KasturiRanganR4/ML0101EN-Clus-Hierarchical-Cars-py-v1.ipynb

## ML0101EN-Clus-Hierarchical-Cars-py-v1.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://www.bigdatauniversity.com\"><img src = \"https://ibm.box.com/shared/static/cw2c7r3o20w9zn8gkecaeyjhgw3xdgbj.png\" width = 400, align = \"center\"></a>\n",
    "\n",
    "# <center>Hierarchical Clustering</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Welcome to Lab of Hierarchical Clustering with Python using Scipy and Scikit-learn package."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Hierarchical Clustering - Agglomerative\n",
    "\n",
    "We will be looking at a clustering technique, which is <b>Agglomerative Hierarchical Clustering</b>. Remember that agglomerative is the bottom up approach. <br> <br>\n",
    "In this lab, we will be looking at Agglomerative clustering, which is more popular than Divisive clustering. <br> <br>\n",
    "We will also be using Complete Linkage as the Linkage Criteria. <br>\n",
    "<b> <i> NOTE: You can also try using Average Linkage wherever Complete Linkage would be used to see the difference! </i> </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd\n",
    "from scipy import ndimage \n",
    "from scipy.cluster import hierarchy \n",
    "from scipy.spatial import distance_matrix \n",
    "from matplotlib import pyplot as plt \n",
    "from sklearn import manifold, datasets \n",
    "from sklearn.cluster import AgglomerativeClustering \n",
    "from sklearn.datasets.samples_generator import make_blobs \n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### Generating Random Data\n",
    "We will be generating a set of data using the <b>make_blobs</b> class. <br> <br>\n",
    "Input these parameters into make_blobs:\n",
    "<ul>\n",
    "    <li> <b>n_samples</b>: The total number of points equally divided among clusters. </li>\n",
    "    <ul> <li> Choose a number from 10-1500 </li> </ul>\n",
    "    <li> <b>centers</b>: The number of centers to generate, or the fixed center locations. </li>\n",
    "    <ul> <li> Choose arrays of x,y coordinates for generating the centers. Have 1-10 centers (ex. centers=[[1,1], [2,5]]) </li> </ul>\n",
    "    <li> <b>cluster_std</b>: The standard deviation of the clusters. The larger the number, the further apart the clusters</li>\n",
    "    <ul> <li> Choose a number between 0.5-1.5 </li> </ul>\n",
    "</ul> <br>\n",
    "Save the result to <b>X1</b> and <b>y1</b>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "X1, y1 = make_blobs(n_samples=50, centers=[[4,4], [-2, -1], [1, 1], [10,4]], cluster_std=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the scatter plot of the randomly generated data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fcf02d563c8>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X1[:, 0], X1[:, 1], marker='o') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### Agglomerative Clustering\n",
    "We will start by clustering the random data points we just created."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The <b> Agglomerative Clustering </b> class will require two inputs:\n",
    "<ul>\n",
    "    <li> <b>n_clusters</b>: The number of clusters to form as well as the number of centroids to generate. </li>\n",
    "    <ul> <li> Value will be: 4 </li> </ul>\n",
    "    <li> <b>linkage</b>: Which linkage criterion to use. The linkage criterion determines which distance to use between sets of observation. The algorithm will merge the pairs of cluster that minimize this criterion. </li>\n",
    "    <ul> \n",
    "        <li> Value will be: 'complete' </li> \n",
    "        <li> <b>Note</b>: It is recommended you try everything with 'average' as well </li>\n",
    "    </ul>\n",
    "</ul> <br>\n",
    "Save the result to a variable called <b> agglom </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "agglom = AgglomerativeClustering(n_clusters = 4, linkage = 'average')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit the model with <b> X2 </b> and <b> y2 </b> from the generated data above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgglomerativeClustering(affinity='euclidean', compute_full_tree='auto',\n",
       "            connectivity=None, linkage='average', memory=None,\n",
       "            n_clusters=4, pooling_func='deprecated')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agglom.fit(X1,y1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the following code to show the clustering! <br>\n",
    "Remember to read the code and comments to gain more understanding on how the plotting works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure of size 6 inches by 4 inches.\n",
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "# These two lines of code are used to scale the data points down,\n",
    "# Or else the data points will be scattered very far apart.\n",
    "\n",
    "# Create a minimum and maximum range of X1.\n",
    "x_min, x_max = np.min(X1, axis=0), np.max(X1, axis=0)\n",
    "\n",
    "# Get the average distance for X1.\n",
    "X1 = (X1 - x_min) / (x_max - x_min)\n",
    "\n",
    "# This loop displays all of the datapoints.\n",
    "for i in range(X1.shape[0]):\n",
    "    # Replace the data points with their respective cluster value \n",
    "    # (ex. 0) and is color coded with a colormap (plt.cm.spectral)\n",
    "    plt.text(X1[i, 0], X1[i, 1], str(y1[i]),\n",
    "             color=plt.cm.nipy_spectral(agglom.labels_[i] / 10.),\n",
    "             fontdict={'weight': 'bold', 'size': 9})\n",
    "    \n",
    "# Remove the x ticks, y ticks, x and y axis\n",
    "plt.xticks([])\n",
    "plt.yticks([])\n",
    "#plt.axis('off')\n",
    "\n",
    "\n",
    "\n",
    "# Display the plot of the original data before clustering\n",
    "plt.scatter(X1[:, 0], X1[:, 1], marker='.')\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Dendrogram Associated for the Agglomerative Hierarchical Clustering\n",
    "Remember that a <b>distance matrix</b> contains the <b> distance from each point to every other point of a dataset </b>. <br>\n",
    "Use the function <b> distance_matrix, </b> which requires <b>two inputs</b>. Use the Feature Matrix, <b> X2 </b> as both inputs and save the distance matrix to a variable called <b> dist_matrix </b> <br> <br>\n",
    "Remember that the distance values are symmetric, with a diagonal of 0's. This is one way of making sure your matrix is correct. <br> (print out dist_matrix to make sure it's correct)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.         0.74836227 0.05850757 ... 0.30492133 0.19019444 0.97627621]\n",
      " [0.74836227 0.         0.69030421 ... 0.50098521 0.57481006 0.39545385]\n",
      " [0.05850757 0.69030421 0.         ... 0.25136579 0.14110003 0.9253408 ]\n",
      " ...\n",
      " [0.30492133 0.50098521 0.25136579 ... 0.         0.23105796 0.81468621]\n",
      " [0.19019444 0.57481006 0.14110003 ... 0.23105796 0.         0.78610615]\n",
      " [0.97627621 0.39545385 0.9253408  ... 0.81468621 0.78610615 0.        ]]\n"
     ]
    }
   ],
   "source": [
    "dist_matrix = distance_matrix(X1,X1) \n",
    "print(dist_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the <b> linkage </b> class from hierarchy, pass in the parameters:\n",
    "<ul>\n",
    "    <li> The distance matrix </li>\n",
    "    <li> 'complete' for complete linkage </li>\n",
    "</ul> <br>\n",
    "Save the result to a variable called <b> Z </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:1: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "Z = hierarchy.linkage(dist_matrix, 'complete')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Hierarchical clustering is typically visualized as a dendrogram as shown in the following cell. Each merge is represented by a horizontal line. The y-coordinate of the horizontal line is the similarity of the two clusters that were merged, where cities are viewed as singleton clusters. \n",
    "By moving up from the bottom layer to the top node, a dendrogram allows us to reconstruct the history of merges that resulted in the depicted clustering. \n",
    "\n",
    "Next, we will save the dendrogram to a variable called <b>dendro</b>. In doing this, the dendrogram will also be displayed.\n",
    "Using the <b> dendrogram </b> class from hierarchy, pass in the parameter:\n",
    "<ul> <li> Z </li> </ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "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": [
    "dendro = hierarchy.dendrogram(Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Practice\n",
    "We used __complete__ linkage for our case, change it to __average__ linkage to see how the dendogram changes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:2: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  \n"
     ]
    },
    {
     "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": [
    "# write your code here\n",
    "Z = hierarchy.linkage(dist_matrix, 'average')\n",
    "dendro = hierarchy.dendrogram(Z)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Double-click __here__ for the solution.\n",
    "\n",
    "<!-- Your answer is below:\n",
    "    \n",
    "Z = hierarchy.linkage(dist_matrix, 'average')\n",
    "dendro = hierarchy.dendrogram(Z)\n",
    "\n",
    "-->"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Clustering on Vehicle dataset\n",
    "\n",
    "Imagine that an automobile manufacturer has developed prototypes for a new vehicle. Before introducing the new model into its range, the manufacturer wants to determine which existing vehicles on the market are most like the prototypes--that is, how vehicles can be grouped, which group is the most similar with the model, and therefore which models they will be competing against.\n",
    "\n",
    "Our objective here, is to use clustering methods, to find the most distinctive clusters of vehicles. It will summarize the existing vehicles and help manufacture to make decision about new models simply."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download data\n",
    "To download the data, we will use **`!wget`**. To download the data, we will use `!wget` to download it from IBM Object Storage.  \n",
    "__Did you know?__ When it comes to Machine Learning, you will likely be working with large datasets. As a business, where can you host your data? IBM is offering a unique opportunity for businesses, with 10 Tb of IBM Cloud Object Storage: [Sign up now for free](http://cocl.us/ML0101EN-IBM-Offer-CC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2020-07-15 06:15:07--  https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/cars_clus.csv\n",
      "Resolving s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)... 67.228.254.196\n",
      "Connecting to s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)|67.228.254.196|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 17774 (17K) [text/csv]\n",
      "Saving to: ‘cars_clus.csv’\n",
      "\n",
      "cars_clus.csv       100%[===================>]  17.36K  --.-KB/s    in 0.02s   \n",
      "\n",
      "2020-07-15 06:15:07 (960 KB/s) - ‘cars_clus.csv’ saved [17774/17774]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget -O cars_clus.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/cars_clus.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read data\n",
    "lets read dataset to see what features the manufacturer has collected about the existing models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of dataset:  (159, 16)\n"
     ]
    },
    {
     "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>manufact</th>\n",
       "      <th>model</th>\n",
       "      <th>sales</th>\n",
       "      <th>resale</th>\n",
       "      <th>type</th>\n",
       "      <th>price</th>\n",
       "      <th>engine_s</th>\n",
       "      <th>horsepow</th>\n",
       "      <th>wheelbas</th>\n",
       "      <th>width</th>\n",
       "      <th>length</th>\n",
       "      <th>curb_wgt</th>\n",
       "      <th>fuel_cap</th>\n",
       "      <th>mpg</th>\n",
       "      <th>lnsales</th>\n",
       "      <th>partition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acura</td>\n",
       "      <td>Integra</td>\n",
       "      <td>16.919</td>\n",
       "      <td>16.360</td>\n",
       "      <td>0.000</td>\n",
       "      <td>21.500</td>\n",
       "      <td>1.800</td>\n",
       "      <td>140.000</td>\n",
       "      <td>101.200</td>\n",
       "      <td>67.300</td>\n",
       "      <td>172.400</td>\n",
       "      <td>2.639</td>\n",
       "      <td>13.200</td>\n",
       "      <td>28.000</td>\n",
       "      <td>2.828</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acura</td>\n",
       "      <td>TL</td>\n",
       "      <td>39.384</td>\n",
       "      <td>19.875</td>\n",
       "      <td>0.000</td>\n",
       "      <td>28.400</td>\n",
       "      <td>3.200</td>\n",
       "      <td>225.000</td>\n",
       "      <td>108.100</td>\n",
       "      <td>70.300</td>\n",
       "      <td>192.900</td>\n",
       "      <td>3.517</td>\n",
       "      <td>17.200</td>\n",
       "      <td>25.000</td>\n",
       "      <td>3.673</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acura</td>\n",
       "      <td>CL</td>\n",
       "      <td>14.114</td>\n",
       "      <td>18.225</td>\n",
       "      <td>0.000</td>\n",
       "      <td>$null$</td>\n",
       "      <td>3.200</td>\n",
       "      <td>225.000</td>\n",
       "      <td>106.900</td>\n",
       "      <td>70.600</td>\n",
       "      <td>192.000</td>\n",
       "      <td>3.470</td>\n",
       "      <td>17.200</td>\n",
       "      <td>26.000</td>\n",
       "      <td>2.647</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acura</td>\n",
       "      <td>RL</td>\n",
       "      <td>8.588</td>\n",
       "      <td>29.725</td>\n",
       "      <td>0.000</td>\n",
       "      <td>42.000</td>\n",
       "      <td>3.500</td>\n",
       "      <td>210.000</td>\n",
       "      <td>114.600</td>\n",
       "      <td>71.400</td>\n",
       "      <td>196.600</td>\n",
       "      <td>3.850</td>\n",
       "      <td>18.000</td>\n",
       "      <td>22.000</td>\n",
       "      <td>2.150</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A4</td>\n",
       "      <td>20.397</td>\n",
       "      <td>22.255</td>\n",
       "      <td>0.000</td>\n",
       "      <td>23.990</td>\n",
       "      <td>1.800</td>\n",
       "      <td>150.000</td>\n",
       "      <td>102.600</td>\n",
       "      <td>68.200</td>\n",
       "      <td>178.000</td>\n",
       "      <td>2.998</td>\n",
       "      <td>16.400</td>\n",
       "      <td>27.000</td>\n",
       "      <td>3.015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  manufact    model   sales  resale   type   price engine_s horsepow wheelbas  \\\n",
       "0    Acura  Integra  16.919  16.360  0.000  21.500    1.800  140.000  101.200   \n",
       "1    Acura       TL  39.384  19.875  0.000  28.400    3.200  225.000  108.100   \n",
       "2    Acura       CL  14.114  18.225  0.000  $null$    3.200  225.000  106.900   \n",
       "3    Acura       RL   8.588  29.725  0.000  42.000    3.500  210.000  114.600   \n",
       "4     Audi       A4  20.397  22.255  0.000  23.990    1.800  150.000  102.600   \n",
       "\n",
       "    width   length curb_wgt fuel_cap     mpg lnsales  partition  \n",
       "0  67.300  172.400    2.639   13.200  28.000   2.828        0.0  \n",
       "1  70.300  192.900    3.517   17.200  25.000   3.673        0.0  \n",
       "2  70.600  192.000    3.470   17.200  26.000   2.647        0.0  \n",
       "3  71.400  196.600    3.850   18.000  22.000   2.150        0.0  \n",
       "4  68.200  178.000    2.998   16.400  27.000   3.015        0.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filename = 'cars_clus.csv'\n",
    "\n",
    "#Read csv\n",
    "pdf = pd.read_csv(filename)\n",
    "print (\"Shape of dataset: \", pdf.shape)\n",
    "\n",
    "pdf.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The featuresets include  price in thousands (price), engine size (engine_s), horsepower (horsepow), wheelbase (wheelbas), width (width), length (length), curb weight (curb_wgt), fuel capacity (fuel_cap) and fuel efficiency (mpg)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning\n",
    "lets simply clear the dataset by dropping the rows that have null value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of dataset before cleaning:  2544\n",
      "Shape of dataset after cleaning:  1872\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>manufact</th>\n",
       "      <th>model</th>\n",
       "      <th>sales</th>\n",
       "      <th>resale</th>\n",
       "      <th>type</th>\n",
       "      <th>price</th>\n",
       "      <th>engine_s</th>\n",
       "      <th>horsepow</th>\n",
       "      <th>wheelbas</th>\n",
       "      <th>width</th>\n",
       "      <th>length</th>\n",
       "      <th>curb_wgt</th>\n",
       "      <th>fuel_cap</th>\n",
       "      <th>mpg</th>\n",
       "      <th>lnsales</th>\n",
       "      <th>partition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acura</td>\n",
       "      <td>Integra</td>\n",
       "      <td>16.919</td>\n",
       "      <td>16.360</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.50</td>\n",
       "      <td>1.8</td>\n",
       "      <td>140.0</td>\n",
       "      <td>101.2</td>\n",
       "      <td>67.3</td>\n",
       "      <td>172.4</td>\n",
       "      <td>2.639</td>\n",
       "      <td>13.2</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.828</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acura</td>\n",
       "      <td>TL</td>\n",
       "      <td>39.384</td>\n",
       "      <td>19.875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.40</td>\n",
       "      <td>3.2</td>\n",
       "      <td>225.0</td>\n",
       "      <td>108.1</td>\n",
       "      <td>70.3</td>\n",
       "      <td>192.9</td>\n",
       "      <td>3.517</td>\n",
       "      <td>17.2</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3.673</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acura</td>\n",
       "      <td>RL</td>\n",
       "      <td>8.588</td>\n",
       "      <td>29.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>210.0</td>\n",
       "      <td>114.6</td>\n",
       "      <td>71.4</td>\n",
       "      <td>196.6</td>\n",
       "      <td>3.850</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.150</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A4</td>\n",
       "      <td>20.397</td>\n",
       "      <td>22.255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1.8</td>\n",
       "      <td>150.0</td>\n",
       "      <td>102.6</td>\n",
       "      <td>68.2</td>\n",
       "      <td>178.0</td>\n",
       "      <td>2.998</td>\n",
       "      <td>16.4</td>\n",
       "      <td>27.0</td>\n",
       "      <td>3.015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A6</td>\n",
       "      <td>18.780</td>\n",
       "      <td>23.555</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.95</td>\n",
       "      <td>2.8</td>\n",
       "      <td>200.0</td>\n",
       "      <td>108.7</td>\n",
       "      <td>76.1</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3.561</td>\n",
       "      <td>18.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.933</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  manufact    model   sales  resale  type  price  engine_s  horsepow  \\\n",
       "0    Acura  Integra  16.919  16.360   0.0  21.50       1.8     140.0   \n",
       "1    Acura       TL  39.384  19.875   0.0  28.40       3.2     225.0   \n",
       "2    Acura       RL   8.588  29.725   0.0  42.00       3.5     210.0   \n",
       "3     Audi       A4  20.397  22.255   0.0  23.99       1.8     150.0   \n",
       "4     Audi       A6  18.780  23.555   0.0  33.95       2.8     200.0   \n",
       "\n",
       "   wheelbas  width  length  curb_wgt  fuel_cap   mpg  lnsales  partition  \n",
       "0     101.2   67.3   172.4     2.639      13.2  28.0    2.828        0.0  \n",
       "1     108.1   70.3   192.9     3.517      17.2  25.0    3.673        0.0  \n",
       "2     114.6   71.4   196.6     3.850      18.0  22.0    2.150        0.0  \n",
       "3     102.6   68.2   178.0     2.998      16.4  27.0    3.015        0.0  \n",
       "4     108.7   76.1   192.0     3.561      18.5  22.0    2.933        0.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print (\"Shape of dataset before cleaning: \", pdf.size)\n",
    "pdf[[ 'sales', 'resale', 'type', 'price', 'engine_s',\n",
    "       'horsepow', 'wheelbas', 'width', 'length', 'curb_wgt', 'fuel_cap',\n",
    "       'mpg', 'lnsales']] = pdf[['sales', 'resale', 'type', 'price', 'engine_s',\n",
    "       'horsepow', 'wheelbas', 'width', 'length', 'curb_wgt', 'fuel_cap',\n",
    "       'mpg', 'lnsales']].apply(pd.to_numeric, errors='coerce')\n",
    "pdf = pdf.dropna()\n",
    "pdf = pdf.reset_index(drop=True)\n",
    "print (\"Shape of dataset after cleaning: \", pdf.size)\n",
    "pdf.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature selection\n",
    "Lets select our feature set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "featureset = pdf[['engine_s',  'horsepow', 'wheelbas', 'width', 'length', 'curb_wgt', 'fuel_cap', 'mpg']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Normalization\n",
    "Now we can normalize the feature set. __MinMaxScaler__ transforms features by scaling each feature to a given range. It is by default (0, 1). That is, this estimator scales and translates each feature individually such that it is between zero and one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.11428571, 0.21518987, 0.18655098, 0.28143713, 0.30625832,\n",
       "        0.2310559 , 0.13364055, 0.43333333],\n",
       "       [0.31428571, 0.43037975, 0.3362256 , 0.46107784, 0.5792277 ,\n",
       "        0.50372671, 0.31797235, 0.33333333],\n",
       "       [0.35714286, 0.39240506, 0.47722343, 0.52694611, 0.62849534,\n",
       "        0.60714286, 0.35483871, 0.23333333],\n",
       "       [0.11428571, 0.24050633, 0.21691974, 0.33532934, 0.38082557,\n",
       "        0.34254658, 0.28110599, 0.4       ],\n",
       "       [0.25714286, 0.36708861, 0.34924078, 0.80838323, 0.56724368,\n",
       "        0.5173913 , 0.37788018, 0.23333333]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "x = featureset.values #returns a numpy array\n",
    "min_max_scaler = MinMaxScaler()\n",
    "feature_mtx = min_max_scaler.fit_transform(x)\n",
    "feature_mtx [0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering using Scipy\n",
    "In this part we use Scipy package to cluster the dataset:  \n",
    "First, we calculate the distance matrix. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:3: DeprecationWarning: scipy.zeros is deprecated and will be removed in SciPy 2.0.0, use numpy.zeros instead\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "import scipy\n",
    "leng = feature_mtx.shape[0]\n",
    "D = scipy.zeros([leng,leng])\n",
    "for i in range(leng):\n",
    "    for j in range(leng):\n",
    "        D[i,j] = scipy.spatial.distance.euclidean(feature_mtx[i], feature_mtx[j])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In agglomerative clustering, at each iteration, the algorithm must update the distance matrix to reflect the distance of the newly formed cluster with the remaining clusters in the forest. \n",
    "The following methods are supported in Scipy for calculating the distance between the newly formed cluster and each:\n",
    "    - single\n",
    "    - complete\n",
    "    - average\n",
    "    - weighted\n",
    "    - centroid\n",
    "    \n",
    "    \n",
    "We use __complete__ for our case, but feel free to change it to see how the results change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:3: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "import pylab\n",
    "import scipy.cluster.hierarchy\n",
    "Z = hierarchy.linkage(D, 'complete')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Essentially, Hierarchical clustering does not require a pre-specified number of clusters. However, in some applications we want a partition of disjoint clusters just as in flat clustering.\n",
    "So you can use a cutting line:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  5,  5,  6,  5,  4,  6,  5,  5,  5,  5,  5,  4,  4,  5,  1,  6,\n",
       "        5,  5,  5,  4,  2, 11,  6,  6,  5,  6,  5,  1,  6,  6, 10,  9,  8,\n",
       "        9,  3,  5,  1,  7,  6,  5,  3,  5,  3,  8,  7,  9,  2,  6,  6,  5,\n",
       "        4,  2,  1,  6,  5,  2,  7,  5,  5,  5,  4,  4,  3,  2,  6,  6,  5,\n",
       "        7,  4,  7,  6,  6,  5,  3,  5,  5,  6,  5,  4,  4,  1,  6,  5,  5,\n",
       "        5,  6,  4,  5,  4,  1,  6,  5,  6,  6,  5,  5,  5,  7,  7,  7,  2,\n",
       "        2,  1,  2,  6,  5,  1,  1,  1,  7,  8,  1,  1,  6,  1,  1],\n",
       "      dtype=int32)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import fcluster\n",
    "max_d = 3\n",
    "clusters = fcluster(Z, max_d, criterion='distance')\n",
    "clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also, you can determine the number of clusters directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 2, 2, 3, 1, 3, 3, 3, 3, 2, 1,\n",
       "       5, 3, 3, 3, 3, 3, 1, 3, 3, 4, 4, 4, 4, 2, 3, 1, 3, 3, 3, 2, 3, 2,\n",
       "       4, 3, 4, 1, 3, 3, 3, 2, 1, 1, 3, 3, 1, 3, 3, 3, 3, 2, 2, 2, 1, 3,\n",
       "       3, 3, 3, 2, 3, 3, 3, 3, 2, 3, 3, 3, 3, 2, 2, 1, 3, 3, 3, 3, 3, 2,\n",
       "       3, 2, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 1, 1, 1,\n",
       "       3, 4, 1, 1, 3, 1, 1], dtype=int32)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import fcluster\n",
    "k = 5\n",
    "clusters = fcluster(Z, k, criterion='maxclust')\n",
    "clusters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, plot the dendrogram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x3600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = pylab.figure(figsize=(18,50))\n",
    "def llf(id):\n",
    "    return '[%s %s %s]' % (pdf['manufact'][id], pdf['model'][id], int(float(pdf['type'][id])) )\n",
    "    \n",
    "dendro = hierarchy.dendrogram(Z,  leaf_label_func=llf, leaf_rotation=0, leaf_font_size =12, orientation = 'right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering using scikit-learn\n",
    "Lets redo it again, but this time using scikit-learn package:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.         0.57777143 0.75455727 ... 0.28530295 0.24917241 0.18879995]\n",
      " [0.57777143 0.         0.22798938 ... 0.36087756 0.66346677 0.62201282]\n",
      " [0.75455727 0.22798938 0.         ... 0.51727787 0.81786095 0.77930119]\n",
      " ...\n",
      " [0.28530295 0.36087756 0.51727787 ... 0.         0.41797928 0.35720492]\n",
      " [0.24917241 0.66346677 0.81786095 ... 0.41797928 0.         0.15212198]\n",
      " [0.18879995 0.62201282 0.77930119 ... 0.35720492 0.15212198 0.        ]]\n"
     ]
    }
   ],
   "source": [
    "dist_matrix = distance_matrix(feature_mtx,feature_mtx) \n",
    "print(dist_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can use the 'AgglomerativeClustering' function from scikit-learn library to cluster the dataset. The AgglomerativeClustering performs a hierarchical clustering using a bottom up approach. The linkage criteria determines the metric used for the merge strategy:\n",
    "\n",
    "- Ward minimizes the sum of squared differences within all clusters. It is a variance-minimizing approach and in this sense is similar to the k-means objective function but tackled with an agglomerative hierarchical approach.\n",
    "- Maximum or complete linkage minimizes the maximum distance between observations of pairs of clusters.\n",
    "- Average linkage minimizes the average of the distances between all observations of pairs of clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 2, 1, 2, 3, 1, 2, 2, 2, 2, 2, 3, 3, 2, 1, 1, 2, 2, 2, 5, 1,\n",
       "       4, 1, 1, 2, 1, 2, 1, 1, 1, 5, 0, 0, 0, 3, 2, 1, 2, 1, 2, 3, 2, 3,\n",
       "       0, 3, 0, 1, 1, 1, 2, 3, 1, 1, 1, 2, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1,\n",
       "       1, 2, 1, 2, 2, 1, 1, 2, 3, 2, 3, 1, 2, 3, 5, 1, 1, 2, 3, 2, 1, 3,\n",
       "       2, 3, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1,\n",
       "       2, 0, 1, 1, 1, 1, 1])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agglom = AgglomerativeClustering(n_clusters = 6, linkage = 'complete')\n",
    "agglom.fit(feature_mtx)\n",
    "agglom.labels_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And, we can add a new field to our dataframe to show the cluster of each row:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>manufact</th>\n",
       "      <th>model</th>\n",
       "      <th>sales</th>\n",
       "      <th>resale</th>\n",
       "      <th>type</th>\n",
       "      <th>price</th>\n",
       "      <th>engine_s</th>\n",
       "      <th>horsepow</th>\n",
       "      <th>wheelbas</th>\n",
       "      <th>width</th>\n",
       "      <th>length</th>\n",
       "      <th>curb_wgt</th>\n",
       "      <th>fuel_cap</th>\n",
       "      <th>mpg</th>\n",
       "      <th>lnsales</th>\n",
       "      <th>partition</th>\n",
       "      <th>cluster_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acura</td>\n",
       "      <td>Integra</td>\n",
       "      <td>16.919</td>\n",
       "      <td>16.360</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.50</td>\n",
       "      <td>1.8</td>\n",
       "      <td>140.0</td>\n",
       "      <td>101.2</td>\n",
       "      <td>67.3</td>\n",
       "      <td>172.4</td>\n",
       "      <td>2.639</td>\n",
       "      <td>13.2</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.828</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acura</td>\n",
       "      <td>TL</td>\n",
       "      <td>39.384</td>\n",
       "      <td>19.875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.40</td>\n",
       "      <td>3.2</td>\n",
       "      <td>225.0</td>\n",
       "      <td>108.1</td>\n",
       "      <td>70.3</td>\n",
       "      <td>192.9</td>\n",
       "      <td>3.517</td>\n",
       "      <td>17.2</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3.673</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acura</td>\n",
       "      <td>RL</td>\n",
       "      <td>8.588</td>\n",
       "      <td>29.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>210.0</td>\n",
       "      <td>114.6</td>\n",
       "      <td>71.4</td>\n",
       "      <td>196.6</td>\n",
       "      <td>3.850</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A4</td>\n",
       "      <td>20.397</td>\n",
       "      <td>22.255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1.8</td>\n",
       "      <td>150.0</td>\n",
       "      <td>102.6</td>\n",
       "      <td>68.2</td>\n",
       "      <td>178.0</td>\n",
       "      <td>2.998</td>\n",
       "      <td>16.4</td>\n",
       "      <td>27.0</td>\n",
       "      <td>3.015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A6</td>\n",
       "      <td>18.780</td>\n",
       "      <td>23.555</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.95</td>\n",
       "      <td>2.8</td>\n",
       "      <td>200.0</td>\n",
       "      <td>108.7</td>\n",
       "      <td>76.1</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3.561</td>\n",
       "      <td>18.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  manufact    model   sales  resale  type  price  engine_s  horsepow  \\\n",
       "0    Acura  Integra  16.919  16.360   0.0  21.50       1.8     140.0   \n",
       "1    Acura       TL  39.384  19.875   0.0  28.40       3.2     225.0   \n",
       "2    Acura       RL   8.588  29.725   0.0  42.00       3.5     210.0   \n",
       "3     Audi       A4  20.397  22.255   0.0  23.99       1.8     150.0   \n",
       "4     Audi       A6  18.780  23.555   0.0  33.95       2.8     200.0   \n",
