{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"mount_file_id":"1-Dpq219gpzK11vsOiufkqeJS9zaDUmR3","authorship_tag":"ABX9TyOoaSIYoVeDCd2JrzaoZRYB"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"id":"8_lomW5N_Jmt","executionInfo":{"status":"ok","timestamp":1752675982374,"user_tz":-180,"elapsed":1747,"user":{"displayName":"Shadi Minawi","userId":"13406495304319946234"}}},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n"]},{"cell_type":"code","source":["df=pd.read_csv(\"/content/drive/MyDrive/Shadi Al Minawi/kidney_disease.csv\")"],"metadata":{"id":"ZrhtkO_rdb2O","executionInfo":{"status":"ok","timestamp":1752675983172,"user_tz":-180,"elapsed":777,"user":{"displayName":"Shadi 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","    <div id=\"df-0ee8a87f-ad2a-4ad8-ae95-6e9c1725772b\">\n","      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0ee8a87f-ad2a-4ad8-ae95-6e9c1725772b')\"\n","                title=\"Suggest charts\"\n","                style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","      </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","      <script>\n","        async function quickchart(key) {\n","          const quickchartButtonEl =\n","            document.querySelector('#' + key + ' button');\n","          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","          quickchartButtonEl.classList.add('colab-df-spinner');\n","          try {\n","            const charts = await google.colab.kernel.invokeFunction(\n","                'suggestCharts', [key], {});\n","          } catch (error) {\n","            console.error('Error during call to suggestCharts:', error);\n","          }\n","          quickchartButtonEl.classList.remove('colab-df-spinner');\n","          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","        }\n","        (() => {\n","          let quickchartButtonEl =\n","            document.querySelector('#df-0ee8a87f-ad2a-4ad8-ae95-6e9c1725772b button');\n","          quickchartButtonEl.style.display =\n","            google.colab.kernel.accessAllowed ? 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id  gender   age  hypertension  heart_disease ever_married  \\\n","0   9046    Male  67.0             0              1          Yes   \n","1  51676  Female  61.0             0              0          Yes   \n","2  31112    Male  80.0             0              1          Yes   \n","3  60182  Female  49.0             0              0          Yes   \n","4   1665  Female  79.0             1              0          Yes   \n","\n","       work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n","0        Private          Urban             228.69  36.6  formerly smoked   \n","1  Self-employed          Rural             202.21   NaN     never smoked   \n","2        Private          Rural             105.92  32.5     never smoked   \n","3        Private          Urban             171.23  34.4           smokes   \n","4  Self-employed          Rural             174.12  24.0     never smoked   \n","\n","   stroke  \n","0       1  \n","1       1  \n","2       1  \n","3       1  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 \"2596\",\n          \"5110\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avg_glucose_level\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1769.6002138244987,\n        \"min\": 45.28356015058203,\n        \"max\": 5110.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          106.1476771037182,\n          91.88499999999999,\n          5110.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bmi\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1724.2356567020179,\n        \"min\": 7.854066729680158,\n        \"max\": 4909.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          28.893236911794666,\n          28.1,\n          4909.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smoking_status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          4,\n          \"1892\",\n          \"5110\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"stroke\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1806.5940143142543,\n        \"min\": 0.0,\n        \"max\": 5110.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.0487279843444227,\n          1.0,\n          0.21531985698026107\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{}}]},{"cell_type":"code","source":["df['bmi'] = df['bmi'].fillna(df['bmi'].median())\n","display(df.info())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":364},"id":"MKbWVn1Yzdbf","executionInfo":{"status":"ok","timestamp":1752675983998,"user_tz":-180,"elapsed":9,"user":{"displayName":"Shadi Minawi","userId":"13406495304319946234"}},"outputId":"12ecdc0f-1ce5-492c-ac36-caeabcf41d3c"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 5110 entries, 0 to 5109\n","Data columns (total 12 columns):\n"," #   Column             Non-Null Count  Dtype  \n","---  ------             --------------  -----  \n"," 0   id                 5110 non-null   int64  \n"," 1   gender             5110 non-null   object \n"," 2   age                5110 non-null   float64\n"," 3   hypertension       5110 non-null   int64  \n"," 4   heart_disease      5110 non-null   int64  \n"," 5   ever_married       5110 non-null   object \n"," 6   work_type          5110 non-null   object \n"," 7   Residence_type     5110 non-null   object \n"," 8   avg_glucose_level  5110 non-null   float64\n"," 9   bmi                5110 non-null   float64\n"," 10  smoking_status     5110 non-null   object \n"," 11  stroke             5110 non-null   int64  \n","dtypes: float64(3), int64(4), object(5)\n","memory usage: 479.2+ KB\n"]},{"output_type":"display_data","data":{"text/plain":["None"]},"metadata":{}}]},{"cell_type":"code","metadata":{"executionInfo":{"status":"ok","timestamp":1752675984002,"user_tz":-180,"elapsed":2,"user":{"displayName":"Shadi Minawi","userId":"13406495304319946234"}},"id":"QizytERwzU3X"},"source":["def remove_outliers(df, column):\n","\n","  Q1 = df[column].quantile(0.25)\n","  Q3 = df[column].quantile(0.75)\n","  IQR = Q3 - Q1\n","\n","  lower_bound = Q1 - 1.5 * IQR\n","  upper_bound = Q3 + 1.5 * IQR\n","  return df[(df[column] >= lower_bound) & (df[column] <= upper_bound)]\n","\n","  df = remove_outliers(df, 'age')\n","df = remove_outliers(df, 'bmi')\n","df = remove_outliers(df, 'avg_glucose_level')"],"execution_count":10,"outputs":[]},{"cell_type":"code","source":["import matplotlib.pyplot as plt\n","import seaborn as sns\n","\n","plt.figure(figsize=(16, 4))\n","\n","# Age