project6.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy.cluster.hierarchy import linkage, dendrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Index</th>\n",
       "      <th>Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Designation</th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Cost involved in recruiting</th>\n",
       "      <th>Induction program cost</th>\n",
       "      <th>New hires performance satisfaction</th>\n",
       "      <th>Time to fill</th>\n",
       "      <th>...</th>\n",
       "      <th>Performance Differential</th>\n",
       "      <th>Performance rating</th>\n",
       "      <th>Type of Training</th>\n",
       "      <th>Hours of trg</th>\n",
       "      <th>Content Satisfaction</th>\n",
       "      <th>Skill development</th>\n",
       "      <th>Knowledge level</th>\n",
       "      <th>Score</th>\n",
       "      <th>Total Score</th>\n",
       "      <th>Average score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Male</td>\n",
       "      <td>Producer</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>400</td>\n",
       "      <td>800</td>\n",
       "      <td>35</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Female</td>\n",
       "      <td>Cinematographer (Director of Photography)</td>\n",
       "      <td>48</td>\n",
       "      <td>13</td>\n",
       "      <td>500</td>\n",
       "      <td>1200</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Male</td>\n",
       "      <td>Director</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>450</td>\n",
       "      <td>900</td>\n",
       "      <td>85</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Female</td>\n",
       "      <td>Editor</td>\n",
       "      <td>56</td>\n",
       "      <td>10</td>\n",
       "      <td>600</td>\n",
       "      <td>1100</td>\n",
       "      <td>60</td>\n",
       "      <td>34</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Female</td>\n",
       "      <td>Art Director</td>\n",
       "      <td>42</td>\n",
       "      <td>14</td>\n",
       "      <td>250</td>\n",
       "      <td>600</td>\n",
       "      <td>40</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Index     Name   Gender                                Designation  Age  \\\n",
       "0      1    Liam      Male                                   Producer   37   \n",
       "1      2  Olivia    Female  Cinematographer (Director of Photography)   48   \n",
       "2      3    Noah      Male                                   Director   24   \n",
       "3      4    Emma    Female                                     Editor   56   \n",
       "4      5     Ava    Female                               Art Director   42   \n",
       "\n",
       "   Experience  Cost involved in recruiting  Induction program cost  \\\n",
       "0           1                          400                     800   \n",
       "1          13                          500                    1200   \n",
       "2           8                          450                     900   \n",
       "3          10                          600                    1100   \n",
       "4          14                          250                     600   \n",
       "\n",
       "   New hires performance satisfaction  Time to fill  ...  \\\n",
       "0                                  35            30  ...   \n",
       "1                                  75            25  ...   \n",
       "2                                  85            18  ...   \n",
       "3                                  60            34  ...   \n",
       "4                                  40            22  ...   \n",
       "\n",
       "   Performance Differential Performance rating  Type of Training  \\\n",
       "0                        25                  3                 2   \n",
       "1                        15                  3                 2   \n",
       "2                        15                  3                 1   \n",
       "3                        30                  1                 1   \n",
       "4                         5                  3                 1   \n",
       "\n",
       "   Hours of trg  Content Satisfaction  Skill development  Knowledge level  \\\n",
       "0            25                     2                  1                1   \n",
       "1            13                     3                  3                1   \n",
       "2             8                     3                  2                2   \n",
       "3             9                     3                  1                1   \n",
       "4            15                     3                  1                1   \n",
       "\n",
       "   Score  Total Score  Average score  \n",
       "0      3           10            2.0  \n",
       "1      2           12            2.4  \n",
       "2      1           11            2.2  \n",
       "3      1            7            1.4  \n",
       "4      2           10            2.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_excel(\"Ex2.xlsx\", sheet_name=\"Sheet5\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Target Given</th>\n",
       "      <th>Target Achieved</th>\n",
       "      <th>Performance Differential</th>\n",
       "      <th>Performance rating</th>\n",
       "      <th>Content Satisfaction</th>\n",
       "      <th>Sourcing Channel</th>\n",
       "      <th>Hours of trg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>55</td>\n",
       "      <td>30</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48</td>\n",
       "      <td>13</td>\n",
       "      <td>60</td>\n",
       "      <td>45</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>10</td>\n",
       "      <td>60</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>42</td>\n",
       "      <td>14</td>\n",
       "      <td>60</td>\n",
       "      <td>55</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Experience  Target Given  Target Achieved  Performance Differential  \\\n",
       "0   37           1            55               30                        25   \n",
       "1   48          13            60               45                        15   \n",
       "2   24           8            45               30                        15   \n",
       "3   56          10            60               30                        30   \n",
