{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction\n", "Welcome to the `matrics_calculator` package documentation! This package provides various useful method for calculating predictive model performance metrics that's used across Data Science studies.\n", "\n", "Below we'll walk you through using the various functions within this package along with providing example for each function. Before continuing with the examples below, confirm that you have `vega-datasets` installed as we'll be using the `countries` data set from this package. If you don't have it installed, you can do so by putting `pip install vega-datasets` into your terminal. After installing vega, run the cells below in order to import the data set and use the functions." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 1: Load the Dataset\n", "\n", "We will first import the `countries` dataset from `vega-datasets`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " _comment year fertility life_expect n_fertility \\\n", "0 Data courtesy of Gapminder.org 1955 7.7 30.332 7.7 \n", "1 NaN 1960 7.7 31.997 7.7 \n", "2 NaN 1965 7.7 34.020 7.7 \n", "3 NaN 1970 7.7 36.088 7.7 \n", "4 NaN 1975 7.7 38.438 7.8 \n", "\n", " n_life_expect country p_fertility p_life_expect \n", "0 31.997 Afghanistan NaN NaN \n", "1 34.020 Afghanistan 7.7 30.332 \n", "2 36.088 Afghanistan 7.7 31.997 \n", "3 38.438 Afghanistan 7.7 34.020 \n", "4 39.854 Afghanistan 7.7 36.088 \n" ] } ], "source": [ "import pandas as pd\n", "from vega_datasets import data\n", "\n", "# Load the countries dataset\n", "countries = data.countries()\n", "\n", "# Display the first few rows of the dataset\n", "print(countries.head())\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2: Understand the Dataset\n", "\n", "The `countries` dataset includes various features like `life_expect`, `fertility`, `year`, `p_fertility` and `p_life_expect` etc. You can choose a numeric column to use as your target variable and other columns as features.\n", "\n", "For example:\n", "\n", "`Target variable (y)`: `life_expect`.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 3: Preprocess the Data\n", "Now we have selected our target variable and features, it is important to preprocess the dataset by handling the missing values and selecting the features that's only relevant to the problem at hand." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset shape: (567, 4)\n" ] } ], "source": [ "# Drop rows with missing values in relevant columns\n", "countries = countries.dropna(subset=[\"life_expect\", \"fertility\", \"year\", \"p_fertility\", \"p_life_expect\"])\n", "\n", "# Select features and target variable\n", "X = countries[[\"fertility\", \"year\", \"p_fertility\", \"p_life_expect\"]]\n", "y = countries[\"life_expect\"]\n", "\n", "# Display the shape of the dataset after cleaning\n", "print(f\"Dataset shape: {X.shape}\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4: Split the Dataset\n", "Split the data into training and testing sets for model evaluation." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training set size: 453\n", "Testing set size: 114\n" ] } ], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "# Split the dataset into training and testing sets\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n", "\n", "# Print dataset sizes\n", "print(f\"Training set size: {X_train.shape[0]}\")\n", "print(f\"Testing set size: {X_test.shape[0]}\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5: Train a Regression Model\n", "Use a simple linear regression model to fit the training data." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LinearRegression\n", "\n", "# Initialize and train the linear regression model\n", "model = LinearRegression()\n", "model.fit(X_train, y_train)\n", "\n", "# Make predictions on the test set\n", "y_pred = model.predict(X_test)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we have trained our simple linear model, we can use the methods provided in this package to calculate some metrics!\n", "\n", "## Function 1: r-squared\n", "\n", "R-squared score measures the proportion of variance in the dependent variable explained by the model, providing insight into the model’s goodness of fit. Below is an example of how to use the `r2` function with our life expectancy dataset and trained regression model." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "r_squared score: 0.978\n" ] } ], "source": [ "# Import the r2 function from our custom package\n", "from matrics_calculator.r2 import r2\n", "\n", "y_test_r = y_test.tolist() if not isinstance(y_test, list) else y_test\n", "y_pred_r = y_pred.tolist() if not isinstance(y_pred, list) else y_pred\n", "\n", "# Calculate r-squared score\n", "r2_score = r2(y_test_r, y_pred_r)\n", "print(f\"r_squared score: {r2_score:.3f}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A value close to 1 (e.g., 0.93) indicates that the model explains most of the variability in the data, demonstrating a strong fit. \n", "\n", "To better understand how well the model captures the variability in life expectancy, let’s visualize the predictions alongside the actual values." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "# True vs Predicted plot\n", "plt.scatter(y_test, y_pred, alpha=0.7, label=\"Predictions\")\n", "plt.plot(\n", " [y_test.min(), y_test.max()],\n", " [y_test.min(), y_test.max()],\n", " \"r--\",\n", " lw=2,\n", " label=\"Perfect Prediction\",\n", ")\n", "plt.xlabel(\"True Life Expectancy\")\n", "plt.ylabel(\"Predicted Life Expectancy\")\n", "plt.title(f\"True vs Predicted Life Expectancy (R² = {r2_score:.3f})\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The scatter plot shows the alignment of predicted values with the 45° line, illustrating how well the model performs." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Function 2: Mean Absolute Percentage Error\n", "\n", "In the countries dataset, MAPE can evaluate how well a regression model predicts life expectancy (`life_expect`) based on features like fertility rate, population, and previous life expectancy.\n", "\n", "MAPE gives an easily interpretable percentage error, which is ideal for communicating model performance to policymakers or stakeholders who may not be familiar with other statistical metrics.\n", "For example, if the MAPE is 8%, you can confidently say that the model's predictions are off by 8% on average." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MAPE: 1.40%\n" ] } ], "source": [ "from matrics_calculator.MAPE import mean_absolute_percentage_error\n", "\n", "# Evaluate MAPE\n", "mape = mean_absolute_percentage_error(y_test, y_pred)\n", "print(f\"MAPE: {mape:.2f}%\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A low MAPE (e.g., <10%) indicates the model is relatively accurate.\n", "A high MAPE suggests the model may not generalize well to the data, requiring further tuning or feature selection.\n", "In our case our MAPE calculated is 1.4% which indicates our simple linear model's predictions are only off by 1.4% on average.