vMW0PbnyQ7R3b+dXaX8W0P7LlEaEEBXgCIe59Y3fUkQFYX93Jxpquwx67rb476siAIt7zs5e20dk7jUUBaj7pd2QA/C54/x5lRXEM2NK2JerIgKKW+ruNv8MTHL5wy86OnVFHBkBG5v7197Orc9eY2Co48hiKM6MGXMC3gJ4BLyRJGoPlhelNxyCDX48/hE6jfLUN3T7cvvjZ6fGm3t0Q17bHVYnH1xXX3hPsodpVHdfe5Y/fVzBD+exxJcZ6QJiFomQ28tj9im4NKeb4vh/WW2MEAAAcBget3tE9AM/NsPFxeTuTXKZqRuL2hdjbHK+K1OLysWMQ9cfB9p1RNA8y0VO/XgnvGQEdvg5kYvttIBKgy9+FLxz/MNrp64xrO9Lo9YfYPUg/q+30HvbYwe7bFa29MSUZph0dVfFtzVshMDYKps2DrJzv7dw7IoXUDl98fqMn5BHPHIIRMxRnZj2wru/fVmAPsLfv/+sPcdwRQU6iCZ069mvMTzLT3K3cgFYWJpJiNQx26LgyZ5DimGdmHofDEl+1Os2cxrGZx8a151jj1dEEM5CeZmWmufDkaFNYjtDiaR5lwUwtaeZBVmYMVrTerpg2m86GK+AiFAnG7T9U0uwGZFmmok3Ij481SRY9Z81Lj2svTrVy3oJ4VaKji0a+ojctKDolvm3+paAdWehXtjUbkyY2NCrZmEymJZN0c+z3blAb4sLUjkQSzHrOnR/fJ+dlHl6xMy9xEMW9OWkkW3VjYtukkDVIONm8i5XimWNAibMkru2M/DNIGME9Ituajf4AYZksSxbZFpGnKxgZQ1Ezy5dluQB4HThXluUkWZYTgXOAf4+3gVOd/dWtU23KD3NWmoUvr8zjP5sbWJrn5BfnzsFsOGxq0pgzP2URN82/DqPGiITE6ZkncEnxxajU8baYtWaumXcNK9JWAGDVWvnRsh+xIHnBRJstmAzW/QVyjwF9f1Jxq6cFi86CTj2ym3sgDK0eNUnGeGcmotaDHEEV7J9BVUsqHDr7qOSZJUliXpad1XtneIjTJKDVqPjmCYWcNEtZqbPqNfzqwrnMy7Rz/sIMLl6ShUpS1M1uPK2EZWOREziVyVsFx/8YNHpQqWHxl2D2eSM+3ZykOdx13F1RxyXPlsevjvkVpQml3HvCvRQ5lETuVFMqD570IHm2vDH4ENMbtUri6pV5nDlXEb8x6dT8/NwyFmYf3pmZm2nn3s8vwGZU7oerihK58bRSDNqJv1ePGdnL4bQ7QGtSVtjnXgSLr45ZbR8Nc5Pm8pMVP4k63SfnnMyVs68ckULqvKR53HnMnVEJ8kJHIbeuvFWIDglGzHDUzNbLsrzkgLZ1siwvHRfLDsFYqkZVtvWyq8mFColZ6VZyE81EIjK7mlzsa3Fj0muwGzTsaXbjMGmZl2kn54BZnS5PgH0tblzeIMlWPQ6TDl8wTJrdgNUwQqWywfC7lfCGrlqwZUDqPDDaDrq7HIlQ37GbQDiIWqNlX/suwnKEDEcBLf5OZFmmJKGEbKsygHT6OqnpqcGoNhIhQnlXOQ69A5vORk1PDcn6BErRYG+vBHs2pM0FvZV2Tzu7OnfR7e8mz55HsbMYrWoMP/fkMrPVzEIBuH8OnPwzcOZFm9c3r+fN6je5oOiCEZ22slvDrR8l8L2lXYNuT9vyHPVLriZg718pfH7vvzin4GwWJC8c0TUBPtrXxvaGbv7y5eUjPsc0YdxVo4LhCLuaemjo8KDXqun0BsiwG+kNhDHpVBQmW+j0KMqMeq2KDIcRi05DdoIpqv44o2gvV9TLJAlS54BKp7SpteBuVv4iybMhRck7a/G0sLtjN+6gmwJ7AYmGRPZ07qHL30WeLY/ihNhx0hVwUdNdgyvowqlzkmZOo8pVRZ27DovWQlgOY9QYmZs0dyrXC5twNbONNR20u4No1BIpFh1lmY4hH1vX6cEbCJNhN07KpOOQ8fcMuPdnQupciAShaauiqpdYqLSptdBZBeGgIg40yEphOBRgb8smKrorserMzEooI9kZr0rW6etkd8du2n3t5FhzKHGWoFPrqHfXEwgHSLekDypCEQ6HWd+ynsruSkxaEyXOEkoTSgf9WFXdVXT5u0g1pZJuiV9lG2Nm4KAk2M9wfr1tkiT9H/AUIANXAtO6St2OBhdfeHwNnX3Jq6k2PU9es4I2t5+r//wpwbDi6M3PsjMv087f19ZwYmkyvzhvDrl9Dk2PL8g9r+/mqbX9Rc/uumg+lyzNGluZx3AQ1v8F3vi//rZjfwDH3gi6eOUWAEmlIitpNhXNm/ja29fT6FViXm06G1+b/zXuXXcvqaZUHj71YYocRTgNTpwGJ29UvcGN798YjeFembESq9bK69Wv84XcM/h2zS4sFR/AKbfSvuhyfr7mdt6vex8AlaTityf+lhOyTxi7zy4YP7a/oNQpGuDIgJIv4zSMvNhajUtDyiDJ//sJ66zovB0xzoxdb6dlFCszAPOy7Pzl40oCoUg0b00wMt7f3cp3ntnA908t5b439nDj6aXc9PyW6Li4KMfBwiwHf/m4ClAKlz561dKZ6cg0bYMnz1ceHAEsKbDyu+Bth23/7pds1lng6v/Q5MjkRx/8iA0tGwA4p+Acuv3dfFj/IaCMk/efcD8n5ZwEKMnUf9r6p6iaWaGjkNNzT+ePm/8YNeGi4ovY27mXhSkLuW7hdeMtYzsteGdXM998agP+kCK8UJpq4Vefm8eSIa4MZg2iejblCAWV1fM3f9rfdt7vofxtZfwGxcG+6C8w98LDSoR/Wvc+131wU7SI5fKkBfxq5S9IdfbLOHf7u7l//f28sO+FaNsdq+7gvKLzDhvi+EHDB/zgvR8Q7AsZLkso4+dH/5yypPjQ9zx73iHPJRAMleHc7S8HkoEXgBeBlL62acvz62ujjgxAs8vP9vpubn95Z/SGDbClrptUm5L38u7uVrY3dEe37WnuiXFkAG7973Zq2oev8HFI2svhrV/Etn14b6yizkF4v3511JEBZQZwW9s2ih3FNHuaeafmnei25t5m7lh7R0wy6scNH1PsLAbg79WvUVHSl1vxzm3sat0adWQAInKEX675JW2jTOYWTACyDJ/8HmbFVzKv6akdVfJ/rUszaIjZfhRFswNEAHQOmnqbRnxNAJtBS6bDyLpqUUBzNLT2+PjpS9s4Y246T62p5vjSZJ5bXxszLm6s6cJh7g9D3NPs5rOZWrh0yz/7HRkAdwt0VSn/3+/IAATc8NHv2NG2PerIAOTacqOODCjj5B1r74iGVVZ0VcTIMp+acyqPbnk0xoR/7/03x2Ydy992/I2K7gqOdOo7PfzhnfKoIwOwu9k9qCDFtKZjL7x9a2xbT0O/IwPKWP7qD5TCx4egq6eBX294MOrIAHzatpmdbTti9tvXuS/GkQH49ae/pq7n0OdvcDfwx01/jDoyADs6drCzY+chjhIIRs+QnRlZljtkWb5BluVFfa8bZFmetneuSERm2wCnZD9uf4jq9vgEYn8oEg09HShDOvD/+/EEwvSMtSqKr1spzhbX3nXYQytcVXFt9e56UkxK/Zt9nfui7Z6QZ1ClkYGDU7fc95AaCQ+qPtLsaR6RXKNggqn9VJGUzYqPFG1wN5BkHHnNhSqXluRDrczoLWgOkGd2GhyjlmcGJQH43V1Conk0ePxhGrt9pFoN1HZ6SbMbqO2IV4nyB8MMXIip7Zyhv/vGTfFt3m7FqTmQ1p10HjCGhgYZu1s8LXhCyvflCsQ+gMvIMQ+c+9v2j8Pdvvh715GGyxeiZpD+1uya+FII48pg9/7wIBLSnvbDKpd5Ar3U9sY7JJ2B2P7UHRjk2SjoPqxymTvgpr6nPq5dqJQJxpvDOjOSJD3Q9+9/JUn6z4GvcbdwnFCpJC5aHL9cmuU0ccHCeHUek06NLCtJhwUDimbmJpowaGO/xllpVjLGugq5I0eJlR2IwQGOvMMeenzGqri2ZanL2Nq2FYCTc/tVrFJMKVEhgP2oJXU0ttuoMZId7BtIrWnk2QtQSbGf/8TsE0k2jXxWXzBBrPkjlJ4JB/z9QpEQrd5WEkdRMLP2MGFmIb0VnSd29c6pd9LiGeThcJgsyHLwzq7RO0VHMik2A6fOTmVNRTsnzUqJ/nsgZr2GyIC0yxmb+L9gkCCEhFxIGKQC+sIrKHDEVl7XqXVx4+RxmceRYlS+0yxLFlZtf5HRbn93NDl6PzadjUA4gEljiuY5HsnkO43R5P+BlGVM2XyikeHIBesB+SRaM6gOyBLIO0bJpT0EydZMzso6Ma694ABBiRxbTlzea1lCWZyy3oFkWbM4OefkuPYC+yC/E4FgDBnKysyTff/eA9w7yGvacuKsFL59YiF6jQqjVs0PTy9lfradrx9XwHkLMlBJkGjWcctZs3l1ayPpdgP3X7qQRdmO6DkKky38+epl5CUpsbfL8xK4/9KFJJjHWOLRlg6X/R0yFivvk8vgin9CQt5hD12atpzvz/sGRo0RrUrL5aWX4fK7CEaCfHfxd1me1p8sbdaauXnFzazqc4DSzGn8ePmPeXHfi+Tb8vjDgu+St/ZxSF8Ilz1NSco8HjjhgegqzwlZJ/C9Jd8T1amnOu4WJeZ6EInZJk8TTr0DzQhUagAiMjS6NSQfMszMFhdmZjfY6fJ3EpZHt6pZmGyh3R2gtmOGrhJMAEadmh+fOYtEi445GTbSbAaynEZOK0uNjov3fn4+4XAEjUrCZtRwxwVzWZTjmGzTx4eik/vUywxKUvUJN0NiKdR+Bqu+q1RbV2th+bUw9yJmJ87mruPuIsGQgEpS0eHt4J7j7ok6KMdnHc8Plv4AY1+CdrYtm9+f/Puoatm+rn386phfUdYnsV9gL+CbC77JuqZ1/OHkP5Brz52Ur2EqYTBouWBhBucvyECtknCYtPz0nDLmZhxcFGdaYstQ7v3pC5X3KXMg/3i4/Bkl3xEUWf2z7gW99aCnAdDqTHx97lc4PfMEJCQSDYncfdQvmJ2yKGa/Qnshfzj5D2RZlPMvT13O7cfcjk1/6O/WpDVxSeklnJp7KipJhVPv5JYVtzA/ef6IPrpAMFSGo2Z2ErBGluVJf0IYS9WocESmocuLJEGmw4gkSYTCEfa29NDs8qPXqMhyGun2hjBqVbT1Bqhp95CXaKKlJ0CTy0eG3UBxigW1WkWyRYdlLBXMDsTbpSwnG53D0o+v6q5iW+sWwnKY2QllmHUWkCDDnKF8Zr+HXc3rKe+pwqoxMytxDiGdESkSodJVRY27liRDEvPshWSiBlMiGB3R87d6WvGGvCSbkmeaIzMz1cw+uBdq18LK6+M2rW1ay/u173Ne4cikZpt71dzwdhI3H3Xwwn6qkI+MDf9g71l3xLQ/uvVRfrTsR6QcMCs9XB55v5wTZ6Vw9cq8UZ1nCjMhqlHeQJhmlw+tSqLLG8SsVxMOQ4dXUXBUSxJZTiNtvX4WZjvJSZgGCdXDpWWnIgCgUkNCIRgTwJ4JnRVQv0EJAUoqVZycngYltyaljEZrMlvattAb7KXYUczsxNl0+jvp8nbR0NtAm7eNJGMSakmNN+TFHXSTYckgxZhCojERm96Gy++i09+JQW3AF/Zh09lGJcwxAYxrv9xc28WORheyDLPTrczLsFPR5qbbG0StVqFVw54mN8WpVsrSbWjUM0QExNsNDRsUpTJ7FmQuBU8bNGxUngcSiyBrWcw9+WAEI0F2tm1nb+derDor85MXkmaJX+EC6PB20BPsIcmYhFlrpt5dz872nXhCHoocRcxKmBW34hiOhNnTsYdWbytatZZ8ez5WnZVdHbuoddWSZExiduJsEo0TXotqBiqTCPYzHDWzLwEPS5LUDnzY91oty/K0LkWsVklkH3AD/ri8nS//9TPCffETczNtPPbFJfxvWzO3vbyDzy/OYkt9F09+0p/4/6WVeVx/UtH4OjKgDFZDGLAGsq9zH19946u0+xTxOZPGxJ9O/xNzk+ZG91lT9x7f+uhmIrKSTFnmKOH+Vb/iP3Xv8IcBijpn5p3JDxffQPIBNoiwsmlEJALr/wqrbhh0c11P/YgKofUff+gQMxhYa8ZDRNv/+3PqnTR7WkbtzCzMdvD69qaZ7MxMCEadmry+sNr9Qa5v7mjiur9viIoB5CeZ+c7JRVz5+Bqe+MoK8pNmkMpWw0Z44lxFGhfAnAxX/QfadsPfzlckmQF0Zjj1NnjlB8phx1zP9zy72dG5C1BCdf9w8h+YlTCL3278bVQ05ZjMY7DpbLxa+Wr0kjctvYkrZl8BgE1vO+xs+JHCZ5UdfP3JdVHRHptBwx++sJiv/PWzaF/MSzRx2pw0fvj8Fv70pWWcWBofGjntCAVg7UPw3q/72875Lex4CSr6xXs4+z5Yds1hT/dJwydc/8710Xv9vKR53Hf8fYM6NAnGBBKMyr2gtqeW69+5nvKucgA0koaHT32YFemxYemfNn3KN9/6JuG+3NoSZwnfWvgtbni3/35zTsE53Lz8ZtG3BWPGcAQArpJluQS4CKgD/gDMuCzbbk+A21/eEXVkALbVu9jb0stdryk3puNKk3hqTayC2ROfVLG7qWdCbR0q79W9F3VkQEnyf2bXM9HBrKurit9sfij6HmBH1x4qvM08uvWxmHP9r+p/7OraOzGGC8aH6o9ArYGk+IrOALU9NaNSMqt3q0k8RIgZAJJEyGhHe4AIgGOMRADmZznYWNNFjy9eoEMwcuo6Pfz+nX0xqmaVbb10eoI0ufysrZjWav2xRCLw2eP9jgxAbytUvAt7Xu93ZEBJvC5/F9KVQsM77ClRRwYgLIe5e93d1LpqY9QfFyQviHFkAB7Y8AC1PbXj85mmMa9tb4xRH3X5Qry0qYFVRf1CJVXtHgxaFSpJ4rb/bqejd5BE+elG+154/67YNndTrCMD8M7t0ByrSnYgnb5O7vr0rph7/da2rezoOPRxAFtbt0YdGYCQHOK3G35L7wDRAZffxX3r7os6MgB7OvewtzP2meHlipfZ17UPgWCsGLIzI0nSlZIkPQI8D5wC/B44drwMmyw8gTANXfGqPb2BUFQC0hsIc2B0nixD9xR9cKp1xd8YK7orogo7vqCHJm/8A6Q35I1RMduPyz/DpC+PNDb9HQpOOGhl6Hp3PcmjlGU+rDPD/ryZWGfGrnPQ5B6dPDMoKwqz0q18sEdIhI8lvf4QDd3xalFdvQFsBg2Ng2ybtsghaN0d3+5ugY7K+HZXvbJyI0m45Pj+3+huxB/2x7QNpnIWiASiKmeCfqrb4+/LtR0ecg+IrHD7Qug1Khq6fHiDhx+Hpjz+HhjgfACDK5t6Ow+rZuYL+QaVvz9QTW8wBlM5bXA34An391Vf2EdDb0O8aSEvGik2EKgnMDUnfwXTk+EElD4ALAQeA74jy/JvZFn+ZDyMmkySrXouWRarFCNJkOUwMjtdWRJVqSRSrPqYfdJsBvISp2a8+Ik58eolFxVfhE6tiBQk2fM4P+fUmO0SEmnGpDgVEovWQr41Z/yMFYwvQS/segXyTxh0sz/sp9vfjdPgGPElansOXWNmPyG9BV1v7Ex+gsFJk2f0zgz0h5oJxo7CJBPnzI9XNCpMttDmDrA8fwapmal1sPjq+PbsZYoK4IEUnKjIncsyhWiRDgjRv6DoApJNyTEqUWE5HFf8ssRZQob50KpURyKnz4kPPT1jbhovbY6VAk6y6OkNhLl4SVbcfXpa4sxT1EwHojMr/XMgeccetmBmkjEpLhdSQqLQXnhYM2Ynzo5ru7D4QpIM/StjiYZELii6IG6/FFNKjNS4UWMk1yZELARjx3DCzJKArwAG4A5Jkj6VJOnJwxw27dCoVXxlVT5XrshBp1aS/x+5cgmlaVYeuHQBJ5Umc89ru7nronksynGgkmBxroP7Ll3A7PSpKQm5JHUJPz3qpzj0DkwaE9cvup7js46PbtfoTFxdfAmfzz8bg9pAhjmD3668nVJ7Ebce/TNWpK1AJamYnTCLe4+7m7LUhZP3YQSjY8/rkFR0UPGIBncjicbEuKTO4dDgHpozE9Zb0R7gzCjyzGMjq7w0N4H3drcQDEcOv7NgSGg0Gs5fkMEVy7PRa1Sk2QzcceFc1la2c/+lC1g4QOlxRlByGpz8MzDYFdGTsx+A3GMg52glb8GUCDoLnPgTyFmpPGRqzZQFIzxw/D1kmDMwqo1cWnIpXyz7Ivn2fB465SGKHcWoJTX1PfXcvup2ZifMRiWpODbzWO489k4co5hMmKmsKkzkh6eVYDdqseo13HByMctynZw9LwOTTk2aTc+PzyjljR1NXLE8h28cV4B2JggAWNPg0r9D3nGgtUD2UVBwMlzyNyVUWKWG0rOUnC3zoWuDadVavjLvK1xcfDFmjZksSxYPnvQgsxJnHdaMOYlzuPf4e0k1paJT6bhy9pV8vuTzSANW+NUqNVfMuoIrSq/AqDaSbk7n/hPuZ0XaCk7IOkF5jnDO5uFTHibPnjfab0YgiDIcNTMbsAo4HiW8LAlF3WyQqavoMQbgA0CPIjbwvCzLPz9gHwn4LXAW4AG+JMvyhgPPNZCxVI3a2ehia303KgnmZTooTVOkDYPhCC0uHwatmkSLMrvT1O1lc2031R29pFoNFCab8YdljFqJmg4vLT1+CpMtzMu0YzMeQgigeYeSWIoMGYsgdQ4E/VDzETRvR7amEzE48DaXIxsTkTMXY0sroNvVwLa2LdS460i1ZGLW26noqSbTlIYmEqHaVUmhLY+5KYswmeKVQlo8LciyTE1PDTvbd6KW1MxylrKktZqgycE2g55d3ZXYdDYyrFns6dpHojGR2c4SPAE3dp2dlL5aNy2eFra3bafJ00SJo4Q2Xxtdvi6KncWUJZZh0BgG/eiyLLOrYxc72ndg09mw6+1Uu6qx6CzMTZxLtm3K1U+YWWpmz3wBnPlQcvqgm1fXr2Zt01rOzj97RKcPhOFzL6Zz26p2DvccYeysxtS2l7qjr422heUwD2x4gIdOeQi1NBx9ksH52UvbuPW8OawsGnkB0CnKuKlG9fpDbK3vYm+zm2SrnnmZdhq7fdR09GLSaajr9GI1aChJsaLVSPR4Q4QiMtkJRvKSLCP6MJNOOARNm6FtryKz3FWtzHxnLFbyy5q2KgqS7mYllKynGTRaSC6j0mBke3cFvcFe0kypuLwd5Ovt2NGwJdRFZ6CHNHMaXb4uUs2pLExeSFgO09TbRG+wF5ffRYIxAYvOQoY5g3ZvO1vbt1LfU0+6JR27zk6ECEWOImpcNVS6KkkzpTEnaU5UEn8gwUiQne072d2xWxlXk+ZOZF2acVUz29HQhcsXAlnCatSQn2BkfU03e1vcGLUqZqXbcJq11Hf6KG91k2YzMD/LQZp98PvRpCPL0LQFGjaDpq+/ObKhYRM0b1eck8zFIEtQ/xl0ViqrNBlLlfAzdyOEg4oTnTyLajnAtvZteIIeyhLLmJUwC3XLDuV8Kg1kLKLdmsy2tm2Ud5Vj1VkpdZYyPyVeOrnF08K2tm00e5opsBcwJ3EOVa4q2rxtROQIVq2VOYlzqHPXRXNu5iTOIcuaxaaWTZR3lWPSmpidMJvZibPxhrx0+jqx6CzYdJOS+C/UzGYww3laWD3g9XtZluPLyMbjB06SZdktSZIWWC1J0v9kWV4zYJ8zgeK+1wrgob5/x53NtV1c9uiaaFytzaDh6a8dxdxMO1q1ikxnf9iYPxDiyTXV/OHd/gS4k0qTOWt+Oi9ubGD1vv7Y/JvPnMVXjy1ArRrkt9O4Gf56DuzPO9GZ4epXoLsOnrsKDHako7+N+p3b2f9YEExdQPfFf+Uv5c/wp93/iJ7q1NxT6Qn0sKZxDZeUXsLmls3s7tzNTxd/j0vmfSXu0immFD6q/4jvvfc9vCEl/tims3H/sb+ht7eZG97+BTJ9qjC2PI7NOpZfrv0lS1KXcPdxd0cVyzp9ndy+5nbeq32Pz5d8nn/v/Te7OvqTXX99zK85p/CcQb/zTa2buOb1a5CQuGHxDdz4wY3RZMRsazYPn/IwOTYRxjYuBDxQ8R5cOEgBwD5qe+pINIz8wb+pV0OCIXxYRwYgpLfHrcyoJTU2nZ1WTxtp5sHlQofD4hwnr29vmonOzLjx8uYGfvRvpaCuVa/h+6eVcNdru/j+qaX8+n9bovmCBUkmTpmdyqMfKvkjaXY9T11zFEUp09ChqV4Nf79Ymd1+6Vv9OQnWdFjyJWWcfvWHcNwP4c2fKVXZgfLTb+WamhejAitalZbvLfker7VW8EHdB1S6lO9GQuJ7S77Hb97/DT9Z8RNWpK7gnnX3sLZpbdSE6xdez8XFF/Po1kd5Yd8L0fbPFX8Op97J5pbNPLr10Wj7Sdkn8YuVv4iTal7buJZvvf2t6Liaa83loVMemooTRcNibUU7X31iHT1+5W+TaNbyywvm8e1/bIwK9izOcXDWvHR++crO6HHHFydx36ULo5OSU4ratYpaXrhPqMCcBBc8rPTF/cy/TFEwXftwf9uCK0BnUgQq+qj8wjN8fdN90TBdjaThkRPuZ/lTX4CAW9kp91g+Ovbr3PLRLdHj8u353LHqDuYlz4u2dfo6ufXjW/mg/oNo2/eXfJ/3at5jQ6sy16ySVNx93N38eu2vafMpzz/p5nS+v+T73PTBTdFniSxrFvcdfx+zE2djtMyosg2CKcRwwszmy7J8nSzLTw/myEiS9LtBjpFlWe77FaHtex24FHQ+8Le+fdcADkmSDl1mdoz4x6c1MQmCLl+IV7c2DrrvzqYeHvsgNunznd2tGLXqGEcG4L4391DdfpBEvK3P9zsyoCTs1X4KH9ytJPnN+Rx8+mjMIdrmzTS6q/nLnn/GtL9Z/SaLU5Qimv/a8y9OzFZyY+7b+ij1bbs4kHA4zIv7Xow6MqAk/n3Q+Al/rnghOvgAVLmqohWp1zevZ0/nnui28q5y3qt9D1AcpIGODMDd6+6muTc+VCgYDvKXbX8hGAlyfPbxvFT+UoyqSm1PLVvatsQdJxgjyt9WwhIMBw+HrO2pIdk08gf/erd6SCFmACGDBa3PFZfc6jQ4aR6jvJkluU5e397MUFegj3TqOj3c8Wr/g+BZ89N57IMKTitL45+f1cQIn1S0eTDr++fDmrr9rK2chmpm/h54+zYlfGzHf2KTq3salQfNll3KA2VHedSRQW9jDb4YpchgJMj7te+TZEyKOjIAMjLP73mek3NO5ncbf0eLtyXGkQF4bOtj7O7aHePIALyw9wWWpS3jiR1PxLS/U/tOjLoUKOP5fevuixlXq3uq2da+bSTfzJTi1a2NUUcG4ItH5/GH9/bFKI8uy0vgvjf3xBz3/t42dk1FpdFQAD56sN+RAaVGUcW7yirgfhLy4NNHYo/d/LSyQrgfjYH1HTti8g1Dcog/bnscb85R0bZ9p/2UP2z6Q8ypKrsr2XuAQunezr0xjgzAHzf9kUWp/cU1I3KER7Y8EpURB7h81uU8tPmhmGeJup46trdvP+jXIBCMBWMZULpqsEZJktSSJG0CWoA3ZVlee8AumcBAua06+ksaDDzP1yVJWidJ0rrW1tErQkciMjWDVAg/WNVwTyBMYJDYe08g/sHNH4ocXEWlsyq+LeiB/Q//RodSDOsAvCFvzA1qP/vbBkoh9gZ78YXjVYWCcpAWT0tce1NvE+FIvL0HnnOw/w92XJe/C3/EH9cejARpcCtKJw69g3Zv/IPPdFNKG+t+Oa7s/K9SWO0QNLgbRqVk1tCjIdE4tBwVWaUhojWi8XbFtDv1DpoGcYZHQpbTiEqC7Q3Tq1+NBSPpm/5QRAnj6cNp0tLmDuA062h1x/+mA2GZgQvQbT3x+0x5gj7FaTElQG/8+IjfBYEe5QGzd8D3qLfQEozvVx2+jkFVINt97Tj0Djp8HTFj6358Yd+gKmYyMoFwIE4JDWLHYgB/yE+rN/5vPZXG1ZGOmQcq5SWYdbT1xEov6zSqQe/Jvf5B1L8mm0gQumvi23vbQG8dsF+YOPlUgIF9SGukI+SO26XZ247f0j85FVBrY5zv/XiCsf1usH7oC/tixCsA2r1Kn96PQ+8Y9PzuQLxtAsFYMu7ZcbIsh2VZXghkAcslSZp7wC6DxTHG/XJlWX5UluWlsiwvTU4efYFGlUrismXx4UznLYzzowAoSDIzLzM2ztNu1JJm02MzxEbrLc11kuU8iLLZ/Evj21JmKUvJAOXvwKxzDzBWQ4Y5g3xrXkxzkjEJd1AZJIocRdS7FVWX49KONlXWBAABAABJREFUImOQ5DqDxsAZ+WfEtZ+QfTyLHaWxl5RUUbUzvVofo2qWZ8vDolVCSTQqTdwAd3b+2aSZ4kOETFoTl85SPv9H9R9xcu7JMdslJMoSy+KOm8qMdb8cNyJh2PsGZB88gtMdcOMP+7GOIp65rkcJMxsqQUN8qJnD4KSxd/AV0uEiSRKLc528cQSqmo2kb2bYjZxe1q8a9f6eVs6cl8YHe1o5c27sgrlKArNOzYCJcVYUTHhV79FjSYal10Dl+1AyiEqZLUvJa2zZETsZ4GrgaFN86NaxWceiUWniRDROzT2Vj+o/4qz8s7DpbHEqZouSF5FrzY0Lr8y0KPek+UmxeQ0WrYU8W15MW5IxiUtKLolpk5CYlXD4BO+JYqRj5hlzY7+Xf62v48LFsffrrfXdMXVnAEw6NYXJUzD0UWeGpV+Nb89dCV0DnJzeNkg4QG3Mmq6EDe/H28liW1HcqS4rPA/Hvv56NDl73uWsgrNi9lFLavLtsSpoebY8TJrYZ5hlqcvY1RkbhXFu4bn8t/y/0ff/Lf8v5+bHPr+oJBXFzuL4zykQjCETJvUhy3IX8B5w4NN0HTDwjpAFxAuVjwPHlSRx+/lzSLXpybAbuPvi+aw4iLRomsPI7efP5Yw5aVj0GpbnObn/0gXc8/oefnHuHFbkJ2DVa7hwUSZ3XjQf+8EEAPKPhfN+D7ZMZUA6535FnWTB5XD0t6GrGjl9PvLSr4I9h1DGEnoveY7k1Hncu/I2Tsk4FrPWzKr0lXx30Q28Wvkqp+acyhdmXcEHdR/wubwzuWnxDRgPooZzdNrR3LDoBpKNyaSZ0/jxsh+zuKuNKxIW8JWSS7HpbJQ4irn16F/wZuWbzE+azyOnPkKRs3+gzLXn8sipj7AsdRkvl7/ML47+BWWJZVi1Vi6fdTnfXPDNqCN0ICdmn8iNS2/EH/Zj0Vr48twvY9fbKXQU8ruTfsecxDnD+hsKhkjdOjAmgOXgFbHr3HWkmFJGlSVZ5x5ajZn9hAxWdAesRCboE2gaI2cGYEmOk9d3jM1Kz0zHqFPz47Nmc8XyHGwGDUatmquOyuWU2SnYDBq+sCIHu1FLcYqF31++CLNeTYJZR36SiYevXDx91cwWXgHLvqaskh/1LUUON3k2fO5xsGZC6x445geKEMAJN4M9C6zpLNAnc8+xd5FlzSLRkMjVZVfj8rvQBzw8uOJnFDuKsOlsXFxyMU69k6VpS7mq7CqKnEXcf8L9LEhegEVr4fTc07lp+U0UOYu469i7WJmxUhnnM1Zx8/KbeXnfy9y07CbOLTgXi9bCstRlPHLqI+TaY+VtJUni8yWf5+vzvo5db6fIUcTvT/79tJskGoxVRYn8/NwyMuwGUm16zpqXzplzU/nasQU4TVoKksycvyCDn549m0uXZmHVa1ia5+TJa5ZTOFXzuGadBafdoYzLzjy46E+QeyysuBZS5ijPBnMvggsfhuJTlRWb/BPg4r8oUuAZi5Ww4XmXMDexjAdOeIBcay5OvZPrF17PmXlnwrE3giUV7NlY7Bl8vuhiLim9BJvORrGjmN8c9xsWJS2KMSvPnsejpz7K4pTFWLQWzi88nx8v/zFn5J1Bvi0fh97BVWVXcUbeGZxbeC6pplRSTamcXXA25xedz5Wzr8Sut1NgL+CuY+9iceriyfh2BUcQQ1YzO+yJJGmjLMuLDmhLBoKyLHdJkmQE3gDukmX55QH7nA18G0XNbAXwoCzLyw91rbFSjZJlmZ1NLmo7PKiQyEkwUZp+6FnpXp9S6dpp0mLUaej2BnGYtIQjMj2+EAlmLTqN+vAXd7cCcv/DZSigFGjzdoLGgOzvRm7YBNZ0VHmrovrxfn8PXZ4WbJIGOipxBXpw6GwEDTZ6g70kaExoW3aAt4OK3BVscNfQE3SzyFHCnPZapUhh0clUaLVIQL4/AB17QaUlkjKLNiIYtCaMpkQ6vB2YtWYsusFvBL3BXtwBNwmGBCVEIughEAqwrmUdnb5OFqYsZG7S3EEdm1ZvKxpJg0PvoM3bhk6tw66fktLWM0PN7K3blJCGwepm9PFmzVvsbN/JabmnHnSfw3Hly6l8ZV73kEPN7HUbCOtMtJb1C0Z0B1w8vfNpHjjxgRHbMZBIROa6pzfwyneOOfiK6fRjXFWjguEI7W4/Fr0Gi0EZ35q6vfT4A3S4Q6glSLMbyU0y0+LyoVWrcJoHn8CYVHzdUPeZoubkzIfs5Ypa1GDIsqJW1lGhKElZUxUnRq1TVjS1xj6VMw3oncr+rbtBDtKVezRBSyo6tY5AJECypIOQF5fWiC/iR5Il3CE3meZMdJr+76nD10Grp5XeYC/rmtcxK2EW85Pno0JFm7eNBEMC/rAfm96GUWMkGA7S4evAorMgyzJb27ayrW0b6ZZ0FiUvItOa2fdRZFq9rejV+okeV8e1XwLUdvQSkSE3UVnZCofD7GvtRQJ2NfdQ3+nl6IJEkiw6HGYdFv0hlEWnCj3NitqYORHaq6B5s9JnLWmQsVC5/3dWKXXCtAZw5PbncgV6wZoCqfPAYKPL10UwEowK9ijnbwGVCsxJuPwuGnsa8ct+NJIGDRpKkkoGNWv/PT7RkIhGrUSg1PXU4Q15KbAVoFYrzzrt3nYkJBKMymRwJBKhpqcGo8ZIqjm+PtAkIdTMZjCj1z7t57eDtKUDT0iSpEZZBXpWluWXJUm6FkCW5YeBV1EcmX0o0sxfHkObDsnGmi4uf2wN/pDy4GXSqXnm60cxP8tx0GPMBi2Fhv7B0ajrd1wGJsMeFssBy+sV78I/LlXqFiz7GtJ7v+7/5SXPgi88D45s9HorqZEw/Pc7sOMl9muD6BddiSWxGNb/FTorqTjlFr6y+kfR+FUJiYcWfIdVb/0M3voZBVe/DCEfPHlhNAFbZUok5UuvgFMJKTvcIGTWmqOhElq1lg5vB19946sxSYgPnvRgVJhgIAPzMmIGXcH4sPd1WPiFQ+5S66olyTjyMKFAGLr8KhyGodd1CRptGLpjF2KtOgvekBdvyItRM3r1G5VKYlGOg7d2NPOlVYcuKidQ0KpVpNn7v3u1SmJbvYtvPLU+2pblNPLUNSvISzIPdorJJxKB9X+DN/+vvy3naKU+x2ArlJIErbvgyc/BabfDc1/uFwMwOGDVDfD2rcp7rRFO/Cm88RMAHGotXP0yDEi2Bjs2YP/0WDLx45wKFb/b8Dver38/2vb1+V/n2vnXUuAoiNtfq9ZGx+Vndz/L7Wtuj24rSyjjwZMeJNWciiRJg8o2zwSyE2L7m1qtxqBVc/WfP6WqvT/06g9XLOLs+dOk+Kh1wL1232vwvx/1v08qhnN/D38ZIKd/5t2w5RmoXz+g7S5Y/o3BaxRZ+/vCWzVv8fOP+ytkZFmyuP+E+wetNTPwHh/d35oVt1/iAfcNlUol6sgIJpTDhplJkvRfSZL+c7DX/v1kWf7rgcfKsrxFluVFfUpoc2VZvq2v/eE+R2a/4tm3ZFkulGV5nizLEza1/fe11VFHBpRk/pe3jF14y5DxditqOrIMcy6MUzOjdRc0DlD5at0NO16K3WfT06C3KDr0GgMbtKqYRDwZmT/UvkFv8WmKLv3ah2Drv2OVpDztUPXRiD/GtvZtcdXb7193P93+7hGfUzAGuFuVWb2U+ArOA6nrqR1V8n9UlnkY818hvR1db2yYmQoVicZEmnvHLs9lUbYINRsNHb0Bfv3azpi2uk4vW+un8G+7swreuyO2reYTZdVlMAIeeO8uyFmhFJcdqGrm6+oXCQBlhrxpMyT0ORzhIHzyR6VezTAo7yqPcWQA/rz1z9T0DJIYPoBGdyP3r78/pm1Hxw52d+4e1vVnCtvrXTGODMAdr+ykfRDRiilN42Z4/67Ytra90L4vts3bEevIAPw/e+cdH1WV/uHnTEvvvRcSIEDovYkIimLvBeuuLOpa1rq6/lZ31y261tW1YcG1otgrWOhFei8BUiAJ6b3OTHJ+f9xkkslMGklI4Tx+5kPue8+590xyPfe+97zv9/35b/a5Nk44Xnacl3e+bGfLrMjkQNGBVnooFP2DjiwlPN3jo+gF6usluWWOil/ObD1OXa02OQGYvOylmxtprjbSQnkE0JwSa4Oyi95EuRPlmyJzGRa3hjfTZTng7+Std3VxJwffREtlHYBScynmOrOT1opTRtpqCBuphTG0Qj2S7MoTXVoly+6ELHMjVjcfDFVFaJofTV6Qv6s/JypPEOvTPSspIyN9eG3NUcprLHi59oOwkz6Gua6O4kpHha6qvqgS1UhdreZ0tMSZDTR1qap8Ldm63MlLrdpyMHlCVcNcXV2sFdhspDy7QWGq4yv0zlQnrdLa7pxprjM7V5yy9sL9qw/gTD20pNqC2drxVeI+QZ0Fapzc/1v+XZ2o4WGptJd5doK53kyZ2fH4p+t1oxg4tLsyI6Vc3dbnVAyyJ9DpBNdNjnGwXzzGuZpZj+IZrCX8ARz5UVudaY7Bxf6tekAieLVQCwsbBa7eoDdCbRmjTX6IFiGiCyJm4Zvyo7Yx8VZHZSshIHb6SX+NJP8k9MI+X+jaodeqMLLe5sjPWjx1GxRU5+NqcMFVf/KVsrMrDPh1IsQMoF5vQupN6Kvtb7CaPHP3rcy4GvUkhXmzOqWPy2f3UUK8XLl5aqydzaATJIX3SiXvjuEbDUPm29tcvCFwiPP2rj4w6TbIWA+JZzvuD06yf/MdPQVy9zRtT/ydNld3glifWPxd7UVnxgaPJdLTMZSnOaEeoVwQb68a5WZwY5DvoFZ6DGwGh3phbLEkfOPUGEK8T34+6xX84yHZXo0OgysEtFAqM3pojnVzhl2iCVO0QZRnFBcPutj+8DqDncCPQtEf6fArJCFEIvBPYBhgmyGklI6Bvf2EaYMCeOaKUby08ggGveDusxKZEOtczazHGXkVCB2kroaI8ZqCTtoqcA+EGfdp0qCN+EZqOTTrXoCiIxA6UnNM0tZq1YN3fMCI1F95ecpfeTv1K6qs1ZwXdSbnlVdC2GgYdhEMOkt7E1lnho3/1WLCZz8KEeNO+iskBSTx6pxXeXHni+RX5XP1kKu5YNAF7XdU9BxSQuoqOOv/2myWWZ5FkFvXYuyzyg0EdEKWuRGLmy+mynyq3ZoSlQPcAsksP95Gr84zKtKHH/fncn5/iaPvQwghuHpiNEaDjvc3ZRDu68a9cwczPLxPinZomDzg7Cc0lah9n0LoKJj1EAS28cA/7CIQei2E54w/wu6lWn7MjHubHiqFDsbdpKkDRkzQwtEm3w6D5nR6iBGeEbw651X+t+9/lJnLiPCM4Jqka/BqXmfECS4GFxaNWkSAWwDfpH5Dgm8Ct4+6/bR1ZoaHefPuLZN45scUMouruHZiNJeNi0Sn62c53+7+MP4W7X58fKPmYE++XVstHHOD5jwHDoXB87QXj2uf1VYEY2fC+Ju1a7UNTAYTVw65EjejG7+e+BVPgyc3DL+BMcFj2uynUPR1OiMA8DbwGPAccCZaon4/myns8XYzcdm4SOYkBSOEwLs1OeVTQLnJg62RI/hVX4mfi2TSsHmMFlAcOoKd1iK2bX2GQb6DmBA6QUvAc/WFhLMgJxjCR4EwgIsnaV6B/Dr+UgpqihjvGcqMyJmU1pYS5T+YbwzHyHedwuSgGMYf+AaXqnxN7nHE5WAwNRXqqi6B479C+lrt5h07EwLa91kNOgOTwyeTHJSMpc5CTmUO36R+Q5WliinhU0gOTMaoVyE+p5TiNM1h9W77jV1medeS/0GTZR4b3PlwBaurj+bMBDa9HfR39WdLzuYujaclY6L9+L8v9lJXL9H3t4ecPkCojyt3nJnA1ROicDXqOyd40lsExGsOzfQ/aDmFLR/2zFWa2lnOHvAOhxM7NQWpCb/V+o69HnRGrdr6iV2ag4PQ3oCbK2D4pRwKG8rGwj2U7n+ToQFJ5FTmMiIwGSOCX3O3kFedz6TQCYwNHI2/p6Ooil7oSQ5K5kjJEYYFDHNY3W6kuLqY7fnb2ZG7g0S/RMaHjOeesfdw47AbcTO6OYhl1Fpr2VOwhw3ZG/B18WVy+GQG+zlXrerv6HSCyYMCeCdqAtXmOgI8O7dC1mvUWSBru1ZfzuSuyS17hmpCEgLwidLu9XoDDDpTc9AjxoKLF8dFPZtHnkt62THGB49mtNEFn9x9mphQVTEMmq29GDXa/y7CPcOZFDaJellPqHsoUV5RlNaUsj1vO7vydzHEfwjjQsZRZi5ja85W0krTGB08mnHB46iyVrHpxCYKawqZEjaFEQEjOFp6lI0nNgIwNXwqwwOGI4T9/FpUXcSO/B3syN1Bgm8CE8Im2OonKRTdQWfuRm5Syp+FEEJKmQE8LoRYi+bg9Gt83HtfUnR15moeXvewbft9Fz9emvgo67M38vK2ZTZ7cmAyL0z/F0Hf3KuFpNl2XMHx6PEs3PwEOdW53D7qdu5fc79d8v294+7lgwMf8O7+d/nP9H8x85u7tGTDm79rWpGREra/a68AFJQECz4Fn45NPh5GDw6WH+Sm5TfZ8mhe2/0ar899ncnhk9vprehW0tZo+TKi7Yf3jPKMLt9cTlToCYzp/MqM1dUbU4V95XV/Vz8Kqguok3WtPtx1lkBPF/w8TOw8Xsy4mF5agR0A9JsHxUZ0Okf1yEYOr4AvFmm1Y5Y1E9J094ebvtcKGoP2cmfJfO3hE2DuX2HVvzh01VvcuP4h2zwnENw//n7WZ6/niyNfkF+thTV+dGgpj03+Py4fYh9ClFmeyd82/Y2d+TsB+CTlE64cfCX3jr/XTkXKUm/hfwf+xxt73rDZxgSN4bkzn3NQkmpk44mN3PnLnbZtHxcflsxbQoLvwA0pcjcZcDf1Aye7kYwN8O7FTUI8/oNgwm9g+SNNbfxiYfq9moJpA7nz/809Wd+SUpoKwJKUj/jDyNu4+dePEDm7tEZrn4ZrP4HB9iGTPx37iT+t+5Nte1bELEI9Q/no0Ec225SwKST6JfK//f8D4OOUj3lyxpP8a/O/KK7V8mrf2PMGL81+iXtW3YO1QSzj1V2v8va8txkVNMp2LEudhf/t/x9v7n3TZhsbPJZnZz3b6rWrUHSWzhTNrBFC6IDDQojfCyEuAQam9uMpJq8qj8V7FtvZimuL2V2dw7vHl9vZ9xTs4UjRQXtHBmDvMg64e5NTnYur3pWauhoHFbFvU79leuR06mQdS1O/onbMAi2xcN/nTY1KjsGqf9gfO/8A5O7t1HfakL3BThBAInljzxvUOhEmUPQgqau14mvtoIWZnXxuk6Ueimr0nZJltvV19cVUbu/MGHVGvEze5FfltdLr5BgV6cNP+7v3mIp+SmUh/PQYJJ4Duz6031dVpDkwjWx7p8mR8QqFojTwDGZDySGHee7nYz/jZfKyOTKNvL7nDbJKUu1sKcUpNkemkWWHl3G4+LCdLbM8kyV7l9jZduTv4EhJC5WrBirMFby04yU7W2ltKTtydzhtr+gFrLWw/nl7RdHBZ8Pqp+zbFac7CFKk1FfZHJlGXtn3NplDWtQIW/VPqK2wbRZUFzio4A0NHMrSQ0vtbBtPbMTT2JSTYxAGjpYctTkyAIm+iXx19CubIwOa0/310a/tjnW8/Djv7HvHzrY9b3ur165CcTJ0xpm5B3AH7gLGAdcDrVfgU3SY1pRpqutqHJL4G9s7ICVmqU0qep0eS72j8lCltRJ3g1Y0sNxSQX2jEk9VMwWzOqujcgo0KaV1kApzhYOtzFxGXX3n39wrThIpIWOdllPVBjV1tZTUFDskIneG3Eo9fi51GDozozRgddPCzFoS6BZAdkW2kx4nz5hoP346oCSaFWi5LuYKLfTM7KjEaGdrVDADMLprylEu3lQ4mbcrLZXUOVGbqrRUYq6zn5edzeX1sh5Li3aWOgtW6agc15rqmVVanapLVltbUXJTnHpknaN6qMGtFbVS++vJjONLI3O9mbqWYdy1pXYS49Z6K1VOji9xLJ5e3+wcOqFzuP5cDa5Or7GS2hK7bWu91em12/IaVyi6QocfPaSUW6SUFUAZcJeU8lIp5aaeG9rpQ6RXJFckXmFnMwgDI7zjmRJg/yDq6+JLvF+iVgHY7iDjGYwJF70LlZZKAlwDHMJzzok5h3VZ6wC4NP583LZrS8gkX97sBJEweoH9sV19msItOsi0iGkOjtgNw27A3ThgKrD3fYpSNcXjlsp3LciuyCLALbBL4VxZFQYC3U9OBtXq6oOx2v6mC+Dn4kdWNzszCUGe5JXXklWiHupOe7xCYMqdzhUkdXqImti0Pf6mpp+LUrUXBDm7mRY42mGemx09Gx06jDr7B8srBl9BTIsQrwTfBIfiluNDxhPvY5+jGOEV4VB8OMA1wGlhTdDuEzcMv8HOphd6RgePdtpe0QsY3WHyHfa2lB9gbIt3xCYPaBGOlYALXkZ7kYgLY+YRduQX+75T7gI3X9tmsHswNwyzvy7SS9MZHzLezhbmEWbnbJjrzUR5RWEQTSF8+wv3c27cuQ5f6+KEi+22I70imRU5y84W4BpAnK8qYKzoPjqjZjYeTQTAq2G7FLhFSrmtzY6KDjEvbh4mvYkvjn6Bv4s/NyZdy7gt7xMVN41BAUPZXXyQUPdQrhxyJVEBQ+CaD7XimulrIWEuBA1l8KY3eeOMx3kz43s2ndjEv2b8i2UpyyisKeSyxMs4UXmCEPcQ7h5zJ1MLT0DQUE2lp3nVaoMLnPGAJmu6+yMITdYqXwcmdur7JAcm8+rcV3l99+uUm8u5afhNzIic0c2/NUWbZKyH0BHt5sscLz9OoFtgl051okIrmHkySJ0eq4sXpspCzM0qYWuKZpldGldLdDrBqEgfVh7MY4ETaXbFacaYBeAeADm74cw/wb7PwDMEZtwP4c0UnmKmw5XvwrpnAaE9XF7wAsmH1/LqtH/wespSyq1VzI+bT7m5nBjPaF488wU+PfI5NdYaxgSNYk7kGej09i8MEvwSeHrm03x06CP2Fe5javhULk64mAB3+4dXD6MHD4x/gES/RJanL2d00GgWDFvQZp7bOTHnYNKZeO/AewS6BXJr8q0MD2g/5FRxCkmcC5e8Dns/08oqjLtJK9Xg5gv7v9DyZSbdBn4xUHI7HF4O8WcSEz+HxVHjWXLgPQ6WpXN+5CzOj5uPS9R5sOZpqCrQVNCG2DsbOqHjiiFX4GXyYtnhZUR7RXNt0rX4u/rz5eEvOVB8gCjPKC4fcjnlteUcKz9GSnEKMyNnMjJwJIvPXsziPYvJrcrl2qHXMjF0Is/Neo439ryBTuj4bfJvGRdir4jqbnTngQkPMNh/cIevXYWiswgpHZcXnTYUYjdwh5RybcP2dOBlKWXbMSw9wPjx4+XWrVtP9Wk7T84+SPkeSo5D0vma09Ca5GZtJZzYRVFNMSadHk+faHAPIKO2iG2Fe/k1dyuJvglMCR7P8NCGm2ydVQt3MHlp8be1peAVirnOTG1dLScqTrCvcB811hqiPKPQ6XTUWGsIcA1gmHcsRoNRezvUGjVl2rK34eQVyGqsNdTJOrtk1n5Gh2Wv+tx1+emt4BEIQ85rs9m7+98FBBNCx7fZri1e2uYDQjIj8uSKrwUeXE7xoBlUhDVNJycqT/BTxs88Mf2Jkx6XM9YfKWBvVilLbpnYfuO+S6fk2PrctdnblOVoL4IOr9AeFBPP1iSZC45oyf+HvtMUzIaeB+Gjm/qZK2n61UvtRUF9PTWynuOVJ1iZuZrcqlzOjj0bk87EhuwNnKg8wfSI6cT5xLHpxCZSS1KZGTmTcaHj8HXxBTTlsVJzKYGugeh0rQdMSCkpt5TjZnBzWPlpjUpzJQa9ARf9KRFuUNdlI/mH4PCPkHdAcypipmrXVnMstZC1BfZ/qT0bDD0f/OI0afCCw+DuC+FjtdWZrO3as4R3uCbY4xeN1VxDlaUMb49mq3uWam2Vu5VnjXJzOXvy95BWmoaXyYukgCTqZB07cnewM38nSf5JjAsZR3JQMjXWGsrMZXarh7V1tVjrrHiYmu7pVZYqBAK3NqShT+ba7WaUhOUApjOyH+WNjgyAlHKdEKK8B8Y0MMg/BO/Mb4qJ3b5EewMz6irn7Q8vh2U3Y5vqXH2o/u0vvH/kMz5spjLylU8cz0/7F/FBwzS5Rn1DnQeTm/YBTHoTaaVp3PjDjXYxrfeMvYdXd71KbV0ti89ezKSwFkUzW+La9YJ4roZ+VrRsIJGxQXvb3F6z8gwmhHTtwT6zQs/o4JMXd7C4+WAqz4WwJluAayD51XnUSSt60X0KRaMifXlrfRo1ljpcjd2jlKboZ+xdBiua/b+xbYlW38PkAV8sbLJveglu/kFTBARtvxMyig5xww832HIf/V39WXpoqS1h+sujX3LH6Dt478B7lNaW8tmRz7hv3H3cOPxGhBC4GFwINrSvpyOEwNvUuXnZo5UxK3qQ4nR473IobSiyuvM9mPsETP29/Up5xjp479Km7X1fwLgb4cc/N9m8I2DmA/DNPU22QXPg8jcwuPnhbWpxj22n1szy9OX8ZeNfbNuzImfhbfLmq9SvAPgu7TtGBIzgH9P/QZxvnMM93EXv4uAYdyR8/GSuXYWio3QmXXezEOI1IcQsIcQZQoiXgVVCiLFCiLE9NcB+S/YOx+S+lU9AZYFj26piWNlCQaymlKO1eXySsszOnFaaRkqZvYqJM3bk7XBIzvs29VtmRM5AInl3/7t2KiSKAUZplpbc3E5F6HokWeVZBLufvJIZQHaFgUC3kxd3qHPzxaU8x85m0muKZnmV3as+5ulqIC7Qg42phd16XEU/ofAorLdXdKIyXwvp2fuZvd1cCelr2j3kttxtdiIuQgg75SeAZSnLmBPdVFjz5V0vk13ZvTlhij5Czt4mR6aR1f+C0mZhs5YaWPe8fZsh58Kaf9vbyrKgwn5u5OhP2spNJ8mvyufFHS/a2YYGDOXrVHsFsr2FezlaerTTx1coeovOvO4c3fBvy7oyU9HSjGd3x4AGDM6UOqw14EzNS9aBE8niOimdquJYO6AI5kzlprau1ra8W22pxomAiWKgcGwjhAxvN1+moDofF4OLQ8G9ztAoy+x3ErLMjZjd/PHIO+hgD3IL4nhFJmGe4Sd9bGeMjPThp/25nDlEqcufdtRbtbDclgjhdB7G0v6KY0v1SGfh283nX9BUnjoa5q3oZzh7UVhnbqFKJh2Vy3QG588Ozq6Tk1ADq5f1Tp8NnKmZqZediv5EZ9TMzmzjoxyZloSPhpYhVtPv1RR0WuIRqFWobo7exCCXAM6OsdeND3QLZLBP+yogY4PHYtDZ+6rnxp1rUzNbMGwBBn0/Ki6m6Bzp6zSBh3Y4XnacYHcn12QnyOmCLHMjVndfjJUF9jUXgAA3fzLLj3dpfM4YE+XHLwfz1MPk6UhAIky41d5m8oDyHBh2kb1dp4f4me0ecmzIWDulJ6PeiKvefv6/aNBFrDy+0rZ9XdJ1hHq0rTSo6KeEDNdUQJsz6TbwiWraNrrB1Dvt2xz6Hib+zt7m4g3uLQRaQkZ0WpQHNDWzW0bcYmdLLUllStgUO1uUVxSDfAd1+vgKRW/RGTWzEOAfQLiU8lwhxDBgipTyzXa6np6EJsONX8Ovr2rxs+NvgcHntN5+2MVaMv7mxVpo0OTb8AwcwsJhNxLnHcearLUM9kvk0kEXMji4fc2FYYHDePPsN3n3wLvkV+VzScIlZFZkMthvMNcPu779fBlF/yZjA0z6XfvNyjK6VCwTIKv85GWZG6nXm6g3umGsKsLi0XTjDnYLJrW0/bDKzhLp54aUkpTcCoaEtiLKoRiY6HRNKmZ7P9XCy6b8HqoKNZnmc/6pKUl5BGmKUOHtR1EPDxjOG+e8wbv736WguoB473henP0iSw8tJacqh/lx8xkZOJJyczkHiw9y8aCLmR092+GFk2KAEJgIN3wFez6FqjyInKSFkOla5OgNmq2p5OXu01Zf4qaD/yDwi4Yd70HwMJh4q+YYmf8M+SkQEK9JiXt2flVZCMGlCZfi5+rHspRlxPnEcW3StSBhqP9QNp3YRHJgMufFn0eiX+edJYWit+jMTLoETZq5MWsyBVgKKGemNaImaqoj9VZN8rgllmo4tgl2vq+9fRl9Ldz4raZQlrYali5g8ND5DDZFcEPURXjoTOgMvg6HOVpylJ8yfmJfwT7mxM5hStgUgtyDGBsylpFBI6mX9Zj0JltYg7FlYa1eotxcztacrXyT+g1hHmGcF38ewwKG9faw+j/VxVB6HPyd16BoTnpZBgldfAOXVWEg4CRlmZtjcffHpTzHzpkJcg9mdVb7OQudRQjB6Gg/fjmYq5yZgUhpFhz5WVMli56kqUQ1f5MdMEhLxk6+Ao5vhvUvaKpmo6+BkJEw4bcgdNrcnb4Odn0Aeldtf+QEh4dSndAxLmQco4JG2eZbgHHB4zDXm21J+COCRmCpt9glUKeXprPy+Eq2525nVtQspkVM65EVm2pLNTvzd/LlkS/xNHpy/qDzGRk0Ep3owpKqonX0Jk2Up6hME9Nx5rg2rkTn7dfUx+osmjT4hN9q9d70JtDpyKrIYm1QBGvNqUwJiuAMkxtRjkfrEAHuAVw++HIuHHQheqFH33AtJwclU1JTgpfRC73+5IVRysxlbMnZwrdHvyXCK4Jz485V93VFj9MZZyZQSvmxEOJhACmlVQihyrm3h07v+DamkfS18H6zYpk7/gc3fa/lO/z4f1qdg9RVsHsptsctv3i46WtbYnd2RTZ3/HwHWRVZAKzMXMlNw2/irrF3YdQZ7d789bW3gCuPr+RP65oUhT5J+YR3z32Xwf6De3FUA4DjmyE4yfnNswXHyo8xJXxKu+3aPF2ZAf8uJP83Ynbzx1SardXGacDX1YcqSyWVlgo8jJ5dPkdzRkf68sO+HG6bldB+Y0X/wVIDq5+E7e9o2ynfw66lcMPn4BVm3/bwCvjq903b25bALcshpOHhK30tvHtx0/6d72pzdLTzle2Wc6zRYMRI08sjndDZOTL51fnct/o+UopTAFiVuYqLBl3Eo5Mf7XYlyK25W7n959tt258e+ZR35r3DyKBTXl1h4FOUBu9eBBUN4iWHvoPZ/wcz7rPPYzz6MyxrFva152O4dhkMmgVG7e9fYa7gyV+fZGWmFqK4JnMNP2X8xPNnPo+vq+9JD7HR4W5OV47XyM8ZP/PnDU1qbMtSlvHuue+S4KfmWUXP0ZlXMpVCiAAa0saFEJOB0h4Z1emAtRbWvWBvq7Nok962hptwwlmahGhzilOhWaL0kZIjNkemkfcOvEd2ed9WySmpKeHlnS/b2aqsVewt3NtLIxpApK+HwCHtNis1l2Guq7XVujhZMssNBHWDM2N198e1zP661aEj2D2E4z2QNzMs3JsjeeUUVJy8pLSiD1Kcqr0Yak7+Abt5E4CKfFjVQkWytgxO7NR+rrPCJvs5ivo6TT63m0gtSbU5Mo18dfQrjpUda6XHyWGuM/PW3rfsbNZ6K6szV3freRQN5OxpcmQaWfuMViemkZoy+PU1+zZ1Fjiyws6UUZZhc2Qa2Za3jbSytO4ccbdQVF3Ef3f+185WYalgX+G+XhqR4nShM87MvcBXwCAhxHrgf8CdbXdRtIqULZRNGu11NMmMCecqJs2UR+qlk1wF6VydpC8hkU7H7vT7KDpHxrqmN8ttcKzsGKHuoV2uJJZVYSDIvRvCzDz8cSk74WAPcg8io5sf7gCMeh3JET78crB7pZ8VvUyrU1/LHdJBcEIzN2vnVNGp++YoZwIUPTF3S6TTc9XXq/m2Z3DyN5T1jnanzwD2f5PW7ol9UbxENvznzK5Q9CSdcWYGAeeiSTEvBw7TuTA1RXOMrjDtbnubTg9D5mu5MwCpK7VEv+b4RENwk0pVom8iIS3UqK4achURnhE9Mepuw8/Vj9+NtE9QdzO4kRyY3EsjGiBYqiF3PwS2r2SWXpZOkHvXpImrrYJKsw4fl64/FJndfDHWlCBaSIeGuAeTVtozbyHHRPuxfG9O+w0V/Qe/WBh5tb3Nf5Cjup9nMMx80N5m8tCUKEErSjz5dvv9QqeJtXQT8b7xxHvb57bNi51HlPfJZkQ4x0Xvwo3Db7Sz6YWeM6LO6NbzKBoIGaEJTDRn6l32amau3jBhoX0bnR4SzrYzxXrHMjV8qp1tZOBIYn1iu3HA3UOAW4DT+7rKmVH0NJ1xRv5PSvmJEMIPmAM8A7wCnNayWPWy3nkCZX29pprTFrEz4bplsOUNbWIbd4umnOMfB36x1GdtRRc5GSInwoGvIXoyJF9uNyFGeEXwypxX+Db1W3bl72J+/HxmRMywS/Kvr7Oi66AMc6vfpweYEzMHL5MXn6Z8SoRnBJckXsIQ//bDoxRtkLVde5gzth9vn1qaSpRX20U12yOzXFuV0XV1eQdA6LG4+eFSlkONX7TNHOoRyvbc7d1wAkfGRPmxZEM61eY63Ewnn/SqOMXU17Wei2hyhzP/pImv7PscYqZD8mXg7aRW0bCLwc0Ptv9Pm3fHXK/J6jYSOx0WfAZb3gSjO3Lq7yF4eNurmQ1zv7Xe2m6eYrB7MM+d+RzL05ezOWczc2PmMitqFm4Gt26fiyeFTeLls15m6aGleJo8uXLwlerlUU8RMEhTM9v1kRa2OOoaSJjT9ExQZ9Wc5YQ5cNlbmsCEyVNT2YudrrVpuI68XLx4dPKj/HLsF1YdX8W08GnMjZmLv6u/Xbu2aFzFEc3ydTp6fXX2Ojwn5hz8XP3YmbsTL5MX0yOnM9hP5cEqepbOODON66HzgVellF8KIR5vq4MQIgotHC0UbW3+dSnlCy3azAK+BBpfvX4mpfxrJ8bVK2SUZbA8fTlrMtcwK3IWZ8eeTbR3tBYru+M9OLFLW2FJPMd5bZlG6uvBL05TLakuhM8XURg9gXU+/nwucxhcsZ9LEi8hadLvWi2AmOiXyD3j7kFKaZusZH09u7M3sPTI5+TXFnNl3PlMCp+Kt6dzlZzimmLWZa3js8OfEecdx2WDL2N44HCnbbsLHxcfzo49m7kxc+0mWUUXyNigJf93gGNlGUwIGd+l0zU6M92F2T0Ql7IsO2cmwDWQ4poSqq1VuBncu+1cAJ6uBhKDPVmdkse8EWHtd1D0LvmHYPfHWmL+8Etg6HzwjXZs5xulSdpO+K3zebMyX1M7y9mniakEJDbUBWkRDmN0g4SzqI2dzva87Xx44C3EIcE1Q65hXMi4ppdGUkLmFjj4LRsHn8Hn6T+QX53P/Pj5TAufRphn69dWvG88t42+jUVyEUIIMsoyeH336473li7ibnRnRuQMpkdMV/PtqSB0BIQ+oV0bQoDVDId/hG3/g9pSzXGJn6U52sMvaXJIynM1ifAd72srPGOvJypsJDcOv5Ebht3Q9LfL3Qc7P4SsLTDyKhg8z8Fhr7HWsCVnCx8d/AgXvQvXJF1DrHcsG09s5PPDnxPvE8+liZc6vdcfKTnC10e+Znveds6LO48zo8/skMqeFBJLvYWDxQeJ8orqk+FwioFHZ5yZLCHEa2irMk8KIVxoP0zNCtwnpdwuhPACtgkhfpRS7m/Rbq2U8vxOjKVXKakp4dF1j7IzfycAu/J3sS5rHc9PfBTf/10IVUVaw2MbtUKZsx91/hYxbRV8dG3T9iY98rxnWVZ7nJd+1ZLotuVt49u0b3nv3PeI8227WGbzG9T+E5u5ZeXdmOu1kJ1NOVv4+4SHuXDYtU77fnP0G57a+hSgqd58m/Yt75333inRmlc31m4kfS3Ezmi3WZm5nGprNb6ufl06XWaZgYBuSP5vxOLhj2tJFqUxTTa90BHiEUJ6WTpJ/t0frjA2xo9vd59QzkxfpywbPrwGio5q28d/1RyIC1/SVmOc0drcsvND2PAf7YHyh2ahZpv+C7/50U5RD2BH3g4W/tgUEvTLsV948+w3mRg2UTOc2AlL5rPt2ne5a+1D1NTVANpc+sD4B7hh+A3tfj0hRKv3lhdmv4CPi0/bB+ggar49xTT+vjPWwYdXN+Vhpa2Gi16GMdc1OTL19bDtbVj1T2372AbY+4l2TQYmNv3titI1lb1GkYFjm2BSCpz9N2gWlbElZ4udgt2egj1cOeRK/rPjP4D9vT7Bt0lt7ETFCW7/6XZOVGo5jDvzd3Kw6CCPTHoEF2dlJpqxPH05T2x6AoDNOZv5Lu073j33XRV1oehROrOGfSVarsw8KWUJ4A880FYHKeUJKeX2hp/LgQNA307m6ADpZem2m00j2/K2kVGa1uTINLLpv1rNj5ZYamDDi/a2+jpyXFx5M/1rO3OZuYxDxYc6NcYdeTttjkwjiw99SFmFY35AXlUer+953c5WZa3iUFHnzqnoZeqskLVNK7TWDumlaYS6h6HrYvp/epmBwG50ZswegbiWZjrYQz1CSS3p/uKZABNj/VmVkk+tVSnN92nyDzU5Mo3s/RSKO5lPVZYNa5/WVnV2fWi/z1LVpGbWjI9TPnawfX7k86aN9A2gN7GnMtPmyDTy/oH3HRQnW6O1e0t6aXqH+iv6MEd/cRSU2LIYqoqbtssyYf3z9m2qiyG3hcpn3n5HtbQti6Ekw7Zprbfy3oH37JqcFXMWS/YtsbNVWiod7vVHSo7YHJlGvjj6BZkVjnNzcwqrC3l9t/2zRLW1mgOFB9rsp1B0lQ47M1LKKinlZ1LKww3bJ6SUK9rr14gQIhYYA/zqZPcUIcQuIcT3QginsU1CiIVCiK1CiK35+fkdPW2P0NqbLZ2zuFWhA2cPjEKAzrF4pUA6jU/tbOy0s/YGoUcIxxUigUDvxK6KqbVPX7ouObFLK7jm6t1u07TSNEI8upb8D1qNmWB3Z4pPJ4fFIxBTeY6Dok+4RxiHiw9323ma4+tuIsbfnTUpBT1y/N6iT12b3YGz+UgInM6vbR9IWymvrwMn856z8xiEYxCDsfn8rdODrHc6j+p1enQdvNW2em8ZQHPxgLsuO4qz/CmdocXqoa5j16Sz68TJs0bL67a1/JeWNmdtRMN/bSEQzvuq1UBFD3NKZkghhCfwKXCPlLKsxe7tQIyUchTwIvCFs2NIKV+XUo6XUo4PCgrq0fG2R6x3LFPD7NVFZkTMINY7zrEo24z7ncd0G1wc1cz0RkJrq7kt7mI7c4BrAEP8OrdEOy5kDG4GNzvboqTr8fJw/N0FuQdx+2h71R5vkzdD/dtXxDrd6UvXJenrOrQqA3Ck9AhhHl0Lq6qTcKLSQHA35szU601YXbwwldmvIEZ4RnC09Cht6O52iYlx/nyxo2Nvz/sLfera7A6ChkJoi4T10deDf7zz9q3hHQazHoGD32ghPs1x9dGKFbfgiiFX2D3I6YSOixIuamoQo90PRriH4WH0sOt70/Cb2syZaU7r95bYDvXvDwy467KjxJ+p3febM2kRuPk2bftEwBkP2bfxDHa87kNGgG+MvW3qXZr4SwMGnYEFwxbYNVl5bCW3Jt9qZ/N18SXJ3z7PMsE3wUFl7+ohVxPl1bbKnr+bP3eMvsPO5mX06vH8W4VC9HRylhDCCHwDLJdSPtuB9unAeCllq69Jx48fL7du3dp9gzwJssqzWJu1lk0nNjElfArTI6Zrcsh5B+DAN9qy8LCLIG4meAQ6P4ilWqvWvutDcPGGxLlw6HtKwkey2duf5ZmrSfBNYE7MnJPKXdmXvYkf0n8kv6aI82PPZkzoBDzcnY+ltLaUbbnb+D7te2K8Y5gbM1fFuGp0+JVSr1+X716iKd81quG0gkRy1y93ccOwG/EyeZ706bIr9Ny/MpCHJhW337gT+B/5hYrwUZS2qLL++p7XuX/c/YR5OlGl6iJl1Rbu+2QXm/90Fu6mfqE436lXnb1+bXYXhUfg0A9ajsCQeRA/G3wargcptTAxo3vruTKWKtC7aOHAuXu1vEbvCE0G3z9eUzcLG+nYrc7CroJdfHP0G3RCx/nx5zMyaKS9Wln2DjjyC1tixvLjiY3kV+czN2YuE0InEOTe8Yd2u3tL2BSmR07v81L7zTg9r8vWsFrAUqk5LPX1kL4G9n8JNaVa0n/MdHBvkbdYWai12/eFJuaSdKHzumH5h+Dgt5C9E5IugPiZ2sp8M8x1Znbla9eti96F8+LPI8Y7hm2521ievrzNe316aTorj69kd/5uzow+k8lhkwnugJR/ubmcbTnb+C7tOyK8Ijg75mySAjomStPDqOWhAUyPOjNCW1t8ByiSUt7TSptQIFdKKYUQE4FlaCs1rQ6sT0yABYdhzzIoOKTV9Ei+HAIT2u/XnEbVktSV2tLysAu1tzcmj/b7Kk4V/cOZqbPCU7Fw8asNqkytk1OVy782/5NFIxd16ZQbs1z55JAHN44o79JxWuJ1Yg+6Ogs5o6+0s3+X9j1jgkczK+rMbj1fI08vP8T1U2K4eEy/eHBUD43NKTwCOz+AlB9g0GxNYjmo2QNaaSbs/0KTyg1OgugpmvMx7maIGNtrwx6AqOuykbS1mqR30RFIukhzSipzYddSqDPDkHMh4ax252tFt6GcmQFMT7+CnAZcD+wRQuxssD0CRANIKV8FLgduE0JYgWrg6rYcmT5BZQEsuwVydjfZDi+H6z5pfRXGGUd+hC+bLcnu+RiuWQqDz+m+sSpOD07sbMiXaf/GeLTkaLe86c0o615Z5kZqPYPxy9joYI/0jOBA4YEec2amJgTw8dbj/cWZUTRSVQyf3waZm7Xt3H1w5Be44QstRMdqgXXPawnSoMnnH/4RJvwG/nch/PZne8dHoegqmVs1pdLahqj6nD1QmaeFAuc1iLnu+Rgue1N7EapQKLpEj+bMSCnXSSmFlHKklHJ0w+c7KeWrDY4MUsqXpJTDpZSjpJSTpZQbenJM3ULhEXtHBiB7OxR1Qm2ppgy2vmVvkxJSOqypoFA0kboKQjpWAO9wcQqh7l2XIU4r7RlnxuIRiLGyAFFXa2eP8YnhQNFBJPWt9Owa42P82ZtVSlZJdY8cX9FDFB1tcmQaydunzdMApcc0udvmVBdrq+G15Zrzo1B0J3n7mxyZRrYt0WrBNGfDi2CuPGXDUigGKgNHIuVU4kSFTLN3YqFLp9diu1ticnO0KRTtceRnp7H+zkgpPkykV2SXT5lWaiTMo/udGanTY/EIxLXYXtLcx+SDi97E8fK25UFPFpNBx9RBASzdfKxHjq/oIVqbdxvtOoNWlLgljapL+lbmc4XiZHF2TRpcoN5ibzN5OlcvUygUnUI5MydDYCIMbVHjM+kirYp0RzF5aEomzRNVDa6QeHb3jFFx+mCu1MLMQtpXjKmwVFJUU0RwJxKSnWGthxMV3SvL3JxarxDcitId7HE+cezJ3+3YoZuYNSSYj7Ycx1rXM6s/ih4gYBCMuMLelng2BA7WfvaJgpktSqL5xUFNCfhEOypFKRRdJXSkdt01Z9of4NBye9uMe8HoeurGpVAMUPqFbE+fw9Ubzn1SK7p2bBNET4a4M7SCWFK2rqTTkvgztRyZlO/B6AGJ52jqZ92JuQrqLOCmkgwHLBkbNAfb2UpfC1KKU4jwjHBaD6MzZJYb8HOtw9RDLxXNniG4F6bSogQt8T7xbM3dyvz485326yoxAR4EerqwYn8u5yV3PRRPcQpw8YKz/wLDL4ayLE0eP3x0k+StTgfjbtKcm8MrwD8OPEO1ULMFn2pytjWl2uqNsZWV8dpyQIDLyav/KU4jQkfAle9Azj7t2vGNhPDxWsJ/ynLteht6HkRMaP0YZdnate3iderGrVD0U5Qzc7L4RMLoa7VPzm746XHI3KLJMY+9EQI6UPug3gLVRZrDUVsF1hqw1HTPm5o6K2Ssh9VPQmU+TL4Nhl4AnqeRrv/pwuEVEDaqQ00PFh3sluT/tFIj4Z7dH2LWSK13KP5HV2vFM5sVYYv2juar1K8prS3Bx8W3R849JymExWtSlTPTn6itgLTV2v8L8bM057457v6QdL72aU55Lmx6VRMHaFzBiZ6iOUAA1WVwZAWse05zds54QHsJ1ZrTo1A0IiUc+h4KDsLo6yB8rOZkh49uu1/eAdjzCez7HHxjYdpdMKhnRE8UioGCCjPrKsXH4N1LNWWS4jRY/zx8/1DDm7x2OPwjfL4Idi+FPUvhgysga0v3jCt7O7x7sebQFKTAN3/QpEkVA4/DKyB8XIea7i/cT4y3kyKuneRIsZEQj54JMQOoM7pjNbnjUpZtZ9cLPQm+CWzJ7Tk514lx/mSXVrMto3vr5yh6iMpC+PRW2Pw6FKdridYfXac5Ku2x83344SFNLCB1Jbx7EeTsatqfthI+/Y1WkyZ7O3x4DRz7tae+iWKgkHdQU8pL+U4TBvrlb7D+BS1Koi0stbDpFVj7jNYv9RdNFe24uuYUirZQzkxXKTikrXw058gKKM5ou5+lGja97Gg/+H33jOvYJu2tdnM2vqQVi1MMHAqOaDkzHaiCXmouo7C6gDCPrq84HCk2EtaDzgyA2Tsc90JHhcCh/kNZn7Wux86r1wnOSw7jpV8O99g5FN1I0VF7B6TRVtjO3688V5sTm1NngRO7m37+9TXHfvs+O/mxKk4P8vY7qpRte1urd9QWhYdh1wf2NksV5O7v3vEpFAMM5cx0FYOLo6019ZzmCD24Bzja3f27Z1zO4mxdfZVyz0Dj0HcQOaFDeVr7C/cR4x2LTnTtf3sp4WiJkQjPnnVmarzDcM9PcbDH+cRSXFPC8fKeUx2bNTiY3Zml7Mks7bFzKLoJZ3MwaIIqbaE3gou3o70x90zowN1J3bDO1BJTnJ44u/ZMHq0roTaiN2oKZx05nkKhsKGcma4SlAQx0+1t0+7RkkzbwmCCaXdrEs2NmDwhcW73jCt6sqNjdOYjKplwoHHgK82Z6QC783cT4x3T5VPmVenR6yTeLj1b27bWJxz3wjSHFUYdOkYFjWRF+o89dm6TQceFo8P51/cHeuwcim4iIAHG3GBvG36JY95MS9z9Ye5f7G1eYRA+RvtZp4fJi+xldo3uWu6hQtEWoclNanqNzP6zJgTQFkFDYMb99ja/OE0dTaFQtIoSAOgqnkFw8StwbIOWuBc1CaImdmwFJHoK3PwDpK7WEkrjZna4VghAbW055dVF+LgHY2xen6a2QnujeOO3kL5WCy2LP6PDeRWKfkJ5rnbNzXq43aZ1sp49BXu4YdgN7bZtj8PFRiK9enZVBhryZly9cCs+RrV/rN2+McFjeGPvGxRUX0igW8+IWsweEszyfTmsScln5mAlnNFnMXnA7D9BwhwtryVsJERNAdcOKDgmng23rICSdM1RCRwMgQlN+6MmwS3LtTlab4SYqdrDZTtUmCsw15nxd+umlXZF/8I3Cq75CNLWanlcsdO154KOkHy5JjCUsVFzfmJnQKhz2f3qmhIqa0rx8wxDb2gnGkShGMAoZ6Y78IvWPp1Fb9AmuI5Ocs04eGIrr+19kx1FB5gZMoEbkxYwKChZS/j/5W9QkqGpqo25of23QYr+yYGvGhzn9m9iR0qO4GXywtvkJKyms6ctNBLZwyFmjVT7ROGed9DBmXEzuDEmaCxLD33MHaPv6JFzG/Q6rpkYzWNf7WP5PTMxGdRCdp/FKxSGX6R9OkN1MaSvg61vaKsys/8P/AdpczNoqzOR4yFgMBxdAZ/dqoV0znwIhpyryfQ3w1JvYcuJLfxnx38oqC7gmqHXcMGgCwh2D+6mL6roN1TmaXN0RR4ItJVC1w7Mv16hmsz48IvbbLYrcwP/3buYlNI05keeydWDLycqqP1aYwrFQETdnfshJ4pSuG3tA/yUvY7CmkI+z/iBR379GyV5e+G9SzTlk/IcTZZ50ytQ33MSuopeZPfHED2tQ0235mwhwSeh/YYd4GChiYhTsDIDUOsbiWcrya8TwyaSXprGryc29dj5x0X74e9h4rXVR3vsHIpeQkrY9g788letpkfWNnj/MkcxAYD01bDsN5rCVOFR+Hyh9uKoBfsL9nPbz7exr3AfuVW5PL/9eb46+tUp+DKKPkXufvjfxXD0Z8jdo0l7r/k3WM3dcvjU3J3cuvoeNuZupbCmkP8dWcYLu16lprasW46vUPQ3lDPTD0kvSaWgusDOtr/4EJmVWY7Sj1vfgLITp3B0ilNCyTFNcjtibLtN62Q9W3K3MsR/SJdPa63Xkv+jvU+NM1PjHYaxshC9k5u0SWfkgkEX8t6B99iTv7tHzi+E4MYpsbyxLo2U3A7IrSv6DxW5sLmFWll9XZOaWXO2veNo2/mBg2l/4X7qW+R4fXDgAwqqChzaKgYw+Qe0unHN2fUBlLWjZtZBUkuOUm2ttrOtyFrNidK0bjm+QtHfUM5MP8TV4FiwTSd0uOidKJ64+2tiA4qBxc4PtTjsDuRmHSo+hJvBjUC3rqswpZYY8Xerx83Qs8n/NoSOGr9oPHOdJ+KHuAdzScIlvLHnDZbsW0JWRRbQvWML8nLhyvGR3PnBDmqtapVzwKB3ca4o6UwkxcdJoVlvR5uHycPB5ufqh6kDoaCKAUSjIl5zXLy1a64bcHPyDOBmcMOk657jKxT9DeXM9EMG+Q/h7PAZdrabEq8k1ifeUUHl7L+Dp4rXHlDU18OOd2HQWR1qvub4Gob5D+uWU+8pMBHr3U7ht26m2i8arywnoT8NRHhGcPOIm7HUW/j3ln9z3+r7WbxnMdtyt1FX3z0rSGcOCcbPw8hfv1b1HgYM7n4w92/2Nt+YJjWz5oy5XhNpacToDqOucmg2KnAUoe6htm2B4O6xd+PtTAJaMXAJHemoQDb3CedO8UkwOCCJUX5JdrZ7RvyWiMCh3XJ8haK/oQQA+iHenqE8NP5+zsufS0b5cRJ8BpEcNBKjTxRcuxSOb9GSD8PHdigMSdHPOPqL9mAV0H4OTLm5nN0Fu/ht8q3dcuqduS4k+nVP3HdHqfGNwf/oGnSWauqNjm8kQXsrOTNiBjMiplNUXURG+TG+Tf2GDw6+z1VDrmZiaOdFNpojhODWGfH8+ct9fLL1OFeMj+rS8RR9hEFnwS0/QOY28AjQZM4DBjm2ixyvqZ5lbgaEJrwRmuzQLMYnhsVnL2ZX/i5Ka0tJDkpmeIBKyj7t8ImAq96DzC1QlqU5yN2oJhrkG8dTU//K7oLdZFfmMMx/KCOCnDjhCsVpgnJm+inBfvGc5eek6rt/fIeqwSv6Mb++AoPndahQ5srjK0n0HYy7k7CEzlJXD/sKTJwTV9l+426k3mCixjcKzxN7KYtuu6aOQBDgFkCAWwBjg8eQVZHFspRlHCg6wPVJC9AJfZv928LdZOAPcwbzxLf7ifJ3Z3K8kxAlRf/C6KJJ5EdPab9t2MgOSefH+sQS6xPb9bEp+jd+MdqnhwgPHEq4WolRKAAVZqZQ9C/yUzTVpbgz2m1aU1fLjxk/MSF0fLec+lCREX+3OrxMpyhfphlVgfH4ZG7pdL8IzwgWJF1HRmkGb+x5A0l9+53aOp6fG3ecmcBt723jwAmlHKRQKBQKRW+jnBmFoj+x9hkYOh8M7Sd6rkhfQbR3dLck/gNsPuFKgu+pzZdppNovFpfSLAzVJZ3u66J34ZLES8iqyOLTlM+6PJYRET5cPzmW69/8laP5FV0+nkKhUCgUipNHOTMKRX+hKBVSfoAh57fftKaYFRnLmR4xvdtOv+mEK0P9T22+TCNSZ6A6IAGfY5tPqr9JZ+SihIvYkL2e7XnbujyeKYMCuHxcJNe+volU5dAoFAqFQtFrKGdGoegv/PRXSDofXDzbbCaRvLPvHcYEjcHPxbdbTn2iQk9htY4Yn1NTX8YZFSFJ+GZsBHlyoWIeBg/Oj7+AJXvfoaimqMvjOWNwMBePieCq1zZxJE/VoFEoFAqFojdQzkx3UVUMxRlgPrXJ0YrThONbIGMdJF3cbtNfjv1CfnU+k8Mnd9vp1xx3Y0SgGV37mgM9htkjEKuLJ57ZJ18gM8IznLEhY3l992tdzp8BmDUkmCsnRHLVa5vYm1Xa5eMpuhFzpTYnVxX39kgUpyuVBdo1aK3t7ZEoFAOaHnVmhBBRQoiVQogDQoh9Qoi7nbQRQoj/CCGOCCF2CyH6n5ZwxgZYMh/+Mwo+vhFyVS0KRTdSZ4Vv7oExN4DRSWHUZhwqOsQXR77kgvjz0XdBuas5UsKPGW6MDOr9G3J52EgCjvxMVwpjTgqbSLW1huXpK7plTNMTgrhhipZDsyW96ys+im4gd782F/9nlDY3Z2zo7REpTifq6+Dwj/DGWfCf0fDFbVBwpLdHpVAMWHp6ZcYK3CelTAImA3cIIVpW7zsXSGz4LARe6eExdS8Fh+H9yyFvn/bUd+RH+GKRehuo6D42vAh6E8TParPZsfLjvLTzv8yPPw8/V79uO/2BQiPmOkFsL4aYNVLtF4vOasYj98BJH0OHjnPjzuXb1G/IqsjslnFNjPNn0RmDuPV/W/nlYG63HFNxklQVw+e/0+ZiKbW5+f3LtblaoTgV5O6FD6+C4nQtLHbvp/DzX8BS3dsjUygGJD3qzEgpT0gptzf8XA4cAFqWwL0I+J/U2AT4CiHCenJc3UpRqmNo2YldUHq8d8ajGFic2A3rn4cpd7RZV+ZY+XGe2fo0Z0WfRax3bLcO4fPDnkwMq+nVEDMbQlAaNZ7gfd+cdO4MgJ+LLzMjZvLKzlex1HePqMHISF/unTOY+z7exbJt6v//XqP0OOS0