       "\n",
       "   wheelbas  width  length  curb_wgt  fuel_cap   mpg  lnsales  partition  \\\n",
       "0     101.2   67.3   172.4     2.639      13.2  28.0    2.828        0.0   \n",
       "1     108.1   70.3   192.9     3.517      17.2  25.0    3.673        0.0   \n",
       "2     114.6   71.4   196.6     3.850      18.0  22.0    2.150        0.0   \n",
       "3     102.6   68.2   178.0     2.998      16.4  27.0    3.015        0.0   \n",
       "4     108.7   76.1   192.0     3.561      18.5  22.0    2.933        0.0   \n",
       "\n",
       "   cluster_  \n",
       "0         1  \n",
       "1         2  \n",
       "2         2  \n",
       "3         1  \n",
       "4         2  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf['cluster_'] = agglom.labels_\n",
    "pdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'mpg')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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y8/MpKyvjtdde46WXXjpa07AqSZIkJU9L9sRtOqJujPG4IfnILE+AxsY/7a0zbdo0li5dSmFhIZMnT2bZsmVt1p49ezY1NTXU1NSwceNGbr/9dgC6du16Gk9zagysHWDZsmXMmDGDzZs3A/Dqq69y8803M2bMGL73ve8B8Nvf/paf/OQnvP/976ehoYH/+3//LwMGDGD06NH07NmTq666ihtvvJGBAwdy7733MmrUqHP3QJIkSZJOKL+D0tWJ6l555ZUsXryY3bt3A7kdSN6ovLyc1atXA7ktM4948cUXGTRoEDNmzKCqqoo1a9bQrVs3Dhw4cLTN5MmTWbhwIQ0NDQBs3bqVHTt2tMdjnRQDawdoaWnhW9/6Fg8//DD79++nZ8+erF27lo997GNs2bKFrVu3UlZWxvbt26murmbhwoVccsklPPXUU1x88cXMmjWLqVOn8vWvf50PfehD9OvX71w/kiRJkqQTKO4cyMbcqGR7yK2+C70Kjz/FeOjQodxzzz1MmDCB4cOHc+eddx5z/q677uLb3/42H/zgB9m1a9fR40888QTDhg2jsrKSF154gVtvvZVevXoxfvx4hg0bxt13382f//mfM23aNMaNG8fll1/O1KlTjwm0b/R3f/d3lJaWcvDgQUpLS5kzZ84Zfwehvb7MjjRq1Kh4ZFWrRMpmYM8W2PY8NDYQO3Wl7Oq/4iNV1zOgrIxbb72VRx55hD59+rB//35SqRR/8Rd/wa233sqNN97I2LFjWbBgAevXr+eHP/whAwcOPNdPJEmSJOkkrF+/niFDhhz9+yvPNtGciRQVnPl7rA3NkU7pwOyx7bTscEK8+TsDCCGsjjG+ZVqpI6xnqqkBVv8Ifr8U6l+GpgOEPa8w/7Y/Y++Laxh5+RBuu+02evTowZAhQ7jiiitYsWIFRUVFPPjgg7z66qt88Ytf5JJLLuHpp582rEqSJEnnsQmlafY1tU+tvU3wodJ0+xQ7T3V4YA0hpEMIz4UQfnb47zkhhK0hhJrDP9d0dB86TDYDa34GDbugW28o7AEFXaCwB1Ov/TOqn/09k/s28oExo/nyl79MU1MTH/jAB+jXrx/z589n5MiRfPnLX6a6uppZs2ZRUFBwrp9IkiRJ0hmo7JumUxoOtbY9kzVLpCWVoSmvhZZUhixttzvUEumcztV7Nzsb29rMBNYD3d9w7BsxxgfOwr071p4tsH87dO/zllN5eWnunv4R/teCx/hfD3ybcR8cT3l5OZ07dz66qha035LXkiRJks69rvmBqZfm8f21rQzoHkmFQCTSlNfKvi6vs6/LQWKIEAOESIiBCw524YKDXenUmkcgkI2RHQfhvw/Lo2v+uzsvdGhgDSGUAtcCc4E7T9D8/LPtech/+1HRmZ+4mouuuYP/52/Xcc01fxpIHjdu3NHfDaySJEnSO8v7+6bZUB9ZuS1D7x4t7Oi5l4MFzaRiIK81TYo/ZYAskX1dDrKn6+t0aSqgz94e7Nibx9iL0rz/XT66Ch0/JfibwN8Bb9456PMhhDUhhIUhhJ5tXRhC+OsQwqoQwqqdO3d2cDdPU2MDpN8+sHbuVMD0yeP4afXTZ7FTkiRJks6lEAI3XZrH0NIMz1+wk9fTLXRqyaOgNe+YsAqQIlDQmkenljxez2vh+Qt2Mqw0w02X5jm4RQcG1hDCdcCOGOPqN536NvBeoBLYBjzY1vUxxu/EGEfFGEf17t27o7p5ZjoXQab5uE2+8T8+xkf+fMJZ6pAkSZKkJGgIrWQG1jOkOE1syuNAc6A503bb5gwcaA7EpjyGFKfJDKynIbSe3Q4nVEeOsI4HqkIIm4EfApNCCItijNtjjJkYYxb4Z2BMB/ahY134Pmg5fmBNZVrhwqFnqUOSJEmSzrUYI79s2U0k8t6u+UwYkGZorxR5KTjQ/NafvBQM7ZViwoA07+2aTyTyny27z2g/1zlz5vDAA6e+bNDevXtZsGDBKV938OBBrr32Wi677DKGDh3KrFmzTrlGWzossMYYZ8cYS2OM5cAngGUxxr8IIVz4hmYfA9Z2VB86XM8B0L0vNOxu+3zD7tz5nqVnt1+SJEmSzpldsYVXs01ccHjJoPxUYEC3FFf0z+PKsjTjLkrzgQtzn1eWpbmifx4DuqXIT+WmAF9AHluzTeyKLWe976cTWI8E67vuuosXXniB5557jhUrVvDv//7vZ9yfc7EP69dDCH8IIawBPgx84Rz0oX2k0lBxHRSVwP4dcGgvNB/Mfe7fkTtecV2unSRJkqR3hXWZBtKh7QVW81KB7gWBHp1yn3mpt7YJIZAOuTon67HHHqOiooLhw4czffr0Y85NnDiRVatWAbBr1y7Ky8tz/Vy3jjFjxlBZWUlFRQW1tbXMmjWLTZs2UVlZyd133w3A/PnzGT16NBUVFdx///0AbN68mSFDhnDHHXcwcuRIdu7cyYc//GEACgoKGDlyJHV1dSfd/7dzNra1Icb4FPDU4d+nH7fx+aZTEbz/47CnDratyy3E1LkoNw24Z6lhVZIkSXoXaYlZ1mYOcAH5Z1TnAvJZmznA+Lwe5IfjjzOuW7eOuXPnsmLFCkpKSqivr+fhhx8+4T0eeeQRZs6cyS233EJzczOZTIZ58+axdu1aampqAKiurqa2tpaVK1cSY6Sqqorly5dTVlbGhg0bePTRR98yIrt3715++tOfMnPmzNP/Ag47K4H1HS+Vhl4Dcz+SJEmS3rUayZIB8s5whd+8EMjGXL38E0yMXbZsGVOnTqWkpASA4uLik7rHuHHjmDt3LnV1ddxwww0MHjz4LW2qq6uprq5mxIgRADQ0NFBbW0tZWRkDBw5k7Nixx7RvbW3lk5/8JDNmzGDQoEEn1Y/jORdTgiVJkiTpHaklRtpzM5qWk1h4KcZ43C1w8vLyyGZzO402NjYePT5t2jSWLl1KYWEhkydPZtmyZW3Wnj17NjU1NdTU1LBx40Zuv/12ALp27fqW9n/913/N4MGD+Zu/+ZsT9vtkGFglSZIkqZ3kh8Dpr+3bdr0TufLKK1m8eDG7d+cWg62vrz/mfHl5OatX53YbXbJkydHjL774IoMGDWLGjBlUVVWxZs0aunXrxoEDB462mTx5MgsXLqShIfc+7datW9mxY0eb/bj33nvZt28f3/zmN0/tIY/DKcGSJEmS1E46kyINtMZ4RtOCW2MkdbjeiQwdOpR77rmHCRMmkE6nGTFixNGFlSC3eu9NN93E448/zqRJk44ef+KJJ1i0aBH5+fn069eP++67j+LiYsaPH8+wYcOYMmUK8+fPZ/369YwbNw6AoqIiFi1aRDp97Fo9dXV1zJ07l8suu4yRI0cC8PnPf55Pf/rTp/0dAIQz2dvnbBk1alQ8sqqVJEmSJCXF+vXrGTJkyDHHnmqp5w+ZA/QKBaddd3ds5vJ0Nybmn9z7qOeTtr6zEMLqGOOoN7d1SrAkSZIktaOh6SIy8U/7k75FzEBsyX22dTpGMjFX593OKcGSJEmS1I5KQj79U53YGZvpQT7ESIrXSWd3k2I/ITYDAYjEUECW7mRSvcjSFUJgH630T3WiJJzZ1jjvBI6wSpIkSVI7CiFwVX4vUgQOZg9QkH2BgswG0rEeYiBSSAyFRAohBtKxnoLMBgqyL3Awe4AUueuPt/Lvu4WBVZIkSZLaWc9UPlemMnTLbqAle4gsXYihM4Q0HAmiIUBIE0NnsnShJXuIbtkNXJnK0DPl6CoYWCVJkiSp3e1q3UpDdiOXpIrpnOrCQTIcjBmyb3qtNRvhYMxwkAydU124JFVMQ3Yju1q3npuOJ4zvsEqSJElSOzqUbaCudQOdKSKVSvM+8jkYs+yIzezMNvHGtZgCgT6pTvQJBXQJKSCQjWnqWjfQNXUBhal398JLjrBKkiRJUjuJMfJKy/OkyCMVjuxVGugS0pSnCnl/3gVU5nXn8nQ3KvO68/687pSnCukS0uQWYoJUSJMij1dann/7lYZPYM6cOTzwwAOnfN3evXtZsGDBad3z6quvZvjw4QwdOpTPfvazZDJtr4J8KgyskiRJktROXo/7OBQb6BQK2zyfIlBAisKQpoAUKdpeWKlTKORQbOD1uK8ju/sWpxNYY4xks1kWL17M73//e9auXcvOnTv50Y9+dMb9MbBKkiRJUjupz2wjtFPMCqSoz2w7qbaPPfYYFRUVDB8+nOnTpx9zbuLEiaxatQqAXbt2UV5eDsC6desYM2YMlZWVVFRUUFtby6xZs9i0aROVlZXcfffdAMyfP5/Ro0dTUVHB/fffD8DmzZsZMmQId9xxByNHjmTLli10794dgNbWVpqbm9tllWPfYZUkSZKkdnIgs4d8OrVLrXw60ZDdc8J269atY+7cuaxYsYKSkhLq6+t5+OGHT3jdI488wsyZM7nllltobm4mk8kwb9481q5dS01NDQDV1dXU1taycuVKYoxUVVWxfPlyysrK2LBhA48++ugxI7KTJ09m5cqVTJkyhalTp57+wx/mCKskSZIktYNMbKWFRlKkT9z4JKRI0xwbycTW47ZbtmwZU6dOpaSkBIDi4uKTqj9u3Di+8pWv8LWvfY2XX36ZwsK3TmOurq6murqaESNGMHLkSF544QVqa2sBGDhwIGPHjj2m/X/8x3+wbds2mpqaWLZs2Un143gMrJIkSZLUDiJZAqFdpsICR+tEsse/b4zHvWdeXh7ZbK5GY2Pj0ePTpk1j6dKlFBYWMnny5DYDZoyR2bNnU1NTQ01NDRs3buT2228HoGvXrm3er3PnzlRVVfGTn/zk+A94EgyskiRJktQOAiki8bRX9n2zI3VO9E7slVdeyeLFi9m9ezcA9fX1x5wvLy9n9erVACxZsuTo8RdffJFBgwYxY8YMqqqqWLNmDd26dePAgQNH20yePJmFCxfS0NAAwNatW9mxY8db+tDQ0MC2bbn3bVtbW/n5z3/OZZdddqqP/Ba+wypJkiRJ7SAd8sinM1kypNshamXJUBA6kw7HrzV06FDuueceJkyYQDqdZsSIEUcXVgK46667uOmmm3j88ceZNGnS0eNPPPEEixYtIj8/n379+nHfffdRXFzM+PHjGTZsGFOmTGH+/PmsX7+ecePGAVBUVMSiRYtIp4+d9vz6669TVVVFU1MTmUyGSZMm8dnPfvaMv4PQXum/I40aNSoeWdVKkiRJkpJi/fr1DBky5Ojfr7SsZ09mO51D29NlT0VjfJ2e6b6U5Q85cePzyJu/M4AQwuoY46g3t3VKsCRJkiS1k+L0hSd85/RkRbIUpy9sl1rnKwOrJEmSJLWTruECCkMRTfHQGdVpiocoDN3oGi5op56dnwyskiRJktROQgiU5b+PLK1kY+a0amRjhiytlOUPabcVh89XBlZJkiRJakeFqSJK8y6lkYZTDq3ZmKGRBkrzLqUwVdRBPTx/uEqwJEmSJLWzkrz+ANS1biAV8+gUCk94TVM8RJZWBuQNOXr9u52BVZIkSZI6QElef7qmLuCVluc5FA8QSJFPJ1KkCSEQYyRLhhaaiGQpDEWU5b/PkdU3cEqwJEmSJHWQwlQRlxSM5uKCkfQMJRTU76Dr8yvo9tyTdH1+BZ327KBn6M3FBSO5pGB0u4XVOXPm8MADD5zydXv37mXBggVndO+qqiqGDRt2RjWOMLBKkiRJUgcKIVDUkkfZmrVc/MLL9D/QiX6tveh/oBPvfX4zZWv+QFFLXiIWWDqdwBpjJJvNbeXzL//yLxQVtd8IsYFVkiRJkjpSNgNrfgYNu6Bbb1JdepLqVESqS0/o3id3fM3Pcu1O02OPPUZFRQXDhw9n+vTpx5ybOHEiq1atAmDXrl2Ul5cDsG7dOsaMGUNlZSUVFRXU1tYya9YsNm3aRGVlJXfffTcA8+fPZ/To0VRUVHD//fcDsHnzZoYMGcIdd9zByJEj2bJlCw0NDTz00EPce++9p/0cb+Y7rJIkSZLUkfZsgf3bc+G0LUW9cuf31EGvgadcft26dcydO5cVK1ZQUlJCfX09Dz/88Amve+SRR5g5cya33HILzc3NZDIZ5s2bx9q1a6mpqQGgurqa2tpaVq5cSYyRqqoqli9fTllZGRs2bODRRx89OiL7hS98gb/927+lS5cup/wMbxvYnncAACAASURBVMcRVkmSJEnqSNueh/yC47fJL4Bt606r/LJly5g6dSolJSUAFBcXn9R148aN4ytf+Qpf+9rXePnllyksfOtKxtXV1VRXVzNixAhGjhzJCy+8QG1tLQADBw5k7NixANTU1LBx40Y+9rGPndYzvB0DqyRJkiR1pMYGSJ8gsKYLcu1OQ4zxuO+/5uXlHX3HtLGx8ejxadOmsXTpUgoLC5k8eTLLli1rs/bs2bOpqak5Gkpvv/12ALp27Xq03W9/+1tWr15NeXk5V1xxBX/84x+ZOHHiaT3PGxlYJUmSJKkjdS6CTPPx22Sac+1Ow5VXXsnixYvZvXs3APX19cecLy8vZ/Xq1QAsWbLk6PEXX3yRQYMGMWPGDKqqqlizZg3dunXjwIEDR9tMnjyZhQsX0tCQC9Nbt25lx44db+nD5z73OV599VU2b97Mb37zGy655BKeeuqp03qeN/IdVkmSJEnqSBe+D15ZBzsPwY562FkPLa2Qnwe9i6FPMRRmYOjQ0yo/dOhQ7rnnHiZMmEA6nWbEiBFHF1YCuOuuu7jpppt4/PHHmTRp0tHjTzzxBIsWLSI/P59+/fpx3333UVxczPjx4xk2bBhTpkxh/vz5rF+/nnHjxgFQVFTEokWLSKfTZ/SVnKwQYzwrNzoTo0aNikdWtZIkSZKkpFi/fj1Dhgx5+wZ1dfCrZfDj70HzIUgV5IJqKkA25oJrthkKCuHGv4QPT4LS0rPV/XOire8shLA6xjjqzW0dYZUkSZKk9tbYCEuXws9/Dnl5cOn7of4laGqAdBpCGmIGMhno1BuK3wNPL4cnl8E110BVFXTufK6f4pwzsEqSJElSe9qxAx56CF57LTdamnc4dl30Pji0Hxp2Qmsz5BVAUW8o7A4hBaVdobU1F3J/9zu4807o8zZb4bxLuOiSJEmSJLWXHTvgK1+B/fuhvPxPYRVyobRLD+gzGC4amvvs0iN3/Ii8vNx1+/fn6rSxwNG7iYFVkiRJktpDY2NuZLW5+cxHRvv0ydV56KFc3XcpA6skSZIktYelS3PTgNtrGm+fPrl6S5e2T73zkIFVkiRJks5UXV3u3dP2XuG3tDRXt66ufeueJwyskiRJknSmnnoq9/5pXjuva3uk5tNPn9Jlc+bM4YEHHjjl2+3du5cFCxac8nUAEydO5NJLL6WyspLKykp2tMP7twZWSZIkSToThw7lAmXfvh1Tv2/fXP1Dhzqm/hucTmCNMZLNZgH4wQ9+QE1NDTU1NfRph6nRBlZJkiRJOhN1dZDNQn5+x9TPz89td7N169s2eeyxx6ioqGD48OFMnz79mHMTJ05k1apVAOzatYvy8nIA1q1bx5gxY6isrKSiooLa2lpmzZrFpk2bqKys5O677wZg/vz5jB49moqKCu6//34ANm/ezJAhQ7jjjjsYOXIkW7Zs6YAHdx9WSZIkSTozRwJrR4oxd5+LL37LqXXr1jF37lxWrFhBSUkJ9fX1PPzwwycs+cgjjzBz5kxuueUWmpubyWQyzJs3j7Vr11JTUwNAdXU1tbW1rFy5khgjVVVVLF++nLKyMjZs2MCjjz56zIjsbbfdRjqd5sYbb+Tee+8lhHBGj21glSRJkqQzsXUrFBR07D0KCt524aVly5YxdepUSkpKACguLj6pkuPGjWPu3LnU1dVxww03MHjw4Le0qa6uprq6mhEjRgDQ0NBAbW0tZWVlDBw4kLFjxx5t+4Mf/ID+/ftz4MABbrzxRh5//HFuvfXWU33SYzglWJIkSZLORHMzpNMde49UKnefNsQYjzuSmZeXd/Qd08Y37Ok6bdo0li5dSmFhIZMnT2bZsmVt1p49e/bR91I3btzI7bffDkDXrl2Padu/f38AunXrxrRp01i5cuWpPWMbDKySJEmSdCYKCiCT6dh7ZLNvO4p75ZVXsnjxYnbv3g1AfX39MefLy8tZvXo1AEuWLDl6/MUXX2TQoEHMmDGDqqoq1qxZQ7du3Thw4MDRNpMnT2bhwoU0NDQAsHXr1jZX/21tbWXXrl0AtLS08LOf/Yxhw4adwQPnOCVYkiRJks5E//5vO/rZbpqb33aP16FDh3LPPfcwYcIE0uk0I0aMOLqwEsBdd93FTTfdxOOPP86kSZOOHn/iiSdYtGgR+fn59OvXj/vuu4/i4mLGjx/PsGHDmDJlCvPnz2f9+vWMGzcOgKKiIhYtWkT6TSPKTU1NTJ48mZaWFjKZDFdddRV/9Vd/dcaPHWKMZ1yko40aNSoeWdVKkiRJkpJi/fr1DMnLg3nzYMCAjrvRK6/AF7/Y5qJL55v169czZMiQY46FEFbHGEe9ua1TgiVJkiTpTJSW5t4xbWnpmPotLZCXlxvJfZcxsEqSJEnSmSgshAkTYPv2jqm/fXuufmFhx9RPMAOrJEmSJJ2piROhtTX3056O1JwwoX3rnicMrJIkSZJ0BmKMuWnB11zztnulnra6ulzdt1lw6XxzqmsoGVglSZIk6TR17tyZ3bt354JYVRX06wdtbPtyWnbsyNWrqmqfeudYjJHdu3fTuXPnk77GbW0kSZIk6TSVlpZSV1fHzp07AUhfdx29vvMdwp49ZIqLT7tuur6emJ/P7mnTyLz0Unt195zr3LkzpacwWmxglSRJkqTTlJ+fz3ve855jD15yCTz0ELz2Wm4qb94pxK7W1tw04IED4c476dWnT/t2+DxjYJUkSZKk9tSnD8yZA0uXws9/ngusfftCfv7bX9PSklsNuLU1985qVRWcwtTZdyoDqyRJkiS1t86d4aab4IMfhKefzv20tkKMUFCQ27c1m4XmZgghF2o//OHcasDvkAWW2oOBVZIkSZI6Smkp3HIL3HADbN2am+5bV5cLqgUFufOlpdC//7tyn9UTMbBKkiRJUkcrLISLL8796KS5rY0kSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUokA6skSZIkKZEMrJIkSZKkRDKwSpIkSZISycAqSZIkSUqkDg+sIYR0COG5EMLPDv9dHEL4ZQih9vBnz47ugyRJkiTp/HM2RlhnAuvf8Pcs4MkY42DgycN/S5IkSZJ0jA4NrCGEUuBa4LtvOHw98P3Dv38f+GhH9kGSJEmSdH7q6BHWbwJ/B2TfcKxvjHEbwOHPPh3cB0mSJEnSeajDAmsI4TpgR4xx9Wle/9chhFUhhFU7d+5s595JkiRJkpKuI0dYxwNVIYTNwA+BSSGERcD2EMKFAIc/d7R1cYzxOzHGUTHGUb179+7AbkqSJEmSkqjDAmuMcXaMsTTGWA58AlgWY/wLYCnw3w83++/ATzqqD5IkSZKk89e52Id1HvBnIYRa4M8O/y1JkiRJ0jHyzsZNYoxPAU8d/n03cOXZuK8kSZIk6fx1LkZYJUmSJEk6IQOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmRDKySJEmSpEQysEqSJEmSEsnAKkmSJElKJAOrJEmSJCmROiywhhA6hxBWhhB+H0JYF0L40uHjc0IIW0MINYd/rumoPkiSJEmSzl95HVi7CZgUY2wIIeQDvwkh/Pvhc9+IMT7QgfeWJEmSJJ3nOiywxhgj0HD4z/zDP7Gj7idJkiRJemfp0HdYQwjpEEINsAP4ZYzx/zt86vMhhDUhhIUhhJ4d2QdJkiRJ0vmpQwNrjDETY6wESoExIYRhwLeB9wKVwDbgwbauDSH8dQhhVQhh1c6dOzuym5IkSZKkBDorqwTHGPcCTwFXxxi3Hw6yWeCfgTFvc813YoyjYoyjevfufTa6KUmSJElKkI5cJbh3CKHH4d8LgauAF0IIF76h2ceAtR3VB0mSJEnS+asjVwm+EPh+CCFNLhgvjjH+LITweAihktwCTJuBz3RgHyRJkiRJ56mOXCV4DTCijePTO+qekiRJkqR3jrPyDqskSZIkSafKwCpJkiRJSiQDqyRJkiQpkQyskiRJkqREMrBKkiRJkhLJwCpJkiRJSiQDqyRJkiQpkQyskiRJkqREMrBKkiRJkhLJwCpJkiRJSiQDqyRJkiQpkQyskiRJkqREMrBKkiRJkhLJwCpJkiRJSiQDqyRJkiQpkQyskiRJkqREMrBKkiRJkhLJwCpJkiRJSiQDqyRJkiQpkQyskiRJkqREMrBK7yDZbPZcd0GSJElqNwZW6R0gm80SYySV8n/SkiRJeufwX7fSeSjGSEtLC//6r/8KQCqVIoTAhg0buP322/n+97/Pxo0bAUddJUmSdP4ysErnmZ07d5LNZnnttdf43Oc+xwsvvADAN77xDW655RauuOIKXn/9dT71qU8BOOoqSZKk85b/kpXOM2PHjuXRRx9lwIABTJs2jX/8x38E4JprruGZZ56hpKSEH/3oR/zmN7/hP//zP4HciKwkSZJ0vjGwSgkXY6S1tZVMJgPAnDlz+Id/+Aeuu+46iouLWb58Oa+99hqXXnopCxcu5KGHHmLx4sXMmzePe++992gNSZIk6XxjYJUSLJvNEkIgLy+PdDrNT3/6U8aOHUt9fT3Dhg3j2WefJS8vj4ceegiAl156ienTp9O7d2969uzJypUree6555wWLEmSpPNSOB9GXkaNGhVXrVp1rrshnRVHRlLT6TQAu3fv5rOf/Sxr1qwhm83SvXt3Bg0axObNm/nWt77F1VdfTVlZGatWrWLu3Lns2LGDAwcO0Lt3b/r27cttt91G7969CSGcy8eSJEmS3lYIYXWMcdSbjzvsIiVIJpMhnU6TTqd55ZVX+OMf/8i1117LkiVL+OQnP0n37t3p27cvo0aN4uWXXyaVSnHZZZeRSqX4p3/6J+bMmcMVV1zBRRddxL333svf//3f06dPH8OqJEmSzkuOsOod68CBA3zzm9+ke/fu3HDDDQwYMOBcd6lN3/3ud+nTpw9VVVUAPP3003zhC1/g+eef51Of+hTPPPMMmzZt4pe//CUbN27khz/8IQMHDqS5uZktW7bw+c9/nuuvv56JEyfy5JNPnuOnkSRJkk6dI6x6V4gxsm/fPr761a8ycuRIXnnlFYYMGcJLL710rrv2Fo2NjQCMGzeOSZMmEWPkq1/9Ktdeey0XXXQRU6ZM4dJLL2XUqFFcddVVzJ8/n9GjR3Pw4EEAysvLqa6u5vLLL+eHP/yhYVWSJEnvOHnnugNSe/mv//ovmpqamD17Nvn5+Tz11FP079//XHfrGOvXr+eZZ57h+uuvp6SkBIAXXniB2bNnc/PNN3Prrbfyi1/8gve+9700NTXRr18/du3aRc+ePVm4cCEXXHAB2WyWkpISCgsL+dWvfsXAgQMpKys7x08mSZIktT9HWHXeW7BgAQMGDGDChAnU1dXR0NBAc3Mzffv2pamp6eiWLtls9pz1cdGiRQwdOpSbbrqJTZs2UVNTww9+8AP69+/PF7/4RV577TX+5//8n6RSKf7mb/6G559/nlWrVvHxj3+cqVOnsm7dOrp27cqll17KyJEjmTlzJnfeeScTJkwA8B1VSZIkvSM5wqrz2oMPPsiXvvQlbrrpJr70pS/Rv39/nnnmGR5//HG2bdt2zHur52Jrl6eeeoovf/nLbNiwge7duzNixAiuuOIKWltb+cxnPsMll1zC7373OwB69OjB17/+dW677TZSqRSlpaWkUil+/OMfc9VVVzF9+nRCCHziE584688hSZIknQuOsOq883pL5PndGX6/I8PTz66mf//+fPe736V///40NTVxzz33kE6nWbhwIa2trRw6dIhMJkNzczPPPPNMh/fv1QMZ/s/vm7hn+SG+s3ofq9c8T99+F7FixQouv/xynnzySSoqKkilUvTr14+tW7cC8JGPfIQlS5YwaNAgSkpKWLp0KSNHjmTPnj18/OMf55Of/KRhVZIkSe8qjrDqvLG/KbJ4Qwv/8VIrOw5GWrNQlxnAjm2/pPKKK2mq30a3oiJ69uzJhRdeyGOPPcbtt99OaWkpAE888QTbt29n1KhRFBQUtHv/DjRn+fJvm3jm1SyZLKRDJPa7kobmDH/ck+Vb/3UAmptJpVJcdNFFfPSjH2XlypWsX7+e/v37s2DBAoqLi/n973/P4MGDufnmm/nmN79J3759272vkiRJ0vnAwKrzwp7GyL2/buS5HVm65EV6dAqkAnS/8U4Obn2BtTXLGXhpBSE0sXnzZvbs2UNDQwOf+9znGDx4MD/4wQ/Yv38/8+bN+//Zu/f4nOv/j+OPz+e6rp035rBhRpgzYWaOOZdikixCUQ4d6EBUopwyORT9hMQ3iUTIKSKJkfP5PMycZ2ZHO+86vX9/rK0WMsVmvO63mxvXZ5/r835/ru1yu557vQ/3JKymmO28uTGD0/GKEi4Ko64DWfNKazz3HmfXf82cbxehn/yN9/p2BWDcuHE0bNiQkSNHcv78eX766aecVYBHjx591/sohBBCCCFEYSP7sIr7nlKKUdsz+e2ilRJOGgb9xgWG0q12EpPSebdZUYpH7WDAgAH4+vqye/duANq1a8fixYvvWR8/3ZPBj6dtlHK9cQEkm9XC6q7FcCzqRdnunzBtSE/aVzSRmppKUFAQVquVevXqUb16dV5//fV71kchhBBCCCHuV7fah1UqrOK+dzlZsTvKhruJm4ZVAEfsOLs4szzcSsKXk0lPT+enn35i7969NGnS5J72L9VsZ/15G0WdFJp247Rwg9FEta7DiNqzhqT9q5mxujLxJc7x5Zdf4ufnR48ePWjXrt097aMQQgghhBCFkQRWcd/betlKihm8XW8eVu12O1cP/EL4qv9jS/h+inkWYeIn4zGZTDRu3Pie92/3VTtpFvB2ufXWMlWeHcKZNTMoFRjEniX/R7p7CmPHjqVNmzb3vH9CCCGEEEIUVhJYxX3vSorCoCtutai1rusUrfAoLiV8KNayH/NHvEDjMlk/2vmxP2lCurptWwYHJ8q37IFnpXoUffwtpnYsQR0vwz3vmxBCCCGEEIWZBFZx33Mxwu2mWruU9CVg0FyupYFjPm/W5JDHd1HtPpNA04hOAyd55wkhhBBCCHFbsg+ruO81LmNA0zSs9n9OrakWRTFnjfJF8rdyWaekjq6BzW7/x/M0XSfNqvBwhPIe977yK4QQQgghRGEngVXc92qVNFDBQ+d6pgJuHlrtSpFqheZlDRR3zt8wWM7DQN2SOvGZ/9yuUooks0ZQRQNORnnrCSGEEEIIcTvyqVnc9xwMGoMCTLiYNOLS1d8qrQqzTRGbrqhYROelWqYC6eNAfweMOiRl3jxQK6WITQdvF+hW/e7vAyuEEEIIIcSDSAKrKBTqeRsJaeZIWXedhEyITbcTl24nJk2RZgF/LwMTmztS0qVgfqSrFzcw8TFHdA2upiqSzXas9qxwnZCpuJoGXq7weWsnSjrL204IIYQQQoi80NTtVrO5DwQEBKh9+/YVdDfEfSDDqjh8zUroJTtpVkVJZ43Hyxvx89RvuUdrfopLt/NThJVVZywkZIAGlHHTeK6qkcfLG3F1kLAqhBBCCCHE32matl8pFXDDcQmsQtx9SikybKBr4KDnz/Y6QgghhBBCFFa3CqyyuYYQd8hms2Ew/PNKxJqm4SzvLiGEEEIIIf4TGZ8oRB5ER0fn/Ds7rM6ePZvQ0FDst9nORgghhBBCCPHvSGAV4h9YLBaWLl3Kzz//nHNs48aNNG7cmPXr1+Pp6YnFYinAHgohhBBCCPHgkkGLQtyC3W7HZDIRFBSEyWTi7NmzVKxYkb1799KjRw/efPPNgu6iEEIIIYQQDzSpsArxF39dhEzXdaKjo4mPj+ezzz5j8uTJAPz666/UrFkTgJSUlBueJ4QQQgghhLg7JLCKh158fDxbtmwBcq/ma7FY6NixIzExMTRt2pTMzEwuXbpE8+bNmT17NgBubm4AXL58Of87LoQQQgghxANOAqt4aIWFhbFgwQK2bdtGTEwMADt27GD//v1YrVZMJhPVq1dn165dBAYG4uvry6JFi3j//fcJCwvjk08+4auvvqJBgwb8/PPP2Gy2Ar4jIYQQQgghHiwSWMVD5+jRowQFBdG9e3fCwsJwdXWldOnS7Nu3jwsXLvDpp5/y3XffAVCzZk1cXFxwcHAgICCA8PBwYmNjWblyJa6uruzYsYPx48fz6quv3narGyGEEEIIIcSdkUWXxEPnf//7H02aNGH48OE5x+bNm8eMGTPYu3cvfn5+9OnThyZNmhAdHY3JZAKgevXqbNy4kW+//ZYPP/yQt956q6BuQQghhBBCiIeCVhgWiwkICFD79u0r6G6IQiohQxGeYCfdorhw8hD/N2Igv2/ZjIuLCzabDYPBQEpKCkFBQQwaNIhnnnmGTz/9lKioKJKSkoiLi2P58uUAHDhwgPLly1O8ePECvishhBBCCCEeHJqm7VdKBfz9uAwJFg+s65mKb49ZGLMjk4UnLKw4YyE0vihXM4zM2pNAXLpC17PeAm5ubrzwwgvMnDkTgMGDB/PYY4+xfPlynJycSEtLA8Df31/CqhBCCCGEEPlEAqt4ICVmKqbtz+RIjI3SruDroVHWXce3qAPlq9Zm06ZNfL4/k2spVux2OwBt2rQhMTGRTZs2YTAYeOaZZ1i9ejXz5s3DxcWlgO9ICCGEEEKIh48EVvFAWhxm4boZSrtpGPQ/t6pxK+ZFMZ9HiD22hdTUNBaetKNpGjExMZw9e5bOnTuzdOnSnPObNm2Kg4NDQdyCEEIIIYQQDz1ZdEk8cKJT7YTF2SnrfuPXNE2jXrturP9yFL9N7k/Nru/xxZFwFn89k4CAACZNmoSTk1P+d1oIIYQQQghxAwms4oFzLNaOrmWF05spUrIMTw+ezLYfZnDghymctiUz8eOPadOmTT73VAghhBBCCPFPJLCKB05ipsJ0my1Rnd2L8ni/EVyNS6ZWWQ/a1JJhv0IIIYQQQtxvZA6reOA4GcBqz9t2TbqzG07Gm1dihRBCCCGEEAVLAqt44FQtZsBmz1sINdugdgl5GwghhBBCCHE/kk/q4oFTsaiGl4vG9czcVdaM1GTsNhsASilSLQo3E1QtJm8DIYQQQggh7kfySV08cHRNo3t1EylmSDZnhdbocyc5sG4RusFAWlIC6VaIz4Ae1U0YdRkSLIQQQgghxP1IAqt4IFUsqvPqowYsNsWlZDumUlXZvXoeX77Rkc9eaMT5U8foX9tIjRK3WZ1J/Ce2PyraQgghhBBC/BuySrB44NhsNgwGA9VKmBjd1MjhK2nsupxJ0RKlSI69wqK1obR+tLwstnQPKaXQNA2DIesXAna7HV3Xc44LIYQQQgiRF1JhFQ+c7JC0fft2gp5qx/xJw+jkk8LudT9Qo7w3RdIj0e2WAu7lg0mprCHY2aH0p59+omvXrkyePJmYmBgJq0IIIYQQ4o5IYBWFmlLqhmGnUVFRdO7cmcWLF/Pqq69is9n4/PPPMRgMtGnThoULF6Lr8qN/N2V/D7IDqdVqZeTIkXzzzTcMHjyYs2fPMM9TXwAAIABJREFU8tlnnxEVFQX8GWyFEEIIIYT4J/KpXRRqfx12eujQIQCKFSvGkSNHcHd3p0uXLvTp0weDwcCaNWvo06cPJ06cYO3atYwYMYKwsLCC7H6hdvr0aSArfGZ/D7788kumTp2Kruv06tWL+fPnc/jwYTZs2MDRo0fZsGEDgFRahRBCCCFEnkhgFYWK3W7HbrfnPLbZbEybNo1q1aoxefJkxo0bR3JyMiNHjmTLli0A+Pv788gjj7B3715cXFz44IMPWLJkCeHh4RQvXrygbuVf27VrV0F3gUOHDjFr1iwgK3weP36c1q1bs3nzZpo0aYLdbqdSpUrMmTOHw4cPs3XrVgICAti7dy8xMTEF3HshhBBCCFFYSGAVhYZSCl3X0XWdtLQ0AMLDwzl79iwnT55k4MCBzJw5k7Vr19KxY0fsdjsbNmxA13Xq1KnDtWvXWLduHe3atWPevHksWbIELy+vAr6rO7N7924+/PBDIiIiCqT9mjVrcujQIerWrcv48ePZs2cPkBVgK1SowJIlS2jYsCFGoxFN01i0aBFBQUH4+vqSmJjI4cOHc36RIIQQQgghxO1IYBX3texqavbqsuHh4bz00kt0796d+Ph4YmNjOXnyJJ07d2bo0KF8+OGH9O7dm2LFitGzZ08mTpwIQGBgIG+88QadOnUCwGQyFdg93YnsCvKmTZuArNehUqVKOYE9P9jtdqxWKwCtWrVi7NixAPzyyy8EBwcDcPnyZapUqYLZbMZsNuec36NHD8aOHUvnzp05f/48Y8aMoXPnzvnWdyGEEEIIUbjJtjbivpS9DUr24kiappGUlMSAAQNo1aoVAwcOpEiRImRkZGA2m3niiSd45513AEhNTSUhIYHg4GA2bNhATEwMJUuWJCAgoCBv6Y5YLBZMJhPh4eHMmjULPz8/AgMDqVevHkOHDiU9PR3gnm4T89fvQfb3Yfz48ZQtW5bIyEg6derEjBkzWLt2LTVr1mTVqlVcunSJSpUqAXDw4EEGDRqEr68vKSkp9O7d+570UwghhBBCPLikwiruS9kBad26dXz00Udcu3aNzZs34+Pjw/DhwylSpAgA9erVw9/fn/DwcGJiYli4cCHNmzdn165dlCpVitWrV1OyZMmCvJU7cu7cOebPn8/rr78OQNWqValUqRJFixZlyZIl2Gw2AgICmDdvHnD3V9sNCwvjm2++ITY2Nud7sGbNGqZOncrp06fx8PDgueeeY8SIEQD07NmTzz//nKCgINzd3Rk6dCifffYZjRo1YtGiRaSmptKlSxcJq0IIIYQQ4l+RwCoKXExMDEFBQezfvz9nCHB8fDx9+vRh/Pjx1KxZEy8vL7y9vdm+fTvwZ1ArXrw4b731FqVKlaJv374sWLCASZMm5QxVLSx+//13unbtSnBwMK6urvz+++98//33aJpG27ZtMRgMeHh48NFHH/H8888TGRmJ2Wy+a9vzHD16lKCgILp37054eDiHDh3i3Llz9O3blzlz5gDw3nvvcfDgQUJCQli+fDmpqam8+OKLZGRk8OuvvzJlyhR69+5NdHQ0Y8eOZdKkSbi6ut6V/gkhhBBCiIeTBFZR4C5cuMDvv//O5MmT+frrr3OOXbx4kd9//53nn38egEaNGlGqVCm++OILNE0jOTmZuXPnUqpUKUaNGsW3337L+vXradOmTUHezh3btGkTH3zwAU899RSbN2+mS5cujBo1itmzZ3Pw4EGaNWuGt7c37du35/Tp06xZs4bq1atz9uzZf91msllxMs7GkRgbp+PtfDl7Dk2aNOHQoUOMHz+etm3bopTCy8uLVatWoes6Bw4c4OzZs5QqVYqWLVvy8ccfo+s6HTp0ICQkBIBnnnmGSZMm8cQTT9ytl0cIIYQQQjzEZA6rKHAmk4lKlSoxZMgQgoODadKkCbGxsVSsWJHIyEhKly6NzWbDZDIxZswYJkyYwLZt2zh16hRNmzale/fuAHh6ehbwndyeXSnOXVdsj7RxKSmrmhweGkZZvxr0fukldE3DZrPRo0cPTp48yaJFi/D29qZ8+fI4Ojry9ttvM3bsWK5cucKAAQPuuP0rKXZCL9rYF20DFKARffoQmzbuZOrijcSlK4o62DEYDJw7d45ffvmFlStX0r59e3bu3ImPjw8AISEh1KlThwkTJjB48GB69ep1F18lIYQQQgghskhgFfnqeqbiQLSNIzF2LHZFeQ+dRhVqo5TKqZSuWLGCqKgofHx8OHbsGD4+Pui6ztGjR2nRogXNmzdn3bp1NGnSpFDto5qQofjmqJmLyQoHA7ibAA2SnUtx4OQaOgwYSynrFYoXccfT05P69esTGxvLp59+SuPGjenfvz9t27YlMjKSQYMGER0dTbly5fLc/vFYG18ftWDQwMsFjH8MJ3bxKYmjowOhZ5M4fN2RVx818kjRrF8AVK9ena5du+asrvzrr7/i7u5Oo0aNmDlzJhkZGTg6OlKmTJl78ZIJIYQQQoiHnHa3F225FwICAtS+ffsKuhviPzp8zcqCE1asdvBwAF2DFDMkxkRxdd0X/G/iB8TFXOOVV14hMjKSHj16sGvXLp577jnWr1+P0WhkwoQJVK5cuaBv5Y4lmxWf788kKRO8XXOv6mu1mNm1fA6HNq+hQr2m1PU0kxATTUJCAnPmzKFbt25s2bKFVatW0bFjRzIyMjCZTBgMhjy3fyHJzuf7zHg6gYspd/vJcdH8+vV4KtZrRoXmwZjNVt5r7EpxZ42RI0eyYcMGunfvztatWwkPD+fTTz+VIb9CCCGEEOKu0jRtv1Lqhm09pMIq8sXZRDtzj1op4QLOxj8Dk5sDFHcsydq9O3msbXv0zCR69epFWloaERERVK1alZSUFNq1a/evhsDeLzactxKfAT5uN25BYzQ50KzbQJp1G8ilBDONyjnR2CWKQYMGATB8+HBcXV1zhjw7OTndcftrIqw4GW8MqwBuxbwoVuYRzuwLpcZjHUjVnNlyyUo7HzMVK1bko48+4uDBg7Rr144ff/zxjtsWQgghhBDi35IKq8gXMw6auZxsp7jzzfcMXTF5MFEXz3Foy894OGpYLBZWrlxJpUqV8Pf3z+fe3l1pFsXIbZkUdwGTfus9U+12O3Y0YtKg5L4ZHD6wj0WLFv3n9q+l2QnZaaasO7fcs/V6zBXWfzkKc3oazXu9y9nTYcRvmkNAfX+mTJmCyWT6z/0QQgghhBDiVqTCKgpMfIYiPMGOj9utzynqXRajVyWOx9kI9NYwmUw899xz+dfJeygi0Y5N/XNYVUoRc/4UhzYu5XDoWmpWKsfEsR/mfO1WQTMvziTYQbt1WAUoUrIMTw+ezLYfZrBt4RQSr1/no/dH0aezDP0VQgghhBAFRwKruOdSzQr9NoHJ0cUdu+5CfLodg8EhH3t372XYbn+Opml4eJXBo0Rp2g6dxdsdGxBYxpDztf8i1aLQ/1gR+J84uxfl8X4jyExLIdbmin8tqaoKIYQQQoiCJYFV3HOORlDqnyuFjbv0JzIF3B0evK2B83pLzm5FaPxsfy4lK0x5X0/p9tc1athV3kOvo4sbJCuMD963QgghhBBCFDLykVTccyWdNbxdNZLNtz4neyZ1teIP3o9kOY+s+qbNfvv54nal0IDyHnfvdfD10NG0rF8Y3LRNuz3X4+x+lnV/8L4XQgghhBCicJFPpOKe0zSNJysYiM8A601Cm1KKqynwaEkdL5cH70fS00mjbkmd2PTbnxubDrVK6LdcnOrfKOeuUfomvzDIDqq6/udrrpQiLgPqeukUdbx7fRBCCCGEEOLfePDSgbgv1SlpIKiSgSspcC1NYbMrlFIkZSouJSvKFdF4vtqDO2fyqYpGdA2uZ/4Z2P9e2UzKVCgFT5a/u0FR0zTaVzSQkAEWm8ppOzuonju0ne+Gv0BKQgwZNjDboHU5mS0ghBBCCCEKngRWkS80TaPdI0YG1XegVgkD19LgSiq4O2j0rmliQF2Hm+4R+qDwdtUZWM+BtOvx/LLkW1LMf87nTbUoLicrbHYYWM+BskWygvvPP//MmTNn7kr7tUoYeLqSxpUUSP6j7aTYKDZ+/Qmb53+Gf/ueWJxLEJOm6F3TiO9dHJIshBBCCCHEvyVlFJFvNE2jYlGNikV1VA1jzrGHgd1up5yHztgnSlN7yDT0tDiuXrnIIw2fol6ztgRXcaCulwE3B43ffvuNIUOGULlyZapUqYKnpydDhw79T+0rpXi8giPerha+3niUsPhk9swPITUuCqs5E/c67SjupOhT25FKRSWsCiGEEEKI+4MEVlEgHpagmi17+O350yeo4fcIG78ew+z/fU23bh1wNBmwWCxYrRnY7Y7s3r2b1atX4+npSXBwMA4ODvTq1QsvL688t6eUylmVWdM0rFYrISEhLF26lHLlynHw8BHeGjeDyEsX+XrCMFqr/Twd0PRe3b4QQgghhBD/ipRShLjLlFI3zE/dsGEDI0aMYPDgwQwbNowiRYrQuGEgCXExTJ8+nVatWrFp0yZ0XWfTpk1069aNdu3a0aRJE5YsWZLnsKqUIjk5mfj4eHRdJykpCYDFixezbNkyWrVqxYABA3B2dODyvg0c2bgUXYPJo4ahadoN/RZCCCGEEKIgSYVViLsoezGjv1aQExMT6du3Lx07dmTDhg0ADBgwgGeeeQaAV155BZvNxuzZs2natCktWrRg9+7drFmzJucaoaGhBAQE4Obm9o/tZ2RksGPHDo4cOYKPjw9Tp07lscceIywsjJdeeomIiAgmTJhAYGAgCxYs4MKFC3z//fe88847HD9+nJo1a96DV0UIIYQQQoh/RyqsQvxHf93fVNd10tLSGDlyJO+++y4bNmygaNGivPzyyxw+fJjk5GQARowYQXh4ON27d6dv375MmjSJmJgYTp06Rdu2bUlOTmbevHmsXr2aFi1asGjRIqxW603bt9vtOZVRZ2dnvv76az788EMGDBhAbGwskZGRaJrG5cuXsdvthIaGUq9ePQwGA+vXr6dcuXLYbDa++eabe/9iCSGEEEIIcQcksArxL9nt9px5otmSkpJ49dVXuXbtGjVq1GD48OGsWLGCRx55hCNHjvDiiy/y7bffYjQaqV27NgsWLKB+/frExcVRvXp1Zs2aRePGjRk1ahRnz55l+vTpDBo0iK+++oqiRYvmaju7fV3XOXXqFIcOHSIjI4MTJ07g4+ND//79mTZtGmlpaVStWpWLFy+SkpJCamoqZ86coWjRogwdOpRly5axePFiRowYURAvoxBCCCGEELckQ4KF+JeyF1IKCwtj2bJldOvWDScnJ44ePcqhQ4cAuHz5Mj/++CMxMTH06NGDq1evMmHCBBo0aEC/fv3YunUro0ePpmrVqly/fp0xY8Zw5swZWrduTatWrXKF4b/unZr9N8Dp06dp3749uq7z/vvv4+zsTK9evTh//jzFihWjdOnSJCcnU7p0aaKjo2nYsCGPPvoo8+bN4+TJk/Tp0wdHR0eZvyqEEEIIIe472l+HM96vAgIC1L59+wq6G+IhZ7PZMBgMOY/tdjujRo3i559/pmzZsgQHB9OgQQOmTJlCYGAgq1evxsfHh1OnTjF9+nR++OEHxo8fT0BAAN7e3vz4448MHDiQjIwMSpQowbVr1wgLC+PFF1/krbfeygmoVqsVTdNQSmE0Zv2OKTIykmHDhuHm5oaDgwNRUVE4ODhw+vRpatWqhdVqpVixYvj5+bF7926ioqKoUqUKxYsXp0ePHlSvXj3Xffw1AAshhBBCCJHfNE3br5QK+PvxPFVYNU179iaHrwNHlVLX/mvnhLhfpaSk5Cx0lB1WDxw4gJ+fH0uXLmXt2rUsWrQILy8vihQpQlRUFFFRUXz88ccMGDCA999/n5YtW3Ls2DGOHTvG2rVrqV+/Pv7+/hw/fpxZs2YxZ84cEhMTmThxIp9//jmOjo4AbN++HU9PT3x9fSlSpAjJyclEREQQGxuLr68vrq6unDhxArPZzJQpU1i4cCGNGzcmNDSU9PR0AgICWL9+PR4eHjg4OODh4UG3bt2oXr16zrY3uq5LWBVCCCGEEPetvH5S7Qv8D+j5x585wDvAdk3TXrxHfROiwOzYsYMePXowY8YMLBYLACtWrKB+/fp88sknxMXFMWrUKI4ePUp8fDxOTk689dZbrF27lvfee4/MzEyWLVtGjRo18Pf358iRI1SvXp0nnniCnTt34u7uzqRJkwDo168fjRo1omfPnixcuJDz589TpUoVnn/+eZ5++mm2bt3K1KlT8fPzo23btnTv3p05c+ZgMBhwdnYGoEiRIri4uHD16lUcHR0ZNGgQ9erVo0qVKri5ueHi4kLfvn2pVasWkLUPrgRVIYQQQghxv8vrJ1Y7UF0p1UUp1QWoAWQCDYH371XnhMhvoaGhtGnThpEjR9KoUSPef/99TCYTJ0+e5KOPPmLChAksXboUb29vevXqhZOTE+PGjcPZ2Zm6deuya9cuqlevzquvvkqlSpWYPHkyU6ZMoXnz5ly8eJEGDRowc+ZM5syZwzfffENUip2T8XaWb9hK08eDePHFF9myZQvu7u6EhIRw8OBBGjZsyNq1a3njjTfYtm0bzZs3Z+vWrWzZsoUqVapgt9tZsWIFXl5enD17ljp16jB37lzefPNNBg0ahMFgwNPTk2LFihX0yyuEEEIIIcQdyeuiS48opaL/8vgaUEUpFa9pmuUe9EuIfGO2Kc4m2km1QFh0KmcizhIecZawOBtfHjJz9tw50uOvcfz4cQYPGUq/Pi+TkpLCnj17ePvtt/nqq68YOnQoiYmJrF69mrp16/Lyyy8zcuTInOG9TzzxBHXr1mX37t0EBQVxJMbGF4dtnE8wY9V04hoM5mhsDMfm96FuQEtK2GLp3bs3mqaxd+9eihYtyrJly9i/fz+nTp1C13UWL15McnIya9euZdKkSQQGBjJp0iRatGhBVFQUZ8+e5bfffmPIkCE8+eSTBfwqCyGEEEIIcefyGlh/1zRtDbD0j8fBwFZN01yBxHvSMyHuMatdsfmilU0XbaRnb3FaojWxqWaCv79E2vHfOLZ8GjWad6T5y8Px8C7P5fhUfvxtFwGVy/D7778TEBBA37592bhxI0FBQbz77rtERERQvnx5SpQowebNm6lfvz6enp54eXnRvkMQS09Z2XrRgruTRpJF43KKHQ0wuniQnnydU5aSHDh6gGfeGENJSxTmjHSuXLmCr68vSUlJhIWF4efnh67rZGZmsnjxYkaPHs0HH3xAs2bNAPDx8cHHx4eQkJACe32FEEIIIYT4r/K0SrCWtbfGs0AzQAO2AT+qfFpiWFYJFneb1a5YcNzCwWs2vF00HI1Z28ckZipWLl3M8S/6UK5Nb9p0ep4aDVsCEL5nExv+F0LdniM4teQTPE02goODady4MePGjWPatGlkZmYyevRo+vXrR5UqVUhPT6datWo57a6JsPDLOSs+7nA0RhGdpnA3Zc0ptaQnE7ZwDG5lq5KWYSbhwM/4N2pG7aJmNm38lUuXLqFpGj179uTgwYM4OjpSpkwZvvjii5yFoWTFXyGEEEIIURj9p1WClVJK07TtgJWs+ax7bxdWNU1zArYCjn+0s0wpNUrTtGLAD8AjwHmgq1Iq4Q7uRYj/bEekjQPRNsp5aDl7nSqlOBpjx7fJs5ya8xbVXplOquOf+6BWrN+C6A96sHfuCBKuXuGSNZ3nn3+ewMBAatSowfTp05kyZQq9evWiVq1alC5dOleb1zMVv12w4eOucS1NcTVV4eFATvsmZ3dcS1ci+WIYVZ//gMynXqecm50najpToXw5li5dSnR0NL/88gvOzs688MIL9OvXL1cbElaFEEIIIcSDJK/b2vQDRgKbyKqwfqFp2lil1Nx/eFom0FoplaJpmgnYpmnaOrIqtb8ppSZomjYMGIYs3CTykc2u2HjBSkmXP8MqQGImpFoUHo5Gqj73PheWjMH23ChSzIozoUvJSE3i8f4fErFvCz2/3EHstu+pWNEbXdfp0KEDx44dw26306FDh5u2u/+qDQCDBueuK5wM5GofwKdJZ07+8AnH5g6j/PMfk2TRGf7OJFLDtlC7dm3WrVuXszKwEEIIIYQQD7q8zmF9F6inlIoD0DStOLADuGVg/aMCm/LHQ9MffxTQCWj5x/FvgVAksIp8dDlFkWwGH/fcYTE61Z6zbHalDq+zrq8fuHvz1e5lFC9RkrZ9P6B05Uf57ZuJeGjpmBv3oE3zrEWVWrRoQYsWLXKupZS6IYzuj7ZRxBHSrZBszhoK/HdOnqWo8cJoDs9+h9P/e5Pdp/diNBgIDPBn6NChODs759pDVQghhBBCiAdZXgPrZSD5L4+TgUu3e5KmaQZgP+AHzFBK7dY0zVspFQWglIrSNM3rDvssxH+SblFomiJrsMCfzDbQ/zhkcHCiwhN9iD+yiaZv/B9NA+rknNekyytsW/wF1YLfI9MGjgaVa1ixpmk3hFWANCsY9T/budk5AA5unjR45xsSL50i6vAW/Bs0YkRwA6p5Zp1/q+sLIYQQQgjxoMlrYI0EdmuatuqPx08DezRNewdAKTXlZk9SStmAupqmFQVWaJpWK68d0zTtFeAVgHLlyuX1aULclqNRQ6kbA59JB/tfZmbXeGEMKRYo5Zm7ktm273A0XScyBRz+Nqz3n4KkkwEybGDQIS/Llbn7VMG5TBVKFAGTJvNThRBCCCHEwyevn4AjgJVkLbhkB1YBVwD3P/78I6VUIllDf58EojVNKw3wx9/XbvGc2UqpAKVUQMmSJfPYTSFur6ybhosJMqy5U2NJVx37Xx5rWlawLOmcO4TqBgMJGVC5qIazMe+VzjpeOtczwcUILiYNs+2fU2u6DUo4azibDJQrImFVCCGEEEI8fPL6KfhnoC7QGXiOrH1Yg5VSY5RSY272BE3TSv5RWUXTNGegLXASWA30/uO03mSFXyHyjcmg0bKcgWtpWUN4sxVzAifDn0EyzQJFnDQ8HHKHUqUUKRZoVT6vAxSyNChlxK6yJnJXKKKRbs3dfm4Kux0cDRrNyhpwNMgQYCGEEEII8fDJ6yfu74ChwDHIVYT6J6WBb/+Yx6oDS5RSazRN2wks0TStL3CRrAAsRL5qUdbI6TjF6UQ7pV0VRl1D1zRqltDYf1WRbrXjaNB4tKSea6qrUorLyVDXS6eq551VPYs7azQpY2BbpI0yrnDFWSMhQ+Fm+vsCTYrrmQpXk84jHjqtyt1ZMBZCCCGEEOJBkddPwjFKqZ/u5MJKqSNAvZscjwPa3Mm1hLjbHAwafR81sSbCys4rNqz2rIWYlNIo46YRl6Hh666hFFjsCruCxAww26Get0736iYM+p1XPTtXNpJiURyMtlGlmMbZRLiWptA1hYOeteXOdTO4O2g0L2ugXx0HXE1SXRVCCCGEEA8n7dZDEv9ykqa1AboDv5G1vyoASqnl965rfwoICFD79u3Lj6bEQyjVojgVbyc5U+Fo1KhQRMPNQeNQtI3fL9tIzFSYdKhRwkBTHwO+7v9tlV6rXbHrio2NF6wkZCjSrBCTpkgxKxwMUL+UgRdqmKjiqctqwEIIIYQQ4qGgadp+pVTA34/ntcL6MlCNrL1Us4cEKyBfAqsQ95KrScPf23DD8aZljTQte/eH4xp1jWZljTQuY+DcdUVipkIBRRw0KhbVMP6Lyu3dZDabcXBwKNA+CCGEEEIIAXkPrHWUUrXvaU+EeMgYdA0/z/ungmq1WjEajTlh9fLly5QtW7aAeyWEEEIIIR5meV01ZpemaTXuaU+EEAXKaMz6/VX//v1xcnKiUaNGzJ49u4B7JYQQQgghHmZ5DazNgEOapp3SNO2IpmlHNU07ci87JoS4d6xWK1arNdexRYsWERAQwIYNG9iyZQv169dnyJAhN5wnhBBCCCFEfslrYH0SqAw8AXQEgv74WwhRCBmNRoxGI0eOHGHmzJkAVKxYkaioKEwmEw0bNmTVqlUopQgJCSng3gohhBBCiIdVngKrUurCzf7c684JIe4Os9mc63FSUhKNGzcmMDCQiRMn4unpSfny5WnXrh3Fixdn3bp1ADzxxBPMmTMHuz2v2y8LIYQQQghx9+S1wiqEKISyh/P+fdXfS5cucfHiRbZt28aFCxdwc3Oja9eu9OnTh/T0dNasWQPA/PnziYqKYsGCBfnedyGEEEIIISSwCvGAOX78OF999RXw50JK48aNo3jx4jzzzDOsWrWK7du3o2kaVapUAbLmr+7cuZO6detSuXJlduzYQWhoKG5ubqxatYrevXsX2P0IIYQQQoiHlwRWIR4gZrOZd999l+nTpxMWFgZAv379mDVrFlOnTsXBwYGuXbvSqlUrYmNjOXr0KADNmjXDzc2NrVu30q5dO/z8/ChdujQAQUFBBXY/QgghhBDi4SaBVYhC7rPPPqN169bs3r0bBwcH2rdvj4ODA3PnzgUgIiKCESNGsGLFCn7++WcqVKhA5cqVqVWrFi+99BIjRoygZcuWODs70759e1555RWWLl1K1apVC/jOhBBCCCHEw04CqxCFjNlqZ/05C+N2ZvDR7xlsPZvM5s2b6dmzJ7/88guvvfYa3t7e7NixA8gKrAMHDiQ1NZX169dz8uRJANavX09wcDBz584lPj6exYsXF+RtCSGEEEIIcQNNKVXQfbitgIAAtW/fvoLuhhAFbnW4mRmHLCSZQUeha2CxKXb3LkqpagGQeJl3hw7BZDIxd+5c3njjDeLj4xkxYkTOSsE//vgjo0aNYt68eQQEBJCSkoKbm1sB35kQQgghhHiYaZq2XykVcMNxCaxCFA5LTmYyZb+FIiZwdcg9OOLgrLeJObWPmh36EPXTp3iVLEn58uVJSEhg06ZNVK1aFYvFQnJyMikpKXTs2JHvv/8eXdfRdRloIYQQQgghCtatAquxIDojhLjmvcEHAAAgAElEQVQzUSl2vjhopZgjOBlvDJi1+0zkp24lsD4aTPdmTfjqtTacOXMGBwcHVq1axalTp1i1ahV79uwhJCSkAO5ACCGEEEKIOyelFSEKgRXhFmz2m4dVAKODE97+TxAxuSP79Wp8/c23VK1alZiYGNatWwdAp06dJKwKIYQQQohCRQKrEIXAxgs23Ez/PHw/YPBcrp85QLoFSgd2YPfu3SxevJhZs2b9qzaVUthstpx/CyGEEEIIkd8ksApRCKRaFKbbvFsd3IpS5JFaXFg2liRzVsDs1q3bv25T0zQMBgPp6ek5CzYJIYQQQgiRn2QOqxCFgItJI9WscLzNeS0nbyMm04CHg3bHbSil0LQ/n5eQkMCYMWPYunUrnTt3plKlSvTo0eOOryuEEEIIIcS/JRVWIQqBNuUMpFhuH0LN6DibwN/7zt/a2WHVYrEAsHz5cvz8/AgNDUXXdcaPH098fPwdX1cIIYQQQoh/SwKrEIVAlyomDDpkWO23PEcpO3EZGkEVjbdcnOnWz1VkZmYyY8YMli1bBmQF1oyMDPr378/GjRsJCQmhWLFi/+k+smXPjRVCCCGEEOKfSGAVohAo7abzZj0j8ZmQar4xtNrsdq6mafgV1en3qOkfr/X3sHjw4EEsFguOjo5ER0dz5MgR4uPjqVevHlOmTGHIkCFs3ryZTp06ER4ejtVq/c/3YzAYAO7KtYQQQgghxINLAqsQhUTXao4MD3RAaRpRqYroVDsxaXaiUhWx6RpNyhiY2dYRN4ebv62zg2p2WExKSiItLY1Ro0YxZ84cAJ599lni4uLYunUrTz/9NGXLlqV06dJYrVY+++wzJk6cyJUrV+6473Z77pC9cOFCGjZsyOjRo1m5cuVNzxFCCCGEEEICqxCFyNOVHVjT2ZlRTRx4qqKRVuWMvFTTyOKOznzWyokiTrnf0sePH8+pYmYH1d9++41nn32Wbt264eLiQnBwMFu2bAGgbt26lC5dmr1791KvXj2effZZhg0bRv369dm/fz9vvvkm5cqVy3N/s7fD0XUdm81GREQEP/zwAytWrODbb78lICCAN998M+ccIYQQQggh/kpWCRaikHEw6jxZQefJCv889Pfw4cPs2rULX19fPDw8OH/+PB07dqR58+ZUq1aN6dOnc/nyZZ566inWr1/PkiVL6Nq1K7Vr1+aDDz6gefPmDBs2jLS0NBISEvDx8clT/5RSKKXQdR1N0zCbzaxbt45p06bRvn17+vTpQ4cOHZg0aRK//voraWlphISEMGLECGw2W06wFkIIIYQQQgKrEA+QK1eukJaWhp+fH3Xq1KF27dqEhobSunVrTp8+Tdu2bZk6dSoAUVFRDB8+nPnz59OyZUsmTpxIrVq12L17N/7+/ri6uqKUwtnZGRcXl5whu7eqhGZXUzVNQ9M0kpKS8PDwYNKkSaxbt47Ro0fz+OOPAzB37lxOnz7Nzp07WbNmDf3792fEiBESVoUQQgghRC4SWIV4QFgsFk6ePMnOnTt5+umnuXz5MhkZGSxatIjixYtz9epVTp48mXP+hx9+SL169UhMTOSVV14hPDycAQMG8PTTT/PJJ59gNOb+7+F2Q3azt8U5ffo0+/bt46uvvmLatGk8/fTThIaGEhsbC0BqaiqnT5+mSZMmAMTExBAdHc2yZcsIDg6+my+JEEIIIYQo5GTSmBCF2F9X/DWZTFy9epWpU6cSFBSE3W6nQYMG1K1bl7Vr19K9e3d27drFmTNncp7r4eHBJ598AsCYMWMIDQ3lnXfewWg03nYRpJttTTNu3Dg6depEWFgYKSkpLFmyhEcffZRGjRoRGRlJamoqrq6u+Pr6cuTIEWrXrs2hQ4fYuHGjhFUhhBBCCHEDqbAKUYhlD6FdvXo1qamp+Pv706hRI2rWrEmHDh0AqFOnDsuWLSMhIYH333+fYcOGUaVKFSIjIxk8eDATJ05k/PjxuLi4AOTMI71dRTW77ejoaLy9vUlISGDbtm3s2bMHd3d3AgMD+eqrr4iIiKBNmzasWrWK/fv307x5c1555RUiIiI4c+YMQUFB9/AVEkIIIYQQhZlUWIUoxM6cOUNgYCAzZ87EYrFQrVo1PvzwQ65fv87GjRsBqF27NuXKlWP+/PkMGzaM4cOHk5KSwosvvsiQIUPw9fXl448/zrnmzeaRZmRk5Pw7e67qvHnzaN26NUOGDGHJkiW4u7tz/fp1du3aBUDDhg3x8fHhhx9+oFmzZpjNZnbu3InNZsNkMlGtWrWcsCpb2gghhBBCiJuRCqsQhYDFYsFk+nNV4G+//ZaWLVuybds2evbsydtvv53ztSpVqlCmTBm2b99O27ZtKVOmDH5+fmzatImLFy/i7++Pv79/zvk//vgjHh4et2z73LlzrFixgnfeeQelFJqm5cyVXbhwIdu3b2fSpEkA9OrViyVLlvD444/j5eVFWloaoaGhvP766/Tr1w8vL6+bBmLZ0kYIIYQQQtyMll0tuZ8FBASoffv2FXQ3hMgX2aFwwYIFnD17llGjRuU6DtClSxeCgoLw8vJi5MiRlC1blkqVKhEaGsrChQu5dOkS8+bNIy4ujnr16vHCCy/g6+tLkSJFctqx2+3oup7run/9WvZqvwBVq1alQYMGHD16lHnz5nHkyBF+/fVXateuzcKFCwkODmbIkCFcv36d5s2bM2DAAC5cuEB6ejpms5ng4GAZ+iuEEEIIIW5J07T9SqmAvx+XCqsQ95nskDhq1CgyMjJ46qmnSE5O5rvvvmPatGm4u7vTtGlTdF2nQ4cOeHt7YzAYKFWqFImJiXz33XeEhISg6zo7duzgzTffxNPTE/gz9CZmKmLSwGyz4WDQKO2qcHPQc4JqdsXTYrFgtVopV64cW7ZsYceOHfj6+hITE8OWLVvw8/Pj4MGDGAwGMjMz8fLyYuXKlaxbt46KFSvy4osv8sYbb1C1atVc7Yv7l+yFK4QQQoj7iQRWIQqIUorIFEVChiI1NZUtPy2mS/s2+FWqRFpaGs8//zwREREsWrSI8ePHs3r1at577z0mTpzI1atXcXBwACAgIACz2UxERAQpKSkULVoUgLZt29K2bductgDOXldsu2zh0LU/54xa01PJTImnbZ1HaOJjoKy7Rnh4OJMmTcLb25v333+f5cuXExgYSEJCAr6+vnh5eREUFESJEiUwGAxs2rSJ2bNnM3DgQB577DH8/PzYuXMn3bp1o1ixYhQrVgxAwmohkB1Ws4ehyy8ZhBBCCFGQZEiwEPnMrhSHom38esFGVKpCA66dOcT3rzWhflBvps2Yhb+Xxssv9aZTp06sXLmSd999l/r16zN48GCcnJwoXrw4x48f55tvvkEpRf/+/Tl58iQvvPACr732Wq72lFLYFaw5a+W3CzacjFDcCQx6Vgi5eHwvS8e9Ts85e0lKiCFzyyzSo8Jp1qwZGzdupHbt2oSEhDBu3DgOHTrEsmXLANi3bx/vvfceuq6TkZFB79696d+/PwAnTpxg4cKFPPbYYzz55JP5+vqKvIuIiMhZxTk7qC5YsIDly5fj5+fHa6+9RqVKlQq4l0IIIYR4GNxqSLAEViHykc2uWHLKyo5IG55O4O7wZ9VxSs9AXIqVomzgUzzd6Rky9/5ActJ1fH19OXr0KDNnziQlJYVJkyaxaNEigoODc4b+XrhwgfLly+e089eqmFKK1Wes/HrBiq+7lhNU/2pil1r0mboSo2sRvhrYgbZtWrN49lT27NnD119/Tbdu3WjYsCG1atVixYoVHDp0iMcee4xKlSpx7NgxatWqlT8voLgrsucv//DDD8yaNYuFCxdSpkwZNm7cyMSJE/noo49YunQpFouFHj160Lx584LushBCCCEecLcKrLI0pxD5aP05Kzsirfh6gIejlmuoZce3J2DPTKVqtWpMG/4aca4VqVy5MvXq1ePy5cscO3YMNzc3xo4dS5cuXThw4AC6njXvNDus2mw2IPfQ24hExW8XbbcMqwCdhnzG+i9H4Vm8JI2f6c2eo6eJTbMTGBiIl5cXO3bswNXVlbFjxzJy5EjmzZuH2WwGyAmr2W2L+5vNZsuZo9y1a1fc3d3ZsmULAGvWrKF+/fo0b96c4cOHU6dOHX755ZeC7K4QQgghHnISWIXIJ8nmrODo466h32ROoF+DVly7cJrytQJ5pEoNZo4cyNX4ZAIDA6levTpffvllzrkDBw7E3d0ds9mca0uYmy2W8/tlK85GbhlWAao2foKzB38nJSGGuq2fweDgwLTvVgHQsmVLDh8+zObNm3nxxReZP38+oaGhVK9ePdc1ZKGewsFgMJCcnMzkyZP5v//7P9q2bcuqVatITEwkMDCQ5ORkbDYbpUuXBsBsNufah1cIIYQQIj9JYBUinxyItmFXYLxFcNQ0jQ5vhrD+y9EEvfUJzV/7hMyi5dF1nfbt21OzZk2sVitxcXG89tpr+Pn55Sy8dCsJGYojMXaKO/9z37LaHs+G2R9TxMuHqv5NWbZkMZk2RZs2bejRowcBAVkjNLIXdZKK6v3PZrPx92kfmzZtonLlytjtdl5++WXeeust4uLi2LVrFz4+PpjNZhYtWgRASkoKRqMRJyengui+EEIIIYQEViHyy5EYO+7/nC/xf7IHB35ZjCUjncYde+JUK2vBohYtWjBgwACMRiNKKd58800mTJhw2zajU+1omrppRffv6rV7niObVmDJzKB648exWq0cOXUOgM6dO+Pu7p7rfKmo3p8yMzNz/m0wGNA0jSNHjnDixAkAWrduTUpKCsWKFcvZl7d9+/asXLmSmjVr0qFDB6ZPn87jjz/O0qVL6dixY4HchxBCCCEESGAVIt9kWBXG27zjDEYjTbq8wtZF0zBqkG5VuSpkSilKlCiRa+Xd7ErnzRZQM9tBqbxtSWIwGmncpT/bfpiBd4VqdBj5HaXKPpKrbXH/CgsL45VXXmHgwIHs3r0bgO3bt9OpUydeffVVxo4dy//+9z8A3njjjZzVngH69u1LeHg4e/fu5ZlnnmHJkiV89NFH7NmzhyZNmhTI/QghhBBCgARWIfKNi0nDYr/9eW37DqfNy+9jsYOrKffCTDfbDzO70pmUlATkDpaOBriTLTQf7zuCVr2GZDeGUfuzw7IX5/0rJCSEzp07U6FCBd57772cIbynTp2if//+7Ny5Ew8PD6ZOncrZs2cZPXo0e/bs4dy5rAq6h4cHgYGBnDp1CqUU5cqVk5WBhRBCCHFfkMAqRD7x99JJMd/+PP2PAJqYofD3zv0WVUrdUOlct24dLVu2ZPr06UDuYFnGLev5NnveqqPZbadb7LgYoYSLDPu93yUmJhIWFsaqVav44IMPqFKlCnXq1AGgT58+FCtWjPr166PrOhUqVGDJkiU4OTnx3HPPMXDgwJzrfPzxxwwaNEh+MSGEEEKI+4oEViHySR0vA0YNLLbbh0erPWsf1freRiArqNrtdjQtd8V10aJF9O/fn5EjRzJixIgbruPuoOHvbSAu/c76Gp+h0bKcAZPhxvBit99YJj5z5gxTpkzh+PHjOf29FbvdftNr/Ft3+3qFza5duzh//jxVq1YlMzMz57XPHiq+bt06unbtyqxZs+jYsSMzZszg8uXLhISE8Mgjj+ScbzQaC+wehBBCCCFuRQKrEPnExaTRvpKRKylZgfRW7EoRmaxoU97A5fBjQFbVVNd1oqKi+OCDD5g7dy7Xr1+ncePGuLm5ERMTA4DFYrnheo+VNZBpV3kKypA1b1bXIMA7d4DJru7+dRud7FBkt9s5ffo0Bw4cyOnvrei6jq7rJCQk/Kd5sVFRUURERORcLzY2Nud1eBDdKpRXr16dlJQUIiMjcXR0zDluMBiw2+24uroSFhZGeHg4YWFhVK1alejoaEqWLMnMmTOloiqEEEKI+5oEViHyUStfA+0qGIhMgbh0hf1vCyolZCguxGXS3NeIKSKUjRs35nx97dq19OjRg3LlynHixAkGDhyIpmkMHDiQDRs2AGAymW5os7yHTsdKJiJTbl/dTbcqYtIUL9Qw4umkYbPZcoJSdnX39OnTDBw4kLlz5xIVFQWAo6Mjbm5unDhxgsjIyJz7gRuDVkREBP369aN58+aMHz8+p+95ZbfbsVj+n737jo6i6v84/p4t2fROSEhCkwCB0EPvRISIUkKTJlIsgFJEFClKkyJNQEBAqoVeIl0poXcIgZDQCRCSEBLSy5a5vz/yyypK0edBwMf7OodzPJvZmTszm7if+d5i4sKFC6xevZp9+/bx2muv0aBBA0aPHs2CBQv+0v5edIXX77cPCn5Lp9PRuHFj1q5dCzw4S3BERAQhISFoNBrat29PuXLl2LZtGzVq1Pj7Gy5JkiRJkvQUyMAqSc+Qoii0Kq3j/Wp6SjpruJMFCVmCO1mC+Czw0OTxfZeSNHRJocUrzenSpQuHDx8G4N69e/Tr14+QkBBOnTpFRkYGNjY2NG7cmPT0dI4cOQI8vBIXUlxLE5dkYi9dISHrj9XWPLPgTqYgLQ/eCtJT1UuLxWJBo9GgKAq5uQV9ir/99lt69epFfn4+U6dOpXv37rz//vt07NiRlJQUNm3axKlTp6znCr8GraioKE6fPs369eupW7cuhw8fJjk5malTpz7xumVlZVmruRqNBr1ez5EjR5g5cyadOnXCzc2N8+fPU7x4ccaMGcOtW7f+k9vzQvl9UD106BATJkywfh4KeXl50axZM5YtW0ZcXJx1wqUff/yRffv2UbNmTb766iuioqLo16/fE9fulSRJkiRJepHIQUuS9IwpikI5dy3l3LWk5ArS8gWqKnDWqxR1cuVI85eZMGECX3/9NevXr2fRokVERkZy7tw5Nm/eTOnSpRkyZAitW7cGwN7envLly7NgwQLq1q370Eqcqqq8/3pNQkJfo9I7nxOdVwSLECiAAGy10KKUlhpFtXjaF7xfo9GwZcsWJk6ciMFg4MMPPyQmJoaNGzcyefJkbty4QfHixTl58iTHjx8HCpZL+fnnn6lcuTIlS5YECmaqXbduHcePH2fYsGH069eP2NhYWrdujbu7O4mJiaxcuZIuXbr8od3Xrl0jPj6eY8eO8eabb+Ll5cXOnTs5ffo0O3bsoHTp0gC4u7vTokULbGxs+P777/H393/6N+4ZEEJw4sQJihcvjre3N1DQ7Xrs2LEcOHCA7t27M3HiRLp160anTp3QarXo9XratGnDkSNH6NevH2XKlOH48eM4Ojry8ccfAwWzAEuSJEmSJP0jFY5Le5H/1ahRQ0jS/yKz2Wz9b4vFIoQQ4sqVK8LZ2Vnk5eUJo9Eo6tatK44cOSJWr14tunXrJpKTk4UQQmRkZIgpU6aIjIwMcfHiRREZGfnAvm/evClSUlKEEELExsaKihUrisGDB4tdu3aJHJMqbmdaxPU0i4jPtIg8k0WYzWahqqr1/X369BFubm7C2dlZODk5iZYtWwpvb29hMBhEyZIlRXBwsDh79qx45ZVXRExMjBBCiB9++EHUrFlTTJkyRezdu1ccPXpUtGnTRoSEhIjMzEzrvocOHSoWLFgghBBi2LBhomnTpg+0PTs7WwwePFjUr19fHD16VAghxNdffy0aNWokvLy8RKlSpcStW7fEuXPnRKVKlUT58uXFmTNnrO+Pior6727Mc/Tdd9+JXr16iV27don58+eLnJwcMWzYMJGUlCS2bt0qfHx8xKxZs0ReXt4D7zObzeLGjRti7ty54ueff35OrZckSZIkSfrPACfFQ7Kg7BIsSc9R4Rqq8+bNY9euXdy/f5+XXnqJmjVrMm7cOPR6PWFhYcycOZP27dvj5eVFz549GTZsGA0bNuTcuXNYLJYHljIBiIyMpEePHpjNZutrXbp0wWw2c/z4cfKz0vF11FDSRYOPg4KNVkGr1RIVFcWUKVO4cOEC27Ztw9fXl6CgINq3b8/nn39OlSpVMBqNtGvXjpycHDIzM8nPz+fAgQMAhIWFER0dzfjx4xk1ahQVK1akdevWODk5ERcXB0BcXBznz5+nRo0aZGRkYLFYiI6OJioqCiioBmdlZREbG8vmzZvx9PRkwYIFzJw5kwkTJjBq1ChSU1P56quvCAoKolatWuTl5XH16lXu3r3LmDFj6Nu3L9euXXtWt/E/JoSwdnUulJOTw6pVq5gwYQINGzbk5s2bnD17ljp16rB+/Xp27tzJwIEDrZ+dQoqiUKJECfr370/z5s2f5WlIkiRJkiT9bRTxX8zS+awEBweLkydPPu9mSNJTt3r1aiZNmkT9+vWxt7fnxo0brF27luPHj/Pqq69y79490tLSaN68Od988w01atRg+/btREdH06ZNGwICAh7Yn6qq1i7BxYsXZ/v27VSsWJE5c+ZgMpkICwtj8uTJdO3alZIlS+Lr64vJZCI+Pp7ly5fzww8/YGtry8iRI1EUhd69e2M0GnF1dbWOk23WrBk6nQ5VVa1rfMbFxfHWW2+RlpbGjz/+iJOTE19++SWNGjUiLi6OUaNG0aFDB1577TW0Wi2fffYZMTExHD16lM8//5xWrVpRtGhRa9uzs7Px8fEhLy+P/v3707FjR9auXUtSUhLnzp0jPz+fzMxMrl69yokTJxg5ciR37twhPz+fZs2aMW7cOGt34ReVEMI6zjcrK4tTp07RoEEDjh8/zuzZsylWrBjTp08nMTGR4cOHU6tWLfr37w/AiRMnSEhIsHYLlyRJkiRJ+qdTFOWUECL4969rx4wZ8xya89csXLhwzDvvvPO8myFJ/5HfBhMoWHrmp59+Ii8vDx8fH7p160bz5s3ZuHEj4eHhNG/enFq1arFx40ays7Np0qQJMTEx7Nmzh7CwMAICAqhXrx7u7u4oioLJZKJatWqULFmS0qVLo9FoyM7O5ubNmzg6OlKhQgWSkpLw9fWldOnSTJkyhZkzZ+Lu7o6qqmzfvp1+/frh7OxMXFwc9+7dY+vWrXzwwQfs3bsXnU7HggUL2L9/P2lpaXzxxRfs2rWLvLw8Nm7ciKurK6tXr+bUqVNkZ2ezfft20tLSSEhIIDAwEB8fHy5dusSNGzcoXbo0bm5uNGzYkKpVqzJo0CAaNGiAs7MziqKQnp6O2Wymc+fOmEwmXF1d2bp1q3Vm5PDwcDZt2kSRIkXYt28fOTk59OnTBz8/P1xcXJg7dy69e/fGzc3tOd7xRytcSxcKKqJZWVksX76c3r17c+bMGX744QdGjBhBjRo1mDBhAq+99hq+vr5YLBY2btzI8ePHWbNmDV9//TUVK1YkOPgPf9MlSZIkSZL+kcaOHZswZsyYhb9/XXYJlqS/SWHvhcKAUrhGampqKgsXLsTBwYGKFSty9uxZWrVqRdu2benbty9TpkwBYOTIkXz00UcAjB8/niVLllj3XbjuJhQsZdO3b1/WrVvHvHnzrMdOSEigaNGiWCwW1q9fzyeffELdunVxd3enePHirFmzhmXLlrFs2TJu3bpFXFwcOp0Oo9GIRqNhzpw5FClSBFVVGTduHPfv32fbtm0EBgbSt29fVFWlTZs23Lx5k5iYGJYuXYqqqty7d486depw69Yt62y9ISEhREVFceHCBVasWMHNmzcpX748RYoUQaPREBERQaVKlahcuTJvv/02sbGxrF27FkVRmDx5MnFxcdjZ2aEoCidOnLBWYzdt2gRAixYtGD9+vHWipxfNw5amuXv3LiNGjOD7779nz5497Nq1i6SkJNauXUupUqWoXbs2ixYtAiA4OJh58+bx0ksvUaFCBU6fPs277777XM5FkiRJkiTpWZKBVZKessIxiYVB1WKxMG/ePGbOnEl6ejpFixZFVVUOHToEQGxsLG3btiUsLIyQkBA2btxIVFQUr732Gj/++CMADg4O1jVW79+/T/PmzQkLCyMyMhKAAQMG0KNHD77++mt27dqF0WgkMzOTbdu2oSgKPXv2pFq1atSqVQuj0cilS5e4dOkSUVFRjBs3DicnJw4ePEj58uWJiorC1dWVHTt2UKJECe7evcv169cZOnQoOp2OY8eOUaZMGRwdHfHz87OeU82aNalfvz7ffPMNTZs2xcXFhSlTpvDyyy+TlZXF6NGjuXr1KoMGDSI8PBwoCHBdu3YlLCyM4sWLc/jwYeLj4/H29mbkyJH4+vry5ZdfEhoaSlhYGL6+vgwePJivvvqK6dOnEx0dbb3uv61ivwgSExOJjY0Ffg2qx44dY/Dgwezfv58iRYrQsGFDtFqtdT3bQYMGWR9MfPDBB6xcuZLmzZszZcoUvLy8GDBgAEOHDsVgMDyfk5IkSZIkSXrGZGCVpKegsMKYkpJinQxny5Yt/PLLLyiKQuPGjbl06RJjx44F4PXXX+fu3btAwcRLt27dYvbs2ezcuZMuXbpY18rs2LEjUBDGCqt0dnZ2aDQaKleuzKxZszh69CharZYmTZrQqVMnRo4cycSJE/Hw8CA/P5/k5GRrVdPW1paQkBDatGmDoihER0eTkpJC/fr1EULQqlUrzpw5g06nIy0tjQsXLtCsWTOGDBnC1q1bsVgshIeHs2jRIvr168eIESM4evQoAI6OjrRp04ZTp05x69YtPvvsMypXrkzr1q2pUqUKNWvWJDk5mXfffZczZ87QvXt3YmJiyMvLw83Nje7du6PX6xk5ciQmk8laeSyspubl5TFv3jzmzZvH4cOH6dat2zO9x3/FpUuXKFasGCNGjLC+Nm3aNAYNGkTRokWZPn06H3/8MU2bNqVy5cqcP38egD59+nDv3j02bdpElSpVmDt3LkOGDGHevHnodHIVMkmSJEmS/n3kpEuS9F84d+4cn376Kbdv3+bVV18lJCQEk8nEpEmTcHR0pGrVqpw9e5YtW7Zw+/ZtunTpwoABA9i/fz+NGjXijTfeIC4ujvXr17N3715GjBhB3bp1rfs/fPgwBw4coEePHnh7e1srdT179qRy5cq4uF7FG6YAACAASURBVLiwcuVKPvroI8aPH09MTAwuLi4kJSVhY2ND2bJliY+PtwbpmjVrWgNpZmYmLi4uXLhwgaioKFq0aIGiKGg0GmrWrMn9+/cJCAigYsWK7NixA7PZzNKlS9myZQuLFy9m2rRpdOrUiarVqtOm/2jSS7ckJS2D08tGE1CmDDE7V4DFhMFgYN68eTRo0IBXXnmFmJgYnJycMBqNtG3bllq1atGrVy+qVq2Kp6cnaWlpWCwWWrduTWZmJkuXLsXb25uIiAgcHR2f161+KCEEFkBLQUXVx8cHgLS0NDp06EB+fj6ffvopr776KgMHDiQ0NJTQ0FBu3rxJkyZNOHr0KBs3biQuLo5evXoREBDAhAkTMJlM1ocbkiRJkiRJ/waPmnRJBlZJ+i8UVsx+W0mLiYmxjuOcOnUqo0aNYvv27bRo0YK9e/dy5MgRvvjiC9544w0WL15sfV++RRCbopKUoxJ5ZB/r5k3CQa/g7uaCwWCgY8eOtGvXDqPRyLAvviLXrijFGnZm/bi+XNy/AWdXD8oHBnL14gVeKluew/v2oNVqMZvN+Pv74+XlRbNmzZg6dSrFixenXbt2HD58GC8vLzIyMjh9+jQGg4GJEyfStWtXRo8ezaVLl1i0aBFarZbMzEx69epFUFAQzs7OpKZlENB7Jou+XcTtnxdT4rNDKApknvuF5NWfYEq8jI2jK2UDAvhq6iROnjzJqFGjOH/+PAcOHKBfv374+PiwefNmTp8+zalTp2jTpg27du0iKyuLiIgIgoODGThwIDVq1Hget/ehLEIQr+ZxxpLBDTUPASzp9A5xR06xZMMa2jZoSkx0NHPmzKFcuXJERUWxbNkyXn75Zb744gtq1KiBTqcjLCyMevXq8cYbbzBixAiaN29Ojx49nvfpSZIkSZIkPRePCqyyj5kk/QkWVXDpvsqROxbu5Qh0WrBJPMvBw0c5sG9vwTYWC1qtlsDAQE6cOEH9+vUJCwvj008/Zdq0abRo0YKmTZtSrlw5Vq5cSdmyZVFVFZNQ2B1nJuKWBaNFoFHgxs1sLl65Sp8fY6nuqXJ9y9dERkaiBobyfayF/Qcuo/EwoUQvJOXgVtS8PPKc/DibkItXw76YHA289nI/Di8YTkbSTbp178G0qV+SnJxMqVKlSEhIIN/Wkys3bnH69Bk8PT356aefGDFiBHv27GHWrFk0bdoUnU7Hjh076NOnD1u2bKF8+fJ888037Dl8kldDW+KuqY9r3d64Jd/BUZOPRm9A1UNS+l20ju54DVhNzJwOfDl/GdvXLGfGjBmMHDmSgwcPoqoqKSkprFixgnHjxrFr1y4mT57M/fv3WbVqFaNGjbJWLF8U91UTm03JpAoTBhQ80KNRFGo0b8r5Lb8wa+UKzpgy+KhJKyIjI2nbti0nT54kNjaWpk2bsnTpUipVqoROp6NOnTo4Ozvj5+dHt27dqF279vM+PUmSJEmSpBeOHMMqSU+QmK0y6ZiRBZEmLt1XybUI0vMFZ3PcSczTse5cGhZVoNVqreNMY2JiqF27NsOHD6d79+7s3r2bffv2AVCsWDFOnDjBJ598Qr6qsPCskR3XLbgawM9JQzFHDXWbtgCLCbvcRE4nazhw28SxDBemnDBz7b7AvnRN7q0fjeXqIUq8twS0esx6J7LjznF9w5ckJSej1+up3XkQFgHhe45RrJgvbu4eeAXWJi8vnx+XL6Zko44Evf426blGrtiUpe+7/Th58iSvv/46c+fOpUuXLmzbto2UlBT8/Pw4evQo+w8f44OpK9AHNMLOxQ0HG/DrMAqNvmAiIOdKL4NGg2rKxxS1BcXelb27dlG/2SvodDo2btxIvXr1+PTTTzEajYSHh3P9+nWuXLmCm5sbO3bsICAg4IUMq2uMiWQLM16KDS5KQVgFaP5OT1yLeVO0iBfHt/3M6PAf6dyzB2lpaQQHB7No0SKGDBlCSkoKQ4cO5a233mLFihU0bNgQKJjl2NXV9XmeniRJkiRJ0gtJBlZJeox7OSpzThvJNgn8nBU87RQc9ApONgrFnG0oXq4SP27ezabLZsxms/V99+/fJzs7m5UrV7J06VJatGjxwH5tbW0BWB1r5mqawN8JbLS/znKrKAqh/cexZ/FEtPcucuSn7zhy7CTGpGsIBRx8SlOkSS9KvrcYtVgV7Mo2IP/CL2hdfHBu8CaegXXYMvFtXLz9Mdg5cufWDYS9O5dv3ObMvu04uhdBr9NQ8qUATKm38PQtxbuNirN4837mLVhkXVqnS5cu5OXlsX//fho3bkznzp15b+CH3NV7U7rfEtyDmvzhmimKgnfrYejsnMmMPYBiMWM25nLi2FF0Oh06nY4OHTqg0+nQarXodDoyMjI4cuQI69atw8vL64Wb8VcVgm2me1gQuCj6h27TqHsnbkSeo2Xv7mwaN5Ula1cTFBRESEiIdR3atWvX0qBBA2rVqsWpU6cIDAx8xmciSZIkSZL0zyIDqyQ9xparZvLN4GH3xwDl6O6Fh29J7kfvY/eVTOJzNGg0GrKzs7G1taVSpUrMnj2batWqsX37dho3bvzA+5OyVSLvWvB1fPiSLNVavMHx8KVsmDIQt9ChKIqGSwv7kXV8HcZ7ceTdvU6uUUXj4I59hSag1ePaoAeqKtCXqoWtpz8nd4VjsHMg6+5N4q/FYrGYKeJfGv8KwQTUCsGYm0W5Os0Z8G0EBjtHag6Yi/pSwwfa8eqrr7Jw4UI0Gg3DPx1B4KideLQYiI3No0cUFA15G1NaInkJlxCqGa+Wg3Cu3Qmh0VGmTBk++OADpk2bxkcffURsbCz16tV7YI3SF02iyCdZGHF5zCiKtsMHcn7vQRxcXXhz8ucYUbmVlUb58uUpW7YsGzduBKBbt270799fLk0jSZIkSZL0J8hJlyTpEe7nCcYezqeYI9aun7+XnnyHHfM/JyMzm54fDKdk/mXmzp1L9erVmTJlCvb29o/c/09XTOy7ZcHH8dHVxP0/ziY+OY2cpp8iLGbSz+8mc/uXFG35PoreFgJD0ShgSUsg/uvOWHIyMPhXQs1IxHL3Mg7+Qehzk8lKSaLipOOUdNFRo5Q75yN+wt23FH7lq1nDcsR3M8jKSKdu7zGMrW9g3eqV5Ofn8+abb3LkyBEaNGjAxVQL7cNz0QCGJ4yAj53wCqb0JCpNPYtqsRC3eRb2l3eycv6XWCwWGjVq9MR78KLYbkrmmiUXt0dUVwstem8oQgjeWTCDa7dvUdWrGK85+ZGamoq7u/szau0/S+HYb0mSJEmS/t3kLMGS9BedSbKwPNqEn9Pju6fmZqaxf9Vcbl+9SGnbLD788ENCQkKeuP+JR/MxqwJ7/aP3b8rP4/PQUrz0VRwWVcEswCHrJrZFimNSIcsIhT2JTemJ3Pi0ErqiAZgSYrGxd0Ln6I5nUR/8a76CTcgQbLDQrGRB6Pp9RdOUn8f4VqWo3XM0GcfW4e9ThFGjRhEc/OvfjZ+vGxmw24iLDTyp1258+BQSf5pG0VcHkX5mG1p3f2p3/YRdw/45QbXQwrxbGNCgVx5fBU5PSmZAyap8E38eGzcXLAj62Po9o1b+s8XFxVGiRInn3QxJkiRJkp4TOUuwJP1FRsuf287OyZVX+o7g2t0s5rbyeGQ19vfyLQKbJ/SC1Rts8W74Bjlnt2Oo/CqKAINn8YIf/u5Zk97FG9eX+5N/6zxF3lpIheKeqI5F0J5YjmJwwGixYNFpH9n1Vm+wpU67PsSd3M30qV/TtlG1P2yTYSw47p85Rb2jB45lamHOSqFU3/moxapg7/ZijU39s4wI7Hhy212KFqHr5M8w5eVjEGBUXvwHgs9SVlYW69evp0qVKlStWhWAvXv3MmPGDLKzs2nVqhWNGzcmODgYVVVf6G7ikiRJkiQ9GzKwStIj2On5ExGlgEkFV2fHPx1WARz0CjkmwZNGMlbpPYWrGQpmy4MZ9WGH8mw3BhQFkwoOngrZJqj+em/MaDmVpGLzhJ6Xof3HcycLqlW1eejP3W0LDipUeEKxkSLN+lCkaW+U/w8dmUaw1/0zA6sBDRYE2j/xiXh10LsA5AsVwws2edTzIoRAURQMBgObN2/GYrFQrlw5bG1t2bx5M+PHj8fDw4PevXtz8eJFgoODZViVJEmSJAmQky5J0iOVcdWgVcCkPrlKdi8X6hX7a+PwgotqSc9/8nal3HQIAVoN6DS/BlWtUhCoHwyxCmYVHPSgioLtXe11eNgVhFhv+8cHqBwzuBjA7xHjal9y1eCgh3z1ye1WFMUaVoUKqgq1/+I1elEEaO3JxPzkDX8jEwtlNQ5/U4v+GiEEFsuf7DLwlI8Lv04qptfrCQwM5MKFCyQmJnLlyhUOHTrE7t27adeuHaVLl2bUqFHPvJ2SJEmSJL24ZGCVpEew1yvU9dVyN/vx2xktAiGgls9fC2PVvQu2Nz8hEPs7KdjpCoKpXgOFw84VpWDiI/U34VFQ8HMvO4VcM/g7K+g0CooCRewVdFqFR41bV4XgXq6geQkdWs3DA2txZw1VvTR/urt0oTwVHGygQ9l/ZqeOIK0jFsEjr93vCSFQEVTUOv7NLXsyVVVRFAWtVovJZAL+/Hn8p4QQ1uMWWrFiBTVq1ODmzZusWLGCgwcP4uPjgxCCw4cPc+DAARYsWEDx4sWJjo7+w/4kSZIkSfp3koFVkh4jtJQOH0eFhCyB+pAvzblmQUI2hAXoKOrw136dXA0KISW0xGc+fN9QEDagoLKpVcDZpqC6Wbi5rRY0GgrCFGCygL0eDFqBTgP+ThosquB2pqBHBR1Vimi5lVnQ7t/KNgluZgjqFtNR1/fRwVtRFPpW0qFVIP9PFhxVtWA8cG1vDX5O/8w/OR6KnlJaO1Iw/antUzBRRmOHm+bxswr/XdTfPMXQaDQkJiYybNgw6tSpw927d//2dW4VRUGj0ZCcnMy0adMA+Omnn/jiiy9Yvnw5PXv25MSJE9y8eZNevXqRl5eHnZ0d0dHR9OjRgx07dmA0GlFV1dqdWJIkSZKkf6d/5rdHSXpG7PUK/avaUNFTw50siM8UJOcIkrIFtzJVck3Qo4KOBn7/WVfX0FI6GvrruJUBafnCWkkqDBy5FoWbGYImxXUMr6VD+f9uwHlmsKgFVVZHfUGAzTODjRaK2gOKQjUvDel5cCcLmpfU0TZAT9/KetqU0ZFnhvgsQUKWID5ToADdAvW8UV73xHG4dXz1tA/QkW95cmi1qJBpAj9HGF3P8I8NHoqi8IreAw9FT7IwPvoBgxAkCyOeig3N9Z7PuJW/ViJ/O/4zJyeHXr164ejoSHh4OF5eXk/9uL/vbpyVlcV3333HO++8Q2ZmJlevXsVgMFiXrxk4cCA3b97k8uXL9OvXD3d3dzp37sybb75J2bJl+eCDD7CxsUGj0aAoChcvXuTHH38kMTHxqbddkiRJkqQX2z+zf54kPUOONgq9K9lwL0flbLLKvVyBXgNl3DSUd9dgo/3PQ5hWo9CxrI5ybgpbolM4dyURzxLlQCgIBFmXj5ITuQWvl+vRPKQZVYo6seJcPntvqeSYf62sOujB6//Hp9rrwddRg9GiUMtHS91iWvycFBRFwUYLISV0NPLTEp8lMFrATge+TsqfnjBKp1EYUc+ACqy/bCY/HwzagrBcuAuLCrn/H6pLuMD8l23xdfpnjl8tZKdoaW9TlD3mVC5ZctAIsEeLFgULgmwKQls5rQNNde4YnjQr1d+g8IHA4cOHWbx4MV26dKFYsWIUKVKE+vXrc/v2ba5evUpgYOBTDa6FQTQtLQ1XV1fu3LnD2rVrEUIwduxY8vLycHZ2JjMzk/z8fPz9/cnMzGT58uXUrl2b7777jvj4eLy9vR9Yk/X27dssWLCAX375BU9PT1asWMGGDRseu76xJEmSJEn/W2RglaQ/ydNeQ0iJpx9CFEWhipeOQ+vW07lCdUoG6VEFRGxezaK5k+natSvr167h0IH9TJw4kWnN7EnJVbl838LNDIEAijkoONhoKOOqYNAVTLxk0BaEy4fRaxVKuvznQdtOpzC2gYEGvhqWnjcSk1qw5M1v9+jjAK3L6OlRQUcRh392WC1kq2h5VV+E+joTMeZsrqm5mFAxoKWSxpFAnSPOyrP7s2qxWB4IeCaTiRkzZrBhwwZ69+5N3bp1cXBw4KWXXmLOnDlUrlyZjRs3EhwczLhx4yhevPh/ddzCpWcOHjzIqFGjcHZ2ply5ckydOpX27duzefNmEhMT8fb2pm7duoSHhxMfH09gYCBOTk5UqVIFKOhR4Ovr+8AxkpOTmTVrFtu3b+f8+fMAhIaGEh4eTocOHdDrn093a0mSJEmSni3lnzCZRXBwsDh58uTzboYkPTWqqnL9+nXc3d1xc3Ozvn716lXS0tKoUaMG7dq1Y+jQoTRo0ICLFy8ya9YsqlatyjvvvPNCjetTheBSqoUjdyzczyuo2JZzU6jtq8dB/2K08X/Jw9YnvXLlCmXKlMFsNtOsWTOWLFmCl5eXtavu7z9jw4cPZ+nSpTg6/rVJoR527KysLN544w26du1Khw4dqFevHgMGDKBixYqsWbOGoKAg3nrrLXJzc4mMjGTOnDlkZmbStWtXihUrRuPGja37+v7779m2bRutWrXijTfeYO/evYwdO5avvvqKGjVqsHjxYg4dOsTYsWPx9/f/q5dOkiRJkqQXmKIop4QQwb9/XY5hlaRnSAhBUlISr7/+OuPHj+f+/fsALFmyhFWrVvH5558THh4OgJeXF7t37wbA39+fihUrcvPmTYAXJqwCaBSF8h46elUy8GFNA/2qGWhW0kaG1acsJSWFSZMm8duHd/Pnz6d69eoMHTqU7777Dp1OR6NGjejYsSMDBw6kT58+BAcHo6oq0dHRjB07lk6dOlGqVCl0ur9eCS4Mq9988w316tXjypUrXL9+HUdHRxo2bIiNjQ2TJ09m69at+Pv7U65cOY4dO0ZGRgZ2dnbUrVuXRYsWsXnzZrKzsxk0aJB132PHjuWHH36gW7duLF68mDFjxlCiRAlCQkKsvwddunTh7t27HDx48Lks0yNJkiRJ0rMnA6sk/c2MRiNCCJYuXYrZbMbW1pZbt24RHx/Pu+++S6tWrThz5gyhoaG888473L59m0OHDtGxY0cOHTpETk4O9vb2XL16ldKlSwNymY9/k/Xr17Njxw7c3NyIiooiKioKi8XCtm3buHHjBvv376dnz57Mnj2bTZs2MWHCBHbt2sWcOXPYsGED3t7enDx5kqSkJPLz81m1ahVffvkltra2jz1u4dI0v/f++++zZ88eJk+eTJkyZRBCYDKZMJlMCCF4+eWXOXPmDElJSdSoUQMoqACrqoqqqjg4FKxN27lzZ1xcXNi6dStQMF71vffeo1WrVsybN48zZ86Qm5tLUFAQ165d49KlS9jb29O0adM/LJkjSZIkSdL/LjmGVZL+Runp6Xz66afs2bOH+Ph48vPz0Wq1xMTEcP36dZo0acLWrVvZsGEDLi4uNGrUiNWrV3PmzBm6deuGu7s7b7/9Nnq9nosXLxIWFga8WBVW6e8xb948li5dioeHB/Xq1aNWrVqEhYWxe/duGjduTGhoKPXr12fMmDHs2rWLsmXLEhERQZUqVShVqhS7du1i+/bt2NjY4OPjg7+/P82aNftTxy7scq4oCikpKWRnZ1O8eHGuXLlCZGQkBw8etG5XuXJlPDw8+Pbbb+nduzcGg4Hg4GD8/PxwcnJi5syZGAy/zhCdm5uLnZ0dTk5OtGvXjm+//ZZWrVqRlZWFm5sbubm5lC9fHq1Wy4EDB+jcuTM7duywnuPQoUP/tmsuSZIkSdKLRwZWSXrK0tLSSEhIYN26dWzcuBF7e3uSk5MxmUyMGjUKJycnnJ2dsbOzIz09Ha1Wy4IFC2jbti0Wi4XQ0FA2bdpE06ZNWb58OUePHuXs2bMsWLAAg8HwvE9Pegaio6PZuXMnixYtomrVqtbXW7RowdatWzl27BilSpXixIkT3Lt3j8jISCIjI+nTpw/16tXD1dWVzz77jLZt27J9+/YnVlOBB8ZFK4rC7du3mT9/PuvWrcPX15cZM2ZQoUIFjEYjkZGRVK1aFZPJhI2NDUOGDCE8PJx3332XlJQUevXqhYeHxwMPVmJiYpgyZQp3796lefPmDBkyhLfeeotly5Zx+fJlatSowU8//YSPjw8BAQFUqlQJZ2dn3N3dGTJkCOXLl3/6F1qSJEmSpBee7BIsSU9Ramoqffv2pXbt2nz11Ve8+eab2Nvbo9frsbGxIScnh6VLlzJo0CBSUlKoUKEC06ZN4+eff7bOvBoaGkpmZiZnz55Fq9XSuHFjBg4cKMPqP5gQArMqntiVu/Dnx44dw87OzhpWC8drOjs7U7duXY4fP05KSgqZmZns3bsXKOh26+LiwtWrV3F2dubw4cN8/PHHTwyrhfv+bbg8c+YM7dq1Q6PRcPHiRerUqcOPP/7IxYsX6dSpE3PmzAHAxsaG8PBwvL29GT58OLNnzyYyMpJBgwZZ95eWlsbt27cZMmQIzZo1Y/Xq1XzzzTcsWbIEV1dXXn/9daZOncoHH3wAwLBhwwgNDeXnn3+mSZMmaDQaKlas+MBsyJIkSZIk/XvIWYIl6T9UWJFSVZV58+bx7bff0rhxY3Q6Hd999x3379/HxcWFVq1a4ezszNatW7l//z6VK1fmlVdeITw8nLt377Jw4UJatGhBnz59+Pbbb4GC8Xx+fn7P+Qyl/0a+RXDhnoWIWxZuZwosAjQKuBkUGvtrqVZUy+2rsRw9epTXX38dT09P63sHDRpE5cqV6dOnzwOfM41GQ2JiIh9//DFt2rShbdu2tG/fnlu3buHm5saECROoU6fOE9sWExPzh+Nu374dRVGoU6cOWq2WNm3aUK1aNaZPn86FCxf4+uuvadK0KfUaN6J5k6Y0b96cM6dPo6oqixcvply5cn/oqr5o0SJSU1MZPHgwRqOR48ePM2nSJGsvhPj4eOLj4wkNDWXNmjWUL1+erVu3otVqadmy5dO9IZIkSZIkvdDkLMGS9BRkGgV3c1SSsy2YVJgxYwZ2dnYMGjSIe/fucerUKdzd3cnLy0NVVRwdHTl69Kh10hxFUYiJiUFRFBwcHEhKSmLcuHG0b98eDw8P63FkWP3nsqiCX26Y+PxQPsvOm0jJExR1AD8nBW8HUBEs3BlJlcatCG33BhdiL3H27Fmys7OtFdZy5cqxePFi6z4LJz/KyMigaNGi1KlTh+3bt5OSksLy5cv5/vvv2bVr1wNhNUuYuWDO5JgpjWOmNKLNmRyLOsNrr71Gly5duHz5MpGRkVy5coWuXbsyfvx41qxZQ1hYGFlZWQwcOJBr166Rl5eHX2BZNP5FWXxsLyvMifTav478ZtWo9X4vDK7OpGdlWdsYGxtLVlYWUPBQJyIiAoPBQE5ODjNnzmT48OGcPHkSs9nMypUr8fX1pW7dutbJl1q1aiXDqiRJkiRJVnIMqyQ9gckiuJBiYWWMmSN3zOSZ4eKXbfAqV4PEPUvxKupNg/r1uHHjBhUrVqR8+fL07t2bVatWYTQaiYuLo379+tjb23P37l0yMzPZsGEDL730En5+frRr144PP/xQTqT0PyDfIvjhgonIuxaKOih42j34TFCjKDjoIW7XMgKq1qFip49xs1OoFKTFwUGHyWRCr9fTv39/JkyYwO7duwkJCbF+Ng4ePIjZbKZt27YYjUZsbW1xdnbGxcXFeoxk1cgpSwYXLdkIBBpR8F5VEWxcMJuStauw5KcNeGlsAIiMjCQ1NZXDhw8D0LdvXzZt2kT9+vVx9/Bg9A+L8O3WGpv6Vcha+AOW63coGVwV3xavEH3qNEcOHuL9KePo3rotbRuFMHz4cBo2bMjQoUMJCQnhl19+ITU1lejoaDw9PalduzaJiYn4+/szYcIEunTpwuzZs2WXd0mSJEmSHkpWWCXpMVLzBB/uyaXrljxWxZq5liZIygZDyBAub1tIZloqatWOeFVpxoEDB4iLi2P+/PmcPXuW/Px8zGYz1apVIzU1leTkZBwcHEhPT+fcuXO4u7uzZ88ehg4diqqqcqmafzhVCFbHmom8q+LvpGDQPvwBRPzFSOLOH6dx1w8o5qiQmm3m2/MWsk0CvV5Pbm4u9+/fZ+bMmcydO5ePPvqIa9euMWTIEIYPH45Go6FYsWIMHjwYZ2fnB/Z93ZLDSmMCVy05uKPHSzHgqbHBU2NDztlL3D5+lqoD3mSVMYGL+RkA3Lp1ixIlShAfHw/A66+/zoEDB/AvVRK72kFs+m4lnugJrl2bt6aP56XggnG1iqLgZGOLd+kSvDLwbcaN/pwLmSlMmDCBbdu2sWrVKpKTk/H19cXV1RUfHx9cXFxo06YNYWFhjBw5km3btgHIsCpJkiRJ0iPJwCpJj5CRL/hoTw5br6tkm0CnAXu9gkEHrkFN0No6gRCkZ+Xw3db9VKnblAMHDhAREcHBgwfx8fEBIDk5mZiYGIoVK0ZERATz588nJiaG+fPn4+/vjxACrVYrK6z/cJFJFo4nmPF3evyyQw6unuh0eoy52QB4O+tIzlH56YqJZcuWERQUxJQpU+jcuTPjxo1Do9FYlzbas2cPr7322kP3G6/mEW5KxhEdbooe7e/a4OTpgd5Gj12OCSd0bLWkcNOSi5ubGwaDgZiYGABCQ0M5f/48e/Pv4dYomFd6dUc1mxFC4ODq8sA+S1SuiBACbx8f2o4YwrQlC4lNvM20adPYunUr+/btY8eOHZhMJgIDA5k0aRLvvvsuP/30E+3ataNEiRL/zSWXJEmSJOlfQAZWSXqEBWeN7LstEAIMWigsmIn/H6vn0ugtAPKitpObmkRO9R5079ufmJgYVFUlNzeXokWLkpiYaJ3t19vbm/fee++BL+oyqP7zCSH4Jc6Cu63yxPup1enxDqjElZMRAKgW6RA0lAAAIABJREFUC172cCJRJTk1ne3btzN58mQAgoKCmDx5Mr/88gtffvnlAxMz/ZbZYmGn8R4OaLFVHv5nXafX418pkOiIgxgUDQ6qws+mFOrWr4+zszOTJ0/m22+/pWPHjjRu0Zwb9lCuRGnqv9EOnV7/0PO6n5BExaYNsLGzpXztYK4dPE7/vm/j7e1Nz549iY6O5tKlS0RGRiKEwN7ens6dO+Po6EhCQsJfuMKSJEmSJP1bycAqSQ+RmifYfNWEWQX971bTUDQFvzZuoR+BTo/l/m1s/ILIMXhSocd4Zs+ejV6vJyAgABsbG95//33MZjMff/yxdR9yiY7/LbcyBXeyBU42T97W0d0L92IluXIyAmNeDhqtFr1WQ25mOlk2HpQsWRJVVa2TGGk0GjSax/+pTlRMZGDBTjw6LDt7eeJVsjgXIg6Rn5ODk95AFhYuZ6ZQpkwZ3nvvPaKiomjZsiUdJ45Ep9GheUL4di7iweWjp/iybQ9mduxFzddbULFtKB98OITc3FzKlCnDwoULqV27tnWmY4DBgwczf/78J18sSZIkSZL+9WRglaSHOHjbxJ2sgmVIHvaVXagqWq0W12bvgWohY/dcUtcM58MGHsydOxe9Xs/06dM5deoUM2bMsH5Rl/43nUq0oFf+XLVcURSqteiMxWRk9di3ib90ljM7VrF1VDt2RhzCZDI9MaT+fszz7rhLrH5nGN8NHU3yjVuPPG69zu0wG40seHsIN86eJ2rVT7Rr+SqnTp2iTZs2zJ49m77vvcs5SxauPPmhilano1T1yjh7ejDt3EHafjyQ1hM+odKrIRQtWtRaUS1c+mbw4MHcvXuXtLQ0OnXq9MT9S5IkSZIkycAqSQ9xMknFrBaMW32YwiqrV8cvUBzd0Tp5YLkfj2o20aXXu2RmZhIUFFSwraI8sUIm/bMl5Qhs/8Kc6y5FitF6yFS8X6pAxIrpnN65ihbvjKb+gJnY29s/8f0ajQZFUTh37hxnzpxh04rv8StbBht7O7bNXkDilWsPfZ9bMW+6Tx2LX4VybJk+j1OrN9Fy9BDmzJmDXq8HIAcLFgS6R3Qt/j13Xx8qNW8MgCk/HzudDdU7t6FWrVoMHTqUzz//HI1GQ506dUhNTWX8+PGcP38ei8UCIB/mSJIkSZL0WHJZG0l6iBzjk2fsFaoFRaPFPaQ/5tRbOLQYiqtPSUa3tkVVVRlS/0WMloJq/F9h5+RK874jyc/JwmDviBCC25kgeLCqf+/ePTw9PR/4TEVHR/PNN9+we/dufHx8SLHX8eHapaRev0nEspWc2baL0IHvPPS4Dq4uhI38kLysbPQO9mRgfuDn5r84WbXZaEJYCiq+eoOBfGHmwqkzzBo9lZ9//plVq1YRFBRE7969+f7771m1ahVz585l2rRpfPbZZwQEBPy1A0qSJEmS9K8iv1FL0kO4Ggoiw+O+uysaLUIILFkp2Jauid6zJDZasLN58phD6X+LvR4sfyHo/baqaLB3BAreb9BhHTcqhGDFihUUK1aMkydPWrsAnzhxghEjRpCRkcGFCxcYNGgQyVdvYEHgUdwXv4rlSLxynXs3bz+2DbaODlgQGH73vwEbRXns577QpSMnmNtzAMfWbyZyx24O/rie1PgEtk39mjWfTaZv375oNBqmTZvGxIkTWblyJUIIfHx8GDVqFGXLlmXgwIGMHDnygf0KIazV1+dJCCGXmpIkSZKkF4D8Vi1JD/FyCS22WrA8obeiMfEiCBW7Cs0QQCkXBR8HOevv8yCEeG7dS0u4KOSYHr/Nb8NP4QONU9t/tM4WnGkEPyeNdVtFUaxrpC5fvpy5c+cC8NJLL1GtWjXS09MBaN26NY62duxfF45Wp8M/KBCL2czprT8/sd2ZmCmjfbALsj1aHNGSJx4dGrPT0pne/i2cPN2ZfHI3zfr24MrxU9w4ex4LkHT1Bm+88QZCCDp37kxGRoZ1feLNmzej0WgYPXo0c+bMoXPnzg/sW1EU66RksbGxTzyHp6Xw/hR+jhTlwRmfZXiVJEmSpOdDBlZJeogqRXUEuCmogPqY76kGn/J4dZkKLn7oNdA9UI+NVgbW/9bjwsHDQmlhwNBoNM9lbGR1Lx0CUB/TbuU3ldMLB7ay7etR3Dh7BFdvfwCyTYKGPuKBCZWCgoJwdXXll19+YdKkScTExODu7k6zZs3w9vZm9+7dAAzoP4C9c74tqGAGlKZh947U6dDmsW0WQmABKmodH3hdqyhU1zmTyR8Da2G7HFxdaPnB2+Rn5wBQs20o8TGX0dvbUaVNSwLLBHDo0CFr+Ozbty+RkZEsX74cjUZDcHAwAKVLl6ZSpUoP3CtVVZk0aRLVq1dn5syZDBgwAKPR+Nhz+W/8NqDCr2POs7OzmTNnDuvWrbO+LkmSJEnSsycDqyQ9hJ1O4c2Keux1BeMTH1dcMVkKug6XdYPGxfXPrI3/ixITE9m3b99Dw0FhF83C6uRvQ45Go+HOnTt88skn9OjRg7y8PDQazTMLrR52CpWKaEjJ/WN7C0OeKS+Xc3vDCyZL2ruJKycjaN53BGkJN/l52TTs9QqBHlo0Gg1bt25lyJAhpKamEhgYSPny5enWrRszZsxg27Zt1K9fHz8/PyIiIgAY2PdtlDwjFy9fRGdjQ7l6tXAu4vHYNqdjxlcx4Kn88TNbTuuAApiESvTeg2ydWbAEjfjN9WzYrQPXz0RxPyGJ7PvpaPU68HKjYZkKvBwSwsqVK8nLy6N169bMnj2b7OxsFi9ejLOzM82bNwd+nTxKo9GQnJzMmTNnuH37Nvn5+URERDBgwAC+//57Vq9e/V/cnYf7bUVVURQSExMZMWIEa9asYe7cuTRp0oSkpCTWrVvHrFmzyMrKeuptkCRJkiTpyWRglaRHaFdWT69Keuz1kG8pCK6qKAinAjCrBa+rQElnmN7EFg87WYX5TxSGB2dnZ4YNG8a+ffsYOHAgly5dsm5T2EUzJiaGAQMGsG3bNhISEoCCrqMdOnTAzc2NcePGYWNj88wnvmpWXEeeWWC0CGsIKvyXcS+B0ztXcmLzcm6eP069Du/h7OVL6p0b6Ay2HN+0lEbeFnb/spPq1avTtWtXjh07xqxZszh79ize3t5ER0ezZcsWPvzwQ+7cuUNQUBDXrl3j+PHjAESeOkWJgADSxBP6JgPpwoQeDS1sPB/6cMBe0dJAcSEFE1pbA7u//R5Tfj4ardZ6rzyL+1GxaQM+qdaEuT0HUKV9K14KLE99Ow9cXV1Zt24dM2fO5OLFi0ydOpX169dTvXp1tmzZwpEjR6z7iYuLY8OGDfTs2ZPExERWr17N6dOnGTx4MO+88w4TJ06kR48eT+0+FVbgC4+v0WhYvHgxL7/8MoqiUKdOHQICAtiyZQsDBgwgLi6ONWvWcOTIkafWBkmSJEmS/jwZWCXpEXQahQ+Dbfi0tp4yrgVL3Bj/P6Tm/394dTFAYz+FJaF2BHrKSbf/qsIKqKIoqKqKvb09RqORDh064OLiwsWLF63BIicnh+nTp9O9e3cCAwPZtm0bLVu25MaNG1y9ehVXV1cGDhyIyWQiNjYWIQSHDh1iwoQJHD58+G8/l+KOgg5l9SRkgen/C5E7vhlD+IyPiPx5LRcObMO3bBXO7Q3Ht1xVHFzcSbwWQ7rWHc8iRZg1sAPz589nwIABJCcn07dvX2JjY4mKimLJkiU4OjqSkJBA+/btGTFiBLm5uQwfPpxatWoB4KIz0MFQFEdFx101nyxhfqBrtRCCbGHhrjBip2jpYFMUZ+XRn9lqNi7U17qi+rjjXtyXfctXFeznN1XWup3aYMzLp+M3U2jSqyvlLibzZvtOjBgxgoCAABISEsjPz0en03Hx4kX69etHWloaZ8+exWwumJ14/vz5fPDBB7z//vuEhoYSFhbGjh07aNmyJUePHrVej+vXrz+V+1QY0I8ePcqGDRtISkpi3rx5pKamYrFYsLe3p27duuzdu5cOHTrw/vvvU6NGDQ4ePEhGRsZTaYMkSZIkSX+e8k+YSCI4OFicPHnyeTdD+hfLyBccjTex8aqFtDyBjUahrLtCh7J6yrhp0P7VNU2kB0RERKDT6ahduzarVq1i7Nix7Nq1i/nz56MoChaLhQ4dOuDo6Iivry+dOnXiyJEjaLVaNmzYQKNGjWjatClFihTBz8+PTZs24eLiQpEiRejcuTOrV6/ms88+o3Hjxk99LGJGRga2trbY2NgghGDhlsPsum4k/cZ5Mm+e5+wva/l0Ywzfj3oTR1dPTMZ8Wr43hugTB/hl7nCEKR8XJydMJiMVKlRg//79TJw4kT179lC7dm3mz5+PEIKZM2fSu3dvMjMzSUhIIDAw8KHtMQmVa5YcTlkySBYmNPzaK8BD0ROsdaa01h6b362zarFYrJMdAVy/fp1evXrh5OPFrfRUMtLSGbpnPbZoUM1mVI2GPI3KmvdHYm9U2bD8O5bMnsuQIUMoUaIE169f5+DBgwwcOJBXXnmFnTt30qBBA1atKgi+3bt3Z9CgQXh6elKtWjVWrFhB3bp1AWjVqhXVqlVj0KBB7Nmzh/9j777Do6q2xo9/z/RJJr2QRiAhEEgoIUAIvfcu0kRKEAUElCaooBAsiBhAihQRkVCDgAGlI4ReQ+hJIIWEkEZ6n3Z+f8REEL3ivfL63vd3Ps+T54FDZmbvczJD1l77rPX111/zxhtvMHTo0L98fUwmE9nZ2djY2KDVaklOTmbixIkkJSXRuHFj+vTpQ0xMDJGRkZSXl+Pu7o6rqyulpaWMGTOG0aNHs3DhQiIiIli2bFn1dmaJRCKRSCR/L0EQroqi2Py3x6WUkETyHKzVAt29VXT3/qdH8t+ranHsyYDx5MmThIeHc+fOHfR6Pe+88w6jRo0iMjKSL7/8ku3bt6PVavn4449p0KAB1tbWhIaGEh0dzdGjRzl48CCrV6+mc+fOREVFkZiYiI+PD8OGDWPmzJkcPnyYffv2ERMTw44dO3Bzc6NevXr/8VwKCwtJT08nLS2NXbt28cEHH1BWVkbfvn2xtbUFhQZs3SgWtVi5eXNs21fYuPmQm56EobyCqP07yLp+AiVm7J2dmDp1KqGhoRQXF3Px4kUePXrEggULqF+/Pt988w25ublotVoEQcDGxqbyNf6AUpDhq9BRT25Jnmik/JfiSRrk2AmKZwL2qq3TTwarUJmBDAoK4vPPP+fc+fNMmT6Nswu/pN/8WehlIhYKJbE79pN7IYZzt+8w19aJDz74gC+++AI3NzeOHz+Oh4cHAQEB7NmzBw8PDzZv3kxFRQWdO3dGpVIxZ84cwsLCGDx4MFu2bKkOWJcvX86GDRsYNmxY9TbxHj16/KVrZDQaUSgUPHjwgMjISAYOHIiXlxd79uxBr9dTv3593NzcmDp1Krt372bGjBlERkYSHR1NzZo1uX79OuHh4ZSVlREdHc3w4cP/cJFAIpFIJBLJiyNtCZZIJC9UVV/N37YJuXHjBlOnTsXV1ZXz588zffp0IiMj6dy5M6+88gqHDh0iLCwMd3d3FixYwJw5czhw4AAPHz4kKCiIkJAQDhw4wJ49ewgKCiIoKIiBAwcydOhQ3nzzTUaNGsWkSZM4ePAgW7duJTMzk1u3bv3H8zEajSxfvpzXX38dHx8frl+/zu7duxk0aBDFxcXI5XLatGxGfUcVThWpOFmqiN7zFRZKgeTLx3h08wx5F/egKnuMg70dY8aMITU1lREjRnDv3j2uXLlCcXExZ86cYfXq1fj7+9OgQYM/LEb1RwRBwF6mxE2mwU2mwV6m/N3HV93n+9VXX/HSSy9x4cIFAE6cOFG9yNA0IIAGdXw4tiGcEWpXir/dx4EJ7xF7+CR7dn1Pjx492LlzJ1u2bGH69OlkZ2cTFRWFr68v8+bNIyAggHv37lFeXk63bt04cOAAs2fPJjg4mNWrVzNr1iyOHj1KZmYmAHXr1mXx4sXs2LGDH3744bmD1djYWDZt2vTUvH766SciIyPZtm0bjx8/5ueffyYmJobHjx+jVqtxcXFh2bJleHh40LFjR27dusWmTZuYPHkywcHBnD9/ngULFjBv3jw8PDye+/xLJBKJRCL5e0gBq0QieSGqKthWtTYpKSlh/vz5bNy4kcTERBo2bEjLli1JTEys3rZ55MgRTp06xY8//ohGo+HTTz/l0qVLNGzYEK1WS2hoKBkZGTRs2BA/Pz9MJhP9+/cnKyuLsLAw2rdvz6VLl1iwYAFDhw7l0qVLbNiwgV69epGUlERkZCSJiYl/eS6iKBIfH8+7776LXC5nypQpJCcn065dO/R6PXv37sXJyYmePXsya9Ysbty4Qd26ddGqFDxKjKWsMI+z36/DZDAgIFJRVsLChQvJycmhQ4cO3Lhxg6ZNm2I0Gtm+fTsjRowgJyeHtLQ0duzYQdeuXWnZsiWCIDxVefivMpvNz1ROjoiIYMSIEaSkpNCoUSOWL1/OiRMnGD9+PD/99BMAWq2Whg0bkpeXh7e3N1euXMHR0ZG8vDyWL1/OjRs3yM/PZ8WKFQwbNgyZTMaOHTvw9PTks88+Izg4mJiYGL744guysrIAsLW1xcfHh+zsbBwdHalVqxarVq16amzOzs7PNa+rV69SUVFBfHw8Gzdu5PHjxxiNRkaPHs2VK1d466232LhxI6+//jphYWE0btyYYcOGMXz4cFq1akVMTAxHjx7lyy+/xGg00rlzZ9q1a0doaCibNm0iICDg3zrfEolEIpFI/nNSwCqRSP52+fn5hISEEBUVBcD3339Py5YtMRgMKBQKhgwZgkwmY+TIkcTGxnLixAm8vb0JDQ2lQYMG/PTTTxQWFjJv3jw2btxIdHQ0O3bsoKysjLp165KTk0NcXByurq7cv3+fR48e0aZNG1avXs2AAQNISUlBFEW8vLyYMWMGM2fOpE6dOrz00kvUrFnzL82lquJvRUUFly9fJiIiAgB7e3tMJhPHjx/HwsICV1dXlEolTZs2RafTcfXqVcrLyykoKMBkMuHk5MQXX3xB27Ztyc3NxWg0YmNjw0cffUReXh7bt2/Hz8+PR48e4e/vz7Jly/j2229JSEggLy+vOstY1QomJSWFhISEvzQPmUxW3WO0KnBNSEjg0KFDfPbZZ4SGhtKyZUsOHTqEn58fnp6eTJ48mb1793LixAl0Oh0ZGRnk5+ezZMkSXF1d+e6772jQoAENGzakrKyM77//njp16pCXl8fXX39N7969CQ0NpaysjJCQEMrLy9m+fTtyuZz79++j0+koFo18suErhkx7k1RzOQWi4V/2tK2az/LlywkMDGThwoVcunQJPz8/AgIC2LZtGyqVCo1Gg4eHBwcPHkSv13PkyBGKiopo0qQJoihiZWWFwWDA3d2dLVu2sHr1ao4dO8aqVavQarX/o1WmJRKJRCKR/D7pf2OJRPK3qGoXApXZszfffJM1ayr7dzZp0oSoqChGjhzJoUOHiI6OpnXr1ixevBiDwVCdzdu2bRvp6ekYDAZq1apFdHQ0eXl5uLm5oVKpyMvL46effuLu3bs4OjqSnp7O6NGjadGiBfv27UMQBDp16sSdO3d48OABy5cvp6ioCGdnZ7Zv386AAQNQKv+8V27VNmaozBA/fPiQ8PBwbt68ycyZM0lJSWHKlClUVFRw8OBB2rVrh6OjIw8fPiQwMJDIyEj27t1LWVkZt2/fRq1Wo9Fo6NatG3369MHGxoZFixYxa9Ys7ty5w8OHD5HL5Zw7d46EhAS8vLyqt++2atWK8PDw6kD74cOHDBw4kBEjRhAWFkZERAR6vf53e84+eayqJdDo0aPp168fc+fOBWDy5Mk4OTlx+vRpAJo2bUp5eTmbN28mNTWV9evXM3ToUPLz8zl69Cj16tUjNTWVQ4cOkZKSgqWlJV999RUjR44kLy+PiIgItmzZQnR0NNu3b+fLL7+kTp06LF++HJ1Ox8svv8z48eOZ+f67rN28iYrWDfmmIo3zzkpOWurZq8/ku4pHrK1I5WdDLtlm/e9mlENDQzlx4gTh4eHs3r2bxo0b4+7ujslkYuXKlWRkZBAbG0tiYmJ1xlUURYYPH06tWrX49ttv6d27N02bNmXDhg106tQJtVqNvb09Op3uuX7mJRKJRCKRvHhSwCqRSP5joig+U7Rn5MiR3L17l9u3b1O3bl3Onj3L6NGjyc/Pp2/fvty7d4+RI0dSVlZGSkoKgiDg6+vLggULGDhwIImJiaxbt646OB06dChOTk6UlJQQHByMt7c3e/fuZc6cOYwZM4b169cD0LdvX/Ly8oiPj8fLy4uvv/6aOXPmoFKp/nQeFRUVz8xn9+7dDBw4ELVazfHjx9FoNHz++ee0bNmShg0b8umnnxIQEMDNmzc5cOAAJSUlKBSV9exiY2PR6/UMGzaMrKwsNm/ezGuvvUbt2rUpKytj586d2NrasnfvXqKiotDpdNXVhquCzarnqnL48GGGDh3K2bNnKS0tZd26ddy7d686G1hSUlL9vVXHbt68SVlZGXPmzMHX15cZM2YQERHB4sWLsbS0ZNSoUaxcuRIAGxsblEol06ZNw8PDA4PBgIODA8XFxZSUlNC/f38sLCxYuXIlCoUCuVzO4MGD2bhxI7NmzSIiIgI7OzuioqIwmUycOHGCtWvXsn79eh49esSY8a8R3LcnZW0aMvn8Plr274WToMJJpsZRUFV/6VBwx1TE1op0DhkfUypWLiAYjcbqgHnDhg34+/sTFRXF5cuX0Wq19OnTh/LycsaOHUtBQQGZmZl4e3uzcOHC6t61P/zwAzVq1CA0NJQZM2YQEBDAuHHjAP72KtISiUQikUj+M1JbG4lE8pfdvXuXffv20bZtW9q0aQPAgQMHWLZsGa1bt6Zz58506NCBd955h4SEBJo2bYper8fCwoKYmBju3LnDrVu3ePXVV6lXrx4bN26kb9++nDp1ivT0dGbOnMmCBQsQRRFHR0e8vb3JzMxELpczbNgwJkyYwMyZM3n11Vfp1asXBQUFBAUFsWzZMnr37k1qaupzb/29c+cOUVFRHD9+HE9PT5YuXcrBgweJiYnh2LFjFBYWkp2djbe3N/Xq1SMlJYWHDx8SGhrKhQsXWLp0afX24Pz8fFQqFd7e3pSWlpKWlsaECROYPXs29evXx9HRkUaNGqHRaHBzc2PevHk4OjpWB0lVFXuftG3bNlJTU+nbty/+/v68++67XLt2DZPJhJWVFR988AGBgYHcvXuXSZMmERgYyNKlSzGZTNyJi2PN2rXciLnGhm82UtPNjfDwcFauXElOTg5ms5nrsXe4X5THkLYdcffywtLSkiGDB7N4wULs7OyoVasWOTk5ODg4MHnyZKytrenRowcqlQoLCwtMJhN6vZ5OnTqRmJiIUqlkzZo1nD59mvv37/Pll1+yefNmZs6cSdia1TCgHQWiEXuUyH8THJpEkQrMmBCRIaBCQF9cQpaFjNLiEs5N+whnJ2cGvvs2n70ynoDunTnw1Qbys7Ix6g3V26rnzp3LvXv3qhct8vPzqVGjBm3atCE+Ph43NzecnJxYsWLF3/BukEgkEolE8nf4o7Y2UsAqkUie282bN3nvvffIycmhR48eODg4MHjwYDZv3kxkZCQWFhbEx8djZWXFtm3bCAkJ4fr167i6umJtbY2dnR0W1nZcPH+GNh26YNaXk5eTjSAIpKWl8fXXXzNhwgRsbGwAKCoq4r333qNdu3bk5ORUV9FdsWIFS5cupaSkhAkTJuDu7s7OnTvx9/enYcOGf2kuDx8+pFevXqxbtw7nGjWoUcuTx3l56A0GZGYz7y/4gEmvjK6+f9bPz4+YmBjs7OyIj4+nvLwcjUbDrFmzSE1NZfPmzWzdupVhw4ah1Wrx8PBg9+7dLFq0iDNnztCkSRPCw8Oxs7MDft22+9tA9dy5c6xduxaDwYCLiwvR0dHMmzePyzHX2H/wAG99thC/wADO7zvI9hVrKCstxcHBgfT0dL4+FMnBzES2LlrK41vxWNRwxMGvLt6ubhz4aBlWOh0BLZpz4/YtardvyaNbsWTGJaCx1uER0JAxW79iY+9XeRR7n7179tC1Sxc+/PBDrl27RnJyMnK5HEEQmDVrFnXr1kWn01FWVoaTkxPz5s0jKCiI+vXrs3v3bg4dOkSfPn0Y8XoId3xrYMSMjfD0tuwy0US2WU+mqKfybIg8uhDNtXXbsG9Yj6ZvjcUsE9harwtaZwe8+nclPvwHSrMe02L4QF5a8iGhfu0xlpbh4+tL5zZt2bRpEz4+PvTv35/Vq1ej0+k4ceIERqOR/Px8Jk6cyJkzZ9BoNP/Re0IikUgkEsnfQ+rDKpFI/pIKk8idxyZuZJspMYBGAUdXfkPzoGA+/GAuGSUiBaV6CmRKCnU1eVQsYmXpgNnSmbj468yY8z5arZauXbsS2DyIUqUt3639ErOYgr1PM0pdm5OddJv713+mdh0f9Ho9p0+fZvbs2WzatIlt27YxY8YMrl27Ro8ePfD398fS0pKYmBiOHDnCwIEDmTt3Lnl5ebi7uzNs2LA/nEt+uZkfE43cyTFTYRIpvh3Fya/m0K9XN3788UcSUlOIK8zjRnIiV27cpEf0EYylZZzqP4axQ0eg1mjQ2djQqVMn3nrrLQYNGkRCQgITJ05k7969JCcnYzabefnll9m5cycbN27kpZdewt3dnZSUFCIjI9m0aRN6vR4rK6vqcVUVQqpiMBiIioqia9eu7Ny5k9OnT5OUlIQoiixY8hlbzv1MiY0F8rqe7D4bxdHkWLaETMPC2orvLpxEn5DKst3b+ErIQu5ujT4nn9K0DJq8+hIXwtZzq7gElY0V9V4bzs3Io4gqBXcO/szU8HVc/fEQsacvcPfwSZL3/0zN4GYUFBay5sAeOnTuxOnTp7ly5Qrbt29Hp9NVV9L19PR86lw3aNCA9PR0pkyZQmBgIFOnTsVPl5ShAAAgAElEQVS3QQN26jPQiwbsnghWzaJIqrmcdLECAQE1Ag9PX+LsZ19RnJ+PXGdBo/lTKFZAYVo6HgO7knHsPHfX70DraIdlo/oUyUTC2g3ANyiQmEM/Y9eqCcHTX+fkyZNkZmayYMECXFxcmD59OpMnT6Z58+ZMmjQJf39/Lly4QMeOHf++N41EIpFIJJK/nXQPq0QieYooipxKNTL/bAWbbhm4m2smvcTMmYvRnDh9ljj/ibx2sIzPLpTz4Xkzr4bHsv1CKuUoMVSUMfHbswQMnMjpqCjiHqTTttdgvtm+h9KGL+HVrCN2zm407zaIuwc34uMfgFylxrP3ZAwouHo1mlWrVpGVlUVSUhIbNmxApVJx9uxZAGrWrEnt2rU5ePAgvr6+fP311/8yo1pqMPPRuXIG7C3jq2t6TqcauZxu4ujlu8TfuUFkbDFH7mXzramQMzevo2zggyCTk3/iItYaK0xFpWAw0iJ8JRr/emzeto26vr5YW1uj0Wiqq8/Wq1ePzMxMGjduTEBAAMeOHSM4OJjZs2czadIkZs6ciVqtxsrK6qm2NFVbgav+npiYSP/+/SkqKmLEiBF4eXlx+EwUUYY80lr4EHP3Lo+u3SLx5Dmu7/iBw/O/QK3V4OLjzd4rZ1mdfpucwkJUWQXoyoxYONihsbOlPK8A0WxGpbPAf9xQ4o6f5nHiA9z96lOriT8VpSXcOBqFWmdB/XatCJ85j/5TXsevdRD7Vn9D3cYNKS4uZvr06Zw/f545c+YwY8YMHB0d0ev1JCcnk5SUxPTp09m2bRtdunQBwM7ODj8/P66ZCsk0V2D7xBqpKIokmct4JFagRYaFIEMuCBjKK8hNTqHpgrfJPneN+DXbyboVh8xaR2FcEn7TxuDSphlNxryMaDByf+9hjAoZg1Z9ikwu5/KmCPYfP8K9xAQ6duzIhQsXuHr1Kl26dMHDw4MVK1YQERFBWVkZXl5eL+Q9JJFIJBKJ5O8jZVglEkk1URTZn2DkaLIJF0tw1P66pqV3csQkU5OSU4xMp4GiLBJ3fUzO1QNo7N0wlJcgWDoQuXgqOQk3MVaUYl3Tj03nHjBkxQm8XWy5Y2GB4O5FWlwMNs7ueDVuhbGiDP2jOzQb9QHmjFvMGzUKrVbD8uXLOXToEM2aNWPXrl388MMPdOzYkd69e1OrVi2A6m21v6dEb2bq8Qru5Jhw1IJK/utcLNr0IXnruxQVFzFpxWK8x/bAqXkTTAUlaJ0dSdr5A87Nm6KwqqwWW3z1FrranhTE3afT0MHExcUB0LNnTzw9Pbl06RJbtmxh3LhxfP3113Tv3p158+YxaNCgp86t2WyuLuZU1S5nyZIl+Pn50atXL3x9fRk4cCBhy5bx0vvTsQxqxMd7t9Gg6VvcOXeJe8dPU29oH9qt+5jrSzdSr0UT0mPu0GxAT3bPXIDZZKQ8K5cH+4/h06sTtl41ST17hXs/HqM8Nx+NvS3Z8QmYikup+8Yw0i/foEXrNpwKj6Bhp7ZorCyRKxTEnj5PUvQNxn/1BU61a+E/ZjAZW/YR9skXrFy5knfeeQdbW1sKCgqwsLAgKiqKtWvX0rFjR06cOIGjoyNQGZBXiGYuGguwF5RPFTRKM1eQJeqxRPbUcasuLTEbjDg38UNla839HfvJuXuP5svnYhvYgKSIA5Rn52Jpa0P9wT0589EK8mITWNy+H7ZuNchLSycv5i46F2eUzvaMHz+eBg0aULt2bcLDw/Hy8uLnn3+mqKhIqgYskUgkEsl/ASnDKpFIqsVkmTiabMLDCtSKJwriiBBfIEfj4Ych7iQqGaSXCtg17kqXLy9jLCtEoVJRcP8qt88eRq+vwNrRlfzsRzw89i13bt8iLTaGrOQ4fJp3JDH6NL6tenDu+7U4eNTBp3kHmga14ta1K8x5fx7NmjWjtLSUc+fOMXbsWLp3707z5s2ZMGECDRo0wMLC4k/n8unFCu7mmnC1fDpYBZAplTj5t0Wfcw/blnW5Ou1DVNY2uHfvgK52TR6dPEPCjr2YysoQ5HKuL1pOrR6d6XJoJ/K+XTh5/SoVFRX8+OOP6PV6Ll++TFlZGYsXL8bPz4+UlJTqYNVgMACVwVtVsFrVyqbq33ft2sXjx48BGDVtMmvDN3FMn42thxvRW/dwe9Fa7u/Yj9lgxK9vV7xaBBI4czyXIw9iWa8Wp3ZFYuVbG6taNRFkMuwa+ZJ88jyNXhlIQMgQynLyafrGK5Tn5pNx4gI+w/rSMnQaJdl5GB2sSI9PoDS/AH1ZOVd/PEwNHy9OfrcDgD7TJlDb2YVaowdhYWFBq1atsLW15dKlS4wbN47o6GiGDBnC6dOnWbRoUXWwWiXBVIoREaXw6zUwiWJ1ZvXJYFUvmjEIIkGfzGJ7nY7YNfLFpmE9fKeO5sq0TzCX6VE52dNw9usUpmfi3aMDNdsGoXWwoyK3kDazJmLt7ISlrQ364hJ2frMJURS5dOkSgiBw8OBBQkJCCAoKIjw8HAcHh+d6X0gkEolEIvnnvLAMqyAINYHNgAtgBtaLovilIAgLgNeB7F++9X1RFA+8qHFIJJLnI4oih5NN2GlALnu6emt+hUih2glb19pk3zyFsX5vdHZOCPb9UVkJODfpjFPjTqit7MlOiafD4Ne4vWU+107+hFtQbxJORnA34QKtBoZg5+pJ37cXE3fhCJ4Ng3j8MIHjGxdTXlxAw56jMBZms3TpUrKysvjxxx9p3bo1kydP/ktzySg2E5VqxlELgvDsupzaxhnHJp2I3fER9sGB5F6I4faytQSHLcS5ZXPK0rNI2hWJ77iRPDx4nMwzF7CqUxvrmh5oarpwz8IWX19f5HI5n3zyCVZWVmzcuJGQkBCgsoDS7du3CQsLo0aNGkybNo0aNWpw79493nzzTQoKCqhbty6tW7emT58+rFy5EqPRyPiPPySusQcKtZqlzXqisLRAbWNF0pHTdPr4HS4sXY9MoeDh+atcW7MZQ2ExOWkZmOx1tPvuc4qu3CHndjyPY+5iodNRmJaBc2M/6vTsQKcl73P9u+9R29tiKq+8Z7T2gK6VvVRtbSgpKCQj6QEtB/djwOy3mFSzMRWlpagtLDCbzagd7ZjwwXt8+eWX3Lp1C4PBwMSJEwkMDPyX1+KeuRT1b9ZGc0U9IiLy31ybYkzIEKg9qDvKt0JpH/kVkXW64tKlFY/PX+Pe+h20WP8R7h2DyTpxifi9h6n/Uk90rk7c2fUTt46cpOukMfz0xRo6jBnO1UPHaNiiGZnJKXh6euLn54enpydvvfUWarWamTNn/qWfK4lEIpFIJP/zXliVYEEQXAFXURSjBUGwAq4CA4GhQLEoil8873NJVYIlkhfvQaGZZVf0uOue7UV5I8tMZqkZWVEGN7eEUlRUhHu/GRQ9jKPs4nYs7GvQeNznKC1tMSFgMEPGno+JO74De59APPq+jTIvgdTD6/HwbUqfqZ+i1GgB+OGLGeSkJfLash8QRZEHeQYaZh7At6YznTp1+rfmsiamgvDbRlws/7inZklZEucXDUWs0NNw6WLSI3+k8PwFnIIC8ezXA5lSgVPzpuTeusvPw8Zj0utpt34ZeUlJ3P18NRYyOVEnT5KRkUG3bt2AyqBfr9fz/vvvc/jwYV599VWCgoKwtbUlMDCQb775hrS0ND788ENOnjzJyJEj0Wq1+Pn5UY5Igxkh1Pf3Z3G3wTxOSWP6w8sc+3QFN9ZvY8DmZWTfiiPm2wj0hcW0nz8NjZ0NBybPw7FrK8wlZTSdMZ7HV25xZf4yanVvR5/locTuPUTuvWS8X+nL7b2HiF+3A+s6tWi1bC4F95K5vX47Hm7u9JkYgn/HttXn56dlaygrLOLl+bMBOBmxF61CwRcvhxATE0OLFi3+9DqIosi6iodokT2VYb1pKkIvmlE9ccyMSLq5AgUyBODG8o0UFxah1FkgGoxY1fHkwa6D2DauR503XyX/1GUefhdJQfJDSnPyUFvrKMvNZ+Keb/Gp7cX1Qz+zbe5HuNeuzd4t29i6dSsxMTGkpaUxYsQIpk+fLlUIlkgkEonkf5F/vK2NIAiRwCqgDVLAKpH8r3PxkYntsQY8rJ4N8o4/MKKWg0wQyM3L5+6+NRgz4zEU5+E1YDp1mnVAFEWKHsaSdmY3Dy/9hM7ZE8+eEyiKv0jhwzgMpYUMHPc2dYM6P/XcJzaHoVRraDtsMmaTifRSGaP9lTStIf+35/LG4TLu55mw1fzxXQ9Gm2IK7W5zOrgXzt27YigqotGksbh3aPXM9xbcS+SnDv1QWOkwFBahtrPl+7276du+MqCuKqQkk8mIjY1l5syZ7N+//5lWNT179