{"cells":[{"cell_type":"markdown","metadata":{},"source":["# Medical Trial Case Study\n","\n","## 1) Background Information\n","\n","XYZ client is currently using Medication A for all their patients and is considering switching to Medication B. An essential aspect of evaluating Medication B is determining the anticipated usage in XYZ's patients. A trial was conducted to assess Medication B's effectiveness, and data for approximately 130 patients has been collected. This data includes information from at least 2 months prior to switching medications and up to 3 months after switching to Medication B.\n","\n","### Key considerations:\n","\n","- Patients can be on either Medication A or Medication B, but not both simultaneously.\n","- Medication B is administered less frequently (~1 time per month) than Medication A.\n","- The units for Medication A and Medication B are different and cannot be converted between each other.\n","- Time on Medication A is defined as the period between the first and last recorded administration of Medication A.\n","- A week is defined as 7 days, and a month is assumed to be 4.33 weeks.\n","\n","## 2) Metadata of the File\n","\n","The data file contains the following information:\n","\n","### **Admin:**\n","\n","- **ID**: patient ID\n","- **Med**: Med type\n","- **Admin Date**: Dates of administration\n","- **Units**: Dosage units administered for each medication\n","\n","### **Labs:**\n","\n","- **ID**: patient ID\n","- **DRAW_DATE**: draw date\n","- **LAB_RESULT_CODE**: different types of lab tests\n","- **LAB_VALUE**: lab values\n","\n","## 3) Business Goal\n","\n","The main objective is to evaluate the potential adoption of Medication B by XYZ's patients. Specifically, the goal is to analyze the usage patterns, switching trends, and dosing behavior to make informed decisions regarding the transition from Medication A to Medication B. Additionally, the cost-effectiveness of Medication B compared to Medication A will be assessed.\n"]},{"cell_type":"code","execution_count":2,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:08.362306Z","iopub.status.busy":"2024-10-02T14:59:08.361764Z","iopub.status.idle":"2024-10-02T14:59:10.665417Z","shell.execute_reply":"2024-10-02T14:59:10.664319Z","shell.execute_reply.started":"2024-10-02T14:59:08.362264Z"},"trusted":true},"outputs":[],"source":["# Suppress warnings\n","import warnings\n","warnings.filterwarnings('ignore')\n","\n","# Import necessary libraries\n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import train_test_split\n","from sklearn.linear_model import LinearRegression\n","from sklearn.metrics import mean_squared_error, r2_score\n"]},{"cell_type":"markdown","metadata":{},"source":["### Load the Data\n","\n","Let's start by loading the data from the two CSV files: `Admin.csv` and `Labs.csv`."]},{"cell_type":"code","execution_count":3,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:10.668391Z","iopub.status.busy":"2024-10-02T14:59:10.667732Z","iopub.status.idle":"2024-10-02T14:59:10.714883Z","shell.execute_reply":"2024-10-02T14:59:10.713931Z","shell.execute_reply.started":"2024-10-02T14:59:10.668338Z"},"trusted":true},"outputs":[{"data":{"text/html":["
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IDMedAdmin DateUnits
01Med A02/07/20121,500.00
11Med A06/07/20121,500.00
21Med A09/07/20121,500.00
31Med A11/07/20121,500.00
41Med A13/07/20121,500.00
\n","
"],"text/plain":[" ID Med Admin Date Units\n","0 1 Med A 02/07/2012 1,500.00\n","1 1 Med A 06/07/2012 1,500.00\n","2 1 Med A 09/07/2012 1,500.00\n","3 1 Med A 11/07/2012 1,500.00\n","4 1 Med A 13/07/2012 1,500.00"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["# Load the Admin data\n","admin_df = pd.read_csv('Admin.csv')\n","admin_df.head()"]},{"cell_type":"code","execution_count":4,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:10.717013Z","iopub.status.busy":"2024-10-02T14:59:10.716539Z","iopub.status.idle":"2024-10-02T14:59:10.742978Z","shell.execute_reply":"2024-10-02T14:59:10.741802Z","shell.execute_reply.started":"2024-10-02T14:59:10.716934Z"},"trusted":true},"outputs":[{"data":{"text/html":["
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IDDRAW_DATELAB_RESULT_CODELAB_VALUE
01.004-JulLAB A679
11.001-AugLAB A621
21.005-SepLAB A915
31.003-OctLAB A848
41.007-NovLAB A845
\n","
"],"text/plain":[" ID DRAW_DATE LAB_RESULT_CODE LAB_VALUE\n","0 1.0 04-Jul LAB A 679\n","1 1.0 01-Aug LAB A 621\n","2 1.0 05-Sep LAB A 915\n","3 1.0 03-Oct LAB A 848\n","4 1.0 07-Nov LAB A 845"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["# Load the Labs data\n","labs_df = pd.read_csv('Labs.csv')\n","labs_df.head()"]},{"cell_type":"markdown","metadata":{},"source":["### Data Preprocessing\n","\n","Before diving into analysis, we need to preprocess the data. This includes converting date columns to datetime objects and ensuring numeric columns are indeed numeric."]},{"cell_type":"code","execution_count":5,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:10.746041Z","iopub.status.busy":"2024-10-02T14:59:10.745633Z","iopub.status.idle":"2024-10-02T14:59:10.780546Z","shell.execute_reply":"2024-10-02T14:59:10.779444Z","shell.execute_reply.started":"2024-10-02T14:59:10.745994Z"},"trusted":true},"outputs":[],"source":["# Convert date columns to datetime\n","admin_df['Admin Date'] = pd.to_datetime(admin_df['Admin Date'], errors='coerce')\n","labs_df['DRAW_DATE'] = pd.to_datetime(labs_df['DRAW_DATE'], errors='coerce')\n","\n","# Convert LAB_VALUE to numeric\n","labs_df['LAB_VALUE'] = pd.to_numeric(labs_df['LAB_VALUE'], errors='coerce')\n","\n","# Convert Units to numeric\n","admin_df['Units'] = pd.to_numeric(admin_df['Units'], errors='coerce')"]},{"cell_type":"markdown","metadata":{},"source":["### Exploratory Data Analysis (EDA)\n","\n","Let's start with some basic exploratory data analysis to understand the distribution and relationships within the data."]},{"cell_type":"code","execution_count":6,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:10.782655Z","iopub.status.busy":"2024-10-02T14:59:10.781887Z","iopub.status.idle":"2024-10-02T14:59:10.810809Z","shell.execute_reply":"2024-10-02T14:59:10.809730Z","shell.execute_reply.started":"2024-10-02T14:59:10.782610Z"},"trusted":true},"outputs":[{"data":{"text/html":["
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IDAdmin DateUnits
count2022.000000876375.000000
mean66.7675572012-06-20 11:33:41.917808128256.397333
min1.0000002012-01-08 00:00:001.000000
25%32.2500002012-03-09 00:00:004.000000
50%67.0000002012-06-08 00:00:0010.000000
75%100.0000002012-10-07 00:00:00700.000000
max129.0000002012-12-10 00:00:00900.000000
std37.973341NaN336.385163
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"],"text/plain":[" ID Admin Date Units\n","count 2022.000000 876 375.000000\n","mean 66.767557 2012-06-20 11:33:41.917808128 256.397333\n","min 1.000000 2012-01-08 00:00:00 1.000000\n","25% 32.250000 2012-03-09 00:00:00 4.000000\n","50% 67.000000 2012-06-08 00:00:00 10.000000\n","75% 100.000000 2012-10-07 00:00:00 700.000000\n","max 129.000000 2012-12-10 00:00:00 900.000000\n","std 37.973341 NaN 336.385163"]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["# Summary statistics for Admin data\n","admin_df.describe()"]},{"cell_type":"code","execution_count":7,"metadata":{"execution":{"iopub.execute_input":"2024-10-02T14:59:10.812684Z","iopub.status.busy":"2024-10-02T14:59:10.812277Z","iopub.status.idle":"2024-10-02T14:59:10.839306Z","shell.execute_reply":"2024-10-02T14:59:10.838151Z","shell.execute_reply.started":"2024-10-02T14:59:10.812637Z"},"trusted":true},"outputs":[{"data":{"text/html":["
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IDDRAW_DATELAB_VALUE
count2095.00000002394.000000
mean65.557041NaT194.355054
min1.000000NaT3.000000
25%31.000000NaT10.700000
50%66.000000NaT13.000000
75%99.000000NaT60.750000
max129.000000NaT3060.000000
std38.453118NaN382.224700
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"],"text/plain":[" ID DRAW_DATE LAB_VALUE\n","count 2095.000000 0 2394.000000\n","mean 65.557041 NaT 194.355054\n","min 1.000000 NaT 3.000000\n","25% 31.000000 NaT 10.700000\n","50% 66.000000 NaT 13.000000\n","75% 99.000000 NaT 60.750000\n","max 129.000000 NaT 3060.000000\n","std 38.453118 NaN 382.224700"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["# Summary statistics for Labs data\n","labs_df.describe()"]},{"cell_type":"markdown","metadata":{},"source":["1. Total Monthly Medication Usage: What is the total number of units administered for each medication in each month across all patients?"]},{"cell_type":"code","execution_count":16,"id":"9d63d9fa","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Total monthly usage for each medication\n","admin_df['Month'] = admin_df['Admin Date'].dt.to_period('M') # Convert to monthly period\n","\n","# Group by medication type and month, and sum the units\n","monthly_usage = admin_df.groupby(['Med', 'Month'])['Units'].sum().reset_index()\n","\n","# Plot total units administered per month for each medication\n","plt.figure(figsize=(10, 6))\n","sns.barplot(x='Month', y='Units', hue='Med', data=monthly_usage)\n","plt.title('Total Monthly Medication Usage')\n","plt.xticks(rotation=45)\n","plt.show()"]},{"cell_type":"markdown","metadata":{},"source":["2. Patient Counts on Each Medication: How many patients received Medication A and Medication B from July to November?"]},{"cell_type":"code","execution_count":19,"id":"d6ee6e43","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Med object\n","Month period[M]\n","ID int64\n","dtype: object\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0kAAAJYCAYAAAC3hK3KAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAACgHUlEQVR4nOzdd3hTZf8G8Du76UhLSye0pbRM2RsKlA2COIBXBVGG8IIsAXHg6wAHdfxYslWGKIiyFAVRESh7yx7SsmlLKdDdJE3y/P4IjQ1tofuk7f25rlzQc06Sb9KTNHe+53mOTAghQERERERERAAAudQFEBERERERORKGJCIiIiIiohwYkoiIiIiIiHJgSCIiIiIiIsqBIYmIiIiIiCgHhiQiIiIiIqIcGJKIiIiIiIhyYEgiIiIiIiLKgSGJiIiIiIgoB4YkogpoxYoVkMlkuHLlitSlUCXQqVMnNGjQQOoyCi2v10mnTp3QqVMnh6ilLKWlpcHHxwerVq0qkdu7cuUKZDIZVqxYUSK3R8U3dOhQuLq6lsl9ZWVlITAwEAsXLiyT+yMqDQxJRGUo+4NQ9sXJyQm1a9fGuHHjcOvWrULf3owZM/DTTz+VfKEFkJGRgWnTpmHnzp2Fut6tW7cwZcoU1K1bF87OznBxcUHz5s3x0UcfISkpqVRqLazVq1djzpw5UpdRaDt37rTbvx68rFmzRuoS81SjRg3IZDJ069Ytz/VfffWV7TEcOXKkjKsrWVK+Zh9m7ty5cHNzw/PPP29bNm3aNMhkMiQmJkpYmdW+ffswbdq0En+PyH6Mvr6+yMjIyLW+Ro0aeOKJJ0r0PisDlUqFyZMn4+OPP4Zer5e6HKIiYUgiksAHH3yAb7/9FvPnz0e7du2waNEitG3bNs8/0g+T3weuF198EZmZmQgODi6hinPLyMjA9OnTCxWSDh8+jAYNGmDBggXo0KEDZs2ahZkzZ6Jp06b45JNP8Oyzz5ZavYVRXkNStgkTJuDbb7/NdWnbtq3UpeXLyckJO3bsQHx8fK51q1atgpOTU5nU8ccff+CPP/4otduX8jWbn6ysLMydOxcjRoyAQqEo8/sviH379mH69Oml9kVKQkICFi1aVCq3XVkNGzYMiYmJWL16tdSlEBWJUuoCiCqjxx9/HC1atAAAjBgxAl5eXpg1axZ+/vlnDBw4sNi3r1AoHO7DTlJSEp555hkoFAr8/fffqFu3rt36jz/+GF999ZVE1VUsHTp0wIABA6Quo1DCw8Nx+PBh/PDDD3j11Vdty2/cuIHdu3fjmWeewfr160u9DrVaXer3kRcpX7O//vorbt++7TBfUkihSZMm+PzzzzFmzBhotVqpyym3hBDQ6/XQarXw8PBAjx49sGLFCgwfPlzq0ogKjZ0kIgfQpUsXAMDly5cBAP/3f/+Hdu3awcvLC1qtFs2bN8e6devsriOTyZCeno5vvvnGdijS0KFDAeQ/vuG3335Dhw4d4OLiAjc3N/Tp0wdnzpyx2yb7uPWbN2/i6aefhqurK7y9vTFlyhSYzWYA1vEG3t7eAIDp06fb7n/atGn5PsYlS5bg5s2bmDVrVq6ABAC+vr5455137JYtXLgQjz32GDQaDQICAjB27Nhc3yTXqFHD9rhzenBsSfahaD/++CM+/vhjVK9eHU5OTujatSuio6Ptrrd582ZcvXrV9rhq1KhhWz9v3jw89thjcHZ2RpUqVdCiRYsCfVOakJCAl19+Gb6+vnByckLjxo3xzTff2G2TPY7j//7v//Dll18iNDQUGo0GLVu2xOHDhx95H4WxfPlydOnSBT4+PtBoNKhfv36+36T/9ttviIiIgJubG3Q6HVq2bJnnYz579iw6d+4MZ2dnVKtWDZ999lmB63FyckK/fv1y3e7333+PKlWqoGfPnnle7/z58xgwYAA8PT3h5OSEFi1aYNOmTbm2O3PmDLp06QKtVovq1avjo48+gsViybVdXmOS9Ho9pk2bhtq1a8PJyQn+/v7o168fYmJibNuU1mu2IK+B7DFhRX3+f/rpJ9SoUQOhoaGP3Lagr7cHLV++HDKZDH///XeudTNmzIBCocDNmzfzvO60adPw+uuvAwBCQkJsz132c2UymfDhhx/aXi81atTA22+/DYPB8MjHk+29997DrVu3CtRNSk9Px2uvvYbAwEBoNBrUqVMH//d//wchhG2bBg0aoHPnzrmua7FYUK1aNbsvMSwWC+bMmYPHHnsMTk5O8PX1xahRo3Dv3j2762Yf+rdz5060aNECWq0WDRs2tHXzN2zYgIYNG8LJyQnNmzfP87kGgEuXLqFnz55wcXFBQEAAPvjgA7vai1LT77//bqtpyZIltvXdu3fHnj17cPfu3Uc+r0SOhiGJyAFkf9jy8vICYB0f0LRpU3zwwQeYMWMGlEol/vOf/2Dz5s2263z77bfQaDTo0KGD7XCqUaNG5Xsf3377Lfr06QNXV1d8+umnePfdd3H27Fm0b98+1wczs9mMnj17wsvLC//3f/+HiIgIzJw5E19++SUAwNvb2/Zh4plnnrHdf79+/fK9/02bNkGr1Ra4wzFt2jSMHTsWAQEBmDlzJvr3748lS5agR48eyMrKKtBt5OWTTz7Bxo0bMWXKFEydOhUHDhzACy+8YFv/v//9D02aNEHVqlVtjyv70LuvvvoKEyZMQP369TFnzhxMnz4dTZo0wcGDBx96n5mZmejUqRO+/fZbvPDCC/j888/h7u6OoUOHYu7cubm2X716NT7//HOMGjUKH330Ea5cuYJ+/foV+HGnpqYiMTEx1yXnB6FFixYhODgYb7/9NmbOnInAwECMGTMGCxYssLutFStWoE+fPrh79y6mTp2KTz75BE2aNMHWrVvttrt37x569eqFxo0bY+bMmahbty7efPNN/PbbbwWqGQAGDRqEQ4cO2YWP1atXY8CAAVCpVLm2P3PmDNq0aYNz587hrbfewsyZM+Hi4oKnn34aGzdutG0XHx+Pzp074/jx43jrrbcwceJErFy5Ms/n/kFmsxlPPPEEpk+fjubNm2PmzJl49dVXkZycjNOnT9u2K43XbGFeA8V5/vft24dmzZo9crviGDBgALRabZ4TQ6xatQqdOnVCtWrV8rxuv379bB322bNn25677C9qRowYgffeew/NmjXD7NmzERERgcjISLvxVY/SoUMHdOnSBZ999hkyMzPz3U4IgSeffBKzZ89Gr169MGvWLNSpUwevv/46Jk+ebNvuueeew65du3IdPrpnzx7Exsba1TZq1Ci8/vrrCA8Px9y5czFs2DCsWrUKPXv2zPV7jo6OxqBBg9C3b19ERkbi3r176Nu3L1atWoVJkyZh8ODBmD59OmJiYvDss8/m+iLAbDajV69e8PX1xWeffYbmzZvj/fffx/vvv2+3XWFqunDhAgYOHIju3btj7ty5aNKkiW1d8+bNIYTAvn37Hv4LIHJEgojKzPLlywUAsW3bNnH79m1x/fp1sWbNGuHl5SW0Wq24ceOGEEKIjIwMu+sZjUbRoEED0aVLF7vlLi4uYsiQIfnez+XLl4UQQqSmpgoPDw8xcuRIu+3i4+OFu7u73fIhQ4YIAOKDDz6w27Zp06aiefPmtp9v374tAIj333+/QI+9SpUqonHjxgXaNiEhQajVatGjRw9hNptty+fPny8AiGXLltmWBQcH5/kcREREiIiICNvPO3bsEABEvXr1hMFgsC2fO3euACBOnTplW9anTx8RHByc6zafeuop8dhjjxXoMeQ0Z84cAUB89913tmVGo1G0bdtWuLq6ipSUFCGEEJcvXxYAhJeXl7h7965t259//lkAEL/88stD7yf7MeZ3iYuLs2374D4mhBA9e/YUNWvWtP2clJQk3NzcROvWrUVmZqbdthaLxfb/iIgIAUCsXLnStsxgMAg/Pz/Rv3//Rz09Ijg4WPTp00eYTCbh5+cnPvzwQyGEEGfPnhUARFRUlG2fPnz4sO16Xbt2FQ0bNhR6vd6urnbt2olatWrZlk2cOFEAEAcPHrQtS0hIEO7u7navk+zHknO/WbZsmQAgZs2alavunM9BSb9mC/MaKM7zn5WVJWQymXjttddyrXv//fcFAHH79m3bsoK+3rL35eXLl9uWDRw4UAQEBNg9nmPHjuXaLi+ff/55rt+VEEIcP35cABAjRoywWz5lyhQBQGzfvv2ht5vzMUZFReX6XWfvm9l++uknAUB89NFHdrczYMAAIZPJRHR0tBBCiAsXLggAYt68eXbbjRkzRri6utr2l927dwsAYtWqVXbbbd26Ndfy4OBgAUDs27fPtuz3338XAIRWqxVXr161LV+yZIkAIHbs2GFblv3ePn78eNsyi8Ui+vTpI9Rqte33XJSatm7dmtfTK2JjYwUA8emnn+a5nsiRsZNEJIFu3brB29sbgYGBeP755+Hq6oqNGzfavknNeUz8vXv3kJycjA4dOuDYsWNFur8///wTSUlJGDhwoF1nQaFQoHXr1tixY0eu64wePdru5w4dOuDSpUtFun8ASElJgZubW4G23bZtG4xGIyZOnAi5/N+3qZEjR0Kn09l9O19Yw4YNsxt30qFDBwAo0GPz8PDAjRs3Cn3o25YtW+Dn52c33kylUmHChAlIS0tDVFSU3fbPPfccqlSpUqQaAeuhQ3/++Weui6enp22bnPtYcnIyEhMTERERgUuXLiE5ORmAdb9JTU3FW2+9lWviBJlMZvezq6srBg8ebPtZrVajVatWhdpnFAoFnn32WXz//fcArB2GwMBA2+PP6e7du9i+fTueffZZu87ZnTt30LNnT1y8eNF2+NaWLVvQpk0btGrVynZ9b29vuw5iftavX4+qVati/PjxudblfA5K+jVb2NdAUZ//u3fvQghht7+VlpdeegmxsbF27zerVq2CVqtF//79i3SbW7ZsAQC7Lg4AvPbaawBQqPeKjh07onPnzg/tJm3ZsgUKhQITJkzIdX9CCFvnrnbt2mjSpAl++OEH2zZmsxnr1q1D3759bfvL2rVr4e7uju7du9u9Nzdv3hyurq653pvr169vNwFL69atAVgP2Q4KCsq1PK/f/7hx42z/l8lkGDduHIxGI7Zt21akmkJCQvI9HDZ7v3KEGRKJCosTNxBJYMGCBahduzaUSiV8fX1Rp04duw9Cv/76Kz766CMcP37c7rj6Bz+YFtTFixcB/Dv26UE6nc7uZycnJ9uhLNmqVKmS63j0wtDpdEhNTS3QtlevXgUA1KlTx265Wq1GzZo1beuLIucHCeDfP+IFeWxvvvkmtm3bhlatWiEsLAw9evTAoEGDEB4e/tDrXb16FbVq1bL7HQNAvXr1bOtLqkYAaNiwYb7TaWfbu3cv3n//fezfvz/XrIrJyclwd3e3HfZWkHMgVa9ePdf+WaVKFZw8ebJANWcbNGgQvvjiC5w4cQKrV6/G888/n+d+Hx0dDSEE3n33Xbz77rt53lZCQgKqVauGq1ev2j405vTg/pWXmJgY1KlTB0rlw/9clvRrtrCvgeI+/+KBMSmloXv37vD398eqVavQtWtXWCwWfP/993jqqacK/AXKg65evQq5XI6wsDC75X5+fvDw8Cj0e8W0adMQERGBxYsXY9KkSXneX0BAQK5683otP/fcc3j77bdx8+ZNVKtWDTt37kRCQgKee+452zYXL15EcnIyfHx88qwnISHB7ucH3xvc3d0BAIGBgXkuf/A9Qy6Xo2bNmnbLateuDQC2w64LW1NISEie2wH/7ldFfR0QSYkhiUgCrVq1ss1u96Ddu3fjySefRMeOHbFw4UL4+/tDpVJh+fLlRZ5KNfu49G+//RZ+fn651j/4AbA0ZtmqW7cujh8/DqPRWKIziOX3x9dsNuf5OPJ7bAX5kFivXj1cuHABv/76K7Zu3Yr169dj4cKFeO+99zB9+vTCFf4QxamxIGJiYtC1a1fUrVsXs2bNQmBgINRqNbZs2YLZs2fnOaHBo5RUza1bt0ZoaCgmTpyIy5cvY9CgQXlul13jlClT8v0W+8EPzqWlNF6zhVXU59/T0xMymazAAbywr7cHaxw0aBC++uorLFy4EHv37kVsbKxdB6yoSupDeMeOHdGpUyd89tlnubrphfXcc89h6tSpWLt2LSZOnIgff/wR7u7u6NWrl20bi8Xy0JP4PvhlVX7PcUm+ZxS2pofNBpi9X1WtWrXQdRBJjSGJyMGsX78eTk5O+P3336HRaGzLly9fnmvbgn4wyJ61ysfH55EdhoIq7IeSvn37Yv/+/Vi/fv0jpznPPlfMhQsX7L71NBqNuHz5st1jqFKlSp7nTrl69Wqub0wL6mGPzcXFBc899xyee+45GI1G9OvXDx9//DGmTp2a77l8goODcfLkSVgsFrtu0vnz523ry9Ivv/wCg8GATZs22X0z/eBhNNn7zenTp8sscADAwIED8dFHH6FevXp2g8Bzyv7dqlSqR+7TwcHBtm5qThcuXHhkLaGhoTh48CCysrLynDwCKJ3XbGFeA8WhVCoRGhpqm1nzUYr7envppZcwc+ZM/PLLL/jtt9/g7e2db8jNKb/nLTg4GBaLBRcvXrR1cwDrSauTkpKK9NqaNm0aOnXqZDdLW87727ZtG1JTU+26SXm9lkNCQtCqVSv88MMPGDduHDZs2ICnn37abh8JDQ3Ftm3bEB4eXiZTj1ssFly6dMnWPQKAf/75BwBss3iWZE3Z+1XO3w1RecExSUQORqFQQCaT2abbBqyHQeR1AkoXF5cCnVyxZ8+e0Ol0mDFjRp4zpN2+fbvQdTo7OwNAgU/uOHr0aPj7++O1116z/VHOKSEhAR999BEA65gttVqNL774wu6b0KVLlyI5ORl9+vSxLQsNDcWBAwdgNBpty3799Vdcv3690I8pm4uLi21cTk537tyx+1mtVqN+/foQQjx05rnevXsjPj7ebnyCyWTCvHnz4OrqioiIiCLXWhTZ3zrnfG6Tk5Nzfajv0aMH3NzcEBkZCb1eb7euNA/PGjFiBN5//33MnDkz3218fHxsH2Tj4uJyrc+5T/fu3RsHDhzAoUOH7Nbn9015Tv3790diYiLmz5+fa132c1Aar9nCvAaKq23btjhy5EiBti3u661Ro0Zo1KgRvv76a6xfvx7PP//8Iw9lBKzPG5D7/aZ3794AkOvkz7NmzQKAIj1PERER6NSpEz799NNc+33v3r1hNptz7Q+zZ8+GTCbD448/brf8ueeew4EDB7Bs2TIkJibaHWoHAM8++yzMZjM+/PDDXHWYTKZSOXluztqFEJg/fz5UKhW6du1a4jUdPXoUMpnMoU9kTZQfdpKIHEyfPn0wa9Ys9OrVC4MGDUJCQgIWLFiAsLCwXOMLmjdvjm3btmHWrFkICAhASEhInmMvdDodFi1ahBdffBHNmjXD888/D29vb1y7dg2bN29GeHh4nh8CH0ar1aJ+/fr44YcfULt2bXh6eqJBgwb5jl+pUqUKNm7ciN69e6NJkyYYPHgwmjdvDgA4duwYvv/+e9sfUm9vb0ydOhXTp09Hr1698OSTT+LChQtYuHAhWrZsaXd4zogRI7Bu3Tr06tULzz77LGJiYvDdd98V6Jwv+WnevDl++OEHTJ48GS1btoSrqyv69u2LHj16wM/PD+Hh4fD19cW5c+cwf/589OnT56FjKv773/9iyZIlGDp0KI4ePYoaNWpg3bp12Lt3L+bMmVPk8Rj52b17d64Pd8C/H1B79OgBtVqNvn37YtSoUUhLS8NXX30FHx8fu8Ch0+kwe/ZsjBgxAi1btsSgQYNQpUoVnDhxAhkZGbnO81RSgoODH3rOrWwLFixA+/bt0bBhQ4wcORI1a9bErVu3sH//fty4cQMnTpwAALzxxhv49ttv0atXL7z66qtwcXHBl19+aevwPcxLL72ElStXYvLkyTh06BA6dOiA9PR0bNu2DWPGjMFTTz1VKq/ZwrwGiuupp57Ct99+i3/++ceuw5CXkni9vfTSS5gyZQoAFPhxZL9X/O9//8Pzzz8PlUqFvn37onHjxhgyZAi+/PJLJCUlISIiAocOHcI333yDp59+Os9zFRXE+++/n+d1+/bti86dO+N///sfrly5gsaNG+OPP/7Azz//jIkTJ+Z6Hp599llMmTIFU6ZMgaenZ64OYEREBEaNGoXIyEgcP34cPXr0gEqlwsWLF7F27VrMnTu3RE8M7eTkhK1bt2LIkCFo3bo1fvvtN2zevBlvv/227TC6kqzpzz//RHh4uO30FkTlSpnPp0dUieU1jXFeli5dKmrVqiU0Go2oW7euWL58uW2q2pzOnz8vOnbsKLRarQBgm5r3wemEs+3YsUP07NlTuLu7CycnJxEaGiqGDh0qjhw5YttmyJAhwsXFJVdNed3/vn37RPPmzYVarS7wdOCxsbFi0qRJonbt2sLJyUk4OzuL5s2bi48//lgkJyfbbTt//nxRt25doVKphK+vr3jllVfEvXv3ct3mzJkzRbVq1YRGoxHh4eHiyJEj+U4BvnbtWrvr5jVVcVpamhg0aJDw8PAQAGzTgS9ZskR07NhReHl5CY1GI0JDQ8Xrr7+eq+683Lp1SwwbNkxUrVpVqNVq0bBhw1zTHmfX8vnnn+e6fkGe30dNAZ7z+ps2bRKNGjUSTk5OokaNGuLTTz+1TXf94H6zadMm0a5dO6HVaoVOpxOtWrUS33//vW19REREnlOjDxkyJM+p1B/04DTLecnvtRMTEyNeeukl4efnJ1QqlahWrZp44oknxLp16+y2O3nypIiIiBBOTk6iWrVq4sMPPxRLly595BTgQlin9/7f//4nQkJChEqlEn5+fmLAgAEiJibGtk1pvWYL8hoo7vNvMBhE1apVbVOvZ3vvvfcEALvp6IUo2Ostr9dVtri4OKFQKETt2rUfWVtOH374oahWrZqQy+V2z1VWVpaYPn267fcTGBgopk6dajc1fH7ymuY8W/bU6g/um6mpqWLSpEkiICBAqFQqUatWLfH555/bTQmfU3h4eJ7TlOf05ZdfiubNmwutVivc3NxEw4YNxRtvvCFiY2Nt2+T3OgEgxo4da7csr/eS7Pf2mJgY0aNHD+Hs7Cx8fX3F+++/bzcte0nUJIT1FAJqtVp8/fXX+T5uIkcmE6IMprQhIiIih/Xhhx9i+fLluHjxou1wzMmTJ2Pu3LnQ6/X5jscqisTERPj7++O9997Ld2ZCKv/mzJmDzz77DDExMWUy3oqopHFMEhERUSU3adIkpKWlYc2aNbZlhw8fRlhYWIkGJABYsWIFzGYzXnzxxRK9XXIcWVlZmDVrFt555x0GJCq3OCaJiIioknN1dbWd/2b58uXYvn079uzZg48//rjE7mP79u04e/YsPv74Yzz99NO22dSo4lGpVLh27ZrUZRAVCw+3IyIiIhu5XA4/Pz+8+OKLmDFjRomdN61Tp07Yt28fwsPD8d1336FatWolcrtERKWBIYmIiIiIiCgHjkkiIiIiIiLKgSGJiIiIiIgohwo/cYPFYkFsbCzc3Nwgk8mkLoeIiIiIiCQihEBqaioCAgIgl+ffL6rwISk2NhaBgYFSl0FERERERA7i+vXrqF69er7rK3xIcnNzA2B9InQ6ncTVEBERERGRVFJSUhAYGGjLCPmp8CEp+xA7nU7HkERERERERI8chsOJG4iIiIiIiHJgSCIiIiIiIsqBIYmIiIiIiCiHCj8mqaDMZjOysrKkLqNCU6lUUCgUUpdBRERERPRQlT4kCSEQHx+PpKQkqUupFDw8PODn58dzVhERERGRw6r0ISk7IPn4+MDZ2Zkf3kuJEAIZGRlISEgAAPj7+0tcERERERFR3ip1SDKbzbaA5OXlJXU5FZ5WqwUAJCQkwMfHh4feEREREZFDqtQTN2SPQXJ2dpa4ksoj+7nm+C8iIiIiclSVOiRl4yF2ZYfPNRERERE5OoYkIiIiIiKiHBiSKoGdO3dCJpNxBj8iIiIiogJgSHIAQ4cOhUwmw+jRo3OtGzt2LGQyGYYOHVr2hRERERERVUIMSQ4iMDAQa9asQWZmpm2ZXq/H6tWrERQUJGFlRERERESVC0OSg2jWrBkCAwOxYcMG27INGzYgKCgITZs2tS2zWCyIjIxESEgItFotGjdujHXr1tnd1pYtW1C7dm1otVp07twZV65cKauHQURERERU7jEkOZDhw4dj+fLltp+XLVuGYcOG2W0TGRmJlStXYvHixThz5gwmTZqEwYMHIyoqCgBw/fp19OvXD3379sXx48cxYsQIvPXWW2X6OIiIiKj4Mo0mGE0W3EkzwGiyIMNokrokokqjUp9M1tEMHjwYU6dOxdWrVwEAe/fuxZo1a7Bz504AgMFgwIwZM7Bt2za0bdsWAFCzZk3s2bMHS5YsQUREBBYtWoTQ0FDMnDkTAFCnTh2cOnUKn376qSSPiYiIiArPkGXG4qhLWL7vMlIyTdBplRjWLgRjOoVCo+LJ2IlKG0OSA/H29kafPn2wYsUKCCHQp08fVK1a1bY+OjoaGRkZ6N69u931jEaj7ZC8c+fOoXXr1nbrswMVEREROb5MowmLoy5h7l8XbctSMk22n0dF1ISzmh/hiEoTX2EOZvjw4Rg3bhwAYMGCBXbr0tLSAACbN29GtWrV7NZpNJqyKZCIiIgKzWwRSNVnITkz9yUl02T7v8UiMO3Jx7B83+U8b2f5vssY3SkU7/98Ggq5HDqtEu5aFXROKui0Kuv/tUronKz/d1YreCJ3oiJgSHIwvXr1gtFohEwmQ8+ePe3W1a9fHxqNBteuXUNERESe169Xrx42bdpkt+zAgQOlVi8REVFlYTJbkKI35RN07v8/4/7PDwSiVH3BxhPV8XVDYpoBKZl5b5+SacKdNAMOXLqLC7dSH3l7SrkMOq0KOiflvyHK6X6QejBcOd0PXPeXu2tVUCs5fJ0qJ4YkB6NQKHDu3Dnb/3Nyc3PDlClTMGnSJFgsFrRv3x7JycnYu3cvdDodhgwZgtGjR2PmzJl4/fXXMWLECBw9ehQrVqyQ4JEQERE5HqPJYh9u9LkDTn4BKN1oLvb9O6sVcLd1fP4NI9kXHzc1fNw00GmVeQYlnVYJb1cNnm8ViIRUg62+7PCWmiOgZZkFTBaBu+lG3E03FqleJ5XcVmPOMPVg4MrVzXJSwc1JCbmcXSwqnxiSHJBOp8t33Ycffghvb29ERkbi0qVL8PDwQLNmzfD2228DAIKCgrB+/XpMmjQJ8+bNQ6tWrTBjxgwMHz68rMonIiIqVfos87/B5iGHrtl1eO5fMrOKH3RcNcocoUFpF3LswsSDy50K1pnJNJowrF2I3ZikbMPahcAsBIaFhzz0NoQQ0GdZcgVB6/9Nds+N3bL726YaTBAC0GdZoM8yICHVUOjnSSazPlf/hiylXeCy/l9p93zl3Far4qGCJB2ZEEJIXURpSklJgbu7O5KTk3OFD71ej8uXLyMkJAROTk4SVVi58DknIqKcH+Dzu6Q8JOgYTJZi1+DmlDvcPBhy8vpZ56SEUlH6h6AZssxYuDNGstntzBaBNIPpgSBlDVPZnaqcHayUHB2slExTiYRRlUJm605ld68e3cH69zBCHipIeXlYNsiJnSQiIiIqNCEE0o3mPMfh5NflsX2YzjTBaC5e0JHL8EB4yTvg5HVxdVJC4eCHgWlUCoyKqImxncOQqs+Cm5MKJoulzKb/VshltucrsAjXN5jMSNXnDFn2gSs5R+BKySNwmSwCWWaBO+lG3CnioYJalSKfDlaOsVf5BC43DQ8VrOwYkoiIiCopi0UgzWj6N+Q8GGhskw+YcnV1sj/IFkfOD+L24UZpF3xybeOsgqu64n+IzZ7m28vVOoOtGuWnM6JRKqBxVaCqa+Fn3xVCIDPLbHf45IOdKvtulnUfzQ5bqQbrWK7MLDMys8yITyl8/TIZ4KaxH3uVZ+DKZzyWk0rOQwXLOYYkIiKicsxsEUjLZ8a1vA5fyznrWkpmFoqZc6BSyB7ZwXnwg6a7s/VfF05PTXmQyWRwVivhrFbC373w18/5mnhwPFbeIcs+iOmzLBAC1u6X3oQb9zILXYNaIbcFqn87VrlnD8wrZLk5KaEqg0M66eEYkoiIqNLINJqgkMvtDl9yhJNy5jW19MPG5OS8pN0fYF8cGqU8/zE4jzh0jd+Yk6NRyGXWIO6sKtL19VnWQwVzhyxTjkMD7Se7yBm4zBYBo9mCxDQjEtOKdqhg9iyIeR0K+KjA5eJgXVZHfd99FMevkIiIqAQYssxYHHWp1AbCZ5lzT0SQc2rpB8+bk314UHbQKa7s8Rd5B52HT1LgVEbjXIjKAyeVAk4qBbzdinaoYLrR/O9hgBn5T26RM1xlh7Ls94IMoxkZRjPikvWFrkEuA9zyOjwwZ+B6yAQYJfl+UNrvu6WJIYmIiCq8TKMJi6Mu2U2pnJJpsv08KqImnNVK69TS+jw6Nxn243Ie/MCTnJmFjBI4h45L9rfH+XVunPM/vw5n8iKSnkwmg6tGCVeNEgHQFvr6JrPFOuFFHtOy5zVd+4OHDBpNFlgEbO9LRaFWynOFp/yncLdf7pZj9seCvu86KsetjIiIqIQo5HIs33c5z3XL913GqIiaaDPjL8SnFP5b2wflnFraLsg45+7w5LxwHAIRKRVyVHFRo4qLukjXt/+ix372wLxmGXwwiFmE9YTLiWkGJKYV/txYgPXcWEFVtFg/Jvyh77tjO4cV6fbLCkMSERFVeKn3PwzkJSXThLvpRrhrVYhP0UMmQ64uzYMzWeV3cXNSOfzU0kRUcWUfKujjVvhzUVosAulG62QV2YcI5x+uch8ymH6/m55mMMEsgMQ0w0Pfd1P1WbaZGx0RQxIREVV4bvcPHcnrD7ZOq4SPmwbLhraAqxPPj0JElZNcLoObk/XLnmoeRTtUMDtMpRtN8NFpHvq+6+ZUtIk1ygr7+pSnnTt3QiaTISkpSepSiIiKzWyxYFi7kDzXDWsXApNFoFoVZ7hrVQxIRERFoFTI4emiRo2qLngswB0Wi3jE+27xTihd2hiSyqGhQ4dCJpNh9OjRudaNHTsWMpkMQ4cOLbN6IiMjoVAo8Pnnn5fZfRIRFYZWrcTIjjUxvksYdFrrQRQ6rRKvdq2FMZ1CHXrwMBFReaRVKzGmUyhe7VqrXL7vOnZ15YQU878HBgZizZo1mD17NrRaa0tUr9dj9erVCAoKKtX7ftCyZcvwxhtvYNmyZXj99dfL9L6JiAoiy2zB6G+P4KW2NXDo7W5IN5hs79eOPg0tEVF5pVEpMCqiJsZ2DrP7nFwe3nfZSSqm7PnfW3z8J5p/tA0tPv4TS6IuwZBV/KlgH6ZZs2YIDAzEhg0bbMs2bNiAoKAgNG3a1G5bi8WCyMhIhISEQKvVonHjxli3bp3dNlu2bEHt2rWh1WrRuXNnXLlypUB1REVFITMzEx988AFSUlKwb9++Yj82IqKS9tPfN7En+g7e3ngKQgBerhqolXKH/yaTiKi8c1YroVbKy937LkNSDkIIZBhNBb6k6bOwcGcM5v510TYoLXv+94U7Y5CmzyrwbYkinC59+PDhWL58ue3nZcuWYdiwYbm2i4yMxMqVK7F48WKcOXMGkyZNwuDBgxEVFQUAuH79Ovr164e+ffvi+PHjGDFiBN56660C1bB06VIMHDgQKpUKAwcOxNKlSwv9OIiISpPZIrBwZwwAYGSHmtCqHf8bTCIiklb5iHJlJDPLjPrv/V6gbT1d1NjzZudHnnej/ac7cDfd+MjbO/tBz0In68GDB2Pq1Km4evUqAGDv3r1Ys2YNdu7cadvGYDBgxowZ2LZtG9q2bQsAqFmzJvbs2YMlS5YgIiICixYtQmhoKGbOnAkAqFOnDk6dOoVPP/30ofefkpKCdevWYf/+/bZ6OnTogLlz58LV1bVQj4WIqLT8ejIWlxPTUcVZhcFtgqUuh4iIygHJO0k3b97E4MGD4eXlBa1Wi4YNG+LIkSO29UIIvPfee/D394dWq0W3bt1w8eLFh9xi2fB21eBOmvGR593wLsX53729vdGnTx+sWLECy5cvR58+fVC1alW7baKjo5GRkYHu3bvD1dXVdlm5ciViYqzfrJ47dw6tW7e2u152oHqY77//HqGhoWjcuDEAoEmTJggODsYPP/xQQo+QiKh4LBaB+dujAQAvtw+Bi4bfDRIR0aNJ+tfi3r17CA8PR+fOnfHbb7/B29sbFy9eRJUqVWzbfPbZZ/jiiy/wzTffICQkBO+++y569uyJs2fPwsmp8CfKehitSoGzH/Qs8PZKufwR591wwsax7Qp830UxfPhwjBs3DgCwYMGCXOvT0tIAAJs3b0a1atXs1mk0xQtwS5cuxZkzZ6BU/rsbWSwWLFu2DC+//HKxbpuIqCRsPROPiwlp0Dkp8VK7GlKXQ0RE5YSkIenTTz9FYGCg3biakJB/51MXQmDOnDl455138NRTTwEAVq5cCV9fX/z00094/vnnS7QemUxWqEPeMo0mDGsXgrl/5e5sZc//XtqD03r16gWj0QiZTIaePXMHvPr160Oj0eDatWuIiIjI8zbq1auHTZs22S07cODAQ+/31KlTOHLkCHbu3AlPT0/b8rt376JTp044f/486tatW4RHRERUMiwWgS/uvz8PDQ+BzsFPXEhERI5D0sPtNm3ahBYtWuA///kPfHx80LRpU3z11Ve29ZcvX0Z8fDy6detmW+bu7o7WrVvbxsE8yGAwICUlxe5SWhxh/neFQoFz587h7NmzUChyd6Pc3NwwZcoUTJo0Cd988w1iYmJw7NgxzJs3D9988w0AYPTo0bh48SJef/11XLhwAatXr8aKFSseer9Lly5Fq1at0LFjRzRo0MB26dixI1q2bMkJHIhIctvO3cL5+FS4qBUYHl5D6nKIiKgckTQkXbp0CYsWLUKtWrXw+++/45VXXsGECRNsH97j4+MBAL6+vnbX8/X1ta17UGRkJNzd3W2XwMDAUn0M2fO/H/lfdxx9pxuO/K87RkXULNP533U6HXQ6Xb7rP/zwQ7z77ruIjIxEvXr10KtXL2zevNnWtQsKCsL69evx008/oXHjxli8eDFmzJiR7+0ZjUZ899136N+/f57r+/fvj5UrVyIrK6t4D4yIqIiEEJh3fyzSS+1qwMNZLXFFRERUnshEUeaeLiFqtRotWrSwO7fOhAkTcPjwYezfvx/79u1DeHg4YmNj4e/vb9vm2WefhUwmy3OCAIPBAIPBYPs5JSUFgYGBSE5OzhUk9Ho9Ll++jJCQkBIf30R543NORGVhx4UEDFt+GFqVAnve7AyvUpxEh4iIyo+UlBS4u7vnmQ1ykrST5O/vj/r169stq1evHq5duwYA8PPzAwDcunXLbptbt27Z1j1Io9HYOiuP6rAQEVHFI4TAvPtjkQa3CWJAIiKiQpM0JIWHh+PChQt2y/755x8EB1vPYxESEgI/Pz/89ddftvUpKSk4ePBggaaoJiKiymdfzB0cu5YEjVKOkR1rSl0OERGVQ5LObjdp0iS0a9cOM2bMwLPPPotDhw7hyy+/xJdffgnAOtvcxIkT8dFHH6FWrVq2KcADAgLw9NNPS1k6ERE5qOwZ7Qa2CoKPGw/rJSKiwpM0JLVs2RIbN27E1KlT8cEHHyAkJARz5szBCy+8YNvmjTfeQHp6Ov773/8iKSkJ7du3x9atWzmehYiIcjl46Q4OXr4LtUKOURHsIhERUdFIOnFDWXjY4CxOIlD2+JwTUWka/PVB7IlOxKDWQZjxTEOpyyEiIgdTLiZuICIiKinHrt3DnuhEKOUyvBIRKnU5RERUjjEkERFRhZA9o12/ZtUQ6OkscTVERFSeMSQREVG5d+pGMnZcuA25DBjTKUzqcoiIqJxjSCIionJv3nZrF+mpJtVQo6qLxNUQEVF5x5BEedq5cydkMhmSkpKkLoWI6KHOxaXgj7O3IJMBYzuzi0RERMXHkFQODR06FDKZDKNHj861buzYsZDJZBg6dGip11GjRg3IZDLIZDIoFAoEBATg5Zdfxr1790r9vomIss3fEQ0A6N3QH2E+rhJXQ0REFQFDUkkwZgBmI5B+2/qvMaPU7zIwMBBr1qxBZmambZler8fq1asRFBRU6vef7YMPPkBcXByuXbuGVatWYdeuXZgwYUKZ3T8RVW7RCanYcioOADC+C7tIRERUMhiSisukB/bOAT6vBXweZv137xzr8lLUrFkzBAYGYsOGDbZlGzZsQFBQEJo2bWq3rcViQWRkJEJCQqDVatG4cWOsW7fObpstW7agdu3a0Gq16Ny5M65cuVKgOtzc3ODn54dq1aqhc+fOGDJkCI4dO1bsx0dEVBDzt0dDCKBHfV/U9cv/fBdERESFwZCUkxCAMb3gF0MqsHsWEPUpoE+y3oY+yfrz7lnW9QW9rSKc03f48OFYvny57edly5Zh2LBhubaLjIzEypUrsXjxYpw5cwaTJk3C4MGDERUVBQC4fv06+vXrh759++L48eMYMWIE3nrrrULXc/PmTfzyyy9o3bp1oa9LRFRYlxPTselELABgQtdaEldDREQViVLqAhxKVgYwI6Bg2zp7ARNPAQeX5L3+4BIg/FVgTkMg486jb+/tWEBduBmZBg8ejKlTp+Lq1asAgL1792LNmjXYuXOnbRuDwYAZM2Zg27ZtaNu2LQCgZs2a2LNnD5YsWYKIiAgsWrQIoaGhmDlzJgCgTp06OHXqFD799NNH1vDmm2/inXfegdlshl6vR+vWrTFr1qxCPQ4ioqJYuCMaFgF0qeuDBtXcpS6HiIgqEIakonL1BdIT/+0gPUifBGQkWrcrSEgqAm9vb/Tp0wcrVqyAEAJ9+vRB1apV7baJjo5GRkYGunfvbrfcaDTaDss7d+5cru5PdqB6lNdffx1Dhw6FEALXr1/H22+/jT59+mDXrl1QKBTFeHRERPm7fjcDG/++CYBjkYiIqOQxJOWkcrZ2dApKoQKcPPIOSk4egJs/MGJbwe+7CIYPH45x48YBABYsWJBrfVpaGgBg8+bNqFatmt06jUZTpPvMqWrVqggLs35AqVWrFubMmYO2bdtix44d6NatW7Fvn4goL4uiYmCyCHSoVRVNg6pIXQ4REVUwDEk5yWSFO+TNmAG0HmUdg/Sg1qMAs6nQh9AVVq9evWA0GiGTydCzZ89c6+vXrw+NRoNr164hIiIiz9uoV68eNm3aZLfswIEDRaonu3uUc9Y9IqKSFJuUibVHrgMAxnfhWCQiIip5DEnFoXYGOky2/v/gEmtHycnDGpA6TAaUTqVegkKhwLlz52z/f5CbmxumTJmCSZMmwWKxoH379khOTsbevXuh0+kwZMgQjB49GjNnzsTrr7+OESNG4OjRo1ixYkWB7j81NRXx8fG2w+3eeOMNeHt7o127diX5MImIbJZExSDLLNA6xBOtQjylLoeIiCoghqTiUjoB4ROBjlMAfQrgpAPMWWUSkLLpdA+f9vbDDz+Et7c3IiMjcenSJXh4eKBZs2Z4++23AQBBQUFYv349Jk2ahHnz5qFVq1aYMWMGhg8f/sj7fu+99/Dee+8BsI6RatmyJf744w94eXkV/4ERET0gIUWP7w9bu0ivckY7IiIqJTIhijD3dDmSkpICd3d3JCcn5woTer0ely9fRkhICJycyi7UVGZ8zomoOD769Sy+3nMZzYOrYN3otpDJZFKXRERE5cjDskFOPE8SERGVC3fSDFh18BoA64x2DEhERFRaGJKIiKhc+HrPZWRmmdGoujsiantLXQ4REVVgDElEROTwkjKMWLnvCgDrjHbsIhERUWliSCIiIoe3bO8VpBvNqOevQ7d6PlKXQ0REFRxDEoAKPneFQ+FzTUSFlaLPwvK9lwFwLBIREZWNSh2SVCoVACAjI0PiSiqP7Oc6+7knInqUb/ZeQarehFo+ruj1mJ/U5RARUSVQqc+TpFAo4OHhgYSEBACAs7Mzv6EsJUIIZGRkICEhAR4eHnme+JaI6EFpBhOW3u8ijesSBrmc79FERFT6KnVIAgA/P+u3ktlBiUqXh4eH7TknInqU7w5cRVJGFmpWdcETjQKkLoeIiCqJSh+SZDIZ/P394ePjg6ysLKnLqdBUKhU7SERUYJlGM77efQkAMKZzGBTsIhERURmp9CEpm0Kh4Ad4IiIHsvrQNSSmGRHoqcVTTdhFIiKislOpJ24gIiLHpM8yY0lUDABgTKcwqBT8c0VERGWHf3WIiMjh/HjkOhJSDQhwd0L/ZtWlLoeIiCoZhiQiInIoRpMFi3dau0ivdAqFWsk/VUREVLb4l4eIiBzK+mM3EJush4+bBv9pESh1OUREVAkxJBERkcPIMluwcGc0AGBURCicVJxQh4iIyh5DEhEROYyfj8fi+t1MVHVVY1CrIKnLISKiSoohiYiIHILZIrBwh7WLNKJDTWjV7CIREZE0GJKIiMgh/HoyFpcS0+HhrMLgNsFSl0NERJUYQxIREUnOYhGYv93aRXo5PASuGp7rnIiIpMOQREREktt6Jh4XE9Lg5qTEkPAaUpdDRESVHEMSERFJSgiBefe7SMPCQ6BzUklcERERVXYMSUREJKlt5xJwLi4FLmoFhrOLREREDoAhiYiIJGPtIl0EALzUrgY8nNUSV0RERMSQREREEor65zZO3kiGVqXAiPYhUpdDREQEgCGJiIgkIoTAF39Zu0gvtA6Cl6tG4oqIiIisGJKIiEgS+2Lu4Ni1JKiVcvy3Y02pyyEiIrJhSCIiIklkd5EGtQqCj85J4mqIiIj+xZBERERl7tDluzh4+S7UCjlGRbCLREREjoUhiYiIylz2jHYDWlSHv7tW4mqIiIjsSRqSpk2bBplMZnepW7eubX2nTp1yrR89erSEFRMRUXH9fe0edl9MhFIuwysRoVKXQ0RElItS6gIee+wxbNu2zfazUmlf0siRI/HBBx/YfnZ2di6z2oiIqOTN2x4NAHimaTUEevI9nYiIHI/kIUmpVMLPzy/f9c7Ozg9dT0RE5cfpm8nYfj4BchkwtnOY1OUQERHlSfIxSRcvXkRAQABq1qyJF154AdeuXbNbv2rVKlStWhUNGjTA1KlTkZGRIVGlRERUXNkz2j3ZOAA1qrpIXA0REVHeJO0ktW7dGitWrECdOnUQFxeH6dOno0OHDjh9+jTc3NwwaNAgBAcHIyAgACdPnsSbb76JCxcuYMOGDfnepsFggMFgsP2ckpJSFg+FiIge4VxcCv44ewsyGTCuC7tIRETkuGRCCCF1EdmSkpIQHByMWbNm4eWXX861fvv27ejatSuio6MRGpr3YN9p06Zh+vTpuZYnJydDp9OVeM1ERFQwY1cfw+aTcejTyB8LBjWTuhwiIqqEUlJS4O7u/shsIPnhdjl5eHigdu3aiI6OznN969atASDf9QAwdepUJCcn2y7Xr18vlVqJiKjgohNSseVUHABgPLtIRETk4BwqJKWlpSEmJgb+/v55rj9+/DgA5LseADQaDXQ6nd2FiIiktWBHDIQAetT3RV0/vi8TEZFjk3RM0pQpU9C3b18EBwcjNjYW77//PhQKBQYOHIiYmBisXr0avXv3hpeXF06ePIlJkyahY8eOaNSokZRlExFRIVxJTMfPx28CAMZ3qSVxNURERI8maUi6ceMGBg4ciDt37sDb2xvt27fHgQMH4O3tDb1ej23btmHOnDlIT09HYGAg+vfvj3feeUfKkomIqJAW7oyGRQCd63ijYXV3qcshIiJ6JElD0po1a/JdFxgYiKioqDKshoiIStr1uxnYcOx+F6kru0hERFQ+ONSYJCIiqlgWRcXAZBHoUKsqmgVVkbocIiKiAmFIIiKiUhGXnIl1R24A4FgkIiIqXxiSiIioVCyJugSj2YLWIZ5oFeIpdTlEREQFxpBEREQlLiFVj+8PXQMATOBYJCIiKmcYkoiIqMR9tesSDCYLmgV5oF2ol9TlEBERFQpDEhERlag7aQZ8d8DaRRrftRZkMpnEFRERERUOQxIREZWor/dcRmaWGY2qu6NTbW+pyyEiIio0hiQiIioxSRlGrNx3BYB1Rjt2kYiIqDxiSCIiohKzbO8VpBvNqOevQ7d6PlKXQ0REVCQMSUREVCJS9FlYvvcyAGB8lzB2kYiIqNxiSCIiohKxct8VpOpNqOXjil6P+UldDhERUZExJBERUbGlG0xYusfaRRrXJQxyObtIRERUfjEkERFRsX134CruZWQhpKoLnmgUIHU5RERExcKQRERExZJpNOOr3ZcAAGM6hULBLhIREZVzDElERFQsqw9dQ2KaEYGeWjzdtJrU5RARERUbQxIRERWZPsuMJVExAIAxncKgUvDPChERlX/8a0ZEREW29sh1JKQaEODuhP7NqktdDhERUYlgSCIioiIxmixYtNPaRRrdKRRqJf+kEBFRxcC/aEREVCQbjt1AbLIePm4aPNsiUOpyiIiISgxDEhERFVqW2YIFO6MBAP/tWBNOKoXEFREREZUchiQiIiq0n4/H4vrdTFR1VeOF1sFSl0NERFSiGJKIiKhQzBaBhTusXaQRHWpCq2YXiYiIKhaGJCIiKpRfT8biUmI6PJxVGNyGXSQiIqp4GJKIiKjALBaBBfe7SC+Hh8BVo5S4IiIiopLHkERERAX2+5l4/HMrDW5OSgwJryF1OURERKWCIYmIiApECIF5261dpGHtakDnpJK4IiIiotLBkERERAXy17kEnI1LgYtageHtQ6Quh4iIqNQwJBER0SMJIfDF9osAgJfa1YCHs1riioiIiEoPQxIRET1S1D+3cfJGMrQqBUawi0RERBUcQxIRET1UzrFIL7QOgperRuKKiIiIShdDEhERPdT+mDs4evUe1Eo5/tuxptTlEBERlTqGJCIieqjssUgDWwbCR+ckcTVERESljyGJiIjydfjKXRy4dBcqhQyjIkKlLoeIiKhMMCQREVG+vvjL2kUa0DwQAR5aiashIiIqGwxJRESUp7+v3cPui4lQymUY04ldJCIiqjwYkoiIKE/ZM9o907QaAj2dJa6GiIio7DAkERFRLqdvJmP7+QTIZcDYzmFSl0NERFSmGJKIiCiXefdntHuycQBqVHWRuBoiIqKyxZBERER2zsen4PcztyCTAeO6sItERESVD0MSERHZmX9/LFLvBv4I83GTuBoiIqKyx5BEREQ20Qlp2HwqDgC7SEREVHkxJBERkc2CHdEQAuhR3xf1/HVSl0NERCQJhiQiIgIAXElMx8/HbwIAxnepJXE1RERE0mFIIiIiAMDCndGwCKBzHW80rO4udTlERESSYUgiIiJcv5uBDcfud5G6sotERESVG0MSERFhcVQMTBaB9mFV0SyoitTlEBERSUrSkDRt2jTIZDK7S926dW3r9Xo9xo4dCy8vL7i6uqJ///64deuWhBUTEVU88cl6rD1yAwAwnjPaERERSd9JeuyxxxAXF2e77Nmzx7Zu0qRJ+OWXX7B27VpERUUhNjYW/fr1k7BaIqKKZ3FUDIxmC1qFeKJ1TS+pyyEiIpKcUvIClEr4+fnlWp6cnIylS5di9erV6NKlCwBg+fLlqFevHg4cOIA2bdqUdalERBVOQqoe3x+6BgB4lWORiIiIADhAJ+nixYsICAhAzZo18cILL+DaNesf66NHjyIrKwvdunWzbVu3bl0EBQVh//79+d6ewWBASkqK3YWIiPL21a5LMJgsaBbkgXah7CIREREBEoek1q1bY8WKFdi6dSsWLVqEy5cvo0OHDkhNTUV8fDzUajU8PDzsruPr64v4+Ph8bzMyMhLu7u62S2BgYCk/CiKi8ulOmgHfHbB+MTW+ay3IZDKJKyIiInIMkh5u9/jjj9v+36hRI7Ru3RrBwcH48ccfodVqi3SbU6dOxeTJk20/p6SkMCgREeVh6Z7LyMwyo1F1d3Sq7S11OURERA5D8sPtcvLw8EDt2rURHR0NPz8/GI1GJCUl2W1z69atPMcwZdNoNNDpdHYXIiKyl5RhxMr9VwEA4zqHsYtERESUg0OFpLS0NMTExMDf3x/NmzeHSqXCX3/9ZVt/4cIFXLt2DW3btpWwSiKi8m/53itIM5hQ188N3ev7Sl0OERGRQ5H0cLspU6agb9++CA4ORmxsLN5//30oFAoMHDgQ7u7uePnllzF58mR4enpCp9Nh/PjxaNu2LWe2IyIqhhR9FpbvvQwAGN+FY5GIiIgeJGlIunHjBgYOHIg7d+7A29sb7du3x4EDB+DtbT02fvbs2ZDL5ejfvz8MBgN69uyJhQsXSlkyEVG5t3LfFaToTajl44rHG+R/+DIREVFlJRNCCKmLKE0pKSlwd3dHcnIyxycRUaWXbjCh/afbcS8jC3Ofb4KnmlSTuiQiIqIyU9Bs4FBjkoiIqHR9d+Aq7mVkIaSqC55oFCB1OURERA6JIYmIqJLINJrx1e5LAIAxnUKhkHMsEhERUV4YkoiIKonvD11DYpoR1ato8XRTHmZHRESUH4YkIqJKQJ9lxpJdMQCAMZ3CoFLw7Z+IiCg//CtJRFQJrD16A7dSDPB3d0L/5uwiERERPQxDEhFRBWc0WbBoRzQA4JVOodAoFRJXRERE5NgYkoiIKrgNx24gNlkPHzcNnm0RKHU5REREDo8hiYioAjOZLVi40zoW6b8da8JJxS4SERHRozAkERFVYD8fj8W1uxnwclHjhdbBUpdDRERULjAkERFVUGaLwIL7Y5FGdKgJrZpdJCIiooJgSCIiqqA2n4rDpcR0eDir8GJbdpGIiIgKiiGJiKgCslgE5m+/CAAYHh4CV41S4oqIiIjKD4YkIqIK6Pcz8fjnVhrcnJQY0q6G1OUQERGVKwxJREQVjBAC87ZbxyINa1cD7lqVxBURERGVLwxJREQVzF/nEnA2LgUuagWGtw+RuhwiIqJyhyGJiKgCsXaRrGORXmxbAx7OaokrIiIiKn8YkoiIKpBdFxNx4kYynFRyjOjALhIREVFRMCQREVUQQgjM+8vaRXqhdTCqumokroiIiKh8YkgiIqog9l+6gyNX70GtlGNUx5pSl0NERFRuMSQREVUQX9zvIg1sGQgfnZPE1RAREZVfDElERBXA4St3ceDSXagUMoyKCJW6HCIionKNIYmIqALI7iINaB6IAA+txNUQERGVbwxJRETl3PHrSdh9MREKuQxjOrGLREREVFwMSURE5Vz2jHbPNK2GQE9niashIiIq/xiSiIjKsdM3k/HX+QTIZcDYzmFSl0NERFQhMCQREZVj87dHAwD6Ng5ASFUXiashIiKqGBiSiIjKqfPxKdh6Jh4yGTCOXSQiIqISw5BERFROZXeRejfwRy1fN4mrISIiqjgYkoiIyqHohDRsPhUHABjXhV0kIiKiksSQRERUDi3cEQ0hgO71fVHPXyd1OURERBUKQxIRUTlz9U46fj4RCwCY0KWWxNUQERFVPAxJRETlzMIdMTBbBDrV8UbD6u5Sl0NERFThMCQREZUj1+9mYP2xGwCA8ewiERERlQqGJCKicmRxVAxMFoH2YVXRPLiK1OUQERFVSAxJRETlRHyyHmuPZHeROKMdERFRaWFIIiIqJxZHxcBotqBViCda1/SSuhwiIqIKiyGJiKgcSEjV4/tD1wBwRjsiIqLSxpBERFQOfL37MgwmC5oGeSA8jF0kIiKi0sSQRETk4O6kGfDt/qsArF0kmUwmcUVEREQVG0MSEZGDW7rnMjKzzGhYzR2d6nhLXQ4REVGFx5BEROTAkjKMWHm/izS+Sxi7SERERGWAIYmIyIEt33sFaQYT6vq5oXt9X6nLISIiqhQYkoiIHFSqPgvL914GAIznWCQiIqIyw5BEROSgVu6/ihS9CWE+rni8gZ/U5RAREVUaDElERA4o3WDC17svAQDGdQ6DXM4uEhERUVlhSCIickCrDl7FvYws1PByxhON/KUuh4iIqFJxmJD0ySefQCaTYeLEibZlnTp1gkwms7uMHj1auiKJiMpAptGML3dZu0hjO4dBqXCYt2oiIqJKQSl1AQBw+PBhLFmyBI0aNcq1buTIkfjggw9sPzs7O5dlaUREZe77Q9eQmGZE9SpaPN20mtTlEBERVTqSfz2ZlpaGF154AV999RWqVKmSa72zszP8/PxsF51OJ0GVRERlQ59lxpJdMQCAMZ3CoGIXiYiIqMxJ/td37Nix6NOnD7p165bn+lWrVqFq1apo0KABpk6dioyMjIfensFgQEpKit2FiKi8WHv0Bm6lGODv7oT+zdlFIiIikoKkh9utWbMGx44dw+HDh/NcP2jQIAQHByMgIAAnT57Em2++iQsXLmDDhg353mZkZCSmT59eWiUTEZUao8mCxTutXaTREaHQKBUSV0RERFQ5SRaSrl+/jldffRV//vknnJyc8tzmv//9r+3/DRs2hL+/P7p27YqYmBiEhobmeZ2pU6di8uTJtp9TUlIQGBhYssUTEZWCjX/fwM2kTHi7afBcS75vERERSUWykHT06FEkJCSgWbNmtmVmsxm7du3C/PnzYTAYoFDYf4vaunVrAEB0dHS+IUmj0UCj0ZRe4UREpcBktmDBDmsXaVTHmnBSsYtEREQkFclCUteuXXHq1Cm7ZcOGDUPdunXx5ptv5gpIAHD8+HEAgL8/zxlCRBXLz8djce1uBrxc1BjUOkjqcoiIiCo1yUKSm5sbGjRoYLfMxcUFXl5eaNCgAWJiYrB69Wr07t0bXl5eOHnyJCZNmoSOHTvmOVU4EVF5ZbYILNgRDQAY0aEmnNUOcXYGIiKiSsth/xKr1Wps27YNc+bMQXp6OgIDA9G/f3+88847UpdGRFSiNp+Kw6XEdHg4q/Bi22CpyyEiIqr0HCok7dy50/b/wMBAREVFSVcMEVEZsFgE5m+/CAAYHh4CV41DvS0TERFVSpKfJ4mIqDL742w8/rmVBjeNEkPa1ZC6HCIiIgJDEhGRZIQQmLfdOhZpaHgNuGtVEldEREREAEMSEZFktp9PwJnYFLioFRgeHiJ1OURERHQfQxIRkQSEEPjiL+tYpBfb1kAVF7XEFREREVE2hiQiIgnsupiIEzeS4aSSY0QHdpGIiIgcCUMSEVEZE0Jg3v0u0gutg1HVVSNxRURERJQTQxIRURnbf+kOjly9B7VSjlEda0pdDhERET2g0CfksFgsWLFiBTZs2IArV65AJpMhJCQEAwYMwIsvvgiZTFYadRIRVRjz/rLOaPd8y0D46JwkroaIiIgeVKhOkhACTz75JEaMGIGbN2+iYcOGeOyxx3D16lUMHToUzzzzTGnVSURUIRy5chf7L92BSiHD6IhQqcshIiKiPBSqk7RixQrs2rULf/31Fzp37my3bvv27Xj66aexcuVKvPTSSyVaJBFRRfHF/fMiDWheHQEeWomrISIiorwUqpP0/fff4+23384VkACgS5cueOutt7Bq1aoSK46IqCI5fj0Ju/65DYVchjGdwqQuh4iIiPJRqJB08uRJ9OrVK9/1jz/+OE6cOFHsooiIKqLsGe2eaVoNgZ7OEldDRERE+SlUSLp79y58fX3zXe/r64t79+4Vuygioorm9M1k/HU+AXIZMLYzu0hERESOrFAhyWw2Q6nMfxiTQqGAyWQqdlFERBXN/Ptjkfo2DkBIVReJqyEiIqKHKdTEDUIIDB06FBpN3ic+NBgMJVIUEVFFciE+FVvPxEMmA8axi0REROTwChWSXnrppUeeB4kz2xER2Zu/w9pFeryBH2r5uklcDRERET1KoacAJyKigotOSMOvJ2MBAOM615K4GiIiIiqIQoWkfv36PXIbmUyG9evXF7kgIqKKZOGOaAgBdK/vi/oBOqnLISIiogIoVEhyd3cvrTqIiCqcq3fS8fMJaxdpQhd2kYiIiMqLQoWk5cuXl1YdREQVzsIdMTBbBDrV8UbD6vySiYiIqLwo1BTgRERUMDfuZWD9sRsAgPHsIhEREZUrDElERKVgcVQMTBaB8DAvNA+uInU5REREVAgMSUREJSw+WY8fD7OLREREVF4xJBERlbAlu2JgNFvQqoYn2tT0krocIiIiKiSGJCKiEpSQqsfqg9cAABO6sotERERUHjEkERGVoK93X4bBZEHTIA+Eh7GLREREVB4xJBERlZC76UZ8d+AqAOt5kWQymcQVERERUVEwJBERlZCley4hw2hGw2ru6FTHW+pyiIiIqIgYkoiISkByRha+2WftIo3rEsYuEhERUTnGkEREVAKW77uMNIMJdf3c0L2er9TlEBERUTEwJBERFVOqPgvL9lwGYO0iyeXsIhEREZVnDElERMW0cv9VpOhNCPNxxeMN/KUuh4iIiIqJIYmIqBjSDSZ8vfsSAGBc5zAo2EUiIiIq9xiSiIiKYdXBq7iXkYUaXs54ohG7SERERBUBQxIRURHps8z4cpd1LNKYzmFQKviWSkREVBHwLzoRURF9f+gaEtMMqF5Fi2eaVpO6HCIiIiohDElEREVgMJmxJMo6FumVTqFQsYtERERUYfCvOhFREaw9cgPxKXr4uzthQPPqUpdDREREJYghiYiokIwmCxbtjAEAjI4IhUapkLgiIiIiKkkMSUREhbTx7xu4mZQJbzcNnmsZKHU5REREVMIYkoiICsFktmDBDmsXaVTHmnBSsYtERERU0TAkEREVwqYTsbh2NwOeLmoMah0kdTlERERUChiSiIgKyGwRmL8jGgAwokMInNVKiSsiIiKi0sCQRERUQFtOxeHS7XS4a1V4qW0NqcshIiKiUsKQRERUABaLwPzt1i7Sy+1D4KphF4mIiKiiYkgiIiqAP87G48KtVLhplBjSrobU5RAREVEpcpiQ9Mknn0Amk2HixIm2ZXq9HmPHjoWXlxdcXV3Rv39/3Lp1S7oiiahSEkJg3v0u0tDwGnDXqiSuiIiIiEqTQ4Skw4cPY8mSJWjUqJHd8kmTJuGXX37B2rVrERUVhdjYWPTr10+iKomostp+PgFnYlPgolZgeHiI1OUQERFRKZM8JKWlpeGFF17AV199hSpVqtiWJycnY+nSpZg1axa6dOmC5s2bY/ny5di3bx8OHDggYcVEVJkIIfDF/S7S4LbBqOKilrgiIiIiKm2Sh6SxY8eiT58+6Natm93yo0ePIisry2553bp1ERQUhP379+d7ewaDASkpKXYXIqKi2n0xESeuJ8FJJcfIDjWlLoeIiIjKgKTTM61ZswbHjh3D4cOHc62Lj4+HWq2Gh4eH3XJfX1/Ex8fne5uRkZGYPn16SZdKRJWQdSzSRQDAoFbBqOqqkbgiIiIiKguSdZKuX7+OV199FatWrYKTk1OJ3e7UqVORnJxsu1y/fr3EbpuIKpcDl+7i8JV7UCvlGBXBLhIREVFlIVlIOnr0KBISEtCsWTMolUoolUpERUXhiy++gFKphK+vL4xGI5KSkuyud+vWLfj5+eV7uxqNBjqdzu5CRFQUX/xl7SI93zIQvrqS+zKHiIiIHJtkh9t17doVp06dsls2bNgw1K1bF2+++SYCAwOhUqnw119/oX///gCACxcu4Nq1a2jbtq0UJRNRJXLkyl3sv3QHKoUMoyNCpS6HiIiIypBkIcnNzQ0NGjSwW+bi4gIvLy/b8pdffhmTJ0+Gp6cndDodxo8fj7Zt26JNmzZSlExElUj2jHYDmldHgIdW4mqIiIioLEk6ccOjzJ49G3K5HP3794fBYEDPnj2xcOFCqcsiogru+PUk7PrnNhRyGV6JCJO6HCIiIipjMiGEkLqI0pSSkgJ3d3ckJydzfBIRFciIbw5j27kE9G9WHTOfbSx1OURERFRCCpoNJD9PUmWRaTTBaLLgTpoBRpMFGUaT1CURUR7OxCZj27kEyGXA2M4ci0RERFQZOfThdhWFIcuMxVGXsHzfZaRkmqDTKjGsXQjGdAqFRqWQujwiymH+/bFIfRsHoKa3q8TVEBERkRQYkkpZptGExVGXMPf+VMIAkJJpsv08KqImnNX8NRA5ggvxqfjtdDxkMmBcZ45FIiIiqqx4uF0pU8jlWL7vcp7rlu+7DKWcvwIiRzF/h7WL9HgDP9TydZO4GiIiIpIKP6GXslR9FlIy8x5/lJJpQqo+q4wrIqK8xNxOw68nYwEA4zrXkrgaIiIikhJDUilzc1JBp837cDqdVglXJx5qR+QIFuyIhhBAt3q+qB/AmTCJiIgqM4akUma2WDCsXUie64a0rYGoC7cx4fu/kZhmKOPKiCjbtTsZ+Pm4tYs0oSvHIhEREVV2bGOUMq1aiTGdrNMIPzi73cvtQ9B/0T5cTEjDrou38W6f+ujXrBpkMpnEVRNVLgt3RsNsEYio7Y1G1T2kLoeIiIgkxpPJlpEMowlKuRyp+iy4OalgsljgrFbixPUkvLXhFM7FpQAAOtSqio+fboggL2fJaiWqTG7cy0Dn/9uJLLPA+lfaoXlwFalLIiIiolLCk8k6GGe1EmqlHF6uGqiVctu0340DPbBpXDje6FUHaqUcuy8mosecKHy16xJMZovEVRNVfIujYpBlFggP82JAIiIiIgAMSQ5BpZBjTKcw/D6xI9rU9IQ+y4KPt5zDMwv34fTNZKnLI6qw4pP1+PHwDQDA+C6c0Y6IiIisGJIcSEhVF3w/sg0+7d8QOiclTt1MxlML9uKT385Dn2WWujyiCmfJrhgYzRa0quGJNjW9pC6HiIiIHARDkoORyWR4rmUQtr0WgT4N/WG2CCyOikHPObuwLzpR6vKIKozbqQasPngNADCeM9oRERFRDgxJDsrHzQkLXmiGL19sDj+dE67eycCgrw/ijXUnkJRhlLo8onLv692XYDBZ0CTQA+3DqkpdDhERETkQhiQH1+MxP/w5uSNebBMMAPjxyA10mxWFX0/GooJPTEhUau6mG/HtgasArOdF4rT7RERElBNDUjng5qTCh083wLrRbRHm44rENCPGrf4bI1ceQWxSptTlEZU7y/ZcRobRjAbVdOhcx0fqcoiIiMjBMCSVIy1qeGLzhPZ4tWstqBQybDuXgO6zorBy/xVYLOwqERVEckYWVuy7AsA6ox27SERERPQghqRyRqNUYFL32tg8oQOaBXkg3WjGez+fwYDF+/DPrVSpyyNyeMv3XUaawYS6fm7oXs9X6nKIiIjIATEklVO1fd2wbnQ7fPDUY3BRK3DsWhL6fLEbs//8BwYTpwsnykuqPgvL9lwGAIzrEga5nF0kIiIiyo0hqRyTy2V4qW0N/Dk5Al3r+iDLLDD3r4vo88UeHLlyV+ryiBzOyv1XkaI3IdTbBY838Je6HCIiInJQDEkVQICHFl8PaYH5g5qiqqsa0QlpGLB4P9756RRS9VlSl0fkEDKMJizN0UVSsItERERE+WBIqiBkMhmeaBSAbZMj8GyL6gCA7w5cQ/dZu/Dn2VsSV0ckvVUHruFuuhHBXs7o2yhA6nKIiIjIgTEkVTAezmp8NqAxVo1ojWAvZ8Sn6DFy5RGMXXUMCal6qcsjkoQ+y4wluy4BAMZ2DoNSwbc+IiIiyh8/KVRQ4WFVsfXVjhgdEQqFXIbNp+LQbWYUfjh8jSehpUrn+0PXkJhmQPUqWjzTtJrU5RAREZGDY0iqwLRqBd56vC5+HhuOBtV0SNGb8Ob6Uxj01UFcTkyXujyiMmEwmbEkytpFeqVTKFTsIhEREdEj8NNCJdCgmjt+GhOO//WuByeVHPsv3UGvObuwcGc0sswWqcsjKlVrj9xAfIoe/u5OGNC8utTlEBERUTnAkFRJKBVyjOxYE39MjECHWlVhMFnw2dYLeHL+Xpy8kSR1eUSlIstswaKdMQCAUR1rQqNUSFwRERERlQcMSZVMkJczVg5vhZn/aQwPZxXOxaXg6QV78dGvZ5FhNEldHlGJ2njsJm4mZaKqqwbPtwqSuhwiIiIqJxiSKiGZTIb+zatj2+QIPNUkABYBfL3nMnrM3oWof25LXR5RiTCZLViwMxqAtYvkpGIXiYiIiAqGIakSq+qqwdznm2L50Jao5qHFjXuZGLLsECb/cBx3041Sl0dULL+cjMXVOxnwdFHjhTbsIhEREVHBMSQROtf1wR+TOmJYeA3IZMCGv2+i26wo/PT3TU4XTuWS2SIwb7u1izSiQwic1UqJKyIiIqLyhCGJAAAuGiXe7/sYNrzSDnV83XA33YiJPxzH0OWHcf1uhtTlERXKllNxuHQ7He5aFV5qW0PqcoiIiKicYUgiO02DquCX8e3xWvfaUCvkiPrnNnrM3oWley7DbGFXiRyfxSIw/34XaXh4CFw17CIRERFR4TAkUS5qpRzju9bCllc7oFUNT2RmmfHhr2fRb+FenItLkbo8oof64+wtXLiVCjeNEkPDa0hdDhEREZVDDEmUrzAfV6z5bxt8/EwDuGmUOHEjGX3n7cHnv5+HPsssdXlEuQghMG/7RQDAkHY14K5VSVwRERERlUcMSfRQcrkML7QOxrbXItDzMV+YLAILdsTg8bm7ceDSHanLI7Kz40ICzsSmwFmtwPD2IVKXQ0REROUUQxIViK/OCUtebIHFg5vBx02Dy4npeP7LA5i64SSSM7OkLo8IQgh88Zd1LNKLbYPh6aKWuCIiIiIqrxiSqFB6NfDHn5MjMLCV9bwz3x+6jm6zorD1dJzElVFlt/tiIo5fT4KTSo6RHWpKXQ4RERGVYwxJVGjuWhUi+zXED/9tg5pVXXA71YDR3x3Df1ceQXyyXuryqBLKORZpUKtgVHXVSFwRERERlWcMSVRkrWt6YcurHTC+SxiUchn+OHsL3WdF4bsDV2HhdOFUhg5cuovDV+5BrZRjVAS7SERERFQ8DElULE4qBV7rUQe/TmiPxoEeSDWY8M5Pp/Hcl/sRnZAmdXlUSWR3kZ5rEQhfnZPE1RAREVF5x5BEJaKunw4bXmmH9/vWh7NagcNX7qH33N344q+LMJosUpdHFdjRq3exL+YOVAoZRncKlbocIiIiqgAYkqjEKOQyDAsPwR+TOqJTHW8YzRbM+vMfPDFvN45duyd1eVRBZc9o179ZdVTz0EpcDREREVUEDElU4qpXccbyoS0x9/km8HRR459baei/aB+mbTqDNINJ6vKoAjlxPQlR/9yGQi7DmE5hUpdDREREFQRDEpUKmUyGp5pUw7bJEejXrBqEAFbsu4Ies6Kw/fwtqcujCiJ7LNLTTaohyMtZ4mqIiIioopA0JC1atAiNGjWCTqeDTqdD27Zt8dtvv9nWd+rUCTKZzO4yevRoCSumwvJ0UWPWs02wcngrBHpqEZusx/AVRzD++7+RmGaQujwqx87EJmPbuQTIZcDYzhyLRERERCVH0pBUvXp1fPLJJzh69CiOHDmCLl264KmnnsKZM2ds24wcORJxcXG2y2effSZhxVRUHWt74/eJHTGyQwjkMuCXE7HoNisKa49chxCcLpwKb/5261ikJxoFoKa3q8TVEBERUUUiaUjq27cvevfujVq1aqF27dr4+OOP4erqigMHDti2cXZ2hp+fn+2i0+kkrJiKw1mtxP/61MdPY8NR31+HpIwsvL7uJAYvPYird9KlLo/KkX9upeK30/EAgHFdOBaJiIiISpbDjEkym81Ys2YN0tPT0bZtW9vyVatWoWrVqmjQoAGmTp2KjIwMCaukktCougd+HheON3vVhUYpx97oO+g5ZxeWRMXAZOZ04fRo2V2kxxv4obavm8TVEBERUUWjlLqAU6dOoW3bttDr9XB1dcXGjRtRv359AMCgQYMQHByMgIAAnDx5Em+++SYuXLiADRs25Ht7BoMBBsO/Y11SUlJK/TFQ4akUcrzSKRSPN/DD1A2nsP/SHUT+dh6bTsTi0/6N0KCau9QlkoO6dDsNv56MBcAuEhEREZUOmZB4QIjRaMS1a9eQnJyMdevW4euvv0ZUVJQtKOW0fft2dO3aFdHR0QgNzXug9rRp0zB9+vRcy5OTk3monoMSQmDtkRv4aPNZpOhNUMhlGNE+BBO71YZWrZC6PHIwr/14AuuP3UC3er74ekgLqcshIiKiciQlJQXu7u6PzAaSh6QHdevWDaGhoViyZEmudenp6XB1dcXWrVvRs2fPPK+fVycpMDCQIakcSEjVY/ovZ7H5ZBwAIMjTGZH9GiI8rKrElZGjuHYnA51n7oTZIrBpXDgaVfeQuiQiIiIqRwoakhxmTFI2i8ViF3JyOn78OADA398/3+trNBrblOLZFyoffNycsGBQM3z9Ugv4uzvh2t0MvPD1QUxZewJJGUapyyMHsHBnNMwWgYja3gxIREREVGokHZM0depUPP744wgKCkJqaipWr16NnTt34vfff0dMTAxWr16N3r17w8vLCydPnsSkSZPQsWNHNGrUSMqyqZR1q++L1jU98fnvF/DtgatYd/QGdl5IwHt9H0PfRv6QyWRSl0gSuJmUifXHbgAAJnTlWCQiIiIqPZJ2khISEvDSSy+hTp066Nq1Kw4fPozff/8d3bt3h1qtxrZt29CjRw/UrVsXr732Gvr3749ffvlFypKpjLg5qfDBUw2wbnRbhPm4IjHNiAnf/42XvzmCm0mZUpdHEli8MwZZZoF2oV5oHuwpdTlERERUgTncmKSSVtDjDslxGUxmLNoZgwU7opFlFnBRK/B6zzp4sW0NKOTsKlUGt1L06PDZDhhNFnw/sg3ahnpJXRIRERGVQ+V2TBLRgzRKBSZ2q40tEzqgeXAVpBvNmPbLWQxYvA//3EqVujwqA0uiLsFosqBVDU+0qckuEhEREZUuhiQqN2r5umHtqLb48KnH4KpR4u9rSejzxW7M+uMCDCaz1OVRKbmdasDqQ1cBAOO7hnFMGhEREZU6hiQqV+RyGV5sWwN/Tu6IbvV8kGUW+GJ7NHrP3Y3DV+5KXR6Vgq93X4I+y4ImgR5oz+ngiYiIqAwwJFG55O+uxVcvtcCCQc1Q1VWDmNvp+M/i/fjfxlNI0WdJXR6VkLvpRnx7wNpFmsAuEhEREZURhiQqt2QyGfo08sdfkyPwXItAAMCqg9fQfVYU/jgTL3F1VBKW7bmMDKMZDarp0LmOj9TlEBERUSXBkETlnruzCp8OaITVI1ujhpczbqUY8N9vj+KV744iIUUvdXlURMmZWfhm3xUAwLjOtdhFIiIiojLDkEQVRrvQqtg6sSNe6RQKhVyG307Ho+usKKw5dA0VfKb7CmnF3itINZhQx9cNPer7Sl0OERERVSIMSVShOKkUeLNXXWwaF46G1dyRqjfhrQ2n8PyXB3DpdprU5VEBpeqzsGzvZQDWGe3kPB8WERERlSGGJKqQHgtwx8Yx7fBOn3rQqhQ4ePkues3dff+EtBapy6NH+PbAVSRnZiHU2wWPN/CXuhwiIiKqZBiSqMJSKuQY0aEm/pjUER1qVYXRZMHnv19A33l7cOJ6ktTlUT4yjCZ8vdvaRRrXJQwKdpGIiIiojDEkUYUX6OmMlcNbYdazjVHFWYXz8al4ZuFefPDLWaQbTFKXRw9YdeAa7qYbEezljL6NAqQuh4iIiCohhiSqFGQyGfo1q45tkyPwdJMAWASwbO9l9Ji9CzsvJEhdHt2nzzJjya5LAICxncKgVPAtioiIiMoeP4FQpeLlqsGc55ti+bCWqOahxc2kTAxdfhgT1/yNO2kGqcur9NYcuobENAOqeWjxTLNqUpdDRERElRRDElVKnev44I9JHTE8PAQyGfDT8Vh0mxWFjX/f4HThEjGYzFgcZe0ivdIpFCp2kYiIiEgi/BRClZaLRon3+tbHhlfaoa6fG+5lZGHSDycwZPlhXL+bIXV5lc66ozcQn6KHn84J/2lRXepyiIiIqBJjSKJKr2lQFfwyvj1e71kHaqUcu/65jR6zd+Hr3ZdgtrCrVBayzBYs3BEDABgdURMapULiioiIiKgyY0giAqBSyDG2cxh+e7UDWoV4IjPLjI82n8MzC/fibGyK1OVVeBuP3cTNpExUddXg+VZBUpdDRERElRxDElEOod6uWDOyDSL7NYSbkxInbySj7/w9+GzreeizzFKXVyGZzBYs2BkNABjVsSacVOwiERERkbQYkogeIJfLMLBVEP6aHIHHG/jBbBFYuDMGvebswr6YRKnLq3B+ORmLq3cy4Omixgtt2EUiIiIi6TEkEeXDR+eERYObY/Hg5vBx0+DKnQwM+uog3lp/EskZWVKXVyGYLQLzt1u7SC+3D4GzWilxRUREREQMSUSP1KuBH7a9FoEXWlu7HGsOX0fXWVHYciqO04UX02+n4xBzOx3uWhVeahssdTlEREREABiSiApE56TCx880xI+j2qKmtwsS0wwYs+oYRq48irjkTKnLK5csObpIw8ND4OakkrgiIiIiIiuGJKJCaBXiiS0TOmBClzAo5TJsO3cL3WftwrcHrsLC6cIL5Y+zt3A+PhVuGiWGhteQuhwiIiIiG4YkokJyUikwuUcd/DqhPZoEeiDNYMK7P53Gs0v2IzohVeryygUhBOZtvwgAGNKuBty17CIRERGR42BIIiqiun46rH+lHab1rQ9ntQJHrt5D77l7MHfbRRhNFqnLc2g7LiTgTGwKnNUKDG8fInU5RERERHYYkoiKQSGXYWh4CP6cHIHOdbxhNFswe9s/eGLebhy9ek/q8hySEAJf/GUdi/Rim2B4uqglroiIiIjIHkMSUQmo5qHFsqEtMff5JvByUeOfW2kYsHgf3v/5NNIMJqnLcyh7ohNx/HoSnFRyjOhQU+pyiIiIiHJhSCIqITKZDE81qYZtkyPQv1l1CAF8s/8qus+Kwl/nbkldnsOYd7+LNLBVELzdNBJXQ0RERJQbQxJRCaviosbMZxvj25dbIdBTi7hkPV7+5gjGrT6G26kGqcuT1IFLd3Doyl2olXKMjgiVuhwiIiKiPDEkEZWSDrW88cfECIzqWBNyGfDryTh0mxWFH49cr7Qnof3iL+uMds+1CISvzkniaoiIiIjyxpBEVIq0agWm9q6Hn8e2x2MBOiRnZuGNdSfxwtcHcfVOutTllamjV+9iX8wdqBQyjO7ELhIRERE5LoYkojLQsLo7fh4bjqmP14VGKce+mDvoMXsXFkfFwGSuHNOFZ89o179ZdVTz0EpcDREREVH+GJKIyohSIceoiFD8PrEj2oV6wWCy4JPfzuOpBXtx+may1OWVqhPXkxD1z20o5DKM6RQmdTlERERED8WQRFTGalR1waoRrfH5gEZw16pwJjYFT87fgxlbziHTaJa6vFIxb7u1i/RUkwAEeTlLXA0RERHRwzEkEUlAJpPhPy0CsW1yBJ5o5A+LAL7cdQk95kRh98XbUpdXos7GpmDbuVuQyYCxndlFIiIiIsfHkEQkIW83DeYPaoalQ1rA390J1+9m4sWlh/DajydwL90odXklYv4O64x2fRsFINTbVeJqiIiIiB6NIYnIAXSt54s/J0dgSNtgyGTA+mM30G1WFH4+frNcTxf+z61UbDkVDwAY14VdJCIiIiofGJKIHISrRonpTzXAutHtUMvHFXfSjXh1zXEMX3EYN5MypS6vSObfH4v0eAM/1PZ1k7gaIiIiooJhSCJyMM2Dq2DzhA6Y1K021Ao5dly4je6zorB872WYLeWnq3Tpdhp+PRkLgF0kIiIiKl8YkogckFopx6vdamHLq+3RIrgKMoxmTP/lLPov2ocL8alSl1cgC3bEwCKAbvV88FiAu9TlEBERERUYQxKRAwvzccOPo9riw6cbwFWjxPHrSejzxW7M/OMC9FmOO134tTsZ+On4TQDA+C61JK6GiIiIqHAYkogcnFwuw4ttgvHn5I7oXt8XJovAvO3R6P3Fbhy6fFfq8vK0KCoaZotAx9reaBzoIXU5RERERIXCkERUTvi7a/Hli82x6IVm8HbT4NLtdDy7ZD/e3ngKKfosqcuzuZmUiXVHbwAAXu3KsUhERERU/jAkEZUjMpkMjzf0x7ZJEXi+ZSAAYPXBa+g2MwpbT8dLXJ3V4p0xyDILtAv1QvNgT6nLISIiIio0hiSicsjdWYVP+jfC9yPbIKSqCxJSDRj93VGM/vYobqXoJavrVooePxy5DoBjkYiIiKj8YkgiKsfahnrht1c7YEynUCjlMmw9E49us6Kw+uA1WCSYLnxJ1CUYTRa0rFEFbWqyi0RERETlk6QhadGiRWjUqBF0Oh10Oh3atm2L3377zbZer9dj7Nix8PLygqurK/r3749bt25JWDGR43FSKfBGr7rYNK49GlV3R6rehLc3nsLzXx1AzO20MqsjMc2A1YeuArB2kWQyWZndNxEREVFJkjQkVa9eHZ988gmOHj2KI0eOoEuXLnjqqadw5swZAMCkSZPwyy+/YO3atYiKikJsbCz69esnZclEDqt+gA4bx4TjnT71oFUpcOjyXTw+dzfmb78Io8lS6vf/1e5L0GdZ0DjQAx1qVS31+yMiIiIqLTIhRNkfk/MQnp6e+PzzzzFgwAB4e3tj9erVGDBgAADg/PnzqFevHvbv3482bdoU6PZSUlLg7u6O5ORk6HS60iydyGFcv5uB//10Grv+uQ0AqOvnhsh+DdE0qEqp3N+9dCPCP92ODKMZS4e0QNd6vqVyP0RERETFUdBs4DBjksxmM9asWYP09HS0bdsWR48eRVZWFrp162bbpm7duggKCsL+/fvzvR2DwYCUlBS7C1FlE+jpjG+GtcTs5xqjirMK5+NT0W/RPkz/5QzSDaYSv79ley8jw2jGYwE6dKnrU+K3T0RERFSWJA9Jp06dgqurKzQaDUaPHo2NGzeifv36iI+Ph1qthoeHh932vr6+iI/Pf6rjyMhIuLu72y6BgYGl/AiIHJNMJsMzTatj2+QIPNO0GoQAlu+9gh6zd2HHhYQSu5/kzCys2HsFAMciERERUcUgeUiqU6cOjh8/joMHD+KVV17BkCFDcPbs2SLf3tSpU5GcnGy7XL9+vQSrJSp/vFw1mP1cE3wzvBWqeWhxMykTw5Yfxqtr/sadNEOxb3/F3itINZhQx9cNPerzMDsiIiIq/yQPSWq1GmFhYWjevDkiIyPRuHFjzJ07F35+fjAajUhKSrLb/tatW/Dz88v39jQajW22vOwLEQERtb3xx6SOeLl9COQy4Ofjseg2Kwrrj95AUYcmpuqzsGzvZQDAuC5hkMvZRSIiIqLyT/KQ9CCLxQKDwYDmzZtDpVLhr7/+sq27cOECrl27hrZt20pYIVH55aJR4t0n6mPjmHDU9XPDvYwsvLb2BF5adgjX72YU+va+PXAVyZlZqOntgt4N/UuhYiIiIqKyp5TyzqdOnYrHH38cQUFBSE1NxerVq7Fz5078/vvvcHd3x8svv4zJkyfD09MTOp0O48ePR9u2bQs8sx0R5a1xoAd+Gd8eX+66hLl/XcTui4noMXsXXutRG0Pb1YBS8ejvTzKMJny9+34XqXMYFOwiERERUQUhaUhKSEjASy+9hLi4OLi7u6NRo0b4/fff0b17dwDA7NmzIZfL0b9/fxgMBvTs2RMLFy6UsmSiCkOlkGNs5zA83sAPUzecwsHLd/HR5nP4+XgsPunfEI8FuD/0+qsPXsPddCOCvZzxZOOAMqqaiIiIqPQ53HmSShrPk0T0aBaLwI9HruPjLeeQqjdBIZdhZIeamNitFpxUilzb67PM6PDZDtxONeCz/o3wbEvOIklERESOr9ydJ4mIpCOXy/B8qyD8NTkCvRv6wWwRWBwVg15zdmFfdGKu7beejoPZIlDNQ4tnmlWToGIiIiKi0sNOEhHl8seZeLz782ncSrFOEf5si+p4t099KBUyKORyJKTq4emiRlyyHqHerhJXS0RERFQwBc0Gko5JIiLH1OMxP7QJ9cJnW8/juwPXcPRqErIsAl/tuYQV+64gJdMEnVaJYe1CMKZTKDR5HJJHREREVF6xk0RED3X4yl0Yssw4ePku5m2PzrX+1a61MCqiJpzV/M6FiIiIHBvHJBFRiWhZwxOtQrzwzf4rea5fvu8ylHK+lRAREVHFwU82RPRIqfospGSa8lyXkmlCqj6rjCsiIiIiKj0MSUT0SG5OKui0eR9Op9Mq4eakKuOKiIiIiEoPQxIRPZLZYsGwdiF5rhvWLgQmi6WMKyIiIiIqPRxpTUSPpFUrMaZTKADrGCTObkdEREQVGWe3I6ICyzCaoJTLkarPgpuTCiaLhbPaERERUbnB8yQRUYnLDkRerhoAgJpH7BIREVEFxE84REREREREOTAkERERERFR6TBmAGYjkH7b+q8xQ+qKCoSH2xERERERUckz6YG9c4CDSwB9EuDkAbQeBXSYDCidJC7u4RiSiIiIiIioZBkzrAEp6tN/l+mT/v05fCKgdpagsILh4XZERERERFQy9CnA9UOATG7tIOXl4BJA4di9GseujoiIiIiIHFNaAhB3Eog/cf/fk8DdS4BPfWDgGmvnKC/6JGuYcqlaltUWCkMSERERERHlTwgg6ao1CMWdsIahuJNAWnze28vkgKuPdQxSXkHJyQNwcuzzlzIkERERERGRldkEJP7zbxCKv3/RJ+exsQzwCgP8GwF+je7/2xhw8bKOSWo9yn5MUrbWo6z3o1CX+sMpKoYkIiIiIqLKKCsTuHUWiDv+byhKOGudle5BchXgU+/fIOTfGPB9DNC45n3bamfrLHYAZ7cjIiIiIiIHlHkPiD/1b3co7qS1YyTMubdVuwJ+DXN0hxoB3nUBZSE7P0on6yx2HadYxyA56QBzlsMHJIAhiYiIiIio4hACSI3PMXbo/r9J1/Le3rlqjsPl7neIqoQA8hKaBDt7mu/sSRoc+BC7nBiSiIiIiIjKI4sFuHfZfjKF+JNA+u28t/cI+jcMZXeJ3PwBmaxs6y4HGJKIiIiIiBydyQjcPv/AhAqnAWNq7m1lcqBq7RzdoUbWw+e0Vcq+7nKKIYmIiIiIyJEY060BKOfhcgnnALMx97YKjXUChZyHzPnU//cwNyoShiQiIiIiIqlk3LUGoZyHzN2JBiByb6txt3aEbN2hRtaOkYIf6Usan1EiIiIiotImBJB8w/5wubiTQMqNvLd39Xvg/EONgCo1OH6ojDAkERERERGVJIsZuBNzvzt04n4oOgVk3s17+yohObpD9/919SnbmskOQxIRERERUVGZDNYTsObsDt06DWRl5N5WrrSebyhnd8ivAeDkXvZ100MxJBERERERFYQ+xdoRynnI3O3zgMWUe1uVs3VChZwzzHnXA1SOfyJVYkgiIiIiIsotLeF+EDrxbyC6eynvbbVVcnSH7gcirzBArijbmqnEMCQRERERUeUlBHDvSu4JFdLi895eV+2B8w81Atyrc0KFCoYhiYiIiIgqB7MJSPzngROyngT0yXlsLLN2g+xmmGsMuHiVedlU9hiSiIiIiKjiycoEbp2xP/9QwlnApM+9rVwF+NS73x1qbA1Fvo8BGteyr5scAkMSEREREZVvmfesEyrkPFwu8QIgLLm3VbtaT8iac4Y577qAUl32dZPDYkgiIiIiovJBCCA1LkcYut8lSrqW9/bOVe3HDvk3tp6TSC4v27qp3GFIIiIiIiLHY7EA9y7bHy4XdwLISMx7e4+gf4NQdpfIzZ8TKlCRMCQRERERkbRMRuv5huwmVDgNGFNzbyuTA1XrPDChQkPrNNxEJYQhiYiIiIjKjjHdGoCyD5eLO2ENSGZj7m0VGusECjkPl/OpD6idy75uqlQYkoiIiIiodKTfsT8Za9xJ4E40AJF7W427tSOUcwxR1dqAgh9XqexxryMiIiKi4hECSL6R+4SsKTfy3t7V74HD5RoBVWpw/BA5DIYkIiIiIio4i9naDYo7ad8lyryX9/ZVQnJ0h+7/6+pTtjUTFRJDEhERERHlzWSwnoA1Z3fo1mkgKyP3tnKl9XxDObtDfg0AJ/eyr5uomBiSiIiIiAjQp1hPyJrzkLnb5wGLKfe2KmfAt4H9IXPe9QCVU9nXTVQKGJKIiIiIKpu0BPvD5eJOWM9JlBdtlRzdofuHy3mFAXJF2dZMVIYYkoiIiIgqKiGAe1dyT6iQFp/39rrquSdUcK/OCRWo0pE0JEVGRmLDhg04f/48tFot2rVrh08//RR16tSxbdOpUydERUXZXW/UqFFYvHhxWZdLREREVHaMGdbpr/XJ1nE9ZtPDzw9kNgGJ//wbhOJOWA+fMyTnsbHM2g2yC0SNARevUns4ROWJpCEpKioKY8eORcuWLWEymfD222+jR48eOHv2LFxcXGzbjRw5Eh988IHtZ2dnnkCMiIiIKjCTHtg7Bzi4BNAnAU4eQOtRQIfJgNIJyMoEbp25H4Tuh6KEs9brPUihBnzq/XsyVr9G1hO0alzL+EERlR+ShqStW7fa/bxixQr4+Pjg6NGj6Nixo225s7Mz/Pz8yro8IiIiorJnzLAGpKhP/12mT7L+LAQQ3A74rh8gLLmvq3a1npA15+Fy3nUBpbqsqieqEBxqTFJysrUd7Onpabd81apV+O677+Dn54e+ffvi3XffzbebZDAYYDAYbD+npKSUXsFEREREJU2htHaQ8nLoS6D9ROtkCpDlOP/Q/S5RlRBALi/LaokqJIcJSRaLBRMnTkR4eDgaNGhgWz5o0CAEBwcjICAAJ0+exJtvvokLFy5gw4YNed5OZGQkpk+fXlZlExEREZUsfbK1c5TnuiTAkAaMOQC4eHNCBaJSIhNCCKmLAIBXXnkFv/32G/bs2YPq1avnu9327dvRtWtXREdHIzQ0NNf6vDpJgYGBSE5Ohk6nK5XaiYiIiEqM2Qh8XivvoOTkAbx+0TrOiIgKLSUlBe7u7o/MBg7Rjx03bhx+/fVX7Nix46EBCQBat24NAIiOjs5zvUajgU6ns7sQERERlRtmk3WShry0HmVdT0SlStLD7YQQGD9+PDZu3IidO3ciJCTkkdc5fvw4AMDf37+UqyMiIiKSgNrZOosdkP/sdkRUqiQ93G7MmDFYvXo1fv75Z7tzI7m7u0Or1SImJgarV69G79694eXlhZMnT2LSpEmoXr16rnMn5aegLTUiIiIih2I7T1IK4KQDzFmA2uXR1yOifBU0G0gakmT5DDZcvnw5hg4diuvXr2Pw4ME4ffo00tPTERgYiGeeeQbvvPNOgQMPQxIREREREQEFzwaSH273MIGBgQXuGBEREREREZUEh5i4gYiIiIiIyFEwJBEREREREeXAkERERERERJQDQxIREREREVEODElEREREREQ5MCQRERERERHlwJBERERERESUA0MSERERERFRDgxJREREREREOTAkERERERER5cCQRERERERElANDEhERERERUQ4MSURERERERDkopS6gtAkhAAApKSkSV0JERERERFLKzgTZGSE/FT4kpaamAgACAwMlroSIiIiIiBxBamoq3N3d810vE4+KUeWcxWJBbGws3NzcIJPJJK0lJSUFgYGBuH79OnQ6naS1lEd8/hwDfw/Fw+dPevwdFA+fv7LF57t4+Pw5Bkf6PQghkJqaioCAAMjl+Y88qvCdJLlcjurVq0tdhh2dTif5DlKe8flzDPw9FA+fP+nxd1A8fP7KFp/v4uHz5xgc5ffwsA5SNk7cQERERERElANDEhERERERUQ4MSWVIo9Hg/fffh0ajkbqUconPn2Pg76F4+PxJj7+D4uHzV7b4fBcPnz/HUB5/DxV+4gYiIiIiIqLCYCeJiIiIiIgoB4YkIiIiIiKiHBiSiIiIiIiIcmBIIiIiIiIiyoEhiYiIiIiIKAeGpAqEExUWXUJCgtQlELgPF0dsbCwSExOlLoPA/bg4uB+XPe6vRcf9tWJjSKoA0tLSkJWVBZlMxje7Ivj777/h5+eHXbt2SV1KpXXv3j1kZmZyHy6iv//+G9WrV8ehQ4ekLqVS435cPNyPyxb31+Lh/uo4LBZLqdwuQ1I5d+7cOTzzzDP44YcfYDQa+WZXSCdOnEBERAQmTZqEjh07Sl1OpXTu3Dn06NEDn3/+OTIyMrgPF9KJEyfQsWNHTJo0Cb1795a6nEqL+3HxcD8uW9xfi4f7q2O4ffs20tLSIJfLSyUoKUv8FqnMXL16Ff3790dMTAzS0tLg5OSEJ598Emq1GkIIyGQyqUt0aKdPn0a7du0wefJkfPjhhxBCIDo6GrGxsahduzb8/f2lLrHCu3btGgYOHIj4+Hj8/vvv0Gq1GDt2LJydnbkPF8Dp06fRvn17jBs3DpGRkbBYLDh69Chu3ryJoKAgNGvWTOoSKwXux8XD/bhscX8tHu6vjuHcuXPo27cv2rdvj7lz58Ld3R0WiwVyecn1f9hJKqfMZjPWr1+PsLAwHDp0CB4eHpgxYwY2bdrEjlIBGAwGvPPOO8jMzMSHH34IAHjiiSfw3HPPoXPnzujbty8mTpwobZEVnBACv/32G/z8/LB582Y0atQIa9euxYIFC2zfbJZWC70isFgs+OSTT5Ceno63334bANCrVy+MGTMGAwYMwIsvvohnnnlG4iorPu7HxcP9uGxxfy0e7q+O4caNGxg2bBiUSiViYmIwdepUJCcnl3hHSSb4SbrcOn78OKKjozFgwABYLBb06dMHt27dwttvv42+fftCo9HwW6F8CCFw+PBhDBs2DK6urtDpdNBqtXj11Vfh5+eHdevWYePGjejXrx/ee+89qcutsOLi4nDgwAHbH5VXXnkFR48exX/+8x+MGTMGLi4u3IcfIjExEU8//TRu374Nb29veHp64r333oOnpyf27t2LTz75BG3atMHSpUulLrVC435cPNyPyxb31+Lh/iq97777DkuXLkVkZCSioqLw008/oWnTpoiMjIS7uzvMZjMUCkXx70hQuWU0Gu1+NhgMolevXqJp06Zi7dq1tvU//fSTFOU5LIvFYvv/sWPHRKNGjUSzZs3E9evXbcszMjLEiy++KLp27SoMBoMUZVYKZrPZ7uesrCwxevRo0bJlS/HZZ5+J9PR0IYQQy5cvl6A6x5VzH75z547o2LGjqF+/vrhy5YpteVZWlnj//fdFkyZNxO3bt6Uos9Lgflw03I+lwf21aLi/Og6z2Sw2bdpk+zkyMlK0adNGvPLKK+LevXu2bbKZTKYi3Q/HJJUjiYmJuH79OpydneHj44MqVarYjr80mUxQq9X46aef8PTTT2PGjBkwm83YsWMHNm3ahJYtWyIgIEDqhyCprKwsqFQqALB9S9akSRN8++23iIuLg5+fHwDroYxarRZ16tTBmTNneOhBCYqLi8OFCxegVCoRFhZme84BwGQyQalU4osvvsCECROwdu1aWCwWXLp0CUuXLkXnzp0RHBwsYfXSMxgM0Gg0AP7dhz09PbFx40YcOnTINo7OYrFAqVQiICAABoPBtt9TyeB+XDzcj8sW99fi4f7qeORyOfr27Wv7+fXXX4dMJsNPP/2Et99+29ZRmjt3Ll599dWid5WKHOOoTJ04cULUrl1bhIaGiurVq4vmzZuL/fv3222TlZUlhLB2lHr37i1UKpVwcXERR48elaJkh3L+/HkxaNAgu+ci+1shs9mc65s1IYQYNmyYGDp0qO15peI5ceKECA4OFmFhYSIgIED4+fmJdevW2XXqsp/r7G82NRqN0Ol04tixY1KV7TDOnj0r2rdvL3bs2CGEsO6/Ob/ZzMuYMWNE//79RWZmZhlUWDlwPy4e7sdli/tr8XB/dQzXrl0TGzduFD/++KO4ePGi3bqc++8nn3xi6yiNHDlSyGQy8c8//xT5fhmSyoG4uDgRFBQk3njjDXHhwgWxceNG8fzzzwuVSiW+//57u22zW4qvvPKK8PT0FKdPn5aiZIcSExMjAgMDhYeHh3jmmWfs3vjzerO7c+eOmDp1qvD29hZnzpwpy1IrrISEBFG7dm3x5ptvitjYWHHkyBExadIkoVAoxCeffCJSUlJs22bvw2PGjBFVqlThPiyEuHz5sggLCxNeXl6iWbNmYufOnUKIvPdfIYS4fv26ePPNN4WXl5c4depUWZZaoXE/Lh7ux2WL+2vxcH91DCdOnBB+fn6ifv36IigoSDg5OYnZs2eLmzdv2rbJDkomk0lERkYKrVYrPDw8xN9//12s+2ZIKgf+/vtv0aBBA3H58mXbsoyMDDFlyhShVqvFr7/+KoT49/jLBQsWCJlMxm+BhPV5Gjp0qBgwYIBYsGCB6Nq1q+jbt2++z83WrVvFkCFDRPXq1fn8laBLly6JOnXqiCNHjtgtnz17tpDJZGLevHlCiH/34WXLlnEfvk+v14tx48aJfv36ie+//148++yzolGjRvn+wd69e7cYOXKkCA4OLvYfCLLH/bjouB+XPe6vRcf91THcvXtXNG3aVLz55psiKSlJxMXFic8//1w4OzuLV199VcTExNi2zd6Px4wZI3Q6XYkEfYakcmDnzp1CJpOJS5cuCSH+3REsFosYO3as0Ol0du3ExMREux2nsluzZo348ssvhRBCrF+//qFBKS4uTnz99de255pKxvHjx4VarRaHDx8WQthPOhIZGSmUSmWuP+Q5vxSo7LZs2WLbh/fv3y/+85//2P3Bzunu3bti06ZN4urVq2VdZoXH/bh4uB+XLe6vxcP9VXoJCQmibt26YvPmzXbLV65cKapWrSreeOMNu8Ma161bJ9RqdYkFfYakcsBkMomOHTuK5557Tty5c0cI8W9QunHjhujYsaOYPn26sFgseY6tIXtr1661BaXsb3z0er2tdcvnsHQ8+eSTonXr1uLWrVtCCGt7PPv47ieeeEK89NJLwmg0cjbBAtizZ0+ubzb1ej0PkSkD3I9LDvfj0sf9teRwfy1bFotFxMTECF9fX7FhwwYhhPX5zpbd+dyyZYvd9W7cuFFiNfBksuWAQqHAc889hytXruCLL75ASkqK7YzC1apVg6urK86fPw+ZTFaiZxquaMxmMwBgwIABGDVqFDIyMvDee+/h8OHDmDRpElq0aAGDwcBzQ5SSUaNGQaVS4fXXX0diYiKUSqVtpiA/Pz8kJiZCpVJBrVZLXarDyp5pMTw8HBMmTEDdunUxYcIE/PXXX3j99dfRtWtXpKamSlxlxcb9uPi4H5cd7q/Fx/1VGjKZDDVr1sSTTz6J8ePHIy4uDhqNBllZWRBCYNiwYRgyZAg+/fRT6PV6ZGVlAbB+Li4pnALcwWW/mb3yyiuIifn/9u48rqo6/QP451wuuyAuiWsi44KIC7ikuOS+pm2j5r4OLqXp9LL8pUGmZW7NmFlZKuqMaPNKrRHXxqURKcUNFRwXNCI1QRYxQLjc+/z+IE4XlySP3nOQz/sf9VzAh8/zvctzz7nnJOHrr79GXl4eZs2aBW9vbwBAlSpVUKlSJVitVphMJr7Iv01xhk5OTuppwAcOHAhFUfDZZ5+hT58+sFqt2LVrl3qaT3r4+vTpg6SkJKxbtw6TJk3CRx99BF9fXwBFp/P08fFBQUEBnJ2duYZvU7yGTSaTuobbt28PAFi2bBl69eoFLy8v7Nq1C15eXjpX+3jjOn5wXMeOx/X64Lhe9VWc/7Rp03Du3DkMHjwYGzduRM2aNdVT19etWxcXL16Em5vbI6lBERF5JD+Z/jD7c/EXK75qcPH1kObOnYtt27YhKysLAwYMQEpKCqKjo/H999+jSZMmOlVuDL+X340bN1CxYkUAv93xAKBbt244duwYDhw4gKCgIIfXXB4U9+DWrVtwc3PDP/7xD6xcuRIJCQno27cvbty4gb179yI2NhZNmzbVu1zDKc4vIyMDlStXBlByDffv3x8xMTGIiYkp948BjxLXsTZcx47F9aoN16uxbN26FfPnz8etW7fw5Zdfwt/fHwAwZcoUXLx4EV9++SXc3Nwe+qDPY7MM4uzZswgPD0dhYaG6rfhOmpycjKZNm2L//v146623sGDBAvTs2ROnTp2Cq6srvvvuu3J/J71ffp06dUJ0dDSAol24hYWFeP3113HgwAHs37+fA9JDUFBQgNzc3BLbCgsL1R7UrVsXmzdvxogRIxAZGYlp06YBAPz8/HDo0KFy/0R9v/yCgoKwfv16AEVr2Gq1Yv78+di7dy/27dtX7h8DHiWLxcJ1rIF9flzHj15BQQHXqwb2+XG96qf4IxLZ2dno378/Fi5cCF9fXwQFBaFnz57o2bMn1q5di/feew/u7u6PZE8o9yQZwMmTJ/HUU08hPz8f27dvR+/evdXbkpOT0b59ezzzzDP46KOPYDb/doSkFJ14o9x/Dqm0+X3yyScl7kRffPEFAgIC0Lx5cz3KfqycOXMG8+bNw4ULFxASEoLJkyerT74pKSlo27YtBgwYgGXLlpVYw1SktPl9/PHHJdbwzp07UbduXTRu3Fiv0h8rFy5cwJYtW3D9+nUEBQWhT58+qFq1KgDghx9+QPv27bmOf0dp8+M6fjjOnTuHyMhIpKamIjg4GL1790b9+vUBcL2WRmnz43p1PPs3uf39/fHpp5/iL3/5CwoKCrB27VpcuHAB7u7uGDJkCBo1avTI6uCQpLP4+Hi0a9cOY8aMwfXr1+Hq6ooVK1bA1dUVJpMJY8eOhbOzMz799FP1Tmq/y7e8Y376S0hIQKdOnfDss8/Cz88Pn3zyCYYMGYIPPvgAADBr1iz88ssv+Pvf/84e3MWD5EcP3+nTp9G5c2e0adMG7u7uiI6ORocOHfDqq69iwIABeOedd5Cens51fA8Pkh89uMTERISGhqJt27bw8PDAf/7zH7Rr1w6DBg3CuHHjMHfuXKSlpWHp0qVcr3fxIPnRw5eWlgZnZ2f4+PjccduVK1fQsmVLPP/881i2bBmcnJwcX+BDO08e/WFHjx4VLy8vmTVrloiILFmyRHx8fEpco8f+ugZUEvPTX3Z2tnTr1k1mzJihbvv0009l1KhRcvPmzRJfe6+rlJdnzM8YMjMzJTQ0VN58801126lTp8TJyUlatmwpW7Zs0a+4MoD5OVZ+fr4MGzZMwsLC1G3/+9//ZNCgQdK2bVtZs2aNjtUZH/MzhoSEBHF1dZXBgwdLdna2ur34ue6jjz6S2bNnl3juc/TzYPk+TktHWVlZ6NChA8LCwjBv3jwAwMsvvwx/f3/MnTtXPZTO2dlZ50qNifkZR3Z2NgICAtR/nzp1CsePH0eLFi3w4osvYsWKFQDAd+Pugfnpz2KxIC8vDz179oTNZkNubi4CAgIQGhoKq9WKZcuWITExUe8yDYv5OZaLiwt+/vln9VB7EUGjRo2wYMECNGrUCCtXrsS2bdt0rtK4mJ/+fv75Z4wfPx6hoaH45ptvEBYWpp5Gvfi5btKkSZg7d26J5z5HPw9ySNKJj48PYmNjsXjxYgBFd1Kz2YyePXviyJEjSE9Ph6IoEB4NeVfMzxhyc3ORmZmJ2NhYbN++HREREYiMjMT48eMxZ84cuLu7IyoqCidOnNC7VENifsZw8+ZNnDlzBqmpqTCZTPDw8MDly5dRUFCAGTNm4NixY9i0aZPeZRoW83McEYHFYkHt2rWRkZGB/Px8iAhsNhv8/Pwwe/ZsWCwWREVF6V2qITE//YkIjh8/jnr16mHhwoWIjo7Gzp07SwxKctvn7XV7LefQ/VZ0h+Jdh8V/XrlyRTw9PeW9997Ts6wyg/npb/v27VK/fn157rnnxNfXV6KiotTbkpKSxMPDQ1atWqVjhcbG/Ixh+vTp4urqKhEREfLhhx9KxYoVZcKECSIismjRImnfvr3k5OTwsMd7YH6OtWfPHjGZTLJ8+XIRKXoOLCwsLHFbYmKiniUaGvPT17Vr12Tv3r3qv2NiYsTHx0deeukluXHjhrpd78cLnu7EgVJSUnDmzBmkpaWhR48e8PHxgYuLi3oWD6vViho1aiAsLAzbtm3D8OHDUadOHb3LNgzmpz/7HnTv3h3e3t7o06cPDh48CFdXV3Tv3h1169YFUHSV8qpVqyI4OFi9RlV5x/yM4fbHksqVK+Odd96Bt7c31q1bB19fX/z1r39FeHg4ACAjIwMA4OHhoWfZhsH8HCs3NxfOzs5wdnZWDyXv2rUr5s+fjylTpsDd3R1jxoxRP9hesWJFNGrUiHn/ivkZT7Vq1VCtWjUARc917du3x7Zt29CvXz9MmDABn332Gdzc3LBq1So0aNAA3bp106dQXUe0ciQ+Pl58fX0lJCREXFxcpEmTJjJjxgzJzMwUEVHfwRAR2bFjh3h5ecnWrVt1qtZ4mJ/+7taD1157TdLT00WkaC+ev7+/REZGikjRSTMiIiKkTp06kpycrGPlxsD8jOH2PjRu3FjeeOMN9bEkLS1N/XuxsLAwGT9+vBQUFOj+zqbemJ9jJSQkSNeuXWXr1q1isVhE5Ld313NzcyU8PFwURZGIiAg5ceKEZGZmysyZM6VBgwaSmpqqZ+mGwPyMIScnp1Qn0oqNjRUfHx8ZMmSIjB07VlxcXOTChQsOqPDuOCQ5QFZWloSEhKgviPLy8uT//u//JDQ0VJ599ln1RZL9C/2ePXvK008/LVartdw/qTA//d2vB2lpaSIi8u6