{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Iris classification" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook will walk through the process of using the ITEA for classification (``ITEA_classifier``) and interpreting the final expression with the ``itea.inspection`` tools." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "\n", "# automatically differentiable implementation of numpy\n", "import jax.numpy as jnp # v0.2.13\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "from sklearn import datasets\n", "from sklearn.metrics import classification_report\n", "\n", "from sklearn.model_selection import train_test_split\n", "from IPython.display import display, Latex\n", "\n", "from itea.classification import ITEA_classifier\n", "from itea.inspection import *\n", "\n", "import warnings\n", "warnings.filterwarnings(action='ignore', module=r'itea')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use the Iris data set in this example.\n", "\n", "This data set contains 3 different classes of Iris flowers and has 4 features: sepal width, sepal length, petal width, and petal length.\n", "\n", "One example of each flower is illustrated in the figure below.\n", "\n", "![](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Machine+Learning+R/iris-machinelearning.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Creating and fitting an ``ITEA_classifier``\n", "\n", "In this execution, we will fix the random_state argument to allow reproductible executions of the ITEA algorithm.\n", "\n", "The IT expression is used as the decision function in a logistic regression. The inner logistic regression uses the saga solver described in _\"Defazio, A., Bach F. & Lacoste-Julien S. (2014). SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives\"_.\n", "\n", "The method will solve a **multinomial** classification problem with the softmax funcion applied over the decision function. By default, no regularization os performed (although the user can controlate this by setting values to alpha and beta parameters), and a maximum of 100 iterations of the saga solver is performed for each expression." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "gen | smallest fitness | mean fitness | highest fitness | remaining time\n", "----------------------------------------------------------------------------\n", " 0 | 0.560000 | 0.848200 | 0.970000 | 0min32sec \n", " 5 | 0.740000 | 0.961800 | 0.980000 | 0min22sec \n", " 10 | 0.790000 | 0.969400 | 0.990000 | 0min23sec \n", " 15 | 0.950000 | 0.982200 | 0.990000 | 0min17sec \n", " 20 | 0.890000 | 0.982200 | 0.990000 | 0min18sec \n", " 25 | 0.860000 | 0.982400 | 0.990000 | 0min18sec \n", " 30 | 0.930000 | 0.981800 | 0.990000 | 0min11sec \n", " 35 | 0.960000 | 0.982600 | 0.990000 | 0min8sec \n", " 40 | 0.940000 | 0.981600 | 0.990000 | 0min5sec \n", " 45 | 0.660000 | 0.973800 | 0.990000 | 0min2sec \n" ] } ], "source": [ "iris_data = datasets.load_iris()\n", "X, y = iris_data['data'], iris_data['target']\n", "labels = iris_data['feature_names']\n", "targets = iris_data['target_names']\n", "\n", "# changing numbers to the class names\n", "y_targets = [targets[yi] for yi in y]\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(\n", " X, y_targets, test_size=0.33, random_state=42)\n", "\n", "# Creating transformation functions for ITEA using jax.numpy\n", "# (so we don't need to analytically calculate its derivatives)\n", "tfuncs = {\n", " 'id' : lambda x: x,\n", " 'sqrt.abs' : lambda x: jnp.sqrt(jnp.abs(x)), \n", " 'log' : jnp.log,\n", " 'exp' : jnp.exp\n", "}\n", "\n", "clf = ITEA_classifier(\n", " gens = 50,\n", " popsize = 50,\n", " max_terms = 2,\n", " expolim = (-1, 1),\n", " verbose = 5,\n", " tfuncs = tfuncs,\n", " labels = labels,\n", " simplify_method = 'simplify_by_var',\n", " fit_kw = {'max_iter':100},\n", " random_state = 42,\n", ").fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the ``ITEA_classifier`` and the best solution found by the ITEA ``ITExpr_classifier`` are both scikit-like models, we can use some base methods like ``get_params``.\n", "\n", "In the cell below we inspect the parameters of the best expression. We can see the logistic regression regularization parameters (alpha and beta), the maximum number of iterations of the coefficients adjustment algorithm (max_iter), and the array of IT terms (expr), containing the terms that are being used to create the decision function for the logistic regression." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'alpha': 0.0,\n", " 'beta': 0.0,\n", " 'expr': [('id', [0, -1, 1, 1]), ('id', [1, -1, -1, 0])],\n", " 'fitness_f': None,\n", " 'labels': array(['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)',\n", " 'petal width (cm)'], dtype='(x)>,\n", " 'sqrt.abs': (x)>,\n", " 'log': .(x)>,\n", " 'exp': .(x)>}}" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# clf.get_params() returns the ITEA parameters\n", "# clf.bestsol_.get_params() returns the best expression parameters\n", "\n", "clf.bestsol_.get_params()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspecting the results from ``ITEA_classifier`` and ``ITExpr_classifier``\n", "\n", "Now that we have fitted the ITEA, our ``clf`` contains the ``bestsol_`` attribute, which is a fitted instance of ``ITExpr_classifier`` ready to be used." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'[-5.254 0.243 5.012]*id(sepal width (cm)^-1 * petal length (cm) * petal width (cm))\\n[ 5.245 0.224 -5.469]*id(sepal length (cm) * sepal width (cm)^-1 * petal length (cm)^-1)\\n[ 4.124 3.503 -7.627]'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final_itexpr = clf.bestsol_\n", "\n", "final_itexpr.to_str(term_separator='\\n')" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " setosa 1.00 1.00 1.00 19\n", " versicolor 0.94 1.00 0.97 15\n", " virginica 1.00 0.94 0.97 16\n", "\n", " accuracy 0.98 50\n", " macro avg 0.98 0.98 0.98 50\n", "weighted avg 0.98 0.98 0.98 50\n", "\n" ] } ], "source": [ "print(classification_report(\n", " y_test,\n", " final_itexpr.predict(X_test),\n", " target_names=targets\n", "))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can use the ``ITExpr_inspector`` to obtain metrics regarding the IT terms in the expression" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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coeffuncstrengthscoef\\nstderr.mean pairwise\\ndisentanglementmean mutual\\ninformationprediction\\nvar.
0[-5.254 0.243 5.012]id[0, -1, 1, 1][3.978 1.134 1.431]0.7660.905[63.693 0.136 57.947]
1[ 5.245 0.224 -5.469]id[1, -1, -1, 0][14.394 7.012 10.91 ]0.7660.905[2.26 0.004 2.458]
2[ 4.124 3.503 -7.627]intercept---[13.579 6.165 7.181]0.0000.000[0. 0. 0.]
\n", "
" ], "text/plain": [ " coef func strengths coef\\nstderr. \\\n", "0 [-5.254 0.243 5.012] id [0, -1, 1, 1] [3.978 1.134 1.431] \n", "1 [ 5.245 0.224 -5.469] id [1, -1, -1, 0] [14.394 7.012 10.91 ] \n", "2 [ 4.124 3.503 -7.627] intercept --- [13.579 6.165 7.181] \n", "\n", " mean pairwise\\ndisentanglement mean mutual\\ninformation \\\n", "0 0.766 0.905 \n", "1 0.766 0.905 \n", "2 0.000 0.000 \n", "\n", " prediction\\nvar. \n", "0 [63.693 0.136 57.947] \n", "1 [2.26 0.004 2.458] \n", "2 [0. 0. 0.] " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(pd.DataFrame(\n", " ITExpr_inspector(\n", " itexpr=final_itexpr, tfuncs=tfuncs\n", " ).fit(X_train, y_train).terms_analysis()\n", "))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By using the ``ITExpr_texifier``, we can create formatted LaTeX strings of the final expression and its derivatives." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$ ITExpr = \\underbrace{\\beta_0 \\cdot id(\\frac{petal length (cm) \\cdot petal width (cm)}{sepal width (cm)})}_{\\text{term 0}} + \\underbrace{\\beta_1 \\cdot id(\\frac{sepal length (cm)}{sepal width (cm) \\cdot petal length (cm)})}_{\\text{term 1}} + I_0$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# The final expression\n", "display(Latex(\n", " '$ ITExpr = ' + ITExpr_texifier.to_latex(\n", " final_itexpr,\n", " term_wrapper=lambda i, term: r'\\underbrace{' + term + r'}_{\\text{term ' + str(i) + '}}'\n", " ) + '$'\n", "))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$ \\frac{\\partial}{\\partial sepal length (cm)} ITExpr = \\underbrace{1\\beta_1 \\cdot id'(\\frac{sepal length (cm)}{sepal width (cm) \\cdot petal length (cm)})(\\frac{1}{sepal width (cm) \\cdot petal length (cm)})}_{\\text{term 1 partial derivative}}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# List containing the partial derivatives\n", "derivatives_latex = ITExpr_texifier.derivatives_to_latex(\n", " final_itexpr,\n", " term_wrapper=lambda i, term: r'\\underbrace{' + term + r'}_{\\text{term ' + str(i) + r' partial derivative}}'\n", ")\n", "\n", "# displaying one of its derivatives\n", "display(Latex(\n", " r'$ \\frac{\\partial}{\\partial ' + labels[0] + '} ITExpr = ' + derivatives_latex[0] + '$'\n", "))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Explaining the ``IT_classifier`` expression using Partial Effects\n", "\n", "Now let's create an instance of ``ITExpr_explainer``.\n", "\n", "We can calculate feature importances with Partial Effects (PE) or approximate the Shapley values using PE. There is also support to use Integrated Gradients as a feature importance method." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# First lets create and fit the explainer with training data\n", "\n", "explainer = ITExpr_explainer(\n", " itexpr=final_itexpr,\n", " tfuncs=tfuncs\n", ").fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for method, method_name in [\n", " ('pe', 'Partial Effects'),\n", " ('shapley', 'Shapley Values'),\n", " ('ig', 'Integrated Gradients')\n", "]:\n", " explainer.plot_feature_importances(\n", " X = X_train,\n", " importance_method = method,\n", " grouping_threshold = 0.0,\n", " target = None,\n", " barh_kw = {'edgecolor' : 'k'},\n", " show = False\n", " )\n", " \n", " # when we call a plot function, the explainers' axes_\n", " # will be the axes of the last plot. we called the plot function\n", " # with show=False to access the plot to add a title and then\n", " # we explicitly used the show() method to display the plots\n", " explainer.axes_.set_title(method_name)\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can explain a single instance as well:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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1TaWlpaxdu5YtW7aoTWrTfm3T3li0b8f1CXpes4G/u/tjdZR5E3jQ3f8VLL8D3Onui2uUm0mk51nTY9GSrZn1JXLdcgLwPeBG4GN3f7pGue7Ae+5+QrB8QbDPGOAz4FR3X29mkwHcfXIwzDrb3WfVqOtaIgn8QmAwkcSbFZSdHdRRAjxD5HrqnmOmAi+6e4qZpQfHvCXYNhkocfdHguVcYLi759c49hbgaHevCL5gdHH3n9UoUxl30O7ZQW+dmm0KhsFHufsnUc75nvr8hEmza63/7KFIxz8lI6WuXaUJ5abnRu29lpWV0atXL+bOnUvXrl0ZNGgQL774IsnJ1b8vbt26lR49erB+/XqOPPJIAL788kvatGlDx44dKS0tZejQoUyaNInhw+sc1BGR2NR5CbIxdx0b8Cywsq4kG1hHJDFhZt8lkkw/rVmoIT1aMzsp6Kk9RGQItw/wd+D6oIeNmXU1sy7BLseb2Z4h3DHAB0DbYLko2CeWu4zfB64G1gS9xM1Ekv38qoXc/Wtgq5nt6TlfVWXzNqB9DMeqaTVwYvB+LnDlnqFfM+tc515RBH93xwL5jYhDDhBxcXE8+eSTXHzxxSQlJXHllVeSnJzMtGnTmDZtWmW5V199laFDh1YmWYDCwkKGDBlCamoqgwYN4qKLLlKSFQlZXCP2OQu4Bsgxs6xg3U/d/W9mNg4id+ECvwAyguFZAybtGfLcB7eb2RCgHMgD3nL3nWaWBCwIrlOVEEmK5URu1LrOzJ4G1gBPuft2M/s9kSHWfOCj+g7q7vlB3e8Hqz4AEoNrnjWNBf5gZtuJfAnYYx5wZ3DOHmhAm98kctf2J+6+wsz+F3jPzMqJDJenN6CugcDCYMhdDmLDhg1j2LDqN7GPGzeu2nJ6ejrp6enV1qWmprJs2bKwwxORKho1dHwwqDmEerAyswTgT+5+URPU9QTwurvPraecho4PAHUNHYvIAanpho5l/3L3QuD30W4ka4Tc+pKsiIg0rcYMHR8UgpuKDomul7u/1ET1/L4p6hERkdipRysiIhIiJVoREZEQKdGKiIiESIlWREQkREq0IiIiIVKiFRERCZESrYiISIiUaEVEREKkRCsiIhIiJVoREZEQKdGKiIiESIlWREQkREq0IiIiITpk56OVxmsTH+9lu3fXWn9EfGt2GZTtLG+GqFqehMQENq7f2NxhiEhs6pyP9pCdJk8ar19qKpmZmc0dhojIIUFDxyIiIiFSohUREQmREq2IiEiIlGhFRERCpEQrIiISIiVaERGRECnRioiIhEiJVkREJERKtCIiIiHSIxillroewdgqvhUVuyqaIaKWR49fFDno1PkIRiVaqcXM/IRJs2ut/+yh4aRkpDRDRC1Pbnou+rcpclCpM9Fq6FhERCRESrQiIiIhUqIVEREJkRKtiIhIiJRoRUREQqREKyIiEiIlWhERkRAp0YqIiIRIiVZERCRESrQiIiIhUqIVEREJkRKtiIhIiJRoRUREQqREKyIiEiIlWpGDzJw5c+jduzc9e/bkwQcfrLX94YcfJi0tjbS0NFJSUmjdujWbN29m/fr1DBkyhKSkJJKTk3niiSeaIXqRlqdBidbMWpvZMjOrPVlpZPsdZpYVvHLNrNzMOjdNqDHH2NHMxsdYtqQh6/eFmaWZ2bAqy5PNbGIM+5mZvWNmHZoghrfNrNO+1iPNp7y8nJtvvpm33nqLvLw8ZsyYQV5eXrUyd9xxB1lZWWRlZfHAAw9w3nnn0blzZ+Li4nj00UdZuXIlCxcuZOrUqbX2FZGm19Ae7W3Ayro2uvvD7p7m7mnAXcB77r55H+JrjI5ATIl2P0sDhtVXKIphQLa7FzdBDNM5MM+NxGjx4sX07NmTE088kfj4eEaPHs1rr71WZ/kZM2YwZswYABISEhgwYAAA7du3JykpiYKCgv0St0hLFnOiNbNE4DLgmRh3GQPMaExQNY472cymB726NWZ2Y5Vtd5jZR2a23Mx+Hqx+EDgp6FU/bGbtzGyumS01sxwzu7yBx691DDPrbmYrzez3ZrbCzP5hZocH2wYFZRcEx881s3jgfmBUENeooPpTzOxdM/vUzG6tI4SrgMr/Sc3s2qD+bDObHqzLMLOnzGxeUNd5ZvaHIMaMKnW9TuTvRQ5SBQUFdOvWrXI5MTGxzmS5fft25syZw4gRI2pty8/PZ9myZZx++umhxSoiEXENKDsF+B+gfX0FzewI4BLgljq2zwR6R9n0mLv/Kcr6VOAM4EhgmZm9CaQAJwOnAQa8bmbnAncCKUGvGjOLA37k7sVmdgyw0Mxed3ePoR1D6zjGumD9GHe/0cxeAkYAzwPPATe5+4dm9iCAu+8ys3uBU939lqDuyUAfYAiRc7razJ5y9901wjgL+M9gn2TgbuAsdy+qMSzfCbgA+AHwRrDfDcBHZpbm7lnuvsXMDjOzo939q/raLweeaB9bM4ta9o033uCss86ic+fqV29KSkoYMWIEU6ZMoUOHfb4iISL1iKlHa2bDgU3uviTGer8PzK9r2NjdR+0ZYq7xipZkAV5z91J3LwLmEUl8Q4PXMmApkaR1crTwgV+Z2XLgbaAr8N0Y27G3Y/zb3bOC90uA7mbWEWjv7h8G61+sp/433X1n0K5NdcTV2d23Be8vAGYF5alxft8IvjzkAF+4e467VwArgO5Vym0Cjqt5EDO7ycwyzSyznphlP1myZEm1P7Ozszn22GNZtWoVJSUl5Ofns3r1atq3b09BQQFbtmxh7dq1lJaWVl6/PeOMM6rVsWjRIv7jP/6DCy+8kEsvvZS1a9eyZcsWCgoKKCwspKioiPz8fEpKSli1ahVlZWVkZ2dHjScnJ4edO3eyZs0aiouLWbduHZs2bWLTpk2sW7eO4uJi1qxZw86dO8nJyamzTWVlZdXaVFRURGFhYdQ2VVRUsHTp0mp1LF26lIqKCvLy8igtLVWb1KZmadPeWAwdO8zsAeAaoAxoC3QAXnH3q+so/yrwF3ePmmga0qMNen7m7vcFy38CXgbOBT5296drlO8OzHb3lGA5HbgUuNrdd5tZPnC+u+ebWYm7t4sSX4m7tzOzR2M8xkSgHfAEkOXuJwTrU4EX3T0liKNmj7bE3R8JlnOB4e6eX+NYW4Cj3b0iGF7u4u4/q1EmI4hnVpTYKrcFy0uAUe7+Sc12V6nPT5hU+363zx4aTkpGSl27SRPKTc+N2nstKyujV69ezJ07l65duzJo0CBefPFFkpOTq5XbunUrPXr0YP369Rx55JFApDd83XXX0blzZ6ZMmbI/miHSkkQfWiLGHq273+Xuie7eHRgNvLOXJHsUcB5VritGqa+hPdrLzaytmR0NnA98BPwduN7M2gXH7WpmXYBtVB/ePopIb3y3mQ0BToilzYG6jlFXu7YA28zsjGDV6Cqba8YVq9XAicH7ucCVwXnAGnhHt0XGGI8F8hsRhxwA4uLiePLJJ7n44otJSkriyiuvJDk5mWnTpjFt2rTKcq+++ipDhw6tTLIA8+fPZ/r06bzzzjuVP//529/+1hzNEGlRGnKNNiozGwfg7nv+lf8I+Ie7f7OvdVexGHgTOB74hbtvBDaaWRKwILhGVUKk17rWzOYHPcS3gIeAN4Ih0SxgVawHdfd/RDsGUL6X3X4M/N7MvgHeBbYG6+cBd5pZFvBArDEQaff5wCfuvsLM/hd4z8zKiQxppzegroHAQncva8A+coAZNmwYw4ZVv4F93Lhx1ZbT09NJT0+vtu7ss8+O2ksWkXDFNHTcnGoOsR7ozKydu5cE7+8EEtz9tn2oLwH4k7tf1ASxPQG87u5z6ymnoeNmVtfQsYgcsOocOt7nHq3UcpmZ3UXk3H5Gw3qctbh7YfAzog5N8Fva3PqSrIiINK0DPtG6++TmjqEh3H0mMLOJ63ypier5fVPUIyIisdOzjkVEREKkRCsiIhIiJVoREZEQKdGKiIiESIlWREQkREq0IiIiIVKiFRERCZESrYiISIiUaEVEREKkRCsiIhIiJVoREZEQKdGKiIiESIlWREQkRAf8fLSy/7WJj/ey3btrrW8V34qKXRXNEFHLk5CYwMb1G5s7DBGJneajldj1S00lMzOzucMQETkkaOhYREQkREq0IiIiIVKiFRERCZESrYiISIiUaEVEREKkRCsiIhIiJVoREZEQ6Xe0IiKHuN27d7NhwwZ27NjR3KEc9Nq2bUtiYiJt2rSJeR8lWhGRQ9yGDRto37493bt3x6zOBxhJPdydr776ig0bNtCjR4+Y99PQsdSSlbWMNm3jMLMGv47rdlxzhy8iNezYsYOjjz5aSXYfmRlHH310g0cG1KOVWsrLK6AcUjJSGrxvbnpuCBGJyL5Skm0ajTmP6tGKiIiESIlWRKSFSUg8vlGXhup6JSQe32SxZWRksHHjoTVzlYaORURamM8L1nPCpNlNVt9nDw1vsroyMjJISUnhuOMOnfs91KMVEZFQffPNN1x22WX069ePlJQUZs6cyZIlSzjvvPMYOHAgF198MYWFhcyaNYvMzEyuuuoq0tLSKC0tZe7cufTv35++ffty/fXXs3PnTgDuvPNOTjnlFFJTU5k4cSIAb7zxBqeffjr9+/fne9/7Hl988UVzNruSEq2IiIRqzpw5HHfccWRnZ5Obm8sll1zChAkTmDVrFkuWLOH666/n7rvvZuTIkZx66qm88MILZGVlYWakp6czc+ZMcnJyKCsr46mnnmLz5s28+uqrrFixguXLl/Ozn/0MgLPPPpuFCxeybNkyRo8ezf/93/81c8sjNHQsIiKh6tu3LxMnTmTSpEkMHz6cTp06kZuby0UXXQRAeXk5CQkJtfZbvXo1PXr0oFevXgBcd911TJ06lVtuuYW2bdtyww03cNlllzF8eGToesOGDYwaNYrCwkJ27drVoN+6hkk9WhERCVWvXr1YsmQJffv25a677uLll18mOTmZrKwssrKyyMnJ4R//+Eet/dw9an1xcXEsXryYESNG8Ne//pVLLrkEgAkTJnDLLbeQk5PD008/fcA8CUuJVkREQrVx40aOOOIIrr76aiZOnMiiRYv48ssvWbBgARB5ROSKFSsAaN++Pdu2bQOgT58+5Ofn88knnwAwffp0zjvvPEpKSti6dSvDhg1jypQpZGVlAbB161a6du0KwB//+Mf93Mq6aehYRKSFObZrtya9U/jYrt32uj0nJ4c77riDVq1a0aZNG5566ini4uK49dZb2bp1K2VlZdx+++0kJyeTnp7OuHHjOPzww1mwYAHPPfccV1xxBWVlZQwaNIhx48axefNmLr/8cnbs2IG78/jjjwMwefJkrrjiCrp27coZZ5zBv//97yZr476wurrm0nKZmUPjnwylz5TIgWXlypUkJSU1dxiHjDrOZ52PjNLQsYiISIiUaEVEREKkRCsiIhIiJVoREZEQKdHKfjNnzhx69+5Nz549efDBB2ttX7VqFYMHD+awww7jkUceqbbt+uuvp0uXLqSkNPwGLRGR5lRvojWzjmY2y8xWmdlKMxscpUwfM1tgZjvNbGI4oTYtM8sws5Gxrm+C4/20yvvuZhbTxK1mdruZXdsEx7/FzMbuaz2NVV5ezs0338xbb71FXl4eM2bMIC8vr1qZzp078+tf/7ryuaVVpaenM2fOnP0VrohIk4mlR/sEMMfd+wD9gJVRymwGbgUeibJNIn5af5HqzCwOuB54sQmO/wcif0fNYvHixfTs2ZMTTzyR+Ph4Ro8ezWuvvVatTJcuXRg0aBBt2rSptf+5555L586d91e4Ioe07okJTTpNXvfE2o9PDNu9997L22+/3eD93n333cpHNu4ve31ghZl1AM4F0gHcfRewq2Y5d98EbDKzy5oqMDM7j0iSB3DgXHffZmZ3AFcChwGvuvt9ZtYdmAMsAvoDHwPXuvt2M7sX+D5wOPAh8J8e4w89zWwg8BjQDigC0t290MzeDY41BOgI/Njd/2VmRwAZQB8iX0i6AzcDI4HDzSwLWAHcDbQ2s98DZwIFwOXuXlojhAuApe5eFsTTE5gGfAcoB64AugE/B74A0oBXgBzgtqDNP3T3tcG5yDez09x9cSztb0oFBQV06/btj9oTExNZtGjR/g5DRIDPCj7H7+vQZPXZzz9vsrqqcnfcnVatavcJ77///lCOWVNZWRlxcfv2bKf6erQnAl8Cz5nZMjN7xsyObOzBzGymmWVFeUUbGp0I3OzuacA5QKmZDQVOBk4jklQGmtm5QfnewO/cPRUoBsYH659090HunkIk8cT0VcbM2gC/AUa6+0AiPcL/rVIkzt1PA24H7gvWjQe2BDH8AhgI4O53AqXunubuVwVlTwamunsy8DUwIkoYZwFLqiy/EOzTj0iCLgzW9yOSWPsC1wC9gtieASZU2T+TyLnc76J9tzGr8/fdInIImTRpEr/97W8rlydPnsyjjz7Kww8/zKBBg0hNTeW++yL/jebn55OUlMT48eMZMGAA69evJz09nZSUFPr27Vv5FKj09HRmzZoFwEcffcSZZ55Jv379OO2009i2bRs7duxg7Nix9O3bl/79+zNv3rxacW3evJkf/vCHpKamcsYZZ7B8+fLK+G666SaGDh3Ktdfu85W7ehNtHDAAeMrd+wPfAHc29mDuPipINjVff4pSfD7wmJndCnQMenVDg9cyYCmRnuPJQfn17j4/eP88cHbwfoiZLTKzHCI9xOQYw+0NpAD/DHqiPwMSq2x/JfhzCZGeK8Ex/xy0NRdYvpf6/+3uWVHqqCqByBcdzKw90NXdXw3q3+Hu24NyH7l7obvvBNYCe57OnVOj3k1A1NmUzewmM8s0s8y9xByT0tJS1q5dy5YtWygoKKCwsJB27drx8ccfU1JSwqpVq1i3bl1lol2yZEm1P7/44gvKyspYs2YNxcXFrFu3jk2bNlFUVMTu3bspLi5mzZo17Ny5k5ycnKh1ZGdnU1ZWxqpVqygpKSE/P5+ioiIKCwspKChgy5YtrF27ltLSUvLy8qioqGDp0qXV6li6dCkVFRXk5eVFbVNRURH5+fmVbSorKyM7OztqPDk5OezcubNWmzZt2sS6devUJrUp1Da5Ozt27KC8vLxyPtemtmPHDioqKigtLcXd+eabb4DIXLSjR4/mxRdfxN0pLS3lpZdeomPHjqxevZoPPviAxYsXk5mZydtvv015eTmrV6/mmmuuYf78+RQVFbFu3Tpyc3NZuHAhY8eOZfv27bg7u3btorS0lCuvvJJHH32UzMxM3nzzTeLj45kyZQruzqJFi5gxYwbXXnstO3bsoLQ0MnC4fft27r33XlJSUli2bBmTJ0/mmmuuYdeuXZSXl5OZmcnMmTN5/vnna7Vp165dtf6e9mavj2A0s2OBhe7ePVg+B7jT3aMOEZvZZKDE3aNeqzWzmUQSWE2PRUu2ZtYXGEakV/Y94EbgY3d/uka57sB77n5CsHxBsM8Y4DPgVHdfH8SHu082swxgtrvPqlFXBjAbWE2khxzt5q93gYnunmlmxwCZ7t7dzF4Dprj7vKDcUuCmoFyJu7erEu/soJdNcANZO3efXOM4TwDL3D0jGMbPc/fEGmXOD2IZHiW2mtsmAN9195/VbFONOpv8EYxlZWX06tWLuXPn0rVrVwYNGsSLL75IcnLt7z2TJ0+mXbt2tW6Kys/PZ/jw4eTmxnQfmYgEaj4y0MyaeOi4uN5HryYlJTF37ly+/PJLxo8fz+DBg5k1axYdO3YEoKSkhLvuuosLL7yQIUOGVD6neMuWLZx66qkMGzaMyy67jKFDh9KqVSvS09MZPnw4vXv3Zty4ccyfP7/a8X70ox8xYcIELrjgAgDOOeccpk6dyubNm3nkkUeYPXs2/fv35+WXX+bEE08EoFu3buTm5vL4449jZpW97Jqa9BGM7v45sN7M9iTHC4G9p+691xdzj9bMTnL3HHd/iMiQZx/g78D1ZrYnYXU1sy7BLsdXuSN6DPAB0DZYLgr2acjdxKuB7+yp08zamFl9veEPiFw/xsxOITKUu8fuYDi6IVYCPQHcvRjYYGY/DOo/LLgm3BC9gGbJUnFxcTz55JNcfPHFJCUlceWVV5KcnMy0adOYNm0aAJ9//jmJiYk89thj/PKXvyQxMZHi4mIAxowZw+DBg1m9ejWJiYk8++yzzdEMEWmkkSNHMmvWLGbOnMno0aNxd+66667KqfI++eQTfvzjHwNw5JHfXqHs1KkT2dnZnH/++UydOpUbbrihWr3uHvUyVCy34uztklbVGPZVLFd4JwAvmFk88CkwNghmHIC7Twt6vplAB6DCzG4HTgmSQ2PdbmZDiNz0kwe85e47zSwJWBCcjBLg6qDMSuA6M3saWENkuHt7cMNRDpAPfBTrwd19V/Azn1+b2VFEztUUIjcz1eW3wB/NbDmR4e3lwNZg2++A5UEv9+4Yw3gLmF5l+RrgaTO7H9hN5GaohjiLyI1TzWLYsGEMGzas2rpx48ZVvj/22GPZsGFD1H1nzJgRamwiEq7Ro0dz4403UlRUxHvvvUdOTg733HMPV111Fe3ataOgoCDqLw6KioqIj49nxIgRnHTSSaSnp1fb3qdPHzZu3MhHH33EoEGD2LZtG4cffjjnnnsuL7zwAhdccAEff/wx69ato3fv3pVT8wGVZe655x7effddjjnmGDp0aLqe/h71JtrgOuKpUdZPq/L+c6pfv9xn7j6hjvVP8O3dyEDlUGyFu4+LUv5nRK6v1lyfXkf96VXeZxG567pmmfOrvC/i2+ugO4Cr3X2HmZ0EzCUydI27TwImVakmpUodUYfa3f0zM/vKzE529zXuvobIdeaqPgXerSO2d/dsM7P+wIogXhFpwU7oemyT3il8Qtdj6y2TnJzMtm3b6Nq1KwkJCSQkJLBy5UoGD44MRLZr147nn3+e1q1bV9uvoKCAsWPHUlFRAcADDzxQbXt8fDwzZ85kwoQJlJaWcvjhh/P2228zfvx4xo0bR9++fYmLiyMjI4PDDjus2r6TJ09m7NixpKamcsQRR4Q2h+0hMU1ezWuezRhHe2Ae0IbIeP0kd39rH+vsTeS66vv7WM9FwBp3z4+hrKbJEzmEaJq8ptXQa7SHxMTvQfJo9mfzufs2ovT+97HO1USuF+9rPf9sgnBERKSB9KxjERGRECnRioiIhEiJVkREJERKtCIiIiFSohUREQmREq2ISAtzXLfjmnSavOO6RX2E+l5t3LiRkSMbPvX3sGHD+Prrr/daprFT6IXlkPgdrTQt/Y5W5NAS7VnHjfn3XZem/HffFNPSha1Jn3UsIiKyr+qaJi8lJZLsMzIyuOKKK/j+97/P0KFD2b59O1deeSWpqamMGjWK008/nczMyMRi3bt3r5y9KCkpiRtvvJHk5GSGDh1aOTNPfVPo5efnc8455zBgwAAGDBjAhx9+GGr7lWhFRCRUo0ePZubMmZXLL730EoMGDapWZsGCBfzxj3/knXfe4be//S2dOnVi+fLl3HPPPZVT/tW0Zs0abr75ZlasWEHHjh15+eWXq23ftWsXo0aN4oknniA7O5u3336bww8/nC5duvDPf/6TpUuXMnPmTG699damb3QVB3b/XEREDnr9+/dn06ZNbNy4kS+//JJOnTpx/PHHVytz0UUX0blzZwA++OADbrvtNgBSUlJITU2NWm+PHj1IS0sDYODAgeTn51fbvnr1ahISEiqT+p4JA7755htuueUWsrKyaN26NR9//HFTNTUqJVoREQndnmnyPv/8c0aPHl1re9Vp6WK93lt1koDWrVtXDh1XrSfaFHqPP/443/3ud8nOzqaiooK2bdvWKtOUNHQsIiKhGz16NH/+85+ZNWtWvXcbn3322bz00ksA5OXlkZOT06hjVp1CD2Dbtm2UlZWxdetWEhISaNWqFdOnT6e8vLxR9cdKPVoRkRYmITGB3PTcJq2vPjWnyas5zFvV+PHjue6660hNTaV///6kpqZy1FFHNTiuvU2hN2LECP7yl78wZMiQJp3kPRr9vEdqiYtr7RZnlO1s+Le8hMQENq7fGEJUItJYB9s0eeXl5ezevZu2bduydu1aLrzwQj7++GPi4+ObOzSghU6TJ00rLa1/5a30IiL72/bt2xkyZAi7d+/G3XnqqacOmCTbGEq0IiJyQGnfvv0h9WVfN0OJiLQAukzYNBpzHpVoRUQOcW3btuWrr75Sst1H7s5XX33V4J8DaehYROQQl5iYyIYNG/jyyy+bO5SDXtu2bUlMTGzQPkq0IiKHuDZt2tCjR4/mDqPF0tCxiIhIiJRoRUREQqREKyIiEiI9GUpqMbNtwOrmjuMAcQxQ1NxBHCB0LqrT+fiWzgUUufsl0TboZiiJZrW7n9rcQRwIzCxT5yJC56I6nY9v6VzsnYaORUREQqREKyIiEiIlWonmd80dwAFE5+JbOhfV6Xx8S+diL3QzlIiISIjUoxUREQmREq2IiEiIlGhbKDO7xMxWm9knZnZnlO1mZr8Oti83swHNEef+EsP5ON/MtppZVvC6tzniDJuZ/cHMNplZbh3bW9rnor7z0SI+FwBm1s3M5pnZSjNbYWa3RSnToj4fsVKibYHMrDUwFbgUOAUYY2an1Ch2KXBy8LoJeGq/BrkfxXg+AP7l7mnB6/79GuT+kwFE/dF9oMV8LgIZ7P18QMv4XACUAf/t7knAGcDNLfn/jYZQom2ZTgM+cfdP3X0X8Gfg8hplLgf+5BELgY5mlrC/A91PYjkfLYK7vw9s3kuRlvS5iOV8tBjuXujuS4P324CVQNcaxVrU5yNWSrQtU1dgfZXlDdT+BxNLmUNFrG0dbGbZZvaWmSXvn9AOOC3pcxGrFve5MLPuQH9gUY1N+nxEoUcwtkwWZV3N33nFUuZQEUtblwInuHuJmQ0D/kpkeKylaUmfi1i0uM+FmbUDXgZud/fimpuj7NKSPx+AerQt1QagW5XlRGBjI8ocKuptq7sXu3tJ8P5vQBszO2b/hXjAaEmfi3q1tM+FmbUhkmRfcPdXohTR5yMKJdqW6SPgZDPrYWbxwGjg9RplXgeuDe4iPAPY6u6F+zvQ/aTe82Fmx5qZBe9PI/Jv56v9Hmnza0mfi3q1pM9F0M5ngZXu/lgdxfT5iEJDxy2Qu5eZ2S3A34HWwB/cfYWZjQu2TwP+BgwDPgG2A2ObK96wxXg+RgI/MbMyoBQY7YfgY9XMbAZwPnCMmW0A7gPaQMv7XEBM56NFfC4CZwHXADlmlhWs+ylwPLTMz0es9AhGERGREGnoWEREJERKtCIiIiFSohUREQmREq2IiEiIlGhFRERCpEQrIvvMzN4NHsu3v4/bva6ZdfahzvPNLKMp65SWTYlWREQkREq0ItKkgt7tFDP70MxygycmYWZHBvO7fmRmy8ys1gxJZjYzeGbwnuUMMxsR9Fz/ZWZLg9eZUfZNN7MnqyzPNrPzg/dDzWxBsO9fguf1YmYPmlleMHfqI01/NkSUaEUkHEe6+5nAeOAPwbq7gXfcfRAwBHjYzI6ssd+fgVEAweMwLyTytKFNwEXuPiDY/utYAwmePfwz4HvB/pnA/zOzzsCPgGR3TwV+2aiWitRDj2AUkTDMgMh8rmbWwcw6AkOBH5jZxKBMWyKP71tZZb+3gF+b2WFEJlx/391Lzewo4EkzSwPKgV4NiOUM4BRgfvBY4nhgAVAM7ACeMbM3gdmNaahIfZRoRSQMNZ/t6kSmUBvh7qvr3Ml9h5m9C1xMpOc6I9j0X8AXQD8iI3E7ouxeRvVRurbBnwb8093H1NwhGNa+kMhEErcAF+y1VSKNoKFjEQnDnuHfs4nM4LKVyKQNE6rMdtO/jn3/TORh9OcE+wAcBRS6ewWRB9u3jrJfPpBmZq3MrBtwWrB+IXCWmfUMjnuEmfUKrtMeFUxvdzuQ1vjmitRNPVoRCcMWM/sQ6ABcH6z7BTAFWB4k23xgeJR9/wH8CXjd3XcF634LvGxmVwDzgG+i7Dcf+DeQA+QSmZQdd//SzNKBGcGQNESu2W4DXjOztkR6vf/V2MaK7I1m7xGRfRYM96a7e37wfqK7ZzZvVI0T3Kmc7u7pzRuJHCo0dCwiIhIiDR2LSFPIAL4GcPfzmzOQJpAP/LWZY5BDiIaORUREQqShYxERkRAp0YqIiIRIiVZERCRESrQiIiIhUqIVEREJ0f8HWlNRSMHglBEAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "explainer.plot_feature_importances(\n", " X = X_test[0, :].reshape(1, -1),\n", " importance_method = 'pe', # change to 'shapley'\n", " grouping_threshold = 0.0,\n", " target = None,\n", " barh_kw = {'edgecolor' : 'k'},\n", " show = True\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Instead of looking into the average Partial Effects, we can plot the Partial Effects for each variable when its co-variables are fixed at the means.\n", "\n", "One phenomenon that can occur in a multiclassification problem is to have one class being a baseline, which is observed below. This explains why the feature importance shoud be summed for all classes." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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ZMG6BzcybUV+UUl8CQwF/pVQy8DTgACeLxxOBu5VSZqpW/JxirSt+yjVFnBCfHc/Huz7mitZXMKH1hPPef0a3GfyZ/Cf/Wvcvvp3wLZ6Ong2Q0lgyyfJZnGvyQnHx5Pdp/QrLzCzZlsoXG4+yKyUfZwcT47u24Lo+Leka5tUob1RlkmXRVBSUVrD5aO7Jx7ak4xSXVwLg7+5It3BvuoZ50yXcmy6hXvi4ORqcWNTEmq8p8v9q/ZPf6bkVlBcw5ccplJhLWHj5Qvxd/OvluFuObeH25bczKGwQ/x323wvqEdQUyDVFnEp+pxem0lLJjctuJKUwhSVXLMHL6cJGBezO2s31S69nfKvxPDvg2XpO2XhkkmUhRL2q6q2TyJJtKRSVV9Iu2INnJ3Tkiu6heEpvHdFM5BaVs+FIDhuP5LAxIZs9qflYNNiZFO1DPJjUM4weLX3oEeFDmI+L9MwRQtikZ9c9S2phKp+M+aTeijsAPYJ6cH/s/by86WXm7p7LbZ1uq7djCyGsy+IDi9mZtZMXB754wcUdgI7+Hbm54818susTJrWZROeAzvWY0nhS4BFC1FlBaQXfb0vly42J7E6t6q0zrksLrusTQfdwb3nzKmxefmkFGw7nsO5QNmsPZbE3vWqcv5O9iR4RPswYHkPvSF+6R3jLnDlCiGZhecJyfk74mZndZ9I9sHu9H/+G9jewNWMrb219iwEtBpzXnBtCCNuQV5bHG1veoHdwb8ZFj7vo403tMpXvDn7Hq3GvMnfMXJt6DyN3n0KIs9JaszXpOAs2JvLD9jRKKippH+IpvXVEs1ButrAlMZc1B7JYczCLHcnHseiqgk5spA8PjmpDn2g/uoR54WQvq8IJIZqX7JJsXlj/Ah39OjZY7xqlFE/2fZItx7bw+JrHWXDZAhzs5N5DiOZk7u655Jfn83Cvh+ulGOPm4Mb0btN5bv1zrExaySURl9RDyqZBCjxCiBodLy7n260pLNiYxL5jBbg62jGhWwum9I5otLl1hDBCQlYRq/dn8sf+TNYdzqa4vBI7k6JrmBfTh7Wmfyt/erT0loKOEKLZe3HDixRWFPLCwBcualLlc/Fx9uGZ/s8wc+VM3tv+Hvf0uKfBziWEaFqySrKYHz+fS6MurdcefFfFXMX8+Pm8vvl1BocNxsFkG4VjKfAIIU6yWDTrj2Tz1aYklu1Kp9xsoUuYFy9e2Znx3VrgLkNOhA0qrahk/eFsVu3LZNW+DBKqlyxv6efK1T3CGBjjT79WftJbTQghTvFXyl/8cvQXZnafSSvvVg1+vqHhQ5nQagJzds1hTNQY2vi0afBzCiGM9+GODymvLGd6t+n1elx7kz339biPe36/h6WHl17QqlxNkbxbE0JwLL+URZuTWRiXxNHsYjyc7bm2VziTe0XQoYXtLR8oRHpeKSv3ZrBy7zHWHMyitMKCs4OJftF+3DogiiFtAoj0dzM6phBCNElllWW8uOFFIj0juaXjLY123gdjH+SP5D94bt1zzLt0ntWuqiWEqJv0onQW7l/IFa2voKVny3o//tDwobTzbcdHOz9iXPQ47EzW3ztbroqCp556ihUrVpz3fqtWrWLcuIuf5EoYo6LSwi+707l97ib6z1rJK8v3EezpzH8nd2PTEyP414ROUtwRNkNrze7UPN5YcYDL31pD35d+4/Fvd7I3vYDJseHMubUX254axZxbe3Nz/0gp7gjRhMh9StMzZ9ccEgsSeazPYzjaOTbaeb2dvXkg9gG2ZW7jmwPfNNp5he2R64p1mLd7HlprpnaZ2iDHV0oxtctUEvIT+OXoLw1yjsYmPXiaCa01WmtMpr/X9J599tlGyWA2m7G3l79yRjuYUcjXcUks3pJCVmEZAR5OTB0czeTYcHlTK2yKudLCpoRcftmTzi+7j5FyvASloHu4Nw+NbsvIDkHEBLrLfFJCNAFyn2I90ovS+Xjnx4xsOZL+Lfo3+vnHtxrPdwe/4/XNr3NJxCX4OPs0egZhHeS6Yt2Olx5n8YHFjI0aSwv3Fg12nksiLiHaK5rZO2YzOnK01fcMtO70zdAjjzzCu+++e/L5M888w2uvvcYrr7xCr1696NKlC08//TQACQkJtG/fnmnTptGjRw+SkpK45ZZb6NSpE507d+b1118H4JZbbmHRokUAbNq0if79+9O1a1d69+5NQUEBpaWl3HrrrXTu3Jnu3bvz+++//y1XTk4OV1xxBV26dKFv377s2LHjZL6pU6cyatQobrrppob+9YhaFJaZ+WpTIle/t5YR/1nNR2uO0D3Cmw9vimXdo8N5ZEw7Ke4Im1BmruT3vRk8vGg7vV5YwbUfrmf+hkTaBXvw76s7s/HxEXwzbQDTh7WmTZCHFHeEqGdyn2L73tzyJhZt4YHYBww5v1KKJ/o8QVFFEe9se8eQDKJxyXWlefpy75eUmEu4tdOtDXoekzJxZ5c7OXj8IKuTVjfouRqDlBMvxrJHIX1n/R4zuDNcOqvWzVOmTOG+++5j2rRpACxcuJBHH32UNWvWsHHjRrTWjB8/nj/++IOIiAj27dvHnDlzePfdd9m8eTMpKSns2rULgOPHj5927PLyciZPnsxXX31Fr169yM/Px8XFhTfeeAOAnTt3snfvXkaNGsX+/ftP2/fpp5+me/fufPfdd6xcuZKbbrqJbdu2AbB582bWrFmDi4tLPf2SRF1ordl4JIevNyfz046q5c1bBbjx2KXtuLJHKIEezkZHFKJelFZU8sf+TJbtSmfFnmMUlJnxcLJnWLtAxnQKZkibANxkgnDRHMl9yklyn1I/dmfv5ofDP3Bbp9sIdQ81LEdrn9Zc0/Yavtr3Fde0vUYmXG4sBlxTQK4rzVFxRTFf7P2CoWFDifGJafDzjYkcw5tb3uTTPZ8yLGJYg5+vIckdr5Xp3r07GRkZpKamkpmZiY+PDzt27OCXX36he/fuABQWFnLgwAEiIiJo2bIlffv2BSA6OprDhw8zc+ZMLrvsMkaNGnXasfft20dISAi9evUCwNOzav6VNWvWMHPmTADatWtHy5Yt/3aBW7NmDYsXLwZg+PDhZGdnk5eXB8D48ePl4taIUo+XsHhzMou2JHM0uxi36uXNJ8WG0yPCW3osCJtQWlHJ6v2ZLN2Zxoo9xygqr8Tb1YFLOwdzaacQ+rf2k2XMhTCA3KfYLq01r256FR8nH+7ofIfRcZjebTpLjyzl3xv/zUejPpL7Gxsm15Xm5/tD33O87Di3db6tUc5nb7Ln+vbX82rcq+zO3k1Hv46Nct6GIAWei3GOanNDmThxIosWLSI9PZ0pU6aQkJDAY489xj/+8Y/T2iUkJODm9r9hNz4+Pmzfvp3ly5fzzjvvsHDhQj755JOT27XWNf7nqLU+Z6aa2pw41qkZRMMoKa/klz3pLNqczJqDWWgNfaN9uWd4DJd2DsbVUf6pC+tXbraw5mAmP2xP49c9xygsM+Pj6sDlXVtwWZcQ+kb74WAnI4+FOEnuU87aRu5Tzs+fKX8SdyyOx/s8joejh9Fx8HLyYnq36by44UVWJa2y+k/drYJB1xSQ60pzYtEWvoj/gk5+negW0K3RzntVzFW8t/09PtvzGbMGGfd3/WLJnbAVmjJlCgsWLGDRokVMnDiR0aNH88knn1BYWAhASkoKGRkZf9svKysLi8XC1VdfzXPPPceWLVtO296uXTtSU1PZtGkTAAUFBZjNZgYPHsz8+fMB2L9/P4mJibRt2/a0fU9ts2rVKvz9/U9WwEXD0FqzKSGHRxfvoNcLK7h3wTaOZBVxz/AY/nx4GAum9uPqnmFS3LkASqkxSql9SqmDSqlHa9h+vVJqR/VjrVKqqxE5m4NKi2btwayTf89vmxvHb/HHGNs5mE9v683GJ0Yw6+ouDIoJkOKOEE2E3KfYHou28MaWNwj3CGdim4lGxzlpYpuJRHpG8vqW1zFbzEbHEQ1IrivNx18pf5GQn8D1Ha5v1J55Ho4eXBVzFcuPLOdY0bFGO299k3d+Vqhjx44UFBQQGhpKSEgIISEhxMfH069fPwDc3d35/PPPsbM7fXhCSkoKt956KxaLBYCXXnrptO2Ojo589dVXzJw5k5KSElxcXFixYgXTpk3jrrvuonPnztjb2zN37lycnJxO2/eZZ57h1ltvpUuXLri6ujJv3rwG/A00b0k5xXy7NYVvtiSTkF2Mq6Mdl3YK4eqeofSN8sNkki7KF0MpZQe8A4wEkoFNSqklWus9pzQ7AgzRWucqpS4FZgN9Gj+tbdJasyM5j++3pfLjjlQyCspwc7RjVMdgLu8awsDWATjaSzFHiKZK7lNsz7Ijy9ifu59Zg2bhYHIwOs5JDiYH/q/n/3Hv7/fyzYFvuKbtNUZHEg1ErivNx/z4+QS4BDC65ehGP/f17a9nfvx8FuxbwL097m3089cHVZfuZ81VbGysjouLO+21+Ph42rdvb1Ai2yO/z7opKK1g2a50Fm9OZsORHKBqCNbEnuFc2im42U8gq5TarLWOradj9QOe0VqPrn7+GIDW+qVa2vsAu7TW55xtsqZrivifI1lFfLc1he+3pZCQXYyjnYmhbQOY0C2U4e0CcXGUOXVE46jPa0pDkvuUxtHcf6cVlgomfDcBF3sXvr786ya3hLDWmlt+voWE/ASWXrUUN4emNzRGriniVPI7rd3h44eZ8P0Epnebzl1d7zIkwz0r72FbxjZ+nfQrTnZO597BILVdV5r3u0IhmjBzpYU/D2bx7ZYUftmTTmmFhSh/Nx4c1YYruocS5uNqdERbFQoknfI8mbP3zrkdWFbbRqXUVGAqQERERH3ksynZhWX8uCONb7emsC3pOEpBv2g/7h7aijGdQvByaTqfFAshRHP03cHvSCpI4p1L3mlyxR2omvPkwdgHuW7pdczbPY9p3aYZHUkIcYG+3PslDiYHJrWZZFiGa9tdy+9Jv/NLwi9c3upyw3JcKCnwCNGEaK3ZlZLPN1uT+WF7KlmF5Xi7OjCxZxhX9wijW7isgtUIavoF19jVUSk1jKoCz8DaDqa1nk3VEC5iY2OlyyRVK2CtiD/Gt1tSWL0/E7NF0y7Yg8fHtuPyri0I8ZJVJ4QQoikoryxn9o7ZdAnowqDQQUbHqVXngM6MbDmSebvnMbntZPxc/IyOJIQ4T0UVRfxw+AfGRI4x9N9w35C+RHpGsmDvAinwCCEuTFJOMd9vS+HbrSkcyizC0c7E8HaBXNkjlGFtA2W+kcaVDISf8jwMSD2zkVKqC/ARcKnWOruRslktrTWbj+ayeEsyP+5Io6DUTJCnE7cPjOLKHqG0C5ZJCYUQoqlZtH8R6UXpPNv/2Sb/AdM93e9hZeJKZu+YzWN9HjM6jhDiPP10+CeKKoqY3G6yoTmUUkxpN4VZG2exO2s3Hf2ta8l0KfAIYZDconJ+2pnG99tS2JSQC0CvSB9uHxjN2M7BeLs6Gpyw2doExCilooAUYApw3akNlFIRwDfAjVrr/Y0f0Xok5RTzzZYUvtmazNHsYlwc7BjTKZire4TRr5UfdjIpuBBCNEml5lI+2vkRPQJ70Dekr9FxzinSK5IrY65k4f6F3NDhBsI9ws+9kxCiSdBas2DfAtr7tqeLfxej4zCh1QTe2PIGX+79kucHPm90nPMiBR4hGlFxuZkV8Rks2VY1NKWiUhMT6M5Do9syvmsLwn1lXh2jaa3NSqkZwHLADvhEa71bKXVX9fb3gacAP+Dd6k80zdYweWJjKSozs2xXOos2J7H+cNWk4P2i/Zg5PEYmBRdCCCuxcN9CMksy+ffgfzf53jsn3N31bn489CPvbnuXlwbVuDaCEKIJ2pa5jQO5B3im3zNN4nrj7ujOuOhxLDm0hId6PYSXk5fRkepM7rKFaGAVlRb+PJDJkm2p/LLnGMXllQR7OnNL/0iu6B5KhxDPJnEhE/+jtV4KLD3jtfdP+f4O4I7GztWUWSyajQk5LNqczNKdaRSXV9LSz5UHRrbhyh4yKbgQQliTEnMJn+z6hD7BfegV3MvoOHUW6BrIte2vZe6uudza6Vba+LQxOpIQog4W7F2Ah4MHl0ZdanSUk65pew1f7/+aHw79wA0dbjA6Tp3JxB42IDU1lYkTJ573fmPHjuX48eNnbfPUU0+xYsWKC0zWfFksmnWHsnnsm530emEFt82N4/d9mUzoFsqXd/Zl7aPDeeKyDnRs4SXFHWHVknOLefO3Awx9dRVTZq/n513pXN6lBYvu6seqB4cy85IYKe4IASilxiil9imlDiqlHj1Lu15KqUql1Pn/x95EyX2K9Vm4byHZpdnc3e1uo6Oct9s73Y67gztvbXnL6CiiAcl1xXbkluby69FfubzV5bg6NJ17xna+7egS0IWF+xeitfWskyI9eGxAixYtWLRo0d9eN5vN2NvX/ke8dOnSWred8Oyzz15UtuZEa83WpOP8sD2VpTvTOJZfhouDHSM7BDGhWwsGxQTIZMnCJpRWVLJ8dzoL45JYeygbraF/Kz/uGxHDmE7BuDrKfy1CnEopZQe8A4ykaiL3TUqpJVrrPTW0+zdVQ0RthtynWJeTvXdC+tAzqKfRcc6bl5MXt3S6hbe2vsW2jG10C+xmdCTRAOS6Yju+P/g9FZYKQ5dGr801ba7hn3/9k7hjcVbTm1HebVqZRx55hHfffffk82eeeYbXXnuNTp06ATB37lwmTZrE5ZdfzqhRoyguLuaaa66hS5cuTJ48mT59+hAXFwdAZGQkWVlZJCQk0L59e+688046duzIqFGjKCkpAeCWW245efHctGkT/fv3p2vXrvTu3ZuCggISEhIYNGgQPXr0oEePHqxdu7aRfyPGqlrWPI+XlsUz8N+/c9W7a5m/PpGuYd68eW13Nj85gjev7c4l7YOkuCOsmtaa7UnHeeLbql5p9y7YxtHsYu69JIY/Hx7GF3f25aoeYVLcEaJmvYGDWuvDWutyYAEwoYZ2M4HFQEZjhqtPcp9i/RbuW0hOaQ53d7W+3jsn3ND+Bvyc/XhjyxtW9cm7qJlcV2yXRVv4ev/X9AjsQWuf1kbH+ZvRkaPxdPTkq31fGR2lzuRO/CL8e+O/2Zuzt16P2c63HY/0fqTW7VOmTOG+++5j2rRpACxcuJD333+fOXPmnGyzbt06duzYga+vL6+++io+Pj7s2LGDXbt20a1btxqPe+DAAb788ks+/PBDrrnmGhYvXswNN/xvrGF5eTmTJ0/mq6++olevXuTn5+Pi4kJgYCC//vorzs7OHDhwgGuvvfbkBdRWaa2JTyvgp52p/LQjjYTsYuxNioEx/vzfyDaM6hiEp7OD0TGFqBfZhWV8ty2Vr+OS2JtegJO9ibGdQ5jUM4y+0X6YZBUsIeoiFEg65Xky0OfUBkqpUOBKYDhQ68eESqmpwFSAiIiIs55U7lOa533KxbD23jsnuDq4cmeXO5m1cRZrU9cyIHSA0ZFsghHXFJDrii3bkLaBxILEJjsc1NnemfGtxrNg3wKyS7Lxc/EzOtI5SYHHynTv3p2MjAxSU1PJzMzEx8fnbzd4I0eOxNfXF4A1a9Zw7733AtCpUye6dKl52bmoqKiTF7+ePXuSkJBw2vZ9+/YREhJCr15V95yenp4AFBUVMWPGDLZt24adnR3799vmitEnijpLd6axdGcah7OKsDMp+kX7cdeQVozuGIyPmyxrLmyDudLCnweyWBiXxIr4Y1RUarqGe/PilZ0Z1zVECphCnL+aKqFndiv4L/CI1rrybHOzaa1nA7MBYmNjm1zXBLlPsW620HvnhEltJvHp7k95Y8sb9GvRD5OyrZ7USqlPgHFAhta6Uw3bFfAGMBYoBm7RWm9p3JT1Q64rtuvr/V/j7eTNyJYjjY5Sq0ltJvF5/Od8d/A7bu98u9FxzkkKPBfhXNXmhjJx4kQWLVpEeno6U6ZM+dt2Nze3k9/XtVuqk5PTye/t7OxOdlE89Tg13XC+/vrrBAUFsX37diwWC87OznX9MZo8rTW7U/NPFnUSsosxKejXyo/bB0UxpmMwfu5O5z6QEFYiIauIrzcnsWhzMsfyy/Bzc+SmfpFcExtO22APo+MJYc2SgfBTnocBqWe0iQUWVP9f6w+MVUqZtdbfXehJ5T7Ftu9T6put9N45wdHOkWndpvHPv/7JiqMrGBU5yuhI9W0u8DbwaS3bLwViqh99gPc4o+fg+TLqmgJyXbFFWSVZ/J74O9e1vw4nu6b7niraO5qeQT1ZtH8Rt3a6tckXi6XAY4WmTJnCnXfeSVZWFqtXr6asrKzWtgMHDmThwoUMGzaMPXv2sHPnzgs6Z7t27UhNTWXTpk306tWLgoICXFxcyMvLIywsDJPJxLx586isrLzQH6tJsFg025KP8/OudJbtSiMpp+RkT52pg1sxumOQFHWETSkuN7N0Z9WEyRuP5GBSMKxtIP8aH8bwdjJ3lBD1ZBMQo5SKAlKAKcB1pzbQWked+F4pNRf48WKKO0aS+xTrZEu9d04YFz2OObvm8NbWtxgeMRx7k+289dFa/6GUijxLkwnAp7qq2rFeKeWtlArRWqc1TsL6JdcV2/PtgW8xazMT2zT9RSMntZnEo38+yvq09fRv0d/oOGdlO1e5ZqRjx44UFBQQGhpKSEjI37oTnmratGncfPPNdOnShe7du9OlSxe8vLzO+5yOjo589dVXzJw5k5KSElxcXFixYgXTpk3j6quv5uuvv2bYsGGnVc+tRaVFsykhh593pfPzrnTS80txsFMMaO3PjGGtGdVBhl8J26K1ZlvScRbGJfHD9jQKy8xE+bvx8Ji2XN0jjCBP+SRKiPqktTYrpWZQtTqWHfCJ1nq3Uuqu6u3vGxqwnsl9ivUprii2qd47J9iZ7Linxz3c+/u9fH/we65uc7XRkRpTTXN/hQKnFXjOZ14vI8l1xbZYtIXFBxbTO7g3UV5R597BYCNbjmTWxlks2r+oyRd4lMwsX7vY2Fh95oRZ8fHxtG/f3qBE56+yspKKigqcnZ05dOgQl1xyCfv378fRsWkULIz6fZaZK1l7MJufd6WzIv4Y2UXlONmbGNImgDGdgrmkfRBeLjLPiLVQSm3WWscaneNcarqmNKbMgjK+25rCwrgkDmQU4uJgx2VdqiZM7h3lW2M3ZCGaI2u+psh9Sv2ztt/phZi7ay6vbX6NTy/9lO6B3Y2OU6+01ty47EbSitL46cqfcLZv/A8xGuqaUt2D58da5uD5CXhJa72m+vlvwMNa6821Hc8WrinQ9K8r1vg7rW9rUtZw94q7eWXwK4yJGmN0nDp5ddOrzI+fzy8TfyHANcDoOLVeV6QHj40rLi5m2LBhVFRUoLXmvffeazIXt8aWX1rBqn2ZLN+dzqq9GRSVV+LuZM+wdoFc2imYIW0CcHOSfxLCtpgrLazal8lXcUn8vjcDs0XTI8Kbf1/dmcu6tMBd/s4LIQwk9ynGK64oZs7uOfQL6WdzxR0ApRT39biPW5ffyhd7v+C2TrcZHamx1GXuL5sk15Wm7+t9X+Pr7MslEZcYHaXOJraZyLw98/j24LdM7TLV6Di1kjt7G+fh4dGsl+1Lzyvl1/hj/LrnGOsOZVFRqfF3d2R8txaM6hBM/9Z+ONnbGR1TiHp3MKOAr+OSWbwlhazCMvzdnbhtYBTXxIbROlAmTBZCNA3N/T6lKViwbwE5pTlM6zbN6CgNJjY4loGhA/lo50dcHXM1Xk7nP1zHCi0BZiilFlA1uXKetc6/c77kutK0HSs6xurk1dzU8SYc7KxnxESkVyR9QvqweP9ibu90O3ampvkeUgo8F6C2GdXF+WmI4YFaa/amF7BizzF+jT/GjuQ8ACL9XLmlfySjOwbTPcIHO5P8+Qnbk19awQ/bU/k6LpltScexNymGtwtkUmw4Q9sG4GAnEyYL0RzIfUr9sfWpDIoqipizaw4DWgygW2A3o+M0qPt63MekHybx0c6PeCD2AaPjXDSl1JfAUMBfKZUMPA04wMl5vZZStUT6QaqWSb/1Qs8l15T6Y+vXlLr45sA3WLSFSW0mGR3lvE1qM4kHVz/IX6l/MThssNFxaiQFnvPk7OxMdnY2fn5+cqG7CFprsrOz62VZwXKzhY1HclgRf4wV8cdIzq1a4rBbuDcPjW7LqA5BtA50lz8vYZMsFs3aQ9l8vTmJn3elU2a20CbInSfGtueK7qEEeMiqb0I0J3KfUn/q816lqfp8z+ccLzvO9G7TjY7S4Nr6tmV8q/HMj5/Pte2upYV7C6MjXRSt9bXn2K6Bi/6DlWtK/WkO15RzMVvMLDqwiP6h/Qn3CD/3Dk3M8PDh+Dn78fW+r6XAYyvCwsJITk4mMzPT6ChWz9nZmbCwsAvaN7uwjFX7Mlm5N4M/9mdSUGbGyd7EwOqVr4a3CyRQVgISNiwhq4jFW5L5ZksKKcdL8HC2Z2LPMCbFhtM1zEtuwoRopuQ+pX5dzL1KU5dXlse83fMYGj6UzgGdjY7TKGZ0n8HPCT/z9ta3eXHQi0bHsQpyTalftnxNqYvVyavJKM7giT5PGB3lgjjYOXBVzFV8vOtjUgtTm2ShWAo858nBwYGoqKa/lJut0VqzJy2f3/dmsHJvBluTjqM1BHo4Ma5rCMPbBTGwtT8ujk1zLKQQ9aGgtIKlO9NYtDmZTQm5mBQMjAng0UvbMbJDEM4O8vdfiOZO7lNEXX2651MKKgqY0W2G0VEaTbBbMNe3v545u+ZwQ4cb6ODXwehITZ5cU0R9WrhvIUGuQU2290tdTGwzkY93fcyi/Yu4p8c9Rsf5G6sq8CilxgBvAHbAR1rrWWdsV9Xbx1I11vQWrfWW6m0JQAFQCZitYfnT5q6wzMyaA1ms2pfB7/syOJZfBkCXMC/uvSSGEe2D6NjCU3oqCJtWadH8dTCLxVuSWb47ndIKC9EBbjw0ui1X9wgj2Et6qgkhhDg/OaU5fL7nc0a1HEVb37ZGx2lUt3e+nW8PfMurca/y8aiP5T5SiEaSmJ/I2tS1TOs2DXuTVZUhTtPCvQWDwwaz+MBi7up6F452TWuFNqv5zSql7IB3gJFULfu3SSm1RGu955RmlwIx1Y8+wHvVX08YprXOaqTI4jxprTmYUciqfZn8vi+DTQk5VFRq3J3sGdzGn6FtAxnaNoBAD3lDK2zf3vR8vt2SwnfbUjiWX4aXiwMTe4ZxdY8wuoV7yw2pEEKIC/bhjg8prSxlenfbn3vnTJ6OnkzrNo0XNrzA70m/MzxiuNGRhGgWFuxbgL2yZ2LMRKOjXLQpbaewKmkVvx79lcuiLzM6zmmspsAD9AYOaq0PA1Qv+TcBOLXAMwH4tHpSsfVKKW+lVEhzWRLQGhWUVvDXwWxW789g9b5MUvNKAWgb5MFtA6IY2jaQ2EgfWf1HNBu7UvJ4eNEO9qTlY29SDG0bwDOXhzG8fSBO9jIESwghxMVJLUzlq31fcUXrK4j2ijY6jiEmtpnIl3u/5LW41xgUOsiqlmoWwhoVVxTz3cHvGNlyJAGuAUbHuWj9WvQjwiOCr/Z9JQWeixAKJJ3yPJnTe+fU1iYUSAM08ItSSgMfaK1n13QSpdRUYCpARERE/SQXJ1VaNLtS8vjzQCZ/7M9ic2IulZaqXjoDWvsx85IYBrcJINTbxeioohmrw3DQdsAcoAfwhNb61fo6d7CXM472Jp65vAOXd22Bn7usgiWEEKL+vLf9PRSKu7vebXQUw9ib7Hkg9gGm/zadL/Z+wc0dbzY6khA2bemRpRSUFzCl3RSjo9QLkzJxTdtreDXuVfbm7KWdbzujI51kTQWemsYj6PNoM0BrnaqUCgR+VUrt1Vr/8bfGVYWf2QCxsbFnHl9cgNTjJaw5kMUfBzL562AWucUVAHQK9eSuIdEMjgmgR0vppSOahjoOB80B7gGuqO/z+7s78d30AfV9WCGEEIJDxw+x5NASbmh/A8FuwUbHMdSg0EEMDB3I+9vf57Loy/B38Tc6khA2SWvNgr0LaOPThu6B3Y2OU2+uaH0F72x7hy/3fsm/+v/L6DgnWVOBJxkIP+V5GJBa1zZa6xNfM5RS31I15OtvBR5x8QpKK1h/OIe/Dmbx54FMDmUWAVUrXg1vF8SgGH8GxvjjLz0TRNN0zuGgWusMIEMp1bT6ZAohhBBn8Z/N/8HN3o07Ot9hdBTDKaV4uNfDXLXkKt7c8ibPDnjW6EhC2KQtGVvYl7uPp/o9ZVNzSHo5eTEuehxLDi3hvh734ePsY3QkwLoKPJuAGKVUFJACTAGuO6PNEmBG9RuyPkCe1jpNKeUGmLTWBdXfjwLkKl5Pys0Wtibm8tfBLNYczGJ7ch6VFo2Lgx29o3y5tncEA2P8aRvkYVP/qIXNqstw0DqTYZ9CCCGago1pG/kj+Q/+r+f/NZk3IkaL8orixvY3Mmf3HCa1mUTngM5GRxLC5ny+53M8HT0ZFz3O6Cj17rp21/H1/q9ZfGBxkymcW02BR2ttVkrNAJZTNS/GJ1rr3Uqpu6q3vw8spWqJ9INULZN+a/XuQcC31cUFe+ALrfXPjfwj2IxKi2Z3ah5/Hcxm7aEs4hJyKamoxKSgc5g3dw9pRf/WfvRs6SOTwgprVJfhoHUmwz6FEEIYzaItvBr3KiFuIVzf/nqj4zQpU7tM5cfDP/L8huf5YuwX2Jnk3lWI+pJckMzKpJXc2vFWXOxtb47V1j6t6RPShwV7F3BLx1uaxPLvxic4D1rrpVQVcU597f1TvtfA39Z7rB5q0bXBA9ooi0WzN72AdYezWXcomw1HsikoNQMQE+jO5F7h9G/lR59oP7xcZBUCYfXqMhxUCCGEsBo/Hf6J+Jx4Xhz4Ik52MkT+VO6O7jzc62Ee+uMhFu5fyLXtrjU6khA248u9X6JQNjO5ck2ub3c99/x+DysSVzAmcozRcayrwCMax4mCzoYj2aw/nM2GIzkcr54YuaWfK5d1DqF/a3/6RvsS6OFscFoh6l1dhoMKIYQQVqG4opj/bv4vnfw6NbnlfJuK0ZGjWXxgMW9ueZORLUfKhMtC1IOiiiK+OfANo1qOsulJ3QeHDSbCI4JPd3/K6JajDZ+SRAo8AnOlhfi0qoLOhiM5bDySQ15JVUEn3NeFke2D6FfdQ0eWLxe2ri7DQZVSwUAc4AlYlFL3AR201vlG5RZCCCFq8tHOj8goyeC1oa9hUrJiaU2UUvyz7z+58vsr+ffGf/PKkFeMjiSE1fv2wLcUVhRyfQfbHhZqZ7Ljxg438sKGF9iasZUeQT0MzSMFnmaotKKSHcl5bEqoKuZsPppLYVnVkKuWfq6M6hBE32g/+kT7EubjanBaIRpfHYaDplM1dEsIIYRospIKkpi3ex7josfRLbCb0XGatJaeLZnaZSrvbHuHy6IvY2j4UKMjCWG1KiwVfLrnU7oHdqdrgO3PlDKh9QTe2fYO83bPkwKPaHh5xRVsScxlU0IOmxJy2J6UR3mlBaiaQ+eK7i3oHeVH70hfgr1kyJUQQgghhC14edPL2JnsuK/HfUZHsQq3d7qd5QnLeW79c/QM6omHo4fRkYSwSr8k/EJaURqP93nc6CiNwsXehWvaXsOHOz4kIS+BSK9Iw7JIgcfGaK1JzCkmLiGXzYm5bE7IZd+xAgDsTYqOoV7c3L8lvSJ9iY30xdfN0eDEQgghhBCivv2e+DurklZxf8/7CXILMjqOVXCwc+DZ/s9yw7Ib+M/m//B0v6eNjiSE1dFaM2fXHKK9ohkcNtjoOI3m2nbXMnfXXObtmWfotUMKPFautKKSXSl5bEnMZfPRXDYfPU5WYRkAHk72dG/pw7guIfSM9KF7uA8ujrL0oxBCCCGELSsxlzBr4yxae7fmhg43GB3HqnQO6MxNHW5i7u65jIgYwYDQAUZHEsKqrEtdx77cfTzb/9lmNe+Xv4s/V7S+gm8PfstdXe4yrLAuBR4rorUmObeErUnH2ZqYy5bE4+xJzaOiUgMQ4evKoBh/erb0oWdLH9oEeWBnMnYWbyGEEEII0bg+2P4BqUWpzB0zFweTg9FxrM6M7jP4M/lPnvrrKb6Z8A1eTl5GRxLCany480MCXQKb5ap9t3a6lcUHFjNvzzwe7vWwIRmkwNOEFZRWsCM5j21Jx9maeJxtSf/rnePsYKJLmDe3D4ymR4Q33SN8CPBwMjixEEIIIYQw0t6cvczdPZcrWl9Bz6CeRsexSk52Trww6AVu+OkGXtjwAi8PftnoSEJYhbj0OOKOxfFo70dxtGt+U4GEeYQxNmosi/Yv4s7Od+Lj7NPoGaTA00SUmSvZm1bAjuTjbEvKY0fycQ5mFqKrOucQHeDG4Db+dI/woXu4N22DPXCwaz5d3oQQQghrppQaA7wB2AEfaa1nnbH9euCR6qeFwN1a6+2Nm1JYO7PFzFN/PYWPsw8Pxj5odByr1tGvI//o+g/e2fYOg0IHcXmry42OJEST98GOD/Bz9uPqmKuNjmKYOzrfwY+Hf+Tz+M+Z2X1mo59fCjwGMFdaOJhZyI7kqkLOzuQ84tMKTq5s5efmSNdwby7v2oJu4d50DfPGy1W61wohhBDWSCllB7wDjASSgU1KqSVa6z2nNDsCDNFa5yqlLgVmA30aP62wZvN2zyM+J57Xh74uw4rqwZ2d72R92nqeW/8cXQK60NKzpdGRhGiytmVsY33aeh6MfRBn++a7MnO0dzQjWo5gfvx8bmx/I97O3o16finwNLATxZydyXnsSsljZ0oee9LyKa2oKua4O9nTOdSLWwdE0jXcmy5hXoR6u6CUzJ0jhBBC2IjewEGt9WEApdQCYAJwssCjtV57Svv1QFijJhRWb3/uft7Z9g4jW45kRMsRRsexCXYmO2YNmsXVS67modUP8fnYz5vlsBMh6uL97e/j4+TDpDaTjI5iuGldp7Hi6Arm7p7LfT3va9RzS4GnHpVWVLL/WAG7U/PZlZLH7tR84tPyKTNXFXNcHe3o2MKT6/u0pHOoF13CvIj0c8MkEyELIYQQtiwUSDrleTJn751zO7Cspg1KqanAVICIiIj6yiesXHllOY/++Siejp78s+8/jY5jU4Ldgnl+wPPc8/s9zNo4i6f6PWV0JCGanE3pm/gr9S8e6PkArg6uRscxXGuf1oyJGsMXe7/gxg434ufi12jnlgLPRfp9bwY/7EhlT2o+BzMKMVuqJs3xcLKnQwtPbuzbkk6hXnQK9SLK301WtRJCCCGan5r+89c1NlRqGFUFnoE1bddaz6Zq+BaxsbE1HkM0P29vfZsDuQd455J38HX2NTqOzRkWMYzbO93Ox7s+prN/Z66MudLoSEI0GVpr3tzyJoEugUxpN8XoOE3G3V3vZnnCcj7Z9QkP9Xqo0c4rBZ6LFJ+ez5oDWXRo4cnwdoF0CvWiYwtPwn1cpWeOEEIIIaCqx074Kc/DgNQzGymlugAfAZdqrbMbKZuwcmtT1jJ391wmtpnI4LDBRsexWTO6z2BX1i6eX/88bXza0NG/o9GRhGgS/kj+g22Z23iy75PNeu6dM0V5RXF59OUs2LuA69tfTwv3Fo1yXlmG6SL9Y3ArNj4xgrm39ubhMe0Y2zmEljLsSgghhBD/swmIUUpFKaUcgSnAklMbKKUigG+AG7XW+w3IKKxQRnEGj615jFberXi418NGx7Fp9iZ7Xh7yMgGuAcxcOZP0onRD8yilxiil9imlDiqlHq1h+1ClVJ5Salv1Q8aWiXpXaankja1vEO4RLj3bajC923SUUry19a1GO6cUeC6SDLkSQgghxNlorc3ADGA5EA8s1FrvVkrdpZS6q7rZU4Af8G