\n", "\n", "Below is an illustrative plot showing how MAPE helps identify where true and predicted values differ." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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SXHo3p1GolpTGzuOKMXi8IaTYfuKJJ8zv7tBDwoVxjhSHhYUM92lxIr8qISFTBeHdHE3/hU2fhU8eBt3xZDvaHw53AB/dPQxKo0ChSZx3jt7wosO7aD64HAPVHnzwQSNuKupHy51RxcDFI30GsxXcVgZveMdzJLgNFy9ebIKQSwqSLOluqLLGWN7wOxP+MFfGRYfBu3RjMEODgei0+DEAuDDFbR8GuboDj8uyvfkdi8t4Ks1+pSuFnztjxgxjIXFzLJkjHA9dMRRHh7PKUAhQaDAomO5XWkwpOkojlii4iiusVhi623jRZJAxz/mScNeXocujcM0rXlxpXeP4mKgQyPC78Hf0mWeeMY/C0KpElx+/KwUIrVpuYe4NA8IPV4+IwfQ8DyjE3XWMvH9rGzRo4HGNumFAOJMjLrnkElRlFCNTBeGPXuH4Fma4FLbI0N9Nt1BxvmoKIZ4ER4KuI55QdB+xgiRfHymzwH2yFmdeLS94kWXaJs2uxd39eFfRZIYBf5T5Q+I9n3c3R4LuB5qUX3755RLN9LwbI4XFZWWNsbzhXT/dRxSkFHCFKVyh9FhgXAAvlhMnTjR3ojSlM/uGQqEwvFB4/5BzW1FkujNsyrK9uV95PBcXm+Her+6Yk8L71S0avN00/JtZVEcLx8N1FOe6KOwOohuJF1eKDV5gSysUGItC8Xak85IWFF5UmYpPq+yR3Er33XefcT95PyiuaCWo6OO3LOnXZbHAcJ1uFyGPKx4nhR/MXqJriH9TgHvvS8YWUWC4YdYjj2lva3bh31HGRzEb1B1LQ8ub93f7999/i1hIacGky6q0GWKBiiwyVRDGozDojCcMTdz8QaZYKexP5g8Mffi0qtDk3bVrV2MG5h0lLyA0iR7JB80LLGuI8C6BP+CF4wp4N0ZRRV84rQo0J7/66qvG7124Qmh5wyBRfgZjMfjDyTtyxgtQvPFO0V26m641uklYk4OmW3dqM8fLGKLDwTtupv3SQsALJy1S3IaMTaCpmXdidHvRtM4LMt11vKNmmisflTFGb2gRcwsrb4tZWer6UMTwQsYLJtOSKS54l8mLBt2HTG8uTtgVhnEc7rgAb5jizQePFaYf84LgLpnP9dKSx+OV5fK9XUx0C3Fb8j28GNNyQ3eJt+u0tNub5wbPAV5YmH7Nc4MXE54vr7/+ugmw5A0D3Sp8zXOA+4RxTLRscB7PCQorbi8GppbGbVMS3Abc3kxxpuWJxwFdVNyG3tvHXdGVxxYtpbSEcB+VBh6rdFfQknLeeecddlmm3h8Obn9+Z/7+uC+8haGVgOKO+5lioKxw/xRXQ4Wf6U63L0v6NWNz3PufAp3nlbsCMcfqLj1AYUL3DQOLeRzyfGIwdXHCmr8JhefxXOO+4X7juUyxSYHCY7Kk5A3GdHG+t9Dhby1/X2+//XbzO0CBzvPbG1oBOT5ukyqNr9OmxNGnX3fo0KHY5ZmixxRMpjhGREQ4+/TpY1IZC6dfu1Npx44d62zVqpUzJCTEvIepqKwImZOTU6rxMbWS4+vdu3eReT/++KPz0ksvNRUouX4+X3PNNUVSvovjcJVCC6feTpo0qdj5//33n3PQoEHOevXqOYODg50NGzZ0XnTRRc6PPvqowHJMdeQ2Zfoql2Fq+ttvv33E9GvCVNQHH3zQVCzlZ/CzBgwYYD7bzcKFC006LbdB4VTs8h5jcRwuZZWp9mVJv3bD5XhsMeWaY2rZsqVzyJAhzmXLlh1T+rV727ASLFN9WXHVm88//9ws9/TTTxc5BiZPnuxs3LixKQ1wxhlnmJT9wpR2ex84cMB55513mvncb0yF5fmzf//+AmNp3769Sbv1TsVes2aNOR+ioqLMOcWUdI6lcLp2cSm63tvdm7y8PPMd27Zta8ZTu3Ztk1a7fPnyIu9nGQS+n+nLZYFpzjfeeGOJ6delPV8//vhj8x4enyWxYMECs8wLL7xw2G1RlmO58PFblvRrdyp8cQ/vfebeHkeq6Hy477N69WpTWoK/zyxlwN9Qli8oDp733N8rVqwoMm/69OnOZs2aOWvWrOkcOXKkOUa8OfXUU53XX3+9s6oTxP98LaaEEOJooeWQcQi8q3XHD1R3aOlgOjC3jXcF2SNBqx9jkmhdU6fzwGblypXGGvfnn39WmV5gJaEYGSGEqELw3pSdklm1uywihrAuEd9DF5wIbCZOnGjikaq6iCGKkRFCiCoAY7MYw8MYIsa5sQhlWWHM0ZGytURgMKdQt/CqjISMEEJUAZh1xdRruoQYUFrVU26FcKMYGSGEEEIELIqREUIIIUTAIiEjhBBCiIClysfIsGgUK8+yYFVVb5wlhBBCVBUY+cK2DGy/cLj+alVeyFDEsCOoEEIIIQIPtnMoqQt6tRAytMS4NwRLhQshhBDC/2EncRoi3Nfxaitk3O4kihgJGSGEECKwOFJYiIJ9hRBCCBGwSMgIIYQQImCRkBFCCCFEwFLlY2RKi91uR25urq+HIUSxBAcHw2q1+noYQgjhd1R7IcM89d27dyMpKcnXQxHisLCHTr169VQPSQghvKj2QsYtYurUqYOIiAhdJIRfiu2MjAzs3bvXvK5fv76vhySEEH6Drbq7k9wipmbNmr4ejhAlEh4ebp4pZni8ys0khBAuqnWwrzsmhpYYIfwd93GqWC4hhMinWgsZN3IniUBAx6kQQhRFQkYIIYQQAYuEjCjAo48+irp165q7/88++wxV9Tt27tzZ83rIkCG47LLLjmmd5bEOIYQQASZkGGz78MMPo3nz5iaYsWXLlnjiiSdMloYb/v3II4+YTA0u07t3b2zYsAHVGV40KTT4CAkJQatWrfD4448jLy/vmNb777//4rHHHsMbb7yBXbt2oW/fvuUuGg63nPs72Ww2NGvWDCNGjEBaWhoqmhdeeAHTp08v1bJbtmwxY1y5cuVRr0MIIUQVyVp6+umn8dprr2HGjBno0KEDli1bhqFDhyI2NhZ33323WeaZZ57Biy++aJah4KHw6dOnD9asWYOwsDBUV84//3xMmzYN2dnZ+OqrrzBs2DBTNG3s2LFHJSh5cf7vv//M60svvdQn8Rg8Bn744QcjyH7//XfccMMNJu2YwqowOTk5RsSVBzze/GEdQggRcGRkMBOh+lpkFi5caC6aF154obkDHzBgAM477zwsWbLEY415/vnn8dBDD5nljj/+eMycORM7d+6ssm6P0hIaGmqKozVt2hS33367sVR98cUXZh7FzahRo9CwYUNERkbi1FNPxYIFCzzvpeWAxdW4fPv27c26KBouvvhiM99isRQQMm+99RbatWtnhGPbtm3x6quvFhjL9u3bcc011yA+Pt583kknnYTFixebz6GFZ9WqVR5ry+GsFrTE8Ds1atQIV111Fa677jrPd3JbdjgWClq3iGX6/E033YTatWub7ubnnHOO+TxvJk6caNxlbAV/4403Iisr67BuIYfDYQQ0LV3cNk2aNMH48ePNPH426dKli/k+Z511VrHr4D6gGGeqNMfao0cPLF261DOf+4Pv//HHH832YkZS9+7dsW7dulLsfSGE8DFOJ/Dii0DLlsDWrdVXyPCHmz/k69evN695Afrtt988Lo3NmzebgnW8SHvf+fLCvGjRIp+N2x+h241WCnLnnXea7TNnzhz89ddfuOKKK4wFx9slR0sHLWIUBv/884+xetHCQ+hW4oPMnj3buPZ4Iafr6amnnjJWMVrICF0/PXv2xI4dO4zo4D68//77jRigGLn33nuNpcW9Tk47mu9ENm7ciI8//hiffPKJx7XD78baKl9//TWWL1+OE088Eb169cLBgwfN/A8++MCIII6bFj+6KAsLscLQqkXxw+9Jy997771nhBBxi2xajvh9OJbi4DbgWLmd/vzzTyOKaEl0j8vNgw8+iMmTJ5uxUchRUAohhN/z8MPA8OGsKovUywZg7bYDcDjyw0IqFacPsdvtztGjRzuDgoKcNpvNPD/11FOe+b///ju3inPnzp0F3nfFFVc4r7zyymLXmZWV5UxOTvY8tm3bZtbBvwuTmZnpXLNmjXkuwOTJTmfDhkd+XHxx0QFwWmney884SgYPHuy89NJLzd8Oh8P5/fffO0NDQ52jRo1yJiQkOK1Wq3PHjh0F3tOrVy/n2LFjzd/Tpk0z22TlypUFlvn000/NdG9atmzpfO+99wpMe+KJJ5zdunUzf7/xxhvO6Oho54EDB4od67hx45wnnHDCEb9T4eWWLVvmrFWrlnPAgAGe+cHBwc69e/d6lvn111+dMTExZp8XHjPHRTjOO+64o8D8U089tcBneW/PlJQUsy2nTp1a7Dg3b95sttGKFSsKTPdeR1pamhnr7NmzPfNzcnKcDRo0cD7zzDPm9fz58816fvjhB88y8+bNM9OKHI9HOl6FEKKS+evXP53pEVG0yzjf73ml86LJPznveu9P57ItxV8LjgZet0u6fnvj0xgZ3i3zjp93vLxr5132PffcgwYNGmDw4MFHtc4JEyYYd8YxkZIC7Nhx5OUaNy46bd++0r2Xn3EMzJ07F1FRUaY4Gq0f1157rbE80GXBmJc2bdoUWJ6uDu/qxYwvoavucKSnp5u4Gbpjbr75Zs90xrC4Y0K4z+hmoVvpWPn777/Nd+L4aYmhy/Hll1/2zKcbjS4kN7T+0CJUuCpzZmamJ96HVqTbbrutwPxu3bph/vz5xY6By3Nb0apztPCzuV9OP/10zzTGL51yyilm/d547wN36wFamOjOEkIIf2R5wkGM/ysD7a8YjZjIUKzp2hORuXb8szMZ4+f9iwcvbIeuTY/9mlBafCpk7rvvPowZMwZXX321ed2pUyckJCQYMUIhw3gJsmfPngL9Zfi6pEwYugVGjhzpeZ2SkoLGxQmOwxETAzRseOTlvC6qBaaV5r38jGPg7LPPNoHSFCQUfnRLEF7YWb6ebpbCZewpErzdNkcK6HVnDE2dOtW487xxr9tdOr88OO6444x7it+F36lwMC/jbwqPj8eFd/yPG8YAHQ3l+X1KAwWOG/f+oDAVQgi/4cABYNw4BhzCERGJGQsTkJSRi509z8OuoCDwahAZakNEiBUJBzMwc2ECujSuAYslqOoLGcZpMLC08AXS/UPOwEqKGcbRuIULhQkDSRngWhwMzuTjmKAQ8hJDZeJQcGpFw4s64y4KQ+sILRq8qz/jjDOO6TMYF0JBsWnTJhN4Wxy0KDDOhrEfxVllKEY4ntLgTiUvLYyHYQyVO127OBikzONl0KBBnml//PFHiets3bq1ETM85hhEXNwYyeG+E8sIcDlmXtGKRGihYbAvLY5CCBEw/PYbcM01zOrg3SPWT3wRG/emoU50aJGbYb6uHRWKDXvTsH5vKtrWO7Yb9oAQMsySYRApzeh0La1YsQLPPfecJ+CRG4U//E8++aS5wLjTr3lxVfGx4qFLiaKDF24GkVLY7Nu3z1yYKTrorikLdNMx+4auJAYM0+3CwNTExERj+WK2EgNpuT9oSaOFhPuR+4guHAoMBm3TBcVsJGYOHbPQPASDwPkZ/GxmGfG7M6Nt3rx5uPzyy0020PDhw01GEf+mq4euTAY3t2jRoth1MsNo9OjRJliXYoTv4fbje+hiYxYShc4333xjvg+XL5x6TZFJoU2LI8Udj2+Oj8Kd6xBCCH/HkWfH/nFPoPbTTyLIfeP21VfIuHUUcvLsCAsu/nc8LNiK/WnZSM6ovJ5wPhUyL730khEmd9xxh7Eg8OJ36623miwZN7ygMFbjlltuMam2TGPlRaQ615A5Esw+ovhjxhCziWrVqoXTTjsNF110UZnXRasEU4MnTZpkLsy8SNMF6LYs8GL/3Xffmc+64IILTPwMU7pfeeUVM79///4ms4euMO4/jo3Cojyg0GUNHWb+sP4QBQcteGeeeaYny4hZUoxZ4XHEtGuOhyLj22+/LXG9PCZp5eFxSGFEceaOs+F0ZnixACHn0+pVnGuLWU+0LA4cOBCpqalGSPEza9SoUS7fXQghKopVy9ch5IahaPdXfnbwhnZdsWHKa0gPjoXDuR+ZOXmICst3jbvJyrUjxGZFbETReRVFECN+UYWhK4p3zMnJyabOiDe8sNFa4F2XRAh/RcerEKKiWff+l6h961DEJx8wrx1BQXj/3IGYcMqVyIUF8ZEhSM3Kg93pRNu60YiLyI9lpJxgjEzHBrGYclXnY46ROdz1228sMkIIIYTwA+x2OMaPR+tHH4PF6YpTTY6Jx/ODH8HH8W2R53AaoZJrd6BxjQhs3JeG1TtT0Kp2JGpHhxlLzL60bMSGB2NQ96aVFuhLJGSEEEKI6s7778PCzKRDrGl/Mt68+TEsSg9GXnYewm0W2J1ARo4DUWE2dGgQg/V70rAtMdOImNBgm7HEUMRUZuo1kZARQgghqjtXX42k199G9G8L8PmlN+Gri4ciNceJ9MRkhFhdbWusQUCO3WGsMjUiQoyYoRXmtp4t0alRLNrUia5US4wbCRkhhBCiuuF0MmMi/7XFgn2vvomn3vgKWzuehEiLFbmOHLDrAAUMsTucsAQFIdjqKpsSHmw1fY6axEdUWqq13/Va8heqeLyzqCLoOBVCFIfD4cTa3SlYvOmAeT5iz6OdO1m/AvjllwKTW7ZvgazuPYyVhb83wRYLaGChS4lrpDUmMtRqit/5KkOpOKq1RcZdVZX1PSq7oqsQZYXHaeFqwEKI6s3yhIOm0i6L1GXn2Y3gqB8Thv5dG+Gyzg2Lunq++QYYOBDYvx9Yu5Z9ZjxV6rns4O5NTZsBZh/VigxBRIgNKVm54FpoiWlUI8L8TaFDwcO4GLqUfEm1FjKsIsxS9qxhQ1gv5Uhl+4WobPiDQRHD45THa+HWE0KIatzzaN6/pl1AeIgVqVm5SMuyY9vBDPy5NQmf/LkDI85t7Qq+zc0FWKNt4sT8FbCyPnsDerXb4bLsleQWR8HWIPCf1RKExvERiA61IT07z2cZSsVRrevIEH59lrlnsTYh/BmKGBb8k9gWQtB9dM/7K7F6RzLiIoKN6MizOxFic7mDMnLtsFmC0LpOFB47MRbHj7oNWLgwfwUskDp9OlCo6a73+tlmgBV6dyRlYv7avfhvX7qp6kt3Etdb0RlKqiNTSnhRYOVWlp5nPxwh/BG6k2SJEUK4ocigeKkdHYotB9KNiKFVxn2bE2azIs/hQOulP6PlmElAWrJrBhsM0yrDfoKHuSmilcU7gJduKrewYUyMrzKUiqPaCxk3vEjoQiGEECIQoKCgdcThsCI9m1YSixExDlO0zomg3GyM/Gk6blj8af6b2MR2zhzgtNPK/HmFhY0/ISEjhBBCBBi0itDFk56TZ8SL1WJBZq4dGTmugN/mB3fjmuVfeZY/eO4FiH9/FlAF+70p/VoIIYQIMOjaaVUnyvQ9oiUmIycP6YdEDNkc3xCPnHsbciw2PNbrFky7d3KVFDFEFhkhhBAiwGrG/LMzBY1rhGP9nlQcSM+GPTMbbN+YY3OVZ6C4+fSEc7G4SSdsq1EPDVbswPBebWCzVT37hYSMEEIIESDp1lO+X4+/ticjK5eNHZ2wsbbLgV149pMJ+LNBWzx67m1GxDAOl0vsjK+PcKsF+9Ny8P3aPejbsT6qGhIyQgghhJ/hnf7MeJjUzDw8+NnfSDiQYYRKeLCr/1HPvxbgyXkvIDo7A8fv3oglTTrhm7anm4wkpl+zjQBbDKRm52F3chaqIhIyQgghhJ9W62VmEivqpmTm4mBGjglsjQi1ITQ3ByO+eR1XLJ3red/mGg1woG5jRIXaTE8kFrGj6MnOc5jX9WLDUBWRkBFCCCH8SMQ8OXcN9qXmICbMhriIEGTl5GFPajbyHE5EhFjRZP92TPzgSRy3e5PnfZ+174kHzxsGW2yM6VbthhlNWXl21IkOxblt66IqIiEjhBBC+Ik7acr3G7B+T5qpVUcLDKvPU8DwQXqv/BFPffsKonIyzessWwieuWAY3u3QCwybseXYER7MvkhBpp4MRQyFzR1nt6qSgb5EQkYIIYTwAz5buQPLExLhhBNhViscDgfScx2m+3RoXg4e/f51XPPXd57lN9VqjLFXPYR1tZshOM+B2HCrKVyXnJmLrDyncSfREkMRc92pTVFVkZARQgghKjFwt7jy/lzm4+XbTVuByGAL8ux2ZOY6TF0Y1pzPs1jR8uB2z/IfdeyFJ/oOgzUqEjmMgbEA3VvWxLMDTsCP6/eawF7GxNCdVFUtMW4kZIQQQohKCtxlNV4Wshvs1XCRIubbNbuxaX+6+Ts5K7+wnZsgixV3X3w/Ppp9H6b0uB6fHt/LTA/OsZvnRjUjMPj0ZggJsVbJFOvDUe27XwshhBCVEbjLbCOmQu9Pz0FseDAevLCdWY5C56/tSdh2MMO4kUh4ThbqpR0wFXq9CXfmIdcaDLuDDiiY4N+uTWrgnnNbV2gnal+g7tdCCCGEHwXu0psUGWJDoxrhSMrMxfPfb0Badp6JaYkKtXpETJt9W/DK508jxJ6Li4a8gNTQSM96m9aPQ0xYCPanZSMr144HL2qHvh3q+00nal9QtR1nQgghhA8Dd+1OJ2wWC8JtFvPMwnQb9qYh1GrBym2J2Jmcidhwm6tSr9OJq1Z9iy9mjkTrA9vQNGk3Hv3hjQLr5TooeiiOTm4WX+1FDJFFRgghhChHvAN3ow8VpyO2IMAaZEFmngPbEjOQlm1Hjt1pLDJhGel4/puXcdmanz3rWVOnOV7udlWBddOCwy7XdE0N6t602osYIiEjhBBClCPMUNqVkoVgiwUs/+KtNdhWIMjpRGoOOyHBZBy127MJL33xNFoe3OFZ7t0uF+DJc25Cto2tIPNJz8lD9xa1jIipajExR4uEjBBCCFGOMM2a2iUqzGqsLlaL1bwmzFzKMA0f2fPRietWfo2Hf5yKUHuumZQaEo4x59+Nee3OMK8pgoKcgP3Q3/ERwbi+WxOJGC8kZIQQQohjqAvTqlYUNu5P87yODrMh1GZFWLQVWbkZxhXE6rpsF5CafSi12unEc/OeQ79/5nvW+1e9VrjzktHYWiM/fZoCiLKH2U5M22aF31mLtqJrk3i5lQ4hISOEEEIcZV0YCotcu8M0dmS3adaJaVk7EvGRwdiVnGXEx46kTKRluWJbPPVOgoLwV73WHiEzrevFmHDWDcixBRf4PC4fYrOgWc1Ik+2UfihYmEKqbT2VFCESMkIIIUQpRcz4ef8iKSPXlP7PtluwfncqcuwOhNosaF0n2jyv2ZViAnwpclhht05UKMKDLdhywNUfyc30rhej/d5N+LHVKfi2TfcC8xgYXC82HDUiglErKgQWlu4FEBZsNanXtP4IFxIyQgghRCncSbTEUMQ0qxlhLCqbdybTQ2Qyk7LyHCaVukP9GJNRxPoxdCXR+UPhEZGeiks2LccX7XvmrzQoCPdfcE+Rz+J7aOFpGBeOqLCCl2nWjqHVhy4s4UJCRgghhDhCPMzf25OxemcyakeHmswjpkGnZ1NUWIz1hTEwdPvsTsnG9sQM5NkdRpDUjglDvbUr8ewnT6Nx8h4khUXhlxZdD/uZVksQrNYgRIQULPXGQvz70rLRsUGs6dckXEjICCGEEEeIh0nOyMG+tBykZeWiUY0IZObYTWyM1WIxVhkG4+Y4gV3JmcizOxFsDUJ6Vh7O/WY2Rv88HcEOV0+kR36civOadYbDwlaQxVMzMsRYXLYmZqJ2VKhxJ9ESQxGj+jFFkZARQgghjhAPw55GiRm55vXB9GRjNWENGIoZ1ruzsT6MJQhZOUy3DkJwUiLenDcFvf9b6lnnsobtcPcl9x1WxFCeDOjaCOe0q+MRUXRN0Z1ES4zqxxRFQkYIIYQ4TDwMXUl064QGW5CVaTcWGP536MmkFpl8pEPNkk7ZuQZTPpuEhqn7POt89bQBeK7H9cizlnzZpRUnPNiKC0+oj/b1Y9GlcY0Cad50J8kSUxQJGSGEEMILigdaQmiJoYgpDOVKniePOp8gpwO3Lf4Y9/7yLmxOV9G7g+ExGHXJvfilxUkmi6k4+AmMtSEnNIpD27qutGqKFqVYHxkJGSGEEMLLGsPAXsbE0J1ESwzFDAN76UaKCLaZNgHFSZIH5r+Dm5d+5nm9uHFHjLx0FPbG1DZihcYUWnC838tpDBS2WYPQIC4c95zbWlaXMiIhI4QQQngF9zI7iYG9jIlhlV4G99KRRINKEBzFihgyq8sFuHrVt4jMycLL3a7Ey2dcizy2J3C43FDMbgoLsZjYGoojvo4LtyI8JBgdG8Rg8OnNFP9yFEjICCGEqPZ4B/cyxZrZSSlZeUg1lXRT0SguwlhPMg81eyyOhBoNcO+FI5EeEo7fm3WG8RY5XS0GWPU3zGZBrsNpAndb14nCwG5NTa0Yxb8cGxIyQgghqjXFBfc2jo/Ehj2pxp2UY2f9liyz7KF4XtRKT8Q9v72H8WffiMyQMM+6vmvTzfN3TFgwYsKDkZKZi6xchymaR0HTpUks7undRtaXckJCRgghRLWmuODeuPBgtK4bbYrbJWXk4EB6jqeDdfctK/HC3GdROz0JwfY8jL5geIH1cTnG13RqGGtcVKwxwxq/9WPD0L9rQ1zWuZGsL+WIhIwQQohqXbV30X8HkJrlcil5QzEDhBs3U54DaBgVjCu/noY7fpsDy6FImbM2L0fN9CQciIzzvI91ZE5sGoe3B59coCu23EcVg4SMEEKIal21lyJmb2o20rNzUS82AmHBFgRbLIgItWJ7YibsDqBJViJe+HAyjt+4wrOOX5p1wYiL7i0oYoKC0KJ2pHEd2WwWpU9XAhIyQgghqnXV3tpRIUjOzEViRh6SMlM86dChNqvpn9T9v+WY9MWzqJmRbN6fF2TBlDOvx9vdrzRtCYKDgkyDSJvVgpOb1cCIcxX/UplIyAghhKh2gb2J6TnGlZRjd5hgXLuD9WJgUqzzHA6EBgcjIyMbdy+YgTv++Mjz/j0xtTCq3xgsrN/O1JghtaJCjRVG8S++QUJGCCFEtYExMX9tT0JqVp5pwkgBQzHDEF13ejSnZefZ0W/1jwVEzK9tTsWjl49CcmQsYp1OpOfYTRbSQxe3Q98O9SVgfISEjBBCiGrD4k0HsTMp02Qn0YXE/kbZeQ5jXck5lG1EYdMkPgJ/97oMv67+Gadt/Qsv9hqKOacPgNPiaiXA99OCw8De5jUjJWJ8iISMEEKIgM04KktG0NItB/DK/I2mLgwTot2dqwlTpB0OBzJzgVCbBTUiQsz80Zfci3oHd+Ofpu0RjiCwb7XbihNsCTKVf2ndEb5DQkYIIUTAZhzl5NlNpdxWdaIwuHvTEoNs+Z5HPvsHB9KzTZ0XShnTw/FQgbsGyXsxZe5kPNNzEDYd1wWRoTYT6JsUUxMHo+MRGWpFTp5LwLC1AAUMY2MYJkMhJXyHhIwQQoiAscJ8tnIHXlvwHzJz7WgYFwaHw2qaOK7YmohtBzPw0EXtiogZd4AvU6wpPGiFORSnazh3wx94dt4UxGan44UvJuGu+99GEOKMm4lWHjqTjm8Yi8xch7HSBFstZt7Wgxno2CDWWIOE75CQEUII4ffQojL99y34ef0+I2LoCtqfmu0SJVzA6cT+tBxM+X49Zt5wagE3E11Q63enmABeWmEoTPh+a14uxsyfhhuWf+FZ1m61okl2CnZl1zbBwA3iXO0HtiVmonZUqGk7kJVrNyImNjwYg7o3VXyMj5GQEUIIERB1X/amZCPP7jSZQgzQZe0W4tYRDqcdC/87gCk/rMe95x3nef+STQex9WCmEUBmOQBNEnfj5c+fxvG7N3iW++q40/H4pSMQGVcToVl5xtpCoULcrqz9adnGleWep3oxvkdCRgghREA0dAwPsSI7xW4q7XpDPePqZ+SKe3nzl//QuEY4BnRtjBXbEvG/JVsPpVi7ljvv39/w9NcvIiYnw0zLttrwxDk34/2uF+KWs1rizNa1iwQQd2lco8zBxaJykJARQgjh9w0dKWK27E+Ho5CIIRQweV4xL9l5Toz99G98tmKHERu03sSE2ZCeko6H5r+NgX/O8yy7uUZ93HnpGGxo0AoN48Jx8QkNim0rwPWo3YB/IiEjhBDCb6EFhLEt7IdE6wzrtuSZdKPDQ8GzJCHRxMOwi3WwNRTxWzdhwF8/eJb5vF1PPNBnGByRkSb+5YRGcQrcDUBclX2EEEIIP4RuHMqWtCw7QoOtpvpuaaHjJ9fuxI6D6diVnIWEuk3waO9bkWULwZg+d2L4xaOQHhqBkGAr6saEKXA3QJFFRgghhN9CC0n9mDCTWh0WZDFiJjOvaJyMN5QiFCRRjlxk5DmRkgWEBFtMxtE3p1yAP1p2wbbo2ghyutxSLIA39oK2CtwNUGSREUII4bdQkFx+YkNThC4tOw85eQ6EH8Eqw5Ts1ge344NpIzDm52kmS4lBvhQ4wTYL0uo2RHSoDSE2i0mhrhkZiugwFbULVGSREUII4dep1z+v22dSrjNyHMhz5BlBQmFiOg14EXRIxPRb/ROe+PYVhOdmo/WezVjUuBN+aX+6ia1xv4/NIWmJaVEr0sTfMBZHBCYSMkIIIfy6fgxTr5vVisTWA+nItjtMIC+bPNIwk+flYorIzcLjP7yO/l4BvRtqN8XOOo1NywEGDeewIF4QTIuBRnERrqaRNqvaDAQwEjJCCCH8un5Ms5oRptt0WLAVm/alITkz19SLYQPHGuE2pOXY0Wz3Frzy+dNoc2CrZx0fnnAeZlw9AnG14pCRlIlaUZHGKhNssZjeSSRBbQYCHgkZIYQQfls/pk50qBExJDbMhhCrxcS2uArgBaF1nSj0/H0ebvjgOeNKIunBYXjiorux44J+eOzc1mYaLTsH0nNMmjUFUUaO3bQgUJuBwEdCRgghhN/BmBV2tg4LDvVMS8+2mwaRYTarqSfjzEjHsGlT0HPpd55l1tdviT8mvIJB552GtnVjPALlwQvbqc1AFUVCRgghhN/BmBWKDTZoZHwLyXWwv9KhQF/zRzDqHdjlec9PZ/XDs31uwbgzTkL7+rEF1kexojYDVRMJGSGEEH4HRUarOlH4Z2cyIkKsxr3E2BbLoawj9k6KjgjF1DvGY/TEW/HxgDuxoPPZQFZeiYG7ajNQNVEdGSGEEH4HRcfg7k1NDAsDctOz8xCXl4nWSbuMe4lWmUY1IpBYsx4enPAxlpzS28S8MGZGgbvVC58KmWbNmhmVXfgxbNgwMz8rK8v8XbNmTURFRaF///7Ys2ePL4cshBCigrKU1u5OweJNB8wzX9MdxNiWDg1iUWfDP3jk0YF4afbDqOvMNunTuXl2HEjLxu7MPGw5kK7A3WqKT11LS5cuhd1u97xevXo1zj33XFxxxRXm9YgRIzBv3jx8+OGHiI2NxZ133ol+/frh999/9+GohRBClHe9GHcgLgN8GRtDtxItMl2b1EDnT2ch6MX7YMnNMctPW/0+hnS/Gev2pMHhdJqqv7WiQtC/ayMF7lZDgpysKuQn3HPPPZg7dy42bNiAlJQU1K5dG++99x4GDBhg5q9duxbt2rXDokWLcNppp5VqnVwPRVBycjJiYuQbFUIIfy16x1RrpkYzwJduovrOLDw17wU0WfCNZ/l/Gx+HUf0fQGKdhqgVFQqLxdXpmq4nxsbQgiMxUzUo7fXbb4J9c3JyMGvWLIwcOdK4l5YvX47c3Fz07t3bs0zbtm3RpEmTwwqZ7Oxs8/DeEEIIIQKj6B1hllKH7Wtx4ysPoEHibs/yX593LR497VoczAtCeHYe6seGI+5QYC8tMoylmbkwwWQnyb1UffCbYN/PPvsMSUlJGDJkiHm9e/duhISEIC4ursBydevWNfNKYsKECUbBuR+NGzeu8LELIYQon6J3cDpx3rezMXbCzR4RkxYRjReHT8b0fnciHTZEBFtNhd7tSRmmVQHh+1nsbsPeNLNeUX0os5CZNm0aMjIyyn0gb7/9Nvr27YsGDRoc03rGjh1rzFDux7Zt28ptjEIIIcoP1nPJzs0zoiQxIwdpmbm47dWxuGrOC7Adip9c0agdRo6dhlWdz0Au+yyxxxKr+1otxp3EInlu6JZijI0aQFYvyixkxowZg3r16uHGG2/EwoULy2UQCQkJ+OGHH3DTTTd5pvEz6G6ilcYbZi1xXkmEhoYaX5r3QwghROWTl+fA16t3Ydrvm80zX3uzIykT+9JysGZnCtbuTsU/u1PwW+02nvlTuw3AkEHPILm26wY32Mo6MkGmGB7Tr1kTj0Xy3DC2hoHCagBZvShzjMyOHTvw5ZdfYvr06TjrrLPQokULDB06FIMHDz6swDiSladOnTq48MILPdO6du2K4OBg/Pjjjybtmqxbtw5bt25Ft27djupzhBBCVA6zFyfg1fkbsT8tp0Bm0R1nt8J1pzY1Qb7vLkowYsQBJyJsVvP31K6XoOmuTVh5ci/Mqd3RpFm7K/vymc0eU7PyjEWGYTAskkfoYmKAsBpAVj+OKWuJ1hEG6M6YMcNkFJ1//vnGUnPxxRfDcujgOhIOhwPNmzfHNddcg4kTJxaYd/vtt+Orr74yoomWlbvuustML4slSFlLQghR+SKGmUh0BYVScFiCkGt3ItduN1aVBy9ojyVbDmLbugScmbAC05p2N+4ltzjJyLUbi0uwzYrIECuOqxvtiaFJyszF+t0pyMpzICYsGB0bxCA7z+FpAKmspapDaa/fxxTsy8DbHj16GAsJhcvff/9tLDMtW7bEggULSrUOupRoZbnhhhuKzJsyZQouuugiY5E588wzjcXnk08+OZYhCyGEqEDoPqIlhiImzGYxrQQYy5KdZ2ccL7JyHZj8/TqE/P4r3n7+Zgyf8QT6J641lheKGQoUC4JgtVgw8LQmqBsT5qnsS5dSsCUIMeHBiAq1mffQPZWSlWcsMRIx1ZOjssjQEvPuu+8al9CmTZtw2WWXGUsMU6XT09Px+OOPY86cOSb2xdfIIiOEEJUHY2HumbMS1qAgI2J4iXEnJBGnw4HbFn6Ikb/NhtXpim/Z1rgVHn10FlJz7MZtxPek5dgxacDxCLFZihTLYxuC609riuhwmxpAVmFKe/0us5Ch2+jbb79FmzZtTHDuoEGDEB9fUAHv3bvXWE/oNvI1EjJCCFF5vPPbJuNWonjhJYDPboFRMy0Rz34xGT22rPAs/2/brph66xNICInF9sQM00eJlhlembq1qIm7erVS1+pqSkpFFcRjUO7PP/982IBbVuTdvHlzWVcthBAigGEA71erd5vu1Dh0ixxk/naie8JfmPz5JNRJTzTT7UEWTOs1EIuuvhVJ2U5s2JvqiZOxO+wmqHfbwQwjiuQyEofDdjT1Xo4Eg7KaNm1a1lULIYQIwOq8tJYs2XQQ/1uy1QTe2iyAO9M6yGHHXb/Nwd2/z4HlkLrZGxWPx695AOvangR7YhaSM/NMMHCI1eWOYkBws1pRiA2zqVqvKH8hc/fdd6NVq1bm2ZuXX34ZGzduxPPPP1/WVQohhAjgZo8b9qRiW2IGcvKciIuwoXZ0GHYlZ5llxv34Jgb/Oc/znl+ad8Fzgx5CTo3auP2MZvhi5S4s2nTAuKDsziATwNuoRgTiwl21YLyr9batp/AAUQ5ZSx9//DFOP/30ItO7d++Ojz76qKyrE0II4ecWl7W7U7B40wHzzNfezR5X70hGsDXI2FpCbRakZdtNhlFEiBW0n0zvegnSQsKRF2TB5LMGY/ywyUiNjjcBu5d1boTberY0LQra1otGhwYx6NAg1iNiiKr1inK3yBw4cMAE3xSGgTj79+8v6+qEEEL4ucXFO2OoVZ0oDDytKd79I7/ZI2u7MDg3xBYEBFmQmWs3qdc2SxB21mmMMRePxIHIOCR2ORl5dqep9zKoe1PjKoqLDEZ0WDDCWDPmUOE7b1StV5S7RYZupW++yW+p7ubrr782VX6FEEIEPt4Wl5hD7h4+/7MzGY98vhp/bU/yNHtkdV2Gr9RM2oeHPp+CaEcucuxOl4soIhg/teuB5Y3aG9dTk/gIXNa5oREttO4wA4niiAXtCifRuqv10nqjar2i3CwyI0eOxJ133ol9+/bhnHPOMdPYRmDy5MmKjxFCiCoABQYtMW6Li7uqLsUHXUbsi5SSlYum8RGHpltx7ubleOSjZ1AjMwWOoCA83PcuhAVb0K5etFk+IsSGGhHB2JWUiZmLtmDO0m1GwAzu3tQ8KJoY2MuYGLqTaIlxV+t1W2+EKLeCeK+99hrGjx+PnTt3mtfNmjXDo48+amrK+BuqIyOEEGXLQPp7ezJe+/k/IypYQbcw+1KzsW5PKo6rG4V64TZc/smr6Pv1LM/8nbF1MODmlxFerzb2pGSbTCTjewKMG4lWGcbTeLcVIMUVvqOIUep19SSlogrieUOrTHh4OKKiouCvSMgIIUTZ4mGSM3JMV2pmIDWOjywQfEtY72V5QiLaZB7AM59MQKv/Vnvm/dK2G+7tOxxpka7fW1pS2DcpN8+JUAbu2pmeHYTWdaIRG+5Kr2Z7gSlXdTbLq/CdqPCCeIUL3wkhhAgca0txIsEdD0NXEuNe6D5KzMg1PYyYWt26bnQBMZOda8elCUsx5sNnEJ2RaqblWW2Y3W8YZpx8CWrarKhnsyAxPRf1Y0Px7+40hAa7gn+tDAbOc2B7UgZiw2OKpFcrxVqUFdvR9FkaNWqUiYthK4LCBh273V7mQQghhKj87CPGprDQXOF4GP6us55LajYL1Tmw7WA6rDWjkOdwINSRhyvefxH9f8tv4LurZn08ed0j2NyiAzrViULP42rhrV+3oFGNcGOBcTidpgkk4fpZvZcp2unZdoSHWLE/LVvp1aLyhMyQIUNMt+qHH34Y9evX9wSBCSGE8D8KW1vCgkNNIO3qHUl46NNUnNOujslMqh0V4vk95zMzjtg2gN2qD6TlIDUrydSKuWLZVwVEjLNff6Q+9RwGBUd6LD1Ltxw0gomfxfdYgoJM52paZAhdTTlOINfhQFAu07aVXi0qUcj89ttv+PXXX9G5s8ufKYQQIrCyj9gOgNaQ7YmZ2HIg3YiMtOw8ND6ULk34XD82HP/tSzO9k7gMWwd8c9oFuHTD7zghYTV2jRuPJg+OQptCN7QUJRQnFEzMdGJWE7taWy2uInlcHzUNhQ0Dfhkjo/RqUWlCpnHjxkXcSUIIIfwPxp3QneSu90IoatwNGkNtVuMuosWE6dScziBcihj+zidl5IA17oJtFjSrHYmYsGAjTGbdOR5Tt25HWMuTMOWQKPHGXRuGNWeahlhd1p09qaZQXrCF/ZScJg6HLqW4iBClV4vKLYjHWjFjxozBli1bju2ThRBCVGhbgUX/HUBqVi5CTOuAPBxMzzYWGIqYcJvFTKfAYZwKZQSnb0tMN+9hr6T4nVvw/vQR6L5/g7HOMBWby6XG1ULycR09QbqFoShh/A1Tq5mVRPHSsnYUwoNZ9dcVM8MYnE4N49TZWhwzZU6/rlGjBjIyMpCXl4eIiAgEBxf0ax48eBD+hNKvhRDVNbCXgmR3SpYRHwy25c89g2+tliBToM4tXprEhxs3E11BdCFR4Jz/9wI8/vVLiM7JxJ4adTH+8VlIj8pvT8Pl2CiSvZJYF6a4dOnigozrxoTi7OPq4JQW8UqvFr5Jv1b1XiGECIzA3tDgIFNJN9cJWB12U8cFdph+R2nZuaa1AAVIvdhwsGYd42FsOdkY981UXL0yvxVNhiUYDvbS8xIyjG1hYbzXFvxnXEvemVBuCwufmRWl2jCiIimzkBk8eHDFjEQIIUS5BfYiKAibd6bDarXAaVKggZw8Vth1xbQ4HNQ0TjSKizBVdxkP0zpxO57/ZAKO25sfOvB5p154vO8dsIXEoAPN+AASM3KMlcVmDTLZTuEhNmPNYUwMhZS3u4iiRbVhREVyTAXxsrKykJOTU2Ca3DdCCOH7wN40d52WYCucNisycvKMG4lCxGFcTTBChA8ud86yb/HQvJcRmZtl1pcdEoqpV96LN1ucgRyHE5bMPKRm5hphsn5Pmlmmbd1oRIUFF+jDxJiYmQsTjCVGlhfhl0ImPT0do0ePxgcffIADBw4Uma+CeEIIUfnQdeOu3UJyvQrRUU4wuDYj145aUaFISs8xKdBOmmfS0nDjB1Nw3pKvPeva0aA5XrtjAnY1bIHWGbkmFoYWm53JmZ6CeY3iwhEbEVJgDJxXuFKvEH6XtXT//ffjp59+Mo0jQ0ND8dZbb+Gxxx5DgwYNMHPmzIoZpRBCiMPiXbuFsOaLuxAd4RPrtjSMDcdx9WKM9YSpHmHbE3DWnz941vPrGRfjyUdmGBFDmIrdvGaEEUAUKXa7E9l5dhNETFdSUmbBirzsXE1BpUq9wm8tMl9++aURLGeddRaGDh2KM844A61atULTpk0xe/ZsXHfddRUzUiGEECXiXbuFIsW7EJ0lyGKylWiV4TTCho3HN4zFrT1PwYF6qYgf9yAmX34PVva8yAQDB2fleZbdnpRpasAkZ+aidnQIUrJzQTtPajG9mCikVKlX+LVFhunVLVq08MTDuNOte/TogV9++aX8RyiEEOKIFK7dkpGdhwax4a66L9kUMzCv7Smp2LE32RSiu7NXK5zWsibq338P5n34Ez5sdxZWbkvCml0pWL0rGau2J2Pd7lRk5LhibZrXijSWmagQG+xOJ8JsFhN3sz0xw7QioMuJ2Uyt60SpUq/wXyFDEbN582bzd9u2bU2sjNtSExcXV/4jFEIIUSqYKcSMoQ4NYk3nataRqR0dagKAKUBqbVqLJ5+6AaN/fbdAZtHyrYmYtc1uLDm02lgPuaRocaEICrVZTK0YxsC4+zDRTZWV5zDLpmXlYX9qthFQFFKq1Cv82rVEd9KqVavQs2dPU+H34osvxssvv4zc3Fw899xzFTNKIYQQpaK42i2takZi/5SXUOflMbDkZKPxvHeB264Eml5UIG37uLrRJm2bnakZLEyxwkJ5bF9AMeOGcTNsZUBLTFpOnnFbcZkTGsUZEaNKvcKvhcyIESM8f/fu3Rtr167F8uXLTZzM8ccfX97jE0IIUUYK1G5JSQEGXod677/vmZ/eoRN212yI5g5nsf2Y2IrATa0oBw6k55jaMbWjwwqImdjwGNMvKTkzD6P7tkWf9vVkiRH+71pioG92drbnNYN8+/XrZ9xMyloSQgg/4s8/ga5dAS8R88UZ/TDg+mdx15I03PP+SizZdPBQ2rYrsLcwNSJDTAbU/rScYhsGp+fY0blxnESMCJxeS1arFbt27UKdOnUKTGdNGU7ztzoy6rUkhKh28Gf9lVeAe+8FDhUtTQ+PwjMDRmHd6ecZ0cLsIgbmhljZyNGOejFhJtPJswq+J9sVZ8MU65jQYOQ6HCYF2/v9jIlR40cRUL2WqHvc5kdvtm/fbj5QCCGED0lNZTAj8PHHnkkJLTrggSsfQGibVog89PvtqcR7IMPEw+xNzUKzkEjz+07hYuJfslzxLyZjqSbnAQfTc407iSnWHRvEKiZG+JxSC5kuXbp4ItZ79eoFmy3/rbTCMJPp/PPPr6hxCiGEKA2hocC2bZ6XB28Zhrva9ENEVLjnJpQ3pGxLQAsLa8XkORwItbnaC9DasvVAOnJZ+jcIRsQ0rhFuCuDFhNlw0xnN0DCu+G7XQvi1kLnsssvM88qVK9GnTx9ERUV55oWEhKBZs2bo379/xYxSCCFE6QgJccXE9OoFTJmCDR1PR8anfyP+UAwMs5NobUnPyTPVfqltKEXO7VAPe5Kz8PP6fcjKdSA02GKsNmwqycBeih8KnZ/X7ceUqzpLwIjAEzLjxo0zzxQsV199tWlPIIQQwsewKOn+/UCbNvnTmjUD1q0DbDbE7k7xtC6glWXD3lRTxI6xMdYgIMe0HHDg9w37ceMZzfHPzhRT6C46LNhYa9xWHPVRElUma6l9+/bGKlOYxYsXY9myZeU1LiGEEEdi0SL6/YGLL3bFxnjhsFixdncKEtNzTGr13pQsY4mhiAm3WUyNGJpjWKE3LsJmCt9NX7jFZDDVjglDVJitSDyk+iiJKiFkhg0bhm1e/lc3O3bsMPOEEEJUMA4HMGkScOaZwNatwPr1wOjRntnLEw6a1OqR76/Cw5+txpYD6difnoOD6TmmEi8FDAUNs5UoVWipOZiWg3W7UrEnNRurdyQVaQZJ1EdJ+CNlzlpas2YNTjzxxGKDgTlPCCFEBUI30uDBwFdf5U/r0QN44AGPiBk/718TC0NLTFhwqBEgadl55pFrtxsrDDtjhwVbkJ3rMI9g+pkQBJvVYtobrN+dgjb1YjzNIN19lJippD5KIqAtMoyN2bNnT5HprC3jnckkhBCinPn1V6Bz53wRQ+vKgw8C8+cDjRoVaDfQrGaECda1WoLMc4takcadFBZsQ9t60WhfPxrBFospORMe4oqFYQAvg3uZqcQ+Slv2pxnLDevJqI+SqDJC5rzzzsPYsWNNgRo3SUlJeOCBB3DuueeW9/iEEELQlTR+PJxnnUU/vpmUV7MWHF9/Azz5pAnqJcW1G3DDtgMM4GUnawoazmdV3hD2UHI6Tb0YCp56saGmj1JMWDDSsu3YtC/NWGhoiVHhO+GPlNmE8uyzz+LMM880rQnoTiIM/q1bty7efffdihijEEJUX2gyYTDvV1+ZeBayomUXPDvoYdQ8WBuDEw56xAWDcF3tBopmlVK4sIP1ml0pphEkU6rtDjaGtCIzz9UgktYYLsd5HUNjsGl/Om7o0RzdWtZUzRhRdSwyDRs2xF9//YVnnnnGZDB17doVL7zwAv7++280bty4YkYphBDVlaAgbD/hFPOnIygIH114A14c8wrsdevhn53JJh6GcTGEQbjuVOviYAfr+rFhaFM32riO7A4gJ8+B6DCbscJQwLhhSjYtOBQxTLWWiBH+ylEFtURGRuKWW24p/9EIIYQoAONeJnW4CH1OXozVZ12Ede1PNnegkTa4WgwczMDMhQno0riGsZq0rB2JFduSUDsqBCFWq6cWjDtY94RGcZh8xQnGDUURxPe3rh0JiyX/vlaBvaJKW2QIXUg9evRAgwYNkJCQYKZNmTIFn3/+eXmPTwghqhe7dgGzZnleUnBs2J+BmTc+bESMN4WL1K3YlojEjBwcSMvG6p0p+HtHsnnenZxZIFjXZrOgfYNYjDyvjYmn2ZqYaQJ67QrsFdVByLz22msYOXIk+vbti8TERE+36xo1