       "4   42          14            60               55                         5   \n",
       "\n",
       "   Performance rating  Content Satisfaction  Sourcing Channel  Hours of trg  \n",
       "0                   3                     2                 1            25  \n",
       "1                   3                     3                 2            13  \n",
       "2                   3                     3                 3             8  \n",
       "3                   1                     3                 4             9  \n",
       "4                   3                     3                 5            15  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df[[\"Age\",\"Experience\",\"Target Given\",\"Target Achieved\",\"Performance Differential\",\"Performance rating\",\"Content Satisfaction\",\"Sourcing Channel\",\"Hours of trg\"]]\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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",
      "text/plain": [
       "<Figure size 2400x2400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation=df1.corr()\n",
    "plt.figure(figsize=(24,24))\n",
    "sns.heatmap(correlation,annot=True,cmap='viridis')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Relationship Between colleagues')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled= scaler.fit_transform(df[['Experience','Performance rating']])\n",
    "\n",
    "scaled_df = pd.DataFrame(scaled, columns=['Experience','Performance rating'])\n",
    "k_opt=3\n",
    "model = KMeans(n_clusters=k_opt,random_state =42,n_init=20)\n",
    "model.fit(scaled_df)\n",
    "\n",
    "scaled_df['labels'] = model.labels_\n",
    "cluster_centers = model.cluster_centers_\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(scaled_df['Experience'], scaled_df['Performance rating'] , c=scaled_df['labels'], cmap='viridis')\n",
    "plt.title('K-means Clustering')\n",
    "plt.xlabel('Job Satisfaction')\n",
    "plt.ylabel('Relationship Between colleagues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Relationship Between colleagues')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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itcjOysbPszZh49e/4uGdJABAeKXi6PFBR7To04QNMBE9s7OJNzHs2FIkZqcZj2kgoF3xOvioemcFk/1LkCRJUjpEQZacnAw/Pz8kJSXB19fXIefoXnwQEuIScx1zcXPBuvtL4OHt4ZBzE5H6GfQGTOwwA0d2xEAS//3IFwRAkoCe4zphwKevKZiQiAq7s4k30e+v/5kdrxdYFl/XG+iw89var3GOr8J++GSN2aYXAPRZeoxvN12+QESkOjtX7MXhX0+YNL3A46YXAH6ath6xMVcUSEZEajHs2FKL44cTLuFKyl15wljAxldha2Zvtlpz6s9zMiQhIrXaNP9XCBrzUxm0LhpsW/i7jImISE0SslJMpjeYM/nkGhnSWMbGV2HpjzKs1jx9lYaIyB43Lty2+Dli0Iu4euaGjImISE1iEmz7jVFc+kMHJ7GOja/CNFq+BUTkWO6elleIETQCPH14HwER5U2Qzs+mOjeN8msqsOtSWMW6Za3W+AU55qY6InIOTXs0gsbF/Me9JEpo3LWhjImISE2qB5SEBtZXhulaqoEMaSxj46uwD38aZrXmva8ddxckEalf56Ft4aZzhSaXeb5aFw3CyoagSTc2vkSUd+2K17E47iJo0bdMU3nCWMDGV2EhJYMwfvVws+M9P+yMJl0jZUxERGpTrEwIZvw2Ab5FfAAAWlcttC5aAI/X8p0VPQk6bphDRM/go+qdUS8w999iuwha/NTofZkT5Y7r+Fohxzq+AJCVlYV5by3CkV9PQBQlVKhTBh/88D78An0cdk4ici7ZWdnYt+4wzh+6CK2LBnWjaqF2s+rcvIKI8s2VlLuYfHIN4tIfwk3jgi4lG6B/2aYOP6+t/RobXyvkanyJiIiIKG+4gQURERER0X+w8SUiIiIip8DGl4iIiIicAhtfIiIiInIKbHyJiIiIyCkov3ccGcVduYPtS3bDoDfghc71Uen5ckpHIiKVuXvjPi4euwytixZVG1WET4C30pGISGX23j2LvxOuwdvVA13C68HXzVPpSEZczswKOZYzS0lMwfDGE3H19A2T44HFAjDz94koVbmEQ85LRM7j4d0kzH3zWxzcdBRPPvZddS5oM6g5Bs/qAzedq8IJiaiw2xN/BpNOrUG6Icvk+AtBFfF57deh0ThuogHX8c0njm589Xo9eoQNRtL9R7mOu7hqsfzSfASVKJLv5yYi55CalIp3641D/JU7MOhFkzFBI6Bem+cwZcMYh/6jRETqdvDeRQw99r3Z8Rr+JbG4wVsOOz/X8S0kfpq2wWzTCwD6bAO+fGeRjImISG02L9iJ25ficzS9ACCJEg5tOYYT0acUSEZEavHZmXUWx08mXsfZpJsypTGPja/Cti3aabXm6I4YxwchItXatuh3SKL5X+5ptBrsWLpbxkREpCb3Mx7hTkaS1bpvL1rveRyNja/CUhPTrNbosw0yJCEitUqIf2hxXDSIuHfjgUxpiEhtbqTZ9vlxL8P8b7jlwsZXYZ5+HlZrtC5aGZIQkVr5B/tZHNdoNSgSFiBTGiJSmzBP2z4/iuiUX0WGja/Covq9bLWmdrNqMiQhIrVqPaAZBI1gdlw0iGjZ9yUZExGRmoS4+yFIZ30BgMHlmsuQxjI2vgrrNaELvPzNr2+nddFg2ILBMiYiIrVp905LBIcXhdYl50e+RiOg9svVUDeqpgLJiEgtRldpb3G8km8YqgeUlCmNeWx8Febm5orvz89DsTIhOcZ8Ar3x5V/TEFIqWIFkRKQWvoE+mLvvE9RsWtXkuMZFg+Z9mmDKprFcyoyInknTkCqYXL0r3DQ590Z7LjACSxy4lJk9uI6vFXJsYPHE5ZNXsW3xLhiy9WjUuT7qtuAVGCLKXzf/uY3zh2OhddGi1ktVERDir3QkIlIRURSxLe4ETj68Dh8Xd/Qs/QKKuvs4/LzcwCKfyNn4EhEREZH9uIEFEREREdF/sPElIiIiIqfAxpeIiIiInAIbXyIiIiJyCmx8iYiIiMgpFKrGd+/evWjXrh3CwsIgCAI2bNhgsX7Pnj0QBCHHV3x8vDyBiYgKkKysbHw/YRWGvTAeI5tOwtZFOyGKotKxiEhFErNSMO30Bgz86xsMObIEB+5eUDqSiZyrDBdgqampqFmzJgYMGIDOnTvb/LwLFy6YLG0RHMwNIYjIuUT/+Cdm9v0aouHfRvfk3rNYMGIZ5vz5CcrVilAwHRGpwVcXtmPFlb0mxw4/iEWwzhc/NBoCfzdvhZL9q1A1vq1bt0br1q3tfl5wcDD8/f3zPxARUSFw9uAFTO/9Za5jGamZeK/Bh1h79zt4+ZrfPp2IyJJVV/fnaHqfuJuZjNf2f4VtL42TOVVOhWqqQ17VqlULxYoVQ4sWLbB//36LtZmZmUhOTjb5IiIqzL5+b4nFcX2WHks+/FGmNESkRotioy2O3898hD3xZ2RKY56qG99ixYphwYIF+OWXX/DLL78gPDwcTZs2xfHjx80+Z9q0afDz8zN+hYeHy5iYiCj/xcZcsVqzd+1fMiQhIjW6kfoAj/QZVut+vLZPhjSWFaqpDvaqWLEiKlasaHwcGRmJS5cuYc6cOVixYkWuzxk3bhxGjBhhfJycnMzml4gKNUm0vjN9VkaWDEmISI3uZz6yqS5Vn+ngJNapuvHNTb169bBvn/n/49DpdNDpdDImIiJyLFd3V2RnZFusKVIsQKY0RKQ2Zb1tWzSgpGdRByexTtVTHXITExODYsWKKR2DiEg2L3aub7Wmx9iOjg9CRKrk6+ZpU/P7fkX7FyjIb4Wq8U1JSUFMTAxiYmIAAFeuXEFMTAyuX78O4PE0hT59+hjr586di40bNyI2NhanT5/GsGHDsGvXLrz77rtKxCciUsTQBYPh5W9+xYaytUqjZd+XZExERGrzac2e0Arm28q2Yc+hmKfyv1kqVI3v0aNHUbt2bdSuXRsAMGLECNSuXRsTJ04EAMTFxRmbYADIysrCyJEjUb16dTRp0gR///03fv/9dzRr1kyR/ERESvD09sAPl+ejSmQFk+MarQZNukXif0dnKJSMiNSijE8IVkQOyTGdQadxRf8yTTGpxqsKJTMlSJJk/a4HJ5acnAw/Pz8kJSWZbIJBRFQYpSan4eTec9B5uKJGkypwcXG6Wz2IyMHuZSTjTNJNFHHzRvWAkrKc09Z+jY2vFWx8iYiIiAo2W/u1QjXVgYiIiIgor9j4EhEREZFTYONLRERERE6BjS8REREROQU2vkRERETkFLiOTQFx9uAFTOn6BR7EPQQAePl6Ysj8N9D8tRcVTkZEanH/1gNsXfg7zh++CK2LFnVb1kKLPo3h5eeldDQiUompp9Zhy61jEPF40bBgnS8W1X+zQGxeAXA5M6vkWM5s1oD5+G3pnlzHytWOwDfHZjrkvETkPPas3o/pfb6CJEoQDSIgPD7uE+CNadvHo2LdssoGJKJCr9GOCciWDLmODa/YFj0jGjns3FzOrJA4vuuk2aYXAGJPXME3w5fKloeI1Cf2xBVM6/0lDNmGx00vAEiPv1KTUjEuaipSElMVzUhEhVvb3dPNNr0AMOfCVmRnZ8uYKHdsfBU27bUvrdZsnP+rDEmISK3WztkMQch9TDRISElMxW/L9siaiYjUIzs7G/cyk63WvX30OxnSWMbGV2GJd5Os1hj0ogxJiEitDm09bvFzRJIkHN52XMZERKQmW+Js+/w4k3TTwUmsY+NLRKRy+mzzv358IitT+V9BElHhlJSdblOdBOVvK2PjqzCdp5vSEYhI5So+XxYarfmPe41Wg8r1K8iYiIjUpH2xOjbVFdX5ODiJdWx8FdZrwqtWa6q9WEmGJESkVp3fb/vvTW25kSS88mYL+QIRkaoEevrATWN9hdxv6r8hQxrL2PgqrOcHnRAaEWx23M3dFbOiJ8mYiIjUpmH7uuj4XmsAMLnyq3XRQBAEDF/0NoqVCVEqHhGpwE8vvG9xvLZ/aYR7FpUpjXlsfAuAFZfmo0n3SAhP3XZdqX55bExeDhcX7jNCRHknCALemdsfE9eOQtVGFeHq7gp3Lx0iO9TD3H2foFX/l5SOSESFXLhnUWxsPBq+Lh4mxzUQ0KNkJL5tMFihZKa4gYUVcmxgQURERER5xw0siIiIiIj+g40vERERETkFNr5ERERE5BTY+BIRERGRU2DjS0REREROgY0vERERETkFLhBbQET/+CeWTlyFO1fuQgLgV9QXrw5/BT3GdlI6GhGpxMrPfsH6uVuR9OARBAgIjQhG/0