Distribution\n","plt.subplot(1, 3, 1)\n","sns.histplot(df['age'], bins=30, kde=True, color='skyblue')\n","plt.title(\"Age Distribution\")\n","\n","# BMI Boxplot\n","plt.subplot(1, 3, 2)\n","sns.boxplot(y=df['bmi'], color='orange')\n","plt.title(\"BMI Boxplot\")\n","\n","# Glucose Level by Stroke\n","plt.subplot(1, 3, 3)\n","sns.boxplot(x='stroke', y='avg_glucose_level', data=df)\n","plt.title(\"Glucose Level by Stroke\")\n","\n","plt.tight_layout()\n","plt.savefig(\"stroke_data_visualizations.png\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":371},"id":"rWJp2Qar19gC","executionInfo":{"status":"ok","timestamp":1752676044216,"user_tz":-180,"elapsed":1541,"user":{"displayName":"Shadi Minawi","userId":"13406495304319946234"}},"outputId":"e207fa89-16f8-4190-ad6c-2ca93e21bc29"},"execution_count":13,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1600x400 with 3 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAABjUAAAGGCAYAAAAzegNcAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAArrBJREFUeJzs3Xd4FFXbBvB7+ybZTVkgDVLovQkKEaULBERKVKqEIijSBF/15UNAFAQsiCJFFAEliCLFChj6KwSkNwEJJtQUSEg2m2T7+f6IWVmTQBKSbMr9u669zJxzZvYZwOzsPHOeIxFCCBAREREREREREREREZVzUlcHQEREREREREREREREVBhMahARERERERERERERUYXApAYREREREREREREREVUITGoQEREREREREREREVGFwKQGERERERERERERERFVCExqEBERERERERERERFRhcCkBhERERERERERERERVQhMahARERERERERERERUYXApAYREREREREREREREVUITGoQUYmLj4+HRCLBmjVrSv291qxZA4lEgvj4eEdbaGgonnzyyVJ/bwDYu3cvJBIJ9u7dWybvR0REROVLWV73EBERvfnmm5BIJK4Oo8or7N9D586d0axZszKIyPVy/0xu377t6lCoCmBSg6icWrZsGSQSCdq1a+fqUCCRSBwvuVwOnU6HNm3aYMqUKfjjjz9K7H2WLVtWbm8IlOfYiIiISkruwwJ3v3x9fdGlSxds27Ytz/jcMc8//3y+x5sxY4ZjzN1fcEeOHAmNRnPfeHK/HOe+pFIpAgIC8OSTT+LQoUPFP9Fy4uDBg3jzzTeRlpbm6lCIiMiF4uLiMHHiRDRo0ADu7u5wd3dHkyZNMGHCBJw+fdrV4blMWT6wWNEZDAbMnj0bzZo1g4eHB6pVq4ZWrVphypQpuHnzpmPcL7/8gjfffNN1gRKVELmrAyCi/EVFRSE0NBS///47YmNjUa9ePZfG88QTT2DEiBEQQiA9PR2nTp3C2rVrsWzZMixcuBDTpk1zjA0JCUF2djYUCkWR3mPZsmWoXr06Ro4cWeh9nnvuOQwePBgqlapI71VUBcXWsWNHZGdnQ6lUlur7ExERlaW33noLtWvXhhACSUlJWLNmDXr37o0ff/wxz80FtVqNTZs2YdmyZXk+D7/++muo1WoYjcYHimf58uXQaDSw2+24du0aPvvsM3Ts2BG///47WrVq9UDHdqWDBw9izpw5GDlyJLy9vV0dDhERucBPP/2EQYMGQS6XY9iwYWjZsiWkUikuXLiAzZs3Y/ny5YiLi0NISIirQ6VyymKxoGPHjrhw4QIiIyMxadIkGAwGnDt3DuvXr8eAAQMQGBgIICepsXTpUiY2qMJjUoOoHIqLi8PBgwexefNmvPDCC4iKisLs2bNdGlODBg0wfPhwp7YFCxagb9++eOWVV9CoUSP07t0bQM5Tm2q1ulTjyczMhIeHB2QyGWQyWam+171IpdJSP1ciIqKyFh4ejrZt2zq2x4wZAz8/P3z99dd5khq9evXCDz/8gG3btqFfv36O9oMHDyIuLg4RERHYtGnTA8Xz9NNPo3r16o7t/v37o1mzZti4cWOFTmoQEVHVdvnyZQwePBghISHYtWsXAgICnPoXLlyIZcuWQSploRUq2NatW3HixAlERUVh6NChTn1GoxFms7lYx7VarbDb7XyIk8ol/lYkKoeioqLg4+ODPn364Omnn0ZUVFS+41JSUvDcc8/B09MT3t7eiIyMxKlTp/Kt63zhwgU8/fTT0Ol0UKvVaNu2LX744YcHirNatWrYsGED5HI55s2b52jPr7Z0YmIiRo0ahVq1akGlUiEgIAD9+vVzrIURGhqKc+fOYd++fY4SE507dwbwTymMffv24aWXXoKvry9q1arl1Hf3mhq5fv31V7Rq1QpqtRpNmjTB5s2bnfoLqoH572PeK7aC1tTYuHEj2rRpAzc3N1SvXh3Dhw/HjRs3nMbklt64ceMG+vfvD41Ggxo1auA///kPbDbbff70iYiIyo63tzfc3Nwgl+d9JqpmzZro2LEj1q9f79QeFRWF5s2bl0odaX9/fwDIE09ycrIjAaNWq9GyZUusXbvWqb9GjRro3LkzhBCO9tjYWHh4eGDQoEGOttwa2MeOHcOjjz4KNzc31K5dGytWrChUjLt378bjjz8ODw8PeHt7o1+/fjh//ryj/80338Srr74KAKhdu7bjGiO/axoiIqqc3n33XWRmZmL16tV5EhpAzufc5MmTERQUVOAx7rW2k0QiyfNE/o0bNzBmzBgEBgZCpVKhdu3aGD9+vNON77/++gvPPPMMdDod3N3d0b59e/z88895jr9kyRI0bdoU7u7u8PHxQdu2bfNcD9y4cQOjR4+Gn58fVCoVmjZtii+++OI+fzJFs27dOsf3b51Oh8GDB+PatWuO/okTJ0Kj0SArKyvPvkOGDIG/v7/Td/Bt27Y5PsO1Wi369OmDc+fOPVCM97qeMBgM8PDwwJQpU/Lsd/36dchkMsyfP7/AY1++fBkA0KFDhzx9arUanp6eAHLuQSxduhSAc5lx4J9/R++//z4WL16MunXrQqVSOUqO3++6piBXrlxBvXr10KxZMyQlJQEA0tLS8PLLLyMoKAgqlQr16tXDwoULYbfb73s8olycqUFUDkVFRWHgwIFQKpUYMmQIli9fjiNHjuDhhx92jLHb7ejbty9+//13jB8/Ho0aNcL333+PyMjIPMc7d+4cOnTogJo1a+K///0vPDw88O2336J///7YtGkTBgwYUOxYg4OD0alTJ+zZswd6vd7xYflvEREROHfuHCZNmoTQ0FAkJycjOjoaV69eRWhoKBYvXoxJkyZBo9FgxowZAAA/Pz+nY7z00kuoUaMGZs2ahczMzHvGdenSJQwaNAgvvvgiIiMjsXr1ajzzzDPYvn07nnjiiSKdY2Fiu9uaNWswatQoPPzww5g/fz6SkpLw0Ucf4cCBAzhx4oRTeQmbzYaePXuiXbt2eP/997Fz50588MEHqFu3LsaPH1+kOImIiEpKeno6bt++DSEEkpOTsWTJEhgMhjyzNnMNHToUU6ZMgcFggEajgdVqxcaNGzFt2rQHLj0FAKmpqQByrn9u3LiBt99+G2q1Gs8++6xjTHZ2Njp37ozY2FhMnDgRtWvXxsaNGzFy5EikpaVhypQp8PX1xfLly/HMM89gyZIlmDx5Mux2O0aOHAmtVotly5Y5ve+dO3fQu3dvPPvssxgyZAi+/fZbjB8/HkqlEqNHjy4w3p07dyI8PBx16tTBm2++iezsbCxZsgQdOnTA8ePHERoaioEDB+LPP//E119/jQ8//NAxE6VGjRoP/OdFREQVw08//YR69eqV2VqaN2/exCOPPIK0tDSMGzcOjRo1wo0bN/Ddd98hKysLSqUSSUlJePTRR5GVlYXJkyejWrVqWLt2LZ566il89913jvsHn332GSZPnoynn34aU6ZMgdFoxOnTp3H48GHHbIGkpCS0b98eEokEEydORI0aNbBt2zaMGTMGer0eL7/88gOf07x58zBz5kw8++yzeP7553Hr1i0sWbIEHTt2dHz/HjRoEJYuXYqff/4ZzzzzjGPfrKws/Pjjjxg5cqSjAsRXX32FyMhI9OzZEwsXLkRWVhaWL1+Oxx57DCdOnEBoaGiRY7zf9YRGo8GAAQPwzTffYNGiRU7VKL7++msIITBs2LACj59bmuzLL7/EG2+8UeAC5i+88AJu3ryJ6OhofPXVV/mOWb16NYxGI8aNGweVSgWdTleo65r8XL58GV27doVOp0N0dDSqV6+OrKwsdOrUCTdu3MALL7yA4OBgHDx4ENOnT0dCQgIWL15cuD9UIkFE5crRo0cFABEdHS2EEMJut4tatWqJKVOmOI3btGmTACAWL17saLPZbKJr164CgFi9erWjvVu3bqJ58+bCaDQ62ux2u3j00UdF/fr17xsTADFhwoQC+6dMmSIAiFOnTgkhhIiLi3OK4c6dOwKAeO+99+75Pk2bNhWdOnXK07569WoBQDz22GPCarXm2xcXF+doCwkJEQDEpk2bHG3p6ekiICBAtG7d2tE2e/Zskd+vwfyOWVBse/bsEQDEnj17hBBCmM1m4evrK5o1ayays7Md43766ScBQMyaNcvRFhkZKQCIt956y+mYrVu3Fm3atMnzXkRERKUt9zPw3y+VSiXWrFmTZ3zuNUJqaqpQKpXiq6++EkII8fPPPwuJRCLi4+Mdn7e3bt1y7BcZGSk8PDzuG0/uvv9+eXt7i+3btzuNXbx4sQAg1q1b52gzm80iLCxMaDQaodfrHe1DhgwR7u7u4s8//xTvvfeeACC2bt3qdLxOnToJAOKDDz5wtJlMJtGqVSvh6+srzGazECLvdY8QwjEmJSXF0Xbq1CkhlUrFiBEjHG257333NQcREVUN6enpAoDo379/nr47d+6IW7duOV5ZWVmOvn9/j83vcygXADF79mzH9ogRI4RUKhVHjhzJM9ZutwshhHj55ZcFAPG///3P0ZeRkSFq164tQkNDhc1mE0II0a9fP9G0adN7nuOYMWNEQECAuH37tlP74MGDhZeXl9N55SckJET06dOnwP74+Hghk8nEvHnznNrPnDkj5HK5o91ut4uaNWuKiIgIp3HffvutACD279/vOE9vb28xduxYp3GJiYnCy8vLqb2g+wn/VtjriR07dggAYtu2bU77t2jRIt97EXfLysoSDRs2FABESEiIGDlypFi1apVISkrKM3bChAn5xp3778jT01MkJyc79RX2uubua77z58+LwMBA8fDDD4vU1FTHmLffflt4eHiIP//80+k9/vvf/wqZTCauXr16z3MlysXyU0TlTFRUFPz8/NClSxcAOVMCBw0ahA0bNjhNh9y+fTsUCgXGjh3raJNKpZgwYYLT8VJTU7F79248++yzyMjIwO3bt3H79m2kpKSgZ8+euHTpUp6ySEWl0WgAABkZGfn2u7m5QalUYu/evbhz506x32fs2LGFXj8jMDDQaQaKp6cnRowYgRMnTiAxMbHYMdzP0aNHkZycjJdeeslprY0+ffqgUaNG+U7ZffHFF522H3/8cfz111+lFiMREdH9LF26FNHR0YiOjsa6devQpUsXPP/883lKOeby8fFBr1698PXXXwMA1q9fj0cffbTEFjXdtGkToqOj8euvv2L16tVo0KABIiIicPDgQceYX375Bf7+/hgyZIijTaFQYPLkyTAYDNi3b5+j/ZNPPoGXlxeefvppzJw5E88995zTeiC55HI5XnjhBce2UqnECy+8gOTkZBw7dizfWBMSEnDy5EmMHDkSOp3O0d6iRQs88cQT+OWXXx7oz4KIiCoHvV4P4J/v03fr3LkzatSo4Xjllgx6EHa7HVu3bkXfvn2d1s3Klft0/y+//IJHHnkEjz32mKNPo9Fg3LhxiI+Pd5Qj8vb2xvXr13HkyJF8308IgU2bNqFv374QQjjuRdy+fRs9e/ZEeno6jh8//kDntHnzZtjtdjz77LNOx/f390f9+vWxZ88ex7k988wz+OWXX2AwGBz7f/PNN6hZs6bjXKOjo5GWloYhQ4Y4HU8mk6Fdu3aO4xVVYa4nunfvjsDAQKfy42fPnsXp06cLnCmby83NDYcPH3aUtVyzZg3GjBmDgIAATJo0CSaTqdCxRkREOM0aLc51zdmzZ9GpUyeEhoZi586d8PHxcfRt3LgRjz/+OHx8fJz+jLt37w6bzYb9+/cXOlaq2pjUICpHbDYbNmzYgC5duiAuLg6xsbGIjY1Fu3btkJSUhF27djnGXrlyBQEBAXB3d3c6Rr169Zy2Y2NjIYTAzJkznS6KatSo4Vh8PDk5+YHizr0o0Gq1+farVCosXLgQ27Ztg5+fHzp27Ih33323yMmF2rVrF3psvXr18ky5bNCgAQCUaq3qK1euAAAaNmyYp69Ro0aO/lxqtTpPmQkfH58HSv4QERE9qEceeQTdu3dH9+7dMWzYMPz8889o0qQJJk6cWOBik0OHDnWUlty6dWuehSofRMeOHdG9e3c88cQTGDlyJHbt2gWtVotJkyY5xly5cgX169fPs5hq48aNHf25dDodPv74Y5w+fRpeXl74+OOP833fwMBAeHh4OLXd73riXtcCjRs3xu3bt+9bRpOIiCq/3O/Pd99kz/Xpp586HiwoKbdu3YJer7/vWldXrlwp8DMstx8AXn/9dWg0GjzyyCOoX78+JkyYgAMHDji9X1paGlauXJnnXsSoUaMAPPi9iEuXLkEIgfr16+d5j/Pnzzsdf9CgQcjOznasLWowGPDLL7/gmWeecdw7uHTpEgCga9eueY7366+/FjvewlxPSKVSDBs2DFu3bnWs/REVFQW1Wu1UMqsgXl5eePfddxEfH4/4+HisWrUKDRs2xCeffIK333670LH++75Lca5r+vbtC61Wix07duQpUX7p0iVs3749z59v9+7dATz4vwmqOrimBlE5snv3biQkJGDDhg3YsGFDnv6oqCj06NGjSMfMXWjpP//5D3r27JnvmH8nQorq7NmzkMlk90w6vPzyy+jbty+2bt2KHTt2YObMmZg/fz52796N1q1bF+p93NzcHijOfyuozmRZLtJd2JknREREriSVStGlSxd89NFHuHTpEpo2bZpnzFNPPQWVSoXIyEiYTCan9S5KmkajQbt27fD9998jMzMzz42CwtixYweAnDrX169fd1rzioiIqLR5eXkhICAAZ8+ezdOXu8ZGYR7Ic9X32saNG+PixYv46aefsH37dmzatAnLli3DrFmzMGfOHMe9iOHDh+e79ieQ87T/g7Db7ZBIJNi2bVu+363vngXTvn17hIaG4ttvv8XQoUPx448/Ijs7G4MGDXI6HpCzroa/v3+e48nlpXsbdcSIEXjvvfewdetWDBkyBOvXr8eTTz4JLy+vIh0nJCQEo0ePxoABA1CnTh1ERUVh7ty5hdq3JO67REREYO3atYiKinKaoQLk/Bk/8cQTeO211/LdNzfZQ3Q/TGoQlSNRUVHw9fXNd2rp5s2bsWXLFqxYsQJubm4ICQnBnj17kJWV5TRbIzY21mm/OnXqAMgpv5Cb+S5JV69exb59+xAWFlbgTI1cdevWxSuvvIJXXnkFly5dQqtWrfDBBx84nj4p6GKsOHJnqNx9zD///BMAHItY5U6BTEtLc7qR8e/ZFEWJLbfMxsWLF9G1a1envosXL5ZYGQ4iIqKyZrVaAeT/RCmQ8yW4f//+WLduHcLDwx0LX5dFPB4eHggJCcHp06dht9udZmtcuHABAJw+g7dv347PP/8cr732GqKiohAZGYnDhw/nuVlx8+bNPEmTf19P/Nvd1wL/duHCBVSvXt1xvJK89iEiooqnT58++Pzzz/H777/jkUceKdYx7v5ee7d/f6+tUaMGPD09802i3C0kJKTAz7Dc/lweHh4YNGgQBg0aBLPZjIEDB2LevHmYPn06atSoAa1WC5vNVir3IoCcewxCCNSuXbtQN8OfffZZfPTRR9Dr9fjmm28QGhqK9u3bOx0PAHx9fUs05sJeTzRr1gytW7dGVFQUatWqhatXr2LJkiXFfl8fHx/UrVvX6e+8qNceRbmuyfXee+9BLpfjpZdeglardZq9W7duXRgMhlL7N0FVB8tPEZUT2dnZ2Lx5M5588kk8/fTTeV4TJ05ERkaGY6pkz549YbFY8NlnnzmOYbfb8yREfH190blzZ3z66adISEjI8763bt0qdsypqakYMmQIbDYbZsyYUeC4rKwsGI1Gp7a6detCq9U61Xb08PDIcyFWXDdv3sSWLVsc23q9Hl9++SVatWrleOIi94Ll7pqNmZmZWLt2bZ7jFTa2tm3bwtfXFytWrHA6t23btuH8+fPo06dPcU+JiIjIZSwWC3799VcolUpH+Yn8/Oc//8Hs2bMxc+bMUo0nNTUVBw8ehL+/P3x9fQEAvXv3RmJiIr755hvHOKvViiVLlkCj0aBTp04Acm76PP/883jkkUfwzjvv4PPPP8fx48fxzjvv5Hkfq9WKTz/91LFtNpvx6aefokaNGmjTpk2+sQUEBKBVq1ZYu3at07XD2bNn8euvv6J3796OttybACV1/UNERBXLa6+9Bnd3d4wePRpJSUl5+oUQ9z2Gp6cnqlevnmctgmXLljltS6VS9O/fHz/++COOHj1a4Hv17t0bv//+O2JiYhx9mZmZWLlyJUJDQ9GkSRMAQEpKitP+SqUSTZo0gRACFosFMpkMERER2LRpU76JlAe5F5Fr4MCBkMlkmDNnTp4/KyFEnhgHDRoEk8mEtWvXYvv27Xlmlfbs2ROenp545513YLFYSizmolxPPPfcc/j111+xePFiVKtWDeHh4fc9/qlTp3D79u087VeuXMEff/zhVDqqqNceRbmuySWRSLBy5Uo8/fTTiIyMdNzHAnISSzExMY4Zs3dLS0tzPLRCdD+cqUFUTvzwww/IyMjAU089lW9/+/btUaNGDURFRWHQoEHo378/HnnkEbzyyiuIjY1Fo0aN8MMPPyA1NRWAc/Z96dKleOyxx9C8eXOMHTsWderUQVJSEmJiYnD9+nWcOnXqvvH9+eefWLduHYQQ0Ov1OHXqFDZu3AiDwYBFixahV69e99y3W7duePbZZ9GkSRPI5XJs2bIFSUlJGDx4sGNcmzZtsHz5csydOxf16tWDr69vntkOhdWgQQOMGTMGR44cgZ+fH7744gskJSVh9erVjjE9evRAcHAwxowZg1dffRUymQxffPEFatSogatXrzodr7CxKRQKLFy4EKNGjUKnTp0wZMgQJCUl4aOPPkJoaCimTp1arPMhIiIqS9u2bXM8kZmcnIz169fj0qVL+O9//5unNvLdWrZsiZYtW5Z4PN999x00Gg2EELh58yZWrVqFO3fuYMWKFY5rnnHjxuHTTz/FyJEjcezYMYSGhuK7777DgQMHsHjxYseM0ilTpiAlJQU7d+6ETCZDr1698Pzzz2Pu3Lno16+fU/yBgYFYuHAh4uPj0aBBA3zzzTc4efIkVq5cCYVCUWC87733HsLDwxEWFoYxY8YgOzsbS5YsgZeXF958803HuNwbGTNmzMDgwYOhUCjQt2/fYpXTIiKiiqd+/fpYv349hgwZgoYNG2LYsGFo2bIlhBCIi4vD+vXrIZVKUatWrXse5/nnn8eCBQvw/PPPo23btti/f79jJsDd3nnnHfz666/o1KkTxo0bh8aNGyMhIQEbN27Eb7/9Bm9vb/z3v//F119/jfDwcEyePBk6nQ5r165FXFwcNm3a5JgN2aNHD/j7+6NDhw7w8/PD+fPn8cknn6BPnz6Oz9wFCxZgz549aNeuHcaOHYsmTZogNTUVx48fx86dOx33L+4lNjY239JJrVu3Rp8+fTB37lxMnz4d8fHx6N+/P7RaLeLi4rBlyxaMGzcO//nPfxz7PPTQQ6hXrx5mzJgBk8nkVHoKyEkQLV++HM899xweeughDB482HF/4Oeff0aHDh3wySef3DfmfyvK9cTQoUPx2muvYcuWLRg/fvw9rzdyRUdHY/bs2XjqqafQvn17aDQa/PXXX/jiiy9gMpnyvfaYPHkyevbsCZlM5nRfJj+Fva65m1Qqxbp169C/f388++yz+OWXX9C1a1e8+uqr+OGHH/Dkk09i5MiRaNOmDTIzM3HmzBl89913iI+PL/XZvlRJCCIqF/r27SvUarXIzMwscMzIkSOFQqEQt2/fFkIIcevWLTF06FCh1WqFl5eXGDlypDhw4IAAIDZs2OC07+XLl8WIESOEv7+/UCgUombNmuLJJ58U33333X1jA+B4SaVS4e3tLVq3bi2mTJkizp07l2d8XFycACBWr14thBDi9u3bYsKECaJRo0bCw8NDeHl5iXbt2olvv/3Wab/ExETRp08fodVqBQDRqVMnIYQQq1evFgDEkSNH8rxXbl9cXJyjLSQkRPTp00fs2LFDtGjRQqhUKtGoUSOxcePGPPsfO3ZMtGvXTiiVShEcHCwWLVqU7zELim3Pnj0CgNizZ4/Tcb/55hvRunVroVKphE6nE8OGDRPXr193GhMZGSk8PDzyxDR79mzBX89EROQKuZ+Bd7/UarVo1aqVWL58ubDb7U7jAYgJEybc85i5n2u3bt1ytBX0GVjQvne/PDw8RFhYWJ7rCCGESEpKEqNGjRLVq1cXSqVSNG/e3HE9IoQQ33//vQAgPvjgA6f99Hq9CAkJES1bthRms1kIIUSnTp1E06ZNxdGjR0VYWJhQq9UiJCREfPLJJ077/vu6J9fOnTtFhw4dhJubm/D09BR9+/YVf/zxR56Y3377bVGzZk0hlUrzXH8QEVHVEBsbK8aPHy/q1asn1Gq1cHNzE40aNRIvvviiOHnypNPY/L4vZmVliTFjxggvLy+h1WrFs88+K5KTkwUAMXv2bKexV65cESNGjBA1atQQKpVK1KlTR0yYMEGYTCbHmMuXL4unn35aeHt7C7VaLR555BHx008/OR3n008/FR07dhTVqlUTKpVK1K1bV7z66qsiPT3daVxSUpKYMGGCCAoKEgqFQvj7+4tu3bqJlStX3vfPJSQkJM91QO5rzJgxjnGbNm0Sjz32mPDw8BAeHh6iUaNGYsKECeLixYt5jjljxgwBQNSrV6/A992zZ4/o2bOn8PLyEmq1WtStW1eMHDlSHD161DGmsN/bC3s9cbfevXsLAOLgwYP3Pb4QQvz1119i1qxZon379sLX11fI5XJRo0YN0adPH7F7926nsVarVUyaNEnUqFFDSCQSxznkXs+89957+b5HYa5r8rvmy8rKEp06dRIajUYcOnRICCFERkaGmD59uqhXr55QKpWievXq4tFHHxXvv/++4zqM6H4kQhRiLhsRVRhbt27FgAED8Ntvv6FDhw6uDoeIiIioQurcuTNu375939rjRERERCVpwIABOHPmTJ41U4noH1xTg6gCy87Odtq22WxYsmQJPD098dBDD7koKiIiIiIiIiIiKqqEhAT8/PPPeO6551wdClG5xjU1iCqwSZMmITs7G2FhYTCZTNi8eTMOHjyId955B25ubq4Oj4iIiIiIiIiI7iMuLg4HDhzA559/DoVCgRdeeMHVIRGVa0xqEFVgXbt2xQcffICffvoJRqMR9erVw5IlSzBx4kRXh0ZERERERERERIWwb98+jBo1CsHBwVi7di38/f1dHRJRucY1NYiIiIiIiIiIiIiIqELgmhpERERERERERERERFQhMKlBREREREREREREREQVAtfUAGC323Hz5k1otVpIJBJXh0NERFRuCCGQkZGBwMBASKV8FuJuvH4gIiIqGK8h8sfrByIiooIV9vqBSQ0AN2/eRFBQkKvDICIiKreuXbuGWrVquTqMcoXXD0RERPfHawhnvH4gIiK6v/tdPzCpAUCr1QLI+cPy9PR0cTRERETlh16vR1BQkOOzkv7B6wciIqKC8Roif7x+ICIiKlhhrx+Y1AAcUz49PT15UUFERJQPlkfIi9cPRERE98drCGe8fiAiIrq/+10/sLAlERERERERERERERFVCExqEBERERERERERERFRhcCkBhERERERERERERERVQhMahARERERERERERERUYXApAYREREREREREREREVUITGoQEREREREREREREVGFIHd1AERERERERA/CbDZj27ZtSEhIQEBAAMLDw6FUKl0dFhERVVJmsxnff/89bt68icDAQPTr14+fO0REZYhJDSIiIiIiqrBWr16NrVu3QgjhaPviiy/Qv39/jBo1yoWRERFRZbRixQp8++23sNvtjrbly5fj2WefxYsvvujCyIiIqg4mNYiIiIiIqEJavXo1tmzZkqddCOFoZ2KDiIhKyooVK7BhwwZIJBKndiEENmzYAABMbBC5gM1mw+nTp5GamgqdTocWLVpAJpO5OiwqRUxqEBERERFRhWM2m/NNaNxty5YtGDZsGEuCEBHRAzObzfj2228BwGl24N3b3377LUaPHs3PHaIytH//fixduhRJSUmONj8/P0yYMAEdO3Z0YWRUmrhQOBERERERVTg//fRTiY4jIiK6ly1btjhKTkmlzrfTcrftdvt9E+5EVHL279+PWbNmIS0tzak9LS0Ns2bNwv79+10TGJU6ztQgIqogTCYTzGZzkfdTKpVQqVSlEBEREZHrxMTEOH6WyWTo378/evTogV9//RVbt26FzWZzjBs4cKCrwiQiokri1KlTjp/btm0LtVoNg8EAjUYDo9GI33//3TFu0KBBrgqTqMqw2WxYtGgRAOChhx7C8OHDUbt2bcTFxWHdunWIiYnBokWL0KFDB5aiqoSY1CAiqgBMJhNCQkORlJhY5H39/P1xJT6eiQ0iIqpUUlJSHD9/9dVX2LVrF77//nsEBATgq6++wtChQ/OMIyIiKq5bt24BABQKhSOBcTeFQgGLxeIYR0Sl6+TJk0hLS0Pz5s0xb948x4yppk2bYt68eZgyZQrOnDmDkydPok2bNi6OlkoakxpERBWA2WxGUmIiNh+/BHeNptD7ZRkMGPhQfZjNZiY1iIioUrFarY6fcxMYuVatWpXvOCIiouLKXSfDYrFALpejefPmqFatGlJSUnDmzBlYLBancURUuk6ePAkAGDVqFIQQOHHihNNC4SNHjsQrr7zCpEYlxaQGEVEF4q7RwF2jdXUYRERELufm5panfnJB44iIiB6Ur68vzp07ByAnYX7ixIkCxxFR2Tl9+jTeffddJN5V2cLf3x89e/Z0YVRU2pjUIKJKg2tOEBERVR3NmzdHQkJCocYRERE9KKPRWKLjiOjBtGrVCl999RXWrFmDsLAwzJw502lNjbVr1zrGUeUjdXUAREQlIXfNCU9PzyK/QkJDYTKZXH0KRFSKFixYAIlEgpdfftnR1rlzZ0gkEqfXiy++6LogiahIPD09S3QcERHRvRT2OyO/WxKVjebNmzvW0RBCOPXlbkulUj7gUkm5dKbG/PnzsXnzZly4cAFubm549NFHsXDhQjRs2NAxxmg04pVXXsGGDRtgMpnQs2dPLFu2DH5+fo4xV69exfjx47Fnzx5oNBpERkZi/vz5kMs5EYWoquCaE0RUkCNHjuDTTz9FixYt8vSNHTsWb731lmPb3d29LEMjogewc+fOQo8bMWJEKUdDRESVHWdqEJUv586dg91uBwCcOHEChw4dcvTl3t+x2+04d+4cWrdu7ZIYqfS4dKbGvn37MGHCBBw6dAjR0dGwWCzo0aMHMjMzHWOmTp2KH3/8ERs3bsS+fftw8+ZNDBw40NFvs9nQp08fmM1mHDx4EGvXrsWaNWswa9YsV5wSEblY7poThX8VPgFSUkwmEzIyMor8IqKiMxgMGDZsGD777DP4+Pjk6Xd3d4e/v7/jxSe6iSqO7OzsEh1HRER0L/9+EvxBxxHRg0lNTQUAzJgxI893PZ1OhxkzZjiNo8rFpVMZtm/f7rS9Zs0a+Pr64tixY+jYsSPS09OxatUqrF+/Hl27dgUArF69Go0bN8ahQ4fQvn17/Prrr/jjjz+wc+dO+Pn5oVWrVnj77bfx+uuv480334RSqXTFqRER5Su3TFbSXQtYFYXNaivhiIgqtwkTJqBPnz7o3r075s6dm6c/KioK69atg7+/P/r27YuZM2dytgZRBSGXyx0lPlavXo2NGzfi5s2bCAwMxDPPPINRo0Y5xhERET2owt4Y5Q1UorKh0+kAAIGBgYiKisLp06eRmpoKnU6HFi1a4MKFC07jqHIpV1f46enpAP75x3bs2DFYLBZ0797dMaZRo0YIDg5GTEwM2rdvj5iYGDRv3typHFXPnj0xfvx4Ti8ionKnuGWyUpISMezx1rDZmNQgKqwNGzbg+PHjOHLkSL79Q4cORUhICAIDA3H69Gm8/vrruHjxIjZv3pzveJPJ5FQjWa/Xl0rcVHmYTCZcv37d1WFUWnc/CTt+/Hg89dRT6N+/P/744w+MHz/eadzly5ddEWKlV6tWLZbvJKIqw8fHB0lJSYUaR0Slr0WLFvD390dUVBTmzp3rdA/YbrcjKioKAQEB+ZYhpoqv3CQ17HY7Xn75ZXTo0AHNmjUDACQmJkKpVMLb29tprJ+fHxL/fso5MTHRKaGR25/blx/elCAiV8stk1VYWQZDKUZDVPlcu3YNU6ZMQXR0NNRqdb5jxo0b5/i5efPmCAgIQLdu3XD58mXUrVs3z/j58+djzpw5pRYzVT7Xr1/H1KlTXR1GlWA0GvHtt9/m25eVlcW/h1Ly4Ycf5vv7koioMpJIJCU6jogejEwmw0svvYTZs2fj//7v/1CzZk2YTCaoVCrcuHEDhw8fxpw5cyCTyVwdKpWCcpPUmDBhAs6ePYvffvut1N+LNyWIiIgqt2PHjiE5ORkPPfSQo81ms2H//v345JNPYDKZ8lzctmvXDgAQGxub70266dOnY9q0aY5tvV6PoKCgUjoDqgxq1aqFDz/80NVhVFqfffYZ/vjjj/uOa9KkCcaOHVsGEVU9tWrVcnUIRERlxmw2l+g4InpwHTt2xKOPPooDBw7k6evQoQM6duzogqioLJSLpMbEiRPx008/Yf/+/U4Xxv7+/jCbzUhLS3OarZGUlAR/f3/HmN9//93peLnTAXPH/BtvShAREVVu3bp1w5kzZ5zaRo0ahUaNGuH111/P92mdkydPAgACAgLyPaZKpWKZFSoSlUrFp9hL0cyZMzFkyJBCjfPw8CiDiIiIqDK7detWiY4joge3YsUKHDhwAD4+PnjiiSdQs2ZN3LhxA9HR0Thw4ABWrFiBF1980dVhUilwaVJDCIFJkyZhy5Yt2Lt3L2rXru3U36ZNGygUCuzatQsREREAgIsXL+Lq1asICwsDAISFhWHevHlITk6Gr68vACA6Ohqenp5o0qRJvu/LmxJERESVm1ardZSzzOXh4YFq1aqhWbNmuHz5MtavX4/evXujWrVqOH36NKZOnYqOHTuy5ipRBeHh4YF69eohNja2wDH16tVjQoOIiEqEVCot0XFE9GDMZjM2btwIHx8fbNy4EXL5P7e5x40bh2eeeQYbN27E6NGjoVQqXRgplQaX/qadMGEC1q1bh/Xr10Or1SIxMRGJiYnIzs4GAHh5eWHMmDGYNm0a9uzZg2PHjmHUqFEICwtD+/btAQA9evRAkyZN8Nxzz+HUqVPYsWMH3njjDUyYMIGJCyIiIsqXUqnEzp070aNHDzRq1AivvPIKIiIi8OOPP7o6NCIqgkWLFqFevXr59tWrVw+LFi0q44iIiKiyKmxdftbvJyob33//PWw2G8aMGeOU0AAAuVyO0aNHw2az4fvvv3dRhFSaXDpTY/ny5QCAzp07O7WvXr0aI0eOBJCz+JxUKkVERARMJhN69uyJZcuWOcbKZDL89NNPGD9+PMLCwuDh4YHIyEi89dZbZXUaREREVAHs3bvX8XNQUBD27dvnumCIqMQsWrQImZmZmDdvHs6ePYtmzZphxowZnKFBREQlytfXFykpKYUaR0Sl7+bNmwDgqObzb7ntueOocnHpTA0hRL6v3IQGAKjVaixduhSpqanIzMzE5s2b86yVERISgl9++QVZWVm4desW3n///TwZOiIiIiIiqpw8PDwwZswYAMCYMWOY0CCifO3fvx99+/ZFYGAgJBIJtm7dmmfM+fPn8dRTT8HLywseHh54+OGHcfXqVUe/0WjEhAkTUK1aNWg0GkRERDjW9aTKTaFQlOg4InowgYGBAICYmJh8+3Pbc8dR5cJCf0RERERERERU6WVmZqJly5ZYunRpvv2XL1/GY489hkaNGmHv3r04ffo0Zs6cCbVa7RgzdepU/Pjjj9i4cSP27duHmzdvYuDAgWV1CuRC169fL9FxRPRg+vXrB5lMhlWrVsFqtTr1Wa1WfPHFF5DJZOjXr5+LIqTSxOkMRERERERERFTphYeHIzw8vMD+GTNmoHfv3nj33XcdbXXr1nX8nJ6ejlWrVmH9+vXo2rUrgJzy2Y0bN8ahQ4cca39S5WQymUp0HBE9GKVSiWeeeQYbNmzAM888g9GjRyMsLAwxMTH44osvcOfOHQwePJiLhFdSnKlBRERERERERFWa3W7Hzz//jAYNGqBnz57w9fVFu3btnEpUHTt2DBaLBd27d3e0NWrUCMHBwQWWPzGZTNDr9U4vqpgKe2OUN1CJys6LL76IwYMHQ6/X44MPPsDTTz+NDz74AHq9HoMHD8aLL77o6hCplHCmBhERERERERFVacnJyTAYDFiwYAHmzp2LhQsXYvv27Rg4cCD27NmDTp06ITExEUqlEt7e3k77+vn5ITExMd/jzp8/H3PmzCmDM6DS5uXlhTt37hRqHBGVnRdffBGjR4/G999/j5s3byIwMBD9+vVjgrGSY1KDiEqVyWSC2Wwu0j5KpRIqlaqUIiIiIiIiInJmt9sB5NRonzp1KgCgVatWOHjwIFasWIFOnToV67jTp0/HtGnTHNt6vR5BQUEPHjCVuYyMjBIdR0QlJ7cUFVUdTGoQUakxmUwICQ1FUgFPLRXEz98fV+LjmdggIiIiIqIyUb16dcjlcjRp0sSpvXHjxvjtt98AAP7+/jCbzUhLS3OarZGUlAR/f/98j6tSqfi9ppIwGo0lOo6IiIqPSQ0iKjVmsxlJiYnYfPwS3DWaQu2TZTBg4EP1YTabefFPRERERERlQqlU4uGHH8bFixed2v/880+EhIQAANq0aQOFQoFdu3YhIiICAHDx4kVcvXoVYWFhZR4zla3c2TwlNY6IiIqPSQ0iKnXuGg3cNVpXh0FERERERFWYwWBAbGysYzsuLg4nT56ETqdDcHAwXn31VQwaNAgdO3ZEly5dsH37dvz444/Yu3cvgJy1EsaMGYNp06ZBp9PB09MTkyZNQlhYGNq3b++is6Ky4ubmhuzs7EKNIyKi0sWkBhERilf3lGt/EBERERFVHEePHkWXLl0c27lrXURGRmLNmjUYMGAAVqxYgfnz52Py5Mlo2LAhNm3ahMcee8yxz4cffgipVIqIiAiYTCb07NkTy5YtK/NzobLn4eGB1NTUQo0jIqLSxaQGEVVpZrMJEqkUNWvWLPK+XPuDiIiIiKji6Ny5M4QQ9xwzevRojB49usB+tVqNpUuXYunSpSUdHpVzFoulRMcREVHxMalBRFWa1WyBsNux4dA5eOt0hd6Pa38QERERERFVHXq9vkTHERFR8TGpQUQEwN2D634QERERERFR/qxWa4mOIyKi4pO6OgAiIiIiIiIiIqLyTCaTleg4IiIqPiY1iIiIiIiIiIiI7sHLy6tExxERUfExqUFERERERERERHQPdru9RMcREVHxMalBRERERERERER0DxkZGSU6joiIio9JDSIiIiIiIiIiontQKBQlOo6IiIpP7uoAiIgqAyEETDYBi11AIpFAJgGkEkAmkUAulbg6PCIiIiIiInoAWq0Wer2+UOOIiKh0MalBRHQfQgiY7QJZVgGjVcBoE8gySzF+7TasjTfBYjfDZBcF7q+USuChkMBLKYNWakPb/sORbQPcRE4ChIiIiIiIiMq39PT0Eh1HRETFx6QGEdFdLHYBg8WOLKsdWVbh+G/enIUUwc3bwmAFgH86JU5bOcx2AbNJ4I4pZ8G4iFkf4kI2IDca4aWSQaeSQqeScUYHERERERFROZWdnV2i44iIqPiY1CCiKstqF8iCDI8/9xKuWZWIvWWEyZb/jAsJADe5BGqZBCqZBFKrGQsnj8GWDVHQaT2glkmhkv1TasouchIhViGQbRXIsNhxx2RDoj4b30XvRf2HH4NVSJBitCHFaIMUFujUMgS4y6BVSDmDg4iIiIiIqBwRouDZ+cUZR0Qlx2az4fTp00hNTYVOp0OLFi0gk8lcHRaVIiY1iKjKsNoF9GY70s126M02GKwCgBa9p86BXgD4O6GhlkngoZDCXS6Buzznv2qZBNK7Eg1ZBhPO7f4Z/moptOq8v0qlEgmkEkAOCdQywEclQ7BGgTpKC3q9MBDbLibApnLHHZMdt402GG0Ct4023Dba4CGXIEijgE7F5AYREREREVF5oFAoYDKZCjWOiMrO/v37sWzZMiQmJjra/P398dJLL6Fjx44ujIxKE5MaRFRp2UVOEiPNbEe62QaDJe8TM3LYcXLXL+j6RA/U8NJAo5CWSRkoiQTwVMrgqZQhWCOHwSqQlGXFrWwbMq0CF9LMcJdLUFurgLeKTxcQERERERG5kk6nQ0JCQqHGEVHZ2L9/P2bPno2wsDDMnDkTtWvXRlxcHKKiojB79mzMmTOHiY1KikkNIqpUrAJIzrbijimn3NO/q0mpZRJ4KaXwVErhpZQh41YiXn11FAadueKy5IFEIoFWIYHWS4kQrcDNTCsSsqzIsgqcu2OGj0oKH0hdEhuVDJPJBLPZXKR9lEolVCpVKUVERERERERFUdhrc17DE5UNm82GZcuWISwsDHPnzoVUmnPfpGnTppg7dy7eeOMNLF++HB06dGApqkrIpXfJ9u/fj759+yIwMBASiQRbt2516pdIJPm+3nvvPceY0NDQPP0LFiwo4zMhIley2AViDTYMf38NzmbKcCndgtvGnISGQgr4qmWo76VA2xoqtKmhRj0vJXzd5FDJyl9pJ4VUghCtAm1qqBHgLoMEwB2THXHQ4tHBY8HyrBWPyWRCSGgoPD09i/QKCQ0t1PR2IiIiIiIqfUlJSSU6jogezOnTp5GYmIhhw4Y5Ehq5pFIphg0bhoSEBJw+fdpFEVJpculMjczMTLRs