71m7E4g+IKK2G2mHn0z0cpMZfw2pDXcLF3MTqSzfN19uWt4W9RVFHEPSvvobii2JAcp6zMdynQAbhWKdWhhqZ/aq27VT+ebdSQoln49uC3HMg9wD097sHBJKs+nynEPYQb2t/Aj4d/ZHf27kY5pxR4hBBCCCEamNZ6qda6jda6ldb6herX3tdav1/9/R1aa59T3ozFGptYNHX/3fxfNqVv4ok+TxDtHW10nGYjxieGV4a8wr7cffx4+EejYpxcmU9rXQ6cWJlPiEZTWF7IW1vfontgd0a3HG10nCbr9s634+Pkw3/i/oPWDT91nhR4hBBCCCGEsCI/Hv6ReXvmMaXtFCa0lvf1jW1w2GC+uOwLI5eDrmllvtAa2vVTSm1XSi1TStU4aZBSaqpSKk4pFZeZmdkQWYWN+nDnh+SU5vBIr0dQSka11MbD0YO7u93NxvSNrEhc0eDnkwKPEEIIIYQQVmJn5k6eWfsMsUGxPNxb5t0xSke/jka+qa3LynxbgJZa667AW8B3NR1Iaz1bax2rtY4NCAio35TCZiXkJfDZns8Y32q8TDheB5PaTKKtT1te3vRygw/tlAKPEEIIIYQQViApP4kZK2fg7+LPa0Nfkzkvmq9zrsyntc7XWhdWf78UcFBK+TdeRGGrtNY8v+F5nOycuK/HfUbHsQr2Jnue6PsE6UXpfLjzwwY9lxR4hBBCCCGEaOJyS3O5+7e7qdSVvDfiPXydfY2OJIxTl5X5glV1FyOlVG+q3vdlN3pSYXN+OvITG9I2cG+PewlwlV5fddU9sDvjW41n7u65HD5+uMHOIwUeIYQ4Qx2WHlVKqTert+9QSvUwIqcQQojmoaC8gLtW3EVaYRpvDnuTKK8ooyMJA9VxZb6JwC6l1HbgTWCKbowZXoVNyyvL45VNr9DZv7ORc1BZrft73o+7gztPrX2KSktlg5xDCjxCCHGKOi49eikQU/2YCrzXqCGFEEI0G8UVxUz/bTr7c/bz+rDX6REknymIOq3M97bWuqPWuqvWuq/Weq2xiYUteGnjS+SX5fNUv6ewM9kZHcfq+Ln48UjvR9ieuZ0v9n7RIOc4Z4FHKeVUl9dO2TZAKeVW/f0NSqn/KKVaXlxMIYRoNHVZenQC8Kmush7wVkqFNHZQIYQQtq2ooojpv01ne+Z2Zg2exeCwwUZHEkI0UyuOruCnwz8xtctU2vm2MzqO1bos6jKGhA3hzS1vkpifWO/Ht69Dm3XAmR8V1PTaCe8BXZVSXYGHgY+BT4EhFxpSCCEaUU1Lj/apQ5tQIO3MgymlplLVy4eIiIhzn700H1K3Ahq0Pv0rJ77UsO20r9SwXy3tam1T03lqOXeNx6HuWerc9sR2/rf9XLlrPDZn2Xbm61zAPhdzXk5xtuPWcMxzZajp+Vnb1LD91Kw1tT3nec8jW00jCWrKX9fzAdz4HTi6/v24QjRBeWV53L3ibvZk72HWoFmMjhxtdCQhRDOVXZLNc+ufo71ve+7ocofRcayaUoon+z7JlUuu5NE/H2XepfPqdcL8Wgs8Sqlgqt6wuCiluvO/5fg8gbPdHZm11lopNQF4Q2v9sVLq5npLLIQQDasuS4/WpU3Vi1rPBmYDxMbG1tjmNNkH4NPx52wm6kLBySVsq78qdcb3NWw7r33Odp6LPG+t5zv1nGce81wZanp+Pvuceu4z9q01c11+rvPd54wMp8U5275CWIf0onTuXnE3R/OP8p+h/2F4xHCjIwkhmimLtvDEmicoLC/ko1Efyep99SDILYhn+j3DA6sf4L1t73FPj3vq7dhn68EzGriFqmX3XuN/d0r5wONn2a9AKfUYcAMwuHo+C/lbIISwFudcerSObS6MXwzc8hOnvYGvqQBw8rUzn5/5pr+2/Wo7Nmc5Ri2v/e341LIPZ8lC3XLXuP2UNvJGXghh5eKz45n+23RKzCW8O+Jd+ob0NTqSEKIZ+2TXJ/yV+hdP9n2SGJ8Yo+PYjFGRo7g69Wo+2vkRfUL60CfkzAEDF6bWAo/Weh4wTyl1tdZ68XkcczJwHXC71jpdKRUBvHKROYUQorGcXHoUSKFq6dHrzmizBJihlFpA1fCtPK3134ZnXRBnT4gcWC+HEkIIYV1+PvIzT619Ci8nLz699FN5MyWEMNTmY5t5e+vbjI4cLatmNYCHez3M1oytPPzHw3w17iuC3YIv+ph1WUWrp1LK+8QTpZSPUur52hprrdO11v/RWv9Z/TxRa/3pRScVQohGUMelR5cCh4GDwIfANEPCCiGEsAkVlgpe3fQqD/3xEO182/HF2C+kuCOEMFRaYRr3r7qfUPdQnun3DEp6Sdc7VwdX/jvsv5RVlnHf7/dRVll20cesS4HnUq318RNPtNa5wNjaGiulrlJKHVBK5Sml8pVSBUqp/ItOKoQQjaQOS49qrfX06u2dtdZxxiYWQghhrY7mH+XGpTcyb888prSdwsejPibANcDoWEKIZqy4opiZK2dSXlnOW5e8hbuju9GRbFaUVxQvDnyR3dm7eWH9Cxd9vLqsomWnlHLSWpcBKKVcgFqXSQdeBi7XWsdfdDohhBBCCCFsUKWlkgX7FvDGljdwMDnwn6H/YWTLkUbHEkI0c2aLmUf/fJQDxw/w9vC3ifaKNjqSzRseMZx7e9xLlGfURR+rLgWez4HflFJzqFol5jZg3lnaH5PijhBCCCGEEDXbn7ufZ9c9y/bM7fRv0Z9/9f9Xvcy9IIQQF0NrzXPrn+P3pN95tPejDAobZHSkZuOOzvWz/Pw5Czxa65eVUjuAEVQtYfKc1nr5WXaJU0p9BXwHnBxEprX+5iKzCiGEEEIIYbVyS3N5Z9s7fL3/azwcPXhx4IuMix4nc1sIIQynteb1La/zzYFvmNplKte3v97oSOIC1KUHD1RNNGrWWq9QSrkqpTy01gW1tPUEioFRp7ymASnwCCGEEKLBVFRWkFmSSUZxBpklmWQWZ5JVkkVmSSbZJdm8Nfwt7Ex2RscUzVBBeQGf7fmMT/d8Sqm5lMltJzO923S8nLyMjiaEEFXFnc2vM2f3HCa3ncyMbjOMjiQu0DkLPEqpO4GpgC/QCggF3gcuqam91vrW+gwohBBCCFFqLiW9KJ304nSOFR0jvSidY8XHOFZ8jIziDDKKM8gpzfnbfnbKDj9nP/xd/SkyF+Hp6GlAetFcZZVk8UX8FyzYu4CCigJGthzJ9G7TaeXdyuhoQggBgEVbeGXTK3we/zmT207m8T6PS69CK1aXHjzTgd7ABgCt9QGlVGBtjZVSzsDtQEfA+cTrWuvbLi6qEEIIIWxVQXkBKYUppBSmkFqYSmphKmlFaaQVpZFelF5j8cbbyZtgt2ACXQPp5N+JQJdAAl2rHgGuAfi7+OPj5CO9dkSj0lqzPXM7X+37iuUJyzFbzIxoOYLbO99OR7+ORscTQoiTyivL+eeaf7IsYRk3tL+Bh3s9LMUdK1eXAk+Z1rr8xB+0UsqeqiFXtfkM2AuMBp4FrqdqiJcQQgghmimLtnCs6BiJBYkkFSSRVJBEckEySQVJpBSmkF+ef1p7F3sXQtxCCHEPoYNfB0LcQgh2CybYNfhkUcfZ3rmWswnR+JILkvk54WeWHFrCkbwjuDm4MbHNRK5rdx2RXpFGxxNCiNPklOZw/6r72XxsM/f1uI/bOt0mxR0bUJcCz2ql1OOAi1JqJDAN+OEs7VtrrScppSZorecppb4AzjYpsxBCCCFsgNaa7NJsEvISSMhP4Gj+URLyE0jMTyS5IJlyS/nJtvYme8Lcwwh1D6VLQBdC3UNPPlq4t8DbyVtuNEWTprVmf+5+VievZmXiSnZn7wagR2APbu53M2OixuDm4GZwSiGE+LtdWbv4v1X/R05JDv8e9G/GRo81OpKoJ3Up8DxK1ZCrncA/gKXAR2dpX1H99bhSqhOQDkReREYhhBBCNCEWbSG1MJXDeYc5dPwQh/MOczjvMEfyjlBQ/r81GBxNjkR4RhDpGcngsMFEeEYQ7hFOhEcEQa5BMnRKWBWtNUfyj7D12FY2pm9kY/pGskqyAOjs35n7e97PyJYjCfMIMzipEELUzKItzI+fz+ubXyfAJYDPxn5GB78ORscS9ajWAo9S6jet9SXAS1rrR4AP63jM2UopH+BJYAngDjx10UmFEEII0eiyS7LZn7uf/bn7OXj8IAdzD3Io7xAl5pKTbfxd/In2iubSyEuJ9o4m0jOSSK9Igl2DpYgjrJLZYiaxILHq737OfnZn72Z39m7yyvIA8HX2pU9IH/qF9GNQ2CD8XfwNTiyEEGeXWpjKU389xYb0DQwNG8pzA57D29nb6Fiinp2tB0+IUmoIMF4ptQA4rZ+01npLTTtprU/07lkNRNdLSiGEEEI0KIu2cDT/KHtz9hKfE8++nH3sy9lHdmn2yTb+Lv609m7N1TFX08q7Fa28WxHtFS1LPdeBUmoM8AZgB3yktZ51xnZVvX0sUAzcUtu9lqgfRRVFHCs6RlpRGimFKSQXJpOYn3hyaKHZYgaqVmJr7d2aEREj6BLQhe6B3Yn0jJQhhEIIq1BhqeDzPZ/z3vb3AHim3zNcFXOVXMNs1NkKPE9RNTwrDPjPGds0MLymnZRSQcCLQAut9aVKqQ5AP631xxcb9mJujs61rxBCCNFcWLSFhPwEdmftZk/2HvZk7yE+J/5krxx7kz2tvVszIHQAbX3a0ta3LTE+Mfg6+xqc3DoppeyAd4CRQDKwSSm1RGu955RmlwIx1Y8+wHvVX8VZaK0pqyyj2FxMcUUxRRVFFJQXUFhRSH55Pvll+RwvO87xsuPkluaSU5pDVkkWmSWZFFUUnXYsB5MDYR5htPRoyaCwQUR7RdPGpw2tvFvhZOdk0E8ohBAXRmvNqqRVvL7ldY7kHWFo+FAe7/04Ie4hRkcTDehsBZ606gLNU1rrZ8/jmHOBOcAT1c/3A18BF1XguZibozrue2Fyj0J+ygXubHDV1PCqrdHnpwn8Dk5oAjma2u/CyR0C2hobRQgbkV2Szc6snezI3MGOrB3sztpNYUUhULVaVVuftlzR+go6+HWgvW97or2icbBzMDi1TekNHNRaHwao7hk9ATj1PmQC8KnWWgPrlVLeSqkQrXXaxZ789XVfUlZZgp3JhJ1J4WACe6VxNGnslQVHOzDpStAW0JWgNdpSCViqvupKtNbo6m2nPq/6agFtQWsLluqvJ763oE9+X1n9eqW2YNGVVGpNpa6kUluoxIK5+nuztlChK6mwVGLGQrmlknJdSbk2U6YrKdNmSi2VlGozpboSy1kXd636X8XT5IivyQkfkxNt7JwZ4BhMgIsLwXYuBJtcCLV3JcDkjB1ApYbsHMjKBjb970D61POccc6T23QNbTnHttqOVZPzaVvLPn/bXJdjXOCxbUYt90g9boKw2MaNIsQ5aK1Zm7qWD3Z8wNaMrUR6RvLmsDcZFjHM6GiiEZytwPMm0BO4gqrlzuvKX2u9UCn1GIDW2qyUqrzwiCdd8M0RVZM8n2vfC7P1M/jjlYs+jBDiDJGD4JYfjU4hhNWxaAuHjx9mS8YWtmVsY1vmNpIKkgCwV/bE+MQwNmosnfw70cm/E1FeUdib6rLmgrgIoUDSKc+T+XvvnJrahAKnFXiUUlOBqQARERF1Ovm3e14g1974Ir5Ja0yASYMdGrvq1+yrX7NHY6819tXfO2hw0BoHrXHXGsfqh5MGZ23BSWtctMbVonHRFtwsGneLpfqh8bRY8LRY8LBo7JTi5Jv0E9+f9sFGbdtOff2U56e9duYx+Hvbv+2jann9LPteSNta9/lbg3Mf44KP3XRoqC5KguXEV6q+aq2x6NPbaKgqeFa3qX6KpmpjslMs3aTAI5qI8spylics5/P4z9mTvYcg1yCe7PskV8ZciYNJPrRpLs52R1ehlJoDhCql3jxzo9b6nlr2K1JK+VF9TVRK9QXyLjrpxd0c1WVf4AJunLpdB5EDz93uTBf1aUl9MPj8hv/8YPjv4IQmEaNJhDj974WrDAURoi7MFjN7c/YSlx7H5mOb2ZKxhfzyfAD8nP3oFtiNSW0m0TWgK+392uNi72Jw4mappnfAZ15469IGrfVsYDZAbGxsnS7es71HY64oohIHzJgwY08FdlRoE2UWE+WVJkotihKzoqRCU2SGgjJNfjnklVVSbjFhoepRqe1wc3Yg2MuNFt5utPT3IDLAkwh/Dxzs7FDKHmUyYVL2mEx2KGWHnanqNZRdVTFAmap+XGWq+Tmc8r06o406y1dOaW89RQdx8bTWZBaWkXq8lLTjJaTllXKsoJTM/DIyC8vIKiwnp6iM3KIKyistZz2WUuDmaI+Lox2ujnY429vh7GiHk70JZ4eqr1UPO65rF95IP6EQtTuYe5DvDn7HD4d/IKc0hyivKJ7u9zQTWk2Q3rjN0NkKPOOAEVTNtbP5PI55P1WrZ7VSSv0FBAATLzjh/1zMzVGdbprgAm6cfKOrHkIIIUQjsGgLB3IPsD5tPRvTN7L52OaTc4lEeEQwouUIegT2oEdgD8I8wmQSxaYhGTj1nWAYkHoBbS5Iu6tfu+B9tdZkF5WTdryUlOPFHM0u5khWEfszCvnxYAEFu81AJW6OBfRo6cOA1j4MbRtA2yAP+bsn6l1hmZn9xwo4eKyQg5mFHMkqIiGriKTcYkorTi/cONqZCPBwIsDDiVBvZzqHeuLj5oiPqyPeLg54uTjg6eKAh7M9Hs4OuDvZ4+Zkh4uDnfzdFU2a1poDxw+wMnElvxz9hQO5B7BX9gwJH8I1ba+hX0g/+TvcjNVa4NFaZwELlFLxWuvtdT2g1npL9epbbakqrOzTWldcfNSLujlyrMO+QgghRJOUXpTOutR1rEtdx4b0DeSU5gAQ6RnJ2Kix9AruRWxQLAGuAQYnFbXYBMQopaKAFGAKcN0ZbZYAM6qHkfcB8upj/p2LpZTC390Jf3cnOoedvlqaxaJJzClme/Jx4hJy2XAkm1nL9jJr2V7CfFy4rEsIE7qG0qGFp0HphTUrrahkR3Ie25Jy2Z6Ux+7UPBKyi09ud7Q3EennSpS/G0PaBBDu60qotwsh3s6EeLng4+ogb3KFzcgqyWJT+iY2pG3gr9S/SC9KR6HoHtidR3s/yqVRl8pCCAI4ew+eE0qUUr8BQVrrTkqpLsB4rfXzNTWuntB4LFXz3tgDo5RSaK3PXInrfF3wzZFSKrMO+wohhBBNQkVlBVsztvJnyp+sSVnDweMHgaplyge0GEDfFn3pHdybYLdgg5OKuqiej3AGsJyq1Tw/0VrvVkrdVb39fWApVfdPB6laCfRWo/LWlcmkiPR3I9LfjQndQgFIzytl1b4Mft6dzsd/HuGD1YfpEubF9X0imNAtFGcHO4NTi6aqotLClqO5/HUwi7WHstmRnHdyOFWYjwudWnhxVY8w2gV70CbIg3BfV+xMUsARtievLI/9uftPrnK5PXM7KYVVi/p4OHjQK7gXd3W5i0Fhgwh0DTQ4rWhq6lLg+RB4CPgAQGu9Qyn1BVBjgQf4ASgFdgJnH+R6Hi7m5qi2fesrmxDCdiilfKla+S8SSACu0Vrn1tDuE6qGsmZorTs1ZkZhm3JLc/kz5U9WJ61mbepaCisKsTfZ0zOoJxNaTaB/aH9ivGPkE2krpbVeStV9yqmvvX/K9xqY3ti56luwlzNTekcwpXcEuUXlfL8thS83JvHI4p28+st+bh8YxU39WuLqKBN7CygqM7NybwbLd6ezen8mBaVmTAq6hHlz68BIYlv60iPCGz93Wab+TEqpMcAbVL23+UhrPeuM7ap6+1iq3hfdorXe0uhBRY0KygtIK0ojpSCFpIIkEgsSSchP4MjxI2SUZJxsF+gaSNeArlzb7lp6BPagvV97WRhBnFVd/na4aq03nnFDaT5L+zCtdZeLi1Wzi7k5qmlfIYSowaPAb1rrWUqpR6ufP1JDu7nA28CnjZhN2JjUwlR+S/yN3xJ/Y2vGVizaQoBLAKMjRzMobBB9Q/ri5uBmdEwhLoiPmyO3DIji5v6RrD2UzfurDzFr2V4+WXOE/xvZhmtiw6UHRjNUadGsOZjF13FJrIg/RmmFBX93J8Z2CmFYu0D6tfLDy0Umhj2b6hET7wAjqZqiYpNSaonW+tQVgi8FYqoffYD3qGWRGXFxKiorKKwopLCikILyAgrKC8gry+N42XGOlx0ntzSX7NJsskuyySjOIKM4g2Jz8WnHcHdwJ8orij4hfYjxiSHGJ4Z2vu3wd/E36KcS1qouBZ4spVQr/rcq1kTOWLLzDMuUUqO01r/UR0AhhGhkE4Ch1d/PA1ZRQ4FHa/2HUiqy0VIJm5GYn8gvR3/h16O/sie76l48xieGOzvfybDwYXTw6yC9dIRNUUoxoLU/A1r7E5eQw4tL43nsm50s2JTErKs60z5E5uhpDnKKylmwKZH56xNJOV6Ct6sDk3qGM65LCLGRvlLsOz+9gYNa68MA1dNTTABOLfBMAD6t/gB8vVLKWykVUh9ze6Wve4vcxDWnvVa1Mo068YbxjC3qf22Uqlp2/kRbOO3ryYc6sY8+uc1yWht98jWoWu7eQtWxK9FYql+r1NXbFFTqqtfN1W0qtcasNBVaU4EFc/XXE8/L0VRoC2VYKNMWynQlJdpCKZWU6KpHsTZTcY7VaF2VHX4mJ/xMTsSYnBngEEiQswshdq60sHMh3M4Vb+VYtdpgMVB8EFIOAsuqDlDjPcEZr/2tjarl9fPYt8Y259r3Ao5fp2OcY/sFn+diMtXh93a+2XxbQZtRtR+nDupS4JlO1apS7ZRSKcAR4PqztF8PfKuUMgEVVKXXWmv531sIYQ2CTtz8VM/hJYObxUVLK0xjWcIyfj7yM/E58QB08e/C/T3vZ0TECMI9Zald0TzERvqy+O7+LNmeyrM/7OHyt9Ywc3gMM4a3ljf4Nio5t5gP/zjMgk1JlJkt9G/lx+Nj2zOiQyBO9jIn0wUKBZJOeZ7M33vn1NQmlLN/UF8n/z74MyssiRd7mCbFpDUOgL2uWp3HXmscq793qv7eWWv8NbhojTPgatG4ao2b1rhZNG4aPC0aD23By6LxqtR4WzT/G2B4SiFIn1kUOuO5PrP8VdO2hty3hjbn2ldctN0+l9CxoQs81ZXhEUopN8CktS44xy6vAf2AndUVYyGEaFKUUiuAmmanfaIBzjUVmAoQERFR34cXTVheWR6/HP2FHw/9yJaMqmkPOvl14sHYBxnVchQh7iEGJxTCGEopJnQLZUibAJ5espvXV+xn/eFs/julG0GezkbHE/Uko6CUt1ce5IsNVYWAq3qEcuegaGKCPAxOZhNqqoae+b6rLm0u6D7FyXsGTgf2UW62UG62YLZYqg9eW5FW4eJgh7uTPZ4uDng5O+Dt6oC3ixN+7k74uTsS6OGMr5sTdiaFQqFU1deqvf/3XCmFSZlOe+3Ec5MyVX2vFHbK7uRXkzKd/Gpvsj/51U7ZYW+yx17ZY2eSYmODOLMcUJci0cUUoc7nPGdpq7Ums6iM1NxSUo4Xk368lGMFpWQVlpNZUEZOYSk5RRXkl1YtFq7Ocnw7k8LVwQ5HexMujiac7U0429vhYG/C0c6Eg73C0VT1tUtEAB1rT1ondZ6hSWtdVMemB4BdUtwRQjRVWusRtW1TSh070YVZKRUCZNTWto7nmk1VL0hiY2PlumjjzBYzf6X8xfeHvmdV0ioqLBVEe0Uzs/tMLo28VHrqCHEKb1dH/ju5G4NiAnjyu12Mf3sNH9/ci06hXufeWTRZZeZKPvrzCO/8fpAys4XJvcKZMaw1LbxdjI5mS5KBU/9DCQNSL6DNBd2nzLr8Uqqm+KlirrRQVF5JUZmZojIzBWVm8ksqyC81k1dSQV5xOTlFFeQUlVW9Qc4p4+DRUnKLK06kAEpwsCslwteV6AB3YgLdaRvsQYcQT6ID3KWHn7U6c2hSExuCrrUm5XgJ8WkF7E3L50BGIQczCknILqK4vPK0tm6OdgR5OuPv4UJkC296uDni6+aIj6sDXq4OeLk44OHsgIezPW6O9ng42+PqaI+jvalRf6aGmII7DVillFoGlJ14sR6WSRdCiMawBLgZmFX99Xtj4whrcDT/KN8c+IYlh5aQVZKFr7Mvk9tO5vJWl9Pet73MqSNELZRSTOwZRqdQT26fG8ek99fx5rXdGdkhyOho4gKsPZjF49/uJCG7mNEdg3j00vZE+ctE8Q1gExCjlIoCUoApwHVntFkCzKien6cPkFcf8+/UxN7OhJeL6bwnxy6tqCQtr5SU3BKScotJyC7iSGYRh7OK+H1vBmZLVb3J1dGOTqFe9GzpQ69IH3pH+eHuJCtJifNXbrawPfk4G4/kEJeQw/bkPHKKyk9uD/V2oXWgO32ifWnp60qEnyuh3q6EeDvj6Wwdk783xL+MI9UPx+qHEEJYk1nAQqXU7UAiMAlAKdWCqmVIx1Y//5KqyZj9lVLJwNNa64+NiSyMUF5Zzm+Jv7Fw30LijsVhp+wYFDaIK1tfyaCwQTiYrONGQIimoF2wJ99O78+d8+K46/PNvD65G+O7tjA6lqijojIzLy2L5/P1iUT6ufLpbb0Z3CbA6Fg2S2ttVkrNAJZTtUz6J1rr3Uqpu6q3v0/V6sFjgYNUTd17q1F5a+PsYEeUv1uNRcAycyWHM4vYk5rPzpQ8tiYd58M/DvPeKo2dSdEt3JthbQMY0SGItkEe8kGKqFV6Xim/7knn932ZrD+cfbJnTutAdy5pF0iXMC86tPCiXbAHbjZQOFS1jaRSSl11th211t80SKImJDY2VsfFxRkdQwhxDkqpzVrrWKNznItcU2xDWmEaC/cv5JsD35BTmkOoeygT20xkQqsJBLjKGxpbINcU4xSWmblt7ibiEnJ4dVJXruoRZnQkcQ67U/OY8cVWErKLuG1AFA+OaouLo8xnciq5ptSPkvJKtibm8tehLP48kMWO5DwAov3dGNe1BVd2D5UeYwKA7MIyftyRxnfbUtiaeByAln6uDGkTwIDW/vSO9MXHzbr7otR2XTlbierys2zTgM0XeIQQQgioGqO9+dhm5sfPZ2XSSgCGhA1hctvJ9GvRD5Nq3PHVQtgqdyd75t7aizs/jePBr7fj7mTPqI41zYkvmoIFGxN5aslufFwd+PLOvvSN9jM6krBhLo529G/tT//W/jw0Go7ll7Ii/hg/7UjjrZUHePO3A/SJ8uWGvi25tFMw9nbyf3NzorVmw5EcPl9/lJ93pWO2aNoFe/DQ6LaM7hhE68DmMcF7rQUerXWT68YnhBBCNKYKSwXLE5bz6e5Pic+Jx8vJi1s63sLktpNp4S7DR4RoCK6O9nx4UyzXfriBmV9uZf4dfYiN9DU6ljiFudLC8z/FM3dtAoNi/Pnv5G74uTude0ch6lGQpzPX92nJ9X1aciy/lEWbk/lqUxIzv9xKqLcLtw2M4rreEdKjzMZVWjTLd6fz3qpD7EzJw9PZnpv7RzIpNox2wZ5Gx2t0dRpkppS6DOgInFy7Umv9bEOFEkIIIYxUVFHEov2L+GzPZxwrPkaUVxRP9XuKcdHjcLGXlWCEaGiujvbMuaUXE99by+3z4vh++gAiZehFk1BUZmba/C2s3p/J7QOjeHxse1nhSBguyNOZ6cNac/eQVqzcm8GHfx7muR/38P7qQ0wf2orr+7bEQXr02BStNSv3ZvDyz/vYd6yASD9XXryyM1d2D23WRb1zFniUUu8DrsAw4CNgIrDxLO3bAO8BQVrrTkqpLsB4rfXz9RNZCCGEaBjHS48zf+985sfPp6C8gF7BvXiq31MMDB0ow7CEaGS+bo7MvbU3499Zw12fb+abaf1xdbT+CTCtWV5xBbfM3cj2pOO8eGVnrusTYXQkIU5jMilGdAhiRIcgNhzO5j+/7ueZH/bw2fqjPDmuA0PbBhodUdSDgxkFPPndbtYdzibSz5U3pnRjXJcWUmwG6nK32l9rfROQq7X+F9APCD9L+w+Bx4AKAK31DqqW7hNCCCGapOySbP6z+T+MWjyK97e/T+/g3swfO59PRn/C4LDBUtwRwiARfq68OaU7+44V8OjindS2OIhoeNmFZUyevY7dKfm8e30PKe6IJq9PtB8Lpvbl45tjqbRobpmziZlfbj1tWWxhXcrNFl5dvo8x//2T3al5PDuhI7/eP4QJ3UKluFOtLh+DlFR/La5eJjgbiDpLe1et9cYzlqozX2A+IYQQosHkluYyZ9ccFuxbQFllGaMjRzO181Ra+7Q2OpoQotrgNgE8OKotryzfR59oX67v09LoSM1OXnEFN368kSNZRXxySy8GxvgbHUmIOlFKcUn7IAbG+PPB6sO8tfIAaw9m8e+ruzCiQ5DR8cR52JdewH1fbSM+LZ+reoTy+Nj2+MvcX39TlwLPj0opb+AVYAtVK2h9dJb2WUqpVtXtUEpNBNIuMqcQQghRbwrKC5i7ey6f7/mcEnMJl0VfxtQuU4nyOtvnF0IIo9w9pBXrD2fz/I/x9Iv2IzrA3ehIzUZhmZmbPtnAwYxCPrw5Voo7wio52dtxzyUxjO4YzP0Lt3HHp3HcMTCKh8e0w9Feeuk2dQvjkvjnd7vwdLbno5tipTh3Fucs8Gitn6v+drFS6kfAWWudd5ZdpgOzgXZKqRTgCHDDRScVQgghLlJZZRlfxn/JR7s+Iq8sj1EtRzG923SivaONjiaEOAuTSfHKxK6M/u8f/N/C7Sy6q59MmNoIKiotTJu/hV2p+bx/Q0+GtAkwOpIQF6VtsAeL7+7Pi0vj+WjNEbYnH+eDG2PxdXM0OpqoQbnZwtNLdvPlxkQGtPbjjSndpdfOOdRa4FFKDddar1RKXVXDNrTW39S0n9b6MDBCKeUGmLTWBfUXVwghhDh/Fm3hp8M/8dbWt0grSmNA6ADu7X4v7f3aGx1NCFFHwV7OvHBlJ2Z8sZUPVh9ixvAYoyPZNK01T32/iz/2ZzLrqs6MlE/MhY1wdrDj2Qmd6NnSh4cW7eCKd/7ik1tiaR3oYXQ0cYr80gru/nwzfx3M5u6hrXhwVFuZZ6cOztaDZwiwEri8hm0aqLHAo5RyAq4GIgH7E3PxyLLqQgghjLD52GZe3vQye7L30MGvA88NeI4+IX2MjiWEuADjurTgpx1pvLXyIJd3bUFLP1k6vaF8vOYIX25MYvqwVkzpLRMqC9szoVso4b6uTP00jonvr+Oz2/rQOczL6FgCyMgv5aZPNnIwo5BXJ3VlYs8woyNZjVoLPFrrp6u/fVZrfeTUbUqps01S8D2QB2wGyi46oRBCCHEBUgtTeS3uNX45+gtBrkG8OPBFLou+TFbEEsLKPX15R/48kMU/v9vFp7f15oyFPUQ9WHcom5eW7WVMx2AeGNnW6DhCNJgeET58c/cArvtoPdd9uJ5Pbu1Fr0hfo2M1a8fyS7l29nrS80uZc2svBsXI0NDzUZdJlhcDPc54bRHQs5b2YVrrMReVSgghhLhAZZVlzN01lw93fohCMa3bNG7peAsu9i5GRxNC1INgL2ceHNWGZ37Yww870hjftYXRkWxKWl4JM77YQqSfK69M6oJJhkQIGxfh58rCf/Tjho82cPMnG5l/Rx+6R/gYHatZOlHcOZZfyqe39SZWim3nrdaPMZVS7ZRSVwNeSqmrTnncAjif5ZhrlVKd6zuoEEIIcS5rU9Zy1fdX8fa2txkcNpglVyzh7q53S3FHCBtzY79IOoV6MmtpPKUVlUbHsRmVFs29X26jtKKSD27siYezg9GRhGgULbxdWDC1L/7uTtwyZxP70mUa2caWV1LBzZ9srCru3C7FnQt1tn7qbYFxgDdV8/CcePQA7jyzsVJqp1JqBzAQ2KKU2qeU2nHK60IIIUSDyCrJ4uHVD/OPFf9AKcUHIz/gP0P/Q4h7iNHRhBANwM6keGJsB1LzSvl4zZFz7yDq5L1VB9mYkMNzV3SSCWdFsxPo6cz8O/rg7GDixo83kHq8xOhIzUZpRSVTP43jUGYhs2+KpWdLKe5cqLPNwfN99bLoj2itX6zDscbVXywhhBDi3LTWfHfwO16Je4UycxnTuk3j9k6342gny50KYev6tfJjRPsg3lt1iMm9wmXp3Iu0NTGX11cc4PKuLbiye6jRcYQwRLivK5/d3oer313L7fPiWHRXP9yc6jKribhQWmseXrSDDUdyeGNKNwa09jc6klU760yTWutKYGRdDqS1Pqq1Pgo8f+L7U1+rh6xCCCHESckFydz5y508tfYp2vi0YdH4Rdzd9W4p7ogmRSnlq5T6VSl1oPrr3yZ2UEqFK6V+V0rFK6V2K6XuNSKrNXpsbDtKKir574r9RkexaqUVlTywcDvBns48f0UnmbhaNGttgjx487ru7EvP5/++2obFoo2OZNM+/PMwS7an8tDotkzoJsXli1WXpUTWKqXeVkoNUkr1OPE4S/uOpz5RStlR+4TMQgghxHmxaAsL9i7gqiVXsSt7F0/2fZJPRn9ClNfZFngUwjCPAr9prWOA36qfn8kMPKC1bg/0BaYrpTo0Ykar1SrAnSm9wvlqUxLJucVGx7Fab/52gMNZRcy6ujNeLjLvjhDD2gbyxGUd+GXPMd5bfcjoODbrzwOZzFq2l7Gdg5k2tJXRcWxCXQo8/akq2jwLvFb9ePXMRkqpx5RSBUAXpVR+9aMAyKBq6XQhhBDioqQXpfOPX//BCxteoFtAN74d/y3XtL1Glj4XTdkEYF719/OAK85soLVO01pvqf6+AIgH5GPMOpoxvDUKxTu/HzQ6ilXalZLHB38cZlLPMFmOWIhT3DYgknFdQnjtl31sPJJjdBybk5Ffyr0LthET6MErE7tKz8F6cs47Yq31sBoew2to95LW2gN4RWvtWf3w0Fr7aa0fa5D0Qgghmo1lR5Zx1fdXsT1zO0/2fZIPRn4gkygLaxCktU6DqkIOEHi2xkqpSKA7sKHho9mGEC8XpvQO5+u4ZJJypBfP+ai0aB77Zic+ro788zLpNCbEqZRSvHRVZyJ8Xbnny61kF5YZHclmWCya+xdup7jczDvX95B5jupRnT7yVEpdppR6WCn11IlHbW2lmCOEsGYyX0bTU1heyGN/PsbDfzxMtHc0iy9fzDVtr5FPekSToZRaoZTaVcNjwnkexx1YDNyntc6vpc1UpVScUiouMzOzPuLbhGlDW2NSirdXSi+e87FgUyI7U/J46vIOeLnK0CwhzuTh7MDb1/Ugp6icf363C61lPp768NGaw6w5mMXTl3ekdaC70XFsyjkLPEqp94HJwExAAZOAlg2cSwghjCLzZTQhu7J2MemHSSw7soxpXacxd8xcwj3DjY4lxGm01iO01p1qeHwPHFNKhQBUf82o6RhKKQeqijvztdbfnOVcs7XWsVrr2IAAGU5zQrCXM9f2DmfxlmTS8mRp47rILSrnleX76BPly+VdpDekELXpFOrFfSNjWLYrnR92pBkdx+odOFbAK8v3MaZjMFN6yT1dfavTHDxa65uAXK31v4B+gPxJCCFslcyX0QRorfl096fcuPRGKnUlc8bM4e5ud2Nvki68wuosAW6u/v5mapiXUFV1R/sYiNda/6cRs9mUOwZFo4E5fyUYHcUqvPbrPgpKzTwzvqP0iBTiHKYOiqZbuDdPfb+LjIJSo+NYrUqL5uHFO3B3sueFK2XFvoZQlwLPiY9BipVSLYAKoNalSpRSn9XlNSGEaKLqdb4MGU5x/vLK8rj393t5Je4VBocN5uvLv6Z7YHejYwlxoWYBI5VSB4CR1c9RSrVQSi2tbjMAuBEYrpTaVv0Ya0xc6xXu68rYziF8sSGR/NIKo+M0afuPFfDFhkRu6BNB+xBPo+MI0eTZ25l47ZqulJRX8q8le4yOY7XmrU1ga+JxnhnfET93J6Pj2KS6fBT6o1LKG3gF2AJo4MOztJdl0oUQTZpSagUQXMOmJ87zOOecL0NrPRuYDRAbGysDt89hb85e/u/3/yO9KJ2Hez3MDe1vkE93hFXTWmcDl9Tweiowtvr7NVQNgxcX6R+Do/lheypfbkjkH0Nkyd3avPzzXtyc7LlvRBujowhhNVoFuDNjWGte+3U/1+zPZEgbGSZ7PlKOl/DK8n0MbxfI+K4tjI5js85Z4NFaP1f97WKl1I+As9Y678x2SqnHgMcBF6XUiTc6Ciin+s2NEEKcTUZxBluObSHuWBw+zj5M7za9Qc6jtR5R2zal1DGlVIjWOq0+5ssQdffDoR/417p/4eXkxdxL59I1oKvRkYQQVqZTqBcDWvvxyV9HuHVAFI72dVpPpFnZeCSHFfEZPDymLT5ujkbHEcKqTB0SzTdbU3j6+138fN9gnB3sjI5kNV78KR6N5tkJMiy0IZ2zwKOUcgamAQOp6r2zRin1ntb6tMGHWuuXgJeUUi/JSlpCiLpIKUwhLj2OuGNxbD62maSCJABc7F0YHTnaqFgn5suYhcyX0SjMFjOvxb3G5/Gf0yu4F68MfgU/Fz+jYwkhrNQdg6K5dc4mlu9O53L5lPg0WmteWhZPsKczt/avdcYF0YQppXyBr4BIIAG4RmudW0O7BKAAqATMWuvYxktpu5zs7XhuQidu+HgDH6w+zL0jYoyOZBXWHszip51p3D+yDWE+rkbHsWl1GaL1KVUXh7eqn18LfEbValp/o7V+rHpZ4RjA+ZTX/7i4qEIIa5dSmMKm9E1sSt9EXHocqUWpAHg6etIzqCeT206mZ1BP2vm2M3Iy3VnAQqXU7UAi1de66jnIPtJaj+V/82XsVEptq97vca310hqOJ84iryyPB1Y/wIa0DdzQ/gbuj70fB5Ms1SuEuHBDYgJo6efKp+sSpMBzhhXxGWxNPM6/r+6Mi6P0PLBSJ1b7nKWUerT6+SO1tB2mtc5qvGjNw8AYfy7rHML7qw8xpXc4QZ7O596pGauotPDMD7sJ83Fh6uBoo+PYvLq8g2qrtT61n/zvSqnttTVWSt0B3AuEAduoWkJ4HTD8InIKIaxQelE6G9M3sjFtI5vSN50s6Pg4+RAbHMtNHW+iV3AvWnu3xqSaRjd6mS+j8Rw+fpiZK2eSVpTG8wOeZ0LrCUZHEkLYAJNJcWPfljz/Uzx7UvPp0EImEYaq3jv/XbGfln6uXN0jzOg44sJNAIZWfz8PWEXtBR7RQB4Z045f9qTz2i/7eHmiDCk/m682JbH/WCHv39BThrQ1groUeLYqpfpqrdcDKKX6AH+dpf29QC9gvdZ6mFKqHfCvi48qhGjqcktz2ZC+gY1pG9mYvpGj+UcB8HLyoldQL27qeBO9g3vT2ru1jL1t5talruOBVQ/gYOfAJ6M/oVtgN6MjCSFsyKSe4bz6yz4+W5/AS1d1MTpOk7AiPoPdqfm8Oqkr9nZN40MVcUFOW+1TKVXbap8a+EUppYEPqhd9EPUkws+Vm/tF8nH1fF+yGl3NisvNvPHbAXpF+jC6Y5DRcZqFuhR4+gA3KaUSq59HAPFKqZ2A1lqf+b9mqda6VCmFUspJa71XKdW2PkMLIZqGEnMJW45tYX3aetanrWdvzl4A3BzciA2KZVKbSfQN6UuMT0yT6aEjjPfNgW94bt1zRHpF8s4l79DCXYZQCCHql5erA1d0C+XbrSk8OqY9Xq7Ne+jnqb13rugm19ymrp5W+xygtU6tLgD9qpTaW9OUGUqpqcBUgIiIiAvK21zNHB7D15uTeXFpPJ/d3sfoOE3SJ2uOkFlQxvs39JAPdxtJXQo8Y87zmMnVy6p/R9XFJBdIPc9jCCGaoEpLJXtz9rIubR3rUtexNWMrFZYKHEwOdAvsxoxuM+gT0odO/p2MnENHNFFaa97Z9g4f7PiA/i3689qQ13B3dDc6lhDCRt3QtyULNiXx3bYUbu4faXQcQ/0mvXesSn2s9lk9tBytdYZS6lugN/C3Ak91z57ZALGxsbo+8jcXXq4OTB/WiheX7mXjkRx6R/kaHalJySkq5/3VhxnVIYieLeV301jqskz60fM5oNb6yupvn1FK/Q54AT9fQDYhRBOQXpTOutR1rE1dy/q09RwvOw5AW5+2XN/+evqG9KVHUA9c7F2MDSqatApLBf9a+y++P/Q9V7a+kif7PSmTKQshGlSnUC86h3rx5cZEburXsll/evze6kOE+bhI7x3bUJfVPt0Ak9a6oPr7UcCzjZqymbixbySz/zjC67/u58upfY2O06R8sPoQxeVmHhotg3kaU4N+xK61Xt2QxxdC1L+yyjI2H9vM2pS1/JX6FwePHwQgwCWAwWGD6deiH31D+uLv4m9wUmEtSswlPLDqAf5M+ZO7u97N3V3vbtZvtIQQjeeaXuE8+d0udqbk0SXM2+g4htiUkMPmo7n8a3xH6b1jG+qy2mcQ8G31/7X2wBdaa/nAvQG4ONoxbWgrnv1xD2sPZdG/ldwfA2QXlvHpuqOM79qCmCAPo+M0K1YxhkIp5Qt8BUQCCcA1WuvcGtqNAd4A7Ki6wM2qfv0Z4E4gs7qpLGcsxCmS8pP4M+VP/kr9i03pmygxl+BgcqBHUA8mtJpA/9D+xHjHyJtycd7yyvKY8dsMtmdu58m+T3JN22uMjiSEaEbGd23BCz/tYcGmpGZb4Hl/1SF8XB2YFCsrZ9mCOq72eRiQpZ0ayXV9Ivjgj0O8/ut++kX7yf0y8PGaI5SaK5kxvLXRUZodqyjwAI8Cv2mtZymlHq1+ftpygEopO+AdYCSQDGxSSi3RWu+pbvK61vrVxgwtRFNVXllO3LE4/kz+kzUpa0jITwAg3COcK1pfwYAWA+gV3AtXB1djgwqrllWSxdRfp5KQl8CrQ15lVOQooyMJIZoZLxcHxnYOYcm2VP55WXtcHa3l1rd+7Esv4Le9Gdw3IqbZ/exCNBZnBzvuHtKKZ37Yw6aE3GY/F09uUTnz1iZwWecQWgdK753GZi1X+gnA0Orv5wGrOKPAQ9XEYQerK9YopRZU77cHIQQZxRn8mfwnfyT/wbq0dZSYS3A0OdIrpBdT2k1hYOhAWnq2NDqmsBFphWnc+eudZBRn8PYlb9O/RX+jIwkhmqkpvSL4ZksKS3emM7Fn8+rF8vGawzg7mLi5X6TRUYSwaZN7RfDWyoO8u+ogvaN6Gx3HUHP+OkJReSUzh8cYHaVZspYCT5DWOg2gesb4wBrahAJJpzxPpmqJ9xNmKKVuAuKAB2oa4iWELdFasydnD38k/cGq5FXsya6qdQa7BXN59OUMDhssvXREg0gqSOKO5XdQUF7A7JGz6RbYzehIQohmrFekDxG+rnyzJblZFXiyC8v4blsqk3qG4ePmaHQcIWyai6Mdtw6I5NVf9rMnNZ8OLTyNjmSI4nIzn64/yqgOQbQNlt47RmgyBR6l1AoguIZNT9T1EDW8dmKpv/eA56qfPwe8BtxWS46pwFSAiIiIOp5aiKah1FzKxvSNrEpaxeqk1WSUZKBQdA3oyr097mVw2GCZS0c0qKP5R7l9+e2UVpby0eiP6ODXwehIQohmTinFVT1CeeO3A6QeL6GFd/NY9fHLjYmUmy3cOiDS6ChCNAs39ovk/dWHeX/1Id68trvRcQyxcFMSx4sr+MeQaKOjNFtNpsCjtR5R2zal1DGlVEh1750QIKOGZslA+CnPw4DU6mMfO+VYHwI/niXHbGA2QGxsrK6tnRBNRW5pLquTV7MqaRVrU9dSYi7B1d6VAaEDGBI2hEFhg/B1bt5jgUXjOJp/lNt+vo0KSwUfj/qYtr6yLKYQomm4snso/11xgO+2pTBtqO1P+llRaeGz9UcZFOMvc2AI0Ui8XBy4vk8EH/55mIdGtyXct3n1kjdXWvhozRF6RHjTs6W89zBKkynwnMMS4GaqlgW8Gfi+hjabgBilVBSQAkwBrgM4URyqbnclsKvBEwvRgJILklmZuJLfk35nS8YWLNpCkGsQ41uNZ1j4MHoF98LRTrpji8Zzorhj1mY+Hv0xMT4y7loI0XS09HMjtqUP32xJ4e4hrWy+J+vSnWkcyy9j1lVdjI4iRLNy64AoPl5zhHlrE/jnuObVi3nZrnSSc0v452XN6+duaqylwDMLWKiUuh1IBCYBKKVaULUc+littVkpNQNYTtUy6Z9orXdX7/+yUqobVUO0EoB/NHJ+IS6K1pr9uftZmbiSFYkr2J+7H4AYnxju6HwHwyOG08G3g83fsIqmKakgiduWV/fckeKOEKKJuqpHGI9/u5NdKfl0DvMyOk6Dmrc2gSh/N4a0CTA6ihDNSrCXM5d1CeGrTUncN7IN7k7W8nb74n205ghR/m6M7BBkdJRmzSr+xmmts4FLang9FRh7yvOlwNIa2t3YoAGFaAAWbWFn1k5+O/obKxJXkFSQhELRPbA7D8Y+yPDw4YR7hp/7QEI0oPSidO785U7KKsv4eJQUd4QQTddlnUN45ofdfLM12aYLPHtS89mSeJx/XtYek0k++BGisd06IIrvt6WyKC6JWwZEGR2nUWxNzGV70nH+Nb4jdnLdMZRVFHiEaC4qLZVsydjCiqMrWJG4goziDOxN9vQJ7sOtnW5lWPgw/F38jY4pBABZJVnc8csd5JXl8dHoj2TOHSFEk+bl6sCwtgH8uCONf17WwWbfhMzfcBQne1OzWjFMiKakW7g3PVv6MGdtAjf1i2wWhdZ5axNwd7LnarnuGE4KPEIYzGwxs/nYZn49+isrjq4guzQbJzsnBrQYwIgeIxgSPgRPx+a51KJouvLK8vjHr/8goziD2SNn09Gvo9GRhBDinC7v2oLlu4+x4XA2/Vvb3gcmhWVmvtuawuVdW+DtKnPxCWGU2wZEMf2LLazcm8EIGx+ylFFQyk8707i+T8tmNSStqZI/ASEMcKKoszxhOb8l/kZOaQ4u9i4MCh3EqMhRDAodhKtD85p5X1iP4opipv82nSN5R3j7krfpFtjN6EhCCFEnl7QLws3RjiXbU22ywPPd1hSKyiu5vk+E0VGEaNZGdwwiyNOJzzcctfkCz5cbkqio1NzUr6XRUQRS4BGi0ZwYfrU8YTm/Hv31ZFFnSNgQRkWOYmDoQFzsXYyOKcRZVVgqeGD1A+zM2smrQ16lf4v+RkcSQog6c3G0Y2SHIJbtSufZCZ1wtDcZHaneaK2ZvyGRji086RbubXQcIZo1ezsTU3pF8ObKAyRmFxPhZ5sf3FZUWpi/4ShD2gQQHeBudByBFHiEaFAWbWFH5g5+TviZXxJ+IbMkE2c7Z4aED2FUy1EMChskRZ0mRinlC3wFRFK16t41WuvcM9o4A38ATlRdRxdprZ9u3KSNz6ItPP3X06xJWcNT/Z5iZMuRRkcSQojzNr5bC77blsqfBzK5pL3tfLK+MyWP+LR8nr+ik6yqKUQTcG3vCN7+/SDzNx7lsUvbGx2nQfwWn0FGQRkvXim9d5oKKfAIUc+01uzN2cuyhGX8fORn0orScDQ5MihsEGOixjA4dLAMv2raHgV+01rPUko9Wv38kTPalAHDtdaFSikHYI1SapnWen1jh21Mb2x5gx8O/8D0btOZ1GaS0XGEEOKCDGwdgLerA0u2p9pUgWfBpiScHUyM79bC6ChCCKqWTB/RPpCv45K5f2QbnOztjI5U7+ZvOEqIlzND2wYYHUVUkwKPEPXkaP5Rlh5ZyrIjyziSdwR7ZU+/Fv2Y2X0mw8KH4e4o3RatxARgaPX384BVnFHg0VproLD6qUP1QzdOPGN8tfcrPtn1CZPaTOIfXf5hdBwhrEZdegWe0tYOiANStNbjGitjc+Nob2JMx2B+2J5KaUUlzg7W/6aruNzMkm2pjO0cgqezg9FxhBDVbujbkuW7j7FsZzpXdA81Ok69Sswu5s8DWdw3IgZ7O9sZ7mrtpMAjxEXIKsli2ZFlLD28lF3Zu1Aoegb15Ib2NzCy5Uh8nH2MjijOX5DWOg1Aa52mlAqsqVH1G7HNQGvgHa31hlraTQWmAkREWOekl6uSVvHixhcZEjaEx/s8Ll3/hTg/dekVeMK9QDwgSyc2sMu6hLBgUxKr92cyumOw0XEu2tKd6RSWmZnSyzr/nxHCVg1o5U+knytfbky0uQLPl5sSMSmY3Cvc6CjiFFLgEeI8FVUU8Vvib/x46Ec2pG/Aoi20923PAz0fYEzUGILdrP9G0dYppVYANf1BPVHXY2itK4FuSilv4FulVCet9a4a2s0GZgPExsZaXS+f+Ox4Hv7jYdr7tuflwS9jb5L/NoQ4T+fsFQiglAoDLgNeAO5vpGzNVr9oP3xcHVi6M80mCjxfbUok2t+NXpHywZIQTYnJpLimVzgv/7yPw5mFNjMRcbnZwtdxSVzSPogQL5lPtCmRO3Uh6sBsMbMudR0/HP6B3xN/p7SylFD3UG7vdDvjoscR7R1tdERxHrTWI2rbppQ6ppQKqe69EwJknONYx5VSq4AxwN8KPNbsWNExZvw2Ay8nL94a/pbMHSXEhalTr0Dgv8DDgMfZDmYLvQKbAns7E2M6BbNkm/UP0zqcWcimhFweGdNOelgK0QRN7BHGa7/sZ2FcMo9e2s7oOPVi5d4MsgrLuba39N5paqTAI0QttNbE58Tzw6EfWHpkKTmlOXg5eTGh9QQui76MbgHd5EbKNi0BbgZmVX/9/swGSqkAoKK6uOMCjAD+3agpG1iJuYSZK2dSZC5i3ph5BLjK5HlC1OZiewUqpcYBGVrrzUqpoWdra+29ApuSsZ1D+HKj9Q/TWrwlGZOCq3rY1vAPIWxFoKczw9sFsmhzMg+MaoODDcxXszAuiSBPJwbHyP1hUyMFHiHOkFGc8f/t3Xl4FFX28PHvIQlJgLCENRAg7Pu+CK6sshhFNgFXHEd/iqLzzqCIjog64zY6jo6IOgyCikpkkU0QQRERlB3CvkbIAgHCEgIhJLnvH10wTegknaTT1Z2cz/P009VVt26drqq+XXXr1i0WH1zMggML2H96P0Flgrgl8hZub3Q7N9W5iaAA7bywhHsdiBGRh4DDwHAAEakNTDXGDAQigBlWPzxlgBhjzCK7AvY0Ywx/Xf1Xdqfs5v3e79MsvJndISnl0zzQKvAG4A4RGQiEABVF5HNjzL3FFLLif7dpLd7mv7dpZWUb5m5K4Oam1alZMcTucJRSuRjZpS7f7zzGD7uT/ba8uezomXRW7knmsR6NtHNlH6QVPEoB6Znp/HD4B+YfmM+vSb+SbbJpX709L3R7gX5R/agUXMnuEJWXGGNOAr1djE8EBlrD24AOXg7Naz7c9iHLfl/GXzr9hZsjb7Y7HKX8Xb6tAo0xE4AJAFYLnnFauVP8SsJtWmsOnCDpTDrP39bC7lCUUnm4pWl1alYMZtb6I35fwTNnUzzZBoZ30tuzfJFW8KhSyxjD1uNbmX9gPksPLeXcpXNElI/gj23+yB2N7qB+xfp2h6iU1/1w+Ac+2PIBdzS6gwdaPWB3OEqVBO60ClQ2GdDacZvWz/tO0LdlTbvDKbDZG+OpGBJInxb+F7tSpUlgQBmGdIzk41UHSU5Np0aYf7a4M8bw9YYjXNcgnKhq5e0OR7mgFTyq1Ek+n8yCAwuYv38+cWfjCA0MpW/9vtzR6A661OpCGdGmhqp0OnD6ABN+nkDrqq2Z2H2i9jGllAe40yowx/iVOJ60pbyge6OqVAoNYsn2JL+r4Dmbfoml248yvHOkX7Y+Uqq0GdYpkikrD/DN5gQeubmR3eEUyvq4U8SdPM/YXk3sDkXlQit4VKlwKesSK+NXMm/fPH5J/IVsk03HGh35Q+s/cGvUrZQP0hpoVbqlZqTy1I9PERIYwjs93yE4INjukJRSqtgFBZShb8uafLfjKBmZ2ZQN9J+LPEtik7iYmc3QjpF2h6KUckOj6hXoWK8yszfG8/BNDf3yQtrsjUcoXzaAAW38+zazkkwreFSJtu/UPubum8uig4s4ffE0NcrV4KHWD3Fn4zupV1EfL6sUQLbJ5vnVz5OQmsDUflOpVV7/tJVSpcfANrWYvTGeXw6coGez3J5i73vmbEqgYbXytK9b2e5QlFJuGtapLs/Ni2Vb/Bna+dlv93xGJou3JTGwTQTlymo1gq/SLaNKnLRLaSw5tIS5++YSeyKWwDKB9Krbizsb38n1ta8noIw2Y1bK2bTt0/jxyI+M7zKeTjU72R2OUkp51Q2NqxEWHMjS2KN+U8FzJOU86w6lMO7Wpn7ZCkCp0iq6XQQvLdzB1xuP+F0Fz3c7jpKWkcWwTtpq0JdpBY8qES53mDx331yWxi3lQuYFGlduzDNdniG6YTRVQqrYHaJSPum3pN/49+Z/MyBqAPe0uMfucJRSyuuCAwPo3aIG3+08yt+yWhPkB4/9/WZzAgB3dqhjcyTK20RkODAJaAF0NcZsyCVdf+BdIABHh+6vey1IlauKIUH0b12LhVuTeCG6JcGB/nPhec7GBOqGh9IlKtzuUFQetIJH+bXT6adZeHAhc/fNZf/p/YQGhjKwwUAGNxlM22pt9aqWUnk4fv44z6x6hqiKUUy6fpL+XpRSpVb/1hF8syWR3w6mcGOTanaHkydjDHM3J9CtYTiRVcrZHY7yvu3AEOCj3BKISAAwGegLxAPrRWSBMWand0JUeRnaMZL5WxL5cXcy/VtH2B2OWxJPX+CXAyd4slcTypTR40VfphU8yu8YY9hwbANz9s3h+7jvycjOoE21NkzqPon+Dfprh8lKuSEzO5OnVz3NhcwLTOs3jXJBepLgDy5dukR8fDzp6el2h1IihISEEBkZSVBQkN2hKJv1aFadcmUDWLI9yecreDYfOc2hE2k8dot/PoVHFY0xZheQ30WZrsB+Y8xBK+1XwCBAK3h8wA2Nq1EjLJjZGxP8poJn3uYEjEE7dfcDWsGj/Mbp9NPMPzCf2XtnE3c2jrCgMIY0GcKwpsNoFt7M7vCU8isfbPmAjcc28uqNr9Kosp4k+Iv4+HjCwsKIiorSFldFZIzh5MmTxMfH06BBA7vDUTYLCQqgZ7MafLfjGC8Pak2AD1+h/mZzAsGBZfQpNiovdYAjTp/jgetcJRSRR4BHAOrV0weQeENAGWFwhzr8d/UhTp67SNUKvv3kUmMMczfF0zUqnHpV9YKgr9MKHuXTjDFsSt7E13u/vtJap131drxywyv0i+pHaGCo3SEq5Xd+TfqVqbFTubPxndze6Ha7w1EFkJ6erpU7HiIiVK1alePHj9sdivIR/VvXYnFsEhviUriuYVW7w3EpIzObhVsT6duyJmEh2vKspBKR5YCrGrznjTHz3cnCxTjjKqEx5mPgY4DOnTu7TKM8b0jHSD5adZCFWxMZfYNvX2TYFn+GA8fTePimhnaHotygFTzKJ53NOMvCAwv5es/XHDhzgApBFRjadCjDmg6jaZWmdoenlN86eeEkE36eQINKDZjQdYLd4ahC0Modz9F1qZz1bF6D4MAyLNl+1GcreH7ae5xT5y8xpKN2rlySGWP6FDGLeKCu0+dIILGIeSoPalYrjFa1KzJnU4LPV/DM3RRP2cAyDGzrH7eTlXZawaN8yo4TO5i1ZxZLDi0hPSud1lVb8/L1L9Mvqp/2EaJUERlj+OsvfyU1I5WP+n6kvymllHJSITiQm5tWZ+n2o0yMbumTHYl+szmBquXLclOT6naHonzbeqCJiDQAEoCRwN32hqRyGtoxkpcX7WTfsVSa1AyzOxyXMjKzWbA1kVtb1qSithr0C77/HEhV4l3IvMC8ffMYtWgUIxePZGncUm5reBtfRX/Fl9FfMrjJYD0RVcoDvtj9BasTVjOu8zhtCae8Yvr06SQm6kVj5T8GtK7F0bPpbD5y2u5QrnHmwiW+33WM29vV9otHuaviISKDRSQe6A4sFpHvrPG1ReRbAGNMJvAE8B2wC4gxxuywK2bl2h3taxNQRpi7OcHuUHK1ck+ythr0M9qCR9km7kwcMXtjmL9/PmczztKoUiMmdJ3A7Y1uJ6ysb9ZiK+Wv9qTs4e0Nb9Mjsgcjmo2wOxxVSkyfPp3WrVtTu3Ztu0NRyi19WtYkKEBYEptEp/pV7A7nKktik8jIzGZwBz3RKs2MMfOAeS7GJwIDnT5/C3zrxdBUAVWrEMwtTavzzeYExt3azCc7d5+7KYFqFbTVoD/RCh7lVVnZWfwU/xNf7f6KtUlrCZRAetfvzchmI+lUs5P2h6BUMbiYdZFnf36WSsGVeOmGl/R3VkK8tHAHOxPPejTPlrUr8uLtrfJMk5aWxl133UV8fDxZWVm88MILNG7cmD//+c+cO3eOatWqMX36dH755Rc2bNjAPffcQ2hoKGvXrmXNmjWMGzeOzMxMunTpwpQpUwgODubZZ59lwYIFBAYGcuutt/LWW2+xcOFC/va3v5GRkUHVqlWZOXMmNWvW9Oj3VSqniiFB3NSkOku2H+X521r4VHk5d3MCDauXp21kJbtDUUp5yJCOdXjii2R+PXiSGxpXszucq5w+n8GK3ce4r1uUthr0I1rBo7wiJT2FufvmErMnhqS0JGqUq8Hj7R9nWNNhVAv1rcJMqZLm3U3vsv/0fqb0mUJ4SLjd4Sg/t3TpUmrXrs3ixYsBOHPmDAMGDGD+/PlUr16dWbNm8fzzzzNt2jTef/993nrrLTp37kx6ejqjR49mxYoVNG3alPvvv58pU6Zw//33M2/ePHbv3o2IcPr0aQBuvPFGfv31V0SEqVOn8uabb/L222/b+M1VaTGwTQQ/7E5ma/wZ2tetbHc4ABxJOc+6Qyk83a+ZT1U6KaWKpk+LmoSFBDJnU7zPVfAs3JbEpSzD0E7aatCfaAWPKlaxx2P5cveXLI1byqXsS1xX6zqe6fIMPer2ILCM7n5KFbdfk37ls52fMbLZSG6sc6Pd4SgPyq+lTXFp06YN48aNY/z48URHR1OlShW2b99O3759AcjKyiIi4tonbezZs4cGDRrQtKmj/6cHHniAyZMn88QTTxASEsIf//hHbrvtNqKjowGIj49nxIgRJCUlkZGRQYMGvv2UEVVy9G3huE3r29gkn6ng+cbqo2NQe73dUamSJCQogOi2EczfksgrgzIpH+w750dzN8XTvFYYLSMq2h2KKgBta6U87mLWRRYcWMCoRaO4+9u7WXF4BUObDGX+oPlM7TeVPvX7aOWOUl6QmpHKC7+8QFTFKP7c+c92h6NKiKZNm7Jx40batGnDhAkTmDNnDq1atWLLli1s2bKF2NhYli1bds18xhiX+QUGBrJu3TqGDh3KN998Q//+/QEYO3YsTzzxBLGxsXz00Uekp6cX6/dS6rJK5YK4oXE1Fm9LynW/9SZjDHM3J9CtYTiRVfShE0qVNEM6RnI+I4ul24/aHcoVB4+fY/Ph0wzpWEdbDfoZPctWHnM07Sgxe2KYs28OKekpNKjUgAldJ3BHozuoULaC3eEp5RYRCQdmAVFAHHCXMeZULmkDgA1AgjEm2lsxuuuNdW+QfD6Zzwd8TmhgqN3hqBIiMTGR8PBw7r33XipUqMDHH3/M8ePHWbt2Ld27d+fSpUvs3buXVq1aERYWRmpqKgDNmzcnLi6O/fv307hxYz777DNuueUWzp07x/nz5xk4cCDdunWjcePGgOPWrzp1HM3CZ8yYYdv3VaXTwDYRPLNnG9viz9DO5lY8W46c5tCJNB67pZGtcSilikfn+lWoX7UcszfGM7RTpN3hADBvcwJlBAa119uz/I1W8KgiMcawOXkzX+z+guW/LyfbZHNL3VsY1XwU3SO6a42v8kfPAiuMMa+LyLPW5/G5pH0Kx+NHfa7t6o+Hf2T+gfk83OZh2lRvY3c4qgSJjY3l6aefpkyZMgQFBTFlyhQCAwN58sknOXPmDJmZmfzpT3+iVatWjB49mkcfffRKJ8uffPIJw4cPv9LJ8qOPPkpKSgqDBg0iPT0dYwzvvPMOAJMmTWL48OHUqVOHbt26cejQIZu/uSpN+rWsxfMBsSyOTbK9gmfupgSCA8swoE0tW+NQShUPEWFIh0jeWb6X+FPnbW+pl51tmLMxnhubVKdmxRBbY1EFpxU8qlAuZl1kyaElfLHrC3al7CKsbBj3tbyPEc1GEBnmGzXPShXSIKCHNTwDWImLCh4RiQRuA/4O+NT9T2cunuGltS/RtEpTHmv3mN3hqBKmX79+9OvX75rxq1atumbc0KFDGTp06JXPvXv3ZvPmzVeliYiIYN26ddfMO2jQIAYNGuSBiJUquErlgri5SXUWbk3k2f7NKWPT44vTL2WxYGsi/VrVIiwkyJYYlFLFb0jHOryzfC/zNiUwtncTW2NZc+AkiWfSmTCwha1xqMLRCh5VIMfSjjFrzyxm753NqYunaFy5MRO7T+S2BrdRLkjvC1clQk1jTBKAMSZJRGrkku5fwDNAWF6ZicgjwCMA9erV82CYuXt93eucuXiGD/t+SFCAnhAopVRh3N6uNit2J7Px8Cm6RNnzBMIVu5I5c+ESwzvrxTOlSrK64eXo1jCcOZvieaJXY1vvgpi98QgVQwLp27KmbTGowtMKHuWWrce3MnPnTL7//XuyTBY96vbgnhb30LVWV70NS/kdEVkOuGrr/ryb80cDycaYjSLSI6+0xpiPgY8BOnfuXOy9da48spJFBxfxWLvHaB7evLgXp5RSJVbfljUJCSrDwq2JtlXwfL3xCBGVQri+kW89Plkp5XlDO0by9OxtbPjdvkrls+mXWLL9KMM7RxISFGBLDKpotIJH5epS1iWW/b6MmbtmEnsilrCgMO5ucTejmo/S27CUXzPG9MltmogcE5EIq/VOBJDsItkNwB0iMhAIASqKyOfGmHuLKWS3nM04y8trX6ZplaY83OZhO0NRSim/Vz44kN7Na/JtbBITo1sSGODdh88eO5vOqr3HeaxHIwJsukVMKeU9A9tEMGnBDmLWH7GtgmfxtiQuZmYzrFNdW5avik4fk66ucSr9FP/Z9h/6z+nPsz8/S2pGKs9d9xzLhy/n6S5Pa+WOKukWAA9Yww8A83MmMMZMMMZEGmOigJHAD3ZX7gC8veFtUtJTeOWGV/TWLKWU8oDb20Vw4lwGaw+e9Pqy521OINs4ruorpUq+8sGBRLetzaJtSaSmX7Ilhq83HKFJjQq0i6xky/JV0WkFj7pi/6n9TFozib6z+/Le5vdoVLkRk3tPZv6d8xnVfJT2saNKi9eBviKyD+hrfUZEaovIt7ZGloffkn5j7r653N/qflpWbWl3OEopi4iEi8j3IrLPeq+SS7rKIjJbRHaLyC4R6e7tWNW1ejSrQVhwIPM2J3h1ucYYYjYcoVP9KjSsXsGry1ZK2eeuLnW5cCmLRduSvL7svcdS2XT4NHd1rqtdcPgxvUWrlMs22fyS8Auf7fyMtUlrCQ4IJrphNPe2uJfGVRrbHZ5SXmeMOQn0djE+ERjoYvxKHE/ass2FzAtMWjOJemH1GNNujJ2hKKWu9Sywwhjzuog8a32+5sl8wLvAUmPMMBEpC+hVFR8QEhTAbW0jWLA1kVcGZVI+2DuHzusOpXDweBpvDmvkleUppXxDx3qVaVKjArPWH2FUV+88nOOyL9cdpmxAGYZ20laD/kxb8JRSFzIvELMnhjvn38mYFWM4cPoAT3Z4kuXDljPp+klauaOUH5mydQrx5+J5sfuLhASG2B2OUgU2ceJEli9fXuD5Vq5cSXR0dDFE5FGDgBnW8AzgzpwJRKQicDPwXwBjTIYx5rSX4lP5GNIxkvMZWSzdftRry/xq/RHCggOJbhvhtWUqpewnIozoUpctR06z91iq15abfimLuZsSuLVVTcLLl/XacpXn+UUFTwGaN08TkWQR2V6Y+UuDY2nHeHfTu/Sd3ZdXfn2FcoHleP2m11k6bCkPt32YyiGV7Q5RKVUAe1L28OmOTxnceDBdI7raHY5SuTLGkJ2d7XLayy+/TJ8+ufZ97jGZmZnFvgwXahpjkgCs9xou0jQEjgOfiMhmEZkqIuVdZSYij4jIBhHZcPz48eKLWl3RJaoK9cLLMXdzvFeWd/p8Botjk7izQx3KldXG9kqVNoM71CEoQPjit8NeW+bS7Uc5c+GS11sNKc/zl38Nd5s3TwfeBz4t5Pwl1o6TO/hs52d8d+g7ssmmV91e3NfyPjrU6KD3WCrlp7Kys3hp7UtUCq7EXzr/xe5wlLcteRaOxno2z1ptYMDreSYZP3489evXZ8wYx+2AkyZNIiwsjOzsbGJiYrh48SKDBw/mpZdeIi4ujgEDBtCzZ0/Wrl3LN998w4svvsiGDRsQEf7whz/w//7f/2P06NFER0czbNgw1q9fz1NPPUVaWhrBwcGsWLGCoKAgHnvsMTZs2EBgYCD//Oc/6dmz51VxpaSk8Ic//IGDBw9Srlw5Pv74Y9q2bcukSZNITEwkLi6OatWq8cUXX3h2nQEishyo5WLS825mEQh0BMYaY34TkXdxHKu8kDOhMeZj4GOAzp07m8JFrApCRBjSsQ7vrthH4ukL1K4cWqzLm7spgYzMbD3RUqqUqlohmIFtIpizMZ5n+jfzSkXvl+sOU79qObo3rFrsy1LFyy9a8OBG82YAY8wqIKWw85c0WdlZ/HD4B0YvHc3IRSP58fCPjGw+ksWDF/NOz3foWLOjVu4o5cdi9sYQeyKWZ7o8Q6VgfdqB8o6RI0cya9asK59jYmKoXr06+/btY926dWzZsoWNGzeyatUqAPbs2cP999/P5s2bOXHiBAkJCWzfvp3Y2FgefPDBq/LOyMhgxIgRvPvuu2zdupXly5cTGhrK5MmTAYiNjeXLL7/kgQceID09/ap5X3zxRTp06MC2bdt49dVXuf/++69M27hxI/Pnzy+Wyh0AY0wfY0xrF6/5wDERiQCw3pNdZBEPxBtjfrM+z8ZR4aN8xJAOkRhDsXe2bIzhq/WHaRdZiZa1KxbrspRSvuu+bvVJvZjJN5sTi31Z+46l8tuhFEZ0qUuZMnpu6O/8pQXPVc2bRcRV82aPzC8ijwCPANSr559XTs5fOs/8A/P5fOfnHE49TET5CMZ1HseQJkMIKxtmd3hKKQ84ceEE7216j24R3RjY4Jq+n1VpkE9Lm+LSoUMHkpOTSUxM5Pjx41SpUoVt27axbNkyOnToAMC5c+fYt28f9erVo379+nTr1g2Ahg0bcvDgQcaOHcttt93GrbfeelXee/bsISIigi5dugBQsaLjBHf16tWMHTsWgObNm1O/fn327t171byrV69mzpw5APTq1YuTJ09y5swZAO644w5CQ4u31UUeFgAP4Hgi3wPA/JwJjDFHReSIiDQzxuzB0dH7Tu+GqfJSr2o5ujUM56v1h3nslkbFdhK09sBJ9h47x5tD2xZL/kop/9CpfhVaRFTk07VxjOpavE+1mr4mjuDAMozs4p/nvupqPlPB44HmzR7hz02fk88n88WuL/h679eczThLm2pt+EeHf9Cnfh8Cy/jMplZKecCb698kIyuDv3b7q7bEU143bNgwZs+ezdGjRxk5ciRxcXFMmDCB//u//7sqXVxcHOXL/68rmSpVqrB161a+++47Jk+eTExMDNOmTbsy3Rjjcn82Jv+/Y1dpLuflHIMNXgdiROQh4DAwHEBEagNTjTGXa2jHAjOtJ2gdBB50lZmyzz3X1Wfsl5v5ad9xejYr6LVG90z7JY7w8mW5o33tYslfKeUfRIT7utXnuXmxbDp8ik71w4tlOWfOX2LupgTubF9HO1cuIXzmFi0PNG/OS1Hn92m7U3bz3M/P0W9OPz7Z8QnXRVzHpwM+ZebAmfRv0F8rd5QqYdYmrmXJoSU81OYh6lesb3c4qhQaOXIkX331FbNnz2bYsGH069ePadOmce7cOQASEhJITr72r/bEiRNkZ2czdOhQXnnlFTZt2nTV9ObNm5OYmMj69esBSE1NJTMzk5tvvpmZM2cCsHfvXg4fPkyzZs2umtc5zcqVK6lWrdqVFkB2MsacNMb0NsY0sd5TrPGJTpU7GGO2GGM6G2PaGmPuNMacsi9q5Uq/VrWoViGYmb/+Xiz5/34yjRW7j3F313qEBAUUyzKUUv5jUPvahIUEMu2XuGJbRsyGI1y4lMUD10cV2zKUd/nLmX++zZuLeX6fk22yWZ2wmk93fMpvR3+jXGA5RjYbyd0t7qZuWF27w1NKFZOMrAxe/e1V6oXV46E2D9kdjiqlWrVqRWpqKnXq1CEiIoKIiAh27dpF9+7dAahQoQKff/45AQFXn6QmJCTw4IMPXnma1muvvXbV9LJlyzJr1izGjh3LhQsXCA0NZfny5YwZM4ZHH32UNm3aEBgYyPTp0wkODr5q3kmTJvHggw/Stm1bypUrx4wZM1DKk8oGlmFEl0imrDxAwukL1PFwZ8ufrv2dABHu664V90opKB8cyN3X1eM/qw5y+OR56lUt59H8s7INM9bGcV2DcO3zqwQRd5o9201EqgIxQD2s5s3GmJSczZtF5EugB1ANOAa8aIz5b27z57fczp07mw0bNhTHVyq09Mx0Fh1cxKc7P+XQmUPUKFeDe1vcy9CmQ6lYVn+YqnQSkY3GmM52x5EfT5QpU2On8u6md/mg9wfcFHmThyJT/mLXrl20aNHC7jBKFFfrtDSVKapg4k+d56Y3f+TxHo0Z169Z/jO4KTX9Ete/9gM9m9fgvVEdPJav8g1apqjCOnY2nRvf+IGRXerxyp2tPZr3wq2JjP1yMx/e25H+rSM8mrcqfrmVK37RgscYcxJHh4M5xycCzs2bRxVkfn9y8sJJZu2Zxaw9s0hJT6FFeAteu+k1+kX1I6hMkN3hKaW84GjaUT7e9jG96vbSyh2llLJBZJVy9G5eky/WHWZMz0Yee3zxp2t/J/ViJg/f1NAj+SmlSoaaFUMY3KEOMRuO8Kc+TahaITj/mdyQnW14/4f9NK5RgVtbuuoGV/krn+mDR7l28PRBJq2ZxK2zb2XK1im0rdaWaf2mMSt6FtENo7VyR6lS5B/r/0G2yeaZrs/YHYpSSpVaj/VoSEpaBl+uO+KR/M5dzOQ/Px+kV/MatIms5JE8lVIlxyM3N+RiZjYz1sR5LM/vdx1jz7FUnujZWB+NXsL4RQue0sYYw/qj65mxcwar4lcRHBDMoMaDuLflvTSspFd2lCqN1iWtY9nvyxjTfgx1KtSxOxyllCq1OtUP57oG4Xy86gD3dqtHcGDROkT+bO3vnD5/ibG9GnsoQqVUSdK4Rhj9WtXkk1/iGH1DgyI/7coYR+ud+lXLEd1Wb80qabQFjw+5lH2JhQcWMmLRCB5a9hDbT2xnTPsxLBu2jIndJ2rljlKlVGZ2Jq+te406FerwYCt9crJSStntiV6NOXb2InM3JRQpn/MZjtY7NzetTod6VTwUnSrJRGS4iOwQkWwRybVfHxGJE5FYEdkiItqxjp8bd2sz0jIymfzj/iLntWJXMrEJZ3i8R2MCA7Q6oKTRFjw+4GzGWebsncPMXTM5dv4YDSs1ZFL3SUQ3iiY4wDP3WSql/FfMnhj2n97Pv3r8i5DAELvDUUqpUu/GxtVoG1mJD1buZ0jHOoVuxfPhygOkpGXwVO8mHo5QlWDbgSHAR26k7WmMOVHM8SgvaFIzjOGd6vLZ2t8ZfX0UdcML90StjMxs/v7tLhpWL8/gjtoivCTSKjsbJZxL4I11b9D36778c+M/iaoYxeTek5k3aB5Dmw7Vyh2lFKfST/H+lvfpFtGNXvV62R2OUkopQET4y63NOJJygf+uPlSoPH4/mcaHqw4yqH1tOtXX1jvKPcaYXcaYPXbHobzvT32bIAJvLyv85p++5hCHTqQxMbolQdp6p0TSrWqD2OOx/GXlXxg4dyBf7f6KXvV6ERMdw9R+U7k58mbKiG4WpZTD5C2TOX/pPOO7jEdEO8FTvikxMZFhw4YVeL6BAwdy+vTpPNNMnDiR5cuXFzIypYrPLU2rc2vLmvx7xX4ST18o8PwvL9xJUBnhuYEtiiE6pTDAMhHZKCKP5JZIRB4RkQ0isuH48eNeDE8VVESlUP54UwO+2ZLIqr0F31bJqem8t2I/vZvXoEezGsUQofIFeouWl2RlZ7HyyEpm7JzB5uTNhAWF8UDLB7i7xd3UKq+PplNKXWvfqX18vfdr7mp6F42raOebynfVrl2b2bNnXzM+MzOTwMDcDzW+/fbbfPN++eWXixSbUsXpheiW9PnnT/z9211Mvruj2/Mt3Z7Eit3JTBjQnJoV9dZbdTURWQ64OkF43hgz381sbjDGJIpIDeB7EdltjFmVM5Ex5mPgY4DOnTubQgetvGJsryZ8t+MY4+dsY+mfbqZSqHtPVDbG8Nzc7VzMzOL527RSuSTTCp5idv7SeeYfmM9nOz/jSOoRapevzTNdnmFIkyGUDypvd3hKKR9ljOEf6/9BhaAKPN7+cbvDUT7ojXVvsDtlt0fzbB7enPFdx+eZZvz48dSvX58xY8YAMGnSJMLCwvjkk0/Yvn0706dPZ/HixaSnp5OWlsaiRYsYPXo0u3fvpkWLFsTFxTF58mQ6d+5MVFQUGzZs4Ny5cwwYMIAbb7yRNWvWUKdOHebPn09oaCijR48mOjqaYcOGsX79ep566inS0tIIDg5mxYoVnDx5kvvuu4+0tDQA3n//fa6//nqPrhelclM3vBxjejTmneV76dMinsEdIvOd59CJNJ7+ehtt6lTiwRsaeCFK5W+MMX08kEei9Z4sIvOArsA1FTzKv4QEBfD28HYMmbKGlxfu5O272rk139SfD7F81zEmRrekYfUKxRylspPeC1RMks8n896m9+g7uy+v/vYqVYKr8NYtb7F4yGLua3mfVu4o5aNEJFxEvheRfda7y44RivvpFD8n/MzapLWMaT+GyiGVPZ29UoU2cuRIZs2adeVzTEwMXbp0uSrN2rVrmTFjBj/88AMffPABVapUYdu2bbzwwgts3LjRZb779u3j8ccfZ8eOHVSuXJk5c+ZcNT0jI4MRI0bw7rvvsnXrVpYvX05oaCg1atTg+++/Z9OmTcyaNYsnn3zS819aqTyM6dmIbg3DGT8nli1HTueZNu1iJo9+tpHAAGHKvR0pG6iH4srzRKS8iIRdHgZuxdE5syoB2tWtzJgejZizKZ4PfzqQb/oNcSm8sXQ3/VvV4sEbooo/QGUrbcHjYXtS9vDpzk/59tC3ZGVn0ateLx5o9QDtq7fX/jOU8g/PAiuMMa+LyLPW59yaNBTL0ykuZV/irQ1vEVUxirua3eXp7FUJkV9Lm+LSoUMHkpOTSUxM5Pjx41SpUoV69epdlaZv376Eh4cDsHr1ap566ikAWrduTdu2bV3m26BBA9q3bw9Ap06diIuLu2r6nj17iIiIuFKZVLFiRQDS0tJ44okn2LJlCwEBAezdu9dTX1UptwQFlOGDezoxaPJqHvl0A188fB2Na4Rdky4lLYMxMzeyLzmVGX/oSmSVwj0FR5VuIjIY+DdQHVgsIluMMf1EpDYw1RgzEKgJzLPOPQKBL4wxS20LWnncn/o05feT53l9yW7KlQ3g/u5RLtOt2nucxz7fSJ0qobw5vK2ej5YCWsHjAdkmm18SfmHGzhn8lvQboYGhDG86nPta3EfdinXtDk8pVTCDgB7W8AxgJblX8BSL2Xtnc+jMId7r+R5BZdy7t1opbxo2bBizZ8/m6NGjjBw58prp5cv/r5WqMe516RAc/L8nRwYEBHDhwtWd1hpjXB6YvvPOO9SsWZOtW7eSnZ1NSIj2Z6K8L7x8Wabe34VR//mV6H+vZmJ0K0Z1rYuIkJ1tWB+Xwl++3kpy6kXevqsdNzWpbnfIyk8ZY+YB81yMTwQGWsMHAffu3VF+KaCM8PZd7bhwKYuJ83ew9cgZxvdvRg2rT69zFzP5at1hXl+ym8Y1KjD9wa5UDNFjytJAK3iK6Pvfv+f9ze9z8MxBaoTW4KmOTzG86XAqBVfKdZ4ePXoAsHLlSu8E6aVlFscyPJmnN9e7t+P21PL8dX17WE1jTBKAMSbJ6pzQlctPpzDAR1YnhdewnlzxCHBNKwdXzmac5YMtH9C1Vld61O1RmPhtVblyZYB8n4xUHFztcwXZD4u6z9q5z+/Z43hkarNmzbwy/8iRI3n44Yc5ceIEP/30ExcvXsw132bNmhETE0PPnj3ZuXMnsbGxhYqxefPmJCYmsn79erp06UJqaiqhoaGcOXOGsmXLsm/fPtasWUNWVlah8i/tcv52/bgMt02zWmEsfeom/vL1Vp6bF8trS3bRqnZF4k6c5+jZdGpWDCbm/7rTvm7lQi/Dru3ivNzCxuDufMX5HYs79tLOk8cApXmdu/vdgwLK8P7dHfjX8n389+dDLNmeRPNaYVQKDWLdoRTSMrK4pWl13r+7A2G5VO54Yj17onwoCk8v09fzy49W8BTRqfRTBAcE89pNr9Gvfj+CArRmVClfl9fTKQqQTbE8neLw2cMEBwQzrvM4bUarfFarVq1ITU2lTp06REREXHM7lbNRo0bx97//nbZt29KhQwfatm1LpUq5XwTJTdmyZZk1axZjx47lwoULhIaGsnz5csaMGUN0dDTfffcdAwYMuKr1kFLeVqNiCDMe7MrCbYn8diiFHYlnaRtZiadbNaNPy5puP/FGKaXcERwYwPj+zRnRuS4frTrA4ZTzJJ1Jp3/rCO7pVo8OdSvr8WQpoxU8RTS0yVCGNx2uPxyl/EheT6cQkWMiEmG13okAknPJo1ieTtG6WmuWDF2it2Ypn+fcEicqKort2x39d44ePZrRo0dfmRYcHMznn39OSEgIBw4coHfv3tSvXx/gSsVQtWrVrswPMG7cuCvD06dPvzLcpUsXfv3116viaNKkCQsWLAAcLZBee+01j3w/pQqrTBlhUPs6DGpfx+5QlFKlRFS18rw2xHUfd6p00QqeIgooE2B3CEopz1oAPAC8br3Pz5nAeiJFGWNMqtPTKV72VABauaNKkgsXLnDjjTdy6dIljDFMmTKFsmXL2h2WUkoppVSJoxU8Sil1tdeBGBF5CDgMDAfQp1MoVTgVKlRgw4YNdoehlFJKKVXiaQWPUko5McacBHq7GK9Pp1A+IbenSamCc/cJX0oppZRS/qCM3QEopZRSyj0hISGcPHlSKyY8wBjDyZMn9bHqSimllCoxtAWPUkop5SciIyOJj4/n+PHjV40/evQoANnZ2YXKt6jzeztfTy0nJCSEyMjI4ghJKaWUUsrrtIJHKaWU8hNBQUE0aNDgmvGPPfYYACtXrixUvkWd39v52rUcpZRSSilfprdoKaWUUkoppZRSSvk5reBRSimllFJKKaWU8nNawaOUUkoppZRSSinl50SfxJE7ETkO/G53HEA14ITdQRSCxu1dpTnu+saY6p4IpjgVsEzx5e2psRWeL8fny7GBd+MriWWK3Xx9/3JFY/Yef4y7IDFrmVK8/HH/cUW/h+/wh+/gslzRCh4/ICIbjDGd7Y6joDRu79K4SxZfXi8aW+H5cny+HBv4fnwqb/64/TRm7/HHuP0x5pKqpGwL/R6+w5+/g96ipZRSSimllFJKKeXntIJHKaWUUkoppZRSys9pBY9/+NjuAApJ4/Yujbtk8eX1orEVni/H58uxge/Hp/Lmj9tPY/Yef4zbH2MuqUrKttDv4Tv89jtoHzxKKaWUUkoppZRSfk5b8CillFJKKaWUUkr5Oa3gUUoppZRSSimllPJzWsHjQ0QkTkRiRWSLiGxwMV1E5D0R2S8i20Skox1x5uRG3D1E5Iw1fYuITLQjzpxEpLKIzBaR3SKyS0S655juq+s7v7h9bn2LSDOneLaIyFkR+VOOND65vj1JROqKyI/WdtshIk+5SJPr9hOR/iKyx1pHz9oU39NOsW0XkSwRCbem5VkWFDG2EBFZJyJbrdhecpEm132oONedm7HdY8W0TUTWiEg7p2nFtt4KEJ8t+52bsdmyz6mic6dM8UXu7Je+SkQCRGSziCyyOxZ3+OtvWPI5FlPFI7//o7z+y3yFiEwTkWQR2Z7L9FyPZXyJG9/DH7aFO8e9frE9rmKM0ZePvIA4oFoe0wcCSwABugG/2R2zm3H3ABbZHaeLuGYAf7SGywKV/WR95xe3T65vp/gCgKNAfX9Y3x7+7hFAR2s4DNgLtHRn+1nr7QDQ0NruW3PO6434cqS/HfjB6XOeZUERYxOggjUcBPwGdHNnHyrudedmbNcDVazhAc77d3GutwLEZ8t+505sdu1z+vLI9i1QmeIrr4Lul770Av4MfOHq9+yLL3/9DZPPsZi+imWd5/t/lNt/mS+9gJuBjsD2XKb7xfGwG9/DH7aFO8flfrE9nF/agse/DAI+NQ6/ApVFJMLuoPyRiFTEUTD9F8AYk2GMOZ0jmc+tbzfj9nW9gQPGmN9zjPe59e1pxpgkY8wmazgV2AXUcXP2rsB+Y8xBY0wG8BWOdWZnfKOALz0ZQx6xGWPMOetjkPXK+ZSA3PahYl137sRmjFljjDllffwViPTU8j0RXx5sX3c5eG2fU0VXxDLPNkX8zdhGRCKB24CpdsdSkpWQYzF/VOzHQd5gjFkFpOSRxC+Oh934Hj7Pzf8ov9gezrSCx7cYYJmIbBSRR1xMrwMccfocj28cKOUXN0B3q6nzEhFp5c3gctEQOA58YjVlnioi5XOk8cX17U7c4Hvr29lIXJ+g+eL6LjYiEgV0wHFlOCdX28+r6yef+BCRckB/YI7TaHfKgqLEFCAiW4Bk4HtjTM7YcltHxb7u3IjN2UM4rgZdVqzrrQDx2bLfubvu7NjnlOfkV6b4mgL+pn3Fv4BngGyb4ygIf/wNu3sspjzL3f8jXz4GdkdJOh72m22Rx3+U320PreDxLTcYYzriaL7/uIjcnGO6uJjHF64o5Rf3Jhy347QD/g184+X4XAnE0axwijGmA5AG5LyX1xfXtztx++L6BkBEygJ3AF+7muxinN3ru1iISAUcJ6l/MsaczTE5t+3ntfWTT3yX3Q78YoxxvnqTX1lQJMaYLGNMexytX7qKSOucobuaLY/x3owNABHpiaOCZ7zT6GJdb27GZ9t+5+66w4Z9TnmGm2WKTynAfukTRCQaSDbGbLQ7lgLyx9+wO8diyvPc+T/y2WPgAigpx8N+sy3y+Y/yu+2hFTw+xBiTaL0nA/NwNEV0Fg/UdfocCSR6J7rc5Re3Mebs5abOxphvgSARqeb1QK8WD8Q7XZGbjePPOmcaX1vf+cbto+v7sgHAJmPMMRfTfHF9e5yIBOH4E5lpjJmbc3oe288r6ye/+Jxc0xLLjTLMI6ym8CtxtOZwlts68tq+lUdsiEhbHLdODDLGnHSaxyvrLa/47N7v8orNiW37