974qXujZSORkQqkG7Iwoijy3H84RVIeLxabqCbN8ZUaYeXQ6srnO4xruNrhRzr+H75ziJsXvBbrmPVXqiEOXs/cch5ich5DH3hI5w98E+uYx2GtMaQLwfInIiI1CQlKx1Ruz9DtmTIdXxAmaZ4q0JLh52f6/gWEif3njHb9ALA6X3n8eO0dTImIiK1WfHJWrNNLwBs/PpXnD14QcZERKQ2ff/6n9mmFwCWXN6DlKx0GRPljo2vwhZ98IPVmnVzt8qQhIjUav08658hC0evkCEJEalRuiELN9IeWK2bcOpnGdJYxsZXYdfP3rJak3QvWYYkRKRWjxJSrNZcPXNDhiREpEZH7sXaVHcm8aaDk1jHxldhgkawocjxOYjIuWm0/KAhorxx1dq2VoJGUP5zho2vwio3KG+1JqRUkAxJiEitgsKLWK2p3KCCDEmISI3qBZa1qS6yqPKfM2x8FfbW7H5Wa/pN6e74IESkWn0md7Na886c/jIkISI10mq1qOFf0mrd2KrtZUhjGRtfhZWqXMLiMkJtBjVH895NZExERGrTqv/LaDXgZbPj781/A8XLF5MxERGpzbfPD0Kgm7fZ8U9r9oSb1k3GRLnjOr5WyLGOL/D4xpIFI5fh/KGLEA0iSlYujoHTeqH2ywVjwWciKvyOR5/Ed+N+xI3zt6DRalC5YQW89UVflKpcQuloRKQS317ciVVXDyDNkAWNIKCKb3F8UrM7wjwDHXpeW/s1Nr5WyNX4EhEREVHecAMLIiIiIqL/YONLRERERE6BjS8REREROQU2vkRERETkFNj4EhEREZFTsG2POZKFwWDAsd9PQZ+ZhdotasLDQ6d0JCJSmfT0TJzY+Td0HjrUerkatFqt0pGISGXiMxKx/+55FHMPQGRwRaXjmGDjWwAYDAaMemkyTu87b3I8rFwo5h+ZBm8/8wtCExHZIinhEd6rNw5xl++YHK/euApmRU9kA0xEz+zw/ViMOL4cWaLe5HjDIhUw7/l+yoR6CtfxtUKOdXy7Fx+EhLjEXMdc3Fyw7v4SeHh7OOTcRKR+6Snp6FykP/TZhlzHixYPxE83vpU5FRGpyeH7sRhydInZ8TJewVj14jCHnZ/r+BYSP3yyxmzTCwD6LD3Gt5suXyAiUp0P23xmtukFgPu3ErBqxnoZExGR2ow4vtzi+OXUuziTeEOmNOax8VXYmtmbrdac+vOcDEmISK3O7L9gtWb1zI0yJCEiNYrPSMwxvSE342J+kiGNZWx8FZb+KMNqjSRyNgoR5Z0tM9rSktNlSEJEarT/7nnrRQASslIcnMQ6Nr4K02j5FhCR8jQaQekIRFRIFXMPsKnORVC+51E+gZOrWLes1Rq/IMfcVEdEzsG3qI/VmsoNC9aSQ0RUeNi6ZNkrxZ9zcBLr2Pgq7MOfhlmtee/rgY4PQkSq9e7c/lZrxq18X4YkRKRWDYtUsFozqkp7GZJYxsZXYSElgzB+9XCz4z0/7IwmXSNlTEREavPyay+i25gOuQ8KwKRfRiGoeBF5QxGRqsx7vh/KeAWbHV/e4F0Z05hXqBrfvXv3ol27dggLC4MgCNiwYYPV5+zZswfPPfccdDodypUrh6VLlzo8p72adI3E1oyVaNmvKQJC/OAX5IvnW9XC2vtLMGBqT6XjEZEKDJreG2vvL0GdljXhF+SLgBA/tB74MrZnrcILneorHY+IVGDVi8PwfYO3EeruDzeNCzy1bng1vAEOt/oMlfyLKx0PQCHbwOLXX3/F/v37UadOHXTu3Bnr169Hx44dzdZfuXIF1apVw1tvvYU33ngD0dHRGDZsGLZu3YqoqCibzinHBhZERERElHe29muFasvi1q1bo3Xr1jbXL1iwABEREfjiiy8AAJUrV8a+ffswZ84cmxtfIiIiIlKHQjXVwV4HDx5E8+bNTY5FRUXh4MGDZp+TmZmJ5ORkky8iIiIiKvxU3fjGx8cjJCTE5FhISAiSk5ORnp77Yu3Tpk2Dn5+f8Ss8PFyOqERERETkYKpufPNi3LhxSEpKMn7duKH8vtJERERE9OwK1Rxfe4WGhuLOnTsmx+7cuQNfX194eHjk+hydTgedTidHPCIiIiKSkaob34YNG2Lbtm0mx3bu3ImGDRsqlMiyuCt3sH3Jbhj0BrzQuT4qPV9O6UhEpDK/fvc7ti3eBRc3Lfp90gM1G1dVOhIRkWwKVeObkpKC2NhY4+MrV64gJiYGgYGBKFmyJMaNG4dbt25h+fLlAIC33noLX3/9NcaMGYMBAwZg165d+Pnnn7F161alvoVcpSSmYHjjibh6+t9pFatnbEBgsQDM/H0iSlUuoWA6IlKD/RsP4+POs/DfBSxHNZ0MV50Lll38CkEliioXjohIJs88xzc5ORkbNmzAuXPn8iOPRUePHkXt2rVRu3ZtAMCIESNQu3ZtTJw4EQAQFxeH69evG+sjIiKwdetW7Ny5EzVr1sQXX3yBxYsXF6ilzPR6PfpVeN+k6X0iIe4h3qo1CvduPlAgGRGpxdmDFzC5k2nT+0R2ph6vlXobGRkZ8gcjIpKZ3RtYdOvWDY0bN8aQIUOQnp6OmjVr4urVq5AkCatWrUKXLl0clVURjt7AYsUna7F80mqLNQ1eqYNPNo3N93MTkXPoEjwAyfcfWayp27Impm0fL1MiIqL8ZWu/ZvcV37179+LFF18EAKxfvx6SJCExMRFffvklpk6dmvfETmrbop1Wa47uiHF8ECJSLWtNLwAcjz4pQxIiImXZ3fgmJSUhMDAQALB9+3Z06dIFnp6eaNu2LS5evJjvAdUuNTHNao0+2yBDEiJyZqKh0OxeT0SUZ3Y3vuHh4Th48CBSU1Oxfft2tGzZEgDw8OFDuLu753tAtfP0y31Ztf/SumhlSEJEzkzQCEpHICJyOLsb32HDhqFXr14oUaIEihUrhqZNmwJ4PAWievXq+Z1P9aL6vWy1pnazajIkISK18vb3slpTowmXNSMi9bP75jbg8eoKN27cQIsWLeDt7Q0A2Lp1K/z9/dGoUaN8D6kkR9/clpWVjW6hb5id8qB10WDZxa8QUio4389NRM7h+K6T+KD5JxZrNqet4G/tiKjQctjNbQBQt25dtG3bFrdu3YJerwcAtG3bVnVNrxzc3Fzx/fl5KFYmJMeYT6A3vvxrGpteInomz71cA2OWvpvrmNZFg+/OzWXTS0ROwe4rvmlpaXjvvfewbNkyAMA///yDMmXK4L333kPx4sUxdqy6lt1y9BXf/7p88iq2Ld4FQ7YejTrXR90WNR16PiJyPj9++guif9wHrYsGfSZ3wwud6isdiYjomdnar9nd+A4dOhT79+/H3Llz0apVK5w8eRJlypTBxo0bMXnyZJw4ceKZwxckcja+RERERGQ/W/s1u7cs3rBhA1avXo0GDRpAEP69C7hq1aq4dOlS3tISERERETmY3XN87927h+DgnHNOU1NTTRphIiIiIqKCxO7Gt27duti6davx8ZNmd/HixWjYsGH+JSMiIiIiykd2T3X47LPP0Lp1a5w9exZ6vR7z5s3D2bNnceDAAfzxxx+OyEhERERE9MzsvuL7wgsvICYmBnq9HtWrV8dvv/2G4OBgHDx4EHXq1HFERiIiIiKiZ5anDSyciVyrOuj1eszsOx+Hth6DJEkoVzsCU7aMg7e39S2NiYhskZWVjZWf/IK/d5+G1kWLl3u9gNYDm0GjydOS7kREOSRmpeCbf35HbEocPLQ6vFaqESKDKzr8vA5bzuz69esWx0uWLGnPyxV4cjS+O5fvwcx+83Md6/BuFIZ89YZDzktEziP6xz8xs+/XEA2iyXF3Lx3m/PkJytWKUCgZEanFVxe2Y8WVvTmOB+t88UOjIfB383bYuR3W+Go0GourNxgMBntersBzdOMbf/UuXi+T+45KT4xc8g5a9Xsp389NRM7h7MELGNpovNlxFzcXrL37Hbx8PWVMRURqsurqfsw+v9XseFGdD7a9NM5h53fYlsUnTpzA8ePHjV+HDh3CggULUKFCBaxZs+aZQjujD1t/arVm/nvfyZCEiNTq6/eWWBzXZ+mx5MMfZUpDRGq0KDba4vj9zEfYE39GpjTm2b2qQ82aObfRrVu3LsLCwjBr1ix07tw5X4I5ixv/3LZak5GaKUMSIlKr2JgrVmv2rv0L733NaVVEZL8bqQ/wSJ9hte7Ha/vQNLSqDInMy7c7GipWrIgjR47k18s5D95aSEQOJonWP2iyMrJkSEJEanQ/85FNdal65S/k2X3FNzk52eSxJEmIi4vD5MmTUb58+XwL5iy0LhoY9KL1QiKiPHJ1d0V2RrbFmiLFAmRKQ0RqU9Y7546+uSnpWdTBSayz+4qvv78/AgICjF+BgYGoUqUKDh48iG+++cYRGVXtpZ4vWK0pViZEhiREpFYvdq5vtabH2I6OD0JEquTr5mlT8/t+xdYypLHM7lUdnt6dTaPRICgoCOXKlYOLi90XkAs8OZYza+PRE9mZerPja+4ugn9Rf4ecm4jULy0lHa+VfAupiWm5jpetVRoLjs+SORURqcnlR3fQ68BXMEi5/xa7bdhzmFTjVYed32HLmTkbORpfvV6P1yPexf1bCSbHPXzc8d2ZOQgqofyvBoiocEtJTMFHr0zD2QP/GI9ptBq82KUBPvxxKDexIKJnFvsoHmNP/IjrafeNx3QaV7xWuhHertDSoed2WOO7adOm3F9IEODu7o5y5cohIkI9C6HLtXMbAGRkZGD9vF+RmZaJV96OQtFQzrkjovyVmpyGk3vPQefhihpNqqjyN3VEpKx7Gck4k3QTRdy8UT1Ano3NHL6BxdNPe3JMEAS88MIL2LBhAwICCn/jJmfjS0RERET2c9gGFjt37sTzzz+PnTt3IikpCUlJSdi5cyfq16+PLVu2YO/evXjw4AFGjRr1TN8AEREREVF+svt3XEOHDsXChQsRGRlpPNasWTO4u7tj8ODBOHPmDObOnYsBAwbka1AiIiIiomdh9xXfS5cu5XoJ2dfXF5cvXwYAlC9fHvfv389RQ0RERESkFLsb3zp16mD06NG4d++e8di9e/cwZswYPP/88wCAixcvIjw8PP9SEhERERE9I7unOnz33Xfo0KEDSpQoYWxub9y4gTJlymDjxo0AgJSUFIwfPz5/kxIRERERPYM8reMriiJ+++03/PPP4/UgK1asiBYtWqhyHUi5VnVITUrFb8v+wNHf/oZoMKBKg4poPagZioYFOuycRORcDm87hnnvLMaDuIcQBKBk5XCMW/EeSleTZ7khIlK/PXfOYlHs77iTngQ3jQteCqmKdyu2hKeLu0PPyw0s8okcje/5wxcxttVUpCWlQ4IESI+XjdNoBYz9YSiadG3okPMSkfP4sM2nOLI9Jtex1yd1RZ9J3eQNRESq8+ahhTjx8GqO4y6CFosbvIkqfiUcdm6HNr6pqan4448/cP36dWRlZZmMvf/++/anLcAc3fgmJzxCn3JDkJ6cAVF8aps/4XED/L+jM1C2Zul8PzcROYefpq3Dko9+sljz7d+zUKZ6aXkCEZHqzDizEb/cOGR2XKdxwR/NJztsdoCt/Zrdc3xPnDiBNm3aIC0tDampqQgMDMT9+/fh6emJ4OBg1TW+jrbj+z1IS06HJOby/x8SIAjA+nlbMWrJu/KHIyJV+PGzdVZrpvf+Cgv//kKGNESkNqIoYtPNoxZrMkU9Vl87gJ4RL8iUKnd2t93Dhw9Hu3bt8PDhQ3h4eOCvv/7CtWvXUKdOHXz++eeOyKhqh7cdz73p/X8GvYiDm4/JmIiI1CYjNdNqzfVzt2RIQkRqFJtyB9mSwWrdjviTMqSxzO7GNyYmBiNHjoRGo4FWq0VmZibCw8Mxc+ZMfPjhh47IqGrZmdlWa/TZehmSEJEz4+0eRJRXmQbrvQwA6EXrzbGj2d34urq6GudnBAcH4/r16wAAPz8/3LhxI3/TOYHKDSpAozX/Nmi0GlSqV07GRESkNhoX6x/1/sGOW7WGiNStvE8oBBvqavgrv4KM3Y1v7dq1ceTIEQBAkyZNMHHiRKxcuRLDhg1DtWrV8j2g2rV9s4XFKy2iQUSn99vKmIiI1KZR++et1rw5q48MSYhIjdxd3PBcYITFGgHAOxWj5Alkgd2N72effYZixYoBAD799FMEBATg7bffxr1797Bw4cJ8D6h2JcoXw7BvBgMCoP3PVZknV4G7DH8F9ds+p1Q8IlKBj1YPh28Rb7Pj1V6ohJdfe1HGRESkNrOeex0+Lh5mx0dUegXeDl7L1xZcx9cKuTawOL3/PH6ZvRlHf/sbBoOIyvXLo/PQtojs8DwEwZZfIBARmWcwGPBxl89xaOtxiIbHSye6ubui4/ttMGh6b4XTEZEapOkz8NnpDdh954zxZrcIr2AMq9QWDYPKO/TcDl3HV6/XY8+ePbh06RJee+01+Pj44Pbt2/D19YW3t/mrCoWRXI0