auD555+viDEKIUT14PvvXVlJgwa5MpEKxL24WgwUxl2kbskmV9r1zqQstKgdhRqH3EQUNpv2Z6BBbHiRYF3+zWkdGsSagF4WzFNgr6jyrqWXXnoJU6dONb2XJk6c6Jl+0kknYdSoUeU9PiGEqPrk5QGPPgo89ZQruJfcfz+wZEmBuBdmFRWG04OtFvy0dq8n7ZqWmroxYca6QpGzPy0HNSJDjPupMBQrnE6LDkWTmkGKKi9k2OXana1UuL5Menp6eY1LCCGqB9u3A9de66oR46ZvX2DGDBPoS1HRqk6UCexlTIx3WrU7lqVJjQhTkdc77TroUMo1Qm2ms/XGw/RIomhR7yRRbVxLzZs3L7bX0jfffIN27dqV17iEEKLq8/XXLleSW8RYrcDTTwNz5wK1a3tExuDuTU3MCmNXiotlObtdnVK5n9QjSVRFymyRYXwMeyplZWWZu4ElS5bgf//7HyZMmIC33nqrYkYphBBVidxc4KGHgGeeyZ/G8hVz5gDduxdZ3B3Lwqq9tKzsT8s27ibGsjAgly6nOUu2Hdb9pB5JoqpSZiFz0003ITw8HA899BAyMjJw7bXXmuwl1pK5+uqrK2aUQghRlbj9duDtt/NfX3IJMG0aEF9ycO3hYlmYon0k95NSqUVVJcjJo/wooZBJS0tDnTp14K+kpKQgNjbWtFSIiZEPWAjhB6xdywwJICfH5Uq65x5X36RjwN0sMjkz16Rk051ESwxFDN1PykISgUZpr99H3eVx7969WLduXX4tg0P+XCGEEEegbVtg5kzT6BGnuKr2HitHcj9JxIiqSpktMqmpqbjjjjtMXIyDjcxMfJoVV111FV555RWjnvwJWWSEEJUFXTxFXD8JW4AnngBefRUIC/PNGJRKLQKQCrPIMEZmxYoVmDdvHrp162amLVq0CMOHD8ett96KOQxWE0KIagZdO25rCDOEaA3pt2Uxhrz9BGypKS4RQzFTwSiVWlQ3ymyRYZ+lb7/91rQo8ObXX3/F+eef73e1ZGSREUJUNO74FBakYy2XKNgxYM4LOH/BR55lcpo1x1+f/YiouuokLYRPLTI1a9Ys1n3EaWxTIIQQ1Qm6cmiJoYhpWjMC0dsTMHzqQ2i5bb1nme869cQb145G8g8JCLFtNxlGrA2juBUhfFAQj2nXrCWze/duzzT+fd999+Hhhx8uhyEJIUTgwHgUupPCQ6xo8O0XeOrJIR4Rk20NxgN9huGWvqOwMduK6LBgxITZTJo0LTi05Aghjg3b0TSN3LhxI5o0aWIeZOvWraZFwb59+/DGG294lv3zzz+PcXhCCOHfMKg2MyUVt3/+Cq5c/pVn+qb4hhh26Wj8W6eFaRfAVOj/9qWhdZ1oNI2PMFV5Zy5MMLVh5GYSohKFDJtFCiGEcBEdZsN5C+cWEDGfdjgbj/S5A6nB4Z5pYTYLch1ObE9iW4EYU+tlw2H6HwkhKkjIjBs3rqxvEUKIqksQ8P7JF6HXmt/Qaed6PHrurfj4hHOBIAvgyM+lYL2tEGuQ6ZGUnm03rijWelH/IyEqOUZm/vz5Jc7zdisJIUSV5VANLZKamYfIiFCMHTAGA254Hh+ecJ5RN97poCza63A6YTXPQK7Dof5HQvhKyDDFmoG9uWx6doj9+/fj4osvxpgxY8prXEII4Z+sWeNqL7BkiXlJIRIbHoKwJo2wq2ELM81OFeN0gqEvjH7hwxIUZKZzms0SZFoHtK4Tpf5HQvjCIvPpp5/i5JNPxpo1a0xhvI4dO5p875UrVx7reIQQwn+ZPt0lYlasAK66CkhKMkKE6dRZeQ4c3zAGNSJCEGKzICrUZh6mhVJQkGnemJ3nQKjN5VJi/yO2DlCgrxCVLGS6d+9uBAvFy4knnojLL78cI0aMwIIFC9C0adNjHI4QQvghaWnA4MHA0KFAZqZrWnQ0kJhohAhrwlCYbEvKQr2YUITaLMi2O5Bjd5gg38gQKzJzHca9xODgTg3j1MRRiHLiqJpGrl+/HsuWLUOjRo2wc+dO0zySnbBZ9VcIIaoUf/8NXHmlq2O1m1tuAZ5/HggPL7ZhI8VKalaemce/6XqqGxOKs4+rg1NaxKuyrxC+FDITJ040mUu33HILJk2aZGrKDBw4EMcffzxmzZrl6b8khBABDbu3vPUWcPfdQFaWa1pUFDB1KnD11UUWp5hhTRh3w8bocBsY8UtBo+aNQvhRr6X69evjnXfeQd++fT3TGPj7wAMP4MUXX0R2djb8CfVaEkKUmZQUOG+5FUHv5zfBdXbpgqD33wdat/bp0ISoLqSU8vpd5hiZv//+u4CIIcHBwcY6891335V5oDt27MD1119vejiFh4ejU6dOxm3lhjrrkUceMQKK83v37o0NGzaU+XOEEP7Zp2jt7hQs3nTAPPO1P7Dm95Wwf/yx5/WXPS7HvcNfxfKQmj4dlxCiHFxLtWrVKnFeu3btyrSuxMREnH766Tj77LPx9ddfo3bt2kakeDeffOaZZ4ylZ8aMGWjevLnp59SnTx+TMRUWFlbW4Qsh/AT2GXLHlOTkuWqq+KqZIgWU2yW0IykT726y4qyLbsfN37yNd4Y+iN9OOAv79mdhy7x/jylI1/tz5G4SopJdSxEREUhISDBig1x44YV46623jKWE7NmzBw0aNIDdbi/1h7PuzO+//45ff/212PkcGtd57733YtSoUWYaTUx169bF9OnTcXUxfurCyLUkhH+KGDZNZMfoOtGhCAu2mgJxrK3C7J/KzOjhWN7/YTX+TbYjwwHsS8sxReva1IlEs9xUJMfV8vwesT9SxwaxmHJV5zILEH8SbkJUS9dSVlaWOZHd/PLLL8h0pyEeoozhNvjiiy9w0kkn4YorrkCdOnXQpUsXTGUg3SE2b95sOmvTneSGX+rUU0/FokWLil0nY3T45b0fQgj/gVYJXtApYprVjEBkqA1WS5B5ZjPF5Mxc00yxMtxMRsS8+gnuuf9q3PTdO6gRGYo8uxN5Dgc27ktHQmhsgRYD3v2Rjka4rd6RbLpfN6oRoS7YQpQTZY6RORw80cvCpk2bTDft1q1b49tvv8Xtt9+Ou+++27iRCEUMoQXGG752zyvMhAkTjNhxPxo3bnzU30cIUf5QBNAqQUtM4d+MYxELZcVhdyDh4acwfvLtaHBwFy79dhZOWL3QlOGNCLYijw0eEzMKtBqg5YjWlLL0R/In4SZEVaRchUxZcTgcpqjeU089ZawxTOm++eab8frrrx/1OseOHWvMUO7Htm3bynXMQohjgyKAYoCioDiORiyUmYMHkX7hJej37mQE2131Xv5r2RG7G7QwLQSoKUKsFtPckU0e3RxNfyR/EW5CoLoLGZ5w3idh4ddHA+Nr2rdvXyRgeOvWrebvevXqeeJvvOFr97zChIaGGl+a90MI4T9QBFAMUBQUR4U3U/zjD6BLF0R/O88z6eu+1+PpMW8is0EjRIbYTEVel6BxItfu8LjOj6Y/kl8INyGqMKUWMjyJ27Rpg/j4ePNIS0szVhT367Zt25b5w5mxxKrAhasGu1sdMEuJguXHH3/0zGfMy+LFi1V4T4gAxd2biKKgcFzd0YqFUnesnjQJzjPOAA7dLCVHxGDisEn46Mq7YbexL1KQiV9hU8cMCi0nYA0KMlYZBvoeTX8knws3Iao4pU6/njZtWrl/OHs0sXcTXUtXXnkllixZgjfffNM8CH9U7rnnHjz55JMmjsadfs1Mpssuu6zcxyOEqHjcvYkY5EpxQNdK4aylcm+mmJwMXHcdMG+e6URN/m7eCSMvux+7omujTUaOafZI4iKCjZBauyfViJiDGTmm0SOzlQYdRYaRW7gxsDcixFrAku0Wbly3umALUUmVfcubuXPnmrgW1o+hUBk5cqSJk3HD4bElAsVNUlISevTogVdffdVYh0qD0q+F8E+KS0emgDgasXBEcnKQfvKpiPxrpXn52fmD8EW/W7EnI89kJxGKDYoqt6BiVtHAbk3RMC7imGu+uLOWGNhbnHBTA0khjv767XMhU9FIyAjhv1RWgTh+zhMvzsUN4+/AB4Puw5pO+a7ppIwcj/WldjQ7V1eMoKpU4SZEFUBC5hASMkJUQ/buBZKSgEOWW7Y/GPn+KsSGBCEiPLTI4mlZuaYQ3u1ntUSnRrEVKqhU2VeI8r1+l7lFgRBC+DULFgDXXgvExQFLlwKRkZ7ModDoiGLfEh5igyUoB03iI9C2XsXd8FC0VOT6haiO+LSOjBBClBtsj/LYY0CvXsCuXcC//wIPPmhmKXNIiKrLUQuZnJwckzqdl5dfLEoIIXwCK32fdx7w6KOuNGvC1iZjx/o25VsI4X9CJiMjAzfeeKNpItmhQwdP8bq77roLEydOrIgxCiFEyfzwA3DCCcBPP7leWyzAk08C33zDfiYFUr6ZIcSUb9aFsTucx1QfRggRoEKGqdKrVq3CggULEBYW5pnOxo7vv/9+eY9PCCGKh9bghx5yWWIY3EsaNADmz3e5lKwFK+kyM4hpzh0axCIlK8/0UWI6dJMaEbisS0PT+0j9joQIPMoc7PvZZ58ZwXLaaacVKOxE68x///1X3uMTQoii0H3Up0++FYacfz4wcyZQu3aJb6OY6dK4hskcWrLpIH5auxd7UrMxc+EWzFmyzbifaLlROrQQVdgis2/fPtSpU6fI9PT09GPuvSSEEKWC7iPGwBBaXp5+2lTtPZyIyX+rq+XAZyt3YOvBDFP4jm0J+Mzquyxcx5ovQogqKmROOukkzOMPxiHc4uWtt95S/yMhROUxejRw443AL7/AMeo+rN2bhsWbDpiaMYdzEXEeC9MlZeSiWc0I41KyWoLMc9P4CONumrkwQW4mIaqqa4l9kfr27Ys1a9aYjKUXXnjB/L1w4UL8/PPPFTNKIUT1Zts2gL8v119f0Crz1luuirnvryxQMfdwLiK6lbhsnejQIlZkvmYLgQ1708xyqvkiRBW0yLDX0cqVK42I6dSpE7777jvjalq0aBG6du1aMaMUQlRfvvwS6NwZGDzYWF+K62G0ekdyqV1E7uJ47HdUHJzO+VxOCFFFhAwbOTIGhvzyyy9o2rQppk6darpV0xoza9YsI2qEEKLcyMkB7r0XuOQS4OBBV4DvAw+w8MsxuYhUHE+IaihkXnrpJaSlpZm/zz77bBzkj4oQQlQUmzcDZ5wBPPdc/rTLLwfmzqX/p8wuIm9UHE+Iahgj06xZM7z44os477zzzIlON1KNGjWKXfbMM88s7zEKIaoTn3wC3HADkJzseh0SAkyeDAwb5hExBV1ERZtAul1E+9Oyi7iI3MXx6HpiMTwKHi5LSwxFjIrjCVEFhcykSZNw2223YcKECeZO53LeGRUD59nZ70QIIcraATo7Gxg1Cnj55fyFW7YEWGizmPg7bxcR3UllcRG5i+PRNUWrDgUPl+3YINaIGNWREaKKCZnLLrvMPOheYitt9lgqrpaMEEIcDpNhdEg8FMkwevBuYPbs/IWvvBJ4800gNrbYdbldRAzsjQixFnAvuV1EFCYluYi8i+MVEVVCiIAhyFnYSXwEmGJ9+umnw2Yrc+a2T0hJSUFsbCySk5ONCBNC+AZ3hhGDcxnXUtid80TrIHS4tLcrqPeFF4BbbingSjrcOhnYW5yLiFYXWVeECExKe/0ulZDhytwr4d+Hw9/EgoSMEP7hTrrn/ZUmTZoZRoWtJ4xVofVkiu0/WNq0djWBPAYrD4N15SISIrAp7fW7VGYVBvbu2rXLuJPi4uKKbUXAHyPFyAhRwXEkAUrhDKO6uxJw0dx3MGPIg8gLDsnPMLrqvDIXoZOLSIjqTamEzE8//YT4eNedzXx2lhVC+CaOJEAtDN4ZRqct/BoDZ05EWHYmMsOj8N7195WYYVRaKFpUhVeI6kmphEzPnj2L/dubpKQkfPXVV+U3MiGqIUXjSEJNzIe7Um2gxnzQShLtyMXgt5/A2Qvneqa3+3cZQrMycDAopECGUVWzSAkhKo5yi9hNSEjAwIEDce2115bXKoWoVhSuVOt24TK1mFk5jCNhpVq6UQLtot5m/za88uLtaLD9P8+033pchNnX34fskDDsOxQjQ8FSFS1SQgg/6rUkhKgYjrZSrd8zfTosp57iETGZwWF4ZcjDeGvow0hEsBFo7iJ0K7Yllrl3khCiehMYOdRCVAOOtlKtv+F2C6XuS0SbJ8Yi9sP/eeZlHtcOk296EguDayMnMaNAETpampjZVBUtUkKIikNCRgg/4Vgq1foL3m6hS374H06emy9icPPNCH/hBTwQGlZs/Mva3SmltkgpsFcIUWYhw15Lh2PHjh2lXZUQogIq1fpboPKSS67HWWsXosm29Xj92vvR88G70TU83PizixMiVcUiJYTwUyEzZcqUIy7TpEmTYx2PENWWQG5mSHfSzN82F3ELvXX7kwjOzsKSkFpIOIJbqCpYpIQQfixkNm/eXLEjEUIEbDPDhB9/w4hRg/Hm0Iewp1Ynz/TE+LrmuXZ23hHdQoFukRJC+AbFyAjhZwRUpVp2OHntNTQdMQKWnBzc89YjePzRd5EZEVVmt1AgW6SEEL5DQkYIPyQgKtUmJwM33QR89JGnjkNqeDTCMtOLCJnSuoUC1SIlhPAdEjJCiLKzbBlw5ZX0OXsmLTj/Gkw8awgaxMfB22ZSVrdQQFmkhBA+R0JGCFE2VxIzGO+7D8g95CaKiwOmTUN0lzMRUU5uoYCwSAkh/AIJGSFE6UhMBG64Afjss/xpp54KzJkDNGuGroDcQkII/xQyKSkppV5hTIzuooSokmzaBMybl/961CjgqaeA4Py4F7mFhBB+KWTi4uKKVNosCbvdfqxjEkL4I127ApMmAY8/DsycCVx4YbGLyS0khPA7ITN//nzP31u2bMGYMWMwZMgQdOvWzUxbtGgRZsyYgQkTJlTcSIUQlcvBgzSxAjavn4m77wauuQaoU8eXIxNCCA9BTqYUlIFevXrhpptuwjX8MfPivffew5tvvokFCxbAn6BbLDY2FsnJyXJ7CVFafvvNJVgGDQLGj/f1aIQQ1ZCUUl6/3eUfSg2tLyeddFKR6Zy2ZMmSso9UCOE/OBwALatnnQVs3+76+7vvfD0qIYQoPyHTuHFjTJ06tcj0t956y8wTQgQoe/cCffsCDzzAYDfXtDPPBDp29PXIhBCi/NKv2Tyyf//++Prrr3EqUy8BY4nZsGEDPv7447KuTgjhD9AlfO21wK5drtcM7n/4YdfDO0ZGCCEC3SJzwQUXYP369bj44otx8OBB8+DfnMZ5QogAgpYXZiH16pUvYurWBb7/HnjsMYkYIUTVC/YNNBTsK0QJHDgAXHUV8OOP+dMoaGbNAurV8+XIhBACFRbsS3799Vdcf/316N69O3bs2GGmvfvuu/iNmQ5CiMAgMtKVYk0sFpdl5ttvJWKEEAFFmYUM42D69OmD8PBw/Pnnn8jOzjbTqZieYpVPIURgEBYGfPAB0LYt8NNPrngYq9XXoxJCiIoVMk8++SRef/11k7kU7FWa/PTTTzfCRgjhp9B6un59wWmtWgH//AP07OmrUQkhROUKmXXr1uFMpmQWgn6spKSkYxuNEKJi+OYboHNn4PLLgYyMgvPoVhJCiAClzL9g9erVw8aNG4tMZ3xMixYtymtcQojyIDcXGDPGVR9m/35gzRpg3Dhfj0oIIXwnZG6++WYMHz4cixcvNo0kd+7cidmzZ2PUqFG4/fbby29kQohjY+tWV4Xep5/On3bRRS5hI4QQVYQyF4lgw0iHw2F6LmVkZBg3U2hoqBEyd911V8WMUghRNr78EhgyJD8rifVgJk4ERo50FbsTQojqXkcmJyfHuJjS0tLQvn17REVFwR9RHRlRrcjJAcaOBZ57Ln9a06bAnDnAaaf5cmRCCOEfdWRuuOEGpKamIiQkxAiYU045xYiY9PR0M08I4SPy8oCzzy4oYi67DFixQiJGCFFlKbOQmTFjBjIzM4tM57SZM2eW17iEEGWF7iN3mxCWRnjhBeCTT4AaNXw9MiGE8H2MDE089ELxQYtMGItpHcJut+Orr75CnTp1KmqcQojSwEDeLVuAW28FTjrJ16MRQgj/ETJxcXEmS4mPNm3aFJnP6Y+xyZwQonL47z/g99+BQYPyp7Ey79SpvhyVEEL4p5CZP3++scacc845pk1BfHy8Zx7jZZo2bYoGDRpU1DiFEN6wtcBNN7mK27VsydLavh6REEL4t5DpeaiE+ebNm9GkSRNjgRFCVDJZWcCIEcDrr+dPY4G7H37w5aiEECJwgn1/+uknfPTRR0Wmf/jhhyYQWAhRQbBPErOPvEXMtdcCn37qy1EJIURgCZkJEyagVq1aRaYz0Ffdr4WoIGbPBk48EVi1yvWawfZvvQXMmgVER/t6dEIIETiVfbdu3YrmzZsXmc4YGc4TQpQjjIG5+27g7bfzp7VtSxMo0LGjL0cmhBCBaZGh5eWvv/4qMn3VqlWoWbNmeY1LCEEGDy4oYvh62TKJGCGEOFohc8011+Duu+82WUysH8MH42bYSPLqq68u6+qEEIfjkUdcbqSICGD6dNcjMtLXoxJCiMB1LT3xxBPYsmWLaRppYyVRwDSRHDRokGJkhChvOnVyxcG0awe0b+/r0QghRNVpGrl+/XrjTgoPD0enTp1MjIw/oqaRwl9wOJxYvzcVyRm5iI0IRps60bBYvMoY/P038PTTwDvvsDiTL4cqhBABc/0us0XGDav7FlfhVwhRlOUJBzFjYQI27k1DTp4dITYrWtWJwuDuTdG1SQ1XBhKDelknhq0+vBs/CiGEODYhM3LkSONSioyMNH8fjuf0AyxEEREzft6/SMrIRZ3oUIQFhyIr145/diZj8sfL8fLPbyD+i4/z3zB/PruwAuHhvhy2EEJUHSGzYsUK5Obmev4uibJW+3300UeL9Gc67rjjsHbtWvN3VlYW7r33XsyZMwfZ2dno06cPXn31VdStW7dMnyOEL91JtMRQxDSrGeE5RyJDbWi7ayNuemUs4vfvyH/D7be7rDFeTVmFEEIco5BhhlJxf5cHHTp0wA9e5dXdAcRkxIgRmDdvnqkaTD/ZnXfeiX79+uF3NsoTIgBgTAzdSbTEeIS+04mz53+Mq/73PILzcswke1Q0rG+/BVx5pW8HLIQQAYbN5wOw2VCvXr0i0xnc8/bbb+O9994zjSrJtGnT0K5dO/zxxx84jaXahfBzGNjLmBi6k0h4RhqGTHsSJy37ybPMukZtkDlzNjqffZIPRyqEEFVYyNAKUlo++eSTMg1gw4YNpmt2WFgYunXrZlogsCnl8uXLjTurd+/enmXbtm1r5i1atKhEIUMXFB/eUc9C+ApmJzGwlzExdCedNf/jAiLm67MH4LULb8Mz7RQ4L4QQFVYQj24d94MpUD/++COWsbroISg6OI3zy8Kpp56K6dOn45tvvsFrr71mOmufccYZSE1Nxe7duxESEoK4uLgC72F8DOeVBIWQ93gbN25cpjEJUZ4wxZrZSfvSssFKB9/1uQ4bWh2P9IhovDzsaTx74TA0bxBvlhNCCFEJdWRGjx6NgwcP4vXXX4fVajXTWN33jjvuMCJn0qRJOFqSkpJMPRpmPrE+zdChQwtYV8gpp5yCs88+G0+z3kYpLTIUM6ojI3yC3Y7l25NN1lJyZi5qR4WiQep+5GbnYk1YPGLDg/Hghe3QtWm8r0cqhBABWUemzC0K3nnnHYwaNcojYgj/Zlo25x0LtL6wNs3GjRtN3ExOTo4RN97s2bOn2JgaN6GhoeYLez+E8AmLFzOaHV0PJhix0qFBrBEzS+2R+Cu4BprUiMDYC9pKxAghxDFQZiGTl5fnSY/2htPYquBYSEtLw3///Yf69euja9euCA4ONi4rN+vWrTMdthlLI4TfwvNg8mSgRw8etCYTqWsNGwae1hR1Y8JgtQTB4XRiT2o23l201dSZEUIIUUlZS3T33HjjjUZw0M1DFi9ejIkTJ5p5ZYGWnYsvvti4k3bu3Ilx48YZ6w4bU9KcxM+hpSc+Pt5YVu666y4jYpSxJPyWAwdcHarnzcufVrcuVq3bjglLE009mXoxYQgLtnqK4tHtJPeSEEJUkpB59tlnjWtn8uTJ2LVrl5lGC8p9991niteVhe3btxvRcuDAAdSuXRs9evQwqdX8m0yZMgUWiwX9+/cvUBBPCL+E9Y3YAX779vxpY8fC8ehjePvj1cUWxYsIsSLhYAZmLkxAl8Y1CvZeEkIIUXFNI71Tm/05DkVNI0WluJKeeQZ46CET3GuoVcvVtbpPH6zdnYKR769CTJjNiJfCpGfnISUrD89ddQLa1tMxKoQQFRrs646TYTXe//3vf567S7qGGOMiRLVi717ggguM5cUjYnr2BFatMiKmYFG8/AB5bzid87mcEEKICnYtJSQk4PzzzzdBt3T3nHvuuYiOjjbp0HzNtGwhqg0JCYA7IJ2inlaZRx5hyeoSi+IVhtM5n8sJIYQoG2W2yAwfPhwnnXQSEhMTTa0XN5dffnmBDCMhqgUnnwywphEbmX73HfD44wVETIGieKnZSM3KRWJGDtKy80CfLj27LJbXuk6UiuIJIURlWGR+/fVXLFy40FTd9aZZs2bYscOri68QVdWVFB9fUKyMGOHKVKpZs9i3MID31Bbx+HXDPmxLzITFAliDghAWbDFuJaZkD+reVIG+QghRGRYZ1ophJd/iMpDoYhKiykKL4/HHu6wu3tClVIKIIawT8/Hy7QgPtiI6zGbqyNidTqRm5SEjx47+XRsp9VoIISpLyJx33nl4/vnnPa8Z7MsgX9aAuYBBj0JUNfLyXHEv557L0tLAk08CP+U3fjwcDocTMxYmmNTrtvWicUKjWHSsH4v29WPQuXEcakQEY8mmg2Y5IYQQlVRHhsG+7du3R1ZWFq699lrTwbpWrVomi0mIKgXdpddeC/zyS/60884DOnUq1dvX703Fxr1pqBMd6snwiwrLP+0sQUHYsDfNLKfUayGEqAQhwwaMq1atwvvvv2+eaY1hBd7rrruuQPCvEAHPN98AAwcC+/e7XrO/GK0x99/PwJdSrSI/9Tq02PmMkdmflq3UayGEqAwhk5ubi7Zt22Lu3LlGuPAhRCBA1w2tHhQMTHNmhlCJwbW5uS5X0sSJ+dMaNQLmzAFOP71Mn6vUayGE8CMhwyaOdCcJEUgw2JZxKnTx0DpC4cB06MHdmxYNsmVW0uWXAwsX5k+76CJg+vTDBvSWhDv1mj2V2I7A7V6CV+p1xwaxSr0WQojKCvYdNmyYKX7H6r5CBIKIYVPG1TuSTYuARjUizLO7WWORztMsg52e7vqbKdbPPgt88cVRiRhCqw8FU2x4sOmpxHYEdofTPPM1pyv1+titbWwDsXjTAfOswGkhqhdl7rXkLnwXFRWFTp06ITIyssD8Tz75BP6Eei1VX3hBu+f9lUbEeDdrJDzsKSRoDZlyVeeCQmL9eqB/fzjeeBPrW3QonTvqKKxCLIJHEaPU60qytgkhAorSXr/LHOwbFxdnulEL4e/xMH9vT8bqncmo7ZUx5Iava0eFIvnfDdj8B9Cye5f8mW3aYPkX8zHjj23YuHRVuVwg+R52ty51nI4otbWNqe3MCmNANWOO3Na2By9sJzEjRDXgmLpfBwKyyFTfO/TkjBzsS8tBXIQNjeMjERdeMKD2hGULMPSdx2Ft0gQRK5YBh7Luil4gXcG6jGehK0gXyAC2tgkhqm/3a1b0ZWzM6aefjpNPPhljxoxBZmZmeY1XiHKPh6kfFw6bJQgpWXnYsCcVSZmuFGdbbg6umT0Zd79yP6Iz0xCxbo0rrbpQATteIJlpxEq8fG4aH4HkzFzMXJigOAwfU1x9nsLWNnd9HiFE1abUQmb8+PF44IEHTGxMw4YN8cILL5jAXyH8geIECMUMWwKw6Fyu3YHtiRmotXc7xj51E3r/8L7nvc4BV7hqw+gCGTDk1+exFjuf0zlf9XmEqPqUWsjMnDkTr776Kr799lt89tln+PLLLzF79mxjqRHC1xQnQPjMLCVaZWg/6b58PsaNG4hmW9aa+Tm2EKwYMx5LJr6KtZlBRgzpAhkYeNfnKQ7V5xGi+lDqYN+tW7cW6KXUu3dvc6HYuXMnGrFYmBA+pKQKunERwWhfIwQD3puCAUu+9EzfVbcxXrplPFbWbIacz1Z7gnnPOq6WCtgFAKrPI4Qos5Bh3ZiwsLAiBfJY7VcIX1flLamCrjUvFxOn3IFmCS4rDNnW51Lcf+4d2OMMQZ0wW4Fsl20H0xEfGYxdyVm6QPox7vo8jIliYC9dfoWDslWfR4jqQamFDH/EhwwZgtDQ/DteVvm97bbbCtSS8bc6MqJ61Akp6Q7dbgvGys5nGCGTExwK60svYlL0SdizM6VAtgvFD9/Hi2JUaDBiwlwF7HSB9F+4/5lB5j4+2LOKxweFpurzCFF9KHX69dChQ0u1wmnTpsGfUPp14FLWNGj38sws8hYgB1IycN/nL6Lhw/fBesLxGPn+KhMIXJzriBV3meV00xnNsWDdPhWwq2p9tIQQ1bcgnr8JFFG9spCKs5wwDZpF5twXLQqMJ46z4M+PfsX/2p7luUNv3ygeNWdPQ4em8aaMfWm6UTeMC8fzV3XWBTIA4D5pW083KUJUV8pc2VeIyqAsadCei9iMGehwxx1on5ODMz7rjj3tOhcRIGXpRq0LpBBCVMGmkUJUBmVKg2aTxyFDXI+MDATl5aHZq8/h1BY1jRDxtqK4Y2nonirsVXUH89KFpGBeIYQIDCRkREDXCam9dQNw0knGGuPhppuADz8s9n3qRi2EEFULCRnhlxzRcpKahYH/fI/mfc8G1h5KrY6KAmbPBqZOBSIijpjt0qFBrAnsZcVfPjPbRX2UhBAisFCMjAi4OiFp+xMx7rPnceay7/PfcMIJwAcfmM7VpUHdqIUQomogISMCrk7IMx9PRMcVv+YvePvtwHPPAYUKNh4JBfMKIUTgIyEj/JpiLSdnvgh0Ow1gcUa6ka680tfDFEII4SMkZITfFysrYjmp1xl47z2XO6lly/IftBBCiIBBQkb4vL3A4VeyHHj2WVdWUkhI/vR+/Sps3EIIIQIHZS2JCsHdLmD1jmTTDqBRjQjzzF5InM75h4WZSi+9BHTvDsyZAzzwQGUNXQghRAAhISMqvL0AK+haLUHmuWl8hOmFxPYCXK5YEhOB/v2Bu+8GcnJc0377DcjOrtTvIYQQwv+RkBE+bS9QhMWLgRNPBD79NH/avfcCv/ziCu4VQgghvFCMjKjA9gIu4UG7Cyvn5todCLZaXO0F0rJd7QW8XUlMoR4zBsjLc02LjwemTwcuvthH30QIIYS/IyEjKrS9QK7DaSrnpmfb4XA6YQkKQqgtCNFhwWY5w4EDrj5Jc+fmr8QdG9O4sc++hxBCCP9HriVRYe0FtiVmYP3uFKRm5sFmCUJ4sBXWIJh2AIyTSc06ZJF55ZWCIoZWmQULJGKEEEIcEQkZUe6w7svA05oiI8eOrDwHQmwWI2DYnJEWGgqaiBArZi3a6gr4pXA55RSgVi3g66+BCROA4EPWGiGEEOIwyLUkKoTocJvpJE1XUnaeHTlOgHXwosNsaBIdAmtIsCfg1xS7Y7dqqxVo2NDXQxdCCBFAyCIjKgQG8tKd1LFBDDrUj0XbetHm+fKU//Dyk9eh9e7/TECwJ+C3SROJGCGEEGVGQkZUaMBvdp4DUWE2xIdZcfV3M3D/M3eg7t7tuP21BxGbl50f8CuEEEIcBXItiQoN+GUl33qZSbhl6ji0X7PUM393dE0cF+fqvSSEEEIcLRIyosICftlT6YvJ72L49McQn5popjuCLJh57iDMvXgoxp7fscwNJIUQQghvJGRExXStttvR9Z0XcOLLTyCIxe4A7I+piUkDH0HW6WdgbFkaRwohhBAlICEjyr9r9c6dwHXXmVowbumT1vMcJDzzCoY2aVB2USSEEEKUgIJ9Rfl2rSZbt7qaPBKmVE+YgKifvkfXU9qaVGuJGCGEEOWFhIwov67Vbk47DXjqKaBRI1eFXha8s+hQE0IIUf7o6iKOvWv1rl0mJqYA7Fj9119Ajx6VMHIhhBDVFQkZUUzXamux803Xau8idmTePKBTJ+DJJwsuTAtMjRoVPGIhhBDVHQkZUWzX6uLgdM43Rexyc4H77gMuusjVvfqxx4Cff670MQshhKjeKGtJFFvEjk0dvd1LTqcT+9Ky0bFBLNpkHgTOvAb444/8N19yicsyI4QQQlQissiIIkXs2Owx4WAG0rPzTMdqPvM1p9+VuhqWE7vkixh2qX7+eeDTT4F41YURQghRuUjIiAKwTsyDF7ZDhwaxSMnKw/bEDPN8Qp0IvLbsXbS6dRCQlORauHlz4PffgeHDGQ3s66ELIYSohsi1JIoVM10a1/BU9q2Zsh8tb74eQcuW5S80YADw1ltAbKwvhyqEEKKaIyEjSnQzsXidITMCyM52/R0SAkyZAtx+u6wwQgghfI5cS+LIhIcDH3wAdO7sio254w6JGCGEEH6BLDKiKBs2uIRKq1b509q2Bf78UwJGCCGEXyGLjCjI//4HnHiiKwYmK6vgPIkYIYQQfoaETADDnkdrd6dg8aYD5vmIPZAOR2YmcMstwLXXAmlpwKpVwNNPl+dwhRBCiHJHrqUAhV2o2eCRvZHYNoAVd1nMjnVgmHVUJtauBa68Evj77/xpgwa5+iUJIYQQfowsMgEqYsbP+xerdyQjJsyGRjUizDMr8nI655eamTOBrl3zRUxEBDBtGjBjBhAVVWHfQQghhCgPJGQCDLqPaIlJyshFs5oRiAy1wWoJMs9N4yOQnJmLmQsTjuxmSk8Hhg4FBg8GMjJc0zp0AJYuBYYMqZTvIoQQQhwrEjIBBovU0Z1UJzq0QC8kwte1o0KxYW+aWa5EWBPmtNOA6dPzp914I7BkCdC+fQWOXgghhChfJGQCDFbaZUxMWLC12PmczvlcrkRCQ4HLL3f9HRkJzJrlqtJLt5IQQggRQCjYN8CIjQg2gb1ZuXbjTioMp3M+lzss48YB+/e7+iQdd1zFDVgIIYSoDhaZiRMnGtfIPffc45mWlZWFYcOGoWbNmoiKikL//v2xZ88eVGfa1Ik22Un70rLhdBaMg+FrTm9dJ8os54Gp1O++W3BFVivw6qsSMUIIIQIavxAyS5cuxRtvvIHjjz++wPQRI0bgyy+/xIcffoiff/4ZO3fuRL9+/VDdeyAxxTo2PBgJBzOQnp0Hu8Npnvma0wd1b2qWA4XO668Dp57qioFhIK8QQghRhfC5kElLS8N1112HqVOnokaNGp7pycnJePvtt/Hcc8/hnHPOQdeuXTFt2jQsXLgQf7DfTzWGdWIevLAdOjSIRUpWHrYnZpjnjg1izXRTRyYlBbj6aldzRwb35ubS7OXroQshhBBVK0aGrqMLL7wQvXv3xpNPPumZvnz5cuTm5prpbtq2bYsmTZpg0aJFOI1ZN8WQnZ1tHm5SeEGvglCsdGlcw2QnMbCXMTF0JxlLzPLlwFVXAf/9l/+Gu+4CJk3y5ZCFEEKIqiVk5syZgz///NO4lgqze/duhISEIC4ursD0unXrmnklMWHCBDz22GOoDlC0tK0Xkz+BrqSXX3ZV5M3JcU2LjQXeeQeo5i45IYQQVROfuZa2bduG4cOHY/bs2QgLCyu39Y4dO9a4pdwPfk61ICnJ1eiRlhe3iDn5ZGDFCokYIYQQVRafCRm6jvbu3YsTTzwRNpvNPBjQ++KLL5q/aXnJyclBEi/QXjBrqV69eiWuNzQ0FDExMQUe1QK6kj75JP/1yJHAb78BzZv7clRCCCFE1XQt9erVC397NykEK+YPNXEwo0ePRuPGjREcHIwff/zRpF2TdevWYevWrejWrZuPRu3HMJB3wQJXgTv2Sbr4Yl+PSAghhKi6QiY6OhodO3YsMC0yMtLUjHFPv/HGGzFy5EjEx8cby8pdd91lRExJgb7Vmi5dgP/9DzjpJKBJE1+PRgghhKgeWUuHY8qUKbBYLMYiw0ykPn364FUWcavuLFwIvPiiq8hdsFcFX8XCCCGEqGYEOQuXh61iMP06NjbWBP4GfLyMwwE8+yzwwAOA3Q6MHq3aMEIIIar19duvLTLCi337gMGDga+/zp/GwoAsdOdtlRFCCCGqET6v7CtKwS+/AJ0754uYoCDgoYeAH36QiBFCCFGtkUXGn6EracIE4JFHXH+TOnWAWbOAc8/19eiEEEIInyMh46+wy/fAgcD33+dPO+ccl4ipX9+XIxNCCCH8BrmW/BW2GnCLGIsFYNuF776TiBFCCCG8kEXGX3n4YeCbb4AdO4D33gPOOsvXIxJCCCH8DgkZf6Fw9lFICPDRR0B4uCsuRgghhBBFkGvJH6DLqHVrYPXqgtObNpWIEUIIIQ6DhIwvycsDHnwQOP98ICEBuPJKID3d16MSQgghAga5lnzF9u3ANde4OlS7Yafq7GxX40chhBBCHBFZZHzBV1+5Cty5RYzNBkyaBHz5JRAf7+vRCSGEEAGDLDKVHdBLVxJFixt2qp4zB+jWzZcjE0IIIQISCZmjwOFwYv3eVCRn5CI2Ihht6kTDYgk6/JsYA3P11a7+SG4uuQSYNk1WGCGEEOIokZApI8sTDmLGwgRs3JuGnDw7QmxWtKoThcHdm6Jr08MIkm3bgKVLXX8zzZpWmbvvdvVNEkIIIcRRoRiZMoqY8fP+xeodyYgJs6FRjQjz/M/OZDOd80ukRw/giSdcAb2//w4MHy4RI4QQQhwjEjJlcCfREpOUkYtmNSMQGWqD1RJknpvGRyA5MxczFyaY5TxZSe5Gj25GjwZWrgROPtkn30EIIYSoakjIlBLGxNCdVCc6FEGFLCl8XTsqFBv2ppnl8PHHQIcOrs7V3rBnUkxM5Q5cCCGEqMJIyJQSBvYyJiYs2FrsfE53ZmYi7v6RwIABQEoK8MgjLjeSEEIIISoEBfuWEmYnMbA3K9du3EmFidu+BQ9NfQj1tm/In8hKvZ06Ve5AhRBCiGqEhEwpYYo1s5MY2BsRYi3gXjr5j28xcPoERGZnuCaEhQEvvADcfLMCeoUQQogKRK6lUsI6MUyxjg0PRsLBDKRn58GSlYlr3hmP2954OF/EHHccsHgxcMstEjFCCCFEBSMhUwZYJ+bBC9uhQ4NYhO7agbGPD0XvXz/PX2DgQGDZMuD44305TCGEEKLaINfSUYiZLo1rYMOWeqj3XrCZ5gwPR9ArrwBDhsgKI4QQQlQissgcpZvpuBb1EfHpx6YmTBCtMEOHSsQIIYQQlYwsMscCa8UwHkYCRgghhPAJssgcKxIxQgghhM+QkBFCCCFEwCIhI4QQQoiARUJGCCGEEAGLhIwQQgghAhYJGSGEEEIELBIyQgghhAhYJGSEEEIIEbBIyAghhBAiYJGQEUIIIUTAIiEjhBBCiIBFQkYIIYQQAYuEjBBCCCECFgkZIYQQQgQsNlRxnE6neU5JSfH1UIQQQghRStzXbfd1vNoKmdTUVPPcuHFjXw9FCCGEEEdxHY+NjS1xfpDzSFInwHE4HNi5cyeio6MRFBSE6qRkKd62bduGmJgYXw9HeKF9459ov/gn2i/Vd784nU4jYho0aACLxVJ9LTL88o0aNUJ1hQeYTn7/RPvGP9F+8U+0X6rnfok9jCXGjYJ9hRBCCBGwSMgIIYQQImCRkKmihIaGYty4ceZZ+BfaN/6J9ot/ov3in4T60X6p8sG+QgghhKi6yCIjhBBCiIBFQkYIIYQQAYuEjBBCCCECFgkZIYQQQgQsEjJViIkTJ5rqxffcc49nWlZWFoYNG4aaNWsiKioK/fv3x549e3w6zurAo48+avaF96Nt27ae+dovvmPHjh24/vrrzbYPDw9Hp06dsGzZMs985j888sgjqF+/vpnfu3dvbNiwwadjruo0a9asyPnCB88RovPFN9jtdjz88MNo3ry5ORdatmyJJ554okDvI384XyRkqghLly7FG2+8geOPP77A9BEjRuDLL7/Ehx9+iJ9//tm0a+jXr5/Pxlmd6NChA3bt2uV5/Pbbb5552i++ITExEaeffjqCg4Px9ddfY82aNZg8eTJq1KjhWeaZZ57Biy++iNdffx2LFy9GZGQk+vTpYy6mouJ+v7zPle+//95Mv+KKK8yzzhff8PTTT+O1117Dyy+/jH///de85vnx0ksv+df5wvRrEdikpqY6W7du7fz++++dPXv2dA4fPtxMT0pKcgYHBzs//PBDz7L//vsvpbRz0aJFPhxx1WfcuHHOE044odh52i++Y/To0c4ePXqUON/hcDjr1avnnDRpUoH9FRoa6vzf//5XSaMU/A1r2bKl2R86X3zHhRde6LzhhhsKTOvXr5/zuuuu86vzRRaZKgBNrhdeeKEx6XmzfPly5ObmFphO90aTJk2waNEiH4y0ekHzKpudtWjRAtdddx22bt1qpmu/+I4vvvgCJ510krnTr1OnDrp06YKpU6d65m/evBm7d+8usG/Y6+XUU0/VvqkkcnJyMGvWLNxwww3GvaTzxXd0794dP/74I9avX29er1q1yliW+/bt61fnS5VvGlnVmTNnDv78809jmi0MD7CQkBDExcUVmF63bl0zT1QcPJGnT5+O4447zpjKH3vsMZxxxhlYvXq19osP2bRpkzGVjxw5Eg888IA5b+6++26zPwYPHuzZ/twX3mjfVB6fffYZkpKSMGTIEPNa54vvGDNmjOlyTeFotVpNzMz48ePNjRnxl/NFQiaAYfv04cOHG39yWFiYr4cjvHDfsRDGLVHYNG3aFB988IEJiBO+weFwGIvMU089ZV7TIkNxSf8+hYzwPW+//bY5f2jNFL7lgw8+wOzZs/Hee++ZmL+VK1eaZBLuG386X+RaCmBoct27dy9OPPFE2Gw282AgHAOv+DdVMc20vLvxhtH+9erV89m4qyO8m2zTpg02btxotr32i29gZkX79u0LTGvXrp3H7efe/oUzYrRvKoeEhAT88MMPuOmmmzzTdL74jvvuu89YZa6++mqT3Tdw4EATeD1hwgS/Ol8kZAKYXr164e+//zYq2f3g3SbNfu6/mZ1BH6ebdevWmR/tbt26+XTs1Y20tDT8999/5kLatWtX7RcfwYwlbmtv6P+ntYwwzZQ/wN77hqZ1ZmNo31Q806ZNM7FLjPlzo/PFd2RkZMBiKSgT6GKiZdOvzpdKCysWlYJ31hK57bbbnE2aNHH+9NNPzmXLljm7detmHqJiuffee50LFixwbt682fn77787e/fu7axVq5Zz7969Zr72i29YsmSJ02azOcePH+/csGGDc/bs2c6IiAjnrFmzPMtMnDjRGRcX5/z888+df/31l/PSSy91Nm/e3JmZmenTsVd17Ha7OSeYWVYYnS++YfDgwc6GDRs6586da37LPvnkE/M7dv/99/vV+SIhU8WFDA+mO+64w1mjRg3zg3355Zc7d+3a5dMxVgeuuuoqZ/369Z0hISHmh4CvN27c6Jmv/eI7vvzyS2fHjh1Nimjbtm2db775ZoH5TCl9+OGHnXXr1jXL9OrVy7lu3Tqfjbe68O2335qU6uK2tc4X35CSkmKuJxSRYWFhzhYtWjgffPBBZ3Z2tl+dL0H8r/LsP0IIIYQQ5YdiZIQQQggRsEjICCGEECJgkZARQgghRMAiISOEEEKIgEVCRgghhBABi4SMEEIIIQIWCRkhhBBCBCwSMkKIcmHLli0ICgoy7THc/P7776ZHC0vMX3bZZT4dnxCiaiIhI4SfQ3FwuMejjz5aaWM566yzTPfb4mjcuDF27dqFjh07eqaNHDkSnTt3xubNmzF9+vSj+swFCxaU+N13794Nf4Hfj81BhRCVi62SP08IUUYoDty8//77eOSRRwo0PoyKivL8zULddrvddD+vbNhMrnDHWzbKvO2229CoUaNjXj+/c0xMTIFpbDAohKjeyCIjhJ9DceB+xMbGGkuE+/XatWsRHR2Nr7/+2nQJDg0NxW+//YYhQ4YUceXQkkKLiht2sJ0wYYLpYBseHo4TTjgBH330Ubm4ltx/HzhwADfccIP5222RWb16Nfr27WsEWN26dTFw4EDs37//iOunaPHeFnywM29WVhY6dOiAW265pYCA4nZ55513ClhLPvvsM7Ru3RphYWHo06cPtm3bVuAzPv/8c5x44olmfosWLfDYY48hLy/PMz8pKQm33nqrGTeXofVp7ty5xmo0dOhQJCcnF7GUvfvuu6YTPcfDMV977bXYu3dvEYsTOwhzuYiICHTv3r1Il+4vv/wSJ598svncWrVq4fLLLzfTH3/88QJWMDe0hD388MOl3n9CBCoSMkJUAcaMGYOJEyfi33//xfHHH1+q91DEzJw5E6+//jr++ecfjBgxAtdffz1+/vnnYx6P281EC8rzzz9v/r7qqquMEDjnnHPQpUsXLFu2DN988w327NmDK6+88qg/ixf22bNnY8aMGUaI0CLF73HuuecaEeUmIyMD48ePN9+ZsTscy9VXX+2Z/+uvv2LQoEEYPnw41qxZgzfeeMMIIL7HLfwowPjeWbNmmWW4zWmJovDg9+T35XflY9SoUeZ9ubm5eOKJJ7Bq1SojpCjyKDQL8+CDD2Ly5Mlmu9Ci5j32efPmGeFywQUXYMWKFUb0nHLKKWYel+N+X7p0qWd5LvPXX38ZcSVEladSW1QKIY6JadOmOWNjYz2v58+fbzoGf/bZZwWWGzx4sPPSSy8tMI1dbNkdnWRlZZkuwgsXLiywzI033ui85pprSt1d3ZvNmzebsaxYscIzjWPlmN088cQTzvPOO6/A+7Zt21Zi12Pv7xgZGVng0b59+wLLPfPMM85atWo577zzTtN5fP/+/Z55HAPX8ccff3im/fvvv2ba4sWLzWt27X3qqacKrPPdd98163J3Z7ZYLCWOs/C+KYmlS5eaz01NTS3w/X744QfPMvPmzTPT2PWZdOvWzXndddeVuM6+ffs6b7/9ds/ru+66y3nWWWcdcSxCVAUUIyNEFYAuibKwceNGY6Gg1cKbnJwcYy2pKGiVmD9/foG4Hm93UJs2bUp8Ly0mdM+4YSaUN/fee6+xeLz88svG1VazZs0C82nloGvGTdu2bY27idYMWjc4Nlpb3BYYQusOXVfcVnSZMdbncGMsjuXLlxs3E9efmJhoLDtk69ataN++vWc5b0ta/fr1zTNdUE2aNDGfffPNN5f4GZxHy8xzzz1n3G3vvfcepkyZUqZxChGoSMgIUQWIjIws8JoXMwb+ekMXh5u0tDSPy6Jhw4YFlmOcTUXBz7344ovx9NNPF5nnvniXBGN5DpcVxIv++vXrjatnw4YNOP/888s8NsbE9OvXr