qRfv35MnjyZ2NhYXn75Zdq2bcsnSz5n0NsTyXuUQenjXAwVegL7dKPOB5PIvRnHybmfo7S0oM+6z9jUZhBaRzvGnNwFQPz5yxjqe5Kwdjsl8Q8oiktCZW9Dv31f4yBTkZ+Uyq3tkSScPE9pTi5Fiak0nDqG4pQ0KvKLqPvWKHp16YqHTPvUWPVlZUzxbka/WZOJ+m4HOgd7Bi9byKKWPZ/7OlSIZtZWpOIkqJ46ftlYgAoB2RMLI0ZRJFOsQPlLNraivJyIel2oP20sN0NX4dIxCLfeHck6cxVkAhobK9QGM7mxCVi518C+rhcXwtbT5OV+9Bk/mtPhuyjIy+XxvSTS4u5Xnqv4eOrVq/fc45dIJBKJRPI/5x9tayMIQm2gKXCRyoB1iiAIo4ErwExRFPN+5zFvAG8Az7RNkEgkfz+DWYQ/WL8yiVAVWsi01tQYMAeFsQSzwhKrX2IRQRDQ2ruhsXfFb+IanHyaAODetDMVJUWIGh11PZ/9yFFbWKG2sKwM+ORyQMT4H66j6c0AImajEZni9z/mRJkZTQ1HPEYMwaZZU2r07oW99vczsjZ1vfGbMp7M85cJCJ2NQ2AAzZ28MJvNCILwVHuaxMREHBwcMJlM1Y83m80oFApGjx7NV199xeTJk0lMTMTe3h61Wk2C2kTvz+fx6PBpagc0JOFKDMfWfUdtJuHU0JfGY17m0aXraGysqNOzI3GRRzg2+1Myom+idnFC3bAOPuOGILPQkPTlZjRO9gDkJ6eic3Wm7ftTsO8YhNbXi5uL1uAc1IQms15HqbOgDBOm35mzSquly/hR3DwWxZvfrqJ2YGNyMfyl62D+nR8oURQx8+vPU/Xx3/xdX1iMW5+OZEVdxtLTFY2rM3UnDCf/VjypkcfwGT0IZbkRhVZN1o1Y8hNTqdW1Ldn3knicnEqTHp1IvHkbpSAjJaVyS7AUrEokEolE8t/nhWdYBUHQAVHAJ6Io7hEEoQbwmMrfTz6ictvwuH/1HFKGVSJ58a5mmAi/8/sZ1qhUEyCilAkU6UUyS0XUctCbwE4D9k9lMkWK9GCjFig1iGgUAnqTiEIm0Nbj2axpVbXcKmlFIiGNlDR2+vcyrKIo8vbxUmKyRBwtZFQUVhYzUls/XQzIaF2Cvn4m5nIQBDlmERwtBOR/sIu4apx6wYzCKLLC2QdHhfrXcaelUVBQwIEDB7h58ybfffdddUD75PwaN27MhAkTePDgAdu3b+f9uXMRRvdGLZOj/mWLrCiKvNeiK3XHvUztDq049cESvLu1I/CNkZhNJqLXbSXhcBQdFkzHoFVzavFqHAL88Br/MueHT8ezb2fyLt/EkJFD50VzcG5Un3zRQKloRm4WEZ7I/JZhoqncGnfZs9tjzWZzdSCe9ziHtAcP+LR1n2eu2R8xiGa+qkjFkacrBF8xFqD8gwyrQhQwG4w8OBSF4OqAITOHq7MXI1ep8Bo1AJ23J/Grt2Au19PhvSkcfXs+/iMGIJPJCHh3IkUHz5J04AT5GVkM/GwuQYHNGKBy/tOxSiQSiUQi+Wf9UYb1hVYJFgRBCewGtoqiuAdAFMVMURRNoiiaga+BoBc5BolE8nzq2MmQASbzs4tYnlYC5cbKP2sUldkx0Vy56mSpfDpwqTCBtUqgppXwS6az8pj7H3QQeTKQMZlFBAG8bP76R5PZbK7+cy9vNSW5WVwOG8Op97uRe/ci8Gu/UwB5uRqxQo6gFDCLIJfxh8Hqk+PU6yvwVGuxk1emltPT01m5ciWvvPIKZ86c4ZVXXmHfvn2kpaUhk8mqx5WSksL9+/fZuHEj6enpHDp0iJycHFr37o5eJqL85bznZ2SRmZjMxG++xJyRw4/j36FmmxY0CRkKgEwuJ3DiqwzZvQ6Xpg1x9fXBITiA4gcPKbgeS8aJi6TsO45nmxYM//FbnBvVB0CNDDNPB6smzAgI2KH83TnLZDLS7yWw55OlfPXaVNYPGf/UufgzSkGGraCg4jf5UxtBSQXmp47JBQEBAVEAuUqJe4cgTGXlJGzeS7uIFdgH+hG3MpyKvHwsPF0xFBRiKimlRuMGIIoUpKRx9PX3uLZ1Dz2mjGfu4V04B/jhLlMjkUgkEonkv9cLC1iFyt9ovgHuiqK49Injrk982yDg1osag0QieX62aoGAGnKyy54NWF11lR8VJrEyy2qhgHIzqOWVX78SKTOCl41ADUsZcgGMvwRsVc/xrzwug2Y15Fipni8gAjAajdVbck0mE2azmZt7vuT2h23JvnseB782PDi5lfLcjKceJ+gVyAo1CDIREfGZwPu3RFHEhIhcpaK/1oG4u3dZtWoVU6ZMYdmyZaxatYpx48bh6upK9+7dWbx4Menp6cTFxbFmzRrmzp1LREQEzZo1Y8GCBdy4cYP+/fsTtmQJ+elZv2yHhtsnznDx+/3UauzPyND3GHZ6F0Fvj0OuVFYH3DKZrHqrs0IQMGXkoHargVNwU1ptX0r3/etpPnboU+PXCHJkCIhPBI8GRBxRYiGTPxXwVynKyWXNa2+jVKvo9u5UMJgIDw9/7msDUFOmofQ3m45dZCrM/NqbFioXQXTIKM0v4MSYWSTs+JFHe45SGJtI8tb9PL4Qg6WnGy492uHRsz2Wrs7c2LKXtnOnoi8uIeP6XbTWOkLCFuLToinmX85VfbnlXxqvRCKRSCSS/11eZIa1DTAK6CwIQswvX72BzwVBuCkIwg2gEzD9BY5BIpH8Bd1ryxGo3Pb7JI0CGjjIKNZXBq3W6sr7Wm3VUHU3oohIQQW4Wgo4W8pQyKC2tUBWKdSyFtAo/nVAWG4UMZihQ83n3wosiiIKhQJBENi3bx/jx4/nzJkzfPH5Ymq6u6Gt2QivQe+gtXPhwfHN6AsfU5D86xqZMssKk0GGUiWiVvz+7REm4y+pZQEqBDP5ET/Rv5YPL730Et988w0lJSW4urpy9erV6gBsyZIl5OTk4OXlxcCBA5k9ezYHDhygXr16CIJQHaQtWrQIs1zGN0NfZ/8XqwjtNIBj67/Dv1PbynuCqcxQlpqMz2zD1ReXcCFsPd+1f5mi67G49euECTOufTqgRf5MFlQAdIIc4y8Bq+mXO0xr/1JsqWrr791T58l7VBncZ9xPoqZ/fTrNmEjTVi1ZtnQpy5cvf+7rA+Art8T0mwxr0rEzyMv0GKhcaKgoKib7zj0sZQrUttakHDiJIJfj0SkYY1EJZelZtN+7Bvtm/uTfiMO5RWO0tjbkJ6Vg6epEzxULGXo6gnHrwnCr6wNAAUbqyizQCf8jpRokkv+v5ObmkpSU9E8PQyKR/H/ihf1PLoriGZ6tqwEg9VyVSP6XcrGUMSlAxbrreor1Io5aUP6yT9bTSoYoisRkiZhEgWZOIumlAoUV5sotwoKAu06Gv6MMmQDFehGFXCCwhhy5IGIyi8/0d61SYhDJKRMZ7a/Ew+qP19GqAkL5L9lIQRCIj49n0KBBFBcXM3LkSL7//nuaNm1KeXk5irJScvMKKNUbSf5+CQkH11F/yLvoXL0pRUNRsQZXKzsUXnnoMaNGhsAvAaXZjEyhQK5QYBJEys0msnfup3Dz97QMCqJVq1bs2LEDKysr7OzsuHnzZnUBpjVr1nD69GmcnJwYNmwYNWrU4MqVK+Tn5wOgUqkQRREvLy+mL/4Yu9PHyL5wjZfmzqBR1w7V8xUEAW+ZBXcUIuWiGe0TH6kKjRqlzpIeX4biEuBPhlhOASbkgI7fD/otBTklookK0YiByuyns6xya3NyzE2OrvuO2yfOUL9tME17daFmw/qkxd6jyKSnq6IG3q++ypuTJrF//3769ev3XPeyugpq7AQlxaIRnaDg9JZdrHt9Gr3fewuv2a8hU6iIHDOdivwiGo8eTO0xg7BrXJ8H+4/TaXMYOu+alKZlYu1bG0GpJGbWZzSdOxm/QT2xmuiEjYcb5aIZGytrHGSVW5vLRTMmRFoobP7l2CQSyb8nJSWFZcuW8d1337F//366desmtYmSSCQvzAu9h1Uikfz38baV8U4LFW3c5eSWVxZBSisWSSs2o5TLGNtQyYzmKvydlPg7yLBVC+hUMrxsZDho4VGxyMMiEbkg8GoDJcs7q+nsqSSjBB4WiZQYRAxmEb1JJK9c5GGRGb0J3mispLnLH6+hVQVHVcHquXPn2L17N+PHj8fDw4OVK1eyefNmDh06ROvWrXn48CFejpYofpyD6cFl5Fodcisn8goKyDZq0allTA1UsbmpM2/oXNEJCh7FXKfEUI5RDialjArBzJl3PuBI31co2vUTnQxyOrRqTXJyMrt376Zr1660adOGiooKjhw5QqtWrdi8eTO5ublMnz6dzp0789FHHzF58mQCAwO5du0aKSkpT83LVqHGp20Q/d+ZWh2smp+oMKwSZPjJLLEQZJSIJspFc+UWaIWCZhNG4hzgRxlmdCiw/+Ve1HJEfq+enmAGrVlAL4CToKKxoEMQBH7esIXPB7xK/bbBLI+9QPMBPfn5my3Y+tRGZqkhf9N+vJU6CgoKaNq0KZs3b66+Jn9GJgh0UdpTIpoxiSJypYL2o4Zy7+R5fh72NmX6cgKmjEFrb8vJ+WHwMAutvQ0aN2dUNlbUHzMYQ34hx7qFkHnsHDa+3tTr1IbGIwfh1aUt5aIZOQK+MgsUyCgTTRRipK/CCSeZ6k/HJ5FI/pzZbH7qtgEXFxeOHDmCp6cn0dHRlJeX/4Ojk0gk/9dJe6UkEskzHC1kvFRPRk8vBalFZipMoJSBu06GtfrZjFpOmcj9fDMlBhGVDGpYyqhj+2sV2EH1ZHSupSA608T5RyYKK0TkApxeNZ2xI15mVL/O1ZncPyIIAmVlZYSFhREZGUliYiLffvstu3fvplGjRgwbNgytVkufPn3w9vYmMDCQI0eOIJfLGTduHFu2baM49wE+pbdolriWcUP7Ut/XF4AuShs8C0sIu5mEuZYXpZYyzk59j9xrNxCMJtxrOHPlg0XoOnbk3Llz6HQ65s6dy4gRI/joo4/4+eefkclkqFQqpk+fTmBgIOfPn0elUhEcHEzfvn2pW7cu69evp1OnTnh6elZnJu2FyiDzyV6uVfezVqkMWnUUYSLDXEG+aACx8vEC4CQocZarwWwmHT3liOSIejBXfsiLoohJqCxo5KBQ0aHUgh+/Dee4iwNBQ/rTZtQQDq76GpVGjSiKeLRujmbvj5z/fj9hi5ewZ/V6OnbsiNFoJCQkhEWLFvHo0SPc3Nz+9GfJZDLhLtcQKNcRbSqiorSMWz+fxqGmO8UZWWzx687wo1vosHoh21oO4PSnq8iNuYu1T20qMOHQsQU17yejsrHCd+Y4NMhwREmZaMaMiE6QU09uiUkUyRIrUCFjkNKZWnLtn45NIpH8uSfbdqWnp2NlZUVGRgbBwcHk5uYyf/78f3iEEonk/7oX3tbm7yC1tZFI/m8xmUzI5XImTZqEl5cXs2fPfubfgepsKsCdO3dYsmQJ+fn5BAQEsHPnTjp16oRWq2X9+vX4+/vj7OzMoUOHCAoKolu3bixcuJAaNWqgUqlo0KABffv2pbCwkNu3b2NnZ8eyZcueeZ1de3Yjt7Tg/RmzMJtMjHr1Vc6dPYsoiuTm5mJpaUmrVq04ePAgMpmMBw8eYDAY6N+/PxkZGXh4eKBWq+nWrRtnzpzh1KlT2NjY4O7ujtFopHXr1kyePLn6F0BRFAnXp6MXzVgIz3f/rvGXAlAACgTkvwS/2WIF7RT2BMitiDUXczglnvvx9/BpH4yNoKClwoat8z9jV0QEw4cP50Z8HM6B/jR6eyw/LfiCvNRHjPxmKc6igsLD59i6bBU/Hz+OQqHg+PHjdOjQgZMnT/LDDz+wfPlyFH/Q47YqEyN7siKxKHLU+JgDZ07z/cTZfHLhMOd2/sA3b75Di0F9GL91DUd3fM/1yIPc23cMtY0VM5LPo1IoSc/Owuxgg0oQ0IgyigQTNoISO0FRfc5sBAXN5NbUlVugec7zKJFIfl9YWBjOzs6MGjUKURRJTk5m5syZZGRkEBAQwJgxY2jevDkdOnQgNDSULl26PNUGSyKRSP4df9TWRsqwSiSS/xG3b98mISGB/v37I5PJMBgMaDQa3N3dn/q+J+9RjY2NRS6X8+jRI6ZPn05OTg7NmjVDqVTi4+PDsWPH0Gg0qNVqLl++jEqlwmQycefOHaZMmcL06dPZu3cvY8eOZd68eQDs2rWLkydP0qNHj+rXOXLkCJ9//jmjRo1i586dqNVqgpo1QxAEPGvWxPvVV9m5cye3b9/G0tKSS5cuIYoiFRUVNGnSBKVSSWZmJr169eLSpUvExMQwZcoU2rZtS1xcHBcvXmTs2LEUFRVx9+7dp36pEwSB5nJrDhseo0X2XC1jFIKA4jclAgyiGRkC9eQWiGYzfnIratdoQIehExm8eDE7duyg98KF1PH2JiwsjMDAQAYPHkzmgxRebdOZwe8uoH2LYLqlVtDAx5PM4HZE1z/GnTt3aNy4Me7u7nTp0gVBEJg9e/YzwWpiYiIbNmzg008/rZ7ftWvXuHDhAps2bWLSpEn0GzCAyPM3KMovYJpfa8x6A66+dSjIyOL811voPmwQLZoGEhp1kbavvNtTDx4AACAASURBVIyvzJIKmQydsxt1ZFqCFDZoBDkiIiWYMIgicgS0ggwnQfVUX1eJRPLXVQWd9vb2fPjhh4waNQpBEIiIiGDIkCGMGDGCHj16sGTJElasWMHAgQNZs2YNXbp0kYJViUTywkifLhKJ5IXT6/VcunSJiRMncvfuXQRBQKlUotfruXjxIqIoYjAYgMqsXHR0NL6+vrRp04a5c+eyfft22rdvT1lZGenp6dStW5fs7GwePHhAYmIiRUVFKBQKTCYTKpWKli1bsmPHDpo3b05hYSGRkZGMGjUKLy8vRo8ejSAI9OjRg+joaPr27cuoUaPIy8tjy5YttGzZktLSUnJycvDx8SEpKYn09HSio6PR6/UUFxfzySefEBISQrt27SgoKCAtLQ2dToeHhwepqanUqVOHmTNnMnDgQFxcXDh16hT29vaEh4fTpk2bZ86Pr9wSF5maQoz/1vkVRZFc0UCwzBqdoKgOxC0sLMjJyaFnz57ExcVRXl5OSEgIZ8+epWvXrsyYMYOgoCAOHziIu60DHdq149PQhQiCgIuLC+vWraNx48YA2Nvb8/HHH3Py5El69+5d/dpmc+U9tS4uLqxdu5br168DMGDAAMaNG0dqaipvv/02V69eZfnSpcwdPZ6ynDycPT0Ys2MNc64do9GAHlz96Qix5y7h4uvDorgL9F7yAbkKMypB4CWVMwNUzrjJNdjLlDjIVHjKtNSRW1BbrqWGTC0FqxLJf6BqV0tV0BkSEgLA/v37gcqtwAcOHKB79+6o1WrmzZuHm5sbISEh3Lx5k3fffZdRo0YRFxf3z0xAIpH8nyZtCZZIJP9j5s+fT3JyMi+99BIDBgxg37591fehymQyrl69SmZmJlOnTqV27dq88cYbzJo1i7S0NCIiItixYwfHjx9HJpOh0+lIT0/HbDYjCAJvvfUWgwcPZs2aNWi1Wuzs7MjNzeXy5cuUl5fTtWtXXFxcmDBhAtnZ2dSvX5/58+ezZMkSgoKCOHXqFG3atMHW1pby8nJUKhUajYb09HQ0Gg0PHjygqKgIb29v9u7dS15eHi+//DKZmZkMHjwYjUaDVqvlxIkTtG/fnl69ehEUFISNjQ0ffvghSUlJvPnmm7Rq1ep3z02O2cBOfTpKZFj+hS2toijyGAMeMjUDlTWQAZGRkURFRZGdnc3NmzfJzc0lODgYGxsbNmzYQKtWrUhLSyMlJYWFCxeybds2Nm/eTO3atYmJiaF79+7Vz1+1ffv3VJ37qqzw+PHjKSgoYNeuXTRp0oSUlBQOHjxIcHAw165dq854t2/fHkdHR7oN7MelWzeIPneBrnOmEDC0HwoEHGRK3AUN3nItroL6ubLOEonkP3f+/Hlq1qxZXchuy5YtXLx4kTfeeIOMjAwWLFhAYGAgAAkJCdSpU4eDBw9y5MgRhg8fTsuWLf/hGUgkkv9mf7QlWL5gwYJ/YDh/zfr16xe88cYb//QwJBLJnygqKiIiIgK1Wo2joyPwayVZQRAIDg6muLiYsLAwOnfuTFpaGnq9ntq1a7NixQqmTp3K+PHjKSwsJCcnh5UrV5Kfn49Go+H8+fOEhISQmprKvXv3KCgowNfXl+Li4ur7V2vWrMnDhw9RKpWcOXOGa9eu0blzZ1xdXcnNzUWr1fLaa6+xY8cOzp07x9ixYzly5Aiurq4EBASQlpbGuXPnqFWrFidOnOD27dukp6dTWlqKi4sL1tbW1KpVi6ysLNq2bYtcLkev1yOKIkeOHCEzM5OwsDDGjRtHvXr1UKlUCIJAq1atGDp0KDVr1vzDc2chyKkp03DHVEwpZjTPsT3YKJp5LBrwkGnop3KmKC+f0aNHc/HiRQYNGkRmZib9+/ensLAQa2trHB0d6d69O9nZ2Rw7dozk5GTu3btHnz59aNeuHa6urtSpU+ep1/jtNr8nFzllMhkpKSmsX7+ecePGER8fz7Vr11AoFPj6+pKbm0uTJk3w9fXFysqKhIQELly4gEKhICgoiPSUVBrXqcfWjZsY3Kw1LRW2tFDY0FBuhadci5WgkIJVieQFeOONN7C3t8fT0xOozKT27t2buLg4tm7dSmBgIP3792fevHn07t0ba2trcnJyqFGjBh4eHkybNo19+/bRt29f/Pz86NmzJx4eHv/wrCQSyX+70NDQ9AULFqz/7XEpwyqRSP5j+fn5zJkzh+joaJydnamoqGDChAkMGTIEqMzSCYKAXq9Ho9HwzjvvUFxcTH5+PteuXavuoXr9+nWGDx+Or68v3bp1Q6fTYWVlBcD9+/epV68emzdvZujQoeTm5jJnzhyWL1+OSqXi8ePHNGrUiK5du3L06FFKSkoYMWIECxYsQBRF/P39KSkpYf78+Rw9epSLFy/SunVrvLy82LdvH9OmTft/7N13fE33/8Dx1zl3ZE+yJLFXiMSIooLaoWhV1Yr55WvXrBpt7do1iqrWjD1CkZq1V2ILCTEiJLJkz7vO+f0RblE60f76Pc/Hw0Med5x7Pif3ntz3eb8/7w+BgYHUqFEDBwcHtFot+/btY/DgwVy4cAGtVounpyft2rXj9OnTLF26lL1797Jz507mz59PdHQ0nTp1+svHMls2csSQTqyUjwYRK0lFoVHAKBUt66MWZTQYyNcISLJMfbUT4d+t5/TJk9y4cYPCwkKCg4P55JNPmDp1KpcvX0alUrFz506Cg4OpWbMmPXr0oG/fvpw9e5b9+/fjU80XHRISoEUoWo/2uUDxye/w6QC2sLAQa2trXFxc6N69O3PnzqVu3bqEh4fTtm1bNBoN8fHxhIeHA3Dy5EkGDhzIjBkzaNOmzV8+VgqF4veTJAmTyYRGoyEjIwM7OzvUajUGg4EePXrQr18/mjRpwqRJk8jOzmbs2LGsXr2aEydOsHv3brZt28bmzZu5desWzZs3Z/To0bi5uf3dw1IoFP8iL8uwKnNYFQrFnxYVFcXmzZu5dOkS3333HQcOHCAsLIwmTZpw4cIFMjMz2bVrF507dyYjI4PY2FhycnJwdXUlLy+PCxcuEBcXhyRJbNmyhZiYGOzs7DAajeh0OgoLC3FxcSExMRG1Wk1sbCxHjx5l2LBhGAwGvvzyS4YNG0b58uVxc3MjLCyMoUOH8uOPP3L+/HlSUlLo3bsPmZmZ1KlTB5PJxNGjR4mIiMDX15eTJ09Su3ZtHj16xLhx4xg8eDD169dHFEW+/fZb9u7d+0wpsLe3N9nZ2fj7+zNgwACWLFnCzJkz8fPzMwerf/UioL2gpq26OA0MbmSkavkpUceptEI2rdzEdxNnc/KRjtOpoEnW0iLbFl+jlnlz5nDjxg02bdqEr68v06dPp2/fvhw7doyUlBQKCgoIDg7m/v37jBs3jjVr1rA9NBQ7J0d2Jdxkqe4B3xc8YJUugW918azTJ3LDmEtadpZ5v1QqFaIosnv3bsaOHUtISAiFhYV07drVnGUGmDZtGra2ttSoUQMfHx+ioqJo3rw5UVFR1KhRg3Xr1tGmTZu/fJwUCsUfI4oiGo2Gu3fvotfr8fPzY+fOnWg0GvLz88nOzgagZ8+eyLJMZGQko0aN4scff+TatWt8+OGHLFu2jPDwcObMmaMEqwqF4o1RugQrFIrflGeQSciR0ZlktCp4dPc6MyaNJz4+npYtWxIcHEzjZs1Yt3snXbp1JaDOWyyY9xXBwcFcuHgRB0dHmrdsSVJiIo9SUxFFEVmWUavVqNVqkpKSEAQBOzs7Ro4cSVJSEmq1mry8PM6ePUvx4sXZvn07rVu3Zu/+gwwcMwnHYi5kpqXyzTffkJqaSo0aNbC0tCTHIPBt6EEWz5qEtXt50m5f5HTCELJvnSMpIYEdO3Zw9OhRBg0aRG5uLh07dsTT05OMjAyOHTtGfn4+LVu2BGDTpk18/fXXLFiwAJ1Ox4MHD7CysmLcuHEMGzbMXAIny7I5I/lnS1gzJAMJso4Mg5GjcSYS0lXY6BzwtXJA1kjs/WoxRl0hgdXfJystk3HzR+PkVZ6JMxcwefJk5s+fj0qlYsaMGahUKkaMGIGlpSWjR4/G09OTGTNmcPnyZZYvX06qLo/VuoeUbNOEn44f4+2G1dEJErKp6I9CVEQEkyZ9RfrdOD7s1Z1JA4eRmZFB3759uX//PiqVCpPJxKpVq5gzZw5btmzh1q1b5rnC3t7eHD58mCNHjmAwGMjIyKBKlSoA+Pv7/6XjpFAofh+j0fhMN+/bt2+zc+dOQkNDWb16Nb169SIkJISgoCD8/f1JSkoCoEyZMkRFRVG7dm1UKhXjx48nISEBX19fihUr9ncNR6FQ/A9TAlaFQvFSD3MlTiWYOPvQhCRTtJCKIHPk628pW7YOG0J2kG6Tww5jOkJwS778bimHPDXcXLGFtBvXCWjVjPptR3F8ySpc/9uXvDlzsfDywr5kSRJPnkCv11OtZg0M+QXodDri4uIoLCykTZs2zJw5k+bNm3P//n1KlCjB+XuZWDgUJzzmIfdCTiCVfwd9ylYSk5Ko6FuT/gMHszNGx8RhfSk0QsVPd2PKSiJhchC3j+8EwKqYJ8W9y3Dl5l0KCgrM82R9fX3NHXCjo6Np0aIFixYtwsLCgnnz5nHv3j1Kly7N0KFDCQoKwsPD45nj9FeCrwdSIeeMWdyXCtGbZG6kS+QZ83l4YhdebweitffBOk2kRvOOpCXcI3TqYNRaCzzLVqawII+Jnw7niwUr8a9+hOXLl/PJJ59w69YtHjx4wMaNG4mNjaVs2bI8ePCAJk2asGjl98Q6W2IrFVLtiyGYBCjAhFouGsOGoO4knruCU+VyuPr5sD1kA1FXI9mxYi3BwcHs2rWL5s2b8/nnn2MwGIiIiKBhw4bExcWxadMmevXqxciRI5k7dy6RkZHMnDlTCU4VijfkSVf09957D3t7e+DnwHXz5s3Mnj2b69ev4+XlxejRo6lYsSK3bt2iYcOGfP311xgMBipVqgRg/n/q1Kl/23gUCoUClDmsCoXiJc4lGlkfbUQlgIs1qMWioCPh5mW2zxxCu693k1whE7WlDmdLDdo8HeubdiL9dhyOVSuQ+yAR69JeuFQPIOtaFBUHd+favG9AEMi4GIlnyxbk3rmLg6szlWv5kxZxhQvhEZQuXZqaNWsSExNDkyZN2LhxI1n5ekyCCmf/5hgexZIXH4OL3ztkxl7BUJCH5wefkbx3AbXG7SAvPYnr84ORJQMOZfwx5GYiGfXYlfZD4+xF/P5v0VrZYIGe3JwcnJ2dqVWrFp07dyYqKopr166xfv16GjVqhI+PD1euXMHV1ZXVq1dTqlQpBEF4JqP6Z8myzAVTNieMGVihwkoSOZ8skWOAgphrbGn3LpU7fkS92VPR6kXODB1LtQbtuPDjBloPmYYuP4fze0JIvHOdoC93UzbzIjOGdOKrr75i06ZNaDQa2rdvT5MmTQgJCeHw4cMkp6fhVLsa70wfQ669JVaIqJ4bR9jA8URt3s3otKvk6Ar56T+fYsrM4ft9PxC9ahuTJ0+ma9eueHp6sm7dOipUqMCoUaOoU6cOjRs35vDhw0DRvGZHR8e/dIwUCsUfEx4ezpIlS2jXrh22trYsXryY6tWrM3r0aPLz86lZsyZhYWHUqlULgAkTJvDw4UNWrVrFyZMnzRe5hg0bZq40USgUijflZXNYlYBVoVD8wqVkI6uuGXCzFrBQPxvQZCbHs+7z7tRcPwe1qwMmnUgxS5FiViKXV23l/MpNFGZkImi0VJs9jgv9x2FbrhS+g/sS8/16cu7GkZ+UTOmObbm/Yy/GvHwcS3tjodViZZKx1GiRZRlJkrgefYPqbfoQtT8EmxLlqD1iFbbuZUEUyb53jWshn5ObEIPTWx3IyUxDzkvDJ6gXurR4bm6bQ/X+84neOA1Ra4GpMB87bx+y4q4jaiwJeDcY+dYRrkdeJS0tDYCCggLs7Oy4ceMGJ06coFq1atSsWfMXnXJfhUhjDgeNaRRHi1oQuJ8jcf2RhINF0f2b3g3CxtWV0k2a4dWqKbHbd2GRYsDJxZu0+LuU8qvLxi96Y+vsQoPgkei1TpxfPppmTZvy9ttv8/HHHxMbG4uHhwdarZaTZ85wvqw9BQ7WJMl6bF7ShViWZWbZ+9D90EYy78UT1n8s3vVr0/bzEZSISmT5vPl89913BAQE4OLigru7O9euXWPJkiV4enrSpUsXNBqNklVVKN6AJ+fKJ0tP5eXlERISwvHjxxEEgb59+7Jo0SLKli3LwIED2bRpE3fu3GHVqlUAZGVl4enpSXh4OFWrVqWwsBBLS8u/c0gKheJ/mNJ0SaFQ/C75BpmN0UZcXhCsAqjUGqz9ypJ46gxakxqtIJNeIKGXoHij2siCjHuT+ph0elL2HeWtrQvJj0+keJ2auDd8G5NOh6hWc3d9KKZCHWpra9BYkRxzhwJBJisrC5PJhMFg4K13WvEgLhaPt96larfJOJWrgcbGAY2VHfalffGo/S4mg56ch7dQWTuge3CNy0sH4VyxNlbFvbgTtoy8pLvkP0qgID2RjFvnsXQojrEwl3O7VpJdKJGTk0OfPn3o06cPAQEB1KpVi4sXL9K7d28CAgIQRRGTyfRqj7Fs4qgxg2JoUD/O2N7NlLDW/PyY+uM/w5Cfj1O5cpz8ZDw25byxKueNZ6XqpMbFAPDR599Spnp9Diz9gqs7v2HC8h9IT09HrVabu37GxMQgiiKedWsgOdiRIhuw/pUlcwRBoHxQY0KadObktEUUq1iWkq0bsTZ4KHnFbbG0tGT48OF88MEHuLi4EBgYiJ2dHePHj6dnz57mpXwUCsXr9WQdZJVKRWFhIZmZmdjY2BAQEMCtW7eoWLEijRs3ZubMmdjb23Ps2DG6du3K1atXuX//PgAODg4sW7YMFxcXZFlWglWFQvGPpASsCoXiGVdTTeglsHpBsAqgcnVEU9adRyciMOYXFHWPVYkkJTwi+V4cpdo0xWg0Ufztmtzf9iOFD5JxruNPypXLlOv8ASWaNMS2lDfIMpWH9uH9A7spEfgOHn7VyExOxSCZKFGiBAaDgRvXrlDcrzF1x27Cs957z+yHxsqOiu1H4OTfHMHaCd29C2hL+CDaOHNz+xzKtx1MiXrvYeNehnqfbuS9Lem0XB5N4JS9NPnqNFaelSm0cqFbcDDXrl0jNDSUYcOGER4ezkcffQT83PH3SfbiVbllykdCRiMUnYLTdVBoAs1TZ2Svt+uTefcObtVrUKxSRU6O+5wsYzqeVQNwLePDnQvHqNGyEx+OX0rDbsMpWbk6FxIKOHToEKGhoTRs2JBDhw7h5+eHLMucN2ajx4QMiL8RULZb8xUAtQb14D8RuwkY1BO7kiW4eucWYz6bgFarRaVS8fnnn7Nx48bXkoFWKBS/tHTpUsaMGUNKSgqiKJKRkcHIkSOpWbMmM2bMYOXKlQQEBNC2bVtSUlIwmUxUqlSJ/Px8kpOTKVu2LBUrVmTx4sXmbQYHB+Pq6qpcaFIoFP9YStMlhULxjMP3Teay1BdJdciiZIfWRE1bzJlh46k67L9kxdzhxsr1uAT4UHPKSApEC/TJyeTee8DlwRNRWVthV7400TOX4VytCk02ryDxyAlSz13k1v4fMWam4T9qPDHfzKNJlw4sG/wJR6OT+fyKA27WL98XGRnRoyqFh7+jxJCtIMCj3TOxrVQbWZKo+P5wKr4/vOixsoyo0iJaqMlLvI0u9T651j6Mm/sd9vpU3N3dzY+TZRlRfHkW8q+QZZkLxmxs+TkIfpgroXrupQRBoN6n4wmfN4fAzyfiXLESquL2FFjr8QkMIvluNJLJhFpriSybcHT1oHjleiwJCWVgt/ef2VYOJpJkHRmyEe3v2EettRUeAX5ErttBwMDuiIV6nP0qY1/ai3qd29O7W/ArOBIKheL3WrNmDXPmzKFKlSo0a9aM+Ph47O3tCQ0Nxc3NjYiICNavX8+sWbN47733CAoKYuHChYSGhtKxY0c0Gg06nQ6A+fPn4+Tk9DePSKFQKH4/JWBVKBRmRkkmJV/G0/blj8m30GFt70atKWO5+X0IUUtWYMjOocqnQygVVBvJJIARLD1cqbtxIZeHTyFp73GSfzpF9THD8AisR3bMHbLv3OP2hu241K6BrX0xwr+cQrX6NfFo+jaiKJKldQGpEGQBXhI4SjKIdsWxKFeHzAML0SfexLpuV1yC+lPiqajbpNNRmJ1C0rkfid33HXnJsVi7lcGr1RCy9VDxcbAqSdJrC1SfMCKTjRFX4efQsdAI6hckKSu9357Vs76k7iefUvmDD9GpDehzjJSr2RC30pU5uu4rIg/vxM7ZlTbDZ2EQReo2a/uL7RTKEsgyOiSsf2dhzfshC/jGpwln5y3n9t4jqB3tKRX4Fnnyqy2PVigUvy43N5cjR47w/fffU7du3Wfu+/DDD8nIyKBHjx7k5eVRsmRJpk2bxvz583F1dWXs2LGEhYURGRnJt99+C2C+OKdQKBT/XygBq0KhMDNKRUvX/FrAJglFZbJaB3uqjRqMIS8PjY0NBYIRWZbMj5NlGY2jHQGrZmPMyUNtb4uNTosgC1h5uGHj6UHFXl2J2xlGpaHtqD8vmAalLShQGwEwSIAoIogv3xdZBkFjiSk7BSu/INz7LMcgakD1OFMqSYgqFSoLC7Q2DhRmJGHnVZGaQ5dhU6YWBqlozE+8idJWicfLAz3FJP/yNgBRrca3W3cur/iegMFDih5L0Q5rrWzQWFjRYdxivCrXACAhR8b4gj56JmRkfvt3+zSHkp6UalSXe0fP0Hz+ROx8K2AjaDE89TtWKBSvX1JSEmfOnGHJkiUAGAwGNBoNsizj4ODAunXr8PHxYfr06ezYsYPRo0czZcoUWrdujYuLC/Xr16dRo0Z/8ygUCoXiz1MCVoVCYWahKkpmmiQZ1UsCRbVJ9Ux0pbGxefyTUJQIfXxfUWBUtPyL2t4GyWgEirKeWns7KvTohCSZqDlzHE45tuTqBSSTAQ0ygqWA/e+oXRUFcKjbGau3upozlLLRhEoQEQQR4fHc0+SLB0g4vYPy732MvbcPAHk6IxqViMWrnZ76mzSPD5Aky+a5pFoV5Bte/PiAocMQH49DFkAjF/2stbKhQechzzxWEHjheDQIRcEqwjOv+1s6h602B7j5sgkEsBL+GfNVn2TDn/yclZXF9evXCQwMfCXLDikU/xSxsbG0bNmSjIwMbGxs0GiKurM9eY8fO3aMtm3bIssyN2/eRJZl9uzZQ5cuXWjevPnfuesKhULxSvwzvnkoFIpX5q90tBUEgZpuKtIKXv4Y5zxbZEF+nLN7/JoyaBER+LlxkCA/GzBoRA3ic7fJKgGNUUVhoQlHLegtBKpbFM2tqmiZjVoEg+nlGT1RABtt0Qsa9QZMJiOCqMLRsui2nPibXFszgQfHNlEmqB/23j7IkoQsyxhRUcxKpKT9mz0NioJAedGaLIzm2xwtHmeUX/T4x8GqJEsIgLX+xROMZVnGJMu4WP0yULMX1KgFEXtU6Pj9GdInX4hNsoyIgCUqnMXfMwv29Xs6Gy6KIidOnGDo0KHA788iKxT/BLIsv/C8/aTpm4eHB/fv3ycuLs58n9FoJD8/n+zsbIKCgjhy5Aienp7k5eVx4sQJunTp8sb2X6FQKF43JWBVKP4lJKkoEHm6o+2fWWe5vqcKnfTy5zrn2qE2qZDEnwMfowTOWhELRGSK5mNKMoiygERRvavG9GxBh4yMJJuw1GsxiipKOwroCgvZNf0r6tSpw9ypn1Gx4Drpul8LPgScLQVUIggaDZKgxlrKI/3Cj0VLNBQrQV5SLEZdAU7laxY9QxQxyUVBdj1PFcVeEOC9bv5qOwxPBfweNkXH7dd+WyaVjKVei9b44sKYTB2UdRBxt/nleLSCSDWVLVai+g+Eqz/TIeEkaHAU1HgKv9KR6zV6/gt9dnY2AwcOJDs7G4BSpUoRGBhIenr637F7CsWf9mRpmoKCoi7fT98O4OvrS+nSpfnxxx+5ceMGAGq1msjISBYuXEivXr2YOXMmp06dYurUqXh6ev4t41AoFIrXRQlYFYp/iScZp4iICJo1a0ZiYuKfyjSVthco5yiQkv/i+1WIuGU6YBSLsqxGqShAtdUI2AtqJGQs1Y+DL+lxKaokoDY9e7oxCRJaWYO+UIWdFoyqQq5/tQpLRE6ePAlAyr5F6BKiyNX/MsySHwfoNhqwVIPRJJO+ZyYP5rQi5eoRzi/oQ37yPbzf6YKlkzu5iXeLnifL5BrA1UqgaUnNL7b7JpQQLHAVtGTKRXXAVmoBN2uBgpeUBcvImFQSxXLtHhf3/lKuQaZxSfVLf+dVVXZYAlaI6P7APFTT4wsXloJILbXD7y4nflVSUlKAny/EHDp0iFu3bmFvb48sy0yePJmTJ08iSRIpKSk4OzubL978FdOnT2fcuHEcOXIE+HMXfxSKF5EeV3k8UVBQwCeffEL9+vVZs2YNn3/+uTkw1ev1APTv3x+tVsuHH35IaGgovXr1olevXri4uADg6upKmTJl3vxgFAqF4g1QAlaF4v+p5zNOOTk5fPHFF0ycOJHBgwfj4eHxp764C4JAr6panCwFEvPkF35RL5HljEuWHYUqE0bRhIetgCiAhSDiLGhAkLHUSJgEGZVRhZVegyTKmCRjUZArSqhkFdlXHnJt2QIs0m/ib+XI/FHj6NOnD/369ePkyZNYoqdO7gkKTAIZhUX7Ij8et/BUSai9BuSCTKwtNNT/8gilm/YgLfoMD8N3U8ynHsaCbLLvX8doNJGlAxs1dPJRU8Hp7ykdFQWBNloXtIjmoLWMg4hRljE9d7glZAo1Rorl2GGje3F2M71AppilgI/zy0/pxUQNFVQ2FBO1yID+dwStJlmmAAk3QYujoKaC6lfWGHqFjEYjEydOxM/Pj0GDBrF//35Onz5Ny5YtmTdvHkuXLmXUqFEsW7aMt99+m08/ObbXlAAAIABJREFU/RRbW1uuXLlCZmbmn2qe9eR9bjAYGDNmDOfPn8fPz49evXpx4sSJ1x6wKpnh/x1POpHfvXuX1atXc+rUKapWrcrFixf56KOP2LNnD2vXrgUwz1f18fFh4sSJTJ48mbNnz1KxYkUuXrzIgAEDlHWQFQrFv57SdEmh+H9KpVIhyzIHDx6kSpUqeHl5IYoiN2/epH379sCf73prbyEwtKaWjdEGrqdJqAUZR4uiTKpJhiwdqLNd8fbSInlmkYuRgsclwAAaRCRRwhkRMc+SfB2YLEyYLCQQTBhTcsm/Fsetb7/BxdGO6zNiaTd0OE6NGrF08WKqVq3K6tWrmTJlClevnmZw0xbszCxLXI6MShDRihI5sVeI27sUu8oNqP5udxrLd1h0ai3nYyMw5GZQvvMkSjXqBALYlPIn4fJRZA9fSpYqw0eV1LxfXvO3znW0F9R8ZOHObn0qKbIerVagsrNIVJqMvRZkUcKgNiHIAm5ZDjjl27wwu5qpKwpy/+uvRfP8Yq7Paa4pTpZsAmSSJD35sgktIurnjoMky+goyqB7CFrsBBXvaV2xFl5/hypZlklMTOTChQvs2LGDw4cPs2HDBlQqFWPHjqVx48aMGDGCdevWMX78eDp06EBkZCSTJ0/GxsaGwsLCP/ya2dnZ2NvbA0UBwtmzZ1m6dCm+vr6kp6ezceNGHB0dqVat2qseLgAhISFERkYycuRIZcmRfyGTyfTMVI24uDjCwsI4ffo07777LnXq1CEgIIBevXpx69Ytunfvzq5du7h16xYVKlRAkiQEQUAQBDp06ECHDh3+xtEoFArFm6dcllMo/h+QZdmcLTWZTMiyTEhICP7+/mzfvp0BAwZw4cIFOnbsiI+Pj7mk9q+URtppBf7rr2V8HS2NvIvaB+fowSQJ+LuqGBlgwfyK7syzrkg/Cy/8RTvKqKyopLLmPY0LX1tVYpZtRfq6FaO9qwP1RWfKRKQT3X4Yt/uOxrguhBVz5xCxbRd1q/px7OhRdDodZ8+eNZfBZWVlkZubiyo5mo1trVjazJIA9QMerhlK7snVVCpXBu8H+2h473smdg7E3cGSFu8E0nHBT5Rs1InMjFSSb0dSvM572NvZElTBlon1LfiwkualXZDfJHtBTRetOx9q3SgpWmJtZ8S7uJEM9BRKMi5Z9pRLccM53/YXwapBknmYKyPLMKSGFneb3z6dWwgi7bWulBWtcRcscBG0mJDJl03kPf6XL5soRMZRUFNCtMBZ1NLRwgM38fXNXY2MjOTEiRNkZ2cjCAL79u0jLi6OHj16YDAY6NKlC9u3b2fBggXUrl0bgKtXr1KsWDEAxo8fT3BwMHfv3sXW9lcWEX7OgwcP6NmzJw0aNGDhwoVcvXoVgOrVq3P3blEJeY8ePZAkiUuXLpnfl6+CJEnmz2eJEiXQ6/VcuHDhlW1f8c/xJFiNj48HipapmTt3LqVKlaJLly7Y2dlx7do17OzsOHXqFP/5z3/Iycnhu+++AzAHqwqFQvG/SsmwKhT/YLJcVAb7pIQsPT0dZ2dnAGJiYtixYwelSpXC29ub7du3M2TIEBo1asSmTZsIDAx8JaVibjYi7cqLtCv/4vs1gkBt0YHaGgfzbU9nFFxFLdWNBSzZsIToI0eYOnwQzZo1o3z58iRERiPUqE1gYCA//PAD58+fZ8KECQwZMoTNmzdTo0YNFi5cSKVKlcjOzqaGmz2aKkYW7V9DWFgYrVq1Ytu2bRw/fpzo6GhGjxzOmjVrmNS2AQcuXmTnpjU0ad+dbl2HUL7HLNxt/nlf/ERBwEuwxEtriUmW0VtI3BVlDt8zcSdTRi+AvYWMWihaw1Vvghw9qAV4u4SKxiXVf6hxlPXjbOktUz4XTNlYS0Wdg39eqRW0soiNqKKmyo6qaltshdfzp8JoNDJ58mS+//57GjVqRG5uLnv27OH69evcuXOH2NhY3NzckCQJV1dXLly4YP7SD7Bnzx5at26NVqslKCiIwMBALl++TGBg4O96/W3btqFSqfjhhx/YsmULI0aM4KeffsLKyooHDx6YM6/Vq1fn0qVLfPTRR395zE+yZU9/NuvXr8+pU6e4dOkSgYGBODg4/MoWFP90Ty+5BLBhwwZWrFiBs7MzDRo0YNCgQbRt2xatVotOp8PCwoL79+9z/vx50tLS2Lx5M7Vq1UKn06HX69Fq/xmduRUKheLvopo0adLfvQ+/afny5ZP++9///t27oVC8cU+urMfExHDo0CG6detG+fLlsbOzY/369YSEhLBy5UoGDhzI+PHjsbOzw9LSko0bN1KlSpW/rVvkky9r69evx9LSEnd3d+Lj4/npp5/44IMPqFixIk5OTixatIgBAwbg5eXFuXPniI6OpkuXLjRq1IgOHTrQv39/wsLCCA4O5tSpU3h5eVGrVi2io6NJSkqiVatW2NvbExUVRUJCAkOGDEEQBHZu30Z+ehKzpk+hf7cOlLIXsdP+84LV54mCgEYQcbUSqeOhprqriFosKsHWmYrud7IUaVFaRRcfDf6uKqw1f3xMKkHARdTip7KljMoaB0FDMUGLm6ilrMqatzQONNE4U1JlhfY1rLv6ZJ3U5ORkFi5cyJYtWzh58iSxsbE8evSI9PR0UlNTuXPnDkajkbi4OKpXr87u3btxcnIiKSmJTz/9lIiICN5++22cnJwIDQ3l4MGDDB8+HCsrqxe+7pkzZ8jMzMTNzY3CwkK2bt1Khw4dqFWrFvXr1+frr7+mWLFiBAQEcPDgQTw8PPD29sbNzY1PP/2UESNG/OWLQE8+09HR0SxZsgQnJye8vLyQZZmIiAjs7e0pW7bsn97+1atXsba2xsLi7+nm/P+FUZKJSZc4n2xiX6yJH24b2HfPyOE4IxdTTCTmyhSaiipNtL9Rav+8J+eZuLg48vPz2bBhA7NmzaJGjRpMmDCBEiVKUKdOHbZs2ULDhg3N5eZ3795lypQpZGRkMH36dDp37vxMKbFCoVD8202ePDlx0qRJy5+/XcmwKhT/IM/PdQJYuHAhixcvpn///nh4eLB+/XpatWpFZmYmbdq04dNPPwWKmi7dvn2bKlWq0KZNmzfW1fRJWePTX+QPHjzI+PHjcXd3Z8+ePXh4ePDll19y/Phx7ty5Q2BgIP369WPGjBkcOHCAFi1aULt2bXJzcwGoWrUq165dY8SIESQlJbF37162bt3KqFGjOHPmDKNGjTKXzXl5eVGpUiX27dvHuXPn6N27N127dv1XfGF3txF5r/zrm7khCAIeggUer7Hc92kbNmzg6NGjdOvWjcDAQFxdXUlOTua9995j1KhRdO7cmUOHDlG7dm2io6MJDQ3F0dGRlStX0rdvX3r27El6ejphYWG0bduWpy9kFhQUMHnyZHMFAvwcGK9du5ZVq1YhSRJWVlb069ePDh068OjRI65cuULz5s0BmDBhApMmTeLKlSvs37+fVatW4e/vj0ajoU6dOmRmZprLkH+v57Nt2dnZTJ48mRMnTtC2bVtWrVpFrVq16NKlC4cOHeLChQvUr1//pUH3y6xZs4YVK1ZgYWHB/PnzqVq16j/+As3fId8gc+ahiaP3jeQYHq/lrCn6Z/+4iiHfIBOeaOJkgglRgNruKt7xVuFh+8vP4tPzS6HofXjkyBG++eYbunTpgl6vJzExkQ0bNrB161bat29PixYtsLe3x8rKioMHD9KzZ0+0Wi1Tp05lzJgxODo6vuGjolAoFP9syhxWheIf4EnH3yfBanJyMgB5eXlERESwZ88eRo8ezdKlS4mOjubGjRt06tSJ6OhovvvuO7Zs2UKTJk1Yu3YtlpaWjBgxgrfeeuuN7LsoioiiSHJyMhEREQBcuXKFjz76iN27dzNv3jy2bNlCamoqNWvWJCoqiujoaAC6dOnCzJkzAWjXrh1du3blhx9+YMmSJZQsWZL79+9jYWGBt7c3I0eORJZlwsLCqF27Nn5+fsybNw+AevXq0bVrV3NTnH9DsPpvUVBQwPnz5wkMDGTjxo3UrFmT2bNnExwczPfff0/lypUpWbIkLVu2pFSpUgiCQGJiIseOHaN+/fqoVCqCgoI4dOgQZcuWZfz48ezevdscrBqNRgC6detGy5Ytza/79Lzvs2fPMmLECI4dO0ZQUBCbN28G4D//+Q+LFi0yP6d9+/aoVCrOnTvHxIkTcXR05IMPPsDPz4+6dev+oWD1yQWjJ8HqzZs3uXLlChYWFrRq1YqIiAj8/f0JCwsjNDSU1NRUGjdubG449UesW7eO9evXM336dA4ePIivr68SrD5HlmVupJmYEa5j9x0jWjV42QmUsBVwsCjKoqpEAY0oYKsVcLMR8LITcLWGC0kmZkXoORhnwPBcG+8n0zWSk5M5cuQI3377LW3atGHIkCF07dqVevXqcfz4cQoLCzl37hxffvkllpaWFBYW8uGHH3Lw4EF0Oh1QdP5XglWFQqH4JSVgVSj+AZ4Eqj/99BP16tWjY8eO/PTTT9jY2BATE8O1a9eAoqUNGjRowIIFC+jTpw/BwcFcvHiRLVu2MHv2bObPn2/+ovq6MqzPbzczM5PevXvTokULjh07BkB4eDgVKlQAihrKvPvuuyxatIj27duTmJjItm3bMBgMTJ8+nX379pGYmAgUZSssLS3ZvHkzlpaWtGnTBldXV27evAkUBbirVq0CigKU48ePA1CmTBmCgoKwtLR8LWNW/HE5OTkMHz6cYcOGYWNjw8KFC1m4cCEDBgygbt26xMXF4efnh6+vL7dv32bQoEHMmjWL/fv3s3HjRgDKli1LaGgo+/bto1WrVgwePNj8/ntykUetfrZQKDc3lylTpuDr60tYWBgAS5cupV27dgDExsZSrlw5CgoKaNq0Ka6urqxYscL8/MDAQNLS0hBFkVmzZjF37lwePHjA8OHD/9D4n3wO165dS48ePejXrx/bt29HFEWaNWvGkCFDWLlyJfPmzaNEiRLs3r2bwMBA9Hq9eV3ZX7Ny5Urz0ic3btwgMDCQBg0aYDAYMBhesqDv/yhJltl1x8jSywZEoShQtVL/voBeLQq42wq4WcOe2yYWnS8gR//zOTArK4tJkyYxduxYwsPDGTRoENbW1lhbFy0BVaxYMdq3b48sy6jVak6dOkW3bt3Yu3cvnTp1YsOGDdjZ2b2WcSsUCsW/hRKwKhRvmCzLL1xDtU2bNqxcuZJly5bRrVs3Nm7cyMWLFxk5ciRff/01UHQ138bGhuPHj3Pz5k2aNWvG3Llz2bZtG40bNwZ+LtF9lRmWgoICoChIeH67Bw8exMHBgQsXLvDJJ58AUK1aNXbu3GkOLlq1akVKSgrTpk3j4MGDHDp0iH79+pmPxZOmNqIoUr9+fUqVKsWmTZsICgoiPz/fnHEaOHAgZ8+e5dy5c7Rq1YrDhw+/sjEqfptJLuoonCsb0cnSCy+KpKWlMWTIEN566y3y8vK4cuUKhYWF3L17l4EDB9KjRw9mz56NhYUF69evp1evXrz77rs0atSIkJAQhg8fTk5ODjk5OXh6ezNv4xq+S46m1BcD+cb0kG908azRJXBJziVXNj7z2jdu3KB58+Y8evSItWvX0rhx42f2MTg4mEuXLpGamsqoUaN4+PAhCxYsYOPGjWzevJldu3Zx7tw5/P39gaLPW7Vq1X4zY/+izzQUZT5Xr17N6NGj8fX1JSoqiosXL5KUlMSVK1fYuXMn7dq14+bNm2zevJn8/Hx69+5N9+7dXzhX9vkgdv78+ciyTIUKFThz5gwjR46kX79+DBo0iE8++YTIyMhf3e//BZIssz3GyKE4I562RXNS/wy1CN72AkkFIksu6cnIL7ookJOTw6xZs6hevTpjx45Fq9XSo0cPFi5cCEDx4sUZO3YsV69epVWrVnz66ac0adLEvPTY8xdcFAqFQvFLwpua5/ZXBAQEyOfPn/+7d0OheKWys7OJjY2lQoUKWFtb061bN+Lj4zl27BgpKSl8//33SJLEmDFjqF27Nu+//z6JiYlotVoyMzOpV68egwcPNm/vRfNf/6obN24wffp0c4MagN27d1NQUEDDhg1xd3end+/e5jmq+fn5WFtbk5OTQ/v27alfvz7Ozs6sXr0ak8lE+fLlWb58OVZWVnh5ebFp0yZatmzJkCFD0Ov1LF++HKPRSFhYGMuXLycsLIyFCxcSGxvLxx9/TNmyZYmOjsbHx+eVjlPxcrIs80g2EGnKJdqYhoABkJEQsBNsqal2ooLKmjtRN6hatSoLFy7k9u3bDB06lPPnz7No0SLatGnDZ599xpQpU9i6dSuDBg3i0qVL7N69m4SEBCIiIujUqRMeHh5cunSJDz/6iCHfL+SynIdOlrBEwFICtUqNDBiQyKEoQLSIiSd+zxHaNm1OQUEB27ZtY/HixeZ9FwTB/H9eXh42Njbk5eUxdepUvLy8GDJkCEePHmXdunXExMQwfPhwPvjgA/Nz8mUThbKEDFgIAjaoXnoxKDs7m2PHjlG9enW8vb357LPPMBgMzJo1i8TERBYvXoyLiwvDhw/Hzc2NL774gvj4eBJTUqjYsC7V27VAtLHBUhBxE4oaYFkIInq9ni1btiBJEj169DC/Xt26dfniiy9o3bo1M2bMIDIykrfffpuUlBQyMjJISEggNDT0Nb9D/tkO3zey45YBbzsB8Q9exEuOvcH9a+FUafAuNo7FAbhxej/7V82lSsDbTOjZhoYNAhk4cCCPHj0ynyMzMjIoX748UVFRuLm5mbf3ZF1VhUKhULyYIAgXZFkOeP525dKeQvEamUwmwsLCzJ0goejLzOTJk9m3bx9NmjQhNTWVrVu3Mm7cODp27Ehqaiqurq74+Phw+PBhbt++zaFDh9i9ezcuLi707NmTsWPHmtejfOJVBqtnzpxh9uzZnDlzhuHDhzN69GiuXLnC8OHDsbW1JSAggFWrVvHDDz/QqHFjTl6+wL78JAxqEbU+DxcrLYtWLKdvl2Du3LnD2rVrOXv2LPb29giCgI2NDcOHD+fKlSu0bNmS8ePHExgYyIMHD/D29sbW1pYHDx4QFhZGUFAQ+/fvx97eHkAJVt+gdMnAAX0KaXIadtIj3MhHfGo9WJ0kMWz4Ws5s3IeLmxs9O3dl544dTJw4kY4dO9K4cWOaNm3K3Llz6dSpE5999hmVKlXiwIEDXLp0CZPJxIEDBwgICODDDz8kMjKSb1atwKJDU87K2TihwV54HCA+lXBUoSLlWgybP/+SzLR0KjVrgO3Vi+Tdf4goioSEhJCYmIiVlRW5ubkMHDgQR0dHbGxsALCxsSEnJ8ecfX3nnXeoU6eOudGRSZZJkAq5ZMrmnlRoHrEMuEoqsvafpsM7zXBxKmrwpNfr+fbbb1m8eDEtWrQgNDSUPn36ULp0aZKTk8nMzMTDwwOtVktYWBg9evRg7969LFuzilRZT50vh2PlYEcsAqJUgITMJVlCaxSpprLFX2NHbGwsBQUF5otCDx8+JC8vj7lz59K6dWvGjRsHgMFgQKPRcPHiRebNm0d8fDxeXl6v943yD/UwV2L3bSMeNn8sWE28fY29Sz4nMyUBn/oteRhzlTLV6xO+cyU3Tu+jw6jZXLt6heDefYm7Fc3IkSP54IMPuH//PiVLlsTJyYl69eoxevRoQkJCzNtVglWFQqH4c5RlbRSK1+BJBmfcuHGcPHmSc+fOAUXB1p07d0hMTCQkJIQSJUowcuRI/P39adiwIZcuXSIyMpKmTZtiY2NDeHg4WVlZNG7cGB8fH3Q6HUOHDiU3N5du3bq98rlPkiTRp08fQkJCKF26NLVq1SI4OBhXV1cyMzMJCAhgzJgxXLx4kRUrVmDlU5Z77jaEnzpF9I0bFA+oxvppcwnbswdt+3e4ezICG1FNDX9/WrZsyaZNm6hevTomk4kFCxbQvXt3XF1dcXJy4tKlS5w7d46qVaty6NAhADQaDW3btqVOnTrmOWGKNyNJ0rFddx+NdAsnOR1tUY4RBA0IGq6duM60tuOJu3SD1gNa8+704dy8eoeoU+GcOHGCrKwsihUrxr1798jJyaGwsJCWLVvi6+trnqes0WgYN24c7u7utGjRgg+7dyOqkgtZJj0uogUq4eVLEe2euwSPCuUYvGIRlRrWw+hfjg8CG5MZl8CUKVOws7NDr9cTGhpKYmIiJUuWpHjx4iQkJPDNN99w+PBhevXqRcmSJYGi9xpApmRguyGZi6YcCmQTjmiwEdSI+Tr2f7mQ9Z9/yclTJwmLOI0gQ40qVcnIyODHH38kNDSUypUrM3bsWCpXroyDgwMxMTHk5eXh5+dHdHQ08fHxWFtb4/lOXXKa1qB884a4WNpigwpLRCwFFbHHw7FTaXBwcOCOPpcoOZ/K1o7cjrzO+fPnWbZsGcuXL6dXr1789NNP+Pn5Ubp06WfW7Jw2bRo2NjZ06tTpjbxf/mlkWeb7SAM60+8rAzYZDRxYPhXX0pU4tXkprqUr0W3qGirUboKjmzdqjRaXkhXwb96R60d3Ebl3LY+SEnAs5kqrFk2Jjo4mPDycoKAgAJo1a4a/v/8zGVaFQqFQ/LqXLWujlAQrFK9IoZRHuimJQjmHqCsxtKvTGZ2pEI2gZc6cOdy/f5/Zs2djZWVFamoqI0aMICMjgxIlSnDz5k2OHz/O2bNn6dy5M9evX8fGxobY2FjKlCkDQHx8PBs3bqRatWrmL0WvgizLJOTKRKWZyNZBdkIMQW/54GEjMGHCBIoXL87QoUPRaDRcv36dAQMG0KRZM+5pTJw/dZpB3y8k8148B75ZSdzV61SoG0CbEYOQgTVjJ1Gvx0fcXbWd3dtDmThxIqdOnSI5ORlPT09EUcTR0ZGtW7eSmprK119/zebNm2ndujWff/75M0uUKN6cdMnAVt19HKRbaJBB+OUczpNbDrNk4BzmnV1OifKeyFIet+KN/PDJd+TFJeDu7k6PHj1QqVSEhIRw/PhxoqKiiI+PZ9u2bYSGhuLt7c3+/fuxsbFBkmW26ZJIkvUUF7W/un/3LkeycuhYJuzfisXjCxmFson79+7xkX0pqpTwNpf/xsXFMWjQIKZOnQpA3759qVevHiNHjqRcuXLPbDdDMrBFn4QJGUdB8+xrXrnGZ3Vbsq4gAYDt8xbz6EECq+YtwPAgmWHDhpGWloa9vT29e/cmODiY/Px8Dhw4wMyZM1GpVHh5eSFJEuXeqonbkC44CRrUMs8siwJwfvc+Di5bzbiwTZiMRgpVAgWykdRFG9i+Zh0DBgzg448/BmDOnDmEh4ezbds2zp07x7JlywgPD6dRo0aMHz/+b1uL+e92N1Ni4UU9Xra/fz7/ugndUWu0pMTF8N8le7G0tkUymRCfql6J2LWaqBM/0mvOFn7asYHrW2YTdyuKc+fO0adPH86dO4eVlZW5pFyhUCgUv59SEqxQvCYm2Ui88SbppmQEBFSoKVXNg5LlPTl4cxu1ytfH29ubR48emUsOb968SWFhobmLqUaj4YcffuC9996jc+fOPHz4kAoVKpiDVQAvLy9zU6NXJb1QZt11PXcyZUQRNCIYKMeVCB0VnVSUquDDzchLXL58mdq1a3Pjxg08PDyoO34QmpQE1k+cwfV9Rwjs2oF+336FvqAQS5vHAURuHs7Fi+NS0otLjlbsP3GMzp07ExMTw+TJk3nnnXdISUmhd+/eBAUFsWjRIqZMmcKYMWOwtbV9peNU/DGHDY+wle6+NFgFqPN+A77+7yxy0rI5fuEmuxZuoU7bOtTq24a1Pcbj6+uLl5cXjRs3pnTp0jRs2JAffvgBWZZxcnJi9OjRREVFmct0E2UdD9Hj8lyg+CJ2xZxRa7Xo8wuwsLYmKzmVbVPmcD7sAMca1OfIllDzdjMzMzGZTJQqVYpixYpx7NixF1Ym6GWJnfoUpBcEqwCl/X1xL1+GlNj7uJYpSYmS3uQ+Sme/mM1bkgFra2uaN2/OqFGjgKLmU3Fxcbz//vtUqlQJg8GAn58fAz4eSryjhkqCBq0gwgtimlptWrLq43FkJqXg6O6KpdGIrFKhC6hM88QWBAT8/Ld8yJAhzJ8/nwsXLlC+fHneeecdZs2aRfHixX/zOP6bnUwwYaF6ebAqyzKyJD0TjL4TPIKNk/6DlY09Rl0BWNs+cz9AbnoKbmUqA+BoreHB3Zvs2buftq2DCA8PN5/jlWBVoVAoXh2lS7BC8RdIssQ9w3UyTMlYYYuVYItWsEQrWDJh7miWTlzNQ+Mtdu7dRnx8PBkZGUDROqsajYbLly+zZs0afH19iY2NBWDmzJlvZK5Tpk7m64s64nNlvOzA01bA1VrA007A0wbuZUnEONbBIAs8qXCwtbUlLSebNStWcnLGYmq825ziJYvmx4miaA5WAa4dPo5zCXcq+VbFrXJ5BvTvz9y5c3F2diYmJoaUlBRcXV1ZuXIln3zyCeXKlUOWZSVY/ZulSXpSpEdYyIUvDVYBjDoD1d6pwYSmHxN18io9Zwyg47ie1G9egeJlSiLLMuvWraNdu3a0b9+exo0b06pVK4YNG8aQIUNYsmQJlStXNm/vijEHDS8vAX6aWqvF27cy1w6fKLpBEPBr0ZgZ53/iavg5QjZt5NChQ7Rp04YePXrQqVMnihUrhizLLy2jv2vKJwsjDr8SMAfPncKWiUXrBl89cISchCQyMzMxlC8KzE+fPs3WrVtZvHgxjRo14siRI0DR3MVDhw5Rs2ZNHmSl49umBRbCy//8CoJA52kT2DZlDlAUXNkKaorXqILsaMuRI0fIzMwEwMrKin79+pGSkoKTkxPdu3f/nw9W9SaZyykmiv3KKleCICCqVBh0hWQ/SgLAy6cmxb3LISNz+/xRJElCMpmQHneAzs1IxcreiazUhyzp15hbZ/fTavxqytVuAmC+SKJQKBSKV0spCVYo/oJMYwqxhkisBLtffNGWZZm6JZpT3L0YlWuUR85WY9DM/6AtAAAgAElEQVQZ6du3Ly1atGDNmjUsXLiQVq1aMWbMGEqVKmV+riRJL1zW4lXadMNARKKJErYvDxAScmUKT6/BLusO/fv3p2zZsnyyaim7122kcdeONOz+0Uufe/N0BPuXrMBkNHLvUiSipZZl8xfi5eLGl19+ybRp06haterrGJriLziqe0SsIRIHoRD5VwJWgD1LthMyYTnLb23GwaWoqVjirdusmbGLvu92ZPHsuWRmZtK3b18mTpwI/Ny5Nycnxxw85shGVuoSKIbmdzXHkWWZHxcsI+l2LMFzJpnLggGWDBlN84B62OXqsLW1pX///r9re+v1ieTLJmyFlxceybJM/xJVcXR3pUwNP/IyM9Hr9LzVvSPf9hjEoX372bNnD5mZmYwZM8a8PA7AgQMH8KtZgx22BVijQvMrASuAyWhkoLcfX985bx5frmwk9tBJ0ncfpW3btrRp0+Y3x/a/KD5H4qvz+mfObZnJ8Ti6/dx8qiAnk0MrZxJ9IoxK9VpgaWtPy/4TuXnmIFum9ccnsBXtRsxBa1l07PMy04gJP0Slus1JS4glJe4mtVp1JSFHpm05NU1KKQVrCsX/sXfe8TWe7x9/P88Z2VOmSJCYCSIEEUTNhlJ7z9YebSmqrV/NojWqtFpUrVIjKELNWBEy7ISIGYJEFrJOzsk55/n9EUltodpqv8/byyuvJPe517nPk/tzX9d9XTIyf5ZnuQTLglVG5hWRJIlLuhNoJQ1q4elH+Ts27CEs9DDTV32Knd6V8+HXGDZsGNOnT6dXr16kp6cXW0OKPot/hytZjk5iYoQWJ3NQis92mdMbC1MxSAfnU6d2LfoPG8JS7U3sUKF4QT8TT8eyYdLX+DRpSJP3e7H/t63cDYtkx9oQzpw5g5+f318xNJk/gSRJ/Jh/FSdjPLcupBJ7+DQ+DX3x8Cn/1PJ3kzOY1WMS2rx8puz6BqPByDd9JmMQVfy8dTsFpy/SuHHj4vLPOohJMOSyqyAdR+H5d1cfaft2CiGTv0aTk8u7Y0dy68IlwteEYOnswKA503jf1fuRcT2c3uZx0o06Vutu44j6hZ+/Yxu2cCJ0NyN/+ZECrZZzByNYOnI8X0yfxug+7xVH6S1q12g0FkfwvmbQsK0gtcTj3DHvRzRZ2XSe9AkAkRu3kZp1j3pY0aZ5Cznq7DM4ecfAL+cKcLMqfC/zsu5yYsdqyvnWx7l8Ve6mJHHvThI3zsXQpM8YEiL3snpCbz4JOYudiweLhr+NXpuPjVMZmvQbS1piAhEbF1G6ki9tP/wKlalZcVt38yXKWosM9i352pWRkZGReTqyYJWRec0YJD2x2sOYYvnMTa5er6exZxt+j1uHjbUNlU3qcuTIEWrVqlUc9dZoNAL85RbVh0nINLDo9B8buudxO1uiUvJO3g6siWVZN9bqknEowYb7cXFw8eoVyuUL9Pdr8Kf6LvP6MBqNXLt2DYVCQbly5SiQjCzKu8DByVM4H3GeRt2bE7Z8Bz0nD6BmizpPrSMzOYPhVXvi7l2OWxeTsHOxZ8CisbzdpD+NlHYIgvBCj4Gz+iz26zNxeoFF93Hy7mexe+HP3E64THbmXd4dOxKvoABEAfqZuHHs2DGWLVtG3bp16dGjxzPdzW8YNGzRpb4w2BMUWj5Hetbim3NHMbMqrC/ySAR96wbhb+UEPLgfKUlPjPm8IYc9BRk4lVCw6jQaRnrWpu3YERxauQ5Lezs6L5zByJqNKC0+x9/1f5zwm3rWn8ujnH3hejIaDOz47nPO7NuIrbM7wUMn4VGtLnlZdwn9djwF+Xnk52ZhYetAv1nrORu2md2Lp1CzZVdSExPIz80iqMeHVKzb9Im2cgskzJQCn9R9ubUrIyMjI/MkctAlGZnXjMSLLaJKpZLugzry648bGTL+PQAaNmz4SJm/U6gWoTdCiQ25gkSTVu9S3l7BHaO2xG0UzYtBr0ehVOJY3gMPhXzH602gyAqo0WiIi4sjLi6OwMBA0u/dJb9eaaxKWTHml4lkJKezftpyrpy6SPUmtVAon8z1a+9airYfduHyyQSm7f0Wr5qeaBDQS8biNfCiNa4HkISnBiB6HuY21nT4fDQ34uK5l3wH78aB6CQjBiSWLVtGSEgIY8aMYc2aNcTExDBz5kxKlSr1RD0GpBK3rVAqaT6oL3t+WEa78YWRej0b+KNS/iEgH4/6W0Th0VTJD4nVZmY0G9iHuLDDjFixkPK1apAu6R7UI/M09Ho9BiMoH1i5dZpc1GYW5NxNw9zanuBhk6ng/xYA5w6FYm5tR6eZa7h18QwL+gWSey+dGs06cuHobuq07YuZlR0m5s++Vy8Axjf/3F/mBRgMhteay1xGRub1IgtWGZlXRPHgn0EyoBCe/Ydu+OcD0Is6TIU3J4+ojYmAUXrSCvo4kiRhlASsH+QxVCO+xHa7EIWy8DFjQMIceUPwT3Pz5k3CwsLo168fFhYWnDhxgkWLFrF27VpWrV5NRPx5okMjCV9/GAd3J8aumYx3wxrPrbPnlAEPHVBo0IummD/nLujjmApiyQ9QHvDw2jWztGTTT7O5deESmampBA/uj4lez7BhwzAYDERHR9O8efNiV93HUb/gPunjdPh89BPRY02e8wwobgcB4SVVedepnz7xGVW9rLL/j3Px4kXs7e1xcHBAqVRiqjQQvngCCXtX4+rlQ2DX4fSYsoyIkEWcDdtMBf+3MOgLSL4Sh7WjK5qc+9yIi8bUwoaz+3+jfsdBdP1icYnaNkhgopDfj387RWI1ISEBDw+P4mjPMjIybwayYJWReUUEQcRBUYZUww0UPPsEXqFQoJMKsBdL/429ez5ulgIuFgLZOgnr53iy3deBh3VhWQAbQYmNoEQjGTArwQa9CEmSMCJRViFvAv4JHr4fbW1tzZ49ewgLC8PBwQErKytatmxJtWrVqFWzJpfyndhRMJV3RrSncc/CfL+JZ69wJzGZeu82fOohx8PfKxWgFWxwLoF7bRHWgvKlDkIedzFOu57EhSNR3Dx/kf6/LqS8gxObIyOJiIggMDCQdevWUb169WfW5yCoUTywCitLIF6LxKokFftZ4FwCN19HQY3Eiw+KHubhcgWSESUCdiVI/fO/gNFoRJIkhg0bRufOnRkyZAgJCQkM6d2PK4lJ+DbvTOKZo6yd2J/qhzMpVyOAhGN7SLlyHhcvb8pWD+Da6Qhmda5BnbZ9GL0mCltn95fqQ14B+DrKgvXfREZGBlZWVqjV6uLP4q+//sqMGTPw9fXF1taWmTNnYm1t/U93VUZG5gGyYJWR+RPYK0uTZkhCL+lQPmPDqpXyMBUssVbY/829ezaCINDaU8FPZ/SYKSVUT7EQ6AwSWVroWUX5h2unIFBbYU2YPgOzl7CW5mHEXlDj8hJBdWReD4+Lu3v37hEeHo5CoWDz5s34+fmxf/9+1q5dy7Fjx/Cv60vdXh04/vsRUq6moMvXcWp3NA26NqEeDZ8vtB6444qCAx5iyQ8nSgsmWPPig5CizaUoiuTn5hEZshXvoEAqBtSm86RxxO47jEPVitQxdybKzY02bdowefJkrKysOHfuHBs2bGDixIlPuP6ZCCLVFZacNuTg8BLZ3gRBIEvSU1Y0xU58sYi0E1V4iKakGnVYv8Kf3/voqa2wfmmL8H+NIqFa9D726tWLNWvW0L59eywtLUm8cpHSfi3oMG4eCcf2sn7qIDZ/9SEdP12Aa4Vq7Pt5Bm6Va2Jp70jLwV/QoOsw7Fw8XqkvBUYoZ/O//X78m8jKymLbtm2ULVuWpk2bcu3aNZydnTl27Bh79+7FwsKC0qVL4+Pjw8CBA1Gr5b9ZMjJvAvJTVkbmT2AimFFOVQM9BeRLuRilP26XGSQ9