nCq8ApQpPsmN/dJX3ADcISJxOG5d6SUin9sbUv789DfszjGk8rx8/498/BjYXSXieNhftoUb/1F+tz20gsdHiEh5EQm7PAzcCuTslXwBcL/Vm3c34IwxJsnLoV7FnbhFpJaIiDXcFcd+dzJnXt5kjDkKHBGRZtao3sDOHMl8bn27E7cvrm8nefWf4XPr29Os7fJfYJcx5p+5pMlt+60HmohIA6sl1Egc68yr8VnpKgG3APOdxrlThhUltuoiUtkaDgX6ALtzJMttHyrWdedObCJSD5gL3GeM2es0vljXWwHis2W/c3O72rLPqaJzt0zxNe7ul77EGDPBGBNpjInC8Tv9wRhzr81h5clff8NuHkMqz8v3/8jHj4HdVSKOh/1hW7j5H+V32yPQ7gDUFTWBedbvIBD4whizVEQeBTDGfAh8i6Mn7/3AeeBBm2J15k7cw4DHRCQTuACMNMb4QtO2scBM60/iIPCgH6xvyD9un1zf4ug/oy/wf07j/GF9e9INwH1ArDj6dgB4DqgH+W6/TBF5AvgOx5MkphljdtgQH8BgYJkxJs1pXpdlgQdjiwBmiEgAjoOEGGPMInf2IWNMca87d2KbCFQFPrDWUaYxpjPFv97cjc+u/c6d2MCefU4Vncsyxbqa68tc7pc2x1QS+fNv+JpjMZvjKfFy+y/3h2NgZyLyJY4nTFUTkXjgRRwdufvV8bAb38PntwXuHff6xfZwJr63npVSSimllFJKKaVUQegtWkoppZRSSimllFJ+Tit4lFJKKaWUUkoppfycVvAopZRSSimllFJK+Tmt4FFKKaWUUkoppZTyc1rBo5RSSimllFJKKeXntIJH+TQR6SEi1zyaNLfxHljenSLS0unzShHp7MZ8EZ6IR0Sqi4i/PCJUKb9W2HJERGqLyOxcpl0pM0TkOafxUSKy3c38/yQi9xc0Lhf5PCEiPv84T6V8lYiMFpHabqSbLiLD3B3vgbi0bFHKjxW1bHFjvkdd/dadywsRaS8iA52mTRKRcW7kLSLyg4hULGhcLvJaLiJVipqPuppW8Ch1tTuBlvklcuHPwH+KunBjzHEgSURuKGpeSqniYYxJNMa4c8D1XP5JriYigcAfgC8KHNi1pgFPeiAfpUqr0UC+J2E20LJFKf82mmIsW4wxHxpjPs0nWXtgYD5pXBkIbDXGnC3EvDl9BozxQD7KiVbwqCIRkfIislhEtorIdhEZYY3vJCI/ichGEflORCKs8StF5F8issZK39Ua39Uat9l6b1bAGKaJyHpr/kHW+NEiMldElorIPhF502meh0RkrxXPf0TkfRG5HrgD+IeIbBGRRlby4SKyzkp/Uy5hDAWWWnkHiMhbIhIrIttEZKw1Pk5EXhWRtSKyQUQ6WuvmgIg86pTXN8A97n5/pUoqu8oXEflWRNpaw5tFZKI1/IqI/DHHFbBQEfnK+q3PAkKt8a8DoVZZMtPKOsAqb3aIyDIRCXWx+F7AJmNMppVPY+sK11YR2SQijcTR8ugnEYmxyqXXReQeq5yKvVx2GWPOA3GX14NSpZn1u90tIjOs3+tsESlnTbumTBHHVfPOwEzrdxwqIhOtY43tIvKxiEgBlp9XufVGzuMMESln/ca3icgsEflNRDpr2aKUb/F22SIiNURkozXcTkSMiNSzPh+wyo4rrXGsGLaKyFrgcWtcWeBlYIQVwwgr+5ZWmXRQRHKrxL0HmO8Uz/3W994qIp9Z46aLyBQR+dHK6xZxnKvtEpHpTnktAEYVcJWr/Bhj9KWvQr9wVGz8x+lzJSAIWANUt8aNAKZZwysvpwduBrZbwxWBQGu4DzDHGu4BLHKx3CvjgVeBe63hysBeoDyO2vGDVkwhwO9AXRw15nFAuBXrz8D71vzTgWFOy1kJvG0NDwSWu4ilAbDR6fNjwByn7xNuvccBj1nD7wDbgDCgOpDsNH8dINbubasvfdn9srF8eRbHQVBFYD3wnTX+R6AZEOWU95+dlt8WyAQ6W5/POeUZZU1rb32OuVxu5Vj2S8BYp8+/AYOt4RCgnBX3aSACCAYSgJesNE8B/3Ka/3ngL3ZvS33py+6X9Rs0wA3W52nAODfKlM5OeYQ7DX8G3G4NT8fp2MEpzXRgmBvLuOY4w4rtI2u4tZYt+tKXb75sKlt24DhGeQLHcco9QH1grTV9EjDOGt4G3GIN/4P/Hb+Mxjr/cZpnjfXbrwacBIJcLPt3IMwabgXsAao5fw8r7q8AAQYBZ4E2OBqXbLxcXllp9wFV7d6OJekViFJFEwu8JSJv4DhR+llEWuM4GPneqoAOAJKc5vkSwBizSkQqikhlHBUdM0SkCY5CMqgAMdwK3CH/u280BKhnDa8wxpwBEJGdOAq/asBPxpgUa/zXQNM88p9rvW/EUYjnFAEcd/rcB/jQWFfJLi/HssB6jwUqGGNSgVQRSReRysaY00AyvtkkXClvs6t8+RnH7QeHgMVAX+tqXJQxZo+IRDmlvRl4z1rmNhHZlke+h4wxW6zhvMqTXQAiEgbUMcbMs/JPt8YDrDfGJFmfDwDLrPljgZ5O+SUDzfP5vkqVFkeMMb9Yw5/j+J0vJe8yxVlPEXkGR2VIOI6TrIVuLLdZPstwdZxxI/AugDFmu5YtSvk0b5cta4AbcByDvAr0x1GZ8rNzIhGpBFQ2xvxkjfoMGJBHvouNMReBiyKSDNQE4nOkCbfOX8DRMnC2MeYEXHPOs9AYY0QkFjhmjIm1YtqBo4zaYqW7fN5zMo+4VAFoBY8qEmPMXhHphOOq02sisgyYB+wwxnTPbTYXn18BfjTGDLZOnlYWIAwBhhpj9lw1UuQ64KLTqCwc+7zbTaotl/O4PH9OF3BUKjnHk/M75swrO0ds2U55h1h5KlWq2Vi+rMfRfPog8D2OSuGHcZw4ubPM3OQsj1zdRuFcnuRVVuUsP5zLFudySssTpf7HVfkg5F2mACAiIcAHOK66HxGRSVz935/n7Pksw9VxRkGOVbRsUcpe3i5bfgZuwnHhej4w3lpmzgdH5HVO4oqr86acMkWkjDEmO5/83TnnAS1LPE774FFFIo4e4M8bYz4H3gI64miqV11EultpgkSkldNsl/vRuBE4Y7WwqYSjKTA4mgwWxHfA2Mv3q4pIh3zSrwNuEZEq4uh0cKjTtFQcV/sLYi9XXy1bBjxq5Y2IhBcwv6aAW0/EUKoks6t8McZkAEeAu4BfcRxIjSPHlTHLKqw+s6zWRW2dpl0SkYK0RgTHFfbGVhxngXgRudPKP/jyff0FoOWJUv9T73LZgaPfh9XkXaY4HxNcPuE6ISIVcNx65a78yi1XVuMogxDH0z3bOE3TskUp3+LtsmUVcC+wz6poScFxMewX50TWnQFnrGMiuLqPz8Kc84DjezW0hlcAd4lIVSj4OY917lYLRzcWykO0gkcVVRtgnYhswXE/9t+sk6NhwBsishVHE7zrneY5JSJrgA+Bh6xxb+K4Qv8LjiaMBfEKjlsutomj49NX8kpsjEnA0ZzxN2A5sBM4Y03+CnhaHB2rNsoli5z5pQEHRKSxNWoqcNiKZytwdwG/T08ct4UoVdrZWb78jKNJ8XlrOBLXFTxTgArW7RPP4KhAvuxjHOXATBfz5WYJjibXl90HPGnlvwbHgVBB3ICjnFNKOSo5HrB+T+HAlHzKlOnAh1YZdBHH0zJjcTwMYb27C3Wj3HLlAxwnh9twXJ3fxv+OVbRsUcq3eLVsMcbEWYOrrPfVwGljzCkXyR8EJoujk2XnljI/4uhU2bmTZXcsxtFfF8aYHcDfgZ+s7/jPAuQD0An49XK3FsozxJiCtNpSqmhEZCWOTr822BxHBWPMOauVzTwcnZ7NK0J+g4FOxpi/eiC2VcCgXApppVQufKV8KSoRmQc8Y4zZV8R8OgB/Nsbc55nIlPJf1u2Zi4wxre2OxR0iEoCjg9N064LTCqCpddJY2Dy1bFHKw/ytbCkqcTwB8FNjTF8P5PUusMAYs6LokanLtA8eVVpNEpE+OJpFLsNRY15oxph5l5snFoWIVAf+qZU7SpVqz+LoELVIJ2E4+g56oejhKKVsUA740boVS3A8hbPQlTsWLVuUUkVijEkSkf+ISEXrds+i2K6VO56nLXiUUkoppZRSSiml/Jz2waOUUkoppZRSSinl57SCRymllFJKKaWUUsrPaQWPUkoppZRSSimllJ/TCh6llFJKKaWUUkopP6cVPEoppZRSSimllFJ+7v8D8bQvZpjXC+oAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(1, 4, figsize=(16, 4))\n", "\n", "explainer.plot_partial_effects_at_means(\n", " X = X_test, # Obtaining explanations for test data \n", " ax = axs,\n", " features = final_itexpr.labels,\n", " target = None,\n", " num_points = 100,\n", " share_y = False,\n", " show_err = False,\n", " show = False,\n", ")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can share the y axis and show errors hatchs:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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TF/HFr3yJdW+8QUN9A6+9+hrgxY+NqWybouIiIm3enfqFe+/Nju3b2bJlMwB/u+suDj/iiHT8OOnkU/j5jTex/p13AGgNtzJjpmf0e+cdd3Sag+qmNTBUzB/fSCkxuxgg58p/Rzc7Z9pIKfnL9r9RFa/hynmX9FvcaWdB0XyunvcpdsVruWfXQ728b+5bpluO1S0D0rQH74c6UPImg0cI8XfgKGCyEKIKuB7wAUgpfw+cC1wjhLCBOHChHAvfTgpFniClZyjouBJNE+msnnfffZevf/3raJqGz+fjd7/7HYZh8MUvfpFwOIxt23z5y19m8eLFXHrppVx99dWEQiFeeeUV/vrXv3Leeedh2zarVq3i6quvpqmpiTPOOINEIoGUkptvvhmAG264gfPOO4+ZM2dy0EEHsXXr1lH+jYwMtnSoNxuZ7K/AUJk8YxLbdaluiVNR6KesIMsdIEWPqPihUIxNesvg8VqNj/4p9Hvvvcf3vv0dNE1g+Hzc/KtfYhgG3/jq12htbcW2ba79wufZZ999ufhTn+LL132RUCjIU889y2//+Acu+eRFOLbDAStXcsWVV9HU1MR555xFIpFESslPf+Z5tnz3e9/nkxddyIwZM1i9ejXbtnXEj/YyLdVNq3+omD++STrJbiJFTlqkSwdhdfYEe77xVd4Jv88FM09nScmiQR12aek+nDj1KB7b/Qz7Fi/MXt7lmgg7jjRye+5tuSYBPZh+LaUkabsEfXpO3ycbeWWyPBysXLlSrlu3rl9jlcmyYqTJNFkeDYTwDGd1TYybk5uhmhxmMpD4kWmynA0NQYW/nIAeVCLPGCbk16ksCmDoYz8BVplD5p7Rih8KRS6xHJedvZzPRq0IdmMdey1cMIKzGh4MzYfG0M5ffLrWYxn7QBju+KFifu5Rv9POhJNhmhPNnda1JW1ahuhZqJlhtGRH16v6ZCM//OAm5hfuwZf3vGJI1yC2dPjZ5t9Sm6zje3t/hcmBim5jpB7EKZgy6PfIRrG/lJIuBs6TCgOUFvhy9h4TwWRZoVDkGCk9Zd60XSzbxXHHluHgeMJF0mg2E3diqXItJSaPReKmw66WODEzR46CCoVCMcL0VXIas3PbMWs0ceXQy2tVmZZC4ZHNYNkZcvtvmTI79nCly2077kWg8Zk55w/5BrMhdK6YezGulPyt6oGs1zHCSYBrDel9upLNaDnRh/dZrlACj0Kh6BeulNiOi+m42I6rTniGAYmkyWwhakfQo7UIs+cWtorRw3G9Llv1bUncXKQmKxQKxQjSWwctyzExnfHTQTAX5WbqfEeh8OhqsAxDL9ESVhwyhNgXGl9jc+Rjzp/1CSp6aXE+ECYHKjh9+vFsaP2At8PZO65pZm6FbcvtXs42Un6OSuBRKBQDI5XVY9kupu3iuCNnGjZRaLFaabXC6LHdiBx/4ShyR1vCYleLMmBWKBT5RW8xK2aPvxsLQ233LqUSeRQKy7FwsmTEWUMUeLSMNuYxO85DNY+zoGg+h1asGtJxu3J05WHMCE7jnqqHSGYRsTUrCuSu05UrJVYXQ+r2qojhRgk8CoVi0EgpsZ1UCZfjqmyGHNJmR2k2m1KZPLl3+FfkBsvxDJibo6YSOhUKxZhHyp4vMKSUSuDp6Rjq/EYxwYk72Tu9OkPpouVanVqj/7v2KaJ2jAtmnp5z709D6Fw8+yyarBYe2b0222RSIk/uyN4uffhvCiqBR6FQ5IT2duvJVLt1dbdr6MScBI1mEyJa28l8TjH2aI6Z7GqJ99qZRqFQKEab3sqz4k4sJ2LIWEMicYd4Z16d0ygmOtnKs1wph/S3kSmo7E7Us7b+RQ6dtIo5BTMHfczeWFA0n4PKV/Bk3fM0mS3d55PjrPlkhnjVzkhkfSuBR6FQ5BZVwpVTEq5JQ7IRGa1F69K5QDG2MG2X6paEyuZRKBRjlqTVs9ARy/Hd67GEKtNSKIZGIotYYQ0lewfZSeBZU/1v/JqPM6efNIRj9s0ZM04CJA/XPtl9o2sh7O4/52DJZrTcWwzOFUrgUSgUw0bXEi7HlXzve9/jqaeeGvCxnn32WU477bRhmOXYx5I29WYjTqwWLd402tNR9IKUMp3No7x5cs/3v/99FT8UiiHQU3mA7dpZ7zaPF1zp8oMbrmft2oHHj+eee5azzjxdlWmNAirmjw0s18Jxu8cO2x28WCGsWNpceWt0B++E3+PEqUdT4ise9DH7wyR/OUdOPoSXGt+gJlHXbXumJ9BQcaXE6uL3YzneNdFwYgzr0RUKxYRESq+duqZ1aMiuK3GRfPf6G9CFwHUlmpbb+tpMbNvGMMZPiHOkS32yiQrpEpAOTkHlaE9J0QteNk+c0pCP8gL/sH7WxxvZ4kc7P/zhD0dkDuMtfigU7fQkPI8X753e4sd3r/8+utAHfez+ZvCo+DEwVMwf+2Qrz4Kh+e9klkP9s+ZxioxCjq08dNDHGwinTD2GFxtf56Gax7h63qc7bRN2qqvXEGJFJkk3gU/3d1qXsBx8+vDl2agMHoVC0SPf+fa3+MPvf5d+/aMf/oBf3HwTN934cw49+CBWrljOD39wAwDbtm1jv6VL+OJ1X+CgA1exc+dOLv/cZ1mx/34csHx/fvXLXwBw+Wc/yz/+sQbLcXn5lVc5+OBD2G+//TjwwANpa2sjkUhw2WWXsXTpUpYvX84zzzzTbV5NTU2ceeaZLFu2jIMOOoj169cDcMMNN3DllVdywgkn8OlPf7rbfvmORNJoNhON1aBHa72cccWYJhy3qGqOE03aoz2VEeeb3/wmv/3tb9Ovb7jhBm688UZ+9rOfsWrVKpYtW8b1118PePFjn3324dprr2XFihXs3LmTSy+9lCVLlrB06VJuvvlmAC699FLWrFkDwBtvvMEhh6j4oVD0l/ZM2mzEx5jA8/3vfJc//eEP6df//aMf8+tf/JJf3nQzRx56GAevPJD/+uGPANi+bTsr91vOV774JQ4/6GCqdlZx9eVXsnrFSg46YBW/+dWvAbjic5/jvvvuA2Ddujc46ojDWHXACg475KB0/Lji8s9xwPL9Wb1qJc8+2zl+SAkNjY0qfvSAivnjl2zlWQDWYDN4XAuRMiDeEtnKe22bOWnKUQT14GCnOCCKfUWcMOUI3mp5l+2xqi5bZU6zeJJZyrQSw1ympaRKhSJP0J/4NtruDTk9pjt1Cc4JP+lx+3nnX8DXvvZVrrr6GgDuW7OGr339G7z88ku8+PIrSCk55+wzeeGF55k9ew6bN2/ij3/+M7/69W946603qa7exVtvvwNAS0tLp2ObpsnFF3+SO+/6GytXrqKtrQ1/IMCvf/UrAN59910++OADTjjhBDZv3txp3+uvv57ly5fz4IMP8vTTT/PpT3+at99+G4A333yTF198kVAolKPf0tgjbLViuzYlroNbNB2E0urHMrbrsrs1QWHAoKLQP6x3bXrk0W9B7bu5Pea0pXDy//S4+cILL+TLX/4y1157LQD33nsv3/rWt3jxxRd5/fXXkVJy+umn8/zzzzNnzhw2bdrEX//6V37729/y5ptvsmvXLjZs8GJetvhxwQUXcM8997Bq1SpaW1sJhUL88pe/BFT8UCiy0VP2TtJJYLs9i9CBJ7+HVpfj848pS0ge/6Met59z3rl862vf4IqrrgLggfvu5ytf+3+8+vLLPPviC0gpueCcc3nphReZNXs2WzZv5rd//AM3/+qX/Oett6iprua1t9YBXeOHi2maXJJx/tEeP37za+/8483/vM2mDz7g1FNPZsN7GzvNK2/ih4r5afLm32wMk+jBl6YnwbgvMr13Hqp5nBKjmCMrDxnUsQbLcVOOYG39izxSu5Zr5n+m2/xcf2lO3iebD89wl/ArgUehUPTI/suXU19XT3V1NQ319ZSVl7Fhw3qeeupJVq9aCUAkGuHDDz9k9uw5zNljD1avPgiAefPms3XrVr7y5S9x8sknc9zxJ3Q69uZNm5g2bRorV64CoLjYq7l94YUX+fwXvoDjSvbee2/22GOPbl/WL774Yvou3DHHHENjYyPhsNdl6vTTT58QX9RRJ4YT20WZayOLZ4KmwvlYJ5q0iZkO5QU+SkO+nLcAHWssX76curo6qqurqa+vp7y8nPXr1/PEE0+wfPlyACKRCFu2bGHOnDnsscceHHSQFz/mz5/Pxx9/zHXXXcepp57KCSd0jh+bNm1i+vTprFrlxY+SkhLAiw3XXXcdAIsWLVLxQ6HIoKcOWtEc3q3OFfvtvz/19fXUVFfT0NBAWVkZ723YwNNPreWw1HlGJBLlow8/ZNbs2cyZM4cDVx8IwNx589i6dStf+8pXOfHkkzj2uOPSx3Wl7Hb+0R4/Xn7pJa75/OcB2HvRIubMmcOWLvHjpRdf4v77VfzIhor54xPbtXsUgO1BlWh1mCtvjnzM5shHXDDzDAKav4/9cktID3JM5WE8XPskVfEaZoWmd2x0bYSdQBpDzyhypYvlmJ3KtNqzKfVhKt9XVwQKRZ7gnPATRsOy9ayzz+aB+++jtraW88+/gO3bt/H1b3yTK664stO4bdu2UVhQmH5dXl7OG+ve4sknnuD3v/sda9as4Y9/+nN6u5Qy6wWuTLVctFMGZDLVlSuzK1G2DkXtxyosLOy2bbyScE0a4tVUSAdRPAv0kf1yVAwcKSVNUZO2hM2kIj8F/hH6Gu7lrutwcu6557JmzRpqa2u58MIL2bZtG9/+9re5KnVXvp1t27Z1+tstLy/nnXfe4fHHH+f//u//uPfee7nlllvS23uLH32h4odiopLtrrEjHRJOvNf9esu0GU7OOOtMHnzgQepqaznn/PPYsX07X/361/jsFZd3Grd923YKusSPl994jbVPPsWffv8HHlhzH7/9o1fuJZG40h1S/OjqxTMm44eK+b2OGZP/ZmOUnrJ3XCkHlcEjrHjaXPnR2rUUG0UcPnn1kOY4WI6tPIwn657nkdq1XDnvkk7bNKsNJwcCD2T34YlbDkWB4TkHVHn9CoWiV84//wL+ce89PHD//Zx19jkcd/wJ3H7rX4lEvDt+u3btoq6uuwt9Q0MDruty1tlnc/0NP+Dt//yn0/a9Fy2ipqaGdeveAKCtrQ3btjns8MO5++9/B2DL5s3s2LmDPfdagJVqt+66kiOOOIK77roL8DolTJ48OX03Z6JhS4eGeA12+GPPGE6RF1iOS204QW04gdnDXfXxwIUXXsjdd9/NmjVrOPfccznxxBO55ZZb+h0/zjnnHH70ox/x1ltvddq+aNEiqqureeONzvEjMzZs3ryZHTt2sPfee3faV8UPxUTEdWXWWBO3o/26SB4Nzj3/PO77xz948IEHOfOsMzn2uOO44/bb0/Gjetcu6rPEj8ZU/DjjrDP57vXf551UOU47C/Ze2K/zj507d7KwS/w47PDDuetOFT96QsX88UdP/jv2oMuzvM/C9lgV77Vt5rjKw/FrvkHPbygUGgUcXXkIb7as79ZRS9iJtBA1VLJ1KIybw3fbXmXwDAApJY5ro6tSCMUEYt/Fi2lrizBj5gymT5/O9OnT2fTBBxx5+GEAFBUVcsutt6Prnd3mq3ft4sorLsdNGbD96Mc/7rTd7/dz511/46tf/hLxeIJQKMgjjz3BVVdfwxc+fy0HLN8fwzD405//QiAQAAkS78L429/9Hlde/jmWLVtGQUEBt91224j8LsYqLpLGZAMlzSYFpfOR/qLRnpKin8RMm7jlUBI0KCvwD1u67mixePFi2tramDlzZjp+bNy4kYMPPhiAoqIi7rzzzm7xY9euXVx22WXp+PGTn3T2CvP7/dxzzz1cd911xONxQqEQTz31FNdeey1XX301S5cuxTAMbr31Vi9+ZHDDDTdw2WWXqfihmFD0VJ41lrtn7bPvvkTaIsyYMYNp06czbfp0Nm3axHFHHg1AYVEhf7rllu7nH9XVXHvlVen4cf2POndiMnw6dwzk/COD737v+1x5hTr/6AkV88cf8R5uHg6qg5ZrI1Jix6O7nyGkBzmy8uChTG/IHF95BE/Xv8hju5/msj0uzNjimS3nwovHdJLdstCG04dHjFXVfqRYuXKlXLduXb/GJiyTN6o+RBMCXTPQhYFP86ELA0MzMDTfkNovKhRdie7ezsK9F432NMY2AnQh0IToVyvqjRs3ss8++3Q+hBBvSilXDvStBxI/2qItbPjo1YG+xYAp0IOUFO+JDJUP+3spcouuCcpCfkpCRk78ebJ91hVDY7Tih0IxVFpiJk1Rs9M600lSH9+ddXxRxGavhQtGYmqjgi4M9CE0KPAZGtoA4/Rwxw8V83PPRP+dWo7FrsiurNvaEjYtMTPrtp7QzDBaMkxNoo4bNv6ck6cew5kzTsrFVIfE3VUP8lzDq/z3vt+mPFPQ0Qzswhk5eY/JoSkEunQJm11RMKTGGz3FD1WiNQhcKbEci4Qdp81spSXZREO8jtroLmqiO6mP19KcbKTVDBOzo1iOOWbTXxWKvCfl0WM5LknbwXbcCf33FnMSNIY3IyM1qo16nuG4ksZokqrmOJEJ2FZdoVAMH9na8o7l7J3hxh1i6YU7yPIUhSKfiPfiz2U5Ay8v10yvPOvJuucwhMGxlYcNem655LjKI5BSsrb+hc4bUmbLuSBbu/T4MGXxqFqjHONKiemYmE53RdPL8jEwhA9D86msH4Ui10hw5PC50ucLlrRojGyl1EngK9lDtVHPMyzHpa41QYuhMakwQMivviMUCsXQSNqdLyRc6RIfaYFHuggpAderuUYCAgSAhhQajFB3QYnERaIxuPfrarSsUIxHejJYBnDkwASedk+bsNXKq01vctikAyn2jQ1LgcmBClaWL+P5hlc5ZdqxFOgdndU0K5ITs+WkEwc6l3slTIeSYO79h5TAM4J0tJnr/MeiCQ1D8+HTfJ2elfCjUCgGiyNdmmK7KLEThMr2An10DOwUg8e0XWrCcUJ+nfICP0Gf+k5QKBQDx7Tdbt1u4nZs5EQK6SKk00NWacpgD8cbIwRS6CNyY8KVDpoY3KWQlF4WT39KwxWKfKU3gcceYPJJu7ny0/Uv4UiX46YcMZSp5ZwTphzF681v83zDq5w09ej0emGnun4N8brcdExc6aJlxDaVwTOOcaWL6SQxu6RuKeFHoVAMlVazEbMxTknZ3gi/ageaj8RNh7gZp8BvUFbgU0KPQqEYEIksV2IxOzL8bywlQtoDKxdu30doKaFn+AQUV7pIIRGDzOJx5OAzgBSKsU7SSeL2kKUjkdgDKdGSDsKOk3CSPNfwCvuXLmZKYHKOZpob5hTMZJ/iBayte5HjKg/HSDdVkmhWFNc/9M5rSSdByChIv3ZcSdJ2CBi5Pa9TeftjmHbhJ2pFCCeb0z4/tbFdNCbqCCebiVnK40ehUPROwonR1LQeJ14/2lNRDIGYaVPdEmd3a2JYuy8oFIrxRdd4YfVgJZBLhHQQrjV4LzjppvYfuM/HQOjpArZf+7pSnX8rxi29lmcN0INKs2OA5OWmN4g5cU6YeuQQZzc8nDDlSMJ2K280v91pvWblppw1W7v0hJn7GKcyePIQx3VwXIeupV7tWT7ew+91+FIt3RUKBWBLh8aWzZRYUYLFe4yYz4Ei90STNtGkrTJ6FApFv0h2MViODnP2jnDtnAkzwrVB6EhteOKcVzKhDzoPx5Wgq69TxTikp/boMIjyLDOKK12eqnuB+YV7sGfh3KFNbpjYt3ghM4JTebL+eQ6qOKCjo6lrIZwEUh+aF082gSdm2ZSSWxsFlcEzjrBdi7gdo9UM05iopzZWTU20ivr4blqSTUStiMr2UQyZ6upqLrrg/AHvd8bpp9HS0tLrmB/ccD1r1z41yJkp+kIiCUerCDe9hzvMd28Vw097Rk9NOE7czI+Mnurqas4999wB73fKKaf0GT++//3v89RTKn4oFJm0d5lsZ7jNlXMp7qSRDsK1qamu5lMXfXLAu59zxpk9xg+JREp30OcfqptW76iYn584rtNrBo/l9v9vXDhJcE3eDr9Hg9nE8WPMeycTIQTHTTmCqngNmyIfddqmmUOPm7ZrY7lWp3UJy815HFHpHeOcnvx9fHpHlo9P8ytvH0W/mTFjBn+/595u623bxjB6DikP/fPhPo99/Q0/GNLcFP0jYbZgN7xDaflCDH9p3zsoxjTtHj0Bn05ZyEdhYOx+tc+YMYM1a9Z0W99X/HjkkUf6PPYPf/jDIc1NoRiPdC3PStjxYTNXHhZxpx3pMmPaFO74+9+6beorftz30IO9HtqRzqDPP1zplWkJlRWbFRXz85NElkyTTJwB+O+0lzc9Wfc8k/zlLC9dMqS5DTery5fzQPWjPFn3PIuK90qvF3YMKGeo+TFJJ45P68jYkVISt5ycnrupDJ4JiuVYxKwo4WRLN2+fVjNM3I6lOn4pJjLf+fa3+MPvf5d+/aMf/oBf3HwTK/bfD4Dbb7+NT154AWefeQannnISsViMiy+6kJUrlnPJJy/i8EMP5s031wGwcMGeNDQ0sG3bNvZbuoRrrr6K5fst49RTTiIe99JAL//cZ7n/vvsAWLfuDY464jBWHbCCww45iLa2NrZt28YxRx/JQQeu4qADV/HKKy+P8G9k/GC7SZoaNxBrqxrtqShyRNJy2N2aYGdTjNaE1fcOw8w3v/lNfvvb36Zf33DDDdx4440sWeKd3N16662cd955fOITn+CEE04gFotx/vnns2zZMi644AJWr17NunVe/Jg7d246fuyzzz5cccUVLF68mBNOOCEdPy699NL0hcQbb7zBIYccwn777ceBBx6Yjh+HH344K1asYMWKFbz8soofivFP0u5antU2LO+Ta3Hne9+9nj/98c/p1//9Xz/hV7/4JatXHADAXbffwac/eTHnn30OZ576CWKxGJ+5+BIOXnkgl17yKY4+/AjeevNNAJYsXERjQwPbt21n5X7Lue6aazlw+QGcceoniMfjSCSXf+6yQZ9/DNSPZLyiYv74obfyLAC73595ibBibIvu5KPoNo6tPLxTF6mxiE/zcfTkQ3i3dSM1id0ZW2ROvHiyZUbFcpyFPXZv841FXBujbSdoPqSmIzU/UjNAM5C6j3zXy9q9fRIZ3j6a0DoyfXR/elkx8tz45k/Z1Lwpp8fcu3xv/t8B3+hx+3nnX8DXvvZVrrr6GgDuW7OGX//f/3H7bbelx7z22qu88eZ/qKio4OabbqSsvJx1b/2H9zZs4MBVB2Q97ocfbuH2O+7kd7//AxdfdCEP3H8/n7z44vR20zS55OJPcuddf2PlylW0trYSCoWYMmUKjzz6OMFgkA+3bOHTn7qEl199LUe/jYmHRNIW2UbSaqWkbAG6+tseF1iOS0NbEttxsR0XXRP89I2f8kHTBzl9n0UVi/jmgd/scfuFF17Il7/8Za699loA7r33Xn7/+9/z17/+NT3mlVdeYf369VRUVPDzn/+c8vJy1q9fz4YNG9h///2zHnfLli38/e9/509/+hPnn38+9913H5dcckl6u2maXHDBBdxzzz2sWtU5fjz55JMEg0G2bNnCRRddlL6YUCjGK5kZPIM1V/7FWzexpXlzLyNk6tF/FpQt4Cv7f6nH7eeeezbf/Oa3ueLKywG4//4H+cUvb+LOO/7miUnA66+9xstvvE5FRQW/uvkXlJWV8cq613n/vfc49MCDsh73ow8/5Jbbb+XXv/stn7n4Eh564EEu/ORFyNT8B3P+MWLt5gfA/77+vyrmq5g/aPoSeCynf595YcUAl6fqnyeoBTh00qoczG74OXLywTy6+2nW1r3IJXPOSa/XzCiur3hIxzbdZPd26RNV4BFC3AKcBtRJKbvldgkvN/KXwClADLhUSvlW7mciwTURLgi6fPiFjtR8SM0HuoEUPk/4yePSJ1e6JJ2EZwqVuiGsCYGREnr8WiDdvl2lp44/9l++nPq6eqqrq2mor6esvIzZs+d0GnPMscdRUVEBwMsvvcTnr7sOgMVLlrB06bKsx507bx77pb7Il69Ywfbt2zpt37xpE9OmTWPlSu+LoKTEa00YjUb58pe+yPp33kHXdbZs6e2EU9FfzGQTTQ3vUFy6F8FA2WhPR5FDHFd6j1G4AFm+fDl1dXVUV1dTX19PeXk5c+Z0jh/HH398On68+OKLfOlL3gXfkiVLWLYse/yYN29e+kLggAMOYNu2bZ22b9q0ienTp7NqVff48YUvfIG3334bXdfZvFnFD8X4RkrZKYNneMyVBy7u9If99t+P+voGampqaKhvoKysjNmzZ6Xe0gXpcvQxx6Tjxysvv8w1n/88APsuXsySpdnLQPaYO5dl+3lZyPsvX86O7du9Q0rvpsdgzj+k9Lx4NG1inwermD8+MB0z1cynZ/qbtaaZEZrMFtY1r+fYysMIDdGkeKQo9hWxumIFrzS9yZkzTqLIKPQ2uCbCSSL1wKCPLaXs1i7ddt2ctkvPG4EHuBX4DXB7D9tPBhakHquB36WeRw7pIBwHkSGGAJ7wIwzQfUjN8DJ/dANEPv36O3ClTPv6RPFOFoQQGd27/PhTvj5K9MkdvWXaDCdnnX02D9x/H7W1tZx//gXdthcWFqaX+2vgHfB3BEZd19PptpnHyfbZ+dUvf8HUqVN44823cF2X0uLCbmMUg8N1EoSb3iNZNJuSotnqb3ec8f9WfB3wYrWueY+R4Nxzz2XNmjXU1tZy4YUXdts+qPgRGFz8uPnmm5k6dSrvvPMOrusSDObHiaZCMViStpv+u3KlS2yQ5spfXvHV7Bukm86mGQ7OPPN0HnzgIXbvruPcc8/u9t4FBR0XSLmIH57h8uDOPxwp0Qbdiyv39JZpM5yomJ//9JW947hu//7tXAvhJnmm/iUkkqMrD83RDEeGYysP58XG13m+4VVOmXZser1mRnBCgxd4ABJOvJPAA14WT64EnrypKZJSPg809TLkDOB26fEqUCaEmD4ys+sD6SDcJMKKoCVb0ON1GJFqjLYq9Ohu9EQTmtWGsBMg86MTSleklJiOSdSK0JJsoi5eS02sivp4rergleecf/4F/OPee3jg/vs56+xzeh17yKGHcl+qHnrj+++zYcO7g3rPvRctoqamhnXr3gCgra0N27ZpbQ0zbdp0NE3jrrvuxHHy8+9l7CJJRHbQ2PQuVi/dExT5i5QS23ExbQfb6edJ2hC48MILufvuu1mzZk2fnVQOO+ww7r3XM3B///33effdwcWPRYsWUV1dzRtvdI4f4XCY6dO9+HHHHXeo+KEY92SWZ8XsaG7/3qUcVnEH4Nxzz2HNmvt58MGHOPPMM7ptF8i078/BhxzCAykPnQ82buS9De8N+P2kdFk4yPMP15XqHBcV88cDfZdn9e84mhUl4SR5ofE1lpctZXKgIgezGzlmhqaxT/ECnql/uZMvrbBjQ75eT2T5HefShydvBJ5+MBPYmfG6KrWuG0KIK4UQ64QQ6+rr60dkctlxO4SfRHNK+NmFEdmFHqtDSzQjrIjXXo5h6kowjPQl+sSsqBJ98oB9Fy+mrS3CjJkzmD69d830qquvoaG+npUrlvPzn/+MpUuXUVoy8C5Nfr+fO+/6G1/98pdYdcAKTj35RBKJBFdddQ133nEHRxx2CFs2b+50J2ikGDvxY/hwzFaaGt8hEq9Tf5/jFCm9FGvTdrGc3LfobGfx4sW0tbUxc+bMPuPHtddeS319PcuWLeN///d/WbZsGaWlg4sf99xzD9dddx377bcfxx9/PIlEgmuvvZbbbruNgw46iM0qfigmAAkrozzLym15lpDD34hjn333IdIWYcaM6UybPi37PFwHkFx+1ZU0NDRw8MoDufnnN7Fk6RJKBhg/JGD49EGffwx3KWw+xA8V8/ObvtqjA9j9MlP3DIlfaVpHzIlzfOXhuZngCHNc5RGE7VbWtbyTsVai2bEhHbe9y3Umdj99jfqDyKeTdyHEXODhHjx4/g38REr5Yur1WuAbUso3ezvmypUrZX8NtxLJGP/Z9PyA550ztHZfH7/n9aMboPlgDKWEDobM8i6/FkiZOSuzV4Do7u0s3HvRaE+j3ziOg2VZBINBPvroI04+6QQ2vLcRv98/ovPwG1qPJUYbN25kn3326bROCPGmlHLlQN9nIPGjLdrCho9eHehbjDICPTSZ0pL56m8yDxlo/BDC81jTNTEqJXpd48exxx7L5s2bRzx+9MZoxQ+FYjBsb4ziuJ7fQ0O8bkD7FkVs9lq4IOu2YW2HPhiEwJZaOn58/NHHnH7yKby1Yf2A44dADPr7Tgjw91JiMdzxI9vxxzL5GvPHM21mG43xxl7HtMRM2hK9C7zCiiHidXx/488o0EN8e+F1eVn670qXGzbeiF/z8Z29v9TxM2g+7MKhFQoV+0so8ZelXxuaxpxJBT3vkIWe4kd+msBkpwqYnfF6FlA9SnMZHlwbgY1wMtO6RKqrl2fonI/+Pu2ZPqZjpj192o2c/Zpfde/KI2KxGCcefxyWZSGl5Ne//s2Y+qJWDBSJE6+n0WyjsGQ+RYHyvPyCVvQPKb070E7KLFQXYkRNQ2OxGEcffXQ6fvzud79T8UOhGCRJ20kboUasHLZGTxkcjymkJB5p5dSTT8OybKSU3PTrXw4qfkhktw43A5iGYgComD/2iFl9Z6b0x2BZsyKsb/2AumQDl8+9OG/PHTWhcdyUw7lz531siW5lYdF8b4NrIewE0hi8r1PcjnUSeHJJ/qgAffNP4AtCiLvxzJXDUsqaUZ7TCNDe1ctEZIqp7R290tk+vrzK9sk0cs7s3uXTAvj1DiNnXRtPH+H8p7i4WLUtH4cIJ0Gs+QOShVMpLZyNT1cnYOMd15W4SHBJCz3aMJ+gFRcXqxa2CkWOaC/Psl07q9/DoBgB353BUlxUyHMvvQCDEGa64khnUAKPYmComD+2cKVLwunbf9HqS+BxbYST4Mm65yn3lbKibGmOZjg6HFRxAA9UP8qTdc93CDx4IpYzBIHHdm0sxxyWc+q8uToWQvwdOAqYLISoAq4HfABSyt8Dj+C1SP8Qr036ZaMz0zFCZkevNNmyffKnjbubaiuXzPiZNKGlBJ9AOttHz5Ofp3+IHrsDKAZOPpWkjj1cnGgNjclWCor3oFhl8+QBOYgfGVk9XgcuT2yfiP/2Kn4o8olkygk1NoTW6F3jx0j47gwF4dpIzefVSg0BicTFRcuhVelIxQ91zpg7JlrMj9vxfv3MfXnFaFaU7bEqNkc+4twZp2Lk+XWZX/NxVOUhPFK7lrpkA1MCk4F2s2V7SFUzcSc+sQUeKeVFfWyXwOdHaDp5Sm/ZPv4s2T5jH1e6JOwECTpEH13T0xk+fj2AT/Pn7Z0YzeenubmJ8vIK9YU9RKSUNDY2qjaZQ0TYUeItm0iEplBaNJOArn6fY5Vcxw+vAxeATGf0aIIJEZtU/FDkGwnL65I3WHNlV4Nwcwul5WUIITwz4zy44BXSRoqhn8O6roum5ebccaTiRzAYpLGxkUmTJk2IuDycTMSY37/yrL66b0o0K8JTdc8T0AIcNml17iY4ihw1+WAe3/0Ma+te5KLZZ6bXa1YU1z9wY/B2Ek6MEga/f0/kjcCjGEakg3Di3bx9pOYH3Yer+73MH91PPpR4Oa6D48ZJ0PHzGJoPn+ZLl3fli+gTKJ1MU0sDDfUNeP0dFP2hJ5PYYDDIrFmzRmFG4wzpIGM1NJthgkWzKQ5WjLPMufHBSMUPMUGEHhU/FPmC5bjYrkvMjuIO0i8nFtSpa2qgoaHBK80aYlvgEUVoyByc4+lCQwzwvNfQs7/vSMSPWbNmUVVVxVjtsJVvTKSYL6Xssz06gN1HOBFWnOZkI280v8PRlYdSYIRyNMPRpdRXwoHly3mp6XVOn34ChYZnhqyZEVx/CYO9PrYcC9u1MXJsOaIEHkUPSISbBDeJbmWs7lTiFcibEi/btbBdi3hGWzuf7vO6dqUMnH2af8xdoGi6Qagie2tQRc/MqSjo8SRLkTuEHSMZ/pBEchIlhTMp8KkWpGOJkY4fhqZRENApChgEfWP/e0GhGK8kUuVZQzJX1gSxAgOQGNFacK0+dxlLOMFK5BAvLkNGARXByf0eL4Rg3uTR+x70+XzMmzdv1N5fkb/E7Xi/xGDL7X2MZrbxdP1LSCTHVh6Wq+mNCY6fciQvN63juYZXOGXasd5K6SCsONI3sO5XmcTtKMVDyALKhhJ4FAPDtRCu1UuJV8rXJw/Mjy3HwnI6TlhUu3aFYhBIBxGvo9VqI1owjbJgpTJhnqDYrktr3KU1bimxR6EYRRKWS8KOY+dAlNESLXkn7gDoiSbswqlD88ewY1iupc4FFeOemN13eRaA05v/jmuStMI83/gqy8uWMjlQkaPZjQ1mhqaxuHhvnq5/keOnHJGOC5rZhjMUgceJUZzjMi11i1sxdFIlXpoZRk/UY0SrMdqq0KO70ZItCCsKrslYLzFqb9cetSI0Jxupi9VQE91JfXw34WQzMTuKPUa7RygUo42w47it22lo3UI42TzosgDF+MATeyyqW+LsaIzREEkSN50JZ1qpUIwGCcvJSWt04STQctlifSSRDnq8eciHiVitOZiMQjF2kVL2y38HwHZ6PrfTzCgvNL5G3Elw0pSjcjS7scUJU4+k1Y7wWvN/0uuEm0Q4yUEf03IsrByL6GM/zUKRp7jeB97M/MCLtJePV+LV7uszdnXG7O3aNS/LR7VrVyi64KIlmombMWIFkygJTqHQVzTak1KMMpmZPbomCPl1Cv0GIZ+Opo2tsliFIt9xXEnM7NxxdHBI9ERTTuY0Wggnjma14fqKB32MmBWlyFeisngU45b+lmdBby3SXdxkmKfqXmBh0XzmFs7O3QTHEIuK9mJ2aCZP7H6OQypWpv1cNTOCEwoM+rhxO0rIGPz+XVFXpYoRJKOLVx77+rjS7dau3evc5RvH7doViv4j3CQiUk1rso1oQSWlgQrVbUsBeBefkYRNJGEjhCDk0ykI6BT4dOWbpVDkgLjlELGHnnWjJcMwDrKWtUQLrh4cUnfYiNVKeWBSDmelUIwdola032N7apGumRFea36LZivMJbPPydXUxhxCCE6YciR/2f431rduZP/Sxd56OwaydNAloZ5HbO5K2pTAoxh9evL10VO+PsKPNHxDqqMebrzOXU6ndu2GZmBovnHRrl2hGAya1YZsjdEYCBMMVVLiL8t5pwBF/iKlJGbaxEwv+PsNzcvs8evKt0ehGCTRZLJTQ4nBIJwEmjleSpMkRrzR8+MZZKcblcWjGK+40u2//04vLdKF2cbjdc8yIziNJSWLcjnFMcfK8mU8WPMoj+1+hv1K9k016JFDapluu3YqcWDwXj6ZqDNtxdhEOgg7jshs2Sf0dFlXh5nz2P2ytV0b27W7tGs3OpV3KdFHMe6RDnqiEdOMUB8spyA4iSJ/icpwU3TDtF1M26Q5RrqUqyBVyqWrUi6Fol/Ux5qH6HUl0RND964ZU7gmWrIVNzB4I1OVxaMYj8SsWL/jRao5XzeEHefdlg1UJ3Zz2ZwLxlxH4lyjC50TphzJ36seZEt0KwuL5gNDb5meyyweJfAo8gfpIBwH0amuXOsQffSUp4/mY7B/XMNNu+iTeXfN0HwpwcenRB/FuEW4SUSslrjZRixYTlGgnCJfybg/EVAMjsxSLoCAzyvjUtk9CkXPmLZNS2Jo5VlasjUvu2b1hWaGkUYAOchy4ZgVpcgoVl0iFeOKiBXp91i7B58ekWzjkd1rqfCVsap8/xzNbGxz6KQDebj2KR6tfZqFe3kCD9JBsyKD9vxKDNk3rQMl8CjynJSZs9thgpw2c9Z8SMM/5s2cbdfq1sq0Q/TxhB+/FlAXwopxgbCjiEiciNVGNFBOsb+MAqNQfb4VvZK0HJKW05Hd49MJ+nVCPh2f8u5RKIAcZO+4JpoZzt2Exhhe6/RpDPZ8sNUKM0mvzO2kFIpRwnItEnb/RQXbziLwuBZbwu/xcXQ7F806c8KU4fs1H8dVHs4DNY+yI7aLOQUzAa9l+mAFnlx2GZ0Y/wqKCUaGmbOdYRymGenSrnSJ1xj19ekQfTrm79M7MnyU6KPIb1zPwNOMEA60EQmUUewvocAoHO2JKfIAx5VEkjaRpJfd49M1gqnsHlXOpZiouNKlITYUcUZixPO7a1afuDZ6vBknNLhSq4Qdx3SS+PXcdbtRKEaLqNl/c2UAO0sHLT3ZyiO711JiFHHopANzNbW84MjJB/Po7qd5dPfTXDXvU95K10ZYMaQvN146g2VsXt0qFMOBayNcu7uZs5Yyc0518hqrvj6WY2E5vYs+qrxLkVek/Hkw22gJlNLmL1FCj2LAWI6L5bi0JbxMSL+heRk+Pl21YldMGNrMNuLW4LteaWYruGYOZzQ2EXYUYYUGfQEWNluoDE3N8awUipFnIOVZAFbXDlrSZlv4Aza2beHsGafgH6PXT8NFgRHi6MpDeWz3M1THdzMjFRc0sw1HCTwKxSgiHYQTRzgZZs5dfH1Il3iNvYuEbKKP8vRR5B2uiR6vRyZbaQmWEvEXU+wrJWSM7hekIj/xzJpdwvHugk9QZfgoxiGudGlOhLGylVD06wCW570zQdCTzdiGf1BZ3KaTJGHHCRqhYZiZQjEyxO04tjswQdjpksGjmVH+XfsUBXqIoyYfnMvp5Q3HTTmCp+tf5JHdT3H53IuBlOeknUAag/P7ygVK4FEoutGHr0+nEq+xZ/bZk6ePL/Xw6wEMzae6GCnGHMJNosfqcJNtNAcitPqKVEaPYshkE3zaxZ6goWEoDx9FntOabCVuDt4YWY83AbnzfxjzSAc93oRTMGVQu4fNFgJ6UJXJK/KWiDmw7B27W4t0lx0t77O+9X3OmH4iwUGal+c7xUYhR00+hCfqnuPUacczPejFFC0ZxlECj0Ix1sn09clY3anEqz3jZ+z9WbWLPpl5SrqmpzN8/KkSL30Mzl0x8RBOHD0WR+qttAQitPkKKfKVKDNmRU5oF3xaU4KPT9cI+FKij6HjN5Tgo8gfXOnSaraSsHvoYdwHmtnq3dCaYAgngWa2ptoaDwzbtYjaEYoGaaaqUIwmjusQy+jm2x9sp2v2ToR/1TxOoV7AMZWH5XJ6eccJU47kmYaXeKR2LZ+bexGQyuJxEoPu2jdU1NWcQjEU8rjEy3EdHDdOIkP20YTmCT66P5X14wk/CsVo0CH0hAgHorT5CijyFVNgFKmyQ0XOaPfwaW/JPm+yEhIV+UNrshVXuiQHU57lWp7h/QRFS4ZxjSBoA2993maGCRkFKhtakXdErMiAOzZZncqzJNubN/Bu60bOmn4yoQmavdNOsa+IoyYfwpN1z3PKtGMzsnhacQqUwKNQjBOylXjRQ4nX2PoTdKVL0kmQdDraJmpCYGiZnj7es7oAUowUHUJPkNZAlDYjRIFRRJGvWGWdKRSKCYvjOrSarbhSDsp/Z8KVZnVDYsQbsQunMtDW6a50aTPDlAUqhmdqCsUwIKWk1Ry435btdMQXzerI3jm68pBcTi9vOXHKUTzX8Cr/rHk83VFLOIlRy+JRZ8YKxUjhWgjXylLi5Ut38UIzxly2jyslppPEdDqncHc1c1a+PorhRjgJ9FgCqQWI+kuI+iME9RBFvmLVtlahUEw4WpItuNIlYQ1c3JmopVndcK1Bt06PWhEKjSJ8+sAzgBSK0SBux3HcgZdzdhgsSz5qfJsNrR9w9oxTJqz3TleKfUUcN+Vw/l37FNtjVexRMAsYvSweJfAoFKOJdBCOg8jImAHyItsnm5mz5+vTIfioEi/FcCDcJHqiHkwfCX8xcTuKXw9S6CsipBeo7DKFQjHusVwr3eY4OVD/nQlemtUVr3V6EOkbuKF/i9ms2qYr8obBZO9ARot0M8J9u/5Fma+EoysPzeHM8p/jpxzBs/Uv82D1Y3xpr8uBVBbPKHTUGltXjAqFwiNbtk83b5/2bJ+x40Xi+fo4JOgQrIQQXUQfn2rdrsgNroWeaIJkGNtfRLMdo1X3U2AUUWgUqvIthUIxbmlJtKR9NAaawaNKs7qjJ5qxdT8M8KaU6SSJWVEKBiEOKRQjiemYJOxE3wO7IJGpEi3Ju3Uv8XF0O5+afS6BQXhXjWcK9BAnTT2a+6r/zebIxywsmg+MTkctdfarUOQNPXn7GEjRUebV0clrbGQxSCkxHRPTMTutz5btYwhDZV8oBo500JJhtGQr0ldImz9ORG8lqIco9BURUCnECoViHJF0kkStKACO63byx+gLzQyr0qysuBl+PAM7DwmbzQSMIMYYy7RWKDIJDzJrr72DljTDPFj9b6YGKjlk0spcTm3ccFTlIaytf4E1ux7mWwu/gCY079rNjiON0IjNQ0UihSLfcW0EdpdOXiJV5mV0lHlpY6uFe0/ZPoZmpEu7DOFT7dsVA0AirAiGFUFqgXT5lqH5KfQVEjIKlU+UQqHIe5riTenlxEDMlV0TLTm4Eo3BIKVkV6KGDyPb2BaroiaxmxarlTY7AkgEGoVGARX+Mqb4JzGvcA57Fs5lVmj66GT5uiZ6ohknODDjZK9VfQsVwcnDNDGFYmhYrpUWhQeKJ/C4vFr9FDWJOq6e92l1LtUDAc3PmdNP5tYd9/BG8zusrlgOgJ5swTaCjNTNd3XVpFCMSyS4JsI1s5Z5oafEH82P1I0x4+8jpcRyLCyns7ePJrRO5V3tIpAq81L0hOfTk4SkjusvIuzEadXCBPUQBUYhwRG8k6JQKBS5ImJGSGY0PUhY/fXf8TpGjURpVlW8mpca1/F2eAONZjMAxUYhM4PTWVS8J8VGEZrQcKVLxI7RZDazse1DXm1+C4AyXwn7ly5hdfly5hfuMaKZvcKKIPTAgP14YlaUAqMQUKVairHHYLN3ACzXJRnbzYPVj7Bn4VyWly7J4czGHwdVrODp+he5v/oRlpctwa/5PN8zK4LrKx6ROYyNqzqFQjFCeGVeuMnOGrLQkSLl6aO3l3z5YIwo9K50s3byai/z8jJ9Ulk/ytRZkUm6fCuM1EMk/EXEjSi6ZlBgeFk9yghcoVDkA650aU42d1pnWv0TbLRkGLo0RsglrnR5q+Vd1ta/wEfR7RjCYN/iBZw67TgWFe3FJH95r0KNlJImq4XNkY95u2UDLzW+wbMNLzMrNJ2jJx/KQRUH4BuhbF490YSt+2CAHiMtZjOgsngUYwvbtQedvQNg2w6P7HiAiB3ji3ueoawU+kATGufN/AQ3fvh71ta9wMnTjvHWJ1txfYWMhHeqEngUCoXXzUs63f19xrjw017mBZ1N42aW74Wh2pYquiCcOHo8DkLH9RXR5kvSprXi1/2EjEJCRoFKO1YoFGOWlmRLpxbHluNiu32XaAk7jjbI7jl9IaXkzZb1PFz7JNWJ3UwJTOa8mZ/gkIqVFBoF/T6OEIJJ/nIOrjiAgysOIOEkeaP5bZ5peIk7dq7hX7VPcvLUozls0uoREHokRrwBu2DqgM53XGn3PUihGGFazda0IftgqG78gKfrX+TQSavS7b8VvbN38Z7sX7qYR3av5aCKFZT7y1I3HNtwA6XD/v55JfAIIU4CfgnowJ+llP/TZftRwEPA1tSq+6WUPxzJOSoU44o+hB/0VCt34RtTpV4KRa9IB80Mo5lhpBbA8hdi+hK0mi0E9AAho5CgHlIlgAqFYsxgOiatXfxz+uW/I22v2+AwsC26k3t2PcRH0e1MD07lirkXc0DZspzEzqAe4PDJqzls0oFsbNvCw7VP8feqB3my7nnOmXkqK0qXDm8mgWujxxtxCqYM33soFMOM7dq0mW2D3l/aJn/76C58wuDM6SflcGbjn/Nnns71G3/Gvbv+xVXzPgWAZrbi+goG3K1voOTN1ZgQQgf+DzgeqALeEEL8U0r5fpehL0gpTxvxCSoUE4mU8IObRHTK+NbSZs6eubNvzJk7KxSZpL16Es1II0TSV0jCiCOERlAPETIKCOohlZKsUChGlcZ4Y7d1Zj/8d/R4E8j++vT0j5gT5/5dj/B846uUGEV8es55HFKxclhEcSEE+5YsZJ/iBbzftpl/7HqYP2y9g4VF87l49tlMD07N+Xum39tJoCVbcANlw/YeCsVw0pJsGVL2zkvbn+Ld1g84b+YnKBkh/5jxwuRABadMO5aHah7nvdZNLC7ZG5CekfswC8f5dNV1IPChlPJjACHE3cAZQFeBR6FQjBoZHj+dMpW7dPVqz/jRfIyVdu6KiY5E2DF0O+aVcBkFJHwh4nYMTQgCSuxRKBSjRKvZ2slYGUAiSVi9Z/BoZhjhJHodM1DeDr/HXTvup9Vu4/jKIzht+vGE9GBO3yMbQggWl+zNouK9eLHxdR6ofpQffnAzJ005ilOmHTtsXmqa2eqdu/iKhuX4CsVwYTkWETMy6P2jsUb+uOkuZodmcEzloTmc2cThhClH8UrTm/y96kGuX/RVfJoP4SQQVgzp638J60DJJ4FnJrAz43UVsDrLuIOFEO8A1cDXpJTvdR0ghLgSuBJgzpw5wzBVhULRmZ66euFl+7R7+2j6mC/3UvFjAiAdNKsNrLaUX08hCSNB3I4hhCCohwgaIVXGpRgwKn4oBorlWjQnmrutN22J28udeWEnPGPlHBF3EtxT9RAvN61jVnA6n9/zUuYWzM7Z8fuLLnSOnHwwy0uXsmbXv/j37rW8Fd7AZXMuYG7h8MxHTzTjCANpDL+Q1RsqfigGQkuyZQh7S+58/1ZazDauWXip8iccJD7N4JOzzuIXH/2Jf9eu5cwZXpmbnmzG9gUZLsPlsXkFlZ1st0y7frO9BewhpYwIIU4BHgQWdNtJyj8CfwRYuXLl8PeLVCgUPePaCGyEE++yob3cS++S9WMwEg70PaHixwRDOp45qdkKmuFl9hhx4nYQIQR+LUDQCBHSQ+iqFFHRByp+KAZKY7wxa4lFsrfyLGmjJ7qXdA2WjyLb+PP2v9FktnDK1GM5bdpxGKMc70p8RXx27kWsKl/OHTvX8D+bf8PJU4/m1OnHY+T8YlSixxuwC6cOu3dGr7NQ8UPRTxJ2YkidszZWv8G/q57j+GmHDZtwOlHYt2Qhh1Ss5LHdz7CibClzCmaCdNATLTjBimF5z3y69VgFZH7CZuFl6aSRUrZKKSOp5UcAnxBC9StUKPISr9xL2DG0ZBg90YARrcVoq8KI7EKP1aEnmtDMVoQdT7V/Vec7imHEtdHMVvRYHUZkFyLehJlsIZxsojZWTV28hlazBbNLKYVCoVAMhnAyTMLOXmKVsHsSeCR6rDEnvjuudPl37Vp+tuV3CATfWHgtZ844adTFnUyWli7ihkX/j9UVy/n37rX8dPP/sTtRPwzv5GLE6kB1ylKMcaSUNA3BWD2RbOXmd39PZbCCc2aenMOZTVzOm/kJioxCbt1xD3YqNgsrgughvg+VfBJ43gAWCCHmCSH8wIXAPzMHCCGmiZQ5ghDiQLyfL3e3MBQKxdhAOqka1ghasgU9Xo8RrcFo24kRrQY3t4aSCkU3UmVcerwOo22Xd3c30UJbspn6+G5qolU0JxuJWVGcHBucKhSK8Y/pmD2WWLhSYtrZb2joiWbPC2+ItFoRfvnRn3mo5jFWlC3lu4u+zJ6Fc4d83OGgwAhx2R4XcvW8T1OfbORHm27mxcbXh2QumxXpYMQagH50L1MoRok2qw3TMQe9/23v/oWaeD1f3vtifARyOLOJS6FRwCWzz6YqXsMjtWvT671My9zHk7EjwfeBlNIWQnwBeByvTfotUsr3hBBXp7b/HjgXuEYIYQNx4EKZ8+iuUCjGNK6NyuRRjCxuh0EzILUA0hck5iSIaX5Igl/3E9CDBPQgfi2gjJoVCkWPuNKlPl7fo0CRtNys2zSrDWEN3lS1nS2Rj/nj1ruIOjE+NftcDpt0YF7ErBVlS5lfOIdbtt3N7Tv+wXutm/jU7HMpMEK5exPXRI/W4xROQTWJUIw1HNehJdEy6P3f2fUyD1c9zekzj2Jp2UJqWocnw2Qisn/ZEg4qX8G/a59i3+IF7FU0zyvVijfjhCbl9L3yRuCBdNnVI13W/T5j+TfAb0Z6XgqFQqFQtCPcJCKZ9AxOhY40Qlh6ENMI0CZ0hBAE9IAn+GhBfLp/tKesUCjGEE2JJizH6nF7PIv/jrATaFnMmAeClJIn657j/upHmRyo4It7fo7ZBTOGdMyRpsxXypf3uoIn6p7jwerH2BbbyeVzP5nT7CPhJtFjDTgFk1Eij2Is0ZRowpWDywhpidVz0zu/ZWZoKp+adzq2lKgbprnlotln8WF0G3/Z/ne+t+grFOghhB1FWCHQS3P2Pn2WaAkhuuVmZVuXse1QIURhavkSIcRNQog9hjZNhUKhUCjyEOkgrIjnIRXZhR7djUi0kEy0EE42UxevpSZaRWOinojVhjWEtGqFQpH/RMxIn62Nk3aXCzjXRI83DOl9Y06c32+9nTXV/2b/ssV8Z+8v5Z24044mNE6aejTfWPh5AH62+Xc8Wvv0oC98syGceOp3ri6AFWODqBUdtLGyKx1uWvdz2qwo39z3swR1P7ajShFzTUgPcvncT9Jshrlrx/3pTEw90ZTyEs0N/fHgeaWf69r5HRATQuwHfAPYDtw+iLkpFAqFQjGuEG4SzQynvHuq0GN1kGwmmTJr7iz4tGI6ydz7SCgUijFJ0knS2Ef3K8txO194SRsjVs9QfByq4tX896Zf8U74fc6b+QmumvspQvrotgTPBfML5/C9RV9hRdlSHqh5lF9+9GfCVmvOji9sJfIoxgaO69AUH7yx8n3v3cl/mt7nir3OZV7RzNQx1ed6OJhfuAenTz+BN1re5pmGl1JrXfR47myDeyzREkJMA2YCISHEcjpyEEuAgl6OaUsppRDiDOCXUsq/CCE+k7MZKxQKhUIxLpCeWbiTAMKAhtQDSMNPUg+Q0AOAQBMCnxbArwfwa378egBN5FOPBIVC0Re2a1MXq+tT0E1YmeJOyvR3CEburzS9yZ077qNAD/H/FlzNgqJ5gz7WWKRAD3HF3IvZp3EBd1c9xA8/uJlL51zA0tJFOTl+u8jjhFS5lmL0aEw0Drqhw1u7XubOD+/j8MoVnDT90PR621ECz3Bx0tSj+Ti6g3ur/sXs0Ewv7uawQUxvHjwnApfitSO/kY6o1Qr8f73s1yaE+DZwCXCEEEIHfEOfqkKhUCgU4xkX4cQRTjz1WiA1P9IIYup+kkaA9sRbQ/MR0AP4ND9+za98fBSKPEZKSX2sHqcfJ/jJdHt0Fz3WAO7gyjot1+Keqn/yfOOrLCyazxVzL6bUVzKoY411hBAcPnk1exbuwZ+23cWvP/4Lx1UezlkzTsGXg5bvwo6jx+qRhVNyMFuFYmC0mq3ErNig9t0V3s5P3/oFexTO4It7X9zJTN1WGTzDhiY0Pjv3Qv5706/4w9Y7+M7eX2JKKHdZkz1GNSnlbcBtQohzpJT3DeCYFwCfBD4npawVQswBfjbEeSoUCoVCMcGQnmGzmdHyWPMh9QCO7ieqB0Dz7p90ZPn4MTQffi2AkYMLF4VCMfzUx+tJOn23NpfIVAaPRI81DLodel2ygT9uvZMd8V2cNOVozphxIrrQB3WsfGJGaBrf3vuLrNn1ME/Vv8CmyEdcPveTTA9OHfKxhZNAxOqAfYc+UYWinySdJM2DNFePJFv50Ws/Qtd0vrvkKoJ6Z4td21UePMNJgR7i2nmf4X82/4Zff/wX/r9FX8nZsfuT432AEKKs/YUQolwI8eOeBkspa6WUN0kpX0i93iGlVB48CoVCoVAMFddKmTY3YURrOnx8Ei2YiWbakk00JxrZHaumJlpFQ7yOVrOFmB3Fdu3Rnr1CoehCY7yx33ffvfboLnqsPlXaOXDebFnPjz/4JQ1mE9fOv5SzZ54yIcSddvyaj0/OPovPz7+MZivMjz/4Bc/Uv5QTrzOhTPIVI4jjOtTH6gf12U06CX70yg3sjjfw7X0vZ0qwotN2V4Kr/P+GnRmhaVw171NUx3fz24/+ipUjo+X+CDwnSylb2l9IKZuBU3oaLIQ4WwixRQgRFkK0CiHahBC5czRTKBQKhUKRwkU4Cc+4OVGPEan2unXF6iHZnEX02Ul9fDfhZDMxK4rlmMrEWaEYJZoTzbSZbf0eHzftQYs7lmvxt50P8IetdzAtWMl39/4y+5cuHvBxxgv7le7L9Yu+ysKiPfl71YP84qM/0Wy2jPa0FIp+IaWkPl4/qBs3juvw89d+wsaWD/nqos+wpGyvbmNU9s7Isbhkby6Zcw4bWjfyk9d+kpNj9id/WxdCBKSUSQAhRAjosU068FPgE1LKjbmYoEKhUCgUigEgnS5ePoDQkanyLkvzYeo+0Aza7fUMzYcv/fDKvFSJl0IxfLQkWggnw/3fQbpY4dpBiTs1id38aetdVCVqOL7yCM6acbL6+wZKfSV8cc/P8VzDK6ypfpgffHAT5888nYMrDujkRaJQjDUaE40k7IHHAle6/PrNG3m17i2u3OtcDp+yIus4JfCMLIdNOpA2O8aRs47MyfH6E93vBNYKIf6K1wfws8BtvYzfrcQdhUKhUCjGENJB2jZ2Mo7tguWC7Qos6cNGx8bAkga20LFdDcf1UrQFOlJqIHWQmreMhuNKHFfiSu/Zkd4dRVdKXNdL7ZYSXFLPqdfemNSUUq2F+5NAJASIlBglhOc5BKAJz0BVCNAQaJr3WkuN1zSBLkDTvG5kmhDoGeu85dRz6tESM1mxR0Vv01EohkQ4GaYl2dL/HVwHK1yLY8X7HpuBlJJnGl7mvl0PE9QDXDf/sywt3Wdgkx3nCCE4qvIQ9ilewK077uXWHfewruUdPjX7HMr9ZaM9PYWiGy2JFiJmZMD7OdLh1+tuYu2uF/jkHqfwiZlH9ThWddAaeU6fcRIrZ4+QwCOl/KkQYj1wHN6tvh9JKR/vZZd1Qoh7gAeBtPublPL+Ic5VoVAoFIpxhetKEg4kLEjakLC9Z9PxnpO2JOl0Xme2Lzves2VLTBes9tcZD9MFO7Wc/Xwtd205syHwhBRBSqQRwqsNTwkw7TfJe7tXLvFEIIkk9X9qXRfxKEdzXjGnjPuvPbTvgQrFIGhKNNGaHIBzgWNCtB7THNjd+mYzzO077uW9ts0sKVnEZ+acN267ZOWCqcFKvr7gGp6pf4n7qx/l+o0/58wZJ3PU5IPRRH8cLRSK4WfA4nAKx3X41Zs38nRK3Llobo9uK4DqoJXv9Dc/cyNgSymfEkIUCCGKpZQ9FQ2XADHghIx1ElACj0KhUCjyHteVxGyImxCzIG61P0viqdfphw0JS6aevddJyxNyEimhZiAIAX4dArr37DfA176sQ8jnPfs0gU/3tvk0MLo+p5YNzXuta8Jbp4Ge8axroIv2Zw2hGxiGgTAMhOZDGAa67ktnzfgMA7/mw68b+HQfujC8ci9hDHvJQ2Z2kOPK9GtHStxUtpErSWUceevas5BsN/VaSuZPLhrWeSomJlJKGhONA7vzbsUhWg+yvXtW/97nlaZ13LPrn9iuwydnncWRkw9WJUf9QBMax045nGWl+3Lnzvu4u+pBXm16k4tnn80eBbNGe3qKCU44GR5Ux6yEneB/X/sv1tW/zcVzT+XCPU7ucx9HCTx5TZ8CjxDiCuBKoALYE5gJ/B44Ntt4KeVluZygQqFQKBS5REpPcIkmIWJCNPWIWTK9HDUhZkI0Jdq0v46lxJm+EEDQByHDE13al0uCEDQEQQMChrc+vWx429qXA0ZKzMlYNlIlSKODBKzUI4WTemgGUviQjoGrG8SFQUwzOvn86JqeEnwMDGGgZzznoouPEF7plfdeg/8dzZtcOOS5KBSZOK5Dfbx+YJ4ZiTDEWwCvXNJ0+laDG5JN3LXzPt5r28yCwnl8Zo/zmRKYPMhZT1wqA5P48p5X8Hrzf/jHrn/x35t+xeGTVnPGjJMoNlR8UIw8gxV3WpIt/Ojl6/kwvJVrF1zAyTMO73MfifLgyXf6k8HzeeBA4DUAKeUWIcSUngYLIYLA54DFQLB9vZTys0ObqkKhUCgUHUjpiS9tJkSS0JaESFISMVPCTUrAiZiSSHrZE2p6uzklBBT6oMAPhX5veUYJhHyCgtT6Al/q4ReEUstBw9sWSgkyE+qOuWsjsBEOnfQfICX+eGKPrelYwgeajtQMSAk7njhjYGSIQJrQcyoAKRSjgeVY1MXrsJx+tr+VLkQbvOydFEm7d3HHdm3W1r/Iv2qfQKBx4awzOGryIaq0aAgIIVhdsYKlpfvwr5oneab+Jd5oeZvTph3H0ZMPVSbVihGjMd44oG577Wxp3sx/v/pjWq0I31p8OQdP3q9f+ylxJ//pT3RKSinN9hNVIYRB76XudwAfACcCPwQuxivxUigUCoUiK1JKkrYn0rSmxJq2pEw9Z38dSfbkK+MR8kGxHwoD3nNloaAwAEXtwo0fivwivdz+CE40cWa4SYk/ONm8djRPANJ0XGFgajpS+EDTsgpAutDTmUC60FOvvWV1MasYa0TMCI2JRmR/nMQBrATEGsDtLOj0JvBsbNvC33c+SG2yjv1K9+WiWWdRocyBc0aBHuKCWadz+KTVrKl+mH/sephn6l/m9OkncGD5chV3FMOGK10a4g3ErNiA9pNS8uS2x/n9u3+g3FfCT/f/KnsWz+73/spgOf/pj8DznBDi/wNCQojjgWuBf/Uyfi8p5XlCiDOklLcJIf4G9GbKrFAoFIpxRnsZVGsi9UhCa0KmnlMiTkKmBZ3WpGcEnA1NQFFKpCkOwvRiWDhZUBxIrQ94Qk3763YBZyhlOoqRwgXXRLg9GS2LVAaQjhQ6lm5gCj3V9t17bheBvC5ZmSKQjtYuAomO10q8Uww3rnRpSjQNwG9HeuVYie7myxKy+u/UJOq4b9e/Wd/6PpX+SXxh/mdZpjpkDRszQlP54p6f473WTdxf/Si3bL+bx3Y/y2nTjmNF2VIl9ChyyoAz/1JEzAi/+c8veanmVfYr25uv73sZpb6B+copg+X8pz8Cz7fwSq7eBa4CHgH+3Mv49k9iixBiCVALzB3CHBUKhUIxBjAdSWsCwmnRRnYsJyCclBliDtg9ZPkGDShJCTNlIZhT7okz7Y+SgPe6JOgJNgW+jrbYiomGBNdCpE4tRFb/I+GVfOGJPpZmYAktVRbW8YzXvwtNaN0EIC2VAeSVgimPDcXgidtxGuON2G4/zLrAy9qJN4KTfbxpu14HuRRNZgv/rn2KlxrfwK/5OXvGKRxbeRg+zZeL6Sv6YHHJ3uxTvIA3W9bzr5on+eO2O5kRnMpJU49mVcWK0Z6eYhwQMSM0JZpw5cBKpV6veY3fvv1/tJhhPjPvDM6afSz6IIRHR5Vo5T09CjxCiLVSymOBn0gpvwn8qZ/H/KMQohz4HvBPoAj4/pBnqlAoFIqcIqVnKhxOtD86BJpOrxMQTnpdobLh1z0xpiQA5SHYo1xQEuhYVxIUHcsB8BtKrFHkEtlRBtZjJhB45WA6Eg1X03GEnhKA2jOBNKSmI2WFyvJRDBjHdWhONvc/a8d1IN4MZrTXYYlUeVaT2cITdc/yfMOrSODIyQdz2rTjKB7g3XnF0NGExqry/TmgbBnrWtbzSO1T3LL9bh6seZxr/GEuXHThaE9RkYc4rkNToomo1XtM6EpjvJE/rf8DL9W8wh6F0/nO4stZULzHoOehSrTyn94yeKYLIY4EThdC3E2XcyYp5VvZdpJStmf3PAfMz8ksFQqFQtEvbLcjy8bLrkll2XQRbdozb7J9jwu8UqiSAJQGYf4kT7ApDXkZNqVBQWnQ29beFUqhGPu44LreyUxvQpBcPHJTUuQ9UkrarDbCiTCO7LvTFdL1SrGSrdAPb56trTU8XvcsrzS9iZSSQyat5NRpxzHJX56D2SuGgiY0Dizfn5Vly9jQuokn6p7lvcb3RntaijykzWyjJdHSvxiSImEneGDLfdy35X5c6XLJ3NM4e/Zx+IZgAC4BS5Vo5T29fQK+j1eeNQu4qcs2CRyTbSchxFTgv4EZUsqThRD7AgdLKf+Sg/kqFArFhKLdyyYc7yh9yhRpwskMESfhdYnKhk/3BJnSAFSEYG65SAs0nlgj0svFftCUf41CoVD0SsyK0Zxs7p9PhnQh2eYJO32UQDjS5T9NG/nnrmf5T/NGDGFw+KTVnDj1KCXsjEE0obGsdB/2K1vMin2PGu3pKPKIhJ2gOdFM0kn2e5+kk+SxrY9y35Y1NCfDHFq5nEvnncG00OQhz8fz31ECT77Tm8BTkxJovi+l/OEAjnkr8FfgO6nXm4F7ACXwKBQKBR1eNmnD4ZT5cIefjUwJN94ji78m4BkJt4s0s0uhdKrIKtiUBL3W3arsRKFQKIZO1IoSToYxnR4U9UwGkLFTl2jimd2v80TNy9Qlmyj1FXP69BM4ctLBqhQrT/Dr/tGegiIPMB2TlmTLgDpkhZNhHtv6KA9//DAtZphlZQv51j6fZd/SPXM2L8dR/jvjgd4Enl8BBwBn4rU77y+TpZT3CiG+DSCltIUQ/c83UygUinHIZbe/y45Gh7YExHvw3vRpXmlUaao8anZppmADxYGM0qgAGLoSbBQKhWIkcKVLm9lGm9nWPwNlOwnJCFjRXoWdVivCKw3reb5uHetbNgOwrGwhl+15JnsG9qbdHFyhUOQ/cTtOa7KVuB3v13gpJR80fcAT2x7j+V0vYLoWK8r34dx9LmVp2YKcz8/uR9moYuzTm8BjCSH+CswUQvyq60Yp5Rd72C8qhJhEKr9LCHEQEB7yTBUKRV7gSontgu14XZRs18tAyXxtu15L7I5lmX1b12Ok1rUvO67ESr12Mvabt249t332oNH+VXSisshPAJH2tvFMhzuXSQVVlo1CoVCMKRJ2gogVIWpFkX1d/LgOmBHPOLmXsq3diUZeb3yX1xveZX3LFlxcpocq+eQep3L01FVMC03GciUNkUSOfxqFQjHSOK5D1I7SZrb1u+35rsgunq96nud3PktVtJqQHuDoqQdy+syjmFM4fdjmaqsMnnFBbwLPacBxeF47bw7gmF/F6561pxDiJaASOHfQM1QoFEgpcWWH2OG4ncWSrOvT4ojMOsZyej6Ot6/sYX2G2NJ+zIz1ufZmE4ChgaF7z76uyxmvQ4a3PLs8mNtJ5ICfnr03Gz56dbSnoVAoFIo+SDpJolaUqBXFcftIQndtsGKpR3YfjYgV473wh7zTspm3mjayK74bgFkFUzlr9rEcXrmC+UWzOgn8CUslvysU+YorXeJ2nKgVJW7H+xSHbddmU9Mm1u1+g9dqXmNnpAqBYEnpXpy18JMcPuUAQnpg2OetOmiND3oUeKSUDcDdQoiNUsp3+ntAKeVbqe5be+Ndm22SUvZPrlQohol2gcRxva5BTqbY0b4+Y123Mel1sptQ0j6+q8DiZG5z2t9HZhVour5XtvXDFXJ1DQzhCSN6FtEkc1vQaN8m8Gkd43XNM/E1tM4PX2q/DmFGdNqWbXxXMUcTA89qWb73wmH6bSkUCoVivOG4DgknQdyOE7fjvYs60vXKr+wEWPFumTqOdNkV282HbTv4oHUrH7RuZVu0GonEr/lYUrqAk2YcyqqKxcwsmNrj2ySVwKNQ5BWWYxF34sStOAkn0auok3SSfNTyEe81vsf7DRt4r/F94k4CXWhejNjzXA6t3J9JgbIRm7/qoDV+6E8ftbgQYi0wVUq5RAixDDhdSvnjbIOFEDpwCjA3dfwThBBIKbt24lKMAdLCh/SaOrQLG64k6/rM7e2v3SzrHFf2OL7retvN/h7t4ovb5Vh2+5wyl2VnUaXrmJHKONREh6DR/myk1uldBBFDg4ABhenxopPY0Ul4ERmCS9fja2BoosvrjjG+1P7t4knXOaiSIIVCoVBMJCzXwnRMEnaCpJPs3SzZtVOCThKcJNjeWCklLVYbO6O17IzVsj1azbZoNVsjVSRcb0yBHmTvkrlcNPkUlpUtYGHJHvg0Xz/mJ7H66LSlUChGDyklpmuSdJIk7SQJJ5FVGJZSEjbD7GzbybbwNraGP+ajlg/Z3rYz3RJ9VsFUjpq6iuXli1hatoAio2CkfxxAddAaT/RH4PkT8HXgDwBSyvVCiL8BWQUe4F9AAngXyOm3kxDiJOCXgA78WUr5P122i9T2U4AYcKmU8q1cvf+rW5vZUCXT4ocrM5e7PNzu69rFEJkpevSwj9NpXXcRptNxux7L7Rjbvr7bvhnLo4kuOkQRPfWsdRVFsiz7jYz1whNH0sKK6H4Mo8txDK2zGNMusOhdBBpddBZT0vt32zc1dyWWKBQKhUIxJpBSpsUcy7VIOkksx0pfWHUe7IJjgmuBbSGdJG2JZhoTLTQkm2lINrM70UhtopHaeAPV8XriTodHTqERYm7hTI6bfjALiuawZ/EcZhVMRRcDN0lW5VkKxdjBdu1OcaT9uT1DJ2EnaEo00RBvoC5WR11sN7XRGmoiNeyKVtNmRdLHKvEVMb9oFmfPPpaFxXPZp2Qepf7i0frROqE6aI0f+iPwFEgpX+9yl7+39gGzpJTLhjat7qQyg/4POB6oAt4QQvxTSvl+xrCTgQWpx2rgd6nnnPDdhz6gqjk3H/52YUNrFxraX2es722MroEQXiZGQO86XnQar2c5ltH1mFpnwSTruAwBRMt8znyfLsfRM4/Tvpzxfip7RKFQKBQKxWCQUmJLG8d1sF0bRzpYrpW+IHNcJ3WnPUncjBI3I0TNNqJWG1GzjUiyjYjVRmuylVYrQqsVocVso9lspdlsxZKdT3cNYTAlWM604GT2KZnH9NAUZhdMZXbhNCb5y3J2TqPKsxSKkSEzhiTsBK1mK61mK23JNlqtVsLJMBEzQsSK0JoM02Z668LJMC3JFpqTLUTtzq3OBYJJgTJmhCo5ZPJ+zCmYxqyCacwtnEG5v2TMXvuoDlrjh/4IPA1CiD3p6Ip1LlDTy/hHhRAnSCmfyMUEMzgQ+FBK+XFqHncDZwCZAs8ZwO3Sk1RfFUKUCSGmSyl7m2+/+c2FS9nw8ZudhZguAokQ3YWT7uPH5h+2QqFQKBS90q8TwGE6SezHe4tcvLdjga4P/Tg5QkrJizveRRMCDYFAogmJhuudYwC6kBiaQBPSy0SRqXTh9mVk+lmm14HEW5bSTW3LSNFvHyNdZPt+qfl0jHeRqTFu6j3al2WXZRcX13VxcZHSxZEurnRxpIPtOtjSwZEutrTTrz2xxhNvTNfCSj3M1GtvnU3StTCljZlaTroWidQj7lre3HrBQKPUCFGqBynTQ8wOTKasYDaTjUImGQVM8RVTaRRSYRR2P4czHUSyCu/eY9Z/wQH9e9uuJBQ3CQ1or55QF2wjiRAa1EyD6Tm/zz1o7HgLW/55Vbf13idDtF/cZdnaeZtEIjMirOwyOv3IGN91m5uxxc04hovERSC9iJR6Lb1KA+i8DokjJY7w/K4s6eIAlnSxcbGRqWWJKV0s3NSzJCkdzNRzEpeEdEmknuM49CWrCqAInXJhUIbBXsJgkihgklFKpfBRKfxMF36mCB8+TQMTMGMQ/hj4OHWEzKP1/LLnlanfb3/Hd/u37fkaNGi7lHUp7cgeQbK9T99jZL/2y7Yyy7EGuV/vmwc7576u6ztv72nuuuYDvw0LjuvjeH3TH4Hn88AfgUVCiF3AVuDiXsa/CjwghNAAC++nklLKkiHOdSawM+N1Fd2zc7KNmUnvglS/WfLu/zJv28u5OJRCoRhGjB2HwGk3jvY0OlFwy7EcEG3MvjHrhWv/Tsy7XdAO+A5M9/EiB8fo2DSwYw395+m0c8/vM+jj5u5nTc+lvxdhQ7y7lhPxYwIg31gJV6wd7Wmkka7Dtc/2dto1MTCkxJASnwQfEp+UBKTEn3oOSEmplIRcSVBKQqnlAulS4EoKXJdi6VLoSopdl2LXpdRxKXVdQjLrafyoMWu0J6AYNO+++ThLv5Hre9yDpyHawvmJ9/seOA4wpMQAfBIMJIYEfypeBCSpmAElSIIuBFNxI5R6FEjpxQopKXYlRannYtelJLWclv47fR93PW/JNrvexvfzfC89brDnDL2fv5R2fT91zjDibNi5kyUjIfCkMmaOE0IUApqUsq2PXW4EDgbelX31hBsY2b57ux6/P2MQQlwJXAkwZ86coc9MoVBMGAYbP5w9Dqe5aXvmkfrcR2bN9uvHZUivWYLZ7lAM/Ri9MeifIwdz6fVLKIc/Y8f79bJfTrI3h3b8/n8p9/Y+Q9w/gwFfVufwvXsaP2uvw4ftYn9w8UPwVbEMKQQSzUvMQaTueAvPVw+BK0UnH7+OZgYCy/XueltOysDXActxMW0XJ307USBl+913ga4JCgIGBQGDkoCf4pCPspDfexT6Ceh6qtRAIIRAE4L0f0JDCNBTl0NCCHShec/oqfE6uhBoaOiat6zjPRvCQBcauhD4vD1AE0jX8T7DrouLk3p2QbpelpDrAA6OY6cyiGxc6WUMuVKmsolcMv/NW1OPjF931n+D/vw79UT2GJidcNzMcanEWJKu+kZKSdKGtiRETO85akLMhKgFcUsStyBuQ8LyHuYAK9rafRoNPeWpqHfYB2TaCGiaZ/rZkY0vumXnC+H9httf77twP5YOxy+GwcUPLVBJQfPlmLbr/c07Lq7bnl3T82dDw/v7LwoYFAV8lAQNSkI+SkN+Kgr9lBf4mVQUYFKhn0K/DwSpv30vBkDH6/ZlLRUDMsdpQks/aym/Kl3o6de60FPxw3s2NCO93tCMTs85K31y3VT2owvS8Z5dp2Od64B0kI6FdG1cx8rIaoRUPmM67shU9pGbylqUUuKQepYubip7cbSpaU0wqKy/gQhJve7XT1GpHzdF+/wk9DDnmClpiEFzDJrjkpY4hBPQmpS0JiCSlERS8Sgjz61HdAF+HXxGu62K9BrdZHQL9jJwwafrHLNsX5b0Nfd+0J8MHgCklNF+Dt0CbMixuANeNs7sjNezgOpBjEFK+Ue8rCRWrlzZ73nax/+I9zc939/hCsWEIp2Cn0q9d6TjLeOkU/Hb0/Ed6Z2UdxonnfS69i87b//O+3aMcdPHb39PN3XcBdP25Jrh+zkHFT+Sx97Axx+9OkyzUijGJ650sVwbS3qlOLZMPVwbq72ER9rY0sko7bHTy470xjmpMU6q9MeWnl+LLdtLg9rHO+yX3Mp3h+nnGUz80HSdyz5913DNh6TtEo5bNMdMmiImDVGT+rYku1sT1IYTbGuJU1UXo64t2emceE5FAYumFbPf7DL2m1XGktmlFAf77hA1Kriu1w0rdVHm2Akcx8JxkqnlZLoUrL1MLPensX1jOi7N0eSIv+9IE7cktW1Q2ybZHYG6CNRHJU0xaIxCMotgowsoDkBR+6MACv2CEh8U+CCU8QgagqDP61Qa0L3GHAHdu9Dy656n5HAghMZBS48dlmPD4OLHlOJCXvvylzqtsxyXWNIhZtlEkzbRpEMkadOWsGhN2LTGrXRMaI5ZNEVMGpuSfBQxaY6ZGXHABExKQz7mVBQwd1IB8yuL2GtKEXtPK2be5EJ8+sBNxkcdTcMrfu0dkXpo0BFjXMt7dqzUw0zFnr7/uRzp4Ljeea+T/i5zsd3U95d0hi0uWUPpoDWAMrC+huXqp+vtOLYrqWmDqrBkVxhq2qCmTVIX8cTkrpQEoDTkPU8tFOwZ8GJRod97FPhERuyBYOo5YHhdjvuLTw+ycvG+A/9hs9BvgWcA1ADPCiEeBdLfUjlok/4GsEAIMQ/YBVwIfLLLmH8CX0j586wGwrny31EohoN2Fd9JXXg46YuNjkfn127qwsTtNKZ9W/b9uootncfaGcuZAkzmsTLFmEwBxukkuoyuKaRG+90ejSqrjmuWXzuq81EoxiOudFPeJyama5F0zfRyp2dpZXikeOvaRRrTtbBS223XxswQbyzXwpK2J+q4lpedkSN0oaczQwxhYGTc+W1fpws97R0xERBCEPTpBH06U0uCvY5NWA47mmJ8VBdhS12ED2paea+mlSfe3w142Qv7TC/h4PmTOGrvKayaV07AGCNeRpoGmh8A4QthUNL9BNixvYux1MO24lhWFNuxUiKj99nN1go5V8THmbmy40p2tcK2Jsn2FqhqkVS1QlNnT1pKglBZCLNLYf/pgooCKA9BWUhQGvQurgp9qjFHrvDpGqUFGqUMXJC1HJf6tiQ14QQ14ThVzXF2NsXY3hjjPztbePjdmrSW4Tc0FkwpYr9Zpew/u5wVe5SzZ2Xh+Px3TMcYf/dtUqbEniTYZuo54YlCGehCR2/3f8sSOj1DaCcdjywn9R2bA0F6vHbQcqWkuhW2NEi2NHixaGcY7NSPK4QXe6YVw16TBJWFUFkkmFQAFSEv9gxEpBkrDIfAszX16OFTPjiklLYQ4gvA43gf+1uklO8JIa5Obf898Ahei/QP8dqkX5ar91fkD17KY4fAYbXfqXXt7ndu06q4nTJr6xjb7e5ulru/ncek9sPFSb9XT0JNx+vhRiBSFzB6KuW967KWSovX02mvutDwa75O64zUs4aWsV7rtp93LA2RuU7o6HSk26afU3PrdCy8ZS21rya0jPcU6TEdx/JS/DNPGJbvfcSw/14VirGO1z3IIu4mSDpJ4m6ChJMk4SRIuEkSTpKka5JwkyRTy0k3ScLxnr3XZnqbJ9L01kQzOwKBX/Ph13z4hA+f5sOnGenlIq0Qvy9znYEhDG9c6tkQBoam4xM+DM3AlxJrvGUjvd3IsuzFr/6n769efPyAf8aJQNCns3BqMQunFnNyxvpwzGL9rhbe2NrEKx83ctsr2/jzi1sJ+XQOXzCZ0/abwTGLplAUGI5TzhyiG96DAsA7QTbAuyCzE2AnwY7jWPEOk2fHJOGaORF9JPnfHr0tKdlUD5vqJVsaJNuaOrJxfBrMKoXFUwQzSmFGiWBaMUwp8jJuFPmBT9eYURZiRlkIKO+2PWE5fFQfYfPuNjbWtLFhV5h/ra/hb697FqkVhX5Wz6vgiIWVHLGwkpllubETH9MIAYbfewQy1jsWWHEvvlgxT2Tu9TAi9Z2YiqUpfa79uz6ZiklxNzngmGS54+fGRn1U8na1ZEOtZGOdV+YJXrbN/Ao4eW/BHuUwq1QwvQT8+viLPz1+2wohzu5tRynl/T2s/8FQJ9XLez6CJ+Jkrvt9xrLEM4VWjABuShCx02nzTipt3k63HLQy0unTKfQZ47oKLx2iS+YxO7a1p9Gn9+2Ukt8hxAwH7RcJ7QJJ+51gn2Z4oobWsT2oB7OMTz1renp8j2My1nUWZbKP71m80dM1zQqFIr9wpUvMiXsPO55ejjuJjOU4MSdBPP2Ik3CT6df9zUYJaAGCWoCA7ieg+QloAQr1EBX+MgKaH7/m7/TcvuwJN95rn+ZLPRsd24Qvt94IijFHaYGPwxdUcviCSgBips0rHzXy1MbdPPHebp54fzdBn8aJi6dx4ao5HDS/Ir8+D+0XZil01yVkxwmZsdRFmdfpK+maxB1POLXdgQuhSdvBzbM2xbYj+aAe3qmRvFsr2dHsCVWGBvMq4Oi9BHtWwLwKT8zR8/BOuGJgBH06i2eUsnhGKWct99a5rmRrY5R125p49eMmXv6ogUc31AKwaFoxJy6eyqnLZrBwavEoznwU0H3eg1QfItsEK+p13rLi/T6MEML77tb94CsEwHJtEk4yHZPcPjx+HDd/M3ik9LJyXtsheX2npCrsrZ9UAPvPEOw7BRZWCqYXT5wswN5up3yil20SyCrwKIaP9lailrTSwka7wNJZSEm9bh+bKaB0GtvhVdCe7tdJrEmtb89W6Uih955zmcYuEOl0+fa7rr5287SMVHq/5qdAN9LCRrYx3jbvDq+eccxsafntrzul7qeO0XH3V1MXKAqFYkgkXZOIHe3+cGJE7ShRO07EiRKz40SdGFEnRtxJ9HpMDY2QHkw9QoT0IJMDkyhIrQtqQYK6J9yE9FB6OfM5oAXwaz4lBCtyRoHf4Nh9pnLsPlP58ZmSdduaWPNWFY+sr+Ght6vZs7KQzxwyl/MOmE3IP0ZKuAaCpoG/0HsAOBaGGcEwoxRa3t+s5drEHU9oTTjJfpVP5Ev2TsKS/Kda8vpOeLtakrA9QWdhJZy7TLDvFMH8SePzrrhicGiaYM/KIvasLOKCVXOQUvJhXYRnN9Xz2Hu1/Grth/xy7YcsmlbMuQfM4pwVsygvzFkRSP7QLiaHyj0j52QbmBGwej8XyIZP866jin2FSCmJO0nvZpAdz2robDn5JS4DhBOSF7dKnvvYE3iEgEWV8KkVgv1nTCxBpys9CjxSSlXe1IW6WB27E/Ve/WOGcOIJHhZWl+yTtCFkWlRpz1yx0uJKdoGms7iSa0FFQ+uUvp5Oh0+lu7cvh/QgvlR6uy9DeGnfN3N8u2jSkSqfIZJkps1niDCZ43SRhyd5CoViwuJKl6gdI2y30Wq10Wq30WpFaLO9R2vqOWJHabUiWNLKehyBoEAPUWgUUKgXUOwrYlpwCoVGiAK9gEI9RIFRQIEeokAPUqAXpJ/9mm/Cnrwo8gNdE6yeP4nV8yfxw9OX8M93qvnrS1v5/kPvcfOTm/ncYfO57NC5FI718q3e0H3eBVmo3CuxSLbiS7bh0wxKfIW40iXuJInaXvZdNrHHlRC3xu4ddNeVrK+FF7dK1lVJko7nm3PIHoLlMwVLpqkyK0X/EUKwYGoxC6YWc8UR86lvS/Lv9dXc99Yufvzvjfz0sU2csnQalx8+nyUzuzbvniBoOoTKvIdtQrIVEuF+t1TPRAhBgRGkwAgi/aXEnQQR28sMBi9rw86jDJ6PGiWPbZK8skPiuLDXJLhspeDA2YKykIpD0E8PHiHEqcBiIO3AJ6X84XBNaqxyxdorqY4O3LO5a3ZKVyGlXQAJagF8vs6iS6flLsJKZzGlq1DTXcBp30fdqVUoFIrsSCmJODFazBaarVbCVistVpiW1HLYaiNst9JqRbIaABtCp9goosQopthXxIzgVIqMQor0Qop9RRTpBRQbRZ6gYxRSqIdUTFZMCEJ+nQtWzeb8lbN49aNGfvn0Fn7+xCb+/OLHXHfMXnz64Ln52XEnE92AggrvYSUgEUYzIxSKEIVGCEc6RO0EESuK6XaIvnHLJnf9Y3JHc1zy9IeSZz6SNMY8D4vD5wkOmSvYe/LwdaNSTCwqiwNceug8Lj10Hh/UtnLHK9t54D+7ePDtag7ZcxJfOnYBq+dPGu1pjh6GH4zJEKqAZBjiLV6GzyDwxJ4QBUYI23WI2FEak225ne8wIKXnp3PfBpf3d0PIgOP3Ehy7QDCrVMWhrvQp8Aghfo/nOHc08GfgXOD1XsYvBH4HTJVSLhFCLANOl1L+ODdTHj2+uP91bKl6t1uGSnYxJmUCqfnQuxjAKhQKhWJ0SDgJGs0WGs1mmq0Wmkzv0Wy10GyGabbC2FmMhIuNQkp9JZQaJcwMTafUV0ypr5gSo5gSXzElKVEnpAdVvFcoekEIwcF7TebgvSbzxrYmfvLIRn708EZue3k7139iX47dZ+poTzE3+ILew53s3XlPtKC7UOIrpMRXSNIxabOiRJ04cXNslWftaJH8e6Pkpe3eHfKl0+BTKzQOmAmGKr1SDCOLppXwX2ct5RsnLeLOV7dzy4tbueCPr3LYXpP51smLJm5GD3jloaFyCJZ5GT2xpkELPQCGplPmL0GXQSxfmDY7Mmw+pkNha5Pkzv94wk5ZEC5eLjhmL0GBT8WinuhPBs8hUsplQoj1UsofCCFupHf/nT8BXwf+ACClXC+E+BuQ9wLPsbOPpSI28JaCCoVCoRgZTNei0WyiPtlEg9lIQ7KJRrOZBrOZRrOJmNPZuFBDo9xfSrmvjHmFs1nuW0K5r4wyfwnlvlLKfKWU+IoxVBnpuEQXGj5D4NM1DE3g15Xf2kiyam4F911zCI9uqOW/H9nI525bx4mLp/KD0xczrXScdNfRdC+jJ1iWuvveDK6bNkUNmYW0aU24MpbVG2Mk2dokuX+Dy7oqCBhw7F6CkxYKppeovwnFyFIa8vH5o/fic4fN47aXt/HbZz/iE79+kfNWzuJbJ+9DxUT06GlHCAiWQqDEiyfx5kGVbrVjO1CYKgWPO3Fax4jQE05I7vqP5IWtkuIAfOYAwTF7CvyqHLRP+iPwtJ8Nx4QQM4BGYF4v4wuklK93OUEaeDsBhUKhUCiykHRN6pMN7E40UJdMPcxG6pONtFjhTmN9wsfkQDmT/BXML5zDJH85Ff5yJvnLmOQvp8QoViVSEwSBwGdo+HQNv+Yt60rMGXWEEJyydDrHLJrCTU9u5q8vbeXVj5u44ROLOWvFzNGeXu5ov/seKIVES/qiLGlBqa+YYqOQqB0j4kRHXOipaZXc847Lazuh0AfnLBWctLegyK/+PhSjS9Cnc9WRe3LR6jn88qkt3PrSNh5/bzffOXUfzjtg1sQW5IXwxONACUTrwYwO6jBWyn/HK98qIKSHiDgxInZkVERnKSXPfuyJO0kbTt9XcMa+goJxHI80BEVGYc6O1x+B52EhRBnwM+AtvCLhP/cyvkEIsWdqHEKIc4GBG9coFAqFYsIipSRst1GT2E1too7aRD21Se+52WrpNLbEKKIyMIl9ivei0j+JysBkJgfKmeyvoMQontgngBMYQ9Pw6V52jt/Q8GlZhDwhQDO8LAuhgxL7Ro2gT+f/O2Ufzth/Bl+5522+cu/brP1gN/915lJKC8ZR9rSmpS/K3Eg9MTPmrRYaxT7Pn6st1WUvl91KsxEzJf94V/LkZomhwzlLBKcsGt8XUor8pCTo43un7cv5K2fzrfvW840163lsQy3/e84yKosDoz290UU3oGS613UrWg8DNEy27c5xRghBsVFIgR6i1Woj6sRyOdteaYlLfv+qyzs1sGgKXL5KY+Y49tgRKWGnyCjEZwT73qGf9CnwSCl/lFq8TwjxMBCUUoZ72eXzwB+BRUKIXcBW4JIhz1ShUCgU45JWK0J1opZd8VqqE96jJlHXqZwqqAWYGqxkYdE8pgYrmRrwHlMCkwjquftSVOQvhuYJOX5dw+/zoRuGJ9poekrE0YCur7OcOCpBcFRZPKOUf37+MP7nsQ+47eVtvFfdyi8u3J/9ZpWN9tRyi24QCUzGKjTQ4/WIlOmyJjRKfcUUGQWErbZuZaW5QErJi9u8O+StCThmL8G5S1UHGsXYZ+9pxay55hD+/MLH3PjEZk78xXP8+sIVHLpg8mhPbfQJFIOvANpqwepf3HCk7DFLRxdeCXuhG6LZbO2xG2iueLta8rtXXOK21xXruAUCbRx/H4f0IKVGMYaW+y6SPR5RCHGMlPJpIcTZWbYhpczqwyOl/Bg4TghRCGhSyrFvza1QKBSKYceWDrWJOnbGq6mKVVOVqKEqXkObHUmPKdQLmBGaxqry/ZgenMb04BSmBaZQ5itRmTgKQICmI9HRfT4Cfn/q4UPTjN6FG0XeEPTr3HD6YlbPr+Cba9Zz0R9f5QenL+acFbPGVeemcMxC+kLYxmy0RBN6siW9TRc6Ff4yCp0CWqzcXVw1RCV/et1lfY3XXvgbR2nMrxg/v1PF+EfXBFcduSdHL5rClbe/yadueY0vH7eA645ZoM4TNB1KZ3oGzLGmPofbTt/ZPn7Nz5TAJNrsCK0Z52u5wpWSB9+TrFkvmV0G3ztUG9edsQyhU+YrGdabk71JRkcCTwOfyLJN0oPRshAiAJwDzAWM9j+0idhWXaFQKCYqlmtTnahlW2wnO2K72BHfxa54bbpDlSEMZgansbRkH2aGpjEzOI1ZoekUG0XqBG0iI3Sk8EQaqflAaEjhA01D1334Az6CPp2goaFnK7lSjCtOXjKdhVOLuPbO//CNNevZ1hDlumP3IujL/R3PkSZuOljtF1dC4IYmIY0C9FgdIqOTX0D3M0WbRMSO0mpHBl22JaXkuY8lt73pHeHSAwTHLxzfd8gV45uFU4t5+IuH8bV/vMNNT25hU22Emy7Yj4ChmiJQUAFGwMvm6cWA2eyHwANeckeJr5igHqDJbMmZCXPSlvz2FZfXd8KhcwVXHCgIjGMT5WKjcESsA3r8hpRSXp9a/KGUcmvmNiFEbybLDwFh4E0gOeQZKhQKhWJM40qX3cl6tkZ3sDW2k22xneyK16RPAAr0EHNCMzm68hDmhGYyOzSDqcFKdNWZagKigWYgNd0TcDRP0JHtPjh0iDZCCAI+QdAwCPo8c2TFxGPPymLuueogvnT32/zfsx+xoznGf525lJJQfvvytCa6Z+RIXwi7eBZ6vB7N6jBMFUJQ7CsiqAdptlow3YFl80RMyZ9fl7y2Q7LvFLj6II3KovF7ETVaKMP+kacoYPC7i1fwq7VbuPmpLdSE49xy6SrKCiZwl612/IVQOgtaq3tsp27ZAxOMvWyeybRYrUMuH40kJT97zmVLg9f6/NRFYtze4PMJgzJfKQF9ZD6X/bkFch+wosu6NcABPYyfJaU8aUizUigUCsWYJebE2RrdwUfRbXwc3cHW2A7iTgLwvHL2KJjFsZWHM7dgNnsUzGKSv3zcfmkrspDOwjGQupHKwNE9EacPUc/QNIJ+jZBPx29oKrtAAUBZgZ8/XHIAP/r3+9z12g5aYhY/O3dZ3rZStxyXaLKHBrOajlM4DZloRk90LrHwaQaV/oGVSnzUKPnFiy7NMbhof8Fpi8S4KnMbKxToQUr9ZaM9jQmJEIIvHbeQ2RUFfPO+9Zz7+1f4+xWrqSxW/nwYASidDa27wOkuDFsDNGQGT8is8JcRsP20WK2DyipsjEl+8ozL7jb40mEaq+eM35hUqBdQ6hvZjq29efAsAhYDpV18eEqA3v5iXhZCLJVSvpujOSoUCoViFGmxwmyObOXDyMd8GNnGrkQtEolAMDM4jVVl+zO/cA7zCucwNVCp7mJOCARoPqRmIHVfh4ij+8jMwukPfp8n6AR9Ov4RzNIRQmBoBj7Nh6EZ6WUlRo5Ngn6dH5y+mIpCP79++kOuuestbr5gP/aoKMy7f7NwvO8MHDdYjtQD6NHdCDouwtpLJQJagCarBaeXUom1H7rcuk5SFoQbjtfYa3J+/Z7yAV3olLf7aajvvlHl7BWzmFwU4Irb13H+H17l7itWMzVPReCcohupTJ5dYJvp1RKJaQ++DXqhUYBPM2g0e49DXWmKSX78lEs4Ad8+WmPfqeMzLmkIyvylFOgj/xnsLYNnb+A0oIzOPjxtwBVdBwsh3sXz5jGAy4QQH+OVaAlASimX5WjOCoVCoRhGms0wmyIfsqntIzZHPqbebAQgoAWYXziH08qOY8/CucwvnKM6WI132rNx9JSYo/mRugFi8B4o6dIrn0GBb/i9dNqFG5/uS4s57c+K/MLQNb507AJKQj5+8shGrvvb2/ziwv2YN6kob7JSHFfSlughe6cL0leAXTwTI1qb7rLVjufNM5lms4WE29kRwXE9r50nt0iWTYPPH6JREsyP308+UaCHKPWVoCthZ8xwxMJK/vKZlVxx+5uc/4dXue+ag5msMnm8EuiSmZ1EHsuRMEhPr3baDZgbzeZ+lY42xyU/XpsSd47RWDBORWef8FHhL8M3SucZvXnwPJRqi/5NKeV/9+NYp+VuWgqFQqEYKaJ2jA8iH/LB/9/efYdJclWH3/+eyp178mZlrfJKYlEkSCCSAEmYDCbZGGNjwK8DyTYmGGxMsP0DGwwYY5KxAAUkkhBICAkklDZotcpxg7R5J890d933j67ZnZ2d0D3TobrnfJ5nnunprq66Nd19u+rUuecOPMh9Aw/z9NhOoHzwelz6aC7oOY/j0kexMrFM6+a0raiose0eyMgxtjvnkKpKiQiBa5HwbBKuXfOhVyKCa7l4tlcO5lgHgzmtlt2hZufYFm8970gcS/j4tffy599dx2dfvYZjejPYLRDk2T9SwMxS9PQwtkcxvRxncDsyJZBji0W330l/YeDAkK3BccO/3Rxyz1PwshOF16/RIVm11swr82puzzquHOR569dv501f+x2X//G5ZILWrtlVE5YNmWXQvwVKxYNF3hfIFpser4u9hX0MR8P1pzM4bvjkL0P2jJQzd9o1uJO0E3S4uaYee8waVjLGlETkBcCcAR5jzOMAIvJNY8ybJj8mIt8E3jTtE5VSSjVU0ZR4dOhxNvU/wL0DD/D48BYMBt/yOT59NM/pPpvV6WNZkViqw63akeVgLBdjexjxyoGcOlxlqkdQZ9pATpSZoxYP17Z449lHIAIfu+Ze/vr7G/jsq9dwRHcq1sW4S6Ghv4LhWYexbIqZZdiD27GmOYHKuhlcy+XBvXv55I0hTw3AO88Rnnt0fP8XrcqzXDrdvGYAxtx5x3bz+dedwZ9++07+4Ou38623n62za0F5uFZ2OezfQmGamjzzJSJ0eh3YhQEGpqkPVigZPndTyPYB+MAFFqt72jO4k3OzZJxUs5tRUZHl34jIF4D/Aw6U9DfG3DXD8idP/kNEbGYuyKyUUqoB9hX6uaf/Pu7pv497+x9kNBzFwuKo1EpetuQiTswcx5GpVTiaodNeLK8czHG8A0GdamvkVMt3LZK+Q3KBQR3HcvBsD8/ycG33wG+lADzH4nXPXEWhZPjkjzbzt1ffwycuO5WVnUk8J56Bjf6RAmE12TuTiUUpvQyGnsIqDh/28Lb9Nn//c8NQoXx1/OQ2rWvRTGk7Sc7NalZgi3jRKUv4xCtO5QNXbOR939vAv77udH3tAGwXssso9D9c81Xn3Ay2WOwr9B+4LzSGL91q2LwD3nWucMqS9nsNLIROLx+bsgWVBHjOi35/bNJ9Bnje5IVE5IPAh4CEiEy8qgKMA19eYDuVUkpVwRjDEyNbWb//Xjbu38zjI1sAyLs51nacxsnZ1ZyYPo6koynmbcNyyzVyHC+qleNR/hquP8e2SPk2Sc/GqbKmzuSsnImAjmd7mj2m5hS4Nm88exUj40U+9/MH+Ycf3cuHX34Sy/KJ2F2tL4WmouLKsxKhlFpyWJBn044x/upnuwgc4Qsv7SaXGqRgand1frEThA4dktWSXnfWKh7bPcSXfvUIJyzN8CcXHNvsJsWD4zPidyOF7TVfddpJYYnF3vH9GAxXbzL85nHDa9cIzzqq/b7XHbHp8jqbVm9nOnO2xBhzYSUrMsb8I/CPIvKPxpgPLrhlSimlqlI0JR4YeJh1++9h/f572VvYjyAcnVrFK5a+hFNzJ7A8WKpXsNqB2OUhVraHsXyMU//MnKksERKeTcp38CvMmJgczPFt/0BAR9+Tar6SnsNbzj2KwbESX77pEfLJh3jv849lacyCPPuGx+efvTPZlCDPndtG+eDPd9OZsPiXl/SwNOMQGo8943sZDcfnXp+aVfnkraOiYaDGicfVe3Wo973oBO5/aoBP/+x+ju/L8PwT+5rdpKYrlkKKThIr6MQe3VPz9SftBJZn8cvHdvO9DYbzjxAuPan9vuc9y6XL64xdofWKQk0i8lLKQ68O9FzGmI9Nt6wGd5RSqnEKYYFNAw9w194NbOjfzHBpBFdcTsmu5tLcizg1eyIZN93sZqqFsjxC28fYfjkzp4lXinzXIuU7JD0bmSNDyLEcAic4GNDRYI6qg1zS5e3PPoq9Q+N8784tdKc9fv+cI+jLBgRu84M8hVJIf4UzZ1VEhFKqj99tfoi/uW4XK7IOn31xD93J8r5aYtHldbK3sJ/h0kjttrvI+JZXritSwclb6CQJU0sb0CpVLcsSPv/6M7jk32/hLy5fz4/f82yWdyzubKzxqMByGHQgxdFph30u1J5hmy/8xrAyD28/W9ruuz+wfDq9fCyzjec8QhSRLwFJ4ELgq8CrgN/VuV1KKaVmUAgLbOq/nzv2rWf9/s2MhWMk7QRrcidxRu4UTswej295zW6mmjeJhloF5Qwdx6fR2TlT2ZaQjLJ1Zipia4l1IJAz8WNbzT+5VotDT9rnvRcdx+6hcb7y60fpyfi88KQlLMk1P8izd2i8upmzKnDbY3v58HVPcWTe419e3EUuOHQfy0VP81jjwmCp9idv7a6amXBCN00p2dt2J7DtJB24fPGNZ3Lpv9/Cu//3Li7/43NxYlyQvd7Giwdn0Cole5HBrUgF05xXqhgaPnLDbgzwied34bv9lExtZu2Kg5SdJB/jelwV1eAxxpwmIhuMMR8Vkc8CV9S7YUoppQ4qmRKbBx7k9r3ruHvfJkbDUVJ2kmd2rOEZ+dNYnT5GZ/VoWVFAxw2iDB2fRtXOmYvnWqRnyNaxLZvADvAdn8AOcC03tgc7qv2JCEuyAR98yQnsGRrj0z+7n96Mz+l0NDXIM1ooMThWw+wd4LZHd/PhqzdxRFeKT7/yJLKFHWCm30beyyEFa9qZbdT0sk6arJupaNmJ4A7a98Xe6iVZ/u5lJ/E3V97Dp392Px+8+MRmN6lpJgd4sGxKyV7swW0ItQlE//dd/WzeWeBjz+vkyHyCQuiya3wPJVOqyfqbqZr+oRrGq93sW5WcDUzkdg6LyDJgN3DUTAvPNE361PuUUkrNzhjDo8NPcNueu7lj3zoGikMk7IAz86fyzI41rM4cq7Netahy3ZwooOPEJ6AD5RPlhGeR9t1DautMDLeaCOro1OQqbhzbYmVnko9ecjJ/9p27+fDVm/j868/AAEuyAQmvsf2lMYadA2M1Xeedj+89ENz5zKtOI5twKZaW4gxsRZj+CnnOzWAh7C8O1LQt7ajDzZFykhUtq8Gd1vPGs4/glod28ZVfP8KFJ/RyztFdzW5SU4wVD+0rjBMQBnns0b0LXve67WN8c/0AFx+X5MKjyp8l13Lo8TrZNb6HYgsHearpH6oR2gES1O69WEmA51oRyQOfBu6iPIPWV2ZZXqdJV0qpBdg1todb997JrXvuYsfYLlxxOC13Emd1nMEp2RNiValfVchyMHZAaAflgE4MA3O2JaR9h3TgYIlgWzYJJ6EBHdVSAtfmyK40//h7p/Jn37mbD115D194wxkA9GZ8Un7j+s+9wwUKpdoNS1i/ZR9/e9U9rOxI8ukouAOA7VFKLcEe2j7jFfiMmwYR9k+avlgdJAhdVUxzHLopDe60qH98xanc+fhe3v/9Dfzkvc8m2cA+IQ7C0EzbL4V+B1IYwSqNznvdw+Mhn7hpD8uzDu89N3/IY47l0ON3sWtsD4UZMg7jSqJp0BN1mAbdYFFK9uLUsC+pZBatj0c3fyAi1wKBMWb/1OV0mnSllJq/sdI4d+3bwC177uCBwYcBOD59DC/uu5Az86fq9KwtR6LsnIDQSUCMgyOObZFJOGQ8l4SbIHACEnYC145vm5WaTS7pcmxvho9dejJ/+b31fOSHm/jnV53G0/2j9GYD0g04oRstlNg3XLtZrDZv7+dDV9xDXzbg068+jVzi0M+ncROEiS7skV0zriPjlIcAaJDnUBZCl9eJb1dWuy50EpSSfRrcaVG5pMcnLjuVt3/jDj75k838w2WnNrtJDTU+U9BZhFKyBxnYMu+hWl++s5+nB0v8+8t6SLqH1ziyxab7QJCndjV/6slC6PQ6CGy/LusvJbuhxsdblRRZDoA/BZ5FOXvnZhH5ojHmkPBePadJF5FO4P+AI4HHgNcYYw7LIRORx4ABoAQUjTFra9kOpVQrsIjTcJfZGGN4bPhJbt79O27fu47RcIwer4tLl76IczqfQZfX0ewmqmqIjXEShHYC4za/MPJcfNeiO5WiM5Eh4SZ0hivVVnoyPqev7OCvX7SaT/74Pj738wd434tWs6N/lFLKJ5esXwCzFNZ2aNYjOwf5wBUbySddPvPq0+hITh+ICP0cUhrHGp85gKNBnkPZYtHtdVacoRjaQXmaeu0rW9pFJ/XxijOW8e1bn+Clpy7l3GO6m92khhkrzJJVaHuEQSf26O6q17vx6TGuuHeQ3zspzal9MwdDbLHo9jvZPb6H8RoWdq4HW2y6vY66ZTCHbgrj1b6eTyWXML5BOWjy+ejv1wPfBF493cLGmA+KSAdwHIdOq37TAtr5AeAXxph/EpEPRH+/f4ZlLzTGzHz5QinVBqQ85MVyysVpLTv62y0PfYn5zD1DxWFu23sXv951G1tHn8KzXNbm13B+1zM5NnWUnmS3EssjdBIH6unEnSUWnck0veks+SCls1yptmVbQm/W56IT+9iyZ4Rv3Po4R3Qmed1Zq9g9NEYxDOlK1+czu2NgtGZDs7buHeGvv78Bz7H4zKtPo3uONpcS3VAan3WYhQZ5ysonb50VD3s2lhsFd+IdvFeV+cglp3DzQ7v5u6s28eP3PAuvybPtNcpYafYaOKGfwxofRMLKg9TjJcOnbt5Lb8rmHWuzcy4/EVjdPb6XsbB2mY615IpDl9dRtwlMjNjl/roOKmnxamPMmkl/3yAi62daWETeDrwXWAGsA84Bfgs8bwHtvBS4ILr9P8CNzBzgUUq1C7ExllsO3NgORqIgTgvWoDHG8MjQ4/xq12+5Y+96CqbIEYkV/P7KV/LMjtPrMq5X1Yex/PJwCCfZEu9Fx3JJOAm6kml6Mxl8Z3EcxCoVuDYdSY83n3cET+wZ5iu/fpQVHUmedVw3+0cKFENDT9rHsmoXVN89OMbIeG2KiO4cGOOvvr+e0MDnXnUaS3MVDNUVoZTqKw+zmKWYacZJgTGLtvCyEwV3Kj15M2JTTC2J/QUkVblcwuWDLzmBv7h8Pf/560d49/OOa3aTGmLWDB6Ihmp14wxurXid3904wOP7inz6hV3TDs2ajjUpyDNaRTCpEXzLo9PrwK5jMLeU6K7bMWQla71bRM4xxtwKICJnA7fMsvx7gWcCtxpjLhSRE4CPLrCdfcaY7QDGmO0i0jvDcga4TkQM8J/GGK39o1TsCVhuORvHdjHiYmwn6vTa4yrZSHGEt/3iD3lg34P4ls+5nWt5dvfZHJFc0eymqQodCOq4SZD4B3U8248KJCfJJwLySQ/PaY/Pk1LVyCddRgol3v/i1TzVP8onf7yZf3vd6RzXl2ForMh4MaQvG9Tk87F3aJz9I7UZcrBveJy//v4GBkeLfPY1aziiq4opdC2HUrIPZ2jbrItl3DQGQ/8im0LdFYduvxO7wmL3hnLQjApr9KjW8YozlnP5HU/yxRsf5tLTl7Gqs3ZTVcfRTAWWpzJOQMnLYY8fVnb3ME8PFvnm+gGee2SCc1ZWVy9SROjyOthX6GeoNFzVc+slaQd0uPm6ZtOHTgLjpeu2/kqOUs8G3iwiT0R/rwI2i8hGwBhjTpuy/KgxZlREEBHfGHOfiKyeayMicj2wZJqH/qaCNk443xizLQoA/VxE7ptuaJiIvAN4B8CqVauqWL1Sat7ExogDdhTMmcjMaYEMiMnm038knASndJ3CMzOncnbHGRXP0qGaq9WCOr4dkHCSBE4CW2zSvqOBnZjR44/GExF6Mj7jxZCPX3oy7/rO3Xzoqnv4jzecSU/Gp1AK2bpvhM6Ud1jh4mrsHhyrWXBncKzI+3+wkaf6R/nUK0/l+L7qazQYN0Ep6MQe3TPrclk3gwEGFkmQp9rgDkAp2YNxmj/RgfYftScifPSSk3nZ52/m49du5itvbu/yrTMWWJ5GGHRgFQZnzQQE+I/f7Sc0hnedlZtXm0SEDi+HXbCaHmzOOmmybu1r4kxmEEqJnrpuo5Ij1hdXuc4t0bTqV1EOsuwFZr+EABhjLprpMRF5WkSWRtk7S4EdM6xjW/R7h4hcCZwFHBbgiTJ7vgywdu3a+ZUJV0pNz3KiLJxyIOeQ2jhtYL79x1+d8Rfc8/CtdWuXqhHLIXRT0fCr+M8iNTWoA5DyHfJJV4dixZAefzSHa1t0Z3xCY/jEK07hvd9dx99cdQ//9trTSXg2xhh2D44xPF6kK+VXFRQtlkJ2DY4zPF6baX9HCyX+5sqNPLpriI9fdjJrVuTnva4w6ECKo1jF2a+M59wMxoQMxuQKer244kbBncpf35LfUZciqPOh/Ud9rF6S5U3nHMHXbnmMWx7axfnHtm/B5bFiFbXBLJsw6Jh1Zr67t4/yy0dHeNsZGZZmFnYhLOtmcMRmb6EfM89ZvOZLKAeZGjFjbRjkaz5r1lRz9nDGmMdn+5lm+VcYY/YZYz4C/B3wX8BlC2znD4G3RLffAlw9dQERSYlIZuI28ELgngVuVyk1E8stzxjk5SgFXRRTSyhmVlJMLaOU7CH08xg3jbGDtgnuqDYlNqGboZTso5haRujlYh3c8WyfnN/BktRyuhO9pNw0ttgErs2yfIK+bKDBHaWmSPsOad/hmJ40f/eyE3lk5yAfu/ZeSuHBE4mR8RJb9g6zc2CM8TlOhIwx9I8W2LJ3pGbBnfFiyN//cBObtvXzoYtP5Oyjuha8zlKyF1PBd3Dey5GykwveXlx5VvXBndBJEiY669gqFRfvef5xdCRd/ukn91GsUYH0OBorVlcfLPSyGGuGWfuM4fO37acvZfOG02oTBE06SXqqzLBbKFccev2uhgR3jOUS+vWfIbeuedvGmF8ZY35ojFloeex/Al4gIg8CL4j+RkSWiciPo2X6KE/hvh74HfAjY8xPF7hdpdREIMfPUQq6JwVyllJK9BD6OYybAsujVaYnVwrA2Inyezq9jDDoiPUsWI7lkvVy9CWX0ZPoI+1mDhwAubbFklzAsnyCYJHMAqLUfHSlfRzL4uyjunjv84/jtkf38C/XP4Axh14tHhgtsGXvMFv2DrN3aJyB0QKjhRLD40X6RwvsHBjj8d3D7BoYIzS1udJcKIV89Jp7uf2xvfzlC1dzweoapfBbNqVkX0WLNuoKdqN5lku3V11wx1gupeRMJT9Vu8knPd514bFs3LqfK++uvLhwq5mzwPJUIpQS0weaf/HICA/uLvCOtTmCGg4F9yyPXr+bwKr/MVnSTtDjd9VtGvSpSkEXNGCm3PgXFQCMMbuB509z/zbg4uj2I8CaqcsopSp0oNCxN6nQsYsGbVRbmRiC5aZiX1fHEoukkyLppHCnKe7pWBb5lEvGd+paDFCpdmFb5Xo82/eP8PI1y9g5OMa3bn2C7rTPW8878rDlx4sh48X6T+FbCg2f+NFmfvvIbt77/ON4ySnTlaScP+MmKPl57LF9cy7b4eYAw/As06y3Et/y6PI6sKoJ7iAUU306Y9Yi86ZzjuBbtz7Ov17/IBefupSUH+9jhGpVWmB5KuMmCZ0EVnHkwH3jJcNX7tjPcZ0uFx1T+6CwLRbdficDxSH6CwM1H7Jli0XezTV0BtvQDjBeY4p4t9c7Vyk1twM1crwDM1dpIEe1O+MkCN0Mxol/gevACUg6aQI7MW3gRkTIJVzyCbem0zsrtRgkPJtcwmX/SIG3nXckuwbG+cZvHycTOLzyzMbPbFgohXziR5u56cFdvOvCY7j09GV12U4YdGIVRpA5piMWETrcPIZ9jLR4kCeIpjquJrgD5WFtxDijU9WH79r85QuP593/u45v/vYx3nnBsc1uUk1VU2B5qjDoxJo0bfoP7xtk+2CJz76oA6uOF5gyToqE5bOv0F+zqdRTdpKsm6nrFOjTCWfIhKoHDfAo1a7ELs9UFQVysMqFj9tl6nGl5iQ2oZduiWwdx3IOZOvYs8wsl/IdOlMerq2fY6XmqzPlMTxeolAK+csXHs/QeJF/v+FhAsfmpactbVg7xovlYVm/fWQ3f3LBMfUNMIlQTPXgDGxF5rgaLiJ0unn2tHCQJ7B8uryOqrMbQy9b1+mLVbxdfMpSvrz8Eb5686O8/qxV5JLT159pRVUPz5rEOAGhm8IqDDE8HvL1dQM8Y5nPM5fXPxDqWOWZ70ZLo/QXBxkP5zdbYcIOyDrphg3HmqzRFxj1CFGplifRdM5pQj9PKdFLMb2cYno5pWTvpGLHPvqRV4uBsfyDtXW8XKyDO4GToCvooS+5jIyXmzG449oWS3PlAsoa3FFqYUSE3qyPiGBbwt++9ETOOqqTz/38AX56z1MNacPweJG/veqeaFjWsbz6GQ3IHrJ9wqCyosETQZ5G1MGotYQdzCu4YyyfUqJ9Z1BSc7Nti/c873h2DY7ztVsea3ZzaqraAstTlYJyceArNg+yfzTkHWtzDR0eHtgBvX433V4nSTuBVcHIA0dsMk6KJX4PXV5HU4I7Bjnwv2uU+B71KqUOd0idHC8aXqUfY6VAME6Skp+JCn7HlyUWKTdDao5snfKyQkfSI5vQOjtK1ZLv2HQkXfYMjePaFh99+Un87dWb+Oef3c/weJHfq2M2zZ6hcT54xUYe3jnIX79odc1r7swmDPJIYQirgswcEaHL62BPoXUyeZJ2gg63+hNPg1Wuu6P97KL3/BN7OXNVnm/89jHedO4qutPxH9pdidEFZPAAYPsMmgT/u3Eb564MOKmnOcdage0T2D7GGAqmQCEsUjRFjClX6rHFwhEb1/JwY3COFHrZuk+LPlXz91opdbiJ4VUTw6qioVZaJ2dmjuXi2R6u5TV0ekXVZGITumlCL/7DsDzbI+VkSDjJik4+Ur5DV8rD0Ywdpeoil3AZHi8xWijhuzafuOwU/uFHm/nCDQ+zf6TAW847sub1JR7eOciHr97E3qFx/uGyUzjn6MbVZZhQSvYiA0/OOVQLDmby7GVf7Asvp+0keS83r+eWkj0NPwlT8WRZwnuefxxv/e/b+drNj/G+F5/Q7CYtWLEUUgwXPv37D+4bo38s5G1nZGvQqoURETzx8GJ8Uc8ghEG+4duN99GwUovBpECOsaKsnJifqDbbwWCOG0XovUOKKGqmwyIgNqGfLdfXifnQw4STJO1m8Cos2ulYFt0Zj6Sn/YBS9SRSnlVr694RQmPwHIu/f/lJfOa6+/nmrU/w2O5hPvDiE0h4tblocP3mp/nsdQ+Q9h0++5o1nLi0SSdJtkuY6MIe2VXR4iJCp9eBjO9nqDRc58bNT87JkHHnVztH6+6oqZ5zXA9rj+jgf3/3BH/4rKPoSrfeUMXJxooLD+4Mjxe5/K5tnLsqxYlNyt5pNaGfa8pICz16VKphrINFjzUrp2KO5ZQDOpaHZ/uHBXPUImO5lLwsxk0S58+OJULSSZNyMzhVfLlnEy6dSU9nx1KqQVzboivtsXOgPEOLbQnve9Fqju5O8Z83PcK7vnMXH7r4RI7tnX8AYGC0wBdvfISfbnqK01bk+PDLTqIz1dwTpNDPlYdqTZr6eC4dXg6rIAwUh+rYsuoIQoebJekk5/V8Y3lad0cdxrKEP37u0fzRN+7kW7c+znsvOr7ZTVqQWgR4rl63jf7RIm867wRg34LX1+4MFqGfb8q2NcCjVD1YzsFgjngYR7NyKmGJFWXm+HiWh2vrcCsVsTxKXg7jJprdkllZYpF2MyTddFXvXde26Mn4BK6+35VqtEzgMjJeYnCsCJQzVl69diVHdaf4x5/cxzu/dSevP2sVv3/2KvwqPqOhMdx4/07+48aH2Tc8zhvPXsVbzj0iNsMuS4meiodqTci5WWyx2Vfor2PLKmOLRYebJ5jnlOYGoZjq1bo7aloXru7l5GVZvn3bE7z53CPpaHJQdiEWWmB5vBjy/Tu3sPaIDk5Y3kU4OI5VjGc2X1yEfhas5hzT6RmnUgsiGMsDe2KI1URWTjwO3uJMRHAt70Agx7P8qjId1OJgLJ/Qz2KceAd2bMsm7WZJOemqhwjmkx4dSVeHFirVRF1pn9HCoXUq1h7ZyX+/9Zl88VcP8+3bnuDHG7fzyjNXcMmaZaSDmb+vxgolbn5oF9++rTzM69ieNJ98xSkc35dpxK5UrsqhWhPSTgpbbPaM78NUERyqJVccOr2OBRVRDYNOmGdwSLU/x7b4o2cfzZ//3zouv+NJ/vi5xzS7SfO2kCnSAa679yn2Dhd43VkrAQiDDqxBDfDMxCDl4VlNomdTSlVqovCx7U8qfuwQ52EicTK5CLIX1c3RE1o1I8uj5OdiH9hxLIe0myXppKp+P2vWjlLxYVvlqdO37Tt0yFI24fL+F5/Ai09ZwrdvfYKv3vwoX//NY5y8LMuZR3TQl/HJJlyGxko83T/KfU8NcMdjexgthhzRleRvX3oizz2+Bzumwy5DP4eMD1Y0q9ZkCTug1+9i9/heimZh2QHVStoBeTe3oOHaoZNsSvFT1VpecsoSvvDLNN+89XHeePYq0kHrFeIeK5YIzfwDsaXQ8N3bn2T1kgxnrMwDYJyA0A6q7jcWi9DLNnWWYw3wKDUdyzlQ8FgLH1dPh1qpebNcSl4+9kOxHMsh4+YqnhFrqlzCpTOlQU6l4iRwbTpTHnuGxg97bM2KPGteleeBpwe48f6d3P7YHv77lscOW6434/Oik5dw/rFdnHlER81n4aqHUrIHGdhS1VAtANdy6fW72VvY35Bp1AUh52ZIO6kFrceIXZ41S6k5+K7Nm889gg//cBPXbtzO6565qtlNqtpC6+/8+sGdbNs3ykcuOfqQY5bQz2MNP7XQ5rWdZs2cNZmesapFTg4UO9YhVvPn2i6e5eNZPm40u5VSVbGcqMbOwg7c6822bDJubl4ZO1CeIasn49dsVh6lVG3lkx4jhRIj49NnpRzfl+H4vgzveM7RDI0V2TdSoH+kQMKz6csErfnZtj3CoAN7dE/VT7XEosvrYLg4zL5CP2Gdhmx5lkuHm1/QkKwJpURPU6+uq9Zy2RnL+cIND/Gd257g0jXLW+4zPlqYf4adMeXsnRUdCc4/5tBi5MZLYUY9JDw8IL6YGS/T9P5Feze1iESzWDmTh1i56BCr6kxk53iWr7NaqYUTm9DLEHoZ4vxZtMQi42VJOZl5Z92kfYeutB/boRpKqbKetM+2faOH1OOZTsp3SPkOy/PxzjisROjnkcLwvIdcJJ0kvu2zr9Bf02weWywyTnrBWTsTylOix/tCgoqXbMLlNWtX8IUbHuY3D+/i+Sf2NbtJVVlI/Z2NW/fzwNOD/H8XHTftsUvJz+GM7FxI89pOqYm1dyZogEe1J7GjoVXewawcvVozL47l4tuanaNqTQi9LKGfIc4Zc5YIKTdL2s3MO5BpidCV9si04Nh9pRYjx7bozfps3z+KWUDtipYiQinZjQxsrXqo1gRbbLq8DsZK4+wv9jMeFubdHAsh5aTIOKmaXUQylksp0VWTdanF5Q1nH8F/3/IY37r1cc4/trtlaucVSyGF0vwDPN+/cyvZwOEFJ00f1DJeBjO6B2lwHa64Cp0k2M2fbU3PeFXrO6xejgda72VeRCTKzPEOBHS0do6qNeMkKfn52AddU26ajJdb0GfAcyx6MwGeE98gllLqcBP1eHYPjjW7KY1j+4RBHnt074JW49sevXY34+E4g8VhRkujFQ/dcsUl5SRI2omaZweXkr2gGcdqHpbmAl6+ZhmX3/Ek9z3Vz+krO5rdpIqMLqD+zrZ9I9zy0C7ecPaqmQNaIoR+dsF9Rrtodu2dCfE+ulZqKss7MLyqXDdH6+UshG3ZhwZ0dGYrVU+WRynIY+yg2S2ZVeAEZL2OBWerZRMuXVpIWamWlUu4jBVLDI4Wm92Uhgn9DqzxoZrU1fAsj07PwxjDWDjOWDhOyRQpmhITiVG2CI44uJZLYPt1u6hUCjowTry/e1R8iQhvOucILr/jSb77uyc5aWmuJS7cLKT+zhV3b8W2hEtPXzbrcqGXxRrdN+/Mv3YR2kFsZn7VAI+KKTk4xCqqlVMO5uiJ0kJMLobs2T5OzDMoVJsQuzzluZtudktm5Vgueb8Df4EBKEuE7oxP2tfPl1KtriftUwrNjEWX244IpWQPzuDWGq5SCGyfwPZrts5qhHZA6LdGxoWKr+OXZHjWsd38aON23nXhsazsTDa7SXOab4BnaKzITzY+xQWre+hOz/G5tRyMm0IKg/PaVrsIY1B7Z4IefarmE/tAnZyD9XK0VsVCiQiu5R1SP0eHW6lGC90MoZ+N9bBJS4SMlyflpBecbaNDspRqLyJCbyZg276RBdWyaCXGCSj5eeyxfc1uyoIZygErNJNSLZBrW7z+rFXc9OAurl63lXc+9xgcO77f9WFoGJ/nEK2fbXqakUKJV565orJt+TmsRRzgMeLEahZYDfCoxpoofux4GJnIztG3YS1YInj2wewcz/J1aIhqGmOVazmYJl2xrVQt6uxMSAcOPWn93CnVbmxLWJIL2F7BzFrtIgw6sQrDLT8FcinRHYuip6o9PPu4bo7pSXHFXVt5/Vmr6Joru6WJRovzy94JjeGqdVs5aWmG1UsyFT3HOAGhHcx7Fr5WV76QGZ9jPz2zVvVjuQfr5Vh+OZgT46v4reZg/RwfP8rQUar5LMIgR+hWdlDQLK7tkvMWPhwLylf4O1MeuYRmHirVrlzbKgd59o9QChdBrYloVi1ncFuzWzJvoZPE+NlmN0O1kZTv8KpnrORTP72Pmx7YyaWnL8eaZvrwOBid5/Todz6+ly17R/jQxSdU9bzQz2INL74Aj4lmhY0TDfCoGijXy8F2J81k5aLFj2vLsZwDmTm+HWj9HBU7xklQCjpA4vveFBGyXo6Uk6lJpo1tCX3ZoGWmTFVKzZ/nWAcyecJFMH26cRItO1TLiFOeNUupGhIpFx3+4o0PccXdW3neiX2xvbgz3/o7V929jY6ky3OO66nqecZNY2T3opsy3XgZsOJ1DBjfo3AVT4fVy3GjejnxjF63Msdyy/VzogwdWwM6Kq7EpuR3Ytx4zB4wk8AJyHmdNQuOeo7FkmwQ6zH4Sqna8h2bpfmAp/aPLopMnlYdqlVK9sbupEu1h56Mz0tOWcL37tzCwzsGOWNVPnZDs8PQMDaP+jvb949w6yO7eeM5q6qvJShC6GVaMiC8EKUYZgnqGaOameUcDOZovZy6m5jhyrcDvDpOFapULRknRSnIx3r4pSUWOb+DpFO7Anhp36Eno/V2lFqMfMdmaS7BU/sXQU2eOsyqVW8lPx/7Cw6qdbm2xavXruTyO7Zw9bqtHL8kE7tZM0eLJcw8sgyvWb8dEXj5abNPjT6TxRbgCZ0ExLDWZLzejapJ5MA05OUhVhNTkutV6XrybO9gQWQN6KhWIzaloBPjxPsgOuEkyfkdNf18dSQ9OlJa80qpxcxzLJblA54eGGNsnkMhWoVxAkpBB/bo3mY3ZU6hHRAGnc1uhmpzJy7N8swjO7h243b+4FlHxS7AMzJefZ80Xgz5yT1Pcd4x3fRk5hm0sD1CJ4FVHJnf81tM3GrvTIjXu1HVnw6xapqJgM5Eho4lGkBTrck4KUqJDuIcBK5H1o6I0J32yATxHG+vlGosx7ZYlgvYOTjG4Gix2c2pq9DvQAojsZ4lx2CVh2ZpZqWqs6Rnc9kZy/nQlfdww307eN1Zq2JVi294HgGeXz+4k/0jBS5Zs3RB2w697KII8MRtavTJNMDTtmTKLFYexnZiXfy03Xi2Vw7mRFk6GtBRLa9lau0kyPudNc3a0WLKSqnpiAi9mYCEW2D34Hj7Fl8WoZTsRQa2IMRzWFop2QO2BuBV/YkIF53Yx79e/yBXr9/GS05dGpvjg2IppFCq/jP6w/XbWJYPOPOIjgVt37gpjNhtX2w59DOxDSa3xBmniLxaRDaJSCgia2dZ7sUicr+IPCQiH2hkG5tKbIydIPSylIIuiqklFDMrKKaWUEp0EXpZjBNocKfOPNsj42XpCnpYmlpBT2IJWS9P4CQ0uKNannESFFNLYh3csUTo8LvoCnpqGtxxbYuluURsDt6UUvGTCVyWd7R5P2G7lJLdzW7FtEpeDuOlm90MtYjkki4vX7OUu5/Yx33b+xmfR1HjehiZx5DRR3cNsXFrPy8/bRnWQoMWEr9pw+shzvvYKmf89wC/B/znTAuIiA38O/ACYAtwu4j80Bhzb2Oa2AiTpiO3nIPTkWvtlqbQDB21OAiloAPjxvvA2bN9Ovyums2QNcF3bZZkA2wrnldplFLx4doWy/IJ+kcL7B0ab8tZtoyXISyMYBUGmt2UA0I7IEx0NbsZWuxgkfEdm0vWLOPrv3mcazds5+TlObrTzS+4O58Azw/Xb8O1hRefvKQmbSgXW45/za75Ct1UrCceim/LJjHGbAbmmq3kLOAhY8wj0bLfBS4FWjDAI5NmsHJ1BquY0Bo68ec5FpnA1ZPxWrE8iomuqE5XfGW8HBk3W/MZrZKeQ2/Gx9L3k1KqCtnAJeU57Bsep3+0OK/ZbOKslOxBBsaRcKzZTcGITSnVF4uhEklPL7guNkd2pzn/2C5+tukp3v7so+hIek0/Bq22wPJIocT19z7Nc4/vIZes0fGe7bZ1seXQyzW7CbNqp4jBcuDJSX9vAc6ebkEReQfwDoBVq1bVv2WzsSZl41huuU6OFj2OBdd28a1AAzoxZ4mQDhwygYPv1P/gKlb9Rx2FXpbQzxHnvsi2bDr8Lnw7qPm604FDT1qnQVe1tVj6D1Wu29WV9skmXPYOjTM41kZFmEUopnpxBrY2tR6PQcrBnZhcAK13AX7tP+In7TtcsmYZNz2wi5se2ElvJmjqLJtjxVLVmYM33LeDofHSvKdGn0m7Fls2lhvrcgUQowCPiFwPTJcX9jfGmKsrWcU09037DjfGfBn4MsDatWsbc1nlkECOo7NXxZBru4dk6Oi05fGW8GwygUvKsxt6Et6U/qORWmT688AJyPtddfmc5hIuXTFIs1btp+37D3UY17bozQbkiiX2DRcYapdAj+1RSvbiDD/VtCaUkr2x+a5ybYtEnTN4tP+IH9sSzj+2m2X5gB+u384LT15CPuk27eLQfKZHv2bDdo7oSnLK8trWlGnXYsuhl6nLej2ndokEsQnwGGMuWuAqtgArJ/29Ati2wHVWSQ4GcmwXI5qRE2eO5eLb5fo5vh1oQKcF2JaQCVzSvlPTjlCVGcunlOyKfUH2nJ8n7danuF1nyiOfbN7VN6VUe/Idm76szWihHOgZHm/9QI/xUpTCLuzR3Q3fdinoiFVR5UwQ7+9NVT/ZwOVlpy7ly79+lId3DtKR8sjWOZtrJkNVBngefHqA+58a4M8uPKb2QSmRqBbPvtqut4kM9SsgXcsAcTv1RrcDx4nIUcBW4HXAG+qyJbEx4kwqdlyejjwuKaJqeo7lHMjO8S0fW1+vlpHwbLKBS7LB2TqLyWIfkgXQlfbJJeJdb0gp1doC12ZJzmZkvMTuobHYzLwzX2GQR8IC1nh/47bpZQmDzoZtrxJpX48pF6ukZ/PS05bytVse49oN2zmuN9OUAE+xFDJWZYHlazdsx3MsXnBSX13aFHrp9grwuCmw6pMQkKjhDIwt0RuJyCuAzwM9wI9EZJ0x5kUisgz4qjHmYmNMUUT+DPgZYANfM8Zsqm1DbIrp5TprVYuwLRvfDqI6OhrQaTUT2TqZwMG1NVunfixKQVfsxxN7tk9n0F23TLuejF/3+glKKTUh4dms8JL0jxbYMzhO2MKFmEuJbjAlrMJQ3bcVumlKyZ66b6caSc/B0eOURUtEWN6R5NnHdXPdpqf5o2cdxdBYkVSDg37VZu+MjJe4fvMOLlzdU7/jH9sntAOs0mh91t9g9crecW2rPYdozcYYcyVw5TT3bwMunvT3j4Ef160hIhrciTHbsg/U0PHtoObTJavGaFZtnUXJcikmumM/S1bazZD18nV5P4gIPRlfr74qpZoiG7gkXZvdQ+OtW59HhFKyD4aewioO120zoZuilOyt2/rnS4dnqbTv8LLTlnLD/Tv51QM7efnpXsMDPNUO+/zFfU8zUijxstOW1qlFZaGXwRpp/QBPPYsr17p+l/ZIqmVZYh0ccmUHuDE/SVUzsy0h7TtkAldr6zSIcZKUEp1AfP/fIkLe6yTppuq2/t6M3/CDMKWUmsyxLfqyAf2jBXYPjrfmtOoilFJL6hbkCb1s7DJ3oHz8otOjq8C1eeaRnazoSHDNhnKx5ZHxUt0Lb08ohabqAsvXrN/O0d0pTlpan6yUCcZLY0Z2IdPPfdQy6lVcGah5H6JHtaplWCJ4dnm4lW8FuLYWQm11vmuTDRzSvqPZOg0U+vm6pZnWim3ZdPrdeHZ9ZrPS4I5SKm6ygYvvWDy9f4xi2IK1eUQopZdihndhj++v2WpLQUfsau5MSOnxi4pkEy4vO20pX/rVIzy6a4iEZ5PwGjP8vdrsnfufGuDBHYO853nH1v/9KxbGTSOFgfpup47KxZXrE+ARkZrW3wEN8KgYKwd0omnLLb9uJ3qqsUTK2TrZhIPv6FWvxrIoJbpiM63sTDzbo9PvrlvdLBGhL+uT9PQrUCkVL75jsywfsH3/KIVSCwZ5gDDZDbaLNbJ7QVftjdjlqdDdZA1bV1s6vFdNSPsOLzppCf9186Ncs34bR3WnGC2UCGp88j6d4WqzdzZsI3AsLqpTceWpQj+D1coBHjdZt8mUEm7tS1Jor6RiQ0SiGjoTQ648vSrSRlzbIptwyfgOlqWva8O1SL2dhJOkw++q22d/InNHgztKqbhybIvl+QTb+0ernhUnLkI/R+gkcIZ2IOFY9c93U+XizTGup+jaVkNO3lVrcGyLvlzAc4/v4ef3Ps0fPedo9g0XWJKr73ukFJqqAjxDY0V+ed8OnndCb8MClMZJYCwXCQsN2V6t1TPrvdbZO6ABHtVEIoJreVFRZB/P8jWg04ZSvkM2cBs2DlkdztgJSsku4lxvByDj5ch6ubpuQ4dlKaVagWUJS7IB2/ePtO5U6rZHMbMcKQxij+5DwvE5nxLaAWHQGfuZHUGLK6vDpQOHl5+2jOs37+CG+3Zw8alL657FMzharKpu1/WbdzBaCHnZmvoWV54q9DLYo3saus1aMOLUNYsw8Gp/bK49k2qYgwGdg8OuNKDTniamOM8GOnVos4VeltDPAfH9rNW7mPKE3mygwR2lVMuwDwR5Wne4FiIYL0PRyyCFEaQ4jFUYAVMq/4iNsV2MHRB6aWih+or6faKmSnsOp67IcWRXkmvWb+fiU5fWPYtnYKzyrBhjDNes38axvWlW99WvaPB0WjXAE/r1+z/ZltSlXIX2TKquPNs7pIaOJXqy3848xyKXcLVockyEQQeh29gv8GpZInQGPfh2UNft6FToSqlWNDHD1rZ9I4StOLvWJMZNYNwEYfyTc+bkuzauXsBSU1jRrLCXrFnG//vlQ9z/1ACrl2TqlsUzWihVleG3aVs/j+wa4i9fcHzjj9Mth9BJ1mWWvXpqteFZEPd8fdVyPNsj7WboCnpYmlpBT2IJWS9P4CQ0uNOmJoomL8snWNGRJBO4GtxpOotSoif2wR3bsulOLKl7cKcr7ZMJ4l17SCmlZuI5Fj0ZnWgiTtJax03NIOU7XHRSH4Fjcc36bQDsHZ57eOJ8DI5VN3vW1eu2kfJtnndib13aM5e4z+A6VejUr7gyQFCn8hXaO6kFcW0X3wrKWTqaobOo6DCsmBKbYrIHrHinuTuWS3fQU7eZsiZ0JD1yCQ3uKKVaW8p3yCc99tXpRFFVJ+VrXUE1vaRnk0u4PO/EXn6xeQd//NyjgXJx41oO6zPGMFRFgGfv8Di/emAnl6xZVrfMkbkYN4kRGzGtUTy+XOKgfjSDR8XC1Ayd3sRScn6HZugsIhNXEld1JulMeRrciRPLo5jqi31wx7N9uhO9dQ/u5BIuHal4/y+UUqpSHUkXX2dtarqEZ+uxj5qRiJD0HC47fTljxZCf3vMUAHuGxqsqhjyX/tEipbDy9f1k41MUQ8Mla5bVrA1VE2mZLB4jDsap33hS17bqNsxTM3jUrDzbi6Yu1wydxS7lO+QSrk4JGlPGDiglu4l73D5wAjr9nroP40sHDl1pHdKglGofIkJ32mPbvtGaniiq6mhxZTWXTOBwbG+aU5ZluWrdNl75jBUUSiH9I0VyyYVnFRtj2D9ceXHlUmi4ZsM2Tl+ZZ1VX/WaEqkTopbHH9ja1DZUI/QzU8Vi1nudT8T4TUA0lIni2R8bLHlJDRzN0Fi9LhFzCZWVnkr5soMGdmDJOilKyh7h36Qkn2ZDgTtJz6NHgjlKqDfmOTV6HnTZVSuvvqDkEURHuV5yxnO37R/ndo+XZo/YOj1eVdTOTgbEixbDy4sq3PLyLp/vHuOz0JmbvTLA9wjrXXqyFemcaJepUfwc0g2dRE5EDs1v5to9reRrEUUA5bTAbuGQCB8vSgslxVp4GPd/sZswp5abJ+511347v2vRmfC30rZRqW/mky9B4sarZc1RtJDwbW4+LVAVSvsOzj+umK+Vx5d1bOefoLkJj2DU4Rl92/gGOarN3AK64ayt9WZ/zj+2e93ZrKfSzWMOjzW7GjOpdXBkgcOp3zq0BnkXEEsGz/QNBHc/SkyB1KN8tXxlMera+N1pA6OdbYixzo4I7rm2xJBtoUFIp1dZEhK6Uz/b9I81uyqKjw7NUpdK+w75hi5evWcrXf/M4T+4ZZmVnkqGxIoNjRdLzfC8NjBUplCoP7j60Y5ANW/bzx885OjbBSeOmMexCiGeQut7FlV3bqmsdL03XaGOWWAROgpyfpzexhKWplXQFvWS8HL4d6Am8OmBimvPl+QQp39H3RgsoBV0tEdzJeNmGBHdsS+jLBrE5eFFKqXpKeLYGG5pAh2epSnmOhe/avOy0Zbi2cMVdWw88tntwjGIVQZoJxVLInsHqZtL7wV1bCByLi09dUvX26kaE0Ms0uxXTMuJg3PrWKfLd+oZgtJdqI47lHJKh41o6RlvNzBIhEzhkE27dqrirehBKie66VvavlYyXJevl674dkXJwx6tjuqtSSsVNZ8pjeLykBZcbJHB1eJaqTtp36Ex5XHRiHz/d9BRvPe9IckmXUmjYMTDG0lx1F9x3DY4TVvF53zs8zi/v28FLTllKJojXeWHoZ7DH9ze7GYcJ/foHnuo9Tb0eDbeoiYLIaTdDZ9DNkuQy+pLL6PC7SLlpDe6oGTmWRWfKY2Vnkq60r8GdlmJRSvS0SHAn15DgDkBPxtcC4EqpRadcL0+v1TaKZkypak0Mw3rVM1YwVgy5ev3BLJ7RQokdA2MVr6t/tMDweLGq7V9191YKJcPvnbG8quc1hO3HrtiyoTHTuNf7mFV7qhah9XPUQnmORS7hktYhWK1J7HLmjh3/2aHKwZ36jl+e0Jny5j2OXSmlWl0+6TEwWqzqqr6an1QdZ71R7cm2hKTncFR3irOP6uSqu7fx2rUr8aMT/KGxIjsHxujJzH5sNzRWZHeVQ7OGx4tctW4b5x/b1fSp0WcSt2LLxk3VvbiyY1l1v7iul+5jyrHcA4VJe5NLtX6OmreEZ7MkF7CiI0kmcPW904rEppjsaZHgTrZhwZ104JBPeg3ZllJKxZFtlYdbq/ryXbuuRVFV+0pHn8/XPnMl+0YKXHfv04c8PjBaYNu+kRkLJ+8fLvB0/2jVQzF/tGE7A6NF3nDWqvk1vAGMm8ZIfAKnod+I7J369yP6jRADlgjugcwcD9f2sGP0ZletKe2X6+vo0JUWJzbFZC+0wLDLtJtp2LCswLXpScc/4KWUUvWWT3r0jxa1Fk8dpbW4spqnlGdjibBmRY7j+9L83x1PcvGpSw+p5zRaKLF17wiZwMF3bVxbGB0PGRovMlooVb3N8WLI5Xdu4fSVeU5cGuMJOaJiy/bYvma3BGP5DSmB4DfgvExD0U3g2odn53Qnesl6OQInocEdNW8iQjbhsrIzSW820OBOq7Mcism+lgjupNw0Ob+jIdtybYu+rGYyKqUUlLN4tBZPfSV0eJaaJxE5MEPtm845gm37Rg/L4gEIjWH/SIEd/aNs3TvC7qGxeQV3AK7f/DS7B8d5w1krF9r8uovLbFqlBmTvgGbwtAXHcnAtD8/2cK3yjyUaV1O1VT64c8kmXJ3hoV1YLsVkD0j8u+mkm2rIVOhQznjszfr6PldKqUlyCVezeOrEtS2dpVEtSCZwGBgtcN4xXRzXm+Zbtz7OC07srcuwv0Ip5Fu3PsHxfWmecURjLrwtiO0ROkms4nDTmmCwMF667tuxRPAdzeBpKZZYBE5AxsvRFfSwJLWcvuQyOoNu0m4W3w40uKNqyrEsulI+KzuSdKQ8PeltFy0U3AmcBB1+V8O215PxG/LlqJRSrcSxLS04Xyc6e5ZaqMC1cW0LEeFt5x/J9v2j/GzT4Vk8tXDN+u081T/KHz7rqJbJdA79fJO3n4UGnKM3amSF9ljzZIl1SFaOZ3nYda66rdQE17bIJ3VGrLZkueWaOy0wVNO3Azr97oZtryPp6YG2UkrNIJsoZwmo2krq8CxVA5nAYc/QOGcf1ckJSzJ867bHeeHJfTWdUWl4vMi3bn2c01fmWdsK2TsR4yYwloeE1c0UVpNtI4R+YyYH8RuUCajpJFWwxKIz6GZJchlLUyvoCnrJenkSTlKDO6ohfNemLxuwslNnxGpLltcywR3P9ugMuhv2Hkx6Dh0pnTFLKaVm4ju21oqpMceytJ6hqomJDDsR4Q/OP5Kn+8f4wV1ba7qNH9y5lX0jBf7o2a2TvTOhETNYTce46bpPjT6hUX1JSwR4ROTVIrJJREIRWTvLco+JyEYRWScid9S6HZZYGsxRTZHwbJbmEizPJzSDoV1ZXjQsK/4Hko7l0hn0NGzIqWtb9GZ0xiyllJpLLhH/ovytRANmqlYc2yIZzca29shOzj26i2/+9nF2DY7VZP27B8f4vzue5FnHdsd75qwZhF6mKVOml4LGZO+AZvBMdQ/we8BNFSx7oTHmdGPMjIEgpVpFyndYlk+wNJfQg4x2dqDmTvxfY9uy6Q56Gjbbn0RFlS2tL6WUUnNKek5Nh3wsdik//t/LqnWkJ81296cXHkMxDPnyTY/UZN2f/+VDFEoh73jOUTVZX8OJ1fAsntBJgN2YC4iubTXsWLYlvgGMMZuNMfc3ux1KNUo6cFjRkaRPpzpvfy1Uc8cSocvvaWgWoxZVVkqp6mQDzeKpBREhocdgqoZSnn1gQpTl+QSvfeZKrt+8g/Vb9i1ovbc8tIubHtzFW849khUdyRq0tDlCL4dpYHgi9BtXp6iR53MtEeCpggGuE5E7ReQdMy0kIu8QkTtE5I6dO3c2sHlKzUxEyCZcVnYm6c0EOiVnTNW0/2ih4I6I0Bn04NqNq4OTTbg6K4xqK3r8oRohHegEDLWQ9OxY/R+1/2h9InLIcc0bzlrF0lzAp35yP4OjxXmtc2isyL/94kGO7knxmrUratXU5rDshmXxhHaAcRMN2RaA7zbuvC42Z5Aicr2I3DPNz6VVrOZ8Y8yZwEuAd4nIc6ZbyBjzZWPMWmPM2p6enpq0X6n5skTIJVxWdiToTvuaWh1zNes/WmhYFkDe78S3g4Ztz3dturSosmozevyhGsG2hJQO616wuA2N1/6jPWQmZdgFrs3fvvREdg6O8Znr7scYU9W6QmP49HX3s2donL98wfE4bXAOEfo5DPUPrIZBZ923MVmj6u9AjKZJN8ZcVIN1bIt+7xCRK4GzqKxuj1INZ0UZO7mEeyBdUy0SlhMFd2LTBc8q6+VIOqmGbc+2hN6MH6srp0op1Uoygcvg2PwyAlRZUodnqTrwHIuEZzMyXgLgxKVZ3v6so/jPmx7h6nXbuOyM5RWv65u/fZybHtjFO597dEsWVp6W5WC8DDLeX7dNNDp7xxJpaLmB1g/zRUQkJSKZidvACykXZ1YqVmxL6Ex5rOpM0pnyNLiz2IhNMdHbMsGdpJsi4zVuhgEo193RTDallJq/hGdrP7oAnmO1RTaEiqfMlDpZr167grOP6uQLNzzEz+99uqJ13HDfDv7nt4/zopP7ePUzWnxo1hSloKOuWTwNz95p4PAsaJEAj4i8QkS2AOcCPxKRn0X3LxORH0eL9QE3i8h64HfAj4wxP21Oi5U6nG0JXSmflR1J8klPZwVajMQu19xpYJHihfDtgLzX2C/BXMI9MI2oUkqp+csE2pfOl34PqXqaXGwZyhkeH37ZSaxZmeeffnIf127YNuNzjTF89/Yn+cSPN3Pysiz/30XHt1/Gs+UQ+vm6rDp0kg3N3gEaPllIS/RexpgrgSunuX8bcHF0+xFgTYObptScHMsil3TJatHDxU2sKLjTGrObOJZLR9DV0Pes79p0at0dpZSqibTvsGdovNnNaEnJmNXfUe1FRMgELvuGD34+E57NJy87hY9ccy+f+/mD3P7YXv7g/CM5ouvgEPlHdw3xzd8+zo0P7OS5x/fwvhevbttJWcIgjzXej5hSzdZpEEqJrpqtr1KNrL8DLRLgaXVvuOwlAHznqp+0/fbrua1ar7ve/xfHssinXDL+oYGdCy64AIAbb7yxZtuqdJ213nbc1xcrttsywR1LhM6gG3uWAtCnH1seI77uoa012+Z86u5M956Zz/uoFu+9OLx/a9mGeu9Po/9fcXh96i2fzwOwb9++A/cthv1uVwt97RzbInBtRgvzP0GafKy0kOOmap/biGPXmbZhWzLrlMbt8pmarr9YqHb539TSTP+TbOCwf6RwSGFl37X52KUn853bnuDyO7Zwy0O7OKYnTUfSZe9wgQd3DGJbwtufdRSvP2vljMdMtfz81KoPqJpYhEEH9siuQ+5+ze//IQCXf+u/ql5l6Odgmtlg67VfE+u9+aZf1XS9c9EAj1I15trljJ2pgR2lWkVn0IPb4GBUt9bdUUqpmksHzoICPItR3GbPUu3JsS1Svn3Y9OiubfGW847k0tOX8b07t/DwziH2DxdwbYt3XXgMzzuhl47k4sh2Dv0cMj6IVRpd8LqM2IRBRw1aVR1BGl7PSwM8StWIa1vkky5pDeyoFpbz8w2dDh3KJyBpX7+OlFKq1lKew24Zr3r65cVM6++oRskl3MMCPBPySY8/evbRDW5R/JSSPcjAFoSF9WGlRA9I4y8kNmGTrVFkWak4c22LnozPio4EmcDV4I5qWUk3Rdpt7DSbrm3RnfIbuk2llFosbEu0nkyVEjo9umoQ37E1Y2wutrfgzJvQy2K81NwL1oFVx9nAZqIhaqXmybUtOlKeZh6otuDZXsNnzILylOg6o5xSStVP2ncYGps+S0AdyncPnd1IqXrLJVxGxnUY5WxCP48Uhuc1VMtYHqVEdx1aVRmrCek0emaqVJU0sKPajSUWnX53w7PPOlPerIUslVJKLVzSs7FECHWY1pyS+p2kGizpOXiOxXgxbHZT4kuEUmoJMjjz9PHTMWJTTPVBE0dXNGNkhw7RUqpCrm3Rmw1Y2ZnU4I5qGzIxY5bV2Pe079rkEq0xq5hSSrUyESHpa+CiEjpcRjXDYimavCCWTTG1BCoc8mTEppheOu2sWY0iSBMGaGkGj1Jz0owd1c6yXuOLKs93SnSllFLzk/KcGYu5qrK5pkdXql5SvmbxVMR2MbYP4fisixlxKKaXgN3cGo/NKLAMGuBRakYa2FHtLuEkSbuZhm+3M+3plOhKKdVAOkxrblpcWTVTR9Lj6f6FTwfe9kTA9in5HVhj+xEOBsUMQujnCYN886Irk1hNupCpZ65KTTEx3Xkm0OEjqn05lkveb3xR5aTnkNXPllJKNZRIeTatQS22PCMdnqWaKeU7+K7NWEELLlciTHQSBh1IaRRKhXJ2j+WBFZ/PcbPqtWuAR6nIRGAn7Ts6dES1NSuqu2M1+OqGJUJ3WseZK6VUM6R8RwM8s9AMHtVsXSmPbftGmt2M1iGCcRLgJJrdkmk163xSAzxq0dPAjlpscn4nrtX4LJqutIejQ7OUUqopdJjWzDzH0u8n1XSBa5MOtF5WO3BtqykFlgHELPJOXkR2Ao83ux3T6AZ2NbsRNdAu+wHtsy/tsh9Qu305whjTU+2TmtR/xOn1i0tb4tIOiE9b4tIOaP+2tFL/UStxek3nqx32AXQ/4mQ++7AY+4/J2uF1n0m77pvuV3xM238s+gBPXInIHcaYtc1ux0K1y35A++xLu+wHtNe+VCpO+xyXtsSlHRCftsSlHaBtaUft8H9sh30A3Y84aYd9aLR2/p+1677pfsWf5iIqpZRSSimllFJKtTgN8CillFJKKaWUUkq1OA3wxNeXm92AGmmX/YD22Zd22Q9or32pVJz2OS5tiUs7ID5tiUs7QNvSjtrh/9gO+wC6H3HSDvvQaO38P2vXfdP9ijmtwaOUUkoppZRSSinV4jSDRymllFJKKaWUUqrFaYBHKaWUUkoppZRSqsVpgKeJROQxEdkoIutE5I5pHhcR+X8i8pCIbBCRM5vRzkpUsC8XiMj+6PF1IvLhZrRzLiKSF5Hvi8h9IrJZRM6d8ngrvSZz7UvsXxMRWT2pfetEpF9E/nzKMi3zmlRKRFaKyA3R67ZJRN47w3IXRP+XTSLyq2a0Q0RyInKNiKyPlnlbrdsRbScQkd9N2s5Hp1mmIe+FCtvyxqgNG0TkNyKyphntmLTsM0WkJCKvqnU7qmlLA96zlbw2DXnPtptK+6W4q+ZzE3ciYovI3SJybbPbMl8yx/Fjq5jrmGuxE5EXi8j90ffzB6Z5PPbHpNMRka+JyA4RuWeGx1vyGLWC/WrV16uS49qWfM0OYYzRnyb9AI8B3bM8fjHwE0CAc4Dbmt3mBezLBcC1zW5nBfvxP8Dbo9sekG/h12SufWmJ12RSe23gKeCIVn1NqtjXpcCZ0e0M8ABw0pRl8sC9wKro794mteNDwKei2z3AHsCrQ1sESEe3XeA24JxmvBcqbMt5QEd0+yX1aEsl7Yges4FfAj8GXtXE/0kj3rOVtKMh79l2+6mkP2iFn0o/N63wA/wF8J1W+i6fZh8eY5bjx1b5YY5jrsX8E30HPQwcHf1v1k9zLHFBK76PgecAZwL3zPB4Sx6jVrBfrfp6VXJc25Kv2eQfzeCJt0uBb5iyW4G8iCxtdqPalYhkKXdo/wVgjBk3xuybslhLvCYV7kureT7wsDHm8Sn3t8RrUg1jzHZjzF3R7QFgM7B8ymJvAK4wxjwRLbejSe0wQEZEBEhTPlku1qEtxhgzGP3pRj9TZwloyHuhkrYYY35jjNkb/XkrsKIZ7Yi8G/gBUPP3SJVtacR7tpJ2NOQ9224q7A9ir4rPTayJyArgpcBXm92Wxa5Nj7lq6SzgIWPMI8aYceC7lL+vW54x5ibK3yEzaclj1Ar2qyVV+D3Wkq/ZZBrgaS4DXCcid4rIO6Z5fDnw5KS/txDfg6m59gXg3Cgl+icicnIjG1eho4GdwH9HKc9fFZHUlGVa5TWpZF8g/q/JZK8D/nea+1vlNZkXETkSOIPyVebJjgc6ROTG6HP35ia14wvAicA2YCPwXmNMWKc22CKyjnKg4ufGmKltadh7oYK2TPaHlK8GNbwdIrIceAXwpXpsv5q20KD3bAXtaNh7tl3N0h+0hCo/v3H1r8D7gFZ/71Zy/Bh3lR5zLVaVfje30jFppdr5GLWlX69Zvsda/jXTAE9znW+MOZNy+v67ROQ5Ux6XaZ4T16tMc+3LXZSH1qwBPg9c1eD2VcKhnI74RWPMGcAQMHWccKu8JpXsSyu8JgCIiAdcAnxvuoenuS+Or0nVRCRNOfPiz40x/VMedoBnUL6C+yLg70Tk+Ca040XAOmAZcDrwhehqZs0ZY0rGmNMpZ8OcJSKnTG3qdE9rUlvKDRK5kHKA5/1Nase/Au83xpTqsf0q29KQ92wF7WjYe7YdzdEftIRKP79xJSIvA3YYY+5sdltqYK7jx1ZQyTHXYlbJd3PLHJNWqV2PUVv69Zrje6zlXzMN8DSRMWZb9HsHcCXlFMbJtgArJ/29gvIVx9iZa1+MMf0TKdHGmB8Droh0N7yhs9sCbJl0Je/7lL+wpy7TCq/JnPvSIq/JhJcAdxljnp7msVZ5TaoiIi7lL59vG2OumGaRLcBPjTFDxphdwE1APQr5ztWOt1EedmOMMQ8BjwIn1Lodk0Wp7zcCL57yUMPfC7O0BRE5jfLwiUuNMbub1I61wHdF5DHgVcB/iMhlTWpLQ96zFbSj4e/ZdlFBf9BSZvv8xtz5wCXR5/q7wPNE5FvNbdL8VHAs3AoqOX5czOb8bm6xY9JqtOUxaiu/XhUeX7f0a6YBniYRkZSIZCZuAy8EplYq/yHw5qia9znAfmPM9gY3dU6V7IuILInqHSAiZ1F+79X1hKdaxpingCdFZHV01/MpFwSdrCVek0r2pRVek0lez/TDs6BFXpNqRK/LfwGbjTGfm2Gxq4Fni4gjIkngbMpjiRvdjicov78QkT5gNfBILdsRrbtHRPLR7QRwEXDflMUa8l6opC0isgq4AniTMeaBWreh0nYYY44yxhxpjDmS8knHnxpjrmpGW2jMe7aSdjTkPdtuKuwPYq/C90isGWM+aIxZEX2uXwf80hjz+01uVtUqPBaOvQqPHxez24HjROSoKCP7dZS/rw9osWPSarTdMSq07utV4fdYy79mTrMbsIj1AVdGnw0H+I4x5qci8k4AY8yXKM94cjHwEDBM+apjHFWyL68C/kREisAI8DpjTBzT3d4NfDv6AnoEeFuLviYw9760xGsSnQi+APjjSfe16mtSqfOBNwEbpVwnAsoz/6yC8n4bYzaLyE+BDZRrMHzVGFPrA+M52wF8HPi6iGyknNb6/ig7o9aWAv8jIjblA4nLjTHXNum9UElbPgx0Uc6YASgaY9Y2oR2NMmdbGvSereR/0qj3bLuZtj+Irt62kmnfI01u02I17fFjc5s0b4cdczW5PbFhjCmKyJ8BP6M8o9bXjDGbWvGYdCoR+V/KM0p1i8gW4O8pF25v6WPUCvarJV8vKjuubcnXbDJpjddCKaWUUkoppZRSSs1Eh2gppZRSSimllFJKtTgN8CillFJKKaWUUkq1OA3wKKWUUkoppZRSSrU4DfAopZRSSimllFJKtTgN8CillFJKKaWUUkq1OA3wqJYjIheIyGFTms50fw22d5mInDTp7xtFZM7pjkVkaS3aIyI90dTCSqkamW9/ISLLROT7Mzx2oG8QkQ9Nuv9IEaloOnAR+XMReXO17ZpmPX8mIi03tadSzSAibxWRZRUs93UReVWl99egXdqPKNUiFtqPVPC8d073uZ7cN4jI6SJy8aTHPiIif1XBukVEfiki2WrbNc26rheRjoWuR82fBniUmttlwElzLTSNvwC+stCNG2N2AttF5PyFrksptTDGmG3GmEoOzD409yKHEhEH+APgO1U37HBfA95Tg/UotRi8FZjzxKwJtB9RqnW8lTr2I8aYLxljvjHHYqcDF8+xzHQuBtYbY/rn8dypvgn8aQ3Wo+ZJAzyq5kQkJSI/EpH1InKPiLw2uv8ZIvIrEblTRH4mIkuj+28UkX8Vkd9Ey58V3X9WdN/d0e/VVbbhayJye/T8S6P73yoiV4jIT0XkQRH550nP+UMReSBqz1dE5Asich5wCfBpEVknIsdEi79aRH4XLf/sGZrxSuCn0bptEfmMiGwUkQ0i8u7o/sdE5JMi8lsRuUNEzoz+Nw+LyDsnresq4I2V7r9Sra5Z/YiI/FhETotu3y0iH45uf1xE3j7lSllCRL4bfab/D0hE9/8TkIj6jG9Hq7ajfmWTiFwnIolpNv884C5jTDFaz7HRlbD1InKXiBwj5cyjX4nI5VH/808i8saoP9o40UcZY4aBxyb+D0otFtFn9D4R+Z/os/l9EUlGjx3Wf0j5Svpa4NvRZzYhIh+Ojh/uEZEvi4hUsf3Z+qhPTT12EJFk9HneICL/JyK3icha7UeUap5G9yMi0isid0a314iIEZFV0d8PR/3EgWycqA3rReS3wLui+zzgY8Broza8Nlr9SVH/84iIzBSwfSNw9aT2vDna7/Ui8s3ovq+LyBdF5IZoXc+V8rnWZhH5+qR1/RB4fZX/clVLxhj90Z+a/lAObHxl0t85wAV+A/RE970W+Fp0+8aJ5YHnAPdEt7OAE92+CPhBdPsC4NpptnvgfuCTwO9Ht/PAA0CKcnT9kahNAfA4sJJyxP0xoDNq66+BL0TP/zrwqknbuRH4bHT7YuD6adpyFHDnpL//BPjBpP3pjH4/BvxJdPtfgA1ABugBdkx6/nJgY7NfW/3Rn0b9NLEf+QDlg6UscDvws+j+G4DVwJGT1v0Xk7Z/GlAE1kZ/D05a55HRY6dHf18+0T9N2fZHgXdP+vs24BXR7QBIRu3eBywFfGAr8NFomfcC/zrp+X8D/GWzX0v90Z9G/kSfNwOcH/39NeCvKug/1k5aR+ek298EXh7d/jqTjgcmLfN14FUVbOOwY4eobf8Z3T5F+xH90Z/m/zSpH9lE+djjzygff7wROAL4bfT4R4C/im5vAJ4b3f40B49L3kp0/jLpOb+JPufdwG7AnWbbjwOZ6PbJwP1A9+T9iNr9XUCAS4F+4FTKCSN3TvRN0bIPAl3Nfh0X64+DUrW3EfiMiHyK8gnUr0XkFMoHLj+PAtg2sH3Sc/4XwBhzk4hkRSRPOdDxPyJyHOVO1q2iDS8ELpGD404DYFV0+xfGmP0AInIv5c6zG/iVMWZPdP/3gONnWf8V0e87KX8JTLUU2Dnp74uAL5noitrEdiI/jH5vBNLGmAFgQERGRSRvjNkH7CCe6eNK1Uuz+pFfUx6S8CjwI+AF0VW7I40x94vIkZOWfQ7w/6JtbhCRDbOs91FjzLro9mz9xmYAEckAy40xV0brH43uB7jdGLM9+vth4Lro+RuBCyetbwdwwhz7q1Q7etIYc0t0+1uUP9M/Zfb+Y7ILReR9lIMhnZRPvK6pYLur59jGdMcOzwL+DcAYc4/2I0rFRqP7kd8A51M+tvgk8GLKwZRfT15IRHJA3hjzq+iubwIvmWW9PzLGjAFjIrID6AO2TFmmMzr/gHIW4PeNMbvgsHOWa4wxRkQ2Ak8bYzZGbdpEuT9aFy03cd6ye5Z2qTrRAI+qOWPMAyLyDMpXqP5RRK4DrgQ2GWPOnelp0/z9ceAGY8wropOqG6tohgCvNMbcf8idImcDY5PuKlH+HFScfh2ZWMfE86caoRxUmtyeqfs4dV3hlLaFk9YdROtUalFoYj9yO+U060eAn1MO/v4R5ZOpSrY5k6n9znRDKyb3G7P1SVP7icl9yOT+SPsNtVhN1xcIs/cfAIhIAPwH5SvxT4rIRzj0+3zWp8+xjemOHao5/tB+RKnGaXQ/8mvg2ZQvPF8NvD/a5tQJIWY7p5jOdOc9UxVFxDLGhHOsv5JzFtB+o6m0Bo+qOSlXkB82xnwL+AxwJuVUvx4ROTdaxhWRkyc9baK+xrOA/VGGTY5y2jCUUw6r8TPg3RPjXUXkjDmW/x3wXBHpkHKBwldOemyAchZANR7g0Ctr1wHvjNaNiHRWub7jgYpmz1CqHTSrHzHGjANPAq8BbqV8wPVXTLmCFrmJqDZWlF102qTHCiJSTdYhlK+6Hxu1ox/YIiKXRev3J8b/V0H7DbVYrZroJyjXgriZ2fuPyd/zEydhu0QkTXnoVaXm6qOmczPl/gYpz9h56qTHtB9Rqnka3Y/cBPw+8GAUaNlD+SLXLZMXijL790fHOnBojc75nLNAeb+Ojm7/AniNiHRB9ecs0bnXEsplKFQTaIBH1cOpwO9EZB3lsdv/EJ00vQr4lIisp5zCd96k5+wVkd8AXwL+MLrvnylfub+FcgpkNT5OeSjGBikXRP34bAsbY7ZSToe8DbgeuBfYHz38XeCvpVxw9ZgZVjF1fUPAwyJybHTXV4EnovasB95Q5f5cSHm4iFKLRTP7kV9TTj0ejm6vYPoAzxeBdDSk4n2UA8UTvkz58/7taZ43k59QTs2e8CbgPdH6f0P5gKka51Puz5RabDYDb4k+O53AF+foP74OfCnqb8Yoz4C5kfIEB7dXutEK+qjp/AflE8YNlK/Yb+Dg8Yf2I0o1T0P7EWPMY9HNm6LfNwP7jDF7p1n8bcC/S7nI8uRMmRsoF1WeXGS5Ej+iXJsLY8wm4BPAr6J9/FwV6wF4BnDrRFkK1XhiTDUZXkrVnojcSLlo2B1NbkfaGDMYZdlcSblo2pULWN8rgGcYY/62Bm27Cbh0hk5eqUUvLv3IQonIlcD7jDEPLnA9ZwB/YYx5U21aplRriIZiXmuMOaXZbamEiNiUi56ORheRfgEcH51Izned2o8otQCt1o8slJRn+/uGMeYFNVjXvwE/NMb8YuEtU/OhNXiUOugjInIR5bTK6yhH3OfNGHPlRHrjQohID/A5De4otSh8gHKR1AWdmFGuHfR3C2+OUqrOksAN0VAsoTyz5ryDOxHtR5RSFTPGbBeRr4hINhrauRD3aHCnuTSDRymllFJKKaWUUqrFaQ0epZRSSimllFJKqRanAR6llFJKKaWUUkqpFqcBHqWUUkoppZRSSqkWpwEepZRSSimllFJKqRanAR6llFJKKaWUUkqpFvf/A1zbWMbcZ0b7AAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(1, 4, figsize=(16, 4))\n", "\n", "explainer.plot_partial_effects_at_means(\n", " X = X_test, # Obtaining explanations for test data \n", " ax = axs,\n", " features = final_itexpr.labels,\n", " target = None,\n", " num_points = 100,\n", " share_y = True,\n", " show_err = True,\n", " show = False,\n", ")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "explainer.plot_normalized_partial_effects(grouping_threshold=0.1, show=False)\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example, wew didn't specified the dictionary with the derivatives of every t ransformation function. ``ITExpr_explainer`` will use jax library to automatically infer the derivatives, as long as you have used ``jax.numpy`` instead of the traditional ``numpy``.\n", "\n", "This means that, after fitting the ``ITExpr_explainer``, we have an dictionary of the vectorized version of the derivatives for each transformation function!" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1. 0.5 0.33333334]\n" ] } ], "source": [ "# printing the derivative of sin, without having to implement it by hand\n", "# (remember that is a vectorized function, and the input should be a np array)\n", "print(\n", " explainer.tfuncs_dx['log'](\n", " np.array([1.0, 2.0, 3.0])\n", " )\n", ")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.7.12" } }, "nbformat": 4, "nbformat_minor": 4 }