CEU0V2pztUJxKig4rK3ONOfg11B2onfGo1AMcE5ZzowQIhYYA/zaYlcE0PzOn4mjw4MQYqEQYqsQYmt+fn6PjbPTuHo72ozuYPI49WNRnHJ69LqsLoal18OE34JnSKvNDpcc5t9b/s2ZUbMZ6j+kW4dwvFzPjlwXJob2fohZI9V+sdQbTPimre/ScZKDkvFx8eGDgx9208ggMcSLP503jH//cIgXfz6MlKe+Jk8jfXbO7GlMHmB0UiTW2VytOOWcFtelq4+jzSMYTO6nfiwKxWnAKXFmhBCewKfAPVLKlpXmnL3vdXgCkFK+LqUcL6UcHxQU1BPDPDmCkmD0dfa2uX8Dv7jeGY/ilNJj16XVrDky4aPbDC/bnLOZ/2z/D+fFndvtjgzAm7u9mRFZjYuh9x7KHRCC4rjpBKaswFhZcPKHQXB27Fz25e9lXdbabhtehJ8bf75gOF/szOLej3dRY6lrv1MP0GfnzJ7GLw7mPmFvG30dBLWMcFb0BqfFdRk6EuLPbNoWAs57GrxCe29MigGPEOJxIcT9vT2O3sDQ0ycQQhjRHJn3pZTOKtZlAlHNtiOB7J4eV7fh5gtz/wojLoeKHPCPh5Bk0CmhOMVJYjXDJzdpYVTjbnbapE7W8/nhz1ifvYHLB19BiHtwtw9jQ5YrR4uN3D2+pNuP3VUsbr6URo4jYssSMmbcidS3X0TUGa56Vy5KuJiPDn2En6sfwwNGdMv4/D1MPDp/GK+vSeXyVzfwynXjiPJXb2VPCTodjLoGQkdooWWeoRA2EtycvC1XKHoCrxC4+FXI2QXVRRAwGEKTe3tUCsWApafVzATwJnBASvlsK82+Am5oUDWbDJRKKftXYKlHICTMhtHXQvRkcFEhZoqTpLoY3r9M+3fG/aBzVCTLry7gqS1Psr9wPwuSFvSII5NVruf5rT5cPqQCYx/1yytChmNx8yVi8xKos5z0cQLdArgo4SJe3fUqewv2dNv4XI167pydwJgoPy54aR3LtmX2atjZaYWLhzYXj75Wm5s9Ant7RIrTDe9QGHyO5lhHjgODqbdHpBhgCCFuaFAB3iWEeLfFvluFEFsa9n0qhHBvsF8hhNjbYF/TYBsuhNgshNjZcLzE3vg+XaGnH1OmAdcDsxt+STuFEOcJIRYJIRY1tPkOSAWOAIuB23t4TApF3yR1Nbw6HdwC4IyHQG+0222uM/Nt2nf8ZePjhHmEc/mQK/Awdv/b/vRSAw+tDuTsuKo+oWDWKkJQFD8TgOgNL2OoLjnpQ0V5RnJxwsW8vnsx36d9R73sntAwIQTnJYfx0LyhvLzyCFe+tpEdx5TSoUKhUChOHiHEcOBPwGwp5SigZemTz6SUExr2HQB+02D/M3BOg/3CBtsi4AUp5WhgPFrEVL+iR8PMpJTrcJ4T07yNBO7oyXEoFH2W+jpIXQUb/6tJyE78HUROsGuSV53HxuyNrDy2klCPMK4bel23Si83Um4WfHnYgy+PeDJ/UCVjgvtO0n+rCB2FCbPxzt5J7OpnKIqbQWncFOpMXp0+VKRnJAuGXcf3ad+z6cQmLhp0EaOCR6EXXZ8mYwM8+OtFI1iVksfCd7cRE+DONROimZMUgo+7sf0DKBQKhULRxGxgmZSyAEBKWSTsFU9HCCGeAHwBT2B5g309sEQI8THQmPqxEfiTECISzQnqdzr2PZ4zo1AogJpSOPKz9m9lvlZ/IGc35OwBV1/Mg2ZzYNTl1NTmUXHgI0pqSsityuFY2TEsso5Y7xjOD5lEoFsg1FZQU1vRpeFUWfVsyPWnqNbIiUpXUko9yapyI86rkitij+FnMJPXj+o/5rnFYIwIwC8rBd+DG7G4elHpFUqNuz9WkztWoztlAXHU69qf8qaFzCOtNJ23d31KuWUJUZ6RhHtFEOAWQIxXDIN8B530OEdF+jI8zIetGUW89MsR7vtkF75uRoaFezMoyJNQH1d83Y14uRqJ8XdnVJTvSZ9LoVAoFAMWQdvVo5cAF0spdwkhbgJmAUgpFwkhJgHzgZ1CiNFSyg+EEL822JYLIX4rpfylR0ffzYj+GMMthMgHMtppFgicvNRR/+F0+Z7QO9+1QEo5ryMN27ou75tiCnz6bNeYlvZ6KSmokhZp0ulw1TsmyIBW+K+b/zddWTeeP5rvsbO5U40HA6Oom7P42RKdjtq2F4odEC0OJOuhrlyefIJOS/QGoXf1bNXDynjqwm0t6uk0/j/Q4esSOjxn9iT9YZ5SY+w6rlLKDqtonCb3cjX+3uWk5sy+TkOY2efAFClloRDCH7gLqJBSPi2EKACGAcVo6RxZUsqbhBCDpJRHG46xA7gZKAPSpJRSCPE8kC6lfP7Uf6uTp186Mx1BCLFVSjm+t8fR05wu3xNOr+/aFv3l99Bfxgn9Z6z9ZZwt6Q/jVmPsOj0xvr7+ndtDjb936e/jbwshxI3AA0AdsANIp8mZuQ14EO1lwR7Aq8GZ+QxIRFvZ+Rm4B/gjsACwADnAtVLKfhSbocLMFAqFQqFQKBSKfoWU8h3gnVb2vQK84sR+qZPm/2z49Fv6qOiqQqFQKBQKhUKhULTNQHZmXu/tAZwiTpfvCafXd22L/vJ76C/jhP4z1v4yzpb0h3GrMXadnhhfX//O7aHG37v09/ErOsCAzZlRKBQKhUKhUCgUA5uBvDKjUCgUCoVCoVAoBjDKmVEoFAqFQqFQKBT9EuXMKBQKhUKhUCgUin6JcmYUCoVCoVAoFIo+hBCioo19G3rwvI/01LF7CiUAoFAoFAqFQqFQ9CGEEBVSSs8WNr2Usu5Un7ev0y9XZubNmycB9VGfU/HpMOq6VJ9T+OkU6tpUn1P06RTqulSfU/jpUWL/+O21sX/8Nj32j9/WN/x7bXcdWwgxSwixUgjxAbCnwVbR8G+YEGKNEGKnEGKvEGKGk/7DhRCbG9rsFkIkNtgXNLO/JoTQCyH+Bbg12N5vaHdvw7H3CiHuabB5CCG+FULsarBf1WD/sxBiS4PtdSGE6K7fQ1v0S2emoKCgt4egUDigrktFX0Vdm4q+iLouFQOBBsdlMRADiIZ/F3enQwNMBP4kpRzWwn4tsFxKORoYBex00ncR8EJDm/FAphAiCbgKmNZgrwOuk1L+EaiWUo6WUl4nhBgH3AxMAiYDtwohxgDzgGwp5Sgp5Qjgh4ZzvSSlnNBgcwPO756v3zZ9wpkRQgxp8AIbP2WN3p9CoVAoFAqFQtFH+Qfg3sLm3mDvLjZLKdOc2LcANwshHgeSpZTlTtpsBB4RQjwExEgpq4GzgHHAFiHEzobteCd9pwOfSykrpZQVwGfADLQVojlCiCeFEDOklKUN7c8UQvwqhNgDzAaGn+wX7gyGU3GS9pBSHgJGgxYPCGQBn/fmmBQKhUKhUCgUinaI7qT9ZKh0ZpRSrhFCzATmA+8KIf4NlAOPNTT5rZTyAyHErw1tlgshfou2gvSOlPLhds7rNExMSpnSsGpzHvBPIcQK4CngZWC8lPJ4g4Pl2qlveZL0CWemBWcBR6WUGb09EEXPk16aTlppGm4GNxL9EglwC+jtIZ3WFFYXcqTkCFWWKmJ9YonzievtISkUCoWiH5FakkpGWQbuRncSfBNOh/v6MbTQMmf2HkUIEQNkSSkXCyE8gLFSyntotiAghIgHUqWU/2n4eSSwAvhSCPGclDJPCOEPeDU8e1uEEEYppQVYAyxpyKURwCXA9UKIcKBISvleQ/7OTTQ5LgVCCE/gcmBZT/8OoG86M1cDH7Y0CiEWAgsBoqO709lV9Ba78nexcMVCqqxVAEwOm8zfpv2NUI/QXh5ZxxlI12VuZS6PbXiM9dnrAXAzuPH63NcZHTy6dwemOCkG0rWpGDio63JgszNvJwt/XEi1tRqAaeHT+MvUvxDiEdLLI+tRHkHLmWkealbVYO9pZgEPCCEsQAVwg5M2VwELGtrkAH+VUhYJIR4FVgghdIAFuAPIAF4HdgshtjfkzSwBNjcc6w0p5Q4hxDnAv4UQ9Q19b5NSlgghFqOFoKWjhcCdEvqUNLMQwgRkA8OllLmttRs/frzcunXrqRuYotupslRx5y93sjlns5392VnPMjdmbi+NyikdVuLo79flz8d+5p6V99jZxgaP5eU5L+Nh9OidQSlao1MKMf392lT0G9R1eRpTaank9p9uZ3vedjv7C2e+wOzo2b00Khs9qqrVkOz/D7TQsmPAI+n/mv9BT55T0URfW5k5F9jeliOjGBhUWio5VHzIwZ5TmdMLo1EA5FXlOdgOFx+mwlyhnBmFAwdzykgM9kKvOyXKmwqFoo9TYa4gpTjFwZ5bNfAf6RocF+W89BJ9Qs2sGdfgJMRMMfDwdfXl7JizHeyJvom9MBoFQLyPo5DJnJg5+Lv698JoFH2Zokoz855fy08HBv5DikKh6Bj+rv5OIysG+QzqhdEoTif6zMqMEMIdmAv8rrfH0htY660cKDzAwaKDeJo8GR4wnGjvgRtPbNQZuX7Y9WRXZLM+ez1uBjduH307IwJH9PbQTluGBwzn4YkP8/z256m2VjM1fCq3jLgFo95oa1NjrWFf4T6OFB8hwC2A4QHDCfMM68VRt05GWQb7CvZRaalkqP9QhgUMQ6/T9/awBgT7sjUVzt2ZJZwzvP/kuCkUio6RV5XH3oK95FXlEecTx/CA4XiaHIvCpxSlsL9oPwLBsIBh3DLiFnKrctmQvQE3gxv3jL2H4YGnRJ1XcRrTZ5wZKWUVMOAlL1pjS84WFv20iHpZD0CkZySvzn2VGG9nAhkDg+yKbHRCx6KRizDXm1lzfA2zo2Y7nTAVPY+nyZNrhl7DjMgZ1FhrCPcMdwgvW5Gxgj+t+5Nte3TQaJ6Z9QzB7sGnerhtklGawcKfFpJdkQ2AXuh5dc6rTA6f3MsjGxgcL6rGoBMcK6zq7aEoFIpuprimmL9s/AtrMtfYbA9NeIjrkq6jeUH3fQX7uGX5LTYRHw+jB2+d/RbPznqW7IpsXA2uRHpG2vVRKHqCPuPMnM5UmCt4YfsLNkcGILMik935uwekM1NjrSGrIovntj3HoeJDrM1aa9u3u2D3gF6R6usIIYjyinK6L6cyh6e2PGVn25m/k0NFh+ycmXpZT2Z5JrV1tU4dolPBzvydNkcGoE7W8eKOF0kOSlb5P91ATmk18UEe5JTV9PZQFApFN3O4+LCdIwPwwvYXmBE5AwBznZkIzwi+OPKFzZEBLRf2u7TvuH/C/ST6qZBxxalDOTN9gNq6WqfJ16W1pU5a92+yyrN4bvtzeJu8KagucNhfVlvWC6NSdARzndnp36fS0lTLq8JcwWeHP+PFHS9SU1fD1PCpPDzxYWJ9Yk/hSLU3iy3Jrcql1lqrnJluIK+8lmh/d47mO63jplAo+jHNHZRGaupqSClO4eG1D1NbV8uCpAUcLz/u0O54haNNoehp+poAwGlJgFsAVw25ys4mEAMyzvTbtG9Znr6cDdkbOCvmLLt9jTG3ir5JiHsI82Ln2dmMOqOdcMDegr38e+u/qanT3thvyN7AO/vewVJvOaVjHRk00sF29dCr8XdTYgbdQWFlLRG+7pRUmXt7KAqFopuJ9Y7F3eBuZ5sQMoGvjn5FbV0tAEsPLWVm5EyHvhfGX3hKxng60FCMsrV9G07lWJycP1wIcVIFMYUQq4QQ47tzPMqZ6SNclHARi0YtwsfFhzjvOP4z+z+MCBhYyfCVlkq+T/segKyKLKSUXDH4CnxcfIj3iefF2S8yPGDgOXADBReDC78f83uuGnwVXkYvRgSO4PW5r9uFExwuOezQb0XGCqcrJT3JiMAR/OfM/xDrHYuviy+3j7qdC+IvOKVjGMgUV1oI83GlrMZKX6pVplAouk6sTyyvzX2NscFj8TB6cNGgi7h+2PWsPr7a1sZSb2F73nb+NOlPBLsHE+IewuNTHmdC6IReHPnARwihB5BSTj1F53MawSWlzJZSXn6KxtCuco8KM+sjhHqEcvuo27ly8JWYdCZ8XH16e0jdjovehZGBIzlScgSAT1I+IdIrkn9M/wejgkbh4zLwvvNAI9o7mj9O+iO3jrwVd6M7XiYvu/1hHo7KZkn+SXgaT62og0lv4szoMxkTPAZLvYVAt0CVhNqNlFRb8HE3YtILKs11eLqoW4lCMZAYHTyal+e8TIW5ggDXAFYeX4nE/sVFubmciwZdxNyYuQjE6b3y/biPQ9FMHi/tlrozQohZwGPACWA0MEwIUSGl9BRChAFLAW+0Z/rbpJRrm/X1AXYB8VLK+gbl4ENAfMNY/wsEAVXArVLKg0KIJUARMAbYLoT4Cnih4ZASmIkm2PWNlHJEg7PxJHBOw/7FUsoXhRBnAU83jGtLw9hqW3y3a4BH0IqafiulfKjBXgE823DM+4B1bf2O1MpMH0IIQZB70IB0ZAAMOgPXJl1LgGuTaJ230Zs47zgHRyajLION2Rs5VHQIc50KZelLGHQGQjxCHBwZgOTAZKaFT7Ntexg9uGvsXbgb3R3a9jQV5gqOlR8jrSzNaU6a4uQpr7HgYTLg4WKgrPrUhhAqFIqex1xnJrM8k9TSVLIqsxgVNIqp4U2LAZ5GT34/+ve4Gd0IcAtQjgwsBmLQHspjgMUN9u5iIvAnKWXLWPxrgeVSytHAKGBn851SylI0Z+aMBtMFDe0twOvAnVLKccD9wMvNug4G5kgp72vYd0fDOWYA1S3GsBCIA8ZIKUcC7wshXIElwFVSymQaHK3mnYQQ4WhO0Gw0J22CEOLiht0ewF4p5SQpZZuODKiVGcUpZoj/EN477z1SS1Ix6A0k+iYS5B5k12Zj9kbuWXkPVdYqdELHfePu48ohV+JqcO2lUSs6SohHCP+Y8Q8OFx+m2lpNnE9cryjy5Vfl8+y2Z/km9RtAWzF6afZLDPYffMrHMhApr7HibtLjYTJQVmMhHLfeHpJCoegmaqw1fHzoY57Z9gz1sh53gzvPn/k8/5z+Tw6X9O7c3kf5B9DyjZ17g71bVmeAzVLKNCf2LcBbQggj8IWUcqeTNkuBq4CVwNXAy0IIT2Aq8EmzqAWXZn0+kVLWNfy8HnhWCPE+8JmUMrNFpMMc4FUppRVASlkkhBgFpEkpUxravAPcATzfrN8EYJWUMh+g4fgzgS+AOuDT1n8d9qiVGUW3Y64zU2luXeUo0iuSmVEzmRo+1cGRya3M5U/r/mRTU6mX9fx7679toWmKvkmVpYoaq5b07+/qz6SwScyKmtVrN7s9BXtsjgzAicoTLN6zWK3ydQN19ZIaSx1uJj3uJj0VNdbeHpJCoegk5ebyVufDIyVH+PfWf9vKRVRZq3h0/aNYpKXX5/Y+Smv1JLqzzoTThyop5Ro0ByALeFcIcYMQ4hIhxM6Gz3jgK+BcIYQ/MA74Be35v0RKObrZJ8nZ+aSU/wJ+C7gBm4QQQ1sMQwAtkyc7EtfdVpuaZs5UuyhnRtFt1Mt6tuVs456V93Dd99fx0cGPKKhylF9ui+KaYvKr8x3sKkyob1JuLuf7tO+56YebWLhiIWsy19icmt7kaMlRB9vW3K2Um8t7YTQDi0qzFVejHp0QuJsMlNcqZ0ah6C/kVeXx3v73WPDdAu5bdR878nY4tMmtynXa71QLufQjjnXS3m0IIWKAPCnlYuBNYKyU8vNmDspWKWUFsBkt7+UbKWWdlLIMSBNCXNFwHNGwmuLsHIOklHuklE8CW4GWzswKYFGjWECD03QQiBVCJDS0uR5Y3aLfr8AZQojAhryba5y06RDKmVF0GwcKD/DbH3/L2qy1HC05yt9//bvd2/GOEOAeQKhHqJ1NIBxsir7BpuxNPLjmQQ4UHWBH/g7u+PkOdufv7u1hMdjPMZxsWvg0vE3evTCagUVjiBmAq1FHpXJmFIp+Qb2s55OUT3hyy5OklqayKnMVt664lUNFh+zahXmEIVq8NA/zCCPALQCFUx5BS6BvTlWDvaeZBewUQuwALqMpUb8lS4EFDf82ch3wGyHELmAfcFErfe8RQuxtaFcNfN9i/xtojtvuhjbXSilrgJvRwtj2APXAq807SSlPAA+jhb/tArZLKb9s/ys7opwZRbexv3A/1nr7B5sl+5Y4LY7ZGkFuQfxrxr/wc/EDwKQz8diUx0jwTWinp+JUY6mz8P7B9x3sKzJW9MJo7EkOTObaodfabsiJvoncNOImjHpjL4+s/1NZa8XdpKVbuhj1yplRKPoJeVV5/G/f/+xstXW1HCq2d2YSfBN4bMpjmHQmAPxc/PjnjH8S5GYfFq5oQFMtuxXIQAu3ygBu7aqamZTSs+HfVVLK81vZ946UcoSUcoyUckYreTVIKZdJKYWUcnUzW5qUcp6UcpSUcpiU8q8N9puklMuatbuz4RyjpJTXSClrpZTpUsoRDfutUsp7G44xSkr5UoP954ZxJUspb2lUMpNSzpJSbm34+YOG/SOklA+2/H4dRQkAKLoNF4OLg83D6IFB17nLbFzIOJaev5Scyhx8XX2J9opGr2tXZlxxihFCOF3p6AsS2/5u/vxh3B+4JPESaq21RHlFnd5qO91IRa0VN2PTykxFbYfDmhUKRS+i1+lxN7rbclIbcdHb37tNehMXJ1zMmOAxlNaWEuoRSpino+y+ohma49Jdyf6KTqJWZhTdQlF1EYm+iZwRcYbNFuAawJ8n/5kqSxV19c4feCz1FrIrsh3yZMI8wxgTMoY4nzjlyPQxaq21ZJVnUVZbxk3Db0LfrJ6Vq96VudFzya/OJ6s8C0t9z8n21lhryCzPbDWO29XgylD/oYwKHqUcmW6kqrYOV6N263Ax6KlSKzMKRb8gyC2IP4z9g50t1D2UJP8kKi2VZJZnUlZbBmiOT7xvPGNCxnTakbHUWcgqz2o3KqO0tpTM8kwqLa0LBikUHUGtzCi6hLXeysbsjfzj13+QXZnN3Oi5vDT7JbIrsqmnnvvW3EeNtYYFSQu4Zug1hHiE2PpmlWfx9r63+fTwp/i6+PLghAeZFTkLN6OSee2rpJWm8dKOl/gx40ciPCP406Q/8d6577Emaw0mvYnpEdNJL03ntp9vo6S2hMsSL+Pm4TcT4RXRreNILUnlxR0v8vOxn4nyiuLRyY8yKWwSOqHez/Q0FbVW3BpyZlwMOiUAoFD0I86KOYtA90A2ZW8izDOMSaGTqLZWc9cvd7E5ZzNJfkk8PPlhxgSPOanjZ5Zn8uaeN/niyBf4ufrx0MSHmBU5yyFyY3vudv7+699JKU5havhU7ht3n5LOV5w06s6v6BKHiw9z5y93klOVg6fRk+UZy/nqyFdEeUXxr83/orS2lNq6Wt7c+yY/Zvxo61cv61l6aClLDy3FWm+loLqAB9c8yP6i/b34bRRtUW2t5rltz7EiYwUSSWZFJnf+cicGvYHbR9/Ob5N/S6WlkgfWPEBBdQHWeqvtb9wo8dkdVFmqeHLLk/x07CckkmPlx7j959s5Uqzku08FVWYrLobGMDOVM6NQ9Cc8jB5MDZ/KvePv5Zqh1+Dr6ssDqx9gc85mAA4UH+COn+7geNnxTh+7rr6ODw5+wLLDy7BKK/nV+dy/+n6H+3pGWQa3/3w7KcVaCZIN2Rt4eO3DlNSUdPn7KU5P+sTKjBDCF00NYQRa8tQtUsqNvTqoAUBqSSrb87ZTbi5nTPAYhgcM7/YE6LTSNK5Lug43gxtl5jKC3YPZV7CP9dnrHdp+evhTLkm4BA+TB4U1hXxx5AuHNgcKDzAuZFy3jlHRPeRV5bHy+Eo7m1VaSStNY6i/ptTYUhUH4IsjX3D9sOttNYUqzBXsKdjD3oK9hHuGMypoFCU1JezI34FJb2JM0Jg239DlVOawIXuD/TjqraSXpas3e6eASnMdLobGMDMdJdWqdo9C0V+osdawt2Avu/J3EegWSJhHGGll9jnj5ZZyjpUfI8o7qlPHLqwp5MsjjmJUKUUpdis9x8qOOYSWpZSkkF2Zja+rb6fOqVBAH3Fm0KTkfpBSXi6EMOFYSVXRSVJLUrll+S0U1hQCmrzxK3NeYVrEtG49T7BbMK9lvUZqaarNdveYu3E1uDq0jfWOxaTX1FHc9e5EekVSXGuf76CkH/subgY3AlwDbNdUIz6mpoR/P1c/h34RXhG4GZpCB79N+5YnNj1h2x7mP4zkwGSWpmiKkZ5GT96e97bNQXIYh9ENHxcfSmtL7exKdvnUUG22YjI0y5kxKwEAhaK/sOr4Kh5Y84Bt+56x92DUGR3yG09mPnXVuxLpGemwEtPyvtD8ftCIi94FV73jc4NC0RF6PcxMCOGNVr30TQAppVlKWdKrgxoAbM/bbvfQKZH8d8d/O5xoV1hdyJ78PWSUZrQaInS8/Dj5Nfl2jgzAkv1LGBcyjnDPcJvNzeBmJ43rYfLgnrH32CmdDfYbzMjAkR3+jopTS7B7MI9MesSu/sC08GkM8R9i2x4ZONKuxotBZ+APY/+Ap0lTWcyuyOa/O/7LpYmXsnDkQn4z4jeUmkvtnNgKSwVrMte0Oo4wjzAenviwnW1W1Cy1KnOKqKyta3JmjDqqlJqZQtEvKKwu5OmtT9vZvjzyJYtGLbKzXTXkKuJ84hz6W+osHC05yv7C/TahgOZ4u3jzh/F/4Py481k0chELRy5kbvRchgcOt2tn0pmYGzPXznbt0GtVzmMLhBAVbezb0Nq+Thz/r0KIOZ3sc6EQ4o/ttAkXQixrq0130xdWZuKBfODthuqj24C7pZR2T91CiIXAQoDo6OhTPsj+hrNK50W1RR1Sl9pfsJ/7Vt9HZkUmbgY3HprwEPPj59tWWyz1Fn7K+Im/bPwL1ydd79C/wlyBp9GTN+a+wcHig1jqLCT6JZLol2jXbnzoeD447wOOlh7F3eBOkn9Sv5N/PN2uyzOjzuS9894jvSwdXxdfkvyT7BwRT5Mnvx3xWzLKM6irr8PP1c+uNoGl3sLCkQt5/+D7ZJZn4qp35cbhNzq8BWxPBWdO9BzeP+990svS8XPxIykgCX9XpVjWnJ66Nitqm+XMGHRUW5Qzo+g4p9uc2Zcw15spM9s7IWllaQzyHcSSc5aQWZlJsFswSf5JthdQjZTWlvL+gfdZvHsxVmllZOBI/jbtb8T7xtu1C3QLJLU0lW/SvsGgM7AweaHD/F5mKaNO1vH70b/HXG/GRe/Cmsw1nBt3bs988QGEEEIvpayTUk7t6rGklH9u6xyt9PkK+Kqd42YDl3d1fJ2hLzgzBmAscKeU8lchxAvAH4H/a95ISvk68DrA+PHj5SkfZT9jdPBoBAJJ069qQdICfF182+xXVlvG4xseJ7MiE9CSvh/f+DhD/IcwInAEoIWw/XHtH6mX9eh1elz0Lvi7+hPsHsyhokOcH38+YR5hGPSGNmNudUJHUkASSQFJXf/CvcTpdl0a9UZGBo1kZJDzFbS9BXt5cO2DTA6dTKhnKEv2L2FfzD4en/I4Rr0RL6MXXxz5gsxy7fqqqavhtd2v8eSMJ+2OMztqdpvjcDG4tDkORc9dm1VmK64NzoyLUU+VWQkAKDrO6TZn9iWC3YK5Zug1vLX3LZvNoDMQ7hFOUkAS42g9X3VvwV5e2fWKbXt3wW7e2vsWj095HINee5Q015lZvHuxLczMWm/l5V0vMyZ4DJPDJ9v6xvnEsTNvJ78c+8VmGx8ynkjPyG77rqea5HeSrwX+AUQDx4BH9ty4p1vqzgghZgGPASeA0cAwIUSFlNJTCBEGLAW80Z6nb5NSrm3W1wfYBcRLKeuFEO7AIbSFhMXAN1LKZUKIdOAt4GzgJSFEGfAsUABsb+h/vhDiJmC8lPL3QoglQBkwHggFHmw4VmzDcUcIIfTAk8A5aDnxi6WULwoh/gxcALgBG4DfSSlPej7oC85MJpAppfy1YXsZmjOj6AIjAkbw8pyX+e+O/1JUU8SCYQuYFzuPWmstO/J28OnhTzHqjFyWeBkjg0dSaank1xO/UlJTwoHiAw7HyyzPtDkz2RXZttCzzw9/zlMzn2Jd1jqOlx/nrrF3MS18mm1yU/Rdaqw17MjbwWeHP8OkN3Fp4qWMChrV6SKnzcmryuP5Wc+zOnM1+VX5PDj+QXIqcyiuLSbYPZhSc6lDtWnQVvOivKJwM7hx+6jbGR08ugvfTNGTVJnr8HHTwkVNeh3VKmdGoeh1pJTsLdjLF0e+oKC6gEsTL2VcyDi7FRa9Ts8lCZegEzq+Pvo1oR6hLBq5yC5UuDWOlDiqRWaUZrA5dzNfHfkKBFwz5BqnIcJpZWl2zkyEZwSvznmV13e/zq78XcyOms11w67Dy8XrJL9979LgyCymKd87Blic/E4y3eXQABOBEVLKtBb2a4HlUsq/NzgOdjnnUspSIcQu4AxgJZoDsVxKaRFCtDgUNVLK6UIIV+AwMFNKmSaE+LCNcYUB04GhaCs2LcPLFgJxwBgppVUI0RhC8ZKU8q8AQoh3gfOBr9v5HbRKrz9xSilzhBDHhRBDpJSHgLMApc/bRYx6I9MjpjMmeAyWOotNIWRj9kYW/rjQ1u7btG9599x32Vewj39s/geXJV5GuEc42ZXZdsdrVKICCHQPtP18Xvx5/GXjXyiqKQJg04lN3DH6Dhb6LFTxr32c7bnb+d1Pv7Ntf5P6DW+f8zZjQ8ae9DFDPUK5e+XdVFurAViXvY4Hxj+Al0m7SXmbvIn0jLSt/DUS7xvPh+d9iE7o+u0N7XSh2lzXTJpZR42l+2S3FQrFyXGg6AA3L7+Z2rpaAH45/gv/nvlv5sXNs2u3Lmsd36R+w5TwKRRWF/LIukdYMm+JQ7hYSyK97FdNBIKLEy9m0Y+LbBEgJTUlDPMfxubczXZtwz3CaUlSQBL/mvEvKi2VeLt4d+klWh/gHzgKV7k32LvLmdnsxJEB2AK8JYQwAl9IKXc6abMUuArNmbkaeLmVcyxt+HcokNrsfB/SEBrqhC+klPXAfiFEiJP9c4BXpZRWACllUYP9TCHEg2i/J39gH11wZvrK0+adwPtCiN1oS2j/6N3hDBw8jB42R6Ze1vP+gfft9tfLeo6WHOWzw5/x5IwnGRE4ggcmPMDsyKYwn+uTrqeuvo4DhQeosdaQ4JvAnWPuBMCoM9ocmUbe3PMmOZU5PfvFFF2irr6O9w68Z2erl/UsT1/epeMeLj5sc2Qaef/A+7ZrJMAtgMemPGanWnPT8JvwMfnwa86vbM7dfFL1DRSnjqpm0swmg54alTOjUPQ6W3O22hyZRl7f/bpd/mxuZS6v7HqFnMocvjjyBWuz1lJcW8zB4oPtHj85MJnfj/49t4+6nUUjF/HQhIfYkrvFLpR944mNXDHkCnxcmhQu58XOcxAAAC0y4GjpUfYW7iW9LJ26+n49j7SW/NWdSWFO1ZuklGvQRLSygHeFEDcIIS4RQuxs+IxHWzE5t2FVZBzwi7NjNTuHw5JNGzS/6Jz1E4Bd+FjDys/LwOVSymS0Va0uSdn1CVe4wZMc39vjOB2QOIYk6qSO20ffzqPrH7UlB86Lncd/z/ovdbKOd/e9y7sH3kUguG/8fVw15CpuGHYD08KncbjkcIfPo+j7dPXv5qx/S5tRZ+TmETdTJ+sw6oyMCR7D73/5vW01cHjAcB6f8jhDA5xLMyt6l2qLfZ2ZGmu/fghRKAYsHZ7PO9jsYNFBfjr2EwB+Ln48OOFBvkv9zu48OnRcPeRqAPRCr624tDh+jbWGjw59xLNbn0UiMegMPD3zac6KOatjA+l7HEMLLXNm71GEEDFAlpRysRDCAxgrpbwH+LxFu81oZVC+aS25vxkHgXghRKyUMh1tVedkWQEsEkKsahZm1ricXyCE8EQTC+iS+lmfcGYUXafGWkOVpQpfV1+78K7C6kLMVjNhXmEUVBVw28jbOFp8lKzKLEBLwh8aOJS/bPyLncrJD+k/MCtqFk9seoIKi6YOKJE8s/UZJoROYFjAMIYHDsfT5Im/q7/d6swtI24hzKN/qZKdbuh1ehYkLWBtli1PEJ3QMS92HpWWSsx1Zqc1YwDq6+vJrsjGy8XL9gautKYUndCRHJiMm8HNbnXmhmE3EOgaSFF1EVJKHl3/qC3MbGrYVHIqc+zCGvcV7mPTiU1EeUe1OQ5F71BtrsPUEGZm0uuotdQjpcRJ/LVCoegmLHUWysxleJm8bPXamjM+dDwmnQlzfVMR24UjF9pCfAFCPEJYNGoRT215ymbzNnm3WtOrOXsK9rAqcxWzombhZfRi44mNfJP6DTMiZuBudEcisdRZWJqylM059mFmg/0GM9U0ldzqXHxNvhwrP8YzW5+x7bfWW/nzhj8z1H8oEV4Rnfq99BEewT5nBqCqwd7TzAIeEEJYgArghlbaLQU+aWjfJlLKaiHE7cAPQogCYHN7fdrgDWAwsLthjIullC8JIRYDe4B0tFC5LqGcmQHAnvw9vLzrZQ4XH+bcuHO5cvCVBLoGsi57HYv3LKbMXMZliZdRUlvCquOrWDBsAe4Gd7bmbeWyxMvQC73Tyu1F1UU2R6YRibSTzY3xjmHx3MV8l/YdB4sOMj9+PlPDp6p8mX7A2JCxvD73dT49/CkmvYmrh1xNlaWK3/34O/Kq8rh6yNXMj59PiEdTGOzBooN8cfgLfjr2E1FeUdyafCuVlkqe3/48LnoX7h13Ly/OfpFvU78lvyqf+fHzifGO4ZF1j7AzfyczImZwccLFvLzrZeplPclByaw6vsphbCnFKTy2/jH2FOzh2qRrOS/uPLu8LUXvUWNpqjOj0wmMeh211npcjfpeHplCMTA5WnyUJfuXsD5rPRNCJ/Cb5N/Y1fMCSPJPYsm8JTYBgEsSL2F8iGPAy8yImRh0BlYeW0m4Rzjnxp9LrE9su2MoqSnh3nH38k3qN6TUpHBu3LkEugbi6+rLkr1LQMAtw29hRfoKh75uBjf++utf2ZC9gcG+g7lg0AUObcrMZRTXFvdLZ2bPjXs+SH4nGbpZzUxK6dnw7ypgVSv73gHe6cCxltEiDExKeVOzn2NbdFkppRwqtLdU/wW2NrRbAixp2b/FmNKBEQ0/W4F7Gz7N2z4KPNreuDuKcmb6OWmladz64622YphL9i0huyKbSxMv5b7V99mWf/+z4z/cOPxGKi2VPLnlSR6b8hj/mK6lJpXVljEpbJLdW3qAMM8wgtyCyK/Ot9kMOoNdMUyAwf6DVcHCfoirwZUp4VOYEj4F0JziRT8toq5hBfq57c/Z6sIIIai0VPLW3rf4Pu17AHKrctlbsJe/T/87x8q11fTbfr6N1+a+xl+n/RWAExUnuPa7a20O8KeHP2WY/zDmxsxlefpy1mauZXLYZAeFswjPCN7a+xbmejNPb30aKSU3jbjpVPxaFO3QPMwMtMKZ1eY65cwoFD1AUXURD655kJSSFAC+S/uOXXm7+N95/yPYPdjWTghBclAyyUHJrR6rrr6Oz458xnv732Oo/1B+zfmVL1O/5IPzPmi3REKQexB3/nKnTcn0w4Mf8sjER3hsw2O2Nv+34f94dNKjbDixwXYfuW3Ubby862W25W4DNMXLcSHjMAgDVtkk6x7iHmL3ffobDY5LdyX79wVuFULcCJiAHcBrvTyeNlGvz/s5qaWpNkemkY3ZG9ldsNvmyJh0Jn4z4jf4mHy4ecTN3DbqNlakr2BP/h4ySjOotlYzOXwyCb4JgJbTsCBpAZY6C49NecxW9NDT6MlTM54i1jv2lH5HxanhYNFB2w2okfcPvG9zRDLKMhwEAmrqauxW6nToMNeZ+eroV3x08CP2FOxxKIC5v2g/Sf7ajTO1NJUZkTOYHKbJdgoEFw26iKyKLLtwifcOvEdRtb3QhKJ3qGnpzKjCmQpFj3Gs/JjNkWkkqzKLjLKMTh8rrzqPg4UH+cf0fzAvbh6/Sf4Nj0x8pNXcV7txlB2zOTKg5Tb+eOxHh3YbT2y0Fb806AwMDxhuc2Qa+fTwp/x5yp/xNGqy0UFuQTw186l+7cwMNKSUz0kpR0sph0kpr5NSVvX2mNpCrcz0c5qrQjWi1+ltkwTArSNvZemhpbaHSg+jBw9PfJiPDn3E+qz1LJ67mA8PfMjo4NHMiZ5DPfX8lPET3iZv3tn/DneMuoPhgcMJdg92kGdUDBzcjS2VJcHXxRejrqGmiM6Eh8GDcku5XZvm8dt/nfZXXtj+gq0mwcMTH3Y4pk7omBw2mQ/nf4iX0Yto72gSfBNILUnFoDNQWFPIH1b9odVxKHqXWmu9LcwMwMWgV86MQtFDuBpcHQpgA7joXTp9LJPOxIWDLuShtQ/ZXlwN8x/GgxMebLevm8HNbrvcXO4QpQHaCsvvR/+eBUkLcDO4UWGpwKAzYK1vWoXJrMgkyC2Ij8//mJLaEkI8+veqjKL3USsz/ZzBfoMZFTTKtu3n4sfjUx4nOSCZOdFz8HPxo7im2O7teKWlkk0nNnGw6CCFNYWsy1rHH8b9gW9Sv+HV3VohqxprDVXWKmqttezM34m13oq7wfFhVzFwGBE4glD3UDvbPePusUl7J/gl8LuRv7Pbn+CbYMuPMugMVFmr7IqreRg9mBI2xa7PRYMuwsPowYjAEcT4xCCEIMAtgAlhExgTMoYE3wSG+Q/j+mHXs3DkQsYEj+GusXep+jN9ACkltZaWzoxOyTMrFD1ErHcsVw2xF5M6P/584n3argvjDLPVzMu7XrZbgd9ftJ+siqx2+4Z4hDDUbyg3DLuBhSMX4uPiwzkx59g5Va56Vy6IvwCj3oinyRM3oxtD/IawIGmB3bHGhYwjzieOKO8okoOSlSOj6DLdvjIjhPBFU1OIbX58KeVd3X0uhRbH+tTMp9iVt4sycxkmvYm/bPwLxbXFzIycyT+n/5OvUr9y6Jdelk6gWyApxSkcKD7ANUnX8PY5b7M9dzu19bXU1dfx4YEPuXf8vXx19Ct+s+I3RHpG8vjUx5kYOlEpFw1AYrxjWHz2Ynbk7aC4ppjRwaMZETjCrs35g84n0iuSvQV7CfUIZVTwKKz1Vh6a8BBuRjcKqwrt2udX53P54MuZGDaRnMocojyjCHIPosJsLyzRnGD3YC5NvJT/7PgPFZYKzo45W4U29hEsdRIEGHT2OTPKmVEoegZXgyuLRi1iavhUUopTSPBLYGTgSDxNnu13bkGFtYITlScc7ZbW5+NGimuKmT9oPot3L6bCUsGc6DkUVBfw5tlvsq9wH0IIxgSPwc3gxqPrH2VF+gq8TF48OOFBrh58NcMDhnOw6CBRXlGMDhrdLxP9FX2Xnggz+w7YhCa5pkpDnwLCPcMJ9wxnV94uFnzf9AZkTeYaPI2eXJJwCd+lfWfXZ1LoJJYe0oq9zo2Zi6vBlfGh40kKSOKh1Q+xOms1lyRcwocHP+R4uVbEMLMikzt/uZOPz/+4Q+oniv5HrE9sm3/bALcAzoo5y6EeQKPTs/r4ajt7hEcEj65/lNq6WjyNnrbQhMVzF7d6jr0Fe3ni1yds2z+k/0CwezD3jb9PqeT1MtWWOlwN9n8Dk15HtVlN9QpFTxHgFsCZ0WdyZvSZXTpOpGckc2Pm2j0PCESHXhZ5Gj15ZF2T0vCKjBV4u3hzaeKljArWokMs9Rae/PVJW25lmbmMR9c/ypJzljAvbh7z4uZ1afwKRWv0xJOBq5TyXinl21LKdxo/PXAeRQvSy9IdbCvSVxDqEcp94+7D2+SNm8GNm4bdRGFNIQLBgxMeZGLoRFt7D6MH9064lznRcwh2D7Y5Mo1UW6sdbIqBy4mKE3xz9Bue3vI0K9JXUFBV0Gb7scFj+cvUvxDkFoRBZ6DUXEq1tZp6WU+ZuQyJJKsii6OlR3lm6zMsS1nGsTL7umIHig44HPfb1G+VAEAfoLaZLHMjJhVmplD0C9yMbtw0/Cbmxc5DL/SEuIfw9+l/J8E3gR/Tf+TpLU/z9dGvya7IdujbqFjZnF+O/UJJbYltu6i6yOHFKWAXeqxQ9AQ9sTLzrhDiVuAboLbRKKVUTyI9jK+Lr4MtyjuKMnMZHx/6mAsHXYhBZ2B/wX5uH307vx/9e7saIo3E+8Tzzxn/JLU0lXf2vUNNXY3d/sZCiYqBTWltKX/b9Dc7ye6rBl/F/RPux9XgKDwB4OXixaWJlzIuZBzmOjNVFkcBFBe9C7vyd7Fk3xIABvkO4pU5r9gKrYa4O78mnQkUKE4t1ZY6XFpIMJuUmplC0W9ICkjir1P/yq3Jt+JmcCPIPYhntz3Lhwc/tLWZGj6VJ2c8acuXBAj1CHU4Vqx3LB5GD9u2h9GDGO8Y9hbutWvn7eLd/V9EoWhGT6zMmIF/AxuBbQ2frT1wHkULhgUMY2r4VNu2QWfg4YkPsyJjBccrjvPegfdYsm8J3i7epBSnkFeVZyfrXFBVwI68HRwuPoxO6BjqP5SHJjxkd44bht3AIN9Bp+w7KXqPoyVHHWoPfZzycbuSoOW15RRUF5BTmYOviy8LRyy023/DsBvsJJ6PlhwlpahJenRk0EiSA5tqJbjqXblzzJ3KmekD1Fjq7