vEREREeWNw9bxvXbtGlq1aoXr168jMzMTLVq0gI+PD2bMmIHMzEwsWLDgmYITERERETmC3XN8hw4dirp16xrX8X2iU6dOiI6OztdwRERERET5xe4rvn/++ScOHDgANzc3k+OlS5fGrVtcAJ2IiIiICia7r/iKogiDIecCxDdv3oSPj0++hCIiIiIiym92N74tW7bE3LlzjY8FQUBKSgomTZqENm3a5Gc2IiIiIqJ8Y/eqDjdv3kRUVBQkScLFixdRt25dXLx4EUWLFsXevXsRHBzsqKyK4KoORERERAWbw5czW7VqFU6ePImUlBQ899xz6NWrl8nNbmohV+O78tNfsGrGemSkZAIAXNy0aN6rMUZ+947DzklEzmVm/6+x+8d90Gc/nq7m7u2OXh91Ro8POimcjIjUICk7DT3/nIf7WY+Mx7TQYFC5lzGg3MsOPbdDG18lzZ8/H7NmzUJ8fDxq1qyJr776CvXq1cu1dunSpejfv7/JMZ1Oh4yMDJvPJ0fjO6b5FJzYdSrXsaDwIvjxGpeII6Jn0zP8Tdy/lZDrWJ2WNTF9+3iZExGRmtxPS0KbvTPMjr9QtCJm1+3rsPPn6zq+mzZtsvnE7du3t7nWXqtXr8aIESOwYMEC1K9fH3PnzkVUVBQuXLhgdoqFr68vLly4YHxc0HZB2716n9mmFwDu3XiAWQPmY/SSd2VMRURqMr3PV2abXgA49tvf2Lf+EF7oVF/GVESkJp32zbY4vu/+BdxPS0JRTz+ZEuXOpiu+Go1t98AJgpDrig/5pX79+nj++efx9ddfA3i8wkR4eDjee+89jB07Nkf90qVLMWzYMCQmJub5nI6+4tu9+CAkxCVarHFx1eLXzFX5fm4icg6t3HrAoLf82Vy0RCB+uv6tTImISE2SstPQInqq1bowjwBsaDLaIRls7dds6mhFUbTpy5FNb1ZWFo4dO4bmzZv/G16jQfPmzXHw4EGzz0tJSUGpUqUQHh6ODh064MyZMxbPk5mZieTkZJMvR0q8k2S15sl8PCKivLDW9AKw+j/gRETmbLp+xKa6O+mJjg1iA7uXM1PK/fv3YTAYEBISYnI8JCQE8fHxuT6nYsWKWLJkCTZu3IgffvgBoigiMjISN2/eNHueadOmwc/Pz/gVHh6er99HDgVs6gUROSd+FBFRXum0btaLAADKf9DYNMf3yy+/tPkF33///TyHyW8NGzZEw4YNjY8jIyNRuXJlfPvtt/jkk09yfc64ceMwYsQI4+Pk5GSHNr/FygTj1sXcG/cndF46h52fiNTPzcMNWelZFmvCyoXKlIaI1KZT8br4/Pxmq3XlfJT/nLGp8Z0zZ45NLyYIgsMa36JFi0Kr1eLOnTsmx+/cuYPQUNt+kK6urqhduzZiY2PN1uh0Ouh08jWao5a8i+EvTrBY02NMB5nSEJEavTriFfz46TqLNR8sfU+mNESkNq6urghw9cLD7FSLdd/WGyhTIvNsmupw5coVm74uX77ssKBubm6oU6cOoqOjjcdEUUR0dLTJVV1LDAYDTp06hWLFijkqpt2qNaqEzkPN73hXo0kV9J7QVcZERKQ2/T/piWovVjY73mXEK6hYr5yMiYhIbbY0HgOthbZyUNlm8HRVfr+HZ1rH98lT5VoibPXq1ejbty++/fZb1KtXD3PnzsXPP/+M8+fPIyQkBH369EHx4sUxbdo0AMCUKVPQoEEDlCtXDomJiZg1axY2bNiAY8eOoUqVKjadU64NLE7uPYsv3vgG8VfuQpIk+Af7YfDM3mjeu4nDzklEzuW35Xuw+IMfkHgvGYIgoFjZEIz67h1Ua1RJ6WhEpBIjjy3Hn/fOGx/7u3pibp2+qOLv2Hum8nUd36ctX74cs2bNwsWLFwEAFSpUwOjRo/H666/nLa2Nunfvjnv37mHixImIj49HrVq1sH37duMNb9evXzdZeu3hw4cYNGgQ4uPjERAQgDp16uDAgQM2N71yqtG4Cpb985XSMYhIxVr2aYqWfZoqHYOIVOyLOn2UjmCR3Vd8Z8+ejQkTJmDIkCFo1KgRAGDfvn2YP38+pk6diuHDhzskqFLkuuJLRERERHnjsC2LIyIi8PHHH6NPH9OOftmyZZg8eTKuXLmSt8QFFBtfIiIiooItXzew+K+4uDhERkbmOB4ZGYm4uDh7X46IiIiISBZ2N77lypXDzz//nOP46tWrUb58+XwJRURERESU3+y+ue3jjz9G9+7dsXfvXuMc3/379yM6OjrXhpiIiIiIqCCwu/Ht0qULDh06hDlz5mDDhg0AgMqVK+Pw4cOoXbt2fudzKnq9Hnt+Pojs9Ey82L0RvL2VX++OiNQlKysbl05cgavOFWVqlDJZCYeIKD/EZyRi/93zKOYegMjgikrHMfFM6/g6AzlubtPr9Xij6vAcWxf7BHpjyfk58C/q75DzEpHzSEtJx+ROsxCz+zQk8fHHvoubC1q83gTDvh3MBpiIntnh+7EYcXw5skS9yfGGRSpg3vP9HHpuh63qsG3bNmi1WkRFRZkc37FjB0RRROvWrfOWuICSo/Ft59MbGamZuQ8KwPoH38Pb39sh5yYi9cvKyMJrJd9G0v3kXMerRFbAvH2fypyKiNTk8P1YDDm6xOx4Ga9grHpxmMPO77BVHcaOHQuDwZDjuCRJGDt2rL0v5/Tmvf2t+aYXACTg/YYfyReIiFTny3cXm216AeDsgX+we/V+GRMRkdqMOL7c4vjl1Ls4k3hDpjTm2d34Xrx4MdedzypVqoTY2Nh8CeVMfl2y22rNjQu3ZUhCRGq1Z5X1pnblJ2tlSEJEahSfkZhjekNuxsX8JEMay+xufP38/HD58uUcx2NjY+Hl5ZUvoZyJITvn1XMiovyUmZ5ltebezQcyJCEiNdp/97xNdQlZKQ5OYp3djW+HDh0wbNgwXLp0yXgsNjYWI0eORPv27fM1nFMQlA5ARGonCNY/aNx0rjIkISI1KuYeYFOdi6D8TbR2J5g5cya8vLxQqVIlREREICIiApUrV0aRIkXw+eefOyKjqhWLCLFa4+bhJkMSIlKriBolrdY0bP+8DEmISI1sXbLsleLPOTiJdXma6nDgwAFs3boV77zzDkaOHIno6Gjs2rUL/v7+DoioblO3jrNaM3hmbxmSEJFavTOnv8VxrYsWb8zoJVMaIlKjhkUqWK0ZVUX5mQFcx9cKOZYz2zj/V3z9Xu5LgLTo2xRjvn/XIeclIuexddFOzHtrEZ7+yHfVueDzXZNRpWHBWmSeiAqfHn/OxeXUu7mOLW/wLir5F3fYuR22jq+zkaPxBYCMjAxM6jALZ/afhyQBJSoUw6e/foSiobbNmyEisiYtJR1LPvwJZ/adh8ZFg8avNkDXUe25eQUR5ZsziTcwLuYnJGSlwEXQoE3YcxhT1fFXetn45hO5Gl8iIiIiyhuHbWBBRERERFQYsfElIiIiIqfgkpcniaKI2NhY3L17F6Iomow1btw4X4IREREREeUnuxvfv/76C6+99hquXbuW4+5gQRBgMHAnMiIiIiIqeOxufN966y3UrVsXW7duRbFixWzaEYiIiIiISGl2N74XL17E2rVrUa5cOUfkcWpxV+5g+5LdMOgNeKFzfVR6nj9jIspfd2/cx8Vjl6F10aJqo4rwCfBWOhIRqczllDu4lnIPHi461A4oDZ224GyJbnfjW79+fcTGxrLxzUcpiSkY3ngirp6+YTy2esYGBBYLwMzfJ6JU5RIKpiMiNXh4Nwlz3/wWBzcdNU5Tc9W5oM2g5hg8qw/cdAXnHyYiKpwuPYrHp6fX43TSv/2Mj4s7+pd9Cb1Kv1AgZgnYvY7v+vXrMX78eIwePRrVq1eHq6vph2WNGjXyNaDSHL2Or16vR4+wwUi6/yjXcRdXLZZfmo+gEkXy/dxE5BxSk1Lxbr1xiL9yBwa96Q3JgkZAvTbPYcqGMdzIgojy7FrqffQ7MB/phiyIyNla9i/TFG9XaOmw89var9l9xbdLly4AgAEDBhiPCYIASZJ4c1se/DRtg9mmFwD02QZ8+c4ifLJprIypiEhNNi/YiduX4iGJOf8xkkQJh7Ycw4noU6jToqYC6YhIDRZe/B0ZYnauTS8ALLv8B7qUrI9gdz+Zk5myu/G9cuWKI3I4rW2LdlqtObojxvFBiEi1ti36Pdem9wmNVoMdS3ez8SWiPEnTZ2LXndMwSKLFul9vx6BvmSYypcqd3Y1vqVKlHJHDaaUmplmt0WfzKjoR5V1C/EOL46JBxL0bD2RKQ0Rqk5iVZrXp1QgC7mUky5TIQo68PGnFihVo1KgRwsLCcO3aNQDA3LlzsXHjxnwN5ww8/Tys1mhdtDIkISK18g+2/KtFjVaDImEBMqUhIrXxdfOABpZvXBMlCUV1PjIlMs/uxvebb77BiBEj0KZNGyQmJhrn9Pr7+2Pu3Ln5nU/1ovq9bLWmdrNqMiQhIrVqPaAZBI35f5REg4iWfV+SMRERqYm3izuahlSBVjDfVkoAWoXVki2TOXY3vl999RUWLVqEjz76CFrtv1ci69ati1OnTuVrOGfQa0IXePl7mh3XumgwbMFgGRMRkdq0e6clgsOLQuuS8yNfoxFQ++VqqBvF+b1ElHeDyjWHq6A1e+W3Z+lGCPXwlzdULuxufK9cuYLatWvnOK7T6ZCampovoZyJm5srvj8/D8XKhOQY8wn0xpd/TUNIqWAFkhGRWvgG+mDuvk9Qs2lVk+MaFw2a92mCKZvGcikzInomZX1C8G39wSjjbdqzuGtcMahcM7xfsZVCyUzZfXNbREQEYmJictzktn37dlSuXDnfgjmTgGB/LI/9GpdPXsW2xbtgyNajUef6qMs7rIkonxQtXgQzfpuIm//cxvnDsdC6aFHrpaoICPFXOhoRqURlv+JY2eh9nEu+hSspd+GpdUP9ouXh6aJTOpqR3Y3viBEj8O677yIjIwOSJOHw4cP46aefMG3aNCxevNgRGZ1GmRqlMeTLAdYLiYjyqESFMJSoEKZ0DCJSKUEQUMWvBKr4FcxdZ+1ufN944w14eHhg/PjxSEtLw2uvvYawsDDMmzcPPXr0cERGIiIiIqJnZveWxf+VlpaGlJQUBAerdw6qo7csJiIiIqJnY2u/lqe7GfR6PX7//XesWLECHh6P16G9ffs2UlJS8paWiIiIiMjB7J7qcO3aNbRq1QrXr19HZmYmWrRoAR8fH8yYMQOZmZlYsGCBI3ISERERET0Tu6/4Dh06FHXr1sXDhw+NV3sBoFOnToiOjs7XcERERERE+cXuK75//vknDhw4ADc3N5PjpUuXxq1bt/ItmLMRRRHbFkVj149/QjSIeK55dfT4sDPc3FyVjkZEKiEa0oHkcUD2cQAawL0t4DUCGi23RSei/BGXkIRJy37DtTsPoXN1Qb+WddH5xRpKxzKyu/EVRdG4TfF/3bx5Ez4+yu/BXBj9czQWI5pORmZapvHYmQMXsPLTdRi7/D281PMFBdMRkRqIKf8DUuaaHkxbBKQthuj/HTTu/JwhomczYsEm7Pn7ksmxqT9GY9aaPVg3uS+KBfoplOxfdk91aNmyJebOnWt8LAgCUlJSMGnSJLRp0yY/szmFlMQUDG003qTpfUI0iPis1zycPxKrQDIiUgsxfWfOptdIAhIHQDQkyBmJiFRmxurdOZreJzKzDeg0aZnMiXJnd+P7xRdfYP/+/ahSpQoyMjLw2muvGac5zJgxwxEZVW3RByuhz855Bf2/vn7vO5nSEJEqJU+0XpM4wvE5iEi11u792+J4lt6AldHHZEpjnt1THUqUKIG///4bq1atwsmTJ5GSkoKBAweiV69eJje7kW32bzhsteafo7n/HxQRkU2kB9Zrso84PgcRqdLZa3dgEK1vC7Ey+gR6NasjQyLz7G58AcDFxQW9e/fO7yxOKSs9y2qNZMN/TEREz8byb56IiMy5dT/RprqM7GzHBrGB3VMdSpYsiT59+uC7777D5cuXHZHJqQSE+lut0Xm4Wa0hInomgpfSCYiokKpVrrhNdaEByi+CYHfj+9lnn8Hd3R0zZsxAuXLlEB4ejt69e2PRokW4ePGiIzKqWvcxHazWNO7aUIYkRKRaLtWt13j2cXwOIlKlID9v+HrqrNZN7tNShjSWCZIk5fn36HFxcfjjjz+wZcsWrF692uxSZ4WZrXs/P4vBNUfiyqnruY55B3jhpxsL4O7p7pBzE5H6iYZE4F5DmJ3OIARAE3JIzkhEpDLHL97EG7PXmB2vWaYYvh/dw2Hnt7Vfs/uKLwCkpaXht99+w1dffYV58+Zh7dq1qFatGt5///08B3ZmC07MwouvNoBG+5+3QwCqRlbED1f+x6aXiJ6JRusPBO0FNCE5B12qAkUPyJ6JiNTlufIlsHBYF3i5m268JQBo/lx5hza99rD7im9kZCROnDiBypUro2nTpmjSpAkaN26MgIAAR2VUlBxXfJ/