GikLJSo81TUQ3rBNZg1HJZ0qKUnJk7iTK2F4cBFLbyz8PjUPulZW4u3w6Oa+osIcUxTkSoYStWOUJLLRU1dh/bdEQJb5w6IKhfdHU1JS+Oyzz1i2bBmOjo6sXbuWRo0akZOTA4Cbm1vxps1DNMWvU2c6je8GSKhN1UzaMZtO43q9sF2jUUOWZIOfyu6FUaQfRhQE/JXW5PDkmioKSlYkVvOysjm5Yw9ft+nBidBdfN9vOBfCI2kxpD9mjnZEf/szToKagQMHIkkS3bp1o2/fvvTo0aM4au/T8FFYISGhl0p+Q9QoSWgwUktRckuMn8IaDQZeNuChQZIwAt6Kl8tTXCTugJdu803DaDQWH8AoFAquXLlCUFAQ48aNIzo6mk6dOpGRkUE1Hx/QZpN4OQEXL2/cffw5e2AzAE36jUOhUpGXdZdqTdqjNjV/ZbFaNJ9lShC8Tuaf4/bt20RFRQFgbW1Nbm4uAwYMoFatWkRHRxMVFUV2djajRo2iRYsWjBs3jgEDBshiVUbmDeLN2kHLyPwLsVbYU1ldB3uFKzryyJdyyJdyMKDHRVGBSib+qIU30xX2LQ8lH/ub4Ouk4E4e3MqWSMuDWs4KxviraVjmSSuQqaCgndqJfAwvFK0GSSJV0lFLYU1lOeDS38bDBwO///47PXr0wMPDg/PnzzNw4EA8PDyoW7cuP//8MwCVK1embt26HD58mLcaNiL++19RV61D9wld6TahLzZOdi9uVNKiF9UYFG64ZBW8tDiqqDBHiYBW+kOgwh8Bm4rGtOObHwmds5BWHw5mzKaVBHbrQMjU2UiSRIUWjblz7CSCIKBWqxk/fjzvv/8+N2/eZPXq1UydOvWZ91hLiSoaKG1JpwB9CfpufLC2ayos8XiJiL0eoimeojnplHyOjJJEuqSjlsKqRJbchxFFEUEQSExMJCsr66Ve+6awbds2Nm3ahCiKiKJIYmIiQ4YMISAggEuXLrFw4UKCg4M5deoUK1asoG3btmhSrpB4KR5Le2cMBTokg5GY7aswtbCi++RlvPPBdMwsbZ7bri4/j50/TGTDtCFcj4164vd3tVDBVsTJXN5KvckYDAYmTJjA2bNn+fnnn9mzZw/W1tYMGzaM7t27Y21tTXx8PLVr1yYqKqo4Z/Tt27f/4Z7LyMgUIT9lZWReA6aiBe6qylQzaURldV2qqOvhYxKIi6rsM12F3xTKWov09lYxq7EJ0xuZ8HVjE3pUVeFu/ezHg6toQhe1CxKFm/YcSf/I5rtAMpIu6cikgAClLUEP0pvI/DUYDI8eHCQkJLBv3z4A0tLSGDZsGM2bN+fEiRNkZ2ejVCoJCgoiPT2dmJgYLl68SOXKlRk9ejT9+/dn6cw5eJt6kYozoAFJB08RV0ajESQjgpSHDpEzp3IJ6TySwb378u2335Kfn1/iMZgJClooS3FXKqDgoQjDlyKPs3T4OI78ugl9QQGN+nTBws4G44MxB48cSOrVRI4fj6FLx46Ud3KlQoUKDB06lNWrV7NixQo6duxIxYoVXygQayusaaCwJQMdWY+t6SIkSSJXMpCKjhpKKxor7V9qbSsEgWCVA66CCekUYHxBn/QPhHFVpSUNlC8+OHi8z+fOnaNDhw507NiRuXPnsnr16qeWe9O4fv06W7duBeD06dNER0ezYMECgoODGT16NA0aNKBBgwZkZWUxePBgkpOTKVeuHK1bt6Zv376oMBK5fCoLBzdDZWLGe99spk6bviUKNFfExhnDuZ92G89ajdi9ZCrHt/9SXEaSJHJ08JaHHEjuTePx56EgCFy4cIFmzZphbW3NsmXL+Oyzzzhy5AgA/v7+eHt7k5WVRUJCAgcPHqRZs2aEhIT8E92XkZF5CvIdVhmZ14hCUKJ4ieiobxJKUUD5EkdYLqIJ/U3cuGbI47ghi3SpAOHBXk+FgL/CBm+FBbYvaRGSeXmK7vIVuUseO3aM6dOnc+nSJWJjYwkNDcXT05PRo0fz7rvvAmBnZ8e7775L586dqV69OnPnzqVx48Y0btwYgCaqUpgKCs4UmGItpWKGBiSRwnNOAQEJhaBHj0BCwn2MOJDw/XrGfTSKWrVqERAQgJ2dHT169MDE5MU5Kg0GA5WUFjTDyP6CDExzdOybv4T4Q0d5672e3Ig9x+0Ll+g69VPKeFcmI+kW91JSsXZ2JGBQL0JHTWJWzEmsBwygW7duNGzYkClTpnDp0iW2b99eonkUBIF6KltcRBOiDfe5ZcxHkASUD2L76il0yy0lqGikcKCSwgLxFQ5iTASR9monDuoziTfkggQ2KB+5m6qRDORgQAAClbbUVdqUqK0iMRYREYFGoyExMZH33nuPVq1aMXr0aJYtW0azZs1wdXV96X7/HSQlJWFnZ8fw4cPR6XS4u7tTpkwZPvjgA0xMTKhWrRoHDx5EpVIRFRWF0Wike/fu/PzzzwwcOJBp06bx3XffERKygY+/mI6iclNa9RhYPC/PE6s5d9OwsHUAQJNzH6VKTePeH+NcvgoWNqXY/t1n+AX3QKFUkponUclOxLuUfO7/plH0PDx69CjOzs6YmZnRv39/du3aRZcuXQDw9vZm48aN7Nu3j+bNm/Ppp5+yd+9ePv74Y3Jycvjoo4+Ky8rIyPzzKCZPnvxP9+GFLFmyZPLgwYP/6W7IyMg8hkIQcBDVVFdYUl1pRTWFJbWV1tRT2lJWYYbpS0QSlik5BoPhiUBKI0eOpFy5cri4uFCzZk1WrVpF1apVsbW1JTs7myVLluDn50dOTg7z5s2jTp061K9fn1atWvHhhx/i4ODwSBuCIOAumuKutCNbsOOGZIpWkjAIAgWSgEYwITLsEmErj3B+3QFmDxlN13fbc+HCBT744ANUKhUGgwFPT0+cnZ2fOo4iS1VRICWAG8fPULNMOS4rdEhWFrT+eBjpl66yb/Eq8nNysS9TGnefKkRv/R3T8m6YeLjSPqgpx1ZuYPWqVZw4cYLY2Fjq169PuXLluH79Os7OzpQtWxaj0Vgia6itqMJHYUlF0RwLFFiLSkqJasqJZjRS2RGotMVRYfKnvAYUgoCXwhxvhSVmiCRJWrLQo8FALgZMUNBAaUsLVSnKK8yf2lbRnVxRFIvXxMGDB9m2bRvr1q2jdevWNGrUiPv379OzZ0+USiW2trZcu3aNt956q8Tz8XcQGxtLTEwMMTExuLq60rVrV0JDQwkLC6NOnTqsW7eODh060KBBA/bv309iYiKjRo0iKyuLa9euYWVlxdGjR4mIiMDKyoo+ffrQt0dXspxqkpILFupnjzPt+iVWf96LU7vXkXnrGs6e3gCc3htClcC3MbWyxalsJWL3b0ZUKLDzrE6e1sgwPzUWalmwvmkcP36cbt26ERMTQ1RUFKampnz44Yf8/vvv3Lt3D39/fywtLblz5w5bt25Fo9Fw+fJlhg8fTsuWLRkxYgQ+Pj7/9DBkZP4nmTJlSvLkyZOXPP5z+UkrIyPzpxEEAQtBgZ2owkpQonxDNsH/VYosCDt37uTevXvY2tqi0+n4/fffi91wBwwYwFdffUXHjh1xcnKiX79+jBs3joYNGxIXF4dWq0WSJKpUqfLMdgRBwFU0oaWyFO+ZVaKRmS/eaj8qmtSmgqY8m0Z+RblcOLJzD87WtmRkZLBy5UrWrl1LTEwMkZGRREdHo9frn6i7SCwVCdWzZ8/StGlT+vTpQ8jsBTS9pWNQncaEzf2RiG2/02vFt5RtXI/Dv4WSfD+T9NspGE9coMbZW7QwcyY4OJjZs2cTGhrKqVOnmD9/Ps7OzlSrVo29e/cCPCLyS0IpUU1dlS3NVKVoripF/QfW19cp8qwFJXVVtgw2KcMQkzK8b+LGUBN33jMpTQ2l1XOjJguCULwWir5+/fXXbNy4kW+++QZfX19MTU3ZuXMnY8eOZcOGDVSqVIl9+/aRmZn50vPxVyBJEgkJCYwZM4Z58+YxaNAgJk+ezJIlSzhw4ACpqanUqFGDgIAAtmzZwvHjx+nVqxcajQalUknPnj1JS0tj4MCB3Lhxg19//ZWZM2cCoBAFenurMVFCpubZLtDnj/xOuZqBDPh2G/m52exdOh0Tc0tMLayJP/J78TwFdBzE4V+/Iy1Pom91NQ7y3dU3ipiYGAAiIyP57LPP2L59O8nJyfzyyy8kJSXRq1cvVq1aBYBSqeS9997D1taW33//vdizxNHR8R/rv4yMzLORn7YyMjIybzAGw5MRZdetW0e1atX45ptvGDVqFBs3bmTixIns27ePW7duAfD2229z/vx5YmNj+eabbxg5ciTOzs6EhITwyy+/YG//4ruXRRF1RVFE0Gj5ddJXLBk2luz9UQQ5eDDo/QGcPXu2uJ+CIHDixAlKly5NXl4eCoWC+Ph47ty580TdoiiSn5/P//3f/zFhwgTWrVvH1KlTOXjwIHfv3iV0829UVlhwZetefpm/kBH1m2N6PZXM6DNYn7mGcCeT0B9/5sLx0xw9epSkpCQWL16Mv78/bdq0YdKkSbi5uVGzZk2SkpKIiop6o+9tioKAqaDAUlBiIojPtagWkZ+fz9SpU2natCmzZ88mKSmJKVOmIAhC8SGBQqEgNDQUOzs77t69S2pqKhYWFpw6depvG9vTkCSpeM1UqlSJq1evEhsbi5eXF1u3bmXJkiV06dKFzMxMtm/fTvPmzRFFkerVqzNs2DAEQWD+/Pl8//33BAUFsWfPHs6dO0fHjh0faaeUmcAIPzUKEVJyCiMmn9y1lviIXcVl4g5uwcuvEaYWVgT1+ACFUsWJ31cT1OsjTu1eT979TADKN+yApDKlqUUSNZ3+nVc/nsXD0aTfZJ4V6XvLli389NNPpKWlkZiYyLRp06hTpw4+Pj4sX74cd3d3OnXqhFKppFWrVrzzzjvcvXuXRYsWsX79+uce3MnIyPzzyIJVRkZG5g1k7dq13L9/H4VCgSAIxYFEtFotR48eZeHChezdu5fu3bvz5Zdf4ubmhpeXF5s3F6bvSE5OxtbWltmzZwPQqlUrxo4dS8WKFZ/brlarZcOGDeTm5iKKIgUFBcWBbSwsLOjbty+TJk1i7dq1DBw4kJycHM6dO4dCocDR0ZGuXbsSFBREUFAQgwYNYurUqbi6uj6yGdbr9YSGhtKrVy/0ej2lS5dm7ty5lC5dGldXVwIDA7lw4QIajYbKlSvz5cefMHXAcITsPHp17op3mbIAdO3aleHDhxMQEMC5c+dwdnYmLCyMbt26YWVlxfXr1wkMDESr1fL111+zatWqf8Wm/Gk87DqdmZlJTk4Oy5Yt4/z580ybNo3c3FwGDhxI3bp1sbOzIzo6Gp1OhyiKjBgxgiVLllCtWjWqVKnCli1baNas2T8yjvj4eNzc3FiwYAHZ2dkkJiYyYsQIMjMzEQQBo9HIokWLEASBFi1aUFBQwP79+0lOTsbO3o5Va1Yyc/5UGrcJJLCVP4t3z+brNV9QtUF58o25T23TxUJktL8JnrYKrt/Ts/WbccTu/43U6xcB8KrdmDP7NgFg4+xO1YatOB/+O64VquPi5cOhXxdwMfEW189E0Kh2NdrW8frb5uvvoiiatEaj+XsalKSnBnJ7/kv++AxkZGRw8OBBjh07BoCrqysnTpzA0dERURSpVKkSW7duZf78+Tg6OhIVFYUoiixZsoQOHTqwbt06vLy8nsjJLCMj82by3zoilJGRkfkXk5eXR3JyMl5eXqxcuZLLly8zduxYhg0bhkqlYvLkybi5uREaGsrAgQMBCA4OJiQkhA0bNjBq1CgWLFhAzZo1cXFx4bvvvqNu3brPbTM7O5sZM2bg5+dH165dMTEx4fLly/Tv358KFSpQtmxZWrVqhYW9HZXfasC3y5ZzT6tB62oPpR1o1eYdvv32W3766SfMzc2ZPXs2Bw4coFGjRpiYmJCjNXA9G9I1RtLS0nBydMTcqOH4qdOcPn2akJAQRFEkJCSEffv2MXjwYHx8fIiMjGTZsmWsWrWKhQsXkpeXR9WqVVm5ciWbN2+mdOnSbNu2jfPnz+Pt7U3Tpk3ZunUrer0eT09Ppk6dSmpqKqmpqeTm5lKxYkVatGjxxtzZLAkPR7QVBIGkpCTCw8NZsWIF06ZNY+3atfz4449Uq1aNwMBAOnXqxObNmxkyZAgrV66kSZMmuLi4MHToUDp27IiNjU2JAmCVBKPRwH1jBnlSYaocC8Eaa7EUovh0AZCfn49SqcRoNOLj48PGjRtZvXo1KSkpaLVamjVrRp06dZg4cSKnT5/Gzc2NkJAQOnXqxPbfQynr60zNoKrs2rCfoHfq8eX0zwtddQXINd4ny5jOLS5jJdriqvTCQixMWaPRaNDr9dhbWTG0porFW47iUM4b0a4MF05F4+BREZ+gtuxePIW7KTewc/GgVBlPrB1Lcy3+LDV6TuDiwU0cmtkbIe8uo0eP+k+KnKioKBYsWIBSqaRTp07FwdleG1lZcPw4xMbC5cuQnQ2iCI6OUKkS1KoF1arBY2mnHv8M3Lp1i0WLFrFz5046d+7MoUOHWLt2LfXq1cPV1ZXLly/TvHlzNm3axOLFi2nTpg1ffvklBQUFrFmzhipVqsjWVBmZfyFy0CUZGRmZf5js7GxMTEz48ccfmTRpEoMGDcLDw4N58+Zx+vRpfH19uXv3LkePHsXf3x+NRsOBAwdo27YtANHR0ZQqVYoWLVrQpEkTKleuzKiJE9C7OZKEltvGfO5JelQIj9yJjIiIoGPHjpiamtKxY0fs7OwQRZFff/2VzZs3Uy8ggPZjRrAqNpKNS1ewZ/duKnRqRft5U9C4O3Dmfiq6sk78MnEGbXp0xcnalrt377Jp0ybOJSYTr6zEuotGtuw/xsIpY9n4y89EX0njisqTe1YV0CRfQlAoqVW9KnZ2dnz77bcMHjwYe3t7bt68SWJiIhqNhiVLljBo0CDWrl3Lu+++S40aNcjLyyM+Pp60tDTq1q1LgwYNUKvVxMbGcvjwYVxcXPD390elUjFq1CiWLVtGlSpVcHV1xdzc/IXpTV43RslItjGTZP1V0gxJpOtvcs+YisaYg0owQYnqif4UfZ+dnY0oinh7e0FHvp8AACAASURBVKNQKJg/fz5Vq1Zlz549pKen07hxYwRBIDk5mStXrjBo0CC++uoratasiaenJwAWFhYolX/ujNpoNHJHn0is9jDxumMk6eO5Y7jOHUMiN/UJXCs4S5r+BipMMBdsyM3NLb5nq1QqEUWRy5cvc+3aNQ4fPkxGRgb16tXD2tqa5ORkzM3NqVixIiEhIYwZM4ZNmzbSuk8zNq/ZRumyLkz7/v/4cOIQGrUIRCEqEAURURBRCMoHc6hGK+WRZrhF8q3bfDVpLl9++SVOTk74+PggCAIq7T1MJC1ONhbcupWE0qM2SnsPbl84yZXY49j7NkertOTk1p+p2qA1XQIr8nGXRrRsWIcvv5yGv7//n5rDf5qnBdq6efMmEyZMYMCAAdSvX5/x48fj5ORE1apV/3yDubmwYQMsWgRnzkBODlhaQqlSYG0Nej0kJsKRI3DwIFhZgbs7hgfBxB7u66lTp+jduzcVK1Zk9erVBAUFsX//fmJiYjAzMyMzM5O6devi5+dHuXLlOH78OGvXrqVdu3bMmzcPM7M3Mx+6jIzMHzwr6JJsYZWRkZH5CzFKBrSSBiNGRMTCjbVQaEW4ffs2t2/fZsWKFcyePZuRI0eyaNEioqKiCAoKwsHBAY1Gw0cffcTFixdZsWIFW7du5YMPPsDPz4/t27eTnZ1NWFgYHTt2xCBJpJkIpLzlw5eaq2SjR6LQ7U5AwAIl1ZUWlE64w83jZ0i6cYMvvviCLl26sH37dm7fvk3z5s0ZN24c9zV5XDOV2FmQjtrelnI+VajSOJCA7h0xAnvnLaa0V3lqvRvMoC3L2WNrIEd3l2sHD/Pdjz/RfVU85nfBXHOHa7uX06h9X9yr1mLtpPdR6+7RYuhUrrj78uNvh3Gp25ZWbd5lzJgxLFu2DFdXV2xsbPj000+xsbEhPT2dHTt2sHPnzuJNtLe3d3FApTlz5pCVlUWjRo1YtGgRXbt25fLly7z//vsMHTqUYcOG4erqyvDhw7G1teXs2bNPREX+q9BLBWQabpOqv4GeAkQUiA8S5RRIOnK5R5o+CXPRBieFOzYKx0c26UuXLuXixYvMmjWL4cOHc+DAAUqXLg3AqFGj6NmzJx988AF2dnacOXOGtm3bIooi69ate6H798uQa7jPqfwwsqUMQECBCmVxwh+QkJAwcs+YxvpjS7l05DbHt8ezYtkKqlSpwhdffMGCBQswNzenUqVK6HQ6atasSU5ODvHx8QQGBhIXF8eyZcsIDQ3lWGQEt27d4mDYYX498BM+NV9sFRMEATVmJJ6/wifvf8FbLYPYvGUTFmaWxQcU27dvp1xZDzp37szUqVOxi/2ZKrXqEzxhNO+1b0blzsFo7qXjYZrP2AY2eHgUbpNsfX1f21z+kxQFkDp06BDVqlWjVKlS7N+/H29vb/Lz85k8eTI+Pj7UqlXrzzd2+TJ8/32hddXNDR63TAsCmJsX/gfik5KIHD+etm+/jcPo0WBtzc6dOxEEgYCAACpUqIC5uTnZ2dnFVu6ZM2eydOlSVqxYwd69e+nXrx8KhYIaNWowc+ZMVCo5rZqMzH8B4d9wn8ff3186fvz4P90NGRkZmRKjlTRk6pNJM9xEQg/8IUIuR95izfcbSbx6gyVLluDr60tKSgru7u5MmjSJCxcusH79ekJCQpg6dSqxsbEA/Pzzz8TFxTF16lRiYmLYvXs3cXFxfPLJJ9QJasjq/NucMWZjQMJUUmAqCMXiJzc1g029PsAoSRRk5+If3Iy7ESdp9lYTDhw4QEpKCj4+Pmi1Wn7ZvZ1vInbz68jP+GJXCKKdNRF79nFw4TJM7W3JjL+MhYsjjSd/TE50LMeXradyw3qUbhKIafn67Bw2CnMTNVXqtySgwwB0mlyunDxM2LKvsHcrz424KN79eC7Hd/yCNi+Xiq0G0vrdjpjHbWD9ml/Izs6matWqXLx4kW3btmFnZ4fBYMDJyQknJyfGjx9Py5YtcXBwYPr06axZswZBEPDx8UGn0+Hg4ICDgwNmZmZcvXqV+fPno1ari1P+DB06lH79+v3lFlatMY+rBWfQShrUmD01R3Nm2l0+GzyVYf/Xnwo1PXBQlSHxWCoGvZGmTZuyb98+1q9fz4ABA6hQoQJ16tQhPDycMmXKADB48GC0Wi0nT57E29ubWbNm4eHh8VrHlq6/xcn8vRgoQIEa8RnhL5ZP2cjGhTsRRZE6b1cj49Z92rzdjuNHTnHixAlMTExwcnIiIyMDHx8frl27xoYNGwgMDMTe3p7SpUsTEBCA3lCAuZuIdSkrerz/4lyYj1vLN/y8hez72fQc3R4b0QEPhU+xwFm5ciVlypQhMzOTTz75hKysLJYuXUqHDh3YsmUL4eHhREVFMWPGDIKCgl7PBP6DGAyGR1yYQ0NDWbFiBTdu3KBixYr06tULFxcXAgICGDBgAB9++CHe3oVpfTIzM7G3t3+1hhMSYNasQoupre1zi8beucNnYWHczMqidYUKNLWyolz58kxMSyPx1i2qVKlCYmIia9asITIykuXLlxMSElLs3p6bm8u0adOYNWsWmzZtokOHDq/WZxkZmX8cQRBOSJL0hCuL7BIsIyMj8xqRJIk7+kQSC2LJk+6jwhS1YIpSUKMU1EQfPM3sifNp0jmA/5v1CdXK+3H4UDgDBw6kffv2BAUFMXHiRFq2bEnjxo3ZvHkzgiDg6+uLKIpERESQmZlJ586dadasGb1798ahbBkW5ScRZ8zBQlJgISpRPSRWATISrnDsqx8wtbTAb0gvyo3uh9IIl8KOoBBF+vbtS3h4OMeOHeOOmw21WrcgYV84N+6mYfCvQtb9LOoO7oXaxITqPdohKhXsHPo5Fw8eRbCxIOP6Tc7vjSDp/Bm8g1txaXcoep2Wmi06YzToObByNo17j8bDx58TO9Zw9WQ4leo2JSn+OLqMm9gHdOF+di4pseEcPHCAdu3acezYMVJTU/Hy8iI5ORmNRsOYMWM4duwYM2bMwNbWljlz5uDk5ERUVBRKpZLLly8TGxtLs2bNiIiIKA7es3z5cmJjY8nIyGDs2LG4urr+petAa8zjku4ERgyYChaIwtNF3uUL1/hx5jLupWehzdZTpoYDm9ZuZfe2fXTr1g1PT08iIiK4c+cOLVu2JD4+ntOnT9OyZUsAWrduXRwZecSIEdja2r5WsZplyCAmfydGjKgwKbaoPsymhbuY0GkOZ49cwM3LhXZDWnDjQjJGo5GLlxPIysih3bvtuHr1KpmZmVStWpV27doRGRmJnZ0dzZs3Z9euXdy8eZNSpUox9It+1HunBn61/F7Yv6hDJxBFESsbSwoK9CgUIjFHThJ18ARmanN+27iNmKjjHAoLx9/fnyVLlvDNN9+QkJBAx44dqVKlCt7e3nh5eVGlShWaN2/OwIEDKVu27Gubw3+SosBpCoWCdevW0bNnT+bOncvXX39NXl4eq1evxs/PD71eT/PmzWnatCkpKSlMmTIFtVr9alb6jAyYPr3Q5dfG5oXFZ4SHU9XRkTWdOtHM0xPPMmW4cfkyoXFxHDh5knbt2xMeHk5WVha+vr6cO3eOnJwcfH19KSgowNTUlICAAHr37k2jRo1eYZZkZGTeFOQ8rDIyMjJ/MZIkcVt/hWTDFUywwFSwRPFYHs0bl29SybsiXft0RmeawyXNKRo3aUy5cuXYsWMH1tbWtGnThnnz5gHw3nvv8cMPPwBQs2ZNevfuTZcuhVYnURQpkIysyr/FRWMeNihRPSO35t0rSQhKBS3nTSRqzhK0cVfQlnXi6r10qvn6sm7dOpo2a0aFOn6ELfgJE0SqjX6P6GXrWFevPRkxZzGxMKdS2+a4+PlQkJNHQU4uo2/F0OdQCKU7t8ap6Vvc3r8fPGxR29iSlZHCucPbSb1+kfycLMpUrUXGrWvoC3RIkpFm739GUM+PKF+zAaUt4dyNNEzs3YpT87Ru3ZpDhw5RqlQpUlJSuHDhApcvX+b48eP06NGDHj16kJycTG5uLmlpafj4+ODi4oK7uztJSUmUK1eOgoICGjduzLx583jnnXc4e/Ysfn4vFkJ/BoOk52rBWSSMqIXn35tTqZR4eJbhvY968cOMZdyKT8O/ZTWMSh379u0DoFGjRkRGRnLx4kXGjRvHjz/+SEZGBlCYtsbDw4Pq1au/9nEYjUZO5+/HgB4lz3atzM/RkpetwauGB98dmET3j9swZEZPEs/fIicrjxxdFlu3bsXR0ZFOnTpRunRpmjdvjlar5bvvvmPs2LFERESwb98+Nmxfg7WnGlMsS9THnKwc/m/Y9Ed+1mdEN+o08uOHmcvISs8lMeUyO37fweTJkxk4cCBr164lPDycSZMmYWNjg1arLU6V8l8LqJSamkr9+vVJTEwkODgYW1tb8vLyAHjnnXeoXr068fHxDB48mPnz59O5c2datWqFJEmvJv4kCVasAKOx0Lr6Ak4lJxN56xajAgIAMDx4H5JMTCgrSdx6EPW8bdu2hIeH4+npSWBgIMuXLwcodvm1sLB4PXduZWRk3khkl2AZGRmZ10SGPpkb+vOYYYnwDIva/h3hrP9pM34B1Um+eQeVuYLy7p7o0gVSUlKK0300adKEsLAwHB0dad26NQsXLnzqhiyuIIvvdUlYoUT5HMta1q0UfqoZTO+wtaScOsf9G7cwc3IgNz+P7M37aRIQyKhvv+adVq1I2BdO/x2rsA6qTdaZBGzLumFq96ilxGg0MtvGh/eObcHeuzI7v/wBtY0F+it3yLl5E/egIC78tIqy1QPo+sViVn/em9TrCeh1OnLvpfPh8nBuxEWz6auRBHQcjE/jNqhtnNi/ah7ThnWhjIsjqampfPLJJxw5coSVK1cyd+5ctFot9+/fx9LSkmnTphEVFcXhw4f59NNP6dKlC9OnT+fq1ascOXKE4cOHo9fr6d69O5UrVy4WI8YHAV3+KjKL1oFgXaLyHer15oeNczkaFkXStVu4ejgjmMCVI7dZsXwlRqMRT09P+vXrx5QpU1izZg2dOnXC1NT0LxsDwDVdLPG6SJTPcQOGwvkMtu1PBd9ytOrXmB3LDhDYphY59/M4dfAcmtx8Stk60rldV1avXo1Wq0WlUuHr64uXlxdffvklJiYmiKLIFd0Zco33MXmB0C9CkiSCPN9h87FVOLo4oNfrUSqVxa6wer2eAoUGF7E81d3qEhsbi4uLS/HvCwoK/vX3HB93+83MzCQqKopGjRphaWlJp06dqFWrFhMmTGDq1KmcOXOGTZsK0/iMGTOG6tWr079/f7Kzs4mMjKRhw4avHqDo4sVC62q5coV3VF/AzawsemzaxOauXXG0sMAoSYiCwJEbN9hw5gzvurnRfONGdIC/vz/h4eHcvXuXY8eO0blzZ5RK5b8q8reMjMzzeZZLsGxhlZGRkXkNFLoCX0ON2TPFKkDDFgE0aBFA1KETOLo4YKoy52zcWc7Fn+PKlSscOHAANzc3KlWqxPLlyzE1NWXfvn1PFauSJBGmz0REeK5YBcjPvIedV1mST8TiVrcm18IiiJ63FI+3AridlkpUVBQt69Yn/eJVKjWsx31JjxkiLjW9nxCrUGjdrdGvC1v7jiIp7jLXN4Vy93Qcbh1bkhwdjVurZogmaq6djuD7QU25cvIwVRu04uM10XQYN4+vO/lw5eRhek1fjadfA1Z/3htra2tsy1Zl5uxv2Lp1K3379gVg4sSJZGVlFae/mTNnDnZ2dmzfvp2RI0dy+/Ztjhw5gsFgQKPRcOfOHfr370///v2ZPHlycXRdo9GIJEl/qViVJIlUww2UlCx9TGpyOgFN6mBqZoJvvWocOxjD4q9X4lnFg+MnjzNnzhyGDx9Oo0aNaNKkCQC9evX6y8WqJEkk6uIQH/x7HqIo0qJHQy6dTuTwlhgGTutGr0/a0WNMWzJT7iOKIukZaYSGhpKenk56ejoVK1Zk/fr1zJ07FzMzM0RRRCdpyDZmoKbkYxMEgbFfjmTB1Ec9yIoEnFKpRI0Zuw7voEmTJsU/L/r6bxarRQaHorFotVoADh48yLp164iJiQFg7Nix/Pbbb2RkZDBo0CAOHjzI0qVLiYqKKn7eAFhZWdGiRQvMzMwwGAyvlrN43z4wMyuRWAVQiSI1nJzYf+0aAMYHbTb08MDawoKvjh9n6bRpdOnSheDgYKysrChXrhw9evRApXoysraMjMx/E9nCKiMjI/MayDbe5YruZImtagAFBXpUKiWXribw2/d7kTQK7ty5Q2hoKFlZWdi+IFhJsiGfmfnXUEkC6heIMENBAYtrtESfl4+JjSU1+nQmLz2T/DwNOXfS8Hd2JyxsP92nfIp7l2CSJR3mzxHeAPr8fOaU8sWxXm28enUhNSKSjNh4BJ2Bd9at4crydZz8eQn1Ogzk3dFfF7/OaDAwsbkLXx5IK/7ZgveC8GvZhRodR5J6cjfnNswmMjISS0tLVq9eza5du4iMjGTJkiX4+PjQpUsX4uLimD9/Pr/99ht79+5FqVQSHBzM8OHDH3GR/TtT2OQa73NJdxxTrErUpl6vp0/zoej1erLv59ChTxsy0zJBKMxd6lmqKh4eHgwdOvRv6P0f5BjuE64JQYHqhYIVQJuvo43jQN7uE8TIOX0wNTfhzJELrJqxGWt7S25fu0OgXyOcHVyZM2fOU+u4Z0gjsSAWM+HFrqQPo9fraeAezMEr2zEz/0PsXrlwjejDJ9i5MQxNvobPxnxOj669XqruN434+HjCwsLo3LkzLi4uAOzfv5+ZM2fi4eFBkyZN6N27N5999hlOTk4MGzYMU1NTmjRpQnBwMOPHj+fjjz9m165dtG/fHl9fX7p16/Z6OqfXw9Ch4Or6ZETgZyBJEnOPHeNSRgbzgoMxf3CAkKvTEXL+PJYaDYcLCqjapQvDhg17Pf2UkZF5Y3mWhVVOayMjI/M/wV/uBmq4jfgSj1Sj0YhKVVj+0JYoMrLTWP/Tb8TExCCKIjYlCFZy3pCLFiPmT4k++zgKlYqyb9Uncd8RnH298WwZROq5BI5+/SO21SvRas4XNDSbQilUHDdkYfKU4DqPozQ1xat1U+5lZOHVtR3lO75DxAfjSYuIIfPseap/MJRO/WY+8TpRoaBpv09YO+l92n08F3MbO8pU9UNQKNkxYwB6wYQqpd1wd3cvDii0a9cuTExM2L59O25ubtSrV49Dhw6Rm5vLggUL+O2333BxcaFFixZPtPc04fhXidhsQyYCQonrViqV+NSqQtLVW4QcWQEUHmSEbTtIKXcbOjbog7n4cgLudZBpuA1IJRKrACamavwaexO16xSanHx6jG3L4s9/JSUxjSadA2gzuDE9WwzCXVX5mXXkGe8jSAIlWHqPoFQqGfxJf36avZIPJw0BYOfGveRk5XL/bja9hnUhqH0dyqte/z3fv4sLFy7w+eefc/HiRZo1a8aZM2dwcXEhMTGRSZMm8eGHH1K+fHk6dOhA1apVqV+/PocOHeL06dMEBATQoEEDvv32W4YNG8bw4cM5cuQIo0ePxtHR8fV9FlJTC++uvsQ9YEEQ6Fm9OhP276f/li183qgR59PSWBgTQy0XF74JCqIzgCxWZWT+p5EFq4yMzH+aIqH6sFj9K8SK1qhBUcJHqiRJXE1I5PeQfRzYcRhXdxf6j+uKSq2kYcOGwNNF1uPcR49YwrIApSqWx75COQw6HZHf/IQuO4e3v52M7Vt1yFEoMSJhQMIIKEpYZ/Dir1noUZcLP68mcWMoJo52BC2eT3nfBuhUeqQs6Y9cnZKENjeb6G3LMbexJ+7gNspUrcXZsE3k3M3g9J4N1GjagTq9J9NUPE1GRjq5ubksXryYNm3acOXKFQ4dOsSZM2eIi4vDYDCg1WqxsLCgT58+xX0qyeFE0ZydOXMGg8HwevJOAgXoEHi5wD0ubk54eLkDhfcRVSolwZ2aky/lYET/Wvr1suQZs176NRNXf0AH92Ekxt9kZNAkBIVIz3Ft6fNpBwrQkmu899zXayUNYgkOX55Gr6GdaezZBnNLMzatDMXG3pppP3xORW8vADRSNnoKXqnuN4Fff/2VevXqsflBEKKCgsKxxMTE4OfnVxyIbdSoUcyaNYuVK1cSHR3NggUL2LdvH+np6XTr1g1JkqhQoQJeXl7Mnj2bWbNmvb5n4b17JXYFfpjSVlbMe/ttFkRFMSsigvtaLVPfeotmnp6FQZyuXy8Uwn/hgaOMjMybjSxYZWRk/tMUCZejR4/y3XffsWDBAhwdHV+5vuTkZCwtLbF6LAJmocwr2WZNEAScSzvh5OrA9MVf4F2zMhopG4mXu6JRIEklbhNAbWWB2sIcnx7tKMjNQ21pAcB9SY+BwrqkB6MpKSa21thW9yZxYyj15kzBulolTPQqBK1QXEvRAYEgCESHriT02/E06Doc/za9id66AlNLa+xc3XEqWxF9gY7EmN0EfNyZiAN7yc3NZc+ePWzatIkLFy4QERFBZGQkTZs2pXbt2vz222+0atUKJyen4naeJlaLAtMUlTly5AhXr15l3bp1fPHFFyUe74t4mXVQhIWVOeYW5kiS9ESU2n/q2s7LrkUAS1sLqtbxIuV6GmN+HEiLHg0frfEFY3mVNoswNTOl28COHA2LZvaKqVSr9fid7xe3/6aSk5PDypUrOXjwIAA6nQ61Wg0UPkuuXr1aXHbIkCHMnz+f3NxcPv/8c2bNmkVycjITJkzA3d29uNz8+fNL5MXxUjyI8Psq2JqaMrFxY3J0OiwfjA34QwD/S987GRmZ14MsWGVkZP4zSJKE0Wh8ZNOfnJzMihUrOHr0KEOGDHllF7iYmBjmzJnD7du3WbVq1ROCVSGo0UlaeE76jyKMRiNWNpZ0H9TxQb8LRY74kpY5S0F8qS2+38AexeMuEqsARsASJbkYUDwQrSWdIwXQdPt6zNSFfdcLRgRJwIiEwiiQlngRQRBx8KiAIAi4VqiOmbUd2ekpuFb2xbVCNWq37oUm+x6/zR6FVSlnUm5ex3pCT/z9/YmKiiI/P5+yZcvyzjvvMHv2bGxsbLCzswMo/j083dJcZG0tWhNF4/ruu+84c+YMGzdupFq1ai8xi89Hiarw/XyJ5dV9UKenuy3DK1sc/ywqwZSX9s0Fvt33xTOs28ILI/8qBfUDwf9qjJ467DlrVngixdS/hZSUFFq2bIlGowEoFqsAnTt3Zvbs2axYsYL+/fsTFxdHcHAw5ubmmJmZMXny5OKyDz8fnZycXn9Hzc3/tLB8RKwCFBSAqalsXZWR+R9HfgLIyMj8ZxAEoViYnD9/HiiMoHn16lXS09Np06ZNcbmSsnv3blq3bk2DBg2oXLky4eHhlC9f/olydqIjhhe4HBoMBuAPq2/R9zrysVU4vrSI9hTMEZAwlHCT+LT6C18rUVWwQABEQcBWUKEtoRRWiKBSKopLCwKoDQoMohHDrXvM7VGLBe815MLRXQBk3LqKUqWmTNVa5GamYV+6LDcTTnNy11oUSiX1e4zCysqGLRvXk5+fT3Z2Nu3atWPnzp388MMPlC1bFjs7u2KXyDVr1uDh4fFInx62pBXN9bx58+jevTtLly4FYMaMGWg0muLAVq/L+mYmWCEJLye6niq0JSMCYCL8tdGAn4WtwolCm+fLzcvTxGphHRJ2CufnvtZCsH4pF+jH37MXfX5MBPMS1/13U/QseBpqtZqMjAxu375dnC9Wp9MVv+bTTz/l5MmTvPXWWwwdOpTAwMBH0tIUCdWHn49/CS4uhYL1dVpDc3LAy+uVXI1lZGT+O8iCVUZG5l9LWload+/eLf5er9czZcoU/Pz8mDVrFuPHj8fe3p7u3bvj6enJ2bNngZKJE71ez/fff8/s2bPp1KkTEyZMKE4lUiSWHsZG4YSAgFF6tlgp2izeTLzNxBEzuXTuCgBGDDgoypR84A+ooDTHSVCj+RNWqXyMOApq/FTWmKJAKxlxFdUPXIRLhoVKQG8EoyAhGgQUehGjwoiztQf+bfpSoNWwe9FUbl08Q63gHuTnZqPLz0OSjChNzLidcJoCrYb2Y+dxcudakuOjGTFiBHFxcYwZM4bBgwfj7e0N/CFKnpaO5OGNeRHp6el06tSJxMREJk+ezJIlS1i2bBleXl7Url2b5cuXv/LcPQ1rhQMiCozSswVISShAg53CBaWgfnHhvwB70RkFKoz8uXEAGNGjQIWN+HxXfFPRsvi+8/N42vv8/PJGBIQ3WrAWPRsSExMf+bkkSf/P3nmHV1G0ffjePSUnlXTSCYRAQg+EXkJHelVQQJqAnzQVECnSxBcFC0VQpAgqghRBkCZIC70GEELoJJAAgZB2kpy28/0REkFqIIi+797XlYuczezM7JzdZX7zPPM8BAUFERoayubNm/Pdf/V6PWazmSlTptCsWTOmT5/OxIkTiYmJoWfPnvfU8TA3+ULHwQECAiC94PufH0pGBlSoUHj1qaio/CtRBauKisq/kvT0dHbt2sVvv/1GdnY2R48eJSYmBo1Gw/bt23njjTdYvnw5S5YsoU6dOgQGBrJp0ybg0ZaYL7/8kqZNmzJ//nxat27Nli1b6NOnDw0bNmTXrl1cunQJnU53n+jVSjo8NP6YMOYfe5DVpH/7d/hm6iIqRJYhrEIpzCIHg+SAo1Tw/WQ6Saau1h0zylNZCIUQmFCopXXFQdZQWetMGhac0WInyZgfIb7vxsVOIjPpGhdW/IK9RY9QFBASzjn2NP+/CRQtHs7tpEtsX/QpB35ZQGDZSLIzUnFwccNqzsG1aAA3Lp4m/uRBrGYTjZs0Zvny5cyYMYOKFSs+8fXkTcyvXbvGmDFj+OWXX/D09OSzzz7jvffeY968eVy9epVNmzZx+fJlxowZw48//ojZbC60wDMaSYOXJgAz2U9dhxACBQVPjX+h9OlpkGUNRTXFCiXok4INH00wsvxo656D5IwOA1bxYE+FvHs8eKGu6QAAIABJREFU73u+kXSTzz+YzcaVW/Itjw/CTDZumqJoXpB79YP4a383btxI8+bN6d69O9OnT+fEiRPAn4tjffr0AaBXr17ExMSwcOFCGjVqxLlz5zCZTEiSRL169YBHW2ufOy+9BHctIj4TNluutbZq1cKpT0VF5V+LKlhVVFT+NdydzN7FxYULFy4wcuRIypcvT0JCAiVLlmTgwIGMGjWK4cOH06FDBz7++GPs7OyoUaMGx44dIy4u7oF179q1izJlyrB3714mTJhAYGDgPW51YWFhhIWFsXjxYuDBVlofbXG0NjsyTLnRUPOsJvu2HyIp4ToA/sX82L/9EJ16tcUiTAhsFNOVe2rBVFXngqekIwNbgUSrEIIMFNzQUkOb6xZbRuOEHTJmFErJjtgAy2NEq81qxU4WkJnKsQmfo1xLx2oncM2wR2OTcXL3pmKTTngFlybbmM6W+ZO5du4PilWoQbHyNUi9fgWDUxHKN+pAjmRHlwHvs2LJYlq2bPlU47Fy5UpatWpFTk4OERERCCHw8vLigw8+ICgoiNjYWFJTU1m3bh2VK1dGr9fz/fffP1VbD8Nd4wuATTyd2DOTjYPkUuB8pIVNKX0kGnSPdXV/FDYsaNARqn+86JAkCW9t0H1iP0+A3f2MLF+wmv7t3kajkalQtdxDLYhCCGzY8HgKD4bnSV5/d+3aRXR0NNHR0UyYMIGFCxeyefPmfMt/3n7VUqVK8cknn9C6dWu+/vprli9fzoQJE/jmm2/y93Pn8Vzdfh9H5crg4pJrGX1WEhOhTh1wd3/2ulRUVP7VqIJVRUXlH43R+KfFUqPRIEkS+/bt4/z587i4uODq6sqgQYNo06YNrq6uxMbGYjab2bt3Lx9++CFGo5ElS5ZQv359wsLCsFofLCJWrFjB6NGjWbx4MTVr1qRFixb3BCZxd3enWbNm7N27l1u3biHL8j0CUQjBtavXif0tEZEtkyXS2fTL77Su8ipLvlnBt9MXE715L+9++BZX45O4kXoNgUIJXSXsZaenHp8iko7een8MyGQ8oaU1V6za0CPRW++Pm5zrXusgaWii9SAVKwZkwjW5ojVLKPftkxVKbls2jYwRBT87HbKsZfOwdzBdTcYj489rimjWGZMxg4qNOuIZWJLs9NvcTryMd3ApnNy88QwsScOBn9Ko7zjG926V38eH8SBrWl75EydO0K9fPz799FOCgoKQJAmr1crevXt57bXXcHV1JTs7m82bN5OcnMyGDRvyrVeFhZ3sQJA2HBNZBXYNNoscJGSK6cs+lzyxBcFe40yovioKtqdyDc47r7S+GvYax8efALhpfDFIjphFTv6xPAF2ZO9xflu9DQBjZhZtu7ZgyPg3cXF1IjPD+MD6TBhx1/jg8ALFf54LM/x5727dupW3336bZcuW4efnx6hRo4iNjaVjx454eHhw9OhRDh48CNy7UPfee+8xc+ZM1q1bl59z+FHW5b8de3vo0weSk3MtpE9LRkZuXa+8Unh9U1FR+deiClYVFZV/LIcPH2bQoEEcPnwYyBUjUVFRDBw4kEOHDtG7d2/GjRvH2bNnuXr1KgDR0dFIkkRaWhrLly+nfPnybNy4EVdXV8aMGUPZsmU5efIk8+bN48qVK0CuKL5y5QohISH3tL9w4UJWrFhBTk4OGo2G8uXLExwczI8//gj8ORG1WCxIkoS/vz8b1m7gyxGL6FZtEBtX/s6Xa/7DuDlDObj7CGt/Wo/GSaFxu3rMH7+UUnZVMYinF6t5hGgdeVMfiBMyt7GSLWwoDxB8ihBkCxup2HBEQz99AKV097YfonGgpsaVZMzYI1Ne44yPpMeMwChsZNosZAkbWZIgCwVjfCLLI9uw7vUhuHgUIfnECU5+ugBh+XOy6uYTRKkaTUg8e5xGvUZg5+hMjjENN99iNO03huCol8m2Qr+Kehy1f7p93tf/OxPzv+bUzSufnZ3NoUOHKFu2LEB+VFU7O7t8d8umTZsSHh7OBx98gJeXF35+fs8y9A/FTetDoLY0OcKIRZgfW14IQY4wIiFRUh/x2Ii6fxfF9WUJ1IRhw1IgS2te+UBNOMX0ZZ74PI2kIUAunXv+HQv1lUuJvNF6MB+/9wWZ6UayjNkUKxnIj1+vYETvcYzoM57hPceyZc124M97wiJMaNDirw19YeL/7lRLFosFWZY5c+YM/fr1w2g0MmPGDEJCQkhPT2fHjh0sXryYRYsW4ejomO/NIcvyPf3P27/91yBu/xgqVIAWLeDSpacTrZmZkJICb70Fzi/Wy0BFReWfwT/sLaeioqJCvhU0ODgYPz8/tm3LtaqsXbuW/v37c+jQITp37oxGo6FEiRJIksTWrVsB6NChA25ublStWpU1a9YwY8YMFi1alF/3l19+SbNmzYiOjmbIkCFs3rwZSZI4ffp0fp7CjIwM+vbty8SJE9m0aRN//PEHAF5eXtSpU4fVq1fn73uUZRmdTkdCQgKzZ89mxYoVbNywiWHvDMdyGyb1mcnAlqNp3qoZn86YQpC2DDM//orF85aBWUarLZx9daE6R4Yagmmoc8cOmVSspAsrGXd+0oWVVKzokYnSujHUEEy47n6xLEkSNbRFqK914zZWcrARJBuIkJwIlRwopnHAXzLgfPkmCZ8vJCDNwvXT54jo2p7Xp46nRGAxbsQdZ9fmtZittnyRWbXV68T8toyA8Mq8/f0+WgyYhMUmuGGxRy8LhlTRU8xFfuTkO+9vixcvZvDgwVy+fDl/Im+z2bC3tycoKIjVq1fnfzaZTFy8eJHJkyfTsmVL3nvvPebMmUPlypULZdwfhac2gBL6isiSRJZIxySy7rMc24SNHJFJDpk4y26Usot8Jov786CcfV1CtVUQgIWcR1pbFWxYyEEApbSRlLOv89CyfyXvuXfWuVFMWwaTyMImLFyIu0SFquVYsn0eHV5vhYOjPQ1a1GXhxtlMnD2KkVPfpWbDalw+lwDk3sNmkdvPEvpKf3vgqrstnpIkkZSUxLBhw2jTpg0rV64kJCSE1157DUmS8j1Izpw5Q0xMDGXLluXYsWM4Oztz/Phxbt68+VCx/UJdfx+FJOVaRlu0gMuXn9w9WAhISoK0NHj3XSjz5AsdKioq/91I/4ZE2pGRkeLQoUMvuhsqKip/M4sWLeLYsWNcv36defPmMXz4cC5fvkxAQABeXl5cu3aNqVOnsnz5crZu3UpAQABBQUF069aNtLQ0ihUrdk99RqORIUOGMGLECEJDQ1m8eDG//PILs2fP5p133sHLy4vPP/8ci8WCyWTCycmJgQMHUq1aNbp164YsyyQlJWGxWPJTqaSnp9OuXTv27dvHyy+/zM6dO7Gzs2PKlCn88ssvAMyfPz+/D3v37qVmzZq8+uqrvPXWW9StW7fQxy1TWDluzeCYLQPjHZdUR0lDeY0zlbTOOD1h8JmbipltlltcVcxIEhiQ2TN3MTcvJ+BfLoyTO3bjEVqCvQuWUDEigl+X/MTGX9cxeMgQytZpQXifz7EKMGglHLRw8cAWgqo0INsmYxUSOhnqB2poVEyLQft4C9i3337L5cuX8wNfSZJEly5daNiwIRaLJX/hYMCAAQQGBuLu7s6KFSt4//336dGjxzON6bMghMAoUrlpvUKqcjM/Dq4ANGjw1ATgrvHBTv7nRrEFSLfd5rRpD7eUJATKfSlvJCQkZDxkP8LtauGscX1snadPn2bfvn33RLadNWsWy5cvp0uPToQ3CeTgzhg2Lt1GdlYO4RVDuXQ2np6DX6NK7UrcvpnK6sXrWf3DOiZ8OZKIGuXIwYgeA8X1FR4p/rMsgmtGQZJR4UqGwGQTaGUJL3sIcJbxcZRxMzy9ZTYtLQ2DwUC/fv2oVasWNWrU4P3336dp06Y0b96cQYMGMWvWLEqVKgVA7969SUhI4MqVK3z22Wc0a9bsnytKnwQh4NgxmD8/V7S6u+daTP8qwBUFbt4EoxHCwqB3byj66BRIKioq/51IknRYCBH51+P/nJB5Kioq/5M8yM0zJSWFbt264eXlRYkSJdi6dSurV6/m008/ZfXq1djb2+Po6MiQIUPYuHEj3bt359q1a1y6dIlBgwbh6uqKq6sr33zzDevWraNNmzb07t0bR0dHjh07xqlTpwgNDaVZs2bExcUxZ84cPvzwQ+rXr0+vXr0oX748Op2O9PR0rl+/jouLC0IIhBD4+uYG1MnOzkaWZUaNGkVOTg6zZs2iV69e/PHHH9SqVYu1a9dSqVIlNm3axJo1a9Dr9Xz00UdERkZSo0YNlixZ8tzG1EnSUkvnRi2d2+ML3yHPdRFyvxMhBJ4aPZ30Ply3ZLP7/Gk+HzuB/b+sJ7BSOS4fPYG9Vsf/DX+fY3MWc2DTFnIyjfj7+4MQJMcdpG/mVgKqNOFSpkR8ukLpmk2w00AlF5kQN5nS7jL2DxCqd/cFcgMp1axZk61bt3LgwAHi4uIwmUzMmjWLtWvX0rBhQ3Q6HYqiEBgYyFdffcXvv//O2bNnWbNmDaGhoc8+qM+AJEk4SW446d2wCSs2rChCQSNp0KBDlv75zk6KsCGw4ab1RWPTkaMYMYlsrHfchLXosJPsMciOFNF4Iu5c48Ou7fDhw5QrV46zZ8/y7bff0qpVK1xcXHjzzTdxcHBg2rRpzJ8/n+OHTzL08/4UDfDEarbh4liEVd+v48DOI7h5urJw+o8oQjD9p//gG+JJDka8NIH4aIs/NCrwlQyFvYk29ifasN3R3HoNyFLuIoLJCmBFIFHSVaZhMQ2l3GS08oPFq6IoyLKMTVgxKmmcPneSuXPmo9VrqdmwKkaRSnB5P94fPQKL1UpkZCRhYWH4+vqyadMmgoKCMBgMzJo1iwsXLuS7tN9d978SSYJKleCTT+DwYdiwAeLjQZZzxawk/flv+fLQtGmuYP23Xq+KispzQxWsKioqLwwhRP5kLDU1FYvFgpeXF3Fxcdy6dYv169cD4O/vz/bt24mKiqJLly5ArrW0TJkyWK1W7OzsGDNmzD1CZ+nSpSxbtozhw4czY8YMYmNjmTp1Kn369GHlypW0bdsWDw8PmjdvzpQpUxg6dCjvv/8+w4cPJyQkhNTUVP744w9KlixJWFhYvqVj2rRpzJ49m2rVqtGrVy+Sk5O5du0aGRkZrFq1Cjc3N6pVq0Z0dDQtWrSgUqVK/Pjjj1y/fp13332X9u3b51+/zWZ7oRaUjIwMfv/9d1566SUMBgM5OTnodLp7+nTp0iW++uorsrOz2ffzrwQGBtI0ohp6vZ4lS5ZgfyOVWrVqcfDgQUaNGkX16tWJiIgAoFmj+jg66qn2BH25+7uTJInbt2+TmJhI2bJl2bFjBw4ODowbN46KFSsihMDOzo7KlSsTGxtLdHQ0devWzXe39ff35/XXXy/08SoMNJIWDVqeIN3oP4ZMJZV48ynM5KBBh6PkipP2wYshQgiyFSMXlOPYSfYE6crgKBfJ/9v06dP57rvvCAwMZNiwYYSHh1OxYkWWLl3KwIEDmTBhAvb29owdO5YDBw6QnJxM/75v0qnO69y0JXI+8TQ3b97E2dMR/zBvhk97C72dDr1kwF32xV3ri14yPLBvWRbBr+et7E60opMlPB14qAgFCSEEiUaFOTEKQS4Sr4Xr8HW6X0xZJTO3LFc5cGo38Reu8O4rYxnx2RBe7deBzHQj27pHEx8fT79R3alRrxre2iCyzVl0796dcePG8fLLL+Pj44O9vX2+WM17N/xrxerdODhA3bq5P5mZuW6/2dm5QtXVNdeaqn8x+YZVVFT+HfwXvAlVVFT+LVgsFmbNmpUf/VKSJBITExk8eDC1a9emZ8+e3Lp1i8DAQNzc3Dh9+jQA5cqV48aNG+zevRuLxUKnTp2oW7culStXzhewWVlZZNy1V+rkyZNUrVqVZs2aMW3aNK5cucKaNWuoUaMGqampHD58GEmSKFKkCO7u7sTHx/Pmm28yZ84cihcvjp+fH2vXrsXV1ZVt27Zhs9lo1aoVkyZNonHjxty6dYuBAwfSv39/tFotixcvZsuWLbRo0YIKFSpw48YNlixZwvLly+nfvz/btm3LF6t5VuUXJVbzgrU4Oztz8uRJ+vbtyzvvvMOaNWvQaDScPHmSNm3aEBkZydq1a2nUqBEnT54kODiYyMhIXFxc8PHxQVEUfvjhB6ZMmULFihWZP38+q9auZMznw/li+USSdGe4YD7OdetlMpTbKA9IkXN30CTIvUcyMjLo3r07//d//wfkBpkxm82ULFmS6tWrM2HCBCA31UdAQEB+EKx/tfvkPxAhFBIt5zhnOoyCgr3kjF4yPDKAkSRJ6CUD9pIzNmHjrOkQiZZzCKEwYcIEtm/fzvfff8/KlSupWLEiJUqUoGHDhmzevJns7GwCAwMZPXo0rq6uHDp0iKZNm/L1119jLzvz9fjvGNJmLFFVGjN59FRK6iMo51yTcnZ1KWNXCx9d8YeK1fh0hY/3m9ibaMPPUcLHUXqEWP3zWtwNEgHOkJwtmHLAzI54S/7zK4QgxZrE/LUzGDliNNNHz6V+4/o4ujjiaO+EVtIjKRpavdKMSlUrUDeqLpKQmTR5Ip9++yFlq5Xi5ZdfJicn5762/2vvZScnCA3NDcxUvjwEBqpiVUVF5bGoglVFReVv4dSpU3zwwQfIskyFChUA2LRpE7169cLT05OTJ0/i5OTE7NmzSU5OpmbNmixbtgyAsmXLkpSUxMqVK5EkiaFDh3LkyBHef/99cnJyGDp0KJUqVWLYsGGsXLkSAF9fXzw9PTEajYSGhlKlShWOHDmCi4sLderU4cMPPwQgNDSUixcv4u7uzsWLFwkMDMRkMhEfH09QUBChoaEcOnSI8+fPExgYyOXLl8nMzGTbtm2YzWbWrl3L4cOHcXd3x83NjZIlS5KQkIC3tzd16tQhLi6O+vXrA/+cqJ55k+HNmzcTHR3Nxo0b8fb2pkOHDqxZs4a6deuSkJCAJElMnz6dLVu20LhxY4oUKUJsbCx16tShRYsWpKWlsX//fhTJxsylU/j15A+M//5tdH4WjEo6WdYMjEoaSdYLnDcf5ZRpD8nWBIxZmUDueNwtfr7//numT5+Ok5MTxYsXJyEhgR07dqAoCuvWrQNgwoQJzJs3DwA/Pz8aNmyYv2ihUngIoRBvjeW69TJ2khM6ya7AdegkO+wkJ65bL7Pv4jY2bdrE3LlzKVu2LBqNBhcXF2RZpkqVKnh4eLBs2TJu377NjRs38hcrABYsWEBKSgp9+/bl2LFjjBwxClc7T5xkVxxkF7SS7pH9uJimMPOIGQH4O0toHiNU/4okSXjaS3jY2Vh+xsaWyzZsipV4aywnkvczccDnWLIVvlr5OXq9jtf6deKXxbn3axE3F3oMepXo3/Yyqt+HvFyzF3FHLxB//grVI2qyadsGBgwYkB/YTUVFRUXlflTBqqKi8ty4fPlyfoRfHx8f9uzZQ9WqVRkzZgz79u2jdOnSpKen4+iYm6Nx2LBhxMTEYLFYaNu2Ld999x2Dho2kaat21GjYgj5DRiBrNNSsWROTyYQkScTGxnLq1Cl27dpFp06d+PTTT4mJiSEoKIgrV64QHx+PImzUb16bmJNHSLFco9fgrly/cY2BAwdSuXJlNBoNQ4cO5euvv0aWZVq3bo3FYmHlypWsWLGCtLQ0Nm/ezIYNGyhdujS7d+9m9erV/PDDD0RHR3Pp0iVCQ0NZtGgRQghmzJhB165d8wMz5VkRX4TV5O4ckACxsbF07dqVli1bsmDBArp06UJUVBTTp0+nYsWKrFixgsGDB7NlyxYiIiJISUnhu+++49VXX6VcuXKcO3eOQ4cOERERwRtvvEHbTq246Xiea5aLBAQEYpCcsMMBvWTATmN/x9rmhL3kzKW4BHq93psO3dqQoxjRaDSsX7+eH374gdTUVMLDw7ly5Qpff/01/fv3JywsjPj4eGRZ5vjx42RmZlK3bl0MBgM//fQTAHXr1iUqKupvH9f/dq5az5FivYa95FzgPbZJCdfJTM9dlJAlGXvJmRx9Ghr7P1MNwZ/PRd7Cw/r163Fzc8PJyYlx48ZRtWpVwsPD2bJlC+7u7gQHBxf4OpKzFL6OMWOvhSJ2BffDvnB0F9kZqQAY9Fo85QxGjhrJgAnvsfdINEXd/GjdpRmnj53JP2fgB32J++McF+IuAeBfzJcft82jffeWfLlsKuOmj+DsiYv8uG0ek5e9R6oxhfPnz98zJioqKioqf6IKVhUVlWdCCEGGcptEyzniLbFcscRxy3qVLJORHj16MHjwYM6fP4+7uzve3t6sXr2aYsWKMXPmTIKDg3nllVdITEzEZDJRtWpVihYtyobftmD0LEfziSv4w+yNb8u30TR5j/XZ4fT/ZgeN2rzC0PdGEBsby/79+6lZsybe3t40bdqUjh07MnLkSJo3b05q2m22H9rMgbRNmEokceHqGdbu+4lTtt2MXzoIxTGbrBwjp0+f5uDBgzg6OrJixQqWLl1KmTJliI6OpkaNGiiKwp49e2jZsiU+Pj4MGDCAl156ie3bt5OSksLcuXMpWrQo69evZ968ebzzzjts2LCB6tWrA3+/RdWmWLhqOcsB4wb2Zv/Cvpw1/Lh/FqFhIVSuXJk1a9YQExPDwIEDuXjxIjt27MBoNLJy5UrKlCmDTqdj5MiRuLi4MHjwYFxcXJg7dy5jx47Fy8uLn3/+GYBPZk2i04gm2NkbcNQUQZY0+al+7ubovuMMfGU4vZoNpHSZ0kz+bgzH03bzeq/ufPTRR0RHR9OxY0cMBgNDhw7liy++4PTp0zRq1Ijq1auTlJREfHw8cXFxAOzfv5/OnTv/rWP6v0SGLYVkWwL2klOB8pce3h3D211HMuDlYZw9dSHfo0CSJFISMvAJ8eTIqT+3A9xN1apVkWWZ1atX8/3339OsWTMmTZrEu++++9SRtG2KYOlpCwJwKYBYVRSF7T98wbTuNdixeBoXju4iKy2FMwd+Z07/hhT1UJCKOjKsy0QURaHbW53JzDBy5mSu6NRoNDRr35AJgz8B4Ob1W7zTbRT2jvb4BhbFarWRcvM2xw+c5MaFNITeSpop5b5gYyoqKioquaiCVUVF5akQQnDTmkisaS/nzUdJtiYQc/oI3y78loMXozkrDlCvZQ1SU2/z7bffAvDGG29w/Phx2rRpQ2xsLBcuXKBRo0ZkZmayZcsWAKo2asOitTtYsOsinsFhtOz+FrUaNMXXSWLfrMGs+/xdNOFNOZrqwOiJk9HpdGzatCm/X8OGDePIkSOcunicci8F8+uWVfz68wYUoeAbVBQvH0/OxlwmIfEq+w/s5/8+eY13Jg7A3t7Ad999R48ePcjJycHd3Z0zZ85Qq1YtsrKyyMrKIjw8nMTERBYsWICPjw+TJk2ie/fufPbZZ4wePZqQkBDWrFlDq1at2LNnT35E4b8LRVG4YDrOruyfOW0+gFGkkZllZM7EHxjUZgy3028zZ9dHDJ88mJCQEMqUKYOXlxdZWVloNBq2bduGh4cHJ06c4OrVq7Rq1QoHBwcMhtyx8fDw4PDhwxw7dowsJYNL1hPoMaDlwS6ZiqIwsu9EJg//Alf3IrR8pSmN29bHUefM5TNX+OPMcbbv2sqcOXOIiopi6dKl+Pv7M3DgQKZNm0Z0dDSlSpViyJAhtGvXjpCQEAA8PDz+zmH9n8ImrMRbTqHDgFQAy+q+bQf5bMws6jWrzeKtc4moUSE3cu4d0Vq6fCkMegM7Dm4mNf02cCdfqtnMpk2bcHFxoW7duly6dAmAzp0706xZs2e6lv1JNs7cVvCyL9h5u3+axcWY3bw26Tt6fbqCkpH1cSjijn+pirw5ezl124ZzeNMBrl25zo9zVlDUz4sGLerw/ZdL8+sY9tEgGrWpD0DSlesc3h3D/M+/Z/UP6ynq50WvIV1Zt+w3utTrQ9lK4Xw5ayaTP/4PSUlJz3TNKioqKv+NaMaPH/+i+/BYvvnmm/H9+vV70d1QUVG5gxAKV6xxXLNdQHMnnYVW0mNMzWL90s1cjkukdoOamCQjiiJQTBKpt1Mxm82YTCYqVqxIVlYWO3bsoGfPnhw/fpwDBw4QWqsF69KCKF+7CcGBfug191obvIJK0bjXe4SUqYhHiQpsX7eSURM/5qvP/kNERES+y2DSzatsObCeFv3qYrC359f5v7Nw8goCQnyJqFOWb8YtZv+mo1SqXY7mPaNQ7Ewc2X6SQW8NYceOHfj5+SGEoGjRoty+fTvXrVhRMJlM+Xtf3dzc2LlzZ36uRCEEer2eRo0a5e/R/TuxWq2cMu3mqnIGjdBjJxsQFsEn//cV1+OTiT+biN6gJywiBLcSBoy3c5BMOurUqcPJkycxGAysW7eOmJgYPDw8OHr0KOvWrWPDhg3Url2bESNGUKlSJZycnEASnDMdBUlCJ9k91CokSRIh4cH0G9aDhq3qcTD6KNcTb1CuShmyM3I4dvAEgWW9Ke5dCq1Wy+bNm6lfvz7VqlUjLS2NuXPn8vbbb1OiRAlatmyJwfDggDoqhcdt2zVSlGsYpILlhN21ZT82m8Jbo/qg02mxWKz3RLnVaGRM2WZOHY9lT/Q+mjdtyY0bN/K3B7Rv356aNWtSq1atQrkOmyKYf8KCs1667z3yKIypN9n63ae0GvQfihYPRwiBVp+7f1dvcCDtynqWfDiNFv27E964Piu/mE/nPu3wC/Jl2rivaNX5JRydHbAz6KlYrRwAt2/e5tCuGN6dOICJQ6ZQs2E1atSP5PSxM7z25st07f8yviU8ObjrKMUDQ+7LH62ioqLyv8KECROSxo8f/81fj6sWVhUVlQKTZL3ATetV7Lk34EmxkEB6v9ONdcs2ERtzBjvJgWKl/KnSIoz0zDR+/vlnjMbcvYvdu3dn/fr1XL9+nSZNmlCzfhPmxWTjaifw9vZ6YLteQSUBOL51FV92KYs18zYlnPHCAAAgAElEQVRj5q/jlde6M3XqVACswoxjMRkHdz0aoaNm4yqM/GoA86OnMnL2AEIrFKff+K6cP3mZuJjz6CQ7UpJTKeLvQIP2NfH09GTHjh3o9Xp8fHw4fPgwRYsW5erVqzg4OFC6dGk++eQTli5dirOzM1arFbjfxfHvIG+/m6IoXLId54aIJ/lcGjfib2G12sjKyMZsMvPqkLZIskTHfs3Zve4wXh5eJCVfZcCgtxg1ahSdOnVCo9FQr149du7cyfLly5k2bRqRkZHMmDGDpUuX0rZt2/x2U23JmMh6aETWuyke+ufku2R4ca5duc7lc/HY2ekJCApg9/7dZIkM6tSpQ2xsLDk5OTg6OjJ48GCSk5NxdnYu/IFTeSBCCG7Y4tFR8IUBbz8vrl+9wdcfL2DcwMlMH/8Vn46eyYlDp5g+/mv+r+NQgkr40/ud7hyJOUy3bt2oX78+BoOB2bNnU6RIEbTawsu0d/a2QroJHHQFey4NTkXIyUhD1tzbF0VRkDU5pN88g2/JEoRVj8C7WCBXLl5l3bLNlCgdzLy1M/D29bxnH6oQgrAKpXLzGhf1YOCYvvyyeB1rl27EL8iXG4nJAFSrVZXTcbG4ezx57mQVFRWV/xXUPKwqKioFwiSyuWGLx15yfqBICwkrTscebVjwxQ+0eLkJcUcv0KZHU5yr+LFq5WrWr19Phw4daNKkCS1btuTs2bPUqVOHm54RKJdtOOkfP8F08fShxydLcfcL5tf5n+FeoSRGo5GPPvqIoDK+/LzoV7oMbov2zqTTy+9eF9KwiBDqt6vJwd+Psebb32jaOYqP+nzJFdNZunbryuxZszGbzSxZsoTExETKlCnDzJkz86P9wp95Qwtzkv2kJCUlMXv2bMqWLUuXLl2wYubI5T2smbOVbav2UDwskOCwQNr3fQmtTovNpuBbzJtr8Tc4ffQcN5Nu4+TsTHA5f/bt30e7du1wcnIiKSmJ33//nU6dOtGhQwc6dOiQ36aiKMiyfEfUXC5Q1Ni8sYqsE8GpY3Ec3n2Mzm+0p2rdCL76ZD62NIkTu89QrVo1XF1dAbC3t8fevoC+nCrPRI4wYhJZGHAq8Ll1mtTgyqVEtv26kyq1K2HKMXPrRgpfTppLQHE/xs8YQVF/b4QQfL1xCrp4T0KDw9A/p5Qmh68r2D3Fo2kx5VCsfHUuxuzGO7g0kiTl54vW65KxmqxIksTCUR+Tk51Doz6vUbFabu7U0uVDgXsXryRJ4kbSTWo0qIrB3o4KVcuwbMEqNqz4nfbdW/LHkVgA9mw9gFMRR/RFVDuCioqKyl9RBauKikqBuG29BkiP3N/Wd3gPPn7vCy6eucyRvceJPXCBiDqOvN7jdXbv3s2WLVto0qQJ06dPB8BsE0RfseHxhPokuELN/N8DQ0pz4mISX34xnX17opn+xQxe6lqPhu1qP7KO195ux40rN/n+05UUDfCkQu1w9u7ex4X4JNq2bcvRo0cZMWIEdnZ2tG7dOv+8POH2IiyqZrOZYcOGsXPnTqKioggLC8tNrbN7OVMmzcHT24Plf3zNzaQU3u88mai2NZCACycvUzTAixP7ThMY4oeLmzMDP+rBmdPnWPHxZi5dusSrr75Kamoq9erVuyeacZ7YzHPttJBDjjAWSNTkjZVfkA8hpYO5dC6eC2cu06h1FM6uzuzZvpfGjRvz1ltvFep4qRQMk8gCns5bQK/X8fqAzrw+oDMWixWdTsuVS4l8/sEseg1+jaL+3vnPDgL8Q3zRa55f/s3zqQpOT1G9wdEZj4AQEs8ex5h6E0dXz/zxuHR0CyER5fAKKsn+tZtp2b87RUqE4OP/6Ojf7l6uxOw7Qb92b5ORlkm7ri3IzsrhQtwlXIo4cyHuEjXqR9KhXzOcNQVzxVZRUVH5X0AVrCoqKk+MEIJkWwL6x7gM6nRaOvVsy44Nu0i+dpNDO49RoU4YLTo1YV+FfZQvX/6e8udTFbKt4GFf8ImyOSMFRWOHc7Fy9KgQTKWe/liFmcfNuf2L+9C8a0Nmj17E50PnYrPasHfSk/BHMm9078/48ePx8fHJL5832X6ROVTj4uK4desWR44cuacfnpXs8Q3yRrGCMSMbT193ajStzP4tR+nxXid+nruR7Kwcrl64RuLlG7Tu1YRje06xaMoKZFliysTPiYyMfGCbfxUvWdZMECAVMJdlvpW1bgTHD51i37aDlChVjGp1K1O+TinC9dULPiAqhUqWko4kZHiGtRhFUdDpcqcWm3/ZhiRJBBT3z7dSAkhCIktJx1XzYNf/ZyXLIkjJEfgX3FAMQIVGHdg87yPWfDGcloMmI0kSWxZMxngrhl6TR+BToiilqlYEIMMMGSYbjrqHT6e0Wi1lK4eRcOEqy3ctBMBisfL7mu0EhQRSplJpAMwih0yR+nSdVlFRUfkvRvU9UVFReWIUrNiwopEev9YVXrEUHXu2wWqxYrC3w2q1gVa5T6wCZFoKNkfOTLnB1kVTmd6jNldij1C6YWcyzQKrYsaGFYnH5zuVJIlGHWvTbVgH/Ev4kJyYwpWz16jdtBqrV6/Od3/N24/2IoVqHmazmfXr1yPLMidOnGD79u2cPXsWobdRs1kkdvZ6rp7PjTLaoF0tfl+xixJli/Hu533p9GZL/rPkfQJK+PDF0LnMHvMdVaLKM//AJ1SpUiW/jcflgbTJFoQkiD9/pUB9zxO+xUOLUb95beo1rXnP3y2YClSfSuFjFqYC51y9GyEEF+IuMWPiN7Sv3o2D0UfpMehV4K9ushos4vl93zk2kKWn31fu4ulD87cmIoTg1xnv8/VbzbBzcOL/ZrxHES/v/HKKoiAA2xNMpXz8vandpAYANpsNnU7LSx0b54tVAA0aLCLnqfqsoqKi8t+MamFVUVF5YgRPntReURS8fDzZHLsKD293skXGQ89XBAWoGfT2jugNDnQc+SUBYRFcyRDYBCAVpJbcCXb7N16iXZ9mpKdkYO+mx0sbQFlDnQLVU9jku07ehRCCKlWq0KhRI8LCwtDpdJQoUYJz587hVdqZSd+9R/SaAyyauoLeIzuz8pv1RLWtic1mQ6PR0KBdrkCs0TSC+HNX8S/uiyxLWKQcFEXJdwP+6yT/r7kh90bvZ+qnU8lKzaZK7UpUj4qkVqNqD+zzw2jUOuqez2rmyX8KBXt+/ookSRT188bb15OP5nxwjxi7p1whtPUoHrPm8kQ4uLjx2sSFpCUn4uTmjUYr41hkF2aTQL7jXVCQRSxHZwccHB0QQtzjcn8vEo8al7xnWUVFReV/DVWwqqioPDEyWkBCCOWxORrzJnMe3u75xzQPeeXYawsmWvT2jtTpPCD/swQYtKCRtMjI2LDBE1pZ83Bxd8FoSkerffJgQs+Du10n7z6WJxy/+eYbzpw5g5eXF+np6YSGhlIsJJATB2Jp0KEWP8/ZwKp5G3FycaTLwNYP3I9aLDQAALPFhKzRPnASnDc5/quA3bllF32GvUZE5QgGdR7BqZg4ajWq9kwWaAFoHpLLVeXvQyPpCrQo9SCcizjRpW+HR5ZRUJ7IS+Np0WsKR7QCFPHyA0CxWVEUiQfd5k+SNadL346PtfgqKOgfEMws77nNe06NRiOOjo6Pb1RFRUXlv4QX7+OmoqLyr0GWZNw0RTGTXaDzFKEgIeEkuz7w78EuMpKUmzuxoFgVgSxD8SIy9pIzdpIjilAKVIckSShYsbOzx0PjV+A+PCs2m+2evpw8eZJx48bx/fffk52dfU/QI3d3d2rUqEFISAgRERE4OTnRoHldbJKVMlVC8fBxo0pUed6a9Dou7s73uPj+dcKsaK14aQPzP99dNm9y/M0337Bo0SJu375NUlISO7fuYt/Ww7za4A28/bwYO+29Z7p2IQQSAjtJjQj8onGQnFGwPb7gMyJQcJCLPLf6nXS5i2BmW+FZcWWNFqvVBVm23HNc4slS5zyJe7JNWHCUcsfl7u0IeefOmDGDKlWqMG/evAL2XkVFReXfjSpYVVRUCoSnxh8F5bF7He/GTBZuGl+00oPDdrrYSVQuquFWwXQwADezoLqPBkedhEbS4qMpAZJSYNFqEzYcZCdctd6PL1xIKEpuH/PEoRCCbdu20aVLF/R6PT/++COTJk3i4sWL+X+HXAtLbGwsGzdupEWLFqRfyyYw1BdXLxd8i3lzbPcpkpNSgIdPlPPaDtSVzv/97rKnTp0iMjKSY8eOkZ2dTdeuXXFxccFOZ+CPg6dZsnMuH84eRWAJf07FxD31GFgw4Si7Ikuqq+OLxiA78Xc5aBuk5xcNV5IkgovIGC2PL1sQzKYiSLI1/7O48+NYSM4BimTDUS6CoihIkoQkSfmLWbNmzeLgwYN8++23DBkypHAaVFFRUfmXoApWFRWVAuEgueAku2HC+ETlbSJ31uilCXhkuTr+Gkw2gaUAVlaLTWARUOuutBKeWj8MkhNWYX5it0AbVpAERTXF0Up/n2tqntX02LFjtGrViuPHj7Ns2TLeeustRo8ezZQpUzAYDKxcuRL4U1DqdDqmTZvG5MmTeeONN/ht42aKeZTELGXTpndTOg9qg5ev+0PbFQLMUjap50xMGf8FJ06cACA9PZ0FCxYghODQoUNMmTKFjz/+mF27dpGYmMjNmzfp0aMHxpQcbqUmcy72AiP6jOfXnzaRnfV0wWJsWPDSBD3VuSqFi73kiAYNNmF9fOGnxCasaNBhkJ6vS2sl78IXrCaTB5KUJ1PJj2yuKYQUV4pQkJFzF29kmcTERN5//31GjhwJwJYtW6hVqxYJCQns2LGD9evXP3ObKioqKv8WVMGqoqJSICRJIlhXFjvJgRyR+UhLq0WYMZNDsLYc9vKjc0wEF5FpUULL1YxcN9/HYVEEVzOhTYiWAOc/X2UG2ZHiugpoZT0WkfP4qLfCik1Y8NT446cLeWy7z8Ldrr95vPvuuwwZMoSePXtSsWJFgoODOXv2LAClSpXC3d0do9GIyZQbVVUIgV6v5z//+Q87duygQ4fc/YJh2ho4SM44FdVTNPDh6UIURZCtZGKQnKjh14wzZ85w6tQpAFasWMGxY8eQJIlTp07RqVMn2rRpQ6VKlTh69CjFihWjd+/eNGrQmKlDZ/P+GxMoFhLI2+PfxN7h0amOHoRZ5GCQHHCW3Qp8rkrhI0savDSBmHl+kWrNZOOlCXjuFvVynhp0cu6iVmFhsThhsTghy2YArAoEuzybWM17J+R6ofigk/RER0fTrl07nJ2d6dOnDwD9+vVj//79bN68mZ9//pkuXbqwc+fOZ7sgFRUVlX8JatAlFRWVAqOV9JTUVybBcpo0JRlJSOiwQ0KDQGDFjIIVHXaU1Efg9ISCpEmwFpuAjRdtOOoEbgaQ/7rvUghSciDLAm1CNDQMun/i660NQsHGRctxTEo2kpDRSrr8lB1C5FpVFWEDCTw1gZSyi3zu1tU819/Vq1cTHBxMpUqVKFu2LAsWLKBTp04AhIeHc+7cOWJiYqhUqRJpaWkIIbCzs7snYq+HhwfwZ3Akg86BypqmHDftIE25iSwkdMKQb8VVFIUcJQtZI+Gq8aS8XRR2DvbUq1ePAwcOULZsWfbs2cPLL78MQNu2bdm0aROrVq3C1TV37/GSJUuoWrUqUz6eyrlrJ8lwTcIe58cG4HoQNmHDhoUQXcVCFy93u1SqFAx3rQ/XbZdQhK3QvxebsCEh4a71LdR6H4SDTqJOgIYdCTb8njIf6/1IZGYUw939D7ItegxaCXdDwe+xu59jjUaDImwkXLyKh0cJ8IZLly5RvHhxRo8ezYULF0hISKB58+Y0b948v47s7GwSEhIK68JUVFRU/tFIBdmH9qKIjIwUhw4detHdUFFReQAmJYsUWxK3lRvYhAUJGQfZBS9NAE6ya4HFjBCCs7cFW+OtnE65s8fzTroam8id5JXxkGkQpCXU7dF1p1mTuWo7R5rtBjkiKz9jhECgk/Q4yM74akvgrQ0udLF69epVAPz9/fOPrVq1irFjx1K7dm3S0tLo1KkTjRo1olmzZowdO5aWLVty69YtZs6cydatW6lcuTI7d+5k0qRJtGjR4onaFUKQartBgiWOW8pVxJ39xrKkwUP2JUAXxsHfj5GYmMirr75KZmYm7777Lr6+viQnJ7NgwQIgV/T17t2bjIwM6tWrx/Lly3Fzc2PmzJkEBwcjhCDReo4b1ngMklOB8nfahBUTWQRqw/HUPr8gVzk5ORgMBbf8/q9zwxrPVctZ7CXnQhP9QgiyRQYBulL3BPp6nmRZBB/vNyFJ4KwvrMULgbNLHEJ3g4oeRQosWBfNXIKTixNtuzZHq9Wyd9tBZn08F4PsQFhIGcaPH4+TkxM1atSgfPnyODk5sX//fjp37szYsWOZOnUqGzduRKvVMnPmTEqVKlVI16WioqLy4pEk6bAQIvK+46pgVVFR+aeSnKUQl6KQZsp9TxWxkwj30OBh/+STRCEEOSKTFOs1skUmCgo6yQ5X2RMXjRea5+SauHnzZlatWsX06dNZs2YNHTt25MMPP6Rjx46Eh4dTpkwZ6tSpw2effcbixYtZt24dv/76a/7527Zt49ixY3Tt2hUvr4e7+D4Ki9WM7U6QGB16LGYrXbp0IT09nbCwMOLi4pg3bx4HDhzg448/xmq1UrduXapVq0bPnj0xGo3s3LmTtWvX0rFjRxo1anRP/UIIrlsvkmS7hBZdrpX9EQJHCIGZLASCIG04blqfp7qux3Hw4EFmzJiBLMt06tSJ1q1bP5d2/ltRhMI581GyRUah7TU1CSP2kgsl9ZWeyiL/tMSl2Jh11Iyvo4TuUflnhMDhdjJON65SJPESLkmX0VgtCEkmp4g7KYElyfT2I71oIFdMEBV2ghJuFuyeIHjUkb3HOXk0lvbdW7Fz4x7WL/+ND78ajd5Oz+cTZtK6fUtert+DCuUr0KRJEz766CMADIZcD4ktW7YwZ84cli9fzujRo2nQoAGNGzcurCFSUVFR+cegClYVFRWV50iea24eR44coWHDhnh6ejJ8+HCaN2/O2LFjOXr0KE5OTrzyyiv50T5v3bpFvXr1mDlzJg0bNryvbkVRninP6cKFC7l27RpRUVEsXLiQOXPmADB27Nj8QE89e/akadOm+Pr6snjxYi5cuMC0adOIjLzv/437MCppJFhOkyOMd9yv9WjQIkm5OXutWLFhRgiBk8aNQG1p7ORnjxL71zGHXMv2gAED6Nu3L66urgwePJgxY8bQvn37Z27vfwmLMHHOfPTOPuNnE605woheMlBSH4HuAXlGnzfb462sPGPF1wn0fxGtstWC5/mTFN+zCdeEcwhJAknGYnBAyDKSEGgsZjSmHIQkkaqxx9igKfW6VCPe9QomkY0Bxwcu1Jw4fIop788gJzuHpu0aEBDsR/NOTejbZggderQmqkM1DFZnTm66zEeT/kNAQABOTk50796d5s2bc/78eZYuXcpPP/3EmDFj6Ny58981ZCoqKiovhIcJVnUPq4qKisozkLcfLU84xcfHExQURGpqKrVq1cLFxYX+/ftjMpmws7OjWbNmTJkyBcgVotHR0URFRTF48OCH1v8kYjUvNc3dZX/55Re2b99OdnY2kydPZseOHfkRgRVFYfz48QQHB5OVlUV4eDgnT56kbdu2NGvWjFu3buXvk30cjnIRSuurYRRppNquk6mkkiMyQYCEhEFywl32wU1TFIP04Mn905A35tu2baN8+fJ4enrm/w4wfPhwSpcuTaVKlQqlvf8ldFLu/vOL5uNkiQzscCjwnlZF2DBhxEFyobi+wgsRqwBRgRpkCVaeteKsE7jeceMtcvUC5VctwOnWNcwOzmQUDYSH3JtWBYwWgZ/WTO2YX9GcWE+p9q250jCYFCkZnTCgRX/Pvb1y4Rpad3mJV/q0A8BstiCEoG6L6mxZt42Xmr6En10JRi/+mCVLlhAWFkaDBg3YsGEDERER/Pzzz1y8eJGff/6Z0NDQ5z9QKioqKv9QVMGqoqKi8gzkTVCPHDnCiBEjSElJoVSpUixZsoQqVapQr149/vjjD8qVK0dUVBSbNm1i4sSJhIaGMm3aNCpUqECNGjXo37//I+t/HHlC9fr16yQkJBAZGYmzszPr16/nnXfewc3NjXbt2tGvXz8OHTpEZGQk2dnZREVFYbPZaN26NadPn8bZ2RngicXq3f10klxxknMDNAkhEChIyIUmUP9qaV6/fj1jxowhMDCQ8uXLU6FCBcLCwujVqxe9evVizpw5+eI1JSUFd/eHp/pRuZ9c0VqZG9Z4rtkuIgkZPfaP3a+sCAUz2QgUfDQl8NYGvdA8u5IkUS9QS5CLzOJTFq7ctlLz0FrK7v4Vs6ML6b7FHnquTeQGeJMkKOupIdDZAUlyBLMZzbKfCTpYHNd+r5DokU6OyEBScj0Mki4lc/VyEv2G90QIhRxrNugENpFD59c7sXvNES4fvkFIw3LEx8dz+vRpfH19MRgMWK1WsrKyGDZs2DN5VqioqKj8t6C+CVVUVFSeECHEfalpsrOz+fzzz/nggw/o168fhw8f5tSpU8yfP58iRYrQsGFDZs+eDUD79u157733MJvNrFq1ik8++YS5c+diZ2eXX/+T8td+pKen07t3b1q1asWPP/7I8OHDadCgAdWrV0eSJHJyclOVDB8+nHHjxjFr1iy6deuG1WrF3d2dSpUq0aVLF7TawlnHlCQJWdI8s1iNjo5m8+bN2Gw2ZFnGZDIRFxcHwP79+1m/fj0LFixg3759rFixAhcXF1q2bEnTpk0pX748ycnJjBgxggMHDhTGZf3PIUsafHTFKa2vhrvGFzNZZCsZ5IgMLMKEVViwCgv/z959h0V1rHEc/57dZelFFAQRVLBgQ0A0FlQswa5YYkmMGjXGQmwxGmuMmmuJMZbYWyKxRWOJPXYldsXeCyA2QEGKwLa5f6zs1RhLrMnNfJ7HR4WzZ+ecReS3M/O+epFDtkgny5SOjvvkVRfAX/sOHlZF3mpYfVhhZxX9y6vpEfMT/rt+5UaegiTZupJtNAdTkzD/rjNChl6QpjP3WvVxUgj1UuPj9NCbL1otFC6McusWzmNn4p/sTTFtCPk0BdEoVtxOvklC/HXyeNuTw33stY7kVxeihHVFyrpUod679fn111/Jysriiy++YMyYMdSoUYP33nuPqVOn4ufnJ8OqJEnSA3IPqyRJ0jPcvn2b/PnzW5b/CiGIioqiQoUKlCxZkpUrVzJ27FjGjh1LrVq1WLFiBdOmTWPz5s3ExsZSt25dmjVrRnJyMt9//z2Ojo9WX33ePar37t3jwoULVKhQ4bHP7d27l+PHj9O9e3fmzZvH8OHDWbduHXFxcURFRTFlyhS8vLwwmUwcPHiQqKgoAgMD+fjjj1/pvXpVcu/15MmT2blzJ/PnzydPnjx88MEHvPvuu3To0IEKFSqQP39+7ty5Q506dRg8eDB2dnb89ttvDB8+HB8fHy5evEhYWBgjR460zB5LL84g9Nw33eO+KZ0McQ+jMPckVStaHBRn7FSO2KmcX3uLqBciBERFwdatmAoVIkWnIjXHxJ0sSNcJTMI8k2qrAVcbhTw2Cnlt/rxYU6ZOh41Gg1qlguRkUKth+HB4sDJBCBPFi5fgmwnjadokAoPBYNk6EBcXh6urKzVr1mT8+PHUrl2b8+fPU6JEiTd9RyRJkv5W5B5WSZKkvygtLY3Q0FA8PT3ZsGEDarWaLVu2MHjwYAoUKMCGDRtwc3Pjm2++Yffu3Vy9ehWAli1bMnXqVJYvX84HH3zAuHHjOHXqFL1798bJycly/tyg+qyweu7cOXbv3s3du3fZtWsXGzduZNOmTWzZsoUOHToQEBDAli1b+O2331i3bh1Go5EFCxYQFBREUFAQc+bMYdu2bbRr1w6VSkWlSpWoVKnSa713Lyp3JjU30Hfr1o0NGzawd+9ePD09URSF5s2bYzKZqFq1KvHx8ezfv9/y+OjoaMLDwwkNDWX37t1Ur14dO7uXL/AkmWkUK5zU+XBS53vbQ/nrYmJg61YoXBiVSkVeW8hrq8bP5flPcSM9netpaQzato3vGzTAP18+yJcPbtyAefMw9u2LolajUqmIjIxk5FejiGjaDCur/wX4H3/8kS+//JKPP/6YfPnM91GGVUmSpCeT600kSfpXMglBgimbDbokFuRcZ252AlE5NzigTyVNmFvBODk5kSdPHm7fvs3q1asBOHHiBC1btmTNmjVMmTKFtWvXcuPGDYKDgzl37hynTp0CoEWLFixbtgyAVq1aMXLkSAoVKvTIst/coKo3Ck4lG1l0Rs/MYzrmndCx8aqe3QeP06hRI9q0acO1a9dwdHTEwcGB999/nx9++IH79+/z+eefc/LkSd59913i4+MZPHgwmzZtIjw8nNOnT6PT6WjevDnx8fGWwkx/Z2q1eRnxuXPnuHbtGtbW1oSHh7Njxw62bdtGaGgoTk5O6HQ6GjRowM2bNy0hPiwsjNWrV5OWloadnR316tWTYVUyu3cP5s8Hd3d4gaW20fHxvLd8OQ0XL8Zeq8XJ2pqdsbEYcv9NeXrCyZOo9+5FpVKxa9cuevfujbOzM+3bt2f9+vVMmzaNoKAg0tPTycnJoVu3bpQrV+4VX6gkSdL/HznDKknSv06cMYvthrvcEwasULBDjRUKm2bMZ+C8RTT7ZjgNa9ehRGI2QUFBuLq68vPPP9OiRQtiYmKIiDBX/XR3d6d+/fpMnz6dYcOGsWfPHnbt2kWZMmXo1asXPXr0eOR5/7j01yQEu64Z2RpnIEMvsFErWKnNKxdP34EdU2dTqMg7bFr2Kx72Ku7du4dWq2X06NHExcUB0K9fP7Zs2ULjxo2pWbMm69evx8fHh7lz57J9+3YmTpxI586d39zN/Ytyl/7munr1Kp988gkpKSmUKFGCqlWr8umnn1KnTh1u3rxJ0aJFKVGiBLz0RmQAACAASURBVBUrVqRu3bqkpKSwYsUKjh8/To8ePWjTps1bvBrpb2vzZrh/3zwb+hdtv3qV4Tt20CU4mOYlS+JkbU2noCBmHj5Mw2LF8HZ2Nq8l9vJi33ffMeyrrzCYTKxZs4aoqCh+//13Vq1aRWpqKvPmzSM4OPg1XKAkSdL/LznDKknSv8p5Qyar9IkYhMBd0ZJHscJaUWGlqHBxycOt0+c5On8Ze44f5fd8ak6fO0uJEiVwdHTkwIEDhIaGsmbNGnQ68969+vXrk56ejrOzM6GhoZaltiaTCY1G88is5sNh1WASLDpjYOUFPbYa8HZU4Wan4GJt3jsnrh/nzoWD+DbqyXeHdVy6q8fZ2Zlq1arh7u7Oli1bAKhduzaXLl0iPT2dr7/+GqPRSLt27bh79y4//PDDn+53/TvJDasbNmzg2LFj7NmzhypVqnDo0CG6devGokWLOHnyJJ06dSIgIICWLVuybNkyWrRoQf/+/WnTpg2TJk1i9+7dMqxKfy4rC7ZtAw+PF3r4xTt3KO3mRsfAQJysrTGaTDQqXhwrtZrtV69iMJkwCQE2NuRXqxnZujU7d+7E2dmZggUL0rp1a6ZNm8aKFStkWJUkSXoBsuiSJEn/GjdNOfysu4UzGrRPaM0xMLgmvuXL4Vncj7zlSiKSUimUnEVeV1cOHTrEtGnTaNy4MUFBQXh7ezNnzhxGjBhBkyZN/tJYVl3Qs/2aAR9H5U8r6abeTmDx0Pa0H78MYZ+P+zlGBlSyxZ5s5syZw5kzZ5g1axYGg4HevXvj6elJnz59cHBwICsrC1tb2xe6R6+TEMLSV9ZoNKJWq1myZAl37txhz549fP/993z44Yc0atSIyMhIAKZNm8bJkycZP348jRs3ZtKkSQQFBbF//34cHR0pXbr0W74q6W9v3z6YNQsKF36hh689f56ZR45QpWBBrqWlYW9lRUEnJ25nZpKYmcnImjUp+GBv+qW4OIp6ecGoURiMxldWdVuSJOnf4ElFl+QMqyRJ/xr7DKloUT0xrALU6tKOGxcuU6llU9YPG0dM9F48yvoTGhpKYmIip06dYsmSJXh7e3PgwAEmTJjwSFh9njcB72QJdiYYKejw52EVQK2xwqNYWS4e2oG9RmAwwZZYPXZ2dhQpUoTY2FgOHz6MRqOhbt26VKpUCQcHB4C/ZViFB61uVCrL7DTA/PnzWbhwIRMmTMDNzY127dqxdOlSy+fd3NywtbXFycmJgIAALl68CEClSpVkWJWez/HjYG//wg+vW7Qodf382BEbi6eDA1ZqNacSEzmbnMzFu3e5fPcuW69cITwqipYbN3Lk+HFIT5dhVZIk6RV5bTOsiqJ4AwsBD8AEzBZCTFYUxRVYBhQGYoFWQoiUp51LzrBKkvSyUkx6ftTdwA2rZ/YG7epZiq/3/8b1s+f5afAoWg7oxZQOPRk2bBjXr19n/vz5jz3mj3sxn2bDFT1b44wUcHjy8UIIdi2aRPK1SzTp+w05OTlsnP8tXcPLkZ6SxMmTJ/Hz82PIkCHP9Zxvwx/vSUpKCiNGjODQoUM0adKExo0bo1KpaNKkCUeOHMHBwQGVSkXp0qX59NNPqV27Nv3796du3br06NHDMisrSX9Jv35gZQWv4I0cvdGIlVrNlZQUvtu3D73JxOpz53C1taVnhQr0rFgR4uNh4ECQlX8lSZL+kifNsL7OwOoJeAohjiqK4ggcASKAjsBdIcRYRVG+APIIIQY+7VwysEqS9LIO6lPZZ7yHm6J95rFLhozm1sUr9P15PjcvXibNWk2/oiHcu3YTW1tb3NzcLGHseXuo5hJCMHhPDg5WYK15PLCaTCYUxTzzei/pBhumDeNOwhXUGg0qh3xo0xMIq1yBQYMGUbBgwb90D94EnU6H0Wh8bJbXZDIxadIktFotrVu35ssvvyQ+Pp5169ZRs2ZN3n//fUtP2B07drB9+3bWr19P69at6dOnD9bW1m/jcqR/usxMiIwEHx9zYaSXYBIC1YNzTNi7l1OJicxp3JhDN25Qxdv7fwfGxkKHDlCz5ks9nyRJ0r/NG18SLIS4KYQ4+uDP6cBZwAtoCvz44LAfMYdYSZKk1yoVc0Xg59FiWH+Ort/CrctX8SzmR17vAtwXJnx8fB4Jq8BfCqsAOUbIMjwaVk1Go/n3B+FXURRuXzmLWmNFxGffYu/sSvypQ2Sn3aFdv1FMnTr1bxdWjUYjN27c4PPPP2ft2rUAHD16lB07dgDm5cDbtm3DysqKPn36cPLkSbp27QpA3759mTNnjmU5dc2aNenfvz/jx49n4MCBzwyrQoh/RMse6S3Izja3sXnJsCqE4FxyMl/u2EHQrFnsiY+ne0gIVmr1o2EVQK2GjIyXej5JkiTpf97IBgtFUQoDQcABIL8Q4iaYQ62iKO5PeExXoCuAj4/PmximJEn/x0wClOcMrFobG+p92oVbl67i4VcEgIfXojzv0t8nj+PBn00mTu/6ldjj+2jcZxyKonD9wnG2zv0PGSmJuBYoQukajWkx6Hs2Th9OHv/KlKtS66We/6961lLns2fP8v333+Pt7U3Lli3x8/Pj999/Z9u2bRw6dAiVSkX79u3p1asXBQoUYOLEicyaNYuwsDAAYmNjadKkiaU9T506dVAUBUdHR6ZMmUJmZqalz+0777zzxPEpikJiYiJ6vR4vL6/XdTukfxohzL9ekqIoeDk6UsDRkflNmhDk6fm0g0G+gSJJkvTKvPaiS4qiOAC/AH2EEGnP+zghxGwhRIgQIsTNze31DVCSpH8FJ0WDgef/IfKDsV8SWLeWubItYP2Kvl3aaECtghyDEZVKhWPe/CTGnuPu9asoisLVmGgCw1vRc84OTEY9O6MmIkwmCgdU5vaF46iy76EoynMVd3oZxgezvk8Kqzqdjh49etCiRQu8vLwIDg7G1taWgIAAUlJS0Ol0HD16lIkTJ7JlyxaOHDlC7dq1KV26tCV4jh8/nsmTJwMQHR1NeHi4ZYb52rVrALRt25bU1FT8/f0fG1tuWE1KSmLOnDm0bduWkydPvrZ7Iv0DvcKl5M42NnwSEvL0sApgMICd3St7XkmSpH+71xpYFUWxwhxWFwkhVj748O0H+1tz97kmvs4xSJIkAfiqbTHyfFV8c5lMJrIw4aJocFVezYIUlaLwjqeau9nmb78ZKcnYOuXh5M41mEwmblw4wdnoDUxuXwWN1oa2I+bj7O5FAf8gBIJL0ebltq9jlvXcuXMYDAYAS3Gj2bNn8+OPP5KSkvLYsTqdjkOHDjF48GDCw8Px8vKiQoUKFClShOTkZACqV69O3rx5OXz4MI0bN8bX15cPP/yQ0qVLc/ToUdq3bw+Ax4MemefPn2fQoEFEREQQHh5O0aJF6dq1K87Ozo+NTVEUUlNT6d69OytXriQqKop69eq98vsi/YM5OJjD40OVqV87lQqeFWolSZKk5/baAqti/mlqHnBWCDHxoU/9CnR48OcOwJrXNQZJ+rcxmUyWvXz/hB7Lb1J+RUs+xYr7f2GWVaVSkYGRCmrnl1sG/IfXpXIBNTfOxzC2eSnO7d1EVnoqF/ZvxWTQo7bScj8thc6TVtN6+BzcChXj2pkj2PgEUtq/BK4Or6f40JEjRxg9ejTr1q0DYPPmzQQGBhITE0NSUhKfffYZd+/etRy/e/dukpKSsLe3R6fTWXqs2tvbU716dby9vdm+fTsA7733Hhs3buT69etMmDCB6dOns3btWpYuXUpQUJDlnGfOnKF9+/bk5OQQExNDZGQkDRs2ZOBAc12+3DYhmzZtolWrVqxevRqtVkurVq0wGo2W8cmvfclCUaBoUUhPf7PPKwOrJEnSK/M6Z1irAh8CtRRFOfbgVwNgLPCuoigXgXcf/F2SpFdApVKhUqm4d+/eG93n+E+gKAqV1c6kY8D4nIEmXRhwQI2f+sWW9xmNRoQQltclKyvLvBfOQeH+iU2UjehJy0HTeLfLEJzdvTi+dQUVGrfHqNdx8eB2EmPP8/Oorvw6+QvS0tL4z6BevP/++y80lifJDdLly5cnMDCQAwcOAJAvXz42bNhA3bp1iYqKYt++fSxYsMDyOGdnZ4oWLUp6ejpardayjxSgbNmyFCpUyFJwqWHDhjg4OJCamgqAu7s7vr6+ACxcuJB58+Zx6dIlSpUqhb+/P3FxcYB52XGHDh3Yu3cver0egGHDhjFr1iw+/vhjoqOj+fjjj2nUqBFubm6Wx8mvfekRZcuaqwW/CZmZ4OwMrq5v5vkkSZL+BV5nleBoIYQihAgQQgQ++LVBCHFHCFFbCFHswe93n302SZL+SAjx2DLNixcv0qVLF2rXrs20adM4cuTIWxrd35Ov2o4qaheS0KEXT59pTRMGjAiaat2xVp7/W6Ver7cEO7VabdmP2bVrV8LDw1m2bBmKouBre5/s62e4ni5wK+yPX0gNTu38lYIly1P9g95cPbGPX8b0xMHDl/pfr6FzBVeKuLz6OnkqlYoLFy7Qu3dvTp8+zcmTJ4mJiSEwMJALFy7wxRdfcOPGDUaMGMHmzZvJeFD91MHBgezsbMue0ZycHABSU1NJSUmhWLFinD9/niNHjiCEYMGCBVSsWNHyvMnJybz//vssWbKE2NhYGjduzJkzZ+jUqRM6nY64uDi0Wi3+/v4UKVIELy8vAgMDOX36NDNnzuT06dNs374dT09P7OzsKFWqFAcPHiQhIeGV3yPpHy7kQYeEB3ufX6vkZKhf/6WrEkuSJEn/89qLLkmS9OoJIYiOjmbnzp0A3Llzh8uXLzNz5kxq1KjB6tWrOXz4MDNnzny7A/2bURSFdzTO1NS4cg8DiUJHtvjfD7EmIUgVehJFDraKitZaT9xUz+7bCnDz5k2GDx9OQkICiYmJmEwmDAYDs2fPpl27doSGhtKnTx/mz5/Ptm3beK9FM5yzb1LU6g53TA4kpmRw88pZ9q9eQOGQOlTpOoZGE7ZQtf1AIis4EeLx8mHV+Cc/sCcnJ9O/f38KFy5M8+bNycjIYM2aNajVarZs2ULXrl0pV64cmzdv5uLFi8yZMwcwt56xsbFhzZo13L1719J6ZuHChRw+fJiqVasyYMAAgoODURQFKysrsrOzuXfvHgBJSUncunWLjRs3MmrUKJo2bcqvv/6Kq6srpUuXZtGiRVy4cIHg4GD8/f3p3bs3K1eu5MyZM1SsWJHU1FRWrVrFhAkTAPOy40OHDnH69OmXvk/S/xlnZ6hcGW7ffr3PYzCY96/+STVrSZIk6cXJwCpJ/yAPV241Go3MmDGDoKAgPv/8c2xtbRk2bBi+vr60b9+emzdvcvnyZTZt2vSWR/33oigKQRonulgXpKbGFVBIFDqShI5k9BRU2dBcm5922gLkVVk91zmzs7Pp2bMnSUlJFClShC5dujBq1Cg0Gg2ZmZmcO3eO9u3b06JFCypXrszBgwfx9PSksI83u6b2pWTcCsSVvVRq/glOhUqjM0FRNzu6lbPiyyrWlMqnfiXXnlus6OjRo5YqvImJiZw5c4ZevXrRuHFj+vfvT0JCAgcOHGDRokVMnjyZxMRE1q5dS2RkJBUqVMBkMuHi4kLHjh25desW7dq1Y8KECVSuXJk1a9ZQpEgR8ufPT0hICIqikJaWxpdffkm5cuXo1KkThw8f5s6dO/j7+xMTEwNAREQEO3fuRKvVotVq+fXXX8mXLx82Njakp6czZMgQfH19+eCDDyhVqhQjRoygUKFCHDlyhDFjxlC8eHH69etHjRo1Xsm9kv7PNGpknmF9sBLgtUhIgIYNzQFZkiRJemWUf0JxipCQEHH48OG3PQxJemv+rBfmoUOHaNGiBdWrVycqKgpFUbh//z79+vUjPDyc5s2b06VLF4QQzJs37y2N/O9PCIEBgQnQoKB+zqV8D78mGRkZjBw5EpVKhUajYdiwYdja2hIfH4+dnR3t27enc+fONGvWjN27d7N48WI++OADQkJCWLp0KevXr6dbt27UqVPnNV4prFixgqlTp2JnZ4dWq2XkyJEUKFCAfv360alTJ2rWrMm5c+fo0aMHvr6+uLi44O/vz8KFC0lLS6NXr1506tQJg8FgKYCUlZXF/v372bhxI7Vq1XqsSu+2bduYN28eTk5OzJw5k7Fjx3Lp0iUCAwOZMWMGTZo0YcyYMQgh8PLywtbWFj8/P1QqFePGjePGjRuMGjWKvXv3IoQgJyeHqlWrUq1aNa5cucKVK1fo378/HTt2fK33Tvo/sGULREVBkSKvfsnunTvg6AgjRoD2+VZlSJIkSY9SFOWIECLkjx+XM6yS9Df1cGXZ3GA0Y8YMwsLCmDJlCm5ubvz8888ULFiQ33//HYC4uDj27t1LvXr1yMjIICcnh2PHjnHhwoW3dh1/d4qiYKWosFZUzxVWL168aHlcrps3b7Jq1Sp++eUX/Pz8sLa2pkOHDgwfPhxXV1fq1q3LypXmzl7Vq1dHpVKxc+dOjEYjH330EStWrHitYTW3Wu+lS5eYMGECGzduJCEhgW+//ZabN29Svnx5Bg4cSPPmzbl+/TparZadO3eSmZlJly5d2LlzJ4MGDSIqKgr4X7VeABsbG8LCwhg/frwlrEZHR9OxY0f27NmDt7c39+7dQ/vgh/hevXrh5OSEh4cH3t7erFmzhj59+lCtWjVsbW05d+4cGzdupGnTpowaNYr69euTlZXF5s2bURQFGxsbNm7cSIMGDWjTpg2nTp2SYVV6PrVqmQswJSTAq3yzPiMD7t+Hrl1lWJUkSXoNZGCVpL+ZQ4cOAf+r+JsbWidMmMD69esZPXo08fHxdO/enbJly2I0Gi2PKVmyJIGBgZY+l9WqVWPz5s0UL178rV3P/5OjR49Sq1YtwFxcaerUqZw4cQI3Nze++eYbmjVrho+PDwCjR49mxYoVZGRk0LhxY+7evcv69esB6NGjB927d8fBweG1j/nQoUMsWLCA+Ph4+vfvz4ULFwgICKBSpUrEx8ezdOlSdu/ebVka3KxZM0qWLMmcOXPYtWsXYP5aVKvVXLx4kVWrVgHmGWaj0fhIdWAhBP/5z3/4/PPPCQ0NJTg4mOLFi1OzZk2cnZ0tM85OTk5s3LiRQYMG4efnR05ODh999BE5OTlkZWWhVquJiIjA2tqac+fO0a1bN0aOHGm5Jnd3d8LDwy0Vk/9sb64kPUathp49zTOs1669mtCalgZ370LfvlC48MufT5IkSXrMqy85KUnSCztx4gR9+/Zl0qRJhISE8NNPP7Fv3z7Gjx9PXFwc3bt3JzQ0lNDQUPz9/Tl//jw1atTgt99+Y+bMmdjY2DBs2DDS09MpWLAg7u7ub/uS/vHOnTtHoUKFsLW1JTg4mNDQUDp37sz9+/e5c+cOW7ZsoXPnzkRERHDy5En27NlD2bJl8fLyonbt2gwdOpRJkyYRFhZGdnY2AGXKlHll4zOZTI+ERp1Ox4YNG1Cr1TRu3BgbGxvi4uLw9vZGURTWrl3L+PHjCQ8Pp1WrVvzyyy/cvn2bhIQEjh07xo4dO8jMzKRChQr4+PgwePBg2rRpw7Fjx2jYsKGlNY2iKJY9sStWrLCEzI0bNxIVFUW+fPnIzs5GURTq1avHuHHjmDVrFv7+/qxbt446depQo0YN1qxZg5eXF/Xq1SMmJoaFCxcSGRmJo6MjOTk5qFQqunTpwu+//05GRsYjIT93WXbuOCTpmezs4LPPYNYsOHrU3C/V1vavn8dkghs3wMYGBg6EEiVe/VglSZIkQM6wStJbl9urE8DHx8fS+gRg586dfPzxx9jb23PlyhVLL0qApk2bMmvWLBo1akTlypWZPXs2ycnJ+Pn5ERwcLMPqK7Ju3TrGjRtHZmYmK1eupG/fvqxevZrIyEh+++036taty65du7h+/Tp16tQhJSWF3D33w4cPt8yqfv7557Ro0eKVj0+lUqEoCvHx8SQlJSGE4O7duwwYMIDr169TtmxZVCoV27dv59SpUxw6dIjIyEg++eQTVCoVZcuWJU+ePJw4cYLQ0FCqVatGVlYWMTExzJ07Fzs7Ozp27Ei+fPmYNm0aH330keW5d+zYwTvvvENUVBTOzs4oikLFihVp06YNffr0oUuXLgQFBVG8eHHS09P56aefGDJkCGlpaRw7doxff/2VDz/8kFOnThEXF0eLFi0YO3YsBw4cYPLkyWRkZODi4oJarWbhwoWPzUjLfqvSC7G1hV694JNPIDUV4uPhwZtJz2QyQWIixMWZ2+X85z8yrEqSJL1mMrBK0luSG1Jze3UCuLi4ULt2bS5cuEB0dDQqlYoiRYoA5oA6Z84cyx5Ke3t7qlWrBkDbtm05evQo/fv3R6WS/6yf5lmF5v64vLRMmTKMHDmSGjVqkJKSQmBgIF5eXpbqtqGhoZZAWLFiRbRaLXv37iU9PZ2goCDL6/Us2cLILVMO8aYsrpuyuWPS/+lYc5eI5zp69CitW7emWbNmREZGcvDgQTp16kSTJk0YP348mzdvJigoiMzMTAYNGkSrVq3w8fEhKioKW1tbVqxYQefOnZk0aRIAISEh5M2blxUrVuDi4sKQIUM4fPgwvXr35o7KyOWcdC7q0kkwZbNr316aNGnCmjVrLEulx4wZw2+//cbUqVNZtmwZKpWKY8eOkZaWRkpKCt999x0XLlygV69ejB49mqCgIOzt7Tl27Bg1a9Zk4sSJ/PDDD1y6dIk5c+bg7u5uuQ9y6a/0yqhUULUqjB0LERGQnm4OodeuQUoK6HTmNjV6PWRmwq1bEBtr/ry/P3zxhTnwOjm97SuRJEn6vyeXBEvSG2Q0Gi3LF3ND6saNG5k4cSINGjSgTp06VK1aFT8/P1q0aME777xjKVbTtWtXLl++zIgRI4iNjUWtVrNgwYK3di3/FJnCyAVjJseN6aQLIyYE1qgorLYlQO2Ap2KNoiiYTCbLXk0wF1Ly9PQkOzubcuXK0bBhQzp37gzA4MGDmT59OpGRkZQrV459+/axZ88e6tevz3vvvYe1tTWOjo5/Wt35YUIIkoWek8YMThszEPwvoJqAvIoV5dVO+KntsFZUCCG4jZ5r+ix+W7uO4BqhbNu+mfCIJowIDKZ169b06dOHLVu2MGTIEKZNm0bnzp1JS0sjNDSUpUuXcvDgQaKjowkICDC3t7mbRKV2LVnYdBk/HokmoFwAQTWrE3/iNIqikCWMXDJlsSXuHCvHTiIzOYXiNatQreuHXC+enxU9B7Nq/VpM2ToKFy5M3759KV++PHv27GHGjBncunULLy8vJk6cSPny5Tl69Ch169aldu3aTJkyhZiYGMLDw/nxxx+pUaMGrVq1omXLlpY3Xh6+h29i6W/u14H0L5EnDzRpAvXqwfnzcOUKnD0L16+bQ6taDS4uUKkSFCtmnk3Nl+9tj1qSJOlfRQZWSXoDoqOjmT17NoUKFaJKlSpUrlwZFxcXRo4cyf79+xk5ciQxMTF8/PHH7N+/nwYNGnDgwAH0ej3t27fHz8+PatWqMXLkSC5fvkxaWhqVKlV625f1t5YljOwxpHDWmAmAI2ryoEEBjAguG++z6ffdJB4+yYD2nQjI5wXAokWLmDhxIn5+fgQFBTFo0CCKFy9OWFgYX331FUIIGjduzKxZs1i9ejURERGUK1cOk8mEEIKKFStaxvC0sJojTGzSJ3PFdB8rFJyxQvPQ8UIITvx+gBmLl1OuUTj1a9Tinp2GowcPcmTxahIvXCbDKy9KaACj+w7n1slzePv4cP/+fX7++WfCwsI4ffo0tra23Lhxg8TERAAmT57M0KFDKfduGBVLBxA58ztq9uuKR+VgVqz/lcUrlnH2t93YaLWsPbQX3+Z1KVghkB/a9yS0TXPeadGYL8rXwj1PPhJPn8U2Xx4y7LSEd+uA/aUbfP/995w+fZrs7Gxq1qzJhx9+iJeXF15eXpQuXZqbN2/i4OBAZmYmrq6uuLu74+/vj1arpVSpUoB5mbMQAiHEGw+Puc+3f/9+nJycLGOS/s9pteYKwmXLQtOmb3s0kiRJ0kNkYJWkV8go9KQak0g2JqATWRzafYx5YxejFlratGpLRnoG3377Le7u7ixevJhOnToxYMAAZsyYwZIlSzhy5AgbNmygQYMGrF27llKlStGxY0dWrFjBypUrqVmzpvwB+jmkCwOrdImkCj2uWD3WrubCrn2sHjsJIQTWTo58HHOcrh0+IqyIuSDQzz//jFqtply5cgQEBNCwYUN8fX2ZOXMm3bp1w8bGhtatW/Ptt98SERFB5cqVqVy58nOP774wskqXSLLQ4Y72sWB7ZtdeVo+ZhKJS8HunPHuWruTA/gO8N/xzbuw8SMzyX5kWewyNlRU/DRiBRig0HzeMkM5tODRoAgsXLqRWrVq88847xMbGsnr1akqXLs3x48fRarVk5HdhUWY8Nu6unN+wneaRXek8/iuun7vI0Ep1ibqfQKwpizUTp5G0djMVwqozYFUUCWfOM7d7f6ysrYle9DPHN+9g/t1LWNvZsXfrdtYsWMSoz7/Ar0BBpk+fzrZt23jvvfcsfVtnzJhBtWrVCAgIYPfu3WRlZeHk5IStre1j/VsfLiT1Oj286gHg8uXLzJ07l8OHD9OjRw/5702SJEmS3jIZWCXpFUkx3Oaa4SwmTGiwRoMNhmxBfGwCa09HYaVoKawNoGfPnnh7e/P7779TtWpVvv32W/bt28fBgweZMGECI0aMoEGDBlSuXJmffvqJDz/8kA8++IAPPvjgbV/iP0K2MLJGl0i6MJBP+fOeiPqcHBKvxDHp/AEMOh3rp8xm8ca1VB8Xxrx585gyZQorVqygXLlyLF++nIYNG/Lll1/y6aefcv78eZKTk5kyZQpNX2AmxiAEG3RJ3BU63J4yvttXYvnuwgEuGDPJWrKSnFt3uCly8I8I5+CqdZzbsx8HVxfORe/Hr0IwGXE3sE/XEZd1j3sGHUlJSYSHh3P6veLo/AAAIABJREFU9GnOnz9P6dKlyZs3Lx4BJenfvSeK3kCtjz4gsH5trKytAShcrgweRYtw8eoV7vrkxb1AAS6ducxFXTqeGXrWjJ9Kg15dKV0zlP5lQ3HxcCc9+S5zhw/g9I49FChbkltlvGnkXZYxY8ZQrVo1tm3bhsFgYMCAAVStWpV3332X/fv3M3bs2LfabumPFYazs7OxsbFhz549TJ06ldOnT1OoUKG3Nj5JkiRJkszkRh1JegVSDLeI1Z9CgzW2iiNWihaVoqJ6eBV0OXoyk3QI4Ez6fhRbIx999BHjxo0DIDY2loiICACsrKw4fPgwx44do2XLlixbtgw7O7u3eGX/PEcN6SQLHXkUqyceE/BuGAa9ntRbiWi0WjAJbFUatplSOHLiOHv27OHw4cNs3bqVtWvXsn79eurXr8+IESPw8PBg0qRJ5MmTB09Pz788vivG+1wzZePK08dnNBq5dPsG+5etZmefkWTfSeHG9r3c9/OkYrNGHPhlLY55XbGysSGwbk3iTpzmyyr1STx2lvjYq0ycMY0SJUrg7+/P3r17MRgM2BRwx69/JyIG9GLgr4uo1aUdrl6PXkO7CV+x7MuxWKMiMeY0Tm55ybDVcD09lcyUVPwqBgOg0mgoVK4MAwLDSLoaR61OH9Bv8Rx07s6cNWSQN29eAgICGDduHLa2tnTt2pUTJ04wcOBAdu3aZQmrb6uQUu7s7YwZM6hcuTLDhg3j7Nmz1K9fnwoVKrBjxw4ADAbDWxmfJEmSJElmMrBK0kvSiWziDWexVuxQK48uWlAUhc9G9WTyiJlYKdZoFCuu6k7S//P+lhDh4eHBjh07CAsL4/r16yxatIgyZcqgVquxt7d/S1f1z6QXJo4b08jzlDAI5tel9chBrPx6IrcuXeHMzmi8ivqiR3A16x7p6elkZWVx8uRJXF1dOXnyJDqdjnbt2jFw4EDy5s37QuMTQnDEmIa9on7qcldFUWg7ZhhfFa7I7d2HaPrjJLyrhrCpyxekJt2haL0wUm8nknDmPD5lS5KdkUnn78cxZPNyGvXrwdCY7ezetYtLly5RtWpVrl27xp49ezhlzEAFVGjwLo55Xf/0uQu/W42rW/ewoHwDTEYjFSI7Yo2KuzYKxSqFMCHiQ0bWiqByqwg+mjIWKxtrei2eTcsvB2Bjb4cTGo4a0zl85AjJycnUqlWLYcOGMXv2bAICAqhVqxbu7u6WKstvopCSEOKx6soAc+fO5dSpU+zYsQOj0UhkZCSpqal06NCBzZs3A6DRyIVIkiRJkvQ2yf+JJekl3TXcRiAeC6u5GrYO5z/9JzL428+ws3MgS6QTc+YQgYGBpKen07dvX/bt20dsbKylCq30Yq4as8gRJpxVTw+sAFXaNGNOt8+4cf4SdXt2pkLT+mQKI0kezlSqVImQkBC8vb2ZMmUK9evXfyXjSxZ6bosc3PjzpcAPK9m8HlY97WgwbbTlYy6+3pxfvIYCvT8mv29hYo+fwr2wD2d27SW4UTjWdna4enliEoLC1Stx4Voc1Su8w9ChQylWphRzcq7j/Iwwf0voqD1xOLEbd/LuhKGWj9sU9KDuV59xasmvlK5ZDbdCBQFoN34Eq/7zHZ2njUelVpMZn8CxI0cpFlSVSpUqYTKZUKvVuLu7o9frsbKy4tixY2+0h2rufthbt25x5swZypQpg7u7O+np6fj4+PDVV1+xfft2OnXqRPHixVEUhc2bN7Nu3ToaNWokKwdLkiRJ0lsk/weWpJcghCDZGI8W2yceo9Fo6DqgI7PH/wCAGg0btq6jVq1a5MmTBzs7O2rXri3D6itw3pSJjfJ8M3ZqjYa2/xlKqRpVqNC0PiajETtUaIoUYODXI5k3bx6bNm16ZWEV4JopG3h69eBcdxQj7wzszu6vvrN8LH9ASfL6eJEi9DQZ2IumA3pRpXUzjHo9M7v04erRE0Qv/oVxjdoCApcyxXBwcKBs2bJcN+VgQjxSifiPTAhShYHSzeoTu2MfugxzhWUhBCoBqRqFsI5tcStU0FIVuUqbZhxZt5nLh2KYFzmQCc07kHE7CUOh/IwePfqRVkFWVlbPff0v4+FlxkIIsrKyGDJkCOHh4WzdupXWrVtz9+5dLl++zLJly3B3d+fYsWP06tWLnJwcvLy8KFu2LJs2bQKQYVWSJEmS3iI5wypJL8GEAQN6bBWbpx7Xrvt7VC/SkLz5XVmzaAOu7i70m/rFGxrlv0emMGLF84eh2l3bE1kkmGaD+6LK7Y8rwKBWXkvboExhRCNUPM8QdQjKd/uQWcWqY5/fjbMr1mPt4oxPqLltjq2rCwB5CnjQ7puv2DxtHhsmzyIjJZWmA3rhVi0EK42z5XzZmB7q8vrnDAgUQG2lIejjthyeEUWVz7uZixOhoMO8rPbhdjNqjYZ6kV34ptmHNB/Sjw7fjSZTo5CjMl/km5ydzK34+/AyY0VRSE1Nxc7OjgMHDnD58mXGjh3Lvn37KFeuHHq9nho1agDwyy+/sGTJEubOnUuPHj1wcXF5I+OWJEmSJOnJZGCVpJfwrACQy9rGmladm7F320FGTBtIiQA/fG18X+vY/o0e36X4dFobG0Lfb0HMhi0ENwy3fPx5X9e/SiCeK6zmHq2xsSawU2uubosm/LsvcS/rD5jb4jw8RjtnJ5oN7kt25n1s7M1FupJNOvPzWc7211T9ooclxP/xHH+cIW30WU+afP6p5e8mQw4mxfxqvO6wmpiYiBCC/PnzW4Lq1q1bmT59Oh07dqR27docPHiQ6OhoNm3ahK2tLStXrqRhw4YYDAb0ej1Dhw4lIyMDgMjISBlUJUmSJOlvRAZWSXoJajSoUWMURtTPWIrab1QPFEVBJ7KxVj15CbH04uwVNWnC8JQF2o9r981Xj4Uq69e0W8JO0WB8zuhohYosDNT4qt8jAVEIcwxV/0nyzQ2rACYF7FT/+xb/PNdkOafAElZz27+YAO0T0nbu/TMaDKg1GoRKhb3q0f9e/tjv9FW4d+8eM2fOpGPHjgDs2LGDnTt3kpiYSGBgIOvXr+fkyZN0796dvn37Mnv2bOrUqQPAsWPHsLe3p0ePHtStW5d79+5Rrly5N1IESpIkSZKk5yc35kjSS1AUhXzqgujJeq5jAYxCTz5Vwdc9tH+lYio7sv/iPOvDYTVLGHFUNDg/oYDWy/JSWSMQCPHs0JpXsTIv0f3DbKYOgbOiQf20vagPzl9QsX7kuVWA8SnPrQYcFI1l6S889HWLIK/q6cWi1A8q6hoUgY/K9pHrzA2C69ats1QIfhEPV/x1dnZm+PDhpKWlkZOTQ1JSEpMmTaJ169YMHz6czp07s2XLFqysrGjYsCErV65k1apVfPPNN7Rr145t27YB4OfnR3BwsGWMu3btIi0t7YXHKEmSJEnSqyMDqyS9JFe1JwKBSTy7n6RB6NAoVjipX6wtivR0fmo7rFAwiL+6ONgsHSPl1U6oXlNRIA9Fi6ui5f5zhOo8Kis0KJbwmcuIwFNl/YRHmaVjpJDKBpeHqiXbKWr81fbc42l9RRUKqKzR/2EW2CgEGhRcnmNRTo4wYWNS8FasHwnb+/fvp3jx4syfP58+ffowd+5cMjMzn3m+h5lMJhRFQaVSWcLw1atX+eyzz9i4cSOtWrWiRIkSpKamAlCyZEkCAwOZNWsWkydPJiwsjOXLl3P58mV++eUXPvnkE+B/IXjChAkEBATwww8/WJYIS5IkSZL0dsnAKkkvyVplh5emGNlkPDW0GoQePTkU0pZB9ZyVbKW/xlpRUVbtQMpTQ9mf0wsTahSKqe2effALUhSFELUTGTz7zQ0VCh4qa7IwWTaPGoRAgwqnpwRHkxBkYyRY7fTY5wLUjuiFwPCUWVZnRYMGxTITK4QgGxOeivVzBfl76KmodUGjUpGamsqXX35JfHw8y5cvZ+jQoaxcuZL+/ftz5swZVq1a9czzGQz/ey1VKhW3bt2if//+9OzZkwsXLlCkSBHq1KnD/v37EULQqVMnpk+fDoCDgwPNmjXjhx9+IDk5mVatWrFgwQJmzJhBiRIlUBQFo9GIoijcuXOHAwcOsHTpUhYsWECBAgWeOTZJkiRJkl4/GVgl6RXIpy5IQU0JcsgiS6RjFAbzXkMhMAid+WPo8bUqh6Mqz9se7v+18hpnHNGQJvTP/RijENxBT01NHmxf85sJRdV2uCtaUp5jfJ4qaxwVDfcxYjKZg2Mhlc0Tg6NJCBKFjkC1Ez6qxytXe6isqaJxJhndE5cGq1AopLIlCxMmkyALE06KBo+nzOqaHrSRScOAE1YUV2wZN24ckZGR6HQ6fHx8SE9P5+rVqwBUq1YNX19fEhISLMt7/yg9PZ2VK1daWtQIIdi0aRPvv/8+vr6+lClThuHDh3P69GlatGhBXFwcO3fupFu3biQkJLB7924URSEoKIixY8eya9cuTCYT1tbmmd+LFy/Svn17hgwZwtGjR4mLiyNv3rwMHDiQCRMm0KdPH9atW/fkF0eSJEmSpDdCBlZJegUURcFN400p68p4qH0xYSCbDLLJQFFUeGtKUMq6ilwK/AbYK2qaad3RoOKu0D1zv2iOMJGEjlB1HkqrHV77+LSKiiZaN2xRc/cZoVWNQnG1nflYRY+nYk2+P9lHKoQgUxhJREegxpHqmjxP7HVaUeNMJbULSehIe/DGyh+5qazIr2i5oxiwR00xld1T98yq1GruCT3Jl2OpkaHBQW3FzZs32bt3L2PGjAGgRo0a3Llzh5SUFFxcXLh+/br5sQ8t7wUsAdbR0ZH169czdOhQ6tevz7JlywgODubnn3+mcuXKrF69mtOnT7Ns2TJ8fX0pWbIkO3fuBCAiIoKlS5dazhMSEkJycrLlnhw4cIB+/foRERFBSEgIHTt2RAhB165dqV+/PiVKlABg+fLlnDlz5qmvkSRJkiRJr5esEixJr5BWscHDqjAeVoUxCSMKCooi3xd60/KorGht7cFW/R3iTNmohIIzaqwevBZCCNIxko0JW1TU1+SjpOb1h9VcjoqGVtb5WadL4pbIQftgme8fZ05zhIk0DHiotISonLhj0pMocrBChQYFAegxYcRcpKmaOh8l1PZPDKtgfnOlssaZAiprDhnvcf3B/dGYv1oxCIFRMeGpsqakYk+8KZt7GHASGrSKiuyMTBSVgrWdHUIIMjBy/lAMGwb/B08bR277+/PJJ5/Qp08fVq9ezZUrV/D19aVChQps3LiRzz//nEaNGrF371569eplGVNuv9aHi2DZ2dkxY8YMBg8eTJs2bQA4evQoQ4YMYeDAgWRlZTFnzhzOnj1LkyZNGDJkCKdOnWL06NGPXK+Hhwdt27Zl8uTJ9OnTh6SkJGrVqoWNjQ1TpkzB29sbd3d3ChUqRHBwMADJycls376dkiVLvqJXXZIkSZKkFyEDqyS9JnKf6tvlqGhops3PXZOeM8YMThjT0QvzfkiBuWpuebUTPipbNK+pyNLTOCga3tN6cF1kc8yQzlVTFop4tF+qLWqqalzwV9vjoGgwCkG8KYvLpizuCyMqFJwUNcXV9uRXtE8Nqg9TFIXCalsKq225Y9JxyXifNIwYhcBOUVFYbYuXYoNaUbgn9Jw1ZBJjTOeeMHB8yzYy76ZQpVNbbp65SFDpMmSt38P00WOpVSOMcuXKodfrGTduHM2bN2fixIl8//33FC9enAkTJrB48WKWLFnCoEGDqFevnmVMuUF18eLFnDt3jn79+jFgwAASEhIICAiwHLdr1y5UKhW1a9fmwIEDnDt3jkWLFjF69GgmT55M0aJFH7nW1atXs3nzZvr06cP48eNp3749iYmJTJ8+naCgIIYOHUpoaCgAmZmZbN26lVGjRlGgQAH69+//3PdUkiRJkqTXQ3me9gpvW0hIiDh8+PDbHoYkSf9gQgj0CEwIrFA9dYnr25AmDNw16dFjQoWCjaLCQ7F+6+PM3YttVOCmKYfDR4/SqV5jvH3NxY56de3G6NGjycnJ4erVqxQrVoyRI0fi4+PDmTNnaNmyJdu3b8fDw8Nyvj8LgcuXLyc6OpqkpCSys7Px8PBg9OjR7Nq1i59++okpU6bg5eVFXFwc1apVo2nTphw/fpz33nuPZs2a4enp+UgP1fPnzzNr1ixu377NJ598QvXq1enSpQt+fn60adOGyMhIvvrqK0JCQkhLS2PIkCFERkZiZWVFdnY2pUqVemP3WJIkSZIkUBTliBAi5I8fl2sVJUn6V1AUBa2iwkZRv/UQ+GecFA2F1bYUU9vjp7bDS2XzVseZG1Rz28goRhM+aluSY07jnjcfVYJD+G7MOJycnLh//z4qlYrly5fzww8/4OPjw8WLFylVqhSVKlVi//79lnM+HFazs7O5cOECAAsXLuTQoUMsXryYWbNm4ezszKJFi4iIiCA9PZ0TJ05w/vx5hBCsWrWKggULMm/ePCIjIylYsCBqtZqMjAxOnDhhGfuRI0dwcXGhevXqAHTt2pWlS5fi7e1N8+bNGT58OG3btqVy5cro9Xry5cuHr6+vDKuSJEmS9DcilwRLkiRJj8kNlikpKQwbNoxLly7RtGlTunfvTnBwMN26dUOv15M3b14CAgJISEjg8uXL6PV6+vfvj7u7O1OmTGHOnDmWmc/cc+buV507dy5Lly4lOjqaPn360KlTJ0wmE25ubpQuXZqDBw+SlJRE7969WbRoERs2bODrr7/GYDBw//598ufPj6IoZGVl8c0337B48WLq1KlDamoqP/74I23btuXIkSOkpaXh5OREhQoVKFWqFN9++y0DBw4kLCyMmJgYpkyZgpub21u715IkSZIkPZmcYZUkSZIs7WPAPBOak5PDkiVL+PTTT/Hw8GDcuHEMHTqU33//nZCQELy9vS39TiMjI6latSpTpkwhIiKCihUrMnHiRABLWBVCoNPpWLRoEVFRUQD06NGDnJwcdu7cSe3atQkKCmLq1KkAVKhQAYCoqCgaNmzIuHHj+Pbbb5k1axbR0dFUrVqVnJwcABISEjAYDJw8eZJPPvmExYsXs2PHDgIDA7G2tmbLli2AOTC3b9+ezZs3A+Dn50fLli1lWJUkSZKkvzE5wypJkvR/KEeYSBI6coS5TYxWUeGuaLF+qGq1wWBAo9FgMpkswfLs2bMUKVIEGxsbrl27xokTJxg6dCj+/v707t2bmTNnUrVqVTp16sTAgQPx9/fnwIEDDBkyhIYNG2Jvb285Z24hpbNnz+Lr64u1tTVxcXGkpaURGxtL4cKFadq0KbNnzyYsLIwuXbrw9ddf07t3b0qUKEFoaCg+Pj4A5M2blyNHjjBz5kwqVar0yLVu27aNy5cv06hRI3Jycli4cCF16tThv+zdd3xN9//A8de9N1OWBIkkQsSWIQkZFaSovSnamrWpKjX7U6OD2iNWhaJFqzp8qxWNVbFLiBVKhAwEkUSmrHvP748rITVKjUi9n49HHuLm3M89JzfJOe/zfn/en9u3b3PkyBFCQ0Np164dRkZGtGzZklatWr2It0AIIYQQz4BkWIUQ4j8kSZfHnrxkVuZc5ufc6/yWl8hveYn8nHud4JzL/JGbRExaMj179mTcuHGAvkPviRMnaN++PW+99Rb9+/fn22+/pU+fPvj5+XHq1Cmu6XLwGtab/adP8MXB31Fa+OHbujnzFi7A09OT27dv89577z10zH79+rFhwwZ69epFZmYmB/ceIXYPBNq8x5bNoaydfJhaJq3Jy8lny5YtAHTr1q0wODUyMmLdunWULVuWmzdvsnXrVk6ePElKSgqvvfYae/fuZcyYMezevZuePXty9uxZtFotPj4+VKxYkZSUFADp+iuEEEKUMJJhFUKI/wCtorAnP4UT2jTUqCmNBoO/rQGcryic1mUQodGxded2KtjZExERgZeXF1u3bsXV1ZXNmzcTEhLCqFGjaNu2LaVdKvLt8YOcqedMGXtbHL1c+SUoGOvVC3Gb/B7eRkaU0piRpzZk586d2NnZPXLMsN/DMbxZkR/nHEXt3hYzc2tMNVZ899NqLOJ9aVlmMsumfU/FMrVx96+s3+87meDRo0fzzjvvEBsbS2BgINHR0WRkZHDgwAG8vLw4cOAAZcqU4ciRIyxevJgpU6bw5ptv3peRLSl0On12/N61aYUQQohXjSxrI4QQJZxWUdial0iU7jblMET9tyxi5B/7CP/1d1qPGEw5Zyduxl/hxwVLMbmdRw0zaxYFBfHOO+/Qt29fmjdvDsAbzZrh+1ZHdD41ObhoDR6BAbzWtQPpScmk30wi5ep1wn/9nRYjBmFQqTyZl69zadFauJ2DqakpCxcuvG/M1xs0w8u4Bx62zfnf+WnEJJ3GSGNMvSrNsTaz4/cTa1CjwaNcCzp6jMbvA7BzuxuwarVazpw5g5mZGbdv36Z69ep07doVNzc3PvzwQ7755hu2bduGlZUVY8eOxdvb+4W/F89CwXm5IBucnp6OhYVFce6SEEII8dzJsjZCCPEftSc/hfPaLGwfEKwCaPPz2b5sNaFLvyIrLR1zG2uSz0Th3L4pEXEXSUhIwM7OjiNHjgD6gKlel7Zs3/0HtarWoGx5O0wtzFEUBTPr0jjUqFY45o6lqyiVnoO5tRV7TkXwRod2xMfHc+3atSJjpsaDm7obJ6/upHINB95rNZc33Hswqu2XdK8/htJm5UhIucic3tvo3Wo0JlZwaB4kRYGBgb4YSK1W4+7ujouLC66urhgaGtKyZUt0Oh02NjaMHDmSDRs28N1335XIYLUgo6pSqVCpVCQnJzNq1Cj8/Pz4/PPPOX78eJHthBBCiFeBBKxCCFGCJevyOKFNx1Zl9ND5me5vBGLtUJ687By2f7mGrFupVPOrR3b0Zaw8a7Hs69WMGjWKkJAQ1q5dy+6Tx9iyZQuNOrfHUKOhw/gReLZsWrgm64PGVKVm4uLnTcj5E3h7e/P1118XjvnN12vZOPUURy9vobn3OwAYGZjQru4gHKxdAPCp0oJ8bR6pWTfZfnIdE35qQmz2YQ4vgpSbaUyePJmxY8cCEBERQUREBAMHDmTx4sV06tQJ0AfalpaWz/tb/tzcW/o7c+ZMunbtirOzM1u3bkWr1TJ06ND7thNCCCH+6+SsJ4QQJVikNh01qgdmVguoVCre+WISmbdSqezlzvJBoyhV2pIKNatRJaAe2/eGYWVlxfTp0zl8+DDDhw7FxdcbrxZNADAwNHysMa2tSmNawxm3AH/27t1bOOaebYeZ9+sQ3F38qVel+UP3cWjzOXSeY8fxmN30DpyMR3VfMlJyGdpvFOnp6bz//vsA/PnnnwwePJiqVaty7NixwiVwSnpDpYSEBObNm0dMTAwBAQFERkbi5eVFpUqVmDJlCgkJCezevRu4WzYshBBC/NdJwCrEK6pg3U258C25chQdJ7UZWKH5x219O7fl1M4wPJq9TlUfb/43YyF5ubl4+PiArTXTZ84gMDCQqbNmMHjXD7w5dgRqzaPHvW/MmUEoOXkY16tF+fLlmTVrFoGBgfT2ns3sLvt5p8EENOqHjxlYuysmhmaMbb8ST+fXydfmYW5jxADPZcybN59KlSoB0KdPHw4fPsz48eMxMjJ6sm/aSyA/P7/I/0+ePAnoM6cRERHs2rWLBg0aUKNGDeLj4wu36969Ozt37gRKfnAuhBBCPC4JWIV4xRQEqBqNBp1OJxe+JViikosWBUPVP/8p1xgY0HbUUDZNn0/XqeN4b81iyjlXpJSpKX59uuHfugUASYYKOhQ0j/Fz8aAxKzlX5oKhln79+tG2bVvycyDplDFm5f75eDRqDb0aTWLFjo8AfVBmUhoy4o3IStIVzt00NTX958FeMsePH2fevHnA3Tm5cXFxHDx4kCFDhhAbG4udnR0NGzbkxIkTJCUlMXLkSGbNmsXBgwfJyMjg/PnzsoasEEKIV44ErEK8Au7NoqpUKnJyctiwYQO1atXi2LFjxbhn4mnkKjqeJD/eYvgAti5aAYBny6ZUqFUdgMr+dXF7zVc/purJMu5/H7NS7RpoUfB5zZ/XXnuNvCxQq1U8RkwNQGe/9/n16HIANGoDVCpQqUGbrS6RczcLKhlMTEwYM2YMeXl5gD5bGhoaSuXKlfH19eW7774DoEWLFmRmZrJ9+3Y6deqEmZkZs2fPZtiwYdjY2ODq6lpsxyKEEEIUh5J39hdC/KOCAFVRFBRFKZJFzcjI4P/+7/+YP38+oaGhJbKbqrjrSfLjRiYmNHinC8e2bHtmr/+sxzQyMKGZRy8OnPv1mYz3ohX87ul0OhRFQXOnrLpmzZq0bt2aqVOnAnDz5k169epF+fLlad68OYcPHyY5OZlKlSqRlZXFhg0bSEtLY9iwYSQmJrJ69Wq++uorrKysiuvQhBBCiGIhAasQ/zFZWVlkZWUBd5fHiIyM5IsvvmDPnj2Ym5tTt25d4uPjKV++PCDzWEsqo8dNW96j5+xP8G5zf+Mj4zuhr/G/OC3cO2a+oqBBhcGd8QxL6bdRnmAllvdazqd+jXb65ymA7u44L7Pbt2+Tk5MD6OejqlQqzpw5w7Rp07h69SpTp05l9erVbNmyha5du2JiYgKAl5cXxsbGzJkzh/j4eBRFwdHRkcTERHr27Mlff/3F/v37gbsZWyGEEOJVIQGrEP8xo0aNYvz48QDk5eUxZ84cBg8ejJ2dHZMnT2bt2rX4+/vTokULNm7cCEjAWlKVUxmhQUXeE0SDfy+rzVcU1KiwVeubFzmoTVCjQvsEPxP3jplKHrU1ZoVZfQNjKO8JmYmPPRzqewLx7FtQujKYWD/+84tDdnY2c+bMKWygpNVq+eyzz+jRowcajQa1Wk29evVwc3OjXbt2REZG8sMPP5CZmYm9vT2TJ08mMjKSLl260L59e5YsWUKVKlUAmDt3LqVLlwYozNgKIYQQrwoJWIX4D7g36/Luu+9y8OBBMjMzMTQ0JDedhlyxAAAgAElEQVQ3lxUrVuDp6UlUVBTR0dFYW1vTtGlTQkJCAFnXsaQyVqnx0JiTyr/PuqWSh7vGHBOVPhAyU2mooTEjjfx/eOb9FEVBi4K7xqLI4y7NIP/2v9u/nFSo2gpext5gkZGRTJo0iR9//BETExMmTZqEnZ0dubm5KIrC2bNnWbduHRMmTCisZpg0aRKmpqZ06dKF9evX07NnTz755BNcXFxYu3Ythw8f5u233wbudhPu3bs3Hh4exXacQgghRHGSq1QhSrCCQLUg63Lr1i38/f1xdnZm+fLlZGRkcPDgQTp16sT06dPZuHEjU6dOxdraGn9/f9LS0tiwYUNxHoJ4Sq4aC3Qo6P5FllynKGgVcNOYF3m8jsaCXHRPlGUFSCOf8ipjyqmKrttatgaYl4espCfbv5w0MDIHu5csVrt27RqtWrViwIABGBoa8sknn7BkyRLOnz/PmDFjWLt2LfHx8aSkpFChQgWys7MLmy01bNgQR0dHUlNT+d///seIESNo3bo1xsbGWFpaAnd/rwu6CQshhBCvMglYhSjBCgLVnTt30qVLF7p27QrAgAED2LBhA+bm5lhZWTF48GB+/PFHAgICiIyM5Pvvv6dKlSqMHDmS+vXrF+chiKdkozakjsaCRPKeqLRbURQSycXNwJwyfwsw7VRG+GtK65fNecwxM5R8QEVzw7L3LZWkUoPPe6DNgezUx9u/3AzITgG/D/RlxS+TmzdvcuPGDaZNm8bkyZOZPHky+/btw8jIiA4dOrBr1y4qV67MzZs3OX78OCYmJhgaGnL58mUApkyZwrZt+iZVjRs3xsfHp8j4UvYrhBBC3KUqCXPX6tWrp4SHhxf3bghRrArWoLy3fDcmJoa2bdsSGBiIjY0NQUFBnDx5kkqVKtGsWTOGDRuGg4MDixYtwszMDHNzc0JDQ3nzzTeZPHmylAL/R2gVha15iUTpblMOQ9T/UD+ruxOsuqhL0cawHAYP2F6nKOzPT+GINg0LDCiF+oFr9moVhRTyMEJNJyNb7NQPjy6To+HgXNDmgpkdaAzv30aXDxnX9Z/7fQB2bo8+9uKQmZlJcHAwf/31F8uXL0er1eLu7s6OHTvIy8tj9OjRjBkzhqtXr/L111/j4+NDamoq+/btIygo6L4A9e+dvIUQQohXkUqlOqooSr2/Py71RkK85ApuKhUEl7du3SpswBIZGUmrVq2YPXs2AFeuXOGjjz7i22+/pX///ixatIhdu3ZRsWJFfvjhB9LT09m9ezdly5YtMr5cLJdsGpWKVoblMMtP4YQ2DbWipjQaDFT3N1hKJQ+tAu4GFrxuYPPAYBVArVLRwMAaO5Uxh7WpJCp5GChghBoVKnQo3EaHGqitMcfHwBIr1QMi0HvYVIHXP4HobRCzG3R5YGACagPQaUGbrc/GOgVA1ZZg4fCMvkH/klarfWC208zMjMDAQPbs2cOaNWvYs2cPjRo1okyZMgA0a9aMlStXsnLlSqpVq8a6deswMzNj8+bNlCtXrnAcnU5X2E1YCCGEEA8mGVYhSojExESmT5/Opk2bGDJkCP369SMkJISNGzcWNk+Kjo7G09OT+Ph4SpcujaurK59//jmdOnUqMpZOpytc8kb8tyTp8ojUpnNKm4EWBQX9Wq0KoEGFu8YcN405NirDx37/FUXhupLLWW0mKUoeeSiYoqaS2pRqmlKUUj15CWtuJiQcg1uX9J8bmoJVJXCoC8aWTzzcM/X3mzj5+fmF80kLvpaens706dNZunQpixcvpmfPnoXPiYyMZPjw4UyePJnGjRsXGbsgSBVCCCFEUQ/LsErAKsRL5kFZndmzZ/PNN9/w0Ucf4ebmxtq1azE1NWXSpEnY2tpy5MgRqlatSlRUFM2aNaN37958+umnnD17llq1ahWOU/D7LoHqf1+OouOGkkvunSVvjFRqbFVGGP+LtVtfFX8PJs+dO8ewYcNwd3enc+fONGrUqMjv58GDB/niiy9Yu3YtVlZW5ObmYmRkxO3bt7l48SKurq5FxpabREIIIcTDScAqRAkTHh5O2bJlcXZ25tixY9SrV48LFy7g4uJCWFgYwcHBzJw5k3Xr1nH06FGqVq3K5cuXcXFxYdu2bRw4cEAujoX4F3bt2kV2djbXrl0jNzeXUqVKsWzZMkJDQ7G0tCwMbJOTk5k9eza3b99mwYIFUl4vhBBCPAWZwyrESygnJwdj46JNar7//nuWLFmChYUFarWaTz75BG9vb/z8/Pj5558ZM2YMVatWpXbt2qxcuZKpU6dy+PBhNm3axCeffML58+efqFusEK+iB1UbhISEsHPnTsLDw8nIyMDR0ZHNmzcDsH37doKCgvj4448LA1Zra2saN25MWFgYeXl5GBo+eg6vEEIIIZ6c1IYJUQxSUlKYNWsWO3fuBPQXzwsXLiQvL4/Y2Fjmz5/Pli1buHr1KtOnT0dRFGbMmMGCBQsAcHR0xMPDgzNnzhATE4Ovry8jRoxgyZIljBs3jurVq0umR4iH0Gq195XnpqSkMHjwYPLy8ggLC2PUqFGUK1eOyMhIAPr168fmzZvRarUYGBgUlvg2bdqUadOmSbAqhBBCPCcSsArxAp07dw7QdxkNCwtDURRCQ0Pp0aMHhw4dIjk5mZEjR3L+/Hk8PDwICAjg5s2b/PbbbwQGBmJhYcHChQsBCAgIYMWKFTg7O6PVajl9+nThfNaePXsW52EK8VLTaDSkp6fz0UcfMXv2bI4fP461tTU9evTgxIkTALRs2RKdTkdERAS5ubk0btwYY2Njli1bBtzt2l0wn7Vg2SkhhBBCPFsSsArxggwePJhu3bpx4sQJjIyMqFatGsuXL+f8+fPs27eP7777Djs7OwwNDdm8eTOLFy8mKCiIcuXKsXjxYgBmzpxJXl4eADY2NlhZWaHT6dBoNDRr1ozx48ffV2IsxKtKq9WycOFCunXrxvbt20lLSwP0pb8BAQGYmZlRuXJlOnfujFarZcSIEaSlpXHixAnKli2Lr68v+/fvJyoqCoDg4GB69+79wNeSzr9CCCHE8yFnWCGek9zcXHbv3k18fDwAdevWJSEhgVWrVgHw7rvvkpiYiJeXF05OToWZnaSkJIyNjfnzzz8LyxHLlClDfHw87du3Z8yYMUVeRy6UhdDLSYMrh+HSHzB9zHIc7Z2IjYnD09OTFStWsGLFCgB8fHzYtm0bHTp04JdffiE+Pp6lS5fi4OBA69atC6sY2rRpg1qtLiz3rVWrFpaWxbzmjhBCCPGKkaZLQjxj2fkK55J1nItJYMXCYKpWqcyiWZ/TtGlTIiIiSE5OZuPGjVhZWREQEMCtW7do27Yta9eupU6dOlhZWdG/f3+mTJnCpk2bGDduHB07diwcX5amEaKo9AS4sBXi94NOq19z9mqUEbkZ0FyZS9V6YG0VzLUbV8jJyaFcuXLs27eP8ePHM336dN5++20++OADBg4cSK9evWjcuDFXrlyhYsWKLFmypLgPTwghhHilScAqxDOSq1XYHpNPWLyWXC2gssW29Uh+nDGATOfGdKhXmdq1a2Nvb09ycjK7du3CxMSE0qVL07BhQ2bMmMGFCxeoWrUqDRs2ZP369djb2xeOX9CZVAJVIe5KPAuH5oOigLk9qO+c1d50fpcfTk/hZMIustY14VxKNuV8TAtL5mNiYqhduzaBgYFERUURHR3Nhg0b6Nu3L6GhoTg6Ohb+zv19fVYhhBBCvDgSsArxDORqFb46lcfZJB3lzcBIowJUVPCsQ3r7XhxcN4vbykQyDkWyas6bGBkZsW3bNnbv3k2jRo3o1KkTjo6OHDp0iKpVqwIUBqtarRaNRiMXzEL8TWo8HJwHxpZgbHH/1zv7jWDl3rG09hrAqp2f4ny6JtVrVqNzl45YW1uTk5PDoEGDyMrKYuzYsfj7+wPg4eEB3C23L4m/ewV/N4QQQoiSruSdhYV4Cf1+KZ+/knQ4WRQEq3c1emcENnaO5FwK59jRcL4NPUCZMmXo1asXqamprF69GpVKxdy5cx/Y3VcuOoV4sDMb9RnVBwWrAN3rjyExNZ5jF7ez/oMLBJTvzdKFK3jvvfeoU6cOw4cPx8DAgPHjxzNz5kxq1qz5Yg/gOSjoVlzwd+P8+fNkZmYCyPrMQgghSiQJWIV4Sll5Cnsuaylv9vB5pa+9ORhtXg65aUn8uGUHiqLQoUMHfvzxR5YvXw6Aubk5IBeVQjyOjOtw/RSYlXv0dm28B6JSqbEwLU27eoMY+foarl69SmRkJL6+vixduhR3d3eg5C5Nc+/fjIJs8OHDh2nQoAE9evSgX79+hWvPCiGEECWNBKxCPKUzSVrydWCoefjFYIWaXni3fIvbqUkk37zJX1f1y2t06NABBweHIhecclEp/klJDayepYSjoFLrPx6ld+Ak9v31P+KTzmNqA1wtz9rlP9GiRYvCbQq+nyWt9FdRlPsC0by8PEaPHs3MmTMZM2YMR44cITExkc8++wzQlwoLIYQQJUnJOjsL8RK6nqmgUT06K6rT6bCydWRo8A5aTVxNnpF54dcURZEgVTyWkhpYPQ9ZiaAx+uftjAxMeNN/JFeTo1GpQKUBXbZhkaC/pH0/C9aFValUaDQasrKyWLp0KeHh4RgaGuLv78+NGzcoU6YMAF988QVLly4FZIqBEEKIkqdknaWFeAk9TqxZcEHsWL0OKrUByj0XyxKsisdV8HMUGhrKihUrSE5OLuY9KkZPcPYa2nwOftVaAfolb1Sqkhekgj47+ttvv3HgwIHCgHvr1q34+fmxZ88eli5dysCBA+natSuVKlUiKSmJ3Nxc/Pz8cHFxYd68eYBk6IUQQpQs0iVYiKdkb6ZCq3u8oFNRFHQKlDOTLId4NEVRUBSlSGAVERHBsmXLiImJwcTEhG3btvHNN99gampajHtaPMzsID/n8bfXKTpUihp0YGz1/PbrWVMUhdjYWGxsbLC0tKRly5bk5+dz9OhRfHx8iIiIYPTo0fTt25esrCxq1KjBiRMnaNGiBfv27cPV1ZVq1aoxduxYPvvsMz788MMSGawLIYR4dclZS4inVKuMBiMD/dI2/yQ1FypZqbA3k6yqeDidTodKpSoSWFy6dIklS5Zw6tQptm3bxubNm8nIyGDnzp2v5LxEx3r6TKnymMlCtUpN1k2wcwdT6+e7b89CYmIip0+fRlEUdu/ezfbt24mOjubPP//kq6++YuHChSiKwv79+zEw0N97LlWqFEOGDCEoKIgOHTpw4cIFjh8/jqIodOnShePHjxfzUQkhhBBPTgJWIZ6SiYGKphU1XMtQHtnhN0+nkJoNzStppAxY3OfkyZMEBQWRlpaGWq0mKyuLzz//nL59+7Jnzx4qV65Mq1atMDMzIzo6GoAmTZqwbds2kpKSinnvXzxTG7D3hoxrj7e9okBuBrg0f7779bRu3LgBwO7du7l06RI6nY7w8HA++OADunTpgqWlJV5eXlhaWnLkyBH69OnDggULCp/v4uKCk5MTlpaWtGnTBjc3N1QqVWEZ8Kt4c0MIIUTJJgGrEM/AG5UM8LE3IC5NISuvaNCqKAppOQpXM6B9VQPcykklvrirIJC4cOECwcHBWFpaEhkZSfPmzcnLy6N///5MnTqVHTt2EBgYiIeHB6GhoQD07NmTM2fOcOTIkVdyOaTaXUFtCLdTHr2dokBqLFR4DcrVejH79m/ExcXh4OCAVqula9eu2NvbExsbS40aNahSpQr/93//h7u7O66urlSvXp3vv/+ebt26YWpqyqRJk5g5cyYzZ87E09MTgIEDB1Krlv6AC7L10nRJCCFESSMBqxDPgEat4p1aBnStYUi+Di6nK3c/MsDMUMVADwPeqCQXi686RVHIy8tj9erVwN1AokmTJpibmxMbG0ulSpXYtGkTffr0YenSpVy5coXp06dTtmxZ6tSpw+nTp0lISMDe3p6mTZtSqlSpVzJrb24HAeP0ZcGpcffPaVUUyL4FKRfBvi549fvnZXCKQ8FNi4oVKxIYGMicOXMA+Omnn3j//fd5//33GThwIPv27SM5ORkrKyu8vb3JyMjg8OHD/Prrr1SvXp3o6GhWr15Nx44dC8d+FW9kCCGEeDZelnPIS3jqFqJk0qhVNHIyYEp9Y97zMqJnbUN6uxoyup4R43yN8Chn8EoGFaIolUpFfn4+EyZMYPHixSQkJAD6Oapubm5kZ2djbm5OXl4egwYNomnTppw6dYpr166xf/9+mjRpQnp6Ovv37wfgo48+onHjxsV5SMWqdCVo/AlUbwc5qXArVh+8psbps6rGVuA7HHyGgYFxce/tg6nVam7dusXGjRupUaMGy5YtA2D06NFcv36dM2fOULduXXJycjh8+DAAlStXxsHBgR9++IHSpUvTq1cvgoOD8fLyKmzYBdKFXAghxJPT6XRFll0s7u7yqpclcn6UevXqKeHh4cW9G0II8dS0Wi0ajYa9e/fy008/kZ6ezldffcWtW7d47bXX2LFjB46Ojnz33Xfs37+fxYsXc/nyZdq0aYONjQ1//PEHFy9exMXFpbgP5aWTnwMp0ZCbCWoDKFUGLJ0eb+mpF6Wgoda9gWRmZiYtW7bEzc2NBg0aMHLkSKZNm8agQYOYMGECN2/eZOXKlSxcuJCwsDCsrKwIDAzEx8eHypUrU6pUqSLjSxdgIYQQz0J6ejqzZs2iZcuWBAQEPPfXU6lURxVFqff3x2UynRBCPEcFAWqBgs8bNmyIq6srPj4+rFy5kn79+uHn58dvv/3G4MGDcXJyIj4+niFDhnDx4kVGjx5NlSpVACRYfQgDYyhXu7j34tEKgsmoqCgsLCwoX748UVFRuLi4FGZWzczMGDlyJIMGDWLIkCF07NiRixcv8sEHH3Dr1i0MDQ3p2bNnYXfge++CS7AqhBDiSf39WgX0VT7JyclUqVIFb2/vYtozPcmwCiHEM/agcsysrKzCTJiiKOh0OjQaDb///jshISFkZ2dTsWJFatasyZtvvgnAuXPn2LhxI82bN8fPz+/FH4h4an/PeEZHR/PRRx9x8eJFWrZsiampKe+++y7+/v7ExcWRl5eHoaEhjo6OLFu2jPbt29OrVy9cXFz45JNPivFIhBBCvDQSEyE2Fi5e1P+bmwsGBlC+PFSrBhUqgNOTlxhFRkZiZmaGs7Mz06ZNY86cOVy9evWFrff+sAyrBKxCCPGMPKjcc926dYwdO5bOnTvTqlUr2rZte9+dzJiYGLp3787Ro0f58ssvGTBggJR2lnAPe/++++47TE1N6dixI7NmzWLatGmkpqZSr149+vXrx7Bhw0hNTaVVq1bcvHmT8+fPk56ejoWFRZGx//5zJoQQ4j9OUSAyEn7/Xf8v6IPUUqVAowGdDrKzIedOB0JHR2jVCnx8wMioyFB/P0edPHmS4cOHY2RkRO3atWnevDlt27bF3Nyc8PBwatas+UKuSyRgFUKIF+TGjRusWLECOzs7srOzadasGadOnWLOnDkcOHCgyB/8ghNAWFgYU6dO5e2332bQoEHFuPfiWVq7di0nTpxg6NChVKlShTZt2mBra0t0dDQODg6MHDkSf39/du3axbx587CxsSEuLo5hw4bh6OhYZM7QvaW/QgghXiFJSfDNNxARARYWUKYMPCp4VBRIS4PkZHBwgEGDUJydURTlvqBTq9Uyb948/Pz8aNSoES1btsTQ0JBff/2V0aNHc+nSJX7++ecHlg0/axKwCiHEM/b3P96pqanMnj2bhIQETE1N2bdvH56enqxZswaATp060bRpU4YPH/7AP/ySVX35KApoc/T/Ghg//rI4wcHBxMXFceXKFWxsbLh48SKDBg0iKSmJDz74gPj4+MIS8YMHD+Ln50dmZibffvstPj4+j5wvJD8nQgjxCjl9GhYv1mdQ7e2fuMz34sWLuKjV0L07tGwJKhWLFi0iOzubrl274uzsTJ8+fbh58ya3bt2iRo0afPzxx7i4uJCeno6dnR3nzp3Dycnpud84lYBVCCGekb//wc7Pz8fAwIDLly9TrVo15s+fz5AhQ1i6dCnR0dEMGTKEatWqsXnzZmbMmMGBAweKce/FP1F0kHQeLm6HhAh9sKpSAQqUqQlVW4Ktq74TccF7X7C+7o4dO2jdujXdunXj0KFDxMTEoFarCQkJYerUqezYsYM6deqwZMkSKlasyPLly4mLi2PWrFnUqFHj7j48YB703x+7d160EEKI/6CTJ2H+fH1G1dz8iZ56NjGRxYcPY25kxMzXX0cbE0OoiwtfnTlD2bJlUalUJCQkMGLECPbs2cOxY8dYuXIldnZ2ABw7dgxvb2/effddXn/9dfr06fM8jrCIhwWscotWCCEeQ2pqauHnBQHD1q1bef3115k6dSr79++nQoUKvPvuu/zxxx8AtGvXjsTERE6ePIlWq6V169bk5uaydevWF77/BY2exMMpCsQfgO3jYN8MuHEGLCvo13q1qgiWFSElTsukQYvo0+AzTv6SiVplQFZWFiqVip07dzJ79mwAPvvsM65fv14YZDZt2hQbGxsuX77M4sWLCQsLY8CAAVhaWrJ69er7gtV756jeG6iqVCouX77MyJEjWbRoETkFc5WEEEL8t1y5AkFBULbsEwerAL+cO0dpExM+bdyYo4mJ5Ds5sX7dOi6dPs3y5cv58ssvee211/jzzz+xt7enTJkyhIWFcf78ebp3787cuXPJzs5m1apVLyRYfRQJWIUQ4h5ZSXD9FCQcg8QzsHf3Qbp27UqnTp3YuHEjt27dAmDBggUEBQUxf/58qlSpQv/+/VEUhVGjRnH27FliYmJwcnLCzc2NHTt2EBMTg4GBAVu2bKFVq1Yv7HjuXfxbrVZL0PoQig7O/ABH9CvLUNoZzO3ulgDfzs1k1R8f89GvjYjK2EMj185E/2TGV+P2Uf+1+gQHB6NWq/H09ASgRo0a+Pr6MnHiRECfibWxscHMzIw2bdowc+ZM9u/fz7Rp07CxsSnyvhQEqlqttsj/AVauXEndunVxdXVl/PjxGBsbP+fvjBBCiBcuPx9WrNA3SzIz+8fNs/LyOJaQQE5+fuFjjhYWHLpyhZPXr9Px++8xNjGhu5cXZbOyOPfnnwC4ubkRExND586d6dq1K9u3b+edd97B19eXNWvWYGJigkqlKryWKC4SsAohBPoS0D+DYNtoODQfDi+Gjm260bltd5pW6c/bnfvyyy+/8N133wHQp08ffvjhB8LCwli2bBmJiYl8/fXXVKtWjcDAQObOnQtA+/btqVWrFuXKlQMoLLV5UdRqNSqVivT0dD788EPatWvHwYMHyb/npPaqUxT4639w7ld9oGr0gBvZV5KjWL93OnN6bWdq1x+o5uSKaYXblL3ZgLFt1nDkSDjDhg0rEkDOmDGDWbNmsWDBAnr16kVKSgplypQp/LpGo0Gr1T6wCUbB1wE2b97M+vXrAXjrrbdISUnB2dkZgLy8vGf3jRBCCPFy2L0bLl0CW9vH2jwuNZX/27mT5UePFj7WoGJFFEXB1swMb3t7vj99mtdr1MC9dGl+nDYNAF9fX06dOoWpqSlt2rRh0aJFhIeHM3r0aAwNDQtvphZcSxQXg2J7ZSGEeAkoCkSFwJmNYFBKX/pZkFVzq1qP1Pyr2Ce2RJuUTRX7q4WBhbW1NatWrSIsLIzDhw+zbt06pk+fTp8+fejVqxf9+vUjKyuLmjVrUrNmzRd2PPc2cyrIrL7//vuoVCqcnJxwcnJixYoVXL9+nY4dO76w/XqZXT8JZ/+nL/1VP6QBYtXynlQoUw2N2oBbmYks3zEeYwNTejWaTKl4TwZ3+IIDBxqxa9cuxowZw7hx4wgICKBZs2YcOnSIGTNmUL169fvGvfe9Klibt0BUVBT9+/fHycmJ8uXLc/z48cKfsW+//ZZmzZpJ8yUhhPivyc+H336DJ7jBXbNsWaY1aUKPn3/GuXRp2teowbWMDCpaWWFtakp3V1e+PHqU7m5ueFWpwpjQUAwmTWJLWBj169fH0NAQABMTE0B/LaFWq1+ac8zLsRdCCFFMLv0BpzeARYWiJaAAbweMIz7pL9JKncfMwoTDWy6hytaX5uTn55OQkEDt2rUBMDIy4q+//mLbtm34+vry559/FktDnIKAJy4ujszMTEA///b3339n7NixDBs2DH9/f7Zu3Vqs5T0vC0WB87+CaWl9E6VHGd4yiA6zyjD1h66Us6zAwDe+oIyFHWblFRL3lsHNzZ0ZM2ZgamrKoEGDOHnyJOPHjycsLKwwWC0o872XVqtFpVKh0Wi4ffs2cXFxAERERNC/f3/Wr1/PtWvX2LNnD5cuXWLKlCn88ssvZGRkoNFo5H0UQoj/krNnITVVv77qE6jr4MBHDRrw9YkT/BAZSZ3y5QmLjSVfp6O7qys6ReH3CxdoV7Mmbzo7c+nwYYKCgpg7d25hoFpAo9G8VMuoScAqhHhl5WbC6e/0jXU0hg/epo33AKZufJMvQrtyKGYTQfOWsHjxYgwMDKhRowaxsbEEBAQQEhLCt99+yxtvvAGA2WPMOXkW/h4AHT9+nICAAHr16sWwYcM4d+4cCxYsIC4ujqysLIyNjfHw8AAoluZPL5v0K5AUBSbW/7ytT5XmGGqMmNh5Pf0af4qZsSUARmYqzlw6RkLsTZo0acKkSZMIDg7Gw8ODJk2aYGtrS0REBHD3hsKNGzfo0aMHOTk5aDQaUlNTGTt2LK6urvz2229otVqSk5OZOHEiPj4+uLi4sH37dqpXr06FChXw8/Pjww8/fG7fFyGEEMXk+HH93NV/oY+nJ709PJhz8CB7YmNpULEi++Li0KjVtKtenbkHD2JlYoJ3pUrkX7uGu7s78OCbqS8TCViFEK+sq+Ggy9Ovr/kwfV//hKspF/Go2IhN427QrsoENv2wmf79++Pt7c2ECRMYOnQoa9as4a233nrui2oXKDi5FKUHnqcAAB5+SURBVLxeXl4eOp2OtWvXMmDAAMLCwnB0dGTevHkYGhrSrVs3xo8fD0DVqlWpVKkSP//88wvZ15dZTJj+ZsXj3EhWqVQMazGfb8I+LXzsemoce87+jKWlBZXN/AvLem1tbQvnlx4/fhwvLy/g7vtma2vLokWLCsf56aefuHXrFhEREQwbNgyNRoOlpSUNGzZk1apVfPbZZ1haWvL777+TmZnJvHnzCkvNX6a74EIIIZ7SuXNgYfGvn96hZk3e9/Xl4127OBgfj92dG+jDfHz45s5UoJoODtgqCudPngR4Ydcu/5bMYRVCvLIu7QBTm0dvY2RgTFO3t4lJjESlAn/nDrRs5M2vpxei1Wpxc3PDzc3txezwPe5tyLN27VoGDRpEs2bNCAsLo2nTpgAMHjyYVatWsX37dj755BM8PDwICgqibNmydOrUSdbwBBIjHy+7WuAN93dYvn0crb37szViFZHxB2hfbyj1vTpga/Q5KhUUTPkpmBN0b0B570VBQkICnTt35q+//iI+Ph5TU1OCgoKwt7fHyMgIFxcX3N3d+eCDDxg+fDgrVqwgIyODr7/+mlq1alGrVq1n8j0QQgjxksjPh6tXoUKFpxqmp4cHRhoNI7ZuRXdn2kgpQ0NK3Tkv+VWoQH0A6yc4ARYjybAKIV5ZWclgYPrP2/Vr8jm/HQ0mNSsJjTFY4cScOXOoVq3a899JeGA7+W3btuHl5cW+ffs4e/Ysy5YtIzU1lW7dunH8+HEAnJ2diY2NJSMjg8qVK+Pp6cmWLVsAqFWrFpUqVXoh+/8yy8v857mr99KoDXjTfyQffduGyrZuLB90lA4+QzEw0KDoIC+76LJBD5pf2qZNG86dO4erqyvOzs5s3LiR0aNH4+DggKmpKQkJCaxevZrw8HBGjBhB7969CQkJoXfv3uzduxcXF5enPWwhhBAvo9xcfXOFp2h2VHDe6Vq7NldHj+Y1J6f7ttGo1frSohKylrdkWIUQryyVGniMfjU25nYMaT6HPG0Oap2CSvPiSjDvXfIkPz8fAwP9n+3jx4/Trl07Pv30U95991369u1LVFQUXl5ezJgxA29vb/z8/EhMTMT2Tlv8P/74o/D54o5/cU3wVsA43mkwofD/Wp0WtUoNqNAYqAsvFlQqVWF29eLFi1hbWxd+TJkyhQ0bNjBgwADmz59P9+7dmTDh7pjXrl3D0tISc3Nz+vbtS9++fZ/mKIUQQpQUTznNo+C8o1KpUAH5Oh0GDwuAS8iUEsmwCiFeWRYOkJvxeNt2e+1Dylo4oM1VYeHwfPdr/fr1fP/994D+hHP27Fn69evH0KFDCQkJAeDq1atUq1aNnJwcatWqhbu7O2vWrKFZs2b069ePtWvXUr9+fd544w2aNWsGgIGBQeGaakLP2AK0uU/2HPWdVtJanX4tW41ag6JVkZQTh9pAKRKobt68mZkzZzJ16lTOnj0LwLx58wgJCeHmzZt07doVExMTfvzxRwA+//xz3NzcSEtLo3Hjxs/oKIUQQpQIxsag0cAzbIL00GAVnrgTcXGRgFUI8cpyaQY5aY+/vU6rvxnpUPfZ70t6ejo5d0pzoqKi+PLLLwHYvXs3gwYNokmTJgwYMICPP/6YqKgoqlevzsmTJ0lKSgKgSZMmbNq0iejoaHr06MGyZcs4e/YsH374YZF5ky/LmmovCwcfyE75d8/V3Kkl3n5yPUNX+PND9AR2794NwIYNG5g8eTI7d+6ka9eulCpVisjISFJTU7G1taVFixZ8/PHHALz11ltMnz4d0Jdqb9q0ibVr11K5cuWnPj4hhBAliEYDFSvCnWXpnpuCm9dPsNZrcZIrFyHEK6u8BxiZQ076422fngAV/MGk9LPdjx07duDs7MzmzZsB6N+/P2lpady4cQNvb29CQ0Oxs7Nj3Lhx5ObmMnnyZPr378/169eZMWMGX375Jbt376Z8+fJs27YNAIs7HQa1Wq2s0/kITvX104WUf5F41ury+XL7OEKPr6GH5zRWfrUSR0dHAIKCgggPD+fzzz/HxcWFhg0bcuLECaKjowFo27YtwcHB5ObmFpb85ufn06VLlxc2N1oIIcRLqGZNSHuCu+n/RkYGODqC4UPW9HvJSMAqhHhlaYyg7hC4naRfk/VRMq6DiSXU7vpsXjsyMpL0dH2k7OXlRdWqVQkODiY8PBxLS0u8vb2JiIjA0tKS8+fPM3v2bL744gv27t3Ln3/+SWxsLEuXLsXR0ZFjx44xZcoU+vXrR3JyMnB3DsvLtvj3y6ZUGbD3gszEJ39ucsY1TsXtZVKbX6jv3RRHt1JUr14dgPfeew8DAwMyMvQ15x06dECr1bJp0ya2bdtGQkICbm5uHDt2DCMjI0aMGCHzi4UQQoC3t75b8PO82ZySAoGBz2/8Z0wCViHEK83ODfxGQk4qpMZB3u27X1MUyL4Ft2LAxAoaTADTZ9QBfuDAgSxcuJCEhAS0Wi29evXC39+fRYsWoSgKOp2ucL7prl278PHxoX79+pw5cwa1Ws3EiRMxNzdn/Pjx/N///R9Llixh8eLFtG/f/tns4CukelvIz9Z/PEzuA754JTmaija1yEnWUKOjDpWKwvesS5cuZGZmcvz4cbRaLebm5gwbNgxFURg/fnxhSbe/v//zOiwhhBAlkYsLODg8vyxrfr6+C7Gv7/MZ/zmQgFUI8cqz94Q3ZkDNzpCXBanxkHZZ/6+RhT4L+/pUMLN9+tfS3mmkMHfuXFJSUli5ciW2tracPn2aAQMGYGVlxZ49e4iPjy9cnqZy5cpER0fToUMHPv30UxYsWMC8efMKx/zyyy8xNDTk2LFjuLu7P/1OvmKsXaDuQEi/+uCg9fCF31n9xxSuJOvLebU6/XuoaFWcjv0Tj27GVPDVn04LstkmJiZ06tSJn3/+mbQ7Fx3u7u58+umnRERE0Llz5xdwZEIIIUoclQo6dYKkpOeTZb1yBd54A+5MHSoJpP5ICCEAUxuo0RaqttA34dHmgYGJ/vGnqajVarVFmh4VfP7aa69hZGTEgAEDaNOmDWXLlmXbtm1MnDiRkJAQsrOzCQ0N5aOPPqJTp054eHgQEhLC22+/TdmyZYuMPWPGjKc6dqGfywpwdAUYGEOpcqCo8tGoDbC1qkhO/m3OJxzF0aYKapWGrJvgrGqEkYWOg8lrqKnqi6LoOwRnZ2ezadMm+vbtS2BgIPHx8VjfWZxdml4JIYT4R/XqgY8PnDgBFSo8u3Fv3QIbG+jY8dmN+QLImVMIIe6hMdRnUi0d9fMb/22wWtDoqCBAzc/Pv+9rdevWpX///kyaNAkfHx+2b9+OnZ0d7du3JzU1lfPnz3Pu3DkAqlSpwvvvv0/ZsmXR6XQoilIkEBZPz6k+BE4GOw99hj3jsgE5aXA29hi3b2dyLi6C+KgkUmOhlEMuDSbA57Mms3r1Kn755RdUKhXp6enMnDmT/fv3Y25uzpYtW/Dw8CjuQxNCCFGSqFTQs6d+2Zk7qwE8tdu39QHr4MFgavpsxnxBVCWhe2S9evWU8PDw4t4NIYT4RzqdrkgW7dy5cwwbNgx3d3c6d+5Mo0aN7ttm8ODBZGdnk5WVxbx583BycmLLli2kp6fz1ltvFRm/IIsnnq2CuacF78vtZDj0SyyjPumDg2V1DDXGnLm2j9HvTqfniFaY2d19H3744QeCg4OxsbEhIiKCwMBAJk+ejJOTU7EdjxBCiP+Ay5fhiy/0n5cr9+/HyciAxEQYPlyfuX1JqVSqo4qi1LvvcQlYhRDi2du1axfZ2dlcu3aN3NxcSpUqxbJlywgNDcXS0hJFUVAUBbVaTVRUFFOnTmXDhg3ExMRIoPOUCk5rjxPXF5wDC4LPgs7NFhYWhIaGMnPmTHbt2gXAxIkTMTExYfjw4VhbWxcp97516xaRkZFUr16dck9zUSGEEELc6+pVWLQIEhL05cFP0lFeUfRzVg0NYdgweMn7XDwsYJU5rEII8S/9PdgBCAkJYefOnYSHh5ORkYGjo2Ph+qrbt28nKCiIjz/+GJ1OVxjsVKtWjblz5zJ06NAiwapkUx9P5g24ehQSz8Cti/olilRqKFUWbKrrS3zL19HPTf27gu9vQkICkyZN4siRI7i5ubF+/XosLS1xdHQkLi6OihUr4uPjw+rVqzlz5gwBAQFFsuSlS5cmICDgRR2yEEKIV4WDA0ydClu2wG+/6e/G2tqC8QNOagXy8+HGDcjN1c+H7dkTSj/jReRfIJnDKoQQ/4JWq0WlUhUJKFNSUhg8eDB5eXmEhYUxatQoypUrR2RkJAD9+vVj8+bN9zViAihfvjwNGjQo8pgEq4+WcQ0OLYDt4yFyI6TGgrEVWFUCyzs9KhKOQvgy+P0DOP8b5N7WFj5fURS0Wi3r1q1j1KhRuLi4cOLECWJjY1mwYAHGxsbY29vzxx9/AODr60tkZCQhISFkZWXJ+yOEEOLFMDaGzp1hxgxo2xZSUyEuDmJj9WXDV6/qM6mxsfrHExLA3x+mTIH33ivRwSpIhlUIIf4VjUZDeno606dPx8bGhmbNmuHp6UmPHj04ePAgAC1btmTnzp1ERERQrVo1GjdujLGxMcuWLWP48OHFfAQll6LApT/g1HpQG4CVkz6jWoQKDEvpPwDycyDyR7h8SEO9IXD84h6qVq2Kg4MDVlZWxMTE0KFDBwCmTZvGxIkTeeuttwgICGDKlCnExMQQHh5O9+7d6dGjB6VKlXqxBy2EEELY2uqXvGnbFq5f1weqV69CTo6+VNjOTp+RtbcvcY2VHkUCViGEeAStVsvixYvZv38/AwcOxM/PD0tLS0JCQpgwYQLdunWjcuXKdO7cmaioKEaMGEFoaCgnTpygTp06+Pr6sn//fry8vHB1dSU4OBhHR8fiPqwSS1HgzI9wbrM+i/qgMt8HMTAGa2fYHR7Ce/U+x65KKQJe96NKlSr06dOHsLAwkpOTyc3NJTAwECsrK/73v/8xZMgQbGxs2LVrF++//z7Nmzd/rscnhBBC/CNDQ/181me55M1LTEqChRACUHSQdF5fPho6GkLeh5Etl2NfzokLZ+Pw9PRkxYoVrFixAgAfHx+2bdtGhw4d+OWXX4iPj2fp0qU4ODjQunVrFi5cCECbNm1Qq9UYGhoCUKtWLSwtLYvtOEu6S7v0wWpp50cHqxM3dODPqK0AaHX6MuDMnDRua64zstlK3qu9ifNnolm1ahW3bt2iYcOGREVFcfz4cQD69OnDypUrycvLo2HDhkyZMkWCVSGEEKIYSMAqhHjlpVyCnRNh73S4dkK/FquxBWgwIj8bmmbPpan5/xHY4A3S0tLIycmhXLlyXLhwgSFDhjBgwAB++eUXgoKCyM7OplevXmzdupUrV65QsWJFlixZQvXq1Yv7MEu89AQ49a0+s6r+hyVoazn4snbv58DducBmxpY0dX+HhOxIxv5UH8MUJ2rWrEVwcDDNmzdHq9USFhYGQLdu3fj1118LbzQIIYQQonhIwCqEeKXdPAd7p0Fepj5rZ14eDExAYwTt/N/F0NCAaN0urp+Es79mY6AyxfhOZ76YmBhq165NYGAg1apVIzo6mg0bNlCzZk1CQ0NxdHQsXN+z4F/x751cp7+Z8DhlwD0bTST+5jnOJxxDrVIXZll1ipZTcfsY0zGYrhVnY5BjxY8//kh+fj4NGjSgdu3a6HQ6FEXB3t7+OR+REEIIIf6JzGEVQryysm7CoflgbKn/eJDOfiNYvmMsbbwG8M3eT3E+X5NartXo1Lkj1tbW5OTkMGjQILKyshg7diz+/v4AeHh4ABQufXLvEijiyaVfhcRIfQfgx9XWeyCrdn3MjB4hgH7dWxPDUhy9uJ26Lm+g1YWTcCmTGjVqEB0dTffu3Z/b/gshhBDi33luV1AqlWqVSqW6oVKpTt/z2FSVSnVFpVIdv/PR+nm9vhBC/JNLu0Gb9/BgFaB7/TEkpsZz9OJ21n9wgQaOvVkatIL33nuPOnXqMHz4cAwMDBg/fjwzZ86kZs2aL2z/XyVXDoNKo19+7nH1eX0Kp+P3cyX5Ahq1QWFpcGe/ERyK2sKcHe9Q27wFwfO+xdPT8zntuRBCCCGexvO85b8GaPmAx+criuJ55yPkOb6+EEI8VH42XNoBZrb/vG0b74GoVGosTEvT2mMQY1uv4erVq0RGRuLr68vSpUtxd3cHpPT3ebkR+egbCw9iZGDC667d+fHQAgA2HV7M8FUBmBiaMaTZbNa+fx6/Sh1Ju/wcdlgIIYQQz8RzKwlWFGWPSqVyfl7jCyHE00i+APm5jzcfsnfgJFpNNyc+6TwVbKuTFlWe79f/hKnF3YY8Op0OtVotpb/PgaKDW5fA/F9MKe3X+DPenGvPgXObcSpbg17/3979x/pV13ccf75aipSCtECHlB+2VmBzOMtWEMKKhSz4Y4QfbiokU7YRcE4XEI2OxQDLkg1RjP8YncxluCGOxBENMRtuAyoGQcBCQfw1KNIVKQxoqY5f9773xzmVu/L9Xtr6vfec9j4fyc33ez/f8z33077yzv2+7zmfc1Z8jDce9tZfvD5rN3jyAVi0fIQTliRJI9PFGtYPJHkPcAfwoap6soM5SJrhnv85bOvZpbvvtge/f+wFrH/ivzhkv/Zqvy/M+UWTCq5RnUpjz8P42MtfGXiQffc6gAtP+VuWvuoN/NpBx7zk9dlz4JlNI5ikJEmaEtPdsH4W+Cug2scrgD8etGGS84DzAA499NDpmp+kGSLb2V++7+RPTnhz836b1OmxPetWBznlt86d9HVjlCSpv6b113RVPVpVY1U1DlwJvPTP3S9u+/mqWl5VyxcuXDh9k5Q0I+wxn+ZPZ9thvMYZe645Krf7vCmZlgaYNQfm7Aljz41+388/s23rmCVJUjemtWFNMnEF0hnAvcO2laSptOA1MHd/ePbpbX/PrMxi86Ow5KRm7aOmRwL7Lt2+rLZ532zfrXIkSdL0msrb2lwD3AockWRdknOAy5OsSXIPcCLwwan6+ZI0mcyCw97W3It1W42PQY3BoSumbl4a7FXL4PnNo93n+FjzuI+rTiRJ6q2pvErwWQOGvzBVP0+SttfBx8LaG+Hp9bD3osm3rXF46iF47Vtg7x24Wq1+OYuWw5qrYfyF0R3d/tkGOOiNsMc+o9mfJEkaPS81IWnGmjMXjr0A9lwIT60dvkbyuc3NbVVefQIc+a5pnaJar3glLD4RNq0fzf7GX4CxZ2HpyaPZnyRJmhquwpI0o83dF1ZcBD+8Hh68sWliZu8OmQ3j7e1U9twPjjqnaVi39+rCGp1fPQPW3wHPbPzlj4puWtecEr5gyWjmJkmSpoYNq6QZb/e94Mgz4YjT4KerYeNP4IX/hd33hoWvg/2PsFHtg93nwdF/Crf8TXNa8I5eqXnTOpi/BI44dbTzkyRJo2fDKkmtOXPhkOOaL/XTfofDsRfCtz8Nz/8c5m3HXc/Gx2DTw02zetwHYbc9pm6ekiRpNDxmIEnaqRzwelh5SXM695MPvPztbmocNj/aHDlfejIc/5FmTawkSeo/j7BKknY6+xwKb7oYHv4W/PDrsPEhKJqjprPnQFVzWveWW9cceFSzZnXf13Y6bUmStJ1sWCVJO6XZc2DxyuZiWE+thY3r4MkfwbObIYG9FjUXVZq/uLlwliRJ2vnYsEqSdmqZBQte03wtPqHr2UiSpFFyDaskSZIkqZdsWCVJkiRJvWTDKkmSJEnqJRtWSZIkSVIv2bBKkiRJknrJhlWSJEmS1Es2rJIkSZKkXrJhlSRJkiT1kg2rJEmSJKmXbFglSZIkSb1kwypJkiRJ6iUbVkmSJElSL9mwSpIkSZJ6yYZVkiRJktRLNqySJEmSpF6yYZUkSZIk9ZINqyRJkiSpl2xYJUmSJEm9ZMMqSZIkSeolG1ZJkiRJUi/ZsEqSJEmSesmGVZIkSZLUS6mqrufwspI8BjzU8TT2Bx7veA76/8ykn8ylf8ykf8ykn8ylf8ykf8ykn3aFXF5dVQu3HtwpGtY+SHJHVS3veh56kZn0k7n0j5n0j5n0k7n0j5n0j5n0066ci6cES5IkSZJ6yYZVkiRJktRLNqzb7vNdT0AvYSb9ZC79Yyb9Yyb9ZC79Yyb9Yyb9tMvm4hpWSZIkSVIveYRVkiRJktRLNqwDJFmbZE2S1UnuaMf2TfKNJD9qHxd0Pc9dXZK/T7Ihyb0TxobmkOSiJD9O8oMkb+5m1ru2IZlcmuS/23pZneRtE14zkymW5JAkNya5P8l9Sc5vx62VDk2Si/XSkSR7JLk9yd1tJn/ZjlsrHZkkE+ukY0lmJ/lukuvb762Tjg3IZMbUiacED5BkLbC8qh6fMHY58ERVXZbkz4EFVfXRruY4EyQ5AdgMfLGqjmzHBuaQ5HXANcAxwCLg34HDq2qso+nvkoZkcimwuao+udW2ZjINkhwIHFhVdyXZG7gTOB34Q6yVzkySyzuxXjqRJMC8qtqcZA5wC3A+8HaslU5MkslbsE46leRCYDnwyqo6xc9f3RuQyaXMkDrxCOu2Ow24qn1+Fc0HD02hqloFPLHV8LAcTgO+XFXPVtWDwI9pClUjNCSTYcxkGlTVI1V1V/v8aeB+4CCslU5Nkssw5jLFqrG5/XZO+1VYK52ZJJNhzGQaJDkY+F3g7yYMWycdGpLJMLtcJjasgxVwQ5I7k5zXjh1QVY9A80EE+JXOZjezDcvhIODhCdutY/IPhxqtDyS5J80pw1tOEzKTaZZkMXAUcBvWSm9slQtYL51pT6lbDWwAvlFV1krHhmQC1kmXPg18BBifMGaddGtQJjBD6sSGdbDjq+o3gbcC729Pg1S/ZcCY57tPj88CS4FlwCPAFe24mUyjJHsBXwEuqKpNk206YMxcpsiAXKyXDlXVWFUtAw4Gjkly5CSbm8k0GJKJddKRJKcAG6rqzm19y4AxMxmhSTKZMXViwzpAVa1vHzcA19EcRn+0XZO0ZW3Shu5mOKMNy2EdcMiE7Q4G1k/z3Gakqnq0/cAxDlzJi6edmMk0add+fQW4uqr+pR22Vjo2KBfrpR+q6ingJpq1ktZKD0zMxDrp1PHAqe31XL4MnJTkn7BOujQwk5lUJzasW0kyr71ABknmAScD9wJfA85uNzsb+Go3M5zxhuXwNeDMJK9IsgQ4DLi9g/nNOFt+gbXOoKkXMJNp0V605AvA/VX1qQkvWSsdGpaL9dKdJAuTzG+fzwV+B/g+1kpnhmVinXSnqi6qqoOrajFwJvCfVfUHWCedGZbJTKqT3bqeQA8dAFzXfNZgN+BLVfWvSb4DXJvkHOAnwDs6nOOMkOQaYCWwf5J1wCXAZQzIoaruS3It8D3gBeD9O/PV0PpqSCYrkyyjOd1kLfBeMJNpdDzwbmBNuw4M4C+wVro2LJezrJfOHAhclWQ2zR/sr62q65PcirXSlWGZ/KN10jv+Tumfy2dKnXhbG0mSJElSL3lKsCRJkiSpl2xYJUmSJEm9ZMMqSZIkSeolG1ZJkiRJUi/ZsEqSJEmSesmGVZKkHZBkcZJ7X35LSZK0o2xYJUmaZkm8D7okSdvAhlWSpB03O8mVSe5LckOSuUmWJfl2knuSXJdkAUCSm5L8dZKbgfOTvCPJvUnuTrKq3WZ2kk8k+U77/ve24yuTrGr3970kn0syq33trCRr2n19vB17Z5JPtc/PT/JA+3xpkls6+H+SJGmH2LBKkrTjDgM+U1W/DjwF/B7wReCjVfUbwBrgkgnbz6+qN1XVFcDFwJur6g3Aqe3r5wAbq+po4Gjg3CRL2teOAT4EvB5YCrw9ySLg48BJwDLg6CSnA6uAFe37VgD/k+Qg4LeBb476P0GSpKliwypJ0o57sKpWt8/vpGkk51fVze3YVcAJE7b/5wnPvwX8Q5Jzgdnt2MnAe5KsBm4D9qNpigFur6oHqmoMuIam+TwauKmqHquqF4CrgROq6qfAXkn2Bg4BvtTOYwU2rJKknYgNqyRJO+7ZCc/HgPkvs/3Ptjypqj8BPkbTUK5Osh8Q4M+qaln7taSqbtjylq32Ve32w9wK/BHwA5omdQVwHE2jLEnSTsGGVZKk0dkIPJlky+m47wZuHrRhkqVVdVtVXQw8TtO4/hvwviRz2m0OTzKvfcsxSZa0a1ffBdxCcxT2TUn2TzIbOGvCz1sFfLh9/C5wIvBsVW0c7T9ZkqSp41UKJUkarbOBzyXZE3iA5ijnIJ9IchjNUdL/AO4G7gEWA3clCfAYcHq7/a3AZTRrWFcB11XVeJKLgBvb/Xy9qr7abv9NmiZ4VVWNJXkY+P5I/6WSJE2xVG19hpEkSeqTJCuBD1fVKV3PRZKk6eQpwZIkSZKkXvIIqyRJkiSplzzCKkmSJEnqJRtWSZIkSVIv2bBKkiRJknrJhlWSJEmS1Es2rJIkSZKkXrJhlSRJkiT10v8Bx+8dV6RZfdAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.cm as cm\n",
    "n_clusters = max(agglom.labels_)+1\n",
    "colors = cm.rainbow(np.linspace(0, 1, n_clusters))\n",
    "cluster_labels = list(range(0, n_clusters))\n",
    "\n",
    "# Create a figure of size 6 inches by 4 inches.\n",
    "plt.figure(figsize=(16,14))\n",
    "\n",
    "for color, label in zip(colors, cluster_labels):\n",
    "    subset = pdf[pdf.cluster_ == label]\n",
    "    for i in subset.index:\n",
    "            plt.text(subset.horsepow[i], subset.mpg[i],str(subset['model'][i]), rotation=25) \n",
    "    plt.scatter(subset.horsepow, subset.mpg, s= subset.price*10, c=color, label='cluster'+str(label),alpha=0.5)\n",
    "#    plt.scatter(subset.horsepow, subset.mpg)\n",
    "plt.legend()\n",
    "plt.title('Clusters')\n",
    "plt.xlabel('horsepow')\n",
    "plt.ylabel('mpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we are seeing the distribution of each cluster using the scatter plot, but it is not very clear where is the centroid of each cluster. Moreover, there are 2 types of vehicles in our dataset, \"truck\" (value of 1 in the type column) and \"car\" (value of 1 in the type column). So, we use them to distinguish the classes, and summarize the cluster. First we count the number of cases in each group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cluster_  type\n",
       "0         1.0      6\n",
       "1         0.0     47\n",
       "          1.0      5\n",
       "2         0.0     27\n",
       "          1.0     11\n",
       "3         0.0     10\n",
       "          1.0      7\n",
       "4         0.0      1\n",
       "5         0.0      3\n",
       "Name: cluster_, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf.groupby(['cluster_','type'])['cluster_'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can look at the characterestics of each cluster:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "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></th>\n",
       "      <th>horsepow</th>\n",
       "      <th>engine_s</th>\n",
       "      <th>mpg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_</th>\n",
       "      <th>type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>1.0</th>\n",
       "      <td>211.666667</td>\n",
       "      <td>4.483333</td>\n",
       "      <td>16.166667</td>\n",
       "      <td>29.024667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0.0</th>\n",
       "      <td>146.531915</td>\n",
       "      <td>2.246809</td>\n",
       "      <td>27.021277</td>\n",
       "      <td>20.306128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>145.000000</td>\n",
       "      <td>2.580000</td>\n",
       "      <td>22.200000</td>\n",
       "      <td>17.009200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>0.0</th>\n",
       "      <td>203.111111</td>\n",
       "      <td>3.303704</td>\n",
       "      <td>24.214815</td>\n",
       "      <td>27.750593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>182.090909</td>\n",
       "      <td>3.345455</td>\n",
       "      <td>20.181818</td>\n",
       "      <td>26.265364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3</th>\n",
       "      <th>0.0</th>\n",
       "      <td>256.500000</td>\n",
       "      <td>4.410000</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>42.870400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>160.571429</td>\n",
       "      <td>3.071429</td>\n",
       "      <td>21.428571</td>\n",
       "      <td>21.527714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>0.0</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>9.235000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>0.0</th>\n",
       "      <td>365.666667</td>\n",
       "      <td>6.233333</td>\n",
       "      <td>19.333333</td>\n",
       "      <td>66.010000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 horsepow  engine_s        mpg      price\n",
       "cluster_ type                                            \n",
       "0        1.0   211.666667  4.483333  16.166667  29.024667\n",
       "1        0.0   146.531915  2.246809  27.021277  20.306128\n",
       "         1.0   145.000000  2.580000  22.200000  17.009200\n",
       "2        0.0   203.111111  3.303704  24.214815  27.750593\n",
       "         1.0   182.090909  3.345455  20.181818  26.265364\n",
       "3        0.0   256.500000  4.410000  21.500000  42.870400\n",
       "         1.0   160.571429  3.071429  21.428571  21.527714\n",
       "4        0.0    55.000000  1.000000  45.000000   9.235000\n",
       "5        0.0   365.666667  6.233333  19.333333  66.010000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_cars = pdf.groupby(['cluster_','type'])['horsepow','engine_s','mpg','price'].mean()\n",
    "agg_cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "It is obvious that we have 3 main clusters with the majority of vehicles in those.\n",
    "\n",
    "__Cars__:\n",
    "- Cluster 1: with almost high mpg, and low in horsepower.\n",
    "- Cluster 2: with good mpg and horsepower, but higher price than average.\n",
    "- Cluster 3: with low mpg, high horsepower, highest price.\n",
    "    \n",
    "    \n",
    "    \n",
    "__Trucks__:\n",
    "- Cluster 1: with almost highest mpg among trucks, and lowest in horsepower and price.\n",
    "- Cluster 2: with almost low mpg and medium horsepower, but higher price than average.\n",
    "- Cluster 3: with good mpg and horsepower, low price.\n",
    "\n",
    "\n",
    "Please notice that we did not use __type__ , and __price__ of cars in the clustering process, but Hierarchical clustering could forge the clusters and discriminate them with quite high accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n",
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'mpg')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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dQcc/+clPcvPNN9O/f382b95M//79aWpq4tVXX6Vv377tu7MDaurVq9dB5w+3BD7GyN13381HP/rRg8793d/9Hbt37z7o+Lx587jmmmu45JJLKCsrA+DPf/4zP/nJT1raDBo0iI0bN/LnP/+ZkpJT7s0JkiRJStgLF6eo/t80qSPv1XZYqW5QfVGaFy9OceExRrZZs2bRu3dvZsyY0a7rampq+N73vndM+1vdc889LFy4kFdeeYXa2tp2X38qyuqS9RBCf+CdwLeyOc5xt+m/2z47vl+qIXPdIfTp0+eg8HnLLbfwla98BYChQ4e2HP/5z39OdXU1+/bt4/HHH+fKK69k/PjxLF26lG3btgFQXV3NCy+8AGRmyCsqKg76ufnmmwEoLS3lu9/9LgBLly7l6quvbgnYl1xyySHrTafTLF26FIDvfe97vOUtbznirZ9++un079+fxx9/HMjs7L53714mTJjAggULWv7LunXr1pZ7+M1vfnPIuq+55hqAlnbpdJovfOELrTaQGzhwII899hg333wza9euPWJtkiRJUmf79z82sO8Yw/h++9KZfo63Y3kDVIyRdDrNu971LlauXJmlyrqmbD9D/hXg08Dr/3H8eAhhdQhhQQjhzENdGEL4SAihPIRQvn/TsBNG476jt2nHdf369ePKK69k2LBhzJw5E4BzzjmHIUOG8MEPfrBV27e85S1MmzaN4uJibrjhBkpKSrj00kv5whe+wNve9jaKioq49tpreemll9pU0q233srOnTsZPHgw999/P3PmzAFgx44dh53Z7tWrF2vXruVv//ZvWb58Offee+9Rx3n44Yd54IEHKCoq4oorruCvf/0rb3vb25gyZUrL68smT558yFnxQ/nP//xPLrroIi655BLOP//8g76niy++mEceeYT3vve9LRvISZIkSdn2wq40Fds6mMab/XFbmhd3ta2vhQsXUlRUxPDhw5k2bVqrc+PGjaO8vBzI/Ht+YWEhAGvXrm3ZGLqoqIiqqqqDNpyGQ2/EvGnTJoYMGcLtt9/OyJEj2bx5M6NHj+a8887rlHs/VYSj7ah9zB2HcB3wjhjj7SGEccCM5mfIzwF2kHlL378A58UYP3SkvkpKSuL+f4BOCEtnwPb17b/urMEwuW0r9ffu3cub3/xm/vCHP3DGGWcAmXdsl5eX87Wvfa39Y7fTj3/8YzZu3Mj06dMPOte7d2+XoEiSJElAZWUlQ4YMafk877/r+X9/aKSxEzJ5fg5MH5nPpy7rfsR2a9euZdKkSaxYsYKCggKqq6t54IEHWpasjxs3jnnz5lFSUsKOHTsoKSlh06ZN/OM//iOjR49m6tSpNDQ0kEqlePnll7nuuutYs2YNkNn3aenSpXzjG98gxkhpaSmf/vSnGTBgAIMGDeKZZ55h9OjRreo5Wl54/XcGEEJYFWM85Z43zeYz5FcCpSGEdwA9gNNDCItijO/f3yCE8B/Aj7NYQ3YUXpZ5z3h7lq3ndstc1wa/+MUv+NCHPsQnP/nJljB+vF133XWJjCtJkiSdzF7YFTsljAM0pjP9Hc3y5cuZPHlyy9uF2ron1JgxY5g9ezZbtmxh0qRJXHjhhQe1OdxGzAMGDGDgwIEHhXG1T9YCeYzxbuBugANmyN8fQjgvxrh/PfX1wJps1ZA1l06APyxt50Uxc10bXHPNNbz44osHHb/lllu45ZZb2jlu53N2XJIkSTq0XfWduwL51Tb0F2M84puS8vLySKczvyWoq6trOT5lyhQuv/xyfvKTnzBhwgS+9a1vMWjQoIP6PtRGzJs2bTrkhs5qnyTeQ/6vIYT/CSGsBq4CPpFADR1z2htg0BWZWe+2yO2Wad+GV55JkiRJOnmd3r1zX1N2Rhv6Gz9+PEuWLGHnzp1AZpPnAxUWFrJq1SqAls2ZATZu3MigQYOYPn06paWlrF69+qANp4+0EbM67rgE8hjjUzHG65r/Pi3G+OYYY1GMsfSA2fKTy7g7oO+Ao4fy3G6ZduPuOD51SZIkSUrMwNMD+Z2UsvJzMv0dzdChQ7nnnnsYO3Ysw4cP55Of/GSr8zNmzODrX/86V1xxBTt27Gg5vnjxYoYNG0ZxcTHPP/88N99880EbTrdnI+ZPf/rT9O/fn71799K/f39mzZrVofs/FWRtU7fOdMJt6rZfUz08NR82PpP5fOAz5bndgJiZGR93B+S1cTZdkiRJ0knj9RuUvbArzbjv76U+1bpdyImc1q+OXn3r6dm3npzcNOlUDvuqu7Onujt7d/YgpluH7+658Ov3ncaA05NY2Jw9bur2mmxu6tb15XWHaz4Bez8If3oy857xxn2Q3zOzgdulE1ymLkmSJJ1CBp6eQ/HZOfz+pcwz23k9mjhnSA1nXfQqgQg5kJv32qRoqilAGiKB7X8+g5cr30BTXSamjTg7p8uFcbVmIO8Mp70BSm7K/EiSJEk6pd0xohtrduyje//dDLx8GyEnkpN76LavhfPIOUNe4eyLa3jh92dTv7kPd4xwlW1XZyCXJEmSpE409k05XDr2ZZrOqm01G340OblAbmTg5dvIu2Avb33ToKNeo5Ob6x8kSZIkqZPEGPlaw4vkn9e+MH6g3PxI/nl7+FrDi5wMe37p2BnIJUmSJKmTPNVUzTNNr9JAx4J0A2meaXqVp5qqj95YJy0DuSRJkiR1glfSjXy9fgv1pDulv3rSfL1+C6+kG4/eWCclA7kkSZIkdYJljdto6uDM+Os1EVnWuL3d182aNYt58+a1+7qamhrmz5/f7uv27t3LO9/5Ti655BKGDh3KXXfd1e4+TkUGckmSJEnqoMaY5meNO7ISyH/WuJ3G2Dmz7kdzLIF8/3PuM2bM4Pnnn+ePf/wjK1as4Gc/+1k2SuxSDOSSJEmS1EHr03s7OYq/JgIb0vuO2GbhwoUUFRUxfPhwpk2b1urcuHHjKC8vB2DHjh0UFhYCsHbtWkaNGkVxcTFFRUVUVVVx1113sWHDBoqLi5k5cyYAc+fO5bLLLqOoqIj77rsPgE2bNjFkyBBuv/12Ro4cyfbt27nqqqsA6NatGyNHjmTLli2d+C10Tb72TJIkSZI6aENqH6ksRfIUkfWpvVyS2+uQ59euXcvs2bNZsWIFBQUFVFdX88ADDxy13wcffJA777yTqVOn0tDQQCqVYs6cOaxZs4aKigoAysrKqKqqYuXKlcQYKS0t5emnn2bAgAGsW7eOhx566KAZ9ZqaGn70ox9x5513dvzmuzgDuSRJkiR10Mb03g7vrH44DUQ2pvce9vzy5cuZPHkyBQUFAPTt27dN/Y4ZM4bZs2ezZcsWJk2axIUXXnhQm7KyMsrKyhgxYgQAtbW1VFVVMWDAAAYOHMjo0aNbtW9qauLv//7vmT59OoMG+R71o3HJuiRJkiR1UF2Wn/E+Uv8xRkIIhz2fl5dHOp25vq6uruX4lClTWLZsGT179mTChAksX778kH3ffffdVFRUUFFRwfr167n11lsB6NXr4Bn7j3zkI1x44YX80z/9U5vv7VRmIJckSZKkDuoRshutjtT/+PHjWbJkCTt37gSgurr1u8sLCwtZtWoVAEuXLm05vnHjRgYNGsT06dMpLS1l9erV9OnTh927d7e0mTBhAgsWLKC2thaArVu3sm3btkPW8bnPfY5XX32Vr3zlK8d2k6cgl6xLkiRJUgcNyjmNbrxy2GXrPWjkHHZzNrX0ZS95pGkih2pOYxu9eZk+1JF/yGu7ERiUc9phxx46dCj33HMPY8eOJTc3lxEjRrRs3AaZ3c9vvPFGHn74Ya6++uqW44sXL2bRokXk5+dz7rnncu+999K3b1+uvPJKhg0bxsSJE5k7dy6VlZWMGTMGgN69e7No0SJyc3Nb1bBlyxZmz57NJZdcwsiRIwH4+Mc/zoc//OE2fX+nqrB/i/oTWUlJSdy/K6AkSZIknSgqKysZMmQIlalaZu3bwD5aLy0/l10M5y+8kVdJkUM+qVbLlNNAI7nkkmYrZ/Ac5/NXTm/VR09y+HzPwYfd1O1ks/87O1AIYVWMsSShkhLjDLkkSZIkddDgnNM48Cnu7jTxVjbQn1fJJU0OkEfqoOtygO7Nx99EDeezi828gd8wiPrmuBaAC3J6Zv0edPz5DLkkSZIkdVB+yGFifgF5BPqxh5v4I2+ihvzmMN4WOUA+aQbwCjfxR/qxhzwCE/PPIj/Lz6grGf6nKkmSJEmdoDT/bM5mD+9iLT1IkXeMr0HLI9KdFO9iLWezh9L8szq5Up0oDOSSJEmS1Al6hRTX8Tzd6Pgr0ALQjTTX8Ty9wsFL3dU1GMglSZIkqROsrnuKQFOn9plDitV1v+7UPnXiMJBLkiRJUgftTP2F7anNxE6YHT9QmhTbUy+yM/WXTu1XJwYDuSRJkiR10IaGP5Lq5Nnx/VI0saGhol3XzJo1i3nz5rV7rJqaGubPn9/u6wDe/va3M3z4cIYOHcptt91GKuVS+6MxkEuSJElSB9Sn97IjtTWrY+xIbaE+vTerY8CxBfIYI+l0miVLlvDcc8+xZs0atm/fzqOPPpqlKrsOA7kkSZIkdcAr6ZfJyXK0yiGHV9IvH/b8woULKSoqYvjw4UybNq3VuXHjxlFeXg7Ajh07KCwsBGDt2rWMGjWK4uJiioqKqKqq4q677mLDhg0UFxczc+ZMAObOnctll11GUVER9913HwCbNm1iyJAh3H777YwcOZLNmzdz+umnA9DU1ERDQwMhBHRkeUkXIEmSJEkns5rUyzTRmNUxmmikJrWNc/P+5qBza9euZfbs2axYsYKCggKqq6t54IEHjtrngw8+yJ133snUqVNpaGgglUoxZ84c1qxZQ0VFZol8WVkZVVVVrFy5khgjpaWlPP300wwYMIB169bx0EMPtZpRnzBhAitXrmTixIlMnjy5876ALsoZckmSJEnqgF3pncdpnB2HPL58+XImT55MQUEBAH379m1Tf2PGjOGLX/wiX/7yl3nhhRfo2bPnQW3KysooKytjxIgRjBw5kueff56qqioABg4cyOjRo1u1f/LJJ3nppZeor69n+fLl7bm9U5KBXJIkSZI6IBWPz+ZlhxsnxnjE5eF5eXmk05nd3+vq6lqOT5kyhWXLltGzZ08mTJhwyAAdY+Tuu++moqKCiooK1q9fz6233gpAr169Djlejx49KC0t5YknnmjzvZ2qDOSSJEmS1AG5ITfRccaPH8+SJUvYuTMzU19dXd3qfGFhIatWrQJg6dKlLcc3btzIoEGDmD59OqWlpaxevZo+ffqwe/fuljYTJkxgwYIF1NbWArB161a2bdt2UA21tbW89NJLQOYZ8p/+9KdccsklHbjbU4PPkEuSJElSB5ye049tqRePwzgFhzw+dOhQ7rnnHsaOHUtubi4jRoxo2bgNYMaMGdx44408/PDDXH311S3HFy9ezKJFi8jPz+fcc8/l3nvvpW/fvlx55ZUMGzaMiRMnMnfuXCorKxkzZgwAvXv3ZtGiReTmtv7lwJ49eygtLaW+vp5UKsXVV1/Nbbfd1vlfQhcTYoxJ13BUJSUlcf+ugJIkSZJ0oqisrOTMC3tQUffLrG7slkc+xT3GH3JTt5NNZWUlQ4YMaXUshLAqxliSUEmJccm6JEmSJHXAmTnnkCad1THSpDkz99ysjqHjz0AuSZIkSR3QPec0CnLfmNUxCnL70z0cvAu6Tm4GckmSJEnqoAu6jSA3S1t05ZLHBd2Ks9K3kmUglyRJkqQO6pd7PmflvomcTo5YOeRyVu4A+uWe36n96sTgLuuSJEmS1AmKeozjV3u+R5r6Q57vtq+eAVVbOHfLNvIam2jKz+Ov/c/mxQv709Cz+yGvySWPoh5js1m2EmQglyRJkqRO0C30YHTPd/HMvidIHbDjek5TiqLfreW8F16GALmp1zaA61NTy4X/s5GXBp7D6jFDSR/wOrFc8hnd8110Cz2O633o+HHJuiRJkiR1kjNyz+KKnu8mn+7kkEtOU4ornlzJeS++TG463SqMQyac56bTnPfiy1zxXyvJSaXIIZd8unNFz3dzRu5Zx1THrFmzmDdvXruvq6mpYf78+cc05n6lpaUMGzasQ32cKgzkkiRJktSJzsg9i6t6TSqstcwAACAASURBVOHs3IEM/92f6PNq7WtBfE8DbN8DL+3O/LmnAcgE8z6v1jL82T9xdu5Aruo15ZjDeEccSyCPMZJOZ+7vscceo3fv3tkorUtyybokSZIkdbJuoQcl8XLi7/4vYdVmqNoBW16FuibIywECEKEpDT3yoP8Z5F5YwPl/W8sb33o5tHOZ+sKFC5k3bx4hBIqKirjgggtazo0bN4558+ZRUlLCjh07KCkpYdOmTaxdu5YPfvCDNDQ0kE6n+cEPfsD/+T//hw0bNlBcXMy1117L3LlzmTt3LkuWLKG+vp7rr7+ez3/+82zatImJEydy1VVX8eyzz/L444/Tr18/7r//fr75zW9y4403du4X2kUZyCVJkiSpMzU2wuOPw72fIWx4EdJpSMXXzqdSrdvvaYR1O2D9TsKTVbBkJHz+y/Ce90B+/lGHW7t2LbNnz2bFihUUFBRQXV3NAw88cNTrHnzwQe68806mTp1KQ0MDqVSKOXPmsGbNGioqKgAoKyujqqqKlStXEmOktLSUp59+mgEDBrBu3Toeeuihlhn1T3ziE3zqU5/itNNOa/t3dYpzybokSZIkdZbf/x4GD4YPfQie/19oTLUO40eSipn2lf+buX7w4Ex/R7F8+XImT55MQUEBAH379m3TcGPGjOGLX/wiX/7yl3nhhRfo2bPnQW3KysooKytjxIgRjBw5kueff56qqioABg4cyOjRowGoqKhg/fr1XH/99W27VwEGckmSJEnquLo6+MQn4Kqr4MUXoba2Y/3V1mb6ueqqTL91dYdtGmMkhHDY83l5eS3PeNcd0M+UKVNYtmwZPXv2ZMKECSxfvvyQfd99991UVFS0hO5bb70VgF69erW0e/bZZ1m1ahWFhYW85S1v4c9//jPjxo1r712fcgzkkiRJktQR1dUwahR84xuwb1/n9r1vX6bfUaMy4xzC+PHjWbJkCTt37mwup3W7wsJCVq1aBcDSpUtbjm/cuJFBgwYxffp0SktLWb16NX369GH37t0tbSZMmMCCBQuobf4Fw9atW9m2bdtBNXzsYx/jL3/5C5s2beK3v/0tF110EU899VSHbv1U4DPkkiRJknSMcmpq4F3vgs2boaEhO4Ps2wfr1mVC+cqV8Lol6UOHDuWee+5h7Nix5ObmMmLECAoLC1vOz5gxgxtvvJGHH36Yq6++uuX44sWLWbRoEfn5+Zx77rnce++99O3blyuvvJJhw4YxceJE5s6dS2VlJWPGjAGgd+/eLFq0iNwD3peuYxdibOPzDAkqKSmJ5eXlSZchSZIkSa+pq6Nu+HB6bNqUvTB+oG7d4OKLM6G8R/t2YT+RVFZWMmTIkFbHQgirYowlCZWUGJesS5IkSdKxuPtuur3wwvEJ45AZZ/16+Oxnj894yjoDuSRJkiS11+9/D9/4Bjn19cd33H374MEH27T7uk58BnJJkiRJao/GRrjxxs7fwK2t9u3LjN/YmMz46jQGckmSJElqj8cfP+yO58dNdTU88USyNajDDOSSJEmS1B5f/nLH3zPeUbW1mTp0UjOQS5IkSVJb/elPmZ8Twdq1UFmZdBXqAAO5JEmSJLXVD34ATU1JV5HR1ASPPXbIU7NmzWLevHnt7rKmpob58+cfUznjxo3j4osvpri4mOLiYrZt23ZM/ZxKDOSSJEmS1Fa//vWJs5laYyM89VSndnksgTzGSDqdBuCRRx6hoqKCiooKzj777E6trSsykEuSJElSW1VUJF1Ba831LFy4kKKiIoYPH860adNaNRk3bhzl5eUA7Nixg8LCQgDWrl3LqFGjKC4upqioiKqqKu666y42bNhAcXExM2fOBGDu3LlcdtllFBUVcd999wGwadMmhgwZwu23387IkSPZvHnzcbrhriUv6QIkSZIk6aRQXQ27dyddRWu7drH2mWeYPXs2K1asoKCggOrqah544IGjXvrggw9y5513MnXqVBoaGkilUsyZM4c1a9ZQ0Rz0y8rKqKqqYuXKlcQYKS0t5emnn2bAgAGsW7eOhx56qNWM+gc/+EFyc3O54YYb+NznPkcIIWu33hUYyCVJkiSpLV55Bbp1g4aGpCt5TbduLH/ySSZPnkxBQQEAffv2bdOlY8aMYfbs2WzZsoVJkyZx4YUXHtSmrKyMsrIyRowYAUBtbS1VVVUMGDCAgQMHMnr06Ja2jzzyCG984xvZvXs3N9xwAw8//DA333xzJ9xk1+WSdUmSJElqi4YGONFmfEMgNjYecSY6Ly+v5Rnvurq6luNTpkxh2bJl9OzZkwkTJrB8+fKDro0xcvfdd7c8F75+/XpuvfVWAHr16tWq7Rvf+EYA+vTpw5QpU1i5cmWHb6+rM5BLkiRJUlt06wYxJl1FazEy/q1vZcmSJezcuROA6urqVk0KCwtZtWoVAEuXLm05vnHjRgYNGsT06dMpLS1l9erV9OnTh90HLMufMGECCxYsoLb5vetbt2495O7pTU1N7NixA4DGxkZ+/OMfM2zYsM691y7IJeuSJEmS1BZnnnliLVcHaGhg6KhR3HPPPYwdO5bc3FxGjBjRsnEbwIwZM7jxxht5+OGHufrqq1uOL168mEWLFpGfn8+5557LvffeS9++fbnyyisZNmwYEydOZO7cuVRWVjJmzBgAevfuzaJFi8jNzW1VRn19PRMmTKCxsZFUKsU111zDP/zDPxyXr+BkFuKJ9hueQygpKYn7dwWUJEmSpMQUFEDzTPQJoaAAtm9Puop2qaysZMiQIa2OhRBWxRhLEiopMS5ZlyRJkqS2Ki5OuoLWTrR61C4GckmSJElqq7FjIT8/6Soy8vNh3Likq1AHGMglSZIkqa1uuAHyTpCtuPLyYNKkpKtol5PhkenjyUAuSZIkSW116aWZnxPB0KHwumexT2QxRnbu3EmPHj2SLuWEcYL8akeSJEmSThKf+Qx86EPQ/CqwJKROO42Xpk5ld2VlYjUcix49etC/f/+kyzhhuMu6JEmSJLVHYyMMHgwvvphcDQMGwPr1J87z7B3kLuuSJEmSpKPLz4clS6Bnz2TG79kTHn20y4TxU5mBXJIkSZLa6/LL4aMfPf6hvGdPuO02GDXq+I6rrDCQS5IkSdKx+NKXMkvXu3U7PuN165YZ74tfPD7jKesM5JIkSZJ0LHr0gKeegje9KfuhvFu3zHPjv/51Zlx1CQZySZIkSTpWffvCypVw8cXZW77es2em/5Ur4cwzszOGEmEglyRJkqSO2B/Kb7ut80P5/mfGDeNdkoFckiRJkjqqRw+4/3741a8yS8t79+5Yf336ZPr51a8y/bpMvUsykEuSJElSZ7n88sz7wR96CEpKMjPcbX09WX5+pn1JCSxYkOnn8suzW68SlZd0AZIkSZLUpeTnw+TJmZ8//Ql++MPM5m8VFbBrV2aDthAgRmhogNNPh+JiGDcOJk2CIUOSvgMdJwZySZIkScqWSy/N/NxzT+ZzdTXU1EB9PXTvDm94Q+YZdJ2Ssh7IQwi5QDmwNcZ4XQihL7AYKAQ2ATfGGF/Jdh2SJEmSlLi+fQ3ganE8niG/E6g84PNdwC9jjBcCv2z+LEmSJEnSKSWrgTyE0B94J/CtAw6/G/hu89+/C7wnmzVIkiRJknQiyvYM+VeATwPpA46dE2N8CaD5z7MPdWEI4SMhhPIQQvn27duzXKYkSZIkScdX1gJ5COE6YFuMcdWxXB9j/GaMsSTGWHLWWWd1cnWSJEmSJCUrm5u6XQmUhhDeAfQATg8hLAJeDiGcF2N8KYRwHrAtizVIkiRJknRCytoMeYzx7hhj/xhjIfA+YHmM8f3AMuADzc0+ADyRrRokSZIkSTpRHY9d1l9vDnBtCKEKuLb5syRJkiRJp5Ssv4ccIMb4FPBU8993AuOPx7iSJEmSJJ2okpghlyRJkiTplGcglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBWQvkIYQeIYSVIYTnQghrQwifbz4+K4SwNYRQ0fzzjmzVIEmSJEnSiSovi33XA1fHGGtDCPnAb0MIP2s+928xxnlZHFuSJEmSpBNa1gJ5jDECtc0f85t/YrbGkyRJkiTpZJLVZ8hDCLkhhApgG/DzGOPvm099PISwOoSwIIRw5mGu/UgIoTyEUL59+/ZslilJkiRJ0nGX1UAeY0zFGIuB/sCoEMIw4OvABUAx8BLwfw9z7TdjjCUxxpKzzjorm2VKkiRJknTcHZdd1mOMNcBTwNtjjC83B/U08B/AqONRgyRJkiRJJ5Js7rJ+VgjhDc1/7wlcAzwfQjjvgGbXA2uyVYMkSZIkSSeqbO6yfh7w3RBCLpngvyTG+OMQwsMhhGIyG7xtAj6axRokSZIkSTohZXOX9dXAiEMcn5atMSVJkiRJOlkcl2fIJUmSJElSawZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEpDXlkYhhEmHOPwq8D8xxm2dW5IkSZIkSV1fmwI5cCswBvhV8+dxwO+Ai0II/xxjfDgLtUmSJEmS1GW1NZCngSExxpcBQgjnAF8HLgeeBgzkkiRJkiS1Q1ufIS/cH8abbQMuijFWA42dX5YkSZIkSV1bW2fIfxNC+DHwaPPnycDTIYReQE1WKpMkSZIkqQtrayC/A5gEvAUIwHeBH8QYI3BVlmqTJEmSJKnLalMgjzHGEMIKoInM8+T/3RzGJUmSJEnSMWjTM+QhhA8DK4HrySxX/10I4UPZLEySJEmSpK6srUvWZwIjYow7AUII/YBngAXZKkySJEmSpK6srbusbwF2H/B5N7C588uRJEmSJOnU0NYZ8q3A70MITzR/LgVWhhA+CRBjvD8bxUmSJEmS1FW1NZBvaP7Zv5HbE81/75ONoiRJkiRJ6uraGsh/CnwWKDzgmhhjLMpGUZIkSZIkdXVtDeSLgBnAGjKvPZMkSZIkSR3Q1kC+Pcb4o6xWIkmSJEnSKaStgfy+EMK3gF8C9fsPxhgfy0pVkiRJkiR1cW0N5B8ELgHyeW3JegQOG8hDCD2Ap4HuzeMsjTHeF0LoCywm8zz6JuDGGOMrx1K8JEmSJEknq7YG8uExxje3s+964OoYY20IIR/4bQjhZ8Ak4JcxxjkhhLuAu4DPtLNvSZIkSZJOajltbPe7EMKl7ek4ZtQ2f8xv/onAu4HvNh//LvCe9vQrSZIkSVJX0NZA/hagIoSwLoSwOoTwPyGE1Ue7KISQG0KoALYBP48x/h44J8b4EkDzn2cf5tqPhBDKQwjl27dvb2OZkiRJkiSdHNq6ZP3tx9J5jDEFFIcQ3gD8MIQwrB3XfhP4JkBJSUk8lvElSZIkSTpRtSmQxxhf6MggMcaaEMJTZIL9yyGE82KML4UQziMzey5JkiRJ0imlrUvW2y2EcFbzzDghhJ7ANcDzwDLgA83NPgA8ka0aJEmSJEk6UbV1yfqxOA/4bgghl0zwXxJj/HEI4VlgSQjhVuBF4L1ZrEGSJEmSpBNS1gJ5jHE1MOIQx3cC47M1riRJkiRJJ4OsLVmXJEmSJEmHZyCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQEGckmSJEmSEmAglyRJkiQpAQZySZIkSZISYCCXJEmSJCkBBnJJkiRJkhJgIJckSZIkKQF5SRcgSdkWY+QPL6dZ/mITz/4lxba9kRCgf58crjw/h7cV5nNRX38/KUmSpOPLQC6pS1v+QhOf+2092/ZG6lOQiq+d21CT4pmtKe4vb+Sivjn869juFJ2Vm1yxkiRJOqU4JSSpS6pPRe74xT7+oayOTbsie5tah/H9GtNQl4LV29O854f7+NLv6onxEA0lSZKkTuYMuaQupz4Ved+P9vHctjR1qbZfV5eCb/1PIy/vjfzbVd0JIWSvSEmSJJ3ynCGX1OXc+9t6ntvevjC+374m+NGGJh5a03jQuZqaGubPn98JFbZffX09N910E4MHD+byyy9n06ZNndb3gw8+yMKFCzutvwPNnDmTSy65hKKiIq6//npqampazn3pS19i8ODBXHzxxTz55JMtx3v37p2VWiRJkk40BnJJXcrvX0rx6Lom6pqOvY99TTD7dw1s3pVudTzJQP7tb3+bM888k/Xr1/OJT3yCz3zmM53Sb1NTE/+fvXuPj6q69///WjOTeyDcDKBRECh3QggBpVxCDQkKKtc2lhiw6veEIx5PgXJEz6MKVg9Y6MUe8Ee/5xiDEhsKUqDYowGqXKRfY0JHBBEJeCNHucVgQu4z+/fHJFNiQggwk+Hyfj4e8wD23rPWZ8IjyX7vtfbas2fPZubMmT5p77uSk5PZv38/+/bto3fv3ixZsgSAjz76iJycHA4cOMCbb77JI488gst1CVdQRERERK5iCuQick35j/9XdUkj499V44IVf69usG3hwoUcOXKEuLg4FixYQHp6Ops2bfLuT0tLY/PmzWRlZTFp0iTuvPNO+vTpw+LFi73HrFmzhuHDhxMXF0dGRkaLQ+imTZuYNWsWANOnT2f79u0XvNc9MjKS+fPnEx8fT1JSEidPngRg7NixPPnkkyQmJvLCCy+waNEili9fDkBhYSHjxo1j8ODBxMfHc+TIEQCWLVvGsGHDiI2N5emnn25RzQApKSk4HJ67o26//XaOHTvm/Tz33XcfISEh3HrrrfTq1Yu8vLwG7z116hQjRozgjTfeaHF/IiIiIlcTBXIRuWZ88a2bD0+6L3xgC9RasP6TWipq/xF6ly5dSs+ePXE6nSxbtoyHH36Yl19+GYAzZ86wZ88eJkyYAEBeXh7Z2dk4nU7WrVtHfn4+Bw8eZO3atbz77rs4nU7sdjvZ2dkApKamEhcX1+hVP5W8qKiIm2++GQCHw0FUVBSnT59u9jOcPXuW+Ph49u7dS2JiYoMLAyUlJezYsYP58+c3eE9aWhpz5szhgw8+YM+ePXTt2pXc3FwOHz5MXl4eTqeTgoICdu7cCcDo0aObrHvbtm2N6snMzOSuu+5q9HkAYmJiKCoq8v77+PHjTJw4kWeeeYaJEyc2+zlFRERErlZa1E1Erhl/+18XNh+uw+YwcOCUm4QuTT8KLTExkTlz5nDixAk2bNjAtGnTvKPBycnJdOzYEYCpU6eye/duHA4HBQUFDBs2DICKigqio6MBWLt2bbO1NDUafqFF52w2G6mpqQDcf//9TJ061buvfvu5SktLKSoqYsqUKQCEhoYCkJubS25uLkOGDAGgrKyMw4cPM2bMGHbt2tVsDfWee+45HA4HaWlpF/w8NTU1JCUlsXLlShITE1vUvoiIiMjVSIFcRK4ZBcddlF/GvePfVeOGD0+5zhvIAdLT08nOziYnJ4fMzEzv9u+GZWMMlmUxa9Ys733U50pNTeXQoUONts+bN4+ZM2cSExPDl19+SUxMDLW1tZw5c4YOHTpc1Oc5t6aIiIhG+883Bd6yLJ544gkyMjIa7Rs9ejSlpaWNti9fvpxx48YBsHr1arZs2cL27du9NdR/nnrHjh3jxhtvBDwzAIYOHcpbb72lQC4iIiLXNE1ZF5FrxvGzvn1+eKULvqn8x7/btGnTKHw+8MAD/Pa3vwVgwIAB3u1bt26luLiYiooKNm7cyMiRI0lKSmL9+vWcOHECgOLiYj7//HPAM0LudDobveoXW7v33ntZvXo1AOvXr+eOO+7whtu+ffs2Wb/b7Wb9+vUAvPbaa4waNarZz9u2bVtiYmLYuHEj4FnZvby8nPHjx5OZmUlZWRngmW5e/xl27drVZN31YfzNN9/k+eefZ/PmzYSHh3v7uvfee8nJyaGqqopPP/2Uw4cPM3z4cMBz4SAzM5OPP/6YpUuXNluziIiIyNVMI+Qics0IOv9A9iWxG8+09XodO3Zk5MiRDBw4kLvuuotly5bRuXNn+vXrx+TJkxu8d9SoUaSnp1NYWMiMGTNISEgA4NlnnyUlJQW3201QUBArV66kW7duF6zloYceIj09nV69etGhQwdycnIAz8Jn5xvZjoiI4MCBAwwdOpSoqKgLTosHePXVV8nIyOCpp54iKCiIdevWkZKSwsGDBxkxYgTgWSxuzZo13un2zXn00UepqqoiOTkZ8CzstmrVKgYMGMCPfvQj+vfvj8PhYOXKldjt//gPtNvt5OTkcM8999C2bVseeeSRC/YlIiIicrUxF1ql90qQkJBg5efnB7oMEbnC/Tq/it/m11Drox9rkUHwqx+Eck/P81+7LC8vZ9CgQezdu5eoqCgAsrKyyM/PZ8WKFb4ppBlbtmzh6NGjPPbYY432RUZGeke1RURERK5kxpgCy7ISAl1Ha9MIuYhcM4ZE2wlz1FBa45v2at0Qe8P57+zZtm0bDz74IPPmzfOG8dZ29913B6RfEREREbl8GiEXkWtGZa3FoKyznPVRIO/ZzrDrx40XPxMRERER37peR8i1qJuIXDNCHYb7+wcR4oN7ycMd8OiQ4MtvSERERETkPBTIReSaMi8hmIigy2vDZqB7lI3pvXVXj4iIiIj4jwK5iFxT2gQbfp8SSuhlZOkwB/w+JRS7zVz4YBERERGRS6RALiLXnJE3OViRFEKoAy4mUjuMZ2X1P94TRs92+vEoIiIiIv6lM04RuSZN6BHE5ilhdGtrCG/BaHm4AwZH2/hrajhDOvv4geYiIiIiIk3QDZIics0a2MnOjvvC+fORWlb8vYbCEjdhDjj34RKVLhja2cacIcEk3WLHGE1TFxEREZHWoUAuIte0ILthau8gpvYOoqzaYv8pNyfK3RhjuCnS0K+jjTCHQriIiIiItD4FchG5bkQGG26/0Q5oSrqIiIiIBJ7uIRcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAAVyERERERERkQBQIBcREREREREJAL8FcmPMzcaYt40xB40xB4wx/1q3fZExpsgY46x7TfBXDSIiIiIiIiJXKocf264F5luWtdcY0wYoMMZsrdv3G8uylvuxbxEREREREZErmt8CuWVZXwFf1f291BhzELjJX/2JiIiIiIiIXE1a5R5yY0x3YAjwXt2mR40x+4wxmcaY9ud5NARmIQAAIABJREFUzz8ZY/KNMfknT55sjTJFREREREREWo2xLMu/HRgTCewAnrMsa4MxpjNwCrCAXwBdLct6sLk2EhISrPz8fL/WKSIi0pyv3VUcdJ3lY9dZvraqcFkWbY2DfvYIvmePoLctHJsxgS5TRETkqmSMKbAsKyHQdbQ2f95DjjEmCHgdyLYsawOAZVnHz9n/X8AWf9YgIiJyqSzLIt/1LWurv+YzdwV2DBW4GxyT5zqDHUOIsXGvI5q7gzsRauwBqlhERESuJn4L5MYYA7wEHLQs69fnbO9ad385wBRgv79qEBERuVTfuGv4bdXnHHSdpdIbwhvPKqvGAiwqLDc5NV+xufYE/xbanYH2Nq1ar4iIiFx9/DlCPhJIBz40xjjrtj0J/NgYE4fnrOYzIMOPNYiIiFy0z1wVPFlxmEpc1F7E+6qxqLZqWVRxhPTgG5kUHO23GkVEROTq589V1ncDTd1M9xd/9SkiInK5jrkrWVjxCeXfmZp+MaqxWFP9vzgwTAy+wYfViYiIyLWkVVZZFxERuRrUWhbPVhxtdJ/4pajC4uXqIj51lfugMhEREbkWKZCLiIjUWVf9Naet6ibuFL80NVg8X/kZrronmpSUlPDiiy/6qPWLU1VVRWpqKr169eK2227js88+81nbq1at4pVXXvFZe+dasGABffv2JTY2lilTplBSUgJAdnY2cXFx3pfNZsPp9NwhFxkZ6ZdaREREfE2BXEREBKi0XGyoOU6Vz+K4Z7GUYquG911ngMAG8pdeeon27dtTWFjI3Llzefzxx33Sbm1tLbNnz2bmzJk+ae+7kpOT2b9/P/v27aN3794sWbIEgLS0NJxOJ06nk1dffZXu3bsTFxfnlxpERET8RYFcREQE2Flbgmly6ZPLU4mb16s9T/xcuHAhR44cIS4ujgULFpCens6mTZu8x6alpbF582aysrKYNGkSd955J3369GHx4sXeY9asWcPw4cOJi4sjIyMDl8vVojo2bdrErFmzAJg+fTrbt2/Hspq/+BAZGcn8+fOJj48nKSmJkydPAjB27FiefPJJEhMTeeGFF1i0aBHLly8HoLCwkHHjxjF48GDi4+M5cuQIAMuWLWPYsGHExsby9NNPt/CrBykpKTgcniVvbr/9do4dO9bomD/84Q/8+Mc/brT91KlTjBgxgjfeeKPF/YmIiLQmBXIRERHg7ZrT5zzezLcK3eVUWC6WLl1Kz549cTqdLFu2jIcffpiXX34ZgDNnzrBnzx4mTJgAQF5eHtnZ2TidTtatW0d+fj4HDx5k7dq1vPvuuzidTux2O9nZ2QCkpqY2mMJd/6qfSl5UVMTNN98MgMPhICoqitOnTzdb99mzZ4mPj2fv3r0kJiY2uDBQUlLCjh07mD9/foP3pKWlMWfOHD744AP27NlD165dyc3N5fDhw+Tl5eF0OikoKGDnzp0AjB49usm6t23b1qiezMxM7rrrrkbb165d2yiQHz9+nIkTJ/LMM88wceLEZj+niIhIoPjzsWciIiJXjU/dFX5rOwQbR90VRHxne2JiInPmzOHEiRNs2LCBadOmeUeDk5OT6dixIwBTp05l9+7dOBwOCgoKGDZsGAAVFRVER3serbZ27dpma2hqNNyY5mcE2Gw2UlNTAbj//vuZOnWqd1/99nOVlpZSVFTElClTAAgNDQUgNzeX3NxchgwZAkBZWRmHDx9mzJgx7Nq1q9ka6j333HM4HA7S0tIabH/vvfcIDw9n4MCB3m01NTUkJSWxcuVKEhMTW9S+iIhIICiQi4jIda/MqvXpvePf5cLiS3clfZvYl56eTnZ2Njk5OWRmZnq3fzcsG2OwLItZs2Z576M+V2pqKocOHWq0fd68ecycOZOYmBi+/PJLYmJiqK2t5cyZM3To0OGiPse5NUVEfPfyQtOhv377E088QUZGRqN9o0ePprS0tNH25cuXM27cOABWr17Nli1b2L59e6OvS05OTqPRcYfDwdChQ3nrrbcUyEVE5IqmQC4iIte9KsuNHWjZ3dgXz1XXR5s2bRqFzwceeIDhw4fTpUsXBgwY4N2+detWiouLCQsLY+PGjWRmZhIeHs6kSZOYO3cu0dHRFBcXU1paSrdu3S44Qn7vvfeyevVqRowYwfr167njjju84bZv3758/PHHjd7jdrtZv3499913H6+99hqjRo1qto+2bdsSExPDxo0bmTx5MlVVVbhcLsaPH8/Pf/5z0tLSiIyMpKioiKCgIKKjoy84Qv7mm2/y/PPPs2PHDsLDwxvVt27dOu/093rGGDIzM/nhD3/I0qVLWbhwYbN9iIiIBIoCuYiIXPeCjM2P4+OeBVscGDp27MjIkSMZOHAgd911F8uWLaNz587069ePyZMnN3jPqFGjSE9Pp7CwkBkzZpCQkADAs88+S0pKCm63m6CgIFauXEm3bt0uWMNDDz1Eeno6vXr1okOHDuTk5ACehc/ON7IdERHBgQMHGDp0KFFRURcM/QCvvvoqGRkZPPXUUwQFBbFu3TpSUlI4ePAgI0aMADyLxa1Zs8Y73b45jz76KFVVVSQnJwOehd1WrVoFwM6dO4mJiaFHjx6N3me328nJyeGee+6hbdu2PPLIIxfsS0REpLWZC62weiVISEiw8vPzA12GiIhcoyzL4odnP8B3TyBvKBwbj4feyhBH20b7ysvLGTRoEHv37iUqKgqArKws8vPzWbFihV/qOdeWLVs4evQojz32WKN9kZGRlJWV+b0GERERY0yBZVkJga6jtWmEXERErnvGGG6xhVLop4XdqrHoaQ9vtH3btm08+OCDzJs3zxvGW9vdd98dkH5FREREI+QiIiIArK/6mpyar/0ySn6jCWFVRH+ftysiInKtuF5HyPUcchERESAluJNfJqyHYmNqcGc/tCwiIiJXOwVyERERoK1xMMbRnmCafzb3xQrCkOho79M2RURE5NqgQC4iIlLn/4TEEOrDX40hGOaHdifE6NetiIiINKYzBBERkTrhxs7jobf6ZJQ8BMMdjg7EN7GyuoiIiAgokIuIiDQwyNGGfwu9lZDLCOUhGL7vaEdGyM0+rExERESuNQrkIiIi3zHcEcV/hPXmBhN8UaPlNjxhfFbwTfw0pBs249v70UVEROTaoueQi4iINOF79nBWhffj9erjbK45iQuLStxNrsQegsENJNjb8pOQm+hiC2ntckVEROQqpEAuIiJyHkHGxn0hXZke3IUC17d86CrlgKuMYqsGtwXhxsb3bBEMdETyfUc72hr9WhUREZGW05mDiIjIBTiM4TZHFLc5ogJdioiIiFxDdA+5iIiIiIiISAAokIuIiIiIiIgEgAK5iIiIiIiISAAokIuIiIiIiIgEgAK5iIiIiIiISAAokIuIiIiIiIgEgAK5iIiIiIiISAAokIuIiIiIiIgEgAK5iIiIiIiISAAokIuIiIiIiIgEgAK5iIiIiIiISAA4Al2AiIg/fFNp8YeDNeR+Vss3VRYA7UMMd97q4L5+QbQLMQGuUERERESudwrkInJNOVTs4rcF1bz5qQsbUOE6d6/FvpPVPJ9XzV232vnp0BB6d9BEIREREREJDJ2Jisg1461Pa5nwegV/PuKiyvXdMO5R6YIqF2w+4uKu18vZ9nlt6xcqIiIiIoICuYhcI7Z+Vss/b62kohbc1oWPd1tQUQv/lFvJX88TyktKSnjxxRd9XGnL7Ny5k/j4eBwOB+vXr/dp26tWreKVV17xaZv11q1bx4ABA7DZbOTn53u3Z2dnExcX533ZbDacTicAkZGRfqlFRERE5EqnQC4iV72jJW7+eWsllU2MiF9IZV0o/+yMu9G+QAbyW265haysLGbMmOHTdmtra5k9ezYzZ870abv1Bg4cyIYNGxgzZkyD7WlpaTidTpxOJ6+++irdu3cnLi7OLzWIiIiIXC0UyEXkqveis5qqSwjj9apd8PsPqhttX7hwIUeOHCEuLo4FCxaQnp7Opk2bvPvT0tLYvHkzWVlZTJo0iTvvvJM+ffqwePFi7zFr1qxh+PDhxMXFkZGRgcvVskK7d+9ObGwsNlvLf0xHRkYyf/584uPjSUpK4uTJkwCMHTuWJ598ksTERF544QUWLVrE8uXLASgsLGTcuHEMHjyY+Ph4jhw5AsCyZcsYNmwYsbGxPP300y2uoV+/fvTp06fZY/7whz/w4x//uNH2U6dOMWLECN54440W9yciIiJyNVMgF5Gr2tkaiw2f1OJqwTT186m14I+HaimvadjI0qVL6dmzJ06nk2XLlvHwww/z8ssvA3DmzBn27NnDhAkTAMjLyyM7Oxun08m6devIz8/n4MGDrF27lnfffRen04ndbic7OxuA1NTUBlO461+XM5X87NmzxMfHs3fvXhITExtcGCgpKWHHjh3Mnz+/wXvS0tKYM2cOH3zwAXv27KFr167k5uZy+PBh8vLycDqdFBQUsHPnTgBGjx7dZN3btm1rcZ1r165tFMiPHz/OxIkTeeaZZ5g4ceIlfw1EAs1luShxneRk7Zccr/2cU7VFVLrPBrosERG5QmmVdRG5qr3+SQ02HzzBzAAbC2uZ0S/ovMckJiYyZ84cTpw4wYYNG5g2bRoOh+fHaHJyMh07dgRg6tSp7N69G4fDQUFBAcOGDQOgoqKC6OhowBNKfc1ms5GamgrA/fffz9SpU7376refq7S0lKKiIqZMmQJAaGgoALm5ueTm5jJkyBAAysrKOHz4MGPGjGHXrl2XVeN7771HeHg4AwcO9G6rqakhKSmJlStXkpiYeFntiwTCWfe3fFbzIcdrP6PCKsOOHc9PFQ83LmzYaWe/ge5Bg4i2d8NmNCYiIiIK5CJylXvnCxflPlgovbwW3vmi+UAOkJ6eTnZ2Njk5OWRmZnq3G9PwqoAxBsuymDVrFkuWLGnUTmpqKocOHWq0fd68eT67v/vcmiIiIhrtt6ympxVYlsUTTzxBRkZGo32jR4+mtLS00fbly5czbty4C9aUk5PTaHTc4XAwdOhQ3nrrLQVyuap86zrN/qpdlLhPYGFh4VmLopbGa1K4cXHKVcQ3rhPYsPG94KHcGjQIo2AuInJdUyAXkataceVlzFW/QFtt2rRpFD4feOABhg8fTpcuXRgwYIB3+9atWykuLiYsLIyNGzeSmZlJeHg4kyZNYu7cuURHR1NcXExpaSndunW7rBHyvn378vHHHzfa7na7Wb9+Pffddx+vvfYao0aNaradtm3bEhMTw8aNG5k8eTJVVVW4XC7Gjx/Pz3/+c9LS0oiMjKSoqIigoCCio6Mva4Tc7Xazbt067/T3esYYMjMz+eEPf8jSpUtZuHDhJfch0hrclovD1Xs5UvN33FzcAhYuanABh6rzOFZ7iPjQFCJt7fxTqIiIXPF0WVZErmq+mK5+vrY6duzIyJEjGThwIAsWLACgc+fO9OvXj5/85CcNjh01ahTp6enExcUxbdo0EhIS6N+/P88++ywpKSnExsaSnJzMV1991aJa3n//fWJiYli3bh0ZGRne8H/q1KnzjmxHRERw4MABhg4dyl//+leeeuqpC/bz6quv8rvf/Y7Y2Fi+//3v8/XXX5OSksKMGTMYMWIEgwYNYvr06U2OijflT3/6EzExMfztb39j4sSJjB8/3rtv586dxMTE0KNHj0bvs9vt5OTk8PbbbwdsZXuRlqixqnm3YiNHa5wXHcbP5aKWb93F7Cpfx/Haz31YoYiIXE3M+U7sriQJCQnWuc+zFRGp90+5FWw5chlLrJ9jyvfsrBwX1uwx5eXlDBo0iL179xIVFQVAVlYW+fn5rFixwid1NGfLli0cPXqUxx57rNG+yMhIysrK/F6DyPWq1qrh3YoNnHWX4G5iWvqlsuFgaGgKnR3dfNamiMjVxhhTYFlWQqDraG2asi4iV7W7ezh4+wsXZ2sur52IIJjYo/n7x7dt28aDDz7IvHnzvGH8UliWxTfurzlR+wXFrq+otDwrMIeZSDrab+QGxy20s0U3ui8d4O67777kfkXk0lmWRUHlW5x1n/FpGAdwU8veylxGhU2jjb2DT9sWEZErm0bIReSqVu2yGJR1ltLGjxG/KFEh8OEDETh8OQe+CV/VHuWjqj1UWxW4cAHf/RlssGMn1EQwIGQU0Y5b/FqPiLTMsZpDfFi1Exc+WEXyPCJNe8aE/0grsIvIdel6HSHXT3wRuaoF2w2zBgQRfBk/zULs8ODAIL+G8VqrmryKv+Cs3E6FVVp3Ut/UBVELF7Wctc6QX/kWeyu24rL8FwBE5MKq3OV8WLXLr2EcoMIq5Ui10699iIjIlUWBXESueg/HBhHe/GzzZoU74CcDL6OBC6ixqtldvoGTrmMXdULvppavXZ/yt4pNCuUiAfRZzQHvI838yUUtH5zczYqV/l+PoilVVVWkpqbSq1cvbrvtNj777DOftb1q1SpeeeUVn7XXlOXLl2OM4dSpU4Dn6RdDhw5l0KBB3sUu60VGRvq1FhGRllIgF5GrXnS4jbX3hBFxCatiRATBH+8No1O4f34c1t93Wm6dwbqEFZnduPjWfZoPKv/aaF9JSUnAViTfuXMn8fHxOBwO1q9f79O2/XnivmDBAvr27UtsbCxTpkyhpKQEgNOnT/ODH/yAyMhIHn300Qbv0Yn79c1tufms5sPLWlH9YpSdKWfFi79rlb6+66WXXqJ9+/YUFhYyd+5cHn/8cZ+0W1tby+zZs5k5c6ZP2mvKl19+ydatW7nlln/c5tOpUyf+/Oc/8+GHH7J69WrS09P91r+IyKVSIBeRa8KgG+z8aUoY7UMgrAXBPNQO7UNh85QwBnSy+62uY7Wf8I3r68taBMqNi+Ouzxs9GimQgfyWW24hKyuLGTNm+LRdf5+4Jycns3//fvbt20fv3r1ZsmQJAKGhofziF79g+fLlfulXrl6nXMd8vohbczKfXs+nRz8nLi6OBQsWkJ6ezqZNm7z709LS2Lx5M1lZWUyaNIk777yTPn36sHjxYu8xa9asYfjw4cTFxZGRkYHL1bKLCZs2bWLWrFkATJ8+ne3bt5/3MYv1IiMjmT9/PvHx8SQlJXHy5EkAxo4dy5NPPkliYiIvvPACixYt8n5/FRYWMm7cOAYPHkx8fDxHjhwBYNmyZQwbNozY2Fiefvrpln/RgLlz5/LLX/6ywWKYQ4YM4cYbbwRgwIABVFZWUlVV1eB9p06dYsSIEbzxxhsX1Z+IiK8okIvINWNgJzu7Z0QwLyGYG8IMEU3MQo8Iguhww8+GBbP7xxH06+i/MG5Zbg5W7fHJfacuajlQtbvByfHChQs5cuRIQE7cu3fvTmxsLDZby3+NXAkn7ikpKTgcnis2t99+O8eOHQM8z3AfNWoUoaGh532vTtyvT8Wur/x+7/i5Zi2eTNdbO/H3v/+dZcuW8fDDD/Pyyy8DcObMGfbs2cOECRMAyMvLIzs7G6fTybp168jPz+fgwYOsXbuWd999F6fTid1uJzs7G4DU1FTi4uIavepnpBQVFXHzzTcD4HA4iIqK4vTp083We/bsWeLj49m7dy+JiYkNfr6UlJSwY8cO5s+f3+A9aWlpzJkzhw8++IA9e/bQtWtXcnNzOXz4MHl5eTidTgoKCti5cycAo0ePbrLubdu2AbB582ZuuukmBg8efN46X3/9dYYMGUJISIh32/Hjx5k4cSLPPPMMEydOvPB/joiIH+ixZyJyTWkfapgzJJh/jgvinS9cvPOli5MVbgzQKdzGHTfbGXOzHVsTjxTztROuL+pWUveNKqucb9zH6WDvAsDSpUvZv38/TqdnEagdO3bwm9/8hkmTJnlP3FevXs2aNWvIy8tj//79hIeHM2zYMCZOnEhERIT3xD0oKIhHHnmE7OxsZs6cSWpqKocOHWpUw7x58y559Lr+xP1Xv/oVzzzzDIsXL/Y+u73+xB1g0aJF3vekpaWxcOFCpkyZQmVlJW63u8GJu2VZ3HvvvezcuZMxY8YwevRoSktLG/W9fPlyxo0b12BbZmYmqampLar9+PHj3HvvvTz77LMkJydf0ueXq1Ox6yuaXoDRv85aZ4g07UhMTGTOnDmcOHGCDRs2MG3aNO9FpeTkZDp27AjA1KlT2b17Nw6Hg4KCAoYNGwZARUUF0dHRAKxdu7bZPpsaDW/q8Yvnstls3u+j+++/n6lTp3r3NfX9VVpaSlFREVOmTAHwXgTLzc0lNzeXIUOGAFBWVsbhw4cZM2YMu3btOm//5eXlPPfcc+Tm5p73mAMHDvD44483OKampoakpCRWrlxJYmJis59RRMSfFMhF5JpkM4Y7ujm4o1vgfsx9XfspLi7zAenncFHLidrPvYH8u1rzxP1SBPrE/VzPPfccDoeDtLS0Cx6rE/frW5m7JED9fkOkrR0A6enpZGdnk5OTQ2ZmpveY74ZlYwyWZTFr1izv7RjnutCFtpiYGL788ktiYmKora3lzJkzdOhwcc9FP7emiIiIRvvPNwXesiyeeOIJMjIyGu1r7kJb586d+fTTT72j48eOHSM+Pp68vDy6dOnCsWPHmDJlCq+88go9e/b0vtfhcDB06FDeeustfV+LSEApkIuI+Emx62uft3na9b/N7m+tE3dfaO0T9/oR8tWrV7Nlyxa2b99+wdE/0In79c7ditPVAcIiQygvq6TW+sfFvAceeIDhw4fTpUsXBgwY4N2+detWiouLCQsLY+PGjWRmZhIeHs6kSZOYO3cu0dHRFBcXU1paSrdu3S54oe3ee+9l9erVjBgxgvXr13PHHXd4v0f69u3Lxx9/3Og9breb9evXc9999/Haa68xatSoZvto27YtMTExbNy4kcmTJ1NVVYXL5WL8+PH8/Oc/Jy0tjcjISIqKiggKCiI6OvqCF9pOnDjh/Xv37t3Jz8+nU6dOlJSUMHHiRJYsWcLIkSMbvMcYQ2ZmJj/84Q9ZunQpCxcubLYPERF/USAXEfGTKqvc521WWGXev7dp06ZR+GytE/fmXMkn7m+++SbPP/88O3bsIDw8vEWfRyfu1zv/395yrrYdIxlwey/Gxd3NPRMmsWzZMjp37ky/fv2YPHlyg2NHjRpFeno6hYWFzJgxg4SEBACeffZZUlJScLvdBAUFsXLlSrp163bBvh966CHS09Pp1asXHTp0ICcnB/Csn3C+C2QREREcOHCAoUOHEhUV1aKfHa+++ioZGRk89dRTBAUFsW7dOlJSUjh48CAjRowAPGtOrFmzxjtr51KsWLGCwsJCfvGLX/CLX/wC8MywqW/TbreTk5PDPffcQ9u2bXnkkUcuuS8RkUtlLrR65pUgISHBys/PD3QZIiIX5c2yl6il2qdthpoIxkX8Y4R6xowZ7Nu3j7vuuotly5YBcOeddzJ58mRmz54NQFZWFn/5y184e/as98S9fiG0tWvXsmTJkgYn7rfffvsF63j//feZMmUK33zzDaGhoXTp0oUDBw5w6tQpRo4c2eToemRkJHPnzuUvf/mL98T9hhtuYOzYsSxfvtwbJhYtWkRkZCQ/+9nPOHz4MBkZGZw6dcp74t6jRw9eeOEF/vu//9vb7po1axpMRz2fXr16UVVV5Z2+f/vtt7Nq1SrAM7L27bffUl1dTbt27cjNzaV///5ERkZSVlZGdXU199xzD5MmTdKJ+3Vk29lXqTznQlhrcBBMfGgy0Q7PI7zKy8sZNGgQe/fuJSoqCvB8X+fn53vXYfCnLVu2cPToUR577LFG++q/P0RELpcxpsCyrIRA19HaFMhFRPzkr2ezKbe+9WmbUbYbGB0+/bz7deIu4lvvV/wPx12ftWqfNmwkhacTYgtn27ZtPPjgg8ybN4+f/vSn3mNa8/u6Ofq+FhFfuV4Duaasi4j4STtbZ8pdvg3kHexdz7vv3BP3+jDe2u6+++6A9CviLx3tN3LS9UWrPovcThAhNs8tFePGjeOLL75odMwDDzzAAw880Go1nY/CuIjI5dEIuYiInxTVHGZf1Q6frbRuJ4iE0PHc4LjZJ+2JyIV96zrNuxUbWvFZ5IYu9ltJCBvfSv2JiFwZrtcRclugCxARuVZ1cfTw6XJQDuOgkz3Ghy2KyIW0tXck3Na21fqzY6dn8OBW609ERAJLgVxExE/sxs73ghOw++DuIDsO+gbd3qLHdImIb/UMGuKT7+OWCDHhtLN1bpW+REQk8BTIRUT8qEdQLBG2KMxljJUbbETZookJ6uPDykSkpW509CTURPq9HzsOBoUk6sKbiMh1RIFcRMSPjLExPHQiwSYMcwk/cg02wkwkCWHjdZIuEiA2Y2doaAo27P7rAztdHT24waHbUkREricK5CIifhZqi2B02HTa2Npf1LRXOw6ibDcwKnwawSbUjxWKyIW0tXekd/Awv0xdNxhCTBgDQ0b7vG0REbmy6bFnIiKtoD6UH6n5gMPVBQDnXX3dThAGQ9/g2+gWNOCqGxk/Y9Xwkessn7jOcsxdhRuLtsZBH3sE37OF08MWdtV9JhGAXsFDqLYq+LzmgM9WXTfYCDahfD9sCg4T7JM2RUTk6qFALiLSSoyx0St4CLcGDeKr2qMcr/2Ub9wnqLEqAQg2YbS3daZLUA+62LtjM/6bHusPh11nWVv9NX93lRKEoQI35z5Yc3ftNxgMbYydaUGdSQ7qSJDRRC25uvQP+T7BJpRPqvNx47qstuw4CDNtuD3sHkJtET6qUEREriZ6DrmIiFyWKstNZlUR22tPU4NFS36rhGDoYIJ4PPRWetjD/V6jiK+dcZ2koDKXKqv8EkbLDTbs9AqKp1fwEGy6MCUict0+h1wj5CIicsm+tWp5vPwTTlrVVLcointUYfG1Vc3jFZ/w05BujAxq78cqRXwvyn4DY8Pv48uajzlS46wL5i5o5vvAjgMLi5sc36Nn8BAibe1ar2AREbkiKZCLiMglqbBc/Fv5J5ywqi7pbloLTzD/TdXnhBgbCY4zXMNdAAAgAElEQVQoX5co4lc2Y6db8ABuCepPifs4J2q/4LTrK0rdp6mtmy9iw0aYaUN7exc62rvS1dFD94qLiIiXArmIiFyS/1t1jJNW9WUvbVWNxbLKz/h9eH/a2YIAKCkp4bXXXuORRx65/EIv0s6dO/npT3/Kvn37yMnJYfr06T5re9WqVYSHhzNz5kyftVlvwYIF/PnPfyY4OJiePXvy8ssv066dZwR23759ZGRk8O2332Kz2Xj//fcJDQ0lMjKSsrIyn9dyvTHG0N7ehfb2LoEuRURErjK6aUlERC7aflcpu2q/oeYipqk3pwY3/1n1hfffJSUlvPjiiz5p+2LdcsstZGVlMWPGDJ+2W1tby+zZs/0SxgGSk5PZv38/+/bto3fv3ixZssTb7/3338+qVas4cOAA77zzDkFBQX6pQURERC6OArmIiFy0NVVfXdQ94xdSCzhdpXzlrgJg4cKFHDlyhLi4OBYsWEB6ejqbNm3yHp+WlsbmzZvJyspi0qRJ3HnnnfTp04fFixf/o8Y1axg+fDhxcXFkZGTgcrVsRezu3bsTGxuLzdbyX5GRkZHMnz+f+Ph4kpKSOHnyJABjx47lySefJDExkRdeeIFFixaxfPlyAAoLCxk3bhyDBw8mPj6eI0eOALBs2TKGDRtGbGwsTz/9dItrSElJweHwTHy7/fbbOXbsGAC5ubnExsYyePBgADp27Ijd3nAF/1OnTjFixAjeeOONFvcnIiIil0+BXERELsrX7ioOu8t93q6FxZYaT5BdunQpPXv2xOl0smzZMh5++GFefvllAM6cOcOePXuYMGECAHl5eWRnZ+N0Olm3bh35+fkcPHiQtWvX8u677+J0OrHb7WRnZwOQmppKXFxco9crr7xyybWfPXuW+Ph49u7dS2JiYoMLAyUlJezYsYP58+c3eE9aWhpz5szhgw8+YM+ePXTt2pXc3FwOHz5MXl4eTqeTgoICdu7cCcDo0aObrHvbtm2N6snMzOSuu+4C4JNPPsEYw/jx44mPj+eXv/xlg2OPHz/OxIkTeeaZZ5g4ceIlfw1ERKQVFBfDkSNw8KDnz+LiQFckl0n3kIuIyEXZ5yr1y9XcWuD92jP8n5CYRvsSExOZM2cOJ06cYMOGDUybNs07GpycnEzHjh0BmDp1Krt378bhcFBQUMCwYcMAqKioIDo6GoC1a9f6vHabzUZqaioA999/P1OnTvXuq99+rtLSUoqKipgyZQoAoaGhgGc0Ozc3lyFDhgBQVlbG4cOHGTNmDLt27WpRLc899xwOh4O0tDTAM2V99+7dvP/++4SHh5OUlMTQoUNJSkqipqaGpKQkVq5cSWJi4qV/AURExD8++ghefx127ACnE0pLITgYjAHLgupqaNMG4uIgMRGmTYP+/QNdtVwEBXIREbkoH7nKqPLhdPVznbSqqbbcTe5LT08nOzubnJwcMjMzvduNMQ2OM8ZgWRazZs3y3kd9rtTUVA4dOtRo+7x583x2f/e5NUVERDTab1lNf/0sy+KJJ54gIyOj0b7Ro0dTWlraaPvy5csZN24cAKtXr2bLli1s377dW0NMTAyJiYl06tQJgAkTJrB3716SkpJwOBwMHTqUt956S4FcRORKUVMDGzfC8897AnltrWdbverqhsefPg3bt8POnbBkiSeQP/44TJ4MWjPkiqcp6yIiclG+rLvP2x+CsHHKqqZNmzaNwucDDzzAb3/7WwAGDBjg3b5161aKi4upqKhg48aNjBw5kqSkJNavX8+JEycAKC4u5vPPPwc8I+ROp7PRqyVhvG/fvk1ud7vdrF+/HoDXXnuNUaNGNdtO27ZtiYmJYePGjQBUVVVRXl7O+PHjyczM9K58XlRU5P0Mu3btarLu+jD+5ptv8vzzz7N582bCw8O9fY0fP559+/ZRXl5ObW0tO3bsoH/d6IkxhszMTD7++GOWLl16wc8vIiJ+9t570KsXPPggFBRARUXDMN6cmhrP8QUFnvf36uVpT65ofgvkxpibjTFvG2MOGmMOGGP+tW57B2PMVmPM4bo/2/urBhER8T2Xn0bHAQzgwrPw2MiRIxk4cCALFiwAoHPnzvTr14+f/OQnDd4zatQo0tPTiYuLY9q0aSQkJNC/f3+effZZUlJSiI2NJTk5ma+++qpFNbz//vvExMSwbt06MjIyvOH/1KlT5x3ZjoiI4MCBAwwdOpS//vWvPPXUUxfs59VXX+V3v/sdsbGxfP/73+frr78mJSWFGTNmMGLECAYNGsT06dObHBVvyqOPPkppaSnJycnExcUxe/ZsANq3b8+8efMYNmwYcXFxxMfHN7hX3G63k5OTw9tvvx2wle1FRK57lZUwdy784AfwxRdwuY+kLCvztPODH3jaraz0TZ3ic+Z8JxeX3bAxXYGulmXtNca0AQqAycADQLFlWUuNMQuB9pZlPd5cWwkJCVZ+fr5f6hQRkYvzZPlh9rv98+zqYAyrwvvTyRbcaF95eTmDBg1i7969REVFAZCVlUV+fj4rVqzwSz3n2rJlC0ePHuWxxx5rtE/P8xYRkUtWXAxjx0JhoWeE29fCwjyj5e+8Ax06+L59HzHGFFiWlRDoOlqb30bILcv6yrKsvXV/LwUOAjcBk4DVdYetxhPSRUTkKtHHHo658GGXxGDoaBrf77Zt2zb69u3Lv/zLv3jDeGu7++67mwzjIiIil6y4GIYPh0OH/BPGwdPuoUOefrQq+xXHbyPkDToxpjuwExgIfGFZVrtz9n1jWVajaevGmH8C/gnglltuGVp/75+IiATW/6st4TeVn1NB04uvXY7etnCWh/fxebsiIiJXnMrKf4Tx7y7U5g/BwdCnD+TlQd3TPa4kGiH3E2NMJPA68FPLsr5t6fssy/q/lmUlWJaVcMMNN/ivQBERuShD7G39chd5KDbuCurkh5ZFRESuQE884Zmm3hphHDz9FBbCk0+2Tn/SIn4N5MaYIDxhPNuyrA11m4/X3V9ef5/5CX/WICIivhVibCQ5OuDww8T1UQ6t8ykiIteB996D3//ef9PUz6eiAlat0urrVxB/rrJugJeAg5Zl/fqcXZuBWXV/nwVs8lcNIiLiH/eFdCHYh4E8BBuzgm8kxOhpnCIico2rqYEf/aj1w3i9igpP/y19nJr4lT/PfEYC6cAdxhhn3WsCsBRINsYcBpLr/i0iIleRKBPEY6HdCPFBKHcA3W2hTNB0dRERuR5s3Bj4xdWKi2GTxkWvBP5cZX23ZVnGsqxYy7Li6l5/sSzrtGVZSZZlfa/uTy31JyJyFfq+ox2TgqIvK5Q7gA4mmJ+H9cQzsUpEROQa9/zzl/+c8UtQArxY/4+yMk8draSqqorU1FR69erFbbfdxmeffeazto0xs40xM33WYOP2/8UYc8gYc8AY88tztscaY/5Wt/1DY0xo3faL+s/V3EAREblk94fcyH3BXQnGXHQsD8HGLbYwfhXem7bG4Zf6RERErigffeR5BUCDQA5w4AAcPNgqfb/00ku0b9+ewsJC5s6dy+OPP+6Tdo0xDsuyVlmW9YpPGmzc/g/wPLY71rKsAcDy+n6BNcDsuu1jgUu6B0CBXERELsu04M78Mqw3XU0IoS34tRKCjWAMM4K78KuwPkQ18dxxERGRa9Lrr0NtbUC6XggcAeKABUB6ZSWbnnvOuz8tLY3NmzeTlZXFpEmTuPPOO+nTpw+LFy/2HrNmzRqGDx9OXFwcGRkZuFyuFvW9adMmZs3yLCM2ffp0tm/fzoUev22MKTPG/MoYs9cYs90Yc0Pd9neMMf9hjNkB/KsxZpEx5md1+3oZY7YZYz6oe1/Puu0LjDHvG2P2GWMWN9Ptd/0zsNSyrCoAy7LqFyRPAfZZlvVB3fbTlmU1+GIYYzrVjaBPbK4DBXIREblsPezh/H/h/fj30B4MtbcltC50h2MjHBth2LADN5oQ0oO7khUxkCnBnbFrmrqIiFxPduwI2GJqS4GegBNYBjxsWbycmwvAmTNn2LNnDxMmTAAgLy+P7OxsnE4n69atIz8/n4MHD7J27VreffddnE4ndrud7OxsAFJTU4mLi2v0euUVz8B1UVERN998MwAOh4OoqChOnz59oZIjgL2WZcUDO4Cnz9nXzrKsRMuyfvWd92QDKy3LGgx8H/jKGJMCfA8Yjud6xFBjzBgAY8yuc9Y7O/c1rq693sBoY8x7xpgdxphh52y3jDFv1QX/fzu3CGNMZ+AN4CnLst5o7kNqjqCIiPiEMYbBjjYMdrTBsixOWjWcsKpxWRaRxs4ttlCCtIq6iIhcz5zOQFfglQjMKS7mxIkTbNiwgWnTpuFweOJhcnIyHTt2BGDq1Kns3r0bh8NBQUEBw4Z5MmlFRQXR0dEArF27ttm+mhoNb8HaMW6gvuE1wIZz9jXq0BjTBrjJsqw/1fVZWbc9Bc+I9t/rDo3EE9B3WpY1+gI1OID2wO3AMOCPxpgeddtH1W0rB7YbYwosy9oOBAHbgTmWZe240IdUIBcREZ8zxhBtgokmONCliIiIXBmKi6G0NNBVNJAOZP/Xf5GzeTOZmZne7d8Ny8YYLMti1qxZLFmypFE7qampHDp0qNH2efPmMXPmTGJiYvjyyy+JiYmhtraWM2fO0KFDh4st99xUf7aJ/edL+AZYYlnW7xvtMGYX0KaJ9/zMsqxtwDFgg+W5opBnjHEDneq277As61RdO38B4vEE8VqgABiPZ2S/WQrkIiIiIiIi/vbNNxAcDNXVAem+DfDdywEPhIQw/MUX6RITw4ABA7zbt27dSnFxMWFhYWzcuJHMzEzCw8OZNGkSc+fOJTo6muLiYkpLS+nWrdsFR8jvvfdeVq9ezYgRI1i/fj133HGHN/T37duXjz/+uKm32YDpQA4wA9jdXB+WZX1rjDlmjJlsWdZGY0wIYAfeAn5hjMm2LKvMGHMTUGNZ1okWjJBvBO4A3jHG9AaCgVN1bf6bMSYcqMYz4eA39aUADwLrjDELLctq9jHfCuQiIiIiIiL+Vl0NAVw7pSMwEhgI3IXnPvLOdjv9evRgclpag2NHjRpFeno6hYWFzJgxg4SEBACeffZZUlJScLvdBAUFsXLlSrp163bBvh966CHS09Pp1asXHTp0ICcnB4BTp041t7jbWWCAMaYAOAOktuBjpgO/N8Y8g2fV8x9alpVrjOkH/K3uIkAZcD9w4vzNeGUCmcaY/XiC96y60fJvjDG/Bt7HE8D/cu694pZluYwx9wF/NsZ8a1nWi001DmAutLrdlSAhIcHKz88PdBkiIiIiIiKX5sgRiIsLyDPIz6c8IoJBHTuyd98+oqKiAMjKyiI/P58VK1b4vf8tW7Zw9OhRHnvsMeruwU6o32eMKbMsK9LvRQSYRshFRERERET8rX37gE1Xb8o24MGzZ5n35JPeMN7a7r777oD0eyXRCLmIiIiIiEhr6NQJLvy4r9bTqROcPBnoKgAajZBfL/T8GRERERERkdYQFxfoChq60uq5DimQi4iIiIiItIbERAgKCnQVHkFBMHZsoKu47imQi4iIiIiItIZp08BxhSzj5XDA1KmBruK6p0AuIiIiIiLSGvr397yuBAMGQL9+ga7iuqdALiIiIiIi0loefxwiA/w0r8hITx0ScArkIiIiIiIirWXyZOjQIbA1dOgAkyYFtgYBFMhFRERERERaT1AQ/PGPEBYWmP7DwmDduitncbnrnAK5iIiIiIhIa7rtNsjIaP1QHhYGs2fD8OGt26+clwK5iIiIiIhIa1uyBHr1guDg1ukvONjT33/8R+v0Jy2iQC4iIiIiItLaQkPhnXfg5pv9H8qDg+GWW2DHDk+/csVQIBcREREREQmEDh0gLw/69PHf9PWwME/7eXnQvr1/+pBLpkAuIiIiIiISKPWhfPZs34fy+nvGFcavWArkIiIiIiIigRQaCr/+Nbz9tmdq+eU+p7xNG087b7/taVfT1K9YCuQiIiIiIiJXgttug8JCePllSEjwjHC39PFkQUGe4xMSIDPT085tt/m3XrlsjkAXICIiIiIiInWCgmD6dM/ro4/gT3/yLP7mdMK333oWaDMGLAuqq6FtW4iLg7FjYepU6Ncv0J9ALoICuYiIiIiIyJWof3/P69//3fPv4mIoKYGqKggJgXbtPPegy1VLgVxERERERORq0KGDAvg1RveQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIiIiIiASAArmIiIiIiIhIACiQi4iIXCHctVBT7vlTRERErn2OQBcgIiJyvaoph/058NF6+GovnD0BNju4XRARDV3jof90GHgfBIUHuloRERHxNQVyERGRVlZbCW8/De+vBAzUlP1jX/3o+NnjUPg/8Pku+J/HYNgc+MFicIQGpGQRERHxA01ZFxERaUX/mw//2Rvy/hNqzjYM402pKfMcl7cCVvTxvF9ERESuDQrkIiIireTIVvj/27vzIKuqO4Hj31/3a0fpVnFUiCtalMYFoYWGigs2GTa3DItjMBLcsuAEEicSK2qNohkzwcHESlVMqFhDcEEhooIhGQWtCC6ZIM20CqIDLhNFh2UQA2LA7j7zx3t0GukGhX7vQb/vp+pVvz7v3HNP9+++8/rX5557p9XCn9+Gho8+27YNm+GDP2W3f31+fvonSZIKy4RckqQCeHcxzByeXTe+Jz7enG3HmXJJkvZ9JuSSJOVZw19g5sg9T8a3+Xhztr2Gv2S/37BhAz//+c/bp/HPaOHChfTu3ZtMJsOsWbPate0pU6Zw7733tmub21x33XWcdNJJ9OzZkxEjRrBhwwYAtm7dypVXXslpp51Gr169ePrpp5u3qaqqyktfJEmly4RckqQ8+/1E2LyufdvcvC7bLhQ3IT/22GOZNm0al156abu229DQwNVXX81ll13Wru1uM3jwYJYuXcpLL73EiSeeyI9+9CMA7r77bgBefvll5s+fz4QJE2hqaspLHyRJMiGXJCmPPt6cvZr6Z10zvisNH2Xb/XgzXH/99bz++utUV1dz3XXXMWbMGObMmdNcd/To0Tz22GNMmzaNYcOGce655/L5z3+eW2+9tbnO/fffT79+/aiurmbs2LE0NjZ+qn4cd9xx9OzZk7KyT/8nRVVVFRMmTKB3794MHDiQtWvXAjBgwABuvPFGamtr+elPf8ott9zCHXfcAcDKlSsZNGgQvXr1onfv3rz++usATJ48mb59+9KzZ08mTpz4qfswZMgQMpnszWa+8IUv8M477wDwyiuvMHDgQAC6dOlC586dWbx4+/UB69at44wzzuC3v/3tp96fJEmtMSGXJCmPls4AIj9tR8DSmTBp0iS6d+9OfX09kydP5utf/zq/+tWvAPjggw94/vnnOf/88wFYtGgR06dPp76+noceeojFixezfPlyZs6cyXPPPUd9fT3l5eVMnz4dgFGjRlFdXb3DY09OJf/www/p3bs3S5Ysoba2drt/DGzYsIEFCxYwYcKE7bYZPXo048aN48UXX+T555/niCOOYN68eaxYsYJFixZRX19PXV0dCxcuBKB///6t9vvJJ5/coT9Tp07lvPPOA6BXr17MmTOHhoYG3nzzTerq6nj77beb665evZoLLriAH/zgB1xwwQW7/TuQJAm8D7kkSXn1yqxd39psd23dBMsfhjO/uH15bW0t48aNY82aNTzyyCNcdNFFzbPBgwcP5tBDDwVg5MiRPPvss2QyGerq6ujbty8AH330EV26dAFg5syZ7d7vsrIyRo0aBcBXv/pVRo4c2fzatvKWNm7cyKpVqxgxYgQA+++fvRn7vHnzmDdvHqeffjoAmzZtYsWKFZxzzjk888wzn6ovP/zhD8lkMowePRqAq666iuXLl1NTU0O3bt0488wzm393H3/8MQMHDuSuu+6itrZ2N396SZL+yoRckqQ8em9Jftt/t6718jFjxjB9+nRmzJjB1KlTm8sjtp+ujwhSSlx++eXN66hbGjVqFK+99toO5ddee227re9u2afKysodXk8ptbpdSokbbriBsWPH7vBa//792bhx4w7ld9xxB4MGDQLgnnvuYe7cuTz11FPNfchkMtx5553N9c8880xOOOGE5tf69OnDE088YUIuSWoXJuSSJOVJUwN8uCa/+/hwNVQecOAOyecVV1xBv379+NznPsepp57aXD5//nzWr1/PAQccwOzZs5k6dSqdOnVi2LBhfPe736VLly6sX7+ejRs30q1btz2aIT/ppJN49dVXdyhvampi1qxZXHLJJTzwwAOcffbZO23noIMO4uijj2b27NkMHz6cLVu20NjYyNChQ7npppsYPXo0VVVVrFq1ioqKCrp06bLLGfLHH3+c22+/nQULFtCpU6fm8s2bN5NSorKykvnz55PJZDjllFOA7D8Opk6dysUXX8ykSZO4/vrrd+O3IknSX5mQS5KUJ41boaw8m5jnS1k5dD7wUM466yx69OjBeeedx+TJk+natSsnn3wyw4cP367+2WefzZgxY1i5ciWXXnopNTU1ANx2220MGTKEpqYmKioquOuuu+jWrdsu9//CCy8wYsQI3n//fX7zm98wceJEli1bxrp169qc2a6srGTZsmX06dOHgw8++FMl/ffddx9jx47l5ptvpqKigoceeoghQ4awfPlyzjjjDCB7sbj777+/+XT7nRk/fjxbtmxh8ODBQPbCblOmTGHNmjUMHTqUsrIyjjrqKO67777ttisvL2fGjBl86Utf4qCDDuJb3/rWLvclSVJboq0Py71JTU1N+uQVTiVJ2ts1NcC/7Afk86M24KatUPaJf7Fv3ryZ0047jSVLlnDwwQcDMG3aNBYvXszPfvazPHYoa+7cubzxxht85zvf2eG1qqoqNm3K08J6SdI+KSLqUko1xe5HoTlDLklSnpRloLJL9rTyfKnsumMy/uSTT3LVVVdx7bXXNifjhXbhhRcWZb+SJO1LnCGXJCmPpp8PK/8jf+2fcAFcOjd/7UuSVAilOkPufcglScqjU/4BKqry0/Z+VXDyRflpW5Ik5Z8JuSRJedTjEvK2hjwl6LHjbbslSdI+woRckqQ8qugEfcdB5oD2bTeTa7ei067rSpKkvZMJuSRJefbFW6HTYe3bZuVh2XYlSdK+y4RckqQ8y+wPox5pv9nsik7w5Yez7UqSpH2XCbkkSQVwZA2Mmr3nSXlFp2w7R5bcdWglSep4TMglSSqQ7oPhigVw0DGffU15phMcfGx2++6D89M/SZJUWCbkkiQV0JE18O3/hn7fhorKXd8Sbb+qbL1+42H8a86MS5LUkWSK3QFJkkpNZn8YfDsMmAhLZ8Lyh+HdOvhwNZSVQ1MjVHaFI/tk7zPeY5RXU5ckqSMyIZckqUgqOsHpV2YfAE0N0LgVyveDMj+hJUnq8Py4lyRpL1GWMRGXJKmUuIZckiRJkqQiMCGXJEmSJKkI8paQR8TUiFgTEUtblN0SEasioj73OD9f+5ckSZIkaW+WzxnyacC5rZTfmVKqzj1+l8f9S5IkSZK018pbQp5SWgisz1f7kiRJkiTty4qxhnx8RLyUO6X9kLYqRcQ3I2JxRCxeu3ZtIfsnSZIkSVLeFToh/wXQHagG3gN+3FbFlNIvU0o1KaWaww8/vFD9kyRJkiSpIAqakKeUVqeUGlNKTcDdQL9C7l+SJEmSpL1FQRPyiDiixbcjgKVt1ZUkSZIkqSPL5KvhiHgQGAAcFhHvABOBARFRDSTgLWBsvvYvSZIkSdLeLFJKxe7DLkXEWuB/irDrw4B1Rdiv9g7GXx4Dpc34y2OgtBn/0mb8C69bSqnkLh62TyTkxRIRi1NKNcXuh4rD+MtjoLQZf3kMlDbjX9qMvwqlGLc9kyRJkiSp5JmQS5IkSZJUBCbkO/fLYndARWX85TFQ2oy/PAZKm/EvbcZfBeEackmSJEmSisAZckmSJEmSisCEXJIkSZKkIjAhbyEi3oqIlyOiPiIW58r+NiLmR8SK3NdDit1PtY+ImBoRayJiaYuyNuMdETdExMqIeC0ihhan12ovbcT/lohYlRsD6iPi/BavGf8OJCKOiYjfR8TyiFgWEdfkyh0DSsROjgHHgRIQEftHxKKIeDEX/1tz5Y4BJWAn8ff9r4JzDXkLEfEWUJNSWtei7N+A9SmlSRFxPXBISun7xeqj2k9EnANsAu5NKfXIlbUa74g4BXgQ6AccCTwJnJhSaixS97WH2oj/LcCmlNIdn6hr/DuYiDgCOCKltCQiDgTqgOHAFTgGlISdHANfxnGgw4uIACpTSpsiogJ4FrgGGIljQIe3k/ifi+9/FZgz5Ls2DLgn9/wesh/W6gBSSguB9Z8obivew4AZKaUtKaU3gZVkB2Xto9qIf1uMfweTUnovpbQk93wjsBw4CseAkrGTY6AtHgMdSMralPu2IvdIOAaUhJ3Evy3GX3ljQr69BMyLiLqI+GaurGtK6T3IfngDXYrWOxVCW/E+Cni7Rb132Pkfbtp3jY+Il3KntG87VdH4d2ARcRxwOvBHHANK0ieOAXAcKAkRUR4R9cAaYH5KyTGghLQRf/D9rwIzId/eWSml3sB5wLjcKa0SQLRS5nqPjucXQHegGngP+HGu3Ph3UBFRBTwM/FNK6c87q9pKmcdAB9DKMeA4UCJSSo0ppWrgaKBfRPTYSXXj38G0EX/f/yo4E/IWUkrv5r6uAR4leyrK6tw6s23rzdYUr4cqgLbi/Q5wTIt6RwPvFk+hiG0AAAQfSURBVLhvyrOU0urcB3QTcDd/PR3N+HdAuXWDDwPTU0qP5IodA0pIa8eA40DpSSltAJ4mu37YMaDEtIy/738Vgwl5TkRU5i7qQkRUAkOApcBjwOW5apcDc4rTQxVIW/F+DLgkIv4mIo4HTgAWFaF/yqNtf4TljCA7BoDx73ByF/T5d2B5SuknLV5yDCgRbR0DjgOlISIOj4jOuecHAIOAV3EMKAltxd/3v4ohU+wO7EW6Ao9mP5/JAA+klB6PiBeAX0fE14A/ARcXsY9qRxHxIDAAOCwi3gEmApNoJd4ppWUR8WvgFaABGOeVNfdtbcR/QERUkz0N7S1gLBj/DuosYAzwcm4NIcCNOAaUkraOga84DpSEI4B7IqKc7ATVr1NKcyPiDzgGlIK24n+f738Vmrc9kyRJkiSpCDxlXZIkSZKkIjAhlyRJkiSpCEzIJUmSJEkqAhNySZIkSZKKwIRckiRJkqQiMCGXJGk3RMRxEbF01zUlSZJaZ0IuSVKBRUSm2H2QJEnFZ0IuSdLuK4+IuyNiWUTMi4gDIqI6Iv4zIl6KiEcj4hCAiHg6Iv41IhYA10TExRGxNCJejIiFuTrlETE5Il7IbT82Vz4gIhbm2nslIqZERFnuta9ExMu5tm7PlX05In6Se35NRLyRe949Ip4twu9JkiS1woRckqTddwJwV0rpVGADcBFwL/D9lFJP4GVgYov6nVNKtSmlHwM3A0NTSr2Av8+9/jXgg5RSX6Av8I2IOD73Wj9gAnAa0B0YGRFHArcDfwdUA30jYjiwEOif264/8H8RcRRwNvBMe/8SJEnS7jEhlyRp972ZUqrPPa8jmyh3TiktyJXdA5zTov7MFs+fA6ZFxDeA8lzZEOCyiKgH/ggcSjbpB1iUUnojpdQIPEg2ue4LPJ1SWptSagCmA+eklP4XqIqIA4FjgAdy/eiPCbkkSXsNE3JJknbflhbPG4HOu6j/4bYnKaWrgX8mmzDXR8ShQADfTilV5x7Hp5TmbdvkE22lXP22/AG4EniNbBLeHziD7D8CJEnSXsCEXJKk9vMB8H5EbDtdfAywoLWKEdE9pfTHlNLNwDqyifkTwD9GREWuzokRUZnbpF9EHJ9bOz4KeJbsLHptRBwWEeXAV1rsbyHwvdzX/wK+CGxJKX3Qvj+yJEnaXV7lVZKk9nU5MCUiOgFvkJ2lbs3kiDiB7Cz3U8CLwEvAccCSiAhgLTA8V/8PwCSya8gXAo+mlJoi4gbg97l2fpdSmpOr/wzZJH9hSqkxIt4GXm3Xn1SSJO2RSOmTZ8BJkqS9SUQMAL6XUrqw2H2RJEntx1PWJUmSJEkqAmfIJUmSJEkqAmfIJUmSJEkqAhNySZIkSZKKwIRckiRJkqQiMCGXJEmSJKkITMglSZIkSSqC/wecpY3oxKYsqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "for color, label in zip(colors, cluster_labels):\n",
    "    subset = agg_cars.loc[(label,),]\n",
    "    for i in subset.index:\n",
    "        plt.text(subset.loc[i][0]+5, subset.loc[i][2], 'type='+str(int(i)) + ', price='+str(int(subset.loc[i][3]))+'k')\n",
    "    plt.scatter(subset.horsepow, subset.mpg, s=subset.price*20, c=color, label='cluster'+str(label))\n",
    "plt.legend()\n",
    "plt.title('Clusters')\n",
    "plt.xlabel('horsepow')\n",
    "plt.ylabel('mpg')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Want to learn more?\n",
    "\n",
    "IBM SPSS Modeler is a comprehensive analytics platform that has many machine learning algorithms. It has been designed to bring predictive intelligence to decisions made by individuals, by groups, by systems – by your enterprise as a whole. A free trial is available through this course, available here: [SPSS Modeler](http://cocl.us/ML0101EN-SPSSModeler).\n",
    "\n",
    "Also, you can use Watson Studio to run these notebooks faster with bigger datasets. Watson Studio is IBM's leading cloud solution for data scientists, built by data scientists. With Jupyter notebooks, RStudio, Apache Spark and popular libraries pre-packaged in the cloud, Watson Studio enables data scientists to collaborate on their projects without having to install anything. Join the fast-growing community of Watson Studio users today with a free account at [Watson Studio](https://cocl.us/ML0101EN_DSX)\n",
    "\n",
    "### Thanks for completing this lesson!\n",
    "\n",
    "Notebook created by: <a href = \"https://ca.linkedin.com/in/saeedaghabozorgi\">Saeed Aghabozorgi</a>\n",
    "\n",
    "<hr>\n",
    "Copyright &copy; 2018 [Cognitive Class](https://cocl.us/DX0108EN_CC). This notebook and its source code are released under the terms of the [MIT License](https://bigdatauniversity.com/mit-license/)."
   ]
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