WSZQQszUyszCkX/wc3oxmD/wUR5R3Gs7BgfHfzIbv+G7A0cKz9GakkqO3J3cKLiBCMDRzIycKStjYvehbvH3m03L1vrrVySeAkmXZPC5fCA4XgZlXiLomfpiZWZe4EEKWXb8SiKbifIPYi/T/87h4oOUW4uJ84njkS/RL5N/dbW5ubhN7Mzfyf/2KwVzJwTM4cHxj9AubmcP6z6A8fLj6MTOm5NvpXrh13P/Pj5DPYfTGZ5JsHuwQz2G2z3JkYxcLHUWxxsEunU3khWeRZv73ubjw99jEQS5x3HX6b+hakRU8mtyiXQLZDntj3nEKrYvKZMuGc4z816jpTiFKqt1cT7xttqICl6l2onYWZGvVqZUSj6K9Z6q4Ps82C/wewt2MszW5/BXG/G39WfZ2c9y/Oznudg8UFtXvaJJ8HPfl621FvQoePusXdTZi7DoDPg6+LrEN2hUHQ3PeHM7AP6dHGd/kiluRIPk+ZEWOosGPUNNTfqzNCszkegWyCBEYG27XpZz8UJF/ND+g94mbyoqathR94O2/6fMn5iathU1mevtz1g1st6Xtv9GuNCxjElfAojg0aS5J/UdE7FaUGsdyxRXlHU1dcR4xPD4eLDRHlGEe0VTbW5Ehe9Kzq9fcjR7oLdLD20lCT/JLxN3uzK38Vb+97in9P+ycgg7a3eUP+hdmEInkZPB2clxCPEaQikonepsdRh0qucGYWiLyClxFpvtb8319eDrAd924931jorep2eKK8oJoZM5GjpUQb7D+ZY2TEuiL+Af23+l83JKaop4uG1D/P+ee8zI3JGq8f0MnmxOnM1qzJX2dmfm/Uc0OLZRaHoRnrCmakDdgohVmKfM6OkmU+CfQX7WJu1ljWZa7hy8JVkV2azLmsdU0MnMt9zEHFrX4Ah82H4xeAfZ+snpWRn/k4+PPAhedV5PDLxEaqt1U6T8zae2EhOZY6DPbsim6zyLFZkrODHjB+ZEDqBCwddqMLMThNCPEL4+7S/80P6D+wp2MNFgy7izKhZLEv5hJ+P/UKcTywXD7qQ8WGTbH1yK3N5cMKDbM3dSnFNMTePuJm00jR2F+zmpZ0vMSdmDpcNvgx/V39+zPiROJ84FgxbQJxPXBsjUfQVaix1DmFmRr2OGotSM1MoTiWHig7x2eHP2Fuwl/Pjz+fMqFmEFmXAr69BRS5MXAjxs8DN165fYXUhazPX8unhT4n3ieeKIVdw7/h7+SnjJ37N+ZUZETMIcAtwWK05UXmCwppCgtyDWh1TaW0pW3K3ONhzKnN4d9+7fJ/+PeNCxnFRwkVqtV3RrfSEM/NFw0fRRUqqS3hn3zt8n/49c6Ln8OnhT9mZvxOAPQV7WOkTz+uhwwj4+XE4tgEufwsaCgvuK9zHLctvsVXd3Za7jadmPsWksEnsLthtd57RQaMxW820JNg9mKe2PMUvx3+xnfPnjJ9585w31Vvz04CMsgwe2/AYaWVpgPb331uwF3ejO7sLdrO7YDerMlfz2pkvMTxkNABxPnHct/o+auu09xg78nZw+6jb2ZyzmT0Fe9hTsIep4VPxd/Un0S+RnMoc7l11L++d9x4x3jG99VUVHaTGmZqZXkeV2dpKD4VC0d0cLz/Owh8XUlSj6SrtLthNWslhHti7GmNWQ4pyxnq4+FUYfY1d3y+OfMHz258HYGf+Tn5I/4F7x93LG3vfALR5PsoryuGcQW5BeBvbTuT3dvFmZOBINp7YaGf3cfGxyTrvKdjDjxk/8va8t22iLwpFV+kJZ2YZUCOlVmJWCKEHXNruAkKIdKAcbWXHKqUc3wNj6xdIKUkrTSOvKo8f0n8AtOrrPx37ya5dSmkq26fcSGRAPIO2f4Cp8CiEjwZge+52zos7zxYmZJVW3tr7FguTFzLYbzApxVrC9aigUXgZvbht9G3sLdxLYY1W9PCaIVcR6BZoc2QaySjPIK00TTkzfZDimmIOFx+mylpFrHfb9WIaOVx82Cb4MNh/sF1V6SPFR2yOTCO/5vzKolGLWHl8JaC9iUspPWJzZrIrsm2OTCOfHv7UTphiQ/YGFo1axKu7XrU7l3Jm+j41lnqMKsxMoehVjhQfsTkyjXx8+DOuHXIVsVnN9JbWPQvRk6HgMOj05AbE8uaeN+36VVmrKKixT3H+Lu07bh91O6/ufpV6WY+7wZ1bR95Kbb393N6SSnMl58Sew/jQ8VjqLOh1eow6o5ZLI3TUS20FN6sii9SSVOXMKLqNnnBmfgbmAI0lZd2AFcDUVns0caYSDoAtOVu4/efbeWLaE+iFHqu0IhBO2x6uyuG+lLd4YtKtXKB3sbWK8Ixgefpyvjr6FQDeJm/uGXsP6WXpDAsYxlnRWtHD9LJ0DhYf5BKveD4MOpNjrh54Cj1xleVk1lkQCIflZp1OFS7sa+RV5fG3TX9j1fFVALgb3Hlt7muMDh7dap+deTu5f/X95FblAlqOzD9n/NNWAFOv07fatzk60dTOVec4pRh1RtsKYavHUNdUv6DaUufgzBj1Oipr1cqMQnGqaHlPBtALvd1crBldYO0zsONdAHSz/4TByRzd8vliX+E+bhh2A4tGLsIqrUgpkfWy3aLFjQ7Lm3vepMqqpU5PCp3EhYMuRErp0Fah6C56qmhmoyNDw89KU7UDSCk5XnacVcdXoRM6fs74mUsSLwFgV/4uZkTYJ96NDBxJWmkaOqFjdUU6hw06m9JUuaXcLpyszFzGquOrmBQ2iS+PfMkru17hlV2v8GP6j5wbMxe+voewNc8yacXfGL78cdzXPkN0ZRmXJFxid87hAcPt3t4r+gb7CvbZHBnQ3rY9u/VZKswVrfb56uhXNkcGNMd2bWaTFHOibyLJAcl2febGzGVHbpOARIh7CEN8E23byW6hDjKclw++zLaSA3Bu7LlszWl6exjuGc5g38Htf0lFr+MsZ8ZF1ZlRKE4pfq5+RHhG2NkuSbwEN9HCURl/C+xdZtsM2ryY3w+70f5YLn4Otb2SA5PZkL2BvYV7qTBXsD57Pa/sfgVDy+O3wMXgwtdHv7Y5MqCt5suG/xoZ4jdE5cwoupWeWJmpFEKMlVJuBxBCjAOqO9BPAiuEEBJ4TUr5evOdQoiFwEKA6Ojobh5y75NTmcNnhz/jw4Mf4ufix22jbuOro19x0aCL+OPEP7I1dytzoucwM3Im23K3Ee4ZjqXewrep3/LAhAf4+ujX3Lj8Js6OOZvfJv+WnIoTDuc4WHyQMI8w3p73NsvTlmPUGzk75mxGmAIgb59De9eiVG5PvJLxnpGsK9jFaJ8EpkWcQaBboEPb05W+cl3mV+c72A4WH6TCUoGnydNhX7WlmoNFBx3sh4oP2X6O8IrggQkPsD57PSnFKSQHJjMpdBJ7C/fiYfIgyjOKmZEzGBI43NYnuiibZ6b+lV9yfqWopogZYZNJMvjgMexmdhTuZqp/MqMipnGoKktzhPyHcEbUGUR4RTiMRdE1euLarLHUY9DZv8VVYWaKztBX5sz+TH5VPhfEX0C5pZwTFScY4j+E1JJUyobMI6j2PqjIh+GXwJ6lYGn2+FWRxyi/oTw6+VE2ZW8ixD2EmZEzCfUI1Z4zcrYyPHA4wwOGc7TkKN+nfc/23O1MCpvE7KjZlFvK2xxXhbmCwyWHndr/NeNfrMlcQ3JQMjMiZrQpJKBQdJaecGbuAT4RQmQ3bIcBV3Wg3zQpZbYQIhj4UQhxUEq5pnFng3PzOsD48eMd11j7OY2rJQAltSU8t+057h57N89sewZPgycfzP+AOF9N8Wl6xHQWfLeAwppCFo1cxPPbnrfpuH925DMKqgu4aNAFDuc4I2ImAW4BBLkHMS5kXNMOa62miLbvM/sOvjGEfH4HFxQc5AK/OCj7GsTzcOsq8I/tgd9C/6OvXJex3rEOtrOizyLANcBpezejG2dEzGBPwR47+5TQJmWy7Ips/rDqD9TW1RLmEcamE5v4NvVbRgWNIrMsk515O/ng4Ad8NP8jBvtrKyv7/UP43cq7CHIPwtvkzU/HfmLh4Ku5/dgBri44DMWfQsAgYm/4inNiz+m+X4DCgZ64NmssdRidCAColRlFR+krc2Z/JtLgyf27X8PHxYcgtyDWZq1lsO8ggjwj4Kw/NzXM3w+7mgpi1g49nw+Or+DLI18S7xPPjrwdfHToI16b+xrXJV3HdUnXAbA7bzcv7njRtsLy87GfKa4p5uKEi9scl7+rP2dFn8WXR7+0syf4JTApbBLz4+d3zy9AoWhBtzszUsotQoihwBBAAAellLYqe0KIuVLKH530y274N08I8TkwEVjTst1ApLC6kKWHltrZJJLi2mL8Xf25e+zdhHmGQVUxnNhFRPkJnpr2BHuKDyEQLBy5kC25W9iYrSmIrMlaw3VDr2Nh8kKW7FuCud7MpNBJhHtGUFqejZ93pP0ADC4w649QnqOpopk84Mw/QUUODD0PykbBtiVN7YuOKGemjzE8cDgPT3yY57c/T7W1mgkhE1g4cmHrmv51Vma7RXIk9hyWp69AJ3RcmnAJk0TTKk5GWYZNEKLxbZuL3oWJYRPxd/PHVe9KblUuqaWpNmfmYEU2Nw6/EQ+jB5Z6C/MN8/k542eu9AonaH/DDU5nhKxtUJoFnkEQNhp81MpMf6C6lTozyplRKHqQqmI4sROK0sAvmkQpeHLEIp5IeZ/DJYcZ7DOIx8PPxrs0G7yaJdUnXQg5+2D3hyD0HJ96G/t3vsDvx/yeKksVJr2JktoSjpYcZVIzif3CmkK7UDGA7XnbKTOXtSn+Y9Qb+U3yb8ipzOHXnF9x1bty19i7GB4wvNU+CkV30BMrMzQ4L3tb2f0kYOfMCCE8AJ2Usrzh57OBv/bE2PoiLnoXgt2DHUKF4nzieP+894n0igRLLWx8CdY+TUXiXL4ODeeLzKY8hKuHXE2hXyEpxSl4GD3YkLOBNcfX8OTMJzlScoRd+btYfexnrk241PkggobAtR9D6THtIfO7+6EkQ9sXOQFGXws7P9C2nYQtKXoXD6MH1wy9hukR020rKc7Cy2zo9CTu/4bHTO4smPoPdFKSsOcL3GqNMPQC2zGb4+/qz5nRZ/LHtX+02YYHDOfcmLNt25He0bxz8F0yyzMBLSn1jxP/iOu+hv/lPYNh8Dnw/uVNB46ZAZe/CV5KIa+v41Sa2aCjVtWZUSh6BmsNbPiPpkzWgHHsjZxbXcTIoNmUu3gSWnAU35/+CTd+bd/XNxrOfw6m3Q1Ch5vJnQsGXcDTW5+25bAM8h3EtPBpdt1azv0ArnpXXPTtCtMS5xPH82c+z4nKE7joXYj0ilTJ/ooepzeuMGeyXCHAOiHELmAz8K2U8odTO6zew9PkyV1j77L7Hz7SM5LxIeM1Rwa01ZCGySx10HQ7RwZgWcoyZkfNBuCaodewPH05aWVp/HvLv8muyGZj9kbuGPFb3N39Wx+IQIuvzdysVRBuJHML+MVqPw+/RHNmyvO6+rUV3YwQgmjvaBL9Ett2ZLTGMOFWPHd+yKj3ryP5gwW4Hf4Jhp5vaxLnE8dFgy6ybc+Lncf7B963O8y+wn1U1BRD/iEoOEJhTaHNkQGok3V8mrIMYqfDjPth9v/Btrftx5KxFnJ22Y5BnVLG6qtUm52vzKicGYXiJLFUa3NfYStzX+FRWP+8vW37OzBoLhFWC0MtZnzrrDDzfghOgsJUyDsI5oaVFaMrBA+FoMEgrXxw8AO7ZPyjJUcpri22O3yCXwIzI2ba2e4ae1fT80g7eJo8SfRLJNo7WjkyilNCj6zMtINDjKyUMhUY1Qtj6TNMDJ3Ie+e+x8Gig3iYPBgRMIJo72bJkeZKm4NRKR0fHKzSSrxPLHePvZs1mWvIqcwBtMTwsyPP4MqwGSR5D2p9APkp2mpM2mrNWZm0SPs5s6Gar0cQXPYmHNsEr04D31i45BWI6YjitqJPEjkefvMjZO8CnR7Cx2g3vQa8TF7cM+4ezo45m6zKLBK94/nw4IcOh6mtKYF3J4PRncpz/89hf151PjUl6XitfR4CEmDaPfDL37RrupGCw/DBlaAzwNS7tevPUyWI9jVqLHUEedm/nXXRK2dGoTgpio/Byidgz8da+O20e2DS78CjmchObbn9y0WAwEQwGLV8mOpiCB0Jk2/XojdW/l1bzUm6EOb8BQKa1EerrVUUVDtWv6ioLbPb9nf157Gpj7GvYB85VTkM8hnEsIBhyjFR9Fl6w5lROMGgM5AclExyULLzBn6x2oNg4RFiqsvxc/Gze5uS6B1HrDTw8I6XqGvm7FwaeRaTlj+BMXs7TPk9zP0btKzpYa2F1U9qzguAuQLWPq29Rc/couXUhCbDe5dBTanWpiQdll4HC9eAr2O1YEU/ITRZ+7RCoFsgM6O0N3Q1lZpjvDxzlW2/UWckziNcu9maK0iy1jnUJro8YhaB277QNgqPaCETI6+GrQ3F2wwu2jUnJdRZtGsvNBmGX9zNX1bRVWqszldmaq0qzEyh6DR7PoHdDfmydWZY85TmmAxrJuBj9AS/OC2H1TcaSjNhzPXw5e3anAmQsxu+e0C7F1s1MSAOfAX+cXDW47Z7foR3DOfGnssXR7+wHV4v9MR7xzkMLdg9mODo4B740gpF99MbbnZ6L5yz/+MZDFe+A0Pm8//snXd4HNXVh9/Zvuq9d8lFLnI3xqabYnog9E4IHQIBQifU0AIhEBJKPpJACBjTezEGAy7YuPciy+q9t+073x9XWmm9ki3Zu6r3fZ597Lk7c+eOfXdmzj3n/E7y2jf5R97NzI6fhVln5vjko3hq0rWM2bGYv895mJzwLIL1wVyccQpXuIOFIQNCraytBopWwpf3wPIXYccXsPkD2PGp7zmdVpGcfcmHwv3dach00l4vcmwkowKTpYnfpZzIORmnEKQLYkLEWF6e+yfGVnbJOU/a8AEvzH2M9NA0QvWh/Db3Us7RRqE0FHZ11FwuwiEMweLBveApWPMv75Pt+W5gLkrSL6wOt4+amV6GmUkk/cfWAlve9W0vWAp7voePboTlL0BzKRz/IBx5O8SMFZ7r6JwuQ6aT8nXCY9OdLR8Iz00HZkMwl4w7j1+P+TXB+mAywzP581FPMS12mv+vTyIZQALimVEUZS6Q0b1/VVXf6Pizlwx0yQGJnyRCvSx1TDJH8sKYU2ip2UHEyn9g+t9FAMxb/18mnfwEluQZxL5/DdqabrVEEqZAYwn85xTQ6uGYe2HhhTDhTHGTrPSW6SVxChx+M5jDoWqrCEVyd3tp0erB3LP0r2QEYgwl7Yt7uDdlFtdO/QNBjWWEvfNbOOJWzy76MSdwzCd3MTX7aGyxU4hdtRBN3gVgDBUPbwB9kDCUp18u5lPRCqGk1539eIskg0dPamZGnQar9MxIJP1DZ4akGVC93bs9Ig3euUR4qwHOfAm2fQi7vxHb2z+FzKPFc3tbNwnk0ASwNHr3lTgVjN75k+NiJ3NfxFguG3cBwbpg4sNlZIVk+ON3Y0ZRlP8C2cAGoPPNVwXe8Pe5BhOX20VRcxE1lhriguJID0vvezxpez3U7RYrK9FjILjDIGiugPo94mXPHCncyaZwsdqiN4t9DGYwCHWz4MqNBNfvhc1dFX5xWgn/4i7CL/1IKJD98JTITTCFw+E3ChEB1Q3Z87vqyuz8QoSfLXm4q8DWuJOFipk5XGxHj4HjH4Fv7us610lPiBUiydDA1gZ1u8T/d2Rmn+SOG6wN7G3ai1bRkhGeQbgxvPednXY4/Cb0i+8noXPuTDoPjOFw9F3C2NWZoKWciA3dcms2vAXjThHhFIoCJz4GlibhmdHohDhAwffCawgQmwtZx0DZOnC0Q1Q2hCX6DEcy8Ngcbh81M71Wg93pxu1W0Wh60neRSCQ+aHUiP2b3V9DWkceSMAlszV2GDEB7bZch08neH+D057uMGY0Ojn8IqnbAMfeA6gJrC+SdT72jjcK6rV73eL3eSFb0eCSSkUIgPDMzgQmquq8PdOTgcrv4pugb7l92P3a3HYPGwONHPs4J6Scc2KBpKBTu46JlYjv1MPjVy+Kl7e0Lu8K2JpwpblBbP4AjboO5vwNzhPjO3gbr/guL7xff7YvbCQXfwbo34Pz/ifCwtjphyHR6VrQGkSsDXXkKc2+GkARhPMVN8E5C1Blg5m8gbY4IEwpPEaFCWpl2NSRoq4UfnobVr4jt0EQhtZ2Y1+shhU2F3PXTXWyr2wbA3MS5/HHuH0kO6cUIUl1gCBIePUe7EIUIihHzqmpLh7fvPt/jXDY47HqhlBaRJubbW+eK8AdFI3KzrvxSqPZo9RCeBsufh/X/FceHp8GFb4sHvWRQ6UmaWaMonrwZs0E7SCOTSIYhiXnw2yXCO6M1QFgyvHqM9z7dDZvuGELg2PvBZQV9MISnw+4lXaFrUVkUTr+Qu5Zc77nHz0uaxwOHP9D7PV4iGaYEImdmC5AQgH6HDMUtxR5DBsDutnP/svspai468ME7v+wyZECEdpWvhT1LoKW8q33bxxDbsXLy07Miwa+Tik3wzb3ipdBl9zY6ACb8SsTcttXCjs/FS+eSB2Hvj5At5JvZ851IsDaECC9MbC6sfR1SZkPqHN8+QbzIpsyECWdA8vQub5Fk8KnY0GXIALRUwLcPC8PX1uIbXw18sfcLz0MOYEXFCpaXLRceGFubz/4YQmDFi8KD9+OfYdVLULZGGDIg5mNUhkjo7860SyEyC7KPFYbJR9d3xXGrbtFfey2MWwA586F+d5chA8LA//HPXca3ZNCwOd0+YWbQEWom82Ykkv4TmSHCxtLnicXEqReJ5+/40yB5BjSViGdyd+Initya7x+DH58Rfxav9M7Bcdn5fJ97/PLy5awoXzEglyWRDCR+W1ZXFOVTRDhZKLBNUZTVgOftQ1XVM/x1rsGmpr3GY8h0YnVZqbPUkRnuqwrixZ5u9WGyjhXSxiteFIbB8Q/B+jehM8/FUi9Czuxt0FzWdVxzWZeHZdXLwq1cuUmsbKfPBYdVVFg/8TFhPH11l3BnV+8Qif4nPAK7voHgeJj/oHhxNEfCgifFi6XWCEf8Thg2igwbGRY07CPEoNFB5hGw+EEo/BHGniyMihgRFuhwOfip7CefbtZUrOa8PWuEwT3rt+KBGtKhaGNtgNquZH+iskW+Syd6s1hhPP4hKPhBGCjZ86FhL5SuEp7EsScLr+NPz3ifuKmbIV+72/f6ipaJeHBZWHNQ6ckzA8KYsThcRA7CmCSSYYu1CXYvhhV/A2OYCAVPmS2Mme2fiHDhcacKD/j2T6BoOaTOFvfVhRd29WOO9BHjsceO46fajT6nXFO5hnPHnhvoK5NIBhR/xgg9c+BdRgaxQbGYtCasLqunzawzE2vuQ12MnBNg99fixS99rtCE76TkZ6ELv/iPYjsouqsWR/ckvfBU8bLqdoocl8V/hORZcPoL8N9fQXudeKFc/ECX0VO5WaihFC2HJY/AmX8XK+mf/76r38KfhHHz7YOw51tRg2Q/YUqSIURnUdNOpl8mQhHr94jtmp1Cxe6idyAoEr1WzzEpx7CldovXYYeZE2DFcyK04bPfi/k392bxZVCMEKHo9MRUb4exJwmvEIi5qNXDV/dA0nTxgF35olh13PuDGEPNTrHKOP402PFZ14kjuhVjix3ne32Zx3aFWUoGjd49M1rpmZFI+svuxfD+VV3bRT/BGf8Qua4g7rF7f4Tj7odtH4nQ7l1fQ9pc79oz7fUQke7VtaF6O8eMuYKtdVu92mcnzA7QxUgkg4ffwsxUVf1BVdUfgFM6/969zV/nGQqkh6XzxJFPYNaJMCuzzsyTRz7pXeSyN8aeBDknCpfyri+9v1NVcfOKSIe880U4mUYLx94nJGw7SZwKpzwjkq1BrOjMvUms4pz4J3Hj05lEUnZYUtdxWz4Q3pcTHoXkmaLeh9f53cLrY44UalNV3jdByRAmaarIq+r0pIWndhkynZSu8mpbkLmAGXEzPNvzk4/i8IZq7xjt5c9DS5X4e1CkSDoN6fCOtFbCmJOEEMTRd8Exd0NkNsy4EirWi9DJkHjIOrpLyQyE0Z48XfxdoxMexLhu+TDJM2D2tV3XEj0GjrzNN3xNMuDYnD17ZgwdnhmJRNJHHO1isac7qgrVW8Uz+qg/wLH3wpgTRZRGcxnkfwuNRWJB9Nj7xP0TIChKCPbMuKKrL2MEJ2eezPS46Z6m+WnzOTzp8MBfm0QywAQie/sE4K592k7uoW3YolE0zE+bz7unvUutpZaYoBjSQtNQ+hKSFZkGv/4/oR3/dQ/J0uHJcOFCIWXbVCpeEKNyQN/tRU5vFCFDCZOhtUok4ydOEfK2Wz6A/A7lE61ehJR9+7AwTgzBYjW8aDlkHyOMoH3RGYXHBkTSv2R4EBQlHm555wlvSuf/4b5ou/5P08PSef645ylqLkKjaMhorCDkzXO89zeEdD0wQeRMXf0dNBaDKUKEfv30Z7EyCMJDdNh1wrhR3cIQWvMvb2NcUYS35sovRR/RHdWsOwmOFZ7FaZd0qJlldYW6SQYNVVWFmlmvOTNSnlki6TOKVihBdscQIsR3Pv2diLwAoewYmeW938a34apvhSBPe70QVkmeLj4zfyNCzaOySA+J5YXjXui6x4dlEGLwlmqWSEYC/syZuR64AchSFKVbtjqhwHJ/nWeooCgK6eHppIenH3jnfTGHi88Rt8LepV3J2YnTRPhNcIxQJ7G1iJtbd0PG1ipWaUyR4sWyO+UbugwZEC+0a/4FuaeLSsN558H3jwvDZs2/4eg74a3zuvY3homXS3urSERMnNL/a5MMHnpTV30WS4NY0esu6TntUh8p7XBjOHmxHYaGahBzr1MmFETYoVYvjBdzlKhZEJ4iPi4nfHJTlyEDQq2vM6dLa4DSX2D6Fd7hlDOvEuFqelPv12IIkiGOQwy7y41Wo/Qov2zQabDYpWdGIukzOiMc8XuR6zL+VPFc1hhFiFmnIQMi0X/Khd7HZh8nFj51JvG8Du5Y7DEE+zy3ve7xEskIxZ+embeAL4EngLu7tbeoqlrf8yGjnLS5cMWXkL9YvNwVr4B/nSQKY255XxTHCk+B+Q+JOh21u+Dre0VcbfJMUTk9pStMiPZa33PUF8CRd4iX3M3viRsmQOkaIYl7xecibtccIYypvT/CgifEzVLWkBm+mCPh1L+IxPmy9UICPH2uMBJ6I3YsXP6ZCA9rroCxC4RB8t+zhOJe5jFw4qNdBpPDInJg9qW1Wsh3l6yCqReL8578NFRshPTDxbzfnyEjGZJYHW6MPYSYgVQzk0gOiugcoT666mWRR3vmP+DnF333c1jhtOeEsE/CVMiYJ4RSvviDqFmXe4bwzMeOHegrkEiGBH4zZlRVbQKaFEW5cd/vFEXRq6raS9zLKEZn6Hi5mwPfPQar/ylWzzcugh2fCK9MUym8/xu45AP47DZoKBDHlv4ianVcs1S4mEGE6+xL7pkQlgIfXuvdPuUCMIWJgoUZR3S1Zx8TiCuVDAYRqRBxoe+q3v6IyxUfEF6WV4/pklEu+B4WXQ6/+UqEfZlCxYpi+TrvPlLnwFd3C9nwtf8WYWoLnoRpF/vjqiSDhK0XJTOQOTMSyUGx6wtRpwtESO2e74RS2Z4l4vnvtIr6XuHJMOYEEUIGIp/1f+eIeywIcQBbC5z3hvCeSySjjEDkzKwDUoEGQAEigApFUaqBq1VVXRuAcw5vWmu66mpkHw8r/yZyBlqrRO6MvV2swkw5T6x6r/mX2Le9Dur3dhkziXlw1qtCitnSIIQGjr1XrNIfe5+oV+N2ihvi+NMG5VIlw4j6vV2GTCchscKrV7dbFOaMzBBiFVveF0bLtEvAUgeR6cKTCKLw65zrITp7wC9B4j8sDhdGfc9FMQ1aacxIJF40FIlFx+YySJoGSTPAGNz1va1V1HbrjjFUSNePO1mItZgihLpj+z7BLXX5XYZMJ3uWiHP1pAYpkYxwAmHMfAV8qKrq1wCKopwILAAWAf8ADgvAOYc3BrMwSFqrRDXfcafAtw91fR8zBk54DL78g1AsmXIBbFwovuuexK83w5TzhQva0S6qCRs6bp5H3gGTz+1Y5Un3TriWSHpCv09IWmgCZBzpXd8gfpLIyZp3qzCUd3wmQhQt3R6+4SlgCB2QIUsCh9XhxthD8j90GDMyZ0YiETSVwTuXQmW3Oi9n/l0s9nSiNYpoik6pexAGSlu1iNToJHYcnPi4d/89ifeYI33v2RLJKMFv0szdmNlpyACoqvoNcJSqqj8DUlt1X9pqoXILzLlRJFrX7IRV//Dep3Y3WBuF9G5TqVB3CoqGX70sjJPmSrGKXr5eeG7CUyBmbJchA6DRQFSmiNGVhszIxO0Sc6Vio1AZA2gsEfOiubznY+xtULkVqraJuGyXs6sPvRkm/bpr34lni1DI7lRtEfLhPz0Dy/8KtmYhEd4pIqDRCblQqYw37LE6XBj0PT8y9DJnRiLponKTtyED8M39wsjpRKcXJRW6GyD6YPj5Je/janaK53934ieJnMbuLHhShBZLJKOQQHhm6hVFuQvocB1wPtCgKIoW6FW7s+P7NUCZqqqjIwaqYjN8+0cRJxueCqc9L9zK+9Z/AeFyXvtvmHeLkGo++Wn44g6xWj7pHFjWUegwMhPO/bdwa0tGD9ZmEX74/Z/E6l7SdDjhYVh0mQgVC4kXwhKZR3Yd01AsCqtu+0jIJc9/WBz749Piz+QZMOtqkUPjsAqVnFUv+547LAXO/j9h1OhMQvr72HuFp0ZrFMp5408dsH8KSWCwOlw9yjKDzJmRSLzoLHbdHVszuGzebcGxQnCnuVzcg1NmCal7n2NbvbdDYkWR7IoN0FYjPDxS/VEyigmEMXMR8CDwESJnZllHmxY4r/fDuAXYDvTgPx2hbF4kDBmAphL4+AY4+RmY+CuhPNaJ1gAavUjw+/5xuPxTePNscNrg8Bvh+8e65J0b9sKHN8CVn4vaI5LRQfl6+PbBbtvrREG2mLFCVay1Ct69DK75sWv1bvvHwpABMX/cDjGXOilbK4xluwVsTaBohGpO5zEgvDeR6UKxDKDkF/j5H97VqY+7v6vQpmTYYnW6excA0Gpol2FmEokgNFEs7HSqh4IQ4zFFeu+34S344cmu7cSpooTChre62nRGcY/1OUc8hJ7k12FLJMMVvxszqqrWAjf38nV+T42KoqQApwJ/Am7z95gGjfKNsOVdqC/syGU5UkggA7TViYS9fSlZCSmzISRRGDsRqcLzsvx58b3qFjU/nB0rPE5rlyHTSc028fIqjZnRQ90e37bCZTD9MmHMgEgibS4Tc8plh60fdu2rNYiVw33Z+xOc+qwo0mYIhrEniT/zvxXJ/xPP8pYET5oKF78H3z0q5uCsq0WOl2TYY7H37pkxyjozEkkX7XVCxGfrB0IIYMwJEJ4mwnK3fiS85YddIxaUulOxQdyztQbY+WXX87+xFFb9U9QNyz4Wxi0Q4eYSiQQIgDGjKMpY4A4go3v/qqoet5/D/grciSiw2Vu/1wDXAKSlpflhpAGmahu8flrXC+KOT+H0v8GMy8S2KVzUdana6n1c3AQoXS3yFi5+Txgx39wn8iE6CYkXLmlVFas/+xKa2GU0SQLKkJmXYUm+bXETRJ2hTvRmCIoRf9caRO2Zsg5xQZddSIHuS/xE2LRQeBD3fCcKcQbFiXjt5lJR9+iyT7r21+ohZz6kzhahaSGx/rtGSb/w99y0Ofcnzaylvs3W43cSSXeGzD0zkJjC4b0rIOtYca8s/AkOyxMRFZ0qZLU7RShv9XbvY1uroHiVWDhqqRDP/1+9BJ/eJL7P/0bUoLvgTZE7K5FIAiIA8C6wHrgf+EO3T48oinIaUH0gyWZVVV9VVXWmqqozY2OHwQtSxQbfle4fnhQJ+gBanViBCUvu+j5xmlCB2vK+SCBsrRYr3Uo3OdQZV4ik6hP/JAyavT95K6TojHDmi8KgkQScITMvk6YJL0knpnBRXTr/W7Gt0cKZHYml+d8KeeWUmRDRLXzB1iKU9DoxRwqZ0D3fd7Xt/gai0mHd65C/RHhe4if5jscYKg2ZQcbfc9Nid6Hfn2dG5sxI+sCQuWcGkoQ8mPEbca9d9zq4HCK3Jfd0OOZuOPouUVMueab3QlTiVLHI1FgE694QBa0nnQN1Bd79F68QC54SiQQITM6MU1XVlw68m4d5wBmKopwCmIAwRVHeVFX1kgMcN7TZN/QLvPMIQCT7T7sUUDs8LW6RyN2J2w6rXhEvpapLJFPnfwvj7aJWTPpcaKkSrujpVwjXdlRmz8UzJSOb0HhRIXr2tUIIIjobQpPgt99BS6UQmLA2wj+PEUYLCGP6sGvB2iTmX3MFZB4Lc28WCaxaA7xzie+8TZkFFy0Sxk7seFF8VTLisTpcGPdTNFPmzEgkHQRFwvw/ivwXSyNEZYu8xsKfxGIlwOTzROL/hF+JxR9FESFpFRuFt7suX0RYhCbCq0f3cJIe3jEkklFKIIyZTxVFuQH4EPDEHaiqWt/Tzqqq3gPcA6AoyjHAHcPekAHhUTGEiBfLTo66U1ROB3C7Ye2/RL2YnPki9yX/WyHRrA8CVIjIELG2PzzV1UdEuniB1JulYpnEG3MkpB/u3ZY0VfzZVgfvXSkM6PGniofo+v+KYqqd80vRwBVfdPVRXyCMoOpuoZA5x0PcRAiNC/TVSIYYFocbnUbp8TujlGaWSLwxhUHCZFH0OjgaCn+E4p+7vt/2EZz8FHz2+642jQ6u/ApSZ4kPgKUJsud759imzJKLlhJJNwJhzFze8Wf30DIVGF3ZavETherY+v9BQ4HwwGQd2/W9o124nmdfLRKx9WbxYtneIBTKxi6A+Alw1B3CZb3lfUibI1zOUkte0l+sjSJx1GUXRnNEGpz0uFDXGX+ayL2aeaUIPeskKkuELG7/BEpWQ9YxIgxNGjKjEqvDhb4Xz4xRp5UCABJJd0pWwdKnoHYXTLlICKZ0x2WHgh/gwoWw9nURGjzzSkie7r2fORxO/YsoSLzzS7GgNOEMCI4ZsEuRSIY6gVAzyzyEY5cCS/02mMEmebrvjakTY4iQzf3qrq62ys1w7utCmrmTsGRxg5t5ZUCHKhnhBEUJQ3nzO2K7sVgk/1/8Plzwv96P298clowqLHYXxv3UmZFhZhJJB9Xb4Y0zwWER2z8+JRY0E6eKfNpOIjPEwuW4k/ffX1SGKLA596bAjFciGeb4XQBAUZQgRVHuVxTl1Y7tMR1J/pLuOCxCJWpfCpeJhOumkoEfk2TkYmmEre97tzksQi3nUKnZCVs+gG2feKunSUYUFocLg07b43cmnQabs9eayBLJ6KJ6e5ch08nGt2HO9SI3BkSphmmXdW134nJA2XrYtAh2fSPyYiUSyX4JRJjZv4G1QEcVPUoRCmefBeBcwxdFB8E9hOsowAe/FUl/5/+v52JZEkl/0RpEkqmlwbtdH3Ro/ZZvgNdP71LuC02Cyz4UeV2SEUW73UlUsLHH7wyyzoxE0oXe7NtmCIG0w+G65cJgicwUIWT7kv8tLLyoS3gl6zg46yVRwFgikfRIIKSZs1VVfRpwAKiqakG8oo9sWmugdo+3Gtn+0Olh3i1CMrcTY5h4GWyrBXOUKITYUhmY8UqGH/b2g58T4cmiiFt3YnMhMc9336YycR7nAeqGuN3wy/95S5C3lMOur/s/PsmQR3hmesmZ0WulNLNE0knCJHF/7c4JD4vFyfiJQpilJ0OmpRo+v91bQbLgOxGCLpFIeiUQnhm7oihmOnQDFUXJppuq2YhDVWHvj/DpLdCwF1IPh1P/LFRMDkTaHPjNN0Ku0dIo8miW/xWOux+KVsCbZ4kCmac8I+JqdYZAX41kqFK7C755EHZ9IebEqc/CmJP6Nycm/VrEaBevEiISaXMgPKXre3s7bPsYvrlXzMdJ58Cx9/Readrt8FY666RmV3+uTDJMsDrcvUozyzozEkk3zDFw4qOinldbjfBUJ0w58HGONrEgtC/7etQlEokXgfDMPAh8BaQqivI/YAlwZwDOMzSo3Q1vny8MGYCSlfD+NUIK90BotEI9au4tIgzou8fEqk3xz6LaOohqwO9eBlVyZWbU4rDAt48IQwbEnFh0KVRt6V8/xlChSHbMXTD1Il8jpXw9fHQdtNeLlcHNi2DlS+By9tyfzthRJ2kfxp/i2yYZ9ljsvdeZ0WkUUMHhknkzEgllv8Bb58GyvwgJ5i//AEseESIs+yM0AXLP9G5TNBAjZZglkv3hd2NGVdXFwNnAFcDbwMwOlbKRSf0e30S/mm3QVNr3PjQamHYJzLgS0ud568mD8P7U5h/6WCXDk9Yq2LlPypmqiqJq/qR6u2/b5kXQVt37MeNOgSPvENLOxjA46QlIm9v7/pJhy/7CzBRFwaSXimYSCSAWOVW3kF9u71jYLPgOGov2f5zeDMc9IAppKopQM73gLYifFPAhSyTDGb+FmSmKsq9+a6dMUpqiKGmqqq7z17mGFOYo3zZDMJhC+9dPZDqc/GdoLBQqJvve9MyRBz1EyTBHHyQeavsayP6eE8Gxvm1R2SJxtTdCE0R9pOmXC6O8e9iaZERhdbgw9CLNDGDSi1oz4Wb9AI5KIhmC9HRvDksCQx/eC2Jy4KxXRI6jIbir0LZEIukVf+bMPLuf71TgOD+ea2hQv1eEis37vXiRUxSRd5A4RSiV9BedXriTT30G3r4A3B2rnDkniD4lo5OQOFE0beGF3ebEiaKY6v5QVTFH22qE0RGZLsQDGouFFyU6G7TdXjyTp0PKbChdLba1BjjxEVHJen9oNBCZdvDXJxkWWBwujPqepZkBTHqZNyORAKKezNRLICxRbLfXQ8YREJPdt+P1Jog66JJ9Esmow2/GjKqqxx54L1AU5YSOULThi6rCrq/gg2sgNF6sSn//JxFuFhwjQm/21Y7vD1nHwdXfC1e1OQLiJ4vzSEYv2fPht9+J0DJzpAg72N+ccLtFxeiPrgd7qzjmzL/D0iehcpMwYuY/BDOuEMITIEQBzntdKOfYWyFmnMjhkkgQnpnecmYAjDot7fZe8qskktGEKVzkJP7whJBhDk8VAiwSiSQgBELN7EA8BQxvY6Z+D7z3G3C0w9ybYfEfu6QU22rhw2vEi2fnqkx/0eqEJ0Z6YySdaHVCzjNpat/2r9st6hV1yitbGuCjG2D6pcKYcTngm/sgZYaofdBJWJL4SCT7YHW49xtmZuwIM5NIRj1la+G7R7q2m0rg63vhwoUH/14gkUh6JRBqZgdi+Necaa4QhgyIl0V1HwWf5nKRtC2RDBbN5b51YqyNoN2n6GFD8YANSTK8EWFm+8mZ0Wlok8aMRNJzon/FBvleIJEEiMEwZtRBOKd/CYkT+QQg5Gn3JTgGgqIHdkwSSXdC4kGzj+PVEALqPi+b0gsj6QNut4rTtX/PjEGnwSLDzCSSnu+rMWPle4FEEiAGw5gZ/kTnwBkviryDHZ+JUDOl459Sb4YzXxL5BxLJYBEzBk77qxCoAGF8n/osbP+8a595t0LiAUQEJBI6vDI6Dcp+cgFNeq2UZpZIAJKmw+xrurZN4bDgCfleIJEEiMHImSkchHP6F41WJPMl5omQs7AkmHyeyJeJSBXGjkQymGj1MOUCoVDWUgXhSRA9BlIPg4ZCISwRMw4MQYM9UskwoN3uwqjrXckMwKjT0GaTnhmJhLBEOPoeGH+aUDKLzpYLRxJJAPFnnZmz9/e9qqofdPy53/2GDVodxOWKz77YWsDeJup2aPb/AiCRBAytXqiRdVcki8r0lfxsrRGexWAZAiHpGavDhWk/sswgwsykZ0Yi6SA4CrKO9m1vrweXE0Jl/RiJxF/40zNz+n6+U4EPevpCURQT8CNg7BjPe6qqPujHcQ0cqgpFK+HbB4WaVN4FcNi1Ui9eMjRpr4etH8JPzwrD59j7YNzJYOxnwVfJiKfdvv/kf5DGjESyX+ztkL8YljwipO8PvxnyzpNFMSUSP+DPOjNXHuShNuA4VVVbFUXRA8sURflSVdWf/TW2AaN6G7z5qy4VqVUvgaUezvhbz0IBEslgkr8EPr+ta/uDq+GiRTD2pMEbk2RI0m53YjpAmJlJp6VVhplJJD1T+gssuqxr+5v7RJjvzN8M3pgkkhFCQAQAFEU5VVGUOxVF+WPnp7d9VUFrx6a+4zM8Fc9qdvrK4W5+F5rKBmc8EklvuJyw5jXf9q0fDfhQJEMfSx88M0a9RhbNlEh6Y88S37bV/xRh6RKJ5JDwuzGjKMrLwPnAzYiaMucC6Qc4RqsoygagGlisquqqHva5RlGUNYqirKmpqfH3sP2DIdi3zRQuvTIjmGExL3tC0UBEmm97uFTbGSn4c2622YWa2f4w6bS02WSYmWT/DNt75qESmuDbFpbcVeZBIpEcNIHwzMxVVfUyoEFV1YeBw4H9viGpqupSVXUqkALMVhRlUg/7vKqq6kxVVWfGxsYGYNh+IGEyJM/wbjvpcQhPHpzxSALOsJiXPaHRCOlQnamrzRQOuacN3pgkfsWfc7Pd7jygmplJr5VqZpIDMmzvmYdK1rGiBl0nWj0c+Xu52CmR+IFASDNbOv5sVxQlCagD+pQBr6pqo6IoS4EFwJYAjC2whCXBua9D2VpR6Td+EiRNG+xRSSQ9kzITrloM5etEgc3kGT2r80lGPe198czopQCARNIrcblwxRdQtg6cVkiaCglTBntUEsmIIBDGzGeKokQAfwbWIfJf/q+3nRVFiQUcHYaMGTgeeCoA4xoYIlJlYSzJ8CExT9Y/kByQNpvzgDkzJr2WNpkzI5H0Tuw48ZFIJH4lEMbM06qq2oD3FUX5DDAB1v3snwi8riiKFhH2tkhV1c8CMC6JRCKRHAQWuwuD9gACALJopkQikUgGgUAYMyuB6QAdRo1NUZR1nW37oqrqJkDGYkkkEskQpdXmPGDRTJNeO3LDzNxuIbX/y2tgCoMFT0LanMEelUQikUjwozGjKEoCkAyYFUWZhlAyAwgDgvx1HolEIpEMLH0xZsx6LZaRaMy4nKIGU+1OOPxGaK2Gty8Q+Q/xEwZ7dBKJRDLq8adn5iTgCoQi2V+6tTcD9/rxPBKJRCIZQFptThLCTPvdZ0R6ZlQVPv89NBTBCY8KGd2YsaKC+6e/EwIainLgfiQSiUQSMPxmzKiq+joi9+XXqqq+769+JRKJRDK4tNmcmA/gmdFrFVxuFYfLjf4A+TXDhpV/h8LlsOAJ73ogOSfAjs+g4HvIPm7wxieRSCSSgNSZWa4oymuKonwJoCjKBEVRrgrAeSQSiUQyALTZXAcMM1MUBbNBS/tIKZxZsBSW/QWOvQ/0+0RKa7Qw/nRY+Y9BGZpEIpFIugiEMfNv4GsgqWN7F3BrAM4jkUgkkgGgzebEbNi/MQMib6Z1JMgzN5XCe1fBEbdDSFzP+2QeDSU/Q0vlwI5NIpFIJF4EwpiJUVV1EeAGUFXVCYyQpTqJRCIZfbT2IcwMwGzQDn95ZpcTFl0OuafvvwaT3gSpc2DrhwM3NolEIpH4EAhjpk1RlGhEsUwURZkDNAXgPBKJRCIZANrs/fDMDHdj5qdnARUmnnXgfdMOhy0fBHxIEolEIumdQBgztwGfAFmKoiwH3gBuDsB5JBKJRDIAtNsPnDMDI8AzU7MLfn4JDr8ZlD48HpOmQvU2aKsL+NAkEolE0jOBMGa2AR8CvwBVwD8ReTMSiUQiGWaoqkq7zUVQH4wZk15Dq3UYGzNf3Q2Tfw3BMX3bX2uAxCmwZ0lgxyWRSCSSXvFnnZlO3kDUlnm8Y/tC4L/AuQE4l0QikUgCSLvdhV6noNEcuJ6KWa+lZbgaM0UroGY7HH5T/45Lmga7voK88/a7W2FTIeuq11HVVkWjrZEGWwN1ljqabc3oNDrGRY3j3HHnMjF64iFchEQikYw+AmHMjFNVdUq37e8VRdkYgPNIJBKJJMC0WJ0EG/r2qDAN55yZpU/CpHNAq+/fcUnT4Mu3we0GjW+wQ52ljgeWP8CW2i1MjJlIhDGCYH0wScFJjI8cT7A+GKfqZE/jHm749gbOyjmLW6bfgiKLcUokEkmfCIQxs15RlDmqqv4MoCjKYcDyAJxHIpFIJAGmxeogyHjgEDMYxsZM1VbxmXdr/48NiQedGaq3QsJkr6+abE1c9uVlTIqZxFNHPYVO0/sjd2zkWOYlz+Nv6/+GS3Vx+8zb+z8WiUQiGYUEImfmMGCFoiiFiqIUAiuBoxVF2awoyqYAnE8ikUgkAaLZ6iSoH56ZJosjwCMKAKtfhbEn9d8r00liHuz90atJVVXuW3YfuVG5nDP2nP0aMp2EGcK4ZdotfLn3S5YUyTwciUQi6QuBMGYWAJnA0R2fTOAU4DTg9ACcTyKRSCQBotni6HOY2bDMmbG3CXnlnBMOvo/4SVDwvVfTD6U/sKdxD2ePPbtfXYUYQrhq0lU88vMjNNlkVQOJRCI5EH43ZlRVLdrfx9/nk0gkEkngaLI4CO5jmFmQQUuzdZh5ZrZ/CnG5fVcw64mEyVD8M7hFfWi36ua5tc9x9piz0Wv67+3JicxhatxUXlz/4sGPSSKRSEYJgfDM9AtFUVIVRfleUZTtiqJsVRTllsEek0QikUgETRZHn2SZQRgzLcMtzGz9m5B59KH1YY4EcxRUbgZgWdky3KqbKbFTDnBg75yZfSZf7P2CkuaSQxubRCKRjHAG3ZgBnMDtqqrmAnOAGxVFmTDIY5JIJBIJwpgxG/pmzAQbdcMrzKylCio2QOphh95X/EQoElo3b257k/lp8w9JkSzUEMpxqcfx9w1/P/SxSSQSyQhm0I0ZVVUrVFVd1/H3FmA7kDy4o+oZt1slv7qVH3ZVs628CZvD5bNPu93JptJGftpdQ1Fd2yCMUiIZ/jRZHKwramB5fi3ljZaD6qPZ4mDtIfYhgfo2O8HGvuXMDLsws20fCUNGZzz0vuImwt4fqGitYEvtFmYlzDrkLo9PP56fyn6S3pn9UN5oYXl+LeuKGmjuxStod7rYXtHMj7tq2F3VgsutDvAoJRJJIAmENPNBoyhKBjANWNXDd9cA1wCkpaUN7MA6+G5HNTe+tQ6b041GgQdOm8CFs9MwdYRgNFvsvLR0Dy/9UABAqFHHa1fMZHZm9KCMVxJ4hsK8HGlUN1t57PPtfLKxHIDYUCP/uXIWE5PC+9xHVbOVRz/bxmebKgCICzXynytnMyEpLCBjHor4a242tNtJCDP1ad8gwzDzzGxeBONO9U9fCZPgl1f5JP8jZiXOwqA1HHKXQfogjk45mn9t/RcPHv6gHwY5+PjznrmtvIkr/v0L1S02AE7LS+SB0yYQ322+2p0u3ltbygMfb8XlVjFoNfz1gqmcMjnxkM4tkUiGDoPumelEUZQQ4H3gVlVVm/f9XlXVV1VVnamq6szY2NgBH19pQzt3vLcRm9MNgFuFRz7bRn51q2efbRUtHkMGoMXm5J4PNlPfZhvw8UoGhsGelyORDSWNHkMGoKbFxgvf7sbq6PtL8vriBo8hA1DdYuPF73djc/p6U0cq/pqbDe0OQk19S2IPGU5hZk1lULMLEqf6p7+gaFRjKJu3vcuchDn+6ROYnzafr/Z+RZ2lzm99Dib+mpc2h4sXvsv3GDIAn22qYENxg9d+e2raPIYMgN3l5s73NlFUKyMnJJKRwpAwZhRF0SMMmf+pqvrBYI+nJ+pb7TS2e7uwVVWsAHfS/e+d7Klp8zlOIpH0TmEP4ZlrihpotvT9JXlPjW8fvxT2rw+JoKHNTqipb058vVbkiFh7CMEdcmz7CNLmHHxtmR5oi8xgTHM12RHZfuszzBjGrIRZLNyx0G99jgSarQ7WFjb4tBfUtnttV7fYfMLKWm1OauUio0QyYhh0Y0YRGZKvAdtVVf3LYI+nN+LCjMSFesdVazUKyRFmz3ZKZJDPcXkpYUSH+CEeWyIZJYyJC/VpO3ZcLBFBfX/pzE3w7eO4cXFEmP334jpaqGuzE9ZHz4yiKISYdMNjAWfL+5B2uF+73KHXcKxTe0iJ/z0xP20+7+x8B5tLvoB3EmE2cOx4X8/OuH1++0nhJgxa71edyCC9VyiaRCIZ3gy6MQPMAy4FjlMUZUPH55TBHtS+JISbeeHCaUQHizjoIIOWv5w3hey4EM8+uYmhPHBqrufGmRxh5tFfTSZ8nxeozaVNLPqlmHd+KWZTaaPPuZwuN1vKmvh4fRlLd1ZT3YPHRyIZSeRXt/LZpnK+3lpJWlQQ1xyZiabjfTA3MYxrj87GoOubohbA1LQIfntEVx+TksK4Yl4Gqwvr+XBdGeuKGrDYpZemLzS22wkz9z29MtSko2moyzM3lkBdvv9CzDr4zlbD2OZa4bb3I0khSaSHpfN5wed+7Xc4o9dpuPqoLE8enEaB3x6RyaSkMDYUN/DR+jKW7a4hKtjAc+dPIaRDxCIySM/zF0zDqNOwdGc1H28oY0tZkxQFkEiGMYMuAKCq6jLAv8tYAWJOVjSf3DyPqiYbkcF6MqKDvVbg2m1O9tS0cs3RWSgIFaB9DZG1hfVc++ZaalvtAEQFG3jlkunM6iYS8OPuGn77+ho6761HjYnhmXOnECdXkiQjkM2ljVz0z1W02IRxkRJh4vcnjOWm43IAqGi09Hulv83moqrZ6umjrMHCrqoWfv/OBs/v6vGzJnHh7DS/r6KPJCx2F06XirmPdWZACJ/Ut9kDOCo/sOUDSJvr1xCzyvYqSlU7it6EqbEEa6R/BUHmp83nP1v/w1k5Z8k520Fjm4MJCaEcnxsHQGFtG9sqmrni37949vnVtCSOzInh4sPS0Gk1WB0u7E4ntyzcwIo9Ig9Jq1H41+WzOHqczHuUSIYjQ8EzM+Sx2F0U1bVR22LDqNVg0GnQazVeD5S9Na0U1bczMyOSxjYbKlBQ28Z9H27xMmi+2FLpMWRAGDwfb+hKdq5rtfHAR1vpvkj04+5atpY3BfQaJRJ/UtVsoaiuDXtHwn1Dm52i2jZaOmR7O39T1S1WFv5S4jFkAEobrRTWtWN1uHG6VHZWtfLXJbuparJQVNtGax+kf9cWNbCyoI5mi7Ojjxb+u7KII3K6qrw/+tn2HvNzJF3UtIiFm/68PIea9DS2D3FjZtNCyDjSr12ur1pHTmQOluhsQss3+LVvgAnRE3C5XawsX+n3vocj7XYnz3yzk4nJ4RyRE8OROTFYHC42ljSi1XTN14/Wl1PZbKOiyYqiCDGf7ZWtHkMGwOVWefDTLTS02ShvtFDS0C49NRLJMGLQPTNDnfzqVh7/Yhs/7a7lj6dN4OMN5awpaiAzJpgHTsvluPHxLN5ayZ++2I4KXHVEJkt21FDRZOWInBguOzyDNntXMuyemlafc3RPVm6zuShv8q2JMSxi0CWjHovdyVdbKnn08+00WRxcOieNEyYk8NCnW9ld1crM9EjuPnk8r/60h2+2VpMUbuK6Y7JJjTJTUi/m/bTUCEJMOt5cuodmq5Ozpydx1Jg4Lvq/VeypaWNmRiSPnDGRCfuRarY5XVx8WDqvryykxerk5EkJZEQHUd3S9ZJtcbhoHS7KW4NEVYuVyKD+SQyHmLTUDmXPTNVWaK8VUsp+ZF31OqbGTaNdU0dY6TpqJp7h1/4VRWF++nz+vfXfzE2e69e+hyNtNhe/P2EMC1eX8Njn2wk16fjd/DFkxQRh1mtp7VggCTfrSY8O4oN1ZXyysZzJyeGcNS0Zo07jUScFyI4J4d21pTz/7W6cbpXfHJHBFYdnEB9u7m0IEolkiCA9M/uhzebkkU+38d2OGs6cmsx/VhSxpkiop+ytbeO2RRtZW1TPzQvXU1jXzrkzUnnok61UNAlPzLL8WlbtrSOqW+LyaXlJgAjFCOtQCFowKcHzfXyYkZO7bQMoCmTFhiCRDHU2lTbx+0UbqW+z43KrBBl0XPvftZTUtTM+PpQNJQ3ctmgjkUFCFKO8ycrDn27j3Bmpnj5OnBjPE1/sQEEhLdJMXKiZu9/f5DH61xQ2cPPb66lr7T0ZOjLIwPNLdtPY7sDlVvlsUwUtNpdXIdsxcSEkR8oXlf1R2WQlKrh/xkyoSU9tyxDO81v/JmQdC4r/Hn/N9hZKW0pJD02nPTqH0PJNoLoPfGA/mZM4h50NO9lZv9PvfQ83QvUavtxcyUcbygkz6bA73Tzy6TYsdjdtdicxIQYMWg2XHJbGvR9spqiujdgQI1vLm3js8+38enqKpy+tRuHIsTE8/sUO2uwubE43Ly0t4JttVYN4hRKJpK9Iz0wPWB1O1hc3Ut9m58fdNQAkhJu8vCp/PC0XvVbDlrJmrA7x0LI5Xezrmf5pdy3L82sJNenZXdNKq9XJPy+dwY7KFhra7UxNjWBqalchP6Ney63Hj8XhVPl2RxVxoUYeOG0CuYmjp9ifZPiyvcK7RJRWo3D3yeNwulUKa9u5bG4GDe02z28GRIhHiEmHQashPEiPqsLfL5rG3to2mixOsmODvbybILyZpQ0Wj1Jgu9XOqsJGfimsx6zXkh0XQphJR3M3z8tXWyo4a1oyq/bWe7w7UcFdSoNOl5tNpU38XFBHkFHLYZnRB/zdNbU7WFvcwPpi4a2dlRlFag+qhsOViiZLvz0z4WY9Vc1DVHXLYYWNC2HBU37tdlPNRjLDM9FptDiDInHrTZjrC7FEZ/n1PHqNnvmp8/nXln/x1FH+vYbhwLL8Gn7Z24BbVTlqTAw7K1u4e8F4ShstBBu0mA1adlU285dzJ7O6sJH4MBNj4kI4eXIiCWEmqpqtJIab2FXVytHjYli8vYraVhuXH57O1jKf8nYsWlPKeTNTMfYjZ0wikQw80pjpgSXbq7nxrfVcdng6MSEGalvtuN0qJr0Gq8PNNUdmsrqwnq+2VHHbCWM9x+m0vit9caFGXCrc+PY6T40LjQL3npLLX5cU8ebPxbx2xUzSorvkJDcUN9Jic3DjsTk0tNl55YcCpqZG9Cj9LJEMJWL2kSGflhrBa8v3sjy/Kz79wtmpHJYZ5bVfTmwI3952FFqthsLaNm5ZuN6TW/b7br+xTow6DUHGrheM5QX1XPfmOk+ce4hRxw3HZPP0110r2BnRwVw5N5MLZqURHWLwKQT5S2E9F//fKs+CRKhRxzvXHc6EXgwat1vlrdVFPPVV1zmmpkbw6qUzRoxYR0m9pd+emUizgcJa3/ofQ4KtH0BUFoT5t/r72qq1ZHWrLdMek0NY6Tq/GzMAx6Qewz0/3UNpSykpoSkHPmCE8NOuGq7+7xrPQkhhbSun5CXyx4+3evaJDjbw9K/zuGXRBk8I6b8vn0lpQzvv/FLi2e+saclkRAXz+c1HYLG7SAg38frKIp9z5iaGou/huS6RSIYWo96YabE6KKprRwEyYoOx2V08u3gXD58xkXCzjiPHxPKXxTv5dFM51x+dTaPFwbS0SLQaDYnhTawtauDCWalEBBmICjJw78nj+dt3+bTYnCgKXH90NvnVrV7F+twqfLWlksOzogk26iipb2d7RRMZ0cE0Wx088eV2Gtod/FxQ7zlma3mzNGYkQ5Jmi4Oiuja0GoVJyeGcMSWRjJhgQBj43ecxwMcbyjgtL5GbjstBVaGxzUZOXAh1rTZ0Wg01LVYvkYxVBXWcNS2ZD9eXedp+My8Tp8vN+uIG4kKNvL6i0Ctht9XmpLbVRlSwgfo2O0adhl9NTSbIoCU+3NfQsDtd/GPpHi/PaovNyZbSRjQK2Jxu0qOCiOjmpSiub+ev3+726mdDSSM7K1tGjDFTWNfG7H0MzwMRFWKgsmkIhpmpKix/HvIu8Gu3dpedHfU7OCrlKE9be3QO4cWrqZpyjl/PBRCkD+KY1GN4ddOrPDLvEb/3P1T5YkuFl0c3NzGMd1YXc+bUJNKjxbPx+x01lDa0c9GsNAx6DW63iktVvRZTAD7aUMb5M1MY122h4rjxcfxnxV7KG8XcDTPpuPTwDDQaqRwnkQx1RrUxU1LfzkOfbGXJjmoATp+SyM3H5nDfKbk8/sUO9tS0otMoXH1UFlOTw9FqNdz9wSb+vbyQIIOW64/JZlVBHdlxITz7zS4sDhexIUaePieP3dUtaBQNX26tYHIPicotVifnzUzhnTWl3PvhFgDOn5XKVUdkeBIXuzMsKmpLRh1FdW088PEWftxVC8Az5+YRH2bi79/vweVWyU0I5Y4Tx3q8F3qtwh9OGs+d722mrNGCUafhxYumced7m1iWL/o4c2oS585I4d21pQCs2FPH2dOS+ev5U8mvacWk0/Lt9ioigvQ88eUOnjk3jyaL72/G4VL5/fFjqGm1odVoePuXYk6cGN/jdThcqo+c8IJJCWwsbeLuDzbjVmFKajjPnjuFnI6ing6X2yuBuJOR9FstqmvnjClJ/TomJsRIWaOviMmgs/MLcDsheYZfu91St5XE4ETMuq78q7aYHBI2LkJx2lF1/fNs9YUT0k/g/uX389vJvyUtzL8S0EOVhjZvEZxgo55fz0jl3bUlfLyhHI0Cv56RQqhZxzcrKimsa8ek1xAbOp5x8aHsrGrxHKuq0L7P7zQnLoSFV89hW0ULLrebcQmhnt+6RCIZ2oxq/+nXWyv5YVc1585M4axpyXy+uYKCmjbe/LnIkx/jdKu8tHQPikbh3g83e1aM2+0u/vrtbi6cnc7jX2zH0nFjrGm18chn26husfPMNzuJCzWRERPMvsqmCyYnsL2ihQ0ljUxPi2BiUhjv/FLC9vIWrpib4bWvUadhXLy8qUqGHp9uLPcYMiBeEv75016Pl2R7ZQvrihuYmhoBwIKJCSxcXeJ52Y0KNvDDzhqPIQPw8YZyEiNMGHVdt6e0qCB2VzbTZnXw7toSNIooXAvw/Le7+fWMZJ+xzcqM4oGPt/LCknyeW7yLs6YlEx1iRO2hoGGwUcdv5mV6thUFJiSG8b9VxR5vzcaSJv69vBCnSxgwKZFBnDLZW6wjzKwjZ4T8Vm1OF5VNVhL66WUKM+lwulWahpICo8sJix+EKRficzM+RNZU/eIVYgbgNgRhDU8itGKTX8/VSYghhPlp8/nrur8GpP+hyL6/tfL6djaWNrK9QhgpbhXeXVOKRqOhsK4dAKvDzSOfbeOcfe4Pk5PDyIkN9jlHWnQwCyYlcGpekjRkJJJhxKg1Zlxulfo2G38+dyq1LTZarE6eP38aTreblQV1PvuX1Fuo2Uc9yeVWaWiz+ST9VzRZSQg3cu1RWUxMCuPb7VU8/es8pqSGkx0bzAOn5hJh0lPXZucPJ44j2KgjKcLM/afmsqOymd8emcUdJ44lNcrM0WNjeevqwxgvBQAkQwybw8XXW7vUfiKCdD2uyK/e28CvpiaREmnmqLExXiukuYlhrCtu9DmmrN7CCRPiyYgO4vYTxzIrMxKrS2VLeTNnTUvmlvljqOxIMi9psGDQanjw9Alkx4YwKTmM5y+YSlKEkVkZkWTGBPPwGROZkxXNs9/s5LxXVvLv5XspbWj3Oudx4+N4+teTyY4N5oicmB69Lku2V3uq25sNWu5aMJ4bjskmJdLMgkkJvHnVYWTG+L4kDUfyq1tJDDf1mAu4PxRFISUyyOv/edBZ9RIYQyFltl+7dbqdbKzexNhI37yu9thxhBf97NfzdefE9BNZV7WOtVVrA3aOoYTD6eLpc/LITQxlbHwIx06IZ0W+77N6d2ULid0McFUV6oanTk4kJdLMuTNSePD0iaRFS4VQiWSkMGrDzLQahQmJ4dz09npP25IdVbx51WFMTg7nl0LvBNb4MCPhZr1XvRdFESs5+xIVbODwzGhueWcDmTHBRAYZ+MvinZw9LYWTJyfw29fXsGBSAodlRXFfR4gZwHc7qvnHxdOJDzNx03FjuHhOOma9FpNUUpEMQQw6DfNyotlcJgq6NrY7SYvyzevKSwnn5EkJzBsTQ7BeQ1pUEMX1wpAoqGllZkYU2/ZRQUsIN6HTKExJiSAuzMgDH22loFbIKv9S2MD88XGcNb1rtfXeD7fw2U1HcEJuPHqt4qkN8fpvZuNwurG6XFz4yiqvPtaXNPLU2XmYOzw8kcEGzpuVxoJJiWg1Ckt31fhcy6zMSEJNXbfN9Ohg/nDSOH57ZBbBRi1G3cj5rW4pa/LkPvWXrNhg1hbV9zvfJiDU7IQfn4GTn/K7V2Zr3TaizVGEGXxX8Vvjckla9yYl8270+3kBjDoj5407j4dWPMT7Z7yPQev/cLahRKPVxT9/zOeuBbloNApWu4PJyWF8t9P7d5ocaaam1TtnKzLYgE6rcOXcDFbsqeXlH/bw14RQQvYRAZFIJMOTUeuZcbvdvLeu1KtNVeG9tSX84aRxXgo+p+Ul0tBu5/5Tcj2hLxoFbpk/hna7k6uOyPQ8q4w6DdcdnU1hfTsTEsP4aXctn2wsx+5UWTApgf8sL6Sy2caemjY+XFfmdX6XW2VdUZcRFRlkQK/VsKuqhSXbq1hf3EBbD/k0EslgoCgK50xPIbujBpJeq6DVKMzPjfPsExti5MQJ8ei1GsbEhdJocXLlvAyCOwyIwrp25uVEkxnTZQQdlhlFTKiR57/L509fbMfudHuMkE6W7Kim++vhzcflkBETREpUkFeRuyCDjvAgA7sr23z6+GRDOVvKmzy/rU71ozCznmCjjhlpESyY2BXakhBu5PqjszHsY7AoikJUsGFEGTIAq/fWk9VDKE5fmJYawQfrynC4/F9rpV/YWmDhxTD9MgjzDUU8VFZV/szYyHE9nzosEcXtwtxQ6PfzdjIzfibR5uhREW52/Pg4EsKD+P2ijdyycANuFC45PJ3Y0C4FxePGx5ERHYReK36LigKXzkmnvs3OxxvKefTz7SzZUcO326s9oWgSiWT4M2o9MwDaHlbLNIrC7Mxo3vrtYeyqbkFVYVt5Ew98vJW85DCePW8KdqebpAgz0cF6dle38XNBHbfOH4PDraJR4N/L9vLUOXnccvwYrjs6mza7k8yYYFIigzzKKG5V7XGxzqDzti+/31nN9W+uxeESsWw3HZvDdUdnE2Ia1f91kiFCTnwob199GPk1reg1CrurW3G7hZyyy+2m3e7i9ZWFnmKxAK/8UMDlczPQahR0Wg1vrSrhoTMmotdq0Gs0ZMeFYHe5yIwOpt3u7HVVOyrYwOu/mUVUkIHsuBCCDL3/JnrqQlFgeX6tR5HsmqOyuPnYHELNYrU2IdzMk+dM5uojM7E4XWTHhJAYMTqKbKodClB3nNjzi/qBmJwczrfbq7jn/c08c94UP4+uj7gc8M6lEDMGck7we/c2l40N1Ru5atJvet5BUWhNmEjknh+xRGX2vM8hoigKl024jMd+foy8mDwWZC4IyHmGAukxwbx2+Uzyq1txqypxIUZuf3cj95w8HrvLjVGroaC2jbWFDVx9VCZuFfRaDUu2VxEd4uu1CoCzTCKRDBKj9o1Yo9FwwexUvttZTWc+sFajeJR7xieGMSY+lBeW7OaVH/cCsKmsmcc+38aia+d6wmksdjdWh4vnukm0npaXSFZMEClRvqua58xI5b21pawqqOcPJ43zCmfTaxXmjxdqS263SkFtK3e9t8ljyAC8+H0+x42PY3p6pH//QSSSgyQuzOSRIg4163n8ix18v7Pa8/2z5+YR2eHpjA0xcvyEeP6xdI/n+4QwEyadlsOyor36TQgThsPe2lbGx4eyo1sOximTE5iQGEZ4Hws6jokLITchlO2VXX2cPCmB5d2EB179sYATJsQzK6MrNCrCbGBGxhAIlRpgdlS2ACpJEQcnMa0oCjcem8Mf3t3IlrImJiX7KjoGFLcLPrgGHBaYd2tA3lzXVa8jOSSJYH3v3quWhMnEbfuU8lmX+/38nYQaQrlx6o089vNjGLVGjk07NmDnGmyiQ4xoNQqqCloNnDMzldsWbfR8H2TQ8vhZk7n1nQ2etvSoIEz7LBKelpdIRg8h4hKJZHgyao0ZgLnZ0fzz0hl8vLECvVbh9ClJzOkW463VKFx6eDqZMcF8sbmCSclhLJiU6JUXUN1i4+TJibRaneytbWNiUhi1rXYaLE56Kmc2LS2ChdcczofrS2m1OXjl0hl8taWSUJOOX01NJi8lnJL6dt5aVUyQQUPdPnKx4pxDsIaDRAJkx4bw0iXT+WJzBTUtNk6YEM/sjC4jpdnqpLHdzu/m57CppImUSDOxYSZqW3uvGJ8ZE8LT5+axZHs1G0sbOSInhqPGxPTZkAFhcP394ul8u72a1XvrOHpcLFvKmvlic6XXftVDtXL9APP5pgpmZkShHIIRYNRpOXJMLB9vKB9YY8bthk9uhvoCOO4B0AQm/G9pyVImRk/a7z6WqHS0thbM9XsD5p0BSAtL43fTf8eDKx9ke/12rs67Gr1mZOWDtFodLN5WxV+X7MblVnn23Ck4XW7+ct4Uvt5SSUzHQond4eLZjrYpqRGcNDEenUaDXqfl5z11HDs+lqPHxhFsHNWvPxLJiELpSaZ0qDNz5kx1zZo1gz0MAHZWNnPqC8sIN+tJijCzp6aVqGADH94wl9jQ/q9qOlxuHvpkK/9bVcw5M1JYV9TgFeuvUeCzm49gQg+1ayQBoc9vc0NpXg4W64obOOelFSRFmAk369lR2cKtx4/h5uPGANBkcXDZa6vZUdnM2PhQqpqtVLfY+PjGeUzpkG8eCBra7Vz0z589sq4gFu8/vemIgfciHBz9sjL6MzdVVeXoPy/l6iOzyIk7NMWnXVUt/G9VEd/8/uhD6qfPqCp8fhuUrIL5D4E+MGGB5a0VPLH6Ca6bci1aZf/GUsz2L3AER1N6+LUBGUt3GqwNvLHtDRptjdw49UZOSD8BnWZAX9oDNi+XbK/iqte79l0wMZ4go47PNpZx1ZFZFNe18/nmSl68aJpXWKtE0oEMLBzBDAkBAEVR/qUoSrWiKFsOvHfgcbrcbCxp5L21JXy9pYKyht4TBbNjQ/jbRdNwuN1sLmsiKtjACxdOOyhDBqCyyco7v5QAoobHpYenkxolHshhJh3PXzBN6t9Lhixbyppwq1DaYGFreTMut8rrKwqp6fAmhpv1PH72JFIizWwua6LN5uSZc/MYn9C/OW1xOFlb1MC7a0pYsr2Kqub+eSsjgww8/es8sjqEB0KMOp47bypj46Vc6/aKFuxOF9kHmfzfnazYYErqLTRbB6DmjKrCN/dD0XI47o8BM2QAvin+himxeQc0ZACaU2YQs2sxiivw4i2Rpkh+N+13nJ1zNv+3+f845YNTWLhjIXaXr4d/uPHRem/BnK+2VnHmlCSmpEby0tICvtlWxY3HZjM9LWJwBiiRSAaNoeJn/Q/wIvDGII8DgOX5dVz5n9We+jETE8N45bIZpET6ys7qtBpOnpTIpKRwGtsdxIcbiTtIQwaEGlpEkJ7aVjs2p5snv9zBmVOTeej0eMbGh5Lag/StRDJUCOtBmCImxFvpa2JSOIuuPZyKJiuhJh1pUUH9Dmf6YlMlt7/bFSt/7LhY/nzOFGK6KRsdiMkpEbx73VzKm6yEm3Q9yqyPRr7ccughZp3oNBqyYoPZVNLEEWNi/DC6/fD947DzCzjxT2AI3P9lk72J1RWruWrSVX3a3x4ajz04hojC5TRkB95DpSgKk2MnMzl2MvkN+XxW8BmvbXmNe2bfw3FpxwX8/IEiKdLbONVpFOra7EQHG/jd/BxcbthW1ojdNfyiTSQSyaExJDwzqqr+CNQP9jgAGtvtPPb5Nq9CmFsrmj21NHojNSqIySnhh2TIgIjtv//UCZ5tm9PN5tJGxidIQ0Yy9JmaGklKt6RxRYE7F4wnzOwdvx8dYmRScjjp0cH9fmkua7DwyGfbvNq+31nDjsrmXo7onegQI5OTw6Uh042vt1YyI81/AiOZMcFsKGk48I6Hwg9/hk3vwPEPi+KYAeTTPZ8xKXoiwfq+348b0w8nYeN7ARxVz+RE5nDL9Fu4NPdSnlz9JPf8dA/tjuEpSXx6XqJH0h3g+Nw43vy5iK+2VvHCknz+/n0+3++qZX1RgOeaRCIZcgwVz8wBURTlGuAagLS0tICdx2J3Ud5DFfOm9gEIk+jgpInxvHPNHLaUNxEbYmRaWiTJPXiFJIPPQM3L4UJGTDD/veow1pc00mRxkJcSwWQ/56BYHC6aLL6/xwEJZRpGHMzcrGiyUNlkZWy8/wyCrJhg1pc0+q0/L1QVlj4BG9+GEx4Dc2BVHivaKvi5YiVXTuxFjrkXWhImEbvjK0IqNtOaODlAo+ud3Ohc/jjnj/xvx/+46POL+Pvxfyc5xP91d/rCwd4zJyVH8N71c9lQ3IBbhalpEfzmP7/47Lc/MRGJRDIyGRKemb6gquqrqqrOVFV1ZmxsbMDOExdm4vxZqV5tigJj+xnTfyiYDToOy4rmqiOyOGNqsvTIDGEGal4OJzJjQzh7egpXzstkRnqkT+2kQyUxwsQx47z/rQ1aDVmxMt+lOwczN7/fUcOU1AhPPSx/kB0bwsaSRvwuNuN2wRd/gM3vidCyoMBKaLtR+c/W/3BYwpx+eWUA0GipyzmWlJ//CYMkumPUGbly4pXMSpjFxZ9fzNbarYMyjkO5Z+YmhnHhYelcPCedCYlhXDjb1xgaSCERiUQyNBg2xsxAodUoXDkvk0vnpGHUaUiJNPPqpTOYlBQ22EOTSCRAsEHHA6dN4IypSeg0CuMSQvnPb2Yxzo/ehNHK4m2V5KVE+LXP2FAjLrdKWQ8e74PG2gRvnQ+lv8BJfwq4Rwbgsz2fYXVamZEw46COb0qdic7aRNSepf4dWD9QFIUTM07kotyLuHbxtfxQ8sOgjeVQURSFc2ekcvWRWZj0GhLCTPz9oml+n78SiWToM2zCzAaS1KggHjx9Itcfk4NJpyEqpO9JxRKJJPBkx4bw53PyuGvBOEIMun7VnJH0TJvNyaq99Vx0WLpf+1UUhdzEMFbvre9RRKXflK+HRVdAwmSY/yBoA19PZVXlKr4rXsLFuZegOViFV0VD1eSzSVv2Ii2Jk3EEB1gQYT9Mi5tGmCGMB1Y8wFWTruKyCZf5RfBhoEmONHP3yeO5cl4GBq2mXwIgEolk5DAkPDOKorwNrATGKYpSqihK32RiAohOqyEpwiwNGYlkiGLUaUmOCJKGjJ9YvK2K3IQwQgJQTHBCYhjf7ag+tE4cVljyKPz3LMg7Dw67NuCGjIrKkuIl/G/7W/x67K8JNRxaKKM1Mp3GjLnkfPVHNA4/eqoOguyIbO6ZfQ/v7XqP23+4nSbb/kVuhipajUJShFkaMhLJKGZIGDOqql6oqmqiqqp6VVVTVFV9bbDHJJFIJKMFVVX59/K9HDk2MN6CGemR/LCzhjbbQdRacTlgw9vw4gxRDPO0v0LmUX4f475UtFXw3Nq/8m3xt1w4/kJizf7JiavLOQ6nOYpxn9yBvrXWL30eLDHmGO6efTeocOZHZ/Lh7g9xugNfD0cikUj8iQwzk0gkklHOojUlNFoczEoPTBJ9RJCBySnhvLR0D3ecNO7ABzisIpxs11dCqSw0EebcKELLAoQbler2anY17GJ1xWqKmguZET+TEzNORNeH4ph9RlGozDubqPylTHr3aqomnkH92OOxhqcItZkBxqA1cGHuhcxOnM3bO97mxQ0vckb2GRyVchS5UbmYdIdWbkAikUgCjeJ3hZkBQFGUGqDoALvFAIO77DUwjJbrhMG51lpVVRf0Zcc+zkt/MFz+z4fLOGH4jLVznH2el9D73NSGx+tTrnstD8DRUG51NdcERNdWdbsM2uBItyEuM9hSuKGx+p3793R+d++Rhrg/HWdK7e3YPfUua1GT6rdxKWaNVskM2n+8mApqu8vpfwk2bxIUVZOrcfVoKS2whbXsVHVur2G5VIOiVeyBHJMhxmA0xBr2a8Hk/zF/q7XYau3hK5OqqpP6eq5R8iyX4x9cDuqeKRleDEtjpi8oirJGVdWZgz2OQDNarhNG17Xuj+Hy7zBcxgnDZ6zDZZz7MhzGLcd46ARifEP9mg+EHP/gMtzHL+kbQyJnRiKRSCQSiUQikUj6izRmJBKJRCKRSCQSybBkJBszrw72AAaI0XKdMLqudX8Ml3+H4TJOGD5jHS7j3JfhMG45xkMnEOMb6td8IOT4B5fhPn5JHxixOTMSiUQikUgkEolkZDOSPTMSiUQikUgkEolkBCONGYlEIpFIJBKJRDIskcaMRCKRSCQSiUQiGZZIY0YikUgkEolEIpEMS6QxI5FIJBKJRCKRSIYl0piRSCQSiUQikUgkw5JhacwsWLBABeRHfgbi02fkvJSfAfz0Czk35WeAPv1Czkv5GcCPZAQzLI2Z2trawR6CROKDnJeSoYqcm5KhiJyXEonEHwxLY0YikUgkEolEIpFIpDEzwrE4LDTbm/u8f5O1CavT2u/z2Fw2Gq2N/T5OIumkpq2Gemt9n/dXVZVGayM2py2Ao5JIBg6Hy0GjtRGX2+XV7nK7aLQ2YnfaabQ24nA5BmmEEolEMvTQBbJzRVFSgTeABMANvKqq6vP77HMM8DGwt6PpA1VVHwnkuEYDDreDtZVr+cfGf9BgbeCS3Es4Pv14os3RPe5f1VbFF3u/4N1d75Icksx1U65jetx0FEU54Lk21mzk1Y2vUtBUwK9yfsXp2aeTFJLk70uSjFAq2yr5vvh7Fu5ciElr4rKJl3FU8lGEGkN7PaaspYyP8j/is4LPGBM5hmvyrmFSzKQBHLVE4l921e/ijW1vsKZqDUclH8WFuReSGZ5JYVMh7+x8h2hTNOVt5awoX8HkmMn8ZtJvyI3OHexhSyQSyaATUGMGcAK3q6q6TlGUUGCtoiiLVVXdts9+P6mqelqAxzKq2Fq7lWu/vRa36gbgsVWP4VbdXJh7oc++qqry3q73eHnTywCUtJSwtmot/zvlfwd8WOY35nP1N1djcVoAeHHDi9Raarlz9p3oNXo/X5VkJLKsbBmPr37cs333T3fzwrEvcGzasT3ub3Pa+PuGv/NpwacAlLaWsrpyNW+f+jaZ4ZkDMmaJxJ9UtVVx83c3U95WDsDbO99mc+1mnjvmOR5a+RBBuiB2Nuzkl8pfAChrLWNVxSreOvUtUkJTBnPoEolEMugENMxMVdUKVVXXdfy9BdgOJAfynBLBhuoNHkOmkze2vUGjrdFn3+r2at7c/qZXm8PtYFfDrgOeJ78h32PIdPLerveoaqvq/6Alo442exsf7P7Ap31pydJej6loq+DzvZ979+NoY0/jHj+PTiIZGAqbCz2GTCdb6rZQ0FTA2qq1TIye6DFkOmmwNbC3aS8SiUQy2hmwnBlFUTKAacCqHr4+XFGUjYqifKkoysRejr9GUZQ1iqKsqampCeRQRwTB+mCftjBjWI/eEr1GT4ghxKfdpDUd8DxGrdGnLUgfhE4TaKff0EDOy0NDp9ERbgz3aY8wRfR6jF6j73He9dQ2mpFzc/jQ09xVUDBqjWgUDW7cPd5Th+OcD9S8vOPdjWyv6Ht+qEQiGTkMiDGjKEoI8D5wq6qq+95t1gHpqqpOAf4GfNRTH6qqvqqq6kxVVWfGxsYGdLwjgenx04k0Rnq2FRRunHpjj0ZOlDmK22bc5tWWEJTQp3js8VHjyQrL8mq7dfqtJAQnHOTIhxdyXh4aRp2RC8ddiFbRetqCdEEcmXxkr8ckhSRx89Sbvdpyo3IZGzk2YOMcjsi5OXzICs9iftp8r7bzx53PuKhxXJp7Kd8Xf89ZOWd5fT8zfibZEdkDOUy/EIh52dBm5721pXy6sfzAO0skkhGHoqqBrSWkKIoe+Az4WlXVv/Rh/0JgpqqqvQrQz5w5U12zZo3/BjnEcbqdNFgbCNGHYNab+3xcQWMBe5v24nA7SA5JZnzUePTanvNYrE4rm2o28UvlL8QFxTErYRYZ4Rl9Ok9xczHrqtZR2lrK9Pjp5MXk9ejpGaYcWAGhg9EyL11uF/W2eoJ0QT0axz1hdVppsbcQYYzwmYN2p5211WtZU7UGg8bAzPiZzEiYQYutBbvb3qNoRbO9mc01m1lfvZ7UsFRmxM0YbbkDfZ6XMHrm5lCj1d6K1Wkl2hy9XzGVZlszFW0VFDQVkN+Qz4SYCUyJnUKMOYZ6Sz0bazZSb63HoDVQ0FhATmQO0+OmkxiSOIBX0ycGZV6uL27grH+sYMGkBF6+ZMYh9ycZkfRrbkqGF4FWM1OA14DtvRkyiqIkAFWqqqqKosxGeIvqAjmu4URhUyH/3fZfFhctZnzUeG6adhN5sXkHPM7hclDaUso/Nv6DRlsjF+deTEJwArFBPa+ENVgb+KXyFxYXLSbcEE5qWCqpoaloNdoe9+9OWlgaaWFp/b42yfCjpKWEhTsW8lnBZ2SEZXDL9FuYHj99v8dsr9vOPzb8g401Gzkq5Sh+M+k3ZEV0efMMOgOHJx3O4UmHA2Lu/lT6Ey+se4E6ax0Xjr+QM3POJC4oznNMmCGMecnzmJc8LzAXKpEcAi63i9WVq3l+3fNUtlVy7thzOXvM2T0aH2sq1vDK5lfYWb+TuUlzuXzi5V5e8ShzVK9iGBJBZZOVUKOOyqb+lxWQSCTDn0AnNswDLgU2K4qyoaPtXiANQFXVl4FzgOsVRXECFuACNdDuomFCu6Odp355imVlywBYWbGSzbWbWXjaQtLD0vd77Obazdz03U2oiH/K59Y+h1bRcvnEy332datuFu5cyL+2/MvTdt3i63jzlDel3K3Eg81p46UNL3lUxOqt9Vyz+BoWnrqQnMicHo8pby3n+m+vp84q1ic+3vMxuxt38+rxrxJu8s2VAdhWt40bl9zombsvrH8BRVH47eTfBuCqJBL/s6N+B9d/ez0uVdSLeXnTyzjdTm6efjMapSu6e2f9Tn7/w+89wiyf7/2cwuZCnj/2eeKD4wdj6MOS2jY7GTFB1LTImlMSyWgk0Gpmy1RVVVRVzVNVdWrH5wtVVV/uMGRQVfVFVVUnqqo6RVXVOaqqrgjkmIYT5a3lHkOmk1ZHKwVNBQc8dkP1Bs/LYCdvbX+rx8KW1e3VLNyx0KvNpbrIb8zv/6AlI5aq9iofFTGby8aept5VxIqaizyGTCfb6rZR0lrS6zGbazf7zN23d7xNnUU6bCXDg10NuzyGTCcLdy6kpt074b2gqcBHYXJr3VYKmwsDPMKRRX2rnaQIM40W+2APRSKRDAIDpmYm6T8GraFHRbEgXdABj40wRvi0xQTF9JgzY9QaiTRF+rT35TyS0YNeqydE75sLtb95YtL5zl+tot2vUl6YIcynLcYUg0Fr6ONIJZLBpUehFVOUj/qYWeebA6nT6DBr+54bKYGGdhuxISasDjd2p/vAB0gkkhGFNGaGMCmhKdw07SavtjmJc8iJ6DmkpzvT4qcRZ+7KMdAoGm6aelOPD9lIUyR3zLzDqy0jLIMJ0RMOcuSSkUhicCK3z7zdq21S9KT9qohlh2dzUsZJXm1XTbpqv2GSebF5JAR1qeEpKNw8/WZCDaEHOXKJZGCZED2BtFDvPMLbZ97uIzk+Pmo885K8874uyb2EMVFjAj3EEUVDu4Ngo5YQo45mq2OwhyORSAaYgKuZBYLRpMzTam9lc+1mdjXsIikkickxkw8oe9xobcTqsuJwOihqKcLpdhIXHEecOQ43bq9E6k7sLju7GnZR016DQWsgMywTRaMQrAtGQaHaUk2EIYLoIF9lqUPB6XZS3FyMSWciKSTJr337iRGvZlbdXo1G0RBjjgG65k+sOdZHAKLd0c7W2q1sr99OXFAcebF5Pf6/lbeWY3FaSA9Lp8Eqivu12lsJN4aTHZmNDh2lraWEGkNJDvGto1vcVExxazEOl4O4oDjGRo3tsUbSKEaqmQ1hGqwN1FnqaLQ10uZoIy4ojjBDGCH6ECwuC0aNEavbSowphtLWUjbXbKaktYSc8BzGRI4hMSQRs86MxWmh0dpIuDGcIH0QNqeNels9ofrQg1aMrGqrQqfR9agS6AcGZV5e+e/VTEuN5J01Jbxx1WyyY0eMmqbEf0g1sxHM6KhsOIwJMYR4KT3tD6fbyc8VP/P0L09T2VbJqZmnEhcUxxvb3uDXY3+Nqqp8vOdjrpp0FWdkn+H1MKtpr+Hzgs95f/f7xAfFc8XEK3hr+1toFA0X5V7EyxtfJtocze+m/445iXP8cm27G3bz7s53+aTgEyKNkdw49UaOTTu2z3K/kkOj3lLPpwWf8n+b/w+dRseNU28kOSSZx35+jFpLLeeNPY8Lcy/0MlaC9EHMSpzFrMRZPfbZ5mhjafFSXtz4Ig3WBs7IOoNTsk7hHxv/wZbaLcxNmsuVE6/krR1vsbRkKamhqdw87WaOSj4KrVYYTjanjd2Nu3lmzTM02Bq4YNwFRJmihqIMrUTihd1lZ1nZMv78y59psDVwSuYpzE2ay10/3kVleyVnZp/J9PjpvLb5NYqaizgx/USuzruaM3LOYEftDp5e8zSbajdxRNIRXD7xcv65+Z+sqljF1Lip3DD1Bt7b9R6LixYzLnIcf5j1B6bGTe3z2Grba/l4z8f8a8u/MOlM3DLtFo5LO25EyOi32JyYDVqCjVqaLNIzI5GMNmSY2QhiR/0OblpyE3ub9mJxWnhv93vsbd5LSmgKr299HafbiUlr4i9r/8JPZT95jnO6nfx32395c/ubWJwWCpsLeeTnR1iQuYAdDTt47OfHOGvMWWyu3cztS29ne932Qx6r2+3mw90f8vbOt2lztFHaWso9y+5hXdW6Q+5b0jeWlS/jmTXP0GhrpNZSy8MrH2ZL7RZKW0tpd7bzn23/YdHORbjVvsegr6tax93L7qa0pZQ2Rxtv73ybT/Z8QlV7FTaXjTZHG69seoWvCr/C6rKyu3E3t/9wO2ur13r62Fq3lVuX3kppq+jjtS2v8VH+RwxHL7JkdLGlbgu3fH+LZ+6+u+tdVpSvwOF2YHFaiDRF8sDyB9jZsBOry8onBZ/w9C9PU9pSyrVLruWXql+wuWxEmiK5d/m9/FT2E3a3ndWVq7njhzuINEVic9nYVLuJ6769jqLmoj6P7fuS7/nrur/SbG+mur2a+5bfx4aaDYH7xxhA2qzCmAky6Gi1Ogd7OBKJZICRxswIoqCpwEdB59uib5mbNBcQD7PDEg8D4L2d72F3CeWXWkstH+R/4HWcW3VjcwmZS7vbjsst+m22N7O3ae8hj7WktcRHGQuEQSYJPE6Xk3d3vuvTvrVuK1nhXTVg3tv9HrWWXuvX+tDT/9+S4iUcnig8i1PjprK8fLnX9w63w0u9aWvdVp8+3t31LvXW+j6PQyIZDLbX+i70fFf8nceb3f2+2slPZT9R3lruNb+jzdGUtpR67VdrqfUS22hztFHYVNincVkcFhbtWuTT/mPpj306fqjTanMSpNdi1mtptUljRiIZbUhjZgTRk9JUrDmWBmuDz9/TwtLQKiKsx6QzEWv2LabZ+T3glTvhj7CEIF2QJ0ejOz2psEn8j1ajJSMsw6c9yhRFk63Jsx0fFN+jIllvhBt9a8fEmGM8867N0dajWln30MKe5kBCcMJ+FdAkkqHAvgn+ALFBsTTYxPzvfk/tJFQf6vMbUxTFqx5NJzqNd2R4X0Ny9Vo9qaGpPu1DNE+x37TZXZgMWkx6jfTMSCSjEGnMjCByo3OZENWlQKagcP748/mm6Bt0io4FmQtYUb4Cs87MheMv9BgoEcYI7px1J0q3/Lis8Cya7OKldkrsFEpaRF2Q49OPZ3zk+EMea2xQLDdMvcHr4Z4amiqLdA4QiiLmRndp2HBjOFnhWdRYRC0MjaLhthm39Wh89MbkmMleL01aRcsluZfwQ+kPAHy19yuun3K91zFTY6d6KaJNjZ1Kemi6Vx+/m/Y7gg0yl0oytMmLzfNaJNAqWs4Zc47HA1LcUszshNlex9wx6w6yw7M5d8y5nrYfS37k4vEXe+13ds7ZrKpY5dk+Mf3EXovV7otOo+PyCZd7SUNHm6I5IumIPl/bUMZid2HWazHptbRIz4xEMuqQamYjjPLWcrbVbaPZ3kxySDJWp5UGWwOpIamoqNhcNhKCEgjRh6AqqkcZzeFysL1+O/mN+YToQ4g1x1LQVECYIYxQfSi7GncRY45hYszE/crq9geb08b66vXsadyDSWdiYvRExkcfuqHkZ0a0mtmu+l3sbNiJVtEyPmo8Jq2JrfVbabW3khOZQ25Urs9qsNVpFSEv+iCiTFE+fe6o28G2+m1YHBayI7LJichhR/0OqtqrSAlNIS00jR31OyhpKSHMGMa4yHHkRud69VHSXOLpo3Mc+yqr9YWa9hrsLjtxwXEjTQ1NqpkNUUpaSthet51mezOx5lgMGgN1tjosDgux5lj0Gj1N9ibanG1kh2eTG52L3Wmn1lpLk7WJvc17SQhOIMGcQEV7BVXtVSQEJ5Adnk1JawnFzcXiXhw9kZggX+92dxxuB9Vt1ei1euKC4thRv4NdDbvQaXTkRuWSGZ7p78sf8Hnpdqtk3/sFb/72MN5bW0pmTDC/my+lrSU+SDWzEYxUMxthJIUk+YQONNma+KzgM15c/yIOt4Pzx51Pq72Vr4u+5oYpN3BGzhlEGCPIi80jLzbPc9y0+Gmev89J9o+CWXdqLbV8U/QNH+/+mFBjKHfOupOM8Ix+hTVJDo2xUWMZG+VdJyYptPfQk71Ne3lh3QssKV5CUnAS9825j7lJcz2GhtVppaC5gBfWvUCLrYUzc84kdXIqR6R4rwAfSJksNSyV1DDfsJi+YnFaWFy0mGfXPEuzrZlzx57L5ZMu71EGWiLxJ6mhqT2GdPXG2qq1/OnnP7G7cTezE2Zz49Qb+cvav7CxZiN5MXnce9i9TIyZCEBCSAKzEnpWEtyX8tZyXt/yOot2LyJUH8odM+/ghIwTGB815BaMDol2hwujXoNGUTDpZJiZRDIakWFmo4B1Vet4cvWTtDpasblsvLHtDSJNkWjQ8Oc1f2ZN5cCv2LpVN+/sfId3d72LXbVTZ63jrp/uYmutb/K3ZGhgcVp4bu1zfFv8LSoqZW1l3Pzdzexu3O3ZZ2vdVu768S7qrHXYVTvv7n6XhTsW9ksRzR9sqd3Cfcvuo95aj1N18vbOt/lw94dSEU0ypChqLuKGb2/w/IZWV67moZUPeQpubqrdxM3f3UxVW1W/+lVVlQ93f8hbO9/C6XbSYGvgvuX3sblms9+vYbBptzsx6zvyP/VaWmxSmlkiGW1IY2YU8F3xdz5tqypXMTl2MgDfFH0z0EOizlLHR/kf+bRvrz902WdJYKhur+b7ku+92lyqy0vdbkedr5rZR3s+os5SF/Dxdaenl7YP8z/0CBFIJEOB4uZi2p3tXm17m/Z6eddrLDWUtpbue+h+abA28GH+hz7tm2o3HdxAhzAWuwtjN2OmzeY6wBESiWSkIY2ZUUBmhG9cdFJwkkdyt7sU70Bh1plJCU3xae9J4UwyNDDrzESbfKuGdxcI6KmqeGpoqpek7EAQFxzn05YWmiZDGCVDip7ENYxao5fEvkbR9KhUuT/MOrPHu9OduCDf38Vwp93uwqQTrzLCmJFhZhLJaEMaM6OAo1OOJs7c9RAL0YeQF5vHroZdRJuimZ82f8DHFGII4ffTf++VXD4uchyTYyYP+FgkfSMuKI77DrvPS/XuyOQjvWLwJ8dMZlzkOM+2TqPj1um3DrgS2ZSYKWRHZHu2DRoDN027iSD9wBpVEsn+yIrI4pyx53i1XZN3DV8Xfu3Zvjbv2n4n6pv1Zm6adhMGjcHTlh2ezbTYafs5anjS7uWZ0dBul54ZiWS0IdXMRglFzUVsrd2KS3WREZZBVXsVbtXNuKhxHnUyi9NCVVsVJp2JMEMYVe1VBOuDMelM1FnqCDOEea2817bX0uJoIcYUQ6gxtM9jcbgclLeVo1f0NNub2dO0hyBdEOOjx5MYvP/E8EFgRKuZ9ReHy8HWuq0UNBUQYYxgcsxkYoO8axTVWGooaS7B6XYSbYomKyKLBmsDTfYmok3RhBl9V6M754RW0ZIUktRjjY3+Ut5azo76HVicFnIichgbORZFGTGCNlLNbBhT015Dq6MVk9ZEm6ON8tZyai21JIUmEWmMxOq0UtJSQrQ5mjhzHFHmKCJNkX3u3+q0Ut1WTYO9gbKWMkw6E+Ojxg9EXZkBn5fL82t56qsd3HNyLjsrW/hgfSmf3DQyJKclfmXE3Pwlvkg1s1FAg7WBrwu/5p+b/onT7eT8cedz5aQriQ+O9+xT1FzEs2ue5fuS7wk3hnPVpKtYUryE07JO44PdH7C9fjspISk8NPchZsbP5OeKn3lo5UNUtlWSF5PHA3Me6JOsckVrBf+3+f94f/f7GLQGrptyHb/O+TXhJt9ii5KhR3FLMS+uf5FVlauINkXzwJwHOCr1KI/scVVrFV8Xfc3LG1+m1dHKaZmnsSBrAU+seoLS1lJyI3N5cO6DHnUmgMq2Sv69+d8s2rUInUbHtVOu5Zwx5/RYgLA/9KTsJ5EMJk63k2Vly3hk5SPUWGqYEjuFqydfzZOrn6S0tZRxkeM4M+dMvij4gltn3Mpf1/6VLXVbyAjL4KG5DzEjfsYBz1HUXMTf1v+Nbwq/IdQQyu0zb+eY1GNGrFfSYndh9ISZSc+MRDIakWFmo4C1VWv52/q/YXVZcapO/rfjf16iAA6Xg39u+qcnubvJ1sRf1v6FS3Iv4fVtr3uS8ktbS7n5u5vZWreVm7+7mcq2SkAkld677F4abY0HHMvXhV+zaNciXKrLo461vma9/y9a4nfaHe08/cvTrKoUhfvqrHXc9sNt7K7vUjPbXLeZP6/5My2OFlRUEkISuOOHOzwJzNsbtnPb0ts8+VoA3xZ9K1SXVCdWl5Xn1z3P2uq1A3txEskAkN+Qz63f3+opTLuxZiMvb3rZI4++s2Enb+94mzGRY7hv2X0eo7+wuZDfffc7T/Hi3nC6nby57U2+LvwaFZVmezMPrniQbXXbAnthg4jF4cLQYcwYdVos0piRSEYd0pgZBfxQ8oNP28d7PsbusgNQa63lq8KvfPZxuB2Utnir6FicFopbinG4veUvdzfu9hg3vdHmaOOTPZ/4tK8oX3HAa5AMPjWWGp//K7fqpqilyLOd35jv9b1G0WBxWrzaytvKqWitAEQ4TE9z4qfSn/w1bIlkyFDSUuKV3A9CRnxMxBivfeKC4qhqryLCGOFpb7Y3U9ZStt/+6631fLH3C5/23Q27e9h7ZOBlzOg1WBzSmJFIRhvSmBkF5ETm+LRNiJ7gSb4P1gd78ma6Y9AYMGl91Z8iDb6x28H64AMq7hi0hh4LtmWHZ/ewt2SoEaQL6lENqfsL175qdN0FHjoxao2EGkSOlV6jJzcq12ef7i93EslIoad8sShTFC32Fs+2WWfG6Xai1+hR6cppVVAIN+4/HDdIF0RGWIZP+755bSMJq8OFQdvpmdFglcaMRDLqkMbMKOCo5KNICemSQQ43hnPe2PM8SdZhhjDunHWnJ+8BYErsFLbWbeXyiZd79XX5hMsZFzWOC8Zd4NV+7+x7e5Ra7o5eo+eS3Eu85EgzwzKZkzjnoK9NMnDEBsXywJwH0CpaT9uJ6ScyLqpLvWxC1AQmRE3wbP9S8QuXTrjUq587Z91JWpiQjdVqtFww/gKvOZEWmsa85HmBugyJZNAYFzmO07NO92wrKFw/5Xq+3Pulp+2yCZfx5d4vuWHqDXxT2FUD7Pop1x9Q1SzEEMJtM2/DqDV62qbHTWdi9MT9HDW8sdhd6DuMGZNOi9XhksVxJZJRhlQzG0I0WBsoai7CqDWSEpJCZXslQbogkkOTD7nvstYydjfsxuV2kR2RTbO9GQ0asiOyMevNqKrK7sbd7G3cS7A+mEhTJCUtJcSaY1EUhar2KuLMcYyJGkOYIYwmWxO7GnZRa6klNTSVsZFjMWgNBx4IUNhUSH5jPnqNnrGRY0kM8VUwa7Q2Um2pJswQRkJwwiFf/yEwotXMbE4bZa1lKIpCSmiKl0HbE063ky21WyhsKiTcGM6U2ClEmaO89slvyKeqvQq7y06MOYaM8Ax2Neyiur2a5JBkxkSMweF2UNleSbA+mOSQZIqaishvzEer0TI2cqxfEvfdqpvSllLsLjtJIUkjLQFaqpkNMVxuF6WtpThcDgxaA3aXHYPWgMvtAkX8dhKCE3C6neys30mdtY5IUyQaVYPdbafZ0UyUMQq7y06UOYr00HQKmwspbysnPiiesZFjCTH07P1usbV4PS/yG/IpaCogxhyDUWskxBBCamiqX1QCD8CAz8vnv91NUX0b585IBeDyf61m00MnYtJrD3CkZJQh1cxGMAFVM1MUJRV4A0gA3MCrqqo+v88+CvA8cArQDlyhquq6QI5rKLK1divPrX2OVZWrMGlNXDHpCtocbXy4+0Pumn0XJ6WfhM/VavsAAH2lSURBVFlvPuj+k0OSSQ5JZnfDbl7e+DJfFn6JBg1njzmbSydcSkZ4BmMjxzI2cqznmO6KU/sSbgxnVsKsgxpLRngGGeEZvX6/rXYb9y2/j/zGfCKNkTw09yGOSjmqx5AlycFT0VrBSxtf4uM9H6NBwyW5l3D5xMuJCeq9cOmWmi08vvpxttdvJ1Qfyq0zbuXUrFMJ1os6Mq32VlZWrOSFdS9gdVmZlzSPu2ff7aXCtKthFw8se4Bt9dsIM4Rx/5z7OT7teNLDfUMdD5ZmezPv73qfv2/4OzaXjaOSj+LO2Xf2GE4pkRwqTbYm3t31Li9teAm7287hSYczMXoi9dZ6ssKzeGnjS7Q52pgWO40H5z7InKS+eaOnmKYwhSn73Se/MZ8Hlz/IptpNhOhDuHv23ZyUcRIGrYGnf3maH0p/wKg1csPUGzhnzDk9hroNZywOp8czAx15M3aXNGYkklFEoJdpnMDtqqrmAnOAGxVFmbDPPicDYzo+1wAvBXhMQw6b08bCnQs9KlFWl5WXN75MblQurY5WHlj+ALsad/nlXEtLlvL53s9xq26cqpNFuxaxqmKVX/r2Bw3WBu5edrcnkbzB1sDtS2+noKlgkEc28viu+Ds+zP/QMxf+s+0/rK5c3ev+de11PLP2GY+6XYujhUd/fpTNNZs9+2yp3cLTvzyN1WUFYHn5ct7Y9oZHMKLF3sKjKx9lW71QV2q2N3PXj3exq8E/87uTzTWb+cvav2Bz2QD4sexHFu5YKFbJJRI/s7lmM8+vex67W4iqrCxfSa2llpyIHJ5Z8wxtjjYA1tes5/l1z2N1Wv1yXovDwrNrnmVT7SYAWh2t3L/8fnbU7+DtHW/zQ6kQf7G5bDy39jk2127eX3fDEou9K2cGRKiZFAGQSEYXATVmVFWt6PSyqKraAmwH9o2ZOhN4QxX8DEQoijLkKicGksq2Sn4s/dGnvai5iChTlOfvh4rNZfM83LozlNTEqtqr2Nu016vNqTp9VNUkh4bD5eDzvZ/7tPc0PzqpaK9gY81Gn/bi5mLP33c3+qomfVP0DQ3WBgBqLbVsqNng9b2KSnFLsc9xh0KnwdWdrwu/7pN8uETSX3oyElZVrMLhcvi0Ly1ZSp2lzi/nrbPWsaxsmU97YVMhXxd+7dM+EiWaLQ63R80MhGdG1pqRSEYXAyYAoChKBjAN2NcNkAx0F88vxdfgQVGUaxRFWaMoypqampqAjXMwCDeGkxWe5dMeY46h2d4s/m7qPfSnrxi1RsZFjvNp7x5aNtiEGcK8ksE76TTqhhrDdV7qtXqmxk71ad9fonC4IZzEYN91hu45Mz19Py5ynEfpLsQQQnxQvM8+0abovgy7z6SGpvq0jY8a7wmHGw0M17k5HOkUtOhOZngmeq1vDlp2RLbf5mGIPqRH9bIYc0yPypE9/S4GGn/PS4vd6eWZMeo0staMRDLKGBBjRlGUEOB94FZVVZv3/bqHQ3xUCVRVfVVV1Zmqqs6MjR1ZMpMRpgiuy7vO6wE3LW4aWo0Wp9vJKZmnMD7a98F0MJyefbqXvG5qaCpHpx7tl779QVJIEg/NfcgrUfXyCZeTE+ErLz0UGM7z8qwxZ3kZFllhWRyVclSv+6eGpXLnzDu9cpcWZCzwUi+bFDOJuUlzPdvB+mB+N/13nuT7WHMsD819yKuPX+f82ksRzR/kxeQxM36mZztEH8INU2/ApPOVGh+pDOe5OdyYFjeN6XHTPdthhjCOSD6CnfU7OS7tOE+7UWvk3sPuJcIU4ZfzRpgiuH/O/Rg0XeIrp2SewoSYCdww9QZC9aGe9hnxM5gSu//8m4HA3/PS6nR5e2ZkmJlEMuoIuJqZoih64DPga1VV/9LD968AS1VVfbtjeydwjKqqFb31OVKVebbUbqGgqQCz1kxKaAoVbRWEG8KJNEV6CqjlRvvW5OgLNqeN4pZij2Tl7obdaDQaxkWOIyvC1yvkD+wuO8UtxTjdTlJDU/u8GulwOyhoLKCkpYRoczRjIsb0quIzAIxoNbOyljL2NO5Bo9EwJmIM8cG+XpOttVupt9YTFxRHdkQ22+u3U91WTbA+mKywLOJCvGvP1FnqyG/Mp93RTmZ4po/Yg1t1s6dxD8XNxUSYIsiJyDlg/YyDoc5Sx+6G3VhcFrLCsvwqMDAEkGpmQ4za9lp2N+6mzdFGhCkCu9OOXqPHrbqxuW04XA5ig2IxaozEBsX6qAD2hZr2Gqrbqwk3hnuk8FVVFb+nlmLCDGHkROZ4aj8VNRVR0CyeKWMixxBt9q8HtAcGfF5e+toq5mRGMz1d1D97+usd3Hr8WI4eKw14iRdSzWwEE2g1MwV4DdjekyHTwSfATYqiLAQOA5r2Z8iMZCbFTGJSzCTPdm50LqsqVnH9t9dT3lZOsD6Y22fczmmZp2E29F3ZrLq9mlc2vsK7u95FReW41OP4w6w/HLAuzKFQZ6njX1v+xZvb38StupmXNI97D7u3x3CMfdFr9IyLGuf31XqJL8mhyb1Kf9tddr4p/IYnVj9Bs72ZGHMMDx3+EC9vfJktdVsw68zcOetOTs081UtpL9ocvd+XJo2iYUzkGMZEBrYw5oHGIZH4k5igGI8SYE17DYt2LeK1za/hcDsYHzmem6ffzFVfX4XVZSUzPJOnj3y6Xx73jdUbuePHO6hsqyREH8JDcx/iuLTj0Gv05ETm9FgcOT08faQZ8T5YHPt6ZjRY7M5BHJFEIhloAh1mNg+4FDhOUZQNHZ9TFEW5TlGU6zr2+QIoAPKBfwI3BHhMw4ay5jIeWfkI5W3lALQ52nhs1WNsrd/ar35+qfyFRbsWeapJf1fynVcxtkCwvno9b2x7A7fqBoSq1cd7PpbFzIYRW2u38tDKhzx5W7WWWv644o9MjZsKgMVp4eGVD/eY9C+RjGY2127m5Y0ve1T8djQIdbFOz/repr38adWfaLG39Km/2vZa7v7pbirbKgGhWnbXj3ext3HvAY4c+dj2EQAwaKUAgEQy2uiXMaMoSqSiKHmKokzv/Oxvf1VVl6mqqqiqmqeq6tSOzxeqqr6squrLHfuoqqreqKpqtqqqk1VVlbEQHVS0V/ioPLlVNyUtJb0c0TPLy5f7tH1d9LVHtjYQrK1a69O2uGgxrY7WgJ1T4l9KW0t95ki9td6n+KRUmpNIvOlJnW9N5Romx0z2bG+o2UC9tb5P/VVbqilt9f6duVQXZa1lhzbQEYDV4fKqM2PQabA63IM4IolEMtD0OcxMUZRHgSuAPXQl6KvAcb0dIzk0okxRRJuiqbN6y3jGmeN6OaJn8mLy+HTPp15tsxNmeyWN+puelHRmxM3ArDv4wp+SgSXOHIdG0Xi8awBmndmnVkuM+dCV9iSSkURP9+gxkWO8JPbTw9K9EvT3R4QxgnBjOE22Jq/22CCZF2Jz7uOZ0Wlol2FmEsmooj+emfOAbFVVj1FV9diOjzRkAkhWRBZ3z74bvaZL3vOyCZf1W9lsXtI8JkV35eKkhKRwZs6ZiJSmwDAzYaaXmlR8UDwXjr/QS8VKMrQZHz2eG6bcgNKRN6lVtNw5604WFy727HPx+ItlbpNEsg+ToidxXGrX4zFUH8qlEy711IQx68z8cc4f+ywCkBSSxCNzH/G6f9487WayI7L9O/BhiM3pXTRTr9VglWpmEsmooj9vlluACKA6MEOR9MTx6ceTGJxISUsJ8cHxRGmDKaneTGtQHBpDKHW2OmLMMbhUFw3WBuKD4ml3tNPqbCXWFEtlWyUWl4XHj3icivYKXG4X6aHpNDua2V63nbSwNI/KWJ2ljtLWUoJ0QWSEZfRYI6EnHG4Hxc3FtNpbiQuKo9XeSrurnUfnPkpFewUOl4PM8EwSQ0ZVLdRhQYuthaKWIrSK1msugKh/dN6Y88iLyaPGUkNicCK50blMjJ5IYXMhkcZIcqNzsTltrKxbiVbRMiZiDG63m/ymfNqd7aSFppEVkUVxczENtgZizbEkhyZT1VBARUsxocYI0qNy0emNg/ivIJEcPI1tteQ37cbudhFqCKPZ0UJWWBb3zL6H88efT5u9jdTQVFJCU3j95NdptjV7tjfXbBZKgeY4XLiIMkWRFJJESUsJte21xATFkBqaSllLGXHmOF5f8DoN1gZizDFkRWTRbG9mZ/1OQg2hpIelj8rFon1zZow6rcyZkUhGGf258z0BrFcUZQvgCaRXVfUMv49K4kGn0TElbgpT4qawrOBrLlt1K832ZoJ0QVw75VoW7lhIm6ONa/Ou5ZVNr2DQGvjtpN/y3LrniDXHcuH4CyloKqDeWs/3Jd8DMD1uOtPipvHaltc4Kf0kbp95O832Zm5fervnxfaavGu4JPcSwoy+BSy70+5o591d7/LXtX/FqTpJCE7g8gmX8+yaZ0kLS+OZo58JuGqV5OAoaSnh0ZWPsrJiJSBqxtw+83YSghMAcLldrK5ezQPLH8DitBBliuLJI5/kgeUPUNVehU6j4+ZpN1PcVMz7+e8D8Mrxr/B9yfcs2rUIt+omMzyT+w+7n5u+uwmL00K4MZzH5j7C8+v+Rn5TPnqNntvzruPssedgPgipWolkMCms28nLW//F53u/AGBC9ASOSj6KxUWLiTRG8q+t/8KtuskIy+DZo5/11Hlpc7Txzs53eG7tc9hcNqJN0dw/537+vPrPXDD+Ah7++WHaHG0kBiVy12F38eCKB2myNWHWmXl47sOMixrHjvod3Pr9rZ7f4h0z7+DsMWePulBem9PtUzRThplJJKOL/oSZvQ48BTwJPNvtIxkASmu3c+fPD3uUpdqd7fx9/d85I/sMmu3N/HPzP/lVzq+otdTy9s63OSnjJEpbS/mp9CeSQ5I9hgzAuup1tDpaiQ+K5+uir1levpyXN75MUYuI53apLl7a+BLb6rcdcFw763fyzJpncKri4VHZVsknez7h2LRjKWgq4JWNr2BzBk5oQHLwfL33a48hA/BV4VesKF/h2S5sLuSen+7B4rQAMCthFs+seYaq9ioAnG4nz619zkvaud5az8KdCz15Nnub9vLm9jc5OeNkAJpsTfxxxUPMSZoDCK/ekxv+xq7a/in0SSRDgbW1mzyGDMC2um1UtleSGZbJ/235P8/voLC5kL+t/xtWpxUQSoFPrX7KI7BRZ63j6V+e5pq8a3hw5YO0OdoAmJ8+n0dWPuLJlbE4Ldz7073satjFwyse9votPrn6SXbV7xqwax8q2J1u9LqukGmRMyMFACSS0UR/jJlaVVVfUFX1e1VVf+j8BGxkEi9q2ippcXjLeNrddo/ccqOt0VPdvKi5yLO6XmetY1eD7wNuc+1mciJEXYIV5Ss8kp/dKWs5sFJOWZvvPtvrt5MZnunpu8ne5LOPZHBxuBx8V/KdT/vPFT97/l7ZVumRlgWRsNzTXLK6xAtaakhqj0p7a6vWMiWuq/J4g63BRxGtvLW8/xchkQwyW+p8jfBN1ZuwuX0XcH6u+JlGayMg5ruKt0x9RVsFdtXuWTwACNIH+SieOVUnZS1l7GjY4XOOnu7HIxmHSxgtOo2sMyORjGb6Y8ysVRTlCUVRDu+rNLPEf0SZY33CB3SKDo0i/gtD9CE4XOLFMzE4kXqLeACGG8PJCs/y6W981HgKmwsBmBE/g0hTpM8+nQbR/ogP8q0YnxWe5TGEpsZNJcyw/1A1ycCj1+qZmzTXp316XNdPOjYoFq2i9WxXtFaQEZbhc4xRK/JdSlpLSApJ8vl+UswkdtR3vXiF6kN9JJ97mkcSyVBnXORY37bocRg1vjlgU2KneMJ244N953uMOQajxugl+GJz2XzunxpFQ0JwQo+/xdH2O7LuUzATRM6MRQoASCSjiv4YM9OAOcDjdIWYPROIQUl8SYuZwGOz7vbIKesUHb+d/Fu+2vsVBo2BqydfzSd7PiFIF8SlEy7li71fEGGMYH7afFrsLZ5YbYDM8EwSghIoay1jRvwMjko5ihun3kiUqStn4fxx5zMhesIBxzUuahxXTbrKsx1mCOPcseeyuGgxMeYYbp52s8djJBlanJp5KmO7vYzNip/FEclHeLYzwzJ5YM4DHoNmaclSbp95u5ec7JUTr6SoqUtuNi4ojpPST/Jsx5pjuXLilSzauQgQhs/9h93H98Ui7FFB4brxlzA2emJArlEiCSQzYqYwJ3GOZzslNIUxEWPY27SXs3PO9rRHm6K5bcZtHo/khKgJXD/les9ilFln5g8z/8Brm1/jntn3eBL5v9z7JXfPvtuzYKBVtNx72L2MjxrPQ3MfIkQfAojf0bV51zIucnQpC+4rywydYWbSmJFIRhPKcKzIPnPmTHXNmsGtrelW3RQ1F1HTXkNsUCzpYemeB1OgcDntFNVtpbK1gpjgBDTGUKotNcSaY1FVlVprLfFB8dhddhptjcSaY6lpr6HN2UZ6WDot9hZcqov4oHiq26vRKBoywzM9Xpny+t0UNxYQbAglM3o8IX1MyLY4LRQ0FtBsbyY+KB6L00KLo4WM0AwSQg7s3Rni9Fm/eijMy/5S2lLK7obdaDVaxkaM9fn/crgc7G3eS62lloSgBDLCMyhrLaO0pdTj9aturya/MV+omUWOweW0s6elEIvTQlpoKmMjx/n0UVq7nbLmYsJNkWRF52IyhQ/Sv8CwpV+66sNxbg41mqxN7G3ei4JCRngG4UYxZyubitjdVIDd7STCFEWjrYFMczxxdjsFOpV2t5O0sDQfr2WLrYWdDTuptdQSHxyP6laJNEeSHJJMcXMx1ZZq4sxxpIWlUdpSSmV7JTHmGDLDMj1KkyXNJZS2dv0Wh8DC0YDOy9KGds76xwpeuGCap217RTOfbCznoxvnHXS/khFJ4GpRSAadPhsziqI8Djytqmpjx3YkcLuqqvcHbng9M9gPZrfqZnHRYu5bdh82lw2j1sgTRzzB8enHB7R2S0Ap3wgLL4DmjtyFw2+CI2+HoFGvMDVijZnCpkLuW3Yfm2o3AXBk8pHcd9h9Xgn9/aa1BpY+CWv+T2xHpMMFb0HCpP0fJ+kv0pgZQIqbi/nj8j+ytnotIIoOPzz3YVJCU7x3bK2BpY/Dmn+J7dE3/wd0XuZXt3LFv1fz53O6Ig8Kalp58+civrz1qIPuVzIiGaYvZ5K+0B9XwsmdhgyAqqoNwCl+H9EwoKi5yGPIgIhrvnfZvV7VnYcV9jb49sEuQwZg5YtQsWHQhiQJPF/u/dJjyAD8VPaTl7rZQVG+tsuQAWgsEsaNw3po/Uokg8iS4iUeQwZgdeVqlpYu9d2xbG2XIQNi/v/4tJz/AcLmdKHX+ubMtMucGYlkVNEfY0arKIonq1FRFDMwKivd1bTX+CQwW11Wai21gzSiQ6S9AYqW+7Y3lg78WCQDgsPl4MeyH33aV1euPrSOa/f4thUtgw4VJ4lkOPJjqe9vZUXZCt8d63b7thX+BJZG/w9KgtXRc86MVRozEsmooj/GzJvAEkVRrlIU5TfAYkTtmVFHXFCcJyGzE7POTKw5dpBGdIgERUL6Eb7tEakDPxbJgKDX6jk65Wif9tkJsw+t45gc37aMI8EUcWj9SiSDyNGpvr+Veck95GTE+KqbkXG0uMdK/I7N6fIqmAlg1GuwOmSdGYlkNNFnY0ZV1aeBx4BcYCLwaEfbqCMtLI3Hj3gck1YkW5p1Zh4/4nHSwtIGeWQHiSEYTngYwjvivxUF5v4OEqcO6rAkgeXkjJOZGjvVs31MyjE9yjX3i+QZMPvaru3IDDj6btAPemKyRHLQzE+d72Xoz02c2+NiAMnTYdbVXduRmXD0H0A3KoMYAo7N4fY1ZnQaKc0skYwydP3ZWVXVr4CvevpOUZSVqqoe7pdRDXE0iobj049nbORYai21xJhjSA9LH9jkf1sbVG6E5gqITIOEKaAzeO9jaYSaneC0QPQYCN9PYndiHlz1LTTsBUMIxIwBvbn3/bvR7minoKmAZlszqaGppIZJj85wID08nb8d9zcKmwvRKlrSw9I9dTD2S30BNBQKb0vseDB0K4AZHEPLMXdRkHcmFkcb6eFZJEb14K3Zl+ZKEaKj0ULsOFB0ULsTHO0QlQMRKQfuQyIJEKlhqTx3+MPsbchHURQyInII05qgaCW4neJ+GZoAwbFwwiMw/VJwOcBlh9ZqMIZCRN8WuxxuB4VNhVS1V3nqyXRKNUu8sTpc6HXez129VoPD6cbtVtFoZM63RDIa8OcdclQtvWoUDRnhGWSEZwz8yW1tsOY1WPIQuF2gNcDpL8DUC7v2aa6Ar+6GbR+J7bBkuOgdSJjce79hieLTD5ptzfxz8z/5z9b/AKIg4ovzX2R6vKynOhyIMEUw1TS17wcULYe3LgBbs9g+4vcw7/dgFjK1te21PLv2WT4r+AwQhQD/Mf8f5Ebn9t5nzU5YeHFXvsHRd4u/b3lfbIcmwEXvCoNbIhkMavMJe/83TKnYKLaTpkPe+fDVXWI7eixc8KYwxA1BEJYESx6FdR2R2EHRcPF7wnOzH5xuJ18WfMmDKx7EqTrRKToenfcop2SdEnDp/+GIzen2EQDQKIoINXO6CDJII1AiGQ348+44/ArWDFcqNgj1MXeHK91lhy/vhM4HLUDp6i5DBqC5DJY9B05v4YJDZUf9Do8hA9DiaOHRnx+lUSZ8jzzaauGTW7oMGRBzqmqLZ3Nz7WaPIQNQa6nl7xv+jtXZi5qTqsK6/3YZMooivDOdhgxASyX88DQ4LP68Gomk72z72Pv+Wr5OeLGDosV23S5Y/6aYzwDlG7oMGYD2Ov6/vfMOj6u4+vA7W7TqvUuWZbl3jI0bYKrBtFBCaKHmSwghkJBKCAkhQBoJgSSQEAi9996bsbHBuPcmSy7qva+2ab4/ZuXdlVbN2tWupHmfZx/tnTv33rPa2bn3zJzzGz76Hdiae73MgaYD3P7l7TilEwCndPK71b9jf+P+wH2WEUS7o7uaGUCkyagXztRoRhF6qGc40lwOskuCo61JhTN0Ur2n+3EHVkN7U/fyQVBlrepWVthQSKOtMaDX0YQB1gb/ak1NpYfflrR0V8DbWLWRJnsP7c5pheLlnm1zDFjrutc79GXA265G02+KPuteVr1b5YQdrrMcOp32xtLu9UvXQnvv/WKttRZHh8OnzN5hp67dz29CQ7vDRYSxeyiZxWzAqp0ZjWbUEEhnRgenDhWJeeBeAfow0SkqlKwTf4u0TVoGUYkBNSUnpnsezqzUWSRHjvrFNkceMamQNad7udcD3bj4cd12H5dzHImWRP/nNEfD5LM92/YWz2i3NxNOgyitCKUJEVPO6l6WORNqC73qnO3JM/R2cjopOBmi/LRtLzKiM4gy+eYqRpuiSY9OH6DBowObswNTDzMzWgRAoxk9BNKZuSKA59L0RtZRcPZ9KlEfIDoZvvEvyJjmqZN7DCy6ETrjrLPmwMIfdHeCBsnk5Mn88phfYjao82bHZHPrwluJs8QF9DqaMCAqEc65FxLcAg/GCDjjL5Ax/XCVGWkz+O7M72IURgAmJU3ie7O+R4Qxws8J3cy+CMad6Nk2mJWaXmfbzZwJx/64u8CFRjNUTD5LvTqZ+g3lsHTOtIw7EWZ+y7M/+yg48RYVMgmQOhlOvhUiehdVyYvP469L/kqcWfWf8RHx/PWEvw5fpcwg0+7onjMDEGE26DAzjWYUIaTsX6qLEOIC4C9AOmoWRgBSStmj/JEQ4lHgbKBKStltqkAIcSLwBlDsLnpVSnlHX7bMmzdPrlu3rl92hyXN5VC1S8VXp09RyaIAdcVqpM8crcq7jlA77VCzBxoP0Z4ygX3tVVS3VZEdm8O4tJmYzVFuBbOd0N5EfVIehc2HaHdZGZdQQG5bk8qZic9WoUEGo1KjistU56/dp65viYf0qerh1eVUqlINByE205Pg6m1Wh5ODTQdpdjSTHZs9fNfb8U+/ZxxD3S4bm8sorNtNq72F/MQC8tKm9+OgUqje5W4LUyEuo9fqsqOD4qrNHGo6QEJkEhOSpxLrcvicw+5o40DzQdqd7eTGZJOUMAYqtqhrJeVD1mxoPKTae3SyaoNSKpU0owmSx6tz1RaqPJmkcRDT+4j2KGRAM+GhbpvDivqDqs8zRap+OMbdn5Vvg8aDKq8rPhdcNmiuBOlSM+HCCBXbqI+IZJ/ZhDRH43BacTpaGZswnrEpftag6YGS5hJqrbWkRKWQGzeslPyGtF3e/f4ualvsnDfHN0Lgj+/u4JYzp7J4fOoRn1sz4tDRQyOYgUh93A2cI6XcOYBjHgfuB57spc5KKeXZvewfWdTshReuUA4HKNnZS58Deys8fT5Y61X5pGVw1r2Q4HZ0OjpUUvQb12Obdh4vFMzhb9seBsAojPxx/q85I/cUxIe/hi3PU3Huv/hd4XOsrl4PQJIliQcX/JZppRvh7aeh4YA6b+ZM+NbjKkH16Qs9yd0zLoRlf4T9q+HV//OIDZz6e1jwfR/ZZpPBREFiQTD/a5o+qGko5k9r/8qHZSsBpSr34Al/Y1ZOL+vGVO2EZy/2aguzVFtIGd/jIWsOfsaNX/yKdpfKDbhkwvncUFNDwsZnVIXjf05E+WYmFn6ktsceB+NPgk/vVNsGI5x5D2x8Fkq/VmULfgAn/gpyuoSwZfTDGdNoAkn5Fnj6AmitVtv5S+C8B6CxBN74oXK4AU7+Dex8W4mxACTkwfE/oapiI3caW4mJSafR3sgXpV8AEGuO5cGlDzI7bXa/zMiNyx1uTkxIaLO7iDB1n5mxmIw6Z0ajGUUMJMyscoCODFLKFYDOXPRm59seRwagrlA5KWse9DgyAHveh1KvEau6ffD2TSA7KJp9Afds+9/hXS7p4vb1f+Ng4z7Y8jwYI9hkNhx2ZADqbfU8XPgqtvgsz8MrQMVWKN8KH9zqq1K17WU49DW8daPHkQGlola9KwD/CE0g2V6z7bAjA0pV7p5ND9DaWtvzQZue7dIWtsDeD3usXtd4kN+v+9thRwbg+cLX2J01RW0IoULBOh0ZgHHHw2d3ebY7XPDhb2DBtZ6