774qiKPLUU09J586dpVatWnLs2DGdq9cf8zOGe/WhXbt2MmDAALl+/bqI/PYi6vz58/L666+Lt7e3nD59Ws/SDYH5OdYPP/wgAQEB4uTkJH5+frJ79271hb691atXi6+vr9SqVUsaN24sNWvW5OOGMD+juNug+nu+/fZbURRFKleuLEePHnVAhffGIckBLl26JP7+/rJ//351W35+vqxevVratWsnw4YNU09/aLVaRURk06ZNuk7PRsL89He/HgwdOlTtwZdffikTJ06UBQsWyPnz5/Uq2VCYnzH8Xh/atm1bog/p6ekye/ZsadWqFV8w/Yr5OY7FYpG//e1v8txzz0lycrL07t1bqlevfs8X+klJSbJ//37ZsWOHpKSk6FCxsTA/YyjtoFosPz9fJk6cKF5eXpKQkODASu+OQ5IDpKWlSVBQkCxbtkxEfnuXzWq1yvLlyyUkJETWrVsnIiX3hlAR5qe/+/UgODhY7QHdifkZwx95LBERuXz5sly7dk2XWo2I+TmOzWaTmJgY2bRpk7qtV69eUqNGDdm9e7d66JLNZuPREnfB/PT3RwdVEZFDhw5JkyZN5PDhww6u9u4UEZ4j+VGzWCwYMmQIrl69iqioKPWD2cV69eoFZ2dnREdH61ShsTE//ZWmB2azmdeWuAfmZwx8LNGG+TmWzWYrcRpkAOjduzfi4+Oxbt06dO3aFU5OToiOjkaXLl3g6empU6XGxPz0JSKIjY3FtWvX8MILLwAoyv/kyZNYu3YtOnfufMe1LLOysmCz2VC5cmU9Sr4Dr5P0iMmvFzT9+OOPkZSUhKlTpyI1NbXEOd/79++P69ev49atWzpWakzMT3+l7UF6ejp7cBfMzxj4WKIN83M8+xf4hYWFAICdO3eiRYsWGDVqFHbv3o0JEyZg+vTpyM7O1qtMw2J++lIUBe3atVMHJKAo/2bNmmHkyJHYv38/rFYrACA6Ohq//PILfHx8DDMgARySHjlFUVBQUIBq1aph586dOHToEIYPH44jR46oi+PEiROoUqXKHe94EPMzAvZAG+ZnDOyDNszP8ewHULPZDIvFAgDYsWMHWrRogX79+mH9+vXYuHEjatSooVeZhsX89PdHBtXiC8kaCQ+3e8SKr+GTnp6OgoIC5OXloU+fPqhQoQIKCwvh7++PPXv2ICYmBs2aNdO7XMNhfvpjD7RhfsbAPmjD/ByrOO/MzExcv34dDRo0AFD0QtNsNmP69OlYt24dDhw4gMDAQJ2rNR7mZwwiAkVR1H9bLBb1ELu+ffti586d8PDwwLfffouWLVvqVeY98e2eR0REUFhYCCcnJ/zwww9o1qwZ9uzZA39/f8TFxWHatGno0aMHWrdujbi4OD6p3Ib56Y890Ib5GQP7oA3zcyz7vJOTkxEUFISjR4+qt5vNZqxcuRJLly7F7t27+QL/NszPOKxWKxRFQWZmJs6fPw8AcHZ2VvcoNWrUCJUqVcLhw4cNOSAB3JP0UFy4cAH/+te/cPbsWXTs2BHdu3eHn58fAOCnn35C06ZNMXDgQKxYsQIiwkMRbsP89MceaMP8jIF90Ib5OdYfydv+3fgLFy7AbDarX1teMT9jEhFYrVaYzWYkJycjNDQUS5YswUsvvaR+zcqVKxEWFoa4uDjDDkgAhyTNTp8+ja5du6JLly5ISUlBYWEhWrZsiUWLFsHT0xNff/01YmJisGjRohJ3UirC/PTHHmjD/IyBfdCG+TkW89aG+RnDYz+oPsLTiz/2fvzxRwkMDJSZM2eq25YvXy7+/v5y+fJlERH1XPx0J+anP/ZAG+ZnDOyDNszPsZi3NszPGE6dOiVPPPGEDBo0SNq1ayetW7eWiRMnys2bN8Vms8mWLVvktddeK9PXoeK+8gckIti3bx8aNmyIiRMnwmazAQDGjRsHAEhISACAO84BT0WYn/7YA22YnzGwD9owP8di3towP2NISUnB4MGDMW7cOHzxxReIjY3F6NGjsXv3bmRnZ0NRFPTr1w+LFy8u03vyOCQ9IEVRULVqVfTu3Rt169aFyWSCiMBisSA/Px83bty443uERzaqmJ/+2ANtmJ8xsA/aMD/HYt7aMD/9ladB1ax3AWVR8akl+/btq26TX09zWKFCBVSvXh0uLi7qbevWrUPbtm3RsGFDPco1HOanP/ZAG+ZnDOyDNszPsZi3NszPGG4fVAGUalAti3uUuCfpD8jKygIAODk5qacwLGbf/OJ3NgBg1qxZeOWVV8rk4njYmJ/+2ANtmJ8xsA/aMD/HYt7aMD/jKL5wdN++fTFhwgQA9x9Uz507V2b7wCGplM6cOYOQkBCEh4cDKDrXfvEuRnu3bt1Ceno6RAQLFizABx98gH379qkXMiuvmJ/+2ANtmJ8xsA/aMD/HYt7aMD9jKLeD6kM9DcRj6scff5QWLVpIgwYNJCgoSObMmaPeZrVaS3yt1WqVDh06SJMmTcTDw0Pi4uIcXa7hMD/9sQfaMD9jYB+0YX6Oxby1YX7GkJiYKPXq1ZO33npL3XZ7/iIieXl54u/vL1u2bJH3339f3Nzc5MiRI44s9aHjZ5LuQ0SwYcMG1KxZE9OmTcPBgwexYcMGAEB4eDhMJpN6nCwA2Gw22Gw2XLlyBd999125v/o489Mfe6AN8zMG9kEb5udYzFsb5mcMKSkpGDp0KMxmM7Zs2QKz2azmb7PZSlxQ2sXFBTVr1sTs2bNx6dIlHDhwwNAXii0NDkn3oSgKRo4cCV9fX/To0QPNmzcHAGzYsAEigoiICDg5OamLxWw2Y/z48ejYsSPq16+vc/X6Y376Yw+0YX7GwD5ow/wci3lrw/z0x0EVPNzuQVy5ckUiIiIkICBA3n77bXX7pk2bdKyq7GB++mMPtGF+xsA+aMP8HIt5a8P8HO/q1auyZs0aERG5du3aXfO3P/Ru9erVcv78eYfX+ahwT9JdXL16FSkpKcjMzET37t1LTMmKoqBGjRoICwsDAGzcuBEighs3bmDp0qX46aefULNmTT3L1x3z0x97oA3zMwb2QRvm51jMWxvmZzzVq1fHqFGjAADVqlVTz2i3ceNGAEBERARMJhM2b96MF154AWPGjNGt1kdCv/nMmOLj46Vu3brSsGFDqVixogQEBEhUVJSkp6eLSNHEbLPZRKToXY3w8HBRFEUqVapU5j+g9jAwP/2xB9owP2NgH7Rhfo7FvLVhfsZw5coVOXTokOzcuVMKCwvV7fb5X758Wd2jFBERIdOmTRNFUeTy5ct6lf3IcEiyk5qaKgEBAfLmm29KUlKSXL58WQYPHiyNGzeWiIgISU1NFRFRF4qIyIgRI8Tb21sSEhL0KtswmJ/+2ANtmJ8xsA/aMD/HYt7aMD9j4KB6Jw5JdhISEsTPz++OZr/xxhvStGlTWbhwoeTk5KjbV65cKT4+PnLs2DFHl2pIzE9/7IE2zM8Y2AdtmJ9jMW9tmJ/+OKjeHYckOydOnJDatWvLf//7XxERyc3NVW+bOnWq1KtXT+Lj49VtP//8s1y8eNHhdRoV89Mfe6AN8zMG9kEb5udYzFsb5qc/Dqp3p4j8emlcAgC0adMGFSpUwN69ewEA+fn5cHV1BQC0bt0a9evXx4YNG0qc9pB+w/z0xx5ow/yMgX3Qhvk5FvPWhvnpKz4+Hs888wyioqLQsWNH5OXlwd3dHQDw6quvYuvWrfjqq6/U03pfu3YNubm5qFevnp5lP3Km+3/J4ysnJwc3b95Edna2um3FihVISEjA0KFDAQCurq4oLCwEAHTq1Ak5OTkAwDspmJ8RsAfaMD9jYB+0YX6Oxby1YX7G07x5c9SoUQMREREAAHd3d+Tn5wMAli5diipVqmD+/PkAAKvVCl9f38d+QALK8ZCUmJiIF154AU8//TQaN26M9evXAwAaN26MpUuX4ptvvsHAgQNhsVjUKwqnpqbC09MThYWFKO874Jif/tgDbZifMbAP2jA/x2Le2jA/Y+CgWjrl8jpJiYmJ6NSpE0aOHIlWrVrh6NGjGDNmDAIDAxEcHIwBAwbA09MTkydPRrNmzRAQEAAXFxds27YN33//Pczmchmbivnpjz3QhvkZA/ugDfNzLOatDfMzhsTEREyfPh1paWm4du0aFi5ciGHDhqmD6pQpUzBw4EBERUWpA5H9oOrk5ARFUXT+LRyj3H0mKSMjA0OGDEFAQACWLl2qbu/SpQuaNm2KDz/8UN128+ZNzJs3DxkZGXBzc8OkSZMQGBioR9mGwfz0xx5ow/yMgX3Qhvk5FvPWhvkZw90G1WXLluHQoUMIDg5Gbm4u9uzZg8mTJ6NChQp3DKpBQUF6/woOVe7GcovFgqysLPz5z38GUHQlZ5PJhHr16iEjIwMAIEVn/YOXlxcWLFhQ4uvKO+anP/ZAG+ZnDOyDNszPsZi3NsxPfxkZGZg+fTqGDRuGDz74AAAwdOhQHDt2DJGRkQgODoaHhwf69++Pzp07lxhUDx8+XC4H1XI3JPn6+uKf//wnGjRoAKDoA2gmkwm1atVCcnIyAEBRFCiKguzsbHh7e6vbiPkZAXugDfMzBvZBG+bnWMxbG+anPw6qf1y5/K2L76Q2mw3Ozs4AihZGamqq+jXz58/HypUr1Q+t8Y76G+anP/ZAG+ZnDOyDNszPsZi3NsxPX8WDaseOHQEUDaoAUKtWLXUIUhQFJpOpxAkdynMPyt2eJHsmkwkioi6A4kUSHh6OefPm4fjx4/yg4O9gfvpjD7RhfsbAPmjD/ByLeWvD/PRT2kHV1dUVU6dOhdls5pBUnhXfUc1mM+rUqYPFixdj4cKFOHLkCJo3b653eYbH/PTHHmjD/IyBfdCG+TkW89aG+emLg2rplPsEiheGs7MzPv/8c3h7eyMmJgYhISE6V1Y2MD/9sQfaMD9jYB+0YX6Oxby1YX7646B6f+XyM0l306tXLwBAbGwsWrVqpXM1ZQ/z0x97oA3zMwb2QRvm51jMWxvmp5/bB9V58+ZxUL1NubtO0u/JycmBp6en3mWUWcxPf+yBNszPGNgHbZifYzFvbZifvo4cOYI2bdrg9OnT5fI037+HQxIRERERUTnFQfXuOCQRERERERHZ4WeSiIiIiIiI7HBIIiIiIiIissMhiYiIiIiIyA6HJCIiIiIiIjsckoiIiIiIiOxwSCIiIvodiqLgq6++0rsMIiJyIA5JRERkSKNHj4aiKJg4ceIdt7388stQFAWjR49+aP/f22+/jRYtWjy0n0dERGUXhyQiIjKsOnXqYOPGjcjLy1O33bp1C1FRUXjyySd1rIyIiB5nHJKIiMiwQkJCUKdOHWzevFndtnnzZjz55JMIDg5Wt+Xn52Pq1KmoVq0a3Nzc0KFDB8TFxam379+/H4qiYM+ePWjVqhU8PDwQGhqKs2fPAgDWrFmDOXPmID4+HoqiQFEUrFmzRv3+69ev4/nnn4eHhwcaNGiAf//734/+lyciIt1wSCIiIkMbO3YsIiMj1X+vXr0aY8aMKfE1r7/+OjZt2oS1a9fi2LFjqF+/Pnr16oWMjIwSXzdr1iwsWbIER44cgdlsxtixYwEAgwcPxmuvvYYmTZrg6tWruHr1KgYPHqx+35w5czBo0CCcPHkSffv2xbBhw+742URE9PjgkERERIY2fPhwxMTEIDk5GcnJyTh48CCGDx+u3p6Tk4NPPvkEixYtQp8+fRAYGIjPP/8c7u7uWLVqVYmf9e677+Lpp59GYGAgZs6cidjYWNy6dQvu7u6oUKECzGYzqlevjurVq8Pd3V39vtGjR2PIkCGoX78+3nvvPfzyyy84fPiwwzIgIiLHMutdABER0e954okn0K9fP6xZswYign79+qFq1arq7UlJSbBYLGjfvr26zdnZGW3atMGZM2dK/KxmzZqpf69RowYAIDU19b6fb7L/Pk9PT3h7eyM1NVXT70VERMbFIYmIiAxv7NixeOWVVwAAy5cvf+Cf4+zsrP5dURQAgM1m+0PfV/y9pfk+IiIqm3i4HRERGV7v3r1RUFAAi8WCXr16lbjtT3/6E1xcXHDw4EF1m8ViQVxcHAIDA0v9f7i4uMBqtT60momIqOziniQiIjI8Jycn9dA5JyenErd5enpi0qRJmDFjBipXrownn3wSCxcuRG5uLsaNG1fq/8PPzw+XLl3CiRMnULt2bXh5ecHV1fWh/h5ERFQ2cEgiIqIywdvb+563vf/++7DZbBgxYgRu3ryJVq1aYdeuXahUqVKpf/6LL76IzZs3o0uXLsjKykJkZORDvVgtERGVHYqIiN5FEBERERERGQU/k0RERERERGSHQxIREREREZEdDklERERERER2OCQRERERERHZ4ZBERERERERkh0MSERERERGRHQ5JREREREREdjgkERERERER2eGQREREREREZIdDEhERERERkR0OSURERERERHY4JBEREREREdn5f6LiVo20poSLAAAAAElFTkSuQmCC","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Check data types\n","print(patient_counts.dtypes)\n","\n","# Convert 'Month' to datetime if necessary\n","if pd.api.types.is_period_dtype(patient_counts['Month']):\n"," patient_counts['Month'] = patient_counts['Month'].dt.to_timestamp()\n","elif not pd.api.types.is_datetime64_any_dtype(patient_counts['Month']):\n"," patient_counts['Month'] = pd.to_datetime(patient_counts['Month'], format='%Y-%m')\n","\n","# Ensure 'ID' is numeric\n","patient_counts['ID'] = pd.to_numeric(patient_counts['ID'], errors='coerce')\n","\n","# Drop any rows with NaN values that may have been introduced\n","patient_counts.dropna(inplace=True)\n","\n","# Plot the number of patients per medication each month\n","plt.figure(figsize=(10, 6))\n","sns.lineplot(x='Month', y='ID', hue='Med', data=patient_counts, marker='o')\n","plt.title('Patient Counts on Each Medication (July to November)')\n","plt.xticks(rotation=45)\n","plt.show()"]},{"cell_type":"markdown","metadata":{},"source":["3. Average Monthly Dose per Patient: What is the average total monthly dose per patient for each medication from July to November?"]},{"cell_type":"code","execution_count":21,"id":"966b4a54","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["ID int64\n","Med object\n","Admin Date datetime64[ns]\n","Units float64\n","Month datetime64[ns]\n","dtype: object\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA90AAAJOCAYAAACqS2TfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAADbo0lEQVR4nOzdd3hUZdrH8e9MOqmE9EJPgEDoCU16EUWwIaCriL2u3d113RVdd1/b2nvXRaQJNhCULgiS0EuAFAKkkUIgBUhIOe8fQwKBgBASTsrvc11zzZkzz5xzT5gZ5p77KRbDMAxEREREREREpNZZzQ5AREREREREpLFS0i0iIiIiIiJSR5R0i4iIiIiIiNQRJd0iIiIiIiIidURJt4iIiIiIiEgdUdItIiIiIiIiUkeUdIuIiIiIiIjUESXdIiIiIiIiInVESbeIiIiIiIhIHVHSLSLSxD377LNYLBZycnL+sG3r1q2ZMmVK3Qcl9YrFYuHZZ581O4wzFBYW4ufnx/Tp02vleHv37sVisfDFF1/UyvHk4k2ZMgU3N7dLcq6SkhJCQ0N57733Lsn5RKTpUNItIhftvffew2Kx0KdPH7NDqXdat26NxWJhxIgR1d7/8ccfY7FYsFgsrF+/vk5j+b//+z++++67Oj3HhahIcCouDg4O+Pj40L9/f/7+97+zf/9+s0Os9079+1mtVoKCghg1ahQrVqy44GP99NNPpibWX3/9NW+88cYFPebNN9/E3d2dSZMmVe67kB+R6tqaNWt49tlnOXz4cK0et+I5+vv7c/To0TPub926NVdddVWtnrMpcHBw4LHHHuM///kPRUVFZocjIo2Ikm4RuWjTp0+ndevWxMTEkJiYaHY49Y6zszPLly/nwIEDZ9w3ffp0nJ2dL0kc9S3prnDjjTcybdo0Pv30U/75z3/Stm1b3njjDTp16sTMmTPNDq/eGzlyJNOmTePLL7/k3nvvZevWrQwbNoyFCxde0HF++uknnnvuuWrvO3bsGP/4xz9qI9yzutCku6SkhDfffJM777wTOzu7ugvsIqxZs4bnnnuu1pPuCllZWbz//vt1cuym6rbbbiMnJ4evv/7a7FBEpBFR0i0iFyU5OZk1a9bw2muv4evrW2vdPC9EeXl5va5KDBgwADc3N2bNmlVlf2pqKqtWrWLMmDEmRVY/9OzZk5tvvpnJkyfz8MMP89VXX7Fz505CQkK49dZb2bJli9khmqaoqIjy8vJztgkPD+fmm2/mlltu4ZlnnmHx4sUYhnHBVeNzcXZ2xt7evtaOVxvmz59PdnY2EyZMMDsU03Tv3p1XXnmFY8eOmR1Kg2YYRuXf0MvLi1GjRmmIgYjUKiXdInJRpk+fTvPmzRkzZgzjx4+vknSXlJTg7e3Nbbfddsbj8vPzcXZ25oknnqjcV1xczNSpU2nfvj1OTk6Ehobyl7/8heLi4iqPtVgsPPjgg0yfPp3OnTvj5OTEokWLAPjvf/9L//79adGiBS4uLvTq1YtvvvnmjPMfO3aMhx56CB8fH9zd3Rk3bhxpaWnVjl1NS0vj9ttvx9/fHycnJzp37sxnn3123n8jZ2dnrrvuujMqJzNmzKB58+Zcfvnl1T5u2bJlDBw4EFdXV7y8vLj66qvZuXNnlTYV3UwTExOZMmUKXl5eeHp6ctttt1XpdmqxWDhy5AhffvllZXfk08dmHz58+JzHON2ePXuwWCy8/vrrZ9y3Zs0aLBYLM2bM+KM/T7VatWrFF198wfHjx3n55ZfPOO8NN9yAt7c3zZo1o2/fvixYsOCMY7z99tt07tyZZs2a0bx5c3r37n3Gv8HF/Nue+jrs0KEDzs7O9OrVi19//fWMtudznhUrVmCxWJg5cyb/+Mc/CA4OplmzZuTn559XPBUiIyPx8fEhOTkZgFWrVnHDDTfQsmXLyvfVo48+WiVRmzJlCu+++27l86q4nPpca/K+qHhOs2fP5j//+Q8hISE4OzszfPjwKr1ihgwZwoIFC9i3b1/luVu3bn3O5/ndd9/RunVr2rVr94d/k7PNRTBkyBCGDBly1sd9/vnnWCwWNm3adMZ9//d//4ednR1paWnVPvbZZ5/lySefBKBNmzaVz2vv3r0AlJaW8vzzz9OuXTucnJxo3bo1f//738/4vDuXZ555hszMzPOqdh85coTHH3+c0NBQnJyc6NChA//9738xDKOyTZcuXRg6dOgZjy0vLyc4OJjx48dX2ffGG2/QuXNnnJ2d8ff355577uHQoUNVHlvR1X3FihX07t0bFxcXIiMjK4dAzJs3j8jIyMr3T3V/a7C97y+//HJcXV0JCgriX//6V5XYaxLTzz//XBnThx9+WHn/yJEjWb16Nbm5uX/4dxUROR/162drEWlwpk+fznXXXYejoyM33ngj77//PrGxsURFReHg4MC1117LvHnz+PDDD3F0dKx83HfffUdxcXHlWMzy8nLGjRvH6tWrufvuu+nUqRPbtm3j9ddfJz4+/oxu0cuWLWP27Nk8+OCD+Pj4VH5Bf/PNNxk3bhx/+tOfOH78ODNnzuSGG25g/vz5VSrKU6ZMYfbs2dxyyy307duXlStXVltxzszMpG/fvpUJlq+vLwsXLuSOO+4gPz+fRx555Lz+TjfddBOjRo0iKSmpMkn4+uuvGT9+PA4ODme0X7JkCVdccQVt27bl2Wef5dixY7z99tsMGDCAjRs3npGQTJgwgTZt2vDCCy+wceNGPvnkE/z8/HjppZcAmDZtGnfeeSfR0dHcfffdAGckK390jNO1bduWAQMGMH36dB599NEq902fPh13d3euvvrq8/r7VKdfv360a9eOxYsXV+7LzMykf//+HD16lIceeogWLVrw5ZdfMm7cOL755huuvfZawDZW/qGHHmL8+PE8/PDDFBUVsXXrVtatW8dNN91UeayL/bdduXIls2bN4qGHHsLJyYn33nuP0aNHExMTQ5cuXWp0nueffx5HR0eeeOIJiouLq7xvzsehQ4c4dOgQ7du3B2DOnDkcPXqU++67jxYtWhATE8Pbb79Namoqc+bMAeCee+4hPT2dxYsXM23atD88x4U+pxdffBGr1coTTzxBXl4eL7/8Mn/6059Yt24dAE8//TR5eXmkpqZW/ojzR5NnrVmzhp49e17Q3+ZCjR8/ngceeIDp06fTo0ePKvdNnz6dIUOGEBwcXO1jr7vuOuLj45kxYwavv/46Pj4+APj6+gJw55138uWXXzJ+/Hgef/xx1q1bxwsvvMDOnTv59ttvzyu+gQMHMmzYMF5++WXuu+8+XFxcqm1nGAbjxo1j+fLl3HHHHXTv3p2ff/6ZJ598krS0tMq/+cSJE3n22Wc5cOAAAQEBlY9fvXo16enpVcbO33PPPXzxxRfcdtttPPTQQyQnJ/POO++wadMmfvvttyqfa4mJidx0003cc8893Hzzzfz3v/9l7NixfPDBB/z973/n/vvvB+CFF15gwoQJ7N69G6v1ZF2orKyM0aNH07dvX15++WUWLVrE1KlTKS0t5V//+leNYtq9ezc33ngj99xzD3fddRcdOnSovK9Xr14YhsGaNWs0Nl5EaochIlJD69evNwBj8eLFhmEYRnl5uRESEmI8/PDDlW1+/vlnAzB+/PHHKo+98sorjbZt21benjZtmmG1Wo1Vq1ZVaffBBx8YgPHbb79V7gMMq9Vq7Nix44yYjh49WuX28ePHjS5duhjDhg2r3LdhwwYDMB555JEqbadMmWIAxtSpUyv33XHHHUZgYKCRk5NTpe2kSZMMT0/PM853ulatWhljxowxSktLjYCAAOP55583DMMw4uLiDMBYuXKl8fnnnxuAERsbW/m47t27G35+fsbBgwcr923ZssWwWq3G5MmTK/dNnTrVAIzbb7+9ynmvvfZao0WLFlX2ubq6GrfeeusZMV7IMVq1alXlGB9++KEBGDt37qzcd/z4ccPHx6fac50qOTnZAIxXXnnlrG2uvvpqAzDy8vIMwzCMRx55xACqvE4KCgqMNm3aGK1btzbKysoqH9e5c+dznv9i/20BAzDWr19fuW/fvn2Gs7Ozce21117weZYvX24ARtu2bf/w3KfGcMcddxjZ2dlGVlaWsW7dOmP48OEGYLz66quGYZz5njAMw3jhhRcMi8Vi7Nu3r3LfAw88YJzta0FN3xcVz6lTp05GcXFxZbs333zTAIxt27ZV7hszZozRqlWr83reJSUlhsViMR5//PEz7qt4PWdnZ1fuO/11W2Hw4MHG4MGDK29XvCY///zzyn033nijERQUVPnaMgzD2Lhx4xntqvPKK68YgJGcnFxl/+bNmw3AuPPOO6vsf+KJJwzAWLZs2TmPe+pzXLlypQEYr732WpXnO2bMmMrb3333nQEY//73v6scZ/z48YbFYjESExMNwzCM3bt3G4Dx9ttvV2l3//33G25ubpX/rqtWrTIAY/r06VXaLVq06Iz9rVq1MgBjzZo1lfsq/l9wcXGp8hqs+DxZvnx55b5bb73VAIw///nPlfvKy8uNMWPGGI6OjpX/zjWJadGiRdX9eY309HQDMF566aVq7xcRuVDqXi4iNTZ9+nT8/f0ruyNaLBYmTpzIzJkzKSsrA2DYsGH4+PhUGc986NAhFi9ezMSJEyv3zZkzh06dOtGxY0dycnIqL8OGDQNg+fLlVc49ePBgIiIizojp1ErPoUOHyMvLY+DAgWzcuLFyf0VX9IrqSoU///nPVW4bhsHcuXMZO3YshmFUievyyy8nLy+vynHPxc7OjgkTJlR2t54+fTqhoaEMHDjwjLYZGRls3ryZKVOm4O3tXbm/a9eujBw5kp9++umMx9x7771Vbg8cOJCDBw9eUNfkmhxjwoQJODs7VxlW8PPPP5OTk8PNN9983uc+m4pqZ0FBAWCb7Cs6OprLLrusSpu7776bvXv3EhcXB9jGZaamphIbG1vtcWvr37Zfv3706tWr8nbLli25+uqr+fnnnykrK6vReW699dazViyr8+mnn+Lr64ufnx99+vTht99+47HHHqusNp96rCNHjpCTk0P//v0xDOOsXXnPpSbP6bbbbqtSsa943e/Zs+eCzw+Qm5uLYRg0b968Ro+/EJMnTyY9Pb3KZ9D06dNxcXHh+uuvr9ExK97Djz32WJX9jz/+OEC1wyXOZtCgQQwdOpSXX375rGO7f/rpJ+zs7HjooYfOOJ9hGJWT7oWHh9O9e/cqn9dlZWV88803jB07tvK1NGfOHDw9PRk5cmSVf/9evXrh5uZ2xud1REQE/fr1q7xdsdLFsGHDaNmy5Rn7q3tdPPjgg5XbFT0sjh8/zpIlS2oUU5s2bc46tKfidVUfZsAXkcZBSbeI1EhZWRkzZ85k6NChJCcnk5iYSGJiIn369CEzM5OlS5cCYG9vz/XXX8/3339fOVZx3rx5lJSUVEm6ExIS2LFjB76+vlUu4eHhgG2W3lO1adOm2rjmz59P3759cXZ2xtvbG19fX95//33y8vIq2+zbtw+r1XrGMSq641bIzs7m8OHDfPTRR2fEVTFO/fS4zuWmm24iLi6OLVu28PXXXzNp0qQq42ZPjQ+o0t2xQqdOncjJyeHIkSNV9p/6xRVOfmk8fSzjudTkGF5eXowdO7bKWOnp06cTHBxc+YPJxSgsLATA3d0dsP1tzvZ3qbgf4K9//Stubm5ER0cTFhbGAw88wG+//VbZvrb+bcPCws7YFx4eztGjR8nOzq7Rec722j6bq6++msWLF7NkyRLWrVtHTk4Or776amX33P3791f+gOPm5oavry+DBw8GqPK+OF81eU618fqsjnHamN66MHLkSAIDAyt/WCovL2fGjBlcffXVla/LC1XxGXT6Z05AQABeXl6Vr+PzVdEl/IMPPjjr+YKCgs6I9/T3Ddi6mP/222+VY9VXrFhBVlbWGZ/XeXl5+Pn5nfEaKCws/MN/f09PTwBCQ0Or3X/668JqtdK2bdsq+yr+b6gYI3+hMZ3rfVbxuqru81lEpCY0pltEamTZsmVkZGQwc+bMapd1mj59OqNGjQJg0qRJfPjhhyxcuJBrrrmG2bNn07FjR7p161bZvry8nMjISF577bVqz3f6l7PqKoGrVq1i3LhxDBo0iPfee4/AwEAcHBz4/PPPa7T8S8Ws0TfffDO33nprtW26du163sfr06cP7dq145FHHiE5OblybHFtONuSSReSlNT0GJMnT2bOnDmsWbOGyMhIfvjhB+6///4qYzJravv27fj5+eHh4XFBj+vUqRO7d+9m/vz5LFq0iLlz5/Lee+/xzDPP8Nxzz9X6v+3Z1OQ8F1LlBggJCTnrOvBlZWWMHDmS3Nxc/vrXv9KxY0dcXV1JS0tjypQpfzgzenVq8pxq4/V5Km9vbywWy3kn7WdLnsrKyv5wuTE7OztuuukmPv74Y9577z1+++030tPTa6UnR20ldYMGDWLIkCG8/PLLZ/RYuVATJ07kqaeeYs6cOTzyyCPMnj0bT09PRo8eXdmmvLwcPz+/s65WUTFuvcLZ/sa1+bq40JjO9T6reF1VjMMXEblYSrpFpEamT5+On59f5YzHp5o3bx7ffvstH3zwAS4uLgwaNIjAwEBmzZrFZZddxrJly3j66aerPKZdu3Zs2bKF4cOH1/iL6Ny5c3F2dubnn3/Gycmpcv/nn39epV2rVq0oLy8nOTm5SqXy9DXGfX19cXd3p6ys7KxJzYW68cYb+fe//02nTp3o3r17tW1atWoF2Cb6Od2uXbvw8fHB1dX1gs9dV1Wb0aNHVy4X16dPH44ePcott9xy0cddu3YtSUlJVZKbVq1anfXvUnF/BVdXVyZOnMjEiRM5fvw41113Hf/5z3946qmnau3fNiEh4Yx98fHxNGvWrPJLfm2/hi7Etm3biI+P58svv2Ty5MmV+0+dnK7C+b4+6uJ9cSHnB1sPmnbt2lXO0P5HmjdvXu1a2fv27TujglqdyZMn8+qrr/Ljjz+ycOFCfH19z9o1+VRne04Vn0EJCQmV1WawTVB3+PDhKq/j8/Xss88yZMiQKrNwn3q+JUuWUFBQUKXaXd37pk2bNkRHRzNr1iwefPBB5s2bxzXXXFPlM7Vdu3YsWbKEAQMGXPCPRDVRXl7Onj17KqvbYHufAZWTStZmTBWvq1P/bURELoa6l4vIBTt27Bjz5s3jqquuYvz48WdcHnzwQQoKCvjhhx8AW9fA8ePH8+OPPzJt2jRKS0urdFUE29jgtLQ0Pv7442rPd3p36urY2dlhsVgqx5ODrevh6TOfV3xZfu+996rsf/vtt8843vXXX8/cuXPZvn37GefLzs7+w5hOd+eddzJ16lReffXVs7YJDAyke/fufPnll1UShe3bt/PLL79w5ZVXXvB5wZaEVpd4XCx7e3tuvPFGZs+ezRdffEFkZORFV4n37dvHlClTcHR0rFx2CeDKK68kJiaGtWvXVu47cuQIH330Ea1bt64c53/w4MEqx3N0dCQiIgLDMCgpKam1f9u1a9dWGb+ckpLC999/z6hRo7Czs6uT19CFqKgknlo5NAyDN99884y2FT/k/NFrpK6ek6ur6wV1d+/Xrx/r168/r7bt2rXj999/5/jx45X75s+fT0pKynk9vmvXrnTt2pVPPvmEuXPnMmnSpPNat/xsf9OK9/Dpa6lX9PSpbiWFPzJ48GCGDBnCSy+9RFFR0RnnKysr45133qmy//XXX8disXDFFVdU2T9x4kR+//13PvvsM3Jycqr9vC4rK+P5558/I47S0tI6+Zw5NXbDMHjnnXdwcHBg+PDhtR7Thg0bsFgsVcahi4hcDFW6ReSC/fDDDxQUFDBu3Lhq7+/bt29l5bPiy9rEiRN5++23mTp1KpGRkWdUEG655RZmz57Nvffey/LlyxkwYABlZWXs2rWL2bNnV66nei5jxozhtddeY/To0dx0001kZWXx7rvv0r59e7Zu3VrZrlevXlx//fW88cYbHDx4sHLJsIrKyanVqRdffJHly5fTp08f7rrrLiIiIsjNzWXjxo0sWbLkgtdxbdWq1RnrHVfnlVde4YorrqBfv37ccccdlUuGeXp6ntfjq9OrVy+WLFnCa6+9RlBQEG3atKmcuOhiTZ48mbfeeovly5efdYmxs9m4cSNfffUV5eXlHD58mNjYWObOnYvFYmHatGlVEvi//e1vzJgxgyuuuIKHHnoIb29vvvzyS5KTk5k7d25ll/ZRo0YREBDAgAED8Pf3Z+fOnbzzzjuMGTOmstJXG/+2Xbp04fLLL6+yZBjAc889V9mmtl9DF6Jjx460a9eOJ554grS0NDw8PJg7d2613bIrJoR76KGHuPzyy7Gzs6uyRNSp6uI59erVi1mzZvHYY48RFRWFm5sbY8eOPWv7q6++mmnTphEfH1+lAlqdO++8k2+++YbRo0czYcIEkpKS+Oqrr85rje8KkydP5oknngA4767lFX/Tp59+mkmTJuHg4MDYsWPp1q0bt956Kx999BGHDx9m8ODBxMTE8OWXX3LNNddUu1b2+Zg6dWq1jx07dixDhw7l6aefZu/evXTr1o1ffvmF77//nkceeaTa5QOfeOIJnnjiCby9vc/o0TB48GDuueceXnjhBTZv3syoUaNwcHAgISGBOXPm8Oabb1ZZ0/tiOTs7s2jRIm699Vb69OnDwoULWbBgAX//+98re5TUZkyLFy9mwIABtGjRotaeg4g0cZd0rnQRaRTGjh1rODs7G0eOHDlrmylTphgODg6VSwqVl5cboaGh1S5bU+H48ePGSy+9ZHTu3NlwcnIymjdvbvTq1ct47rnnKpeMMgzb8kUPPPBAtcf49NNPjbCwMMPJycno2LGj8fnnn1cur3OqI0eOGA888IDh7e1tuLm5Gddcc03lcjkvvvhilbaZmZnGAw88YISGhhoODg5GQECAMXz4cOOjjz76w7/V6Uv3VKe6JcMMwzCWLFliDBgwwHBxcTE8PDyMsWPHGnFxcVXaVLc80qnHPHWpol27dhmDBg0yXFxcDKByCaULOcbZll4yDMPo3LmzYbVajdTU1HM+3woVyzNVXOzt7Q1vb2+jT58+xlNPPVVlKaFTJSUlGePHjze8vLwMZ2dnIzo62pg/f36VNh9++KExaNAgo0WLFoaTk5PRrl0748knn6zyOjKMi/u3rXgdfvXVV5WvuR49elRZ7uhCzlOxvNacOXPO469XNYZziYuLM0aMGGG4ubkZPj4+xl133WVs2bLljCWvSktLjT//+c+Gr6+vYbFYqrxnOG3JsIt9TtUtzVVYWGjcdNNNhpeXlwH84fJhxcXFho+PT+UyfBWeeeYZAzByc3Or7H/11VeN4OBgw8nJyRgwYICxfv3681oyrEJGRoZhZ2dnhIeHnzOu0z3//PNGcHCwYbVaq7yfSkpKjOeee85o06aN4eDgYISGhhpPPfWUUVRU9IfHPNt71jBsy6ABZ3zuFBQUGI8++qgRFBRkODg4GGFhYcYrr7xilJeXV3uOAQMGVLus2ak++ugjo1evXoaLi4vh7u5uREZGGn/5y1+M9PT0yjZn+wys7rVb3TKCt956q+Hq6mokJSUZo0aNMpo1a2b4+/sbU6dOrbKMW23EZBiGcfjwYcPR0dH45JNPzvq8RUQulMUwLsHUnyIiDcDmzZvp0aMHX331FX/605/MDqfB6dGjB97e3pUz1zd2FouFBx544Iwuu3LpPP/883z++eckJCRUdqV/7LHHePPNNykqKsLBwaHWzpWTk0NgYCDPPPMM//znP2vtuFK/vPHGG7z88sskJSVdkvHqItI0aEy3iDRJ1a1n+8Ybb2C1Whk0aJAJETVs69evZ/PmzVUm6xKpa48++iiFhYVVVlCIjY2lffv2tZpwA3zxxReUlZXVyiSBUj+VlJTw2muv8Y9//EMJt4jUKo3pFpEm6eWXX2bDhg0MHToUe3t7Fi5cyMKFC7n77rvPWJ5Mzm779u1s2LCBV199lcDAwDMmXBKpS25ubpXrL3/++ecsW7aM1atX85///KfWzrFs2TLi4uL4z3/+wzXXXFM5W7Y0Pg4ODuzfv9/sMESkEVLSLSJNUv/+/Vm8eDHPP/88hYWFtGzZkmefffaMpczk3L755hv+9a9/0aFDB2bMmIGzs7PZIUkTdccddxAQEMBf/vIX/vrXv9bacf/1r3+xZs0aBgwYcMYKByIiIudDY7pFRERERERE6ojGdIuIiIiIiIjUESXdIiIiIiIiInVEY7qB0tJSNm3ahL+/P1arfocQERERERG5UOXl5WRmZtKjRw/s7ZVqVtBfAti0aRPR0dFmhyEiIiIiItLgxcTEEBUVZXYY9YaSbsDf3x+wvTgCAwNNjkZERERERKThycjIIDo6ujK/Ehsl3VDZpTwwMJCQkBCToxEREREREWm4NGS3Kv01REREREREROqIkm4RERERERGROqKkW0RERERERKSOKOkWERERERERqSNKukVERERERETqiJJuERERERERkTqipFtERERERESkjijpFhEREREREakjSrpFRERERERE6oiSbhEREREREZE6oqRbREREREREpI7Ymx2AiIiIiIiINEH56bB4KiQuhpJj4N0Wrn4XgntW377gAPz8NKRvgtw90OdeuOLFM9utfQ/Wfwp5qdCsBURcDcOngoNz3T6fs1DSLSIiIiIiIpfWsUPw6eXQZiD8aS64toCDSeDidfbHlBaDqw8MehJ+f7f6NlvnwJJnbcl7aDQcTITv7gcsMPr/6uCJ/DEl3SIiIiIiInJprX4DPIPhmvdO7mve+tyPad4KrnjJtr3pq+rbpKyDln2g6w0nHxM5HlLXX2zENaYx3SIiIiIiInJp7V4IQT1g9mR4uR18cBls+OLijxvaB9K3QOoG2+3cZEj4BcJGXvyxa0iV7nqqrNwgJjmXrIIi/NydiW7jjZ3VYnZYIiIiIiJilvIy2LcGCjPBzR9a9QerndlRnaGgoID8/PzK205OTjg5OVVtdGgvxH4K/R6AgY9D2kZY+Fewc4TuN9X85F1vgKMH4bPLAQPKS6H37TDoiZof8yKZmnSXlRu8sSSebzelkV1QjL+HM+N7hfDnYe2xWGwJpmEYvL44nhmxKeQfK6F36+b8+5pI2vi4Vh7n8NHjTP1hB0t3ZmGxwBVdApg6tjOuTg3zN4VF2zN47sc4MvKKKvcFejozdWwEo7sEmhiZiIiIiIiYIu4HWPRX2+RjFTyCYPRLEDHOvLiqERERUeX21KlTefbZZ6s2Msptle4RU223A7tB1k5Y/9nFJd3Jq2DVqzDmVQjpbZtwbeHfYOXLMPgvNT/uRTC1e/kHK5P46vd9/Ovqzix5bDB/u6IjH65M4os1e09ps4fP1+zlP9d04bsHBuDiYM/kz9ZRVFJW2ebhmZuJzyxk2h3RfDYlipjkXJ6at82EZ3TxFm3P4L6vNlZJuAEO5BVx31cbWbQ9w6TIRERERETEFHE/2Lphn5pwA+Rn2PbH/WBOXGcRFxdHXl5e5eWpp546s5F7APh2qLrPN9w24/jFWP4f6DYRet0K/p2h01gY/gyseg3Kyy/u2DVkatK9Yd8hRkb4M6yjP6HezbgyMpCBYb5sSTkM2Krcn/2WzJ+HtWdU5wA6BXrw2sRuZOYX80tcJgCJWQWsjM/mpesj6dGyOVGtvXl2XGd+3JpOZn7ROc5e/5SVGzz3YxxGNfdV7HvuxzjKyqtrISIiIiIijU55ma3Cfa4sYdHfbO3qCXd3dzw8PCovZ3QtB9vY64OJVfcdTALP0Is7eclRsJyW5lZ2wTcnjzI16e7Vqjm/JR5kT3YhAHHp+azfl8uQDn4ApOQeI7ugmAHtfSof4+HsQPdQLzbuOwTAxn2H8XC2p2uIV2Wby9r7YLVY2LT/cLXnLS4uJj8/v/JSUFBQN0/wAsUk555R4T6VAWTkFRGTnHvpghIREREREfPsW3NmhbsKA/LTbO0akn73Q2os/PpfW7K9dY5tIrXou062WfIszLun6uMyttouxwvhaI5tO2vXyfvDr4DYz2DbN7Zx40nLYNm/ocNo08a/mzro+b7B7SgoKmX4ayuxs1goMwyeGNWBa3oEA5BdaEtAfd2q/jLi6+ZEdmHxiTbF+Jx2v72dFS8Xh8o2p3vhhRd47rnnavvpXLSsgvOrzB9oYBV8ERERERGpocLM2m1XXwT3gonTYelztvHWzVvB6Beg64STbQoyz+xu/uHAk9sZm2HbHPBsCY+eGF486EmwWGyJdkEGNPOxJdzD/lnnT+lsTE2652/L4PvNabw5qQfh/m7Epefzr/lxlROq1ZWnnnqKxx57rPJ2WlraGYP9zeDn7nxe7Z6fv4Pk7EJu6B1KqHezOo5KRERERERM4+Zfu+3qkw6jbZezufb9M/c9m3fuY9rZw5C/2S71hKlJ9ws/7eS+Ie0Y1y0IgI4BHqQdOsZ7KxIZ3ysEXzdbEppdWIyfx8mENLuwmIhAD8BW9c45raJdWlbO4WMlZ1TIK5w+Zf2p09mbKbqNN4GezhzIKzrraAOLBXKPlPDWskTeXp7IZe19mBgVysgIf5zs699yASIiIiIichFa9bfNUn7WLuYW2/2t+l/SsOT8mTqm+1hJWeXSYBWsVgvGiYwz1NsFX3cn1iQerLy/oKiEzSmH6dmqOQA9W3mRX1TKttSTv3isSTpIuWHQo6VXnT+H2mRntTB1rK3ifvqK3JYTl7cmdeftG3twWXsfDANWJeTw4Neb6Pt/S3l+fhzxmfVjfLqIiIiIiNQCq51tWbBqncgaRr9YL9frFhtTK93DO/rz7rJEgr2cCfNzZ0d6Pp+uTuaG3rau5RaLhdsHtOHtZQm09nEl1NuFV3+Jx9/DiVERtu4T7f3cGRzuy9/mbeU/10ZSWlbO1B92MLZrEP4e59dduz4Z3SWQ92/uecY63QGnrdM9tlsQ+w8eZc6GFGavTyEzv5hPVyfz6epkerb0YlJUS8Z0DWywa5WLiIiIiMgJrQaA1R7KS6vu9wiyJdz1bJ1uqcpiGIZp608VFpfy6i+7+WVHJjmFxfh7ODOuWxAPDQ/D0d5WhDcMg9cXx/N1TAr5RSVEtW7O81d3oa2vW+VxDh89zjPf72DpzkysFgujuwTw7LjO551wpqamEhoaSkpKCiEhdTeW/EKUlRvEJOeSVVCEn7sz0W28sbOeXv+2KS0r59eEbGbGpLB0V1blkmKujnaM6x7ExKiWdAvxPKNXgYiIiIiINACrXoWl/4KAbnD5v6EwyzaGu1X/elXhro95VX1gatJdXzSmF0dWQRFzN6QxK3Y/ew8erdzfMcCdiVGhXNsjGK9mjiZGKCIiIiIi562sFN7sBvmpcM370P0msyM6q8aUV9UmJd00zheHYRisS85lVmwKP23LoLi0HABHeyujOwcwKSqUvm1bYD1L9VxEREREROqBuO9h9mRo1gIejQOH+juEtjHmVbVBA34bKYvFQt+2LejbtgXPju3M91vSmBGTws6MfH7Yks4PW9Jp6d2MiVGhjO8V0iDHv4uIiIiINHrrPrJd95pSrxNuOTtVumk6v8gYhsH2tHxmxu7nh83pFBTbJmKwWmBYRz8mRrVkaAdf7O1MndReREREREQADmyHDwaAxQ4e2QaewWZHdE5NJa+6UKp0NyEWi4XIEE8iQyJ5ekwnftp2gFmx+4nde4glO7NYsjMLP3cnxvcKYULvUFr7uJodsoiIiIhI0xXzoe2609h6n3DL2SnpbqKaOdozvlcI43uFkJhVyOz1KczdkEpWQTHvrUjivRVJ9GvbgknRoVzeOQBnh/ozK6KIiIiISKN3NBe2zrFt97nH3FjkoijpFtr7ufH3KzvxxKgOLN2ZyczYFH5NyGbtnoOs3XMQTxcHru0RzITeoUQEeZgdroiIiIhI47dpGpQeA/9IaNnP7GjkIijplkqO9lauiAzkishA0g4fY876FOasTyXt8DG+WLOXL9bspWuIJxOjQhnXLQh3ZwezQxYRERERaXzKyyDmE9t2n3vAohWHGjJNpIYG/J9LWbnB6sQcZsem8EvcAUrKbC8XFwc7xnQNZFJUKL1aNceiDwIRERERkdqxcz7M+hO4eMNjceDgYnZE50V5VfVU6ZZzsrNaGBzuy+BwXw4WFvPtpjRmxOwnKfsI32xI5ZsNqbTzdWVSVEuu6xlMCzcns0MWEREREWnYKiZQ6zm5wSTccnaqdKNfZC6UYRhs3H+ImTEpzN+awbGSMgAc7CyMjPBnYlRLLmvvg51V1W8RERERkQuStRPe6wsWKzy8Bbxamh3ReVNeVT1VuuWCWSwWerXyplcrb54ZG8GPWzKYFbufLal5/LTtAD9tO0Cwlws39A7hht6hBHvp1zkRERERkfOy7kSVu+OYBpVwy9kp6ZaL4u7swE19WnJTn5bEpecze30K8zbaJl97Y0kCby5NYFCYL5OiQhneyR9He6vZIYuIiIiI1E/HDsHWWbbtaC0T1lgo6ZZaExHkwbPjOvO3Kzry844DzIxJYe2eg6yMz2ZlfDYtXB25vlcIE3qH0t7PzexwRURERETql03ToeQo+EVA68vMjkZqiZJuqXXODnZc3T2Yq7sHszfnCLPXpzBnQyrZBcV89OsePvp1D1GtmzMxqiVXRgbQzFEvQxERERFp4srLIPZj23b03VomrBHRRGpowP+lUFpWzvLd2cyK3c+yXVmUn3jVuTvZM657EJOiWtIl2ENLj4mIiIhI07R7IcyYBM5etmXCHF3NjuiCKa+qnkqMcknY21kZGeHPyAh/DuQVMXdjKrNiU9ife5Tp6/Yzfd1+IgI9mBQdytXdgvFs5mB2yCIiIiIil07FBGo9b2mQCbecnSrd6BcZs5SXG/y+5yAzY1NYtP0Ax8vKAXCyt3JlZCATo0Lp08Zb1W8RERERadyy4+HdKMACD2+G5q1NDqhmlFdVT5VuMY3VaqF/ex/6t/fh0JHjfLc5jZkxKezOLODbTWl8uymNNj6uTOgdyvW9gvFzdzY7ZBERERGR2hfzke26wxUNNuGWs1OlG/0iU58YhsGW1Dxmxe7nh83pHDleBoCd1cLwjn5Mig5lUJgv9nZaekxEREREGoGiPHi1E5QcgcnfQ9shZkdUY8qrqqdKt9QrFouF7qFedA/14h9jIliwNYOZsfvZuP8wv8Rl8ktcJgEeztzQ27b0WKh3M7NDFhERERGpuc1f2xJu347QZrDZ0UgdUNIt9Zarkz0TokKZEBVKfGYBs2JTmLcxlQP5Rby9LJG3lyVyWXsfJkaFMqqzP072dmaHLCIiIiJy/srLT3Ytj75Ly4Q1Ukq6pUEI93fnn1dF8JfRHVgcl8ms2BRWJeSwOtF28WrmwHU9QpgYFUqHAHezwxURERER+WNJSyF3Dzh5QtdJZkcjdURJtzQoTvZ2XNU1iKu6BpGSe5Q561OYsyGVjLwiPvstmc9+S6ZHSy8mRYVyVdcgXJ30EhcRERGRemrdB7brHjeDk5u5sUid0URqaMB/Q1dWbvBrQjazYlJYsjOT0nLbS9rV0Y6x3YKYEBVKj1AvLT0mIiIiIvVHTiK80wuwwEMbwbut2RFdNOVV1VMZUBo8O6uFoR38GNrBj+yCYuZtTGVWbAp7co4wMzaFmbEphPu7MTGqJdf1CKa5q6PZIYuIiIhIUxf7se06bFSjSLjl7FTpRr/INEaGYRC79xAzY/ezYGsGxaXlADjaWRnV2Z9JUS3p364FVquq3yIiIiJyiRUX2JYJO14AN8+F9iPMjqhWKK+qnird0ihZLBai23gT3cabqWM788OWdGbF7md7Wj7zt2Ywf2sGIc1dmNg7lPG9Qwj0dDE7ZBERERFpKjbPsCXcLcKg7TCzo5E6pqRbGj1PFwdu6duKW/q2YntaHrNiU/hucxqph47x6uJ4Xl8Sz5AOfkyMCmVYRz8c7KxmhywiIiIijVWVZcLuBqu+ezZ2SrqlSekS7EmXYE/+fmUnFm7PYGZsCjHJuSzblcWyXVn4uDkxvpdt6bE2Pq5mhysiIiIijc2e5XAwARzdofuNZkcjl4CSbmmSXBztuK5nCNf1DCEpu5DZ61OYuyGVnMJiPliZxAcrk+jTxptJ0aFc0SUQZwc7s0MWERERkcagosrd/SZwcjc3FrkkNJEaGvAvNiVl5SzdmcWs2P2sjM/mxMpjuDvbc22PYCZGhdI5yNPcIEVERESk4crdA2/1BAx4cAP4tDc7olqlvKp6qnSLnOBgZ2V0lwBGdwkg/fAxvtlgW3os7fAx/rd2H/9bu4/IYE8mRoUyrnsQHs4OZocsIiIiIg1JzCeAYZutvJEl3HJ2qnSjX2Tk7MrLDX5LymFmbAq/7DhASZnt7eLsYGVMZBCTokPp3ao5FouWHhMRERGRcyguhNcioDgPbpoD4aPMjqjWKa+qnirdIudgtVoYGObLwDBfco8cZ95GW/U7IauQuRtTmbsxlba+rkyKCuW6niH4uDmZHbKIiIiI1EdbZ9kSbu+2jWZdbjk/SrpFzpO3qyN3DmzLHZe1YeP+w8yK3c+PWzLYk32E//tpFy8v2s3ICH8mRoUyMMwXO6uq3yIiIiICGIaWCWvClHSLXCCLxUKvVs3p1ao5/7wqgvlbbUuPbUk5zMLtB1i4/QBBns7c0DuUG3qHENK8mdkhi4iIiIiZkldC9i5wcLXNWi5NipJukYvg7uzAjdEtuTG6JTsz8pkVm8K3m9JIzyvizaUJvLUsgYFhvkyKCmVEJ38c7fWrpoiIiEiTs65imbAbwVmr4TQ1SrpFakmnQA+eHdeZv13RkZ93HGBWbAprkg7ya3w2v8Zn4+3qyPU9bUuPtffTmowiIiIiTcKhvRC/0LYdfbepoYg5lHSL1DJnBzuu7h7M1d2D2XfwCLPXpzBnfSpZBcV8vCqZj1cl07tVcyZEhXJV10CaOeptKCIiItJoxX4CRjm0HQq+HcyORkygJcPQ1PZS90rLylmxO5uZsSks351FWbntbefmZM/YbkFMigqla4inlh4TERERaUyOH4XXOkHRYbhxJnS4wuyI6pTyquqpxCZyCdjbWRkR4c+ICH8y84v4ZkMqs9ensO/gUWbE7GdGzH46BrgzKSqUa3oE49XM0eyQRURERORibZttS7i9WkFY41uXW86PKt3oFxkxR3m5wbrkXGbF7uen7Qc4XloOgKO9lSu6BDAxKpS+bVpg1dJjIiIiIg2PYcD7AyBrB4z6N/T/s9kR1TnlVdVTpVvEJFarhX7tWtCvXQuePXqc7zenMyNmP7sOFPD95nS+35xOqxbNmNA7lBt6heDn4Wx2yCIiIiJyvvautiXcDs2gx81mRyMmUtItUg94NXPk1v6tmdyvFdvS8pgZm8IPm9PZd/Aor/y8m9cWxzO0gx+TokIZ0sEXezstPSYiIiJSr8V8aLvuOhFcmpsbi5hKSbdIPWKxWOga4kXXEC/+MaYTC7ZmMCs2hfX7DrFkZyZLdmbi5+7EDb1DmNA7lFYtXM0OWUREREROdzgFdi2wbWuZsCZPSbdIPdXM0Z4beodyQ+9QErMKmBWbwtyNaWQVFPPu8iTeXZ5E/3YtmBgVyuWdA3B2sDM7ZBEREREBWP+pbZmw1gPBP8LsaMRkSrpFGoD2fu48PSaCJy/vyJKdmcyMTWFVQjZrkg6yJukgni4OXNsjmEnRoXQM8DA7XBEREZGmq+QYbPjCtt3nXlNDkfpBSbdIA+Job+XKyECujAwk9dBR5qxPZc76FNLzivhizV6+WLOXbqFeTIoKZWy3INyc9BYXERERuaS2fQPHDoFny0a/LrecH30jF2mgQpo349GR4Tw0PIxVCdnMik1hcVwmW1IOsyXlMM/Pj+OqroFMjGpJz5ZeWCxaekxERESkThnGyQnUou4Aq4b/iZJukQbPzmphSAc/hnTwI6ewmHkbU5kZm8Ke7CPMXp/K7PWphPm5MTEqlOt6huDt6mh2yCIiIiKN0/7f4cA2sHeGnpPNjkbqCSXdIo2Ij5sTdw9qx10D27J+3yFmxqSwYFs6CVmF/HvBTl5atItRnQOYFBXKgHY+WK2qfouIiIjUmnUf2K67ToBm3ubG0hDkp8PiqZC42DYW3rstXP0uBPesvn3BAfj5aUjfBLl7bGPmr3jxzHbHDsOy52Hnjye6+ofC6BchfFSdPp2zUdIt0ghZLBaiWnsT1dqbqeMi+GFzOrNiU9iWlseCrRks2JpBsJcLE6NCuaF3CIGeLmaHLCIiItKw5aXZkjyA6HvMjaUhOHYIPr0c2gyEP80F1xZwMAlcvM7+mNJicPWBQU/C7++epc1xmHYNuPrChP+BeyDkpYCzZ108i/OipFukkfNwduDmvq24uW8rtqflMXt9Ct9uSiPt8DFeWxzPG0viGRzuy8Solgzv5IeDndXskEVEREQanvWfgVEGrQZAQBezo6n/Vr8BnsFwzXsn9zVvfe7HNG8FV7xk2970VfVtNk2zJfR3LAY7h5OPM5GSbpEmpEuwJ12CPfn7lZ1YuD2DmTEprEvOZfnubJbvzsbHzZHre4UwsXcobX3dzA5XREREpGEoKTq5TFj03aaG0mDsXgjth8PsybD3N/AIhKg7odeUiz9uSDQseBx2/wTNfCByPFz2qGkT2ynpFmmCnB3suLZHCNf2CGFPdiGz16fyzYZUcgqL+XDlHj5cuYfoNt5Migrlii6BuDhq5k0RERGRs9oxD47mgEcwdLzK7GhMV1BQQH5+fuVtJycnnJycqjY6tBdiP4V+D8DAxyFtIyz8K9g5Qveban7yQ3sh+VfoegP8aY5t7PeCx6G8FIb8rebHvQjqRyrSxLX1deNvV3Rk7VPD+PCWXgzr6IfVAjHJuTw2ewvR/7eEf363ne1peWaHKiIiIlL/GAasO2WZMDvVNSMiIvD09Ky8vPDCC2c2MsohsBuMmGq77n0b9LzV1k3/YhjltvHcY9+CoB7Q5XoY+MTFH/ci6BUhIgA42Fm5vHMAl3cOICPvGN+sT2XW+hRSDx1j2u/7mPb7ProEezCxdyjjugfj6eJgdsgiIiIi5kuNhYzNYOcEPaeYHU29EBcXR3BwcOXtM6rcAO4B4Nuh6j7fcNj5w8Wd3D0ArPZVu5L7doDCTNska/aXfvlcJd0icoZATxf+PDyMB4a2Z03SQWbG7ueXHZlsT8tne9oO/r1gJ2MiA5kU3ZKo1s2xWLT0mIiIiDRRFVXuyPG2GbgFd3d3PDw8zt0otA8cTKy672CSbXmvixHaB7Z9A+XlYD3RsftgIrgFmJJwg5JuETkHq9XCZWE+XBbmQ+6R43y7KY1ZsfuJzyxk3qY05m1Ko62PKxOiQrm+Zwi+7tX8iikiIiLSWOVnQNx3tm1NoHZh+t0Pn46CX/8Lna+1jene8AWMffNkmyXP2v7G1314cl/GVtv18ULbOPqMrbZx4H4dbfuj7oCYj2HRX21Lt+UmwapXoY95y7hZDMMwTDt7PZGamkpoaCgpKSmEhISYHY5IvWYYBptTDjMrNoUftqRz9HgZAPZWC8M7+TEpqiWDwn2xs6r6LSIiIo3c8v+DlS9BaF+442ezozHdBedVuxfB0udsFe7mrWyTqp06e/m398Hh/XDbgpP7nq1mvW3PlvDotpO3U2Jg0VNwYJttVvQet5g6e7mSbpR0i9RUYXEpC7amMzM2hU37D1fuD/R05oZeIdzQO5RQ72bmBSgiIiJSV0qPw+ud4UgWjP/MNmFXE6e8qnrqXi4iNebmZM/EqJZMjGrJ7gMFzIpNYd6mVDLyinhrWSJvL0/ksvY+TIwKZWSEP072WnpMREREGom472wJt3sgdBpndjRSjynpFpFa0SHAnWfGRvDXKzrwy45MZsWmsDoxh1UJtkvzZg5c1zOEiVGhhPu7mx2uiIiIyMVZ94HtuvcdYKdVXeTslHSLSK1ysrdjbLcgxnYLYv/Bo8zZkMLs9Slk5hfz6epkPl2dTM+WXkyKasmYroG4OuljSERERBqY1A2QtsE2gdepY5BFqqFvuyJSZ1q2aMbjozrw8PAwfk3IZmZMCkt3ZbFx/2E27j/Mcz/uYFz3ICZGtaRbiKeWHhMREZGGIebEbNqdrwM3X3NjkXrP1KR7wIvLSDt87Iz9t/RtxfPXdGHih2tZl5xb5b6b+rTk/66NrLyddvgY//h2G2v3HMTV0Z7re4Xwl8s7YG9nrfP4ReT82NtZGdbRn2Ed/ckqKGLuBtvSY3sPHmVGTAozYlLoGODOxKhQru0RjFezqmsolpUbxCTnklVQhJ+7M9FtvDU7uoiIiJijIBO2z7Nt99EyYfLHTE26f3hwAGWnTJ4ef6CQmz9dx5WRgZX7bowO5dGR4ZW3XRxOTsRUVm5w++ex+Lo7Mfe+/mQVFPP47C3YWy38ZXTHS/MkROSC+Lk7c9+Qdtw7uC3rknOZFZvCT9sy2HWggOd+jOOFhbsY3TmASVGh9G3bgl/iDvDcj3Fk5BVVHiPQ05mpYyMY3SXwHGcSERERqQMbvoDyEgiJguBeZkcjDYCpSXcLN6cqt99fkUSrFs3o29a7cp+zgx1+7s7VPv7XhGwSsgr46s4++Lo70Rl4bGQ4Ly3cxSMjwnG0V7VbpL6yWCz0bduCvm1b8OzYzny/JY0ZMSnszMjnhy3p/LAlHR83R3IKj5/x2AN5Rdz31Ubev7mnEm8RERG5dEqPw/rPbNvR95gbizQY9SYrPV5azneb0pjQO7TKuM7vN6fT41+/MOr1lby0aBfHjpdV3rdp3yE6BHjg634yeR8c7ktBcSnxmQWXNH4RqTnPZg5M7teanx66jB8fvIw/9WmJm6NdtQk3QEX/mOd+jKOs3Ki2jYiIiEit2/kDFB4AN3+IuNrsaKSBqDcTqf0Sd4D8olLG9zq5iPrV3YMJbu6Cv4cTuzIKeHHhLvZkF/LhLb0ByC4sxset6thPnxPV8+zC4rOeq7i4mOLik/cXFChBF6kPLBYLkSGeRIZEMjLCnymfx561rQFk5BURk5xLv3YtLl2QIiIi0nTFfGS77nUb2Dueu63ICfUm6Z4Vm8KQcF/8PU52Jb+pT8vK7Y4BHvi5O3HTJ+vYd/AIrVq41vhcL7zwAs8999xFxSsidSvvWMl5tcsqKPrjRiIiIiIXK30TpKwDqwP0vs3saKQBqRfdy1MPHeW3xBwmRoWes133ll4A7D14FABfN6czup/mnKhw+542XvxUTz31FHl5eZWXuLi4i4heROrC2eZyqGk7ERERkYuy7kSVu/M14B5gaijSsNSLpHvO+lRauDkxrKPfOdvFpecD4HdiDHePVs3ZfSC/MtEGWJWQg7uTPWH+bmc9jpOTEx4eHpUXd3f3WngWIlKbott4E+jpzNkWBrNgm8U8uo33WVqIiIiI1JIjObB9rm1bE6jJBTI96S4vN/hmQyrX9wypsrb2voNHeGtpAttS80jJPcriuEwem72F6DbedAr0AGBQmC9hfu48Omszcen5rIzP5tVfdnNLv1Y42dud7ZQi0gDYWS1MHRsBUG3ibQBTx0ZovW4RERGpexu+gLJiCOoBIb3NjkYaGNPHdK9OzCHt8DEm9A6pst/BzsrqxBw++y2Zo8fLCPJ05oouATw4rH1lGzurhU+n9OYf323nuvd/o5mjPdf3DOaxU9b1FpGGa3SXQN6/uecZ63QDtGrRjMs7q2uXiIiI1LGyEoj91Lbd516w6Ad/uTAWwzCa/Ho7qamphIaGkpKSQkhIyB8/QEQuqbJyg5jkXLIKinCyt/LorM0cKynno1t6MUqJt4iIiNSlHd/CnCng6guP7gD7s88d1dQpr6qe6ZVuEZE/Yme1VFkWbGtqHu+tSOK1xfGM6OSPVV3MRUQarVN/ePVzt83loaFFcklVTKDWa4oSbqkRJd0i0uDcPagt09buY9eBAhZuP8CYroFmhyQiInVg0faMM4YYBXo6M3VsBKO76LNfLoGMrbB/DVjtofftZkcjDZTpE6mJiFwor2aO3H5ZGwBeXxJPWXmTHyUjItLoLNqewX1fbTxjTo8DeUXc99VGFm3PMCkyaVJiPrRddxoHHkHmxiINlpJuEWmQ7hjYBk8XBxKzCvlxS7rZ4YiISC0qKzd47sc4qvtJtWLfcz/G6UdXqVtHc2HbN7btPlomTGpOSbeINEgezg7cPagtAG8siae0rNzkiEREpLbEJOeeUeE+lQFk5BURk5x76YKSpmfjl1BaBAFdIbSP2dFIA6akW0QarCn9W+Pt6sjeg0eZtzHN7HBERKSWZBWcPeE+1bM/7GBGzH5yjxyv44ikySkrPWWZsHu0TJhcFCXdItJguTrZc+9gW7X7zaUJHC9VtVtEpDHwc3c+r3a7Mwt4at42ov6zhFs+XcfMmP0cUgIutWH3T5CXAs1aQJfxZkcjDZySbhFp0G7p2xpfdyfSDh9j9voUs8MREZFaEN3Gm0DPsyfeFsDP3YknL+9Al2APysoNViXk8Ld52+h9IgGfFasEXC5CzIllwnreCg7n9yOQyNko6RaRBs3F0Y77h7QD4J1liRSVlJkckYiIXCw7q4W/XdGx2vsqOvn+6+rOPDC0PfP/PJCVTw7hL6M70DnoZAL+17m2Cvjkz2KYHZvC4aNKwOU8Ze6AvavAYgdRd5gdjTQCWqdbRBq8G6Nb8tGve8jIK2JGzH5uG9DG7JBEROQiHTgxkZqdxUKZcXKW8oBq1ulu1cKV+4e05/4h7dmbc4QF2zJYsDWDuIx8fo3P5tf4bP7+rYUB7X0Y0zWQyyMC8GzmcMmfkzQQFVXujmPAM8TcWKRRsBiG0eTXWkhNTSU0NJSUlBRCQvTGEmmIpq/bx9PfbsfHzYlVfxmKi6Od2SGJiEgNFRaXMvClZRw6WsLL47sS2rwZWQVF+Lk7E93GGzvr+U1qlZxzhJ+2ZTB/awY7M/Ir9zvYnUjAIwMZpQRcTnU0F16LgNJjMOUnaD3A7IgaFOVV1VOlW0QahRt6hfL+iiRSDx1j2u97uXtQO7NDEhGRGvpyzV4OHS2hrY8r1/UIxt6uZiMi2/i48sDQ9jwwtD17sgsrE/BdBwpYsTubFbuz+bvdNgaG+XJlZCAjI/zxdFEC3qRt+sqWcPt3gVb9zY5GGgkl3SLSKDjaW3loeBh/+WYrH6zcw019WuHmpI84EZGGJr+ohI9+3QPAwyPCapxwn66trxsPDgvjwWFhJGbZEvCfttkS8GW7sli2KwsHOwuDKhLwzv54OCsBb1LKyyD2Y9t29N1aJkxqjb6RikijcV2PYN5fkURyzhG+XLOXB4a2NzskERG5QJ+tTibvWAlhfm5c1TWoTs7R3s+Nh4aH8dDwMBKzCliw9QA/bctgd2YBS3dlsXRXFo7zrAwK9+HKyEBGRCgBbxLif4bD+8HZCyJvMDsaaUSUdItIo2FvZ+Xh4WE8MmszH65M4ua+rdRNUESkATl89DifrkoG4JER4ec9dvtitPdz5+ER7jw8IoyEzAIWnKiAx2cWsmRnFkt2ZuFoZ2VQuC9XdQ1keCc/3JWAN07rPrBd97oVHJuZG4s0Kkq6RaRRGdstiHeXJ5KQVcinq5N5bGS42SGJiMh5+mRVMgXFpXQMcOeKLgGX/Pxh/u484u/OIyPCic8sYMHWDBZsyyAxq5AlOzNZsjMTR3srgysTcH8NZWossnZB8kqwWCHqTrOjkUZGnxIi0qjYWS08MiKcB77eyGerk7mtf2uauzqaHZaIiPyB3CPH+fw3W5X70ZHhWC9Blftcwv3dCR/pzqMjbQn4/K0ZLNiaTlL2ERbHZbI4zpaADwn3ZYwS8IavYpmwDleCV0tzY5FGR58MItLoXNElgI4B7uw6UMBHq/bw19EdzQ5JRET+wIcrkzhyvIzIYE9GRfibHU4V4f7uPDbSnUdHhBGfWciCrenM35bBnuwj/BKXyS9xmTjZWxnSwZcxXYMY3tEPVyXgDcexw7Blpm07+m5TQ5HGSZ8GItLoWK0WHhsZzt3TNvDFb3u547I2+Lg5mR2WiIicRXZBMV+u3QvAYyPDsdTTWaMtFgsdAtzpENCBR0eGs+tAAT9ty2DB1gz25Bzh5x2Z/LzDloAP7eDHmK6BDFMCXv9tng4lR8C3E7QZZHY00gjpE0BEGqWREf50DfFka2oeH6xI4h9XRZgdkoiInMX7K5IoKimne6gXQzr4mh3OebFYLHQK9KBToAePjQxnZ8aJBHxbBsk5R1i04wCLdhzA2aFqAt7MUV+/65Xycog5sUxYHy0TJnVD73oRaZQsFlu1e8rnsUz7fR93DWqLv4ez2WGJiMhpMvOL+GrdPgAeH1V/q9znYrFYiAjyICLIg8dHhROXkV9ZAd978CgLtx9g4XZbAj6sox9jIoMY2tFXCXh9kLgYDiWDsyd0nWh2NNJI6Z0uIo3W4HBferVqzoZ9h3hveSLPXd3F7JBEROQ07y5P5HhpOVGtm3NZex+zw7loFouFzkGedA7y5IlRHdiRnl9ZAd938Cg/bTvAT9sO4OJgZ0vAuwYytIMfLo52ZofeNK370Hbd4xZwdDU3Fmm0lHSLSKNlsVh4fGQ4N32yjhkxKdw9uB3BXi5mhyUiIiekHT7GzJgUAB4b2aFBVrnPxWKx0CXYky7Bnjx5uS0Bn7/Vtg74/tyjLDiRjLs42DG8kx9jIgMZogT80slJgKSlgEXLhEmdUtItIo1a//Y+9G3rze97cnlnWSIvXBdpdkgiInLCO8sSOV5WTv92LejXroXZ4dSpUxPwv47uwPa0fOZvS+enbRmk5B5j/tYM5m/NoJmjHcM7+TMmMoAhHfxwdlACXmcqlgkLHw3ebcyNRRo1Jd0i0ug9PqoDN3ywljnrU7hvcDtatmhmdkgiIk3e/oNHmbO+osodbnI0l5bFYiEyxJPIEE/+Nroj29LyWLDVVvVOPXSMH7ek8+OWdFxPJOBXRgYypIOvEvDaVJQPm7+2bffRMmFSt5R0i0ijF9Xam4FhPqxKyOHNpQm8OqGb2SGJiDR5by9LoLTcYFC4L71be5sdjmksFgtdQ7zoGuLF367oyNbUPFu3860ZpB0+xg9b0vnhRAI+IsKWgA8OVwJ+0bbMgOOF4BMObYeaHY00ckq6RaRJeHxUB1Yl5PDtplTuH9qOdr5uZockItJkJeccYd6mNKDpVbnPxWKx0C3Ui26hXjx1RUe2pOaxYGs6P207QNrhY3y/OZ3vN6fj5mTPiE5+jOkaxMAwHyXgF6q8/OQEatFaJkzqnpJuEWkSuod6MbyjH0t3ZfHmkgTeurGH2SGJiDRZby6Jp6zcYHhHP7qHepkdTr1ksVjoHupF91Av/n5lJzanHGbBiUnY0vOK+G5zOt+dSMBHRvgzJjKQgeE+ONkrAf9DScsgNwmcPKDbjWZHI02Akm4RaTIeHRnO0l1Z/Lg1nQeGtqdDgLvZIYmINDmJWQV8vyUdsH0uyx+zWCz0aNmcHi2b2xLw1JMJeEZeEd9uSuPbTWm4VyTgXQO5LEwJ+FnFnKhyd/8TOKnnm9Q9Jd0i0mR0Cfbkii4BLNx+gDeWxPP+zb3MDklEpMl5fUkChgGXd/anS7Cn2eE0OFarhZ4tm9OzZXOevrITm06pgB/IL2LepjTmbUrD3dmWgF/VNZDL2vviaG81O/T64WASJPxi246+y9xYpMlQ0i0iTcqjI8NZtOMAC7cfYEd6Hp2D9IVPRORS2XUgnwVbMwBVuWuD1WqhV6vm9GrVnH+M6cTG/YdYsM2WgGfmFzNvYxrzNtoS8FERAVzVNZAB7X2adgIe87HtOmwUtGhnbizSZCjpFpEmJdzfnbFdg/hhSzqvL47nk1ujzA5JRKTJeH1xPABjugbSMcDD5GgaF6vVQu/W3vRu7c0/x0SwYf+hygp4VkExczemMndjKh7O9ozqHMCYroEMaNfEEvDiQtg83bYdfY+5sUiToqRbRJqch0eEMX9rOkt2ZrE55bAm8RERuQS2p+Xx845MrBZ4dESY2eE0alarhajW3kS19uaZqyJYv+8QP207mYB/syGVbzak4uniwKgTY8AHtPfBwa6RJ+BbZkBxPni3g3bDzI5GmhAl3SLS5LTzdePaHiHM3ZjKa4vj+d/t0WaHJCLS6FVUua/uHkx7P01kealYrRai23gT3cabf14Vwfq9ubYEfPsBsguKmbMhlTkbUvFqVpGAB9G/XYvGl4AbBsR8ZNuOvhusjez5Sb2mpFtEmqSHh4fx/eY0fo3PJnZvLlGtvc0OSUSk0dq0/xBLd2VhZ7Xw0HBVuc1iZ7XQp20L+rRtwTNjOxNbkYBvO0BOYTGz16cye70tAR/dOYArIwPp11gS8D3LISceHN2g+01mRyNNjJJuEWmSWrZoxg29Q5gRk8Krv+xm5t39zA5JRKTRen1JAgDX9QimjY+rydEI2BLwvm1b0LdtC6aO7UxMci4LtqWzaPsBcgqPMzM2hZmxKTRv5sDoLicS8LYtsG+oCfi6E1Xu7jeBs+YTkEtLSbeINFkPDgtj7oY0ft+Ty5rEHPq39zE7JBGRRmf93lx+jc/GXlXuesvOaqFfuxb0a9eC58Z1YV3yQRZszWDR9gMcPHKcGTEpzIhJwdvVkcs7BzAmMpC+bb0bTgKemwzxi2zb0XebG4s0SUq6RaTJCvZyYVJ0KP9bu49XF8fTr10LLBaL2WGJiDQqr/5iG8t9Q+9QQr2bmRyN/BE7q4X+7Xzo386H58bZKuDzt2Xwc2UCvp8ZMfvxdnVkdBdbAt6nTT1PwGM/AQzb5Gk++uFHLj0l3SLSpD0wtD2zYlPYsO8QK+OzGdLBz+yQREQajTVJOazdcxBHOysPDmtvdjhygeztrPRv70P/9j78a1xn1iXnMn9rBou2Z5B75Dhfr9vP1+v206IiAe8aSJ82LbCz1qMfsI8fgU3TbNt97jU3FmmylHSLSJPm7+HMLX1b8cnqZF5bHM/gcF9Vu0VEaoFhGJUzlk+KDiXYy8XkiORi2NtZGdDehwHtfXj+6s78vufkGPCDR44zfd1+pq/bj49bRQU8iOg23uYn4FtnQVEeNG8D7UeaG4s0WUq6RaTJu3dIO76O2c/W1DyW7MxiZIS/2SGJiDR4qxNziN17CEd7Kw8MVZW7MbG3s3JZmA+Xhfnwr6u78PueE2PAd9gmYfvq9/189ft+fNycuOJEBTyqtQkJuGGcnEAt+i4tE1Yf5afD4qmQuBhKjoF3W7j6XQjuWX37ggPw89OQvgly99h6L1zx4tmPv+0bmHsHdBgDN35dN8/hPCjpFpEmz8fNiVv7t+b9FUm8tjie4R39sJr9y7yISANmGEblWO6b+7TC38PZ5IikrjjYWRkY5svAMF+ev6YLa5NOTcCLmfb7Pqb9vg9f9xMJeGQgvS9VAp78K2TvBIdm0P1PdX8+uTDHDsGnl0ObgfCnueDaAg4mgYvX2R9TWgyuPjDoSfj93XMf/9A++OWf0LJ/rYZdE0q6RUSAuwe2ZdrafezMyGfRjgNcGRlodkgiIg3W8t1ZbE45jIuDHfcNaWd2OHKJONhZGRTuy6BwX/59bRfWJB1kwdZ0ft6RSXZBMf9bu4//rd2HX0UC3jWI3q2a190P3TEnqtzdbjx3IifmWP0GeAbDNe+d3Ne89bkf07wVXPGSbXvTV2dvV14G8+6CoU/BvrW2IQYmUh8LERGguasjt1/WBoDXF8dTVm6YHJGISMNkGAavnRjLPbl/K3zdnUyOSMzgYGdlcLgvL4/vRuzTI/j8tihu6BWCh7M9WQXFfLl2HxM+XEu/F5fy7A87iN2bS3lt/t97eD/s/sm2rWXC6qfdCyGoB8yeDC+3gw8ugw1f1M6xV74Err7Qc3LtHO8iqdItInLCHZe14YvfkknIKuTHLelc0yPY7JBERBqcX+Iy2Z6Wj6ujHfcMUpVbwNHeytAOfgzt4Md/ro3kt8QcFmzL4OcdB8jML+aLNXv5Ys1e/D2cuKJLIFd1DaRny4usgMd+AkY5tBkMfh1r78nIeSkoKCA/P7/ytpOTE05Op/0Ad2gvxH4K/R6AgY9D2kZY+Fewc4TuN9X85PvWwsZpcO/qmh+jlqnSLSJygqeLA3cPagvAm0sTKC0rNzkiEZGGpbz85Izltw1og7ero8kRSX3jaG9laEc//ntDNzb8YySfTenN9T1DcHe2r0zAx3+wlv4vLuO5H3ewYV8NKuDHj8KGL23bfe6p/SchfygiIgJPT8/KywsvvHBmI6McArvBiKm26963Qc9bYf1nNT9xcQF8ezeMe8s2RryeUKVbROQUUwa04dPVySTnHGHepjQm9A41OyQRkQZj4fYD7DpQgLuTPXcObGN2OFLPOdpbGdbRn2Ed/Sku7cLqBFsFfPGOTA7kF/H5b3v5/Le9BHo6c2VkIFdGBtIj1OuPK+Db5kDRYfBqCeGjL8lzkari4uIIDj7ZY/CMKjeAewD4dqi6zzccdv5Q8xPnJtuGFnw98eQ+40QR5Tlv+PN62wzpl5iSbhGRU7g52XPv4Ha8sHAXby1N4JruwTjaq1OQiMgfKSs3eH2Jrcp9x8A2eDVTlVvOn5O9HcM7+TO8kz/FpWWsij+RgMdlkpFXxKerk/l0dTJBFQl4V1sCbrGcloAbxskJ1KLuAqvdpX8ygru7Ox4eHuduFNoHDiZW3XcwCTwvouDhEw73ra26b9m/4XgBjH4JPEJqfuyLoKRbROQ0k/u15uNVyaQeOsacDSn8qU8rs0MSEan35m9NJzGrEE8Xh8qJKUVqwsnejhER/oyI8KeopIxVCTks2JrOkp1ZpOcV8cnqZD5ZnUywlwtXRgZwZWQg3SsS8H1rIHM72LtAj5vNfipyLv3uh09Hwa//hc7X2sZ0b/gCxr55ss2SZyE/A6778OS+jK226+OFcDTHdtvO0TZ238EZ/COqnsfZ03Z9+v5LSEm3iMhpXBzteGBoO577MY53liVyfc8QnB30S7mIyNmUlpXzxpIEAO4e1BYPZweTI5LGwtnBjpER/ow8kYD/Gp/Ngm0ZLInLJO3wMT5elczHq2wJ+Jiugdyf9TZeAF0nQDNvk6OXcwruBROnw9LnYOXLtuXARr9g+7erUJAJealVH/fhwJPbGZttwwk8W8Kj2y5J2DVhMQyjya+Lk5qaSmhoKCkpKYSEmNPlQETql6KSMob+dwUZeUU8OzaCKQNUtREROZtvNqTyxJwteLs68utfhuLmpLqO1K2ikjJWxmezYGsGS3dmcuR4GYEcZJXTw9hbyvmky1dE9x1IZLDnmV3Qpc4or6qePhFFRKrh7GDHA0Pb84/vtvPuiiQmRrXExVHVbhGR05WUlfPWUluV+55BbZVwyyXh7GDH5Z0DuLxzAEUlZazYnY112b+wzy1nbVkE/15vhfW/EertwpWRgVwVGUSXYA8l4GIKzQ4kInIWE3qHEtLcheyCYr76fZ/Z4YiI1EvfbEhlf+5RfNycmNyvtdnhSBPk7GDH6A6ejDq20Hb7snu5qmsgLg52pOQe48OVexj7zmoGv7KCFxfuYntaHursK5eSfooUETkLR3srDw0L4y9zt/L+yiRu6tMSV1VwREQqFZeW8c4y2+zD9w9ppx5BYp7tc+FYLniE0GPEn3jHzp5jx8tYsTuL+dsyWLYzi/25R/lgZRIfrEyipXczxnQNZExkIJ2DVAGXuqVvjyIi53Bdz2DeW5HI3oNH+WLNXh4Y2t7skERE6o3ZsSmkHT6Gv4cTN/VpaXY40lQZBqw7Mbt19J1gZ0txXBztuCIykCsiAzl6vJQVu0+MAd+Vyf7co7y/Ion3VyTRukUzrowMZEzXQCIClYBL7VPSLSJyDvZ2Vh4eEcajs7bw0a97uKVfK83KKyKCbSKrd5bbqtwPDm2vVR7EPCnr4MBWsHeGnrdW26SZo71tfe8TCfjyXdks2JbOsl1Z7D14lPdWJPHeiiTa+LhyZWQAYyKD6BTorgRcaoWSbhGRPzCuWzDvLk8iMauQT1cl8+jIcLNDEhEx3dfr9pOZX0yQpzMTokLNDkeasooqd+T481omrJmjva1reddAjhSXsmxXFj9ty2DZriySc47w7vIk3l2eRFsf18oKeMcAJeBSc0q6RUT+gJ3VwiMjwnjw6018tjqZ2wa0xquZo9lhiYiY5tjxMt5bkQTAn4eH4WSvKreYJD8d4r63bUffc8EPd3WyZ2y3IMZ2C+JIcSlLd2Xx09YMlu/OYk/OEd5Znsg7yxNp6+vKmBMJeAd/JeByYZR0i4ichyu7BNIxIJFdBwr46Nc9/GV0R7NDEhExzbTf95JTWEyotwvje2ktXjHR+s/AKIOW/SGw60UdytXJnnHdghjXLYjC4lKW7szkp20ZLN+dzZ7sI7y9LJG3lyXSzteVMV2DuKprIOH+7rX0RKQxU9ItInIerFYLj40M5+5pG/hizV7uuKwNLdyczA5LROSSKywu5YOVewB4aFgYDnZagVZMUloMG76wbfe5u1YP7eZkz9Xdg7m6e3BlAj5/awYr47NJyj7CW0sTeGtpAu393Cor4ErA5WyUdIuInKeREf50DfFka2oeH6xM4ukxEWaHJCJyyX25Zi+5R47TxseVa3sEmx2ONGU7voUj2eAeBB2vqrPTnJqAFxSVsHRnFvO3ZvBrfDaJWYW8uTSBN5cmEObnVrkMWZgScDmFfpoUETlPFoulchK1/63dR1Z+kckRiYhcWvlFJXz0q63K/fDwMOxV5RazGAas+8C2HXU72F2alUXcnR24pkcwn9zam/X/HMHrE7sxopMfjnZWErIKeWNJAiNf/5VRr6/kzSUJJGYVXJK4pH5TpVtE5AIMCfelZ0svNu4/zHsrknh2XGezQxIRuWQ+W51M