Q6/WI2X0G2Zl61GxaBZ7eXCWDiPKXaEgAMn4FBE9A1xYaLe8hIKL8de1OAg6euYbgQG+8XKu8LOd02BXf8+fPw8vLC5UqVUKlSpVQuXJlWZve+fPno3Tp0nB3d0f9+vVx+LDl5cDWrFmDSpUqwd3dHdWrV8e2bdtkSmo/FxcX1G1REw1fqcOml4gcQqMNhMarFzSendj0EpFDlAoJRI+Xa8vW9NrD7sb3wYMH2LVrFxo0aIAdO3agUaNGKF68OF577TUsWrTIERmNVq9ejREjRmDSpEk4fvw4atasiaioKNy9ezfX+gMHDqBnz54YOHAgTpw4gY4dO6Jjx444ffq0Q3MSERERUcHzTDe3SZKEY8eO4euvv8bKlSsdfnNb/fr18fzzz+Prr78GAIiiiPDwcLz33nsYO3Zsjvru3bsjNTUVW7ZsMR5r0KABatWqhQULFth0TjmnOhARERGR/Rw21eH48eOYPXs22rdvjyJFiqBhw4Y4efIk3nvvPaxbt+6ZQluSlZWFY8eOoXnz5sZjGo0GzZs3x8GDB3N9zsGDB03qASAqKspsPQBkZmYiOTnZ5IuIiIiICj+7d26rV68eateujSZNmmDQoEFo3Lgx/Pz8HJHNxP3792EwGBASYnpXckhICM6fP5/rc+Lj43Otj4+PN3ueadOm4eOPP372wERERERUoNjd+CYkJKj6V/7jxo3DiBEjjI+Tk5MRHh6uYCIiIiIiyg92N761atXCkSNHUKRIEZPjiYmJeO655xy2jXHRokWh1Wpx584dk+N37txBaGhors8JDQ21qx4AdDoddDrru4/kN0l8BKSvh5T5JwADBLfagEc3CNpc1t0kIsoDMesU8GgaoI8FoAHcngd8xkHjEqZ0NCJSiVW7TmDhr3/hUVomtBoNnitfHNMGtIFfAVmtyu45vlevXs31BrbMzEzcunUrX0Llxs3NDXXq1EF0dLTxmCiKiI6ORsOGuW/p27BhQ5N6ANi5c6fZeqVIWX9DutcU0qNPgay9QNY+SCnzId17CVLGr0rHIyIVEJOmAgldgOyjgJQISAlA5g7g/ksQ09crHY+IVKDNR4sxc80eJKZkwCBKyNIb8Ne563hp9ALsO31F6XgA7Ljiu2nTJuOfd+zYYTKv12AwIDo6GqVLl87XcE8bMWIE+vbti7p166JevXqYO3cuUlNT0b9/fwBAnz59ULx4cUybNg0AMHToUDRp0gRffPEF2rZti1WrVuHo0aNYuHChQ3PaQxITIT0cAEipAP67wIYIQIKUOBwoUhqCa2WFEhJRYSembwHSl5sZlYCksRBd60HjUlzWXESkHm/NXYv4hEdmx4fO34DDX78PrVYrY6qcbG58O3bsCAAQBAF9+/Y1GXN1dUXp0qXxxRdf5Gu4p3Xv3h337t3DxIkTER8fj1q1amH79u3GG9iuX78Ojebfi9iRkZH48ccfMX78eHz44YcoX748NmzYgGrVqjk0p13SfwGkFJg2vU9IADSQUpdB8J8uczAiUo1Hs60USMCjz4CA+bLEISJ1MRgMOHzhhsUaCcCsn/dgbM9m8oQyw+51fCMiInDkyBEULVrUUZkKFEev4ysm9AGy/rJcJARAE3Io389NRM5BjK9gvUjwgybkiOPDEJHqHD5/HW/N+8VqXRFfT+yc8aZDMtjar9l9c9uVK//O0cjIyIC7u3veEtJjUpYNRdkOj0FEzs5xmw8RkbqlZGTaVGcQ87xnWr6x++Y2URTxySefoHjx4vD29jau4jBhwgR89913+R5Q9VxrAbA030ULuNaQKQwRqZLgY73GpYzjcxCRKtWrWMqmuoolghycxDq7G9+pU6di6dKlmDlzJtzc3IzHq1WrhsWLF+drOGcgePbA4xvZzDFA8OxrYZyIyArP16zXeI9yfA4iUiVvDzeEFbE+HfTT/q1lSGOZ3Y3v8uXLsXDhQvTq1cvkzryaNWua3UGNzBNcSkPwnQJAgOmV3/9/azz7A7qm8gcjIvXwGg5oK5ofd+8Cja6BfHmISHWWj+kJrUYwO97jpVoI9PWUMVHu7G58b926hXLlyuU4LooisrM5FzUvBM/uEAJ/BHTNAMEDgBvgWheC/3wIPmMhCOb/QyIiskaj0QBFNgKeAwHB+z8DIYDPJ9D4T1MuHBGpQqCvJ36f8SaqlDTdeMvHQ4cJvZpjTLeXFEpmyu6b26pUqYI///wTpUqZzudYu3YtateunW/BnI3gVgeCWx2lYxCRSmk0GsD3g8dfREQO4OftgR/G2TC1SkF2N74TJ05E3759cevWLYiiiHXr1uHChQtYvnw5tmzZ4oiMRERERETPzO6pDh06dMDmzZvx+++/w8vLCxMnTsS5c+ewefNmtGjRwhEZiYiIiIiemd0bWDgbR29gQURERETPxtZ+ze4rvk+7fPkyzpw5A1G0tCQXEREREZGybG58s7OzMWnSJLRr1w6ffvopDAYDevbsifLly6NGjRqoVq0arl696sCoRERERER5Z3PjO3bsWHzzzTcIDQ3FkiVL0LlzZ5w4cQI//vgjVq1aBRcXF3z00UeOzEpERERElGc2r+qwdu1aLF26FG3atME///yDSpUqYevWrWjd+vEuHMHBwejVq5fDgqqdlH0GUupSIHMvAAPg+hwEr74QdI2UjkZEKiE+6AdkH/jPES3g8Ro0fhOUikREKnIvORntxy9FZrbB5HinyKqY8HpLhVKZsvnmNldXV1y9ehXFixcHAHh4eODkyZMoX748ACAuLg7h4eHQ6/WOS6sAOW5uk9I3QUoag8e7tz35j0X7+M9e70LjM9Qh5yUi5yHG1waQmvugtiI0QZtlzUNE6nLjXgI6TFxmdrx8WFGsnvC6w86f7ze3GQwGuLq6Gh+7uLiYbFms0WjABSLsJ+lv/H/TK+Lfphf//jl1PqTMfQokIyK1EB+8DrNNLwAYLkBMXS1bHiJSn46Tllscv3j7Pm7cS5ApjXl2bWCxY8cO+Pn5AXi8RXF0dDROnz4NAEhMTMz3cM5ASl+Fx1d6zdFCSl0GQfeCXJGISG2yD1mveTQd8Oru+CxEpDr3kpNtuvj52mc/4c8578qQyDy7Gt++ffuaPH7zzTdNHguCpQaOcpV1HKZXep9mALKPy5WGiJyWhSvCREQWLN56xKa61IwsByexzubGl+v0OoigtV4DW2qIiIiI5Oeps+s6qqKeeQMLejaC24uw/DZoAV1jueIQkSrZ8FEvBDo+BhGp0lttG9hUF+Tn6eAk1rHxVZpnV0Bwh/m3QoTg1U/GQESkOu4drdf4feHwGESkTjqdDm4u1n87vebDfo4PYwUbX4UJmkAIAYtyaX61ADQQ/KZDcK2mUDoiUgON/3RAU9p8gVtbaNy5ZjgR5d0fn79pcbx9w8rw9dXJlMY8m9fxdVZyrOMLAJLhAZC+BlLmnwD0gFsdCB49ILiUdNg5ici5iCmLgJSvAaQ/PiAEAH7ToXF/SdFcRKQePaauwD+37hsfu7poMOet9oisGuHQ89rar7HxtUKuxpeIiIiI8sbWfi3Pt+EdPXoU586dAwBUrlwZdevWzetLERERERE5nN2N782bN9GzZ0/s378f/v7+AB5vXhEZGYlVq1ahRIkS+Z2RiIiIiOiZ2X1z2xtvvIHs7GycO3cOCQkJSEhIwLlz5yCKIt544w1HZCQiIiIiemZ2z/H18PDAgQMHULt2bZPjx44dw4svvoi0tLR8Dag0zvElIiIiKths7dfsvuIbHh6O7OzsHMcNBgPCwsLsfTkiIiIiIlnY3fjOmjUL7733Ho4ePWo8dvToUQwdOhSff/55voZzNqJeDzFtE8TUNRD1KUrHISIVErOTID5aBDHlR4i5XMQgInpWl28/wJy1f2DdnyeVjpKD3VMdAgICkJaWBr1eDxeXx/fGPfmzl5eXSW1CQkL+JVWIHFMdRL0eSGgNiNdMBwR/oMiv0LgUcch5ich5iNm3gQdRADJNB4SiQOAf0Li6KpKLiNRj619nMWHZjhzHSwb7Y8PH/R16boctZzZ37txnyUW5uV8HxgXl/0tKBO5HQix6CBoXf5lDEZFaiNn3gQdNcx+U7gMPagGhZ+SMREQqY67pBYDrdxPRdOT/sOeLd2ROlZPdjW/fvn0dkcNpiUkTkWvTayQBD3sAQdvlikREapPQzkpBNsSHw6EJmCNLHCJSH3NN7xPJaZnYe/ISGtcoK1Oi3Nk0xzc5Odnkz5a+yE7pa63XGC47PgcRqZf0wHpN5q+Oz0FEqnT5tg2fMQDGLt7m4CTW2XTFNyAgAHFxcQgODoa/vz8EQchRI0kSBEGAwWDI95Dqplc6ABERAFHpAERUSG08cNqmuoxs5XsemxrfXbt2ITAwEACwe/duhwYiIiIiosKjVEiATXW5XDeVnU2Nb5MmTXL9M+UDTUlAvG6lSCdLFCJSKy0AK7+NE4rKkoSI1KfzizUw9cdoq3UNKpWUIY1ldt/cBgCJiYk4fPgw7t69C1E0/fVYnz598iWY0whcCNxvZbnG+wN5shCROnkOAtIWWK4JXCpLFCJSp5LB/rh+N9Fizfz3u8gTxgK71/HdvHkzevXqhZSUFPj6+prM9xUEQRVr9/6XLOv4pvwApEzJfVDXGZqA6Q45LxE5D/HBACB7X+6DXiOh8XlT3kBEpDpNR/4PyWmZuY59PaQjIqtGOOzctvZrdje+FSpUQJs2bfDZZ5/B09PzmYMWdHI0vgAg6jOApLeB7OMAREAbAQR8B41LkMPOSUTORcy+DST0BKS7AARAWxnwX8XNK4go3+w9eQljF29DRrYeggDUrxiO/w191eHndVjj6+XlhVOnTqFMmTLPHLIwkKvxJSIiIqK8sbVfs2kd3/+KiorC0aNHnykcEREREZHcbLq5bdOmTcY/t23bFqNHj8bZs2dRvXp1uD71K7L27dvnb0IiIiIionxg01QHjca2C8Nq3MCCUx2IiIiICjZb+zWbrvg+vWQZEREREVFhY/cc39wkJibmx8sQERERETmM3Y3vjBkzsHr1auPjrl27IjAwEMWLF8fff/+dr+GcjZh1FuLDYRAThkDM4NbQREREVPj8cfIS5q7biyXbDyM5LUPpOCbsXs4sIiICK1euRGRkJHbu3Ilu3bph9erV+Pnnn3H9+nX89ttvjsqqCFk2sDDcA+61AZD01IgbELgMGrc6DjkvERERUX7ZdeIiJizbgfTMbJPjL1aLwJy329t8z1heOGw5s/j4eISHhwMAtmzZgm7duqFly5YYM2YMjhw5kvfETko0ZAH3miBn0wsAWUBCT4hZl+SORURERGSzA2euYtTCLTmaXgD48/QVDPxijQKpcrK78Q0ICMCNGzcAANu3b0fz5s0BAJIkqW5FB1k8+hCA3nJN0hBZohARERHlxdSVOy2O/335Ns5euyNTGvPsbnw7d+6M1157DS1atMCDBw/QunVrAMCJEydQrly5fA/4REJCAnr16gVfX1/4+/tj4MCBSElJsficpk2bQhAEk6+33nrLYRnzJGOH9RoDr/gSERFRwXQ/KQXxDy33ZADwv00HZEhjmU3Lmf3XnDlzULp0ady4cQMzZ86Et7c3ACAuLg7vvPNOvgd8olevXoiLi8POnTuRnZ2N/v37Y/Dgwfjxxx8tPm/QoEGYMmWK8bGnp6fDMuZNzl8JEBERERUWN+4l2lR3L8l6c+xodje+rq6uGDVqVI7jw4cPz5dAuTl37hy2b9+OI0eOoG7dugCAr776Cm3atMHnn3+OsLAws8/19PREaGiozefKzMxEZmam8XFycnLeg9vEFUCm1SoiIiKigiisiJ9NdUV8vRycxDq7G18AuHjxInbv3o27d+/m2Nxi4sSJ+RLsvw4ePAh/f39j0wsAzZs3h0ajwaFDh9CpUyezz125ciV++OEHhIaGol27dpgwYYLFq77Tpk3Dxx9/nK/5LdI1AzK3Wa7RlpInCxEREZGdQgJ8EOTvjXuJlq/ovvlKA5kSmWd347to0SK8/fbbKFq0KEJDQyEIgnFMEASHNL7x8fEIDg42Oebi4oLAwEDEx8ebfd5rr72GUqVKISwsDCdPnsQHH3yACxcuYN26dWafM27cOIwYMcL4ODk52biKhUP4TgPu7QBg4cZAv68dd34iIiKiZzSu+0sY8e1ms+OVSwajZhnzv6GXi92N79SpU/Hpp5/igw8+eOaTjx07FjNmzLBYc+7cuTy//uDBg41/rl69OooVK4ZmzZrh0qVLKFu2bK7P0el00Ol0eT6nvTRaD4hFdwL3XwGQ9tSoFvBfCI1bRdnyEBEREdmraa1y+KRfK3zyw05k6U0v5tUpXwLfvN9FoWSm7G58Hz58iK5du+bLyUeOHIl+/fpZrClTpgxCQ0Nx9+5dk+N6vR4JCQl2zd+tX78+ACA2NtZs46sEjUsJIDQGYuZBIGURAD3g0QEaz4LxHwkRERGRNW3rV0br5yti66Fz+PvybXh76NC72XMo6uetdDQjuxvfrl274rfffsuXZcGCgoIQFBRkta5hw4ZITEzEsWPHUKfO413Mdu3aBVEUjc2sLWJiYgAAxYoVy1NeR9PoGgK6hkrHICIiIsoTjUaDdg2rol3DqkpHyZXdjW+5cuUwYcIE/PXXX6hevTpcXV1Nxt9///18C/dE5cqV0apVKwwaNAgLFixAdnY2hgwZgh49ehhXdLh16xaaNWuG5cuXo169erh06RJ+/PFHtGnTBkWKFMHJkycxfPhwNG7cGDVq1Mj3jERERERUsAmSJEn2PCEiIsL8iwkCLl++/MyhcpOQkIAhQ4Zg8+bN0Gg06NKlC7788kvjOsJXr15FREQEdu/ejaZNm+LGjRvo3bs3Tp8+jdTUVISHh6NTp04YP368xT2cn2br3s9EREREpAxb+zW7G19nw8aXiIiIqGCztV+ze8vi/5IkCeybiYiIiKgwyFPju3z5clSvXh0eHh7w8PBAjRo1sGLFivzORkRERESUb+y+uW327NmYMGEChgwZgkaNGgEA9u3bh7feegv379936NbFaibq9cCjMUDmHgAS4FIF8P8WGpeCswQIERVuoiEdSB4HZB8HoAHc2wJeI6DRapWORkQqEZeQhEnLfsO1Ow+hc3VBv5Z10fnFgrOoQJ5ubvv444/Rp08fk+PLli3D5MmTceXKlXwNqDQ55viKaeuBZDMbgnj0hsYv/3fDIyLnIqb8D0iZm8uIAPh/B437C3JHIiKVGbFgE/b8fSnHcZ2rFusm90WxQD+Hndthc3zj4uIQGRmZ43hkZCTi4uLsfTmnJ+pvmm96ASD9B4hp5rdYJiKyRkzfaabpBQAJSBwA0ZAgZyQiUpkZq3fn2vQCQGa2AZ0mLZM5Ue7sbnzLlSuHn3/+Ocfx1atXo3z58vkSyqk8fMN6TfLHjs9BROqVbMNvjRJHOD4HEanW2r1/WxzP0huwMvqYTGnMs3uO78cff4zu3btj7969xjm++/fvR3R0dK4NMVlhsGVqSLrDYxCRikkPrNdkH3F8DiJSpbPX7sAgWp85uzL6BHo1qyNDIvPsvuLbpUsXHDp0CEWLFsWGDRuwYcMGFC1aFIcPH0anTp0ckVHluBwcERUEBqUDEFEhdet+ok11GdnZjg1iA7uv+AJAnTp18MMPP+R3FielBf/BISLFCV5KJyCiQqpWueI21YUG+Dg4iXU2Nb7JycnGO+SSk5Mt1nJ3Mzvp2gGZGyzXaErKEoWIVMqlOqA/ZbnGs4/lcSIiM4L8vOHrqUNyWqbFusl9WsqUyDybpjoEBATg7t27AAB/f38EBATk+HpynOyjCZgJwNVyUeBqWbIQkUoFfIfHv10yQwiAxmeobHGISH1mv9Xe4njNMsVQoUSwTGnMs+mK765duxAYGAgA2L17t0MDOaWifwMJLwHinacGvICiv0LjUkSRWESkDhqtP8SgvcCDzjk/Z1yqAgFrlQlGRKrxXPkSWDisC4Yv2ITUjH/n8goAmj1XHjMHvaJcuP+wewOL69evIzw8HIIgmByXJAk3btxAyZLq+rW8HBtYPCHqM4D0ZYCUDnj2gsYlyKHnIyLnIxoSgIxfAcET0LWFRuumdCQiUplrdxJw8Mw1BAd64+Va8ix1a2u/Znfjq9VqERcXh+Bg08vVDx48QHBwMAwGdd2oJWfjS0RERET2c9jObZIk5bjaCwApKSlwd3e39+WIiIiIiGRh83JmI0Y83tVHEARMmDABnp6exjGDwYBDhw6hVq1a+R6QiIiIiCg/2Nz4njhxAsDjK76nTp2Cm9u/88Lc3NxQs2ZNjBo1Kv8TEhERERHlA5sb3yerOfTv3x/z5s3jfFciIiIiKlTs3rnt+++/d0QOIiIiIiKHytOWxUePHsXPP/+M69evIysry2Rs3bp1+RLM2YhZ/wBJIwHDZQASoA0BfKZA4/6i0tGISCXE5K+AtPkAxP8/4gb4zoHGs4WSsYhIRfbExGLB1oOIT0iBzlWLl2uVw3sdX4Cne8FYOtHuVR1WrVqFyMhInDt3DuvXr0d2djbOnDmDXbt2wc/PzxEZVU98NAdIeAUwXACQDUAPGG4BiQMhJgxWOh4RqYAYXx9I+wr/Nr0AkAUkvwvxfm+lYhGRirwx+2eM+HYz/rl5H8lpGbiXlIrVf/yNpqO+wdlrT2/SpQy7G9/PPvsMc+bMwebNm+Hm5oZ58+bh/Pnz6Natm+o2r5CDmHUKSP3GfEHWHogpi+QLRESqIz7oD+Ch+QL9YYip22XLQ0Tq89lP0Th+8VauY3qDiIFfrIYoirmOy8nuxvfSpUto27YtgMerOaSmpkIQBAwfPhwLFy7M94CqlzTGek3K/xyfg4jUK3u/9ZpHXJWHiPJGFEVsPHDaYk1mtgE/7T4hUyLz7G58AwIC8OjRIwBA8eLFcfr04280MTERaWlp+ZvOGRiu2lCU6ugUROT0sqyXEBHlIvb2A2TrrV/N3X7kggxpLLP75rbGjRtj586dqF69Orp27YqhQ4di165d2LlzJ5o1a+aIjCpn147RRERERAVKela2TXXZBuWnOtjd+H799dfIyMgAAHz00UdwdXXFgQMH0KVLF4wfPz7fA6qeEABID6wUaWWJQkTOLOdW9EREtqhYIhiCAEhWruXVKhMmTyAL7G58AwMDjX/WaDQYO3ZsvgZyOj6jgORxlmt0reTJQkTqJAQD0l3LNe495clCRKrj7uaCOuVL4Og/N83WCACGdGgkXygzbJrjm5ycbPMX2Ufj2QVwqWm+QAgEfD+XLxARqU/ALisFXtD4T5YjCRGp1Ow328PXU2d2fFS3pvC2MC4XQZKsXZh+fGVXECz/GkySJAiCAIPBkG/hCoLk5GT4+fkhKSnJods0i0nTgfQf8O8NJlrArRngNw8aLac6ENGzEbOygIdNAem+6YC2BjRBaxXJRETqkpaRhakrf0d0TCyy9Y/7wTKhgRjxahNEVi3t0HPb2q/Z1Pj+8ccfNp+4SZMmNtcWBnI1vkRERESUN7b2azbN8VVbM0tEREREzsfudXwB4M8//0Tv3r0RGRmJW7ce79KxYsUK7Nu3L1/DERERERHlF7sb319++QVRUVHw8PDA8ePHkZmZCQBISkrCZ599lu8BiYiIiIjyg92N79SpU7FgwQIsWrQIrq6uxuONGjXC8ePH8zUcEREREVF+sbvxvXDhAho3bpzjuJ+fHxITE/MjExERERFRvrO78Q0NDUVsbGyO4/v27UOZMmXyJRQRERERUX6ze+e2QYMGYejQoViyZAkEQcDt27dx8OBBjBo1ChMmTHBERqcgpm8CHs0FxFsApMcbV3gNgMZ7sNLRiEglxMQPgIzNAPT/f8QT8H4bGu83lYxFRCqRpddj5s978Ouh80jPyoZGEFApPBijujZBrXLFlY4HwMZ1fP9LkiR89tlnmDZtGtLS0gAAOp0Oo0aNwieffOKQkEqSYx1fMWkykP5j7oOudaEpYmaMiMhG4t0XAfFO7oOuL0BTZIm8gYhIVdKzstBu/BIkPErPdXzS6y3RIbKqw86frxtY5CYrKwuxsbFISUlBlSpV4O3tjfT0dHh4eOQ5dEHk6MZXzDwMPOxtuch7BDTeb+X7uYnIOYiJo4CMTZaL/OZD49FCnkBEpDrvfrUOB89eMzsuCMC+ue/Cw83NIee3tV/L0zq+AODm5oYqVaqgXr16cHV1xezZsxEREZHXl3NeKbOs16QudXgMIlKxjK3Wax6p7zd2RCSPLL0ef527brFGkoD/bTwoUyLzbG58MzMzMW7cONStWxeRkZHYsGEDAOD7779HREQE5syZg+HDhzsqp3pl57xRMAcpwfE5iEjFDNZLxHuOj0FEqnTh+j3YMoHg6MUbMqSxzOab2yZOnIhvv/0WzZs3x4EDB9C1a1f0798ff/31F2bPno2uXbtCq9U6Mqs6CRrA6n8rghxJiIiIiOzm6mLbdVStJs8TDfKNzY3vmjVrsHz5crRv3x6nT59GjRo1oNfr8ffff0MQ2JjlmWtNIMvKVs+aMHmyEJFKuQPIsFyiLSVLEiJSnwolguCi1UBvEC3WvVyrnEyJzLO59b558ybq1KkDAKhWrRp0Oh2GDx/OpvdZ+X5kvcZnmMNjEJGKefW3XuM30/E5iEiVNBoNWterZLHG1UWDPs3rypTIPJsbX4PBALf/3Inn4uICb29vh4RyJhqXsoCPhfWPPbpB49FBvkBEpDoan+GAi4V/cDwGQONWQ75ARKQ6k3q3QJVSIbmOaTUCFgztAhcbp0Q4ks3LmWk0GrRu3Ro6nQ4AsHnzZrz88svw8vIyqVu3bl3+p1SQHOv4AoCYfRF4NA3Ijnl866NrGcB7NDS6Bg47JxE5FzFtPfBo1r83zGpLAn7ToHGro2wwIlKNzQfP4Lvth3EvMRVuLlq8WD0Cwzo3RqCvp0PPm+/r+Pbvb8OvyvB4lQc1kavxJSIiIqK8sbVfs/nmNrU1tERERETkXJSfbGGjTz/9FJGRkfD09IS/v79Nz5EkCRMnTkSxYsXg4eGB5s2b4+LFi44NSkREREQFUqFpfLOystC1a1e8/fbbNj9n5syZ+PLLL7FgwQIcOnQIXl5eiIqKQkaGlWV9iIiIiEh1bJ7jW1AsXboUw4YNQ2JiosU6SZIQFhaGkSNHYtSoUQCApKQkhISEYOnSpejRo4dN5+McXyIiIqKCzdZ+rdBc8bXXlStXEB8fj+bNmxuP+fn5oX79+jh40Pxe0ZmZmUhOTjb5IiIiIqLCT7WNb3x8PAAgJMR0TbmQkBDjWG6mTZsGPz8/41d4eLhDc/6XKIoQs85AzPobopgl23mJyHmIYtbjz5issxBFy7ssERHlRVa2HrcfJONhSrrSUXKweVUHRxg7dixmzJhhsebcuXOoVMnybiD5ady4cRgxYoTxcXJyssObX1EUgeSPgIyNAPT/f1SA6NYI8P8aGo1j174jIvUTxVQg8V0g6yCAJzPcXCF6dAR8PoFGo9rrIEQkk6TUDCzcehAbDpxBemY2AKBW2TC82bYB6lcuGNuiK9r4jhw5Ev369bNYU6ZMmTy9dmhoKADgzp07KFasmPH4nTt3UKtWLbPP0+l0xk06ZPOwO5D991MHJSBrH3CvGcSg3dBo3OXNRESqIYoZwL1m/25cYZQNpK8B9LFAkdWKZCMidUhKzUC/Watw814iDOK/t4+dvByHd75ah6n9Wlvd1lgOija+QUFBCAoKcshrR0REIDQ0FNHR0cZGNzk5GYcOHbJrZQhHE9M35tL0/of0AHg0FfCbKl8oIlKX5I9zaXr/I/sExPQt0Hi8Il8mIlKVhVv/ytH0AoD4/2sofPLDTrxYPQLeHjJfXHxKofnd1vXr1xETE4Pr16/DYDAgJiYGMTExSElJMdZUqlQJ69evBwAIgoBhw4Zh6tSp2LRpE06dOoU+ffogLCwMHTt2VOi7yEXK/6zXpG92fA4iUq+MrdZrUr5xfA4iUqWsbD02HDido+n9r8xsPbYfOS9jqtwpesXXHhMnTsSyZcuMj2vXrg0A2L17N5o2bQoAuHDhApKSkow1Y8aMQWpqKgYPHozExES88MIL2L59O9zdC9C0AcMdG4oK3uRwIipMbFi7XIxzfAwiUqX7yWnGOb3maLUaXIm38JsnmRSaxnfp0qVYunSpxZqnlyQWBAFTpkzBlClTHJjsGQk6QEqzViRLFCJSKwH/3tBmjpscQYhIhTx0rlZrJEmCp075z5lCM9VBtXRNrde4VHZ4DCJSMZeK1mvcmzk+BxGpUoC3B2qVDYNGMH+hziBKaP5ceRlT5Y6Nr9J8PwCgtVzjM16WKESkUj4fWilwAXxGyxKFiNTpzbYNcvzm/QmNIOCFahGoGB4sc6pcsigdwNlpNIFAwAoAuf2aQAB8P4NGV1fuWESkIhpdA8DnE+Q+bcoNCFwJjcZf5lREpCb1K5fC1P6t4e7qAgGAi1YDrebxZ05k1dKYNrCNsgH/nyCZa88JgO17Pz8rUdQDaYuBjJ0ADIBrXcBnODQaL4edk4iciyimAo9mA9nHAGgB9yjA8w1uXkFE+SYlPRPbj5zHlfgEeOjc0Py58qgkw5VeW/s1Nr5WyNX4EhEREVHe2Nqv8X/ziYiIiMgpsPElIiIiIqfAxpeIiIiInAIbXyIiIiJyCmx8iYiIiMgpFJoti52BqL8BpP8CSHrAvSU0bjWUjkREKiM+WgSkrwHgAniPhsbzJaUjERHJho1vASCKycCDnoDh4r8H0xZCFIKAIsuhcSmrXDgiUgUxdT3w6APTg8lvQkzWAEV+g8a1pDLBiIhkxKkOChNFPXCvhWnT+4R0D7jfHqI+Xv5gRKQaYvr+nE3vv6PAg+YQs9NkzUREpAQ2vkpLWwBIDy0UZAOPJskWh4hUKOkd6zWJvR2fg4hIYWx8lZb2s/WazD8dn4OIVCzdeonhtONjEBEpjI2v0sRkG4r0Do9BREREpHZsfJUm+NhQxHsQiYiIiJ4VG1+leXaxXuPWwPE5iEjFdNZLtBUdH4OISGFsfJXm9Y6Vq75awPcT2eIQkQr5fmG9xn+143MQESmMja/CNBo3oOhvgCaXNTQFPyBwLTQuxeUPRkSqofFsCXh/aL6gyAZoXD3lC0REpBBOHi0ANNoiQPDvELPPA2lrAGQD7lHQ6BopHY2IVELj3Q/w7gcx6TMgYxsALeD9HjReryodjYhINoIkSZLSIQqy5ORk+Pn5ISkpCb6+vkrHISIiIqKn2NqvcaoDERERETkFNr5ERERE5BTY+BIRERGRU2DjS0REREROgY0vERERETkFLmdWQIiiCKSvBjI2AxABt0jA663H6/wSEeUDSTIAmX9Ayv4bgBaC7kXAtRYEQVA6GhGpRHpWNqJPXMSVuAR46tzQrHY5lA4NVDqWEZczs0KO5czErFNAQm8A6U+NaAG/WdB4vOKQ8xKR85Cyz0B6+A4gxuHxNQ8JgAFwrQHB/38QtMEKJySiwm5XTCwmLduB1IwsuGg1ECUJoiihxXMVMLlvS3i4uTrs3FzOrJAQxWQgoTtyNr0AYACSRkDMOil3LCJSEclwG1LC64B45/+P6AEYHv8x+wykhD6QpCyl4hGRChz75ybGLNyCtIzHnyV6gwhRfHxtNfrERUz4fruS8YzY+Crt0Uw8/kfIUs0UWaIQkTpJqcsAKR2AmMuoATBcBjJ2yB2LiFTk261/AXj8u6SniZKEXTGxiL11X95QuWDjq7SM363XZJ92fA4iUq+MzTBe4c2VBlLGFrnSEJHKJKVm4Og/NyBamD2r1QjYefwfGVPljo2v0qQMG4pyu0pDRGQjMcVaASA+kiUKEalPakam1RpBEJCSbr3O0dj4Kk1T1IYid4fHICIVcykFwNLKDVrApYxcaYhIZYr4ekHnanmhMIMoomRwgEyJzGPjqzTvwdZr3Fs7PgcRqZbg2Qu5z7x7wgDBs5tccYhIZXSuLmjfsCq0GvP/g+2q1aJNvUoypsodG1+FaTy7AdoK5gsEX8B3knyBiEh9PDoDrvVh9iPfsy8E1xqyRiIidXmzbQOEBPjkaH41/79O+NgeL8PHU/nfYLPxLQiKbAJ0rWD6dgiA63NA0B5oNJ5KJSMiFRAENwiBiwGvwY//Z/oJTRgE30kQfD5ULhwRqUKgryeWjemBdg2rwtVFazxeoUQQ5rzVHh0bVVMw3b+4gYUVcmxg8YQo6oHsQ4CUCbjVh0bj5dDzEZHzkaQswHAdgCugDYcg8PoHEeWv1IwsxCckw9PdDcUCHds7PWFrv8YtiwsQjcYF0DVSOgYRqZgguAEu5ZSOQUQq5uXuhrJhtty8Lz/+rz4REREROQU2vkRERETkFNj4EhEREZFTYONLRERERE6BjS8REREROQWu6lBAiPrbwKPPgKyjAETAtQLgPQ4at6pKRyMilRCzTgGPpgH6WAAawO15wGccNC5hSkcjIpV4e+5aHLpww/jYw80Fy8f0QNniQQqm+hfX8bVCjnV8xbS1QLKZBeQ9+0Hjy8XliejZiElTgfTluYwIgN90aDw6yZ6JiNTlubfnmB3r3ew5jHi1icPObWu/xqkOChP118w3vQCQthRi+jb5AhGR6ojpW8w0vQAgAUljIepvyZqJiNQlcuhXFsd/iD6OzMxMmdKYx8ZXaY8+s6FmtuNzEJF6Wf0MkWz7LCIiykVmZiYysvRW67pMWSFDGsvY+Cot65j1GvGG9RoiInPEm9Zrsg47PgcRqdKSHUdtqrud8MjBSawrNI3vp59+isjISHh6esLf39+m5/Tr1w+CIJh8tWrVyrFB7SUZbClyeAwicna2fBYREeWU8Chd6Qg2KzSNb1ZWFrp27Yq3337brue1atUKcXFxxq+ffvrJQQnzyCXCeo3g5/gcRKRego/1Gpcyjs9BRKo0oGU9m+o83JRfTEz5BDb6+OOPAQBLly6163k6nQ6hoaEOSJRPfEYCD/tbrvHsLU8WIlInz9eA1G8t13iPkicLEalOsSBfCAJgbZ2wJSO7yxPIgkJzxTev9uzZg+DgYFSsWBFvv/02Hjx4YLE+MzMTycnJJl+OpNE1Atw7mC9wqQp4vefQDESkcl7DAW1F8+PuXaDRNZAvDxGpzo9je1kcLxHkh4olg2VKY56qG99WrVph+fLliI6OxowZM/DHH3+gdevWMBjMz2WbNm0a/Pz8jF/h4eEOz6nxnwX4TAaE//wHIfgAnoOBwF+g0aj6bSIiB9NoNECRjYDnQEDw/s9ACODzCTT+05QLR0SqULFkMNaM7w2XXHqWpjXKYNOUAQqkyknRDSzGjh2LGTNmWKw5d+4cKlWqZHy8dOlSDBs2DImJiXaf7/Llyyhbtix+//13NGvWLNeazMxMk3XmkpOTER4e7tANLIiIiIgo72zdwELROb4jR45Ev379LNaUKZN/N1yUKVMGRYsWRWxsrNnGV6fTQafT5ds5iYiIiKhgULTxDQoKQlCQfHs337x5Ew8ePECxYsVkOycRERERFQyFZvLo9evXERMTg+vXr8NgMCAmJgYxMTFISUkx1lSqVAnr168HAKSkpGD06NH466+/cPXqVURHR6NDhw4oV64coqKilPo2iIiIiEghhWY5s4kTJ2LZsmXGx7Vr1wYA7N69G02bNgUAXLhwAUlJSQAArVaLkydPYtmyZUhMTERYWBhatmyJTz75hFMZiIiIiJyQoje3FQa2TpYmIiIiImXY2q8VmqkORERERETPotBMdVA7KfsMpNSlQOZeAAbA9TkIXn0h6BopHY2IiIhIFdj4FgBS+iZISWMACAD+f3ONrD8hZe2B5PUuND5DlYxHREREpAqc6qAwSX/j/5teEcamF/j3z6nzIWXuUyAZERERkbqw8VWYlL4Kj6/0mqOFlLrMwjgRERER2YKNr9KyjsP0Su/TDED2cbnSEBEREakWG1+lCVobimypISIiIiJL2PgqTHB7EZbfBi2gayxXHCIiIiLVYuOrNM+ugOAO82+FCMGrn4yBiIiIiNSJja/CBE0ghIBFuTS/WgAaCH7TIbhWUygdERERkXpwHd8CQHB7HigaDaSvgZT5JwA94FYHgkcPCC4llY5HREREpApsfAsIQVsE8H4LgvdbSkchIiIiUiVOdSAiIiIip8DGl4iIiIicAhtfIiIiInIKbHyJiIiIyCmw8SUiIiIip8BVHQoQSZIA8S4AEdAEQ7BpO2MiItuJWQlA+veA4A2494fGzU3pSESkMgnJaTgeexPB/t6oUSZM6Tgm2PgWAJIkAenrIKUuBAxXHh/UFAU8+wBeAyEIrsoGJKJCT8y6BiS0AmD492DaFxDhDQT+xQaYiJ7Z2Wt3MOTrdUhMyTAe0whA+4bVMPH1Fgom+xenOhQAUsrnkJLHAYar/x4U70NKmQMpcQgkSa9YNiIq/MSseCChBUyaXqMUIKGG3JGISGXOXruD3tN/NGl6AUCUgA0HTuPteb8olMwUG1+FSdmngdRFTx49PQpk7gYyNssdi4jUJKG1lQIR4oMBskQhInUa8vV6i+OHzl/H5bgHMqUxj42vwqS0VQAszeXVQEpbKVccIlKlVOsl2fscH4OIVCkhOQ2JKelW6yYu3SFDGsvY+CpNfxG5//rxCRHQX5IrDREREZFdjsfetKnudkKSg5NYx8ZXaYI3AMFKjacsUYiIiIjsFezvbVOdm4vyayqw8VWY4N4KOef2/pcWcG8rVxwiUiUr/3MNALDtHy4ioqfVKBMGjQ0fM92b1nR8GCvY+CrN4xVAWwK5z/PVAIIOgmcfuVMRkZq497ReE7jM8TmISLXaN6xmcdxFq0H/qHoypTGPja/CBMEDQsByQBvx/0dcYFxeWRMAIWAZBJcSSsUjIhXQ+E8GtBaWLPMYBI1bddnyEJH6THy9BepXKpnrmItWgzUTXpc5Ue4ESZIs/Z7d6SUnJ8PPzw9JSUnw9fV12HkkSQSyDkDK3A/AAMG1JuDeAoLAReWJKH883sSiK4D/v8FEUxrw38zNK4go31yOe4CJS3fgdkIS3Fy06NakJga0qu/w89rar7HxtUKuxpeIiIiI8sbWfo1THYiIiIjIKbDxJSIiIiKnwMaXiIiIiJwCG18iIiIicgpsfImIiIjIKbDxJSIiIiKnwMaXiIiIiJwCG18iIiIicgpsfImIiIjIKbDxJSIiIiKnwMaXiIiIiJwCG18iIiIicgpsfImIiIjIKbDxJSIiIiKn4KJ0gIJOkiQAQHJyssJJiIiIiCg3T/q0J32bOWx8rXj06BEAIDw8XOEkRERERGTJo0eP4OfnZ3ZckKy1xk5OFEXcvn0bPj4+EARB6ThOLTk5GeHh4bhx4wZ8fX2VjkPPgO+lOvB9VA++l+rgzO+jJEl49OgRwsLCoNGYn8nLK75WaDQalChRQukY9B++vr5O9xdarfheqgPfR/Xge6kOzvo+WrrS+wRvbiMiIiIip8DGl4iIiIicAhtfKjR0Oh0mTZoEnU6ndBR6Rnwv1YHvo3rwvVQHvo/W8eY2IiIiInIKvOJLRERERE6BjS8REREROQU2vkRERETkFNj4EhEREZFTYONLBdqnn36KyMhIeHp6wt/f36bnSJKEiRMnolixYvDw8EDz5s1x8eJFxwYlixISEtCrVy/4+vrC398fAwcOREpKisXnNG3aFIIgmHy99dZbMiWmJ+bPn4/SpUvD3d0d9evXx+HDhy3Wr1mzBpUqVYK7uzuqV6+Obdu2yZSUrLHnvVy6dGmOv3/u7u4ypqXc7N27F+3atUNYWBgEQcCGDRusPmfPnj147rnnoNPpUK5cOSxdutThOQsyNr5UoGVlZaFr1654++23bX7OzJkz8eWXX2LBggU4dOgQvLy8EBUVhYyMDAcmJUt69eqFM2fOYOfOndiyZQv27t2LwYMHW33eoEGDEBcXZ/yaOXOmDGnpidWrV2PEiBGYNGkSjh8/jpo1ayIqKgp3797Ntf7AgQPo2bMnBg4ciBMnTqBjx47o2LEjTp8+LXNyepq97yXwePev//79u3btmoyJKTepqamoWbMm5s+fb1P9lStX0LZtW7z00kuIiYnBsGHD8MYbb2DHjh0OTlqASUSFwPfffy/5+flZrRNFUQoNDZVmzZplPJaYmCjpdDrpp59+cmBCMufs2bMSAOnIkSPGY7/++qskCIJ069Yts89r0qSJNHToUBkSkjn16tWT3n33XeNjg8EghYWFSdOmTcu1vlu3blLbtm1NjtWvX1968803HZqTrLP3vbT1M5eUA0Bav369xZoxY8ZIVatWNTnWvXt3KSoqyoHJCjZe8SVVuXLlCuLj49G8eXPjMT8/P9SvXx8HDx5UMJnzOnjwIPz9/VG3bl3jsebNm0Oj0eDQoUMWn7ty5UoULVoU1apVw7hx45CWlubouPT/srKycOzYMZO/SxqNBs2bNzf7d+ngwYMm9QAQFRXFv3sKy8t7CQApKSkoVaoUwsPD0aFDB5w5c0aOuJSP+HcyJxelAxDlp/j4eABASEiIyfGQkBDjGMkrPj4ewcHBJsdcXFwQGBho8T157bXXUKpUKYSFheHkyZP44IMPcOHCBaxbt87RkQnA/fv3YTAYcv27dP78+VyfEx8fz797BVBe3suKFStiyZIlqFGjBpKSkvD5558jMjISZ86cQYkSJeSITfnA3N/J5ORkpKenw8PDQ6FkyuEVX5Ld2LFjc9w08fSXuQ9jKjgc/T4OHjwYUVFRqF69Onr16oXly5dj/fr1uHTpUj5+F0SUm4YNG6JPnz6oVasWmjRpgnXr1iEoKAjffvut0tGIngmv+JLsRo4ciX79+lmsKVOmTJ5eOzQ0FABw584dFCtWzHj8zp07qFWrVp5ek3Jn6/sYGhqa4wYavV6PhIQE4/tli/r16wMAYmNjUbZsWbvzkn2KFi0KrVaLO3fumBy/c+eO2fctNDTUrnqSR17ey6e5urqidu3aiI2NdUREchBzfyd9fX2d8movwMaXFBAUFISgoCCHvHZERARCQ0MRHR1tbHSTk5Nx6NAhu1aGIOtsfR8bNmyIxMREHDt2DHXq1AEA7Nq1C6IoGptZW8TExACAyf/QkOO4ubmhTp06iI6ORseOHQEAoigiOjoaQ4YMyfU5DRs2RHR0NIYNG2Y8tnPnTjRs2FCGxGROXt7LpxkMBpw6dQpt2rRxYFLKbw0bNsyxpKDT/51U+u46IkuuXbsmnThxQvr4448lb29v6cSJE9KJEyekR48eGWsqVqworVu3zvh4+vTpkr+/v7Rx40bp5MmTUocOHaSIiAgpPT1diW+BJElq1aqVVLt2benQoUPSvn37pPLly0s9e/Y0jt+8eVOqWLGidOjQIUmSJCk2NlaaMmWKdPToUenKlSvSxo0bpTJlykiNGzdW6ltwSqtWrZJ0Op20dOlS6ezZs9LgwYMlf39/KT4+XpIkSXr99delsWPHGuv3798vubi4SJ9//rl07tw5adKkSZKrq6t06tQppb4F+n/2vpcff/yxtGPHDunSpUvSsWPHpB49ekju7u7SmTNnlPoWSJKkR48eGf8dBCDNnj1bOnHihHTt2jVJkiRp7Nix0uuvv26sv3z5suTp6SmNHj1aOnfunDR//nxJq9VK27dvV+pbUBwbXyrQ+vbtKwHI8bV7925jDQDp+++/Nz4WRVGaMGGCFBISIul0OqlZs2bShQsX5A9PRg8ePJB69uwpeXt7S76+vlL//v1N/uflypUrJu/r9evXpcaNG0uBgYGSTqeTypUrJ40ePVpKSkpS6DtwXl999ZVUsmRJyc3NTapXr570119/GceaNGki9e3b16T+559/lipUqCC5ublJVatWlbZu3SpzYjLHnvdy2LBhxtqQkBCpTZs20vHjxxVITf+1e/fuXP9NfPLe9e3bV2rSpEmO59SqVUtyc3OTypQpY/LvpTMSJEmSFLnUTEREREQkI67qQEREREROgY0vERERETkFNr5ERERE5BTY+BIRERGRU2DjS0REREROgY0vERERETkFNr5ERERE5BTY+BIRERGRU2DjS0SUj/bs2QNBEJCYmKh0FADA1atXIQgCYmJibKo/f/48GjRoAHd3d9SqVcthuZYuXQp/f3+HvT4RUW7Y+BIRWdGvXz907NjRoef4+++/0b59ewQHB8Pd3R2lS5dG9+7dcffuXZtfI7ec4eHhiIuLQ7Vq1Wx6jUmTJsHLywsXLlxAdHS0Pd+CWaVLl8bcuXNNjnXv3h3//PNPvrw+EZGtXJQOQETk7O7du4dmzZrhlVdewY4dO+Dv74+rV69i06ZNSE1NfabX1mq1CA0Ntbn+0qVLaNu2LUqVKvVM57XGw8MDHh4eDj0HEdHTeMWXiMgOmZmZeP/9941XZl944QUcOXIkR93+/ftRo0YNuLu7o0GDBjh9+rTZ19y/fz+SkpKwePFi1K5dGxEREXjppZcwZ84cREREAAAMBgMGDhyIiIgIeHh4oGLFipg3b57xNSZPnoxly5Zh48aNEAQBgiBgz549OaY6PHz4EL169UJQUBA8PDxQvnx5fP/99wAAQRBw7NgxTJkyBYIgYPLkyQCADz74ABUqVICnpyfKlCmDCRMmIDs72+R72Lx5M55//nm4u7ujaNGi6NSpEwCgadOmuHbtGoYPH27MBeQ+1eGbb75B2bJl4ebmhooVK2LFihUm44IgYPHixejUqRM8PT1Rvnx5bNq0yco7RkT0Lza+RER2GDNmDH755RcsW7YMx48fR7ly5RAVFYWEhASTutGjR+OLL77AkSNHEBQUhHbt2uVoFp8IDQ2FXq/H+vXrIUlSrjWiKKJEiRJYs2YNzp49i4kTJ+LDDz/Ezz//DAAYNWoUunXrhlatWiEuLg5xcXGIjIzM8ToTJkzA2bNn8euvv+LcuXP45ptvULRoUQBAXFwcqlatipEjRyIuLg6jRo0CAPj4+GDp0qU4e/Ys5s2bh0WLFmHOnDnG19y6dSs6deqENm3a4MSJE4iOjka9evUAAOvWrUOJEiUwZcoUY67crF+/HkOHDsXIkSNx+vRpvPnmm+jfvz92795tUvfxxx+jW7duOHnyJNq0aYNevXrl+NkTEZklERGRRX379pU6dOggpaSkSK6urtLKlSuNY1lZWVJYWJg0c+ZMSZIkaffu3RIAadWqVcaaBw8eSB4eHtLq1avNnuPDDz+UXFxcpMDAQKlVq1bSzJkzpfj4eIu53n33XalLly45cv7XlStXJADSiRMnJEmSpHbt2kn9+/c3+5o1a9aUJk2aZPG8s2bNkurUqWN83LBhQ6lXr15m60uVKiXNmTPH5Nj3338v+fn5GR9HRkZKgwYNMqnp2rWr1KZNG+NjANL48eONj1NSUiQA0q+//moxLxHRE7ziS0Rko0uXLiE7OxuNGjUyHnN1dUW9evVw7tw5k9qGDRsa/xwYGIiKFSvmqPmvTz/9FPHx8ViwYAGqVq2KBQsWoFKlSjh16pSxZv78+ahTpw6CgoLg7e2NhQsX4vr163Z9D2+//TZWrVqFWrVqYcyYMThw4IDV56xevRqNGjVCaGgovL29MX78eJPzxsTEoFmzZnbleNq5c+dMfq4A0KhRoxw/sxo1ahj/7OXlBV9fX7tuACQi58bGl4iogChSpAi6du2Kzz//HOfOnUNYWBg+//xzAMCqVaswatQoDBw4EL/99htiYmLQv39/ZGVl2XWO1q1bG+fc3r59G82aNTNOacjNwYMH0atXL7Rp0wZbtmzBiRMn8NFHH5mcV86b1FxdXU0eC4IAURRlOz8RFW5sfImIbPTkxqv9+/cbj2VnZ+PIkSOoUqWKSe1ff/1l/PPDhw/xzz//oHLlyjafy83NDWXLljWu6rB//35ERkbinXfeQe3atVGuXDlcunQpx3MMBoPV1w4KCkLfvn3xww8/YO7cuVi4cKHZ2gMHDqBUqVL46KOPULduXZQvXx7Xrl0zqalRo4bFpc9syVW5cmWTnyvw+Ht++udKRPQsuJwZEZGNvLy88Pbbb2P06NEIDAxEyZIlMXPmTKSlpWHgwIEmtVOmTEGRIkUQEhKCjz76CEWLFjW7FvCWLVuwatUq9OjRAxUqVIAkSdi8eTO2bdtmXHGhfPnyWL58OXbs2IGIiAisWLECR44cMa76ADxeL3fHjh24cOECihQpAj8/vxznmjhxIurUqYOqVasiMzMTW7ZssdiQly9fHtevX8eqVavw/PPPY+vWrVi/fr1JzaRJk9CsWTOULVsWPXr0gF6vx7Zt2/DBBx8Yc+3duxc9evSATqcz3kz3X6NHj0a3bt1Qu3ZtNG/eHJs3b8a6devw+++/m81GRGQvXvElIrJCFEW4uDy+TjB9+nR06dIFr7/+Op577jnExsZix44dCAgIMHnO9OnTMXToUNSpUwfx8fHYvHkz3Nzccn39KlWqwNPTEyNHjkStWrXQoEED/Pzzz1i8eDFef/11AMCbb76Jzp07o3v37qhfvz4ePHiAd955x+R1Bg0ahIoVK6Ju3boICgrKcQUVeHz1ddy4cahRowYaN24MrVaLVatWmf3e27dvj+HDh2PIkCGoVasWDhw4gAkTJpjUNG3aFGvWrMGmTZtQq1YtvPzyyzh8+LBxfMqUKbh69SrKli2LoKCgXM/TsWNHzJs3D59//jmqVq2Kb7/9Ft9//z2aNm1qNhsRkb0ESTKzdg4REQEAWrVqhXLlyuHrr79WOgoRET0DXvElIjLj4cOH2LJlC/bs2YPmzZsrHYeIiJ4R5/gSEZkxYMAAHDlyBCNHjkSHDh2UjkNERM+IUx2IiIiIyClwqgMREREROQU2vkRERETkFNj4EhEREZFTYONLRERERE6BjS8REREROQU2vkRERETkFNj4EhEREZFTYONLRERERE7h/wA3z4VAJ/+q2QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled= scaler.fit_transform(df[['Performance rating','Hours of trg']])\n",
    "\n",
    "scaled_df = pd.DataFrame(scaled, columns=['Performance rating','Hours of trg'])\n",
    "scaled_df.head()\n",
    "k_opt=4\n",
    "model = KMeans(n_clusters=k_opt,random_state =42,n_init=20)\n",
    "model.fit(scaled_df)\n",
    "\n",
    "scaled_df['labels'] = model.labels_\n",
    "cluster_centers = model.cluster_centers_\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(scaled_df['Performance rating'], scaled_df['Hours of trg'] , c=scaled_df['labels'], cmap='viridis')\n",
    "plt.title('K-means Clustering')\n",
    "plt.xlabel('Job Satisfaction')\n",
    "plt.ylabel('Relationship Between colleagues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Relationship Between colleagues')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled= scaler.fit_transform(df[['Performance rating','Sourcing Channel']])\n",
    "\n",
    "scaled_df = pd.DataFrame(scaled, columns=['Performance rating','Sourcing Channel'])\n",
    "scaled_df.head()\n",
    "k_opt=3\n",
    "model = KMeans(n_clusters=k_opt,random_state =42,n_init=20)\n",
    "model.fit(scaled_df)\n",
    "\n",
    "scaled_df['labels'] = model.labels_\n",
    "cluster_centers = model.cluster_centers_\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(scaled_df['Performance rating'], scaled_df['Sourcing Channel'] , c=scaled_df['labels'], cmap='viridis')\n",
    "plt.title('K-means Clustering')\n",
    "plt.xlabel('Job Satisfaction')\n",
    "plt.ylabel('Relationship Between colleagues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Relationship Between colleagues')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled= scaler.fit_transform(df[['Performance rating','Content Satisfaction']])\n",
    "\n",
    "scaled_df = pd.DataFrame(scaled, columns=['Performance rating','Content Satisfaction'])\n",
    "scaled_df.head()\n",
    "k_opt=3\n",
    "model = KMeans(n_clusters=k_opt,random_state =42,n_init=20)\n",
    "model.fit(scaled_df)\n",
    "\n",
    "scaled_df['labels'] = model.labels_\n",
    "cluster_centers = model.cluster_centers_\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(scaled_df['Performance rating'], scaled_df['Content Satisfaction'] , c=scaled_df['labels'], cmap='viridis')\n",
    "plt.title('K-means Clustering')\n",
    "plt.xlabel('Job Satisfaction')\n",
    "plt.ylabel('Relationship Between colleagues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "linkage_matrix = linkage(correlation, method='ward')\n",
    "\n",
    "# Plot the dendrogram\n",
    "plt.figure(figsize=(8, 6))\n",
    "dendrogram(linkage_matrix, labels=correlation.index, orientation='top')\n",
    "plt.title('Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('Data Points')\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylabel('Distance')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}