1j3FeOIykp6erqJxeGD7q/atWsbAcPXFI3eeAszxswQt+g50mdzm3K/ffrppwgJCTH7esCAAWUerxCBiISMEFUQXjAZVOsN7+rdF0taAnjh40W1Z8+elTYuBtJ+/PHHaNasWblnVtEiwZo1N954o7FQ9O7dG+3atfPMZ9Au40/csSUMpmWcjHsZjo3TWrVqVez6aTHZvn27EUvFWWUoIGjB8YbB2Ax4ZiwN44YIx1BW+NmMiykp5oXbcvDgwZg2bZoZB2N/jkZ4CRGISMgIUQVhQO2kSZNMYGu3bt1McCqFjdttRBcNg1EZ4Mu7/h49epiMG7pWGLDKi2JJ7Nu3r0DRu9JYU9wMGzYMU6dOxTXXXIP7778f8fHxxs01Z84cvPXWW8aacjiLC9083tB9RHH2yiuvYNGiRSbAlYKBlqbrrrsOf/zxh7mwEy5311134cUXXzQX/jvvvBOnnXaaR9gwrf2iiy4yrhxaM2jVojuI2+3JJ580gu/MM89E//79jQuHgodChdYTWn8ozmjVoeBgBhizj7gufv5LL71k0tC5Lgb+lpVx48ahV69eaNmypREpFGVfffUVRo8e7Vnmpptu8ogy7kchqg2+DtIRQhx7sG9iYmKRZR955BFn3bp1zfIjRowwQbDuYF/icDiczz//vPO4445zBgcHO2vXru3s06eP8+effy7x8/l+fl7hB4N4SxPsS9avX++8/PLLnXFxcc7w8HBn27Ztnffcc48ZT3G4v2Nxj0WLFpmgXa7nvffe87yH26Nx48bO+++/v8B2+/jjj50tWrRwhoaGOnv37u1MSEgo8FnffPONs3v37mZ9MTExzlNOOcX55ptveuYfOHDAOXToUGfNmjWdYWFhzo4dOzrnzp3rmX/bbbeZeRzbuHHjzDSOq1mzZuYzGbT7xRdfFNhOxe1DzuM0blM3HHvnzp2dISEhJqi5X79+RbbVGWec4ezQoUOJ+0+IqkgQ//O1mBJCiIqEadSso0NXUlWFP+WskXPHHXeYispCVBfkWhJCiACH7j6659iyQbVjRHVDQkYIIQIcVj1mtd8333wTNWrU8PVwhKhU5FoSQgghRMCiFgVCCCGECFgkZIQQQggRsEjICCGEECJgkZARQgghRMAiISOEEEKIgEVCRgghhBABi4SMEEIIIQIWCRkhhBBCBCwSMkIIIYRAoPJ/vVoowwjLZq4AAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(y_test, y_pred, alpha=0.7)\n", "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--', lw=2, label='Perfect Prediction')\n", "plt.xlabel(\"True Life Expectancy\")\n", "plt.ylabel(\"Predicted Life Expectancy\")\n", "plt.title(f\"True vs Predicted Life Expectancy (MAPE: {mape:.2f}%)\")\n", "plt.legend()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Function 3: Mean Absolute Error\n", "\n", "Predicting life expectancy is a critical task in understanding global health and socioeconomic trends. Using the countries dataset, we’ve built a simple linear regression model to predict life expectancy based on features such as fertility rate, population trends, and previous life expectancy. But how well does our model perform?\n", "\n", "This is where the Mean Absolute Error (MAE) comes in. MAE tells us, on average, how far off our predictions are from the actual values in the dataset. It’s an intuitive metric for assessing the accuracy of regression models, especially when working with interpretable values like years.\n", "\n", "An MAE value tells us how many years, on average, our model’s predictions deviate from the true life expectancy." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MAE: 0.86\n" ] } ], "source": [ "from matrics_calculator.MAE import mean_absolute_error\n", "\n", "# Calculate MAE\n", "mae = mean_absolute_error(y_test, y_pred)\n", "print(f\"MAE: {mae:.2f}\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "An MAE of 0.86 years means that our model's predictions of life expectancy are, on average, off by less than a year for each country. This is quite accurate given the diversity in the dataset, which spans countries with vastly different health and development profiles." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To understand where the model performs well and where it struggles, let’s visualize the residuals (the difference between actual and predicted life expectancy):" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "# Calculate residuals\n", "residuals = y_test - y_pred\n", "\n", "# Plot residuals\n", "plt.scatter(y_pred, residuals, alpha=0.7, label=\"Residuals\")\n", "plt.axhline(0, color='r', linestyle='--', label=\"Zero Error Line\")\n", "plt.xlabel(\"Predicted Life Expectancy\")\n", "plt.ylabel(\"Residuals (True - Predicted)\")\n", "plt.title(\"Residual Plot\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This residual plot shows how far off the model's predictions are from the actual life expectancy values. Most residuals are scattered closely around the zero error line, indicating reasonably accurate predictions, but the large outlier suggests the model struggled with at least one observation, likely due to unique or missing factors." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# True vs. Predicted Plot\n", "plt.scatter(y_test, y_pred, alpha=0.7, label=\"Predictions\")\n", "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--', lw=2, label=\"Perfect Prediction\")\n", "plt.xlabel(\"True Life Expectancy\")\n", "plt.ylabel(\"Predicted Life Expectancy\")\n", "plt.title(\"True vs Predicted Life Expectancy\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above plot compares the actual life expectancy values to the model's predictions. Ideally, points should line up along the 45° line, which would mean the predictions are spot on—any deviations from this line show where the model is off." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Function 4: Mean Squared Error\n", "\n", "Accurate predictions are critical when estimating life expectancy, as it helps understand global health and socioeconomic trends. While MAE gives the average deviation, Mean Squared Error (MSE) provides insight into how large errors are squared, emphasizing larger deviations. This makes it particularly useful for penalizing outliers.\n", "\n", "Below is an example of how to use the mean_squared_error function with our life expectancy dataset and trained regression model." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MSE: 2.22\n" ] } ], "source": [ "# Import the MSE function from our custom package\n", "from matrics_calculator.MSE import mean_squared_error\n", "\n", "# Calculate MSE\n", "mse = mean_squared_error(y_test, y_pred)\n", "print(f\"MSE: {mse:.2f}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "An MSE of 2.22 means that, on average, the squared difference between the actual life expectancy and the predicted values is approximately 2.22 years. This emphasizes any significant deviations, making it easier to identify where the model’s predictions fall short.\n", "\n", "To understand where the model struggles, let’s visualize and compare predictions with the actual data." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# True vs Predicted plot\n", "plt.scatter(y_test, y_pred, alpha=0.7, label=\"Predictions\")\n", "plt.plot(\n", " [y_test.min(), y_test.max()],\n", " [y_test.min(), y_test.max()],\n", " \"r--\",\n", " lw=2,\n", " label=\"Perfect Prediction\",\n", ")\n", "plt.xlabel(\"True Life Expectancy\")\n", "plt.ylabel(\"Predicted Life Expectancy\")\n", "plt.title(\"True vs Predicted Life Expectancy\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The True vs. Predicted plot compares the actual life expectancy values to the model’s predictions. Ideally, points should lie along the 45° line. Deviations indicate where the model’s predictions are inaccurate, highlighting possible areas for improvement in the feature set or model architecture.\n", "\n", "By combining the numeric output (MSE value) with these visualizations, users can better understand their model’s performance and identify patterns in prediction errors." ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "mc", "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": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 4 }