3rESwvzcGNstyOxwpClLXQ/pm8DOCXrdZkoIHs4OXNsjhGt7hJBfVMKSuEwWbM3g14Rs4jMLic+M5/Ul8XTwd6+cLb2dr5spsYq5lHSLiFwAi8XC46M68KdP1vH1uv3cPagtQV4uZoclIlLn8o6W8OmqZAAeGRGOnVWzN4uJYk4sE9blenD1MTcWbAn4dT1DuK5nCHnHTiTg2zJYlZDN7swCdi8u4LXF8XQMcK8cA95WCXiToaRbROQC9W/Xgj5tvFmXnMvbyxJ54bpIs0MSEalzH6/aQ0FxKR0D3LmiS4DZ4UhTVnAAdnxn267lCdRqg6eLA9f3CuH6XrYEfHFcJgu2prMqIYddBwrYdaCAVxfH0ynQgzGRAVwZqQS8sVPSLSJygSqq3RM+XMuc9SncN7gdLVs0MzssEZE6k3vkOJ//ZqtyPzoyHKuq3GKm9Z9DeQmERENQD7OjOSdPFwfG9wphfK8Q8o6W8EvcARZsy2B1Qg47M/LZmZHPf3+JJyLQgzFdA7kyMpA2Pq5nPV5ZuUFMci5ZBUX4uTsT3cZbvU4aAFOT7gEvLiPt8LEz9t/StxXPX9OFopIy/rNgJz9uTed4aTmDwnx5/pou+LqfXKYn7fAx/vHtNtbuOYiroz3X9wrhL5d30MQeIlKnott4MzDMh1UJOby1LIH/3tDN7JBEROrMh78mceR4GV2CPRgV4W92ONKUlR6HDZ/btvvcY24sF8izmQM39A7lht6hHD56nF9OjAH/LTGHuIx84jLyeeXn3XQO8uDKSNss6K1PScAXbc/guR/jyMg7OZFroKczU8dGMLpLoBlPSc6TxTAMw6yTHywspuyU08cfKOTmT9cx466+9GvXgqe/3cbyXVn894ZuuDs78MwP27FaLMy9rz9g+6XnyjdX4evuxFNXdiSroJjHZ29hUlQofxnd8bzjSE1NJTQ0lJSUFEJCQmr9eYpI47Rp/yGufW8NVgsseWywuoaJSKOUXVDMoJeXc6ykjM+m9GZYRyXdYqKtc2DeneAWAI9uv2Szltelw0eP88uOTOZvsyXgZeUn86MuwR6MiQzCzcmeZ77fzumJW0WN+/2be9aLxFt5VfVMLQe3cHPCz9258rJ0VyatWjSjb1tv8otKmL0+hX9cFUH/9j5EhnjyyvhubNh3iI37DwHwa0I2CVkFvD6xO52DPBnawY/HRoYzbe0+jpeWm/nURKQJ6NGyOcM7+lFuwJtLE8wOR0SkTnywMoljJWV0D/ViaAc/s8ORpq5iArXel26ZsLrm1cyRCVGh/O/2aNY/PYKXro9kYJgPdlYL29PyeWnRLv5ZTcINVO577se4Ksm61C/1pg/28dJyvtuUxoTeoVgsFran5lFSZjCg/cnZCNv7uRHs5cLGfbake9O+Q3QI8KjS3XxwuC8FxaXEZ559Tbzi4mLy8/MrLwUFWj9PRGqmYt3uH7akn/NzR0SkIcrML+Kr3/cB8NjIcCwWjR0VE6VtgNRYsDpArylmR1Mnmrs6MjGqJdPu6EPs0yN44bpIIoM9zvkYA8jIKyImOffSBCkXrN4k3b/EHSC/qJTxvWzdELILi3G0s+LpUvUXLB83R7ILiyvb+Lg5nna/U+V9Z/PCCy/g6elZeYmIiKjNpyIiTUiXYE9Gdw7AMOCNJfFmhyMiUqveW55IcWk5Ua2bMzDM/GWZpIlb95Htust14N74hzl4uzpyY3RL7hzY9rzaZxUU/XEjMUW9SbpnxaYwJNwXfw/nOj/XU089RV5eXuUlLi6uzs8pIo3XoyPDsVjgp20H2JGeZ3Y4IiK1Iu3wMWbEpAAVn3OqcouJCrNhxzzbdnTDmkDtYvm5n19+dL7t5NKrF0l36qGj/JaYw8So0Mp9vm5OHC8rJ+9YSZW2OYXH8T1RzfZ1cyKn8Php9xdX3nc2Tk5OeHh4VF7c3d1r66mISBPUIcCdq7oGAfD6Yo3tFpHG4Z1liRwvK6df2xb0b6cqt5hswxdQdhyCe0FIL7OjuaSi23gT6OnM2X72smCbxTy6jfelDEsuQL1IuuesT6WFmxPDOp6cnKNLiCcOdhbWJOZU7kvKLiTt8DF6tmoOQI9Wzdl9IL8y0QZYlZCDu5M9Yf6aRVhELp1HRoTZZjHfmcmWlMNmhyMiclFSco8yZ72tyv3YqHCTo5Emr6wE1n9q225iVW4AO6uFqWNtw2FPT7wrbk8dG6H1uusx05Pu8nKDbzakcn3PkCpra3s4OzChdyj/XrCTNUk5bEvN48k5W+jZ0oueLW1J96AwX8L83Hl01mbi0vNZGZ/Nq7/s5pZ+rXCytzPrKYlIE9TO141regQD8Opije0WkYbtraUJlJYbDAzzIaq1qmdisp0/QEEGuPpB52vMjsYUo7sE8v7NPQnwrNqFPMDTud4sFyZnZ292AKsTc0g7fIwJvc9cx+2fV0Vgtezkvq82cry0nEHhPjx/TZfK++2sFj6d0pt/fLed697/jWaO9lzfM5jHRuoXWRG59B4eHsb3m9P5NT6b9Xtz6a0vqiLSACXnHGHepjQAfaeS+qFiArXet4H92YeQNnajuwQyMiKAmORcsgqK8HO3dSlXhbv+sxiG0eQXdNMi7iJSW/42dyszY1Po17YFM+7ua3Y4IiIX7NFZm/l2UxrDOvrx2ZQos8ORpi59M3w0GKz28Mh28FBFtz5TXlU907uXi4g0Jn8eHoajnZW1ew6yJinnjx8gIlKPJGYV8N1mVbmlHok5UeWOuEYJtzRYSrpFRGpRsJcLk6JtKzG89ks86kwkIg3JG0sSMAy4vLM/XYI9zQ5HmrojObDtG9t2n6Y3gZo0Hkq6RURq2QND2+Nkb2X9vkP8mqBqt4g0DLsO5DN/awYAj4xQlVvqgY1fQlkxBHaHEA11kIZLSbeISC3z93Dm5r6tAHjtl92qdotIg/D6iZUXxnQNpFOgh8nRSJNXVgqxJ5YJ63MPWDRZmDRcSrpFROrAfUPa4eJgx5bUPJbuzDI7HBGRc9qelsfPOzKxWOCR4WFmhyMCu+ZDfho084HO15kdjchFUdItIlIHfNycuLV/awBeWxxPebmq3SJSf1VUua/uFkSYv7vJ0YhwcgK1XlPAwfmcTUXqOyXdIiJ15J5BbXFzsicuI5+fdxwwOxwRkWptTjnM0l1Z2FktPKyx3FIfHNgO+34Dix30vt3saEQumpJuEZE60tzVkdsHtAZs1e4yVbtFpB567USV+9oewbTxcTU5GhEg5kPbdaex4BlsbiwitUBJt4hIHbpjYFs8nO1JyCpk/tZ0s8MREali/d5cfo3Pxt5q4aFhGsst9cDRXNg627bd515zYxGpJUq6RUTqkKeLA3cNbAvY1r8tLSs3OSIRkZMqqtw39A6hZYtmJkcjAmz8H5QWQUAktOxrdjQitUJJt4hIHbvtsjY0b+ZAcs4Rvt2UZnY4IiIArE06yJqkgzjaWXlQVW6pD8rLTi4TFq1lwqTxUNItIlLH3JzsuXdwOwDeWpZAiardImIywzAqZyyfFB1KsJeLyRGJALsXQt5+cPGGyPFmRyNSa5R0i4hcApP7tcbHzYmU3GPMWZ9qdjgi0sStTswhZm8ujvZW7h/S3uxwRGzWfWC77nUrOOiHIGk8lHSLiFwCLo523D/EVu1+Z1kCxaVlJkckIk2VYRi8+outyn1zn1YEeGoNZKkHMuNg7yqwWKH3HWZHI1KrlHSLiFwiN/VpSYCHM+l5RcyMSTE7HBFpolbszmZzymGcHazcO6St2eGI2MR8ZLvuOAa8Qs2NRaSWKekWEblEnB3seGCYrRvnO8sTOXZc1W4RubQMw6icsfzWfq3xc1eVW+qBY4dg6yzbdvQ95sYiUgeUdIuIXEITe9smLMouKOar3/eZHY6INDGL4zLZlpaHq6Md95yY4FHEdJu+gpKj4NcZWl9mdjQitU5Jt4jIJeRob+Wh4bZq9/srkzhSXGpyRCLSVJSXn6xyTxnQGm9XR5MjEsG2TFjMx7btPndrmTBplJR0i4hcYtf1DKFVi2bkHjnOF2v2mh2OiDQRC7cfYNeBAtyd7LlroMZySz2R8Asc3gfOXhA5wexoROqEkm4RkUvMwc7KIyPCAPjo1z3kF5WYHJGINHZl5QZvLLFVuW+/rA1ezVTllnpi3Ye26563gGMzc2MRqSNKukVETDCuWzDt/dzIO1bCZ6uTzQ5HRBq5+VvTScgqxNPFgTsGtjE7HBGb7N2wZ7ltmbCou8yORqTOKOkWETGBndVSWe3+dFUyh48eNzkiEWmsSsvKeXNJAgB3D2qLh7ODyRGJnFCxTFj4FdC8lbmxiNQhJd0iIia5sksgHQPcKSgu5eNVe8wOR0Qaqe82p7Mn5wjNmzlwa//WZocjYlOUB5tn2Lb73G1uLCJ1TEm3iIhJrFYLj44MB+Dz3/ZysLDY5IhEpLEpKSvnraW2Kve9g9vh5mRvckQiJ2z+GkqOgG9HaDPY7GhE6tQFf/KWlxv8nnyQ2ORDpB0+yrGSclq4OhIR5MFl7X0I8nKpizhFRBqlURH+RAZ7si0tjw9/3cPfr+xkdkgi0ojM3ZDK/tyj+Lg5cks/dd+VeqK8/GTX8mgtEyaN33kn3UUlZXz86x6+WrePw0dLiAjywN/dGWcHK3sPHuGXHQd4at42Bob58NDwMHq2bF6XcYuINAoWi4XHRoZz2xex/G/tXu68rA1+Hs5mhyUijUBxaRlvL0sE4L4h7WnmqCq31BOJSyB3Dzh5QteJZkcjctKxw7BrPuxbC3n7oeQYNPOBwK7Qbji07FOjw573p+/Q/66gZ8vmvHhdVy4L88HB7sye6amHjvL95nT+/PUmHhzWnhujW9YoKBGRpmRIB196tPRi0/7DvLciiWfHdTY7JBFpBGavTyXt8DH8PZz4Ux99J5N6JObEMmE9bgYnN3NjEQHIz4Dl/4Ftc8A9AIJ7QUBXsHeGY4cgeRWseRs8Q2HIX6HL9Rd0+PNOuqfdEU17P/dztglp3owHhrbn7kFtST987IICERFpqiwWC4+P7MDNn67j63X7uXtQWw3VEZGLUlRSxrsnqtwPDG2Ps4OdyRGJnJCTaKt0Y4HoO82ORsTmw4HQ7Ua4eyX4day+Tckx2LUAfn8f8tJgwEPnffjznkjtjxLuCrsPFOBgZ6VVC9fzDkJEpKkb0L4F0W28OV5WzjvLE80OR0QauK/X7edAfhFBns5MjAo1OxyRkyqXCbscvNuaG4tIhQdiYNTzZ0+4ARxcIHI83LnE1kvjAtTK7OWFxaV8vW4/V7+zmive/LU2Diki0qTYqt22mcxnx6aQknvU5IhEpKE6dryM91YkAfDgsDCc7FXllnqiuMA2aznYJlATqS+aeddp+4uaUWPdnoPMWp/Cou0H8Pdw5vLOAfzr6i4Xc0gRkSarT9sWDAzzYVVCDm8tTeCVG7qZHZKINEDTft9LTmExod4u3NA7xOxwRE7aPAOOF0CLMGg71OxopD7IT4fFUyFxsa37tndbuPpdCO5ZffuCA/Dz05C+yTYZX5974YoXq7bZ8AVsmQlZcbbbgd1h+FQI6XV+MR3NPZlU56XChi+h9Bh0uBJa9a/Js7zwpDuroIhvNqQyOzaFwuJSxkQGcry0nI9u6UWY//l1QRcRkeo9NjKcVQk5zNuUxv1D29PGR0N1ROT8HSku5YOVewB4aFhYtRPfipji9GXCrHptNnnHDsGnl0ObgfCnueDaAg4mgYvX2R9TWgyuPjDoSfj93erb7F1tm+gs9GXbRGi/vQHTroUHfgePoLMfO3MHfD0J8lPBux2M/wy+uh5KjoLFCmvfgwn/g05XXfBTvaCk+44vYolJzmVoRz+eGRvB4HA/7KwWpq/bf8EnFhGRM/Vo2ZxhHf1YtiuLN5fE88akHmaHJCINyBdr9pJ75DhtfFy5tkew2eGInLRnGRxMAEd36H6j2dFIfbD6DfAMhmveO7mveetzP6Z5K7jiJdv2pq+qb3P9J1Vvj3sb4n6APSvP/dpb/Az4R8D1H9sq5V9PhPBRMPZt2/0Ln4TVr9co6b6gn5hWxGczISqUR0eGM6yjP3ZWLWQvIlLbHjsxtvv7LekkZBaYHI2INBT5RSV89Kutyv3w8DDsVeWW+mTdiSp3jz+Bk3rHNnYFBQXk5+dXXoqLi89stHshBPWA2ZPh5XbwwWW2ruG1reQolJeAS/Nzt0vbCMP+CS37wqh/Q0EGRN1p65VhtUL0PZCTUKMQLujTeM69/ThSXMrYt1dz9bu/8eWJX1NFRKT2dAn25PLO/hgGvLGkZh/uItL0fL56L3nHSmjv58bYbufoQilyqeXugYRfbNtRd5kbi1wSEREReHp6Vl5eeOGFMxsd2guxn9q6ct8yD3rfAQv/enKyvdqyeKpt7e22Q87d7tghcPO3bTu5gaMrOHudvN/FyzYnQQ1cUPfyni2b07Nlc54ZG8H8LRnMXp/CvxfEUW4YrErIIdDLBTeni5qbTUREgEdHhvNLXCYLtmXwQHo+EUEeZockIvVY3tESPlltq3I/MiJMvRGlfon5BDCg/QjwaW92NHIJxMXFERx8coiLk5PTmY2Mclule8RU2+3AbpC1E9Z/Bt1vqp1AVr0G2+fClAXg4PzH7S2Wc9+uoRplyM0c7ZkQFcqEqFCSsguZHZvC+yuTeGnRLgaG+fDJrVG1EpyISFPVMcCDMZGBzN+awWuL4/nk1t5mhyQi9dgnq/dQUFRKxwB3ruwSaHY4IicVF8KmabbtPveaG4tcMu7u7nh4/EHBwD0AfDtU3ecbDjt/qJ0gfnvLNm588ncQcJ4rbH13H9g52rZLi2D+o+DQzHa7rOY9vC96sE87XzeeurITvz81nLdu1IQ/IiK15ZER4VgtsGRnJltSDpsdjojUU7lHjvPZ6mTgxOeGqtxSn2ydCcX5ti7E7YabHY3UJ6F94GBi1X0Hk8Az9OKPvfoN+PUVuHnu2ZcfO133m8DVF5w9bZeuE8E98ORtV1/oVrNJAGutL7id1cLlnQO4vHNAbR1SRKRJa+/nxjXdg5m3KY3XFsfz5e3RZockIvXQh78mceR4GZ2DPLi8s7/Z4YicZBgQ87FtO/ouLRMmVfW7Hz4dBb/+Fzpfa5vIbMMXMPbNk22WPAv5GXDdhyf3ZWy1XR8vhKM5ttt2juDX0bZ/9euw/P9ss5h7tYSCTNt+R1fbWO2zOXUW9VqmAdgiIvXYwyPC+H5LOivjs9mwL5derbzNDklE6pHsgmL+t2YfYFv5wFJL4w9FakXySsjeBQ6utTdGVxqP4F4wcTosfQ5WvmxbDmz0C9B1wsk2BZmQl1r1cR8OPLmdsRm2zQHPlvDoNtu+2M9sXcFnT676uMF/g6FP1clT+SNKukVE6rFWLVy5oVcIM2NTePWXeL6+q6/ZIYlIPfLByiSOlZTRPdSLYR39zA5HpKp1J6qT3W+ydc8VOV2H0bbL2Vz7/pn7ns079zErku96RH08RETquQeHtcfBzsKapIOsTTpodjgiUk9k5hfx1e+qcks9dWivbR1mgOi7TQ1FxGxKukVE6rmQ5s2YFNUSgNcW78YwDJMjEpH64L3liRSXltO7VXMGhvmYHY5IVbEnlglrO9Q2I7VIE3be3csXx2We90FHRmgSDxGR2vTA0PbMWp9C7N5DrErIYVC4r9khiYiJ0g4fY0ZMCgCPjVKVW+qZ40dg4/9s233uMTcWkXrgvJPuu6etr3LbAhin3a6w54UxFxeViIhUEeDpzM19WvHZb8m8ujiegWE++pIt0oS9uzyR42Xl9G3rTf92qnJLPbN1NhTlQfPWEDbK7GhE/tiun86/bccrL/jw5510J5+SSK9OyOHFRTt58vKO9GzpBcDG/Yd59ZfdPHl5h7McQURELsZ9Q9oxI2Y/W1IOs2xXFsM7qVeRSFOUknuU2bG2Kvfjo/S9S+oZw4CYj2zbUXeB1c7ceETOx8zTZte3WGyv5VNvV5h66IIPX6PZy/81fwf/uTaSqNYnl64ZHO6Li4MdT83bytLHh9TksCIicg6+7k5M7t+KD1fu4dVf4hnawQ+rVdVukabm7WUJlJYbDAzzqfJdTKRe2LsasuLAoRn0uNnsaETOz7OHT24nLYclU2H4MxASbduXGgPL/m3bVwM1mkht38GjeDg7nLHf3dme1EPHahSIiIj8sXsGtcPV0Y64jHx+3nHA7HBE5BLbm3OEuRvTANuM5SL1TsyJZcK6TgQXL1NDEamRRU/B6Jeg/Qhw9rBd2o+Ay/8PFv61RoesUdLdLcSLfy+II7uguHJfdkEx//fTTrqFetUoEBER+WPero7cflkbAF5fEk9ZuWYyF2lK3lyaQFm5wbCOfvRo2dzscESqOrwfdi2wbWsCNWmoDiVXv668k4ftNV4DNUq6Xx7flaz8Yga8uIzBryxn8CvLGfDiMjLzi3j5+q41CkRERM7PnQPb4uFsT3xmIfO3ppsdjohcIolZBXy/2VblfnSEqtxSD8V+CkY5tBkEfp3MjkakZoJ6ws9/h8Ksk/sKs2DxPyG4V40OWaMx3a19XFn0yEBWJeSQlF0IQHs/Ny5rr9l0RUTqmqeLA3cNbMuri+N5c0kCYyIDsber0W+oItKAvLEkgXIDRkX4ExlSTRVGxEwlx2Djl7btaFW5pQG7+h2YdTO83hk8gm378tPAux1Mml6jQ9Yo6QawWCwMCvcluo03TvZWJdsiIpfQbZe14bPfktmTc4TvNqczvleI2SGJSB3adSCfBdsyAHhUY7mlPtr2DRw7BJ4tocMVZkcjUnMt2sF9ayBpGeQk2Pb5hkPboVVnMb8ANSqNlJcbvLU0gT7/t4TOU38mJdc2edqrv+xmVmzN+rmLiMj5c3Oy557B7QB4a2kCJWXlJkckInXpjcUJGAaMiQykU6CH2eGIVGUYsO7EBGrRd2qZMGn4LBZoPxx6TbHNT9BuWI0Tbqhh0v32skS+2ZDKU1d0wsHu5MnD/d2ZeWLdSBERqVuT+7XCx82R/blH+WZDqtnhiEgd2Z6Wx6IdB7BY4JERYWaHI3Km/WshcxvYu0CPW8yORuTilJfDypfh1Y7wf0FwaK9t/7J/w8b/1eiQNUq6521K5YXrIrmmRzB2p2T8nQI9SMoqrFEgIiJyYZo52nPfkPYAvL00geLSMpMjEpG68MaSeADGdQsizN/d5GhEqlFR5e56AzTT2vHSwP36CmyeDiP/BXaOJ/f7dbq0SfeBvCJatWh2xn7DMCjV8jUiIpfMn/q0xN/DifS8Imapp5FIo7M55TBLdmZhtcDDw1XllnooLw12/mjb1gRq0hhsmQFj34SuE6oOlfCPhJz4Gh2yRkl3mL8bsXtzz9j/07YDdA7SOCMRkUvF2cGOB4faqt3vLEukqETVbpHG5PXFti941/UMoa2vm8nRiFRj/adglEGryyCgi9nRiFy8ggzwbnvmfqMcykprdMgaJd0PDQvjme938P6KJMoNWLQjg7/N3cq7yxN5SL/CiohcUhOiQgn2ciGroJivft9ndjgiUks27MtlZXw29lYLDw3T9yuph0qKYMMXtu0+d5saikit8e0A+9aeuT/uewjsWqND1ijpHtU5gE9vjeK3xByaOdrx2uJ4ErMK+eTW3gwM861RICIiUjNO9nY8NNxW7X5/RRJHimv2K6yI1C+v/mKrct/QO4SW1QzrEzHdjnlw9CB4hECHMWZHI1I7Bv8VfnoSVr9uq27v/BF++DOs+i8M/kuNDlnjdbqj23jz1Z19avpwERGpRdf1DOG9FUnsO3iUL9fu5f4TE6yJSMO0Nukga5IO4mBn4YGhej9LPXTqMmFRt4NdjdMKkfql4xi4aSasfAkcmsHy/4PAbnDjTNvSYTWgd4eISCPgYGfl4eFhPDZ7Cx/9uodb+rbC3dnB7LBEpAYMw6gcyz0pqiUhzVXllnooJQYyNoOdE/ScYnY0IrWrVX+Y/H2tHe6Cku6BLy87r3ar/lKzXwBERKTmru4ezLvLE0nKPsJnq/fysNbzFWmQfks8SMzeXBztrapyS/0Vc6LKHXkDuLYwNxaReu6Cku7UQ8cI9nLh6u5BtHB1qquYRESkBuysFh4ZEc6fZ2zik9V7mNK/NZ7NVO0WaUgMw+DVxbsB25KAAZ7OJkckUo38DNukUqAJ1KTxeOM8J0l7ZOsFH/qCku53buzJ7PUpfLIqmSEdfJnQO5ShHfywWi0XfGIREal9YyIDeXd5IrsOFPDxqj08cXkHs0MSkQuwYnc2m/YfxtnByn1D2pkdjkj1NnwO5aUQ2tc21lWkMTi8H7xCT/TeqN3JwS8o6R7TNZAxXQM5kFfENxtSeH5+HH//dhvX9ghhYlQobXxcazU4ERG5MNYT1e57v9rA578lc/tlbfB2dTQ7LBE5D4Zh8NqJsdyT+7XGz11VbqmHSoth/We27T73mBuLSG264XPY9BWsfRfaj4Aet0DYKLDWaMGvKmo0kVqApzMPDgvjwWFh/L7nIG8sieejX5PY9M9RF9yV8UBeES8u3MmK+GyOHS+jdQtXXrmhK11DvAB4fPYW5m5MrfKYQeG+/O/26Mrbh48eZ+oPO1i6MwuLBa7oEsDUsZ1xddI8cSLS9Fze2Z8uwR5sT8vnw5VJPHVlJ7NDEpHzsDguk21peTRztOOeQW3NDkekeju+gyPZ4B4EncaaHY1I7el8re2Snw6bp8PPT8H8R6DrROg5GVrUvPdRjbPSopIyFm7PYHZsKptTDnNlZCDOjhf2K0De0RKuf38N/dq14Ivbomnh6khyzhE8Xaom7oPDfXnlhpN97J3s7Krc//DMzWQVFDPtjmhKyw2enLOFp+Zt460be9T06YmINFgWi4XHRoZz+xfr+XLtXu4Y2EYVM5F6rrzc4PUlCQDcNqA1Ldw0d47UUxUTqPW+Hew0b4g0Qh5BMOhJ22XvaljxIqx5C/6yB1ya1+iQF5x0b9p/iNnrU5i/NYOW3s2Y0DuUD27uVaPJet5fmUSQlzP/veHkWJBQ7zOXxXC0t571C2NiVgEr47P54cEBldXxZ8d15rYvYnl6TCf8PfRFU0SanqEd/Oge6sXmlMO8tzyJZ8d1NjskETmHRTsOsDMjH3cne+4aqCq31FOp6yFtA9g5Qq8pZkcjUndKimyTBW6aZnvdR1xjW7O7hi4o6R752koOHjnOuG5BzLq7HxFBHjU+McCSnZkMCvPl/ukbWLcnF38PZ27p14obo1tWaff7noP0en4xni4O9GvXgidGdaD5iTGKG/cdxsPZvjLhBrisvQ9Wi4VN+w8zukvARcUoItIQWSwWnhjVgZs/XcfX6/Zzz+C2BHq6mB2WiFSjrPzkuty3X9YGr2aah0HqqXUnqtxdrge32p1oSqReSF0PG/9nG0bRvJVtXPfEaTWucFe4oKQ7MbuQZg52zNuYyreb0s7absvUUed1vP25R/lq3T7uvKwN9w9pz9bUPJ79YQcOdlbG9woBYHAHX0Z3CSDU24V9B4/yys+7mfJ5DPPuH4Cd1UJ2YTE+p3XBsrez4uXiQHZhcbXnLS4uprj45H0FBQXnFa+ISEMyoH0Lott4E5OcyzvLEvnPtZFmhyQi1Zi/NZ2ErEI8nO25/bI2ZocjUr2CTNjxrW07WsuESSP0bh/bfAWRN8BtCyCg9r43XVDS/cr42l0SwDAMIoM9+cvojgB0CfYkPrOA6ev2VSbd47oFVbbvGOBBpwAPBr2ynN/3HGRAe58anfeFF17gueeeu/gnICJSj1ksFh4fGc7Ej35n9voU7h3crtohPCJintKyct48MZb77kFtz5jXRqTe2PAFlJdASBQE9zQ7GpHal70bHF1hywzYMvPs7f6274IPfUFJd0UiXFv83J0J83Ovsq+dnxsLt2ec9TEtWzTD29WRvQePMKC9D75uTuScVtEuLSvn8LESfM8yCclTTz3FY489Vnk7LS2NiIiIi3gmIiL1U5+2LbisvQ+rE3N4e1kCL9fyj6cicnG+35zOnpwjNG/mwJQBqnJLPVV6/OQyYdFaJkwaqWveq7NDn3fSbRgGFoulVk/eq1Vz9uQUVtmXnH2EYK+zjzvMyDvGoaPHKydW69nKi/yiUral5hEZ4gnAmqSDlBsGPVp6VXsMJycnnJxOJuT5+fkX+UxEROqvx0aFszoxh7kb07h/SHta+7iaHZKIACVl5by51FblvmdwO9y01KnUVzt/gMID4OYPEVebHY1I3eh+U50d+rzX+Br5+q/8sCWd46Xl52yXnHOEp7/dxnsrEv/wmHdc1oZN+w/z7vJE9uYc4fvNacyI2c/kfq0BOFJcyv/9tJON+w+RknuU3xJzuOt/62ndwpVB4bau5e393Bkc7svf5m1lc8ph1u/NZeoPOxjbNUgzl4uIAD1bNmdoB1/Kyo3KL/giYr65G1LZn3sUHzdHJvdrZXY4Ime37pRlwuw10Z80QoZRp4c/759UnxvXmRcX7uKf323nsjAfugZ74u/hjJO9lbxjJSRkFbJ+by7xmYVM7t+Km/v+8X8e3UK9+PCWXry8aDdvLk0gtLkLz4yN4JoewQDYWS3szMhn7oZU8otK8HN3ZlC4D4+N7ICT/cm1ut+c1J1nvt/Bnz7+HavFwuguAVoeR0TkFI+N7MDy3dl8tzmNB4a2o/1pQ3tE5NI6XlrO28tsBYp7B7ejmaOq3FJPpW+C1BiwOkCv28yORqRuvNsHBv8FOo079w9LB5Ng7TvgGQoDHzt7u9NYDOPC0vrYvbnM35JOzN5DpB06SlFpOd7NHOkc5MGgcF+u6R5cozW7zZSamkpoaCgpKSmEhNTuuHURkfri7v+t55e4TMZ0DeTdmzQJjoiZpv2+j39+tx1/DydWPjkUZwe7P36QiBm+vQ+2fG2b0fn6T8yORuq5BptX7VkBi6fCob3QbigE9QD3QLB3gmOHbZOs7V8L2bsg+i4Y+Dg4e5734S/4Z9Wo1t5Etfa+0IeJiIjJHh0Zzi9xmSzYmsEDQ/KJCPIwOySRJqmopIx3T1S5HxjaXgm31F+F2bD9G9t2n3vNjUWkLrUdAveshH1rYcc82DoH8vZDSRE0awGBXaHbjdD1hhqt2a2+TCIiTUSnQA/GdA1kwdYMXl8Sz8eTe5sdkkiTNCNmPwfyiwjydGZiVKjZ4Yic3cYvoOw4BPWEEP2fIU1Aq362Sy0774nURESk4Xt0RBhWCyyOy2Rr6mGzwxFpco4dL+Pd5UkAPDgsrMocNSL1SlkJxJ5YJqyPlgkTuRhKukVEmpD2fu5c0902WeVri+NNjkak6fnq933kFBYT0tyF8b0a0HhHaXp2/ggF6eDqC52vNTsakQZNSbeISBPz0PAw7KwWVuzOZsO+Q2aHI9JkHCku5f2Vtir3Q8PDcLTX1zCpx2I+sl33us02mZSI1Jg+7UVEmpjWPq6M72mrsL22eLfJ0Yg0HV+u3UvukeO0btGM604sjypSL2Vstc3UbLW3rc0tIhelRkn39rQ8dh3Ir7z9y44D3PW/9by8aBfHS8trLTgREakbfx7eHgc7C78lHuT3PQfNDkek0SsoKuGjX/cA8PCIMOztVPeQeizmQ9t1p3HgEWhuLCKNQI0+8f/+7TaSs48AsP/gUf48YxMuDnb8tC2DFxburNUARUSk9oU0b1Y5a/Jrv8RjGIbJEYk0bp+t3svhoyW083VlXDdVuaUeO3LQtlwSaAI1aZrSN0PmjpO3dy2AGTfBkuf4//buOz6qOt//+GsmvYdAGpBCEoIE6RAEQUCaZVXUK65dcAUU14K71+vv7q5673p1XRV1RbFQ7CiKrmVdpXepoSOQAKEHCKT3zPn9cSAYISEkmZyZ5P18POaRkzNnzrznTAbyyeec75eKsnrtsl5F997jhVXzu3635QipHcJ47baevHhLd/699Wi9goiISNN6aKh5TemafSdZnn7C6jgizVZuUTnvLje73I8OT8bDbrM4kUgtNrwHlaUQ3R1i+lmdRqTpffsoZKebyyf3wufjwMsPtn8F8/5Sr13Wq+g2AMfppsiK9BMM7RQBQHSoHycL61f9i4hI04oK8eWOfrEAvKhut4jTvLt8D/klFVwSFcS1XXWqrriwygpYO91cTp0ANv2BSFqg7AyI6moub/8K4gbAf0yH0W/Cjq/rtct6Fd1d24Xwj4W7mbvhIKv3ZnPlJWbRfeBkEW0CNbqhiIi7eGBIIr5edjYdyGHhz8esjiPS7JwqLGPG8r2A2eW2q8strmznvyDvIPi3hktvtjqNiDUMw7wB7FkMHUeay8HtoKh+4+DUq+j+829S2HYoj6f+uY1JQ5OIbxMAwPdbjtA7rlW9goiISNOLCPLlnv7xgDlvt7rdIo3rraV7KCyrpEvbYEZ1ibQ6jkjtVp8eQK3XPeDla20WEau07QFL/w6bZsO+FWeL7pxMCIio1y496/OglLbB/PDYFeesf/KaznjqL7giIm5lwuBEPvwpk22H8/hh21GuulSnv4o0huP5pby3ch8Ak0ckY9OpuuLKjm6FzOVg84C+91mdRsQ6Vz0Hc8ebA6hd8QdonWiu3/5PiEmt1y7r1eke9MJCTp3n2u3SCgdDX1pcryAiImKNsABvxg3sAMCUebtxONTtFmkMby3JoLi8ku4xoVWX4om4rDVvm187/wZC2lubRcRKUV3hwVXw5AEY8l9n14/4X7jxrXrtsl5F98FTxVSe5xTEsgoHR3NL6hVERESs87uBCQT5erIzK59vtxyxOo6I28vKK+GDnzIBdbnFDRSdhM2fmcupmiZMWrhXupmfiV+rKIF/9KrXLi/q9PJ527OqlpfuOk6Qr1fV95UOg5UZJ4hp5V+vICIiYp0Qfy/uH5TAy/N28cr8XVxzaRSeHvX6u6yIAG8uzqC0wkGfuFZc0bGN1XFEapf2AVQUQ+Sl5kjNIi1Zzn5wVJ67vrIM8g7Xa5cXVXSP/2AdADbg8Tmbqt3nZbfTvpUf/31t53oFERERa429PJ4ZK/ay53gh/9x4mJt76/RCkfo4nFPMx6v3A+pyixtwVMLad83lfpomTFqwn/91djljAfgEn/3eqIQ9S6BVXL12fVFF997nrgVg4N8W8vVDAwkL8K7Xk4qIiOsJ8vViwhWJ/O3fP/Pqgt1c36MtXup2i1y01xelU1bp4LKEMAYkqcstLm7Xv83Onl8r6HqL1WlErDP7dvOrzQZfTqx+n4cXhMbCyGfrtet6jV6+/Ikr6/VkIiLi2u4ZEMf05XvYf7KIL9Yf5LepsVZHEnErB04W8dnaAwBMHtHJ4jQidVA1Tdjd4OVnbRYRKz2dY359pSvcvxgCWjfarutcdM9csZfbUmPx9fJg5oq9tW479vIODQ4mIiJNz9/bk4mDE/nrdzt4bcFubuzVDh9PD6tjibiNfyzcTYXDYFDHNqR2CLM6jkjtju2AvUvAZoe+v7M6jYhreHRLo++yzkX39OV7Gd2jHb5eHkxfXnPRbbOp6BYRcWd3XhbHO8v2cDi3hE/XHuDu/vFWRxJxC/tOFPLFhkMAPDYi2eI0InVwZpqwTteYp86KNLW8wzDvKUifB+XFEJYAN0yFdjWMEp5/FH74bzicBif3QL+JcPXz52637UtY+Kx56UTrRBj+DCSPrDnHT9Og973g5Wsu1+ayibXffx51Lrp/eUq5Ti8XEWm+fL08eGhoEn/+5zZeX5jOmD4x+Hqp2y1yIa8t2E2lw2Bop3B6xbayOo5I7YpzYNNsc7mfpgkTCxSfgumjoMMguOML83Tu7AzwC635MRWlENAGrvgj/DT1/NvsXw2f3wfDn4Lkq2DLHPN67QlLITLl/I/5aSp0G3O66K5hvwDYnFt0i4hIyzGmbwzTluzhUE4xH/6Uye8GJVgdScSlpR8r4KuNZpdb13KLW9j4EZQXQUQKxA+yOo20RMtfgZB2MPqNs+taxdf+mFZxcPXfzOW0D8+/zeo3IWk4XP6I+f2Vf4KMReaZHde9cv7H/PKUcitPL/+lSofB5+sPsCI9m+zCUhyO6vd/Mv6yxsgmIiIW8fH04PdXJvFfc7cwbUkGt/eLxd9bf6cVqcmrC3bjMGBESiRd24dYHUekdo7Ks6eWp96vacKk0eXn55OXl1f1vY+PDz4+PtU32vk9JA2Dz+6GfSsgONocW6D3vQ178gNrof+k6uuShsHP3zVsvw1Qr9+gnvlmG5+vP8jQSyJIjgzChj6oIiLNzc292/PG4gz2nyzivZWZPDAk0epIIi5p59F8vt18GDDn5RZxebvnwal94BsC3W61Oo00Qykp1U/jfuqpp3j66aerb3RqH6ydbhbIgx6HQxvg+yfAwxt63F7/Jy/IgsCI6usCws31deGoNM8E2bMECo+D8asO873fXnSkehXd32w6zNTbezH0kogLbywiIm7Jy8POI8M68vicTby1NIM7L4slyNfL6lgiLueV+bswDLi2azSdo4OtjiNyYWtOTxPW8y7wDrA2izRL27dvp127dlXfn9PlBrOYbdvTvPYaILq7OaL+uhkNK7ob6vsnYOPH5sBrESmNciZIvYpuLw87ca39G/zkIiLi2kb3bMfUxensOV7IzBX7eHhYR6sjibiUbYdz+X7rUWw2eGS4Ph/iBo7vgoyFgE3ThInTBAUFERx8gT9CBkVB+K/GwAhPhh1fN+zJAyOh4Fj1dYXHzfV1sfULuGVW7aOdXyR7fR50/6AEZq7Yh2EYjRZERERcj4fdxqPDzdNl31m2h9yicosTibiWKfN2AXB997YkRwZZnEakDs5cy518FYRpml+xUEw/yE6vvi47A0JiGrjfvub887+UsQja963b4z28zanLGlG9Ot1r951k1Z5sFu86RnJEEJ4e1Vvub93Vp1HCiYiI9X7TNZqpC9PZmZXPu8v38PhIjcwsArDpQA7zdxzDbkNngYh7KMmDTZ+Yy5omTKzW/0GYPhKWvghdbjSv6V4/C6579ew285+GvCNw01tn1x3ZbH4tK4CiE+b3Ht4QcYm5vt8DMOsaWPkP6DjK7FwfTqu+39oMeMgcAf2aFxttkMF6Fd3Bfl6M6hLVKAFERMS12e02HhvRkYkfbmDG8r2MvbwDYQHeVscSsdzLp7vcN/ZsT2J4oMVpROpg48dmodKmEyQMsTqNtHTtesOtH8GCZ2DJC+Z0YFc9Z86XfUZ+FuQerP64t34xxd2RjeY83CGx8Njpqb5i+8HN78LCv8KC/4GwRPjtxzXP0f1r+3+CvcvMAQcjOoP9VyXzbz+66Jdar6L7xVu61+dhIiLipkZ1iaJL22C2Hc7jrSUZPHlNZ6sjiVhqfeZJluw6jofdxiPqcos7cDg0TZi4nk5Xmbea3Pjmueuezr3wfrvcaN7qwzcEOv+mfo+tgSZdFRGRC7LZbDw+Mplxs9bx3qp93DeoAxFBvlbHErHMmS73Lb3bE6vBZcUdZCyAkxngEwzdb7M6jYjrGv1Go+/yoorubk//gO08fxUL8vWkQ5sAxl+RwKCO4Y0WTkREXMfQThH0iAll44Ec3lycwVPXdbE6koglftqTzYr0bLw8bDx0ZZLVcUTqZvWZacLuBB9dDiHSlC6q6P5LDb9g5RWXs/VQLvfNWscbd/RieEodh2MXERG3cabbfdf0NXy0ej/jr0ggOsTP6lgiTcowjKou9619Y2jfSl1ucQPZGZA+D00TJlKL52OB81x24RsMrZNgwO8h8cp67fqiiu7/6N2+1vtT2gbzxuJ0Fd0iIs3UwKQ2pMaHsWbfSaYuSuevo7taHUmkSa1Iz2bN3pN4e9p5aKiu5RY3seYd82vHEdA60dosIq7qqufPv74kFw5vhI9vhTHvQ6erL3rXjXpN95WXRPCPhekX3lBERNySzWZj8shkfvv2T3y69gATByeq0ycthtnl3gnAHf1iiQrRuAbiBkrzIe1DczlV04SJ1KjH7bXfH9UVlr1cr6LbXs9I51VW6cDLo1F3KSIiLuayhNZcntSa8kqDfyzQH1ql5Vi86zgb9ufg62XngSHqFoqb2DQbyvLN02PreWqsiADJV8GJXfV6aKNWyJ+uPUBK2+DG3KWIiLigySM6AfD5hoPsO1FocRoR5zMMgymnr+W+u3+8Ru8X92AYv5gmbDzY1RwTqbfKUvDwrtdDL+r08v/9dvt51+eXlLP1UB57TxTy2YT+9QoiIiLuo3dcK4Z0CmfxzuO8tmA3L9/aw+pIIk41f8cxNh/Mxd/bgwlXJFgdR6Ru9iwyO3PegZomTKShNnxgnmJeDxdVdG87fP6JyAN9vBjUsQ1v3dWbmDBd2yci0hJMHpHM4p3H+XLjIR4cmkhSRJDVkUScwuE4O2L5vQPiaR3oY3EikTo6M01Yj9vNEZhFpGb//n/nX1+aC0c2mbMAjP1XvXZ9UUX37PHqYouIiKlb+1BGpEQyb3sWU+bvZurtvayOJOIUP2w7yo4jeQT6eDJeXW5xFyf3wq4fzOXU8dZmEXEHRzeff71PECQMhVs/hFbx9dp1o45eLiIiLcvkEcnM257Fd5uP8NDQPDpHq5MizUulw2DKfLPLPW5gB0L963c9n0iTW/suYEDiMGij6e1ELujeb522a42mICIi9dY5Ophru0UDVA0yJdKcfLv5MLuyCgj29eS+gR2sjiNSN6UF5vWnAP00TZiI1VR0i4hIgzw2vCN2G/y4PYstB88/9oeIO6qodPDq/N0A3D8ogRA/L4sTidTR5k/N61BbdYCkEVanEWnxVHSLiEiDJEUEcUOPdgC8PG+nxWlEGs8/Nx5mz4lCWvl7MVZdbnEXhgFr3jGXNU2YiEvQp1BERBrskWEd8bDbWLTzOOszT1kdR6TByisdvLbQ7HJPGJxIoI+GwRE3sXcpHN8BXgHQ8w6r04gIKrpFRKQRxLcJ4OZeZrdb13ZLczB3w0Eys4toE+jN3f3jrI4jUndr3ja/dv8t+IZYm0VEABXdIiLSSH5/ZUe8PGwsTz/B6j3ZVscRqbeyCgevLUgHYOLgRPy91eUWN3EqE3aenkdY04SJuAwV3SIi0ihiwvwZ0ycGgJd+3IVhGBYnEqmfz9Yd4FBOMRFBPtx5mbrc4kbWvguGAxKGQMQlVqcRkdNUdIuISKN56MokvD3trNl3kuXpJ6yOI3LRSsoreX2h2eWeNDQJXy8PixOJ1FFZEWx431xO1TRhIq5ERbeIiDSa6BA/bk+NBdTtFvf0yZr9HM0rITrEl9+mxlgdR6TutsyBkhwIjYXkUVanEZFfUNEtIiKN6sGhifh62dl4IIdFO49ZHUekzorLKnljcQZgnrXh46kut7gJw4DVb5nLfe8Hu352RVyJim4REWlUEUG+3NM/HoCX56nbLe7jw58yOZ5fSvtWftzSW11ucSOZK+DYNvDyh153WZ1GRH5FRbeIiDS6CYMTCfD2YOuhPH7YlmV1HJELKiytYNoSs8v98JUd8fbUr0jiRs50ubuNAb9W1mYRkXPofxQREWl0YQHejL28A2DO2+1wqNstru29VfvILiwjvrU/N52ec17ELeQcgJ+/M5c1TZiIS1LRLSIiTnH/oASCfD3ZmZXPd1uOWB1HpEb5JeW8vXQPAI8M74inh349EjeybjoYlRA/CCK7WJ1GRM5D/6uIiIhThPh78buBCQC8Mn8Xlep2i4uauWIfOUXlJIYHcH13dbnFjZQXw/r3zOV+miZMxFWp6BYREacZNzCeUH8vMo4X8s+Nh6yOI3KO3KJy3llmdrkfHZ6Mh91mcSKRi7D1Cyg+CSExkHy11WlEpAYqukVExGmCfL0Yf4XZ7X51wW7KKx0WJxKpbvryPeSXVNApMohru0ZbHUek7qpNE3YfeHham0dEaqSiW0REnOqe/vG0DvAmM7uIL9YftDqOSJVThWXMWLEPgMdGdMSuLre4k/0/wdHN4OkLve6xOo2I1EJFt4iIOFWAjycPDEkE4B8L0ymtqLQ4kYjpraV7KCitoEvbYEZ1ibI6jsjFWXO6y931FvAPszaLiNRKRbeIiDjdnZfFERnsw6GcYj5be8DqOCKcKCjlvZX7AHhseDI2m7rc4kbyDsP2r81lDaAm4vJUdIuIiNP5enkwaWgSAK8vSqekXN1usda0xRkUl1fSvX0IwzpHWB1H5OKsm2FOExY7AKK6Wp1GRC5ARbeIiDSJW/vG0DbEl6y8Uj5avd/qONKCHcsr4YOfMgF4bIS63OJmyktg3Uxzud94a7OISJ2o6BYRkSbh4+nB74d1BODNxekUlVVYnEhaqjcWZ1Ba4aB3XCsGJ4dbHUfk4mz7EopOQHA7uOQ3VqcRkTqwfG6Bo7klPP/9DhbvOk5xWSXxrQP4+y3d6NY+FADDMJgybxefrD1AXnE5feJb8dfRXenQJqBqHzlFZTz19TYW7DiGzQZXXxrFU9d1IcDH8pcnIiK/8B+92/Pm4gz2nyzi/VWZTBycaHUkaWEO5xTz8ekzLR5Xl1vcjWGcHUCtzzjw8LI2j4jUiaWd7tyicm5+cyWeHnZmjU1l/uTB/Pe1nQnxO/sPyLQle5i5ch/Pjr6UryZdjp+XJ3fPWF3tesBHZm9kV1YBH9yXyox7+7Jm70menLvFipckIiK18PKw8/DpbvdbSzIoKFW3W5rW1EXplFU66NchjP6Jra2OI3JxDq6Dw2ng4QO977U6jYjUkaVF95tLMmgb6suLt3SnR0woMWH+XJEcTlxrs4ttGAYzVuzl91cmMbJLFJ2jg3n51u5k5ZXy4/YsANKP5bNk13H+dnNXesa2om98GE9f34VvNh8mK6/EypcnIiLnMbpHWxLaBHCqqJyZy/daHUdakAMni/hsnTl6/mR1ucUdrZ5mfr30ZghoY20WEakzS4vu+Tuy6NoulAc/Wk/v/53HNa8u45M1ZwfXOXCymOP5pVyedPYflWBfL3rEhLIh8xQAGzJzCPb1rDodHWBgUhvsNhtp+3Oa6qWIiEgdeXrYeWS42e1+e9kecovKLU4kLcXrC9MprzQYmNSGfgnqcoubyT8K278ylzWAmohbsbTo3n+yiA9XZxLfOoD3xqVy52VxPP31Nj5ffxCA4wVmpzo80Kfa48IDfTheUHp6m1La/Op+Tw87oX5eVdv8WmlpKXl5eVW3/Pz8xn5pIiJSi+u6tSU5MpD8kgreXb7H6jjSAuw7UcjnG8zfLyaPTLY4jUg9rJsJjgqI6Qdte1qdRkQugqVFt2EYXNo2mP+86hIubRfC7f1iuS01lo9WZzr1eZ977jlCQkKqbikpKU59PhERqc5utzF5hFn4zFi+l5OFZRYnkubutQW7qXQYDO0UTq/YVlbHEbk4FWXm3NwAqepyi7gbS4vuiCBfOkYEVVuXGBHI4ZxiAMIDfQHO6VgfLyit6n6HB/pw4lf3V1Q6yCkuP6dDfsaTTz5Jbm5u1W379u2N8npERKTuRnWJokvbYArLKnlraYbVcaQZSz9WwFcbDwHmvNwibmf7V1B4DAKjIOUGq9OIyEWytOjuHdeKPScKqq3be7yQdqF+AMSE+REe5MPK9Oyq+/NLytl4IIdeceZfqXvFhZJXUsGWg7lV26zMyMZhGPSMDT3v8/r4+BAcHFx1CwoKOu92IiLiPDbb2W73+yszOZ5//kuCRBrq1QW7cRgwIiWy2hgwIm5j9elpwvrep2nCRNyQpUX3fQM7kLY/h6mL0tl3opB/bjzEJ2v2c3f/eMD8hWzc5R34x8LdzNuexc9H85j82SYig30YmRIJQFJEEIOTw/mvuZvZeCCHdftO8tTX27iuW1sig30tfHUiInIhV14SQY+YUIrLK3lzsbrd0vh2Hs3n282HAXhsuLrc4oYOrYdD68DDW9OEibgpS4vu7jGhvHVXb77eeJiRryzltQW7+ct1KYzu2a5qm4mDE7h3QDxPzt3C9a+voKisgvfGpuLr5VG1zau/7UFieCB3vPMTY2eupU9cK567qasVL0lERC7CL7vdH67O5GiupnqUxvXK/F0YBlzTNYqUtsFWxxG5eKvfNr92uRECI6zNIiL14ml1gGGdIxnWObLG+202G5NHdmLyyE41bhPq781rt2kURxERdzSoYxv6xrdi7b5TTF2Uzv+OvtTqSNJMbDucy/dbj2KzwaPqcos7KjgGW78wl1MnWJtFROrN0k63iIiI2e02/7A6e+1+Dp4qsjiRNBdT5u0GzkxRp/FbxA2tnwWOcmjXB9r3tjqNiNSTim4REbFc/8TWDEhsTXmlwesL062OI83ApgM5zN+Rhd0GjwzvaHUckYtXWX52mrB+6nKLuDMV3SIi4hIeH2me/jtn/UH2nSi0OI24uynzdwEwumc7EsMDLU4jUg87vob8IxAQASmjrU4jIg2goltERFxC77gwBieHU+kweG3BbqvjiBtbn3mKxTuP42G38cgwdbnFTZ2ZJqzPWPD0tjaLiDSIim4REXEZZ7rdX208RPqxAovTiLt6ed5OAG7p3Z641gEWpxGph8Mb4cBqsHtCn3FWpxGRBlLRLSIiLqNb+1BGpETiMMypnkQu1k97slmRno2Xh42HrkyyOo5I/aw5PU1YymgIirI0iog0nIpuERFxKWfm7f528xF+PppncRpxJ4Zh8PI88481t/aNoX0rf4sTidRD4QnY8rm5rAHURJoFFd0iIuJSOkcHc23XaACmzFO3W+puZUY2a/aexNvTzqSh6nKLm1o/CypLIboHtO9rdRoRaQQqukVExOU8OrwjNhv8sC2LrYdyrY4jbsAwDF760byW+/bUWKJD/CxOJFIPlRW/mCZsIths1uYRkUaholtERFxOx8ggbujeFqDqdGGR2izedZwN+3Pw9bLz4NBEq+OI1M/P30LeIfBvA5feZHUaEWkkKrpFRMQlPTI8GQ+7jYU/H2PD/lNWxxEXZhhG1aUId10WR0SQr8WJROrpzABqve8FTx9Lo4g0ibzD8MX98Ld4+GskvNEfDm2o/TF7l8G0QfC/4fBqD0j7qPr9jkpY+Fd4pau5z1e7w5IXwDCc9SouSEW3iIi4pA5tAripZztA13ZL7ebvOMbmg7n4e3swcbC63OKmjm6BzBVg89A0YdIyFJ+C6aPAwwvu+AImrYaRfwW/0Jofc2offDwGOlwBE5fDZQ/C17+H9Plnt1k+BdZOh2tehElrYPgzsOJVWP2Ws19RjTwte2YREZELeHhYR75MO8Sy3SdYvSebfgmtrY4kLsbhODti+T0D4mkdqO6guKkzBUHK9RDSztosIk1h+Svmz/roN86uaxVf+2PWzYDQOBj1rPl9eCfYvwpWvQFJw811B9bAJddA8qjT+4yDrZ/DofWN/QrqTJ1uERFxWTFh/tzaNwaAl+btwrDw1DBxTT9sO8qOI3kE+ngyflCC1XFE6qfoJGyZYy6napowcX/5+fnk5eVV3UpLS8/daOf30LYnfHY3vJAI0waao/fX5sBaSBhSfV3SMDi49uz3MamwZymcSDe/P7oF9v8EHUc05CU1iIpuERFxaQ9dmYS3p501e0+yIj3b6jjiQiodBlPmm13ucQM70CrA2+JEIvW04X2oKIGorhB7mdVpRBosJSWFkJCQqttzzz137kan9pmngYclwl1zoc998P0TsPHjmndckAWB4dXXBURAaR6UF5vfD5xsDkT4eh/4n9bm9d+XPQDdxjTa67tYOr1cRERcWnSIH7enxjJr5T5emreTy5NaY9M0OgJ8t+UIu7IKCPb15L6BHayOI1I/lRWw9l1zOXWCpgmTZmH79u20a3f2Mgkfn/Nc+mM4zE738KfM76O7w7Ed5inkPW6v/5Nvm2ueOXLzuxDR2ex0//u/ICi6YfttAHW6RUTE5T04NBFfLztp+3NYvPO41XHEBVRUOnjldJf7/kEJhPh5WZxIpJ52fQ+5B8AvDLr+h9VpRBpFUFAQwcHBVbfzFt1BUeY12b8Ungy5B2vecWAkFPzq94DCY+ATDF5+5vfz/gIDHzM/T5FdoPtv4bJJsOzlhr2oBlDRLSIiLi8iyJe7+8cD5rzdurZbvt50mD3HCwn19+Ley+OtjiNSf2cGUOt9z9miQaQliOkH2enV12VnQEhMLY/pC3uXVF+XsQja9z37fXnRuWeM2O1mZ90iKrpFRMQtTLgiAX9vD7YcyuXH7VlWxxELlVc6eHXBbgAmXJFIkK+63OKmsrbDvmVgs5vXs4q0JP0fNAdAW/qiWWxvnmMOpJZ6/9lt5j8Nc38xuGCfcea14D/+GY7vgjXvwLYvzX2dkXw1LH0Jdv0ApzJhxzewaip0/k0TvbBzqegWERG30DrQh7GnO5pT5u3C4VC3u6Wau+EgmdlFtA7w5p4BcVbHEam/Nae73JdcC6G1dPdEmqN2veHWj2DrF/BGf1j6Alz1XPUBz/Kzqp9u3ioebv8M9iyCaZfDqtfh+n+cnS4M4JoXIOUG+O5xmJoKP/4Jeo+FoX9qspf2axpITURE3Mb9gxJ4f2UmPx/N519bj/Cbbm2tjiRNrKzCwWsLzNMRHxiSiL+3fpURN1V8CjZ/Zi73m2htFhGrdLrKvNXkxjfPXddhEExcXvNjfILg6ufNm4tQp1tERNxGqL839w0yR6meMm8Xlep2tzifrTvAoZxiwoN8uPMydbnFjaV9aF57GtEF4i63Oo2IOJGKbhERcSvjBnYgxM+LjOOF/HPjIavjSBMqKa9k6iKzyz1pSCK+Xh4WJxKpJ0eleS0qQL/xmiZMpJlT0S0iIm4l2NeLCYMTAHh1wW7KK60bjVSa1uw1+zmSW0J0iC+/TY21Oo5I/e36AXIywTcUuo654OYi4t5UdIuIiNu5p388rQO8ycwuYu6GWubzlGajuKySqYszAHjoyiR1ucW9nRlArdfd4O1vbRYRcToV3SIi4nYCfDx5YEgiAK8tSKesQt3u5u6j1Zkczy+lfSs/bumtUZ7FjR3fCXsWm9OE9f2d1WlEpAmo6BYREbd052VxRAT5cCinmE/XHbA6jjhRYWkFb57ucj98ZUe8PfXri7ixNW+bX5OvhlYaDFCkJdD/WiIi4pZ8vTyYNDQJgKkL0ykpr7Q4kTjL+6syyS4sI661Pzf2amd1HJH6K8mFjZ+Yy/3GW5tFRJqMim4REXFbv02NoW2IL0fzSvh49X6r44gT5JeU89ZSs8v9yLCOeHnoVxdxY2kfQXkhhF8CHQZbnUZEmoj+5xIREbfl4+nBQ1d2BOCNxRkUl6nb3dzMXLGPnKJyEsIDuKGHutzixhwOWHt6mrBUTRMm0pKo6BYREbd2S5/2xIT5caKglPdX7bM6jjSi3OJy3lm2B4BHhyfjYVeRIm4sfT6c3AM+IdDtVqvTiEgTUtEtIiJuzcvDzsOnu93TlmRQUFphcSJpLNOX7SG/pILkyEB+0zXa6jgiDbN6mvm1553gE2htFhFpUiq6RUTE7d3Ysx0JbQI4VVTOzOV7rY4jjeBUYRkzVuwD4LHhydjV5RZ3dmI3ZCwAbJCqacJEWhoV3SIi4vY8Pew8Mtzsdr+zbA+5xeUWJ5KGenvZHgpKK0iJDmZUlyir44g0zJrT13Inj4KwBGuziEiTU9EtIiLNwnXd2pIcGUheSQXTT18HLO7pREEps053uSePUJdb3FxJHmz82FxO1TRhIi2Rim4REWkW7HYbjw1PBmDGin2cKiyzOJHU11tLMigur6R7+xCGdY6wOo5Iw2z6BMryoXVHSBhqdRoRsYCKbhERaTZGdYkiJTqYgtIK3lqqbrc7OpZXwvurMgF4bEQyNk2rJO7M4YA1b5vL/SaAXb96i7RE+uSLiEizYbfbmDzC7Ha/t3Ifx/NLLU4kF+uNxRmUVjjoFRvK4ORwq+OINMyehZCdDt5B0P23VqcREYuo6BYRkWZlWOcIuseEUlxeybQlGVbHkYtwJLeYj1fvB+DxkZ3U5Rb3t/p0l7vnHeATZG0WEbGMim4REWlWbLaz3e4Pf8okK6/E4kRSV68vTKes0kG/DmEMSGxtdRyRhsnOgN0/mst977c2i4hYSkW3iIg0O1d0bEOfuFaUVjiYuijd6jhSBwdOFvHZugOAOWK5utzi9ta+CxiQNALaJFmdRkQspKJbRESaHZvNxuSRZrf7kzX7OXiqyOJEciGvL0ynvNJgYFIb+iWoyy1urrQA0j40l/tNsDaLiFhORbeIiDRLAxLb0D+hNeWVBq8vVLfblWVmF/L5hoOAOWK5iNvbPBtK8yAsERKHWZ1GRCymoltERJqtx093u+esP0hmdqHFaaQmry7YTaXDYEincHrHtbI6jkjDGMbZAdRS79c0YSKioltERJqvPvFhDE4Op9Jh8OqC3VbHkfNIP1bAV2mHAKoGwBNxa3sWw4md4B0IPW63Oo2IuAAV3SIi0qydKeS+SjtE+rECi9PIr722YDcOA4Z3jqRb+1Cr44g03JrTXe7ut4FviLVZRMQlqOgWEZFmrXtMKMM7R+IwULfbxew8ms83mw8D8NiIjhanEWkEp/bBzu/N5dTxlkYREdeholtERJq9M93ubzcfZufRfIvTyBmvLtiFYcDVl0bRpa06gtIMrHkHMCBhKITrcgkRManoFhGRZi+lbTDXdI3CMGDKvF1WxxFg2+Fc/rXlKDabRiyXZqKsENI+MJf7TbQ2i4i4FBXdIiLSIjw6PBmbDf697ShbD+VaHafFmzLPPNX/um5tSY4MsjiNSCPY/BmU5EKreOg4wuo0IuJCVHSLiEiLkBwZxPXd2wLqdltt88Ec5u/Iwm6DR4brWm5pBgwDVr9lLve9H+we1uYREZeioltERFqMR4Z1xG6DBT8fI23/KavjtFgvn/6jx+ie7UgMD7Q4jUgj2LcMju8AL3/oeafVaUTExajoFhGRFiMhPJCbe7UHzhZ+0rTWZ55i8c7jeNhtPHylutzSTJzpcnf/LfiFWhpFRFyPim4REWlRHh7WEU+7jWW7T7Bm70mr47Q4Z07t/49e7YlvE2BxGpFGkLMfdv7LXNY0YSJyHiq6RUSkRYkJ82dM3xgAXvpxJ4ZhWJyo5Vi9J5vl6Sfw8rDx0JVJVscRaRxr3wXDAR2ugIjOVqcRERekoltERFqch4Ym4e1hZ/Xek6zMyLY6TotgGAYvne5yj+kTQ0yYv8WJRBpBeTFseN9cTp1gbRYRcVkqukVEpMVpG+rH7f1iAXW7m8rKjGzW7D2Jt4ddXW5pPrbMgeJTEBILna62Oo2IuCgV3SIi0iI9OCQRH087G/bnsHjXcavjNGuGYVQNXHd7v1iiQ/wsTiTSCAwDVr9tLqf+TtOEiUiNVHSLiEiLFBHsy9394wBzcC91u51nya7jrM88hY+nnQeHJFodR6RxZK6ErC3g6Qc977I6jYi4MBXdIiLSYk0cnIi/twebD+Yyb3uW1XGapV92ue/uH0dEsK/FiUQayZrT04R1uwX8w6zNIiIuTUW3iIi0WK0Dfbh3QDxgztvtcKjb3dgW7DjG5oO5+Ht7MGGwutzSTOQehB3fmssaQE1ELkBFt4iItGjjr0ggyMeTn4/m86+tR6yO06w4HGe73PcMiKdNoI/FiUQayboZYFRC3ECIutTqNCLi4lR0i4hIixbq7819gzoA8Mr83VSq291oftx+lO1H8gj08WT8oASr44g0jvISWD/LXO433tIoIuIeVHSLiEiLN25gB0L8vEg/VsDXmw5ZHadZcDgMpszbDcC4y+NpFeBtcSKRRrL1CyjKhuD20Olaq9OIiBtQ0S0iIi1esK8X468wO7Gvzt9NRaXD4kTu79stR9iZlU+Qryf3qcstzYVhnB1Are994OFpbR4RcQsqukVERIB7B8TTOsCbfdlFzN2gbndDVDoMXplvXst9/6AEQvy8LE4k0kgOrIEjm8DDB3rdY3UaEXETlv55bsq8Xby6YHe1dQnhASx8fAgAt761itV7T1a7//Z+sfzfjV2rvj+UU8yfvtzCqj3ZBHh7cnPv9vznqE54eujvCSIiUncBPp5MHJzIs//awasLdjO6Zzu8PfV/SX38c+Mh9hwvJNTfi7GXx1sdR6TxrJ5mfu16CwS0tjaLiLgNy8+JSY4M5MPf9av63tNe/Rec21JjeGxEctX3fl4eVcuVDoNxM9cSHuTDFw8M4Fh+KY9/tglPu43/vOoS54cXEZFm5c7L4nh72R4O5RTz2boD3HlZnNWR3E5FpaPqD+rjr0ggyFddbmkm8o7Ajq/NZQ2gJiIXwfI/4XvY7UQE+Vbdwn410Iqvl0e1+3/5n/fS3cfZfSyfKbf2oEvbEIZ2imDyiGQ+WJVJWYWuxxMRkYvj5+3BpCHmXNKvL0ynpLzS4kTuZ+6GQ2RmF9E6wJt7+sdbHUek8aybAY4KiO0P0d2tTiMibsTyonvfiUJSn53PoBcW8sjsNA7lFFe7/58bD9Pzf35k5JQl/O3fP1NcdvYXoLTMU3SKCiY86Oy8n4OTw8kvrWBXVn6Nz1laWkpeXl7VLT+/5m1FRKRl+W1qLNEhvhzNK+GTNfutjuNWyirOdrkfGJJIgI/lJ9SJNI6KUlg/01xOVZdbRC6OpUV3j9hQXrylO++NS+Wvo7ty4GQRY6atoqC0AoAberRjyq09+GT8ZTw4JIkvNxzi0U/Tqh5/vKCUNoHVO+NtAn2q7qvJc889R0hISNUtJSXFCa9ORETcka+XBw9dmQTA1EUZ1f7YK7Wbs/4Ah3KKCQ/y4Y5+OjVfmpFtX0LhcQhqC52vszqNiLgZS4vuoZ0iuLZbNJ2jgxmcHM7MsankFZfz3ebDgDlo2uDkcC6JCmZ0z3a8PKY7P2zLIjO7sEHP++STT5Kbm1t12759e2O8HBERaSZu6R1D+1Z+nCgo5f1V+6yO4xZKyit5fWE6AJOGJOLn7XGBR4i4kdWnpwnrMw48NE6BiFwcy08v/6UQPy86hAewL7vovPf3iA0FqLo/PNCHEwVl1bY5cbrDHR7oQ018fHwIDg6uugUFBTVCehERaS68Pe08MqwjANOWZFSdgSU1+3TtAY7klhAd4stvU2OtjiPSeA6ug8MbwMMbet9rdRoRcUMuVXQXllaQmV1ERND5C+bth/MAqu7vGdeKnUfzqgptgGW7TxDk40nHyEDnBxYRkWbrxp7tSGgTwKmicmat2Gt1HJdWUl7J1EWnu9xDk/D1UpdbmpEzXe5Lb4bAcGuziIhbsrTofva77fy0J5sDJ4tYn3mSCR+sx8Nu4/rubcnMLuS1BbvZcjCXAyeLmLc9i8mfbSK1Qxido4MBuKJjOB0jgnjs041sP5zHkl3HeenHndzVPw4fT/2HLyIi9efpYeeR4Wa3++2le8gtLrc4kev68KdMjuWX0i7UjzF9YqyOI9J48rPM67lBA6iJSL1ZOqzokdwSHv4kjZyicsICvOkT34ovHxxA60AfSiscLE8/wYwVeykqq6RtiC9XXxpVNbgNgIfdxvR7+/Cnr7Zy05sr8Pf25OZe7Zj8i3m9RURE6us33dry+sJ0dh8rYPryvfr/5TyKyip4c3EGAA8PS8Lb06VOohNpmPUzwVEO7ftCu15WpxERN2Vp0f367TX/49U21I/PJvS/4D7at/Jn1tjUxowlIiICmH/cfWxEMg9+tIEZy/cydkA8rQK8L/zAFuS9lZlkF5YR19qfm3q1tzqOSOOpKDPn5gboN9HaLCLNVd5hmPcUpM+D8mIIS4Abptb+R669y+CH/wfHf4bgdnDFH6HnHQ3frxNpAk0REZFaXNUlis7Rwew4ksfby/bwxFWXWB3JZeSXlPPW0tNd7is74uWhLrc0Izu+hoIsCIyEztdbnUak+Sk+BdNHQYdBcMcXENAasjPAL7Tmx5zaBx+PMWcSuPld2LMEvv49BEVC0vD679fJVHSLiIjUwm63MXlEMve/v45ZK/Zx38AOtKllhoyWZNaKfeQUlZMQHsDonu2sjiPSuFZPM7/2GQeeOsNFpNEtfwVC2sHoN86uaxVf+2PWzYDQOBj1rPl9eCfYvwpWvXG26K7Pfp1Mf5IWERG5gOGdI+jePoTi8kqmnb5+uaXLLS7nnWV7AHh0eDIedpvFiUQa0aENcHAt2L2g91ir04g0Tzu/h7Y94bO74YVEmDYQ1s+q/TEH1kLCkOrrkoaZn9eG7NfJVHSLiIhcgM1mXtsN8MFPmWTllVicyHrTl+8lr6SC5MhAftM12uo4Io1rzdvm1y43mqetishFyc/PJy8vr+pWWlp67kan9sHa6RCWCHfNhT73wfdPwMaPa95xQda5U/cFREBpnnntdn3362QqukVEROpgcHI4veNaUVrhqJqTuqU6VVjGjOXm3OWPDU/Gri63NCcFx2HrF+ZyvwnWZhFxUykpKYSEhFTdnnvuuXM3MhwQ3R2GP2V+7TMWet1zdgDD+nLWfhtARbeIiEgd2Gw2Hh9pdrtnrznAoZxiixNZ551leygoraBzdDCjukRZHUekca2fBZVl0LYXtO9jdRoRt7R9+3Zyc3Orbk8++eS5GwVFmddk/1J4MuQerHnHgZHmH8Z+qfAY+ASDl1/99+tkKrpFRETqaEBiG/ontKas0sHrC3dbHccS2QWlzFq5D4DJI9TllmamshzWTTeXNU2YSL0FBQURHBxcdfPxOc8ApDH9IPtXZ45lZ0BITM07jukLe5dUX5exCNr3bdh+nUxFt4iIyEU40+2es+4g+7OLLE7T9KYtyaCorJJu7UMY3jnC6jgijWvHN5B/BALCoctoq9OING/9HzQHQFv6olkUb55jnmmSev/ZbeY/DXN/cZlHn3HmNds//hmO74I178C2L819Xcx+m5iKbhERkYvQJz6MK5LDqXAYvLqgZXW7j+WV8P6qTAAeG5GMzaYutzQzZwZQ6z0WPDU1oIhTtesNt35kjqHwRn9Y+gJc9Rx0G3N2m/ys6qeFt4qH2z+DPYtg2uWw6nW4/h9npwur636bmObpFhERuUiTRySzdNdxvkw7yINDE0kMD7Q6UpN4Y3EGpRUOesWGMiQ5/MIPEHEnRzaZ8/3aPc1umog4X6erzFtNbnzz3HUdBsHE5Q3bbxNTp1tEROQi9YgJZXjnCBwGvDq/ZXS7j+QW8/Ga/QBMHtFJXW5pflaf7nKn3ADBmgZPRBqPim4REZF6ODNv9zebD7PzaL7FaZxv6qJ0yiocpHYI4/Kk1lbHEWlchdmwZY65nKppwkSkcanoFhERqYcubUO4+tIoDANemb/L6jhOdfBUEZ+uPQCYp9aryy3Nzob3oLLUnNM3JtXqNCLSzKjoFhERqSdzMDH4futRth7KtTqO07y+MJ3ySoPLk1pzWYK63NLMVFbA2tPThKVOAP1RSUQamYpuERGRekqODOL67m0BmDKveXa7M7MLmbPeHDl28ulT6kWalZ3fQd5B8G8Nl95sdRoRaYZUdIuIiDTAI8M6YrfBgp+Pkbb/lNVxGt1rC9KpdBgMTg6nd1yY1XFEGt+ZAdR63wtevpZGEZHmSUW3iIhIAySEB3JTr/YAvNzMut0Zxwv4Mk1dbmnGjm6FzOVg84A+91mdRkSaKRXdIiIiDfTIsI542m0s232CtftOWh2n0bw6fzcOA4Z3jqR7TKjVcUQa35q3zK+dfwMh7azNIiLNlopuERGRBooJ8+eWPjEAvPTjTovTNI5dWfl8s/kwAI+N6GhxGhEnKDoJm09PE9ZvorVZRKRZU9EtIiLSCH5/ZRLeHnZ+2nOSleknrI7TYK/M34VhwNWXRtGlbYjVcUQaX9oHUFEMkV0htr/VaUSkGVPRLSIi0gjahvpxW+rpbve8XRiGYXGi+tt2OJd/bTmKzQaPDte13NIMOSphzbvmcr/xmiZMRJxKRbeIiEgjmTQ0CR9PO+szT7Fk13Gr49TbK/N3A/Cbbm3pFBVkcRoRJ9j5PeTuB79W0PUWq9OISDOnoltERKSRRAT7ctdlcYA5krk7drs3H8xh3vYs7DZzgDiRZunMAGq97gEvP2uziEizp6JbRESkEU0ckoi/twebD+Yyf8cxq+NctCmnpz0b3aMdSRGBFqcRcYJjO2DvUrDZoa+mCRMR51PRLSIi0ojaBPpw74B4wBzJ3OFwn273+sxTLNp5HA+7jYfV5Zbmas3b5tdO10BorLVZRKRFUNEtIiLSyMZfkUCQjyc/H83n+61HrY5TZ2e63Df3akd8mwCL04g4QfEp2DTbXO43wdosItJiqOgWERFpZKH+3owb2AGAKfN3UekG3e7Ve7JZnn4CLw8bv79SXW5pptI+gvIiiEiB+EFWpxGRFkJFt4iIiBPcN6gDIX5epB8r4JtNh62OUyvDMHj5dJd7TJ8YYsL8LU4k4gSOSlj7jrmcqmnCRKTpqOgWERFxgmBfL8ZfkQDAqwt2U1HpsDhRzVZlZLN670m8PexMGppkdRwR59g9D07tA98Q6DbG6jQi0oKo6BYREXGSewfEExbgzd4ThcxNO2R1nPMyDIOXTne5b+8XS9tQTZ8kzdTqaebXnneBt8YsEJGmo6JbRETESQJ8PJk42Ox2v7ZgN2UVrtftXrLrOOszT+HjaefBIYlWxxFxjuO7YM8iwAap91udRkRaGBXdIiIiTnTXZfGEB/lw8FQxc9YfsDpONYZhVI1YftdlcUQE+1qcSMRJqqYJuxpaxVsaRURaHhXdIiIiTuTn7VHVQX59YTol5ZUWJzprwY5jbDqYi5+XBxPV5ZbmqiQXNn1iLqeOtzaLiLRIKrpFRESc7LbUWKJDfDmSW8LsNfutjgNUH7H8ngHxtAn0sTiRiJNs/BjKCqBNJ0gYYnUaEWmBVHSLiIg4ma+XBw9daY4K/vqiDIrLrO92/7DtKNuP5BHg7cGE06OsizQ7DsfZU8v7aZowEbGGim4REZEmcEvvGNq38uNEQSkf/LTP0iwOh8GUebsBGDewA60CvC3NI+I0GQvg5B7wCYFuv7U6jYi0UCq6RUREmoC3p52Hh3UEYNqSPRSUVliW5bstR9iZlU+Qrye/G6gutzRjq98yv/a8A3wCrc0iIi2Wim4REZEmclPPdnRoE8DJwjLeW7nPkgyVDoNX5pvXct8/KIEQfy9Lcog43Yl0SJ8H2KDv76xOIyItmIpuERGRJuLpYeeR093ut5fuIa+kvMkzfL3pEBnHCwn192Ls5fFN/vwiTWbtO+bXjiOhtUbnFxHrqOgWERFpQtd1b0vHiEByi8uZvmxvkz53RaWDV+eb13KPvyKBIF91uaWZKs2HtI/M5X6aJkxErKWiW0REpAl52G08OjwZgBnL95JTVNZkzz13wyH2ZRfROsCbe/rHN9nzijS5TbOhLB9aJ0HClVanEZEWTkW3iIhIE7v60iguiQoiv7SCt5fuaZLnLKtw8NpCs8s9cXAiAT6eTfK8Ik3O4Tg7gFrqeLDr110RsZb+FRIREWlidruNySPMbveslfvILih1+nPOWX+Ag6eKCQ/y4c7L4pz+fCKW2bMIsneDdxB0v83qNCIiKrpFRESsMCIlkm7tQygqq2TakgynPldpRSWvL0wH4MEhifh5ezj1+UQsteZt82uP28E32NosIiKo6BYREbGEzXa22/3+qkyy8kqc9lyz1xzgSG4JUcG+3JYa67TnEbHcyT2w6wdzOVUDqImIa1DRLSIiYpHByeH0jmtFaYWDNxalO+U5SsormXp635OuTMLXS11uacbWvAsYkDgM2iRZnUZEBFDRLSIiYhmbzcbjp7vdn6w5wKGc4kZ/jg9/yuRYfintQv24tU9Mo+9fxGWUFkDah+Zyv4nWZhER+QUV3SIiIhYakNSGyxLCKKt0VF133ViKyiqqrhd/eFgS3p76b1+asc2fQmkuhCVA0nCr04iIVNH/viIiIhZ7fGQnAOasO8D+7KJG2+/7qzI5UVBGbJg/N/Vq32j7FXE5hnF2ALW+92uaMBFxKfoXSURExGJ948MY1LENFQ6jai7thiooreCt013uR4Z1xMtD/+VLM7Z3CRz/GbwCoOcdVqcREalG/wOLiIi4gDPd7rkbDrLneEGD9zdz+V5OFZWT0CaAG3q0bfD+RFza6jPThN0GviHWZhER+RUV3SIiIi6gR0wowy6JwGHAqwsa1u3OLS7nnWV7AHhkeEc81eWW5uxUJuz63lzWNGEi4oL0v7CIiIiLeOz0SOZfbzrMrqz8eu9n+vK95JVUkBwZyG+6qcstzdzad8FwQMIQCO9kdRoRkXOo6BYREXERl7YL4epLozAMmDJvV732kVNUxozlewF4dHgyHnZbY0YUcS1lRbDhfXM5dYK1WUREaqCiW0RExIU8NiIZmw2+33qUbYdzL/rxby/dQ0FpBZ2jg7mqS5QTEoq4kC2fQUkOhMZB8iir04iInJeKbhEREReSHBnEdadPCb/Ybnd2QSmzVu4D4LHhHbGryy3NmWGcHUAt9X6we1ibR0SkBiq6RUREXMwjwztit8H8HcfYeCCnzo97a+keisoq6dY+hBEpkc4LKOIKMlfAsW3g5Q8977Q6jYhIjVR0i4iIuJjE8EBu7NkegJfr2O0+ll/C+6v2AWdOUVeXW5q51dPMr93GgF8ra7OIiNRCRbeIiIgLemRYRzztNpbuOs66fScvuP2bizMoKXfQMzaUIcnhTZBQxEI5B+Dn78xlDaAmIi5ORbeIiIgLim3tzy19zG73Sz/W3u0+klvMR6v3A/D4iE7qckvzt266OU1Y/CCITLE6jYhIrVR0i4iIuKiHruyIt4edVXuyWZlxosbtpi5Kp6zCQWp8GJcntW7ChCIWKC+G9e+Zy/3U5RYR16eiW0RExEW1C/Xjt6kxALz84y4Mwzhnm4Onivh07QEAJo/UtdzSAmz5HIpPQkgMJF9tdRoRkQtS0S0iIuLCJg1NwsfTzrrMUyzdfW63+/WF6ZRXGlye1JrLEtTllmbOMGDNW+Zy39+Bh6e1eURE6kBFt4iIiAuLDPblrsviAHjpx53Vut2Z2YXMWX8QgMkjki3JJ9Kk9v8ER7eApy/0utvqNCIidaKiW0RExMVNHJKIv7cHmw/mMn/Hsar1ry1Ip9JhMDg5nN5xYRYmFGkiZ7rcXW8Bf/3Mi4h7sPScnCnzdvHqgt3V1iWEB7Dw8SEAlJRX8ux3O/hm82HKKhxc0TGc/x19KeFBPlXbH8op5k9fbmHVnmwCvD25uXd7/nNUJzw99PcEERFpHtoE+nDPgHjeXJzBSz/uJMDbg22H85i7wexyP6YutzRnjkrIXAnHdsC2f5rrNICaSPOQdxjmPQXp88xBEsMS4Iap0K5XzY/Zuwx++H9w/GcIbgdX/BF63nH+bZe9DAuegX4PwNXPO+c11IHlF8IkRwby4e/6VX3vaT9bLP/vt9tZ9PMx3ri9F0G+Xvzl661M/HA9XzwwAIBKh8G4mWsJD/LhiwcGcCy/lMc/24Sn3cZ/XnVJk78WERERZxk/KIGZy/fy89F8bn93ddV6H087R3OLISbUunAizrL9a/j3E+Yv5md4eMPJvRDV1bpcItJwxadg+ijoMAju+AICWkN2BviF1vyYU/vg4zHQZxzc/C7sWQJf/x6CIiFpePVtD62H9TMh8lJnvoo6sbwd7GG3ExHkW3ULC/AGIK+knM/WHeBPv0lhQFIburYP4e//0Z31mafYsP8UAEt3H2f3sXym3NqDLm1DGNopgskjkvlgVSZlFQ4rX5aIiEijWr03m5Lz/N9WWuHggQ838O+tRyxIJeJE27+Gz+6uXnADVJaZ67d/bU0uEWkcy1+BkHYw+g1o3xtaxUPSMLPbXZN1MyA0DkY9C+GdoN94SLkBVr1RfbvSAvjifrjuNfANdeKLqBvLi+59JwpJfXY+g15YyCOz0ziUUwzA1oO5p0djbVO1bVJEIO1C/diQaRbdaZmn6BQVXO1088HJ4eSXVrArK79pX4iIiIiTVDoMnvlme63bPPPNdiod504pJuKWHJVmh5tafqb//V/mdiLinnZ+D217mn9EeyERpg2E9bNqf8yBtZAwpPq6pGFwcG31df/6AySPgsShjZm43iwtunvEhvLiLd15b1wqfx3dlQMnixgzbRUFpRUcLyjF28NOiJ9Xtce0CfTmeEEpAMcLSmkT6P2r+32q7qtJaWkpeXl5Vbf8fBXoIiLiutbsPcmR3JIa7zeAI7klrNl7sulCiThT5spzO9zVGJB3yNxORFxOfn5+tXqrtPQ8tdmpfbB2OoQlwl1zoc998P0TsPHjmndckAWB4dXXBURAaZ55TTjAls/hyCYY9lSjvZ6GsrToHtopgmu7RdM5OpjByeHMHJtKXnE5322u7R/ZhnvuuecICQmpuqWkpDj1+URERBriWH7NBXd9thNxeQVZjbudiDSplJSUavXWc889d+5GhgOiu8Pwp8yvfcZCr3vMU8jrK/egeRbMTe+Al2/999PILB9I7ZdC/LzoEB7AvuwiBiW1oazSQW5xebVu94mCMsJPd7PDA33YeCC32j5OnO5wn9nmfJ588kkmT55c9f2hQ4dUeIuIiMuKCKrbLw513U7E5QVGNu52ItKktm/fTrt27aq+9/E5T20WFGVel/1L4cmwo5bxGgIjoeB49XWFx8AnGLz84PBGKDwOb11x9n6jEjJXwJq34c/Hwe5x8S+ogVyq6C4srSAzu4gbe/pwafsQvDxsrEw/wdVdowHIOF7AoZxiesW1AqBnXCteX5TOiYLSqtPKl+0+QZCPJx0jA2t8Hh8fn2pvfF5enhNflYiISMOkdggjOsSXo7kl573C1QZEhfiS2kHzFkszETcAgttC3hHOf123zbw/bkBTJxOROggKCiI4OLj2jWL6QXZ69XXZGRASU8tj+sLuedXXZSyC9n3N5YTB8MCq6vf/80FokwyXP2pJwQ0Wn17+7Hfb+WlPNgdOFrE+8yQTPliPh93G9d3bEuzrxZg+Mfz1ux2szDjBloO5/HHOJnrFhtIr1iy6r+gYTseIIB77dCPbD+exZNdxXvpxJ3f1j8PH05oDKiIi0tg87Daeus48I8v2q/vOfP/UdSl42H99r4ibsnvAVX87/U0NP/VXPW/ZL9Ai0gj6P2gOgLb0RbPY3jzHHEgt9f6z28x/GuZOOPt9n3HmteA//hmO74I178C2L819AfgEQWRK9ZtXAPiFmcsWsbTTfSS3hIc/SSOnqJywAG/6xLfiywcH0Pp01/rPv0nBbtvBAx9uoKzCwRXJbfjf0WfnWfOw25h+bx/+9NVWbnpzBf7entzcqx2TRyRb9ZJERESc4qpLo3nzzl488832aoOqRYX48tR1KVx1abSF6UScIOV6GPP+ufN0B7c1C+6U663LJiIN16433PoRLHgGlrwAreLgqueg25iz2+Rnmddpn9EqHm7/DH54ElZPM/89uP4f587R7WJshmG0+PlFDh48SExMDAcOHKB9+/ZWxxEREalRpcNgzd6THMsvISLIPKVcHW5p1hyV5ijlBVnm9ZxxA9ThFnFRqqvOz6Wu6RYREZHaedht9E9sbXUMkaZj94AOg6xOISJSb5Ze0y0iIiIiIiLSnKnoFhEREREREXESFd0iIiIiIiIiTqKiW0RERERERMRJVHSLiIiIiIiIOImKbhEREREREREnUdEtIiIiIiIi4iQqukVEREREREScREW3iIiIiIiIiJOo6BYRERERERFxEhXdIiIiIiIiIk6ioltERERERETESVR0i4iIiIiIiDiJim4RERERERERJ1HRLSIiIiIiIuIknlYHcAUOhwOAI0eOWJxERERERETEPZ2pp87UV2JS0Q1kZWUBkJqaanESERERERER95aVlUVsbKzVMVyGzTAMw+oQVquoqCAtLY3IyEjsdtc54z4/P5+UlBS2b99OUFCQ1XGaJR1j96H3yvl0jN2H3ivn0vF1PXpPnE/H2H248nvlcDjIysqiZ8+eeHqqv3uGim4XlpeXR0hICLm5uQQHB1sdp1nSMXYfeq+cT8fYfei9ci4dX9ej98T5dIzdh94r9+M6bV0RERERERGRZkZFt4iIiIiIiIiTqOh2YT4+Pjz11FP4+PhYHaXZ0jF2H3qvnE/H2H3ovXIuHV/Xo/fE+XSM3YfeK/eja7pFREREREREnESdbhEREREREREnUdEtIiIiIiIi4iQqukVEREREREScREU38Nxzz9G3b1+CgoKIiIhg9OjR7Ny5s9o2JSUlTJo0idatWxMYGMjNN99MVlZWtW0efvhhevfujY+PDz169DjneRYvXswNN9xAdHQ0AQEB9OjRg48++qhOGadOnUp8fDy+vr7069ePNWvWVN23b98+bDbbeW9z5sypdb+bN29m0KBB+Pr6EhMTwwsvvFDt/m3btnHzzTcTHx+PzWbjlVdeqVPeX2upx7ikpIR7772Xrl274unpyejRo8+b+Xz7PXr0aJ1yNzZ3f68Ajh49yl133UVUVBQBAQH06tWLL7744oL73b9/P9deey3+/v5ERETwxz/+kYqKiqr7jxw5wu23305ycjJ2u51HH320Tnl/qSUf3wtlrulz9tNPP9UptzM0h/crIyODG2+8kfDwcIKDgxkzZsw5+c5HnweTs46vq34eXP09Wbp0Kddddx1t27bFZrPx1VdfnbONYRj85S9/ITo6Gj8/P4YPH87u3bsvuO+m+JmHln2MXfXnvibN4b2aO3cuI0eOpHXr1thsNjZu3Fin137y5EnuuOMOgoODCQ0N5b777qOgoKDa677Q77hylopuYMmSJUyaNImffvqJefPmUV5ezsiRIyksLKza5rHHHuObb75hzpw5LFmyhMOHD3PTTTeds69x48Zx6623nvd5Vq5cSbdu3fjiiy/YvHkzY8eO5e677+bbb7+tNd+nn37K5MmTeeqpp9iwYQPdu3dn1KhRHDt2DICYmBiOHDlS7fbMM88QGBjI1VdfXeN+8/LyGDlyJHFxcaxfv56///3vPP3007z99ttV2xQVFZGQkMDzzz9PVFRUrTlr01KPcWVlJX5+fjz88MMMHz681gw7d+6stv+IiIhat3cWd3+vAO6++2527tzJ119/zZYtW7jpppsYM2YMaWlpNe63srKSa6+9lrKyMlauXMl7773HrFmz+Mtf/lK1TWlpKeHh4fzpT3+ie/futeasSUs9vnXJfMb8+fOrfRZ69+59wf06i7u/X4WFhYwcORKbzcbChQtZsWIFZWVlXHfddTgcjhr3q8+DyVnHty6Zz2jqz4OrvyeFhYV0796dqVOn1rjNCy+8wGuvvca0adNYvXo1AQEBjBo1ipKSkhof01Q/89Byj3FdMp/hKv8PNIf3qrCwkIEDB/K3v/2tjq/adMcdd7Bt2zbmzZvHt99+y9KlSxk/fnzV/RfzO64Ahpzj2LFjBmAsWbLEMAzDyMnJMby8vIw5c+ZUbbNjxw4DMFatWnXO45966imje/fudXqua665xhg7dmyt26SmphqTJk2q+r6ystJo27at8dxzz9X4mB49ehjjxo2rdb9vvPGG0apVK6O0tLRq3RNPPGF06tTpvNvHxcUZU6ZMqXWfddVSjvEv3XPPPcYNN9xwzvpFixYZgHHq1Kk676spueN7FRAQYLz//vvVHhcWFma88847Ne73X//6l2G3242jR49WrXvzzTeN4ODgap+RMwYPHmw88sgjF3pJF9RSjm9dMu/du9cAjLS0tDrtxwru9n798MMPht1uN3Jzc6u2ycnJMWw2mzFv3rwa96vPg8lZx7cumV3l8+Bq78kvAcaXX35ZbZ3D4TCioqKMv//971XrcnJyDB8fH+OTTz6pcV9W/cwbRss5xr/k6j/3NXG39+qXLubYbt++3QCMtWvXVq37/vvvDZvNZhw6dOic7Wv6HVfOUqf7PHJzcwEICwsDYP369ZSXl1f7K84ll1xCbGwsq1atavBznXme8ykrK2P9+vXVnttutzN8+PAan3v9+vVs3LiR++67r9bnXrVqFVdccQXe3t5V60aNGsXOnTs5derURb6Si9NSjvHF6NGjB9HR0YwYMYIVK1Y02n4byh3fqwEDBvDpp59y8uRJHA4Hs2fPpqSkhCFDhtS471WrVtG1a1ciIyOr1o0aNYq8vDy2bdvWoNdVm5ZyfC/G9ddfT0REBAMHDuTrr79ulH02Fnd7v0pLS7HZbNXmcvX19cVut7N8+fIa963Pg3OP78Ww+vPgSu9JXezdu5ejR49WyxcSEkK/fv1qzWfVzzy0nGN8Maz+ua+Ju71X9bVq1SpCQ0Pp06dP1brhw4djt9tZvXq1JZncnYruX3E4HDz66KNcfvnlXHrppYB5/aK3tzehoaHVto2MjGzQdbefffYZa9euZezYsTVuc+LECSorK6v9J3Ch554+fTqdO3dmwIABtT7/0aNHz7vfM/c5S0s6xnURHR3NtGnT+OKLL/jiiy+IiYlhyJAhbNiwocH7bih3fa8+++wzysvLad26NT4+PkyYMIEvv/ySpKSkGvdtxeehJR3fuggMDOSll15izpw5fPfddwwcOJDRo0e7zC9c7vh+XXbZZQQEBPDEE09QVFREYWEhf/jDH6isrOTIkSM17lufB+ce37pwhc+Dq70ndXEmw8X8n37mcfqdqG7qe4zrwhV+7mviju9VfR09evScyxw9PT0JCwuzbMwhd6ei+1cmTZrE1q1bmT17tlOfZ9GiRYwdO5Z33nmHLl26ALBs2TICAwOrbnUd5OWXiouL+fjjj8/pwHbp0qVqv7Vdg9wUdIyr69SpExMmTKB3794MGDCAGTNmMGDAAKZMmXLR2Rqbu75Xf/7zn8nJyWH+/PmsW7eOyZMnM2bMGLZs2QLA1VdfXbXfM89nBR3f6tq0acPkyZPp168fffv25fnnn+fOO+/k73//+8W9YCdxx/crPDycOXPm8M033xAYGEhISAg5OTn06tULu938FUCfB9c8vq7weXDH96QuXOVnHnSMf80Vfu5r0lzfq4kTJ1bbtziHp9UBXMlDDz1UNVBA+/btq9ZHRUVRVlZGTk5Otb9kZWVl1WtwsSVLlnDdddcxZcoU7r777qr1ffr0qTaiYGRkJD4+Pnh4eJwzCmJNz/35559TVFRUbb8A//rXvygvLwfAz8+v6nWdb79n7nOGlnaM6ys1NbXRTk2sL3d9rzIyMnj99dfZunVr1X9W3bt3Z9myZUydOpVp06bx7rvvUlxcDICXl1fV6/r1qMTO/Dy0tONbX/369WPevHkN2kdjcNf3C2DkyJFkZGRw4sQJPD09CQ0NJSoqioSEBAB9Hmj641tfTfl5cMX3pC7OZMjKyiI6OrpavjOjRrvCzzy0vGNcX67w/4C7vld18T//8z/84Q9/qLYuKiqq2gCqABUVFZw8edJpn4dmz+qLyl2Bw+EwJk2aZLRt29bYtWvXOfefGSTh888/r1r3888/12uQhEWLFhkBAQHG66+/Xud8qampxkMPPVT1fWVlpdGuXbvzDvI1ePBg4+abb67Tfs8MpFZWVla17sknn3TKQGot9Rj/0sUMMjF8+HDjxhtvvOjnaAzu/l5t3rzZAIzt27dXe9zIkSON+++/v8b9nhlEJysrq2rdW2+9ZQQHBxslJSXnbF/fQXRa6vGta+Zf+93vfmf07NmzbuGdwN3fr/NZsGCBYbPZjJ9//rnGbfR5MDnr+NY18681xefB1d+TX6KWQb5efPHFqnW5ubl1HkjN2T/zZzK2xGNc18y/ZuX/A+7+Xv1SfQZSW7duXdW6H374QQOpNYCKbsMwHnjgASMkJMRYvHixceTIkapbUVFR1TYTJ040YmNjjYULFxrr1q0z+vfvb/Tv37/afnbv3m2kpaUZEyZMMJKTk420tDQjLS2tatTLhQsXGv7+/saTTz5Z7Xmys7NrzTd79mzDx8fHmDVrlrF9+3Zj/PjxRmhoaLURNs88v81mM77//vs6ve6cnBwjMjLSuOuuu4ytW7cas2fPNvz9/Y233nqrapvS0tKq1xEdHW384Q9/MNLS0ozdu3fX6TnOaKnH2DAMY9u2bUZaWppx3XXXGUOGDKnKfMaUKVOMr776yti9e7exZcsW45FHHjHsdrsxf/78Oj9HY3L396qsrMxISkoyBg0aZKxevdpIT083XnzxRcNmsxnfffddjfutqKgwLr30UmPkyJHGxo0bjX//+99GeHi48eSTT1bb7szr6N27t3H77bcbaWlpxrZt23R8L3B865J51qxZxscff2zs2LHD2LFjh/Hss88adrvdmDFjRp2Pb2Nz9/fLMAxjxowZxqpVq4z09HTjgw8+MMLCwozJkyfXul99HkzOOr51yWzV58HV35P8/PyqfQHGyy+/bKSlpRmZmZlV2zz//PNGaGio8c9//tPYvHmzccMNNxgdOnQwiouLa9xvU/3MG0bLPcZ1yexq/w80h/cqOzvbSEtLM7777jsDMGbPnm2kpaUZR44cqXXfV111ldGzZ09j9erVxvLly42OHTsat912W7VtLvQ7rpylotsw/zJ0vtvMmTOrtikuLjYefPBBo1WrVoa/v79x4403nvPDOnjw4PPuZ+/evYZhmH8FOt/9gwcPvmDGf/zjH0ZsbKzh7e1tpKamGj/99NM52zz55JNGTEyMUVlZWefXvmnTJmPgwIGGj4+P0a5dO+P555+vdv+Zv4rVJ/MvteRjHBcXd95MZ/ztb38zEhMTDV9fXyMsLMwYMmSIsXDhwjrvv7E1h/dq165dxk033WREREQY/v7+Rrdu3c6Z4up89u3bZ1x99dWGn5+f0aZNG+Pxxx83ysvLL3h84uLiLrjv2h7fUo7vhTLPmjXL6Ny5s+Hv728EBwcbqamp1aZhsUJzeL+eeOIJIzIy0vDy8jI6duxovPTSS4bD4bjgfvV5MDnr+Lrq58HV35Mz02z++nbPPfdUbeNwOIw///nPRmRkpOHj42MMGzbM2Llz5wVfe1P8zNe0j5ZyjF31574mzeG9mjlz5nm3eeqpp2rdd3Z2tnHbbbcZgYGBRnBwsDF27FgjPz+/2jYX+h1XzrIZhmEgIiIiIiIiIo1Oo5eLiIiIiIiIOImKbhEREREREREnUdEtIiIiIiIi4iQqukVEREREREScREW3iIiIiIiIiJOo6BYRERERERFxEhXdIiIiIiIiIk6ioltERERERETESVR0i4iINGM2m42vvvrK6hgiIiItlopuERERJ7j33nux2WxMnDjxnPsmTZqEzWbj3nvvbbTne/rpp+nRo0ej7U9EREQah4puERERJ4mJiWH27NkUFxdXrSspKeHjjz8mNjbWwmQiIiLSVFR0i4iIOEmvXr2IiYlh7ty5Vevmzp1LbGwsPXv2rFpXWlrKww8/TEREBL6+vgwcOJC1a9dW3b948WJsNhsLFiygT58++Pv7M2DAAHbu3AnArFmzeOaZZ9i0aRM2mw2bzcasWbOqHn/ixAluvPFG/P396dixI19//bXzX7yIiIgAKrpFREScaty4ccycObPq+xkzZjB27Nhq2/znf/4nX3zxBe+99x4bNmwgKSmJUaNGcfLkyWrb/fd//zcvvfQS69atw9PTk3HjxgFw66238vjjj9OlSxeOHDnCkSNHuPXWW6se98wzzzBmzBg2b97MNddcwx133HHOvkVERMQ5VHSLiIg40Z133sny5cvJzMwkMzOTFStWcOedd1bdX1hYyJtvvsnf//53rr76alJSUnjnnXfw8/Nj+vTp1fb17LPPMnjwYFJSUviv//ovVq5cSUlJCX5+fgQGBuLp6UlUVBRRUVH4+flVPe7ee+/ltttuIykpif/7v/+joKCANWvWNNkxEBERack8rQ4gIiLSnIWHh3Pttdcya9YsDMPg2muvpU2bNlX3Z2RkUF5ezuWXX161zsvLi9TUVHbs2FFtX926datajo6OBuDYsWMXvD78l48LCAggODiYY8eONeh1iYiISN2o6BYREXGycePG8dBDDwEwderUeu/Hy8uratlmswHgcDgu6nFnHluXx4mIiEjD6fRyERERJ7vqqqsoKyujvLycUaNGVbsvMTERb29vVqxYUbWuvLyctWvXkpKSUufn8Pb2prKystEyi4iISONQp1tERMTJPDw8qk4V9/DwqHZfQEAADzzwAH/84x8JCwsjNjaWF154gaKiIu677746P0d8fDx79+5l48aNtG/fnqCgIHx8fBr1dYiIiMjFU9EtIiLSBIKDg2u87/nnn8fhcHDXXXeRn59Pnz59+OGHH2jVqlWd93/zzTczd+5chg4dSk5ODjNnzuTee+9thOQiIiLSEDbDMAyrQ4iIiIiIiIg0R7qmW0RERERERMRJVHSLiIiIiIiIOImKbhEREREREREnUdEtIiIiIiIi4iQqukVEREREREScREW3iIiIiIiIiJOo6BYRERERERFxEhXdIiIiIiIiIk6ioltERERERETESVR0i4iIiIiIiDiJim4RERERERERJ1HRLSIiIiIiIuIk/x9YmpoxIc4ArgAAAABJRU5ErkJggg==","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Check data types\n","print(filtered_df.dtypes)\n","\n","# Convert 'Month' to datetime if necessary\n","if pd.api.types.is_period_dtype(filtered_df['Month']):\n"," filtered_df['Month'] = filtered_df['Month'].dt.to_timestamp()\n","elif not pd.api.types.is_datetime64_any_dtype(filtered_df['Month']):\n"," filtered_df['Month'] = pd.to_datetime(filtered_df['Month'], format='%Y-%m')\n","\n","# Ensure 'Units' is numeric\n","filtered_df['Units'] = pd.to_numeric(filtered_df['Units'], errors='coerce')\n","\n","# Drop any rows with NaN values that may have been introduced\n","filtered_df.dropna(inplace=True)\n","\n","# Calculate total dose per patient for each month\n","monthly_dose = filtered_df.groupby(['ID', 'Med', 'Month'])['Units'].sum().reset_index()\n","\n","# Calculate average dose per patient per month for each medication\n","avg_monthly_dose = monthly_dose.groupby(['Med', 'Month'])['Units'].mean().reset_index()\n","\n","# Plot the average total dose per patient each month for each medication with separate y-axes\n","fig, ax1 = plt.subplots(figsize=(10, 6))\n","\n","medications = avg_monthly_dose['Med'].unique()\n","colors = ['tab:blue', 'tab:orange']\n","\n","ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n","\n","for i, med in enumerate(medications):\n"," med_data = avg_monthly_dose[avg_monthly_dose['Med'] == med]\n"," if i == 0:\n"," ax1.plot(med_data['Month'], med_data['Units'], color=colors[i], marker='o', label=med)\n"," ax1.set_ylabel(f'Units ({med})', color=colors[i])\n"," ax1.tick_params(axis='y', labelcolor=colors[i])\n"," else:\n"," ax2.plot(med_data['Month'], med_data['Units'], color=colors[i], marker='o', label=med)\n"," ax2.set_ylabel(f'Units ({med})', color=colors[i])\n"," ax2.tick_params(axis='y', labelcolor=colors[i])\n","\n","plt.title('Average Monthly Dose per Patient (July to November)')\n","ax1.set_xlabel('Month')\n","fig.tight_layout() # otherwise the right y-label is slightly clipped\n","plt.xticks(rotation=45)\n","plt.show()"]},{"cell_type":"markdown","metadata":{},"source":["4. Switching Analysis:\n","How many patients switched from Medication A to Medication B each month (September, October, November)?\n","How many patients started on Medication B without being on Medication A in the past?"]},{"cell_type":"code","execution_count":30,"id":"df198e53","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Convert 'Admin Date' to datetime if necessary\n","if not pd.api.types.is_datetime64_any_dtype(admin_df['Admin Date']):\n"," admin_df['Admin Date'] = pd.to_datetime(admin_df['Admin Date'])\n","\n","# Identify patients who switched from A to B\n","switch_df = admin_df.pivot_table(index='ID', columns='Med', values='Admin Date', aggfunc='min')\n","\n","# Patients who switched from A to B\n","try:\n"," switch_df = switch_df.dropna(subset=['Med A', 'Med B']) # Patients with both medications\n","except KeyError as e:\n"," print(f\"\\nKeyError: {e}\")\n"," print(\"Columns in switch_df:\", switch_df.columns)\n","\n","switch_df['Switch Month'] = switch_df['Med B'].dt.to_period('M') # Month of switch\n","\n","# Reset index to make 'ID' a column again\n","switch_df = switch_df.reset_index()\n","\n","# Count patients who switched each month\n","switch_count = switch_df.groupby('Switch Month')['ID'].count().reset_index()\n","\n","# Plot patients switching from A to B\n","plt.figure(figsize=(10, 6))\n","sns.barplot(x='Switch Month', y='ID', data=switch_count)\n","plt.title('Number of Patients Switching from Medication A to B')\n","plt.xlabel('Switch Month')\n","plt.ylabel('Number of Patients')\n","plt.xticks(rotation=45)\n","plt.show()"]},{"cell_type":"code","execution_count":32,"id":"abf8c606","metadata":{},"outputs":[{"data":{"text/plain":["34"]},"execution_count":32,"metadata":{},"output_type":"execute_result"}],"source":["# Patients who started on B without being on A\n","start_on_b_df = admin_df[admin_df['Med'] == 'Med B']\n","patients_no_A = start_on_b_df[~start_on_b_df['ID'].isin(switch_df['ID'])]['ID'].nunique()\n","\n","# Number of patients who started on Medication B without being on Medication A\n","patients_no_A"]},{"cell_type":"code","execution_count":35,"id":"1ae29c5c","metadata":{},"outputs":[{"data":{"text/html":["
\n","\n","\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
MedIDMed AMed BSwitch MonthTime on A (Weeks)
012012-01-082012-12-092012-1248.000000
142012-01-082012-12-092012-1248.000000
252012-01-082012-12-092012-1248.000000
382012-01-092012-11-102012-1143.714286
492012-01-092012-11-102012-1143.714286
\n","
"],"text/plain":["Med ID Med A Med B Switch Month Time on A (Weeks)\n","0 1 2012-01-08 2012-12-09 2012-12 48.000000\n","1 4 2012-01-08 2012-12-09 2012-12 48.000000\n","2 5 2012-01-08 2012-12-09 2012-12 48.000000\n","3 8 2012-01-09 2012-11-10 2012-11 43.714286\n","4 9 2012-01-09 2012-11-10 2012-11 43.714286"]},"execution_count":35,"metadata":{},"output_type":"execute_result"}],"source":["switch_df.head()"]},{"cell_type":"markdown","metadata":{},"source":["5. Time on Medication A Before Switch:\n","For patients who switched to Medication B, what is the average number of weeks spent on Medication A before switching?"]},{"cell_type":"code","execution_count":34,"id":"ff1e8b9d","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Average time on Medication A before switching: 41.26 weeks\n"]}],"source":["# Calculate time on Medication A before switching to B\n","switch_df['Time on A (Weeks)'] = (switch_df['Med B'] - switch_df['Med A']).dt.days / 7\n","\n","# Average time on Medication A before switching\n","avg_time_on_A = switch_df['Time on A (Weeks)'].mean()\n","\n","print(f\"Average time on Medication A before switching: {avg_time_on_A:.2f} weeks\")"]},{"cell_type":"markdown","metadata":{},"source":["6. Dose Comparison Before and After Switch:\n","What is the average monthly dose of Medication A for patients before switching to Medication B?\n","What is the average monthly dose of Medication B post-switch?\n","Breakeven Analysis: If Medication A costs $1 for 100 units, what is the breakeven price point for Medication B on a per-unit basis?"]},{"cell_type":"code","execution_count":36,"id":"fd0dd035","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Average monthly dose of Medication A before switching: 612.68 units\n"]}],"source":["# Filter for patients who switched and their Medication A doses\n","med_A_switch = admin_df[(admin_df['ID'].isin(switch_df.index)) & (admin_df['Med'] == 'Med A')]\n","\n","# Calculate average monthly dose of Medication A before switching\n","avg_dose_A_before_switch = med_A_switch.groupby('ID')['Units'].mean().mean()\n","\n","print(f\"Average monthly dose of Medication A before switching: {avg_dose_A_before_switch:.2f} units\")"]},{"cell_type":"code","execution_count":37,"id":"bbec4c11","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Average monthly dose of Medication B after switching: 5.71 units\n"]}],"source":["# Filter for patients who switched and their Medication B doses\n","med_B_switch = admin_df[(admin_df['ID'].isin(switch_df.index)) & (admin_df['Med'] == 'Med B')]\n","\n","# Calculate average monthly dose of Medication B after switching\n","avg_dose_B_after_switch = med_B_switch.groupby('ID')['Units'].mean().mean()\n","\n","print(f\"Average monthly dose of Medication B after switching: {avg_dose_B_after_switch:.2f} units\")\n"]},{"cell_type":"markdown","metadata":{},"source":["7. Dose Change Over Time: How does the average total monthly dose per patient (for both Medication A and B) change for patients switched in September vs. October vs. November?"]},{"cell_type":"code","execution_count":54,"id":"05a4332f","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Identify switch months (September, October, November)\n","filter_months = [pd.Period('2012-09', freq='M'), pd.Period('2012-10', freq='M'), pd.Period('2012-11', freq='M')]\n","switch_sep_oct_nov = switch_df[switch_df['Switch Month'].isin(filter_months)]\n","\n","# Check if 'Admin Date' column exists in admin_df\n","if 'Admin Date' not in admin_df.columns:\n"," raise KeyError(\"The 'Admin Date' column is not found in the admin_df DataFrame.\")\n","\n","# Merge switch data with administration data to get the doses\n","merged_df = pd.merge(admin_df, switch_sep_oct_nov[['ID', 'Switch Month']], on='ID')\n","\n","# Ensure 'Admin Date' column is present in the merged DataFrame\n","if 'Admin Date' not in merged_df.columns:\n"," raise KeyError(\"The 'Admin Date' column is not found in the merged_df DataFrame.\")\n","\n","# Calculate total monthly dose per patient for both medications\n","monthly_dose = merged_df.groupby(['ID', 'Switch Month', 'Med']).resample('M', on='Admin Date')['Units'].sum().reset_index()\n","\n","# Calculate average total monthly dose per patient for each switch month\n","avg_monthly_dose = monthly_dose.groupby(['Switch Month', 'Med'])['Units'].mean().unstack()\n","\n","# Plot the data\n","plt.figure(figsize=(10, 6))\n","avg_monthly_dose.plot(kind='bar', ax=plt.gca())\n","plt.title('Average Total Monthly Dose per Patient for Each Switch Month')\n","plt.xlabel('Switch Month')\n","plt.ylabel('Average Total Monthly Dose')\n","plt.legend(title='Medication')\n","plt.xticks(rotation=45)\n","plt.tight_layout()\n","plt.show()"]},{"cell_type":"markdown","metadata":{},"source":["8.Second Dose Analysis: For patients switched to Medication B:\n","What percentage of the second Medication B dose is the same, higher, lower, or zero compared to the first dose?\n","Lab Value Comparison: For patients that switched from Medication A to B, what was the average LAB B value while on Medication A compared to while on Medication B?"]},{"cell_type":"code","execution_count":58,"id":"1f9e9ca0","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# Identify the second dose for patients who switched to Medication B\n","med_B_doses = med_B_switch.groupby('ID').apply(lambda x: x.nsmallest(2, 'Admin Date')).reset_index(drop=True)\n","\n","# Compare first and second dose\n","dose_comparison = med_B_doses.groupby('ID')['Units'].diff().fillna(0)\n","\n","# Calculate percentage of second dose being the same, higher, lower, or zero\n","second_dose_analysis = pd.cut(dose_comparison, bins=[-np.inf, -1, 0, 1, np.inf], labels=['Lower', 'Zero', 'Same', 'Higher']).value_counts(normalize=True) * 100\n","\n","# Plot the data\n","plt.figure(figsize=(8, 6))\n","sns.barplot(x=second_dose_analysis.index, y=second_dose_analysis.values, palette='viridis')\n","plt.title('Second Dose Analysis')\n","plt.xlabel('Dose Comparison')\n","plt.ylabel('Percentage (%)')\n","plt.show()"]},{"cell_type":"markdown","id":"118b0520","metadata":{},"source":["### 9. **Lab Value Analysis for Medication A and B:**\n","To confirm whether Medication B is a suitable replacement for Medication A, we can compare the average lab values for patients while they were on Medication A and Medication B. "]},{"cell_type":"code","execution_count":59,"id":"b00fcb31","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Average LAB_VALUE while on Medication A: 190.00\n","Average LAB_VALUE while on Medication B: 191.84\n"]}],"source":["# Merge admin_df and labs_df on 'ID' and 'Admin Date' to combine patient medication and lab data\n","merged_lab_data = pd.merge(admin_df, labs_df, left_on=['ID', 'Admin Date'], right_on=['ID', 'DRAW_DATE'], how='inner')\n","\n","# Filter for patients who switched from Medication A to Medication B\n","lab_switch_data = merged_lab_data[merged_lab_data['ID'].isin(switch_df['ID'])]\n","\n","# Calculate average LAB_VALUE while on Medication A and while on Medication B\n","lab_values_A = lab_switch_data[lab_switch_data['Med'] == 'Med A']['LAB_VALUE'].mean()\n","lab_values_B = lab_switch_data[lab_switch_data['Med'] == 'Med B']['LAB_VALUE'].mean()\n","\n","print(f\"Average LAB_VALUE while on Medication A: {lab_values_A:.2f}\")\n","print(f\"Average LAB_VALUE while on Medication B: {lab_values_B:.2f}\")"]},{"cell_type":"markdown","id":"2a52e6bc","metadata":{},"source":["### 10. **Efficacy Comparison Based on Lab Values:**\n","We can now run a statistical test to see if there's a significant difference between the lab values while on Medication A and B."]},{"cell_type":"code","execution_count":61,"id":"dd4bbf63","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["T-statistic: -0.20\n","P-value: 0.8395\n","No significant difference in lab values between Medication A and B.\n"]}],"source":["from scipy.stats import ttest_ind\n","\n","# Get lab values for patients while on Medication A and B\n","lab_values_A_data = lab_switch_data[lab_switch_data['Med'] == 'Med A']['LAB_VALUE']\n","lab_values_B_data = lab_switch_data[lab_switch_data['Med'] == 'Med B']['LAB_VALUE']\n","\n","# Perform a t-test to check if there is a significant difference between lab values\n","t_stat, p_value = ttest_ind(lab_values_A_data, lab_values_B_data, nan_policy='omit')\n","\n","print(f\"T-statistic: {t_stat:.2f}\")\n","print(f\"P-value: {p_value:.4f}\")\n","\n","if p_value < 0.05:\n"," print(\"There is a significant difference in lab values between Medication A and B.\")\n","else:\n"," print(\"No significant difference in lab values between Medication A and B.\")"]}],"metadata":{"kaggle":{"accelerator":"none","dataSources":[{"datasetId":5715081,"sourceId":9411660,"sourceType":"datasetVersion"}],"dockerImageVersionId":30761,"isGpuEnabled":false,"isInternetEnabled":false,"language":"python","sourceType":"notebook"},"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":"3.11.6"}},"nbformat":4,"nbformat_minor":5}