yNf+BCo8imkYTEpwOWP1PjyMDsH8FNJbBrnc8jowlXqmSdToyoGZsDq5hS/YMlletpSCx4LAjA9DiaOGetffQYm8Zms8ySlBqZt0H3CNMOsxMoxlN9OnMCCEucIeYrRNCvCCEuLSzzF0+WBYJITYLId4TQvQ4FCuEuFYIsU4Isa66urqnauHPoS+7l+3/AvxJGdfv97xvqz2slFPnaEF2UcK2Oq002NzniM/hQFt5t9NtadhDq7+Y7fYG9SDbleYK/1KiLcP4/x9gwqVdVrZ1v/bOhr002+r91EbJeR9Y1b28pOeQjyZbIyWt3dXKatwyspgiuyuOdTg8crWd2FtUuTctlT1eV3NkhEvbHDbYW6BkbfdyS6yv4xKX6ds3d1JfTKmrFYHA6uwuI76zbqd2Zghsu2x39jQzo9XMNJrRRH9mZs5xv+KBNuA0r7LBhodtAMZKKWcD/wJe76milPIhKeU8KeW8tLRhnJMx2Y8qzvTz/KvfeIfZxOeo/AIgyxRLhME3GTolMoWMaPf/peEAU+O7n++UzEUkWP04J7EZMPH07uXJBRDXZRFNoxkSx3SvO0oJl3Y5Nr77d3Ji5gKSYjL9H2CMgOnndy+fuLTHa6TEZDA7uft4Q25ntKrD2l1xTBjAZPEti83o7uAk5/d4Xc2RES5tc9gQmQBTz+le3t6olMg6qd+v8ry6kjWbicYYJJJoU3S33Utyl5AUqRX5Atku2x0dRPgRALCYDLTZnYM6t0ajGT706cxIKa+RUl4D/K/zvVfZI4O5uJSySUrZ4n7/LmAWQozsjL2JS2HOlSokRwi1ivSkZTDv/2DssaqOMQJO+g3kzPUclzgGLnoK4rLI//we/r7gN4flbjOiM7hn8R1kJk2EM+4GYwSzKvbwgylXYDKoB80FaUdzWcYijFU7lIQoqAfNud+B7Dlw0q2Q7b6eKRJO/yOMma9yKBLcsdtRSXDhE5Da/0RWzdAwPXU2P5t53WEnd1byNL4/47tYLLE9HzT1XJjunlwVBtUGx53QY/W4mHR+c8wvGO+WX44yRfH7Y37FpIYqzzmMFljyS9WGAcq2wHkPepyc+BylvNeZYxMRC+f9B9J1fowmxBgMMPcaGH+qe9sEx/1MiZ6MWwLTzlN9dodDtdt5/+dR3JtyDmTPZcauT/jRxItYU76GK6ddefj3ODN1JtcfdT2Wro69ZlC0O1yY/czMRJgMtGlpZo1m1DAQNbMNUsqj+yrzc1w+8HYPamaZqFwcKYSYD7yMmqnp1ahho8zTUgVVO8DWohyANLcT4Gj3xF8n5XvUwayNKofBFKlmRYx+9BmaylVITmwGZY4mGqy1xEcmU9lcQl17LXnxYxkfmY7J1owjIZeSlhJsLhu58XnEttUrIYH4LKWoZjABQi2EaIpWSlaNhyAiToVW1O9XimoJOUolzRKnws4aDih53vSpPkIAI5Rho2bmcto5VLcLq8NKTsJY4mN7mJXxxt6mVjIXBkgeR62jlb31e2lztpEfn09BVLpqw80VyqFOnUJ9/T7KW8uJjYhlTPIURHuDas8GI6RMVAthVm4HWyukTVQqaRXboK1Gtb30qVBbrNpaZILaH50Y7H/PSEOrmQ0GKdWil7V7VRtMn6bWUQLVx9UfULPQSQVK2axyu2r/LqfKC2upBumEmHSVayNQIi6xaTiFkUORMTiNRpDglE5yYnOIt/gX/myxt1DYUEi1tZqc2BwmJE7oXco8vBnSdnnJQ19y0uR0ZuUm+pS/sqGEjHgLvzjdzwyaZrSi1cxGMH2qmQkhFgGLgTQhxE+9dsUDxj6OfQ44EUgVQpQAvwPMAFLKB4ELgR8IIZyAFbikL0dm2NBUBm/cCPs+VtvmaLjiNchbCOZI3zVhOolKgKhZvZ83Pku9gGyyiKnfz7+2PsgLxe8AStns74t+z8kTz8UMjPOWtPV+uI1OhrKN8OR5nnydzJkw4VSISoZPfg8d7mn6OVfCKbfBlhfgw1s95zjzr2okM8Br12iODKMpgvz0PtpPVyKiD4czVrRW8LvVv2N12WpAzbz8d+EdzHnmMpW4b4mDs+8j6fXrSHK5c15mXqycmM3Pqu3zHoT1T3hywyJi4MLH4PnLVHsSAs74K6y+Hxr2qzpHXQ6n3Xk4jFKjCToHVsHT3zych8jks+Dse9WAjiXOs+jwwa/gxSs9OV1L74R1j6oBAFBhuMfdBO/drLajkjBd+QbjUvv3EN3maOOx7Y/x0JaHABAI/nDcHzi74GyE0M9efdFTmFmkyUirTc/MaDSjhf7kzEQAsSjHJ87r1YRyRnpESnmplDJLSmmWUuZKKR+RUj7odmSQUt4vpZwupZwtpVwopVw9uI8TRpRt8DgyAI42+Og2/wn1g2Bv/e7DjgwoZbM7NtxLZXUfwnNOG6z8u6/wQMVWFe7z1QMeRwZg45NQuh4++q3vOT74te8K2Jphzfba7YcdGVCiEvftfILWSe58qhnfVGp2Lq/k/a0vQLIKO0MYwNHqK3Jhb4WV98DiG9W2lKodzfDSDtn0tFYz0wwd1gZ492aPIwOw+x3fJH9Qs9ibnvE4MjFpajax05EBNcNdsRUSx7rPXQ9fPqBmcPrBvsZ9hx0ZAInkrq/u4lDzoYF/rlGIrYcws0izzpnRaEYTfc7MSCk/Bz4XQjwupTzQV32Nm6aK7mVVajFLLHEBu0x9p4KZF7XttTTbG+l1+UN7C5Rv7l7eYVchRV1prQbZ4VvmcoBVK2+PFKraqrqV7W06QEvqEmJAheE0dlczw2VTfy3x/pXuavbAnCs82w6ryk/wplWrbWmGCFsz1PiRl2/t0v6dVqj0crLjs30dmU5qCyExzyNzXrZROfFRCX2aUt/eXW2wzdlGk73JT21NV6wOFxZ/amZmI62N7X6O0Gg0I5H+SDO/JYR4E/iXEOLNrq8hsHF4kja5e9m0c1WMdQAZEzcGg/D9GqclTSY9Nrv3A6OS1Uh7V4QJsrukQQkBKRNUbLk30SlqsTjNiKAgofvCp0szF5Bc7J6tqdimRCG8EQJM7ryp9gbPLI03E0+DvR94tuNzoM3rIU4IlSOm0QwFMWkeERRvUib4bkfEwKQzPdvVuyHrqO7HjVngK20/81v9cmQAcmNzuylT5sbmkhndj3w3DTZnT2FmBlr1zIxGM2roT5jZ34B7gGJUXsvD7lcLoGNDeiJ7jlrpPMKtJjVhKRz7YzAFNr9kfNos7ll4O0kWpRY1LXESv5/3S+L7cjKEgKOvVPK8QijRgcU/UotlzrrIc9OOTlY5Dzlz4ZJnVeI/KOGCi5/WMs0jiBmpM/j1gl8flpU9Luc4rpl8KebOWZO6Ijj1DsiZp7ajklSOjKPdrWRmVqISp/xOPQgCFJyk8qo6169JmQjnPwhVuzzn+OajvjLkGk0wMUfCSb+G/OPVtiUevnE/ZM7uXnfq2UpxUhhAuiAuGxb+ULVzgxFmX6occWe76kdnXqTq95P8hHz+cfI/SItSEsUFCQX89YS/kho9skU9A0W7w/86M5FmI6027cxoNKOFgaiZrZBSLumrbCgYNso8UipVHKdVOQH+ZHJLNyilnMh4iE5VITlxOWC2uJV2EtWDXvrUnq/TWk954z6aHa1kRqYS31QOtkY1a2JvUTHiSXnQVqdCfNKnQap7FLJ6LzQeAEOEuinbm5VYQWSCEjGwxPk6LM2VSpUqJg1iAzvLFKYMGzWzbjRXqtyt5nLVFrLngLcgBKgQmcod6sEsYwYyMY/SllLaXe1kx2QT7XRC2XpoKoWkcZA6Baq2Q32RapvpM8FapUatDUalTBafq8J4nHb1PmOqyjtoq1VrzMSkKuW+5lKlnKcd4iNBq5n1B6ddhYrVFak+K3OmR2jC1qx+I83l0Fiq2mVLhRrYscQrB6a1WjkuUUmqH010DxLZm8FgVv027sEggdp/BAqPlW2VNNoaSYtKG+5r0Qxpu5x22/v869I5REf4RswXVjXz/NpDvPOj44/43JoRh1bUGMH0mTPjRZoQokBKWQQghBgH6JXYekOI3hcDLF4JL1yuboyn/QFevVY5EUvvhBd+oBSkQK1xcPqfIdPP6HVbHXxwC1lbnidrzuVQsxcOrVH7DCZYegd8eicglCLZB7eoh9Ar31A5L09+Q8V3g3JyLnkWktzJrFGJ3a8Xl6FemvCmrR5W3Qdf/dtTdvJvYNGPlKMMUL4FnjpXtSGAhDGIy18htzNE0t4Kq+6FL/6utiMT4fQ/wJs3evKnJp+pQhY3PX34HJxxNzx/qdo2RSoVv7GL1crpnUQl9DsUR6M5Yna+Aa9+z7NI61HfVn1tdJIaqNn/Bbx8jZpNfOcmNdgDkDkLxp8Eq/6htpPGqbDcT25X68t8crsqj06BK9+EdD9hxQMgIzqDjGjdrw4UW4+LZhpps2s1M41mtNCfMLNOfgIsF0IsF0IsBz4DbgqGUaMChw3WPqLyDMafDNteUaEKJ9wMn93lcWQAilf4JqJ6U7kdtjyv3ieO9TgyoBTJ1j0KU7+h1NR2vqUWRbTWq/JNz3scGVDriRwYOYJyo5rKrb6ODMDnf4EKt+iDlLDhSY8jA0qpafe7nu3qPR5HBtTD3Kd3+gpB7H7X4/x2nqNsg3r4A9WmP7494Cp+Gk2fNByCd37ucWRAqZNV7XDvL4HP/gR5i2H7ax5HBlQOjCnSvRYXKvHfZYP2RmgpV04MqNnGzgVgNUOKw9WhJsX8ODNRETrMTKMZTfTbmZFSvg9MBH7sfk2WUn7Q+1GaHnG0qjAyUAnR9fvV+6hk9UDYFW8JZW+81cRc9u776/er83d9X7EFHC1+6mvBuhGBt5PSicuhHFlQjm75xu51Knd43ndVWopO8q9017Xd1e7zFcCo3evrNGs0Q4Gt2X+/2dlntjcqJyXBq//1pr1Rhdx20lyhnJjGUhUu2Un5JiXjrBlSelIyA7XOjNWhZ2Y0mtFCf9TMTnb/vQA4Cxjvfp3lLtMcCdHJasYE1AJuE5d63k9Y6lu3N7Wn5PGe0UPvG28nE5fC/pXq/YRT1PkBZl8GaX4WdstbMLDPoQlPkgu6q8/F53jakdEMs7/d/bgpXupNSfkqd6CTso2epOlOhEGNYHuTfzwULfdsz7xI5StoNENJfDZkz/UtM5pVnwlKeW/KWSrUbMKp3Y+PTQebl0Ry6iQlv5w50zMQBTD7ku5S45qg027vxZmJMNBmczFS1uDWaDS9058e+AT333P8vPzoW2r6zbRz4eir1KhgXJZSFlv3iFJ/KjhZ1YlNh3Puh5z5/s+RPhUueU49qG57GU77o0pkFQImLYPcY9SClzO/pWZ9mkph0Q3qJj79AnV9g1E9tJ75N1VfM/zJmgXffMQjN5sxXamIpU701Jl8hlKwM0aopOWTf+vrrCQXwGXPKwUygNY6OPEWT524TLjgYRWeYzQrZ/r4nysnyBylHJ2ZF8GC61Qb02iGkqhEOPdfMPY4tZ2QC5c87xnEiYiGed9VuYKdg0vCoHLDTr1dLSxsMClFykU3qhyzxTeq/QYTmCxw7E+gc1FZzZDS7ujAYvbfr5gMBowGgc2pZ8w0mtFAv9XMwokRpcxTsU2FKRjMan0XW6N7pNsA1hr1oClMSlEqJg2y5kBKl7U8WqqgdJ1asDB9KsRmqpCi+Gx1DqddhVI0Vyp50YQ8MLpnc5x2FdZmjNCqUv4ZvmpmAPUH3epzGZCY032/y6m+f2FQSkzVO6Fsi1LBS5sCGdOUwl57k3rgSx6vQnNaqpTzkjoZIqLUccIIGbOhtUK1R1srZM5QydR65DrQaDWz/mJrViFilgSIcyswupxQsRUaDypFvcZDSnY5JgUwqBkZUwQYLYBU+Tcum/pNRCWrME1bI9QVq/d9KU6OHoasXe6uaObaJ9fx52/O8rv/+0+v47OfnUhKrOWIzq8ZcWg1sxFMv9XMhBD7gK+AlcAKKeWOPg7R9EXpenjiHE8+QXyOUhmr2QMvfNuTuJozV40ebnxKqUedcbfH8WitgXd+qpL7OznvQTjKrSYV4eWgeCdqd2KKgJTxgf9smvAgKU+9esJo8ix0WbFNKT91JkgbTHDho/D69cq5ATUzs/01qHavEzP+VDjv32rhQFCzjM9dpuSbQc3YXP6qUuTTaEKBJU69vCn6FF64Qik8fnSbckiEgLPug/dvVsIVoGYZZ12sxDNAzZRf6V4r+tmLlawzqNmbq96CnC4LDmuChtXhwmLueZAkOsJEq81Fip8VETQazchiIMOl04D/AinA34QQRUKI14Jj1ijA5YQvH/BNjG4qVQ+J7/7CV4GndL3Hedn9ru9q05XbfR0ZgPd/pUYSNZqBULbB48iAesD7/G44/qeespV/g6nneLb3fayU0zopXe9xZEDNEH50u5rZ0WjCgdZaeO9mFYa78WnVzkGFo2172ePIgHLOXXbP2jEtVbDrHZVn0+nIgHL2v37IV4VSE1SsveTMAESbjTTbHENokUajCRUDcWZcgMP9twOoBKqCYdSowGVXMzBdsVt9b5KH63t1ytYGz/v2xu512xuUWppGMxCs9d3LmrooN7n8PBx4t8HWmu77G/b7yt5qNKHEaYXGEjXL0lTqKe+63Ym13ndmp7bQfzuv3uX/96EJCu0OFxGmnnPxlDyzdi41mtHAQJyZJuA+oBi4Skq5SEr5/aBYNRqIiFbJ912Jz1breXgjDCrZFFQ+Teokz76UCSrfxZv84yHOT36ERtMb/mL+p35DhZV1klwALZWebYMJUrzaY+bM7uc46ttazUwTPsRkwKxLoPhzJYLRibeqpDeJeWpGppMpZ0P2nO71jr4KzJHdyzVBoc3uIqKXmZkos5Hmdu1cajSjgYE4M5cCK4DrgeeFEL8XQpwSHLNGCVPOgSW/VCEMUUlw9r0qWfrEW1SctsEIiflKZWzTs8qJ+dbjKoemk/Sp8O2X1T4h1DnPugci43q6qkbjn9yFcO4DSlnPaIbZl8KcKzxr1uQvUflYjnblYCeNg8teVCIBnWTPgQsfV0pnRjMc8z045rtaAEATPpjMKnQy5xiISVdKj0Yz4FaAXPxjNXgUkwrfuF+tLRMRo1TMzrgb8o+DvIVw5j2q3zZHqz578pl9XVkTQKwOFxF+FszsJCrCSIteOFOjGRUMWM1MCDEFOAO4CUiXUkYFwa5eCWtlnsYStR5Ha41Svsk+yhNv3RUpVWhCU6lSgrIkKFUoc5RSNhNC3SgNJmguVTfThFz/52qrU6o9sek9X09zJAxvNTNvHFYo3wxVO9UDWu48tUhqxVblbGQdpcrqilXd5HGqLVkbVehidLIKt3G0q9mZiBj1wOePliqVe9DpGGkCzehUM2uuVP1rU5kSLsmeA5HxfR/XiaNdqUdW7YDYLDXoY4xQCfwxqar/7HCp8xvNyimX0h1+ZoCEbN/zNZWpBTMTclR/rRmydvnUl/tZubeGa44d53f/o6uKOGFSOpcv9CN8oxmN6B/oCGYgamavAEcBhShFsyuBNcExa5jSVA6vfBcOfukpO/8hmH2x//ola5WaWWfCaUwqzL8WPvujGvW+/FWIdYfnRCf1fu3oZPXSaHpi19uqfXZyzj/g/VvA0aa2o5LUmkVjF/keF5WgXp2YI/0r43kTmx4YmzWaTqz1SmnMO+zx1Dtg8Q39X8do97vw8jWe7cxZyoEvWQuXPKvKDEZfmXoheh5Eis/2X64JOlZH72FmkSYjze16ZkajGQ0MJPbjz8AkKeXpUsq7pJSfSykPy74IIfwEG48yKrf6OjIAH/xKjd51xeWEL+/3Vc5prVEzLFFJai2PkrXBtVczemgqVyp3nWTMgMJPPI4MqIfF3e8MvW0aTX+o2unryAB8dhfUFfXv+OYK5Qx5U7FFzb5UbFWzlpphQ585MxEmnTOj0YwS+u3MSCnXSil7kwb5SwDsGd7YmruXWetVaENXOuxK9rMrbbUqnAzAWhdI6zSjGafVk/sCKszMO5G/k8aSobNJoxkIdj8KjS67r0PeG452/ypkndLM/vpvTdjSZnNh6SVnJjrCSKNVOzMazWggkFm5Oh4xdXJ3ZbFp5/sPRTBHw7z/616ePk1J2YJ/xRyN5kiIz4EZF3q2S9ZCwYnd600+a8hM0mgGRMp4iEzwLcueC4n9zImIz1IqZt4YzarPNhghzY+anyZsabU7iTT3HF6onRmNZvQQSGdmYEoCI5GM6SrPJWu2Siid+x04+bc9y3VOPgOW3qkeNJMLYNndcGA1JBWo+O0s7cxoAoTJAifdohzo2EwlTjHuBDj5NiWbHJ8NZ/wFxi0JtaUajX+SC1T/OvY4JT4x/QI4798Qldi/400WOOFmmP99JWSRPh2W3gVFK+Gyl/zLimvClla7E4u550eYmAiTdmY0mlFCvwUAjgQhxKPA2UCVlHKGn/0C+AdwJtAGXC2l3BBMmwJGSyWUrIfq3ZC3QC2kVn8QMmfAhU+AKUIlQfem5BSdqmQ+DSZ1o81bBNO+AQioK4SvH1TSoYlj1LWS8iD3GJWM2lQBpWuhdp+SZ86ZBzEpQ/bxNUOMvRVKN0DZBqUQljsfkvN969Tug5KvVShNzjxIGKOUm2oLlfOSPgUmnKpyBGLSlQrUkp/B9POU1HLyOFV30ycqJC13LiTkqWvqdqYJB3LnwaXPg61JCaZ0rr9V584xrN6t1t7KnKkWJa7cocQqcuZBa6XKixkzH+ZepX5Htha1XbkD9ryv8m+ik2HMAkidGNrPqumVNpuLyF4WzYy2GGnSzoxGMyoIpDOz30/Z48D9wJM9HHMGMNH9WgD8x/03vLG1wKd/gA1PwNI7lPrY/pWe/cf+RK070Jck7aGv4MlveFaNjkyEq9+Byu3w2rWeeqkTYfzJ8PFtajT9G/fDR7+FHa976hz3EzjhFjBbAvUpNeHEjjfh9es82+nT4NsvKocF1MPcU+dDwwG1PXEpRMTB9lc9xxzzXeXclLilUNOmqnWL0qeo7dp98OT50HhQbQsBZ/0dPrjVk5ew+Edw8m88D5EazVATGee7jlZbPay8BzY+5SmbfoGSE9/3qZr5PvoqWP5Hz/6cuXDxM1C5DV66Ck65Dd66Qckwg3J0rnwT0rwWhNWEFa02PTOj0WgUfYaZCSEu6O3VWU9KeUHXY6WUK4DestjPBZ6Uiq+ARCFE1pF8kCGldq9yZACi03wdGYCvHoCqbb2fw+mA1f/yODKgbr573oOVf/OtW7MXotyyy8WfQ8VmX0cGYNU/oG7fQD+JZjjQVA4f3upbVrUDyrd6tss2ehwZUCPR3o4MwLpH1MxMJ9U7fRWcSjd4HBlQD3Zf/RumeC0G+OX9avZGowkXqrbDpqd9y7a/qmZXAKafr9qtN6XrlWP/0W9h4mmw5QWPIwPQXK5mOTVhS6vd1WvOTGykiSYtzazRjAr6MzNzTi/7JPBqL/v7Igc45LVd4i4r71pRCHEtcC1AXl7eIC4ZABxWz3uXrft+l923jj+k079kc0u1WrStW32vMrsf9R7ZoRSrNEPKkLRLlx3aG7uXe6s42Vt89/kTHpRStZP+ngNUuFmnuh6o4/tq25qwIKz6zGDiaPN1RDrp/A2YI8HuR6nM3upWj0zwVfrrxNoQUDM1ikC1y7Y+BABi3NLMUkqEXtBUoxnR9DkzI6W8ppfXdwZ5fX89jF8hASnlQ1LKeVLKeWlpaYO87CBJHq8WtQSVSBrVZUHLvEWQ0kd4gjlKJaJ2ZfIZUHCSb5kxAgzukDVLvMpdiM3wrZM1RwkHaIaUIWmXcdkw50rfMpNF5cF0kjHDd+HA9qbuKnrp06DBa+zAFKnaUieZs1TujDczLoC9H3q2s2arRGxN2BNWfWYwSZnYPb8lYYySxQfYvwomneG73xytfjPzvw/7PnHnKnohhMpP1AScQLXLNnvvOTMRJgMGIWiz97aiRJjjcsDWl1WYsUvPMmk0PTGgnBkhxFnAdOCwPJeU8o5BXL8E8FpqmVzAz3RFmBGXAZc8o+K0V9wDFzysQssqtqkwnvnXQlw/VkCfdDqcdS+sulfdXE+6VYVGpIxXK65vfFo9OB7zf/DFfTD+VKVIlTULvv0yfH63yruZdLrKZYhO6vOSmmGIyQzH3aRUmzY9o5zpU36r1PM6yZqtlJ4+uROaSiEmAy56Clb/UynkTVgK866Bba8oRzhpHJzwC8hb6Occd6gwm2O+CxNOgeZKNRsz8TQ49scqQVqjCReSx8G5/1FhuwdXqxDLxTfC5ueUUp85Eo79kepLt76ocsVOvlXlikVepXIbWypVH7rtFbUG0ym/09L4YU5fOTMA8VFm6tvsxFiCqnUUHDpc8My31OyhdMGaB+GyF8ESG2rLNJqwQ0h/0/P+KgrxIBANnAT8D7gQ+FpK6WexFJ/j8oG3e1AzOwu4AaVmtgD4p5Ryfl+2zJs3T65bt65fdgcVpw2sjeoh02FVnU58zsCT8Ftr1ai6t8SolNBarZwcc5SqY4mDiChPHUe7GoGPSlIPvJpg0O/4hKC3S+820dMNzdas2kWse8TzcBt1t5GODpVbE5nQs1PS9Ry6nYUjA4qbCZs+M5jYWpVTEpum+kqHTTn20SlqcKijA9pqlKxzRIzvsS3Vqp91WNWMpbfAgGYgDFm7nPyb93jw8rm9hpr95vWt3HfxHGbmJvRYJ2z5+n9ukaE71UxhZ97XpS+AIZCraowadKzhCGYgwxWLpZSzhBBbpJS/F0LcQx/5MkKI54ATgVQhRAnwO8AMIKV8EHgX5cgUoqSZrxn4RwghJotnBsYUoW6YR4I/qVshlLRzJ/5mesyRPa9hoxl5dG0T/rDEqVcn3m0U1E0wedzAzqHbmWY4YIkBi1cIpNkCKV7bBkPPv59Ox12Peg8LnK4OHK4OLKbeH+rjIs3UtdmHyKoA4nLAyr/Ckps94cMLr1fKkl8+AMfeGFr7NJowYyDOTGfWb5sQIhuoBXp9KpJSXtrHfgn8cAA2aDQajUajGcW02l1EmY19JvbHR5qoa/Uj0hPu7HlfhUh654IZTGoJhvd+AZOX6XWQNBovBjJX+bYQIhH4K7ABta7M80GwSaPRaDQajcYvLTYnURE9h5d1EhtporZlGM7MbHquuxAQqAWPZ1wIb/3Yv4KfRjNKGYgzc7eUskFK+QowFpgC3BUcszQajUaj0Wi609LuJCai78CS+EgzVc3DbGbG3qbWk8tb5H//lLOVQMvOt4bWLo0mjBmIM/Nl5xsppU1K2ehdptFoNBqNRhNsWmyOfs3MJEabqWxsHwKLAkjx55AywTdv0RuDEY6+Cj7+nZZr1mjc9OnMCCEyhRBzgSghxBwhxNHu14kodTONRqPRaDSaIaGpvX9hZknREVQ2DzNnZs8HkHN073Wyj1aKfNtfGxqbNJowpz8CAKcDV6PWgPm7V3kT8Osg2KTRaDQajUbjl+Z2J1G9SDJ3khQdQcVwm5nZ9wkc/4ve6wgB0y9Qa9TNvFBtazSjmD6dGSnlE8ATQohvuvNlNBqNRqPRaEJCc7uD6H7MzKTGWqhoakdK2afyWVjQcBBsLZCU33fdnLmw7hE49DXkLQi6aRpNODOQnJlVQohHhBDvAQghpgkhel0wU6PRaDQajSaQ9HdmJirCSITRQF3rMFE0K14JmbP6N9MiDDBhKax/POhmaTThzkCcmceAD4Bs9/Ye4KZAG6TRaDQajUbTE01WB5H9cGYAMhMi2V/bGmSLAkTx55Axrf/1x50Au94GxzALpdNoAsxAnJlUKeWLQAeAlNIJuIJilUaj0Wg0Go0fGtocxFr6t+Z3VkIUhVUtQbYoQOz/AjJm9r9+TCokF8C+T4Nnk0YzDBiIM9MqhEgBJIAQYiHQGBSrNBqNRqPRaPzQYLUT009nJjcpim2lTUG2KAA0HAJHGyTkDuy4MQtgx+tBMUmjGS4MxJn5KfAmUCCEWAU8CdwYFKs0Go1Go9Fo/NDY5iDG0r8ws0kZcawprg2yRQHgwCo1KzNQoYIxC2Dvh9DRERy7NJphwECcmR3Aa8BaoBJ4GJU3o9FoNBqNRjMkNFj7H2Y2Pi2WmhY7W0oagmvUYCleAelTB35cbDpEJkLZxoCbpNEMFwbizDwJTAH+CPwLmAg8FQyjNBqNRqPRaPzRaHUQE9E/Z8ZoEFyxcCyXPvQVP31hE1LKIFt3hOz/AjJmHNmx2XOg8OPA2qPRDCMG4sxMllJ+V0r5mft1LTApWIZpNBqNRqPRdKXR6iA2sn/ODMDCghT+/e25rDtQz6rCMAw5ayyF9gZIGntkx2fO0iIAmlHNQJyZje6kfwCEEAuAVYE3SaPRaDQajaY7TlcHbTZXv2dmOokwGTh+YirvbC0LkmWDYP9KyJyt1o45EjKmQ8VmcFgDa5dGM0wYSG+wALhSCHHQvZ0H7BRCbAWklHJWwK0bJhRWNfPm5jLWFNVx5swslk7LIDsxKtRmaTQjhn1VLby1pYwv99WybEYmS6dlkJsUHWqzRjUt7Q5W76vl2TUHSYuzcOn8PObkJQ6PldY1w5ZGq0r+NxgG3s6mZyfw8MqiIFg1SPZ9euQhZgDmKCXRXLIWxi0JnF0azTBhIM7MsqBZMYwpb7TyvSfXU1yjFuVaU1zHlpIG/nD+DCLNAxs50mg03alqaue6p9ez171WxJriOtbtr+ev35pF9ABHZzWB47Pd1dz4nCfp+I1NZbx83SJmjUkMnVGaEU99m52EKPMRHTsmOYryRittdmf49B1SQtFnsPSuwZ0nfZrKu9HOjGYU0u9fs5TyQDANGa7srWw57Mh08urGUq5dUsDkzPgQWaXRjBz2VjUfdmQ6eWdrOTecPJ6pWQkhsmp009zu4P7P9vqU2V0dfFVcq50ZTVCpa3UQG3lkzozJYCAnMYo9lS0cFS7ttHIbGCIgPntw50mfdsQiAGUtZbyw6wV21+/GYrIwK3UWS8cuJS8+b3A2aTRDxBEGaGo68RdRIUCHWmg0AaKn35JA/8ZChQAMfr4Xf2UaTSCpa7URP4Dk/65kJ0ZR2GVwJKTsfg9y5g7+PGlTlTyzyzGgw97f/z4XvXURZa1lHJ1xNBMSJ7C1ZivffvfbXP3+1Xxy4BOcHc7B26fRBBHtzAySSRlxTMqI9Sm7aN4YxibreH6NJhBMSI9lepbvLOcFR+cwNiUmRBZpYiPN3HjyRJ8yi8nAwoKUEFmkGS3UttqJG4Qzkx5nobg6jJyZHW+ohS8HiyUWYjOhYmu/D1lRsoI/fvVHfjrvp1w0+SLmpM9hYdZCvj3129y95G7mZszl35v/zemvnM4DGx/gQJMO0NGEJ2ESNDp8yYiP5MHL5/Lh9krW7q/jtOmZHD9R39A1moFid7kwIDAZfcdY0uMiuf/bR/PRjkrWFNVy6rQMTpiURlRE/1YA1wSHEyal8djVx/DqhhJS4yx8Y3Y2UzLjQm2WZoRT22Lv94KZ/siIj6S4trXvikNBzV5oLldqZIEgfQoc+hpyju6zalVbFbd+cSvXz76eMXFjuu03GUwszFrIwqyFHGw6yKrSVVz+7uXER8QzN2Muk5MnkxaVRpRJiR1JJBajhYzoDPLi8zAcqTKbRnMEBN2ZEUIsA/4BGIH/SSn/3GX/icAbQLG76FUp5R3BtiuQFKTFct2JsVzHeHaUNfKPT/ayvayJb80dw+nTM8lMiAy1iRpN2NLS7mRVYQ2PfFFMjMXId48v4Jj8ZCJMnpvhuNQYrl1SwLVLCkJoqcabGIuJk6akMz8/ibUH6vnjuzuJjzTz3eMLmJefhNmoH2Y0gae62XbEAgCgnJnP91QH0KJBsOEpGHcCGAI0MJM6GQ5+CQuv67Pqn7/+M8fnHM+EpAl91s2LzyMvPo+Lp1zMoeZDFNYX8nXF1zTbmrF32AEV9uvocFDdVo1Lurho8kVcM+Oaw86ORhNMgurMCCGMwAPAUqAEWCuEeFNKuaNL1ZVSyrODactQUFTdwiUPf0WTVcWXbivdTkm9lZuXTe422qzRaBSr9tXw/afXH95evqeaF65dyPxxeoZzOPDZnmpueNajavbZ7ipe/P4i5uUnh9AqzUilutnGxC6h3QMhLc5CWUMYrMdia4GNT8GyPwXunOlTYMsLfVbbXL2ZDZUbuOu4gSmoGYSBsfFjGRvf++KeZS1lvLnvTd4rfo8Hlz5ITmzOgK6j0QyUYD9hzwcKpZRFUko78DxwbpCvGTJ2VzQfdmQ6eXx1MaXh0HFqNGGI3enikZXFPmVSwofbK0NkkWYgWB0uHl7hu25Hh4Tlu8Nk5Fsz4qhusZE4iJmZhCgzrTYX7Q5XAK06AlbfD1mzIT6AD/px2eBog6beFwb954Z/cnbB2ViMlsBd24vs2Gyum30di7IXcfV7V1PVVhWU62g0nQTbmckBDnltl7jLurJICLFZCPGeEMJv8KgQ4lohxDohxLrq6vC8URr9LOJlNhr8lmtGBsOhXYYzAkFURPduSOfDDJ6haJsGINLc/buKNOuZaI1/BtsuVZhZxBFf3yAEqXERlNSHcJCxZD2s+Q/MuSKw5xUC0qeqvJke2F6znaLGIo7NOTaw1/bD0rFLWZy9mB99+iMcA1RZ02gGQrDvOP6e4mWX7Q3AWCnlbOBfwOv+TiSlfEhKOU9KOS8tLS2wVgaIqVnx5Cb5xof++JSJ5CTqmNGRynBol+GM2WTge0vG+0icW0wGTp2aETqjRghD0TYtZiPXnzjepyzSbOCESfq3oPHPYNtlbauNxOgjn5kBSI21UN4YAmdGStj6MjxzISy+EWLTA3+N1ElwaE2Pux/d9iin5J2CyTA0+k9nFpyJ2WDmwc0PDsn1NKOTYLfmEsBbJiMX8Jn/lFI2eb1/VwjxbyFEqpSyJsi2BRSHq4OEKDNPfecYNh5qoL7Vwfj0WI4ak+h3nYya5nYkkBbXszhAk9WBxWzAYtKj1JqRy/z8JJ7/3kLe315BtNnIadMzmJWbQIvVgc3pIqWX30hXWm1OjEIQ6Z7ZaXe4cLo6Di+yZ3U4abQ6SI+1YDAEbiynyeogymzEbBq5MxLNVgcRXv1RRYOVSLOR2bkJvPHDxby2sZRYi4nTpmcyMzeRNrsKuQ2bldY1wx6r3YXDKYke5MxtaqyF0qGemancDm/8EOwtcNKtkDY5ONdJ6zlvprK1ktVlq/nz8X/2uz8YGISBK6Zdwe+//D1nFpzJ+MTxfR+k0QyQYN9l1gIThRDjgFLgEuAy7wpCiEygUkophRDzUbNFtUG2K6DsKGvi0S+K2F3ZwnUnFPDetgr2VbVyxswsshOiSIz2TIlXNVpZWVjD46sPIJFcuWgsx41PJTvJsy5NeYOVt7aU8cLaQ4xPi+UHJ45nTl5SKD6aRhN0IkxGFhSksMC9Rond2cGnu6p4eGURtS12Lpyby7LpmYxN7XldmUarnU93VfPwin3EWEz89NRJSOCB5YVUNdm45th8pmbG88iqYraXNXHCpDQunJvDjJzEQdl+qK6Nl9eX8ObmMmbmJnDt8QXMyEkY1DnDjYrGdt7eUsZzXx9iXGo0PzxpPGuK6nllQwlpcRbOnJnFl/tqOH5iGltLG2izOXl3azn/WV6I0WDg+hPHc9zEVO3UaAZNVXM7yTERg16UOinaPLS5rAdWw/PfhjmXw4RTIZiyxakToXoXOKxg9o0KeWnPSyzIWkC0eWjXwUuKTOKsgrP445o/8sjpjwzptTWjg6DeXaSUTiHEDcAHKGnmR6WU24UQ17n3PwhcCPxACOEErMAlUsquoWhhS0l9G1c9+jXVLTZ+fMpEfvnyFlrtKrHwgc8KqWpq547zphNlVv/qr/fX87OXthw+/pcvb+W+i2dzntuZcXVIHlu9n4fcSbX7qltZubeG1394LJP1Gg6aUcDa4lq+/9R6nB2qG/jTe7twuDq4ocsijd4s313NT17YdHh7U0kDf/twDy73OX792jauP3E8q/fVUtdqp7imld0VTdx/2dGkxB5ZEmy7w8lfP9jNm5vVZHNxTSsr9lTzxg+PHTELenZ0SJ5ec4D7Py0EwGiAFXtrufejPQDsrWrh6+I6fnbaJH792lZ+tWwKGw818Jf3dx8+x7VPreeJ78zXoWeaQVPZZCNpkCFmACkxlqHLmWmtgRevhGNv6tf6L4PGFAlJ+VC2CcYuOlzs6HDw8p6XuWnuTcG3wQ8njTmJzw99zurS1SzOWRwSGzQjl6DHREgp35VSTpJSjpdS/sFd9qDbkUFKeb+UcrqUcraUcqGUcnWwbQokhZUtVLfYALVoVKcj08lrG0spqvIs0PXW5u4qI69tLD38vrzRyuOr9vvstzpc7K5oQqMZDWwuaTzsyHTy7JqDHKzzv9Bdu8PFo6s8imjREUZqW+2HHZlO3txcxomTPQ/UXxbVUVjVfMR2HqpXM6jeNLQ52Ft55OcMNyqa2n3U5i5fMJYXvj7oU8fZIalvcxxeF2j1vu4T66+sP9StTKMZKFXN7STFHHnyfycpsRFDNzPz6Z2Qt3hoHJlO0qao2SAvlh9aTlp0Wshkkk0GE+dNOI97N9zLMBqv1gwTRm6A9xBh8VLtMfqZ+o40G30Wj4vzIykZH+kpMxkMfpWcInTejGaU4E8JK8Zi8llE0xuDgASv35CrQxLhZ12nWIsJq9dgg9EgMBmP/HdlNhj8Xmck/VZNRkGMxfN5rA4X0X5WXzcbDbg6JEIIv+FkSdGDfwDVaCqbBrdgZicpsRbKh8KZaSyFba/CrIuDfy1v0qfC/i98ip7f9TzH5xw/tHZ04eiMo7E6rXxe8nlI7dCMPLQzM0gmZsRxTL7KZ2m0OshP8Y1F/cEJBUzyCg87Z1aWzwOQ2Si44Ojcw9uZCZH8atkUn3PkJUczPTs+GOZrNGHH0XnJJHcZfb3+xPFkxvtXBYwwGbnuhPF0KqDbnB1ERxi7KR5dMn8Mn+7yrHdw2TFjmJp55IvvjUmO5oaTfVfPnpETP6LCQdPjIvnVGVMPb//n80K+v6TAp05yTARmoyAqwki708XCccmYjZ6BHYvJwHlz9KJ5msFT0Wgd1BoznaTGRlDZZKOjI8gzBF8/DAUnQeQQ37/Tp0PpWuhQgzeHmg6xq24X8zLmDa0dXTAIA2eNO4t/b/q3np3RBBSdkdkLtS02Is1GYrxGIp2uDhraHMRFmrCYjaTGWvj7RUexq6KJhjYHp05NZ0dFMweqW5lfkHLY0enkuAkp/O+qeXy5r5YOKVk8PoVFXVY6P2d2FgVp0RyqsxIbaWJSRhxjkoc2YU+jGQytNiftDtcR5aMclZfIw1fOZfW+WmpbbBw3IY3545JpsTmoa7GTEW/BYvbtuo4Zl8yL31/Eyr01REcYWTIplaXTMlixt4a6VjsnTEojKdrMr8+cyu6KZo7OS+SY/GSiLUf+YGQ0CK5YOJapmfGsKa5lYnocCwtSyIjvv/racGDZjEzykqI4WN9GVkIkKTERPPfdBXy8q5LkGAt5yVFUNLbzj4uPot3hoiAthpeuU9+FQQiOn5jKzBEmiqAJDWUN7YxNGfy90GIyEhVhpKbVRvoA1BIHhMsJm56GU+8Izvl7IyoRolOgYgtkz+HFPS+yOHsxZuPgHcHBcnTG0by5702+Kv+KRdmL+j5Ao+kH2pnxQ3mjlVfXl/LMmgNkJ0bxs9MmMX9cCgdqW3lsVTEfbK9kzphEbjxlIjNyEmiwOnhpXQmbDjVwytR0ZuUmUtpgZcOBeiakx5KZ4BlRNhqNLJmUxpJekmEbrA5W76vjxXWHyE+J5qdLJzMuVQ5awUWjCTZOVwdfFdVxz0e7qWqyccWisZw/J5uMHmZV/OFwddBmc7HpYAMdUjI+tY0d5SYe+nwf28qaOH5iKlcuymf2mMTDx5iNBublJzMvPxkAq93JZ7ur+XB7BXZXB5EmA984KoerFucH9PMmRkdw6rQMTp02ctfFabI6WF1US3O7k13lzby7tZz0eAuXzs9jXXEdc3ITEcDv3txBrMXIT5ZO5viJqRw1RiswagJLRVM7c/ISA3Ku9Dglzxw0Z6Z4OcSkQuKYPqsGhYyZULQCW8Y0Xi98nZuPuTk0dnTBIAycnn86D215SDszmoChw8y6IKXkuTUH+euHuylrbGfdgXqueORrdlU0ccurW3nqq4NUNdv4YEclVz36NTvLGrnykTV8uKOSqmYbz319iFfWl2A0Gnhs9X7+s3wfbTZnv6/vcHXw8Ioi/vHJXsob2/myqI7LH1nDrvKRk1SsGblsK23kykfXsPFgA6UNVv783i5eWV/a94FebC1t5KrHvuaTXVV8truauKgIbnh2A5/urqaq2cYrG0q57Y1tVPay6N3XxXX88NkNrN1fz+ZDjdz78V7e2jQwOzRudcVV+3llQwk2h4v/fVFMWWM7mw41cutr28hPi+XyR9dwqN7Kwbo2dpQ3870n17HxYH2oTdeMQCoa27uFoB4pqXFBVjTb8hKMPS545++LzJlQ9Ckf7P+AMXFjyIgJnwGXBVkL2N+0n+0120NtimaEoJ0ZoK7VRn2rHVAJho+v3u+z39khKa2zsqa4zqe8ttXOnsoW6tscPuXrDtQzNUvFzb+ztZzi2u4qTPWtdupabd3KK5vaebaLWpDN2cGeQaguaTTBpq7FRkObnS2ljXQNQ39s1X7KG61UNbVjd7r8n8CLLYcaiLGYuHnZJP5w3gzszg5qWuw+dTaXNLKvpvvvqrbFRmObnU2HGugakv3CuhIO1bUN+LONZioarTz55X5OmpzOW1vKffY5OyRWh/o+61rVoqGdLN9dPaR2akY+HR2S6mZb4JyZmAgOBqs/cDlgz3swNoQSxJmzkCVreW7bY5w05qTQ2eEHk8HEqXmn8r+t/wu1KZoRwqgOM2tos/P+tgru/6wQo0Fw06kTWViQQkK0maZ239kUi9mAySC6Sca6/CSxmY3i8ANdjMVXzazZ6uCjnZXc9/FeOqTkR6dM5PTpGSRERbiPNRAXaaau1ffhzftBQaMJF+pb7byztZz/LN9HpNnI1YvHdquTFGPmlfUlPPJFMadMSef7J4xnYkbPSfJ5yZHcce4M/vv5Pupa7dx29rRudYwGcXgleoDaVhtvby7nv5/vIyXWzLlH5XY7JjHa7FcpTdMzESYDCVFmmtudJEababT6DtyYDaqvs5gNODs6DpenxGr1Mk1gqW21Exlh8PndD4a0uEj2+xkQCQj7v4C4bIgJ4dpKllissRnk15Uya/6s0NnRA8fnHs8tK2/hYNNB8uLzQm2OZpgzqu/sXxTW8KtXt1JSb+VAbRs/eWEzO8qa+PWZU33qjUmKIj8lmssW+P7gFhYkExdp6pbkf/ExeXy4vQKAH508kUleD25fFdfx0xc3c7CujZJ6K798eYvPugwZ8ZHc2uX6E9NjmabVzDRhyPI9Vfzm9W2UNljZV91CRZONLK8EeCHgonljuP+zQurbHLy8oZSfvbSJ+jZ7j+cUwshPX9zEropmqpptHKht5bgJqT51rlw0lmleqmEf76jkd29up6yxna2lzWQmRJLmJT4gBPzwpPGkBSs+foSSFhfJb86ayofbK7j0GN/+LycxinZHB+lxFgTgcKkRnIQoM0sm6gUyNYGlvNHq85seLBnxFvb7iZoICLvegdzQKocBrDdJLiQOgwi/R70oUxQn5J7Ao9seDbUpmhHAqJ2Z6eiQPLvmIJMyYrlqUT4SeHhlEW9sKuWvF87m7RsX09jmwmSEzDgLdW0OkqLN3HXeDMob20mPs7C7oomtpY1MyYjjmmPH4XJ1EB9lJtpi5PRpGUSZDaTFWSiqbiEvKZomm5PS+jamZMYyKzcJg0CFvUjJobq2w4plZ8zMJDsxko0HG8hMiGTOmESMBkGLzUHsINSXNJpAYne6eOqrAz5lD68o4u4LZ9Jmd1Hf5mB6djx/encX8/OTKUiLZWtpI+sP1NPQ0k5pvZU4i5GxqUoeubq5HaMQ7KlqZlxKNHeeN4MIo4E3N5VwzqxMzp+TzYHaNiZnxnFUbiIYoLCqmTiLiWfWHCQj3sKpUzOwOTv407s7+ftFs2lud+DskKTGRTA7t3tCusPVQU2LjTiLidhI/7+thjY7dmcHaXGWES/C4XB2UNNqIy7SRKzFjM3hZHpWPI9ePY/mdhcvXLsAh0sSZRYYjQYiDAbOnJmBQDAzJx67SzI5I46JGXHUNNsQgiNStNNoulJabyU1gG0pKyGK/TVBCDOTEna/CyfeEvhzD4CixiJWG5zcVLOfLVKqEZ0w45S8U/jNqt9ww5wbSI1K7fsAjaYHRq0zYzAIvjU3l/LGdv756V6MQvCd48aRHmdhT2UzL68v5fVNZWTEWfjukgKeWl3Mxcfk8dW+GjYcbCAvOYr/O76ARquDo/OS+NenheyuaOakKWnMz0/mng93s3RaJqdMS+ep1QdYNiOTh1cW02pzcun8PBqtdgrSYslMiOS2N3ZgMRu4/sTxnD49k5RYC4vGp7JofCr7qlr49/J9vL+tgslZcdxyxlTmjtUqQZrQYzQYyE6IYgMNh8uOm5ACCJ788gAtNienT8/k12dN4YHP9vHy+hKOyU/m5esWcv/yIj7aUcnYlGh+dcYUdpU38+DnRVjMBm44aQK3nDmV297YTl2rnQvn5jIuNZZ7P97NgVors3ITSI+L5L5PdvP+tioK0mL40ckT+Hp/Pa9tKMViNnDlonxa7E7u+WgPda12rl6cT0FqnI/MenF1Cw+uKOLdLeVMyojjV2dO4Ri3GhqAzeHi8z3V/Pn9XTS0Objm2HwumptLRkL/ldmGE0XVLfzHq6+5+fTJvLy+hDNnZvHB9kqOHpvIysImXt9YSnqchUvnj+Hz3VUcPymdL/ZWc9asbBxOJyX1JtYU1/GvT/diECp894wZmcRH6dAzzZFT2mANaPhiSmwEzTYHze0O4noYyDgiqnaA7IDE7iG3Q4VE8uLul8gfuwS2f0R09R7a0ieHzJ6eiLfEszBrIU9sf4KfzftZqM3RDGPCb+5xCGlzuLj7g91UNtkoa2znrnd2YjEZeHHdIZ748gCNVgd7qlr41StbuGJRPs+vO8TbWysoa2znq+J6fv7SFsamxPCj5zay/kA9LTYnb20u5+X1JSwan8pL60t4bX0p5x6VzW/f2M7BujZqW+3c/1khcZFmBHDfx3upbrFRUm/l169t46sij8hAS7uD297cxkvrS2i2OVm3v54rH1nDvuqW0P3TNBo3RoPgmmPzsZg83cgFc3P5iTtErKTeyiNfFPPR9krKGqy02JwsKkjm38uLeGVDKU3tTopr2viqqI4739l5+Hfwq1e3UljVQlFNK/VtDh5eWcw728o5UGulrLGd97dXctub25iUkUCzzUlRdSsbDzbw0Iqiw+f403u72F/Tyr5qdY57P97LqxtKDtvZandy5zs7eGHtIZptTtYfrOeKR9awt9IjtLHpUAPXPrWeoupW6lrt3PPhHl7fVDak/+OhoqXdwW/f8PQ1Lpfkf18UExtp5K0t5Rysa2VLSSNPrN5Po9XB3qoW7npnJwsKUvnDuztZUJDCL17eQnJsJFtKG/nN69uobLJR3tjOza9s5cuiur6N0Gh64WBdGykxgZuZMQhBblI0e6sCfD/d/R7kHhPSmZANVRupa69jVtpsmrNmkbL3k5DZ0hen55/OK3tfoaG9IdSmaIYxo9aZcTo7eGtz9weTiqZ2Xt/oW94h1dov28uafMobrQ4O1LR2EwvYXNLIxAwVOrOltIHdld2VyD7cUcmh+u5T3J/v8axQXtpgZVVhrc/+VruLIu3MaMKEo/OSePkHi7nrvBnc862ZHKhp7aYi9t62Ck5wr6s0JSuOz3Z72vi8sUl8vqe78tXO8mbGei0U+97WCo73WptpZ3kzqe5R2vkFySz3c47dFS2MSfbMojz11QFqW5SCYFmDlU93+R7T7uig0Ou3tf5Ad3nhp7460E2cYyTQta9ZPCGVj3ZUcvKUDN7cVMa5R+Xwehdp6w6p+iOBSs6OMhtZf6CeNruDrry+UctiawbHgdo20uICG7I4Jikq8Mse7HpbOTMhotXZxtM7nubUsadgEAaaco8mpfBThKv/S0QMJSlRKcxNn8uTO54MtSmaYcyodWZMJgOZflbqjjAaSPXTYUaZjZgN3f9d3mErnVhMBpzuZFijEH5HkzLiLZj8nM979fBIs9Gvipm/a2o0oUAIwcycBC5fOJZvzs0jLqp7uEZqrOWwAyAlxEV62m99m91vHHxSTITPIEFanIUGL9EAs1FgNKqRz/pWRw/nUCpcnWQmRGJxq5lFmozE+vkdxXmV+QtpyYyPHJGKaF37muZ2B0nREVjtLlJjI2iwOvwmX0e4lRujzEYcrg5SYiw4/Mhv5yUPftV2zejmYF2bz/0xEOQlx7C5pCFwJ2yuhNpCyJgRuHMOAInksW2PMj5xPHlxSrDDHpuOPSaNxP2rQmJTfzhj3Bm8sPsFPTujOWJG3l15AFw0b4zPDTw+0sT49Fh+fMpEnxnicakx1Lc5uqmZnTw5jbS4iMOjzp1cvnAs729Tamb/d3wBESaDz4OA2Sg4ZUoGc/ISfUJ0kmN8z5WXHM3Ny3zjXE+anMbkXmRtNZpQMjMnwWc2xCDgmmPz+XSXmo3574oibjp10uH9m0saWTotw+d3kBRtJjcp6rADZDQIrlg0ls+8ZlL+77hxvOUO+dpwsJ5lMzK7/ZayEyJpcK8BZTQIfrZ08mEBjTHJ0dxy5hQf24+bkMqUTI9q4DH5yWQneh6eTAbBT5dOIjpi5A0mdO1r3t5SzvdPKODP7+3ipqWTeOCzvfzwpAk+/WJ+SjTNNie5SVG4OiQpsRHMHpNAXnIs0RGefjXOYuKc2dlD+XE0I4yODklZg5X0AM/MTEiP9TsDe8Tsfhdy5oIxNEI9bxS+SUVLBSfmnuhT3jB2IZmbXqTbtHmYkBadxtyMuTy09aFQm6IZpggZpo27N+bNmyfXrVsXkHN9XVzH9rJGDEIwIyeBuWOTaGyzs/5APXuqWkiMMpOXHM22kkby02LokJLimlay4iOZlBlLc7uL6AgDuytbqGqyMSE9lo4OSXFtGxPSY0iINNHc7iIuykRJvRWbs4NxqdFUN9kwGyEuysLuimbMRnX9OXkqud/udFHVbMMooLimjcLqFjLjI5mVm0DmCE1ADlP6HfgcyHY5nNl0sJ4d5U202JxMyohjbFIUtW12HC5JhFGQGG1ib1UbxTVtJMdEMC0zFoPRwLbSRiKMBmbkJNBic7C9rJlW9zlykyLZWtpERWM7ecnRTMmMY39tG4VVLaTFWTgqN552p1TnMBuYlZOIySDYXNJAi83JtOx4ZuYoVcBOWm1OtpY2sLeyhfQ4C7PGJJIRF0lFUzsmgyA9PpLimha2ljTSanMxLTueGTkJPucIIQMyoj9ts6XdyZbSBva5/6cFKTEcrLci6UAgaLU5ibGYKKppJT7KTFKUmYY2B0kxEVQ125iUEUtti5UpmYnYnB1sLfX0q5Mz9QDMKCHg7RKgpL6Ncx9Yxf2XHn3EhvnD2dHBdU+tZ8UvTwqM6t4T50LeAsg/fvDnGgASyVv73mZFyQounXIJMeaYLhU6GPf5Pexf8hOaxoReMtof9e313P7l7bx0zkvkxOYE4xJh0XFrgsOod2YGwu6KJv7y3i52VzRz1/kz+OenhWw+1MBReYncfPoUFhSkHK5rc7j4dHcVd761g5oWO5fMH8P3ji84LL/cG/trWnngs0Je21hKTlIUv//GdI6bkIrJOKon0kKFdmYGQLPVwQc7Krj3wz002ZxcNn8Mx05I4+73d7GjvIn545L5xWmTmeulGhYuVDZZeWbNIR5eUUR0hJGbl03hzJlZxEaG5UxMUB4aAfZVt/D3D3fz/vZKxqVGc8c3ZrCwIIXSBisPrdjHqZPTeX9nJW9vKScuwsSPT53IyVPTSIvTgyya4LTLz/dUc8+Hu7nljKl91h0o//hkD988OpdvzRszuBO11cF9M+HCx8A8dL+FdpeNJ3c8SXFjERdM+CZxEbF+68WVbSG56HO2feshMITnItxvFL5Bm7ONv5/492CcXjszIxj9dNxP6lvt3PTCZj7dXc1PTpvEza9sZePBBjokbDjQwI+f30RhlSeRcFtpIz94egNlje3YXR08+eUBnvxyP66O3p1Hm9PFfR/v4aX1JTg7JAdq2/jO42vZWd7U63EaTTiw9oBS+SttbKe53cm07ARueG4D28qa6JDwVVEdv3h5C4dqg7C+wyB5d2sF//xkL1aHi9pWO798ZQvrDowuFa5Wu5M7397BO1srcHVICqtaueqxr9ld2czjq4upa2lneWENz319iOZ2J2VN7dz86lY2HmwMtemaEczeymayE4PjICwYl8ILaw8N/kTbX1MhZkPoyOxt2Mttq2+jxd7CZZMv69GRAWjOmonLHEXWxueGzL6BsmzcMjZVbeKr8q9CbYpmmKGdmX5SWm897FB0dEiqmm0++yua2in2WoBrV0V3hZQX1h2iurm91+tUNtl4c3N3NbXCQMtHajRBYGcXxb82m5Mmq6+KTlFNK8XBWnn7CGm1OXj+6+4PNCv31oTAmtBR0dDO8t2+Km8Ol2RPRTMvri3h/KPzeHtLebfjdpTpwRZN8NhR1kROkJyZeflJlDZYWe6lsnhEbHgKCk4MiE19YXVaeXLHk/xr4/0cm7WYM8edgbmvPB0hqJh1IRlbXyWudOOQ2DlQLEYLl065lNtX306bI/wGvDThi3Zm+km0xXg4wTgqwthNQl4ISIjyhKMkxXTvWHISo4mK6H16NzrCSHpcd8WWeD8qURpNuJEU46sAFuUnWd5sFD6KZuGA2WhgXGpMt/IxSaMrdCoqwkhidPe+JiHaTHZiJHVtNrITuvdPyTF6QUxN8NhW1kh+SvffZyAwGQx897hx3PTCJv75yV4+3F5BTYut7wO9qdgKTaWQHdicHn9sqt7Er7+4lfr2er4z4xomJ/d/MUxnVCLlcy5j/Id3El21O4hWHjlHpR9Ffnw+d6+9O9SmaIYR2pnpJ2NTYg6r/azYXcPlC32Vza5enO+jhDQzN5FpWZ5to0Fw65lTSOhjFezUWAt3nDvdx1k6Jj+J6dkJAfgUGk1wOWpMAuPTPA8d20obOH+ObzLnD04Yz7QwSwiPMBm5dkmBj+xyVkIkx01MDaFVQ092YhS3nzPdp+ykyWnMyE7gN2dP4w9v7+T6k8ZjNno6qHGpMczK1f2TJji02Z0crGsLqrz3tOwEfrVsCrsqmnhoRREn/W05z6450P8TrL4fJi0Lai5Ks72Z/2x+kKd2PM2y/GWcnn86kcaBS1W3pU6gctY3mfTOLWE7Q3PplEtZVbqKd4reCbUpmmGCFgAYAC02J9vLGjlY20ZBagzVLWqF6+yEKGaNSSCri8pYaX0b28uaaLY5mZQey7Ts/ikh2Z0d7ChvpNCtpjY9p/u5NUOGFgAYILvKG9lW2kSbw8XE9FiyE6LYXt5EZVM7Y5KimZ2bQFqA14sIFLsqmthV3kyE0cD07HjG+pmtCROCJgDQ7nCxvayR4ppWkmMszMiOJz0+EleHZHtZI/VtNgwI9tW0EW02MiUrjlm5iUfyGTQjj4C3yy/21vCHd3dw29nTe60XSCoa2/njezu567wZnD49s/fKdUXw0Elw3oNg6Tln5UiRSNZWrOOZnU8zJWkKx+Ueh9kw+EiN6JpCsjY8S9m8K6macS7dwk1CTElzCfesv4f7TryPeZkBUWALrw+oCShBd2aEEMuAfwBG4H9Syj932S/c+88E2oCrpZQbejunfmjUDCHamdGEI0FzZjSaQRDwdnnn2ztobLPzzbmDVBsbIIVVzfz9oz289+MlZPoJrQTUui3PfAvis2HmtwJuQ5W1iqd3PENFawWn558WcMlic2sNOeufoi1lPPtP+AkuS3jNmG+v3c7/tv6Pe064hwVZCwZ7Ou3MjGCCGmYmhDACDwBnANOAS4UQ07pUOwOY6H5dC/wnmDZpNBqNRqMJf5yuDt7aXMYx41L6rhxgJqTHsXRaBj9+fmPPKqRr/gv1xTDtvIBeu9HeyLO7nuP3X95BcmQSV02/MihrrzhiUjlw7A0gJTNe+C6JxV+E1cKa01Om8/1Z3+fnn/+cx7Y9hqvDFWqTNGFKsHNm5gOFUsoiKaUdeB44t0udc4EnpeIrIFEIkRVkuzQajUaj0YQxL647RFqcJaj5Mr1x7uwc2uwufvfGNjq8HZoOF6z6J6z8Gyy5GfpSEusHjg4nW2u28d8t/+WWlb+mvr2ea6ZfzcKshRhF8HJxpNFM1YxzqZj9LcZ8+V+mvPET4g+tBdkRtGsOhCnJU7hl/i28X/w+F751Ie8Xv4/dZQ+1WZowI9iSQjmAt95pCdB1rtBfnRzAR/9TCHEtauaGvDzf5HuNJlTodqkJV3Tb1IQj/W2XT67ez21vbufmZZOpaw3dw+sVC8fytw9380VhDVdMNbKw+QOmFz+h8mOW/EI5Mq29S7i3Otooby3HKV04OhzYnO20uaw0tjdQ015DWUs5NdYa4s1xjE8cz5X5Z6nkfmsT7dahkT1vj4im/qiLSSnfwriP/kCEvYXazBk0pY7HGpeBPTIepzmSlsQ87NFJQ2JTJyaDie/M/A6bqzbz9/V/5xcrfsHkpMlMS5lGXnweqVGpxJnjmJMxh+TI8FuQWRN8gpozI4T4FnC6lPK77u0rgPlSyhu96rwD/ElK+YV7+xPgl1LK9b2ctxroS2okFRgNi0SMls8JofmsNVLKZf2p2M92GQiGy3c+XOyE4WNrp539bpcwpG2zJ4bD/1fbOHgipZQz+lu5t3aZc90jM0wJGRZXa4MLYQhp7JMwGDBExh4e/C22XEattcPZ2zGddEiEIdIoZIToPRJGul9hQloPMzMfR1jkjfEpIY33MsYYTcKPmFLtR7Xl5c+Ul3UpPqI+UzO8CPbMTAngnbWXC3RtaP2p44OUMq2vCwsh1kkpAyKBEc6Mls8J4f9Z+9MuA0G4/x86GS52wvCx9UjtHKq22RPD4f+rbRw8QogBqUwM33t5I/0VbQ9P+/tPV/tPBXaG0J5euQp42rdouP//Nf0j2Dkza4GJQohxQogI4BLgzS513gSuFIqFQKOUsvsS0xqNRqPRaDQajUbjRVBnZqSUTiHEDcAHKGnmR6WU24UQ17n3Pwi8i5JlLkRJM18TTJs0Go1Go9FoNBrNyCDYYWZIKd9FOSzeZQ96vZfAD4Nw6YeCcM5wZLR8Thhdn7U3hsv/YbjYCcPH1uFiZ1eGg93axsETDPvC/TP3hbY/tAx3+zX9IOiLZmo0Go1Go9FoNBpNMAh2zoxGo9FoNBqNRqPRBAXtzGg0Go1Go9FoNJphyYh1ZoQQRiHERiHE26G2JVgIIRKFEC8LIXYJIXYKIRaF2qZgIIT4iRBiuxBimxDiOSFEZKhtGmqEEGOEEJ+5v+ftQogfh9qmnhBCRAohvhZCbHbb+vtQ29Qbw6WvEELsF0JsFUJsGqgEbqgYLu023NvAcOjrg9FPCyGWCSF2CyEKhRC/CoSdQ4UQ4lEhRJUQYluobTkShstvtyeG231IMzhGrDMD/JgwlkMPEP8A3pdSTgFmMwI/rxAiB/gRMM+9GJsRJfE92nACP5NSTgUWAj8UQkwLsU09YQNOllLOBo4Clrll18OV4dRXnCSlPGoYrZswXNptuLeBsO7rg9FPCyGMwAPAGcA04NIwbTs98TgwnBdpHC6/3Z4YbvchzSAYkc6MECIXOAv4X6htCRZCiHhgCfAIgJTSLqVsCKlRwcMERAkhTEA0fSyqOhKRUpZLKTe43zejHmZyQmuVf6Sixb1pdr/CUmlkNPQVoWQ4tNtwbwPDqK8PdD89HyiUUhZJKe3A88C5gzznkCGlXAHUhdqOI2U4/HZ7YzjdhzSDZ0Q6M8B9wC+BjhDbEUwKgGrgMXd4xP+EEDGhNirQSClLgb8BB4Fy1KKqH4bWqtAihMgH5gBrQmxKj7jDdjYBVcBHUspwtfU+hk9fIYEPhRDrhRDXhtqYgRLG7fY+wrsNhH1fH6R+Ogc45LVdwjB6mB5JhPFvt1eG0X1IM0hGnDMjhDgbqJJSrg+1LUHGBBwN/EdKOQdoBYZVTHF/EEIkoUbjxgHZQIwQ4vLQWhU6hBCxwCvATVLKplDb0xNSSpeU8iggF5gvhJgRYpO6MQz7imOllEejwm5+KIRYEmqD+ku4ttth0gbCvq8PUj8t/JTpkfUhJlx/u/1hONyHNIFhxDkzwLHAN4QQ+1HT0icLIZ4OrUlBoQQo8RppeBl1wxtpnAoUSymrpZQO4FVgcYhtCglCCDPqpvKMlPLVUNvTH9zhMMsJz9jxYdVXSCnL3H+rgNdQYThhT5i32+HQBoZDXx+MfroEGOO1ncsoDDEOJWH+2+03YX4f0gSAEefMSClvkVLmSinzUQmIn0opR9xIvpSyAjgkhJjsLjoF2BFCk4LFQWChECJaCCFQnzOskl+HAvdnfwTYKaX8e6jt6Q0hRJoQItH9Pgr1oLMrpEb5YTj1FUKIGCFEXOd74DQg7FWSwr3dDoc2MEz6+mD002uBiUKIcUKICNT38+Ygz6npJ+H+2+2L4XIf0gQGU6gN0AyKG4Fn3B19EXBNiO0JOFLKNUKIl4ENKHWVjcBDobUqJBwLXAFsdccAA/xaSvlu6EzqkSzgCbcakQF4UUoZlpK3w4gM4DX1fIEJeFZK+X5oTeoXw6ndhjNh3dcHo5+WUjqFEDcAH6DU0R6VUm4ftLFDhBDiOeBEIFUIUQL8Tkr5SGitGhDD/ber70OjCCGlDkHVaDQajUaj0Wg0w48RF2am0Wg0Go1Go9FoRgfamdFoNBqNRqPRaDTDEu3MaDQajUaj0Wg0mmGJdmY0Go1Go9FoNBrNsEQ7MxqNRqPRaDQajWZYop0ZjUaj0Wg0Go1GMyzRzkyYI4Q4UQjRoza6EOJqIcT9Qbju1UKIbK/t/UKI1EBfRzP86auN9uP4eUKIf/awb78QIlUIkSiEuD5Q19QMP7r2Sb3Ue1wIcWEv+5cLIeYF2DbdPkc5gWqf/Tj+DiHEqX7KD7c59/vFgbqmRhPuaGdG0xNXA312zBrNYJFSrpNS/qiPaonA9X3U0YxsriZ8+6REdPsc7VzNELRPKeVtUsqP+6h2IrC4jzoazYhBOzMBQAgRI4R4RwixWQixTQhxsRBirhDicyHEeiHEB0KILHfd5UKI+4QQq91157vL57vLNrr/Tj4CO9KEEK8IIda6X8e6y28XQjzqvnaREOJHXsf8VgixSwjxkRDiOSHEz90jOPNQK05vEkJEuavfKITYIITYKoSY0osdsUKIx9z1tgghvukubxFC/MX9P/nY/Zk7bfrGQD+vpv+Eso2620GiUNQKIa50lz8lhDi1y4hiihDiQ/c1/gsI92n+DIx3t8e/ustihRAvu9vvM0II0f3qh204xm3zZiHE10KIOPdI6utCiLeEEMVCiBuEED91X/srIUTykf23Nf1BCJHv/u6ecPcTLwshov21S399khDiNnc/t00I8VBv338vNpwmhPjS3a+9JISIdZfvF0L8vmt/5+5jP3KX/1cIcUCoGWvdPkcYoWif7j72Vff7c4UQViFEhBAiUghR5C4/PMsihFjmtvEL4IJOu4HrgJ+4bTneffol7jZWJPqYpRFC/NLd7jcLIf7sLlsuhLhXCLFCCLHT3WZfFULsFULcdUT/ZI0mUEgp9WuQL+CbwMNe2wnAaiDNvX0x8Kj7/fLOusASYJv7fTxgcr8/FXjF/f5E4O1ern01cL/7/bPAce73ecBO9/vb3fZYgFSgFjCjOt9NQBQQB+wFfu5l5zyv6+wHbnS/vx74Xy82/QW4z2s7yf1XAme4378GfOi2YzawKdTf40h+hbiNPgicBcwA1nqdey8Q63088E/gNvf7s9xtJhXI77TD65qNQC5qUObLzrbv5/oRQBFwjPfncP92Ct1tP819vuvcde4Fbgr19zaSX+7vVALHurcfBX7RR7v07pOSvd4/BZzjfv84cGEv112O6vtSgRVAjLv8Zq+2tx8//R1wP3CL+/0y3T5H7isU7dP9vRe73/8N1V8eC5wAPOd9PBAJHAImogZ9XsTTj96O+17udcxL7rY4DSjs5XOf4f6M0d6fw/35/uJ+/2OgDMhCPVeUACmh/s70a/S+TGgCwVbgb0KIvwBvA/WoB7eP3IMxRqDcq/5zAFLKFUKIeCFEIuqG9YQQYiKqAzUfgR2nAtO8BoDihRBx7vfvSCltgE0IUQVkAMcBb0gprQBCiLf6OP+r7r/rcY8C9WLHJZ0bUsp691s78L77/VbAJqV0CCG2om4cmuARyja6EuUUHQD+A1wrhMgB6qSULV0GLJfgbltSyneEEPVdT+bF11LKEgAhxCZUG/rCT73JQLmUcq37vE3uYwA+k1I2A81CiEag8zewFZjVz8+nOXIOSSlXud8/Dfya3tulNycJIX4JRAPJwHY8319/WIh6sFvlvlYEyunoxF9/dxxwPoCU8n3dPkc8Q9o+pZROIUShEGIqMB/4O6pPNKL6UW+moByfvQBCiKeBa3s5/etSyg5ghxAio5d6pwKPSSnb3DbVee170/13K7BdSlnuvnYRMAY1UKrRDDnamQkAUso9Qoi5wJnAn4CPUD/0RT0d4mf7TtSN63z3NPHyIzDFACzqdE46cXe6Nq8iF+q7H2hYRuc5Oo/vCUH3zwjgkFJ2lnd0nk9K2SGE0G0xiIS4ja4AfoiaLbwV9TB4Id1vzj1duyf8tWl/9NQeu56jw2u7o5fzaQJH1++lmd7bJQBCiEjg36iR8ENCiNtRI9UDQQAfSSkv7WG/v/5uIH2mbp/Dn1C0z5Wo2REH8DFqVsUI/Lwf9vWGd1vqrR33pz16t8XObd0eNSFD58wEAKEUTNqklE+jpoYXAGlCiEXu/WYhxHSvQy52lx8HNEopG1FhP6Xu/VcfoSkfAjd42XVUH/W/AM5xx+PGosJ6OmlGjcQHwo6kIzyPJkCEso1KKQ+hQnEmSimLUO3u5/h3ZlYA33Zf+wygs+0Mpj3uArKFEMe4zxunneewIa+zDQKXAl/Rc7v0bgOdD4Y17r7rSJSavgKOFUJMcF8rWggxqY9jvgAuctc/Dd0+RzqhaJ8rgJuAL6WU1UAKahZme5d6u4BxQojxXvZ1Mtj793eEENEAQudmaYYB2pkJDDOBr92hBLcCt6E6r78IITaj8lK8lUXqhRCrUbkE/+cuuxv4kxBiFWoU5kj4ETBPqGTFHagkwB5xhzW8CWxGhVSsQ8VlgxoNelD4CgD0l7uAJKESHzcDJw3weE3gCXUbXQPscb9fCeTgP+Tm96hE1Q3AacBBACllLSocaJvwJFj3CymlHeWc/cv9WT9i4KP4muCwE7hKCLEFFYrzL3pul4/j7pNQo8IPo8JdXkflFgwI94Pi1cBz7ut/hXpo7I3fA6e52+cZqBCjZt0+RyyhaJ9rUGHgK9zbW4AtXlENAEgp21FhZe8IJQBwwGv3W8D5wlcAoF9IKd9HPResc38WfzNCGk1YIbr8PjRBRgixHJWYty7UtoBSHnPnLUSjOs9rpZQbQm2XJnSEWxvVjEzcoYpvSylnhNqW/iKEsAAud27DIuA/UsqjQmyWJggMx/ap0YxW9FS25iEhxDTUSOAT2pHRaDSaHskDXhRCGFCCJt8LsT0ajUYz6tEzM8MEIcQ1KDlEb1ZJKX8YCnsgPG3ShI5waA9CiNeAcV2Kb5ZSfjBUNmjCg3BsC+FokyY0hLotCCFmoiSjvbFJKRcMxfU1mkCinRmNRqPRaDQajUYzLNECABqNRqPRaDQajWZYop0ZjUaj0Wg0Go1GMyzRzoxGo9FoNBqNRqMZlmhnRqPRaDQajUaj0QxL/h+Dli0V8eK/ZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 823.25x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris_data_clean, hue='class')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "o2tUj2HYr22v"
   },
   "source": [
    "There's a strange distribution of the petal measurements because of the different species. This is actually great news for our classification task since it means that the petal measurements will make it easy to distinguish between `Iris-setosa` and the other `Iris` types. Distinguishing `Iris-versicolor` and `Iris-virginica` will prove more difficult given how much their measurements overlap."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4a7j9plHsNzi"
   },
   "source": [
    "There are also correlations between petal length and petal width, as well as sepal length and sepal width. The field biologists assure us that this is to be expected: Longer flower petals also tend to be wider, and the same applies for sepals.\n",
    "\n",
    "We can also make violin plots of the data to compare the measurement distributions of the classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 606
    },
    "id": "fZCMEQMMr2rB",
    "outputId": "8ddb3160-c6b2-4fcf-9bd0-0a23c2be953e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 10))\n",
    "\n",
    "for column_index, column in enumerate(iris_data_clean.columns):\n",
    "    if column == 'class':\n",
    "        continue\n",
    "    plt.subplot(2, 2, column_index + 1)\n",
    "    sns.violinplot(x='class', y=column, data=iris_data_clean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "r0IrLmWUsav_"
   },
   "source": [
    "### Step 4: Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wMgebXMqslOQ"
   },
   "source": [
    "As tiresome as it can be, tidying and exploring our data is a vital component to any data analysis. If we had jumped straight to the modeling step, we would have created a faulty classification model. Remember, your model is as good as the data you feed it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_qlLYzMGszj6"
   },
   "source": [
    "As the first step, let's split the data into a training set and testing set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "id": "_Klvbr46sgd4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2],\n",
       "       [4.9, 3. , 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.3, 0.2],\n",
       "       [4.6, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.6, 1.4, 0.2]])"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We're using all four measurements as inputs\n",
    "# Note that scikit-learn expects each entry to be a list of values, e.g.,\n",
    "# [ [val1, val2, val3],\n",
    "#   [val1, val2, val3],\n",
    "#   ... ]\n",
    "# such that our input data set is represented as a list of lists\n",
    "\n",
    "# We can extract the data in this format from pandas like this:\n",
    "all_inputs = iris_data_clean[['sepal_length_cm', 'sepal_width_cm',\n",
    "                             'petal_length_cm', 'petal_width_cm']].values\n",
    "\n",
    "# Similarly, we can extract the class labels\n",
    "all_labels = iris_data_clean['class'].values\n",
    "\n",
    "# Make sure that you don't mix up the order of the entries\n",
    "# all_inputs[5] inputs should correspond to the class in all_labels[5]\n",
    "\n",
    "# Here's what a subset of our inputs looks like:\n",
    "all_inputs[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "id": "Iph5pMDhs624"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "(training_inputs,\n",
    " testing_inputs,\n",
    " training_classes,\n",
    " testing_classes) = train_test_split(all_inputs, all_labels, test_size=0.27, random_state = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tsPjLoyis_m6"
   },
   "source": [
    "With our data split, we can start fitting models to our data. Here's where you come in. Our company's Head of Data is all about eco-friendly and putting a stop to pollution. As a result, he loves tree-based classifiers. You have to build a tree-based classifier and train it on the training set. A template for the same has been provided below.\n",
    "\n",
    "Tweak various parameters until you achieve a good enough score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {
    "id": "anUfxwDst-Yf"
   },
   "outputs": [],
   "source": [
    "from sklearn import tree\n",
    "# Create the classifier\n",
    "classifier = tree.DecisionTreeClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {
    "id": "vl8c8gits9qA"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9743589743589743"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the classifier on the training set\n",
    "classifier.fit(training_inputs, training_classes)\n",
    "\n",
    "# Validate the classifier on the testing set using classification accuracy\n",
    "classifier.score(testing_inputs, testing_classes)"
   ]
  }
 ],
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