2RKjR4/GwIED8/T/e1rftm3bMGbMGERERDi1v/XWWxg7dqxjW6vVlk7ARFSuJGRacOK2ERfSzDDbBZp27QMBwF0ugU4lg04lg0YhqZDrUiikEtTxVMLf3Y7L6RboLXb0fe0dXLHZ4G4T5TIhQ/kzm81ISkzE5uOX4K7RFGqfLIMBAx+qD7PZzCe9iIiIiIiIiP4lNTUVAFC7du18+3Pbc8dR5eLSpEZ4eDjCw8ML7Pf393fa/v7779GlSxfUqVPHqV2r1eYZS0SVk8UucP6OCcdvG5GYZXW0a+TATys/wosTJqCaV+VJbLrLpWimUyI2KRXXswXg5oGTt41o4K2ED9faqFDcNRq4ayrPv00iIiIioqqksOVrWOaGqGzkrl8TFxeHpk2b5umPi4tzGkeVS4Up0p6UlISff/4ZY8aMydO3YMECVKtWDa1bt8Z7770Hq9WazxGIqCLLstqxPyETS8+m4perBiRmWSGTAE19VBhW3wsjQpTY8clcuFXC60eJRAIfmPHJsO5Qww6rAP64Y8Z1gwWC9aiIiIiIiIhKXXZ2domOI6IH06JFC/j7+yMqKgp2u92pz263IyoqCgEBAWjRooWLIqTSVGGSGmvXroVWq81Tpmry5MnYsGED9uzZgxdeeAHvvPMOXnvttXsey2QyQa/XO72IqHzSm23Yed2A5edScTAxG0abgJdSis6B7pjQVIe+oVoEaRQVssRUUd2Kj0VtuRF+f2durhis+DPdAjsTG0T3tWDBAkgkErz88suONqPRiAkTJqBatWrQaDSIiIhgDWQiIiIiypfNZivRcUT0YGQyGV566SXExMTgjTfewLlz55CVlYVz587hjTfeQExMDMaPH8/ZU5WUS8tPFcUXX3yBYcOGQa1WO7VPmzbN8XOLFi2gVCrxwgsvYP78+QXWIZ8/fz7mzJlTqvESVTYmkwlms7lI+2RkZBT7/TKtAjHXDDiZYoT973v2fm4yhPm5o4G3EtIqkMTIj1QC1PNSQqOw4i99zoLoVrtAQ28l5NKq+WdCdD9HjhzBp59+mucJnalTp+Lnn3/Gxo0b4eXlhYkTJ2LgwIE4cOCAiyIlIiIiovJKIpEUaqZ8VXjgjqi86NixI+bMmYNly5ZhwoQJjvaAgADMmTMHHTt2dGF0VJoqRFLjf//7Hy5evIhvvvnmvmPbtWsHq9WK+Ph4NGzYMN8x06dPd0qG6PV6BAUFlVi8RJWNyWRCSGgokhITi7W/zVr4J1WsAug58Q2su2KG9e/rxSCNHI/6uSNUWzVmZBSGv7scKpkEF9LMSDPbcTbVhCY+Kii5gDiRE4PBgGHDhuGzzz7D3LlzHe3p6elYtWoV1q9fj65duwIAVq9ejcaNG+PQoUNo3769q0ImIiIionJIqVTCZDIVahwRlZ2OHTuiQ4cOOH36NFJTU6HT6dCiRQvO0KjkKkRSY9WqVWjTpg1atmx537EnT56EVCqFr69vgWNUKlWBsziIKC+z2YykxERsPn4J7hpNofdLSUrEsMdbF2r6rV0IJGRZcS1Ths6jp8AqgEB3OToFuiNEy4vC/PioZGimU+GPVBMyrQJnUk1o6qOEWl5hKgsSlboJEyagT58+6N69u1NS49ixY7BYLOjevbujrVGjRggODkZMTEy+SQ2TyeT0RZblK4mIiIiqDoVCUaikhkKhKINoiOhuMpkMrVu3dnUYVIZcmtQwGAyIjY11bMfFxeHkyZPQ6XQIDg4GkHPDYOPGjfjggw/y7B8TE4PDhw+jS5cu0Gq1iImJwdSpUzF8+HD4+PiU2XnkpzileoCcjD4TLlReuWs0cNdoCz0+y2Ao1Lg7Jhv+0ltgtAkAEiRe+gOjO7ZAcz8vzsy4D61CihbVVDh3xwyjTeBMqhnNdUxsEAHAhg0bcPz4cRw5ciRPX2JiIpRKJby9vZ3a/fz8kFjArDSWryQiIiKqunx8fGAoxHdcV9+PIiKqClya1Dh69Ci6dOni2M4tCRUZGYk1a9YAyLkhIYTAkCFD8uyvUqmwYcMGvPnmmzCZTKhduzamTp3qVFrKFR6kVI+fvz+uxMczsUFVQrbVjrgMC+6Y7AAAhRQIUNjwf0O64O20NCY0CslNLkULnQpnU03ItgmcvWNGc50KKpaioirs2rVrmDJlCqKjo/Osx1VcLF9JREREVHVxoXAiovLDpUmNzp0733eRpXHjxmHcuHH59j300EM4dOhQaYT2QIpbqifLYMDAh+rDbDYzqUGVmtUucD3TipuZVuTMzQAC3OUI0shhzjJA2O2uDrHCUcokaPp3YsNoEzibakJzHX+PUNV17NgxJCcn46GHHnK02Ww27N+/H5988gl27NgBs9mMtLQ0p9kaSUlJ8Pf3z/eYLF9JREREVPKMRiOuXr3q6jDuKz09vdDj/vzzz1KO5sEFBweX2MM/RERlrUKsqVFRFbVUD1FlJ4TALaMN8RkWWP7OW3grpajtqYD73+WSil60jXKpZBI00ylxJiWnFNW5OybU5f1XqqK6deuGM2fOOLWNGjUKjRo1wuuvv46goCAoFArs2rULERERAICLFy/i6tWrCAsLc0XIRERERFXS1atXC3yYtSLKzMysEOezcuVKNGjQwNVhEBEVC5MaRFQmDBY7/tJbkPF3NkMtk6C2VgEflZRlpkqQSiZFU50SZ1NNyLIKxNplULp5uDosojKn1WrRrFkzpzYPDw9Uq1bN0T5mzBhMmzYNOp0Onp6emDRpEsLCwvJdJJyIiIiISkdwcDBWrlzp6jDu68svv8Rvv/1233GPPfYYRowYUQYRPZjctWyJiCoiJjWIqFR5+FTHDasSaSkmAIBUAgR5yBHoIYeUyYxS4SaXOkpRZdslGDz/U9jvU+qPqCr68MMPIZVKERERAZPJhJ49e2LZsmWuDouIiIioSlGr1RVixsCMGTMQHh5eqHFubm5lEBERUdXFpAYRlQq7EEiFCq9sPYQ0kfOrpoZahhCtggtYlwF3uRSNvVU4k2pE4449ceC2Db09XR0VkWvt3bvXaVutVmPp0qVYunSpawIiIiIiogrDzc0NHTp0wIEDBwoc06FDByY0iIjKAJMaRFSihBC4Y7IjLsMCI9zgpnWDGnbU16nhqZS5OrwqRauUIkRtR7xRhtPpNvgmZ6OtLy+wiYiIiIiIimPevHmYMWNGvomNDh06YN68eS6IiqhkGY1GXL161dVhVCnBwcFQq9WuDqNCYVKDiEpMpiUnmZFuzlk3QwY7Nr79Ct6YMw+eSq7r4Ao+coHlH72F8CmzsOtGJrxVMtTzUro6LCIiIiIiogpp3rx5yM7OxsKFC7F371507twZr7/+OmdoUKVx9erVCrHYfWWycuXKClGGrzxhUoOIHpjZJnDVYEFStg0AIAEQ6CGHW+ZtHNmyDpK3+LSKK+1fuwSvzHwTf+jt+D5ejxENvFHDjb/+iYiIiIiIisPNzQ1Dhw7F3r17MXToUCY0qFIJDg7GypUrXR1GkV25csUxmyokJMTV4RRJcHCwq0OocHhXi6iKMZlMMJvNRdonIyMj33arXSAhy4obmVbY/l6HuppahlCNHGq5FLczHzRaKikda8iRaRe4YrBgc5wekQ29oZZJXR0WEREREREREZUjarW6Qs8aCAkJqdDxU+EwqUEVQnFuxCuVSqhUqlKKqGIymUwICQ1FUmJisfa3WXNmYtiEQGKWFdcNVlj/TmZ4yCWo7amAF9fNKJeyDAZ0q6HBt0bgjsmO7y+nIdxfDokk/0Xb+f8PERERERERERGVR0xqULlX3Bvxfv7+uBIfzxuzdzGbzUhKTMTm45fgrtEUer+UpEQMe7w1LFYbEjKtuJ5pwd/LZkAtkyBYI0d1tazAG+TkOmazCRKpFDVr1gQA1GrSCi988RPioELfyW9g/9ol+e7H/3+IiIiIiIiIiKg8YlKDyr3i3IjPMhgw8KH6MJvNvCmbD3eNBu4abaHHZxgM6Bg5EZesbrBmWAAASmlOMsPXjcmM8sxqtkDY7dhw6By8dToAwG2LBNdMQPiUmZj0+gxo5cJpH/7/Q0RERERERERE5RWTGlRhFPVGfFkrToksoHyX+THZ7EjMsuEmPBE+ZTasAFRSCWpq5PBzk0HKZEaF4e7xz/8/QULApLcgOduGeJMMrbQqqLi+BhERERERERERVQBMahCVgAdZq6K8lfkRQiDNbEdilhWppr9rTEGK5Lg/0bpeCIKrezGZUcFJJBLU8VQg02JHplXgzzQLmumUnHFDRERERERERETlHh/NJSoBd5fI2v5nQqFfm49fQlJiYrFmeJQ0i13gRqYFx2+b8McdsyOh4aWUIhCZWPzM4/CW2pjQqCRkEgkaeishlQB6ix3XM62uDomIiIiIqFTt378fffv2RWBgICQSCbZu3Vrg2BdffBESiQSLFy92ak9NTcWwYcPg6ekJb29vjBkzBgaDoXQDJyIiIiecqUFUgsp7iaz8GCx2JGRZcTvbhtx5GTIJ4Osmg7+7HO5yKW4npkLY7fc8DlU8bnIp6noqcCndgqsGK7yVMmiVzHUTERERUeWUmZmJli1bYvTo0Rg4cGCB47Zs2YJDhw4hMDAwT9+wYcOQkJCA6OhoWCwWjBo1CuPGjcP69etLM3QiIiK6C5MaRFWQXQDJ2VYkZFlhsPyzSLSHXAJ/dzlqqGWQSTkjoyqooZbhjsmO20YbLqab0apa+SiDRkRERERU0sLDwxEeHn7PMTdu3MCkSZOwY8cO9OnTx6nv/Pnz2L59O44cOYK2bdsCAJYsWYLevXvj/fffzzcJQkRERCWPSQ2iKiTdItBryiyczZTBBgsAQAKguloGf3cZtAop11WoYiQSCep6KpBhscNkE/hLb0EtfjIQERERURVkt9vx3HPP4dVXX0XTpk3z9MfExMDb29uR0ACA7t27QyqV4vDhwxgwYECefUwmE0wmk2Nbr9eXTvBERERVCG9dEVVydpFzo/r47Wz8pbegU+Qk2ACopBL4u8vg6yaHUsZERlUml0rQwEuBM6lm3DLa4K7ivwciIiIiqnoWLlwIuVyOyZMn59ufmJgIX19fpza5XA6dTofExMR895k/fz7mzJlT4rESERFVZUxqEP2LyWQq8sLdGRkZpRRN8ZlsdpxKMeHYrWykm/9ZD+PPg7vRq2sn+Ht5cFYGOXgqZQjSyHHNYMV1kxTa6n6uDomIiIiIqMwcO3YMH330EY4fP16i35OmT5+OadOmObb1ej2CgoJK7PhERERVEZMaRHcxmUwICQ1FUgFP2dyPzWor4YiKLt1sw9HkbJxKMcFsz1kvQy2ToLlOhQZudgQ/NAiD/kxgQoPyCPKQI9VoQ6YVGDhzEYQQ99+JiIiIiKgS+N///ofk5GQEBwc72mw2G1555RUsXrwY8fHx8Pf3R3JystN+VqsVqamp8Pf3z/e4KpUKKhXXrSMiIipJTGoQ3cVsNiMpMRGbj1+Cu0ZT6P1SkhIx7PHWsNlcl9RIyLLg96RsXEgzI/dWdDWVDA/7uqGpTgWFVFIuZ5RQ+SGRSNDAS4mTKUY0erwHLmTY8Yinq6MiIiIiIip9zz33HLp37+7U1rNnTzz33HMYNWoUACAsLAxpaWk4duwY2rRpAwDYvXs37HY72rVrV+YxExERVVVMahDlw12jgbtGW+jxWQZDKUZTMCEEYvVm/J6cjWsGq6M9WKPAI75uqOup4IwMKhJ3hRQBSjtummX47bYVjWrY4KmUuTosIiIiIqIHZjAYEBsb69iOi4vDyZMnodPpEBwcjGrVqjmNVygU8Pf3R8OGDQEAjRs3Rq9evTB27FisWLECFosFEydOxODBgxEYGFim50JERFSVMalBVAFZ7AJnU404kmxEqilndogUQGMfFR72dYO/O//XpuLzVQgcOnYUwc3bYttVA56t68nkGBERERFVeEePHkWXLl0c27lrXURGRmLNmjWFOkZUVBQmTpyIbt26QSqVIiIiAh9//HFphEtEREQF4J1Pogok02LHsdvZOHHLiGxbTpEplUyCVtXUaFNDzSfqqURIJMB3syfh1S0xiMuw4HSKCS2rq10dFhERERHRA+ncuXOR1o2Lj4/P06bT6bB+/foSjIqIiIiKSurKN9+/fz/69u2LwMBASCQSbN261al/5MiRkEgkTq9evXo5jUlNTcWwYcPg6ekJb29vjBkzBgYXlQIiKi23s6345WoGlp1LxcHEbGTbBLyUUnSr6YGXmvqgS00PJjSoRN2Kj0U7Xc6/qd03M2Gw2F0cERERERERERERkYtnamRmZqJly5YYPXo0Bg4cmO+YXr16YfXq1Y5tlUrl1D9s2DAkJCQgOjoaFosFo0aNwrhx4/jkBFV4QghcMVjwe3I2/tJbHO2B7nI84uuGBt5KSFkSiEpRS28Z4rIlSMiyIvq6AQNqc9VwIiIiIiIiIiJyLZcmNcLDwxEeHn7PMSqVCv7+/vn2nT9/Htu3b8eRI0fQtm1bAMCSJUvQu3dvvP/++1yoiyokm13gfJoJvydnIznb5mhv4KXEI75uqOkh5/oGVCakEgl6BWmw5mIaLqaZcSndhPpeqvvvSEREREREREREVErK/Zoae/fuha+vL3x8fNC1a1fMnTsX1apVAwDExMTA29vbkdAAgO7du0MqleLw4cMYMGCAq8ImKrJsqx2nUow4esvoKPWjkALNdWo87OsGHxXLS1HZ83OXo52vGw4lZ+PXa5kI1iigkrm0ciERERERVQEFVXPIz+bNm0sxEiIiIipvynVSo1evXhg4cCBq166Ny5cv4//+7/8QHh6OmJgYyGQyJCYmwtfX12kfuVwOnU6HxMTEAo9rMplgMpkc23q9vtTOgeh+/Os3wY4bWYg3mmD9e806dxnQwkuGpl4yqGUCMGchw+y8n1KpzFOOjag0dAhwx4U0E9LMduy7mYUeQRpXh0RERERElZyXl5erQyAiIqJyqlwnNQYPHuz4uXnz5mjRogXq1q2LvXv3olu3bsU+7vz58zFnzpySCJGoWIQQSDHZcS1Tginf7ENsdk77zQtncGD9pzi1YwtsFvM9j+Hn748r8fFMbFCpU0hzylBtuKzH8dtGNNWpUNND4eqwiIiIiKgSu3ttTSIiIqK7leukxr/VqVMH1atXR2xsLLp16wZ/f38kJyc7jbFarUhNTS1wHQ4AmD59OqZNm+bY1uv1CAoKKrW4iXIZrXYkG21IyrLBbBcAZLBZrfCUWBGokaNVm8bo03YxgMX3PE6WwYCBD9WH2WxmUoPKRKinEs10KpxNNWH7VQNGNvKGjGu7EBEREVEZsVqt2Lt3Ly5fvoyhQ4dCq9Xi5s2b8PT0hEbDmcRERERVSYVKaly/fh0pKSkICAgAAISFhSEtLQ3Hjh1DmzZtAAC7d++G3W5Hu3btCjyOSqXijWAqMza7QIrJhuRsG9LNdke7Qgp42o34T5+HsW73YXh7aV0YJdH9da3pgcvpZtwy2nD8lhEP+7q5OiQiIiIiqgKuXLmCXr164erVqzCZTHjiiSeg1WqxcOFCmEwmrFixwtUhEhERURly6WqvBoMBJ0+exMmTJwEAcXFxOHnyJK5evQqDwYBXX30Vhw4dQnx8PHbt2oV+/fqhXr166NmzJwCgcePG6NWrF8aOHYvff/8dBw4cwMSJEzF48GAEBga68MyoqrPZBW5lW3Hhjgm/JxtxKd3iSGh4KaWo76VA2xpqVIcR+lsFr/9CVJ64y6XoHOgBAPhfQpZjQXui8mj58uVo0aIFPD094enpibCwMGzbts3R37lzZ0gkEqfXiy++6MKIiYiIqCBTpkxB27ZtcefOHbi5/fNgzYABA7Br1y4XRkZERESu4NKZGkePHkWXLl0c27kloSIjI7F8+XKcPn0aa9euRVpaGgIDA9GjRw+8/fbbTrMsoqKiMHHiRHTr1g1SqRQRERH4+OOPy/xciLwDaiHVJkfCHRPSTHbcfbtXLZPA100GXzcZVDKX5hKphGVkZJTq+PKmRTUVTqYYkZBlxZ4bmegbyhlGVD7VqlULCxYsQP369SGEwNq1a9GvXz+cOHECTZs2BQCMHTsWb731lmMfd3d3V4VLRERE9/C///0PBw8ehFKpdGoPDQ3FjRs3XBQVERERuYpLkxqdO3eGEKLA/h07dtz3GDqdDuvXry/JsIgKxWIX0JvtSDfbkAItXv/5BBLsAEw56Qy1TILqahmqqWXwkOc8BUyVh9lsgkQqRc2aNYu1v81qK+GIyoZEIkHPIA3WXEzDuTsmtKymRrCWi4ZT+dO3b1+n7Xnz5mH58uU4dOiQI6nh7u5+zzW4iIiIqHyw2+2w2fJeP1+/fh1aLR+yISIiqmoq1JoaVPGZTCaYzeYi7VMenmwXQiDbJmCw2JFhtkNvsSPLendCLmfBb61CguoeKuhUMrgzkVGpWc0WCLsdGw6dg7dOV+j9UpISMezx1vl+Kaso/N3laF1djRO3jfj1ugGjuGg4lXM2mw0bN25EZmYmwsLCHO1RUVFYt24d/P390bdvX8ycOZOzNYiIiMqhHj16YPHixVi5ciWAnAdtDAYDZs+ejd69e7s4OiIiIiprTGpQmTGZTAgJDUVSYvHWkCjLJ9tNdiAz2wqDJSeRYbDaYc9nUpGbTAIvpRTSbD1e6NoC38acgbdGU2Zxkuu5e2jgrin802FZBkMpRlN2Oga440KaCbeNNhy7ZcQjXDScyqEzZ84gLCwMRqMRGo0GW7ZsQZMmTQAAQ4cORUhICAIDA3H69Gm8/vrruHjxIjZv3lzg8UwmE0wmk2Nbr9eX+jkQERER8MEHH6Bnz55o0qQJjEYjhg4dikuXLqF69er4+uuvXR0eERERlTEmNcqh4sxMUCqVTmuNlEdmsxlJiYnYfPwS3Itw47+0n2w3WOxIyLIgIdOKa3ozZu6+iD+y5AAsTuOkEkAjl0KjkECrlMFTIYVSlvN0+u1sC4wG3tyiqsPt70XDt1014LeELDT2VkKrlLk6LCInDRs2xMmTJ5Geno7vvvsOkZGR2LdvH5o0aYJx48Y5xjVv3hwBAQHo1q0bLl++jLp16+Z7vPnz52POnDllFT4RERH9rVatWjh16hQ2bNiA06dPw2AwYMyYMRg2bJjTwuFERERUNTCpUY48SI1+P39/XImPL/eJDQBw17juyXa7EEjMsuKqwYKbmVYkZFmRYbE7jXH31kECAQ+FFBqF9O9EhpTlpIj+pYVOhVO3jbiZZcXuG5noV9vT1SEROVEqlahXrx4AoE2bNjhy5Ag++ugjfPrpp3nGtmvXDgAQGxtbYFJj+vTpmDZtmmNbr9cjKCioFCInIiKiuxmNRqjVagwfPtzVoRAREVE5wKRGOVLcGv1ZBgMGPlQfZrO5QiQ1ylqK0YrYdDOuGCy4brDCnE8dqRpqGfzd5dDJbHi6Ryd8vnUHNFrWVSe6F4lEgh5BGqy9mIbzaWa0zDAjQCmKvG4OUDFmm1HFZ7fbncpH3e3kyZMAgICAgAL3V6lU/HdKRETkAr6+vhgwYACGDx+Obt26QSqVujokIiIiciEmNcqhotboJ2dCCBhsQK8psxB1xYw0i/MNLJVMgmCNArU85AjwUMDfTe4oI5WRkYGb509DygkZRIWSu2j48dtG/HrVgDd7tUTC9etFPk5Fmm1GFcP06dMRHh6O4OBgZGRkYP369di7dy927NiBy5cvY/369ejduzeqVauG06dPY+rUqejYsSNatGjh6tCJiIjoX9auXYv169ejX79+8PLywqBBgzB8+HC0bdvW1aERERGRCzCpQZWGySaQnG1FcrYNRpscnSInIc0iIJUAIRoFansqEaJRoIabDFKWkSIqMbmLhqea7ajbuS+WTptWpHVzONuMSkNycjJGjBiBhIQEeHl5oUWLFtixYweeeOIJXLt2DTt37sTixYuRmZmJoKAgRERE4I033nB12ERERJSPAQMGYMCAAcjIyMB3332Hr7/+Gu3bt0edOnUwfPhwzJo1y9UhEhERURliUoMqNCEE0sx2JGRZccf0z9oYUggc/2UTXhs1GE39PKGSVc7pyUVdVL44i9AT3Y9aLkWnvxcN7zbuVSjc3TjbjFxu1apVBfYFBQVh3759ZRgNERERlQStVotRo0Zh1KhR+OOPPzBs2DDMmTOHSQ0iIqIqhkkNqpCEEEg12XHdYIHB+s8aGZ4KKfzcZXCzZuP1N8bjs8nDKmVC40EWlQcAm9VWwhFRVddCp8KxpEwkQ4sbZju8XB0QEREREVU6RqMRP/zwA9avX4/t27fDz88Pr776qqvDIiIiojLGpAZVKEIIpBhtuGqwItuWk8yQAvBzlyHAXQ43eU4CI8vgwiDLQHEXlU9JSsSwx1vDZmNSg0qWRCJBxxpyfHvVhDtWKfRmGzyVMleHVeEVZ3YVF10nIiKiymbHjh1Yv349tm7dCrlcjqeffhq//vorOnbs6OrQiIiIyAWY1KAKI1tIcC3VDL0lp8yUTAIEuMsR6CGHooqu7F3UReWzDJU820Mu5aeW4tj36/HwgOH4S29By2pSSLh+TbE8yGwsLrpORERElc2AAQPw5JNP4ssvv0Tv3r2hUChcHRIRERG5EJMaVO5ZIcHAWYvxl1UNwA4pgJoeOckMeRVNZhCVVzs+mYf2A4Yh0wokZdvg786PmeIo7mwsLrpORERElVFSUhK0Wq7ZRkRERDl4t4nKLSEEbhltiIMnHu4/DABQQy1DiFYBlYzJDKLyKPPObfgr7bhhluFKhgXV1LIqO5OqJBR1NhYRERFRZaTVanH58mWsXr0aly9fxkcffQRfX19s27YNwcHBaNq0qatDJCIiojJU+VZQpkrBZBM4n2bGpXQL7JDg+h8nUVtmRANvJRMaROVcDYWAu1wCqwCuGiyuDoeIiIiIKrh9+/ahefPmOHz4MDZv3gzD32V1T506hdmzZ7s4OiIiIiprTGpQuSKEQHK2FSduG3HHZIcEQHVkY3lkL7hL7a4Oj4gKQSIB6mhz6hwnZtlgsPD/XSIiIiIqvv/+97+YO3cuoqOjoVQqHe1du3bFoUOHXBgZERERuQKTGlRuWO0Cf6ZbcCndApsANAoJWlVXoRpMsNtsrg6PiIrASyVDdbUMABCnt0AI4eKIiIiIiKiiOnPmDAYMGJCn3dfXF7dv33ZBRERERORKTGpQuWCw2HEqxYTbxpzkRbBGjhY6Fdzl/CdKVFGFahWQSgC9xY5bRiYmiYiIiKh4vL29kZCQkKf9xIkTqFmzpgsiIiIiIlfiHWNyKSEEErKsOJ1igtEmoJRK0FynRJBGAYmEa2cQVWQqmQS1POQAgPgMC6x2ztYgIiIioqIbPHgwXn/9dSQmJkIikcBut+PAgQP4z3/+gxEjRrg6PCIiIipjTGqQy9iEwKV0C/7SWyAA6FRStKqugqdS5urQiKiE1PSQQy2TwGIHrmdaXR0OEREREVVA77zzDho1aoSgoCAYDAY0adIEHTt2xKOPPoo33njD1eERERFRGZO7OgCqmoxWOy6kmZFpzXlyO1QrR6C7nLMziCoZqUSC2loFzqeZcTPTCl83GcvKEREREVGRKJVKfPbZZ5g5cybOnj0Lg8GA1q1bo379+q4OjYiIiFyASQ0qc3qrBFdSTLAKQCEFGnor4cXZGUSVlk4tg49KijsmO+L0FjTxUTKBSURERERFFhwcjODgYFeHQURERC7GpAaVGSEEHhs+HpeNOU9pa+QSNPJRQiXjU9tElV1trQJpJhPSzHakmuyopmYik4iIiIgKNm3atEKPXbRoUSlGQkREROUNkxpUJsw2gegkK/pMewsA4OsmQ11PBaR8WpuoSnCTS1HTQ47rmVbEZVjgrZJCxv//iYiIiKgAJ06cKNQ4zgAmIiKqepjUoFJ3x2TD5r/0uGW0w2axIMRDimBPNS8+iaqYWh5yJGdbYbIJ3My0IkijcHVIRERERFRO7dmzp8j7XL9+HYGBgZBKWQ2AiIioMnPpJ/3+/fvRt29fBAYGQiKRYOvWrY4+i8WC119/Hc2bN4eHhwcCAwMxYsQI3Lx50+kYoaGhkEgkTq8FCxaU8ZlQQS6nm7HmYhpuGW1wkwGfj49ADaVgQoOoCpJJJQjV5iQyrhusMNrsLo6IiIiIiCqTJk2aID4+3tVhEBERUSlzaVIjMzMTLVu2xNKlS/P0ZWVl4fjx45g5cyaOHz+OzZs34+LFi3jqqafyjH3rrbeQkJDgeE2aNKkswqd7EELgQGIWNv6lh8kmEOgux7NBSsQfj3F1aETkQtXVMngqpLADiNdbXB0OEREREVUiQghXh0BERERlwKXlp8LDwxEeHp5vn5eXF6Kjo53aPvnkEzzyyCO4evUqgoODHe1arRb+/v6lGisVntFmx0/xBsTqzQCA1tXV6FbTA9mZBhdHRkSuJpFIUMdTgZMpJqSY7Egz2aB0dVBEVdCtW7eg1+tdHQZRibp27ZrTf4kqE09PT9SoUcPVYRARERGVCxVqTY309HRIJBJ4e3s7tS9YsABvv/02goODMXToUEydOhVyeYU6tUrjVrYVm+P0uGOyQyYBegZp0KKa2tVhEVE54qGQIsBdhoQsG/7SW9CQvyKIytStW7fw0vgXYTJzthRVTosWLXJ1CEQlTqVUYNnyFUxsPKD9+/fjvffew7Fjx5CQkIAtW7agf//+AHJKYL/xxhv45Zdf8Ndff8HLywvdu3fHggULEBgY6DhGamoqJk2ahB9//BFSqRQRERH46KOPoNFoXHRWREREVU+FufNvNBrx+uuvY8iQIfD09HS0T548GQ899BB0Oh0OHjyI6dOnIyEh4Z5fZkwmE0wmk2ObTyo+OCEETtw2YveNTFgF4KmQYmAdT/i7V5h/YlTOZGRklOp4ur/S/DsI1ihwK9uGbJvALQvX2CEqS3q9HiazBc89dA3+WqOrwyEiovtIzFDjq+NB0Ov1TGo8oNwS2KNHj8bAgQOd+u4ugd2yZUvcuXMHU6ZMwVNPPYWjR486xg0bNgwJCQmIjo6GxWLBqFGjMG7cOKxfv76sT4eIiKjKqhB3nC0WC5599lkIIbB8+XKnvmnTpjl+btGiBZRKJV544QXMnz8fKpUq3+PNnz8fc+bMKdWYq5Isix2/XDMgNj2n3FRtrQJ9Q7RwV7h0yRaqoMxmEyRSKWrWrFms/W1WWwlHVPWUxd+BXCpBiFaBy3oLEsxSaHT8gk5U1vy1RgR5M6lBRESVh0Ry74dlHrQE9vnz57F9+3YcOXIEbdu2BQAsWbIEvXv3xvvvv+80o4OIiIhKT7lPauQmNK5cuYLdu3c7zdLIT7t27WC1WhEfH4+GDRvmO2b69OlOyRC9Xo+goKASjbuq+Etvxs9XMpBpFZBJgM6BHmhbQ33fi0migljNFgi7HRsOnYO3Tlfo/VKSEjHs8daw2ZjUeFBl9Xfg5yZDUpYVBisQPmV2ccMlIiIiIgJQ8guF/7sEdkxMDLy9vR0JDQDo3r07pFIpDh8+jAEDBuQ5BitFEBERlbxyndTITWhcunQJe/bsQbVq1e67z8mTJyGVSuHr61vgGJVKVeAsDiocg8WO3Tcy8cednIuz6moZ+oZo4cdyU1RC3D00cNdoCz0+y8CF6Etaaf8d5CwarsTpVCMe6jsI17LsaFL4tyMiIiKiKiY2NhaXL19Gx44d4ebmBiGE0wN1f/zxR4nNlsivBHZiYmKeew1yuRw6nQ6JiYn5HoeVIoiIiEqeS+9AGwwGxMbGOrbj4uJw8uRJ6HQ6BAQE4Omnn8bx48fx008/wWazOS4SdDodlEolYmJicPjwYXTp0gVarRYxMTGYOnUqhg8fDh8fH1edVqVm/3vtjP0JWTDZcp6CaVNDjc6BHlBIOTuDiIpGq5SiukLgtkWCPckW1KsuoJTxdwkRERER/SMlJQWDBg3C7t27IZFIcOnSJdSpUwdjxoyBj48PPvjgAwAosQoM9yqBXVSsFEFERFTyirXoQZ06dZCSkpKnPS0tDXXq1Cn0cY4ePYrWrVujdevWAHLWx2jdujVmzZqFGzdu4IcffsD169fRqlUrBAQEOF4HDx4EkDPjYsOGDejUqROaNm2KefPmYerUqVi5cmVxTovuIz7DjLUX0xB9PRMmm4C/uxwjG3rjiVoaJjSIqNgClXbcSbiGDCvwv4RMV4dDREREROXM1KlTIZfLcfXqVbi7uzvaBw0ahO3bt5foe91dAjs6OtqpBLa/vz+Sk5OdxlutVqSmpsLf3z/f46lUKnh6ejq9iIiI6MEUa6ZGfHx8vjXTTSYTbty4UejjdO7c+Z41L+9XD/Ohhx7CoUOHCv1+VHRCCFzJsOBgUjauGiwAAJVMgk4B7mhVXQ0p184gogckkwBb5/0Hoz75BkdvGdHYR4VAD4WrwyIiIiKicuLXX3/Fjh07UKtWLaf2+vXr48qVKyX2PvcrgR0WFoa0tDQcO3YMbdq0AQDs3r0bdrsd7dq1K7E4iIiI6N6KlNT44YcfHD/v2LEDXl5ejm2bzYZdu3YhNDS0xIIj1zHbBM7fMeH47WwkZecksGQSoFV1NR71c4eHoliTfIiI8vXnwd1ooJXizww7tl01YGRDb8g4A4yIiIiIAGRmZjrN0MiVmppapPUyH7QEduPGjdGrVy+MHTsWK1asgMViwcSJEzF48OASW8uDiIiI7q9ISY3+/fsDyFncNTIy0qlPoVAgNDTUUcuSKh6TzY6/9BZcSjcjNt0Msz1npoxcArSsrsYjvm7wUspcHCURVVaPVZfjWrYFt4w2HErORgf/vF9ciYiIiKjqefzxx/Hll1/i7bffBpBzT8Jut+Pdd99Fly5dCn2co0ePOo3PXesiMjISb775puNBzlatWjntt2fPHnTu3BkAEBUVhYkTJ6Jbt26QSqWIiIjAxx9//ABnR0REREVVpKSG3W4HANSuXRtHjhxB9erVSyUoKhs2IZCcZcX1TCviM8yIz7DAdlfFLx+VFK2qqdG8mhrucs7MIKLS5SaT4ImaGvxwJQMHErNQ11MJf/diVUkkwvLly7F8+XLEx8cDAJo2bYpZs2YhPDwcAGA0GvHKK69gw4YNMJlM6NmzJ5YtWwY/Pz8XRk1ERET5effdd9GtWzccPXoUZrMZr732Gs6dO4fU1FQcOHCg0Md50BLYQM6sjfXr1xf6PYmIiKjkFetuUVxcXEnHQWXAZLPjZqYV1zItuGGw4maWBRa78xgflRQNvFRo4K1EoLscEq6ZQURlqLGPEhfSlPgz3Ywfr2RgZENvKFiGioqhVq1aWLBgAerXrw8hBNauXYt+/frhxIkTaNq0KaZOnYqff/4ZGzduhJeXFyZOnIiBAwcW6cYIERERlY1mzZrhzz//xCeffAKtVguDwYCBAwdiwoQJCAgIcHV4REREVMaK/Qjsrl27sGvXLiQnJztmcOT64osvHjgwenAWu8CNTAuuZOS8ErKs+PdzJ2qZBDU95AjSKFDPU4lqahkTGUTkMhKJBOHBGtw8n4YUow17bmSiR5DG1WFRBdS3b1+n7Xnz5mH58uU4dOgQatWqhVWrVmH9+vXo2rUrAGD16tVo3LgxDh06hPbt27siZCIiIroHLy8vzJgxw9VhEBERUTlQrKTGnDlz8NZbb6Ft27YICAjgTfByxC4ELuvN+CPVhFi9Oc9MDC+lFLU8FKilkaOWhwLVmcQgonLGTS5FnxANvrmsx/HbRtTxVKKel9LVYVEFZrPZsHHjRmRmZiIsLAzHjh2DxWJB9+7dHWMaNWqE4OBgxMTEMKlBRERUzmzfvh0ajQaPPfYYAGDp0qX47LPP0KRJEyxduhQ+Pj4ujpCIiIjKUrGSGitWrMCaNWvw3HPPlXQ8VExylRqn0qw4c/UO0s3/ZDK0CimCNQqEaHNeXOibiCqC2p5KPFxDjSO3jPjlagbGNPKBh4Jr+1DRnDlzBmFhYTAajdBoNNiyZQuaNGmCkydPQqlUwtvb22m8n58fEhMTCzyeyWSCyWRybOv1+tIKnYiIiO7y6quvYuHChQByPt+nTZuGV155BXv27MG0adOwevVqF0dIREREZalYSQ2z2YxHH320pGOhYhBCINUiwbTNB/HbbRuAnMV2m+lUaKJTwd+N62IQUcXUKdAD8RkW3DLa8MvVDDxdx5O/z6hIGjZsiJMnTyI9PR3fffcdIiMjsW/fvmIfb/78+ZgzZ04JRkhERESFERcXhyZNmgAANm3ahL59++Kdd97B8ePH0bt3bxdHR0RERGWtWI+9Pv/881i/fn1Jx0JFZLELnE8z44pJBp+AIGjkQK8gDV5qpkO3WhoEuCt4A5CIKoyMjAynV3amAd1qSCGTAJf1Fuy/lpZnzN1PzVPFpdPpcPv2bQCAj48PdDpdga+iUCqVqFevHtq0aYP58+ejZcuW+Oijj+Dv7w+z2Yy0tDSn8UlJSfD39y/weNOnT0d6errjde3atSKfKxERERWdUqlEVlYWAGDnzp3o0aMHgJxrCM6cJCIiqnqKNVPDaDRi5cqV2LlzJ1q0aAGFQuHUv2jRohIJjgqmN9twIS1nzQwJBH5dtgCr33wFPioLjJkWGAt5HKVSCZVKVaqxEhHdi9lsgkQqRc2aNfPtfyRiBAbM+AAHks0Y/fRT+OvIb44+P39/XImP5++xCu7DDz+EVqsFACxevLjU3sdut8NkMqFNmzZQKBTYtWsXIiIiAAAXL17E1atXERYWVuD+KpWK/9aIiIhc4LHHHsO0adPQoUMH/P777/jmm28AAH/++Sdq1arl4uiIiIiorBUrqXH69Gm0atUKAHD27FmnPs4MKH0pRhv+TDPDDsBNLkEgsrHni8UI+bzoySTeECQiV7OaLRB2OzYcOgfvfJ7EFwK4arIjFTKM/3QzGrrboJQCWQYDBj5UH2azmb/DKrjIyMh8f34Q06dPR3h4OIKDg5GRkYH169dj79692LFjB7y8vDBmzBhMmzYNOp0Onp6emDRpEsLCwrhIOBERUTn0ySef4KWXXsJ3332H5cuXOx6G2bZtG3r16uXi6IiIiKisFSupsWfPnpKOgwopOduKS+kWAICPSoqG3krcSbpzzxuCBeENQSIqT9w9NHDXaPPta6AROJNiQqYViDMr0FzH31mVXXJyMpKTk2G3253aW7RoUej9R4wYgYSEBHh5eaFFixbYsWMHnnjiCQA5s0OkUikiIiJgMpnQs2dPLFu2rMTPg4iIiB5ccHAwfvrppzztH374oQuiISIiIlcrVlKDXCPVaHMkNPzcZKjr6bxmxr1uCBIRVWQyiQSNfZQ4lWJCllXgz3QzQvgJVikdO3YMkZGROH/+PIQQTn0SiQQ2m61Qx1m1atU9+9VqNZYuXYqlS5cWO1YiIiIqOzabDVu3bsX58+cBAE2bNsVTTz0FmUzm4siIiIiorBXrllCXLl3uWWZq9+7dxQ6I8qc323AxzQwA8M0noUFEVNmpZFI09lHhbIoJd0x2SG1SV4dEpWD06NFo0KABVq1aBT8/P37WEREREWJjY9G7d2/cuHEDDRs2BADMnz8fQUFB+Pnnn1G3bl0XR0hERERlqVhJjdz1NHJZLBacPHkSZ8+eLbFa2PQPs03gwt9raPiopKjHhAYRVVFahRQNvJW4kGZGilWK8JffhF6fUeTjKJVKlt0rp/766y9s2rQJ9erVc3UoREREVE5MnjwZdevWxaFDh6D7u+RySkoKhg8fjsmTJ+Pnn392cYRERERUloqV1CiobuWbb74Jg8HwQAGRMyFyyqxY7IC7XIKGXkomNIioSqumlqGepwKxegs6jpiA0QsW49dP5hXpGH7+/rgSH8/ERjnUrVs3nDp1ikkNIiIicti3b59TQgMAqlWrhgULFqBDhw4ujIyIiIhcoUQrkg8fPhyPPPII3n///ZI8bJV2LdOKdLMdUgnQ0FsJmbTkExoZGXzKmYgqFj93OfT6dCTDHV1Gv4xnX5iMmko7CpPzzTIYMPCh+jCbzSX+e8wmBBIyrbhltCLdZIfJLmC3WNF59MvIsEqgsotS+T1emXz++eeIjIzE2bNn0axZMygUCqf+p556ykWRERERkauoVKp8v7caDAYolUoXRERERESuVKJJjZiYGKjV6pI8ZJWWabHjusEKAKjrqYC7vGTrx5vNJkikUtSsWbPI+/IpZyJyNR+Y8dn8N9Fv+ru4ZZFCyBSo76WAtIxns1nsArHpZvxxx4QrGRaY7SLPmJ4TZyDWCFw2GuHrJkNNDzncSvh3emURExODAwcOYNu2bXn6irJQOBEREVUeTz75JMaNG4dVq1bhkUceAQAcPnwYL774Ih94ICIiqoKKldQYOHCg07YQAgkJCTh69ChmzpxZIoFVdUIIxOrNEAB0Kil83Uo0/wQAsJotEHY7Nhw6B++7pvHeT2k+5UxEVBSHNq7GS2+8jZs2FW4bbTDa7GjsrYJSVvqJjTsmG47fysbpVBNMtn8SGW4yCQI95PBSyuAmlyDbaMbqDRvRNnwALEKCpGwbkrJtqOUhR5BGXuZJmPJu0qRJGD58OGbOnAk/Pz9Xh0NERETlwMcff4zIyEiEhYU5ZnFarVY89dRT+Oijj1wcHREREZW1Yt0p9/LyctqWSqVo2LAh3nrrLfTo0aNEAqvqErJsMFgEZBKgjmfpTqd199DAXaMt1fcgIiot3lIbvD2VuJhmhsEicOK2EfW8lKimlpX4ewkhEJ9hwdFb2bistzjavZRSNPFRoaG3Cn5uMqe1jzIy7Oj5fy8gMuIpWFXuuJFpxR2THdczrUgz2dDQRwm1jLM2cqWkpGDq1KlMaBAREZGDt7c3vv/+e8TGxuL8+fMAgMaNG3MNLiIioiqqWEmN1atXl3QcdBerAK4acm6WhWgVUJXBE8dERBWZt0qGFtVUuJhmRqZV4EKaGTXUshL7HWqy2XEm1YTjt4xINf1T/qiupwJtarihtlbhlMjIj0QCeCll8FLKcNtow+V0MwxWgbMpZjTTKaFmOSoAObNB9+zZg7p167o6FCIiIipn6tWrx0QGERERPdiaGseOHXM8JdG0aVO0bt26RIKq6m7ZFbAJwEMugb9byT9pTERUGbnJpWhRTYUrGVbczLLiltGGFJMNge5yBLjLi1ySSgiBxGwrzqSYcDbV5FgrQymVoHk1FdpUd4OumLNBqqtl0CpUOJtqhtEmcDaViY1cDRo0wPTp0/Hbb7+hefPmeRYKnzx5sosiIyIiIleJiIjAI488gtdff92p/d1338WRI0ewceNGF0VGRERErlCspEZycjIGDx6MvXv3wtvbGwCQlpaGLl26YMOGDahRo0ZJxlilVAuqjVR7zl9LaCGe/CUion9IJRLU9lSgupsMcXozMiwC1zOtuJFphU4tQzWVFMq863g7GK123MyyIk5vRqzejDsmu6OvulqGh6qr0VSngqoEykWpZFI016lwNtWEbJvA+TQzWuhUkEmr9u/9zz//HBqNBvv27cO+ffuc+iQSCZMaREREVdD+/fvx5ptv5mkPDw/HBx98UPYBERERkUsVK6kxadIkZGRk4Ny5c2jcuDEA4I8//kBkZCQmT56Mr7/+ukSDrEp6TnwDgAQ+Sim8VZyl8aAyMjJKdTwRlU9aRU7CINVkx41MKzIsdqQYbUgx2gDIMX3HGWy+boabIh0SCWC0CejNdmRY7E7HkUuA+l5KtKyuRoim5BPNSpkETXUqnEoxIssqEKu3oIGX4v47VmJxcXGOn4XIyUAxwU9ERFS1GQwGKJV515pUKBTQ6/UuiIiIiIhcqVhJje3bt2Pnzp2OhAYANGnSBEuXLi3SQuH79+/He++9h2PHjiEhIQFbtmxB//79Hf1CCMyePRufffYZ0tLS0KFDByxfvhz169d3jElNTcWkSZPw448/QiqVIiIiAh999BE0Gk1xTs2ljJCi+RNPARAI0Vbtm1oPymw2QSKVombNmsXa32a13X8QEZVrEokE1dQyVFPLYPg7qZFqsiHLaodnDX8kGAVgtOTZz0spRYhWgdpaJep6KotctqqoVDIJGnkrcTbVjNtGGzwVUlT1T4BVq1bhww8/xKVLlwAA9evXx8svv4znn3/exZFVLkkZKleHQEREhcDf10Dz5s3xzTffYNasWU7tGzZsQJMmTVwUFREREblKsZIadrs9T41rIOcpCbvdns8e+cvMzETLli0xevRoDBw4ME//u+++i48//hhr165F7dq1MXPmTPTs2RN//PEH1Go1AGDYsGFISEhAdHQ0LBYLRo0ahXHjxmH9+vXFOTWXSkXOOXlKbPBQsK76g7CaLRB2OzYcOgdvna7Q+6UkJWLY461hszGpQVSZaBRSaBQ5yYqMjAy8+PST+GHHTkiVaggAapkEHnIpqrvJoC6B0lJF5amUIVSrQFyGBfEGC0JQdT8DZs2ahUWLFmHSpEkICwsDAMTExGDq1Km4evUq3nrrLRdHWHl8eTzY1SEQEREVysyZMzFw4EBcvnwZXbt2BQDs2rULX3/9NdfTICIiqoKKldTo2rUrpkyZgq+//hqBgYEAgBs3bmDq1Kno1q1boY8THh6O8PDwfPuEEFi8eDHeeOMN9OvXDwDw5Zdfws/PD1u3bsXgwYNx/vx5bN++HUeOHEHbtm0BAEuWLEHv3r3x/vvvO2KrCLKsdmT8/WxuDVneJ4epeNw9NHDXaAs9PstgKMVoiKg8kEmAa2eOoa5GBq1W7epwHALcZUgx2qC32JEEN1eH4zLLly/HZ599hiFDhjjannrqKbRo0QKTJk1iUqMEjXjoKvy0JleHQURE95GUoaryiei+ffti69ateOedd/Ddd9/Bzc0NLVq0wM6dO9GpUydXh0dERERlrFhJjU8++QRPPfUUQkNDERQUBAC4du0amjVrhnXr1pVIYHFxcUhMTET37t0dbV5eXmjXrh1iYmIwePBgxMTEwNvb25HQAIDu3btDKpXi8OHDGDBgQInEUhZuZFoBSPDHvu1o2r2jq8MhIqIyJpFIUM9LgRO3TciCAq3CI1wdkktYLBanz/Vcbdq0gdVqdUFElZef1oQgb6OrwyAiIiqUPn36oE+fPq4Og4iIiMqBYiU1goKCcPz4cezcuRMXLlwAADRu3NgpAfGgEhMTAQB+fn5O7X5+fo6+xMRE+Pr6OvXL5XLodDrHmPyYTCaYTP88mejqhcVMNoFb2Tnljvau+hDPMKlBRFQlucmlCNLIcdVgRfjLb8IuXB1R2XvuueewfPlyLFq0yKl95cqVGDZsmIuiIiIiIiIiIqLyokhJjd27d2PixIk4dOgQPD098cQTT+CJJ54AAKSnp6Np06ZYsWIFHn/88VIJtqTMnz8fc+bMcXUYDolZVggAbrDi2tnjrg6HiIhcqKaHHAkGEzxr+CPFbkbhVwWquKZNm+b4WSKR4PPPP8evv/6K9u3bAwAOHz6Mq1evYsSIEa4KkYiIiFxIKpVCIpEU2M81EYmIiKqWIiU1Fi9ejLFjx8LT0zNPn5eXF1544QUsWrSoRJIa/v7+AICkpCQEBAQ42pOSktCqVSvHmOTkZKf9rFYrUlNTHfvnZ/r06U43UPR6vaOMVlmzC4HErJxyGj5gXWsioqpOKpGgGoxIhAdu2xUItQsopAV/ia8MTpw44bTdpk0bAMDly5cBANWrV0f16tVx7ty5Mo+NiIiIXG/Lli1O2xaLBSdOnMDatWvL1QOLREREVDaKlNQ4deoUFi5cWGB/jx498P777z9wUABQu3Zt+Pv7Y9euXY4khl6vx+HDhzF+/HgAQFhYGNLS0nDs2DHHDZDdu3fDbrejXbt2BR5bpVJBpVKVSJwP6la2DVYBKKUSaOxcIJyIiABPWHDi0jkE1G+KG5lWhGoVrg6pVO3Zs8fVIRAREVE51q9fvzxtTz/9NJo2bYpvvvkGY8aMcUFURERE5CpFSmokJSVBoSj4xopcLsetW7cKfTyDwYDY2FjHdlxcHE6ePAmdTofg4GC8/PLLmDt3LurXr4/atWtj5syZCAwMRP/+/QHkrOPRq1cvjB07FitWrIDFYsHEiRMxePBgBAYGFuXUXEIIgYS/Z2kEuMsgMbg4oCLKyMgo1fFERFWVBMCOJfMw8uP1SMiyoqaHvNLP1iAiIiIqqvbt22PcuHGuDoOIqEBJSUlIT093dRhVwpUrV5z+S6XLy8srz1rYZalISY2aNWvi7NmzqFevXr79p0+fdioVdT9Hjx5Fly5dHNu5JaEiIyOxZs0avPbaa8jMzMS4ceOQlpaGxx57DNu3b4darXbsExUVhYkTJ6Jbt26QSqWIiIjAxx9/XJTTchmDRSDTKiAF4OcuR3oFSWqYzSZIpFLUrFmzWPvbrKx3SkR0Pxd/i4YadhiFFAlZVgRrKvdsDSIiIqKiyM7Oxscff1zs76VERKUtKSkJw58bAYuZ5ebL0rx581wdQpWgUKqw7qsvXZbYKFJSo3fv3pg5cyZ69erllFgAci4oZs+ejSeffLLQx+vcuTOEEAX2SyQSvPXWW3jrrbcKHKPT6bB+/fpCv2d5kpSdM0ujmlpWoZ7AtZotEHY7Nhw6B29d4ZewTUlKxLDHW3MRNyKiQqous+C6TYWEzJzZGrJ7LJBJREREVFn5+Pg4LRQuhEBGRgbc3d2xbt06F0ZW/vCp8LLDp8LLlqufCi+O9PR0WMwmZNfpBLvay9XhEJUYqTEd+Gsf0tPTK0ZS44033sDmzZvRoEEDTJw4EQ0bNgQAXLhwAUuXLoXNZsOMGTNKJdDKxmoXuGXMubnv5y5zcTTF4+6hgbtGW+jxWYYKMhWFiKgAJpMJZrO5SPs8SOk9T4kNKpkEJptAcpYNAR5F+tgmIiIiqhQ+/PBDp6SGVCpFjRo10K5dO/j4+LgwsvKFT4W7Bp8KLxuufir8QdjVXrB7VHd1GESVSpHujvj5+eHgwYMYP348pk+f7phlIZFI0LNnTyxdurRC/nJxhRSjDXYBqGUSeCqkrg6HiIjuw2QyISQ0FEmJicXavzil9yQSoKa7HH/pLbiRZYW/u8zpCz0RERFRVTBy5EhXh1Ah8KlwqqzKw1PhRFS+FPmRz5CQEPzyyy+4c+cOYmNjIYRA/fr1+XREESVl/z1Lw403qIiIKgKz2YykxERsPn4J7hpNofd70NJ7vm4yXM2wwGQTuGOyQ6eumLP7iIiIiIri9OnThR7bokWLUoyk4uFT4UREVNkVu46Fj48PHn744ZKMpcrIstqRYbEDAHzdWEqEiKgicdeUbek9mUQCXzc5bmZZkZhtZVKDiIiIqoRWrVpBIpHccx1OIKdyBNdtJCIiqlp4R90Fbv09S8NHJYVSxlkaRER0b/7uMtzMsuKOyQ6j1Q61nGULiYiIqHKLi4tzdQhERERUTjGpUcaEEI6khi+ftiUiokJwk0vhrZQizWxHYrYNoVomNYiIiKhyCwkJcXUIREREVE7xrkgZy7DYYbILyCSAD5MaRERUSP7uOc8hJGdbYb9PGQYiIiKiyuSHH37I9/Xjjz8iOjq60LM69u/fj759+yIwMBASiQRbt2516hdCYNasWQgICICbmxu6d++OS5cuOY1JTU3FsGHD4OnpCW9vb4wZMwaGByw3SkREREXDpEYZS/57lkY1tQwyLhBORESFpFNJoZACFjtwx2R3dTjl3vz58/Hwww9Dq9XC19cX/fv3x8WLF53GdO7cGRKJxOn14osvuihiIiIiKkj//v0xYMAA9O/fP8+rZ8+eqFevHjp16oQ7d+7c8ziZmZlo2bIlli5dmm//u+++i48//hgrVqzA4cOH4eHhgZ49e8JoNDrGDBs2DOfOnUN0dDR++ukn7N+/H+PGjSvR8yUiIqJ7Y1KjDNmFQIoxJ6lRg7M0iIioCCR/LxgO5MzWoHvbt28fJkyYgEOHDiE6OhoWiwU9evRAZmam07ixY8ciISHB8Xr33XddFDEREREVJDo6Gg8//DCio6ORnp6O9PR0REdHo127do7EQkpKCv7zn//c8zjh4eGYO3cuBgwYkKdPCIHFixfjjTfeQL9+/dCiRQt8+eWXuHnzpmNGx/nz57F9+3Z8/vnnaNeuHR577DEsWbIEGzZswM2bN0vj1ImIiCgfXFOjDN0x2WEVgEIKeCmZTyIioqLxVctwIzNnwXCLXUAh5Yy/gmzfvt1pe82aNfD19cWxY8fQsWNHR7u7uzv8/f3LOjwiIiIqgilTpmDlypV49NFHHW3dunWDWq3GuHHjcO7cOSxevBijR48u9nvExcUhMTER3bt3d7R5eXmhXbt2iImJweDBgxETEwNvb2+0bdvWMaZ79+6QSqU4fPhwvskSk8kEk8nk2Nbr9cWOkYiIiHLwznoZyp2lUV0tg4Slp4iIqIjcFVJo5BIIALf+LmdIhZOeng4A0Ol0Tu1RUVGoXr06mjVrhunTpyMrK6vAY5hMJuj1eqcXERERlb7Lly/D09MzT7unpyf++usvAED9+vVx+/btYr9HYmIiAMDPz8+p3c/Pz9GXmJgIX19fp365XA6dTucY82/z58+Hl5eX4xUUFFTsGImIiCgHkxplxC4EUk3/JDWIiIiKgyWois5ut+Pll19Ghw4d0KxZM0f70KFDsW7dOuzZswfTp0/HV199heHDhxd4HN6UICIico02bdrg1Vdfxa1btxxtt27dwmuvvYaHH34YAHDp0qVy+dk8ffp0R8ms9PR0XLt2zdUhERERVXgsP1VG7pjssAlAKQW0CuaSiIioeKq7yRCXYUGmVSDTYocHP1Pua8KECTh79ix+++03p/a7F/Vs3rw5AgIC0K1bN1y+fBl169bNc5zp06dj2rRpjm29Xl8ub54QERFVNqtWrUK/fv1Qq1Ytx2fvtWvXUKdOHXz//fcAAIPBgDfeeKPY75FbjjIpKQkBAQGO9qSkJLRq1coxJjk52Wk/q9WK1NTUAstZqlQqqFSqYsdFREREeTGpUUZyS09VY+kpIiJ6AAqpBD4qKVJNdtw22pjUuI+JEyc6FhCtVavWPce2a9cOABAbG5tvUoM3JYiIiFyjYcOG+OP/27v3+BjvvP/j70nIAUkQ5FBJDK1DKw5FQ6k6ZIXWqbKs6rZot7oalFgqXaJSpNwtKVWq60Z/ZGl3i2rvTZcgRYlTQ900DqWJkihtkibWiMz8/rCdu6njtslcM5nX8/G4HjLf63tdeU++ZC7zme/3OnJE//znP3Xs2DF7229+8xt5eFy7Fho4cOCv+h5ms1nBwcFKT0+3FzGKioqUmZmp0aNHS5I6deqkgoIC7d+/X+3atZMkbdmyRVar1X4dAQAAKh9FDQdg6SkAQEWq5+NpL2qE16pGsfwGbDabxo4dq3Xr1mnbtm0ym823PSYrK0uSyn06EwAAOAcPDw/17t1bvXv3vmmfyMhI/c///M9NZ1IWFxfrxIkT9senTp1SVlaW6tatq/DwcI0fP14zZ87UPffcI7PZrGnTpik0NNReMGnRooV69+6tZ599VkuWLFFpaanGjBmjoUOHKjQ0tEKfLwAAuDmKGg7A0lMAgIpU19tTHirV5TKbSq7aVKs6RY2fi4uLU2pqqjZs2CA/Pz/7zTsDAgLk6+urkydPKjU1VY888ogCAwN16NAhTZgwQV27dlWrVq0MTg8AAH6J06dPq7S09Kb79+3bp+7du9sf/7is5PDhw7VixQpNnjxZJSUlGjVqlAoKCtSlSxelpaXJx8fHfszq1as1ZswY9ezZUx4eHoqNjdWCBQsq70kBAIDrUNRwgB9nabD0FACgInh6mFTXx1MXLpfp23+VqRYF8+ssXrxYktStW7dy7cuXL9eIESPk5eWlzZs3KyUlRSUlJQoLC1NsbOyvWosbAAA4t27duslms910v8lkUlJSkpKSkm7ap27dukpNTa2MeAAA4A5R1KhkNptN3/37fhp1vVl6CgBQMer9u6hx4XKZGvmxBNXP3eoNC0kKCwtTRkaGg9IAAAAAAICKwkc7K1lRqVVXbZKnSfL34scNAKgYdbw95GmSrlht+qHUanQcAAAAAAAAh+Bd9kr23eVrbzTV9faUB5+iBQBUEA+TyT4D8OJlihoAAAAAAMA9UNSoRDbb/91Po64PS08BACrWj68t31nKbrvcEgAAAAAAQFVAUaMSXbZJl8tsMkmqzdJTAIAKVsfLQyZde625dJWiBgAAcG9vv/22goKCjI4BAAAqGTcKr0SFV68tNxX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